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);background-size:100% 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diff --git a/p__knowledgegraph__Detail__id.eadcf1d2.async.js b/p__knowledgegraph__Detail__id.743940d2.async.js
similarity index 56%
rename from p__knowledgegraph__Detail__id.eadcf1d2.async.js
rename to p__knowledgegraph__Detail__id.743940d2.async.js
index 0448ad87d2..f6fba84d2e 100644
--- a/p__knowledgegraph__Detail__id.eadcf1d2.async.js
+++ b/p__knowledgegraph__Detail__id.743940d2.async.js
@@ -1 +1 @@
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CRH3RTdkduNZF179eQD6rZN68lihpiF0jUwIeTHmmSASjcKmU7ZDrRpkJxtiyJVQ+Bgba3hST5udfOkRiL7wNEj+t4WVJFcHclD69N2Q+dBLZi2o8Hc/BO8XwxB99jZIvrU9ESt99h5ggtmuqSfGW1qc3AsGAeMuYFRC8k2dXck8dulf9wDVNcit6Tmtf+xeLX/hF2ZJcnMS4q85tyPg7C4tfT5wPasDk6AO51v2Z+LNBLxbmnf/USj8fWD5bdfm43pve+6Gi8AWw1aNQwyyH78S2FXdqjGGuXff2i1Q2XVYBLoegSk3MiedNLKRozEBwwcPQL1Wa3Ijs5VQmP2YWsknlxM24Yr/+6QthYjwmmuuEfcWi47MuxE3V0pUyEk7qHsI1QBovVEDbCYQg9t2nPUmrWXKlMjztJGtse7krv9+2AWeAAKJ1+6C2Bzu0pnD1vccAX2sArGXnXncR3qiYmLD+C+o1J88t22s4nyWWfz4T6G+5/Csrr2ffiVg4sRj3+Yz94n0KX7m51C/86mWh/b8068Yt3u3tOq3H4fyF+7ruJy5rHqdDq7/4igU/6418Yz96tmQeN2utoeXv3A/VL/9WLdAZddhEeh6BKbcyBLAcVnUWgAKVTz82COfRdBDAuAoCDGCJEd9EpNx9AteNllWGa9+YSrlf+lLX9KIXObj5LWTRgx5y9ddd5246aYj0vP2R+oxFUOPUtrDrE/QD6g2CiaGJAb7t55yVSyR2hVoGhJov1E/+aRCd/JOmp157SLAVj227i2kMbGIPPcUEOnjCVrl5n1Q+c8HAFMR6Pnnq9paheYzV+493zVxjM2NkyF6P/XK+Ry+4n3yH7wD/EfGZs3LLvXez17ddj21H+wHPVRa8vVGr9wBInN8/Gc4yXzIV/ZvrgBOFGnVyv/5S9DDJYg+bzu4u7fM6lK58WGofGVva5L80ZeDGGgtWUuegtzbvgG67C05HnZAi8BaRYCJoZQIosmNXC0X944dPngzoh7STAxJjjgIY8KlHLlYjFRl1XVPq7/ylVvUddddN3c24TKDd1KJIVsNL7vsegmw35mcnIxVsJQgHzOK/D5EGiANm5BoMJpMnbPxlNOuqdc0epyEwgH11p28zJeGHf5kIMBJHOze4yZ6Y8AJF+0aEwLK10H0xSH+a7PdrJPv+o5JPFlMfFo4N8cwznQ1Ozv6IHPtZScDpjnnnHzrzdAq01eekoXsX812uYcD5v/iVvAPtXZBz5yUrbvy9N725+ff7gE1Wjaf9376asBE68xfdiOzO7lT6/3cq4HjI1u1ybfcbDKGM3/5InB2znaRF/7qTvAeGpl1qLNrI2Te3T6hpXbnU1D6zM/nxNp2sAhYBAIEmt3IjiPANbWRBY0c3P+lWqn4ECEOoYBhIhyV6IyjQ/k4Jcs9PT1VgNP822+/Vp1sa6HZx8k8oaE7+cEHQfo9tWi0UI2XtZ+WIHsV+f0EsMlYDYEGt+7Y+btayywTQ2M1ZLFrq2l4Mk/fis0tHQf6enugr7cP4vEYRCOumbtW96BSqcL4xDiMT0yC8ltIlKzYKpd+IvfpmyD9rvaZvuNvvAHAUy2TBzgBgxMxuLUjDPNdsc5VYfJt35jVPfLc7ZD6w2fOd5gV60cVDyZ+/+st54vs3gKpP35O27VMvPEGYEvZfJpzei9kPnB5+7He/HWgsgciHYWeT17Vth8nnnACSrsm+hMm8aZVo7IPE2++0cR49jD5nBErSJ6GiTd/3VwnM1vqrZdA5Nmts9S5b/7628F/rH0iz3ww6sY+6/V+0o3nYq2tadqNHCSdMDEUQuUOPfbovwmgI8ZaCGLEQXFMgZpICKdQS8cqzmS0du65oLrBjXzSiSEvIHQnAwy5JVmOiyImlaAeBdgHoDaicSfTYN/mbVfG09nzjaYhxxlad/Ja+07N2g+n+g8ODsKWLYPgSNlxv75ScOTIEAwNDZk/GFZbY6kXdvk2N3YNt3PzsbSJv3/SdJen9swmBLkaVG7aByz50o5U8LHFf/4ZJH9vd9ts5cpXH4T6XYdbJnLEX33OnAkhPEfthwegduvi49Tktuy8EnPU/knIve97LS+B2K+cBYlff3rLz/Q4x2R+c96XTifirgt1mHzLTWYsZ0c/ZK69tPW4mmCcM7X99t4j99wBSP/FC1se7z85Afn33wbt5IL8vSOQ/5tAO7K58bXW+4+vAHBbf6/8AznIv/e788ZiNXRcT/eT1XA+1uIaj3cjB9qFlWLuvvGhQ99CxCEyxFCOSKBxqXFSp6iUVIkKwKDXLW7kriCGodVwdDTpNruTNahe0HqAADch0GA0Et2x8YwzX1+vEhqx67B2MpfQW308YC1+J5Z0T5FIBHbufBqkkkH8Uy6Xh2NjY5DPF6DuBTFPEdeFTCYNG/r7IZsN4q+KpRLs2/co1OsnJtS8pJuY52DoSuj93Kvm2Xv+3cr/+z6AmAOJa85reRDrCuavvR16P/OrbQctfPD74D3SWqqErYVsNZyrlT53D9RuZ/2uxbXo87dD8s1zWyhDiZ5WsyXfeCFELzuj5UK8h0eh9KmfQ8/fv2x+C2WZCSM10ab5Gqo/2A/q0bG262ZXc+5Pbuk4X/Ty0yH5u60zvms/PQSlT/ysrWB4+ct7ofr1h2eNP5d2Yel/3QO12xZ/zuYH5PL3Wk/3k+VH087QCoHAjcx6hWCqnRhR6xjSyBOPf6FWrz1GgEMINAxCjAqQE81u5IGBktct1kLe20l1JfMCmBhef/31+OUv73Wa3cmE1IMaNgDiRgRiq+GWLWfufAOB7PeM1bCRgGLdyWvuW8o38aefdy7wc7VahcefeNIQwk6NCeKZZ5wOsVjMkMJfPvDgqiGHc8W9negJZqmaxK8/A+QpbZIWvrIX/PuOQuZ/vLjtFJN/9E3Qk5WWn6MUXPd9zkb+EmlLCZxfAg3fE1pU+eCFsuWNLXCtGotj1398ENLvOXEh6ZnjVv5zL0BEAFtXWzXvgWEo/O0PO2IY/69Ph/grWouch4kl2Q+9pKU2Yztdx07JLBxLOslVcFpVj5nzbHdfh/V2P+m+M7A+VhTIE6JJPDFu5ChLVauxI4/v+3cEHOL4QiAaIQHHkHCy2Y38utft8q+99lrqhvjCriCGvIhmd3K1Wo8RqZSWkPVB9YHCjQSwGQUN9m0avCKR7r24xhbDWkAM+WEthmvni8funl27zjWWwkKhAA/te3TesYMcO3TOzqdBOp02lsO9ex9cFW7lyDO3Quq/P3vJT2LhYz828YftGluq5Gm9beduFqSea3HOtgxELm9tiZvr2KX43H90HOo/OTDnUD0ffwWI/tZlAU0yT9Gblx7jnBM1OrCrnuMa21WcqX7vCSj/270dh+OYSB6jVWNZHv/+o9DzidkxjBxrOfmHN80iyc7T+iHz/jaubZ7E1zDxlpuBj1/tbT3eT1b7OVut6w/dyEwMnShCNCKgXJj4+fjw0K2k2VoIR0HSiANyXCjIIcpiLBapdpsbuWuIYbM7uVA4FC1qTILy04pEH2jiNDvjThauc/rWM3f+dr2mhclODq2G1p28Wr9Ls9a9desW2H7KNmMp/MUDD86bFIYDMTl8xnnnGsvhgYOH4PDhI12PDZOG2EumNQjlmX3tBYePFoHmqKtrNqwJOKs0+qLTWu6fy6NxximX20v8l9Yxd5ydy1m682mxF58Jid+5YD5dl6UPx0JWvvZQ57FdCX0sVdOmugCX35ODKYi+fLqGczuJGZZwEXGn7VhG4sXXUPzbOyHxpt3gnNE6e7n8xV9A9ZZHO64789dXABPvVi3/gTuAk1M4kWRm4/hDlsLRIyXQk9Wpj1lAnYXUO7XiJ++eF9FelpO5hIOux/vJEsJnh5onAqEb2ZDCRtJJJCr04cf3fV57/pPsRgaAYRB4TKIeB+kUUoJK6fS2Wre5kbuKGIbuZA4dkzKXqJJOadQ9wO5kYHeyHiSCwcHTd7wehDvA7mSOM+QHF03R1mw4z0u4e7sxqbvowvNNosneBx+a033cbifsVt517jnACSn33Hv/gsnlyUTIOasfMu9rbc3hDNPcn3yrrWv3RNbdMeZuzxEofPwn8xp2MZU55jXBHJ1Kn7obaj/qbDGUW9KQ/duXth0p997vAleRCZtzzgbIvGd2eUKj7/fHt0D2Y1cCRlonb3DiBidwcOskAs74ens6//HC8acch9qqsSxP7KU7OoqiN5M8rlLDAt+cxdypccJR8Z+m61QvxTla6THs/WSlEV+/8wmTjhzEFpr4wigCaG906MnHvoAIQwRiCIBGQMAxQWIyhqKoVJa1rOrd5kbuGmLIC5npTq4iJSMCsh55/aDFAAFtZk3D3k2Dlyeyvc8O4gyDEnlKcwU9m4Gy2r+WAwMbYMeZZ5hEkwcfmh0wv5D9nXvO2SYh5bHHn4DR0dVT55V15VhfrmVj/c55WAuNe3HvCER2bwWRbS2q7D81aWoKd5qPLVls0ZpP6+TunM/xi+0zV41kHj9y4aCpANOuTbzpRqD6tORRu2ojnEjD1skezupt0yb+240mRm8uEXAuN9eudB8PzRqVPf/Qeh4en+eZU3amqX70fDUteWzOquY/RlZrs/eT1XrmVt+6TWyhgKkSeEwMy7mJn04MD91mtAsBj4LQoy66Y3UNuRhhqVvdyF1FDGe6k8sgE9qrZxTIXtS0gUBtQhKDKMX2bTvOfmO9piUnoLA72WgaWnfy6vs2zVjxzrPOgr6+HpNsMjIyuqj9bNw4YJJRxscnYd8jjyxqrJU62D1rA6TfN9tCtdD5Q7LBCQucuNCqhW7i7EevBDmQaNmn9Pl7ofbdJ+Y1PSewsJzMUrZ29XtbzRGKPHeav1MmLrtaJ/9oWqtRbk5B9sMvbekqZnxZmzD93tYSMkze2ZLHzTmzDzLXtRcBn0s30T17oO08TO7zf/k9yH7wchMr2pakcpxhMcjSn6tv8xjFj/4Y6veyB2x1tvV+P1mdZ231rdoYC002csON7BpRa3XosYc/R0ofYIkaRDxK7EYGNSHcSD4BqtytbuSuI4bN7uRapBiXSqUU6h5UtIG0aiShiMHB7af9JjrxzaZ2cj3MTrbu5NX3lTp+xRec/wwjYH3vfb8wMYaLaRxjeOEFzzAC2PfdPz+r12LmW4pjO2XMLmT8kGwYt+E/vqKtRiFbBGNXTsfTzZyDs5q9XwwvZOpF95Wn90Dkwi3gXrAZWEB6Pq2dAPfMY5O/fSFEX9I6QcZ/+BjkP/T9qUPa9Q3rDkcvPb1tkor/6Bhw7B+3TiLg89FN7DRP/WeHjA4lZxhjJjarJCLPz7GOkyxwzSR1exYyH2pf9WUmXqu98sl6v5/M57tj+yweASaFyNZCJoZc6SQigPzq0NCBJ79IWpukExRyhCQekyQmlZTFaD3FUg9d6UbuKmLIi2F38h13gKjV9rrFYjlWJi+F0sugxn7QFLiTQQxm+ze8INW/8YX1mjLE0GOLoTpxdzJrDxERCBRBXLqJJOX/+F/jZ/OE5sFOaxNTwJ9zrWs+jmMchTD9uQ837sN9w5/N8U3jsQRa+NnUfI2aOmG/VvPzoGy6nurDLxrvTa268VeMWQjPGywaeIWEBMhrblpbOD8fz5l8YQvXTPwXkTlAsMZQgIWRKmEMAJAamAVvNkoDNcYx+w4+D3DjxQbvTY0fYooIP7t7D2g1v+oT7b7WQkp41jN3m3F4vG5vztkbIPPexVsLZ1q+TjT2jytq5P7sW/NyXS8GW65d7O4aAPfCQfMQPbF5DccZs969Q1C763BAXudRrST9rheA+/TWbnqukVz6n8F1wu5fQ6hbxA8WPvxD8H45DIn/ch7ErtrZcq0s6F369N3ms/hrzm0vVfPwKBQ+9IOO++00D+sTsk4hN66vzXW2Zzb/oWOQ/6uA8HYixq0WwVbGCbZ8rtIwHf7+831gKe8njBOHLQX/jN6agc78xOHu/LPxXoXvB32mfjbdgr7Bkwbie6d5Ds6CGduMY+TczINvm8FbTfMEcm/mPs7zhs9T8zWOMT+bMcM5wzVOrTxYY2Nv0/tpes/cysMx2EPHt/PgubGRqTnMUYwR/9Kh4HdrABWHJTR+Dueb+izs09gfkPmdatYUYmHGm8bwhnIqAAAgAElEQVRkXjeKFejEv4tZu9ANiWFUQnFs5Ae5sWN3EjAxZDcyjpKgMVJuPoFuMZVKVKPRXd6ll4LuhtrIM2E66TqGzQsK3cn3FosOjEPU9XWSfM5O1r2chMIl8rg8HpLcsv2snW+q+xDlSihqse7kkAQ2CGHAWwLSYn5RNL8O3phN9pjkGLIWkJ5mghYcbw5scM5pwshky5CuqXH5wg9IH4933PyGZTbIVWPN4Zg8cED6Qu9XSLwa620Qs6lxzfcwIIFTRHdqzFafBeSSxw+WFe5FMCs0RLOxhcYzvx+gYNYcrq1pn8FnDYLbREiX4kYuhYBLLrl41RDD9HteCO45rfX1OLtUHwtq7nJyisi2J0/efUeh8JEfTX2tOGM1+5GXz0//r+nLyHGK9TufWpbbKsfNRS4IiCDHU7arATxzciaD9XuGoH7XIfB+OTIvMtg8Rs9HX962kgzrDVZuDuJa46/cCfEWouAcC8huZG6ptz8bIhdvbYkPxx9yljS35B88E6LPay0CzrqJpc92/qOl0zxMZJnQcmv3B0D15keAZXg4eaXnn69qW6+53YluV2d5WS6MJR50KYlheD8xVC4kyg2iFhCfgDRNkb4GoTGf8T3eHMOkiAPi+T4ayqwRNN4Kxpgi4TPHa5CwJrJk/sRuEMeQpLaaf4q6hsQwXC/jHZJGw9mCvZlxA5Y5RQDNPKZ/uMdpIhckfjYRPmMoaF5v2Dfgw4Y0NpjxTFKsSQe/ZxprM2M31hLOr5k0hiR1ia+ZhQ7X7EaW7EJmi6ELtQOP7PssoTrC+oVospHhmEQxgY5T8BxRgj6oXZhK+d0kat28964jhqE7WcqcW5Yywe5krSiLosmdTDS44ZRTX+XGUju8mg7ErrkSihW7Xuh13VX916vrp132q7k31pSpjMFxa52kZbivt3cEWHJlpv4cW5LYojTfxnFlHF+2HC162emQfGPrKh6t5mPLZf2eI+DddQjqDyycDIZjshi3qS7TplIJZ+ByJi73y378ypaWy9Jn74HaHUE1kHaC0vxZ8V/uhvqPgwzpzLWXg7OjjVTNlx6A6k37OsLcaZ78//g++PuCxKr0+y4F96z+WWPx9cBlEaPPPxWSb754wae0euvjYCrorMK2Xu8nq/BUrdolh7WRJWciG1FrAV61+Nixg0/dECSdNNzIGo8JiTl2IyeUKiuV9boxG3nqftltZ4Sthpdddr0M3ckV1ElQ9Ywg7CPBcYa4iWsnJxPJc/tPOfU1NS6R18hO5iSUhiW/27Zl1zMPBJYlWHxiwpTI6+bGSQycZNCqVb/BFp8HIPlb50O0SetwZl+OByt/9h4gTtGf0ThuL/uB9tVNmrtTqQ65P78VOG6vbXPmUe6kzcHJN1wAXOKtU+OM2Pp9R8H72SHgyiDUoY7wzHGMtaEVBpxM8nftS92F8jLtyu4xMc/98TensnR7P/uq9lI1TVnAvf/yylk1sMM1F//xp1C/+3BHLHr/9VVtpWUm3/aN4DwJhN7/eXXL9Uz+92+Cnqi0JY48OZXrgInj63SHi5pPHGS3frfW6/2kW8/HWltXI+rLJJ0ExFBANIY0dvCpr5bKpQe5NjKXwEMhRrWCMZCRfJxEKXQj3377tapbKp3Muo9228ma6U6OFjGhXS+tPN0DxmoIm4hgM7uUt+446w0ETu+U1ZDLYFlNw247pfNez3qUl+iUdWqshe/+DiRef37byhcMbrPrsh3YrMfHlsm5Gtfd5fq77ZqzcwNk/nLxsZBzreNEP29HZNxnbIL0nz2/7bChvAwnZ3CSxsxWueFhqPy/IJ6P4yBZC7BdCzOkRcKFnk+3r0PdrHXYaizRE4eef2ojVVNTMPF7N5jD5PYeyH5oNvFnQsjEUA5mIPvhK1oul0l45St7zTXWruWvvQ38JyZO9JSctOPW4/3kpIG9DicOtQunS+BxroE/cfjxR0wJPES2FsIwaBiTrpwQnluopajc7W5kPpVd5UrmBYW1k2+66Yj0vP2RqhuNS11Kqjr1IGC/j3pAAGwmEoM9Gza+INnb/9xQ09BfZBLKOry2u2rL61GQNvn688HZOdsFyCfGuDY3JIC159q12ncfh9Lnp119TEbAEbOSRubS8Avnm0vUOPqCUyH5+wt3Sa7UhdacbNE8J4tAJ97QmvxQrgYTb7vZ1FDmzPBZjUvEsbUwVzMfdUoUYjf+xO83soBP74XMBy6fk4y269BpHnVgEnLv/Z45tJ17nl3I7ErulIDEMYqVrzzYUZOxcvM+qPznAyt1CpdsnvV4P1ky8OxAcyIQJp04pjayMKLWpYmxH08eG7kTUQ9pgKMOiVECGpMRnFQiWYp5tYrrnlZ/5Su3qG6qjTxzs11HDENyGLqTKxUvWqZ8kpTIaNC9iDTAVkM05JAGtz1t5xuUlsmpJBQOmLWxhnNe1N3awZawOv7MZK69FJwdrYkj9/QeGjUadXIgCWJjwrgEK//nl1D55vHajZyE0vOxl7cv4ZavQf7dt4IuBOSnXYu/dhfErz67Wy8fk4wRZhc3LzLx+gsg9rLpsoPNn3mPjEHhg3dA+p3PMzI5M9tM2RYuM5j8vd0tMVD7JyH3voCwcanD1Ftml6oz97gGGe0EJJet4/J1rRq7oNkVzS35pt0QvXR2iTtOOql+6zEjkN2utF+YXMIWR7Y8tmp6qACT7/pO157zTguz95NVedq6ftFhbCEnb5qkkygLXKvSoUf3/Tu7kI12oYBhIhwVICZQ6nwCM6V43K1xNnI3u5EZ/K4lhtdcc43g7GSZdyPRQjVe1n6akHqQsJ9L5IWVUHoGNr0g2dP/zHptWtPQhBhZweuu/3K1WqAteg+A2SjIDUz0kpD8nYsWnEla/PhPoD6jzFr6z58P7nmb2l4T6lgJcu/89pzSJEx0mPB0a2P5FpZxmdnSf/o8cM+fTfq4HxO/yk37oIcFrVs0tsyxhS5sbOWNvmxHa8LWVEou/qpzIP5r57bs5z8yBvkPBlqH7RpnRnOGdKvWbMVrl6DCMjUiE4PU22bL2PCYxu3+x7eYe2Wnubhv7s+/A+pIoVtPe9t12fvJqjtlXb/gUNLOVDqZkqgRUJocu3tydPjOqUonQCOENIaEkwnhFGrpWEVlvHo3ZyOH4HclMeTFtSuR55PfF2gasnQNbGbL4ZYdZ/+mUpjwWfDaA2MxtFbDrv9+tV1gJBKBp593LvAzC11zJZR8vvMvJa6PzJVOWNi6Xq/DLx940Dx3e+OKFdEXnhpY/AYSRk6lXf3d+e5lZs1fFnVmDbu5Gosls2hyp8aJI3IgNddQLT8Xg6mOsZJ8EFvSmKidaKvddRDUk9MkLhwn++GXgRxsve7yV/YCTVYh0iJzWx8tAVeACVvkBadCiq14DSmrmets1hbkLGDOBm7V6ncegOJnAq3Ddi31R8+GyCWtJXFK/7oHQCLEX31ua+1HTTDx+zcClyps9wdB9eZ9JrGJ21xVdxij6o2LK1N5oud0scetp/vJYrGyx8+NQLO10OHInYgAKal85LGH/8NYCoPHMGsXOuiMr4YSeDN33bXEMMxOBtjvHKoMR6aTUFQvCOg3SSig2QSyOTuw+QWpbP/u5koo1mo49wXezT34Zr5z59MglUyaZXL95GNjY4Yg1j3PvBdxXWBCuKG/39RF5lYslUwW8moghbze+K/tgvirltY1GyZS8PhyU8pUu8ConPN0s15i/v23zdnvRDt0ivMLx1wWqRzO2v3cq9tqOc6HEPP65iO101yzOfP+S8F5WuswAE74qMxBtNolwvBa2BoYvWRb20x1dSAHxY/9BLIcPtCmHVenmTH6F9Y5bJ2drPZPQO59y3dtnOg1Nd/j1sv9ZL542H4nhkBLa2FEQDE3tic3evROMKRQDLdKOtkW31QHOM3vdjcyI9PVxJDdyQ8+CJI1DcMkFO1hVgH2gdYDhLDJJKIAbd50+tNeC+BkPS6R52swhTNshvKJXf1dchS7gQYHB2HLlkFwZGdi4ysFR44MwdDQ0LQAbZfso9MyFuua5ZJnerQEeqQEip+Hi1C7LdDaY6tW5n0vaktOWq2LCQcncCxHS/zWBRC7onWcXzgfx8SV/+P+JZ2ea0FzTei2BOl9twETn06NpYKSv31B2y7kKRPbybp/Yev5xFVtY/vmyv7mMYwETcxpOSdnG3OcI2dbt2q12580CUjt4kH9AzngrOjmlnrrJRB5dvswAXY767FAaH01tvVwP1mN52U1rXk6ExlAOgLcCFMoPzf85KNf4QonnHCCxNZCMSqBxoVLuTDphLULzz0XVLeKWjefh64lhrzI5hJ5nIRSwVIClJ/WAD1cCQV0EGtIiJti6fR5GzZvu7xe18hl8jhDmbhMno01XE3fu5Zr5ezCvt4e6OvtM7WUoxHX9KvVPVMLeXxiHMYnJkH5/qrbaycB5Lk2w3GEHE/YrsVeuRMSLSp4dBp3WSx2jQlZLqYdkQnXxBnWnGm9lI1dqRxj2a5xFvFMUfDj+goM6ja3cR+D0qCGCsDSL2HjOtW9n+kgVfP+24AttO0ax5n2/vNVLT+muoKJN90AnSq5lP7XPcAxjqI33nKM8hd/AVwru7nNJYJd+sL9UPv2Y0t5ak7KWGv5fnJSAF0nkwa6hQgoATgTOaiLjHTs6OHbqoXCA0g0HJS/oxGudCIAJkE6hTgly2HSSbeWwJt5CruaGIaahmw1ZM9hLVKMO0RJ7dWyLF2jkHUNcZNAUypv88ZTTr1SusktHsca+rYayjr5vq7qbbJViYP/jdVvtDxt+RstQfSlOzrG5HWyrjnbMpD54IuNdM1C23IlGnQiMuEaC3/3w6D28RK22IvPhMTvtLf2NSeWLNm0rgQ5mG5PRv/gJmAx8XaNSx9m3ndpy4/VwTzk3nMr8Dkm0fr8OltSLWsnmwE1weTbbwE9WTme/2aiYK7HNq2dFNCSYWYHsgh0MQLNVU4cFrSOCFBe6cjIwaduMdZCgmEUNCwJj7FEjXCjOR+xFK2n+ItWXy3WQj4FXU8MuUQeaxpGIhNOs9VQgexFrfoDqyFsAtSbnGjs1I3bTv8VpTASuJQJwmooQT1H2ywC3YUA1wkmb3a1El5lp/rJ/Hn53++H6ndmW3C4rFv6A5e3FGoOd89ZyJz53KrVvr8fTHLDErbI7i0mEWKuNvnOb4MeKc7VbUGfd9LxW9BAS9SZCeHEH9zUcbROepFzWYrNtfOO54J70WDLObjOdOHDHA41u2WuuwycM/tar40JJVdbmUPSaIlgssNYBLoGAXYhG2IYVjmJICec1EcOPfkNv1Z9CkgMBwknNEJCjklQE83Wwnq91+927cJmsLuaGPJCmyuhsHSNKnux0GqoQPQh0QZAbUrlAcCmTM+G3en+jbvZaugxMWyqoWy5Ydd8z+xC5oFAz8euBLEh0bZn4a9/AN6Do7M+T7x2F8Q6aA2y8HH1G48CayS2Zg4KJt/xrc5l8eax/rBL5BmbIfWO58xpvWR37uQf3gTEFYyWsHUiSUs4zbyH8h8fB05S6dQ6nUNTJvH//rLt4Vwxhes9o2x9ey996m6o/Sio5TyzxV9zLsRffU7bsVkjkrUibbMIrBcEpkrfCQTBlsKGtbAwNrInP3mM/4Ie5tJ3QGKEEI9J0OOhtVAm3OpqkahZdcSwndWQYw2RsE9pGgjcybgJiDZu2HbqFY6b2Ox5gdXQWA75d42NN1wv3+VVv8/Yr54NidftarsP1qDL/ckts0gUW3s4G5br57ZqnJCQ/4tbTWJCp6zZZtmVxYDJJf9S73oeoDt3VnTt9ieg9LlpaZjFzNt8bPZvrgC5Ncha74ZW/8lBKH7yro5L6ZQIUvrcPcDJJe1ap2uHyyxOvvUm4OdWzTmjFzLXt6/W4t13FAof+VE3wGjXYBFYdgTCLGS+nXI95KAmMoLvlY8eO/TUrYA4wqSQ3chS4Cghjc+MLVxt1kIGtesthrzIZqth9EDK9WLVGJfJI19kFOheYKshaxtiYDVEdAY3n37mlVqLGFsOVaNUntU2XPbvkZ1gCRCIXLwVUm9/dtuRWOsv/5EfztLrY/LFFSxEh9i2ZvHrTvOwu3Py7d9sSyDms00mqel3v6BtZm3zGCz4zPGFzQkc85ljPn1MjWR34bGW8xn7RPrUf3QA2F3fqWU/eDmwxmWrFlYraXd8p1hOthSyxbBT65RNDZ6CibfcvCzn6USwtMdYBJYTgSnNQhmIWXNcoRC6evTJx28h8oeMtZDIaBaCsRaKCXR0njOR3WqsWtte9FaDoPVMDFcNMWy2GtbrE5EyyAQondI+ZBUo41ImwI2AtBEINibS6bN7Nm17tlcn6Tcsh6SN0RBsvOFyfpXs2ItCwBGQeNU5ALHZFjZ2seqjRaj/9FDLLFpOWGgniMxr0sfKpkTaVEOExDW72pKm2g8OHFfxYyH7YjcmW64wGWSQt2tUVYbg1vccXsjwa74vy+Ngi2uAN167fX/bxBVMRiB62ezyeCFg/n1HwT+U74gfX0Ncdaddq//k0KqWrVnzF4/d4JIgEMYVIlc4cRAcl4khqsnhQz8tFwoPA8IIkLEYNlzIclw4kAMpiglQ5Uikt74arYUM3qoghrzQ5gxl1jWsx1TMK8sEkmqUyoN+QBrgZJSAHNJAemDThalM/y52KRtyyDWUrYTNknxp7CAWAYuARcAiYBFYiwg0S9NIlqtiUugiFPNjewujw/cC4iiTQiNNQ+xCBlP6jlAW3IQqR6qyupp0C2eew1VFDNlqeMcdIMJqKImKilVJp0hjhusoG5eyIYd6IyAOAMFA3+C257nx9FZDDL2gVF7oUrbJKGvxK233ZBGwCFgELAIWgRND4LhkE4Eg3YAYepXC4fGhQz8ChFEgGgUhDClkFzKTQhSUj6EoluOyGlY5Yd3Ca6+9lhBxaTPqTmxr8z5q1RDDZqvhE0/0CoAht17X0bpTj6MOXMoaqTfIUqYBMpZDGCCgDZu2n3EZilhPmIwSSNjwI3At22YRsAhYBCwCFgGLwPpGICSFLGQ9JU3jIpCuTg4feOJ2BDwGBKM4ZSnEY4Jwgl3IJEQx4kcqkYioAQx6Z5wxoVdDlZNWZ3zVEcPQango/jMZJqI4lUqijpRiq6EA7ENS/YS4URMMIMIGgXLjhlNOfyGim2bLoe9r0MrovNpM5fV9H7C7twhYBCwCFgGLQFDYiAmh0SsEcBxhLIVEXuHYwSd/oEmNEMExgTCKxHGFckwDjbO1MEJY9OPxcphwsq3yLLVarYV8KawqYhhaDcNElHS6Lg9VhiPsUq4BJEGrtEbq0UwONW3gOEO2GgLABkS5aeMppz2P0E0at3KYqWzJob0lWAQsAhYBi4BFYN0iMJMUcgYyk0IkrzRycP+PiBSXYzLWQo4vJIHHBNdCJpwEIQtRgFLoQi4UImo1iVmveothuIHmRJRYrOooJSM1WYnXq5BE6WWkgh5F0I8C+pkcamJiCBuk42wa2Hb6czXJeDM5tG7ldXs/sBu3CFgELAIWgXWMwPHu40CWhkmhQFUZPfTkj5XvDzcshccMKdQwJhHGlIRJUm4+EoNSVMUrUqp6tRrzV1Ppu3anfdVZDJuthpyIErqUAfIRz/HiSJQiJTIcbygI+zSofkAxwIkpBNTvOpFNvVtOuwRRNiyHAGQTUtbxbcFu3SJgEbAIWATWIwLNiSbIiSbsQjbuY1WaOLL/Ls+vDyPgGCeYAOlRAXJMs4g14QRKnSfEouu7FYBMnTULV7sLObwGViUxnEkOOUt5yBt3qUpRVavFBegUCciS4phD3QcIG4zVEKAfAPqFkP19W7ZfImUsw/GGiuMN2bXMJWs5IYX/2aSU9XifsHu2CFgELAIWgTWOgCGEHEnH8YSiUQO5EVeoVDU/fuTAXVqrMQAYI4AxgcaNfEyDGEeJk6ghp0EUZTRawRjWBt0+D+A0fzXHFTaf8lVLDENyeM011wjOUo5EJpxRXXQ53tCTfhyUk65rPyM55pBEH4LqD8ghMjnsA8DevsHtu51Iot+UzFNB3KERwDZZKTZjeY3fG+z2LAIWAYuARWCdIWDiCYEJIZqEE3YdhxnIfr08Nj50YA8ATQDAOAEZUkggxwTqccWJJsLJg/QLrnIqHFc4IFIeC1mv5izkmZfAqieGnIiyd+9efPBBkBxvCFBxazWKeYLFr1njUGU0il4C6gWCfgLdP00OoSe7YfN58XTPFt8DNARRB8TQxh2us7uF3a5FwCJgEbAIrGkEjosnFGishUFVE6BKceJIbnT4AQCYDEkhghgDFq8GnBCkJ1DIPKEoulqVo1GsAsS9MK5w165dtBo1C1ud8FVNDJtdys3kkJNRPK8e80Q9YWIOWQBbUM80OaQ+disTANdZ7olnek7N9m8+Syt0fJOtTMDl86xreU3fI+zmLAIWAYuARWAdIDDTdcxl7thK6BhrIfm5saOPVPKTTwHiJAJMsPsYAcdDUog6ELA2MYU6UnbdSLU52WQtkUK+HFY9MWwmh2EySuKwcojciB/xY6qugoSUJnKIoPuIsA8ReklTLyD0OG50oGfTKecJEUkqFegcGkmbUAS7IYi9Dr5DdosWAYuARcAiYBFYEwiEUjT8zBqFgeuYnwVoXS9NDh98wPdqo0AwiQIniGACkcaJ4wkBJ5pJoYzIilN3qohevbxV+msl2WRNuZKbN8MSNs3i183k0Kt5CQmYDMihypJm66HoQ6ReAOolwF4k6AGkTGZg81mxZN+g9kmYuEN2K2vOXGZBbBt7uCbuFHYTFgGLgEXAIrCmEZiKJUQEthDyg+ses6VQOKirpfGh/OjRR4AwTwiTaOIKmRjiBIIeR8FJJjLHlkIFVHKjbnk9kMI1YzEMr+5O5JAt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oDqM/o5IUgRIONYy4xBlEOW75Hm5n+rQ1r3d3CQ1RwWZlvcVMC5SGQygmA8T1pFrtkgWVTyTN6ngFIGvpWNdjWZhTXds/4Mf3LuIBpbscXtV2Rhpn96CioqoksRvMxOSyLlBPJsllQWSR1zhcg3UHoCFY/QldMBQ0qje1mQsaZKkhmjDdt/1hY01mppGiqbyB5bZrV0U8VAMAvKg2FCKAl73kFQblhihYSwEoRTY2qxEOs2ZxJrhHZJpRTOsy5+sMuBThicCMQzl1GdeMXS6Kc/+vApAGQ69ha8PXvQrTKomJDIKpJEgqKk4UvDLHuLzrUYw7PAV3wyFatdY8ZqohG5hEADKZERrjGDxFSwgDSxMrChrDa3tS3pnPdaLNqKHbRoVUDke11bSBuDTKCeCTlPKtfSTsYidIQpKIOKIZEmjDUGEiPAT2n8zx5CLZ1fNb3D3TpVCEjDSRNkqz5W33zC7u56NDAfCuDxN1jiMHr9GAE0ohtdWO+K4aDRKHswKbySdbBKnkBqMkRzDl6+aczXGiSmG4zVMplBB6K0anDdTjdr7lGzm9SKjjbdLlCRds+UyTVqS/YZKxPvsuNyLWPNmzxqAxaZJg4TiLVUYjWFqNt2FeBYUqpIjMTGrIQQ6yU2vT5hZwZRrRvMjTF+2CPCDEGwljE8PwTV4lvVYQynKxV0ywi+q9DY9zRWTjxkG9x9AbSbxQd6wiFZCkR9FUvVKhIr45JG2OUKkwLFZaRhnhw/+YPg1re+iV7f00eXCeVzQvZZ7aoMShVhHq8ZXI+kWBUMux3rniiINZwV4JIxnuQ8jqqapoqF0YIprN1n5Vtm5RmTiDOJZLMdWGT9ZxvqprYb0xQHts1uwn5iIwek+E8j5zCnn8KwVMhOjtEdURtb//fPcjEVYa8uBSnex8LJ++xkuBdAZvr7n2BAEXxEmD05RoltbE03KqkksVpfWnrnpV3htz8IH5Nedenk2GDt+CS7GbLfMpkp3QjcyWspvpxTgzHlMvNeDYrrUlzTyCctrTZkbe0QYVXrbUpruWf36o7WG1u+eX1rgFvb0MrQXP7dI0UJrAzKFTL7n9T8pyOJ/On3jlD6e5e4qxaFlT97ttB5NGjj869fYq8UYwhJLTz5XGnxbta+A0ALhNHxqJDe/Mkxqlkld/w8eupxVI4THf3shdKcbfl3z3A3JVX5v4525VsnXj1VH/aVesGQFjHogzOO/1sazY3mBWOGHUZfLuGYqjGwmskmu+WmsXXFpA3di6YIzE2N/OYuEKyP0fJQbGnLhTO2noIxuT3ZvCzpbpYQDozp7zKmuB/mL4nSd//82eZ8vv5BdQDlUvzmE5SnQje7LND1DL036rh5uiOWuAHgt2w6cgFD4wdxrc33v32Oe0iE5TjhLF37f/MTr7yS28ffPtsY/dNDhY2s/6tvr/WKwP+SlXBsFM0omrmpnKOWnXKgtLGnGKwbVxAGwgiLJcWGERkSkSaTshCp0TY/YqwWzsFr6g+R54+aV24kWnNPEoxj2T0lhIZE56mcTQFwjOkpEgZHtP55QZtVn7y/+sFhyiPWx5llfKYx9OfPFfMs3v0uK9bKw9Euf9mfPfkS5VtKcgDtttx9Ejt/+DRdaX98/G0OskGU6/UakuWwMfHK4MbBrC+/WxvSYaO+8Y6Z/t7fNo4YkkMi5ZrxZHWJoWaF81wk8w3nOSA2T2TlojSmJBg+wE5Ohe1Dl02r1wYLmoi1DwTmcQQ71tyKyY1utktgbfBcStJarMRsJxW25kGKUfbYDPgwtYE0+6AIU4fBjZ+MF0+35/r1d7lLKbg/PEI2CPHgi5m+dQ57ZlJMW0rMAfzW2XDv+EF/g/LsO0t9IoFs6Cqv/u3F9dP/7Mht4X+CxVd/J348XfWuTLTTg8xi7Px5NTk2thEmOnZmpXtZe0+tee7nEsgdaZ4YgW5TmKUignCs2SENHOvbkmFlg/R5VMZKtHyVLX5sg1wGgjLNyEjkyiTVjKQl93LPh6zxDFOUBmWXIX1j5rqQXS5lZoWkbdC51n3J+bCtFCzxjFTjx3561LPJ9g55zHR8ErvqEr6JoqRary39zRcH8jMH9iTCUAEjPz5A1+jYW+wXBtH940000YOWwjbSK+M9quTNPUh2tNs49haXlsrJaCTFrox5WEvZkwIFFvC0gGLOFUrT3G6GAJtecvvothVqzeCC1cqCGErCuNJq7KbCYseYzAHqLnjVM7xYMKYqbGisGWtcUTK78JND5dYxOqbfPofuRMf9dxDCxqSZvn0JO1ODUqNeEzqj5YnnSxva+qsX6iPq8swSfe1sddBLS7UfHqGHypHNAP2NU/VhSbIYpt78e0dR/TTukV394XAlyIwbVIUqpkyBkZmfwXUEZ4pABZfE3tz+a4lBK/zIilGtMyVFIoyOpGGdmzSy5VdblIVi5jQ2RHOOKVz/2fNYzsd24oQ49juvdzmIB9I0q3aC0jk/a/+mh7En0lBxNUbseitvH6KNM4zHJrmEsOrT187y4FKK2ulfEcC8U+sLv18fMkaVtTJxhGDx9Pivf6T082e4u5w0jrVZ/o5oTd6xJcsmiVrFRMwJaVOVjCUpyws/u4bVfBvbCRbHjqOAJOrPEnKN762+fRAL911sZnr1I+xgiUoaxZwmSMu6vvjmC30bWjoHUMGnF9/mwKvUKxNjt8nzYXL0QeWWqrrjRr/hLPeFTepEQLj+3vXeOo63IXg0N+nZv17tKbvOSyYPD0ojODNQMkPGKQuOQSZURtVj1o1a2KhPLgyEOP8dPv7663RpYrVcLHtdpIVvN55r1vVVr7D40EAqM33lMrrcGN2hgI84ho5NY+nqlbnJ127L969+UB9J1+aXcyH9xfejfT8/4l3dqo3XnQC/eIOD7BYqxGsBsa/syUomN9MJa+GZpJHpBHFXMgBk1TJ0uXrbCK6WT9PafEV4j+1nPwTbsmoZ5F6eVssjvqo4nuuk0uOCcGBIJZwoLwYiMlnBcxpZUlh9p2VuPApRjM9woRzDVQZdWYYCasgaWXWlr7dce7MjAGvlf9GJRv/qUHAlB3DPW1f80b7hkZ8/69mNh1v2myr3HTQz7X9zyq04fb5XcDwm6SQ6kqkrpJNBuL5POrO7PlyYNCHhNBNNUnkm02y0ZO0qG70O0jhdidfml6Kpb+x/5ADAHeOyG+5OQrz6OQwuNrBW9NDHaVJmxVF4bXm2vG9YTFinon29wfKlffGetcC7Yal5w5Aem+RSJYyH3r7sbdn210dZ9b+zOvYoIsDHLuCxMKuHblo0UiV9mWGzTt7N3mXoq7iKq6/stafH8ssa0nFXvCdhb6atM+5w5ewO+6HVeJeqV2fbNs/f2QQ/g47H3mB38jWk46egCgGeyLA++87JrtXfeK0xpOumb13TApeLK0KvFT882N1xZJtp/BS6lIwHl0re9c5o9qbBhKPvhTs5IGe54M9sVeh7A48Tv1z5LTpq+gARIdry/KWzPPj2wfx0pj52iUfTRlyMUu/y6R9Bv/wPMJolSWlp1v1k6hsUHzzLxXOHKPfT25dVsokbj2SJic6+FMw8MJjQ+aFdLXc/hpVek4Yqs6d/9J0IJ078WoeUX5zk3no1LJx7oelHWy1bzSrh1VcoZxPLAVf3Nu/bLNP2dCz7TByDbsvoOyZrzairGJrY2wxLvXyBR+xvVvzNczTz8gUuG8aepI5PLNuNvTVfCnorexK4V3Kwftlu/stGnRsumz8eVPCieAcTp8L4lmU33Yz00ICqHfhKD4akjgNiXY8uX12aPH4g/bTKxh5CrITJk6cPeh/m6DDTkXPJ2KlD7mTTa2P6wtnkwPuf95o/NsRM4x8mT50+6F2wj+OneNgNEL8zRvm+5y98yLsiXqu1We35s+Feqfy1dvnh8/yYTqHPHaJpqzWB5PFy1Z3aAOpuTrCKbQpusR72I98A79XPrkzMoRVAuR+1PxTAzg+PvrvUlbiFHmJytPTCpQaWp6eR4DXrJzxYe1uK0Qpp2w6zSsuV6DrzNOURELtQ4RD2vneALrUBfO4XydMfPOt9ZJ/tAgRhvPPDg/7lvPwNlof3154681z5fHOMTIfeqz5x9mj5Unss46e4cvoI3efIVzP7cvAcfCcN+zIlfAo5CXv8pY+fptY5+/sKiY2CTwVgZ3Pjp7iQJWGPdoVv3wvHxI0wXB8NexsTCycZrx1/KKh3DK/1m1udhu7Rd7nrvRdux+ieusDlzslZUB9NRjPhjZNifN8+oeXjRam7uzIV+0269xoqu7Vy+sjIr+TK/soA3r02FtDI1Lscp+jHiB17LoM9TmWqo9jEDe96bzQwMGEmFhYY588zXn/dJjW3xua0ttx3QDgAOjYAmg6npBnc7zuiUXSV9MnmcJpRijQjHRZQWPu1XNeOyW8ZgJsRu5U9Wq4WY90dQESuNKQyBWlzIEgSCOUaqWGEwyatRSaVnk0WG+WykV7R1Gs12MPaRubZY8oUCS0LQjVWlaMCweRRpmJpMhJuChIFNmkIY6MI7JkkoKQhdXf9fgrg4Qz68BqfKYAP7z5XFnL/FFShAVVLV1TR7RFxUpVGEBVkM+Db0CUWpspOwiZ0tS45PVmjgGxqekI/TMg/0hh+jUr/HxQyzAyn02DWAAAAAElFTkSuQmCC",Oe="data:image/png;base64,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",ze="data:image/png;base64,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e.x===this.x&&e.y===this.y}fromArray(e,t=0){return this.x=e[t],this.y=e[t+1],this}toArray(e=[],t=0){return e[t]=this.x,e[t+1]=this.y,e}fromBufferAttribute(e,t){return this.x=e.getX(t),this.y=e.getY(t),this}rotateAround(e,t){const n=Math.cos(t),i=Math.sin(t),r=this.x-e.x,s=this.y-e.y;return this.x=r*n-s*i+e.x,this.y=r*i+s*n+e.y,this}random(){return this.x=Math.random(),this.y=Math.random(),this}*[Symbol.iterator](){yield this.x,yield this.y}}class Ms{constructor(e=0,t=0,n=0,i=1){this.isQuaternion=!0,this._x=e,this._y=t,this._z=n,this._w=i}static slerpFlat(e,t,n,i,r,s,o){let a=n[i+0],l=n[i+1],u=n[i+2],c=n[i+3];const d=r[s+0],h=r[s+1],f=r[s+2],p=r[s+3];if(0===o)return e[t+0]=a,e[t+1]=l,e[t+2]=u,void(e[t+3]=c);if(1===o)return e[t+0]=d,e[t+1]=h,e[t+2]=f,void(e[t+3]=p);if(c!==p||a!==d||l!==h||u!==f){let e=1-o;const t=a*d+l*h+u*f+c*p,n=t>=0?1:-1,i=1-t*t;if(i>Number.EPSILON){const r=Math.sqrt(i),s=Math.atan2(r,t*n);e=Math.sin(e*s)/r,o=Math.sin(o*s)/r}const r=o*n;if(a=a*e+d*r,l=l*e+h*r,u=u*e+f*r,c=c*e+p*r,e===1-o){const e=1/Math.sqrt(a*a+l*l+u*u+c*c);a*=e,l*=e,u*=e,c*=e}}e[t]=a,e[t+1]=l,e[t+2]=u,e[t+3]=c}static multiplyQuaternionsFlat(e,t,n,i,r,s){const o=n[i],a=n[i+1],l=n[i+2],u=n[i+3],c=r[s],d=r[s+1],h=r[s+2],f=r[s+3];return e[t]=o*f+u*c+a*h-l*d,e[t+1]=a*f+u*d+l*c-o*h,e[t+2]=l*f+u*h+o*d-a*c,e[t+3]=u*f-o*c-a*d-l*h,e}get x(){return this._x}set x(e){this._x=e,this._onChangeCallback()}get y(){return this._y}set y(e){this._y=e,this._onChangeCallback()}get z(){return this._z}set z(e){this._z=e,this._onChangeCallback()}get w(){return this._w}set w(e){this._w=e,this._onChangeCallback()}set(e,t,n,i){return this._x=e,this._y=t,this._z=n,this._w=i,this._onChangeCallback(),this}clone(){return new this.constructor(this._x,this._y,this._z,this._w)}copy(e){return this._x=e.x,this._y=e.y,this._z=e.z,this._w=e.w,this._onChangeCallback(),this}setFromEuler(e,t=!0){const n=e._x,i=e._y,r=e._z,s=e._order,o=Math.cos,a=Math.sin,l=o(n/2),u=o(i/2),c=o(r/2),d=a(n/2),h=a(i/2),f=a(r/2);switch(s){case"XYZ":this._x=d*u*c+l*h*f,this._y=l*h*c-d*u*f,this._z=l*u*f+d*h*c,this._w=l*u*c-d*h*f;break;case"YXZ":this._x=d*u*c+l*h*f,this._y=l*h*c-d*u*f,this._z=l*u*f-d*h*c,this._w=l*u*c+d*h*f;break;case"ZXY":this._x=d*u*c-l*h*f,this._y=l*h*c+d*u*f,this._z=l*u*f+d*h*c,this._w=l*u*c-d*h*f;break;case"ZYX":this._x=d*u*c-l*h*f,this._y=l*h*c+d*u*f,this._z=l*u*f-d*h*c,this._w=l*u*c+d*h*f;break;case"YZX":this._x=d*u*c+l*h*f,this._y=l*h*c+d*u*f,this._z=l*u*f-d*h*c,this._w=l*u*c-d*h*f;break;case"XZY":this._x=d*u*c-l*h*f,this._y=l*h*c-d*u*f,this._z=l*u*f+d*h*c,this._w=l*u*c+d*h*f;break;default:console.warn("THREE.Quaternion: .setFromEuler() encountered an unknown order: "+s)}return!0===t&&this._onChangeCallback(),this}setFromAxisAngle(e,t){const n=t/2,i=Math.sin(n);return this._x=e.x*i,this._y=e.y*i,this._z=e.z*i,this._w=Math.cos(n),this._onChangeCallback(),this}setFromRotationMatrix(e){const t=e.elements,n=t[0],i=t[4],r=t[8],s=t[1],o=t[5],a=t[9],l=t[2],u=t[6],c=t[10],d=n+o+c;if(d>0){const e=.5/Math.sqrt(d+1);this._w=.25/e,this._x=(u-a)*e,this._y=(r-l)*e,this._z=(s-i)*e}else if(n>o&&n>c){const e=2*Math.sqrt(1+n-o-c);this._w=(u-a)/e,this._x=.25*e,this._y=(i+s)/e,this._z=(r+l)/e}else if(o>c){const e=2*Math.sqrt(1+o-n-c);this._w=(r-l)/e,this._x=(i+s)/e,this._y=.25*e,this._z=(a+u)/e}else{const e=2*Math.sqrt(1+c-n-o);this._w=(s-i)/e,this._x=(r+l)/e,this._y=(a+u)/e,this._z=.25*e}return this._onChangeCallback(),this}setFromUnitVectors(e,t){let n=e.dot(t)+1;return n<1e-8?(n=0,Math.abs(e.x)>Math.abs(e.z)?(this._x=-e.y,this._y=e.x,this._z=0,this._w=n):(this._x=0,this._y=-e.z,this._z=e.y,this._w=n)):(this._x=e.y*t.z-e.z*t.y,this._y=e.z*t.x-e.x*t.z,this._z=e.x*t.y-e.y*t.x,this._w=n),this.normalize()}angleTo(e){return 2*Math.acos(Math.abs(vs(this.dot(e),-1,1)))}rotateTowards(e,t){const n=this.angleTo(e);if(0===n)return this;const i=Math.min(1,t/n);return this.slerp(e,i),this}identity(){return this.set(0,0,0,1)}invert(){return this.conjugate()}conjugate(){return this._x*=-1,this._y*=-1,this._z*=-1,this._onChangeCallback(),this}dot(e){return this._x*e._x+this._y*e._y+this._z*e._z+this._w*e._w}lengthSq(){return this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w}length(){return Math.sqrt(this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w)}normalize(){let e=this.length();return 0===e?(this._x=0,this._y=0,this._z=0,this._w=1):(e=1/e,this._x=this._x*e,this._y=this._y*e,this._z=this._z*e,this._w=this._w*e),this._onChangeCallback(),this}multiply(e){return this.multiplyQuaternions(this,e)}premultiply(e){return this.multiplyQuaternions(e,this)}multiplyQuaternions(e,t){const n=e._x,i=e._y,r=e._z,s=e._w,o=t._x,a=t._y,l=t._z,u=t._w;return this._x=n*u+s*o+i*l-r*a,this._y=i*u+s*a+r*o-n*l,this._z=r*u+s*l+n*a-i*o,this._w=s*u-n*o-i*a-r*l,this._onChangeCallback(),this}slerp(e,t){if(0===t)return this;if(1===t)return this.copy(e);const n=this._x,i=this._y,r=this._z,s=this._w;let o=s*e._w+n*e._x+i*e._y+r*e._z;if(o<0?(this._w=-e._w,this._x=-e._x,this._y=-e._y,this._z=-e._z,o=-o):this.copy(e),o>=1)return this._w=s,this._x=n,this._y=i,this._z=r,this;const a=1-o*o;if(a<=Number.EPSILON){const e=1-t;return this._w=e*s+t*this._w,this._x=e*n+t*this._x,this._y=e*i+t*this._y,this._z=e*r+t*this._z,this.normalize(),this}const l=Math.sqrt(a),u=Math.atan2(l,o),c=Math.sin((1-t)*u)/l,d=Math.sin(t*u)/l;return this._w=s*c+this._w*d,this._x=n*c+this._x*d,this._y=i*c+this._y*d,this._z=r*c+this._z*d,this._onChangeCallback(),this}slerpQuaternions(e,t,n){return this.copy(e).slerp(t,n)}random(){const e=2*Math.PI*Math.random(),t=2*Math.PI*Math.random(),n=Math.random(),i=Math.sqrt(1-n),r=Math.sqrt(n);return this.set(i*Math.sin(e),i*Math.cos(e),r*Math.sin(t),r*Math.cos(t))}equals(e){return e._x===this._x&&e._y===this._y&&e._z===this._z&&e._w===this._w}fromArray(e,t=0){return this._x=e[t],this._y=e[t+1],this._z=e[t+2],this._w=e[t+3],this._onChangeCallback(),this}toArray(e=[],t=0){return e[t]=this._x,e[t+1]=this._y,e[t+2]=this._z,e[t+3]=this._w,e}fromBufferAttribute(e,t){return this._x=e.getX(t),this._y=e.getY(t),this._z=e.getZ(t),this._w=e.getW(t),this._onChangeCallback(),this}toJSON(){return this.toArray()}_onChange(e){return this._onChangeCallback=e,this}_onChangeCallback(){}*[Symbol.iterator](){yield this._x,yield this._y,yield this._z,yield this._w}}class Es{constructor(e=0,t=0,n=0){Es.prototype.isVector3=!0,this.x=e,this.y=t,this.z=n}set(e,t,n){return void 0===n&&(n=this.z),this.x=e,this.y=t,this.z=n,this}setScalar(e){return this.x=e,this.y=e,this.z=e,this}setX(e){return this.x=e,this}setY(e){return this.y=e,this}setZ(e){return this.z=e,this}setComponent(e,t){switch(e){case 0:this.x=t;break;case 1:this.y=t;break;case 2:this.z=t;break;default:throw new Error("index is out of range: "+e)}return this}getComponent(e){switch(e){case 0:return this.x;case 1:return this.y;case 2:return this.z;default:throw new Error("index is out of range: "+e)}}clone(){return new this.constructor(this.x,this.y,this.z)}copy(e){return this.x=e.x,this.y=e.y,this.z=e.z,this}add(e){return this.x+=e.x,this.y+=e.y,this.z+=e.z,this}addScalar(e){return this.x+=e,this.y+=e,this.z+=e,this}addVectors(e,t){return this.x=e.x+t.x,this.y=e.y+t.y,this.z=e.z+t.z,this}addScaledVector(e,t){return this.x+=e.x*t,this.y+=e.y*t,this.z+=e.z*t,this}sub(e){return this.x-=e.x,this.y-=e.y,this.z-=e.z,this}subScalar(e){return this.x-=e,this.y-=e,this.z-=e,this}subVectors(e,t){return this.x=e.x-t.x,this.y=e.y-t.y,this.z=e.z-t.z,this}multiply(e){return this.x*=e.x,this.y*=e.y,this.z*=e.z,this}multiplyScalar(e){return this.x*=e,this.y*=e,this.z*=e,this}multiplyVectors(e,t){return this.x=e.x*t.x,this.y=e.y*t.y,this.z=e.z*t.z,this}applyEuler(e){return this.applyQuaternion(Ss.setFromEuler(e))}applyAxisAngle(e,t){return this.applyQuaternion(Ss.setFromAxisAngle(e,t))}applyMatrix3(e){const t=this.x,n=this.y,i=this.z,r=e.elements;return this.x=r[0]*t+r[3]*n+r[6]*i,this.y=r[1]*t+r[4]*n+r[7]*i,this.z=r[2]*t+r[5]*n+r[8]*i,this}applyNormalMatrix(e){return this.applyMatrix3(e).normalize()}applyMatrix4(e){const t=this.x,n=this.y,i=this.z,r=e.elements,s=1/(r[3]*t+r[7]*n+r[11]*i+r[15]);return this.x=(r[0]*t+r[4]*n+r[8]*i+r[12])*s,this.y=(r[1]*t+r[5]*n+r[9]*i+r[13])*s,this.z=(r[2]*t+r[6]*n+r[10]*i+r[14])*s,this}applyQuaternion(e){const t=this.x,n=this.y,i=this.z,r=e.x,s=e.y,o=e.z,a=e.w,l=2*(s*i-o*n),u=2*(o*t-r*i),c=2*(r*n-s*t);return this.x=t+a*l+s*c-o*u,this.y=n+a*u+o*l-r*c,this.z=i+a*c+r*u-s*l,this}project(e){return this.applyMatrix4(e.matrixWorldInverse).applyMatrix4(e.projectionMatrix)}unproject(e){return this.applyMatrix4(e.projectionMatrixInverse).applyMatrix4(e.matrixWorld)}transformDirection(e){const t=this.x,n=this.y,i=this.z,r=e.elements;return this.x=r[0]*t+r[4]*n+r[8]*i,this.y=r[1]*t+r[5]*n+r[9]*i,this.z=r[2]*t+r[6]*n+r[10]*i,this.normalize()}divide(e){return this.x/=e.x,this.y/=e.y,this.z/=e.z,this}divideScalar(e){return this.multiplyScalar(1/e)}min(e){return this.x=Math.min(this.x,e.x),this.y=Math.min(this.y,e.y),this.z=Math.min(this.z,e.z),this}max(e){return this.x=Math.max(this.x,e.x),this.y=Math.max(this.y,e.y),this.z=Math.max(this.z,e.z),this}clamp(e,t){return this.x=vs(this.x,e.x,t.x),this.y=vs(this.y,e.y,t.y),this.z=vs(this.z,e.z,t.z),this}clampScalar(e,t){return this.x=vs(this.x,e,t),this.y=vs(this.y,e,t),this.z=vs(this.z,e,t),this}clampLength(e,t){const n=this.length();return this.divideScalar(n||1).multiplyScalar(vs(n,e,t))}floor(){return this.x=Math.floor(this.x),this.y=Math.floor(this.y),this.z=Math.floor(this.z),this}ceil(){return this.x=Math.ceil(this.x),this.y=Math.ceil(this.y),this.z=Math.ceil(this.z),this}round(){return this.x=Math.round(this.x),this.y=Math.round(this.y),this.z=Math.round(this.z),this}roundToZero(){return this.x=Math.trunc(this.x),this.y=Math.trunc(this.y),this.z=Math.trunc(this.z),this}negate(){return this.x=-this.x,this.y=-this.y,this.z=-this.z,this}dot(e){return this.x*e.x+this.y*e.y+this.z*e.z}lengthSq(){return this.x*this.x+this.y*this.y+this.z*this.z}length(){return Math.sqrt(this.x*this.x+this.y*this.y+this.z*this.z)}manhattanLength(){return Math.abs(this.x)+Math.abs(this.y)+Math.abs(this.z)}normalize(){return this.divideScalar(this.length()||1)}setLength(e){return this.normalize().multiplyScalar(e)}lerp(e,t){return this.x+=(e.x-this.x)*t,this.y+=(e.y-this.y)*t,this.z+=(e.z-this.z)*t,this}lerpVectors(e,t,n){return this.x=e.x+(t.x-e.x)*n,this.y=e.y+(t.y-e.y)*n,this.z=e.z+(t.z-e.z)*n,this}cross(e){return this.crossVectors(this,e)}crossVectors(e,t){const n=e.x,i=e.y,r=e.z,s=t.x,o=t.y,a=t.z;return this.x=i*a-r*o,this.y=r*s-n*a,this.z=n*o-i*s,this}projectOnVector(e){const t=e.lengthSq();if(0===t)return this.set(0,0,0);const n=e.dot(this)/t;return this.copy(e).multiplyScalar(n)}projectOnPlane(e){return Ts.copy(this).projectOnVector(e),this.sub(Ts)}reflect(e){return this.sub(Ts.copy(e).multiplyScalar(2*this.dot(e)))}angleTo(e){const t=Math.sqrt(this.lengthSq()*e.lengthSq());if(0===t)return Math.PI/2;const n=this.dot(e)/t;return Math.acos(vs(n,-1,1))}distanceTo(e){return Math.sqrt(this.distanceToSquared(e))}distanceToSquared(e){const t=this.x-e.x,n=this.y-e.y,i=this.z-e.z;return t*t+n*n+i*i}manhattanDistanceTo(e){return Math.abs(this.x-e.x)+Math.abs(this.y-e.y)+Math.abs(this.z-e.z)}setFromSpherical(e){return this.setFromSphericalCoords(e.radius,e.phi,e.theta)}setFromSphericalCoords(e,t,n){const i=Math.sin(t)*e;return this.x=i*Math.sin(n),this.y=Math.cos(t)*e,this.z=i*Math.cos(n),this}setFromCylindrical(e){return this.setFromCylindricalCoords(e.radius,e.theta,e.y)}setFromCylindricalCoords(e,t,n){return this.x=e*Math.sin(t),this.y=n,this.z=e*Math.cos(t),this}setFromMatrixPosition(e){const t=e.elements;return this.x=t[12],this.y=t[13],this.z=t[14],this}setFromMatrixScale(e){const t=this.setFromMatrixColumn(e,0).length(),n=this.setFromMatrixColumn(e,1).length(),i=this.setFromMatrixColumn(e,2).length();return this.x=t,this.y=n,this.z=i,this}setFromMatrixColumn(e,t){return this.fromArray(e.elements,4*t)}setFromMatrix3Column(e,t){return this.fromArray(e.elements,3*t)}setFromEuler(e){return this.x=e._x,this.y=e._y,this.z=e._z,this}setFromColor(e){return this.x=e.r,this.y=e.g,this.z=e.b,this}equals(e){return e.x===this.x&&e.y===this.y&&e.z===this.z}fromArray(e,t=0){return this.x=e[t],this.y=e[t+1],this.z=e[t+2],this}toArray(e=[],t=0){return e[t]=this.x,e[t+1]=this.y,e[t+2]=this.z,e}fromBufferAttribute(e,t){return this.x=e.getX(t),this.y=e.getY(t),this.z=e.getZ(t),this}random(){return this.x=Math.random(),this.y=Math.random(),this.z=Math.random(),this}randomDirection(){const e=Math.random()*Math.PI*2,t=2*Math.random()-1,n=Math.sqrt(1-t*t);return this.x=n*Math.cos(e),this.y=t,this.z=n*Math.sin(e),this}*[Symbol.iterator](){yield this.x,yield this.y,yield this.z}}const Ts=new Es,Ss=new Ms;class Ps{constructor(e,t,n,i,r,s,o,a,l){Ps.prototype.isMatrix3=!0,this.elements=[1,0,0,0,1,0,0,0,1],void 0!==e&&this.set(e,t,n,i,r,s,o,a,l)}set(e,t,n,i,r,s,o,a,l){const u=this.elements;return u[0]=e,u[1]=i,u[2]=o,u[3]=t,u[4]=r,u[5]=a,u[6]=n,u[7]=s,u[8]=l,this}identity(){return this.set(1,0,0,0,1,0,0,0,1),this}copy(e){const t=this.elements,n=e.elements;return t[0]=n[0],t[1]=n[1],t[2]=n[2],t[3]=n[3],t[4]=n[4],t[5]=n[5],t[6]=n[6],t[7]=n[7],t[8]=n[8],this}extractBasis(e,t,n){return e.setFromMatrix3Column(this,0),t.setFromMatrix3Column(this,1),n.setFromMatrix3Column(this,2),this}setFromMatrix4(e){const t=e.elements;return this.set(t[0],t[4],t[8],t[1],t[5],t[9],t[2],t[6],t[10]),this}multiply(e){return this.multiplyMatrices(this,e)}premultiply(e){return this.multiplyMatrices(e,this)}multiplyMatrices(e,t){const n=e.elements,i=t.elements,r=this.elements,s=n[0],o=n[3],a=n[6],l=n[1],u=n[4],c=n[7],d=n[2],h=n[5],f=n[8],p=i[0],g=i[3],m=i[6],v=i[1],A=i[4],x=i[7],y=i[2],b=i[5],w=i[8];return r[0]=s*p+o*v+a*y,r[3]=s*g+o*A+a*b,r[6]=s*m+o*x+a*w,r[1]=l*p+u*v+c*y,r[4]=l*g+u*A+c*b,r[7]=l*m+u*x+c*w,r[2]=d*p+h*v+f*y,r[5]=d*g+h*A+f*b,r[8]=d*m+h*x+f*w,this}multiplyScalar(e){const t=this.elements;return t[0]*=e,t[3]*=e,t[6]*=e,t[1]*=e,t[4]*=e,t[7]*=e,t[2]*=e,t[5]*=e,t[8]*=e,this}determinant(){const e=this.elements,t=e[0],n=e[1],i=e[2],r=e[3],s=e[4],o=e[5],a=e[6],l=e[7],u=e[8];return t*s*u-t*o*l-n*r*u+n*o*a+i*r*l-i*s*a}invert(){const e=this.elements,t=e[0],n=e[1],i=e[2],r=e[3],s=e[4],o=e[5],a=e[6],l=e[7],u=e[8],c=u*s-o*l,d=o*a-u*r,h=l*r-s*a,f=t*c+n*d+i*h;if(0===f)return this.set(0,0,0,0,0,0,0,0,0);const p=1/f;return e[0]=c*p,e[1]=(i*l-u*n)*p,e[2]=(o*n-i*s)*p,e[3]=d*p,e[4]=(u*t-i*a)*p,e[5]=(i*r-o*t)*p,e[6]=h*p,e[7]=(n*a-l*t)*p,e[8]=(s*t-n*r)*p,this}transpose(){let e;const t=this.elements;return e=t[1],t[1]=t[3],t[3]=e,e=t[2],t[2]=t[6],t[6]=e,e=t[5],t[5]=t[7],t[7]=e,this}getNormalMatrix(e){return this.setFromMatrix4(e).invert().transpose()}transposeIntoArray(e){const t=this.elements;return e[0]=t[0],e[1]=t[3],e[2]=t[6],e[3]=t[1],e[4]=t[4],e[5]=t[7],e[6]=t[2],e[7]=t[5],e[8]=t[8],this}setUvTransform(e,t,n,i,r,s,o){const a=Math.cos(r),l=Math.sin(r);return this.set(n*a,n*l,-n*(a*s+l*o)+s+e,-i*l,i*a,-i*(-l*s+a*o)+o+t,0,0,1),this}scale(e,t){return this.premultiply(Ns.makeScale(e,t)),this}rotate(e){return this.premultiply(Ns.makeRotation(-e)),this}translate(e,t){return this.premultiply(Ns.makeTranslation(e,t)),this}makeTranslation(e,t){return e.isVector2?this.set(1,0,e.x,0,1,e.y,0,0,1):this.set(1,0,e,0,1,t,0,0,1),this}makeRotation(e){const t=Math.cos(e),n=Math.sin(e);return this.set(t,-n,0,n,t,0,0,0,1),this}makeScale(e,t){return this.set(e,0,0,0,t,0,0,0,1),this}equals(e){const t=this.elements,n=e.elements;for(let e=0;e<9;e++)if(t[e]!==n[e])return!1;return!0}fromArray(e,t=0){for(let n=0;n<9;n++)this.elements[n]=e[n+t];return this}toArray(e=[],t=0){const n=this.elements;return e[t]=n[0],e[t+1]=n[1],e[t+2]=n[2],e[t+3]=n[3],e[t+4]=n[4],e[t+5]=n[5],e[t+6]=n[6],e[t+7]=n[7],e[t+8]=n[8],e}clone(){return(new this.constructor).fromArray(this.elements)}}const Ns=new Ps;function Bs(e){for(let t=e.length-1;t>=0;--t)if(e[t]>=65535)return!0;return!1}Int8Array,Uint8Array,Uint8ClampedArray,Int16Array,Uint16Array,Int32Array,Uint32Array,Float32Array,Float64Array;function Ds(e){return document.createElementNS("http://www.w3.org/1999/xhtml",e)}function Is(){const e=Ds("canvas");return e.style.display="block",e}const Ls={};function js(e){e in Ls||(Ls[e]=!0,console.warn(e))}const Os=(new Ps).set(.4123908,.3575843,.1804808,.212639,.7151687,.0721923,.0193308,.1191948,.9505322),zs=(new Ps).set(3.2409699,-1.5373832,-.4986108,-.9692436,1.8759675,.0415551,.0556301,-.203977,1.0569715);function Rs(){const e={enabled:!0,workingColorSpace:_r,spaces:{},convert:function(e,t,n){return!1!==this.enabled&&t!==n&&t&&n?(this.spaces[t].transfer===es&&(e.r=Fs(e.r),e.g=Fs(e.g),e.b=Fs(e.b)),this.spaces[t].primaries!==this.spaces[n].primaries&&(e.applyMatrix3(this.spaces[t].toXYZ),e.applyMatrix3(this.spaces[n].fromXYZ)),this.spaces[n].transfer===es&&(e.r=Hs(e.r),e.g=Hs(e.g),e.b=Hs(e.b)),e):e},workingToColorSpace:function(e,t){return this.convert(e,this.workingColorSpace,t)},colorSpaceToWorking:function(e,t){return this.convert(e,t,this.workingColorSpace)},getPrimaries:function(e){return this.spaces[e].primaries},getTransfer:function(e){return e===Kr?$r:this.spaces[e].transfer},getToneMappingMode:function(e){return this.spaces[e].outputColorSpaceConfig.toneMappingMode||"standard"},getLuminanceCoefficients:function(e,t=this.workingColorSpace){return e.fromArray(this.spaces[t].luminanceCoefficients)},define:function(e){Object.assign(this.spaces,e)},_getMatrix:function(e,t,n){return e.copy(this.spaces[t].toXYZ).multiply(this.spaces[n].fromXYZ)},_getDrawingBufferColorSpace:function(e){return this.spaces[e].outputColorSpaceConfig.drawingBufferColorSpace},_getUnpackColorSpace:function(e=this.workingColorSpace){return this.spaces[e].workingColorSpaceConfig.unpackColorSpace},fromWorkingColorSpace:function(t,n){return js("THREE.ColorManagement: .fromWorkingColorSpace() has been renamed to .workingToColorSpace()."),e.workingToColorSpace(t,n)},toWorkingColorSpace:function(t,n){return js("THREE.ColorManagement: .toWorkingColorSpace() has been renamed to .colorSpaceToWorking()."),e.colorSpaceToWorking(t,n)}},t=[.64,.33,.3,.6,.15,.06],n=[.2126,.7152,.0722],i=[.3127,.329];return e.define({[_r]:{primaries:t,whitePoint:i,transfer:$r,toXYZ:Os,fromXYZ:zs,luminanceCoefficients:n,workingColorSpaceConfig:{unpackColorSpace:qr},outputColorSpaceConfig:{drawingBufferColorSpace:qr}},[qr]:{primaries:t,whitePoint:i,transfer:es,toXYZ:Os,fromXYZ:zs,luminanceCoefficients:n,outputColorSpaceConfig:{drawingBufferColorSpace:qr}}}),e}const ks=Rs();function Fs(e){return e<.04045?.0773993808*e:Math.pow(.9478672986*e+.0521327014,2.4)}function Hs(e){return e<.0031308?12.92*e:1.055*Math.pow(e,.41666)-.055}let Us;class Xs{static getDataURL(e,t="image/png"){if(/^data:/i.test(e.src))return e.src;if("undefined"==typeof HTMLCanvasElement)return e.src;let n;if(e instanceof HTMLCanvasElement)n=e;else{void 0===Us&&(Us=Ds("canvas")),Us.width=e.width,Us.height=e.height;const t=Us.getContext("2d");e instanceof ImageData?t.putImageData(e,0,0):t.drawImage(e,0,0,e.width,e.height),n=Us}return n.toDataURL(t)}static sRGBToLinear(e){if("undefined"!=typeof HTMLImageElement&&e instanceof HTMLImageElement||"undefined"!=typeof HTMLCanvasElement&&e instanceof HTMLCanvasElement||"undefined"!=typeof ImageBitmap&&e instanceof ImageBitmap){const t=Ds("canvas");t.width=e.width,t.height=e.height;const n=t.getContext("2d");n.drawImage(e,0,0,e.width,e.height);const i=n.getImageData(0,0,e.width,e.height),r=i.data;for(let e=0;e<r.length;e++)r[e]=255*Fs(r[e]/255);return n.putImageData(i,0,0),t}if(e.data){const t=e.data.slice(0);for(let e=0;e<t.length;e++)t instanceof Uint8Array||t instanceof Uint8ClampedArray?t[e]=Math.floor(255*Fs(t[e]/255)):t[e]=Fs(t[e]);return{data:t,width:e.width,height:e.height}}return console.warn("THREE.ImageUtils.sRGBToLinear(): Unsupported image type. No color space conversion applied."),e}}let Gs=0;class Vs{constructor(e=null){this.isSource=!0,Object.defineProperty(this,"id",{value:Gs++}),this.uuid=ms(),this.data=e,this.dataReady=!0,this.version=0}getSize(e){const t=this.data;return"undefined"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement?e.set(t.videoWidth,t.videoHeight,0):t instanceof VideoFrame?e.set(t.displayHeight,t.displayWidth,0):null!==t?e.set(t.width,t.height,t.depth||0):e.set(0,0,0),e}set needsUpdate(e){!0===e&&this.version++}toJSON(e){const t=void 0===e||"string"==typeof e;if(!t&&void 0!==e.images[this.uuid])return e.images[this.uuid];const n={uuid:this.uuid,url:""},i=this.data;if(null!==i){let e;if(Array.isArray(i)){e=[];for(let t=0,n=i.length;t<n;t++)i[t].isDataTexture?e.push(Ws(i[t].image)):e.push(Ws(i[t]))}else e=Ws(i);n.url=e}return t||(e.images[this.uuid]=n),n}}function Ws(e){return"undefined"!=typeof HTMLImageElement&&e instanceof HTMLImageElement||"undefined"!=typeof HTMLCanvasElement&&e instanceof HTMLCanvasElement||"undefined"!=typeof ImageBitmap&&e instanceof ImageBitmap?Xs.getDataURL(e):e.data?{data:Array.from(e.data),width:e.width,height:e.height,type:e.data.constructor.name}:(console.warn("THREE.Texture: Unable to serialize Texture."),{})}let Qs=0;const Zs=new Es;class Ys extends ds{constructor(e=Ys.DEFAULT_IMAGE,t=Ys.DEFAULT_MAPPING,n=1001,i=1001,r=1006,s=1008,o=1023,a=1009,l=Ys.DEFAULT_ANISOTROPY,u=""){super(),this.isTexture=!0,Object.defineProperty(this,"id",{value:Qs++}),this.uuid=ms(),this.name="",this.source=new Vs(e),this.mipmaps=[],this.mapping=t,this.channel=0,this.wrapS=n,this.wrapT=i,this.magFilter=r,this.minFilter=s,this.anisotropy=l,this.format=o,this.internalFormat=null,this.type=a,this.offset=new Cs(0,0),this.repeat=new Cs(1,1),this.center=new Cs(0,0),this.rotation=0,this.matrixAutoUpdate=!0,this.matrix=new Ps,this.generateMipmaps=!0,this.premultiplyAlpha=!1,this.flipY=!0,this.unpackAlignment=4,this.colorSpace=u,this.userData={},this.updateRanges=[],this.version=0,this.onUpdate=null,this.renderTarget=null,this.isRenderTargetTexture=!1,this.isArrayTexture=!!(e&&e.depth&&e.depth>1),this.pmremVersion=0}get width(){return this.source.getSize(Zs).x}get height(){return this.source.getSize(Zs).y}get depth(){return this.source.getSize(Zs).z}get image(){return this.source.data}set image(e=null){this.source.data=e}updateMatrix(){this.matrix.setUvTransform(this.offset.x,this.offset.y,this.repeat.x,this.repeat.y,this.rotation,this.center.x,this.center.y)}addUpdateRange(e,t){this.updateRanges.push({start:e,count:t})}clearUpdateRanges(){this.updateRanges.length=0}clone(){return(new this.constructor).copy(this)}copy(e){return this.name=e.name,this.source=e.source,this.mipmaps=e.mipmaps.slice(0),this.mapping=e.mapping,this.channel=e.channel,this.wrapS=e.wrapS,this.wrapT=e.wrapT,this.magFilter=e.magFilter,this.minFilter=e.minFilter,this.anisotropy=e.anisotropy,this.format=e.format,this.internalFormat=e.internalFormat,this.type=e.type,this.offset.copy(e.offset),this.repeat.copy(e.repeat),this.center.copy(e.center),this.rotation=e.rotation,this.matrixAutoUpdate=e.matrixAutoUpdate,this.matrix.copy(e.matrix),this.generateMipmaps=e.generateMipmaps,this.premultiplyAlpha=e.premultiplyAlpha,this.flipY=e.flipY,this.unpackAlignment=e.unpackAlignment,this.colorSpace=e.colorSpace,this.renderTarget=e.renderTarget,this.isRenderTargetTexture=e.isRenderTargetTexture,this.isArrayTexture=e.isArrayTexture,this.userData=JSON.parse(JSON.stringify(e.userData)),this.needsUpdate=!0,this}setValues(e){for(const t in e){const n=e[t];if(void 0===n){console.warn(`THREE.Texture.setValues(): parameter '${t}' has value of undefined.`);continue}const i=this[t];void 0!==i?i&&n&&i.isVector2&&n.isVector2||i&&n&&i.isVector3&&n.isVector3||i&&n&&i.isMatrix3&&n.isMatrix3?i.copy(n):this[t]=n:console.warn(`THREE.Texture.setValues(): property '${t}' does not exist.`)}}toJSON(e){const t=void 0===e||"string"==typeof e;if(!t&&void 0!==e.textures[this.uuid])return e.textures[this.uuid];const n={metadata:{version:4.7,type:"Texture",generator:"Texture.toJSON"},uuid:this.uuid,name:this.name,image:this.source.toJSON(e).uuid,mapping:this.mapping,channel:this.channel,repeat:[this.repeat.x,this.repeat.y],offset:[this.offset.x,this.offset.y],center:[this.center.x,this.center.y],rotation:this.rotation,wrap:[this.wrapS,this.wrapT],format:this.format,internalFormat:this.internalFormat,type:this.type,colorSpace:this.colorSpace,minFilter:this.minFilter,magFilter:this.magFilter,anisotropy:this.anisotropy,flipY:this.flipY,generateMipmaps:this.generateMipmaps,premultiplyAlpha:this.premultiplyAlpha,unpackAlignment:this.unpackAlignment};return Object.keys(this.userData).length>0&&(n.userData=this.userData),t||(e.textures[this.uuid]=n),n}dispose(){this.dispatchEvent({type:"dispose"})}transformUv(e){if(this.mapping!==Pi)return e;if(e.applyMatrix3(this.matrix),e.x<0||e.x>1)switch(this.wrapS){case ji:e.x=e.x-Math.floor(e.x);break;case Oi:e.x=e.x<0?0:1;break;case zi:1===Math.abs(Math.floor(e.x)%2)?e.x=Math.ceil(e.x)-e.x:e.x=e.x-Math.floor(e.x)}if(e.y<0||e.y>1)switch(this.wrapT){case ji:e.y=e.y-Math.floor(e.y);break;case Oi:e.y=e.y<0?0:1;break;case zi:1===Math.abs(Math.floor(e.y)%2)?e.y=Math.ceil(e.y)-e.y:e.y=e.y-Math.floor(e.y)}return this.flipY&&(e.y=1-e.y),e}set needsUpdate(e){!0===e&&(this.version++,this.source.needsUpdate=!0)}set needsPMREMUpdate(e){!0===e&&this.pmremVersion++}}Ys.DEFAULT_IMAGE=null,Ys.DEFAULT_MAPPING=Pi,Ys.DEFAULT_ANISOTROPY=1;class Js{constructor(e=0,t=0,n=0,i=1){Js.prototype.isVector4=!0,this.x=e,this.y=t,this.z=n,this.w=i}get width(){return this.z}set width(e){this.z=e}get height(){return this.w}set height(e){this.w=e}set(e,t,n,i){return this.x=e,this.y=t,this.z=n,this.w=i,this}setScalar(e){return this.x=e,this.y=e,this.z=e,this.w=e,this}setX(e){return this.x=e,this}setY(e){return this.y=e,this}setZ(e){return this.z=e,this}setW(e){return this.w=e,this}setComponent(e,t){switch(e){case 0:this.x=t;break;case 1:this.y=t;break;case 2:this.z=t;break;case 3:this.w=t;break;default:throw new Error("index is out of range: "+e)}return this}getComponent(e){switch(e){case 0:return this.x;case 1:return this.y;case 2:return this.z;case 3:return this.w;default:throw new Error("index is out of range: "+e)}}clone(){return new this.constructor(this.x,this.y,this.z,this.w)}copy(e){return this.x=e.x,this.y=e.y,this.z=e.z,this.w=void 0!==e.w?e.w:1,this}add(e){return this.x+=e.x,this.y+=e.y,this.z+=e.z,this.w+=e.w,this}addScalar(e){return this.x+=e,this.y+=e,this.z+=e,this.w+=e,this}addVectors(e,t){return this.x=e.x+t.x,this.y=e.y+t.y,this.z=e.z+t.z,this.w=e.w+t.w,this}addScaledVector(e,t){return this.x+=e.x*t,this.y+=e.y*t,this.z+=e.z*t,this.w+=e.w*t,this}sub(e){return this.x-=e.x,this.y-=e.y,this.z-=e.z,this.w-=e.w,this}subScalar(e){return this.x-=e,this.y-=e,this.z-=e,this.w-=e,this}subVectors(e,t){return this.x=e.x-t.x,this.y=e.y-t.y,this.z=e.z-t.z,this.w=e.w-t.w,this}multiply(e){return this.x*=e.x,this.y*=e.y,this.z*=e.z,this.w*=e.w,this}multiplyScalar(e){return this.x*=e,this.y*=e,this.z*=e,this.w*=e,this}applyMatrix4(e){const t=this.x,n=this.y,i=this.z,r=this.w,s=e.elements;return this.x=s[0]*t+s[4]*n+s[8]*i+s[12]*r,this.y=s[1]*t+s[5]*n+s[9]*i+s[13]*r,this.z=s[2]*t+s[6]*n+s[10]*i+s[14]*r,this.w=s[3]*t+s[7]*n+s[11]*i+s[15]*r,this}divide(e){return this.x/=e.x,this.y/=e.y,this.z/=e.z,this.w/=e.w,this}divideScalar(e){return this.multiplyScalar(1/e)}setAxisAngleFromQuaternion(e){this.w=2*Math.acos(e.w);const t=Math.sqrt(1-e.w*e.w);return t<1e-4?(this.x=1,this.y=0,this.z=0):(this.x=e.x/t,this.y=e.y/t,this.z=e.z/t),this}setAxisAngleFromRotationMatrix(e){let t,n,i,r;const s=.01,o=.1,a=e.elements,l=a[0],u=a[4],c=a[8],d=a[1],h=a[5],f=a[9],p=a[2],g=a[6],m=a[10];if(Math.abs(u-d)<s&&Math.abs(c-p)<s&&Math.abs(f-g)<s){if(Math.abs(u+d)<o&&Math.abs(c+p)<o&&Math.abs(f+g)<o&&Math.abs(l+h+m-3)<o)return this.set(1,0,0,0),this;t=Math.PI;const e=(l+1)/2,a=(h+1)/2,v=(m+1)/2,A=(u+d)/4,x=(c+p)/4,y=(f+g)/4;return e>a&&e>v?e<s?(n=0,i=.707106781,r=.707106781):(n=Math.sqrt(e),i=A/n,r=x/n):a>v?a<s?(n=.707106781,i=0,r=.707106781):(i=Math.sqrt(a),n=A/i,r=y/i):v<s?(n=.707106781,i=.707106781,r=0):(r=Math.sqrt(v),n=x/r,i=y/r),this.set(n,i,r,t),this}let v=Math.sqrt((g-f)*(g-f)+(c-p)*(c-p)+(d-u)*(d-u));return Math.abs(v)<.001&&(v=1),this.x=(g-f)/v,this.y=(c-p)/v,this.z=(d-u)/v,this.w=Math.acos((l+h+m-1)/2),this}setFromMatrixPosition(e){const t=e.elements;return this.x=t[12],this.y=t[13],this.z=t[14],this.w=t[15],this}min(e){return this.x=Math.min(this.x,e.x),this.y=Math.min(this.y,e.y),this.z=Math.min(this.z,e.z),this.w=Math.min(this.w,e.w),this}max(e){return this.x=Math.max(this.x,e.x),this.y=Math.max(this.y,e.y),this.z=Math.max(this.z,e.z),this.w=Math.max(this.w,e.w),this}clamp(e,t){return this.x=vs(this.x,e.x,t.x),this.y=vs(this.y,e.y,t.y),this.z=vs(this.z,e.z,t.z),this.w=vs(this.w,e.w,t.w),this}clampScalar(e,t){return this.x=vs(this.x,e,t),this.y=vs(this.y,e,t),this.z=vs(this.z,e,t),this.w=vs(this.w,e,t),this}clampLength(e,t){const n=this.length();return this.divideScalar(n||1).multiplyScalar(vs(n,e,t))}floor(){return this.x=Math.floor(this.x),this.y=Math.floor(this.y),this.z=Math.floor(this.z),this.w=Math.floor(this.w),this}ceil(){return this.x=Math.ceil(this.x),this.y=Math.ceil(this.y),this.z=Math.ceil(this.z),this.w=Math.ceil(this.w),this}round(){return this.x=Math.round(this.x),this.y=Math.round(this.y),this.z=Math.round(this.z),this.w=Math.round(this.w),this}roundToZero(){return this.x=Math.trunc(this.x),this.y=Math.trunc(this.y),this.z=Math.trunc(this.z),this.w=Math.trunc(this.w),this}negate(){return this.x=-this.x,this.y=-this.y,this.z=-this.z,this.w=-this.w,this}dot(e){return this.x*e.x+this.y*e.y+this.z*e.z+this.w*e.w}lengthSq(){return this.x*this.x+this.y*this.y+this.z*this.z+this.w*this.w}length(){return Math.sqrt(this.x*this.x+this.y*this.y+this.z*this.z+this.w*this.w)}manhattanLength(){return Math.abs(this.x)+Math.abs(this.y)+Math.abs(this.z)+Math.abs(this.w)}normalize(){return this.divideScalar(this.length()||1)}setLength(e){return this.normalize().multiplyScalar(e)}lerp(e,t){return this.x+=(e.x-this.x)*t,this.y+=(e.y-this.y)*t,this.z+=(e.z-this.z)*t,this.w+=(e.w-this.w)*t,this}lerpVectors(e,t,n){return this.x=e.x+(t.x-e.x)*n,this.y=e.y+(t.y-e.y)*n,this.z=e.z+(t.z-e.z)*n,this.w=e.w+(t.w-e.w)*n,this}equals(e){return e.x===this.x&&e.y===this.y&&e.z===this.z&&e.w===this.w}fromArray(e,t=0){return this.x=e[t],this.y=e[t+1],this.z=e[t+2],this.w=e[t+3],this}toArray(e=[],t=0){return e[t]=this.x,e[t+1]=this.y,e[t+2]=this.z,e[t+3]=this.w,e}fromBufferAttribute(e,t){return this.x=e.getX(t),this.y=e.getY(t),this.z=e.getZ(t),this.w=e.getW(t),this}random(){return this.x=Math.random(),this.y=Math.random(),this.z=Math.random(),this.w=Math.random(),this}*[Symbol.iterator](){yield this.x,yield this.y,yield this.z,yield this.w}}class Ks extends ds{constructor(e=1,t=1,n={}){super(),n=Object.assign({generateMipmaps:!1,internalFormat:null,minFilter:Hi,depthBuffer:!0,stencilBuffer:!1,resolveDepthBuffer:!0,resolveStencilBuffer:!0,depthTexture:null,samples:0,count:1,depth:1,multiview:!1},n),this.isRenderTarget=!0,this.width=e,this.height=t,this.depth=n.depth,this.scissor=new Js(0,0,e,t),this.scissorTest=!1,this.viewport=new Js(0,0,e,t);const i={width:e,height:t,depth:n.depth},r=new Ys(i);this.textures=[];const s=n.count;for(let e=0;e<s;e++)this.textures[e]=r.clone(),this.textures[e].isRenderTargetTexture=!0,this.textures[e].renderTarget=this;this._setTextureOptions(n),this.depthBuffer=n.depthBuffer,this.stencilBuffer=n.stencilBuffer,this.resolveDepthBuffer=n.resolveDepthBuffer,this.resolveStencilBuffer=n.resolveStencilBuffer,this._depthTexture=null,this.depthTexture=n.depthTexture,this.samples=n.samples,this.multiview=n.multiview}_setTextureOptions(e={}){const t={minFilter:Hi,generateMipmaps:!1,flipY:!1,internalFormat:null};void 0!==e.mapping&&(t.mapping=e.mapping),void 0!==e.wrapS&&(t.wrapS=e.wrapS),void 0!==e.wrapT&&(t.wrapT=e.wrapT),void 0!==e.wrapR&&(t.wrapR=e.wrapR),void 0!==e.magFilter&&(t.magFilter=e.magFilter),void 0!==e.minFilter&&(t.minFilter=e.minFilter),void 0!==e.format&&(t.format=e.format),void 0!==e.type&&(t.type=e.type),void 0!==e.anisotropy&&(t.anisotropy=e.anisotropy),void 0!==e.colorSpace&&(t.colorSpace=e.colorSpace),void 0!==e.flipY&&(t.flipY=e.flipY),void 0!==e.generateMipmaps&&(t.generateMipmaps=e.generateMipmaps),void 0!==e.internalFormat&&(t.internalFormat=e.internalFormat);for(let e=0;e<this.textures.length;e++){this.textures[e].setValues(t)}}get texture(){return this.textures[0]}set texture(e){this.textures[0]=e}set depthTexture(e){null!==this._depthTexture&&(this._depthTexture.renderTarget=null),null!==e&&(e.renderTarget=this),this._depthTexture=e}get depthTexture(){return this._depthTexture}setSize(e,t,n=1){if(this.width!==e||this.height!==t||this.depth!==n){this.width=e,this.height=t,this.depth=n;for(let i=0,r=this.textures.length;i<r;i++)this.textures[i].image.width=e,this.textures[i].image.height=t,this.textures[i].image.depth=n,this.textures[i].isArrayTexture=this.textures[i].image.depth>1;this.dispose()}this.viewport.set(0,0,e,t),this.scissor.set(0,0,e,t)}clone(){return(new this.constructor).copy(this)}copy(e){this.width=e.width,this.height=e.height,this.depth=e.depth,this.scissor.copy(e.scissor),this.scissorTest=e.scissorTest,this.viewport.copy(e.viewport),this.textures.length=0;for(let t=0,n=e.textures.length;t<n;t++){this.textures[t]=e.textures[t].clone(),this.textures[t].isRenderTargetTexture=!0,this.textures[t].renderTarget=this;const n=Object.assign({},e.textures[t].image);this.textures[t].source=new Vs(n)}return this.depthBuffer=e.depthBuffer,this.stencilBuffer=e.stencilBuffer,this.resolveDepthBuffer=e.resolveDepthBuffer,this.resolveStencilBuffer=e.resolveStencilBuffer,null!==e.depthTexture&&(this.depthTexture=e.depthTexture.clone()),this.samples=e.samples,this}dispose(){this.dispatchEvent({type:"dispose"})}}class qs extends Ks{constructor(e=1,t=1,n={}){super(e,t,n),this.isWebGLRenderTarget=!0}}class _s extends Ys{constructor(e=null,t=1,n=1,i=1){super(null),this.isDataArrayTexture=!0,this.image={data:e,width:t,height:n,depth:i},this.magFilter=Ri,this.minFilter=Ri,this.wrapR=Oi,this.generateMipmaps=!1,this.flipY=!1,this.unpackAlignment=1,this.layerUpdates=new Set}addLayerUpdate(e){this.layerUpdates.add(e)}clearLayerUpdates(){this.layerUpdates.clear()}}class $s extends Ys{constructor(e=null,t=1,n=1,i=1){super(null),this.isData3DTexture=!0,this.image={data:e,width:t,height:n,depth:i},this.magFilter=Ri,this.minFilter=Ri,this.wrapR=Oi,this.generateMipmaps=!1,this.flipY=!1,this.unpackAlignment=1}}class eo{constructor(e=new Es(1/0,1/0,1/0),t=new Es(-1/0,-1/0,-1/0)){this.isBox3=!0,this.min=e,this.max=t}set(e,t){return this.min.copy(e),this.max.copy(t),this}setFromArray(e){this.makeEmpty();for(let t=0,n=e.length;t<n;t+=3)this.expandByPoint(no.fromArray(e,t));return this}setFromBufferAttribute(e){this.makeEmpty();for(let t=0,n=e.count;t<n;t++)this.expandByPoint(no.fromBufferAttribute(e,t));return this}setFromPoints(e){this.makeEmpty();for(let t=0,n=e.length;t<n;t++)this.expandByPoint(e[t]);return this}setFromCenterAndSize(e,t){const n=no.copy(t).multiplyScalar(.5);return this.min.copy(e).sub(n),this.max.copy(e).add(n),this}setFromObject(e,t=!1){return this.makeEmpty(),this.expandByObject(e,t)}clone(){return(new this.constructor).copy(this)}copy(e){return this.min.copy(e.min),this.max.copy(e.max),this}makeEmpty(){return this.min.x=this.min.y=this.min.z=1/0,this.max.x=this.max.y=this.max.z=-1/0,this}isEmpty(){return this.max.x<this.min.x||this.max.y<this.min.y||this.max.z<this.min.z}getCenter(e){return this.isEmpty()?e.set(0,0,0):e.addVectors(this.min,this.max).multiplyScalar(.5)}getSize(e){return this.isEmpty()?e.set(0,0,0):e.subVectors(this.max,this.min)}expandByPoint(e){return this.min.min(e),this.max.max(e),this}expandByVector(e){return this.min.sub(e),this.max.add(e),this}expandByScalar(e){return this.min.addScalar(-e),this.max.addScalar(e),this}expandByObject(e,t=!1){e.updateWorldMatrix(!1,!1);const n=e.geometry;if(void 0!==n){const i=n.getAttribute("position");if(!0===t&&void 0!==i&&!0!==e.isInstancedMesh)for(let t=0,n=i.count;t<n;t++)!0===e.isMesh?e.getVertexPosition(t,no):no.fromBufferAttribute(i,t),no.applyMatrix4(e.matrixWorld),this.expandByPoint(no);else void 0!==e.boundingBox?(null===e.boundingBox&&e.computeBoundingBox(),io.copy(e.boundingBox)):(null===n.boundingBox&&n.computeBoundingBox(),io.copy(n.boundingBox)),io.applyMatrix4(e.matrixWorld),this.union(io)}const i=e.children;for(let e=0,n=i.length;e<n;e++)this.expandByObject(i[e],t);return this}containsPoint(e){return e.x>=this.min.x&&e.x<=this.max.x&&e.y>=this.min.y&&e.y<=this.max.y&&e.z>=this.min.z&&e.z<=this.max.z}containsBox(e){return this.min.x<=e.min.x&&e.max.x<=this.max.x&&this.min.y<=e.min.y&&e.max.y<=this.max.y&&this.min.z<=e.min.z&&e.max.z<=this.max.z}getParameter(e,t){return t.set((e.x-this.min.x)/(this.max.x-this.min.x),(e.y-this.min.y)/(this.max.y-this.min.y),(e.z-this.min.z)/(this.max.z-this.min.z))}intersectsBox(e){return e.max.x>=this.min.x&&e.min.x<=this.max.x&&e.max.y>=this.min.y&&e.min.y<=this.max.y&&e.max.z>=this.min.z&&e.min.z<=this.max.z}intersectsSphere(e){return this.clampPoint(e.center,no),no.distanceToSquared(e.center)<=e.radius*e.radius}intersectsPlane(e){let t,n;return e.normal.x>0?(t=e.normal.x*this.min.x,n=e.normal.x*this.max.x):(t=e.normal.x*this.max.x,n=e.normal.x*this.min.x),e.normal.y>0?(t+=e.normal.y*this.min.y,n+=e.normal.y*this.max.y):(t+=e.normal.y*this.max.y,n+=e.normal.y*this.min.y),e.normal.z>0?(t+=e.normal.z*this.min.z,n+=e.normal.z*this.max.z):(t+=e.normal.z*this.max.z,n+=e.normal.z*this.min.z),t<=-e.constant&&n>=-e.constant}intersectsTriangle(e){if(this.isEmpty())return!1;this.getCenter(co),ho.subVectors(this.max,co),ro.subVectors(e.a,co),so.subVectors(e.b,co),oo.subVectors(e.c,co),ao.subVectors(so,ro),lo.subVectors(oo,so),uo.subVectors(ro,oo);let t=[0,-ao.z,ao.y,0,-lo.z,lo.y,0,-uo.z,uo.y,ao.z,0,-ao.x,lo.z,0,-lo.x,uo.z,0,-uo.x,-ao.y,ao.x,0,-lo.y,lo.x,0,-uo.y,uo.x,0];return!!go(t,ro,so,oo,ho)&&(t=[1,0,0,0,1,0,0,0,1],!!go(t,ro,so,oo,ho)&&(fo.crossVectors(ao,lo),t=[fo.x,fo.y,fo.z],go(t,ro,so,oo,ho)))}clampPoint(e,t){return t.copy(e).clamp(this.min,this.max)}distanceToPoint(e){return this.clampPoint(e,no).distanceTo(e)}getBoundingSphere(e){return this.isEmpty()?e.makeEmpty():(this.getCenter(e.center),e.radius=.5*this.getSize(no).length()),e}intersect(e){return this.min.max(e.min),this.max.min(e.max),this.isEmpty()&&this.makeEmpty(),this}union(e){return this.min.min(e.min),this.max.max(e.max),this}applyMatrix4(e){return this.isEmpty()||(to[0].set(this.min.x,this.min.y,this.min.z).applyMatrix4(e),to[1].set(this.min.x,this.min.y,this.max.z).applyMatrix4(e),to[2].set(this.min.x,this.max.y,this.min.z).applyMatrix4(e),to[3].set(this.min.x,this.max.y,this.max.z).applyMatrix4(e),to[4].set(this.max.x,this.min.y,this.min.z).applyMatrix4(e),to[5].set(this.max.x,this.min.y,this.max.z).applyMatrix4(e),to[6].set(this.max.x,this.max.y,this.min.z).applyMatrix4(e),to[7].set(this.max.x,this.max.y,this.max.z).applyMatrix4(e),this.setFromPoints(to)),this}translate(e){return this.min.add(e),this.max.add(e),this}equals(e){return e.min.equals(this.min)&&e.max.equals(this.max)}toJSON(){return{min:this.min.toArray(),max:this.max.toArray()}}fromJSON(e){return this.min.fromArray(e.min),this.max.fromArray(e.max),this}}const to=[new Es,new Es,new Es,new Es,new Es,new Es,new Es,new Es],no=new Es,io=new eo,ro=new Es,so=new Es,oo=new Es,ao=new Es,lo=new Es,uo=new Es,co=new Es,ho=new Es,fo=new Es,po=new Es;function go(e,t,n,i,r){for(let s=0,o=e.length-3;s<=o;s+=3){po.fromArray(e,s);const o=r.x*Math.abs(po.x)+r.y*Math.abs(po.y)+r.z*Math.abs(po.z),a=t.dot(po),l=n.dot(po),u=i.dot(po);if(Math.max(-Math.max(a,l,u),Math.min(a,l,u))>o)return!1}return!0}const mo=new eo,vo=new Es,Ao=new Es;class xo{constructor(e=new Es,t=-1){this.isSphere=!0,this.center=e,this.radius=t}set(e,t){return this.center.copy(e),this.radius=t,this}setFromPoints(e,t){const n=this.center;void 0!==t?n.copy(t):mo.setFromPoints(e).getCenter(n);let i=0;for(let t=0,r=e.length;t<r;t++)i=Math.max(i,n.distanceToSquared(e[t]));return this.radius=Math.sqrt(i),this}copy(e){return this.center.copy(e.center),this.radius=e.radius,this}isEmpty(){return this.radius<0}makeEmpty(){return this.center.set(0,0,0),this.radius=-1,this}containsPoint(e){return e.distanceToSquared(this.center)<=this.radius*this.radius}distanceToPoint(e){return e.distanceTo(this.center)-this.radius}intersectsSphere(e){const t=this.radius+e.radius;return e.center.distanceToSquared(this.center)<=t*t}intersectsBox(e){return e.intersectsSphere(this)}intersectsPlane(e){return Math.abs(e.distanceToPoint(this.center))<=this.radius}clampPoint(e,t){const n=this.center.distanceToSquared(e);return t.copy(e),n>this.radius*this.radius&&(t.sub(this.center).normalize(),t.multiplyScalar(this.radius).add(this.center)),t}getBoundingBox(e){return this.isEmpty()?(e.makeEmpty(),e):(e.set(this.center,this.center),e.expandByScalar(this.radius),e)}applyMatrix4(e){return this.center.applyMatrix4(e),this.radius=this.radius*e.getMaxScaleOnAxis(),this}translate(e){return this.center.add(e),this}expandByPoint(e){if(this.isEmpty())return this.center.copy(e),this.radius=0,this;vo.subVectors(e,this.center);const t=vo.lengthSq();if(t>this.radius*this.radius){const e=Math.sqrt(t),n=.5*(e-this.radius);this.center.addScaledVector(vo,n/e),this.radius+=n}return this}union(e){return e.isEmpty()?this:this.isEmpty()?(this.copy(e),this):(!0===this.center.equals(e.center)?this.radius=Math.max(this.radius,e.radius):(Ao.subVectors(e.center,this.center).setLength(e.radius),this.expandByPoint(vo.copy(e.center).add(Ao)),this.expandByPoint(vo.copy(e.center).sub(Ao))),this)}equals(e){return e.center.equals(this.center)&&e.radius===this.radius}clone(){return(new this.constructor).copy(this)}toJSON(){return{radius:this.radius,center:this.center.toArray()}}fromJSON(e){return this.radius=e.radius,this.center.fromArray(e.center),this}}const yo=new Es,bo=new Es,wo=new Es,Co=new Es,Mo=new Es,Eo=new Es,To=new Es;class So{constructor(e=new Es,t=new Es(0,0,-1)){this.origin=e,this.direction=t}set(e,t){return this.origin.copy(e),this.direction.copy(t),this}copy(e){return this.origin.copy(e.origin),this.direction.copy(e.direction),this}at(e,t){return t.copy(this.origin).addScaledVector(this.direction,e)}lookAt(e){return this.direction.copy(e).sub(this.origin).normalize(),this}recast(e){return this.origin.copy(this.at(e,yo)),this}closestPointToPoint(e,t){t.subVectors(e,this.origin);const n=t.dot(this.direction);return n<0?t.copy(this.origin):t.copy(this.origin).addScaledVector(this.direction,n)}distanceToPoint(e){return Math.sqrt(this.distanceSqToPoint(e))}distanceSqToPoint(e){const t=yo.subVectors(e,this.origin).dot(this.direction);return t<0?this.origin.distanceToSquared(e):(yo.copy(this.origin).addScaledVector(this.direction,t),yo.distanceToSquared(e))}distanceSqToSegment(e,t,n,i){bo.copy(e).add(t).multiplyScalar(.5),wo.copy(t).sub(e).normalize(),Co.copy(this.origin).sub(bo);const r=.5*e.distanceTo(t),s=-this.direction.dot(wo),o=Co.dot(this.direction),a=-Co.dot(wo),l=Co.lengthSq(),u=Math.abs(1-s*s);let c,d,h,f;if(u>0)if(c=s*a-o,d=s*o-a,f=r*u,c>=0)if(d>=-f)if(d<=f){const e=1/u;c*=e,d*=e,h=c*(c+s*d+2*o)+d*(s*c+d+2*a)+l}else d=r,c=Math.max(0,-(s*d+o)),h=-c*c+d*(d+2*a)+l;else d=-r,c=Math.max(0,-(s*d+o)),h=-c*c+d*(d+2*a)+l;else d<=-f?(c=Math.max(0,-(-s*r+o)),d=c>0?-r:Math.min(Math.max(-r,-a),r),h=-c*c+d*(d+2*a)+l):d<=f?(c=0,d=Math.min(Math.max(-r,-a),r),h=d*(d+2*a)+l):(c=Math.max(0,-(s*r+o)),d=c>0?r:Math.min(Math.max(-r,-a),r),h=-c*c+d*(d+2*a)+l);else d=s>0?-r:r,c=Math.max(0,-(s*d+o)),h=-c*c+d*(d+2*a)+l;return n&&n.copy(this.origin).addScaledVector(this.direction,c),i&&i.copy(bo).addScaledVector(wo,d),h}intersectSphere(e,t){yo.subVectors(e.center,this.origin);const n=yo.dot(this.direction),i=yo.dot(yo)-n*n,r=e.radius*e.radius;if(i>r)return null;const s=Math.sqrt(r-i),o=n-s,a=n+s;return a<0?null:o<0?this.at(a,t):this.at(o,t)}intersectsSphere(e){return!(e.radius<0)&&this.distanceSqToPoint(e.center)<=e.radius*e.radius}distanceToPlane(e){const t=e.normal.dot(this.direction);if(0===t)return 0===e.distanceToPoint(this.origin)?0:null;const n=-(this.origin.dot(e.normal)+e.constant)/t;return n>=0?n:null}intersectPlane(e,t){const n=this.distanceToPlane(e);return null===n?null:this.at(n,t)}intersectsPlane(e){const t=e.distanceToPoint(this.origin);if(0===t)return!0;return e.normal.dot(this.direction)*t<0}intersectBox(e,t){let n,i,r,s,o,a;const l=1/this.direction.x,u=1/this.direction.y,c=1/this.direction.z,d=this.origin;return l>=0?(n=(e.min.x-d.x)*l,i=(e.max.x-d.x)*l):(n=(e.max.x-d.x)*l,i=(e.min.x-d.x)*l),u>=0?(r=(e.min.y-d.y)*u,s=(e.max.y-d.y)*u):(r=(e.max.y-d.y)*u,s=(e.min.y-d.y)*u),n>s||r>i?null:((r>n||isNaN(n))&&(n=r),(s<i||isNaN(i))&&(i=s),c>=0?(o=(e.min.z-d.z)*c,a=(e.max.z-d.z)*c):(o=(e.max.z-d.z)*c,a=(e.min.z-d.z)*c),n>a||o>i?null:((o>n||n!=n)&&(n=o),(a<i||i!=i)&&(i=a),i<0?null:this.at(n>=0?n:i,t)))}intersectsBox(e){return null!==this.intersectBox(e,yo)}intersectTriangle(e,t,n,i,r){Mo.subVectors(t,e),Eo.subVectors(n,e),To.crossVectors(Mo,Eo);let s,o=this.direction.dot(To);if(o>0){if(i)return null;s=1}else{if(!(o<0))return null;s=-1,o=-o}Co.subVectors(this.origin,e);const a=s*this.direction.dot(Eo.crossVectors(Co,Eo));if(a<0)return null;const l=s*this.direction.dot(Mo.cross(Co));if(l<0)return null;if(a+l>o)return null;const u=-s*Co.dot(To);return u<0?null:this.at(u/o,r)}applyMatrix4(e){return this.origin.applyMatrix4(e),this.direction.transformDirection(e),this}equals(e){return e.origin.equals(this.origin)&&e.direction.equals(this.direction)}clone(){return(new this.constructor).copy(this)}}class Po{constructor(e,t,n,i,r,s,o,a,l,u,c,d,h,f,p,g){Po.prototype.isMatrix4=!0,this.elements=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],void 0!==e&&this.set(e,t,n,i,r,s,o,a,l,u,c,d,h,f,p,g)}set(e,t,n,i,r,s,o,a,l,u,c,d,h,f,p,g){const m=this.elements;return m[0]=e,m[4]=t,m[8]=n,m[12]=i,m[1]=r,m[5]=s,m[9]=o,m[13]=a,m[2]=l,m[6]=u,m[10]=c,m[14]=d,m[3]=h,m[7]=f,m[11]=p,m[15]=g,this}identity(){return this.set(1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1),this}clone(){return(new Po).fromArray(this.elements)}copy(e){const t=this.elements,n=e.elements;return t[0]=n[0],t[1]=n[1],t[2]=n[2],t[3]=n[3],t[4]=n[4],t[5]=n[5],t[6]=n[6],t[7]=n[7],t[8]=n[8],t[9]=n[9],t[10]=n[10],t[11]=n[11],t[12]=n[12],t[13]=n[13],t[14]=n[14],t[15]=n[15],this}copyPosition(e){const t=this.elements,n=e.elements;return t[12]=n[12],t[13]=n[13],t[14]=n[14],this}setFromMatrix3(e){const t=e.elements;return this.set(t[0],t[3],t[6],0,t[1],t[4],t[7],0,t[2],t[5],t[8],0,0,0,0,1),this}extractBasis(e,t,n){return e.setFromMatrixColumn(this,0),t.setFromMatrixColumn(this,1),n.setFromMatrixColumn(this,2),this}makeBasis(e,t,n){return this.set(e.x,t.x,n.x,0,e.y,t.y,n.y,0,e.z,t.z,n.z,0,0,0,0,1),this}extractRotation(e){const t=this.elements,n=e.elements,i=1/No.setFromMatrixColumn(e,0).length(),r=1/No.setFromMatrixColumn(e,1).length(),s=1/No.setFromMatrixColumn(e,2).length();return t[0]=n[0]*i,t[1]=n[1]*i,t[2]=n[2]*i,t[3]=0,t[4]=n[4]*r,t[5]=n[5]*r,t[6]=n[6]*r,t[7]=0,t[8]=n[8]*s,t[9]=n[9]*s,t[10]=n[10]*s,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,this}makeRotationFromEuler(e){const t=this.elements,n=e.x,i=e.y,r=e.z,s=Math.cos(n),o=Math.sin(n),a=Math.cos(i),l=Math.sin(i),u=Math.cos(r),c=Math.sin(r);if("XYZ"===e.order){const e=s*u,n=s*c,i=o*u,r=o*c;t[0]=a*u,t[4]=-a*c,t[8]=l,t[1]=n+i*l,t[5]=e-r*l,t[9]=-o*a,t[2]=r-e*l,t[6]=i+n*l,t[10]=s*a}else if("YXZ"===e.order){const e=a*u,n=a*c,i=l*u,r=l*c;t[0]=e+r*o,t[4]=i*o-n,t[8]=s*l,t[1]=s*c,t[5]=s*u,t[9]=-o,t[2]=n*o-i,t[6]=r+e*o,t[10]=s*a}else if("ZXY"===e.order){const e=a*u,n=a*c,i=l*u,r=l*c;t[0]=e-r*o,t[4]=-s*c,t[8]=i+n*o,t[1]=n+i*o,t[5]=s*u,t[9]=r-e*o,t[2]=-s*l,t[6]=o,t[10]=s*a}else if("ZYX"===e.order){const e=s*u,n=s*c,i=o*u,r=o*c;t[0]=a*u,t[4]=i*l-n,t[8]=e*l+r,t[1]=a*c,t[5]=r*l+e,t[9]=n*l-i,t[2]=-l,t[6]=o*a,t[10]=s*a}else if("YZX"===e.order){const e=s*a,n=s*l,i=o*a,r=o*l;t[0]=a*u,t[4]=r-e*c,t[8]=i*c+n,t[1]=c,t[5]=s*u,t[9]=-o*u,t[2]=-l*u,t[6]=n*c+i,t[10]=e-r*c}else if("XZY"===e.order){const e=s*a,n=s*l,i=o*a,r=o*l;t[0]=a*u,t[4]=-c,t[8]=l*u,t[1]=e*c+r,t[5]=s*u,t[9]=n*c-i,t[2]=i*c-n,t[6]=o*u,t[10]=r*c+e}return t[3]=0,t[7]=0,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,this}makeRotationFromQuaternion(e){return this.compose(Do,e,Io)}lookAt(e,t,n){const i=this.elements;return Oo.subVectors(e,t),0===Oo.lengthSq()&&(Oo.z=1),Oo.normalize(),Lo.crossVectors(n,Oo),0===Lo.lengthSq()&&(1===Math.abs(n.z)?Oo.x+=1e-4:Oo.z+=1e-4,Oo.normalize(),Lo.crossVectors(n,Oo)),Lo.normalize(),jo.crossVectors(Oo,Lo),i[0]=Lo.x,i[4]=jo.x,i[8]=Oo.x,i[1]=Lo.y,i[5]=jo.y,i[9]=Oo.y,i[2]=Lo.z,i[6]=jo.z,i[10]=Oo.z,this}multiply(e){return this.multiplyMatrices(this,e)}premultiply(e){return this.multiplyMatrices(e,this)}multiplyMatrices(e,t){const n=e.elements,i=t.elements,r=this.elements,s=n[0],o=n[4],a=n[8],l=n[12],u=n[1],c=n[5],d=n[9],h=n[13],f=n[2],p=n[6],g=n[10],m=n[14],v=n[3],A=n[7],x=n[11],y=n[15],b=i[0],w=i[4],C=i[8],M=i[12],E=i[1],T=i[5],S=i[9],P=i[13],N=i[2],B=i[6],D=i[10],I=i[14],L=i[3],j=i[7],O=i[11],z=i[15];return r[0]=s*b+o*E+a*N+l*L,r[4]=s*w+o*T+a*B+l*j,r[8]=s*C+o*S+a*D+l*O,r[12]=s*M+o*P+a*I+l*z,r[1]=u*b+c*E+d*N+h*L,r[5]=u*w+c*T+d*B+h*j,r[9]=u*C+c*S+d*D+h*O,r[13]=u*M+c*P+d*I+h*z,r[2]=f*b+p*E+g*N+m*L,r[6]=f*w+p*T+g*B+m*j,r[10]=f*C+p*S+g*D+m*O,r[14]=f*M+p*P+g*I+m*z,r[3]=v*b+A*E+x*N+y*L,r[7]=v*w+A*T+x*B+y*j,r[11]=v*C+A*S+x*D+y*O,r[15]=v*M+A*P+x*I+y*z,this}multiplyScalar(e){const t=this.elements;return t[0]*=e,t[4]*=e,t[8]*=e,t[12]*=e,t[1]*=e,t[5]*=e,t[9]*=e,t[13]*=e,t[2]*=e,t[6]*=e,t[10]*=e,t[14]*=e,t[3]*=e,t[7]*=e,t[11]*=e,t[15]*=e,this}determinant(){const e=this.elements,t=e[0],n=e[4],i=e[8],r=e[12],s=e[1],o=e[5],a=e[9],l=e[13],u=e[2],c=e[6],d=e[10],h=e[14];return e[3]*(+r*a*c-i*l*c-r*o*d+n*l*d+i*o*h-n*a*h)+e[7]*(+t*a*h-t*l*d+r*s*d-i*s*h+i*l*u-r*a*u)+e[11]*(+t*l*c-t*o*h-r*s*c+n*s*h+r*o*u-n*l*u)+e[15]*(-i*o*u-t*a*c+t*o*d+i*s*c-n*s*d+n*a*u)}transpose(){const e=this.elements;let t;return t=e[1],e[1]=e[4],e[4]=t,t=e[2],e[2]=e[8],e[8]=t,t=e[6],e[6]=e[9],e[9]=t,t=e[3],e[3]=e[12],e[12]=t,t=e[7],e[7]=e[13],e[13]=t,t=e[11],e[11]=e[14],e[14]=t,this}setPosition(e,t,n){const i=this.elements;return e.isVector3?(i[12]=e.x,i[13]=e.y,i[14]=e.z):(i[12]=e,i[13]=t,i[14]=n),this}invert(){const e=this.elements,t=e[0],n=e[1],i=e[2],r=e[3],s=e[4],o=e[5],a=e[6],l=e[7],u=e[8],c=e[9],d=e[10],h=e[11],f=e[12],p=e[13],g=e[14],m=e[15],v=c*g*l-p*d*l+p*a*h-o*g*h-c*a*m+o*d*m,A=f*d*l-u*g*l-f*a*h+s*g*h+u*a*m-s*d*m,x=u*p*l-f*c*l+f*o*h-s*p*h-u*o*m+s*c*m,y=f*c*a-u*p*a-f*o*d+s*p*d+u*o*g-s*c*g,b=t*v+n*A+i*x+r*y;if(0===b)return this.set(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0);const w=1/b;return e[0]=v*w,e[1]=(p*d*r-c*g*r-p*i*h+n*g*h+c*i*m-n*d*m)*w,e[2]=(o*g*r-p*a*r+p*i*l-n*g*l-o*i*m+n*a*m)*w,e[3]=(c*a*r-o*d*r-c*i*l+n*d*l+o*i*h-n*a*h)*w,e[4]=A*w,e[5]=(u*g*r-f*d*r+f*i*h-t*g*h-u*i*m+t*d*m)*w,e[6]=(f*a*r-s*g*r-f*i*l+t*g*l+s*i*m-t*a*m)*w,e[7]=(s*d*r-u*a*r+u*i*l-t*d*l-s*i*h+t*a*h)*w,e[8]=x*w,e[9]=(f*c*r-u*p*r-f*n*h+t*p*h+u*n*m-t*c*m)*w,e[10]=(s*p*r-f*o*r+f*n*l-t*p*l-s*n*m+t*o*m)*w,e[11]=(u*o*r-s*c*r-u*n*l+t*c*l+s*n*h-t*o*h)*w,e[12]=y*w,e[13]=(u*p*i-f*c*i+f*n*d-t*p*d-u*n*g+t*c*g)*w,e[14]=(f*o*i-s*p*i-f*n*a+t*p*a+s*n*g-t*o*g)*w,e[15]=(s*c*i-u*o*i+u*n*a-t*c*a-s*n*d+t*o*d)*w,this}scale(e){const t=this.elements,n=e.x,i=e.y,r=e.z;return t[0]*=n,t[4]*=i,t[8]*=r,t[1]*=n,t[5]*=i,t[9]*=r,t[2]*=n,t[6]*=i,t[10]*=r,t[3]*=n,t[7]*=i,t[11]*=r,this}getMaxScaleOnAxis(){const e=this.elements,t=e[0]*e[0]+e[1]*e[1]+e[2]*e[2],n=e[4]*e[4]+e[5]*e[5]+e[6]*e[6],i=e[8]*e[8]+e[9]*e[9]+e[10]*e[10];return Math.sqrt(Math.max(t,n,i))}makeTranslation(e,t,n){return e.isVector3?this.set(1,0,0,e.x,0,1,0,e.y,0,0,1,e.z,0,0,0,1):this.set(1,0,0,e,0,1,0,t,0,0,1,n,0,0,0,1),this}makeRotationX(e){const t=Math.cos(e),n=Math.sin(e);return this.set(1,0,0,0,0,t,-n,0,0,n,t,0,0,0,0,1),this}makeRotationY(e){const t=Math.cos(e),n=Math.sin(e);return this.set(t,0,n,0,0,1,0,0,-n,0,t,0,0,0,0,1),this}makeRotationZ(e){const t=Math.cos(e),n=Math.sin(e);return this.set(t,-n,0,0,n,t,0,0,0,0,1,0,0,0,0,1),this}makeRotationAxis(e,t){const n=Math.cos(t),i=Math.sin(t),r=1-n,s=e.x,o=e.y,a=e.z,l=r*s,u=r*o;return this.set(l*s+n,l*o-i*a,l*a+i*o,0,l*o+i*a,u*o+n,u*a-i*s,0,l*a-i*o,u*a+i*s,r*a*a+n,0,0,0,0,1),this}makeScale(e,t,n){return this.set(e,0,0,0,0,t,0,0,0,0,n,0,0,0,0,1),this}makeShear(e,t,n,i,r,s){return this.set(1,n,r,0,e,1,s,0,t,i,1,0,0,0,0,1),this}compose(e,t,n){const i=this.elements,r=t._x,s=t._y,o=t._z,a=t._w,l=r+r,u=s+s,c=o+o,d=r*l,h=r*u,f=r*c,p=s*u,g=s*c,m=o*c,v=a*l,A=a*u,x=a*c,y=n.x,b=n.y,w=n.z;return i[0]=(1-(p+m))*y,i[1]=(h+x)*y,i[2]=(f-A)*y,i[3]=0,i[4]=(h-x)*b,i[5]=(1-(d+m))*b,i[6]=(g+v)*b,i[7]=0,i[8]=(f+A)*w,i[9]=(g-v)*w,i[10]=(1-(d+p))*w,i[11]=0,i[12]=e.x,i[13]=e.y,i[14]=e.z,i[15]=1,this}decompose(e,t,n){const i=this.elements;let r=No.set(i[0],i[1],i[2]).length();const s=No.set(i[4],i[5],i[6]).length(),o=No.set(i[8],i[9],i[10]).length();this.determinant()<0&&(r=-r),e.x=i[12],e.y=i[13],e.z=i[14],Bo.copy(this);const a=1/r,l=1/s,u=1/o;return Bo.elements[0]*=a,Bo.elements[1]*=a,Bo.elements[2]*=a,Bo.elements[4]*=l,Bo.elements[5]*=l,Bo.elements[6]*=l,Bo.elements[8]*=u,Bo.elements[9]*=u,Bo.elements[10]*=u,t.setFromRotationMatrix(Bo),n.x=r,n.y=s,n.z=o,this}makePerspective(e,t,n,i,r,s,o=2e3,a=!1){const l=this.elements,u=2*r/(t-e),c=2*r/(n-i),d=(t+e)/(t-e),h=(n+i)/(n-i);let f,p;if(a)f=r/(s-r),p=s*r/(s-r);else if(o===as)f=-(s+r)/(s-r),p=-2*s*r/(s-r);else{if(o!==ls)throw new Error("THREE.Matrix4.makePerspective(): Invalid coordinate system: "+o);f=-s/(s-r),p=-s*r/(s-r)}return l[0]=u,l[4]=0,l[8]=d,l[12]=0,l[1]=0,l[5]=c,l[9]=h,l[13]=0,l[2]=0,l[6]=0,l[10]=f,l[14]=p,l[3]=0,l[7]=0,l[11]=-1,l[15]=0,this}makeOrthographic(e,t,n,i,r,s,o=2e3,a=!1){const l=this.elements,u=2/(t-e),c=2/(n-i),d=-(t+e)/(t-e),h=-(n+i)/(n-i);let f,p;if(a)f=1/(s-r),p=s/(s-r);else if(o===as)f=-2/(s-r),p=-(s+r)/(s-r);else{if(o!==ls)throw new Error("THREE.Matrix4.makeOrthographic(): Invalid coordinate system: "+o);f=-1/(s-r),p=-r/(s-r)}return l[0]=u,l[4]=0,l[8]=0,l[12]=d,l[1]=0,l[5]=c,l[9]=0,l[13]=h,l[2]=0,l[6]=0,l[10]=f,l[14]=p,l[3]=0,l[7]=0,l[11]=0,l[15]=1,this}equals(e){const t=this.elements,n=e.elements;for(let e=0;e<16;e++)if(t[e]!==n[e])return!1;return!0}fromArray(e,t=0){for(let n=0;n<16;n++)this.elements[n]=e[n+t];return this}toArray(e=[],t=0){const n=this.elements;return e[t]=n[0],e[t+1]=n[1],e[t+2]=n[2],e[t+3]=n[3],e[t+4]=n[4],e[t+5]=n[5],e[t+6]=n[6],e[t+7]=n[7],e[t+8]=n[8],e[t+9]=n[9],e[t+10]=n[10],e[t+11]=n[11],e[t+12]=n[12],e[t+13]=n[13],e[t+14]=n[14],e[t+15]=n[15],e}}const No=new Es,Bo=new Po,Do=new Es(0,0,0),Io=new Es(1,1,1),Lo=new Es,jo=new Es,Oo=new Es,zo=new Po,Ro=new Ms;class ko{constructor(e=0,t=0,n=0,i=ko.DEFAULT_ORDER){this.isEuler=!0,this._x=e,this._y=t,this._z=n,this._order=i}get x(){return this._x}set x(e){this._x=e,this._onChangeCallback()}get y(){return this._y}set y(e){this._y=e,this._onChangeCallback()}get z(){return this._z}set z(e){this._z=e,this._onChangeCallback()}get order(){return this._order}set order(e){this._order=e,this._onChangeCallback()}set(e,t,n,i=this._order){return this._x=e,this._y=t,this._z=n,this._order=i,this._onChangeCallback(),this}clone(){return new this.constructor(this._x,this._y,this._z,this._order)}copy(e){return this._x=e._x,this._y=e._y,this._z=e._z,this._order=e._order,this._onChangeCallback(),this}setFromRotationMatrix(e,t=this._order,n=!0){const i=e.elements,r=i[0],s=i[4],o=i[8],a=i[1],l=i[5],u=i[9],c=i[2],d=i[6],h=i[10];switch(t){case"XYZ":this._y=Math.asin(vs(o,-1,1)),Math.abs(o)<.9999999?(this._x=Math.atan2(-u,h),this._z=Math.atan2(-s,r)):(this._x=Math.atan2(d,l),this._z=0);break;case"YXZ":this._x=Math.asin(-vs(u,-1,1)),Math.abs(u)<.9999999?(this._y=Math.atan2(o,h),this._z=Math.atan2(a,l)):(this._y=Math.atan2(-c,r),this._z=0);break;case"ZXY":this._x=Math.asin(vs(d,-1,1)),Math.abs(d)<.9999999?(this._y=Math.atan2(-c,h),this._z=Math.atan2(-s,l)):(this._y=0,this._z=Math.atan2(a,r));break;case"ZYX":this._y=Math.asin(-vs(c,-1,1)),Math.abs(c)<.9999999?(this._x=Math.atan2(d,h),this._z=Math.atan2(a,r)):(this._x=0,this._z=Math.atan2(-s,l));break;case"YZX":this._z=Math.asin(vs(a,-1,1)),Math.abs(a)<.9999999?(this._x=Math.atan2(-u,l),this._y=Math.atan2(-c,r)):(this._x=0,this._y=Math.atan2(o,h));break;case"XZY":this._z=Math.asin(-vs(s,-1,1)),Math.abs(s)<.9999999?(this._x=Math.atan2(d,l),this._y=Math.atan2(o,r)):(this._x=Math.atan2(-u,h),this._y=0);break;default:console.warn("THREE.Euler: .setFromRotationMatrix() encountered an unknown order: "+t)}return this._order=t,!0===n&&this._onChangeCallback(),this}setFromQuaternion(e,t,n){return zo.makeRotationFromQuaternion(e),this.setFromRotationMatrix(zo,t,n)}setFromVector3(e,t=this._order){return this.set(e.x,e.y,e.z,t)}reorder(e){return Ro.setFromEuler(this),this.setFromQuaternion(Ro,e)}equals(e){return e._x===this._x&&e._y===this._y&&e._z===this._z&&e._order===this._order}fromArray(e){return this._x=e[0],this._y=e[1],this._z=e[2],void 0!==e[3]&&(this._order=e[3]),this._onChangeCallback(),this}toArray(e=[],t=0){return e[t]=this._x,e[t+1]=this._y,e[t+2]=this._z,e[t+3]=this._order,e}_onChange(e){return this._onChangeCallback=e,this}_onChangeCallback(){}*[Symbol.iterator](){yield this._x,yield this._y,yield this._z,yield this._order}}ko.DEFAULT_ORDER="XYZ";class Fo{constructor(){this.mask=1}set(e){this.mask=(1<<e|0)>>>0}enable(e){this.mask|=1<<e|0}enableAll(){this.mask=-1}toggle(e){this.mask^=1<<e|0}disable(e){this.mask&=~(1<<e|0)}disableAll(){this.mask=0}test(e){return 0!=(this.mask&e.mask)}isEnabled(e){return 0!=(this.mask&(1<<e|0))}}let Ho=0;const Uo=new Es,Xo=new Ms,Go=new Po,Vo=new Es,Wo=new Es,Qo=new Es,Zo=new Ms,Yo=new Es(1,0,0),Jo=new Es(0,1,0),Ko=new Es(0,0,1),qo={type:"added"},_o={type:"removed"},$o={type:"childadded",child:null},ea={type:"childremoved",child:null};class ta extends ds{constructor(){super(),this.isObject3D=!0,Object.defineProperty(this,"id",{value:Ho++}),this.uuid=ms(),this.name="",this.type="Object3D",this.parent=null,this.children=[],this.up=ta.DEFAULT_UP.clone();const e=new Es,t=new ko,n=new Ms,i=new Es(1,1,1);t._onChange((function(){n.setFromEuler(t,!1)})),n._onChange((function(){t.setFromQuaternion(n,void 0,!1)})),Object.defineProperties(this,{position:{configurable:!0,enumerable:!0,value:e},rotation:{configurable:!0,enumerable:!0,value:t},quaternion:{configurable:!0,enumerable:!0,value:n},scale:{configurable:!0,enumerable:!0,value:i},modelViewMatrix:{value:new Po},normalMatrix:{value:new Ps}}),this.matrix=new Po,this.matrixWorld=new Po,this.matrixAutoUpdate=ta.DEFAULT_MATRIX_AUTO_UPDATE,this.matrixWorldAutoUpdate=ta.DEFAULT_MATRIX_WORLD_AUTO_UPDATE,this.matrixWorldNeedsUpdate=!1,this.layers=new Fo,this.visible=!0,this.castShadow=!1,this.receiveShadow=!1,this.frustumCulled=!0,this.renderOrder=0,this.animations=[],this.customDepthMaterial=void 0,this.customDistanceMaterial=void 0,this.userData={}}onBeforeShadow(){}onAfterShadow(){}onBeforeRender(){}onAfterRender(){}applyMatrix4(e){this.matrixAutoUpdate&&this.updateMatrix(),this.matrix.premultiply(e),this.matrix.decompose(this.position,this.quaternion,this.scale)}applyQuaternion(e){return this.quaternion.premultiply(e),this}setRotationFromAxisAngle(e,t){this.quaternion.setFromAxisAngle(e,t)}setRotationFromEuler(e){this.quaternion.setFromEuler(e,!0)}setRotationFromMatrix(e){this.quaternion.setFromRotationMatrix(e)}setRotationFromQuaternion(e){this.quaternion.copy(e)}rotateOnAxis(e,t){return Xo.setFromAxisAngle(e,t),this.quaternion.multiply(Xo),this}rotateOnWorldAxis(e,t){return Xo.setFromAxisAngle(e,t),this.quaternion.premultiply(Xo),this}rotateX(e){return this.rotateOnAxis(Yo,e)}rotateY(e){return this.rotateOnAxis(Jo,e)}rotateZ(e){return this.rotateOnAxis(Ko,e)}translateOnAxis(e,t){return Uo.copy(e).applyQuaternion(this.quaternion),this.position.add(Uo.multiplyScalar(t)),this}translateX(e){return this.translateOnAxis(Yo,e)}translateY(e){return this.translateOnAxis(Jo,e)}translateZ(e){return this.translateOnAxis(Ko,e)}localToWorld(e){return this.updateWorldMatrix(!0,!1),e.applyMatrix4(this.matrixWorld)}worldToLocal(e){return this.updateWorldMatrix(!0,!1),e.applyMatrix4(Go.copy(this.matrixWorld).invert())}lookAt(e,t,n){e.isVector3?Vo.copy(e):Vo.set(e,t,n);const i=this.parent;this.updateWorldMatrix(!0,!1),Wo.setFromMatrixPosition(this.matrixWorld),this.isCamera||this.isLight?Go.lookAt(Wo,Vo,this.up):Go.lookAt(Vo,Wo,this.up),this.quaternion.setFromRotationMatrix(Go),i&&(Go.extractRotation(i.matrixWorld),Xo.setFromRotationMatrix(Go),this.quaternion.premultiply(Xo.invert()))}add(e){if(arguments.length>1){for(let e=0;e<arguments.length;e++)this.add(arguments[e]);return this}return e===this?(console.error("THREE.Object3D.add: object can't be added as a child of itself.",e),this):(e&&e.isObject3D?(e.removeFromParent(),e.parent=this,this.children.push(e),e.dispatchEvent(qo),$o.child=e,this.dispatchEvent($o),$o.child=null):console.error("THREE.Object3D.add: object not an instance of THREE.Object3D.",e),this)}remove(e){if(arguments.length>1){for(let e=0;e<arguments.length;e++)this.remove(arguments[e]);return this}const t=this.children.indexOf(e);return-1!==t&&(e.parent=null,this.children.splice(t,1),e.dispatchEvent(_o),ea.child=e,this.dispatchEvent(ea),ea.child=null),this}removeFromParent(){const e=this.parent;return null!==e&&e.remove(this),this}clear(){return this.remove(...this.children)}attach(e){return this.updateWorldMatrix(!0,!1),Go.copy(this.matrixWorld).invert(),null!==e.parent&&(e.parent.updateWorldMatrix(!0,!1),Go.multiply(e.parent.matrixWorld)),e.applyMatrix4(Go),e.removeFromParent(),e.parent=this,this.children.push(e),e.updateWorldMatrix(!1,!0),e.dispatchEvent(qo),$o.child=e,this.dispatchEvent($o),$o.child=null,this}getObjectById(e){return this.getObjectByProperty("id",e)}getObjectByName(e){return this.getObjectByProperty("name",e)}getObjectByProperty(e,t){if(this[e]===t)return this;for(let n=0,i=this.children.length;n<i;n++){const i=this.children[n].getObjectByProperty(e,t);if(void 0!==i)return i}}getObjectsByProperty(e,t,n=[]){this[e]===t&&n.push(this);const i=this.children;for(let r=0,s=i.length;r<s;r++)i[r].getObjectsByProperty(e,t,n);return n}getWorldPosition(e){return this.updateWorldMatrix(!0,!1),e.setFromMatrixPosition(this.matrixWorld)}getWorldQuaternion(e){return this.updateWorldMatrix(!0,!1),this.matrixWorld.decompose(Wo,e,Qo),e}getWorldScale(e){return this.updateWorldMatrix(!0,!1),this.matrixWorld.decompose(Wo,Zo,e),e}getWorldDirection(e){this.updateWorldMatrix(!0,!1);const t=this.matrixWorld.elements;return e.set(t[8],t[9],t[10]).normalize()}raycast(){}traverse(e){e(this);const t=this.children;for(let n=0,i=t.length;n<i;n++)t[n].traverse(e)}traverseVisible(e){if(!1===this.visible)return;e(this);const t=this.children;for(let n=0,i=t.length;n<i;n++)t[n].traverseVisible(e)}traverseAncestors(e){const t=this.parent;null!==t&&(e(t),t.traverseAncestors(e))}updateMatrix(){this.matrix.compose(this.position,this.quaternion,this.scale),this.matrixWorldNeedsUpdate=!0}updateMatrixWorld(e){this.matrixAutoUpdate&&this.updateMatrix(),(this.matrixWorldNeedsUpdate||e)&&(!0===this.matrixWorldAutoUpdate&&(null===this.parent?this.matrixWorld.copy(this.matrix):this.matrixWorld.multiplyMatrices(this.parent.matrixWorld,this.matrix)),this.matrixWorldNeedsUpdate=!1,e=!0);const t=this.children;for(let n=0,i=t.length;n<i;n++){t[n].updateMatrixWorld(e)}}updateWorldMatrix(e,t){const n=this.parent;if(!0===e&&null!==n&&n.updateWorldMatrix(!0,!1),this.matrixAutoUpdate&&this.updateMatrix(),!0===this.matrixWorldAutoUpdate&&(null===this.parent?this.matrixWorld.copy(this.matrix):this.matrixWorld.multiplyMatrices(this.parent.matrixWorld,this.matrix)),!0===t){const e=this.children;for(let t=0,n=e.length;t<n;t++){e[t].updateWorldMatrix(!1,!0)}}}toJSON(e){const t=void 0===e||"string"==typeof e,n={};t&&(e={geometries:{},materials:{},textures:{},images:{},shapes:{},skeletons:{},animations:{},nodes:{}},n.metadata={version:4.7,type:"Object",generator:"Object3D.toJSON"});const i={};function r(t,n){return void 0===t[n.uuid]&&(t[n.uuid]=n.toJSON(e)),n.uuid}if(i.uuid=this.uuid,i.type=this.type,""!==this.name&&(i.name=this.name),!0===this.castShadow&&(i.castShadow=!0),!0===this.receiveShadow&&(i.receiveShadow=!0),!1===this.visible&&(i.visible=!1),!1===this.frustumCulled&&(i.frustumCulled=!1),0!==this.renderOrder&&(i.renderOrder=this.renderOrder),Object.keys(this.userData).length>0&&(i.userData=this.userData),i.layers=this.layers.mask,i.matrix=this.matrix.toArray(),i.up=this.up.toArray(),!1===this.matrixAutoUpdate&&(i.matrixAutoUpdate=!1),this.isInstancedMesh&&(i.type="InstancedMesh",i.count=this.count,i.instanceMatrix=this.instanceMatrix.toJSON(),null!==this.instanceColor&&(i.instanceColor=this.instanceColor.toJSON())),this.isBatchedMesh&&(i.type="BatchedMesh",i.perObjectFrustumCulled=this.perObjectFrustumCulled,i.sortObjects=this.sortObjects,i.drawRanges=this._drawRanges,i.reservedRanges=this._reservedRanges,i.geometryInfo=this._geometryInfo.map((e=>({...e,boundingBox:e.boundingBox?e.boundingBox.toJSON():void 0,boundingSphere:e.boundingSphere?e.boundingSphere.toJSON():void 0}))),i.instanceInfo=this._instanceInfo.map((e=>({...e}))),i.availableInstanceIds=this._availableInstanceIds.slice(),i.availableGeometryIds=this._availableGeometryIds.slice(),i.nextIndexStart=this._nextIndexStart,i.nextVertexStart=this._nextVertexStart,i.geometryCount=this._geometryCount,i.maxInstanceCount=this._maxInstanceCount,i.maxVertexCount=this._maxVertexCount,i.maxIndexCount=this._maxIndexCount,i.geometryInitialized=this._geometryInitialized,i.matricesTexture=this._matricesTexture.toJSON(e),i.indirectTexture=this._indirectTexture.toJSON(e),null!==this._colorsTexture&&(i.colorsTexture=this._colorsTexture.toJSON(e)),null!==this.boundingSphere&&(i.boundingSphere=this.boundingSphere.toJSON()),null!==this.boundingBox&&(i.boundingBox=this.boundingBox.toJSON())),this.isScene)this.background&&(this.background.isColor?i.background=this.background.toJSON():this.background.isTexture&&(i.background=this.background.toJSON(e).uuid)),this.environment&&this.environment.isTexture&&!0!==this.environment.isRenderTargetTexture&&(i.environment=this.environment.toJSON(e).uuid);else if(this.isMesh||this.isLine||this.isPoints){i.geometry=r(e.geometries,this.geometry);const t=this.geometry.parameters;if(void 0!==t&&void 0!==t.shapes){const n=t.shapes;if(Array.isArray(n))for(let t=0,i=n.length;t<i;t++){const i=n[t];r(e.shapes,i)}else r(e.shapes,n)}}if(this.isSkinnedMesh&&(i.bindMode=this.bindMode,i.bindMatrix=this.bindMatrix.toArray(),void 0!==this.skeleton&&(r(e.skeletons,this.skeleton),i.skeleton=this.skeleton.uuid)),void 0!==this.material)if(Array.isArray(this.material)){const t=[];for(let n=0,i=this.material.length;n<i;n++)t.push(r(e.materials,this.material[n]));i.material=t}else i.material=r(e.materials,this.material);if(this.children.length>0){i.children=[];for(let t=0;t<this.children.length;t++)i.children.push(this.children[t].toJSON(e).object)}if(this.animations.length>0){i.animations=[];for(let t=0;t<this.animations.length;t++){const n=this.animations[t];i.animations.push(r(e.animations,n))}}if(t){const t=s(e.geometries),i=s(e.materials),r=s(e.textures),o=s(e.images),a=s(e.shapes),l=s(e.skeletons),u=s(e.animations),c=s(e.nodes);t.length>0&&(n.geometries=t),i.length>0&&(n.materials=i),r.length>0&&(n.textures=r),o.length>0&&(n.images=o),a.length>0&&(n.shapes=a),l.length>0&&(n.skeletons=l),u.length>0&&(n.animations=u),c.length>0&&(n.nodes=c)}return n.object=i,n;function s(e){const t=[];for(const n in e){const i=e[n];delete i.metadata,t.push(i)}return t}}clone(e){return(new this.constructor).copy(this,e)}copy(e,t=!0){if(this.name=e.name,this.up.copy(e.up),this.position.copy(e.position),this.rotation.order=e.rotation.order,this.quaternion.copy(e.quaternion),this.scale.copy(e.scale),this.matrix.copy(e.matrix),this.matrixWorld.copy(e.matrixWorld),this.matrixAutoUpdate=e.matrixAutoUpdate,this.matrixWorldAutoUpdate=e.matrixWorldAutoUpdate,this.matrixWorldNeedsUpdate=e.matrixWorldNeedsUpdate,this.layers.mask=e.layers.mask,this.visible=e.visible,this.castShadow=e.castShadow,this.receiveShadow=e.receiveShadow,this.frustumCulled=e.frustumCulled,this.renderOrder=e.renderOrder,this.animations=e.animations.slice(),this.userData=JSON.parse(JSON.stringify(e.userData)),!0===t)for(let t=0;t<e.children.length;t++){const n=e.children[t];this.add(n.clone())}return this}}ta.DEFAULT_UP=new Es(0,1,0),ta.DEFAULT_MATRIX_AUTO_UPDATE=!0,ta.DEFAULT_MATRIX_WORLD_AUTO_UPDATE=!0;const na=new Es,ia=new Es,ra=new Es,sa=new Es,oa=new Es,aa=new Es,la=new Es,ua=new Es,ca=new Es,da=new Es,ha=new Js,fa=new Js,pa=new Js;class ga{constructor(e=new Es,t=new Es,n=new Es){this.a=e,this.b=t,this.c=n}static getNormal(e,t,n,i){i.subVectors(n,t),na.subVectors(e,t),i.cross(na);const r=i.lengthSq();return r>0?i.multiplyScalar(1/Math.sqrt(r)):i.set(0,0,0)}static getBarycoord(e,t,n,i,r){na.subVectors(i,t),ia.subVectors(n,t),ra.subVectors(e,t);const s=na.dot(na),o=na.dot(ia),a=na.dot(ra),l=ia.dot(ia),u=ia.dot(ra),c=s*l-o*o;if(0===c)return r.set(0,0,0),null;const d=1/c,h=(l*a-o*u)*d,f=(s*u-o*a)*d;return r.set(1-h-f,f,h)}static containsPoint(e,t,n,i){return null!==this.getBarycoord(e,t,n,i,sa)&&(sa.x>=0&&sa.y>=0&&sa.x+sa.y<=1)}static getInterpolation(e,t,n,i,r,s,o,a){return null===this.getBarycoord(e,t,n,i,sa)?(a.x=0,a.y=0,"z"in a&&(a.z=0),"w"in a&&(a.w=0),null):(a.setScalar(0),a.addScaledVector(r,sa.x),a.addScaledVector(s,sa.y),a.addScaledVector(o,sa.z),a)}static getInterpolatedAttribute(e,t,n,i,r,s){return ha.setScalar(0),fa.setScalar(0),pa.setScalar(0),ha.fromBufferAttribute(e,t),fa.fromBufferAttribute(e,n),pa.fromBufferAttribute(e,i),s.setScalar(0),s.addScaledVector(ha,r.x),s.addScaledVector(fa,r.y),s.addScaledVector(pa,r.z),s}static isFrontFacing(e,t,n,i){return na.subVectors(n,t),ia.subVectors(e,t),na.cross(ia).dot(i)<0}set(e,t,n){return this.a.copy(e),this.b.copy(t),this.c.copy(n),this}setFromPointsAndIndices(e,t,n,i){return this.a.copy(e[t]),this.b.copy(e[n]),this.c.copy(e[i]),this}setFromAttributeAndIndices(e,t,n,i){return this.a.fromBufferAttribute(e,t),this.b.fromBufferAttribute(e,n),this.c.fromBufferAttribute(e,i),this}clone(){return(new this.constructor).copy(this)}copy(e){return this.a.copy(e.a),this.b.copy(e.b),this.c.copy(e.c),this}getArea(){return na.subVectors(this.c,this.b),ia.subVectors(this.a,this.b),.5*na.cross(ia).length()}getMidpoint(e){return e.addVectors(this.a,this.b).add(this.c).multiplyScalar(1/3)}getNormal(e){return ga.getNormal(this.a,this.b,this.c,e)}getPlane(e){return e.setFromCoplanarPoints(this.a,this.b,this.c)}getBarycoord(e,t){return ga.getBarycoord(e,this.a,this.b,this.c,t)}getInterpolation(e,t,n,i,r){return ga.getInterpolation(e,this.a,this.b,this.c,t,n,i,r)}containsPoint(e){return ga.containsPoint(e,this.a,this.b,this.c)}isFrontFacing(e){return ga.isFrontFacing(this.a,this.b,this.c,e)}intersectsBox(e){return e.intersectsTriangle(this)}closestPointToPoint(e,t){const n=this.a,i=this.b,r=this.c;let s,o;oa.subVectors(i,n),aa.subVectors(r,n),ua.subVectors(e,n);const a=oa.dot(ua),l=aa.dot(ua);if(a<=0&&l<=0)return t.copy(n);ca.subVectors(e,i);const u=oa.dot(ca),c=aa.dot(ca);if(u>=0&&c<=u)return t.copy(i);const d=a*c-u*l;if(d<=0&&a>=0&&u<=0)return s=a/(a-u),t.copy(n).addScaledVector(oa,s);da.subVectors(e,r);const h=oa.dot(da),f=aa.dot(da);if(f>=0&&h<=f)return t.copy(r);const p=h*l-a*f;if(p<=0&&l>=0&&f<=0)return o=l/(l-f),t.copy(n).addScaledVector(aa,o);const g=u*f-h*c;if(g<=0&&c-u>=0&&h-f>=0)return la.subVectors(r,i),o=(c-u)/(c-u+(h-f)),t.copy(i).addScaledVector(la,o);const m=1/(g+p+d);return s=p*m,o=d*m,t.copy(n).addScaledVector(oa,s).addScaledVector(aa,o)}equals(e){return e.a.equals(this.a)&&e.b.equals(this.b)&&e.c.equals(this.c)}}const ma={aliceblue:15792383,antiquewhite:16444375,aqua:65535,aquamarine:8388564,azure:15794175,beige:16119260,bisque:16770244,black:0,blanchedalmond:16772045,blue:255,blueviolet:9055202,brown:10824234,burlywood:14596231,cadetblue:6266528,chartreuse:8388352,chocolate:13789470,coral:16744272,cornflowerblue:6591981,cornsilk:16775388,crimson:14423100,cyan:65535,darkblue:139,darkcyan:35723,darkgoldenrod:12092939,darkgray:11119017,darkgreen:25600,darkgrey:11119017,darkkhaki:12433259,darkmagenta:9109643,darkolivegreen:5597999,darkorange:16747520,darkorchid:10040012,darkred:9109504,darksalmon:15308410,darkseagreen:9419919,darkslateblue:4734347,darkslategray:3100495,darkslategrey:3100495,darkturquoise:52945,darkviolet:9699539,deeppink:16716947,deepskyblue:49151,dimgray:6908265,dimgrey:6908265,dodgerblue:2003199,firebrick:11674146,floralwhite:16775920,forestgreen:2263842,fuchsia:16711935,gainsboro:14474460,ghostwhite:16316671,gold:16766720,goldenrod:14329120,gray:8421504,green:32768,greenyellow:11403055,grey:8421504,honeydew:15794160,hotpink:16738740,indianred:13458524,indigo:4915330,ivory:16777200,khaki:15787660,lavender:15132410,lavenderblush:16773365,lawngreen:8190976,lemonchiffon:16775885,lightblue:11393254,lightcoral:15761536,lightcyan:14745599,lightgoldenrodyellow:16448210,lightgray:13882323,lightgreen:9498256,lightgrey:13882323,lightpink:16758465,lightsalmon:16752762,lightseagreen:2142890,lightskyblue:8900346,lightslategray:7833753,lightslategrey:7833753,lightsteelblue:11584734,lightyellow:16777184,lime:65280,limegreen:3329330,linen:16445670,magenta:16711935,maroon:8388608,mediumaquamarine:6737322,mediumblue:205,mediumorchid:12211667,mediumpurple:9662683,mediumseagreen:3978097,mediumslateblue:8087790,mediumspringgreen:64154,mediumturquoise:4772300,mediumvioletred:13047173,midnightblue:1644912,mintcream:16121850,mistyrose:16770273,moccasin:16770229,navajowhite:16768685,navy:128,oldlace:16643558,olive:8421376,olivedrab:7048739,orange:16753920,orangered:16729344,orchid:14315734,palegoldenrod:15657130,palegreen:10025880,paleturquoise:11529966,palevioletred:14381203,papayawhip:16773077,peachpuff:16767673,peru:13468991,pink:16761035,plum:14524637,powderblue:11591910,purple:8388736,rebeccapurple:6697881,red:16711680,rosybrown:12357519,royalblue:4286945,saddlebrown:9127187,salmon:16416882,sandybrown:16032864,seagreen:3050327,seashell:16774638,sienna:10506797,silver:12632256,skyblue:8900331,slateblue:6970061,slategray:7372944,slategrey:7372944,snow:16775930,springgreen:65407,steelblue:4620980,tan:13808780,teal:32896,thistle:14204888,tomato:16737095,turquoise:4251856,violet:15631086,wheat:16113331,white:16777215,whitesmoke:16119285,yellow:16776960,yellowgreen:10145074},va={h:0,s:0,l:0},Aa={h:0,s:0,l:0};function xa(e,t,n){return n<0&&(n+=1),n>1&&(n-=1),n<1/6?e+6*(t-e)*n:n<.5?t:n<2/3?e+6*(t-e)*(2/3-n):e}class ya{constructor(e,t,n){return this.isColor=!0,this.r=1,this.g=1,this.b=1,this.set(e,t,n)}set(e,t,n){if(void 0===t&&void 0===n){const t=e;t&&t.isColor?this.copy(t):"number"==typeof t?this.setHex(t):"string"==typeof t&&this.setStyle(t)}else this.setRGB(e,t,n);return this}setScalar(e){return this.r=e,this.g=e,this.b=e,this}setHex(e,t=qr){return e=Math.floor(e),this.r=(e>>16&255)/255,this.g=(e>>8&255)/255,this.b=(255&e)/255,ks.colorSpaceToWorking(this,t),this}setRGB(e,t,n,i=ks.workingColorSpace){return this.r=e,this.g=t,this.b=n,ks.colorSpaceToWorking(this,i),this}setHSL(e,t,n,i=ks.workingColorSpace){if(e=As(e,1),t=vs(t,0,1),n=vs(n,0,1),0===t)this.r=this.g=this.b=n;else{const i=n<=.5?n*(1+t):n+t-n*t,r=2*n-i;this.r=xa(r,i,e+1/3),this.g=xa(r,i,e),this.b=xa(r,i,e-1/3)}return ks.colorSpaceToWorking(this,i),this}setStyle(e,t=qr){function n(t){void 0!==t&&parseFloat(t)<1&&console.warn("THREE.Color: Alpha component of "+e+" will be ignored.")}let i;if(i=/^(\w+)\(([^\)]*)\)/.exec(e)){let r;const s=i[1],o=i[2];switch(s){case"rgb":case"rgba":if(r=/^\s*(\d+)\s*,\s*(\d+)\s*,\s*(\d+)\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec(o))return n(r[4]),this.setRGB(Math.min(255,parseInt(r[1],10))/255,Math.min(255,parseInt(r[2],10))/255,Math.min(255,parseInt(r[3],10))/255,t);if(r=/^\s*(\d+)\%\s*,\s*(\d+)\%\s*,\s*(\d+)\%\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec(o))return n(r[4]),this.setRGB(Math.min(100,parseInt(r[1],10))/100,Math.min(100,parseInt(r[2],10))/100,Math.min(100,parseInt(r[3],10))/100,t);break;case"hsl":case"hsla":if(r=/^\s*(\d*\.?\d+)\s*,\s*(\d*\.?\d+)\%\s*,\s*(\d*\.?\d+)\%\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec(o))return n(r[4]),this.setHSL(parseFloat(r[1])/360,parseFloat(r[2])/100,parseFloat(r[3])/100,t);break;default:console.warn("THREE.Color: Unknown color model "+e)}}else if(i=/^\#([A-Fa-f\d]+)$/.exec(e)){const n=i[1],r=n.length;if(3===r)return this.setRGB(parseInt(n.charAt(0),16)/15,parseInt(n.charAt(1),16)/15,parseInt(n.charAt(2),16)/15,t);if(6===r)return this.setHex(parseInt(n,16),t);console.warn("THREE.Color: Invalid hex color "+e)}else if(e&&e.length>0)return this.setColorName(e,t);return this}setColorName(e,t=qr){const n=ma[e.toLowerCase()];return void 0!==n?this.setHex(n,t):console.warn("THREE.Color: Unknown color "+e),this}clone(){return new this.constructor(this.r,this.g,this.b)}copy(e){return this.r=e.r,this.g=e.g,this.b=e.b,this}copySRGBToLinear(e){return this.r=Fs(e.r),this.g=Fs(e.g),this.b=Fs(e.b),this}copyLinearToSRGB(e){return this.r=Hs(e.r),this.g=Hs(e.g),this.b=Hs(e.b),this}convertSRGBToLinear(){return this.copySRGBToLinear(this),this}convertLinearToSRGB(){return this.copyLinearToSRGB(this),this}getHex(e=qr){return ks.workingToColorSpace(ba.copy(this),e),65536*Math.round(vs(255*ba.r,0,255))+256*Math.round(vs(255*ba.g,0,255))+Math.round(vs(255*ba.b,0,255))}getHexString(e=qr){return("000000"+this.getHex(e).toString(16)).slice(-6)}getHSL(e,t=ks.workingColorSpace){ks.workingToColorSpace(ba.copy(this),t);const n=ba.r,i=ba.g,r=ba.b,s=Math.max(n,i,r),o=Math.min(n,i,r);let a,l;const u=(o+s)/2;if(o===s)a=0,l=0;else{const e=s-o;switch(l=u<=.5?e/(s+o):e/(2-s-o),s){case n:a=(i-r)/e+(i<r?6:0);break;case i:a=(r-n)/e+2;break;case r:a=(n-i)/e+4}a/=6}return e.h=a,e.s=l,e.l=u,e}getRGB(e,t=ks.workingColorSpace){return ks.workingToColorSpace(ba.copy(this),t),e.r=ba.r,e.g=ba.g,e.b=ba.b,e}getStyle(e=qr){ks.workingToColorSpace(ba.copy(this),e);const t=ba.r,n=ba.g,i=ba.b;return e!==qr?`color(${e} ${t.toFixed(3)} ${n.toFixed(3)} ${i.toFixed(3)})`:`rgb(${Math.round(255*t)},${Math.round(255*n)},${Math.round(255*i)})`}offsetHSL(e,t,n){return this.getHSL(va),this.setHSL(va.h+e,va.s+t,va.l+n)}add(e){return this.r+=e.r,this.g+=e.g,this.b+=e.b,this}addColors(e,t){return this.r=e.r+t.r,this.g=e.g+t.g,this.b=e.b+t.b,this}addScalar(e){return this.r+=e,this.g+=e,this.b+=e,this}sub(e){return this.r=Math.max(0,this.r-e.r),this.g=Math.max(0,this.g-e.g),this.b=Math.max(0,this.b-e.b),this}multiply(e){return this.r*=e.r,this.g*=e.g,this.b*=e.b,this}multiplyScalar(e){return this.r*=e,this.g*=e,this.b*=e,this}lerp(e,t){return this.r+=(e.r-this.r)*t,this.g+=(e.g-this.g)*t,this.b+=(e.b-this.b)*t,this}lerpColors(e,t,n){return this.r=e.r+(t.r-e.r)*n,this.g=e.g+(t.g-e.g)*n,this.b=e.b+(t.b-e.b)*n,this}lerpHSL(e,t){this.getHSL(va),e.getHSL(Aa);const n=xs(va.h,Aa.h,t),i=xs(va.s,Aa.s,t),r=xs(va.l,Aa.l,t);return this.setHSL(n,i,r),this}setFromVector3(e){return this.r=e.x,this.g=e.y,this.b=e.z,this}applyMatrix3(e){const t=this.r,n=this.g,i=this.b,r=e.elements;return this.r=r[0]*t+r[3]*n+r[6]*i,this.g=r[1]*t+r[4]*n+r[7]*i,this.b=r[2]*t+r[5]*n+r[8]*i,this}equals(e){return e.r===this.r&&e.g===this.g&&e.b===this.b}fromArray(e,t=0){return this.r=e[t],this.g=e[t+1],this.b=e[t+2],this}toArray(e=[],t=0){return e[t]=this.r,e[t+1]=this.g,e[t+2]=this.b,e}fromBufferAttribute(e,t){return this.r=e.getX(t),this.g=e.getY(t),this.b=e.getZ(t),this}toJSON(){return this.getHex()}*[Symbol.iterator](){yield this.r,yield this.g,yield this.b}}const ba=new ya;ya.NAMES=ma;let wa=0;class Ca extends ds{constructor(){super(),this.isMaterial=!0,Object.defineProperty(this,"id",{value:wa++}),this.uuid=ms(),this.name="",this.type="Material",this.blending=1,this.side=0,this.vertexColors=!1,this.opacity=1,this.transparent=!1,this.alphaHash=!1,this.blendSrc=Ti,this.blendDst=Si,this.blendEquation=Mi,this.blendSrcAlpha=null,this.blendDstAlpha=null,this.blendEquationAlpha=null,this.blendColor=new ya(0,0,0),this.blendAlpha=0,this.depthFunc=3,this.depthTest=!0,this.depthWrite=!0,this.stencilWriteMask=255,this.stencilFunc=519,this.stencilRef=0,this.stencilFuncMask=255,this.stencilFail=ts,this.stencilZFail=ts,this.stencilZPass=ts,this.stencilWrite=!1,this.clippingPlanes=null,this.clipIntersection=!1,this.clipShadows=!1,this.shadowSide=null,this.colorWrite=!0,this.precision=null,this.polygonOffset=!1,this.polygonOffsetFactor=0,this.polygonOffsetUnits=0,this.dithering=!1,this.alphaToCoverage=!1,this.premultipliedAlpha=!1,this.forceSinglePass=!1,this.allowOverride=!0,this.visible=!0,this.toneMapped=!0,this.userData={},this.version=0,this._alphaTest=0}get alphaTest(){return this._alphaTest}set alphaTest(e){this._alphaTest>0!=e>0&&this.version++,this._alphaTest=e}onBeforeRender(){}onBeforeCompile(){}customProgramCacheKey(){return this.onBeforeCompile.toString()}setValues(e){if(void 0!==e)for(const t in e){const n=e[t];if(void 0===n){console.warn(`THREE.Material: parameter '${t}' has value of undefined.`);continue}const i=this[t];void 0!==i?i&&i.isColor?i.set(n):i&&i.isVector3&&n&&n.isVector3?i.copy(n):this[t]=n:console.warn(`THREE.Material: '${t}' is not a property of THREE.${this.type}.`)}}toJSON(e){const t=void 0===e||"string"==typeof e;t&&(e={textures:{},images:{}});const n={metadata:{version:4.7,type:"Material",generator:"Material.toJSON"}};function i(e){const t=[];for(const n in e){const i=e[n];delete i.metadata,t.push(i)}return t}if(n.uuid=this.uuid,n.type=this.type,""!==this.name&&(n.name=this.name),this.color&&this.color.isColor&&(n.color=this.color.getHex()),void 0!==this.roughness&&(n.roughness=this.roughness),void 0!==this.metalness&&(n.metalness=this.metalness),void 0!==this.sheen&&(n.sheen=this.sheen),this.sheenColor&&this.sheenColor.isColor&&(n.sheenColor=this.sheenColor.getHex()),void 0!==this.sheenRoughness&&(n.sheenRoughness=this.sheenRoughness),this.emissive&&this.emissive.isColor&&(n.emissive=this.emissive.getHex()),void 0!==this.emissiveIntensity&&1!==this.emissiveIntensity&&(n.emissiveIntensity=this.emissiveIntensity),this.specular&&this.specular.isColor&&(n.specular=this.specular.getHex()),void 0!==this.specularIntensity&&(n.specularIntensity=this.specularIntensity),this.specularColor&&this.specularColor.isColor&&(n.specularColor=this.specularColor.getHex()),void 0!==this.shininess&&(n.shininess=this.shininess),void 0!==this.clearcoat&&(n.clearcoat=this.clearcoat),void 0!==this.clearcoatRoughness&&(n.clearcoatRoughness=this.clearcoatRoughness),this.clearcoatMap&&this.clearcoatMap.isTexture&&(n.clearcoatMap=this.clearcoatMap.toJSON(e).uuid),this.clearcoatRoughnessMap&&this.clearcoatRoughnessMap.isTexture&&(n.clearcoatRoughnessMap=this.clearcoatRoughnessMap.toJSON(e).uuid),this.clearcoatNormalMap&&this.clearcoatNormalMap.isTexture&&(n.clearcoatNormalMap=this.clearcoatNormalMap.toJSON(e).uuid,n.clearcoatNormalScale=this.clearcoatNormalScale.toArray()),this.sheenColorMap&&this.sheenColorMap.isTexture&&(n.sheenColorMap=this.sheenColorMap.toJSON(e).uuid),this.sheenRoughnessMap&&this.sheenRoughnessMap.isTexture&&(n.sheenRoughnessMap=this.sheenRoughnessMap.toJSON(e).uuid),void 0!==this.dispersion&&(n.dispersion=this.dispersion),void 0!==this.iridescence&&(n.iridescence=this.iridescence),void 0!==this.iridescenceIOR&&(n.iridescenceIOR=this.iridescenceIOR),void 0!==this.iridescenceThicknessRange&&(n.iridescenceThicknessRange=this.iridescenceThicknessRange),this.iridescenceMap&&this.iridescenceMap.isTexture&&(n.iridescenceMap=this.iridescenceMap.toJSON(e).uuid),this.iridescenceThicknessMap&&this.iridescenceThicknessMap.isTexture&&(n.iridescenceThicknessMap=this.iridescenceThicknessMap.toJSON(e).uuid),void 0!==this.anisotropy&&(n.anisotropy=this.anisotropy),void 0!==this.anisotropyRotation&&(n.anisotropyRotation=this.anisotropyRotation),this.anisotropyMap&&this.anisotropyMap.isTexture&&(n.anisotropyMap=this.anisotropyMap.toJSON(e).uuid),this.map&&this.map.isTexture&&(n.map=this.map.toJSON(e).uuid),this.matcap&&this.matcap.isTexture&&(n.matcap=this.matcap.toJSON(e).uuid),this.alphaMap&&this.alphaMap.isTexture&&(n.alphaMap=this.alphaMap.toJSON(e).uuid),this.lightMap&&this.lightMap.isTexture&&(n.lightMap=this.lightMap.toJSON(e).uuid,n.lightMapIntensity=this.lightMapIntensity),this.aoMap&&this.aoMap.isTexture&&(n.aoMap=this.aoMap.toJSON(e).uuid,n.aoMapIntensity=this.aoMapIntensity),this.bumpMap&&this.bumpMap.isTexture&&(n.bumpMap=this.bumpMap.toJSON(e).uuid,n.bumpScale=this.bumpScale),this.normalMap&&this.normalMap.isTexture&&(n.normalMap=this.normalMap.toJSON(e).uuid,n.normalMapType=this.normalMapType,n.normalScale=this.normalScale.toArray()),this.displacementMap&&this.displacementMap.isTexture&&(n.displacementMap=this.displacementMap.toJSON(e).uuid,n.displacementScale=this.displacementScale,n.displacementBias=this.displacementBias),this.roughnessMap&&this.roughnessMap.isTexture&&(n.roughnessMap=this.roughnessMap.toJSON(e).uuid),this.metalnessMap&&this.metalnessMap.isTexture&&(n.metalnessMap=this.metalnessMap.toJSON(e).uuid),this.emissiveMap&&this.emissiveMap.isTexture&&(n.emissiveMap=this.emissiveMap.toJSON(e).uuid),this.specularMap&&this.specularMap.isTexture&&(n.specularMap=this.specularMap.toJSON(e).uuid),this.specularIntensityMap&&this.specularIntensityMap.isTexture&&(n.specularIntensityMap=this.specularIntensityMap.toJSON(e).uuid),this.specularColorMap&&this.specularColorMap.isTexture&&(n.specularColorMap=this.specularColorMap.toJSON(e).uuid),this.envMap&&this.envMap.isTexture&&(n.envMap=this.envMap.toJSON(e).uuid,void 0!==this.combine&&(n.combine=this.combine)),void 0!==this.envMapRotation&&(n.envMapRotation=this.envMapRotation.toArray()),void 0!==this.envMapIntensity&&(n.envMapIntensity=this.envMapIntensity),void 0!==this.reflectivity&&(n.reflectivity=this.reflectivity),void 0!==this.refractionRatio&&(n.refractionRatio=this.refractionRatio),this.gradientMap&&this.gradientMap.isTexture&&(n.gradientMap=this.gradientMap.toJSON(e).uuid),void 0!==this.transmission&&(n.transmission=this.transmission),this.transmissionMap&&this.transmissionMap.isTexture&&(n.transmissionMap=this.transmissionMap.toJSON(e).uuid),void 0!==this.thickness&&(n.thickness=this.thickness),this.thicknessMap&&this.thicknessMap.isTexture&&(n.thicknessMap=this.thicknessMap.toJSON(e).uuid),void 0!==this.attenuationDistance&&this.attenuationDistance!==1/0&&(n.attenuationDistance=this.attenuationDistance),void 0!==this.attenuationColor&&(n.attenuationColor=this.attenuationColor.getHex()),void 0!==this.size&&(n.size=this.size),null!==this.shadowSide&&(n.shadowSide=this.shadowSide),void 0!==this.sizeAttenuation&&(n.sizeAttenuation=this.sizeAttenuation),1!==this.blending&&(n.blending=this.blending),0!==this.side&&(n.side=this.side),!0===this.vertexColors&&(n.vertexColors=!0),this.opacity<1&&(n.opacity=this.opacity),!0===this.transparent&&(n.transparent=!0),this.blendSrc!==Ti&&(n.blendSrc=this.blendSrc),this.blendDst!==Si&&(n.blendDst=this.blendDst),this.blendEquation!==Mi&&(n.blendEquation=this.blendEquation),null!==this.blendSrcAlpha&&(n.blendSrcAlpha=this.blendSrcAlpha),null!==this.blendDstAlpha&&(n.blendDstAlpha=this.blendDstAlpha),null!==this.blendEquationAlpha&&(n.blendEquationAlpha=this.blendEquationAlpha),this.blendColor&&this.blendColor.isColor&&(n.blendColor=this.blendColor.getHex()),0!==this.blendAlpha&&(n.blendAlpha=this.blendAlpha),3!==this.depthFunc&&(n.depthFunc=this.depthFunc),!1===this.depthTest&&(n.depthTest=this.depthTest),!1===this.depthWrite&&(n.depthWrite=this.depthWrite),!1===this.colorWrite&&(n.colorWrite=this.colorWrite),255!==this.stencilWriteMask&&(n.stencilWriteMask=this.stencilWriteMask),519!==this.stencilFunc&&(n.stencilFunc=this.stencilFunc),0!==this.stencilRef&&(n.stencilRef=this.stencilRef),255!==this.stencilFuncMask&&(n.stencilFuncMask=this.stencilFuncMask),this.stencilFail!==ts&&(n.stencilFail=this.stencilFail),this.stencilZFail!==ts&&(n.stencilZFail=this.stencilZFail),this.stencilZPass!==ts&&(n.stencilZPass=this.stencilZPass),!0===this.stencilWrite&&(n.stencilWrite=this.stencilWrite),void 0!==this.rotation&&0!==this.rotation&&(n.rotation=this.rotation),!0===this.polygonOffset&&(n.polygonOffset=!0),0!==this.polygonOffsetFactor&&(n.polygonOffsetFactor=this.polygonOffsetFactor),0!==this.polygonOffsetUnits&&(n.polygonOffsetUnits=this.polygonOffsetUnits),void 0!==this.linewidth&&1!==this.linewidth&&(n.linewidth=this.linewidth),void 0!==this.dashSize&&(n.dashSize=this.dashSize),void 0!==this.gapSize&&(n.gapSize=this.gapSize),void 0!==this.scale&&(n.scale=this.scale),!0===this.dithering&&(n.dithering=!0),this.alphaTest>0&&(n.alphaTest=this.alphaTest),!0===this.alphaHash&&(n.alphaHash=!0),!0===this.alphaToCoverage&&(n.alphaToCoverage=!0),!0===this.premultipliedAlpha&&(n.premultipliedAlpha=!0),!0===this.forceSinglePass&&(n.forceSinglePass=!0),!0===this.wireframe&&(n.wireframe=!0),this.wireframeLinewidth>1&&(n.wireframeLinewidth=this.wireframeLinewidth),"round"!==this.wireframeLinecap&&(n.wireframeLinecap=this.wireframeLinecap),"round"!==this.wireframeLinejoin&&(n.wireframeLinejoin=this.wireframeLinejoin),!0===this.flatShading&&(n.flatShading=!0),!1===this.visible&&(n.visible=!1),!1===this.toneMapped&&(n.toneMapped=!1),!1===this.fog&&(n.fog=!1),Object.keys(this.userData).length>0&&(n.userData=this.userData),t){const t=i(e.textures),r=i(e.images);t.length>0&&(n.textures=t),r.length>0&&(n.images=r)}return n}clone(){return(new this.constructor).copy(this)}copy(e){this.name=e.name,this.blending=e.blending,this.side=e.side,this.vertexColors=e.vertexColors,this.opacity=e.opacity,this.transparent=e.transparent,this.blendSrc=e.blendSrc,this.blendDst=e.blendDst,this.blendEquation=e.blendEquation,this.blendSrcAlpha=e.blendSrcAlpha,this.blendDstAlpha=e.blendDstAlpha,this.blendEquationAlpha=e.blendEquationAlpha,this.blendColor.copy(e.blendColor),this.blendAlpha=e.blendAlpha,this.depthFunc=e.depthFunc,this.depthTest=e.depthTest,this.depthWrite=e.depthWrite,this.stencilWriteMask=e.stencilWriteMask,this.stencilFunc=e.stencilFunc,this.stencilRef=e.stencilRef,this.stencilFuncMask=e.stencilFuncMask,this.stencilFail=e.stencilFail,this.stencilZFail=e.stencilZFail,this.stencilZPass=e.stencilZPass,this.stencilWrite=e.stencilWrite;const t=e.clippingPlanes;let n=null;if(null!==t){const e=t.length;n=new Array(e);for(let i=0;i!==e;++i)n[i]=t[i].clone()}return this.clippingPlanes=n,this.clipIntersection=e.clipIntersection,this.clipShadows=e.clipShadows,this.shadowSide=e.shadowSide,this.colorWrite=e.colorWrite,this.precision=e.precision,this.polygonOffset=e.polygonOffset,this.polygonOffsetFactor=e.polygonOffsetFactor,this.polygonOffsetUnits=e.polygonOffsetUnits,this.dithering=e.dithering,this.alphaTest=e.alphaTest,this.alphaHash=e.alphaHash,this.alphaToCoverage=e.alphaToCoverage,this.premultipliedAlpha=e.premultipliedAlpha,this.forceSinglePass=e.forceSinglePass,this.visible=e.visible,this.toneMapped=e.toneMapped,this.userData=JSON.parse(JSON.stringify(e.userData)),this}dispose(){this.dispatchEvent({type:"dispose"})}set needsUpdate(e){!0===e&&this.version++}}class Ma extends Ca{constructor(e){super(),this.isMeshBasicMaterial=!0,this.type="MeshBasicMaterial",this.color=new ya(16777215),this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.specularMap=null,this.alphaMap=null,this.envMap=null,this.envMapRotation=new ko,this.combine=0,this.reflectivity=1,this.refractionRatio=.98,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap="round",this.wireframeLinejoin="round",this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.map=e.map,this.lightMap=e.lightMap,this.lightMapIntensity=e.lightMapIntensity,this.aoMap=e.aoMap,this.aoMapIntensity=e.aoMapIntensity,this.specularMap=e.specularMap,this.alphaMap=e.alphaMap,this.envMap=e.envMap,this.envMapRotation.copy(e.envMapRotation),this.combine=e.combine,this.reflectivity=e.reflectivity,this.refractionRatio=e.refractionRatio,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.wireframeLinecap=e.wireframeLinecap,this.wireframeLinejoin=e.wireframeLinejoin,this.fog=e.fog,this}}const Ea=Ta();function Ta(){const e=new ArrayBuffer(4),t=new Float32Array(e),n=new Uint32Array(e),i=new Uint32Array(512),r=new Uint32Array(512);for(let e=0;e<256;++e){const t=e-127;t<-27?(i[e]=0,i[256|e]=32768,r[e]=24,r[256|e]=24):t<-14?(i[e]=1024>>-t-14,i[256|e]=1024>>-t-14|32768,r[e]=-t-1,r[256|e]=-t-1):t<=15?(i[e]=t+15<<10,i[256|e]=t+15<<10|32768,r[e]=13,r[256|e]=13):t<128?(i[e]=31744,i[256|e]=64512,r[e]=24,r[256|e]=24):(i[e]=31744,i[256|e]=64512,r[e]=13,r[256|e]=13)}const s=new Uint32Array(2048),o=new Uint32Array(64),a=new Uint32Array(64);for(let e=1;e<1024;++e){let t=e<<13,n=0;for(;0==(8388608&t);)t<<=1,n-=8388608;t&=-8388609,n+=947912704,s[e]=t|n}for(let e=1024;e<2048;++e)s[e]=939524096+(e-1024<<13);for(let e=1;e<31;++e)o[e]=e<<23;o[31]=1199570944,o[32]=2147483648;for(let e=33;e<63;++e)o[e]=2147483648+(e-32<<23);o[63]=3347054592;for(let e=1;e<64;++e)32!==e&&(a[e]=1024);return{floatView:t,uint32View:n,baseTable:i,shiftTable:r,mantissaTable:s,exponentTable:o,offsetTable:a}}function Sa(e){Math.abs(e)>65504&&console.warn("THREE.DataUtils.toHalfFloat(): Value out of range."),e=vs(e,-65504,65504),Ea.floatView[0]=e;const t=Ea.uint32View[0],n=t>>23&511;return Ea.baseTable[n]+((8388607&t)>>Ea.shiftTable[n])}function Pa(e){const t=e>>10;return Ea.uint32View[0]=Ea.mantissaTable[Ea.offsetTable[t]+(1023&e)]+Ea.exponentTable[t],Ea.floatView[0]}const Na=new Es,Ba=new Cs;let Da=0;class Ia{constructor(e,t,n=!1){if(Array.isArray(e))throw new TypeError("THREE.BufferAttribute: array should be a Typed Array.");this.isBufferAttribute=!0,Object.defineProperty(this,"id",{value:Da++}),this.name="",this.array=e,this.itemSize=t,this.count=void 0!==e?e.length/t:0,this.normalized=n,this.usage=rs,this.updateRanges=[],this.gpuType=Ji,this.version=0}onUploadCallback(){}set needsUpdate(e){!0===e&&this.version++}setUsage(e){return this.usage=e,this}addUpdateRange(e,t){this.updateRanges.push({start:e,count:t})}clearUpdateRanges(){this.updateRanges.length=0}copy(e){return this.name=e.name,this.array=new e.array.constructor(e.array),this.itemSize=e.itemSize,this.count=e.count,this.normalized=e.normalized,this.usage=e.usage,this.gpuType=e.gpuType,this}copyAt(e,t,n){e*=this.itemSize,n*=t.itemSize;for(let i=0,r=this.itemSize;i<r;i++)this.array[e+i]=t.array[n+i];return this}copyArray(e){return this.array.set(e),this}applyMatrix3(e){if(2===this.itemSize)for(let t=0,n=this.count;t<n;t++)Ba.fromBufferAttribute(this,t),Ba.applyMatrix3(e),this.setXY(t,Ba.x,Ba.y);else if(3===this.itemSize)for(let t=0,n=this.count;t<n;t++)Na.fromBufferAttribute(this,t),Na.applyMatrix3(e),this.setXYZ(t,Na.x,Na.y,Na.z);return this}applyMatrix4(e){for(let t=0,n=this.count;t<n;t++)Na.fromBufferAttribute(this,t),Na.applyMatrix4(e),this.setXYZ(t,Na.x,Na.y,Na.z);return this}applyNormalMatrix(e){for(let t=0,n=this.count;t<n;t++)Na.fromBufferAttribute(this,t),Na.applyNormalMatrix(e),this.setXYZ(t,Na.x,Na.y,Na.z);return this}transformDirection(e){for(let t=0,n=this.count;t<n;t++)Na.fromBufferAttribute(this,t),Na.transformDirection(e),this.setXYZ(t,Na.x,Na.y,Na.z);return this}set(e,t=0){return this.array.set(e,t),this}getComponent(e,t){let n=this.array[e*this.itemSize+t];return this.normalized&&(n=ys(n,this.array)),n}setComponent(e,t,n){return this.normalized&&(n=bs(n,this.array)),this.array[e*this.itemSize+t]=n,this}getX(e){let t=this.array[e*this.itemSize];return this.normalized&&(t=ys(t,this.array)),t}setX(e,t){return this.normalized&&(t=bs(t,this.array)),this.array[e*this.itemSize]=t,this}getY(e){let t=this.array[e*this.itemSize+1];return this.normalized&&(t=ys(t,this.array)),t}setY(e,t){return this.normalized&&(t=bs(t,this.array)),this.array[e*this.itemSize+1]=t,this}getZ(e){let t=this.array[e*this.itemSize+2];return this.normalized&&(t=ys(t,this.array)),t}setZ(e,t){return this.normalized&&(t=bs(t,this.array)),this.array[e*this.itemSize+2]=t,this}getW(e){let t=this.array[e*this.itemSize+3];return this.normalized&&(t=ys(t,this.array)),t}setW(e,t){return this.normalized&&(t=bs(t,this.array)),this.array[e*this.itemSize+3]=t,this}setXY(e,t,n){return e*=this.itemSize,this.normalized&&(t=bs(t,this.array),n=bs(n,this.array)),this.array[e+0]=t,this.array[e+1]=n,this}setXYZ(e,t,n,i){return e*=this.itemSize,this.normalized&&(t=bs(t,this.array),n=bs(n,this.array),i=bs(i,this.array)),this.array[e+0]=t,this.array[e+1]=n,this.array[e+2]=i,this}setXYZW(e,t,n,i,r){return e*=this.itemSize,this.normalized&&(t=bs(t,this.array),n=bs(n,this.array),i=bs(i,this.array),r=bs(r,this.array)),this.array[e+0]=t,this.array[e+1]=n,this.array[e+2]=i,this.array[e+3]=r,this}onUpload(e){return this.onUploadCallback=e,this}clone(){return new this.constructor(this.array,this.itemSize).copy(this)}toJSON(){const e={itemSize:this.itemSize,type:this.array.constructor.name,array:Array.from(this.array),normalized:this.normalized};return""!==this.name&&(e.name=this.name),this.usage!==rs&&(e.usage=this.usage),e}}class La extends Ia{constructor(e,t,n){super(new Uint16Array(e),t,n)}}class ja extends Ia{constructor(e,t,n){super(new Uint32Array(e),t,n)}}class Oa extends Ia{constructor(e,t,n){super(new Uint16Array(e),t,n),this.isFloat16BufferAttribute=!0}getX(e){let t=Pa(this.array[e*this.itemSize]);return this.normalized&&(t=ys(t,this.array)),t}setX(e,t){return this.normalized&&(t=bs(t,this.array)),this.array[e*this.itemSize]=Sa(t),this}getY(e){let t=Pa(this.array[e*this.itemSize+1]);return this.normalized&&(t=ys(t,this.array)),t}setY(e,t){return this.normalized&&(t=bs(t,this.array)),this.array[e*this.itemSize+1]=Sa(t),this}getZ(e){let t=Pa(this.array[e*this.itemSize+2]);return this.normalized&&(t=ys(t,this.array)),t}setZ(e,t){return this.normalized&&(t=bs(t,this.array)),this.array[e*this.itemSize+2]=Sa(t),this}getW(e){let t=Pa(this.array[e*this.itemSize+3]);return this.normalized&&(t=ys(t,this.array)),t}setW(e,t){return this.normalized&&(t=bs(t,this.array)),this.array[e*this.itemSize+3]=Sa(t),this}setXY(e,t,n){return e*=this.itemSize,this.normalized&&(t=bs(t,this.array),n=bs(n,this.array)),this.array[e+0]=Sa(t),this.array[e+1]=Sa(n),this}setXYZ(e,t,n,i){return e*=this.itemSize,this.normalized&&(t=bs(t,this.array),n=bs(n,this.array),i=bs(i,this.array)),this.array[e+0]=Sa(t),this.array[e+1]=Sa(n),this.array[e+2]=Sa(i),this}setXYZW(e,t,n,i,r){return e*=this.itemSize,this.normalized&&(t=bs(t,this.array),n=bs(n,this.array),i=bs(i,this.array),r=bs(r,this.array)),this.array[e+0]=Sa(t),this.array[e+1]=Sa(n),this.array[e+2]=Sa(i),this.array[e+3]=Sa(r),this}}class za extends Ia{constructor(e,t,n){super(new Float32Array(e),t,n)}}let Ra=0;const ka=new Po,Fa=new ta,Ha=new Es,Ua=new eo,Xa=new eo,Ga=new Es;class Va extends ds{constructor(){super(),this.isBufferGeometry=!0,Object.defineProperty(this,"id",{value:Ra++}),this.uuid=ms(),this.name="",this.type="BufferGeometry",this.index=null,this.indirect=null,this.attributes={},this.morphAttributes={},this.morphTargetsRelative=!1,this.groups=[],this.boundingBox=null,this.boundingSphere=null,this.drawRange={start:0,count:1/0},this.userData={}}getIndex(){return this.index}setIndex(e){return Array.isArray(e)?this.index=new(Bs(e)?ja:La)(e,1):this.index=e,this}setIndirect(e){return this.indirect=e,this}getIndirect(){return this.indirect}getAttribute(e){return this.attributes[e]}setAttribute(e,t){return this.attributes[e]=t,this}deleteAttribute(e){return delete this.attributes[e],this}hasAttribute(e){return void 0!==this.attributes[e]}addGroup(e,t,n=0){this.groups.push({start:e,count:t,materialIndex:n})}clearGroups(){this.groups=[]}setDrawRange(e,t){this.drawRange.start=e,this.drawRange.count=t}applyMatrix4(e){const t=this.attributes.position;void 0!==t&&(t.applyMatrix4(e),t.needsUpdate=!0);const n=this.attributes.normal;if(void 0!==n){const t=(new Ps).getNormalMatrix(e);n.applyNormalMatrix(t),n.needsUpdate=!0}const i=this.attributes.tangent;return void 0!==i&&(i.transformDirection(e),i.needsUpdate=!0),null!==this.boundingBox&&this.computeBoundingBox(),null!==this.boundingSphere&&this.computeBoundingSphere(),this}applyQuaternion(e){return ka.makeRotationFromQuaternion(e),this.applyMatrix4(ka),this}rotateX(e){return ka.makeRotationX(e),this.applyMatrix4(ka),this}rotateY(e){return ka.makeRotationY(e),this.applyMatrix4(ka),this}rotateZ(e){return ka.makeRotationZ(e),this.applyMatrix4(ka),this}translate(e,t,n){return ka.makeTranslation(e,t,n),this.applyMatrix4(ka),this}scale(e,t,n){return ka.makeScale(e,t,n),this.applyMatrix4(ka),this}lookAt(e){return Fa.lookAt(e),Fa.updateMatrix(),this.applyMatrix4(Fa.matrix),this}center(){return this.computeBoundingBox(),this.boundingBox.getCenter(Ha).negate(),this.translate(Ha.x,Ha.y,Ha.z),this}setFromPoints(e){const t=this.getAttribute("position");if(void 0===t){const t=[];for(let n=0,i=e.length;n<i;n++){const i=e[n];t.push(i.x,i.y,i.z||0)}this.setAttribute("position",new za(t,3))}else{const n=Math.min(e.length,t.count);for(let i=0;i<n;i++){const n=e[i];t.setXYZ(i,n.x,n.y,n.z||0)}e.length>t.count&&console.warn("THREE.BufferGeometry: Buffer size too small for points data. Use .dispose() and create a new geometry."),t.needsUpdate=!0}return this}computeBoundingBox(){null===this.boundingBox&&(this.boundingBox=new eo);const e=this.attributes.position,t=this.morphAttributes.position;if(e&&e.isGLBufferAttribute)return console.error("THREE.BufferGeometry.computeBoundingBox(): GLBufferAttribute requires a manual bounding box.",this),void this.boundingBox.set(new Es(-1/0,-1/0,-1/0),new Es(1/0,1/0,1/0));if(void 0!==e){if(this.boundingBox.setFromBufferAttribute(e),t)for(let e=0,n=t.length;e<n;e++){const n=t[e];Ua.setFromBufferAttribute(n),this.morphTargetsRelative?(Ga.addVectors(this.boundingBox.min,Ua.min),this.boundingBox.expandByPoint(Ga),Ga.addVectors(this.boundingBox.max,Ua.max),this.boundingBox.expandByPoint(Ga)):(this.boundingBox.expandByPoint(Ua.min),this.boundingBox.expandByPoint(Ua.max))}}else this.boundingBox.makeEmpty();(isNaN(this.boundingBox.min.x)||isNaN(this.boundingBox.min.y)||isNaN(this.boundingBox.min.z))&&console.error('THREE.BufferGeometry.computeBoundingBox(): Computed min/max have NaN values. The "position" attribute is likely to have NaN values.',this)}computeBoundingSphere(){null===this.boundingSphere&&(this.boundingSphere=new xo);const e=this.attributes.position,t=this.morphAttributes.position;if(e&&e.isGLBufferAttribute)return console.error("THREE.BufferGeometry.computeBoundingSphere(): GLBufferAttribute requires a manual bounding sphere.",this),void this.boundingSphere.set(new Es,1/0);if(e){const n=this.boundingSphere.center;if(Ua.setFromBufferAttribute(e),t)for(let e=0,n=t.length;e<n;e++){const n=t[e];Xa.setFromBufferAttribute(n),this.morphTargetsRelative?(Ga.addVectors(Ua.min,Xa.min),Ua.expandByPoint(Ga),Ga.addVectors(Ua.max,Xa.max),Ua.expandByPoint(Ga)):(Ua.expandByPoint(Xa.min),Ua.expandByPoint(Xa.max))}Ua.getCenter(n);let i=0;for(let t=0,r=e.count;t<r;t++)Ga.fromBufferAttribute(e,t),i=Math.max(i,n.distanceToSquared(Ga));if(t)for(let r=0,s=t.length;r<s;r++){const s=t[r],o=this.morphTargetsRelative;for(let t=0,r=s.count;t<r;t++)Ga.fromBufferAttribute(s,t),o&&(Ha.fromBufferAttribute(e,t),Ga.add(Ha)),i=Math.max(i,n.distanceToSquared(Ga))}this.boundingSphere.radius=Math.sqrt(i),isNaN(this.boundingSphere.radius)&&console.error('THREE.BufferGeometry.computeBoundingSphere(): Computed radius is NaN. The "position" attribute is likely to have NaN values.',this)}}computeTangents(){const e=this.index,t=this.attributes;if(null===e||void 0===t.position||void 0===t.normal||void 0===t.uv)return void console.error("THREE.BufferGeometry: .computeTangents() failed. Missing required attributes (index, position, normal or uv)");const n=t.position,i=t.normal,r=t.uv;!1===this.hasAttribute("tangent")&&this.setAttribute("tangent",new Ia(new Float32Array(4*n.count),4));const s=this.getAttribute("tangent"),o=[],a=[];for(let e=0;e<n.count;e++)o[e]=new Es,a[e]=new Es;const l=new Es,u=new Es,c=new Es,d=new Cs,h=new Cs,f=new Cs,p=new Es,g=new Es;function m(e,t,i){l.fromBufferAttribute(n,e),u.fromBufferAttribute(n,t),c.fromBufferAttribute(n,i),d.fromBufferAttribute(r,e),h.fromBufferAttribute(r,t),f.fromBufferAttribute(r,i),u.sub(l),c.sub(l),h.sub(d),f.sub(d);const s=1/(h.x*f.y-f.x*h.y);isFinite(s)&&(p.copy(u).multiplyScalar(f.y).addScaledVector(c,-h.y).multiplyScalar(s),g.copy(c).multiplyScalar(h.x).addScaledVector(u,-f.x).multiplyScalar(s),o[e].add(p),o[t].add(p),o[i].add(p),a[e].add(g),a[t].add(g),a[i].add(g))}let v=this.groups;0===v.length&&(v=[{start:0,count:e.count}]);for(let t=0,n=v.length;t<n;++t){const n=v[t],i=n.start;for(let t=i,r=i+n.count;t<r;t+=3)m(e.getX(t+0),e.getX(t+1),e.getX(t+2))}const A=new Es,x=new Es,y=new Es,b=new Es;function w(e){y.fromBufferAttribute(i,e),b.copy(y);const t=o[e];A.copy(t),A.sub(y.multiplyScalar(y.dot(t))).normalize(),x.crossVectors(b,t);const n=x.dot(a[e])<0?-1:1;s.setXYZW(e,A.x,A.y,A.z,n)}for(let t=0,n=v.length;t<n;++t){const n=v[t],i=n.start;for(let t=i,r=i+n.count;t<r;t+=3)w(e.getX(t+0)),w(e.getX(t+1)),w(e.getX(t+2))}}computeVertexNormals(){const e=this.index,t=this.getAttribute("position");if(void 0!==t){let n=this.getAttribute("normal");if(void 0===n)n=new Ia(new Float32Array(3*t.count),3),this.setAttribute("normal",n);else for(let e=0,t=n.count;e<t;e++)n.setXYZ(e,0,0,0);const i=new Es,r=new Es,s=new Es,o=new Es,a=new Es,l=new Es,u=new Es,c=new Es;if(e)for(let d=0,h=e.count;d<h;d+=3){const h=e.getX(d+0),f=e.getX(d+1),p=e.getX(d+2);i.fromBufferAttribute(t,h),r.fromBufferAttribute(t,f),s.fromBufferAttribute(t,p),u.subVectors(s,r),c.subVectors(i,r),u.cross(c),o.fromBufferAttribute(n,h),a.fromBufferAttribute(n,f),l.fromBufferAttribute(n,p),o.add(u),a.add(u),l.add(u),n.setXYZ(h,o.x,o.y,o.z),n.setXYZ(f,a.x,a.y,a.z),n.setXYZ(p,l.x,l.y,l.z)}else for(let e=0,o=t.count;e<o;e+=3)i.fromBufferAttribute(t,e+0),r.fromBufferAttribute(t,e+1),s.fromBufferAttribute(t,e+2),u.subVectors(s,r),c.subVectors(i,r),u.cross(c),n.setXYZ(e+0,u.x,u.y,u.z),n.setXYZ(e+1,u.x,u.y,u.z),n.setXYZ(e+2,u.x,u.y,u.z);this.normalizeNormals(),n.needsUpdate=!0}}normalizeNormals(){const e=this.attributes.normal;for(let t=0,n=e.count;t<n;t++)Ga.fromBufferAttribute(e,t),Ga.normalize(),e.setXYZ(t,Ga.x,Ga.y,Ga.z)}toNonIndexed(){function e(e,t){const n=e.array,i=e.itemSize,r=e.normalized,s=new n.constructor(t.length*i);let o=0,a=0;for(let r=0,l=t.length;r<l;r++){o=e.isInterleavedBufferAttribute?t[r]*e.data.stride+e.offset:t[r]*i;for(let e=0;e<i;e++)s[a++]=n[o++]}return new Ia(s,i,r)}if(null===this.index)return console.warn("THREE.BufferGeometry.toNonIndexed(): BufferGeometry is already non-indexed."),this;const t=new Va,n=this.index.array,i=this.attributes;for(const r in i){const s=e(i[r],n);t.setAttribute(r,s)}const r=this.morphAttributes;for(const i in r){const s=[],o=r[i];for(let t=0,i=o.length;t<i;t++){const i=e(o[t],n);s.push(i)}t.morphAttributes[i]=s}t.morphTargetsRelative=this.morphTargetsRelative;const s=this.groups;for(let e=0,n=s.length;e<n;e++){const n=s[e];t.addGroup(n.start,n.count,n.materialIndex)}return t}toJSON(){const e={metadata:{version:4.7,type:"BufferGeometry",generator:"BufferGeometry.toJSON"}};if(e.uuid=this.uuid,e.type=this.type,""!==this.name&&(e.name=this.name),Object.keys(this.userData).length>0&&(e.userData=this.userData),void 0!==this.parameters){const t=this.parameters;for(const n in t)void 0!==t[n]&&(e[n]=t[n]);return e}e.data={attributes:{}};const t=this.index;null!==t&&(e.data.index={type:t.array.constructor.name,array:Array.prototype.slice.call(t.array)});const n=this.attributes;for(const t in n){const i=n[t];e.data.attributes[t]=i.toJSON(e.data)}const i={};let r=!1;for(const t in this.morphAttributes){const n=this.morphAttributes[t],s=[];for(let t=0,i=n.length;t<i;t++){const i=n[t];s.push(i.toJSON(e.data))}s.length>0&&(i[t]=s,r=!0)}r&&(e.data.morphAttributes=i,e.data.morphTargetsRelative=this.morphTargetsRelative);const s=this.groups;s.length>0&&(e.data.groups=JSON.parse(JSON.stringify(s)));const o=this.boundingSphere;return null!==o&&(e.data.boundingSphere=o.toJSON()),e}clone(){return(new this.constructor).copy(this)}copy(e){this.index=null,this.attributes={},this.morphAttributes={},this.groups=[],this.boundingBox=null,this.boundingSphere=null;const t={};this.name=e.name;const n=e.index;null!==n&&this.setIndex(n.clone());const i=e.attributes;for(const e in i){const n=i[e];this.setAttribute(e,n.clone(t))}const r=e.morphAttributes;for(const e in r){const n=[],i=r[e];for(let e=0,r=i.length;e<r;e++)n.push(i[e].clone(t));this.morphAttributes[e]=n}this.morphTargetsRelative=e.morphTargetsRelative;const s=e.groups;for(let e=0,t=s.length;e<t;e++){const t=s[e];this.addGroup(t.start,t.count,t.materialIndex)}const o=e.boundingBox;null!==o&&(this.boundingBox=o.clone());const a=e.boundingSphere;return null!==a&&(this.boundingSphere=a.clone()),this.drawRange.start=e.drawRange.start,this.drawRange.count=e.drawRange.count,this.userData=e.userData,this}dispose(){this.dispatchEvent({type:"dispose"})}}const Wa=new Po,Qa=new So,Za=new xo,Ya=new Es,Ja=new Es,Ka=new Es,qa=new Es,_a=new Es,$a=new Es,el=new Es,tl=new Es;class nl extends ta{constructor(e=new Va,t=new Ma){super(),this.isMesh=!0,this.type="Mesh",this.geometry=e,this.material=t,this.morphTargetDictionary=void 0,this.morphTargetInfluences=void 0,this.count=1,this.updateMorphTargets()}copy(e,t){return super.copy(e,t),void 0!==e.morphTargetInfluences&&(this.morphTargetInfluences=e.morphTargetInfluences.slice()),void 0!==e.morphTargetDictionary&&(this.morphTargetDictionary=Object.assign({},e.morphTargetDictionary)),this.material=Array.isArray(e.material)?e.material.slice():e.material,this.geometry=e.geometry,this}updateMorphTargets(){const e=this.geometry.morphAttributes,t=Object.keys(e);if(t.length>0){const n=e[t[0]];if(void 0!==n){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,t=n.length;e<t;e++){const t=n[e].name||String(e);this.morphTargetInfluences.push(0),this.morphTargetDictionary[t]=e}}}}getVertexPosition(e,t){const n=this.geometry,i=n.attributes.position,r=n.morphAttributes.position,s=n.morphTargetsRelative;t.fromBufferAttribute(i,e);const o=this.morphTargetInfluences;if(r&&o){$a.set(0,0,0);for(let n=0,i=r.length;n<i;n++){const i=o[n],a=r[n];0!==i&&(_a.fromBufferAttribute(a,e),s?$a.addScaledVector(_a,i):$a.addScaledVector(_a.sub(t),i))}t.add($a)}return t}raycast(e,t){const n=this.geometry,i=this.material,r=this.matrixWorld;if(void 0!==i){if(null===n.boundingSphere&&n.computeBoundingSphere(),Za.copy(n.boundingSphere),Za.applyMatrix4(r),Qa.copy(e.ray).recast(e.near),!1===Za.containsPoint(Qa.origin)){if(null===Qa.intersectSphere(Za,Ya))return;if(Qa.origin.distanceToSquared(Ya)>(e.far-e.near)**2)return}Wa.copy(r).invert(),Qa.copy(e.ray).applyMatrix4(Wa),null!==n.boundingBox&&!1===Qa.intersectsBox(n.boundingBox)||this._computeIntersections(e,t,Qa)}}_computeIntersections(e,t,n){let i;const r=this.geometry,s=this.material,o=r.index,a=r.attributes.position,l=r.attributes.uv,u=r.attributes.uv1,c=r.attributes.normal,d=r.groups,h=r.drawRange;if(null!==o)if(Array.isArray(s))for(let r=0,a=d.length;r<a;r++){const a=d[r],f=s[a.materialIndex];for(let r=Math.max(a.start,h.start),s=Math.min(o.count,Math.min(a.start+a.count,h.start+h.count));r<s;r+=3){i=il(this,f,e,n,l,u,c,o.getX(r),o.getX(r+1),o.getX(r+2)),i&&(i.faceIndex=Math.floor(r/3),i.face.materialIndex=a.materialIndex,t.push(i))}}else{for(let r=Math.max(0,h.start),a=Math.min(o.count,h.start+h.count);r<a;r+=3){i=il(this,s,e,n,l,u,c,o.getX(r),o.getX(r+1),o.getX(r+2)),i&&(i.faceIndex=Math.floor(r/3),t.push(i))}}else if(void 0!==a)if(Array.isArray(s))for(let r=0,o=d.length;r<o;r++){const o=d[r],f=s[o.materialIndex];for(let r=Math.max(o.start,h.start),s=Math.min(a.count,Math.min(o.start+o.count,h.start+h.count));r<s;r+=3){i=il(this,f,e,n,l,u,c,r,r+1,r+2),i&&(i.faceIndex=Math.floor(r/3),i.face.materialIndex=o.materialIndex,t.push(i))}}else{for(let r=Math.max(0,h.start),o=Math.min(a.count,h.start+h.count);r<o;r+=3){i=il(this,s,e,n,l,u,c,r,r+1,r+2),i&&(i.faceIndex=Math.floor(r/3),t.push(i))}}}}function il(e,t,n,i,r,s,o,a,l,u){e.getVertexPosition(a,Ja),e.getVertexPosition(l,Ka),e.getVertexPosition(u,qa);const c=function(e,t,n,i,r,s,o,a){let l;if(l=1===t.side?i.intersectTriangle(o,s,r,!0,a):i.intersectTriangle(r,s,o,0===t.side,a),null===l)return null;tl.copy(a),tl.applyMatrix4(e.matrixWorld);const u=n.ray.origin.distanceTo(tl);return u<n.near||u>n.far?null:{distance:u,point:tl.clone(),object:e}}(e,t,n,i,Ja,Ka,qa,el);if(c){const e=new Es;ga.getBarycoord(el,Ja,Ka,qa,e),r&&(c.uv=ga.getInterpolatedAttribute(r,a,l,u,e,new Cs)),s&&(c.uv1=ga.getInterpolatedAttribute(s,a,l,u,e,new Cs)),o&&(c.normal=ga.getInterpolatedAttribute(o,a,l,u,e,new Es),c.normal.dot(i.direction)>0&&c.normal.multiplyScalar(-1));const t={a:a,b:l,c:u,normal:new Es,materialIndex:0};ga.getNormal(Ja,Ka,qa,t.normal),c.face=t,c.barycoord=e}return c}class rl extends Va{constructor(e=1,t=1,n=1,i=1,r=1,s=1){super(),this.type="BoxGeometry",this.parameters={width:e,height:t,depth:n,widthSegments:i,heightSegments:r,depthSegments:s};const o=this;i=Math.floor(i),r=Math.floor(r),s=Math.floor(s);const a=[],l=[],u=[],c=[];let d=0,h=0;function f(e,t,n,i,r,s,f,p,g,m,v){const A=s/g,x=f/m,y=s/2,b=f/2,w=p/2,C=g+1,M=m+1;let E=0,T=0;const S=new Es;for(let s=0;s<M;s++){const o=s*x-b;for(let a=0;a<C;a++){const d=a*A-y;S[e]=d*i,S[t]=o*r,S[n]=w,l.push(S.x,S.y,S.z),S[e]=0,S[t]=0,S[n]=p>0?1:-1,u.push(S.x,S.y,S.z),c.push(a/g),c.push(1-s/m),E+=1}}for(let e=0;e<m;e++)for(let t=0;t<g;t++){const n=d+t+C*e,i=d+t+C*(e+1),r=d+(t+1)+C*(e+1),s=d+(t+1)+C*e;a.push(n,i,s),a.push(i,r,s),T+=6}o.addGroup(h,T,v),h+=T,d+=E}f("z","y","x",-1,-1,n,t,e,s,r,0),f("z","y","x",1,-1,n,t,-e,s,r,1),f("x","z","y",1,1,e,n,t,i,s,2),f("x","z","y",1,-1,e,n,-t,i,s,3),f("x","y","z",1,-1,e,t,n,i,r,4),f("x","y","z",-1,-1,e,t,-n,i,r,5),this.setIndex(a),this.setAttribute("position",new za(l,3)),this.setAttribute("normal",new za(u,3)),this.setAttribute("uv",new za(c,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new rl(e.width,e.height,e.depth,e.widthSegments,e.heightSegments,e.depthSegments)}}function sl(e){const t={};for(const n in e){t[n]={};for(const i in e[n]){const r=e[n][i];r&&(r.isColor||r.isMatrix3||r.isMatrix4||r.isVector2||r.isVector3||r.isVector4||r.isTexture||r.isQuaternion)?r.isRenderTargetTexture?(console.warn("UniformsUtils: Textures of render targets cannot be cloned via cloneUniforms() or mergeUniforms()."),t[n][i]=null):t[n][i]=r.clone():Array.isArray(r)?t[n][i]=r.slice():t[n][i]=r}}return t}function ol(e){const t={};for(let n=0;n<e.length;n++){const i=sl(e[n]);for(const e in i)t[e]=i[e]}return t}function al(e){const t=e.getRenderTarget();return null===t?e.outputColorSpace:!0===t.isXRRenderTarget?t.texture.colorSpace:ks.workingColorSpace}const ll={clone:sl,merge:ol};class ul extends Ca{constructor(e){super(),this.isShaderMaterial=!0,this.type="ShaderMaterial",this.defines={},this.uniforms={},this.uniformsGroups=[],this.vertexShader="void main() {\n\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\n}",this.fragmentShader="void main() {\n\tgl_FragColor = vec4( 1.0, 0.0, 0.0, 1.0 );\n}",this.linewidth=1,this.wireframe=!1,this.wireframeLinewidth=1,this.fog=!1,this.lights=!1,this.clipping=!1,this.forceSinglePass=!0,this.extensions={clipCullDistance:!1,multiDraw:!1},this.defaultAttributeValues={color:[1,1,1],uv:[0,0],uv1:[0,0]},this.index0AttributeName=void 0,this.uniformsNeedUpdate=!1,this.glslVersion=null,void 0!==e&&this.setValues(e)}copy(e){return super.copy(e),this.fragmentShader=e.fragmentShader,this.vertexShader=e.vertexShader,this.uniforms=sl(e.uniforms),this.uniformsGroups=function(e){const t=[];for(let n=0;n<e.length;n++)t.push(e[n].clone());return t}(e.uniformsGroups),this.defines=Object.assign({},e.defines),this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.fog=e.fog,this.lights=e.lights,this.clipping=e.clipping,this.extensions=Object.assign({},e.extensions),this.glslVersion=e.glslVersion,this}toJSON(e){const t=super.toJSON(e);t.glslVersion=this.glslVersion,t.uniforms={};for(const n in this.uniforms){const i=this.uniforms[n].value;i&&i.isTexture?t.uniforms[n]={type:"t",value:i.toJSON(e).uuid}:i&&i.isColor?t.uniforms[n]={type:"c",value:i.getHex()}:i&&i.isVector2?t.uniforms[n]={type:"v2",value:i.toArray()}:i&&i.isVector3?t.uniforms[n]={type:"v3",value:i.toArray()}:i&&i.isVector4?t.uniforms[n]={type:"v4",value:i.toArray()}:i&&i.isMatrix3?t.uniforms[n]={type:"m3",value:i.toArray()}:i&&i.isMatrix4?t.uniforms[n]={type:"m4",value:i.toArray()}:t.uniforms[n]={value:i}}Object.keys(this.defines).length>0&&(t.defines=this.defines),t.vertexShader=this.vertexShader,t.fragmentShader=this.fragmentShader,t.lights=this.lights,t.clipping=this.clipping;const n={};for(const e in this.extensions)!0===this.extensions[e]&&(n[e]=!0);return Object.keys(n).length>0&&(t.extensions=n),t}}class cl extends ta{constructor(){super(),this.isCamera=!0,this.type="Camera",this.matrixWorldInverse=new Po,this.projectionMatrix=new Po,this.projectionMatrixInverse=new Po,this.coordinateSystem=as,this._reversedDepth=!1}get reversedDepth(){return this._reversedDepth}copy(e,t){return super.copy(e,t),this.matrixWorldInverse.copy(e.matrixWorldInverse),this.projectionMatrix.copy(e.projectionMatrix),this.projectionMatrixInverse.copy(e.projectionMatrixInverse),this.coordinateSystem=e.coordinateSystem,this}getWorldDirection(e){return super.getWorldDirection(e).negate()}updateMatrixWorld(e){super.updateMatrixWorld(e),this.matrixWorldInverse.copy(this.matrixWorld).invert()}updateWorldMatrix(e,t){super.updateWorldMatrix(e,t),this.matrixWorldInverse.copy(this.matrixWorld).invert()}clone(){return(new this.constructor).copy(this)}}const dl=new Es,hl=new Cs,fl=new Cs;class pl extends cl{constructor(e=50,t=1,n=.1,i=2e3){super(),this.isPerspectiveCamera=!0,this.type="PerspectiveCamera",this.fov=e,this.zoom=1,this.near=n,this.far=i,this.focus=10,this.aspect=t,this.view=null,this.filmGauge=35,this.filmOffset=0,this.updateProjectionMatrix()}copy(e,t){return super.copy(e,t),this.fov=e.fov,this.zoom=e.zoom,this.near=e.near,this.far=e.far,this.focus=e.focus,this.aspect=e.aspect,this.view=null===e.view?null:Object.assign({},e.view),this.filmGauge=e.filmGauge,this.filmOffset=e.filmOffset,this}setFocalLength(e){const t=.5*this.getFilmHeight()/e;this.fov=2*gs*Math.atan(t),this.updateProjectionMatrix()}getFocalLength(){const e=Math.tan(.5*ps*this.fov);return.5*this.getFilmHeight()/e}getEffectiveFOV(){return 2*gs*Math.atan(Math.tan(.5*ps*this.fov)/this.zoom)}getFilmWidth(){return this.filmGauge*Math.min(this.aspect,1)}getFilmHeight(){return this.filmGauge/Math.max(this.aspect,1)}getViewBounds(e,t,n){dl.set(-1,-1,.5).applyMatrix4(this.projectionMatrixInverse),t.set(dl.x,dl.y).multiplyScalar(-e/dl.z),dl.set(1,1,.5).applyMatrix4(this.projectionMatrixInverse),n.set(dl.x,dl.y).multiplyScalar(-e/dl.z)}getViewSize(e,t){return this.getViewBounds(e,hl,fl),t.subVectors(fl,hl)}setViewOffset(e,t,n,i,r,s){this.aspect=e/t,null===this.view&&(this.view={enabled:!0,fullWidth:1,fullHeight:1,offsetX:0,offsetY:0,width:1,height:1}),this.view.enabled=!0,this.view.fullWidth=e,this.view.fullHeight=t,this.view.offsetX=n,this.view.offsetY=i,this.view.width=r,this.view.height=s,this.updateProjectionMatrix()}clearViewOffset(){null!==this.view&&(this.view.enabled=!1),this.updateProjectionMatrix()}updateProjectionMatrix(){const e=this.near;let t=e*Math.tan(.5*ps*this.fov)/this.zoom,n=2*t,i=this.aspect*n,r=-.5*i;const s=this.view;if(null!==this.view&&this.view.enabled){const e=s.fullWidth,o=s.fullHeight;r+=s.offsetX*i/e,t-=s.offsetY*n/o,i*=s.width/e,n*=s.height/o}const o=this.filmOffset;0!==o&&(r+=e*o/this.getFilmWidth()),this.projectionMatrix.makePerspective(r,r+i,t,t-n,e,this.far,this.coordinateSystem,this.reversedDepth),this.projectionMatrixInverse.copy(this.projectionMatrix).invert()}toJSON(e){const t=super.toJSON(e);return t.object.fov=this.fov,t.object.zoom=this.zoom,t.object.near=this.near,t.object.far=this.far,t.object.focus=this.focus,t.object.aspect=this.aspect,null!==this.view&&(t.object.view=Object.assign({},this.view)),t.object.filmGauge=this.filmGauge,t.object.filmOffset=this.filmOffset,t}}const gl=-90;class ml extends ta{constructor(e,t,n){super(),this.type="CubeCamera",this.renderTarget=n,this.coordinateSystem=null,this.activeMipmapLevel=0;const i=new pl(gl,1,e,t);i.layers=this.layers,this.add(i);const r=new pl(gl,1,e,t);r.layers=this.layers,this.add(r);const s=new pl(gl,1,e,t);s.layers=this.layers,this.add(s);const o=new pl(gl,1,e,t);o.layers=this.layers,this.add(o);const a=new pl(gl,1,e,t);a.layers=this.layers,this.add(a);const l=new pl(gl,1,e,t);l.layers=this.layers,this.add(l)}updateCoordinateSystem(){const e=this.coordinateSystem,t=this.children.concat(),[n,i,r,s,o,a]=t;for(const e of t)this.remove(e);if(e===as)n.up.set(0,1,0),n.lookAt(1,0,0),i.up.set(0,1,0),i.lookAt(-1,0,0),r.up.set(0,0,-1),r.lookAt(0,1,0),s.up.set(0,0,1),s.lookAt(0,-1,0),o.up.set(0,1,0),o.lookAt(0,0,1),a.up.set(0,1,0),a.lookAt(0,0,-1);else{if(e!==ls)throw new Error("THREE.CubeCamera.updateCoordinateSystem(): Invalid coordinate system: "+e);n.up.set(0,-1,0),n.lookAt(-1,0,0),i.up.set(0,-1,0),i.lookAt(1,0,0),r.up.set(0,0,1),r.lookAt(0,1,0),s.up.set(0,0,-1),s.lookAt(0,-1,0),o.up.set(0,-1,0),o.lookAt(0,0,1),a.up.set(0,-1,0),a.lookAt(0,0,-1)}for(const e of t)this.add(e),e.updateMatrixWorld()}update(e,t){null===this.parent&&this.updateMatrixWorld();const{renderTarget:n,activeMipmapLevel:i}=this;this.coordinateSystem!==e.coordinateSystem&&(this.coordinateSystem=e.coordinateSystem,this.updateCoordinateSystem());const[r,s,o,a,l,u]=this.children,c=e.getRenderTarget(),d=e.getActiveCubeFace(),h=e.getActiveMipmapLevel(),f=e.xr.enabled;e.xr.enabled=!1;const p=n.texture.generateMipmaps;n.texture.generateMipmaps=!1,e.setRenderTarget(n,0,i),e.render(t,r),e.setRenderTarget(n,1,i),e.render(t,s),e.setRenderTarget(n,2,i),e.render(t,o),e.setRenderTarget(n,3,i),e.render(t,a),e.setRenderTarget(n,4,i),e.render(t,l),n.texture.generateMipmaps=p,e.setRenderTarget(n,5,i),e.render(t,u),e.setRenderTarget(c,d,h),e.xr.enabled=f,n.texture.needsPMREMUpdate=!0}}class vl extends Ys{constructor(e=[],t=301,n,i,r,s,o,a,l,u){super(e,t,n,i,r,s,o,a,l,u),this.isCubeTexture=!0,this.flipY=!1}get images(){return this.image}set images(e){this.image=e}}class Al extends qs{constructor(e=1,t={}){super(e,e,t),this.isWebGLCubeRenderTarget=!0;const n={width:e,height:e,depth:1},i=[n,n,n,n,n,n];this.texture=new vl(i),this._setTextureOptions(t),this.texture.isRenderTargetTexture=!0}fromEquirectangularTexture(e,t){this.texture.type=t.type,this.texture.colorSpace=t.colorSpace,this.texture.generateMipmaps=t.generateMipmaps,this.texture.minFilter=t.minFilter,this.texture.magFilter=t.magFilter;const n={uniforms:{tEquirect:{value:null}},vertexShader:"\n\n\t\t\t\tvarying vec3 vWorldDirection;\n\n\t\t\t\tvec3 transformDirection( in vec3 dir, in mat4 matrix ) {\n\n\t\t\t\t\treturn normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );\n\n\t\t\t\t}\n\n\t\t\t\tvoid main() {\n\n\t\t\t\t\tvWorldDirection = transformDirection( position, modelMatrix );\n\n\t\t\t\t\t#include <begin_vertex>\n\t\t\t\t\t#include <project_vertex>\n\n\t\t\t\t}\n\t\t\t",fragmentShader:"\n\n\t\t\t\tuniform sampler2D tEquirect;\n\n\t\t\t\tvarying vec3 vWorldDirection;\n\n\t\t\t\t#include <common>\n\n\t\t\t\tvoid main() {\n\n\t\t\t\t\tvec3 direction = normalize( vWorldDirection );\n\n\t\t\t\t\tvec2 sampleUV = equirectUv( direction );\n\n\t\t\t\t\tgl_FragColor = texture2D( tEquirect, sampleUV );\n\n\t\t\t\t}\n\t\t\t"},i=new rl(5,5,5),r=new ul({name:"CubemapFromEquirect",uniforms:sl(n.uniforms),vertexShader:n.vertexShader,fragmentShader:n.fragmentShader,side:1,blending:0});r.uniforms.tEquirect.value=t;const s=new nl(i,r),o=t.minFilter;t.minFilter===Xi&&(t.minFilter=Hi);return new ml(1,10,this).update(e,s),t.minFilter=o,s.geometry.dispose(),s.material.dispose(),this}clear(e,t=!0,n=!0,i=!0){const r=e.getRenderTarget();for(let r=0;r<6;r++)e.setRenderTarget(this,r),e.clear(t,n,i);e.setRenderTarget(r)}}class xl extends ta{constructor(){super(),this.isGroup=!0,this.type="Group"}}const yl={type:"move"};class bl{constructor(){this._targetRay=null,this._grip=null,this._hand=null}getHandSpace(){return null===this._hand&&(this._hand=new xl,this._hand.matrixAutoUpdate=!1,this._hand.visible=!1,this._hand.joints={},this._hand.inputState={pinching:!1}),this._hand}getTargetRaySpace(){return null===this._targetRay&&(this._targetRay=new xl,this._targetRay.matrixAutoUpdate=!1,this._targetRay.visible=!1,this._targetRay.hasLinearVelocity=!1,this._targetRay.linearVelocity=new Es,this._targetRay.hasAngularVelocity=!1,this._targetRay.angularVelocity=new Es),this._targetRay}getGripSpace(){return null===this._grip&&(this._grip=new xl,this._grip.matrixAutoUpdate=!1,this._grip.visible=!1,this._grip.hasLinearVelocity=!1,this._grip.linearVelocity=new Es,this._grip.hasAngularVelocity=!1,this._grip.angularVelocity=new Es),this._grip}dispatchEvent(e){return null!==this._targetRay&&this._targetRay.dispatchEvent(e),null!==this._grip&&this._grip.dispatchEvent(e),null!==this._hand&&this._hand.dispatchEvent(e),this}connect(e){if(e&&e.hand){const t=this._hand;if(t)for(const n of e.hand.values())this._getHandJoint(t,n)}return this.dispatchEvent({type:"connected",data:e}),this}disconnect(e){return this.dispatchEvent({type:"disconnected",data:e}),null!==this._targetRay&&(this._targetRay.visible=!1),null!==this._grip&&(this._grip.visible=!1),null!==this._hand&&(this._hand.visible=!1),this}update(e,t,n){let i=null,r=null,s=null;const o=this._targetRay,a=this._grip,l=this._hand;if(e&&"visible-blurred"!==t.session.visibilityState){if(l&&e.hand){s=!0;for(const i of e.hand.values()){const e=t.getJointPose(i,n),r=this._getHandJoint(l,i);null!==e&&(r.matrix.fromArray(e.transform.matrix),r.matrix.decompose(r.position,r.rotation,r.scale),r.matrixWorldNeedsUpdate=!0,r.jointRadius=e.radius),r.visible=null!==e}const i=l.joints["index-finger-tip"],r=l.joints["thumb-tip"],o=i.position.distanceTo(r.position),a=.02,u=.005;l.inputState.pinching&&o>a+u?(l.inputState.pinching=!1,this.dispatchEvent({type:"pinchend",handedness:e.handedness,target:this})):!l.inputState.pinching&&o<=a-u&&(l.inputState.pinching=!0,this.dispatchEvent({type:"pinchstart",handedness:e.handedness,target:this}))}else null!==a&&e.gripSpace&&(r=t.getPose(e.gripSpace,n),null!==r&&(a.matrix.fromArray(r.transform.matrix),a.matrix.decompose(a.position,a.rotation,a.scale),a.matrixWorldNeedsUpdate=!0,r.linearVelocity?(a.hasLinearVelocity=!0,a.linearVelocity.copy(r.linearVelocity)):a.hasLinearVelocity=!1,r.angularVelocity?(a.hasAngularVelocity=!0,a.angularVelocity.copy(r.angularVelocity)):a.hasAngularVelocity=!1));null!==o&&(i=t.getPose(e.targetRaySpace,n),null===i&&null!==r&&(i=r),null!==i&&(o.matrix.fromArray(i.transform.matrix),o.matrix.decompose(o.position,o.rotation,o.scale),o.matrixWorldNeedsUpdate=!0,i.linearVelocity?(o.hasLinearVelocity=!0,o.linearVelocity.copy(i.linearVelocity)):o.hasLinearVelocity=!1,i.angularVelocity?(o.hasAngularVelocity=!0,o.angularVelocity.copy(i.angularVelocity)):o.hasAngularVelocity=!1,this.dispatchEvent(yl)))}return null!==o&&(o.visible=null!==i),null!==a&&(a.visible=null!==r),null!==l&&(l.visible=null!==s),this}_getHandJoint(e,t){if(void 0===e.joints[t.jointName]){const n=new xl;n.matrixAutoUpdate=!1,n.visible=!1,e.joints[t.jointName]=n,e.add(n)}return e.joints[t.jointName]}}class wl extends ta{constructor(){super(),this.isScene=!0,this.type="Scene",this.background=null,this.environment=null,this.fog=null,this.backgroundBlurriness=0,this.backgroundIntensity=1,this.backgroundRotation=new ko,this.environmentIntensity=1,this.environmentRotation=new ko,this.overrideMaterial=null,"undefined"!=typeof __THREE_DEVTOOLS__&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent("observe",{detail:this}))}copy(e,t){return super.copy(e,t),null!==e.background&&(this.background=e.background.clone()),null!==e.environment&&(this.environment=e.environment.clone()),null!==e.fog&&(this.fog=e.fog.clone()),this.backgroundBlurriness=e.backgroundBlurriness,this.backgroundIntensity=e.backgroundIntensity,this.backgroundRotation.copy(e.backgroundRotation),this.environmentIntensity=e.environmentIntensity,this.environmentRotation.copy(e.environmentRotation),null!==e.overrideMaterial&&(this.overrideMaterial=e.overrideMaterial.clone()),this.matrixAutoUpdate=e.matrixAutoUpdate,this}toJSON(e){const t=super.toJSON(e);return null!==this.fog&&(t.object.fog=this.fog.toJSON()),this.backgroundBlurriness>0&&(t.object.backgroundBlurriness=this.backgroundBlurriness),1!==this.backgroundIntensity&&(t.object.backgroundIntensity=this.backgroundIntensity),t.object.backgroundRotation=this.backgroundRotation.toArray(),1!==this.environmentIntensity&&(t.object.environmentIntensity=this.environmentIntensity),t.object.environmentRotation=this.environmentRotation.toArray(),t}}class Cl{constructor(e,t){this.isInterleavedBuffer=!0,this.array=e,this.stride=t,this.count=void 0!==e?e.length/t:0,this.usage=rs,this.updateRanges=[],this.version=0,this.uuid=ms()}onUploadCallback(){}set needsUpdate(e){!0===e&&this.version++}setUsage(e){return this.usage=e,this}addUpdateRange(e,t){this.updateRanges.push({start:e,count:t})}clearUpdateRanges(){this.updateRanges.length=0}copy(e){return this.array=new e.array.constructor(e.array),this.count=e.count,this.stride=e.stride,this.usage=e.usage,this}copyAt(e,t,n){e*=this.stride,n*=t.stride;for(let i=0,r=this.stride;i<r;i++)this.array[e+i]=t.array[n+i];return this}set(e,t=0){return this.array.set(e,t),this}clone(e){void 0===e.arrayBuffers&&(e.arrayBuffers={}),void 0===this.array.buffer._uuid&&(this.array.buffer._uuid=ms()),void 0===e.arrayBuffers[this.array.buffer._uuid]&&(e.arrayBuffers[this.array.buffer._uuid]=this.array.slice(0).buffer);const t=new this.array.constructor(e.arrayBuffers[this.array.buffer._uuid]),n=new this.constructor(t,this.stride);return n.setUsage(this.usage),n}onUpload(e){return this.onUploadCallback=e,this}toJSON(e){return void 0===e.arrayBuffers&&(e.arrayBuffers={}),void 0===this.array.buffer._uuid&&(this.array.buffer._uuid=ms()),void 0===e.arrayBuffers[this.array.buffer._uuid]&&(e.arrayBuffers[this.array.buffer._uuid]=Array.from(new Uint32Array(this.array.buffer))),{uuid:this.uuid,buffer:this.array.buffer._uuid,type:this.array.constructor.name,stride:this.stride}}}const Ml=new Es;class El{constructor(e,t,n,i=!1){this.isInterleavedBufferAttribute=!0,this.name="",this.data=e,this.itemSize=t,this.offset=n,this.normalized=i}get count(){return this.data.count}get array(){return this.data.array}set needsUpdate(e){this.data.needsUpdate=e}applyMatrix4(e){for(let t=0,n=this.data.count;t<n;t++)Ml.fromBufferAttribute(this,t),Ml.applyMatrix4(e),this.setXYZ(t,Ml.x,Ml.y,Ml.z);return this}applyNormalMatrix(e){for(let t=0,n=this.count;t<n;t++)Ml.fromBufferAttribute(this,t),Ml.applyNormalMatrix(e),this.setXYZ(t,Ml.x,Ml.y,Ml.z);return this}transformDirection(e){for(let t=0,n=this.count;t<n;t++)Ml.fromBufferAttribute(this,t),Ml.transformDirection(e),this.setXYZ(t,Ml.x,Ml.y,Ml.z);return this}getComponent(e,t){let n=this.array[e*this.data.stride+this.offset+t];return this.normalized&&(n=ys(n,this.array)),n}setComponent(e,t,n){return this.normalized&&(n=bs(n,this.array)),this.data.array[e*this.data.stride+this.offset+t]=n,this}setX(e,t){return this.normalized&&(t=bs(t,this.array)),this.data.array[e*this.data.stride+this.offset]=t,this}setY(e,t){return this.normalized&&(t=bs(t,this.array)),this.data.array[e*this.data.stride+this.offset+1]=t,this}setZ(e,t){return this.normalized&&(t=bs(t,this.array)),this.data.array[e*this.data.stride+this.offset+2]=t,this}setW(e,t){return this.normalized&&(t=bs(t,this.array)),this.data.array[e*this.data.stride+this.offset+3]=t,this}getX(e){let t=this.data.array[e*this.data.stride+this.offset];return this.normalized&&(t=ys(t,this.array)),t}getY(e){let t=this.data.array[e*this.data.stride+this.offset+1];return this.normalized&&(t=ys(t,this.array)),t}getZ(e){let t=this.data.array[e*this.data.stride+this.offset+2];return this.normalized&&(t=ys(t,this.array)),t}getW(e){let t=this.data.array[e*this.data.stride+this.offset+3];return this.normalized&&(t=ys(t,this.array)),t}setXY(e,t,n){return e=e*this.data.stride+this.offset,this.normalized&&(t=bs(t,this.array),n=bs(n,this.array)),this.data.array[e+0]=t,this.data.array[e+1]=n,this}setXYZ(e,t,n,i){return e=e*this.data.stride+this.offset,this.normalized&&(t=bs(t,this.array),n=bs(n,this.array),i=bs(i,this.array)),this.data.array[e+0]=t,this.data.array[e+1]=n,this.data.array[e+2]=i,this}setXYZW(e,t,n,i,r){return e=e*this.data.stride+this.offset,this.normalized&&(t=bs(t,this.array),n=bs(n,this.array),i=bs(i,this.array),r=bs(r,this.array)),this.data.array[e+0]=t,this.data.array[e+1]=n,this.data.array[e+2]=i,this.data.array[e+3]=r,this}clone(e){if(void 0===e){console.log("THREE.InterleavedBufferAttribute.clone(): Cloning an interleaved buffer attribute will de-interleave buffer data.");const e=[];for(let t=0;t<this.count;t++){const n=t*this.data.stride+this.offset;for(let t=0;t<this.itemSize;t++)e.push(this.data.array[n+t])}return new Ia(new this.array.constructor(e),this.itemSize,this.normalized)}return void 0===e.interleavedBuffers&&(e.interleavedBuffers={}),void 0===e.interleavedBuffers[this.data.uuid]&&(e.interleavedBuffers[this.data.uuid]=this.data.clone(e)),new El(e.interleavedBuffers[this.data.uuid],this.itemSize,this.offset,this.normalized)}toJSON(e){if(void 0===e){console.log("THREE.InterleavedBufferAttribute.toJSON(): Serializing an interleaved buffer attribute will de-interleave buffer data.");const e=[];for(let t=0;t<this.count;t++){const n=t*this.data.stride+this.offset;for(let t=0;t<this.itemSize;t++)e.push(this.data.array[n+t])}return{itemSize:this.itemSize,type:this.array.constructor.name,array:e,normalized:this.normalized}}return void 0===e.interleavedBuffers&&(e.interleavedBuffers={}),void 0===e.interleavedBuffers[this.data.uuid]&&(e.interleavedBuffers[this.data.uuid]=this.data.toJSON(e)),{isInterleavedBufferAttribute:!0,itemSize:this.itemSize,data:this.data.uuid,offset:this.offset,normalized:this.normalized}}}class Tl extends Ca{constructor(e){super(),this.isSpriteMaterial=!0,this.type="SpriteMaterial",this.color=new ya(16777215),this.map=null,this.alphaMap=null,this.rotation=0,this.sizeAttenuation=!0,this.transparent=!0,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.map=e.map,this.alphaMap=e.alphaMap,this.rotation=e.rotation,this.sizeAttenuation=e.sizeAttenuation,this.fog=e.fog,this}}class Sl extends Ys{constructor(e=null,t=1,n=1,i,r,s,o,a,l=1003,u=1003,c,d){super(null,s,o,a,l,u,i,r,c,d),this.isDataTexture=!0,this.image={data:e,width:t,height:n},this.generateMipmaps=!1,this.flipY=!1,this.unpackAlignment=1}}class Pl extends Ia{constructor(e,t,n,i=1){super(e,t,n),this.isInstancedBufferAttribute=!0,this.meshPerAttribute=i}copy(e){return super.copy(e),this.meshPerAttribute=e.meshPerAttribute,this}toJSON(){const e=super.toJSON();return e.meshPerAttribute=this.meshPerAttribute,e.isInstancedBufferAttribute=!0,e}}const Nl=new Es,Bl=new Es,Dl=new Ps;class Il{constructor(e=new Es(1,0,0),t=0){this.isPlane=!0,this.normal=e,this.constant=t}set(e,t){return this.normal.copy(e),this.constant=t,this}setComponents(e,t,n,i){return this.normal.set(e,t,n),this.constant=i,this}setFromNormalAndCoplanarPoint(e,t){return this.normal.copy(e),this.constant=-t.dot(this.normal),this}setFromCoplanarPoints(e,t,n){const i=Nl.subVectors(n,t).cross(Bl.subVectors(e,t)).normalize();return this.setFromNormalAndCoplanarPoint(i,e),this}copy(e){return this.normal.copy(e.normal),this.constant=e.constant,this}normalize(){const e=1/this.normal.length();return this.normal.multiplyScalar(e),this.constant*=e,this}negate(){return this.constant*=-1,this.normal.negate(),this}distanceToPoint(e){return this.normal.dot(e)+this.constant}distanceToSphere(e){return this.distanceToPoint(e.center)-e.radius}projectPoint(e,t){return t.copy(e).addScaledVector(this.normal,-this.distanceToPoint(e))}intersectLine(e,t){const n=e.delta(Nl),i=this.normal.dot(n);if(0===i)return 0===this.distanceToPoint(e.start)?t.copy(e.start):null;const r=-(e.start.dot(this.normal)+this.constant)/i;return r<0||r>1?null:t.copy(e.start).addScaledVector(n,r)}intersectsLine(e){const t=this.distanceToPoint(e.start),n=this.distanceToPoint(e.end);return t<0&&n>0||n<0&&t>0}intersectsBox(e){return e.intersectsPlane(this)}intersectsSphere(e){return e.intersectsPlane(this)}coplanarPoint(e){return e.copy(this.normal).multiplyScalar(-this.constant)}applyMatrix4(e,t){const n=t||Dl.getNormalMatrix(e),i=this.coplanarPoint(Nl).applyMatrix4(e),r=this.normal.applyMatrix3(n).normalize();return this.constant=-i.dot(r),this}translate(e){return this.constant-=e.dot(this.normal),this}equals(e){return e.normal.equals(this.normal)&&e.constant===this.constant}clone(){return(new this.constructor).copy(this)}}const Ll=new xo,jl=new Cs(.5,.5),Ol=new Es;class zl{constructor(e=new Il,t=new Il,n=new Il,i=new Il,r=new Il,s=new Il){this.planes=[e,t,n,i,r,s]}set(e,t,n,i,r,s){const o=this.planes;return o[0].copy(e),o[1].copy(t),o[2].copy(n),o[3].copy(i),o[4].copy(r),o[5].copy(s),this}copy(e){const t=this.planes;for(let n=0;n<6;n++)t[n].copy(e.planes[n]);return this}setFromProjectionMatrix(e,t=2e3,n=!1){const i=this.planes,r=e.elements,s=r[0],o=r[1],a=r[2],l=r[3],u=r[4],c=r[5],d=r[6],h=r[7],f=r[8],p=r[9],g=r[10],m=r[11],v=r[12],A=r[13],x=r[14],y=r[15];if(i[0].setComponents(l-s,h-u,m-f,y-v).normalize(),i[1].setComponents(l+s,h+u,m+f,y+v).normalize(),i[2].setComponents(l+o,h+c,m+p,y+A).normalize(),i[3].setComponents(l-o,h-c,m-p,y-A).normalize(),n)i[4].setComponents(a,d,g,x).normalize(),i[5].setComponents(l-a,h-d,m-g,y-x).normalize();else if(i[4].setComponents(l-a,h-d,m-g,y-x).normalize(),t===as)i[5].setComponents(l+a,h+d,m+g,y+x).normalize();else{if(t!==ls)throw new Error("THREE.Frustum.setFromProjectionMatrix(): Invalid coordinate system: "+t);i[5].setComponents(a,d,g,x).normalize()}return this}intersectsObject(e){if(void 0!==e.boundingSphere)null===e.boundingSphere&&e.computeBoundingSphere(),Ll.copy(e.boundingSphere).applyMatrix4(e.matrixWorld);else{const t=e.geometry;null===t.boundingSphere&&t.computeBoundingSphere(),Ll.copy(t.boundingSphere).applyMatrix4(e.matrixWorld)}return this.intersectsSphere(Ll)}intersectsSprite(e){Ll.center.set(0,0,0);const t=jl.distanceTo(e.center);return Ll.radius=.7071067811865476+t,Ll.applyMatrix4(e.matrixWorld),this.intersectsSphere(Ll)}intersectsSphere(e){const t=this.planes,n=e.center,i=-e.radius;for(let e=0;e<6;e++){if(t[e].distanceToPoint(n)<i)return!1}return!0}intersectsBox(e){const t=this.planes;for(let n=0;n<6;n++){const i=t[n];if(Ol.x=i.normal.x>0?e.max.x:e.min.x,Ol.y=i.normal.y>0?e.max.y:e.min.y,Ol.z=i.normal.z>0?e.max.z:e.min.z,i.distanceToPoint(Ol)<0)return!1}return!0}containsPoint(e){const t=this.planes;for(let n=0;n<6;n++)if(t[n].distanceToPoint(e)<0)return!1;return!0}clone(){return(new this.constructor).copy(this)}}const Rl=new Po,kl=new zl;class Fl{constructor(){this.coordinateSystem=as}intersectsObject(e,t){if(!t.isArrayCamera||0===t.cameras.length)return!1;for(let n=0;n<t.cameras.length;n++){const i=t.cameras[n];if(Rl.multiplyMatrices(i.projectionMatrix,i.matrixWorldInverse),kl.setFromProjectionMatrix(Rl,i.coordinateSystem,i.reversedDepth),kl.intersectsObject(e))return!0}return!1}intersectsSprite(e,t){if(!t||!t.cameras||0===t.cameras.length)return!1;for(let n=0;n<t.cameras.length;n++){const i=t.cameras[n];if(Rl.multiplyMatrices(i.projectionMatrix,i.matrixWorldInverse),kl.setFromProjectionMatrix(Rl,i.coordinateSystem,i.reversedDepth),kl.intersectsSprite(e))return!0}return!1}intersectsSphere(e,t){if(!t||!t.cameras||0===t.cameras.length)return!1;for(let n=0;n<t.cameras.length;n++){const i=t.cameras[n];if(Rl.multiplyMatrices(i.projectionMatrix,i.matrixWorldInverse),kl.setFromProjectionMatrix(Rl,i.coordinateSystem,i.reversedDepth),kl.intersectsSphere(e))return!0}return!1}intersectsBox(e,t){if(!t||!t.cameras||0===t.cameras.length)return!1;for(let n=0;n<t.cameras.length;n++){const i=t.cameras[n];if(Rl.multiplyMatrices(i.projectionMatrix,i.matrixWorldInverse),kl.setFromProjectionMatrix(Rl,i.coordinateSystem,i.reversedDepth),kl.intersectsBox(e))return!0}return!1}containsPoint(e,t){if(!t||!t.cameras||0===t.cameras.length)return!1;for(let n=0;n<t.cameras.length;n++){const i=t.cameras[n];if(Rl.multiplyMatrices(i.projectionMatrix,i.matrixWorldInverse),kl.setFromProjectionMatrix(Rl,i.coordinateSystem,i.reversedDepth),kl.containsPoint(e))return!0}return!1}clone(){return new Fl}}class Hl extends Ca{constructor(e){super(),this.isLineBasicMaterial=!0,this.type="LineBasicMaterial",this.color=new ya(16777215),this.map=null,this.linewidth=1,this.linecap="round",this.linejoin="round",this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.map=e.map,this.linewidth=e.linewidth,this.linecap=e.linecap,this.linejoin=e.linejoin,this.fog=e.fog,this}}const Ul=new Es,Xl=new Es,Gl=new Po,Vl=new So,Wl=new xo,Ql=new Es,Zl=new Es;class Yl extends ta{constructor(e=new Va,t=new Hl){super(),this.isLine=!0,this.type="Line",this.geometry=e,this.material=t,this.morphTargetDictionary=void 0,this.morphTargetInfluences=void 0,this.updateMorphTargets()}copy(e,t){return super.copy(e,t),this.material=Array.isArray(e.material)?e.material.slice():e.material,this.geometry=e.geometry,this}computeLineDistances(){const e=this.geometry;if(null===e.index){const t=e.attributes.position,n=[0];for(let e=1,i=t.count;e<i;e++)Ul.fromBufferAttribute(t,e-1),Xl.fromBufferAttribute(t,e),n[e]=n[e-1],n[e]+=Ul.distanceTo(Xl);e.setAttribute("lineDistance",new za(n,1))}else console.warn("THREE.Line.computeLineDistances(): Computation only possible with non-indexed BufferGeometry.");return this}raycast(e,t){const n=this.geometry,i=this.matrixWorld,r=e.params.Line.threshold,s=n.drawRange;if(null===n.boundingSphere&&n.computeBoundingSphere(),Wl.copy(n.boundingSphere),Wl.applyMatrix4(i),Wl.radius+=r,!1===e.ray.intersectsSphere(Wl))return;Gl.copy(i).invert(),Vl.copy(e.ray).applyMatrix4(Gl);const o=r/((this.scale.x+this.scale.y+this.scale.z)/3),a=o*o,l=this.isLineSegments?2:1,u=n.index,c=n.attributes.position;if(null!==u){const n=Math.max(0,s.start),i=Math.min(u.count,s.start+s.count);for(let r=n,s=i-1;r<s;r+=l){const n=u.getX(r),i=u.getX(r+1),s=Jl(this,e,Vl,a,n,i,r);s&&t.push(s)}if(this.isLineLoop){const r=u.getX(i-1),s=u.getX(n),o=Jl(this,e,Vl,a,r,s,i-1);o&&t.push(o)}}else{const n=Math.max(0,s.start),i=Math.min(c.count,s.start+s.count);for(let r=n,s=i-1;r<s;r+=l){const n=Jl(this,e,Vl,a,r,r+1,r);n&&t.push(n)}if(this.isLineLoop){const r=Jl(this,e,Vl,a,i-1,n,i-1);r&&t.push(r)}}}updateMorphTargets(){const e=this.geometry.morphAttributes,t=Object.keys(e);if(t.length>0){const n=e[t[0]];if(void 0!==n){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,t=n.length;e<t;e++){const t=n[e].name||String(e);this.morphTargetInfluences.push(0),this.morphTargetDictionary[t]=e}}}}}function Jl(e,t,n,i,r,s,o){const a=e.geometry.attributes.position;Ul.fromBufferAttribute(a,r),Xl.fromBufferAttribute(a,s);if(n.distanceSqToSegment(Ul,Xl,Ql,Zl)>i)return;Ql.applyMatrix4(e.matrixWorld);const l=t.ray.origin.distanceTo(Ql);return l<t.near||l>t.far?void 0:{distance:l,point:Zl.clone().applyMatrix4(e.matrixWorld),index:o,face:null,faceIndex:null,barycoord:null,object:e}}class Kl extends Ca{constructor(e){super(),this.isPointsMaterial=!0,this.type="PointsMaterial",this.color=new ya(16777215),this.map=null,this.alphaMap=null,this.size=1,this.sizeAttenuation=!0,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.map=e.map,this.alphaMap=e.alphaMap,this.size=e.size,this.sizeAttenuation=e.sizeAttenuation,this.fog=e.fog,this}}class ql extends Ys{constructor(e,t){super({width:e,height:t}),this.isFramebufferTexture=!0,this.magFilter=Ri,this.minFilter=Ri,this.generateMipmaps=!1,this.needsUpdate=!0}}class _l extends Ys{constructor(e,t,n=1014,i,r,s,o=1003,a=1003,l,u=1026,c=1){if(u!==sr&&u!==or)throw new Error("DepthTexture format must be either THREE.DepthFormat or THREE.DepthStencilFormat");super({width:e,height:t,depth:c},i,r,s,o,a,u,n,l),this.isDepthTexture=!0,this.flipY=!1,this.generateMipmaps=!1,this.compareFunction=null}copy(e){return super.copy(e),this.source=new Vs(Object.assign({},e.image)),this.compareFunction=e.compareFunction,this}toJSON(e){const t=super.toJSON(e);return null!==this.compareFunction&&(t.compareFunction=this.compareFunction),t}}class $l extends Ys{constructor(e=null){super(),this.sourceTexture=e,this.isExternalTexture=!0}copy(e){return super.copy(e),this.sourceTexture=e.sourceTexture,this}}class eu extends Va{constructor(e=1,t=1,n=1,i=32,r=1,s=!1,o=0,a=2*Math.PI){super(),this.type="CylinderGeometry",this.parameters={radiusTop:e,radiusBottom:t,height:n,radialSegments:i,heightSegments:r,openEnded:s,thetaStart:o,thetaLength:a};const l=this;i=Math.floor(i),r=Math.floor(r);const u=[],c=[],d=[],h=[];let f=0;const p=[],g=n/2;let m=0;function v(n){const r=f,s=new Cs,p=new Es;let v=0;const A=!0===n?e:t,x=!0===n?1:-1;for(let e=1;e<=i;e++)c.push(0,g*x,0),d.push(0,x,0),h.push(.5,.5),f++;const y=f;for(let e=0;e<=i;e++){const t=e/i*a+o,n=Math.cos(t),r=Math.sin(t);p.x=A*r,p.y=g*x,p.z=A*n,c.push(p.x,p.y,p.z),d.push(0,x,0),s.x=.5*n+.5,s.y=.5*r*x+.5,h.push(s.x,s.y),f++}for(let e=0;e<i;e++){const t=r+e,i=y+e;!0===n?u.push(i,i+1,t):u.push(i+1,i,t),v+=3}l.addGroup(m,v,!0===n?1:2),m+=v}!function(){const s=new Es,v=new Es;let A=0;const x=(t-e)/n;for(let l=0;l<=r;l++){const u=[],m=l/r,A=m*(t-e)+e;for(let e=0;e<=i;e++){const t=e/i,r=t*a+o,l=Math.sin(r),p=Math.cos(r);v.x=A*l,v.y=-m*n+g,v.z=A*p,c.push(v.x,v.y,v.z),s.set(l,x,p).normalize(),d.push(s.x,s.y,s.z),h.push(t,1-m),u.push(f++)}p.push(u)}for(let n=0;n<i;n++)for(let i=0;i<r;i++){const s=p[i][n],o=p[i+1][n],a=p[i+1][n+1],l=p[i][n+1];(e>0||0!==i)&&(u.push(s,o,l),A+=3),(t>0||i!==r-1)&&(u.push(o,a,l),A+=3)}l.addGroup(m,A,0),m+=A}(),!1===s&&(e>0&&v(!0),t>0&&v(!1)),this.setIndex(u),this.setAttribute("position",new za(c,3)),this.setAttribute("normal",new za(d,3)),this.setAttribute("uv",new za(h,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new eu(e.radiusTop,e.radiusBottom,e.height,e.radialSegments,e.heightSegments,e.openEnded,e.thetaStart,e.thetaLength)}}class tu extends eu{constructor(e=1,t=1,n=32,i=1,r=!1,s=0,o=2*Math.PI){super(0,e,t,n,i,r,s,o),this.type="ConeGeometry",this.parameters={radius:e,height:t,radialSegments:n,heightSegments:i,openEnded:r,thetaStart:s,thetaLength:o}}static fromJSON(e){return new tu(e.radius,e.height,e.radialSegments,e.heightSegments,e.openEnded,e.thetaStart,e.thetaLength)}}class nu{constructor(){this.type="Curve",this.arcLengthDivisions=200,this.needsUpdate=!1,this.cacheArcLengths=null}getPoint(){console.warn("THREE.Curve: .getPoint() not implemented.")}getPointAt(e,t){const n=this.getUtoTmapping(e);return this.getPoint(n,t)}getPoints(e=5){const t=[];for(let n=0;n<=e;n++)t.push(this.getPoint(n/e));return t}getSpacedPoints(e=5){const t=[];for(let n=0;n<=e;n++)t.push(this.getPointAt(n/e));return t}getLength(){const e=this.getLengths();return e[e.length-1]}getLengths(e=this.arcLengthDivisions){if(this.cacheArcLengths&&this.cacheArcLengths.length===e+1&&!this.needsUpdate)return this.cacheArcLengths;this.needsUpdate=!1;const t=[];let n,i=this.getPoint(0),r=0;t.push(0);for(let s=1;s<=e;s++)n=this.getPoint(s/e),r+=n.distanceTo(i),t.push(r),i=n;return this.cacheArcLengths=t,t}updateArcLengths(){this.needsUpdate=!0,this.getLengths()}getUtoTmapping(e,t=null){const n=this.getLengths();let i=0;const r=n.length;let s;s=t||e*n[r-1];let o,a=0,l=r-1;for(;a<=l;)if(i=Math.floor(a+(l-a)/2),o=n[i]-s,o<0)a=i+1;else{if(!(o>0)){l=i;break}l=i-1}if(i=l,n[i]===s)return i/(r-1);const u=n[i];return(i+(s-u)/(n[i+1]-u))/(r-1)}getTangent(e,t){const n=1e-4;let i=e-n,r=e+n;i<0&&(i=0),r>1&&(r=1);const s=this.getPoint(i),o=this.getPoint(r),a=t||(s.isVector2?new Cs:new Es);return a.copy(o).sub(s).normalize(),a}getTangentAt(e,t){const n=this.getUtoTmapping(e);return this.getTangent(n,t)}computeFrenetFrames(e,t=!1){const n=new Es,i=[],r=[],s=[],o=new Es,a=new Po;for(let t=0;t<=e;t++){const n=t/e;i[t]=this.getTangentAt(n,new Es)}r[0]=new Es,s[0]=new Es;let l=Number.MAX_VALUE;const u=Math.abs(i[0].x),c=Math.abs(i[0].y),d=Math.abs(i[0].z);u<=l&&(l=u,n.set(1,0,0)),c<=l&&(l=c,n.set(0,1,0)),d<=l&&n.set(0,0,1),o.crossVectors(i[0],n).normalize(),r[0].crossVectors(i[0],o),s[0].crossVectors(i[0],r[0]);for(let t=1;t<=e;t++){if(r[t]=r[t-1].clone(),s[t]=s[t-1].clone(),o.crossVectors(i[t-1],i[t]),o.length()>Number.EPSILON){o.normalize();const e=Math.acos(vs(i[t-1].dot(i[t]),-1,1));r[t].applyMatrix4(a.makeRotationAxis(o,e))}s[t].crossVectors(i[t],r[t])}if(!0===t){let t=Math.acos(vs(r[0].dot(r[e]),-1,1));t/=e,i[0].dot(o.crossVectors(r[0],r[e]))>0&&(t=-t);for(let n=1;n<=e;n++)r[n].applyMatrix4(a.makeRotationAxis(i[n],t*n)),s[n].crossVectors(i[n],r[n])}return{tangents:i,normals:r,binormals:s}}clone(){return(new this.constructor).copy(this)}copy(e){return this.arcLengthDivisions=e.arcLengthDivisions,this}toJSON(){const e={metadata:{version:4.7,type:"Curve",generator:"Curve.toJSON"}};return e.arcLengthDivisions=this.arcLengthDivisions,e.type=this.type,e}fromJSON(e){return this.arcLengthDivisions=e.arcLengthDivisions,this}}class iu extends nu{constructor(e=0,t=0,n=1,i=1,r=0,s=2*Math.PI,o=!1,a=0){super(),this.isEllipseCurve=!0,this.type="EllipseCurve",this.aX=e,this.aY=t,this.xRadius=n,this.yRadius=i,this.aStartAngle=r,this.aEndAngle=s,this.aClockwise=o,this.aRotation=a}getPoint(e,t=new Cs){const n=t,i=2*Math.PI;let r=this.aEndAngle-this.aStartAngle;const s=Math.abs(r)<Number.EPSILON;for(;r<0;)r+=i;for(;r>i;)r-=i;r<Number.EPSILON&&(r=s?0:i),!0!==this.aClockwise||s||(r===i?r=-i:r-=i);const o=this.aStartAngle+e*r;let a=this.aX+this.xRadius*Math.cos(o),l=this.aY+this.yRadius*Math.sin(o);if(0!==this.aRotation){const e=Math.cos(this.aRotation),t=Math.sin(this.aRotation),n=a-this.aX,i=l-this.aY;a=n*e-i*t+this.aX,l=n*t+i*e+this.aY}return n.set(a,l)}copy(e){return super.copy(e),this.aX=e.aX,this.aY=e.aY,this.xRadius=e.xRadius,this.yRadius=e.yRadius,this.aStartAngle=e.aStartAngle,this.aEndAngle=e.aEndAngle,this.aClockwise=e.aClockwise,this.aRotation=e.aRotation,this}toJSON(){const e=super.toJSON();return e.aX=this.aX,e.aY=this.aY,e.xRadius=this.xRadius,e.yRadius=this.yRadius,e.aStartAngle=this.aStartAngle,e.aEndAngle=this.aEndAngle,e.aClockwise=this.aClockwise,e.aRotation=this.aRotation,e}fromJSON(e){return super.fromJSON(e),this.aX=e.aX,this.aY=e.aY,this.xRadius=e.xRadius,this.yRadius=e.yRadius,this.aStartAngle=e.aStartAngle,this.aEndAngle=e.aEndAngle,this.aClockwise=e.aClockwise,this.aRotation=e.aRotation,this}}function ru(){let e=0,t=0,n=0,i=0;function r(r,s,o,a){e=r,t=o,n=-3*r+3*s-2*o-a,i=2*r-2*s+o+a}return{initCatmullRom:function(e,t,n,i,s){r(t,n,s*(n-e),s*(i-t))},initNonuniformCatmullRom:function(e,t,n,i,s,o,a){let l=(t-e)/s-(n-e)/(s+o)+(n-t)/o,u=(n-t)/o-(i-t)/(o+a)+(i-n)/a;l*=o,u*=o,r(t,n,l,u)},calc:function(r){const s=r*r;return e+t*r+n*s+i*(s*r)}}}const su=new Es,ou=new ru,au=new ru,lu=new ru;function uu(e,t,n,i,r){const s=.5*(i-t),o=.5*(r-n),a=e*e;return(2*n-2*i+s+o)*(e*a)+(-3*n+3*i-2*s-o)*a+s*e+n}function cu(e,t,n,i){return function(e,t){const n=1-e;return n*n*t}(e,t)+function(e,t){return 2*(1-e)*e*t}(e,n)+function(e,t){return e*e*t}(e,i)}function du(e,t,n,i,r){return function(e,t){const n=1-e;return n*n*n*t}(e,t)+function(e,t){const n=1-e;return 3*n*n*e*t}(e,n)+function(e,t){return 3*(1-e)*e*e*t}(e,i)+function(e,t){return e*e*e*t}(e,r)}class hu extends nu{constructor(e=new Cs,t=new Cs,n=new Cs,i=new Cs){super(),this.isCubicBezierCurve=!0,this.type="CubicBezierCurve",this.v0=e,this.v1=t,this.v2=n,this.v3=i}getPoint(e,t=new Cs){const n=t,i=this.v0,r=this.v1,s=this.v2,o=this.v3;return n.set(du(e,i.x,r.x,s.x,o.x),du(e,i.y,r.y,s.y,o.y)),n}copy(e){return super.copy(e),this.v0.copy(e.v0),this.v1.copy(e.v1),this.v2.copy(e.v2),this.v3.copy(e.v3),this}toJSON(){const e=super.toJSON();return e.v0=this.v0.toArray(),e.v1=this.v1.toArray(),e.v2=this.v2.toArray(),e.v3=this.v3.toArray(),e}fromJSON(e){return super.fromJSON(e),this.v0.fromArray(e.v0),this.v1.fromArray(e.v1),this.v2.fromArray(e.v2),this.v3.fromArray(e.v3),this}}class fu extends nu{constructor(e=new Es,t=new Es,n=new Es,i=new Es){super(),this.isCubicBezierCurve3=!0,this.type="CubicBezierCurve3",this.v0=e,this.v1=t,this.v2=n,this.v3=i}getPoint(e,t=new Es){const n=t,i=this.v0,r=this.v1,s=this.v2,o=this.v3;return n.set(du(e,i.x,r.x,s.x,o.x),du(e,i.y,r.y,s.y,o.y),du(e,i.z,r.z,s.z,o.z)),n}copy(e){return super.copy(e),this.v0.copy(e.v0),this.v1.copy(e.v1),this.v2.copy(e.v2),this.v3.copy(e.v3),this}toJSON(){const e=super.toJSON();return e.v0=this.v0.toArray(),e.v1=this.v1.toArray(),e.v2=this.v2.toArray(),e.v3=this.v3.toArray(),e}fromJSON(e){return super.fromJSON(e),this.v0.fromArray(e.v0),this.v1.fromArray(e.v1),this.v2.fromArray(e.v2),this.v3.fromArray(e.v3),this}}class pu extends nu{constructor(e=new Cs,t=new Cs){super(),this.isLineCurve=!0,this.type="LineCurve",this.v1=e,this.v2=t}getPoint(e,t=new Cs){const n=t;return 1===e?n.copy(this.v2):(n.copy(this.v2).sub(this.v1),n.multiplyScalar(e).add(this.v1)),n}getPointAt(e,t){return this.getPoint(e,t)}getTangent(e,t=new Cs){return t.subVectors(this.v2,this.v1).normalize()}getTangentAt(e,t){return this.getTangent(e,t)}copy(e){return super.copy(e),this.v1.copy(e.v1),this.v2.copy(e.v2),this}toJSON(){const e=super.toJSON();return e.v1=this.v1.toArray(),e.v2=this.v2.toArray(),e}fromJSON(e){return super.fromJSON(e),this.v1.fromArray(e.v1),this.v2.fromArray(e.v2),this}}class gu extends nu{constructor(e=new Cs,t=new Cs,n=new Cs){super(),this.isQuadraticBezierCurve=!0,this.type="QuadraticBezierCurve",this.v0=e,this.v1=t,this.v2=n}getPoint(e,t=new Cs){const n=t,i=this.v0,r=this.v1,s=this.v2;return n.set(cu(e,i.x,r.x,s.x),cu(e,i.y,r.y,s.y)),n}copy(e){return super.copy(e),this.v0.copy(e.v0),this.v1.copy(e.v1),this.v2.copy(e.v2),this}toJSON(){const e=super.toJSON();return e.v0=this.v0.toArray(),e.v1=this.v1.toArray(),e.v2=this.v2.toArray(),e}fromJSON(e){return super.fromJSON(e),this.v0.fromArray(e.v0),this.v1.fromArray(e.v1),this.v2.fromArray(e.v2),this}}class mu extends nu{constructor(e=new Es,t=new Es,n=new Es){super(),this.isQuadraticBezierCurve3=!0,this.type="QuadraticBezierCurve3",this.v0=e,this.v1=t,this.v2=n}getPoint(e,t=new Es){const n=t,i=this.v0,r=this.v1,s=this.v2;return n.set(cu(e,i.x,r.x,s.x),cu(e,i.y,r.y,s.y),cu(e,i.z,r.z,s.z)),n}copy(e){return super.copy(e),this.v0.copy(e.v0),this.v1.copy(e.v1),this.v2.copy(e.v2),this}toJSON(){const e=super.toJSON();return e.v0=this.v0.toArray(),e.v1=this.v1.toArray(),e.v2=this.v2.toArray(),e}fromJSON(e){return super.fromJSON(e),this.v0.fromArray(e.v0),this.v1.fromArray(e.v1),this.v2.fromArray(e.v2),this}}class vu extends nu{constructor(e=[]){super(),this.isSplineCurve=!0,this.type="SplineCurve",this.points=e}getPoint(e,t=new Cs){const n=t,i=this.points,r=(i.length-1)*e,s=Math.floor(r),o=r-s,a=i[0===s?s:s-1],l=i[s],u=i[s>i.length-2?i.length-1:s+1],c=i[s>i.length-3?i.length-1:s+2];return n.set(uu(o,a.x,l.x,u.x,c.x),uu(o,a.y,l.y,u.y,c.y)),n}copy(e){super.copy(e),this.points=[];for(let t=0,n=e.points.length;t<n;t++){const n=e.points[t];this.points.push(n.clone())}return this}toJSON(){const e=super.toJSON();e.points=[];for(let t=0,n=this.points.length;t<n;t++){const n=this.points[t];e.points.push(n.toArray())}return e}fromJSON(e){super.fromJSON(e),this.points=[];for(let t=0,n=e.points.length;t<n;t++){const n=e.points[t];this.points.push((new Cs).fromArray(n))}return this}}var Au=Object.freeze({__proto__:null,ArcCurve:class extends iu{constructor(e,t,n,i,r,s){super(e,t,n,n,i,r,s),this.isArcCurve=!0,this.type="ArcCurve"}},CatmullRomCurve3:class extends nu{constructor(e=[],t=!1,n="centripetal",i=.5){super(),this.isCatmullRomCurve3=!0,this.type="CatmullRomCurve3",this.points=e,this.closed=t,this.curveType=n,this.tension=i}getPoint(e,t=new Es){const n=t,i=this.points,r=i.length,s=(r-(this.closed?0:1))*e;let o,a,l=Math.floor(s),u=s-l;this.closed?l+=l>0?0:(Math.floor(Math.abs(l)/r)+1)*r:0===u&&l===r-1&&(l=r-2,u=1),this.closed||l>0?o=i[(l-1)%r]:(su.subVectors(i[0],i[1]).add(i[0]),o=su);const c=i[l%r],d=i[(l+1)%r];if(this.closed||l+2<r?a=i[(l+2)%r]:(su.subVectors(i[r-1],i[r-2]).add(i[r-1]),a=su),"centripetal"===this.curveType||"chordal"===this.curveType){const e="chordal"===this.curveType?.5:.25;let t=Math.pow(o.distanceToSquared(c),e),n=Math.pow(c.distanceToSquared(d),e),i=Math.pow(d.distanceToSquared(a),e);n<1e-4&&(n=1),t<1e-4&&(t=n),i<1e-4&&(i=n),ou.initNonuniformCatmullRom(o.x,c.x,d.x,a.x,t,n,i),au.initNonuniformCatmullRom(o.y,c.y,d.y,a.y,t,n,i),lu.initNonuniformCatmullRom(o.z,c.z,d.z,a.z,t,n,i)}else"catmullrom"===this.curveType&&(ou.initCatmullRom(o.x,c.x,d.x,a.x,this.tension),au.initCatmullRom(o.y,c.y,d.y,a.y,this.tension),lu.initCatmullRom(o.z,c.z,d.z,a.z,this.tension));return n.set(ou.calc(u),au.calc(u),lu.calc(u)),n}copy(e){super.copy(e),this.points=[];for(let t=0,n=e.points.length;t<n;t++){const n=e.points[t];this.points.push(n.clone())}return this.closed=e.closed,this.curveType=e.curveType,this.tension=e.tension,this}toJSON(){const e=super.toJSON();e.points=[];for(let t=0,n=this.points.length;t<n;t++){const n=this.points[t];e.points.push(n.toArray())}return e.closed=this.closed,e.curveType=this.curveType,e.tension=this.tension,e}fromJSON(e){super.fromJSON(e),this.points=[];for(let t=0,n=e.points.length;t<n;t++){const n=e.points[t];this.points.push((new Es).fromArray(n))}return this.closed=e.closed,this.curveType=e.curveType,this.tension=e.tension,this}},CubicBezierCurve:hu,CubicBezierCurve3:fu,EllipseCurve:iu,LineCurve:pu,LineCurve3:class extends nu{constructor(e=new Es,t=new Es){super(),this.isLineCurve3=!0,this.type="LineCurve3",this.v1=e,this.v2=t}getPoint(e,t=new Es){const n=t;return 1===e?n.copy(this.v2):(n.copy(this.v2).sub(this.v1),n.multiplyScalar(e).add(this.v1)),n}getPointAt(e,t){return this.getPoint(e,t)}getTangent(e,t=new Es){return t.subVectors(this.v2,this.v1).normalize()}getTangentAt(e,t){return this.getTangent(e,t)}copy(e){return super.copy(e),this.v1.copy(e.v1),this.v2.copy(e.v2),this}toJSON(){const e=super.toJSON();return e.v1=this.v1.toArray(),e.v2=this.v2.toArray(),e}fromJSON(e){return super.fromJSON(e),this.v1.fromArray(e.v1),this.v2.fromArray(e.v2),this}},QuadraticBezierCurve:gu,QuadraticBezierCurve3:mu,SplineCurve:vu});class xu extends Va{constructor(e=1,t=1,n=1,i=1){super(),this.type="PlaneGeometry",this.parameters={width:e,height:t,widthSegments:n,heightSegments:i};const r=e/2,s=t/2,o=Math.floor(n),a=Math.floor(i),l=o+1,u=a+1,c=e/o,d=t/a,h=[],f=[],p=[],g=[];for(let e=0;e<u;e++){const t=e*d-s;for(let n=0;n<l;n++){const i=n*c-r;f.push(i,-t,0),p.push(0,0,1),g.push(n/o),g.push(1-e/a)}}for(let e=0;e<a;e++)for(let t=0;t<o;t++){const n=t+l*e,i=t+l*(e+1),r=t+1+l*(e+1),s=t+1+l*e;h.push(n,i,s),h.push(i,r,s)}this.setIndex(h),this.setAttribute("position",new za(f,3)),this.setAttribute("normal",new za(p,3)),this.setAttribute("uv",new za(g,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new xu(e.width,e.height,e.widthSegments,e.heightSegments)}}class yu extends Va{constructor(e=1,t=32,n=16,i=0,r=2*Math.PI,s=0,o=Math.PI){super(),this.type="SphereGeometry",this.parameters={radius:e,widthSegments:t,heightSegments:n,phiStart:i,phiLength:r,thetaStart:s,thetaLength:o},t=Math.max(3,Math.floor(t)),n=Math.max(2,Math.floor(n));const a=Math.min(s+o,Math.PI);let l=0;const u=[],c=new Es,d=new Es,h=[],f=[],p=[],g=[];for(let h=0;h<=n;h++){const m=[],v=h/n;let A=0;0===h&&0===s?A=.5/t:h===n&&a===Math.PI&&(A=-.5/t);for(let n=0;n<=t;n++){const a=n/t;c.x=-e*Math.cos(i+a*r)*Math.sin(s+v*o),c.y=e*Math.cos(s+v*o),c.z=e*Math.sin(i+a*r)*Math.sin(s+v*o),f.push(c.x,c.y,c.z),d.copy(c).normalize(),p.push(d.x,d.y,d.z),g.push(a+A,1-v),m.push(l++)}u.push(m)}for(let e=0;e<n;e++)for(let i=0;i<t;i++){const t=u[e][i+1],r=u[e][i],o=u[e+1][i],l=u[e+1][i+1];(0!==e||s>0)&&h.push(t,r,l),(e!==n-1||a<Math.PI)&&h.push(r,o,l)}this.setIndex(h),this.setAttribute("position",new za(f,3)),this.setAttribute("normal",new za(p,3)),this.setAttribute("uv",new za(g,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new yu(e.radius,e.widthSegments,e.heightSegments,e.phiStart,e.phiLength,e.thetaStart,e.thetaLength)}}class bu extends Va{constructor(e=new mu(new Es(-1,-1,0),new Es(-1,1,0),new Es(1,1,0)),t=64,n=1,i=8,r=!1){super(),this.type="TubeGeometry",this.parameters={path:e,tubularSegments:t,radius:n,radialSegments:i,closed:r};const s=e.computeFrenetFrames(t,r);this.tangents=s.tangents,this.normals=s.normals,this.binormals=s.binormals;const o=new Es,a=new Es,l=new Cs;let u=new Es;const c=[],d=[],h=[],f=[];function p(r){u=e.getPointAt(r/t,u);const l=s.normals[r],h=s.binormals[r];for(let e=0;e<=i;e++){const t=e/i*Math.PI*2,r=Math.sin(t),s=-Math.cos(t);a.x=s*l.x+r*h.x,a.y=s*l.y+r*h.y,a.z=s*l.z+r*h.z,a.normalize(),d.push(a.x,a.y,a.z),o.x=u.x+n*a.x,o.y=u.y+n*a.y,o.z=u.z+n*a.z,c.push(o.x,o.y,o.z)}}!function(){for(let e=0;e<t;e++)p(e);p(!1===r?t:0),function(){for(let e=0;e<=t;e++)for(let n=0;n<=i;n++)l.x=e/t,l.y=n/i,h.push(l.x,l.y)}(),function(){for(let e=1;e<=t;e++)for(let t=1;t<=i;t++){const n=(i+1)*(e-1)+(t-1),r=(i+1)*e+(t-1),s=(i+1)*e+t,o=(i+1)*(e-1)+t;f.push(n,r,o),f.push(r,s,o)}}()}(),this.setIndex(f),this.setAttribute("position",new za(c,3)),this.setAttribute("normal",new za(d,3)),this.setAttribute("uv",new za(h,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}toJSON(){const e=super.toJSON();return e.path=this.parameters.path.toJSON(),e}static fromJSON(e){return new bu((new Au[e.path.type]).fromJSON(e.path),e.tubularSegments,e.radius,e.radialSegments,e.closed)}}class wu extends Ca{constructor(e){super(),this.isShadowMaterial=!0,this.type="ShadowMaterial",this.color=new ya(0),this.transparent=!0,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.fog=e.fog,this}}class Cu extends Ca{constructor(e){super(),this.isMeshStandardMaterial=!0,this.type="MeshStandardMaterial",this.defines={STANDARD:""},this.color=new ya(16777215),this.roughness=1,this.metalness=0,this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new ya(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new Cs(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.roughnessMap=null,this.metalnessMap=null,this.alphaMap=null,this.envMap=null,this.envMapRotation=new ko,this.envMapIntensity=1,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap="round",this.wireframeLinejoin="round",this.flatShading=!1,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.defines={STANDARD:""},this.color.copy(e.color),this.roughness=e.roughness,this.metalness=e.metalness,this.map=e.map,this.lightMap=e.lightMap,this.lightMapIntensity=e.lightMapIntensity,this.aoMap=e.aoMap,this.aoMapIntensity=e.aoMapIntensity,this.emissive.copy(e.emissive),this.emissiveMap=e.emissiveMap,this.emissiveIntensity=e.emissiveIntensity,this.bumpMap=e.bumpMap,this.bumpScale=e.bumpScale,this.normalMap=e.normalMap,this.normalMapType=e.normalMapType,this.normalScale.copy(e.normalScale),this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this.roughnessMap=e.roughnessMap,this.metalnessMap=e.metalnessMap,this.alphaMap=e.alphaMap,this.envMap=e.envMap,this.envMapRotation.copy(e.envMapRotation),this.envMapIntensity=e.envMapIntensity,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.wireframeLinecap=e.wireframeLinecap,this.wireframeLinejoin=e.wireframeLinejoin,this.flatShading=e.flatShading,this.fog=e.fog,this}}class Mu extends Cu{constructor(e){super(),this.isMeshPhysicalMaterial=!0,this.defines={STANDARD:"",PHYSICAL:""},this.type="MeshPhysicalMaterial",this.anisotropyRotation=0,this.anisotropyMap=null,this.clearcoatMap=null,this.clearcoatRoughness=0,this.clearcoatRoughnessMap=null,this.clearcoatNormalScale=new Cs(1,1),this.clearcoatNormalMap=null,this.ior=1.5,Object.defineProperty(this,"reflectivity",{get:function(){return vs(2.5*(this.ior-1)/(this.ior+1),0,1)},set:function(e){this.ior=(1+.4*e)/(1-.4*e)}}),this.iridescenceMap=null,this.iridescenceIOR=1.3,this.iridescenceThicknessRange=[100,400],this.iridescenceThicknessMap=null,this.sheenColor=new ya(0),this.sheenColorMap=null,this.sheenRoughness=1,this.sheenRoughnessMap=null,this.transmissionMap=null,this.thickness=0,this.thicknessMap=null,this.attenuationDistance=1/0,this.attenuationColor=new ya(1,1,1),this.specularIntensity=1,this.specularIntensityMap=null,this.specularColor=new ya(1,1,1),this.specularColorMap=null,this._anisotropy=0,this._clearcoat=0,this._dispersion=0,this._iridescence=0,this._sheen=0,this._transmission=0,this.setValues(e)}get anisotropy(){return this._anisotropy}set anisotropy(e){this._anisotropy>0!=e>0&&this.version++,this._anisotropy=e}get clearcoat(){return this._clearcoat}set clearcoat(e){this._clearcoat>0!=e>0&&this.version++,this._clearcoat=e}get iridescence(){return this._iridescence}set iridescence(e){this._iridescence>0!=e>0&&this.version++,this._iridescence=e}get dispersion(){return this._dispersion}set dispersion(e){this._dispersion>0!=e>0&&this.version++,this._dispersion=e}get sheen(){return this._sheen}set sheen(e){this._sheen>0!=e>0&&this.version++,this._sheen=e}get transmission(){return this._transmission}set transmission(e){this._transmission>0!=e>0&&this.version++,this._transmission=e}copy(e){return super.copy(e),this.defines={STANDARD:"",PHYSICAL:""},this.anisotropy=e.anisotropy,this.anisotropyRotation=e.anisotropyRotation,this.anisotropyMap=e.anisotropyMap,this.clearcoat=e.clearcoat,this.clearcoatMap=e.clearcoatMap,this.clearcoatRoughness=e.clearcoatRoughness,this.clearcoatRoughnessMap=e.clearcoatRoughnessMap,this.clearcoatNormalMap=e.clearcoatNormalMap,this.clearcoatNormalScale.copy(e.clearcoatNormalScale),this.dispersion=e.dispersion,this.ior=e.ior,this.iridescence=e.iridescence,this.iridescenceMap=e.iridescenceMap,this.iridescenceIOR=e.iridescenceIOR,this.iridescenceThicknessRange=[...e.iridescenceThicknessRange],this.iridescenceThicknessMap=e.iridescenceThicknessMap,this.sheen=e.sheen,this.sheenColor.copy(e.sheenColor),this.sheenColorMap=e.sheenColorMap,this.sheenRoughness=e.sheenRoughness,this.sheenRoughnessMap=e.sheenRoughnessMap,this.transmission=e.transmission,this.transmissionMap=e.transmissionMap,this.thickness=e.thickness,this.thicknessMap=e.thicknessMap,this.attenuationDistance=e.attenuationDistance,this.attenuationColor.copy(e.attenuationColor),this.specularIntensity=e.specularIntensity,this.specularIntensityMap=e.specularIntensityMap,this.specularColor.copy(e.specularColor),this.specularColorMap=e.specularColorMap,this}}class Eu extends Ca{constructor(e){super(),this.isMeshPhongMaterial=!0,this.type="MeshPhongMaterial",this.color=new ya(16777215),this.specular=new ya(1118481),this.shininess=30,this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new ya(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new Cs(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.specularMap=null,this.alphaMap=null,this.envMap=null,this.envMapRotation=new ko,this.combine=0,this.reflectivity=1,this.refractionRatio=.98,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap="round",this.wireframeLinejoin="round",this.flatShading=!1,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.specular.copy(e.specular),this.shininess=e.shininess,this.map=e.map,this.lightMap=e.lightMap,this.lightMapIntensity=e.lightMapIntensity,this.aoMap=e.aoMap,this.aoMapIntensity=e.aoMapIntensity,this.emissive.copy(e.emissive),this.emissiveMap=e.emissiveMap,this.emissiveIntensity=e.emissiveIntensity,this.bumpMap=e.bumpMap,this.bumpScale=e.bumpScale,this.normalMap=e.normalMap,this.normalMapType=e.normalMapType,this.normalScale.copy(e.normalScale),this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this.specularMap=e.specularMap,this.alphaMap=e.alphaMap,this.envMap=e.envMap,this.envMapRotation.copy(e.envMapRotation),this.combine=e.combine,this.reflectivity=e.reflectivity,this.refractionRatio=e.refractionRatio,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.wireframeLinecap=e.wireframeLinecap,this.wireframeLinejoin=e.wireframeLinejoin,this.flatShading=e.flatShading,this.fog=e.fog,this}}class Tu extends Ca{constructor(e){super(),this.isMeshToonMaterial=!0,this.defines={TOON:""},this.type="MeshToonMaterial",this.color=new ya(16777215),this.map=null,this.gradientMap=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new ya(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new Cs(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.alphaMap=null,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap="round",this.wireframeLinejoin="round",this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.map=e.map,this.gradientMap=e.gradientMap,this.lightMap=e.lightMap,this.lightMapIntensity=e.lightMapIntensity,this.aoMap=e.aoMap,this.aoMapIntensity=e.aoMapIntensity,this.emissive.copy(e.emissive),this.emissiveMap=e.emissiveMap,this.emissiveIntensity=e.emissiveIntensity,this.bumpMap=e.bumpMap,this.bumpScale=e.bumpScale,this.normalMap=e.normalMap,this.normalMapType=e.normalMapType,this.normalScale.copy(e.normalScale),this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this.alphaMap=e.alphaMap,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.wireframeLinecap=e.wireframeLinecap,this.wireframeLinejoin=e.wireframeLinejoin,this.fog=e.fog,this}}class Su extends Ca{constructor(e){super(),this.isMeshNormalMaterial=!0,this.type="MeshNormalMaterial",this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new Cs(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.wireframe=!1,this.wireframeLinewidth=1,this.flatShading=!1,this.setValues(e)}copy(e){return super.copy(e),this.bumpMap=e.bumpMap,this.bumpScale=e.bumpScale,this.normalMap=e.normalMap,this.normalMapType=e.normalMapType,this.normalScale.copy(e.normalScale),this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.flatShading=e.flatShading,this}}class Pu extends Ca{constructor(e){super(),this.isMeshLambertMaterial=!0,this.type="MeshLambertMaterial",this.color=new ya(16777215),this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new ya(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new Cs(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.specularMap=null,this.alphaMap=null,this.envMap=null,this.envMapRotation=new ko,this.combine=0,this.reflectivity=1,this.refractionRatio=.98,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap="round",this.wireframeLinejoin="round",this.flatShading=!1,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.map=e.map,this.lightMap=e.lightMap,this.lightMapIntensity=e.lightMapIntensity,this.aoMap=e.aoMap,this.aoMapIntensity=e.aoMapIntensity,this.emissive.copy(e.emissive),this.emissiveMap=e.emissiveMap,this.emissiveIntensity=e.emissiveIntensity,this.bumpMap=e.bumpMap,this.bumpScale=e.bumpScale,this.normalMap=e.normalMap,this.normalMapType=e.normalMapType,this.normalScale.copy(e.normalScale),this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this.specularMap=e.specularMap,this.alphaMap=e.alphaMap,this.envMap=e.envMap,this.envMapRotation.copy(e.envMapRotation),this.combine=e.combine,this.reflectivity=e.reflectivity,this.refractionRatio=e.refractionRatio,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.wireframeLinecap=e.wireframeLinecap,this.wireframeLinejoin=e.wireframeLinejoin,this.flatShading=e.flatShading,this.fog=e.fog,this}}class Nu extends Ca{constructor(e){super(),this.isMeshDepthMaterial=!0,this.type="MeshDepthMaterial",this.depthPacking=3200,this.map=null,this.alphaMap=null,this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.wireframe=!1,this.wireframeLinewidth=1,this.setValues(e)}copy(e){return super.copy(e),this.depthPacking=e.depthPacking,this.map=e.map,this.alphaMap=e.alphaMap,this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this}}class Bu extends Ca{constructor(e){super(),this.isMeshDistanceMaterial=!0,this.type="MeshDistanceMaterial",this.map=null,this.alphaMap=null,this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.setValues(e)}copy(e){return super.copy(e),this.map=e.map,this.alphaMap=e.alphaMap,this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this}}class Du extends Ca{constructor(e){super(),this.isMeshMatcapMaterial=!0,this.defines={MATCAP:""},this.type="MeshMatcapMaterial",this.color=new ya(16777215),this.matcap=null,this.map=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new Cs(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.alphaMap=null,this.flatShading=!1,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.defines={MATCAP:""},this.color.copy(e.color),this.matcap=e.matcap,this.map=e.map,this.bumpMap=e.bumpMap,this.bumpScale=e.bumpScale,this.normalMap=e.normalMap,this.normalMapType=e.normalMapType,this.normalScale.copy(e.normalScale),this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this.alphaMap=e.alphaMap,this.flatShading=e.flatShading,this.fog=e.fog,this}}class Iu extends Hl{constructor(e){super(),this.isLineDashedMaterial=!0,this.type="LineDashedMaterial",this.scale=1,this.dashSize=3,this.gapSize=1,this.setValues(e)}copy(e){return super.copy(e),this.scale=e.scale,this.dashSize=e.dashSize,this.gapSize=e.gapSize,this}}function Lu(e,t){return e&&e.constructor!==t?"number"==typeof t.BYTES_PER_ELEMENT?new t(e):Array.prototype.slice.call(e):e}function ju(e){return ArrayBuffer.isView(e)&&!(e instanceof DataView)}class Ou{constructor(e,t,n,i){this.parameterPositions=e,this._cachedIndex=0,this.resultBuffer=void 0!==i?i:new t.constructor(n),this.sampleValues=t,this.valueSize=n,this.settings=null,this.DefaultSettings_={}}evaluate(e){const t=this.parameterPositions;let n=this._cachedIndex,i=t[n],r=t[n-1];e:{t:{let s;n:{i:if(!(e<i)){for(let s=n+2;;){if(void 0===i){if(e<r)break i;return n=t.length,this._cachedIndex=n,this.copySampleValue_(n-1)}if(n===s)break;if(r=i,i=t[++n],e<i)break t}s=t.length;break n}if(e>=r)break e;{const o=t[1];e<o&&(n=2,r=o);for(let s=n-2;;){if(void 0===r)return this._cachedIndex=0,this.copySampleValue_(0);if(n===s)break;if(i=r,r=t[--n-1],e>=r)break t}s=n,n=0}}for(;n<s;){const i=n+s>>>1;e<t[i]?s=i:n=i+1}if(i=t[n],r=t[n-1],void 0===r)return this._cachedIndex=0,this.copySampleValue_(0);if(void 0===i)return n=t.length,this._cachedIndex=n,this.copySampleValue_(n-1)}this._cachedIndex=n,this.intervalChanged_(n,r,i)}return this.interpolate_(n,r,e,i)}getSettings_(){return this.settings||this.DefaultSettings_}copySampleValue_(e){const t=this.resultBuffer,n=this.sampleValues,i=this.valueSize,r=e*i;for(let e=0;e!==i;++e)t[e]=n[r+e];return t}interpolate_(){throw new Error("call to abstract method")}intervalChanged_(){}}class zu extends Ou{constructor(e,t,n,i){super(e,t,n,i),this._weightPrev=-0,this._offsetPrev=-0,this._weightNext=-0,this._offsetNext=-0,this.DefaultSettings_={endingStart:Zr,endingEnd:Zr}}intervalChanged_(e,t,n){const i=this.parameterPositions;let r=e-2,s=e+1,o=i[r],a=i[s];if(void 0===o)switch(this.getSettings_().endingStart){case Yr:r=e,o=2*t-n;break;case Jr:r=i.length-2,o=t+i[r]-i[r+1];break;default:r=e,o=n}if(void 0===a)switch(this.getSettings_().endingEnd){case Yr:s=e,a=2*n-t;break;case Jr:s=1,a=n+i[1]-i[0];break;default:s=e-1,a=t}const l=.5*(n-t),u=this.valueSize;this._weightPrev=l/(t-o),this._weightNext=l/(a-n),this._offsetPrev=r*u,this._offsetNext=s*u}interpolate_(e,t,n,i){const r=this.resultBuffer,s=this.sampleValues,o=this.valueSize,a=e*o,l=a-o,u=this._offsetPrev,c=this._offsetNext,d=this._weightPrev,h=this._weightNext,f=(n-t)/(i-t),p=f*f,g=p*f,m=-d*g+2*d*p-d*f,v=(1+d)*g+(-1.5-2*d)*p+(-.5+d)*f+1,A=(-1-h)*g+(1.5+h)*p+.5*f,x=h*g-h*p;for(let e=0;e!==o;++e)r[e]=m*s[u+e]+v*s[l+e]+A*s[a+e]+x*s[c+e];return r}}class Ru extends Ou{constructor(e,t,n,i){super(e,t,n,i)}interpolate_(e,t,n,i){const r=this.resultBuffer,s=this.sampleValues,o=this.valueSize,a=e*o,l=a-o,u=(n-t)/(i-t),c=1-u;for(let e=0;e!==o;++e)r[e]=s[l+e]*c+s[a+e]*u;return r}}class ku extends Ou{constructor(e,t,n,i){super(e,t,n,i)}interpolate_(e){return this.copySampleValue_(e-1)}}class Fu{constructor(e,t,n,i){if(void 0===e)throw new Error("THREE.KeyframeTrack: track name is undefined");if(void 0===t||0===t.length)throw new Error("THREE.KeyframeTrack: no keyframes in track named "+e);this.name=e,this.times=Lu(t,this.TimeBufferType),this.values=Lu(n,this.ValueBufferType),this.setInterpolation(i||this.DefaultInterpolation)}static toJSON(e){const t=e.constructor;let n;if(t.toJSON!==this.toJSON)n=t.toJSON(e);else{n={name:e.name,times:Lu(e.times,Array),values:Lu(e.values,Array)};const t=e.getInterpolation();t!==e.DefaultInterpolation&&(n.interpolation=t)}return n.type=e.ValueTypeName,n}InterpolantFactoryMethodDiscrete(e){return new ku(this.times,this.values,this.getValueSize(),e)}InterpolantFactoryMethodLinear(e){return new Ru(this.times,this.values,this.getValueSize(),e)}InterpolantFactoryMethodSmooth(e){return new zu(this.times,this.values,this.getValueSize(),e)}setInterpolation(e){let t;switch(e){case Vr:t=this.InterpolantFactoryMethodDiscrete;break;case Wr:t=this.InterpolantFactoryMethodLinear;break;case Qr:t=this.InterpolantFactoryMethodSmooth}if(void 0===t){const t="unsupported interpolation for "+this.ValueTypeName+" keyframe track named "+this.name;if(void 0===this.createInterpolant){if(e===this.DefaultInterpolation)throw new Error(t);this.setInterpolation(this.DefaultInterpolation)}return console.warn("THREE.KeyframeTrack:",t),this}return this.createInterpolant=t,this}getInterpolation(){switch(this.createInterpolant){case this.InterpolantFactoryMethodDiscrete:return Vr;case this.InterpolantFactoryMethodLinear:return Wr;case this.InterpolantFactoryMethodSmooth:return Qr}}getValueSize(){return this.values.length/this.times.length}shift(e){if(0!==e){const t=this.times;for(let n=0,i=t.length;n!==i;++n)t[n]+=e}return this}scale(e){if(1!==e){const t=this.times;for(let n=0,i=t.length;n!==i;++n)t[n]*=e}return this}trim(e,t){const n=this.times,i=n.length;let r=0,s=i-1;for(;r!==i&&n[r]<e;)++r;for(;-1!==s&&n[s]>t;)--s;if(++s,0!==r||s!==i){r>=s&&(s=Math.max(s,1),r=s-1);const e=this.getValueSize();this.times=n.slice(r,s),this.values=this.values.slice(r*e,s*e)}return this}validate(){let e=!0;const t=this.getValueSize();t-Math.floor(t)!=0&&(console.error("THREE.KeyframeTrack: Invalid value size in track.",this),e=!1);const n=this.times,i=this.values,r=n.length;0===r&&(console.error("THREE.KeyframeTrack: Track is empty.",this),e=!1);let s=null;for(let t=0;t!==r;t++){const i=n[t];if("number"==typeof i&&isNaN(i)){console.error("THREE.KeyframeTrack: Time is not a valid number.",this,t,i),e=!1;break}if(null!==s&&s>i){console.error("THREE.KeyframeTrack: Out of order keys.",this,t,i,s),e=!1;break}s=i}if(void 0!==i&&ju(i))for(let t=0,n=i.length;t!==n;++t){const n=i[t];if(isNaN(n)){console.error("THREE.KeyframeTrack: Value is not a valid number.",this,t,n),e=!1;break}}return e}optimize(){const e=this.times.slice(),t=this.values.slice(),n=this.getValueSize(),i=this.getInterpolation()===Qr,r=e.length-1;let s=1;for(let o=1;o<r;++o){let r=!1;const a=e[o];if(a!==e[o+1]&&(1!==o||a!==e[0]))if(i)r=!0;else{const e=o*n,i=e-n,s=e+n;for(let o=0;o!==n;++o){const n=t[e+o];if(n!==t[i+o]||n!==t[s+o]){r=!0;break}}}if(r){if(o!==s){e[s]=e[o];const i=o*n,r=s*n;for(let e=0;e!==n;++e)t[r+e]=t[i+e]}++s}}if(r>0){e[s]=e[r];for(let e=r*n,i=s*n,o=0;o!==n;++o)t[i+o]=t[e+o];++s}return s!==e.length?(this.times=e.slice(0,s),this.values=t.slice(0,s*n)):(this.times=e,this.values=t),this}clone(){const e=this.times.slice(),t=this.values.slice(),n=new(0,this.constructor)(this.name,e,t);return n.createInterpolant=this.createInterpolant,n}}Fu.prototype.ValueTypeName="",Fu.prototype.TimeBufferType=Float32Array,Fu.prototype.ValueBufferType=Float32Array,Fu.prototype.DefaultInterpolation=Wr;class Hu extends Fu{constructor(e,t,n){super(e,t,n)}}Hu.prototype.ValueTypeName="bool",Hu.prototype.ValueBufferType=Array,Hu.prototype.DefaultInterpolation=Vr,Hu.prototype.InterpolantFactoryMethodLinear=void 0,Hu.prototype.InterpolantFactoryMethodSmooth=void 0;class Uu extends Fu{constructor(e,t,n,i){super(e,t,n,i)}}Uu.prototype.ValueTypeName="color";class Xu extends Fu{constructor(e,t,n,i){super(e,t,n,i)}}Xu.prototype.ValueTypeName="number";class Gu extends Ou{constructor(e,t,n,i){super(e,t,n,i)}interpolate_(e,t,n,i){const r=this.resultBuffer,s=this.sampleValues,o=this.valueSize,a=(n-t)/(i-t);let l=e*o;for(let e=l+o;l!==e;l+=4)Ms.slerpFlat(r,0,s,l-o,s,l,a);return r}}class Vu extends Fu{constructor(e,t,n,i){super(e,t,n,i)}InterpolantFactoryMethodLinear(e){return new Gu(this.times,this.values,this.getValueSize(),e)}}Vu.prototype.ValueTypeName="quaternion",Vu.prototype.InterpolantFactoryMethodSmooth=void 0;class Wu extends Fu{constructor(e,t,n){super(e,t,n)}}Wu.prototype.ValueTypeName="string",Wu.prototype.ValueBufferType=Array,Wu.prototype.DefaultInterpolation=Vr,Wu.prototype.InterpolantFactoryMethodLinear=void 0,Wu.prototype.InterpolantFactoryMethodSmooth=void 0;class Qu extends Fu{constructor(e,t,n,i){super(e,t,n,i)}}Qu.prototype.ValueTypeName="vector";const Zu={enabled:!1,files:{},add:function(e,t){!1!==this.enabled&&(this.files[e]=t)},get:function(e){if(!1!==this.enabled)return this.files[e]},remove:function(e){delete this.files[e]},clear:function(){this.files={}}};class Yu{constructor(e,t,n){const i=this;let r,s=!1,o=0,a=0;const l=[];this.onStart=void 0,this.onLoad=e,this.onProgress=t,this.onError=n,this.abortController=new AbortController,this.itemStart=function(e){a++,!1===s&&void 0!==i.onStart&&i.onStart(e,o,a),s=!0},this.itemEnd=function(e){o++,void 0!==i.onProgress&&i.onProgress(e,o,a),o===a&&(s=!1,void 0!==i.onLoad&&i.onLoad())},this.itemError=function(e){void 0!==i.onError&&i.onError(e)},this.resolveURL=function(e){return r?r(e):e},this.setURLModifier=function(e){return r=e,this},this.addHandler=function(e,t){return l.push(e,t),this},this.removeHandler=function(e){const t=l.indexOf(e);return-1!==t&&l.splice(t,2),this},this.getHandler=function(e){for(let t=0,n=l.length;t<n;t+=2){const n=l[t],i=l[t+1];if(n.global&&(n.lastIndex=0),n.test(e))return i}return null},this.abort=function(){return this.abortController.abort(),this.abortController=new AbortController,this}}}const Ju=new Yu;class Ku{constructor(e){this.manager=void 0!==e?e:Ju,this.crossOrigin="anonymous",this.withCredentials=!1,this.path="",this.resourcePath="",this.requestHeader={}}load(){}loadAsync(e,t){const n=this;return new Promise((function(i,r){n.load(e,i,t,r)}))}parse(){}setCrossOrigin(e){return this.crossOrigin=e,this}setWithCredentials(e){return this.withCredentials=e,this}setPath(e){return this.path=e,this}setResourcePath(e){return this.resourcePath=e,this}setRequestHeader(e){return this.requestHeader=e,this}abort(){return this}}Ku.DEFAULT_MATERIAL_NAME="__DEFAULT";const qu=new WeakMap;class _u extends Ku{constructor(e){super(e)}load(e,t,n,i){void 0!==this.path&&(e=this.path+e),e=this.manager.resolveURL(e);const r=this,s=Zu.get(`image:${e}`);if(void 0!==s){if(!0===s.complete)r.manager.itemStart(e),setTimeout((function(){t&&t(s),r.manager.itemEnd(e)}),0);else{let e=qu.get(s);void 0===e&&(e=[],qu.set(s,e)),e.push({onLoad:t,onError:i})}return s}const o=Ds("img");function a(){u(),t&&t(this);const n=qu.get(this)||[];for(let e=0;e<n.length;e++){const t=n[e];t.onLoad&&t.onLoad(this)}qu.delete(this),r.manager.itemEnd(e)}function l(t){u(),i&&i(t),Zu.remove(`image:${e}`);const n=qu.get(this)||[];for(let e=0;e<n.length;e++){const i=n[e];i.onError&&i.onError(t)}qu.delete(this),r.manager.itemError(e),r.manager.itemEnd(e)}function u(){o.removeEventListener("load",a,!1),o.removeEventListener("error",l,!1)}return o.addEventListener("load",a,!1),o.addEventListener("error",l,!1),"data:"!==e.slice(0,5)&&void 0!==this.crossOrigin&&(o.crossOrigin=this.crossOrigin),Zu.add(`image:${e}`,o),r.manager.itemStart(e),o.src=e,o}}class $u extends ta{constructor(e,t=1){super(),this.isLight=!0,this.type="Light",this.color=new ya(e),this.intensity=t}dispose(){}copy(e,t){return super.copy(e,t),this.color.copy(e.color),this.intensity=e.intensity,this}toJSON(e){const t=super.toJSON(e);return t.object.color=this.color.getHex(),t.object.intensity=this.intensity,void 0!==this.groundColor&&(t.object.groundColor=this.groundColor.getHex()),void 0!==this.distance&&(t.object.distance=this.distance),void 0!==this.angle&&(t.object.angle=this.angle),void 0!==this.decay&&(t.object.decay=this.decay),void 0!==this.penumbra&&(t.object.penumbra=this.penumbra),void 0!==this.shadow&&(t.object.shadow=this.shadow.toJSON()),void 0!==this.target&&(t.object.target=this.target.uuid),t}}class ec extends $u{constructor(e,t,n){super(e,n),this.isHemisphereLight=!0,this.type="HemisphereLight",this.position.copy(ta.DEFAULT_UP),this.updateMatrix(),this.groundColor=new ya(t)}copy(e,t){return super.copy(e,t),this.groundColor.copy(e.groundColor),this}}const tc=new Po,nc=new Es,ic=new Es;class rc{constructor(e){this.camera=e,this.intensity=1,this.bias=0,this.normalBias=0,this.radius=1,this.blurSamples=8,this.mapSize=new Cs(512,512),this.mapType=Gi,this.map=null,this.mapPass=null,this.matrix=new Po,this.autoUpdate=!0,this.needsUpdate=!1,this._frustum=new zl,this._frameExtents=new Cs(1,1),this._viewportCount=1,this._viewports=[new Js(0,0,1,1)]}getViewportCount(){return this._viewportCount}getFrustum(){return this._frustum}updateMatrices(e){const t=this.camera,n=this.matrix;nc.setFromMatrixPosition(e.matrixWorld),t.position.copy(nc),ic.setFromMatrixPosition(e.target.matrixWorld),t.lookAt(ic),t.updateMatrixWorld(),tc.multiplyMatrices(t.projectionMatrix,t.matrixWorldInverse),this._frustum.setFromProjectionMatrix(tc,t.coordinateSystem,t.reversedDepth),t.reversedDepth?n.set(.5,0,0,.5,0,.5,0,.5,0,0,1,0,0,0,0,1):n.set(.5,0,0,.5,0,.5,0,.5,0,0,.5,.5,0,0,0,1),n.multiply(tc)}getViewport(e){return this._viewports[e]}getFrameExtents(){return this._frameExtents}dispose(){this.map&&this.map.dispose(),this.mapPass&&this.mapPass.dispose()}copy(e){return this.camera=e.camera.clone(),this.intensity=e.intensity,this.bias=e.bias,this.radius=e.radius,this.autoUpdate=e.autoUpdate,this.needsUpdate=e.needsUpdate,this.normalBias=e.normalBias,this.blurSamples=e.blurSamples,this.mapSize.copy(e.mapSize),this}clone(){return(new this.constructor).copy(this)}toJSON(){const e={};return 1!==this.intensity&&(e.intensity=this.intensity),0!==this.bias&&(e.bias=this.bias),0!==this.normalBias&&(e.normalBias=this.normalBias),1!==this.radius&&(e.radius=this.radius),512===this.mapSize.x&&512===this.mapSize.y||(e.mapSize=this.mapSize.toArray()),e.camera=this.camera.toJSON(!1).object,delete e.camera.matrix,e}}class sc extends rc{constructor(){super(new pl(50,1,.5,500)),this.isSpotLightShadow=!0,this.focus=1,this.aspect=1}updateMatrices(e){const t=this.camera,n=2*gs*e.angle*this.focus,i=this.mapSize.width/this.mapSize.height*this.aspect,r=e.distance||t.far;n===t.fov&&i===t.aspect&&r===t.far||(t.fov=n,t.aspect=i,t.far=r,t.updateProjectionMatrix()),super.updateMatrices(e)}copy(e){return super.copy(e),this.focus=e.focus,this}}class oc extends $u{constructor(e,t,n=0,i=Math.PI/3,r=0,s=2){super(e,t),this.isSpotLight=!0,this.type="SpotLight",this.position.copy(ta.DEFAULT_UP),this.updateMatrix(),this.target=new ta,this.distance=n,this.angle=i,this.penumbra=r,this.decay=s,this.map=null,this.shadow=new sc}get power(){return this.intensity*Math.PI}set power(e){this.intensity=e/Math.PI}dispose(){this.shadow.dispose()}copy(e,t){return super.copy(e,t),this.distance=e.distance,this.angle=e.angle,this.penumbra=e.penumbra,this.decay=e.decay,this.target=e.target.clone(),this.shadow=e.shadow.clone(),this}}const ac=new Po,lc=new Es,uc=new Es;class cc extends rc{constructor(){super(new pl(90,1,.5,500)),this.isPointLightShadow=!0,this._frameExtents=new Cs(4,2),this._viewportCount=6,this._viewports=[new Js(2,1,1,1),new Js(0,1,1,1),new Js(3,1,1,1),new Js(1,1,1,1),new Js(3,0,1,1),new Js(1,0,1,1)],this._cubeDirections=[new Es(1,0,0),new Es(-1,0,0),new Es(0,0,1),new Es(0,0,-1),new Es(0,1,0),new Es(0,-1,0)],this._cubeUps=[new Es(0,1,0),new Es(0,1,0),new Es(0,1,0),new Es(0,1,0),new Es(0,0,1),new Es(0,0,-1)]}updateMatrices(e,t=0){const n=this.camera,i=this.matrix,r=e.distance||n.far;r!==n.far&&(n.far=r,n.updateProjectionMatrix()),lc.setFromMatrixPosition(e.matrixWorld),n.position.copy(lc),uc.copy(n.position),uc.add(this._cubeDirections[t]),n.up.copy(this._cubeUps[t]),n.lookAt(uc),n.updateMatrixWorld(),i.makeTranslation(-lc.x,-lc.y,-lc.z),ac.multiplyMatrices(n.projectionMatrix,n.matrixWorldInverse),this._frustum.setFromProjectionMatrix(ac,n.coordinateSystem,n.reversedDepth)}}class dc extends $u{constructor(e,t,n=0,i=2){super(e,t),this.isPointLight=!0,this.type="PointLight",this.distance=n,this.decay=i,this.shadow=new cc}get power(){return 4*this.intensity*Math.PI}set power(e){this.intensity=e/(4*Math.PI)}dispose(){this.shadow.dispose()}copy(e,t){return super.copy(e,t),this.distance=e.distance,this.decay=e.decay,this.shadow=e.shadow.clone(),this}}class hc extends cl{constructor(e=-1,t=1,n=1,i=-1,r=.1,s=2e3){super(),this.isOrthographicCamera=!0,this.type="OrthographicCamera",this.zoom=1,this.view=null,this.left=e,this.right=t,this.top=n,this.bottom=i,this.near=r,this.far=s,this.updateProjectionMatrix()}copy(e,t){return super.copy(e,t),this.left=e.left,this.right=e.right,this.top=e.top,this.bottom=e.bottom,this.near=e.near,this.far=e.far,this.zoom=e.zoom,this.view=null===e.view?null:Object.assign({},e.view),this}setViewOffset(e,t,n,i,r,s){null===this.view&&(this.view={enabled:!0,fullWidth:1,fullHeight:1,offsetX:0,offsetY:0,width:1,height:1}),this.view.enabled=!0,this.view.fullWidth=e,this.view.fullHeight=t,this.view.offsetX=n,this.view.offsetY=i,this.view.width=r,this.view.height=s,this.updateProjectionMatrix()}clearViewOffset(){null!==this.view&&(this.view.enabled=!1),this.updateProjectionMatrix()}updateProjectionMatrix(){const e=(this.right-this.left)/(2*this.zoom),t=(this.top-this.bottom)/(2*this.zoom),n=(this.right+this.left)/2,i=(this.top+this.bottom)/2;let r=n-e,s=n+e,o=i+t,a=i-t;if(null!==this.view&&this.view.enabled){const e=(this.right-this.left)/this.view.fullWidth/this.zoom,t=(this.top-this.bottom)/this.view.fullHeight/this.zoom;r+=e*this.view.offsetX,s=r+e*this.view.width,o-=t*this.view.offsetY,a=o-t*this.view.height}this.projectionMatrix.makeOrthographic(r,s,o,a,this.near,this.far,this.coordinateSystem,this.reversedDepth),this.projectionMatrixInverse.copy(this.projectionMatrix).invert()}toJSON(e){const t=super.toJSON(e);return t.object.zoom=this.zoom,t.object.left=this.left,t.object.right=this.right,t.object.top=this.top,t.object.bottom=this.bottom,t.object.near=this.near,t.object.far=this.far,null!==this.view&&(t.object.view=Object.assign({},this.view)),t}}class fc extends rc{constructor(){super(new hc(-5,5,5,-5,.5,500)),this.isDirectionalLightShadow=!0}}class pc extends $u{constructor(e,t){super(e,t),this.isDirectionalLight=!0,this.type="DirectionalLight",this.position.copy(ta.DEFAULT_UP),this.updateMatrix(),this.target=new ta,this.shadow=new fc}dispose(){this.shadow.dispose()}copy(e){return super.copy(e),this.target=e.target.clone(),this.shadow=e.shadow.clone(),this}}class gc extends $u{constructor(e,t){super(e,t),this.isAmbientLight=!0,this.type="AmbientLight"}}class mc extends $u{constructor(e,t,n=10,i=10){super(e,t),this.isRectAreaLight=!0,this.type="RectAreaLight",this.width=n,this.height=i}get power(){return this.intensity*this.width*this.height*Math.PI}set power(e){this.intensity=e/(this.width*this.height*Math.PI)}copy(e){return super.copy(e),this.width=e.width,this.height=e.height,this}toJSON(e){const t=super.toJSON(e);return t.object.width=this.width,t.object.height=this.height,t}}class vc{constructor(){this.isSphericalHarmonics3=!0,this.coefficients=[];for(let e=0;e<9;e++)this.coefficients.push(new Es)}set(e){for(let t=0;t<9;t++)this.coefficients[t].copy(e[t]);return this}zero(){for(let e=0;e<9;e++)this.coefficients[e].set(0,0,0);return this}getAt(e,t){const n=e.x,i=e.y,r=e.z,s=this.coefficients;return t.copy(s[0]).multiplyScalar(.282095),t.addScaledVector(s[1],.488603*i),t.addScaledVector(s[2],.488603*r),t.addScaledVector(s[3],.488603*n),t.addScaledVector(s[4],n*i*1.092548),t.addScaledVector(s[5],i*r*1.092548),t.addScaledVector(s[6],.315392*(3*r*r-1)),t.addScaledVector(s[7],n*r*1.092548),t.addScaledVector(s[8],.546274*(n*n-i*i)),t}getIrradianceAt(e,t){const n=e.x,i=e.y,r=e.z,s=this.coefficients;return t.copy(s[0]).multiplyScalar(.886227),t.addScaledVector(s[1],1.023328*i),t.addScaledVector(s[2],1.023328*r),t.addScaledVector(s[3],1.023328*n),t.addScaledVector(s[4],.858086*n*i),t.addScaledVector(s[5],.858086*i*r),t.addScaledVector(s[6],.743125*r*r-.247708),t.addScaledVector(s[7],.858086*n*r),t.addScaledVector(s[8],.429043*(n*n-i*i)),t}add(e){for(let t=0;t<9;t++)this.coefficients[t].add(e.coefficients[t]);return this}addScaledSH(e,t){for(let n=0;n<9;n++)this.coefficients[n].addScaledVector(e.coefficients[n],t);return this}scale(e){for(let t=0;t<9;t++)this.coefficients[t].multiplyScalar(e);return this}lerp(e,t){for(let n=0;n<9;n++)this.coefficients[n].lerp(e.coefficients[n],t);return this}equals(e){for(let t=0;t<9;t++)if(!this.coefficients[t].equals(e.coefficients[t]))return!1;return!0}copy(e){return this.set(e.coefficients)}clone(){return(new this.constructor).copy(this)}fromArray(e,t=0){const n=this.coefficients;for(let i=0;i<9;i++)n[i].fromArray(e,t+3*i);return this}toArray(e=[],t=0){const n=this.coefficients;for(let i=0;i<9;i++)n[i].toArray(e,t+3*i);return e}static getBasisAt(e,t){const n=e.x,i=e.y,r=e.z;t[0]=.282095,t[1]=.488603*i,t[2]=.488603*r,t[3]=.488603*n,t[4]=1.092548*n*i,t[5]=1.092548*i*r,t[6]=.315392*(3*r*r-1),t[7]=1.092548*n*r,t[8]=.546274*(n*n-i*i)}}class Ac extends $u{constructor(e=new vc,t=1){super(void 0,t),this.isLightProbe=!0,this.sh=e}copy(e){return super.copy(e),this.sh.copy(e.sh),this}fromJSON(e){return this.intensity=e.intensity,this.sh.fromArray(e.sh),this}toJSON(e){const t=super.toJSON(e);return t.object.sh=this.sh.toArray(),t}}new WeakMap;class xc extends pl{constructor(e=[]){super(),this.isArrayCamera=!0,this.isMultiViewCamera=!1,this.cameras=e}}class yc{constructor(e=!0){this.autoStart=e,this.startTime=0,this.oldTime=0,this.elapsedTime=0,this.running=!1}start(){this.startTime=performance.now(),this.oldTime=this.startTime,this.elapsedTime=0,this.running=!0}stop(){this.getElapsedTime(),this.running=!1,this.autoStart=!1}getElapsedTime(){return this.getDelta(),this.elapsedTime}getDelta(){let e=0;if(this.autoStart&&!this.running)return this.start(),0;if(this.running){const t=performance.now();e=(t-this.oldTime)/1e3,this.oldTime=t,this.elapsedTime+=e}return e}}const bc="\\[\\]\\.:\\/",wc=new RegExp("["+bc+"]","g"),Cc="[^"+bc+"]",Mc="[^"+bc.replace("\\.","")+"]",Ec=new RegExp("^"+/((?:WC+[\/:])*)/.source.replace("WC",Cc)+/(WCOD+)?/.source.replace("WCOD",Mc)+/(?:\.(WC+)(?:\[(.+)\])?)?/.source.replace("WC",Cc)+/\.(WC+)(?:\[(.+)\])?/.source.replace("WC",Cc)+"$"),Tc=["material","materials","bones","map"];class Sc{constructor(e,t,n){this.path=t,this.parsedPath=n||Sc.parseTrackName(t),this.node=Sc.findNode(e,this.parsedPath.nodeName),this.rootNode=e,this.getValue=this._getValue_unbound,this.setValue=this._setValue_unbound}static create(e,t,n){return e&&e.isAnimationObjectGroup?new Sc.Composite(e,t,n):new Sc(e,t,n)}static sanitizeNodeName(e){return e.replace(/\s/g,"_").replace(wc,"")}static parseTrackName(e){const t=Ec.exec(e);if(null===t)throw new Error("PropertyBinding: Cannot parse trackName: "+e);const n={nodeName:t[2],objectName:t[3],objectIndex:t[4],propertyName:t[5],propertyIndex:t[6]},i=n.nodeName&&n.nodeName.lastIndexOf(".");if(void 0!==i&&-1!==i){const e=n.nodeName.substring(i+1);-1!==Tc.indexOf(e)&&(n.nodeName=n.nodeName.substring(0,i),n.objectName=e)}if(null===n.propertyName||0===n.propertyName.length)throw new Error("PropertyBinding: can not parse propertyName from trackName: "+e);return n}static findNode(e,t){if(void 0===t||""===t||"."===t||-1===t||t===e.name||t===e.uuid)return e;if(e.skeleton){const n=e.skeleton.getBoneByName(t);if(void 0!==n)return n}if(e.children){const n=function(e){for(let i=0;i<e.length;i++){const r=e[i];if(r.name===t||r.uuid===t)return r;const s=n(r.children);if(s)return s}return null},i=n(e.children);if(i)return i}return null}_getValue_unavailable(){}_setValue_unavailable(){}_getValue_direct(e,t){e[t]=this.targetObject[this.propertyName]}_getValue_array(e,t){const n=this.resolvedProperty;for(let i=0,r=n.length;i!==r;++i)e[t++]=n[i]}_getValue_arrayElement(e,t){e[t]=this.resolvedProperty[this.propertyIndex]}_getValue_toArray(e,t){this.resolvedProperty.toArray(e,t)}_setValue_direct(e,t){this.targetObject[this.propertyName]=e[t]}_setValue_direct_setNeedsUpdate(e,t){this.targetObject[this.propertyName]=e[t],this.targetObject.needsUpdate=!0}_setValue_direct_setMatrixWorldNeedsUpdate(e,t){this.targetObject[this.propertyName]=e[t],this.targetObject.matrixWorldNeedsUpdate=!0}_setValue_array(e,t){const n=this.resolvedProperty;for(let i=0,r=n.length;i!==r;++i)n[i]=e[t++]}_setValue_array_setNeedsUpdate(e,t){const n=this.resolvedProperty;for(let i=0,r=n.length;i!==r;++i)n[i]=e[t++];this.targetObject.needsUpdate=!0}_setValue_array_setMatrixWorldNeedsUpdate(e,t){const n=this.resolvedProperty;for(let i=0,r=n.length;i!==r;++i)n[i]=e[t++];this.targetObject.matrixWorldNeedsUpdate=!0}_setValue_arrayElement(e,t){this.resolvedProperty[this.propertyIndex]=e[t]}_setValue_arrayElement_setNeedsUpdate(e,t){this.resolvedProperty[this.propertyIndex]=e[t],this.targetObject.needsUpdate=!0}_setValue_arrayElement_setMatrixWorldNeedsUpdate(e,t){this.resolvedProperty[this.propertyIndex]=e[t],this.targetObject.matrixWorldNeedsUpdate=!0}_setValue_fromArray(e,t){this.resolvedProperty.fromArray(e,t)}_setValue_fromArray_setNeedsUpdate(e,t){this.resolvedProperty.fromArray(e,t),this.targetObject.needsUpdate=!0}_setValue_fromArray_setMatrixWorldNeedsUpdate(e,t){this.resolvedProperty.fromArray(e,t),this.targetObject.matrixWorldNeedsUpdate=!0}_getValue_unbound(e,t){this.bind(),this.getValue(e,t)}_setValue_unbound(e,t){this.bind(),this.setValue(e,t)}bind(){let e=this.node;const t=this.parsedPath,n=t.objectName,i=t.propertyName;let r=t.propertyIndex;if(e||(e=Sc.findNode(this.rootNode,t.nodeName),this.node=e),this.getValue=this._getValue_unavailable,this.setValue=this._setValue_unavailable,!e)return void console.warn("THREE.PropertyBinding: No target node found for track: "+this.path+".");if(n){let i=t.objectIndex;switch(n){case"materials":if(!e.material)return void console.error("THREE.PropertyBinding: Can not bind to material as node does not have a material.",this);if(!e.material.materials)return void console.error("THREE.PropertyBinding: Can not bind to material.materials as node.material does not have a materials array.",this);e=e.material.materials;break;case"bones":if(!e.skeleton)return void console.error("THREE.PropertyBinding: Can not bind to bones as node does not have a skeleton.",this);e=e.skeleton.bones;for(let t=0;t<e.length;t++)if(e[t].name===i){i=t;break}break;case"map":if("map"in e){e=e.map;break}if(!e.material)return void console.error("THREE.PropertyBinding: Can not bind to material as node does not have a material.",this);if(!e.material.map)return void console.error("THREE.PropertyBinding: Can not bind to material.map as node.material does not have a map.",this);e=e.material.map;break;default:if(void 0===e[n])return void console.error("THREE.PropertyBinding: Can not bind to objectName of node undefined.",this);e=e[n]}if(void 0!==i){if(void 0===e[i])return void console.error("THREE.PropertyBinding: Trying to bind to objectIndex of objectName, but is undefined.",this,e);e=e[i]}}const s=e[i];if(void 0===s){const n=t.nodeName;return void console.error("THREE.PropertyBinding: Trying to update property for track: "+n+"."+i+" but it wasn't found.",e)}let o=this.Versioning.None;this.targetObject=e,!0===e.isMaterial?o=this.Versioning.NeedsUpdate:!0===e.isObject3D&&(o=this.Versioning.MatrixWorldNeedsUpdate);let a=this.BindingType.Direct;if(void 0!==r){if("morphTargetInfluences"===i){if(!e.geometry)return void console.error("THREE.PropertyBinding: Can not bind to morphTargetInfluences because node does not have a geometry.",this);if(!e.geometry.morphAttributes)return void console.error("THREE.PropertyBinding: Can not bind to morphTargetInfluences because node does not have a geometry.morphAttributes.",this);void 0!==e.morphTargetDictionary[r]&&(r=e.morphTargetDictionary[r])}a=this.BindingType.ArrayElement,this.resolvedProperty=s,this.propertyIndex=r}else void 0!==s.fromArray&&void 0!==s.toArray?(a=this.BindingType.HasFromToArray,this.resolvedProperty=s):Array.isArray(s)?(a=this.BindingType.EntireArray,this.resolvedProperty=s):this.propertyName=i;this.getValue=this.GetterByBindingType[a],this.setValue=this.SetterByBindingTypeAndVersioning[a][o]}unbind(){this.node=null,this.getValue=this._getValue_unbound,this.setValue=this._setValue_unbound}}Sc.Composite=class{constructor(e,t,n){const i=n||Sc.parseTrackName(t);this._targetGroup=e,this._bindings=e.subscribe_(t,i)}getValue(e,t){this.bind();const n=this._targetGroup.nCachedObjects_,i=this._bindings[n];void 0!==i&&i.getValue(e,t)}setValue(e,t){const n=this._bindings;for(let i=this._targetGroup.nCachedObjects_,r=n.length;i!==r;++i)n[i].setValue(e,t)}bind(){const e=this._bindings;for(let t=this._targetGroup.nCachedObjects_,n=e.length;t!==n;++t)e[t].bind()}unbind(){const e=this._bindings;for(let t=this._targetGroup.nCachedObjects_,n=e.length;t!==n;++t)e[t].unbind()}},Sc.prototype.BindingType={Direct:0,EntireArray:1,ArrayElement:2,HasFromToArray:3},Sc.prototype.Versioning={None:0,NeedsUpdate:1,MatrixWorldNeedsUpdate:2},Sc.prototype.GetterByBindingType=[Sc.prototype._getValue_direct,Sc.prototype._getValue_array,Sc.prototype._getValue_arrayElement,Sc.prototype._getValue_toArray],Sc.prototype.SetterByBindingTypeAndVersioning=[[Sc.prototype._setValue_direct,Sc.prototype._setValue_direct_setNeedsUpdate,Sc.prototype._setValue_direct_setMatrixWorldNeedsUpdate],[Sc.prototype._setValue_array,Sc.prototype._setValue_array_setNeedsUpdate,Sc.prototype._setValue_array_setMatrixWorldNeedsUpdate],[Sc.prototype._setValue_arrayElement,Sc.prototype._setValue_arrayElement_setNeedsUpdate,Sc.prototype._setValue_arrayElement_setMatrixWorldNeedsUpdate],[Sc.prototype._setValue_fromArray,Sc.prototype._setValue_fromArray_setNeedsUpdate,Sc.prototype._setValue_fromArray_setMatrixWorldNeedsUpdate]];new Float32Array(1);class Pc extends Cl{constructor(e,t,n=1){super(e,t),this.isInstancedInterleavedBuffer=!0,this.meshPerAttribute=n}copy(e){return super.copy(e),this.meshPerAttribute=e.meshPerAttribute,this}clone(e){const t=super.clone(e);return t.meshPerAttribute=this.meshPerAttribute,t}toJSON(e){const t=super.toJSON(e);return t.isInstancedInterleavedBuffer=!0,t.meshPerAttribute=this.meshPerAttribute,t}}const Nc=new Po;class Bc{constructor(e,t,n=0,i=1/0){this.ray=new So(e,t),this.near=n,this.far=i,this.camera=null,this.layers=new Fo,this.params={Mesh:{},Line:{threshold:1},LOD:{},Points:{threshold:1},Sprite:{}}}set(e,t){this.ray.set(e,t)}setFromCamera(e,t){t.isPerspectiveCamera?(this.ray.origin.setFromMatrixPosition(t.matrixWorld),this.ray.direction.set(e.x,e.y,.5).unproject(t).sub(this.ray.origin).normalize(),this.camera=t):t.isOrthographicCamera?(this.ray.origin.set(e.x,e.y,(t.near+t.far)/(t.near-t.far)).unproject(t),this.ray.direction.set(0,0,-1).transformDirection(t.matrixWorld),this.camera=t):console.error("THREE.Raycaster: Unsupported camera type: "+t.type)}setFromXRController(e){return Nc.identity().extractRotation(e.matrixWorld),this.ray.origin.setFromMatrixPosition(e.matrixWorld),this.ray.direction.set(0,0,-1).applyMatrix4(Nc),this}intersectObject(e,t=!0,n=[]){return Ic(e,this,n,t),n.sort(Dc),n}intersectObjects(e,t=!0,n=[]){for(let i=0,r=e.length;i<r;i++)Ic(e[i],this,n,t);return n.sort(Dc),n}}function Dc(e,t){return e.distance-t.distance}function Ic(e,t,n,i){let r=!0;if(e.layers.test(t.layers)){!1===e.raycast(t,n)&&(r=!1)}if(!0===r&&!0===i){const i=e.children;for(let e=0,r=i.length;e<r;e++)Ic(i[e],t,n,!0)}}class Lc{constructor(e=1,t=0,n=0){this.radius=e,this.phi=t,this.theta=n}set(e,t,n){return this.radius=e,this.phi=t,this.theta=n,this}copy(e){return this.radius=e.radius,this.phi=e.phi,this.theta=e.theta,this}makeSafe(){const e=1e-6;return this.phi=vs(this.phi,e,Math.PI-e),this}setFromVector3(e){return this.setFromCartesianCoords(e.x,e.y,e.z)}setFromCartesianCoords(e,t,n){return this.radius=Math.sqrt(e*e+t*t+n*n),0===this.radius?(this.theta=0,this.phi=0):(this.theta=Math.atan2(e,n),this.phi=Math.acos(vs(t/this.radius,-1,1))),this}clone(){return(new this.constructor).copy(this)}}class jc{constructor(e,t,n,i){jc.prototype.isMatrix2=!0,this.elements=[1,0,0,1],void 0!==e&&this.set(e,t,n,i)}identity(){return this.set(1,0,0,1),this}fromArray(e,t=0){for(let n=0;n<4;n++)this.elements[n]=e[n+t];return this}set(e,t,n,i){const r=this.elements;return r[0]=e,r[2]=t,r[1]=n,r[3]=i,this}}class Oc extends ds{constructor(e,t=null){super(),this.object=e,this.domElement=t,this.enabled=!0,this.state=-1,this.keys={},this.mouseButtons={LEFT:null,MIDDLE:null,RIGHT:null},this.touches={ONE:null,TWO:null}}connect(e){void 0!==e?(null!==this.domElement&&this.disconnect(),this.domElement=e):console.warn("THREE.Controls: connect() now requires an element.")}disconnect(){}dispose(){}update(){}}function zc(e,t,n,i){const r=function(e){switch(e){case Gi:case Vi:return{byteLength:1,components:1};case Qi:case Wi:case Ki:return{byteLength:2,components:1};case qi:case _i:return{byteLength:2,components:4};case Yi:case Zi:case Ji:return{byteLength:4,components:1};case er:case tr:return{byteLength:4,components:3}}throw new Error(`Unknown texture type ${e}.`)}(i);switch(n){case nr:return e*t;case ar:case lr:return e*t/r.components*r.byteLength;case ur:case cr:return e*t*2/r.components*r.byteLength;case ir:return e*t*3/r.components*r.byteLength;case rr:case 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Resizing buffer attributes is not supported.");!function(t,n,i){const r=n.array,s=n.updateRanges;if(e.bindBuffer(i,t),0===s.length)e.bufferSubData(i,0,r);else{s.sort(((e,t)=>e.start-t.start));let t=0;for(let e=1;e<s.length;e++){const n=s[t],i=s[e];i.start<=n.start+n.count+1?n.count=Math.max(n.count,i.start+i.count-n.start):(++t,s[t]=i)}s.length=t+1;for(let t=0,n=s.length;t<n;t++){const n=s[t];e.bufferSubData(i,n.start*r.BYTES_PER_ELEMENT,r,n.start,n.count)}n.clearUpdateRanges()}n.onUploadCallback()}(r.buffer,n,i),r.version=n.version}}}}const pp={alphahash_fragment:"#ifdef USE_ALPHAHASH\n\tif ( diffuseColor.a < getAlphaHashThreshold( vPosition ) ) discard;\n#endif",alphahash_pars_fragment:"#ifdef USE_ALPHAHASH\n\tconst float ALPHA_HASH_SCALE = 0.05;\n\tfloat hash2D( vec2 value ) {\n\t\treturn fract( 1.0e4 * sin( 17.0 * value.x + 0.1 * value.y ) * ( 0.1 + abs( sin( 13.0 * value.y + value.x ) ) ) );\n\t}\n\tfloat hash3D( vec3 value ) {\n\t\treturn hash2D( vec2( hash2D( value.xy ), value.z ) );\n\t}\n\tfloat getAlphaHashThreshold( vec3 position ) {\n\t\tfloat maxDeriv = max(\n\t\t\tlength( dFdx( position.xyz ) ),\n\t\t\tlength( dFdy( position.xyz ) )\n\t\t);\n\t\tfloat pixScale = 1.0 / ( ALPHA_HASH_SCALE * maxDeriv );\n\t\tvec2 pixScales = vec2(\n\t\t\texp2( floor( log2( pixScale ) ) ),\n\t\t\texp2( ceil( log2( pixScale ) ) )\n\t\t);\n\t\tvec2 alpha = vec2(\n\t\t\thash3D( floor( pixScales.x * position.xyz ) ),\n\t\t\thash3D( floor( pixScales.y * position.xyz ) )\n\t\t);\n\t\tfloat lerpFactor = fract( log2( pixScale ) );\n\t\tfloat x = ( 1.0 - lerpFactor ) * alpha.x + lerpFactor * alpha.y;\n\t\tfloat a = min( lerpFactor, 1.0 - lerpFactor );\n\t\tvec3 cases = vec3(\n\t\t\tx * x / ( 2.0 * a * ( 1.0 - a ) ),\n\t\t\t( x - 0.5 * a ) / ( 1.0 - a ),\n\t\t\t1.0 - ( ( 1.0 - x ) * ( 1.0 - x ) / ( 2.0 * a * ( 1.0 - a ) ) )\n\t\t);\n\t\tfloat threshold = ( x < ( 1.0 - a ) )\n\t\t\t? ( ( x < a ) ? cases.x : cases.y )\n\t\t\t: cases.z;\n\t\treturn clamp( threshold , 1.0e-6, 1.0 );\n\t}\n#endif",alphamap_fragment:"#ifdef USE_ALPHAMAP\n\tdiffuseColor.a *= texture2D( alphaMap, vAlphaMapUv ).g;\n#endif",alphamap_pars_fragment:"#ifdef USE_ALPHAMAP\n\tuniform sampler2D alphaMap;\n#endif",alphatest_fragment:"#ifdef USE_ALPHATEST\n\t#ifdef ALPHA_TO_COVERAGE\n\tdiffuseColor.a = smoothstep( alphaTest, alphaTest + fwidth( diffuseColor.a ), diffuseColor.a );\n\tif ( diffuseColor.a == 0.0 ) discard;\n\t#else\n\tif ( diffuseColor.a < alphaTest ) discard;\n\t#endif\n#endif",alphatest_pars_fragment:"#ifdef USE_ALPHATEST\n\tuniform float alphaTest;\n#endif",aomap_fragment:"#ifdef USE_AOMAP\n\tfloat ambientOcclusion = ( texture2D( aoMap, vAoMapUv ).r - 1.0 ) * aoMapIntensity + 1.0;\n\treflectedLight.indirectDiffuse *= ambientOcclusion;\n\t#if defined( USE_CLEARCOAT ) \n\t\tclearcoatSpecularIndirect *= ambientOcclusion;\n\t#endif\n\t#if defined( USE_SHEEN ) \n\t\tsheenSpecularIndirect *= ambientOcclusion;\n\t#endif\n\t#if defined( USE_ENVMAP ) && defined( STANDARD )\n\t\tfloat dotNV = saturate( dot( geometryNormal, geometryViewDir ) );\n\t\treflectedLight.indirectSpecular *= computeSpecularOcclusion( dotNV, ambientOcclusion, material.roughness );\n\t#endif\n#endif",aomap_pars_fragment:"#ifdef USE_AOMAP\n\tuniform sampler2D aoMap;\n\tuniform float aoMapIntensity;\n#endif",batching_pars_vertex:"#ifdef USE_BATCHING\n\t#if ! defined( GL_ANGLE_multi_draw )\n\t#define gl_DrawID _gl_DrawID\n\tuniform int _gl_DrawID;\n\t#endif\n\tuniform highp sampler2D batchingTexture;\n\tuniform highp usampler2D batchingIdTexture;\n\tmat4 getBatchingMatrix( const in float i ) {\n\t\tint size = textureSize( batchingTexture, 0 ).x;\n\t\tint j = int( i ) * 4;\n\t\tint x = j % size;\n\t\tint y = j / size;\n\t\tvec4 v1 = texelFetch( batchingTexture, ivec2( x, y ), 0 );\n\t\tvec4 v2 = texelFetch( batchingTexture, ivec2( x + 1, y ), 0 );\n\t\tvec4 v3 = texelFetch( batchingTexture, ivec2( x + 2, y ), 0 );\n\t\tvec4 v4 = texelFetch( batchingTexture, ivec2( x + 3, y ), 0 );\n\t\treturn mat4( v1, v2, v3, v4 );\n\t}\n\tfloat getIndirectIndex( const in int i ) {\n\t\tint size = textureSize( batchingIdTexture, 0 ).x;\n\t\tint x = i % size;\n\t\tint y = i / size;\n\t\treturn float( texelFetch( batchingIdTexture, ivec2( x, y ), 0 ).r );\n\t}\n#endif\n#ifdef USE_BATCHING_COLOR\n\tuniform sampler2D batchingColorTexture;\n\tvec3 getBatchingColor( const in float i ) {\n\t\tint size = textureSize( batchingColorTexture, 0 ).x;\n\t\tint j = int( i );\n\t\tint x = j % size;\n\t\tint y = j / size;\n\t\treturn texelFetch( batchingColorTexture, ivec2( x, y ), 0 ).rgb;\n\t}\n#endif",batching_vertex:"#ifdef USE_BATCHING\n\tmat4 batchingMatrix = getBatchingMatrix( getIndirectIndex( gl_DrawID ) );\n#endif",begin_vertex:"vec3 transformed = vec3( position );\n#ifdef USE_ALPHAHASH\n\tvPosition = vec3( position );\n#endif",beginnormal_vertex:"vec3 objectNormal = vec3( normal );\n#ifdef USE_TANGENT\n\tvec3 objectTangent = vec3( tangent.xyz );\n#endif",bsdfs:"float G_BlinnPhong_Implicit( ) {\n\treturn 0.25;\n}\nfloat D_BlinnPhong( const in float shininess, const in float dotNH ) {\n\treturn RECIPROCAL_PI * ( shininess * 0.5 + 1.0 ) * pow( dotNH, shininess );\n}\nvec3 BRDF_BlinnPhong( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in vec3 specularColor, const in float shininess ) {\n\tvec3 halfDir = normalize( lightDir + viewDir );\n\tfloat dotNH = saturate( dot( normal, halfDir ) );\n\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\n\tvec3 F = F_Schlick( specularColor, 1.0, dotVH );\n\tfloat G = G_BlinnPhong_Implicit( );\n\tfloat D = D_BlinnPhong( shininess, dotNH );\n\treturn F * ( G * D );\n} // validated",iridescence_fragment:"#ifdef USE_IRIDESCENCE\n\tconst mat3 XYZ_TO_REC709 = mat3(\n\t\t 3.2404542, -0.9692660,  0.0556434,\n\t\t-1.5371385,  1.8760108, -0.2040259,\n\t\t-0.4985314,  0.0415560,  1.0572252\n\t);\n\tvec3 Fresnel0ToIor( vec3 fresnel0 ) {\n\t\tvec3 sqrtF0 = sqrt( fresnel0 );\n\t\treturn ( vec3( 1.0 ) + sqrtF0 ) / ( vec3( 1.0 ) - sqrtF0 );\n\t}\n\tvec3 IorToFresnel0( vec3 transmittedIor, float incidentIor ) {\n\t\treturn pow2( ( transmittedIor - vec3( incidentIor ) ) / ( transmittedIor + vec3( incidentIor ) ) );\n\t}\n\tfloat IorToFresnel0( float transmittedIor, float incidentIor ) {\n\t\treturn pow2( ( transmittedIor - incidentIor ) / ( transmittedIor + incidentIor ));\n\t}\n\tvec3 evalSensitivity( float OPD, vec3 shift ) {\n\t\tfloat phase = 2.0 * PI * OPD * 1.0e-9;\n\t\tvec3 val = vec3( 5.4856e-13, 4.4201e-13, 5.2481e-13 );\n\t\tvec3 pos = vec3( 1.6810e+06, 1.7953e+06, 2.2084e+06 );\n\t\tvec3 var = vec3( 4.3278e+09, 9.3046e+09, 6.6121e+09 );\n\t\tvec3 xyz = val * sqrt( 2.0 * PI * var ) * cos( pos * phase + shift ) * exp( - pow2( phase ) * var );\n\t\txyz.x += 9.7470e-14 * sqrt( 2.0 * PI * 4.5282e+09 ) * cos( 2.2399e+06 * phase + shift[ 0 ] ) * exp( - 4.5282e+09 * pow2( phase ) );\n\t\txyz /= 1.0685e-7;\n\t\tvec3 rgb = XYZ_TO_REC709 * xyz;\n\t\treturn rgb;\n\t}\n\tvec3 evalIridescence( float outsideIOR, float eta2, float cosTheta1, float thinFilmThickness, vec3 baseF0 ) {\n\t\tvec3 I;\n\t\tfloat iridescenceIOR = mix( outsideIOR, eta2, smoothstep( 0.0, 0.03, thinFilmThickness ) );\n\t\tfloat sinTheta2Sq = pow2( outsideIOR / iridescenceIOR ) * ( 1.0 - pow2( cosTheta1 ) );\n\t\tfloat cosTheta2Sq = 1.0 - sinTheta2Sq;\n\t\tif ( cosTheta2Sq < 0.0 ) {\n\t\t\treturn vec3( 1.0 );\n\t\t}\n\t\tfloat cosTheta2 = sqrt( cosTheta2Sq );\n\t\tfloat R0 = IorToFresnel0( iridescenceIOR, outsideIOR );\n\t\tfloat R12 = F_Schlick( R0, 1.0, cosTheta1 );\n\t\tfloat T121 = 1.0 - R12;\n\t\tfloat phi12 = 0.0;\n\t\tif ( iridescenceIOR < outsideIOR ) phi12 = PI;\n\t\tfloat phi21 = PI - phi12;\n\t\tvec3 baseIOR = Fresnel0ToIor( clamp( baseF0, 0.0, 0.9999 ) );\t\tvec3 R1 = IorToFresnel0( baseIOR, iridescenceIOR );\n\t\tvec3 R23 = F_Schlick( R1, 1.0, cosTheta2 );\n\t\tvec3 phi23 = vec3( 0.0 );\n\t\tif ( baseIOR[ 0 ] < iridescenceIOR ) phi23[ 0 ] = PI;\n\t\tif ( baseIOR[ 1 ] < iridescenceIOR ) phi23[ 1 ] = PI;\n\t\tif ( baseIOR[ 2 ] < iridescenceIOR ) phi23[ 2 ] = PI;\n\t\tfloat OPD = 2.0 * iridescenceIOR * thinFilmThickness * cosTheta2;\n\t\tvec3 phi = vec3( phi21 ) + phi23;\n\t\tvec3 R123 = clamp( R12 * R23, 1e-5, 0.9999 );\n\t\tvec3 r123 = sqrt( R123 );\n\t\tvec3 Rs = pow2( T121 ) * R23 / ( vec3( 1.0 ) - R123 );\n\t\tvec3 C0 = R12 + Rs;\n\t\tI = C0;\n\t\tvec3 Cm = Rs - T121;\n\t\tfor ( int m = 1; m <= 2; ++ m ) {\n\t\t\tCm *= r123;\n\t\t\tvec3 Sm = 2.0 * evalSensitivity( float( m ) * OPD, float( m ) * phi );\n\t\t\tI += Cm * Sm;\n\t\t}\n\t\treturn max( I, vec3( 0.0 ) );\n\t}\n#endif",bumpmap_pars_fragment:"#ifdef USE_BUMPMAP\n\tuniform sampler2D bumpMap;\n\tuniform float bumpScale;\n\tvec2 dHdxy_fwd() {\n\t\tvec2 dSTdx = dFdx( vBumpMapUv );\n\t\tvec2 dSTdy = dFdy( vBumpMapUv );\n\t\tfloat Hll = bumpScale * texture2D( bumpMap, vBumpMapUv ).x;\n\t\tfloat dBx = bumpScale * texture2D( bumpMap, vBumpMapUv + dSTdx ).x - Hll;\n\t\tfloat dBy = bumpScale * texture2D( bumpMap, vBumpMapUv + dSTdy ).x - Hll;\n\t\treturn vec2( dBx, dBy );\n\t}\n\tvec3 perturbNormalArb( vec3 surf_pos, vec3 surf_norm, vec2 dHdxy, float faceDirection ) {\n\t\tvec3 vSigmaX = normalize( dFdx( surf_pos.xyz ) );\n\t\tvec3 vSigmaY = normalize( dFdy( surf_pos.xyz ) );\n\t\tvec3 vN = surf_norm;\n\t\tvec3 R1 = cross( vSigmaY, vN );\n\t\tvec3 R2 = cross( vN, vSigmaX );\n\t\tfloat fDet = dot( vSigmaX, R1 ) * faceDirection;\n\t\tvec3 vGrad = sign( fDet ) * ( dHdxy.x * R1 + dHdxy.y * R2 );\n\t\treturn normalize( abs( fDet ) * surf_norm - vGrad );\n\t}\n#endif",clipping_planes_fragment:"#if NUM_CLIPPING_PLANES > 0\n\tvec4 plane;\n\t#ifdef ALPHA_TO_COVERAGE\n\t\tfloat distanceToPlane, distanceGradient;\n\t\tfloat clipOpacity = 1.0;\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = 0; i < UNION_CLIPPING_PLANES; i ++ ) {\n\t\t\tplane = clippingPlanes[ i ];\n\t\t\tdistanceToPlane = - dot( vClipPosition, plane.xyz ) + plane.w;\n\t\t\tdistanceGradient = fwidth( distanceToPlane ) / 2.0;\n\t\t\tclipOpacity *= smoothstep( - distanceGradient, distanceGradient, distanceToPlane );\n\t\t\tif ( clipOpacity == 0.0 ) discard;\n\t\t}\n\t\t#pragma unroll_loop_end\n\t\t#if UNION_CLIPPING_PLANES < NUM_CLIPPING_PLANES\n\t\t\tfloat unionClipOpacity = 1.0;\n\t\t\t#pragma unroll_loop_start\n\t\t\tfor ( int i = UNION_CLIPPING_PLANES; i < NUM_CLIPPING_PLANES; i ++ ) {\n\t\t\t\tplane = clippingPlanes[ i ];\n\t\t\t\tdistanceToPlane = - dot( vClipPosition, plane.xyz ) + plane.w;\n\t\t\t\tdistanceGradient = fwidth( distanceToPlane ) / 2.0;\n\t\t\t\tunionClipOpacity *= 1.0 - smoothstep( - distanceGradient, distanceGradient, distanceToPlane );\n\t\t\t}\n\t\t\t#pragma unroll_loop_end\n\t\t\tclipOpacity *= 1.0 - unionClipOpacity;\n\t\t#endif\n\t\tdiffuseColor.a *= clipOpacity;\n\t\tif ( diffuseColor.a == 0.0 ) discard;\n\t#else\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = 0; i < UNION_CLIPPING_PLANES; i ++ ) {\n\t\t\tplane = clippingPlanes[ i ];\n\t\t\tif ( dot( vClipPosition, plane.xyz ) > plane.w ) discard;\n\t\t}\n\t\t#pragma unroll_loop_end\n\t\t#if UNION_CLIPPING_PLANES < NUM_CLIPPING_PLANES\n\t\t\tbool clipped = true;\n\t\t\t#pragma unroll_loop_start\n\t\t\tfor ( int i = UNION_CLIPPING_PLANES; i < NUM_CLIPPING_PLANES; i ++ ) {\n\t\t\t\tplane = clippingPlanes[ i ];\n\t\t\t\tclipped = ( dot( vClipPosition, plane.xyz ) > plane.w ) && clipped;\n\t\t\t}\n\t\t\t#pragma unroll_loop_end\n\t\t\tif ( clipped ) discard;\n\t\t#endif\n\t#endif\n#endif",clipping_planes_pars_fragment:"#if NUM_CLIPPING_PLANES > 0\n\tvarying vec3 vClipPosition;\n\tuniform vec4 clippingPlanes[ NUM_CLIPPING_PLANES ];\n#endif",clipping_planes_pars_vertex:"#if NUM_CLIPPING_PLANES > 0\n\tvarying vec3 vClipPosition;\n#endif",clipping_planes_vertex:"#if NUM_CLIPPING_PLANES > 0\n\tvClipPosition = - mvPosition.xyz;\n#endif",color_fragment:"#if defined( USE_COLOR_ALPHA )\n\tdiffuseColor *= vColor;\n#elif defined( USE_COLOR )\n\tdiffuseColor.rgb *= vColor;\n#endif",color_pars_fragment:"#if defined( USE_COLOR_ALPHA )\n\tvarying vec4 vColor;\n#elif defined( USE_COLOR )\n\tvarying vec3 vColor;\n#endif",color_pars_vertex:"#if defined( USE_COLOR_ALPHA )\n\tvarying vec4 vColor;\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR ) || defined( USE_BATCHING_COLOR )\n\tvarying vec3 vColor;\n#endif",color_vertex:"#if defined( USE_COLOR_ALPHA )\n\tvColor = vec4( 1.0 );\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR ) || defined( USE_BATCHING_COLOR )\n\tvColor = vec3( 1.0 );\n#endif\n#ifdef USE_COLOR\n\tvColor *= color;\n#endif\n#ifdef USE_INSTANCING_COLOR\n\tvColor.xyz *= instanceColor.xyz;\n#endif\n#ifdef USE_BATCHING_COLOR\n\tvec3 batchingColor = getBatchingColor( getIndirectIndex( gl_DrawID ) );\n\tvColor.xyz *= batchingColor.xyz;\n#endif",common:"#define PI 3.141592653589793\n#define PI2 6.283185307179586\n#define PI_HALF 1.5707963267948966\n#define RECIPROCAL_PI 0.3183098861837907\n#define RECIPROCAL_PI2 0.15915494309189535\n#define EPSILON 1e-6\n#ifndef saturate\n#define saturate( a ) clamp( a, 0.0, 1.0 )\n#endif\n#define whiteComplement( a ) ( 1.0 - saturate( a ) )\nfloat pow2( const in float x ) { return x*x; }\nvec3 pow2( const in vec3 x ) { return x*x; }\nfloat pow3( const in float x ) { return x*x*x; }\nfloat pow4( const in float x ) { float x2 = x*x; return x2*x2; }\nfloat max3( const in vec3 v ) { return max( max( v.x, v.y ), v.z ); }\nfloat average( const in vec3 v ) { return dot( v, vec3( 0.3333333 ) ); }\nhighp float rand( const in vec2 uv ) {\n\tconst highp float a = 12.9898, b = 78.233, c = 43758.5453;\n\thighp float dt = dot( uv.xy, vec2( a,b ) ), sn = mod( dt, PI );\n\treturn fract( sin( sn ) * c );\n}\n#ifdef HIGH_PRECISION\n\tfloat precisionSafeLength( vec3 v ) { return length( v ); }\n#else\n\tfloat precisionSafeLength( vec3 v ) {\n\t\tfloat maxComponent = max3( abs( v ) );\n\t\treturn length( v / maxComponent ) * maxComponent;\n\t}\n#endif\nstruct IncidentLight {\n\tvec3 color;\n\tvec3 direction;\n\tbool visible;\n};\nstruct ReflectedLight {\n\tvec3 directDiffuse;\n\tvec3 directSpecular;\n\tvec3 indirectDiffuse;\n\tvec3 indirectSpecular;\n};\n#ifdef USE_ALPHAHASH\n\tvarying vec3 vPosition;\n#endif\nvec3 transformDirection( in vec3 dir, in mat4 matrix ) {\n\treturn normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );\n}\nvec3 inverseTransformDirection( in vec3 dir, in mat4 matrix ) {\n\treturn normalize( ( vec4( dir, 0.0 ) * matrix ).xyz );\n}\nmat3 transposeMat3( const in mat3 m ) {\n\tmat3 tmp;\n\ttmp[ 0 ] = vec3( m[ 0 ].x, m[ 1 ].x, m[ 2 ].x );\n\ttmp[ 1 ] = vec3( m[ 0 ].y, m[ 1 ].y, m[ 2 ].y );\n\ttmp[ 2 ] = vec3( m[ 0 ].z, m[ 1 ].z, m[ 2 ].z );\n\treturn tmp;\n}\nbool isPerspectiveMatrix( mat4 m ) {\n\treturn m[ 2 ][ 3 ] == - 1.0;\n}\nvec2 equirectUv( in vec3 dir ) {\n\tfloat u = atan( dir.z, dir.x ) * RECIPROCAL_PI2 + 0.5;\n\tfloat v = asin( clamp( dir.y, - 1.0, 1.0 ) ) * RECIPROCAL_PI + 0.5;\n\treturn vec2( u, v );\n}\nvec3 BRDF_Lambert( const in vec3 diffuseColor ) {\n\treturn RECIPROCAL_PI * diffuseColor;\n}\nvec3 F_Schlick( const in vec3 f0, const in float f90, const in float dotVH ) {\n\tfloat fresnel = exp2( ( - 5.55473 * dotVH - 6.98316 ) * dotVH );\n\treturn f0 * ( 1.0 - fresnel ) + ( f90 * fresnel );\n}\nfloat F_Schlick( const in float f0, const in float f90, const in float dotVH ) {\n\tfloat fresnel = exp2( ( - 5.55473 * dotVH - 6.98316 ) * dotVH );\n\treturn f0 * ( 1.0 - fresnel ) + ( f90 * fresnel );\n} // validated",cube_uv_reflection_fragment:"#ifdef ENVMAP_TYPE_CUBE_UV\n\t#define cubeUV_minMipLevel 4.0\n\t#define cubeUV_minTileSize 16.0\n\tfloat getFace( vec3 direction ) {\n\t\tvec3 absDirection = abs( direction );\n\t\tfloat face = - 1.0;\n\t\tif ( absDirection.x > absDirection.z ) {\n\t\t\tif ( absDirection.x > absDirection.y )\n\t\t\t\tface = direction.x > 0.0 ? 0.0 : 3.0;\n\t\t\telse\n\t\t\t\tface = direction.y > 0.0 ? 1.0 : 4.0;\n\t\t} else {\n\t\t\tif ( absDirection.z > absDirection.y )\n\t\t\t\tface = direction.z > 0.0 ? 2.0 : 5.0;\n\t\t\telse\n\t\t\t\tface = direction.y > 0.0 ? 1.0 : 4.0;\n\t\t}\n\t\treturn face;\n\t}\n\tvec2 getUV( vec3 direction, float face ) {\n\t\tvec2 uv;\n\t\tif ( face == 0.0 ) {\n\t\t\tuv = vec2( direction.z, direction.y ) / abs( direction.x );\n\t\t} else if ( face == 1.0 ) {\n\t\t\tuv = vec2( - direction.x, - direction.z ) / abs( direction.y );\n\t\t} else if ( face == 2.0 ) {\n\t\t\tuv = vec2( - direction.x, direction.y ) / abs( direction.z );\n\t\t} else if ( face == 3.0 ) {\n\t\t\tuv = vec2( - direction.z, direction.y ) / abs( direction.x );\n\t\t} else if ( face == 4.0 ) {\n\t\t\tuv = vec2( - direction.x, direction.z ) / abs( direction.y );\n\t\t} else {\n\t\t\tuv = vec2( direction.x, direction.y ) / abs( direction.z );\n\t\t}\n\t\treturn 0.5 * ( uv + 1.0 );\n\t}\n\tvec3 bilinearCubeUV( sampler2D envMap, vec3 direction, float mipInt ) {\n\t\tfloat face = getFace( direction );\n\t\tfloat filterInt = max( cubeUV_minMipLevel - mipInt, 0.0 );\n\t\tmipInt = max( mipInt, cubeUV_minMipLevel );\n\t\tfloat faceSize = exp2( mipInt );\n\t\thighp vec2 uv = getUV( direction, face ) * ( faceSize - 2.0 ) + 1.0;\n\t\tif ( face > 2.0 ) {\n\t\t\tuv.y += faceSize;\n\t\t\tface -= 3.0;\n\t\t}\n\t\tuv.x += face * faceSize;\n\t\tuv.x += filterInt * 3.0 * cubeUV_minTileSize;\n\t\tuv.y += 4.0 * ( exp2( CUBEUV_MAX_MIP ) - faceSize );\n\t\tuv.x *= CUBEUV_TEXEL_WIDTH;\n\t\tuv.y *= CUBEUV_TEXEL_HEIGHT;\n\t\t#ifdef texture2DGradEXT\n\t\t\treturn texture2DGradEXT( envMap, uv, vec2( 0.0 ), vec2( 0.0 ) ).rgb;\n\t\t#else\n\t\t\treturn texture2D( envMap, uv ).rgb;\n\t\t#endif\n\t}\n\t#define cubeUV_r0 1.0\n\t#define cubeUV_m0 - 2.0\n\t#define cubeUV_r1 0.8\n\t#define cubeUV_m1 - 1.0\n\t#define cubeUV_r4 0.4\n\t#define cubeUV_m4 2.0\n\t#define cubeUV_r5 0.305\n\t#define cubeUV_m5 3.0\n\t#define cubeUV_r6 0.21\n\t#define cubeUV_m6 4.0\n\tfloat roughnessToMip( float roughness ) {\n\t\tfloat mip = 0.0;\n\t\tif ( roughness >= cubeUV_r1 ) {\n\t\t\tmip = ( cubeUV_r0 - roughness ) * ( cubeUV_m1 - cubeUV_m0 ) / ( cubeUV_r0 - cubeUV_r1 ) + cubeUV_m0;\n\t\t} else if ( roughness >= cubeUV_r4 ) {\n\t\t\tmip = ( cubeUV_r1 - roughness ) * ( cubeUV_m4 - cubeUV_m1 ) / ( cubeUV_r1 - cubeUV_r4 ) + cubeUV_m1;\n\t\t} else if ( roughness >= cubeUV_r5 ) {\n\t\t\tmip = ( cubeUV_r4 - roughness ) * ( cubeUV_m5 - cubeUV_m4 ) / ( cubeUV_r4 - cubeUV_r5 ) + cubeUV_m4;\n\t\t} else if ( roughness >= cubeUV_r6 ) {\n\t\t\tmip = ( cubeUV_r5 - roughness ) * ( cubeUV_m6 - cubeUV_m5 ) / ( cubeUV_r5 - cubeUV_r6 ) + cubeUV_m5;\n\t\t} else {\n\t\t\tmip = - 2.0 * log2( 1.16 * roughness );\t\t}\n\t\treturn mip;\n\t}\n\tvec4 textureCubeUV( sampler2D envMap, vec3 sampleDir, float roughness ) {\n\t\tfloat mip = clamp( roughnessToMip( roughness ), cubeUV_m0, CUBEUV_MAX_MIP );\n\t\tfloat mipF = fract( mip );\n\t\tfloat mipInt = floor( mip );\n\t\tvec3 color0 = bilinearCubeUV( envMap, sampleDir, mipInt );\n\t\tif ( mipF == 0.0 ) {\n\t\t\treturn vec4( color0, 1.0 );\n\t\t} else {\n\t\t\tvec3 color1 = bilinearCubeUV( envMap, sampleDir, mipInt + 1.0 );\n\t\t\treturn vec4( mix( color0, color1, mipF ), 1.0 );\n\t\t}\n\t}\n#endif",defaultnormal_vertex:"vec3 transformedNormal = objectNormal;\n#ifdef USE_TANGENT\n\tvec3 transformedTangent = objectTangent;\n#endif\n#ifdef USE_BATCHING\n\tmat3 bm = mat3( batchingMatrix );\n\ttransformedNormal /= vec3( dot( bm[ 0 ], bm[ 0 ] ), dot( bm[ 1 ], bm[ 1 ] ), dot( bm[ 2 ], bm[ 2 ] ) );\n\ttransformedNormal = bm * transformedNormal;\n\t#ifdef USE_TANGENT\n\t\ttransformedTangent = bm * transformedTangent;\n\t#endif\n#endif\n#ifdef USE_INSTANCING\n\tmat3 im = mat3( instanceMatrix );\n\ttransformedNormal /= vec3( dot( im[ 0 ], im[ 0 ] ), dot( im[ 1 ], im[ 1 ] ), dot( im[ 2 ], im[ 2 ] ) );\n\ttransformedNormal = im * transformedNormal;\n\t#ifdef USE_TANGENT\n\t\ttransformedTangent = im * transformedTangent;\n\t#endif\n#endif\ntransformedNormal = normalMatrix * transformedNormal;\n#ifdef FLIP_SIDED\n\ttransformedNormal = - transformedNormal;\n#endif\n#ifdef USE_TANGENT\n\ttransformedTangent = ( modelViewMatrix * vec4( transformedTangent, 0.0 ) ).xyz;\n\t#ifdef FLIP_SIDED\n\t\ttransformedTangent = - transformedTangent;\n\t#endif\n#endif",displacementmap_pars_vertex:"#ifdef USE_DISPLACEMENTMAP\n\tuniform sampler2D displacementMap;\n\tuniform float displacementScale;\n\tuniform float displacementBias;\n#endif",displacementmap_vertex:"#ifdef USE_DISPLACEMENTMAP\n\ttransformed += normalize( objectNormal ) * ( texture2D( displacementMap, vDisplacementMapUv ).x * displacementScale + displacementBias );\n#endif",emissivemap_fragment:"#ifdef USE_EMISSIVEMAP\n\tvec4 emissiveColor = texture2D( emissiveMap, vEmissiveMapUv );\n\t#ifdef DECODE_VIDEO_TEXTURE_EMISSIVE\n\t\temissiveColor = sRGBTransferEOTF( emissiveColor );\n\t#endif\n\ttotalEmissiveRadiance *= emissiveColor.rgb;\n#endif",emissivemap_pars_fragment:"#ifdef USE_EMISSIVEMAP\n\tuniform sampler2D emissiveMap;\n#endif",colorspace_fragment:"gl_FragColor = linearToOutputTexel( gl_FragColor );",colorspace_pars_fragment:"vec4 LinearTransferOETF( in vec4 value ) {\n\treturn value;\n}\nvec4 sRGBTransferEOTF( in vec4 value ) {\n\treturn vec4( mix( pow( value.rgb * 0.9478672986 + vec3( 0.0521327014 ), vec3( 2.4 ) ), value.rgb * 0.0773993808, vec3( lessThanEqual( value.rgb, vec3( 0.04045 ) ) ) ), value.a );\n}\nvec4 sRGBTransferOETF( in vec4 value ) {\n\treturn vec4( mix( pow( value.rgb, vec3( 0.41666 ) ) * 1.055 - vec3( 0.055 ), value.rgb * 12.92, vec3( lessThanEqual( value.rgb, vec3( 0.0031308 ) ) ) ), value.a );\n}",envmap_fragment:"#ifdef USE_ENVMAP\n\t#ifdef ENV_WORLDPOS\n\t\tvec3 cameraToFrag;\n\t\tif ( isOrthographic ) {\n\t\t\tcameraToFrag = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\n\t\t} else {\n\t\t\tcameraToFrag = normalize( vWorldPosition - cameraPosition );\n\t\t}\n\t\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\n\t\t#ifdef ENVMAP_MODE_REFLECTION\n\t\t\tvec3 reflectVec = reflect( cameraToFrag, worldNormal );\n\t\t#else\n\t\t\tvec3 reflectVec = refract( cameraToFrag, worldNormal, refractionRatio );\n\t\t#endif\n\t#else\n\t\tvec3 reflectVec = vReflect;\n\t#endif\n\t#ifdef ENVMAP_TYPE_CUBE\n\t\tvec4 envColor = textureCube( envMap, envMapRotation * vec3( flipEnvMap * reflectVec.x, reflectVec.yz ) );\n\t#else\n\t\tvec4 envColor = vec4( 0.0 );\n\t#endif\n\t#ifdef ENVMAP_BLENDING_MULTIPLY\n\t\toutgoingLight = mix( outgoingLight, outgoingLight * envColor.xyz, specularStrength * reflectivity );\n\t#elif defined( ENVMAP_BLENDING_MIX )\n\t\toutgoingLight = mix( outgoingLight, envColor.xyz, specularStrength * reflectivity );\n\t#elif defined( ENVMAP_BLENDING_ADD )\n\t\toutgoingLight += envColor.xyz * specularStrength * reflectivity;\n\t#endif\n#endif",envmap_common_pars_fragment:"#ifdef USE_ENVMAP\n\tuniform float envMapIntensity;\n\tuniform float flipEnvMap;\n\tuniform mat3 envMapRotation;\n\t#ifdef ENVMAP_TYPE_CUBE\n\t\tuniform samplerCube envMap;\n\t#else\n\t\tuniform sampler2D envMap;\n\t#endif\n\t\n#endif",envmap_pars_fragment:"#ifdef USE_ENVMAP\n\tuniform float reflectivity;\n\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( PHONG ) || defined( LAMBERT )\n\t\t#define ENV_WORLDPOS\n\t#endif\n\t#ifdef ENV_WORLDPOS\n\t\tvarying vec3 vWorldPosition;\n\t\tuniform float refractionRatio;\n\t#else\n\t\tvarying vec3 vReflect;\n\t#endif\n#endif",envmap_pars_vertex:"#ifdef USE_ENVMAP\n\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( PHONG ) || defined( LAMBERT )\n\t\t#define ENV_WORLDPOS\n\t#endif\n\t#ifdef ENV_WORLDPOS\n\t\t\n\t\tvarying vec3 vWorldPosition;\n\t#else\n\t\tvarying vec3 vReflect;\n\t\tuniform float refractionRatio;\n\t#endif\n#endif",envmap_physical_pars_fragment:"#ifdef USE_ENVMAP\n\tvec3 getIBLIrradiance( const in vec3 normal ) {\n\t\t#ifdef ENVMAP_TYPE_CUBE_UV\n\t\t\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\n\t\t\tvec4 envMapColor = textureCubeUV( envMap, envMapRotation * worldNormal, 1.0 );\n\t\t\treturn PI * envMapColor.rgb * envMapIntensity;\n\t\t#else\n\t\t\treturn vec3( 0.0 );\n\t\t#endif\n\t}\n\tvec3 getIBLRadiance( const in vec3 viewDir, const in vec3 normal, const in float roughness ) {\n\t\t#ifdef ENVMAP_TYPE_CUBE_UV\n\t\t\tvec3 reflectVec = reflect( - viewDir, normal );\n\t\t\treflectVec = normalize( mix( reflectVec, normal, roughness * roughness) );\n\t\t\treflectVec = inverseTransformDirection( reflectVec, viewMatrix );\n\t\t\tvec4 envMapColor = textureCubeUV( envMap, envMapRotation * reflectVec, roughness );\n\t\t\treturn envMapColor.rgb * envMapIntensity;\n\t\t#else\n\t\t\treturn vec3( 0.0 );\n\t\t#endif\n\t}\n\t#ifdef USE_ANISOTROPY\n\t\tvec3 getIBLAnisotropyRadiance( const in vec3 viewDir, const in vec3 normal, const in float roughness, const in vec3 bitangent, const in float anisotropy ) {\n\t\t\t#ifdef ENVMAP_TYPE_CUBE_UV\n\t\t\t\tvec3 bentNormal = cross( bitangent, viewDir );\n\t\t\t\tbentNormal = normalize( cross( bentNormal, bitangent ) );\n\t\t\t\tbentNormal = normalize( mix( bentNormal, normal, pow2( pow2( 1.0 - anisotropy * ( 1.0 - roughness ) ) ) ) );\n\t\t\t\treturn getIBLRadiance( viewDir, bentNormal, roughness );\n\t\t\t#else\n\t\t\t\treturn vec3( 0.0 );\n\t\t\t#endif\n\t\t}\n\t#endif\n#endif",envmap_vertex:"#ifdef USE_ENVMAP\n\t#ifdef ENV_WORLDPOS\n\t\tvWorldPosition = worldPosition.xyz;\n\t#else\n\t\tvec3 cameraToVertex;\n\t\tif ( isOrthographic ) {\n\t\t\tcameraToVertex = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\n\t\t} else {\n\t\t\tcameraToVertex = normalize( worldPosition.xyz - cameraPosition );\n\t\t}\n\t\tvec3 worldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\n\t\t#ifdef ENVMAP_MODE_REFLECTION\n\t\t\tvReflect = reflect( cameraToVertex, worldNormal );\n\t\t#else\n\t\t\tvReflect = refract( cameraToVertex, worldNormal, refractionRatio );\n\t\t#endif\n\t#endif\n#endif",fog_vertex:"#ifdef USE_FOG\n\tvFogDepth = - mvPosition.z;\n#endif",fog_pars_vertex:"#ifdef USE_FOG\n\tvarying float vFogDepth;\n#endif",fog_fragment:"#ifdef USE_FOG\n\t#ifdef FOG_EXP2\n\t\tfloat fogFactor = 1.0 - exp( - fogDensity * fogDensity * vFogDepth * vFogDepth );\n\t#else\n\t\tfloat fogFactor = smoothstep( fogNear, fogFar, vFogDepth );\n\t#endif\n\tgl_FragColor.rgb = mix( gl_FragColor.rgb, fogColor, fogFactor );\n#endif",fog_pars_fragment:"#ifdef USE_FOG\n\tuniform vec3 fogColor;\n\tvarying float vFogDepth;\n\t#ifdef FOG_EXP2\n\t\tuniform float fogDensity;\n\t#else\n\t\tuniform float fogNear;\n\t\tuniform float fogFar;\n\t#endif\n#endif",gradientmap_pars_fragment:"#ifdef USE_GRADIENTMAP\n\tuniform sampler2D gradientMap;\n#endif\nvec3 getGradientIrradiance( vec3 normal, vec3 lightDirection ) {\n\tfloat dotNL = dot( normal, lightDirection );\n\tvec2 coord = vec2( dotNL * 0.5 + 0.5, 0.0 );\n\t#ifdef USE_GRADIENTMAP\n\t\treturn vec3( texture2D( gradientMap, coord ).r );\n\t#else\n\t\tvec2 fw = fwidth( coord ) * 0.5;\n\t\treturn mix( vec3( 0.7 ), vec3( 1.0 ), smoothstep( 0.7 - fw.x, 0.7 + fw.x, coord.x ) );\n\t#endif\n}",lightmap_pars_fragment:"#ifdef USE_LIGHTMAP\n\tuniform sampler2D lightMap;\n\tuniform float lightMapIntensity;\n#endif",lights_lambert_fragment:"LambertMaterial material;\nmaterial.diffuseColor = diffuseColor.rgb;\nmaterial.specularStrength = specularStrength;",lights_lambert_pars_fragment:"varying vec3 vViewPosition;\nstruct LambertMaterial {\n\tvec3 diffuseColor;\n\tfloat specularStrength;\n};\nvoid RE_Direct_Lambert( const in IncidentLight directLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in LambertMaterial material, inout ReflectedLight reflectedLight ) {\n\tfloat dotNL = saturate( dot( geometryNormal, directLight.direction ) );\n\tvec3 irradiance = dotNL * directLight.color;\n\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\nvoid RE_IndirectDiffuse_Lambert( const in vec3 irradiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in LambertMaterial material, inout ReflectedLight reflectedLight ) {\n\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\n#define RE_Direct\t\t\t\tRE_Direct_Lambert\n#define RE_IndirectDiffuse\t\tRE_IndirectDiffuse_Lambert",lights_pars_begin:"uniform bool receiveShadow;\nuniform vec3 ambientLightColor;\n#if defined( USE_LIGHT_PROBES )\n\tuniform vec3 lightProbe[ 9 ];\n#endif\nvec3 shGetIrradianceAt( in vec3 normal, in vec3 shCoefficients[ 9 ] ) {\n\tfloat x = normal.x, y = normal.y, z = normal.z;\n\tvec3 result = shCoefficients[ 0 ] * 0.886227;\n\tresult += shCoefficients[ 1 ] * 2.0 * 0.511664 * y;\n\tresult += shCoefficients[ 2 ] * 2.0 * 0.511664 * z;\n\tresult += shCoefficients[ 3 ] * 2.0 * 0.511664 * x;\n\tresult += shCoefficients[ 4 ] * 2.0 * 0.429043 * x * y;\n\tresult += shCoefficients[ 5 ] * 2.0 * 0.429043 * y * z;\n\tresult += shCoefficients[ 6 ] * ( 0.743125 * z * z - 0.247708 );\n\tresult += shCoefficients[ 7 ] * 2.0 * 0.429043 * x * z;\n\tresult += shCoefficients[ 8 ] * 0.429043 * ( x * x - y * y );\n\treturn result;\n}\nvec3 getLightProbeIrradiance( const in vec3 lightProbe[ 9 ], const in vec3 normal ) {\n\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\n\tvec3 irradiance = shGetIrradianceAt( worldNormal, lightProbe );\n\treturn irradiance;\n}\nvec3 getAmbientLightIrradiance( const in vec3 ambientLightColor ) {\n\tvec3 irradiance = ambientLightColor;\n\treturn irradiance;\n}\nfloat getDistanceAttenuation( const in float lightDistance, const in float cutoffDistance, const in float decayExponent ) {\n\tfloat distanceFalloff = 1.0 / max( pow( lightDistance, decayExponent ), 0.01 );\n\tif ( cutoffDistance > 0.0 ) {\n\t\tdistanceFalloff *= pow2( saturate( 1.0 - pow4( lightDistance / cutoffDistance ) ) );\n\t}\n\treturn distanceFalloff;\n}\nfloat getSpotAttenuation( const in float coneCosine, const in float penumbraCosine, const in float angleCosine ) {\n\treturn smoothstep( coneCosine, penumbraCosine, angleCosine );\n}\n#if NUM_DIR_LIGHTS > 0\n\tstruct DirectionalLight {\n\t\tvec3 direction;\n\t\tvec3 color;\n\t};\n\tuniform DirectionalLight directionalLights[ NUM_DIR_LIGHTS ];\n\tvoid getDirectionalLightInfo( const in DirectionalLight directionalLight, out IncidentLight light ) {\n\t\tlight.color = directionalLight.color;\n\t\tlight.direction = directionalLight.direction;\n\t\tlight.visible = true;\n\t}\n#endif\n#if NUM_POINT_LIGHTS > 0\n\tstruct PointLight {\n\t\tvec3 position;\n\t\tvec3 color;\n\t\tfloat distance;\n\t\tfloat decay;\n\t};\n\tuniform PointLight pointLights[ NUM_POINT_LIGHTS ];\n\tvoid getPointLightInfo( const in PointLight pointLight, const in vec3 geometryPosition, out IncidentLight light ) {\n\t\tvec3 lVector = pointLight.position - geometryPosition;\n\t\tlight.direction = normalize( lVector );\n\t\tfloat lightDistance = length( lVector );\n\t\tlight.color = pointLight.color;\n\t\tlight.color *= getDistanceAttenuation( lightDistance, pointLight.distance, pointLight.decay );\n\t\tlight.visible = ( light.color != vec3( 0.0 ) );\n\t}\n#endif\n#if NUM_SPOT_LIGHTS > 0\n\tstruct SpotLight {\n\t\tvec3 position;\n\t\tvec3 direction;\n\t\tvec3 color;\n\t\tfloat distance;\n\t\tfloat decay;\n\t\tfloat coneCos;\n\t\tfloat penumbraCos;\n\t};\n\tuniform SpotLight spotLights[ NUM_SPOT_LIGHTS ];\n\tvoid getSpotLightInfo( const in SpotLight spotLight, const in vec3 geometryPosition, out IncidentLight light ) {\n\t\tvec3 lVector = spotLight.position - geometryPosition;\n\t\tlight.direction = normalize( lVector );\n\t\tfloat angleCos = dot( light.direction, spotLight.direction );\n\t\tfloat spotAttenuation = getSpotAttenuation( spotLight.coneCos, spotLight.penumbraCos, angleCos );\n\t\tif ( spotAttenuation > 0.0 ) {\n\t\t\tfloat lightDistance = length( lVector );\n\t\t\tlight.color = spotLight.color * spotAttenuation;\n\t\t\tlight.color *= getDistanceAttenuation( lightDistance, spotLight.distance, spotLight.decay );\n\t\t\tlight.visible = ( light.color != vec3( 0.0 ) );\n\t\t} else {\n\t\t\tlight.color = vec3( 0.0 );\n\t\t\tlight.visible = false;\n\t\t}\n\t}\n#endif\n#if NUM_RECT_AREA_LIGHTS > 0\n\tstruct RectAreaLight {\n\t\tvec3 color;\n\t\tvec3 position;\n\t\tvec3 halfWidth;\n\t\tvec3 halfHeight;\n\t};\n\tuniform sampler2D ltc_1;\tuniform sampler2D ltc_2;\n\tuniform RectAreaLight rectAreaLights[ NUM_RECT_AREA_LIGHTS ];\n#endif\n#if NUM_HEMI_LIGHTS > 0\n\tstruct HemisphereLight {\n\t\tvec3 direction;\n\t\tvec3 skyColor;\n\t\tvec3 groundColor;\n\t};\n\tuniform HemisphereLight hemisphereLights[ NUM_HEMI_LIGHTS ];\n\tvec3 getHemisphereLightIrradiance( const in HemisphereLight hemiLight, const in vec3 normal ) {\n\t\tfloat dotNL = dot( normal, hemiLight.direction );\n\t\tfloat hemiDiffuseWeight = 0.5 * dotNL + 0.5;\n\t\tvec3 irradiance = mix( hemiLight.groundColor, hemiLight.skyColor, hemiDiffuseWeight );\n\t\treturn irradiance;\n\t}\n#endif",lights_toon_fragment:"ToonMaterial material;\nmaterial.diffuseColor = diffuseColor.rgb;",lights_toon_pars_fragment:"varying vec3 vViewPosition;\nstruct ToonMaterial {\n\tvec3 diffuseColor;\n};\nvoid RE_Direct_Toon( const in IncidentLight directLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\n\tvec3 irradiance = getGradientIrradiance( geometryNormal, directLight.direction ) * directLight.color;\n\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\nvoid RE_IndirectDiffuse_Toon( const in vec3 irradiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\n\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\n#define RE_Direct\t\t\t\tRE_Direct_Toon\n#define RE_IndirectDiffuse\t\tRE_IndirectDiffuse_Toon",lights_phong_fragment:"BlinnPhongMaterial material;\nmaterial.diffuseColor = diffuseColor.rgb;\nmaterial.specularColor = specular;\nmaterial.specularShininess = shininess;\nmaterial.specularStrength = specularStrength;",lights_phong_pars_fragment:"varying vec3 vViewPosition;\nstruct BlinnPhongMaterial {\n\tvec3 diffuseColor;\n\tvec3 specularColor;\n\tfloat specularShininess;\n\tfloat specularStrength;\n};\nvoid RE_Direct_BlinnPhong( const in IncidentLight directLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\n\tfloat dotNL = saturate( dot( geometryNormal, directLight.direction ) );\n\tvec3 irradiance = dotNL * directLight.color;\n\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n\treflectedLight.directSpecular += irradiance * BRDF_BlinnPhong( directLight.direction, geometryViewDir, geometryNormal, material.specularColor, material.specularShininess ) * material.specularStrength;\n}\nvoid RE_IndirectDiffuse_BlinnPhong( const in vec3 irradiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\n\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\n#define RE_Direct\t\t\t\tRE_Direct_BlinnPhong\n#define RE_IndirectDiffuse\t\tRE_IndirectDiffuse_BlinnPhong",lights_physical_fragment:"PhysicalMaterial material;\nmaterial.diffuseColor = diffuseColor.rgb * ( 1.0 - metalnessFactor );\nvec3 dxy = max( abs( dFdx( nonPerturbedNormal ) ), abs( dFdy( nonPerturbedNormal ) ) );\nfloat geometryRoughness = max( max( dxy.x, dxy.y ), dxy.z );\nmaterial.roughness = max( roughnessFactor, 0.0525 );material.roughness += geometryRoughness;\nmaterial.roughness = min( material.roughness, 1.0 );\n#ifdef IOR\n\tmaterial.ior = ior;\n\t#ifdef USE_SPECULAR\n\t\tfloat specularIntensityFactor = specularIntensity;\n\t\tvec3 specularColorFactor = specularColor;\n\t\t#ifdef USE_SPECULAR_COLORMAP\n\t\t\tspecularColorFactor *= texture2D( specularColorMap, vSpecularColorMapUv ).rgb;\n\t\t#endif\n\t\t#ifdef USE_SPECULAR_INTENSITYMAP\n\t\t\tspecularIntensityFactor *= texture2D( specularIntensityMap, vSpecularIntensityMapUv ).a;\n\t\t#endif\n\t\tmaterial.specularF90 = mix( specularIntensityFactor, 1.0, metalnessFactor );\n\t#else\n\t\tfloat specularIntensityFactor = 1.0;\n\t\tvec3 specularColorFactor = vec3( 1.0 );\n\t\tmaterial.specularF90 = 1.0;\n\t#endif\n\tmaterial.specularColor = mix( min( pow2( ( material.ior - 1.0 ) / ( material.ior + 1.0 ) ) * specularColorFactor, vec3( 1.0 ) ) * specularIntensityFactor, diffuseColor.rgb, metalnessFactor );\n#else\n\tmaterial.specularColor = mix( vec3( 0.04 ), diffuseColor.rgb, metalnessFactor );\n\tmaterial.specularF90 = 1.0;\n#endif\n#ifdef USE_CLEARCOAT\n\tmaterial.clearcoat = clearcoat;\n\tmaterial.clearcoatRoughness = clearcoatRoughness;\n\tmaterial.clearcoatF0 = vec3( 0.04 );\n\tmaterial.clearcoatF90 = 1.0;\n\t#ifdef USE_CLEARCOATMAP\n\t\tmaterial.clearcoat *= texture2D( clearcoatMap, vClearcoatMapUv ).x;\n\t#endif\n\t#ifdef USE_CLEARCOAT_ROUGHNESSMAP\n\t\tmaterial.clearcoatRoughness *= texture2D( clearcoatRoughnessMap, vClearcoatRoughnessMapUv ).y;\n\t#endif\n\tmaterial.clearcoat = saturate( material.clearcoat );\tmaterial.clearcoatRoughness = max( material.clearcoatRoughness, 0.0525 );\n\tmaterial.clearcoatRoughness += geometryRoughness;\n\tmaterial.clearcoatRoughness = min( material.clearcoatRoughness, 1.0 );\n#endif\n#ifdef USE_DISPERSION\n\tmaterial.dispersion = dispersion;\n#endif\n#ifdef USE_IRIDESCENCE\n\tmaterial.iridescence = iridescence;\n\tmaterial.iridescenceIOR = iridescenceIOR;\n\t#ifdef USE_IRIDESCENCEMAP\n\t\tmaterial.iridescence *= texture2D( iridescenceMap, vIridescenceMapUv ).r;\n\t#endif\n\t#ifdef USE_IRIDESCENCE_THICKNESSMAP\n\t\tmaterial.iridescenceThickness = (iridescenceThicknessMaximum - iridescenceThicknessMinimum) * texture2D( iridescenceThicknessMap, vIridescenceThicknessMapUv ).g + iridescenceThicknessMinimum;\n\t#else\n\t\tmaterial.iridescenceThickness = iridescenceThicknessMaximum;\n\t#endif\n#endif\n#ifdef USE_SHEEN\n\tmaterial.sheenColor = sheenColor;\n\t#ifdef USE_SHEEN_COLORMAP\n\t\tmaterial.sheenColor *= texture2D( sheenColorMap, vSheenColorMapUv ).rgb;\n\t#endif\n\tmaterial.sheenRoughness = clamp( sheenRoughness, 0.07, 1.0 );\n\t#ifdef USE_SHEEN_ROUGHNESSMAP\n\t\tmaterial.sheenRoughness *= texture2D( sheenRoughnessMap, vSheenRoughnessMapUv ).a;\n\t#endif\n#endif\n#ifdef USE_ANISOTROPY\n\t#ifdef USE_ANISOTROPYMAP\n\t\tmat2 anisotropyMat = mat2( anisotropyVector.x, anisotropyVector.y, - anisotropyVector.y, anisotropyVector.x );\n\t\tvec3 anisotropyPolar = texture2D( anisotropyMap, vAnisotropyMapUv ).rgb;\n\t\tvec2 anisotropyV = anisotropyMat * normalize( 2.0 * anisotropyPolar.rg - vec2( 1.0 ) ) * anisotropyPolar.b;\n\t#else\n\t\tvec2 anisotropyV = anisotropyVector;\n\t#endif\n\tmaterial.anisotropy = length( anisotropyV );\n\tif( material.anisotropy == 0.0 ) {\n\t\tanisotropyV = vec2( 1.0, 0.0 );\n\t} else {\n\t\tanisotropyV /= material.anisotropy;\n\t\tmaterial.anisotropy = saturate( material.anisotropy );\n\t}\n\tmaterial.alphaT = mix( pow2( material.roughness ), 1.0, pow2( material.anisotropy ) );\n\tmaterial.anisotropyT = tbn[ 0 ] * anisotropyV.x + tbn[ 1 ] * anisotropyV.y;\n\tmaterial.anisotropyB = tbn[ 1 ] * anisotropyV.x - tbn[ 0 ] * anisotropyV.y;\n#endif",lights_physical_pars_fragment:"struct PhysicalMaterial {\n\tvec3 diffuseColor;\n\tfloat roughness;\n\tvec3 specularColor;\n\tfloat specularF90;\n\tfloat dispersion;\n\t#ifdef USE_CLEARCOAT\n\t\tfloat clearcoat;\n\t\tfloat clearcoatRoughness;\n\t\tvec3 clearcoatF0;\n\t\tfloat clearcoatF90;\n\t#endif\n\t#ifdef USE_IRIDESCENCE\n\t\tfloat iridescence;\n\t\tfloat iridescenceIOR;\n\t\tfloat iridescenceThickness;\n\t\tvec3 iridescenceFresnel;\n\t\tvec3 iridescenceF0;\n\t#endif\n\t#ifdef USE_SHEEN\n\t\tvec3 sheenColor;\n\t\tfloat sheenRoughness;\n\t#endif\n\t#ifdef IOR\n\t\tfloat ior;\n\t#endif\n\t#ifdef USE_TRANSMISSION\n\t\tfloat transmission;\n\t\tfloat transmissionAlpha;\n\t\tfloat thickness;\n\t\tfloat attenuationDistance;\n\t\tvec3 attenuationColor;\n\t#endif\n\t#ifdef USE_ANISOTROPY\n\t\tfloat anisotropy;\n\t\tfloat alphaT;\n\t\tvec3 anisotropyT;\n\t\tvec3 anisotropyB;\n\t#endif\n};\nvec3 clearcoatSpecularDirect = vec3( 0.0 );\nvec3 clearcoatSpecularIndirect = vec3( 0.0 );\nvec3 sheenSpecularDirect = vec3( 0.0 );\nvec3 sheenSpecularIndirect = vec3(0.0 );\nvec3 Schlick_to_F0( const in vec3 f, const in float f90, const in float dotVH ) {\n    float x = clamp( 1.0 - dotVH, 0.0, 1.0 );\n    float x2 = x * x;\n    float x5 = clamp( x * x2 * x2, 0.0, 0.9999 );\n    return ( f - vec3( f90 ) * x5 ) / ( 1.0 - x5 );\n}\nfloat V_GGX_SmithCorrelated( const in float alpha, const in float dotNL, const in float dotNV ) {\n\tfloat a2 = pow2( alpha );\n\tfloat gv = dotNL * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNV ) );\n\tfloat gl = dotNV * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNL ) );\n\treturn 0.5 / max( gv + gl, EPSILON );\n}\nfloat D_GGX( const in float alpha, const in float dotNH ) {\n\tfloat a2 = pow2( alpha );\n\tfloat denom = pow2( dotNH ) * ( a2 - 1.0 ) + 1.0;\n\treturn RECIPROCAL_PI * a2 / pow2( denom );\n}\n#ifdef USE_ANISOTROPY\n\tfloat V_GGX_SmithCorrelated_Anisotropic( const in float alphaT, const in float alphaB, const in float dotTV, const in float dotBV, const in float dotTL, const in float dotBL, const in float dotNV, const in float dotNL ) {\n\t\tfloat gv = dotNL * length( vec3( alphaT * dotTV, alphaB * dotBV, dotNV ) );\n\t\tfloat gl = dotNV * length( vec3( alphaT * dotTL, alphaB * dotBL, dotNL ) );\n\t\tfloat v = 0.5 / ( gv + gl );\n\t\treturn saturate(v);\n\t}\n\tfloat D_GGX_Anisotropic( const in float alphaT, const in float alphaB, const in float dotNH, const in float dotTH, const in float dotBH ) {\n\t\tfloat a2 = alphaT * alphaB;\n\t\thighp vec3 v = vec3( alphaB * dotTH, alphaT * dotBH, a2 * dotNH );\n\t\thighp float v2 = dot( v, v );\n\t\tfloat w2 = a2 / v2;\n\t\treturn RECIPROCAL_PI * a2 * pow2 ( w2 );\n\t}\n#endif\n#ifdef USE_CLEARCOAT\n\tvec3 BRDF_GGX_Clearcoat( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in PhysicalMaterial material) {\n\t\tvec3 f0 = material.clearcoatF0;\n\t\tfloat f90 = material.clearcoatF90;\n\t\tfloat roughness = material.clearcoatRoughness;\n\t\tfloat alpha = pow2( roughness );\n\t\tvec3 halfDir = normalize( lightDir + viewDir );\n\t\tfloat dotNL = saturate( dot( normal, lightDir ) );\n\t\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\t\tfloat dotNH = saturate( dot( normal, halfDir ) );\n\t\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\n\t\tvec3 F = F_Schlick( f0, f90, dotVH );\n\t\tfloat V = V_GGX_SmithCorrelated( alpha, dotNL, dotNV );\n\t\tfloat D = D_GGX( alpha, dotNH );\n\t\treturn F * ( V * D );\n\t}\n#endif\nvec3 BRDF_GGX( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in PhysicalMaterial material ) {\n\tvec3 f0 = material.specularColor;\n\tfloat f90 = material.specularF90;\n\tfloat roughness = material.roughness;\n\tfloat alpha = pow2( roughness );\n\tvec3 halfDir = normalize( lightDir + viewDir );\n\tfloat dotNL = saturate( dot( normal, lightDir ) );\n\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\tfloat dotNH = saturate( dot( normal, halfDir ) );\n\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\n\tvec3 F = F_Schlick( f0, f90, dotVH );\n\t#ifdef USE_IRIDESCENCE\n\t\tF = mix( F, material.iridescenceFresnel, material.iridescence );\n\t#endif\n\t#ifdef USE_ANISOTROPY\n\t\tfloat dotTL = dot( material.anisotropyT, lightDir );\n\t\tfloat dotTV = dot( material.anisotropyT, viewDir );\n\t\tfloat dotTH = dot( material.anisotropyT, halfDir );\n\t\tfloat dotBL = dot( material.anisotropyB, lightDir );\n\t\tfloat dotBV = dot( material.anisotropyB, viewDir );\n\t\tfloat dotBH = dot( material.anisotropyB, halfDir );\n\t\tfloat V = V_GGX_SmithCorrelated_Anisotropic( material.alphaT, alpha, dotTV, dotBV, dotTL, dotBL, dotNV, dotNL );\n\t\tfloat D = D_GGX_Anisotropic( material.alphaT, alpha, dotNH, dotTH, dotBH );\n\t#else\n\t\tfloat V = V_GGX_SmithCorrelated( alpha, dotNL, dotNV );\n\t\tfloat D = D_GGX( alpha, dotNH );\n\t#endif\n\treturn F * ( V * D );\n}\nvec2 LTC_Uv( const in vec3 N, const in vec3 V, const in float roughness ) {\n\tconst float LUT_SIZE = 64.0;\n\tconst float LUT_SCALE = ( LUT_SIZE - 1.0 ) / LUT_SIZE;\n\tconst float LUT_BIAS = 0.5 / LUT_SIZE;\n\tfloat dotNV = saturate( dot( N, V ) );\n\tvec2 uv = vec2( roughness, sqrt( 1.0 - dotNV ) );\n\tuv = uv * LUT_SCALE + LUT_BIAS;\n\treturn uv;\n}\nfloat LTC_ClippedSphereFormFactor( const in vec3 f ) {\n\tfloat l = length( f );\n\treturn max( ( l * l + f.z ) / ( l + 1.0 ), 0.0 );\n}\nvec3 LTC_EdgeVectorFormFactor( const in vec3 v1, const in vec3 v2 ) {\n\tfloat x = dot( v1, v2 );\n\tfloat y = abs( x );\n\tfloat a = 0.8543985 + ( 0.4965155 + 0.0145206 * y ) * y;\n\tfloat b = 3.4175940 + ( 4.1616724 + y ) * y;\n\tfloat v = a / b;\n\tfloat theta_sintheta = ( x > 0.0 ) ? v : 0.5 * inversesqrt( max( 1.0 - x * x, 1e-7 ) ) - v;\n\treturn cross( v1, v2 ) * theta_sintheta;\n}\nvec3 LTC_Evaluate( const in vec3 N, const in vec3 V, const in vec3 P, const in mat3 mInv, const in vec3 rectCoords[ 4 ] ) {\n\tvec3 v1 = rectCoords[ 1 ] - rectCoords[ 0 ];\n\tvec3 v2 = rectCoords[ 3 ] - rectCoords[ 0 ];\n\tvec3 lightNormal = cross( v1, v2 );\n\tif( dot( lightNormal, P - rectCoords[ 0 ] ) < 0.0 ) return vec3( 0.0 );\n\tvec3 T1, T2;\n\tT1 = normalize( V - N * dot( V, N ) );\n\tT2 = - cross( N, T1 );\n\tmat3 mat = mInv * transposeMat3( mat3( T1, T2, N ) );\n\tvec3 coords[ 4 ];\n\tcoords[ 0 ] = mat * ( rectCoords[ 0 ] - P );\n\tcoords[ 1 ] = mat * ( rectCoords[ 1 ] - P );\n\tcoords[ 2 ] = mat * ( rectCoords[ 2 ] - P );\n\tcoords[ 3 ] = mat * ( rectCoords[ 3 ] - P );\n\tcoords[ 0 ] = normalize( coords[ 0 ] );\n\tcoords[ 1 ] = normalize( coords[ 1 ] );\n\tcoords[ 2 ] = normalize( coords[ 2 ] );\n\tcoords[ 3 ] = normalize( coords[ 3 ] );\n\tvec3 vectorFormFactor = vec3( 0.0 );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 0 ], coords[ 1 ] );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 1 ], coords[ 2 ] );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 2 ], coords[ 3 ] );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 3 ], coords[ 0 ] );\n\tfloat result = LTC_ClippedSphereFormFactor( vectorFormFactor );\n\treturn vec3( result );\n}\n#if defined( USE_SHEEN )\nfloat D_Charlie( float roughness, float dotNH ) {\n\tfloat alpha = pow2( roughness );\n\tfloat invAlpha = 1.0 / alpha;\n\tfloat cos2h = dotNH * dotNH;\n\tfloat sin2h = max( 1.0 - cos2h, 0.0078125 );\n\treturn ( 2.0 + invAlpha ) * pow( sin2h, invAlpha * 0.5 ) / ( 2.0 * PI );\n}\nfloat V_Neubelt( float dotNV, float dotNL ) {\n\treturn saturate( 1.0 / ( 4.0 * ( dotNL + dotNV - dotNL * dotNV ) ) );\n}\nvec3 BRDF_Sheen( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, vec3 sheenColor, const in float sheenRoughness ) {\n\tvec3 halfDir = normalize( lightDir + viewDir );\n\tfloat dotNL = saturate( dot( normal, lightDir ) );\n\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\tfloat dotNH = saturate( dot( normal, halfDir ) );\n\tfloat D = D_Charlie( sheenRoughness, dotNH );\n\tfloat V = V_Neubelt( dotNV, dotNL );\n\treturn sheenColor * ( D * V );\n}\n#endif\nfloat IBLSheenBRDF( const in vec3 normal, const in vec3 viewDir, const in float roughness ) {\n\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\tfloat r2 = roughness * roughness;\n\tfloat a = roughness < 0.25 ? -339.2 * r2 + 161.4 * roughness - 25.9 : -8.48 * r2 + 14.3 * roughness - 9.95;\n\tfloat b = roughness < 0.25 ? 44.0 * r2 - 23.7 * roughness + 3.26 : 1.97 * r2 - 3.27 * roughness + 0.72;\n\tfloat DG = exp( a * dotNV + b ) + ( roughness < 0.25 ? 0.0 : 0.1 * ( roughness - 0.25 ) );\n\treturn saturate( DG * RECIPROCAL_PI );\n}\nvec2 DFGApprox( const in vec3 normal, const in vec3 viewDir, const in float roughness ) {\n\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\tconst vec4 c0 = vec4( - 1, - 0.0275, - 0.572, 0.022 );\n\tconst vec4 c1 = vec4( 1, 0.0425, 1.04, - 0.04 );\n\tvec4 r = roughness * c0 + c1;\n\tfloat a004 = min( r.x * r.x, exp2( - 9.28 * dotNV ) ) * r.x + r.y;\n\tvec2 fab = vec2( - 1.04, 1.04 ) * a004 + r.zw;\n\treturn fab;\n}\nvec3 EnvironmentBRDF( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness ) {\n\tvec2 fab = DFGApprox( normal, viewDir, roughness );\n\treturn specularColor * fab.x + specularF90 * fab.y;\n}\n#ifdef USE_IRIDESCENCE\nvoid computeMultiscatteringIridescence( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float iridescence, const in vec3 iridescenceF0, const in float roughness, inout vec3 singleScatter, inout vec3 multiScatter ) {\n#else\nvoid computeMultiscattering( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness, inout vec3 singleScatter, inout vec3 multiScatter ) {\n#endif\n\tvec2 fab = DFGApprox( normal, viewDir, roughness );\n\t#ifdef USE_IRIDESCENCE\n\t\tvec3 Fr = mix( specularColor, iridescenceF0, iridescence );\n\t#else\n\t\tvec3 Fr = specularColor;\n\t#endif\n\tvec3 FssEss = Fr * fab.x + specularF90 * fab.y;\n\tfloat Ess = fab.x + fab.y;\n\tfloat Ems = 1.0 - Ess;\n\tvec3 Favg = Fr + ( 1.0 - Fr ) * 0.047619;\tvec3 Fms = FssEss * Favg / ( 1.0 - Ems * Favg );\n\tsingleScatter += FssEss;\n\tmultiScatter += Fms * Ems;\n}\n#if NUM_RECT_AREA_LIGHTS > 0\n\tvoid RE_Direct_RectArea_Physical( const in RectAreaLight rectAreaLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\n\t\tvec3 normal = geometryNormal;\n\t\tvec3 viewDir = geometryViewDir;\n\t\tvec3 position = geometryPosition;\n\t\tvec3 lightPos = rectAreaLight.position;\n\t\tvec3 halfWidth = rectAreaLight.halfWidth;\n\t\tvec3 halfHeight = rectAreaLight.halfHeight;\n\t\tvec3 lightColor = rectAreaLight.color;\n\t\tfloat roughness = material.roughness;\n\t\tvec3 rectCoords[ 4 ];\n\t\trectCoords[ 0 ] = lightPos + halfWidth - halfHeight;\t\trectCoords[ 1 ] = lightPos - halfWidth - halfHeight;\n\t\trectCoords[ 2 ] = lightPos - halfWidth + halfHeight;\n\t\trectCoords[ 3 ] = lightPos + halfWidth + halfHeight;\n\t\tvec2 uv = LTC_Uv( normal, viewDir, roughness );\n\t\tvec4 t1 = texture2D( ltc_1, uv );\n\t\tvec4 t2 = texture2D( ltc_2, uv );\n\t\tmat3 mInv = mat3(\n\t\t\tvec3( t1.x, 0, t1.y ),\n\t\t\tvec3(    0, 1,    0 ),\n\t\t\tvec3( t1.z, 0, t1.w )\n\t\t);\n\t\tvec3 fresnel = ( material.specularColor * t2.x + ( vec3( 1.0 ) - material.specularColor ) * t2.y );\n\t\treflectedLight.directSpecular += lightColor * fresnel * LTC_Evaluate( normal, viewDir, position, mInv, rectCoords );\n\t\treflectedLight.directDiffuse += lightColor * material.diffuseColor * LTC_Evaluate( normal, viewDir, position, mat3( 1.0 ), rectCoords );\n\t}\n#endif\nvoid RE_Direct_Physical( const in IncidentLight directLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\n\tfloat dotNL = saturate( dot( geometryNormal, directLight.direction ) );\n\tvec3 irradiance = dotNL * directLight.color;\n\t#ifdef USE_CLEARCOAT\n\t\tfloat dotNLcc = saturate( dot( geometryClearcoatNormal, directLight.direction ) );\n\t\tvec3 ccIrradiance = dotNLcc * directLight.color;\n\t\tclearcoatSpecularDirect += ccIrradiance * BRDF_GGX_Clearcoat( directLight.direction, geometryViewDir, geometryClearcoatNormal, material );\n\t#endif\n\t#ifdef USE_SHEEN\n\t\tsheenSpecularDirect += irradiance * BRDF_Sheen( directLight.direction, geometryViewDir, geometryNormal, material.sheenColor, material.sheenRoughness );\n\t#endif\n\treflectedLight.directSpecular += irradiance * BRDF_GGX( directLight.direction, geometryViewDir, geometryNormal, material );\n\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\nvoid RE_IndirectDiffuse_Physical( const in vec3 irradiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\n\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\nvoid RE_IndirectSpecular_Physical( const in vec3 radiance, const in vec3 irradiance, const in vec3 clearcoatRadiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in PhysicalMaterial material, inout ReflectedLight reflectedLight) {\n\t#ifdef USE_CLEARCOAT\n\t\tclearcoatSpecularIndirect += clearcoatRadiance * EnvironmentBRDF( geometryClearcoatNormal, geometryViewDir, material.clearcoatF0, material.clearcoatF90, material.clearcoatRoughness );\n\t#endif\n\t#ifdef USE_SHEEN\n\t\tsheenSpecularIndirect += irradiance * material.sheenColor * IBLSheenBRDF( geometryNormal, geometryViewDir, material.sheenRoughness );\n\t#endif\n\tvec3 singleScattering = vec3( 0.0 );\n\tvec3 multiScattering = vec3( 0.0 );\n\tvec3 cosineWeightedIrradiance = irradiance * RECIPROCAL_PI;\n\t#ifdef USE_IRIDESCENCE\n\t\tcomputeMultiscatteringIridescence( geometryNormal, geometryViewDir, material.specularColor, material.specularF90, material.iridescence, material.iridescenceFresnel, material.roughness, singleScattering, multiScattering );\n\t#else\n\t\tcomputeMultiscattering( geometryNormal, geometryViewDir, material.specularColor, material.specularF90, material.roughness, singleScattering, multiScattering );\n\t#endif\n\tvec3 totalScattering = singleScattering + multiScattering;\n\tvec3 diffuse = material.diffuseColor * ( 1.0 - max( max( totalScattering.r, totalScattering.g ), totalScattering.b ) );\n\treflectedLight.indirectSpecular += radiance * singleScattering;\n\treflectedLight.indirectSpecular += multiScattering * cosineWeightedIrradiance;\n\treflectedLight.indirectDiffuse += diffuse * cosineWeightedIrradiance;\n}\n#define RE_Direct\t\t\t\tRE_Direct_Physical\n#define RE_Direct_RectArea\t\tRE_Direct_RectArea_Physical\n#define RE_IndirectDiffuse\t\tRE_IndirectDiffuse_Physical\n#define RE_IndirectSpecular\t\tRE_IndirectSpecular_Physical\nfloat computeSpecularOcclusion( const in float dotNV, const in float ambientOcclusion, const in float roughness ) {\n\treturn saturate( pow( dotNV + ambientOcclusion, exp2( - 16.0 * roughness - 1.0 ) ) - 1.0 + ambientOcclusion );\n}",lights_fragment_begin:"\nvec3 geometryPosition = - vViewPosition;\nvec3 geometryNormal = normal;\nvec3 geometryViewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( vViewPosition );\nvec3 geometryClearcoatNormal = vec3( 0.0 );\n#ifdef USE_CLEARCOAT\n\tgeometryClearcoatNormal = clearcoatNormal;\n#endif\n#ifdef USE_IRIDESCENCE\n\tfloat dotNVi = saturate( dot( normal, geometryViewDir ) );\n\tif ( material.iridescenceThickness == 0.0 ) {\n\t\tmaterial.iridescence = 0.0;\n\t} else {\n\t\tmaterial.iridescence = saturate( material.iridescence );\n\t}\n\tif ( material.iridescence > 0.0 ) {\n\t\tmaterial.iridescenceFresnel = evalIridescence( 1.0, material.iridescenceIOR, dotNVi, material.iridescenceThickness, material.specularColor );\n\t\tmaterial.iridescenceF0 = Schlick_to_F0( material.iridescenceFresnel, 1.0, dotNVi );\n\t}\n#endif\nIncidentLight directLight;\n#if ( NUM_POINT_LIGHTS > 0 ) && defined( RE_Direct )\n\tPointLight pointLight;\n\t#if defined( USE_SHADOWMAP ) && NUM_POINT_LIGHT_SHADOWS > 0\n\tPointLightShadow pointLightShadow;\n\t#endif\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {\n\t\tpointLight = pointLights[ i ];\n\t\tgetPointLightInfo( pointLight, geometryPosition, directLight );\n\t\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_POINT_LIGHT_SHADOWS )\n\t\tpointLightShadow = pointLightShadows[ i ];\n\t\tdirectLight.color *= ( directLight.visible && receiveShadow ) ? getPointShadow( pointShadowMap[ i ], pointLightShadow.shadowMapSize, pointLightShadow.shadowIntensity, pointLightShadow.shadowBias, pointLightShadow.shadowRadius, vPointShadowCoord[ i ], pointLightShadow.shadowCameraNear, pointLightShadow.shadowCameraFar ) : 1.0;\n\t\t#endif\n\t\tRE_Direct( directLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if ( NUM_SPOT_LIGHTS > 0 ) && defined( RE_Direct )\n\tSpotLight spotLight;\n\tvec4 spotColor;\n\tvec3 spotLightCoord;\n\tbool inSpotLightMap;\n\t#if defined( USE_SHADOWMAP ) && NUM_SPOT_LIGHT_SHADOWS > 0\n\tSpotLightShadow spotLightShadow;\n\t#endif\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {\n\t\tspotLight = spotLights[ i ];\n\t\tgetSpotLightInfo( spotLight, geometryPosition, directLight );\n\t\t#if ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS_WITH_MAPS )\n\t\t#define SPOT_LIGHT_MAP_INDEX UNROLLED_LOOP_INDEX\n\t\t#elif ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )\n\t\t#define SPOT_LIGHT_MAP_INDEX NUM_SPOT_LIGHT_MAPS\n\t\t#else\n\t\t#define SPOT_LIGHT_MAP_INDEX ( UNROLLED_LOOP_INDEX - NUM_SPOT_LIGHT_SHADOWS + NUM_SPOT_LIGHT_SHADOWS_WITH_MAPS )\n\t\t#endif\n\t\t#if ( SPOT_LIGHT_MAP_INDEX < NUM_SPOT_LIGHT_MAPS )\n\t\t\tspotLightCoord = vSpotLightCoord[ i ].xyz / vSpotLightCoord[ i ].w;\n\t\t\tinSpotLightMap = all( lessThan( abs( spotLightCoord * 2. - 1. ), vec3( 1.0 ) ) );\n\t\t\tspotColor = texture2D( spotLightMap[ SPOT_LIGHT_MAP_INDEX ], spotLightCoord.xy );\n\t\t\tdirectLight.color = inSpotLightMap ? directLight.color * spotColor.rgb : directLight.color;\n\t\t#endif\n\t\t#undef SPOT_LIGHT_MAP_INDEX\n\t\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )\n\t\tspotLightShadow = spotLightShadows[ i ];\n\t\tdirectLight.color *= ( directLight.visible && receiveShadow ) ? getShadow( spotShadowMap[ i ], spotLightShadow.shadowMapSize, spotLightShadow.shadowIntensity, spotLightShadow.shadowBias, spotLightShadow.shadowRadius, vSpotLightCoord[ i ] ) : 1.0;\n\t\t#endif\n\t\tRE_Direct( directLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if ( NUM_DIR_LIGHTS > 0 ) && defined( RE_Direct )\n\tDirectionalLight directionalLight;\n\t#if defined( USE_SHADOWMAP ) && NUM_DIR_LIGHT_SHADOWS > 0\n\tDirectionalLightShadow directionalLightShadow;\n\t#endif\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {\n\t\tdirectionalLight = directionalLights[ i ];\n\t\tgetDirectionalLightInfo( directionalLight, directLight );\n\t\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_DIR_LIGHT_SHADOWS )\n\t\tdirectionalLightShadow = directionalLightShadows[ i ];\n\t\tdirectLight.color *= ( directLight.visible && receiveShadow ) ? getShadow( directionalShadowMap[ i ], directionalLightShadow.shadowMapSize, directionalLightShadow.shadowIntensity, directionalLightShadow.shadowBias, directionalLightShadow.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\n\t\t#endif\n\t\tRE_Direct( directLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if ( NUM_RECT_AREA_LIGHTS > 0 ) && defined( RE_Direct_RectArea )\n\tRectAreaLight rectAreaLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_RECT_AREA_LIGHTS; i ++ ) {\n\t\trectAreaLight = rectAreaLights[ i ];\n\t\tRE_Direct_RectArea( rectAreaLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if defined( RE_IndirectDiffuse )\n\tvec3 iblIrradiance = vec3( 0.0 );\n\tvec3 irradiance = getAmbientLightIrradiance( ambientLightColor );\n\t#if defined( USE_LIGHT_PROBES )\n\t\tirradiance += getLightProbeIrradiance( lightProbe, geometryNormal );\n\t#endif\n\t#if ( NUM_HEMI_LIGHTS > 0 )\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {\n\t\t\tirradiance += getHemisphereLightIrradiance( hemisphereLights[ i ], geometryNormal );\n\t\t}\n\t\t#pragma unroll_loop_end\n\t#endif\n#endif\n#if defined( RE_IndirectSpecular )\n\tvec3 radiance = vec3( 0.0 );\n\tvec3 clearcoatRadiance = vec3( 0.0 );\n#endif",lights_fragment_maps:"#if defined( RE_IndirectDiffuse )\n\t#ifdef USE_LIGHTMAP\n\t\tvec4 lightMapTexel = texture2D( lightMap, vLightMapUv );\n\t\tvec3 lightMapIrradiance = lightMapTexel.rgb * lightMapIntensity;\n\t\tirradiance += lightMapIrradiance;\n\t#endif\n\t#if defined( USE_ENVMAP ) && defined( STANDARD ) && defined( ENVMAP_TYPE_CUBE_UV )\n\t\tiblIrradiance += getIBLIrradiance( geometryNormal );\n\t#endif\n#endif\n#if defined( USE_ENVMAP ) && defined( RE_IndirectSpecular )\n\t#ifdef USE_ANISOTROPY\n\t\tradiance += getIBLAnisotropyRadiance( geometryViewDir, geometryNormal, material.roughness, material.anisotropyB, material.anisotropy );\n\t#else\n\t\tradiance += getIBLRadiance( geometryViewDir, geometryNormal, material.roughness );\n\t#endif\n\t#ifdef USE_CLEARCOAT\n\t\tclearcoatRadiance += getIBLRadiance( geometryViewDir, geometryClearcoatNormal, material.clearcoatRoughness );\n\t#endif\n#endif",lights_fragment_end:"#if defined( RE_IndirectDiffuse )\n\tRE_IndirectDiffuse( irradiance, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );\n#endif\n#if defined( RE_IndirectSpecular )\n\tRE_IndirectSpecular( radiance, iblIrradiance, clearcoatRadiance, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );\n#endif",logdepthbuf_fragment:"#if defined( USE_LOGARITHMIC_DEPTH_BUFFER )\n\tgl_FragDepth = vIsPerspective == 0.0 ? gl_FragCoord.z : log2( vFragDepth ) * logDepthBufFC * 0.5;\n#endif",logdepthbuf_pars_fragment:"#if defined( USE_LOGARITHMIC_DEPTH_BUFFER )\n\tuniform float logDepthBufFC;\n\tvarying float vFragDepth;\n\tvarying float vIsPerspective;\n#endif",logdepthbuf_pars_vertex:"#ifdef USE_LOGARITHMIC_DEPTH_BUFFER\n\tvarying float vFragDepth;\n\tvarying float vIsPerspective;\n#endif",logdepthbuf_vertex:"#ifdef USE_LOGARITHMIC_DEPTH_BUFFER\n\tvFragDepth = 1.0 + gl_Position.w;\n\tvIsPerspective = float( isPerspectiveMatrix( projectionMatrix ) );\n#endif",map_fragment:"#ifdef USE_MAP\n\tvec4 sampledDiffuseColor = texture2D( map, vMapUv );\n\t#ifdef DECODE_VIDEO_TEXTURE\n\t\tsampledDiffuseColor = sRGBTransferEOTF( sampledDiffuseColor );\n\t#endif\n\tdiffuseColor *= sampledDiffuseColor;\n#endif",map_pars_fragment:"#ifdef USE_MAP\n\tuniform sampler2D map;\n#endif",map_particle_fragment:"#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\n\t#if defined( USE_POINTS_UV )\n\t\tvec2 uv = vUv;\n\t#else\n\t\tvec2 uv = ( uvTransform * vec3( gl_PointCoord.x, 1.0 - gl_PointCoord.y, 1 ) ).xy;\n\t#endif\n#endif\n#ifdef USE_MAP\n\tdiffuseColor *= texture2D( map, uv );\n#endif\n#ifdef USE_ALPHAMAP\n\tdiffuseColor.a *= texture2D( alphaMap, uv ).g;\n#endif",map_particle_pars_fragment:"#if defined( USE_POINTS_UV )\n\tvarying vec2 vUv;\n#else\n\t#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\n\t\tuniform mat3 uvTransform;\n\t#endif\n#endif\n#ifdef USE_MAP\n\tuniform sampler2D map;\n#endif\n#ifdef USE_ALPHAMAP\n\tuniform sampler2D alphaMap;\n#endif",metalnessmap_fragment:"float metalnessFactor = metalness;\n#ifdef USE_METALNESSMAP\n\tvec4 texelMetalness = texture2D( metalnessMap, vMetalnessMapUv );\n\tmetalnessFactor *= texelMetalness.b;\n#endif",metalnessmap_pars_fragment:"#ifdef USE_METALNESSMAP\n\tuniform sampler2D metalnessMap;\n#endif",morphinstance_vertex:"#ifdef USE_INSTANCING_MORPH\n\tfloat morphTargetInfluences[ MORPHTARGETS_COUNT ];\n\tfloat morphTargetBaseInfluence = texelFetch( morphTexture, ivec2( 0, gl_InstanceID ), 0 ).r;\n\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\n\t\tmorphTargetInfluences[i] =  texelFetch( morphTexture, ivec2( i + 1, gl_InstanceID ), 0 ).r;\n\t}\n#endif",morphcolor_vertex:"#if defined( USE_MORPHCOLORS )\n\tvColor *= morphTargetBaseInfluence;\n\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\n\t\t#if defined( USE_COLOR_ALPHA )\n\t\t\tif ( morphTargetInfluences[ i ] != 0.0 ) vColor += getMorph( gl_VertexID, i, 2 ) * morphTargetInfluences[ i ];\n\t\t#elif defined( USE_COLOR )\n\t\t\tif ( morphTargetInfluences[ i ] != 0.0 ) vColor += getMorph( gl_VertexID, i, 2 ).rgb * morphTargetInfluences[ i ];\n\t\t#endif\n\t}\n#endif",morphnormal_vertex:"#ifdef USE_MORPHNORMALS\n\tobjectNormal *= morphTargetBaseInfluence;\n\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\n\t\tif ( morphTargetInfluences[ i ] != 0.0 ) objectNormal += getMorph( gl_VertexID, i, 1 ).xyz * morphTargetInfluences[ i ];\n\t}\n#endif",morphtarget_pars_vertex:"#ifdef USE_MORPHTARGETS\n\t#ifndef USE_INSTANCING_MORPH\n\t\tuniform float morphTargetBaseInfluence;\n\t\tuniform float morphTargetInfluences[ MORPHTARGETS_COUNT ];\n\t#endif\n\tuniform sampler2DArray morphTargetsTexture;\n\tuniform ivec2 morphTargetsTextureSize;\n\tvec4 getMorph( const in int vertexIndex, const in int morphTargetIndex, const in int offset ) {\n\t\tint texelIndex = vertexIndex * MORPHTARGETS_TEXTURE_STRIDE + offset;\n\t\tint y = texelIndex / morphTargetsTextureSize.x;\n\t\tint x = texelIndex - y * morphTargetsTextureSize.x;\n\t\tivec3 morphUV = ivec3( x, y, morphTargetIndex );\n\t\treturn texelFetch( morphTargetsTexture, morphUV, 0 );\n\t}\n#endif",morphtarget_vertex:"#ifdef USE_MORPHTARGETS\n\ttransformed *= morphTargetBaseInfluence;\n\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\n\t\tif ( morphTargetInfluences[ i ] != 0.0 ) transformed += getMorph( gl_VertexID, i, 0 ).xyz * morphTargetInfluences[ i ];\n\t}\n#endif",normal_fragment_begin:"float faceDirection = gl_FrontFacing ? 1.0 : - 1.0;\n#ifdef FLAT_SHADED\n\tvec3 fdx = dFdx( vViewPosition );\n\tvec3 fdy = dFdy( vViewPosition );\n\tvec3 normal = normalize( cross( fdx, fdy ) );\n#else\n\tvec3 normal = normalize( vNormal );\n\t#ifdef DOUBLE_SIDED\n\t\tnormal *= faceDirection;\n\t#endif\n#endif\n#if defined( USE_NORMALMAP_TANGENTSPACE ) || defined( USE_CLEARCOAT_NORMALMAP ) || defined( USE_ANISOTROPY )\n\t#ifdef USE_TANGENT\n\t\tmat3 tbn = mat3( normalize( vTangent ), normalize( vBitangent ), normal );\n\t#else\n\t\tmat3 tbn = getTangentFrame( - vViewPosition, normal,\n\t\t#if defined( USE_NORMALMAP )\n\t\t\tvNormalMapUv\n\t\t#elif defined( USE_CLEARCOAT_NORMALMAP )\n\t\t\tvClearcoatNormalMapUv\n\t\t#else\n\t\t\tvUv\n\t\t#endif\n\t\t);\n\t#endif\n\t#if defined( DOUBLE_SIDED ) && ! defined( FLAT_SHADED )\n\t\ttbn[0] *= faceDirection;\n\t\ttbn[1] *= faceDirection;\n\t#endif\n#endif\n#ifdef USE_CLEARCOAT_NORMALMAP\n\t#ifdef USE_TANGENT\n\t\tmat3 tbn2 = mat3( normalize( vTangent ), normalize( vBitangent ), normal );\n\t#else\n\t\tmat3 tbn2 = getTangentFrame( - vViewPosition, normal, vClearcoatNormalMapUv );\n\t#endif\n\t#if defined( DOUBLE_SIDED ) && ! defined( FLAT_SHADED )\n\t\ttbn2[0] *= faceDirection;\n\t\ttbn2[1] *= faceDirection;\n\t#endif\n#endif\nvec3 nonPerturbedNormal = normal;",normal_fragment_maps:"#ifdef USE_NORMALMAP_OBJECTSPACE\n\tnormal = texture2D( normalMap, vNormalMapUv ).xyz * 2.0 - 1.0;\n\t#ifdef FLIP_SIDED\n\t\tnormal = - normal;\n\t#endif\n\t#ifdef DOUBLE_SIDED\n\t\tnormal = normal * faceDirection;\n\t#endif\n\tnormal = normalize( normalMatrix * normal );\n#elif defined( USE_NORMALMAP_TANGENTSPACE )\n\tvec3 mapN = texture2D( normalMap, vNormalMapUv ).xyz * 2.0 - 1.0;\n\tmapN.xy *= normalScale;\n\tnormal = normalize( tbn * mapN );\n#elif defined( USE_BUMPMAP )\n\tnormal = perturbNormalArb( - vViewPosition, normal, dHdxy_fwd(), faceDirection );\n#endif",normal_pars_fragment:"#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n\t#ifdef USE_TANGENT\n\t\tvarying vec3 vTangent;\n\t\tvarying vec3 vBitangent;\n\t#endif\n#endif",normal_pars_vertex:"#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n\t#ifdef USE_TANGENT\n\t\tvarying vec3 vTangent;\n\t\tvarying vec3 vBitangent;\n\t#endif\n#endif",normal_vertex:"#ifndef FLAT_SHADED\n\tvNormal = normalize( transformedNormal );\n\t#ifdef USE_TANGENT\n\t\tvTangent = normalize( transformedTangent );\n\t\tvBitangent = normalize( cross( vNormal, vTangent ) * tangent.w );\n\t#endif\n#endif",normalmap_pars_fragment:"#ifdef USE_NORMALMAP\n\tuniform sampler2D normalMap;\n\tuniform vec2 normalScale;\n#endif\n#ifdef USE_NORMALMAP_OBJECTSPACE\n\tuniform mat3 normalMatrix;\n#endif\n#if ! defined ( USE_TANGENT ) && ( defined ( USE_NORMALMAP_TANGENTSPACE ) || defined ( USE_CLEARCOAT_NORMALMAP ) || defined( USE_ANISOTROPY ) )\n\tmat3 getTangentFrame( vec3 eye_pos, vec3 surf_norm, vec2 uv ) {\n\t\tvec3 q0 = dFdx( eye_pos.xyz );\n\t\tvec3 q1 = dFdy( eye_pos.xyz );\n\t\tvec2 st0 = dFdx( uv.st );\n\t\tvec2 st1 = dFdy( uv.st );\n\t\tvec3 N = surf_norm;\n\t\tvec3 q1perp = cross( q1, N );\n\t\tvec3 q0perp = cross( N, q0 );\n\t\tvec3 T = q1perp * st0.x + q0perp * st1.x;\n\t\tvec3 B = q1perp * st0.y + q0perp * st1.y;\n\t\tfloat det = max( dot( T, T ), dot( B, B ) );\n\t\tfloat scale = ( det == 0.0 ) ? 0.0 : inversesqrt( det );\n\t\treturn mat3( T * scale, B * scale, N );\n\t}\n#endif",clearcoat_normal_fragment_begin:"#ifdef USE_CLEARCOAT\n\tvec3 clearcoatNormal = nonPerturbedNormal;\n#endif",clearcoat_normal_fragment_maps:"#ifdef USE_CLEARCOAT_NORMALMAP\n\tvec3 clearcoatMapN = texture2D( clearcoatNormalMap, vClearcoatNormalMapUv ).xyz * 2.0 - 1.0;\n\tclearcoatMapN.xy *= clearcoatNormalScale;\n\tclearcoatNormal = normalize( tbn2 * clearcoatMapN );\n#endif",clearcoat_pars_fragment:"#ifdef USE_CLEARCOATMAP\n\tuniform sampler2D clearcoatMap;\n#endif\n#ifdef USE_CLEARCOAT_NORMALMAP\n\tuniform sampler2D clearcoatNormalMap;\n\tuniform vec2 clearcoatNormalScale;\n#endif\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\n\tuniform sampler2D clearcoatRoughnessMap;\n#endif",iridescence_pars_fragment:"#ifdef USE_IRIDESCENCEMAP\n\tuniform sampler2D iridescenceMap;\n#endif\n#ifdef USE_IRIDESCENCE_THICKNESSMAP\n\tuniform sampler2D iridescenceThicknessMap;\n#endif",opaque_fragment:"#ifdef OPAQUE\ndiffuseColor.a = 1.0;\n#endif\n#ifdef USE_TRANSMISSION\ndiffuseColor.a *= material.transmissionAlpha;\n#endif\ngl_FragColor = vec4( outgoingLight, diffuseColor.a );",packing:"vec3 packNormalToRGB( const in vec3 normal ) {\n\treturn normalize( normal ) * 0.5 + 0.5;\n}\nvec3 unpackRGBToNormal( const in vec3 rgb ) {\n\treturn 2.0 * rgb.xyz - 1.0;\n}\nconst float PackUpscale = 256. / 255.;const float UnpackDownscale = 255. / 256.;const float ShiftRight8 = 1. / 256.;\nconst float Inv255 = 1. / 255.;\nconst vec4 PackFactors = vec4( 1.0, 256.0, 256.0 * 256.0, 256.0 * 256.0 * 256.0 );\nconst vec2 UnpackFactors2 = vec2( UnpackDownscale, 1.0 / PackFactors.g );\nconst vec3 UnpackFactors3 = vec3( UnpackDownscale / PackFactors.rg, 1.0 / PackFactors.b );\nconst vec4 UnpackFactors4 = vec4( UnpackDownscale / PackFactors.rgb, 1.0 / PackFactors.a );\nvec4 packDepthToRGBA( const in float v ) {\n\tif( v <= 0.0 )\n\t\treturn vec4( 0., 0., 0., 0. );\n\tif( v >= 1.0 )\n\t\treturn vec4( 1., 1., 1., 1. );\n\tfloat vuf;\n\tfloat af = modf( v * PackFactors.a, vuf );\n\tfloat bf = modf( vuf * ShiftRight8, vuf );\n\tfloat gf = modf( vuf * ShiftRight8, vuf );\n\treturn vec4( vuf * Inv255, gf * PackUpscale, bf * PackUpscale, af );\n}\nvec3 packDepthToRGB( const in float v ) {\n\tif( v <= 0.0 )\n\t\treturn vec3( 0., 0., 0. );\n\tif( v >= 1.0 )\n\t\treturn vec3( 1., 1., 1. );\n\tfloat vuf;\n\tfloat bf = modf( v * PackFactors.b, vuf );\n\tfloat gf = modf( vuf * ShiftRight8, vuf );\n\treturn vec3( vuf * Inv255, gf * PackUpscale, bf );\n}\nvec2 packDepthToRG( const in float v ) {\n\tif( v <= 0.0 )\n\t\treturn vec2( 0., 0. );\n\tif( v >= 1.0 )\n\t\treturn vec2( 1., 1. );\n\tfloat vuf;\n\tfloat gf = modf( v * 256., vuf );\n\treturn vec2( vuf * Inv255, gf );\n}\nfloat unpackRGBAToDepth( const in vec4 v ) {\n\treturn dot( v, UnpackFactors4 );\n}\nfloat unpackRGBToDepth( const in vec3 v ) {\n\treturn dot( v, UnpackFactors3 );\n}\nfloat unpackRGToDepth( const in vec2 v ) {\n\treturn v.r * UnpackFactors2.r + v.g * UnpackFactors2.g;\n}\nvec4 pack2HalfToRGBA( const in vec2 v ) {\n\tvec4 r = vec4( v.x, fract( v.x * 255.0 ), v.y, fract( v.y * 255.0 ) );\n\treturn vec4( r.x - r.y / 255.0, r.y, r.z - r.w / 255.0, r.w );\n}\nvec2 unpackRGBATo2Half( const in vec4 v ) {\n\treturn vec2( v.x + ( v.y / 255.0 ), v.z + ( v.w / 255.0 ) );\n}\nfloat viewZToOrthographicDepth( const in float viewZ, const in float near, const in float far ) {\n\treturn ( viewZ + near ) / ( near - far );\n}\nfloat orthographicDepthToViewZ( const in float depth, const in float near, const in float far ) {\n\treturn depth * ( near - far ) - near;\n}\nfloat viewZToPerspectiveDepth( const in float viewZ, const in float near, const in float far ) {\n\treturn ( ( near + viewZ ) * far ) / ( ( far - near ) * viewZ );\n}\nfloat perspectiveDepthToViewZ( const in float depth, const in float near, const in float far ) {\n\treturn ( near * far ) / ( ( far - near ) * depth - far );\n}",premultiplied_alpha_fragment:"#ifdef PREMULTIPLIED_ALPHA\n\tgl_FragColor.rgb *= gl_FragColor.a;\n#endif",project_vertex:"vec4 mvPosition = vec4( transformed, 1.0 );\n#ifdef USE_BATCHING\n\tmvPosition = batchingMatrix * mvPosition;\n#endif\n#ifdef USE_INSTANCING\n\tmvPosition = instanceMatrix * mvPosition;\n#endif\nmvPosition = modelViewMatrix * mvPosition;\ngl_Position = projectionMatrix * mvPosition;",dithering_fragment:"#ifdef DITHERING\n\tgl_FragColor.rgb = dithering( gl_FragColor.rgb );\n#endif",dithering_pars_fragment:"#ifdef DITHERING\n\tvec3 dithering( vec3 color ) {\n\t\tfloat grid_position = rand( gl_FragCoord.xy );\n\t\tvec3 dither_shift_RGB = vec3( 0.25 / 255.0, -0.25 / 255.0, 0.25 / 255.0 );\n\t\tdither_shift_RGB = mix( 2.0 * dither_shift_RGB, -2.0 * dither_shift_RGB, grid_position );\n\t\treturn color + dither_shift_RGB;\n\t}\n#endif",roughnessmap_fragment:"float roughnessFactor = roughness;\n#ifdef USE_ROUGHNESSMAP\n\tvec4 texelRoughness = texture2D( roughnessMap, vRoughnessMapUv );\n\troughnessFactor *= texelRoughness.g;\n#endif",roughnessmap_pars_fragment:"#ifdef USE_ROUGHNESSMAP\n\tuniform sampler2D roughnessMap;\n#endif",shadowmap_pars_fragment:"#if NUM_SPOT_LIGHT_COORDS > 0\n\tvarying vec4 vSpotLightCoord[ NUM_SPOT_LIGHT_COORDS ];\n#endif\n#if NUM_SPOT_LIGHT_MAPS > 0\n\tuniform sampler2D spotLightMap[ NUM_SPOT_LIGHT_MAPS ];\n#endif\n#ifdef USE_SHADOWMAP\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\t\tuniform sampler2D directionalShadowMap[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tstruct DirectionalLightShadow {\n\t\t\tfloat shadowIntensity;\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_SPOT_LIGHT_SHADOWS > 0\n\t\tuniform sampler2D spotShadowMap[ NUM_SPOT_LIGHT_SHADOWS ];\n\t\tstruct SpotLightShadow {\n\t\t\tfloat shadowIntensity;\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\t\tuniform sampler2D pointShadowMap[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tstruct PointLightShadow {\n\t\t\tfloat shadowIntensity;\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t\tfloat shadowCameraNear;\n\t\t\tfloat shadowCameraFar;\n\t\t};\n\t\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\n\t#endif\n\tfloat texture2DCompare( sampler2D depths, vec2 uv, float compare ) {\n\t\tfloat depth = unpackRGBAToDepth( texture2D( depths, uv ) );\n\t\t#ifdef USE_REVERSED_DEPTH_BUFFER\n\t\t\treturn step( depth, compare );\n\t\t#else\n\t\t\treturn step( compare, depth );\n\t\t#endif\n\t}\n\tvec2 texture2DDistribution( sampler2D shadow, vec2 uv ) {\n\t\treturn unpackRGBATo2Half( texture2D( shadow, uv ) );\n\t}\n\tfloat VSMShadow( sampler2D shadow, vec2 uv, float compare ) {\n\t\tfloat occlusion = 1.0;\n\t\tvec2 distribution = texture2DDistribution( shadow, uv );\n\t\t#ifdef USE_REVERSED_DEPTH_BUFFER\n\t\t\tfloat hard_shadow = step( distribution.x, compare );\n\t\t#else\n\t\t\tfloat hard_shadow = step( compare, distribution.x );\n\t\t#endif\n\t\tif ( hard_shadow != 1.0 ) {\n\t\t\tfloat distance = compare - distribution.x;\n\t\t\tfloat variance = max( 0.00000, distribution.y * distribution.y );\n\t\t\tfloat softness_probability = variance / (variance + distance * distance );\t\t\tsoftness_probability = clamp( ( softness_probability - 0.3 ) / ( 0.95 - 0.3 ), 0.0, 1.0 );\t\t\tocclusion = clamp( max( hard_shadow, softness_probability ), 0.0, 1.0 );\n\t\t}\n\t\treturn occlusion;\n\t}\n\tfloat getShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowIntensity, float shadowBias, float shadowRadius, vec4 shadowCoord ) {\n\t\tfloat shadow = 1.0;\n\t\tshadowCoord.xyz /= shadowCoord.w;\n\t\tshadowCoord.z += shadowBias;\n\t\tbool inFrustum = shadowCoord.x >= 0.0 && shadowCoord.x <= 1.0 && shadowCoord.y >= 0.0 && shadowCoord.y <= 1.0;\n\t\tbool frustumTest = inFrustum && shadowCoord.z <= 1.0;\n\t\tif ( frustumTest ) {\n\t\t#if defined( SHADOWMAP_TYPE_PCF )\n\t\t\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\n\t\t\tfloat dx0 = - texelSize.x * shadowRadius;\n\t\t\tfloat dy0 = - texelSize.y * shadowRadius;\n\t\t\tfloat dx1 = + texelSize.x * shadowRadius;\n\t\t\tfloat dy1 = + texelSize.y * shadowRadius;\n\t\t\tfloat dx2 = dx0 / 2.0;\n\t\t\tfloat dy2 = dy0 / 2.0;\n\t\t\tfloat dx3 = dx1 / 2.0;\n\t\t\tfloat dy3 = dy1 / 2.0;\n\t\t\tshadow = (\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy2 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy2 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy2 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy3 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy3 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy3 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy1 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy1 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy1 ), shadowCoord.z )\n\t\t\t) * ( 1.0 / 17.0 );\n\t\t#elif defined( SHADOWMAP_TYPE_PCF_SOFT )\n\t\t\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\n\t\t\tfloat dx = texelSize.x;\n\t\t\tfloat dy = texelSize.y;\n\t\t\tvec2 uv = shadowCoord.xy;\n\t\t\tvec2 f = fract( uv * shadowMapSize + 0.5 );\n\t\t\tuv -= f * texelSize;\n\t\t\tshadow = (\n\t\t\t\ttexture2DCompare( shadowMap, uv, shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, uv + vec2( dx, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, uv + vec2( 0.0, dy ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, uv + texelSize, shadowCoord.z ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, 0.0 ), shadowCoord.z ),\n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 0.0 ), shadowCoord.z ),\n\t\t\t\t\t f.x ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, dy ), shadowCoord.z ),\n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, dy ), shadowCoord.z ),\n\t\t\t\t\t f.x ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( 0.0, -dy ), shadowCoord.z ),\n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( 0.0, 2.0 * dy ), shadowCoord.z ),\n\t\t\t\t\t f.y ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( dx, -dy ), shadowCoord.z ),\n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( dx, 2.0 * dy ), shadowCoord.z ),\n\t\t\t\t\t f.y ) +\n\t\t\t\tmix( mix( texture2DCompare( shadowMap, uv + vec2( -dx, -dy ), shadowCoord.z ),\n\t\t\t\t\t\t  texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, -dy ), shadowCoord.z ),\n\t\t\t\t\t\t  f.x ),\n\t\t\t\t\t mix( texture2DCompare( shadowMap, uv + vec2( -dx, 2.0 * dy ), shadowCoord.z ),\n\t\t\t\t\t\t  texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 2.0 * dy ), shadowCoord.z ),\n\t\t\t\t\t\t  f.x ),\n\t\t\t\t\t f.y )\n\t\t\t) * ( 1.0 / 9.0 );\n\t\t#elif defined( SHADOWMAP_TYPE_VSM )\n\t\t\tshadow = VSMShadow( shadowMap, shadowCoord.xy, shadowCoord.z );\n\t\t#else\n\t\t\tshadow = texture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z );\n\t\t#endif\n\t\t}\n\t\treturn mix( 1.0, shadow, shadowIntensity );\n\t}\n\tvec2 cubeToUV( vec3 v, float texelSizeY ) {\n\t\tvec3 absV = abs( v );\n\t\tfloat scaleToCube = 1.0 / max( absV.x, max( absV.y, absV.z ) );\n\t\tabsV *= scaleToCube;\n\t\tv *= scaleToCube * ( 1.0 - 2.0 * texelSizeY );\n\t\tvec2 planar = v.xy;\n\t\tfloat almostATexel = 1.5 * texelSizeY;\n\t\tfloat almostOne = 1.0 - almostATexel;\n\t\tif ( absV.z >= almostOne ) {\n\t\t\tif ( v.z > 0.0 )\n\t\t\t\tplanar.x = 4.0 - v.x;\n\t\t} else if ( absV.x >= almostOne ) {\n\t\t\tfloat signX = sign( v.x );\n\t\t\tplanar.x = v.z * signX + 2.0 * signX;\n\t\t} else if ( absV.y >= almostOne ) {\n\t\t\tfloat signY = sign( v.y );\n\t\t\tplanar.x = v.x + 2.0 * signY + 2.0;\n\t\t\tplanar.y = v.z * signY - 2.0;\n\t\t}\n\t\treturn vec2( 0.125, 0.25 ) * planar + vec2( 0.375, 0.75 );\n\t}\n\tfloat getPointShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowIntensity, float shadowBias, float shadowRadius, vec4 shadowCoord, float shadowCameraNear, float shadowCameraFar ) {\n\t\tfloat shadow = 1.0;\n\t\tvec3 lightToPosition = shadowCoord.xyz;\n\t\t\n\t\tfloat lightToPositionLength = length( lightToPosition );\n\t\tif ( lightToPositionLength - shadowCameraFar <= 0.0 && lightToPositionLength - shadowCameraNear >= 0.0 ) {\n\t\t\tfloat dp = ( lightToPositionLength - shadowCameraNear ) / ( shadowCameraFar - shadowCameraNear );\t\t\tdp += shadowBias;\n\t\t\tvec3 bd3D = normalize( lightToPosition );\n\t\t\tvec2 texelSize = vec2( 1.0 ) / ( shadowMapSize * vec2( 4.0, 2.0 ) );\n\t\t\t#if defined( SHADOWMAP_TYPE_PCF ) || defined( SHADOWMAP_TYPE_PCF_SOFT ) || defined( SHADOWMAP_TYPE_VSM )\n\t\t\t\tvec2 offset = vec2( - 1, 1 ) * shadowRadius * texelSize.y;\n\t\t\t\tshadow = (\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyy, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyy, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyx, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyx, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxy, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxy, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxx, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxx, texelSize.y ), dp )\n\t\t\t\t) * ( 1.0 / 9.0 );\n\t\t\t#else\n\t\t\t\tshadow = texture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp );\n\t\t\t#endif\n\t\t}\n\t\treturn mix( 1.0, shadow, shadowIntensity );\n\t}\n#endif",shadowmap_pars_vertex:"#if NUM_SPOT_LIGHT_COORDS > 0\n\tuniform mat4 spotLightMatrix[ NUM_SPOT_LIGHT_COORDS ];\n\tvarying vec4 vSpotLightCoord[ NUM_SPOT_LIGHT_COORDS ];\n#endif\n#ifdef USE_SHADOWMAP\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\t\tuniform mat4 directionalShadowMatrix[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tstruct DirectionalLightShadow {\n\t\t\tfloat shadowIntensity;\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_SPOT_LIGHT_SHADOWS > 0\n\t\tstruct SpotLightShadow {\n\t\t\tfloat shadowIntensity;\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\t\tuniform mat4 pointShadowMatrix[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tstruct PointLightShadow {\n\t\t\tfloat shadowIntensity;\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t\tfloat shadowCameraNear;\n\t\t\tfloat shadowCameraFar;\n\t\t};\n\t\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\n\t#endif\n#endif",shadowmap_vertex:"#if ( defined( USE_SHADOWMAP ) && ( NUM_DIR_LIGHT_SHADOWS > 0 || NUM_POINT_LIGHT_SHADOWS > 0 ) ) || ( NUM_SPOT_LIGHT_COORDS > 0 )\n\tvec3 shadowWorldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\n\tvec4 shadowWorldPosition;\n#endif\n#if defined( USE_SHADOWMAP )\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\n\t\t\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * directionalLightShadows[ i ].shadowNormalBias, 0 );\n\t\t\tvDirectionalShadowCoord[ i ] = directionalShadowMatrix[ i ] * shadowWorldPosition;\n\t\t}\n\t\t#pragma unroll_loop_end\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\n\t\t\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * pointLightShadows[ i ].shadowNormalBias, 0 );\n\t\t\tvPointShadowCoord[ i ] = pointShadowMatrix[ i ] * shadowWorldPosition;\n\t\t}\n\t\t#pragma unroll_loop_end\n\t#endif\n#endif\n#if NUM_SPOT_LIGHT_COORDS > 0\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_SPOT_LIGHT_COORDS; i ++ ) {\n\t\tshadowWorldPosition = worldPosition;\n\t\t#if ( defined( USE_SHADOWMAP ) && UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )\n\t\t\tshadowWorldPosition.xyz += shadowWorldNormal * spotLightShadows[ i ].shadowNormalBias;\n\t\t#endif\n\t\tvSpotLightCoord[ i ] = spotLightMatrix[ i ] * shadowWorldPosition;\n\t}\n\t#pragma unroll_loop_end\n#endif",shadowmask_pars_fragment:"float getShadowMask() {\n\tfloat shadow = 1.0;\n\t#ifdef USE_SHADOWMAP\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\tDirectionalLightShadow directionalLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\n\t\tdirectionalLight = directionalLightShadows[ i ];\n\t\tshadow *= receiveShadow ? getShadow( directionalShadowMap[ i ], directionalLight.shadowMapSize, directionalLight.shadowIntensity, directionalLight.shadowBias, directionalLight.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\n\t}\n\t#pragma unroll_loop_end\n\t#endif\n\t#if NUM_SPOT_LIGHT_SHADOWS > 0\n\tSpotLightShadow spotLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {\n\t\tspotLight = spotLightShadows[ i ];\n\t\tshadow *= receiveShadow ? getShadow( spotShadowMap[ i ], spotLight.shadowMapSize, spotLight.shadowIntensity, spotLight.shadowBias, spotLight.shadowRadius, vSpotLightCoord[ i ] ) : 1.0;\n\t}\n\t#pragma unroll_loop_end\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\tPointLightShadow pointLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\n\t\tpointLight = pointLightShadows[ i ];\n\t\tshadow *= receiveShadow ? getPointShadow( pointShadowMap[ i ], pointLight.shadowMapSize, pointLight.shadowIntensity, pointLight.shadowBias, pointLight.shadowRadius, vPointShadowCoord[ i ], pointLight.shadowCameraNear, pointLight.shadowCameraFar ) : 1.0;\n\t}\n\t#pragma unroll_loop_end\n\t#endif\n\t#endif\n\treturn shadow;\n}",skinbase_vertex:"#ifdef USE_SKINNING\n\tmat4 boneMatX = getBoneMatrix( skinIndex.x );\n\tmat4 boneMatY = getBoneMatrix( skinIndex.y );\n\tmat4 boneMatZ = getBoneMatrix( skinIndex.z );\n\tmat4 boneMatW = getBoneMatrix( skinIndex.w );\n#endif",skinning_pars_vertex:"#ifdef USE_SKINNING\n\tuniform mat4 bindMatrix;\n\tuniform mat4 bindMatrixInverse;\n\tuniform highp sampler2D boneTexture;\n\tmat4 getBoneMatrix( const in float i ) {\n\t\tint size = textureSize( boneTexture, 0 ).x;\n\t\tint j = int( i ) * 4;\n\t\tint x = j % size;\n\t\tint y = j / size;\n\t\tvec4 v1 = texelFetch( boneTexture, ivec2( x, y ), 0 );\n\t\tvec4 v2 = texelFetch( boneTexture, ivec2( x + 1, y ), 0 );\n\t\tvec4 v3 = texelFetch( boneTexture, ivec2( x + 2, y ), 0 );\n\t\tvec4 v4 = texelFetch( boneTexture, ivec2( x + 3, y ), 0 );\n\t\treturn mat4( v1, v2, v3, v4 );\n\t}\n#endif",skinning_vertex:"#ifdef USE_SKINNING\n\tvec4 skinVertex = bindMatrix * vec4( transformed, 1.0 );\n\tvec4 skinned = vec4( 0.0 );\n\tskinned += boneMatX * skinVertex * skinWeight.x;\n\tskinned += boneMatY * skinVertex * skinWeight.y;\n\tskinned += boneMatZ * skinVertex * skinWeight.z;\n\tskinned += boneMatW * skinVertex * skinWeight.w;\n\ttransformed = ( bindMatrixInverse * skinned ).xyz;\n#endif",skinnormal_vertex:"#ifdef USE_SKINNING\n\tmat4 skinMatrix = mat4( 0.0 );\n\tskinMatrix += skinWeight.x * boneMatX;\n\tskinMatrix += skinWeight.y * boneMatY;\n\tskinMatrix += skinWeight.z * boneMatZ;\n\tskinMatrix += skinWeight.w * boneMatW;\n\tskinMatrix = bindMatrixInverse * skinMatrix * bindMatrix;\n\tobjectNormal = vec4( skinMatrix * vec4( objectNormal, 0.0 ) ).xyz;\n\t#ifdef USE_TANGENT\n\t\tobjectTangent = vec4( skinMatrix * vec4( objectTangent, 0.0 ) ).xyz;\n\t#endif\n#endif",specularmap_fragment:"float specularStrength;\n#ifdef USE_SPECULARMAP\n\tvec4 texelSpecular = texture2D( specularMap, vSpecularMapUv );\n\tspecularStrength = texelSpecular.r;\n#else\n\tspecularStrength = 1.0;\n#endif",specularmap_pars_fragment:"#ifdef USE_SPECULARMAP\n\tuniform sampler2D specularMap;\n#endif",tonemapping_fragment:"#if defined( TONE_MAPPING )\n\tgl_FragColor.rgb = toneMapping( gl_FragColor.rgb );\n#endif",tonemapping_pars_fragment:"#ifndef saturate\n#define saturate( a ) clamp( a, 0.0, 1.0 )\n#endif\nuniform float toneMappingExposure;\nvec3 LinearToneMapping( vec3 color ) {\n\treturn saturate( toneMappingExposure * color );\n}\nvec3 ReinhardToneMapping( vec3 color ) {\n\tcolor *= toneMappingExposure;\n\treturn saturate( color / ( vec3( 1.0 ) + color ) );\n}\nvec3 CineonToneMapping( vec3 color ) {\n\tcolor *= toneMappingExposure;\n\tcolor = max( vec3( 0.0 ), color - 0.004 );\n\treturn pow( ( color * ( 6.2 * color + 0.5 ) ) / ( color * ( 6.2 * color + 1.7 ) + 0.06 ), vec3( 2.2 ) );\n}\nvec3 RRTAndODTFit( vec3 v ) {\n\tvec3 a = v * ( v + 0.0245786 ) - 0.000090537;\n\tvec3 b = v * ( 0.983729 * v + 0.4329510 ) + 0.238081;\n\treturn a / b;\n}\nvec3 ACESFilmicToneMapping( vec3 color ) {\n\tconst mat3 ACESInputMat = mat3(\n\t\tvec3( 0.59719, 0.07600, 0.02840 ),\t\tvec3( 0.35458, 0.90834, 0.13383 ),\n\t\tvec3( 0.04823, 0.01566, 0.83777 )\n\t);\n\tconst mat3 ACESOutputMat = mat3(\n\t\tvec3(  1.60475, -0.10208, -0.00327 ),\t\tvec3( -0.53108,  1.10813, -0.07276 ),\n\t\tvec3( -0.07367, -0.00605,  1.07602 )\n\t);\n\tcolor *= toneMappingExposure / 0.6;\n\tcolor = ACESInputMat * color;\n\tcolor = RRTAndODTFit( color );\n\tcolor = ACESOutputMat * color;\n\treturn saturate( color );\n}\nconst mat3 LINEAR_REC2020_TO_LINEAR_SRGB = mat3(\n\tvec3( 1.6605, - 0.1246, - 0.0182 ),\n\tvec3( - 0.5876, 1.1329, - 0.1006 ),\n\tvec3( - 0.0728, - 0.0083, 1.1187 )\n);\nconst mat3 LINEAR_SRGB_TO_LINEAR_REC2020 = mat3(\n\tvec3( 0.6274, 0.0691, 0.0164 ),\n\tvec3( 0.3293, 0.9195, 0.0880 ),\n\tvec3( 0.0433, 0.0113, 0.8956 )\n);\nvec3 agxDefaultContrastApprox( vec3 x ) {\n\tvec3 x2 = x * x;\n\tvec3 x4 = x2 * x2;\n\treturn + 15.5 * x4 * x2\n\t\t- 40.14 * x4 * x\n\t\t+ 31.96 * x4\n\t\t- 6.868 * x2 * x\n\t\t+ 0.4298 * x2\n\t\t+ 0.1191 * x\n\t\t- 0.00232;\n}\nvec3 AgXToneMapping( vec3 color ) {\n\tconst mat3 AgXInsetMatrix = mat3(\n\t\tvec3( 0.856627153315983, 0.137318972929847, 0.11189821299995 ),\n\t\tvec3( 0.0951212405381588, 0.761241990602591, 0.0767994186031903 ),\n\t\tvec3( 0.0482516061458583, 0.101439036467562, 0.811302368396859 )\n\t);\n\tconst mat3 AgXOutsetMatrix = mat3(\n\t\tvec3( 1.1271005818144368, - 0.1413297634984383, - 0.14132976349843826 ),\n\t\tvec3( - 0.11060664309660323, 1.157823702216272, - 0.11060664309660294 ),\n\t\tvec3( - 0.016493938717834573, - 0.016493938717834257, 1.2519364065950405 )\n\t);\n\tconst float AgxMinEv = - 12.47393;\tconst float AgxMaxEv = 4.026069;\n\tcolor *= toneMappingExposure;\n\tcolor = LINEAR_SRGB_TO_LINEAR_REC2020 * color;\n\tcolor = AgXInsetMatrix * color;\n\tcolor = max( color, 1e-10 );\tcolor = log2( color );\n\tcolor = ( color - AgxMinEv ) / ( AgxMaxEv - AgxMinEv );\n\tcolor = clamp( color, 0.0, 1.0 );\n\tcolor = agxDefaultContrastApprox( color );\n\tcolor = AgXOutsetMatrix * color;\n\tcolor = pow( max( vec3( 0.0 ), color ), vec3( 2.2 ) );\n\tcolor = LINEAR_REC2020_TO_LINEAR_SRGB * color;\n\tcolor = clamp( color, 0.0, 1.0 );\n\treturn color;\n}\nvec3 NeutralToneMapping( vec3 color ) {\n\tconst float StartCompression = 0.8 - 0.04;\n\tconst float Desaturation = 0.15;\n\tcolor *= toneMappingExposure;\n\tfloat x = min( color.r, min( color.g, color.b ) );\n\tfloat offset = x < 0.08 ? x - 6.25 * x * x : 0.04;\n\tcolor -= offset;\n\tfloat peak = max( color.r, max( color.g, color.b ) );\n\tif ( peak < StartCompression ) return color;\n\tfloat d = 1. - StartCompression;\n\tfloat newPeak = 1. - d * d / ( peak + d - StartCompression );\n\tcolor *= newPeak / peak;\n\tfloat g = 1. - 1. / ( Desaturation * ( peak - newPeak ) + 1. );\n\treturn mix( color, vec3( newPeak ), g );\n}\nvec3 CustomToneMapping( vec3 color ) { return color; }",transmission_fragment:"#ifdef USE_TRANSMISSION\n\tmaterial.transmission = transmission;\n\tmaterial.transmissionAlpha = 1.0;\n\tmaterial.thickness = thickness;\n\tmaterial.attenuationDistance = attenuationDistance;\n\tmaterial.attenuationColor = attenuationColor;\n\t#ifdef USE_TRANSMISSIONMAP\n\t\tmaterial.transmission *= texture2D( transmissionMap, vTransmissionMapUv ).r;\n\t#endif\n\t#ifdef USE_THICKNESSMAP\n\t\tmaterial.thickness *= texture2D( thicknessMap, vThicknessMapUv ).g;\n\t#endif\n\tvec3 pos = vWorldPosition;\n\tvec3 v = normalize( cameraPosition - pos );\n\tvec3 n = inverseTransformDirection( normal, viewMatrix );\n\tvec4 transmitted = getIBLVolumeRefraction(\n\t\tn, v, material.roughness, material.diffuseColor, material.specularColor, material.specularF90,\n\t\tpos, modelMatrix, viewMatrix, projectionMatrix, material.dispersion, material.ior, material.thickness,\n\t\tmaterial.attenuationColor, material.attenuationDistance );\n\tmaterial.transmissionAlpha = mix( material.transmissionAlpha, transmitted.a, material.transmission );\n\ttotalDiffuse = mix( totalDiffuse, transmitted.rgb, material.transmission );\n#endif",transmission_pars_fragment:"#ifdef USE_TRANSMISSION\n\tuniform float transmission;\n\tuniform float thickness;\n\tuniform float attenuationDistance;\n\tuniform vec3 attenuationColor;\n\t#ifdef USE_TRANSMISSIONMAP\n\t\tuniform sampler2D transmissionMap;\n\t#endif\n\t#ifdef USE_THICKNESSMAP\n\t\tuniform sampler2D thicknessMap;\n\t#endif\n\tuniform vec2 transmissionSamplerSize;\n\tuniform sampler2D transmissionSamplerMap;\n\tuniform mat4 modelMatrix;\n\tuniform mat4 projectionMatrix;\n\tvarying vec3 vWorldPosition;\n\tfloat w0( float a ) {\n\t\treturn ( 1.0 / 6.0 ) * ( a * ( a * ( - a + 3.0 ) - 3.0 ) + 1.0 );\n\t}\n\tfloat w1( float a ) {\n\t\treturn ( 1.0 / 6.0 ) * ( a *  a * ( 3.0 * a - 6.0 ) + 4.0 );\n\t}\n\tfloat w2( float a ){\n\t\treturn ( 1.0 / 6.0 ) * ( a * ( a * ( - 3.0 * a + 3.0 ) + 3.0 ) + 1.0 );\n\t}\n\tfloat w3( float a ) {\n\t\treturn ( 1.0 / 6.0 ) * ( a * a * a );\n\t}\n\tfloat g0( float a ) {\n\t\treturn w0( a ) + w1( a );\n\t}\n\tfloat g1( float a ) {\n\t\treturn w2( a ) + w3( a );\n\t}\n\tfloat h0( float a ) {\n\t\treturn - 1.0 + w1( a ) / ( w0( a ) + w1( a ) );\n\t}\n\tfloat h1( float a ) {\n\t\treturn 1.0 + w3( a ) / ( w2( a ) + w3( a ) );\n\t}\n\tvec4 bicubic( sampler2D tex, vec2 uv, vec4 texelSize, float lod ) {\n\t\tuv = uv * texelSize.zw + 0.5;\n\t\tvec2 iuv = floor( uv );\n\t\tvec2 fuv = fract( uv );\n\t\tfloat g0x = g0( fuv.x );\n\t\tfloat g1x = g1( fuv.x );\n\t\tfloat h0x = h0( fuv.x );\n\t\tfloat h1x = h1( fuv.x );\n\t\tfloat h0y = h0( fuv.y );\n\t\tfloat h1y = h1( fuv.y );\n\t\tvec2 p0 = ( vec2( iuv.x + h0x, iuv.y + h0y ) - 0.5 ) * texelSize.xy;\n\t\tvec2 p1 = ( vec2( iuv.x + h1x, iuv.y + h0y ) - 0.5 ) * texelSize.xy;\n\t\tvec2 p2 = ( vec2( iuv.x + h0x, iuv.y + h1y ) - 0.5 ) * texelSize.xy;\n\t\tvec2 p3 = ( vec2( iuv.x + h1x, iuv.y + h1y ) - 0.5 ) * texelSize.xy;\n\t\treturn g0( fuv.y ) * ( g0x * textureLod( tex, p0, lod ) + g1x * textureLod( tex, p1, lod ) ) +\n\t\t\tg1( fuv.y ) * ( g0x * textureLod( tex, p2, lod ) + g1x * textureLod( tex, p3, lod ) );\n\t}\n\tvec4 textureBicubic( sampler2D sampler, vec2 uv, float lod ) {\n\t\tvec2 fLodSize = vec2( textureSize( sampler, int( lod ) ) );\n\t\tvec2 cLodSize = vec2( textureSize( sampler, int( lod + 1.0 ) ) );\n\t\tvec2 fLodSizeInv = 1.0 / fLodSize;\n\t\tvec2 cLodSizeInv = 1.0 / cLodSize;\n\t\tvec4 fSample = bicubic( sampler, uv, vec4( fLodSizeInv, fLodSize ), floor( lod ) );\n\t\tvec4 cSample = bicubic( sampler, uv, vec4( cLodSizeInv, cLodSize ), ceil( lod ) );\n\t\treturn mix( fSample, cSample, fract( lod ) );\n\t}\n\tvec3 getVolumeTransmissionRay( const in vec3 n, const in vec3 v, const in float thickness, const in float ior, const in mat4 modelMatrix ) {\n\t\tvec3 refractionVector = refract( - v, normalize( n ), 1.0 / ior );\n\t\tvec3 modelScale;\n\t\tmodelScale.x = length( vec3( modelMatrix[ 0 ].xyz ) );\n\t\tmodelScale.y = length( vec3( modelMatrix[ 1 ].xyz ) );\n\t\tmodelScale.z = length( vec3( modelMatrix[ 2 ].xyz ) );\n\t\treturn normalize( refractionVector ) * thickness * modelScale;\n\t}\n\tfloat applyIorToRoughness( const in float roughness, const in float ior ) {\n\t\treturn roughness * clamp( ior * 2.0 - 2.0, 0.0, 1.0 );\n\t}\n\tvec4 getTransmissionSample( const in vec2 fragCoord, const in float roughness, const in float ior ) {\n\t\tfloat lod = log2( transmissionSamplerSize.x ) * applyIorToRoughness( roughness, ior );\n\t\treturn textureBicubic( transmissionSamplerMap, fragCoord.xy, lod );\n\t}\n\tvec3 volumeAttenuation( const in float transmissionDistance, const in vec3 attenuationColor, const in float attenuationDistance ) {\n\t\tif ( isinf( attenuationDistance ) ) {\n\t\t\treturn vec3( 1.0 );\n\t\t} else {\n\t\t\tvec3 attenuationCoefficient = -log( attenuationColor ) / attenuationDistance;\n\t\t\tvec3 transmittance = exp( - attenuationCoefficient * transmissionDistance );\t\t\treturn transmittance;\n\t\t}\n\t}\n\tvec4 getIBLVolumeRefraction( const in vec3 n, const in vec3 v, const in float roughness, const in vec3 diffuseColor,\n\t\tconst in vec3 specularColor, const in float specularF90, const in vec3 position, const in mat4 modelMatrix,\n\t\tconst in mat4 viewMatrix, const in mat4 projMatrix, const in float dispersion, const in float ior, const in float thickness,\n\t\tconst in vec3 attenuationColor, const in float attenuationDistance ) {\n\t\tvec4 transmittedLight;\n\t\tvec3 transmittance;\n\t\t#ifdef USE_DISPERSION\n\t\t\tfloat halfSpread = ( ior - 1.0 ) * 0.025 * dispersion;\n\t\t\tvec3 iors = vec3( ior - halfSpread, ior, ior + halfSpread );\n\t\t\tfor ( int i = 0; i < 3; i ++ ) {\n\t\t\t\tvec3 transmissionRay = getVolumeTransmissionRay( n, v, thickness, iors[ i ], modelMatrix );\n\t\t\t\tvec3 refractedRayExit = position + transmissionRay;\n\t\t\t\tvec4 ndcPos = projMatrix * viewMatrix * vec4( refractedRayExit, 1.0 );\n\t\t\t\tvec2 refractionCoords = ndcPos.xy / ndcPos.w;\n\t\t\t\trefractionCoords += 1.0;\n\t\t\t\trefractionCoords /= 2.0;\n\t\t\t\tvec4 transmissionSample = getTransmissionSample( refractionCoords, roughness, iors[ i ] );\n\t\t\t\ttransmittedLight[ i ] = transmissionSample[ i ];\n\t\t\t\ttransmittedLight.a += transmissionSample.a;\n\t\t\t\ttransmittance[ i ] = diffuseColor[ i ] * volumeAttenuation( length( transmissionRay ), attenuationColor, attenuationDistance )[ i ];\n\t\t\t}\n\t\t\ttransmittedLight.a /= 3.0;\n\t\t#else\n\t\t\tvec3 transmissionRay = getVolumeTransmissionRay( n, v, thickness, ior, modelMatrix );\n\t\t\tvec3 refractedRayExit = position + transmissionRay;\n\t\t\tvec4 ndcPos = projMatrix * viewMatrix * vec4( refractedRayExit, 1.0 );\n\t\t\tvec2 refractionCoords = ndcPos.xy / ndcPos.w;\n\t\t\trefractionCoords += 1.0;\n\t\t\trefractionCoords /= 2.0;\n\t\t\ttransmittedLight = getTransmissionSample( refractionCoords, roughness, ior );\n\t\t\ttransmittance = diffuseColor * volumeAttenuation( length( transmissionRay ), attenuationColor, attenuationDistance );\n\t\t#endif\n\t\tvec3 attenuatedColor = transmittance * transmittedLight.rgb;\n\t\tvec3 F = EnvironmentBRDF( n, v, specularColor, specularF90, roughness );\n\t\tfloat transmittanceFactor = ( transmittance.r + transmittance.g + transmittance.b ) / 3.0;\n\t\treturn vec4( ( 1.0 - F ) * attenuatedColor, 1.0 - ( 1.0 - transmittedLight.a ) * transmittanceFactor );\n\t}\n#endif",uv_pars_fragment:"#if defined( USE_UV ) || defined( USE_ANISOTROPY )\n\tvarying vec2 vUv;\n#endif\n#ifdef USE_MAP\n\tvarying vec2 vMapUv;\n#endif\n#ifdef USE_ALPHAMAP\n\tvarying vec2 vAlphaMapUv;\n#endif\n#ifdef USE_LIGHTMAP\n\tvarying vec2 vLightMapUv;\n#endif\n#ifdef USE_AOMAP\n\tvarying vec2 vAoMapUv;\n#endif\n#ifdef USE_BUMPMAP\n\tvarying vec2 vBumpMapUv;\n#endif\n#ifdef USE_NORMALMAP\n\tvarying vec2 vNormalMapUv;\n#endif\n#ifdef USE_EMISSIVEMAP\n\tvarying vec2 vEmissiveMapUv;\n#endif\n#ifdef USE_METALNESSMAP\n\tvarying vec2 vMetalnessMapUv;\n#endif\n#ifdef USE_ROUGHNESSMAP\n\tvarying vec2 vRoughnessMapUv;\n#endif\n#ifdef USE_ANISOTROPYMAP\n\tvarying vec2 vAnisotropyMapUv;\n#endif\n#ifdef USE_CLEARCOATMAP\n\tvarying vec2 vClearcoatMapUv;\n#endif\n#ifdef USE_CLEARCOAT_NORMALMAP\n\tvarying vec2 vClearcoatNormalMapUv;\n#endif\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\n\tvarying vec2 vClearcoatRoughnessMapUv;\n#endif\n#ifdef USE_IRIDESCENCEMAP\n\tvarying vec2 vIridescenceMapUv;\n#endif\n#ifdef USE_IRIDESCENCE_THICKNESSMAP\n\tvarying vec2 vIridescenceThicknessMapUv;\n#endif\n#ifdef USE_SHEEN_COLORMAP\n\tvarying vec2 vSheenColorMapUv;\n#endif\n#ifdef USE_SHEEN_ROUGHNESSMAP\n\tvarying vec2 vSheenRoughnessMapUv;\n#endif\n#ifdef USE_SPECULARMAP\n\tvarying vec2 vSpecularMapUv;\n#endif\n#ifdef USE_SPECULAR_COLORMAP\n\tvarying vec2 vSpecularColorMapUv;\n#endif\n#ifdef USE_SPECULAR_INTENSITYMAP\n\tvarying vec2 vSpecularIntensityMapUv;\n#endif\n#ifdef USE_TRANSMISSIONMAP\n\tuniform mat3 transmissionMapTransform;\n\tvarying vec2 vTransmissionMapUv;\n#endif\n#ifdef USE_THICKNESSMAP\n\tuniform mat3 thicknessMapTransform;\n\tvarying vec2 vThicknessMapUv;\n#endif",uv_pars_vertex:"#if defined( USE_UV ) || defined( USE_ANISOTROPY )\n\tvarying vec2 vUv;\n#endif\n#ifdef USE_MAP\n\tuniform mat3 mapTransform;\n\tvarying vec2 vMapUv;\n#endif\n#ifdef USE_ALPHAMAP\n\tuniform mat3 alphaMapTransform;\n\tvarying vec2 vAlphaMapUv;\n#endif\n#ifdef USE_LIGHTMAP\n\tuniform mat3 lightMapTransform;\n\tvarying vec2 vLightMapUv;\n#endif\n#ifdef USE_AOMAP\n\tuniform mat3 aoMapTransform;\n\tvarying vec2 vAoMapUv;\n#endif\n#ifdef USE_BUMPMAP\n\tuniform mat3 bumpMapTransform;\n\tvarying vec2 vBumpMapUv;\n#endif\n#ifdef USE_NORMALMAP\n\tuniform mat3 normalMapTransform;\n\tvarying vec2 vNormalMapUv;\n#endif\n#ifdef USE_DISPLACEMENTMAP\n\tuniform mat3 displacementMapTransform;\n\tvarying vec2 vDisplacementMapUv;\n#endif\n#ifdef USE_EMISSIVEMAP\n\tuniform mat3 emissiveMapTransform;\n\tvarying vec2 vEmissiveMapUv;\n#endif\n#ifdef USE_METALNESSMAP\n\tuniform mat3 metalnessMapTransform;\n\tvarying vec2 vMetalnessMapUv;\n#endif\n#ifdef USE_ROUGHNESSMAP\n\tuniform mat3 roughnessMapTransform;\n\tvarying vec2 vRoughnessMapUv;\n#endif\n#ifdef USE_ANISOTROPYMAP\n\tuniform mat3 anisotropyMapTransform;\n\tvarying vec2 vAnisotropyMapUv;\n#endif\n#ifdef USE_CLEARCOATMAP\n\tuniform mat3 clearcoatMapTransform;\n\tvarying vec2 vClearcoatMapUv;\n#endif\n#ifdef USE_CLEARCOAT_NORMALMAP\n\tuniform mat3 clearcoatNormalMapTransform;\n\tvarying vec2 vClearcoatNormalMapUv;\n#endif\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\n\tuniform mat3 clearcoatRoughnessMapTransform;\n\tvarying vec2 vClearcoatRoughnessMapUv;\n#endif\n#ifdef USE_SHEEN_COLORMAP\n\tuniform mat3 sheenColorMapTransform;\n\tvarying vec2 vSheenColorMapUv;\n#endif\n#ifdef USE_SHEEN_ROUGHNESSMAP\n\tuniform mat3 sheenRoughnessMapTransform;\n\tvarying vec2 vSheenRoughnessMapUv;\n#endif\n#ifdef USE_IRIDESCENCEMAP\n\tuniform mat3 iridescenceMapTransform;\n\tvarying vec2 vIridescenceMapUv;\n#endif\n#ifdef USE_IRIDESCENCE_THICKNESSMAP\n\tuniform mat3 iridescenceThicknessMapTransform;\n\tvarying vec2 vIridescenceThicknessMapUv;\n#endif\n#ifdef USE_SPECULARMAP\n\tuniform mat3 specularMapTransform;\n\tvarying vec2 vSpecularMapUv;\n#endif\n#ifdef USE_SPECULAR_COLORMAP\n\tuniform mat3 specularColorMapTransform;\n\tvarying vec2 vSpecularColorMapUv;\n#endif\n#ifdef USE_SPECULAR_INTENSITYMAP\n\tuniform mat3 specularIntensityMapTransform;\n\tvarying vec2 vSpecularIntensityMapUv;\n#endif\n#ifdef USE_TRANSMISSIONMAP\n\tuniform mat3 transmissionMapTransform;\n\tvarying vec2 vTransmissionMapUv;\n#endif\n#ifdef USE_THICKNESSMAP\n\tuniform mat3 thicknessMapTransform;\n\tvarying vec2 vThicknessMapUv;\n#endif",uv_vertex:"#if defined( USE_UV ) || defined( USE_ANISOTROPY )\n\tvUv = vec3( uv, 1 ).xy;\n#endif\n#ifdef USE_MAP\n\tvMapUv = ( mapTransform * vec3( MAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_ALPHAMAP\n\tvAlphaMapUv = ( alphaMapTransform * vec3( ALPHAMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_LIGHTMAP\n\tvLightMapUv = ( lightMapTransform * vec3( LIGHTMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_AOMAP\n\tvAoMapUv = ( aoMapTransform * vec3( AOMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_BUMPMAP\n\tvBumpMapUv = ( bumpMapTransform * vec3( BUMPMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_NORMALMAP\n\tvNormalMapUv = ( normalMapTransform * vec3( NORMALMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_DISPLACEMENTMAP\n\tvDisplacementMapUv = ( displacementMapTransform * vec3( DISPLACEMENTMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_EMISSIVEMAP\n\tvEmissiveMapUv = ( emissiveMapTransform * vec3( EMISSIVEMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_METALNESSMAP\n\tvMetalnessMapUv = ( metalnessMapTransform * vec3( METALNESSMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_ROUGHNESSMAP\n\tvRoughnessMapUv = ( roughnessMapTransform * vec3( ROUGHNESSMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_ANISOTROPYMAP\n\tvAnisotropyMapUv = ( anisotropyMapTransform * vec3( ANISOTROPYMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_CLEARCOATMAP\n\tvClearcoatMapUv = ( clearcoatMapTransform * vec3( CLEARCOATMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_CLEARCOAT_NORMALMAP\n\tvClearcoatNormalMapUv = ( clearcoatNormalMapTransform * vec3( CLEARCOAT_NORMALMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\n\tvClearcoatRoughnessMapUv = ( clearcoatRoughnessMapTransform * vec3( CLEARCOAT_ROUGHNESSMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_IRIDESCENCEMAP\n\tvIridescenceMapUv = ( iridescenceMapTransform * vec3( IRIDESCENCEMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_IRIDESCENCE_THICKNESSMAP\n\tvIridescenceThicknessMapUv = ( iridescenceThicknessMapTransform * vec3( IRIDESCENCE_THICKNESSMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_SHEEN_COLORMAP\n\tvSheenColorMapUv = ( sheenColorMapTransform * vec3( SHEEN_COLORMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_SHEEN_ROUGHNESSMAP\n\tvSheenRoughnessMapUv = ( sheenRoughnessMapTransform * vec3( SHEEN_ROUGHNESSMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_SPECULARMAP\n\tvSpecularMapUv = ( specularMapTransform * vec3( SPECULARMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_SPECULAR_COLORMAP\n\tvSpecularColorMapUv = ( specularColorMapTransform * vec3( SPECULAR_COLORMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_SPECULAR_INTENSITYMAP\n\tvSpecularIntensityMapUv = ( specularIntensityMapTransform * vec3( SPECULAR_INTENSITYMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_TRANSMISSIONMAP\n\tvTransmissionMapUv = ( transmissionMapTransform * vec3( TRANSMISSIONMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_THICKNESSMAP\n\tvThicknessMapUv = ( thicknessMapTransform * vec3( THICKNESSMAP_UV, 1 ) ).xy;\n#endif",worldpos_vertex:"#if defined( USE_ENVMAP ) || defined( DISTANCE ) || defined ( USE_SHADOWMAP ) || defined ( USE_TRANSMISSION ) || NUM_SPOT_LIGHT_COORDS > 0\n\tvec4 worldPosition = vec4( transformed, 1.0 );\n\t#ifdef USE_BATCHING\n\t\tworldPosition = batchingMatrix * worldPosition;\n\t#endif\n\t#ifdef USE_INSTANCING\n\t\tworldPosition = instanceMatrix * worldPosition;\n\t#endif\n\tworldPosition = modelMatrix * worldPosition;\n#endif",background_vert:"varying vec2 vUv;\nuniform mat3 uvTransform;\nvoid main() {\n\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\n\tgl_Position = vec4( position.xy, 1.0, 1.0 );\n}",background_frag:"uniform sampler2D t2D;\nuniform float backgroundIntensity;\nvarying vec2 vUv;\nvoid main() {\n\tvec4 texColor = texture2D( t2D, vUv );\n\t#ifdef DECODE_VIDEO_TEXTURE\n\t\ttexColor = vec4( mix( pow( texColor.rgb * 0.9478672986 + vec3( 0.0521327014 ), vec3( 2.4 ) ), texColor.rgb * 0.0773993808, vec3( lessThanEqual( texColor.rgb, vec3( 0.04045 ) ) ) ), texColor.w );\n\t#endif\n\ttexColor.rgb *= backgroundIntensity;\n\tgl_FragColor = texColor;\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n}",backgroundCube_vert:"varying vec3 vWorldDirection;\n#include <common>\nvoid main() {\n\tvWorldDirection = transformDirection( position, modelMatrix );\n\t#include <begin_vertex>\n\t#include <project_vertex>\n\tgl_Position.z = gl_Position.w;\n}",backgroundCube_frag:"#ifdef ENVMAP_TYPE_CUBE\n\tuniform samplerCube envMap;\n#elif defined( ENVMAP_TYPE_CUBE_UV )\n\tuniform sampler2D envMap;\n#endif\nuniform float flipEnvMap;\nuniform float backgroundBlurriness;\nuniform float backgroundIntensity;\nuniform mat3 backgroundRotation;\nvarying vec3 vWorldDirection;\n#include <cube_uv_reflection_fragment>\nvoid main() {\n\t#ifdef ENVMAP_TYPE_CUBE\n\t\tvec4 texColor = textureCube( envMap, backgroundRotation * vec3( flipEnvMap * vWorldDirection.x, vWorldDirection.yz ) );\n\t#elif defined( ENVMAP_TYPE_CUBE_UV )\n\t\tvec4 texColor = textureCubeUV( envMap, backgroundRotation * vWorldDirection, backgroundBlurriness );\n\t#else\n\t\tvec4 texColor = vec4( 0.0, 0.0, 0.0, 1.0 );\n\t#endif\n\ttexColor.rgb *= backgroundIntensity;\n\tgl_FragColor = texColor;\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n}",cube_vert:"varying vec3 vWorldDirection;\n#include <common>\nvoid main() {\n\tvWorldDirection = transformDirection( position, modelMatrix );\n\t#include <begin_vertex>\n\t#include <project_vertex>\n\tgl_Position.z = gl_Position.w;\n}",cube_frag:"uniform samplerCube tCube;\nuniform float tFlip;\nuniform float opacity;\nvarying vec3 vWorldDirection;\nvoid main() {\n\tvec4 texColor = textureCube( tCube, vec3( tFlip * vWorldDirection.x, vWorldDirection.yz ) );\n\tgl_FragColor = texColor;\n\tgl_FragColor.a *= opacity;\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n}",depth_vert:"#include <common>\n#include <batching_pars_vertex>\n#include <uv_pars_vertex>\n#include <displacementmap_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvarying vec2 vHighPrecisionZW;\nvoid main() {\n\t#include <uv_vertex>\n\t#include <batching_vertex>\n\t#include <skinbase_vertex>\n\t#include <morphinstance_vertex>\n\t#ifdef USE_DISPLACEMENTMAP\n\t\t#include <beginnormal_vertex>\n\t\t#include <morphnormal_vertex>\n\t\t#include <skinnormal_vertex>\n\t#endif\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <displacementmap_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\tvHighPrecisionZW = gl_Position.zw;\n}",depth_frag:"#if DEPTH_PACKING == 3200\n\tuniform float opacity;\n#endif\n#include <common>\n#include <packing>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <alphamap_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvarying vec2 vHighPrecisionZW;\nvoid main() {\n\tvec4 diffuseColor = vec4( 1.0 );\n\t#include <clipping_planes_fragment>\n\t#if DEPTH_PACKING == 3200\n\t\tdiffuseColor.a = opacity;\n\t#endif\n\t#include <map_fragment>\n\t#include <alphamap_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\t#include <logdepthbuf_fragment>\n\t#ifdef USE_REVERSED_DEPTH_BUFFER\n\t\tfloat fragCoordZ = vHighPrecisionZW[ 0 ] / vHighPrecisionZW[ 1 ];\n\t#else\n\t\tfloat fragCoordZ = 0.5 * vHighPrecisionZW[ 0 ] / vHighPrecisionZW[ 1 ] + 0.5;\n\t#endif\n\t#if DEPTH_PACKING == 3200\n\t\tgl_FragColor = vec4( vec3( 1.0 - fragCoordZ ), opacity );\n\t#elif DEPTH_PACKING == 3201\n\t\tgl_FragColor = packDepthToRGBA( fragCoordZ );\n\t#elif DEPTH_PACKING == 3202\n\t\tgl_FragColor = vec4( packDepthToRGB( fragCoordZ ), 1.0 );\n\t#elif DEPTH_PACKING == 3203\n\t\tgl_FragColor = vec4( packDepthToRG( fragCoordZ ), 0.0, 1.0 );\n\t#endif\n}",distanceRGBA_vert:"#define DISTANCE\nvarying vec3 vWorldPosition;\n#include <common>\n#include <batching_pars_vertex>\n#include <uv_pars_vertex>\n#include <displacementmap_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\t#include <uv_vertex>\n\t#include <batching_vertex>\n\t#include <skinbase_vertex>\n\t#include <morphinstance_vertex>\n\t#ifdef USE_DISPLACEMENTMAP\n\t\t#include <beginnormal_vertex>\n\t\t#include <morphnormal_vertex>\n\t\t#include <skinnormal_vertex>\n\t#endif\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <displacementmap_vertex>\n\t#include <project_vertex>\n\t#include <worldpos_vertex>\n\t#include <clipping_planes_vertex>\n\tvWorldPosition = worldPosition.xyz;\n}",distanceRGBA_frag:"#define DISTANCE\nuniform vec3 referencePosition;\nuniform float nearDistance;\nuniform float farDistance;\nvarying vec3 vWorldPosition;\n#include <common>\n#include <packing>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <alphamap_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main () {\n\tvec4 diffuseColor = vec4( 1.0 );\n\t#include <clipping_planes_fragment>\n\t#include <map_fragment>\n\t#include <alphamap_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\tfloat dist = length( vWorldPosition - referencePosition );\n\tdist = ( dist - nearDistance ) / ( farDistance - nearDistance );\n\tdist = saturate( dist );\n\tgl_FragColor = packDepthToRGBA( dist );\n}",equirect_vert:"varying vec3 vWorldDirection;\n#include <common>\nvoid main() {\n\tvWorldDirection = transformDirection( position, modelMatrix );\n\t#include <begin_vertex>\n\t#include <project_vertex>\n}",equirect_frag:"uniform sampler2D tEquirect;\nvarying vec3 vWorldDirection;\n#include <common>\nvoid main() {\n\tvec3 direction = normalize( vWorldDirection );\n\tvec2 sampleUV = equirectUv( direction );\n\tgl_FragColor = texture2D( tEquirect, sampleUV );\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n}",linedashed_vert:"uniform float scale;\nattribute float lineDistance;\nvarying float vLineDistance;\n#include <common>\n#include <uv_pars_vertex>\n#include <color_pars_vertex>\n#include <fog_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\tvLineDistance = scale * lineDistance;\n\t#include <uv_vertex>\n\t#include <color_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphcolor_vertex>\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\t#include <fog_vertex>\n}",linedashed_frag:"uniform vec3 diffuse;\nuniform float opacity;\nuniform float dashSize;\nuniform float totalSize;\nvarying float vLineDistance;\n#include <common>\n#include <color_pars_fragment>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <fog_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include <clipping_planes_fragment>\n\tif ( mod( vLineDistance, totalSize ) > dashSize ) {\n\t\tdiscard;\n\t}\n\tvec3 outgoingLight = vec3( 0.0 );\n\t#include <logdepthbuf_fragment>\n\t#include <map_fragment>\n\t#include <color_fragment>\n\toutgoingLight = diffuseColor.rgb;\n\t#include <opaque_fragment>\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n\t#include <premultiplied_alpha_fragment>\n}",meshbasic_vert:"#include <common>\n#include <batching_pars_vertex>\n#include <uv_pars_vertex>\n#include <envmap_pars_vertex>\n#include <color_pars_vertex>\n#include <fog_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\t#include <uv_vertex>\n\t#include <color_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphcolor_vertex>\n\t#include <batching_vertex>\n\t#if defined ( USE_ENVMAP ) || defined ( USE_SKINNING )\n\t\t#include <beginnormal_vertex>\n\t\t#include <morphnormal_vertex>\n\t\t#include <skinbase_vertex>\n\t\t#include <skinnormal_vertex>\n\t\t#include <defaultnormal_vertex>\n\t#endif\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\t#include <worldpos_vertex>\n\t#include <envmap_vertex>\n\t#include <fog_vertex>\n}",meshbasic_frag:"uniform vec3 diffuse;\nuniform float opacity;\n#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n#endif\n#include <common>\n#include <dithering_pars_fragment>\n#include <color_pars_fragment>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <alphamap_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <aomap_pars_fragment>\n#include <lightmap_pars_fragment>\n#include <envmap_common_pars_fragment>\n#include <envmap_pars_fragment>\n#include <fog_pars_fragment>\n#include <specularmap_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include <clipping_planes_fragment>\n\t#include <logdepthbuf_fragment>\n\t#include <map_fragment>\n\t#include <color_fragment>\n\t#include <alphamap_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\t#include <specularmap_fragment>\n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\t#ifdef USE_LIGHTMAP\n\t\tvec4 lightMapTexel = texture2D( lightMap, vLightMapUv );\n\t\treflectedLight.indirectDiffuse += lightMapTexel.rgb * lightMapIntensity * RECIPROCAL_PI;\n\t#else\n\t\treflectedLight.indirectDiffuse += vec3( 1.0 );\n\t#endif\n\t#include <aomap_fragment>\n\treflectedLight.indirectDiffuse *= diffuseColor.rgb;\n\tvec3 outgoingLight = reflectedLight.indirectDiffuse;\n\t#include <envmap_fragment>\n\t#include <opaque_fragment>\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n\t#include <premultiplied_alpha_fragment>\n\t#include <dithering_fragment>\n}",meshlambert_vert:"#define LAMBERT\nvarying vec3 vViewPosition;\n#include <common>\n#include <batching_pars_vertex>\n#include <uv_pars_vertex>\n#include <displacementmap_pars_vertex>\n#include <envmap_pars_vertex>\n#include <color_pars_vertex>\n#include <fog_pars_vertex>\n#include <normal_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <shadowmap_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\t#include <uv_vertex>\n\t#include <color_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphcolor_vertex>\n\t#include <batching_vertex>\n\t#include <beginnormal_vertex>\n\t#include <morphnormal_vertex>\n\t#include <skinbase_vertex>\n\t#include <skinnormal_vertex>\n\t#include <defaultnormal_vertex>\n\t#include <normal_vertex>\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <displacementmap_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\tvViewPosition = - mvPosition.xyz;\n\t#include <worldpos_vertex>\n\t#include <envmap_vertex>\n\t#include <shadowmap_vertex>\n\t#include <fog_vertex>\n}",meshlambert_frag:"#define LAMBERT\nuniform vec3 diffuse;\nuniform vec3 emissive;\nuniform float opacity;\n#include <common>\n#include <packing>\n#include <dithering_pars_fragment>\n#include <color_pars_fragment>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <alphamap_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <aomap_pars_fragment>\n#include <lightmap_pars_fragment>\n#include <emissivemap_pars_fragment>\n#include <envmap_common_pars_fragment>\n#include <envmap_pars_fragment>\n#include <fog_pars_fragment>\n#include <bsdfs>\n#include <lights_pars_begin>\n#include <normal_pars_fragment>\n#include <lights_lambert_pars_fragment>\n#include <shadowmap_pars_fragment>\n#include <bumpmap_pars_fragment>\n#include <normalmap_pars_fragment>\n#include <specularmap_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include <clipping_planes_fragment>\n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\tvec3 totalEmissiveRadiance = emissive;\n\t#include <logdepthbuf_fragment>\n\t#include <map_fragment>\n\t#include <color_fragment>\n\t#include <alphamap_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\t#include <specularmap_fragment>\n\t#include <normal_fragment_begin>\n\t#include <normal_fragment_maps>\n\t#include <emissivemap_fragment>\n\t#include <lights_lambert_fragment>\n\t#include <lights_fragment_begin>\n\t#include <lights_fragment_maps>\n\t#include <lights_fragment_end>\n\t#include <aomap_fragment>\n\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\n\t#include <envmap_fragment>\n\t#include <opaque_fragment>\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n\t#include <premultiplied_alpha_fragment>\n\t#include <dithering_fragment>\n}",meshmatcap_vert:"#define MATCAP\nvarying vec3 vViewPosition;\n#include <common>\n#include <batching_pars_vertex>\n#include <uv_pars_vertex>\n#include <color_pars_vertex>\n#include <displacementmap_pars_vertex>\n#include <fog_pars_vertex>\n#include <normal_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\t#include <uv_vertex>\n\t#include <color_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphcolor_vertex>\n\t#include <batching_vertex>\n\t#include <beginnormal_vertex>\n\t#include <morphnormal_vertex>\n\t#include <skinbase_vertex>\n\t#include <skinnormal_vertex>\n\t#include <defaultnormal_vertex>\n\t#include <normal_vertex>\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <displacementmap_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\t#include <fog_vertex>\n\tvViewPosition = - mvPosition.xyz;\n}",meshmatcap_frag:"#define MATCAP\nuniform vec3 diffuse;\nuniform float opacity;\nuniform sampler2D matcap;\nvarying vec3 vViewPosition;\n#include <common>\n#include <dithering_pars_fragment>\n#include <color_pars_fragment>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <alphamap_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <fog_pars_fragment>\n#include <normal_pars_fragment>\n#include <bumpmap_pars_fragment>\n#include <normalmap_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include <clipping_planes_fragment>\n\t#include <logdepthbuf_fragment>\n\t#include <map_fragment>\n\t#include <color_fragment>\n\t#include <alphamap_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\t#include <normal_fragment_begin>\n\t#include <normal_fragment_maps>\n\tvec3 viewDir = normalize( vViewPosition );\n\tvec3 x = normalize( vec3( viewDir.z, 0.0, - viewDir.x ) );\n\tvec3 y = cross( viewDir, x );\n\tvec2 uv = vec2( dot( x, normal ), dot( y, normal ) ) * 0.495 + 0.5;\n\t#ifdef USE_MATCAP\n\t\tvec4 matcapColor = texture2D( matcap, uv );\n\t#else\n\t\tvec4 matcapColor = vec4( vec3( mix( 0.2, 0.8, uv.y ) ), 1.0 );\n\t#endif\n\tvec3 outgoingLight = diffuseColor.rgb * matcapColor.rgb;\n\t#include <opaque_fragment>\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n\t#include <premultiplied_alpha_fragment>\n\t#include <dithering_fragment>\n}",meshnormal_vert:"#define NORMAL\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( USE_NORMALMAP_TANGENTSPACE )\n\tvarying vec3 vViewPosition;\n#endif\n#include <common>\n#include <batching_pars_vertex>\n#include <uv_pars_vertex>\n#include <displacementmap_pars_vertex>\n#include <normal_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\t#include <uv_vertex>\n\t#include <batching_vertex>\n\t#include <beginnormal_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphnormal_vertex>\n\t#include <skinbase_vertex>\n\t#include <skinnormal_vertex>\n\t#include <defaultnormal_vertex>\n\t#include <normal_vertex>\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <displacementmap_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( USE_NORMALMAP_TANGENTSPACE )\n\tvViewPosition = - mvPosition.xyz;\n#endif\n}",meshnormal_frag:"#define NORMAL\nuniform float opacity;\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( USE_NORMALMAP_TANGENTSPACE )\n\tvarying vec3 vViewPosition;\n#endif\n#include <packing>\n#include <uv_pars_fragment>\n#include <normal_pars_fragment>\n#include <bumpmap_pars_fragment>\n#include <normalmap_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( 0.0, 0.0, 0.0, opacity );\n\t#include <clipping_planes_fragment>\n\t#include <logdepthbuf_fragment>\n\t#include <normal_fragment_begin>\n\t#include <normal_fragment_maps>\n\tgl_FragColor = vec4( packNormalToRGB( normal ), diffuseColor.a );\n\t#ifdef OPAQUE\n\t\tgl_FragColor.a = 1.0;\n\t#endif\n}",meshphong_vert:"#define PHONG\nvarying vec3 vViewPosition;\n#include <common>\n#include <batching_pars_vertex>\n#include <uv_pars_vertex>\n#include <displacementmap_pars_vertex>\n#include <envmap_pars_vertex>\n#include <color_pars_vertex>\n#include <fog_pars_vertex>\n#include <normal_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <shadowmap_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\t#include <uv_vertex>\n\t#include <color_vertex>\n\t#include <morphcolor_vertex>\n\t#include <batching_vertex>\n\t#include <beginnormal_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphnormal_vertex>\n\t#include <skinbase_vertex>\n\t#include <skinnormal_vertex>\n\t#include <defaultnormal_vertex>\n\t#include <normal_vertex>\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <displacementmap_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\tvViewPosition = - mvPosition.xyz;\n\t#include <worldpos_vertex>\n\t#include <envmap_vertex>\n\t#include <shadowmap_vertex>\n\t#include <fog_vertex>\n}",meshphong_frag:"#define PHONG\nuniform vec3 diffuse;\nuniform vec3 emissive;\nuniform vec3 specular;\nuniform float shininess;\nuniform float opacity;\n#include <common>\n#include <packing>\n#include <dithering_pars_fragment>\n#include <color_pars_fragment>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <alphamap_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <aomap_pars_fragment>\n#include <lightmap_pars_fragment>\n#include <emissivemap_pars_fragment>\n#include <envmap_common_pars_fragment>\n#include <envmap_pars_fragment>\n#include <fog_pars_fragment>\n#include <bsdfs>\n#include <lights_pars_begin>\n#include <normal_pars_fragment>\n#include <lights_phong_pars_fragment>\n#include <shadowmap_pars_fragment>\n#include <bumpmap_pars_fragment>\n#include <normalmap_pars_fragment>\n#include <specularmap_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include <clipping_planes_fragment>\n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\tvec3 totalEmissiveRadiance = emissive;\n\t#include <logdepthbuf_fragment>\n\t#include <map_fragment>\n\t#include <color_fragment>\n\t#include <alphamap_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\t#include <specularmap_fragment>\n\t#include <normal_fragment_begin>\n\t#include <normal_fragment_maps>\n\t#include <emissivemap_fragment>\n\t#include <lights_phong_fragment>\n\t#include <lights_fragment_begin>\n\t#include <lights_fragment_maps>\n\t#include <lights_fragment_end>\n\t#include <aomap_fragment>\n\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + reflectedLight.directSpecular + reflectedLight.indirectSpecular + totalEmissiveRadiance;\n\t#include <envmap_fragment>\n\t#include <opaque_fragment>\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n\t#include <premultiplied_alpha_fragment>\n\t#include <dithering_fragment>\n}",meshphysical_vert:"#define STANDARD\nvarying vec3 vViewPosition;\n#ifdef USE_TRANSMISSION\n\tvarying vec3 vWorldPosition;\n#endif\n#include <common>\n#include <batching_pars_vertex>\n#include <uv_pars_vertex>\n#include <displacementmap_pars_vertex>\n#include <color_pars_vertex>\n#include <fog_pars_vertex>\n#include <normal_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <shadowmap_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\t#include <uv_vertex>\n\t#include <color_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphcolor_vertex>\n\t#include <batching_vertex>\n\t#include <beginnormal_vertex>\n\t#include <morphnormal_vertex>\n\t#include <skinbase_vertex>\n\t#include <skinnormal_vertex>\n\t#include <defaultnormal_vertex>\n\t#include <normal_vertex>\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <displacementmap_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\tvViewPosition = - mvPosition.xyz;\n\t#include <worldpos_vertex>\n\t#include <shadowmap_vertex>\n\t#include <fog_vertex>\n#ifdef USE_TRANSMISSION\n\tvWorldPosition = worldPosition.xyz;\n#endif\n}",meshphysical_frag:"#define STANDARD\n#ifdef PHYSICAL\n\t#define IOR\n\t#define USE_SPECULAR\n#endif\nuniform vec3 diffuse;\nuniform vec3 emissive;\nuniform float roughness;\nuniform float metalness;\nuniform float opacity;\n#ifdef IOR\n\tuniform float ior;\n#endif\n#ifdef USE_SPECULAR\n\tuniform float specularIntensity;\n\tuniform vec3 specularColor;\n\t#ifdef USE_SPECULAR_COLORMAP\n\t\tuniform sampler2D specularColorMap;\n\t#endif\n\t#ifdef USE_SPECULAR_INTENSITYMAP\n\t\tuniform sampler2D specularIntensityMap;\n\t#endif\n#endif\n#ifdef USE_CLEARCOAT\n\tuniform float clearcoat;\n\tuniform float clearcoatRoughness;\n#endif\n#ifdef USE_DISPERSION\n\tuniform float dispersion;\n#endif\n#ifdef USE_IRIDESCENCE\n\tuniform float iridescence;\n\tuniform float iridescenceIOR;\n\tuniform float iridescenceThicknessMinimum;\n\tuniform float iridescenceThicknessMaximum;\n#endif\n#ifdef USE_SHEEN\n\tuniform vec3 sheenColor;\n\tuniform float sheenRoughness;\n\t#ifdef USE_SHEEN_COLORMAP\n\t\tuniform sampler2D sheenColorMap;\n\t#endif\n\t#ifdef USE_SHEEN_ROUGHNESSMAP\n\t\tuniform sampler2D sheenRoughnessMap;\n\t#endif\n#endif\n#ifdef USE_ANISOTROPY\n\tuniform vec2 anisotropyVector;\n\t#ifdef USE_ANISOTROPYMAP\n\t\tuniform sampler2D anisotropyMap;\n\t#endif\n#endif\nvarying vec3 vViewPosition;\n#include <common>\n#include <packing>\n#include <dithering_pars_fragment>\n#include <color_pars_fragment>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <alphamap_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <aomap_pars_fragment>\n#include <lightmap_pars_fragment>\n#include <emissivemap_pars_fragment>\n#include <iridescence_fragment>\n#include <cube_uv_reflection_fragment>\n#include <envmap_common_pars_fragment>\n#include <envmap_physical_pars_fragment>\n#include <fog_pars_fragment>\n#include <lights_pars_begin>\n#include <normal_pars_fragment>\n#include <lights_physical_pars_fragment>\n#include <transmission_pars_fragment>\n#include <shadowmap_pars_fragment>\n#include <bumpmap_pars_fragment>\n#include <normalmap_pars_fragment>\n#include <clearcoat_pars_fragment>\n#include <iridescence_pars_fragment>\n#include <roughnessmap_pars_fragment>\n#include <metalnessmap_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include <clipping_planes_fragment>\n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\tvec3 totalEmissiveRadiance = emissive;\n\t#include <logdepthbuf_fragment>\n\t#include <map_fragment>\n\t#include <color_fragment>\n\t#include <alphamap_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\t#include <roughnessmap_fragment>\n\t#include <metalnessmap_fragment>\n\t#include <normal_fragment_begin>\n\t#include <normal_fragment_maps>\n\t#include <clearcoat_normal_fragment_begin>\n\t#include <clearcoat_normal_fragment_maps>\n\t#include <emissivemap_fragment>\n\t#include <lights_physical_fragment>\n\t#include <lights_fragment_begin>\n\t#include <lights_fragment_maps>\n\t#include <lights_fragment_end>\n\t#include <aomap_fragment>\n\tvec3 totalDiffuse = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse;\n\tvec3 totalSpecular = reflectedLight.directSpecular + reflectedLight.indirectSpecular;\n\t#include <transmission_fragment>\n\tvec3 outgoingLight = totalDiffuse + totalSpecular + totalEmissiveRadiance;\n\t#ifdef USE_SHEEN\n\t\tfloat sheenEnergyComp = 1.0 - 0.157 * max3( material.sheenColor );\n\t\toutgoingLight = outgoingLight * sheenEnergyComp + sheenSpecularDirect + sheenSpecularIndirect;\n\t#endif\n\t#ifdef USE_CLEARCOAT\n\t\tfloat dotNVcc = saturate( dot( geometryClearcoatNormal, geometryViewDir ) );\n\t\tvec3 Fcc = F_Schlick( material.clearcoatF0, material.clearcoatF90, dotNVcc );\n\t\toutgoingLight = outgoingLight * ( 1.0 - material.clearcoat * Fcc ) + ( clearcoatSpecularDirect + clearcoatSpecularIndirect ) * material.clearcoat;\n\t#endif\n\t#include <opaque_fragment>\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n\t#include <premultiplied_alpha_fragment>\n\t#include <dithering_fragment>\n}",meshtoon_vert:"#define TOON\nvarying vec3 vViewPosition;\n#include <common>\n#include <batching_pars_vertex>\n#include <uv_pars_vertex>\n#include <displacementmap_pars_vertex>\n#include <color_pars_vertex>\n#include <fog_pars_vertex>\n#include <normal_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <shadowmap_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\t#include <uv_vertex>\n\t#include <color_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphcolor_vertex>\n\t#include <batching_vertex>\n\t#include <beginnormal_vertex>\n\t#include <morphnormal_vertex>\n\t#include <skinbase_vertex>\n\t#include <skinnormal_vertex>\n\t#include <defaultnormal_vertex>\n\t#include <normal_vertex>\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <displacementmap_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\tvViewPosition = - mvPosition.xyz;\n\t#include <worldpos_vertex>\n\t#include <shadowmap_vertex>\n\t#include <fog_vertex>\n}",meshtoon_frag:"#define TOON\nuniform vec3 diffuse;\nuniform vec3 emissive;\nuniform float opacity;\n#include <common>\n#include <packing>\n#include <dithering_pars_fragment>\n#include <color_pars_fragment>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <alphamap_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <aomap_pars_fragment>\n#include <lightmap_pars_fragment>\n#include <emissivemap_pars_fragment>\n#include <gradientmap_pars_fragment>\n#include <fog_pars_fragment>\n#include <bsdfs>\n#include <lights_pars_begin>\n#include <normal_pars_fragment>\n#include <lights_toon_pars_fragment>\n#include <shadowmap_pars_fragment>\n#include <bumpmap_pars_fragment>\n#include <normalmap_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include <clipping_planes_fragment>\n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\tvec3 totalEmissiveRadiance = emissive;\n\t#include <logdepthbuf_fragment>\n\t#include <map_fragment>\n\t#include <color_fragment>\n\t#include <alphamap_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\t#include <normal_fragment_begin>\n\t#include <normal_fragment_maps>\n\t#include <emissivemap_fragment>\n\t#include <lights_toon_fragment>\n\t#include <lights_fragment_begin>\n\t#include <lights_fragment_maps>\n\t#include <lights_fragment_end>\n\t#include <aomap_fragment>\n\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\n\t#include <opaque_fragment>\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n\t#include <premultiplied_alpha_fragment>\n\t#include <dithering_fragment>\n}",points_vert:"uniform float size;\nuniform float scale;\n#include <common>\n#include <color_pars_vertex>\n#include <fog_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\n#ifdef USE_POINTS_UV\n\tvarying vec2 vUv;\n\tuniform mat3 uvTransform;\n#endif\nvoid main() {\n\t#ifdef USE_POINTS_UV\n\t\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\n\t#endif\n\t#include <color_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphcolor_vertex>\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <project_vertex>\n\tgl_PointSize = size;\n\t#ifdef USE_SIZEATTENUATION\n\t\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\n\t\tif ( isPerspective ) gl_PointSize *= ( scale / - mvPosition.z );\n\t#endif\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\t#include <worldpos_vertex>\n\t#include <fog_vertex>\n}",points_frag:"uniform vec3 diffuse;\nuniform float opacity;\n#include <common>\n#include <color_pars_fragment>\n#include <map_particle_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <fog_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include <clipping_planes_fragment>\n\tvec3 outgoingLight = vec3( 0.0 );\n\t#include <logdepthbuf_fragment>\n\t#include <map_particle_fragment>\n\t#include <color_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\toutgoingLight = diffuseColor.rgb;\n\t#include <opaque_fragment>\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n\t#include <premultiplied_alpha_fragment>\n}",shadow_vert:"#include <common>\n#include <batching_pars_vertex>\n#include <fog_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <shadowmap_pars_vertex>\nvoid main() {\n\t#include <batching_vertex>\n\t#include <beginnormal_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphnormal_vertex>\n\t#include <skinbase_vertex>\n\t#include <skinnormal_vertex>\n\t#include <defaultnormal_vertex>\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <worldpos_vertex>\n\t#include <shadowmap_vertex>\n\t#include <fog_vertex>\n}",shadow_frag:"uniform vec3 color;\nuniform float opacity;\n#include <common>\n#include <packing>\n#include <fog_pars_fragment>\n#include <bsdfs>\n#include <lights_pars_begin>\n#include <logdepthbuf_pars_fragment>\n#include <shadowmap_pars_fragment>\n#include <shadowmask_pars_fragment>\nvoid main() {\n\t#include <logdepthbuf_fragment>\n\tgl_FragColor = vec4( color, opacity * ( 1.0 - getShadowMask() ) );\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n}",sprite_vert:"uniform float rotation;\nuniform vec2 center;\n#include <common>\n#include <uv_pars_vertex>\n#include <fog_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\t#include <uv_vertex>\n\tvec4 mvPosition = modelViewMatrix[ 3 ];\n\tvec2 scale = vec2( length( modelMatrix[ 0 ].xyz ), length( modelMatrix[ 1 ].xyz ) );\n\t#ifndef USE_SIZEATTENUATION\n\t\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\n\t\tif ( isPerspective ) scale *= - mvPosition.z;\n\t#endif\n\tvec2 alignedPosition = ( position.xy - ( center - vec2( 0.5 ) ) ) * scale;\n\tvec2 rotatedPosition;\n\trotatedPosition.x = cos( rotation ) * alignedPosition.x - sin( rotation ) * alignedPosition.y;\n\trotatedPosition.y = sin( rotation ) * alignedPosition.x + cos( rotation ) * alignedPosition.y;\n\tmvPosition.xy += rotatedPosition;\n\tgl_Position = projectionMatrix * mvPosition;\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\t#include <fog_vertex>\n}",sprite_frag:"uniform vec3 diffuse;\nuniform float opacity;\n#include <common>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <alphamap_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <fog_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include <clipping_planes_fragment>\n\tvec3 outgoingLight = vec3( 0.0 );\n\t#include <logdepthbuf_fragment>\n\t#include <map_fragment>\n\t#include <alphamap_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\toutgoingLight = diffuseColor.rgb;\n\t#include <opaque_fragment>\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n}"},gp={common:{diffuse:{value:new ya(16777215)},opacity:{value:1},map:{value:null},mapTransform:{value:new Ps},alphaMap:{value:null},alphaMapTransform:{value:new Ps},alphaTest:{value:0}},specularmap:{specularMap:{value:null},specularMapTransform:{value:new Ps}},envmap:{envMap:{value:null},envMapRotation:{value:new Ps},flipEnvMap:{value:-1},reflectivity:{value:1},ior:{value:1.5},refractionRatio:{value:.98}},aomap:{aoMap:{value:null},aoMapIntensity:{value:1},aoMapTransform:{value:new Ps}},lightmap:{lightMap:{value:null},lightMapIntensity:{value:1},lightMapTransform:{value:new Ps}},bumpmap:{bumpMap:{value:null},bumpMapTransform:{value:new Ps},bumpScale:{value:1}},normalmap:{normalMap:{value:null},normalMapTransform:{value:new Ps},normalScale:{value:new Cs(1,1)}},displacementmap:{displacementMap:{value:null},displacementMapTransform:{value:new Ps},displacementScale:{value:1},displacementBias:{value:0}},emissivemap:{emissiveMap:{value:null},emissiveMapTransform:{value:new Ps}},metalnessmap:{metalnessMap:{value:null},metalnessMapTransform:{value:new Ps}},roughnessmap:{roughnessMap:{value:null},roughnessMapTransform:{value:new Ps}},gradientmap:{gradientMap:{value:null}},fog:{fogDensity:{value:25e-5},fogNear:{value:1},fogFar:{value:2e3},fogColor:{value:new ya(16777215)}},lights:{ambientLightColor:{value:[]},lightProbe:{value:[]},directionalLights:{value:[],properties:{direction:{},color:{}}},directionalLightShadows:{value:[],properties:{shadowIntensity:1,shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{}}},directionalShadowMap:{value:[]},directionalShadowMatrix:{value:[]},spotLights:{value:[],properties:{color:{},position:{},direction:{},distance:{},coneCos:{},penumbraCos:{},decay:{}}},spotLightShadows:{value:[],properties:{shadowIntensity:1,shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{}}},spotLightMap:{value:[]},spotShadowMap:{value:[]},spotLightMatrix:{value:[]},pointLights:{value:[],properties:{color:{},position:{},decay:{},distance:{}}},pointLightShadows:{value:[],properties:{shadowIntensity:1,shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{},shadowCameraNear:{},shadowCameraFar:{}}},pointShadowMap:{value:[]},pointShadowMatrix:{value:[]},hemisphereLights:{value:[],properties:{direction:{},skyColor:{},groundColor:{}}},rectAreaLights:{value:[],properties:{color:{},position:{},width:{},height:{}}},ltc_1:{value:null},ltc_2:{value:null}},points:{diffuse:{value:new ya(16777215)},opacity:{value:1},size:{value:1},scale:{value:1},map:{value:null},alphaMap:{value:null},alphaMapTransform:{value:new Ps},alphaTest:{value:0},uvTransform:{value:new Ps}},sprite:{diffuse:{value:new ya(16777215)},opacity:{value:1},center:{value:new Cs(.5,.5)},rotation:{value:0},map:{value:null},mapTransform:{value:new Ps},alphaMap:{value:null},alphaMapTransform:{value:new Ps},alphaTest:{value:0}}},mp={basic:{uniforms:ol([gp.common,gp.specularmap,gp.envmap,gp.aomap,gp.lightmap,gp.fog]),vertexShader:pp.meshbasic_vert,fragmentShader:pp.meshbasic_frag},lambert:{uniforms:ol([gp.common,gp.specularmap,gp.envmap,gp.aomap,gp.lightmap,gp.emissivemap,gp.bumpmap,gp.normalmap,gp.displacementmap,gp.fog,gp.lights,{emissive:{value:new ya(0)}}]),vertexShader:pp.meshlambert_vert,fragmentShader:pp.meshlambert_frag},phong:{uniforms:ol([gp.common,gp.specularmap,gp.envmap,gp.aomap,gp.lightmap,gp.emissivemap,gp.bumpmap,gp.normalmap,gp.displacementmap,gp.fog,gp.lights,{emissive:{value:new 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this._fromTexture(e,t)}compileCubemapShader(){null===this._cubemapMaterial&&(this._cubemapMaterial=Xp(),this._compileMaterial(this._cubemapMaterial))}compileEquirectangularShader(){null===this._equirectMaterial&&(this._equirectMaterial=Up(),this._compileMaterial(this._equirectMaterial))}dispose(){this._dispose(),null!==this._cubemapMaterial&&this._cubemapMaterial.dispose(),null!==this._equirectMaterial&&this._equirectMaterial.dispose()}_setSize(e){this._lodMax=Math.floor(Math.log2(e)),this._cubeSize=Math.pow(2,this._lodMax)}_dispose(){null!==this._blurMaterial&&this._blurMaterial.dispose(),null!==this._pingPongRenderTarget&&this._pingPongRenderTarget.dispose();for(let e=0;e<this._lodPlanes.length;e++)this._lodPlanes[e].dispose()}_cleanup(e){this._renderer.setRenderTarget(Bp,Dp,Ip),this._renderer.xr.enabled=Lp,e.scissorTest=!1,Hp(e,0,0,e.width,e.height)}_fromTexture(e,t){e.mapping===Ni||e.mapping===Bi?this._setSize(0===e.image.length?16:e.image[0].width||e.image[0].image.width):this._setSize(e.image.width/4),Bp=this._renderer.getRenderTarget(),Dp=this._renderer.getActiveCubeFace(),Ip=this._renderer.getActiveMipmapLevel(),Lp=this._renderer.xr.enabled,this._renderer.xr.enabled=!1;const n=t||this._allocateTargets();return this._textureToCubeUV(e,n),this._applyPMREM(n),this._cleanup(n),n}_allocateTargets(){const e=3*Math.max(this._cubeSize,112),t=4*this._cubeSize,n={magFilter:Hi,minFilter:Hi,generateMipmaps:!1,type:Ki,format:rr,colorSpace:_r,depthBuffer:!1},i=Fp(e,t,n);if(null===this._pingPongRenderTarget||this._pingPongRenderTarget.width!==e||this._pingPongRenderTarget.height!==t){null!==this._pingPongRenderTarget&&this._dispose(),this._pingPongRenderTarget=Fp(e,t,n);const{_lodMax:i}=this;({sizeLods:this._sizeLods,lodPlanes:this._lodPlanes,sigmas:this._sigmas}=function(e){const t=[],n=[],i=[];let r=e;const s=e-4+1+Tp.length;for(let o=0;o<s;o++){const s=Math.pow(2,r);n.push(s);let a=1/s;o>e-4?a=Tp[o-e+4-1]:0===o&&(a=0),i.push(a);const l=1/(s-2),u=-l,c=1+l,d=[u,u,c,u,c,c,u,u,c,c,u,c],h=6,f=6,p=3,g=2,m=1,v=new Float32Array(p*f*h),A=new Float32Array(g*f*h),x=new Float32Array(m*f*h);for(let e=0;e<h;e++){const t=e%3*2/3-1,n=e>2?0:-1,i=[t,n,0,t+2/3,n,0,t+2/3,n+1,0,t,n,0,t+2/3,n+1,0,t,n+1,0];v.set(i,p*f*e),A.set(d,g*f*e);const r=[e,e,e,e,e,e];x.set(r,m*f*e)}const y=new Va;y.setAttribute("position",new Ia(v,p)),y.setAttribute("uv",new Ia(A,g)),y.setAttribute("faceIndex",new Ia(x,m)),t.push(y),r>4&&r--}return{lodPlanes:t,sizeLods:n,sigmas:i}}(i)),this._blurMaterial=function(e,t,n){const i=new Float32Array(Sp),r=new Es(0,1,0),s=new ul({name:"SphericalGaussianBlur",defines:{n:Sp,CUBEUV_TEXEL_WIDTH:1/t,CUBEUV_TEXEL_HEIGHT:1/n,CUBEUV_MAX_MIP:`${e}.0`},uniforms:{envMap:{value:null},samples:{value:1},weights:{value:i},latitudinal:{value:!1},dTheta:{value:0},mipInt:{value:0},poleAxis:{value:r}},vertexShader:Gp(),fragmentShader:"\n\n\t\t\tprecision mediump float;\n\t\t\tprecision mediump int;\n\n\t\t\tvarying vec3 vOutputDirection;\n\n\t\t\tuniform sampler2D envMap;\n\t\t\tuniform int samples;\n\t\t\tuniform float weights[ n ];\n\t\t\tuniform bool latitudinal;\n\t\t\tuniform float dTheta;\n\t\t\tuniform float mipInt;\n\t\t\tuniform vec3 poleAxis;\n\n\t\t\t#define ENVMAP_TYPE_CUBE_UV\n\t\t\t#include <cube_uv_reflection_fragment>\n\n\t\t\tvec3 getSample( float theta, vec3 axis ) {\n\n\t\t\t\tfloat cosTheta = cos( theta );\n\t\t\t\t// Rodrigues' axis-angle rotation\n\t\t\t\tvec3 sampleDirection = vOutputDirection * cosTheta\n\t\t\t\t\t+ cross( axis, vOutputDirection ) * sin( theta )\n\t\t\t\t\t+ axis * dot( axis, vOutputDirection ) * ( 1.0 - cosTheta );\n\n\t\t\t\treturn bilinearCubeUV( envMap, sampleDirection, mipInt );\n\n\t\t\t}\n\n\t\t\tvoid main() {\n\n\t\t\t\tvec3 axis = latitudinal ? poleAxis : cross( poleAxis, vOutputDirection );\n\n\t\t\t\tif ( all( equal( axis, vec3( 0.0 ) ) ) ) {\n\n\t\t\t\t\taxis = vec3( vOutputDirection.z, 0.0, - vOutputDirection.x );\n\n\t\t\t\t}\n\n\t\t\t\taxis = normalize( axis );\n\n\t\t\t\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\n\t\t\t\tgl_FragColor.rgb += weights[ 0 ] * getSample( 0.0, axis );\n\n\t\t\t\tfor ( int i = 1; i < n; i++ ) {\n\n\t\t\t\t\tif ( i >= samples ) {\n\n\t\t\t\t\t\tbreak;\n\n\t\t\t\t\t}\n\n\t\t\t\t\tfloat theta = dTheta * float( i );\n\t\t\t\t\tgl_FragColor.rgb += weights[ i ] * getSample( -1.0 * theta, axis );\n\t\t\t\t\tgl_FragColor.rgb += weights[ i ] * getSample( theta, axis );\n\n\t\t\t\t}\n\n\t\t\t}\n\t\t",blending:0,depthTest:!1,depthWrite:!1});return s}(i,e,t)}return i}_compileMaterial(e){const t=new nl(this._lodPlanes[0],e);this._renderer.compile(t,Pp)}_sceneToCubeUV(e,t,n,i,r){const s=new pl(90,1,t,n),o=[1,-1,1,1,1,1],a=[1,1,1,-1,-1,-1],l=this._renderer,u=l.autoClear,c=l.toneMapping;l.getClearColor(Np),l.toneMapping=0,l.autoClear=!1;l.state.buffers.depth.getReversed()&&(l.setRenderTarget(i),l.clearDepth(),l.setRenderTarget(null));const d=new Ma({name:"PMREM.Background",side:1,depthWrite:!1,depthTest:!1}),h=new nl(new rl,d);let f=!1;const p=e.background;p?p.isColor&&(d.color.copy(p),e.background=null,f=!0):(d.color.copy(Np),f=!0);for(let t=0;t<6;t++){const n=t%3;0===n?(s.up.set(0,o[t],0),s.position.set(r.x,r.y,r.z),s.lookAt(r.x+a[t],r.y,r.z)):1===n?(s.up.set(0,0,o[t]),s.position.set(r.x,r.y,r.z),s.lookAt(r.x,r.y+a[t],r.z)):(s.up.set(0,o[t],0),s.position.set(r.x,r.y,r.z),s.lookAt(r.x,r.y,r.z+a[t]));const u=this._cubeSize;Hp(i,n*u,t>2?u:0,u,u),l.setRenderTarget(i),f&&l.render(h,s),l.render(e,s)}h.geometry.dispose(),h.material.dispose(),l.toneMapping=c,l.autoClear=u,e.background=p}_textureToCubeUV(e,t){const n=this._renderer,i=e.mapping===Ni||e.mapping===Bi;i?(null===this._cubemapMaterial&&(this._cubemapMaterial=Xp()),this._cubemapMaterial.uniforms.flipEnvMap.value=!1===e.isRenderTargetTexture?-1:1):null===this._equirectMaterial&&(this._equirectMaterial=Up());const r=i?this._cubemapMaterial:this._equirectMaterial,s=new nl(this._lodPlanes[0],r);r.uniforms.envMap.value=e;const o=this._cubeSize;Hp(t,0,0,3*o,2*o),n.setRenderTarget(t),n.render(s,Pp)}_applyPMREM(e){const t=this._renderer,n=t.autoClear;t.autoClear=!1;const i=this._lodPlanes.length;for(let t=1;t<i;t++){const n=Math.sqrt(this._sigmas[t]*this._sigmas[t]-this._sigmas[t-1]*this._sigmas[t-1]),r=zp[(i-t-1)%zp.length];this._blur(e,t-1,t,n,r)}t.autoClear=n}_blur(e,t,n,i,r){const s=this._pingPongRenderTarget;this._halfBlur(e,s,t,n,i,"latitudinal",r),this._halfBlur(s,e,n,n,i,"longitudinal",r)}_halfBlur(e,t,n,i,r,s,o){const a=this._renderer,l=this._blurMaterial;"latitudinal"!==s&&"longitudinal"!==s&&console.error("blur direction must be either latitudinal or longitudinal!");const u=new nl(this._lodPlanes[i],l),c=l.uniforms,d=this._sizeLods[n]-1,h=isFinite(r)?Math.PI/(2*d):2*Math.PI/39,f=r/h,p=isFinite(r)?1+Math.floor(3*f):Sp;p>Sp&&console.warn(`sigmaRadians, ${r}, is too large and will clip, as it requested ${p} samples when the maximum is set to 20`);const g=[];let m=0;for(let e=0;e<Sp;++e){const t=e/f,n=Math.exp(-t*t/2);g.push(n),0===e?m+=n:e<p&&(m+=2*n)}for(let e=0;e<g.length;e++)g[e]=g[e]/m;c.envMap.value=e.texture,c.samples.value=p,c.weights.value=g,c.latitudinal.value="latitudinal"===s,o&&(c.poleAxis.value=o);const{_lodMax:v}=this;c.dTheta.value=h,c.mipInt.value=v-n;const A=this._sizeLods[i];Hp(t,3*A*(i>v-4?i-v+4:0),4*(this._cubeSize-A),3*A,2*A),a.setRenderTarget(t),a.render(u,Pp)}}function Fp(e,t,n){const i=new qs(e,t,n);return i.texture.mapping=Li,i.texture.name="PMREM.cubeUv",i.scissorTest=!0,i}function Hp(e,t,n,i,r){e.viewport.set(t,n,i,r),e.scissor.set(t,n,i,r)}function Up(){return new ul({name:"EquirectangularToCubeUV",uniforms:{envMap:{value:null}},vertexShader:Gp(),fragmentShader:"\n\n\t\t\tprecision mediump float;\n\t\t\tprecision mediump int;\n\n\t\t\tvarying vec3 vOutputDirection;\n\n\t\t\tuniform sampler2D envMap;\n\n\t\t\t#include <common>\n\n\t\t\tvoid main() {\n\n\t\t\t\tvec3 outputDirection = normalize( vOutputDirection );\n\t\t\t\tvec2 uv = equirectUv( outputDirection );\n\n\t\t\t\tgl_FragColor = vec4( texture2D ( envMap, uv ).rgb, 1.0 );\n\n\t\t\t}\n\t\t",blending:0,depthTest:!1,depthWrite:!1})}function Xp(){return new ul({name:"CubemapToCubeUV",uniforms:{envMap:{value:null},flipEnvMap:{value:-1}},vertexShader:Gp(),fragmentShader:"\n\n\t\t\tprecision mediump float;\n\t\t\tprecision mediump int;\n\n\t\t\tuniform float flipEnvMap;\n\n\t\t\tvarying vec3 vOutputDirection;\n\n\t\t\tuniform samplerCube envMap;\n\n\t\t\tvoid main() {\n\n\t\t\t\tgl_FragColor = textureCube( envMap, vec3( flipEnvMap * vOutputDirection.x, vOutputDirection.yz ) );\n\n\t\t\t}\n\t\t",blending:0,depthTest:!1,depthWrite:!1})}function Gp(){return"\n\n\t\tprecision mediump float;\n\t\tprecision mediump int;\n\n\t\tattribute float faceIndex;\n\n\t\tvarying vec3 vOutputDirection;\n\n\t\t// RH coordinate system; PMREM face-indexing convention\n\t\tvec3 getDirection( vec2 uv, float face ) {\n\n\t\t\tuv = 2.0 * uv - 1.0;\n\n\t\t\tvec3 direction = vec3( uv, 1.0 );\n\n\t\t\tif ( face == 0.0 ) {\n\n\t\t\t\tdirection = direction.zyx; // ( 1, v, u ) pos x\n\n\t\t\t} else if ( face == 1.0 ) {\n\n\t\t\t\tdirection = direction.xzy;\n\t\t\t\tdirection.xz *= -1.0; // ( -u, 1, -v ) pos y\n\n\t\t\t} else if ( face == 2.0 ) {\n\n\t\t\t\tdirection.x *= -1.0; // ( -u, v, 1 ) pos z\n\n\t\t\t} else if ( face == 3.0 ) {\n\n\t\t\t\tdirection = direction.zyx;\n\t\t\t\tdirection.xz *= -1.0; // ( -1, v, -u ) neg x\n\n\t\t\t} else if ( face == 4.0 ) {\n\n\t\t\t\tdirection = direction.xzy;\n\t\t\t\tdirection.xy *= -1.0; // ( -u, -1, v ) neg y\n\n\t\t\t} else if ( face == 5.0 ) {\n\n\t\t\t\tdirection.z *= -1.0; // ( u, v, -1 ) neg z\n\n\t\t\t}\n\n\t\t\treturn direction;\n\n\t\t}\n\n\t\tvoid main() {\n\n\t\t\tvOutputDirection = getDirection( uv, faceIndex );\n\t\t\tgl_Position = vec4( position, 1.0 );\n\n\t\t}\n\t"}function Vp(e){let t=new WeakMap,n=null;function i(e){const n=e.target;n.removeEventListener("dispose",i);const r=t.get(n);void 0!==r&&(t.delete(n),r.dispose())}return{get:function(r){if(r&&r.isTexture){const s=r.mapping,o=s===Di||s===Ii,a=s===Ni||s===Bi;if(o||a){let s=t.get(r);const l=void 0!==s?s.texture.pmremVersion:0;if(r.isRenderTargetTexture&&r.pmremVersion!==l)return null===n&&(n=new kp(e)),s=o?n.fromEquirectangular(r,s):n.fromCubemap(r,s),s.texture.pmremVersion=r.pmremVersion,t.set(r,s),s.texture;if(void 0!==s)return s.texture;{const l=r.image;return o&&l&&l.height>0||a&&l&&function(e){let t=0;const n=6;for(let i=0;i<n;i++)void 0!==e[i]&&t++;return t===n}(l)?(null===n&&(n=new kp(e)),s=o?n.fromEquirectangular(r):n.fromCubemap(r),s.texture.pmremVersion=r.pmremVersion,t.set(r,s),r.addEventListener("dispose",i),s.texture):null}}}return r},dispose:function(){t=new WeakMap,null!==n&&(n.dispose(),n=null)}}}function Wp(e){const t={};function n(n){if(void 0!==t[n])return t[n];let i;switch(n){case"WEBGL_depth_texture":i=e.getExtension("WEBGL_depth_texture")||e.getExtension("MOZ_WEBGL_depth_texture")||e.getExtension("WEBKIT_WEBGL_depth_texture");break;case"EXT_texture_filter_anisotropic":i=e.getExtension("EXT_texture_filter_anisotropic")||e.getExtension("MOZ_EXT_texture_filter_anisotropic")||e.getExtension("WEBKIT_EXT_texture_filter_anisotropic");break;case"WEBGL_compressed_texture_s3tc":i=e.getExtension("WEBGL_compressed_texture_s3tc")||e.getExtension("MOZ_WEBGL_compressed_texture_s3tc")||e.getExtension("WEBKIT_WEBGL_compressed_texture_s3tc");break;case"WEBGL_compressed_texture_pvrtc":i=e.getExtension("WEBGL_compressed_texture_pvrtc")||e.getExtension("WEBKIT_WEBGL_compressed_texture_pvrtc");break;default:i=e.getExtension(n)}return t[n]=i,i}return{has:function(e){return null!==n(e)},init:function(){n("EXT_color_buffer_float"),n("WEBGL_clip_cull_distance"),n("OES_texture_float_linear"),n("EXT_color_buffer_half_float"),n("WEBGL_multisampled_render_to_texture"),n("WEBGL_render_shared_exponent")},get:function(e){const t=n(e);return null===t&&js("THREE.WebGLRenderer: "+e+" extension not supported."),t}}}function Qp(e,t,n,i){const r={},s=new WeakMap;function o(e){const a=e.target;null!==a.index&&t.remove(a.index);for(const e in a.attributes)t.remove(a.attributes[e]);a.removeEventListener("dispose",o),delete r[a.id];const l=s.get(a);l&&(t.remove(l),s.delete(a)),i.releaseStatesOfGeometry(a),!0===a.isInstancedBufferGeometry&&delete a._maxInstanceCount,n.memory.geometries--}function a(e){const n=[],i=e.index,r=e.attributes.position;let o=0;if(null!==i){const e=i.array;o=i.version;for(let t=0,i=e.length;t<i;t+=3){const i=e[t+0],r=e[t+1],s=e[t+2];n.push(i,r,r,s,s,i)}}else{if(void 0===r)return;{const e=r.array;o=r.version;for(let t=0,i=e.length/3-1;t<i;t+=3){const 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c=t.get("WEBGL_multi_draw");if(null===c)for(let t=0;t<e.length;t++)o(e[t]/s,a[t],u[t]);else{c.multiDrawElementsInstancedWEBGL(i,a,0,r,e,0,u,0,l);let t=0;for(let e=0;e<l;e++)t+=a[e]*u[e];n.update(t,i,1)}}}function Yp(e){const t={frame:0,calls:0,triangles:0,points:0,lines:0};return{memory:{geometries:0,textures:0},render:t,programs:null,autoReset:!0,reset:function(){t.calls=0,t.triangles=0,t.points=0,t.lines=0},update:function(n,i,r){switch(t.calls++,i){case e.TRIANGLES:t.triangles+=r*(n/3);break;case e.LINES:t.lines+=r*(n/2);break;case e.LINE_STRIP:t.lines+=r*(n-1);break;case e.LINE_LOOP:t.lines+=r*n;break;case e.POINTS:t.points+=r*n;break;default:console.error("THREE.WebGLInfo: Unknown draw mode:",i)}}}}function Jp(e,t,n){const i=new WeakMap,r=new Js;return{update:function(s,o,a){const l=s.morphTargetInfluences,u=o.morphAttributes.position||o.morphAttributes.normal||o.morphAttributes.color,c=void 0!==u?u.length:0;let d=i.get(o);if(void 0===d||d.count!==c){void 0!==d&&d.texture.dispose();const h=void 0!==o.morphAttributes.position,f=void 0!==o.morphAttributes.normal,p=void 0!==o.morphAttributes.color,g=o.morphAttributes.position||[],m=o.morphAttributes.normal||[],v=o.morphAttributes.color||[];let A=0;!0===h&&(A=1),!0===f&&(A=2),!0===p&&(A=3);let x=o.attributes.position.count*A,y=1;x>t.maxTextureSize&&(y=Math.ceil(x/t.maxTextureSize),x=t.maxTextureSize);const b=new Float32Array(x*y*4*c),w=new _s(b,x,y,c);w.type=Ji,w.needsUpdate=!0;const C=4*A;for(let E=0;E<c;E++){const T=g[E],S=m[E],P=v[E],N=x*y*4*E;for(let B=0;B<T.count;B++){const D=B*C;!0===h&&(r.fromBufferAttribute(T,B),b[N+D+0]=r.x,b[N+D+1]=r.y,b[N+D+2]=r.z,b[N+D+3]=0),!0===f&&(r.fromBufferAttribute(S,B),b[N+D+4]=r.x,b[N+D+5]=r.y,b[N+D+6]=r.z,b[N+D+7]=0),!0===p&&(r.fromBufferAttribute(P,B),b[N+D+8]=r.x,b[N+D+9]=r.y,b[N+D+10]=r.z,b[N+D+11]=4===P.itemSize?r.w:1)}}function M(){w.dispose(),i.delete(o),o.removeEventListener("dispose",M)}d={count:c,texture:w,size:new 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Int32Array(t),ig[t]=n);for(let i=0;i!==t;++i)n[i]=e.allocateTextureUnit();return n}function dg(e,t){const n=this.cache;n[0]!==t&&(e.uniform1f(this.addr,t),n[0]=t)}function hg(e,t){const n=this.cache;if(void 0!==t.x)n[0]===t.x&&n[1]===t.y||(e.uniform2f(this.addr,t.x,t.y),n[0]=t.x,n[1]=t.y);else{if(lg(n,t))return;e.uniform2fv(this.addr,t),ug(n,t)}}function fg(e,t){const n=this.cache;if(void 0!==t.x)n[0]===t.x&&n[1]===t.y&&n[2]===t.z||(e.uniform3f(this.addr,t.x,t.y,t.z),n[0]=t.x,n[1]=t.y,n[2]=t.z);else if(void 0!==t.r)n[0]===t.r&&n[1]===t.g&&n[2]===t.b||(e.uniform3f(this.addr,t.r,t.g,t.b),n[0]=t.r,n[1]=t.g,n[2]=t.b);else{if(lg(n,t))return;e.uniform3fv(this.addr,t),ug(n,t)}}function pg(e,t){const n=this.cache;if(void 0!==t.x)n[0]===t.x&&n[1]===t.y&&n[2]===t.z&&n[3]===t.w||(e.uniform4f(this.addr,t.x,t.y,t.z,t.w),n[0]=t.x,n[1]=t.y,n[2]=t.z,n[3]=t.w);else{if(lg(n,t))return;e.uniform4fv(this.addr,t),ug(n,t)}}function gg(e,t){const n=this.cache,i=t.elements;if(void 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0!==t.x)n[0]===t.x&&n[1]===t.y&&n[2]===t.z||(e.uniform3i(this.addr,t.x,t.y,t.z),n[0]=t.x,n[1]=t.y,n[2]=t.z);else{if(lg(n,t))return;e.uniform3iv(this.addr,t),ug(n,t)}}function bg(e,t){const n=this.cache;if(void 0!==t.x)n[0]===t.x&&n[1]===t.y&&n[2]===t.z&&n[3]===t.w||(e.uniform4i(this.addr,t.x,t.y,t.z,t.w),n[0]=t.x,n[1]=t.y,n[2]=t.z,n[3]=t.w);else{if(lg(n,t))return;e.uniform4iv(this.addr,t),ug(n,t)}}function wg(e,t){const n=this.cache;n[0]!==t&&(e.uniform1ui(this.addr,t),n[0]=t)}function Cg(e,t){const n=this.cache;if(void 0!==t.x)n[0]===t.x&&n[1]===t.y||(e.uniform2ui(this.addr,t.x,t.y),n[0]=t.x,n[1]=t.y);else{if(lg(n,t))return;e.uniform2uiv(this.addr,t),ug(n,t)}}function Mg(e,t){const n=this.cache;if(void 0!==t.x)n[0]===t.x&&n[1]===t.y&&n[2]===t.z||(e.uniform3ui(this.addr,t.x,t.y,t.z),n[0]=t.x,n[1]=t.y,n[2]=t.z);else{if(lg(n,t))return;e.uniform3uiv(this.addr,t),ug(n,t)}}function Eg(e,t){const n=this.cache;if(void 0!==t.x)n[0]===t.x&&n[1]===t.y&&n[2]===t.z&&n[3]===t.w||(e.uniform4ui(this.addr,t.x,t.y,t.z,t.w),n[0]=t.x,n[1]=t.y,n[2]=t.z,n[3]=t.w);else{if(lg(n,t))return;e.uniform4uiv(this.addr,t),ug(n,t)}}function Tg(e,t,n){const i=this.cache,r=n.allocateTextureUnit();let s;i[0]!==r&&(e.uniform1i(this.addr,r),i[0]=r),this.type===e.SAMPLER_2D_SHADOW?(_p.compareFunction=is,s=_p):s=qp,n.setTexture2D(t||s,r)}function Sg(e,t,n){const i=this.cache,r=n.allocateTextureUnit();i[0]!==r&&(e.uniform1i(this.addr,r),i[0]=r),n.setTexture3D(t||eg,r)}function Pg(e,t,n){const i=this.cache,r=n.allocateTextureUnit();i[0]!==r&&(e.uniform1i(this.addr,r),i[0]=r),n.setTextureCube(t||tg,r)}function Ng(e,t,n){const i=this.cache,r=n.allocateTextureUnit();i[0]!==r&&(e.uniform1i(this.addr,r),i[0]=r),n.setTexture2DArray(t||$p,r)}function Bg(e,t){e.uniform1fv(this.addr,t)}function Dg(e,t){const n=ag(t,this.size,2);e.uniform2fv(this.addr,n)}function Ig(e,t){const n=ag(t,this.size,3);e.uniform3fv(this.addr,n)}function Lg(e,t){const n=ag(t,this.size,4);e.uniform4fv(this.addr,n)}function jg(e,t){const n=ag(t,this.size,4);e.uniformMatrix2fv(this.addr,!1,n)}function Og(e,t){const n=ag(t,this.size,9);e.uniformMatrix3fv(this.addr,!1,n)}function zg(e,t){const n=ag(t,this.size,16);e.uniformMatrix4fv(this.addr,!1,n)}function Rg(e,t){e.uniform1iv(this.addr,t)}function kg(e,t){e.uniform2iv(this.addr,t)}function Fg(e,t){e.uniform3iv(this.addr,t)}function Hg(e,t){e.uniform4iv(this.addr,t)}function Ug(e,t){e.uniform1uiv(this.addr,t)}function Xg(e,t){e.uniform2uiv(this.addr,t)}function Gg(e,t){e.uniform3uiv(this.addr,t)}function Vg(e,t){e.uniform4uiv(this.addr,t)}function Wg(e,t,n){const i=this.cache,r=t.length,s=cg(n,r);lg(i,s)||(e.uniform1iv(this.addr,s),ug(i,s));for(let e=0;e!==r;++e)n.setTexture2D(t[e]||qp,s[e])}function Qg(e,t,n){const i=this.cache,r=t.length,s=cg(n,r);lg(i,s)||(e.uniform1iv(this.addr,s),ug(i,s));for(let e=0;e!==r;++e)n.setTexture3D(t[e]||eg,s[e])}function Zg(e,t,n){const i=this.cache,r=t.length,s=cg(n,r);lg(i,s)||(e.uniform1iv(this.addr,s),ug(i,s));for(let e=0;e!==r;++e)n.setTextureCube(t[e]||tg,s[e])}function Yg(e,t,n){const i=this.cache,r=t.length,s=cg(n,r);lg(i,s)||(e.uniform1iv(this.addr,s),ug(i,s));for(let e=0;e!==r;++e)n.setTexture2DArray(t[e]||$p,s[e])}class Jg{constructor(e,t,n){this.id=e,this.addr=n,this.cache=[],this.type=t.type,this.setValue=function(e){switch(e){case 5126:return dg;case 35664:return hg;case 35665:return fg;case 35666:return pg;case 35674:return gg;case 35675:return mg;case 35676:return vg;case 5124:case 35670:return Ag;case 35667:case 35671:return xg;case 35668:case 35672:return yg;case 35669:case 35673:return bg;case 5125:return wg;case 36294:return Cg;case 36295:return Mg;case 36296:return Eg;case 35678:case 36198:case 36298:case 36306:case 35682:return Tg;case 35679:case 36299:case 36307:return Sg;case 35680:case 36300:case 36308:case 36293:return Pg;case 36289:case 36303:case 36311:case 36292:return Ng}}(t.type)}}class Kg{constructor(e,t,n){this.id=e,this.addr=n,this.cache=[],this.type=t.type,this.size=t.size,this.setValue=function(e){switch(e){case 5126:return Bg;case 35664:return Dg;case 35665:return Ig;case 35666:return Lg;case 35674:return jg;case 35675:return Og;case 35676:return zg;case 5124:case 35670:return Rg;case 35667:case 35671:return kg;case 35668:case 35672:return Fg;case 35669:case 35673:return Hg;case 5125:return Ug;case 36294:return Xg;case 36295:return Gg;case 36296:return Vg;case 35678:case 36198:case 36298:case 36306:case 35682:return Wg;case 35679:case 36299:case 36307:return Qg;case 35680:case 36300:case 36308:case 36293:return Zg;case 36289:case 36303:case 36311:case 36292:return Yg}}(t.type)}}class qg{constructor(e){this.id=e,this.seq=[],this.map={}}setValue(e,t,n){const i=this.seq;for(let r=0,s=i.length;r!==s;++r){const s=i[r];s.setValue(e,t[s.id],n)}}}const _g=/(\w+)(\])?(\[|\.)?/g;function $g(e,t){e.seq.push(t),e.map[t.id]=t}function em(e,t,n){const 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e.replace(/NUM_DIR_LIGHTS/g,t.numDirLights).replace(/NUM_SPOT_LIGHTS/g,t.numSpotLights).replace(/NUM_SPOT_LIGHT_MAPS/g,t.numSpotLightMaps).replace(/NUM_SPOT_LIGHT_COORDS/g,n).replace(/NUM_RECT_AREA_LIGHTS/g,t.numRectAreaLights).replace(/NUM_POINT_LIGHTS/g,t.numPointLights).replace(/NUM_HEMI_LIGHTS/g,t.numHemiLights).replace(/NUM_DIR_LIGHT_SHADOWS/g,t.numDirLightShadows).replace(/NUM_SPOT_LIGHT_SHADOWS_WITH_MAPS/g,t.numSpotLightShadowsWithMaps).replace(/NUM_SPOT_LIGHT_SHADOWS/g,t.numSpotLightShadows).replace(/NUM_POINT_LIGHT_SHADOWS/g,t.numPointLightShadows)}function hm(e,t){return e.replace(/NUM_CLIPPING_PLANES/g,t.numClippingPlanes).replace(/UNION_CLIPPING_PLANES/g,t.numClippingPlanes-t.numClipIntersection)}const fm=/^[ \t]*#include +<([\w\d./]+)>/gm;function pm(e){return e.replace(fm,mm)}const gm=new Map;function mm(e,t){let n=pp[t];if(void 0===n){const e=gm.get(t);if(void 0===e)throw new Error("Can not resolve #include <"+t+">");n=pp[e],console.warn('THREE.WebGLRenderer: Shader 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Use "%s" instead.',t,e)}return pm(n)}const vm=/#pragma unroll_loop_start\s+for\s*\(\s*int\s+i\s*=\s*(\d+)\s*;\s*i\s*<\s*(\d+)\s*;\s*i\s*\+\+\s*\)\s*{([\s\S]+?)}\s+#pragma unroll_loop_end/g;function Am(e){return e.replace(vm,xm)}function xm(e,t,n,i){let r="";for(let e=parseInt(t);e<parseInt(n);e++)r+=i.replace(/\[\s*i\s*\]/g,"[ "+e+" ]").replace(/UNROLLED_LOOP_INDEX/g,e);return r}function ym(e){let t=`precision ${e.precision} float;\n\tprecision ${e.precision} int;\n\tprecision ${e.precision} sampler2D;\n\tprecision ${e.precision} samplerCube;\n\tprecision ${e.precision} sampler3D;\n\tprecision ${e.precision} sampler2DArray;\n\tprecision ${e.precision} sampler2DShadow;\n\tprecision ${e.precision} samplerCubeShadow;\n\tprecision ${e.precision} sampler2DArrayShadow;\n\tprecision ${e.precision} isampler2D;\n\tprecision ${e.precision} isampler3D;\n\tprecision ${e.precision} isamplerCube;\n\tprecision ${e.precision} isampler2DArray;\n\tprecision ${e.precision} usampler2D;\n\tprecision 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t=this.materialCache.get(e);for(const e of t)e.usedTimes--,0===e.usedTimes&&this.shaderCache.delete(e.code);return this.materialCache.delete(e),this}getVertexShaderID(e){return this._getShaderStage(e.vertexShader).id}getFragmentShaderID(e){return this._getShaderStage(e.fragmentShader).id}dispose(){this.shaderCache.clear(),this.materialCache.clear()}_getShaderCacheForMaterial(e){const t=this.materialCache;let n=t.get(e);return void 0===n&&(n=new Set,t.set(e,n)),n}_getShaderStage(e){const t=this.shaderCache;let n=t.get(e);return void 0===n&&(n=new Mm(e),t.set(e,n)),n}}class Mm{constructor(e){this.id=wm++,this.code=e,this.usedTimes=0}}function Em(e,t,n,i,r,s,o){const a=new Fo,l=new Cm,u=new Set,c=[],d=r.logarithmicDepthBuffer,h=r.vertexTextures;let f=r.precision;const p={MeshDepthMaterial:"depth",MeshDistanceMaterial:"distanceRGBA",MeshNormalMaterial:"normal",MeshBasicMaterial:"basic",MeshLambertMaterial:"lambert",MeshPhongMaterial:"phong",MeshToonMaterial:"toon",MeshStandardMaterial:"physical",MeshPhysicalMaterial:"physical",MeshMatcapMaterial:"matcap",LineBasicMaterial:"basic",LineDashedMaterial:"dashed",PointsMaterial:"points",ShadowMaterial:"shadow",SpriteMaterial:"sprite"};function g(e){return u.add(e),0===e?"uv":`uv${e}`}return{getParameters:function(s,a,c,m,v){const A=m.fog,x=v.geometry,y=s.isMeshStandardMaterial?m.environment:null,b=(s.isMeshStandardMaterial?n:t).get(s.envMap||y),w=b&&b.mapping===Li?b.image.height:null,C=p[s.type];null!==s.precision&&(f=r.getMaxPrecision(s.precision),f!==s.precision&&console.warn("THREE.WebGLProgram.getParameters:",s.precision,"not supported, using",f,"instead."));const M=x.morphAttributes.position||x.morphAttributes.normal||x.morphAttributes.color,E=void 0!==M?M.length:0;let T,S,P,N,B=0;if(void 0!==x.morphAttributes.position&&(B=1),void 0!==x.morphAttributes.normal&&(B=2),void 0!==x.morphAttributes.color&&(B=3),C){const e=mp[C];T=e.vertexShader,S=e.fragmentShader}else T=s.vertexShader,S=s.fragmentShader,l.update(s),P=l.getVertexShaderID(s),N=l.getFragmentShaderID(s);const D=e.getRenderTarget(),I=e.state.buffers.depth.getReversed(),L=!0===v.isInstancedMesh,j=!0===v.isBatchedMesh,O=!!s.map,z=!!s.matcap,R=!!b,k=!!s.aoMap,F=!!s.lightMap,H=!!s.bumpMap,U=!!s.normalMap,X=!!s.displacementMap,G=!!s.emissiveMap,V=!!s.metalnessMap,W=!!s.roughnessMap,Q=s.anisotropy>0,Z=s.clearcoat>0,Y=s.dispersion>0,J=s.iridescence>0,K=s.sheen>0,q=s.transmission>0,_=Q&&!!s.anisotropyMap,$=Z&&!!s.clearcoatMap,ee=Z&&!!s.clearcoatNormalMap,te=Z&&!!s.clearcoatRoughnessMap,ne=J&&!!s.iridescenceMap,ie=J&&!!s.iridescenceThicknessMap,re=K&&!!s.sheenColorMap,se=K&&!!s.sheenRoughnessMap,oe=!!s.specularMap,ae=!!s.specularColorMap,le=!!s.specularIntensityMap,ue=q&&!!s.transmissionMap,ce=q&&!!s.thicknessMap,de=!!s.gradientMap,he=!!s.alphaMap,fe=s.alphaTest>0,pe=!!s.alphaHash,ge=!!s.extensions;let me=0;s.toneMapped&&(null!==D&&!0!==D.isXRRenderTarget||(me=e.toneMapping));const ve={shaderID:C,shaderType:s.type,shaderName:s.name,vertexShader:T,fragmentShader:S,defines:s.defines,customVertexShaderID:P,customFragmentShaderID:N,isRawShaderMaterial:!0===s.isRawShaderMaterial,glslVersion:s.glslVersion,precision:f,batching:j,batchingColor:j&&null!==v._colorsTexture,instancing:L,instancingColor:L&&null!==v.instanceColor,instancingMorph:L&&null!==v.morphTexture,supportsVertexTextures:h,outputColorSpace:null===D?e.outputColorSpace:!0===D.isXRRenderTarget?D.texture.colorSpace:_r,alphaToCoverage:!!s.alphaToCoverage,map:O,matcap:z,envMap:R,envMapMode:R&&b.mapping,envMapCubeUVHeight:w,aoMap:k,lightMap:F,bumpMap:H,normalMap:U,displacementMap:h&&X,emissiveMap:G,normalMapObjectSpace:U&&1===s.normalMapType,normalMapTangentSpace:U&&0===s.normalMapType,metalnessMap:V,roughnessMap:W,anisotropy:Q,anisotropyMap:_,clearcoat:Z,clearcoatMap:$,clearcoatNormalMap:ee,clearcoatRoughnessMap:te,dispersion:Y,iridescence:J,iridescenceMap:ne,iridescenceThicknessMap:ie,sheen:K,sheenColorMap:re,sheenRoughnessMap:se,specularMap:oe,specularColorMap:ae,specularIntensityMap:le,transmission:q,transmissionMap:ue,thicknessMap:ce,gradientMap:de,opaque:!1===s.transparent&&1===s.blending&&!1===s.alphaToCoverage,alphaMap:he,alphaTest:fe,alphaHash:pe,combine:s.combine,mapUv:O&&g(s.map.channel),aoMapUv:k&&g(s.aoMap.channel),lightMapUv:F&&g(s.lightMap.channel),bumpMapUv:H&&g(s.bumpMap.channel),normalMapUv:U&&g(s.normalMap.channel),displacementMapUv:X&&g(s.displacementMap.channel),emissiveMapUv:G&&g(s.emissiveMap.channel),metalnessMapUv:V&&g(s.metalnessMap.channel),roughnessMapUv:W&&g(s.roughnessMap.channel),anisotropyMapUv:_&&g(s.anisotropyMap.channel),clearcoatMapUv:$&&g(s.clearcoatMap.channel),clearcoatNormalMapUv:ee&&g(s.clearcoatNormalMap.channel),clearcoatRoughnessMapUv:te&&g(s.clearcoatRoughnessMap.channel),iridescenceMapUv:ne&&g(s.iridescenceMap.channel),iridescenceThicknessMapUv:ie&&g(s.iridescenceThicknessMap.channel),sheenColorMapUv:re&&g(s.sheenColorMap.channel),sheenRoughnessMapUv:se&&g(s.sheenRoughnessMap.channel),specularMapUv:oe&&g(s.specularMap.channel),specularColorMapUv:ae&&g(s.specularColorMap.channel),specularIntensityMapUv:le&&g(s.specularIntensityMap.channel),transmissionMapUv:ue&&g(s.transmissionMap.channel),thicknessMapUv:ce&&g(s.thicknessMap.channel),alphaMapUv:he&&g(s.alphaMap.channel),vertexTangents:!!x.attributes.tangent&&(U||Q),vertexColors:s.vertexColors,vertexAlphas:!0===s.vertexColors&&!!x.attributes.color&&4===x.attributes.color.itemSize,pointsUvs:!0===v.isPoints&&!!x.attributes.uv&&(O||he),fog:!!A,useFog:!0===s.fog,fogExp2:!!A&&A.isFogExp2,flatShading:!0===s.flatShading&&!1===s.wireframe,sizeAttenuation:!0===s.sizeAttenuation,logarithmicDepthBuffer:d,reversedDepthBuffer:I,skinning:!0===v.isSkinnedMesh,morphTargets:void 0!==x.morphAttributes.position,morphNormals:void 0!==x.morphAttributes.normal,morphColors:void 0!==x.morphAttributes.color,morphTargetsCount:E,morphTextureStride:B,numDirLights:a.directional.length,numPointLights:a.point.length,numSpotLights:a.spot.length,numSpotLightMaps:a.spotLightMap.length,numRectAreaLights:a.rectArea.length,numHemiLights:a.hemi.length,numDirLightShadows:a.directionalShadowMap.length,numPointLightShadows:a.pointShadowMap.length,numSpotLightShadows:a.spotShadowMap.length,numSpotLightShadowsWithMaps:a.numSpotLightShadowsWithMaps,numLightProbes:a.numLightProbes,numClippingPlanes:o.numPlanes,numClipIntersection:o.numIntersection,dithering:s.dithering,shadowMapEnabled:e.shadowMap.enabled&&c.length>0,shadowMapType:e.shadowMap.type,toneMapping:me,decodeVideoTexture:O&&!0===s.map.isVideoTexture&&ks.getTransfer(s.map.colorSpace)===es,decodeVideoTextureEmissive:G&&!0===s.emissiveMap.isVideoTexture&&ks.getTransfer(s.emissiveMap.colorSpace)===es,premultipliedAlpha:s.premultipliedAlpha,doubleSided:2===s.side,flipSided:1===s.side,useDepthPacking:s.depthPacking>=0,depthPacking:s.depthPacking||0,index0AttributeName:s.index0AttributeName,extensionClipCullDistance:ge&&!0===s.extensions.clipCullDistance&&i.has("WEBGL_clip_cull_distance"),extensionMultiDraw:(ge&&!0===s.extensions.multiDraw||j)&&i.has("WEBGL_multi_draw"),rendererExtensionParallelShaderCompile:i.has("KHR_parallel_shader_compile"),customProgramCacheKey:s.customProgramCacheKey()};return ve.vertexUv1s=u.has(1),ve.vertexUv2s=u.has(2),ve.vertexUv3s=u.has(3),u.clear(),ve},getProgramCacheKey:function(t){const n=[];if(t.shaderID?n.push(t.shaderID):(n.push(t.customVertexShaderID),n.push(t.customFragmentShaderID)),void 0!==t.defines)for(const e in t.defines)n.push(e),n.push(t.defines[e]);return!1===t.isRawShaderMaterial&&(!function(e,t){e.push(t.precision),e.push(t.outputColorSpace),e.push(t.envMapMode),e.push(t.envMapCubeUVHeight),e.push(t.mapUv),e.push(t.alphaMapUv),e.push(t.lightMapUv),e.push(t.aoMapUv),e.push(t.bumpMapUv),e.push(t.normalMapUv),e.push(t.displacementMapUv),e.push(t.emissiveMapUv),e.push(t.metalnessMapUv),e.push(t.roughnessMapUv),e.push(t.anisotropyMapUv),e.push(t.clearcoatMapUv),e.push(t.clearcoatNormalMapUv),e.push(t.clearcoatRoughnessMapUv),e.push(t.iridescenceMapUv),e.push(t.iridescenceThicknessMapUv),e.push(t.sheenColorMapUv),e.push(t.sheenRoughnessMapUv),e.push(t.specularMapUv),e.push(t.specularColorMapUv),e.push(t.specularIntensityMapUv),e.push(t.transmissionMapUv),e.push(t.thicknessMapUv),e.push(t.combine),e.push(t.fogExp2),e.push(t.sizeAttenuation),e.push(t.morphTargetsCount),e.push(t.morphAttributeCount),e.push(t.numDirLights),e.push(t.numPointLights),e.push(t.numSpotLights),e.push(t.numSpotLightMaps),e.push(t.numHemiLights),e.push(t.numRectAreaLights),e.push(t.numDirLightShadows),e.push(t.numPointLightShadows),e.push(t.numSpotLightShadows),e.push(t.numSpotLightShadowsWithMaps),e.push(t.numLightProbes),e.push(t.shadowMapType),e.push(t.toneMapping),e.push(t.numClippingPlanes),e.push(t.numClipIntersection),e.push(t.depthPacking)}(n,t),function(e,t){a.disableAll(),t.supportsVertexTextures&&a.enable(0);t.instancing&&a.enable(1);t.instancingColor&&a.enable(2);t.instancingMorph&&a.enable(3);t.matcap&&a.enable(4);t.envMap&&a.enable(5);t.normalMapObjectSpace&&a.enable(6);t.normalMapTangentSpace&&a.enable(7);t.clearcoat&&a.enable(8);t.iridescence&&a.enable(9);t.alphaTest&&a.enable(10);t.vertexColors&&a.enable(11);t.vertexAlphas&&a.enable(12);t.vertexUv1s&&a.enable(13);t.vertexUv2s&&a.enable(14);t.vertexUv3s&&a.enable(15);t.vertexTangents&&a.enable(16);t.anisotropy&&a.enable(17);t.alphaHash&&a.enable(18);t.batching&&a.enable(19);t.dispersion&&a.enable(20);t.batchingColor&&a.enable(21);t.gradientMap&&a.enable(22);e.push(a.mask),a.disableAll(),t.fog&&a.enable(0);t.useFog&&a.enable(1);t.flatShading&&a.enable(2);t.logarithmicDepthBuffer&&a.enable(3);t.reversedDepthBuffer&&a.enable(4);t.skinning&&a.enable(5);t.morphTargets&&a.enable(6);t.morphNormals&&a.enable(7);t.morphColors&&a.enable(8);t.premultipliedAlpha&&a.enable(9);t.shadowMapEnabled&&a.enable(10);t.doubleSided&&a.enable(11);t.flipSided&&a.enable(12);t.useDepthPacking&&a.enable(13);t.dithering&&a.enable(14);t.transmission&&a.enable(15);t.sheen&&a.enable(16);t.opaque&&a.enable(17);t.pointsUvs&&a.enable(18);t.decodeVideoTexture&&a.enable(19);t.decodeVideoTextureEmissive&&a.enable(20);t.alphaToCoverage&&a.enable(21);e.push(a.mask)}(n,t),n.push(e.outputColorSpace)),n.push(t.customProgramCacheKey),n.join()},getUniforms:function(e){const t=p[e.type];let n;if(t){const e=mp[t];n=ll.clone(e.uniforms)}else n=e.uniforms;return n},acquireProgram:function(t,n){let i;for(let e=0,t=c.length;e<t;e++){const t=c[e];if(t.cacheKey===n){i=t,++i.usedTimes;break}}return void 0===i&&(i=new bm(e,n,t,s),c.push(i)),i},releaseProgram:function(e){if(0==--e.usedTimes){const t=c.indexOf(e);c[t]=c[c.length-1],c.pop(),e.destroy()}},releaseShaderCache:function(e){l.remove(e)},programs:c,dispose:function(){l.dispose()}}}function Tm(){let e=new WeakMap;return{has:function(t){return e.has(t)},get:function(t){let n=e.get(t);return void 0===n&&(n={},e.set(t,n)),n},remove:function(t){e.delete(t)},update:function(t,n,i){e.get(t)[n]=i},dispose:function(){e=new WeakMap}}}function Sm(e,t){return e.groupOrder!==t.groupOrder?e.groupOrder-t.groupOrder:e.renderOrder!==t.renderOrder?e.renderOrder-t.renderOrder:e.material.id!==t.material.id?e.material.id-t.material.id:e.z!==t.z?e.z-t.z:e.id-t.id}function Pm(e,t){return e.groupOrder!==t.groupOrder?e.groupOrder-t.groupOrder:e.renderOrder!==t.renderOrder?e.renderOrder-t.renderOrder:e.z!==t.z?t.z-e.z:e.id-t.id}function Nm(){const e=[];let t=0;const n=[],i=[],r=[];function s(n,i,r,s,o,a){let l=e[t];return void 0===l?(l={id:n.id,object:n,geometry:i,material:r,groupOrder:s,renderOrder:n.renderOrder,z:o,group:a},e[t]=l):(l.id=n.id,l.object=n,l.geometry=i,l.material=r,l.groupOrder=s,l.renderOrder=n.renderOrder,l.z=o,l.group=a),t++,l}return{opaque:n,transmissive:i,transparent:r,init:function(){t=0,n.length=0,i.length=0,r.length=0},push:function(e,t,o,a,l,u){const c=s(e,t,o,a,l,u);o.transmission>0?i.push(c):!0===o.transparent?r.push(c):n.push(c)},unshift:function(e,t,o,a,l,u){const c=s(e,t,o,a,l,u);o.transmission>0?i.unshift(c):!0===o.transparent?r.unshift(c):n.unshift(c)},finish:function(){for(let n=t,i=e.length;n<i;n++){const t=e[n];if(null===t.id)break;t.id=null,t.object=null,t.geometry=null,t.material=null,t.group=null}},sort:function(e,t){n.length>1&&n.sort(e||Sm),i.length>1&&i.sort(t||Pm),r.length>1&&r.sort(t||Pm)}}}function Bm(){let e=new WeakMap;return{get:function(t,n){const i=e.get(t);let r;return void 0===i?(r=new Nm,e.set(t,[r])):n>=i.length?(r=new Nm,i.push(r)):r=i[n],r},dispose:function(){e=new WeakMap}}}function Dm(){const e={};return{get:function(t){if(void 0!==e[t.id])return e[t.id];let n;switch(t.type){case"DirectionalLight":n={direction:new Es,color:new ya};break;case"SpotLight":n={position:new Es,direction:new Es,color:new ya,distance:0,coneCos:0,penumbraCos:0,decay:0};break;case"PointLight":n={position:new Es,color:new ya,distance:0,decay:0};break;case"HemisphereLight":n={direction:new Es,skyColor:new ya,groundColor:new ya};break;case"RectAreaLight":n={color:new ya,position:new Es,halfWidth:new Es,halfHeight:new Es}}return e[t.id]=n,n}}}let Im=0;function Lm(e,t){return(t.castShadow?2:0)-(e.castShadow?2:0)+(t.map?1:0)-(e.map?1:0)}function jm(e){const t=new Dm,n=function(){const e={};return{get:function(t){if(void 0!==e[t.id])return e[t.id];let n;switch(t.type){case"DirectionalLight":case"SpotLight":n={shadowIntensity:1,shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new Cs};break;case"PointLight":n={shadowIntensity:1,shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new Cs,shadowCameraNear:1,shadowCameraFar:1e3}}return e[t.id]=n,n}}}(),i={version:0,hash:{directionalLength:-1,pointLength:-1,spotLength:-1,rectAreaLength:-1,hemiLength:-1,numDirectionalShadows:-1,numPointShadows:-1,numSpotShadows:-1,numSpotMaps:-1,numLightProbes:-1},ambient:[0,0,0],probe:[],directional:[],directionalShadow:[],directionalShadowMap:[],directionalShadowMatrix:[],spot:[],spotLightMap:[],spotShadow:[],spotShadowMap:[],spotLightMatrix:[],rectArea:[],rectAreaLTC1:null,rectAreaLTC2:null,point:[],pointShadow:[],pointShadowMap:[],pointShadowMatrix:[],hemi:[],numSpotLightShadowsWithMaps:0,numLightProbes:0};for(let e=0;e<9;e++)i.probe.push(new Es);const r=new Es,s=new Po,o=new Po;return{setup:function(r){let s=0,o=0,a=0;for(let e=0;e<9;e++)i.probe[e].set(0,0,0);let l=0,u=0,c=0,d=0,h=0,f=0,p=0,g=0,m=0,v=0,A=0;r.sort(Lm);for(let e=0,x=r.length;e<x;e++){const x=r[e],y=x.color,b=x.intensity,w=x.distance,C=x.shadow&&x.shadow.map?x.shadow.map.texture:null;if(x.isAmbientLight)s+=y.r*b,o+=y.g*b,a+=y.b*b;else if(x.isLightProbe){for(let e=0;e<9;e++)i.probe[e].addScaledVector(x.sh.coefficients[e],b);A++}else if(x.isDirectionalLight){const e=t.get(x);if(e.color.copy(x.color).multiplyScalar(x.intensity),x.castShadow){const e=x.shadow,t=n.get(x);t.shadowIntensity=e.intensity,t.shadowBias=e.bias,t.shadowNormalBias=e.normalBias,t.shadowRadius=e.radius,t.shadowMapSize=e.mapSize,i.directionalShadow[l]=t,i.directionalShadowMap[l]=C,i.directionalShadowMatrix[l]=x.shadow.matrix,f++}i.directional[l]=e,l++}else if(x.isSpotLight){const e=t.get(x);e.position.setFromMatrixPosition(x.matrixWorld),e.color.copy(y).multiplyScalar(b),e.distance=w,e.coneCos=Math.cos(x.angle),e.penumbraCos=Math.cos(x.angle*(1-x.penumbra)),e.decay=x.decay,i.spot[c]=e;const r=x.shadow;if(x.map&&(i.spotLightMap[m]=x.map,m++,r.updateMatrices(x),x.castShadow&&v++),i.spotLightMatrix[c]=r.matrix,x.castShadow){const e=n.get(x);e.shadowIntensity=r.intensity,e.shadowBias=r.bias,e.shadowNormalBias=r.normalBias,e.shadowRadius=r.radius,e.shadowMapSize=r.mapSize,i.spotShadow[c]=e,i.spotShadowMap[c]=C,g++}c++}else if(x.isRectAreaLight){const e=t.get(x);e.color.copy(y).multiplyScalar(b),e.halfWidth.set(.5*x.width,0,0),e.halfHeight.set(0,.5*x.height,0),i.rectArea[d]=e,d++}else if(x.isPointLight){const e=t.get(x);if(e.color.copy(x.color).multiplyScalar(x.intensity),e.distance=x.distance,e.decay=x.decay,x.castShadow){const e=x.shadow,t=n.get(x);t.shadowIntensity=e.intensity,t.shadowBias=e.bias,t.shadowNormalBias=e.normalBias,t.shadowRadius=e.radius,t.shadowMapSize=e.mapSize,t.shadowCameraNear=e.camera.near,t.shadowCameraFar=e.camera.far,i.pointShadow[u]=t,i.pointShadowMap[u]=C,i.pointShadowMatrix[u]=x.shadow.matrix,p++}i.point[u]=e,u++}else if(x.isHemisphereLight){const e=t.get(x);e.skyColor.copy(x.color).multiplyScalar(b),e.groundColor.copy(x.groundColor).multiplyScalar(b),i.hemi[h]=e,h++}}d>0&&(!0===e.has("OES_texture_float_linear")?(i.rectAreaLTC1=gp.LTC_FLOAT_1,i.rectAreaLTC2=gp.LTC_FLOAT_2):(i.rectAreaLTC1=gp.LTC_HALF_1,i.rectAreaLTC2=gp.LTC_HALF_2)),i.ambient[0]=s,i.ambient[1]=o,i.ambient[2]=a;const x=i.hash;x.directionalLength===l&&x.pointLength===u&&x.spotLength===c&&x.rectAreaLength===d&&x.hemiLength===h&&x.numDirectionalShadows===f&&x.numPointShadows===p&&x.numSpotShadows===g&&x.numSpotMaps===m&&x.numLightProbes===A||(i.directional.length=l,i.spot.length=c,i.rectArea.length=d,i.point.length=u,i.hemi.length=h,i.directionalShadow.length=f,i.directionalShadowMap.length=f,i.pointShadow.length=p,i.pointShadowMap.length=p,i.spotShadow.length=g,i.spotShadowMap.length=g,i.directionalShadowMatrix.length=f,i.pointShadowMatrix.length=p,i.spotLightMatrix.length=g+m-v,i.spotLightMap.length=m,i.numSpotLightShadowsWithMaps=v,i.numLightProbes=A,x.directionalLength=l,x.pointLength=u,x.spotLength=c,x.rectAreaLength=d,x.hemiLength=h,x.numDirectionalShadows=f,x.numPointShadows=p,x.numSpotShadows=g,x.numSpotMaps=m,x.numLightProbes=A,i.version=Im++)},setupView:function(e,t){let n=0,a=0,l=0,u=0,c=0;const d=t.matrixWorldInverse;for(let t=0,h=e.length;t<h;t++){const h=e[t];if(h.isDirectionalLight){const e=i.directional[n];e.direction.setFromMatrixPosition(h.matrixWorld),r.setFromMatrixPosition(h.target.matrixWorld),e.direction.sub(r),e.direction.transformDirection(d),n++}else if(h.isSpotLight){const e=i.spot[l];e.position.setFromMatrixPosition(h.matrixWorld),e.position.applyMatrix4(d),e.direction.setFromMatrixPosition(h.matrixWorld),r.setFromMatrixPosition(h.target.matrixWorld),e.direction.sub(r),e.direction.transformDirection(d),l++}else if(h.isRectAreaLight){const e=i.rectArea[u];e.position.setFromMatrixPosition(h.matrixWorld),e.position.applyMatrix4(d),o.identity(),s.copy(h.matrixWorld),s.premultiply(d),o.extractRotation(s),e.halfWidth.set(.5*h.width,0,0),e.halfHeight.set(0,.5*h.height,0),e.halfWidth.applyMatrix4(o),e.halfHeight.applyMatrix4(o),u++}else if(h.isPointLight){const e=i.point[a];e.position.setFromMatrixPosition(h.matrixWorld),e.position.applyMatrix4(d),a++}else if(h.isHemisphereLight){const e=i.hemi[c];e.direction.setFromMatrixPosition(h.matrixWorld),e.direction.transformDirection(d),c++}}},state:i}}function Om(e){const t=new jm(e),n=[],i=[];const r={lightsArray:n,shadowsArray:i,camera:null,lights:t,transmissionRenderTarget:{}};return{init:function(e){r.camera=e,n.length=0,i.length=0},state:r,setupLights:function(){t.setup(n)},setupLightsView:function(e){t.setupView(n,e)},pushLight:function(e){n.push(e)},pushShadow:function(e){i.push(e)}}}function zm(e){let t=new WeakMap;return{get:function(n,i=0){const r=t.get(n);let s;return void 0===r?(s=new Om(e),t.set(n,[s])):i>=r.length?(s=new Om(e),r.push(s)):s=r[i],s},dispose:function(){t=new WeakMap}}}function Rm(e,t,n){let i=new zl;const r=new Cs,s=new Cs,o=new Js,a=new Nu({depthPacking:3201}),l=new Bu,u={},c=n.maxTextureSize,d={0:1,1:0,2:2},h=new ul({defines:{VSM_SAMPLES:8},uniforms:{shadow_pass:{value:null},resolution:{value:new Cs},radius:{value:4}},vertexShader:"void main() {\n\tgl_Position = vec4( position, 1.0 );\n}",fragmentShader:"uniform sampler2D shadow_pass;\nuniform vec2 resolution;\nuniform float radius;\n#include <packing>\nvoid main() {\n\tconst float samples = float( VSM_SAMPLES );\n\tfloat mean = 0.0;\n\tfloat squared_mean = 0.0;\n\tfloat uvStride = samples <= 1.0 ? 0.0 : 2.0 / ( samples - 1.0 );\n\tfloat uvStart = samples <= 1.0 ? 0.0 : - 1.0;\n\tfor ( float i = 0.0; i < samples; i ++ ) {\n\t\tfloat uvOffset = uvStart + i * uvStride;\n\t\t#ifdef HORIZONTAL_PASS\n\t\t\tvec2 distribution = unpackRGBATo2Half( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( uvOffset, 0.0 ) * radius ) / resolution ) );\n\t\t\tmean += distribution.x;\n\t\t\tsquared_mean += distribution.y * distribution.y + distribution.x * distribution.x;\n\t\t#else\n\t\t\tfloat depth = unpackRGBAToDepth( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( 0.0, uvOffset ) * radius ) / resolution ) );\n\t\t\tmean += depth;\n\t\t\tsquared_mean += depth * depth;\n\t\t#endif\n\t}\n\tmean = mean / samples;\n\tsquared_mean = squared_mean / samples;\n\tfloat std_dev = sqrt( squared_mean - mean * mean );\n\tgl_FragColor = pack2HalfToRGBA( vec2( mean, std_dev ) );\n}"}),f=h.clone();f.defines.HORIZONTAL_PASS=1;const p=new Va;p.setAttribute("position",new Ia(new Float32Array([-1,-1,.5,3,-1,.5,-1,3,.5]),3));const g=new nl(p,h),m=this;this.enabled=!1,this.autoUpdate=!0,this.needsUpdate=!1,this.type=1;let v=this.type;function A(n,i){const s=t.update(g);h.defines.VSM_SAMPLES!==n.blurSamples&&(h.defines.VSM_SAMPLES=n.blurSamples,f.defines.VSM_SAMPLES=n.blurSamples,h.needsUpdate=!0,f.needsUpdate=!0),null===n.mapPass&&(n.mapPass=new qs(r.x,r.y)),h.uniforms.shadow_pass.value=n.map.texture,h.uniforms.resolution.value=n.mapSize,h.uniforms.radius.value=n.radius,e.setRenderTarget(n.mapPass),e.clear(),e.renderBufferDirect(i,null,s,h,g,null),f.uniforms.shadow_pass.value=n.mapPass.texture,f.uniforms.resolution.value=n.mapSize,f.uniforms.radius.value=n.radius,e.setRenderTarget(n.map),e.clear(),e.renderBufferDirect(i,null,s,f,g,null)}function x(t,n,i,r){let s=null;const o=!0===i.isPointLight?t.customDistanceMaterial:t.customDepthMaterial;if(void 0!==o)s=o;else if(s=!0===i.isPointLight?l:a,e.localClippingEnabled&&!0===n.clipShadows&&Array.isArray(n.clippingPlanes)&&0!==n.clippingPlanes.length||n.displacementMap&&0!==n.displacementScale||n.alphaMap&&n.alphaTest>0||n.map&&n.alphaTest>0||!0===n.alphaToCoverage){const e=s.uuid,t=n.uuid;let i=u[e];void 0===i&&(i={},u[e]=i);let r=i[t];void 0===r&&(r=s.clone(),i[t]=r,n.addEventListener("dispose",b)),s=r}if(s.visible=n.visible,s.wireframe=n.wireframe,s.side=3===r?null!==n.shadowSide?n.shadowSide:n.side:null!==n.shadowSide?n.shadowSide:d[n.side],s.alphaMap=n.alphaMap,s.alphaTest=!0===n.alphaToCoverage?.5:n.alphaTest,s.map=n.map,s.clipShadows=n.clipShadows,s.clippingPlanes=n.clippingPlanes,s.clipIntersection=n.clipIntersection,s.displacementMap=n.displacementMap,s.displacementScale=n.displacementScale,s.displacementBias=n.displacementBias,s.wireframeLinewidth=n.wireframeLinewidth,s.linewidth=n.linewidth,!0===i.isPointLight&&!0===s.isMeshDistanceMaterial){e.properties.get(s).light=i}return s}function y(n,r,s,o,a){if(!1===n.visible)return;if(n.layers.test(r.layers)&&(n.isMesh||n.isLine||n.isPoints)&&(n.castShadow||n.receiveShadow&&3===a)&&(!n.frustumCulled||i.intersectsObject(n))){n.modelViewMatrix.multiplyMatrices(s.matrixWorldInverse,n.matrixWorld);const i=t.update(n),l=n.material;if(Array.isArray(l)){const t=i.groups;for(let u=0,c=t.length;u<c;u++){const c=t[u],d=l[c.materialIndex];if(d&&d.visible){const t=x(n,d,o,a);n.onBeforeShadow(e,n,r,s,i,t,c),e.renderBufferDirect(s,null,i,t,n,c),n.onAfterShadow(e,n,r,s,i,t,c)}}}else if(l.visible){const t=x(n,l,o,a);n.onBeforeShadow(e,n,r,s,i,t,null),e.renderBufferDirect(s,null,i,t,n,null),n.onAfterShadow(e,n,r,s,i,t,null)}}const l=n.children;for(let e=0,t=l.length;e<t;e++)y(l[e],r,s,o,a)}function b(e){e.target.removeEventListener("dispose",b);for(const t in u){const n=u[t],i=e.target.uuid;if(i in n){n[i].dispose(),delete n[i]}}}this.render=function(t,n,a){if(!1===m.enabled)return;if(!1===m.autoUpdate&&!1===m.needsUpdate)return;if(0===t.length)return;const l=e.getRenderTarget(),u=e.getActiveCubeFace(),d=e.getActiveMipmapLevel(),h=e.state;h.setBlending(0),!0===h.buffers.depth.getReversed()?h.buffers.color.setClear(0,0,0,0):h.buffers.color.setClear(1,1,1,1),h.buffers.depth.setTest(!0),h.setScissorTest(!1);const f=3!==v&&3===this.type,p=3===v&&3!==this.type;for(let l=0,u=t.length;l<u;l++){const u=t[l],d=u.shadow;if(void 0===d){console.warn("THREE.WebGLShadowMap:",u,"has no shadow.");continue}if(!1===d.autoUpdate&&!1===d.needsUpdate)continue;r.copy(d.mapSize);const g=d.getFrameExtents();if(r.multiply(g),s.copy(d.mapSize),(r.x>c||r.y>c)&&(r.x>c&&(s.x=Math.floor(c/g.x),r.x=s.x*g.x,d.mapSize.x=s.x),r.y>c&&(s.y=Math.floor(c/g.y),r.y=s.y*g.y,d.mapSize.y=s.y)),null===d.map||!0===f||!0===p){const e=3!==this.type?{minFilter:Ri,magFilter:Ri}:{};null!==d.map&&d.map.dispose(),d.map=new qs(r.x,r.y,e),d.map.texture.name=u.name+".shadowMap",d.camera.updateProjectionMatrix()}e.setRenderTarget(d.map),e.clear();const m=d.getViewportCount();for(let e=0;e<m;e++){const 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u=D(t,o),c=o.source;n.bindTexture(l,t.__webglTexture,e.TEXTURE0+a);const d=i.get(c);if(c.version!==d.__version||!0===u){n.activeTexture(e.TEXTURE0+a);const t=ks.getPrimaries(ks.workingColorSpace),i=o.colorSpace===Kr?null:ks.getPrimaries(o.colorSpace),h=o.colorSpace===Kr||t===i?e.NONE:e.BROWSER_DEFAULT_WEBGL;e.pixelStorei(e.UNPACK_FLIP_Y_WEBGL,o.flipY),e.pixelStorei(e.UNPACK_PREMULTIPLY_ALPHA_WEBGL,o.premultiplyAlpha),e.pixelStorei(e.UNPACK_ALIGNMENT,o.unpackAlignment),e.pixelStorei(e.UNPACK_COLORSPACE_CONVERSION_WEBGL,h);let f=g(o.image,!1,r.maxTextureSize);f=X(o,f);const p=s.convert(o.format,o.colorSpace),A=s.convert(o.type);let w,C=x(o.internalFormat,p,A,o.colorSpace,o.isVideoTexture);B(l,o);const M=o.mipmaps,E=!0!==o.isVideoTexture,T=void 0===d.__version||!0===u,S=c.dataReady,P=b(o,f);if(o.isDepthTexture)C=y(o.format===or,o.type),T&&(E?n.texStorage2D(e.TEXTURE_2D,1,C,f.width,f.height):n.texImage2D(e.TEXTURE_2D,0,C,f.width,f.height,0,p,A,null));else if(o.isDataTexture)if(M.length>0){E&&T&&n.texStorage2D(e.TEXTURE_2D,P,C,M[0].width,M[0].height);for(let t=0,i=M.length;t<i;t++)w=M[t],E?S&&n.texSubImage2D(e.TEXTURE_2D,t,0,0,w.width,w.height,p,A,w.data):n.texImage2D(e.TEXTURE_2D,t,C,w.width,w.height,0,p,A,w.data);o.generateMipmaps=!1}else E?(T&&n.texStorage2D(e.TEXTURE_2D,P,C,f.width,f.height),S&&function(t,i,r,s){const o=t.updateRanges;if(0===o.length)n.texSubImage2D(e.TEXTURE_2D,0,0,0,i.width,i.height,r,s,i.data);else{o.sort(((e,t)=>e.start-t.start));let a=0;for(let e=1;e<o.length;e++){const t=o[a],n=o[e],r=t.start+t.count,s=I(n.start,i.width,4),l=I(t.start,i.width,4);n.start<=r+1&&s===l&&I(n.start+n.count-1,i.width,4)===s?t.count=Math.max(t.count,n.start+n.count-t.start):(++a,o[a]=n)}o.length=a+1;const l=e.getParameter(e.UNPACK_ROW_LENGTH),u=e.getParameter(e.UNPACK_SKIP_PIXELS),c=e.getParameter(e.UNPACK_SKIP_ROWS);e.pixelStorei(e.UNPACK_ROW_LENGTH,i.width);for(let t=0,a=o.length;t<a;t++){const a=o[t],l=Math.floor(a.start/4),u=Math.ceil(a.count/4),c=l%i.width,d=Math.floor(l/i.width),h=u,f=1;e.pixelStorei(e.UNPACK_SKIP_PIXELS,c),e.pixelStorei(e.UNPACK_SKIP_ROWS,d),n.texSubImage2D(e.TEXTURE_2D,0,c,d,h,f,r,s,i.data)}t.clearUpdateRanges(),e.pixelStorei(e.UNPACK_ROW_LENGTH,l),e.pixelStorei(e.UNPACK_SKIP_PIXELS,u),e.pixelStorei(e.UNPACK_SKIP_ROWS,c)}}(o,f,p,A)):n.texImage2D(e.TEXTURE_2D,0,C,f.width,f.height,0,p,A,f.data);else if(o.isCompressedTexture)if(o.isCompressedArrayTexture){E&&T&&n.texStorage3D(e.TEXTURE_2D_ARRAY,P,C,M[0].width,M[0].height,f.depth);for(let t=0,i=M.length;t<i;t++)if(w=M[t],o.format!==rr)if(null!==p)if(E){if(S)if(o.layerUpdates.size>0){const i=zc(w.width,w.height,o.format,o.type);for(const r of o.layerUpdates){const s=w.data.subarray(r*i/w.data.BYTES_PER_ELEMENT,(r+1)*i/w.data.BYTES_PER_ELEMENT);n.compressedTexSubImage3D(e.TEXTURE_2D_ARRAY,t,0,0,r,w.width,w.height,1,p,s)}o.clearLayerUpdates()}else n.compressedTexSubImage3D(e.TEXTURE_2D_ARRAY,t,0,0,0,w.width,w.height,f.depth,p,w.data)}else n.compressedTexImage3D(e.TEXTURE_2D_ARRAY,t,C,w.width,w.height,f.depth,0,w.data,0,0);else console.warn("THREE.WebGLRenderer: Attempt to load unsupported compressed texture format in .uploadTexture()");else E?S&&n.texSubImage3D(e.TEXTURE_2D_ARRAY,t,0,0,0,w.width,w.height,f.depth,p,A,w.data):n.texImage3D(e.TEXTURE_2D_ARRAY,t,C,w.width,w.height,f.depth,0,p,A,w.data)}else{E&&T&&n.texStorage2D(e.TEXTURE_2D,P,C,M[0].width,M[0].height);for(let t=0,i=M.length;t<i;t++)w=M[t],o.format!==rr?null!==p?E?S&&n.compressedTexSubImage2D(e.TEXTURE_2D,t,0,0,w.width,w.height,p,w.data):n.compressedTexImage2D(e.TEXTURE_2D,t,C,w.width,w.height,0,w.data):console.warn("THREE.WebGLRenderer: Attempt to load unsupported compressed texture format in .uploadTexture()"):E?S&&n.texSubImage2D(e.TEXTURE_2D,t,0,0,w.width,w.height,p,A,w.data):n.texImage2D(e.TEXTURE_2D,t,C,w.width,w.height,0,p,A,w.data)}else if(o.isDataArrayTexture)if(E){if(T&&n.texStorage3D(e.TEXTURE_2D_ARRAY,P,C,f.width,f.height,f.depth),S)if(o.layerUpdates.size>0){const t=zc(f.width,f.height,o.format,o.type);for(const i of o.layerUpdates){const r=f.data.subarray(i*t/f.data.BYTES_PER_ELEMENT,(i+1)*t/f.data.BYTES_PER_ELEMENT);n.texSubImage3D(e.TEXTURE_2D_ARRAY,0,0,0,i,f.width,f.height,1,p,A,r)}o.clearLayerUpdates()}else n.texSubImage3D(e.TEXTURE_2D_ARRAY,0,0,0,0,f.width,f.height,f.depth,p,A,f.data)}else n.texImage3D(e.TEXTURE_2D_ARRAY,0,C,f.width,f.height,f.depth,0,p,A,f.data);else if(o.isData3DTexture)E?(T&&n.texStorage3D(e.TEXTURE_3D,P,C,f.width,f.height,f.depth),S&&n.texSubImage3D(e.TEXTURE_3D,0,0,0,0,f.width,f.height,f.depth,p,A,f.data)):n.texImage3D(e.TEXTURE_3D,0,C,f.width,f.height,f.depth,0,p,A,f.data);else if(o.isFramebufferTexture){if(T)if(E)n.texStorage2D(e.TEXTURE_2D,P,C,f.width,f.height);else{let t=f.width,i=f.height;for(let r=0;r<P;r++)n.texImage2D(e.TEXTURE_2D,r,C,t,i,0,p,A,null),t>>=1,i>>=1}}else if(M.length>0){if(E&&T){const t=G(M[0]);n.texStorage2D(e.TEXTURE_2D,P,C,t.width,t.height)}for(let t=0,i=M.length;t<i;t++)w=M[t],E?S&&n.texSubImage2D(e.TEXTURE_2D,t,0,0,p,A,w):n.texImage2D(e.TEXTURE_2D,t,C,p,A,w);o.generateMipmaps=!1}else if(E){if(T){const t=G(f);n.texStorage2D(e.TEXTURE_2D,P,C,t.width,t.height)}S&&n.texSubImage2D(e.TEXTURE_2D,0,0,0,p,A,f)}else n.texImage2D(e.TEXTURE_2D,0,C,p,A,f);m(o)&&v(l),d.__version=c.version,o.onUpdate&&o.onUpdate(o)}t.__version=o.version}function j(t,r,o,l,u,c){const d=s.convert(o.format,o.colorSpace),h=s.convert(o.type),f=x(o.internalFormat,d,h,o.colorSpace),p=i.get(r),g=i.get(o);if(g.__renderTarget=r,!p.__hasExternalTextures){const t=Math.max(1,r.width>>c),i=Math.max(1,r.height>>c);u===e.TEXTURE_3D||u===e.TEXTURE_2D_ARRAY?n.texImage3D(u,c,f,t,i,r.depth,0,d,h,null):n.texImage2D(u,c,f,t,i,0,d,h,null)}n.bindFramebuffer(e.FRAMEBUFFER,t),U(r)?a.framebufferTexture2DMultisampleEXT(e.FRAMEBUFFER,l,u,g.__webglTexture,0,H(r)):(u===e.TEXTURE_2D||u>=e.TEXTURE_CUBE_MAP_POSITIVE_X&&u<=e.TEXTURE_CUBE_MAP_NEGATIVE_Z)&&e.framebufferTexture2D(e.FRAMEBUFFER,l,u,g.__webglTexture,c),n.bindFramebuffer(e.FRAMEBUFFER,null)}function O(t,n,i){if(e.bindRenderbuffer(e.RENDERBUFFER,t),n.depthBuffer){const r=n.depthTexture,s=r&&r.isDepthTexture?r.type:null,o=y(n.stencilBuffer,s),l=n.stencilBuffer?e.DEPTH_STENCIL_ATTACHMENT:e.DEPTH_ATTACHMENT,u=H(n);U(n)?a.renderbufferStorageMultisampleEXT(e.RENDERBUFFER,u,o,n.width,n.height):i?e.renderbufferStorageMultisample(e.RENDERBUFFER,u,o,n.width,n.height):e.renderbufferStorage(e.RENDERBUFFER,o,n.width,n.height),e.framebufferRenderbuffer(e.FRAMEBUFFER,l,e.RENDERBUFFER,t)}else{const t=n.textures;for(let r=0;r<t.length;r++){const o=t[r],l=s.convert(o.format,o.colorSpace),u=s.convert(o.type),c=x(o.internalFormat,l,u,o.colorSpace),d=H(n);i&&!1===U(n)?e.renderbufferStorageMultisample(e.RENDERBUFFER,d,c,n.width,n.height):U(n)?a.renderbufferStorageMultisampleEXT(e.RENDERBUFFER,d,c,n.width,n.height):e.renderbufferStorage(e.RENDERBUFFER,c,n.width,n.height)}}e.bindRenderbuffer(e.RENDERBUFFER,null)}function z(t,r){if(r&&r.isWebGLCubeRenderTarget)throw new Error("Depth Texture with cube render targets is not supported");if(n.bindFramebuffer(e.FRAMEBUFFER,t),!r.depthTexture||!r.depthTexture.isDepthTexture)throw new Error("renderTarget.depthTexture must be an instance of THREE.DepthTexture");const s=i.get(r.depthTexture);s.__renderTarget=r,s.__webglTexture&&r.depthTexture.image.width===r.width&&r.depthTexture.image.height===r.height||(r.depthTexture.image.width=r.width,r.depthTexture.image.height=r.height,r.depthTexture.needsUpdate=!0),T(r.depthTexture,0);const o=s.__webglTexture,l=H(r);if(r.depthTexture.format===sr)U(r)?a.framebufferTexture2DMultisampleEXT(e.FRAMEBUFFER,e.DEPTH_ATTACHMENT,e.TEXTURE_2D,o,0,l):e.framebufferTexture2D(e.FRAMEBUFFER,e.DEPTH_ATTACHMENT,e.TEXTURE_2D,o,0);else{if(r.depthTexture.format!==or)throw new Error("Unknown depthTexture format");U(r)?a.framebufferTexture2DMultisampleEXT(e.FRAMEBUFFER,e.DEPTH_STENCIL_ATTACHMENT,e.TEXTURE_2D,o,0,l):e.framebufferTexture2D(e.FRAMEBUFFER,e.DEPTH_STENCIL_ATTACHMENT,e.TEXTURE_2D,o,0)}}function R(t){const r=i.get(t),s=!0===t.isWebGLCubeRenderTarget;if(r.__boundDepthTexture!==t.depthTexture){const e=t.depthTexture;if(r.__depthDisposeCallback&&r.__depthDisposeCallback(),e){const t=()=>{delete r.__boundDepthTexture,delete r.__depthDisposeCallback,e.removeEventListener("dispose",t)};e.addEventListener("dispose",t),r.__depthDisposeCallback=t}r.__boundDepthTexture=e}if(t.depthTexture&&!r.__autoAllocateDepthBuffer){if(s)throw new Error("target.depthTexture not supported in Cube render 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n=t.stencilBuffer?e.DEPTH_STENCIL_ATTACHMENT:e.DEPTH_ATTACHMENT,i=r.__webglDepthbuffer;e.bindRenderbuffer(e.RENDERBUFFER,i),e.framebufferRenderbuffer(e.FRAMEBUFFER,n,e.RENDERBUFFER,i)}}n.bindFramebuffer(e.FRAMEBUFFER,null)}const k=[],F=[];function H(e){return Math.min(r.maxSamples,e.samples)}function U(e){const n=i.get(e);return e.samples>0&&!0===t.has("WEBGL_multisampled_render_to_texture")&&!1!==n.__useRenderToTexture}function X(e,t){const n=e.colorSpace,i=e.format,r=e.type;return!0===e.isCompressedTexture||!0===e.isVideoTexture||n!==_r&&n!==Kr&&(ks.getTransfer(n)===es?i===rr&&r===Gi||console.warn("THREE.WebGLTextures: sRGB encoded textures have to use RGBAFormat and UnsignedByteType."):console.error("THREE.WebGLTextures: Unsupported texture color space:",n)),t}function G(e){return"undefined"!=typeof HTMLImageElement&&e instanceof HTMLImageElement?(u.width=e.naturalWidth||e.width,u.height=e.naturalHeight||e.height):"undefined"!=typeof VideoFrame&&e instanceof VideoFrame?(u.width=e.displayWidth,u.height=e.displayHeight):(u.width=e.width,u.height=e.height),u}this.allocateTextureUnit=function(){const e=E;return e>=r.maxTextures&&console.warn("THREE.WebGLTextures: Trying to use "+e+" texture units while this GPU supports only "+r.maxTextures),E+=1,e},this.resetTextureUnits=function(){E=0},this.setTexture2D=T,this.setTexture2DArray=function(t,r){const s=i.get(t);!1===t.isRenderTargetTexture&&t.version>0&&s.__version!==t.version?L(s,t,r):n.bindTexture(e.TEXTURE_2D_ARRAY,s.__webglTexture,e.TEXTURE0+r)},this.setTexture3D=function(t,r){const s=i.get(t);!1===t.isRenderTargetTexture&&t.version>0&&s.__version!==t.version?L(s,t,r):n.bindTexture(e.TEXTURE_3D,s.__webglTexture,e.TEXTURE0+r)},this.setTextureCube=function(t,o){const a=i.get(t);t.version>0&&a.__version!==t.version?function(t,o,a){if(6!==o.image.length)return;const l=D(t,o),u=o.source;n.bindTexture(e.TEXTURE_CUBE_MAP,t.__webglTexture,e.TEXTURE0+a);const c=i.get(u);if(u.version!==c.__version||!0===l){n.activeTexture(e.TEXTURE0+a);const t=ks.getPrimaries(ks.workingColorSpace),i=o.colorSpace===Kr?null:ks.getPrimaries(o.colorSpace),d=o.colorSpace===Kr||t===i?e.NONE:e.BROWSER_DEFAULT_WEBGL;e.pixelStorei(e.UNPACK_FLIP_Y_WEBGL,o.flipY),e.pixelStorei(e.UNPACK_PREMULTIPLY_ALPHA_WEBGL,o.premultiplyAlpha),e.pixelStorei(e.UNPACK_ALIGNMENT,o.unpackAlignment),e.pixelStorei(e.UNPACK_COLORSPACE_CONVERSION_WEBGL,d);const h=o.isCompressedTexture||o.image[0].isCompressedTexture,f=o.image[0]&&o.image[0].isDataTexture,p=[];for(let e=0;e<6;e++)p[e]=h||f?f?o.image[e].image:o.image[e]:g(o.image[e],!0,r.maxCubemapSize),p[e]=X(o,p[e]);const A=p[0],y=s.convert(o.format,o.colorSpace),w=s.convert(o.type),C=x(o.internalFormat,y,w,o.colorSpace),M=!0!==o.isVideoTexture,E=void 0===c.__version||!0===l,T=u.dataReady;let S,P=b(o,A);if(B(e.TEXTURE_CUBE_MAP,o),h){M&&E&&n.texStorage2D(e.TEXTURE_CUBE_MAP,P,C,A.width,A.height);for(let t=0;t<6;t++){S=p[t].mipmaps;for(let i=0;i<S.length;i++){const r=S[i];o.format!==rr?null!==y?M?T&&n.compressedTexSubImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,i,0,0,r.width,r.height,y,r.data):n.compressedTexImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,i,C,r.width,r.height,0,r.data):console.warn("THREE.WebGLRenderer: Attempt to load unsupported compressed texture format in .setTextureCube()"):M?T&&n.texSubImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,i,0,0,r.width,r.height,y,w,r.data):n.texImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,i,C,r.width,r.height,0,y,w,r.data)}}}else{if(S=o.mipmaps,M&&E){S.length>0&&P++;const t=G(p[0]);n.texStorage2D(e.TEXTURE_CUBE_MAP,P,C,t.width,t.height)}for(let t=0;t<6;t++)if(f){M?T&&n.texSubImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,0,0,0,p[t].width,p[t].height,y,w,p[t].data):n.texImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,0,C,p[t].width,p[t].height,0,y,w,p[t].data);for(let i=0;i<S.length;i++){const r=S[i].image[t].image;M?T&&n.texSubImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,i+1,0,0,r.width,r.height,y,w,r.data):n.texImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,i+1,C,r.width,r.height,0,y,w,r.data)}}else{M?T&&n.texSubImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,0,0,0,y,w,p[t]):n.texImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,0,C,y,w,p[t]);for(let i=0;i<S.length;i++){const r=S[i];M?T&&n.texSubImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,i+1,0,0,y,w,r.image[t]):n.texImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,i+1,C,y,w,r.image[t])}}}m(o)&&v(e.TEXTURE_CUBE_MAP),c.__version=u.version,o.onUpdate&&o.onUpdate(o)}t.__version=o.version}(a,t,o):n.bindTexture(e.TEXTURE_CUBE_MAP,a.__webglTexture,e.TEXTURE0+o)},this.rebindTextures=function(t,n,r){const s=i.get(t);void 0!==n&&j(s.__webglFramebuffer,t,t.texture,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,0),void 0!==r&&R(t)},this.setupRenderTarget=function(t){const r=t.texture,a=i.get(t),l=i.get(r);t.addEventListener("dispose",C);const u=t.textures,c=!0===t.isWebGLCubeRenderTarget,d=u.length>1;if(d||(void 0===l.__webglTexture&&(l.__webglTexture=e.createTexture()),l.__version=r.version,o.memory.textures++),c){a.__webglFramebuffer=[];for(let t=0;t<6;t++)if(r.mipmaps&&r.mipmaps.length>0){a.__webglFramebuffer[t]=[];for(let n=0;n<r.mipmaps.length;n++)a.__webglFramebuffer[t][n]=e.createFramebuffer()}else a.__webglFramebuffer[t]=e.createFramebuffer()}else{if(r.mipmaps&&r.mipmaps.length>0){a.__webglFramebuffer=[];for(let t=0;t<r.mipmaps.length;t++)a.__webglFramebuffer[t]=e.createFramebuffer()}else a.__webglFramebuffer=e.createFramebuffer();if(d)for(let t=0,n=u.length;t<n;t++){const n=i.get(u[t]);void 0===n.__webglTexture&&(n.__webglTexture=e.createTexture(),o.memory.textures++)}if(t.samples>0&&!1===U(t)){a.__webglMultisampledFramebuffer=e.createFramebuffer(),a.__webglColorRenderbuffer=[],n.bindFramebuffer(e.FRAMEBUFFER,a.__webglMultisampledFramebuffer);for(let n=0;n<u.length;n++){const i=u[n];a.__webglColorRenderbuffer[n]=e.createRenderbuffer(),e.bindRenderbuffer(e.RENDERBUFFER,a.__webglColorRenderbuffer[n]);const r=s.convert(i.format,i.colorSpace),o=s.convert(i.type),l=x(i.internalFormat,r,o,i.colorSpace,!0===t.isXRRenderTarget),c=H(t);e.renderbufferStorageMultisample(e.RENDERBUFFER,c,l,t.width,t.height),e.framebufferRenderbuffer(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0+n,e.RENDERBUFFER,a.__webglColorRenderbuffer[n])}e.bindRenderbuffer(e.RENDERBUFFER,null),t.depthBuffer&&(a.__webglDepthRenderbuffer=e.createRenderbuffer(),O(a.__webglDepthRenderbuffer,t,!0)),n.bindFramebuffer(e.FRAMEBUFFER,null)}}if(c){n.bindTexture(e.TEXTURE_CUBE_MAP,l.__webglTexture),B(e.TEXTURE_CUBE_MAP,r);for(let n=0;n<6;n++)if(r.mipmaps&&r.mipmaps.length>0)for(let i=0;i<r.mipmaps.length;i++)j(a.__webglFramebuffer[n][i],t,r,e.COLOR_ATTACHMENT0,e.TEXTURE_CUBE_MAP_POSITIVE_X+n,i);else j(a.__webglFramebuffer[n],t,r,e.COLOR_ATTACHMENT0,e.TEXTURE_CUBE_MAP_POSITIVE_X+n,0);m(r)&&v(e.TEXTURE_CUBE_MAP),n.unbindTexture()}else if(d){for(let r=0,s=u.length;r<s;r++){const s=u[r],o=i.get(s);let l=e.TEXTURE_2D;(t.isWebGL3DRenderTarget||t.isWebGLArrayRenderTarget)&&(l=t.isWebGL3DRenderTarget?e.TEXTURE_3D:e.TEXTURE_2D_ARRAY),n.bindTexture(l,o.__webglTexture),B(l,s),j(a.__webglFramebuffer,t,s,e.COLOR_ATTACHMENT0+r,l,0),m(s)&&v(l)}n.unbindTexture()}else{let i=e.TEXTURE_2D;if((t.isWebGL3DRenderTarget||t.isWebGLArrayRenderTarget)&&(i=t.isWebGL3DRenderTarget?e.TEXTURE_3D:e.TEXTURE_2D_ARRAY),n.bindTexture(i,l.__webglTexture),B(i,r),r.mipmaps&&r.mipmaps.length>0)for(let n=0;n<r.mipmaps.length;n++)j(a.__webglFramebuffer[n],t,r,e.COLOR_ATTACHMENT0,i,n);else j(a.__webglFramebuffer,t,r,e.COLOR_ATTACHMENT0,i,0);m(r)&&v(i),n.unbindTexture()}t.depthBuffer&&R(t)},this.updateRenderTargetMipmap=function(e){const t=e.textures;for(let r=0,s=t.length;r<s;r++){const s=t[r];if(m(s)){const t=A(e),r=i.get(s).__webglTexture;n.bindTexture(t,r),v(t),n.unbindTexture()}}},this.updateMultisampleRenderTarget=function(t){if(t.samples>0)if(!1===U(t)){const r=t.textures,s=t.width,o=t.height;let a=e.COLOR_BUFFER_BIT;const u=t.stencilBuffer?e.DEPTH_STENCIL_ATTACHMENT:e.DEPTH_ATTACHMENT,c=i.get(t),d=r.length>1;if(d)for(let t=0;t<r.length;t++)n.bindFramebuffer(e.FRAMEBUFFER,c.__webglMultisampledFramebuffer),e.framebufferRenderbuffer(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0+t,e.RENDERBUFFER,null),n.bindFramebuffer(e.FRAMEBUFFER,c.__webglFramebuffer),e.framebufferTexture2D(e.DRAW_FRAMEBUFFER,e.COLOR_ATTACHMENT0+t,e.TEXTURE_2D,null,0);n.bindFramebuffer(e.READ_FRAMEBUFFER,c.__webglMultisampledFramebuffer);const h=t.texture.mipmaps;h&&h.length>0?n.bindFramebuffer(e.DRAW_FRAMEBUFFER,c.__webglFramebuffer[0]):n.bindFramebuffer(e.DRAW_FRAMEBUFFER,c.__webglFramebuffer);for(let n=0;n<r.length;n++){if(t.resolveDepthBuffer&&(t.depthBuffer&&(a|=e.DEPTH_BUFFER_BIT),t.stencilBuffer&&t.resolveStencilBuffer&&(a|=e.STENCIL_BUFFER_BIT)),d){e.framebufferRenderbuffer(e.READ_FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.RENDERBUFFER,c.__webglColorRenderbuffer[n]);const t=i.get(r[n]).__webglTexture;e.framebufferTexture2D(e.DRAW_FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0)}e.blitFramebuffer(0,0,s,o,0,0,s,o,a,e.NEAREST),!0===l&&(k.length=0,F.length=0,k.push(e.COLOR_ATTACHMENT0+n),t.depthBuffer&&!1===t.resolveDepthBuffer&&(k.push(u),F.push(u),e.invalidateFramebuffer(e.DRAW_FRAMEBUFFER,F)),e.invalidateFramebuffer(e.READ_FRAMEBUFFER,k))}if(n.bindFramebuffer(e.READ_FRAMEBUFFER,null),n.bindFramebuffer(e.DRAW_FRAMEBUFFER,null),d)for(let t=0;t<r.length;t++){n.bindFramebuffer(e.FRAMEBUFFER,c.__webglMultisampledFramebuffer),e.framebufferRenderbuffer(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0+t,e.RENDERBUFFER,c.__webglColorRenderbuffer[t]);const s=i.get(r[t]).__webglTexture;n.bindFramebuffer(e.FRAMEBUFFER,c.__webglFramebuffer),e.framebufferTexture2D(e.DRAW_FRAMEBUFFER,e.COLOR_ATTACHMENT0+t,e.TEXTURE_2D,s,0)}n.bindFramebuffer(e.DRAW_FRAMEBUFFER,c.__webglMultisampledFramebuffer)}else if(t.depthBuffer&&!1===t.resolveDepthBuffer&&l){const n=t.stencilBuffer?e.DEPTH_STENCIL_ATTACHMENT:e.DEPTH_ATTACHMENT;e.invalidateFramebuffer(e.DRAW_FRAMEBUFFER,[n])}},this.setupDepthRenderbuffer=R,this.setupFrameBufferTexture=j,this.useMultisampledRTT=U}function Um(e,t){return{convert:function(n,i=""){let r;const s=ks.getTransfer(i);if(n===Gi)return e.UNSIGNED_BYTE;if(n===qi)return e.UNSIGNED_SHORT_4_4_4_4;if(n===_i)return e.UNSIGNED_SHORT_5_5_5_1;if(n===er)return e.UNSIGNED_INT_5_9_9_9_REV;if(n===tr)return e.UNSIGNED_INT_10F_11F_11F_REV;if(n===Vi)return e.BYTE;if(n===Wi)return e.SHORT;if(n===Qi)return e.UNSIGNED_SHORT;if(n===Zi)return e.INT;if(n===Yi)return e.UNSIGNED_INT;if(n===Ji)return e.FLOAT;if(n===Ki)return e.HALF_FLOAT;if(n===nr)return e.ALPHA;if(n===ir)return e.RGB;if(n===rr)return e.RGBA;if(n===sr)return e.DEPTH_COMPONENT;if(n===or)return e.DEPTH_STENCIL;if(n===ar)return e.RED;if(n===lr)return e.RED_INTEGER;if(n===ur)return e.RG;if(n===cr)return e.RG_INTEGER;if(n===dr)return e.RGBA_INTEGER;if(n===hr||n===fr||n===pr||n===gr)if(s===es){if(r=t.get("WEBGL_compressed_texture_s3tc_srgb"),null===r)return null;if(n===hr)return r.COMPRESSED_SRGB_S3TC_DXT1_EXT;if(n===fr)return r.COMPRESSED_SRGB_ALPHA_S3TC_DXT1_EXT;if(n===pr)return r.COMPRESSED_SRGB_ALPHA_S3TC_DXT3_EXT;if(n===gr)return r.COMPRESSED_SRGB_ALPHA_S3TC_DXT5_EXT}else{if(r=t.get("WEBGL_compressed_texture_s3tc"),null===r)return null;if(n===hr)return r.COMPRESSED_RGB_S3TC_DXT1_EXT;if(n===fr)return r.COMPRESSED_RGBA_S3TC_DXT1_EXT;if(n===pr)return r.COMPRESSED_RGBA_S3TC_DXT3_EXT;if(n===gr)return r.COMPRESSED_RGBA_S3TC_DXT5_EXT}if(n===mr||n===vr||n===Ar||n===xr){if(r=t.get("WEBGL_compressed_texture_pvrtc"),null===r)return null;if(n===mr)return r.COMPRESSED_RGB_PVRTC_4BPPV1_IMG;if(n===vr)return r.COMPRESSED_RGB_PVRTC_2BPPV1_IMG;if(n===Ar)return r.COMPRESSED_RGBA_PVRTC_4BPPV1_IMG;if(n===xr)return r.COMPRESSED_RGBA_PVRTC_2BPPV1_IMG}if(n===yr||n===br||n===wr){if(r=t.get("WEBGL_compressed_texture_etc"),null===r)return null;if(n===yr||n===br)return s===es?r.COMPRESSED_SRGB8_ETC2:r.COMPRESSED_RGB8_ETC2;if(n===wr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ETC2_EAC:r.COMPRESSED_RGBA8_ETC2_EAC}if(n===Cr||n===Mr||n===Er||n===Tr||n===Sr||n===Pr||n===Nr||n===Br||n===Dr||n===Ir||n===Lr||n===jr||n===Or||n===zr){if(r=t.get("WEBGL_compressed_texture_astc"),null===r)return null;if(n===Cr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_4x4_KHR:r.COMPRESSED_RGBA_ASTC_4x4_KHR;if(n===Mr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_5x4_KHR:r.COMPRESSED_RGBA_ASTC_5x4_KHR;if(n===Er)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_5x5_KHR:r.COMPRESSED_RGBA_ASTC_5x5_KHR;if(n===Tr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_6x5_KHR:r.COMPRESSED_RGBA_ASTC_6x5_KHR;if(n===Sr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_6x6_KHR:r.COMPRESSED_RGBA_ASTC_6x6_KHR;if(n===Pr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_8x5_KHR:r.COMPRESSED_RGBA_ASTC_8x5_KHR;if(n===Nr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_8x6_KHR:r.COMPRESSED_RGBA_ASTC_8x6_KHR;if(n===Br)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_8x8_KHR:r.COMPRESSED_RGBA_ASTC_8x8_KHR;if(n===Dr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_10x5_KHR:r.COMPRESSED_RGBA_ASTC_10x5_KHR;if(n===Ir)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_10x6_KHR:r.COMPRESSED_RGBA_ASTC_10x6_KHR;if(n===Lr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_10x8_KHR:r.COMPRESSED_RGBA_ASTC_10x8_KHR;if(n===jr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_10x10_KHR:r.COMPRESSED_RGBA_ASTC_10x10_KHR;if(n===Or)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_12x10_KHR:r.COMPRESSED_RGBA_ASTC_12x10_KHR;if(n===zr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_12x12_KHR:r.COMPRESSED_RGBA_ASTC_12x12_KHR}if(n===Rr||n===kr||n===Fr){if(r=t.get("EXT_texture_compression_bptc"),null===r)return null;if(n===Rr)return s===es?r.COMPRESSED_SRGB_ALPHA_BPTC_UNORM_EXT:r.COMPRESSED_RGBA_BPTC_UNORM_EXT;if(n===kr)return r.COMPRESSED_RGB_BPTC_SIGNED_FLOAT_EXT;if(n===Fr)return r.COMPRESSED_RGB_BPTC_UNSIGNED_FLOAT_EXT}if(n===Hr||n===Ur||n===Xr||n===Gr){if(r=t.get("EXT_texture_compression_rgtc"),null===r)return null;if(n===Hr)return r.COMPRESSED_RED_RGTC1_EXT;if(n===Ur)return r.COMPRESSED_SIGNED_RED_RGTC1_EXT;if(n===Xr)return r.COMPRESSED_RED_GREEN_RGTC2_EXT;if(n===Gr)return r.COMPRESSED_SIGNED_RED_GREEN_RGTC2_EXT}return n===$i?e.UNSIGNED_INT_24_8:void 0!==e[n]?e[n]:null}}}class Xm{constructor(){this.texture=null,this.mesh=null,this.depthNear=0,this.depthFar=0}init(e,t){if(null===this.texture){const n=new $l(e.texture);e.depthNear===t.depthNear&&e.depthFar===t.depthFar||(this.depthNear=e.depthNear,this.depthFar=e.depthFar),this.texture=n}}getMesh(e){if(null!==this.texture&&null===this.mesh){const t=e.cameras[0].viewport,n=new ul({vertexShader:"\nvoid main() {\n\n\tgl_Position = vec4( position, 1.0 );\n\n}",fragmentShader:"\nuniform sampler2DArray depthColor;\nuniform float depthWidth;\nuniform float depthHeight;\n\nvoid main() {\n\n\tvec2 coord = vec2( gl_FragCoord.x / depthWidth, gl_FragCoord.y / depthHeight );\n\n\tif ( coord.x >= 1.0 ) {\n\n\t\tgl_FragDepth = texture( depthColor, vec3( coord.x - 1.0, coord.y, 1 ) ).r;\n\n\t} else {\n\n\t\tgl_FragDepth = texture( depthColor, vec3( coord.x, coord.y, 0 ) ).r;\n\n\t}\n\n}",uniforms:{depthColor:{value:this.texture},depthWidth:{value:t.z},depthHeight:{value:t.w}}});this.mesh=new nl(new xu(20,20),n)}return this.mesh}reset(){this.texture=null,this.mesh=null}getDepthTexture(){return this.texture}}class Gm extends ds{constructor(e,t){super();const n=this;let i=null,r=1,s=null,o="local-floor",a=1,l=null,u=null,c=null,d=null,h=null,f=null;const p="undefined"!=typeof XRWebGLBinding,g=new Xm,m={},v=t.getContextAttributes();let A=null,x=null;const y=[],b=[],w=new Cs;let C=null;const M=new pl;M.viewport=new Js;const E=new pl;E.viewport=new Js;const T=[M,E],S=new xc;let P=null,N=null;function B(e){const t=b.indexOf(e.inputSource);if(-1===t)return;const n=y[t];void 0!==n&&(n.update(e.inputSource,e.frame,l||s),n.dispatchEvent({type:e.type,data:e.inputSource}))}function D(){i.removeEventListener("select",B),i.removeEventListener("selectstart",B),i.removeEventListener("selectend",B),i.removeEventListener("squeeze",B),i.removeEventListener("squeezestart",B),i.removeEventListener("squeezeend",B),i.removeEventListener("end",D),i.removeEventListener("inputsourceschange",I);for(let e=0;e<y.length;e++){const t=b[e];null!==t&&(b[e]=null,y[e].disconnect(t))}P=null,N=null,g.reset();for(const e in m)delete m[e];e.setRenderTarget(A),h=null,d=null,c=null,i=null,x=null,R.stop(),n.isPresenting=!1,e.setPixelRatio(C),e.setSize(w.width,w.height,!1),n.dispatchEvent({type:"sessionend"})}function I(e){for(let t=0;t<e.removed.length;t++){const n=e.removed[t],i=b.indexOf(n);i>=0&&(b[i]=null,y[i].disconnect(n))}for(let t=0;t<e.added.length;t++){const n=e.added[t];let i=b.indexOf(n);if(-1===i){for(let e=0;e<y.length;e++){if(e>=b.length){b.push(n),i=e;break}if(null===b[e]){b[e]=n,i=e;break}}if(-1===i)break}const r=y[i];r&&r.connect(n)}}this.cameraAutoUpdate=!0,this.enabled=!1,this.isPresenting=!1,this.getController=function(e){let t=y[e];return void 0===t&&(t=new bl,y[e]=t),t.getTargetRaySpace()},this.getControllerGrip=function(e){let t=y[e];return void 0===t&&(t=new bl,y[e]=t),t.getGripSpace()},this.getHand=function(e){let t=y[e];return void 0===t&&(t=new bl,y[e]=t),t.getHandSpace()},this.setFramebufferScaleFactor=function(e){r=e,!0===n.isPresenting&&console.warn("THREE.WebXRManager: Cannot change 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m[e]};let z=null;const R=new hp;R.setAnimationLoop((function(t,r){if(u=r.getViewerPose(l||s),f=r,null!==u){const t=u.views;null!==h&&(e.setRenderTargetFramebuffer(x,h.framebuffer),e.setRenderTarget(x));let r=!1;t.length!==S.cameras.length&&(S.cameras.length=0,r=!0);for(let n=0;n<t.length;n++){const i=t[n];let s=null;if(null!==h)s=h.getViewport(i);else{const t=c.getViewSubImage(d,i);s=t.viewport,0===n&&(e.setRenderTargetTextures(x,t.colorTexture,t.depthStencilTexture),e.setRenderTarget(x))}let o=T[n];void 0===o&&(o=new pl,o.layers.enable(n),o.viewport=new Js,T[n]=o),o.matrix.fromArray(i.transform.matrix),o.matrix.decompose(o.position,o.quaternion,o.scale),o.projectionMatrix.fromArray(i.projectionMatrix),o.projectionMatrixInverse.copy(o.projectionMatrix).invert(),o.viewport.set(s.x,s.y,s.width,s.height),0===n&&(S.matrix.copy(o.matrix),S.matrix.decompose(S.position,S.quaternion,S.scale)),!0===r&&S.cameras.push(o)}const s=i.enabledFeatures;if(s&&s.includes("depth-sensing")&&"gpu-optimized"==i.depthUsage&&p){c=n.getBinding();const e=c.getDepthInformation(t[0]);e&&e.isValid&&e.texture&&g.init(e,i.renderState)}if(s&&s.includes("camera-access")&&p){e.state.unbindTexture(),c=n.getBinding();for(let e=0;e<t.length;e++){const n=t[e].camera;if(n){let e=m[n];e||(e=new $l,m[n]=e);const t=c.getCameraImage(n);e.sourceTexture=t}}}}for(let e=0;e<y.length;e++){const t=b[e],n=y[e];null!==t&&void 0!==n&&n.update(t,r,l||s)}z&&z(t,r),r.detectedPlanes&&n.dispatchEvent({type:"planesdetected",data:r}),f=null})),this.setAnimationLoop=function(e){z=e},this.dispose=function(){}}}const Vm=new ko,Wm=new Po;function Qm(e,t){function n(e,t){!0===e.matrixAutoUpdate&&e.updateMatrix(),t.value.copy(e.matrix)}function i(e,i){e.opacity.value=i.opacity,i.color&&e.diffuse.value.copy(i.color),i.emissive&&e.emissive.value.copy(i.emissive).multiplyScalar(i.emissiveIntensity),i.map&&(e.map.value=i.map,n(i.map,e.mapTransform)),i.alphaMap&&(e.alphaMap.value=i.alphaMap,n(i.alphaMap,e.alphaMapTransform)),i.bumpMap&&(e.bumpMap.value=i.bumpMap,n(i.bumpMap,e.bumpMapTransform),e.bumpScale.value=i.bumpScale,1===i.side&&(e.bumpScale.value*=-1)),i.normalMap&&(e.normalMap.value=i.normalMap,n(i.normalMap,e.normalMapTransform),e.normalScale.value.copy(i.normalScale),1===i.side&&e.normalScale.value.negate()),i.displacementMap&&(e.displacementMap.value=i.displacementMap,n(i.displacementMap,e.displacementMapTransform),e.displacementScale.value=i.displacementScale,e.displacementBias.value=i.displacementBias),i.emissiveMap&&(e.emissiveMap.value=i.emissiveMap,n(i.emissiveMap,e.emissiveMapTransform)),i.specularMap&&(e.specularMap.value=i.specularMap,n(i.specularMap,e.specularMapTransform)),i.alphaTest>0&&(e.alphaTest.value=i.alphaTest);const r=t.get(i),s=r.envMap,o=r.envMapRotation;s&&(e.envMap.value=s,Vm.copy(o),Vm.x*=-1,Vm.y*=-1,Vm.z*=-1,s.isCubeTexture&&!1===s.isRenderTargetTexture&&(Vm.y*=-1,Vm.z*=-1),e.envMapRotation.value.setFromMatrix4(Wm.makeRotationFromEuler(Vm)),e.flipEnvMap.value=s.isCubeTexture&&!1===s.isRenderTargetTexture?-1:1,e.reflectivity.value=i.reflectivity,e.ior.value=i.ior,e.refractionRatio.value=i.refractionRatio),i.lightMap&&(e.lightMap.value=i.lightMap,e.lightMapIntensity.value=i.lightMapIntensity,n(i.lightMap,e.lightMapTransform)),i.aoMap&&(e.aoMap.value=i.aoMap,e.aoMapIntensity.value=i.aoMapIntensity,n(i.aoMap,e.aoMapTransform))}return{refreshFogUniforms:function(t,n){n.color.getRGB(t.fogColor.value,al(e)),n.isFog?(t.fogNear.value=n.near,t.fogFar.value=n.far):n.isFogExp2&&(t.fogDensity.value=n.density)},refreshMaterialUniforms:function(e,r,s,o,a){r.isMeshBasicMaterial||r.isMeshLambertMaterial?i(e,r):r.isMeshToonMaterial?(i(e,r),function(e,t){t.gradientMap&&(e.gradientMap.value=t.gradientMap)}(e,r)):r.isMeshPhongMaterial?(i(e,r),function(e,t){e.specular.value.copy(t.specular),e.shininess.value=Math.max(t.shininess,1e-4)}(e,r)):r.isMeshStandardMaterial?(i(e,r),function(e,t){e.metalness.value=t.metalness,t.metalnessMap&&(e.metalnessMap.value=t.metalnessMap,n(t.metalnessMap,e.metalnessMapTransform));e.roughness.value=t.roughness,t.roughnessMap&&(e.roughnessMap.value=t.roughnessMap,n(t.roughnessMap,e.roughnessMapTransform));t.envMap&&(e.envMapIntensity.value=t.envMapIntensity)}(e,r),r.isMeshPhysicalMaterial&&function(e,t,i){e.ior.value=t.ior,t.sheen>0&&(e.sheenColor.value.copy(t.sheenColor).multiplyScalar(t.sheen),e.sheenRoughness.value=t.sheenRoughness,t.sheenColorMap&&(e.sheenColorMap.value=t.sheenColorMap,n(t.sheenColorMap,e.sheenColorMapTransform)),t.sheenRoughnessMap&&(e.sheenRoughnessMap.value=t.sheenRoughnessMap,n(t.sheenRoughnessMap,e.sheenRoughnessMapTransform)));t.clearcoat>0&&(e.clearcoat.value=t.clearcoat,e.clearcoatRoughness.value=t.clearcoatRoughness,t.clearcoatMap&&(e.clearcoatMap.value=t.clearcoatMap,n(t.clearcoatMap,e.clearcoatMapTransform)),t.clearcoatRoughnessMap&&(e.clearcoatRoughnessMap.value=t.clearcoatRoughnessMap,n(t.clearcoatRoughnessMap,e.clearcoatRoughnessMapTransform)),t.clearcoatNormalMap&&(e.clearcoatNormalMap.value=t.clearcoatNormalMap,n(t.clearcoatNormalMap,e.clearcoatNormalMapTransform),e.clearcoatNormalScale.value.copy(t.clearcoatNormalScale),1===t.side&&e.clearcoatNormalScale.value.negate()));t.dispersion>0&&(e.dispersion.value=t.dispersion);t.iridescence>0&&(e.iridescence.value=t.iridescence,e.iridescenceIOR.value=t.iridescenceIOR,e.iridescenceThicknessMinimum.value=t.iridescenceThicknessRange[0],e.iridescenceThicknessMaximum.value=t.iridescenceThicknessRange[1],t.iridescenceMap&&(e.iridescenceMap.value=t.iridescenceMap,n(t.iridescenceMap,e.iridescenceMapTransform)),t.iridescenceThicknessMap&&(e.iridescenceThicknessMap.value=t.iridescenceThicknessMap,n(t.iridescenceThicknessMap,e.iridescenceThicknessMapTransform)));t.transmission>0&&(e.transmission.value=t.transmission,e.transmissionSamplerMap.value=i.texture,e.transmissionSamplerSize.value.set(i.width,i.height),t.transmissionMap&&(e.transmissionMap.value=t.transmissionMap,n(t.transmissionMap,e.transmissionMapTransform)),e.thickness.value=t.thickness,t.thicknessMap&&(e.thicknessMap.value=t.thicknessMap,n(t.thicknessMap,e.thicknessMapTransform)),e.attenuationDistance.value=t.attenuationDistance,e.attenuationColor.value.copy(t.attenuationColor));t.anisotropy>0&&(e.anisotropyVector.value.set(t.anisotropy*Math.cos(t.anisotropyRotation),t.anisotropy*Math.sin(t.anisotropyRotation)),t.anisotropyMap&&(e.anisotropyMap.value=t.anisotropyMap,n(t.anisotropyMap,e.anisotropyMapTransform)));e.specularIntensity.value=t.specularIntensity,e.specularColor.value.copy(t.specularColor),t.specularColorMap&&(e.specularColorMap.value=t.specularColorMap,n(t.specularColorMap,e.specularColorMapTransform));t.specularIntensityMap&&(e.specularIntensityMap.value=t.specularIntensityMap,n(t.specularIntensityMap,e.specularIntensityMapTransform))}(e,r,a)):r.isMeshMatcapMaterial?(i(e,r),function(e,t){t.matcap&&(e.matcap.value=t.matcap)}(e,r)):r.isMeshDepthMaterial?i(e,r):r.isMeshDistanceMaterial?(i(e,r),function(e,n){const i=t.get(n).light;e.referencePosition.value.setFromMatrixPosition(i.matrixWorld),e.nearDistance.value=i.shadow.camera.near,e.farDistance.value=i.shadow.camera.far}(e,r)):r.isMeshNormalMaterial?i(e,r):r.isLineBasicMaterial?(function(e,t){e.diffuse.value.copy(t.color),e.opacity.value=t.opacity,t.map&&(e.map.value=t.map,n(t.map,e.mapTransform))}(e,r),r.isLineDashedMaterial&&function(e,t){e.dashSize.value=t.dashSize,e.totalSize.value=t.dashSize+t.gapSize,e.scale.value=t.scale}(e,r)):r.isPointsMaterial?function(e,t,i,r){e.diffuse.value.copy(t.color),e.opacity.value=t.opacity,e.size.value=t.size*i,e.scale.value=.5*r,t.map&&(e.map.value=t.map,n(t.map,e.uvTransform));t.alphaMap&&(e.alphaMap.value=t.alphaMap,n(t.alphaMap,e.alphaMapTransform));t.alphaTest>0&&(e.alphaTest.value=t.alphaTest)}(e,r,s,o):r.isSpriteMaterial?function(e,t){e.diffuse.value.copy(t.color),e.opacity.value=t.opacity,e.rotation.value=t.rotation,t.map&&(e.map.value=t.map,n(t.map,e.mapTransform));t.alphaMap&&(e.alphaMap.value=t.alphaMap,n(t.alphaMap,e.alphaMapTransform));t.alphaTest>0&&(e.alphaTest.value=t.alphaTest)}(e,r):r.isShadowMaterial?(e.color.value.copy(r.color),e.opacity.value=r.opacity):r.isShaderMaterial&&(r.uniformsNeedUpdate=!1)}}}function Zm(e,t,n,i){let r={},s={},o=[];const a=e.getParameter(e.MAX_UNIFORM_BUFFER_BINDINGS);function l(e,t,n,i){const r=e.value,s=t+"_"+n;if(void 0===i[s])return i[s]="number"==typeof r||"boolean"==typeof r?r:r.clone(),!0;{const e=i[s];if("number"==typeof r||"boolean"==typeof r){if(e!==r)return i[s]=r,!0}else if(!1===e.equals(r))return e.copy(r),!0}return!1}function u(e){const t={boundary:0,storage:0};return"number"==typeof e||"boolean"==typeof e?(t.boundary=4,t.storage=4):e.isVector2?(t.boundary=8,t.storage=8):e.isVector3||e.isColor?(t.boundary=16,t.storage=12):e.isVector4?(t.boundary=16,t.storage=16):e.isMatrix3?(t.boundary=48,t.storage=48):e.isMatrix4?(t.boundary=64,t.storage=64):e.isTexture?console.warn("THREE.WebGLRenderer: Texture samplers can not be part of an uniforms group."):console.warn("THREE.WebGLRenderer: Unsupported uniform value type.",e),t}function c(t){const n=t.target;n.removeEventListener("dispose",c);const i=o.indexOf(n.__bindingPointIndex);o.splice(i,1),e.deleteBuffer(r[n.id]),delete r[n.id],delete s[n.id]}return{bind:function(e,t){const n=t.program;i.uniformBlockBinding(e,n)},update:function(n,d){let h=r[n.id];void 0===h&&(!function(e){const t=e.uniforms;let n=0;const i=16;for(let e=0,r=t.length;e<r;e++){const r=Array.isArray(t[e])?t[e]:[t[e]];for(let e=0,t=r.length;e<t;e++){const t=r[e],s=Array.isArray(t.value)?t.value:[t.value];for(let e=0,r=s.length;e<r;e++){const r=u(s[e]),o=n%i,a=o%r.boundary,l=o+a;n+=a,0!==l&&i-l<r.storage&&(n+=i-l),t.__data=new Float32Array(r.storage/Float32Array.BYTES_PER_ELEMENT),t.__offset=n,n+=r.storage}}}const r=n%i;r>0&&(n+=i-r);e.__size=n,e.__cache={}}(n),h=function(t){const n=function(){for(let e=0;e<a;e++)if(-1===o.indexOf(e))return o.push(e),e;return console.error("THREE.WebGLRenderer: Maximum number of simultaneously usable uniforms groups reached."),0}();t.__bindingPointIndex=n;const i=e.createBuffer(),r=t.__size,s=t.usage;return e.bindBuffer(e.UNIFORM_BUFFER,i),e.bufferData(e.UNIFORM_BUFFER,r,s),e.bindBuffer(e.UNIFORM_BUFFER,null),e.bindBufferBase(e.UNIFORM_BUFFER,n,i),i}(n),r[n.id]=h,n.addEventListener("dispose",c));const f=d.program;i.updateUBOMapping(n,f);const p=t.render.frame;s[n.id]!==p&&(!function(t){const n=r[t.id],i=t.uniforms,s=t.__cache;e.bindBuffer(e.UNIFORM_BUFFER,n);for(let t=0,n=i.length;t<n;t++){const n=Array.isArray(i[t])?i[t]:[i[t]];for(let i=0,r=n.length;i<r;i++){const r=n[i];if(!0===l(r,t,i,s)){const t=r.__offset,n=Array.isArray(r.value)?r.value:[r.value];let i=0;for(let s=0;s<n.length;s++){const o=n[s],a=u(o);"number"==typeof o||"boolean"==typeof o?(r.__data[0]=o,e.bufferSubData(e.UNIFORM_BUFFER,t+i,r.__data)):o.isMatrix3?(r.__data[0]=o.elements[0],r.__data[1]=o.elements[1],r.__data[2]=o.elements[2],r.__data[3]=0,r.__data[4]=o.elements[3],r.__data[5]=o.elements[4],r.__data[6]=o.elements[5],r.__data[7]=0,r.__data[8]=o.elements[6],r.__data[9]=o.elements[7],r.__data[10]=o.elements[8],r.__data[11]=0):(o.toArray(r.__data,i),i+=a.storage/Float32Array.BYTES_PER_ELEMENT)}e.bufferSubData(e.UNIFORM_BUFFER,t,r.__data)}}}e.bindBuffer(e.UNIFORM_BUFFER,null)}(n),s[n.id]=p)},dispose:function(){for(const t in r)e.deleteBuffer(r[t]);o=[],r={},s={}}}}const Ym=["alphaMap","alphaTest","anisotropy","anisotropyMap","anisotropyRotation","aoMap","aoMapIntensity","attenuationColor","attenuationDistance","bumpMap","clearcoat","clearcoatMap","clearcoatNormalMap","clearcoatNormalScale","clearcoatRoughness","color","dispersion","displacementMap","emissive","emissiveIntensity","emissiveMap","envMap","envMapIntensity","gradientMap","ior","iridescence","iridescenceIOR","iridescenceMap","iridescenceThicknessMap","lightMap","lightMapIntensity","map","matcap","metalness","metalnessMap","normalMap","normalScale","opacity","roughness","roughnessMap","sheen","sheenColor","sheenColorMap","sheenRoughnessMap","shininess","specular","specularColor","specularColorMap","specularIntensity","specularIntensityMap","specularMap","thickness","transmission","transmissionMap"],Jm=new WeakMap;class Km{constructor(e){this.renderObjects=new WeakMap,this.hasNode=this.containsNode(e),this.hasAnimation=!0===e.object.isSkinnedMesh,this.refreshUniforms=Ym,this.renderId=0}firstInitialization(e){return!1===this.renderObjects.has(e)&&(this.getRenderObjectData(e),!0)}needsVelocity(e){const t=e.getMRT();return null!==t&&t.has("velocity")}getRenderObjectData(e){let t=this.renderObjects.get(e);if(void 0===t){const{geometry:n,material:i,object:r}=e;if(t={material:this.getMaterialData(i),geometry:{id:n.id,attributes:this.getAttributesData(n.attributes),indexVersion:n.index?n.index.version:null,drawRange:{start:n.drawRange.start,count:n.drawRange.count}},worldMatrix:r.matrixWorld.clone()},r.center&&(t.center=r.center.clone()),r.morphTargetInfluences&&(t.morphTargetInfluences=r.morphTargetInfluences.slice()),null!==e.bundle&&(t.version=e.bundle.version),t.material.transmission>0){const{width:n,height:i}=e.context;t.bufferWidth=n,t.bufferHeight=i}t.lights=this.getLightsData(e.lightsNode.getLights()),this.renderObjects.set(e,t)}return t}getAttributesData(e){const t={};for(const n in e){const i=e[n];t[n]={version:i.version}}return t}containsNode(e){const t=e.material;for(const e in t)if(t[e]&&t[e].isNode)return!0;return null!==e.renderer.overrideNodes.modelViewMatrix||null!==e.renderer.overrideNodes.modelNormalViewMatrix}getMaterialData(e){const t={};for(const n of this.refreshUniforms){const i=e[n];null!=i&&("object"==typeof i&&void 0!==i.clone?!0===i.isTexture?t[n]={id:i.id,version:i.version}:t[n]=i.clone():t[n]=i)}return t}equals(e,t){const{object:n,material:i,geometry:r}=e,s=this.getRenderObjectData(e);if(!0!==s.worldMatrix.equals(n.matrixWorld))return s.worldMatrix.copy(n.matrixWorld),!1;const o=s.material;for(const e in o){const t=o[e],n=i[e];if(void 0!==t.equals){if(!1===t.equals(n))return t.copy(n),!1}else if(!0===n.isTexture){if(t.id!==n.id||t.version!==n.version)return t.id=n.id,t.version=n.version,!1}else if(t!==n)return o[e]=n,!1}if(o.transmission>0){const{width:t,height:n}=e.context;if(s.bufferWidth!==t||s.bufferHeight!==n)return s.bufferWidth=t,s.bufferHeight=n,!1}const a=s.geometry,l=r.attributes,u=a.attributes,c=Object.keys(u),d=Object.keys(l);if(a.id!==r.id)return a.id=r.id,!1;if(c.length!==d.length)return s.geometry.attributes=this.getAttributesData(l),!1;for(const e of c){const t=u[e],n=l[e];if(void 0===n)return delete u[e],!1;if(t.version!==n.version)return t.version=n.version,!1}const h=r.index,f=a.indexVersion,p=h?h.version:null;if(f!==p)return a.indexVersion=p,!1;if(a.drawRange.start!==r.drawRange.start||a.drawRange.count!==r.drawRange.count)return a.drawRange.start=r.drawRange.start,a.drawRange.count=r.drawRange.count,!1;if(s.morphTargetInfluences){let e=!1;for(let t=0;t<s.morphTargetInfluences.length;t++)s.morphTargetInfluences[t]!==n.morphTargetInfluences[t]&&(e=!0);if(e)return!0}if(s.lights)for(let e=0;e<t.length;e++)if(s.lights[e].map!==t[e].map)return!1;return s.center&&!1===s.center.equals(n.center)?(s.center.copy(n.center),!0):(null!==e.bundle&&(s.version=e.bundle.version),!0)}getLightsData(e){const t=[];for(const n of e)!0===n.isSpotLight&&null!==n.map&&t.push({map:n.map.version});return t}getLights(e,t){if(Jm.has(e)){const n=Jm.get(e);if(n.renderId===t)return n.lightsData}const n=this.getLightsData(e.getLights());return Jm.set(e,{renderId:t,lightsData:n}),n}needsRefresh(e,t){if(this.hasNode||this.hasAnimation||this.firstInitialization(e)||this.needsVelocity(t.renderer))return!0;const{renderId:n}=t;if(this.renderId!==n)return this.renderId=n,!0;const i=!0===e.object.static,r=null!==e.bundle&&!0===e.bundle.static&&this.getRenderObjectData(e).version===e.bundle.version;if(i||r)return!1;const s=this.getLights(e.lightsNode,n);return!0!==this.equals(e,s)}}function qm(e,t=0){let n=3735928559^t,i=1103547991^t;if(e instanceof Array)for(let t,r=0;r<e.length;r++)t=e[r],n=Math.imul(n^t,2654435761),i=Math.imul(i^t,1597334677);else for(let t,r=0;r<e.length;r++)t=e.charCodeAt(r),n=Math.imul(n^t,2654435761),i=Math.imul(i^t,1597334677);return n=Math.imul(n^n>>>16,2246822507),n^=Math.imul(i^i>>>13,3266489909),i=Math.imul(i^i>>>16,2246822507),i^=Math.imul(n^n>>>13,3266489909),4294967296*(2097151&i)+(n>>>0)}const _m=e=>qm(e),$m=e=>qm(e),ev=(...e)=>qm(e);function tv(e,t=!1){const n=[];!0===e.isNode&&n.push(e.id);for(const{property:i,childNode:r}of nv(e))n.push(qm(i.slice(0,-4)),r.getCacheKey(t));return qm(n)}function*nv(e,t=!1){for(const n of Object.getOwnPropertyNames(e)){if(!0===n.startsWith("_"))continue;const i=e[n];if(!0===Array.isArray(i))for(let e=0;e<i.length;e++){const r=i[e];r&&(!0===r.isNode||t&&"function"==typeof r.toJSON)&&(yield{property:n,index:e,childNode:r})}else if(i&&!0===i.isNode)yield{property:n,childNode:i};else if(i&&Object.getPrototypeOf(i)===Object.prototype)for(const e in i){if(!0===e.startsWith("_"))continue;const r=i[e];r&&(!0===r.isNode||t&&"function"==typeof r.toJSON)&&(yield{property:n,index:e,childNode:r})}}}const iv=new Map([[1,"float"],[2,"vec2"],[3,"vec3"],[4,"vec4"],[9,"mat3"],[16,"mat4"]]),rv=new WeakMap;function sv(e){return iv.get(e)}function ov(e){if(null==e)return null;const t=typeof e;return!0===e.isNode?"node":"number"===t?"float":"boolean"===t?"bool":"string"===t?"string":"function"===t?"shader":!0===e.isVector2?"vec2":!0===e.isVector3?"vec3":!0===e.isVector4?"vec4":!0===e.isMatrix2?"mat2":!0===e.isMatrix3?"mat3":!0===e.isMatrix4?"mat4":!0===e.isColor?"color":e instanceof ArrayBuffer?"ArrayBuffer":null}function av(e,...t){const n=e?e.slice(-4):void 0;return 1===t.length&&("vec2"===n?t=[t[0],t[0]]:"vec3"===n?t=[t[0],t[0],t[0]]:"vec4"===n&&(t=[t[0],t[0],t[0],t[0]])),"color"===e?new ya(...t):"vec2"===n?new Cs(...t):"vec3"===n?new Es(...t):"vec4"===n?new Js(...t):"mat2"===n?new jc(...t):"mat3"===n?new Ps(...t):"mat4"===n?new Po(...t):"bool"===e?t[0]||!1:"float"===e||"int"===e||"uint"===e?t[0]||0:"string"===e?t[0]||"":"ArrayBuffer"===e?cv(t[0]):null}function lv(e){let t=rv.get(e);return void 0===t&&(t={},rv.set(e,t)),t}function uv(e){let t="";const n=new Uint8Array(e);for(let e=0;e<n.length;e++)t+=String.fromCharCode(n[e]);return btoa(t)}function cv(e){return Uint8Array.from(atob(e),(e=>e.charCodeAt(0))).buffer}const dv={VERTEX:"vertex",FRAGMENT:"fragment"},hv={NONE:"none",FRAME:"frame",RENDER:"render",OBJECT:"object"},fv={READ_ONLY:"readOnly",WRITE_ONLY:"writeOnly",READ_WRITE:"readWrite"},pv=["fragment","vertex"],gv=["setup","analyze","generate"],mv=[...pv,"compute"],vv=["x","y","z","w"],Av={analyze:"setup",generate:"analyze"};let xv=0;class yv extends ds{static get type(){return"Node"}constructor(e=null){super(),this.nodeType=e,this.updateType=hv.NONE,this.updateBeforeType=hv.NONE,this.updateAfterType=hv.NONE,this.uuid=ws.generateUUID(),this.version=0,this.global=!1,this.parents=!1,this.isNode=!0,this._cacheKey=null,this._cacheKeyVersion=0,Object.defineProperty(this,"id",{value:xv++})}set needsUpdate(e){!0===e&&this.version++}get type(){return this.constructor.type}onUpdate(e,t){return this.updateType=t,this.update=e.bind(this),this}onFrameUpdate(e){return this.onUpdate(e,hv.FRAME)}onRenderUpdate(e){return this.onUpdate(e,hv.RENDER)}onObjectUpdate(e){return this.onUpdate(e,hv.OBJECT)}onReference(e){return this.updateReference=e.bind(this),this}updateReference(){return this}isGlobal(){return this.global}*getChildren(){for(const{childNode:e}of nv(this))yield e}dispose(){this.dispatchEvent({type:"dispose"})}traverse(e){e(this);for(const t of this.getChildren())t.traverse(e)}getCacheKey(e=!1){return!0!==(e=e||this.version!==this._cacheKeyVersion)&&null!==this._cacheKey||(this._cacheKey=ev(tv(this,e),this.customCacheKey()),this._cacheKeyVersion=this.version),this._cacheKey}customCacheKey(){return 0}getScope(){return this}getHash(){return this.uuid}getUpdateType(){return this.updateType}getUpdateBeforeType(){return this.updateBeforeType}getUpdateAfterType(){return this.updateAfterType}getElementType(e){const t=this.getNodeType(e);return e.getElementType(t)}getMemberType(){return"void"}getNodeType(e){const t=e.getNodeProperties(this);return t.outputNode?t.outputNode.getNodeType(e):this.nodeType}getShared(e){const t=this.getHash(e);return e.getNodeFromHash(t)||this}getArrayCount(){return null}setup(e){const t=e.getNodeProperties(this);let n=0;for(const e of this.getChildren())t["node"+n++]=e;return t.outputNode||null}analyze(e,t=null){const n=e.increaseUsage(this);if(!0===this.parents){const n=e.getDataFromNode(this,"any");n.stages=n.stages||{},n.stages[e.shaderStage]=n.stages[e.shaderStage]||[],n.stages[e.shaderStage].push(t)}if(1===n){const t=e.getNodeProperties(this);for(const n of Object.values(t))n&&!0===n.isNode&&n.build(e,this)}}generate(e,t){const{outputNode:n}=e.getNodeProperties(this);if(n&&!0===n.isNode)return n.build(e,t)}updateBefore(){console.warn("Abstract function.")}updateAfter(){console.warn("Abstract function.")}update(){console.warn("Abstract function.")}build(e,t=null){const n=this.getShared(e);if(this!==n)return n.build(e,t);const i=e.getDataFromNode(this);i.buildStages=i.buildStages||{},i.buildStages[e.buildStage]=!0;const r=Av[e.buildStage];if(r&&!0!==i.buildStages[r]){const t=e.getBuildStage();e.setBuildStage(r),this.build(e),e.setBuildStage(t)}e.addNode(this),e.addChain(this);let s=null;const o=e.getBuildStage();if("setup"===o){this.updateReference(e);const t=e.getNodeProperties(this);if(!0!==t.initialized){t.initialized=!0,t.outputNode=this.setup(e)||t.outputNode||null;for(const n of Object.values(t))if(n&&!0===n.isNode){if(!0===n.parents){const t=e.getNodeProperties(n);t.parents=t.parents||[],t.parents.push(this)}n.build(e)}}s=t.outputNode}else if("analyze"===o)this.analyze(e,t);else if("generate"===o){if(1===this.generate.length){const n=this.getNodeType(e),i=e.getDataFromNode(this);s=i.snippet,void 0===s?void 0===i.generated?(i.generated=!0,s=this.generate(e)||"",i.snippet=s):(console.warn("THREE.Node: Recursion detected.",this),s="/* Recursion detected. */"):void 0!==i.flowCodes&&void 0!==e.context.nodeBlock&&e.addFlowCodeHierarchy(this,e.context.nodeBlock),s=e.format(s,n,t)}else s=this.generate(e,t)||"";""===s&&null!==t&&"void"!==t&&"OutputType"!==t&&(console.error(`THREE.TSL: Invalid generated code, expected a "${t}".`),s=e.generateConst(t))}return e.removeChain(this),e.addSequentialNode(this),s}getSerializeChildren(){return nv(this)}serialize(e){const t=this.getSerializeChildren(),n={};for(const{property:i,index:r,childNode:s}of t)void 0!==r?(void 0===n[i]&&(n[i]=Number.isInteger(r)?[]:{}),n[i][r]=s.toJSON(e.meta).uuid):n[i]=s.toJSON(e.meta).uuid;Object.keys(n).length>0&&(e.inputNodes=n)}deserialize(e){if(void 0!==e.inputNodes){const t=e.meta.nodes;for(const n in e.inputNodes)if(Array.isArray(e.inputNodes[n])){const i=[];for(const r of e.inputNodes[n])i.push(t[r]);this[n]=i}else if("object"==typeof e.inputNodes[n]){const i={};for(const r in e.inputNodes[n]){const s=e.inputNodes[n][r];i[r]=t[s]}this[n]=i}else{const i=e.inputNodes[n];this[n]=t[i]}}}toJSON(e){const{uuid:t,type:n}=this,i=void 0===e||"string"==typeof e;i&&(e={textures:{},images:{},nodes:{}});let r=e.nodes[t];function s(e){const t=[];for(const n in e){const i=e[n];delete i.metadata,t.push(i)}return t}if(void 0===r&&(r={uuid:t,type:n,meta:e,metadata:{version:4.7,type:"Node",generator:"Node.toJSON"}},!0!==i&&(e.nodes[r.uuid]=r),this.serialize(r),delete r.meta),i){const t=s(e.textures),n=s(e.images),i=s(e.nodes);t.length>0&&(r.textures=t),n.length>0&&(r.images=n),i.length>0&&(r.nodes=i)}return r}}class bv extends yv{static get type(){return"ArrayElementNode"}constructor(e,t){super(),this.node=e,this.indexNode=t,this.isArrayElementNode=!0}getNodeType(e){return this.node.getElementType(e)}generate(e){const t=this.indexNode.getNodeType(e);return`${this.node.build(e)}[ ${this.indexNode.build(e,!e.isVector(t)&&e.isInteger(t)?t:"uint")} ]`}}class wv extends yv{static get type(){return"ConvertNode"}constructor(e,t){super(),this.node=e,this.convertTo=t}getNodeType(e){const t=this.node.getNodeType(e);let n=null;for(const i of this.convertTo.split("|"))null!==n&&e.getTypeLength(t)!==e.getTypeLength(i)||(n=i);return n}serialize(e){super.serialize(e),e.convertTo=this.convertTo}deserialize(e){super.deserialize(e),this.convertTo=e.convertTo}generate(e,t){const n=this.node,i=this.getNodeType(e),r=n.build(e,i);return e.format(r,i,t)}}class Cv extends yv{static get type(){return"TempNode"}constructor(e=null){super(e),this.isTempNode=!0}hasDependencies(e){return e.getDataFromNode(this).usageCount>1}build(e,t){if("generate"===e.getBuildStage()){const n=e.getVectorType(this.getNodeType(e,t)),i=e.getDataFromNode(this);if(void 0!==i.propertyName)return e.format(i.propertyName,n,t);if("void"!==n&&"void"!==t&&this.hasDependencies(e)){const r=super.build(e,n),s=e.getVarFromNode(this,null,n),o=e.getPropertyName(s);return e.addLineFlowCode(`${o} = ${r}`,this),i.snippet=r,i.propertyName=o,e.format(i.propertyName,n,t)}}return super.build(e,t)}}class Mv extends Cv{static get type(){return"JoinNode"}constructor(e=[],t=null){super(t),this.nodes=e}getNodeType(e){return null!==this.nodeType?e.getVectorType(this.nodeType):e.getTypeFromLength(this.nodes.reduce(((t,n)=>t+e.getTypeLength(n.getNodeType(e))),0))}generate(e,t){const n=this.getNodeType(e),i=e.getTypeLength(n),r=this.nodes,s=e.getComponentType(n),o=[];let a=0;for(const t of r){if(a>=i){console.error(`THREE.TSL: Length of parameters exceeds maximum length of function '${n}()' type.`);break}let r,l=t.getNodeType(e),u=e.getTypeLength(l);a+u>i&&(console.error(`THREE.TSL: Length of '${n}()' data exceeds maximum length of output type.`),u=i-a,l=e.getTypeFromLength(u)),a+=u,r=t.build(e,l);if(e.getComponentType(l)!==s){const t=e.getTypeFromLength(u,s);r=e.format(r,l,t)}o.push(r)}const l=`${e.getType(n)}( ${o.join(", ")} )`;return e.format(l,n,t)}}const Ev=vv.join("");class Tv extends yv{static get type(){return"SplitNode"}constructor(e,t="x"){super(),this.node=e,this.components=t,this.isSplitNode=!0}getVectorLength(){let e=this.components.length;for(const t of this.components)e=Math.max(vv.indexOf(t)+1,e);return e}getComponentType(e){return e.getComponentType(this.node.getNodeType(e))}getNodeType(e){return e.getTypeFromLength(this.components.length,this.getComponentType(e))}getScope(){return this.node.getScope()}generate(e,t){const n=this.node,i=e.getTypeLength(n.getNodeType(e));let r=null;if(i>1){let s=null;this.getVectorLength()>=i&&(s=e.getTypeFromLength(this.getVectorLength(),this.getComponentType(e)));const o=n.build(e,s);r=this.components.length===i&&this.components===Ev.slice(0,this.components.length)?e.format(o,s,t):e.format(`${o}.${this.components}`,this.getNodeType(e),t)}else r=n.build(e,t);return r}serialize(e){super.serialize(e),e.components=this.components}deserialize(e){super.deserialize(e),this.components=e.components}}class Sv extends Cv{static get type(){return"SetNode"}constructor(e,t,n){super(),this.sourceNode=e,this.components=t,this.targetNode=n}getNodeType(e){return this.sourceNode.getNodeType(e)}generate(e){const{sourceNode:t,components:n,targetNode:i}=this,r=this.getNodeType(e),s=e.getComponentType(i.getNodeType(e)),o=e.getTypeFromLength(n.length,s),a=i.build(e,o),l=t.build(e,r),u=e.getTypeLength(r),c=[];for(let e=0;e<u;e++){const t=vv[e];t===n[0]?(c.push(a),e+=n.length-1):c.push(l+"."+t)}return`${e.getType(r)}( ${c.join(", ")} )`}}class Pv extends Cv{static get type(){return"FlipNode"}constructor(e,t){super(),this.sourceNode=e,this.components=t}getNodeType(e){return this.sourceNode.getNodeType(e)}generate(e){const{components:t,sourceNode:n}=this,i=this.getNodeType(e),r=n.build(e),s=e.getVarFromNode(this),o=e.getPropertyName(s);e.addLineFlowCode(o+" = "+r,this);const a=e.getTypeLength(i),l=[];let u=0;for(let e=0;e<a;e++){const n=vv[e];n===t[u]?(l.push("1.0 - "+o+"."+n),u++):l.push(o+"."+n)}return`${e.getType(i)}( ${l.join(", ")} )`}}class Nv extends yv{static get type(){return"InputNode"}constructor(e,t=null){super(t),this.isInputNode=!0,this.value=e,this.precision=null}getNodeType(){return null===this.nodeType?ov(this.value):this.nodeType}getInputType(e){return this.getNodeType(e)}setPrecision(e){return this.precision=e,this}serialize(e){super.serialize(e),e.value=this.value,this.value&&this.value.toArray&&(e.value=this.value.toArray()),e.valueType=ov(this.value),e.nodeType=this.nodeType,"ArrayBuffer"===e.valueType&&(e.value=uv(e.value)),e.precision=this.precision}deserialize(e){super.deserialize(e),this.nodeType=e.nodeType,this.value=Array.isArray(e.value)?av(e.valueType,...e.value):e.value,this.precision=e.precision||null,this.value&&this.value.fromArray&&(this.value=this.value.fromArray(e.value))}generate(){console.warn("Abstract function.")}}const Bv=/float|u?int/;class Dv extends Nv{static get type(){return"ConstNode"}constructor(e,t=null){super(e,t),this.isConstNode=!0}generateConst(e){return e.generateConst(this.getNodeType(e),this.value)}generate(e,t){const n=this.getNodeType(e);return Bv.test(n)&&Bv.test(t)?e.generateConst(t,this.value):e.format(this.generateConst(e),n,t)}}class Iv extends yv{static get type(){return"MemberNode"}constructor(e,t){super(),this.structNode=e,this.property=t,this.isMemberNode=!0}hasMember(e){return(!this.structNode.isMemberNode||!1!==this.structNode.hasMember(e))&&"void"!==this.structNode.getMemberType(e,this.property)}getNodeType(e){return!1===this.hasMember(e)?"float":this.structNode.getMemberType(e,this.property)}getMemberType(e,t){if(!1===this.hasMember(e))return"float";const n=this.getNodeType(e);return e.getStructTypeNode(n).getMemberType(e,t)}generate(e){if(!1===this.hasMember(e)){console.warn(`THREE.TSL: Member "${this.property}" does not exist in struct.`);const t=this.getNodeType(e);return e.generateConst(t)}return this.structNode.build(e)+"."+this.property}}let Lv=null;const jv=new Map;function Ov(e,t){if(jv.has(e))console.warn(`THREE.TSL: Redefinition of method chaining '${e}'.`);else{if("function"!=typeof t)throw new Error(`THREE.TSL: Node element ${e} is not a function`);jv.set(e,t),"assign"!==e&&(yv.prototype[e]=function(...e){return this.isStackNode?this.add(t(...e)):t(this,...e)},yv.prototype[e+"Assign"]=function(...e){return this.isStackNode?this.assign(e[0],t(...e)):this.assign(t(this,...e))})}}const zv=e=>(e=>e.replace(/r|s/g,"x").replace(/g|t/g,"y").replace(/b|p/g,"z").replace(/a|q/g,"w"))(e).split("").sort().join("");yv.prototype.assign=function(...e){if(!0!==this.isStackNode)return null!==Lv?Lv.assign(this,...e):console.error("THREE.TSL: No stack defined for assign operation. 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o=0;o<4;o++)t=Fv[e]+Fv[r]+Fv[s]+Fv[o],n=Hv[e]+Hv[r]+Hv[s]+Hv[o],i=Uv[e]+Uv[r]+Uv[s]+Uv[o],kv(t,n,i)}}}for(let e=0;e<32;e++)Rv[e]={get(){this._cache=this._cache||{};let t=this._cache[e];return void 0===t&&(t=new bv(this,new Dv(e,"uint")),this._cache[e]=t),t},set(t){this[e].assign(cA(t))}};Object.defineProperties(yv.prototype,Rv);const Xv=new WeakMap,Gv=function(e,t=null){for(const n in e)e[n]=cA(e[n],t);return e},Vv=function(e,t=null){const n=e.length;for(let i=0;i<n;i++)e[i]=cA(e[i],t);return e},Wv=function(e,t=null,n=null,i=null){function r(e){return null!==i?(e=cA(Object.assign(e,i)),!0===i.intent&&(e=e.toVarIntent())):e=cA(e),e}let s,o,a,l=t;function u(t){let n;return n=l?/[a-z]/i.test(l)?l+"()":l:e.type,void 0!==o&&t.length<o?(console.error(`THREE.TSL: "${n}" parameter length is less than minimum required.`),t.concat(new Array(o-t.length).fill(0))):void 0!==a&&t.length>a?(console.error(`THREE.TSL: "${n}" parameter length exceeds limit.`),t.slice(0,a)):t}return null===t?s=(...t)=>r(new e(...fA(u(t)))):null!==n?(n=cA(n),s=(...i)=>r(new e(t,...fA(u(i)),n))):s=(...n)=>r(new e(t,...fA(u(n)))),s.setParameterLength=(...e)=>(1===e.length?o=a=e[0]:2===e.length&&([o,a]=e),s),s.setName=e=>(l=e,s),s},Qv=function(e,...t){return cA(new e(...fA(t)))};class Zv extends yv{constructor(e,t){super(),this.shaderNode=e,this.rawInputs=t,this.isShaderCallNodeInternal=!0}getNodeType(e){return this.shaderNode.nodeType||this.getOutputNode(e).getNodeType(e)}getMemberType(e,t){return this.getOutputNode(e).getMemberType(e,t)}call(e){const{shaderNode:t,rawInputs:n}=this,i=e.getNodeProperties(t),r=e.getClosestSubBuild(t.subBuilds)||"",s=r||"default";if(i[s])return i[s];const o=e.subBuildFn;e.subBuildFn=r;let a=null;if(t.layout){let i=Xv.get(e.constructor);void 0===i&&(i=new WeakMap,Xv.set(e.constructor,i));let r=i.get(t);void 0===r&&(r=cA(e.buildFunctionNode(t)),i.set(t,r)),e.addInclude(r);const s=n?function(e){let t;hA(e);t=e[0]&&(e[0].isNode||Object.getPrototypeOf(e[0])!==Object.prototype)?[...e]:e[0];return t}(n):null;a=cA(r.call(s))}else{const i=new Proxy(e,{get:(e,t,n)=>{let i;return i=Symbol.iterator===t?function*(){yield}:Reflect.get(e,t,n),i}}),r=n?function(e){let t=0;return hA(e),new Proxy(e,{get:(n,i,r)=>{let s;if("length"===i)return s=e.length,s;if(Symbol.iterator===i)s=function*(){for(const t of e)yield cA(t)};else{if(e.length>0)if(Object.getPrototypeOf(e[0])===Object.prototype){const n=e[0];s=void 0===n[i]?n[t++]:Reflect.get(n,i,r)}else e[0]instanceof yv&&(s=void 0===e[i]?e[t++]:Reflect.get(e,i,r));else s=Reflect.get(n,i,r);s=cA(s)}return s}})}(n):null,s=Array.isArray(n)?n.length>0:null!==n,o=t.jsFunc,l=s||o.length>1?o(r,i):o(i);a=cA(l)}return e.subBuildFn=o,t.once&&(i[s]=a),a}setupOutput(e){return e.addStack(),e.stack.outputNode=this.call(e),e.removeStack()}getOutputNode(e){const t=e.getNodeProperties(this),n=e.getSubBuildOutput(this);return t[n]=t[n]||this.setupOutput(e),t[n].subBuild=e.getClosestSubBuild(this),t[n]}build(e,t=null){let n=null;const i=e.getBuildStage(),r=e.getNodeProperties(this),s=e.getSubBuildOutput(this),o=this.getOutputNode(e);if("setup"===i){const t=e.getSubBuildProperty("initialized",this);if(!0!==r[t]&&(r[t]=!0,r[s]=this.getOutputNode(e),r[s].build(e),this.shaderNode.subBuilds))for(const t of e.chaining){const n=e.getDataFromNode(t,"any");n.subBuilds=n.subBuilds||new Set;for(const e of this.shaderNode.subBuilds)n.subBuilds.add(e)}n=r[s]}else"analyze"===i?o.build(e,t):"generate"===i&&(n=o.build(e,t)||"");return n}}class Yv extends yv{constructor(e,t){super(t),this.jsFunc=e,this.layout=null,this.global=!0,this.once=!1}setLayout(e){return this.layout=e,this}call(e=null){return cA(new Zv(this,e))}setup(){return this.call()}}const Jv=[!1,!0],Kv=[0,1,2,3],qv=[-1,-2],_v=[.5,1.5,1/3,1e-6,1e6,Math.PI,2*Math.PI,1/Math.PI,2/Math.PI,1/(2*Math.PI),Math.PI/2],$v=new Map;for(const e of Jv)$v.set(e,new Dv(e));const eA=new Map;for(const e of Kv)eA.set(e,new Dv(e,"uint"));const tA=new Map([...eA].map((e=>new Dv(e.value,"int"))));for(const e of qv)tA.set(e,new Dv(e,"int"));const nA=new Map([...tA].map((e=>new Dv(e.value))));for(const e of _v)nA.set(e,new Dv(e));for(const e of _v)nA.set(-e,new Dv(-e));const iA={bool:$v,uint:eA,ints:tA,float:nA},rA=new Map([...$v,...nA]),sA=(e,t)=>rA.has(e)?rA.get(e):!0===e.isNode?e:new Dv(e,t),oA=function(e,t=null){return(...n)=>{for(const t of n)if(void 0===t)return console.error(`THREE.TSL: Invalid parameter for the type "${e}".`),cA(new Dv(0,e));if((0===n.length||!["bool","float","int","uint"].includes(e)&&n.every((e=>{const t=typeof e;return"object"!==t&&"function"!==t})))&&(n=[av(e,...n)]),1===n.length&&null!==t&&t.has(n[0]))return dA(t.get(n[0]));if(1===n.length){const t=sA(n[0],e);return t.nodeType===e?dA(t):dA(new wv(t,e))}const i=n.map((e=>sA(e)));return dA(new Mv(i,e))}},aA=e=>"object"==typeof e&&null!==e?e.value:e,lA=e=>null!=e?e.nodeType||e.convertTo||("string"==typeof e?e:null):null;function uA(e,t){return new Yv(e,t)}const cA=(e,t=null)=>function(e,t=null){const n=ov(e);return"node"===n?e:null===t&&("float"===n||"boolean"===n)||n&&"shader"!==n&&"string"!==n?cA(sA(e,t)):"shader"===n?e.isFn?e:xA(e):e}(e,t),dA=(e,t=null)=>cA(e,t).toVarIntent(),hA=(e,t=null)=>new Gv(e,t),fA=(e,t=null)=>new Vv(e,t),pA=(e,t=null,n=null,i=null)=>new Wv(e,t,n,i),gA=(e,...t)=>new Qv(e,...t),mA=(e,t=null,n=null,i={})=>new Wv(e,t,n,{intent:!0,...i});let vA=0;class AA extends yv{constructor(e,t=null){super();let n=null;null!==t&&("object"==typeof t?n=t.return:("string"==typeof t?n=t:console.error("THREE.TSL: Invalid layout type."),t=null)),this.shaderNode=new uA(e,n),null!==t&&this.setLayout(t),this.isFn=!0}setLayout(e){const t=this.shaderNode.nodeType;if("object"!=typeof e.inputs){const n={name:"fn"+vA++,type:t,inputs:[]};for(const t in e)"return"!==t&&n.inputs.push({name:t,type:e[t]});e=n}return this.shaderNode.setLayout(e),this}getNodeType(e){return this.shaderNode.getNodeType(e)||"float"}call(...e){const t=this.shaderNode.call(e);return"void"===this.shaderNode.nodeType&&t.toStack(),t.toVarIntent()}once(e=null){return this.shaderNode.once=!0,this.shaderNode.subBuilds=e,this}generate(e){const t=this.getNodeType(e);return console.error('THREE.TSL: "Fn()" was declared but not invoked. 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n===e&&(e=av(n)),e=e&&!0===e.isNode?e.node&&e.node.value||e.value:e,cA(new Px(e,n))};class Bx extends Cv{static get type(){return"ArrayNode"}constructor(e,t,n=null){super(e),this.count=t,this.values=n,this.isArrayNode=!0}getArrayCount(){return this.count}getNodeType(e){return null===this.nodeType&&(this.nodeType=this.values[0].getNodeType(e)),this.nodeType}getElementType(e){return this.getNodeType(e)}generate(e){const t=this.getNodeType(e);return e.generateArray(t,this.count,this.values)}}const Dx=(...e)=>{let t;if(1===e.length){const n=e[0];t=new Bx(null,n.length,n)}else{const n=e[0],i=e[1];t=new Bx(n,i)}return cA(t)};Ov("toArray",((e,t)=>Dx(Array(t).fill(e))));class Ix extends Cv{static get type(){return"AssignNode"}constructor(e,t){super(),this.targetNode=e,this.sourceNode=t,this.isAssignNode=!0}hasDependencies(){return!1}getNodeType(e,t){return"void"!==t?this.targetNode.getNodeType(e):"void"}needsSplitAssign(e){const{targetNode:t}=this;if(!1===e.isAvailable("swizzleAssign")&&t.isSplitNode&&t.components.length>1){const n=e.getTypeLength(t.node.getNodeType(e));return vv.join("").slice(0,n)!==t.components}return!1}setup(e){const{targetNode:t,sourceNode:n}=this,i=t.getScope();e.getNodeProperties(i).assign=!0;const r=e.getNodeProperties(this);r.sourceNode=n,r.targetNode=t.context({assign:!0})}generate(e,t){const{targetNode:n,sourceNode:i}=e.getNodeProperties(this),r=this.needsSplitAssign(e),s=n.build(e),o=n.getNodeType(e),a=i.build(e,o),l=i.getNodeType(e),u=e.getDataFromNode(this);let c;if(!0===u.initialized)"void"!==t&&(c=s);else if(r){const i=e.getVarFromNode(this,null,o),r=e.getPropertyName(i);e.addLineFlowCode(`${r} = ${a}`,this);const l=n.node,u=l.node.context({assign:!0}).build(e);for(let t=0;t<l.components.length;t++){const n=l.components[t];e.addLineFlowCode(`${u}.${n} = ${r}[ ${t} ]`,this)}"void"!==t&&(c=s)}else c=`${s} = ${a}`,"void"!==t&&"void"!==l||(e.addLineFlowCode(c,this),"void"!==t&&(c=s));return u.initialized=!0,e.format(c,o,t)}}const Lx=pA(Ix).setParameterLength(2);Ov("assign",Lx);class jx extends Cv{static get type(){return"FunctionCallNode"}constructor(e=null,t={}){super(),this.functionNode=e,this.parameters=t}setParameters(e){return this.parameters=e,this}getParameters(){return this.parameters}getNodeType(e){return this.functionNode.getNodeType(e)}getMemberType(e,t){return this.functionNode.getMemberType(e,t)}generate(e){const t=[],n=this.functionNode,i=n.getInputs(e),r=this.parameters,s=(t,n)=>{const i=n.type;let r;return r="pointer"===i?"&"+t.build(e):t.build(e,i),r};if(Array.isArray(r)){if(r.length>i.length)console.error("THREE.TSL: The number of provided parameters exceeds the expected number of inputs in 'Fn()'."),r.length=i.length;else if(r.length<i.length)for(console.error("THREE.TSL: The number of provided parameters is less than the expected number of inputs in 'Fn()'.");r.length<i.length;)r.push(EA(0));for(let e=0;e<r.length;e++)t.push(s(r[e],i[e]))}else for(const e of i){const n=r[e.name];void 0!==n?t.push(s(n,e)):(console.error(`THREE.TSL: Input '${e.name}' not found in 'Fn()'.`),t.push(s(EA(0),e)))}return`${n.build(e,"property")}( ${t.join(", ")} )`}}const Ox=(e,...t)=>(t=t.length>1||t[0]&&!0===t[0].isNode?fA(t):hA(t[0]),cA(new jx(cA(e),t)));Ov("call",Ox);const zx={"==":"equal","!=":"notEqual","<":"lessThan",">":"greaterThan","<=":"lessThanEqual",">=":"greaterThanEqual","%":"mod"};class Rx extends Cv{static get type(){return"OperatorNode"}constructor(e,t,n,...i){if(super(),i.length>0){let r=new Rx(e,t,n);for(let t=0;t<i.length-1;t++)r=new Rx(e,r,i[t]);t=r,n=i[i.length-1]}this.op=e,this.aNode=t,this.bNode=n,this.isOperatorNode=!0}getOperatorMethod(e,t){return e.getMethod(zx[this.op],t)}getNodeType(e,t=null){const n=this.op,i=this.aNode,r=this.bNode,s=i.getNodeType(e),o=r?r.getNodeType(e):null;if("void"===s||"void"===o)return t||"void";if("%"===n)return s;if("~"===n||"&"===n||"|"===n||"^"===n||">>"===n||"<<"===n)return e.getIntegerType(s);if("!"===n||"&&"===n||"||"===n||"^^"===n)return"bool";if("=="===n||"!="===n||"<"===n||">"===n||"<="===n||">="===n){const t=Math.max(e.getTypeLength(s),e.getTypeLength(o));return t>1?`bvec${t}`:"bool"}if(e.isMatrix(s)){if("float"===o)return s;if(e.isVector(o))return e.getVectorFromMatrix(s);if(e.isMatrix(o))return s}else if(e.isMatrix(o)){if("float"===s)return o;if(e.isVector(s))return e.getVectorFromMatrix(o)}return e.getTypeLength(o)>e.getTypeLength(s)?o:s}generate(e,t){const n=this.op,{aNode:i,bNode:r}=this,s=this.getNodeType(e,t);let o=null,a=null;"void"!==s?(o=i.getNodeType(e),a=r?r.getNodeType(e):null,"<"===n||">"===n||"<="===n||">="===n||"=="===n||"!="===n?e.isVector(o)?a=o:e.isVector(a)?o=a:o!==a&&(o=a="float"):">>"===n||"<<"===n?(o=s,a=e.changeComponentType(a,"uint")):"%"===n?(o=s,a=e.isInteger(o)&&e.isInteger(a)?a:o):e.isMatrix(o)?"float"===a?a="float":e.isVector(a)?a=e.getVectorFromMatrix(o):e.isMatrix(a)||(o=a=s):o=e.isMatrix(a)?"float"===o?"float":e.isVector(o)?e.getVectorFromMatrix(a):a=s:a=s):o=a=s;const l=i.build(e,o),u=r?r.build(e,a):null,c=e.getFunctionOperator(n);if("void"!==t){const i=e.renderer.coordinateSystem===as;if("=="===n||"!="===n||"<"===n||">"===n||"<="===n||">="===n)return i&&e.isVector(o)?e.format(`${this.getOperatorMethod(e,t)}( ${l}, ${u} )`,s,t):e.format(`( ${l} ${n} ${u} )`,s,t);if("%"===n)return e.isInteger(a)?e.format(`( ${l} % ${u} )`,s,t):e.format(`${this.getOperatorMethod(e,s)}( ${l}, ${u} )`,s,t);if("!"===n||"~"===n)return e.format(`(${n}${l})`,o,t);if(c)return e.format(`${c}( ${l}, ${u} )`,s,t);if(e.isMatrix(o)&&"float"===a)return e.format(`( ${u} ${n} ${l} )`,s,t);if("float"===o&&e.isMatrix(a))return e.format(`${l} ${n} ${u}`,s,t);{let r=`( ${l} ${n} ${u} )`;return!i&&"bool"===s&&e.isVector(o)&&e.isVector(a)&&(r=`all${r}`),e.format(r,s,t)}}if("void"!==o)return c?e.format(`${c}( ${l}, ${u} )`,s,t):e.isMatrix(o)&&"float"===a?e.format(`${u} ${n} ${l}`,s,t):e.format(`${l} ${n} ${u}`,s,t)}serialize(e){super.serialize(e),e.op=this.op}deserialize(e){super.deserialize(e),this.op=e.op}}const kx=mA(Rx,"+").setParameterLength(2,1/0).setName("add"),Fx=mA(Rx,"-").setParameterLength(2,1/0).setName("sub"),Hx=mA(Rx,"*").setParameterLength(2,1/0).setName("mul"),Ux=mA(Rx,"/").setParameterLength(2,1/0).setName("div"),Xx=mA(Rx,"%").setParameterLength(2).setName("mod"),Gx=mA(Rx,"==").setParameterLength(2).setName("equal"),Vx=mA(Rx,"!=").setParameterLength(2).setName("notEqual"),Wx=mA(Rx,"<").setParameterLength(2).setName("lessThan"),Qx=mA(Rx,">").setParameterLength(2).setName("greaterThan"),Zx=mA(Rx,"<=").setParameterLength(2).setName("lessThanEqual"),Yx=mA(Rx,">=").setParameterLength(2).setName("greaterThanEqual"),Jx=mA(Rx,"&&").setParameterLength(2,1/0).setName("and"),Kx=mA(Rx,"||").setParameterLength(2,1/0).setName("or"),qx=mA(Rx,"!").setParameterLength(1).setName("not"),_x=mA(Rx,"^^").setParameterLength(2).setName("xor"),$x=mA(Rx,"&").setParameterLength(2).setName("bitAnd"),ey=mA(Rx,"~").setParameterLength(2).setName("bitNot"),ty=mA(Rx,"|").setParameterLength(2).setName("bitOr"),ny=mA(Rx,"^").setParameterLength(2).setName("bitXor"),iy=mA(Rx,"<<").setParameterLength(2).setName("shiftLeft"),ry=mA(Rx,">>").setParameterLength(2).setName("shiftRight"),sy=xA((([e])=>(e.addAssign(1),e))),oy=xA((([e])=>(e.subAssign(1),e))),ay=xA((([e])=>{const t=TA(e).toConst();return e.addAssign(1),t})),ly=xA((([e])=>{const t=TA(e).toConst();return e.subAssign(1),t}));Ov("add",kx),Ov("sub",Fx),Ov("mul",Hx),Ov("div",Ux),Ov("mod",Xx),Ov("equal",Gx),Ov("notEqual",Vx),Ov("lessThan",Wx),Ov("greaterThan",Qx),Ov("lessThanEqual",Zx),Ov("greaterThanEqual",Yx),Ov("and",Jx),Ov("or",Kx),Ov("not",qx),Ov("xor",_x),Ov("bitAnd",$x),Ov("bitNot",ey),Ov("bitOr",ty),Ov("bitXor",ny),Ov("shiftLeft",iy),Ov("shiftRight",ry),Ov("incrementBefore",sy),Ov("decrementBefore",oy),Ov("increment",ay),Ov("decrement",ly);const uy=(e,t)=>(console.warn('THREE.TSL: "modInt()" is deprecated. Use "mod( int( ... ) )" instead.'),Xx(TA(e),TA(t)));Ov("modInt",uy);class cy extends Cv{static get type(){return"MathNode"}constructor(e,t,n=null,i=null){if(super(),(e===cy.MAX||e===cy.MIN)&&arguments.length>3){let r=new cy(e,t,n);for(let t=2;t<arguments.length-1;t++)r=new cy(e,r,arguments[t]);t=r,n=arguments[arguments.length-1],i=null}this.method=e,this.aNode=t,this.bNode=n,this.cNode=i,this.isMathNode=!0}getInputType(e){const t=this.aNode.getNodeType(e),n=this.bNode?this.bNode.getNodeType(e):null,i=this.cNode?this.cNode.getNodeType(e):null,r=e.isMatrix(t)?0:e.getTypeLength(t),s=e.isMatrix(n)?0:e.getTypeLength(n),o=e.isMatrix(i)?0:e.getTypeLength(i);return r>s&&r>o?t:s>o?n:o>r?i:t}getNodeType(e){const t=this.method;return t===cy.LENGTH||t===cy.DISTANCE||t===cy.DOT?"float":t===cy.CROSS?"vec3":t===cy.ALL||t===cy.ANY?"bool":t===cy.EQUALS?e.changeComponentType(this.aNode.getNodeType(e),"bool"):this.getInputType(e)}setup(e){const{aNode:t,bNode:n,method:i}=this;let r=null;if(i===cy.ONE_MINUS)r=Fx(1,t);else if(i===cy.RECIPROCAL)r=Ux(1,t);else if(i===cy.DIFFERENCE)r=Ly(Fx(t,n));else if(i===cy.TRANSFORM_DIRECTION){let i=t,s=n;e.isMatrix(i.getNodeType(e))?s=RA(LA(s),0):i=RA(LA(i),0);const o=Hx(i,s).xyz;r=Ey(o)}return null!==r?r:super.setup(e)}generate(e,t){if(e.getNodeProperties(this).outputNode)return super.generate(e,t);let n=this.method;const i=this.getNodeType(e),r=this.getInputType(e),s=this.aNode,o=this.bNode,a=this.cNode,l=e.renderer.coordinateSystem;if(n===cy.NEGATE)return e.format("( - "+s.build(e,r)+" )",i,t);{const u=[];return n===cy.CROSS?u.push(s.build(e,i),o.build(e,i)):l===as&&n===cy.STEP?u.push(s.build(e,1===e.getTypeLength(s.getNodeType(e))?"float":r),o.build(e,r)):l!==as||n!==cy.MIN&&n!==cy.MAX?n===cy.REFRACT?u.push(s.build(e,r),o.build(e,r),a.build(e,"float")):n===cy.MIX?u.push(s.build(e,r),o.build(e,r),a.build(e,1===e.getTypeLength(a.getNodeType(e))?"float":r)):(l===ls&&n===cy.ATAN&&null!==o&&(n="atan2"),"fragment"===e.shaderStage||n!==cy.DFDX&&n!==cy.DFDY||(console.warn(`THREE.TSL: '${n}' is not supported in the ${e.shaderStage} stage.`),n="/*"+n+"*/"),u.push(s.build(e,r)),null!==o&&u.push(o.build(e,r)),null!==a&&u.push(a.build(e,r))):u.push(s.build(e,r),o.build(e,1===e.getTypeLength(o.getNodeType(e))?"float":r)),e.format(`${e.getMethod(n,i)}( ${u.join(", ")} )`,i,t)}}serialize(e){super.serialize(e),e.method=this.method}deserialize(e){super.deserialize(e),this.method=e.method}}cy.ALL="all",cy.ANY="any",cy.RADIANS="radians",cy.DEGREES="degrees",cy.EXP="exp",cy.EXP2="exp2",cy.LOG="log",cy.LOG2="log2",cy.SQRT="sqrt",cy.INVERSE_SQRT="inversesqrt",cy.FLOOR="floor",cy.CEIL="ceil",cy.NORMALIZE="normalize",cy.FRACT="fract",cy.SIN="sin",cy.COS="cos",cy.TAN="tan",cy.ASIN="asin",cy.ACOS="acos",cy.ATAN="atan",cy.ABS="abs",cy.SIGN="sign",cy.LENGTH="length",cy.NEGATE="negate",cy.ONE_MINUS="oneMinus",cy.DFDX="dFdx",cy.DFDY="dFdy",cy.ROUND="round",cy.RECIPROCAL="reciprocal",cy.TRUNC="trunc",cy.FWIDTH="fwidth",cy.TRANSPOSE="transpose",cy.DETERMINANT="determinant",cy.INVERSE="inverse",cy.EQUALS="equals",cy.MIN="min",cy.MAX="max",cy.STEP="step",cy.REFLECT="reflect",cy.DISTANCE="distance",cy.DIFFERENCE="difference",cy.DOT="dot",cy.CROSS="cross",cy.POW="pow",cy.TRANSFORM_DIRECTION="transformDirection",cy.MIX="mix",cy.CLAMP="clamp",cy.REFRACT="refract",cy.SMOOTHSTEP="smoothstep",cy.FACEFORWARD="faceforward";const dy=EA(1e-6),hy=EA(Math.PI),fy=(Math.PI,mA(cy,cy.ALL).setParameterLength(1)),py=mA(cy,cy.ANY).setParameterLength(1),gy=mA(cy,cy.RADIANS).setParameterLength(1),my=mA(cy,cy.DEGREES).setParameterLength(1),vy=mA(cy,cy.EXP).setParameterLength(1),Ay=mA(cy,cy.EXP2).setParameterLength(1),xy=mA(cy,cy.LOG).setParameterLength(1),yy=mA(cy,cy.LOG2).setParameterLength(1),by=mA(cy,cy.SQRT).setParameterLength(1),wy=mA(cy,cy.INVERSE_SQRT).setParameterLength(1),Cy=mA(cy,cy.FLOOR).setParameterLength(1),My=mA(cy,cy.CEIL).setParameterLength(1),Ey=mA(cy,cy.NORMALIZE).setParameterLength(1),Ty=mA(cy,cy.FRACT).setParameterLength(1),Sy=mA(cy,cy.SIN).setParameterLength(1),Py=mA(cy,cy.COS).setParameterLength(1),Ny=mA(cy,cy.TAN).setParameterLength(1),By=mA(cy,cy.ASIN).setParameterLength(1),Dy=mA(cy,cy.ACOS).setParameterLength(1),Iy=mA(cy,cy.ATAN).setParameterLength(1,2),Ly=mA(cy,cy.ABS).setParameterLength(1),jy=mA(cy,cy.SIGN).setParameterLength(1),Oy=mA(cy,cy.LENGTH).setParameterLength(1),zy=mA(cy,cy.NEGATE).setParameterLength(1),Ry=mA(cy,cy.ONE_MINUS).setParameterLength(1),ky=mA(cy,cy.DFDX).setParameterLength(1),Fy=mA(cy,cy.DFDY).setParameterLength(1),Hy=mA(cy,cy.ROUND).setParameterLength(1),Uy=mA(cy,cy.RECIPROCAL).setParameterLength(1),Xy=mA(cy,cy.TRUNC).setParameterLength(1),Gy=mA(cy,cy.FWIDTH).setParameterLength(1),Vy=mA(cy,cy.TRANSPOSE).setParameterLength(1),Wy=mA(cy,cy.DETERMINANT).setParameterLength(1),Qy=mA(cy,cy.INVERSE).setParameterLength(1),Zy=(e,t)=>(console.warn('THREE.TSL: "equals" is deprecated. Use "equal" inside a vector instead, like: "bvec*( equal( ... ) )"'),Gx(e,t)),Yy=mA(cy,cy.MIN).setParameterLength(2,1/0),Jy=mA(cy,cy.MAX).setParameterLength(2,1/0),Ky=mA(cy,cy.STEP).setParameterLength(2),qy=mA(cy,cy.REFLECT).setParameterLength(2),_y=mA(cy,cy.DISTANCE).setParameterLength(2),$y=mA(cy,cy.DIFFERENCE).setParameterLength(2),eb=mA(cy,cy.DOT).setParameterLength(2),tb=mA(cy,cy.CROSS).setParameterLength(2),nb=mA(cy,cy.POW).setParameterLength(2),ib=e=>Hx(e,e),rb=e=>Hx(e,e,e),sb=e=>Hx(e,e,e,e),ob=mA(cy,cy.TRANSFORM_DIRECTION).setParameterLength(2),ab=e=>Hx(jy(e),nb(Ly(e),1/3)),lb=e=>eb(e,e),ub=mA(cy,cy.MIX).setParameterLength(3),cb=(e,t=0,n=1)=>cA(new cy(cy.CLAMP,cA(e),cA(t),cA(n))),db=e=>cb(e),hb=mA(cy,cy.REFRACT).setParameterLength(3),fb=mA(cy,cy.SMOOTHSTEP).setParameterLength(3),pb=mA(cy,cy.FACEFORWARD).setParameterLength(3),gb=xA((([e])=>{const t=eb(e.xy,NA(12.9898,78.233)),n=Xx(t,hy);return Ty(Sy(n).mul(43758.5453))})),mb=(e,t,n)=>ub(t,n,e),vb=(e,t,n)=>fb(t,n,e),Ab=(e,t)=>Ky(t,e),xb=(e,t)=>(console.warn('THREE.TSL: "atan2" is overloaded. Use "atan" instead.'),Iy(e,t));Ov("all",fy),Ov("any",py),Ov("equals",Zy),Ov("radians",gy),Ov("degrees",my),Ov("exp",vy),Ov("exp2",Ay),Ov("log",xy),Ov("log2",yy),Ov("sqrt",by),Ov("inverseSqrt",wy),Ov("floor",Cy),Ov("ceil",My),Ov("normalize",Ey),Ov("fract",Ty),Ov("sin",Sy),Ov("cos",Py),Ov("tan",Ny),Ov("asin",By),Ov("acos",Dy),Ov("atan",Iy),Ov("abs",Ly),Ov("sign",jy),Ov("length",Oy),Ov("lengthSq",lb),Ov("negate",zy),Ov("oneMinus",Ry),Ov("dFdx",ky),Ov("dFdy",Fy),Ov("round",Hy),Ov("reciprocal",Uy),Ov("trunc",Xy),Ov("fwidth",Gy),Ov("atan2",xb),Ov("min",Yy),Ov("max",Jy),Ov("step",Ab),Ov("reflect",qy),Ov("distance",_y),Ov("dot",eb),Ov("cross",tb),Ov("pow",nb),Ov("pow2",ib),Ov("pow3",rb),Ov("pow4",sb),Ov("transformDirection",ob),Ov("mix",mb),Ov("clamp",cb),Ov("refract",hb),Ov("smoothstep",vb),Ov("faceForward",pb),Ov("difference",$y),Ov("saturate",db),Ov("cbrt",ab),Ov("transpose",Vy),Ov("determinant",Wy),Ov("inverse",Qy),Ov("rand",gb);class yb extends yv{static get type(){return"ConditionalNode"}constructor(e,t,n=null){super(),this.condNode=e,this.ifNode=t,this.elseNode=n}getNodeType(e){const{ifNode:t,elseNode:n}=e.getNodeProperties(this);if(void 0===t)return e.flowBuildStage(this,"setup"),this.getNodeType(e);const i=t.getNodeType(e);if(null!==n){const t=n.getNodeType(e);if(e.getTypeLength(t)>e.getTypeLength(i))return t}return i}setup(e){const t=this.condNode.cache(),n=this.ifNode.cache(),i=this.elseNode?this.elseNode.cache():null,r=e.context.nodeBlock;e.getDataFromNode(n).parentNodeBlock=r,null!==i&&(e.getDataFromNode(i).parentNodeBlock=r);const s=e.context.uniformFlow,o=e.getNodeProperties(this);o.condNode=t,o.ifNode=s?n:n.context({nodeBlock:n}),o.elseNode=i?s?i:i.context({nodeBlock:i}):null}generate(e,t){const n=this.getNodeType(e),i=e.getDataFromNode(this);if(void 0!==i.nodeProperty)return i.nodeProperty;const{condNode:r,ifNode:s,elseNode:o}=e.getNodeProperties(this),a=e.currentFunctionNode,l="void"!==t,u=l?ZA(n).build(e):"";i.nodeProperty=u;const c=r.build(e,"bool");if(e.context.uniformFlow&&null!==o){const i=s.build(e,n),r=o.build(e,n),a=e.getTernary(c,i,r);return e.format(a,n,t)}e.addFlowCode(`\n${e.tab}if ( ${c} ) {\n\n`).addFlowTab();let d=s.build(e,n);if(d&&(l?d=u+" = "+d+";":(d="return "+d+";",null===a&&(console.warn("THREE.TSL: Return statement used in an inline 'Fn()'. Define a layout struct to allow return values."),d="// "+d))),e.removeFlowTab().addFlowCode(e.tab+"\t"+d+"\n\n"+e.tab+"}"),null!==o){e.addFlowCode(" else {\n\n").addFlowTab();let t=o.build(e,n);t&&(l?t=u+" = "+t+";":(t="return "+t+";",null===a&&(console.warn("THREE.TSL: Return statement used in an inline 'Fn()'. Define a layout struct to allow return values."),t="// "+t))),e.removeFlowTab().addFlowCode(e.tab+"\t"+t+"\n\n"+e.tab+"}\n\n")}else e.addFlowCode("\n\n");return e.format(u,n,t)}}const bb=pA(yb).setParameterLength(2,3);Ov("select",bb);class wb extends yv{static get type(){return"ContextNode"}constructor(e,t={}){super(),this.isContextNode=!0,this.node=e,this.value=t}getScope(){return this.node.getScope()}getNodeType(e){return this.node.getNodeType(e)}getMemberType(e,t){return this.node.getMemberType(e,t)}analyze(e){const t=e.getContext();e.setContext({...e.context,...this.value}),this.node.build(e),e.setContext(t)}setup(e){const t=e.getContext();e.setContext({...e.context,...this.value}),this.node.build(e),e.setContext(t)}generate(e,t){const n=e.getContext();e.setContext({...e.context,...this.value});const i=this.node.build(e,t);return e.setContext(n),i}}const Cb=pA(wb).setParameterLength(1,2),Mb=e=>Cb(e,{uniformFlow:!0}),Eb=(e,t)=>Cb(e,{nodeName:t});function Tb(e,t){return console.warn('THREE.TSL: "label()" has been deprecated. Use "setName()" instead.'),Eb(e,t)}Ov("context",Cb),Ov("label",Tb),Ov("uniformFlow",Mb),Ov("setName",Eb);class Sb extends yv{static get type(){return"VarNode"}constructor(e,t=null,n=!1){super(),this.node=e,this.name=t,this.global=!0,this.isVarNode=!0,this.readOnly=n,this.parents=!0,this.intent=!1}setIntent(e){return this.intent=e,this}getIntent(){return this.intent}getMemberType(e,t){return this.node.getMemberType(e,t)}getElementType(e){return this.node.getElementType(e)}getNodeType(e){return this.node.getNodeType(e)}getArrayCount(e){return this.node.getArrayCount(e)}build(...e){if(!0===this.intent){if(!0!==e[0].getNodeProperties(this).assign)return this.node.build(...e)}return super.build(...e)}generate(e){const{node:t,name:n,readOnly:i}=this,{renderer:r}=e,s=!0===r.backend.isWebGPUBackend;let o=!1,a=!1;i&&(o=e.isDeterministic(t),a=s?i:o);const l=e.getVectorType(this.getNodeType(e)),u=t.build(e,l),c=e.getVarFromNode(this,n,l,void 0,a),d=e.getPropertyName(c);let h=d;if(a)if(s)h=o?`const ${d}`:`let ${d}`;else{const n=t.getArrayCount(e);h=`const ${e.getVar(c.type,d,n)}`}return e.addLineFlowCode(`${h} = ${u}`,this),d}}const Pb=pA(Sb),Nb=(e,t=null)=>Pb(e,t).toStack(),Bb=(e,t=null)=>Pb(e,t,!0).toStack(),Db=e=>null===bA()?e:Pb(e).setIntent(!0).toStack();Ov("toVar",Nb),Ov("toConst",Bb),Ov("toVarIntent",Db);class Ib extends yv{static get type(){return"SubBuild"}constructor(e,t,n=null){super(n),this.node=e,this.name=t,this.isSubBuildNode=!0}getNodeType(e){if(null!==this.nodeType)return this.nodeType;e.addSubBuild(this.name);const t=this.node.getNodeType(e);return e.removeSubBuild(),t}build(e,...t){e.addSubBuild(this.name);const n=this.node.build(e,...t);return e.removeSubBuild(),n}}const Lb=(e,t,n=null)=>cA(new Ib(cA(e),t,n));class jb extends yv{static get type(){return"VaryingNode"}constructor(e,t=null){super(),this.node=e,this.name=t,this.isVaryingNode=!0,this.interpolationType=null,this.interpolationSampling=null,this.global=!0}setInterpolation(e,t=null){return this.interpolationType=e,this.interpolationSampling=t,this}getHash(e){return this.name||super.getHash(e)}getNodeType(e){return this.node.getNodeType(e)}setupVarying(e){const t=e.getNodeProperties(this);let n=t.varying;if(void 0===n){const i=this.name,r=this.getNodeType(e),s=this.interpolationType,o=this.interpolationSampling;t.varying=n=e.getVaryingFromNode(this,i,r,s,o),t.node=Lb(this.node,"VERTEX")}return n.needsInterpolation||(n.needsInterpolation="fragment"===e.shaderStage),n}setup(e){this.setupVarying(e),e.flowNodeFromShaderStage(dv.VERTEX,this.node)}analyze(e){this.setupVarying(e),e.flowNodeFromShaderStage(dv.VERTEX,this.node)}generate(e){const t=e.getSubBuildProperty("property",e.currentStack),n=e.getNodeProperties(this),i=this.setupVarying(e);if(void 0===n[t]){const r=this.getNodeType(e),s=e.getPropertyName(i,dv.VERTEX);e.flowNodeFromShaderStage(dv.VERTEX,n.node,r,s),n[t]=s}return e.getPropertyName(i)}}const Ob=pA(jb).setParameterLength(1,2),zb=e=>Ob(e);Ov("toVarying",Ob),Ov("toVertexStage",zb),Ov("varying",((...e)=>(console.warn("THREE.TSL: .varying() has been renamed to .toVarying()."),Ob(...e)))),Ov("vertexStage",((...e)=>(console.warn("THREE.TSL: .vertexStage() has been renamed to .toVertexStage()."),Ob(...e))));const Rb=xA((([e])=>{const t=e.mul(.9478672986).add(.0521327014).pow(2.4),n=e.mul(.0773993808),i=e.lessThanEqual(.04045);return ub(t,n,i)})).setLayout({name:"sRGBTransferEOTF",type:"vec3",inputs:[{name:"color",type:"vec3"}]}),kb=xA((([e])=>{const t=e.pow(.41666).mul(1.055).sub(.055),n=e.mul(12.92),i=e.lessThanEqual(.0031308);return ub(t,n,i)})).setLayout({name:"sRGBTransferOETF",type:"vec3",inputs:[{name:"color",type:"vec3"}]}),Fb="WorkingColorSpace";class Hb extends Cv{static get type(){return"ColorSpaceNode"}constructor(e,t,n){super("vec4"),this.colorNode=e,this.source=t,this.target=n}resolveColorSpace(e,t){return t===Fb?ks.workingColorSpace:"OutputColorSpace"===t?e.context.outputColorSpace||e.renderer.outputColorSpace:t}setup(e){const{colorNode:t}=this,n=this.resolveColorSpace(e,this.source),i=this.resolveColorSpace(e,this.target);let r=t;return!1!==ks.enabled&&n!==i&&n&&i?(ks.getTransfer(n)===es&&(r=RA(Rb(r.rgb),r.a)),ks.getPrimaries(n)!==ks.getPrimaries(i)&&(r=RA(XA(ks._getMatrix(new Ps,n,i)).mul(r.rgb),r.a)),ks.getTransfer(i)===es&&(r=RA(kb(r.rgb),r.a)),r):r}}const Ub=(e,t)=>cA(new Hb(cA(e),Fb,t)),Xb=(e,t)=>cA(new Hb(cA(e),t,Fb));Ov("workingToColorSpace",Ub),Ov("colorSpaceToWorking",Xb);let Gb=class extends bv{static get type(){return"ReferenceElementNode"}constructor(e,t){super(e,t),this.referenceNode=e,this.isReferenceElementNode=!0}getNodeType(){return this.referenceNode.uniformType}generate(e){const t=super.generate(e),n=this.referenceNode.getNodeType(),i=this.getNodeType();return e.format(t,n,i)}};class Vb extends yv{static get type(){return"ReferenceBaseNode"}constructor(e,t,n=null,i=null){super(),this.property=e,this.uniformType=t,this.object=n,this.count=i,this.properties=e.split("."),this.reference=n,this.node=null,this.group=null,this.updateType=hv.OBJECT}setGroup(e){return this.group=e,this}element(e){return cA(new Gb(this,cA(e)))}setNodeType(e){const t=Nx(null,e);null!==this.group&&t.setGroup(this.group),this.node=t}getNodeType(e){return null===this.node&&(this.updateReference(e),this.updateValue()),this.node.getNodeType(e)}getValueFromReference(e=this.reference){const{properties:t}=this;let n=e[t[0]];for(let e=1;e<t.length;e++)n=n[t[e]];return n}updateReference(e){return this.reference=null!==this.object?this.object:e.object,this.reference}setup(){return this.updateValue(),this.node}update(){this.updateValue()}updateValue(){null===this.node&&this.setNodeType(this.uniformType);const e=this.getValueFromReference();Array.isArray(e)?this.node.array=e:this.node.value=e}}class Wb extends Vb{static get type(){return"RendererReferenceNode"}constructor(e,t,n=null){super(e,t,n),this.renderer=n,this.setGroup(Tx)}updateReference(e){return this.reference=null!==this.renderer?this.renderer:e.renderer,this.reference}}const Qb=(e,t,n=null)=>cA(new Wb(e,t,n));class Zb extends Cv{static get type(){return"ToneMappingNode"}constructor(e,t=Jb,n=null){super("vec3"),this.toneMapping=e,this.exposureNode=t,this.colorNode=n}customCacheKey(){return ev(this.toneMapping)}setup(e){const t=this.colorNode||e.context.color,n=this.toneMapping;if(0===n)return t;let i=null;const r=e.renderer.library.getToneMappingFunction(n);return null!==r?i=RA(r(t.rgb,this.exposureNode),t.a):(console.error("ToneMappingNode: Unsupported Tone Mapping configuration.",n),i=t),i}}const Yb=(e,t,n)=>cA(new Zb(e,cA(t),cA(n))),Jb=Qb("toneMappingExposure","float");Ov("toneMapping",((e,t,n)=>Yb(t,n,e)));class Kb extends Nv{static get type(){return"BufferAttributeNode"}constructor(e,t=null,n=0,i=0){super(e,t),this.isBufferNode=!0,this.bufferType=t,this.bufferStride=n,this.bufferOffset=i,this.usage=rs,this.instanced=!1,this.attribute=null,this.global=!0,e&&!0===e.isBufferAttribute&&(this.attribute=e,this.usage=e.usage,this.instanced=e.isInstancedBufferAttribute)}getHash(e){if(0===this.bufferStride&&0===this.bufferOffset){let t=e.globalCache.getData(this.value);return void 0===t&&(t={node:this},e.globalCache.setData(this.value,t)),t.node.uuid}return this.uuid}getNodeType(e){return null===this.bufferType&&(this.bufferType=e.getTypeFromAttribute(this.attribute)),this.bufferType}setup(e){if(null!==this.attribute)return;const t=this.getNodeType(e),n=this.value,i=e.getTypeLength(t),r=this.bufferStride||i,s=this.bufferOffset,o=!0===n.isInterleavedBuffer?n:new Cl(n,r),a=new El(o,i,s);o.setUsage(this.usage),this.attribute=a,this.attribute.isInstancedBufferAttribute=this.instanced}generate(e){const t=this.getNodeType(e),n=e.getBufferAttributeFromNode(this,t),i=e.getPropertyName(n);let r=null;if("vertex"===e.shaderStage||"compute"===e.shaderStage)this.name=i,r=i;else{r=Ob(this).build(e,t)}return r}getInputType(){return"bufferAttribute"}setUsage(e){return this.usage=e,this.attribute&&!0===this.attribute.isBufferAttribute&&(this.attribute.usage=e),this}setInstanced(e){return this.instanced=e,this}}const qb=(e,t=null,n=0,i=0)=>cA(new Kb(e,t,n,i)),_b=(e,t=null,n=0,i=0)=>qb(e,t,n,i).setUsage(ss),$b=(e,t=null,n=0,i=0)=>qb(e,t,n,i).setInstanced(!0),ew=(e,t=null,n=0,i=0)=>_b(e,t,n,i).setInstanced(!0);Ov("toAttribute",(e=>qb(e.value)));class tw extends yv{static get type(){return"ComputeNode"}constructor(e,t){super("void"),this.isComputeNode=!0,this.computeNode=e,this.workgroupSize=t,this.count=null,this.version=1,this.name="",this.updateBeforeType=hv.OBJECT,this.onInitFunction=null}setCount(e){return this.count=e,this}getCount(){return this.count}dispose(){this.dispatchEvent({type:"dispose"})}setName(e){return this.name=e,this}label(e){return console.warn('THREE.TSL: "label()" has been deprecated. Use "setName()" instead.'),this.setName(e)}onInit(e){return this.onInitFunction=e,this}updateBefore({renderer:e}){e.compute(this)}setup(e){const t=this.computeNode.build(e);if(t){e.getNodeProperties(this).outputComputeNode=t.outputNode,t.outputNode=null}return t}generate(e,t){const{shaderStage:n}=e;if("compute"===n){const t=this.computeNode.build(e,"void");""!==t&&e.addLineFlowCode(t,this)}else{const n=e.getNodeProperties(this).outputComputeNode;if(n)return n.build(e,t)}}}const nw=(e,t=[64])=>{(0===t.length||t.length>3)&&console.error("THREE.TSL: compute() workgroupSize must have 1, 2, or 3 elements");for(let e=0;e<t.length;e++){const n=t[e];("number"!=typeof n||n<=0||!Number.isInteger(n))&&console.error(`THREE.TSL: compute() workgroupSize element at index [ ${e} ] must be a positive integer`)}for(;t.length<3;)t.push(1);return cA(new tw(cA(e),t))},iw=(e,t,n)=>nw(e,n).setCount(t);Ov("compute",iw),Ov("computeKernel",nw);class rw extends yv{static get type(){return"CacheNode"}constructor(e,t=!0){super(),this.node=e,this.parent=t,this.isCacheNode=!0}getNodeType(e){const t=e.getCache(),n=e.getCacheFromNode(this,this.parent);e.setCache(n);const i=this.node.getNodeType(e);return e.setCache(t),i}build(e,...t){const n=e.getCache(),i=e.getCacheFromNode(this,this.parent);e.setCache(i);const r=this.node.build(e,...t);return e.setCache(n),r}}const sw=(e,t)=>cA(new rw(cA(e),t));Ov("cache",sw);class ow extends yv{static get type(){return"BypassNode"}constructor(e,t){super(),this.isBypassNode=!0,this.outputNode=e,this.callNode=t}getNodeType(e){return this.outputNode.getNodeType(e)}generate(e){const t=this.callNode.build(e,"void");return""!==t&&e.addLineFlowCode(t,this),this.outputNode.build(e)}}const aw=pA(ow).setParameterLength(2);Ov("bypass",aw);class lw extends yv{static get type(){return"RemapNode"}constructor(e,t,n,i=EA(0),r=EA(1)){super(),this.node=e,this.inLowNode=t,this.inHighNode=n,this.outLowNode=i,this.outHighNode=r,this.doClamp=!0}setup(){const{node:e,inLowNode:t,inHighNode:n,outLowNode:i,outHighNode:r,doClamp:s}=this;let o=e.sub(t).div(n.sub(t));return!0===s&&(o=o.clamp()),o.mul(r.sub(i)).add(i)}}const uw=pA(lw,null,null,{doClamp:!1}).setParameterLength(3,5),cw=pA(lw).setParameterLength(3,5);Ov("remap",uw),Ov("remapClamp",cw);class dw extends yv{static get type(){return"ExpressionNode"}constructor(e="",t="void"){super(t),this.snippet=e}generate(e,t){const n=this.getNodeType(e),i=this.snippet;if("void"!==n)return e.format(i,n,t);e.addLineFlowCode(i,this)}}const hw=pA(dw).setParameterLength(1,2),fw=e=>(e?bb(e,hw("discard")):hw("discard")).toStack();Ov("discard",fw);class pw extends Cv{static get type(){return"RenderOutputNode"}constructor(e,t,n){super("vec4"),this.colorNode=e,this.toneMapping=t,this.outputColorSpace=n,this.isRenderOutputNode=!0}setup({context:e}){let t=this.colorNode||e.color;const n=(null!==this.toneMapping?this.toneMapping:e.toneMapping)||0,i=(null!==this.outputColorSpace?this.outputColorSpace:e.outputColorSpace)||Kr;return 0!==n&&(t=t.toneMapping(n)),i!==Kr&&i!==ks.workingColorSpace&&(t=t.workingToColorSpace(i)),t}}const gw=(e,t=null,n=null)=>cA(new pw(cA(e),t,n));Ov("renderOutput",gw);class mw extends Cv{static get type(){return"DebugNode"}constructor(e,t=null){super(),this.node=e,this.callback=t}getNodeType(e){return this.node.getNodeType(e)}setup(e){return this.node.build(e)}analyze(e){return this.node.build(e)}generate(e){const t=this.callback,n=this.node.build(e),i="--- TSL debug - "+e.shaderStage+" shader ---",r="-".repeat(i.length);let s="";return s+="// #"+i+"#\n",s+=e.flow.code.replace(/^\t/gm,"")+"\n",s+="/* ... */ "+n+" /* ... */\n",s+="// #"+r+"#\n",null!==t?t(e,s):console.log(s),n}}const vw=(e,t=null)=>cA(new mw(cA(e),t)).toStack();Ov("debug",vw);class Aw extends yv{static get type(){return"AttributeNode"}constructor(e,t=null){super(t),this.global=!0,this._attributeName=e}getHash(e){return this.getAttributeName(e)}getNodeType(e){let t=this.nodeType;if(null===t){const n=this.getAttributeName(e);if(e.hasGeometryAttribute(n)){const i=e.geometry.getAttribute(n);t=e.getTypeFromAttribute(i)}else t="float"}return t}setAttributeName(e){return this._attributeName=e,this}getAttributeName(){return this._attributeName}generate(e){const t=this.getAttributeName(e),n=this.getNodeType(e);if(!0===e.hasGeometryAttribute(t)){const i=e.geometry.getAttribute(t),r=e.getTypeFromAttribute(i),s=e.getAttribute(t,r);if("vertex"===e.shaderStage)return e.format(s.name,r,n);return Ob(this).build(e,n)}return console.warn(`AttributeNode: Vertex attribute "${t}" not found on geometry.`),e.generateConst(n)}serialize(e){super.serialize(e),e.global=this.global,e._attributeName=this._attributeName}deserialize(e){super.deserialize(e),this.global=e.global,this._attributeName=e._attributeName}}const xw=(e,t=null)=>cA(new Aw(e,t)),yw=(e=0)=>xw("uv"+(e>0?e:""),"vec2");class bw extends yv{static get type(){return"TextureSizeNode"}constructor(e,t=null){super("uvec2"),this.isTextureSizeNode=!0,this.textureNode=e,this.levelNode=t}generate(e,t){const n=this.textureNode.build(e,"property"),i=null===this.levelNode?"0":this.levelNode.build(e,"int");return e.format(`${e.getMethod("textureDimensions")}( ${n}, ${i} )`,this.getNodeType(e),t)}}const ww=pA(bw).setParameterLength(1,2);class Cw extends Px{static get type(){return"MaxMipLevelNode"}constructor(e){super(0),this._textureNode=e,this.updateType=hv.FRAME}get textureNode(){return this._textureNode}get texture(){return this._textureNode.value}update(){const e=this.texture,t=e.images,n=t&&t.length>0?t[0]&&t[0].image||t[0]:e.image;if(n&&void 0!==n.width){const{width:e,height:t}=n;this.value=Math.log2(Math.max(e,t))}}}const Mw=pA(Cw).setParameterLength(1),Ew=new Ys;class Tw extends Px{static get type(){return"TextureNode"}constructor(e=Ew,t=null,n=null,i=null){super(e),this.isTextureNode=!0,this.uvNode=t,this.levelNode=n,this.biasNode=i,this.compareNode=null,this.depthNode=null,this.gradNode=null,this.offsetNode=null,this.sampler=!0,this.updateMatrix=!1,this.updateType=hv.NONE,this.referenceNode=null,this._value=e,this._matrixUniform=null,this.setUpdateMatrix(null===t)}set value(e){this.referenceNode?this.referenceNode.value=e:this._value=e}get value(){return this.referenceNode?this.referenceNode.value:this._value}getUniformHash(){return this.value.uuid}getNodeType(){return!0===this.value.isDepthTexture?"float":this.value.type===Yi?"uvec4":this.value.type===Zi?"ivec4":"vec4"}getInputType(){return"texture"}getDefaultUV(){return yw(this.value.channel)}updateReference(){return this.value}getTransformedUV(e){return null===this._matrixUniform&&(this._matrixUniform=Nx(this.value.matrix)),this._matrixUniform.mul(LA(e,1)).xy}setUpdateMatrix(e){return this.updateMatrix=e,this.updateType=e?hv.OBJECT:hv.NONE,this}setupUV(e,t){const n=this.value;return e.isFlipY()&&(n.image instanceof ImageBitmap&&!0===n.flipY||!0===n.isRenderTargetTexture||!0===n.isFramebufferTexture||!0===n.isDepthTexture)&&(t=this.sampler?t.flipY():t.setY(TA(ww(this,this.levelNode).y).sub(t.y).sub(1))),t}setup(e){const t=e.getNodeProperties(this);t.referenceNode=this.referenceNode;const n=this.value;if(!n||!0!==n.isTexture)throw new Error("THREE.TSL: `texture( value )` function expects a valid instance of THREE.Texture().");let i=this.uvNode;null!==i&&!0!==e.context.forceUVContext||!e.context.getUV||(i=e.context.getUV(this,e)),i||(i=this.getDefaultUV()),!0===this.updateMatrix&&(i=this.getTransformedUV(i)),i=this.setupUV(e,i);let r=this.levelNode;null===r&&e.context.getTextureLevel&&(r=e.context.getTextureLevel(this)),t.uvNode=i,t.levelNode=r,t.biasNode=this.biasNode,t.compareNode=this.compareNode,t.gradNode=this.gradNode,t.depthNode=this.depthNode,t.offsetNode=this.offsetNode}generateUV(e,t){return t.build(e,!0===this.sampler?"vec2":"ivec2")}generateOffset(e,t){return t.build(e,"ivec2")}generateSnippet(e,t,n,i,r,s,o,a,l){const u=this.value;let c;return c=i?e.generateTextureLevel(u,t,n,i,s,l):r?e.generateTextureBias(u,t,n,r,s,l):a?e.generateTextureGrad(u,t,n,a,s,l):o?e.generateTextureCompare(u,t,n,o,s,l):!1===this.sampler?e.generateTextureLoad(u,t,n,s,l):e.generateTexture(u,t,n,s,l),c}generate(e,t){const n=this.value,i=e.getNodeProperties(this),r=super.generate(e,"property");if(/^sampler/.test(t))return r+"_sampler";if(e.isReference(t))return r;{const s=e.getDataFromNode(this);let o=s.propertyName;if(void 0===o){const{uvNode:t,levelNode:n,biasNode:a,compareNode:l,depthNode:u,gradNode:c,offsetNode:d}=i,h=this.generateUV(e,t),f=n?n.build(e,"float"):null,p=a?a.build(e,"float"):null,g=u?u.build(e,"int"):null,m=l?l.build(e,"float"):null,v=c?[c[0].build(e,"vec2"),c[1].build(e,"vec2")]:null,A=d?this.generateOffset(e,d):null,x=e.getVarFromNode(this);o=e.getPropertyName(x);const y=this.generateSnippet(e,r,h,f,p,g,m,v,A);e.addLineFlowCode(`${o} = ${y}`,this),s.snippet=y,s.propertyName=o}let a=o;const l=this.getNodeType(e);return e.needsToWorkingColorSpace(n)&&(a=Xb(hw(a,l),n.colorSpace).setup(e).build(e,l)),e.format(a,l,t)}}setSampler(e){return this.sampler=e,this}getSampler(){return this.sampler}uv(e){return console.warn("THREE.TextureNode: .uv() has been renamed. Use .sample() instead."),this.sample(e)}sample(e){const t=this.clone();return t.uvNode=cA(e),t.referenceNode=this.getBase(),cA(t)}load(e){return this.sample(e).setSampler(!1)}blur(e){const t=this.clone();t.biasNode=cA(e).mul(Mw(t)),t.referenceNode=this.getBase();const n=t.value;return!1===t.generateMipmaps&&(n&&!1===n.generateMipmaps||n.minFilter===Ri||n.magFilter===Ri)&&(console.warn("THREE.TSL: texture().blur() requires mipmaps and sampling. Use .generateMipmaps=true and .minFilter/.magFilter=THREE.LinearFilter in the Texture."),t.biasNode=null),cA(t)}level(e){const t=this.clone();return t.levelNode=cA(e),t.referenceNode=this.getBase(),cA(t)}size(e){return ww(this,e)}bias(e){const t=this.clone();return t.biasNode=cA(e),t.referenceNode=this.getBase(),cA(t)}getBase(){return this.referenceNode?this.referenceNode.getBase():this}compare(e){const t=this.clone();return t.compareNode=cA(e),t.referenceNode=this.getBase(),cA(t)}grad(e,t){const n=this.clone();return n.gradNode=[cA(e),cA(t)],n.referenceNode=this.getBase(),cA(n)}depth(e){const t=this.clone();return t.depthNode=cA(e),t.referenceNode=this.getBase(),cA(t)}offset(e){const t=this.clone();return t.offsetNode=cA(e),t.referenceNode=this.getBase(),cA(t)}serialize(e){super.serialize(e),e.value=this.value.toJSON(e.meta).uuid,e.sampler=this.sampler,e.updateMatrix=this.updateMatrix,e.updateType=this.updateType}deserialize(e){super.deserialize(e),this.value=e.meta.textures[e.value],this.sampler=e.sampler,this.updateMatrix=e.updateMatrix,this.updateType=e.updateType}update(){const e=this.value,t=this._matrixUniform;null!==t&&(t.value=e.matrix),!0===e.matrixAutoUpdate&&e.updateMatrix()}clone(){const e=new this.constructor(this.value,this.uvNode,this.levelNode,this.biasNode);return e.sampler=this.sampler,e.depthNode=this.depthNode,e.compareNode=this.compareNode,e.gradNode=this.gradNode,e.offsetNode=this.offsetNode,e}}const Sw=pA(Tw).setParameterLength(1,4).setName("texture"),Pw=(e=Ew,t=null,n=null,i=null)=>{let r;return e&&!0===e.isTextureNode?(r=cA(e.clone()),r.referenceNode=e.getBase(),null!==t&&(r.uvNode=cA(t)),null!==n&&(r.levelNode=cA(n)),null!==i&&(r.biasNode=cA(i))):r=Sw(e,t,n,i),r},Nw=(...e)=>Pw(...e).setSampler(!1);class Bw extends Px{static get type(){return"BufferNode"}constructor(e,t,n=0){super(e,t),this.isBufferNode=!0,this.bufferType=t,this.bufferCount=n}getElementType(e){return this.getNodeType(e)}getInputType(){return"buffer"}}const Dw=(e,t,n)=>cA(new Bw(e,t,n));class Iw extends bv{static get type(){return"UniformArrayElementNode"}constructor(e,t){super(e,t),this.isArrayBufferElementNode=!0}generate(e){const t=super.generate(e),n=this.getNodeType(),i=this.node.getPaddedType();return e.format(t,i,n)}}class Lw extends Bw{static get type(){return"UniformArrayNode"}constructor(e,t=null){super(null),this.array=e,this.elementType=null===t?ov(e[0]):t,this.paddedType=this.getPaddedType(),this.updateType=hv.RENDER,this.isArrayBufferNode=!0}getNodeType(){return this.paddedType}getElementType(){return this.elementType}getPaddedType(){const e=this.elementType;let t="vec4";return"mat2"===e?t="mat2":!0===/mat/.test(e)?t="mat4":"i"===e.charAt(0)?t="ivec4":"u"===e.charAt(0)&&(t="uvec4"),t}update(){const{array:e,value:t}=this,n=this.elementType;if("float"===n||"int"===n||"uint"===n)for(let n=0;n<e.length;n++){t[4*n]=e[n]}else if("color"===n)for(let n=0;n<e.length;n++){const i=4*n,r=e[n];t[i]=r.r,t[i+1]=r.g,t[i+2]=r.b||0}else if("mat2"===n)for(let n=0;n<e.length;n++){const i=4*n,r=e[n];t[i]=r.elements[0],t[i+1]=r.elements[1],t[i+2]=r.elements[2],t[i+3]=r.elements[3]}else if("mat3"===n)for(let n=0;n<e.length;n++){const i=16*n,r=e[n];t[i]=r.elements[0],t[i+1]=r.elements[1],t[i+2]=r.elements[2],t[i+4]=r.elements[3],t[i+5]=r.elements[4],t[i+6]=r.elements[5],t[i+8]=r.elements[6],t[i+9]=r.elements[7],t[i+10]=r.elements[8],t[i+15]=1}else if("mat4"===n)for(let n=0;n<e.length;n++){const i=16*n,r=e[n];for(let e=0;e<r.elements.length;e++)t[i+e]=r.elements[e]}else for(let n=0;n<e.length;n++){const i=4*n,r=e[n];t[i]=r.x,t[i+1]=r.y,t[i+2]=r.z||0,t[i+3]=r.w||0}}setup(e){const t=this.array.length,n=this.elementType;let i=Float32Array;const r=this.paddedType,s=e.getTypeLength(r);return"i"===n.charAt(0)&&(i=Int32Array),"u"===n.charAt(0)&&(i=Uint32Array),this.value=new i(t*s),this.bufferCount=t,this.bufferType=r,super.setup(e)}element(e){return cA(new Iw(this,cA(e)))}}const jw=(e,t)=>cA(new Lw(e,t));const Ow=pA(class extends yv{constructor(e){super("float"),this.name=e,this.isBuiltinNode=!0}generate(){return this.name}}).setParameterLength(1);let zw,Rw;class kw extends yv{static get type(){return"ScreenNode"}constructor(e){super(),this.scope=e,this._output=null,this.isViewportNode=!0}getNodeType(){return this.scope===kw.DPR?"float":this.scope===kw.VIEWPORT?"vec4":"vec2"}getUpdateType(){let e=hv.NONE;return this.scope!==kw.SIZE&&this.scope!==kw.VIEWPORT&&this.scope!==kw.DPR||(e=hv.RENDER),this.updateType=e,e}update({renderer:e}){const t=e.getRenderTarget();this.scope===kw.VIEWPORT?null!==t?Rw.copy(t.viewport):(e.getViewport(Rw),Rw.multiplyScalar(e.getPixelRatio())):this.scope===kw.DPR?this._output.value=e.getPixelRatio():null!==t?(zw.width=t.width,zw.height=t.height):e.getDrawingBufferSize(zw)}setup(){const e=this.scope;let t=null;return t=e===kw.SIZE?Nx(zw||(zw=new Cs)):e===kw.VIEWPORT?Nx(Rw||(Rw=new Js)):e===kw.DPR?Nx(1):NA(Xw.div(Uw)),this._output=t,t}generate(e){if(this.scope===kw.COORDINATE){let t=e.getFragCoord();if(e.isFlipY()){const n=e.getNodeProperties(Uw).outputNode.build(e);t=`${e.getType("vec2")}( ${t}.x, ${n}.y - ${t}.y )`}return t}return super.generate(e)}}kw.COORDINATE="coordinate",kw.VIEWPORT="viewport",kw.SIZE="size",kw.UV="uv",kw.DPR="dpr";const Fw=gA(kw,kw.DPR),Hw=gA(kw,kw.UV),Uw=gA(kw,kw.SIZE),Xw=gA(kw,kw.COORDINATE),Gw=gA(kw,kw.VIEWPORT),Vw=Gw.zw,Ww=(Gw.xy,Nx(0,"uint").setName("u_cameraIndex").setGroup(Mx("cameraIndex")).toVarying("v_cameraIndex")),Qw=Nx("float").setName("cameraNear").setGroup(Tx).onRenderUpdate((({camera:e})=>e.near)),Zw=Nx("float").setName("cameraFar").setGroup(Tx).onRenderUpdate((({camera:e})=>e.far)),Yw=xA((({camera:e})=>{let t;if(e.isArrayCamera&&e.cameras.length>0){const n=[];for(const t of e.cameras)n.push(t.projectionMatrix);t=jw(n).setGroup(Tx).setName("cameraProjectionMatrices").element(e.isMultiViewCamera?Ow("gl_ViewID_OVR"):Ww).toConst("cameraProjectionMatrix")}else t=Nx("mat4").setName("cameraProjectionMatrix").setGroup(Tx).onRenderUpdate((({camera:e})=>e.projectionMatrix));return t})).once()(),Jw=xA((({camera:e})=>{let t;if(e.isArrayCamera&&e.cameras.length>0){const n=[];for(const t of e.cameras)n.push(t.matrixWorldInverse);t=jw(n).setGroup(Tx).setName("cameraViewMatrices").element(e.isMultiViewCamera?Ow("gl_ViewID_OVR"):Ww).toConst("cameraViewMatrix")}else t=Nx("mat4").setName("cameraViewMatrix").setGroup(Tx).onRenderUpdate((({camera:e})=>e.matrixWorldInverse));return t})).once()(),Kw=xA((({camera:e})=>{let t;if(e.isArrayCamera&&e.cameras.length>0){const n=[];for(let t=0,i=e.cameras.length;t<i;t++)n.push(new Es);const i=jw(n).setGroup(Tx).setName("cameraPositions").onRenderUpdate((({camera:e},t)=>{const n=e.cameras,i=t.array;for(let e=0,t=n.length;e<t;e++)i[e].setFromMatrixPosition(n[e].matrixWorld)}));t=i.element(e.isMultiViewCamera?Ow("gl_ViewID_OVR"):Ww).toConst("cameraPosition")}else t=Nx(new Es).setName("cameraPosition").setGroup(Tx).onRenderUpdate((({camera:e},t)=>t.value.setFromMatrixPosition(e.matrixWorld)));return t})).once()(),qw=new xo;class _w extends yv{static get type(){return"Object3DNode"}constructor(e,t=null){super(),this.scope=e,this.object3d=t,this.updateType=hv.OBJECT,this.uniformNode=new Px(null)}getNodeType(){const e=this.scope;return e===_w.WORLD_MATRIX?"mat4":e===_w.POSITION||e===_w.VIEW_POSITION||e===_w.DIRECTION||e===_w.SCALE?"vec3":e===_w.RADIUS?"float":void 0}update(e){const t=this.object3d,n=this.uniformNode,i=this.scope;if(i===_w.WORLD_MATRIX)n.value=t.matrixWorld;else if(i===_w.POSITION)n.value=n.value||new Es,n.value.setFromMatrixPosition(t.matrixWorld);else if(i===_w.SCALE)n.value=n.value||new Es,n.value.setFromMatrixScale(t.matrixWorld);else if(i===_w.DIRECTION)n.value=n.value||new Es,t.getWorldDirection(n.value);else if(i===_w.VIEW_POSITION){const i=e.camera;n.value=n.value||new Es,n.value.setFromMatrixPosition(t.matrixWorld),n.value.applyMatrix4(i.matrixWorldInverse)}else if(i===_w.RADIUS){const i=e.object.geometry;null===i.boundingSphere&&i.computeBoundingSphere(),qw.copy(i.boundingSphere).applyMatrix4(t.matrixWorld),n.value=qw.radius}}generate(e){const t=this.scope;return t===_w.WORLD_MATRIX?this.uniformNode.nodeType="mat4":t===_w.POSITION||t===_w.VIEW_POSITION||t===_w.DIRECTION||t===_w.SCALE?this.uniformNode.nodeType="vec3":t===_w.RADIUS&&(this.uniformNode.nodeType="float"),this.uniformNode.build(e)}serialize(e){super.serialize(e),e.scope=this.scope}deserialize(e){super.deserialize(e),this.scope=e.scope}}_w.WORLD_MATRIX="worldMatrix",_w.POSITION="position",_w.SCALE="scale",_w.VIEW_POSITION="viewPosition",_w.DIRECTION="direction",_w.RADIUS="radius";const $w=pA(_w,_w.POSITION).setParameterLength(1);class eC extends _w{static get type(){return"ModelNode"}constructor(e){super(e)}update(e){this.object3d=e.object,super.update(e)}}const tC=gA(eC,eC.WORLD_MATRIX),nC=Nx(new Ps).onObjectUpdate((({object:e},t)=>t.value.getNormalMatrix(e.matrixWorld))),iC=xA((e=>e.renderer.overrideNodes.modelViewMatrix||rC)).once()().toVar("modelViewMatrix"),rC=Jw.mul(tC),sC=xA((e=>(e.context.isHighPrecisionModelViewMatrix=!0,Nx("mat4").onObjectUpdate((({object:e,camera:t})=>e.modelViewMatrix.multiplyMatrices(t.matrixWorldInverse,e.matrixWorld)))))).once()().toVar("highpModelViewMatrix"),oC=xA((e=>{const t=e.context.isHighPrecisionModelViewMatrix;return Nx("mat3").onObjectUpdate((({object:e,camera:n})=>(!0!==t&&e.modelViewMatrix.multiplyMatrices(n.matrixWorldInverse,e.matrixWorld),e.normalMatrix.getNormalMatrix(e.modelViewMatrix))))})).once()().toVar("highpModelNormalViewMatrix"),aC=xw("position","vec3"),lC=aC.toVarying("positionLocal"),uC=aC.toVarying("positionPrevious"),cC=xA((e=>tC.mul(lC).xyz.toVarying(e.getSubBuildProperty("v_positionWorld"))),"vec3").once(["POSITION"])(),dC=xA((()=>lC.transformDirection(tC).toVarying("v_positionWorldDirection").normalize().toVar("positionWorldDirection")),"vec3").once(["POSITION"])(),hC=xA((e=>e.context.setupPositionView().toVarying("v_positionView")),"vec3").once(["POSITION"])(),fC=hC.negate().toVarying("v_positionViewDirection").normalize().toVar("positionViewDirection");class pC extends yv{static get type(){return"FrontFacingNode"}constructor(){super("bool"),this.isFrontFacingNode=!0}generate(e){if("fragment"!==e.shaderStage)return"true";const{material:t}=e;return 1===t.side?"false":e.getFrontFacing()}}const gC=gA(pC),mC=EA(gC).mul(2).sub(1),vC=xA((([e],{material:t})=>{const n=t.side;return 1===n?e=e.mul(-1):2===n&&(e=e.mul(mC)),e})),AC=xw("normal","vec3"),xC=xA((e=>!1===e.geometry.hasAttribute("normal")?(console.warn('THREE.TSL: Vertex attribute "normal" not found on geometry.'),LA(0,1,0)):AC),"vec3").once()().toVar("normalLocal"),yC=hC.dFdx().cross(hC.dFdy()).normalize().toVar("normalFlat"),bC=xA((e=>{let t;return t=!0===e.material.flatShading?yC:SC(xC).toVarying("v_normalViewGeometry").normalize(),t}),"vec3").once()().toVar("normalViewGeometry"),wC=xA((e=>{let t=bC.transformDirection(Jw);return!0!==e.material.flatShading&&(t=t.toVarying("v_normalWorldGeometry")),t.normalize().toVar("normalWorldGeometry")}),"vec3").once()(),CC=xA((({subBuildFn:e,material:t,context:n})=>{let i;return"NORMAL"===e||"VERTEX"===e?(i=bC,!0!==t.flatShading&&(i=vC(i))):i=n.setupNormal().context({getUV:null}),i}),"vec3").once(["NORMAL","VERTEX"])().toVar("normalView"),MC=CC.transformDirection(Jw).toVar("normalWorld"),EC=xA((({subBuildFn:e,context:t})=>{let n;return n="NORMAL"===e||"VERTEX"===e?CC:t.setupClearcoatNormal().context({getUV:null}),n}),"vec3").once(["NORMAL","VERTEX"])().toVar("clearcoatNormalView"),TC=xA((([e,t=tC])=>{const n=XA(t),i=e.div(LA(n[0].dot(n[0]),n[1].dot(n[1]),n[2].dot(n[2])));return n.mul(i).xyz})),SC=xA((([e],t)=>{const n=t.renderer.overrideNodes.modelNormalViewMatrix;if(null!==n)return n.transformDirection(e);const i=nC.mul(e);return Jw.transformDirection(i)})),PC=(xA((()=>(console.warn('THREE.TSL: "transformedNormalView" is deprecated. Use "normalView" instead.'),CC))).once(["NORMAL","VERTEX"])(),xA((()=>(console.warn('THREE.TSL: "transformedNormalWorld" is deprecated. Use "normalWorld" instead.'),MC))).once(["NORMAL","VERTEX"])(),xA((()=>(console.warn('THREE.TSL: "transformedClearcoatNormalView" is deprecated. Use "clearcoatNormalView" instead.'),EC))).once(["NORMAL","VERTEX"])(),new ko),NC=new Po,BC=Nx(0).onReference((({material:e})=>e)).onObjectUpdate((({material:e})=>e.refractionRatio)),DC=Nx(1).onReference((({material:e})=>e)).onObjectUpdate((function({material:e,scene:t}){return e.envMap?e.envMapIntensity:t.environmentIntensity})),IC=Nx(new Po).onReference((function(e){return e.material})).onObjectUpdate((function({material:e,scene:t}){const n=null!==t.environment&&null===e.envMap?t.environmentRotation:e.envMapRotation;return n?(PC.copy(n),NC.makeRotationFromEuler(PC)):NC.identity(),NC})),LC=fC.negate().reflect(CC),jC=fC.negate().refract(CC,BC),OC=LC.transformDirection(Jw).toVar("reflectVector"),zC=jC.transformDirection(Jw).toVar("reflectVector"),RC=new vl;class kC extends Tw{static get type(){return"CubeTextureNode"}constructor(e,t=null,n=null,i=null){super(e,t,n,i),this.isCubeTextureNode=!0}getInputType(){return"cubeTexture"}getDefaultUV(){const e=this.value;return e.mapping===Ni?OC:e.mapping===Bi?zC:(console.error('THREE.CubeTextureNode: Mapping "%s" not supported.',e.mapping),LA(0,0,0))}setUpdateMatrix(){}setupUV(e,t){const n=this.value;return e.renderer.coordinateSystem!==ls&&n.isRenderTargetTexture||(t=LA(t.x.negate(),t.yz)),IC.mul(t)}generateUV(e,t){return t.build(e,"vec3")}}const FC=pA(kC).setParameterLength(1,4).setName("cubeTexture"),HC=(e=RC,t=null,n=null,i=null)=>{let r;return e&&!0===e.isCubeTextureNode?(r=cA(e.clone()),r.referenceNode=e,null!==t&&(r.uvNode=cA(t)),null!==n&&(r.levelNode=cA(n)),null!==i&&(r.biasNode=cA(i))):r=FC(e,t,n,i),r};class UC extends bv{static get type(){return"ReferenceElementNode"}constructor(e,t){super(e,t),this.referenceNode=e,this.isReferenceElementNode=!0}getNodeType(){return this.referenceNode.uniformType}generate(e){const t=super.generate(e),n=this.referenceNode.getNodeType(),i=this.getNodeType();return e.format(t,n,i)}}class XC extends yv{static get type(){return"ReferenceNode"}constructor(e,t,n=null,i=null){super(),this.property=e,this.uniformType=t,this.object=n,this.count=i,this.properties=e.split("."),this.reference=n,this.node=null,this.group=null,this.name=null,this.updateType=hv.OBJECT}element(e){return cA(new UC(this,cA(e)))}setGroup(e){return this.group=e,this}setName(e){return this.name=e,this}label(e){return console.warn('THREE.TSL: "label()" has been deprecated. Use "setName()" instead.'),this.setName(e)}setNodeType(e){let t=null;t=null!==this.count?Dw(null,e,this.count):Array.isArray(this.getValueFromReference())?jw(null,e):"texture"===e?Pw(null):"cubeTexture"===e?HC(null):Nx(null,e),null!==this.group&&t.setGroup(this.group),null!==this.name&&t.setName(this.name),this.node=t}getNodeType(e){return null===this.node&&(this.updateReference(e),this.updateValue()),this.node.getNodeType(e)}getValueFromReference(e=this.reference){const{properties:t}=this;let n=e[t[0]];for(let e=1;e<t.length;e++)n=n[t[e]];return n}updateReference(e){return this.reference=null!==this.object?this.object:e.object,this.reference}setup(){return this.updateValue(),this.node}update(){this.updateValue()}updateValue(){null===this.node&&this.setNodeType(this.uniformType);const e=this.getValueFromReference();Array.isArray(e)?this.node.array=e:this.node.value=e}}const GC=(e,t,n)=>cA(new XC(e,t,n)),VC=(e,t,n,i)=>cA(new XC(e,t,i,n));class WC extends XC{static get type(){return"MaterialReferenceNode"}constructor(e,t,n=null){super(e,t,n),this.material=n,this.isMaterialReferenceNode=!0}updateReference(e){return this.reference=null!==this.material?this.material:e.material,this.reference}}const QC=(e,t,n=null)=>cA(new WC(e,t,n)),ZC=yw(),YC=hC.dFdx(),JC=hC.dFdy(),KC=ZC.dFdx(),qC=ZC.dFdy(),_C=CC,$C=JC.cross(_C),eM=_C.cross(YC),tM=$C.mul(KC.x).add(eM.mul(qC.x)),nM=$C.mul(KC.y).add(eM.mul(qC.y)),iM=tM.dot(tM).max(nM.dot(nM)),rM=iM.equal(0).select(0,iM.inverseSqrt()),sM=tM.mul(rM).toVar("tangentViewFrame"),oM=nM.mul(rM).toVar("bitangentViewFrame"),aM=xA((e=>(!1===e.geometry.hasAttribute("tangent")&&e.geometry.computeTangents(),xw("tangent","vec4"))))(),lM=aM.xyz.toVar("tangentLocal"),uM=xA((({subBuildFn:e,geometry:t,material:n})=>{let i;return i="VERTEX"===e||t.hasAttribute("tangent")?iC.mul(RA(lM,0)).xyz.toVarying("v_tangentView").normalize():sM,!0!==n.flatShading&&(i=vC(i)),i}),"vec3").once(["NORMAL","VERTEX"])().toVar("tangentView"),cM=xA((([e,t],{subBuildFn:n,material:i})=>{let r=e.mul(aM.w).xyz;return"NORMAL"===n&&!0!==i.flatShading&&(r=r.toVarying(t)),r})).once(["NORMAL"]),dM=xA((({subBuildFn:e,geometry:t,material:n})=>{let i;return i="VERTEX"===e||t.hasAttribute("tangent")?cM(CC.cross(uM),"v_bitangentView").normalize():oM,!0!==n.flatShading&&(i=vC(i)),i}),"vec3").once(["NORMAL","VERTEX"])().toVar("bitangentView"),hM=XA(uM,dM,CC).toVar("TBNViewMatrix"),fM=xA((()=>{let e=ux.cross(fC);return e=e.cross(ux).normalize(),e=ub(e,CC,ax.mul(qA.oneMinus()).oneMinus().pow2().pow2()).normalize(),e})).once()();class pM extends Cv{static get type(){return"NormalMapNode"}constructor(e,t=null){super("vec3"),this.node=e,this.scaleNode=t,this.normalMapType=0}setup({material:e}){const{normalMapType:t,scaleNode:n}=this;let i=this.node.mul(2).sub(1);if(null!==n){let t=n;!0===e.flatShading&&(t=vC(t)),i=LA(i.xy.mul(t),i.z)}let r=null;return 1===t?r=SC(i):0===t?r=hM.mul(i).normalize():(console.error(`THREE.NodeMaterial: Unsupported normal map type: ${t}`),r=CC),r}}const gM=pA(pM).setParameterLength(1,2),mM=xA((({textureNode:e,bumpScale:t})=>{const n=t=>e.cache().context({getUV:e=>t(e.uvNode||yw()),forceUVContext:!0}),i=EA(n((e=>e)));return NA(EA(n((e=>e.add(e.dFdx())))).sub(i),EA(n((e=>e.add(e.dFdy())))).sub(i)).mul(t)})),vM=xA((e=>{const{surf_pos:t,surf_norm:n,dHdxy:i}=e,r=t.dFdx().normalize(),s=n,o=t.dFdy().normalize().cross(s),a=s.cross(r),l=r.dot(o).mul(mC),u=l.sign().mul(i.x.mul(o).add(i.y.mul(a)));return l.abs().mul(n).sub(u).normalize()}));class AM extends Cv{static get type(){return"BumpMapNode"}constructor(e,t=null){super("vec3"),this.textureNode=e,this.scaleNode=t}setup(){const e=null!==this.scaleNode?this.scaleNode:1,t=mM({textureNode:this.textureNode,bumpScale:e});return vM({surf_pos:hC,surf_norm:CC,dHdxy:t})}}const xM=pA(AM).setParameterLength(1,2),yM=new Map;class bM extends yv{static get type(){return"MaterialNode"}constructor(e){super(),this.scope=e}getCache(e,t){let n=yM.get(e);return void 0===n&&(n=QC(e,t),yM.set(e,n)),n}getFloat(e){return this.getCache(e,"float")}getColor(e){return this.getCache(e,"color")}getTexture(e){return this.getCache("map"===e?"map":e+"Map","texture")}setup(e){const t=e.context.material,n=this.scope;let i=null;if(n===bM.COLOR){const e=void 0!==t.color?this.getColor(n):LA();i=t.map&&!0===t.map.isTexture?e.mul(this.getTexture("map")):e}else if(n===bM.OPACITY){const e=this.getFloat(n);i=t.alphaMap&&!0===t.alphaMap.isTexture?e.mul(this.getTexture("alpha")):e}else if(n===bM.SPECULAR_STRENGTH)i=t.specularMap&&!0===t.specularMap.isTexture?this.getTexture("specular").r:EA(1);else if(n===bM.SPECULAR_INTENSITY){const e=this.getFloat(n);i=t.specularIntensityMap&&!0===t.specularIntensityMap.isTexture?e.mul(this.getTexture(n).a):e}else if(n===bM.SPECULAR_COLOR){const e=this.getColor(n);i=t.specularColorMap&&!0===t.specularColorMap.isTexture?e.mul(this.getTexture(n).rgb):e}else if(n===bM.ROUGHNESS){const e=this.getFloat(n);i=t.roughnessMap&&!0===t.roughnessMap.isTexture?e.mul(this.getTexture(n).g):e}else if(n===bM.METALNESS){const e=this.getFloat(n);i=t.metalnessMap&&!0===t.metalnessMap.isTexture?e.mul(this.getTexture(n).b):e}else if(n===bM.EMISSIVE){const e=this.getFloat("emissiveIntensity"),r=this.getColor(n).mul(e);i=t.emissiveMap&&!0===t.emissiveMap.isTexture?r.mul(this.getTexture(n)):r}else if(n===bM.NORMAL)t.normalMap?(i=gM(this.getTexture("normal"),this.getCache("normalScale","vec2")),i.normalMapType=t.normalMapType):i=t.bumpMap?xM(this.getTexture("bump").r,this.getFloat("bumpScale")):CC;else if(n===bM.CLEARCOAT){const e=this.getFloat(n);i=t.clearcoatMap&&!0===t.clearcoatMap.isTexture?e.mul(this.getTexture(n).r):e}else if(n===bM.CLEARCOAT_ROUGHNESS){const e=this.getFloat(n);i=t.clearcoatRoughnessMap&&!0===t.clearcoatRoughnessMap.isTexture?e.mul(this.getTexture(n).r):e}else if(n===bM.CLEARCOAT_NORMAL)i=t.clearcoatNormalMap?gM(this.getTexture(n),this.getCache(n+"Scale","vec2")):CC;else if(n===bM.SHEEN){const e=this.getColor("sheenColor").mul(this.getFloat("sheen"));i=t.sheenColorMap&&!0===t.sheenColorMap.isTexture?e.mul(this.getTexture("sheenColor").rgb):e}else if(n===bM.SHEEN_ROUGHNESS){const e=this.getFloat(n);i=t.sheenRoughnessMap&&!0===t.sheenRoughnessMap.isTexture?e.mul(this.getTexture(n).a):e,i=i.clamp(.07,1)}else if(n===bM.ANISOTROPY)if(t.anisotropyMap&&!0===t.anisotropyMap.isTexture){const e=this.getTexture(n);i=UA(rE.x,rE.y,rE.y.negate(),rE.x).mul(e.rg.mul(2).sub(NA(1)).normalize().mul(e.b))}else i=rE;else if(n===bM.IRIDESCENCE_THICKNESS){const e=GC("1","float",t.iridescenceThicknessRange);if(t.iridescenceThicknessMap){const r=GC("0","float",t.iridescenceThicknessRange);i=e.sub(r).mul(this.getTexture(n).g).add(r)}else i=e}else if(n===bM.TRANSMISSION){const e=this.getFloat(n);i=t.transmissionMap?e.mul(this.getTexture(n).r):e}else if(n===bM.THICKNESS){const e=this.getFloat(n);i=t.thicknessMap?e.mul(this.getTexture(n).g):e}else if(n===bM.IOR)i=this.getFloat(n);else if(n===bM.LIGHT_MAP)i=this.getTexture(n).rgb.mul(this.getFloat("lightMapIntensity"));else if(n===bM.AO)i=this.getTexture(n).r.sub(1).mul(this.getFloat("aoMapIntensity")).add(1);else if(n===bM.LINE_DASH_OFFSET)i=t.dashOffset?this.getFloat(n):EA(0);else{const t=this.getNodeType(e);i=this.getCache(n,t)}return i}}bM.ALPHA_TEST="alphaTest",bM.COLOR="color",bM.OPACITY="opacity",bM.SHININESS="shininess",bM.SPECULAR="specular",bM.SPECULAR_STRENGTH="specularStrength",bM.SPECULAR_INTENSITY="specularIntensity",bM.SPECULAR_COLOR="specularColor",bM.REFLECTIVITY="reflectivity",bM.ROUGHNESS="roughness",bM.METALNESS="metalness",bM.NORMAL="normal",bM.CLEARCOAT="clearcoat",bM.CLEARCOAT_ROUGHNESS="clearcoatRoughness",bM.CLEARCOAT_NORMAL="clearcoatNormal",bM.EMISSIVE="emissive",bM.ROTATION="rotation",bM.SHEEN="sheen",bM.SHEEN_ROUGHNESS="sheenRoughness",bM.ANISOTROPY="anisotropy",bM.IRIDESCENCE="iridescence",bM.IRIDESCENCE_IOR="iridescenceIOR",bM.IRIDESCENCE_THICKNESS="iridescenceThickness",bM.IOR="ior",bM.TRANSMISSION="transmission",bM.THICKNESS="thickness",bM.ATTENUATION_DISTANCE="attenuationDistance",bM.ATTENUATION_COLOR="attenuationColor",bM.LINE_SCALE="scale",bM.LINE_DASH_SIZE="dashSize",bM.LINE_GAP_SIZE="gapSize",bM.LINE_WIDTH="linewidth",bM.LINE_DASH_OFFSET="dashOffset",bM.POINT_SIZE="size",bM.DISPERSION="dispersion",bM.LIGHT_MAP="light",bM.AO="ao";const wM=gA(bM,bM.ALPHA_TEST),CM=gA(bM,bM.COLOR),MM=gA(bM,bM.SHININESS),EM=gA(bM,bM.EMISSIVE),TM=gA(bM,bM.OPACITY),SM=gA(bM,bM.SPECULAR),PM=gA(bM,bM.SPECULAR_INTENSITY),NM=gA(bM,bM.SPECULAR_COLOR),BM=gA(bM,bM.SPECULAR_STRENGTH),DM=gA(bM,bM.REFLECTIVITY),IM=gA(bM,bM.ROUGHNESS),LM=gA(bM,bM.METALNESS),jM=gA(bM,bM.NORMAL),OM=gA(bM,bM.CLEARCOAT),zM=gA(bM,bM.CLEARCOAT_ROUGHNESS),RM=gA(bM,bM.CLEARCOAT_NORMAL),kM=gA(bM,bM.ROTATION),FM=gA(bM,bM.SHEEN),HM=gA(bM,bM.SHEEN_ROUGHNESS),UM=gA(bM,bM.ANISOTROPY),XM=gA(bM,bM.IRIDESCENCE),GM=gA(bM,bM.IRIDESCENCE_IOR),VM=gA(bM,bM.IRIDESCENCE_THICKNESS),WM=gA(bM,bM.TRANSMISSION),QM=gA(bM,bM.THICKNESS),ZM=gA(bM,bM.IOR),YM=gA(bM,bM.ATTENUATION_DISTANCE),JM=gA(bM,bM.ATTENUATION_COLOR),KM=gA(bM,bM.LINE_SCALE),qM=gA(bM,bM.LINE_DASH_SIZE),_M=gA(bM,bM.LINE_GAP_SIZE),$M=(bM.LINE_WIDTH,gA(bM,bM.LINE_DASH_OFFSET)),eE=gA(bM,bM.POINT_SIZE),tE=gA(bM,bM.DISPERSION),nE=gA(bM,bM.LIGHT_MAP),iE=gA(bM,bM.AO),rE=Nx(new Cs).onReference((function(e){return e.material})).onRenderUpdate((function({material:e}){this.value.set(e.anisotropy*Math.cos(e.anisotropyRotation),e.anisotropy*Math.sin(e.anisotropyRotation))})),sE=xA((e=>e.context.setupModelViewProjection()),"vec4").once()().toVarying("v_modelViewProjection");class oE extends yv{static get type(){return"IndexNode"}constructor(e){super("uint"),this.scope=e,this.isIndexNode=!0}generate(e){const t=this.getNodeType(e),n=this.scope;let i,r;if(n===oE.VERTEX)i=e.getVertexIndex();else if(n===oE.INSTANCE)i=e.getInstanceIndex();else if(n===oE.DRAW)i=e.getDrawIndex();else if(n===oE.INVOCATION_LOCAL)i=e.getInvocationLocalIndex();else if(n===oE.INVOCATION_SUBGROUP)i=e.getInvocationSubgroupIndex();else{if(n!==oE.SUBGROUP)throw new Error("THREE.IndexNode: Unknown scope: "+n);i=e.getSubgroupIndex()}if("vertex"===e.shaderStage||"compute"===e.shaderStage)r=i;else{r=Ob(this).build(e,t)}return r}}oE.VERTEX="vertex",oE.INSTANCE="instance",oE.SUBGROUP="subgroup",oE.INVOCATION_LOCAL="invocationLocal",oE.INVOCATION_SUBGROUP="invocationSubgroup",oE.DRAW="draw";const aE=gA(oE,oE.VERTEX),lE=gA(oE,oE.INSTANCE),uE=(oE.SUBGROUP,oE.INVOCATION_SUBGROUP,oE.INVOCATION_LOCAL,gA(oE,oE.DRAW));class cE extends yv{static get type(){return"InstanceNode"}constructor(e,t,n=null){super("void"),this.count=e,this.instanceMatrix=t,this.instanceColor=n,this.instanceMatrixNode=null,this.instanceColorNode=null,this.updateType=hv.FRAME,this.buffer=null,this.bufferColor=null}setup(e){const{instanceMatrix:t,instanceColor:n}=this,{count:i}=t;let{instanceMatrixNode:r,instanceColorNode:s}=this;if(null===r){if(i<=1e3)r=Dw(t.array,"mat4",Math.max(i,1)).element(lE);else{const e=new Pc(t.array,16,1);this.buffer=e;const n=t.usage===ss?ew:$b,i=[n(e,"vec4",16,0),n(e,"vec4",16,4),n(e,"vec4",16,8),n(e,"vec4",16,12)];r=GA(...i)}this.instanceMatrixNode=r}if(n&&null===s){const e=new Pl(n.array,3),t=n.usage===ss?ew:$b;this.bufferColor=e,s=LA(t(e,"vec3",3,0)),this.instanceColorNode=s}const o=r.mul(lC).xyz;if(lC.assign(o),e.hasGeometryAttribute("normal")){const e=TC(xC,r);xC.assign(e)}null!==this.instanceColorNode&&YA("vec3","vInstanceColor").assign(this.instanceColorNode)}update(){this.instanceMatrix.usage!==ss&&null!==this.buffer&&this.instanceMatrix.version!==this.buffer.version&&(this.buffer.version=this.instanceMatrix.version),this.instanceColor&&this.instanceColor.usage!==ss&&null!==this.bufferColor&&this.instanceColor.version!==this.bufferColor.version&&(this.bufferColor.version=this.instanceColor.version)}}class dE extends cE{static get type(){return"InstancedMeshNode"}constructor(e){const{count:t,instanceMatrix:n,instanceColor:i}=e;super(t,n,i),this.instancedMesh=e}}const hE=pA(dE).setParameterLength(1);class fE extends yv{static get type(){return"BatchNode"}constructor(e){super("void"),this.batchMesh=e,this.batchingIdNode=null}setup(e){null===this.batchingIdNode&&(null===e.getDrawIndex()?this.batchingIdNode=lE:this.batchingIdNode=uE);const t=xA((([e])=>{const t=TA(ww(Nw(this.batchMesh._indirectTexture),0).x),n=TA(e).mod(t),i=TA(e).div(t);return Nw(this.batchMesh._indirectTexture,BA(n,i)).x})).setLayout({name:"getIndirectIndex",type:"uint",inputs:[{name:"id",type:"int"}]}),n=t(TA(this.batchingIdNode)),i=this.batchMesh._matricesTexture,r=TA(ww(Nw(i),0).x),s=EA(n).mul(4).toInt().toVar(),o=s.mod(r),a=s.div(r),l=GA(Nw(i,BA(o,a)),Nw(i,BA(o.add(1),a)),Nw(i,BA(o.add(2),a)),Nw(i,BA(o.add(3),a))),u=this.batchMesh._colorsTexture;if(null!==u){const e=xA((([e])=>{const t=TA(ww(Nw(u),0).x),n=e,i=n.mod(t),r=n.div(t);return Nw(u,BA(i,r)).rgb})).setLayout({name:"getBatchingColor",type:"vec3",inputs:[{name:"id",type:"int"}]}),t=e(n);YA("vec3","vBatchColor").assign(t)}const c=XA(l);lC.assign(l.mul(lC));const d=xC.div(LA(c[0].dot(c[0]),c[1].dot(c[1]),c[2].dot(c[2]))),h=c.mul(d).xyz;xC.assign(h),e.hasGeometryAttribute("tangent")&&lM.mulAssign(c)}}const pE=pA(fE).setParameterLength(1);const gE=new WeakMap;class mE extends yv{static get type(){return"SkinningNode"}constructor(e){super("void"),this.skinnedMesh=e,this.updateType=hv.OBJECT,this.skinIndexNode=xw("skinIndex","uvec4"),this.skinWeightNode=xw("skinWeight","vec4"),this.bindMatrixNode=GC("bindMatrix","mat4"),this.bindMatrixInverseNode=GC("bindMatrixInverse","mat4"),this.boneMatricesNode=VC("skeleton.boneMatrices","mat4",e.skeleton.bones.length),this.positionNode=lC,this.toPositionNode=lC,this.previousBoneMatricesNode=null}getSkinnedPosition(e=this.boneMatricesNode,t=this.positionNode){const{skinIndexNode:n,skinWeightNode:i,bindMatrixNode:r,bindMatrixInverseNode:s}=this,o=e.element(n.x),a=e.element(n.y),l=e.element(n.z),u=e.element(n.w),c=r.mul(t),d=kx(o.mul(i.x).mul(c),a.mul(i.y).mul(c),l.mul(i.z).mul(c),u.mul(i.w).mul(c));return s.mul(d).xyz}getSkinnedNormal(e=this.boneMatricesNode,t=xC){const{skinIndexNode:n,skinWeightNode:i,bindMatrixNode:r,bindMatrixInverseNode:s}=this,o=e.element(n.x),a=e.element(n.y),l=e.element(n.z),u=e.element(n.w);let c=kx(i.x.mul(o),i.y.mul(a),i.z.mul(l),i.w.mul(u));return c=s.mul(c).mul(r),c.transformDirection(t).xyz}getPreviousSkinnedPosition(e){const t=e.object;return null===this.previousBoneMatricesNode&&(t.skeleton.previousBoneMatrices=new Float32Array(t.skeleton.boneMatrices),this.previousBoneMatricesNode=VC("skeleton.previousBoneMatrices","mat4",t.skeleton.bones.length)),this.getSkinnedPosition(this.previousBoneMatricesNode,uC)}needsPreviousBoneMatrices(e){const t=e.renderer.getMRT();return t&&t.has("velocity")||!0===lv(e.object).useVelocity}setup(e){this.needsPreviousBoneMatrices(e)&&uC.assign(this.getPreviousSkinnedPosition(e));const t=this.getSkinnedPosition();if(this.toPositionNode&&this.toPositionNode.assign(t),e.hasGeometryAttribute("normal")){const t=this.getSkinnedNormal();xC.assign(t),e.hasGeometryAttribute("tangent")&&lM.assign(t)}return t}generate(e,t){if("void"!==t)return super.generate(e,t)}update(e){const t=e.object&&e.object.skeleton?e.object.skeleton:this.skinnedMesh.skeleton;gE.get(t)!==e.frameId&&(gE.set(t,e.frameId),null!==this.previousBoneMatricesNode&&t.previousBoneMatrices.set(t.boneMatrices),t.update())}}const vE=e=>cA(new mE(e));class AE extends yv{static get type(){return"LoopNode"}constructor(e=[]){super(),this.params=e}getVarName(e){return String.fromCharCode("i".charCodeAt(0)+e)}getProperties(e){const t=e.getNodeProperties(this);if(void 0!==t.stackNode)return t;const n={};for(let e=0,t=this.params.length-1;e<t;e++){const t=this.params[e],i=!0!==t.isNode&&t.name||this.getVarName(e),r=!0!==t.isNode&&t.type||"int";n[i]=hw(i,r)}const i=e.addStack();t.returnsNode=this.params[this.params.length-1](n,e),t.stackNode=i;const r=this.params[0];return!0!==r.isNode&&"function"==typeof r.update&&(t.updateNode=xA(this.params[0].update)(n)),e.removeStack(),t}getNodeType(e){const{returnsNode:t}=this.getProperties(e);return t?t.getNodeType(e):"void"}setup(e){this.getProperties(e)}generate(e){const t=this.getProperties(e),n=this.params,i=t.stackNode;for(let i=0,r=n.length-1;i<r;i++){const r=n[i];let s,o=!1,a=null,l=null,u=null,c=null,d=null,h=null;if(r.isNode?"bool"===r.getNodeType(e)?(o=!0,c="bool",l=r.build(e,c)):(c="int",u=this.getVarName(i),a="0",l=r.build(e,c),d="<"):(c=r.type||"int",u=r.name||this.getVarName(i),a=r.start,l=r.end,d=r.condition,h=r.update,"number"==typeof a?a=e.generateConst(c,a):a&&a.isNode&&(a=a.build(e,c)),"number"==typeof l?l=e.generateConst(c,l):l&&l.isNode&&(l=l.build(e,c)),void 0!==a&&void 0===l?(a+=" - 1",l="0",d=">="):void 0!==l&&void 0===a&&(a="0",d="<"),void 0===d&&(d=Number(a)>Number(l)?">=":"<")),o)s=`while ( ${l} )`;else{const n={start:a,end:l},i=n.start,r=n.end;let o;const f=()=>d.includes("<")?"+=":"-=";if(null!=h)switch(typeof h){case"function":o=e.flowStagesNode(t.updateNode,"void").code.replace(/\t|;/g,"");break;case"number":o=u+" "+f()+" "+e.generateConst(c,h);break;case"string":o=u+" "+h;break;default:h.isNode?o=u+" "+f()+" "+h.build(e):(console.error("THREE.TSL: 'Loop( { update: ... } )' is not a function, string or number."),o="break /* invalid update */")}else h="int"===c||"uint"===c?d.includes("<")?"++":"--":f()+" 1.",o=u+" "+h;s=`for ( ${e.getVar(c,u)+" = "+i}; ${u+" "+d+" "+r}; ${o} )`}e.addFlowCode((0===i?"\n":"")+e.tab+s+" {\n\n").addFlowTab()}const r=i.build(e,"void"),s=t.returnsNode?t.returnsNode.build(e):"";e.removeFlowTab().addFlowCode("\n"+e.tab+r);for(let t=0,n=this.params.length-1;t<n;t++)e.addFlowCode((0===t?"":e.tab)+"}\n\n").removeFlowTab();return e.addFlowTab(),s}}const xE=(...e)=>cA(new AE(fA(e,"int"))).toStack(),yE=()=>hw("break").toStack(),bE=new WeakMap,wE=new Js,CE=xA((({bufferMap:e,influence:t,stride:n,width:i,depth:r,offset:s})=>{const o=TA(aE).mul(n).add(s),a=o.div(i),l=o.sub(a.mul(i));return Nw(e,BA(l,a)).depth(r).xyz.mul(t)}));class ME extends yv{static get type(){return"MorphNode"}constructor(e){super("void"),this.mesh=e,this.morphBaseInfluence=Nx(1),this.updateType=hv.OBJECT}setup(e){const{geometry:t}=e,n=void 0!==t.morphAttributes.position,i=t.hasAttribute("normal")&&void 0!==t.morphAttributes.normal,r=t.morphAttributes.position||t.morphAttributes.normal||t.morphAttributes.color,s=void 0!==r?r.length:0,{texture:o,stride:a,size:l}=function(e){const t=void 0!==e.morphAttributes.position,n=void 0!==e.morphAttributes.normal,i=void 0!==e.morphAttributes.color,r=e.morphAttributes.position||e.morphAttributes.normal||e.morphAttributes.color,s=void 0!==r?r.length:0;let o=bE.get(e);if(void 0===o||o.count!==s){void 0!==o&&o.texture.dispose();const a=e.morphAttributes.position||[],l=e.morphAttributes.normal||[],u=e.morphAttributes.color||[];let c=0;!0===t&&(c=1),!0===n&&(c=2),!0===i&&(c=3);let d=e.attributes.position.count*c,h=1;const f=4096;d>f&&(h=Math.ceil(d/f),d=f);const p=new Float32Array(d*h*4*s),g=new _s(p,d,h,s);g.type=Ji,g.needsUpdate=!0;const m=4*c;for(let A=0;A<s;A++){const x=a[A],y=l[A],b=u[A],w=d*h*4*A;for(let C=0;C<x.count;C++){const M=C*m;!0===t&&(wE.fromBufferAttribute(x,C),p[w+M+0]=wE.x,p[w+M+1]=wE.y,p[w+M+2]=wE.z,p[w+M+3]=0),!0===n&&(wE.fromBufferAttribute(y,C),p[w+M+4]=wE.x,p[w+M+5]=wE.y,p[w+M+6]=wE.z,p[w+M+7]=0),!0===i&&(wE.fromBufferAttribute(b,C),p[w+M+8]=wE.x,p[w+M+9]=wE.y,p[w+M+10]=wE.z,p[w+M+11]=4===b.itemSize?wE.w:1)}}function v(){g.dispose(),bE.delete(e),e.removeEventListener("dispose",v)}o={count:s,texture:g,stride:c,size:new Cs(d,h)},bE.set(e,o),e.addEventListener("dispose",v)}return o}(t);!0===n&&lC.mulAssign(this.morphBaseInfluence),!0===i&&xC.mulAssign(this.morphBaseInfluence);const u=TA(l.width);xE(s,(({i:e})=>{const t=EA(0).toVar();this.mesh.count>1&&null!==this.mesh.morphTexture&&void 0!==this.mesh.morphTexture?t.assign(Nw(this.mesh.morphTexture,BA(TA(e).add(1),TA(lE))).r):t.assign(GC("morphTargetInfluences","float").element(e).toVar()),wA(t.notEqual(0),(()=>{!0===n&&lC.addAssign(CE({bufferMap:o,influence:t,stride:a,width:u,depth:e,offset:TA(0)})),!0===i&&xC.addAssign(CE({bufferMap:o,influence:t,stride:a,width:u,depth:e,offset:TA(1)}))}))}))}update(){const e=this.morphBaseInfluence;this.mesh.geometry.morphTargetsRelative?e.value=1:e.value=1-this.mesh.morphTargetInfluences.reduce(((e,t)=>e+t),0)}}const EE=pA(ME).setParameterLength(1);class TE extends yv{static get type(){return"LightingNode"}constructor(){super("vec3"),this.isLightingNode=!0}}class SE extends TE{static get type(){return"AONode"}constructor(e=null){super(),this.aoNode=e}setup(e){e.context.ambientOcclusion.mulAssign(this.aoNode)}}class PE extends wb{static get type(){return"LightingContextNode"}constructor(e,t=null,n=null,i=null){super(e),this.lightingModel=t,this.backdropNode=n,this.backdropAlphaNode=i,this._value=null}getContext(){const{backdropNode:e,backdropAlphaNode:t}=this,n={directDiffuse:LA().toVar("directDiffuse"),directSpecular:LA().toVar("directSpecular"),indirectDiffuse:LA().toVar("indirectDiffuse"),indirectSpecular:LA().toVar("indirectSpecular")};return{radiance:LA().toVar("radiance"),irradiance:LA().toVar("irradiance"),iblIrradiance:LA().toVar("iblIrradiance"),ambientOcclusion:EA(1).toVar("ambientOcclusion"),reflectedLight:n,backdrop:e,backdropAlpha:t}}setup(e){return this.value=this._value||(this._value=this.getContext()),this.value.lightingModel=this.lightingModel||e.context.lightingModel,super.setup(e)}}const NE=pA(PE);class BE extends TE{static get type(){return"IrradianceNode"}constructor(e){super(),this.node=e}setup(e){e.context.irradiance.addAssign(this.node)}}const DE=new Cs;class IE extends Tw{static get type(){return"ViewportTextureNode"}constructor(e=Hw,t=null,n=null){let i=null;null===n?(i=new ql,i.minFilter=Xi,n=i):i=n,super(n,e,t),this.generateMipmaps=!1,this.defaultFramebuffer=i,this.isOutputTextureNode=!0,this.updateBeforeType=hv.FRAME,this._cacheTextures=new WeakMap}getTextureForReference(e=null){let t,n;if(this.referenceNode?(t=this.referenceNode.defaultFramebuffer,n=this.referenceNode._cacheTextures):(t=this.defaultFramebuffer,n=this._cacheTextures),null===e)return t;if(!1===n.has(e)){const i=t.clone();n.set(e,i)}return n.get(e)}updateReference(e){const t=e.renderer.getRenderTarget();return this.value=this.getTextureForReference(t),this.value}updateBefore(e){const t=e.renderer,n=t.getRenderTarget();null===n?t.getDrawingBufferSize(DE):DE.set(n.width,n.height);const i=this.getTextureForReference(n);i.image.width===DE.width&&i.image.height===DE.height||(i.image.width=DE.width,i.image.height=DE.height,i.needsUpdate=!0);const r=i.generateMipmaps;i.generateMipmaps=this.generateMipmaps,t.copyFramebufferToTexture(i),i.generateMipmaps=r}clone(){const e=new this.constructor(this.uvNode,this.levelNode,this.value);return e.generateMipmaps=this.generateMipmaps,e}}const LE=pA(IE,null,null,{generateMipmaps:!0}).setParameterLength(0,3);let jE=null;class OE extends IE{static get type(){return"ViewportDepthTextureNode"}constructor(e=Hw,t=null){null===jE&&(jE=new _l),super(e,t,jE)}getTextureForReference(){return jE}}const zE=pA(OE).setParameterLength(0,2);class RE extends yv{static get type(){return"ViewportDepthNode"}constructor(e,t=null){super("float"),this.scope=e,this.valueNode=t,this.isViewportDepthNode=!0}generate(e){const{scope:t}=this;return t===RE.DEPTH_BASE?e.getFragDepth():super.generate(e)}setup({camera:e}){const{scope:t}=this,n=this.valueNode;let i=null;if(t===RE.DEPTH_BASE)null!==n&&(i=XE().assign(n));else if(t===RE.DEPTH)i=e.isPerspectiveCamera?FE(hC.z,Qw,Zw):kE(hC.z,Qw,Zw);else if(t===RE.LINEAR_DEPTH)if(null!==n)if(e.isPerspectiveCamera){const e=HE(n,Qw,Zw);i=kE(e,Qw,Zw)}else i=n;else i=kE(hC.z,Qw,Zw);return i}}RE.DEPTH_BASE="depthBase",RE.DEPTH="depth",RE.LINEAR_DEPTH="linearDepth";const kE=(e,t,n)=>e.add(t).div(t.sub(n)),FE=(e,t,n)=>t.add(e).mul(n).div(n.sub(t).mul(e)),HE=(e,t,n)=>t.mul(n).div(n.sub(t).mul(e).sub(n)),UE=(e,t,n)=>{t=t.max(1e-6).toVar();const i=yy(e.negate().div(t)),r=yy(n.div(t));return i.div(r)},XE=pA(RE,RE.DEPTH_BASE),GE=gA(RE,RE.DEPTH),VE=pA(RE,RE.LINEAR_DEPTH).setParameterLength(0,1);zE();GE.assign=e=>XE(e);class WE extends yv{static get type(){return"ClippingNode"}constructor(e=WE.DEFAULT){super(),this.scope=e}setup(e){super.setup(e);const t=e.clippingContext,{intersectionPlanes:n,unionPlanes:i}=t;return this.hardwareClipping=e.material.hardwareClipping,this.scope===WE.ALPHA_TO_COVERAGE?this.setupAlphaToCoverage(n,i):this.scope===WE.HARDWARE?this.setupHardwareClipping(i,e):this.setupDefault(n,i)}setupAlphaToCoverage(e,t){return xA((()=>{const n=EA().toVar("distanceToPlane"),i=EA().toVar("distanceToGradient"),r=EA(1).toVar("clipOpacity"),s=t.length;if(!1===this.hardwareClipping&&s>0){const e=jw(t).setGroup(Tx);xE(s,(({i:t})=>{const s=e.element(t);n.assign(hC.dot(s.xyz).negate().add(s.w)),i.assign(n.fwidth().div(2)),r.mulAssign(fb(i.negate(),i,n))}))}const o=e.length;if(o>0){const t=jw(e).setGroup(Tx),s=EA(1).toVar("intersectionClipOpacity");xE(o,(({i:e})=>{const r=t.element(e);n.assign(hC.dot(r.xyz).negate().add(r.w)),i.assign(n.fwidth().div(2)),s.mulAssign(fb(i.negate(),i,n).oneMinus())})),r.mulAssign(s.oneMinus())}JA.a.mulAssign(r),JA.a.equal(0).discard()}))()}setupDefault(e,t){return xA((()=>{const n=t.length;if(!1===this.hardwareClipping&&n>0){const e=jw(t).setGroup(Tx);xE(n,(({i:t})=>{const n=e.element(t);hC.dot(n.xyz).greaterThan(n.w).discard()}))}const i=e.length;if(i>0){const t=jw(e).setGroup(Tx),n=PA(!0).toVar("clipped");xE(i,(({i:e})=>{const i=t.element(e);n.assign(hC.dot(i.xyz).greaterThan(i.w).and(n))})),n.discard()}}))()}setupHardwareClipping(e,t){const n=e.length;return t.enableHardwareClipping(n),xA((()=>{const i=jw(e).setGroup(Tx),r=Ow(t.getClipDistance());xE(n,(({i:e})=>{const t=i.element(e),n=hC.dot(t.xyz).sub(t.w).negate();r.element(e).assign(n)}))}))()}}WE.ALPHA_TO_COVERAGE="alphaToCoverage",WE.DEFAULT="default",WE.HARDWARE="hardware";const QE=xA((([e])=>Ty(Hx(1e4,Sy(Hx(17,e.x).add(Hx(.1,e.y)))).mul(kx(.1,Ly(Sy(Hx(13,e.y).add(e.x)))))))),ZE=xA((([e])=>QE(NA(QE(e.xy),e.z)))),YE=xA((([e])=>{const t=Jy(Oy(ky(e.xyz)),Oy(Fy(e.xyz))),n=EA(1).div(EA(.05).mul(t)).toVar("pixScale"),i=NA(Ay(Cy(yy(n))),Ay(My(yy(n)))),r=NA(ZE(Cy(i.x.mul(e.xyz))),ZE(Cy(i.y.mul(e.xyz)))),s=Ty(yy(n)),o=kx(Hx(s.oneMinus(),r.x),Hx(s,r.y)),a=Yy(s,s.oneMinus()),l=LA(o.mul(o).div(Hx(2,a).mul(Fx(1,a))),o.sub(Hx(.5,a)).div(Fx(1,a)),Fx(1,Fx(1,o).mul(Fx(1,o)).div(Hx(2,a).mul(Fx(1,a))))),u=o.lessThan(a.oneMinus()).select(o.lessThan(a).select(l.x,l.y),l.z);return cb(u,1e-6,1)})).setLayout({name:"getAlphaHashThreshold",type:"float",inputs:[{name:"position",type:"vec3"}]});class JE extends Aw{static get type(){return"VertexColorNode"}constructor(e){super(null,"vec4"),this.isVertexColorNode=!0,this.index=e}getAttributeName(){const e=this.index;return"color"+(e>0?e:"")}generate(e){const t=this.getAttributeName(e);let n;return n=!0===e.hasGeometryAttribute(t)?super.generate(e):e.generateConst(this.nodeType,new Js(1,1,1,1)),n}serialize(e){super.serialize(e),e.index=this.index}deserialize(e){super.deserialize(e),this.index=e.index}}const KE=(e=0)=>cA(new JE(e)),qE=xA((([e])=>RA(e.rgb.mul(e.a),e.a)),{color:"vec4",return:"vec4"});class _E extends Ca{static get type(){return"NodeMaterial"}get type(){return this.constructor.type}set type(e){}constructor(){super(),this.isNodeMaterial=!0,this.fog=!0,this.lights=!1,this.hardwareClipping=!1,this.lightsNode=null,this.envNode=null,this.aoNode=null,this.colorNode=null,this.normalNode=null,this.opacityNode=null,this.backdropNode=null,this.backdropAlphaNode=null,this.alphaTestNode=null,this.maskNode=null,this.positionNode=null,this.geometryNode=null,this.depthNode=null,this.receivedShadowPositionNode=null,this.castShadowPositionNode=null,this.receivedShadowNode=null,this.castShadowNode=null,this.outputNode=null,this.mrtNode=null,this.fragmentNode=null,this.vertexNode=null,Object.defineProperty(this,"shadowPositionNode",{get:()=>this.receivedShadowPositionNode,set:e=>{console.warn('THREE.NodeMaterial: ".shadowPositionNode" was renamed to ".receivedShadowPositionNode".'),this.receivedShadowPositionNode=e}})}customProgramCacheKey(){return this.type+tv(this)}build(e){this.setup(e)}setupObserver(e){return new Km(e)}setup(e){e.context.setupNormal=()=>Lb(this.setupNormal(e),"NORMAL","vec3"),e.context.setupPositionView=()=>this.setupPositionView(e),e.context.setupModelViewProjection=()=>this.setupModelViewProjection(e);const t=e.renderer,n=t.getRenderTarget();e.addStack();const i=Lb(this.setupVertex(e),"VERTEX"),r=this.vertexNode||i;let s;e.stack.outputNode=r,this.setupHardwareClipping(e),null!==this.geometryNode&&(e.stack.outputNode=e.stack.outputNode.bypass(this.geometryNode)),e.addFlow("vertex",e.removeStack()),e.addStack();const o=this.setupClipping(e);if(!0!==this.depthWrite&&!0!==this.depthTest||(null!==n?!0===n.depthBuffer&&this.setupDepth(e):!0===t.depth&&this.setupDepth(e)),null===this.fragmentNode){this.setupDiffuseColor(e),this.setupVariants(e);const i=this.setupLighting(e);null!==o&&e.stack.add(o);const r=RA(i,JA.a).max(0);s=this.setupOutput(e,r),fx.assign(s);const a=null!==this.outputNode;if(a&&(s=this.outputNode),null!==n){const e=t.getMRT(),n=this.mrtNode;null!==e?(a&&fx.assign(s),s=e,null!==n&&(s=e.merge(n))):null!==n&&(s=n)}}else{let t=this.fragmentNode;!0!==t.isOutputStructNode&&(t=RA(t)),s=this.setupOutput(e,t)}e.stack.outputNode=s,e.addFlow("fragment",e.removeStack()),e.observer=this.setupObserver(e)}setupClipping(e){if(null===e.clippingContext)return null;const{unionPlanes:t,intersectionPlanes:n}=e.clippingContext;let i=null;if(t.length>0||n.length>0){const t=e.renderer.samples;this.alphaToCoverage&&t>1?i=cA(new WE(WE.ALPHA_TO_COVERAGE)):e.stack.add(cA(new WE))}return i}setupHardwareClipping(e){if(this.hardwareClipping=!1,null===e.clippingContext)return;const t=e.clippingContext.unionPlanes.length;t>0&&t<=8&&e.isAvailable("clipDistance")&&(e.stack.add(cA(new WE(WE.HARDWARE))),this.hardwareClipping=!0)}setupDepth(e){const{renderer:t,camera:n}=e;let i=this.depthNode;if(null===i){const e=t.getMRT();e&&e.has("depth")?i=e.get("depth"):!0===t.logarithmicDepthBuffer&&(i=n.isPerspectiveCamera?UE(hC.z,Qw,Zw):kE(hC.z,Qw,Zw))}null!==i&&GE.assign(i).toStack()}setupPositionView(){return iC.mul(lC).xyz}setupModelViewProjection(){return Yw.mul(hC)}setupVertex(e){return e.addStack(),this.setupPosition(e),e.context.vertex=e.removeStack(),sE}setupPosition(e){const{object:t,geometry:n}=e;if((n.morphAttributes.position||n.morphAttributes.normal||n.morphAttributes.color)&&EE(t).toStack(),!0===t.isSkinnedMesh&&vE(t).toStack(),this.displacementMap){const e=QC("displacementMap","texture"),t=QC("displacementScale","float"),n=QC("displacementBias","float");lC.addAssign(xC.normalize().mul(e.x.mul(t).add(n)))}return t.isBatchedMesh&&pE(t).toStack(),t.isInstancedMesh&&t.instanceMatrix&&!0===t.instanceMatrix.isInstancedBufferAttribute&&hE(t).toStack(),null!==this.positionNode&&lC.assign(Lb(this.positionNode,"POSITION","vec3")),lC}setupDiffuseColor({object:e,geometry:t}){null!==this.maskNode&&PA(this.maskNode).not().discard();let n=this.colorNode?RA(this.colorNode):CM;if(!0===this.vertexColors&&t.hasAttribute("color")&&(n=n.mul(KE())),e.instanceColor){n=YA("vec3","vInstanceColor").mul(n)}if(e.isBatchedMesh&&e._colorsTexture){n=YA("vec3","vBatchColor").mul(n)}JA.assign(n);const i=this.opacityNode?EA(this.opacityNode):TM;JA.a.assign(JA.a.mul(i));let r=null;(null!==this.alphaTestNode||this.alphaTest>0)&&(r=null!==this.alphaTestNode?EA(this.alphaTestNode):wM,JA.a.lessThanEqual(r).discard()),!0===this.alphaHash&&JA.a.lessThan(YE(lC)).discard();!1===this.transparent&&1===this.blending&&!1===this.alphaToCoverage?JA.a.assign(1):null===r&&JA.a.lessThanEqual(0).discard()}setupVariants(){}setupOutgoingLight(){return!0===this.lights?LA(0):JA.rgb}setupNormal(){return this.normalNode?LA(this.normalNode):jM}setupEnvironment(){let e=null;return this.envNode?e=this.envNode:this.envMap&&(e=this.envMap.isCubeTexture?QC("envMap","cubeTexture"):QC("envMap","texture")),e}setupLightMap(e){let t=null;return e.material.lightMap&&(t=new BE(nE)),t}setupLights(e){const t=[],n=this.setupEnvironment(e);n&&n.isLightingNode&&t.push(n);const i=this.setupLightMap(e);if(i&&i.isLightingNode&&t.push(i),null!==this.aoNode||e.material.aoMap){const e=null!==this.aoNode?this.aoNode:iE;t.push(new SE(e))}let r=this.lightsNode||e.lightsNode;return t.length>0&&(r=e.renderer.lighting.createNode([...r.getLights(),...t])),r}setupLightingModel(){}setupLighting(e){const{material:t}=e,{backdropNode:n,backdropAlphaNode:i,emissiveNode:r}=this,s=!0===this.lights||null!==this.lightsNode?this.setupLights(e):null;let o=this.setupOutgoingLight(e);if(s&&s.getScope().hasLights){const t=this.setupLightingModel(e)||null;o=NE(s,t,n,i)}else null!==n&&(o=LA(null!==i?ub(o,n,i):n));return(r&&!0===r.isNode||t.emissive&&!0===t.emissive.isColor)&&(KA.assign(LA(r||EM)),o=o.add(KA)),o}setupFog(e,t){const n=e.fogNode;return n&&(fx.assign(t),t=RA(n.toVar())),t}setupPremultipliedAlpha(e,t){return qE(t)}setupOutput(e,t){return!0===this.fog&&(t=this.setupFog(e,t)),!0===this.premultipliedAlpha&&(t=this.setupPremultipliedAlpha(e,t)),t}setDefaultValues(e){for(const t in e){const n=e[t];void 0===this[t]&&(this[t]=n,n&&n.clone&&(this[t]=n.clone()))}const t=Object.getOwnPropertyDescriptors(e.constructor.prototype);for(const e in t)void 0===Object.getOwnPropertyDescriptor(this.constructor.prototype,e)&&void 0!==t[e].get&&Object.defineProperty(this.constructor.prototype,e,t[e])}toJSON(e){const t=void 0===e||"string"==typeof e;t&&(e={textures:{},images:{},nodes:{}});const n=Ca.prototype.toJSON.call(this,e),i=nv(this);n.inputNodes={};for(const{property:t,childNode:r}of i)n.inputNodes[t]=r.toJSON(e).uuid;function r(e){const t=[];for(const n in e){const i=e[n];delete i.metadata,t.push(i)}return t}if(t){const t=r(e.textures),i=r(e.images),s=r(e.nodes);t.length>0&&(n.textures=t),i.length>0&&(n.images=i),s.length>0&&(n.nodes=s)}return n}copy(e){return this.lightsNode=e.lightsNode,this.envNode=e.envNode,this.colorNode=e.colorNode,this.normalNode=e.normalNode,this.opacityNode=e.opacityNode,this.backdropNode=e.backdropNode,this.backdropAlphaNode=e.backdropAlphaNode,this.alphaTestNode=e.alphaTestNode,this.maskNode=e.maskNode,this.positionNode=e.positionNode,this.geometryNode=e.geometryNode,this.depthNode=e.depthNode,this.receivedShadowPositionNode=e.receivedShadowPositionNode,this.castShadowPositionNode=e.castShadowPositionNode,this.receivedShadowNode=e.receivedShadowNode,this.castShadowNode=e.castShadowNode,this.outputNode=e.outputNode,this.mrtNode=e.mrtNode,this.fragmentNode=e.fragmentNode,this.vertexNode=e.vertexNode,super.copy(e)}}const $E=new Hl;class eT extends _E{static get type(){return"LineBasicNodeMaterial"}constructor(e){super(),this.isLineBasicNodeMaterial=!0,this.setDefaultValues($E),this.setValues(e)}}const tT=new Iu;class nT extends _E{static get type(){return"LineDashedNodeMaterial"}constructor(e){super(),this.isLineDashedNodeMaterial=!0,this.setDefaultValues(tT),this.dashOffset=0,this.offsetNode=null,this.dashScaleNode=null,this.dashSizeNode=null,this.gapSizeNode=null,this.setValues(e)}setupVariants(){const e=this.offsetNode?EA(this.offsetNode):$M,t=this.dashScaleNode?EA(this.dashScaleNode):KM,n=this.dashSizeNode?EA(this.dashSizeNode):qM,i=this.gapSizeNode?EA(this.gapSizeNode):_M;px.assign(n),gx.assign(i);const r=Ob(xw("lineDistance").mul(t));(e?r.add(e):r).mod(px.add(gx)).greaterThan(px).discard()}}const iT=e=>cA(e).mul(.5).add(.5),rT=new Su;class sT extends _E{static get type(){return"MeshNormalNodeMaterial"}constructor(e){super(),this.isMeshNormalNodeMaterial=!0,this.setDefaultValues(rT),this.setValues(e)}setupDiffuseColor(){const e=this.opacityNode?EA(this.opacityNode):TM;JA.assign(Xb(RA(iT(CC),e),qr))}}const oT=xA((([e=dC])=>{const t=e.z.atan(e.x).mul(1/(2*Math.PI)).add(.5),n=e.y.clamp(-1,1).asin().mul(1/Math.PI).add(.5);return NA(t,n)}));class aT extends Al{constructor(e=1,t={}){super(e,t),this.isCubeRenderTarget=!0}fromEquirectangularTexture(e,t){const n=t.minFilter,i=t.generateMipmaps;t.generateMipmaps=!0,this.texture.type=t.type,this.texture.colorSpace=t.colorSpace,this.texture.generateMipmaps=t.generateMipmaps,this.texture.minFilter=t.minFilter,this.texture.magFilter=t.magFilter;const r=new rl(5,5,5),s=oT(dC),o=new _E;o.colorNode=Pw(t,s,0),o.side=1,o.blending=0;const a=new nl(r,o),l=new wl;l.add(a),t.minFilter===Xi&&(t.minFilter=Hi);const u=new ml(1,10,this),c=e.getMRT();return e.setMRT(null),u.update(e,l),e.setMRT(c),t.minFilter=n,t.currentGenerateMipmaps=i,a.geometry.dispose(),a.material.dispose(),this}}const lT=new WeakMap;class uT extends Cv{static get type(){return"CubeMapNode"}constructor(e){super("vec3"),this.envNode=e,this._cubeTexture=null,this._cubeTextureNode=HC(null);const t=new vl;t.isRenderTargetTexture=!0,this._defaultTexture=t,this.updateBeforeType=hv.RENDER}updateBefore(e){const{renderer:t,material:n}=e,i=this.envNode;if(i.isTextureNode||i.isMaterialReferenceNode){const e=i.isTextureNode?i.value:n[i.property];if(e&&e.isTexture){const n=e.mapping;if(n===Di||n===Ii){if(lT.has(e)){const t=lT.get(e);dT(t,e.mapping),this._cubeTexture=t}else{const n=e.image;if(function(e){return null!=e&&e.height>0}(n)){const i=new aT(n.height);i.fromEquirectangularTexture(t,e),dT(i.texture,e.mapping),this._cubeTexture=i.texture,lT.set(e,i.texture),e.addEventListener("dispose",cT)}else this._cubeTexture=this._defaultTexture}this._cubeTextureNode.value=this._cubeTexture}else this._cubeTextureNode=this.envNode}}}setup(e){return this.updateBefore(e),this._cubeTextureNode}}function cT(e){const t=e.target;t.removeEventListener("dispose",cT);const n=lT.get(t);void 0!==n&&(lT.delete(t),n.dispose())}function dT(e,t){t===Di?e.mapping=Ni:t===Ii&&(e.mapping=Bi)}const hT=pA(uT).setParameterLength(1);class fT extends TE{static get type(){return"BasicEnvironmentNode"}constructor(e=null){super(),this.envNode=e}setup(e){e.context.environment=hT(this.envNode)}}class pT extends TE{static get type(){return"BasicLightMapNode"}constructor(e=null){super(),this.lightMapNode=e}setup(e){const t=EA(1/Math.PI);e.context.irradianceLightMap=this.lightMapNode.mul(t)}}class gT{start(e){e.lightsNode.setupLights(e,e.lightsNode.getLightNodes(e)),this.indirect(e)}finish(){}direct(){}directRectArea(){}indirect(){}ambientOcclusion(){}}class mT extends gT{constructor(){super()}indirect({context:e}){const t=e.ambientOcclusion,n=e.reflectedLight,i=e.irradianceLightMap;n.indirectDiffuse.assign(RA(0)),i?n.indirectDiffuse.addAssign(i):n.indirectDiffuse.addAssign(RA(1,1,1,0)),n.indirectDiffuse.mulAssign(t),n.indirectDiffuse.mulAssign(JA.rgb)}finish(e){const{material:t,context:n}=e,i=n.outgoingLight,r=e.context.environment;if(r)switch(t.combine){case 0:i.rgb.assign(ub(i.rgb,i.rgb.mul(r.rgb),BM.mul(DM)));break;case 1:i.rgb.assign(ub(i.rgb,r.rgb,BM.mul(DM)));break;case 2:i.rgb.addAssign(r.rgb.mul(BM.mul(DM)));break;default:console.warn("THREE.BasicLightingModel: Unsupported .combine value:",t.combine)}}}const vT=new Ma;class AT extends _E{static get type(){return"MeshBasicNodeMaterial"}constructor(e){super(),this.isMeshBasicNodeMaterial=!0,this.lights=!0,this.setDefaultValues(vT),this.setValues(e)}setupNormal(){return vC(bC)}setupEnvironment(e){const t=super.setupEnvironment(e);return t?new fT(t):null}setupLightMap(e){let t=null;return e.material.lightMap&&(t=new pT(nE)),t}setupOutgoingLight(){return JA.rgb}setupLightingModel(){return new mT}}const xT=xA((({f0:e,f90:t,dotVH:n})=>{const i=n.mul(-5.55473).sub(6.98316).mul(n).exp2();return e.mul(i.oneMinus()).add(t.mul(i))})),yT=xA((e=>e.diffuseColor.mul(1/Math.PI))),bT=xA((({dotNH:e})=>hx.mul(EA(.5)).add(1).mul(EA(1/Math.PI)).mul(e.pow(hx)))),wT=xA((({lightDirection:e})=>{const t=e.add(fC).normalize(),n=CC.dot(t).clamp(),i=fC.dot(t).clamp(),r=xT({f0:cx,f90:1,dotVH:i}),s=EA(.25),o=bT({dotNH:n});return r.mul(s).mul(o)}));class CT extends mT{constructor(e=!0){super(),this.specular=e}direct({lightDirection:e,lightColor:t,reflectedLight:n}){const i=CC.dot(e).clamp().mul(t);n.directDiffuse.addAssign(i.mul(yT({diffuseColor:JA.rgb}))),!0===this.specular&&n.directSpecular.addAssign(i.mul(wT({lightDirection:e})).mul(BM))}indirect(e){const{ambientOcclusion:t,irradiance:n,reflectedLight:i}=e.context;i.indirectDiffuse.addAssign(n.mul(yT({diffuseColor:JA}))),i.indirectDiffuse.mulAssign(t)}}const MT=new Pu;class ET extends _E{static get type(){return"MeshLambertNodeMaterial"}constructor(e){super(),this.isMeshLambertNodeMaterial=!0,this.lights=!0,this.setDefaultValues(MT),this.setValues(e)}setupEnvironment(e){const t=super.setupEnvironment(e);return t?new fT(t):null}setupLightingModel(){return new CT(!1)}}const TT=new Eu;class ST extends _E{static get type(){return"MeshPhongNodeMaterial"}constructor(e){super(),this.isMeshPhongNodeMaterial=!0,this.lights=!0,this.shininessNode=null,this.specularNode=null,this.setDefaultValues(TT),this.setValues(e)}setupEnvironment(e){const t=super.setupEnvironment(e);return t?new fT(t):null}setupLightingModel(){return new CT}setupVariants(){const e=(this.shininessNode?EA(this.shininessNode):MM).max(1e-4);hx.assign(e);const t=this.specularNode||SM;cx.assign(t)}copy(e){return this.shininessNode=e.shininessNode,this.specularNode=e.specularNode,super.copy(e)}}const PT=xA((e=>{if(!1===e.geometry.hasAttribute("normal"))return EA(0);const t=bC.dFdx().abs().max(bC.dFdy().abs());return t.x.max(t.y).max(t.z)})),NT=xA((e=>{const{roughness:t}=e,n=PT();let i=t.max(.0525);return i=i.add(n),i=i.min(1),i})),BT=xA((({alpha:e,dotNL:t,dotNV:n})=>{const i=e.pow2(),r=t.mul(i.add(i.oneMinus().mul(n.pow2())).sqrt()),s=n.mul(i.add(i.oneMinus().mul(t.pow2())).sqrt());return Ux(.5,r.add(s).max(dy))})).setLayout({name:"V_GGX_SmithCorrelated",type:"float",inputs:[{name:"alpha",type:"float"},{name:"dotNL",type:"float"},{name:"dotNV",type:"float"}]}),DT=xA((({alphaT:e,alphaB:t,dotTV:n,dotBV:i,dotTL:r,dotBL:s,dotNV:o,dotNL:a})=>{const l=a.mul(LA(e.mul(n),t.mul(i),o).length()),u=o.mul(LA(e.mul(r),t.mul(s),a).length());return Ux(.5,l.add(u)).saturate()})).setLayout({name:"V_GGX_SmithCorrelated_Anisotropic",type:"float",inputs:[{name:"alphaT",type:"float",qualifier:"in"},{name:"alphaB",type:"float",qualifier:"in"},{name:"dotTV",type:"float",qualifier:"in"},{name:"dotBV",type:"float",qualifier:"in"},{name:"dotTL",type:"float",qualifier:"in"},{name:"dotBL",type:"float",qualifier:"in"},{name:"dotNV",type:"float",qualifier:"in"},{name:"dotNL",type:"float",qualifier:"in"}]}),IT=xA((({alpha:e,dotNH:t})=>{const n=e.pow2(),i=t.pow2().mul(n.oneMinus()).oneMinus();return n.div(i.pow2()).mul(1/Math.PI)})).setLayout({name:"D_GGX",type:"float",inputs:[{name:"alpha",type:"float"},{name:"dotNH",type:"float"}]}),LT=EA(1/Math.PI),jT=xA((({alphaT:e,alphaB:t,dotNH:n,dotTH:i,dotBH:r})=>{const s=e.mul(t),o=LA(t.mul(i),e.mul(r),s.mul(n)),a=o.dot(o),l=s.div(a);return LT.mul(s.mul(l.pow2()))})).setLayout({name:"D_GGX_Anisotropic",type:"float",inputs:[{name:"alphaT",type:"float",qualifier:"in"},{name:"alphaB",type:"float",qualifier:"in"},{name:"dotNH",type:"float",qualifier:"in"},{name:"dotTH",type:"float",qualifier:"in"},{name:"dotBH",type:"float",qualifier:"in"}]}),OT=xA((({lightDirection:e,f0:t,f90:n,roughness:i,f:r,normalView:s=CC,USE_IRIDESCENCE:o,USE_ANISOTROPY:a})=>{const l=i.pow2(),u=e.add(fC).normalize(),c=s.dot(e).clamp(),d=s.dot(fC).clamp(),h=s.dot(u).clamp(),f=fC.dot(u).clamp();let p,g,m=xT({f0:t,f90:n,dotVH:f});if(aA(o)&&(m=ix.mix(m,r)),aA(a)){const t=lx.dot(e),n=lx.dot(fC),i=lx.dot(u),r=ux.dot(e),s=ux.dot(fC),o=ux.dot(u);p=DT({alphaT:ox,alphaB:l,dotTV:n,dotBV:s,dotTL:t,dotBL:r,dotNV:d,dotNL:c}),g=jT({alphaT:ox,alphaB:l,dotNH:h,dotTH:i,dotBH:o})}else p=BT({alpha:l,dotNL:c,dotNV:d}),g=IT({alpha:l,dotNH:h});return m.mul(p).mul(g)})),zT=xA((({roughness:e,dotNV:t})=>{const n=RA(-1,-.0275,-.572,.022),i=RA(1,.0425,1.04,-.04),r=e.mul(n).add(i),s=r.x.mul(r.x).min(t.mul(-9.28).exp2()).mul(r.x).add(r.y);return NA(-1.04,1.04).mul(s).add(r.zw)})).setLayout({name:"DFGApprox",type:"vec2",inputs:[{name:"roughness",type:"float"},{name:"dotNV",type:"vec3"}]}),RT=xA((e=>{const{dotNV:t,specularColor:n,specularF90:i,roughness:r}=e,s=zT({dotNV:t,roughness:r});return n.mul(s.x).add(i.mul(s.y))})),kT=xA((({f:e,f90:t,dotVH:n})=>{const i=n.oneMinus().saturate(),r=i.mul(i),s=i.mul(r,r).clamp(0,.9999);return e.sub(LA(t).mul(s)).div(s.oneMinus())})).setLayout({name:"Schlick_to_F0",type:"vec3",inputs:[{name:"f",type:"vec3"},{name:"f90",type:"float"},{name:"dotVH",type:"float"}]}),FT=xA((({roughness:e,dotNH:t})=>{const n=e.pow2(),i=EA(1).div(n),r=t.pow2().oneMinus().max(.0078125);return EA(2).add(i).mul(r.pow(i.mul(.5))).div(2*Math.PI)})).setLayout({name:"D_Charlie",type:"float",inputs:[{name:"roughness",type:"float"},{name:"dotNH",type:"float"}]}),HT=xA((({dotNV:e,dotNL:t})=>EA(1).div(EA(4).mul(t.add(e).sub(t.mul(e)))))).setLayout({name:"V_Neubelt",type:"float",inputs:[{name:"dotNV",type:"float"},{name:"dotNL",type:"float"}]}),UT=xA((({lightDirection:e})=>{const t=e.add(fC).normalize(),n=CC.dot(e).clamp(),i=CC.dot(fC).clamp(),r=CC.dot(t).clamp(),s=FT({roughness:nx,dotNH:r}),o=HT({dotNV:i,dotNL:n});return tx.mul(s).mul(o)})),XT=xA((({N:e,V:t,roughness:n})=>{const i=e.dot(t).saturate(),r=NA(n,i.oneMinus().sqrt());return r.assign(r.mul(.984375).add(.0078125)),r})).setLayout({name:"LTC_Uv",type:"vec2",inputs:[{name:"N",type:"vec3"},{name:"V",type:"vec3"},{name:"roughness",type:"float"}]}),GT=xA((({f:e})=>{const t=e.length();return Jy(t.mul(t).add(e.z).div(t.add(1)),0)})).setLayout({name:"LTC_ClippedSphereFormFactor",type:"float",inputs:[{name:"f",type:"vec3"}]}),VT=xA((({v1:e,v2:t})=>{const n=e.dot(t),i=n.abs().toVar(),r=i.mul(.0145206).add(.4965155).mul(i).add(.8543985).toVar(),s=i.add(4.1616724).mul(i).add(3.417594).toVar(),o=r.div(s),a=n.greaterThan(0).select(o,Jy(n.mul(n).oneMinus(),1e-7).inverseSqrt().mul(.5).sub(o));return e.cross(t).mul(a)})).setLayout({name:"LTC_EdgeVectorFormFactor",type:"vec3",inputs:[{name:"v1",type:"vec3"},{name:"v2",type:"vec3"}]}),WT=xA((({N:e,V:t,P:n,mInv:i,p0:r,p1:s,p2:o,p3:a})=>{const l=s.sub(r).toVar(),u=a.sub(r).toVar(),c=l.cross(u),d=LA().toVar();return wA(c.dot(n.sub(r)).greaterThanEqual(0),(()=>{const l=t.sub(e.mul(t.dot(e))).normalize(),u=e.cross(l).negate(),c=i.mul(XA(l,u,e).transpose()).toVar(),h=c.mul(r.sub(n)).normalize().toVar(),f=c.mul(s.sub(n)).normalize().toVar(),p=c.mul(o.sub(n)).normalize().toVar(),g=c.mul(a.sub(n)).normalize().toVar(),m=LA(0).toVar();m.addAssign(VT({v1:h,v2:f})),m.addAssign(VT({v1:f,v2:p})),m.addAssign(VT({v1:p,v2:g})),m.addAssign(VT({v1:g,v2:h})),d.assign(LA(GT({f:m})))})),d})).setLayout({name:"LTC_Evaluate",type:"vec3",inputs:[{name:"N",type:"vec3"},{name:"V",type:"vec3"},{name:"P",type:"vec3"},{name:"mInv",type:"mat3"},{name:"p0",type:"vec3"},{name:"p1",type:"vec3"},{name:"p2",type:"vec3"},{name:"p3",type:"vec3"}]}),QT=1/6,ZT=e=>Hx(QT,Hx(e,Hx(e,e.negate().add(3)).sub(3)).add(1)),YT=e=>Hx(QT,Hx(e,Hx(e,Hx(3,e).sub(6))).add(4)),JT=e=>Hx(QT,Hx(e,Hx(e,Hx(-3,e).add(3)).add(3)).add(1)),KT=e=>Hx(QT,nb(e,3)),qT=e=>ZT(e).add(YT(e)),_T=e=>JT(e).add(KT(e)),$T=e=>kx(-1,YT(e).div(ZT(e).add(YT(e)))),eS=e=>kx(1,KT(e).div(JT(e).add(KT(e)))),tS=(e,t,n)=>{const i=e.uvNode,r=Hx(i,t.zw).add(.5),s=Cy(r),o=Ty(r),a=qT(o.x),l=_T(o.x),u=$T(o.x),c=eS(o.x),d=$T(o.y),h=eS(o.y),f=NA(s.x.add(u),s.y.add(d)).sub(.5).mul(t.xy),p=NA(s.x.add(c),s.y.add(d)).sub(.5).mul(t.xy),g=NA(s.x.add(u),s.y.add(h)).sub(.5).mul(t.xy),m=NA(s.x.add(c),s.y.add(h)).sub(.5).mul(t.xy),v=qT(o.y).mul(kx(a.mul(e.sample(f).level(n)),l.mul(e.sample(p).level(n)))),A=_T(o.y).mul(kx(a.mul(e.sample(g).level(n)),l.mul(e.sample(m).level(n))));return v.add(A)},nS=xA((([e,t])=>{const n=NA(e.size(TA(t))),i=NA(e.size(TA(t.add(1)))),r=Ux(1,n),s=Ux(1,i),o=tS(e,RA(r,n),Cy(t)),a=tS(e,RA(s,i),My(t));return Ty(t).mix(o,a)})),iS=xA((([e,t,n,i,r])=>{const s=LA(hb(t.negate(),Ey(e),Ux(1,i))),o=LA(Oy(r[0].xyz),Oy(r[1].xyz),Oy(r[2].xyz));return Ey(s).mul(n.mul(o))})).setLayout({name:"getVolumeTransmissionRay",type:"vec3",inputs:[{name:"n",type:"vec3"},{name:"v",type:"vec3"},{name:"thickness",type:"float"},{name:"ior",type:"float"},{name:"modelMatrix",type:"mat4"}]}),rS=xA((([e,t])=>e.mul(cb(t.mul(2).sub(2),0,1)))).setLayout({name:"applyIorToRoughness",type:"float",inputs:[{name:"roughness",type:"float"},{name:"ior",type:"float"}]}),sS=LE(),oS=LE(),aS=xA((([e,t,n],{material:i})=>{const r=(1===i.side?sS:oS).sample(e),s=yy(Uw.x).mul(rS(t,n));return nS(r,s)})),lS=xA((([e,t,n])=>(wA(n.notEqual(0),(()=>{const i=xy(t).negate().div(n);return vy(i.negate().mul(e))})),LA(1)))).setLayout({name:"volumeAttenuation",type:"vec3",inputs:[{name:"transmissionDistance",type:"float"},{name:"attenuationColor",type:"vec3"},{name:"attenuationDistance",type:"float"}]}),uS=xA((([e,t,n,i,r,s,o,a,l,u,c,d,h,f,p])=>{let g,m;if(p){g=RA().toVar(),m=LA().toVar();const r=c.sub(1).mul(p.mul(.025)),s=LA(c.sub(r),c,c.add(r));xE({start:0,end:3},(({i:r})=>{const c=s.element(r),p=iS(e,t,d,c,a),v=o.add(p),A=u.mul(l.mul(RA(v,1))),x=NA(A.xy.div(A.w)).toVar();x.addAssign(1),x.divAssign(2),x.assign(NA(x.x,x.y.oneMinus()));const y=aS(x,n,c);g.element(r).assign(y.element(r)),g.a.addAssign(y.a),m.element(r).assign(i.element(r).mul(lS(Oy(p),h,f).element(r)))})),g.a.divAssign(3)}else{const r=iS(e,t,d,c,a),s=o.add(r),p=u.mul(l.mul(RA(s,1))),v=NA(p.xy.div(p.w)).toVar();v.addAssign(1),v.divAssign(2),v.assign(NA(v.x,v.y.oneMinus())),g=aS(v,n,c),m=i.mul(lS(Oy(r),h,f))}const v=m.rgb.mul(g.rgb),A=e.dot(t).clamp(),x=LA(RT({dotNV:A,specularColor:r,specularF90:s,roughness:n})),y=m.r.add(m.g,m.b).div(3);return RA(x.oneMinus().mul(v),g.a.oneMinus().mul(y).oneMinus())})),cS=XA(3.2404542,-.969266,.0556434,-1.5371385,1.8760108,-.2040259,-.4985314,.041556,1.0572252),dS=(e,t)=>e.sub(t).div(e.add(t)).pow2(),hS=xA((({outsideIOR:e,eta2:t,cosTheta1:n,thinFilmThickness:i,baseF0:r})=>{const s=ub(e,t,fb(0,.03,i)),o=e.div(s).pow2().mul(n.pow2().oneMinus()).oneMinus();wA(o.lessThan(0),(()=>LA(1)));const a=o.sqrt(),l=dS(s,e),u=xT({f0:l,f90:1,dotVH:n}),c=u.oneMinus(),d=s.lessThan(e).select(Math.PI,0),h=EA(Math.PI).sub(d),f=(e=>{const t=e.sqrt();return LA(1).add(t).div(LA(1).sub(t))})(r.clamp(0,.9999)),p=dS(f,s.toVec3()),g=xT({f0:p,f90:1,dotVH:a}),m=LA(f.x.lessThan(s).select(Math.PI,0),f.y.lessThan(s).select(Math.PI,0),f.z.lessThan(s).select(Math.PI,0)),v=s.mul(i,a,2),A=LA(h).add(m),x=u.mul(g).clamp(1e-5,.9999),y=x.sqrt(),b=c.pow2().mul(g).div(LA(1).sub(x)),w=u.add(b).toVar(),C=b.sub(c).toVar();return xE({start:1,end:2,condition:"<=",name:"m"},(({m:e})=>{C.mulAssign(y);const t=((e,t)=>{const n=e.mul(2*Math.PI*1e-9),i=LA(54856e-17,44201e-17,52481e-17),r=LA(1681e3,1795300,2208400),s=LA(43278e5,93046e5,66121e5),o=EA(9747e-17*Math.sqrt(2*Math.PI*45282e5)).mul(n.mul(2239900).add(t.x).cos()).mul(n.pow2().mul(-45282e5).exp());let a=i.mul(s.mul(2*Math.PI).sqrt()).mul(r.mul(n).add(t).cos()).mul(n.pow2().negate().mul(s).exp());return a=LA(a.x.add(o),a.y,a.z).div(1.0685e-7),cS.mul(a)})(EA(e).mul(v),EA(e).mul(A)).mul(2);w.addAssign(C.mul(t))})),w.max(LA(0))})).setLayout({name:"evalIridescence",type:"vec3",inputs:[{name:"outsideIOR",type:"float"},{name:"eta2",type:"float"},{name:"cosTheta1",type:"float"},{name:"thinFilmThickness",type:"float"},{name:"baseF0",type:"vec3"}]}),fS=xA((({normal:e,viewDir:t,roughness:n})=>{const i=e.dot(t).saturate(),r=n.pow2(),s=bb(n.lessThan(.25),EA(-339.2).mul(r).add(EA(161.4).mul(n)).sub(25.9),EA(-8.48).mul(r).add(EA(14.3).mul(n)).sub(9.95)),o=bb(n.lessThan(.25),EA(44).mul(r).sub(EA(23.7).mul(n)).add(3.26),EA(1.97).mul(r).sub(EA(3.27).mul(n)).add(.72));return bb(n.lessThan(.25),0,EA(.1).mul(n).sub(.025)).add(s.mul(i).add(o).exp()).mul(1/Math.PI).saturate()})),pS=LA(.04),gS=EA(1);class mS extends gT{constructor(e=!1,t=!1,n=!1,i=!1,r=!1,s=!1){super(),this.clearcoat=e,this.sheen=t,this.iridescence=n,this.anisotropy=i,this.transmission=r,this.dispersion=s,this.clearcoatRadiance=null,this.clearcoatSpecularDirect=null,this.clearcoatSpecularIndirect=null,this.sheenSpecularDirect=null,this.sheenSpecularIndirect=null,this.iridescenceFresnel=null,this.iridescenceF0=null}start(e){if(!0===this.clearcoat&&(this.clearcoatRadiance=LA().toVar("clearcoatRadiance"),this.clearcoatSpecularDirect=LA().toVar("clearcoatSpecularDirect"),this.clearcoatSpecularIndirect=LA().toVar("clearcoatSpecularIndirect")),!0===this.sheen&&(this.sheenSpecularDirect=LA().toVar("sheenSpecularDirect"),this.sheenSpecularIndirect=LA().toVar("sheenSpecularIndirect")),!0===this.iridescence){const e=CC.dot(fC).clamp();this.iridescenceFresnel=hS({outsideIOR:EA(1),eta2:rx,cosTheta1:e,thinFilmThickness:sx,baseF0:cx}),this.iridescenceF0=kT({f:this.iridescenceFresnel,f90:1,dotVH:e})}if(!0===this.transmission){const t=cC,n=Kw.sub(cC).normalize(),i=MC,r=e.context;r.backdrop=uS(i,n,qA,JA,cx,dx,t,tC,Jw,Yw,mx,Ax,yx,xx,this.dispersion?bx:null),r.backdropAlpha=vx,JA.a.mulAssign(ub(1,r.backdrop.a,vx))}super.start(e)}computeMultiscattering(e,t,n){const i=CC.dot(fC).clamp(),r=zT({roughness:qA,dotNV:i}),s=(this.iridescenceF0?ix.mix(cx,this.iridescenceF0):cx).mul(r.x).add(n.mul(r.y)),o=r.x.add(r.y).oneMinus(),a=cx.add(cx.oneMinus().mul(.047619)),l=s.mul(a).div(o.mul(a).oneMinus());e.addAssign(s),t.addAssign(l.mul(o))}direct({lightDirection:e,lightColor:t,reflectedLight:n}){const i=CC.dot(e).clamp().mul(t);if(!0===this.sheen&&this.sheenSpecularDirect.addAssign(i.mul(UT({lightDirection:e}))),!0===this.clearcoat){const n=EC.dot(e).clamp().mul(t);this.clearcoatSpecularDirect.addAssign(n.mul(OT({lightDirection:e,f0:pS,f90:gS,roughness:ex,normalView:EC})))}n.directDiffuse.addAssign(i.mul(yT({diffuseColor:JA.rgb}))),n.directSpecular.addAssign(i.mul(OT({lightDirection:e,f0:cx,f90:1,roughness:qA,iridescence:this.iridescence,f:this.iridescenceFresnel,USE_IRIDESCENCE:this.iridescence,USE_ANISOTROPY:this.anisotropy})))}directRectArea({lightColor:e,lightPosition:t,halfWidth:n,halfHeight:i,reflectedLight:r,ltc_1:s,ltc_2:o}){const a=t.add(n).sub(i),l=t.sub(n).sub(i),u=t.sub(n).add(i),c=t.add(n).add(i),d=CC,h=fC,f=hC.toVar(),p=XT({N:d,V:h,roughness:qA}),g=s.sample(p).toVar(),m=o.sample(p).toVar(),v=XA(LA(g.x,0,g.y),LA(0,1,0),LA(g.z,0,g.w)).toVar(),A=cx.mul(m.x).add(cx.oneMinus().mul(m.y)).toVar();r.directSpecular.addAssign(e.mul(A).mul(WT({N:d,V:h,P:f,mInv:v,p0:a,p1:l,p2:u,p3:c}))),r.directDiffuse.addAssign(e.mul(JA).mul(WT({N:d,V:h,P:f,mInv:XA(1,0,0,0,1,0,0,0,1),p0:a,p1:l,p2:u,p3:c})))}indirect(e){this.indirectDiffuse(e),this.indirectSpecular(e),this.ambientOcclusion(e)}indirectDiffuse(e){const{irradiance:t,reflectedLight:n}=e.context;n.indirectDiffuse.addAssign(t.mul(yT({diffuseColor:JA})))}indirectSpecular(e){const{radiance:t,iblIrradiance:n,reflectedLight:i}=e.context;if(!0===this.sheen&&this.sheenSpecularIndirect.addAssign(n.mul(tx,fS({normal:CC,viewDir:fC,roughness:nx}))),!0===this.clearcoat){const e=EC.dot(fC).clamp(),t=RT({dotNV:e,specularColor:pS,specularF90:gS,roughness:ex});this.clearcoatSpecularIndirect.addAssign(this.clearcoatRadiance.mul(t))}const r=LA().toVar("singleScattering"),s=LA().toVar("multiScattering"),o=n.mul(1/Math.PI);this.computeMultiscattering(r,s,dx);const a=r.add(s),l=JA.mul(a.r.max(a.g).max(a.b).oneMinus());i.indirectSpecular.addAssign(t.mul(r)),i.indirectSpecular.addAssign(s.mul(o)),i.indirectDiffuse.addAssign(l.mul(o))}ambientOcclusion(e){const{ambientOcclusion:t,reflectedLight:n}=e.context,i=CC.dot(fC).clamp().add(t),r=qA.mul(-16).oneMinus().negate().exp2(),s=t.sub(i.pow(r).oneMinus()).clamp();!0===this.clearcoat&&this.clearcoatSpecularIndirect.mulAssign(t),!0===this.sheen&&this.sheenSpecularIndirect.mulAssign(t),n.indirectDiffuse.mulAssign(t),n.indirectSpecular.mulAssign(s)}finish({context:e}){const{outgoingLight:t}=e;if(!0===this.clearcoat){const e=EC.dot(fC).clamp(),n=xT({dotVH:e,f0:pS,f90:gS}),i=t.mul($A.mul(n).oneMinus()).add(this.clearcoatSpecularDirect.add(this.clearcoatSpecularIndirect).mul($A));t.assign(i)}if(!0===this.sheen){const e=tx.r.max(tx.g).max(tx.b).mul(.157).oneMinus(),n=t.mul(e).add(this.sheenSpecularDirect,this.sheenSpecularIndirect);t.assign(n)}}}const vS=EA(1),AS=EA(-2),xS=EA(.8),yS=EA(-1),bS=EA(.4),wS=EA(2),CS=EA(.305),MS=EA(3),ES=EA(.21),TS=EA(4),SS=EA(4),PS=EA(16),NS=xA((([e])=>{const t=LA(Ly(e)).toVar(),n=EA(-1).toVar();return wA(t.x.greaterThan(t.z),(()=>{wA(t.x.greaterThan(t.y),(()=>{n.assign(bb(e.x.greaterThan(0),0,3))})).Else((()=>{n.assign(bb(e.y.greaterThan(0),1,4))}))})).Else((()=>{wA(t.z.greaterThan(t.y),(()=>{n.assign(bb(e.z.greaterThan(0),2,5))})).Else((()=>{n.assign(bb(e.y.greaterThan(0),1,4))}))})),n})).setLayout({name:"getFace",type:"float",inputs:[{name:"direction",type:"vec3"}]}),BS=xA((([e,t])=>{const n=NA().toVar();return wA(t.equal(0),(()=>{n.assign(NA(e.z,e.y).div(Ly(e.x)))})).ElseIf(t.equal(1),(()=>{n.assign(NA(e.x.negate(),e.z.negate()).div(Ly(e.y)))})).ElseIf(t.equal(2),(()=>{n.assign(NA(e.x.negate(),e.y).div(Ly(e.z)))})).ElseIf(t.equal(3),(()=>{n.assign(NA(e.z.negate(),e.y).div(Ly(e.x)))})).ElseIf(t.equal(4),(()=>{n.assign(NA(e.x.negate(),e.z).div(Ly(e.y)))})).Else((()=>{n.assign(NA(e.x,e.y).div(Ly(e.z)))})),Hx(.5,n.add(1))})).setLayout({name:"getUV",type:"vec2",inputs:[{name:"direction",type:"vec3"},{name:"face",type:"float"}]}),DS=xA((([e])=>{const t=EA(0).toVar();return wA(e.greaterThanEqual(xS),(()=>{t.assign(vS.sub(e).mul(yS.sub(AS)).div(vS.sub(xS)).add(AS))})).ElseIf(e.greaterThanEqual(bS),(()=>{t.assign(xS.sub(e).mul(wS.sub(yS)).div(xS.sub(bS)).add(yS))})).ElseIf(e.greaterThanEqual(CS),(()=>{t.assign(bS.sub(e).mul(MS.sub(wS)).div(bS.sub(CS)).add(wS))})).ElseIf(e.greaterThanEqual(ES),(()=>{t.assign(CS.sub(e).mul(TS.sub(MS)).div(CS.sub(ES)).add(MS))})).Else((()=>{t.assign(EA(-2).mul(yy(Hx(1.16,e))))})),t})).setLayout({name:"roughnessToMip",type:"float",inputs:[{name:"roughness",type:"float"}]}),IS=xA((([e,t])=>{const n=e.toVar();n.assign(Hx(2,n).sub(1));const i=LA(n,1).toVar();return wA(t.equal(0),(()=>{i.assign(i.zyx)})).ElseIf(t.equal(1),(()=>{i.assign(i.xzy),i.xz.mulAssign(-1)})).ElseIf(t.equal(2),(()=>{i.x.mulAssign(-1)})).ElseIf(t.equal(3),(()=>{i.assign(i.zyx),i.xz.mulAssign(-1)})).ElseIf(t.equal(4),(()=>{i.assign(i.xzy),i.xy.mulAssign(-1)})).ElseIf(t.equal(5),(()=>{i.z.mulAssign(-1)})),i})).setLayout({name:"getDirection",type:"vec3",inputs:[{name:"uv",type:"vec2"},{name:"face",type:"float"}]}),LS=xA((([e,t,n,i,r,s])=>{const o=EA(n),a=LA(t),l=cb(DS(o),AS,s),u=Ty(l),c=Cy(l),d=LA(jS(e,a,c,i,r,s)).toVar();return wA(u.notEqual(0),(()=>{const t=LA(jS(e,a,c.add(1),i,r,s)).toVar();d.assign(ub(d,t,u))})),d})),jS=xA((([e,t,n,i,r,s])=>{const o=EA(n).toVar(),a=LA(t),l=EA(NS(a)).toVar(),u=EA(Jy(SS.sub(o),0)).toVar();o.assign(Jy(o,SS));const c=EA(Ay(o)).toVar(),d=NA(BS(a,l).mul(c.sub(2)).add(1)).toVar();return wA(l.greaterThan(2),(()=>{d.y.addAssign(c),l.subAssign(3)})),d.x.addAssign(l.mul(c)),d.x.addAssign(u.mul(Hx(3,PS))),d.y.addAssign(Hx(4,Ay(s).sub(c))),d.x.mulAssign(i),d.y.mulAssign(r),e.sample(d).grad(NA(),NA())})),OS=xA((({envMap:e,mipInt:t,outputDirection:n,theta:i,axis:r,CUBEUV_TEXEL_WIDTH:s,CUBEUV_TEXEL_HEIGHT:o,CUBEUV_MAX_MIP:a})=>{const l=Py(i),u=n.mul(l).add(r.cross(n).mul(Sy(i))).add(r.mul(r.dot(n).mul(l.oneMinus())));return jS(e,u,t,s,o,a)})),zS=xA((({n:e,latitudinal:t,poleAxis:n,outputDirection:i,weights:r,samples:s,dTheta:o,mipInt:a,envMap:l,CUBEUV_TEXEL_WIDTH:u,CUBEUV_TEXEL_HEIGHT:c,CUBEUV_MAX_MIP:d})=>{const h=LA(bb(t,n,tb(n,i))).toVar();wA(h.equal(LA(0)),(()=>{h.assign(LA(i.z,0,i.x.negate()))})),h.assign(Ey(h));const f=LA().toVar();return f.addAssign(r.element(0).mul(OS({theta:0,axis:h,outputDirection:i,mipInt:a,envMap:l,CUBEUV_TEXEL_WIDTH:u,CUBEUV_TEXEL_HEIGHT:c,CUBEUV_MAX_MIP:d}))),xE({start:TA(1),end:e},(({i:e})=>{wA(e.greaterThanEqual(s),(()=>{yE()}));const t=EA(o.mul(EA(e))).toVar();f.addAssign(r.element(e).mul(OS({theta:t.mul(-1),axis:h,outputDirection:i,mipInt:a,envMap:l,CUBEUV_TEXEL_WIDTH:u,CUBEUV_TEXEL_HEIGHT:c,CUBEUV_MAX_MIP:d}))),f.addAssign(r.element(e).mul(OS({theta:t,axis:h,outputDirection:i,mipInt:a,envMap:l,CUBEUV_TEXEL_WIDTH:u,CUBEUV_TEXEL_HEIGHT:c,CUBEUV_MAX_MIP:d})))})),RA(f,1)})),RS=[.125,.215,.35,.446,.526,.582],kS=20,FS=new hc(-1,1,1,-1,0,1),HS=new pl(90,1),US=new ya;let XS=null,GS=0,VS=0;const WS=(1+Math.sqrt(5))/2,QS=1/WS,ZS=[new Es(-WS,QS,0),new Es(WS,QS,0),new Es(-QS,0,WS),new Es(QS,0,WS),new Es(0,WS,-QS),new Es(0,WS,QS),new Es(-1,1,-1),new Es(1,1,-1),new Es(-1,1,1),new Es(1,1,1)],YS=new Es,JS=new WeakMap,KS=[3,1,5,0,4,2],qS=IS(yw(),xw("faceIndex")).normalize(),_S=LA(qS.x,qS.y,qS.z);class $S{constructor(e){this._renderer=e,this._pingPongRenderTarget=null,this._lodMax=0,this._cubeSize=0,this._lodPlanes=[],this._sizeLods=[],this._sigmas=[],this._lodMeshes=[],this._blurMaterial=null,this._cubemapMaterial=null,this._equirectMaterial=null,this._backgroundBox=null}get _hasInitialized(){return this._renderer.hasInitialized()}fromScene(e,t=0,n=.1,i=100,r={}){const{size:s=256,position:o=YS,renderTarget:a=null}=r;if(this._setSize(s),!1===this._hasInitialized){console.warn("THREE.PMREMGenerator: .fromScene() called before the backend is initialized. Try using .fromSceneAsync() instead.");const s=a||this._allocateTarget();return r.renderTarget=s,this.fromSceneAsync(e,t,n,i,r),s}XS=this._renderer.getRenderTarget(),GS=this._renderer.getActiveCubeFace(),VS=this._renderer.getActiveMipmapLevel();const l=a||this._allocateTarget();return l.depthBuffer=!0,this._init(l),this._sceneToCubeUV(e,n,i,l,o),t>0&&this._blur(l,0,0,t),this._applyPMREM(l),this._cleanup(l),l}async fromSceneAsync(e,t=0,n=.1,i=100,r={}){return!1===this._hasInitialized&&await this._renderer.init(),this.fromScene(e,t,n,i,r)}fromEquirectangular(e,t=null){if(!1===this._hasInitialized){console.warn("THREE.PMREMGenerator: .fromEquirectangular() called before the backend is initialized. Try using .fromEquirectangularAsync() instead."),this._setSizeFromTexture(e);const n=t||this._allocateTarget();return this.fromEquirectangularAsync(e,n),n}return this._fromTexture(e,t)}async fromEquirectangularAsync(e,t=null){return!1===this._hasInitialized&&await this._renderer.init(),this._fromTexture(e,t)}fromCubemap(e,t=null){if(!1===this._hasInitialized){console.warn("THREE.PMREMGenerator: .fromCubemap() called before the backend is initialized. Try using .fromCubemapAsync() instead."),this._setSizeFromTexture(e);const n=t||this._allocateTarget();return this.fromCubemapAsync(e,t),n}return this._fromTexture(e,t)}async fromCubemapAsync(e,t=null){return!1===this._hasInitialized&&await this._renderer.init(),this._fromTexture(e,t)}async compileCubemapShader(){null===this._cubemapMaterial&&(this._cubemapMaterial=iP(),await this._compileMaterial(this._cubemapMaterial))}async compileEquirectangularShader(){null===this._equirectMaterial&&(this._equirectMaterial=rP(),await this._compileMaterial(this._equirectMaterial))}dispose(){this._dispose(),null!==this._cubemapMaterial&&this._cubemapMaterial.dispose(),null!==this._equirectMaterial&&this._equirectMaterial.dispose(),null!==this._backgroundBox&&(this._backgroundBox.geometry.dispose(),this._backgroundBox.material.dispose())}_setSizeFromTexture(e){e.mapping===Ni||e.mapping===Bi?this._setSize(0===e.image.length?16:e.image[0].width||e.image[0].image.width):this._setSize(e.image.width/4)}_setSize(e){this._lodMax=Math.floor(Math.log2(e)),this._cubeSize=Math.pow(2,this._lodMax)}_dispose(){null!==this._blurMaterial&&this._blurMaterial.dispose(),null!==this._pingPongRenderTarget&&this._pingPongRenderTarget.dispose();for(let e=0;e<this._lodPlanes.length;e++)this._lodPlanes[e].dispose()}_cleanup(e){this._renderer.setRenderTarget(XS,GS,VS),e.scissorTest=!1,tP(e,0,0,e.width,e.height)}_fromTexture(e,t){this._setSizeFromTexture(e),XS=this._renderer.getRenderTarget(),GS=this._renderer.getActiveCubeFace(),VS=this._renderer.getActiveMipmapLevel();const n=t||this._allocateTarget();return this._init(n),this._textureToCubeUV(e,n),this._applyPMREM(n),this._cleanup(n),n}_allocateTarget(){return eP(3*Math.max(this._cubeSize,112),4*this._cubeSize)}_init(e){if(null===this._pingPongRenderTarget||this._pingPongRenderTarget.width!==e.width||this._pingPongRenderTarget.height!==e.height){null!==this._pingPongRenderTarget&&this._dispose(),this._pingPongRenderTarget=eP(e.width,e.height);const{_lodMax:t}=this;({sizeLods:this._sizeLods,lodPlanes:this._lodPlanes,sigmas:this._sigmas,lodMeshes:this._lodMeshes}=function(e){const t=[],n=[],i=[],r=[];let s=e;const o=e-4+1+RS.length;for(let a=0;a<o;a++){const o=Math.pow(2,s);n.push(o);let l=1/o;a>e-4?l=RS[a-e+4-1]:0===a&&(l=0),i.push(l);const u=1/(o-2),c=-u,d=1+u,h=[c,c,d,c,d,d,c,c,d,d,c,d],f=6,p=6,g=3,m=2,v=1,A=new Float32Array(g*p*f),x=new Float32Array(m*p*f),y=new Float32Array(v*p*f);for(let e=0;e<f;e++){const t=e%3*2/3-1,n=e>2?0:-1,i=[t,n,0,t+2/3,n,0,t+2/3,n+1,0,t,n,0,t+2/3,n+1,0,t,n+1,0],r=KS[e];A.set(i,g*p*r),x.set(h,m*p*r);const s=[r,r,r,r,r,r];y.set(s,v*p*r)}const b=new Va;b.setAttribute("position",new Ia(A,g)),b.setAttribute("uv",new Ia(x,m)),b.setAttribute("faceIndex",new Ia(y,v)),t.push(b),r.push(new nl(b,null)),s>4&&s--}return{lodPlanes:t,sizeLods:n,sigmas:i,lodMeshes:r}}(t)),this._blurMaterial=function(e,t,n){const i=jw(new Array(kS).fill(0)),r=Nx(new Es(0,1,0)),s=Nx(0),o=EA(kS),a=Nx(0),l=Nx(1),u=Pw(null),c=Nx(0),d=EA(1/t),h=EA(1/n),f=EA(e),p={n:o,latitudinal:a,weights:i,poleAxis:r,outputDirection:_S,dTheta:s,samples:l,envMap:u,mipInt:c,CUBEUV_TEXEL_WIDTH:d,CUBEUV_TEXEL_HEIGHT:h,CUBEUV_MAX_MIP:f},g=nP("blur");return g.fragmentNode=zS({...p,latitudinal:a.equal(1)}),JS.set(g,p),g}(t,e.width,e.height)}}async _compileMaterial(e){const t=new nl(this._lodPlanes[0],e);await this._renderer.compile(t,FS)}_sceneToCubeUV(e,t,n,i,r){const s=HS;s.near=t,s.far=n;const o=[1,1,1,1,-1,1],a=[1,-1,1,-1,1,-1],l=this._renderer,u=l.autoClear;l.getClearColor(US),l.autoClear=!1;let c=this._backgroundBox;if(null===c){const e=new Ma({name:"PMREM.Background",side:1,depthWrite:!1,depthTest:!1});c=new nl(new rl,e)}let d=!1;const h=e.background;h?h.isColor&&(c.material.color.copy(h),e.background=null,d=!0):(c.material.color.copy(US),d=!0),l.setRenderTarget(i),l.clear(),d&&l.render(c,s);for(let t=0;t<6;t++){const n=t%3;0===n?(s.up.set(0,o[t],0),s.position.set(r.x,r.y,r.z),s.lookAt(r.x+a[t],r.y,r.z)):1===n?(s.up.set(0,0,o[t]),s.position.set(r.x,r.y,r.z),s.lookAt(r.x,r.y+a[t],r.z)):(s.up.set(0,o[t],0),s.position.set(r.x,r.y,r.z),s.lookAt(r.x,r.y,r.z+a[t]));const u=this._cubeSize;tP(i,n*u,t>2?u:0,u,u),l.render(e,s)}l.autoClear=u,e.background=h}_textureToCubeUV(e,t){const n=this._renderer,i=e.mapping===Ni||e.mapping===Bi;i?null===this._cubemapMaterial&&(this._cubemapMaterial=iP(e)):null===this._equirectMaterial&&(this._equirectMaterial=rP(e));const r=i?this._cubemapMaterial:this._equirectMaterial;r.fragmentNode.value=e;const s=this._lodMeshes[0];s.material=r;const o=this._cubeSize;tP(t,0,0,3*o,2*o),n.setRenderTarget(t),n.render(s,FS)}_applyPMREM(e){const t=this._renderer,n=t.autoClear;t.autoClear=!1;const i=this._lodPlanes.length;for(let t=1;t<i;t++){const n=Math.sqrt(this._sigmas[t]*this._sigmas[t]-this._sigmas[t-1]*this._sigmas[t-1]),r=ZS[(i-t-1)%ZS.length];this._blur(e,t-1,t,n,r)}t.autoClear=n}_blur(e,t,n,i,r){const s=this._pingPongRenderTarget;this._halfBlur(e,s,t,n,i,"latitudinal",r),this._halfBlur(s,e,n,n,i,"longitudinal",r)}_halfBlur(e,t,n,i,r,s,o){const a=this._renderer,l=this._blurMaterial;"latitudinal"!==s&&"longitudinal"!==s&&console.error("blur direction must be either latitudinal or longitudinal!");const u=this._lodMeshes[i];u.material=l;const c=JS.get(l),d=this._sizeLods[n]-1,h=isFinite(r)?Math.PI/(2*d):2*Math.PI/39,f=r/h,p=isFinite(r)?1+Math.floor(3*f):kS;p>kS&&console.warn(`sigmaRadians, ${r}, is too large and will clip, as it requested ${p} samples when the maximum is set to 20`);const g=[];let m=0;for(let e=0;e<kS;++e){const t=e/f,n=Math.exp(-t*t/2);g.push(n),0===e?m+=n:e<p&&(m+=2*n)}for(let e=0;e<g.length;e++)g[e]=g[e]/m;e.texture.frame=(e.texture.frame||0)+1,c.envMap.value=e.texture,c.samples.value=p,c.weights.array=g,c.latitudinal.value="latitudinal"===s?1:0,o&&(c.poleAxis.value=o);const{_lodMax:v}=this;c.dTheta.value=h,c.mipInt.value=v-n;const A=this._sizeLods[i];tP(t,3*A*(i>v-4?i-v+4:0),4*(this._cubeSize-A),3*A,2*A),a.setRenderTarget(t),a.render(u,FS)}}function eP(e,t){const n=new Ks(e,t,{magFilter:Hi,minFilter:Hi,generateMipmaps:!1,type:Ki,format:rr,colorSpace:_r});return n.texture.mapping=Li,n.texture.name="PMREM.cubeUv",n.texture.isPMREMTexture=!0,n.scissorTest=!0,n}function tP(e,t,n,i,r){e.viewport.set(t,n,i,r),e.scissor.set(t,n,i,r)}function nP(e){const t=new _E;return t.depthTest=!1,t.depthWrite=!1,t.blending=0,t.name=`PMREM_${e}`,t}function iP(e){const t=nP("cubemap");return t.fragmentNode=HC(e,_S),t}function rP(e){const t=nP("equirect");return t.fragmentNode=Pw(e,oT(_S),0),t}const sP=new WeakMap;function oP(e,t,n){const i=function(e){let t=sP.get(e);void 0===t&&(t=new WeakMap,sP.set(e,t));return t}(t);let r=i.get(e);if((void 0!==r?r.pmremVersion:-1)!==e.pmremVersion){const t=e.image;if(e.isCubeTexture){if(!function(e){if(null==e)return!1;let t=0;const n=6;for(let i=0;i<n;i++)void 0!==e[i]&&t++;return t===n}(t))return null;r=n.fromCubemap(e,r)}else{if(!function(e){return null!=e&&e.height>0}(t))return null;r=n.fromEquirectangular(e,r)}r.pmremVersion=e.pmremVersion,i.set(e,r)}return r.texture}class aP extends Cv{static get type(){return"PMREMNode"}constructor(e,t=null,n=null){super("vec3"),this._value=e,this._pmrem=null,this.uvNode=t,this.levelNode=n,this._generator=null;const i=new Ys;i.isRenderTargetTexture=!0,this._texture=Pw(i),this._width=Nx(0),this._height=Nx(0),this._maxMip=Nx(0),this.updateBeforeType=hv.RENDER}set value(e){this._value=e,this._pmrem=null}get value(){return this._value}updateFromTexture(e){const t=function(e){const t=Math.log2(e)-2,n=1/e;return{texelWidth:1/(3*Math.max(Math.pow(2,t),112)),texelHeight:n,maxMip:t}}(e.image.height);this._texture.value=e,this._width.value=t.texelWidth,this._height.value=t.texelHeight,this._maxMip.value=t.maxMip}updateBefore(e){let t=this._pmrem;const n=t?t.pmremVersion:-1,i=this._value;n!==i.pmremVersion&&(t=!0===i.isPMREMTexture?i:oP(i,e.renderer,this._generator),null!==t&&(this._pmrem=t,this.updateFromTexture(t)))}setup(e){null===this._generator&&(this._generator=new $S(e.renderer)),this.updateBefore(e);let t=this.uvNode;null===t&&e.context.getUV&&(t=e.context.getUV(this)),t=IC.mul(LA(t.x,t.y.negate(),t.z));let n=this.levelNode;return null===n&&e.context.getTextureLevel&&(n=e.context.getTextureLevel(this)),LS(this._texture,t,n,this._width,this._height,this._maxMip)}dispose(){super.dispose(),null!==this._generator&&this._generator.dispose()}}const lP=pA(aP).setParameterLength(1,3),uP=new WeakMap;class cP extends TE{static get type(){return"EnvironmentNode"}constructor(e=null){super(),this.envNode=e}setup(e){const{material:t}=e;let n=this.envNode;if(n.isTextureNode||n.isMaterialReferenceNode){const e=n.isTextureNode?n.value:t[n.property];let i=uP.get(e);void 0===i&&(i=lP(e),uP.set(e,i)),n=i}const i=!0===t.useAnisotropy||t.anisotropy>0?fM:CC,r=n.context(dP(qA,i)).mul(DC),s=n.context(hP(MC)).mul(Math.PI).mul(DC),o=sw(r),a=sw(s);e.context.radiance.addAssign(o),e.context.iblIrradiance.addAssign(a);const l=e.context.lightingModel.clearcoatRadiance;if(l){const e=n.context(dP(ex,EC)).mul(DC),t=sw(e);l.addAssign(t)}}}const dP=(e,t)=>{let n=null;return{getUV:()=>(null===n&&(n=fC.negate().reflect(t),n=e.mul(e).mix(n,t).normalize(),n=n.transformDirection(Jw)),n),getTextureLevel:()=>e}},hP=e=>({getUV:()=>e,getTextureLevel:()=>EA(1)}),fP=new Cu;class pP extends _E{static get type(){return"MeshStandardNodeMaterial"}constructor(e){super(),this.isMeshStandardNodeMaterial=!0,this.lights=!0,this.emissiveNode=null,this.metalnessNode=null,this.roughnessNode=null,this.setDefaultValues(fP),this.setValues(e)}setupEnvironment(e){let t=super.setupEnvironment(e);return null===t&&e.environmentNode&&(t=e.environmentNode),t?new cP(t):null}setupLightingModel(){return new mS}setupSpecular(){const e=ub(LA(.04),JA.rgb,_A);cx.assign(e),dx.assign(1)}setupVariants(){const e=this.metalnessNode?EA(this.metalnessNode):LM;_A.assign(e);let t=this.roughnessNode?EA(this.roughnessNode):IM;t=NT({roughness:t}),qA.assign(t),this.setupSpecular(),JA.assign(RA(JA.rgb.mul(e.oneMinus()),JA.a))}copy(e){return this.emissiveNode=e.emissiveNode,this.metalnessNode=e.metalnessNode,this.roughnessNode=e.roughnessNode,super.copy(e)}}const gP=new Mu;class mP extends pP{static get type(){return"MeshPhysicalNodeMaterial"}constructor(e){super(),this.isMeshPhysicalNodeMaterial=!0,this.clearcoatNode=null,this.clearcoatRoughnessNode=null,this.clearcoatNormalNode=null,this.sheenNode=null,this.sheenRoughnessNode=null,this.iridescenceNode=null,this.iridescenceIORNode=null,this.iridescenceThicknessNode=null,this.specularIntensityNode=null,this.specularColorNode=null,this.iorNode=null,this.transmissionNode=null,this.thicknessNode=null,this.attenuationDistanceNode=null,this.attenuationColorNode=null,this.dispersionNode=null,this.anisotropyNode=null,this.setDefaultValues(gP),this.setValues(e)}get useClearcoat(){return this.clearcoat>0||null!==this.clearcoatNode}get useIridescence(){return this.iridescence>0||null!==this.iridescenceNode}get useSheen(){return this.sheen>0||null!==this.sheenNode}get useAnisotropy(){return this.anisotropy>0||null!==this.anisotropyNode}get useTransmission(){return this.transmission>0||null!==this.transmissionNode}get useDispersion(){return this.dispersion>0||null!==this.dispersionNode}setupSpecular(){const e=this.iorNode?EA(this.iorNode):ZM;mx.assign(e),cx.assign(ub(Yy(ib(mx.sub(1).div(mx.add(1))).mul(NM),LA(1)).mul(PM),JA.rgb,_A)),dx.assign(ub(PM,1,_A))}setupLightingModel(){return new mS(this.useClearcoat,this.useSheen,this.useIridescence,this.useAnisotropy,this.useTransmission,this.useDispersion)}setupVariants(e){if(super.setupVariants(e),this.useClearcoat){const e=this.clearcoatNode?EA(this.clearcoatNode):OM,t=this.clearcoatRoughnessNode?EA(this.clearcoatRoughnessNode):zM;$A.assign(e),ex.assign(NT({roughness:t}))}if(this.useSheen){const e=this.sheenNode?LA(this.sheenNode):FM,t=this.sheenRoughnessNode?EA(this.sheenRoughnessNode):HM;tx.assign(e),nx.assign(t)}if(this.useIridescence){const e=this.iridescenceNode?EA(this.iridescenceNode):XM,t=this.iridescenceIORNode?EA(this.iridescenceIORNode):GM,n=this.iridescenceThicknessNode?EA(this.iridescenceThicknessNode):VM;ix.assign(e),rx.assign(t),sx.assign(n)}if(this.useAnisotropy){const e=(this.anisotropyNode?NA(this.anisotropyNode):UM).toVar();ax.assign(e.length()),wA(ax.equal(0),(()=>{e.assign(NA(1,0))})).Else((()=>{e.divAssign(NA(ax)),ax.assign(ax.saturate())})),ox.assign(ax.pow2().mix(qA.pow2(),1)),lx.assign(hM[0].mul(e.x).add(hM[1].mul(e.y))),ux.assign(hM[1].mul(e.x).sub(hM[0].mul(e.y)))}if(this.useTransmission){const e=this.transmissionNode?EA(this.transmissionNode):WM,t=this.thicknessNode?EA(this.thicknessNode):QM,n=this.attenuationDistanceNode?EA(this.attenuationDistanceNode):YM,i=this.attenuationColorNode?LA(this.attenuationColorNode):JM;if(vx.assign(e),Ax.assign(t),xx.assign(n),yx.assign(i),this.useDispersion){const e=this.dispersionNode?EA(this.dispersionNode):tE;bx.assign(e)}}}setupClearcoatNormal(){return this.clearcoatNormalNode?LA(this.clearcoatNormalNode):RM}setup(e){e.context.setupClearcoatNormal=()=>Lb(this.setupClearcoatNormal(e),"NORMAL","vec3"),super.setup(e)}copy(e){return this.clearcoatNode=e.clearcoatNode,this.clearcoatRoughnessNode=e.clearcoatRoughnessNode,this.clearcoatNormalNode=e.clearcoatNormalNode,this.sheenNode=e.sheenNode,this.sheenRoughnessNode=e.sheenRoughnessNode,this.iridescenceNode=e.iridescenceNode,this.iridescenceIORNode=e.iridescenceIORNode,this.iridescenceThicknessNode=e.iridescenceThicknessNode,this.specularIntensityNode=e.specularIntensityNode,this.specularColorNode=e.specularColorNode,this.transmissionNode=e.transmissionNode,this.thicknessNode=e.thicknessNode,this.attenuationDistanceNode=e.attenuationDistanceNode,this.attenuationColorNode=e.attenuationColorNode,this.dispersionNode=e.dispersionNode,this.anisotropyNode=e.anisotropyNode,super.copy(e)}}const vP=xA((({normal:e,lightDirection:t,builder:n})=>{const i=e.dot(t),r=NA(i.mul(.5).add(.5),0);if(n.material.gradientMap){const e=QC("gradientMap","texture").context({getUV:()=>r});return LA(e.r)}{const e=r.fwidth().mul(.5);return ub(LA(.7),LA(1),fb(EA(.7).sub(e.x),EA(.7).add(e.x),r.x))}}));class AP extends gT{direct({lightDirection:e,lightColor:t,reflectedLight:n},i){const r=vP({normal:AC,lightDirection:e,builder:i}).mul(t);n.directDiffuse.addAssign(r.mul(yT({diffuseColor:JA.rgb})))}indirect(e){const{ambientOcclusion:t,irradiance:n,reflectedLight:i}=e.context;i.indirectDiffuse.addAssign(n.mul(yT({diffuseColor:JA}))),i.indirectDiffuse.mulAssign(t)}}const xP=new Tu;class yP extends _E{static get type(){return"MeshToonNodeMaterial"}constructor(e){super(),this.isMeshToonNodeMaterial=!0,this.lights=!0,this.setDefaultValues(xP),this.setValues(e)}setupLightingModel(){return new AP}}const bP=xA((()=>{const e=LA(fC.z,0,fC.x.negate()).normalize(),t=fC.cross(e);return NA(e.dot(CC),t.dot(CC)).mul(.495).add(.5)})).once(["NORMAL","VERTEX"])().toVar("matcapUV"),wP=new Du;class CP extends _E{static get type(){return"MeshMatcapNodeMaterial"}constructor(e){super(),this.isMeshMatcapNodeMaterial=!0,this.setDefaultValues(wP),this.setValues(e)}setupVariants(e){const t=bP;let n;n=e.material.matcap?QC("matcap","texture").context({getUV:()=>t}):LA(ub(.2,.8,t.y)),JA.rgb.mulAssign(n.rgb)}}class MP extends Cv{static get type(){return"RotateNode"}constructor(e,t){super(),this.positionNode=e,this.rotationNode=t}getNodeType(e){return this.positionNode.getNodeType(e)}setup(e){const{rotationNode:t,positionNode:n}=this;if("vec2"===this.getNodeType(e)){const e=t.cos(),i=t.sin();return UA(e,i,i.negate(),e).mul(n)}{const e=t,i=GA(RA(1,0,0,0),RA(0,Py(e.x),Sy(e.x).negate(),0),RA(0,Sy(e.x),Py(e.x),0),RA(0,0,0,1)),r=GA(RA(Py(e.y),0,Sy(e.y),0),RA(0,1,0,0),RA(Sy(e.y).negate(),0,Py(e.y),0),RA(0,0,0,1)),s=GA(RA(Py(e.z),Sy(e.z).negate(),0,0),RA(Sy(e.z),Py(e.z),0,0),RA(0,0,1,0),RA(0,0,0,1));return i.mul(r).mul(s).mul(RA(n,1)).xyz}}}const EP=pA(MP).setParameterLength(2),TP=new Tl;class SP extends _E{static get type(){return"SpriteNodeMaterial"}constructor(e){super(),this.isSpriteNodeMaterial=!0,this._useSizeAttenuation=!0,this.positionNode=null,this.rotationNode=null,this.scaleNode=null,this.transparent=!0,this.setDefaultValues(TP),this.setValues(e)}setupPositionView(e){const{object:t,camera:n}=e,{positionNode:i,rotationNode:r,scaleNode:s,sizeAttenuation:o}=this,a=iC.mul(LA(i||0));let l=NA(tC[0].xyz.length(),tC[1].xyz.length());null!==s&&(l=l.mul(NA(s))),n.isPerspectiveCamera&&!1===o&&(l=l.mul(a.z.negate()));let u=aC.xy;if(t.center&&!0===t.center.isVector2){const e=((e,t,n)=>cA(new Vb(e,t,n)))("center","vec2",t);u=u.sub(e.sub(.5))}u=u.mul(l);const c=EA(r||kM),d=EP(u,c);return RA(a.xy.add(d),a.zw)}copy(e){return this.positionNode=e.positionNode,this.rotationNode=e.rotationNode,this.scaleNode=e.scaleNode,super.copy(e)}get sizeAttenuation(){return this._useSizeAttenuation}set sizeAttenuation(e){this._useSizeAttenuation!==e&&(this._useSizeAttenuation=e,this.needsUpdate=!0)}}const PP=new Kl,NP=new Cs;class BP extends SP{static get type(){return"PointsNodeMaterial"}constructor(e){super(),this.sizeNode=null,this.isPointsNodeMaterial=!0,this.setDefaultValues(PP),this.setValues(e)}setupPositionView(){const{positionNode:e}=this;return iC.mul(LA(e||lC)).xyz}setupVertexSprite(e){const{material:t,camera:n}=e,{rotationNode:i,scaleNode:r,sizeNode:s,sizeAttenuation:o}=this;let a=super.setupVertex(e);if(!0!==t.isNodeMaterial)return a;let l=null!==s?NA(s):eE;l=l.mul(Fw),n.isPerspectiveCamera&&!0===o&&(l=l.mul(DP.div(hC.z.negate()))),r&&r.isNode&&(l=l.mul(NA(r)));let u=aC.xy;if(i&&i.isNode){const e=EA(i);u=EP(u,e)}return u=u.mul(l),u=u.div(Vw.div(2)),u=u.mul(a.w),a=a.add(RA(u,0,0)),a}setupVertex(e){return e.object.isPoints?super.setupVertex(e):this.setupVertexSprite(e)}get alphaToCoverage(){return this._useAlphaToCoverage}set alphaToCoverage(e){this._useAlphaToCoverage!==e&&(this._useAlphaToCoverage=e,this.needsUpdate=!0)}}const DP=Nx(1).onFrameUpdate((function({renderer:e}){const t=e.getSize(NP);this.value=.5*t.y}));class IP extends gT{constructor(){super(),this.shadowNode=EA(1).toVar("shadowMask")}direct({lightNode:e}){null!==e.shadowNode&&this.shadowNode.mulAssign(e.shadowNode)}finish({context:e}){JA.a.mulAssign(this.shadowNode.oneMinus()),e.outgoingLight.rgb.assign(JA.rgb)}}const LP=new wu;class jP extends _E{static get type(){return"ShadowNodeMaterial"}constructor(e){super(),this.isShadowNodeMaterial=!0,this.lights=!0,this.transparent=!0,this.setDefaultValues(LP),this.setValues(e)}setupLightingModel(){return new IP}}ZA("vec3"),ZA("vec3"),ZA("vec3");class OP{constructor(e,t){this.nodes=e,this.info=t,this._context="undefined"!=typeof self?self:null,this._animationLoop=null,this._requestId=null}start(){const e=(t,n)=>{this._requestId=this._context.requestAnimationFrame(e),!0===this.info.autoReset&&this.info.reset(),this.nodes.nodeFrame.update(),this.info.frame=this.nodes.nodeFrame.frameId,null!==this._animationLoop&&this._animationLoop(t,n)};e()}stop(){this._context.cancelAnimationFrame(this._requestId),this._requestId=null}getAnimationLoop(){return this._animationLoop}setAnimationLoop(e){this._animationLoop=e}getContext(){return this._context}setContext(e){this._context=e}dispose(){this.stop()}}class zP{constructor(){this.weakMap=new WeakMap}get(e){let t=this.weakMap;for(let n=0;n<e.length-1;n++)if(t=t.get(e[n]),void 0===t)return;return t.get(e[e.length-1])}set(e,t){let n=this.weakMap;for(let t=0;t<e.length-1;t++){const i=e[t];!1===n.has(i)&&n.set(i,new WeakMap),n=n.get(i)}return n.set(e[e.length-1],t),this}delete(e){let t=this.weakMap;for(let n=0;n<e.length-1;n++)if(t=t.get(e[n]),void 0===t)return!1;return t.delete(e[e.length-1])}}let RP=0;class kP{constructor(e,t,n,i,r,s,o,a,l,u){this.id=RP++,this._nodes=e,this._geometries=t,this.renderer=n,this.object=i,this.material=r,this.scene=s,this.camera=o,this.lightsNode=a,this.context=l,this.geometry=i.geometry,this.version=r.version,this.drawRange=null,this.attributes=null,this.attributesId=null,this.pipeline=null,this.group=null,this.vertexBuffers=null,this.drawParams=null,this.bundle=null,this.clippingContext=u,this.clippingContextCacheKey=null!==u?u.cacheKey:"",this.initialNodesCacheKey=this.getDynamicCacheKey(),this.initialCacheKey=this.getCacheKey(),this._nodeBuilderState=null,this._bindings=null,this._monitor=null,this.onDispose=null,this.isRenderObject=!0,this.onMaterialDispose=()=>{this.dispose()},this.onGeometryDispose=()=>{this.attributes=null,this.attributesId=null},this.material.addEventListener("dispose",this.onMaterialDispose),this.geometry.addEventListener("dispose",this.onGeometryDispose)}updateClipping(e){this.clippingContext=e}get clippingNeedsUpdate(){return null!==this.clippingContext&&this.clippingContext.cacheKey!==this.clippingContextCacheKey&&(this.clippingContextCacheKey=this.clippingContext.cacheKey,!0)}get hardwareClippingPlanes(){return!0===this.material.hardwareClipping?this.clippingContext.unionClippingCount:0}getNodeBuilderState(){return this._nodeBuilderState||(this._nodeBuilderState=this._nodes.getForRender(this))}getMonitor(){return this._monitor||(this._monitor=this.getNodeBuilderState().observer)}getBindings(){return this._bindings||(this._bindings=this.getNodeBuilderState().createBindings())}getBindingGroup(e){for(const t of this.getBindings())if(t.name===e)return t}getIndex(){return this._geometries.getIndex(this)}getIndirect(){return this._geometries.getIndirect(this)}getChainArray(){return[this.object,this.material,this.context,this.lightsNode]}setGeometry(e){this.geometry=e,this.attributes=null,this.attributesId=null}getAttributes(){if(null!==this.attributes)return this.attributes;const e=this.getNodeBuilderState().nodeAttributes,t=this.geometry,n=[],i=new Set,r={};for(const s of e){let e;if(s.node&&s.node.attribute?e=s.node.attribute:(e=t.getAttribute(s.name),r[s.name]=e.version),void 0===e)continue;n.push(e);const o=e.isInterleavedBufferAttribute?e.data:e;i.add(o)}return this.attributes=n,this.attributesId=r,this.vertexBuffers=Array.from(i.values()),n}getVertexBuffers(){return null===this.vertexBuffers&&this.getAttributes(),this.vertexBuffers}getDrawParameters(){const{object:e,material:t,geometry:n,group:i,drawRange:r}=this,s=this.drawParams||(this.drawParams={vertexCount:0,firstVertex:0,instanceCount:0,firstInstance:0}),o=this.getIndex(),a=null!==o;let l=1;if(!0===n.isInstancedBufferGeometry?l=n.instanceCount:void 0!==e.count&&(l=Math.max(0,e.count)),0===l)return null;if(s.instanceCount=l,!0===e.isBatchedMesh)return s;let u=1;!0!==t.wireframe||e.isPoints||e.isLineSegments||e.isLine||e.isLineLoop||(u=2);let c=r.start*u,d=(r.start+r.count)*u;null!==i&&(c=Math.max(c,i.start*u),d=Math.min(d,(i.start+i.count)*u));const h=n.attributes.position;let f=1/0;a?f=o.count:null!=h&&(f=h.count),c=Math.max(c,0),d=Math.min(d,f);const p=d-c;return p<0||p===1/0?null:(s.vertexCount=p,s.firstVertex=c,s)}getGeometryCacheKey(){const{geometry:e}=this;let t="";for(const n of Object.keys(e.attributes).sort()){const i=e.attributes[n];t+=n+",",i.data&&(t+=i.data.stride+","),i.offset&&(t+=i.offset+","),i.itemSize&&(t+=i.itemSize+","),i.normalized&&(t+="n,")}for(const n of Object.keys(e.morphAttributes).sort()){const i=e.morphAttributes[n];t+="morph-"+n+",";for(let e=0,n=i.length;e<n;e++){t+=i[e].id+","}}return e.index&&(t+="index,"),t}getMaterialCacheKey(){const{object:e,material:t,renderer:n}=this;let i=t.customProgramCacheKey();for(const e of function(e){const t=Object.keys(e);let n=Object.getPrototypeOf(e);for(;n;){const e=Object.getOwnPropertyDescriptors(n);for(const n in e)if(void 0!==e[n]){const i=e[n];i&&"function"==typeof i.get&&t.push(n)}n=Object.getPrototypeOf(n)}return t}(t)){if(/^(is[A-Z]|_)|^(visible|version|uuid|name|opacity|userData)$/.test(e))continue;const r=t[e];let s;if(null!==r){const e=typeof r;"number"===e?s=0!==r?"1":"0":"object"===e?(s="{",r.isTexture&&(s+=r.mapping,!0===n.backend.isWebGPUBackend&&(s+=r.magFilter,s+=r.minFilter,s+=r.wrapS,s+=r.wrapT,s+=r.wrapR)),s+="}"):s=String(r)}else s=String(r);i+=s+","}return i+=this.clippingContextCacheKey+",",e.geometry&&(i+=this.getGeometryCacheKey()),e.skeleton&&(i+=e.skeleton.bones.length+","),e.isBatchedMesh&&(i+=e._matricesTexture.uuid+",",null!==e._colorsTexture&&(i+=e._colorsTexture.uuid+",")),(e.isInstancedMesh||e.count>1)&&(i+=e.uuid+","),i+=e.receiveShadow+",",_m(i)}get needsGeometryUpdate(){if(this.geometry.id!==this.object.geometry.id)return!0;if(null!==this.attributes){const e=this.attributesId;for(const t in e){const n=this.geometry.getAttribute(t);if(void 0===n||e[t]!==n.id)return!0}}return!1}get needsUpdate(){return this.initialNodesCacheKey!==this.getDynamicCacheKey()||this.clippingNeedsUpdate}getDynamicCacheKey(){let e=0;return!0!==this.material.isShadowPassMaterial&&(e=this._nodes.getCacheKey(this.scene,this.lightsNode)),this.camera.isArrayCamera&&(e=ev(e,this.camera.cameras.length)),this.object.receiveShadow&&(e=ev(e,1)),e}getCacheKey(){return this.getMaterialCacheKey()+this.getDynamicCacheKey()}dispose(){this.material.removeEventListener("dispose",this.onMaterialDispose),this.geometry.removeEventListener("dispose",this.onGeometryDispose),this.onDispose()}}const FP=[];class HP{constructor(e,t,n,i,r,s){this.renderer=e,this.nodes=t,this.geometries=n,this.pipelines=i,this.bindings=r,this.info=s,this.chainMaps={}}get(e,t,n,i,r,s,o,a){const l=this.getChainMap(a);FP[0]=e,FP[1]=t,FP[2]=s,FP[3]=r;let u=l.get(FP);return void 0===u?(u=this.createRenderObject(this.nodes,this.geometries,this.renderer,e,t,n,i,r,s,o,a),l.set(FP,u)):(u.updateClipping(o),u.needsGeometryUpdate&&u.setGeometry(e.geometry),(u.version!==t.version||u.needsUpdate)&&(u.initialCacheKey!==u.getCacheKey()?(u.dispose(),u=this.get(e,t,n,i,r,s,o,a)):u.version=t.version)),FP.length=0,u}getChainMap(e="default"){return this.chainMaps[e]||(this.chainMaps[e]=new zP)}dispose(){this.chainMaps={}}createRenderObject(e,t,n,i,r,s,o,a,l,u,c){const d=this.getChainMap(c),h=new kP(e,t,n,i,r,s,o,a,l,u);return h.onDispose=()=>{this.pipelines.delete(h),this.bindings.delete(h),this.nodes.delete(h),d.delete(h.getChainArray())},h}}class UP{constructor(){this.data=new WeakMap}get(e){let t=this.data.get(e);return void 0===t&&(t={},this.data.set(e,t)),t}delete(e){let t=null;return this.data.has(e)&&(t=this.data.get(e),this.data.delete(e)),t}has(e){return this.data.has(e)}dispose(){this.data=new WeakMap}}const XP=1,GP=2,VP=3,WP=4,QP=16;class ZP extends UP{constructor(e){super(),this.backend=e}delete(e){const t=super.delete(e);return null!==t&&this.backend.destroyAttribute(e),t}update(e,t){const n=this.get(e);if(void 0===n.version)t===XP?this.backend.createAttribute(e):t===GP?this.backend.createIndexAttribute(e):t===VP?this.backend.createStorageAttribute(e):t===WP&&this.backend.createIndirectStorageAttribute(e),n.version=this._getBufferAttribute(e).version;else{const t=this._getBufferAttribute(e);(n.version<t.version||t.usage===ss)&&(this.backend.updateAttribute(e),n.version=t.version)}}_getBufferAttribute(e){return e.isInterleavedBufferAttribute&&(e=e.data),e}}function YP(e){return null!==e.index?e.index.version:e.attributes.position.version}function JP(e){const t=[],n=e.index,i=e.attributes.position;if(null!==n){const e=n.array;for(let n=0,i=e.length;n<i;n+=3){const i=e[n+0],r=e[n+1],s=e[n+2];t.push(i,r,r,s,s,i)}}else{for(let e=0,n=i.array.length/3-1;e<n;e+=3){const n=e+0,i=e+1,r=e+2;t.push(n,i,i,r,r,n)}}const r=new(Bs(t)?ja:La)(t,1);return r.version=YP(e),r}class KP extends UP{constructor(e,t){super(),this.attributes=e,this.info=t,this.wireframes=new WeakMap,this.attributeCall=new WeakMap}has(e){const t=e.geometry;return super.has(t)&&!0===this.get(t).initialized}updateForRender(e){!1===this.has(e)&&this.initGeometry(e),this.updateAttributes(e)}initGeometry(e){const t=e.geometry;this.get(t).initialized=!0,this.info.memory.geometries++;const n=()=>{this.info.memory.geometries--;const i=t.index,r=e.getAttributes();null!==i&&this.attributes.delete(i);for(const e of r)this.attributes.delete(e);const s=this.wireframes.get(t);void 0!==s&&this.attributes.delete(s),t.removeEventListener("dispose",n)};t.addEventListener("dispose",n)}updateAttributes(e){const t=e.getAttributes();for(const e of t)e.isStorageBufferAttribute||e.isStorageInstancedBufferAttribute?this.updateAttribute(e,VP):this.updateAttribute(e,XP);const n=this.getIndex(e);null!==n&&this.updateAttribute(n,GP);const i=e.geometry.indirect;null!==i&&this.updateAttribute(i,WP)}updateAttribute(e,t){const n=this.info.render.calls;e.isInterleavedBufferAttribute?void 0===this.attributeCall.get(e)?(this.attributes.update(e,t),this.attributeCall.set(e,n)):this.attributeCall.get(e.data)!==n&&(this.attributes.update(e,t),this.attributeCall.set(e.data,n),this.attributeCall.set(e,n)):this.attributeCall.get(e)!==n&&(this.attributes.update(e,t),this.attributeCall.set(e,n))}getIndirect(e){return e.geometry.indirect}getIndex(e){const{geometry:t,material:n}=e;let i=t.index;if(!0===n.wireframe){const e=this.wireframes;let n=e.get(t);void 0===n?(n=JP(t),e.set(t,n)):n.version!==YP(t)&&(this.attributes.delete(n),n=JP(t),e.set(t,n)),i=n}return i}}class qP{constructor(){this.autoReset=!0,this.frame=0,this.calls=0,this.render={calls:0,frameCalls:0,drawCalls:0,triangles:0,points:0,lines:0,timestamp:0},this.compute={calls:0,frameCalls:0,timestamp:0},this.memory={geometries:0,textures:0}}update(e,t,n){this.render.drawCalls++,e.isMesh||e.isSprite?this.render.triangles+=n*(t/3):e.isPoints?this.render.points+=n*t:e.isLineSegments?this.render.lines+=n*(t/2):e.isLine?this.render.lines+=n*(t-1):console.error("THREE.WebGPUInfo: Unknown object type.")}reset(){this.render.drawCalls=0,this.render.frameCalls=0,this.compute.frameCalls=0,this.render.triangles=0,this.render.points=0,this.render.lines=0}dispose(){this.reset(),this.calls=0,this.render.calls=0,this.compute.calls=0,this.render.timestamp=0,this.compute.timestamp=0,this.memory.geometries=0,this.memory.textures=0}}class _P{constructor(e){this.cacheKey=e,this.usedTimes=0}}class $P extends _P{constructor(e,t,n){super(e),this.vertexProgram=t,this.fragmentProgram=n}}class eN extends _P{constructor(e,t){super(e),this.computeProgram=t,this.isComputePipeline=!0}}let tN=0;class nN{constructor(e,t,n,i=null,r=null){this.id=tN++,this.code=e,this.stage=t,this.name=n,this.transforms=i,this.attributes=r,this.usedTimes=0}}class iN extends UP{constructor(e,t){super(),this.backend=e,this.nodes=t,this.bindings=null,this.caches=new Map,this.programs={vertex:new Map,fragment:new Map,compute:new Map}}getForCompute(e,t){const{backend:n}=this,i=this.get(e);if(this._needsComputeUpdate(e)){const r=i.pipeline;r&&(r.usedTimes--,r.computeProgram.usedTimes--);const s=this.nodes.getForCompute(e);let o=this.programs.compute.get(s.computeShader);void 0===o&&(r&&0===r.computeProgram.usedTimes&&this._releaseProgram(r.computeProgram),o=new nN(s.computeShader,"compute",e.name,s.transforms,s.nodeAttributes),this.programs.compute.set(s.computeShader,o),n.createProgram(o));const a=this._getComputeCacheKey(e,o);let l=this.caches.get(a);void 0===l&&(r&&0===r.usedTimes&&this._releasePipeline(r),l=this._getComputePipeline(e,o,a,t)),l.usedTimes++,o.usedTimes++,i.version=e.version,i.pipeline=l}return i.pipeline}getForRender(e,t=null){const{backend:n}=this,i=this.get(e);if(this._needsRenderUpdate(e)){const r=i.pipeline;r&&(r.usedTimes--,r.vertexProgram.usedTimes--,r.fragmentProgram.usedTimes--);const s=e.getNodeBuilderState(),o=e.material?e.material.name:"";let a=this.programs.vertex.get(s.vertexShader);void 0===a&&(r&&0===r.vertexProgram.usedTimes&&this._releaseProgram(r.vertexProgram),a=new nN(s.vertexShader,"vertex",o),this.programs.vertex.set(s.vertexShader,a),n.createProgram(a));let l=this.programs.fragment.get(s.fragmentShader);void 0===l&&(r&&0===r.fragmentProgram.usedTimes&&this._releaseProgram(r.fragmentProgram),l=new nN(s.fragmentShader,"fragment",o),this.programs.fragment.set(s.fragmentShader,l),n.createProgram(l));const u=this._getRenderCacheKey(e,a,l);let c=this.caches.get(u);void 0===c?(r&&0===r.usedTimes&&this._releasePipeline(r),c=this._getRenderPipeline(e,a,l,u,t)):e.pipeline=c,c.usedTimes++,a.usedTimes++,l.usedTimes++,i.pipeline=c}return i.pipeline}delete(e){const t=this.get(e).pipeline;return t&&(t.usedTimes--,0===t.usedTimes&&this._releasePipeline(t),t.isComputePipeline?(t.computeProgram.usedTimes--,0===t.computeProgram.usedTimes&&this._releaseProgram(t.computeProgram)):(t.fragmentProgram.usedTimes--,t.vertexProgram.usedTimes--,0===t.vertexProgram.usedTimes&&this._releaseProgram(t.vertexProgram),0===t.fragmentProgram.usedTimes&&this._releaseProgram(t.fragmentProgram))),super.delete(e)}dispose(){super.dispose(),this.caches=new Map,this.programs={vertex:new Map,fragment:new Map,compute:new Map}}updateForRender(e){this.getForRender(e)}_getComputePipeline(e,t,n,i){n=n||this._getComputeCacheKey(e,t);let r=this.caches.get(n);return void 0===r&&(r=new eN(n,t),this.caches.set(n,r),this.backend.createComputePipeline(r,i)),r}_getRenderPipeline(e,t,n,i,r){i=i||this._getRenderCacheKey(e,t,n);let s=this.caches.get(i);return void 0===s&&(s=new $P(i,t,n),this.caches.set(i,s),e.pipeline=s,this.backend.createRenderPipeline(e,r)),s}_getComputeCacheKey(e,t){return e.id+","+t.id}_getRenderCacheKey(e,t,n){return t.id+","+n.id+","+this.backend.getRenderCacheKey(e)}_releasePipeline(e){this.caches.delete(e.cacheKey)}_releaseProgram(e){const t=e.code,n=e.stage;this.programs[n].delete(t)}_needsComputeUpdate(e){const t=this.get(e);return void 0===t.pipeline||t.version!==e.version}_needsRenderUpdate(e){return void 0===this.get(e).pipeline||this.backend.needsRenderUpdate(e)}}class rN extends UP{constructor(e,t,n,i,r,s){super(),this.backend=e,this.textures=n,this.pipelines=r,this.attributes=i,this.nodes=t,this.info=s,this.pipelines.bindings=this}getForRender(e){const t=e.getBindings();for(const e of t){const n=this.get(e);void 0===n.bindGroup&&(this._init(e),this.backend.createBindings(e,t,0),n.bindGroup=e)}return t}getForCompute(e){const t=this.nodes.getForCompute(e).bindings;for(const e of t){const n=this.get(e);void 0===n.bindGroup&&(this._init(e),this.backend.createBindings(e,t,0),n.bindGroup=e)}return t}updateForCompute(e){this._updateBindings(this.getForCompute(e))}updateForRender(e){this._updateBindings(this.getForRender(e))}_updateBindings(e){for(const t of e)this._update(t,e)}_init(e){for(const t of e.bindings)if(t.isSampledTexture)this.textures.updateTexture(t.texture);else if(t.isStorageBuffer){const e=t.attribute,n=e.isIndirectStorageBufferAttribute?WP:VP;this.attributes.update(e,n)}}_update(e,t){const{backend:n}=this;let i=!1,r=!0,s=0,o=0;for(const t of e.bindings){if(t.isNodeUniformsGroup){if(!1===this.nodes.updateGroup(t))continue}if(t.isStorageBuffer){const e=t.attribute,n=e.isIndirectStorageBufferAttribute?WP:VP;this.attributes.update(e,n)}if(t.isUniformBuffer){t.update()&&n.updateBinding(t)}else if(t.isSampledTexture){const e=t.update(),a=t.texture,l=this.textures.get(a);e&&(this.textures.updateTexture(a),t.generation!==l.generation&&(t.generation=l.generation,i=!0,r=!1));if(void 0!==n.get(a).externalTexture||l.isDefaultTexture?r=!1:(s=10*s+a.id,o+=a.version),!0===a.isStorageTexture){const e=this.get(a);!0===t.store?e.needsMipmap=!0:this.textures.needsMipmaps(a)&&!0===e.needsMipmap&&(this.backend.generateMipmaps(a),e.needsMipmap=!1)}}else t.isSampler&&t.update()}!0===i&&this.backend.updateBindings(e,t,r?s:0,o)}}function sN(e,t){return e.groupOrder!==t.groupOrder?e.groupOrder-t.groupOrder:e.renderOrder!==t.renderOrder?e.renderOrder-t.renderOrder:e.z!==t.z?e.z-t.z:e.id-t.id}function oN(e,t){return e.groupOrder!==t.groupOrder?e.groupOrder-t.groupOrder:e.renderOrder!==t.renderOrder?e.renderOrder-t.renderOrder:e.z!==t.z?t.z-e.z:e.id-t.id}function aN(e){return(e.transmission>0||e.transmissionNode)&&2===e.side&&!1===e.forceSinglePass}class lN{constructor(e,t,n){this.renderItems=[],this.renderItemsIndex=0,this.opaque=[],this.transparentDoublePass=[],this.transparent=[],this.bundles=[],this.lightsNode=e.getNode(t,n),this.lightsArray=[],this.scene=t,this.camera=n,this.occlusionQueryCount=0}begin(){return this.renderItemsIndex=0,this.opaque.length=0,this.transparentDoublePass.length=0,this.transparent.length=0,this.bundles.length=0,this.lightsArray.length=0,this.occlusionQueryCount=0,this}getNextRenderItem(e,t,n,i,r,s,o){let a=this.renderItems[this.renderItemsIndex];return void 0===a?(a={id:e.id,object:e,geometry:t,material:n,groupOrder:i,renderOrder:e.renderOrder,z:r,group:s,clippingContext:o},this.renderItems[this.renderItemsIndex]=a):(a.id=e.id,a.object=e,a.geometry=t,a.material=n,a.groupOrder=i,a.renderOrder=e.renderOrder,a.z=r,a.group=s,a.clippingContext=o),this.renderItemsIndex++,a}push(e,t,n,i,r,s,o){const a=this.getNextRenderItem(e,t,n,i,r,s,o);!0===e.occlusionTest&&this.occlusionQueryCount++,!0===n.transparent||n.transmission>0?(aN(n)&&this.transparentDoublePass.push(a),this.transparent.push(a)):this.opaque.push(a)}unshift(e,t,n,i,r,s,o){const a=this.getNextRenderItem(e,t,n,i,r,s,o);!0===n.transparent||n.transmission>0?(aN(n)&&this.transparentDoublePass.unshift(a),this.transparent.unshift(a)):this.opaque.unshift(a)}pushBundle(e){this.bundles.push(e)}pushLight(e){this.lightsArray.push(e)}sort(e,t){this.opaque.length>1&&this.opaque.sort(e||sN),this.transparentDoublePass.length>1&&this.transparentDoublePass.sort(t||oN),this.transparent.length>1&&this.transparent.sort(t||oN)}finish(){this.lightsNode.setLights(this.lightsArray);for(let e=this.renderItemsIndex,t=this.renderItems.length;e<t;e++){const t=this.renderItems[e];if(null===t.id)break;t.id=null,t.object=null,t.geometry=null,t.material=null,t.groupOrder=null,t.renderOrder=null,t.z=null,t.group=null,t.clippingContext=null}}}const uN=[];class cN{constructor(e){this.lighting=e,this.lists=new zP}get(e,t){const n=this.lists;uN[0]=e,uN[1]=t;let i=n.get(uN);return void 0===i&&(i=new lN(this.lighting,e,t),n.set(uN,i)),uN.length=0,i}dispose(){this.lists=new zP}}let dN=0;class hN{constructor(){this.id=dN++,this.color=!0,this.clearColor=!0,this.clearColorValue={r:0,g:0,b:0,a:1},this.depth=!0,this.clearDepth=!0,this.clearDepthValue=1,this.stencil=!1,this.clearStencil=!0,this.clearStencilValue=1,this.viewport=!1,this.viewportValue=new Js,this.scissor=!1,this.scissorValue=new Js,this.renderTarget=null,this.textures=null,this.depthTexture=null,this.activeCubeFace=0,this.activeMipmapLevel=0,this.sampleCount=1,this.width=0,this.height=0,this.occlusionQueryCount=0,this.clippingContext=null,this.isRenderContext=!0}getCacheKey(){return fN(this)}}function fN(e){const{textures:t,activeCubeFace:n,activeMipmapLevel:i}=e,r=[n,i];for(const e of t)r.push(e.id);return $m(r)}const pN=[],gN=new wl,mN=new cl;class vN{constructor(){this.chainMaps={}}get(e,t,n=null){let i;if(pN[0]=e,pN[1]=t,null===n)i="default";else{const e=n.texture.format;i=`${n.textures.length}:${e}:${n.samples}:${n.depthBuffer}:${n.stencilBuffer}`}const r=this._getChainMap(i);let s=r.get(pN);return void 0===s&&(s=new hN,r.set(pN,s)),pN.length=0,null!==n&&(s.sampleCount=0===n.samples?1:n.samples),s}getForClear(e=null){return this.get(gN,mN,e)}_getChainMap(e){return this.chainMaps[e]||(this.chainMaps[e]=new zP)}dispose(){this.chainMaps={}}}const AN=new Es;class xN extends UP{constructor(e,t,n){super(),this.renderer=e,this.backend=t,this.info=n}updateRenderTarget(e,t=0){const n=this.get(e),i=0===e.samples?1:e.samples,r=n.depthTextureMips||(n.depthTextureMips={}),s=e.textures,o=this.getSize(s[0]),a=o.width>>t,l=o.height>>t;let u=e.depthTexture||r[t];const c=!0===e.depthBuffer||!0===e.stencilBuffer;let d=!1;void 0===u&&c&&(u=new _l,u.format=e.stencilBuffer?or:sr,u.type=e.stencilBuffer?$i:Yi,u.image.width=a,u.image.height=l,u.image.depth=o.depth,u.isArrayTexture=!0===e.multiview&&o.depth>1,r[t]=u),n.width===o.width&&o.height===n.height||(d=!0,u&&(u.needsUpdate=!0,u.image.width=a,u.image.height=l,u.image.depth=u.isArrayTexture?u.image.depth:1)),n.width=o.width,n.height=o.height,n.textures=s,n.depthTexture=u||null,n.depth=e.depthBuffer,n.stencil=e.stencilBuffer,n.renderTarget=e,n.sampleCount!==i&&(d=!0,u&&(u.needsUpdate=!0),n.sampleCount=i);const h={sampleCount:i};if(!0!==e.isXRRenderTarget){for(let e=0;e<s.length;e++){const t=s[e];d&&(t.needsUpdate=!0),this.updateTexture(t,h)}u&&this.updateTexture(u,h)}if(!0!==n.initialized){n.initialized=!0;const t=()=>{e.removeEventListener("dispose",t);for(let e=0;e<s.length;e++)this._destroyTexture(s[e]);u&&this._destroyTexture(u),this.delete(e),this.backend.delete(e)};e.addEventListener("dispose",t)}}updateTexture(e,t={}){const n=this.get(e);if(!0===n.initialized&&n.version===e.version)return;const i=e.isRenderTargetTexture||e.isDepthTexture||e.isFramebufferTexture,r=this.backend;if(i&&!0===n.initialized&&(r.destroySampler(e),r.destroyTexture(e)),e.isFramebufferTexture){const t=this.renderer.getRenderTarget();e.type=t?t.texture.type:Gi}const{width:s,height:o,depth:a}=this.getSize(e);if(t.width=s,t.height=o,t.depth=a,t.needsMipmaps=this.needsMipmaps(e),t.levels=t.needsMipmaps?this.getMipLevels(e,s,o):1,e.isCubeTexture&&e.mipmaps.length>0&&t.levels++,i||!0===e.isStorageTexture||!0===e.isExternalTexture)r.createSampler(e),r.createTexture(e,t),n.generation=e.version;else{if(!0!==n.initialized&&r.createSampler(e),e.version>0){const i=e.image;if(void 0===i)console.warn("THREE.Renderer: Texture marked for update but image is undefined.");else if(!1===i.complete)console.warn("THREE.Renderer: Texture marked for update but image is incomplete.");else{if(e.images){const n=[];for(const t of e.images)n.push(t);t.images=n}else t.image=i;void 0!==n.isDefaultTexture&&!0!==n.isDefaultTexture||(r.createTexture(e,t),n.isDefaultTexture=!1,n.generation=e.version),!0===e.source.dataReady&&r.updateTexture(e,t),t.needsMipmaps&&0===e.mipmaps.length&&r.generateMipmaps(e),e.onUpdate&&e.onUpdate(e)}}else r.createDefaultTexture(e),n.isDefaultTexture=!0,n.generation=e.version}if(!0!==n.initialized){n.initialized=!0,n.generation=e.version,this.info.memory.textures++,e.isVideoTexture&&ks.getTransfer(e.colorSpace)!==es&&console.warn("WebGPURenderer: Video textures must use a color space with a sRGB transfer function, e.g. SRGBColorSpace.");const t=()=>{e.removeEventListener("dispose",t),this._destroyTexture(e)};e.addEventListener("dispose",t)}n.version=e.version}getSize(e,t=AN){let n=e.images?e.images[0]:e.image;return n?(void 0!==n.image&&(n=n.image),"undefined"!=typeof HTMLVideoElement&&n instanceof HTMLVideoElement?(t.width=n.videoWidth||1,t.height=n.videoHeight||1,t.depth=1):n instanceof VideoFrame?(t.width=n.displayWidth||1,t.height=n.displayHeight||1,t.depth=1):(t.width=n.width||1,t.height=n.height||1,t.depth=e.isCubeTexture?6:n.depth||1)):t.width=t.height=t.depth=1,t}getMipLevels(e,t,n){let i;return i=e.mipmaps.length>0?e.mipmaps.length:!0===e.isCompressedTexture?1:Math.floor(Math.log2(Math.max(t,n)))+1,i}needsMipmaps(e){return!0===e.generateMipmaps||e.mipmaps.length>0}_destroyTexture(e){!0===this.has(e)&&(this.backend.destroySampler(e),this.backend.destroyTexture(e),this.delete(e),this.info.memory.textures--)}}class yN extends ya{constructor(e,t,n,i=1){super(e,t,n),this.a=i}set(e,t,n,i=1){return this.a=i,super.set(e,t,n)}copy(e){return void 0!==e.a&&(this.a=e.a),super.copy(e)}clone(){return new this.constructor(this.r,this.g,this.b,this.a)}}class bN extends QA{static get type(){return"ParameterNode"}constructor(e,t=null){super(e,t),this.isParameterNode=!0}getHash(){return this.uuid}generate(){return this.name}}class wN extends yv{static get type(){return"StackNode"}constructor(e=null){super(),this.nodes=[],this.outputNode=null,this.parent=e,this._currentCond=null,this._expressionNode=null,this.isStackNode=!0}getNodeType(e){return this.hasOutput?this.outputNode.getNodeType(e):"void"}getMemberType(e,t){return this.hasOutput?this.outputNode.getMemberType(e,t):"void"}add(e){return!0!==e.isNode?(console.error("THREE.TSL: Invalid node added to stack."),this):(this.nodes.push(e),this)}If(e,t){const n=new uA(t);return this._currentCond=bb(e,n),this.add(this._currentCond)}ElseIf(e,t){const n=new uA(t),i=bb(e,n);return this._currentCond.elseNode=i,this._currentCond=i,this}Else(e){return this._currentCond.elseNode=new uA(e),this}Switch(e){return this._expressionNode=cA(e),this}Case(...e){const t=[];if(e.length>=2)for(let n=0;n<e.length-1;n++)t.push(this._expressionNode.equal(cA(e[n])));else console.error("THREE.TSL: Invalid parameter length. Case() requires at least two parameters.");const n=new uA(e[e.length-1]);let i=t[0];for(let e=1;e<t.length;e++)i=i.or(t[e]);const r=bb(i,n);return null===this._currentCond?(this._currentCond=r,this.add(this._currentCond)):(this._currentCond.elseNode=r,this._currentCond=r,this)}Default(e){return this.Else(e),this}setup(e){const t=e.getNodeProperties(this);let n=0;for(const i of this.getChildren()){if(i.isVarNode&&!0===i.intent){if(!0!==e.getNodeProperties(i).assign)continue}t["node"+n++]=i}return t.outputNode||null}get hasOutput(){return this.outputNode&&this.outputNode.isNode}build(e,...t){const n=e.currentStack,i=bA();yA(this),e.currentStack=this;const r=e.buildStage;for(const t of this.nodes){if(t.isVarNode&&!0===t.intent){if(!0!==e.getNodeProperties(t).assign)continue}if("setup"===r)t.build(e);else if("analyze"===r)t.build(e,this);else if("generate"===r){const n=e.getDataFromNode(t,"any").stages,i=n&&n[e.shaderStage];if(t.isVarNode&&i&&1===i.length&&i[0]&&i[0].isStackNode)continue;t.build(e,"void")}}let s;return s=this.hasOutput?this.outputNode.build(e,...t):super.build(e,...t),yA(i),e.currentStack=n,s}}const CN=pA(wN).setParameterLength(0,1);new Il,new Es,new Es,new Es,new Po,new Es(0,0,-1),new Js,new Es,new Es,new Js,new Cs;const MN=new Ks;Hw.flipX();MN.depthTexture=new _l(1,1);const EN=new hc(-1,1,1,-1,0,1);class TN extends Va{constructor(e=!1){super();const t=!1===e?[0,-1,0,1,2,1]:[0,2,0,0,2,0];this.setAttribute("position",new za([-1,3,0,-1,-1,0,3,-1,0],3)),this.setAttribute("uv",new za(t,2))}}const SN=new TN;class PN extends nl{constructor(e=null){super(SN,e),this.camera=EN,this.isQuadMesh=!0}async renderAsync(e){return e.renderAsync(this,EN)}render(e){e.render(this,EN)}}class NN extends yv{static get type(){return"EventNode"}constructor(e,t){super("void"),this.eventType=e,this.callback=t,e===NN.OBJECT?this.updateType=hv.OBJECT:e===NN.MATERIAL&&(this.updateType=hv.RENDER)}update(e){this.callback(e)}}NN.OBJECT="object",NN.MATERIAL="material";const BN=new ko,DN=new Po;class IN extends yv{static get type(){return"SceneNode"}constructor(e=IN.BACKGROUND_BLURRINESS,t=null){super(),this.scope=e,this.scene=t}setup(e){const t=this.scope,n=null!==this.scene?this.scene:e.scene;let i;return t===IN.BACKGROUND_BLURRINESS?i=GC("backgroundBlurriness","float",n):t===IN.BACKGROUND_INTENSITY?i=GC("backgroundIntensity","float",n):t===IN.BACKGROUND_ROTATION?i=Nx("mat4").setName("backgroundRotation").setGroup(Tx).onRenderUpdate((()=>{const e=n.background;return null!==e&&e.isTexture&&e.mapping!==Pi?(BN.copy(n.backgroundRotation),BN.x*=-1,BN.y*=-1,BN.z*=-1,DN.makeRotationFromEuler(BN)):DN.identity(),DN})):console.error("THREE.SceneNode: Unknown scope:",t),i}}IN.BACKGROUND_BLURRINESS="backgroundBlurriness",IN.BACKGROUND_INTENSITY="backgroundIntensity",IN.BACKGROUND_ROTATION="backgroundRotation";const LN=gA(IN,IN.BACKGROUND_BLURRINESS),jN=gA(IN,IN.BACKGROUND_INTENSITY),ON=gA(IN,IN.BACKGROUND_ROTATION);const zN=xA((({texture:e,uv:t})=>{const n=1e-4,i=LA().toVar();return wA(t.x.lessThan(n),(()=>{i.assign(LA(1,0,0))})).ElseIf(t.y.lessThan(n),(()=>{i.assign(LA(0,1,0))})).ElseIf(t.z.lessThan(n),(()=>{i.assign(LA(0,0,1))})).ElseIf(t.x.greaterThan(.9999),(()=>{i.assign(LA(-1,0,0))})).ElseIf(t.y.greaterThan(.9999),(()=>{i.assign(LA(0,-1,0))})).ElseIf(t.z.greaterThan(.9999),(()=>{i.assign(LA(0,0,-1))})).Else((()=>{const n=.01,r=e.sample(t.add(LA(-.01,0,0))).r.sub(e.sample(t.add(LA(n,0,0))).r),s=e.sample(t.add(LA(0,-.01,0))).r.sub(e.sample(t.add(LA(0,n,0))).r),o=e.sample(t.add(LA(0,0,-.01))).r.sub(e.sample(t.add(LA(0,0,n))).r);i.assign(LA(r,s,o))})),i.normalize()}));class RN extends Tw{static get type(){return"Texture3DNode"}constructor(e,t=null,n=null){super(e,t,n),this.isTexture3DNode=!0}getInputType(){return"texture3D"}getDefaultUV(){return LA(.5,.5,.5)}setUpdateMatrix(){}setupUV(e,t){const n=this.value;return!e.isFlipY()||!0!==n.isRenderTargetTexture&&!0!==n.isFramebufferTexture||(t=this.sampler?t.flipY():t.setY(TA(ww(this,this.levelNode).y).sub(t.y).sub(1))),t}generateUV(e,t){return t.build(e,"vec3")}generateOffset(e,t){return t.build(e,"ivec3")}normal(e){return zN({texture:this,uv:e})}}const kN=pA(RN).setParameterLength(1,3);new WeakMap;const FN=new Cs;class HN extends Tw{static get type(){return"PassTextureNode"}constructor(e,t){super(t),this.passNode=e,this.setUpdateMatrix(!1)}setup(e){return this.passNode.build(e),super.setup(e)}clone(){return new this.constructor(this.passNode,this.value)}}class UN extends HN{static get type(){return"PassMultipleTextureNode"}constructor(e,t,n=!1){super(e,null),this.textureName=t,this.previousTexture=n}updateTexture(){this.value=this.previousTexture?this.passNode.getPreviousTexture(this.textureName):this.passNode.getTexture(this.textureName)}setup(e){return this.updateTexture(),super.setup(e)}clone(){const e=new this.constructor(this.passNode,this.textureName,this.previousTexture);return e.uvNode=this.uvNode,e.levelNode=this.levelNode,e.biasNode=this.biasNode,e.sampler=this.sampler,e.depthNode=this.depthNode,e.compareNode=this.compareNode,e.gradNode=this.gradNode,e}}class XN extends Cv{static get type(){return"PassNode"}constructor(e,t,n,i={}){super("vec4"),this.scope=e,this.scene=t,this.camera=n,this.options=i,this._pixelRatio=1,this._width=1,this._height=1;const r=new _l;r.isRenderTargetTexture=!0,r.name="depth";const s=new Ks(this._width*this._pixelRatio,this._height*this._pixelRatio,{type:Ki,...i});s.texture.name="output",s.depthTexture=r,this.renderTarget=s,this._textures={output:s.texture,depth:r},this._textureNodes={},this._linearDepthNodes={},this._viewZNodes={},this._previousTextures={},this._previousTextureNodes={},this._cameraNear=Nx(0),this._cameraFar=Nx(0),this._mrt=null,this._layers=null,this._resolution=1,this._viewport=null,this._scissor=null,this.isPassNode=!0,this.updateBeforeType=hv.FRAME,this.global=!0}setResolution(e){return this._resolution=e,this}getResolution(){return this._resolution}setLayers(e){return this._layers=e,this}getLayers(){return this._layers}setMRT(e){return this._mrt=e,this}getMRT(){return this._mrt}getTexture(e){let t=this._textures[e];if(void 0===t){t=this.renderTarget.texture.clone(),t.name=e,this._textures[e]=t,this.renderTarget.textures.push(t)}return t}getPreviousTexture(e){let t=this._previousTextures[e];return void 0===t&&(t=this.getTexture(e).clone(),this._previousTextures[e]=t),t}toggleTexture(e){const t=this._previousTextures[e];if(void 0!==t){const n=this._textures[e],i=this.renderTarget.textures.indexOf(n);this.renderTarget.textures[i]=t,this._textures[e]=t,this._previousTextures[e]=n,this._textureNodes[e].updateTexture(),this._previousTextureNodes[e].updateTexture()}}getTextureNode(e="output"){let t=this._textureNodes[e];return void 0===t&&(t=cA(new UN(this,e)),t.updateTexture(),this._textureNodes[e]=t),t}getPreviousTextureNode(e="output"){let t=this._previousTextureNodes[e];return void 0===t&&(void 0===this._textureNodes[e]&&this.getTextureNode(e),t=cA(new UN(this,e,!0)),t.updateTexture(),this._previousTextureNodes[e]=t),t}getViewZNode(e="depth"){let t=this._viewZNodes[e];if(void 0===t){const n=this._cameraNear,i=this._cameraFar;this._viewZNodes[e]=t=HE(this.getTextureNode(e),n,i)}return t}getLinearDepthNode(e="depth"){let t=this._linearDepthNodes[e];if(void 0===t){const n=this._cameraNear,i=this._cameraFar,r=this.getViewZNode(e);this._linearDepthNodes[e]=t=kE(r,n,i)}return t}async compileAsync(e){const t=e.getRenderTarget(),n=e.getMRT();e.setRenderTarget(this.renderTarget),e.setMRT(this._mrt),await e.compileAsync(this.scene,this.camera),e.setRenderTarget(t),e.setMRT(n)}setup({renderer:e}){return this.renderTarget.samples=void 0===this.options.samples?e.samples:this.options.samples,this.renderTarget.texture.type=e.getColorBufferType(),this.scope===XN.COLOR?this.getTextureNode():this.getLinearDepthNode()}updateBefore(e){const{renderer:t}=e,{scene:n}=this;let i,r;const s=t.getOutputRenderTarget();s&&!0===s.isXRRenderTarget?(r=1,i=t.xr.getCamera(),t.xr.updateCamera(i),FN.set(s.width,s.height)):(i=this.camera,r=t.getPixelRatio(),t.getSize(FN)),this._pixelRatio=r,this.setSize(FN.width,FN.height);const o=t.getRenderTarget(),a=t.getMRT(),l=i.layers.mask;this._cameraNear.value=i.near,this._cameraFar.value=i.far,null!==this._layers&&(i.layers.mask=this._layers.mask);for(const e in this._previousTextures)this.toggleTexture(e);t.setRenderTarget(this.renderTarget),t.setMRT(this._mrt),t.render(n,i),t.setRenderTarget(o),t.setMRT(a),i.layers.mask=l}setSize(e,t){this._width=e,this._height=t;const n=this._width*this._pixelRatio*this._resolution,i=this._height*this._pixelRatio*this._resolution;this.renderTarget.setSize(n,i),null!==this._scissor&&this.renderTarget.scissor.copy(this._scissor),null!==this._viewport&&this.renderTarget.viewport.copy(this._viewport)}setScissor(e,t,n,i){null===e?this._scissor=null:(null===this._scissor&&(this._scissor=new Js),e.isVector4?this._scissor.copy(e):this._scissor.set(e,t,n,i),this._scissor.multiplyScalar(this._pixelRatio*this._resolution).floor())}setViewport(e,t,n,i){null===e?this._viewport=null:(null===this._viewport&&(this._viewport=new Js),e.isVector4?this._viewport.copy(e):this._viewport.set(e,t,n,i),this._viewport.multiplyScalar(this._pixelRatio*this._resolution).floor())}setPixelRatio(e){this._pixelRatio=e,this.setSize(this._width,this._height)}dispose(){this.renderTarget.dispose()}}XN.COLOR="color",XN.DEPTH="depth";const GN=xA((([e,t])=>e.mul(t).clamp())).setLayout({name:"linearToneMapping",type:"vec3",inputs:[{name:"color",type:"vec3"},{name:"exposure",type:"float"}]}),VN=xA((([e,t])=>(e=e.mul(t)).div(e.add(1)).clamp())).setLayout({name:"reinhardToneMapping",type:"vec3",inputs:[{name:"color",type:"vec3"},{name:"exposure",type:"float"}]}),WN=xA((([e,t])=>{const n=(e=(e=e.mul(t)).sub(.004).max(0)).mul(e.mul(6.2).add(.5)),i=e.mul(e.mul(6.2).add(1.7)).add(.06);return n.div(i).pow(2.2)})).setLayout({name:"cineonToneMapping",type:"vec3",inputs:[{name:"color",type:"vec3"},{name:"exposure",type:"float"}]}),QN=xA((([e])=>{const t=e.mul(e.add(.0245786)).sub(90537e-9),n=e.mul(e.add(.432951).mul(.983729)).add(.238081);return t.div(n)})),ZN=xA((([e,t])=>{const n=XA(.59719,.35458,.04823,.076,.90834,.01566,.0284,.13383,.83777),i=XA(1.60475,-.53108,-.07367,-.10208,1.10813,-.00605,-.00327,-.07276,1.07602);return e=e.mul(t).div(.6),e=n.mul(e),e=QN(e),(e=i.mul(e)).clamp()})).setLayout({name:"acesFilmicToneMapping",type:"vec3",inputs:[{name:"color",type:"vec3"},{name:"exposure",type:"float"}]}),YN=XA(LA(1.6605,-.1246,-.0182),LA(-.5876,1.1329,-.1006),LA(-.0728,-.0083,1.1187)),JN=XA(LA(.6274,.0691,.0164),LA(.3293,.9195,.088),LA(.0433,.0113,.8956)),KN=xA((([e])=>{const t=LA(e).toVar(),n=LA(t.mul(t)).toVar(),i=LA(n.mul(n)).toVar();return EA(15.5).mul(i.mul(n)).sub(Hx(40.14,i.mul(t))).add(Hx(31.96,i).sub(Hx(6.868,n.mul(t))).add(Hx(.4298,n).add(Hx(.1191,t).sub(.00232))))})),qN=xA((([e,t])=>{const n=LA(e).toVar(),i=XA(LA(.856627153315983,.137318972929847,.11189821299995),LA(.0951212405381588,.761241990602591,.0767994186031903),LA(.0482516061458583,.101439036467562,.811302368396859)),r=XA(LA(1.1271005818144368,-.1413297634984383,-.14132976349843826),LA(-.11060664309660323,1.157823702216272,-.11060664309660294),LA(-.016493938717834573,-.016493938717834257,1.2519364065950405)),s=EA(-12.47393),o=EA(4.026069);return n.mulAssign(t),n.assign(JN.mul(n)),n.assign(i.mul(n)),n.assign(Jy(n,1e-10)),n.assign(yy(n)),n.assign(n.sub(s).div(o.sub(s))),n.assign(cb(n,0,1)),n.assign(KN(n)),n.assign(r.mul(n)),n.assign(nb(Jy(LA(0),n),LA(2.2))),n.assign(YN.mul(n)),n.assign(cb(n,0,1)),n})).setLayout({name:"agxToneMapping",type:"vec3",inputs:[{name:"color",type:"vec3"},{name:"exposure",type:"float"}]}),_N=xA((([e,t])=>{const n=EA(.76),i=EA(.15);e=e.mul(t);const r=Yy(e.r,Yy(e.g,e.b)),s=bb(r.lessThan(.08),r.sub(Hx(6.25,r.mul(r))),.04);e.subAssign(s);const o=Jy(e.r,Jy(e.g,e.b));wA(o.lessThan(n),(()=>e));const a=Fx(1,n),l=Fx(1,a.mul(a).div(o.add(a.sub(n))));e.mulAssign(l.div(o));const u=Fx(1,Ux(1,i.mul(o.sub(l)).add(1)));return ub(e,LA(l),u)})).setLayout({name:"neutralToneMapping",type:"vec3",inputs:[{name:"color",type:"vec3"},{name:"exposure",type:"float"}]});class $N extends yv{static get type(){return"CodeNode"}constructor(e="",t=[],n=""){super("code"),this.isCodeNode=!0,this.global=!0,this.code=e,this.includes=t,this.language=n}setIncludes(e){return this.includes=e,this}getIncludes(){return this.includes}generate(e){const t=this.getIncludes(e);for(const n of t)n.build(e);const n=e.getCodeFromNode(this,this.getNodeType(e));return n.code=this.code,n.code}serialize(e){super.serialize(e),e.code=this.code,e.language=this.language}deserialize(e){super.deserialize(e),this.code=e.code,this.language=e.language}}class eB extends $N{static get type(){return"FunctionNode"}constructor(e="",t=[],n=""){super(e,t,n)}getNodeType(e){return this.getNodeFunction(e).type}getMemberType(e,t){const n=this.getNodeType(e);return e.getStructTypeNode(n).getMemberType(e,t)}getInputs(e){return this.getNodeFunction(e).inputs}getNodeFunction(e){const t=e.getDataFromNode(this);let n=t.nodeFunction;return void 0===n&&(n=e.parser.parseFunction(this.code),t.nodeFunction=n),n}generate(e,t){super.generate(e);const n=this.getNodeFunction(e),i=n.name,r=n.type,s=e.getCodeFromNode(this,r);""!==i&&(s.name=i);const o=e.getPropertyName(s),a=this.getNodeFunction(e).getCode(o);return s.code=a+"\n","property"===t?o:e.format(`${o}()`,r,t)}}class tB extends Map{get(e,t=null,...n){if(this.has(e))return super.get(e);if(null!==t){const i=t(...n);return this.set(e,i),i}}}new tB;function nB(e){let t;const n=e.context.getViewZ;return void 0!==n&&(t=n(this)),(t||hC.z).negate()}const iB=xA((([e,t],n)=>{const i=nB(n);return fb(e,t,i)})),rB=xA((([e],t)=>{const n=nB(t);return e.mul(e,n,n).negate().exp().oneMinus()})),sB=xA((([e,t])=>RA(t.toFloat().mix(fx.rgb,e.toVec3()),fx.a)));pA(class extends yv{constructor(e){super(),this.scope=e}generate(e){const{scope:t}=this,{renderer:n}=e;!0===n.backend.isWebGLBackend?e.addFlowCode(`\t// ${t}Barrier \n`):e.addLineFlowCode(`${t}Barrier()`,this)}});class oB extends yv{static get type(){return"AtomicFunctionNode"}constructor(e,t,n){super("uint"),this.method=e,this.pointerNode=t,this.valueNode=n,this.parents=!0}getInputType(e){return this.pointerNode.getNodeType(e)}getNodeType(e){return this.getInputType(e)}generate(e){const t=e.getNodeProperties(this),n=t.parents,i=this.method,r=this.getNodeType(e),s=this.getInputType(e),o=this.pointerNode,a=this.valueNode,l=[];l.push(`&${o.build(e,s)}`),null!==a&&l.push(a.build(e,s));const u=`${e.getMethod(i,r)}( ${l.join(", ")} )`;if(!(!!n&&(1===n.length&&!0===n[0].isStackNode)))return void 0===t.constNode&&(t.constNode=hw(u,r).toConst()),t.constNode.build(e);e.addLineFlowCode(u,this)}}oB.ATOMIC_LOAD="atomicLoad",oB.ATOMIC_STORE="atomicStore",oB.ATOMIC_ADD="atomicAdd",oB.ATOMIC_SUB="atomicSub",oB.ATOMIC_MAX="atomicMax",oB.ATOMIC_MIN="atomicMin",oB.ATOMIC_AND="atomicAnd",oB.ATOMIC_OR="atomicOr",oB.ATOMIC_XOR="atomicXor";pA(oB);class aB extends Cv{static get type(){return"SubgroupFunctionNode"}constructor(e,t=null,n=null){super(),this.method=e,this.aNode=t,this.bNode=n}getInputType(e){const t=this.aNode?this.aNode.getNodeType(e):null,n=this.bNode?this.bNode.getNodeType(e):null;return(e.isMatrix(t)?0:e.getTypeLength(t))>(e.isMatrix(n)?0:e.getTypeLength(n))?t:n}getNodeType(e){const t=this.method;return t===aB.SUBGROUP_ELECT?"bool":t===aB.SUBGROUP_BALLOT?"uvec4":this.getInputType(e)}generate(e,t){const n=this.method,i=this.getNodeType(e),r=this.getInputType(e),s=this.aNode,o=this.bNode,a=[];if(n===aB.SUBGROUP_BROADCAST||n===aB.SUBGROUP_SHUFFLE||n===aB.QUAD_BROADCAST){const t=o.getNodeType(e);a.push(s.build(e,i),o.build(e,"float"===t?"int":i))}else n===aB.SUBGROUP_SHUFFLE_XOR||n===aB.SUBGROUP_SHUFFLE_DOWN||n===aB.SUBGROUP_SHUFFLE_UP?a.push(s.build(e,i),o.build(e,"uint")):(null!==s&&a.push(s.build(e,r)),null!==o&&a.push(o.build(e,r)));const l=0===a.length?"()":`( ${a.join(", ")} )`;return e.format(`${e.getMethod(n,i)}${l}`,i,t)}serialize(e){super.serialize(e),e.method=this.method}deserialize(e){super.deserialize(e),this.method=e.method}}aB.SUBGROUP_ELECT="subgroupElect",aB.SUBGROUP_BALLOT="subgroupBallot",aB.SUBGROUP_ADD="subgroupAdd",aB.SUBGROUP_INCLUSIVE_ADD="subgroupInclusiveAdd",aB.SUBGROUP_EXCLUSIVE_AND="subgroupExclusiveAdd",aB.SUBGROUP_MUL="subgroupMul",aB.SUBGROUP_INCLUSIVE_MUL="subgroupInclusiveMul",aB.SUBGROUP_EXCLUSIVE_MUL="subgroupExclusiveMul",aB.SUBGROUP_AND="subgroupAnd",aB.SUBGROUP_OR="subgroupOr",aB.SUBGROUP_XOR="subgroupXor",aB.SUBGROUP_MIN="subgroupMin",aB.SUBGROUP_MAX="subgroupMax",aB.SUBGROUP_ALL="subgroupAll",aB.SUBGROUP_ANY="subgroupAny",aB.SUBGROUP_BROADCAST_FIRST="subgroupBroadcastFirst",aB.QUAD_SWAP_X="quadSwapX",aB.QUAD_SWAP_Y="quadSwapY",aB.QUAD_SWAP_DIAGONAL="quadSwapDiagonal",aB.SUBGROUP_BROADCAST="subgroupBroadcast",aB.SUBGROUP_SHUFFLE="subgroupShuffle",aB.SUBGROUP_SHUFFLE_XOR="subgroupShuffleXor",aB.SUBGROUP_SHUFFLE_UP="subgroupShuffleUp",aB.SUBGROUP_SHUFFLE_DOWN="subgroupShuffleDown",aB.QUAD_BROADCAST="quadBroadcast";let lB;function uB(e){lB=lB||new WeakMap;let t=lB.get(e);return void 0===t&&lB.set(e,t={}),t}function cB(e){const t=uB(e);return t.shadowMatrix||(t.shadowMatrix=Nx("mat4").setGroup(Tx).onRenderUpdate((t=>(!0===e.castShadow&&!1!==t.renderer.shadowMap.enabled||e.shadow.updateMatrices(e),e.shadow.matrix))))}function dB(e,t=cC){const n=cB(e).mul(t);return n.xyz.div(n.w)}function hB(e){const t=uB(e);return t.position||(t.position=Nx(new Es).setGroup(Tx).onRenderUpdate(((t,n)=>n.value.setFromMatrixPosition(e.matrixWorld))))}function fB(e){const t=uB(e);return t.targetPosition||(t.targetPosition=Nx(new Es).setGroup(Tx).onRenderUpdate(((t,n)=>n.value.setFromMatrixPosition(e.target.matrixWorld))))}function pB(e){const t=uB(e);return t.viewPosition||(t.viewPosition=Nx(new Es).setGroup(Tx).onRenderUpdate((({camera:t},n)=>{n.value=n.value||new Es,n.value.setFromMatrixPosition(e.matrixWorld),n.value.applyMatrix4(t.matrixWorldInverse)})))}const gB=e=>Jw.transformDirection(hB(e).sub(fB(e))),mB=(e,t)=>{for(const n of t)if(n.isAnalyticLightNode&&n.light.id===e)return n;return null},vB=new WeakMap,AB=[];class xB extends yv{static get type(){return"LightsNode"}constructor(){super("vec3"),this.totalDiffuseNode=ZA("vec3","totalDiffuse"),this.totalSpecularNode=ZA("vec3","totalSpecular"),this.outgoingLightNode=ZA("vec3","outgoingLight"),this._lights=[],this._lightNodes=null,this._lightNodesHash=null,this.global=!0}customCacheKey(){const e=this._lights;for(let t=0;t<e.length;t++){const n=e[t];if(AB.push(n.id),AB.push(n.castShadow?1:0),!0===n.isSpotLight){const e=null!==n.map?n.map.id:-1,t=n.colorNode?n.colorNode.getCacheKey():-1;AB.push(e,t)}}const t=$m(AB);return AB.length=0,t}getHash(e){if(null===this._lightNodesHash){null===this._lightNodes&&this.setupLightsNode(e);const t=[];for(const e of this._lightNodes)t.push(e.getHash());this._lightNodesHash="lights-"+t.join(",")}return this._lightNodesHash}analyze(e){const t=e.getNodeProperties(this);for(const n of t.nodes)n.build(e);t.outputNode.build(e)}setupLightsNode(e){const t=[],n=this._lightNodes,i=(e=>e.sort(((e,t)=>e.id-t.id)))(this._lights),r=e.renderer.library;for(const e of i)if(e.isNode)t.push(cA(e));else{let i=null;if(null!==n&&(i=mB(e.id,n)),null===i){const n=r.getLightNodeClass(e.constructor);if(null===n){console.warn(`LightsNode.setupNodeLights: Light node not found for ${e.constructor.name}`);continue}let i=null;vB.has(e)?i=vB.get(e):(i=cA(new n(e)),vB.set(e,i)),t.push(i)}}this._lightNodes=t}setupDirectLight(e,t,n){const{lightingModel:i,reflectedLight:r}=e.context;i.direct({...n,lightNode:t,reflectedLight:r},e)}setupDirectRectAreaLight(e,t,n){const{lightingModel:i,reflectedLight:r}=e.context;i.directRectArea({...n,lightNode:t,reflectedLight:r},e)}setupLights(e,t){for(const n of t)n.build(e)}getLightNodes(e){return null===this._lightNodes&&this.setupLightsNode(e),this._lightNodes}setup(e){const t=e.lightsNode;e.lightsNode=this;let n=this.outgoingLightNode;const i=e.context,r=i.lightingModel,s=e.getNodeProperties(this);if(r){const{totalDiffuseNode:t,totalSpecularNode:o}=this;i.outgoingLight=n;const a=e.addStack();s.nodes=a.nodes,r.start(e);const{backdrop:l,backdropAlpha:u}=i,{directDiffuse:c,directSpecular:d,indirectDiffuse:h,indirectSpecular:f}=i.reflectedLight;let p=c.add(h);null!==l&&(p=LA(null!==u?u.mix(p,l):l),i.material.transparent=!0),t.assign(p),o.assign(d.add(f)),n.assign(t.add(o)),r.finish(e),n=n.bypass(e.removeStack())}else s.nodes=[];return e.lightsNode=t,n}setLights(e){return this._lights=e,this._lightNodes=null,this._lightNodesHash=null,this}getLights(){return this._lights}get hasLights(){return this._lights.length>0}}class yB extends yv{static get type(){return"ShadowBaseNode"}constructor(e){super(),this.light=e,this.updateBeforeType=hv.RENDER,this.isShadowBaseNode=!0}setupShadowPosition({context:e,material:t}){bB.assign(t.receivedShadowPositionNode||e.shadowPositionWorld||cC)}}const bB=ZA("vec3","shadowPositionWorld");function wB(e,t={}){return t.toneMapping=e.toneMapping,t.toneMappingExposure=e.toneMappingExposure,t.outputColorSpace=e.outputColorSpace,t.renderTarget=e.getRenderTarget(),t.activeCubeFace=e.getActiveCubeFace(),t.activeMipmapLevel=e.getActiveMipmapLevel(),t.renderObjectFunction=e.getRenderObjectFunction(),t.pixelRatio=e.getPixelRatio(),t.mrt=e.getMRT(),t.clearColor=e.getClearColor(t.clearColor||new ya),t.clearAlpha=e.getClearAlpha(),t.autoClear=e.autoClear,t.scissorTest=e.getScissorTest(),t}function CB(e,t){return t=wB(e,t),e.setMRT(null),e.setRenderObjectFunction(null),e.setClearColor(0,1),e.autoClear=!0,t}function MB(e,t){e.toneMapping=t.toneMapping,e.toneMappingExposure=t.toneMappingExposure,e.outputColorSpace=t.outputColorSpace,e.setRenderTarget(t.renderTarget,t.activeCubeFace,t.activeMipmapLevel),e.setRenderObjectFunction(t.renderObjectFunction),e.setPixelRatio(t.pixelRatio),e.setMRT(t.mrt),e.setClearColor(t.clearColor,t.clearAlpha),e.autoClear=t.autoClear,e.setScissorTest(t.scissorTest)}function EB(e,t={}){return t.background=e.background,t.backgroundNode=e.backgroundNode,t.overrideMaterial=e.overrideMaterial,t}function TB(e,t){return t=EB(e,t),e.background=null,e.backgroundNode=null,e.overrideMaterial=null,t}function SB(e,t){e.background=t.background,e.backgroundNode=t.backgroundNode,e.overrideMaterial=t.overrideMaterial}function PB(e,t,n){return n=TB(t,n=CB(e,n))}function NB(e,t,n){MB(e,n),SB(t,n)}const BB=new WeakMap,DB=xA((({depthTexture:e,shadowCoord:t,depthLayer:n})=>{let i=Pw(e,t.xy).setName("t_basic");return e.isArrayTexture&&(i=i.depth(n)),i.compare(t.z)})),IB=xA((({depthTexture:e,shadowCoord:t,shadow:n,depthLayer:i})=>{const r=(t,n)=>{let r=Pw(e,t);return e.isArrayTexture&&(r=r.depth(i)),r.compare(n)},s=GC("mapSize","vec2",n).setGroup(Tx),o=GC("radius","float",n).setGroup(Tx),a=NA(1).div(s),l=a.x.negate().mul(o),u=a.y.negate().mul(o),c=a.x.mul(o),d=a.y.mul(o),h=l.div(2),f=u.div(2),p=c.div(2),g=d.div(2);return kx(r(t.xy.add(NA(l,u)),t.z),r(t.xy.add(NA(0,u)),t.z),r(t.xy.add(NA(c,u)),t.z),r(t.xy.add(NA(h,f)),t.z),r(t.xy.add(NA(0,f)),t.z),r(t.xy.add(NA(p,f)),t.z),r(t.xy.add(NA(l,0)),t.z),r(t.xy.add(NA(h,0)),t.z),r(t.xy,t.z),r(t.xy.add(NA(p,0)),t.z),r(t.xy.add(NA(c,0)),t.z),r(t.xy.add(NA(h,g)),t.z),r(t.xy.add(NA(0,g)),t.z),r(t.xy.add(NA(p,g)),t.z),r(t.xy.add(NA(l,d)),t.z),r(t.xy.add(NA(0,d)),t.z),r(t.xy.add(NA(c,d)),t.z)).mul(1/17)})),LB=xA((({depthTexture:e,shadowCoord:t,shadow:n,depthLayer:i})=>{const r=(t,n)=>{let r=Pw(e,t);return e.isArrayTexture&&(r=r.depth(i)),r.compare(n)},s=GC("mapSize","vec2",n).setGroup(Tx),o=NA(1).div(s),a=o.x,l=o.y,u=t.xy,c=Ty(u.mul(s).add(.5));return u.subAssign(c.mul(o)),kx(r(u,t.z),r(u.add(NA(a,0)),t.z),r(u.add(NA(0,l)),t.z),r(u.add(o),t.z),ub(r(u.add(NA(a.negate(),0)),t.z),r(u.add(NA(a.mul(2),0)),t.z),c.x),ub(r(u.add(NA(a.negate(),l)),t.z),r(u.add(NA(a.mul(2),l)),t.z),c.x),ub(r(u.add(NA(0,l.negate())),t.z),r(u.add(NA(0,l.mul(2))),t.z),c.y),ub(r(u.add(NA(a,l.negate())),t.z),r(u.add(NA(a,l.mul(2))),t.z),c.y),ub(ub(r(u.add(NA(a.negate(),l.negate())),t.z),r(u.add(NA(a.mul(2),l.negate())),t.z),c.x),ub(r(u.add(NA(a.negate(),l.mul(2))),t.z),r(u.add(NA(a.mul(2),l.mul(2))),t.z),c.x),c.y)).mul(1/9)})),jB=xA((({depthTexture:e,shadowCoord:t,depthLayer:n})=>{const i=EA(1).toVar();let r=Pw(e).sample(t.xy);e.isArrayTexture&&(r=r.depth(n)),r=r.rg;const s=Ky(t.z,r.x);return wA(s.notEqual(EA(1)),(()=>{const e=t.z.sub(r.x),n=Jy(0,r.y.mul(r.y));let o=n.div(n.add(e.mul(e)));o=cb(Fx(o,.3).div(.95-.3)),i.assign(cb(Jy(s,o)))})),i})),OB=xA((([e,t,n])=>{let i=cC.sub(e).length();return i=i.sub(t).div(n.sub(t)),i=i.saturate(),i})),zB=e=>{let t=BB.get(e);if(void 0===t){const n=e.isPointLight?(e=>{const t=e.shadow.camera,n=GC("near","float",t).setGroup(Tx),i=GC("far","float",t).setGroup(Tx),r=$w(e);return OB(r,n,i)})(e):null;t=new _E,t.colorNode=RA(0,0,0,1),t.depthNode=n,t.isShadowPassMaterial=!0,t.name="ShadowMaterial",t.fog=!1,BB.set(e,t)}return t},RB=new zP,kB=[],FB=(e,t,n,i)=>{kB[0]=e,kB[1]=t;let r=RB.get(kB);return void 0!==r&&r.shadowType===n&&r.useVelocity===i||(r=(r,s,o,a,l,u,...c)=>{(!0===r.castShadow||r.receiveShadow&&3===n)&&(i&&(lv(r).useVelocity=!0),r.onBeforeShadow(e,r,o,t.camera,a,s.overrideMaterial,u),e.renderObject(r,s,o,a,l,u,...c),r.onAfterShadow(e,r,o,t.camera,a,s.overrideMaterial,u))},r.shadowType=n,r.useVelocity=i,RB.set(kB,r)),kB[0]=null,kB[1]=null,r},HB=xA((({samples:e,radius:t,size:n,shadowPass:i,depthLayer:r})=>{const s=EA(0).toVar("meanVertical"),o=EA(0).toVar("squareMeanVertical"),a=e.lessThanEqual(EA(1)).select(EA(0),EA(2).div(e.sub(1))),l=e.lessThanEqual(EA(1)).select(EA(0),EA(-1));xE({start:TA(0),end:TA(e),type:"int",condition:"<"},(({i:e})=>{const u=l.add(EA(e).mul(a));let c=i.sample(kx(Xw.xy,NA(0,u).mul(t)).div(n));i.value.isArrayTexture&&(c=c.depth(r)),c=c.x,s.addAssign(c),o.addAssign(c.mul(c))})),s.divAssign(e),o.divAssign(e);const u=by(o.sub(s.mul(s)));return NA(s,u)})),UB=xA((({samples:e,radius:t,size:n,shadowPass:i,depthLayer:r})=>{const s=EA(0).toVar("meanHorizontal"),o=EA(0).toVar("squareMeanHorizontal"),a=e.lessThanEqual(EA(1)).select(EA(0),EA(2).div(e.sub(1))),l=e.lessThanEqual(EA(1)).select(EA(0),EA(-1));xE({start:TA(0),end:TA(e),type:"int",condition:"<"},(({i:e})=>{const u=l.add(EA(e).mul(a));let c=i.sample(kx(Xw.xy,NA(u,0).mul(t)).div(n));i.value.isArrayTexture&&(c=c.depth(r)),s.addAssign(c.x),o.addAssign(kx(c.y.mul(c.y),c.x.mul(c.x)))})),s.divAssign(e),o.divAssign(e);const u=by(o.sub(s.mul(s)));return NA(s,u)})),XB=[DB,IB,LB,jB];let GB;const VB=new PN;class WB extends yB{static get type(){return"ShadowNode"}constructor(e,t=null){super(e),this.shadow=t||e.shadow,this.shadowMap=null,this.vsmShadowMapVertical=null,this.vsmShadowMapHorizontal=null,this.vsmMaterialVertical=null,this.vsmMaterialHorizontal=null,this._node=null,this._cameraFrameId=new WeakMap,this.isShadowNode=!0,this.depthLayer=0}setupShadowFilter(e,{filterFn:t,depthTexture:n,shadowCoord:i,shadow:r,depthLayer:s}){const o=i.x.greaterThanEqual(0).and(i.x.lessThanEqual(1)).and(i.y.greaterThanEqual(0)).and(i.y.lessThanEqual(1)).and(i.z.lessThanEqual(1)),a=t({depthTexture:n,shadowCoord:i,shadow:r,depthLayer:s});return o.select(a,EA(1))}setupShadowCoord(e,t){const{shadow:n}=this,{renderer:i}=e,r=GC("bias","float",n).setGroup(Tx);let s,o=t;if(n.camera.isOrthographicCamera||!0!==i.logarithmicDepthBuffer)o=o.xyz.div(o.w),s=o.z,i.coordinateSystem===ls&&(s=s.mul(2).sub(1));else{const e=o.w;o=o.xy.div(e);const t=GC("near","float",n.camera).setGroup(Tx),i=GC("far","float",n.camera).setGroup(Tx);s=UE(e.negate(),t,i)}return o=LA(o.x,o.y.oneMinus(),s.add(r)),o}getShadowFilterFn(e){return XB[e]}setupRenderTarget(e,t){const n=new _l(e.mapSize.width,e.mapSize.height);n.name="ShadowDepthTexture",n.compareFunction=ns;const i=t.createRenderTarget(e.mapSize.width,e.mapSize.height);return i.texture.name="ShadowMap",i.texture.type=e.mapType,i.depthTexture=n,{shadowMap:i,depthTexture:n}}setupShadow(e){const{renderer:t}=e,{light:n,shadow:i}=this,r=t.shadowMap.type,{depthTexture:s,shadowMap:o}=this.setupRenderTarget(i,e);if(i.camera.updateProjectionMatrix(),3===r&&!0!==i.isPointLightShadow){s.compareFunction=null,o.depth>1?(o._vsmShadowMapVertical||(o._vsmShadowMapVertical=e.createRenderTarget(i.mapSize.width,i.mapSize.height,{format:ur,type:Ki,depth:o.depth,depthBuffer:!1}),o._vsmShadowMapVertical.texture.name="VSMVertical"),this.vsmShadowMapVertical=o._vsmShadowMapVertical,o._vsmShadowMapHorizontal||(o._vsmShadowMapHorizontal=e.createRenderTarget(i.mapSize.width,i.mapSize.height,{format:ur,type:Ki,depth:o.depth,depthBuffer:!1}),o._vsmShadowMapHorizontal.texture.name="VSMHorizontal"),this.vsmShadowMapHorizontal=o._vsmShadowMapHorizontal):(this.vsmShadowMapVertical=e.createRenderTarget(i.mapSize.width,i.mapSize.height,{format:ur,type:Ki,depthBuffer:!1}),this.vsmShadowMapHorizontal=e.createRenderTarget(i.mapSize.width,i.mapSize.height,{format:ur,type:Ki,depthBuffer:!1}));let t=Pw(s);s.isArrayTexture&&(t=t.depth(this.depthLayer));let n=Pw(this.vsmShadowMapVertical.texture);s.isArrayTexture&&(n=n.depth(this.depthLayer));const r=GC("blurSamples","float",i).setGroup(Tx),a=GC("radius","float",i).setGroup(Tx),l=GC("mapSize","vec2",i).setGroup(Tx);let u=this.vsmMaterialVertical||(this.vsmMaterialVertical=new _E);u.fragmentNode=HB({samples:r,radius:a,size:l,shadowPass:t,depthLayer:this.depthLayer}).context(e.getSharedContext()),u.name="VSMVertical",u=this.vsmMaterialHorizontal||(this.vsmMaterialHorizontal=new _E),u.fragmentNode=UB({samples:r,radius:a,size:l,shadowPass:n,depthLayer:this.depthLayer}).context(e.getSharedContext()),u.name="VSMHorizontal"}const a=GC("intensity","float",i).setGroup(Tx),l=GC("normalBias","float",i).setGroup(Tx),u=cB(n).mul(bB.add(MC.mul(l))),c=this.setupShadowCoord(e,u),d=i.filterNode||this.getShadowFilterFn(t.shadowMap.type)||null;if(null===d)throw new Error("THREE.WebGPURenderer: Shadow map type not supported yet.");const h=3===r&&!0!==i.isPointLightShadow?this.vsmShadowMapHorizontal.texture:s,f=this.setupShadowFilter(e,{filterFn:d,shadowTexture:o.texture,depthTexture:h,shadowCoord:c,shadow:i,depthLayer:this.depthLayer});let p=Pw(o.texture,c);s.isArrayTexture&&(p=p.depth(this.depthLayer));const g=ub(1,f.rgb.mix(p,1),a.mul(p.a)).toVar();return this.shadowMap=o,this.shadow.map=o,g}setup(e){if(!1!==e.renderer.shadowMap.enabled)return xA((()=>{let t=this._node;return this.setupShadowPosition(e),null===t&&(this._node=t=this.setupShadow(e)),e.material.shadowNode&&console.warn('THREE.NodeMaterial: ".shadowNode" is deprecated. Use ".castShadowNode" instead.'),e.material.receivedShadowNode&&(t=e.material.receivedShadowNode(t)),t}))()}renderShadow(e){const{shadow:t,shadowMap:n,light:i}=this,{renderer:r,scene:s}=e;t.updateMatrices(i),n.setSize(t.mapSize.width,t.mapSize.height,n.depth),r.render(s,t.camera)}updateShadow(e){const{shadowMap:t,light:n,shadow:i}=this,{renderer:r,scene:s,camera:o}=e,a=r.shadowMap.type,l=t.depthTexture.version;this._depthVersionCached=l;const u=i.camera.layers.mask;0==(4294967294&i.camera.layers.mask)&&(i.camera.layers.mask=o.layers.mask);const c=r.getRenderObjectFunction(),d=r.getMRT(),h=!!d&&d.has("velocity");GB=PB(r,s,GB),s.overrideMaterial=zB(n),r.setRenderObjectFunction(FB(r,i,a,h)),r.setClearColor(0,0),r.setRenderTarget(t),this.renderShadow(e),r.setRenderObjectFunction(c),3===a&&!0!==i.isPointLightShadow&&this.vsmPass(r),i.camera.layers.mask=u,NB(r,s,GB)}vsmPass(e){const{shadow:t}=this,n=this.shadowMap.depth;this.vsmShadowMapVertical.setSize(t.mapSize.width,t.mapSize.height,n),this.vsmShadowMapHorizontal.setSize(t.mapSize.width,t.mapSize.height,n),e.setRenderTarget(this.vsmShadowMapVertical),VB.material=this.vsmMaterialVertical,VB.render(e),e.setRenderTarget(this.vsmShadowMapHorizontal),VB.material=this.vsmMaterialHorizontal,VB.render(e)}dispose(){this.shadowMap.dispose(),this.shadowMap=null,null!==this.vsmShadowMapVertical&&(this.vsmShadowMapVertical.dispose(),this.vsmShadowMapVertical=null,this.vsmMaterialVertical.dispose(),this.vsmMaterialVertical=null),null!==this.vsmShadowMapHorizontal&&(this.vsmShadowMapHorizontal.dispose(),this.vsmShadowMapHorizontal=null,this.vsmMaterialHorizontal.dispose(),this.vsmMaterialHorizontal=null),super.dispose()}updateBefore(e){const{shadow:t}=this;let n=t.needsUpdate||t.autoUpdate;n&&(this._cameraFrameId[e.camera]===e.frameId&&(n=!1),this._cameraFrameId[e.camera]=e.frameId),n&&(this.updateShadow(e),this.shadowMap.depthTexture.version===this._depthVersionCached&&(t.needsUpdate=!1))}}const QB=(e,t)=>cA(new WB(e,t)),ZB=new ya,YB=xA((([e,t])=>{const n=e.toVar(),i=Ly(n),r=Ux(1,Jy(i.x,Jy(i.y,i.z)));i.mulAssign(r),n.mulAssign(r.mul(t.mul(2).oneMinus()));const s=NA(n.xy).toVar(),o=t.mul(1.5).oneMinus();return wA(i.z.greaterThanEqual(o),(()=>{wA(n.z.greaterThan(0),(()=>{s.x.assign(Fx(4,n.x))}))})).ElseIf(i.x.greaterThanEqual(o),(()=>{const e=jy(n.x);s.x.assign(n.z.mul(e).add(e.mul(2)))})).ElseIf(i.y.greaterThanEqual(o),(()=>{const e=jy(n.y);s.x.assign(n.x.add(e.mul(2)).add(2)),s.y.assign(n.z.mul(e).sub(2))})),NA(.125,.25).mul(s).add(NA(.375,.75)).flipY()})).setLayout({name:"cubeToUV",type:"vec2",inputs:[{name:"pos",type:"vec3"},{name:"texelSizeY",type:"float"}]}),JB=xA((({depthTexture:e,bd3D:t,dp:n,texelSize:i})=>Pw(e,YB(t,i.y)).compare(n))),KB=xA((({depthTexture:e,bd3D:t,dp:n,texelSize:i,shadow:r})=>{const s=GC("radius","float",r).setGroup(Tx),o=NA(-1,1).mul(s).mul(i.y);return Pw(e,YB(t.add(o.xyy),i.y)).compare(n).add(Pw(e,YB(t.add(o.yyy),i.y)).compare(n)).add(Pw(e,YB(t.add(o.xyx),i.y)).compare(n)).add(Pw(e,YB(t.add(o.yyx),i.y)).compare(n)).add(Pw(e,YB(t,i.y)).compare(n)).add(Pw(e,YB(t.add(o.xxy),i.y)).compare(n)).add(Pw(e,YB(t.add(o.yxy),i.y)).compare(n)).add(Pw(e,YB(t.add(o.xxx),i.y)).compare(n)).add(Pw(e,YB(t.add(o.yxx),i.y)).compare(n)).mul(1/9)})),qB=xA((({filterFn:e,depthTexture:t,shadowCoord:n,shadow:i})=>{const r=n.xyz.toVar(),s=r.length(),o=Nx("float").setGroup(Tx).onRenderUpdate((()=>i.camera.near)),a=Nx("float").setGroup(Tx).onRenderUpdate((()=>i.camera.far)),l=GC("bias","float",i).setGroup(Tx),u=Nx(i.mapSize).setGroup(Tx),c=EA(1).toVar();return wA(s.sub(a).lessThanEqual(0).and(s.sub(o).greaterThanEqual(0)),(()=>{const n=s.sub(o).div(a.sub(o)).toVar();n.addAssign(l);const d=r.normalize(),h=NA(1).div(u.mul(NA(4,2)));c.assign(e({depthTexture:t,bd3D:d,dp:n,texelSize:h,shadow:i}))})),c})),_B=new Js,$B=new Cs,eD=new Cs;class tD extends WB{static get type(){return"PointShadowNode"}constructor(e,t=null){super(e,t)}getShadowFilterFn(e){return 0===e?JB:KB}setupShadowCoord(e,t){return t}setupShadowFilter(e,{filterFn:t,shadowTexture:n,depthTexture:i,shadowCoord:r,shadow:s}){return qB({filterFn:t,shadowTexture:n,depthTexture:i,shadowCoord:r,shadow:s})}renderShadow(e){const{shadow:t,shadowMap:n,light:i}=this,{renderer:r,scene:s}=e,o=t.getFrameExtents();eD.copy(t.mapSize),eD.multiply(o),n.setSize(eD.width,eD.height),$B.copy(t.mapSize);const a=r.autoClear,l=r.getClearColor(ZB),u=r.getClearAlpha();r.autoClear=!1,r.setClearColor(t.clearColor,t.clearAlpha),r.clear();const c=t.getViewportCount();for(let e=0;e<c;e++){const o=t.getViewport(e),a=$B.x*o.x,l=eD.y-$B.y-$B.y*o.y;_B.set(a,l,$B.x*o.z,$B.y*o.w),n.viewport.copy(_B),t.updateMatrices(i,e),r.render(s,t.camera)}r.autoClear=a,r.setClearColor(l,u)}}const nD=(e,t)=>cA(new tD(e,t));class iD extends TE{static get type(){return"AnalyticLightNode"}constructor(e=null){super(),this.light=e,this.color=new ya,this.colorNode=e&&e.colorNode||Nx(this.color).setGroup(Tx),this.baseColorNode=null,this.shadowNode=null,this.shadowColorNode=null,this.isAnalyticLightNode=!0,this.updateType=hv.FRAME}getHash(){return this.light.uuid}getLightVector(e){return pB(this.light).sub(e.context.positionView||hC)}setupDirect(){}setupDirectRectArea(){}setupShadowNode(){return QB(this.light)}setupShadow(e){const{renderer:t}=e;if(!1===t.shadowMap.enabled)return;let n=this.shadowColorNode;if(null===n){const e=this.light.shadow.shadowNode;let t;t=void 0!==e?cA(e):this.setupShadowNode(),this.shadowNode=t,this.shadowColorNode=n=this.colorNode.mul(t),this.baseColorNode=this.colorNode}this.colorNode=n}setup(e){this.colorNode=this.baseColorNode||this.colorNode,this.light.castShadow?e.object.receiveShadow&&this.setupShadow(e):null!==this.shadowNode&&(this.shadowNode.dispose(),this.shadowNode=null,this.shadowColorNode=null);const t=this.setupDirect(e),n=this.setupDirectRectArea(e);t&&e.lightsNode.setupDirectLight(e,this,t),n&&e.lightsNode.setupDirectRectAreaLight(e,this,n)}update(){const{light:e}=this;this.color.copy(e.color).multiplyScalar(e.intensity)}}const rD=xA((({lightDistance:e,cutoffDistance:t,decayExponent:n})=>{const i=e.pow(n).max(.01).reciprocal();return t.greaterThan(0).select(i.mul(e.div(t).pow4().oneMinus().clamp().pow2()),i)})),sD=({color:e,lightVector:t,cutoffDistance:n,decayExponent:i})=>{const r=t.normalize(),s=t.length(),o=rD({lightDistance:s,cutoffDistance:n,decayExponent:i});return{lightDirection:r,lightColor:e.mul(o)}};class oD extends iD{static get type(){return"PointLightNode"}constructor(e=null){super(e),this.cutoffDistanceNode=Nx(0).setGroup(Tx),this.decayExponentNode=Nx(2).setGroup(Tx)}update(e){const{light:t}=this;super.update(e),this.cutoffDistanceNode.value=t.distance,this.decayExponentNode.value=t.decay}setupShadowNode(){return nD(this.light)}setupDirect(e){return sD({color:this.colorNode,lightVector:this.getLightVector(e),cutoffDistance:this.cutoffDistanceNode,decayExponent:this.decayExponentNode})}}xA((([e=yw()],{renderer:t,material:n})=>{const i=lb(e.mul(2).sub(1));let r;if(n.alphaToCoverage&&t.samples>1){const e=EA(i.fwidth()).toVar();r=fb(e.oneMinus(),e.add(1),i).oneMinus()}else r=bb(i.greaterThan(1),0,1);return r}));const aD=xA((([e,t])=>{const n=e.x,i=e.y,r=e.z;let s=t.element(0).mul(.886227);return s=s.add(t.element(1).mul(1.023328).mul(i)),s=s.add(t.element(2).mul(1.023328).mul(r)),s=s.add(t.element(3).mul(1.023328).mul(n)),s=s.add(t.element(4).mul(.858086).mul(n).mul(i)),s=s.add(t.element(5).mul(.858086).mul(i).mul(r)),s=s.add(t.element(6).mul(r.mul(r).mul(.743125).sub(.247708))),s=s.add(t.element(7).mul(.858086).mul(n).mul(r)),s=s.add(t.element(8).mul(.429043).mul(Hx(n,n).sub(Hx(i,i)))),s}));const lD=new yN;class uD extends UP{constructor(e,t){super(),this.renderer=e,this.nodes=t}update(e,t,n){const i=this.renderer,r=this.nodes.getBackgroundNode(e)||e.background;let s=!1;if(null===r)i._clearColor.getRGB(lD),lD.a=i._clearColor.a;else if(!0===r.isColor)r.getRGB(lD),lD.a=1,s=!0;else if(!0===r.isNode){const a=this.get(e),l=r;lD.copy(i._clearColor);let u=a.backgroundMesh;if(void 0===u){const d=Cb(RA(l).mul(jN),{getUV:()=>ON.mul(wC),getTextureLevel:()=>LN});let h=sE;h=h.setZ(h.w);const f=new _E;function p(){r.removeEventListener("dispose",p),u.material.dispose(),u.geometry.dispose()}f.name="Background.material",f.side=1,f.depthTest=!1,f.depthWrite=!1,f.allowOverride=!1,f.fog=!1,f.lights=!1,f.vertexNode=h,f.colorNode=d,a.backgroundMeshNode=d,a.backgroundMesh=u=new nl(new yu(1,32,32),f),u.frustumCulled=!1,u.name="Background.mesh",u.onBeforeRender=function(e,t,n){this.matrixWorld.copyPosition(n.matrixWorld)},r.addEventListener("dispose",p)}const c=l.getCacheKey();a.backgroundCacheKey!==c&&(a.backgroundMeshNode.node=RA(l).mul(jN),a.backgroundMeshNode.needsUpdate=!0,u.material.needsUpdate=!0,a.backgroundCacheKey=c),t.unshift(u,u.geometry,u.material,0,0,null,null)}else console.error("THREE.Renderer: Unsupported background configuration.",r);const o=i.xr.getEnvironmentBlendMode();if("additive"===o?lD.set(0,0,0,1):"alpha-blend"===o&&lD.set(0,0,0,0),!0===i.autoClear||!0===s){const g=n.clearColorValue;g.r=lD.r,g.g=lD.g,g.b=lD.b,g.a=lD.a,!0!==i.backend.isWebGLBackend&&!0!==i.alpha||(g.r*=g.a,g.g*=g.a,g.b*=g.a),n.depthClearValue=i._clearDepth,n.stencilClearValue=i._clearStencil,n.clearColor=!0===i.autoClearColor,n.clearDepth=!0===i.autoClearDepth,n.clearStencil=!0===i.autoClearStencil}else n.clearColor=!1,n.clearDepth=!1,n.clearStencil=!1}}let cD=0;class dD{constructor(e="",t=[],n=0,i=[]){this.name=e,this.bindings=t,this.index=n,this.bindingsReference=i,this.id=cD++}}class hD{constructor(e,t,n,i,r,s,o,a,l,u=[]){this.vertexShader=e,this.fragmentShader=t,this.computeShader=n,this.transforms=u,this.nodeAttributes=i,this.bindings=r,this.updateNodes=s,this.updateBeforeNodes=o,this.updateAfterNodes=a,this.observer=l,this.usedTimes=0}createBindings(){const e=[];for(const t of this.bindings){if(!0!==t.bindings[0].groupNode.shared){const n=new dD(t.name,[],t.index,t.bindingsReference);e.push(n);for(const e of t.bindings)n.bindings.push(e.clone())}else e.push(t)}return e}}class fD{constructor(e,t,n=null){this.isNodeAttribute=!0,this.name=e,this.type=t,this.node=n}}class pD{constructor(e,t,n){this.isNodeUniform=!0,this.name=e,this.type=t,this.node=n}get value(){return this.node.value}set value(e){this.node.value=e}get id(){return this.node.id}get groupNode(){return this.node.groupNode}}class gD{constructor(e,t,n=!1,i=null){this.isNodeVar=!0,this.name=e,this.type=t,this.readOnly=n,this.count=i}}class mD extends gD{constructor(e,t,n=null,i=null){super(e,t),this.needsInterpolation=!1,this.isNodeVarying=!0,this.interpolationType=n,this.interpolationSampling=i}}class vD{constructor(e,t,n=""){this.name=e,this.type=t,this.code=n,Object.defineProperty(this,"isNodeCode",{value:!0})}}let AD=0;class xD{constructor(e=null){this.id=AD++,this.nodesData=new WeakMap,this.parent=e}getData(e){let t=this.nodesData.get(e);return void 0===t&&null!==this.parent&&(t=this.parent.getData(e)),t}setData(e,t){this.nodesData.set(e,t)}}class yD{constructor(e,t){this.name=e,this.members=t,this.output=!1}}class bD{constructor(e,t){this.name=e,this.value=t,this.boundary=0,this.itemSize=0,this.offset=0}setValue(e){this.value=e}getValue(){return this.value}}class wD extends bD{constructor(e,t=0){super(e,t),this.isNumberUniform=!0,this.boundary=4,this.itemSize=1}}class CD extends bD{constructor(e,t=new Cs){super(e,t),this.isVector2Uniform=!0,this.boundary=8,this.itemSize=2}}class MD extends bD{constructor(e,t=new Es){super(e,t),this.isVector3Uniform=!0,this.boundary=16,this.itemSize=3}}class ED extends bD{constructor(e,t=new Js){super(e,t),this.isVector4Uniform=!0,this.boundary=16,this.itemSize=4}}class TD extends bD{constructor(e,t=new ya){super(e,t),this.isColorUniform=!0,this.boundary=16,this.itemSize=3}}class SD extends bD{constructor(e,t=new jc){super(e,t),this.isMatrix2Uniform=!0,this.boundary=8,this.itemSize=4}}class PD extends bD{constructor(e,t=new Ps){super(e,t),this.isMatrix3Uniform=!0,this.boundary=48,this.itemSize=12}}class ND extends bD{constructor(e,t=new Po){super(e,t),this.isMatrix4Uniform=!0,this.boundary=64,this.itemSize=16}}class BD extends wD{constructor(e){super(e.name,e.value),this.nodeUniform=e}getValue(){return this.nodeUniform.value}getType(){return this.nodeUniform.type}}class DD extends CD{constructor(e){super(e.name,e.value),this.nodeUniform=e}getValue(){return this.nodeUniform.value}getType(){return this.nodeUniform.type}}class ID extends MD{constructor(e){super(e.name,e.value),this.nodeUniform=e}getValue(){return this.nodeUniform.value}getType(){return this.nodeUniform.type}}class LD extends ED{constructor(e){super(e.name,e.value),this.nodeUniform=e}getValue(){return this.nodeUniform.value}getType(){return this.nodeUniform.type}}class jD extends TD{constructor(e){super(e.name,e.value),this.nodeUniform=e}getValue(){return this.nodeUniform.value}getType(){return this.nodeUniform.type}}class OD extends SD{constructor(e){super(e.name,e.value),this.nodeUniform=e}getValue(){return this.nodeUniform.value}getType(){return this.nodeUniform.type}}class zD extends PD{constructor(e){super(e.name,e.value),this.nodeUniform=e}getValue(){return this.nodeUniform.value}getType(){return this.nodeUniform.type}}class RD extends ND{constructor(e){super(e.name,e.value),this.nodeUniform=e}getValue(){return this.nodeUniform.value}getType(){return this.nodeUniform.type}}const kD=new WeakMap,FD=new Map([[Int8Array,"int"],[Int16Array,"int"],[Int32Array,"int"],[Uint8Array,"uint"],[Uint16Array,"uint"],[Uint32Array,"uint"],[Float32Array,"float"]]),HD=e=>/e/g.test(e)?String(e).replace(/\+/g,""):(e=Number(e))+(e%1?"":".0");class UD{constructor(e,t,n){this.object=e,this.material=e&&e.material||null,this.geometry=e&&e.geometry||null,this.renderer=t,this.parser=n,this.scene=null,this.camera=null,this.nodes=[],this.sequentialNodes=[],this.updateNodes=[],this.updateBeforeNodes=[],this.updateAfterNodes=[],this.hashNodes={},this.observer=null,this.lightsNode=null,this.environmentNode=null,this.fogNode=null,this.clippingContext=null,this.vertexShader=null,this.fragmentShader=null,this.computeShader=null,this.flowNodes={vertex:[],fragment:[],compute:[]},this.flowCode={vertex:"",fragment:"",compute:""},this.uniforms={vertex:[],fragment:[],compute:[],index:0},this.structs={vertex:[],fragment:[],compute:[],index:0},this.types={vertex:[],fragment:[],compute:[],index:0},this.bindings={vertex:{},fragment:{},compute:{}},this.bindingsIndexes={},this.bindGroups=null,this.attributes=[],this.bufferAttributes=[],this.varyings=[],this.codes={},this.vars={},this.declarations={},this.flow={code:""},this.chaining=[],this.stack=CN(),this.stacks=[],this.tab="\t",this.currentFunctionNode=null,this.context={material:this.material},this.cache=new xD,this.globalCache=this.cache,this.flowsData=new WeakMap,this.shaderStage=null,this.buildStage=null,this.subBuildLayers=[],this.currentStack=null,this.subBuildFn=null}getBindGroupsCache(){let e=kD.get(this.renderer);return void 0===e&&(e=new zP,kD.set(this.renderer,e)),e}createRenderTarget(e,t,n){return new Ks(e,t,n)}createCubeRenderTarget(e,t){return new aT(e,t)}includes(e){return this.nodes.includes(e)}getOutputStructName(){}_getBindGroup(e,t){const n=this.getBindGroupsCache(),i=[];let r,s=!0;for(const e of t)i.push(e),s=s&&!0!==e.groupNode.shared;return s?(r=n.get(i),void 0===r&&(r=new dD(e,i,this.bindingsIndexes[e].group,i),n.set(i,r))):r=new dD(e,i,this.bindingsIndexes[e].group,i),r}getBindGroupArray(e,t){const n=this.bindings[t];let i=n[e];return void 0===i&&(void 0===this.bindingsIndexes[e]&&(this.bindingsIndexes[e]={binding:0,group:Object.keys(this.bindingsIndexes).length}),n[e]=i=[]),i}getBindings(){let e=this.bindGroups;if(null===e){const t={},n=this.bindings;for(const e of mv)for(const i in n[e]){const r=n[e][i];(t[i]||(t[i]=[])).push(...r)}e=[];for(const n in t){const i=t[n],r=this._getBindGroup(n,i);e.push(r)}this.bindGroups=e}return e}sortBindingGroups(){const e=this.getBindings();e.sort(((e,t)=>e.bindings[0].groupNode.order-t.bindings[0].groupNode.order));for(let t=0;t<e.length;t++){const n=e[t];this.bindingsIndexes[n.name].group=t,n.index=t}}setHashNode(e,t){this.hashNodes[t]=e}addNode(e){!1===this.nodes.includes(e)&&(this.nodes.push(e),this.setHashNode(e,e.getHash(this)))}addSequentialNode(e){!1===this.sequentialNodes.includes(e)&&this.sequentialNodes.push(e)}buildUpdateNodes(){for(const e of this.nodes){e.getUpdateType()!==hv.NONE&&this.updateNodes.push(e)}for(const e of this.sequentialNodes){const t=e.getUpdateBeforeType(),n=e.getUpdateAfterType();t!==hv.NONE&&this.updateBeforeNodes.push(e),n!==hv.NONE&&this.updateAfterNodes.push(e)}}get currentNode(){return this.chaining[this.chaining.length-1]}isFilteredTexture(e){return e.magFilter===Hi||e.magFilter===Ui||e.magFilter===Fi||e.magFilter===Xi||e.minFilter===Hi||e.minFilter===Ui||e.minFilter===Fi||e.minFilter===Xi}addChain(e){this.chaining.push(e)}removeChain(e){if(this.chaining.pop()!==e)throw new Error("NodeBuilder: Invalid node chaining!")}getMethod(e){return e}getTernary(){return null}getNodeFromHash(e){return this.hashNodes[e]}addFlow(e,t){return this.flowNodes[e].push(t),t}setContext(e){this.context=e}getContext(){return this.context}getSharedContext(){return this.context,this.context}setCache(e){this.cache=e}getCache(){return this.cache}getCacheFromNode(e,t=!0){const n=this.getDataFromNode(e);return void 0===n.cache&&(n.cache=new xD(t?this.getCache():null)),n.cache}isAvailable(){return!1}getVertexIndex(){console.warn("Abstract function.")}getInstanceIndex(){console.warn("Abstract function.")}getDrawIndex(){console.warn("Abstract function.")}getFrontFacing(){console.warn("Abstract function.")}getFragCoord(){console.warn("Abstract 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t>=0?`${Math.round(t)}u`:"0u";if("bool"===e)return t?"true":"false";if("color"===e)return`${this.getType("vec3")}( ${HD(t.r)}, ${HD(t.g)}, ${HD(t.b)} )`;const n=this.getTypeLength(e),i=this.getComponentType(e),r=e=>this.generateConst(i,e);if(2===n)return`${this.getType(e)}( ${r(t.x)}, ${r(t.y)} )`;if(3===n)return`${this.getType(e)}( ${r(t.x)}, ${r(t.y)}, ${r(t.z)} )`;if(4===n&&"mat2"!==e)return`${this.getType(e)}( ${r(t.x)}, ${r(t.y)}, ${r(t.z)}, ${r(t.w)} )`;if(n>=4&&t&&(t.isMatrix2||t.isMatrix3||t.isMatrix4))return`${this.getType(e)}( ${t.elements.map(r).join(", ")} )`;if(n>4)return`${this.getType(e)}()`;throw new Error(`NodeBuilder: Type '${e}' not found in generate constant attempt.`)}getType(e){return"color"===e?"vec3":e}hasGeometryAttribute(e){return this.geometry&&void 0!==this.geometry.getAttribute(e)}getAttribute(e,t){const n=this.attributes;for(const t of n)if(t.name===e)return t;const i=new fD(e,t);return this.registerDeclaration(i),n.push(i),i}getPropertyName(e){return e.name}isVector(e){return/vec\d/.test(e)}isMatrix(e){return/mat\d/.test(e)}isReference(e){return"void"===e||"property"===e||"sampler"===e||"samplerComparison"===e||"texture"===e||"cubeTexture"===e||"storageTexture"===e||"depthTexture"===e||"texture3D"===e}needsToWorkingColorSpace(){return!1}getComponentTypeFromTexture(e){const t=e.type;if(e.isDataTexture){if(t===Zi)return"int";if(t===Yi)return"uint"}return"float"}getElementType(e){return"mat2"===e?"vec2":"mat3"===e?"vec3":"mat4"===e?"vec4":this.getComponentType(e)}getComponentType(e){if("float"===(e=this.getVectorType(e))||"bool"===e||"int"===e||"uint"===e)return e;const t=/(b|i|u|)(vec|mat)([2-4])/.exec(e);return null===t?null:"b"===t[1]?"bool":"i"===t[1]?"int":"u"===t[1]?"uint":"float"}getVectorType(e){return"color"===e?"vec3":"texture"===e||"cubeTexture"===e||"storageTexture"===e||"texture3D"===e?"vec4":e}getTypeFromLength(e,t="float"){if(1===e)return t;let n=sv(e);const i="float"===t?"":t[0];return!0===/mat2/.test(t)&&(n=n.replace("vec","mat")),i+n}getTypeFromArray(e){return FD.get(e.constructor)}isInteger(e){return/int|uint|(i|u)vec/.test(e)}getTypeFromAttribute(e){let t=e;e.isInterleavedBufferAttribute&&(t=e.data);const n=t.array,i=e.itemSize,r=e.normalized;let s;return e instanceof Oa||!0===r||(s=this.getTypeFromArray(n)),this.getTypeFromLength(i,s)}getTypeLength(e){const t=this.getVectorType(e),n=/vec([2-4])/.exec(t);return null!==n?Number(n[1]):"float"===t||"bool"===t||"int"===t||"uint"===t?1:!0===/mat2/.test(e)?4:!0===/mat3/.test(e)?9:!0===/mat4/.test(e)?16:0}getVectorFromMatrix(e){return e.replace("mat","vec")}changeComponentType(e,t){return this.getTypeFromLength(this.getTypeLength(e),t)}getIntegerType(e){const t=this.getComponentType(e);return"int"===t||"uint"===t?e:this.changeComponentType(e,"int")}addStack(){this.stack=CN(this.stack);const e=bA();return this.stacks.push(e),yA(this.stack),this.stack}removeStack(){const e=this.stack;return this.stack=e.parent,yA(this.stacks.pop()),e}getDataFromNode(e,t=this.shaderStage,n=null){let i=(n=null===n?e.isGlobal(this)?this.globalCache:this.cache:n).getData(e);void 0===i&&(i={},n.setData(e,i)),void 0===i[t]&&(i[t]={});let r=i[t];const s=i.any?i.any.subBuilds:null,o=this.getClosestSubBuild(s);return o&&(void 0===r.subBuildsCache&&(r.subBuildsCache={}),r=r.subBuildsCache[o]||(r.subBuildsCache[o]={}),r.subBuilds=s),r}getNodeProperties(e,t="any"){const n=this.getDataFromNode(e,t);return n.properties||(n.properties={outputNode:null})}getBufferAttributeFromNode(e,t){const n=this.getDataFromNode(e);let i=n.bufferAttribute;if(void 0===i){const r=this.uniforms.index++;i=new fD("nodeAttribute"+r,t,e),this.bufferAttributes.push(i),n.bufferAttribute=i}return i}getStructTypeNode(e,t=this.shaderStage){return this.types[t][e]||null}getStructTypeFromNode(e,t,n=null,i=this.shaderStage){const r=this.getDataFromNode(e,i,this.globalCache);let s=r.structType;if(void 0===s){const o=this.structs.index++;null===n&&(n="StructType"+o),s=new yD(n,t),this.structs[i].push(s),this.types[i][n]=e,r.structType=s}return s}getOutputStructTypeFromNode(e,t){const n=this.getStructTypeFromNode(e,t,"OutputType","fragment");return n.output=!0,n}getUniformFromNode(e,t,n=this.shaderStage,i=null){const r=this.getDataFromNode(e,n,this.globalCache);let s=r.uniform;if(void 0===s){const o=this.uniforms.index++;s=new pD(i||"nodeUniform"+o,t,e),this.uniforms[n].push(s),this.registerDeclaration(s),r.uniform=s}return s}getVarFromNode(e,t=null,n=e.getNodeType(this),i=this.shaderStage,r=!1){const s=this.getDataFromNode(e,i),o=this.getSubBuildProperty("variable",s.subBuilds);let a=s[o];if(void 0===a){const l=r?"_const":"_var",u=this.vars[i]||(this.vars[i]=[]),c=this.vars[l]||(this.vars[l]=0);null===t&&(t=(r?"nodeConst":"nodeVar")+c,this.vars[l]++),"variable"!==o&&(t=this.getSubBuildProperty(t,s.subBuilds));const d=e.getArrayCount(this);a=new gD(t,n,r,d),r||u.push(a),this.registerDeclaration(a),s[o]=a}return a}isDeterministic(e){if(e.isMathNode)return this.isDeterministic(e.aNode)&&(!e.bNode||this.isDeterministic(e.bNode))&&(!e.cNode||this.isDeterministic(e.cNode));if(e.isOperatorNode)return this.isDeterministic(e.aNode)&&(!e.bNode||this.isDeterministic(e.bNode));if(e.isArrayNode){if(null!==e.values)for(const t of e.values)if(!this.isDeterministic(t))return!1;return!0}return!!e.isConstNode}getVaryingFromNode(e,t=null,n=e.getNodeType(this),i=null,r=null){const s=this.getDataFromNode(e,"any"),o=this.getSubBuildProperty("varying",s.subBuilds);let a=s[o];if(void 0===a){const e=this.varyings,l=e.length;null===t&&(t="nodeVarying"+l),"varying"!==o&&(t=this.getSubBuildProperty(t,s.subBuilds)),a=new mD(t,n,i,r),e.push(a),this.registerDeclaration(a),s[o]=a}return a}registerDeclaration(e){const t=this.shaderStage,n=this.declarations[t]||(this.declarations[t]={}),i=this.getPropertyName(e);let r=1,s=i;for(;void 0!==n[s];)s=i+"_"+r++;r>1&&(e.name=s,console.warn(`THREE.TSL: Declaration name '${i}' of '${e.type}' already in use. Renamed to '${s}'.`)),n[s]=e}getCodeFromNode(e,t,n=this.shaderStage){const i=this.getDataFromNode(e);let r=i.code;if(void 0===r){const e=this.codes[n]||(this.codes[n]=[]),s=e.length;r=new vD("nodeCode"+s,t),e.push(r),i.code=r}return r}addFlowCodeHierarchy(e,t){const{flowCodes:n,flowCodeBlock:i}=this.getDataFromNode(e);let r=!0,s=t;for(;s;){if(!0===i.get(s)){r=!1;break}s=this.getDataFromNode(s).parentNodeBlock}if(r)for(const e of n)this.addLineFlowCode(e)}addLineFlowCodeBlock(e,t,n){const i=this.getDataFromNode(e),r=i.flowCodes||(i.flowCodes=[]),s=i.flowCodeBlock||(i.flowCodeBlock=new WeakMap);r.push(t),s.set(n,!0)}addLineFlowCode(e,t=null){return""===e||(null!==t&&this.context.nodeBlock&&this.addLineFlowCodeBlock(t,e,this.context.nodeBlock),e=this.tab+e,/;\s*$/.test(e)||(e+=";\n"),this.flow.code+=e),this}addFlowCode(e){return this.flow.code+=e,this}addFlowTab(){return this.tab+="\t",this}removeFlowTab(){return this.tab=this.tab.slice(0,-1),this}getFlowData(e){return this.flowsData.get(e)}flowNode(e){const t=e.getNodeType(this),n=this.flowChildNode(e,t);return this.flowsData.set(e,n),n}addInclude(e){null!==this.currentFunctionNode&&this.currentFunctionNode.includes.push(e)}buildFunctionNode(e){const t=new eB,n=this.currentFunctionNode;return this.currentFunctionNode=t,t.code=this.buildFunctionCode(e),this.currentFunctionNode=n,t}flowShaderNode(e){const t=e.layout,n={[Symbol.iterator](){let e=0;const t=Object.values(this);return{next:()=>({value:t[e],done:e++>=t.length})}}};for(const e of t.inputs)n[e.name]=new bN(e.type,e.name);e.layout=null;const i=e.call(n),r=this.flowStagesNode(i,t.type);return e.layout=t,r}flowBuildStage(e,t,n=null){const i=this.getBuildStage();this.setBuildStage(t);const r=e.build(this,n);return this.setBuildStage(i),r}flowStagesNode(e,t=null){const n=this.flow,i=this.vars,r=this.declarations,s=this.cache,o=this.buildStage,a=this.stack,l={code:""};this.flow=l,this.vars={},this.declarations={},this.cache=new xD,this.stack=CN();for(const n of gv)this.setBuildStage(n),l.result=e.build(this,t);return l.vars=this.getVars(this.shaderStage),this.flow=n,this.vars=i,this.declarations=r,this.cache=s,this.stack=a,this.setBuildStage(o),l}getFunctionOperator(){return null}buildFunctionCode(){console.warn("Abstract function.")}flowChildNode(e,t=null){const n=this.flow,i={code:""};return this.flow=i,i.result=e.build(this,t),this.flow=n,i}flowNodeFromShaderStage(e,t,n=null,i=null){const r=this.tab,s=this.cache,o=this.shaderStage,a=this.context;this.setShaderStage(e);const l={...this.context};delete l.nodeBlock,this.cache=this.globalCache,this.tab="\t",this.context=l;let u=null;if("generate"===this.buildStage){const r=this.flowChildNode(t,n);null!==i&&(r.code+=`${this.tab+i} = ${r.result};\n`),this.flowCode[e]=this.flowCode[e]+r.code,u=r}else u=t.build(this);return this.setShaderStage(o),this.cache=s,this.tab=r,this.context=a,u}getAttributesArray(){return this.attributes.concat(this.bufferAttributes)}getAttributes(){console.warn("Abstract function.")}getVaryings(){console.warn("Abstract function.")}getVar(e,t,n=null){return`${null!==n?this.generateArrayDeclaration(e,n):this.getType(e)} ${t}`}getVars(e){let t="";const n=this.vars[e];if(void 0!==n)for(const e of n)t+=`${this.getVar(e.type,e.name)}; `;return t}getUniforms(){console.warn("Abstract function.")}getCodes(e){const t=this.codes[e];let n="";if(void 0!==t)for(const e of t)n+=e.code+"\n";return n}getHash(){return this.vertexShader+this.fragmentShader+this.computeShader}setShaderStage(e){this.shaderStage=e}getShaderStage(){return this.shaderStage}setBuildStage(e){this.buildStage=e}getBuildStage(){return this.buildStage}buildCode(){console.warn("Abstract function.")}get subBuild(){return this.subBuildLayers[this.subBuildLayers.length-1]||null}addSubBuild(e){this.subBuildLayers.push(e)}removeSubBuild(){return this.subBuildLayers.pop()}getClosestSubBuild(e){let t;if(t=e&&e.isNode?e.isShaderCallNodeInternal?e.shaderNode.subBuilds:e.isStackNode?[e.subBuild]:this.getDataFromNode(e,"any").subBuilds:e instanceof Set?[...e]:e,!t)return null;const n=this.subBuildLayers;for(let e=t.length-1;e>=0;e--){const i=t[e];if(n.includes(i))return i}return null}getSubBuildOutput(e){return this.getSubBuildProperty("outputNode",e)}getSubBuildProperty(e="",t=null){let n,i;return n=null!==t?this.getClosestSubBuild(t):this.subBuildFn,i=n?e?n+"_"+e:n:e,i}build(){const{object:e,material:t,renderer:n}=this;if(null!==t){let e=n.library.fromMaterial(t);null===e&&(console.error(`NodeMaterial: Material "${t.type}" is not compatible.`),e=new _E),e.build(this)}else this.addFlow("compute",e);for(const e of gv){this.setBuildStage(e),this.context.vertex&&this.context.vertex.isNode&&this.flowNodeFromShaderStage("vertex",this.context.vertex);for(const t of mv){this.setShaderStage(t);const n=this.flowNodes[t];for(const t of n)"generate"===e?this.flowNode(t):t.build(this)}}return this.setBuildStage(null),this.setShaderStage(null),this.buildCode(),this.buildUpdateNodes(),this}getNodeUniform(e,t){if("float"===t||"int"===t||"uint"===t)return new BD(e);if("vec2"===t||"ivec2"===t||"uvec2"===t)return new DD(e);if("vec3"===t||"ivec3"===t||"uvec3"===t)return new ID(e);if("vec4"===t||"ivec4"===t||"uvec4"===t)return new LD(e);if("color"===t)return new jD(e);if("mat2"===t)return new OD(e);if("mat3"===t)return new zD(e);if("mat4"===t)return new RD(e);throw new Error(`Uniform "${t}" not declared.`)}format(e,t,n){if((t=this.getVectorType(t))===(n=this.getVectorType(n))||null===n||this.isReference(n))return e;const i=this.getTypeLength(t),r=this.getTypeLength(n);return 16===i&&9===r?`${this.getType(n)}( ${e}[ 0 ].xyz, ${e}[ 1 ].xyz, ${e}[ 2 ].xyz )`:9===i&&4===r?`${this.getType(n)}( ${e}[ 0 ].xy, ${e}[ 1 ].xy )`:i>4||r>4||0===r?e:i===r?`${this.getType(n)}( ${e} )`:i>r?(e="bool"===n?`all( ${e} )`:`${e}.${"xyz".slice(0,r)}`,this.format(e,this.getTypeFromLength(r,this.getComponentType(t)),n)):4===r&&i>1?`${this.getType(n)}( ${this.format(e,t,"vec3")}, 1.0 )`:2===i?`${this.getType(n)}( ${this.format(e,t,"vec2")}, 0.0 )`:(1===i&&r>1&&t!==this.getComponentType(n)&&(e=`${this.getType(this.getComponentType(n))}( ${e} )`),`${this.getType(n)}( ${e} )`)}getSignature(){return`// Three.js r${mi} - Node System\n`}}class XD{constructor(){this.time=0,this.deltaTime=0,this.frameId=0,this.renderId=0,this.updateMap=new WeakMap,this.updateBeforeMap=new WeakMap,this.updateAfterMap=new WeakMap,this.renderer=null,this.material=null,this.camera=null,this.object=null,this.scene=null}_getMaps(e,t){let n=e.get(t);return void 0===n&&(n={renderMap:new WeakMap,frameMap:new WeakMap},e.set(t,n)),n}updateBeforeNode(e){const t=e.getUpdateBeforeType(),n=e.updateReference(this);if(t===hv.FRAME){const{frameMap:t}=this._getMaps(this.updateBeforeMap,n);t.get(n)!==this.frameId&&!1!==e.updateBefore(this)&&t.set(n,this.frameId)}else if(t===hv.RENDER){const{renderMap:t}=this._getMaps(this.updateBeforeMap,n);t.get(n)!==this.renderId&&!1!==e.updateBefore(this)&&t.set(n,this.renderId)}else t===hv.OBJECT&&e.updateBefore(this)}updateAfterNode(e){const t=e.getUpdateAfterType(),n=e.updateReference(this);if(t===hv.FRAME){const{frameMap:t}=this._getMaps(this.updateAfterMap,n);t.get(n)!==this.frameId&&!1!==e.updateAfter(this)&&t.set(n,this.frameId)}else if(t===hv.RENDER){const{renderMap:t}=this._getMaps(this.updateAfterMap,n);t.get(n)!==this.renderId&&!1!==e.updateAfter(this)&&t.set(n,this.renderId)}else t===hv.OBJECT&&e.updateAfter(this)}updateNode(e){const t=e.getUpdateType(),n=e.updateReference(this);if(t===hv.FRAME){const{frameMap:t}=this._getMaps(this.updateMap,n);t.get(n)!==this.frameId&&!1!==e.update(this)&&t.set(n,this.frameId)}else if(t===hv.RENDER){const{renderMap:t}=this._getMaps(this.updateMap,n);t.get(n)!==this.renderId&&!1!==e.update(this)&&t.set(n,this.renderId)}else t===hv.OBJECT&&e.update(this)}update(){this.frameId++,void 0===this.lastTime&&(this.lastTime=performance.now()),this.deltaTime=(performance.now()-this.lastTime)/1e3,this.lastTime=performance.now(),this.time+=this.deltaTime}}class GD{constructor(e,t,n=null,i="",r=!1){this.type=e,this.name=t,this.count=n,this.qualifier=i,this.isConst=r}}GD.isNodeFunctionInput=!0;class VD extends iD{static get type(){return"DirectionalLightNode"}constructor(e=null){super(e)}setupDirect(){const e=this.colorNode;return{lightDirection:gB(this.light),lightColor:e}}}const WD=new Po,QD=new Po;let ZD=null;class YD extends iD{static get type(){return"RectAreaLightNode"}constructor(e=null){super(e),this.halfHeight=Nx(new Es).setGroup(Tx),this.halfWidth=Nx(new Es).setGroup(Tx),this.updateType=hv.RENDER}update(e){super.update(e);const{light:t}=this,n=e.camera.matrixWorldInverse;QD.identity(),WD.copy(t.matrixWorld),WD.premultiply(n),QD.extractRotation(WD),this.halfWidth.value.set(.5*t.width,0,0),this.halfHeight.value.set(0,.5*t.height,0),this.halfWidth.value.applyMatrix4(QD),this.halfHeight.value.applyMatrix4(QD)}setupDirectRectArea(e){let t,n;e.isAvailable("float32Filterable")?(t=Pw(ZD.LTC_FLOAT_1),n=Pw(ZD.LTC_FLOAT_2)):(t=Pw(ZD.LTC_HALF_1),n=Pw(ZD.LTC_HALF_2));const{colorNode:i,light:r}=this;return{lightColor:i,lightPosition:pB(r),halfWidth:this.halfWidth,halfHeight:this.halfHeight,ltc_1:t,ltc_2:n}}static setLTC(e){ZD=e}}class JD extends iD{static get type(){return"SpotLightNode"}constructor(e=null){super(e),this.coneCosNode=Nx(0).setGroup(Tx),this.penumbraCosNode=Nx(0).setGroup(Tx),this.cutoffDistanceNode=Nx(0).setGroup(Tx),this.decayExponentNode=Nx(0).setGroup(Tx),this.colorNode=Nx(this.color).setGroup(Tx)}update(e){super.update(e);const{light:t}=this;this.coneCosNode.value=Math.cos(t.angle),this.penumbraCosNode.value=Math.cos(t.angle*(1-t.penumbra)),this.cutoffDistanceNode.value=t.distance,this.decayExponentNode.value=t.decay}getSpotAttenuation(e,t){const{coneCosNode:n,penumbraCosNode:i}=this;return fb(n,i,t)}getLightCoord(e){const t=e.getNodeProperties(this);let n=t.projectionUV;return void 0===n&&(n=dB(this.light,e.context.positionWorld),t.projectionUV=n),n}setupDirect(e){const{colorNode:t,cutoffDistanceNode:n,decayExponentNode:i,light:r}=this,s=this.getLightVector(e),o=s.normalize(),a=o.dot(gB(r)),l=this.getSpotAttenuation(e,a),u=s.length(),c=rD({lightDistance:u,cutoffDistance:n,decayExponent:i});let d,h,f=t.mul(l).mul(c);if(r.colorNode?(h=this.getLightCoord(e),d=r.colorNode(h)):r.map&&(h=this.getLightCoord(e),d=Pw(r.map,h.xy).onRenderUpdate((()=>r.map))),d){f=h.mul(2).sub(1).abs().lessThan(1).all().select(f.mul(d),f)}return{lightColor:f,lightDirection:o}}}class KD extends JD{static get type(){return"IESSpotLightNode"}getSpotAttenuation(e,t){const n=this.light.iesMap;let i=null;if(n&&!0===n.isTexture){const e=t.acos().mul(1/Math.PI);i=Pw(n,NA(e,0),0).r}else i=super.getSpotAttenuation(t);return i}}const qD=xA((([e,t])=>{const n=e.abs().sub(t);return Oy(Jy(n,0)).add(Yy(Jy(n.x,n.y),0))}));class _D extends JD{static get type(){return"ProjectorLightNode"}update(e){super.update(e);const t=this.light;if(this.penumbraCosNode.value=Math.min(Math.cos(t.angle*(1-t.penumbra)),.99999),null===t.aspect){let e=1;null!==t.map&&(e=t.map.width/t.map.height),t.shadow.aspect=e}else t.shadow.aspect=t.aspect}getSpotAttenuation(e){const t=EA(0),n=this.penumbraCosNode,i=cB(this.light).mul(e.context.positionWorld||cC);return wA(i.w.greaterThan(0),(()=>{const e=i.xyz.div(i.w),r=qD(e.xy.sub(NA(.5)),NA(.5)),s=Ux(-1,Fx(1,Dy(n)).sub(1));t.assign(db(r.mul(-2).mul(s)))})),t}}class $D extends iD{static get type(){return"AmbientLightNode"}constructor(e=null){super(e)}setup({context:e}){e.irradiance.addAssign(this.colorNode)}}class eI extends iD{static get type(){return"HemisphereLightNode"}constructor(e=null){super(e),this.lightPositionNode=hB(e),this.lightDirectionNode=this.lightPositionNode.normalize(),this.groundColorNode=Nx(new ya).setGroup(Tx)}update(e){const{light:t}=this;super.update(e),this.lightPositionNode.object3d=t,this.groundColorNode.value.copy(t.groundColor).multiplyScalar(t.intensity)}setup(e){const{colorNode:t,groundColorNode:n,lightDirectionNode:i}=this,r=MC.dot(i).mul(.5).add(.5),s=ub(n,t,r);e.context.irradiance.addAssign(s)}}class tI extends iD{static get type(){return"LightProbeNode"}constructor(e=null){super(e);const t=[];for(let e=0;e<9;e++)t.push(new Es);this.lightProbe=jw(t)}update(e){const{light:t}=this;super.update(e);for(let e=0;e<9;e++)this.lightProbe.array[e].copy(t.sh.coefficients[e]).multiplyScalar(t.intensity)}setup(e){const t=aD(MC,this.lightProbe);e.context.irradiance.addAssign(t)}}class nI{parseFunction(){console.warn("Abstract function.")}}class iI{constructor(e,t,n="",i=""){this.type=e,this.inputs=t,this.name=n,this.precision=i}getCode(){console.warn("Abstract function.")}}iI.isNodeFunction=!0;const rI=/^\s*(highp|mediump|lowp)?\s*([a-z_0-9]+)\s*([a-z_0-9]+)?\s*\(([\s\S]*?)\)/i,sI=/[a-z_0-9]+/gi,oI="#pragma main";class aI extends iI{constructor(e){const{type:t,inputs:n,name:i,precision:r,inputsCode:s,blockCode:o,headerCode:a}=(e=>{const t=(e=e.trim()).indexOf(oI),n=-1!==t?e.slice(t+oI.length):e,i=n.match(rI);if(null!==i&&5===i.length){const r=i[4],s=[];let o=null;for(;null!==(o=sI.exec(r));)s.push(o);const a=[];let l=0;for(;l<s.length;){const e="const"===s[l][0];!0===e&&l++;let t=s[l][0];"in"===t||"out"===t||"inout"===t?l++:t="";const n=s[l++][0];let i=Number.parseInt(s[l][0]);!1===Number.isNaN(i)?l++:i=null;const r=s[l++][0];a.push(new GD(n,r,i,t,e))}const u=n.substring(i[0].length),c=void 0!==i[3]?i[3]:"";return{type:i[2],inputs:a,name:c,precision:void 0!==i[1]?i[1]:"",inputsCode:r,blockCode:u,headerCode:-1!==t?e.slice(0,t):""}}throw new Error("FunctionNode: Function is not a GLSL code.")})(e);super(t,n,i,r),this.inputsCode=s,this.blockCode=o,this.headerCode=a}getCode(e=this.name){let t;const n=this.blockCode;if(""!==n){const{type:i,inputsCode:r,headerCode:s,precision:o}=this;let a=`${i} ${e} ( ${r.trim()} )`;""!==o&&(a=`${o} ${a}`),t=s+a+n}else t="";return t}}class lI extends nI{parseFunction(e){return new aI(e)}}const uI=new WeakMap,cI=[],dI=[];class hI extends UP{constructor(e,t){super(),this.renderer=e,this.backend=t,this.nodeFrame=new XD,this.nodeBuilderCache=new Map,this.callHashCache=new zP,this.groupsData=new zP,this.cacheLib={}}updateGroup(e){const t=e.groupNode,n=t.name;if(n===Sx.name)return!0;if(n===Tx.name){const t=this.get(e),n=this.nodeFrame.renderId;return t.renderId!==n&&(t.renderId=n,!0)}if(n===Ex.name){const t=this.get(e),n=this.nodeFrame.frameId;return t.frameId!==n&&(t.frameId=n,!0)}cI[0]=t,cI[1]=e;let i=this.groupsData.get(cI);return void 0===i&&this.groupsData.set(cI,i={}),cI.length=0,i.version!==t.version&&(i.version=t.version,!0)}getForRenderCacheKey(e){return e.initialCacheKey}getForRender(e){const t=this.get(e);let n=t.nodeBuilderState;if(void 0===n){const{nodeBuilderCache:i}=this,r=this.getForRenderCacheKey(e);if(n=i.get(r),void 0===n){const t=this.backend.createNodeBuilder(e.object,this.renderer);t.scene=e.scene,t.material=e.material,t.camera=e.camera,t.context.material=e.material,t.lightsNode=e.lightsNode,t.environmentNode=this.getEnvironmentNode(e.scene),t.fogNode=this.getFogNode(e.scene),t.clippingContext=e.clippingContext,this.renderer.getOutputRenderTarget()&&this.renderer.getOutputRenderTarget().multiview&&t.enableMultiview(),t.build(),n=this._createNodeBuilderState(t),i.set(r,n)}n.usedTimes++,t.nodeBuilderState=n}return n}delete(e){if(e.isRenderObject){const t=this.get(e).nodeBuilderState;t.usedTimes--,0===t.usedTimes&&this.nodeBuilderCache.delete(this.getForRenderCacheKey(e))}return super.delete(e)}getForCompute(e){const t=this.get(e);let n=t.nodeBuilderState;if(void 0===n){const i=this.backend.createNodeBuilder(e,this.renderer);i.build(),n=this._createNodeBuilderState(i),t.nodeBuilderState=n}return n}_createNodeBuilderState(e){return new hD(e.vertexShader,e.fragmentShader,e.computeShader,e.getAttributesArray(),e.getBindings(),e.updateNodes,e.updateBeforeNodes,e.updateAfterNodes,e.observer,e.transforms)}getEnvironmentNode(e){this.updateEnvironment(e);let t=null;if(e.environmentNode&&e.environmentNode.isNode)t=e.environmentNode;else{const n=this.get(e);n.environmentNode&&(t=n.environmentNode)}return t}getBackgroundNode(e){this.updateBackground(e);let t=null;if(e.backgroundNode&&e.backgroundNode.isNode)t=e.backgroundNode;else{const n=this.get(e);n.backgroundNode&&(t=n.backgroundNode)}return t}getFogNode(e){return this.updateFog(e),e.fogNode||this.get(e).fogNode||null}getCacheKey(e,t){cI[0]=e,cI[1]=t;const n=this.renderer.info.calls,i=this.callHashCache.get(cI)||{};if(i.callId!==n){const r=this.getEnvironmentNode(e),s=this.getFogNode(e);t&&dI.push(t.getCacheKey(!0)),r&&dI.push(r.getCacheKey()),s&&dI.push(s.getCacheKey()),dI.push(this.renderer.getOutputRenderTarget()&&this.renderer.getOutputRenderTarget().multiview?1:0),dI.push(this.renderer.shadowMap.enabled?1:0),i.callId=n,i.cacheKey=$m(dI),this.callHashCache.set(cI,i),dI.length=0}return cI.length=0,i.cacheKey}get isToneMappingState(){return!this.renderer.getRenderTarget()}updateBackground(e){const t=this.get(e),n=e.background;if(n){const i=0===e.backgroundBlurriness&&t.backgroundBlurriness>0||e.backgroundBlurriness>0&&0===t.backgroundBlurriness;if(t.background!==n||i){const r=this.getCacheNode("background",n,(()=>{if(!0===n.isCubeTexture||n.mapping===Di||n.mapping===Ii||n.mapping===Li){if(e.backgroundBlurriness>0||n.mapping===Li)return lP(n);{let e;return e=!0===n.isCubeTexture?HC(n):Pw(n),hT(e)}}if(!0===n.isTexture)return Pw(n,Hw.flipY()).setUpdateMatrix(!0);!0!==n.isColor&&console.error("WebGPUNodes: Unsupported background configuration.",n)}),i);t.backgroundNode=r,t.background=n,t.backgroundBlurriness=e.backgroundBlurriness}}else t.backgroundNode&&(delete t.backgroundNode,delete t.background)}getCacheNode(e,t,n,i=!1){const r=this.cacheLib[e]||(this.cacheLib[e]=new WeakMap);let s=r.get(t);return(void 0===s||i)&&(s=n(),r.set(t,s)),s}updateFog(e){const t=this.get(e),n=e.fog;if(n){if(t.fog!==n){const e=this.getCacheNode("fog",n,(()=>{if(n.isFogExp2){const e=GC("color","color",n).setGroup(Tx),t=GC("density","float",n).setGroup(Tx);return sB(e,rB(t))}if(n.isFog){const e=GC("color","color",n).setGroup(Tx),t=GC("near","float",n).setGroup(Tx),i=GC("far","float",n).setGroup(Tx);return sB(e,iB(t,i))}console.error("THREE.Renderer: Unsupported fog configuration.",n)}));t.fogNode=e,t.fog=n}}else delete t.fogNode,delete t.fog}updateEnvironment(e){const t=this.get(e),n=e.environment;if(n){if(t.environment!==n){const e=this.getCacheNode("environment",n,(()=>!0===n.isCubeTexture?HC(n):!0===n.isTexture?Pw(n):void console.error("Nodes: Unsupported environment configuration.",n)));t.environmentNode=e,t.environment=n}}else t.environmentNode&&(delete t.environmentNode,delete t.environment)}getNodeFrame(e=this.renderer,t=null,n=null,i=null,r=null){const s=this.nodeFrame;return s.renderer=e,s.scene=t,s.object=n,s.camera=i,s.material=r,s}getNodeFrameForRender(e){return this.getNodeFrame(e.renderer,e.scene,e.object,e.camera,e.material)}getOutputCacheKey(){const e=this.renderer;return e.toneMapping+","+e.currentColorSpace+","+e.xr.isPresenting}hasOutputChange(e){return uI.get(e)!==this.getOutputCacheKey()}getOutputNode(e){const t=this.renderer,n=this.getOutputCacheKey(),i=e.isArrayTexture?kN(e,LA(Hw,Ow("gl_ViewID_OVR"))).renderOutput(t.toneMapping,t.currentColorSpace):Pw(e,Hw).renderOutput(t.toneMapping,t.currentColorSpace);return uI.set(e,n),i}updateBefore(e){const t=e.getNodeBuilderState();for(const n of t.updateBeforeNodes)this.getNodeFrameForRender(e).updateBeforeNode(n)}updateAfter(e){const t=e.getNodeBuilderState();for(const n of t.updateAfterNodes)this.getNodeFrameForRender(e).updateAfterNode(n)}updateForCompute(e){const t=this.getNodeFrame(),n=this.getForCompute(e);for(const e of n.updateNodes)t.updateNode(e)}updateForRender(e){const t=this.getNodeFrameForRender(e),n=e.getNodeBuilderState();for(const e of n.updateNodes)t.updateNode(e)}needsRefresh(e){const t=this.getNodeFrameForRender(e);return e.getMonitor().needsRefresh(e,t)}dispose(){super.dispose(),this.nodeFrame=new XD,this.nodeBuilderCache=new Map,this.cacheLib={}}}const fI=new Il;class pI{constructor(e=null){this.version=0,this.clipIntersection=null,this.cacheKey="",this.shadowPass=!1,this.viewNormalMatrix=new Ps,this.clippingGroupContexts=new WeakMap,this.intersectionPlanes=[],this.unionPlanes=[],this.parentVersion=null,null!==e&&(this.viewNormalMatrix=e.viewNormalMatrix,this.clippingGroupContexts=e.clippingGroupContexts,this.shadowPass=e.shadowPass,this.viewMatrix=e.viewMatrix)}projectPlanes(e,t,n){const i=e.length;for(let r=0;r<i;r++){fI.copy(e[r]).applyMatrix4(this.viewMatrix,this.viewNormalMatrix);const i=t[n+r],s=fI.normal;i.x=-s.x,i.y=-s.y,i.z=-s.z,i.w=fI.constant}}updateGlobal(e,t){this.shadowPass=null!==e.overrideMaterial&&e.overrideMaterial.isShadowPassMaterial,this.viewMatrix=t.matrixWorldInverse,this.viewNormalMatrix.getNormalMatrix(this.viewMatrix)}update(e,t){let n=!1;e.version!==this.parentVersion&&(this.intersectionPlanes=Array.from(e.intersectionPlanes),this.unionPlanes=Array.from(e.unionPlanes),this.parentVersion=e.version),this.clipIntersection!==t.clipIntersection&&(this.clipIntersection=t.clipIntersection,this.clipIntersection?this.unionPlanes.length=e.unionPlanes.length:this.intersectionPlanes.length=e.intersectionPlanes.length);const i=t.clippingPlanes,r=i.length;let s,o;if(this.clipIntersection?(s=this.intersectionPlanes,o=e.intersectionPlanes.length):(s=this.unionPlanes,o=e.unionPlanes.length),s.length!==o+r){s.length=o+r;for(let e=0;e<r;e++)s[o+e]=new Js;n=!0}this.projectPlanes(i,s,o),n&&(this.version++,this.cacheKey=`${this.intersectionPlanes.length}:${this.unionPlanes.length}`)}getGroupContext(e){if(this.shadowPass&&!e.clipShadows)return this;let t=this.clippingGroupContexts.get(e);return void 0===t&&(t=new pI(this),this.clippingGroupContexts.set(e,t)),t.update(this,e),t}get unionClippingCount(){return this.unionPlanes.length}}class gI{constructor(e,t){this.bundleGroup=e,this.camera=t}}const mI=[];class vI{constructor(){this.bundles=new zP}get(e,t){const n=this.bundles;mI[0]=e,mI[1]=t;let i=n.get(mI);return void 0===i&&(i=new gI(e,t),n.set(mI,i)),mI.length=0,i}dispose(){this.bundles=new zP}}class AI{constructor(){this.lightNodes=new WeakMap,this.materialNodes=new Map,this.toneMappingNodes=new Map}fromMaterial(e){if(e.isNodeMaterial)return e;let t=null;const n=this.getMaterialNodeClass(e.type);if(null!==n){t=new n;for(const n in e)t[n]=e[n]}return t}addToneMapping(e,t){this.addType(e,t,this.toneMappingNodes)}getToneMappingFunction(e){return this.toneMappingNodes.get(e)||null}getMaterialNodeClass(e){return this.materialNodes.get(e)||null}addMaterial(e,t){this.addType(e,t,this.materialNodes)}getLightNodeClass(e){return this.lightNodes.get(e)||null}addLight(e,t){this.addClass(e,t,this.lightNodes)}addType(e,t,n){if(n.has(t))console.warn(`Redefinition of node ${t}`);else{if("function"!=typeof e)throw new Error(`Node class ${e.name} is not a class.`);if("function"==typeof t||"object"==typeof t)throw new Error(`Base class ${t} is not a class.`);n.set(t,e)}}addClass(e,t,n){if(n.has(t))console.warn(`Redefinition of node ${t.name}`);else{if("function"!=typeof e)throw new Error(`Node class ${e.name} is not a class.`);if("function"!=typeof t)throw new Error(`Base class ${t.name} is not a class.`);n.set(t,e)}}}const xI=new xB,yI=[];class bI extends zP{constructor(){super()}createNode(e=[]){return(new xB).setLights(e)}getNode(e,t){if(e.isQuadMesh)return xI;yI[0]=e,yI[1]=t;let n=this.get(yI);return void 0===n&&(n=this.createNode(),this.set(yI,n)),yI.length=0,n}}class wI extends Ks{constructor(e=1,t=1,n={}){super(e,t,n),this.isXRRenderTarget=!0,this._hasExternalTextures=!1,this._autoAllocateDepthBuffer=!0,this._isOpaqueFramebuffer=!1}copy(e){return super.copy(e),this._hasExternalTextures=e._hasExternalTextures,this._autoAllocateDepthBuffer=e._autoAllocateDepthBuffer,this._isOpaqueFramebuffer=e._isOpaqueFramebuffer,this}}const CI=new Es,MI=new Es;class EI extends ds{constructor(e,t=!1){super(),this.enabled=!1,this.isPresenting=!1,this.cameraAutoUpdate=!0,this._renderer=e,this._cameraL=new pl,this._cameraL.viewport=new Js,this._cameraR=new pl,this._cameraR.viewport=new Js,this._cameras=[this._cameraL,this._cameraR],this._cameraXR=new xc,this._currentDepthNear=null,this._currentDepthFar=null,this._controllers=[],this._controllerInputSources=[],this._xrRenderTarget=null,this._layers=[],this._sessionUsesLayers=!1,this._supportsGlBinding="undefined"!=typeof XRWebGLBinding,this._frameBufferTargets=null,this._createXRLayer=BI.bind(this),this._gl=null,this._currentAnimationContext=null,this._currentAnimationLoop=null,this._currentPixelRatio=null,this._currentSize=new Cs,this._onSessionEvent=SI.bind(this),this._onSessionEnd=PI.bind(this),this._onInputSourcesChange=NI.bind(this),this._onAnimationFrame=DI.bind(this),this._referenceSpace=null,this._referenceSpaceType="local-floor",this._customReferenceSpace=null,this._framebufferScaleFactor=1,this._foveation=1,this._session=null,this._glBaseLayer=null,this._glBinding=null,this._glProjLayer=null,this._xrFrame=null,this._supportsLayers=this._supportsGlBinding&&"createProjectionLayer"in XRWebGLBinding.prototype,this._useMultiviewIfPossible=t,this._useMultiview=!1}getController(e){return this._getController(e).getTargetRaySpace()}getControllerGrip(e){return this._getController(e).getGripSpace()}getHand(e){return this._getController(e).getHandSpace()}getFoveation(){if(null!==this._glProjLayer||null!==this._glBaseLayer)return this._foveation}setFoveation(e){this._foveation=e,null!==this._glProjLayer&&(this._glProjLayer.fixedFoveation=e),null!==this._glBaseLayer&&void 0!==this._glBaseLayer.fixedFoveation&&(this._glBaseLayer.fixedFoveation=e)}getFramebufferScaleFactor(){return this._framebufferScaleFactor}setFramebufferScaleFactor(e){this._framebufferScaleFactor=e,!0===this.isPresenting&&console.warn("THREE.XRManager: Cannot change framebuffer scale while presenting.")}getReferenceSpaceType(){return this._referenceSpaceType}setReferenceSpaceType(e){this._referenceSpaceType=e,!0===this.isPresenting&&console.warn("THREE.XRManager: Cannot change reference space type while presenting.")}getReferenceSpace(){return this._customReferenceSpace||this._referenceSpace}setReferenceSpace(e){this._customReferenceSpace=e}getCamera(){return this._cameraXR}getEnvironmentBlendMode(){if(null!==this._session)return this._session.environmentBlendMode}getBinding(){return null===this._glBinding&&this._supportsGlBinding&&(this._glBinding=new XRWebGLBinding(this._session,this._gl)),this._glBinding}getFrame(){return this._xrFrame}useMultiview(){return this._useMultiview}createQuadLayer(e,t,n,i,r,s,o,a={}){const l=new xu(e,t),u=new wI(r,s,{format:rr,type:Gi,depthTexture:new _l(r,s,a.stencil?$i:Yi,void 0,void 0,void 0,void 0,void 0,void 0,a.stencil?or:sr),stencilBuffer:a.stencil,resolveDepthBuffer:!1,resolveStencilBuffer:!1});u._autoAllocateDepthBuffer=!0;const c=new Ma({color:16777215,side:0});c.map=u.texture,c.map.offset.y=1,c.map.repeat.y=-1;const d=new nl(l,c);d.position.copy(n),d.quaternion.copy(i);const h={type:"quad",width:e,height:t,translation:n,quaternion:i,pixelwidth:r,pixelheight:s,plane:d,material:c,rendercall:o,renderTarget:u};if(this._layers.push(h),null!==this._session){h.plane.material=new Ma({color:16777215,side:0}),h.plane.material.blending=5,h.plane.material.blendEquation=Mi,h.plane.material.blendSrc=Ei,h.plane.material.blendDst=Ei,h.xrlayer=this._createXRLayer(h);const e=this._session.renderState.layers;e.unshift(h.xrlayer),this._session.updateRenderState({layers:e})}else u.isXRRenderTarget=!1;return d}createCylinderLayer(e,t,n,i,r,s,o,a,l={}){const u=new eu(e,e,e*t/n,64,64,!0,Math.PI-t/2,t),c=new wI(s,o,{format:rr,type:Gi,depthTexture:new _l(s,o,l.stencil?$i:Yi,void 0,void 0,void 0,void 0,void 0,void 0,l.stencil?or:sr),stencilBuffer:l.stencil,resolveDepthBuffer:!1,resolveStencilBuffer:!1});c._autoAllocateDepthBuffer=!0;const d=new Ma({color:16777215,side:1});d.map=c.texture,d.map.offset.y=1,d.map.repeat.y=-1;const h=new nl(u,d);h.position.copy(i),h.quaternion.copy(r);const f={type:"cylinder",radius:e,centralAngle:t,aspectratio:n,translation:i,quaternion:r,pixelwidth:s,pixelheight:o,plane:h,material:d,rendercall:a,renderTarget:c};if(this._layers.push(f),null!==this._session){f.plane.material=new Ma({color:16777215,side:1}),f.plane.material.blending=5,f.plane.material.blendEquation=Mi,f.plane.material.blendSrc=Ei,f.plane.material.blendDst=Ei,f.xrlayer=this._createXRLayer(f);const e=this._session.renderState.layers;e.unshift(f.xrlayer),this._session.updateRenderState({layers:e})}else c.isXRRenderTarget=!1;return h}renderLayers(){const e=new Es,t=new Ms,n=this._renderer,i=this.isPresenting,r=n.getOutputRenderTarget(),s=n._frameBufferTarget;this.isPresenting=!1;const o=new Cs;n.getSize(o);const a=n._quad;for(const i of this._layers)if(i.renderTarget.isXRRenderTarget=null!==this._session,i.renderTarget._hasExternalTextures=i.renderTarget.isXRRenderTarget,i.renderTarget.isXRRenderTarget&&this._sessionUsesLayers){i.xrlayer.transform=new XRRigidTransform(i.plane.getWorldPosition(e),i.plane.getWorldQuaternion(t));const r=this._glBinding.getSubImage(i.xrlayer,this._xrFrame);n.backend.setXRRenderTargetTextures(i.renderTarget,r.colorTexture,void 0),n._setXRLayerSize(i.renderTarget.width,i.renderTarget.height),n.setOutputRenderTarget(i.renderTarget),n.setRenderTarget(null),n._frameBufferTarget=null,this._frameBufferTargets||(this._frameBufferTargets=new WeakMap);const{frameBufferTarget:s,quad:o}=this._frameBufferTargets.get(i.renderTarget)||{frameBufferTarget:null,quad:null};s?(n._frameBufferTarget=s,n._quad=o):(n._quad=new PN(new _E),this._frameBufferTargets.set(i.renderTarget,{frameBufferTarget:n._getFrameBufferTarget(),quad:n._quad})),i.rendercall(),n._frameBufferTarget=null}else n.setRenderTarget(i.renderTarget),i.rendercall();n.setRenderTarget(null),n.setOutputRenderTarget(r),n._frameBufferTarget=s,n._setXRLayerSize(o.x,o.y),n._quad=a,this.isPresenting=i}getSession(){return this._session}async setSession(e){const t=this._renderer,n=t.backend;this._gl=t.getContext();const i=this._gl,r=i.getContextAttributes();if(this._session=e,null!==e){if(!0===n.isWebGPUBackend)throw new Error('THREE.XRManager: XR is currently not supported with a WebGPU backend. Use WebGL by passing "{ forceWebGL: true }" to the constructor of the renderer.');if(e.addEventListener("select",this._onSessionEvent),e.addEventListener("selectstart",this._onSessionEvent),e.addEventListener("selectend",this._onSessionEvent),e.addEventListener("squeeze",this._onSessionEvent),e.addEventListener("squeezestart",this._onSessionEvent),e.addEventListener("squeezeend",this._onSessionEvent),e.addEventListener("end",this._onSessionEnd),e.addEventListener("inputsourceschange",this._onInputSourcesChange),await n.makeXRCompatible(),this._currentPixelRatio=t.getPixelRatio(),t.getSize(this._currentSize),this._currentAnimationContext=t._animation.getContext(),this._currentAnimationLoop=t._animation.getAnimationLoop(),t._animation.stop(),!0===this._supportsLayers){let n=null,s=null,o=null;t.depth&&(o=t.stencil?i.DEPTH24_STENCIL8:i.DEPTH_COMPONENT24,n=t.stencil?or:sr,s=t.stencil?$i:Yi);const a={colorFormat:i.RGBA8,depthFormat:o,scaleFactor:this._framebufferScaleFactor,clearOnAccess:!1};this._useMultiviewIfPossible&&t.hasFeature("OVR_multiview2")&&(a.textureType="texture-array",this._useMultiview=!0),this._glBinding=this.getBinding();const l=this._glBinding.createProjectionLayer(a),u=[l];this._glProjLayer=l,t.setPixelRatio(1),t._setXRLayerSize(l.textureWidth,l.textureHeight);const c=this._useMultiview?2:1,d=new _l(l.textureWidth,l.textureHeight,s,void 0,void 0,void 0,void 0,void 0,void 0,n,c);if(this._xrRenderTarget=new wI(l.textureWidth,l.textureHeight,{format:rr,type:Gi,colorSpace:t.outputColorSpace,depthTexture:d,stencilBuffer:t.stencil,samples:r.antialias?4:0,resolveDepthBuffer:!1===l.ignoreDepthValues,resolveStencilBuffer:!1===l.ignoreDepthValues,depth:this._useMultiview?2:1,multiview:this._useMultiview}),this._xrRenderTarget._hasExternalTextures=!0,this._xrRenderTarget.depth=this._useMultiview?2:1,this._sessionUsesLayers=e.enabledFeatures.includes("layers"),this._referenceSpace=await e.requestReferenceSpace(this.getReferenceSpaceType()),this._sessionUsesLayers)for(const e of this._layers)e.plane.material=new Ma({color:16777215,side:"cylinder"===e.type?1:0}),e.plane.material.blending=5,e.plane.material.blendEquation=Mi,e.plane.material.blendSrc=Ei,e.plane.material.blendDst=Ei,e.xrlayer=this._createXRLayer(e),u.unshift(e.xrlayer);e.updateRenderState({layers:u})}else{const n={antialias:t.samples>0,alpha:!0,depth:t.depth,stencil:t.stencil,framebufferScaleFactor:this.getFramebufferScaleFactor()},r=new XRWebGLLayer(e,i,n);this._glBaseLayer=r,e.updateRenderState({baseLayer:r}),t.setPixelRatio(1),t._setXRLayerSize(r.framebufferWidth,r.framebufferHeight),this._xrRenderTarget=new wI(r.framebufferWidth,r.framebufferHeight,{format:rr,type:Gi,colorSpace:t.outputColorSpace,stencilBuffer:t.stencil,resolveDepthBuffer:!1===r.ignoreDepthValues,resolveStencilBuffer:!1===r.ignoreDepthValues}),this._xrRenderTarget._isOpaqueFramebuffer=!0,this._referenceSpace=await e.requestReferenceSpace(this.getReferenceSpaceType())}this.setFoveation(this.getFoveation()),t._animation.setAnimationLoop(this._onAnimationFrame),t._animation.setContext(e),t._animation.start(),this.isPresenting=!0,this.dispatchEvent({type:"sessionstart"})}}updateCamera(e){const t=this._session;if(null===t)return;const n=e.near,i=e.far,r=this._cameraXR,s=this._cameraL,o=this._cameraR;r.near=o.near=s.near=n,r.far=o.far=s.far=i,r.isMultiViewCamera=this._useMultiview,this._currentDepthNear===r.near&&this._currentDepthFar===r.far||(t.updateRenderState({depthNear:r.near,depthFar:r.far}),this._currentDepthNear=r.near,this._currentDepthFar=r.far),r.layers.mask=6|e.layers.mask,s.layers.mask=3&r.layers.mask,o.layers.mask=5&r.layers.mask;const a=e.parent,l=r.cameras;TI(r,a);for(let e=0;e<l.length;e++)TI(l[e],a);2===l.length?function(e,t,n){CI.setFromMatrixPosition(t.matrixWorld),MI.setFromMatrixPosition(n.matrixWorld);const i=CI.distanceTo(MI),r=t.projectionMatrix.elements,s=n.projectionMatrix.elements,o=r[14]/(r[10]-1),a=r[14]/(r[10]+1),l=(r[9]+1)/r[5],u=(r[9]-1)/r[5],c=(r[8]-1)/r[0],d=(s[8]+1)/s[0],h=o*c,f=o*d,p=i/(-c+d),g=p*-c;if(t.matrixWorld.decompose(e.position,e.quaternion,e.scale),e.translateX(g),e.translateZ(p),e.matrixWorld.compose(e.position,e.quaternion,e.scale),e.matrixWorldInverse.copy(e.matrixWorld).invert(),-1===r[10])e.projectionMatrix.copy(t.projectionMatrix),e.projectionMatrixInverse.copy(t.projectionMatrixInverse);else{const t=o+p,n=a+p,r=h-g,s=f+(i-g),c=l*a/n*t,d=u*a/n*t;e.projectionMatrix.makePerspective(r,s,c,d,t,n),e.projectionMatrixInverse.copy(e.projectionMatrix).invert()}}(r,s,o):r.projectionMatrix.copy(s.projectionMatrix),function(e,t,n){null===n?e.matrix.copy(t.matrixWorld):(e.matrix.copy(n.matrixWorld),e.matrix.invert(),e.matrix.multiply(t.matrixWorld));e.matrix.decompose(e.position,e.quaternion,e.scale),e.updateMatrixWorld(!0),e.projectionMatrix.copy(t.projectionMatrix),e.projectionMatrixInverse.copy(t.projectionMatrixInverse),e.isPerspectiveCamera&&(e.fov=2*gs*Math.atan(1/e.projectionMatrix.elements[5]),e.zoom=1)}(e,r,a)}_getController(e){let t=this._controllers[e];return void 0===t&&(t=new bl,this._controllers[e]=t),t}}function TI(e,t){null===t?e.matrixWorld.copy(e.matrix):e.matrixWorld.multiplyMatrices(t.matrixWorld,e.matrix),e.matrixWorldInverse.copy(e.matrixWorld).invert()}function SI(e){const t=this._controllerInputSources.indexOf(e.inputSource);if(-1===t)return;const n=this._controllers[t];if(void 0!==n){const t=this.getReferenceSpace();n.update(e.inputSource,e.frame,t),n.dispatchEvent({type:e.type,data:e.inputSource})}}function PI(){const e=this._session,t=this._renderer;e.removeEventListener("select",this._onSessionEvent),e.removeEventListener("selectstart",this._onSessionEvent),e.removeEventListener("selectend",this._onSessionEvent),e.removeEventListener("squeeze",this._onSessionEvent),e.removeEventListener("squeezestart",this._onSessionEvent),e.removeEventListener("squeezeend",this._onSessionEvent),e.removeEventListener("end",this._onSessionEnd),e.removeEventListener("inputsourceschange",this._onInputSourcesChange);for(let e=0;e<this._controllers.length;e++){const t=this._controllerInputSources[e];null!==t&&(this._controllerInputSources[e]=null,this._controllers[e].disconnect(t))}if(this._currentDepthNear=null,this._currentDepthFar=null,t._resetXRState(),this._session=null,this._xrRenderTarget=null,!0===this._sessionUsesLayers)for(const e of this._layers)e.renderTarget=new wI(e.pixelwidth,e.pixelheight,{format:rr,type:Gi,depthTexture:new _l(e.pixelwidth,e.pixelheight,e.stencilBuffer?$i:Yi,void 0,void 0,void 0,void 0,void 0,void 0,e.stencilBuffer?or:sr),stencilBuffer:e.stencilBuffer,resolveDepthBuffer:!1,resolveStencilBuffer:!1}),e.renderTarget.isXRRenderTarget=!1,e.plane.material=e.material,e.material.map=e.renderTarget.texture,e.material.map.offset.y=1,e.material.map.repeat.y=-1,delete e.xrlayer;this.isPresenting=!1,this._useMultiview=!1,t._animation.stop(),t._animation.setAnimationLoop(this._currentAnimationLoop),t._animation.setContext(this._currentAnimationContext),t._animation.start(),t.setPixelRatio(this._currentPixelRatio),t.setSize(this._currentSize.width,this._currentSize.height,!1),this.dispatchEvent({type:"sessionend"})}function NI(e){const t=this._controllers,n=this._controllerInputSources;for(let i=0;i<e.removed.length;i++){const r=e.removed[i],s=n.indexOf(r);s>=0&&(n[s]=null,t[s].disconnect(r))}for(let i=0;i<e.added.length;i++){const r=e.added[i];let s=n.indexOf(r);if(-1===s){for(let e=0;e<t.length;e++){if(e>=n.length){n.push(r),s=e;break}if(null===n[e]){n[e]=r,s=e;break}}if(-1===s)break}const o=t[s];o&&o.connect(r)}}function BI(e){return"quad"===e.type?this._glBinding.createQuadLayer({transform:new XRRigidTransform(e.translation,e.quaternion),width:e.width/2,height:e.height/2,space:this._referenceSpace,viewPixelWidth:e.pixelwidth,viewPixelHeight:e.pixelheight,clearOnAccess:!1}):this._glBinding.createCylinderLayer({transform:new XRRigidTransform(e.translation,e.quaternion),radius:e.radius,centralAngle:e.centralAngle,aspectRatio:e.aspectRatio,space:this._referenceSpace,viewPixelWidth:e.pixelwidth,viewPixelHeight:e.pixelheight,clearOnAccess:!1})}function DI(e,t){if(void 0===t)return;const n=this._cameraXR,i=this._renderer,r=i.backend,s=this._glBaseLayer,o=this.getReferenceSpace(),a=t.getViewerPose(o);if(this._xrFrame=t,null!==a){const e=a.views;null!==this._glBaseLayer&&r.setXRTarget(s.framebuffer);let t=!1;e.length!==n.cameras.length&&(n.cameras.length=0,t=!0);for(let i=0;i<e.length;i++){const o=e[i];let a;if(!0===this._supportsLayers){const e=this._glBinding.getViewSubImage(this._glProjLayer,o);a=e.viewport,0===i&&r.setXRRenderTargetTextures(this._xrRenderTarget,e.colorTexture,this._glProjLayer.ignoreDepthValues&&!this._useMultiview?void 0:e.depthStencilTexture)}else a=s.getViewport(o);let l=this._cameras[i];void 0===l&&(l=new pl,l.layers.enable(i),l.viewport=new Js,this._cameras[i]=l),l.matrix.fromArray(o.transform.matrix),l.matrix.decompose(l.position,l.quaternion,l.scale),l.projectionMatrix.fromArray(o.projectionMatrix),l.projectionMatrixInverse.copy(l.projectionMatrix).invert(),l.viewport.set(a.x,a.y,a.width,a.height),0===i&&(n.matrix.copy(l.matrix),n.matrix.decompose(n.position,n.quaternion,n.scale)),!0===t&&n.cameras.push(l)}i.setOutputRenderTarget(this._xrRenderTarget)}for(let e=0;e<this._controllers.length;e++){const n=this._controllerInputSources[e],i=this._controllers[e];null!==n&&void 0!==i&&i.update(n,t,o)}this._currentAnimationLoop&&this._currentAnimationLoop(e,t),t.detectedPlanes&&this.dispatchEvent({type:"planesdetected",data:t}),this._xrFrame=null}const II=new wl,LI=new Cs,jI=new Js,OI=new zl,zI=new Fl,RI=new Po,kI=new Js;class FI{constructor(e,t={}){this.isRenderer=!0;const{logarithmicDepthBuffer:n=!1,alpha:i=!0,depth:r=!0,stencil:s=!1,antialias:o=!1,samples:a=0,getFallback:l=null,colorBufferType:u=Ki,multiview:c=!1}=t;this.domElement=e.getDomElement(),this.backend=e,this.samples=a||!0===o?4:0,this.autoClear=!0,this.autoClearColor=!0,this.autoClearDepth=!0,this.autoClearStencil=!0,this.alpha=i,this.logarithmicDepthBuffer=n,this.outputColorSpace=qr,this.toneMapping=0,this.toneMappingExposure=1,this.sortObjects=!0,this.depth=r,this.stencil=s,this.info=new qP,this.overrideNodes={modelViewMatrix:null,modelNormalViewMatrix:null},this.library=new AI,this.lighting=new bI,this._getFallback=l,this._pixelRatio=1,this._width=this.domElement.width,this._height=this.domElement.height,this._viewport=new Js(0,0,this._width,this._height),this._scissor=new Js(0,0,this._width,this._height),this._scissorTest=!1,this._attributes=null,this._geometries=null,this._nodes=null,this._animation=null,this._bindings=null,this._objects=null,this._pipelines=null,this._bundles=null,this._renderLists=null,this._renderContexts=null,this._textures=null,this._background=null,this._quad=new PN(new _E),this._quad.material.name="Renderer_output",this._currentRenderContext=null,this._opaqueSort=null,this._transparentSort=null,this._frameBufferTarget=null;const d=!0===this.alpha?0:1;this._clearColor=new yN(0,0,0,d),this._clearDepth=1,this._clearStencil=0,this._renderTarget=null,this._activeCubeFace=0,this._activeMipmapLevel=0,this._outputRenderTarget=null,this._mrt=null,this._renderObjectFunction=null,this._currentRenderObjectFunction=null,this._currentRenderBundle=null,this._handleObjectFunction=this._renderObjectDirect,this._isDeviceLost=!1,this.onDeviceLost=this._onDeviceLost,this._colorBufferType=u,this._initialized=!1,this._initPromise=null,this._compilationPromises=null,this.transparent=!0,this.opaque=!0,this.shadowMap={enabled:!1,type:1},this.xr=new EI(this,c),this.debug={checkShaderErrors:!0,onShaderError:null,getShaderAsync:async(e,t,n)=>{await this.compileAsync(e,t);const i=this._renderLists.get(e,t),r=this._renderContexts.get(e,t,this._renderTarget),s=e.overrideMaterial||n.material,o=this._objects.get(n,s,e,t,i.lightsNode,r,r.clippingContext),{fragmentShader:a,vertexShader:l}=o.getNodeBuilderState();return{fragmentShader:a,vertexShader:l}}}}async init(){if(this._initialized)throw new Error("Renderer: Backend has already been initialized.");return null!==this._initPromise||(this._initPromise=new Promise((async(e,t)=>{let n=this.backend;try{await n.init(this)}catch(e){if(null===this._getFallback)return void t(e);try{this.backend=n=this._getFallback(e),await n.init(this)}catch(e){return void t(e)}}this._nodes=new hI(this,n),this._animation=new OP(this._nodes,this.info),this._attributes=new ZP(n),this._background=new uD(this,this._nodes),this._geometries=new KP(this._attributes,this.info),this._textures=new xN(this,n,this.info),this._pipelines=new iN(n,this._nodes),this._bindings=new rN(n,this._nodes,this._textures,this._attributes,this._pipelines,this.info),this._objects=new HP(this,this._nodes,this._geometries,this._pipelines,this._bindings,this.info),this._renderLists=new cN(this.lighting),this._bundles=new vI,this._renderContexts=new vN,this._animation.start(),this._initialized=!0,e(this)}))),this._initPromise}get coordinateSystem(){return this.backend.coordinateSystem}async compileAsync(e,t,n=null){if(!0===this._isDeviceLost)return;!1===this._initialized&&await this.init();const i=this._nodes.nodeFrame,r=i.renderId,s=this._currentRenderContext,o=this._currentRenderObjectFunction,a=this._compilationPromises,l=!0===e.isScene?e:II;null===n&&(n=e);const u=this._renderTarget,c=this._renderContexts.get(n,t,u),d=this._activeMipmapLevel,h=[];this._currentRenderContext=c,this._currentRenderObjectFunction=this.renderObject,this._handleObjectFunction=this._createObjectPipeline,this._compilationPromises=h,i.renderId++,i.update(),c.depth=this.depth,c.stencil=this.stencil,c.clippingContext||(c.clippingContext=new pI),c.clippingContext.updateGlobal(l,t),l.onBeforeRender(this,e,t,u);const f=this._renderLists.get(e,t);if(f.begin(),this._projectObject(e,t,0,f,c.clippingContext),n!==e&&n.traverseVisible((function(e){e.isLight&&e.layers.test(t.layers)&&f.pushLight(e)})),f.finish(),null!==u){this._textures.updateRenderTarget(u,d);const e=this._textures.get(u);c.textures=e.textures,c.depthTexture=e.depthTexture}else c.textures=null,c.depthTexture=null;this._background.update(l,f,c);const p=f.opaque,g=f.transparent,m=f.transparentDoublePass,v=f.lightsNode;!0===this.opaque&&p.length>0&&this._renderObjects(p,t,l,v),!0===this.transparent&&g.length>0&&this._renderTransparents(g,m,t,l,v),i.renderId=r,this._currentRenderContext=s,this._currentRenderObjectFunction=o,this._compilationPromises=a,this._handleObjectFunction=this._renderObjectDirect,await Promise.all(h)}async renderAsync(e,t){!1===this._initialized&&await this.init(),this._renderScene(e,t)}async waitForGPU(){await this.backend.waitForGPU()}set highPrecision(e){!0===e?(this.overrideNodes.modelViewMatrix=sC,this.overrideNodes.modelNormalViewMatrix=oC):this.highPrecision&&(this.overrideNodes.modelViewMatrix=null,this.overrideNodes.modelNormalViewMatrix=null)}get highPrecision(){return this.overrideNodes.modelViewMatrix===sC&&this.overrideNodes.modelNormalViewMatrix===oC}setMRT(e){return this._mrt=e,this}getMRT(){return this._mrt}getColorBufferType(){return this._colorBufferType}_onDeviceLost(e){let t=`THREE.WebGPURenderer: ${e.api} Device Lost:\n\nMessage: ${e.message}`;e.reason&&(t+=`\nReason: ${e.reason}`),console.error(t),this._isDeviceLost=!0}_renderBundle(e,t,n){const{bundleGroup:i,camera:r,renderList:s}=e,o=this._currentRenderContext,a=this._bundles.get(i,r),l=this.backend.get(a);void 0===l.renderContexts&&(l.renderContexts=new Set);const u=i.version!==l.version,c=!1===l.renderContexts.has(o)||u;if(l.renderContexts.add(o),c){this.backend.beginBundle(o),(void 0===l.renderObjects||u)&&(l.renderObjects=[]),this._currentRenderBundle=a;const{transparentDoublePass:e,transparent:c,opaque:d}=s;!0===this.opaque&&d.length>0&&this._renderObjects(d,r,t,n),!0===this.transparent&&c.length>0&&this._renderTransparents(c,e,r,t,n),this._currentRenderBundle=null,this.backend.finishBundle(o,a),l.version=i.version}else{const{renderObjects:e}=l;for(let t=0,n=e.length;t<n;t++){const n=e[t];this._nodes.needsRefresh(n)&&(this._nodes.updateBefore(n),this._nodes.updateForRender(n),this._bindings.updateForRender(n),this._nodes.updateAfter(n))}}this.backend.addBundle(o,a)}render(e,t){if(!1===this._initialized)return console.warn("THREE.Renderer: .render() called before the backend is initialized. Try using .renderAsync() instead."),this.renderAsync(e,t);this._renderScene(e,t)}_getFrameBufferTarget(){const{currentToneMapping:e,currentColorSpace:t}=this,n=0!==e,i=t!==ks.workingColorSpace;if(!1===n&&!1===i)return null;const{width:r,height:s}=this.getDrawingBufferSize(LI),{depth:o,stencil:a}=this;let l=this._frameBufferTarget;null===l&&(l=new Ks(r,s,{depthBuffer:o,stencilBuffer:a,type:this._colorBufferType,format:rr,colorSpace:ks.workingColorSpace,generateMipmaps:!1,minFilter:Hi,magFilter:Hi,samples:this.samples}),l.isPostProcessingRenderTarget=!0,this._frameBufferTarget=l);const u=this.getOutputRenderTarget();return l.depthBuffer=o,l.stencilBuffer=a,null!==u?l.setSize(u.width,u.height,u.depth):l.setSize(r,s,1),l.viewport.copy(this._viewport),l.scissor.copy(this._scissor),l.viewport.multiplyScalar(this._pixelRatio),l.scissor.multiplyScalar(this._pixelRatio),l.scissorTest=this._scissorTest,l.multiview=null!==u&&u.multiview,l.resolveDepthBuffer=null===u||u.resolveDepthBuffer,l._autoAllocateDepthBuffer=null!==u&&u._autoAllocateDepthBuffer,l}_renderScene(e,t,n=!0){if(!0===this._isDeviceLost)return;const i=n?this._getFrameBufferTarget():null,r=this._nodes.nodeFrame,s=r.renderId,o=this._currentRenderContext,a=this._currentRenderObjectFunction,l=!0===e.isScene?e:II,u=this._renderTarget||this._outputRenderTarget,c=this._activeCubeFace,d=this._activeMipmapLevel;let h;null!==i?(h=i,this.setRenderTarget(h)):h=u;const f=this._renderContexts.get(e,t,h);this._currentRenderContext=f,this._currentRenderObjectFunction=this._renderObjectFunction||this.renderObject,this.info.calls++,this.info.render.calls++,this.info.render.frameCalls++,r.renderId=this.info.calls;const p=this.coordinateSystem,g=this.xr;if(t.coordinateSystem!==p&&!1===g.isPresenting&&(t.coordinateSystem=p,t.updateProjectionMatrix(),t.isArrayCamera))for(const e of t.cameras)e.coordinateSystem=p,e.updateProjectionMatrix();!0===e.matrixWorldAutoUpdate&&e.updateMatrixWorld(),null===t.parent&&!0===t.matrixWorldAutoUpdate&&t.updateMatrixWorld(),!0===g.enabled&&!0===g.isPresenting&&(!0===g.cameraAutoUpdate&&g.updateCamera(t),t=g.getCamera());let m=this._viewport,v=this._scissor,A=this._pixelRatio;null!==h&&(m=h.viewport,v=h.scissor,A=1),this.getDrawingBufferSize(LI),jI.set(0,0,LI.width,LI.height);const x=void 0===m.minDepth?0:m.minDepth,y=void 0===m.maxDepth?1:m.maxDepth;f.viewportValue.copy(m).multiplyScalar(A).floor(),f.viewportValue.width>>=d,f.viewportValue.height>>=d,f.viewportValue.minDepth=x,f.viewportValue.maxDepth=y,f.viewport=!1===f.viewportValue.equals(jI),f.scissorValue.copy(v).multiplyScalar(A).floor(),f.scissor=this._scissorTest&&!1===f.scissorValue.equals(jI),f.scissorValue.width>>=d,f.scissorValue.height>>=d,f.clippingContext||(f.clippingContext=new pI),f.clippingContext.updateGlobal(l,t),l.onBeforeRender(this,e,t,h);const b=t.isArrayCamera?zI:OI;t.isArrayCamera||(RI.multiplyMatrices(t.projectionMatrix,t.matrixWorldInverse),b.setFromProjectionMatrix(RI,t.coordinateSystem,t.reversedDepth));const w=this._renderLists.get(e,t);if(w.begin(),this._projectObject(e,t,0,w,f.clippingContext),w.finish(),!0===this.sortObjects&&w.sort(this._opaqueSort,this._transparentSort),null!==h){this._textures.updateRenderTarget(h,d);const e=this._textures.get(h);f.textures=e.textures,f.depthTexture=e.depthTexture,f.width=e.width,f.height=e.height,f.renderTarget=h,f.depth=h.depthBuffer,f.stencil=h.stencilBuffer}else f.textures=null,f.depthTexture=null,f.width=LI.width,f.height=LI.height,f.depth=this.depth,f.stencil=this.stencil;f.width>>=d,f.height>>=d,f.activeCubeFace=c,f.activeMipmapLevel=d,f.occlusionQueryCount=w.occlusionQueryCount,f.scissorValue.max(kI.set(0,0,0,0)),f.scissorValue.x+f.scissorValue.width>f.width&&(f.scissorValue.width=Math.max(f.width-f.scissorValue.x,0)),f.scissorValue.y+f.scissorValue.height>f.height&&(f.scissorValue.height=Math.max(f.height-f.scissorValue.y,0)),this._background.update(l,w,f),f.camera=t,this.backend.beginRender(f);const{bundles:C,lightsNode:M,transparentDoublePass:E,transparent:T,opaque:S}=w;return C.length>0&&this._renderBundles(C,l,M),!0===this.opaque&&S.length>0&&this._renderObjects(S,t,l,M),!0===this.transparent&&T.length>0&&this._renderTransparents(T,E,t,l,M),this.backend.finishRender(f),r.renderId=s,this._currentRenderContext=o,this._currentRenderObjectFunction=a,null!==i&&(this.setRenderTarget(u,c,d),this._renderOutput(h)),l.onAfterRender(this,e,t,h),f}_setXRLayerSize(e,t){this._width=e,this._height=t,this.setViewport(0,0,e,t)}_renderOutput(e){const t=this._quad;this._nodes.hasOutputChange(e.texture)&&(t.material.fragmentNode=this._nodes.getOutputNode(e.texture),t.material.needsUpdate=!0);const n=this.autoClear,i=this.xr.enabled;this.autoClear=!1,this.xr.enabled=!1,this._renderScene(t,t.camera,!1),this.autoClear=n,this.xr.enabled=i}getMaxAnisotropy(){return this.backend.getMaxAnisotropy()}getActiveCubeFace(){return this._activeCubeFace}getActiveMipmapLevel(){return this._activeMipmapLevel}async setAnimationLoop(e){!1===this._initialized&&await this.init(),this._animation.setAnimationLoop(e)}async getArrayBufferAsync(e){return await this.backend.getArrayBufferAsync(e)}getContext(){return this.backend.getContext()}getPixelRatio(){return this._pixelRatio}getDrawingBufferSize(e){return e.set(this._width*this._pixelRatio,this._height*this._pixelRatio).floor()}getSize(e){return e.set(this._width,this._height)}setPixelRatio(e=1){this._pixelRatio!==e&&(this._pixelRatio=e,this.setSize(this._width,this._height,!1))}setDrawingBufferSize(e,t,n){this.xr&&this.xr.isPresenting||(this._width=e,this._height=t,this._pixelRatio=n,this.domElement.width=Math.floor(e*n),this.domElement.height=Math.floor(t*n),this.setViewport(0,0,e,t),this._initialized&&this.backend.updateSize())}setSize(e,t,n=!0){this.xr&&this.xr.isPresenting||(this._width=e,this._height=t,this.domElement.width=Math.floor(e*this._pixelRatio),this.domElement.height=Math.floor(t*this._pixelRatio),!0===n&&(this.domElement.style.width=e+"px",this.domElement.style.height=t+"px"),this.setViewport(0,0,e,t),this._initialized&&this.backend.updateSize())}setOpaqueSort(e){this._opaqueSort=e}setTransparentSort(e){this._transparentSort=e}getScissor(e){const t=this._scissor;return e.x=t.x,e.y=t.y,e.width=t.width,e.height=t.height,e}setScissor(e,t,n,i){const r=this._scissor;e.isVector4?r.copy(e):r.set(e,t,n,i)}getScissorTest(){return this._scissorTest}setScissorTest(e){this._scissorTest=e,this.backend.setScissorTest(e)}getViewport(e){return e.copy(this._viewport)}setViewport(e,t,n,i,r=0,s=1){const o=this._viewport;e.isVector4?o.copy(e):o.set(e,t,n,i),o.minDepth=r,o.maxDepth=s}getClearColor(e){return e.copy(this._clearColor)}setClearColor(e,t=1){this._clearColor.set(e),this._clearColor.a=t}getClearAlpha(){return this._clearColor.a}setClearAlpha(e){this._clearColor.a=e}getClearDepth(){return this._clearDepth}setClearDepth(e){this._clearDepth=e}getClearStencil(){return this._clearStencil}setClearStencil(e){this._clearStencil=e}isOccluded(e){const t=this._currentRenderContext;return t&&this.backend.isOccluded(t,e)}clear(e=!0,t=!0,n=!0){if(!1===this._initialized)return console.warn("THREE.Renderer: .clear() called before the backend is initialized. Try using .clearAsync() instead."),this.clearAsync(e,t,n);const i=this._renderTarget||this._getFrameBufferTarget();let r=null;if(null!==i){this._textures.updateRenderTarget(i);const e=this._textures.get(i);r=this._renderContexts.getForClear(i),r.textures=e.textures,r.depthTexture=e.depthTexture,r.width=e.width,r.height=e.height,r.renderTarget=i,r.depth=i.depthBuffer,r.stencil=i.stencilBuffer,r.clearColorValue=this.backend.getClearColor(),r.activeCubeFace=this.getActiveCubeFace(),r.activeMipmapLevel=this.getActiveMipmapLevel()}this.backend.clear(e,t,n,r),null!==i&&null===this._renderTarget&&this._renderOutput(i)}clearColor(){return this.clear(!0,!1,!1)}clearDepth(){return this.clear(!1,!0,!1)}clearStencil(){return this.clear(!1,!1,!0)}async clearAsync(e=!0,t=!0,n=!0){!1===this._initialized&&await this.init(),this.clear(e,t,n)}async clearColorAsync(){this.clearAsync(!0,!1,!1)}async clearDepthAsync(){this.clearAsync(!1,!0,!1)}async clearStencilAsync(){this.clearAsync(!1,!1,!0)}get currentToneMapping(){return this.isOutputTarget?this.toneMapping:0}get currentColorSpace(){return this.isOutputTarget?this.outputColorSpace:ks.workingColorSpace}get isOutputTarget(){return this._renderTarget===this._outputRenderTarget||null===this._renderTarget}dispose(){!0===this._initialized&&(this.info.dispose(),this.backend.dispose(),this._animation.dispose(),this._objects.dispose(),this._pipelines.dispose(),this._nodes.dispose(),this._bindings.dispose(),this._renderLists.dispose(),this._renderContexts.dispose(),this._textures.dispose(),null!==this._frameBufferTarget&&this._frameBufferTarget.dispose(),Object.values(this.backend.timestampQueryPool).forEach((e=>{null!==e&&e.dispose()}))),this.setRenderTarget(null),this.setAnimationLoop(null)}setRenderTarget(e,t=0,n=0){this._renderTarget=e,this._activeCubeFace=t,this._activeMipmapLevel=n}getRenderTarget(){return this._renderTarget}setOutputRenderTarget(e){this._outputRenderTarget=e}getOutputRenderTarget(){return this._outputRenderTarget}_resetXRState(){this.backend.setXRTarget(null),this.setOutputRenderTarget(null),this.setRenderTarget(null),this._frameBufferTarget.dispose(),this._frameBufferTarget=null}setRenderObjectFunction(e){this._renderObjectFunction=e}getRenderObjectFunction(){return this._renderObjectFunction}compute(e,t=null){if(!0===this._isDeviceLost)return;if(!1===this._initialized)return console.warn("THREE.Renderer: .compute() called before the backend is initialized. Try using .computeAsync() instead."),this.computeAsync(e);const n=this._nodes.nodeFrame,i=n.renderId;this.info.calls++,this.info.compute.calls++,this.info.compute.frameCalls++,n.renderId=this.info.calls;const r=this.backend,s=this._pipelines,o=this._bindings,a=this._nodes,l=Array.isArray(e)?e:[e];if(void 0===l[0]||!0!==l[0].isComputeNode)throw new Error("THREE.Renderer: .compute() expects a ComputeNode.");r.beginCompute(e);for(const n of l){if(!1===s.has(n)){const e=()=>{n.removeEventListener("dispose",e),s.delete(n),o.delete(n),a.delete(n)};n.addEventListener("dispose",e);const t=n.onInitFunction;null!==t&&t.call(n,{renderer:this})}a.updateForCompute(n),o.updateForCompute(n);const i=o.getForCompute(n),l=s.getForCompute(n,i);r.compute(e,n,i,l,t)}r.finishCompute(e),n.renderId=i}async computeAsync(e,t=null){!1===this._initialized&&await this.init(),this.compute(e,t)}async hasFeatureAsync(e){return!1===this._initialized&&await this.init(),this.backend.hasFeature(e)}async resolveTimestampsAsync(e="render"){return!1===this._initialized&&await this.init(),this.backend.resolveTimestampsAsync(e)}hasFeature(e){return!1===this._initialized?(console.warn("THREE.Renderer: .hasFeature() called before the backend is initialized. Try using .hasFeatureAsync() instead."),!1):this.backend.hasFeature(e)}hasInitialized(){return this._initialized}async initTextureAsync(e){!1===this._initialized&&await this.init(),this._textures.updateTexture(e)}initTexture(e){!1===this._initialized&&console.warn("THREE.Renderer: .initTexture() called before the backend is initialized. Try using .initTextureAsync() instead."),this._textures.updateTexture(e)}copyFramebufferToTexture(e,t=null){if(null!==t)if(t.isVector2)t=kI.set(t.x,t.y,e.image.width,e.image.height).floor();else{if(!t.isVector4)return void console.error("THREE.Renderer.copyFramebufferToTexture: Invalid rectangle.");t=kI.copy(t).floor()}else t=kI.set(0,0,e.image.width,e.image.height);let n,i=this._currentRenderContext;null!==i?n=i.renderTarget:(n=this._renderTarget||this._getFrameBufferTarget(),null!==n&&(this._textures.updateRenderTarget(n),i=this._textures.get(n))),this._textures.updateTexture(e,{renderTarget:n}),this.backend.copyFramebufferToTexture(e,i,t)}copyTextureToTexture(e,t,n=null,i=null,r=0,s=0){this._textures.updateTexture(e),this._textures.updateTexture(t),this.backend.copyTextureToTexture(e,t,n,i,r,s)}async readRenderTargetPixelsAsync(e,t,n,i,r,s=0,o=0){return this.backend.copyTextureToBuffer(e.textures[s],t,n,i,r,o)}_projectObject(e,t,n,i,r){if(!1===e.visible)return;if(e.layers.test(t.layers))if(e.isGroup)n=e.renderOrder,e.isClippingGroup&&e.enabled&&(r=r.getGroupContext(e));else if(e.isLOD)!0===e.autoUpdate&&e.update(t);else if(e.isLight)i.pushLight(e);else if(e.isSprite){const s=t.isArrayCamera?zI:OI;if(!e.frustumCulled||s.intersectsSprite(e,t)){!0===this.sortObjects&&kI.setFromMatrixPosition(e.matrixWorld).applyMatrix4(RI);const{geometry:t,material:s}=e;s.visible&&i.push(e,t,s,n,kI.z,null,r)}}else if(e.isLineLoop)console.error("THREE.Renderer: Objects of type THREE.LineLoop are not supported. Please use THREE.Line or THREE.LineSegments.");else if(e.isMesh||e.isLine||e.isPoints){const s=t.isArrayCamera?zI:OI;if(!e.frustumCulled||s.intersectsObject(e,t)){const{geometry:t,material:s}=e;if(!0===this.sortObjects&&(null===t.boundingSphere&&t.computeBoundingSphere(),kI.copy(t.boundingSphere.center).applyMatrix4(e.matrixWorld).applyMatrix4(RI)),Array.isArray(s)){const o=t.groups;for(let a=0,l=o.length;a<l;a++){const l=o[a],u=s[l.materialIndex];u&&u.visible&&i.push(e,t,u,n,kI.z,l,r)}}else s.visible&&i.push(e,t,s,n,kI.z,null,r)}}if(!0===e.isBundleGroup&&void 0!==this.backend.beginBundle){const n=i;(i=this._renderLists.get(e,t)).begin(),n.pushBundle({bundleGroup:e,camera:t,renderList:i}),i.finish()}const s=e.children;for(let e=0,o=s.length;e<o;e++)this._projectObject(s[e],t,n,i,r)}_renderBundles(e,t,n){for(const i of e)this._renderBundle(i,t,n)}_renderTransparents(e,t,n,i,r){if(t.length>0){for(const{material:e}of t)e.side=1;this._renderObjects(t,n,i,r,"backSide");for(const{material:e}of t)e.side=0;this._renderObjects(e,n,i,r);for(const{material:e}of t)e.side=2}else this._renderObjects(e,n,i,r)}_renderObjects(e,t,n,i,r=null){for(let s=0,o=e.length;s<o;s++){const{object:o,geometry:a,material:l,group:u,clippingContext:c}=e[s];this._currentRenderObjectFunction(o,n,t,a,l,u,i,c,r)}}renderObject(e,t,n,i,r,s,o,a=null,l=null){let u,c,d;if(e.onBeforeRender(this,t,n,i,r,s),!0===r.allowOverride&&null!==t.overrideMaterial){const e=t.overrideMaterial;r.positionNode&&r.positionNode.isNode&&(u=e.positionNode,e.positionNode=r.positionNode),e.alphaTest=r.alphaTest,e.alphaMap=r.alphaMap,e.transparent=r.transparent||r.transmission>0,e.isShadowPassMaterial&&(e.side=null===r.shadowSide?r.side:r.shadowSide,r.depthNode&&r.depthNode.isNode&&(d=e.depthNode,e.depthNode=r.depthNode),r.castShadowNode&&r.castShadowNode.isNode&&(c=e.colorNode,e.colorNode=r.castShadowNode),r.castShadowPositionNode&&r.castShadowPositionNode.isNode&&(u=e.positionNode,e.positionNode=r.castShadowPositionNode)),r=e}!0===r.transparent&&2===r.side&&!1===r.forceSinglePass?(r.side=1,this._handleObjectFunction(e,r,t,n,o,s,a,"backSide"),r.side=0,this._handleObjectFunction(e,r,t,n,o,s,a,l),r.side=2):this._handleObjectFunction(e,r,t,n,o,s,a,l),void 0!==u&&(t.overrideMaterial.positionNode=u),void 0!==d&&(t.overrideMaterial.depthNode=d),void 0!==c&&(t.overrideMaterial.colorNode=c),e.onAfterRender(this,t,n,i,r,s)}_renderObjectDirect(e,t,n,i,r,s,o,a){const l=this._objects.get(e,t,n,i,r,this._currentRenderContext,o,a);l.drawRange=e.geometry.drawRange,l.group=s;const u=this._nodes.needsRefresh(l);if(u&&(this._nodes.updateBefore(l),this._geometries.updateForRender(l),this._nodes.updateForRender(l),this._bindings.updateForRender(l)),this._pipelines.updateForRender(l),null!==this._currentRenderBundle){this.backend.get(this._currentRenderBundle).renderObjects.push(l),l.bundle=this._currentRenderBundle.bundleGroup}this.backend.draw(l,this.info),u&&this._nodes.updateAfter(l)}_createObjectPipeline(e,t,n,i,r,s,o,a){const l=this._objects.get(e,t,n,i,r,this._currentRenderContext,o,a);l.drawRange=e.geometry.drawRange,l.group=s,this._nodes.updateBefore(l),this._geometries.updateForRender(l),this._nodes.updateForRender(l),this._bindings.updateForRender(l),this._pipelines.getForRender(l,this._compilationPromises),this._nodes.updateAfter(l)}get compile(){return this.compileAsync}}class HI{constructor(e=""){this.name=e,this.visibility=0}setVisibility(e){this.visibility|=e}clone(){return Object.assign(new this.constructor,this)}}class UI extends HI{constructor(e,t=null){super(e),this.isBuffer=!0,this.bytesPerElement=Float32Array.BYTES_PER_ELEMENT,this._buffer=t}get byteLength(){return(e=this._buffer.byteLength)+(QP-e%QP)%QP;var e}get buffer(){return this._buffer}update(){return!0}}class XI extends UI{constructor(e,t=null){super(e,t),this.isUniformBuffer=!0}}let GI=0;class VI extends XI{constructor(e,t){super("UniformBuffer_"+GI++,e?e.value:null),this.nodeUniform=e,this.groupNode=t}get buffer(){return this.nodeUniform.value}}class WI extends XI{constructor(e){super(e),this.isUniformsGroup=!0,this._values=null,this.uniforms=[]}addUniform(e){return this.uniforms.push(e),this}removeUniform(e){const t=this.uniforms.indexOf(e);return-1!==t&&this.uniforms.splice(t,1),this}get values(){return null===this._values&&(this._values=Array.from(this.buffer)),this._values}get buffer(){let e=this._buffer;if(null===e){const t=this.byteLength;e=new Float32Array(new ArrayBuffer(t)),this._buffer=e}return e}get byteLength(){const e=this.bytesPerElement;let t=0;for(let n=0,i=this.uniforms.length;n<i;n++){const i=this.uniforms[n],r=i.boundary,s=i.itemSize*e,o=t%QP,a=o%r,l=o+a;t+=a,0!==l&&QP-l<s&&(t+=QP-l),i.offset=t/e,t+=s}return Math.ceil(t/QP)*QP}update(){let e=!1;for(const t of this.uniforms)!0===this.updateByType(t)&&(e=!0);return e}updateByType(e){return e.isNumberUniform?this.updateNumber(e):e.isVector2Uniform?this.updateVector2(e):e.isVector3Uniform?this.updateVector3(e):e.isVector4Uniform?this.updateVector4(e):e.isColorUniform?this.updateColor(e):e.isMatrix3Uniform?this.updateMatrix3(e):e.isMatrix4Uniform?this.updateMatrix4(e):void console.error("THREE.WebGPUUniformsGroup: Unsupported uniform type.",e)}updateNumber(e){let t=!1;const n=this.values,i=e.getValue(),r=e.offset,s=e.getType();if(n[r]!==i){this._getBufferForType(s)[r]=n[r]=i,t=!0}return t}updateVector2(e){let t=!1;const n=this.values,i=e.getValue(),r=e.offset,s=e.getType();if(n[r+0]!==i.x||n[r+1]!==i.y){const e=this._getBufferForType(s);e[r+0]=n[r+0]=i.x,e[r+1]=n[r+1]=i.y,t=!0}return t}updateVector3(e){let t=!1;const n=this.values,i=e.getValue(),r=e.offset,s=e.getType();if(n[r+0]!==i.x||n[r+1]!==i.y||n[r+2]!==i.z){const e=this._getBufferForType(s);e[r+0]=n[r+0]=i.x,e[r+1]=n[r+1]=i.y,e[r+2]=n[r+2]=i.z,t=!0}return t}updateVector4(e){let t=!1;const n=this.values,i=e.getValue(),r=e.offset,s=e.getType();if(n[r+0]!==i.x||n[r+1]!==i.y||n[r+2]!==i.z||n[r+4]!==i.w){const e=this._getBufferForType(s);e[r+0]=n[r+0]=i.x,e[r+1]=n[r+1]=i.y,e[r+2]=n[r+2]=i.z,e[r+3]=n[r+3]=i.w,t=!0}return t}updateColor(e){let t=!1;const n=this.values,i=e.getValue(),r=e.offset;if(n[r+0]!==i.r||n[r+1]!==i.g||n[r+2]!==i.b){const e=this.buffer;e[r+0]=n[r+0]=i.r,e[r+1]=n[r+1]=i.g,e[r+2]=n[r+2]=i.b,t=!0}return t}updateMatrix3(e){let t=!1;const n=this.values,i=e.getValue().elements,r=e.offset;if(n[r+0]!==i[0]||n[r+1]!==i[1]||n[r+2]!==i[2]||n[r+4]!==i[3]||n[r+5]!==i[4]||n[r+6]!==i[5]||n[r+8]!==i[6]||n[r+9]!==i[7]||n[r+10]!==i[8]){const e=this.buffer;e[r+0]=n[r+0]=i[0],e[r+1]=n[r+1]=i[1],e[r+2]=n[r+2]=i[2],e[r+4]=n[r+4]=i[3],e[r+5]=n[r+5]=i[4],e[r+6]=n[r+6]=i[5],e[r+8]=n[r+8]=i[6],e[r+9]=n[r+9]=i[7],e[r+10]=n[r+10]=i[8],t=!0}return t}updateMatrix4(e){let t=!1;const n=this.values,i=e.getValue().elements,r=e.offset;if(!1===function(e,t,n){for(let i=0,r=t.length;i<r;i++)if(e[n+i]!==t[i])return!1;return!0}(n,i,r)){this.buffer.set(i,r),function(e,t,n){for(let i=0,r=t.length;i<r;i++)e[n+i]=t[i]}(n,i,r),t=!0}return t}_getBufferForType(e){return"int"===e||"ivec2"===e||"ivec3"===e||"ivec4"===e?new Int32Array(this.buffer.buffer):"uint"===e||"uvec2"===e||"uvec3"===e||"uvec4"===e?new Uint32Array(this.buffer.buffer):this.buffer}}let QI=0;class ZI extends WI{constructor(e,t){super(e),this.id=QI++,this.groupNode=t,this.isNodeUniformsGroup=!0}}class YI extends HI{constructor(e,t){super(e),this.texture=t,this.version=t?t.version:0,this.generation=null,this.isSampler=!0}set texture(e){if(this._texture===e)return;const t=()=>{this._texture=null,this.generation=null,this.version=0};this._texture&&this._texture.removeEventListener("dispose",t),this._texture=e,this.generation=null,this.version=0,this._texture&&this._texture.addEventListener("dispose",t)}get texture(){return this._texture}update(){const{texture:e,version:t}=this;return t!==e.version&&(this.version=e.version,!0)}clone(){const e=super.clone();return e._texture=null,e.texture=this.texture,e}}let JI=0;class KI extends YI{constructor(e,t){super(e,t),this.id=JI++,this.store=!1,this.isSampledTexture=!0}}class qI extends KI{constructor(e,t,n,i=null){super(e,t?t.value:null),this.textureNode=t,this.groupNode=n,this.access=i}update(){const{textureNode:e}=this;return this.texture!==e.value?(this.texture=e.value,!0):super.update()}}class _I extends qI{constructor(e,t,n,i=null){super(e,t,n,i),this.isSampledCubeTexture=!0}}class $I extends qI{constructor(e,t,n,i=null){super(e,t,n,i),this.isSampledTexture3D=!0}}const eL={textureDimensions:"textureSize",equals:"equal",bitcast_float_int:"floatBitsToInt",bitcast_int_float:"intBitsToFloat",bitcast_uint_float:"uintBitsToFloat",bitcast_float_uint:"floatBitsToUint"},tL={low:"lowp",medium:"mediump",high:"highp"},nL={swizzleAssign:!0,storageBuffer:!1},iL={perspective:"smooth",linear:"noperspective"},rL={centroid:"centroid"},sL="\nprecision highp float;\nprecision highp int;\nprecision highp sampler2D;\nprecision highp sampler3D;\nprecision highp samplerCube;\nprecision highp sampler2DArray;\n\nprecision highp usampler2D;\nprecision highp usampler3D;\nprecision highp usamplerCube;\nprecision highp usampler2DArray;\n\nprecision highp isampler2D;\nprecision highp isampler3D;\nprecision highp isamplerCube;\nprecision highp isampler2DArray;\n\nprecision lowp sampler2DShadow;\nprecision lowp sampler2DArrayShadow;\nprecision lowp samplerCubeShadow;\n";class oL extends UD{constructor(e,t){super(e,t,new lI),this.uniformGroups={},this.transforms=[],this.extensions={},this.builtins={vertex:[],fragment:[],compute:[]}}needsToWorkingColorSpace(e){return!0===e.isVideoTexture&&e.colorSpace!==Kr}getMethod(e){return eL[e]||e}getBitcastMethod(e,t){return eL[`bitcast_${t}_${e}`]}getTernary(e,t,n){return`${e} ? ${t} : ${n}`}getOutputStructName(){return""}buildFunctionCode(e){const t=e.layout,n=this.flowShaderNode(e),i=[];for(const e of t.inputs)i.push(this.getType(e.type)+" "+e.name);return`${this.getType(t.type)} ${t.name}( ${i.join(", ")} ) {\n\n\t${n.vars}\n\n${n.code}\n\treturn ${n.result};\n\n}`}setupPBO(e){const t=e.value;if(void 0===t.pbo){const e=t.array,n=t.count*t.itemSize,{itemSize:i}=t,r=t.array.constructor.name.toLowerCase().includes("int");let s=r?lr:ar;2===i?s=r?cr:ur:3===i?s=r?1032:ir:4===i&&(s=r?dr:rr);const o={Float32Array:Ji,Uint8Array:Gi,Uint16Array:Qi,Uint32Array:Yi,Int8Array:Vi,Int16Array:Wi,Int32Array:Zi,Uint8ClampedArray:Gi},a=Math.pow(2,Math.ceil(Math.log2(Math.sqrt(n/i))));let l=Math.ceil(n/i/a);a*l*i<n&&l++;const u=a*l*i,c=new e.constructor(u);c.set(e,0),t.array=c;const d=new Sl(t.array,a,l,s,o[t.array.constructor.name]||Ji);d.needsUpdate=!0,d.isPBOTexture=!0;const h=new Tw(d,null,null);h.setPrecision("high"),t.pboNode=h,t.pbo=h.value,this.getUniformFromNode(t.pboNode,"texture",this.shaderStage,this.context.nodeName)}}getPropertyName(e,t=this.shaderStage){return e.isNodeUniform&&!0!==e.node.isTextureNode&&!0!==e.node.isBufferNode?t.charAt(0)+"_"+e.name:super.getPropertyName(e,t)}generatePBO(e){const{node:t,indexNode:n}=e,i=t.value;if(this.renderer.backend.has(i)){this.renderer.backend.get(i).pbo=i.pbo}const r=this.getUniformFromNode(i.pboNode,"texture",this.shaderStage,this.context.nodeName),s=this.getPropertyName(r);this.increaseUsage(n);const o=n.build(this,"uint"),a=this.getDataFromNode(e);let l=a.propertyName;if(void 0===l){const n=this.getVarFromNode(e);l=this.getPropertyName(n);const r=this.getDataFromNode(t);let u=r.propertySizeName;void 0===u&&(u=l+"Size",this.getVarFromNode(t,u,"uint"),this.addLineFlowCode(`${u} = uint( textureSize( ${s}, 0 ).x )`,e),r.propertySizeName=u);const{itemSize:c}=i,d="."+vv.join("").slice(0,c),h=`ivec2(${o} % ${u}, ${o} / ${u})`,f=this.generateTextureLoad(null,s,h,null,null,"0");let p="vec4";i.pbo.type===Yi?p="uvec4":i.pbo.type===Zi&&(p="ivec4"),this.addLineFlowCode(`${l} = ${p}(${f})${d}`,e),a.propertyName=l}return l}generateTextureLoad(e,t,n,i,r,s="0"){let o;return o=i?r?`texelFetchOffset( ${t}, ivec3( ${n}, ${i} ), ${s}, ${r} )`:`texelFetch( ${t}, ivec3( ${n}, ${i} ), ${s} )`:r?`texelFetchOffset( ${t}, ${n}, ${s}, ${r} )`:`texelFetch( ${t}, ${n}, ${s} )`,null!==e&&e.isDepthTexture&&(o+=".x"),o}generateTexture(e,t,n,i,r){return i&&(n=`vec3( ${n}, ${i} )`),e.isDepthTexture?r?`textureOffset( ${t}, ${n}, ${r} ).x`:`texture( ${t}, ${n} ).x`:r?`textureOffset( ${t}, ${n}, ${r} )`:`texture( ${t}, ${n} )`}generateTextureLevel(e,t,n,i,r){return r?`textureLodOffset( ${t}, ${n}, ${i}, ${r} )`:`textureLod( ${t}, ${n}, ${i} )`}generateTextureBias(e,t,n,i,r){return r?`textureOffset( ${t}, ${n}, ${r}, ${i} )`:`texture( ${t}, ${n}, ${i} )`}generateTextureGrad(e,t,n,i,r){return r?`textureGradOffset( ${t}, ${n}, ${i[0]}, ${i[1]}, ${r} )`:`textureGrad( ${t}, ${n}, ${i[0]}, ${i[1]} )`}generateTextureCompare(e,t,n,i,r,s,o=this.shaderStage){if("fragment"===o)return r?s?`textureOffset( ${t}, vec4( ${n}, ${r}, ${i} ), ${s} )`:`texture( ${t}, vec4( ${n}, ${r}, ${i} ) )`:s?`textureOffset( ${t}, vec3( ${n}, ${i} ), ${s} )`:`texture( ${t}, vec3( ${n}, ${i} ) )`;console.error(`WebGPURenderer: THREE.DepthTexture.compareFunction() does not support ${o} shader.`)}getVars(e){const t=[],n=this.vars[e];if(void 0!==n)for(const e of n)t.push(`${this.getVar(e.type,e.name,e.count)};`);return t.join("\n\t")}getUniforms(e){const t=this.uniforms[e],n=[],i={};for(const r of t){let t=null,s=!1;if("texture"===r.type||"texture3D"===r.type){const e=r.node.value;let n="";!0!==e.isDataTexture&&!0!==e.isData3DTexture||(e.type===Yi?n="u":e.type===Zi&&(n="i")),t="texture3D"===r.type&&!1===e.isArrayTexture?`${n}sampler3D ${r.name};`:e.compareFunction?!0===e.isArrayTexture?`sampler2DArrayShadow ${r.name};`:`sampler2DShadow ${r.name};`:!0===e.isArrayTexture||!0===e.isDataArrayTexture||!0===e.isCompressedArrayTexture?`${n}sampler2DArray ${r.name};`:`${n}sampler2D ${r.name};`}else if("cubeTexture"===r.type)t=`samplerCube ${r.name};`;else if("buffer"===r.type){const e=r.node,n=this.getType(e.bufferType),i=e.bufferCount,s=i>0?i:"";t=`${e.name} {\n\t${n} ${r.name}[${s}];\n};\n`}else{t=`${this.getVectorType(r.type)} ${this.getPropertyName(r,e)};`,s=!0}const o=r.node.precision;if(null!==o&&(t=tL[o]+" "+t),s){t="\t"+t;const e=r.groupNode.name;(i[e]||(i[e]=[])).push(t)}else t="uniform "+t,n.push(t)}let r="";for(const t in i){const n=i[t];r+=this._getGLSLUniformStruct(e+"_"+t,n.join("\n"))+"\n"}return r+=n.join("\n"),r}getTypeFromAttribute(e){let t=super.getTypeFromAttribute(e);if(/^[iu]/.test(t)&&e.gpuType!==Zi){let n=e;e.isInterleavedBufferAttribute&&(n=e.data);const i=n.array;!1==(i instanceof Uint32Array||i instanceof Int32Array)&&(t=t.slice(1))}return t}getAttributes(e){let t="";if("vertex"===e||"compute"===e){const e=this.getAttributesArray();let n=0;for(const i of e)t+=`layout( location = ${n++} ) in ${i.type} ${i.name};\n`}return t}getStructMembers(e){const t=[];for(const n of e.members)t.push(`\t${n.type} ${n.name};`);return t.join("\n")}getStructs(e){const t=[],n=this.structs[e],i=[];for(const e of n)if(e.output)for(const t of e.members)i.push(`layout( location = ${t.index} ) out ${t.type} ${t.name};`);else{let n="struct "+e.name+" {\n";n+=this.getStructMembers(e),n+="\n};\n",t.push(n)}return 0===i.length&&i.push("layout( location = 0 ) out vec4 fragColor;"),"\n"+i.join("\n")+"\n\n"+t.join("\n")}getVaryings(e){let t="";const n=this.varyings;if("vertex"===e||"compute"===e)for(const i of n){"compute"===e&&(i.needsInterpolation=!0);const n=this.getType(i.type);if(i.needsInterpolation)if(i.interpolationType){t+=`${iL[i.interpolationType]||i.interpolationType} ${rL[i.interpolationSampling]||""} out ${n} ${i.name};\n`}else{t+=`${n.includes("int")||n.includes("uv")||n.includes("iv")?"flat ":""}out ${n} ${i.name};\n`}else t+=`${n} ${i.name};\n`}else if("fragment"===e)for(const e of n)if(e.needsInterpolation){const n=this.getType(e.type);if(e.interpolationType){t+=`${iL[e.interpolationType]||e.interpolationType} ${rL[e.interpolationSampling]||""} in ${n} ${e.name};\n`}else{t+=`${n.includes("int")||n.includes("uv")||n.includes("iv")?"flat ":""}in ${n} ${e.name};\n`}}for(const n of this.builtins[e])t+=`${n};\n`;return t}getVertexIndex(){return"uint( gl_VertexID )"}getInstanceIndex(){return"uint( gl_InstanceID )"}getInvocationLocalIndex(){return`uint( gl_InstanceID ) % ${this.object.workgroupSize.reduce(((e,t)=>e*t),1)}u`}getDrawIndex(){return this.renderer.backend.extensions.has("WEBGL_multi_draw")?"uint( gl_DrawID )":null}getFrontFacing(){return"gl_FrontFacing"}getFragCoord(){return"gl_FragCoord.xy"}getFragDepth(){return"gl_FragDepth"}enableExtension(e,t,n=this.shaderStage){const i=this.extensions[n]||(this.extensions[n]=new Map);!1===i.has(e)&&i.set(e,{name:e,behavior:t})}getExtensions(e){const t=[];if("vertex"===e){const t=this.renderer.backend.extensions;this.object.isBatchedMesh&&t.has("WEBGL_multi_draw")&&this.enableExtension("GL_ANGLE_multi_draw","require",e)}const n=this.extensions[e];if(void 0!==n)for(const{name:e,behavior:i}of n.values())t.push(`#extension ${e} : ${i}`);return t.join("\n")}getClipDistance(){return"gl_ClipDistance"}isAvailable(e){let t=nL[e];if(void 0===t){let n;switch(t=!1,e){case"float32Filterable":n="OES_texture_float_linear";break;case"clipDistance":n="WEBGL_clip_cull_distance"}if(void 0!==n){const e=this.renderer.backend.extensions;e.has(n)&&(e.get(n),t=!0)}nL[e]=t}return t}isFlipY(){return!0}enableHardwareClipping(e){this.enableExtension("GL_ANGLE_clip_cull_distance","require"),this.builtins.vertex.push(`out float gl_ClipDistance[ ${e} ]`)}enableMultiview(){this.enableExtension("GL_OVR_multiview2","require","fragment"),this.enableExtension("GL_OVR_multiview2","require","vertex"),this.builtins.vertex.push("layout(num_views = 2) in")}registerTransform(e,t){this.transforms.push({varyingName:e,attributeNode:t})}getTransforms(){const e=this.transforms;let t="";for(let n=0;n<e.length;n++){const i=e[n],r=this.getPropertyName(i.attributeNode);r&&(t+=`${i.varyingName} = ${r};\n\t`)}return t}_getGLSLUniformStruct(e,t){return`\nlayout( std140 ) uniform ${e} {\n${t}\n};`}_getGLSLVertexCode(e){return`#version 300 es\n\n${this.getSignature()}\n\n// extensions\n${e.extensions}\n\n// precision\n${sL}\n\n// uniforms\n${e.uniforms}\n\n// varyings\n${e.varyings}\n\n// attributes\n${e.attributes}\n\n// codes\n${e.codes}\n\nvoid main() {\n\n\t// vars\n\t${e.vars}\n\n\t// transforms\n\t${e.transforms}\n\n\t// flow\n\t${e.flow}\n\n\tgl_PointSize = 1.0;\n\n}\n`}_getGLSLFragmentCode(e){return`#version 300 es\n\n${this.getSignature()}\n\n// extensions\n${e.extensions}\n\n// precision\n${sL}\n\n// uniforms\n${e.uniforms}\n\n// varyings\n${e.varyings}\n\n// codes\n${e.codes}\n\n// structs\n${e.structs}\n\nvoid main() {\n\n\t// vars\n\t${e.vars}\n\n\t// flow\n\t${e.flow}\n\n}\n`}buildCode(){const e=null!==this.material?{fragment:{},vertex:{}}:{compute:{}};this.sortBindingGroups();for(const t in e){let n="// code\n\n";n+=this.flowCode[t];const i=this.flowNodes[t],r=i[i.length-1];for(const e of i){const i=this.getFlowData(e),s=e.name;s&&(n.length>0&&(n+="\n"),n+=`\t// flow -> ${s}\n\t`),n+=`${i.code}\n\t`,e===r&&"compute"!==t&&(n+="// result\n\t","vertex"===t?(n+="gl_Position = ",n+=`${i.result};`):"fragment"===t&&(e.outputNode.isOutputStructNode||(n+="fragColor = ",n+=`${i.result};`)))}const s=e[t];s.extensions=this.getExtensions(t),s.uniforms=this.getUniforms(t),s.attributes=this.getAttributes(t),s.varyings=this.getVaryings(t),s.vars=this.getVars(t),s.structs=this.getStructs(t),s.codes=this.getCodes(t),s.transforms=this.getTransforms(t),s.flow=n}null!==this.material?(this.vertexShader=this._getGLSLVertexCode(e.vertex),this.fragmentShader=this._getGLSLFragmentCode(e.fragment)):this.computeShader=this._getGLSLVertexCode(e.compute)}getUniformFromNode(e,t,n,i=null){const r=super.getUniformFromNode(e,t,n,i),s=this.getDataFromNode(e,n,this.globalCache);let o=s.uniformGPU;if(void 0===o){const i=e.groupNode,a=i.name,l=this.getBindGroupArray(a,n);if("texture"===t)o=new qI(r.name,r.node,i),l.push(o);else if("cubeTexture"===t)o=new _I(r.name,r.node,i),l.push(o);else if("texture3D"===t)o=new $I(r.name,r.node,i),l.push(o);else if("buffer"===t){e.name=`NodeBuffer_${e.id}`,r.name=`buffer${e.id}`;const t=new VI(e,i);t.name=e.name,l.push(t),o=t}else{const e=this.uniformGroups[n]||(this.uniformGroups[n]={});let s=e[a];void 0===s&&(s=new ZI(n+"_"+a,i),e[a]=s,l.push(s)),o=this.getNodeUniform(r,t),s.addUniform(o)}s.uniformGPU=o}return r}}let aL=null,lL=null;class uL{constructor(e={}){this.parameters=Object.assign({},e),this.data=new WeakMap,this.renderer=null,this.domElement=null,this.timestampQueryPool={render:null,compute:null},this.trackTimestamp=!0===e.trackTimestamp}async init(e){this.renderer=e}get coordinateSystem(){}beginRender(){}finishRender(){}beginCompute(){}finishCompute(){}draw(){}compute(){}createProgram(){}destroyProgram(){}createBindings(){}updateBindings(){}updateBinding(){}createRenderPipeline(){}createComputePipeline(){}needsRenderUpdate(){}getRenderCacheKey(){}createNodeBuilder(){}createSampler(){}destroySampler(){}createDefaultTexture(){}createTexture(){}updateTexture(){}generateMipmaps(){}destroyTexture(){}async copyTextureToBuffer(){}copyTextureToTexture(){}copyFramebufferToTexture(){}createAttribute(){}createIndexAttribute(){}createStorageAttribute(){}updateAttribute(){}destroyAttribute(){}getContext(){}updateSize(){}updateViewport(){}getTimestampUID(e){const t=this.get(e);let n=!0===e.isComputeNode?"c":"r";return n+=":"+t.frameCalls+":"+e.id,n}isOccluded(){}async resolveTimestampsAsync(e="render"){if(!this.trackTimestamp)return void js("WebGPURenderer: Timestamp tracking is disabled.");const t=this.timestampQueryPool[e];if(!t)return void js(`WebGPURenderer: No timestamp query pool for type '${e}' found.`);const n=await t.resolveQueriesAsync();return this.renderer.info[e].timestamp=n,n}async waitForGPU(){}async getArrayBufferAsync(){}async hasFeatureAsync(){}hasFeature(){}getMaxAnisotropy(){}getDrawingBufferSize(){return aL=aL||new Cs,this.renderer.getDrawingBufferSize(aL)}setScissorTest(){}getClearColor(){const e=this.renderer;return lL=lL||new yN,e.getClearColor(lL),lL.getRGB(lL),lL}getDomElement(){let e=this.domElement;return null===e&&(e=void 0!==this.parameters.canvas?this.parameters.canvas:Is(),"setAttribute"in e&&e.setAttribute("data-engine",`three.js r${mi} webgpu`),this.domElement=e),e}set(e,t){this.data.set(e,t)}get(e){let t=this.data.get(e);return void 0===t&&(t={},this.data.set(e,t)),t}has(e){return this.data.has(e)}delete(e){this.data.delete(e)}dispose(){}}let cL,dL,hL=0;class fL{constructor(e,t){this.buffers=[e.bufferGPU,t],this.type=e.type,this.bufferType=e.bufferType,this.pbo=e.pbo,this.byteLength=e.byteLength,this.bytesPerElement=e.BYTES_PER_ELEMENT,this.version=e.version,this.isInteger=e.isInteger,this.activeBufferIndex=0,this.baseId=e.id}get id(){return`${this.baseId}|${this.activeBufferIndex}`}get bufferGPU(){return this.buffers[this.activeBufferIndex]}get transformBuffer(){return this.buffers[1^this.activeBufferIndex]}switchBuffers(){this.activeBufferIndex^=1}}class pL{constructor(e){this.backend=e}createAttribute(e,t){const n=this.backend,{gl:i}=n,r=e.array,s=e.usage||i.STATIC_DRAW,o=e.isInterleavedBufferAttribute?e.data:e,a=n.get(o);let l,u=a.bufferGPU;if(void 0===u&&(u=this._createBuffer(i,t,r,s),a.bufferGPU=u,a.bufferType=t,a.version=o.version),r instanceof Float32Array)l=i.FLOAT;else if("undefined"!=typeof Float16Array&&r instanceof Float16Array)l=i.HALF_FLOAT;else if(r instanceof Uint16Array)l=e.isFloat16BufferAttribute?i.HALF_FLOAT:i.UNSIGNED_SHORT;else if(r instanceof Int16Array)l=i.SHORT;else if(r instanceof Uint32Array)l=i.UNSIGNED_INT;else if(r instanceof Int32Array)l=i.INT;else if(r instanceof Int8Array)l=i.BYTE;else if(r instanceof Uint8Array)l=i.UNSIGNED_BYTE;else{if(!(r instanceof Uint8ClampedArray))throw new Error("THREE.WebGLBackend: Unsupported buffer data format: "+r);l=i.UNSIGNED_BYTE}let c={bufferGPU:u,bufferType:t,type:l,byteLength:r.byteLength,bytesPerElement:r.BYTES_PER_ELEMENT,version:e.version,pbo:e.pbo,isInteger:l===i.INT||l===i.UNSIGNED_INT||e.gpuType===Zi,id:hL++};if(e.isStorageBufferAttribute||e.isStorageInstancedBufferAttribute){const e=this._createBuffer(i,t,r,s);c=new fL(c,e)}n.set(e,c)}updateAttribute(e){const t=this.backend,{gl:n}=t,i=e.array,r=e.isInterleavedBufferAttribute?e.data:e,s=t.get(r),o=s.bufferType,a=e.isInterleavedBufferAttribute?e.data.updateRanges:e.updateRanges;if(n.bindBuffer(o,s.bufferGPU),0===a.length)n.bufferSubData(o,0,i);else{for(let e=0,t=a.length;e<t;e++){const t=a[e];n.bufferSubData(o,t.start*i.BYTES_PER_ELEMENT,i,t.start,t.count)}r.clearUpdateRanges()}n.bindBuffer(o,null),s.version=r.version}destroyAttribute(e){const t=this.backend,{gl:n}=t;e.isInterleavedBufferAttribute&&t.delete(e.data);const i=t.get(e);n.deleteBuffer(i.bufferGPU),t.delete(e)}async getArrayBufferAsync(e){const t=this.backend,{gl:n}=t,i=e.isInterleavedBufferAttribute?e.data:e,{bufferGPU:r}=t.get(i),s=e.array,o=s.byteLength;n.bindBuffer(n.COPY_READ_BUFFER,r);const a=n.createBuffer();n.bindBuffer(n.COPY_WRITE_BUFFER,a),n.bufferData(n.COPY_WRITE_BUFFER,o,n.STREAM_READ),n.copyBufferSubData(n.COPY_READ_BUFFER,n.COPY_WRITE_BUFFER,0,0,o),await t.utils._clientWaitAsync();const l=new e.array.constructor(s.length);return n.bindBuffer(n.COPY_WRITE_BUFFER,a),n.getBufferSubData(n.COPY_WRITE_BUFFER,0,l),n.deleteBuffer(a),n.bindBuffer(n.COPY_READ_BUFFER,null),n.bindBuffer(n.COPY_WRITE_BUFFER,null),l.buffer}_createBuffer(e,t,n,i){const r=e.createBuffer();return e.bindBuffer(t,r),e.bufferData(t,n,i),e.bindBuffer(t,null),r}}class gL{constructor(e){this.backend=e,this.gl=this.backend.gl,this.enabled={},this.currentFlipSided=null,this.currentCullFace=null,this.currentProgram=null,this.currentBlendingEnabled=!1,this.currentBlending=null,this.currentBlendSrc=null,this.currentBlendDst=null,this.currentBlendSrcAlpha=null,this.currentBlendDstAlpha=null,this.currentPremultipledAlpha=null,this.currentPolygonOffsetFactor=null,this.currentPolygonOffsetUnits=null,this.currentColorMask=null,this.currentDepthFunc=null,this.currentDepthMask=null,this.currentStencilFunc=null,this.currentStencilRef=null,this.currentStencilFuncMask=null,this.currentStencilFail=null,this.currentStencilZFail=null,this.currentStencilZPass=null,this.currentStencilMask=null,this.currentLineWidth=null,this.currentClippingPlanes=0,this.currentVAO=null,this.currentIndex=null,this.currentBoundFramebuffers={},this.currentDrawbuffers=new WeakMap,this.maxTextures=this.gl.getParameter(this.gl.MAX_TEXTURE_IMAGE_UNITS),this.currentTextureSlot=null,this.currentBoundTextures={},this.currentBoundBufferBases={},this._init()}_init(){const e=this.gl;cL={[Mi]:e.FUNC_ADD,101:e.FUNC_SUBTRACT,102:e.FUNC_REVERSE_SUBTRACT},dL={[Ei]:e.ZERO,201:e.ONE,202:e.SRC_COLOR,[Ti]:e.SRC_ALPHA,210:e.SRC_ALPHA_SATURATE,208:e.DST_COLOR,206:e.DST_ALPHA,203:e.ONE_MINUS_SRC_COLOR,[Si]:e.ONE_MINUS_SRC_ALPHA,209:e.ONE_MINUS_DST_COLOR,207:e.ONE_MINUS_DST_ALPHA};const t=e.getParameter(e.SCISSOR_BOX),n=e.getParameter(e.VIEWPORT);this.currentScissor=(new Js).fromArray(t),this.currentViewport=(new Js).fromArray(n),this._tempVec4=new Js}enable(e){const{enabled:t}=this;!0!==t[e]&&(this.gl.enable(e),t[e]=!0)}disable(e){const{enabled:t}=this;!1!==t[e]&&(this.gl.disable(e),t[e]=!1)}setFlipSided(e){if(this.currentFlipSided!==e){const{gl:t}=this;e?t.frontFace(t.CW):t.frontFace(t.CCW),this.currentFlipSided=e}}setCullFace(e){const{gl:t}=this;0!==e?(this.enable(t.CULL_FACE),e!==this.currentCullFace&&(1===e?t.cullFace(t.BACK):2===e?t.cullFace(t.FRONT):t.cullFace(t.FRONT_AND_BACK))):this.disable(t.CULL_FACE),this.currentCullFace=e}setLineWidth(e){const{currentLineWidth:t,gl:n}=this;e!==t&&(n.lineWidth(e),this.currentLineWidth=e)}setBlending(e,t,n,i,r,s,o,a){const{gl:l}=this;if(0!==e){if(!1===this.currentBlendingEnabled&&(this.enable(l.BLEND),this.currentBlendingEnabled=!0),5===e)r=r||t,s=s||n,o=o||i,t===this.currentBlendEquation&&r===this.currentBlendEquationAlpha||(l.blendEquationSeparate(cL[t],cL[r]),this.currentBlendEquation=t,this.currentBlendEquationAlpha=r),n===this.currentBlendSrc&&i===this.currentBlendDst&&s===this.currentBlendSrcAlpha&&o===this.currentBlendDstAlpha||(l.blendFuncSeparate(dL[n],dL[i],dL[s],dL[o]),this.currentBlendSrc=n,this.currentBlendDst=i,this.currentBlendSrcAlpha=s,this.currentBlendDstAlpha=o),this.currentBlending=e,this.currentPremultipledAlpha=!1;else if(e!==this.currentBlending||a!==this.currentPremultipledAlpha){if(this.currentBlendEquation===Mi&&this.currentBlendEquationAlpha===Mi||(l.blendEquation(l.FUNC_ADD),this.currentBlendEquation=Mi,this.currentBlendEquationAlpha=Mi),a)switch(e){case 1:l.blendFuncSeparate(l.ONE,l.ONE_MINUS_SRC_ALPHA,l.ONE,l.ONE_MINUS_SRC_ALPHA);break;case 2:l.blendFunc(l.ONE,l.ONE);break;case 3:l.blendFuncSeparate(l.ZERO,l.ONE_MINUS_SRC_COLOR,l.ZERO,l.ONE);break;case 4:l.blendFuncSeparate(l.DST_COLOR,l.ONE_MINUS_SRC_ALPHA,l.ZERO,l.ONE);break;default:console.error("THREE.WebGLState: Invalid blending: ",e)}else switch(e){case 1:l.blendFuncSeparate(l.SRC_ALPHA,l.ONE_MINUS_SRC_ALPHA,l.ONE,l.ONE_MINUS_SRC_ALPHA);break;case 2:l.blendFuncSeparate(l.SRC_ALPHA,l.ONE,l.ONE,l.ONE);break;case 3:console.error("THREE.WebGLState: SubtractiveBlending requires material.premultipliedAlpha = true");break;case 4:console.error("THREE.WebGLState: MultiplyBlending requires material.premultipliedAlpha = true");break;default:console.error("THREE.WebGLState: Invalid blending: ",e)}this.currentBlendSrc=null,this.currentBlendDst=null,this.currentBlendSrcAlpha=null,this.currentBlendDstAlpha=null,this.currentBlending=e,this.currentPremultipledAlpha=a}}else!0===this.currentBlendingEnabled&&(this.disable(l.BLEND),this.currentBlendingEnabled=!1)}setColorMask(e){this.currentColorMask!==e&&(this.gl.colorMask(e,e,e,e),this.currentColorMask=e)}setDepthTest(e){const{gl:t}=this;e?this.enable(t.DEPTH_TEST):this.disable(t.DEPTH_TEST)}setDepthMask(e){this.currentDepthMask!==e&&(this.gl.depthMask(e),this.currentDepthMask=e)}setDepthFunc(e){if(this.currentDepthFunc!==e){const{gl:t}=this;switch(e){case 0:t.depthFunc(t.NEVER);break;case 1:t.depthFunc(t.ALWAYS);break;case 2:t.depthFunc(t.LESS);break;case 3:default:t.depthFunc(t.LEQUAL);break;case 4:t.depthFunc(t.EQUAL);break;case 5:t.depthFunc(t.GEQUAL);break;case 6:t.depthFunc(t.GREATER);break;case 7:t.depthFunc(t.NOTEQUAL)}this.currentDepthFunc=e}}scissor(e,t,n,i){const r=this._tempVec4.set(e,t,n,i);if(!1===this.currentScissor.equals(r)){const{gl:e}=this;e.scissor(r.x,r.y,r.z,r.w),this.currentScissor.copy(r)}}viewport(e,t,n,i){const r=this._tempVec4.set(e,t,n,i);if(!1===this.currentViewport.equals(r)){const{gl:e}=this;e.viewport(r.x,r.y,r.z,r.w),this.currentViewport.copy(r)}}setScissorTest(e){const t=this.gl;e?t.enable(t.SCISSOR_TEST):t.disable(t.SCISSOR_TEST)}setStencilTest(e){const{gl:t}=this;e?this.enable(t.STENCIL_TEST):this.disable(t.STENCIL_TEST)}setStencilMask(e){this.currentStencilMask!==e&&(this.gl.stencilMask(e),this.currentStencilMask=e)}setStencilFunc(e,t,n){this.currentStencilFunc===e&&this.currentStencilRef===t&&this.currentStencilFuncMask===n||(this.gl.stencilFunc(e,t,n),this.currentStencilFunc=e,this.currentStencilRef=t,this.currentStencilFuncMask=n)}setStencilOp(e,t,n){this.currentStencilFail===e&&this.currentStencilZFail===t&&this.currentStencilZPass===n||(this.gl.stencilOp(e,t,n),this.currentStencilFail=e,this.currentStencilZFail=t,this.currentStencilZPass=n)}setMaterial(e,t,n){const{gl:i}=this;2===e.side?this.disable(i.CULL_FACE):this.enable(i.CULL_FACE);let r=1===e.side;t&&(r=!r),this.setFlipSided(r),1===e.blending&&!1===e.transparent?this.setBlending(0):this.setBlending(e.blending,e.blendEquation,e.blendSrc,e.blendDst,e.blendEquationAlpha,e.blendSrcAlpha,e.blendDstAlpha,e.premultipliedAlpha),this.setDepthFunc(e.depthFunc),this.setDepthTest(e.depthTest),this.setDepthMask(e.depthWrite),this.setColorMask(e.colorWrite);const s=e.stencilWrite;if(this.setStencilTest(s),s&&(this.setStencilMask(e.stencilWriteMask),this.setStencilFunc(e.stencilFunc,e.stencilRef,e.stencilFuncMask),this.setStencilOp(e.stencilFail,e.stencilZFail,e.stencilZPass)),this.setPolygonOffset(e.polygonOffset,e.polygonOffsetFactor,e.polygonOffsetUnits),!0===e.alphaToCoverage&&this.backend.renderer.samples>1?this.enable(i.SAMPLE_ALPHA_TO_COVERAGE):this.disable(i.SAMPLE_ALPHA_TO_COVERAGE),n>0&&this.currentClippingPlanes!==n){const e=12288;for(let t=0;t<8;t++)t<n?this.enable(e+t):this.disable(e+t)}}setPolygonOffset(e,t,n){const{gl:i}=this;e?(this.enable(i.POLYGON_OFFSET_FILL),this.currentPolygonOffsetFactor===t&&this.currentPolygonOffsetUnits===n||(i.polygonOffset(t,n),this.currentPolygonOffsetFactor=t,this.currentPolygonOffsetUnits=n)):this.disable(i.POLYGON_OFFSET_FILL)}useProgram(e){return this.currentProgram!==e&&(this.gl.useProgram(e),this.currentProgram=e,!0)}setVertexState(e,t=null){const n=this.gl;return(this.currentVAO!==e||this.currentIndex!==t)&&(n.bindVertexArray(e),null!==t&&n.bindBuffer(n.ELEMENT_ARRAY_BUFFER,t),this.currentVAO=e,this.currentIndex=t,!0)}resetVertexState(){const e=this.gl;e.bindVertexArray(null),e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null),this.currentVAO=null,this.currentIndex=null}bindFramebuffer(e,t){const{gl:n,currentBoundFramebuffers:i}=this;return i[e]!==t&&(n.bindFramebuffer(e,t),i[e]=t,e===n.DRAW_FRAMEBUFFER&&(i[n.FRAMEBUFFER]=t),e===n.FRAMEBUFFER&&(i[n.DRAW_FRAMEBUFFER]=t),!0)}drawBuffers(e,t){const{gl:n}=this;let i=[],r=!1;if(null!==e.textures){i=this.currentDrawbuffers.get(t),void 0===i&&(i=[],this.currentDrawbuffers.set(t,i));const s=e.textures;if(i.length!==s.length||i[0]!==n.COLOR_ATTACHMENT0){for(let e=0,t=s.length;e<t;e++)i[e]=n.COLOR_ATTACHMENT0+e;i.length=s.length,r=!0}}else i[0]!==n.BACK&&(i[0]=n.BACK,r=!0);r&&n.drawBuffers(i)}activeTexture(e){const{gl:t,currentTextureSlot:n,maxTextures:i}=this;void 0===e&&(e=t.TEXTURE0+i-1),n!==e&&(t.activeTexture(e),this.currentTextureSlot=e)}bindTexture(e,t,n){const{gl:i,currentTextureSlot:r,currentBoundTextures:s,maxTextures:o}=this;void 0===n&&(n=null===r?i.TEXTURE0+o-1:r);let a=s[n];void 0===a&&(a={type:void 0,texture:void 0},s[n]=a),a.type===e&&a.texture===t||(r!==n&&(i.activeTexture(n),this.currentTextureSlot=n),i.bindTexture(e,t),a.type=e,a.texture=t)}bindBufferBase(e,t,n){const{gl:i}=this,r=`${e}-${t}`;return this.currentBoundBufferBases[r]!==n&&(i.bindBufferBase(e,t,n),this.currentBoundBufferBases[r]=n,!0)}unbindTexture(){const{gl:e,currentTextureSlot:t,currentBoundTextures:n}=this,i=n[t];void 0!==i&&void 0!==i.type&&(e.bindTexture(i.type,null),i.type=void 0,i.texture=void 0)}}class mL{constructor(e){this.backend=e,this.gl=this.backend.gl,this.extensions=e.extensions}convert(e,t=""){const{gl:n,extensions:i}=this;let r;const s=ks.getTransfer(t);if(e===Gi)return n.UNSIGNED_BYTE;if(e===qi)return n.UNSIGNED_SHORT_4_4_4_4;if(e===_i)return n.UNSIGNED_SHORT_5_5_5_1;if(e===er)return n.UNSIGNED_INT_5_9_9_9_REV;if(e===tr)return n.UNSIGNED_INT_10F_11F_11F_REV;if(e===Vi)return n.BYTE;if(e===Wi)return n.SHORT;if(e===Qi)return n.UNSIGNED_SHORT;if(e===Zi)return n.INT;if(e===Yi)return n.UNSIGNED_INT;if(e===Ji)return n.FLOAT;if(e===Ki)return n.HALF_FLOAT;if(e===nr)return n.ALPHA;if(e===ir)return n.RGB;if(e===rr)return n.RGBA;if(e===sr)return n.DEPTH_COMPONENT;if(e===or)return n.DEPTH_STENCIL;if(e===ar)return n.RED;if(e===lr)return n.RED_INTEGER;if(e===ur)return n.RG;if(e===cr)return n.RG_INTEGER;if(e===dr)return n.RGBA_INTEGER;if(e===hr||e===fr||e===pr||e===gr)if(s===es){if(r=i.get("WEBGL_compressed_texture_s3tc_srgb"),null===r)return null;if(e===hr)return r.COMPRESSED_SRGB_S3TC_DXT1_EXT;if(e===fr)return r.COMPRESSED_SRGB_ALPHA_S3TC_DXT1_EXT;if(e===pr)return r.COMPRESSED_SRGB_ALPHA_S3TC_DXT3_EXT;if(e===gr)return r.COMPRESSED_SRGB_ALPHA_S3TC_DXT5_EXT}else{if(r=i.get("WEBGL_compressed_texture_s3tc"),null===r)return null;if(e===hr)return r.COMPRESSED_RGB_S3TC_DXT1_EXT;if(e===fr)return r.COMPRESSED_RGBA_S3TC_DXT1_EXT;if(e===pr)return r.COMPRESSED_RGBA_S3TC_DXT3_EXT;if(e===gr)return r.COMPRESSED_RGBA_S3TC_DXT5_EXT}if(e===mr||e===vr||e===Ar||e===xr){if(r=i.get("WEBGL_compressed_texture_pvrtc"),null===r)return null;if(e===mr)return r.COMPRESSED_RGB_PVRTC_4BPPV1_IMG;if(e===vr)return r.COMPRESSED_RGB_PVRTC_2BPPV1_IMG;if(e===Ar)return r.COMPRESSED_RGBA_PVRTC_4BPPV1_IMG;if(e===xr)return r.COMPRESSED_RGBA_PVRTC_2BPPV1_IMG}if(e===yr||e===br||e===wr){if(r=i.get("WEBGL_compressed_texture_etc"),null===r)return null;if(e===yr||e===br)return s===es?r.COMPRESSED_SRGB8_ETC2:r.COMPRESSED_RGB8_ETC2;if(e===wr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ETC2_EAC:r.COMPRESSED_RGBA8_ETC2_EAC}if(e===Cr||e===Mr||e===Er||e===Tr||e===Sr||e===Pr||e===Nr||e===Br||e===Dr||e===Ir||e===Lr||e===jr||e===Or||e===zr){if(r=i.get("WEBGL_compressed_texture_astc"),null===r)return null;if(e===Cr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_4x4_KHR:r.COMPRESSED_RGBA_ASTC_4x4_KHR;if(e===Mr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_5x4_KHR:r.COMPRESSED_RGBA_ASTC_5x4_KHR;if(e===Er)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_5x5_KHR:r.COMPRESSED_RGBA_ASTC_5x5_KHR;if(e===Tr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_6x5_KHR:r.COMPRESSED_RGBA_ASTC_6x5_KHR;if(e===Sr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_6x6_KHR:r.COMPRESSED_RGBA_ASTC_6x6_KHR;if(e===Pr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_8x5_KHR:r.COMPRESSED_RGBA_ASTC_8x5_KHR;if(e===Nr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_8x6_KHR:r.COMPRESSED_RGBA_ASTC_8x6_KHR;if(e===Br)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_8x8_KHR:r.COMPRESSED_RGBA_ASTC_8x8_KHR;if(e===Dr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_10x5_KHR:r.COMPRESSED_RGBA_ASTC_10x5_KHR;if(e===Ir)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_10x6_KHR:r.COMPRESSED_RGBA_ASTC_10x6_KHR;if(e===Lr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_10x8_KHR:r.COMPRESSED_RGBA_ASTC_10x8_KHR;if(e===jr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_10x10_KHR:r.COMPRESSED_RGBA_ASTC_10x10_KHR;if(e===Or)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_12x10_KHR:r.COMPRESSED_RGBA_ASTC_12x10_KHR;if(e===zr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_12x12_KHR:r.COMPRESSED_RGBA_ASTC_12x12_KHR}if(e===Rr){if(r=i.get("EXT_texture_compression_bptc"),null===r)return null;if(e===Rr)return s===es?r.COMPRESSED_SRGB_ALPHA_BPTC_UNORM_EXT:r.COMPRESSED_RGBA_BPTC_UNORM_EXT}if(e===Hr||e===Ur||e===Xr||e===Gr){if(r=i.get("EXT_texture_compression_rgtc"),null===r)return null;if(e===Hr)return r.COMPRESSED_RED_RGTC1_EXT;if(e===Ur)return r.COMPRESSED_SIGNED_RED_RGTC1_EXT;if(e===Xr)return r.COMPRESSED_RED_GREEN_RGTC2_EXT;if(e===Gr)return r.COMPRESSED_SIGNED_RED_GREEN_RGTC2_EXT}return e===$i?n.UNSIGNED_INT_24_8:void 0!==n[e]?n[e]:null}_clientWaitAsync(){const{gl:e}=this,t=e.fenceSync(e.SYNC_GPU_COMMANDS_COMPLETE,0);return e.flush(),new Promise(((n,i)=>{!function r(){const s=e.clientWaitSync(t,e.SYNC_FLUSH_COMMANDS_BIT,0);if(s===e.WAIT_FAILED)return e.deleteSync(t),void i();s!==e.TIMEOUT_EXPIRED?(e.deleteSync(t),n()):requestAnimationFrame(r)}()}))}}let vL,AL,xL,yL=!1;class bL{constructor(e){this.backend=e,this.gl=e.gl,this.extensions=e.extensions,this.defaultTextures={},!1===yL&&(this._init(),yL=!0)}_init(){const e=this.gl;vL={[ji]:e.REPEAT,[Oi]:e.CLAMP_TO_EDGE,[zi]:e.MIRRORED_REPEAT},AL={[Ri]:e.NEAREST,[ki]:e.NEAREST_MIPMAP_NEAREST,[Fi]:e.NEAREST_MIPMAP_LINEAR,[Hi]:e.LINEAR,[Ui]:e.LINEAR_MIPMAP_NEAREST,[Xi]:e.LINEAR_MIPMAP_LINEAR},xL={512:e.NEVER,519:e.ALWAYS,[ns]:e.LESS,[is]:e.LEQUAL,514:e.EQUAL,518:e.GEQUAL,516:e.GREATER,517:e.NOTEQUAL}}getGLTextureType(e){const{gl:t}=this;let n;return n=!0===e.isCubeTexture?t.TEXTURE_CUBE_MAP:!0===e.isArrayTexture||!0===e.isDataArrayTexture||!0===e.isCompressedArrayTexture?t.TEXTURE_2D_ARRAY:!0===e.isData3DTexture?t.TEXTURE_3D:t.TEXTURE_2D,n}getInternalFormat(e,t,n,i,r=!1){const{gl:s,extensions:o}=this;if(null!==e){if(void 0!==s[e])return s[e];console.warn("THREE.WebGLRenderer: Attempt to use non-existing WebGL internal format '"+e+"'")}let a=t;if(t===s.RED&&(n===s.FLOAT&&(a=s.R32F),n===s.HALF_FLOAT&&(a=s.R16F),n===s.UNSIGNED_BYTE&&(a=s.R8),n===s.UNSIGNED_SHORT&&(a=s.R16),n===s.UNSIGNED_INT&&(a=s.R32UI),n===s.BYTE&&(a=s.R8I),n===s.SHORT&&(a=s.R16I),n===s.INT&&(a=s.R32I)),t===s.RED_INTEGER&&(n===s.UNSIGNED_BYTE&&(a=s.R8UI),n===s.UNSIGNED_SHORT&&(a=s.R16UI),n===s.UNSIGNED_INT&&(a=s.R32UI),n===s.BYTE&&(a=s.R8I),n===s.SHORT&&(a=s.R16I),n===s.INT&&(a=s.R32I)),t===s.RG&&(n===s.FLOAT&&(a=s.RG32F),n===s.HALF_FLOAT&&(a=s.RG16F),n===s.UNSIGNED_BYTE&&(a=s.RG8),n===s.UNSIGNED_SHORT&&(a=s.RG16),n===s.UNSIGNED_INT&&(a=s.RG32UI),n===s.BYTE&&(a=s.RG8I),n===s.SHORT&&(a=s.RG16I),n===s.INT&&(a=s.RG32I)),t===s.RG_INTEGER&&(n===s.UNSIGNED_BYTE&&(a=s.RG8UI),n===s.UNSIGNED_SHORT&&(a=s.RG16UI),n===s.UNSIGNED_INT&&(a=s.RG32UI),n===s.BYTE&&(a=s.RG8I),n===s.SHORT&&(a=s.RG16I),n===s.INT&&(a=s.RG32I)),t===s.RGB){const e=r?$r:ks.getTransfer(i);n===s.FLOAT&&(a=s.RGB32F),n===s.HALF_FLOAT&&(a=s.RGB16F),n===s.UNSIGNED_BYTE&&(a=s.RGB8),n===s.UNSIGNED_SHORT&&(a=s.RGB16),n===s.UNSIGNED_INT&&(a=s.RGB32UI),n===s.BYTE&&(a=s.RGB8I),n===s.SHORT&&(a=s.RGB16I),n===s.INT&&(a=s.RGB32I),n===s.UNSIGNED_BYTE&&(a=e===es?s.SRGB8:s.RGB8),n===s.UNSIGNED_SHORT_5_6_5&&(a=s.RGB565),n===s.UNSIGNED_SHORT_5_5_5_1&&(a=s.RGB5_A1),n===s.UNSIGNED_SHORT_4_4_4_4&&(a=s.RGB4),n===s.UNSIGNED_INT_5_9_9_9_REV&&(a=s.RGB9_E5),n===s.UNSIGNED_INT_10F_11F_11F_REV&&(a=s.R11F_G11F_B10F)}if(t===s.RGB_INTEGER&&(n===s.UNSIGNED_BYTE&&(a=s.RGB8UI),n===s.UNSIGNED_SHORT&&(a=s.RGB16UI),n===s.UNSIGNED_INT&&(a=s.RGB32UI),n===s.BYTE&&(a=s.RGB8I),n===s.SHORT&&(a=s.RGB16I),n===s.INT&&(a=s.RGB32I)),t===s.RGBA){const e=r?$r:ks.getTransfer(i);n===s.FLOAT&&(a=s.RGBA32F),n===s.HALF_FLOAT&&(a=s.RGBA16F),n===s.UNSIGNED_BYTE&&(a=s.RGBA8),n===s.UNSIGNED_SHORT&&(a=s.RGBA16),n===s.UNSIGNED_INT&&(a=s.RGBA32UI),n===s.BYTE&&(a=s.RGBA8I),n===s.SHORT&&(a=s.RGBA16I),n===s.INT&&(a=s.RGBA32I),n===s.UNSIGNED_BYTE&&(a=e===es?s.SRGB8_ALPHA8:s.RGBA8),n===s.UNSIGNED_SHORT_4_4_4_4&&(a=s.RGBA4),n===s.UNSIGNED_SHORT_5_5_5_1&&(a=s.RGB5_A1)}return t===s.RGBA_INTEGER&&(n===s.UNSIGNED_BYTE&&(a=s.RGBA8UI),n===s.UNSIGNED_SHORT&&(a=s.RGBA16UI),n===s.UNSIGNED_INT&&(a=s.RGBA32UI),n===s.BYTE&&(a=s.RGBA8I),n===s.SHORT&&(a=s.RGBA16I),n===s.INT&&(a=s.RGBA32I)),t===s.DEPTH_COMPONENT&&(n===s.UNSIGNED_SHORT&&(a=s.DEPTH_COMPONENT16),n===s.UNSIGNED_INT&&(a=s.DEPTH_COMPONENT24),n===s.FLOAT&&(a=s.DEPTH_COMPONENT32F)),t===s.DEPTH_STENCIL&&n===s.UNSIGNED_INT_24_8&&(a=s.DEPTH24_STENCIL8),a!==s.R16F&&a!==s.R32F&&a!==s.RG16F&&a!==s.RG32F&&a!==s.RGBA16F&&a!==s.RGBA32F||o.get("EXT_color_buffer_float"),a}setTextureParameters(e,t){const{gl:n,extensions:i,backend:r}=this,s=ks.getPrimaries(ks.workingColorSpace),o=t.colorSpace===Kr?null:ks.getPrimaries(t.colorSpace),a=t.colorSpace===Kr||s===o?n.NONE:n.BROWSER_DEFAULT_WEBGL;n.pixelStorei(n.UNPACK_FLIP_Y_WEBGL,t.flipY),n.pixelStorei(n.UNPACK_PREMULTIPLY_ALPHA_WEBGL,t.premultiplyAlpha),n.pixelStorei(n.UNPACK_ALIGNMENT,t.unpackAlignment),n.pixelStorei(n.UNPACK_COLORSPACE_CONVERSION_WEBGL,a),n.texParameteri(e,n.TEXTURE_WRAP_S,vL[t.wrapS]),n.texParameteri(e,n.TEXTURE_WRAP_T,vL[t.wrapT]),e!==n.TEXTURE_3D&&e!==n.TEXTURE_2D_ARRAY||t.isArrayTexture||n.texParameteri(e,n.TEXTURE_WRAP_R,vL[t.wrapR]),n.texParameteri(e,n.TEXTURE_MAG_FILTER,AL[t.magFilter]);const l=void 0!==t.mipmaps&&t.mipmaps.length>0,u=t.minFilter===Hi&&l?Xi:t.minFilter;if(n.texParameteri(e,n.TEXTURE_MIN_FILTER,AL[u]),t.compareFunction&&(n.texParameteri(e,n.TEXTURE_COMPARE_MODE,n.COMPARE_REF_TO_TEXTURE),n.texParameteri(e,n.TEXTURE_COMPARE_FUNC,xL[t.compareFunction])),!0===i.has("EXT_texture_filter_anisotropic")){if(t.magFilter===Ri)return;if(t.minFilter!==Fi&&t.minFilter!==Xi)return;if(t.type===Ji&&!1===i.has("OES_texture_float_linear"))return;if(t.anisotropy>1){const s=i.get("EXT_texture_filter_anisotropic");n.texParameterf(e,s.TEXTURE_MAX_ANISOTROPY_EXT,Math.min(t.anisotropy,r.getMaxAnisotropy()))}}}createDefaultTexture(e){const{gl:t,backend:n,defaultTextures:i}=this,r=this.getGLTextureType(e);let s=i[r];void 0===s&&(s=t.createTexture(),n.state.bindTexture(r,s),t.texParameteri(r,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(r,t.TEXTURE_MAG_FILTER,t.NEAREST),i[r]=s),n.set(e,{textureGPU:s,glTextureType:r,isDefault:!0})}createTexture(e,t){const{gl:n,backend:i}=this,{levels:r,width:s,height:o,depth:a}=t,l=i.utils.convert(e.format,e.colorSpace),u=i.utils.convert(e.type),c=this.getInternalFormat(e.internalFormat,l,u,e.colorSpace,e.isVideoTexture),d=n.createTexture(),h=this.getGLTextureType(e);i.state.bindTexture(h,d),this.setTextureParameters(h,e),e.isArrayTexture||e.isDataArrayTexture||e.isCompressedArrayTexture?n.texStorage3D(n.TEXTURE_2D_ARRAY,r,c,s,o,a):e.isData3DTexture?n.texStorage3D(n.TEXTURE_3D,r,c,s,o,a):e.isVideoTexture||n.texStorage2D(h,r,c,s,o),i.set(e,{textureGPU:d,glTextureType:h,glFormat:l,glType:u,glInternalFormat:c})}copyBufferToTexture(e,t){const{gl:n,backend:i}=this,{textureGPU:r,glTextureType:s,glFormat:o,glType:a}=i.get(t),{width:l,height:u}=t.source.data;n.bindBuffer(n.PIXEL_UNPACK_BUFFER,e),i.state.bindTexture(s,r),n.pixelStorei(n.UNPACK_FLIP_Y_WEBGL,!1),n.pixelStorei(n.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!1),n.texSubImage2D(s,0,0,0,l,u,o,a,0),n.bindBuffer(n.PIXEL_UNPACK_BUFFER,null),i.state.unbindTexture()}updateTexture(e,t){const{gl:n}=this,{width:i,height:r}=t,{textureGPU:s,glTextureType:o,glFormat:a,glType:l,glInternalFormat:u}=this.backend.get(e);if(!e.isRenderTargetTexture&&void 0!==s)if(this.backend.state.bindTexture(o,s),this.setTextureParameters(o,e),e.isCompressedTexture){const i=e.mipmaps,r=t.image;for(let t=0;t<i.length;t++){const s=i[t];e.isCompressedArrayTexture?e.format!==n.RGBA?null!==a?n.compressedTexSubImage3D(n.TEXTURE_2D_ARRAY,t,0,0,0,s.width,s.height,r.depth,a,s.data):console.warn("THREE.WebGLRenderer: Attempt to load unsupported compressed texture format in .uploadTexture()"):n.texSubImage3D(n.TEXTURE_2D_ARRAY,t,0,0,0,s.width,s.height,r.depth,a,l,s.data):null!==a?n.compressedTexSubImage2D(n.TEXTURE_2D,t,0,0,s.width,s.height,a,s.data):console.warn("Unsupported compressed texture format")}}else if(e.isCubeTexture){const s=t.images,o=e.mipmaps;for(let e=0;e<6;e++){const t=wL(s[e]);n.texSubImage2D(n.TEXTURE_CUBE_MAP_POSITIVE_X+e,0,0,0,i,r,a,l,t);for(let t=0;t<o.length;t++){const i=wL(o[t].images[e]);n.texSubImage2D(n.TEXTURE_CUBE_MAP_POSITIVE_X+e,t+1,0,0,i.width,i.height,a,l,i)}}}else if(e.isDataArrayTexture||e.isArrayTexture){const i=t.image;if(e.layerUpdates.size>0){const t=zc(i.width,i.height,e.format,e.type);for(const r of e.layerUpdates){const e=i.data.subarray(r*t/i.data.BYTES_PER_ELEMENT,(r+1)*t/i.data.BYTES_PER_ELEMENT);n.texSubImage3D(n.TEXTURE_2D_ARRAY,0,0,0,r,i.width,i.height,1,a,l,e)}e.clearLayerUpdates()}else n.texSubImage3D(n.TEXTURE_2D_ARRAY,0,0,0,0,i.width,i.height,i.depth,a,l,i.data)}else if(e.isData3DTexture){const e=t.image;n.texSubImage3D(n.TEXTURE_3D,0,0,0,0,e.width,e.height,e.depth,a,l,e.data)}else if(e.isVideoTexture)e.update(),n.texImage2D(o,0,u,a,l,t.image);else{const s=e.mipmaps;if(s.length>0)for(let e=0,t=s.length;e<t;e++){const t=s[e],i=wL(t);n.texSubImage2D(o,e,0,0,t.width,t.height,a,l,i)}else{const e=wL(t.image);n.texSubImage2D(o,0,0,0,i,r,a,l,e)}}}generateMipmaps(e){const{gl:t,backend:n}=this,{textureGPU:i,glTextureType:r}=n.get(e);n.state.bindTexture(r,i),t.generateMipmap(r)}deallocateRenderBuffers(e){const{gl:t,backend:n}=this;if(e){const i=n.get(e);if(i.renderBufferStorageSetup=void 0,i.framebuffers){for(const e in i.framebuffers)t.deleteFramebuffer(i.framebuffers[e]);delete i.framebuffers}if(i.depthRenderbuffer&&(t.deleteRenderbuffer(i.depthRenderbuffer),delete i.depthRenderbuffer),i.stencilRenderbuffer&&(t.deleteRenderbuffer(i.stencilRenderbuffer),delete i.stencilRenderbuffer),i.msaaFrameBuffer&&(t.deleteFramebuffer(i.msaaFrameBuffer),delete i.msaaFrameBuffer),i.msaaRenderbuffers){for(let e=0;e<i.msaaRenderbuffers.length;e++)t.deleteRenderbuffer(i.msaaRenderbuffers[e]);delete i.msaaRenderbuffers}}}destroyTexture(e){const{gl:t,backend:n}=this,{textureGPU:i,renderTarget:r}=n.get(e);this.deallocateRenderBuffers(r),t.deleteTexture(i),n.delete(e)}copyTextureToTexture(e,t,n=null,i=null,r=0,s=0){const{gl:o,backend:a}=this,{state:l}=this.backend,{textureGPU:u,glTextureType:c,glType:d,glFormat:h}=a.get(t);let f,p,g,m,v,A,x,y,b;l.bindTexture(c,u);const w=e.isCompressedTexture?e.mipmaps[s]:e.image;if(null!==n)f=n.max.x-n.min.x,p=n.max.y-n.min.y,g=n.isBox3?n.max.z-n.min.z:1,m=n.min.x,v=n.min.y,A=n.isBox3?n.min.z:0;else{const t=Math.pow(2,-r);f=Math.floor(w.width*t),p=Math.floor(w.height*t),g=e.isDataArrayTexture||e.isArrayTexture?w.depth:e.isData3DTexture?Math.floor(w.depth*t):1,m=0,v=0,A=0}null!==i?(x=i.x,y=i.y,b=i.z):(x=0,y=0,b=0),o.pixelStorei(o.UNPACK_FLIP_Y_WEBGL,t.flipY),o.pixelStorei(o.UNPACK_PREMULTIPLY_ALPHA_WEBGL,t.premultiplyAlpha),o.pixelStorei(o.UNPACK_ALIGNMENT,t.unpackAlignment);const C=o.getParameter(o.UNPACK_ROW_LENGTH),M=o.getParameter(o.UNPACK_IMAGE_HEIGHT),E=o.getParameter(o.UNPACK_SKIP_PIXELS),T=o.getParameter(o.UNPACK_SKIP_ROWS),S=o.getParameter(o.UNPACK_SKIP_IMAGES);o.pixelStorei(o.UNPACK_ROW_LENGTH,w.width),o.pixelStorei(o.UNPACK_IMAGE_HEIGHT,w.height),o.pixelStorei(o.UNPACK_SKIP_PIXELS,m),o.pixelStorei(o.UNPACK_SKIP_ROWS,v),o.pixelStorei(o.UNPACK_SKIP_IMAGES,A);const P=t.isDataArrayTexture||t.isData3DTexture||t.isArrayTexture;if(e.isRenderTargetTexture||e.isDepthTexture){const n=a.get(e),i=a.get(t),r=a.get(n.renderTarget),s=a.get(i.renderTarget),u=r.framebuffers[n.cacheKey],c=s.framebuffers[i.cacheKey];l.bindFramebuffer(o.READ_FRAMEBUFFER,u),l.bindFramebuffer(o.DRAW_FRAMEBUFFER,c);let d=o.COLOR_BUFFER_BIT;e.isDepthTexture&&(d=o.DEPTH_BUFFER_BIT),o.blitFramebuffer(m,v,f,p,x,y,f,p,d,o.NEAREST),l.bindFramebuffer(o.READ_FRAMEBUFFER,null),l.bindFramebuffer(o.DRAW_FRAMEBUFFER,null)}else P?e.isDataTexture||e.isData3DTexture?o.texSubImage3D(c,s,x,y,b,f,p,g,h,d,w.data):t.isCompressedArrayTexture?o.compressedTexSubImage3D(c,s,x,y,b,f,p,g,h,w.data):o.texSubImage3D(c,s,x,y,b,f,p,g,h,d,w):e.isDataTexture?o.texSubImage2D(c,s,x,y,f,p,h,d,w.data):e.isCompressedTexture?o.compressedTexSubImage2D(c,s,x,y,w.width,w.height,h,w.data):o.texSubImage2D(c,s,x,y,f,p,h,d,w);o.pixelStorei(o.UNPACK_ROW_LENGTH,C),o.pixelStorei(o.UNPACK_IMAGE_HEIGHT,M),o.pixelStorei(o.UNPACK_SKIP_PIXELS,E),o.pixelStorei(o.UNPACK_SKIP_ROWS,T),o.pixelStorei(o.UNPACK_SKIP_IMAGES,S),0===s&&t.generateMipmaps&&o.generateMipmap(c),l.unbindTexture()}copyFramebufferToTexture(e,t,n){const{gl:i}=this,{state:r}=this.backend,{textureGPU:s}=this.backend.get(e),{x:o,y:a,z:l,w:u}=n,c=!0===e.isDepthTexture||t.renderTarget&&t.renderTarget.samples>0,d=t.renderTarget?t.renderTarget.height:this.backend.getDrawingBufferSize().y;if(c){const n=0!==o||0!==a;let c,h;if(!0===e.isDepthTexture?(c=i.DEPTH_BUFFER_BIT,h=i.DEPTH_ATTACHMENT,t.stencil&&(c|=i.STENCIL_BUFFER_BIT)):(c=i.COLOR_BUFFER_BIT,h=i.COLOR_ATTACHMENT0),n){const e=this.backend.get(t.renderTarget),n=e.framebuffers[t.getCacheKey()],h=e.msaaFrameBuffer;r.bindFramebuffer(i.DRAW_FRAMEBUFFER,n),r.bindFramebuffer(i.READ_FRAMEBUFFER,h);const f=d-a-u;i.blitFramebuffer(o,f,o+l,f+u,o,f,o+l,f+u,c,i.NEAREST),r.bindFramebuffer(i.READ_FRAMEBUFFER,n),r.bindTexture(i.TEXTURE_2D,s),i.copyTexSubImage2D(i.TEXTURE_2D,0,0,0,o,f,l,u),r.unbindTexture()}else{const e=i.createFramebuffer();r.bindFramebuffer(i.DRAW_FRAMEBUFFER,e),i.framebufferTexture2D(i.DRAW_FRAMEBUFFER,h,i.TEXTURE_2D,s,0),i.blitFramebuffer(0,0,l,u,0,0,l,u,c,i.NEAREST),i.deleteFramebuffer(e)}}else r.bindTexture(i.TEXTURE_2D,s),i.copyTexSubImage2D(i.TEXTURE_2D,0,0,0,o,d-u-a,l,u),r.unbindTexture();e.generateMipmaps&&this.generateMipmaps(e),this.backend._setFramebuffer(t)}setupRenderBufferStorage(e,t,n,i=!1){const{gl:r}=this,s=t.renderTarget,{depthTexture:o,depthBuffer:a,stencilBuffer:l,width:u,height:c}=s;if(r.bindRenderbuffer(r.RENDERBUFFER,e),a&&!l){let t=r.DEPTH_COMPONENT24;if(!0===i){this.extensions.get("WEBGL_multisampled_render_to_texture").renderbufferStorageMultisampleEXT(r.RENDERBUFFER,s.samples,t,u,c)}else n>0?(o&&o.isDepthTexture&&o.type===r.FLOAT&&(t=r.DEPTH_COMPONENT32F),r.renderbufferStorageMultisample(r.RENDERBUFFER,n,t,u,c)):r.renderbufferStorage(r.RENDERBUFFER,t,u,c);r.framebufferRenderbuffer(r.FRAMEBUFFER,r.DEPTH_ATTACHMENT,r.RENDERBUFFER,e)}else a&&l&&(n>0?r.renderbufferStorageMultisample(r.RENDERBUFFER,n,r.DEPTH24_STENCIL8,u,c):r.renderbufferStorage(r.RENDERBUFFER,r.DEPTH_STENCIL,u,c),r.framebufferRenderbuffer(r.FRAMEBUFFER,r.DEPTH_STENCIL_ATTACHMENT,r.RENDERBUFFER,e));r.bindRenderbuffer(r.RENDERBUFFER,null)}async copyTextureToBuffer(e,t,n,i,r,s){const{backend:o,gl:a}=this,{textureGPU:l,glFormat:u,glType:c}=this.backend.get(e),d=a.createFramebuffer();a.bindFramebuffer(a.READ_FRAMEBUFFER,d);const h=e.isCubeTexture?a.TEXTURE_CUBE_MAP_POSITIVE_X+s:a.TEXTURE_2D;a.framebufferTexture2D(a.READ_FRAMEBUFFER,a.COLOR_ATTACHMENT0,h,l,0);const f=this._getTypedArrayType(c),p=i*r*this._getBytesPerTexel(c,u),g=a.createBuffer();a.bindBuffer(a.PIXEL_PACK_BUFFER,g),a.bufferData(a.PIXEL_PACK_BUFFER,p,a.STREAM_READ),a.readPixels(t,n,i,r,u,c,0),a.bindBuffer(a.PIXEL_PACK_BUFFER,null),await o.utils._clientWaitAsync();const m=new f(p/f.BYTES_PER_ELEMENT);return a.bindBuffer(a.PIXEL_PACK_BUFFER,g),a.getBufferSubData(a.PIXEL_PACK_BUFFER,0,m),a.bindBuffer(a.PIXEL_PACK_BUFFER,null),a.deleteFramebuffer(d),m}_getTypedArrayType(e){const{gl:t}=this;if(e===t.UNSIGNED_BYTE)return Uint8Array;if(e===t.UNSIGNED_SHORT_4_4_4_4)return Uint16Array;if(e===t.UNSIGNED_SHORT_5_5_5_1)return Uint16Array;if(e===t.UNSIGNED_SHORT_5_6_5)return Uint16Array;if(e===t.UNSIGNED_SHORT)return Uint16Array;if(e===t.UNSIGNED_INT)return Uint32Array;if(e===t.HALF_FLOAT)return Uint16Array;if(e===t.FLOAT)return Float32Array;throw new Error(`Unsupported WebGL type: ${e}`)}_getBytesPerTexel(e,t){const{gl:n}=this;let i=0;return e===n.UNSIGNED_BYTE&&(i=1),e!==n.UNSIGNED_SHORT_4_4_4_4&&e!==n.UNSIGNED_SHORT_5_5_5_1&&e!==n.UNSIGNED_SHORT_5_6_5&&e!==n.UNSIGNED_SHORT&&e!==n.HALF_FLOAT||(i=2),e!==n.UNSIGNED_INT&&e!==n.FLOAT||(i=4),t===n.RGBA?4*i:t===n.RGB?3*i:t===n.ALPHA?i:void 0}}function wL(e){return e.isDataTexture?e.image.data:"undefined"!=typeof HTMLImageElement&&e instanceof HTMLImageElement||"undefined"!=typeof HTMLCanvasElement&&e instanceof HTMLCanvasElement||"undefined"!=typeof ImageBitmap&&e instanceof ImageBitmap||"undefined"!=typeof OffscreenCanvas&&e instanceof OffscreenCanvas?e:e.data}class CL{constructor(e){this.backend=e,this.gl=this.backend.gl,this.availableExtensions=this.gl.getSupportedExtensions(),this.extensions={}}get(e){let t=this.extensions[e];return void 0===t&&(t=this.gl.getExtension(e),this.extensions[e]=t),t}has(e){return this.availableExtensions.includes(e)}}class ML{constructor(e){this.backend=e,this.maxAnisotropy=null}getMaxAnisotropy(){if(null!==this.maxAnisotropy)return this.maxAnisotropy;const e=this.backend.gl,t=this.backend.extensions;if(!0===t.has("EXT_texture_filter_anisotropic")){const n=t.get("EXT_texture_filter_anisotropic");this.maxAnisotropy=e.getParameter(n.MAX_TEXTURE_MAX_ANISOTROPY_EXT)}else this.maxAnisotropy=0;return this.maxAnisotropy}}const EL={WEBGL_multi_draw:"WEBGL_multi_draw",WEBGL_compressed_texture_astc:"texture-compression-astc",WEBGL_compressed_texture_etc:"texture-compression-etc2",WEBGL_compressed_texture_etc1:"texture-compression-etc1",WEBGL_compressed_texture_pvrtc:"texture-compression-pvrtc",WEBKIT_WEBGL_compressed_texture_pvrtc:"texture-compression-pvrtc",WEBGL_compressed_texture_s3tc:"texture-compression-bc",EXT_texture_compression_bptc:"texture-compression-bptc",EXT_disjoint_timer_query_webgl2:"timestamp-query",OVR_multiview2:"OVR_multiview2"};class TL{constructor(e){this.gl=e.gl,this.extensions=e.extensions,this.info=e.renderer.info,this.mode=null,this.index=0,this.type=null,this.object=null}render(e,t){const{gl:n,mode:i,object:r,type:s,info:o,index:a}=this;0!==a?n.drawElements(i,t,s,e):n.drawArrays(i,e,t),o.update(r,t,1)}renderInstances(e,t,n){const{gl:i,mode:r,type:s,index:o,object:a,info:l}=this;0!==n&&(0!==o?i.drawElementsInstanced(r,t,s,e,n):i.drawArraysInstanced(r,e,t,n),l.update(a,t,n))}renderMultiDraw(e,t,n){const{extensions:i,mode:r,object:s,info:o}=this;if(0===n)return;const a=i.get("WEBGL_multi_draw");if(null===a)for(let i=0;i<n;i++)this.render(e[i],t[i]);else{0!==this.index?a.multiDrawElementsWEBGL(r,t,0,this.type,e,0,n):a.multiDrawArraysWEBGL(r,e,0,t,0,n);let i=0;for(let e=0;e<n;e++)i+=t[e];o.update(s,i,1)}}renderMultiDrawInstances(e,t,n,i){const{extensions:r,mode:s,object:o,info:a}=this;if(0===n)return;const l=r.get("WEBGL_multi_draw");if(null===l)for(let r=0;r<n;r++)this.renderInstances(e[r],t[r],i[r]);else{0!==this.index?l.multiDrawElementsInstancedWEBGL(s,t,0,this.type,e,0,i,0,n):l.multiDrawArraysInstancedWEBGL(s,e,0,t,0,i,0,n);let r=0;for(let e=0;e<n;e++)r+=t[e]*i[e];a.update(o,r,1)}}}class SL{constructor(e=256){this.trackTimestamp=!0,this.maxQueries=e,this.currentQueryIndex=0,this.queryOffsets=new Map,this.isDisposed=!1,this.lastValue=0,this.pendingResolve=!1}allocateQueriesForContext(){}async resolveQueriesAsync(){}dispose(){}}class PL extends SL{constructor(e,t,n=2048){if(super(n),this.gl=e,this.type=t,this.ext=e.getExtension("EXT_disjoint_timer_query_webgl2")||e.getExtension("EXT_disjoint_timer_query"),!this.ext)return console.warn("EXT_disjoint_timer_query not supported; timestamps will be disabled."),void(this.trackTimestamp=!1);this.queries=[];for(let t=0;t<this.maxQueries;t++)this.queries.push(e.createQuery());this.activeQuery=null,this.queryStates=new Map}allocateQueriesForContext(e){if(!this.trackTimestamp)return null;if(this.currentQueryIndex+2>this.maxQueries)return js(`WebGPUTimestampQueryPool [${this.type}]: Maximum number of queries exceeded, when using trackTimestamp it is necessary to resolves the queries via renderer.resolveTimestampsAsync( THREE.TimestampQuery.${this.type.toUpperCase()} ).`),null;const t=this.currentQueryIndex;return this.currentQueryIndex+=2,this.queryStates.set(t,"inactive"),this.queryOffsets.set(e,t),t}beginQuery(e){if(!this.trackTimestamp||this.isDisposed)return;const t=this.queryOffsets.get(e);if(null==t)return;if(null!==this.activeQuery)return;const n=this.queries[t];if(n)try{"inactive"===this.queryStates.get(t)&&(this.gl.beginQuery(this.ext.TIME_ELAPSED_EXT,n),this.activeQuery=t,this.queryStates.set(t,"started"))}catch(e){console.error("Error in beginQuery:",e),this.activeQuery=null,this.queryStates.set(t,"inactive")}}endQuery(e){if(!this.trackTimestamp||this.isDisposed)return;const t=this.queryOffsets.get(e);if(null!=t&&this.activeQuery===t)try{this.gl.endQuery(this.ext.TIME_ELAPSED_EXT),this.queryStates.set(t,"ended"),this.activeQuery=null}catch(e){console.error("Error in endQuery:",e),this.queryStates.set(t,"inactive"),this.activeQuery=null}}async resolveQueriesAsync(){if(!this.trackTimestamp||this.pendingResolve)return this.lastValue;this.pendingResolve=!0;try{const e=[];for(const[t,n]of this.queryStates)if("ended"===n){const n=this.queries[t];e.push(this.resolveQuery(n))}if(0===e.length)return this.lastValue;const t=(await Promise.all(e)).reduce(((e,t)=>e+t),0);return this.lastValue=t,this.currentQueryIndex=0,this.queryOffsets.clear(),this.queryStates.clear(),this.activeQuery=null,t}catch(e){return console.error("Error resolving queries:",e),this.lastValue}finally{this.pendingResolve=!1}}async resolveQuery(e){return new Promise((t=>{if(this.isDisposed)return void t(this.lastValue);let n,i=!1;const r=e=>{i||(i=!0,n&&(clearTimeout(n),n=null),t(e))},s=()=>{if(this.isDisposed)r(this.lastValue);else try{if(this.gl.getParameter(this.ext.GPU_DISJOINT_EXT))return void r(this.lastValue);if(!this.gl.getQueryParameter(e,this.gl.QUERY_RESULT_AVAILABLE))return void(n=setTimeout(s,1));const i=this.gl.getQueryParameter(e,this.gl.QUERY_RESULT);t(Number(i)/1e6)}catch(e){console.error("Error checking query:",e),t(this.lastValue)}};s()}))}dispose(){if(!this.isDisposed&&(this.isDisposed=!0,this.trackTimestamp)){for(const e of this.queries)this.gl.deleteQuery(e);this.queries=[],this.queryStates.clear(),this.queryOffsets.clear(),this.lastValue=0,this.activeQuery=null}}}class NL extends uL{constructor(e={}){super(e),this.isWebGLBackend=!0,this.attributeUtils=null,this.extensions=null,this.capabilities=null,this.textureUtils=null,this.bufferRenderer=null,this.gl=null,this.state=null,this.utils=null,this.vaoCache={},this.transformFeedbackCache={},this.discard=!1,this.disjoint=null,this.parallel=null,this._currentContext=null,this._knownBindings=new WeakSet,this._supportsInvalidateFramebuffer="undefined"!=typeof navigator&&/OculusBrowser/g.test(navigator.userAgent),this._xrFramebuffer=null}init(e){super.init(e);const t=this.parameters,n={antialias:e.samples>0,alpha:!0,depth:e.depth,stencil:e.stencil},i=void 0!==t.context?t.context:e.domElement.getContext("webgl2",n);function r(t){t.preventDefault();const n={api:"WebGL",message:t.statusMessage||"Unknown reason",reason:null,originalEvent:t};e.onDeviceLost(n)}this._onContextLost=r,e.domElement.addEventListener("webglcontextlost",r,!1),this.gl=i,this.extensions=new CL(this),this.capabilities=new ML(this),this.attributeUtils=new pL(this),this.textureUtils=new bL(this),this.bufferRenderer=new TL(this),this.state=new gL(this),this.utils=new mL(this),this.extensions.get("EXT_color_buffer_float"),this.extensions.get("WEBGL_clip_cull_distance"),this.extensions.get("OES_texture_float_linear"),this.extensions.get("EXT_color_buffer_half_float"),this.extensions.get("WEBGL_multisampled_render_to_texture"),this.extensions.get("WEBGL_render_shared_exponent"),this.extensions.get("WEBGL_multi_draw"),this.extensions.get("OVR_multiview2"),this.disjoint=this.extensions.get("EXT_disjoint_timer_query_webgl2"),this.parallel=this.extensions.get("KHR_parallel_shader_compile")}get coordinateSystem(){return as}async getArrayBufferAsync(e){return await this.attributeUtils.getArrayBufferAsync(e)}async waitForGPU(){await this.utils._clientWaitAsync()}async makeXRCompatible(){!0!==this.gl.getContextAttributes().xrCompatible&&await this.gl.makeXRCompatible()}setXRTarget(e){this._xrFramebuffer=e}setXRRenderTargetTextures(e,t,n=null){const i=this.gl;if(this.set(e.texture,{textureGPU:t,glInternalFormat:i.RGBA8}),null!==n){const t=e.stencilBuffer?i.DEPTH24_STENCIL8:i.DEPTH_COMPONENT24;this.set(e.depthTexture,{textureGPU:n,glInternalFormat:t}),!0===this.extensions.has("WEBGL_multisampled_render_to_texture")&&!0===e._autoAllocateDepthBuffer&&!1===e.multiview&&console.warn("THREE.WebGLBackend: Render-to-texture extension was disabled because an external texture was provided"),e._autoAllocateDepthBuffer=!1}}initTimestampQuery(e,t){if(!this.disjoint||!this.trackTimestamp)return;this.timestampQueryPool[e]||(this.timestampQueryPool[e]=new PL(this.gl,e,2048));const n=this.timestampQueryPool[e];null!==n.allocateQueriesForContext(t)&&n.beginQuery(t)}prepareTimestampBuffer(e,t){if(!this.disjoint||!this.trackTimestamp)return;this.timestampQueryPool[e].endQuery(t)}getContext(){return this.gl}beginRender(e){const{state:t}=this,n=this.get(e);if(n.frameCalls=this.renderer.info.render.frameCalls,e.viewport)this.updateViewport(e);else{const{width:e,height:n}=this.getDrawingBufferSize();t.viewport(0,0,e,n)}if(e.scissor){const{x:n,y:i,width:r,height:s}=e.scissorValue;t.scissor(n,e.height-s-i,r,s)}this.initTimestampQuery(cs,this.getTimestampUID(e)),n.previousContext=this._currentContext,this._currentContext=e,this._setFramebuffer(e),this.clear(e.clearColor,e.clearDepth,e.clearStencil,e,!1);const i=e.occlusionQueryCount;i>0&&(n.currentOcclusionQueries=n.occlusionQueries,n.currentOcclusionQueryObjects=n.occlusionQueryObjects,n.lastOcclusionObject=null,n.occlusionQueries=new Array(i),n.occlusionQueryObjects=new Array(i),n.occlusionQueryIndex=0)}finishRender(e){const{gl:t,state:n}=this,i=this.get(e),r=i.previousContext;n.resetVertexState();const s=e.occlusionQueryCount;s>0&&(s>i.occlusionQueryIndex&&t.endQuery(t.ANY_SAMPLES_PASSED),this.resolveOccludedAsync(e));const o=e.textures;if(null!==o)for(let e=0;e<o.length;e++){const t=o[e];t.generateMipmaps&&this.generateMipmaps(t)}if(this._currentContext=r,this._resolveRenderTarget(e),null!==r)if(this._setFramebuffer(r),r.viewport)this.updateViewport(r);else{const{width:e,height:t}=this.getDrawingBufferSize();n.viewport(0,0,e,t)}this.prepareTimestampBuffer(cs,this.getTimestampUID(e))}resolveOccludedAsync(e){const t=this.get(e),{currentOcclusionQueries:n,currentOcclusionQueryObjects:i}=t;if(n&&i){const e=new WeakSet,{gl:r}=this;t.currentOcclusionQueryObjects=null,t.currentOcclusionQueries=null;const s=()=>{let o=0;for(let t=0;t<n.length;t++){const s=n[t];null!==s&&(r.getQueryParameter(s,r.QUERY_RESULT_AVAILABLE)&&(0===r.getQueryParameter(s,r.QUERY_RESULT)&&e.add(i[t]),n[t]=null,r.deleteQuery(s),o++))}o<n.length?requestAnimationFrame(s):t.occluded=e};s()}}isOccluded(e,t){const n=this.get(e);return n.occluded&&n.occluded.has(t)}updateViewport(e){const{state:t}=this,{x:n,y:i,width:r,height:s}=e.viewportValue;t.viewport(n,e.height-s-i,r,s)}setScissorTest(e){this.state.setScissorTest(e)}getClearColor(){const e=super.getClearColor();return e.r*=e.a,e.g*=e.a,e.b*=e.a,e}clear(e,t,n,i=null,r=!0,s=!0){const{gl:o,renderer:a}=this;if(null===i){i={textures:null,clearColorValue:this.getClearColor()}}let l=0;if(e&&(l|=o.COLOR_BUFFER_BIT),t&&(l|=o.DEPTH_BUFFER_BIT),n&&(l|=o.STENCIL_BUFFER_BIT),0!==l){let u;u=i.clearColorValue?i.clearColorValue:this.getClearColor();const c=a.getClearDepth(),d=a.getClearStencil();if(t&&this.state.setDepthMask(!0),null===i.textures)o.clearColor(u.r,u.g,u.b,u.a),o.clear(l);else{if(r&&this._setFramebuffer(i),e)for(let e=0;e<i.textures.length;e++)0===e?o.clearBufferfv(o.COLOR,e,[u.r,u.g,u.b,u.a]):o.clearBufferfv(o.COLOR,e,[0,0,0,1]);t&&n?o.clearBufferfi(o.DEPTH_STENCIL,0,c,d):t?o.clearBufferfv(o.DEPTH,0,[c]):n&&o.clearBufferiv(o.STENCIL,0,[d]),r&&s&&this._resolveRenderTarget(i)}}}beginCompute(e){const{state:t,gl:n}=this;this.get(e).frameCalls=this.renderer.info.compute.frameCalls,t.bindFramebuffer(n.FRAMEBUFFER,null),this.initTimestampQuery(us,this.getTimestampUID(e))}compute(e,t,n,i,r=null){const{state:s,gl:o}=this;!1===this.discard&&(o.enable(o.RASTERIZER_DISCARD),this.discard=!0);const{programGPU:a,transformBuffers:l,attributes:u}=this.get(i),c=this._getVaoKey(u),d=this.vaoCache[c];void 0===d?this.vaoCache[c]=this._createVao(u):s.setVertexState(d),s.useProgram(a),this._bindUniforms(n);const h=this._getTransformFeedback(l);o.bindTransformFeedback(o.TRANSFORM_FEEDBACK,h),o.beginTransformFeedback(o.POINTS),r=null!==r?r:t.count,Array.isArray(r)&&(js("WebGLBackend.compute(): The count parameter must be a single number, not an array."),r=r[0]),u[0].isStorageInstancedBufferAttribute?o.drawArraysInstanced(o.POINTS,0,1,r):o.drawArrays(o.POINTS,0,r),o.endTransformFeedback(),o.bindTransformFeedback(o.TRANSFORM_FEEDBACK,null);for(let e=0;e<l.length;e++){const t=l[e];t.pbo&&this.has(t.pbo)&&this.textureUtils.copyBufferToTexture(t.transformBuffer,t.pbo),t.switchBuffers()}}finishCompute(e){const t=this.gl;this.discard=!1,t.disable(t.RASTERIZER_DISCARD),this.prepareTimestampBuffer(us,this.getTimestampUID(e)),this._currentContext&&this._setFramebuffer(this._currentContext)}_isRenderCameraDepthArray(e){return e.depthTexture&&e.depthTexture.isArrayTexture&&e.camera.isArrayCamera}draw(e){const{object:t,pipeline:n,material:i,context:r,hardwareClippingPlanes:s}=e,{programGPU:o}=this.get(n),{gl:a,state:l}=this,u=this.get(r),c=e.getDrawParameters();if(null===c)return;this._bindUniforms(e.getBindings());const d=t.isMesh&&t.matrixWorld.determinant()<0;l.setMaterial(i,d,s),l.useProgram(o);const h=e.getAttributes(),f=this.get(h);let p=f.vaoGPU;if(void 0===p){const e=this._getVaoKey(h);p=this.vaoCache[e],void 0===p&&(p=this._createVao(h),this.vaoCache[e]=p,f.vaoGPU=p)}const g=e.getIndex(),m=null!==g?this.get(g).bufferGPU:null;l.setVertexState(p,m);const v=u.lastOcclusionObject;if(v!==t&&void 0!==v){if(null!==v&&!0===v.occlusionTest&&(a.endQuery(a.ANY_SAMPLES_PASSED),u.occlusionQueryIndex++),!0===t.occlusionTest){const e=a.createQuery();a.beginQuery(a.ANY_SAMPLES_PASSED,e),u.occlusionQueries[u.occlusionQueryIndex]=e,u.occlusionQueryObjects[u.occlusionQueryIndex]=t}u.lastOcclusionObject=t}const A=this.bufferRenderer;t.isPoints?A.mode=a.POINTS:t.isLineSegments?A.mode=a.LINES:t.isLine?A.mode=a.LINE_STRIP:t.isLineLoop?A.mode=a.LINE_LOOP:!0===i.wireframe?(l.setLineWidth(i.wireframeLinewidth*this.renderer.getPixelRatio()),A.mode=a.LINES):A.mode=a.TRIANGLES;const{vertexCount:x,instanceCount:y}=c;let{firstVertex:b}=c;if(A.object=t,null!==g){b*=g.array.BYTES_PER_ELEMENT;const e=this.get(g);A.index=g.count,A.type=e.type}else A.index=0;const w=()=>{t.isBatchedMesh?null!==t._multiDrawInstances?(js("THREE.WebGLBackend: renderMultiDrawInstances has been deprecated and will be removed in r184. Append to renderMultiDraw arguments and use indirection."),A.renderMultiDrawInstances(t._multiDrawStarts,t._multiDrawCounts,t._multiDrawCount,t._multiDrawInstances)):this.hasFeature("WEBGL_multi_draw")?A.renderMultiDraw(t._multiDrawStarts,t._multiDrawCounts,t._multiDrawCount):js("THREE.WebGLRenderer: WEBGL_multi_draw not supported."):y>1?A.renderInstances(b,x,y):A.render(b,x)};if(!0===e.camera.isArrayCamera&&e.camera.cameras.length>0&&!1===e.camera.isMultiViewCamera){const n=this.get(e.camera),i=e.camera.cameras,r=e.getBindingGroup("cameraIndex").bindings[0];if(void 0===n.indexesGPU||n.indexesGPU.length!==i.length){const e=new Uint32Array([0,0,0,0]),t=[];for(let n=0,r=i.length;n<r;n++){const i=a.createBuffer();e[0]=n,a.bindBuffer(a.UNIFORM_BUFFER,i),a.bufferData(a.UNIFORM_BUFFER,e,a.STATIC_DRAW),t.push(i)}n.indexesGPU=t}const s=this.get(r),o=this.renderer.getPixelRatio(),u=this._currentContext.renderTarget,c=this._isRenderCameraDepthArray(this._currentContext),d=this._currentContext.activeCubeFace;if(c){const e=this.get(u.depthTexture);if(e.clearedRenderId!==this.renderer._nodes.nodeFrame.renderId){e.clearedRenderId=this.renderer._nodes.nodeFrame.renderId;const{stencilBuffer:t}=u;for(let e=0,n=i.length;e<n;e++)this.renderer._activeCubeFace=e,this._currentContext.activeCubeFace=e,this._setFramebuffer(this._currentContext),this.clear(!1,!0,t,this._currentContext,!1,!1);this.renderer._activeCubeFace=d,this._currentContext.activeCubeFace=d}}for(let r=0,u=i.length;r<u;r++){const u=i[r];if(t.layers.test(u.layers)){c&&(this.renderer._activeCubeFace=r,this._currentContext.activeCubeFace=r,this._setFramebuffer(this._currentContext));const t=u.viewport;if(void 0!==t){const n=t.x*o,i=t.y*o,r=t.width*o,s=t.height*o;l.viewport(Math.floor(n),Math.floor(e.context.height-s-i),Math.floor(r),Math.floor(s))}l.bindBufferBase(a.UNIFORM_BUFFER,s.index,n.indexesGPU[r]),w()}this._currentContext.activeCubeFace=d,this.renderer._activeCubeFace=d}}else w()}needsRenderUpdate(){return!1}getRenderCacheKey(){return""}createDefaultTexture(e){this.textureUtils.createDefaultTexture(e)}createTexture(e,t){this.textureUtils.createTexture(e,t)}updateTexture(e,t){this.textureUtils.updateTexture(e,t)}generateMipmaps(e){this.textureUtils.generateMipmaps(e)}destroyTexture(e){this.textureUtils.destroyTexture(e)}async copyTextureToBuffer(e,t,n,i,r,s){return this.textureUtils.copyTextureToBuffer(e,t,n,i,r,s)}createSampler(){}destroySampler(){}createNodeBuilder(e,t){return new oL(e,t)}createProgram(e){const t=this.gl,{stage:n,code:i}=e,r="fragment"===n?t.createShader(t.FRAGMENT_SHADER):t.createShader(t.VERTEX_SHADER);t.shaderSource(r,i),t.compileShader(r),this.set(e,{shaderGPU:r})}destroyProgram(e){this.delete(e)}createRenderPipeline(e,t){const n=this.gl,i=e.pipeline,{fragmentProgram:r,vertexProgram:s}=i,o=n.createProgram(),a=this.get(r).shaderGPU,l=this.get(s).shaderGPU;if(n.attachShader(o,a),n.attachShader(o,l),n.linkProgram(o),this.set(i,{programGPU:o,fragmentShader:a,vertexShader:l}),null!==t&&this.parallel){const r=new Promise((t=>{const r=this.parallel,s=()=>{n.getProgramParameter(o,r.COMPLETION_STATUS_KHR)?(this._completeCompile(e,i),t()):requestAnimationFrame(s)};s()}));t.push(r)}else this._completeCompile(e,i)}_handleSource(e,t){const n=e.split("\n"),i=[],r=Math.max(t-6,0),s=Math.min(t+6,n.length);for(let e=r;e<s;e++){const r=e+1;i.push(`${r===t?">":" "} ${r}: ${n[e]}`)}return i.join("\n")}_getShaderErrors(e,t,n){const i=e.getShaderParameter(t,e.COMPILE_STATUS),r=(e.getShaderInfoLog(t)||"").trim();if(i&&""===r)return"";const s=/ERROR: 0:(\d+)/.exec(r);if(s){const i=parseInt(s[1]);return n.toUpperCase()+"\n\n"+r+"\n\n"+this._handleSource(e.getShaderSource(t),i)}return r}_logProgramError(e,t,n){if(this.renderer.debug.checkShaderErrors){const i=this.gl,r=(i.getProgramInfoLog(e)||"").trim();if(!1===i.getProgramParameter(e,i.LINK_STATUS))if("function"==typeof this.renderer.debug.onShaderError)this.renderer.debug.onShaderError(i,e,n,t);else{const s=this._getShaderErrors(i,n,"vertex"),o=this._getShaderErrors(i,t,"fragment");console.error("THREE.WebGLProgram: Shader Error "+i.getError()+" - VALIDATE_STATUS "+i.getProgramParameter(e,i.VALIDATE_STATUS)+"\n\nProgram Info Log: "+r+"\n"+s+"\n"+o)}else""!==r&&console.warn("THREE.WebGLProgram: Program Info Log:",r)}}_completeCompile(e,t){const{state:n,gl:i}=this,r=this.get(t),{programGPU:s,fragmentShader:o,vertexShader:a}=r;!1===i.getProgramParameter(s,i.LINK_STATUS)&&this._logProgramError(s,o,a),n.useProgram(s);const l=e.getBindings();this._setupBindings(l,s),this.set(t,{programGPU:s})}createComputePipeline(e,t){const{state:n,gl:i}=this,r={stage:"fragment",code:"#version 300 es\nprecision highp float;\nvoid main() {}"};this.createProgram(r);const{computeProgram:s}=e,o=i.createProgram(),a=this.get(r).shaderGPU,l=this.get(s).shaderGPU,u=s.transforms,c=[],d=[];for(let e=0;e<u.length;e++){const t=u[e];c.push(t.varyingName),d.push(t.attributeNode)}i.attachShader(o,a),i.attachShader(o,l),i.transformFeedbackVaryings(o,c,i.SEPARATE_ATTRIBS),i.linkProgram(o),!1===i.getProgramParameter(o,i.LINK_STATUS)&&this._logProgramError(o,a,l),n.useProgram(o),this._setupBindings(t,o);const h=s.attributes,f=[],p=[];for(let e=0;e<h.length;e++){const t=h[e].node.attribute;f.push(t),this.has(t)||this.attributeUtils.createAttribute(t,i.ARRAY_BUFFER)}for(let e=0;e<d.length;e++){const t=d[e].attribute;this.has(t)||this.attributeUtils.createAttribute(t,i.ARRAY_BUFFER);const n=this.get(t);p.push(n)}this.set(e,{programGPU:o,transformBuffers:p,attributes:f})}createBindings(e,t){if(!1===this._knownBindings.has(t)){this._knownBindings.add(t);let e=0,n=0;for(const i of t){this.set(i,{textures:n,uniformBuffers:e});for(const t of i.bindings)t.isUniformBuffer&&e++,t.isSampledTexture&&n++}}this.updateBindings(e,t)}updateBindings(e){const{gl:t}=this,n=this.get(e);let i=n.uniformBuffers,r=n.textures;for(const n of e.bindings){const e=this.get(n);if(n.isUniformsGroup||n.isUniformBuffer){const r=n.buffer;let{bufferGPU:s}=this.get(r);void 0===s?(s=t.createBuffer(),t.bindBuffer(t.UNIFORM_BUFFER,s),t.bufferData(t.UNIFORM_BUFFER,r,t.DYNAMIC_DRAW),this.set(r,{bufferGPU:s})):(t.bindBuffer(t.UNIFORM_BUFFER,s),t.bufferSubData(t.UNIFORM_BUFFER,0,r)),e.index=i++,e.bufferGPU=s,this.set(n,e)}else if(n.isSampledTexture){const{textureGPU:t,glTextureType:i}=this.get(n.texture);e.index=r++,e.textureGPU=t,e.glTextureType=i,this.set(n,e)}}}updateBinding(e){const t=this.gl;if(e.isUniformsGroup||e.isUniformBuffer){const n=this.get(e).bufferGPU,i=e.buffer;t.bindBuffer(t.UNIFORM_BUFFER,n),t.bufferData(t.UNIFORM_BUFFER,i,t.DYNAMIC_DRAW)}}createIndexAttribute(e){const t=this.gl;this.attributeUtils.createAttribute(e,t.ELEMENT_ARRAY_BUFFER)}createAttribute(e){if(this.has(e))return;const t=this.gl;this.attributeUtils.createAttribute(e,t.ARRAY_BUFFER)}createStorageAttribute(e){if(this.has(e))return;const t=this.gl;this.attributeUtils.createAttribute(e,t.ARRAY_BUFFER)}updateAttribute(e){this.attributeUtils.updateAttribute(e)}destroyAttribute(e){this.attributeUtils.destroyAttribute(e)}hasFeature(e){const t=Object.keys(EL).filter((t=>EL[t]===e)),n=this.extensions;for(let e=0;e<t.length;e++)if(n.has(t[e]))return!0;return!1}getMaxAnisotropy(){return this.capabilities.getMaxAnisotropy()}copyTextureToTexture(e,t,n=null,i=null,r=0,s=0){this.textureUtils.copyTextureToTexture(e,t,n,i,r,s)}copyFramebufferToTexture(e,t,n){this.textureUtils.copyFramebufferToTexture(e,t,n)}_setFramebuffer(e){const{gl:t,state:n}=this;let i=null;if(null!==e.textures){const r=e.renderTarget,s=this.get(r),{samples:o,depthBuffer:a,stencilBuffer:l}=r,u=!0===r.isWebGLCubeRenderTarget,c=!0===r.isRenderTarget3D,d=r.depth>1,h=!0===r.isXRRenderTarget,f=!0===h&&!0===r._hasExternalTextures;let p=s.msaaFrameBuffer,g=s.depthRenderbuffer;const m=this.extensions.get("WEBGL_multisampled_render_to_texture"),v=this.extensions.get("OVR_multiview2"),A=this._useMultisampledExtension(r),x=fN(e);let y;if(u?(s.cubeFramebuffers||(s.cubeFramebuffers={}),y=s.cubeFramebuffers[x]):h&&!1===f?y=this._xrFramebuffer:(s.framebuffers||(s.framebuffers={}),y=s.framebuffers[x]),void 0===y){y=t.createFramebuffer(),n.bindFramebuffer(t.FRAMEBUFFER,y);const i=e.textures,a=[];if(u){s.cubeFramebuffers[x]=y;const{textureGPU:e}=this.get(i[0]),n=this.renderer._activeCubeFace,r=this.renderer._activeMipmapLevel;t.framebufferTexture2D(t.FRAMEBUFFER,t.COLOR_ATTACHMENT0,t.TEXTURE_CUBE_MAP_POSITIVE_X+n,e,r)}else{s.framebuffers[x]=y;for(let n=0;n<i.length;n++){const s=i[n],a=this.get(s);a.renderTarget=e.renderTarget,a.cacheKey=x;const l=t.COLOR_ATTACHMENT0+n;if(r.multiview)v.framebufferTextureMultisampleMultiviewOVR(t.FRAMEBUFFER,l,a.textureGPU,0,o,0,2);else if(c||d){const e=this.renderer._activeCubeFace,n=this.renderer._activeMipmapLevel;t.framebufferTextureLayer(t.FRAMEBUFFER,l,a.textureGPU,n,e)}else if(A)m.framebufferTexture2DMultisampleEXT(t.FRAMEBUFFER,l,t.TEXTURE_2D,a.textureGPU,0,o);else{const e=this.renderer._activeMipmapLevel;t.framebufferTexture2D(t.FRAMEBUFFER,l,t.TEXTURE_2D,a.textureGPU,e)}}}const h=l?t.DEPTH_STENCIL_ATTACHMENT:t.DEPTH_ATTACHMENT;if(!0===r._autoAllocateDepthBuffer){const n=t.createRenderbuffer();this.textureUtils.setupRenderBufferStorage(n,e,0,A),s.xrDepthRenderbuffer=n,a.push(l?t.DEPTH_STENCIL_ATTACHMENT:t.DEPTH_ATTACHMENT),t.bindRenderbuffer(t.RENDERBUFFER,n),t.framebufferRenderbuffer(t.FRAMEBUFFER,h,t.RENDERBUFFER,n)}else if(null!==e.depthTexture){a.push(l?t.DEPTH_STENCIL_ATTACHMENT:t.DEPTH_ATTACHMENT);const n=this.get(e.depthTexture);if(n.renderTarget=e.renderTarget,n.cacheKey=x,r.multiview)v.framebufferTextureMultisampleMultiviewOVR(t.FRAMEBUFFER,h,n.textureGPU,0,o,0,2);else if(f&&A)m.framebufferTexture2DMultisampleEXT(t.FRAMEBUFFER,h,t.TEXTURE_2D,n.textureGPU,0,o);else if(e.depthTexture.isArrayTexture){const e=this.renderer._activeCubeFace;t.framebufferTextureLayer(t.FRAMEBUFFER,h,n.textureGPU,0,e)}else t.framebufferTexture2D(t.FRAMEBUFFER,h,t.TEXTURE_2D,n.textureGPU,0)}s.depthInvalidationArray=a}else{if(this._isRenderCameraDepthArray(e)){n.bindFramebuffer(t.FRAMEBUFFER,y);const i=this.renderer._activeCubeFace,r=this.get(e.depthTexture),s=l?t.DEPTH_STENCIL_ATTACHMENT:t.DEPTH_ATTACHMENT;t.framebufferTextureLayer(t.FRAMEBUFFER,s,r.textureGPU,0,i)}if((h||A||r.multiview)&&!0!==r._isOpaqueFramebuffer){n.bindFramebuffer(t.FRAMEBUFFER,y);const i=this.get(e.textures[0]);r.multiview?v.framebufferTextureMultisampleMultiviewOVR(t.FRAMEBUFFER,t.COLOR_ATTACHMENT0,i.textureGPU,0,o,0,2):A?m.framebufferTexture2DMultisampleEXT(t.FRAMEBUFFER,t.COLOR_ATTACHMENT0,t.TEXTURE_2D,i.textureGPU,0,o):t.framebufferTexture2D(t.FRAMEBUFFER,t.COLOR_ATTACHMENT0,t.TEXTURE_2D,i.textureGPU,0);const a=l?t.DEPTH_STENCIL_ATTACHMENT:t.DEPTH_ATTACHMENT;if(!0===r._autoAllocateDepthBuffer){const e=s.xrDepthRenderbuffer;t.bindRenderbuffer(t.RENDERBUFFER,e),t.framebufferRenderbuffer(t.FRAMEBUFFER,a,t.RENDERBUFFER,e)}else{const n=this.get(e.depthTexture);r.multiview?v.framebufferTextureMultisampleMultiviewOVR(t.FRAMEBUFFER,a,n.textureGPU,0,o,0,2):A?m.framebufferTexture2DMultisampleEXT(t.FRAMEBUFFER,a,t.TEXTURE_2D,n.textureGPU,0,o):t.framebufferTexture2D(t.FRAMEBUFFER,a,t.TEXTURE_2D,n.textureGPU,0)}}}if(o>0&&!1===A&&!r.multiview){if(void 0===p){const i=[];p=t.createFramebuffer(),n.bindFramebuffer(t.FRAMEBUFFER,p);const r=[],u=e.textures;for(let n=0;n<u.length;n++){r[n]=t.createRenderbuffer(),t.bindRenderbuffer(t.RENDERBUFFER,r[n]),i.push(t.COLOR_ATTACHMENT0+n);const s=e.textures[n],a=this.get(s);t.renderbufferStorageMultisample(t.RENDERBUFFER,o,a.glInternalFormat,e.width,e.height),t.framebufferRenderbuffer(t.FRAMEBUFFER,t.COLOR_ATTACHMENT0+n,t.RENDERBUFFER,r[n])}if(t.bindRenderbuffer(t.RENDERBUFFER,null),s.msaaFrameBuffer=p,s.msaaRenderbuffers=r,a&&void 0===g){g=t.createRenderbuffer(),this.textureUtils.setupRenderBufferStorage(g,e,o),s.depthRenderbuffer=g;const n=l?t.DEPTH_STENCIL_ATTACHMENT:t.DEPTH_ATTACHMENT;i.push(n)}s.invalidationArray=i}i=s.msaaFrameBuffer}else i=y;n.drawBuffers(e,y)}n.bindFramebuffer(t.FRAMEBUFFER,i)}_getVaoKey(e){let t="";for(let n=0;n<e.length;n++){t+=":"+this.get(e[n]).id}return t}_createVao(e){const{gl:t}=this,n=t.createVertexArray();t.bindVertexArray(n);for(let n=0;n<e.length;n++){const i=e[n],r=this.get(i);let s,o;t.bindBuffer(t.ARRAY_BUFFER,r.bufferGPU),t.enableVertexAttribArray(n),!0===i.isInterleavedBufferAttribute?(s=i.data.stride*r.bytesPerElement,o=i.offset*r.bytesPerElement):(s=0,o=0),r.isInteger?t.vertexAttribIPointer(n,i.itemSize,r.type,s,o):t.vertexAttribPointer(n,i.itemSize,r.type,i.normalized,s,o),i.isInstancedBufferAttribute&&!i.isInterleavedBufferAttribute?t.vertexAttribDivisor(n,i.meshPerAttribute):i.isInterleavedBufferAttribute&&i.data.isInstancedInterleavedBuffer&&t.vertexAttribDivisor(n,i.data.meshPerAttribute)}return t.bindBuffer(t.ARRAY_BUFFER,null),n}_getTransformFeedback(e){let t="";for(let n=0;n<e.length;n++)t+=":"+e[n].id;let n=this.transformFeedbackCache[t];if(void 0!==n)return n;const{gl:i}=this;n=i.createTransformFeedback(),i.bindTransformFeedback(i.TRANSFORM_FEEDBACK,n);for(let t=0;t<e.length;t++){const n=e[t];i.bindBufferBase(i.TRANSFORM_FEEDBACK_BUFFER,t,n.transformBuffer)}return i.bindTransformFeedback(i.TRANSFORM_FEEDBACK,null),this.transformFeedbackCache[t]=n,n}_setupBindings(e,t){const n=this.gl;for(const i of e)for(const e of i.bindings){const i=this.get(e).index;if(e.isUniformsGroup||e.isUniformBuffer){const r=n.getUniformBlockIndex(t,e.name);n.uniformBlockBinding(t,r,i)}else if(e.isSampledTexture){const r=n.getUniformLocation(t,e.name);n.uniform1i(r,i)}}}_bindUniforms(e){const{gl:t,state:n}=this;for(const i of e)for(const e of i.bindings){const i=this.get(e),r=i.index;e.isUniformsGroup||e.isUniformBuffer?n.bindBufferBase(t.UNIFORM_BUFFER,r,i.bufferGPU):e.isSampledTexture&&n.bindTexture(i.glTextureType,i.textureGPU,t.TEXTURE0+r)}}_resolveRenderTarget(e){const{gl:t,state:n}=this,i=e.renderTarget;if(null!==e.textures&&i){const r=this.get(i);if(i.samples>0&&!1===this._useMultisampledExtension(i)){const s=r.framebuffers[e.getCacheKey()];let o=t.COLOR_BUFFER_BIT;i.resolveDepthBuffer&&(i.depthBuffer&&(o|=t.DEPTH_BUFFER_BIT),i.stencilBuffer&&i.resolveStencilBuffer&&(o|=t.STENCIL_BUFFER_BIT));const a=r.msaaFrameBuffer,l=r.msaaRenderbuffers,u=e.textures,c=u.length>1;if(n.bindFramebuffer(t.READ_FRAMEBUFFER,a),n.bindFramebuffer(t.DRAW_FRAMEBUFFER,s),c)for(let e=0;e<u.length;e++)t.framebufferRenderbuffer(t.READ_FRAMEBUFFER,t.COLOR_ATTACHMENT0+e,t.RENDERBUFFER,null),t.framebufferTexture2D(t.DRAW_FRAMEBUFFER,t.COLOR_ATTACHMENT0+e,t.TEXTURE_2D,null,0);for(let n=0;n<u.length;n++){if(c){const{textureGPU:e}=this.get(u[n]);t.framebufferRenderbuffer(t.READ_FRAMEBUFFER,t.COLOR_ATTACHMENT0,t.RENDERBUFFER,l[n]),t.framebufferTexture2D(t.DRAW_FRAMEBUFFER,t.COLOR_ATTACHMENT0,t.TEXTURE_2D,e,0)}if(e.scissor){const{x:n,y:i,width:r,height:s}=e.scissorValue,a=e.height-s-i;t.blitFramebuffer(n,a,n+r,a+s,n,a,n+r,a+s,o,t.NEAREST)}else t.blitFramebuffer(0,0,e.width,e.height,0,0,e.width,e.height,o,t.NEAREST)}if(c)for(let e=0;e<u.length;e++){const{textureGPU:n}=this.get(u[e]);t.framebufferRenderbuffer(t.READ_FRAMEBUFFER,t.COLOR_ATTACHMENT0+e,t.RENDERBUFFER,l[e]),t.framebufferTexture2D(t.DRAW_FRAMEBUFFER,t.COLOR_ATTACHMENT0+e,t.TEXTURE_2D,n,0)}!0===this._supportsInvalidateFramebuffer&&t.invalidateFramebuffer(t.READ_FRAMEBUFFER,r.invalidationArray)}else if(!1===i.resolveDepthBuffer&&r.framebuffers){const i=r.framebuffers[e.getCacheKey()];n.bindFramebuffer(t.DRAW_FRAMEBUFFER,i),t.invalidateFramebuffer(t.DRAW_FRAMEBUFFER,r.depthInvalidationArray)}}}_useMultisampledExtension(e){return!0===e.multiview||e.samples>0&&!0===this.extensions.has("WEBGL_multisampled_render_to_texture")&&!1!==e._autoAllocateDepthBuffer}dispose(){const e=this.extensions.get("WEBGL_lose_context");e&&e.loseContext(),this.renderer.domElement.removeEventListener("webglcontextlost",this._onContextLost)}}const BL="point-list",DL="line-list",IL="line-strip",LL="triangle-list",jL="triangle-strip",OL="never",zL="less",RL="equal",kL="less-equal",FL="greater",HL="not-equal",UL="greater-equal",XL="always",GL="store",VL="load",WL="clear",QL="ccw",ZL="cw",YL="none",JL="back",KL="uint16",qL="uint32",_L="r8unorm",$L="r8snorm",ej="r8uint",tj="r8sint",nj="r16uint",ij="r16sint",rj="r16float",sj="rg8unorm",oj="rg8snorm",aj="rg8uint",lj="rg8sint",uj="r32uint",cj="r32sint",dj="r32float",hj="rg16uint",fj="rg16sint",pj="rg16float",gj="rgba8unorm",mj="rgba8unorm-srgb",vj="rgba8snorm",Aj="rgba8uint",xj="rgba8sint",yj="bgra8unorm",bj="bgra8unorm-srgb",wj="rgb9e5ufloat",Cj="rgb10a2unorm",Mj="rg11b10ufloat",Ej="rg32uint",Tj="rg32sint",Sj="rg32float",Pj="rgba16uint",Nj="rgba16sint",Bj="rgba16float",Dj="rgba32uint",Ij="rgba32sint",Lj="rgba32float",jj="depth16unorm",Oj="depth24plus",zj="depth24plus-stencil8",Rj="depth32float",kj="depth32float-stencil8",Fj="bc1-rgba-unorm",Hj="bc1-rgba-unorm-srgb",Uj="bc2-rgba-unorm",Xj="bc2-rgba-unorm-srgb",Gj="bc3-rgba-unorm",Vj="bc3-rgba-unorm-srgb",Wj="bc4-r-unorm",Qj="bc4-r-snorm",Zj="bc5-rg-unorm",Yj="bc5-rg-snorm",Jj="bc6h-rgb-ufloat",Kj="bc6h-rgb-float",qj="bc7-rgba-unorm",_j="bc7-rgba-unorm-srgb",$j="etc2-rgb8unorm",eO="etc2-rgb8unorm-srgb",tO="etc2-rgb8a1unorm",nO="etc2-rgb8a1unorm-srgb",iO="etc2-rgba8unorm",rO="etc2-rgba8unorm-srgb",sO="eac-r11unorm",oO="eac-r11snorm",aO="eac-rg11unorm",lO="eac-rg11snorm",uO="astc-4x4-unorm",cO="astc-4x4-unorm-srgb",dO="astc-5x4-unorm",hO="astc-5x4-unorm-srgb",fO="astc-5x5-unorm",pO="astc-5x5-unorm-srgb",gO="astc-6x5-unorm",mO="astc-6x5-unorm-srgb",vO="astc-6x6-unorm",AO="astc-6x6-unorm-srgb",xO="astc-8x5-unorm",yO="astc-8x5-unorm-srgb",bO="astc-8x6-unorm",wO="astc-8x6-unorm-srgb",CO="astc-8x8-unorm",MO="astc-8x8-unorm-srgb",EO="astc-10x5-unorm",TO="astc-10x5-unorm-srgb",SO="astc-10x6-unorm",PO="astc-10x6-unorm-srgb",NO="astc-10x8-unorm",BO="astc-10x8-unorm-srgb",DO="astc-10x10-unorm",IO="astc-10x10-unorm-srgb",LO="astc-12x10-unorm",jO="astc-12x10-unorm-srgb",OO="astc-12x12-unorm",zO="astc-12x12-unorm-srgb",RO="clamp-to-edge",kO="repeat",FO="mirror-repeat",HO="linear",UO="nearest",XO="zero",GO="one",VO="src",WO="one-minus-src",QO="src-alpha",ZO="one-minus-src-alpha",YO="dst",JO="one-minus-dst",KO="dst-alpha",qO="one-minus-dst-alpha",_O="src-alpha-saturated",$O="constant",ez="one-minus-constant",tz="add",nz="subtract",iz="reverse-subtract",rz="min",sz="max",oz=0,az=15,lz="keep",uz="zero",cz="replace",dz="invert",hz="increment-clamp",fz="decrement-clamp",pz="increment-wrap",gz="decrement-wrap",mz="storage",vz="read-only-storage",Az="write-only",xz="read-only",yz="read-write",bz="non-filtering",wz="comparison",Cz="float",Mz="unfilterable-float",Ez="depth",Tz="sint",Sz="uint",Pz="2d",Nz="3d",Bz="2d",Dz="2d-array",Iz="cube",Lz="3d",jz="all",Oz="vertex",zz="instance",Rz={CoreFeaturesAndLimits:"core-features-and-limits",DepthClipControl:"depth-clip-control",Depth32FloatStencil8:"depth32float-stencil8",TextureCompressionBC:"texture-compression-bc",TextureCompressionBCSliced3D:"texture-compression-bc-sliced-3d",TextureCompressionETC2:"texture-compression-etc2",TextureCompressionASTC:"texture-compression-astc",TextureCompressionASTCSliced3D:"texture-compression-astc-sliced-3d",TimestampQuery:"timestamp-query",IndirectFirstInstance:"indirect-first-instance",ShaderF16:"shader-f16",RG11B10UFloat:"rg11b10ufloat-renderable",BGRA8UNormStorage:"bgra8unorm-storage",Float32Filterable:"float32-filterable",Float32Blendable:"float32-blendable",ClipDistances:"clip-distances",DualSourceBlending:"dual-source-blending",Subgroups:"subgroups",TextureFormatsTier1:"texture-formats-tier1",TextureFormatsTier2:"texture-formats-tier2"};class kz extends YI{constructor(e,t,n){super(e,t?t.value:null),this.textureNode=t,this.groupNode=n}update(){this.texture=this.textureNode.value}}class Fz extends UI{constructor(e,t){super(e,t?t.array:null),this.attribute=t,this.isStorageBuffer=!0}}let Hz=0;class Uz extends Fz{constructor(e,t){super("StorageBuffer_"+Hz++,e?e.value:null),this.nodeUniform=e,this.access=e?e.access:fv.READ_WRITE,this.groupNode=t}get buffer(){return this.nodeUniform.value}}class Xz extends UP{constructor(e){super(),this.device=e;this.mipmapSampler=e.createSampler({minFilter:HO}),this.flipYSampler=e.createSampler({minFilter:UO}),this.transferPipelines={},this.flipYPipelines={},this.mipmapVertexShaderModule=e.createShaderModule({label:"mipmapVertex",code:"\nstruct VarysStruct {\n\t@builtin( position ) Position: vec4<f32>,\n\t@location( 0 ) vTex : vec2<f32>\n};\n\n@vertex\nfn main( @builtin( vertex_index ) vertexIndex : u32 ) -> VarysStruct {\n\n\tvar Varys : VarysStruct;\n\n\tvar pos = array< vec2<f32>, 4 >(\n\t\tvec2<f32>( -1.0,  1.0 ),\n\t\tvec2<f32>(  1.0,  1.0 ),\n\t\tvec2<f32>( -1.0, -1.0 ),\n\t\tvec2<f32>(  1.0, -1.0 )\n\t);\n\n\tvar tex = array< vec2<f32>, 4 >(\n\t\tvec2<f32>( 0.0, 0.0 ),\n\t\tvec2<f32>( 1.0, 0.0 ),\n\t\tvec2<f32>( 0.0, 1.0 ),\n\t\tvec2<f32>( 1.0, 1.0 )\n\t);\n\n\tVarys.vTex = tex[ vertexIndex ];\n\tVarys.Position = vec4<f32>( pos[ vertexIndex ], 0.0, 1.0 );\n\n\treturn Varys;\n\n}\n"}),this.mipmapFragmentShaderModule=e.createShaderModule({label:"mipmapFragment",code:"\n@group( 0 ) @binding( 0 )\nvar imgSampler : sampler;\n\n@group( 0 ) @binding( 1 )\nvar img : texture_2d<f32>;\n\n@fragment\nfn main( @location( 0 ) vTex : vec2<f32> ) -> @location( 0 ) vec4<f32> {\n\n\treturn textureSample( img, imgSampler, vTex );\n\n}\n"}),this.flipYFragmentShaderModule=e.createShaderModule({label:"flipYFragment",code:"\n@group( 0 ) @binding( 0 )\nvar imgSampler : sampler;\n\n@group( 0 ) @binding( 1 )\nvar img : texture_2d<f32>;\n\n@fragment\nfn main( @location( 0 ) vTex : vec2<f32> ) -> @location( 0 ) vec4<f32> {\n\n\treturn textureSample( img, imgSampler, vec2( vTex.x, 1.0 - vTex.y ) );\n\n}\n"})}getTransferPipeline(e){let t=this.transferPipelines[e];return void 0===t&&(t=this.device.createRenderPipeline({label:`mipmap-${e}`,vertex:{module:this.mipmapVertexShaderModule,entryPoint:"main"},fragment:{module:this.mipmapFragmentShaderModule,entryPoint:"main",targets:[{format:e}]},primitive:{topology:jL,stripIndexFormat:qL},layout:"auto"}),this.transferPipelines[e]=t),t}getFlipYPipeline(e){let t=this.flipYPipelines[e];return void 0===t&&(t=this.device.createRenderPipeline({label:`flipY-${e}`,vertex:{module:this.mipmapVertexShaderModule,entryPoint:"main"},fragment:{module:this.flipYFragmentShaderModule,entryPoint:"main",targets:[{format:e}]},primitive:{topology:jL,stripIndexFormat:qL},layout:"auto"}),this.flipYPipelines[e]=t),t}flipY(e,t,n=0){const i=t.format,{width:r,height:s}=t.size,o=this.getTransferPipeline(i),a=this.getFlipYPipeline(i),l=this.device.createTexture({size:{width:r,height:s,depthOrArrayLayers:1},format:i,usage:GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING}),u=e.createView({baseMipLevel:0,mipLevelCount:1,dimension:Bz,baseArrayLayer:n}),c=l.createView({baseMipLevel:0,mipLevelCount:1,dimension:Bz,baseArrayLayer:0}),d=this.device.createCommandEncoder({}),h=(e,t,n)=>{const i=e.getBindGroupLayout(0),r=this.device.createBindGroup({layout:i,entries:[{binding:0,resource:this.flipYSampler},{binding:1,resource:t}]}),s=d.beginRenderPass({colorAttachments:[{view:n,loadOp:WL,storeOp:GL,clearValue:[0,0,0,0]}]});s.setPipeline(e),s.setBindGroup(0,r),s.draw(4,1,0,0),s.end()};h(o,u,c),h(a,c,u),this.device.queue.submit([d.finish()]),l.destroy()}generateMipmaps(e,t,n=0){const i=this.get(e);void 0===i.useCount&&(i.useCount=0,i.layers=[]);const r=i.layers[n]||this._mipmapCreateBundles(e,t,n),s=this.device.createCommandEncoder({});this._mipmapRunBundles(s,r),this.device.queue.submit([s.finish()]),0!==i.useCount&&(i.layers[n]=r),i.useCount++}_mipmapCreateBundles(e,t,n){const i=this.getTransferPipeline(t.format),r=i.getBindGroupLayout(0);let s=e.createView({baseMipLevel:0,mipLevelCount:1,dimension:Bz,baseArrayLayer:n});const o=[];for(let a=1;a<t.mipLevelCount;a++){const l=this.device.createBindGroup({layout:r,entries:[{binding:0,resource:this.mipmapSampler},{binding:1,resource:s}]}),u=e.createView({baseMipLevel:a,mipLevelCount:1,dimension:Bz,baseArrayLayer:n}),c={colorAttachments:[{view:u,loadOp:WL,storeOp:GL,clearValue:[0,0,0,0]}]},d=this.device.createRenderBundleEncoder({colorFormats:[t.format]});d.setPipeline(i),d.setBindGroup(0,l),d.draw(4,1,0,0),o.push({renderBundles:[d.finish()],passDescriptor:c}),s=u}return o}_mipmapRunBundles(e,t){const n=t.length;for(let i=0;i<n;i++){const n=t[i],r=e.beginRenderPass(n.passDescriptor);r.executeBundles(n.renderBundles),r.end()}}}const Gz={512:"never",[ns]:"less",514:"equal",[is]:"less-equal",516:"greater",518:"greater-equal",519:"always",517:"not-equal"},Vz=[0,1,3,2,4,5];class Wz{constructor(e){this.backend=e,this._passUtils=null,this.defaultTexture={},this.defaultCubeTexture={},this.defaultVideoFrame=null,this.colorBuffer=null,this.depthTexture=new _l,this.depthTexture.name="depthBuffer"}createSampler(e){const t=this.backend,n=t.device,i=t.get(e),r={addressModeU:this._convertAddressMode(e.wrapS),addressModeV:this._convertAddressMode(e.wrapT),addressModeW:this._convertAddressMode(e.wrapR),magFilter:this._convertFilterMode(e.magFilter),minFilter:this._convertFilterMode(e.minFilter),mipmapFilter:this._convertFilterMode(e.minFilter),maxAnisotropy:1};r.magFilter===HO&&r.minFilter===HO&&r.mipmapFilter===HO&&(r.maxAnisotropy=e.anisotropy),e.isDepthTexture&&null!==e.compareFunction&&(r.compare=Gz[e.compareFunction]),i.sampler=n.createSampler(r)}createDefaultTexture(e){let t;const n=Qz(e);t=e.isCubeTexture?this._getDefaultCubeTextureGPU(n):this._getDefaultTextureGPU(n),this.backend.get(e).texture=t}createTexture(e,t={}){const n=this.backend,i=n.get(e);if(i.initialized)throw new Error("WebGPUTextureUtils: Texture already initialized.");if(e.isExternalTexture)return i.texture=e.sourceTexture,void(i.initialized=!0);void 0===t.needsMipmaps&&(t.needsMipmaps=!1),void 0===t.levels&&(t.levels=1),void 0===t.depth&&(t.depth=1);const{width:r,height:s,depth:o,levels:a}=t;e.isFramebufferTexture&&(t.renderTarget?t.format=this.backend.utils.getCurrentColorFormat(t.renderTarget):t.format=this.backend.utils.getPreferredCanvasFormat());const l=this._getDimension(e),u=e.internalFormat||t.format||Qz(e,n.device);i.format=u;const{samples:c,primarySamples:d,isMSAA:h}=n.utils.getTextureSampleData(e);let f=GPUTextureUsage.TEXTURE_BINDING|GPUTextureUsage.COPY_DST|GPUTextureUsage.COPY_SRC;!0===e.isStorageTexture&&(f|=GPUTextureUsage.STORAGE_BINDING),!0!==e.isCompressedTexture&&!0!==e.isCompressedArrayTexture&&u!==wj&&(f|=GPUTextureUsage.RENDER_ATTACHMENT);const p={label:e.name,size:{width:r,height:s,depthOrArrayLayers:o},mipLevelCount:a,sampleCount:d,dimension:l,format:u,usage:f};if(void 0===u)return console.warn("WebGPURenderer: Texture format not supported."),void this.createDefaultTexture(e);if(e.isCubeTexture&&(p.textureBindingViewDimension=Iz),i.texture=n.device.createTexture(p),h){const e=Object.assign({},p);e.label=e.label+"-msaa",e.sampleCount=c,e.mipLevelCount=1,i.msaaTexture=n.device.createTexture(e)}i.initialized=!0,i.textureDescriptorGPU=p}destroyTexture(e){const t=this.backend,n=t.get(e);void 0!==n.texture&&n.texture.destroy(),void 0!==n.msaaTexture&&n.msaaTexture.destroy(),t.delete(e)}destroySampler(e){delete this.backend.get(e).sampler}generateMipmaps(e){const t=this.backend.get(e);if(e.isCubeTexture)for(let e=0;e<6;e++)this._generateMipmaps(t.texture,t.textureDescriptorGPU,e);else{const n=e.image.depth||1;for(let e=0;e<n;e++)this._generateMipmaps(t.texture,t.textureDescriptorGPU,e)}}getColorBuffer(){this.colorBuffer&&this.colorBuffer.destroy();const e=this.backend,{width:t,height:n}=e.getDrawingBufferSize();return this.colorBuffer=e.device.createTexture({label:"colorBuffer",size:{width:t,height:n,depthOrArrayLayers:1},sampleCount:e.utils.getSampleCount(e.renderer.samples),format:e.utils.getPreferredCanvasFormat(),usage:GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.COPY_SRC}),this.colorBuffer}getDepthBuffer(e=!0,t=!1){const n=this.backend,{width:i,height:r}=n.getDrawingBufferSize(),s=this.depthTexture,o=n.get(s).texture;let a,l;if(t?(a=or,l=$i):e&&(a=sr,l=Yi),void 0!==o){if(s.image.width===i&&s.image.height===r&&s.format===a&&s.type===l)return o;this.destroyTexture(s)}return s.name="depthBuffer",s.format=a,s.type=l,s.image.width=i,s.image.height=r,this.createTexture(s,{width:i,height:r}),n.get(s).texture}updateTexture(e,t){const n=this.backend.get(e),i=e.mipmaps,{textureDescriptorGPU:r}=n;if(!e.isRenderTargetTexture&&void 0!==r){if(e.isDataTexture)if(i.length>0)for(let t=0,s=i.length;t<s;t++){const s=i[t];this._copyBufferToTexture(s,n.texture,r,0,e.flipY,0,t)}else this._copyBufferToTexture(t.image,n.texture,r,0,e.flipY);else if(e.isArrayTexture||e.isDataArrayTexture||e.isData3DTexture)for(let i=0;i<t.image.depth;i++)this._copyBufferToTexture(t.image,n.texture,r,i,e.flipY,i);else if(e.isCompressedTexture||e.isCompressedArrayTexture)this._copyCompressedBufferToTexture(e.mipmaps,n.texture,r);else if(e.isCubeTexture)this._copyCubeMapToTexture(e,n.texture,r);else if(i.length>0)for(let t=0,s=i.length;t<s;t++){const s=i[t];this._copyImageToTexture(s,n.texture,r,0,e.flipY,e.premultiplyAlpha,t)}else this._copyImageToTexture(t.image,n.texture,r,0,e.flipY,e.premultiplyAlpha);n.version=e.version}}async copyTextureToBuffer(e,t,n,i,r,s){const o=this.backend.device,a=this.backend.get(e),l=a.texture,u=a.textureDescriptorGPU.format,c=this._getBytesPerTexel(u);let d=i*c;d=256*Math.ceil(d/256);const h=o.createBuffer({size:(r-1)*d+i*c,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ}),f=o.createCommandEncoder();f.copyTextureToBuffer({texture:l,origin:{x:t,y:n,z:s}},{buffer:h,bytesPerRow:d},{width:i,height:r});const p=this._getTypedArrayType(u);o.queue.submit([f.finish()]),await h.mapAsync(GPUMapMode.READ);return new p(h.getMappedRange())}_getDefaultTextureGPU(e){let t=this.defaultTexture[e];if(void 0===t){const n=new Ys;n.minFilter=Ri,n.magFilter=Ri,this.createTexture(n,{width:1,height:1,format:e}),this.defaultTexture[e]=t=n}return this.backend.get(t).texture}_getDefaultCubeTextureGPU(e){let t=this.defaultTexture[e];if(void 0===t){const n=new vl;n.minFilter=Ri,n.magFilter=Ri,this.createTexture(n,{width:1,height:1,depth:6}),this.defaultCubeTexture[e]=t=n}return this.backend.get(t).texture}_copyCubeMapToTexture(e,t,n){const i=e.images,r=e.mipmaps;for(let s=0;s<6;s++){const o=i[s],a=!0===e.flipY?Vz[s]:s;o.isDataTexture?this._copyBufferToTexture(o.image,t,n,a,e.flipY):this._copyImageToTexture(o,t,n,a,e.flipY,e.premultiplyAlpha);for(let i=0;i<r.length;i++){const o=r[i].images[s];o.isDataTexture?this._copyBufferToTexture(o.image,t,n,a,e.flipY,0,i+1):this._copyImageToTexture(o,t,n,a,e.flipY,e.premultiplyAlpha,i+1)}}}_copyImageToTexture(e,t,n,i,r,s,o=0){const a=this.backend.device,l=o>0?e.width:n.size.width,u=o>0?e.height:n.size.height;a.queue.copyExternalImageToTexture({source:e,flipY:r},{texture:t,mipLevel:o,origin:{x:0,y:0,z:i},premultipliedAlpha:s},{width:l,height:u,depthOrArrayLayers:1})}_getPassUtils(){let e=this._passUtils;return null===e&&(this._passUtils=e=new Xz(this.backend.device)),e}_generateMipmaps(e,t,n=0){this._getPassUtils().generateMipmaps(e,t,n)}_flipY(e,t,n=0){this._getPassUtils().flipY(e,t,n)}_copyBufferToTexture(e,t,n,i,r,s=0,o=0){const a=this.backend.device,l=e.data,u=this._getBytesPerTexel(n.format),c=e.width*u;a.queue.writeTexture({texture:t,mipLevel:o,origin:{x:0,y:0,z:i}},l,{offset:e.width*e.height*u*s,bytesPerRow:c},{width:e.width,height:e.height,depthOrArrayLayers:1}),!0===r&&this._flipY(t,n,i)}_copyCompressedBufferToTexture(e,t,n){const i=this.backend.device,r=this._getBlockData(n.format),s=n.size.depthOrArrayLayers>1;for(let o=0;o<e.length;o++){const a=e[o],l=a.width,u=a.height,c=s?n.size.depthOrArrayLayers:1,d=Math.ceil(l/r.width)*r.byteLength,h=d*Math.ceil(u/r.height);for(let e=0;e<c;e++)i.queue.writeTexture({texture:t,mipLevel:o,origin:{x:0,y:0,z:e}},a.data,{offset:e*h,bytesPerRow:d,rowsPerImage:Math.ceil(u/r.height)},{width:Math.ceil(l/r.width)*r.width,height:Math.ceil(u/r.height)*r.height,depthOrArrayLayers:1})}}_getBlockData(e){return e===Fj||e===Hj?{byteLength:8,width:4,height:4}:e===Uj||e===Xj||e===Gj||e===Vj?{byteLength:16,width:4,height:4}:e===Wj||e===Qj?{byteLength:8,width:4,height:4}:e===Zj||e===Yj||e===Jj||e===Kj||e===qj||e===_j?{byteLength:16,width:4,height:4}:e===$j||e===eO||e===tO||e===nO?{byteLength:8,width:4,height:4}:e===iO||e===rO?{byteLength:16,width:4,height:4}:e===sO||e===oO?{byteLength:8,width:4,height:4}:e===aO||e===lO||e===uO||e===cO?{byteLength:16,width:4,height:4}:e===dO||e===hO?{byteLength:16,width:5,height:4}:e===fO||e===pO?{byteLength:16,width:5,height:5}:e===gO||e===mO?{byteLength:16,width:6,height:5}:e===vO||e===AO?{byteLength:16,width:6,height:6}:e===xO||e===yO?{byteLength:16,width:8,height:5}:e===bO||e===wO?{byteLength:16,width:8,height:6}:e===CO||e===MO?{byteLength:16,width:8,height:8}:e===EO||e===TO?{byteLength:16,width:10,height:5}:e===SO||e===PO?{byteLength:16,width:10,height:6}:e===NO||e===BO?{byteLength:16,width:10,height:8}:e===DO||e===IO?{byteLength:16,width:10,height:10}:e===LO||e===jO?{byteLength:16,width:12,height:10}:e===OO||e===zO?{byteLength:16,width:12,height:12}:void 0}_convertAddressMode(e){let t=RO;return e===ji?t=kO:e===zi&&(t=FO),t}_convertFilterMode(e){let t=HO;return e!==Ri&&e!==ki&&e!==Fi||(t=UO),t}_getBytesPerTexel(e){return e===_L||e===$L||e===ej||e===tj?1:e===nj||e===ij||e===rj||e===sj||e===oj||e===aj||e===lj?2:e===uj||e===cj||e===dj||e===hj||e===fj||e===pj||e===gj||e===mj||e===vj||e===Aj||e===xj||e===yj||e===bj||e===wj||e===Cj||e===Mj||e===Rj||e===Oj||e===zj||e===kj?4:e===Ej||e===Tj||e===Sj||e===Pj||e===Nj||e===Bj?8:e===Dj||e===Ij||e===Lj?16:void 0}_getTypedArrayType(e){return e===ej?Uint8Array:e===tj?Int8Array:e===_L?Uint8Array:e===$L?Int8Array:e===aj?Uint8Array:e===lj?Int8Array:e===sj?Uint8Array:e===oj?Int8Array:e===Aj?Uint8Array:e===xj?Int8Array:e===gj||e===mj?Uint8Array:e===vj?Int8Array:e===nj?Uint16Array:e===ij?Int16Array:e===hj?Uint16Array:e===fj?Int16Array:e===Pj?Uint16Array:e===Nj?Int16Array:e===rj||e===pj||e===Bj?Uint16Array:e===uj?Uint32Array:e===cj?Int32Array:e===dj?Float32Array:e===Ej?Uint32Array:e===Tj?Int32Array:e===Sj?Float32Array:e===Dj?Uint32Array:e===Ij?Int32Array:e===Lj?Float32Array:e===yj||e===bj?Uint8Array:e===Cj||e===wj||e===Mj?Uint32Array:e===Rj?Float32Array:e===Oj||e===zj?Uint32Array:e===kj?Float32Array:void 0}_getDimension(e){let t;return t=e.is3DTexture||e.isData3DTexture?Nz:Pz,t}}function Qz(e,t=null){const n=e.format,i=e.type,r=e.colorSpace,s=ks.getTransfer(r);let o;if(!0===e.isCompressedTexture||!0===e.isCompressedArrayTexture)switch(n){case hr:case fr:o=s===es?Hj:Fj;break;case pr:o=s===es?Xj:Uj;break;case gr:o=s===es?Vj:Gj;break;case Hr:o=Wj;break;case Ur:o=Qj;break;case Xr:o=Zj;break;case Gr:o=Yj;break;case Rr:o=s===es?_j:qj;break;case br:case yr:o=s===es?eO:$j;break;case wr:o=s===es?rO:iO;break;case Cr:o=s===es?cO:uO;break;case Mr:o=s===es?hO:dO;break;case Er:o=s===es?pO:fO;break;case Tr:o=s===es?mO:gO;break;case Sr:o=s===es?AO:vO;break;case Pr:o=s===es?yO:xO;break;case Nr:o=s===es?wO:bO;break;case Br:o=s===es?MO:CO;break;case Dr:o=s===es?TO:EO;break;case Ir:o=s===es?PO:SO;break;case Lr:o=s===es?BO:NO;break;case jr:o=s===es?IO:DO;break;case Or:o=s===es?jO:LO;break;case zr:o=s===es?zO:OO;break;case rr:o=s===es?mj:gj;break;default:console.error("WebGPURenderer: Unsupported texture format.",n)}else switch(n){case rr:switch(i){case Vi:o=vj;break;case Wi:o=Nj;break;case Qi:o=Pj;break;case Yi:o=Dj;break;case Zi:o=Ij;break;case Gi:o=s===es?mj:gj;break;case Ki:o=Bj;break;case Ji:o=Lj;break;default:console.error("WebGPURenderer: Unsupported texture type with RGBAFormat.",i)}break;case ir:switch(i){case er:o=wj;break;case tr:o=Mj;break;default:console.error("WebGPURenderer: Unsupported texture type with RGBFormat.",i)}break;case ar:switch(i){case Vi:o=$L;break;case Wi:o=ij;break;case Qi:o=nj;break;case Yi:o=uj;break;case Zi:o=cj;break;case Gi:o=_L;break;case Ki:o=rj;break;case Ji:o=dj;break;default:console.error("WebGPURenderer: Unsupported texture type with RedFormat.",i)}break;case ur:switch(i){case Vi:o=oj;break;case Wi:o=fj;break;case Qi:o=hj;break;case Yi:o=Ej;break;case Zi:o=Tj;break;case Gi:o=sj;break;case Ki:o=pj;break;case Ji:o=Sj;break;default:console.error("WebGPURenderer: Unsupported texture type with RGFormat.",i)}break;case sr:switch(i){case Qi:o=jj;break;case Yi:o=Oj;break;case Ji:o=Rj;break;default:console.error("WebGPURenderer: Unsupported texture type with DepthFormat.",i)}break;case or:switch(i){case $i:o=zj;break;case Ji:t&&!1===t.features.has(Rz.Depth32FloatStencil8)&&console.error('WebGPURenderer: Depth textures with DepthStencilFormat + FloatType can only be used with the "depth32float-stencil8" GPU feature.'),o=kj;break;default:console.error("WebGPURenderer: Unsupported texture type with DepthStencilFormat.",i)}break;case lr:switch(i){case Zi:o=cj;break;case Yi:o=uj;break;default:console.error("WebGPURenderer: Unsupported texture type with RedIntegerFormat.",i)}break;case cr:switch(i){case Zi:o=Tj;break;case Yi:o=Ej;break;default:console.error("WebGPURenderer: Unsupported texture type with RGIntegerFormat.",i)}break;case dr:switch(i){case Zi:o=Ij;break;case Yi:o=Dj;break;default:console.error("WebGPURenderer: Unsupported texture type with RGBAIntegerFormat.",i)}break;default:console.error("WebGPURenderer: Unsupported texture format.",n)}return o}const Zz=/^[fn]*\s*([a-z_0-9]+)?\s*\(([\s\S]*?)\)\s*[\-\>]*\s*([a-z_0-9]+(?:<[\s\S]+?>)?)/i,Yz=/([a-z_0-9]+)\s*:\s*([a-z_0-9]+(?:<[\s\S]+?>)?)/gi,Jz={f32:"float",i32:"int",u32:"uint",bool:"bool","vec2<f32>":"vec2","vec2<i32>":"ivec2","vec2<u32>":"uvec2","vec2<bool>":"bvec2",vec2f:"vec2",vec2i:"ivec2",vec2u:"uvec2",vec2b:"bvec2","vec3<f32>":"vec3","vec3<i32>":"ivec3","vec3<u32>":"uvec3","vec3<bool>":"bvec3",vec3f:"vec3",vec3i:"ivec3",vec3u:"uvec3",vec3b:"bvec3","vec4<f32>":"vec4","vec4<i32>":"ivec4","vec4<u32>":"uvec4","vec4<bool>":"bvec4",vec4f:"vec4",vec4i:"ivec4",vec4u:"uvec4",vec4b:"bvec4","mat2x2<f32>":"mat2",mat2x2f:"mat2","mat3x3<f32>":"mat3",mat3x3f:"mat3","mat4x4<f32>":"mat4",mat4x4f:"mat4",sampler:"sampler",texture_1d:"texture",texture_2d:"texture",texture_2d_array:"texture",texture_multisampled_2d:"cubeTexture",texture_depth_2d:"depthTexture",texture_depth_2d_array:"depthTexture",texture_depth_multisampled_2d:"depthTexture",texture_depth_cube:"depthTexture",texture_depth_cube_array:"depthTexture",texture_3d:"texture3D",texture_cube:"cubeTexture",texture_cube_array:"cubeTexture",texture_storage_1d:"storageTexture",texture_storage_2d:"storageTexture",texture_storage_2d_array:"storageTexture",texture_storage_3d:"storageTexture"};class Kz extends iI{constructor(e){const{type:t,inputs:n,name:i,inputsCode:r,blockCode:s,outputType:o}=(e=>{const t=(e=e.trim()).match(Zz);if(null!==t&&4===t.length){const n=t[2],i=[];let r=null;for(;null!==(r=Yz.exec(n));)i.push({name:r[1],type:r[2]});const s=[];for(let e=0;e<i.length;e++){const{name:t,type:n}=i[e];let r=n;r.startsWith("ptr")?r="pointer":(r.startsWith("texture")&&(r=n.split("<")[0]),r=Jz[r]),s.push(new GD(r,t))}const o=e.substring(t[0].length),a=t[3]||"void",l=void 0!==t[1]?t[1]:"";return{type:Jz[a]||a,inputs:s,name:l,inputsCode:n,blockCode:o,outputType:a}}throw new Error("FunctionNode: Function is not a WGSL code.")})(e);super(t,n,i),this.inputsCode=r,this.blockCode=s,this.outputType=o}getCode(e=this.name){const t="void"!==this.outputType?"-> "+this.outputType:"";return`fn ${e} ( ${this.inputsCode.trim()} ) ${t}`+this.blockCode}}class qz extends nI{parseFunction(e){return new Kz(e)}}const _z="undefined"!=typeof self?self.GPUShaderStage:{VERTEX:1,FRAGMENT:2,COMPUTE:4},$z={[fv.READ_ONLY]:"read",[fv.WRITE_ONLY]:"write",[fv.READ_WRITE]:"read_write"},eR={[ji]:"repeat",[Oi]:"clamp",[zi]:"mirror"},tR={vertex:_z?_z.VERTEX:1,fragment:_z?_z.FRAGMENT:2,compute:_z?_z.COMPUTE:4},nR={instance:!0,swizzleAssign:!1,storageBuffer:!0},iR={"^^":"tsl_xor"},rR={float:"f32",int:"i32",uint:"u32",bool:"bool",color:"vec3<f32>",vec2:"vec2<f32>",ivec2:"vec2<i32>",uvec2:"vec2<u32>",bvec2:"vec2<bool>",vec3:"vec3<f32>",ivec3:"vec3<i32>",uvec3:"vec3<u32>",bvec3:"vec3<bool>",vec4:"vec4<f32>",ivec4:"vec4<i32>",uvec4:"vec4<u32>",bvec4:"vec4<bool>",mat2:"mat2x2<f32>",mat3:"mat3x3<f32>",mat4:"mat4x4<f32>"},sR={},oR={tsl_xor:new $N("fn tsl_xor( a : bool, b : bool ) -> bool { return ( a || b ) && !( a && b ); }"),mod_float:new $N("fn tsl_mod_float( x : f32, y : f32 ) -> f32 { return x - y * floor( x / y ); }"),mod_vec2:new $N("fn tsl_mod_vec2( x : vec2f, y : vec2f ) -> vec2f { return x - y * floor( x / y ); }"),mod_vec3:new $N("fn tsl_mod_vec3( x : vec3f, y : vec3f ) -> vec3f { return x - y * floor( x / y ); }"),mod_vec4:new $N("fn tsl_mod_vec4( x : vec4f, y : vec4f ) -> vec4f { return x - y * floor( x / y ); }"),equals_bool:new $N("fn tsl_equals_bool( a : bool, b : bool ) -> bool { return a == b; }"),equals_bvec2:new $N("fn tsl_equals_bvec2( a : vec2f, b : vec2f ) -> vec2<bool> { return vec2<bool>( a.x == b.x, a.y == b.y ); }"),equals_bvec3:new $N("fn tsl_equals_bvec3( a : vec3f, b : vec3f ) -> vec3<bool> { return vec3<bool>( a.x == b.x, a.y == b.y, a.z == b.z ); }"),equals_bvec4:new $N("fn tsl_equals_bvec4( a : vec4f, b : vec4f ) -> vec4<bool> { return vec4<bool>( a.x == b.x, a.y == b.y, a.z == b.z, a.w == b.w ); }"),repeatWrapping_float:new $N("fn tsl_repeatWrapping_float( coord: f32 ) -> f32 { return fract( coord ); }"),mirrorWrapping_float:new $N("fn tsl_mirrorWrapping_float( coord: f32 ) -> f32 { let mirrored = fract( coord * 0.5 ) * 2.0; return 1.0 - abs( 1.0 - mirrored ); }"),clampWrapping_float:new $N("fn tsl_clampWrapping_float( coord: f32 ) -> f32 { return clamp( coord, 0.0, 1.0 ); }"),biquadraticTexture:new $N("\nfn tsl_biquadraticTexture( map : texture_2d<f32>, coord : vec2f, iRes : vec2u, level : u32 ) -> vec4f {\n\n\tlet res = vec2f( iRes );\n\n\tlet uvScaled = coord * res;\n\tlet uvWrapping = ( ( uvScaled % res ) + res ) % res;\n\n\t// https://www.shadertoy.com/view/WtyXRy\n\n\tlet uv = uvWrapping - 0.5;\n\tlet iuv = floor( uv );\n\tlet f = fract( uv );\n\n\tlet rg1 = textureLoad( map, vec2u( iuv + vec2( 0.5, 0.5 ) ) % iRes, level );\n\tlet rg2 = textureLoad( map, vec2u( iuv + vec2( 1.5, 0.5 ) ) % iRes, level );\n\tlet rg3 = textureLoad( map, vec2u( iuv + vec2( 0.5, 1.5 ) ) % iRes, level );\n\tlet rg4 = textureLoad( map, vec2u( iuv + vec2( 1.5, 1.5 ) ) % iRes, level );\n\n\treturn mix( mix( rg1, rg2, f.x ), mix( rg3, rg4, f.x ), f.y );\n\n}\n")},aR={dFdx:"dpdx",dFdy:"- dpdy",mod_float:"tsl_mod_float",mod_vec2:"tsl_mod_vec2",mod_vec3:"tsl_mod_vec3",mod_vec4:"tsl_mod_vec4",equals_bool:"tsl_equals_bool",equals_bvec2:"tsl_equals_bvec2",equals_bvec3:"tsl_equals_bvec3",equals_bvec4:"tsl_equals_bvec4",inversesqrt:"inverseSqrt",bitcast:"bitcast<f32>"};let lR="";!0!==("undefined"!=typeof navigator&&/Firefox|Deno/g.test(navigator.userAgent))&&(lR+="diagnostic( off, derivative_uniformity );\n");class uR extends UD{constructor(e,t){super(e,t,new qz),this.uniformGroups={},this.builtins={},this.directives={},this.scopedArrays=new Map}_generateTextureSample(e,t,n,i,r,s=this.shaderStage){return"fragment"===s?i?r?`textureSample( ${t}, ${t}_sampler, ${n}, ${i}, ${r} )`:`textureSample( ${t}, ${t}_sampler, ${n}, ${i} )`:r?`textureSample( ${t}, ${t}_sampler, ${n}, ${r} )`:`textureSample( ${t}, ${t}_sampler, ${n} )`:this.generateTextureSampleLevel(e,t,n,"0",i)}generateTextureSampleLevel(e,t,n,i,r,s){return!1===this.isUnfilterable(e)?s?`textureSampleLevel( ${t}, ${t}_sampler, ${n}, ${i}, ${s} )`:`textureSampleLevel( ${t}, ${t}_sampler, ${n}, ${i} )`:this.isFilteredTexture(e)?this.generateFilteredTexture(e,t,n,s,i):this.generateTextureLod(e,t,n,r,s,i)}generateWrapFunction(e){const t=`tsl_coord_${eR[e.wrapS]}S_${eR[e.wrapT]}_${e.isData3DTexture?"3d":"2d"}T`;let n=sR[t];if(void 0===n){const i=[],r=e.isData3DTexture?"vec3f":"vec2f";let s=`fn ${t}( coord : ${r} ) -> ${r} {\n\n\treturn ${r}(\n`;const o=(e,t)=>{e===ji?(i.push(oR.repeatWrapping_float),s+=`\t\ttsl_repeatWrapping_float( coord.${t} )`):e===Oi?(i.push(oR.clampWrapping_float),s+=`\t\ttsl_clampWrapping_float( coord.${t} )`):e===zi?(i.push(oR.mirrorWrapping_float),s+=`\t\ttsl_mirrorWrapping_float( coord.${t} )`):(s+=`\t\tcoord.${t}`,console.warn(`WebGPURenderer: Unsupported texture wrap type "${e}" for vertex shader.`))};o(e.wrapS,"x"),s+=",\n",o(e.wrapT,"y"),e.isData3DTexture&&(s+=",\n",o(e.wrapR,"z")),s+="\n\t);\n\n}\n",sR[t]=n=new $N(s,i)}return n.build(this),t}generateArrayDeclaration(e,t){return`array< ${this.getType(e)}, ${t} >`}generateTextureDimension(e,t,n){const i=this.getDataFromNode(e,this.shaderStage,this.globalCache);void 0===i.dimensionsSnippet&&(i.dimensionsSnippet={});let r=i.dimensionsSnippet[n];if(void 0===i.dimensionsSnippet[n]){let s,o;const{primarySamples:a}=this.renderer.backend.utils.getTextureSampleData(e),l=a>1;o=e.isData3DTexture?"vec3<u32>":"vec2<u32>",s=l||e.isStorageTexture?t:`${t}${n?`, u32( ${n} )`:""}`,r=new Sb(new dw(`textureDimensions( ${s} )`,o)),i.dimensionsSnippet[n]=r,(e.isArrayTexture||e.isDataArrayTexture||e.isData3DTexture)&&(i.arrayLayerCount=new Sb(new dw(`textureNumLayers(${t})`,"u32"))),e.isTextureCube&&(i.cubeFaceCount=new Sb(new dw("6u","u32")))}return r.build(this)}generateFilteredTexture(e,t,n,i,r="0u"){this._include("biquadraticTexture");const s=this.generateWrapFunction(e),o=this.generateTextureDimension(e,t,r);return i&&(n=`${n} + vec2<f32>(${i}) / ${o}`),`tsl_biquadraticTexture( ${t}, ${s}( ${n} ), ${o}, u32( ${r} ) )`}generateTextureLod(e,t,n,i,r,s="0u"){const o=this.generateWrapFunction(e),a=this.generateTextureDimension(e,t,s),l=e.isData3DTexture?"vec3":"vec2";r&&(n=`${n} + ${l}<f32>(${r}) / ${l}<f32>( ${a} )`);const u=`${l}<u32>( ${o}( ${n} ) * ${l}<f32>( ${a} ) )`;return this.generateTextureLoad(e,t,u,i,null,s)}generateTextureLoad(e,t,n,i,r,s="0u"){let o;return r&&(n=`${n} + ${r}`),i?o=`textureLoad( ${t}, ${n}, ${i}, u32( ${s} ) )`:(o=`textureLoad( ${t}, ${n}, u32( ${s} ) )`,this.renderer.backend.compatibilityMode&&e.isDepthTexture&&(o+=".x")),o}generateTextureStore(e,t,n,i,r){let s;return s=i?`textureStore( ${t}, ${n}, ${i}, ${r} )`:`textureStore( ${t}, ${n}, ${r} )`,s}isSampleCompare(e){return!0===e.isDepthTexture&&null!==e.compareFunction}isUnfilterable(e){return"float"!==this.getComponentTypeFromTexture(e)||!this.isAvailable("float32Filterable")&&!0===e.isDataTexture&&e.type===Ji||!1===this.isSampleCompare(e)&&e.minFilter===Ri&&e.magFilter===Ri||this.renderer.backend.utils.getTextureSampleData(e).primarySamples>1}generateTexture(e,t,n,i,r,s=this.shaderStage){let o=null;return o=this.isUnfilterable(e)?this.generateTextureLod(e,t,n,i,r,"0",s):this._generateTextureSample(e,t,n,i,r,s),o}generateTextureGrad(e,t,n,i,r,s,o=this.shaderStage){if("fragment"===o)return s?`textureSampleGrad( ${t}, ${t}_sampler, ${n},  ${i[0]}, ${i[1]}, ${s} )`:`textureSampleGrad( ${t}, ${t}_sampler, ${n},  ${i[0]}, ${i[1]} )`;console.error(`WebGPURenderer: THREE.TextureNode.gradient() does not support ${o} shader.`)}generateTextureCompare(e,t,n,i,r,s,o=this.shaderStage){if("fragment"===o)return!0===e.isDepthTexture&&!0===e.isArrayTexture?s?`textureSampleCompare( ${t}, ${t}_sampler, ${n}, ${r}, ${i}, ${s} )`:`textureSampleCompare( ${t}, ${t}_sampler, ${n}, ${r}, ${i} )`:s?`textureSampleCompare( ${t}, ${t}_sampler, ${n}, ${i}, ${s} )`:`textureSampleCompare( ${t}, ${t}_sampler, ${n}, ${i} )`;console.error(`WebGPURenderer: THREE.DepthTexture.compareFunction() does not support ${o} shader.`)}generateTextureLevel(e,t,n,i,r,s){return!1===this.isUnfilterable(e)?s?`textureSampleLevel( ${t}, ${t}_sampler, ${n}, ${i}, ${s} )`:`textureSampleLevel( ${t}, ${t}_sampler, ${n}, ${i} )`:this.isFilteredTexture(e)?this.generateFilteredTexture(e,t,n,s,i):this.generateTextureLod(e,t,n,r,s,i)}generateTextureBias(e,t,n,i,r,s,o=this.shaderStage){if("fragment"===o)return s?`textureSampleBias( ${t}, ${t}_sampler, ${n}, ${i}, ${s} )`:`textureSampleBias( ${t}, ${t}_sampler, ${n}, ${i} )`;console.error(`WebGPURenderer: THREE.TextureNode.biasNode does not support ${o} shader.`)}getPropertyName(e,t=this.shaderStage){if(!0===e.isNodeVarying&&!0===e.needsInterpolation){if("vertex"===t)return`varyings.${e.name}`}else if(!0===e.isNodeUniform){const t=e.name,n=e.type;return"texture"===n||"cubeTexture"===n||"storageTexture"===n||"texture3D"===n?t:"buffer"===n||"storageBuffer"===n||"indirectStorageBuffer"===n?this.isCustomStruct(e)?t:t+".value":e.groupNode.name+"."+t}return super.getPropertyName(e)}getOutputStructName(){return"output"}getFunctionOperator(e){const t=iR[e];return void 0!==t?(this._include(t),t):null}getNodeAccess(e,t){return"compute"!==t?!0===e.isAtomic?(console.warn("WebGPURenderer: Atomic operations are only supported in compute shaders."),fv.READ_WRITE):fv.READ_ONLY:e.access}getStorageAccess(e,t){return $z[this.getNodeAccess(e,t)]}getUniformFromNode(e,t,n,i=null){const r=super.getUniformFromNode(e,t,n,i),s=this.getDataFromNode(e,n,this.globalCache);if(void 0===s.uniformGPU){let o;const a=e.groupNode,l=a.name,u=this.getBindGroupArray(l,n);if("texture"===t||"cubeTexture"===t||"storageTexture"===t||"texture3D"===t){let i=null;const s=this.getNodeAccess(e,n);if("texture"===t||"storageTexture"===t?i=!0===e.value.is3DTexture?new $I(r.name,r.node,a,s):new qI(r.name,r.node,a,s):"cubeTexture"===t?i=new _I(r.name,r.node,a,s):"texture3D"===t&&(i=new $I(r.name,r.node,a,s)),i.store=!0===e.isStorageTextureNode,i.setVisibility(tR[n]),!1===this.isUnfilterable(e.value)&&!1===i.store){const e=new kz(`${r.name}_sampler`,r.node,a);e.setVisibility(tR[n]),u.push(e,i),o=[e,i]}else u.push(i),o=[i]}else if("buffer"===t||"storageBuffer"===t||"indirectStorageBuffer"===t){const s=new("buffer"===t?VI:Uz)(e,a);s.setVisibility(tR[n]),u.push(s),o=s,r.name=i||"NodeBuffer_"+r.id}else{const e=this.uniformGroups[n]||(this.uniformGroups[n]={});let i=e[l];void 0===i&&(i=new ZI(l,a),i.setVisibility(tR[n]),e[l]=i,u.push(i)),o=this.getNodeUniform(r,t),i.addUniform(o)}s.uniformGPU=o}return r}getBuiltin(e,t,n,i=this.shaderStage){const r=this.builtins[i]||(this.builtins[i]=new Map);return!1===r.has(e)&&r.set(e,{name:e,property:t,type:n}),t}hasBuiltin(e,t=this.shaderStage){return void 0!==this.builtins[t]&&this.builtins[t].has(e)}getVertexIndex(){return"vertex"===this.shaderStage?this.getBuiltin("vertex_index","vertexIndex","u32","attribute"):"vertexIndex"}buildFunctionCode(e){const t=e.layout,n=this.flowShaderNode(e),i=[];for(const e of t.inputs)i.push(e.name+" : "+this.getType(e.type));let r=`fn ${t.name}( ${i.join(", ")} ) -> ${this.getType(t.type)} {\n${n.vars}\n${n.code}\n`;return n.result&&(r+=`\treturn ${n.result};\n`),r+="\n}\n",r}getInstanceIndex(){return"vertex"===this.shaderStage?this.getBuiltin("instance_index","instanceIndex","u32","attribute"):"instanceIndex"}getInvocationLocalIndex(){return this.getBuiltin("local_invocation_index","invocationLocalIndex","u32","attribute")}getSubgroupSize(){return this.enableSubGroups(),this.getBuiltin("subgroup_size","subgroupSize","u32","attribute")}getInvocationSubgroupIndex(){return this.enableSubGroups(),this.getBuiltin("subgroup_invocation_id","invocationSubgroupIndex","u32","attribute")}getSubgroupIndex(){return this.enableSubGroups(),this.getBuiltin("subgroup_id","subgroupIndex","u32","attribute")}getDrawIndex(){return null}getFrontFacing(){return this.getBuiltin("front_facing","isFront","bool")}getFragCoord(){return this.getBuiltin("position","fragCoord","vec4<f32>")+".xy"}getFragDepth(){return"output."+this.getBuiltin("frag_depth","depth","f32","output")}getClipDistance(){return"varyings.hw_clip_distances"}isFlipY(){return!1}enableDirective(e,t=this.shaderStage){(this.directives[t]||(this.directives[t]=new Set)).add(e)}getDirectives(e){const t=[],n=this.directives[e];if(void 0!==n)for(const e of n)t.push(`enable ${e};`);return t.join("\n")}enableSubGroups(){this.enableDirective("subgroups")}enableSubgroupsF16(){this.enableDirective("subgroups-f16")}enableClipDistances(){this.enableDirective("clip_distances")}enableShaderF16(){this.enableDirective("f16")}enableDualSourceBlending(){this.enableDirective("dual_source_blending")}enableHardwareClipping(e){this.enableClipDistances(),this.getBuiltin("clip_distances","hw_clip_distances",`array<f32, ${e} >`,"vertex")}getBuiltins(e){const t=[],n=this.builtins[e];if(void 0!==n)for(const{name:e,property:i,type:r}of n.values())t.push(`@builtin( ${e} ) ${i} : ${r}`);return t.join(",\n\t")}getScopedArray(e,t,n,i){return!1===this.scopedArrays.has(e)&&this.scopedArrays.set(e,{name:e,scope:t,bufferType:n,bufferCount:i}),e}getScopedArrays(e){if("compute"!==e)return;const t=[];for(const{name:e,scope:n,bufferType:i,bufferCount:r}of this.scopedArrays.values()){const s=this.getType(i);t.push(`var<${n}> ${e}: array< ${s}, ${r} >;`)}return t.join("\n")}getAttributes(e){const t=[];if("compute"===e&&(this.getBuiltin("global_invocation_id","globalId","vec3<u32>","attribute"),this.getBuiltin("workgroup_id","workgroupId","vec3<u32>","attribute"),this.getBuiltin("local_invocation_id","localId","vec3<u32>","attribute"),this.getBuiltin("num_workgroups","numWorkgroups","vec3<u32>","attribute"),this.renderer.hasFeature("subgroups")&&(this.enableDirective("subgroups",e),this.getBuiltin("subgroup_size","subgroupSize","u32","attribute"))),"vertex"===e||"compute"===e){const e=this.getBuiltins("attribute");e&&t.push(e);const n=this.getAttributesArray();for(let e=0,i=n.length;e<i;e++){const i=n[e],r=i.name,s=this.getType(i.type);t.push(`@location( ${e} ) ${r} : ${s}`)}}return t.join(",\n\t")}getStructMembers(e){const t=[];for(const n of e.members){const i=e.output?"@location( "+n.index+" ) ":"";let r=this.getType(n.type);n.atomic&&(r="atomic< "+r+" >"),t.push(`\t${i+n.name} : ${r}`)}return e.output&&t.push(`\t${this.getBuiltins("output")}`),t.join(",\n")}getStructs(e){let t="";const n=this.structs[e];if(n.length>0){const e=[];for(const t of n){let n=`struct ${t.name} {\n`;n+=this.getStructMembers(t),n+="\n};",e.push(n)}t="\n"+e.join("\n\n")+"\n"}return t}getVar(e,t,n=null){let i=`var ${t} : `;return i+=null!==n?this.generateArrayDeclaration(e,n):this.getType(e),i}getVars(e){const t=[],n=this.vars[e];if(void 0!==n)for(const e of n)t.push(`\t${this.getVar(e.type,e.name,e.count)};`);return`\n${t.join("\n")}\n`}getVaryings(e){const t=[];if("vertex"===e&&this.getBuiltin("position","Vertex","vec4<f32>","vertex"),"vertex"===e||"fragment"===e){const n=this.varyings,i=this.vars[e];for(let r=0;r<n.length;r++){const s=n[r];if(s.needsInterpolation){let e=`@location( ${r} )`;if(s.interpolationType){const t=null!==s.interpolationSampling?`, ${s.interpolationSampling} )`:" )";e+=` @interpolate( ${s.interpolationType}${t}`}else/^(int|uint|ivec|uvec)/.test(s.type)&&(e+=` @interpolate( ${this.renderer.backend.compatibilityMode?"flat, either":"flat"} )`);t.push(`${e} ${s.name} : ${this.getType(s.type)}`)}else"vertex"===e&&!1===i.includes(s)&&i.push(s)}}const n=this.getBuiltins(e);n&&t.push(n);const i=t.join(",\n\t");return"vertex"===e?this._getWGSLStruct("VaryingsStruct","\t"+i):i}isCustomStruct(e){const t=e.value,n=e.node,i=(t.isBufferAttribute||t.isInstancedBufferAttribute)&&null!==n.structTypeNode,r=n.value&&n.value.array&&"number"==typeof n.value.itemSize&&n.value.array.length>n.value.itemSize;return i&&!r}getUniforms(e){const t=this.uniforms[e],n=[],i=[],r=[],s={};for(const r of t){const t=r.groupNode.name,o=this.bindingsIndexes[t];if("texture"===r.type||"cubeTexture"===r.type||"storageTexture"===r.type||"texture3D"===r.type){const t=r.node.value;let i;!1===this.isUnfilterable(t)&&!0!==r.node.isStorageTextureNode&&(this.isSampleCompare(t)?n.push(`@binding( ${o.binding++} ) @group( ${o.group} ) var ${r.name}_sampler : sampler_comparison;`):n.push(`@binding( ${o.binding++} ) @group( ${o.group} ) var ${r.name}_sampler : sampler;`));let s="";const{primarySamples:a}=this.renderer.backend.utils.getTextureSampleData(t);if(a>1&&(s="_multisampled"),!0===t.isCubeTexture)i="texture_cube<f32>";else if(!0===t.isDepthTexture)i=this.renderer.backend.compatibilityMode&&null===t.compareFunction?`texture${s}_2d<f32>`:`texture_depth${s}_2d${!0===t.isArrayTexture?"_array":""}`;else if(!0===r.node.isStorageTextureNode){const n=Qz(t),s=this.getStorageAccess(r.node,e),o=r.node.value.is3DTexture,a=r.node.value.isArrayTexture;i=`texture_storage_${o?"3d":"2d"+(a?"_array":"")}<${n}, ${s}>`}else if(!0===t.isArrayTexture||!0===t.isDataArrayTexture||!0===t.isCompressedArrayTexture)i="texture_2d_array<f32>";else if(!0===t.is3DTexture||!0===t.isData3DTexture)i="texture_3d<f32>";else{i=`texture${s}_2d<${this.getComponentTypeFromTexture(t).charAt(0)}32>`}n.push(`@binding( ${o.binding++} ) @group( ${o.group} ) var ${r.name} : ${i};`)}else if("buffer"===r.type||"storageBuffer"===r.type||"indirectStorageBuffer"===r.type){const t=r.node,n=this.getType(t.getNodeType(this)),s=t.bufferCount,a=s>0&&"buffer"===r.type?", "+s:"",l=t.isStorageBufferNode?`storage, ${this.getStorageAccess(t,e)}`:"uniform";if(this.isCustomStruct(r))i.push(`@binding( ${o.binding++} ) @group( ${o.group} ) var<${l}> ${r.name} : ${n};`);else{const e=`\tvalue : array< ${t.isAtomic?`atomic<${n}>`:`${n}`}${a} >`;i.push(this._getWGSLStructBinding(r.name,e,l,o.binding++,o.group))}}else{const e=this.getType(this.getVectorType(r.type)),t=r.groupNode.name;(s[t]||(s[t]={index:o.binding++,id:o.group,snippets:[]})).snippets.push(`\t${r.name} : ${e}`)}}for(const e in s){const t=s[e];r.push(this._getWGSLStructBinding(e,t.snippets.join(",\n"),"uniform",t.index,t.id))}let o=n.join("\n");return o+=i.join("\n"),o+=r.join("\n"),o}buildCode(){const e=null!==this.material?{fragment:{},vertex:{}}:{compute:{}};this.sortBindingGroups();for(const t in e){this.shaderStage=t;const n=e[t];n.uniforms=this.getUniforms(t),n.attributes=this.getAttributes(t),n.varyings=this.getVaryings(t),n.structs=this.getStructs(t),n.vars=this.getVars(t),n.codes=this.getCodes(t),n.directives=this.getDirectives(t),n.scopedArrays=this.getScopedArrays(t);let i="// code\n\n";i+=this.flowCode[t];const r=this.flowNodes[t],s=r[r.length-1],o=s.outputNode,a=void 0!==o&&!0===o.isOutputStructNode;for(const e of r){const r=this.getFlowData(e),l=e.name;if(l&&(i.length>0&&(i+="\n"),i+=`\t// flow -> ${l}\n`),i+=`${r.code}\n\t`,e===s&&"compute"!==t)if(i+="// result\n\n\t","vertex"===t)i+=`varyings.Vertex = ${r.result};`;else if("fragment"===t)if(a)n.returnType=o.getNodeType(this),n.structs+="var<private> output : "+n.returnType+";",i+=`return ${r.result};`;else{let e="\t@location(0) color: vec4<f32>";const t=this.getBuiltins("output");t&&(e+=",\n\t"+t),n.returnType="OutputStruct",n.structs+=this._getWGSLStruct("OutputStruct",e),n.structs+="\nvar<private> output : OutputStruct;",i+=`output.color = ${r.result};\n\n\treturn output;`}}n.flow=i}if(this.shaderStage=null,null!==this.material)this.vertexShader=this._getWGSLVertexCode(e.vertex),this.fragmentShader=this._getWGSLFragmentCode(e.fragment);else{const t=this.object.workgroupSize;this.computeShader=this._getWGSLComputeCode(e.compute,t)}}getMethod(e,t=null){let n;return null!==t&&(n=this._getWGSLMethod(e+"_"+t)),void 0===n&&(n=this._getWGSLMethod(e)),n||e}getBitcastMethod(e){return`bitcast<${this.getType(e)}>`}getTernary(e,t,n){return`select( ${n}, ${t}, ${e} )`}getType(e){return rR[e]||e}isAvailable(e){let t=nR[e];return void 0===t&&("float32Filterable"===e?t=this.renderer.hasFeature("float32-filterable"):"clipDistance"===e&&(t=this.renderer.hasFeature("clip-distances")),nR[e]=t),t}_getWGSLMethod(e){return void 0!==oR[e]&&this._include(e),aR[e]}_include(e){const t=oR[e];return t.build(this),null!==this.currentFunctionNode&&this.currentFunctionNode.includes.push(t),t}_getWGSLVertexCode(e){return`${this.getSignature()}\n// directives\n${e.directives}\n\n// structs\n${e.structs}\n\n// uniforms\n${e.uniforms}\n\n// varyings\n${e.varyings}\nvar<private> varyings : VaryingsStruct;\n\n// codes\n${e.codes}\n\n@vertex\nfn main( ${e.attributes} ) -> VaryingsStruct {\n\n\t// vars\n\t${e.vars}\n\n\t// flow\n\t${e.flow}\n\n\treturn varyings;\n\n}\n`}_getWGSLFragmentCode(e){return`${this.getSignature()}\n// global\n${lR}\n\n// structs\n${e.structs}\n\n// uniforms\n${e.uniforms}\n\n// codes\n${e.codes}\n\n@fragment\nfn main( ${e.varyings} ) -> ${e.returnType} {\n\n\t// vars\n\t${e.vars}\n\n\t// flow\n\t${e.flow}\n\n}\n`}_getWGSLComputeCode(e,t){const[n,i,r]=t;return`${this.getSignature()}\n// directives\n${e.directives}\n\n// system\nvar<private> instanceIndex : u32;\n\n// locals\n${e.scopedArrays}\n\n// structs\n${e.structs}\n\n// uniforms\n${e.uniforms}\n\n// codes\n${e.codes}\n\n@compute @workgroup_size( ${n}, ${i}, ${r} )\nfn main( ${e.attributes} ) {\n\n\t// system\n\tinstanceIndex = globalId.x\n\t\t+ globalId.y * ( ${n} * numWorkgroups.x )\n\t\t+ globalId.z * ( ${n} * numWorkgroups.x ) * ( ${i} * numWorkgroups.y );\n\n\t// vars\n\t${e.vars}\n\n\t// flow\n\t${e.flow}\n\n}\n`}_getWGSLStruct(e,t){return`\nstruct ${e} {\n${t}\n};`}_getWGSLStructBinding(e,t,n,i=0,r=0){const s=e+"Struct";return`${this._getWGSLStruct(s,t)}\n@binding( ${i} ) @group( ${r} )\nvar<${n}> ${e} : ${s};`}}class cR{constructor(e){this.backend=e}getCurrentDepthStencilFormat(e){let t;return null!==e.depthTexture?t=this.getTextureFormatGPU(e.depthTexture):e.depth&&e.stencil?t=zj:e.depth&&(t=Oj),t}getTextureFormatGPU(e){return this.backend.get(e).format}getTextureSampleData(e){let t;if(e.isFramebufferTexture)t=1;else if(e.isDepthTexture&&!e.renderTarget){const e=this.backend.renderer,n=e.getRenderTarget();t=n?n.samples:e.samples}else e.renderTarget&&(t=e.renderTarget.samples);t=t||1;const n=t>1&&null!==e.renderTarget&&!0!==e.isDepthTexture&&!0!==e.isFramebufferTexture;return{samples:t,primarySamples:n?1:t,isMSAA:n}}getCurrentColorFormat(e){let t;return t=null!==e.textures?this.getTextureFormatGPU(e.textures[0]):this.getPreferredCanvasFormat(),t}getCurrentColorSpace(e){return null!==e.textures?e.textures[0].colorSpace:this.backend.renderer.outputColorSpace}getPrimitiveTopology(e,t){return e.isPoints?BL:e.isLineSegments||e.isMesh&&!0===t.wireframe?DL:e.isLine?IL:e.isMesh?LL:void 0}getSampleCount(e){return e>=4?4:1}getSampleCountRenderContext(e){return null!==e.textures?this.getSampleCount(e.sampleCount):this.getSampleCount(this.backend.renderer.samples)}getPreferredCanvasFormat(){const e=this.backend.parameters.outputType;if(void 0===e)return navigator.gpu.getPreferredCanvasFormat();if(e===Gi)return yj;if(e===Ki)return Bj;throw new Error("Unsupported outputType")}}const dR=new Map([[Int8Array,["sint8","snorm8"]],[Uint8Array,["uint8","unorm8"]],[Int16Array,["sint16","snorm16"]],[Uint16Array,["uint16","unorm16"]],[Int32Array,["sint32","snorm32"]],[Uint32Array,["uint32","unorm32"]],[Float32Array,["float32"]]]);"undefined"!=typeof Float16Array&&dR.set(Float16Array,["float16"]);const hR=new Map([[Oa,["float16"]]]),fR=new Map([[Int32Array,"sint32"],[Int16Array,"sint32"],[Uint32Array,"uint32"],[Uint16Array,"uint32"],[Float32Array,"float32"]]);class pR{constructor(e){this.backend=e}createAttribute(e,t){const n=this._getBufferAttribute(e),i=this.backend,r=i.get(n);let s=r.buffer;if(void 0===s){const o=i.device;let a=n.array;if(!1===e.normalized)if(a.constructor===Int16Array||a.constructor===Int8Array)a=new Int32Array(a);else if((a.constructor===Uint16Array||a.constructor===Uint8Array)&&(a=new Uint32Array(a),t&GPUBufferUsage.INDEX))for(let e=0;e<a.length;e++)65535===a[e]&&(a[e]=4294967295);if(n.array=a,(n.isStorageBufferAttribute||n.isStorageInstancedBufferAttribute)&&3===n.itemSize){a=new a.constructor(4*n.count);for(let e=0;e<n.count;e++)a.set(n.array.subarray(3*e,3*e+3),4*e);n.itemSize=4,n.array=a,r._force3to4BytesAlignment=!0}const l=a.byteLength,u=l+(4-l%4)%4;s=o.createBuffer({label:n.name,size:u,usage:t,mappedAtCreation:!0}),new a.constructor(s.getMappedRange()).set(a),s.unmap(),r.buffer=s}}updateAttribute(e){const t=this._getBufferAttribute(e),n=this.backend,i=n.device,r=n.get(t),s=n.get(t).buffer;let o=t.array;if(!0===r._force3to4BytesAlignment){o=new o.constructor(4*t.count);for(let e=0;e<t.count;e++)o.set(t.array.subarray(3*e,3*e+3),4*e);t.array=o}const a=this._isTypedArray(o),l=t.updateRanges;if(0===l.length)i.queue.writeBuffer(s,0,o,0);else{const e=a?1:o.BYTES_PER_ELEMENT;for(let t=0,n=l.length;t<n;t++){const n=l[t];let u,c;if(!0===r._force3to4BytesAlignment){u=4*Math.floor(n.start/3)*e,c=4*Math.ceil(n.count/3)*e}else u=n.start*e,c=n.count*e;const d=u*(a?o.BYTES_PER_ELEMENT:1);i.queue.writeBuffer(s,d,o,u,c)}t.clearUpdateRanges()}}createShaderVertexBuffers(e){const t=e.getAttributes(),n=new Map;for(let e=0;e<t.length;e++){const i=t[e],r=i.array.BYTES_PER_ELEMENT,s=this._getBufferAttribute(i);let o=n.get(s);if(void 0===o){let e,t;!0===i.isInterleavedBufferAttribute?(e=i.data.stride*r,t=i.data.isInstancedInterleavedBuffer?zz:Oz):(e=i.itemSize*r,t=i.isInstancedBufferAttribute?zz:Oz),!1!==i.normalized||i.array.constructor!==Int16Array&&i.array.constructor!==Uint16Array||(e=4),o={arrayStride:e,attributes:[],stepMode:t},n.set(s,o)}const a=this._getVertexFormat(i),l=!0===i.isInterleavedBufferAttribute?i.offset*r:0;o.attributes.push({shaderLocation:e,offset:l,format:a})}return Array.from(n.values())}destroyAttribute(e){const t=this.backend;t.get(this._getBufferAttribute(e)).buffer.destroy(),t.delete(e)}async getArrayBufferAsync(e){const t=this.backend,n=t.device,i=t.get(this._getBufferAttribute(e)).buffer,r=i.size,s=n.createBuffer({label:`${e.name}_readback`,size:r,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ}),o=n.createCommandEncoder({label:`readback_encoder_${e.name}`});o.copyBufferToBuffer(i,0,s,0,r);const a=o.finish();n.queue.submit([a]),await s.mapAsync(GPUMapMode.READ);const l=s.getMappedRange(),u=new e.array.constructor(l.slice(0));return s.unmap(),u.buffer}_getVertexFormat(e){const{itemSize:t,normalized:n}=e,i=e.array.constructor,r=e.constructor;let s;if(1===t)s=fR.get(i);else{const e=(hR.get(r)||dR.get(i))[n?1:0];if(e){const n=i.BYTES_PER_ELEMENT*t,r=4*Math.floor((n+3)/4)/i.BYTES_PER_ELEMENT;if(r%1)throw new Error("THREE.WebGPUAttributeUtils: Bad vertex format item size.");s=`${e}x${r}`}}return s||console.error("THREE.WebGPUAttributeUtils: Vertex format not supported yet."),s}_isTypedArray(e){return ArrayBuffer.isView(e)&&!(e instanceof DataView)}_getBufferAttribute(e){return e.isInterleavedBufferAttribute&&(e=e.data),e}}class gR{constructor(e){this.backend=e,this.bindGroupLayoutCache=new WeakMap}createBindingsLayout(e){const t=this.backend,n=t.device,i=[];let r=0;for(const n of e.bindings){const e={binding:r++,visibility:n.visibility};if(n.isUniformBuffer||n.isStorageBuffer){const t={};n.isStorageBuffer&&(4&n.visibility&&(n.access===fv.READ_WRITE||n.access===fv.WRITE_ONLY)?t.type=mz:t.type=vz),e.buffer=t}else if(n.isSampledTexture&&n.store){const t={};t.format=this.backend.get(n.texture).texture.format;const i=n.access;t.access=i===fv.READ_WRITE?yz:i===fv.WRITE_ONLY?Az:xz,n.texture.isArrayTexture?t.viewDimension=Dz:n.texture.is3DTexture&&(t.viewDimension=Lz),e.storageTexture=t}else if(n.isSampledTexture){const i={},{primarySamples:r}=t.utils.getTextureSampleData(n.texture);if(r>1&&(i.multisampled=!0,n.texture.isDepthTexture||(i.sampleType=Mz)),n.texture.isDepthTexture)t.compatibilityMode&&null===n.texture.compareFunction?i.sampleType=Mz:i.sampleType=Ez;else if(n.texture.isDataTexture||n.texture.isDataArrayTexture||n.texture.isData3DTexture){const e=n.texture.type;e===Zi?i.sampleType=Tz:e===Yi?i.sampleType=Sz:e===Ji&&(this.backend.hasFeature("float32-filterable")?i.sampleType=Cz:i.sampleType=Mz)}n.isSampledCubeTexture?i.viewDimension=Iz:n.texture.isArrayTexture||n.texture.isDataArrayTexture||n.texture.isCompressedArrayTexture?i.viewDimension=Dz:n.isSampledTexture3D&&(i.viewDimension=Lz),e.texture=i}else if(n.isSampler){const i={};n.texture.isDepthTexture&&(null!==n.texture.compareFunction?i.type=wz:t.compatibilityMode&&(i.type=bz)),e.sampler=i}else console.error(`WebGPUBindingUtils: Unsupported binding "${n}".`);i.push(e)}return n.createBindGroupLayout({entries:i})}createBindings(e,t,n,i=0){const{backend:r,bindGroupLayoutCache:s}=this,o=r.get(e);let a,l=s.get(e.bindingsReference);void 0===l&&(l=this.createBindingsLayout(e),s.set(e.bindingsReference,l)),n>0&&(void 0===o.groups&&(o.groups=[],o.versions=[]),o.versions[n]===i&&(a=o.groups[n])),void 0===a&&(a=this.createBindGroup(e,l),n>0&&(o.groups[n]=a,o.versions[n]=i)),o.group=a,o.layout=l}updateBinding(e){const t=this.backend,n=t.device,i=e.buffer,r=t.get(e).buffer;n.queue.writeBuffer(r,0,i,0)}createBindGroupIndex(e,t){const n=this.backend.device,i=GPUBufferUsage.UNIFORM|GPUBufferUsage.COPY_DST,r=e[0],s=n.createBuffer({label:"bindingCameraIndex_"+r,size:16,usage:i});n.queue.writeBuffer(s,0,e,0);const o=[{binding:0,resource:{buffer:s}}];return n.createBindGroup({label:"bindGroupCameraIndex_"+r,layout:t,entries:o})}createBindGroup(e,t){const n=this.backend,i=n.device;let r=0;const s=[];for(const t of e.bindings){if(t.isUniformBuffer){const e=n.get(t);if(void 0===e.buffer){const n=t.byteLength,r=GPUBufferUsage.UNIFORM|GPUBufferUsage.COPY_DST,s=i.createBuffer({label:"bindingBuffer_"+t.name,size:n,usage:r});e.buffer=s}s.push({binding:r,resource:{buffer:e.buffer}})}else if(t.isStorageBuffer){const e=n.get(t);if(void 0===e.buffer){const i=t.attribute;e.buffer=n.get(i).buffer}s.push({binding:r,resource:{buffer:e.buffer}})}else if(t.isSampledTexture){const e=n.get(t.texture);let o;if(void 0!==e.externalTexture)o=i.importExternalTexture({source:e.externalTexture});else{const n=t.store?1:e.texture.mipLevelCount;let i=`view-${e.texture.width}-${e.texture.height}`;if(e.texture.depthOrArrayLayers>1&&(i+=`-${e.texture.depthOrArrayLayers}`),i+=`-${n}`,o=e[i],void 0===o){const r=jz;let s;s=t.isSampledCubeTexture?Iz:t.isSampledTexture3D?Lz:t.texture.isArrayTexture||t.texture.isDataArrayTexture||t.texture.isCompressedArrayTexture?Dz:Bz,o=e[i]=e.texture.createView({aspect:r,dimension:s,mipLevelCount:n})}}s.push({binding:r,resource:o})}else if(t.isSampler){const e=n.get(t.texture);s.push({binding:r,resource:e.sampler})}r++}return i.createBindGroup({label:"bindGroup_"+e.name,layout:t,entries:s})}}class mR{constructor(e){this.backend=e,this._activePipelines=new WeakMap}setPipeline(e,t){this._activePipelines.get(e)!==t&&(e.setPipeline(t),this._activePipelines.set(e,t))}_getSampleCount(e){return this.backend.utils.getSampleCountRenderContext(e)}createRenderPipeline(e,t){const{object:n,material:i,geometry:r,pipeline:s}=e,{vertexProgram:o,fragmentProgram:a}=s,l=this.backend,u=l.device,c=l.utils,d=l.get(s),h=[];for(const t of e.getBindings()){const e=l.get(t);h.push(e.layout)}const f=l.attributeUtils.createShaderVertexBuffers(e);let p;0===i.blending||1===i.blending&&!1===i.transparent||(p=this._getBlending(i));let g={};!0===i.stencilWrite&&(g={compare:this._getStencilCompare(i),failOp:this._getStencilOperation(i.stencilFail),depthFailOp:this._getStencilOperation(i.stencilZFail),passOp:this._getStencilOperation(i.stencilZPass)});const m=this._getColorWriteMask(i),v=[];if(null!==e.context.textures){const t=e.context.textures;for(let e=0;e<t.length;e++){const n=c.getTextureFormatGPU(t[e]);v.push({format:n,blend:p,writeMask:m})}}else{const t=c.getCurrentColorFormat(e.context);v.push({format:t,blend:p,writeMask:m})}const A=l.get(o).module,x=l.get(a).module,y=this._getPrimitiveState(n,r,i),b=this._getDepthCompare(i),w=c.getCurrentDepthStencilFormat(e.context),C=this._getSampleCount(e.context),M={label:`renderPipeline_${i.name||i.type}_${i.id}`,vertex:Object.assign({},A,{buffers:f}),fragment:Object.assign({},x,{targets:v}),primitive:y,multisample:{count:C,alphaToCoverageEnabled:i.alphaToCoverage&&C>1},layout:u.createPipelineLayout({bindGroupLayouts:h})},E={},T=e.context.depth,S=e.context.stencil;if(!0!==T&&!0!==S||(!0===T&&(E.format=w,E.depthWriteEnabled=i.depthWrite,E.depthCompare=b),!0===S&&(E.stencilFront=g,E.stencilBack={},E.stencilReadMask=i.stencilFuncMask,E.stencilWriteMask=i.stencilWriteMask),!0===i.polygonOffset&&(E.depthBias=i.polygonOffsetUnits,E.depthBiasSlopeScale=i.polygonOffsetFactor,E.depthBiasClamp=0),M.depthStencil=E),null===t)d.pipeline=u.createRenderPipeline(M);else{const e=new Promise((e=>{u.createRenderPipelineAsync(M).then((t=>{d.pipeline=t,e()}))}));t.push(e)}}createBundleEncoder(e,t="renderBundleEncoder"){const n=this.backend,{utils:i,device:r}=n,s=i.getCurrentDepthStencilFormat(e),o={label:t,colorFormats:[i.getCurrentColorFormat(e)],depthStencilFormat:s,sampleCount:this._getSampleCount(e)};return r.createRenderBundleEncoder(o)}createComputePipeline(e,t){const n=this.backend,i=n.device,r=n.get(e.computeProgram).module,s=n.get(e),o=[];for(const e of t){const t=n.get(e);o.push(t.layout)}s.pipeline=i.createComputePipeline({compute:r,layout:i.createPipelineLayout({bindGroupLayouts:o})})}_getBlending(e){let t,n;const i=e.blending,r=e.blendSrc,s=e.blendDst,o=e.blendEquation;if(5===i){const i=null!==e.blendSrcAlpha?e.blendSrcAlpha:r,a=null!==e.blendDstAlpha?e.blendDstAlpha:s,l=null!==e.blendEquationAlpha?e.blendEquationAlpha:o;t={srcFactor:this._getBlendFactor(r),dstFactor:this._getBlendFactor(s),operation:this._getBlendOperation(o)},n={srcFactor:this._getBlendFactor(i),dstFactor:this._getBlendFactor(a),operation:this._getBlendOperation(l)}}else{const r=(e,i,r,s)=>{t={srcFactor:e,dstFactor:i,operation:tz},n={srcFactor:r,dstFactor:s,operation:tz}};if(e.premultipliedAlpha)switch(i){case 1:r(GO,ZO,GO,ZO);break;case 2:r(GO,GO,GO,GO);break;case 3:r(XO,WO,XO,GO);break;case 4:r(YO,ZO,XO,GO)}else switch(i){case 1:r(QO,ZO,GO,ZO);break;case 2:r(QO,GO,GO,GO);break;case 3:console.error("THREE.WebGPURenderer: SubtractiveBlending requires material.premultipliedAlpha = true");break;case 4:console.error("THREE.WebGPURenderer: MultiplyBlending requires material.premultipliedAlpha = true")}}if(void 0!==t&&void 0!==n)return{color:t,alpha:n};console.error("THREE.WebGPURenderer: Invalid blending: ",i)}_getBlendFactor(e){let t;switch(e){case Ei:t=XO;break;case 201:t=GO;break;case 202:t=VO;break;case 203:t=WO;break;case Ti:t=QO;break;case Si:t=ZO;break;case 208:t=YO;break;case 209:t=JO;break;case 206:t=KO;break;case 207:t=qO;break;case 210:t=_O;break;case 211:t=$O;break;case 212:t=ez;break;default:console.error("THREE.WebGPURenderer: Blend factor not supported.",e)}return t}_getStencilCompare(e){let t;const n=e.stencilFunc;switch(n){case 512:t=OL;break;case 519:t=XL;break;case 513:t=zL;break;case 515:t=kL;break;case 514:t=RL;break;case 518:t=UL;break;case 516:t=FL;break;case 517:t=HL;break;default:console.error("THREE.WebGPURenderer: Invalid stencil function.",n)}return t}_getStencilOperation(e){let t;switch(e){case ts:t=lz;break;case 0:t=uz;break;case 7681:t=cz;break;case 5386:t=dz;break;case 7682:t=hz;break;case 7683:t=fz;break;case 34055:t=pz;break;case 34056:t=gz;break;default:console.error("THREE.WebGPURenderer: Invalid stencil operation.",t)}return t}_getBlendOperation(e){let t;switch(e){case Mi:t=tz;break;case 101:t=nz;break;case 102:t=iz;break;case 103:t=rz;break;case 104:t=sz;break;default:console.error("THREE.WebGPUPipelineUtils: Blend equation not supported.",e)}return t}_getPrimitiveState(e,t,n){const i={},r=this.backend.utils;i.topology=r.getPrimitiveTopology(e,n),null!==t.index&&!0===e.isLine&&!0!==e.isLineSegments&&(i.stripIndexFormat=t.index.array instanceof Uint16Array?KL:qL);let s=1===n.side;return e.isMesh&&e.matrixWorld.determinant()<0&&(s=!s),i.frontFace=!0===s?ZL:QL,i.cullMode=2===n.side?YL:JL,i}_getColorWriteMask(e){return!0===e.colorWrite?az:oz}_getDepthCompare(e){let t;if(!1===e.depthTest)t=XL;else{const n=e.depthFunc;switch(n){case 0:t=OL;break;case 1:t=XL;break;case 2:t=zL;break;case 3:t=kL;break;case 4:t=RL;break;case 5:t=UL;break;case 6:t=FL;break;case 7:t=HL;break;default:console.error("THREE.WebGPUPipelineUtils: Invalid depth function.",n)}}return t}}class vR extends SL{constructor(e,t,n=2048){super(n),this.device=e,this.type=t,this.querySet=this.device.createQuerySet({type:"timestamp",count:this.maxQueries,label:`queryset_global_timestamp_${t}`});const i=8*this.maxQueries;this.resolveBuffer=this.device.createBuffer({label:`buffer_timestamp_resolve_${t}`,size:i,usage:GPUBufferUsage.QUERY_RESOLVE|GPUBufferUsage.COPY_SRC}),this.resultBuffer=this.device.createBuffer({label:`buffer_timestamp_result_${t}`,size:i,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ})}allocateQueriesForContext(e){if(!this.trackTimestamp||this.isDisposed)return null;if(this.currentQueryIndex+2>this.maxQueries)return js(`WebGPUTimestampQueryPool [${this.type}]: Maximum number of queries exceeded, when using trackTimestamp it is necessary to resolves the queries via renderer.resolveTimestampsAsync( THREE.TimestampQuery.${this.type.toUpperCase()} ).`),null;const t=this.currentQueryIndex;return this.currentQueryIndex+=2,this.queryOffsets.set(e,t),t}async resolveQueriesAsync(){if(!this.trackTimestamp||0===this.currentQueryIndex||this.isDisposed)return this.lastValue;if(this.pendingResolve)return this.pendingResolve;this.pendingResolve=this._resolveQueries();try{return await this.pendingResolve}finally{this.pendingResolve=null}}async _resolveQueries(){if(this.isDisposed)return this.lastValue;try{if("unmapped"!==this.resultBuffer.mapState)return this.lastValue;const e=new Map(this.queryOffsets),t=this.currentQueryIndex,n=8*t;this.currentQueryIndex=0,this.queryOffsets.clear();const i=this.device.createCommandEncoder();i.resolveQuerySet(this.querySet,0,t,this.resolveBuffer,0),i.copyBufferToBuffer(this.resolveBuffer,0,this.resultBuffer,0,n);const r=i.finish();if(this.device.queue.submit([r]),"unmapped"!==this.resultBuffer.mapState)return this.lastValue;if(await this.resultBuffer.mapAsync(GPUMapMode.READ,0,n),this.isDisposed)return"mapped"===this.resultBuffer.mapState&&this.resultBuffer.unmap(),this.lastValue;const s=new BigUint64Array(this.resultBuffer.getMappedRange(0,n));let o=0;for(const[,t]of e){const e=s[t],n=s[t+1];o+=Number(n-e)/1e6}return this.resultBuffer.unmap(),this.lastValue=o,o}catch(e){return console.error("Error resolving queries:",e),"mapped"===this.resultBuffer.mapState&&this.resultBuffer.unmap(),this.lastValue}}async dispose(){if(!this.isDisposed){if(this.isDisposed=!0,this.pendingResolve)try{await this.pendingResolve}catch(e){console.error("Error waiting for pending resolve:",e)}if(this.resultBuffer&&"mapped"===this.resultBuffer.mapState)try{this.resultBuffer.unmap()}catch(e){console.error("Error unmapping buffer:",e)}this.querySet&&(this.querySet.destroy(),this.querySet=null),this.resolveBuffer&&(this.resolveBuffer.destroy(),this.resolveBuffer=null),this.resultBuffer&&(this.resultBuffer.destroy(),this.resultBuffer=null),this.queryOffsets.clear(),this.pendingResolve=null}}}class AR extends uL{constructor(e={}){super(e),this.isWebGPUBackend=!0,this.parameters.alpha=void 0===e.alpha||e.alpha,this.parameters.compatibilityMode=void 0!==e.compatibilityMode&&e.compatibilityMode,this.parameters.requiredLimits=void 0===e.requiredLimits?{}:e.requiredLimits,this.compatibilityMode=this.parameters.compatibilityMode,this.device=null,this.context=null,this.colorBuffer=null,this.defaultRenderPassdescriptor=null,this.utils=new cR(this),this.attributeUtils=new pR(this),this.bindingUtils=new gR(this),this.pipelineUtils=new mR(this),this.textureUtils=new Wz(this),this.occludedResolveCache=new Map}async init(e){await super.init(e);const t=this.parameters;let n;if(void 0===t.device){const e={powerPreference:t.powerPreference,featureLevel:t.compatibilityMode?"compatibility":void 0},i="undefined"!=typeof navigator?await navigator.gpu.requestAdapter(e):null;if(null===i)throw new Error("WebGPUBackend: Unable to create WebGPU adapter.");const r=Object.values(Rz),s=[];for(const e of r)i.features.has(e)&&s.push(e);const o={requiredFeatures:s,requiredLimits:t.requiredLimits};n=await i.requestDevice(o)}else n=t.device;n.lost.then((t=>{const n={api:"WebGPU",message:t.message||"Unknown reason",reason:t.reason||null,originalEvent:t};e.onDeviceLost(n)}));const i=void 0!==t.context?t.context:e.domElement.getContext("webgpu");this.device=n,this.context=i;const r=t.alpha?"premultiplied":"opaque",s=ks.getToneMappingMode(this.renderer.outputColorSpace);this.context.configure({device:this.device,format:this.utils.getPreferredCanvasFormat(),usage:GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.COPY_SRC,alphaMode:r,toneMapping:{mode:s}}),this.trackTimestamp=this.trackTimestamp&&this.hasFeature(Rz.TimestampQuery),this.updateSize()}get coordinateSystem(){return ls}async getArrayBufferAsync(e){return await this.attributeUtils.getArrayBufferAsync(e)}getContext(){return this.context}_getDefaultRenderPassDescriptor(){let e=this.defaultRenderPassdescriptor;if(null===e){const t=this.renderer;e={colorAttachments:[{view:null}]},!0!==this.renderer.depth&&!0!==this.renderer.stencil||(e.depthStencilAttachment={view:this.textureUtils.getDepthBuffer(t.depth,t.stencil).createView()});const n=e.colorAttachments[0];this.renderer.samples>0?n.view=this.colorBuffer.createView():n.resolveTarget=void 0,this.defaultRenderPassdescriptor=e}const t=e.colorAttachments[0];return this.renderer.samples>0?t.resolveTarget=this.context.getCurrentTexture().createView():t.view=this.context.getCurrentTexture().createView(),e}_isRenderCameraDepthArray(e){return e.depthTexture&&e.depthTexture.image.depth>1&&e.camera.isArrayCamera}_getRenderPassDescriptor(e,t={}){const n=e.renderTarget,i=this.get(n);let r=i.descriptors;void 0!==r&&i.width===n.width&&i.height===n.height&&i.samples===n.samples||(r={},i.descriptors=r);const s=e.getCacheKey();let o=r[s];if(void 0===o){const t=e.textures,a=[];let l;const u=this._isRenderCameraDepthArray(e);for(let i=0;i<t.length;i++){const r=this.get(t[i]),s={label:`colorAttachment_${i}`,baseMipLevel:e.activeMipmapLevel,mipLevelCount:1,baseArrayLayer:e.activeCubeFace,arrayLayerCount:1,dimension:Bz};if(n.isRenderTarget3D)l=e.activeCubeFace,s.baseArrayLayer=0,s.dimension=Lz,s.depthOrArrayLayers=t[i].image.depth;else if(n.isRenderTarget&&t[i].image.depth>1)if(!0===u){const t=e.camera.cameras;for(let e=0;e<t.length;e++){const t={...s,baseArrayLayer:e,arrayLayerCount:1,dimension:Bz},n=r.texture.createView(t);a.push({view:n,resolveTarget:void 0,depthSlice:void 0})}}else s.dimension=Dz,s.depthOrArrayLayers=t[i].image.depth;if(!0!==u){const e=r.texture.createView(s);let t,n;void 0!==r.msaaTexture?(t=r.msaaTexture.createView(),n=e):(t=e,n=void 0),a.push({view:t,resolveTarget:n,depthSlice:l})}}if(o={textureViews:a},e.depth){const t=this.get(e.depthTexture),n={};e.depthTexture.isArrayTexture&&(n.dimension=Bz,n.arrayLayerCount=1,n.baseArrayLayer=e.activeCubeFace),o.depthStencilView=t.texture.createView(n)}r[s]=o,i.width=n.width,i.height=n.height,i.samples=n.samples,i.activeMipmapLevel=e.activeMipmapLevel,i.activeCubeFace=e.activeCubeFace}const a={colorAttachments:[]};for(let e=0;e<o.textureViews.length;e++){const n=o.textureViews[e];let i={r:0,g:0,b:0,a:1};0===e&&t.clearValue&&(i=t.clearValue),a.colorAttachments.push({view:n.view,depthSlice:n.depthSlice,resolveTarget:n.resolveTarget,loadOp:t.loadOp||VL,storeOp:t.storeOp||GL,clearValue:i})}return o.depthStencilView&&(a.depthStencilAttachment={view:o.depthStencilView}),a}beginRender(e){const t=this.get(e);t.frameCalls=this.renderer.info.render.frameCalls;const n=this.device,i=e.occlusionQueryCount;let r,s;i>0&&(t.currentOcclusionQuerySet&&t.currentOcclusionQuerySet.destroy(),t.currentOcclusionQueryBuffer&&t.currentOcclusionQueryBuffer.destroy(),t.currentOcclusionQuerySet=t.occlusionQuerySet,t.currentOcclusionQueryBuffer=t.occlusionQueryBuffer,t.currentOcclusionQueryObjects=t.occlusionQueryObjects,r=n.createQuerySet({type:"occlusion",count:i,label:`occlusionQuerySet_${e.id}`}),t.occlusionQuerySet=r,t.occlusionQueryIndex=0,t.occlusionQueryObjects=new Array(i),t.lastOcclusionObject=null),s=null===e.textures?this._getDefaultRenderPassDescriptor():this._getRenderPassDescriptor(e,{loadOp:VL}),this.initTimestampQuery(cs,this.getTimestampUID(e),s),s.occlusionQuerySet=r;const o=s.depthStencilAttachment;if(null!==e.textures){const t=s.colorAttachments;for(let n=0;n<t.length;n++){const i=t[n];e.clearColor?(i.clearValue=0===n?e.clearColorValue:{r:0,g:0,b:0,a:1},i.loadOp=WL):i.loadOp=VL,i.storeOp=GL}}else{const t=s.colorAttachments[0];e.clearColor?(t.clearValue=e.clearColorValue,t.loadOp=WL):t.loadOp=VL,t.storeOp=GL}e.depth&&(e.clearDepth?(o.depthClearValue=e.clearDepthValue,o.depthLoadOp=WL):o.depthLoadOp=VL,o.depthStoreOp=GL),e.stencil&&(e.clearStencil?(o.stencilClearValue=e.clearStencilValue,o.stencilLoadOp=WL):o.stencilLoadOp=VL,o.stencilStoreOp=GL);const a=n.createCommandEncoder({label:"renderContext_"+e.id});if(!0===this._isRenderCameraDepthArray(e)){const n=e.camera.cameras;t.layerDescriptors&&t.layerDescriptors.length===n.length?this._updateDepthLayerDescriptors(e,t,n):this._createDepthLayerDescriptors(e,t,s,n),t.bundleEncoders=[],t.bundleSets=[];for(let i=0;i<n.length;i++){const n=this.pipelineUtils.createBundleEncoder(e,"renderBundleArrayCamera_"+i),r={attributes:{},bindingGroups:[],pipeline:null,index:null};t.bundleEncoders.push(n),t.bundleSets.push(r)}t.currentPass=null}else{const n=a.beginRenderPass(s);if(t.currentPass=n,e.viewport&&this.updateViewport(e),e.scissor){const{x:t,y:i,width:r,height:s}=e.scissorValue;n.setScissorRect(t,i,r,s)}}t.descriptor=s,t.encoder=a,t.currentSets={attributes:{},bindingGroups:[],pipeline:null,index:null},t.renderBundles=[]}_createDepthLayerDescriptors(e,t,n,i){const r=n.depthStencilAttachment;t.layerDescriptors=[];const s=this.get(e.depthTexture);s.viewCache||(s.viewCache=[]);for(let o=0;o<i.length;o++){const i={...n,colorAttachments:[{...n.colorAttachments[0],view:n.colorAttachments[o].view}]};if(n.depthStencilAttachment){const t=o;s.viewCache[t]||(s.viewCache[t]=s.texture.createView({dimension:Bz,baseArrayLayer:o,arrayLayerCount:1})),i.depthStencilAttachment={view:s.viewCache[t],depthLoadOp:r.depthLoadOp||WL,depthStoreOp:r.depthStoreOp||GL,depthClearValue:r.depthClearValue||1},e.stencil&&(i.depthStencilAttachment.stencilLoadOp=r.stencilLoadOp,i.depthStencilAttachment.stencilStoreOp=r.stencilStoreOp,i.depthStencilAttachment.stencilClearValue=r.stencilClearValue)}else i.depthStencilAttachment={...r};t.layerDescriptors.push(i)}}_updateDepthLayerDescriptors(e,t,n){for(let i=0;i<n.length;i++){const n=t.layerDescriptors[i];if(n.depthStencilAttachment){const t=n.depthStencilAttachment;e.depth&&(e.clearDepth?(t.depthClearValue=e.clearDepthValue,t.depthLoadOp=WL):t.depthLoadOp=VL),e.stencil&&(e.clearStencil?(t.stencilClearValue=e.clearStencilValue,t.stencilLoadOp=WL):t.stencilLoadOp=VL)}}}finishRender(e){const t=this.get(e),n=e.occlusionQueryCount;t.renderBundles.length>0&&t.currentPass.executeBundles(t.renderBundles),n>t.occlusionQueryIndex&&t.currentPass.endOcclusionQuery();const i=t.encoder;if(!0===this._isRenderCameraDepthArray(e)){const n=[];for(let e=0;e<t.bundleEncoders.length;e++){const i=t.bundleEncoders[e];n.push(i.finish())}for(let r=0;r<t.layerDescriptors.length;r++)if(r<n.length){const s=t.layerDescriptors[r],o=i.beginRenderPass(s);if(e.viewport){const{x:t,y:n,width:i,height:r,minDepth:s,maxDepth:a}=e.viewportValue;o.setViewport(t,n,i,r,s,a)}if(e.scissor){const{x:t,y:n,width:i,height:r}=e.scissorValue;o.setScissorRect(t,n,i,r)}o.executeBundles([n[r]]),o.end()}}else t.currentPass&&t.currentPass.end();if(n>0){const i=8*n;let r=this.occludedResolveCache.get(i);void 0===r&&(r=this.device.createBuffer({size:i,usage:GPUBufferUsage.QUERY_RESOLVE|GPUBufferUsage.COPY_SRC}),this.occludedResolveCache.set(i,r));const s=this.device.createBuffer({size:i,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ});t.encoder.resolveQuerySet(t.occlusionQuerySet,0,n,r,0),t.encoder.copyBufferToBuffer(r,0,s,0,i),t.occlusionQueryBuffer=s,this.resolveOccludedAsync(e)}if(this.device.queue.submit([t.encoder.finish()]),null!==e.textures){const t=e.textures;for(let e=0;e<t.length;e++){const n=t[e];!0===n.generateMipmaps&&this.textureUtils.generateMipmaps(n)}}}isOccluded(e,t){const n=this.get(e);return n.occluded&&n.occluded.has(t)}async resolveOccludedAsync(e){const t=this.get(e),{currentOcclusionQueryBuffer:n,currentOcclusionQueryObjects:i}=t;if(n&&i){const e=new WeakSet;t.currentOcclusionQueryObjects=null,t.currentOcclusionQueryBuffer=null,await n.mapAsync(GPUMapMode.READ);const r=n.getMappedRange(),s=new BigUint64Array(r);for(let t=0;t<i.length;t++)s[t]===BigInt(0)&&e.add(i[t]);n.destroy(),t.occluded=e}}updateViewport(e){const{currentPass:t}=this.get(e),{x:n,y:i,width:r,height:s,minDepth:o,maxDepth:a}=e.viewportValue;t.setViewport(n,i,r,s,o,a)}getClearColor(){const e=super.getClearColor();return!0===this.renderer.alpha&&(e.r*=e.a,e.g*=e.a,e.b*=e.a),e}clear(e,t,n,i=null){const r=this.device,s=this.renderer;let o,a,l,u,c=[];if(e){const e=this.getClearColor();a={r:e.r,g:e.g,b:e.b,a:e.a}}if(null===i){l=s.depth,u=s.stencil;const t=this._getDefaultRenderPassDescriptor();if(e){c=t.colorAttachments;const e=c[0];e.clearValue=a,e.loadOp=WL,e.storeOp=GL}(l||u)&&(o=t.depthStencilAttachment)}else{l=i.depth,u=i.stencil;const r={loadOp:e?WL:VL,clearValue:e?a:void 0};l&&(r.depthLoadOp=t?WL:VL,r.depthClearValue=t?s.getClearDepth():void 0,r.depthStoreOp=GL),u&&(r.stencilLoadOp=n?WL:VL,r.stencilClearValue=n?s.getClearStencil():void 0,r.stencilStoreOp=GL);const d=this._getRenderPassDescriptor(i,r);c=d.colorAttachments,o=d.depthStencilAttachment}l&&o&&(t?(o.depthLoadOp=WL,o.depthClearValue=s.getClearDepth(),o.depthStoreOp=GL):(o.depthLoadOp=VL,o.depthStoreOp=GL)),u&&o&&(n?(o.stencilLoadOp=WL,o.stencilClearValue=s.getClearStencil(),o.stencilStoreOp=GL):(o.stencilLoadOp=VL,o.stencilStoreOp=GL));const d=r.createCommandEncoder({label:"clear"});d.beginRenderPass({colorAttachments:c,depthStencilAttachment:o}).end(),r.queue.submit([d.finish()])}beginCompute(e){const t=this.get(e);t.frameCalls=this.renderer.info.compute.frameCalls;const n={label:"computeGroup_"+e.id};this.initTimestampQuery(us,this.getTimestampUID(e),n),t.cmdEncoderGPU=this.device.createCommandEncoder({label:"computeGroup_"+e.id}),t.passEncoderGPU=t.cmdEncoderGPU.beginComputePass(n)}compute(e,t,n,i,r=null){const s=this.get(t),{passEncoderGPU:o}=this.get(e),a=this.get(i).pipeline;this.pipelineUtils.setPipeline(o,a);for(let e=0,t=n.length;e<t;e++){const t=n[e],i=this.get(t);o.setBindGroup(e,i.group)}let l;if(null===r&&(r=t.count),"number"==typeof r){const e=r;if(void 0===s.dispatchSize||s.count!==e){s.dispatchSize=[0,1,1],s.count=e;const n=t.workgroupSize;let i=n[0];for(let e=1;e<n.length;e++)i*=n[e];const r=Math.ceil(e/i),o=this.device.limits.maxComputeWorkgroupsPerDimension;l=[r,1,1],r>o&&(l[0]=Math.min(r,o),l[1]=Math.ceil(r/o)),s.dispatchSize=l}l=s.dispatchSize}else l=r;o.dispatchWorkgroups(l[0],l[1]||1,l[2]||1)}finishCompute(e){const t=this.get(e);t.passEncoderGPU.end(),this.device.queue.submit([t.cmdEncoderGPU.finish()])}async waitForGPU(){await this.device.queue.onSubmittedWorkDone()}draw(e,t){const{object:n,material:i,context:r,pipeline:s}=e,o=e.getBindings(),a=this.get(r),l=this.get(s).pipeline,u=e.getIndex(),c=null!==u,d=e.getDrawParameters();if(null===d)return;const h=(t,n)=>{this.pipelineUtils.setPipeline(t,l),n.pipeline=l;const s=n.bindingGroups;for(let e=0,n=o.length;e<n;e++){const n=o[e],i=this.get(n);s[n.index]!==n.id&&(t.setBindGroup(n.index,i.group),s[n.index]=n.id)}if(!0===c&&n.index!==u){const e=this.get(u).buffer,i=u.array instanceof Uint16Array?KL:qL;t.setIndexBuffer(e,i),n.index=u}const d=e.getVertexBuffers();for(let e=0,i=d.length;e<i;e++){const i=d[e];if(n.attributes[e]!==i){const r=this.get(i).buffer;t.setVertexBuffer(e,r),n.attributes[e]=i}}!0===r.stencil&&!0===i.stencilWrite&&a.currentStencilRef!==i.stencilRef&&(t.setStencilReference(i.stencilRef),a.currentStencilRef=i.stencilRef)},f=(i,r)=>{if(h(i,r),!0===n.isBatchedMesh){const e=n._multiDrawStarts,r=n._multiDrawCounts,s=n._multiDrawCount,o=n._multiDrawInstances;null!==o&&js("THREE.WebGPUBackend: renderMultiDrawInstances has been deprecated and will be removed in r184. Append to renderMultiDraw arguments and use indirection.");for(let a=0;a<s;a++){const s=o?o[a]:1,l=s>1?0:a;!0===c?i.drawIndexed(r[a],s,e[a]/u.array.BYTES_PER_ELEMENT,0,l):i.draw(r[a],s,e[a],l),t.update(n,r[a],s)}}else if(!0===c){const{vertexCount:r,instanceCount:s,firstVertex:o}=d,a=e.getIndirect();if(null!==a){const e=this.get(a).buffer;i.drawIndexedIndirect(e,0)}else i.drawIndexed(r,s,o,0,0);t.update(n,r,s)}else{const{vertexCount:r,instanceCount:s,firstVertex:o}=d,a=e.getIndirect();if(null!==a){const e=this.get(a).buffer;i.drawIndirect(e,0)}else i.draw(r,s,o,0);t.update(n,r,s)}};if(e.camera.isArrayCamera&&e.camera.cameras.length>0){const t=this.get(e.camera),i=e.camera.cameras,s=e.getBindingGroup("cameraIndex");if(void 0===t.indexesGPU||t.indexesGPU.length!==i.length){const e=this.get(s),n=[],r=new Uint32Array([0,0,0,0]);for(let t=0,s=i.length;t<s;t++){r[0]=t;const i=this.bindingUtils.createBindGroupIndex(r,e.layout);n.push(i)}t.indexesGPU=n}const o=this.renderer.getPixelRatio();for(let e=0,l=i.length;e<l;e++){const l=i[e];if(n.layers.test(l.layers)){const n=l.viewport;let i=a.currentPass,u=a.currentSets;if(a.bundleEncoders){i=a.bundleEncoders[e],u=a.bundleSets[e]}n&&i.setViewport(Math.floor(n.x*o),Math.floor(n.y*o),Math.floor(n.width*o),Math.floor(n.height*o),r.viewportValue.minDepth,r.viewportValue.maxDepth),s&&t.indexesGPU&&(i.setBindGroup(s.index,t.indexesGPU[e]),u.bindingGroups[s.index]=s.id),f(i,u)}}}else if(a.currentPass){if(void 0!==a.occlusionQuerySet){const e=a.lastOcclusionObject;e!==n&&(null!==e&&!0===e.occlusionTest&&(a.currentPass.endOcclusionQuery(),a.occlusionQueryIndex++),!0===n.occlusionTest&&(a.currentPass.beginOcclusionQuery(a.occlusionQueryIndex),a.occlusionQueryObjects[a.occlusionQueryIndex]=n),a.lastOcclusionObject=n)}f(a.currentPass,a.currentSets)}}needsRenderUpdate(e){const t=this.get(e),{object:n,material:i}=e,r=this.utils,s=r.getSampleCountRenderContext(e.context),o=r.getCurrentColorSpace(e.context),a=r.getCurrentColorFormat(e.context),l=r.getCurrentDepthStencilFormat(e.context),u=r.getPrimitiveTopology(n,i);let c=!1;return t.material===i&&t.materialVersion===i.version&&t.transparent===i.transparent&&t.blending===i.blending&&t.premultipliedAlpha===i.premultipliedAlpha&&t.blendSrc===i.blendSrc&&t.blendDst===i.blendDst&&t.blendEquation===i.blendEquation&&t.blendSrcAlpha===i.blendSrcAlpha&&t.blendDstAlpha===i.blendDstAlpha&&t.blendEquationAlpha===i.blendEquationAlpha&&t.colorWrite===i.colorWrite&&t.depthWrite===i.depthWrite&&t.depthTest===i.depthTest&&t.depthFunc===i.depthFunc&&t.stencilWrite===i.stencilWrite&&t.stencilFunc===i.stencilFunc&&t.stencilFail===i.stencilFail&&t.stencilZFail===i.stencilZFail&&t.stencilZPass===i.stencilZPass&&t.stencilFuncMask===i.stencilFuncMask&&t.stencilWriteMask===i.stencilWriteMask&&t.side===i.side&&t.alphaToCoverage===i.alphaToCoverage&&t.sampleCount===s&&t.colorSpace===o&&t.colorFormat===a&&t.depthStencilFormat===l&&t.primitiveTopology===u&&t.clippingContextCacheKey===e.clippingContextCacheKey||(t.material=i,t.materialVersion=i.version,t.transparent=i.transparent,t.blending=i.blending,t.premultipliedAlpha=i.premultipliedAlpha,t.blendSrc=i.blendSrc,t.blendDst=i.blendDst,t.blendEquation=i.blendEquation,t.blendSrcAlpha=i.blendSrcAlpha,t.blendDstAlpha=i.blendDstAlpha,t.blendEquationAlpha=i.blendEquationAlpha,t.colorWrite=i.colorWrite,t.depthWrite=i.depthWrite,t.depthTest=i.depthTest,t.depthFunc=i.depthFunc,t.stencilWrite=i.stencilWrite,t.stencilFunc=i.stencilFunc,t.stencilFail=i.stencilFail,t.stencilZFail=i.stencilZFail,t.stencilZPass=i.stencilZPass,t.stencilFuncMask=i.stencilFuncMask,t.stencilWriteMask=i.stencilWriteMask,t.side=i.side,t.alphaToCoverage=i.alphaToCoverage,t.sampleCount=s,t.colorSpace=o,t.colorFormat=a,t.depthStencilFormat=l,t.primitiveTopology=u,t.clippingContextCacheKey=e.clippingContextCacheKey,c=!0),c}getRenderCacheKey(e){const{object:t,material:n}=e,i=this.utils,r=e.context,s=t.isMesh&&t.matrixWorld.determinant()<0;return[n.transparent,n.blending,n.premultipliedAlpha,n.blendSrc,n.blendDst,n.blendEquation,n.blendSrcAlpha,n.blendDstAlpha,n.blendEquationAlpha,n.colorWrite,n.depthWrite,n.depthTest,n.depthFunc,n.stencilWrite,n.stencilFunc,n.stencilFail,n.stencilZFail,n.stencilZPass,n.stencilFuncMask,n.stencilWriteMask,n.side,s,i.getSampleCountRenderContext(r),i.getCurrentColorSpace(r),i.getCurrentColorFormat(r),i.getCurrentDepthStencilFormat(r),i.getPrimitiveTopology(t,n),e.getGeometryCacheKey(),e.clippingContextCacheKey].join()}createSampler(e){this.textureUtils.createSampler(e)}destroySampler(e){this.textureUtils.destroySampler(e)}createDefaultTexture(e){this.textureUtils.createDefaultTexture(e)}createTexture(e,t){this.textureUtils.createTexture(e,t)}updateTexture(e,t){this.textureUtils.updateTexture(e,t)}generateMipmaps(e){this.textureUtils.generateMipmaps(e)}destroyTexture(e){this.textureUtils.destroyTexture(e)}async copyTextureToBuffer(e,t,n,i,r,s){return this.textureUtils.copyTextureToBuffer(e,t,n,i,r,s)}initTimestampQuery(e,t,n){if(!this.trackTimestamp)return;this.timestampQueryPool[e]||(this.timestampQueryPool[e]=new vR(this.device,e,2048));const i=this.timestampQueryPool[e],r=i.allocateQueriesForContext(t);n.timestampWrites={querySet:i.querySet,beginningOfPassWriteIndex:r,endOfPassWriteIndex:r+1}}createNodeBuilder(e,t){return new uR(e,t)}createProgram(e){this.get(e).module={module:this.device.createShaderModule({code:e.code,label:e.stage+(""!==e.name?`_${e.name}`:"")}),entryPoint:"main"}}destroyProgram(e){this.delete(e)}createRenderPipeline(e,t){this.pipelineUtils.createRenderPipeline(e,t)}createComputePipeline(e,t){this.pipelineUtils.createComputePipeline(e,t)}beginBundle(e){const t=this.get(e);t._currentPass=t.currentPass,t._currentSets=t.currentSets,t.currentSets={attributes:{},bindingGroups:[],pipeline:null,index:null},t.currentPass=this.pipelineUtils.createBundleEncoder(e)}finishBundle(e,t){const n=this.get(e),i=n.currentPass.finish();this.get(t).bundleGPU=i,n.currentSets=n._currentSets,n.currentPass=n._currentPass}addBundle(e,t){this.get(e).renderBundles.push(this.get(t).bundleGPU)}createBindings(e,t,n,i){this.bindingUtils.createBindings(e,t,n,i)}updateBindings(e,t,n,i){this.bindingUtils.createBindings(e,t,n,i)}updateBinding(e){this.bindingUtils.updateBinding(e)}createIndexAttribute(e){let t=GPUBufferUsage.INDEX|GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST;(e.isStorageBufferAttribute||e.isStorageInstancedBufferAttribute)&&(t|=GPUBufferUsage.STORAGE),this.attributeUtils.createAttribute(e,t)}createAttribute(e){this.attributeUtils.createAttribute(e,GPUBufferUsage.VERTEX|GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST)}createStorageAttribute(e){this.attributeUtils.createAttribute(e,GPUBufferUsage.STORAGE|GPUBufferUsage.VERTEX|GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST)}createIndirectStorageAttribute(e){this.attributeUtils.createAttribute(e,GPUBufferUsage.STORAGE|GPUBufferUsage.INDIRECT|GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST)}updateAttribute(e){this.attributeUtils.updateAttribute(e)}destroyAttribute(e){this.attributeUtils.destroyAttribute(e)}updateSize(){this.colorBuffer=this.textureUtils.getColorBuffer(),this.defaultRenderPassdescriptor=null}getMaxAnisotropy(){return 16}hasFeature(e){return this.device.features.has(e)}copyTextureToTexture(e,t,n=null,i=null,r=0,s=0){let o=0,a=0,l=0,u=0,c=0,d=0,h=e.image.width,f=e.image.height,p=1;null!==n&&(!0===n.isBox3?(u=n.min.x,c=n.min.y,d=n.min.z,h=n.max.x-n.min.x,f=n.max.y-n.min.y,p=n.max.z-n.min.z):(u=n.min.x,c=n.min.y,h=n.max.x-n.min.x,f=n.max.y-n.min.y,p=1)),null!==i&&(o=i.x,a=i.y,l=i.z||0);const g=this.device.createCommandEncoder({label:"copyTextureToTexture_"+e.id+"_"+t.id}),m=this.get(e).texture,v=this.get(t).texture;g.copyTextureToTexture({texture:m,mipLevel:r,origin:{x:u,y:c,z:d}},{texture:v,mipLevel:s,origin:{x:o,y:a,z:l}},[h,f,p]),this.device.queue.submit([g.finish()]),0===s&&t.generateMipmaps&&this.textureUtils.generateMipmaps(t)}copyFramebufferToTexture(e,t,n){const i=this.get(t);let r=null;r=t.renderTarget?e.isDepthTexture?this.get(t.depthTexture).texture:this.get(t.textures[0]).texture:e.isDepthTexture?this.textureUtils.getDepthBuffer(t.depth,t.stencil):this.context.getCurrentTexture();const s=this.get(e).texture;if(r.format!==s.format)return void console.error("WebGPUBackend: copyFramebufferToTexture: Source and destination formats do not match.",r.format,s.format);let o;if(i.currentPass?(i.currentPass.end(),o=i.encoder):o=this.device.createCommandEncoder({label:"copyFramebufferToTexture_"+e.id}),o.copyTextureToTexture({texture:r,origin:[n.x,n.y,0]},{texture:s},[n.z,n.w]),i.currentPass){const{descriptor:e}=i;for(let t=0;t<e.colorAttachments.length;t++)e.colorAttachments[t].loadOp=VL;if(t.depth&&(e.depthStencilAttachment.depthLoadOp=VL),t.stencil&&(e.depthStencilAttachment.stencilLoadOp=VL),i.currentPass=o.beginRenderPass(e),i.currentSets={attributes:{},bindingGroups:[],pipeline:null,index:null},t.viewport&&this.updateViewport(t),t.scissor){const{x:e,y:n,width:r,height:s}=t.scissorValue;i.currentPass.setScissorRect(e,n,r,s)}}else this.device.queue.submit([o.finish()]);e.generateMipmaps&&this.textureUtils.generateMipmaps(e)}}class xR extends oc{constructor(e,t,n,i,r,s){super(e,t,n,i,r,s),this.iesMap=null}copy(e,t){return super.copy(e,t),this.iesMap=e.iesMap,this}}class yR extends oc{constructor(e,t,n,i,r,s){super(e,t,n,i,r,s),this.aspect=null}copy(e,t){return super.copy(e,t),this.aspect=e.aspect,this}}class bR extends AI{constructor(){super(),this.addMaterial(ST,"MeshPhongMaterial"),this.addMaterial(pP,"MeshStandardMaterial"),this.addMaterial(mP,"MeshPhysicalMaterial"),this.addMaterial(yP,"MeshToonMaterial"),this.addMaterial(AT,"MeshBasicMaterial"),this.addMaterial(ET,"MeshLambertMaterial"),this.addMaterial(sT,"MeshNormalMaterial"),this.addMaterial(CP,"MeshMatcapMaterial"),this.addMaterial(eT,"LineBasicMaterial"),this.addMaterial(nT,"LineDashedMaterial"),this.addMaterial(BP,"PointsMaterial"),this.addMaterial(SP,"SpriteMaterial"),this.addMaterial(jP,"ShadowMaterial"),this.addLight(oD,dc),this.addLight(VD,pc),this.addLight(YD,mc),this.addLight(JD,oc),this.addLight($D,gc),this.addLight(eI,ec),this.addLight(tI,Ac),this.addLight(KD,xR),this.addLight(_D,yR),this.addToneMapping(GN,1),this.addToneMapping(VN,2),this.addToneMapping(WN,3),this.addToneMapping(ZN,4),this.addToneMapping(qN,6),this.addToneMapping(_N,7)}}class wR extends FI{constructor(e={}){let t;e.forceWebGL?t=NL:(t=AR,e.getFallback=()=>(console.warn("THREE.WebGPURenderer: WebGPU is not available, running under WebGL2 backend."),new NL(e)));super(new t(e),e),this.library=new bR,this.isWebGPURenderer=!0,"undefined"!=typeof __THREE_DEVTOOLS__&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent("observe",{detail:this}))}}const CR={type:"change"},MR={type:"start"},ER={type:"end"},TR=1e-6,SR=-1,PR=0,NR=1,BR=2,DR=3,IR=4,LR=new Cs,jR=new Cs,OR=new Es,zR=new Es,RR=new Es,kR=new Ms,FR=new Es,HR=new Es,UR=new Es,XR=new Es;class GR extends Oc{constructor(e,t=null){super(e,t),this.screen={left:0,top:0,width:0,height:0},this.rotateSpeed=1,this.zoomSpeed=1.2,this.panSpeed=.3,this.noRotate=!1,this.noZoom=!1,this.noPan=!1,this.staticMoving=!1,this.dynamicDampingFactor=.2,this.minDistance=0,this.maxDistance=1/0,this.minZoom=0,this.maxZoom=1/0,this.keys=["KeyA","KeyS","KeyD"],this.mouseButtons={LEFT:vi,MIDDLE:Ai,RIGHT:xi},this.target=new Es,this.state=SR,this.keyState=SR,this._lastPosition=new Es,this._lastZoom=1,this._touchZoomDistanceStart=0,this._touchZoomDistanceEnd=0,this._lastAngle=0,this._eye=new Es,this._movePrev=new Cs,this._moveCurr=new Cs,this._lastAxis=new Es,this._zoomStart=new Cs,this._zoomEnd=new Cs,this._panStart=new Cs,this._panEnd=new Cs,this._pointers=[],this._pointerPositions={},this._onPointerMove=WR.bind(this),this._onPointerDown=VR.bind(this),this._onPointerUp=QR.bind(this),this._onPointerCancel=ZR.bind(this),this._onContextMenu=ek.bind(this),this._onMouseWheel=$R.bind(this),this._onKeyDown=JR.bind(this),this._onKeyUp=YR.bind(this),this._onTouchStart=tk.bind(this),this._onTouchMove=nk.bind(this),this._onTouchEnd=ik.bind(this),this._onMouseDown=KR.bind(this),this._onMouseMove=qR.bind(this),this._onMouseUp=_R.bind(this),this._target0=this.target.clone(),this._position0=this.object.position.clone(),this._up0=this.object.up.clone(),this._zoom0=this.object.zoom,null!==t&&(this.connect(t),this.handleResize()),this.update()}connect(e){super.connect(e),window.addEventListener("keydown",this._onKeyDown),window.addEventListener("keyup",this._onKeyUp),this.domElement.addEventListener("pointerdown",this._onPointerDown),this.domElement.addEventListener("pointercancel",this._onPointerCancel),this.domElement.addEventListener("wheel",this._onMouseWheel,{passive:!1}),this.domElement.addEventListener("contextmenu",this._onContextMenu),this.domElement.style.touchAction="none"}disconnect(){window.removeEventListener("keydown",this._onKeyDown),window.removeEventListener("keyup",this._onKeyUp),this.domElement.removeEventListener("pointerdown",this._onPointerDown),this.domElement.removeEventListener("pointermove",this._onPointerMove),this.domElement.removeEventListener("pointerup",this._onPointerUp),this.domElement.removeEventListener("pointercancel",this._onPointerCancel),this.domElement.removeEventListener("wheel",this._onMouseWheel),this.domElement.removeEventListener("contextmenu",this._onContextMenu),this.domElement.style.touchAction="auto"}dispose(){this.disconnect()}handleResize(){const e=this.domElement.getBoundingClientRect(),t=this.domElement.ownerDocument.documentElement;this.screen.left=e.left+window.pageXOffset-t.clientLeft,this.screen.top=e.top+window.pageYOffset-t.clientTop,this.screen.width=e.width,this.screen.height=e.height}update(){this._eye.subVectors(this.object.position,this.target),this.noRotate||this._rotateCamera(),this.noZoom||this._zoomCamera(),this.noPan||this._panCamera(),this.object.position.addVectors(this.target,this._eye),this.object.isPerspectiveCamera?(this._checkDistances(),this.object.lookAt(this.target),this._lastPosition.distanceToSquared(this.object.position)>TR&&(this.dispatchEvent(CR),this._lastPosition.copy(this.object.position))):this.object.isOrthographicCamera?(this.object.lookAt(this.target),(this._lastPosition.distanceToSquared(this.object.position)>TR||this._lastZoom!==this.object.zoom)&&(this.dispatchEvent(CR),this._lastPosition.copy(this.object.position),this._lastZoom=this.object.zoom)):console.warn("THREE.TrackballControls: Unsupported camera type.")}reset(){this.state=SR,this.keyState=SR,this.target.copy(this._target0),this.object.position.copy(this._position0),this.object.up.copy(this._up0),this.object.zoom=this._zoom0,this.object.updateProjectionMatrix(),this._eye.subVectors(this.object.position,this.target),this.object.lookAt(this.target),this.dispatchEvent(CR),this._lastPosition.copy(this.object.position),this._lastZoom=this.object.zoom}_panCamera(){if(jR.copy(this._panEnd).sub(this._panStart),jR.lengthSq()){if(this.object.isOrthographicCamera){const e=(this.object.right-this.object.left)/this.object.zoom/this.domElement.clientWidth,t=(this.object.top-this.object.bottom)/this.object.zoom/this.domElement.clientWidth;jR.x*=e,jR.y*=t}jR.multiplyScalar(this._eye.length()*this.panSpeed),zR.copy(this._eye).cross(this.object.up).setLength(jR.x),zR.add(OR.copy(this.object.up).setLength(jR.y)),this.object.position.add(zR),this.target.add(zR),this.staticMoving?this._panStart.copy(this._panEnd):this._panStart.add(jR.subVectors(this._panEnd,this._panStart).multiplyScalar(this.dynamicDampingFactor))}}_rotateCamera(){XR.set(this._moveCurr.x-this._movePrev.x,this._moveCurr.y-this._movePrev.y,0);let e=XR.length();e?(this._eye.copy(this.object.position).sub(this.target),FR.copy(this._eye).normalize(),HR.copy(this.object.up).normalize(),UR.crossVectors(HR,FR).normalize(),HR.setLength(this._moveCurr.y-this._movePrev.y),UR.setLength(this._moveCurr.x-this._movePrev.x),XR.copy(HR.add(UR)),RR.crossVectors(XR,this._eye).normalize(),e*=this.rotateSpeed,kR.setFromAxisAngle(RR,e),this._eye.applyQuaternion(kR),this.object.up.applyQuaternion(kR),this._lastAxis.copy(RR),this._lastAngle=e):!this.staticMoving&&this._lastAngle&&(this._lastAngle*=Math.sqrt(1-this.dynamicDampingFactor),this._eye.copy(this.object.position).sub(this.target),kR.setFromAxisAngle(this._lastAxis,this._lastAngle),this._eye.applyQuaternion(kR),this.object.up.applyQuaternion(kR)),this._movePrev.copy(this._moveCurr)}_zoomCamera(){let e;this.state===IR?(e=this._touchZoomDistanceStart/this._touchZoomDistanceEnd,this._touchZoomDistanceStart=this._touchZoomDistanceEnd,this.object.isPerspectiveCamera?this._eye.multiplyScalar(e):this.object.isOrthographicCamera?(this.object.zoom=ws.clamp(this.object.zoom/e,this.minZoom,this.maxZoom),this._lastZoom!==this.object.zoom&&this.object.updateProjectionMatrix()):console.warn("THREE.TrackballControls: Unsupported camera type")):(e=1+(this._zoomEnd.y-this._zoomStart.y)*this.zoomSpeed,1!==e&&e>0&&(this.object.isPerspectiveCamera?this._eye.multiplyScalar(e):this.object.isOrthographicCamera?(this.object.zoom=ws.clamp(this.object.zoom/e,this.minZoom,this.maxZoom),this._lastZoom!==this.object.zoom&&this.object.updateProjectionMatrix()):console.warn("THREE.TrackballControls: Unsupported camera type")),this.staticMoving?this._zoomStart.copy(this._zoomEnd):this._zoomStart.y+=(this._zoomEnd.y-this._zoomStart.y)*this.dynamicDampingFactor)}_getMouseOnScreen(e,t){return LR.set((e-this.screen.left)/this.screen.width,(t-this.screen.top)/this.screen.height),LR}_getMouseOnCircle(e,t){return LR.set((e-.5*this.screen.width-this.screen.left)/(.5*this.screen.width),(this.screen.height+2*(this.screen.top-t))/this.screen.width),LR}_addPointer(e){this._pointers.push(e)}_removePointer(e){delete this._pointerPositions[e.pointerId];for(let t=0;t<this._pointers.length;t++)if(this._pointers[t].pointerId==e.pointerId)return void this._pointers.splice(t,1)}_trackPointer(e){let t=this._pointerPositions[e.pointerId];void 0===t&&(t=new Cs,this._pointerPositions[e.pointerId]=t),t.set(e.pageX,e.pageY)}_getSecondPointerPosition(e){const t=e.pointerId===this._pointers[0].pointerId?this._pointers[1]:this._pointers[0];return this._pointerPositions[t.pointerId]}_checkDistances(){this.noZoom&&this.noPan||(this._eye.lengthSq()>this.maxDistance*this.maxDistance&&(this.object.position.addVectors(this.target,this._eye.setLength(this.maxDistance)),this._zoomStart.copy(this._zoomEnd)),this._eye.lengthSq()<this.minDistance*this.minDistance&&(this.object.position.addVectors(this.target,this._eye.setLength(this.minDistance)),this._zoomStart.copy(this._zoomEnd)))}}function VR(e){!1!==this.enabled&&(0===this._pointers.length&&(this.domElement.setPointerCapture(e.pointerId),this.domElement.addEventListener("pointermove",this._onPointerMove),this.domElement.addEventListener("pointerup",this._onPointerUp)),this._addPointer(e),"touch"===e.pointerType?this._onTouchStart(e):this._onMouseDown(e))}function WR(e){!1!==this.enabled&&("touch"===e.pointerType?this._onTouchMove(e):this._onMouseMove(e))}function QR(e){!1!==this.enabled&&("touch"===e.pointerType?this._onTouchEnd(e):this._onMouseUp(),this._removePointer(e),0===this._pointers.length&&(this.domElement.releasePointerCapture(e.pointerId),this.domElement.removeEventListener("pointermove",this._onPointerMove),this.domElement.removeEventListener("pointerup",this._onPointerUp)))}function ZR(e){this._removePointer(e)}function YR(){!1!==this.enabled&&(this.keyState=SR,window.addEventListener("keydown",this._onKeyDown))}function JR(e){!1!==this.enabled&&(window.removeEventListener("keydown",this._onKeyDown),this.keyState===SR&&(e.code!==this.keys[PR]||this.noRotate?e.code!==this.keys[NR]||this.noZoom?e.code!==this.keys[BR]||this.noPan||(this.keyState=BR):this.keyState=NR:this.keyState=PR))}function KR(e){let t;switch(e.button){case 0:t=this.mouseButtons.LEFT;break;case 1:t=this.mouseButtons.MIDDLE;break;case 2:t=this.mouseButtons.RIGHT;break;default:t=-1}switch(t){case Ai:this.state=NR;break;case vi:this.state=PR;break;case xi:this.state=BR;break;default:this.state=SR}const n=this.keyState!==SR?this.keyState:this.state;n!==PR||this.noRotate?n!==NR||this.noZoom?n!==BR||this.noPan||(this._panStart.copy(this._getMouseOnScreen(e.pageX,e.pageY)),this._panEnd.copy(this._panStart)):(this._zoomStart.copy(this._getMouseOnScreen(e.pageX,e.pageY)),this._zoomEnd.copy(this._zoomStart)):(this._moveCurr.copy(this._getMouseOnCircle(e.pageX,e.pageY)),this._movePrev.copy(this._moveCurr)),this.dispatchEvent(MR)}function qR(e){const t=this.keyState!==SR?this.keyState:this.state;t!==PR||this.noRotate?t!==NR||this.noZoom?t!==BR||this.noPan||this._panEnd.copy(this._getMouseOnScreen(e.pageX,e.pageY)):this._zoomEnd.copy(this._getMouseOnScreen(e.pageX,e.pageY)):(this._movePrev.copy(this._moveCurr),this._moveCurr.copy(this._getMouseOnCircle(e.pageX,e.pageY)))}function _R(){this.state=SR,this.dispatchEvent(ER)}function $R(e){if(!1!==this.enabled&&!0!==this.noZoom){switch(e.preventDefault(),e.deltaMode){case 2:this._zoomStart.y-=.025*e.deltaY;break;case 1:this._zoomStart.y-=.01*e.deltaY;break;default:this._zoomStart.y-=25e-5*e.deltaY}this.dispatchEvent(MR),this.dispatchEvent(ER)}}function ek(e){!1!==this.enabled&&e.preventDefault()}function tk(e){if(this._trackPointer(e),1===this._pointers.length)this.state=DR,this._moveCurr.copy(this._getMouseOnCircle(this._pointers[0].pageX,this._pointers[0].pageY)),this._movePrev.copy(this._moveCurr);else{this.state=IR;const e=this._pointers[0].pageX-this._pointers[1].pageX,t=this._pointers[0].pageY-this._pointers[1].pageY;this._touchZoomDistanceEnd=this._touchZoomDistanceStart=Math.sqrt(e*e+t*t);const n=(this._pointers[0].pageX+this._pointers[1].pageX)/2,i=(this._pointers[0].pageY+this._pointers[1].pageY)/2;this._panStart.copy(this._getMouseOnScreen(n,i)),this._panEnd.copy(this._panStart)}this.dispatchEvent(MR)}function nk(e){if(this._trackPointer(e),1===this._pointers.length)this._movePrev.copy(this._moveCurr),this._moveCurr.copy(this._getMouseOnCircle(e.pageX,e.pageY));else{const t=this._getSecondPointerPosition(e),n=e.pageX-t.x,i=e.pageY-t.y;this._touchZoomDistanceEnd=Math.sqrt(n*n+i*i);const r=(e.pageX+t.x)/2,s=(e.pageY+t.y)/2;this._panEnd.copy(this._getMouseOnScreen(r,s))}}function ik(e){switch(this._pointers.length){case 0:this.state=SR;break;case 1:this.state=DR,this._moveCurr.copy(this._getMouseOnCircle(e.pageX,e.pageY)),this._movePrev.copy(this._moveCurr);break;case 2:this.state=IR;for(let t=0;t<this._pointers.length;t++)if(this._pointers[t].pointerId!==e.pointerId){const e=this._pointerPositions[this._pointers[t].pointerId];this._moveCurr.copy(this._getMouseOnCircle(e.x,e.y)),this._movePrev.copy(this._moveCurr);break}}this.dispatchEvent(ER)}const rk={type:"change"},sk={type:"start"},ok={type:"end"},ak=new So,lk=new Il,uk=Math.cos(70*ws.DEG2RAD),ck=new Es,dk=2*Math.PI,hk=-1,fk=0,pk=1,gk=2,mk=3,vk=4,Ak=5,xk=6,yk=1e-6;class bk extends Oc{constructor(e,t=null){super(e,t),this.state=hk,this.target=new Es,this.cursor=new Es,this.minDistance=0,this.maxDistance=1/0,this.minZoom=0,this.maxZoom=1/0,this.minTargetRadius=0,this.maxTargetRadius=1/0,this.minPolarAngle=0,this.maxPolarAngle=Math.PI,this.minAzimuthAngle=-1/0,this.maxAzimuthAngle=1/0,this.enableDamping=!1,this.dampingFactor=.05,this.enableZoom=!0,this.zoomSpeed=1,this.enableRotate=!0,this.rotateSpeed=1,this.keyRotateSpeed=1,this.enablePan=!0,this.panSpeed=1,this.screenSpacePanning=!0,this.keyPanSpeed=7,this.zoomToCursor=!1,this.autoRotate=!1,this.autoRotateSpeed=2,this.keys={LEFT:"ArrowLeft",UP:"ArrowUp",RIGHT:"ArrowRight",BOTTOM:"ArrowDown"},this.mouseButtons={LEFT:vi,MIDDLE:Ai,RIGHT:xi},this.touches={ONE:yi,TWO:wi},this.target0=this.target.clone(),this.position0=this.object.position.clone(),this.zoom0=this.object.zoom,this._domElementKeyEvents=null,this._lastPosition=new Es,this._lastQuaternion=new Ms,this._lastTargetPosition=new Es,this._quat=(new Ms).setFromUnitVectors(e.up,new Es(0,1,0)),this._quatInverse=this._quat.clone().invert(),this._spherical=new Lc,this._sphericalDelta=new Lc,this._scale=1,this._panOffset=new Es,this._rotateStart=new Cs,this._rotateEnd=new Cs,this._rotateDelta=new Cs,this._panStart=new Cs,this._panEnd=new Cs,this._panDelta=new Cs,this._dollyStart=new Cs,this._dollyEnd=new Cs,this._dollyDelta=new Cs,this._dollyDirection=new Es,this._mouse=new Cs,this._performCursorZoom=!1,this._pointers=[],this._pointerPositions={},this._controlActive=!1,this._onPointerMove=Ck.bind(this),this._onPointerDown=wk.bind(this),this._onPointerUp=Mk.bind(this),this._onContextMenu=Dk.bind(this),this._onMouseWheel=Sk.bind(this),this._onKeyDown=Pk.bind(this),this._onTouchStart=Nk.bind(this),this._onTouchMove=Bk.bind(this),this._onMouseDown=Ek.bind(this),this._onMouseMove=Tk.bind(this),this._interceptControlDown=Ik.bind(this),this._interceptControlUp=Lk.bind(this),null!==this.domElement&&this.connect(this.domElement),this.update()}connect(e){super.connect(e),this.domElement.addEventListener("pointerdown",this._onPointerDown),this.domElement.addEventListener("pointercancel",this._onPointerUp),this.domElement.addEventListener("contextmenu",this._onContextMenu),this.domElement.addEventListener("wheel",this._onMouseWheel,{passive:!1});this.domElement.getRootNode().addEventListener("keydown",this._interceptControlDown,{passive:!0,capture:!0}),this.domElement.style.touchAction="none"}disconnect(){this.domElement.removeEventListener("pointerdown",this._onPointerDown),this.domElement.removeEventListener("pointermove",this._onPointerMove),this.domElement.removeEventListener("pointerup",this._onPointerUp),this.domElement.removeEventListener("pointercancel",this._onPointerUp),this.domElement.removeEventListener("wheel",this._onMouseWheel),this.domElement.removeEventListener("contextmenu",this._onContextMenu),this.stopListenToKeyEvents();this.domElement.getRootNode().removeEventListener("keydown",this._interceptControlDown,{capture:!0}),this.domElement.style.touchAction="auto"}dispose(){this.disconnect()}getPolarAngle(){return this._spherical.phi}getAzimuthalAngle(){return this._spherical.theta}getDistance(){return this.object.position.distanceTo(this.target)}listenToKeyEvents(e){e.addEventListener("keydown",this._onKeyDown),this._domElementKeyEvents=e}stopListenToKeyEvents(){null!==this._domElementKeyEvents&&(this._domElementKeyEvents.removeEventListener("keydown",this._onKeyDown),this._domElementKeyEvents=null)}saveState(){this.target0.copy(this.target),this.position0.copy(this.object.position),this.zoom0=this.object.zoom}reset(){this.target.copy(this.target0),this.object.position.copy(this.position0),this.object.zoom=this.zoom0,this.object.updateProjectionMatrix(),this.dispatchEvent(rk),this.update(),this.state=hk}update(e=null){const t=this.object.position;ck.copy(t).sub(this.target),ck.applyQuaternion(this._quat),this._spherical.setFromVector3(ck),this.autoRotate&&this.state===hk&&this._rotateLeft(this._getAutoRotationAngle(e)),this.enableDamping?(this._spherical.theta+=this._sphericalDelta.theta*this.dampingFactor,this._spherical.phi+=this._sphericalDelta.phi*this.dampingFactor):(this._spherical.theta+=this._sphericalDelta.theta,this._spherical.phi+=this._sphericalDelta.phi);let n=this.minAzimuthAngle,i=this.maxAzimuthAngle;isFinite(n)&&isFinite(i)&&(n<-Math.PI?n+=dk:n>Math.PI&&(n-=dk),i<-Math.PI?i+=dk:i>Math.PI&&(i-=dk),this._spherical.theta=n<=i?Math.max(n,Math.min(i,this._spherical.theta)):this._spherical.theta>(n+i)/2?Math.max(n,this._spherical.theta):Math.min(i,this._spherical.theta)),this._spherical.phi=Math.max(this.minPolarAngle,Math.min(this.maxPolarAngle,this._spherical.phi)),this._spherical.makeSafe(),!0===this.enableDamping?this.target.addScaledVector(this._panOffset,this.dampingFactor):this.target.add(this._panOffset),this.target.sub(this.cursor),this.target.clampLength(this.minTargetRadius,this.maxTargetRadius),this.target.add(this.cursor);let r=!1;if(this.zoomToCursor&&this._performCursorZoom||this.object.isOrthographicCamera)this._spherical.radius=this._clampDistance(this._spherical.radius);else{const e=this._spherical.radius;this._spherical.radius=this._clampDistance(this._spherical.radius*this._scale),r=e!=this._spherical.radius}if(ck.setFromSpherical(this._spherical),ck.applyQuaternion(this._quatInverse),t.copy(this.target).add(ck),this.object.lookAt(this.target),!0===this.enableDamping?(this._sphericalDelta.theta*=1-this.dampingFactor,this._sphericalDelta.phi*=1-this.dampingFactor,this._panOffset.multiplyScalar(1-this.dampingFactor)):(this._sphericalDelta.set(0,0,0),this._panOffset.set(0,0,0)),this.zoomToCursor&&this._performCursorZoom){let e=null;if(this.object.isPerspectiveCamera){const t=ck.length();e=this._clampDistance(t*this._scale);const n=t-e;this.object.position.addScaledVector(this._dollyDirection,n),this.object.updateMatrixWorld(),r=!!n}else if(this.object.isOrthographicCamera){const t=new Es(this._mouse.x,this._mouse.y,0);t.unproject(this.object);const n=this.object.zoom;this.object.zoom=Math.max(this.minZoom,Math.min(this.maxZoom,this.object.zoom/this._scale)),this.object.updateProjectionMatrix(),r=n!==this.object.zoom;const i=new Es(this._mouse.x,this._mouse.y,0);i.unproject(this.object),this.object.position.sub(i).add(t),this.object.updateMatrixWorld(),e=ck.length()}else console.warn("WARNING: OrbitControls.js encountered an unknown camera type - zoom to cursor disabled."),this.zoomToCursor=!1;null!==e&&(this.screenSpacePanning?this.target.set(0,0,-1).transformDirection(this.object.matrix).multiplyScalar(e).add(this.object.position):(ak.origin.copy(this.object.position),ak.direction.set(0,0,-1).transformDirection(this.object.matrix),Math.abs(this.object.up.dot(ak.direction))<uk?this.object.lookAt(this.target):(lk.setFromNormalAndCoplanarPoint(this.object.up,this.target),ak.intersectPlane(lk,this.target))))}else if(this.object.isOrthographicCamera){const e=this.object.zoom;this.object.zoom=Math.max(this.minZoom,Math.min(this.maxZoom,this.object.zoom/this._scale)),e!==this.object.zoom&&(this.object.updateProjectionMatrix(),r=!0)}return this._scale=1,this._performCursorZoom=!1,!!(r||this._lastPosition.distanceToSquared(this.object.position)>yk||8*(1-this._lastQuaternion.dot(this.object.quaternion))>yk||this._lastTargetPosition.distanceToSquared(this.target)>yk)&&(this.dispatchEvent(rk),this._lastPosition.copy(this.object.position),this._lastQuaternion.copy(this.object.quaternion),this._lastTargetPosition.copy(this.target),!0)}_getAutoRotationAngle(e){return null!==e?dk/60*this.autoRotateSpeed*e:dk/60/60*this.autoRotateSpeed}_getZoomScale(e){const t=Math.abs(.01*e);return Math.pow(.95,this.zoomSpeed*t)}_rotateLeft(e){this._sphericalDelta.theta-=e}_rotateUp(e){this._sphericalDelta.phi-=e}_panLeft(e,t){ck.setFromMatrixColumn(t,0),ck.multiplyScalar(-e),this._panOffset.add(ck)}_panUp(e,t){!0===this.screenSpacePanning?ck.setFromMatrixColumn(t,1):(ck.setFromMatrixColumn(t,0),ck.crossVectors(this.object.up,ck)),ck.multiplyScalar(e),this._panOffset.add(ck)}_pan(e,t){const n=this.domElement;if(this.object.isPerspectiveCamera){const i=this.object.position;ck.copy(i).sub(this.target);let r=ck.length();r*=Math.tan(this.object.fov/2*Math.PI/180),this._panLeft(2*e*r/n.clientHeight,this.object.matrix),this._panUp(2*t*r/n.clientHeight,this.object.matrix)}else this.object.isOrthographicCamera?(this._panLeft(e*(this.object.right-this.object.left)/this.object.zoom/n.clientWidth,this.object.matrix),this._panUp(t*(this.object.top-this.object.bottom)/this.object.zoom/n.clientHeight,this.object.matrix)):(console.warn("WARNING: OrbitControls.js encountered an unknown camera type - pan disabled."),this.enablePan=!1)}_dollyOut(e){this.object.isPerspectiveCamera||this.object.isOrthographicCamera?this._scale/=e:(console.warn("WARNING: OrbitControls.js encountered an unknown camera type - dolly/zoom disabled."),this.enableZoom=!1)}_dollyIn(e){this.object.isPerspectiveCamera||this.object.isOrthographicCamera?this._scale*=e:(console.warn("WARNING: OrbitControls.js encountered an unknown camera type - dolly/zoom disabled."),this.enableZoom=!1)}_updateZoomParameters(e,t){if(!this.zoomToCursor)return;this._performCursorZoom=!0;const n=this.domElement.getBoundingClientRect(),i=e-n.left,r=t-n.top,s=n.width,o=n.height;this._mouse.x=i/s*2-1,this._mouse.y=-r/o*2+1,this._dollyDirection.set(this._mouse.x,this._mouse.y,1).unproject(this.object).sub(this.object.position).normalize()}_clampDistance(e){return Math.max(this.minDistance,Math.min(this.maxDistance,e))}_handleMouseDownRotate(e){this._rotateStart.set(e.clientX,e.clientY)}_handleMouseDownDolly(e){this._updateZoomParameters(e.clientX,e.clientX),this._dollyStart.set(e.clientX,e.clientY)}_handleMouseDownPan(e){this._panStart.set(e.clientX,e.clientY)}_handleMouseMoveRotate(e){this._rotateEnd.set(e.clientX,e.clientY),this._rotateDelta.subVectors(this._rotateEnd,this._rotateStart).multiplyScalar(this.rotateSpeed);const t=this.domElement;this._rotateLeft(dk*this._rotateDelta.x/t.clientHeight),this._rotateUp(dk*this._rotateDelta.y/t.clientHeight),this._rotateStart.copy(this._rotateEnd),this.update()}_handleMouseMoveDolly(e){this._dollyEnd.set(e.clientX,e.clientY),this._dollyDelta.subVectors(this._dollyEnd,this._dollyStart),this._dollyDelta.y>0?this._dollyOut(this._getZoomScale(this._dollyDelta.y)):this._dollyDelta.y<0&&this._dollyIn(this._getZoomScale(this._dollyDelta.y)),this._dollyStart.copy(this._dollyEnd),this.update()}_handleMouseMovePan(e){this._panEnd.set(e.clientX,e.clientY),this._panDelta.subVectors(this._panEnd,this._panStart).multiplyScalar(this.panSpeed),this._pan(this._panDelta.x,this._panDelta.y),this._panStart.copy(this._panEnd),this.update()}_handleMouseWheel(e){this._updateZoomParameters(e.clientX,e.clientY),e.deltaY<0?this._dollyIn(this._getZoomScale(e.deltaY)):e.deltaY>0&&this._dollyOut(this._getZoomScale(e.deltaY)),this.update()}_handleKeyDown(e){let t=!1;switch(e.code){case this.keys.UP:e.ctrlKey||e.metaKey||e.shiftKey?this.enableRotate&&this._rotateUp(dk*this.keyRotateSpeed/this.domElement.clientHeight):this.enablePan&&this._pan(0,this.keyPanSpeed),t=!0;break;case this.keys.BOTTOM:e.ctrlKey||e.metaKey||e.shiftKey?this.enableRotate&&this._rotateUp(-dk*this.keyRotateSpeed/this.domElement.clientHeight):this.enablePan&&this._pan(0,-this.keyPanSpeed),t=!0;break;case this.keys.LEFT:e.ctrlKey||e.metaKey||e.shiftKey?this.enableRotate&&this._rotateLeft(dk*this.keyRotateSpeed/this.domElement.clientHeight):this.enablePan&&this._pan(this.keyPanSpeed,0),t=!0;break;case this.keys.RIGHT:e.ctrlKey||e.metaKey||e.shiftKey?this.enableRotate&&this._rotateLeft(-dk*this.keyRotateSpeed/this.domElement.clientHeight):this.enablePan&&this._pan(-this.keyPanSpeed,0),t=!0}t&&(e.preventDefault(),this.update())}_handleTouchStartRotate(e){if(1===this._pointers.length)this._rotateStart.set(e.pageX,e.pageY);else{const t=this._getSecondPointerPosition(e),n=.5*(e.pageX+t.x),i=.5*(e.pageY+t.y);this._rotateStart.set(n,i)}}_handleTouchStartPan(e){if(1===this._pointers.length)this._panStart.set(e.pageX,e.pageY);else{const t=this._getSecondPointerPosition(e),n=.5*(e.pageX+t.x),i=.5*(e.pageY+t.y);this._panStart.set(n,i)}}_handleTouchStartDolly(e){const t=this._getSecondPointerPosition(e),n=e.pageX-t.x,i=e.pageY-t.y,r=Math.sqrt(n*n+i*i);this._dollyStart.set(0,r)}_handleTouchStartDollyPan(e){this.enableZoom&&this._handleTouchStartDolly(e),this.enablePan&&this._handleTouchStartPan(e)}_handleTouchStartDollyRotate(e){this.enableZoom&&this._handleTouchStartDolly(e),this.enableRotate&&this._handleTouchStartRotate(e)}_handleTouchMoveRotate(e){if(1==this._pointers.length)this._rotateEnd.set(e.pageX,e.pageY);else{const t=this._getSecondPointerPosition(e),n=.5*(e.pageX+t.x),i=.5*(e.pageY+t.y);this._rotateEnd.set(n,i)}this._rotateDelta.subVectors(this._rotateEnd,this._rotateStart).multiplyScalar(this.rotateSpeed);const t=this.domElement;this._rotateLeft(dk*this._rotateDelta.x/t.clientHeight),this._rotateUp(dk*this._rotateDelta.y/t.clientHeight),this._rotateStart.copy(this._rotateEnd)}_handleTouchMovePan(e){if(1===this._pointers.length)this._panEnd.set(e.pageX,e.pageY);else{const t=this._getSecondPointerPosition(e),n=.5*(e.pageX+t.x),i=.5*(e.pageY+t.y);this._panEnd.set(n,i)}this._panDelta.subVectors(this._panEnd,this._panStart).multiplyScalar(this.panSpeed),this._pan(this._panDelta.x,this._panDelta.y),this._panStart.copy(this._panEnd)}_handleTouchMoveDolly(e){const t=this._getSecondPointerPosition(e),n=e.pageX-t.x,i=e.pageY-t.y,r=Math.sqrt(n*n+i*i);this._dollyEnd.set(0,r),this._dollyDelta.set(0,Math.pow(this._dollyEnd.y/this._dollyStart.y,this.zoomSpeed)),this._dollyOut(this._dollyDelta.y),this._dollyStart.copy(this._dollyEnd);const s=.5*(e.pageX+t.x),o=.5*(e.pageY+t.y);this._updateZoomParameters(s,o)}_handleTouchMoveDollyPan(e){this.enableZoom&&this._handleTouchMoveDolly(e),this.enablePan&&this._handleTouchMovePan(e)}_handleTouchMoveDollyRotate(e){this.enableZoom&&this._handleTouchMoveDolly(e),this.enableRotate&&this._handleTouchMoveRotate(e)}_addPointer(e){this._pointers.push(e.pointerId)}_removePointer(e){delete this._pointerPositions[e.pointerId];for(let t=0;t<this._pointers.length;t++)if(this._pointers[t]==e.pointerId)return void this._pointers.splice(t,1)}_isTrackingPointer(e){for(let t=0;t<this._pointers.length;t++)if(this._pointers[t]==e.pointerId)return!0;return!1}_trackPointer(e){let t=this._pointerPositions[e.pointerId];void 0===t&&(t=new Cs,this._pointerPositions[e.pointerId]=t),t.set(e.pageX,e.pageY)}_getSecondPointerPosition(e){const t=e.pointerId===this._pointers[0]?this._pointers[1]:this._pointers[0];return this._pointerPositions[t]}_customWheelEvent(e){const t=e.deltaMode,n={clientX:e.clientX,clientY:e.clientY,deltaY:e.deltaY};switch(t){case 1:n.deltaY*=16;break;case 2:n.deltaY*=100}return e.ctrlKey&&!this._controlActive&&(n.deltaY*=10),n}}function wk(e){!1!==this.enabled&&(0===this._pointers.length&&(this.domElement.setPointerCapture(e.pointerId),this.domElement.addEventListener("pointermove",this._onPointerMove),this.domElement.addEventListener("pointerup",this._onPointerUp)),this._isTrackingPointer(e)||(this._addPointer(e),"touch"===e.pointerType?this._onTouchStart(e):this._onMouseDown(e)))}function Ck(e){!1!==this.enabled&&("touch"===e.pointerType?this._onTouchMove(e):this._onMouseMove(e))}function Mk(e){switch(this._removePointer(e),this._pointers.length){case 0:this.domElement.releasePointerCapture(e.pointerId),this.domElement.removeEventListener("pointermove",this._onPointerMove),this.domElement.removeEventListener("pointerup",this._onPointerUp),this.dispatchEvent(ok),this.state=hk;break;case 1:const t=this._pointers[0],n=this._pointerPositions[t];this._onTouchStart({pointerId:t,pageX:n.x,pageY:n.y})}}function Ek(e){let t;switch(e.button){case 0:t=this.mouseButtons.LEFT;break;case 1:t=this.mouseButtons.MIDDLE;break;case 2:t=this.mouseButtons.RIGHT;break;default:t=-1}switch(t){case Ai:if(!1===this.enableZoom)return;this._handleMouseDownDolly(e),this.state=pk;break;case vi:if(e.ctrlKey||e.metaKey||e.shiftKey){if(!1===this.enablePan)return;this._handleMouseDownPan(e),this.state=gk}else{if(!1===this.enableRotate)return;this._handleMouseDownRotate(e),this.state=fk}break;case xi:if(e.ctrlKey||e.metaKey||e.shiftKey){if(!1===this.enableRotate)return;this._handleMouseDownRotate(e),this.state=fk}else{if(!1===this.enablePan)return;this._handleMouseDownPan(e),this.state=gk}break;default:this.state=hk}this.state!==hk&&this.dispatchEvent(sk)}function Tk(e){switch(this.state){case fk:if(!1===this.enableRotate)return;this._handleMouseMoveRotate(e);break;case pk:if(!1===this.enableZoom)return;this._handleMouseMoveDolly(e);break;case gk:if(!1===this.enablePan)return;this._handleMouseMovePan(e)}}function Sk(e){!1!==this.enabled&&!1!==this.enableZoom&&this.state===hk&&(e.preventDefault(),this.dispatchEvent(sk),this._handleMouseWheel(this._customWheelEvent(e)),this.dispatchEvent(ok))}function Pk(e){!1!==this.enabled&&this._handleKeyDown(e)}function Nk(e){switch(this._trackPointer(e),this._pointers.length){case 1:switch(this.touches.ONE){case yi:if(!1===this.enableRotate)return;this._handleTouchStartRotate(e),this.state=mk;break;case bi:if(!1===this.enablePan)return;this._handleTouchStartPan(e),this.state=vk;break;default:this.state=hk}break;case 2:switch(this.touches.TWO){case wi:if(!1===this.enableZoom&&!1===this.enablePan)return;this._handleTouchStartDollyPan(e),this.state=Ak;break;case Ci:if(!1===this.enableZoom&&!1===this.enableRotate)return;this._handleTouchStartDollyRotate(e),this.state=xk;break;default:this.state=hk}break;default:this.state=hk}this.state!==hk&&this.dispatchEvent(sk)}function Bk(e){switch(this._trackPointer(e),this.state){case mk:if(!1===this.enableRotate)return;this._handleTouchMoveRotate(e),this.update();break;case vk:if(!1===this.enablePan)return;this._handleTouchMovePan(e),this.update();break;case Ak:if(!1===this.enableZoom&&!1===this.enablePan)return;this._handleTouchMoveDollyPan(e),this.update();break;case xk:if(!1===this.enableZoom&&!1===this.enableRotate)return;this._handleTouchMoveDollyRotate(e),this.update();break;default:this.state=hk}}function Dk(e){!1!==this.enabled&&e.preventDefault()}function Ik(e){if("Control"===e.key){this._controlActive=!0;this.domElement.getRootNode().addEventListener("keyup",this._interceptControlUp,{passive:!0,capture:!0})}}function Lk(e){if("Control"===e.key){this._controlActive=!1;this.domElement.getRootNode().removeEventListener("keyup",this._interceptControlUp,{passive:!0,capture:!0})}}const jk={type:"change"},Ok=1e-6,zk=new Ms;class Rk extends Oc{constructor(e,t=null){super(e,t),this.movementSpeed=1,this.rollSpeed=.005,this.dragToLook=!1,this.autoForward=!1,this._moveState={up:0,down:0,left:0,right:0,forward:0,back:0,pitchUp:0,pitchDown:0,yawLeft:0,yawRight:0,rollLeft:0,rollRight:0},this._moveVector=new Es(0,0,0),this._rotationVector=new Es(0,0,0),this._lastQuaternion=new Ms,this._lastPosition=new Es,this._status=0,this._onKeyDown=kk.bind(this),this._onKeyUp=Fk.bind(this),this._onPointerMove=Uk.bind(this),this._onPointerDown=Hk.bind(this),this._onPointerUp=Xk.bind(this),this._onPointerCancel=Gk.bind(this),this._onContextMenu=Vk.bind(this),null!==t&&this.connect(t)}connect(e){super.connect(e),window.addEventListener("keydown",this._onKeyDown),window.addEventListener("keyup",this._onKeyUp),this.domElement.addEventListener("pointermove",this._onPointerMove),this.domElement.addEventListener("pointerdown",this._onPointerDown),this.domElement.addEventListener("pointerup",this._onPointerUp),this.domElement.addEventListener("pointercancel",this._onPointerCancel),this.domElement.addEventListener("contextmenu",this._onContextMenu)}disconnect(){window.removeEventListener("keydown",this._onKeyDown),window.removeEventListener("keyup",this._onKeyUp),this.domElement.removeEventListener("pointermove",this._onPointerMove),this.domElement.removeEventListener("pointerdown",this._onPointerDown),this.domElement.removeEventListener("pointerup",this._onPointerUp),this.domElement.removeEventListener("pointercancel",this._onPointerCancel),this.domElement.removeEventListener("contextmenu",this._onContextMenu)}dispose(){this.disconnect()}update(e){if(!1===this.enabled)return;const t=this.object,n=e*this.movementSpeed,i=e*this.rollSpeed;t.translateX(this._moveVector.x*n),t.translateY(this._moveVector.y*n),t.translateZ(this._moveVector.z*n),zk.set(this._rotationVector.x*i,this._rotationVector.y*i,this._rotationVector.z*i,1).normalize(),t.quaternion.multiply(zk),(this._lastPosition.distanceToSquared(t.position)>Ok||8*(1-this._lastQuaternion.dot(t.quaternion))>Ok)&&(this.dispatchEvent(jk),this._lastQuaternion.copy(t.quaternion),this._lastPosition.copy(t.position))}_updateMovementVector(){const e=this._moveState.forward||this.autoForward&&!this._moveState.back?1:0;this._moveVector.x=-this._moveState.left+this._moveState.right,this._moveVector.y=-this._moveState.down+this._moveState.up,this._moveVector.z=-e+this._moveState.back}_updateRotationVector(){this._rotationVector.x=-this._moveState.pitchDown+this._moveState.pitchUp,this._rotationVector.y=-this._moveState.yawRight+this._moveState.yawLeft,this._rotationVector.z=-this._moveState.rollRight+this._moveState.rollLeft}_getContainerDimensions(){return this.domElement!=document?{size:[this.domElement.offsetWidth,this.domElement.offsetHeight],offset:[this.domElement.offsetLeft,this.domElement.offsetTop]}:{size:[window.innerWidth,window.innerHeight],offset:[0,0]}}}function kk(e){if(!e.altKey&&!1!==this.enabled){switch(e.code){case"ShiftLeft":case"ShiftRight":this.movementSpeedMultiplier=.1;break;case"KeyW":this._moveState.forward=1;break;case"KeyS":this._moveState.back=1;break;case"KeyA":this._moveState.left=1;break;case"KeyD":this._moveState.right=1;break;case"KeyR":this._moveState.up=1;break;case"KeyF":this._moveState.down=1;break;case"ArrowUp":this._moveState.pitchUp=1;break;case"ArrowDown":this._moveState.pitchDown=1;break;case"ArrowLeft":this._moveState.yawLeft=1;break;case"ArrowRight":this._moveState.yawRight=1;break;case"KeyQ":this._moveState.rollLeft=1;break;case"KeyE":this._moveState.rollRight=1}this._updateMovementVector(),this._updateRotationVector()}}function Fk(e){if(!1!==this.enabled){switch(e.code){case"ShiftLeft":case"ShiftRight":this.movementSpeedMultiplier=1;break;case"KeyW":this._moveState.forward=0;break;case"KeyS":this._moveState.back=0;break;case"KeyA":this._moveState.left=0;break;case"KeyD":this._moveState.right=0;break;case"KeyR":this._moveState.up=0;break;case"KeyF":this._moveState.down=0;break;case"ArrowUp":this._moveState.pitchUp=0;break;case"ArrowDown":this._moveState.pitchDown=0;break;case"ArrowLeft":this._moveState.yawLeft=0;break;case"ArrowRight":this._moveState.yawRight=0;break;case"KeyQ":this._moveState.rollLeft=0;break;case"KeyE":this._moveState.rollRight=0}this._updateMovementVector(),this._updateRotationVector()}}function Hk(e){if(!1!==this.enabled)if(this.dragToLook)this._status++;else{switch(e.button){case 0:this._moveState.forward=1;break;case 2:this._moveState.back=1}this._updateMovementVector()}}function Uk(e){if(!1!==this.enabled&&(!this.dragToLook||this._status>0)){const t=this._getContainerDimensions(),n=t.size[0]/2,i=t.size[1]/2;this._moveState.yawLeft=-(e.pageX-t.offset[0]-n)/n,this._moveState.pitchDown=(e.pageY-t.offset[1]-i)/i,this._updateRotationVector()}}function Xk(e){if(!1!==this.enabled){if(this.dragToLook)this._status--,this._moveState.yawLeft=this._moveState.pitchDown=0;else{switch(e.button){case 0:this._moveState.forward=0;break;case 2:this._moveState.back=0}this._updateMovementVector()}this._updateRotationVector()}}function Gk(){!1!==this.enabled&&(this.dragToLook?(this._status=0,this._moveState.yawLeft=this._moveState.pitchDown=0):(this._moveState.forward=0,this._moveState.back=0,this._updateMovementVector()),this._updateRotationVector())}function Vk(e){!1!==this.enabled&&e.preventDefault()}const Wk={name:"CopyShader",uniforms:{tDiffuse:{value:null},opacity:{value:1}},vertexShader:"\n\n\t\tvarying vec2 vUv;\n\n\t\tvoid main() {\n\n\t\t\tvUv = uv;\n\t\t\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\n\n\t\t}",fragmentShader:"\n\n\t\tuniform float opacity;\n\n\t\tuniform sampler2D tDiffuse;\n\n\t\tvarying vec2 vUv;\n\n\t\tvoid main() {\n\n\t\t\tvec4 texel = texture2D( tDiffuse, vUv );\n\t\t\tgl_FragColor = opacity * texel;\n\n\n\t\t}"};class Qk{constructor(){this.isPass=!0,this.enabled=!0,this.needsSwap=!0,this.clear=!1,this.renderToScreen=!1}setSize(){}render(){console.error("THREE.Pass: .render() must be implemented in derived pass.")}dispose(){}}const Zk=new hc(-1,1,1,-1,0,1);const Yk=new class extends Va{constructor(){super(),this.setAttribute("position",new za([-1,3,0,-1,-1,0,3,-1,0],3)),this.setAttribute("uv",new za([0,2,0,0,2,0],2))}};class Jk{constructor(e){this._mesh=new nl(Yk,e)}dispose(){this._mesh.geometry.dispose()}render(e){e.render(this._mesh,Zk)}get material(){return this._mesh.material}set material(e){this._mesh.material=e}}class Kk extends Qk{constructor(e,t="tDiffuse"){super(),this.textureID=t,this.uniforms=null,this.material=null,e instanceof ul?(this.uniforms=e.uniforms,this.material=e):e&&(this.uniforms=ll.clone(e.uniforms),this.material=new ul({name:void 0!==e.name?e.name:"unspecified",defines:Object.assign({},e.defines),uniforms:this.uniforms,vertexShader:e.vertexShader,fragmentShader:e.fragmentShader})),this._fsQuad=new Jk(this.material)}render(e,t,n){this.uniforms[this.textureID]&&(this.uniforms[this.textureID].value=n.texture),this._fsQuad.material=this.material,this.renderToScreen?(e.setRenderTarget(null),this._fsQuad.render(e)):(e.setRenderTarget(t),this.clear&&e.clear(e.autoClearColor,e.autoClearDepth,e.autoClearStencil),this._fsQuad.render(e))}dispose(){this.material.dispose(),this._fsQuad.dispose()}}class qk extends Qk{constructor(e,t){super(),this.scene=e,this.camera=t,this.clear=!0,this.needsSwap=!1,this.inverse=!1}render(e,t,n){const i=e.getContext(),r=e.state;let s,o;r.buffers.color.setMask(!1),r.buffers.depth.setMask(!1),r.buffers.color.setLocked(!0),r.buffers.depth.setLocked(!0),this.inverse?(s=0,o=1):(s=1,o=0),r.buffers.stencil.setTest(!0),r.buffers.stencil.setOp(i.REPLACE,i.REPLACE,i.REPLACE),r.buffers.stencil.setFunc(i.ALWAYS,s,4294967295),r.buffers.stencil.setClear(o),r.buffers.stencil.setLocked(!0),e.setRenderTarget(n),this.clear&&e.clear(),e.render(this.scene,this.camera),e.setRenderTarget(t),this.clear&&e.clear(),e.render(this.scene,this.camera),r.buffers.color.setLocked(!1),r.buffers.depth.setLocked(!1),r.buffers.color.setMask(!0),r.buffers.depth.setMask(!0),r.buffers.stencil.setLocked(!1),r.buffers.stencil.setFunc(i.EQUAL,1,4294967295),r.buffers.stencil.setOp(i.KEEP,i.KEEP,i.KEEP),r.buffers.stencil.setLocked(!0)}}class _k extends Qk{constructor(){super(),this.needsSwap=!1}render(e){e.state.buffers.stencil.setLocked(!1),e.state.buffers.stencil.setTest(!1)}}class $k{constructor(e,t){if(this.renderer=e,this._pixelRatio=e.getPixelRatio(),void 0===t){const n=e.getSize(new Cs);this._width=n.width,this._height=n.height,(t=new qs(this._width*this._pixelRatio,this._height*this._pixelRatio,{type:Ki})).texture.name="EffectComposer.rt1"}else this._width=t.width,this._height=t.height;this.renderTarget1=t,this.renderTarget2=t.clone(),this.renderTarget2.texture.name="EffectComposer.rt2",this.writeBuffer=this.renderTarget1,this.readBuffer=this.renderTarget2,this.renderToScreen=!0,this.passes=[],this.copyPass=new Kk(Wk),this.copyPass.material.blending=0,this.clock=new yc}swapBuffers(){const e=this.readBuffer;this.readBuffer=this.writeBuffer,this.writeBuffer=e}addPass(e){this.passes.push(e),e.setSize(this._width*this._pixelRatio,this._height*this._pixelRatio)}insertPass(e,t){this.passes.splice(t,0,e),e.setSize(this._width*this._pixelRatio,this._height*this._pixelRatio)}removePass(e){const t=this.passes.indexOf(e);-1!==t&&this.passes.splice(t,1)}isLastEnabledPass(e){for(let t=e+1;t<this.passes.length;t++)if(this.passes[t].enabled)return!1;return!0}render(e){void 0===e&&(e=this.clock.getDelta());const t=this.renderer.getRenderTarget();let n=!1;for(let t=0,i=this.passes.length;t<i;t++){const i=this.passes[t];if(!1!==i.enabled){if(i.renderToScreen=this.renderToScreen&&this.isLastEnabledPass(t),i.render(this.renderer,this.writeBuffer,this.readBuffer,e,n),i.needsSwap){if(n){const t=this.renderer.getContext(),n=this.renderer.state.buffers.stencil;n.setFunc(t.NOTEQUAL,1,4294967295),this.copyPass.render(this.renderer,this.writeBuffer,this.readBuffer,e),n.setFunc(t.EQUAL,1,4294967295)}this.swapBuffers()}void 0!==qk&&(i instanceof qk?n=!0:i instanceof _k&&(n=!1))}}this.renderer.setRenderTarget(t)}reset(e){if(void 0===e){const t=this.renderer.getSize(new Cs);this._pixelRatio=this.renderer.getPixelRatio(),this._width=t.width,this._height=t.height,(e=this.renderTarget1.clone()).setSize(this._width*this._pixelRatio,this._height*this._pixelRatio)}this.renderTarget1.dispose(),this.renderTarget2.dispose(),this.renderTarget1=e,this.renderTarget2=e.clone(),this.writeBuffer=this.renderTarget1,this.readBuffer=this.renderTarget2}setSize(e,t){this._width=e,this._height=t;const n=this._width*this._pixelRatio,i=this._height*this._pixelRatio;this.renderTarget1.setSize(n,i),this.renderTarget2.setSize(n,i);for(let e=0;e<this.passes.length;e++)this.passes[e].setSize(n,i)}setPixelRatio(e){this._pixelRatio=e,this.setSize(this._width,this._height)}dispose(){this.renderTarget1.dispose(),this.renderTarget2.dispose(),this.copyPass.dispose()}}class eF extends 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u=i.programs;i.environment=e.isMeshStandardMaterial?t.environment:null,i.fog=t.fog,i.envMap=(e.isMeshStandardMaterial?te:ee).get(e.envMap||i.environment),i.envMapRotation=null!==i.environment&&null===e.envMap?t.environmentRotation:e.envMapRotation,void 0===u&&(e.addEventListener("dispose",Ee),u=new Map,i.programs=u);let c=u.get(l);if(void 0!==c){if(i.currentProgram===c&&i.lightsStateVersion===o)return ke(e,a),c}else a.uniforms=se.getUniforms(e),e.onBeforeCompile(a,x),c=se.acquireProgram(a,l),u.set(l,c),i.uniforms=a.uniforms;const d=i.uniforms;return(e.isShaderMaterial||e.isRawShaderMaterial)&&!0!==e.clipping||(d.clippingPlanes=ue.uniform),ke(e,a),i.needsLights=function(e){return e.isMeshLambertMaterial||e.isMeshToonMaterial||e.isMeshPhongMaterial||e.isMeshStandardMaterial||e.isShadowMaterial||e.isShaderMaterial&&!0===e.lights}(e),i.lightsStateVersion=o,i.needsLights&&(d.ambientLightColor.value=r.state.ambient,d.lightProbe.value=r.state.probe,d.directionalLights.value=r.state.directional,d.directionalLightShadows.value=r.state.directionalShadow,d.spotLights.value=r.state.spot,d.spotLightShadows.value=r.state.spotShadow,d.rectAreaLights.value=r.state.rectArea,d.ltc_1.value=r.state.rectAreaLTC1,d.ltc_2.value=r.state.rectAreaLTC2,d.pointLights.value=r.state.point,d.pointLightShadows.value=r.state.pointShadow,d.hemisphereLights.value=r.state.hemi,d.directionalShadowMap.value=r.state.directionalShadowMap,d.directionalShadowMatrix.value=r.state.directionalShadowMatrix,d.spotShadowMap.value=r.state.spotShadowMap,d.spotLightMatrix.value=r.state.spotLightMatrix,d.spotLightMap.value=r.state.spotLightMap,d.pointShadowMap.value=r.state.pointShadowMap,d.pointShadowMatrix.value=r.state.pointShadowMatrix),i.currentProgram=c,i.uniformsList=null,c}function Re(e){if(null===e.uniformsList){const t=e.currentProgram.getUniforms();e.uniformsList=tm.seqWithValue(t.seq,e.uniforms)}return e.uniformsList}function ke(e,t){const n=_.get(e);n.outputColorSpace=t.outputColorSpace,n.batching=t.batching,n.batchingColor=t.batchingColor,n.instancing=t.instancing,n.instancingColor=t.instancingColor,n.instancingMorph=t.instancingMorph,n.skinning=t.skinning,n.morphTargets=t.morphTargets,n.morphNormals=t.morphNormals,n.morphColors=t.morphColors,n.morphTargetsCount=t.morphTargetsCount,n.numClippingPlanes=t.numClippingPlanes,n.numIntersection=t.numClipIntersection,n.vertexAlphas=t.vertexAlphas,n.vertexTangents=t.vertexTangents,n.toneMapping=t.toneMapping}Be.setAnimationLoop((function(e){Se&&Se(e)})),"undefined"!=typeof self&&Be.setContext(self),this.setAnimationLoop=function(e){Se=e,be.setAnimationLoop(e),null===e?Be.stop():Be.start()},be.addEventListener("sessionstart",Pe),be.addEventListener("sessionend",Ne),this.render=function(e,t){if(void 0!==t&&!0!==t.isCamera)return void console.error("THREE.WebGLRenderer.render: camera is not an instance of THREE.Camera.");if(!0===y)return;if(!0===e.matrixWorldAutoUpdate&&e.updateMatrixWorld(),null===t.parent&&!0===t.matrixWorldAutoUpdate&&t.updateMatrixWorld(),!0===be.enabled&&!0===be.isPresenting&&(!0===be.cameraAutoUpdate&&be.updateCamera(t),t=be.getCamera()),!0===e.isScene&&e.onBeforeRender(x,e,t,C),m=le.get(e,A.length),m.init(t),A.push(m),X.multiplyMatrices(t.projectionMatrix,t.matrixWorldInverse),F.setFromProjectionMatrix(X,as,t.reversedDepth),U=this.localClippingEnabled,H=ue.init(this.clippingPlanes,U),g=ae.get(e,v.length),g.init(),v.push(g),!0===be.enabled&&!0===be.isPresenting){const e=x.xr.getDepthSensingMesh();null!==e&&De(e,t,-1/0,x.sortObjects)}De(e,t,0,x.sortObjects),g.finish(),!0===x.sortObjects&&g.sort(j,O),Q=!1===be.enabled||!1===be.isPresenting||!1===be.hasDepthSensing(),Q&&de.addToRenderList(g,e),this.info.render.frame++,!0===H&&ue.beginShadows();const n=m.state.shadowsArray;ce.render(n,e,t),!0===H&&ue.endShadows(),!0===this.info.autoReset&&this.info.reset();const i=g.opaque,r=g.transmissive;if(m.setupLights(),t.isArrayCamera){const n=t.cameras;if(r.length>0)for(let t=0,s=n.length;t<s;t++){Le(i,r,e,n[t])}Q&&de.render(e);for(let t=0,i=n.length;t<i;t++){const i=n[t];Ie(g,e,i,i.viewport)}}else r.length>0&&Le(i,r,e,t),Q&&de.render(e),Ie(g,e,t);null!==C&&0===w&&($.updateMultisampleRenderTarget(C),$.updateRenderTargetMipmap(C)),!0===e.isScene&&e.onAfterRender(x,e,t),me.resetDefaultState(),M=-1,E=null,A.pop(),A.length>0?(m=A[A.length-1],!0===H&&ue.setGlobalState(x.clippingPlanes,m.state.camera)):m=null,v.pop(),g=v.length>0?v[v.length-1]:null},this.getActiveCubeFace=function(){return b},this.getActiveMipmapLevel=function(){return w},this.getRenderTarget=function(){return C},this.setRenderTargetTextures=function(e,t,n){const i=_.get(e);i.__autoAllocateDepthBuffer=!1===e.resolveDepthBuffer,!1===i.__autoAllocateDepthBuffer&&(i.__useRenderToTexture=!1),_.get(e.texture).__webglTexture=t,_.get(e.depthTexture).__webglTexture=i.__autoAllocateDepthBuffer?void 0:n,i.__hasExternalTextures=!0},this.setRenderTargetFramebuffer=function(e,t){const n=_.get(e);n.__webglFramebuffer=t,n.__useDefaultFramebuffer=void 0===t};const Fe=Ae.createFramebuffer();this.setRenderTarget=function(e,t=0,n=0){C=e,b=t,w=n;let i=!0,r=null,s=!1,o=!1;if(e){const a=_.get(e);if(void 0!==a.__useDefaultFramebuffer)K.bindFramebuffer(Ae.FRAMEBUFFER,null),i=!1;else if(void 0===a.__webglFramebuffer)$.setupRenderTarget(e);else if(a.__hasExternalTextures)$.rebindTextures(e,_.get(e.texture).__webglTexture,_.get(e.depthTexture).__webglTexture);else if(e.depthBuffer){const t=e.depthTexture;if(a.__boundDepthTexture!==t){if(null!==t&&_.has(t)&&(e.width!==t.image.width||e.height!==t.image.height))throw new Error("WebGLRenderTarget: Attached DepthTexture is 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t=_.get(e.texture);Ae.framebufferTexture2D(Ae.FRAMEBUFFER,Ae.COLOR_ATTACHMENT0,Ae.TEXTURE_2D,t.__webglTexture,n)}M=-1},this.readRenderTargetPixels=function(e,t,n,i,r,s,o,a=0){if(!e||!e.isWebGLRenderTarget)return void console.error("THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not THREE.WebGLRenderTarget.");let l=_.get(e).__webglFramebuffer;if(e.isWebGLCubeRenderTarget&&void 0!==o&&(l=l[o]),l){K.bindFramebuffer(Ae.FRAMEBUFFER,l);try{const o=e.textures[a],l=o.format,u=o.type;if(!J.textureFormatReadable(l))return void console.error("THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not in RGBA or implementation defined format.");if(!J.textureTypeReadable(u))return void console.error("THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not in UnsignedByteType or implementation defined type.");t>=0&&t<=e.width-i&&n>=0&&n<=e.height-r&&(e.textures.length>1&&Ae.readBuffer(Ae.COLOR_ATTACHMENT0+a),Ae.readPixels(t,n,i,r,ge.convert(l),ge.convert(u),s))}finally{const e=null!==C?_.get(C).__webglFramebuffer:null;K.bindFramebuffer(Ae.FRAMEBUFFER,e)}}},this.readRenderTargetPixelsAsync=async function(e,t,n,i,r,s,o,a=0){if(!e||!e.isWebGLRenderTarget)throw new Error("THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not THREE.WebGLRenderTarget.");let l=_.get(e).__webglFramebuffer;if(e.isWebGLCubeRenderTarget&&void 0!==o&&(l=l[o]),l){if(t>=0&&t<=e.width-i&&n>=0&&n<=e.height-r){K.bindFramebuffer(Ae.FRAMEBUFFER,l);const o=e.textures[a],u=o.format,c=o.type;if(!J.textureFormatReadable(u))throw new Error("THREE.WebGLRenderer.readRenderTargetPixelsAsync: renderTarget is not in RGBA or implementation defined format.");if(!J.textureTypeReadable(c))throw new Error("THREE.WebGLRenderer.readRenderTargetPixelsAsync: renderTarget is not in UnsignedByteType or implementation defined type.");const d=Ae.createBuffer();Ae.bindBuffer(Ae.PIXEL_PACK_BUFFER,d),Ae.bufferData(Ae.PIXEL_PACK_BUFFER,s.byteLength,Ae.STREAM_READ),e.textures.length>1&&Ae.readBuffer(Ae.COLOR_ATTACHMENT0+a),Ae.readPixels(t,n,i,r,ge.convert(u),ge.convert(c),0);const h=null!==C?_.get(C).__webglFramebuffer:null;K.bindFramebuffer(Ae.FRAMEBUFFER,h);const f=Ae.fenceSync(Ae.SYNC_GPU_COMMANDS_COMPLETE,0);return Ae.flush(),await function(e,t,n){return new Promise((function(i,r){setTimeout((function s(){switch(e.clientWaitSync(t,e.SYNC_FLUSH_COMMANDS_BIT,0)){case e.WAIT_FAILED:r();break;case e.TIMEOUT_EXPIRED:setTimeout(s,n);break;default:i()}}),n)}))}(Ae,f,4),Ae.bindBuffer(Ae.PIXEL_PACK_BUFFER,d),Ae.getBufferSubData(Ae.PIXEL_PACK_BUFFER,0,s),Ae.deleteBuffer(d),Ae.deleteSync(f),s}throw new Error("THREE.WebGLRenderer.readRenderTargetPixelsAsync: requested read bounds are out of range.")}},this.copyFramebufferToTexture=function(e,t=null,n=0){const i=Math.pow(2,-n),r=Math.floor(e.image.width*i),s=Math.floor(e.image.height*i),o=null!==t?t.x:0,a=null!==t?t.y:0;$.setTexture2D(e,0),Ae.copyTexSubImage2D(Ae.TEXTURE_2D,n,0,0,o,a,r,s),K.unbindTexture()};const He=Ae.createFramebuffer(),Ue=Ae.createFramebuffer();this.copyTextureToTexture=function(e,t,n=null,i=null,r=0,s=null){let o,a,l,u,c,d,h,f,p;null===s&&(0!==r?(js("WebGLRenderer: copyTextureToTexture function signature has changed to support src and dst mipmap levels."),s=r,r=0):s=0);const g=e.isCompressedTexture?e.mipmaps[s]:e.image;if(null!==n)o=n.max.x-n.min.x,a=n.max.y-n.min.y,l=n.isBox3?n.max.z-n.min.z:1,u=n.min.x,c=n.min.y,d=n.isBox3?n.min.z:0;else{const t=Math.pow(2,-r);o=Math.floor(g.width*t),a=Math.floor(g.height*t),l=e.isDataArrayTexture?g.depth:e.isData3DTexture?Math.floor(g.depth*t):1,u=0,c=0,d=0}null!==i?(h=i.x,f=i.y,p=i.z):(h=0,f=0,p=0);const m=ge.convert(t.format),v=ge.convert(t.type);let A;t.isData3DTexture?($.setTexture3D(t,0),A=Ae.TEXTURE_3D):t.isDataArrayTexture||t.isCompressedArrayTexture?($.setTexture2DArray(t,0),A=Ae.TEXTURE_2D_ARRAY):($.setTexture2D(t,0),A=Ae.TEXTURE_2D),Ae.pixelStorei(Ae.UNPACK_FLIP_Y_WEBGL,t.flipY),Ae.pixelStorei(Ae.UNPACK_PREMULTIPLY_ALPHA_WEBGL,t.premultiplyAlpha),Ae.pixelStorei(Ae.UNPACK_ALIGNMENT,t.unpackAlignment);const x=Ae.getParameter(Ae.UNPACK_ROW_LENGTH),y=Ae.getParameter(Ae.UNPACK_IMAGE_HEIGHT),b=Ae.getParameter(Ae.UNPACK_SKIP_PIXELS),w=Ae.getParameter(Ae.UNPACK_SKIP_ROWS),C=Ae.getParameter(Ae.UNPACK_SKIP_IMAGES);Ae.pixelStorei(Ae.UNPACK_ROW_LENGTH,g.width),Ae.pixelStorei(Ae.UNPACK_IMAGE_HEIGHT,g.height),Ae.pixelStorei(Ae.UNPACK_SKIP_PIXELS,u),Ae.pixelStorei(Ae.UNPACK_SKIP_ROWS,c),Ae.pixelStorei(Ae.UNPACK_SKIP_IMAGES,d);const M=e.isDataArrayTexture||e.isData3DTexture,E=t.isDataArrayTexture||t.isData3DTexture;if(e.isDepthTexture){const n=_.get(e),i=_.get(t),g=_.get(n.__renderTarget),m=_.get(i.__renderTarget);K.bindFramebuffer(Ae.READ_FRAMEBUFFER,g.__webglFramebuffer),K.bindFramebuffer(Ae.DRAW_FRAMEBUFFER,m.__webglFramebuffer);for(let n=0;n<l;n++)M&&(Ae.framebufferTextureLayer(Ae.READ_FRAMEBUFFER,Ae.COLOR_ATTACHMENT0,_.get(e).__webglTexture,r,d+n),Ae.framebufferTextureLayer(Ae.DRAW_FRAMEBUFFER,Ae.COLOR_ATTACHMENT0,_.get(t).__webglTexture,s,p+n)),Ae.blitFramebuffer(u,c,o,a,h,f,o,a,Ae.DEPTH_BUFFER_BIT,Ae.NEAREST);K.bindFramebuffer(Ae.READ_FRAMEBUFFER,null),K.bindFramebuffer(Ae.DRAW_FRAMEBUFFER,null)}else if(0!==r||e.isRenderTargetTexture||_.has(e)){const n=_.get(e),i=_.get(t);K.bindFramebuffer(Ae.READ_FRAMEBUFFER,He),K.bindFramebuffer(Ae.DRAW_FRAMEBUFFER,Ue);for(let e=0;e<l;e++)M?Ae.framebufferTextureLayer(Ae.READ_FRAMEBUFFER,Ae.COLOR_ATTACHMENT0,n.__webglTexture,r,d+e):Ae.framebufferTexture2D(Ae.READ_FRAMEBUFFER,Ae.COLOR_ATTACHMENT0,Ae.TEXTURE_2D,n.__webglTexture,r),E?Ae.framebufferTextureLayer(Ae.DRAW_FRAMEBUFFER,Ae.COLOR_ATTACHMENT0,i.__webglTexture,s,p+e):Ae.framebufferTexture2D(Ae.DRAW_FRAMEBUFFER,Ae.COLOR_ATTACHMENT0,Ae.TEXTURE_2D,i.__webglTexture,s),0!==r?Ae.blitFramebuffer(u,c,o,a,h,f,o,a,Ae.COLOR_BUFFER_BIT,Ae.NEAREST):E?Ae.copyTexSubImage3D(A,s,h,f,p+e,u,c,o,a):Ae.copyTexSubImage2D(A,s,h,f,u,c,o,a);K.bindFramebuffer(Ae.READ_FRAMEBUFFER,null),K.bindFramebuffer(Ae.DRAW_FRAMEBUFFER,null)}else E?e.isDataTexture||e.isData3DTexture?Ae.texSubImage3D(A,s,h,f,p,o,a,l,m,v,g.data):t.isCompressedArrayTexture?Ae.compressedTexSubImage3D(A,s,h,f,p,o,a,l,m,g.data):Ae.texSubImage3D(A,s,h,f,p,o,a,l,m,v,g):e.isDataTexture?Ae.texSubImage2D(Ae.TEXTURE_2D,s,h,f,o,a,m,v,g.data):e.isCompressedTexture?Ae.compressedTexSubImage2D(Ae.TEXTURE_2D,s,h,f,g.width,g.height,m,g.data):Ae.texSubImage2D(Ae.TEXTURE_2D,s,h,f,o,a,m,v,g);Ae.pixelStorei(Ae.UNPACK_ROW_LENGTH,x),Ae.pixelStorei(Ae.UNPACK_IMAGE_HEIGHT,y),Ae.pixelStorei(Ae.UNPACK_SKIP_PIXELS,b),Ae.pixelStorei(Ae.UNPACK_SKIP_ROWS,w),Ae.pixelStorei(Ae.UNPACK_SKIP_IMAGES,C),0===s&&t.generateMipmaps&&Ae.generateMipmap(A),K.unbindTexture()},this.initRenderTarget=function(e){void 0===_.get(e).__webglFramebuffer&&$.setupRenderTarget(e)},this.initTexture=function(e){e.isCubeTexture?$.setTextureCube(e,0):e.isData3DTexture?$.setTexture3D(e,0):e.isDataArrayTexture||e.isCompressedArrayTexture?$.setTexture2DArray(e,0):$.setTexture2D(e,0),K.unbindTexture()},this.resetState=function(){b=0,w=0,C=null,K.reset(),me.reset()},"undefined"!=typeof __THREE_DEVTOOLS__&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent("observe",{detail:this}))}get coordinateSystem(){return as}get outputColorSpace(){return this._outputColorSpace}set outputColorSpace(e){this._outputColorSpace=e;const t=this.getContext();t.drawingBufferColorSpace=ks._getDrawingBufferColorSpace(e),t.unpackColorSpace=ks._getUnpackColorSpace()}},Scene:wl,PerspectiveCamera:pl,Raycaster:Bc,SRGBColorSpace:qr,TextureLoader:class extends Ku{constructor(e){super(e)}load(e,t,n,i){const r=new Ys,s=new _u(this.manager);return s.setCrossOrigin(this.crossOrigin),s.setPath(this.path),s.load(e,(function(e){r.image=e,r.needsUpdate=!0,void 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"}),(0,B.jsx)("img",{style:p()(p()({},m),{},{zIndex:17}),className:BG,src:"data:image/png;base64,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lm5/Qzn+a45Drw0CX84N0620vQforczSDsswoKl3jf1q3EaRwQ0jG1VdQ6GmM+3pIFh5mMtpAn/WuPTRFM0K91QgZt9y5XgZUXZVletpLT66/9xnAWjkxt2GUZ9qSe1EGh8EfBJOwQlnYt9ZegRehCfclh3m0PjC9yd3vLGsccnm6ShAD2+o2WwDzVhlankGcU/k2Nmj2vjuN1+8WPGbngP0dlKQ5d5UVBnSiKXw+/7FjyZo/nFZlwLxwi8tHP+R7dT94fGz/yfhaJRKwqsGaR/X9zqow7+Hu7ZT9bplhwH94+kd31EWvmp1mm+RC2/UmbBtlj904MDmK+6bMqKdVXLLytBvposVv9cHNHuR9noAhTcp6DhGVsUx5d+Dn9imUJ6X5V4Q+La0/HGZ/+Sf/c1VgCa8/N8t3ek4tFCKrNbIlH+X10zL6U8R5f809pU/I6B1YoVwfOVCPfdjsA9+pR8UZ2ePjw+fWM2hfxzu+w6dJqiCkM4vzOc2CuywiLGRSDaqP7VIL30I9wC902e14f0M6CqMuWBbcdyDKKo4ymnNlqioAsB5UQWagB602qoRBJD2veNk4NPvDQGa6xk3wRM18s4yCtmxuFQWl9fXY9haWML8VW2Z/8OtDPqn4QC8Aw5vpeimZdYAunX0O0tfwTnW2kWB5XGX49/KfA1vMatFk0sfWusqsmnfXooCtyyHniGqzMcL5ba3Lc9dE6VXyXNPUemHAWACoCf8538zRvOmLVe0g4K7BmiCF3+qfed3ll2bNZ2UwnDHkfdNxyx9bN++9cLo7GAmbv6ttzSgr8YLI7d1yygiE8fIlKesvGZazbQfCLFKtcBOSJ+szX74lgc0wIvf3z7+3RU/oF6WYkvJmKLQDo7/hiAUmcWP4R6gb2jutnrT2y9frtr9DcehdZygikJi6mTm/jVT/p3EALz7kGk1y/xA5GrQ4bTh+/b3/Oc/ktzqHBrwxYfax/+B9Gtksg62PRlTGNjB8Rfzu1qoCKMIkjgGpqPmU0d6YQ/QW0XmDZZ7O12uZrE/OvDGBnVWcumrUHhBSpYdngWiJ1pJ8AeTl97Xxmzlc32D3drSbbsmcgC++MPtY99tIHAv9pJnEku0VuSIQoA4AWDq8N2/ZjoiTUTjCzOIeyLHlp7uDRZ6O1E1Tpamtnu7n+VeKKQfJTaqBEGEtog4+r/XzvyLttR8fpRLCJi/vjf18P3J5PPOI7pvALGgUYMRn2pe/qk5Gf/gdtvn8rsFaAXiwo+37viBNJRdC0l+LdYpBcGOZehqRy98YHqa9wG87NMtK0P/wtWrNZyuOw7tJQnmYUhM+XcOIXmQIFOX379mOpFAM1DhhMwyHwJpKZd5LrL4P9bP/qse6u8un5gH4vzPd+/6Wf5tuwZFVRJT/k2BpL9WV1/1d9WFD9zIE94tQEvCiz+zeMd/k0tFKLLkMqgrqeelg+N389OfK6aj+j8cdEFCZ+EDuAfoG3nWW77nF+hqzU/qfQ5duuOUn8y1cTNEO/fHACYrwq9BVws1IbpZl3o9azNdBfNH3vO/EeN1tZtHYvZnF+/6b12H2AGU9wQw7af/pzZ//99FLzdAw/kfi+/85yLzazLPwtTzEwN2aWFMLA4Gslm5Xme6hh+CD535PUBvGZo3VpABLRK/DMc4VMnqXdv1PA8qmXdIhAbJ2hiF6HWzTEuf/ZN9MET0X6rPfaiH+h+UFUkQiz+9ePePiVG+ECDhz6PZb/5yuPQrN9L73ePQcP77ure/if0PQ5tEwopIWi9MIG3NV/wr1yONbK/X2DPzj01O8p6tl326ZUWOGaLacrrsTMl5EJCXpsjUiRj9a6YKUDY6dByUgo7Nrmhl86aRq50oPM/+58qZDw4CmuuJSH4+sur6uRX9x0mAsiXSbzBI5TEr23rQuwZowPM/0L37e2SeY+55dtn0kn1eMO4nuC+RdGUxoPWiM27Yfx2Ya4/hHqC39ZC3W9gBGlIH6I1SM7ZTspUe6FXVmY5n0iZK38eAd6iu7OuWRPSfvC8xoFdk6M3q3Un+bgL6B/P7V3y6e57tpgC2GadTfhoeuiJbX7K+p9ksXprHtzIODcG1xxD3OPRWJutGy7yT5uoEdQfoJE0gDEJHi3Rdhj7YMne3JS4uV8Ucb32q5XkwHgR+L8vA6/vFJZlPf1x55gPd/woA/WD39u8tdzC2rOzlvu8E/32t/DUtD88kkWqHAc8ZANNi/oprpm72hvMhmNsD9I0idYv3MaDz1B99xsRA5KOJJXMqi/DKMuQLMggcoKUxgQceGK/wFZYe0R+IMx/oSv1dW2x+R8V2lUP37vm+EtAdY1YAPdGyr459ej4OZWtt9L6Nh+P3zNz7JyZWQgHuaPC7fPMtK0O/k6iepK0DDpBBQCZNkenwfNUW6aCEvNkeD85YIF3L8sCLTSg9j0zeD1lQ8ewn1en3d/HWB/SP9O75p+UcLEvTzQPfBMtJs5L5d3Sa8gu5T3k5V0xHzd9wfhSYq+/HPUDv6rvIgCZIHaA3SgrQC6/pO8ijOI7okgstgyL08uthBdiv81PR6ffd8oAmmP2x+N4VQM9VZNtvmWaYw2GQdqk75rlQB5tFTx2O7CcguPp+xD0OvRnYdpL/8Px8w6tWRwN66IngsqlXE3Mos34uVdYJApkKArIekMgBrY/yD/3T7+3IfGW3x076ttm9uyZyEMz+cOvef2YrQEajl3dNhIYaEkWvNUazgrzRoUU2iU1p4/jqR8bHi42LL/N0y4ocD9N8I0qrB3l+dQCkUkCm/NukgDIAYsq/+XllialWenraB4wsi8/odWUARqEJ0KD3H6tn3r0s82/5Wjyv3QM0XvzB9NQP9RazqpK2Qto3xhfLtiGupES21FVuNl/l3DHl+WhAcHUGcQ/QuwmOR4gaMaQO0JuGv+13xGS5rMfqgJfkJxJTLJ28wLMgafkP6mfe0pbZt+9mn8u6dwvQPsmr/+TyPW9XkFaF5y9nFTqdV+SOfTAqEFzZA/QuI4MB3YHs0MhmhsOB9sN71hDHqhmOWZ030gwos5mQoEROlP/51PNvbav8m3e526763QK0R+LKP5675xcrwnieB7kGtZgpOd+rUrpheNNNBl0H//IeoHcZGe9aWGjSeHU0oIfazjMQU5ndBxYrFgxZEqmtyC470VE3jVCK6I/rz/8PbZXe0oBWJC78UHLPDwgAqXJR1woEgcFEe9fSBrX6wU7XPJkyECrTUUksx5ffNzbGB7W87NMtK0O/i4jPLNsU0CbLsJGLg57Fagy0CJJ6HqJv+1FGhecRENlPii/9elfmKzumd/PJ7RaHliBmf1Df/xD3nT87PQVZZHFCdvJGHKnzPUUjd25L3yeeJ6YjAQ1w+X2Ie4DeTVAwoAUUO02HJYzBdit5Xg96+ljqe7O9yC57uY6CxI+syqmQogE8T9lPyi/86y5mtzagCS98f/LKFR/tjrRsrraNnA7zC70UZKfJ920Ryn2jEOurn5wHcGkP0LuJ5q/uxngr0VgAWX/r9OoHlEEGPvjAtN6m21FAuljFixEAqRyjIDGRUNejBrEe+g/D07/awVtbbVeIHPf/UA45sCV0QaVt8jwts1yOd+GVvZr/rPZo22FxM/AvfRhxJarpLj/aHVV/y4ocDGgF2ZHNRl9bNqdyHy72pF2WvucAHaYM6CLGBidDOf1RePpf3fKABnHhoeT+Hy7H1ZYFoPl3fdHcr0N4MY7ktg0kBvyLe4DeDGk7zO9z6KOjq7nOsSut9JhBEJ1QvEge2UqOkTBmOKi5/ZOAAZ2tbMHaYfc2vH23ZGjegvVQcu+PFtvFNPSkbDGgqdcLGrG4bzGyz9iK2vbREk3wL8zscejdhATAu2lpXEOzD+j1pWgPMBLXstvRU3O9ppgLcggDg5EEvRKR32hFf1L90sx/DYD+geTeHytnvivlEua58jN1DEDbZEw9vxkDGJXvQfvCe7FxQ77Uu4uCtbXfsiLHu4nGM8iPFUMaPOSBf68OpyhirARZfoSjhELFm/NBkwWFzMWsZmuYhj+tnn20jdm3fS0ewG5y6O9P7v9xC5rYhVZn3VAksI/C8FoWpVfIq/QP4hwON7nxqAPwZt+LuAfo3QQHA9oAHC/gWyyCmBbwLq6ZlklpiLCXToiU9vEOUozEvFRgA4s1kUPlk5UvPbyo0tftZp/LuncR0Jf+affUT0CCNa31lJQipggu62q47N7aG0wWYPZ/RCxi9r7M0y3Lod9GNIF9QA/Psc1zZP0y08E8pbWHsW1GVt2Wal0XIKASqC56dPUPo2ff2roFfTkG40P7JK/9w6v3/pqfZwGFwWyi7Pm8KrvD+yLLuXE6eJc2OtbIHQxzfg/Qu/wmM6BNnt/Gzax9QMONFw/MS5Jq09ARq0U9tdTVuZGCnZWEhE83z/xMy0u+fpe77apnDv0QTMH/Alfhc9CFc5BQF4oQCTtJvpVX3tS+/y2hgMiz1k89caldsZfIxZq8fg6XzQGFB8R01PzxnkTjecSU87M0ffGxer0IQv0yTzuexJdqfO9ptSaTMHSA3kSEdkXqudgvdT5mhYgNkbaykE8wNSq36H2m+dw7Wir9xq/FeKbBg3mW39cG199R8xUK/uq7szt/VaUcARh9tHyGpvV7nnohU7Rt7UbZmdDzXngv4h6gd/R0Nrn5PUSTvTy/fStt1BN7UPAOFwmXQYIVBgM+XM0pt9yhfwb+xjv7Q5f87k9upb6XYxkJYuH+5NC7b8/GZq2UTpRIpe5GGTZ8S9PdEJ7LpBwN6o3X1LyL/oUP1etXX47jHu7TrcuhiSYTyN1pUjoHUF5Bhzl2oE2tEcOxVgQvGiU7gcaKyUxFSQZz4e/ugSRI8npbpXdloANtBfBp4CYH0T8VXBhjBAqBYEGY3EhUCgwXRECrkcVx/n5jz0/qLT/bP1ftviaVep24IUU3kcA0svDZeupfUEamQqEFskBCWgGWTZkEAqwLTi3RoiUiURzSgggcmx9JQmIEnL/djn2xpsPCV6N/cmde8Z3/RS0106ix0aqa0wIUDc9XOXdMR81n4HnnPoS4B+jdfKN/mVpTGsLRx6MNrHFqKZ2wGtJOFS/z4igwWJE2qyKDuH8wBaVAQmAdu/kBsoCogIYjnBPjtYjBj4K3j1vGo0WmHAqd88laZGCTBkf/buzyt56vtDgI+ppDYT0rlr5u4cD/fDBrXHLtaQuoBCFXZRnUglgoQj5laLg/5cQiCBTY1lV5kV+mlfnuHzXbs3aJlNISUVa7+lRXwnMmkL1NRbQhju2Bd3YP0LuJZgD4ZaKpDPKTI5sZAHS9a+7Ja+piL8/bIlLkJabqWVsBI6/DTCqLadaQGexnkG7UdWSgcVonpD8ZiyvnKEuAz1WvfP1z0eKKObpgoBh/3fKhjx3N6xdcfcNHAgycK+tekuGzmfscGCWgkdQxgbgojCzadbJGsechRrvIgGYA15fMqbymZhNF246vISA7+5tYW3Xc8y4/3huu/pYVORjQsY7dyTuFobeMD3r9mv9W6ZljypO0APqCF0XGT03VBxXxprty1nRmwBOiholxO2CGj6C44dnt3/jXzdnvWvSSV/DP0HhXTsYTnzmW1C+WYUG3216Jf375jMAOBILr4uOXXSrx3/EY0FIr5YnaYvaq9rj/RVu42a1KpHNE5RHTUfOJKnruNxH3AL1TIGx0/8PUniYtHaCF8sjqHJny7xLcTEWiw2ps78wr8kJis6XAioqHWBkMvAjSt5hSQxpyHNpYi1IIYsr1MRdlTlly5/LacU/muP2yTAeZdwlYtBZZhGDK+eW1Eyu4/qH8NYDr3ztcXmgrrIdtEUUXjEkFysLhqgR0ryIWcshto40nWajpePkLwrvulFW2Mzx/5VwydeNR9rmPYe3ybj7Pm1X3LcuhHyaaNjq+eysTEWZiTKXmUE52yQTYCi2GViGu2M6ktJjlTZHApmERRgF2s0OFtsuBiWVpbZGpA7zWSEoR02K8RY0sN5PEDlXFBcuHjK6yBZLNBSVeao8Iz9M9D85bRWu481bmD1R05mOIe4De0mTdYKGfb7f3Yai2BGittYhQVFVM+4BUhDbrUaA6xOwYjRBSWurZhsztAcKBxdUN9u3m3zZKyGZACwSFbRPARQLJx+YSCGltnvmYe+OIRloPFzJp522wjspuC51AsbCwAAAgAElEQVQ1mT3zeLV6aQtFX/IityyHfju197W1umfUDA7L1KWUrVIVqUxPkTHTxIdRAHWEb9uAMhXGNiDVh4qyq4Perz3GbXWrm3Hg0XBc/5g41gGyrs7pAl1aXcOKDG0BraI2VMPzZEFanVcwpyYYjIAd+SNx3hAvGoN8/VXG5hjMlT39OO4BevOZ2kGJtxPt6+rk3u1WERisiZ4eJ8IAja0SkYfI+7GYWZsGS8tCCIfoQuMxoHJYaayvZlhRKwyrIbbbq62WL1405L2vTlZGCUQZBbJtU6qy2o/IJEJQFz2R5r68mqsbd0oqeyUze/q3qtWLW+3lS1nuluXQb+l09qdB0Af04DJw4+n0MqxinldRShSIEnLjGaIAUhozmZ2yxDYMZVAa1iZbKYQWWAB8mHMXfxsF+NV9GF5EDi8yV5cefSQK67ktgbDMiQ161mrFIgcKTFQFroAKYkTDR3trEsYKA5SE3gJJugEvu9XfOKWyr/wW7gF6V1/Ut1Bnf6zlKQez/rHF5VHFw0cZC82fZiCmvFkUbV6V7MwhDEmQzkiChpo21odYCmUlhyErkUC4PGc3AUIEg1JY4e4Ay/YVFMoS8GtQWO8cLXXV68wA6dIA0/8CSEYroBVcsxYOuPymGJJMuR/WFscqC4FWoDAgwSjuhydb1jMXleeZzBamUiU8ImswDbx5BvTg+N189eeC6VYekq/CL/8W4h6H3spk3WiZX+h0Dhgp73OfXgUkNSBT/i21QaMkMR2unwEtU1FDyZblQnNrISHUfl1k2cG+RbCwAqJAsgKtNYLY9metIAY5IFpjV1gzoSAkNqhIy9jmDBJEJV9fpdlmk7plgyAC10CW0N3LNnbHnAsJWUiwyF1g3xMAvsMKQe4lAvfFKDg58aKwombRstWw8OEQ1iC/dRkbVnhrzpq0mci0Oh+Jnv3tSsUFeny5p1tW5PgF6hzIU3DGirXPSwEYzeFWiqwBEdc3WBVpXltxeOB8Hyxk1MC8r7ZjDsoqM6YOIX0OCoKh7MDOf7SauSZfKyDUSJalAAapRiKBvLRz2rXVazsHOkLm7oWVkL8ASP2vAF/zewSWX7cin18YZ20vAV90it8KEti2obiIvBunTP0DjpIKLoCU+RpL4ypNPYCQkqwxyNS10L9myr9lIL7027gH6F19md/c7R60viwAXYKX6SZJZbYmjai5JVV53jdzwcw2bN4PLYYOlQ5pfTyzJFKwXk7a8ncd2OdiUAFB2H8B+vezJqW4YVBL4ZxFOPbpSv1o+3WvFBso31ehrNTN1fXrZ2cpQmzL0Js1TkQZDC5qIAmgAPSatJFtlRE8xBCU/dK/xcrsZnP7csi/ZTk0A1r78n6exDWPx2hQUoEuAT7wgLzc1oIcq+zKUQKAQFqR6CZYe8CpzAR/tsFRB2hri2tTgFAJxg6LCYwsBGONkJI98Vgq0c5Vz4ku/AY4h6U++JkW3nLO555969ijDlk+cXI4ujwpnCdd4Zffv5fd/vj9KTpU1Mc1k6C2qngX9KDp2xiQUkIXswViQA8DdDMGMFReKPvMHqB3+XV9M9HBPO2+chSghx8gA7sEuMqpFtqgaiADXhAWKQPMRd1ocqHF2E2zD0Ygxp+QgAJZoycZTSwtC16kCclFBTNiRuOKUM3YZOZcrBWvX3M5lpnBAZl/OHHCWMt+qmStZupkGvYjlU7gsCyVG3R2c/5L4U3KAOcXCX3Rkh5dNOL6aMozFZOgEDkGx1/MF+vytKMurRGp++JanyF4VjzzsUplzWlgu/yIb6j6W5ZD/3S3ewgkvMoBsHANdi7CxQNa/ckkYxClJKYqtzWlqcqAKjgln7HiWZNkDcrwILs8O99nh2KQCKQMKYmoWS5wjs8s/5b+ow7fxG8AugUhw94t2pidlsdsD4owfQdrZ9ghlrsRkRUXKMEgeztb6fqfG4F8+As3Zy0jn+vkgxaN038YYJDzbW1RU7M6t7IcD/DGMgBK/ALQg+PfynwNi3DSZs88Xpl48YYQ9jW+6dYFNHUP2RRePWq+BiTgNWopBrTQol68BNb5OKMHBnMxRpk9YlEoMuQ5FlhoNhyUeKcLWtCAZJg/M8h4UcdYY/AiR2Jy3JPDTbPI3RczBkQE9zdOhv2dAVmsQGQ/ambUboHIBZDIsgpPIH8XyErrPLCLvEJ9KIxbsZIwKO0i+tKBrXR9Lb8AeSTnRu327kvvTop33WP9nwZkyr/La6b827fpF/cAvctv5k9T95BJ9WuKZlZL0eUDLTlWyY2ZejnWJFHNfczJkEJUbDEE9CfzXjZpDUnhSSBDrI3TAiG34PR2FhXYAsB95yBReK6xhoJ9QPqaCrCs6+t76Ln8Nd56GgUqWy70Bk3dbIRZcbXuy+JoLOvsBBLxId6KiJyswH3xAtnzfHU1R90iEjGScepIQoN5KOcsuCAd18WcUc9lWKYe+sIFAX7hcazscejdxPRP9HqHpaA+oDduyQDbISQw9SzVIMYaO70HuaiCwDEPMcozG2apraFwqooMEHKJxPoMIq1512nBjR1LKxUX17UgpvB+66fVvhcCFDBzZzoqcb3Foq+of3AN6dSDhQoPNYvRbBskoSzymc7oSYV5FMgOCOQXr6utXTSCUpaYdADzlnjb5PXxF1+IAbmZL6VkMcvRkV88yr7wu9H4C7v5PG9W3besyPHzvd7hRNDXFROxmS/F9VWP0lSTGusSaMIDMUbE0LZgjPDiJAmkwBgRNfJabECB7FRwbinnFMgF82e+x4lYX8ttFLeg24I1qCYZ3uHC2gu27DCD74O/WFeuPNdSE+JEIre6HBBhlAJriO3eAQohg5B6ThcOmggpMYTXjLSdEtBrV33D8FlnS0x/0SxJfP53o2gP0DfrrRtVz8/25o/kIuwDerOWrj8wBrSv/ePC5FNSKMnyK3PETJOX5Wxus7oAGQd8LPXaJUu+3g5RYR10ajfJ4uvaMqv3vgzu2Sp8T4g0spbD6fJII2Cfg7tOMY7LL0LfijjoNuLkdfbpVzL0kcWK/lYuYYlslmF+KQnwBRTSrH3hh9UaGwMcyXz+49H4uc1m+eWQf8ty6J/t9Y5kUj9QTOLqB2R1hhIDKSGT/MTBgoeWzXie8Aw1MbdHWYXAnI8Nz4wFbSyk2vLXudhRLYDYa6Ow/BWWQbcRlS2FvEG2b7tGMoLVZM58zSY/6rNZd6vb8doX5d16jisodB9OpccSRNFWYaRhe/l1HTVXZ/nFcT4jg34XbnO4WzxKIUQYcJw+XlkWhnFeaxJgNw/McxzL3wphSBhNRnA8Em1c8AZ2Exl9ytvwfAorPvfxKNoD9G6+sT9LvSNxpr/eM6gA0ZOSzzpGz51pVX67JVunwbISjQRptoYIjQc9UkfAGGQVQcH0CsDGSc6qBuaazDaZCHYachoJ1qyJvt9FIYr0TeBO6u0PdT3+UIC3ryUcuC7Ll8oY97kg5LNf+iDn34bYNcSZTlj77bxLSDP4tQ08ZSUr7CwBLwddb9xv9razXyBBqcqlsh7Hh5LsGCuJTdzGgHYqdVbSGY0kMmMyYyRrTgoVJ1OuT/ni7z+Oe4C+qXh+4okn5OK3fEtwCWoVFaho0dPHlxFfxQ9cW+CYXtoSGZaGQUpjjXFGClaRGV8YNMw8DQZaHFNa3s6LLI5dIKxmq4nzw9TGYpIZ1iT3xWMnRqBhzTKzSVZPu0Wbi3lUuL85PZosbH59j7u+cz6rBYu/FS8FMS0Qx2oRVpyzHO12dbOphkHklHV996T+/vN+HSxwy/4O8b58wXw58CWrCJ2Nsu/2xypFYjkj8ekpq7DjzPzuZsMOVPyRUdKSO1QXBGWch7z3xZnPuTSrTzCzBjJDlAOqJ/9DFJ29qQ90lyp72YocHz19OjBTJ6PMQs2aNGR7HfqBhV6iRSPMZrPudCuEV3CIXB+pbg1leYAtFoAl+zRIKZW1gWcxBFIVqXUkpPSQZBVyvV8IWbq3les7BgHonNDwS8CG577jUGEuLMzUzvGt0AX3zdWMeWbomgPE9DFsNnQhLUSYgUXkigNT3/eDOIBNYT5nPXV/Rzdbyguph3m1FBSwpprt5CxN8wsi2du12HRrERKL9jIgpRpEBkg9jRgTmBQtBmjRyzDvsvnIp6BuTW6Mwi4DXhjw2dIjCn2oCDLxzIEYzop62PO6V3rH/+Ivkoceemg9eWWXoLq1al82gGYAL+zbV4We3/BV6ANmAhVlSW6SIDVpJgD9Wp2yDsSQLvkLTfmKZQ9PGTBLUqkQM1MTQmkhgLVtvrQyQIk+aBtIlD6R9QtLX+E0YS3VhKUCVU4edmYUB1rSlnKyZK3g/8BYBjGDttjIwpwVHPxZpdHHOdsr+zLF2i1U5aK09JcrSrjFoPP16IskTlvCdRa8n/XUBXdno6VxTJTNPVIiKiUQWZByHxMnzjhfELfCRJug9HoIml2p2UHEIFBmCDJCkVphchYxNJiEF5/GGPbC7vBiQPIZ6gbI+LiE7IVi0Je5+dy9cuy8yeMwk1EAGQhDqQHUvWnodeamp3sz3NOXQXrJAD3DaoIFqHlJ3CQ/qjCAjaU8wqAXd5Z6UU2bWE1JSMGPu5BGE8xj4oZOU1yM83l7sHki8bJv44cgbC55ecQsRQAwFw6RTCRIBMVTtmwYblukDhmjEaWvLOwHg2NIoPiBFxaTvrNQYUZ0/yyH5uq7Hjsviv5jW22C3ExGHn7SWytfOocIofiNc2AvrNpOwGegsuKQnbPZr4T1ivzxyLWAq+ThvCXBQlLoGdMAlBW2OhIfKQMYg4JYG8xIgOaX3Lhvi+G3O0uROopfK6IGexlKTX91bCl/oR1IdUD0Yiv3CxO0fdtWFfJECDkIqAaZjDudLLnWnrntthsODLnTd+JrCugZIpVeaDcbtXozNVnop2BF6Pesgm56ZSHH6oSuiiuYqv1j2nYNZUJpjFBRTAuzcSsasySC2mQYisq8lx/qBnSvAX4g1hOEVUWyAkAV/p4TQkIW27m0y5ooRlZ38EHuEiM01miBMQNUWZwErZtIUrEejvG7SqPgMDzEfPpoXvF+G1jube2BDG+rdTKu00mX1vFC+C5qu75ZtnhjS901g5w3HDhcC0yMsvNWypaw4CvEkMGYI7UJqWONEUqImmewKdhS6iyONqNCFOkyu+C1s0TpFbtl3JsfW6HjqpGnpzvexWypk1fHdSvyDsqla20/aNbjqgDseAvS10Fkg2rF6CzwybcW426gW0vvOHBg5NmIW5un7ZfadUDPfPrTyr/zgSb69fFcQoBJqjGwnU4364VRlk9MT+f3A5i/utabzmLA3FYI5bygPNSsfQPotSsqjGTkjRuJnhSUCgpaL4x19+WZ+HYw1PQEVNBghVhCAGrlAhYMmZ4VyJKK9EFMSIMNAqtzsMsGVc9KQ7xQdLjRuqLIG5eWxsDaqHBjLhw7V/ygB9XIg/7N/TVbuSgsHkGp0Sind2PDxXXwln7Rfcth+SINGB77QrSr2AnxArtG2AXyvEVCk7MXSN/eJ4QRDZ943MAixUKGdsktLojPAzNNBWoCUURotNaIPYOmo9G2LIlMoQ2QVMQCUIDBkyeSpb+NO1O52g+T+aVYtnwwpNPuwdqYiTsgr/bm9MlGavLwiDIB+LaT1IQfRlmWcUDBzqE0Wvi5Q9jbPkS3d8euAfqR+fkG6uoUEFbY7qt801Yi6lzLruja/Hz+yKlT+tevwnQ37nGgTXaNDD2r40wJqZNep2KmUrU/ntZajvuspbWmrbO0DcFYBqrbWFLqgY4yr5eEVV695QrnDdhrWlOqPZ0q1k6RmPAsTANhoMEu5MLO8+qdF0QkKLfGmCLSp/ui+6B1qEjVhMWGtLbG3wP2nyi2nfCOrEKVUSgrSrGhr1MecBdF3o3obObErnR9i2NfZma5uO/7cd29dLUlsTQyslKN3U1Z/4BOjHf/a0uYgKK2EWLZIHWBKNe8RZLFD2ME+EqKHKTxKFccKUrDfoVY5ZAGKdJlraiN1nqCRS+imm/VPkHQIDCZBdnRSG0t8wXe0shftnrPPndI+nOyS6lpBPON1mzckkcwj5Jp6BUCWW8p78JyK26ekAhp6v4W1U54LJpkXa8uvTAyWUae9Bfza88sztx3340FvdkE3zcV0CxSwFx3CmR1QmQZCrIdWQlbKoGssR+yn0PMGehNNaFarRYk2m8E0rKBjrrtjh0X1xYBTgHVe1MQqCmUfpaZ7mJTVHvx1WfSRqMhu3LfidzaQ+0K3tGV5pU5+y749lJG2DOSMgaLsuxAhvs9LfhBeZm0l3Iw17QSqSCMBBmdA+nrngvXDTNkrCK0yrfSI0MREFWFkBEaiLguRGJDjWCdHbKTv2PIrIcbZOFuJVdsdXVvwOodA+4NcgaQfr6zFg7YvQuJhK0wbAzMubtWiB5J6hFiz0oZg8mN9RTLwGsWYzI3kpTy0YCxgtiMH0SkDrGByUjqaciuaOWlvPcQjJUKVSBBNH0jDvPaO0fTQ8I4VXYuQbPoEf393dfEBWqONfJud0wIlTZlMCvzou3Y7zbyQFWTxdiSDWzaSlsfec34EufxWgnOnfNJN3ysT4QgoAE2CzVSLFvduUfvnNx28MiNMH1TAD1zlsJ8LNmvMtE0mlKr9JKn0nhhYSF97M47U45q/OgSNJLWMgbKrxtPBMlCosknWzN2cQEW0nT5pL39dqh0s+4xIM9K9OdAzPVOTU/HDyGamUUaM2l8tyExxcdIdDw6uOTripZ2PhEUs4HXsgmaAyJmMKVIHpZEviETx0hnyKOUVWWSqJohdp3E2i8vDCBfM3X461/396lIoVGhBIGaApZPBZGPhAGxLoCEAiUl5lqR4PhiwApl9rYDyk25U3tFSHGe1EWsOhfzmUV0CcISkmZLCYLWJDG1hBlJk4LADFDkjE1jyChP6MJ2VIoxA/1dGY9xXxyOTkpUjButDthSyl8zo2zCmwWGxi98TdXISD4qb5wBbSTkGuy8yfM/+l8nJ595+PTp4PDkyXBpORkPq3JMW7P8yv3hi88884yE8VPObt8wQM9eAf34a3HN1q8niOQsgJ8tgq8JGhqgLtOMDKRzM4fcsXFb2oW+a4D+jfMULfjpIcxFTXpeG7LWUnUhTo+/cn/iQPjpT6uD9TpeeuAB9K7BZC+LlclSqTDEOF1s28rB7uxffyL7xFd1mjOX4hMZ2QkvwKvxXHf57Oc/3eO/u7f8/PJELv1XIOGYUCjJ2GjOh8uLfnKcRYfVplqUFUN3CCvqTiWG1On59JU+C+VYAaEDLemU9bbbkdCcLYR5Ju9B4R3gQvJGEma/rEMTbKAAbXnrt0DhobA5cogu/rNbyLFZ3SlP3OrPkuCbqbBmFupE1v0wtQ73JBl+xI7+gwDe1DfDWvbYjqziY5CdfnHLSViKIi1vk4BjFiFlIaZC8i+mLp77L6WYMEPkJy8uV0Mv2m8sBiJun90up+U66MxCmHthNfLVWMY7Kr7KxGYOuKMvtvVcBgd3Qxza6YwbRw8bEHWfvFY3XV5KRTv58NGjrK5Z6czM4uKYsmP1eDkRxss8kwUooHc1u9LNmumZfOaNb9T81n7+UnaXFSD9PLl48Mrp9s+99rUrb/fM01dr+Vjt1RLkpHsy1tYA6bkXpvRiqs2aY9ikRT/QcA+ral30DIE6FfpcBrbFplyn4rLKdydTeJiTCyt+c1JpcnefcvZJdgcBDbtkOo2G06S48RiOf8SAXS2yXHds2nrfirGhL6UUbOEjcWNjk4RRNcf7OXQCr7LrGp5tGP+z6qD/5QF9M85cpIgCmLBpvl+K9PzMge0fW1GIqRBm1K1Gxptgzxiw/uWZQzd2jNx2AY2PzPYOS09NWrTdJE7mQ7sYD+odWWbyrsJ0lsdeJ0MZqVR1M+R3fUHqOH3hy3+RrHBeIpGd75wSyjd1z5991zSbaQdeCM6f7b5CeOoEbzGSnrTGQi0E/0+frizXSdG3Dj9uslZVtXeXIAxLpbFFirWky6mEJVbUOhHWWuVMFCxl8msikB2WGYGrFnF9IXjACXrrAPtalGQQC3bTQ5QcysDyFkUh2J1vW5x5dV8FVA3coUhNG6K0meHpupHPKxH87cyB1UdTvPnJJ71DR+4eNySOa7Dn3nvwxk7LYsb2zNxcBDBdy2w2RZTZseXk/LvumW5vZx63DGhezNk8OC7JM0D+1WUD3Q8fxXiwMRYx5o8ckZP1A01PCnktQSFTk5vA6mar0Zm5D1etbN99Jbndy3S14VWff8cBp9JZ9al5ZJ4aeZp+EwFGZbBB0ibSi60/vHg89FNF37sW0Byp0N8nMnPY2QX74QIIMTVCL2spF3O0PWe+5sWdBJQGOXSn4OAxLlqcMzSw/RkM9ePcbWdSd6usswpaF4PGGZL4ZXSb0QsRhn2YnPPSyt7CHXQk1HTEt+oYEcVjmfz7iLwl0smF8GjjqWGr4INPPCHvfO2bpqgiTuRXWl/80KtuXPfMwH76zEIVKtFYTmrCl2bp1F9+6vxWTe1bAvSvXIyPCyUnbK6veV60OPOxR3swM7Nmdf1rXTqYLYGXioS9GijNUqEXaXFs6e87M298I3OM6+LIVaqlaXyfCaNnPjDEmcvn8CvPx8etsiu7UtwihqgpNf6Z//EPXvncLz/8z4GgNrzFSSAqX+NBqe0UW9ScCs1pEngjIGUcU9kAtC2ZnlGYsY27f0aJs7wJlBwZqTA9cqeLgOSWTxHiTzAoz4Blfw3m7IV75yB2thfLrnRPdTW49p0DETsqFf0QzvLdN5O7fYy5BuEJo3mbWOFaatkZy/ka3kAa1d9qhvdKwAYRxAd73v9tJRmVU9e31b+cuQ3XWAKZmel7v/Fonpva+4/WvnAD3Vh1y+8QeWdfXK6xnJ6Z3G+G1bPvmsZNufWGgJ55+mk/nTh5MkAQy3ly8Z4h+bbswbsWFpoNM16JTRKyTbbbTtEgs9XG1ehF6M68kR0iV6d/caF1t7ZknvvrPz1biiDDZd4zm9xlBJ4CXdzuHOkNRhrsYt3MffbpycnjWpjX92NfsLa6780mSGgd+OCNo8EpNJaF9wJ0LhqjNLxPkLk2IsYadWzYcUcJ1sgYBjiLcuRMygw4Xgw6TzjnCy28Irodh95ycnIRe+N6+042dqH9CYxFBhqHH0fB1KnKWOFAkPf7O+jO3b+PZasCrOzwybEM+u58hcOUM1K6PDemofbLvqycB7NJ/tDE+zmMBxbvsYhpoGl2MhFfLvYp6gy72V9+YB0x4G3nKQpN/OrAX/rczKFDN8OIgm+/fLkSmMYEoZqGLL/06yc2Duu7LqA/ePlydd7U7wJPtu1C+8oH7pleJd8OzgGLI7kOIugbObvQBUQ/HTvnOPPIcEbvPN97HWbJl99/xwTrIUeuat99Nj5hpV3Z2V0qqkhiBEbPVq92nvrcPcG3kYXDozgCWd6LTZVAwzigaAhLXulgz05qfG6947hf1ciwlZhQ5JZMZjlErUSnMuOFFRnjODG3wZEci8XfwKFD/cbZ848veWse+xMX3L3cp1UUum6cKXyNi6C45XXxF6eCdH7/xWlYPG5lkQVjdvLbPDzU0GQMG9oHDI9rps0D0QwyvMNpchA6E7H8G986mZw9SXqhCf5iFIfmfBYX/t/Z7n2+wbnNgDfqea33t995krxzhy+PoZw8LKxZ/tcH1ndlHQnomatUSzC/W+bmWs9cu/rho0dXycplw6yXnJg8ud9kieTNRDomgiQFq4zuLE1cHqWLLO99z2zvmxKK/n5YDh8c1LueW2iCH7xeEwT8kB0geEO2iwdqAiKc79r26Utj3mukxEILMrR/xcmdhJ6wJkItGgpEDYmCYsfJQGuFgEqFzOwsciyoGEKh2UyJEp1lEQW7sCFv+TCgGGvCkCnucyIRf/oLzjpSX1bqPBjozN3dTnTpFMi8mYCtplxECka5texTx7tzlSTyWM/tLIMAy7m08fAhQaPGX7wyqyL5jcaNtTIktV9pOui0kGSSqSR4ys/5M2/AKsUrkguVI9GT63nWsSx98lu+705KbfK+227yhoCZGTHzk29pZBXvGOU2ee+RxldGDWQNoN92/nxUkfvvA9JXvKXoyvBCrqyktAClk5PVoFeXWdKTiU4UiorIrvYWH/vGSZZ31tUnvvNS73ViLjv9vleOsUVpZDmeoKOvf9MrSNvb3Y7+FVsCiwO8+8h4lk/FsdnFyxNwuCfthPv0DyX3RUdEZZ0R2UNDFWGhxlZDIPKlEGi4wsJid90O7c4LZIOe+3P/0Esig4KVzbz5ivXFjEDeVeIig3Jh7daaLvhMwdUHLdu8RcTFlnHcnMUVwe27DVwuGhOruK3g6NX8ZvX3Grh3xHXCeV9jZoTtEEBLS9szQhSRzdZhcRvGGkXE0IhxYWi/sljlF1kgdRsd8bkQS5mVV8pGS5s8+cHb9q171grL0a3bXne/rNClD+7blUOG8JHT8/U8DE5YML33HW2eGR7yKkBzh7JTrz9lrW3ddiC8wKbq9T4DM2cXx9TYWDOOE3DfaU1G6TZzK1v/3GJr5qGNbfXveG75ThWF8sz/9cnT68nQ3PY7n52r55XaqwXSNHM/Vksp9ukl6hklOn4Wx4nxtKdUYzGMj3VCeTQhkwspOBKdS2s+uQZ4Q6E0HIzWUChJhgIxREMBR/TnsEkrpuh+zOcVZ+ehL4ALkOSifbFzPQvYBYjXfZdXOTkVPhrMmF1U05XIL6tn3dnFC41N/0QBF6SJYxPEBmHJCFiwEgqz5FBoyJHj59Nzc+sjyjFlYQIBK849lYQNLMw2Y/iydBJOWaHbsvts/fnaV0ath8piLEP7Nn4gstGT64kl6+FpG393oO5V6yd9X1/5tanVUVFXAfrd55dPWhl6cdd//rE7kY9vXC/hzFkKAJbC1JMS2c1Toexq4YX5Yrd+18GFzRy+2cp4yWLDHlYAABzISURBVMZfl9v06Y/cNr68ATfH98y2JmJtj0uMEjC9LoSyW+vWM6xe0k8vLuoD/imUnaVI1IO69rJ9C76+LwnEYdZoWPYiK2Isr0gYgwBn1RfzerAciRmkRPLA8Njcrg2+ZjM3f2/5G3Ed6AMzMyyTDr9Aw5O4afnS98nJ4C66EnvVcXAE3maWQzEuVoFmVmKaC8qKw23XeYGv73pUwoiab+0YAvIXire2u5lRGq9UjfhKJXW2gOKv/NUQksX4c9W8+uxGIH2QSN7+Yuce/kR94ET92a1a+1juZqvyNgDNRfFt55fHQ8+70yx1nxlcpK4AmjUVlAR3Ypye3mihxrW9/fLl6liwf6qTJLxt0+SGTMocOm+Zdh16jx86xDL3ZuZLfOds77AlOAxe64sf2sBv1ok3lyCEFCyc+4weVgGWk/HmJ8kbq10LY6lDL6qOL3jmVAL2pJbQtGBii7JnUGfkeVYYi3aE6Zs/8ezcxOZraYuQoi44I0vvLLIQcSBdZ8hw+gcqouyzqwcZ4zboctCYwfNZXMi7AiB9EYRXoqzuc7KMi5/OOwJRcdh2wUtQXhMaUCK37OOhrSVf5siyOus0FB9vxftk3SZXt7dxFeN3p9kKwlxLJAwliCpaqEuiCnLAr74jFEpMggwvVmL1gm9svMqoyVuEUWQIyfP1ufTczGvX11rw8+m8sHwcCPcZ1fr8emuuYdAymL+wkN3DjlFJluUit3FmVTe3rV6Qid5S54Xk8QGr8eD9LI7e/s3fc9iSmvjgEf9zJd6uA/p85/5ciKXGV/7m0nqaibJCFk06994b1Ox+Wjaz1NSaoNezcPWqnfnsZ+0oHfWoN5CtTNXpk0etxenQmmc3e5G2/Ba7BcQj/rxe8P2q57cBpjoC7rbCHNceTLGzlJGYWKNT5nYkxKbm7350UbYwFifbsycGu96zmc6CYzHOv8MFM3Cbl4rtVfyP494Vx1AUQc6L/V5kOO5iP7AjO3Xw39zGGaWcnrvwpCtDG1xnEKxpYa0LU8euihh7riuSLaSGKhKgIjgQDftM8NeHk0CSltpeauYjlJcqmVxYFd3GiTa8V5bhYRY8LZ+LIZrb6GvNwDr4wBtu90UwocF++SO3FV52W0ozM+I9//0j41UFYSdNPIzzUFsRZjkH0OEzZOylDx8fe369umbOng2TcN/9aMzz7z3inJsKNdPbL1NV2N69VlS+9KED+DXdYcCaEl9OHdAoDkjfu9g4FF3YTFzZ0mRdL4QzT5N3FeZ8vzKtiK4GrTA4nIA+Bp7Yb4yetr5fYxchw2sGQRn7dxSfdPaXLmTx9USWUX0xJkcXeqyvhpBuMzWzc3ceRXHLNh2j3D3MeV0oX1SI6LHHnyAMJFIAxHuFyeO94c6Y5FaThuMyLEurlkMLi0EO854VWeFjMpSKQJEs37QVivOZzi9Ozn6+txFzm7lIlaV06a7iFBp6fhPRcU2T/DLc9x3fd2cuxJRhKxyqOONwZolNpG/yeDFJPnbfvhURaLgC/jLks/HBGO3UbxypMZcuAP2uC71jBCK641Dw/EYLwW0CacvFWVRojHXGtTJH2Js5sNnZm8ath3rhxJdnQHX0FU/WfNVSQqTzrcgemphMdLJP+ThpCMcNmDoIFeVkKi6CC0cdFXy2FIdKcOH/edFkGfBkjFMaF8dGMJNmbZ8ztLjWSx22Y5LuD0UQdGew4U2qLMBr3pHgon7xvmsOjKEESWaXTnUHxL6fHPfAcvh/yWHXWd/CXjIesH+0STxQPQnYlanu+hbbHmDiwnAAR+flACZFWjkXvb/ry+3YRWyZ3FxWobqsk0Z3M658+Ou/66gAccAQLlqTX3rsBvya+VkkLy43g6lmlHbSUBBW0kxHhozPB0AhQuvik3/+9EZKg7f91flI3jH56jv3RU8ydgtAn+/cb4Pq3LlpmPvE9gX0LQN3w4IzM+LhH324pnw5Za2etiJoR3FyfiODzs1puHBCv/gUyGo2q7yJUGWxkukEokl6smI8TwsTJlWsG6FqFqCWWl31hBdYYQM+Ei5H6SlJyhjLe0sl+05by/GaOWAosVqO435xqFIXtKYINlAc8MlaDrY4uhO0WLR2WhNNAqURlgOdcxBpF7SOA1TngcZUSJWiNZm0lCuSxkpNoFnE5w04189JGQawA7JkRs/LAP5FqZRqweT2qlQ0b/RY/NidbrG5rhr1yDd9zwGd54dB2NxQfmkfTC/doEYD37Ww0PCh/gprKddIXZXaTip0HC+SCZuA3bme+O3/47evbSTCsvjbvuN1r6mbyumZ25CdzwB++WL3AZNWnvvIv3+0tVX592aBabgeFkGkmopyq/cJ9McEmET76sK/+be/sfhS9M1x9M+AmD9yRqq5UMjbPSGWpFjqSFGZRMReRwA0IBNtZJozYJOegGoVAoGYxz02fd8lpDjM1gqO8lmaOVZFKBpY56843hfRHJ0PNVLh1G/7UY8GgbvhsyjibCCH12WluUDKQEMLBM0LGcwHWdxb6kwlGxnBZp4mv1NdPpxanEaOQRz6V6JOtFy5G7o3Kh7yvM6fOeNNHjjZ7HSTqgRTM7mokNWe4S9dbhNIunMffcXhDcP4snblyGz3lEc4/4Fj1YsO0G+72H2tz9qN//DR9ksBmlEPhHfBXGkvR2ETxnMNE1zGM7AgG8mVDx04sMYzb7desB3UW8ipMzP4iz/61lejgNuICs3aoDPToBXPgdRpf6//1UnNQ2k9Q4krJiXYnM986R8ho2QuycYsUljCJYVi2Zo0BphIJ09Cvh4gGXDtS+2JNNYHUYRVoDSOlD8Xp0lncnait5E+egtzhjNnF5tps3YfCorzzLahq9tS6DT3hBSpUIlUVcx7+Ufv2Pjk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",QV="data:image/png;base64,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r=!i&&n.widgetNode;r&&e.map.push(e.pos,e.pos+t,r),!i&&e.cm.display.input.needsContentAttribute&&(r||(r=e.content.appendChild(document.createElement("span"))),r.setAttribute("cm-marker",n.id)),r&&(e.cm.display.input.setUneditable(r),e.content.appendChild(r)),e.pos+=t,e.trailingSpace=!1}function bn(e,t,n){var i=e.markedSpans,r=e.text,s=0;if(i)for(var o,a,l,u,c,d,h,f=r.length,p=0,g=1,m="",v=0;;){if(v==p){l=u=c=a="",h=null,d=null,v=1/0;for(var A=[],x=void 0,y=0;y<i.length;++y){var b=i[y],w=b.marker;if("bookmark"==w.type&&b.from==p&&w.widgetNode)A.push(w);else if(b.from<=p&&(null==b.to||b.to>p||w.collapsed&&b.to==p&&b.from==p)){if(null!=b.to&&b.to!=p&&v>b.to&&(v=b.to,u=""),w.className&&(l+=" "+w.className),w.css&&(a=(a?a+";":"")+w.css),w.startStyle&&b.from==p&&(c+=" "+w.startStyle),w.endStyle&&b.to==v&&(x||(x=[])).push(w.endStyle,b.to),w.title&&((h||(h={})).title=w.title),w.attributes)for(var C in w.attributes)(h||(h={}))[C]=w.attributes[C];w.collapsed&&(!d||Qt(d.marker,w)<0)&&(d=b)}else 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t=e.delayedCallbacks,n=0;do{for(;n<t.length;n++)t[n].call(null);for(var i=0;i<e.ops.length;i++){var r=e.ops[i];if(r.cursorActivityHandlers)for(;r.cursorActivityCalled<r.cursorActivityHandlers.length;)r.cursorActivityHandlers[r.cursorActivityCalled++].call(null,r.cm)}}while(n<t.length)}function Sn(e,t){var n=e.ownsGroup;if(n)try{Tn(n)}finally{Mn=null,t(n)}}var Pn=null;function Nn(e,t){var n=ge(e,t);if(n.length){var i,r=Array.prototype.slice.call(arguments,2);Mn?i=Mn.delayedCallbacks:Pn?i=Pn:(i=Pn=[],setTimeout(Bn,0));for(var s=function(e){i.push((function(){return n[e].apply(null,r)}))},o=0;o<n.length;++o)s(o)}}function Bn(){var e=Pn;Pn=null;for(var t=0;t<e.length;++t)e[t]()}function Dn(e,t,n,i){for(var r=0;r<t.changes.length;r++){var s=t.changes[r];"text"==s?On(e,t):"gutter"==s?Rn(e,t,n,i):"class"==s?zn(e,t):"widget"==s&&kn(e,t,i)}t.changes=null}function In(e){return e.node==e.text&&(e.node=N("div",null,null,"position: 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zn(e,t){Ln(e,t),t.line.wrapClass?In(t).className=t.line.wrapClass:t.node!=t.text&&(t.node.className="");var n=t.textClass?t.textClass+" "+(t.line.textClass||""):t.line.textClass;t.text.className=n||""}function Rn(e,t,n,i){if(t.gutter&&(t.node.removeChild(t.gutter),t.gutter=null),t.gutterBackground&&(t.node.removeChild(t.gutterBackground),t.gutterBackground=null),t.line.gutterClass){var r=In(t);t.gutterBackground=N("div",null,"CodeMirror-gutter-background "+t.line.gutterClass,"left: "+(e.options.fixedGutter?i.fixedPos:-i.gutterTotalWidth)+"px; width: "+i.gutterTotalWidth+"px"),e.display.input.setUneditable(t.gutterBackground),r.insertBefore(t.gutterBackground,t.text)}var s=t.line.gutterMarkers;if(e.options.lineNumbers||s){var o=In(t),a=t.gutter=N("div",null,"CodeMirror-gutter-wrapper","left: "+(e.options.fixedGutter?i.fixedPos:-i.gutterTotalWidth)+"px");if(e.display.input.setUneditable(a),o.insertBefore(a,t.text),t.line.gutterClass&&(a.className+=" 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Un(e,t,n,i,r){if(t.widgets)for(var s=In(n),o=0,a=t.widgets;o<a.length;++o){var l=a[o],u=N("div",[l.node],"CodeMirror-linewidget"+(l.className?" 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n=Te(t);n!=e.wrapper;n=n.parentNode)if(!n||1==n.nodeType&&"true"==n.getAttribute("cm-ignore-events")||n.parentNode==e.sizer&&n!=e.mover)return!0}function Wn(e){return e.lineSpace.offsetTop}function Qn(e){return e.mover.offsetHeight-e.lineSpace.offsetHeight}function Zn(e){if(e.cachedPaddingH)return e.cachedPaddingH;var t=P(e.measure,N("pre","x","CodeMirror-line-like")),n=window.getComputedStyle?window.getComputedStyle(t):t.currentStyle,i={left:parseInt(n.paddingLeft),right:parseInt(n.paddingRight)};return isNaN(i.left)||isNaN(i.right)||(e.cachedPaddingH=i),i}function Yn(e){return U-e.display.nativeBarWidth}function Jn(e){return e.display.scroller.clientWidth-Yn(e)-e.display.barWidth}function Kn(e){return e.display.scroller.clientHeight-Yn(e)-e.display.barHeight}function qn(e,t,n){var i=e.options.lineWrapping,r=i&&Jn(e);if(!t.measure.heights||i&&t.measure.width!=r){var s=t.measure.heights=[];if(i){t.measure.width=r;for(var o=t.text.firstChild.getClientRects(),a=0;a<o.length-1;a++){var 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n=si;if("left"==t)for(var i=0;i<e.length&&(n=e[i]).left==n.right;i++);else for(var r=e.length-1;r>=0&&(n=e[r]).left==n.right;r--);return n}function li(e,t,n,i){var r,s=oi(t.map,n,i),l=s.node,u=s.start,c=s.end,d=s.collapse;if(3==l.nodeType){for(var h=0;h<4;h++){for(;u&&se(t.line.text.charAt(s.coverStart+u));)--u;for(;s.coverStart+c<s.coverEnd&&se(t.line.text.charAt(s.coverStart+c));)++c;if((r=o&&a<9&&0==u&&c==s.coverEnd-s.coverStart?l.parentNode.getBoundingClientRect():ai(E(l,u,c).getClientRects(),i)).left||r.right||0==u)break;c=u,u-=1,d="right"}o&&a<11&&(r=ui(e.display.measure,r))}else{var f;u>0&&(d=i="right"),r=e.options.lineWrapping&&(f=l.getClientRects()).length>1?f["right"==i?f.length-1:0]:l.getBoundingClientRect()}if(o&&a<9&&!u&&(!r||!r.left&&!r.right)){var p=l.parentNode.getClientRects()[0];r=p?{left:p.left,right:p.left+Bi(e.display),top:p.top,bottom:p.bottom}:si}for(var g=r.top-t.rect.top,m=r.bottom-t.rect.top,v=(g+m)/2,A=t.view.measure.heights,x=0;x<A.length-1&&!(v<A[x]);x++);var y=x?A[x-1]:0,b=A[x],w={left:("right"==d?r.right:r.left)-t.rect.left,right:("left"==d?r.left:r.right)-t.rect.left,top:y,bottom:b};return r.left||r.right||(w.bogus=!0),e.options.singleCursorHeightPerLine||(w.rtop=g,w.rbottom=m),w}function ui(e,t){if(!window.screen||null==screen.logicalXDPI||screen.logicalXDPI==screen.deviceXDPI||!ke(e))return t;var n=screen.logicalXDPI/screen.deviceXDPI,i=screen.logicalYDPI/screen.deviceYDPI;return{left:t.left*n,right:t.right*n,top:t.top*i,bottom:t.bottom*i}}function ci(e){if(e.measure&&(e.measure.cache={},e.measure.heights=null,e.rest))for(var t=0;t<e.rest.length;t++)e.measure.caches[t]={}}function di(e){e.display.externalMeasure=null,S(e.display.lineMeasure);for(var t=0;t<e.display.view.length;t++)ci(e.display.view[t])}function hi(e){di(e),e.display.cachedCharWidth=e.display.cachedTextHeight=e.display.cachedPaddingH=null,e.options.lineWrapping||(e.display.maxLineChanged=!0),e.display.lineNumChars=null}function fi(){return c&&m?-(document.body.getBoundingClientRect().left-parseInt(getComputedStyle(document.body).marginLeft)):window.pageXOffset||(document.documentElement||document.body).scrollLeft}function pi(){return c&&m?-(document.body.getBoundingClientRect().top-parseInt(getComputedStyle(document.body).marginTop)):window.pageYOffset||(document.documentElement||document.body).scrollTop}function gi(e){var t=0;if(e.widgets)for(var n=0;n<e.widgets.length;++n)e.widgets[n].above&&(t+=Gn(e.widgets[n]));return t}function mi(e,t,n,i,r){if(!r){var s=gi(t);n.top+=s,n.bottom+=s}if("line"==i)return n;i||(i="local");var o=on(t);if("local"==i?o+=Wn(e.display):o-=e.display.viewOffset,"page"==i||"window"==i){var a=e.display.lineSpace.getBoundingClientRect();o+=a.top+("window"==i?0:pi());var l=a.left+("window"==i?0:fi());n.left+=l,n.right+=l}return n.top+=o,n.bottom+=o,n}function vi(e,t,n){if("div"==n)return t;var i=t.left,r=t.top;if("page"==n)i-=fi(),r-=pi();else if("local"==n||!n){var s=e.display.sizer.getBoundingClientRect();i+=s.left,r+=s.top}var o=e.display.lineSpace.getBoundingClientRect();return{left:i-o.left,top:r-o.top}}function Ai(e,t,n,i,r){return i||(i=qe(e.doc,t.line)),mi(e,i,ei(e,i,t.ch,r),n)}function xi(e,t,n,i,r,s){function o(t,o){var a=ii(e,r,t,o?"right":"left",s);return o?a.left=a.right:a.right=a.left,mi(e,i,a,n)}i=i||qe(e.doc,t.line),r||(r=ni(e,i));var a=he(i,e.doc.direction),l=t.ch,u=t.sticky;if(l>=i.text.length?(l=i.text.length,u="before"):l<=0&&(l=0,u="after"),!a)return o("before"==u?l-1:l,"before"==u);function c(e,t,n){return o(n?e-1:e,1==a[t].level!=n)}var d=ce(a,l,u),h=ue,f=c(l,d,"before"==u);return null!=h&&(f.other=c(l,h,"before"!=u)),f}function yi(e,t){var n=0;t=ht(e.doc,t),e.options.lineWrapping||(n=Bi(e.display)*t.ch);var 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d=(e.options.lineWrapping?Pi:Si)(e,t,n,s,c,i,r);a=(u=1!=d.level)?d.from:d.to-1,l=u?d.to:d.from-1}var h,f,p=null,g=null,m=ae((function(t){var n=ii(e,s,t);return n.top+=o,n.bottom+=o,!!Ei(n,i,r,!1)&&(n.top<=r&&n.left<=i&&(p=t,g=n),!0)}),a,l),v=!1;if(g){var A=i-g.left<g.right-i,x=A==u;m=p+(x?0:1),f=x?"after":"before",h=A?g.left:g.right}else{u||m!=l&&m!=a||m++,f=0==m?"after":m==t.text.length?"before":ii(e,s,m-(u?1:0)).bottom+o<=r==u?"after":"before";var y=xi(e,st(n,m,f),"line",t,s);h=y.left,v=r<y.top?-1:r>=y.bottom?1:0}return bi(n,m=oe(t.text,m,1),f,v,i-h)}function Si(e,t,n,i,r,s,o){var a=ae((function(a){var l=r[a],u=1!=l.level;return Ei(xi(e,st(n,u?l.to:l.from,u?"before":"after"),"line",t,i),s,o,!0)}),0,r.length-1),l=r[a];if(a>0){var u=1!=l.level,c=xi(e,st(n,u?l.from:l.to,u?"after":"before"),"line",t,i);Ei(c,s,o,!0)&&c.top>o&&(l=r[a-1])}return l}function Pi(e,t,n,i,r,s,o){var a=Ci(e,t,i,o),l=a.begin,u=a.end;/\s/.test(t.text.charAt(u-1))&&u--;for(var c=null,d=null,h=0;h<r.length;h++){var f=r[h];if(!(f.from>=u||f.to<=l)){var p=ii(e,i,1!=f.level?Math.min(u,f.to)-1:Math.max(l,f.from)).right,g=p<s?s-p+1e9:p-s;(!c||d>g)&&(c=f,d=g)}}return c||(c=r[r.length-1]),c.from<l&&(c={from:l,to:c.to,level:c.level}),c.to>u&&(c={from:c.from,to:u,level:c.level}),c}function Ni(e){if(null!=e.cachedTextHeight)return e.cachedTextHeight;if(null==ri){ri=N("pre",null,"CodeMirror-line-like");for(var t=0;t<49;++t)ri.appendChild(document.createTextNode("x")),ri.appendChild(N("br"));ri.appendChild(document.createTextNode("x"))}P(e.measure,ri);var n=ri.offsetHeight/50;return n>3&&(e.cachedTextHeight=n),S(e.measure),n||1}function Bi(e){if(null!=e.cachedCharWidth)return e.cachedCharWidth;var t=N("span","xxxxxxxxxx"),n=N("pre",[t],"CodeMirror-line-like");P(e.measure,n);var i=t.getBoundingClientRect(),r=(i.right-i.left)/10;return r>2&&(e.cachedCharWidth=r),r||10}function Di(e){for(var t=e.display,n={},i={},r=t.gutters.clientLeft,s=t.gutters.firstChild,o=0;s;s=s.nextSibling,++o){var a=e.display.gutterSpecs[o].className;n[a]=s.offsetLeft+s.clientLeft+r,i[a]=s.clientWidth}return{fixedPos:Ii(t),gutterTotalWidth:t.gutters.offsetWidth,gutterLeft:n,gutterWidth:i,wrapperWidth:t.wrapper.clientWidth}}function Ii(e){return e.scroller.getBoundingClientRect().left-e.sizer.getBoundingClientRect().left}function Li(e){var t=Ni(e.display),n=e.options.lineWrapping,i=n&&Math.max(5,e.display.scroller.clientWidth/Bi(e.display)-3);return function(r){if(rn(e.doc,r))return 0;var s=0;if(r.widgets)for(var o=0;o<r.widgets.length;o++)r.widgets[o].height&&(s+=r.widgets[o].height);return n?s+(Math.ceil(r.text.length/i)||1)*t:s+t}}function ji(e){var t=e.doc,n=Li(e);t.iter((function(e){var t=n(e);t!=e.height&&et(e,t)}))}function Oi(e,t,n,i){var r=e.display;if(!n&&"true"==Te(t).getAttribute("cm-not-content"))return null;var s,o,a=r.lineSpace.getBoundingClientRect();try{s=t.clientX-a.left,o=t.clientY-a.top}catch(e){return null}var l,u=wi(e,s,o);if(i&&u.xRel>0&&(l=qe(e.doc,u.line).text).length==u.ch){var c=k(l,l.length,e.options.tabSize)-l.length;u=st(u.line,Math.max(0,Math.round((s-Zn(e.display).left)/Bi(e.display))-c))}return u}function zi(e,t){if(t>=e.display.viewTo)return null;if((t-=e.display.viewFrom)<0)return null;for(var n=e.display.view,i=0;i<n.length;i++)if((t-=n[i].size)<0)return i}function Ri(e,t,n,i){null==t&&(t=e.doc.first),null==n&&(n=e.doc.first+e.doc.size),i||(i=0);var r=e.display;if(i&&n<r.viewTo&&(null==r.updateLineNumbers||r.updateLineNumbers>t)&&(r.updateLineNumbers=t),e.curOp.viewChanged=!0,t>=r.viewTo)Bt&&tn(e.doc,t)<r.viewTo&&Fi(e);else if(n<=r.viewFrom)Bt&&nn(e.doc,n+i)>r.viewFrom?Fi(e):(r.viewFrom+=i,r.viewTo+=i);else if(t<=r.viewFrom&&n>=r.viewTo)Fi(e);else if(t<=r.viewFrom){var s=Hi(e,n,n+i,1);s?(r.view=r.view.slice(s.index),r.viewFrom=s.lineN,r.viewTo+=i):Fi(e)}else if(n>=r.viewTo){var o=Hi(e,t,t,-1);o?(r.view=r.view.slice(0,o.index),r.viewTo=o.lineN):Fi(e)}else{var a=Hi(e,t,t,-1),l=Hi(e,n,n+i,1);a&&l?(r.view=r.view.slice(0,a.index).concat(Cn(e,a.lineN,l.lineN)).concat(r.view.slice(l.index)),r.viewTo+=i):Fi(e)}var u=r.externalMeasured;u&&(n<u.lineN?u.lineN+=i:t<u.lineN+u.size&&(r.externalMeasured=null))}function ki(e,t,n){e.curOp.viewChanged=!0;var i=e.display,r=e.display.externalMeasured;if(r&&t>=r.lineN&&t<r.lineN+r.size&&(i.externalMeasured=null),!(t<i.viewFrom||t>=i.viewTo)){var s=i.view[zi(e,t)];if(null!=s.node){var o=s.changes||(s.changes=[]);-1==H(o,n)&&o.push(n)}}}function Fi(e){e.display.viewFrom=e.display.viewTo=e.doc.first,e.display.view=[],e.display.viewOffset=0}function Hi(e,t,n,i){var r,s=zi(e,t),o=e.display.view;if(!Bt||n==e.doc.first+e.doc.size)return{index:s,lineN:n};for(var a=e.display.viewFrom,l=0;l<s;l++)a+=o[l].size;if(a!=t){if(i>0){if(s==o.length-1)return null;r=a+o[s].size-t,s++}else r=a-t;t+=r,n+=r}for(;tn(e.doc,n)!=n;){if(s==(i<0?0:o.length-1))return null;n+=i*o[s-(i<0?1:0)].size,s+=i}return{index:s,lineN:n}}function Ui(e,t,n){var i=e.display;0==i.view.length||t>=i.viewTo||n<=i.viewFrom?(i.view=Cn(e,t,n),i.viewFrom=t):(i.viewFrom>t?i.view=Cn(e,t,i.viewFrom).concat(i.view):i.viewFrom<t&&(i.view=i.view.slice(zi(e,t))),i.viewFrom=t,i.viewTo<n?i.view=i.view.concat(Cn(e,i.viewTo,n)):i.viewTo>n&&(i.view=i.view.slice(0,zi(e,n)))),i.viewTo=n}function Xi(e){for(var t=e.display.view,n=0,i=0;i<t.length;i++){var r=t[i];r.hidden||r.node&&!r.changes||++n}return n}function Gi(e){e.display.input.showSelection(e.display.input.prepareSelection())}function Vi(e,t){void 0===t&&(t=!0);for(var n=e.doc,i={},r=i.cursors=document.createDocumentFragment(),s=i.selection=document.createDocumentFragment(),o=0;o<n.sel.ranges.length;o++)if(t||o!=n.sel.primIndex){var a=n.sel.ranges[o];if(!(a.from().line>=e.display.viewTo||a.to().line<e.display.viewFrom)){var l=a.empty();(l||e.options.showCursorWhenSelecting)&&Wi(e,a.head,r),l||Zi(e,a,s)}}return i}function Wi(e,t,n){var i=xi(e,t,"div",null,null,!e.options.singleCursorHeightPerLine),r=n.appendChild(N("div"," ","CodeMirror-cursor"));if(r.style.left=i.left+"px",r.style.top=i.top+"px",r.style.height=Math.max(0,i.bottom-i.top)*e.options.cursorHeight+"px",i.other){var s=n.appendChild(N("div"," ","CodeMirror-cursor CodeMirror-secondarycursor"));s.style.display="",s.style.left=i.other.left+"px",s.style.top=i.other.top+"px",s.style.height=.85*(i.other.bottom-i.other.top)+"px"}}function Qi(e,t){return e.top-t.top||e.left-t.left}function Zi(e,t,n){var i=e.display,r=e.doc,s=document.createDocumentFragment(),o=Zn(e.display),a=o.left,l=Math.max(i.sizerWidth,Jn(e)-i.sizer.offsetLeft)-o.right,u="ltr"==r.direction;function c(e,t,n,i){t<0&&(t=0),t=Math.round(t),i=Math.round(i),s.appendChild(N("div",null,"CodeMirror-selected","position: absolute; left: "+e+"px;\n                             top: "+t+"px; width: "+(null==n?l-e:n)+"px;\n                             height: "+(i-t)+"px"))}function d(t,n,i){var s,o,d=qe(r,t),h=d.text.length;function f(n,i){return Ai(e,st(t,n),"div",d,i)}function p(t,n,i){var r=Mi(e,d,null,t),s="ltr"==n==("after"==i)?"left":"right";return f("after"==i?r.begin:r.end-(/\s/.test(d.text.charAt(r.end-1))?2:1),s)[s]}var g=he(d,r.direction);return le(g,n||0,null==i?h:i,(function(e,t,r,d){var m="ltr"==r,v=f(e,m?"left":"right"),A=f(t-1,m?"right":"left"),x=null==n&&0==e,y=null==i&&t==h,b=0==d,w=!g||d==g.length-1;if(A.top-v.top<=3){var C=(u?y:x)&&w,M=(u?x:y)&&b?a:(m?v:A).left,E=C?l:(m?A:v).right;c(M,v.top,E-M,v.bottom)}else{var T,S,P,N;m?(T=u&&x&&b?a:v.left,S=u?l:p(e,r,"before"),P=u?a:p(t,r,"after"),N=u&&y&&w?l:A.right):(T=u?p(e,r,"before"):a,S=!u&&x&&b?l:v.right,P=!u&&y&&w?a:A.left,N=u?p(t,r,"after"):l),c(T,v.top,S-T,v.bottom),v.bottom<A.top&&c(a,v.bottom,null,A.top),c(P,A.top,N-P,A.bottom)}(!s||Qi(v,s)<0)&&(s=v),Qi(A,s)<0&&(s=A),(!o||Qi(v,o)<0)&&(o=v),Qi(A,o)<0&&(o=A)})),{start:s,end:o}}var h=t.from(),f=t.to();if(h.line==f.line)d(h.line,h.ch,f.ch);else{var p=qe(r,h.line),g=qe(r,f.line),m=_t(p)==_t(g),v=d(h.line,h.ch,m?p.text.length+1:null).end,A=d(f.line,m?0:null,f.ch).start;m&&(v.top<A.top-2?(c(v.right,v.top,null,v.bottom),c(a,A.top,A.left,A.bottom)):c(v.right,v.top,A.left-v.right,v.bottom)),v.bottom<A.top&&c(a,v.bottom,null,A.top)}n.appendChild(s)}function Yi(e){if(e.state.focused){var t=e.display;clearInterval(t.blinker);var n=!0;t.cursorDiv.style.visibility="",e.options.cursorBlinkRate>0?t.blinker=setInterval((function(){e.hasFocus()||_i(e),t.cursorDiv.style.visibility=(n=!n)?"":"hidden"}),e.options.cursorBlinkRate):e.options.cursorBlinkRate<0&&(t.cursorDiv.style.visibility="hidden")}}function Ji(e){e.state.focused||(e.display.input.focus(),qi(e))}function Ki(e){e.state.delayingBlurEvent=!0,setTimeout((function(){e.state.delayingBlurEvent&&(e.state.delayingBlurEvent=!1,_i(e))}),100)}function qi(e,t){e.state.delayingBlurEvent&&(e.state.delayingBlurEvent=!1),"nocursor"!=e.options.readOnly&&(e.state.focused||(ve(e,"focus",e,t),e.state.focused=!0,L(e.display.wrapper,"CodeMirror-focused"),e.curOp||e.display.selForContextMenu==e.doc.sel||(e.display.input.reset(),l&&setTimeout((function(){return e.display.input.reset(!0)}),20)),e.display.input.receivedFocus()),Yi(e))}function _i(e,t){e.state.delayingBlurEvent||(e.state.focused&&(ve(e,"blur",e,t),e.state.focused=!1,T(e.display.wrapper,"CodeMirror-focused")),clearInterval(e.display.blinker),setTimeout((function(){e.state.focused||(e.display.shift=!1)}),150))}function $i(e){for(var t=e.display,n=t.lineDiv.offsetTop,i=0;i<t.view.length;i++){var r=t.view[i],s=e.options.lineWrapping,l=void 0,u=0;if(!r.hidden){if(o&&a<8){var c=r.node.offsetTop+r.node.offsetHeight;l=c-n,n=c}else{var d=r.node.getBoundingClientRect();l=d.bottom-d.top,!s&&r.text.firstChild&&(u=r.text.firstChild.getBoundingClientRect().right-d.left-1)}var h=r.line.height-l;if((h>.005||h<-.005)&&(et(r.line,l),er(r.line),r.rest))for(var f=0;f<r.rest.length;f++)er(r.rest[f]);if(u>e.display.sizerWidth){var p=Math.ceil(u/Bi(e.display));p>e.display.maxLineLength&&(e.display.maxLineLength=p,e.display.maxLine=r.line,e.display.maxLineChanged=!0)}}}}function er(e){if(e.widgets)for(var t=0;t<e.widgets.length;++t){var n=e.widgets[t],i=n.node.parentNode;i&&(n.height=i.offsetHeight)}}function tr(e,t,n){var i=n&&null!=n.top?Math.max(0,n.top):e.scroller.scrollTop;i=Math.floor(i-Wn(e));var r=n&&null!=n.bottom?n.bottom:i+e.wrapper.clientHeight,s=nt(t,i),o=nt(t,r);if(n&&n.ensure){var a=n.ensure.from.line,l=n.ensure.to.line;a<s?(s=a,o=nt(t,on(qe(t,a))+e.wrapper.clientHeight)):Math.min(l,t.lastLine())>=o&&(s=nt(t,on(qe(t,l))-e.wrapper.clientHeight),o=l)}return{from:s,to:Math.max(o,s+1)}}function nr(e,t){if(!Ae(e,"scrollCursorIntoView")){var n=e.display,i=n.sizer.getBoundingClientRect(),r=null;if(t.top+i.top<0?r=!0:t.bottom+i.top>(window.innerHeight||document.documentElement.clientHeight)&&(r=!1),null!=r&&!p){var s=N("div","​",null,"position: absolute;\n                         top: "+(t.top-n.viewOffset-Wn(e.display))+"px;\n                         height: "+(t.bottom-t.top+Yn(e)+n.barHeight)+"px;\n                         left: "+t.left+"px; width: "+Math.max(2,t.right-t.left)+"px;");e.display.lineSpace.appendChild(s),s.scrollIntoView(r),e.display.lineSpace.removeChild(s)}}}function ir(e,t,n,i){var r;null==i&&(i=0),e.options.lineWrapping||t!=n||(n="before"==(t=t.ch?st(t.line,"before"==t.sticky?t.ch-1:t.ch,"after"):t).sticky?st(t.line,t.ch+1,"before"):t);for(var s=0;s<5;s++){var o=!1,a=xi(e,t),l=n&&n!=t?xi(e,n):a,u=sr(e,r={left:Math.min(a.left,l.left),top:Math.min(a.top,l.top)-i,right:Math.max(a.left,l.left),bottom:Math.max(a.bottom,l.bottom)+i}),c=e.doc.scrollTop,d=e.doc.scrollLeft;if(null!=u.scrollTop&&(hr(e,u.scrollTop),Math.abs(e.doc.scrollTop-c)>1&&(o=!0)),null!=u.scrollLeft&&(pr(e,u.scrollLeft),Math.abs(e.doc.scrollLeft-d)>1&&(o=!0)),!o)break}return r}function rr(e,t){var n=sr(e,t);null!=n.scrollTop&&hr(e,n.scrollTop),null!=n.scrollLeft&&pr(e,n.scrollLeft)}function sr(e,t){var n=e.display,i=Ni(e.display);t.top<0&&(t.top=0);var r=e.curOp&&null!=e.curOp.scrollTop?e.curOp.scrollTop:n.scroller.scrollTop,s=Kn(e),o={};t.bottom-t.top>s&&(t.bottom=t.top+s);var a=e.doc.height+Qn(n),l=t.top<i,u=t.bottom>a-i;if(t.top<r)o.scrollTop=l?0:t.top;else if(t.bottom>r+s){var c=Math.min(t.top,(u?a:t.bottom)-s);c!=r&&(o.scrollTop=c)}var d=e.options.fixedGutter?0:n.gutters.offsetWidth,h=e.curOp&&null!=e.curOp.scrollLeft?e.curOp.scrollLeft:n.scroller.scrollLeft-d,f=Jn(e)-n.gutters.offsetWidth,p=t.right-t.left>f;return p&&(t.right=t.left+f),t.left<10?o.scrollLeft=0:t.left<h?o.scrollLeft=Math.max(0,t.left+d-(p?0:10)):t.right>f+h-3&&(o.scrollLeft=t.right+(p?0:10)-f),o}function or(e,t){null!=t&&(cr(e),e.curOp.scrollTop=(null==e.curOp.scrollTop?e.doc.scrollTop:e.curOp.scrollTop)+t)}function ar(e){cr(e);var t=e.getCursor();e.curOp.scrollToPos={from:t,to:t,margin:e.options.cursorScrollMargin}}function lr(e,t,n){null==t&&null==n||cr(e),null!=t&&(e.curOp.scrollLeft=t),null!=n&&(e.curOp.scrollTop=n)}function ur(e,t){cr(e),e.curOp.scrollToPos=t}function cr(e){var t=e.curOp.scrollToPos;t&&(e.curOp.scrollToPos=null,dr(e,yi(e,t.from),yi(e,t.to),t.margin))}function dr(e,t,n,i){var r=sr(e,{left:Math.min(t.left,n.left),top:Math.min(t.top,n.top)-i,right:Math.max(t.right,n.right),bottom:Math.max(t.bottom,n.bottom)+i});lr(e,r.scrollLeft,r.scrollTop)}function hr(e,t){Math.abs(e.doc.scrollTop-t)<2||(n||Gr(e,{top:t}),fr(e,t,!0),n&&Gr(e),Or(e,100))}function fr(e,t,n){t=Math.max(0,Math.min(e.display.scroller.scrollHeight-e.display.scroller.clientHeight,t)),(e.display.scroller.scrollTop!=t||n)&&(e.doc.scrollTop=t,e.display.scrollbars.setScrollTop(t),e.display.scroller.scrollTop!=t&&(e.display.scroller.scrollTop=t))}function pr(e,t,n,i){t=Math.max(0,Math.min(t,e.display.scroller.scrollWidth-e.display.scroller.clientWidth)),(n?t==e.doc.scrollLeft:Math.abs(e.doc.scrollLeft-t)<2)&&!i||(e.doc.scrollLeft=t,Zr(e),e.display.scroller.scrollLeft!=t&&(e.display.scroller.scrollLeft=t),e.display.scrollbars.setScrollLeft(t))}function gr(e){var t=e.display,n=t.gutters.offsetWidth,i=Math.round(e.doc.height+Qn(e.display));return{clientHeight:t.scroller.clientHeight,viewHeight:t.wrapper.clientHeight,scrollWidth:t.scroller.scrollWidth,clientWidth:t.scroller.clientWidth,viewWidth:t.wrapper.clientWidth,barLeft:e.options.fixedGutter?n:0,docHeight:i,scrollHeight:i+Yn(e)+t.barHeight,nativeBarWidth:t.nativeBarWidth,gutterWidth:n}}var mr=function(e,t,n){this.cm=n;var i=this.vert=N("div",[N("div",null,null,"min-width: 1px")],"CodeMirror-vscrollbar"),r=this.horiz=N("div",[N("div",null,null,"height: 100%; min-height: 1px")],"CodeMirror-hscrollbar");i.tabIndex=r.tabIndex=-1,e(i),e(r),pe(i,"scroll",(function(){i.clientHeight&&t(i.scrollTop,"vertical")})),pe(r,"scroll",(function(){r.clientWidth&&t(r.scrollLeft,"horizontal")})),this.checkedZeroWidth=!1,o&&a<8&&(this.horiz.style.minHeight=this.vert.style.minWidth="18px")};mr.prototype.update=function(e){var t=e.scrollWidth>e.clientWidth+1,n=e.scrollHeight>e.clientHeight+1,i=e.nativeBarWidth;if(n){this.vert.style.display="block",this.vert.style.bottom=t?i+"px":"0";var r=e.viewHeight-(t?i:0);this.vert.firstChild.style.height=Math.max(0,e.scrollHeight-e.clientHeight+r)+"px"}else this.vert.style.display="",this.vert.firstChild.style.height="0";if(t){this.horiz.style.display="block",this.horiz.style.right=n?i+"px":"0",this.horiz.style.left=e.barLeft+"px";var s=e.viewWidth-e.barLeft-(n?i:0);this.horiz.firstChild.style.width=Math.max(0,e.scrollWidth-e.clientWidth+s)+"px"}else this.horiz.style.display="",this.horiz.firstChild.style.width="0";return!this.checkedZeroWidth&&e.clientHeight>0&&(0==i&&this.zeroWidthHack(),this.checkedZeroWidth=!0),{right:n?i:0,bottom:t?i:0}},mr.prototype.setScrollLeft=function(e){this.horiz.scrollLeft!=e&&(this.horiz.scrollLeft=e),this.disableHoriz&&this.enableZeroWidthBar(this.horiz,this.disableHoriz,"horiz")},mr.prototype.setScrollTop=function(e){this.vert.scrollTop!=e&&(this.vert.scrollTop=e),this.disableVert&&this.enableZeroWidthBar(this.vert,this.disableVert,"vert")},mr.prototype.zeroWidthHack=function(){var e=A&&!f?"12px":"18px";this.horiz.style.height=this.vert.style.width=e,this.horiz.style.pointerEvents=this.vert.style.pointerEvents="none",this.disableHoriz=new F,this.disableVert=new F},mr.prototype.enableZeroWidthBar=function(e,t,n){function i(){var r=e.getBoundingClientRect();("vert"==n?document.elementFromPoint(r.right-1,(r.top+r.bottom)/2):document.elementFromPoint((r.right+r.left)/2,r.bottom-1))!=e?e.style.pointerEvents="none":t.set(1e3,i)}e.style.pointerEvents="auto",t.set(1e3,i)},mr.prototype.clear=function(){var e=this.horiz.parentNode;e.removeChild(this.horiz),e.removeChild(this.vert)};var vr=function(){};function Ar(e,t){t||(t=gr(e));var n=e.display.barWidth,i=e.display.barHeight;xr(e,t);for(var r=0;r<4&&n!=e.display.barWidth||i!=e.display.barHeight;r++)n!=e.display.barWidth&&e.options.lineWrapping&&$i(e),xr(e,gr(e)),n=e.display.barWidth,i=e.display.barHeight}function xr(e,t){var n=e.display,i=n.scrollbars.update(t);n.sizer.style.paddingRight=(n.barWidth=i.right)+"px",n.sizer.style.paddingBottom=(n.barHeight=i.bottom)+"px",n.heightForcer.style.borderBottom=i.bottom+"px solid transparent",i.right&&i.bottom?(n.scrollbarFiller.style.display="block",n.scrollbarFiller.style.height=i.bottom+"px",n.scrollbarFiller.style.width=i.right+"px"):n.scrollbarFiller.style.display="",i.bottom&&e.options.coverGutterNextToScrollbar&&e.options.fixedGutter?(n.gutterFiller.style.display="block",n.gutterFiller.style.height=i.bottom+"px",n.gutterFiller.style.width=t.gutterWidth+"px"):n.gutterFiller.style.display=""}vr.prototype.update=function(){return{bottom:0,right:0}},vr.prototype.setScrollLeft=function(){},vr.prototype.setScrollTop=function(){},vr.prototype.clear=function(){};var yr={native:mr,null:vr};function br(e){e.display.scrollbars&&(e.display.scrollbars.clear(),e.display.scrollbars.addClass&&T(e.display.wrapper,e.display.scrollbars.addClass)),e.display.scrollbars=new yr[e.options.scrollbarStyle]((function(t){e.display.wrapper.insertBefore(t,e.display.scrollbarFiller),pe(t,"mousedown",(function(){e.state.focused&&setTimeout((function(){return e.display.input.focus()}),0)})),t.setAttribute("cm-not-content","true")}),(function(t,n){"horizontal"==n?pr(e,t):hr(e,t)}),e),e.display.scrollbars.addClass&&L(e.display.wrapper,e.display.scrollbars.addClass)}var wr=0;function Cr(e){e.curOp={cm:e,viewChanged:!1,startHeight:e.doc.height,forceUpdate:!1,updateInput:0,typing:!1,changeObjs:null,cursorActivityHandlers:null,cursorActivityCalled:0,selectionChanged:!1,updateMaxLine:!1,scrollLeft:null,scrollTop:null,scrollToPos:null,focus:!1,id:++wr},En(e.curOp)}function Mr(e){var t=e.curOp;t&&Sn(t,(function(e){for(var t=0;t<e.ops.length;t++)e.ops[t].cm.curOp=null;Er(e)}))}function Er(e){for(var t=e.ops,n=0;n<t.length;n++)Tr(t[n]);for(var i=0;i<t.length;i++)Sr(t[i]);for(var r=0;r<t.length;r++)Pr(t[r]);for(var s=0;s<t.length;s++)Nr(t[s]);for(var o=0;o<t.length;o++)Br(t[o])}function Tr(e){var t=e.cm,n=t.display;kr(t),e.updateMaxLine&&ln(t),e.mustUpdate=e.viewChanged||e.forceUpdate||null!=e.scrollTop||e.scrollToPos&&(e.scrollToPos.from.line<n.viewFrom||e.scrollToPos.to.line>=n.viewTo)||n.maxLineChanged&&t.options.lineWrapping,e.update=e.mustUpdate&&new Rr(t,e.mustUpdate&&{top:e.scrollTop,ensure:e.scrollToPos},e.forceUpdate)}function Sr(e){e.updatedDisplay=e.mustUpdate&&Ur(e.cm,e.update)}function Pr(e){var t=e.cm,n=t.display;e.updatedDisplay&&$i(t),e.barMeasure=gr(t),n.maxLineChanged&&!t.options.lineWrapping&&(e.adjustWidthTo=ei(t,n.maxLine,n.maxLine.text.length).left+3,t.display.sizerWidth=e.adjustWidthTo,e.barMeasure.scrollWidth=Math.max(n.scroller.clientWidth,n.sizer.offsetLeft+e.adjustWidthTo+Yn(t)+t.display.barWidth),e.maxScrollLeft=Math.max(0,n.sizer.offsetLeft+e.adjustWidthTo-Jn(t))),(e.updatedDisplay||e.selectionChanged)&&(e.preparedSelection=n.input.prepareSelection())}function Nr(e){var t=e.cm;null!=e.adjustWidthTo&&(t.display.sizer.style.minWidth=e.adjustWidthTo+"px",e.maxScrollLeft<t.doc.scrollLeft&&pr(t,Math.min(t.display.scroller.scrollLeft,e.maxScrollLeft),!0),t.display.maxLineChanged=!1);var n=e.focus&&e.focus==I();e.preparedSelection&&t.display.input.showSelection(e.preparedSelection,n),(e.updatedDisplay||e.startHeight!=t.doc.height)&&Ar(t,e.barMeasure),e.updatedDisplay&&Qr(t,e.barMeasure),e.selectionChanged&&Yi(t),t.state.focused&&e.updateInput&&t.display.input.reset(e.typing),n&&Ji(e.cm)}function Br(e){var t=e.cm,n=t.display,i=t.doc;e.updatedDisplay&&Xr(t,e.update),null==n.wheelStartX||null==e.scrollTop&&null==e.scrollLeft&&!e.scrollToPos||(n.wheelStartX=n.wheelStartY=null),null!=e.scrollTop&&fr(t,e.scrollTop,e.forceScroll),null!=e.scrollLeft&&pr(t,e.scrollLeft,!0,!0),e.scrollToPos&&nr(t,ir(t,ht(i,e.scrollToPos.from),ht(i,e.scrollToPos.to),e.scrollToPos.margin));var r=e.maybeHiddenMarkers,s=e.maybeUnhiddenMarkers;if(r)for(var o=0;o<r.length;++o)r[o].lines.length||ve(r[o],"hide");if(s)for(var a=0;a<s.length;++a)s[a].lines.length&&ve(s[a],"unhide");n.wrapper.offsetHeight&&(i.scrollTop=t.display.scroller.scrollTop),e.changeObjs&&ve(t,"changes",t,e.changeObjs),e.update&&e.update.finish()}function Dr(e,t){if(e.curOp)return t();Cr(e);try{return t()}finally{Mr(e)}}function Ir(e,t){return function(){if(e.curOp)return t.apply(e,arguments);Cr(e);try{return t.apply(e,arguments)}finally{Mr(e)}}}function Lr(e){return function(){if(this.curOp)return e.apply(this,arguments);Cr(this);try{return e.apply(this,arguments)}finally{Mr(this)}}}function jr(e){return function(){var t=this.cm;if(!t||t.curOp)return e.apply(this,arguments);Cr(t);try{return e.apply(this,arguments)}finally{Mr(t)}}}function Or(e,t){e.doc.highlightFrontier<e.display.viewTo&&e.state.highlight.set(t,z(zr,e))}function zr(e){var t=e.doc;if(!(t.highlightFrontier>=e.display.viewTo)){var n=+new Date+e.options.workTime,i=xt(e,t.highlightFrontier),r=[];t.iter(i.line,Math.min(t.first+t.size,e.display.viewTo+500),(function(s){if(i.line>=e.display.viewFrom){var o=s.styles,a=s.text.length>e.options.maxHighlightLength?Ze(t.mode,i.state):null,l=vt(e,s,i,!0);a&&(i.state=a),s.styles=l.styles;var u=s.styleClasses,c=l.classes;c?s.styleClasses=c:u&&(s.styleClasses=null);for(var d=!o||o.length!=s.styles.length||u!=c&&(!u||!c||u.bgClass!=c.bgClass||u.textClass!=c.textClass),h=0;!d&&h<o.length;++h)d=o[h]!=s.styles[h];d&&r.push(i.line),s.stateAfter=i.save(),i.nextLine()}else s.text.length<=e.options.maxHighlightLength&&yt(e,s.text,i),s.stateAfter=i.line%5==0?i.save():null,i.nextLine();if(+new Date>n)return Or(e,e.options.workDelay),!0})),t.highlightFrontier=i.line,t.modeFrontier=Math.max(t.modeFrontier,i.line),r.length&&Dr(e,(function(){for(var t=0;t<r.length;t++)ki(e,r[t],"text")}))}}var Rr=function(e,t,n){var i=e.display;this.viewport=t,this.visible=tr(i,e.doc,t),this.editorIsHidden=!i.wrapper.offsetWidth,this.wrapperHeight=i.wrapper.clientHeight,this.wrapperWidth=i.wrapper.clientWidth,this.oldDisplayWidth=Jn(e),this.force=n,this.dims=Di(e),this.events=[]};function kr(e){var t=e.display;!t.scrollbarsClipped&&t.scroller.offsetWidth&&(t.nativeBarWidth=t.scroller.offsetWidth-t.scroller.clientWidth,t.heightForcer.style.height=Yn(e)+"px",t.sizer.style.marginBottom=-t.nativeBarWidth+"px",t.sizer.style.borderRightWidth=Yn(e)+"px",t.scrollbarsClipped=!0)}function Fr(e){if(e.hasFocus())return null;var t=I();if(!t||!D(e.display.lineDiv,t))return null;var n={activeElt:t};if(window.getSelection){var i=window.getSelection();i.anchorNode&&i.extend&&D(e.display.lineDiv,i.anchorNode)&&(n.anchorNode=i.anchorNode,n.anchorOffset=i.anchorOffset,n.focusNode=i.focusNode,n.focusOffset=i.focusOffset)}return n}function Hr(e){if(e&&e.activeElt&&e.activeElt!=I()&&(e.activeElt.focus(),!/^(INPUT|TEXTAREA)$/.test(e.activeElt.nodeName)&&e.anchorNode&&D(document.body,e.anchorNode)&&D(document.body,e.focusNode))){var t=window.getSelection(),n=document.createRange();n.setEnd(e.anchorNode,e.anchorOffset),n.collapse(!1),t.removeAllRanges(),t.addRange(n),t.extend(e.focusNode,e.focusOffset)}}function Ur(e,t){var n=e.display,i=e.doc;if(t.editorIsHidden)return Fi(e),!1;if(!t.force&&t.visible.from>=n.viewFrom&&t.visible.to<=n.viewTo&&(null==n.updateLineNumbers||n.updateLineNumbers>=n.viewTo)&&n.renderedView==n.view&&0==Xi(e))return!1;Yr(e)&&(Fi(e),t.dims=Di(e));var r=i.first+i.size,s=Math.max(t.visible.from-e.options.viewportMargin,i.first),o=Math.min(r,t.visible.to+e.options.viewportMargin);n.viewFrom<s&&s-n.viewFrom<20&&(s=Math.max(i.first,n.viewFrom)),n.viewTo>o&&n.viewTo-o<20&&(o=Math.min(r,n.viewTo)),Bt&&(s=tn(e.doc,s),o=nn(e.doc,o));var a=s!=n.viewFrom||o!=n.viewTo||n.lastWrapHeight!=t.wrapperHeight||n.lastWrapWidth!=t.wrapperWidth;Ui(e,s,o),n.viewOffset=on(qe(e.doc,n.viewFrom)),e.display.mover.style.top=n.viewOffset+"px";var l=Xi(e);if(!a&&0==l&&!t.force&&n.renderedView==n.view&&(null==n.updateLineNumbers||n.updateLineNumbers>=n.viewTo))return!1;var u=Fr(e);return l>4&&(n.lineDiv.style.display="none"),Vr(e,n.updateLineNumbers,t.dims),l>4&&(n.lineDiv.style.display=""),n.renderedView=n.view,Hr(u),S(n.cursorDiv),S(n.selectionDiv),n.gutters.style.height=n.sizer.style.minHeight=0,a&&(n.lastWrapHeight=t.wrapperHeight,n.lastWrapWidth=t.wrapperWidth,Or(e,400)),n.updateLineNumbers=null,!0}function Xr(e,t){for(var n=t.viewport,i=!0;;i=!1){if(i&&e.options.lineWrapping&&t.oldDisplayWidth!=Jn(e))i&&(t.visible=tr(e.display,e.doc,n));else if(n&&null!=n.top&&(n={top:Math.min(e.doc.height+Qn(e.display)-Kn(e),n.top)}),t.visible=tr(e.display,e.doc,n),t.visible.from>=e.display.viewFrom&&t.visible.to<=e.display.viewTo)break;if(!Ur(e,t))break;$i(e);var r=gr(e);Gi(e),Ar(e,r),Qr(e,r),t.force=!1}t.signal(e,"update",e),e.display.viewFrom==e.display.reportedViewFrom&&e.display.viewTo==e.display.reportedViewTo||(t.signal(e,"viewportChange",e,e.display.viewFrom,e.display.viewTo),e.display.reportedViewFrom=e.display.viewFrom,e.display.reportedViewTo=e.display.viewTo)}function Gr(e,t){var n=new Rr(e,t);if(Ur(e,n)){$i(e),Xr(e,n);var i=gr(e);Gi(e),Ar(e,i),Qr(e,i),n.finish()}}function Vr(e,t,n){var i=e.display,r=e.options.lineNumbers,s=i.lineDiv,o=s.firstChild;function a(t){var n=t.nextSibling;return l&&A&&e.display.currentWheelTarget==t?t.style.display="none":t.parentNode.removeChild(t),n}for(var u=i.view,c=i.viewFrom,d=0;d<u.length;d++){var h=u[d];if(h.hidden);else if(h.node&&h.node.parentNode==s){for(;o!=h.node;)o=a(o);var f=r&&null!=t&&t<=c&&h.lineNumber;h.changes&&(H(h.changes,"gutter")>-1&&(f=!1),Dn(e,h,c,n)),f&&(S(h.lineNumber),h.lineNumber.appendChild(document.createTextNode(rt(e.options,c)))),o=h.node.nextSibling}else{var p=Fn(e,h,c,n);s.insertBefore(p,o)}c+=h.size}for(;o;)o=a(o)}function Wr(e){var t=e.gutters.offsetWidth;e.sizer.style.marginLeft=t+"px"}function Qr(e,t){e.display.sizer.style.minHeight=t.docHeight+"px",e.display.heightForcer.style.top=t.docHeight+"px",e.display.gutters.style.height=t.docHeight+e.display.barHeight+Yn(e)+"px"}function Zr(e){var t=e.display,n=t.view;if(t.alignWidgets||t.gutters.firstChild&&e.options.fixedGutter){for(var i=Ii(t)-t.scroller.scrollLeft+e.doc.scrollLeft,r=t.gutters.offsetWidth,s=i+"px",o=0;o<n.length;o++)if(!n[o].hidden){e.options.fixedGutter&&(n[o].gutter&&(n[o].gutter.style.left=s),n[o].gutterBackground&&(n[o].gutterBackground.style.left=s));var a=n[o].alignable;if(a)for(var l=0;l<a.length;l++)a[l].style.left=s}e.options.fixedGutter&&(t.gutters.style.left=i+r+"px")}}function Yr(e){if(!e.options.lineNumbers)return!1;var t=e.doc,n=rt(e.options,t.first+t.size-1),i=e.display;if(n.length!=i.lineNumChars){var r=i.measure.appendChild(N("div",[N("div",n)],"CodeMirror-linenumber CodeMirror-gutter-elt")),s=r.firstChild.offsetWidth,o=r.offsetWidth-s;return i.lineGutter.style.width="",i.lineNumInnerWidth=Math.max(s,i.lineGutter.offsetWidth-o)+1,i.lineNumWidth=i.lineNumInnerWidth+o,i.lineNumChars=i.lineNumInnerWidth?n.length:-1,i.lineGutter.style.width=i.lineNumWidth+"px",Wr(e.display),!0}return!1}function Jr(e,t){for(var n=[],i=!1,r=0;r<e.length;r++){var s=e[r],o=null;if("string"!=typeof s&&(o=s.style,s=s.className),"CodeMirror-linenumbers"==s){if(!t)continue;i=!0}n.push({className:s,style:o})}return t&&!i&&n.push({className:"CodeMirror-linenumbers",style:null}),n}function Kr(e){var t=e.gutters,n=e.gutterSpecs;S(t),e.lineGutter=null;for(var i=0;i<n.length;++i){var r=n[i],s=r.className,o=r.style,a=t.appendChild(N("div",null,"CodeMirror-gutter "+s));o&&(a.style.cssText=o),"CodeMirror-linenumbers"==s&&(e.lineGutter=a,a.style.width=(e.lineNumWidth||1)+"px")}t.style.display=n.length?"":"none",Wr(e)}function qr(e){Kr(e.display),Ri(e),Zr(e)}function _r(e,t,i,r){var s=this;this.input=i,s.scrollbarFiller=N("div",null,"CodeMirror-scrollbar-filler"),s.scrollbarFiller.setAttribute("cm-not-content","true"),s.gutterFiller=N("div",null,"CodeMirror-gutter-filler"),s.gutterFiller.setAttribute("cm-not-content","true"),s.lineDiv=B("div",null,"CodeMirror-code"),s.selectionDiv=N("div",null,null,"position: relative; z-index: 1"),s.cursorDiv=N("div",null,"CodeMirror-cursors"),s.measure=N("div",null,"CodeMirror-measure"),s.lineMeasure=N("div",null,"CodeMirror-measure"),s.lineSpace=B("div",[s.measure,s.lineMeasure,s.selectionDiv,s.cursorDiv,s.lineDiv],null,"position: relative; outline: none");var u=B("div",[s.lineSpace],"CodeMirror-lines");s.mover=N("div",[u],null,"position: relative"),s.sizer=N("div",[s.mover],"CodeMirror-sizer"),s.sizerWidth=null,s.heightForcer=N("div",null,null,"position: absolute; height: "+U+"px; width: 1px;"),s.gutters=N("div",null,"CodeMirror-gutters"),s.lineGutter=null,s.scroller=N("div",[s.sizer,s.heightForcer,s.gutters],"CodeMirror-scroll"),s.scroller.setAttribute("tabIndex","-1"),s.wrapper=N("div",[s.scrollbarFiller,s.gutterFiller,s.scroller],"CodeMirror"),o&&a<8&&(s.gutters.style.zIndex=-1,s.scroller.style.paddingRight=0),l||n&&v||(s.scroller.draggable=!0),e&&(e.appendChild?e.appendChild(s.wrapper):e(s.wrapper)),s.viewFrom=s.viewTo=t.first,s.reportedViewFrom=s.reportedViewTo=t.first,s.view=[],s.renderedView=null,s.externalMeasured=null,s.viewOffset=0,s.lastWrapHeight=s.lastWrapWidth=0,s.updateLineNumbers=null,s.nativeBarWidth=s.barHeight=s.barWidth=0,s.scrollbarsClipped=!1,s.lineNumWidth=s.lineNumInnerWidth=s.lineNumChars=null,s.alignWidgets=!1,s.cachedCharWidth=s.cachedTextHeight=s.cachedPaddingH=null,s.maxLine=null,s.maxLineLength=0,s.maxLineChanged=!1,s.wheelDX=s.wheelDY=s.wheelStartX=s.wheelStartY=null,s.shift=!1,s.selForContextMenu=null,s.activeTouch=null,s.gutterSpecs=Jr(r.gutters,r.lineNumbers),Kr(s),i.init(s)}Rr.prototype.signal=function(e,t){ye(e,t)&&this.events.push(arguments)},Rr.prototype.finish=function(){for(var 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o=[];vs(e,(function(e,t){t||-1!=H(o,e.history)||(oo(e.history,i),o.push(e.history)),to(e,i,null,Is(e,i))}))},f=r.changes.length-1;f>=0;--f){var p=h(f);if(p)return p.v}}}}function eo(e,t){if(0!=t&&(e.first+=t,e.sel=new rs(K(e.sel.ranges,(function(e){return new ss(st(e.anchor.line+t,e.anchor.ch),st(e.head.line+t,e.head.ch))})),e.sel.primIndex),e.cm)){Ri(e.cm,e.first,e.first-t,t);for(var n=e.cm.display,i=n.viewFrom;i<n.viewTo;i++)ki(e.cm,i,"gutter")}}function to(e,t,n,i){if(e.cm&&!e.cm.curOp)return Ir(e.cm,to)(e,t,n,i);if(t.to.line<e.first)eo(e,t.text.length-1-(t.to.line-t.from.line));else if(!(t.from.line>e.lastLine())){if(t.from.line<e.first){var r=t.text.length-1-(e.first-t.from.line);eo(e,r),t={from:st(e.first,0),to:st(t.to.line+r,t.to.ch),text:[J(t.text)],origin:t.origin}}var s=e.lastLine();t.to.line>s&&(t={from:t.from,to:st(s,qe(e,s).text.length),text:[t.text[0]],origin:t.origin}),t.removed=_e(e,t.from,t.to),n||(n=cs(e,t)),e.cm?no(e.cm,t,i):ms(e,t,i),Xs(e,n,G),e.cantEdit&&Zs(e,st(e.firstLine(),0))&&(e.cantEdit=!1)}}function no(e,t,n){var i=e.doc,r=e.display,s=t.from,o=t.to,a=!1,l=s.line;e.options.lineWrapping||(l=tt(_t(qe(i,s.line))),i.iter(l,o.line+1,(function(e){if(e==r.maxLine)return a=!0,!0}))),i.sel.contains(t.from,t.to)>-1&&xe(e),ms(i,t,n,Li(e)),e.options.lineWrapping||(i.iter(l,s.line+t.text.length,(function(e){var t=an(e);t>r.maxLineLength&&(r.maxLine=e,r.maxLineLength=t,r.maxLineChanged=!0,a=!1)})),a&&(e.curOp.updateMaxLine=!0)),Pt(i,s.line),Or(e,400);var u=t.text.length-(o.line-s.line)-1;t.full?Ri(e):s.line!=o.line||1!=t.text.length||gs(e.doc,t)?Ri(e,s.line,o.line+1,u):ki(e,s.line,"text");var c=ye(e,"changes"),d=ye(e,"change");if(d||c){var h={from:s,to:o,text:t.text,removed:t.removed,origin:t.origin};d&&Nn(e,"change",e,h),c&&(e.curOp.changeObjs||(e.curOp.changeObjs=[])).push(h)}e.display.selForContextMenu=null}function io(e,t,n,i,r){var s;i||(i=n),ot(i,n)<0&&(n=(s=[i,n])[0],i=s[1]),"string"==typeof t&&(t=e.splitLines(t)),qs(e,{from:n,to:i,text:t,origin:r})}function ro(e,t,n,i){n<e.line?e.line+=i:t<e.line&&(e.line=t,e.ch=0)}function so(e,t,n,i){for(var r=0;r<e.length;++r){var s=e[r],o=!0;if(s.ranges){s.copied||((s=e[r]=s.deepCopy()).copied=!0);for(var a=0;a<s.ranges.length;a++)ro(s.ranges[a].anchor,t,n,i),ro(s.ranges[a].head,t,n,i)}else{for(var l=0;l<s.changes.length;++l){var u=s.changes[l];if(n<u.from.line)u.from=st(u.from.line+i,u.from.ch),u.to=st(u.to.line+i,u.to.ch);else if(t<=u.to.line){o=!1;break}}o||(e.splice(0,r+1),r=0)}}}function oo(e,t){var n=t.from.line,i=t.to.line,r=t.text.length-(i-n)-1;so(e.done,n,i,r),so(e.undone,n,i,r)}function ao(e,t,n,i){var r=t,s=t;return"number"==typeof t?s=qe(e,dt(e,t)):r=tt(t),null==r?null:(i(s,r)&&e.cm&&ki(e.cm,r,n),s)}function lo(e){this.lines=e,this.parent=null;for(var t=0,n=0;n<e.length;++n)e[n].parent=this,t+=e[n].height;this.height=t}function uo(e){this.children=e;for(var t=0,n=0,i=0;i<e.length;++i){var r=e[i];t+=r.chunkSize(),n+=r.height,r.parent=this}this.size=t,this.height=n,this.parent=null}ss.prototype.from=function(){return ct(this.anchor,this.head)},ss.prototype.to=function(){return ut(this.anchor,this.head)},ss.prototype.empty=function(){return this.head.line==this.anchor.line&&this.head.ch==this.anchor.ch},lo.prototype={chunkSize:function(){return this.lines.length},removeInner:function(e,t){for(var n=e,i=e+t;n<i;++n){var r=this.lines[n];this.height-=r.height,dn(r),Nn(r,"delete")}this.lines.splice(e,t)},collapse:function(e){e.push.apply(e,this.lines)},insertInner:function(e,t,n){this.height+=n,this.lines=this.lines.slice(0,e).concat(t).concat(this.lines.slice(e));for(var i=0;i<t.length;++i)t[i].parent=this},iterN:function(e,t,n){for(var i=e+t;e<i;++e)if(n(this.lines[e]))return!0}},uo.prototype={chunkSize:function(){return this.size},removeInner:function(e,t){this.size-=t;for(var n=0;n<this.children.length;++n){var i=this.children[n],r=i.chunkSize();if(e<r){var s=Math.min(t,r-e),o=i.height;if(i.removeInner(e,s),this.height-=o-i.height,r==s&&(this.children.splice(n--,1),i.parent=null),0==(t-=s))break;e=0}else e-=r}if(this.size-t<25&&(this.children.length>1||!(this.children[0]instanceof lo))){var a=[];this.collapse(a),this.children=[new lo(a)],this.children[0].parent=this}},collapse:function(e){for(var t=0;t<this.children.length;++t)this.children[t].collapse(e)},insertInner:function(e,t,n){this.size+=t.length,this.height+=n;for(var i=0;i<this.children.length;++i){var r=this.children[i],s=r.chunkSize();if(e<=s){if(r.insertInner(e,t,n),r.lines&&r.lines.length>50){for(var o=r.lines.length%25+25,a=o;a<r.lines.length;){var l=new lo(r.lines.slice(a,a+=25));r.height-=l.height,this.children.splice(++i,0,l),l.parent=this}r.lines=r.lines.slice(0,o),this.maybeSpill()}break}e-=s}},maybeSpill:function(){if(!(this.children.length<=10)){var e=this;do{var t=new uo(e.children.splice(e.children.length-5,5));if(e.parent){e.size-=t.size,e.height-=t.height;var n=H(e.parent.children,e);e.parent.children.splice(n+1,0,t)}else{var i=new uo(e.children);i.parent=e,e.children=[i,t],e=i}t.parent=e.parent}while(e.children.length>10);e.parent.maybeSpill()}},iterN:function(e,t,n){for(var i=0;i<this.children.length;++i){var r=this.children[i],s=r.chunkSize();if(e<s){var o=Math.min(t,s-e);if(r.iterN(e,o,n))return!0;if(0==(t-=o))break;e=0}else e-=s}}};var co=function(e,t,n){if(n)for(var i in n)n.hasOwnProperty(i)&&(this[i]=n[i]);this.doc=e,this.node=t};function ho(e,t,n){on(t)<(e.curOp&&e.curOp.scrollTop||e.doc.scrollTop)&&or(e,n)}function fo(e,t,n,i){var r=new co(e,n,i),s=e.cm;return s&&r.noHScroll&&(s.display.alignWidgets=!0),ao(e,t,"widget",(function(t){var n=t.widgets||(t.widgets=[]);if(null==r.insertAt?n.push(r):n.splice(Math.min(n.length-1,Math.max(0,r.insertAt)),0,r),r.line=t,s&&!rn(e,t)){var i=on(t)<e.scrollTop;et(t,t.height+Gn(r)),i&&or(s,r.height),s.curOp.forceUpdate=!0}return!0})),s&&Nn(s,"lineWidgetAdded",s,r,"number"==typeof t?t:tt(t)),r}co.prototype.clear=function(){var e=this.doc.cm,t=this.line.widgets,n=this.line,i=tt(n);if(null!=i&&t){for(var r=0;r<t.length;++r)t[r]==this&&t.splice(r--,1);t.length||(n.widgets=null);var s=Gn(this);et(n,Math.max(0,n.height-s)),e&&(Dr(e,(function(){ho(e,n,-s),ki(e,i,"widget")})),Nn(e,"lineWidgetCleared",e,this,i))}},co.prototype.changed=function(){var e=this,t=this.height,n=this.doc.cm,i=this.line;this.height=null;var r=Gn(this)-t;r&&(rn(this.doc,i)||et(i,i.height+r),n&&Dr(n,(function(){n.curOp.forceUpdate=!0,ho(n,i,r),Nn(n,"lineWidgetChanged",n,e,tt(i))})))},be(co);var po=0,go=function(e,t){this.lines=[],this.type=t,this.doc=e,this.id=++po};function mo(e,t,n,i,r){if(i&&i.shared)return Ao(e,t,n,i,r);if(e.cm&&!e.cm.curOp)return Ir(e.cm,mo)(e,t,n,i,r);var s=new go(e,r),o=ot(t,n);if(i&&R(i,s,!1),o>0||0==o&&!1!==s.clearWhenEmpty)return s;if(s.replacedWith&&(s.collapsed=!0,s.widgetNode=B("span",[s.replacedWith],"CodeMirror-widget"),i.handleMouseEvents||s.widgetNode.setAttribute("cm-ignore-events","true"),i.insertLeft&&(s.widgetNode.insertLeft=!0)),s.collapsed){if(qt(e,t.line,t,n,s)||t.line!=n.line&&qt(e,n.line,t,n,s))throw new Error("Inserting collapsed marker partially overlapping an existing one");It()}s.addToHistory&&Es(e,{from:t,to:n,origin:"markText"},e.sel,NaN);var a,l=t.line,u=e.cm;if(e.iter(l,n.line+1,(function(e){u&&s.collapsed&&!u.options.lineWrapping&&_t(e)==u.display.maxLine&&(a=!0),s.collapsed&&l!=t.line&&et(e,0),zt(e,new Lt(s,l==t.line?t.ch:null,l==n.line?n.ch:null)),++l})),s.collapsed&&e.iter(t.line,n.line+1,(function(t){rn(e,t)&&et(t,0)})),s.clearOnEnter&&pe(s,"beforeCursorEnter",(function(){return s.clear()})),s.readOnly&&(Dt(),(e.history.done.length||e.history.undone.length)&&e.clearHistory()),s.collapsed&&(s.id=++po,s.atomic=!0),u){if(a&&(u.curOp.updateMaxLine=!0),s.collapsed)Ri(u,t.line,n.line+1);else if(s.className||s.startStyle||s.endStyle||s.css||s.attributes||s.title)for(var c=t.line;c<=n.line;c++)ki(u,c,"text");s.atomic&&Vs(u.doc),Nn(u,"markerAdded",u,s)}return s}go.prototype.clear=function(){if(!this.explicitlyCleared){var e=this.doc.cm,t=e&&!e.curOp;if(t&&Cr(e),ye(this,"clear")){var n=this.find();n&&Nn(this,"clear",n.from,n.to)}for(var i=null,r=null,s=0;s<this.lines.length;++s){var o=this.lines[s],a=jt(o.markedSpans,this);e&&!this.collapsed?ki(e,tt(o),"text"):e&&(null!=a.to&&(r=tt(o)),null!=a.from&&(i=tt(o))),o.markedSpans=Ot(o.markedSpans,a),null==a.from&&this.collapsed&&!rn(this.doc,o)&&e&&et(o,Ni(e.display))}if(e&&this.collapsed&&!e.options.lineWrapping)for(var l=0;l<this.lines.length;++l){var u=_t(this.lines[l]),c=an(u);c>e.display.maxLineLength&&(e.display.maxLine=u,e.display.maxLineLength=c,e.display.maxLineChanged=!0)}null!=i&&e&&this.collapsed&&Ri(e,i,r+1),this.lines.length=0,this.explicitlyCleared=!0,this.atomic&&this.doc.cantEdit&&(this.doc.cantEdit=!1,e&&Vs(e.doc)),e&&Nn(e,"markerCleared",e,this,i,r),t&&Mr(e),this.parent&&this.parent.clear()}},go.prototype.find=function(e,t){var n,i;null==e&&"bookmark"==this.type&&(e=1);for(var r=0;r<this.lines.length;++r){var s=this.lines[r],o=jt(s.markedSpans,this);if(null!=o.from&&(n=st(t?s:tt(s),o.from),-1==e))return n;if(null!=o.to&&(i=st(t?s:tt(s),o.to),1==e))return i}return n&&{from:n,to:i}},go.prototype.changed=function(){var e=this,t=this.find(-1,!0),n=this,i=this.doc.cm;t&&i&&Dr(i,(function(){var r=t.line,s=tt(t.line),o=ti(i,s);if(o&&(ci(o),i.curOp.selectionChanged=i.curOp.forceUpdate=!0),i.curOp.updateMaxLine=!0,!rn(n.doc,r)&&null!=n.height){var a=n.height;n.height=null;var l=Gn(n)-a;l&&et(r,r.height+l)}Nn(i,"markerChanged",i,e)}))},go.prototype.attachLine=function(e){if(!this.lines.length&&this.doc.cm){var t=this.doc.cm.curOp;t.maybeHiddenMarkers&&-1!=H(t.maybeHiddenMarkers,this)||(t.maybeUnhiddenMarkers||(t.maybeUnhiddenMarkers=[])).push(this)}this.lines.push(e)},go.prototype.detachLine=function(e){if(this.lines.splice(H(this.lines,e),1),!this.lines.length&&this.doc.cm){var t=this.doc.cm.curOp;(t.maybeHiddenMarkers||(t.maybeHiddenMarkers=[])).push(this)}},be(go);var vo=function(e,t){this.markers=e,this.primary=t;for(var n=0;n<e.length;++n)e[n].parent=this};function Ao(e,t,n,i,r){(i=R(i)).shared=!1;var s=[mo(e,t,n,i,r)],o=s[0],a=i.widgetNode;return vs(e,(function(e){a&&(i.widgetNode=a.cloneNode(!0)),s.push(mo(e,ht(e,t),ht(e,n),i,r));for(var l=0;l<e.linked.length;++l)if(e.linked[l].isParent)return;o=J(s)})),new vo(s,o)}function xo(e){return e.findMarks(st(e.first,0),e.clipPos(st(e.lastLine())),(function(e){return e.parent}))}function yo(e,t){for(var n=0;n<t.length;n++){var i=t[n],r=i.find(),s=e.clipPos(r.from),o=e.clipPos(r.to);if(ot(s,o)){var a=mo(e,s,o,i.primary,i.primary.type);i.markers.push(a),a.parent=i}}}function bo(e){for(var t=function(t){var n=e[t],i=[n.primary.doc];vs(n.primary.doc,(function(e){return i.push(e)}));for(var r=0;r<n.markers.length;r++){var s=n.markers[r];-1==H(i,s.doc)&&(s.parent=null,n.markers.splice(r--,1))}},n=0;n<e.length;n++)t(n)}vo.prototype.clear=function(){if(!this.explicitlyCleared){this.explicitlyCleared=!0;for(var e=0;e<this.markers.length;++e)this.markers[e].clear();Nn(this,"clear")}},vo.prototype.find=function(e,t){return this.primary.find(e,t)},be(vo);var wo=0,Co=function(e,t,n,i,r){if(!(this instanceof Co))return new Co(e,t,n,i,r);null==n&&(n=0),uo.call(this,[new lo([new un("",null)])]),this.first=n,this.scrollTop=this.scrollLeft=0,this.cantEdit=!1,this.cleanGeneration=1,this.modeFrontier=this.highlightFrontier=n;var s=st(n,0);this.sel=as(s),this.history=new bs(null),this.id=++wo,this.modeOption=t,this.lineSep=i,this.direction="rtl"==r?"rtl":"ltr",this.extend=!1,"string"==typeof e&&(e=this.splitLines(e)),ms(this,{from:s,to:s,text:e}),Us(this,as(s),G)};Co.prototype=$(uo.prototype,{constructor:Co,iter:function(e,t,n){n?this.iterN(e-this.first,t-e,n):this.iterN(this.first,this.first+this.size,e)},insert:function(e,t){for(var n=0,i=0;i<t.length;++i)n+=t[i].height;this.insertInner(e-this.first,t,n)},remove:function(e,t){this.removeInner(e-this.first,t)},getValue:function(e){var t=$e(this,this.first,this.first+this.size);return!1===e?t:t.join(e||this.lineSeparator())},setValue:jr((function(e){var t=st(this.first,0),n=this.first+this.size-1;qs(this,{from:t,to:st(n,qe(this,n).text.length),text:this.splitLines(e),origin:"setValue",full:!0},!0),this.cm&&lr(this.cm,0,0),Us(this,as(t),G)})),replaceRange:function(e,t,n,i){io(this,e,t=ht(this,t),n=n?ht(this,n):t,i)},getRange:function(e,t,n){var i=_e(this,ht(this,e),ht(this,t));return!1===n?i:i.join(n||this.lineSeparator())},getLine:function(e){var t=this.getLineHandle(e);return t&&t.text},getLineHandle:function(e){if(it(this,e))return qe(this,e)},getLineNumber:function(e){return tt(e)},getLineHandleVisualStart:function(e){return"number"==typeof e&&(e=qe(this,e)),_t(e)},lineCount:function(){return this.size},firstLine:function(){return this.first},lastLine:function(){return this.first+this.size-1},clipPos:function(e){return ht(this,e)},getCursor:function(e){var t=this.sel.primary();return null==e||"head"==e?t.head:"anchor"==e?t.anchor:"end"==e||"to"==e||!1===e?t.to():t.from()},listSelections:function(){return this.sel.ranges},somethingSelected:function(){return this.sel.somethingSelected()},setCursor:jr((function(e,t,n){ks(this,ht(this,"number"==typeof e?st(e,t||0):e),null,n)})),setSelection:jr((function(e,t,n){ks(this,ht(this,e),ht(this,t||e),n)})),extendSelection:jr((function(e,t,n){Os(this,ht(this,e),t&&ht(this,t),n)})),extendSelections:jr((function(e,t){zs(this,pt(this,e),t)})),extendSelectionsBy:jr((function(e,t){zs(this,pt(this,K(this.sel.ranges,e)),t)})),setSelections:jr((function(e,t,n){if(e.length){for(var i=[],r=0;r<e.length;r++)i[r]=new ss(ht(this,e[r].anchor),ht(this,e[r].head));null==t&&(t=Math.min(e.length-1,this.sel.primIndex)),Us(this,os(this.cm,i,t),n)}})),addSelection:jr((function(e,t,n){var i=this.sel.ranges.slice(0);i.push(new ss(ht(this,e),ht(this,t||e))),Us(this,os(this.cm,i,i.length-1),n)})),getSelection:function(e){for(var t,n=this.sel.ranges,i=0;i<n.length;i++){var r=_e(this,n[i].from(),n[i].to());t=t?t.concat(r):r}return!1===e?t:t.join(e||this.lineSeparator())},getSelections:function(e){for(var t=[],n=this.sel.ranges,i=0;i<n.length;i++){var r=_e(this,n[i].from(),n[i].to());!1!==e&&(r=r.join(e||this.lineSeparator())),t[i]=r}return t},replaceSelection:function(e,t,n){for(var i=[],r=0;r<this.sel.ranges.length;r++)i[r]=e;this.replaceSelections(i,t,n||"+input")},replaceSelections:jr((function(e,t,n){for(var i=[],r=this.sel,s=0;s<r.ranges.length;s++){var o=r.ranges[s];i[s]={from:o.from(),to:o.to(),text:this.splitLines(e[s]),origin:n}}for(var a=t&&"end"!=t&&hs(this,i,t),l=i.length-1;l>=0;l--)qs(this,i[l]);a?Hs(this,a):this.cm&&ar(this.cm)})),undo:jr((function(){$s(this,"undo")})),redo:jr((function(){$s(this,"redo")})),undoSelection:jr((function(){$s(this,"undo",!0)})),redoSelection:jr((function(){$s(this,"redo",!0)})),setExtending:function(e){this.extend=e},getExtending:function(){return this.extend},historySize:function(){for(var e=this.history,t=0,n=0,i=0;i<e.done.length;i++)e.done[i].ranges||++t;for(var r=0;r<e.undone.length;r++)e.undone[r].ranges||++n;return{undo:t,redo:n}},clearHistory:function(){var e=this;this.history=new bs(this.history.maxGeneration),vs(this,(function(t){return t.history=e.history}),!0)},markClean:function(){this.cleanGeneration=this.changeGeneration(!0)},changeGeneration:function(e){return e&&(this.history.lastOp=this.history.lastSelOp=this.history.lastOrigin=null),this.history.generation},isClean:function(e){return this.history.generation==(e||this.cleanGeneration)},getHistory:function(){return{done:Ls(this.history.done),undone:Ls(this.history.undone)}},setHistory:function(e){var t=this.history=new bs(this.history.maxGeneration);t.done=Ls(e.done.slice(0),null,!0),t.undone=Ls(e.undone.slice(0),null,!0)},setGutterMarker:jr((function(e,t,n){return ao(this,e,"gutter",(function(e){var i=e.gutterMarkers||(e.gutterMarkers={});return i[t]=n,!n&&ie(i)&&(e.gutterMarkers=null),!0}))})),clearGutter:jr((function(e){var t=this;this.iter((function(n){n.gutterMarkers&&n.gutterMarkers[e]&&ao(t,n,"gutter",(function(){return n.gutterMarkers[e]=null,ie(n.gutterMarkers)&&(n.gutterMarkers=null),!0}))}))})),lineInfo:function(e){var t;if("number"==typeof e){if(!it(this,e))return null;if(t=e,!(e=qe(this,e)))return null}else if(null==(t=tt(e)))return null;return{line:t,handle:e,text:e.text,gutterMarkers:e.gutterMarkers,textClass:e.textClass,bgClass:e.bgClass,wrapClass:e.wrapClass,widgets:e.widgets}},addLineClass:jr((function(e,t,n){return ao(this,e,"gutter"==t?"gutter":"class",(function(e){var i="text"==t?"textClass":"background"==t?"bgClass":"gutter"==t?"gutterClass":"wrapClass";if(e[i]){if(M(n).test(e[i]))return!1;e[i]+=" "+n}else e[i]=n;return!0}))})),removeLineClass:jr((function(e,t,n){return ao(this,e,"gutter"==t?"gutter":"class",(function(e){var i="text"==t?"textClass":"background"==t?"bgClass":"gutter"==t?"gutterClass":"wrapClass",r=e[i];if(!r)return!1;if(null==n)e[i]=null;else{var s=r.match(M(n));if(!s)return!1;var o=s.index+s[0].length;e[i]=r.slice(0,s.index)+(s.index&&o!=r.length?" 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n}function ta(e,t,n){if("string"==typeof t&&!(t=qo[t]))return!1;e.display.input.ensurePolled();var i=e.display.shift,r=!1;try{e.isReadOnly()&&(e.state.suppressEdits=!0),n&&(e.display.shift=!1),r=t(e)!=X}finally{e.display.shift=i,e.state.suppressEdits=!1}return r}function na(e,t,n){for(var i=0;i<e.state.keyMaps.length;i++){var r=Uo(t,e.state.keyMaps[i],n,e);if(r)return r}return e.options.extraKeys&&Uo(t,e.options.extraKeys,n,e)||Uo(t,e.options.keyMap,n,e)}var ia=new F;function ra(e,t,n,i){var r=e.state.keySeq;if(r){if(Xo(t))return"handled";if(/\'$/.test(t)?e.state.keySeq=null:ia.set(50,(function(){e.state.keySeq==r&&(e.state.keySeq=null,e.display.input.reset())})),sa(e,r+" "+t,n,i))return!0}return sa(e,t,n,i)}function sa(e,t,n,i){var r=na(e,t,i);return"multi"==r&&(e.state.keySeq=t),"handled"==r&&Nn(e,"keyHandled",e,t,n),"handled"!=r&&"multi"!=r||(we(n),Yi(e)),!!r}function oa(e,t){var n=Vo(t,!0);return!!n&&(t.shiftKey&&!e.state.keySeq?ra(e,"Shift-"+n,t,(function(t){return 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da(e){16==e.keyCode&&(this.doc.sel.shift=!1),Ae(this,e)}function ha(e){var t=this;if(!(e.target&&e.target!=t.display.input.getField()||Vn(t.display,e)||Ae(t,e)||e.ctrlKey&&!e.altKey||A&&e.metaKey)){var n=e.keyCode,i=e.charCode;if(d&&n==la)return la=null,void we(e);if(!d||e.which&&!(e.which<10)||!oa(t,e)){var r=String.fromCharCode(null==i?n:i);"\b"!=r&&(aa(t,e,r)||t.display.input.onKeyPress(e))}}}var fa,pa,ga=400,ma=function(e,t,n){this.time=e,this.pos=t,this.button=n};function va(e,t){var n=+new Date;return pa&&pa.compare(n,e,t)?(fa=pa=null,"triple"):fa&&fa.compare(n,e,t)?(pa=new ma(n,e,t),fa=null,"double"):(fa=new ma(n,e,t),pa=null,"single")}function Aa(e){var t=this,n=t.display;if(!(Ae(t,e)||n.activeTouch&&n.input.supportsTouch()))if(n.input.ensurePolled(),n.shift=e.shiftKey,Vn(n,e))l||(n.scroller.draggable=!1,setTimeout((function(){return n.scroller.draggable=!0}),100));else if(!Sa(t,e)){var i=Oi(t,e),r=Se(e),s=i?va(i,r):"single";window.focus(),1==r&&t.state.selectingText&&t.state.selectingText(e),i&&xa(t,r,i,s,e)||(1==r?i?ba(t,i,s,e):Te(e)==n.scroller&&we(e):2==r?(i&&Os(t.doc,i),setTimeout((function(){return n.input.focus()}),20)):3==r&&(C?t.display.input.onContextMenu(e):Ki(t)))}}function xa(e,t,n,i,r){var s="Click";return"double"==i?s="Double"+s:"triple"==i&&(s="Triple"+s),ra(e,Go(s=(1==t?"Left":2==t?"Middle":"Right")+s,r),r,(function(t){if("string"==typeof t&&(t=qo[t]),!t)return!1;var i=!1;try{e.isReadOnly()&&(e.state.suppressEdits=!0),i=t(e,n)!=X}finally{e.state.suppressEdits=!1}return i}))}function ya(e,t,n){var i=e.getOption("configureMouse"),r=i?i(e,t,n):{};if(null==r.unit){var s=x?n.shiftKey&&n.metaKey:n.altKey;r.unit=s?"rectangle":"single"==t?"char":"double"==t?"word":"line"}return(null==r.extend||e.doc.extend)&&(r.extend=e.doc.extend||n.shiftKey),null==r.addNew&&(r.addNew=A?n.metaKey:n.ctrlKey),null==r.moveOnDrag&&(r.moveOnDrag=!(A?n.altKey:n.ctrlKey)),r}function ba(e,t,n,i){o?setTimeout(z(Ji,e),0):e.curOp.focus=I();var r,s=ya(e,n,i),a=e.doc.sel;e.options.dragDrop&&Be&&!e.isReadOnly()&&"single"==n&&(r=a.contains(t))>-1&&(ot((r=a.ranges[r]).from(),t)<0||t.xRel>0)&&(ot(r.to(),t)>0||t.xRel<0)?wa(e,i,t,s):Ma(e,i,t,s)}function wa(e,t,n,i){var r=e.display,s=!1,u=Ir(e,(function(t){l&&(r.scroller.draggable=!1),e.state.draggingText=!1,me(r.wrapper.ownerDocument,"mouseup",u),me(r.wrapper.ownerDocument,"mousemove",c),me(r.scroller,"dragstart",d),me(r.scroller,"drop",u),s||(we(t),i.addNew||Os(e.doc,n,null,null,i.extend),l&&!h||o&&9==a?setTimeout((function(){r.wrapper.ownerDocument.body.focus({preventScroll:!0}),r.input.focus()}),20):r.input.focus())})),c=function(e){s=s||Math.abs(t.clientX-e.clientX)+Math.abs(t.clientY-e.clientY)>=10},d=function(){return s=!0};l&&(r.scroller.draggable=!0),e.state.draggingText=u,u.copy=!i.moveOnDrag,r.scroller.dragDrop&&r.scroller.dragDrop(),pe(r.wrapper.ownerDocument,"mouseup",u),pe(r.wrapper.ownerDocument,"mousemove",c),pe(r.scroller,"dragstart",d),pe(r.scroller,"drop",u),Ki(e),setTimeout((function(){return r.input.focus()}),20)}function Ca(e,t,n){if("char"==n)return new ss(t,t);if("word"==n)return e.findWordAt(t);if("line"==n)return new ss(st(t.line,0),ht(e.doc,st(t.line+1,0)));var i=n(e,t);return new ss(i.from,i.to)}function Ma(e,t,n,i){var r=e.display,s=e.doc;we(t);var o,a,l=s.sel,u=l.ranges;if(i.addNew&&!i.extend?(a=s.sel.contains(n),o=a>-1?u[a]:new ss(n,n)):(o=s.sel.primary(),a=s.sel.primIndex),"rectangle"==i.unit)i.addNew||(o=new ss(n,n)),n=Oi(e,t,!0,!0),a=-1;else{var c=Ca(e,n,i.unit);o=i.extend?js(o,c.anchor,c.head,i.extend):c}i.addNew?-1==a?(a=u.length,Us(s,os(e,u.concat([o]),a),{scroll:!1,origin:"*mouse"})):u.length>1&&u[a].empty()&&"char"==i.unit&&!i.extend?(Us(s,os(e,u.slice(0,a).concat(u.slice(a+1)),0),{scroll:!1,origin:"*mouse"}),l=s.sel):Rs(s,a,o,V):(a=0,Us(s,new rs([o],0),V),l=s.sel);var d=n;function h(t){if(0!=ot(d,t))if(d=t,"rectangle"==i.unit){for(var r=[],u=e.options.tabSize,c=k(qe(s,n.line).text,n.ch,u),h=k(qe(s,t.line).text,t.ch,u),f=Math.min(c,h),p=Math.max(c,h),g=Math.min(n.line,t.line),m=Math.min(e.lastLine(),Math.max(n.line,t.line));g<=m;g++){var v=qe(s,g).text,A=Q(v,f,u);f==p?r.push(new ss(st(g,A),st(g,A))):v.length>A&&r.push(new ss(st(g,A),st(g,Q(v,p,u))))}r.length||r.push(new ss(n,n)),Us(s,os(e,l.ranges.slice(0,a).concat(r),a),{origin:"*mouse",scroll:!1}),e.scrollIntoView(t)}else{var x,y=o,b=Ca(e,t,i.unit),w=y.anchor;ot(b.anchor,w)>0?(x=b.head,w=ct(y.from(),b.anchor)):(x=b.anchor,w=ut(y.to(),b.head));var C=l.ranges.slice(0);C[a]=Ea(e,new ss(ht(s,w),x)),Us(s,os(e,C,a),V)}}var f=r.wrapper.getBoundingClientRect(),p=0;function g(t){var n=++p,o=Oi(e,t,!0,"rectangle"==i.unit);if(o)if(0!=ot(o,d)){e.curOp.focus=I(),h(o);var a=tr(r,s);(o.line>=a.to||o.line<a.from)&&setTimeout(Ir(e,(function(){p==n&&g(t)})),150)}else{var l=t.clientY<f.top?-20:t.clientY>f.bottom?20:0;l&&setTimeout(Ir(e,(function(){p==n&&(r.scroller.scrollTop+=l,g(t))})),50)}}function m(t){e.state.selectingText=!1,p=1/0,t&&(we(t),r.input.focus()),me(r.wrapper.ownerDocument,"mousemove",v),me(r.wrapper.ownerDocument,"mouseup",A),s.history.lastSelOrigin=null}var v=Ir(e,(function(e){0!==e.buttons&&Se(e)?g(e):m(e)})),A=Ir(e,m);e.state.selectingText=A,pe(r.wrapper.ownerDocument,"mousemove",v),pe(r.wrapper.ownerDocument,"mouseup",A)}function Ea(e,t){var n=t.anchor,i=t.head,r=qe(e.doc,n.line);if(0==ot(n,i)&&n.sticky==i.sticky)return t;var s=he(r);if(!s)return t;var o=ce(s,n.ch,n.sticky),a=s[o];if(a.from!=n.ch&&a.to!=n.ch)return t;var l,u=o+(a.from==n.ch==(1!=a.level)?0:1);if(0==u||u==s.length)return t;if(i.line!=n.line)l=(i.line-n.line)*("ltr"==e.doc.direction?1:-1)>0;else{var c=ce(s,i.ch,i.sticky),d=c-o||(i.ch-n.ch)*(1==a.level?-1:1);l=c==u-1||c==u?d<0:d>0}var h=s[u+(l?-1:0)],f=l==(1==h.level),p=f?h.from:h.to,g=f?"after":"before";return n.ch==p&&n.sticky==g?t:new ss(new st(n.line,p,g),i)}function Ta(e,t,n,i){var r,s;if(t.touches)r=t.touches[0].clientX,s=t.touches[0].clientY;else try{r=t.clientX,s=t.clientY}catch(e){return!1}if(r>=Math.floor(e.display.gutters.getBoundingClientRect().right))return!1;i&&we(t);var o=e.display,a=o.lineDiv.getBoundingClientRect();if(s>a.bottom||!ye(e,n))return Me(t);s-=a.top-o.viewOffset;for(var l=0;l<e.display.gutterSpecs.length;++l){var u=o.gutters.childNodes[l];if(u&&u.getBoundingClientRect().right>=r)return ve(e,n,e,nt(e.doc,s),e.display.gutterSpecs[l].className,t),Me(t)}}function Sa(e,t){return Ta(e,t,"gutterClick",!0)}function Pa(e,t){Vn(e.display,t)||Na(e,t)||Ae(e,t,"contextmenu")||C||e.display.input.onContextMenu(t)}function Na(e,t){return!!ye(e,"gutterContextMenu")&&Ta(e,t,"gutterContextMenu",!1)}function Ba(e){e.display.wrapper.className=e.display.wrapper.className.replace(/\s*cm-s-\S+/g,"")+e.options.theme.replace(/(^|\s)\s*/g," cm-s-"),hi(e)}ma.prototype.compare=function(e,t,n){return this.time+ga>e&&0==ot(t,this.pos)&&n==this.button};var Da={toString:function(){return"CodeMirror.Init"}},Ia={},La={};function ja(e){var t=e.optionHandlers;function n(n,i,r,s){e.defaults[n]=i,r&&(t[n]=s?function(e,t,n){n!=Da&&r(e,t,n)}:r)}e.defineOption=n,e.Init=Da,n("value","",(function(e,t){return e.setValue(t)}),!0),n("mode",null,(function(e,t){e.doc.modeOption=t,fs(e)}),!0),n("indentUnit",2,fs,!0),n("indentWithTabs",!1),n("smartIndent",!0),n("tabSize",4,(function(e){ps(e),hi(e),Ri(e)}),!0),n("lineSeparator",null,(function(e,t){if(e.doc.lineSep=t,t){var n=[],i=e.doc.first;e.doc.iter((function(e){for(var r=0;;){var s=e.text.indexOf(t,r);if(-1==s)break;r=s+t.length,n.push(st(i,s))}i++}));for(var r=n.length-1;r>=0;r--)io(e.doc,t,n[r],st(n[r].line,n[r].ch+t.length))}})),n("specialChars",/[\u0000-\u001f\u007f-\u009f\u00ad\u061c\u200b-\u200c\u200e\u200f\u2028\u2029\ufeff\ufff9-\ufffc]/g,(function(e,t,n){e.state.specialChars=new RegExp(t.source+(t.test("\t")?"":"|\t"),"g"),n!=Da&&e.refresh()})),n("specialCharPlaceholder",mn,(function(e){return e.refresh()}),!0),n("electricChars",!0),n("inputStyle",v?"contenteditable":"textarea",(function(){throw new Error("inputStyle can not (yet) be changed in a running editor")}),!0),n("spellcheck",!1,(function(e,t){return e.getInputField().spellcheck=t}),!0),n("autocorrect",!1,(function(e,t){return e.getInputField().autocorrect=t}),!0),n("autocapitalize",!1,(function(e,t){return e.getInputField().autocapitalize=t}),!0),n("rtlMoveVisually",!y),n("wholeLineUpdateBefore",!0),n("theme","default",(function(e){Ba(e),qr(e)}),!0),n("keyMap","default",(function(e,t,n){var i=Wo(t),r=n!=Da&&Wo(n);r&&r.detach&&r.detach(e,i),i.attach&&i.attach(e,r||null)})),n("extraKeys",null),n("configureMouse",null),n("lineWrapping",!1,za,!0),n("gutters",[],(function(e,t){e.display.gutterSpecs=Jr(t,e.options.lineNumbers),qr(e)}),!0),n("fixedGutter",!0,(function(e,t){e.display.gutters.style.left=t?Ii(e.display)+"px":"0",e.refresh()}),!0),n("coverGutterNextToScrollbar",!1,(function(e){return Ar(e)}),!0),n("scrollbarStyle","native",(function(e){br(e),Ar(e),e.display.scrollbars.setScrollTop(e.doc.scrollTop),e.display.scrollbars.setScrollLeft(e.doc.scrollLeft)}),!0),n("lineNumbers",!1,(function(e,t){e.display.gutterSpecs=Jr(e.options.gutters,t),qr(e)}),!0),n("firstLineNumber",1,qr,!0),n("lineNumberFormatter",(function(e){return e}),qr,!0),n("showCursorWhenSelecting",!1,Gi,!0),n("resetSelectionOnContextMenu",!0),n("lineWiseCopyCut",!0),n("pasteLinesPerSelection",!0),n("selectionsMayTouch",!1),n("readOnly",!1,(function(e,t){"nocursor"==t&&(_i(e),e.display.input.blur()),e.display.input.readOnlyChanged(t)})),n("screenReaderLabel",null,(function(e,t){t=""===t?null:t,e.display.input.screenReaderLabelChanged(t)})),n("disableInput",!1,(function(e,t){t||e.display.input.reset()}),!0),n("dragDrop",!0,Oa),n("allowDropFileTypes",null),n("cursorBlinkRate",530),n("cursorScrollMargin",0),n("cursorHeight",1,Gi,!0),n("singleCursorHeightPerLine",!0,Gi,!0),n("workTime",100),n("workDelay",100),n("flattenSpans",!0,ps,!0),n("addModeClass",!1,ps,!0),n("pollInterval",100),n("undoDepth",200,(function(e,t){return e.doc.history.undoDepth=t})),n("historyEventDelay",1250),n("viewportMargin",10,(function(e){return e.refresh()}),!0),n("maxHighlightLength",1e4,ps,!0),n("moveInputWithCursor",!0,(function(e,t){t||e.display.input.resetPosition()})),n("tabindex",null,(function(e,t){return e.display.input.getField().tabIndex=t||""})),n("autofocus",null),n("direction","ltr",(function(e,t){return e.doc.setDirection(t)}),!0),n("phrases",null)}function Oa(e,t,n){if(!t!=!(n&&n!=Da)){var i=e.display.dragFunctions,r=t?pe:me;r(e.display.scroller,"dragstart",i.start),r(e.display.scroller,"dragenter",i.enter),r(e.display.scroller,"dragover",i.over),r(e.display.scroller,"dragleave",i.leave),r(e.display.scroller,"drop",i.drop)}}function za(e){e.options.lineWrapping?(L(e.display.wrapper,"CodeMirror-wrap"),e.display.sizer.style.minWidth="",e.display.sizerWidth=null):(T(e.display.wrapper,"CodeMirror-wrap"),ln(e)),ji(e),Ri(e),hi(e),setTimeout((function(){return Ar(e)}),100)}function Ra(e,t){var n=this;if(!(this instanceof Ra))return new Ra(e,t);this.options=t=t?R(t):{},R(Ia,t,!1);var i=t.value;"string"==typeof i?i=new Co(i,t.mode,null,t.lineSeparator,t.direction):t.mode&&(i.modeOption=t.mode),this.doc=i;var r=new Ra.inputStyles[t.inputStyle](this),s=this.display=new _r(e,i,r,t);for(var u in s.wrapper.CodeMirror=this,Ba(this),t.lineWrapping&&(this.display.wrapper.className+=" CodeMirror-wrap"),br(this),this.state={keyMaps:[],overlays:[],modeGen:0,overwrite:!1,delayingBlurEvent:!1,focused:!1,suppressEdits:!1,pasteIncoming:-1,cutIncoming:-1,selectingText:!1,draggingText:!1,highlight:new F,keySeq:null,specialChars:null},t.autofocus&&!v&&s.input.focus(),o&&a<11&&setTimeout((function(){return n.display.input.reset(!0)}),20),ka(this),Do(),Cr(this),this.curOp.forceUpdate=!0,As(this,i),t.autofocus&&!v||this.hasFocus()?setTimeout((function(){n.hasFocus()&&!n.state.focused&&qi(n)}),20):_i(this),La)La.hasOwnProperty(u)&&La[u](this,t[u],Da);Yr(this),t.finishInit&&t.finishInit(this);for(var c=0;c<Fa.length;++c)Fa[c](this);Mr(this),l&&t.lineWrapping&&"optimizelegibility"==getComputedStyle(s.lineDiv).textRendering&&(s.lineDiv.style.textRendering="auto")}function ka(e){var t=e.display;pe(t.scroller,"mousedown",Ir(e,Aa)),pe(t.scroller,"dblclick",o&&a<11?Ir(e,(function(t){if(!Ae(e,t)){var n=Oi(e,t);if(n&&!Sa(e,t)&&!Vn(e.display,t)){we(t);var i=e.findWordAt(n);Os(e.doc,i.anchor,i.head)}}})):function(t){return Ae(e,t)||we(t)}),pe(t.scroller,"contextmenu",(function(t){return Pa(e,t)})),pe(t.input.getField(),"contextmenu",(function(n){t.scroller.contains(n.target)||Pa(e,n)}));var n,i={end:0};function r(){t.activeTouch&&(n=setTimeout((function(){return t.activeTouch=null}),1e3),(i=t.activeTouch).end=+new Date)}function s(e){if(1!=e.touches.length)return!1;var t=e.touches[0];return t.radiusX<=1&&t.radiusY<=1}function l(e,t){if(null==t.left)return!0;var n=t.left-e.left,i=t.top-e.top;return n*n+i*i>400}pe(t.scroller,"touchstart",(function(r){if(!Ae(e,r)&&!s(r)&&!Sa(e,r)){t.input.ensurePolled(),clearTimeout(n);var o=+new Date;t.activeTouch={start:o,moved:!1,prev:o-i.end<=300?i:null},1==r.touches.length&&(t.activeTouch.left=r.touches[0].pageX,t.activeTouch.top=r.touches[0].pageY)}})),pe(t.scroller,"touchmove",(function(){t.activeTouch&&(t.activeTouch.moved=!0)})),pe(t.scroller,"touchend",(function(n){var i=t.activeTouch;if(i&&!Vn(t,n)&&null!=i.left&&!i.moved&&new Date-i.start<300){var s,o=e.coordsChar(t.activeTouch,"page");s=!i.prev||l(i,i.prev)?new ss(o,o):!i.prev.prev||l(i,i.prev.prev)?e.findWordAt(o):new ss(st(o.line,0),ht(e.doc,st(o.line+1,0))),e.setSelection(s.anchor,s.head),e.focus(),we(n)}r()})),pe(t.scroller,"touchcancel",r),pe(t.scroller,"scroll",(function(){t.scroller.clientHeight&&(hr(e,t.scroller.scrollTop),pr(e,t.scroller.scrollLeft,!0),ve(e,"scroll",e))})),pe(t.scroller,"mousewheel",(function(t){return is(e,t)})),pe(t.scroller,"DOMMouseScroll",(function(t){return is(e,t)})),pe(t.wrapper,"scroll",(function(){return t.wrapper.scrollTop=t.wrapper.scrollLeft=0})),t.dragFunctions={enter:function(t){Ae(e,t)||Ee(t)},over:function(t){Ae(e,t)||(So(e,t),Ee(t))},start:function(t){return To(e,t)},drop:Ir(e,Eo),leave:function(t){Ae(e,t)||Po(e)}};var u=t.input.getField();pe(u,"keyup",(function(t){return da.call(e,t)})),pe(u,"keydown",Ir(e,ua)),pe(u,"keypress",Ir(e,ha)),pe(u,"focus",(function(t){return qi(e,t)})),pe(u,"blur",(function(t){return _i(e,t)}))}Ra.defaults=Ia,Ra.optionHandlers=La;var Fa=[];function Ha(e,t,n,i){var r,s=e.doc;null==n&&(n="add"),"smart"==n&&(s.mode.indent?r=xt(e,t).state:n="prev");var o=e.options.tabSize,a=qe(s,t),l=k(a.text,null,o);a.stateAfter&&(a.stateAfter=null);var u,c=a.text.match(/^\s*/)[0];if(i||/\S/.test(a.text)){if("smart"==n&&((u=s.mode.indent(r,a.text.slice(c.length),a.text))==X||u>150)){if(!i)return;n="prev"}}else u=0,n="not";"prev"==n?u=t>s.first?k(qe(s,t-1).text,null,o):0:"add"==n?u=l+e.options.indentUnit:"subtract"==n?u=l-e.options.indentUnit:"number"==typeof n&&(u=l+n),u=Math.max(0,u);var d="",h=0;if(e.options.indentWithTabs)for(var f=Math.floor(u/o);f;--f)h+=o,d+="\t";if(h<u&&(d+=Y(u-h)),d!=c)return io(s,d,st(t,0),st(t,c.length),"+input"),a.stateAfter=null,!0;for(var p=0;p<s.sel.ranges.length;p++){var g=s.sel.ranges[p];if(g.head.line==t&&g.head.ch<c.length){var m=st(t,c.length);Rs(s,p,new ss(m,m));break}}}Ra.defineInitHook=function(e){return Fa.push(e)};var Ua=null;function Xa(e){Ua=e}function Ga(e,t,n,i,r){var s=e.doc;e.display.shift=!1,i||(i=s.sel);var o=+new Date-200,a="paste"==r||e.state.pasteIncoming>o,l=je(t),u=null;if(a&&i.ranges.length>1)if(Ua&&Ua.text.join("\n")==t){if(i.ranges.length%Ua.text.length==0){u=[];for(var c=0;c<Ua.text.length;c++)u.push(s.splitLines(Ua.text[c]))}}else l.length==i.ranges.length&&e.options.pasteLinesPerSelection&&(u=K(l,(function(e){return[e]})));for(var d=e.curOp.updateInput,h=i.ranges.length-1;h>=0;h--){var f=i.ranges[h],p=f.from(),g=f.to();f.empty()&&(n&&n>0?p=st(p.line,p.ch-n):e.state.overwrite&&!a?g=st(g.line,Math.min(qe(s,g.line).text.length,g.ch+J(l).length)):a&&Ua&&Ua.lineWise&&Ua.text.join("\n")==l.join("\n")&&(p=g=st(p.line,0)));var m={from:p,to:g,text:u?u[h%u.length]:l,origin:r||(a?"paste":e.state.cutIncoming>o?"cut":"+input")};qs(e.doc,m),Nn(e,"inputRead",e,m)}t&&!a&&Wa(e,t),ar(e),e.curOp.updateInput<2&&(e.curOp.updateInput=d),e.curOp.typing=!0,e.state.pasteIncoming=e.state.cutIncoming=-1}function Va(e,t){var n=e.clipboardData&&e.clipboardData.getData("Text");if(n)return e.preventDefault(),t.isReadOnly()||t.options.disableInput||Dr(t,(function(){return Ga(t,n,0,null,"paste")})),!0}function Wa(e,t){if(e.options.electricChars&&e.options.smartIndent)for(var n=e.doc.sel,i=n.ranges.length-1;i>=0;i--){var r=n.ranges[i];if(!(r.head.ch>100||i&&n.ranges[i-1].head.line==r.head.line)){var s=e.getModeAt(r.head),o=!1;if(s.electricChars){for(var a=0;a<s.electricChars.length;a++)if(t.indexOf(s.electricChars.charAt(a))>-1){o=Ha(e,r.head.line,"smart");break}}else s.electricInput&&s.electricInput.test(qe(e.doc,r.head.line).text.slice(0,r.head.ch))&&(o=Ha(e,r.head.line,"smart"));o&&Nn(e,"electricInput",e,r.head.line)}}}function Qa(e){for(var t=[],n=[],i=0;i<e.doc.sel.ranges.length;i++){var r=e.doc.sel.ranges[i].head.line,s={anchor:st(r,0),head:st(r+1,0)};n.push(s),t.push(e.getRange(s.anchor,s.head))}return{text:t,ranges:n}}function Za(e,t,n,i){e.setAttribute("autocorrect",n?"":"off"),e.setAttribute("autocapitalize",i?"":"off"),e.setAttribute("spellcheck",!!t)}function Ya(){var e=N("textarea",null,null,"position: absolute; bottom: -1em; padding: 0; width: 1px; height: 1em; outline: none"),t=N("div",[e],null,"overflow: hidden; position: relative; width: 3px; height: 0px;");return l?e.style.width="1000px":e.setAttribute("wrap","off"),g&&(e.style.border="1px solid black"),Za(e),t}function Ja(e){var t=e.optionHandlers,n=e.helpers={};e.prototype={constructor:e,focus:function(){window.focus(),this.display.input.focus()},setOption:function(e,n){var i=this.options,r=i[e];i[e]==n&&"mode"!=e||(i[e]=n,t.hasOwnProperty(e)&&Ir(this,t[e])(this,n,r),ve(this,"optionChange",this,e))},getOption:function(e){return this.options[e]},getDoc:function(){return this.doc},addKeyMap:function(e,t){this.state.keyMaps[t?"push":"unshift"](Wo(e))},removeKeyMap:function(e){for(var t=this.state.keyMaps,n=0;n<t.length;++n)if(t[n]==e||t[n].name==e)return t.splice(n,1),!0},addOverlay:Lr((function(t,n){var i=t.token?t:e.getMode(this.options,t);if(i.startState)throw new Error("Overlays may not be stateful.");q(this.state.overlays,{mode:i,modeSpec:t,opaque:n&&n.opaque,priority:n&&n.priority||0},(function(e){return e.priority})),this.state.modeGen++,Ri(this)})),removeOverlay:Lr((function(e){for(var t=this.state.overlays,n=0;n<t.length;++n){var i=t[n].modeSpec;if(i==e||"string"==typeof e&&i.name==e)return t.splice(n,1),this.state.modeGen++,void Ri(this)}})),indentLine:Lr((function(e,t,n){"string"!=typeof t&&"number"!=typeof t&&(t=null==t?this.options.smartIndent?"smart":"prev":t?"add":"subtract"),it(this.doc,e)&&Ha(this,e,t,n)})),indentSelection:Lr((function(e){for(var t=this.doc.sel.ranges,n=-1,i=0;i<t.length;i++){var r=t[i];if(r.empty())r.head.line>n&&(Ha(this,r.head.line,e,!0),n=r.head.line,i==this.doc.sel.primIndex&&ar(this));else{var s=r.from(),o=r.to(),a=Math.max(n,s.line);n=Math.min(this.lastLine(),o.line-(o.ch?0:1))+1;for(var l=a;l<n;++l)Ha(this,l,e);var u=this.doc.sel.ranges;0==s.ch&&t.length==u.length&&u[i].from().ch>0&&Rs(this.doc,i,new ss(s,u[i].to()),G)}}})),getTokenAt:function(e,t){return Mt(this,e,t)},getLineTokens:function(e,t){return Mt(this,st(e),t,!0)},getTokenTypeAt:function(e){e=ht(this.doc,e);var t,n=At(this,qe(this.doc,e.line)),i=0,r=(n.length-1)/2,s=e.ch;if(0==s)t=n[2];else for(;;){var o=i+r>>1;if((o?n[2*o-1]:0)>=s)r=o;else{if(!(n[2*o+1]<s)){t=n[2*o+2];break}i=o+1}}var a=t?t.indexOf("overlay "):-1;return a<0?t:0==a?null:t.slice(0,a-1)},getModeAt:function(t){var n=this.doc.mode;return n.innerMode?e.innerMode(n,this.getTokenAt(t).state).mode:n},getHelper:function(e,t){return this.getHelpers(e,t)[0]},getHelpers:function(e,t){var i=[];if(!n.hasOwnProperty(t))return i;var r=n[t],s=this.getModeAt(e);if("string"==typeof s[t])r[s[t]]&&i.push(r[s[t]]);else if(s[t])for(var o=0;o<s[t].length;o++){var a=r[s[t][o]];a&&i.push(a)}else s.helperType&&r[s.helperType]?i.push(r[s.helperType]):r[s.name]&&i.push(r[s.name]);for(var l=0;l<r._global.length;l++){var u=r._global[l];u.pred(s,this)&&-1==H(i,u.val)&&i.push(u.val)}return i},getStateAfter:function(e,t){var n=this.doc;return xt(this,(e=dt(n,null==e?n.first+n.size-1:e))+1,t).state},cursorCoords:function(e,t){var n=this.doc.sel.primary();return xi(this,null==e?n.head:"object"==typeof e?ht(this.doc,e):e?n.from():n.to(),t||"page")},charCoords:function(e,t){return Ai(this,ht(this.doc,e),t||"page")},coordsChar:function(e,t){return wi(this,(e=vi(this,e,t||"page")).left,e.top)},lineAtHeight:function(e,t){return e=vi(this,{top:e,left:0},t||"page").top,nt(this.doc,e+this.display.viewOffset)},heightAtLine:function(e,t,n){var i,r=!1;if("number"==typeof e){var s=this.doc.first+this.doc.size-1;e<this.doc.first?e=this.doc.first:e>s&&(e=s,r=!0),i=qe(this.doc,e)}else i=e;return mi(this,i,{top:0,left:0},t||"page",n||r).top+(r?this.doc.height-on(i):0)},defaultTextHeight:function(){return Ni(this.display)},defaultCharWidth:function(){return Bi(this.display)},getViewport:function(){return{from:this.display.viewFrom,to:this.display.viewTo}},addWidget:function(e,t,n,i,r){var s=this.display,o=(e=xi(this,ht(this.doc,e))).bottom,a=e.left;if(t.style.position="absolute",t.setAttribute("cm-ignore-events","true"),this.display.input.setUneditable(t),s.sizer.appendChild(t),"over"==i)o=e.top;else if("above"==i||"near"==i){var l=Math.max(s.wrapper.clientHeight,this.doc.height),u=Math.max(s.sizer.clientWidth,s.lineSpace.clientWidth);("above"==i||e.bottom+t.offsetHeight>l)&&e.top>t.offsetHeight?o=e.top-t.offsetHeight:e.bottom+t.offsetHeight<=l&&(o=e.bottom),a+t.offsetWidth>u&&(a=u-t.offsetWidth)}t.style.top=o+"px",t.style.left=t.style.right="","right"==r?(a=s.sizer.clientWidth-t.offsetWidth,t.style.right="0px"):("left"==r?a=0:"middle"==r&&(a=(s.sizer.clientWidth-t.offsetWidth)/2),t.style.left=a+"px"),n&&rr(this,{left:a,top:o,right:a+t.offsetWidth,bottom:o+t.offsetHeight})},triggerOnKeyDown:Lr(ua),triggerOnKeyPress:Lr(ha),triggerOnKeyUp:da,triggerOnMouseDown:Lr(Aa),execCommand:function(e){if(qo.hasOwnProperty(e))return qo[e].call(null,this)},triggerElectric:Lr((function(e){Wa(this,e)})),findPosH:function(e,t,n,i){var r=1;t<0&&(r=-1,t=-t);for(var s=ht(this.doc,e),o=0;o<t&&!(s=Ka(this.doc,s,r,n,i)).hitSide;++o);return s},moveH:Lr((function(e,t){var n=this;this.extendSelectionsBy((function(i){return n.display.shift||n.doc.extend||i.empty()?Ka(n.doc,i.head,e,t,n.options.rtlMoveVisually):e<0?i.from():i.to()}),W)})),deleteH:Lr((function(e,t){var n=this.doc.sel,i=this.doc;n.somethingSelected()?i.replaceSelection("",null,"+delete"):Qo(this,(function(n){var r=Ka(i,n.head,e,t,!1);return e<0?{from:r,to:n.head}:{from:n.head,to:r}}))})),findPosV:function(e,t,n,i){var r=1,s=i;t<0&&(r=-1,t=-t);for(var o=ht(this.doc,e),a=0;a<t;++a){var l=xi(this,o,"div");if(null==s?s=l.left:l.left=s,(o=qa(this,l,r,n)).hitSide)break}return o},moveV:Lr((function(e,t){var n=this,i=this.doc,r=[],s=!this.display.shift&&!i.extend&&i.sel.somethingSelected();if(i.extendSelectionsBy((function(o){if(s)return e<0?o.from():o.to();var a=xi(n,o.head,"div");null!=o.goalColumn&&(a.left=o.goalColumn),r.push(a.left);var l=qa(n,a,e,t);return"page"==t&&o==i.sel.primary()&&or(n,Ai(n,l,"div").top-a.top),l}),W),r.length)for(var o=0;o<i.sel.ranges.length;o++)i.sel.ranges[o].goalColumn=r[o]})),findWordAt:function(e){var t=qe(this.doc,e.line).text,n=e.ch,i=e.ch;if(t){var r=this.getHelper(e,"wordChars");"before"!=e.sticky&&i!=t.length||!n?++i:--n;for(var s=t.charAt(n),o=ne(s,r)?function(e){return ne(e,r)}:/\s/.test(s)?function(e){return/\s/.test(e)}:function(e){return!/\s/.test(e)&&!ne(e)};n>0&&o(t.charAt(n-1));)--n;for(;i<t.length&&o(t.charAt(i));)++i}return new ss(st(e.line,n),st(e.line,i))},toggleOverwrite:function(e){null!=e&&e==this.state.overwrite||((this.state.overwrite=!this.state.overwrite)?L(this.display.cursorDiv,"CodeMirror-overwrite"):T(this.display.cursorDiv,"CodeMirror-overwrite"),ve(this,"overwriteToggle",this,this.state.overwrite))},hasFocus:function(){return this.display.input.getField()==I()},isReadOnly:function(){return!(!this.options.readOnly&&!this.doc.cantEdit)},scrollTo:Lr((function(e,t){lr(this,e,t)})),getScrollInfo:function(){var e=this.display.scroller;return{left:e.scrollLeft,top:e.scrollTop,height:e.scrollHeight-Yn(this)-this.display.barHeight,width:e.scrollWidth-Yn(this)-this.display.barWidth,clientHeight:Kn(this),clientWidth:Jn(this)}},scrollIntoView:Lr((function(e,t){null==e?(e={from:this.doc.sel.primary().head,to:null},null==t&&(t=this.options.cursorScrollMargin)):"number"==typeof e?e={from:st(e,0),to:null}:null==e.from&&(e={from:e,to:null}),e.to||(e.to=e.from),e.margin=t||0,null!=e.from.line?ur(this,e):dr(this,e.from,e.to,e.margin)})),setSize:Lr((function(e,t){var n=this,i=function(e){return"number"==typeof e||/^\d+$/.test(String(e))?e+"px":e};null!=e&&(this.display.wrapper.style.width=i(e)),null!=t&&(this.display.wrapper.style.height=i(t)),this.options.lineWrapping&&di(this);var r=this.display.viewFrom;this.doc.iter(r,this.display.viewTo,(function(e){if(e.widgets)for(var t=0;t<e.widgets.length;t++)if(e.widgets[t].noHScroll){ki(n,r,"widget");break}++r})),this.curOp.forceUpdate=!0,ve(this,"refresh",this)})),operation:function(e){return Dr(this,e)},startOperation:function(){return Cr(this)},endOperation:function(){return Mr(this)},refresh:Lr((function(){var e=this.display.cachedTextHeight;Ri(this),this.curOp.forceUpdate=!0,hi(this),lr(this,this.doc.scrollLeft,this.doc.scrollTop),Wr(this.display),(null==e||Math.abs(e-Ni(this.display))>.5||this.options.lineWrapping)&&ji(this),ve(this,"refresh",this)})),swapDoc:Lr((function(e){var t=this.doc;return t.cm=null,this.state.selectingText&&this.state.selectingText(),As(this,e),hi(this),this.display.input.reset(),lr(this,e.scrollLeft,e.scrollTop),this.curOp.forceScroll=!0,Nn(this,"swapDoc",this,t),t})),phrase:function(e){var t=this.options.phrases;return t&&Object.prototype.hasOwnProperty.call(t,e)?t[e]:e},getInputField:function(){return this.display.input.getField()},getWrapperElement:function(){return this.display.wrapper},getScrollerElement:function(){return this.display.scroller},getGutterElement:function(){return this.display.gutters}},be(e),e.registerHelper=function(t,i,r){n.hasOwnProperty(t)||(n[t]=e[t]={_global:[]}),n[t][i]=r},e.registerGlobalHelper=function(t,i,r,s){e.registerHelper(t,i,s),n[t]._global.push({pred:r,val:s})}}function Ka(e,t,n,i,r){var s=t,o=n,a=qe(e,t.line),l=r&&"rtl"==e.direction?-n:n;function u(){var n=t.line+l;return!(n<e.first||n>=e.first+e.size)&&(t=new st(n,t.ch,t.sticky),a=qe(e,n))}function c(s){var o;if("codepoint"==i){var c=a.text.charCodeAt(t.ch+(i>0?0:-1));o=isNaN(c)?null:new st(t.line,Math.max(0,Math.min(a.text.length,t.ch+n*(c>=55296&&c<56320?2:1))),-n)}else o=r?Ko(e.cm,a,t,n):Yo(a,t,n);if(null==o){if(s||!u())return!1;t=Jo(r,e.cm,a,t.line,l)}else t=o;return!0}if("char"==i||"codepoint"==i)c();else if("column"==i)c(!0);else if("word"==i||"group"==i)for(var d=null,h="group"==i,f=e.cm&&e.cm.getHelper(t,"wordChars"),p=!0;!(n<0)||c(!p);p=!1){var g=a.text.charAt(t.ch)||"\n",m=ne(g,f)?"w":h&&"\n"==g?"n":!h||/\s/.test(g)?null:"p";if(!h||p||m||(m="s"),d&&d!=m){n<0&&(n=1,c(),t.sticky="after");break}if(m&&(d=m),n>0&&!c(!p))break}var v=Zs(e,t,s,o,!0);return at(s,v)&&(v.hitSide=!0),v}function qa(e,t,n,i){var r,s,o=e.doc,a=t.left;if("page"==i){var l=Math.min(e.display.wrapper.clientHeight,window.innerHeight||document.documentElement.clientHeight),u=Math.max(l-.5*Ni(e.display),3);r=(n>0?t.bottom:t.top)+n*u}else"line"==i&&(r=n>0?t.bottom+3:t.top-3);for(;(s=wi(e,a,r)).outside;){if(n<0?r<=0:r>=o.height){s.hitSide=!0;break}r+=5*n}return s}var _a=function(e){this.cm=e,this.lastAnchorNode=this.lastAnchorOffset=this.lastFocusNode=this.lastFocusOffset=null,this.polling=new F,this.composing=null,this.gracePeriod=!1,this.readDOMTimeout=null};function $a(e,t){var n=ti(e,t.line);if(!n||n.hidden)return null;var i=qe(e.doc,t.line),r=_n(n,i,t.line),s=he(i,e.doc.direction),o="left";s&&(o=ce(s,t.ch)%2?"right":"left");var a=oi(r.map,t.ch,o);return a.offset="right"==a.collapse?a.end:a.start,a}function el(e){for(var t=e;t;t=t.parentNode)if(/CodeMirror-gutter-wrapper/.test(t.className))return!0;return!1}function tl(e,t){return t&&(e.bad=!0),e}function nl(e,t,n,i,r){var s="",o=!1,a=e.doc.lineSeparator(),l=!1;function u(e){return function(t){return t.id==e}}function c(){o&&(s+=a,l&&(s+=a),o=l=!1)}function d(e){e&&(c(),s+=e)}function h(t){if(1==t.nodeType){var n=t.getAttribute("cm-text");if(n)return void d(n);var s,f=t.getAttribute("cm-marker");if(f){var p=e.findMarks(st(i,0),st(r+1,0),u(+f));return void(p.length&&(s=p[0].find(0))&&d(_e(e.doc,s.from,s.to).join(a)))}if("false"==t.getAttribute("contenteditable"))return;var g=/^(pre|div|p|li|table|br)$/i.test(t.nodeName);if(!/^br$/i.test(t.nodeName)&&0==t.textContent.length)return;g&&c();for(var m=0;m<t.childNodes.length;m++)h(t.childNodes[m]);/^(pre|p)$/i.test(t.nodeName)&&(l=!0),g&&(o=!0)}else 3==t.nodeType&&d(t.nodeValue.replace(/\u200b/g,"").replace(/\u00a0/g," "))}for(;h(t),t!=n;)t=t.nextSibling,l=!1;return s}function il(e,t,n){var i;if(t==e.display.lineDiv){if(!(i=e.display.lineDiv.childNodes[n]))return tl(e.clipPos(st(e.display.viewTo-1)),!0);t=null,n=0}else for(i=t;;i=i.parentNode){if(!i||i==e.display.lineDiv)return null;if(i.parentNode&&i.parentNode==e.display.lineDiv)break}for(var r=0;r<e.display.view.length;r++){var s=e.display.view[r];if(s.node==i)return rl(s,t,n)}}function rl(e,t,n){var i=e.text.firstChild,r=!1;if(!t||!D(i,t))return tl(st(tt(e.line),0),!0);if(t==i&&(r=!0,t=i.childNodes[n],n=0,!t)){var s=e.rest?J(e.rest):e.line;return tl(st(tt(s),s.text.length),r)}var o=3==t.nodeType?t:null,a=t;for(o||1!=t.childNodes.length||3!=t.firstChild.nodeType||(o=t.firstChild,n&&(n=o.nodeValue.length));a.parentNode!=i;)a=a.parentNode;var l=e.measure,u=l.maps;function c(t,n,i){for(var r=-1;r<(u?u.length:0);r++)for(var s=r<0?l.map:u[r],o=0;o<s.length;o+=3){var a=s[o+2];if(a==t||a==n){var c=tt(r<0?e.line:e.rest[r]),d=s[o]+i;return(i<0||a!=t)&&(d=s[o+(i?1:0)]),st(c,d)}}}var d=c(o,a,n);if(d)return tl(d,r);for(var h=a.nextSibling,f=o?o.nodeValue.length-n:0;h;h=h.nextSibling){if(d=c(h,h.firstChild,0))return tl(st(d.line,d.ch-f),r);f+=h.textContent.length}for(var p=a.previousSibling,g=n;p;p=p.previousSibling){if(d=c(p,p.firstChild,-1))return tl(st(d.line,d.ch+g),r);g+=p.textContent.length}}_a.prototype.init=function(e){var t=this,n=this,i=n.cm,r=n.div=e.lineDiv;function s(e){for(var t=e.target;t;t=t.parentNode){if(t==r)return!0;if(/\bCodeMirror-(?:line)?widget\b/.test(t.className))break}return!1}function o(e){if(s(e)&&!Ae(i,e)){if(i.somethingSelected())Xa({lineWise:!1,text:i.getSelections()}),"cut"==e.type&&i.replaceSelection("",null,"cut");else{if(!i.options.lineWiseCopyCut)return;var t=Qa(i);Xa({lineWise:!0,text:t.text}),"cut"==e.type&&i.operation((function(){i.setSelections(t.ranges,0,G),i.replaceSelection("",null,"cut")}))}if(e.clipboardData){e.clipboardData.clearData();var o=Ua.text.join("\n");if(e.clipboardData.setData("Text",o),e.clipboardData.getData("Text")==o)return void e.preventDefault()}var a=Ya(),l=a.firstChild;i.display.lineSpace.insertBefore(a,i.display.lineSpace.firstChild),l.value=Ua.text.join("\n");var u=document.activeElement;O(l),setTimeout((function(){i.display.lineSpace.removeChild(a),u.focus(),u==r&&n.showPrimarySelection()}),50)}}Za(r,i.options.spellcheck,i.options.autocorrect,i.options.autocapitalize),pe(r,"paste",(function(e){!s(e)||Ae(i,e)||Va(e,i)||a<=11&&setTimeout(Ir(i,(function(){return t.updateFromDOM()})),20)})),pe(r,"compositionstart",(function(e){t.composing={data:e.data,done:!1}})),pe(r,"compositionupdate",(function(e){t.composing||(t.composing={data:e.data,done:!1})})),pe(r,"compositionend",(function(e){t.composing&&(e.data!=t.composing.data&&t.readFromDOMSoon(),t.composing.done=!0)})),pe(r,"touchstart",(function(){return n.forceCompositionEnd()})),pe(r,"input",(function(){t.composing||t.readFromDOMSoon()})),pe(r,"copy",o),pe(r,"cut",o)},_a.prototype.screenReaderLabelChanged=function(e){e?this.div.setAttribute("aria-label",e):this.div.removeAttribute("aria-label")},_a.prototype.prepareSelection=function(){var e=Vi(this.cm,!1);return e.focus=document.activeElement==this.div,e},_a.prototype.showSelection=function(e,t){e&&this.cm.display.view.length&&((e.focus||t)&&this.showPrimarySelection(),this.showMultipleSelections(e))},_a.prototype.getSelection=function(){return this.cm.display.wrapper.ownerDocument.getSelection()},_a.prototype.showPrimarySelection=function(){var e=this.getSelection(),t=this.cm,i=t.doc.sel.primary(),r=i.from(),s=i.to();if(t.display.viewTo==t.display.viewFrom||r.line>=t.display.viewTo||s.line<t.display.viewFrom)e.removeAllRanges();else{var o=il(t,e.anchorNode,e.anchorOffset),a=il(t,e.focusNode,e.focusOffset);if(!o||o.bad||!a||a.bad||0!=ot(ct(o,a),r)||0!=ot(ut(o,a),s)){var l=t.display.view,u=r.line>=t.display.viewFrom&&$a(t,r)||{node:l[0].measure.map[2],offset:0},c=s.line<t.display.viewTo&&$a(t,s);if(!c){var d=l[l.length-1].measure,h=d.maps?d.maps[d.maps.length-1]:d.map;c={node:h[h.length-1],offset:h[h.length-2]-h[h.length-3]}}if(u&&c){var f,p=e.rangeCount&&e.getRangeAt(0);try{f=E(u.node,u.offset,c.offset,c.node)}catch(e){}f&&(!n&&t.state.focused?(e.collapse(u.node,u.offset),f.collapsed||(e.removeAllRanges(),e.addRange(f))):(e.removeAllRanges(),e.addRange(f)),p&&null==e.anchorNode?e.addRange(p):n&&this.startGracePeriod()),this.rememberSelection()}else e.removeAllRanges()}}},_a.prototype.startGracePeriod=function(){var e=this;clearTimeout(this.gracePeriod),this.gracePeriod=setTimeout((function(){e.gracePeriod=!1,e.selectionChanged()&&e.cm.operation((function(){return e.cm.curOp.selectionChanged=!0}))}),20)},_a.prototype.showMultipleSelections=function(e){P(this.cm.display.cursorDiv,e.cursors),P(this.cm.display.selectionDiv,e.selection)},_a.prototype.rememberSelection=function(){var e=this.getSelection();this.lastAnchorNode=e.anchorNode,this.lastAnchorOffset=e.anchorOffset,this.lastFocusNode=e.focusNode,this.lastFocusOffset=e.focusOffset},_a.prototype.selectionInEditor=function(){var e=this.getSelection();if(!e.rangeCount)return!1;var t=e.getRangeAt(0).commonAncestorContainer;return D(this.div,t)},_a.prototype.focus=function(){"nocursor"!=this.cm.options.readOnly&&(this.selectionInEditor()&&document.activeElement==this.div||this.showSelection(this.prepareSelection(),!0),this.div.focus())},_a.prototype.blur=function(){this.div.blur()},_a.prototype.getField=function(){return this.div},_a.prototype.supportsTouch=function(){return!0},_a.prototype.receivedFocus=function(){var e=this;function t(){e.cm.state.focused&&(e.pollSelection(),e.polling.set(e.cm.options.pollInterval,t))}this.selectionInEditor()?this.pollSelection():Dr(this.cm,(function(){return e.cm.curOp.selectionChanged=!0})),this.polling.set(this.cm.options.pollInterval,t)},_a.prototype.selectionChanged=function(){var e=this.getSelection();return e.anchorNode!=this.lastAnchorNode||e.anchorOffset!=this.lastAnchorOffset||e.focusNode!=this.lastFocusNode||e.focusOffset!=this.lastFocusOffset},_a.prototype.pollSelection=function(){if(null==this.readDOMTimeout&&!this.gracePeriod&&this.selectionChanged()){var e=this.getSelection(),t=this.cm;if(m&&c&&this.cm.display.gutterSpecs.length&&el(e.anchorNode))return this.cm.triggerOnKeyDown({type:"keydown",keyCode:8,preventDefault:Math.abs}),this.blur(),void this.focus();if(!this.composing){this.rememberSelection();var n=il(t,e.anchorNode,e.anchorOffset),i=il(t,e.focusNode,e.focusOffset);n&&i&&Dr(t,(function(){Us(t.doc,as(n,i),G),(n.bad||i.bad)&&(t.curOp.selectionChanged=!0)}))}}},_a.prototype.pollContent=function(){null!=this.readDOMTimeout&&(clearTimeout(this.readDOMTimeout),this.readDOMTimeout=null);var e,t,n,i=this.cm,r=i.display,s=i.doc.sel.primary(),o=s.from(),a=s.to();if(0==o.ch&&o.line>i.firstLine()&&(o=st(o.line-1,qe(i.doc,o.line-1).length)),a.ch==qe(i.doc,a.line).text.length&&a.line<i.lastLine()&&(a=st(a.line+1,0)),o.line<r.viewFrom||a.line>r.viewTo-1)return!1;o.line==r.viewFrom||0==(e=zi(i,o.line))?(t=tt(r.view[0].line),n=r.view[0].node):(t=tt(r.view[e].line),n=r.view[e-1].node.nextSibling);var l,u,c=zi(i,a.line);if(c==r.view.length-1?(l=r.viewTo-1,u=r.lineDiv.lastChild):(l=tt(r.view[c+1].line)-1,u=r.view[c+1].node.previousSibling),!n)return!1;for(var d=i.doc.splitLines(nl(i,n,u,t,l)),h=_e(i.doc,st(t,0),st(l,qe(i.doc,l).text.length));d.length>1&&h.length>1;)if(J(d)==J(h))d.pop(),h.pop(),l--;else{if(d[0]!=h[0])break;d.shift(),h.shift(),t++}for(var f=0,p=0,g=d[0],m=h[0],v=Math.min(g.length,m.length);f<v&&g.charCodeAt(f)==m.charCodeAt(f);)++f;for(var A=J(d),x=J(h),y=Math.min(A.length-(1==d.length?f:0),x.length-(1==h.length?f:0));p<y&&A.charCodeAt(A.length-p-1)==x.charCodeAt(x.length-p-1);)++p;if(1==d.length&&1==h.length&&t==o.line)for(;f&&f>o.ch&&A.charCodeAt(A.length-p-1)==x.charCodeAt(x.length-p-1);)f--,p++;d[d.length-1]=A.slice(0,A.length-p).replace(/^\u200b+/,""),d[0]=d[0].slice(f).replace(/\u200b+$/,"");var b=st(t,f),w=st(l,h.length?J(h).length-p:0);return d.length>1||d[0]||ot(b,w)?(io(i.doc,d,b,w,"+input"),!0):void 0},_a.prototype.ensurePolled=function(){this.forceCompositionEnd()},_a.prototype.reset=function(){this.forceCompositionEnd()},_a.prototype.forceCompositionEnd=function(){this.composing&&(clearTimeout(this.readDOMTimeout),this.composing=null,this.updateFromDOM(),this.div.blur(),this.div.focus())},_a.prototype.readFromDOMSoon=function(){var e=this;null==this.readDOMTimeout&&(this.readDOMTimeout=setTimeout((function(){if(e.readDOMTimeout=null,e.composing){if(!e.composing.done)return;e.composing=null}e.updateFromDOM()}),80))},_a.prototype.updateFromDOM=function(){var e=this;!this.cm.isReadOnly()&&this.pollContent()||Dr(this.cm,(function(){return Ri(e.cm)}))},_a.prototype.setUneditable=function(e){e.contentEditable="false"},_a.prototype.onKeyPress=function(e){0==e.charCode||this.composing||(e.preventDefault(),this.cm.isReadOnly()||Ir(this.cm,Ga)(this.cm,String.fromCharCode(null==e.charCode?e.keyCode:e.charCode),0))},_a.prototype.readOnlyChanged=function(e){this.div.contentEditable=String("nocursor"!=e)},_a.prototype.onContextMenu=function(){},_a.prototype.resetPosition=function(){},_a.prototype.needsContentAttribute=!0;var sl=function(e){this.cm=e,this.prevInput="",this.pollingFast=!1,this.polling=new F,this.hasSelection=!1,this.composing=null};function ol(e,t){if((t=t?R(t):{}).value=e.value,!t.tabindex&&e.tabIndex&&(t.tabindex=e.tabIndex),!t.placeholder&&e.placeholder&&(t.placeholder=e.placeholder),null==t.autofocus){var n=I();t.autofocus=n==e||null!=e.getAttribute("autofocus")&&n==document.body}function i(){e.value=a.getValue()}var r;if(e.form&&(pe(e.form,"submit",i),!t.leaveSubmitMethodAlone)){var s=e.form;r=s.submit;try{var o=s.submit=function(){i(),s.submit=r,s.submit(),s.submit=o}}catch(e){}}t.finishInit=function(n){n.save=i,n.getTextArea=function(){return e},n.toTextArea=function(){n.toTextArea=isNaN,i(),e.parentNode.removeChild(n.getWrapperElement()),e.style.display="",e.form&&(me(e.form,"submit",i),t.leaveSubmitMethodAlone||"function"!=typeof e.form.submit||(e.form.submit=r))}},e.style.display="none";var a=Ra((function(t){return e.parentNode.insertBefore(t,e.nextSibling)}),t);return a}function al(e){e.off=me,e.on=pe,e.wheelEventPixels=ns,e.Doc=Co,e.splitLines=je,e.countColumn=k,e.findColumn=Q,e.isWordChar=te,e.Pass=X,e.signal=ve,e.Line=un,e.changeEnd=ls,e.scrollbarModel=yr,e.Pos=st,e.cmpPos=ot,e.modes=Fe,e.mimeModes=He,e.resolveMode=Ge,e.getMode=Ve,e.modeExtensions=We,e.extendMode=Qe,e.copyState=Ze,e.startState=Je,e.innerMode=Ye,e.commands=qo,e.keyMap=ko,e.keyName=Vo,e.isModifierKey=Xo,e.lookupKey=Uo,e.normalizeKeyMap=Ho,e.StringStream=Ke,e.SharedTextMarker=vo,e.TextMarker=go,e.LineWidget=co,e.e_preventDefault=we,e.e_stopPropagation=Ce,e.e_stop=Ee,e.addClass=L,e.contains=D,e.rmClass=T,e.keyNames=jo}sl.prototype.init=function(e){var t=this,n=this,i=this.cm;this.createField(e);var r=this.textarea;function s(e){if(!Ae(i,e)){if(i.somethingSelected())Xa({lineWise:!1,text:i.getSelections()});else{if(!i.options.lineWiseCopyCut)return;var t=Qa(i);Xa({lineWise:!0,text:t.text}),"cut"==e.type?i.setSelections(t.ranges,null,G):(n.prevInput="",r.value=t.text.join("\n"),O(r))}"cut"==e.type&&(i.state.cutIncoming=+new Date)}}e.wrapper.insertBefore(this.wrapper,e.wrapper.firstChild),g&&(r.style.width="0px"),pe(r,"input",(function(){o&&a>=9&&t.hasSelection&&(t.hasSelection=null),n.poll()})),pe(r,"paste",(function(e){Ae(i,e)||Va(e,i)||(i.state.pasteIncoming=+new Date,n.fastPoll())})),pe(r,"cut",s),pe(r,"copy",s),pe(e.scroller,"paste",(function(t){if(!Vn(e,t)&&!Ae(i,t)){if(!r.dispatchEvent)return i.state.pasteIncoming=+new Date,void n.focus();var s=new Event("paste");s.clipboardData=t.clipboardData,r.dispatchEvent(s)}})),pe(e.lineSpace,"selectstart",(function(t){Vn(e,t)||we(t)})),pe(r,"compositionstart",(function(){var e=i.getCursor("from");n.composing&&n.composing.range.clear(),n.composing={start:e,range:i.markText(e,i.getCursor("to"),{className:"CodeMirror-composing"})}})),pe(r,"compositionend",(function(){n.composing&&(n.poll(),n.composing.range.clear(),n.composing=null)}))},sl.prototype.createField=function(e){this.wrapper=Ya(),this.textarea=this.wrapper.firstChild},sl.prototype.screenReaderLabelChanged=function(e){e?this.textarea.setAttribute("aria-label",e):this.textarea.removeAttribute("aria-label")},sl.prototype.prepareSelection=function(){var e=this.cm,t=e.display,n=e.doc,i=Vi(e);if(e.options.moveInputWithCursor){var r=xi(e,n.sel.primary().head,"div"),s=t.wrapper.getBoundingClientRect(),o=t.lineDiv.getBoundingClientRect();i.teTop=Math.max(0,Math.min(t.wrapper.clientHeight-10,r.top+o.top-s.top)),i.teLeft=Math.max(0,Math.min(t.wrapper.clientWidth-10,r.left+o.left-s.left))}return i},sl.prototype.showSelection=function(e){var t=this.cm.display;P(t.cursorDiv,e.cursors),P(t.selectionDiv,e.selection),null!=e.teTop&&(this.wrapper.style.top=e.teTop+"px",this.wrapper.style.left=e.teLeft+"px")},sl.prototype.reset=function(e){if(!this.contextMenuPending&&!this.composing){var t=this.cm;if(t.somethingSelected()){this.prevInput="";var n=t.getSelection();this.textarea.value=n,t.state.focused&&O(this.textarea),o&&a>=9&&(this.hasSelection=n)}else e||(this.prevInput=this.textarea.value="",o&&a>=9&&(this.hasSelection=null))}},sl.prototype.getField=function(){return this.textarea},sl.prototype.supportsTouch=function(){return!1},sl.prototype.focus=function(){if("nocursor"!=this.cm.options.readOnly&&(!v||I()!=this.textarea))try{this.textarea.focus()}catch(e){}},sl.prototype.blur=function(){this.textarea.blur()},sl.prototype.resetPosition=function(){this.wrapper.style.top=this.wrapper.style.left=0},sl.prototype.receivedFocus=function(){this.slowPoll()},sl.prototype.slowPoll=function(){var e=this;this.pollingFast||this.polling.set(this.cm.options.pollInterval,(function(){e.poll(),e.cm.state.focused&&e.slowPoll()}))},sl.prototype.fastPoll=function(){var e=!1,t=this;function n(){t.poll()||e?(t.pollingFast=!1,t.slowPoll()):(e=!0,t.polling.set(60,n))}t.pollingFast=!0,t.polling.set(20,n)},sl.prototype.poll=function(){var e=this,t=this.cm,n=this.textarea,i=this.prevInput;if(this.contextMenuPending||!t.state.focused||Oe(n)&&!i&&!this.composing||t.isReadOnly()||t.options.disableInput||t.state.keySeq)return!1;var r=n.value;if(r==i&&!t.somethingSelected())return!1;if(o&&a>=9&&this.hasSelection===r||A&&/[\uf700-\uf7ff]/.test(r))return t.display.input.reset(),!1;if(t.doc.sel==t.display.selForContextMenu){var s=r.charCodeAt(0);if(8203!=s||i||(i="​"),8666==s)return this.reset(),this.cm.execCommand("undo")}for(var l=0,u=Math.min(i.length,r.length);l<u&&i.charCodeAt(l)==r.charCodeAt(l);)++l;return Dr(t,(function(){Ga(t,r.slice(l),i.length-l,null,e.composing?"*compose":null),r.length>1e3||r.indexOf("\n")>-1?n.value=e.prevInput="":e.prevInput=r,e.composing&&(e.composing.range.clear(),e.composing.range=t.markText(e.composing.start,t.getCursor("to"),{className:"CodeMirror-composing"}))})),!0},sl.prototype.ensurePolled=function(){this.pollingFast&&this.poll()&&(this.pollingFast=!1)},sl.prototype.onKeyPress=function(){o&&a>=9&&(this.hasSelection=null),this.fastPoll()},sl.prototype.onContextMenu=function(e){var t=this,n=t.cm,i=n.display,r=t.textarea;t.contextMenuPending&&t.contextMenuPending();var s=Oi(n,e),u=i.scroller.scrollTop;if(s&&!d){n.options.resetSelectionOnContextMenu&&-1==n.doc.sel.contains(s)&&Ir(n,Us)(n.doc,as(s),G);var c,h=r.style.cssText,f=t.wrapper.style.cssText,p=t.wrapper.offsetParent.getBoundingClientRect();if(t.wrapper.style.cssText="position: static",r.style.cssText="position: absolute; width: 30px; height: 30px;\n      top: "+(e.clientY-p.top-5)+"px; left: 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1.8-.85-2.31-4.98c-.24-.5-.02-1.1.48-1.33l.28-.08 2.3-.45L8 5.12V15.9l1.82-1.47.25-.16m3.57 7.7a.99.99 0 01-1.33-.47l-2.18-4.74-2.51 2.02c-.17.14-.38.22-.62.22a1 1 0 01-1-1V3a1 1 0 011-1c.24 0 .47.09.64.23l.01-.01 11.49 9.64a1.001 1.001 0 01-.44 1.75l-3.16.62 2.2 4.73c.26.5.02 1.09-.48 1.32l-3.62 1.69z"/></svg>',"select"),this.addActionButton(n,'<svg viewBox="0 0 24 24"><path d="M9 3v1H4v2h1v13a2 2 0 002 2h10a2 2 0 002-2V6h1V4h-5V3H9M7 6h10v13H7V6m2 2v9h2V8H9m4 0v9h2V8h-2z"/></svg>',"delete"),this.uiStyleSettings.clearButtonVisible&&this.addActionButton(n,'<svg viewBox="0 0 24 24"><path d="M19.36 2.72l1.42 1.42-5.72 5.71c1.07 1.54 1.22 3.39.32 4.59L9.06 8.12c1.2-.9 3.05-.75 4.59.32l5.71-5.72M5.93 17.57c-2.01-2.01-3.24-4.41-3.58-6.65l4.88-2.09 7.44 7.44-2.09 4.88c-2.24-.34-4.64-1.57-6.65-3.58z"/></svg>',"clear"),this.uiStyleSettings.undoButtonVisible&&this.addActionButton(n,'<svg viewBox="0 0 24 24"><path d="M12.5 8c-2.65 0-5.05 1-6.9 2.6L2 7v9h9l-3.62-3.62c1.39-1.16 3.16-1.88 5.12-1.88 3.54 0 6.55 2.31 7.6 5.5l2.37-.78C21.08 11.03 17.15 8 12.5 8z"/></svg>',"undo"),this.uiStyleSettings.redoButtonVisible&&this.addActionButton(n,'<svg viewBox="0 0 24 24"><path d="M18.4 10.6C16.55 9 14.15 8 11.5 8c-4.65 0-8.58 3.03-9.96 7.22L3.9 16a8.002 8.002 0 017.6-5.5c1.95 0 3.73.72 5.12 1.88L13 16h9V7l-3.6 3.6z"/></svg>',"redo"),this.uiStyleSettings.zoomButtonVisible&&this.addActionButton(n,'<svg viewBox="0 0 24 24"><path d="M15.5 14l5 5-1.5 1.5-5-5v-.79l-.27-.28A6.471 6.471 0 019.5 16 6.5 6.5 0 013 9.5 6.5 6.5 0 019.5 3 6.5 6.5 0 0116 9.5c0 1.61-.59 3.09-1.57 4.23l.28.27h.79m-6 0C12 14 14 12 14 9.5S12 5 9.5 5 5 7 5 9.5 7 14 9.5 14m2.5-4h-2v2H9v-2H7V9h2V7h1v2h2v1z"/></svg>',"zoom"),this.uiStyleSettings.zoomButtonVisible&&this.uiStyleSettings.zoomOutButtonVisible&&this.addActionButton(n,'<svg viewBox="0 0 24 24"><path d="M15.5 14h-.79l-.28-.27A6.471 6.471 0 0016 9.5 6.5 6.5 0 009.5 3 6.5 6.5 0 003 9.5 6.5 6.5 0 009.5 16c1.61 0 3.09-.59 4.23-1.57l.27.28v.79l5 5 1.5-1.5-5-5m-6 0C7 14 5 12 5 9.5S7 5 9.5 5 14 7 14 9.5 12 14 9.5 14M7 9h5v1H7V9z"/></svg>',"zoom-out"),this.uiStyleSettings.notesButtonVisible&&this.addActionButton(n,'<svg viewBox="0 0 24 24"><path d="M18.13 12l1.26-1.26c.44-.44 1-.68 1.61-.74V9l-6-6H5c-1.11 0-2 .89-2 2v14a2 2 0 002 2h6v-1.87l.13-.13H5V5h7v7h6.13M14 4.5l5.5 5.5H14V4.5m5.13 9.33l2.04 2.04L15.04 22H13v-2.04l6.13-6.13m3.72.36l-.98.98-2.04-2.04.98-.98c.19-.2.52-.2.72 0l1.32 1.32c.2.2.2.53 0 .72z"/></svg>',"notes"),this.markerButtonBlock=document.createElement("div"),this.markerButtonBlock.className=this.toolbarBlockStyleClass.name,this.markerButtonBlock.style.flexGrow="2",this.markerButtonBlock.style.textAlign="center",this.uiContainer.appendChild(this.markerButtonBlock),this.markerButtonOverflowBlock=document.createElement("div"),this.markerButtonOverflowBlock.className=this.toolbarOverflowBlockStyleClass.name+" "+(this.uiStyleSettings.toolbarOverflowBlockStyleColorsClassName?this.uiStyleSettings.toolbarOverflowBlockStyleColorsClassName:this.toolbarOverflowBlockStyleColorsClass.name),this.markerButtonOverflowBlock.style.display="none",this.uiContainer.appendChild(this.markerButtonOverflowBlock),this.markerItems&&(this.markerItems.forEach((function(e){var n=document.createElement("div");n.className=""+t.toolbarButtonStyleClass.name,n.setAttribute("data-type-name",e.typeName),n.innerHTML=e.icon,n.addEventListener("click",(function(){t.markerToolbarButtonClicked(n,e)})),t.buttons.push(n),t.markerButtons.push(n)})),this.overflowButton=document.createElement("div"),this.overflowButton.className=this.toolbarButtonStyleClass.name+" "+(this.uiStyleSettings.toolbarButtonStyleColorsClassName?this.uiStyleSettings.toolbarButtonStyleColorsClassName:this.toolbarButtonStyleColorsClass.name),this.overflowButton.innerHTML='<svg viewBox="0 0 24 24"><path d="M12 16a2 2 0 012 2 2 2 0 01-2 2 2 2 0 01-2-2 2 2 0 012-2m0-6a2 2 0 012 2 2 2 0 01-2 2 2 2 0 01-2-2 2 2 0 012-2m0-6a2 2 0 012 2 2 2 0 01-2 2 2 2 0 01-2-2 2 2 0 012-2z"/></svg>',this.overflowButton.addEventListener("click",this.overflowButtonClicked),this.markerButtonBlock.appendChild(this.overflowButton));var i=document.createElement("div");i.className=this.toolbarBlockStyleClass.name,i.style.whiteSpace="nowrap",i.style.display=!1!==this.uiStyleSettings.resultButtonBlockVisible?"":"none",this.uiContainer.appendChild(i),this.addActionButton(i,'<svg viewBox="0 0 24 24"><path d="M9 20.42l-6.21-6.21 2.83-2.83L9 14.77l9.88-9.89 2.83 2.83L9 20.42z"/></svg>',"render"),this.addActionButton(i,'<svg viewBox="0 0 24 24"><path d="M20 6.91L17.09 4 12 9.09 6.91 4 4 6.91 9.09 12 4 17.09 6.91 20 12 14.91 17.09 20 20 17.09 14.91 12 20 6.91z"/></svg>',"close"),this.markerjsContainer.appendChild(this.uiContainer),this.setSelectMode(),this.setCurrentMarker(),this.adjustLayout()},e.prototype.addButtonClickListener=function(e){this.buttonClickListeners.push(e)},e.prototype.removeButtonClickListener=function(e){this.buttonClickListeners.indexOf(e)>-1&&this.buttonClickListeners.splice(this.buttonClickListeners.indexOf(e),1)},e.prototype.setSelectMode=function(){this.resetButtonStyles(),this.setActiveButton(this.buttons[0])},e.prototype.adjustLayout=function(){if(this.markerButtons&&this.markerButtons.length>0){var e=Math.floor(this.markerButtonBlock.clientWidth/this.uiStyleSettings.toolbarHeight)-1;this.markerButtonBlock.innerHTML="",this.markerButtonOverflowBlock.innerHTML="";for(var t=0;t<this.markerButtons.length;t++)t<e||t===e&&this.markerButtons.length-1===e?this.markerButtonBlock.appendChild(this.markerButtons[t]):(t===e&&this.markerButtonBlock.appendChild(this.overflowButton),this.markerButtonOverflowBlock.appendChild(this.markerButtons[t]))}},e.prototype.overflowButtonClicked=function(){"none"!==this.markerButtonOverflowBlock.style.display?(this.markerButtonOverflowBlock.className=this.markerButtonOverflowBlock.className.replace(this.styles.fadeInAnimationClassName,""),this.markerButtonOverflowBlock.style.display="none"):(this.markerButtonOverflowBlock.className+=" "+this.styles.fadeInAnimationClassName,this.markerButtonOverflowBlock.style.top=this.uiContainer.offsetTop+this.overflowButton.offsetHeight+"px",this.markerButtonOverflowBlock.style.right=this.uiContainer.offsetWidth-this.overflowButton.offsetLeft-this.overflowButton.offsetWidth+2*this.uiContainer.offsetLeft+"px",this.markerButtonOverflowBlock.style.display="inline-block")},e.prototype.resetButtonStyles=function(){var e=this;this.buttons.forEach((function(t){t.className=t.className.replace(e.uiStyleSettings.toolbarButtonStyleColorsClassName?e.uiStyleSettings.toolbarButtonStyleColorsClassName:e.toolbarButtonStyleColorsClass.name,"").trim(),t.className=t.className.replace(e.uiStyleSettings.toolbarActiveButtonStyleColorsClassName?e.uiStyleSettings.toolbarActiveButtonStyleColorsClassName:e.toolbarActiveButtonStyleColorsClass.name,"").trim(),t.className+=" "+(e.uiStyleSettings.toolbarButtonStyleColorsClassName?e.uiStyleSettings.toolbarButtonStyleColorsClassName:e.toolbarButtonStyleColorsClass.name)}))},e.prototype.addActionButton=function(e,t,n){var i=this,r=document.createElement("div");switch(r.className=""+this.toolbarButtonStyleClass.name,r.innerHTML=t,r.setAttribute("data-action",n),r.addEventListener("click",(function(){i.actionToolbarButtonClicked(r,n)})),n){case"select":case"undo":case"redo":r.style.fill=this.uiStyleSettings.selectButtonColor;break;case"delete":case"clear":r.style.fill=this.uiStyleSettings.deleteButtonColor;break;case"render":r.style.fill=this.uiStyleSettings.okButtonColor;break;case"close":r.style.fill=this.uiStyleSettings.closeButtonColor}e.appendChild(r),this.buttons.push(r)},e.prototype.addStyles=function(){this.toolbarStyleClass=this.styles.addClass(new p("toolbar","\n      width: 100%;\n      flex-shrink: 0;\n      display: flex;\n      flex-direction: row;\n      justify-content: space-between;      \n      height: "+this.uiStyleSettings.toolbarHeight+"px;\n      box-sizing: content-box;\n      "+("inline"===this.displayMode?"border-top-left-radius: "+Math.round(this.uiStyleSettings.toolbarHeight/10)+"px;":"")+"\n      "+("inline"===this.displayMode?"border-top-right-radius: "+Math.round(this.uiStyleSettings.toolbarHeight/10)+"px;":"")+"\n      overflow: hidden;\n    ")),this.toolbarStyleColorsClass=this.styles.addClass(new p("toolbar_colors","\n      background-color: "+this.uiStyleSettings.toolbarBackgroundColor+";\n      box-shadow: 0px 3px rgba(33, 33, 33, 0.1);\n    ")),this.toolbarBlockStyleClass=this.styles.addClass(new p("toolbar-block","\n        display: inline-block;\n        box-sizing: content-box;\n    ")),this.toolbarOverflowBlockStyleClass=this.styles.addClass(new p("toolbar-overflow-block","\n        position: absolute;\n        top: "+this.uiStyleSettings.toolbarHeight+"px;\n        max-width: "+2*this.uiStyleSettings.toolbarHeight+"px;\n        z-index: 10;\n        box-sizing: content-box;\n      ")),this.toolbarOverflowBlockStyleColorsClass=this.styles.addClass(new p("toolbar-overflow-block_colors","\n        background-color: "+this.uiStyleSettings.toolbarBackgroundColor+";\n      "));var e=this.uiStyleSettings.toolbarHeight/4;this.toolbarButtonStyleClass=this.styles.addClass(new p("toolbar_button","\n      display: inline-block;\n      width: "+(this.uiStyleSettings.toolbarHeight-2*e)+"px;\n      height: "+(this.uiStyleSettings.toolbarHeight-2*e)+"px;\n      padding: "+e+"px;\n      box-sizing: content-box;\n    ")),this.toolbarButtonStyleColorsClass=this.styles.addClass(new p("toolbar_button_colors","\n      fill: "+this.uiStyleSettings.toolbarColor+";\n    ")),this.toolbarActiveButtonStyleColorsClass=this.styles.addClass(new p("toolbar_active_button","\n      fill: "+this.uiStyleSettings.toolbarColor+";\n      background-color: "+this.uiStyleSettings.toolbarBackgroundHoverColor+"\n    ")),this.styles.addRule(new f("."+this.toolbarButtonStyleClass.name+" svg","\n      height: "+this.uiStyleSettings.toolbarHeight/2+"px;\n    ")),this.styles.addRule(new f("."+this.toolbarButtonStyleColorsClass.name+":hover","\n        background-color: "+this.uiStyleSettings.toolbarBackgroundHoverColor+"\n    "))},e.prototype.markerToolbarButtonClicked=function(e,t){this.setActiveButton(e),this.buttonClickListeners&&this.buttonClickListeners.length>0&&this.buttonClickListeners.forEach((function(e){return e("marker",t)})),this.markerButtonOverflowBlock.style.display="none"},e.prototype.actionToolbarButtonClicked=function(e,t){this.buttonClickListeners&&this.buttonClickListeners.length>0&&this.buttonClickListeners.forEach((function(e){return e("action",t)})),this.markerButtonOverflowBlock.style.display="none",this.setActiveButton(this.buttons[0])},e.prototype.setActiveButton=function(e){this.resetButtonStyles(),e.className=e.className.replace(this.uiStyleSettings.toolbarButtonStyleColorsClassName?this.uiStyleSettings.toolbarButtonStyleColorsClassName:this.toolbarButtonStyleColorsClass.name,"").trim(),e.className+=" "+(this.uiStyleSettings.toolbarActiveButtonStyleColorsClassName?this.uiStyleSettings.toolbarActiveButtonStyleColorsClassName:this.toolbarActiveButtonStyleColorsClass.name)},e.prototype.setActiveMarkerButton=function(e){var t=this.markerButtons.find((function(t){return t.getAttribute("data-type-name")===e}));t&&this.setActiveButton(t)},e.prototype.setCurrentMarker=function(e){var t=this;this.currentMarker=e,this.buttons.filter((function(e){return/delete|notes/.test(e.getAttribute("data-action"))})).forEach((function(e){void 0===t.currentMarker?(e.style.fillOpacity="0.4",e.style.pointerEvents="none"):(e.style.fillOpacity="1",e.style.pointerEvents="all")}))},e}(),m=function(){function e(e,t,n,i){this.panels=[],this.panelButtons=[],this.markerjsContainer=e,this.displayMode=t,this.uiStyleSettings=n,this.styles=i,this.panelButtonClick=this.panelButtonClick.bind(this),this.addStyles()}return e.prototype.addStyles=function(){var e;this.toolboxStyleClass=this.styles.addClass(new p("toolbox","\n      width: 100%;\n      flex-shrink: 0;\n      display: flex;\n      flex-direction: column;\n      font-family: sans-serif;\n      "+("popup"===this.displayMode?"height:"+2.5*this.uiStyleSettings.toolbarHeight+"px;":"")+"\n      box-sizing: content-box;\n      "+("popup"===this.displayMode?"background-color: "+this.uiStyleSettings.canvasBackgroundColor+";":"")+"\n      "+("inline"===this.displayMode?"border-bottom-left-radius: "+Math.round(this.uiStyleSettings.toolbarHeight/10)+"px;":"")+"\n      "+("inline"===this.displayMode?"border-bottom-right-radius: "+Math.round(this.uiStyleSettings.toolbarHeight/10)+"px;":"")+"\n      overflow: hidden;\n    ")),this.toolboxStyleColorsClass=this.styles.addClass(new p("toolbox_colors","\n      color: "+this.uiStyleSettings.toolboxColor+";\n    "));var t=this.uiStyleSettings.toolbarHeight/4;this.toolboxButtonRowStyleClass=this.styles.addClass(new p("toolbox-button-row","\n      display: flex;\n      cursor: default;\n      box-sizing: content-box;\n    ")),this.toolboxButtonRowStyleColorsClass=this.styles.addClass(new p("toolbox-button-row_colors","\n      background-color: "+this.uiStyleSettings.toolbarBackgroundColor+";\n    ")),this.toolboxPanelRowStyleClass=this.styles.addClass(new p("toolbox-panel-row","\n      display: flex;\n      "+("inline"===this.displayMode?"position: absolute;":"")+"\n      "+("inline"===this.displayMode?"bottom: "+this.uiStyleSettings.toolbarHeight+"px;":"")+"\n      cursor: default;\n      height: "+1.5*this.uiStyleSettings.toolbarHeight+"px;\n      "+("inline"===this.displayMode?"width: 100%;":"")+"\n      box-sizing: content-box;\n    ")),this.toolboxPanelRowStyleColorsClass=this.styles.addClass(new p("toolbox-panel-row_colors","\n      background-color: "+(null!==(e=this.uiStyleSettings.toolboxBackgroundColor)&&void 0!==e?e:this.uiStyleSettings.toolbarBackgroundHoverColor)+";\n    ")),this.toolboxButtonStyleClass=this.styles.addClass(new p("toolbox_button","\n      display: inline-block;\n      width: "+(this.uiStyleSettings.toolbarHeight-2*t)+"px;\n      height: "+(this.uiStyleSettings.toolbarHeight-2*t)+"px;\n      padding: "+t+"px;\n      box-sizing: content-box;\n    ")),this.toolboxButtonStyleColorsClass=this.styles.addClass(new p("toolbox-button_colors","\n      fill: "+this.uiStyleSettings.toolbarColor+";\n    ")),this.toolboxActiveButtonStyleColorsClass=this.styles.addClass(new p("toolbox-active-button_colors","\n      background-color: "+this.uiStyleSettings.toolbarBackgroundHoverColor+";\n      fill: "+this.uiStyleSettings.toolbarColor+";\n    ")),this.styles.addRule(new f("."+this.toolboxButtonStyleColorsClass.name+":hover","\n        background-color: "+this.uiStyleSettings.toolbarBackgroundHoverColor+"\n    ")),this.styles.addRule(new f("."+this.toolboxButtonStyleClass.name+" svg","\n      height: "+this.uiStyleSettings.toolbarHeight/2+"px;\n    "))},e.prototype.show=function(e){var t;this.uiContainer=document.createElement("div"),this.uiContainer.style.visibility=e,this.uiContainer.className=this.toolboxStyleClass.name+" "+(null!==(t=this.uiStyleSettings.toolboxStyleColorsClassName)&&void 0!==t?t:this.toolboxStyleColorsClass.name),this.markerjsContainer.appendChild(this.uiContainer)},e.prototype.setPanelButtons=function(e){var t,n,i=this;this.panels=e,void 0!==this.uiContainer&&(this.uiContainer.innerHTML="",this.panelRow=document.createElement("div"),this.panelRow.className=this.toolboxPanelRowStyleClass.name+" "+(null!==(t=this.uiStyleSettings.toolboxPanelRowStyleColorsClassName)&&void 0!==t?t:this.toolboxPanelRowStyleColorsClass.name),this.uiContainer.appendChild(this.panelRow),this.buttonRow=document.createElement("div"),this.buttonRow.className=this.toolboxButtonRowStyleClass.name+" "+(null!==(n=this.uiStyleSettings.toolboxButtonRowStyleColorsClassName)&&void 0!==n?n:this.toolboxButtonRowStyleColorsClass.name)+" ",this.uiContainer.appendChild(this.buttonRow),this.panelButtons.splice(0),this.panels.forEach((function(e){var t;e.uiStyleSettings=i.uiStyleSettings;var n=document.createElement("div");n.className=i.toolboxButtonStyleClass.name+" "+(null!==(t=i.uiStyleSettings.toolboxButtonStyleColorsClassName)&&void 0!==t?t:i.toolboxButtonStyleColorsClass.name),n.innerHTML=e.icon,n.title=e.title,n.addEventListener("click",(function(){i.panelButtonClick(e)})),i.panelButtons.push(n),i.buttonRow.appendChild(n)})),"inline"===this.displayMode?this.panelRow.style.display="none":this.panelRow.style.visibility="hidden")},e.prototype.panelButtonClick=function(e){var t=this,n=-1;if(e!==this.activePanel){n=this.panels.indexOf(e),this.panelRow.innerHTML="";var i=e.getUi();i.style.margin=this.uiStyleSettings.toolbarHeight/4+"px",this.panelRow.appendChild(i),this.panelRow.style.display="flex",this.panelRow.style.visibility="visible",this.panelRow.className=this.panelRow.className.replace(this.styles.fadeOutAnimationClassName,""),this.panelRow.className+=" "+this.styles.fadeInAnimationClassName,this.activePanel=e}else this.activePanel=void 0,this.panelRow.className=this.panelRow.className.replace(this.styles.fadeInAnimationClassName,""),this.panelRow.className+=" "+this.styles.fadeOutAnimationClassName,setTimeout((function(){"inline"===t.displayMode?t.panelRow.style.display="none":t.panelRow.style.visibility="hidden"}),200);this.panelButtons.forEach((function(e,i){var r,s;e.className=t.toolboxButtonStyleClass.name+" "+(i===n?""+(null!==(r=t.uiStyleSettings.toolboxActiveButtonStyleColorsClassName)&&void 0!==r?r:t.toolboxActiveButtonStyleColorsClass.name):""+(null!==(s=t.uiStyleSettings.toolboxButtonStyleColorsClassName)&&void 0!==s?s:t.toolboxButtonStyleColorsClass.name))}))},e}(),v=function(e,t){this.title=e,this.icon=t},A=function(e){function t(t,n,i,r){var s=e.call(this,t,r||'<svg viewBox="0 0 24 24"><path d="M17.5 12a1.5 1.5 0 01-1.5-1.5A1.5 1.5 0 0117.5 9a1.5 1.5 0 011.5 1.5 1.5 1.5 0 01-1.5 1.5m-3-4A1.5 1.5 0 0113 6.5 1.5 1.5 0 0114.5 5 1.5 1.5 0 0116 6.5 1.5 1.5 0 0114.5 8m-5 0A1.5 1.5 0 018 6.5 1.5 1.5 0 019.5 5 1.5 1.5 0 0111 6.5 1.5 1.5 0 019.5 8m-3 4A1.5 1.5 0 015 10.5 1.5 1.5 0 016.5 9 1.5 1.5 0 018 10.5 1.5 1.5 0 016.5 12M12 3a9 9 0 00-9 9 9 9 0 009 9 1.5 1.5 0 001.5-1.5c0-.39-.15-.74-.39-1-.23-.27-.38-.62-.38-1a1.5 1.5 0 011.5-1.5H16a5 5 0 005-5c0-4.42-4.03-8-9-8z"/></svg>')||this;return s.colors=[],s.addTransparent=!1,s.colorBoxes=[],s.colors=n,s.currentColor=i,s.setCurrentColor=s.setCurrentColor.bind(s),s.getColorBox=s.getColorBox.bind(s),s}return r(t,e),t.prototype.getUi=function(){var e=this,t=document.createElement("div");return t.style.overflow="hidden",t.style.whiteSpace="nowrap",this.colors.forEach((function(n){var i=e.getColorBox(n);t.appendChild(i),e.colorBoxes.push(i)})),t},t.prototype.getColorBox=function(e){var t=this,n=this.uiStyleSettings.toolbarHeight/4,i=this.uiStyleSettings.toolbarHeight-n,r=document.createElement("div");r.style.display="inline-block",r.style.boxSizing="content-box",r.style.width=i-2+"px",r.style.height=i-2+"px",r.style.padding="1px",r.style.marginRight="2px",r.style.marginBottom="2px",r.style.borderWidth="2px",r.style.borderStyle="solid",r.style.borderRadius=(i+2)/2+"px",r.style.borderColor=e===this.currentColor?this.uiStyleSettings.toolboxAccentColor:"transparent",r.addEventListener("click",(function(){t.setCurrentColor(e,r)}));var s=document.createElement("div");return s.style.display="inline-block",s.style.width=i-2+"px",s.style.height=i-2+"px",s.style.backgroundColor=e,s.style.borderRadius=i/2+"px","transparent"===e&&(s.style.fill=this.uiStyleSettings.toolboxAccentColor,s.innerHTML='<svg viewBox="0 0 24 24">\n        <path d="M2,5.27L3.28,4L20,20.72L18.73,22L15.65,18.92C14.5,19.3 13.28,19.5 12,19.5C7,19.5 2.73,16.39 1,12C1.69,10.24 2.79,8.69 4.19,7.46L2,5.27M12,9A3,3 0 0,1 15,12C15,12.35 14.94,12.69 14.83,13L11,9.17C11.31,9.06 11.65,9 12,9M12,4.5C17,4.5 21.27,7.61 23,12C22.18,14.08 20.79,15.88 19,17.19L17.58,15.76C18.94,14.82 20.06,13.54 20.82,12C19.17,8.64 15.76,6.5 12,6.5C10.91,6.5 9.84,6.68 8.84,7L7.3,5.47C8.74,4.85 10.33,4.5 12,4.5M3.18,12C4.83,15.36 8.24,17.5 12,17.5C12.69,17.5 13.37,17.43 14,17.29L11.72,15C10.29,14.85 9.15,13.71 9,12.28L5.6,8.87C4.61,9.72 3.78,10.78 3.18,12Z" />\n      </svg>'),r.appendChild(s),r},t.prototype.setCurrentColor=function(e,t){var n=this;this.currentColor=e,this.colorBoxes.forEach((function(e){e.style.borderColor=e===t?n.uiStyleSettings.toolboxAccentColor:"transparent"})),this.onColorChanged&&this.onColorChanged(e)},t}(v),x=function(){function e(e,t,n){this._state="new",this._isSelected=!1,this._container=e,this._overlayContainer=t,this.globalSettings=n,this.stateChanged=this.stateChanged.bind(this),this.colorChanged=this.colorChanged.bind(this),this.fillColorChanged=this.fillColorChanged.bind(this)}return Object.defineProperty(e.prototype,"typeName",{get:function(){return Object.getPrototypeOf(this).constructor.typeName},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"container",{get:function(){return this._container},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"overlayContainer",{get:function(){return this._overlayContainer},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"state",{get:function(){return this._state},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"toolboxPanels",{get:function(){return[]},enumerable:!1,configurable:!0}),e.prototype.ownsTarget=function(e){return!1},Object.defineProperty(e.prototype,"isSelected",{get:function(){return this._isSelected},enumerable:!1,configurable:!0}),e.prototype.select=function(){this.container.style.cursor="move",this._isSelected=!0,this.manipulationStartState=this.getState()},e.prototype.deselect=function(){this.container.style.cursor="default",this._isSelected=!1,this.stateChanged()},e.prototype.pointerDown=function(e,t){},e.prototype.dblClick=function(e,t){},e.prototype.manipulate=function(e){},e.prototype.pointerUp=function(e){this.stateChanged()},e.prototype.dispose=function(){},e.prototype.addMarkerVisualToContainer=function(e){this.container.childNodes.length>0?this.container.insertBefore(e,this.container.childNodes[0]):this.container.appendChild(e)},e.prototype.getState=function(){return{typeName:e.typeName,state:this.state,notes:this.notes}},e.prototype.restoreState=function(e){this._state=e.state,this.notes=e.notes},e.prototype.scale=function(e,t){},e.prototype.colorChanged=function(e){this.onColorChanged&&this.onColorChanged(e),this.stateChanged()},e.prototype.fillColorChanged=function(e){this.onFillColorChanged&&this.onFillColorChanged(e),this.stateChanged()},e.prototype.stateChanged=function(){if(this.onStateChanged&&"creating"!==this.state&&"new"!==this.state){var e=this.getState();void 0!==this.manipulationStartState&&(this.manipulationStartState.state="select"),e.state="select",JSON.stringify(this.manipulationStartState)!=JSON.stringify(e)&&this.onStateChanged(this)}},e.typeName="MarkerBase",e}(),y=function(){function e(){this.findGripByVisual=this.findGripByVisual.bind(this)}return e.prototype.findGripByVisual=function(e){return this.topLeft.ownsTarget(e)?this.topLeft:this.topCenter.ownsTarget(e)?this.topCenter:this.topRight.ownsTarget(e)?this.topRight:this.centerLeft.ownsTarget(e)?this.centerLeft:this.centerRight.ownsTarget(e)?this.centerRight:this.bottomLeft.ownsTarget(e)?this.bottomLeft:this.bottomCenter.ownsTarget(e)?this.bottomCenter:this.bottomRight.ownsTarget(e)?this.bottomRight:void 0},e}(),b=function(){function e(){this.GRIP_SIZE=10,this.visual=l.createGroup(),this.visual.appendChild(l.createCircle(1.5*this.GRIP_SIZE,[["fill","transparent"]])),this.visual.appendChild(l.createCircle(this.GRIP_SIZE,[["fill","#cccccc"],["fill-opacity","0.7"],["stroke","#333333"],["stroke-width","2"],["stroke-opacity","0.7"]]))}return e.prototype.ownsTarget=function(e){return e===this.visual||e===this.visual.childNodes[0]||e===this.visual.childNodes[1]},e}(),w=function(){function e(){}return e.toITransformMatrix=function(e){return{a:e.a,b:e.b,c:e.c,d:e.d,e:e.e,f:e.f}},e.toSVGMatrix=function(e,t){return e.a=t.a,e.b=t.b,e.c=t.c,e.d=t.d,e.e=t.e,e.f=t.f,e},e}(),C=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.left=0,r.top=0,r.width=0,r.height=0,r.defaultSize={x:50,y:20},r.offsetX=0,r.offsetY=0,r.rotationAngle=0,r.CB_DISTANCE=10,r._suppressMarkerCreateEvent=!1,r.container.transform.baseVal.appendItem(l.createTransform()),r.setupControlBox(),r}return r(t,e),Object.defineProperty(t.prototype,"centerX",{get:function(){return this.left+this.width/2},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"centerY",{get:function(){return this.top+this.height/2},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"visual",{get:function(){return this._visual},set:function(e){this._visual=e;var t=l.createTransform();this._visual.transform.baseVal.appendItem(t)},enumerable:!1,configurable:!0}),t.prototype.ownsTarget=function(t){return!!e.prototype.ownsTarget.call(this,t)||!!(void 0!==this.controlGrips.findGripByVisual(t)||void 0!==this.rotatorGrip&&this.rotatorGrip.ownsTarget(t))},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),"new"===this.state&&(this.left=t.x,this.top=t.y),this.manipulationStartLeft=this.left,this.manipulationStartTop=this.top,this.manipulationStartWidth=this.width,this.manipulationStartHeight=this.height;var i=this.unrotatePoint(t);if(this.manipulationStartX=i.x,this.manipulationStartY=i.y,this.offsetX=i.x-this.left,this.offsetY=i.y-this.top,"new"!==this.state)if(this.select(),this.activeGrip=this.controlGrips.findGripByVisual(n),void 0!==this.activeGrip)this._state="resize";else if(void 0!==this.rotatorGrip&&this.rotatorGrip.ownsTarget(n)){this.activeGrip=this.rotatorGrip;var r=this.rotatePoint({x:this.centerX,y:this.centerY});this.left=r.x-this.width/2,this.top=r.y-this.height/2,this.moveVisual({x:this.left,y:this.top});var s=this.container.transform.baseVal.getItem(0);s.setRotate(this.rotationAngle,this.centerX,this.centerY),this.container.transform.baseVal.replaceItem(s,0),this.adjustControlBox(),this._state="rotate"}else this._state="move"},t.prototype.pointerUp=function(t){var n=this.state;e.prototype.pointerUp.call(this,t),"creating"===this.state&&this.width<10&&this.height<10?(this.width=this.defaultSize.x,this.height=this.defaultSize.y):this.manipulate(t),this._state="select","creating"===n&&this.onMarkerCreated&&!1===this._suppressMarkerCreateEvent&&this.onMarkerCreated(this)},t.prototype.moveVisual=function(e){this.visual.style.transform="translate("+e.x+"px, "+e.y+"px)"},t.prototype.manipulate=function(e){var t=this.unrotatePoint(e);"creating"===this.state?this.resize(e):"move"===this.state?(this.left=this.manipulationStartLeft+(t.x-this.manipulationStartLeft)-this.offsetX,this.top=this.manipulationStartTop+(t.y-this.manipulationStartTop)-this.offsetY,this.moveVisual({x:this.left,y:this.top}),this.adjustControlBox()):"resize"===this.state?this.resize(t):"rotate"===this.state&&this.rotate(e)},t.prototype.resize=function(e){var t=this.manipulationStartLeft,n=this.manipulationStartWidth,i=this.manipulationStartTop,r=this.manipulationStartHeight;switch(this.activeGrip){case this.controlGrips.bottomLeft:case this.controlGrips.centerLeft:case this.controlGrips.topLeft:t=this.manipulationStartLeft+e.x-this.manipulationStartX,n=this.manipulationStartWidth+this.manipulationStartLeft-t;break;case this.controlGrips.bottomRight:case this.controlGrips.centerRight:case this.controlGrips.topRight:case void 0:n=this.manipulationStartWidth+e.x-this.manipulationStartX}switch(this.activeGrip){case this.controlGrips.topCenter:case this.controlGrips.topLeft:case this.controlGrips.topRight:i=this.manipulationStartTop+e.y-this.manipulationStartY,r=this.manipulationStartHeight+this.manipulationStartTop-i;break;case this.controlGrips.bottomCenter:case this.controlGrips.bottomLeft:case this.controlGrips.bottomRight:case void 0:r=this.manipulationStartHeight+e.y-this.manipulationStartY}n>=0?(this.left=t,this.width=n):(this.left=t+n,this.width=-n),r>=0?(this.top=i,this.height=r):(this.top=i+r,this.height=-r),this.setSize()},t.prototype.setSize=function(){this.moveVisual({x:this.left,y:this.top}),this.adjustControlBox()},t.prototype.rotate=function(e){if(Math.abs(e.x-this.centerX)>.1){var t=Math.sign(e.x-this.centerX);this.rotationAngle=180*Math.atan((e.y-this.centerY)/(e.x-this.centerX))/Math.PI+90*t,this.applyRotation()}},t.prototype.applyRotation=function(){var e=this.container.transform.baseVal.getItem(0);e.setRotate(this.rotationAngle,this.centerX,this.centerY),this.container.transform.baseVal.replaceItem(e,0)},t.prototype.rotatePoint=function(e){if(0===this.rotationAngle)return e;var t=this.container.getCTM(),n=l.createPoint(e.x,e.y);return{x:(n=n.matrixTransform(t)).x,y:n.y}},t.prototype.unrotatePoint=function(e){if(0===this.rotationAngle)return e;var t=this.container.getCTM();t=t.inverse();var n=l.createPoint(e.x,e.y);return{x:(n=n.matrixTransform(t)).x,y:n.y}},t.prototype.select=function(){e.prototype.select.call(this),this.adjustControlBox(),this.controlBox.style.display=""},t.prototype.deselect=function(){e.prototype.deselect.call(this),this.controlBox.style.display="none"},t.prototype.setupControlBox=function(){this.controlBox=l.createGroup();var e=l.createTransform();e.setTranslate(-this.CB_DISTANCE/2,-this.CB_DISTANCE/2),this.controlBox.transform.baseVal.appendItem(e),this.container.appendChild(this.controlBox),this.controlRect=l.createRect(this.width+this.CB_DISTANCE,this.height+this.CB_DISTANCE,[["stroke","black"],["stroke-width","1"],["stroke-opacity","0.5"],["stroke-dasharray","3, 2"],["fill","transparent"],["pointer-events","none"]]),this.controlBox.appendChild(this.controlRect),!0!==this.globalSettings.disableRotation&&(this.rotatorGripLine=l.createLine((this.width+2*this.CB_DISTANCE)/2,this.top-this.CB_DISTANCE,(this.width+2*this.CB_DISTANCE)/2,this.top-3*this.CB_DISTANCE,[["stroke","black"],["stroke-width","1"],["stroke-opacity","0.5"],["stroke-dasharray","3, 2"]]),this.controlBox.appendChild(this.rotatorGripLine)),this.controlGrips=new y,this.addControlGrips(),this.controlBox.style.display="none"},t.prototype.adjustControlBox=function(){var e=this.controlBox.transform.baseVal.getItem(0);e.setTranslate(this.left-this.CB_DISTANCE/2,this.top-this.CB_DISTANCE/2),this.controlBox.transform.baseVal.replaceItem(e,0),this.controlRect.setAttribute("width",(this.width+this.CB_DISTANCE).toString()),this.controlRect.setAttribute("height",(this.height+this.CB_DISTANCE).toString()),void 0!==this.rotatorGripLine&&(this.rotatorGripLine.setAttribute("x1",((this.width+this.CB_DISTANCE)/2).toString()),this.rotatorGripLine.setAttribute("y1",(-this.CB_DISTANCE/2).toString()),this.rotatorGripLine.setAttribute("x2",((this.width+this.CB_DISTANCE)/2).toString()),this.rotatorGripLine.setAttribute("y2",(3*-this.CB_DISTANCE).toString())),this.positionGrips()},t.prototype.addControlGrips=function(){this.controlGrips.topLeft=this.createGrip(),this.controlGrips.topCenter=this.createGrip(),this.controlGrips.topRight=this.createGrip(),this.controlGrips.centerLeft=this.createGrip(),this.controlGrips.centerRight=this.createGrip(),this.controlGrips.bottomLeft=this.createGrip(),this.controlGrips.bottomCenter=this.createGrip(),this.controlGrips.bottomRight=this.createGrip(),!0!==this.globalSettings.disableRotation&&(this.rotatorGrip=this.createGrip()),this.positionGrips()},t.prototype.createGrip=function(){var e=new b;return e.visual.transform.baseVal.appendItem(l.createTransform()),this.controlBox.appendChild(e.visual),e},t.prototype.positionGrips=function(){var e=this.controlGrips.topLeft.GRIP_SIZE,t=-e/2,n=t,i=(this.width+this.CB_DISTANCE)/2-e/2,r=(this.height+this.CB_DISTANCE)/2-e/2,s=this.height+this.CB_DISTANCE-e/2,o=this.width+this.CB_DISTANCE-e/2;this.positionGrip(this.controlGrips.topLeft.visual,t,n),this.positionGrip(this.controlGrips.topCenter.visual,i,n),this.positionGrip(this.controlGrips.topRight.visual,o,n),this.positionGrip(this.controlGrips.centerLeft.visual,t,r),this.positionGrip(this.controlGrips.centerRight.visual,o,r),this.positionGrip(this.controlGrips.bottomLeft.visual,t,s),this.positionGrip(this.controlGrips.bottomCenter.visual,i,s),this.positionGrip(this.controlGrips.bottomRight.visual,o,s),void 0!==this.rotatorGrip&&this.positionGrip(this.rotatorGrip.visual,i,n-3*this.CB_DISTANCE)},t.prototype.positionGrip=function(e,t,n){var i=e.transform.baseVal.getItem(0);i.setTranslate(t,n),e.transform.baseVal.replaceItem(i,0)},t.prototype.hideControlBox=function(){this.controlBox.style.display="none"},t.prototype.showControlBox=function(){this.controlBox.style.display=""},t.prototype.getState=function(){return Object.assign({left:this.left,top:this.top,width:this.width,height:this.height,rotationAngle:this.rotationAngle,visualTransformMatrix:w.toITransformMatrix(this.visual.transform.baseVal.getItem(0).matrix),containerTransformMatrix:w.toITransformMatrix(this.container.transform.baseVal.getItem(0).matrix)},e.prototype.getState.call(this))},t.prototype.restoreState=function(t){e.prototype.restoreState.call(this,t);var n=t;this.left=n.left,this.top=n.top,this.width=n.width,this.height=n.height,this.rotationAngle=n.rotationAngle,this.visual.transform.baseVal.getItem(0).setMatrix(w.toSVGMatrix(this.visual.transform.baseVal.getItem(0).matrix,n.visualTransformMatrix)),this.container.transform.baseVal.getItem(0).setMatrix(w.toSVGMatrix(this.container.transform.baseVal.getItem(0).matrix,n.containerTransformMatrix))},t.prototype.scale=function(t,n){e.prototype.scale.call(this,t,n);var i=this.rotatePoint({x:this.left,y:this.top}),r=this.unrotatePoint({x:i.x*t,y:i.y*n});this.left=r.x,this.top=r.y,this.width=this.width*t,this.height=this.height*n,this.adjustControlBox()},t}(x),M=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.fillColor="transparent",r.strokeColor="transparent",r.strokeWidth=0,r.strokeDasharray="",r.opacity=1,r.setStrokeColor=r.setStrokeColor.bind(r),r.setFillColor=r.setFillColor.bind(r),r.setStrokeWidth=r.setStrokeWidth.bind(r),r.setStrokeDasharray=r.setStrokeDasharray.bind(r),r.createVisual=r.createVisual.bind(r),r}return r(t,e),t.prototype.ownsTarget=function(t){return!(!e.prototype.ownsTarget.call(this,t)&&t!==this.visual)},t.prototype.createVisual=function(){this.visual=l.createRect(1,1,[["fill",this.fillColor],["stroke",this.strokeColor],["stroke-width",this.strokeWidth.toString()],["stroke-dasharray",this.strokeDasharray],["opacity",this.opacity.toString()]]),this.addMarkerVisualToContainer(this.visual)},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),"new"===this.state&&(this.createVisual(),this.moveVisual(t),this._state="creating")},t.prototype.manipulate=function(t){e.prototype.manipulate.call(this,t)},t.prototype.resize=function(t){e.prototype.resize.call(this,t),this.setSize()},t.prototype.setSize=function(){e.prototype.setSize.call(this),l.setAttributes(this.visual,[["width",this.width.toString()],["height",this.height.toString()]])},t.prototype.pointerUp=function(t){e.prototype.pointerUp.call(this,t),this.setSize()},t.prototype.setStrokeColor=function(e){this.strokeColor=e,this.visual&&l.setAttributes(this.visual,[["stroke",this.strokeColor]]),this.colorChanged(e),this.stateChanged()},t.prototype.setFillColor=function(e){this.fillColor=e,this.visual&&l.setAttributes(this.visual,[["fill",this.fillColor]]),this.stateChanged()},t.prototype.setStrokeWidth=function(e){this.strokeWidth=e,this.visual&&l.setAttributes(this.visual,[["stroke-width",this.strokeWidth.toString()]]),this.stateChanged()},t.prototype.setStrokeDasharray=function(e){this.strokeDasharray=e,this.visual&&l.setAttributes(this.visual,[["stroke-dasharray",this.strokeDasharray]]),this.stateChanged()},t.prototype.getState=function(){return Object.assign({fillColor:this.fillColor,strokeColor:this.strokeColor,strokeWidth:this.strokeWidth,strokeDasharray:this.strokeDasharray,opacity:this.opacity},e.prototype.getState.call(this))},t.prototype.restoreState=function(t){var n=t;this.fillColor=n.fillColor,this.strokeColor=n.strokeColor,this.strokeWidth=n.strokeWidth,this.strokeDasharray=n.strokeDasharray,this.opacity=n.opacity,this.createVisual(),e.prototype.restoreState.call(this,t),this.setSize()},t.prototype.scale=function(t,n){e.prototype.scale.call(this,t,n),this.setSize()},t.title="Rectangle marker",t}(C),E=function(e){function t(t,n,i,r){var s=e.call(this,t,r||'<svg viewBox="0 0 24 24"><path d="M3 17h18v-2H3v2m0 3h18v-1H3v1m0-7h18v-3H3v3m0-9v4h18V4H3z"/></svg>')||this;return s.widths=[],s.widthBoxes=[],s.widths=n,s.currentWidth=i,s.setCurrentWidth=s.setCurrentWidth.bind(s),s}return r(t,e),t.prototype.getUi=function(){var e=this,t=document.createElement("div");return t.style.display="flex",t.style.overflow="hidden",t.style.flexGrow="2",this.widths.forEach((function(n){var i=document.createElement("div");i.style.display="flex",i.style.flexGrow="2",i.style.alignItems="center",i.style.justifyContent="space-between",i.style.padding="5px",i.style.borderWidth="2px",i.style.borderStyle="solid",i.style.borderColor=n===e.currentWidth?e.uiStyleSettings.toolboxAccentColor:"transparent",i.addEventListener("click",(function(){e.setCurrentWidth(n,i)})),t.appendChild(i);var r=document.createElement("div");r.innerText=n.toString(),r.style.marginRight="5px",i.appendChild(r);var s=document.createElement("div");s.style.minHeight="20px",s.style.flexGrow="2",s.style.display="flex",s.style.alignItems="center";var o=document.createElement("hr");o.style.minWidth="20px",o.style.border="0px",o.style.borderTop=n+"px solid "+e.uiStyleSettings.toolboxColor,o.style.flexGrow="2",s.appendChild(o),i.appendChild(s),e.widthBoxes.push(i)})),t},t.prototype.setCurrentWidth=function(e,t){var n=this;this.currentWidth=e,this.widthBoxes.forEach((function(e){e.style.borderColor=e===t?n.uiStyleSettings.toolboxAccentColor:"transparent"})),this.onWidthChanged&&this.onWidthChanged(this.currentWidth)},t}(v),T=function(e){function t(t,n,i,r){var s=e.call(this,t,r||'<svg viewBox="0 0 24 24"><path d="M3 16h5v-2H3v2m6.5 0h5v-2h-5v2m6.5 0h5v-2h-5v2M3 20h2v-2H3v2m4 0h2v-2H7v2m4 0h2v-2h-2v2m4 0h2v-2h-2v2m4 0h2v-2h-2v2M3 12h8v-2H3v2m10 0h8v-2h-8v2M3 4v4h18V4H3z"/></svg>')||this;return s.styles=[],s.styleBoxes=[],s.styles=n,s.currentStyle=i,s.setCurrentStyle=s.setCurrentStyle.bind(s),s}return r(t,e),t.prototype.getUi=function(){var e=this,t=document.createElement("div");return t.style.display="flex",t.style.overflow="hidden",t.style.flexGrow="2",this.styles.forEach((function(n){var i=document.createElement("div");i.style.display="flex",i.style.alignItems="center",i.style.justifyContent="space-between",i.style.padding="5px",i.style.borderWidth="2px",i.style.borderStyle="solid",i.style.overflow="hidden",i.style.maxWidth=100/e.styles.length-5+"%",i.style.borderColor=n===e.currentStyle?e.uiStyleSettings.toolboxAccentColor:"transparent",i.addEventListener("click",(function(){e.setCurrentStyle(n,i)})),t.appendChild(i);var r=document.createElement("div");r.style.minHeight="20px",r.style.flexGrow="2",r.style.overflow="hidden";var s='<svg width="100" height="20">\n      <line x1="0" y1="10" x2="100" y2="10" stroke="'+e.uiStyleSettings.toolboxColor+'" stroke-width="3" '+(""!==n?'stroke-dasharray="'+n+'"':"")+" />\n  </svg>";r.innerHTML=s,i.appendChild(r),e.styleBoxes.push(i)})),t},t.prototype.setCurrentStyle=function(e,t){var n=this;this.currentStyle=e,this.styleBoxes.forEach((function(e){e.style.borderColor=e===t?n.uiStyleSettings.toolboxAccentColor:"transparent"})),this.onStyleChanged&&this.onStyleChanged(this.currentStyle)},t}(v),S=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.strokeColor=i.defaultColor,r.strokeWidth=i.defaultStrokeWidth,r.strokeDasharray=i.defaultStrokeDasharray,r.strokePanel=new A("Line color",i.defaultColorSet,i.defaultColor),r.strokePanel.onColorChanged=r.setStrokeColor,r.strokeWidthPanel=new E("Line width",i.defaultStrokeWidths,i.defaultStrokeWidth),r.strokeWidthPanel.onWidthChanged=r.setStrokeWidth,r.strokeStylePanel=new T("Line style",i.defaultStrokeDasharrays,i.defaultStrokeDasharray),r.strokeStylePanel.onStyleChanged=r.setStrokeDasharray,r}return r(t,e),Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.strokePanel,this.strokeWidthPanel,this.strokeStylePanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=e.prototype.getState.call(this);return n.typeName=t.typeName,n},t.typeName="FrameMarker",t.title="Frame marker",t.icon='<svg viewBox="0 0 24 24"><path d="M4 6v13h16V6H4m14 11H6V8h12v9z"/></svg>',t}(M),P=function(){this.defaultColorSet=["#EF4444","#10B981","#2563EB","#FFFF00","#7C3AED","#F472B6","#000000","#FFFFFF"],this.defaultColor=this.defaultColorSet[0],this.defaultFillColor=this.defaultColorSet[0],this.defaultStrokeColor=this.defaultColorSet[7],this.defaultHighlightColor=this.defaultColorSet[3],this.defaultStrokeWidth=3,this.defaultStrokeDasharray="",this.defaultHighlightOpacity=.5,this.defaultFontFamily="Helvetica, Arial, sans-serif",this.defaultStrokeWidths=[1,2,3,5,10],this.defaultStrokeDasharrays=["","3","12 3","9 6 3 6"],this.defaultOpacitySteps=[.1,.25,.5,.75,1],this.displayMode="inline",this.defaultFontFamilies=['Times, "Times New Roman", serif',"Helvetica, Arial, sans-serif",'Courier, "Courier New", monospace',"cursive","fantasy"],this.popupMargin=30,this.newFreehandMarkerOnPointerUp=!1,this.defaultColorsFollowCurrentColors=!1,this.freehandPixelRatio=1,this.disableRotation=!1,this.defaultCaptionFontSize="1rem",this.defaultCaptionText="Text"},N=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.x1=0,r.y1=0,r.x2=0,r.y2=0,r.defaultLength=50,r.manipulationStartX=0,r.manipulationStartY=0,r.manipulationStartX1=0,r.manipulationStartY1=0,r.manipulationStartX2=0,r.manipulationStartY2=0,r.setupControlBox(),r}return r(t,e),t.prototype.ownsTarget=function(t){return!!e.prototype.ownsTarget.call(this,t)||!(!this.grip1.ownsTarget(t)&&!this.grip2.ownsTarget(t))},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),this.manipulationStartX=t.x,this.manipulationStartY=t.y,"new"===this.state&&(this.x1=t.x,this.y1=t.y,this.x2=t.x,this.y2=t.y),this.manipulationStartX1=this.x1,this.manipulationStartY1=this.y1,this.manipulationStartX2=this.x2,this.manipulationStartY2=this.y2,"new"!==this.state&&(this.select(),this.grip1.ownsTarget(n)?this.activeGrip=this.grip1:this.grip2.ownsTarget(n)?this.activeGrip=this.grip2:this.activeGrip=void 0,this.activeGrip?this._state="resize":this._state="move")},t.prototype.pointerUp=function(t){var n=this.state;e.prototype.pointerUp.call(this,t),"creating"===this.state&&Math.abs(this.x1-this.x2)<10&&Math.abs(this.y1-this.y2)<10?(this.x2=this.x1+this.defaultLength,this.adjustVisual(),this.adjustControlBox()):this.manipulate(t),this._state="select","creating"===n&&this.onMarkerCreated&&this.onMarkerCreated(this)},t.prototype.adjustVisual=function(){},t.prototype.manipulate=function(e){"creating"===this.state?this.resize(e):"move"===this.state?(this.x1=this.manipulationStartX1+e.x-this.manipulationStartX,this.y1=this.manipulationStartY1+e.y-this.manipulationStartY,this.x2=this.manipulationStartX2+e.x-this.manipulationStartX,this.y2=this.manipulationStartY2+e.y-this.manipulationStartY,this.adjustVisual(),this.adjustControlBox()):"resize"===this.state&&this.resize(e)},t.prototype.resize=function(e){switch(this.activeGrip){case this.grip1:this.x1=e.x,this.y1=e.y;break;case this.grip2:case void 0:this.x2=e.x,this.y2=e.y}this.adjustVisual(),this.adjustControlBox()},t.prototype.select=function(){e.prototype.select.call(this),this.adjustControlBox(),this.controlBox.style.display=""},t.prototype.deselect=function(){e.prototype.deselect.call(this),this.controlBox.style.display="none"},t.prototype.setupControlBox=function(){this.controlBox=l.createGroup(),this.container.appendChild(this.controlBox),this.addControlGrips(),this.controlBox.style.display="none"},t.prototype.adjustControlBox=function(){this.positionGrips()},t.prototype.addControlGrips=function(){this.grip1=this.createGrip(),this.grip2=this.createGrip(),this.positionGrips()},t.prototype.createGrip=function(){var e=new b;return e.visual.transform.baseVal.appendItem(l.createTransform()),this.controlBox.appendChild(e.visual),e},t.prototype.positionGrips=function(){var e=this.grip1.GRIP_SIZE;this.positionGrip(this.grip1.visual,this.x1-e/2,this.y1-e/2),this.positionGrip(this.grip2.visual,this.x2-e/2,this.y2-e/2)},t.prototype.positionGrip=function(e,t,n){var i=e.transform.baseVal.getItem(0);i.setTranslate(t,n),e.transform.baseVal.replaceItem(i,0)},t.prototype.getState=function(){return Object.assign({x1:this.x1,y1:this.y1,x2:this.x2,y2:this.y2},e.prototype.getState.call(this))},t.prototype.restoreState=function(t){e.prototype.restoreState.call(this,t);var n=t;this.x1=n.x1,this.y1=n.y1,this.x2=n.x2,this.y2=n.y2},t.prototype.scale=function(t,n){e.prototype.scale.call(this,t,n),this.x1=this.x1*t,this.y1=this.y1*n,this.x2=this.x2*t,this.y2=this.y2*n,this.adjustVisual(),this.adjustControlBox()},t}(x),B=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.strokeColor="transparent",r.strokeWidth=0,r.strokeDasharray="",r.setStrokeColor=r.setStrokeColor.bind(r),r.setStrokeWidth=r.setStrokeWidth.bind(r),r.setStrokeDasharray=r.setStrokeDasharray.bind(r),r.strokeColor=i.defaultColor,r.strokeWidth=i.defaultStrokeWidth,r.strokeDasharray=i.defaultStrokeDasharray,r.strokePanel=new A("Line color",i.defaultColorSet,i.defaultColor),r.strokePanel.onColorChanged=r.setStrokeColor,r.strokeWidthPanel=new E("Line width",i.defaultStrokeWidths,i.defaultStrokeWidth),r.strokeWidthPanel.onWidthChanged=r.setStrokeWidth,r.strokeStylePanel=new T("Line style",i.defaultStrokeDasharrays,i.defaultStrokeDasharray),r.strokeStylePanel.onStyleChanged=r.setStrokeDasharray,r}return r(t,e),t.prototype.ownsTarget=function(t){return!(!e.prototype.ownsTarget.call(this,t)&&t!==this.visual&&t!==this.selectorLine&&t!==this.visibleLine)},t.prototype.createVisual=function(){this.visual=l.createGroup(),this.selectorLine=l.createLine(this.x1,this.y1,this.x2,this.y2,[["stroke","transparent"],["stroke-width",(this.strokeWidth+10).toString()]]),this.visibleLine=l.createLine(this.x1,this.y1,this.x2,this.y2,[["stroke",this.strokeColor],["stroke-width",this.strokeWidth.toString()]]),this.visual.appendChild(this.selectorLine),this.visual.appendChild(this.visibleLine),this.addMarkerVisualToContainer(this.visual)},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),"new"===this.state&&(this.createVisual(),this.adjustVisual(),this._state="creating")},t.prototype.adjustVisual=function(){this.selectorLine&&this.visibleLine&&(this.selectorLine.setAttribute("x1",this.x1.toString()),this.selectorLine.setAttribute("y1",this.y1.toString()),this.selectorLine.setAttribute("x2",this.x2.toString()),this.selectorLine.setAttribute("y2",this.y2.toString()),this.visibleLine.setAttribute("x1",this.x1.toString()),this.visibleLine.setAttribute("y1",this.y1.toString()),this.visibleLine.setAttribute("x2",this.x2.toString()),this.visibleLine.setAttribute("y2",this.y2.toString()),l.setAttributes(this.visibleLine,[["stroke",this.strokeColor]]),l.setAttributes(this.visibleLine,[["stroke-width",this.strokeWidth.toString()]]),l.setAttributes(this.visibleLine,[["stroke-dasharray",this.strokeDasharray.toString()]]))},t.prototype.setStrokeColor=function(e){this.strokeColor=e,this.adjustVisual(),this.colorChanged(e)},t.prototype.setStrokeWidth=function(e){this.strokeWidth=e,this.adjustVisual()},t.prototype.setStrokeDasharray=function(e){this.strokeDasharray=e,this.adjustVisual(),this.stateChanged()},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.strokePanel,this.strokeWidthPanel,this.strokeStylePanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=Object.assign({strokeColor:this.strokeColor,strokeWidth:this.strokeWidth,strokeDasharray:this.strokeDasharray},e.prototype.getState.call(this));return n.typeName=t.typeName,n},t.prototype.restoreState=function(t){e.prototype.restoreState.call(this,t);var n=t;this.strokeColor=n.strokeColor,this.strokeWidth=n.strokeWidth,this.strokeDasharray=n.strokeDasharray,this.createVisual(),this.adjustVisual()},t.typeName="LineMarker",t.title="Line marker",t.icon='<svg viewBox="0 0 24 24"><path d="M19 13H5v-2h14v2z"/></svg>',t}(N),D=function(e){function t(t,n,i,r){var s=e.call(this,t,r||'<svg viewBox="0 0 24 24"><path d="M17 8h3v12h1v1h-4v-1h1v-3h-4l-1.5 3H14v1h-4v-1h1l6-12m1 1l-3.5 7H18V9M5 3h5c1.11 0 2 .89 2 2v11H9v-5H6v5H3V5c0-1.11.89-2 2-2m1 2v4h3V5H6z"/></svg>')||this;return s.fonts=[],s.fontBoxes=[],s.fonts=n,s.currentFont=i,s.setCurrentFont=s.setCurrentFont.bind(s),s}return r(t,e),t.prototype.getUi=function(){var e=this,t=document.createElement("div");return t.style.overflow="hidden",t.style.flexGrow="2",this.fonts.forEach((function(n){var i=document.createElement("div");i.style.display="inline-block",i.style.alignItems="center",i.style.justifyContent="space-between",i.style.padding="5px",i.style.borderWidth="2px",i.style.borderStyle="solid",i.style.overflow="hidden",i.style.maxWidth=100/e.fonts.length-5+"%",i.style.borderColor=n===e.currentFont?e.uiStyleSettings.toolboxAccentColor:"transparent",i.addEventListener("click",(function(){e.setCurrentFont(n,i)})),t.appendChild(i);var r=document.createElement("div");r.style.display="flex",r.style.minHeight="20px",r.style.flexGrow="2",r.style.fontFamily=n,r.style.overflow="hidden";var s=document.createElement("div");s.style.whiteSpace="nowrap",s.style.overflow="hidden",s.style.textOverflow="ellipsis",s.innerHTML="The quick brown fox jumps over the lazy dog",r.appendChild(s),i.appendChild(r),e.fontBoxes.push(i)})),t},t.prototype.setCurrentFont=function(e,t){var n=this;this.currentFont=e,this.fontBoxes.forEach((function(e){e.style.borderColor=e===t?n.uiStyleSettings.toolboxAccentColor:"transparent"})),this.onFontChanged&&this.onFontChanged(this.currentFont)},t}(v),I=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.color="transparent",r.padding=5,r.DEFAULT_TEXT="请输入文本",r.text=r.DEFAULT_TEXT,r.isMoved=!1,r.color=i.defaultColor,r.fontFamily=i.defaultFontFamily,r.defaultSize={x:100,y:30},r.setColor=r.setColor.bind(r),r.setFont=r.setFont.bind(r),r.renderText=r.renderText.bind(r),r.sizeText=r.sizeText.bind(r),r.textEditDivClicked=r.textEditDivClicked.bind(r),r.showTextEditor=r.showTextEditor.bind(r),r.setSize=r.setSize.bind(r),r.positionTextEditor=r.positionTextEditor.bind(r),r.colorPanel=new A("Color",i.defaultColorSet,i.defaultColor),r.colorPanel.onColorChanged=r.setColor,r.fontFamilyPanel=new D("Font",i.defaultFontFamilies,i.defaultFontFamily),r.fontFamilyPanel.onFontChanged=r.setFont,r}return r(t,e),t.prototype.ownsTarget=function(t){if(e.prototype.ownsTarget.call(this,t)||t===this.visual||t===this.textElement||t===this.bgRectangle)return!0;var n=!1;return this.textElement.childNodes.forEach((function(e){e===t&&(n=!0)})),n},t.prototype.createVisual=function(){this.visual=l.createGroup(),this.bgRectangle=l.createRect(1,1,[["fill","transparent"]]),this.visual.appendChild(this.bgRectangle),this.textElement=l.createText([["fill",this.color],["font-family",this.fontFamily],["font-size","16px"],["x","0"],["y","0"]]),this.textElement.transform.baseVal.appendItem(l.createTransform()),this.textElement.transform.baseVal.appendItem(l.createTransform()),this.visual.appendChild(this.textElement),this.addMarkerVisualToContainer(this.visual),this.renderText()},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),this.isMoved=!1,this.pointerDownPoint=t,this.pointerDownTimestamp=Date.now(),"new"===this.state&&(this.createVisual(),this.moveVisual(t),this._state="creating")},t.prototype.renderText=function(){var e=this;if(this.textElement){for(;this.textElement.lastChild;)this.textElement.removeChild(this.textElement.lastChild);this.text.split(/\r\n|[\n\v\f\r\x85\u2028\u2029]/).forEach((function(t){e.textElement.appendChild(l.createTSpan(""===t.trim()?" ":t.trim(),[["x","0"],["dy","1.2em"]]))})),setTimeout(this.sizeText,10)}},t.prototype.getTextScale=function(){var e=this.textElement.getBBox(),t=1;if(e.width>0&&e.height>0){var n=(1*this.width-this.width*this.padding*2/100)/e.width,i=(1*this.height-this.height*this.padding*2/100)/e.height;t=Math.min(n,i)}return t},t.prototype.getTextPosition=function(e){var t=this.textElement.getBBox(),n=0,i=0;return t.width>0&&t.height>0&&(n=(this.width-t.width*e)/2,i=this.height/2-t.height*e/2),{x:n,y:i}},t.prototype.sizeText=function(){var e=this.textElement.getBBox(),t=this.getTextScale(),n=this.getTextPosition(t);n.y-=e.y*t,navigator.userAgent.indexOf("Edge/")>-1?this.textElement.style.transform="translate("+n.x+"px, "+n.y+"px) scale("+t+", "+t+")":(this.textElement.transform.baseVal.getItem(0).setTranslate(n.x,n.y),this.textElement.transform.baseVal.getItem(1).setScale(t,t))},t.prototype.manipulate=function(t){e.prototype.manipulate.call(this,t),void 0!==this.pointerDownPoint&&(this.isMoved=Math.abs(t.x-this.pointerDownPoint.x)>5||Math.abs(t.y-this.pointerDownPoint.y)>5)},t.prototype.resize=function(t){e.prototype.resize.call(this,t),this.isMoved=!0,this.setSize(),this.sizeText()},t.prototype.setSize=function(){e.prototype.setSize.call(this),this.visual&&this.bgRectangle&&(l.setAttributes(this.visual,[["width",this.width.toString()],["height",this.height.toString()]]),l.setAttributes(this.bgRectangle,[["width",this.width.toString()],["height",this.height.toString()]]))},t.prototype.pointerUp=function(t){var n=this.state;"creating"===n&&(this._suppressMarkerCreateEvent=!0),e.prototype.pointerUp.call(this,t),this.setSize(),("creating"===n||!this.isMoved&&Date.now()-this.pointerDownTimestamp>500)&&this.showTextEditor(),this.pointerDownPoint=void 0},t.prototype.showTextEditor=function(){var e=this;this._state="edit",this.overlayContainer.innerHTML="",this.textEditDiv=document.createElement("div"),this.textEditDiv.style.flexGrow="2",this.textEditDiv.style.alignItems="center",this.textEditDiv.style.justifyContent="center",this.textEditDiv.style.pointerEvents="auto",this.textEditDiv.style.overflow="hidden",this.textEditor=document.createElement("div"),this.textEditor.style.position="absolute",this.textEditor.style.fontFamily=this.fontFamily,this.textEditor.style.lineHeight="1em",this.textEditor.innerText=this.text,this.textEditor.contentEditable="true",this.textEditor.style.color=this.color,this.textEditor.style.whiteSpace="pre",this.positionTextEditor(),this.textEditor.addEventListener("pointerup",(function(e){e.stopPropagation()})),this.textEditor.addEventListener("input",(function(){for(var t=Number.parseFloat(e.textEditor.style.fontSize);e.textEditor.clientWidth>=Number.parseInt(e.textEditor.style.maxWidth)&&t>.9;)t-=.1,e.textEditor.style.fontSize=Math.max(t,.9)+"em"})),this.textEditor.addEventListener("keyup",(function(e){e.cancelBubble=!0})),this.textEditor.addEventListener("paste",(function(e){if(e.clipboardData){var t=e.clipboardData.getData("text"),n=window.getSelection();if(!n.rangeCount)return!1;n.deleteFromDocument(),n.getRangeAt(0).insertNode(document.createTextNode(t)),e.preventDefault()}})),this.textEditDiv.addEventListener("pointerup",(function(){e.textEditDivClicked(e.textEditor.innerText)})),this.textEditDiv.appendChild(this.textEditor),this.overlayContainer.appendChild(this.textEditDiv),this.hideVisual(),this.textEditor.focus(),document.execCommand("selectAll")},t.prototype.positionTextEditor=function(){if("edit"===this.state)if(void 0===this.textEditor)this.showTextEditor();else{this.textElement.style.display="";var e=this.getTextScale(),t=this.rotatePoint({x:this.left+this.width/2,y:this.top+this.height/2}),n=this.textElement.getBBox(),i={x:n.width*e,y:n.height*e};t.x-=i.x/2,t.y-=i.y/2,this.textEditor.style.top=t.y+"px",this.textEditor.style.left=t.x+"px",this.textEditor.style.maxWidth=this.overlayContainer.offsetWidth-t.x+"px",this.textEditor.style.fontSize=Math.max(16*e,12)+"px",this.textElement.style.display="none"}},t.prototype.textEditDivClicked=function(e){this.text=e.trim(),this.overlayContainer.innerHTML="",this.renderText(),this.showVisual(),this._suppressMarkerCreateEvent&&(this._suppressMarkerCreateEvent=!1,this.onMarkerCreated&&this.onMarkerCreated(this)),this.stateChanged()},t.prototype.select=function(){e.prototype.select.call(this),"edit"===this.state&&this.textEditDivClicked(this.textEditor.innerText)},t.prototype.deselect=function(){"edit"===this.state&&this.textEditDivClicked(this.textEditor.innerText),e.prototype.deselect.call(this)},t.prototype.dblClick=function(t,n){e.prototype.dblClick.call(this,t,n),this.showTextEditor()},t.prototype.setColor=function(e){this.textElement&&l.setAttributes(this.textElement,[["fill",e]]),this.color=e,this.textEditor&&(this.textEditor.style.color=this.color),this.colorChanged(e)},t.prototype.setFont=function(e){this.textElement&&l.setAttributes(this.textElement,[["font-family",e]]),this.fontFamily=e,this.textEditor&&(this.textEditor.style.fontFamily=this.fontFamily),this.renderText(),this.stateChanged()},t.prototype.hideVisual=function(){this.textElement.style.display="none",this.hideControlBox()},t.prototype.showVisual=function(){"edit"===this.state&&(this._state="select"),this.textElement.style.display="",this.showControlBox()},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.colorPanel,this.fontFamilyPanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=Object.assign({color:this.color,fontFamily:this.fontFamily,padding:this.padding,text:this.text},e.prototype.getState.call(this));return n.typeName=t.typeName,n},t.prototype.restoreState=function(t){var n=t;this.color=n.color,this.fontFamily=n.fontFamily,this.padding=n.padding,this.text=n.text,this.createVisual(),e.prototype.restoreState.call(this,t),this.setSize()},t.prototype.scale=function(t,n){e.prototype.scale.call(this,t,n),this.setSize(),this.sizeText(),this.positionTextEditor()},t.typeName="TextMarker",t.title="Text marker",t.icon='<svg viewBox="0 0 24 24"><path d="M9.6 14L12 7.7l2.4 6.3M11 5L5.5 19h2.2l1.1-3H15l1.1 3h2.2L13 5h-2z"/></svg>',t}(C),L=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.color="transparent",r.lineWidth=3,r.drawing=!1,r.pixelRatio=1,r.color=i.defaultColor,r.lineWidth=i.defaultStrokeWidth,r.pixelRatio=i.freehandPixelRatio,r.setColor=r.setColor.bind(r),r.addCanvas=r.addCanvas.bind(r),r.finishCreation=r.finishCreation.bind(r),r.setLineWidth=r.setLineWidth.bind(r),r.colorPanel=new A("Color",i.defaultColorSet,i.defaultColor),r.colorPanel.onColorChanged=r.setColor,r.lineWidthPanel=new E("Line width",i.defaultStrokeWidths,i.defaultStrokeWidth),r.lineWidthPanel.onWidthChanged=r.setLineWidth,r}return r(t,e),t.prototype.ownsTarget=function(t){return!(!e.prototype.ownsTarget.call(this,t)&&t!==this.visual&&t!==this.drawingImage)},t.prototype.createVisual=function(){this.visual=l.createGroup(),this.drawingImage=l.createImage(),this.visual.appendChild(this.drawingImage);var e=l.createTransform();this.visual.transform.baseVal.appendItem(e),this.addMarkerVisualToContainer(this.visual)},t.prototype.pointerDown=function(t,n){"new"===this.state&&(this.addCanvas(),this.createVisual(),this._state="creating"),"creating"===this.state?(this.canvasContext.strokeStyle=this.color,this.canvasContext.lineWidth=this.lineWidth,this.canvasContext.beginPath(),this.canvasContext.moveTo(t.x,t.y),this.drawing=!0):e.prototype.pointerDown.call(this,t,n)},t.prototype.manipulate=function(t){"creating"===this.state?this.drawing&&(this.canvasContext.lineTo(t.x,t.y),this.canvasContext.stroke()):e.prototype.manipulate.call(this,t)},t.prototype.resize=function(t){e.prototype.resize.call(this,t),l.setAttributes(this.visual,[["width",this.width.toString()],["height",this.height.toString()]]),l.setAttributes(this.drawingImage,[["width",this.width.toString()],["height",this.height.toString()]])},t.prototype.pointerUp=function(t){"creating"===this._state?this.drawing&&(this.canvasContext.closePath(),this.drawing=!1,this.globalSettings.newFreehandMarkerOnPointerUp&&this.finishCreation()):e.prototype.pointerUp.call(this,t)},t.prototype.addCanvas=function(){this.overlayContainer.innerHTML="",this.canvasElement=document.createElement("canvas"),this.canvasElement.width=this.overlayContainer.clientWidth*this.pixelRatio,this.canvasElement.height=this.overlayContainer.clientHeight*this.pixelRatio,this.canvasContext=this.canvasElement.getContext("2d"),this.canvasContext.scale(this.pixelRatio,this.pixelRatio),this.overlayContainer.appendChild(this.canvasElement)},t.prototype.select=function(){"creating"===this.state&&this.finishCreation(),e.prototype.select.call(this)},t.prototype.deselect=function(){"creating"===this.state&&this.finishCreation(),e.prototype.deselect.call(this)},t.prototype.finishCreation=function(){for(var e=this.canvasContext.getImageData(0,0,this.canvasElement.width,this.canvasElement.height),t=[this.canvasElement.width+1,this.canvasElement.height+1,-1,-1],n=t[0],i=t[1],r=t[2],s=t[3],o=!1,a=0;a<this.canvasElement.height;a++)for(var l=0;l<this.canvasElement.width;l++)e.data[a*this.canvasElement.width*4+4*l+3]>0&&(o=!0,a<i&&(i=a),l<n&&(n=l),a>s&&(s=a),l>r&&(r=l));if(o){this.left=n/this.pixelRatio,this.top=i/this.pixelRatio,this.width=(r-n)/this.pixelRatio,this.height=(s-i)/this.pixelRatio;var u=document.createElement("canvas");u.width=r-n,u.height=s-i,u.getContext("2d").putImageData(this.canvasContext.getImageData(n,i,r-n,s-i),0,0),this.drawingImgUrl=u.toDataURL("image/png"),this.setDrawingImage(),this._state="select",this.onMarkerCreated&&this.onMarkerCreated(this)}this.overlayContainer.innerHTML=""},t.prototype.setDrawingImage=function(){l.setAttributes(this.drawingImage,[["width",this.width.toString()],["height",this.height.toString()]]),l.setAttributes(this.drawingImage,[["href",this.drawingImgUrl]]),this.moveVisual({x:this.left,y:this.top})},t.prototype.setColor=function(e){this.color=e,this.colorChanged(e)},t.prototype.setLineWidth=function(e){this.lineWidth=e},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return"new"===this.state||"creating"===this.state?[this.colorPanel,this.lineWidthPanel]:[]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=Object.assign({drawingImgUrl:this.drawingImgUrl},e.prototype.getState.call(this));return n.typeName=t.typeName,n},t.prototype.restoreState=function(t){this.createVisual(),e.prototype.restoreState.call(this,t),this.drawingImgUrl=t.drawingImgUrl,this.setDrawingImage()},t.prototype.scale=function(t,n){e.prototype.scale.call(this,t,n),this.setDrawingImage()},t.typeName="FreehandMarker",t.title="Freehand marker",t.icon='<svg viewBox="0 0 24 24"><path d="M9.75 20.85c1.78-.7 1.39-2.63.49-3.85-.89-1.25-2.12-2.11-3.36-2.94A9.817 9.817 0 014.54 12c-.28-.33-.85-.94-.27-1.06.59-.12 1.61.46 2.13.68.91.38 1.81.82 2.65 1.34l1.01-1.7C8.5 10.23 6.5 9.32 4.64 9.05c-1.06-.16-2.18.06-2.54 1.21-.32.99.19 1.99.77 2.77 1.37 1.83 3.5 2.71 5.09 4.29.34.33.75.72.95 1.18.21.44.16.47-.31.47-1.24 0-2.79-.97-3.8-1.61l-1.01 1.7c1.53.94 4.09 2.41 5.96 1.79m11.09-15.6c.22-.22.22-.58 0-.79l-1.3-1.3a.562.562 0 00-.78 0l-1.02 1.02 2.08 2.08M11 10.92V13h2.08l6.15-6.15-2.08-2.08L11 10.92z"/></svg>',t}(C),j=function(e){function t(t,n,i){var r=e.call(this,t,i||'<svg viewBox="0 0 24 24"><path d="M8 14v4l-6-6 6-6v4h8V6l6 6-6 6v-4H8z"/></svg>')||this;return r.typeBoxes=[],r.currentType=n,r.setCurrentType=r.setCurrentType.bind(r),r}return r(t,e),t.prototype.getUi=function(){var e=this,t=document.createElement("div");t.style.display="flex",t.style.overflow="hidden",t.style.flexGrow="2";for(var n=function(n){var r="both";switch(n){case 0:r="both";break;case 1:r="start";break;case 2:r="end";break;case 3:r="none"}var s=document.createElement("div");if(s.style.display="flex",s.style.flexGrow="2",s.style.alignItems="center",s.style.justifyContent="space-between",s.style.padding="5px",s.style.borderWidth="2px",s.style.borderStyle="solid",s.style.borderColor=r===i.currentType?i.uiStyleSettings.toolboxAccentColor:"transparent",s.addEventListener("click",(function(){e.setCurrentType(r,s)})),t.appendChild(s),"both"===r||"start"===r){var o=document.createElement("div");o.style.display="flex",o.style.alignItems="center",o.style.minHeight="20px",o.innerHTML='<svg viewBox="0 0 10 10" width="10" height="10" xmlns="http://www.w3.org/2000/svg">\n          <polygon points="0,5 10,0 10,10" fill="'+(void 0!==i.uiStyleSettings?i.uiStyleSettings.toolboxColor:"#eeeeee")+'" />\n        </svg>',o.style.marginLeft="5px",s.appendChild(o)}var a=document.createElement("div");a.style.display="flex",a.style.alignItems="center",a.style.minHeight="20px",a.style.flexGrow="2";var l=document.createElement("hr");if(l.style.minWidth="20px",l.style.border="0px",l.style.borderTop="3px solid "+(void 0!==i.uiStyleSettings?i.uiStyleSettings.toolboxColor:"#eeeeee"),l.style.flexGrow="2",a.appendChild(l),s.appendChild(a),"both"===r||"end"===r){var u=document.createElement("div");u.style.display="flex",u.style.alignItems="center",u.style.minHeight="20px",u.innerHTML='<svg viewBox="0 0 10 10" width="10" height="10" xmlns="http://www.w3.org/2000/svg">\n          <polygon points="0,0 10,5 0,10" fill="'+(void 0!==i.uiStyleSettings?i.uiStyleSettings.toolboxColor:"#eeeeee")+'" />\n        </svg>',u.style.marginRight="5px",s.appendChild(u)}i.typeBoxes.push(s)},i=this,r=0;r<4;r++)n(r);return t},t.prototype.setCurrentType=function(e,t){var n=this;this.currentType=e,this.typeBoxes.forEach((function(e){e.style.borderColor=e===t?void 0!==n.uiStyleSettings?n.uiStyleSettings.toolboxAccentColor:"#3080c3":"transparent"})),this.onArrowTypeChanged&&this.onArrowTypeChanged(this.currentType)},t}(v),O=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.arrowType="end",r.arrowBaseHeight=10,r.arrowBaseWidth=10,r.getArrowPoints=r.getArrowPoints.bind(r),r.setArrowType=r.setArrowType.bind(r),r.arrowTypePanel=new j("Arrow type","end"),r.arrowTypePanel.onArrowTypeChanged=r.setArrowType,r}return r(t,e),t.prototype.ownsTarget=function(t){return!(!e.prototype.ownsTarget.call(this,t)&&t!==this.arrow1&&t!==this.arrow2)},t.prototype.getArrowPoints=function(e,t){var n=this.arrowBaseWidth+2*this.strokeWidth,i=this.arrowBaseHeight+2*this.strokeWidth;return e-n/2+","+(t+i/2)+" "+e+","+(t-i/2)+" "+(e+n/2)+","+(t+i/2)},t.prototype.createTips=function(){this.arrow1=l.createPolygon(this.getArrowPoints(this.x1,this.y1),[["fill",this.strokeColor]]),this.arrow1.transform.baseVal.appendItem(l.createTransform()),this.visual.appendChild(this.arrow1),this.arrow2=l.createPolygon(this.getArrowPoints(this.x2,this.y2),[["fill",this.strokeColor]]),this.arrow2.transform.baseVal.appendItem(l.createTransform()),this.visual.appendChild(this.arrow2)},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),"creating"===this.state&&this.createTips()},t.prototype.adjustVisual=function(){if(e.prototype.adjustVisual.call(this),this.arrow1&&this.arrow2){this.arrow1.style.display="both"===this.arrowType||"start"===this.arrowType?"":"none",this.arrow2.style.display="both"===this.arrowType||"end"===this.arrowType?"":"none",l.setAttributes(this.arrow1,[["points",this.getArrowPoints(this.x1,this.y1)],["fill",this.strokeColor]]),l.setAttributes(this.arrow2,[["points",this.getArrowPoints(this.x2,this.y2)],["fill",this.strokeColor]]);var t=0;Math.abs(this.x1-this.x2)>.1&&(t=180*Math.atan((this.y2-this.y1)/(this.x2-this.x1))/Math.PI+90*Math.sign(this.x1-this.x2));var n=this.arrow1.transform.baseVal.getItem(0);n.setRotate(t,this.x1,this.y1),this.arrow1.transform.baseVal.replaceItem(n,0);var i=this.arrow2.transform.baseVal.getItem(0);i.setRotate(t+180,this.x2,this.y2),this.arrow2.transform.baseVal.replaceItem(i,0)}},t.prototype.setArrowType=function(e){this.arrowType=e,this.adjustVisual(),this.stateChanged()},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.strokePanel,this.strokeWidthPanel,this.strokeStylePanel,this.arrowTypePanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=Object.assign({arrowType:this.arrowType},e.prototype.getState.call(this));return n.typeName=t.typeName,n},t.prototype.restoreState=function(t){e.prototype.restoreState.call(this,t);var n=t;this.arrowType=n.arrowType,this.createTips(),this.adjustVisual()},t.typeName="ArrowMarker",t.title="Arrow marker",t.icon='<svg viewBox="0 0 24 24"><path d="M19 6.41L17.59 5 7 15.59V9H5v10h10v-2H8.41L19 6.41z"/></svg>',t}(B),z=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.fillColor=i.defaultFillColor,r.strokeWidth=0,r.fillPanel=new A("Color",i.defaultColorSet,i.defaultFillColor),r.fillPanel.onColorChanged=r.setFillColor,r}return r(t,e),Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.fillPanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=e.prototype.getState.call(this);return n.typeName=t.typeName,n},t.typeName="CoverMarker",t.title="Cover marker",t.icon='<svg viewBox="0 0 24 24"><path d="M4 6v13h16V6H4z"/></svg>',t}(M),R=function(e){function t(t,n,i,r){var s=e.call(this,t,r||'<svg viewBox="0 0 24 24"><path d="M17.66 8L12 2.35 6.34 8A8.02 8.02 0 004 13.64c0 2 .78 4.11 2.34 5.67a7.99 7.99 0 0011.32 0c1.56-1.56 2.34-3.67 2.34-5.67S19.22 9.56 17.66 8M6 14c0-2 .62-3.27 1.76-4.4L12 5.27l4.24 4.38C17.38 10.77 18 12 18 14H6z"/></svg>')||this;return s.opacities=[],s.opacityBoxes=[],s.opacities=n,s.currentOpacity=i,s.setCurrentOpacity=s.setCurrentOpacity.bind(s),s}return r(t,e),t.prototype.getUi=function(){var e=this,t=document.createElement("div");return t.style.display="flex",t.style.overflow="hidden",t.style.flexGrow="2",t.style.justifyContent="space-between",this.opacities.forEach((function(n){var i=document.createElement("div");i.style.display="flex",i.style.alignItems="center",i.style.justifyContent="center",i.style.padding="5px",i.style.borderWidth="2px",i.style.borderStyle="solid",i.style.borderColor=n===e.currentOpacity?e.uiStyleSettings.toolboxAccentColor:"transparent",i.addEventListener("click",(function(){e.setCurrentOpacity(n,i)})),t.appendChild(i);var r=document.createElement("div");r.innerText=100*n+"%",i.appendChild(r),e.opacityBoxes.push(i)})),t},t.prototype.setCurrentOpacity=function(e,t){var n=this;this.currentOpacity=e,this.opacityBoxes.forEach((function(e){e.style.borderColor=e===t?n.uiStyleSettings.toolboxAccentColor:"transparent"})),this.onOpacityChanged&&this.onOpacityChanged(this.currentOpacity)},t}(v),k=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.setOpacity=r.setOpacity.bind(r),r.fillColor=i.defaultHighlightColor,r.strokeWidth=0,r.opacity=i.defaultHighlightOpacity,r.fillPanel=new A("Color",i.defaultColorSet,r.fillColor),r.fillPanel.onColorChanged=r.setFillColor,r.opacityPanel=new R("Opacity",i.defaultOpacitySteps,r.opacity),r.opacityPanel.onOpacityChanged=r.setOpacity,r}return r(t,e),t.prototype.setOpacity=function(e){this.opacity=e,this.visual&&l.setAttributes(this.visual,[["opacity",this.opacity.toString()]]),this.stateChanged()},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.fillPanel,this.opacityPanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=e.prototype.getState.call(this);return n.typeName=t.typeName,n},t.typeName="HighlightMarker",t.title="Highlight marker",t.icon='<svg viewBox="0 0 24 24"><path d="M18.5 1.15c-.53 0-1.04.19-1.43.58l-5.81 5.82 5.65 5.65 5.82-5.81c.77-.78.77-2.04 0-2.83l-2.84-2.83c-.39-.39-.89-.58-1.39-.58M10.3 8.5l-5.96 5.96c-.78.78-.78 2.04.02 2.85C3.14 18.54 1.9 19.77.67 21h5.66l.86-.86c.78.76 2.03.75 2.81-.02l5.95-5.96"/></svg>',t}(z),F='<svg viewBox="0 0 24 24"><path d="M9.62 12L12 5.67 14.37 12M11 3L5.5 17h2.25l1.12-3h6.25l1.13 3h2.25L13 3h-2z"/></svg>',H='<svg viewBox="0 0 24 24"><path d="M19 11.5s-2 2.17-2 3.5a2 2 0 002 2 2 2 0 002-2c0-1.33-2-3.5-2-3.5M5.21 10L10 5.21 14.79 10m1.77-1.06L7.62 0 6.21 1.41l2.38 2.38-5.15 5.15c-.59.56-.59 1.53 0 2.12l5.5 5.5c.29.29.68.44 1.06.44s.77-.15 1.06-.44l5.5-5.5c.59-.59.59-1.56 0-2.12z"/></svg>',U=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.bgColor="transparent",r.tipPosition={x:0,y:0},r.tipBase1Position={x:0,y:0},r.tipBase2Position={x:0,y:0},r.tipMoving=!1,r.color=i.defaultStrokeColor,r.bgColor=i.defaultFillColor,r.fontFamily=i.defaultFontFamily,r.defaultSize={x:100,y:30},r.setBgColor=r.setBgColor.bind(r),r.getTipPoints=r.getTipPoints.bind(r),r.positionTip=r.positionTip.bind(r),r.setTipPoints=r.setTipPoints.bind(r),r.colorPanel=new A("Text color",i.defaultColorSet,r.color,F),r.colorPanel.onColorChanged=r.setColor,r.bgColorPanel=new A("Fill color",i.defaultColorSet,r.bgColor,H),r.bgColorPanel.onColorChanged=r.setBgColor,r.fontFamilyPanel=new D("Font",i.defaultFontFamilies,i.defaultFontFamily),r.fontFamilyPanel.onFontChanged=r.setFont,r.tipGrip=new b,r.tipGrip.visual.transform.baseVal.appendItem(l.createTransform()),r.controlBox.appendChild(r.tipGrip.visual),r}return r(t,e),t.prototype.ownsTarget=function(t){return e.prototype.ownsTarget.call(this,t)||this.tipGrip.ownsTarget(t)||this.tip===t},t.prototype.createTip=function(){l.setAttributes(this.bgRectangle,[["fill",this.bgColor],["rx","10px"]]),this.tip=l.createPolygon(this.getTipPoints(),[["fill",this.bgColor]]),this.visual.appendChild(this.tip)},t.prototype.pointerDown=function(t,n){"new"===this.state&&e.prototype.pointerDown.call(this,t,n),"creating"===this.state?this.createTip():this.tipGrip.ownsTarget(n)?(this.manipulationStartLeft=this.left,this.manipulationStartTop=this.top,this.tipMoving=!0):e.prototype.pointerDown.call(this,t,n)},t.prototype.pointerUp=function(t){if(this.tipMoving)this.tipMoving=!1,this.isMoved=!0,e.prototype.pointerUp.call(this,t);else{var n="creating"===this.state;e.prototype.pointerUp.call(this,t),this.setTipPoints(n),this.positionTip()}},t.prototype.manipulate=function(t){if(this.tipMoving){var n=this.unrotatePoint(t);this.tipPosition={x:n.x-this.manipulationStartLeft,y:n.y-this.manipulationStartTop},this.positionTip()}else e.prototype.manipulate.call(this,t)},t.prototype.setBgColor=function(e){this.bgRectangle&&this.tip&&(l.setAttributes(this.bgRectangle,[["fill",e]]),l.setAttributes(this.tip,[["fill",e]])),this.bgColor=e,this.fillColorChanged(e)},t.prototype.getTipPoints=function(){return this.setTipPoints("creating"===this.state),this.tipBase1Position.x+","+this.tipBase1Position.y+" "+this.tipBase2Position.x+","+this.tipBase2Position.y+" "+this.tipPosition.x+","+this.tipPosition.y},t.prototype.setTipPoints=function(e){void 0===e&&(e=!1);var t=Math.min(this.height/2,15),n=this.height/5;e&&(this.tipPosition={x:t+n/2,y:this.height+20});var i=Math.atan(this.height/2/(this.width/2));this.tipPosition.x<this.width/2&&this.tipPosition.y<this.height/2?i<Math.atan((this.height/2-this.tipPosition.y)/(this.width/2-this.tipPosition.x))?(n=this.width/5,t=Math.min(this.width/2,15),this.tipBase1Position={x:t,y:0},this.tipBase2Position={x:t+n,y:0}):(this.tipBase1Position={x:0,y:t},this.tipBase2Position={x:0,y:t+n}):this.tipPosition.x>=this.width/2&&this.tipPosition.y<this.height/2?i<Math.atan((this.height/2-this.tipPosition.y)/(this.tipPosition.x-this.width/2))?(n=this.width/5,t=Math.min(this.width/2,15),this.tipBase1Position={x:this.width-t-n,y:0},this.tipBase2Position={x:this.width-t,y:0}):(this.tipBase1Position={x:this.width,y:t},this.tipBase2Position={x:this.width,y:t+n}):this.tipPosition.x>=this.width/2&&this.tipPosition.y>=this.height/2?i<Math.atan((this.tipPosition.y-this.height/2)/(this.tipPosition.x-this.width/2))?(n=this.width/5,t=Math.min(this.width/2,15),this.tipBase1Position={x:this.width-t-n,y:this.height},this.tipBase2Position={x:this.width-t,y:this.height}):(this.tipBase1Position={x:this.width,y:this.height-t-n},this.tipBase2Position={x:this.width,y:this.height-t}):i<Math.atan((this.tipPosition.y-this.height/2)/(this.width/2-this.tipPosition.x))?(n=this.width/5,t=Math.min(this.width/2,15),this.tipBase1Position={x:t,y:this.height},this.tipBase2Position={x:t+n,y:this.height}):(this.tipBase1Position={x:0,y:this.height-t},this.tipBase2Position={x:0,y:this.height-t-n})},t.prototype.resize=function(t){e.prototype.resize.call(this,t),this.positionTip()},t.prototype.positionTip=function(){l.setAttributes(this.tip,[["points",this.getTipPoints()]]);var e=this.tipGrip.visual.transform.baseVal.getItem(0);e.setTranslate(this.tipPosition.x,this.tipPosition.y),this.tipGrip.visual.transform.baseVal.replaceItem(e,0)},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.colorPanel,this.bgColorPanel,this.fontFamilyPanel]},enumerable:!1,configurable:!0}),t.prototype.select=function(){this.positionTip(),e.prototype.select.call(this)},t.prototype.getState=function(){var n=Object.assign({bgColor:this.bgColor,tipPosition:this.tipPosition},e.prototype.getState.call(this));return n.typeName=t.typeName,n},t.prototype.restoreState=function(t){var n=t;this.bgColor=n.bgColor,this.tipPosition=n.tipPosition,e.prototype.restoreState.call(this,t),this.createTip(),this.setTipPoints()},t.prototype.scale=function(t,n){e.prototype.scale.call(this,t,n),this.tipPosition={x:this.tipPosition.x*t,y:this.tipPosition.y*n},this.positionTip()},t.typeName="CalloutMarker",t.title="Callout marker",t.icon='<svg viewBox="0 0 24 24"><path d="M4 2h16a2 2 0 012 2v12a2 2 0 01-2 2h-4l-4 4-4-4H4a2 2 0 01-2-2V4a2 2 0 012-2m0 2v12h4.83L12 19.17 15.17 16H20V4H4m2 3h12v2H6V7m0 4h10v2H6v-2z"/></svg>',t}(I),X=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.fillColor="transparent",r.strokeColor="transparent",r.strokeWidth=0,r.strokeDasharray="",r.opacity=1,r.strokeColor=i.defaultColor,r.strokeWidth=i.defaultStrokeWidth,r.strokeDasharray=i.defaultStrokeDasharray,r.fillColor=i.defaultFillColor,r.setStrokeColor=r.setStrokeColor.bind(r),r.setFillColor=r.setFillColor.bind(r),r.setStrokeWidth=r.setStrokeWidth.bind(r),r.setStrokeDasharray=r.setStrokeDasharray.bind(r),r.setOpacity=r.setOpacity.bind(r),r.createVisual=r.createVisual.bind(r),r.strokePanel=new A("Line color",a(i.defaultColorSet,["transparent"]),i.defaultColor),r.strokePanel.onColorChanged=r.setStrokeColor,r.fillPanel=new A("Fill color",a(i.defaultColorSet,["transparent"]),r.fillColor,H),r.fillPanel.onColorChanged=r.setFillColor,r.strokeWidthPanel=new E("Line width",i.defaultStrokeWidths,i.defaultStrokeWidth),r.strokeWidthPanel.onWidthChanged=r.setStrokeWidth,r.strokeStylePanel=new T("Line style",i.defaultStrokeDasharrays,i.defaultStrokeDasharray),r.strokeStylePanel.onStyleChanged=r.setStrokeDasharray,r.opacityPanel=new R("Opacity",i.defaultOpacitySteps,r.opacity),r.opacityPanel.onOpacityChanged=r.setOpacity,r}return r(t,e),t.prototype.ownsTarget=function(t){return!(!e.prototype.ownsTarget.call(this,t)&&t!==this.visual)},t.prototype.createVisual=function(){this.visual=l.createEllipse(this.width/2,this.height/2,[["fill",this.fillColor],["stroke",this.strokeColor],["stroke-width",this.strokeWidth.toString()],["stroke-dasharray",this.strokeDasharray],["opacity",this.opacity.toString()]]),this.addMarkerVisualToContainer(this.visual)},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),"new"===this.state&&(this.createVisual(),this.moveVisual(t),this._state="creating")},t.prototype.manipulate=function(t){e.prototype.manipulate.call(this,t)},t.prototype.resize=function(t){e.prototype.resize.call(this,t),this.setSize()},t.prototype.setSize=function(){e.prototype.setSize.call(this),l.setAttributes(this.visual,[["cx",(this.width/2).toString()],["cy",(this.height/2).toString()],["rx",(this.width/2).toString()],["ry",(this.height/2).toString()]])},t.prototype.pointerUp=function(t){e.prototype.pointerUp.call(this,t),this.setSize()},t.prototype.setStrokeColor=function(e){this.strokeColor=e,this.visual&&l.setAttributes(this.visual,[["stroke",this.strokeColor]]),this.colorChanged(e),this.stateChanged()},t.prototype.setFillColor=function(e){this.fillColor=e,this.visual&&l.setAttributes(this.visual,[["fill",this.fillColor]]),this.fillColorChanged(e),this.stateChanged()},t.prototype.setStrokeWidth=function(e){this.strokeWidth=e,this.visual&&l.setAttributes(this.visual,[["stroke-width",this.strokeWidth.toString()]]),this.stateChanged()},t.prototype.setStrokeDasharray=function(e){this.strokeDasharray=e,this.visual&&l.setAttributes(this.visual,[["stroke-dasharray",this.strokeDasharray]]),this.stateChanged()},t.prototype.setOpacity=function(e){this.opacity=e,this.visual&&l.setAttributes(this.visual,[["opacity",this.opacity.toString()]]),this.stateChanged()},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.strokePanel,this.fillPanel,this.strokeWidthPanel,this.strokeStylePanel,this.opacityPanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=Object.assign({fillColor:this.fillColor,strokeColor:this.strokeColor,strokeWidth:this.strokeWidth,strokeDasharray:this.strokeDasharray,opacity:this.opacity},e.prototype.getState.call(this));return n.typeName=t.typeName,n},t.prototype.restoreState=function(t){var n=t;this.fillColor=n.fillColor,this.strokeColor=n.strokeColor,this.strokeWidth=n.strokeWidth,this.strokeDasharray=n.strokeDasharray,this.opacity=n.opacity,this.createVisual(),e.prototype.restoreState.call(this,t),this.setSize()},t.prototype.scale=function(t,n){e.prototype.scale.call(this,t,n),this.setSize()},t.typeName="EllipseMarker",t.title="Ellipse marker",t.icon='<svg viewBox="0 0 24 24"><path d="M12 4C6.5 4 2 7.58 2 12s4.5 8 10 8 10-3.58 10-8-4.5-8-10-8z"/></svg>',t}(C),G=function(e){function t(t,n,i){return e.call(this,t,n,i)||this}return r(t,e),Object.defineProperty(t.prototype,"tipLength",{get:function(){return 10+3*this.strokeWidth},enumerable:!1,configurable:!0}),t.prototype.ownsTarget=function(t){return!(!e.prototype.ownsTarget.call(this,t)&&t!==this.tip1&&t!==this.tip2)},t.prototype.createTips=function(){this.tip1=l.createLine(this.x1-this.tipLength/2,this.y1,this.x1+this.tipLength/2,this.y1,[["stroke",this.strokeColor],["stroke-width",this.strokeWidth.toString()]]),this.tip1.transform.baseVal.appendItem(l.createTransform()),this.visual.appendChild(this.tip1),this.tip2=l.createLine(this.x2-this.tipLength/2,this.y2,this.x2+this.tipLength/2,this.y2,[["stroke",this.strokeColor],["stroke-width",this.strokeWidth.toString()]]),this.tip2.transform.baseVal.appendItem(l.createTransform()),this.visual.appendChild(this.tip2)},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),"creating"===this.state&&this.createTips()},t.prototype.adjustVisual=function(){if(e.prototype.adjustVisual.call(this),this.tip1&&this.tip2&&(l.setAttributes(this.tip1,[["x1",(this.x1-this.tipLength/2).toString()],["y1",this.y1.toString()],["x2",(this.x1+this.tipLength/2).toString()],["y2",this.y1.toString()],["stroke",this.strokeColor],["stroke-width",this.strokeWidth.toString()]]),l.setAttributes(this.tip2,[["x1",(this.x2-this.tipLength/2).toString()],["y1",this.y2.toString()],["x2",(this.x2+this.tipLength/2).toString()],["y2",this.y2.toString()],["stroke",this.strokeColor],["stroke-width",this.strokeWidth.toString()]]),Math.abs(this.x1-this.x2)>.1)){var t=180*Math.atan((this.y2-this.y1)/(this.x2-this.x1))/Math.PI+90*Math.sign(this.x1-this.x2),n=this.tip1.transform.baseVal.getItem(0);n.setRotate(t,this.x1,this.y1),this.tip1.transform.baseVal.replaceItem(n,0);var i=this.tip2.transform.baseVal.getItem(0);i.setRotate(t+180,this.x2,this.y2),this.tip2.transform.baseVal.replaceItem(i,0)}},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.strokePanel,this.strokeWidthPanel,this.strokeStylePanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=e.prototype.getState.call(this);return n.typeName=t.typeName,n},t.prototype.restoreState=function(t){e.prototype.restoreState.call(this,t),this.createTips(),this.adjustVisual()},t.typeName="MeasurementMarker",t.title="Measurement marker",t.icon='<svg viewBox="0 0 24 24"><path d="M1.39 18.36l1.77-1.76L4.58 18l1.06-1.05-1.42-1.41 1.42-1.42 2.47 2.48 1.06-1.06-2.47-2.48 1.41-1.41 1.42 1.41L10.59 12l-1.42-1.41 1.42-1.42 2.47 2.48 1.06-1.06-2.47-2.48 1.41-1.41 1.41 1.41 1.07-1.06-1.42-1.41 1.42-1.42L18 6.7l1.07-1.06-2.47-2.48 1.76-1.77 4.25 4.25L5.64 22.61l-4.25-4.25z"/></svg>',t}(B),V=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.strokePanel.colors=i.defaultColorSet,r.fillColor="transparent",r}return r(t,e),Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.strokePanel,this.strokeWidthPanel,this.strokeStylePanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=e.prototype.getState.call(this);return n.typeName=t.typeName,n},t.typeName="EllipseFrameMarker",t.title="Ellipse frame marker",t.icon='<svg viewBox="0 0 24 24"><path d="M12 6c4.41 0 8 2.69 8 6s-3.59 6-8 6-8-2.69-8-6 3.59-6 8-6m0-2C6.5 4 2 7.58 2 12s4.5 8 10 8 10-3.58 10-8-4.5-8-10-8z"/></svg>',t}(X),W=function(){function e(){this.undoStack=[],this.redoStack=[]}return Object.defineProperty(e.prototype,"isUndoPossible",{get:function(){return this.undoStack.length>0},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"isRedoPossible",{get:function(){return this.redoStack.length>0},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"undoStepCount",{get:function(){return this.undoStack.length},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"redoStepCount",{get:function(){return this.redoStack.length},enumerable:!1,configurable:!0}),e.prototype.addUndoStep=function(e){0!==this.undoStack.length&&JSON.stringify(this.undoStack[this.undoStack.length-1])===JSON.stringify(e)||(this.undoStack.push(e),JSON.stringify(this.lastRedoStep)!==JSON.stringify(e)&&this.redoStack.splice(0,this.redoStack.length))},e.prototype.replaceLastUndoStep=function(e){this.undoStack.length>0&&(this.undoStack[this.undoStack.length-1]=e)},e.prototype.getLastUndoStep=function(){return this.undoStack.length>0?this.undoStack[this.undoStack.length-1]:void 0},e.prototype.undo=function(){if(this.undoStack.length>1){var e=this.undoStack.pop();return void 0!==e&&this.redoStack.push(e),this.undoStack.length>0?this.undoStack[this.undoStack.length-1]:void 0}},e.prototype.redo=function(){return this.lastRedoStep=this.redoStack.pop(),this.lastRedoStep},e}(),Q=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.strokeColor="transparent",r.strokeWidth=0,r.strokeDasharray="",r.curveX=0,r.curveY=0,r.manipulationStartCurveX=0,r.manipulationStartCurveY=0,r.setStrokeColor=r.setStrokeColor.bind(r),r.setStrokeWidth=r.setStrokeWidth.bind(r),r.setStrokeDasharray=r.setStrokeDasharray.bind(r),r.positionGrips=r.positionGrips.bind(r),r.addControlGrips=r.addControlGrips.bind(r),r.adjustVisual=r.adjustVisual.bind(r),r.setupControlBox=r.setupControlBox.bind(r),r.resize=r.resize.bind(r),r.strokeColor=i.defaultColor,r.strokeWidth=i.defaultStrokeWidth,r.strokeDasharray=i.defaultStrokeDasharray,r.strokePanel=new A("Line color",i.defaultColorSet,i.defaultColor),r.strokePanel.onColorChanged=r.setStrokeColor,r.strokeWidthPanel=new E("Line width",i.defaultStrokeWidths,i.defaultStrokeWidth),r.strokeWidthPanel.onWidthChanged=r.setStrokeWidth,r.strokeStylePanel=new T("Line style",i.defaultStrokeDasharrays,i.defaultStrokeDasharray),r.strokeStylePanel.onStyleChanged=r.setStrokeDasharray,r}return r(t,e),t.prototype.ownsTarget=function(t){return!(!e.prototype.ownsTarget.call(this,t)&&t!==this.visual&&t!==this.selectorCurve&&t!==this.visibleCurve&&!this.curveGrip.ownsTarget(t))},t.prototype.getPathD=function(){return"M "+this.x1+" "+this.y1+" Q "+this.curveX+" "+this.curveY+", "+this.x2+" "+this.y2},t.prototype.createVisual=function(){this.visual=l.createGroup(),this.selectorCurve=l.createPath(this.getPathD(),[["stroke","transparent"],["stroke-width",(this.strokeWidth+10).toString()],["fill","transparent"]]),this.visibleCurve=l.createPath(this.getPathD(),[["stroke",this.strokeColor],["stroke-width",this.strokeWidth.toString()],["fill","transparent"]]),this.visual.appendChild(this.selectorCurve),this.visual.appendChild(this.visibleCurve),this.addMarkerVisualToContainer(this.visual)},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),this.manipulationStartCurveX=this.curveX,this.manipulationStartCurveY=this.curveY,"new"===this.state&&(this.curveX=t.x,this.curveY=t.y),"new"===this.state?(this.createVisual(),this.adjustVisual(),this._state="creating"):this.curveGrip.ownsTarget(n)&&(this.activeGrip=this.curveGrip,this._state="resize")},t.prototype.adjustVisual=function(){this.selectorCurve&&this.visibleCurve&&(this.selectorCurve.setAttribute("d",this.getPathD()),this.visibleCurve.setAttribute("d",this.getPathD()),l.setAttributes(this.visibleCurve,[["stroke",this.strokeColor]]),l.setAttributes(this.visibleCurve,[["stroke-width",this.strokeWidth.toString()]]),l.setAttributes(this.visibleCurve,[["stroke-dasharray",this.strokeDasharray.toString()]]))},t.prototype.setupControlBox=function(){e.prototype.setupControlBox.call(this),this.curveControlLine1=l.createLine(this.x1,this.y1,this.curveX,this.curveY,[["stroke","black"],["stroke-width","1"],["stroke-opacity","0.5"],["stroke-dasharray","3, 2"]]),this.curveControlLine2=l.createLine(this.x2,this.y2,this.curveX,this.curveY,[["stroke","black"],["stroke-width","1"],["stroke-opacity","0.5"],["stroke-dasharray","3, 2"]]),this.controlBox.insertBefore(this.curveControlLine1,this.controlBox.firstChild),this.controlBox.insertBefore(this.curveControlLine2,this.controlBox.firstChild)},t.prototype.addControlGrips=function(){this.curveGrip=this.createGrip(),this.curveX=0,this.curveY=0,e.prototype.addControlGrips.call(this)},t.prototype.positionGrips=function(){e.prototype.positionGrips.call(this);var t=this.curveGrip.GRIP_SIZE;this.positionGrip(this.curveGrip.visual,this.curveX-t/2,this.curveY-t/2),this.curveControlLine1&&this.curveControlLine2&&(this.curveControlLine1.setAttribute("x1",this.x1.toString()),this.curveControlLine1.setAttribute("y1",this.y1.toString()),this.curveControlLine1.setAttribute("x2",this.curveX.toString()),this.curveControlLine1.setAttribute("y2",this.curveY.toString()),this.curveControlLine2.setAttribute("x1",this.x2.toString()),this.curveControlLine2.setAttribute("y1",this.y2.toString()),this.curveControlLine2.setAttribute("x2",this.curveX.toString()),this.curveControlLine2.setAttribute("y2",this.curveY.toString()))},t.prototype.manipulate=function(t){"move"===this.state&&(this.curveX=this.manipulationStartCurveX+t.x-this.manipulationStartX,this.curveY=this.manipulationStartCurveY+t.y-this.manipulationStartY),e.prototype.manipulate.call(this,t)},t.prototype.resize=function(t){this.activeGrip===this.curveGrip&&(this.curveX=t.x,this.curveY=t.y),e.prototype.resize.call(this,t),"creating"===this.state&&(this.curveX=this.x1+(this.x2-this.x1)/2,this.curveY=this.y1+(this.y2-this.y1)/2)},t.prototype.setStrokeColor=function(e){this.strokeColor=e,this.adjustVisual(),this.colorChanged(e)},t.prototype.setStrokeWidth=function(e){this.strokeWidth=e,this.adjustVisual()},t.prototype.setStrokeDasharray=function(e){this.strokeDasharray=e,this.adjustVisual()},t.prototype.scale=function(t,n){this.curveX=this.curveX*t,this.curveY=this.curveY*n,e.prototype.scale.call(this,t,n)},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.strokePanel,this.strokeWidthPanel,this.strokeStylePanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=Object.assign({strokeColor:this.strokeColor,strokeWidth:this.strokeWidth,strokeDasharray:this.strokeDasharray,curveX:this.curveX,curveY:this.curveY},e.prototype.getState.call(this));return n.typeName=t.typeName,n},t.prototype.restoreState=function(t){e.prototype.restoreState.call(this,t);var n=t;this.strokeColor=n.strokeColor,this.strokeWidth=n.strokeWidth,this.strokeDasharray=n.strokeDasharray,this.curveX=n.curveX,this.curveY=n.curveY,this.createVisual(),this.adjustVisual()},t.typeName="CurveMarker",t.title="Curve marker",t.icon='<svg viewBox="0 0 24 24"><path d="M18.5 2A1.5 1.5 0 0120 3.5 1.5 1.5 0 0118.5 5c-.23 0-.45-.05-.65-.15l-3.69 3.7.34.45c2.19-1.26 4.76-2 7.5-2l1 .03v2.01L22 9c-2.58 0-5 .75-7 2.04A3.96 3.96 0 0111.04 15C9.75 17 9 19.42 9 22l.04 1H7.03L7 22c0-2.74.74-5.31 2-7.5l-.45-.34-3.7 3.69c.1.2.15.42.15.65A1.5 1.5 0 013.5 20 1.5 1.5 0 012 18.5 1.5 1.5 0 013.5 17c.23 0 .45.05.65.15l3.69-3.7C7.31 12.78 7 11.92 7 11a4 4 0 014-4c.92 0 1.78.31 2.45.84l3.7-3.69c-.1-.2-.15-.42-.15-.65A1.5 1.5 0 0118.5 2M11 9a2 2 0 00-2 2 2 2 0 002 2 2 2 0 002-2 2 2 0 00-2-2z"/></svg>',t}(N),Z=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.fillColor="transparent",r.strokeColor="transparent",r.strokeWidth=0,r.strokeDasharray="",r.textColor="transparent",r.fontSize="1rem",r.isMoved=!1,r.captionText="Caption",r.PADDING=5,r.captionBoxWidth=0,r.captionBoxHeight=0,r.strokeColor=i.defaultColor,r.strokeWidth=i.defaultStrokeWidth,r.strokeDasharray=i.defaultStrokeDasharray,r.fillColor=i.defaultFillColor,r.textColor=i.defaultStrokeColor,r.fontFamily=i.defaultFontFamily,r.fontSize=i.defaultCaptionFontSize,r.captionText=i.defaultCaptionText,r.setStrokeColor=r.setStrokeColor.bind(r),r.setFillColor=r.setFillColor.bind(r),r.setStrokeWidth=r.setStrokeWidth.bind(r),r.setStrokeDasharray=r.setStrokeDasharray.bind(r),r.createVisual=r.createVisual.bind(r),r.sizeCaption=r.sizeCaption.bind(r),r.setCaptionText=r.setCaptionText.bind(r),r.showTextEditor=r.showTextEditor.bind(r),r.positionTextEditor=r.positionTextEditor.bind(r),r.finishTextEditing=r.finishTextEditing.bind(r),r.setFont=r.setFont.bind(r),r.setTextColor=r.setTextColor.bind(r),r.strokePanel=new A("Line color",a(i.defaultColorSet,["transparent"]),r.strokeColor),r.strokePanel.onColorChanged=r.setStrokeColor,r.fillPanel=new A("Fill color",a(i.defaultColorSet,["transparent"]),r.fillColor,H),r.fillPanel.onColorChanged=r.setFillColor,r.strokeWidthPanel=new E("Line width",i.defaultStrokeWidths,i.defaultStrokeWidth),r.strokeWidthPanel.onWidthChanged=r.setStrokeWidth,r.strokeStylePanel=new T("Line style",i.defaultStrokeDasharrays,i.defaultStrokeDasharray),r.strokeStylePanel.onStyleChanged=r.setStrokeDasharray,r.fontFamilyPanel=new D("Font",i.defaultFontFamilies,i.defaultFontFamily),r.fontFamilyPanel.onFontChanged=r.setFont,r.textColorPanel=new A("Text color",i.defaultColorSet,r.textColor,F),r.textColorPanel.onColorChanged=r.setTextColor,r}return r(t,e),t.prototype.ownsTarget=function(t){return!(!e.prototype.ownsTarget.call(this,t)&&t!==this.visual&&t!==this.frame&&t!==this.captionBg&&t!==this.captionElement)},t.prototype.createVisual=function(){this.visual=l.createGroup(),this.addMarkerVisualToContainer(this.visual),this.captionBg=l.createRect(1,1,[["fill",this.fillColor]]),this.visual.appendChild(this.captionBg),this.captionElement=l.createText([["fill",this.textColor],["font-family",this.fontFamily]]),this.captionElement.style.fontSize=this.fontSize,this.captionElement.style.textAnchor="start",this.captionElement.style.dominantBaseline="text-before-edge",this.captionElement.textContent=this.captionText,this.visual.appendChild(this.captionElement),this.frame=l.createRect(this.width,this.height,[["fill","transparent"],["stroke",this.strokeColor],["stroke-width",this.strokeWidth.toString()],["stroke-dasharray",this.strokeDasharray]]),this.visual.appendChild(this.frame),this.sizeCaption()},t.prototype.setCaptionText=function(e){this.captionText=e,this.captionElement.textContent=this.captionText,this.sizeCaption()},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),this.isMoved=!1,this.pointerDownPoint=t,this.pointerDownTimestamp=Date.now(),"new"===this.state&&(this.createVisual(),this.moveVisual(t),this._state="creating")},t.prototype.manipulate=function(t){e.prototype.manipulate.call(this,t),void 0!==this.pointerDownPoint&&(this.isMoved=Math.abs(t.x-this.pointerDownPoint.x)>5||Math.abs(t.y-this.pointerDownPoint.y)>5)},t.prototype.resize=function(t){e.prototype.resize.call(this,t),this.setSize()},t.prototype.sizeCaption=function(){var e=this.captionElement.getBBox();""!==this.captionText.trim()?(this.captionBoxWidth=e.width+2*this.PADDING,this.captionBoxHeight=e.height+2*this.PADDING):(this.captionBoxWidth=0,this.captionBoxHeight=0),l.setAttributes(this.captionBg,[["width",this.captionBoxWidth.toString()],["height",this.captionBoxHeight.toString()],["clip-path","path('M0,0 H"+this.width+" V"+this.height+" H"+-this.width+" Z')"]]),l.setAttributes(this.captionElement,[["x",this.PADDING.toString()],["y",this.PADDING.toString()],["clip-path","path('M0,0 H"+(this.width-this.PADDING)+" V"+this.height+" H"+(-this.width-this.PADDING)+" Z')"]])},t.prototype.showTextEditor=function(){var e=this;this._state="edit",this.overlayContainer.innerHTML="",this.textEditDiv=document.createElement("div"),this.textEditDiv.style.flexGrow="2",this.textEditDiv.style.alignItems="center",this.textEditDiv.style.justifyContent="center",this.textEditDiv.style.pointerEvents="auto",this.textEditDiv.style.overflow="hidden",this.textEditBox=document.createElement("input"),this.textEditBox.style.position="absolute",this.textEditBox.style.width=this.width+"px",this.captionBoxHeight>0&&(this.textEditBox.style.height=this.captionBoxHeight+"px"),this.textEditBox.style.fontSize=this.fontSize,this.textEditBox.style.fontFamily=this.fontFamily,this.textEditBox.style.backgroundColor=this.fillColor,this.textEditBox.style.color=this.textColor,this.textEditBox.style.borderWidth="0",this.textEditBox.setAttribute("value",this.captionText),this.textEditBox.select(),this.textEditDiv.appendChild(this.textEditBox),this.overlayContainer.appendChild(this.textEditDiv),this.textEditBox.addEventListener("pointerup",(function(e){e.stopPropagation()})),this.textEditBox.addEventListener("keypress",(function(t){"Enter"===t.key&&e.finishTextEditing(e.textEditBox.value)})),this.textEditBox.addEventListener("keyup",(function(e){e.cancelBubble=!0})),this.textEditBox.addEventListener("blur",(function(){e.finishTextEditing(e.textEditBox.value)})),this.textEditDiv.addEventListener("pointerup",(function(){e.finishTextEditing(e.textEditBox.value)})),this.positionTextEditor(),this.textEditBox.focus()},t.prototype.positionTextEditor=function(){"edit"===this.state&&(void 0===this.textEditBox?this.showTextEditor():(this.textEditBox.style.left=this.left+"px",this.textEditBox.style.top=this.top+"px",this.textEditBox.style.transform="rotate("+this.rotationAngle+"deg)",this.textEditBox.style.transformOrigin=this.width/2+"px "+this.height/2+"px"))},t.prototype.finishTextEditing=function(e){this.setCaptionText(e.trim()),this.overlayContainer.innerHTML="",this.stateChanged()},t.prototype.setFont=function(e){this.captionElement&&l.setAttributes(this.captionElement,[["font-family",e]]),this.fontFamily=e,this.textEditBox&&(this.textEditBox.style.fontFamily=this.fontFamily),this.sizeCaption(),this.stateChanged()},t.prototype.setTextColor=function(e){this.captionElement&&l.setAttributes(this.captionElement,[["fill",e]]),this.textColor=e,this.textEditBox&&(this.textEditBox.style.color=this.textColor),this.stateChanged()},t.prototype.setSize=function(){e.prototype.setSize.call(this),l.setAttributes(this.frame,[["width",this.width.toString()],["height",this.height.toString()]]),this.sizeCaption()},t.prototype.pointerUp=function(t){e.prototype.pointerUp.call(this,t),this.setSize(),!this.isMoved&&Date.now()-this.pointerDownTimestamp>500&&this.showTextEditor(),this.pointerDownPoint=void 0},t.prototype.dblClick=function(t,n){e.prototype.dblClick.call(this,t,n),this.showTextEditor()},t.prototype.setStrokeColor=function(e){this.strokeColor=e,this.frame&&l.setAttributes(this.frame,[["stroke",this.strokeColor]]),this.colorChanged(e),this.stateChanged()},t.prototype.setFillColor=function(e){this.fillColor=e,this.captionBg&&l.setAttributes(this.captionBg,[["fill",this.fillColor]]),this.fillColorChanged(e),this.stateChanged()},t.prototype.setStrokeWidth=function(e){this.strokeWidth=e,this.frame&&l.setAttributes(this.frame,[["stroke-width",this.strokeWidth.toString()]]),this.stateChanged()},t.prototype.setStrokeDasharray=function(e){this.strokeDasharray=e,this.frame&&l.setAttributes(this.frame,[["stroke-dasharray",this.strokeDasharray]]),this.stateChanged()},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.strokePanel,this.fillPanel,this.strokeWidthPanel,this.strokeStylePanel,this.fontFamilyPanel,this.textColorPanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var t=Object.assign({fillColor:this.fillColor,strokeColor:this.strokeColor,strokeWidth:this.strokeWidth,strokeDasharray:this.strokeDasharray,opacity:1,textColor:this.textColor,fontFamily:this.fontFamily,fontSize:this.fontSize,captionText:this.captionText},e.prototype.getState.call(this));return t.typeName=this.typeName,t},t.prototype.restoreState=function(t){var n=t;this.fillColor=n.fillColor,this.strokeColor=n.strokeColor,this.strokeWidth=n.strokeWidth,this.strokeDasharray=n.strokeDasharray,this.textColor=n.textColor,this.fontFamily=n.fontFamily,this.captionText=n.captionText,this.fontSize=n.fontSize,this.createVisual(),e.prototype.restoreState.call(this,t),this.setSize()},t.prototype.scale=function(t,n){e.prototype.scale.call(this,t,n),this.setSize()},t.typeName="CaptionFrameMarker",t.title="Caption frame marker",t.icon='<svg viewBox="0 0 24 24"><path d="M5 3c-1.11 0-2 .89-2 2v14c0 1.11.89 2 2 2h14c1.11 0 2-.89 2-2V5c0-1.11-.89-2-2-2H5m0 2h14v14H5V5m2 2v2h10V7H7z"/></svg>',t}(C),Y=function(){function e(e,t){void 0===t&&(t=!1),this.cancelable=!1,this._defaultPrevented=!1,this.markerArea=e,this.cancelable=t}return Object.defineProperty(e.prototype,"defaultPrevented",{get:function(){return this._defaultPrevented},enumerable:!1,configurable:!0}),e.prototype.preventDefault=function(){this._defaultPrevented=!0},e}(),J=function(e){function t(t,n,i){var r=e.call(this,t,!1)||this;return r.dataUrl=n,r.state=i,r}return r(t,e),t}(Y),K=function(e){function t(t,n,i){void 0===i&&(i=!1);var r=e.call(this,t,i)||this;return r.marker=n,r}return r(t,e),t}(Y),q=function(){function e(){this.render=[],this.beforeclose=[],this.close=[],this.show=[],this.restorestate=[],this.statechange=[],this.markerselect=[],this.markerdeselect=[],this.markercreating=[],this.markercreate=[],this.markerbeforedelete=[],this.markerdelete=[],this.markerchange=[],this.focus=[],this.blur=[]}return e.prototype.addEventListener=function(e,t){this[e].push(t)},e.prototype.removeEventListener=function(e,t){var n=this[e].indexOf(t);n>-1&&this[e].splice(n,1)},e}(),_=function(){function e(t){this.touchPoints=0,this._availableMarkerTypes=this.DEFAULT_MARKER_TYPES,this.mode="select",this.markers=[],this.isDragging=!1,this.renderEventListeners=[],this.closeEventListeners=[],this.settings=new P,this._isOpen=!1,this.undoRedoManager=new W,this.renderAtNaturalSize=!1,this.renderImageType="image/png",this.renderMarkersOnly=!1,this.zoomSteps=[1,1.5,2,4],this._zoomLevel=1,this._isResizing=!1,this.prevPanPoint={x:0,y:0},this.eventListeners=new q,this._silentRenderMode=!1,this._isFocused=!1,this._instanceNo=e.instanceCounter++,this.styles=new h(this.instanceNo),this.uiStyleSettings=this.styles.settings,this.target=t,this.targetRoot=document.body,this.width=t.clientWidth,this.height=t.clientHeight,this.styles.removeStyleSheet(),this.open=this.open.bind(this),this.setTopLeft=this.setTopLeft.bind(this),this.toolbarButtonClicked=this.toolbarButtonClicked.bind(this),this.createNewMarker=this.createNewMarker.bind(this),this.addNewMarker=this.addNewMarker.bind(this),this.markerCreated=this.markerCreated.bind(this),this.setCurrentMarker=this.setCurrentMarker.bind(this),this.onPointerDown=this.onPointerDown.bind(this),this.onDblClick=this.onDblClick.bind(this),this.onPointerMove=this.onPointerMove.bind(this),this.onPointerUp=this.onPointerUp.bind(this),this.onPointerOut=this.onPointerOut.bind(this),this.onKeyUp=this.onKeyUp.bind(this),this.overrideOverflow=this.overrideOverflow.bind(this),this.restoreOverflow=this.restoreOverflow.bind(this),this.close=this.close.bind(this),this.closeUI=this.closeUI.bind(this),this.addCloseEventListener=this.addCloseEventListener.bind(this),this.removeCloseEventListener=this.removeCloseEventListener.bind(this),this.addRenderEventListener=this.addRenderEventListener.bind(this),this.removeRenderEventListener=this.removeRenderEventListener.bind(this),this.clientToLocalCoordinates=this.clientToLocalCoordinates.bind(this),this.onWindowResize=this.onWindowResize.bind(this),this.deleteSelectedMarker=this.deleteSelectedMarker.bind(this),this.setWindowHeight=this.setWindowHeight.bind(this),this.removeMarker=this.removeMarker.bind(this),this.colorChanged=this.colorChanged.bind(this),this.fillColorChanged=this.fillColorChanged.bind(this),this.onPopupTargetResize=this.onPopupTargetResize.bind(this),this.showNotesEditor=this.showNotesEditor.bind(this),this.hideNotesEditor=this.hideNotesEditor.bind(this),this.stepZoom=this.stepZoom.bind(this),this.focus=this.focus.bind(this),this.blur=this.blur.bind(this),this.markerStateChanged=this.markerStateChanged.bind(this),this.switchToSelectMode=this.switchToSelectMode.bind(this),this.addDefs=this.addDefs.bind(this),this.addDefsToImage=this.addDefsToImage.bind(this)}return Object.defineProperty(e.prototype,"ALL_MARKER_TYPES",{get:function(){return[S,L,O,I,V,X,k,U,G,z,B,Q,Z]},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"DEFAULT_MARKER_TYPES",{get:function(){return[S,L,O,I,X,k,U]},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"BASIC_MARKER_TYPES",{get:function(){return[S,L,O,I,k]},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"availableMarkerTypes",{get:function(){return this._availableMarkerTypes},set:function(e){var t=this;this._availableMarkerTypes.splice(0),e.forEach((function(e){if("string"==typeof e){var n=t.ALL_MARKER_TYPES.find((function(t){return t.typeName===e}));void 0!==n&&t._availableMarkerTypes.push(n)}else t._availableMarkerTypes.push(e)}))},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"currentMarker",{get:function(){return this._currentMarker},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"isOpen",{get:function(){return this._isOpen},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"isUndoPossible",{get:function(){return!(!this.undoRedoManager||!this.undoRedoManager.isUndoPossible)},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"isRedoPossible",{get:function(){return!(!this.undoRedoManager||!this.undoRedoManager.isRedoPossible)},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"zoomLevel",{get:function(){return this._zoomLevel},set:function(e){this._zoomLevel=e,this.editorCanvas&&this.contentDiv&&(this.editorCanvas.style.transform="scale("+this._zoomLevel+")",this.contentDiv.scrollTo({left:(this.editorCanvas.clientWidth*this._zoomLevel-this.contentDiv.clientWidth)/2,top:(this.editorCanvas.clientHeight*this._zoomLevel-this.contentDiv.clientHeight)/2}))},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"instanceNo",{get:function(){return this._instanceNo},enumerable:!1,configurable:!0}),e.prototype.open=function(){this.setupResizeObserver(),this.setEditingTarget(),this.setTopLeft(),this.initMarkerCanvas(),this.initOverlay(),this.attachEvents(),"popup"===this.settings.displayMode&&this.onPopupTargetResize(),u.isLicensed||this.addLogo(),this._isOpen=!0,this._isFocused=!0},e.prototype.show=function(){var e=this;void 0===this.styles.styleSheetRoot&&void 0!==d.styleSheetRoot&&(this.styles.styleSheetRoot=d.styleSheetRoot),this.setWindowHeight(),this.showUI(),this.open(),this.eventListeners.show.forEach((function(t){return t(new Y(e))}))},e.prototype.render=function(){return s(this,void 0,void 0,(function(){var e;return o(this,(function(t){switch(t.label){case 0:return this.setCurrentMarker(),(e=new c).naturalSize=this.renderAtNaturalSize,e.imageType=this.renderImageType,e.imageQuality=this.renderImageQuality,e.markersOnly=this.renderMarkersOnly,e.width=this.renderWidth,e.height=this.renderHeight,[4,e.rasterize(this.target instanceof HTMLImageElement?this.target:null,this.markerImage,this.renderTarget)];case 1:return t.sent(),[4,e.rasterize(this.target instanceof HTMLImageElement?this.target:null,this.markerImage,this.renderTarget)];case 2:return[2,t.sent()]}}))}))},e.prototype.close=function(e){var t=this;if(void 0===e&&(e=!1),this.isOpen){var n=!1;e||this.eventListeners.beforeclose.forEach((function(e){var i=new Y(t,!0);e(i),i.defaultPrevented&&(n=!0)})),n||(this.coverDiv&&this.closeUI(),this.targetObserver&&(this.targetObserver.unobserve(this.target),this.targetObserver.unobserve(this.editorCanvas)),"popup"===this.settings.displayMode&&window.removeEventListener("resize",this.setWindowHeight),this.eventListeners.close.forEach((function(e){return e(new Y(t))})),this.detachEvents(),this._isOpen=!1)}},e.prototype.addMarkersToToolbar=function(){for(var e,t=[],n=0;n<arguments.length;n++)t[n]=arguments[n];(e=this._availableMarkerTypes).push.apply(e,t)},e.prototype.addRenderEventListener=function(e){this.addEventListener("render",(function(t){e(t.dataUrl,t.state)}))},e.prototype.removeRenderEventListener=function(e){},e.prototype.addCloseEventListener=function(e){this.addEventListener("close",(function(){e()}))},e.prototype.removeCloseEventListener=function(e){},e.prototype.setupResizeObserver=function(){var e=this;"inline"===this.settings.displayMode?window.ResizeObserver&&(this.targetObserver=new ResizeObserver((function(){e.resize(e.target.clientWidth,e.target.clientHeight)})),this.targetObserver.observe(this.target)):"popup"===this.settings.displayMode&&(window.ResizeObserver&&(this.targetObserver=new ResizeObserver((function(){return e.onPopupTargetResize()})),this.targetObserver.observe(this.editorCanvas)),window.addEventListener("resize",this.setWindowHeight))},e.prototype.onPopupTargetResize=function(){var e=1*this.target.clientWidth/this.target.clientHeight,t=this.editorCanvas.clientWidth/e>this.editorCanvas.clientHeight?this.editorCanvas.clientHeight*e:this.editorCanvas.clientWidth,n=t<this.editorCanvas.clientWidth?this.editorCanvas.clientHeight:this.editorCanvas.clientWidth/e;this.resize(t,n)},e.prototype.setWindowHeight=function(){this.windowHeight=window.innerHeight},e.prototype.resize=function(e,t){this._isResizing=!0;var n=e/this.imageWidth,i=t/this.imageHeight;this.imageWidth=Math.round(e),this.imageHeight=Math.round(t),this.target instanceof HTMLImageElement&&this.editingTarget instanceof HTMLImageElement&&(this.editingTarget.src=this.target.src),this.editingTarget.width=this.imageWidth,this.editingTarget.height=this.imageHeight,this.editingTarget.style.width=this.imageWidth+"px",this.editingTarget.style.height=this.imageHeight+"px",this.markerImage.setAttribute("width",this.imageWidth.toString()),this.markerImage.setAttribute("height",this.imageHeight.toString()),this.markerImage.setAttribute("viewBox","0 0 "+this.imageWidth.toString()+" "+this.imageHeight.toString()),this.markerImageHolder.style.width=this.imageWidth+"px",this.markerImageHolder.style.height=this.imageHeight+"px",this.overlayContainer.style.width=this.imageWidth+"px",this.overlayContainer.style.height=this.imageHeight+"px","popup"!==this.settings.displayMode?this.coverDiv.style.width=this.imageWidth.toString()+"px":(this.setTopLeft(),this.positionMarkerImage()),void 0!==this.toolbar&&this.toolbar.adjustLayout(),this.positionLogo(),this.scaleMarkers(n,i),this._isResizing=!1},e.prototype.scaleMarkers=function(e,t){var n,i=this;this._currentMarker&&this._currentMarker instanceof I?this._currentMarker.scale(e,t):(n=this._currentMarker,this.setCurrentMarker()),this.markers.forEach((function(n){n!==i._currentMarker&&n.scale(e,t)})),void 0!==n&&this.setCurrentMarker(n)},e.prototype.setEditingTarget=function(){this.imageWidth=Math.round(this.target.clientWidth),this.imageHeight=Math.round(this.target.clientHeight),this.target instanceof HTMLImageElement&&this.editingTarget instanceof HTMLImageElement&&(this.editingTarget.src=this.target.src),this.editingTarget.width=this.imageWidth,this.editingTarget.height=this.imageHeight,this.editingTarget.style.width=this.imageWidth+"px",this.editingTarget.style.height=this.imageHeight+"px"},e.prototype.setTopLeft=function(){var e=this.editingTarget.getBoundingClientRect(),t=this.editorCanvas.getBoundingClientRect();this.left=e.left-t.left,this.top=e.top-t.top},e.prototype.initMarkerCanvas=function(){this.markerImageHolder=document.createElement("div"),this.markerImageHolder.style.setProperty("touch-action","pinch-zoom"),this.markerImage=document.createElementNS("http://www.w3.org/2000/svg","svg"),this.markerImage.setAttribute("xmlns","http://www.w3.org/2000/svg"),this.markerImage.setAttribute("width",this.imageWidth.toString()),this.markerImage.setAttribute("height",this.imageHeight.toString()),this.markerImage.setAttribute("viewBox","0 0 "+this.imageWidth.toString()+" "+this.imageHeight.toString()),this.markerImage.style.pointerEvents="auto",this.markerImageHolder.style.position="absolute",this.markerImageHolder.style.width=this.imageWidth+"px",this.markerImageHolder.style.height=this.imageHeight+"px",this.markerImageHolder.style.transformOrigin="top left",this.positionMarkerImage(),this.markerImageHolder.appendChild(this.markerImage),this.editorCanvas.appendChild(this.markerImageHolder)},e.prototype.addDefs=function(){for(var e,t=[],n=0;n<arguments.length;n++)t[n]=arguments[n];this.defs=l.createDefs(),this.addDefsToImage(),(e=this.defs).append.apply(e,t)},e.prototype.addDefsToImage=function(){this.defs&&this.markerImage.insertBefore(this.defs,this.markerImage.firstChild)},e.prototype.initOverlay=function(){this.overlayContainer=document.createElement("div"),this.overlayContainer.style.position="absolute",this.overlayContainer.style.left="0px",this.overlayContainer.style.top="0px",this.overlayContainer.style.width=this.imageWidth+"px",this.overlayContainer.style.height=this.imageHeight+"px",this.overlayContainer.style.display="flex",this.markerImageHolder.appendChild(this.overlayContainer)},e.prototype.positionMarkerImage=function(){this.markerImageHolder.style.top=this.top/this.zoomLevel+"px",this.markerImageHolder.style.left=this.left/this.zoomLevel+"px"},e.prototype.attachEvents=function(){this.markerImage.addEventListener("pointerdown",this.onPointerDown),this.markerImage.addEventListener("dblclick",this.onDblClick),this.attachWindowEvents()},e.prototype.attachWindowEvents=function(){window.addEventListener("pointermove",this.onPointerMove),window.addEventListener("pointerup",this.onPointerUp),window.addEventListener("pointercancel",this.onPointerOut),window.addEventListener("pointerout",this.onPointerOut),window.addEventListener("pointerleave",this.onPointerUp),window.addEventListener("resize",this.onWindowResize),window.addEventListener("keyup",this.onKeyUp)},e.prototype.detachEvents=function(){this.markerImage.removeEventListener("pointerdown",this.onPointerDown),this.markerImage.removeEventListener("dblclick",this.onDblClick),this.detachWindowEvents()},e.prototype.detachWindowEvents=function(){window.removeEventListener("pointermove",this.onPointerMove),window.removeEventListener("pointerup",this.onPointerUp),window.removeEventListener("pointercancel",this.onPointerOut),window.removeEventListener("pointerout",this.onPointerOut),window.removeEventListener("pointerleave",this.onPointerUp),window.removeEventListener("resize",this.onWindowResize),window.removeEventListener("keyup",this.onKeyUp)},e.prototype.addLogo=function(){this.logoUI=document.createElement("div"),this.logoUI.style.display="inline-block",this.logoUI.style.margin="0px",this.logoUI.style.padding="0px",this.logoUI.style.fill="#333333";var e=document.createElement("a");e.href="https://markerjs.com/",e.target="_blank",e.innerHTML='<svg viewBox="0 0 112 96" xmlns="http://www.w3.org/2000/svg" fill-rule="evenodd" clip-rule="evenodd" stroke-linejoin="round" stroke-miterlimit="1.414"><path fill="#e5f20d" fill-opacity=".647" d="M0 40.386h111.96V95.62H0z"/><path d="M93.61 61.452c0 .987-.328 1.831-.987 2.53-.657.7-1.52 1.048-2.591 1.048-1.481 0-2.222-.74-2.222-2.22 0-16.617-.533-29.347-1.604-38.192-1.068-8.842-2.92-13.265-5.552-13.265-4.443 0-10.94 15.509-19.497 46.52v.124c0 .987-.328 1.831-.987 2.53-.657.7-1.52 1.048-2.592 1.048-1.48 0-2.22-.74-2.22-2.22 0-3.29.165-8.392.493-15.302.33-7.732.494-13.82.494-18.262 0-6.17-.186-10.55-.556-13.142-.37-2.591-1.172-3.887-2.406-3.887-2.796 0-6.333 5.12-10.612 15.363C38.494 34.367 34.01 46.44 29.32 60.34l-1.11 3.209a5.714 5.714 0 01-1.42 2.097c-.617.578-1.295.864-2.036.864-.987 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marker.js",e.style.display="grid",e.style.alignItems="center",e.style.justifyItems="center",e.style.padding="3px",e.style.width="20px",e.style.height="20px",this.logoUI.appendChild(e),this.editorCanvas.appendChild(this.logoUI),this.logoUI.style.position="absolute",this.logoUI.style.pointerEvents="all",this.positionLogo()},e.prototype.positionLogo=function(){this.logoUI&&("right"!==this.uiStyleSettings.logoPosition?this.logoUI.style.left=this.markerImageHolder.offsetLeft+10+"px":this.logoUI.style.left=this.markerImageHolder.offsetLeft+this.markerImageHolder.offsetWidth-this.logoUI.clientWidth-10+"px",this.logoUI.style.top=this.markerImageHolder.offsetTop+this.markerImageHolder.offsetHeight-this.logoUI.clientHeight-10+"px")},e.prototype.overrideOverflow=function(){this.scrollXState=window.scrollX,this.scrollYState=window.scrollY,this.bodyOverflowState=document.body.style.overflow,window.scroll({top:0,left:0}),document.body.style.overflow="hidden"},e.prototype.restoreOverflow=function(){document.body.style.overflow=this.bodyOverflowState,window.scroll({top:this.scrollYState,left:this.scrollXState})},e.prototype.showUI=function(){switch("popup"===this.settings.displayMode&&this.overrideOverflow(),this.coverDiv=document.createElement("div"),this.coverDiv.style.visibility=this._silentRenderMode?"hidden":"visible",this.coverDiv.className=this.styles.classNamePrefixBase+" "+this.styles.classNamePrefix,this.coverDiv.style.fontSize="16px",this.coverDiv.style.userSelect="none",this.settings.displayMode){case"inline":this.coverDiv.style.position="absolute";var e=void 0!==this.settings.uiOffsetTop?this.target.offsetTop+this.settings.uiOffsetTop:this.target.offsetTop>this.styles.settings.toolbarHeight?this.target.offsetTop-this.styles.settings.toolbarHeight:0;this.coverDiv.style.top=e+"px",this.coverDiv.style.left=this.target.offsetLeft.toString()+"px",this.coverDiv.style.width=this.target.offsetWidth.toString()+"px",this.coverDiv.style.zIndex=void 0!==this.uiStyleSettings.zIndex?this.uiStyleSettings.zIndex:"5";break;case"popup":this.coverDiv.style.position="absolute",this.coverDiv.style.top="0px",this.coverDiv.style.left="0px",this.coverDiv.style.width="100vw",this.coverDiv.style.height=window.innerHeight+"px",this.coverDiv.style.backgroundColor="rgba(0, 0, 0, 0.75)",this.coverDiv.style.zIndex=void 0!==this.uiStyleSettings.zIndex?this.uiStyleSettings.zIndex:"1000",this.coverDiv.style.display="flex"}this.targetRoot.appendChild(this.coverDiv),this.uiDiv=document.createElement("div"),this.uiDiv.style.display="flex",this.uiDiv.style.flexDirection="column",this.uiDiv.style.flexGrow="2",this.uiDiv.style.margin="popup"===this.settings.displayMode?this.settings.popupMargin+"px":"0px",this.uiDiv.style.border="0px",this.coverDiv.appendChild(this.uiDiv),this.toolbar=new g(this.uiDiv,this.settings.displayMode,this._availableMarkerTypes,this.uiStyleSettings,this.styles),this.toolbar.addButtonClickListener(this.toolbarButtonClicked),this.toolbar.show(this._silentRenderMode||this.uiStyleSettings.hideToolbar?"hidden":"visible"),this.contentDiv=document.createElement("div"),this.contentDiv.style.display="flex",this.contentDiv.style.flexDirection="row",this.contentDiv.style.flexGrow="2",this.contentDiv.style.flexShrink="1","popup"===this.settings.displayMode&&(this.contentDiv.style.backgroundColor=this.uiStyleSettings.canvasBackgroundColor,this.contentDiv.style.maxHeight=this.windowHeight-2*this.settings.popupMargin-3.5*this.uiStyleSettings.toolbarHeight+"px",this.contentDiv.style.maxWidth="calc(100vw - "+2*this.settings.popupMargin+"px)"),this.contentDiv.style.overflow="auto",this.uiDiv.appendChild(this.contentDiv),this.editorCanvas=document.createElement("div"),this.editorCanvas.style.flexGrow="2",this.editorCanvas.style.flexShrink="1",this.editorCanvas.style.position="relative",this.editorCanvas.style.overflow="hidden",this.editorCanvas.style.display="flex","popup"===this.settings.displayMode&&(this.editorCanvas.style.alignItems="center",this.editorCanvas.style.justifyContent="center"),this.editorCanvas.style.pointerEvents="none",this.editorCanvas.style.transformOrigin="left top",this.editorCanvas.style.transform="scale("+this.zoomLevel+")",this.contentDiv.appendChild(this.editorCanvas),this.editingTarget=this.target instanceof HTMLImageElement?document.createElement("img"):document.createElement("canvas"),void 0===this.settings.uiOffsetTop&&this.target.offsetTop<this.styles.settings.toolbarHeight&&(this.editingTarget.style.marginTop=this.target.offsetTop-this.styles.settings.toolbarHeight+"px"),this.editorCanvas.appendChild(this.editingTarget),this.toolbox=new m(this.uiDiv,this.settings.displayMode,this.uiStyleSettings,this.styles),this.toolbox.show(this._silentRenderMode||this.uiStyleSettings.hideToolbox?"hidden":"visible")},e.prototype.closeUI=function(){"popup"===this.settings.displayMode&&this.restoreOverflow(),this.targetRoot.removeChild(this.coverDiv)},e.prototype.removeMarker=function(e){this.markerImage.removeChild(e.container),this.markers.indexOf(e)>-1&&this.markers.splice(this.markers.indexOf(e),1),e.dispose()},e.prototype.switchToSelectMode=function(){this.mode="select",this.hideNotesEditor(),void 0!==this._currentMarker&&("new"!==this._currentMarker.state?this._currentMarker.select():(this.removeMarker(this._currentMarker),this.setCurrentMarker(),this.markerImage.style.cursor="default"),this.addUndoStep())},e.prototype.toolbarButtonClicked=function(e,t){if("marker"===e&&void 0!==t)this.createNewMarker(t);else if("action"===e)switch(t){case"select":this.switchToSelectMode(),this.switchToSelectMode();break;case"delete":this.deleteSelectedMarker();break;case"clear":this.clear();break;case"undo":this.undo();break;case"redo":this.redo();break;case"zoom":this.stepZoom();break;case"zoom-out":this.zoomLevel=1;break;case"notes":void 0===this.notesArea?(this.switchToSelectMode(),this.zoomLevel=1,this.showNotesEditor()):this.switchToSelectMode();break;case"close":this.close();break;case"render":this.switchToSelectMode(),this.startRenderAndClose()}},e.prototype.deleteSelectedMarker=function(){var e=this;if(void 0!==this._currentMarker){var t=!1;if(this.eventListeners.markerbeforedelete.forEach((function(n){var i=new K(e,e._currentMarker,!0);n(i),i.defaultPrevented&&(t=!0)})),!t){var n=this._currentMarker;this._currentMarker.dispose(),this.markerImage.removeChild(this._currentMarker.container),this.markers.splice(this.markers.indexOf(this._currentMarker),1),this.setCurrentMarker(),this.addUndoStep(),this.eventListeners.markerdelete.forEach((function(t){return t(new K(e,n))}))}}},e.prototype.clear=function(){var e=this,t=!1;if(this.markers.length>0&&(this.eventListeners.markerbeforedelete.forEach((function(n){var i=new K(e,void 0,!0);n(i),i.defaultPrevented&&(t=!0)})),!t)){this.setCurrentMarker();for(var n=function(t){var n=i.markers[t];i.setCurrentMarker(i.markers[t]),i._currentMarker.dispose(),i.markerImage.removeChild(i._currentMarker.container),i.markers.splice(i.markers.indexOf(i._currentMarker),1),i.eventListeners.markerdelete.forEach((function(t){return t(new K(e,n))}))},i=this,r=this.markers.length-1;r>=0;r--)n(r);this.addUndoStep()}},Object.defineProperty(e.prototype,"isNotesAreaOpen",{get:function(){return void 0!==this.notesArea},enumerable:!1,configurable:!0}),e.prototype.showNotesEditor=function(){var e;void 0!==this._currentMarker&&(this.overlayContainer.innerHTML="",this.notesArea=document.createElement("textarea"),this.notesArea.className=this.uiStyleSettings.notesAreaStyleClassName,this.notesArea.style.pointerEvents="auto",this.notesArea.style.alignSelf="stretch",this.notesArea.style.width="100%",this.notesArea.style.margin=this.uiStyleSettings.toolbarHeight/4+"px",this.notesArea.value=null!==(e=this._currentMarker.notes)&&void 0!==e?e:"",this.overlayContainer.appendChild(this.notesArea))},e.prototype.hideNotesEditor=function(){this.isNotesAreaOpen&&(void 0!==this._currentMarker&&(this._currentMarker.notes=""!==this.notesArea.value.trim()?this.notesArea.value:void 0),this.overlayContainer.removeChild(this.notesArea),this.notesArea=void 0)},e.prototype.selectLastMarker=function(){this.markers.length>0?this.setCurrentMarker(this.markers[this.markers.length-1]):this.setCurrentMarker()},e.prototype.addUndoStep=function(){var e=this;if(void 0===this._currentMarker||"edit"!==this._currentMarker.state){var t=this.getState(),n=this.undoRedoManager.getLastUndoStep();if(!n||n.width===t.width&&n.height===t.height){var i=this.undoRedoManager.undoStepCount;this.undoRedoManager.addUndoStep(t),i<this.undoRedoManager.undoStepCount&&this.eventListeners.statechange.forEach((function(t){return t(new Y(e))}))}else this.undoRedoManager.replaceLastUndoStep(t),this.eventListeners.statechange.forEach((function(t){return t(new Y(e))}))}},e.prototype.undo=function(){this.switchToSelectMode(),this.addUndoStep(),this.undoStep()},e.prototype.undoStep=function(){var e=this,t=this.undoRedoManager.undo();void 0!==t&&(this.restoreState(t),this.addDefsToImage(),this.selectLastMarker(),this.eventListeners.statechange.forEach((function(t){return t(new Y(e))})))},e.prototype.redo=function(){this.switchToSelectMode(),this.redoStep()},e.prototype.redoStep=function(){var e=this,t=this.undoRedoManager.redo();void 0!==t&&(this.restoreState(t),this.addDefsToImage(),this.selectLastMarker(),this.eventListeners.statechange.forEach((function(t){return t(new Y(e))})))},e.prototype.stepZoom=function(){var e=this.zoomSteps.indexOf(this.zoomLevel);this.zoomLevel=e<this.zoomSteps.length-1?this.zoomSteps[e+1]:this.zoomSteps[0]},e.prototype.panTo=function(e){this.contentDiv.scrollBy({left:this.prevPanPoint.x-e.x,top:this.prevPanPoint.y-e.y}),this.prevPanPoint=e},e.prototype.startRenderAndClose=function(){return s(this,void 0,void 0,(function(){var e,t,n=this;return o(this,(function(i){switch(i.label){case 0:return[4,this.render()];case 1:return e=i.sent(),t=this.getState(),this.eventListeners.render.forEach((function(i){return i(new J(n,e,t))})),this.close(!0),[2]}}))}))},e.prototype.getState=function(e){!0===e&&this.setCurrentMarker();var t={width:this.imageWidth,height:this.imageHeight,markers:[]};return this.markers.forEach((function(e){return t.markers.push(e.getState())})),t},e.prototype.restoreState=function(e){var t=this;for(this.markers.splice(0);this.markerImage.lastChild;)this.markerImage.removeChild(this.markerImage.lastChild);e.markers.forEach((function(e){var n=t._availableMarkerTypes.find((function(t){return t.typeName===e.typeName}));if(void 0!==n){var i=t.addNewMarker(n);i.restoreState(e),t.markers.push(i)}})),e.width&&e.height&&(e.width!==this.imageWidth||e.height!==this.imageHeight)&&this.scaleMarkers(this.imageWidth/e.width,this.imageHeight/e.height),this.eventListeners.restorestate.forEach((function(e){return e(new Y(t))}))},e.prototype.addNewMarker=function(e){var t=l.createGroup();return this.markerImage.appendChild(t),new e(t,this.overlayContainer,this.settings)},e.prototype.createNewMarker=function(e){var t,n=this;(t="string"==typeof e?this._availableMarkerTypes.find((function(t){return t.typeName===e})):e)&&(this.setCurrentMarker(),this.addUndoStep(),this._currentMarker=this.addNewMarker(t),this._currentMarker.onMarkerCreated=this.markerCreated,this._currentMarker.onColorChanged=this.colorChanged,this._currentMarker.onFillColorChanged=this.fillColorChanged,this._currentMarker.onStateChanged=this.markerStateChanged,this.markerImage.style.cursor="crosshair",this.toolbar.setActiveMarkerButton(t.typeName),this.toolbox.setPanelButtons(this._currentMarker.toolboxPanels),this.eventListeners.markercreating.forEach((function(e){return e(new K(n,n._currentMarker))})))},e.prototype.markerCreated=function(e){var t=this;this.mode="select",this.markerImage.style.cursor="default",this.markers.push(e),this.setCurrentMarker(e),e instanceof L&&this.settings.newFreehandMarkerOnPointerUp?this.createNewMarker(L):this.toolbar.setSelectMode(),this.addUndoStep(),this.eventListeners.markercreate.forEach((function(e){return e(new K(t,t._currentMarker))}))},e.prototype.colorChanged=function(e){this.settings.defaultColorsFollowCurrentColors&&(this.settings.defaultColor=e,this.settings.defaultStrokeColor=e)},e.prototype.fillColorChanged=function(e){this.settings.defaultColorsFollowCurrentColors&&(this.settings.defaultFillColor=e)},e.prototype.markerStateChanged=function(e){var t=this;this.eventListeners.markerchange.forEach((function(n){return n(new K(t,e))}))},e.prototype.setCurrentMarker=function(e){var t=this;this._currentMarker!==e&&void 0!==this._currentMarker&&(this._currentMarker.deselect(),this.toolbar.setCurrentMarker(),this.toolbox.setPanelButtons([]),this._isResizing||this.eventListeners.markerdeselect.forEach((function(e){return e(new K(t,t._currentMarker))}))),this._currentMarker=e,void 0===this._currentMarker||this._currentMarker.isSelected||("new"!==this._currentMarker.state&&this._currentMarker.select(),this.toolbar.setCurrentMarker(this._currentMarker),this.toolbox.setPanelButtons(this._currentMarker.toolboxPanels),this._isResizing||this.eventListeners.markerselect.forEach((function(e){return e(new K(t,t._currentMarker))})))},e.prototype.onPointerDown=function(e){if(this._isFocused||this.focus(),this.touchPoints++,1===this.touchPoints||"touch"!==e.pointerType)if(void 0===this._currentMarker||"new"!==this._currentMarker.state&&"creating"!==this._currentMarker.state){if("select"===this.mode){var t=this.markers.find((function(t){return t.ownsTarget(e.target)}));void 0!==t?(this.setCurrentMarker(t),this.isDragging=!0,this._currentMarker.pointerDown(this.clientToLocalCoordinates(e.clientX,e.clientY),e.target)):(this.setCurrentMarker(),this.isDragging=!0,this.prevPanPoint={x:e.clientX,y:e.clientY})}}else this.isDragging=!0,this._currentMarker.pointerDown(this.clientToLocalCoordinates(e.clientX,e.clientY))},e.prototype.onDblClick=function(e){if(this._isFocused||this.focus(),"select"===this.mode){var t=this.markers.find((function(t){return t.ownsTarget(e.target)}));void 0!==t&&t!==this._currentMarker&&this.setCurrentMarker(t),void 0!==this._currentMarker?this._currentMarker.dblClick(this.clientToLocalCoordinates(e.clientX,e.clientY),e.target):this.setCurrentMarker()}},e.prototype.onPointerMove=function(e){1!==this.touchPoints&&"touch"===e.pointerType||(void 0!==this._currentMarker||this.isDragging)&&(void 0!==this._currentMarker&&"edit"===this._currentMarker.state||e.preventDefault(),void 0!==this._currentMarker?this._currentMarker.manipulate(this.clientToLocalCoordinates(e.clientX,e.clientY)):this.zoomLevel>1&&this.panTo({x:e.clientX,y:e.clientY}))},e.prototype.onPointerUp=function(e){this.touchPoints>0&&this.touchPoints--,0===this.touchPoints&&this.isDragging&&void 0!==this._currentMarker&&this._currentMarker.pointerUp(this.clientToLocalCoordinates(e.clientX,e.clientY)),this.isDragging=!1,this.addUndoStep()},e.prototype.onPointerOut=function(){this.touchPoints>0&&this.touchPoints--},e.prototype.onKeyUp=function(e){void 0===this._currentMarker||void 0!==this.notesArea||"Delete"!==e.key&&"Backspace"!==e.key||this.deleteSelectedMarker()},e.prototype.clientToLocalCoordinates=function(e,t){var n=this.markerImage.getBoundingClientRect();return{x:(e-n.left)/this.zoomLevel,y:(t-n.top)/this.zoomLevel}},e.prototype.onWindowResize=function(){this.positionUI()},e.prototype.positionUI=function(){switch(this.setTopLeft(),this.settings.displayMode){case"inline":var e=this.target.getClientRects().item(0).y>this.styles.settings.toolbarHeight?this.target.offsetTop-this.styles.settings.toolbarHeight:0;this.coverDiv.style.top=e+"px",this.coverDiv.style.left=this.target.offsetLeft.toString()+"px";break;case"popup":this.coverDiv.style.top="0px",this.coverDiv.style.left="0px",this.coverDiv.style.width="100vw",this.coverDiv.style.height=this.windowHeight+"px",this.contentDiv.style.maxHeight=this.windowHeight-2*this.settings.popupMargin-3.5*this.styles.settings.toolbarHeight+"px"}this.positionMarkerImage(),this.positionLogo()},e.prototype.addLicenseKey=function(e){u.addKey(e)},e.prototype.addEventListener=function(e,t){this.eventListeners.addEventListener(e,t)},e.prototype.removeEventListener=function(e,t){this.eventListeners.removeEventListener(e,t)},e.prototype.renderState=function(e){this._silentRenderMode=!0,this.settings.displayMode="inline",this.isOpen||this.show(),this.restoreState(e),this.startRenderAndClose(),this._silentRenderMode=!1},Object.defineProperty(e.prototype,"isFocused",{get:function(){return this._isFocused},enumerable:!1,configurable:!0}),e.prototype.focus=function(){var e=this;this._isFocused||(this.attachWindowEvents(),this._isFocused=!0,void 0!==this._previousCurrentMarker&&this.setCurrentMarker(this._previousCurrentMarker),this.eventListeners.focus.forEach((function(t){return t(new Y(e))})))},e.prototype.blur=function(){var e=this;this._isFocused&&(this.detachWindowEvents(),this._isFocused=!1,this._previousCurrentMarker=this._currentMarker,this.setCurrentMarker(),this.eventListeners.blur.forEach((function(t){return t(new Y(e))})))},e.instanceCounter=0,e}()},91998:function(e,t,n){e.exports=function(e,t){if(!e)throw new Error("Graph structure cannot be undefined");var s=(t&&t.createSimulator||n(72879))(t);if(Array.isArray(t))throw new Error("Physics settings is expected to be an object");var o=e.version>19?function(t){var n=e.getLinks(t);return n?1+n.size/3:1}:function(t){var n=e.getLinks(t);return n?1+n.length/3:1};t&&"function"==typeof t.nodeMass&&(o=t.nodeMass);var a=new Map,l={},u=0,c=s.settings.springTransform||r;u=0,e.forEachNode((function(e){m(e.id),u+=1})),e.forEachLink(A),e.on("changed",g);var d=!1,h={step:function(){if(0===u)return f(!0),!0;var e=s.step();h.lastMove=e,h.fire("step");var t=e/u<=.01;return f(t),t},getNodePosition:function(e){return b(e).pos},setNodePosition:function(e){var t=b(e);t.setPosition.apply(t,Array.prototype.slice.call(arguments,1))},getLinkPosition:function(e){var t=l[e];if(t)return{from:t.from.pos,to:t.to.pos}},getGraphRect:function(){return s.getBBox()},forEachBody:p,pinNode:function(e,t){b(e.id).isPinned=!!t},isNodePinned:function(e){return b(e.id).isPinned},dispose:function(){e.off("changed",g),h.fire("disposed")},getBody:function(e){return a.get(e)},getSpring:function(t,n){var i;if(void 0===n)i="object"!=typeof t?t:t.id;else{var r=e.hasLink(t,n);if(!r)return;i=r.id}return l[i]},getForceVectorLength:function(){var e=0,t=0;return p((function(n){e+=Math.abs(n.force.x),t+=Math.abs(n.force.y)})),Math.sqrt(e*e+t*t)},simulator:s,graph:e,lastMove:0};return i(h),h;function f(e){var t;d!==e&&(d=e,t=e,h.fire("stable",t))}function p(e){a.forEach(e)}function g(t){for(var n=0;n<t.length;++n){var i=t[n];"add"===i.changeType?(i.node&&m(i.node.id),i.link&&A(i.link)):"remove"===i.changeType&&(i.node&&v(i.node),i.link&&x(i.link))}u=e.getNodesCount()}function m(t){var n=a.get(t);if(!n){var i=e.getNode(t);if(!i)throw new Error("initBody() was called with unknown node id");var r=i.position;if(!r){var o=function(e){var t=[];if(!e.links)return t;for(var n=Math.min(e.links.length,2),i=0;i<n;++i){var r=e.links[i],s=r.fromId!==e.id?a.get(r.fromId):a.get(r.toId);s&&s.pos&&t.push(s)}return t}(i);r=s.getBestNewBodyPosition(o)}(n=s.addBodyAt(r)).id=t,a.set(t,n),y(t),function(e){return e&&(e.isPinned||e.data&&e.data.isPinned)}(i)&&(n.isPinned=!0)}}function v(e){var t=e.id,n=a.get(t);n&&(a.delete(t),s.removeBody(n))}function A(e){y(e.fromId),y(e.toId);var t=a.get(e.fromId),n=a.get(e.toId),i=s.addSpring(t,n,e.length);c(e,i),l[e.id]=i}function x(t){var n=l[t.id];if(n){var i=e.getNode(t.fromId),r=e.getNode(t.toId);i&&y(i.id),r&&y(r.id),delete l[t.id],s.removeSpring(n)}}function y(e){var t=a.get(e);if(t.mass=o(e),Number.isNaN(t.mass))throw new Error("Node mass should be a number")}function b(e){var t=a.get(e);return t||(m(e),t=a.get(e)),t}},e.exports.simulator=n(72879);var i=n(82396);function r(){}},98786:function(e,t,n){const i=n(59321);e.exports=function(e){return function(t,n){let r=n&&n.indent||0,s=n&&void 0!==n.join?n.join:"\n",o=Array(r+1).join(" "),a=[];for(let n=0;n<e;++n){let e=i(n),r=0===n?"":o;a.push(r+t.replace(/{var}/g,e))}return a.join(s)}}},41085:function(e,t,n){e.exports=function(e){let t=r(e);return new Function("bodies","settings","random",t)},e.exports.generateFunctionBody=r;const i=n(98786);function r(e){let t=i(e);return`\n  var boundingBox = {\n    ${t("min_{var}: 0, max_{var}: 0,",{indent:4})}\n  };\n\n  return {\n    box: boundingBox,\n\n    update: updateBoundingBox,\n\n    reset: resetBoundingBox,\n\n    getBestNewPosition: function (neighbors) {\n      var ${t("base_{var} = 0",{join:", "})};\n\n      if (neighbors.length) {\n        for (var i = 0; i < neighbors.length; ++i) {\n          let neighborPos = neighbors[i].pos;\n          ${t("base_{var} += neighborPos.{var};",{indent:10})}\n        }\n\n        ${t("base_{var} /= neighbors.length;",{indent:8})}\n      } else {\n        ${t("base_{var} = (boundingBox.min_{var} + boundingBox.max_{var}) / 2;",{indent:8})}\n      }\n\n      var springLength = settings.springLength;\n      return {\n        ${t("{var}: base_{var} + (random.nextDouble() - 0.5) * springLength,",{indent:8})}\n      };\n    }\n  };\n\n  function updateBoundingBox() {\n    var i = bodies.length;\n    if (i === 0) return; // No bodies - no borders.\n\n    ${t("var max_{var} = -Infinity;",{indent:4})}\n    ${t("var min_{var} = Infinity;",{indent:4})}\n\n    while(i--) {\n      // this is O(n), it could be done faster with quadtree, if we check the root node bounds\n      var bodyPos = bodies[i].pos;\n      ${t("if (bodyPos.{var} < min_{var}) min_{var} = bodyPos.{var};",{indent:6})}\n      ${t("if (bodyPos.{var} > max_{var}) max_{var} = bodyPos.{var};",{indent:6})}\n    }\n\n    ${t("boundingBox.min_{var} = min_{var};",{indent:4})}\n    ${t("boundingBox.max_{var} = max_{var};",{indent:4})}\n  }\n\n  function resetBoundingBox() {\n    ${t("boundingBox.min_{var} = boundingBox.max_{var} = 0;",{indent:4})}\n  }\n`}},53623:function(e,t,n){const i=n(98786);function r(e,t){return`\n${o(e,t)}\n${s(e)}\nreturn {Body: Body, Vector: Vector};\n`}function s(e){let t=i(e),n=t("{var}",{join:", "});return`\nfunction Body(${n}) {\n  this.isPinned = false;\n  this.pos = new Vector(${n});\n  this.force = new Vector();\n  this.velocity = new Vector();\n  this.mass = 1;\n\n  this.springCount = 0;\n  this.springLength = 0;\n}\n\nBody.prototype.reset = function() {\n  this.force.reset();\n  this.springCount = 0;\n  this.springLength = 0;\n}\n\nBody.prototype.setPosition = function (${n}) {\n  ${t("this.pos.{var} = {var} || 0;",{indent:2})}\n};`}function o(e,t){let n=i(e),r="";return t&&(r=`${n("\n   var v{var};\nObject.defineProperty(this, '{var}', {\n  set: function(v) { \n    if (!Number.isFinite(v)) throw new Error('Cannot set non-numbers to {var}');\n    v{var} = v; \n  },\n  get: function() { return v{var}; }\n});")}`),`function Vector(${n("{var}",{join:", "})}) {\n  ${r}\n    if (typeof arguments[0] === 'object') {\n      // could be another vector\n      let v = arguments[0];\n      ${n('if (!Number.isFinite(v.{var})) throw new Error("Expected value is not a finite number at Vector constructor ({var})");',{indent:4})}\n      ${n("this.{var} = v.{var};",{indent:4})}\n    } else {\n      ${n('this.{var} = typeof {var} === "number" ? {var} : 0;',{indent:4})}\n    }\n  }\n  \n  Vector.prototype.reset = function () {\n    ${n("this.{var} = ",{join:""})}0;\n  };`}e.exports=function(e,t){let n=r(e,t),{Body:i}=new Function(n)();return i},e.exports.generateCreateBodyFunctionBody=r,e.exports.getVectorCode=o,e.exports.getBodyCode=s},48812:function(e,t,n){const i=n(98786);function r(e){return`\n  if (!Number.isFinite(options.dragCoefficient)) throw new Error('dragCoefficient is not a finite number');\n\n  return {\n    update: function(body) {\n      ${i(e)("body.force.{var} -= options.dragCoefficient * body.velocity.{var};",{indent:6})}\n    }\n  };\n`}e.exports=function(e){let t=r(e);return new Function("options",t)},e.exports.generateCreateDragForceFunctionBody=r},7584:function(e,t,n){const i=n(98786);function r(e){let t=i(e);return`\n  if (!Number.isFinite(options.springCoefficient)) throw new Error('Spring coefficient is not a number');\n  if (!Number.isFinite(options.springLength)) throw new Error('Spring length is not a number');\n\n  return {\n    /**\n     * Updates forces acting on a spring\n     */\n    update: function (spring) {\n      var body1 = spring.from;\n      var body2 = spring.to;\n      var length = spring.length < 0 ? options.springLength : spring.length;\n      ${t("var d{var} = body2.pos.{var} - body1.pos.{var};",{indent:6})}\n      var r = Math.sqrt(${t("d{var} * d{var}",{join:" + "})});\n\n      if (r === 0) {\n        ${t("d{var} = (random.nextDouble() - 0.5) / 50;",{indent:8})}\n        r = Math.sqrt(${t("d{var} * d{var}",{join:" + "})});\n      }\n\n      var d = r - length;\n      var coefficient = ((spring.coefficient > 0) ? spring.coefficient : options.springCoefficient) * d / r;\n\n      ${t("body1.force.{var} += coefficient * d{var}",{indent:6})};\n      body1.springCount += 1;\n      body1.springLength += r;\n\n      ${t("body2.force.{var} -= coefficient * d{var}",{indent:6})};\n      body2.springCount += 1;\n      body2.springLength += r;\n    }\n  };\n`}e.exports=function(e){let t=r(e);return new Function("options","random",t)},e.exports.generateCreateSpringForceFunctionBody=r},26302:function(e,t,n){const i=n(98786);function r(e){let t=i(e);return`\n  var length = bodies.length;\n  if (length === 0) return 0;\n\n  ${t("var d{var} = 0, t{var} = 0;",{indent:2})}\n\n  for (var i = 0; i < length; ++i) {\n    var body = bodies[i];\n    if (body.isPinned) continue;\n\n    if (adaptiveTimeStepWeight && body.springCount) {\n      timeStep = (adaptiveTimeStepWeight * body.springLength/body.springCount);\n    }\n\n    var coeff = timeStep / body.mass;\n\n    ${t("body.velocity.{var} += coeff * body.force.{var};",{indent:4})}\n    ${t("var v{var} = body.velocity.{var};",{indent:4})}\n    var v = Math.sqrt(${t("v{var} * v{var}",{join:" + "})});\n\n    if (v > 1) {\n      // We normalize it so that we move within timeStep range. \n      // for the case when v <= 1 - we let velocity to fade out.\n      ${t("body.velocity.{var} = v{var} / v;",{indent:6})}\n    }\n\n    ${t("d{var} = timeStep * body.velocity.{var};",{indent:4})}\n\n    ${t("body.pos.{var} += d{var};",{indent:4})}\n\n    ${t("t{var} += Math.abs(d{var});",{indent:4})}\n  }\n\n  return (${t("t{var} * t{var}",{join:" + "})})/length;\n`}e.exports=function(e){let t=r(e);return new Function("bodies","timeStep","adaptiveTimeStepWeight",t)},e.exports.generateIntegratorFunctionBody=r},24454:function(e,t,n){const i=n(98786),r=n(59321);function s(e){let t=i(e),n=Math.pow(2,e);return`\n${c()}\n${u(e)}\n${o(e)}\n${l(e)}\n${a(e)}\n\nfunction createQuadTree(options, random) {\n  options = options || {};\n  options.gravity = typeof options.gravity === 'number' ? options.gravity : -1;\n  options.theta = typeof options.theta === 'number' ? options.theta : 0.8;\n\n  var gravity = options.gravity;\n  var updateQueue = [];\n  var insertStack = new InsertStack();\n  var theta = options.theta;\n\n  var nodesCache = [];\n  var currentInCache = 0;\n  var root = newNode();\n\n  return {\n    insertBodies: insertBodies,\n\n    /**\n     * Gets root node if it is present\n     */\n    getRoot: function() {\n      return root;\n    },\n\n    updateBodyForce: update,\n\n    options: function(newOptions) {\n      if (newOptions) {\n        if (typeof newOptions.gravity === 'number') {\n          gravity = newOptions.gravity;\n        }\n        if (typeof newOptions.theta === 'number') {\n          theta = newOptions.theta;\n        }\n\n        return this;\n      }\n\n      return {\n        gravity: gravity,\n        theta: theta\n      };\n    }\n  };\n\n  function newNode() {\n    // To avoid pressure on GC we reuse nodes.\n    var node = nodesCache[currentInCache];\n    if (node) {\n${function(e){let t=[];for(let i=0;i<n;++i)t.push(`${e}quad${i} = null;`);return t.join("\n")}("      node.")}\n      node.body = null;\n      node.mass = ${t("node.mass_{var} = ",{join:""})}0;\n      ${t("node.min_{var} = node.max_{var} = ",{join:""})}0;\n    } else {\n      node = new QuadNode();\n      nodesCache[currentInCache] = node;\n    }\n\n    ++currentInCache;\n    return node;\n  }\n\n  function update(sourceBody) {\n    var queue = updateQueue;\n    var v;\n    ${t("var d{var};",{indent:4})}\n    var r; \n    ${t("var f{var} = 0;",{indent:4})}\n    var queueLength = 1;\n    var shiftIdx = 0;\n    var pushIdx = 1;\n\n    queue[0] = root;\n\n    while (queueLength) {\n      var node = queue[shiftIdx];\n      var body = node.body;\n\n      queueLength -= 1;\n      shiftIdx += 1;\n      var differentBody = (body !== sourceBody);\n      if (body && differentBody) {\n        // If the current node is a leaf node (and it is not source body),\n        // calculate the force exerted by the current node on body, and add this\n        // amount to body's net force.\n        ${t("d{var} = body.pos.{var} - sourceBody.pos.{var};",{indent:8})}\n        r = Math.sqrt(${t("d{var} * d{var}",{join:" + "})});\n\n        if (r === 0) {\n          // Poor man's protection against zero distance.\n          ${t("d{var} = (random.nextDouble() - 0.5) / 50;",{indent:10})}\n          r = Math.sqrt(${t("d{var} * d{var}",{join:" + "})});\n        }\n\n        // This is standard gravitation force calculation but we divide\n        // by r^3 to save two operations when normalizing force vector.\n        v = gravity * body.mass * sourceBody.mass / (r * r * r);\n        ${t("f{var} += v * d{var};",{indent:8})}\n      } else if (differentBody) {\n        // Otherwise, calculate the ratio s / r,  where s is the width of the region\n        // represented by the internal node, and r is the distance between the body\n        // and the node's center-of-mass\n        ${t("d{var} = node.mass_{var} / node.mass - sourceBody.pos.{var};",{indent:8})}\n        r = Math.sqrt(${t("d{var} * d{var}",{join:" + "})});\n\n        if (r === 0) {\n          // Sorry about code duplication. I don't want to create many functions\n          // right away. Just want to see performance first.\n          ${t("d{var} = (random.nextDouble() - 0.5) / 50;",{indent:10})}\n          r = Math.sqrt(${t("d{var} * d{var}",{join:" + "})});\n        }\n        // If s / r < θ, treat this internal node as a single body, and calculate the\n        // force it exerts on sourceBody, and add this amount to sourceBody's net force.\n        if ((node.max_${r(0)} - node.min_${r(0)}) / r < theta) {\n          // in the if statement above we consider node's width only\n          // because the region was made into square during tree creation.\n          // Thus there is no difference between using width or height.\n          v = gravity * node.mass * sourceBody.mass / (r * r * r);\n          ${t("f{var} += v * d{var};",{indent:10})}\n        } else {\n          // Otherwise, run the procedure recursively on each of the current node's children.\n\n          // I intentionally unfolded this loop, to save several CPU cycles.\n${function(){let e=Array(11).join(" "),t=[];for(let i=0;i<n;++i)t.push(e+`if (node.quad${i}) {`),t.push(e+`  queue[pushIdx] = node.quad${i};`),t.push(e+"  queueLength += 1;"),t.push(e+"  pushIdx += 1;"),t.push(e+"}");return t.join("\n")}()}\n        }\n      }\n    }\n\n    ${t("sourceBody.force.{var} += f{var};",{indent:4})}\n  }\n\n  function insertBodies(bodies) {\n    ${t("var {var}min = Number.MAX_VALUE;",{indent:4})}\n    ${t("var {var}max = Number.MIN_VALUE;",{indent:4})}\n    var i = bodies.length;\n\n    // To reduce quad tree depth we are looking for exact bounding box of all particles.\n    while (i--) {\n      var pos = bodies[i].pos;\n      ${t("if (pos.{var} < {var}min) {var}min = pos.{var};",{indent:6})}\n      ${t("if (pos.{var} > {var}max) {var}max = pos.{var};",{indent:6})}\n    }\n\n    // Makes the bounds square.\n    var maxSideLength = -Infinity;\n    ${t("if ({var}max - {var}min > maxSideLength) maxSideLength = {var}max - {var}min ;",{indent:4})}\n\n    currentInCache = 0;\n    root = newNode();\n    ${t("root.min_{var} = {var}min;",{indent:4})}\n    ${t("root.max_{var} = {var}min + maxSideLength;",{indent:4})}\n\n    i = bodies.length - 1;\n    if (i >= 0) {\n      root.body = bodies[i];\n    }\n    while (i--) {\n      insert(bodies[i], root);\n    }\n  }\n\n  function insert(newBody) {\n    insertStack.reset();\n    insertStack.push(root, newBody);\n\n    while (!insertStack.isEmpty()) {\n      var stackItem = insertStack.pop();\n      var node = stackItem.node;\n      var body = stackItem.body;\n\n      if (!node.body) {\n        // This is internal node. Update the total mass of the node and center-of-mass.\n        ${t("var {var} = body.pos.{var};",{indent:8})}\n        node.mass += body.mass;\n        ${t("node.mass_{var} += body.mass * {var};",{indent:8})}\n\n        // Recursively insert the body in the appropriate quadrant.\n        // But first find the appropriate quadrant.\n        var quadIdx = 0; // Assume we are in the 0's quad.\n        ${t("var min_{var} = node.min_{var};",{indent:8})}\n        ${t("var max_{var} = (min_{var} + node.max_{var}) / 2;",{indent:8})}\n\n${function(t){let n=[],i=Array(t+1).join(" ");for(let t=0;t<e;++t)n.push(i+`if (${r(t)} > max_${r(t)}) {`),n.push(i+`  quadIdx = quadIdx + ${Math.pow(2,t)};`),n.push(i+`  min_${r(t)} = max_${r(t)};`),n.push(i+`  max_${r(t)} = node.max_${r(t)};`),n.push(i+"}");return n.join("\n")}(8)}\n\n        var child = getChild(node, quadIdx);\n\n        if (!child) {\n          // The node is internal but this quadrant is not taken. Add\n          // subnode to it.\n          child = newNode();\n          ${t("child.min_{var} = min_{var};",{indent:10})}\n          ${t("child.max_{var} = max_{var};",{indent:10})}\n          child.body = body;\n\n          setChild(node, quadIdx, child);\n        } else {\n          // continue searching in this quadrant.\n          insertStack.push(child, body);\n        }\n      } else {\n        // We are trying to add to the leaf node.\n        // We have to convert current leaf into internal node\n        // and continue adding two nodes.\n        var oldBody = node.body;\n        node.body = null; // internal nodes do not cary bodies\n\n        if (isSamePosition(oldBody.pos, body.pos)) {\n          // Prevent infinite subdivision by bumping one node\n          // anywhere in this quadrant\n          var retriesCount = 3;\n          do {\n            var offset = random.nextDouble();\n            ${t("var d{var} = (node.max_{var} - node.min_{var}) * offset;",{indent:12})}\n\n            ${t("oldBody.pos.{var} = node.min_{var} + d{var};",{indent:12})}\n            retriesCount -= 1;\n            // Make sure we don't bump it out of the box. If we do, next iteration should fix it\n          } while (retriesCount > 0 && isSamePosition(oldBody.pos, body.pos));\n\n          if (retriesCount === 0 && isSamePosition(oldBody.pos, body.pos)) {\n            // This is very bad, we ran out of precision.\n            // if we do not return from the method we'll get into\n            // infinite loop here. So we sacrifice correctness of layout, and keep the app running\n            // Next layout iteration should get larger bounding box in the first step and fix this\n            return;\n          }\n        }\n        // Next iteration should subdivide node further.\n        insertStack.push(node, oldBody);\n        insertStack.push(node, body);\n      }\n    }\n  }\n}\nreturn createQuadTree;\n\n`}function o(e){let t=i(e);return`\n  function isSamePosition(point1, point2) {\n    ${t("var d{var} = Math.abs(point1.{var} - point2.{var});",{indent:2})}\n  \n    return ${t("d{var} < 1e-8",{join:" && "})};\n  }  \n`}function a(e){var t=Math.pow(2,e);return`\nfunction setChild(node, idx, child) {\n  ${function(){let e=[];for(let n=0;n<t;++n){let t=0===n?"  ":"  else ";e.push(`${t}if (idx === ${n}) node.quad${n} = child;`)}return e.join("\n")}()}\n}`}function l(e){return`function getChild(node, idx) {\n${function(){let t=[],n=Math.pow(2,e);for(let e=0;e<n;++e)t.push(`  if (idx === ${e}) return node.quad${e};`);return t.join("\n")}()}\n  return null;\n}`}function u(e){let t=i(e),n=Math.pow(2,e);return`\nfunction QuadNode() {\n  // body stored inside this node. In quad tree only leaf nodes (by construction)\n  // contain bodies:\n  this.body = null;\n\n  // Child nodes are stored in quads. Each quad is presented by number:\n  // 0 | 1\n  // -----\n  // 2 | 3\n${function(e){let t=[];for(let i=0;i<n;++i)t.push(`${e}quad${i} = null;`);return t.join("\n")}("  this.")}\n\n  // Total mass of current node\n  this.mass = 0;\n\n  // Center of mass coordinates\n  ${t("this.mass_{var} = 0;",{indent:2})}\n\n  // bounding box coordinates\n  ${t("this.min_{var} = 0;",{indent:2})}\n  ${t("this.max_{var} = 0;",{indent:2})}\n}\n`}function c(){return"\n/**\n * Our implementation of QuadTree is non-recursive to avoid GC hit\n * This data structure represent stack of elements\n * which we are trying to insert into quad tree.\n */\nfunction InsertStack () {\n    this.stack = [];\n    this.popIdx = 0;\n}\n\nInsertStack.prototype = {\n    isEmpty: function() {\n        return this.popIdx === 0;\n    },\n    push: function (node, body) {\n        var item = this.stack[this.popIdx];\n        if (!item) {\n            // we are trying to avoid memory pressure: create new element\n            // only when absolutely necessary\n            this.stack[this.popIdx] = new InsertStackElement(node, body);\n        } else {\n            item.node = node;\n            item.body = body;\n        }\n        ++this.popIdx;\n    },\n    pop: function () {\n        if (this.popIdx > 0) {\n            return this.stack[--this.popIdx];\n        }\n    },\n    reset: function () {\n        this.popIdx = 0;\n    }\n};\n\nfunction InsertStackElement(node, body) {\n    this.node = node; // QuadTree node\n    this.body = body; // physical body which needs to be inserted to node\n}\n"}e.exports=function(e){let t=s(e);return new Function(t)()},e.exports.generateQuadTreeFunctionBody=s,e.exports.getInsertStackCode=c,e.exports.getQuadNodeCode=u,e.exports.isSamePosition=o,e.exports.getChildBodyCode=l,e.exports.setChildBodyCode=a},59321:function(e){e.exports=function(e){return 0===e?"x":1===e?"y":2===e?"z":"c"+(e+1)}},72879:function(e,t,n){e.exports=function(e){var 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"},11051:function(e){"use 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"},30711:function(e){"use strict";e.exports="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAgCAYAAAAbifjMAAADeUlEQVR4AYxSW2tUVxT+1tp7kjC0UChVsRcotJWOhVIraLVDA/a1b7WFvjSUFiGhlEL70LfQp9LaEkiTl740L4Wqv0AFLwleQAVRJxmjgqJRosYrgzqTs/3WPmeOc2Ji3Jy1197rrO9bt63oWJ+e3/NG7+Tuvg7TsscCQasp1ZCEkS3TeyvLIjOHAgHmkyog5eYj2fnZzLEynmMVCIK4KsQDopW7d+6P4DlWTrBl8ujLAe7dAJrEIQmur3fy8LL9oHcapinNzRAnAY4GB2Em8xD248Qz+5ETEFUFoxvQSALPJCw/SgL7MbNkP3KCEFw1MHoqNIsjp0MIWrl9b3bJftCTfvaJf4kRYbIgCwT4vs31019jkZUTeHFfMnojMHUTI7KJxDNtvI9Wp6ef6kdOsG/NupOq3d/RESmQ6RPYzgbw5QB7H8V+KDrWwXfW/ifSNRSjtnvAvqSkjqPVylyjWeiHfnhk9uMODri31/wsWjoAeICjbIPZTIBk1H2bzl3N34fOh7Cpk2S/SKssL34RRC9bJiE4ToITsYzUs6G8AyPVizdjP5S0WEiy+61Vs+pLn4u4hzEDJUEaHfEOV261wPcRypEAXAtJJt58/WgQ/32IQEa1DFhSYGPTUqRy48Hd0ZyAHE99Z0cvov73BdSHz2NqaBpTf9UxtX0Kk3/UUDf5/VSki0Ancuj4xhUT8cJt5S+HN0DDMJwAKojCszqF2F1CrWdVT7/Slz4LwIMnV7SC7OKPbiHIRE2bN9tBkoaUSltnBtc3aC+CeweDT5KHO8ThtRg1AwVqIQmo4WVgbnhjzYJrZ9pmOCPHt9PpEwrAaOIlphzBJBCvYzeHPvrXfE2Mz3SU1b8d+wqa/CC0qtcUaPVmRHBS636h1B+ds00zjVf/PPF+AvyjjBij80+MmmmeG6UexLrbGNP8bQp8TMn/waGMGFHAaE/EbIL+a4Np3Ski3XMCeLnFKMjF/lDinXVf/3XDWAop7nTJDB7jsFsmKVAgKjX/Cgp1Z4iozD09qJ8wEGKnBVE7cN66dWbb+kZ0WmR7QtDlJwgKkcSsJHLqBq79tC7OexFsNJlrPFz+du0cwTUrgxp8YWNXfvwgn3d0WmTLCeyfqIwLI1NqKK1csm7zbUuRoCQsAw3fxXe+bfWSdbfBpgsEXaLjzunApW/ee2bdBmzLYwAAAP//V59S+gAAAAZJREFUAwB5UwrzEPRfvQAAAABJRU5ErkJggg=="},64690:function(e){"use strict";e.exports="data:image/png;base64,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"},40517:function(e){"use 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"},89006:function(e){"use strict";e.exports="data:image/png;base64,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"},57581:function(e){"use strict";e.exports="data:image/png;base64,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"},4212:function(e){"use strict";e.exports="data:image/png;base64,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"},50356:function(e){"use strict";e.exports="data:image/png;base64,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"},40362:function(e){"use 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"},74732:function(e){"use strict";e.exports="data:image/png;base64,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"},87017:function(e){"use strict";e.exports="data:image/png;base64,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"},49747:function(e){"use strict";e.exports="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAP4AAADuCAYAAAAZQLrKAAAAAXNSR0IArs4c6QAAIABJREFUeF7sfQmcFOXRftXb3TN7ch/eideCeIs5jOYT7zsqBoyIcgmIiYkazyRfJPnHGM8kJhER5RDBCBFv8USTDzVGSbxlFzUqRuU+9pqj+61/3u5+p9++ZqZnF1iQ+SXuMtvd09PdT9VTVU/Vi7D9tVVfgSHD/lTXqlX35Bb24MDqgKgGiWosohpgrAYJagh4ChE0Ak1D4BoS6hxAE1+cAViEZBIwC8GyiMBCYDlCaAPO2zTENkJsA8Q2BryFabS+1mpf98L877ds1RfuS37y+CX//lvF1x88Yaphrqvqp1tWf860/sB5H2DQAwB6cA7GlvgSjEEeANYDh/XA2GrGrRWmpq3Qe2ZWLrlzovjb9lcXvgLbgd/Fbs6Qyc/rG978YGdk2m4EsDMR9CfAXkAUea+QYTsSrQOE9UTaRiJqJ7TaDIZtIP6f19pSWjqbA7DqYZWVhb5Wruc687SdPrfEV3/0sx211LqeehpWac3QV0sBaDkrmwbDqgFONXkuGIRWg4jViFY3IOhBiD2JU3XkpUMkBFqLCCsQ4D/ErU+6H7Dnf16YfJTZxS71l/p0tgN/C9/+IaNnVDU3w1dNoK8g4G5AsBO5NFyeGjLgRGw1Il+BHFegwVZp3FrXZ4f+6xb+4eTslvgKJ138RHr1Fyt6WkzrSXnelxj1J2L9EXkf4iKC8F4IYAHCZwT0iQ74cX09fPTCzDGZLXHe2z/TuQLbgb8FnoSvDZuxg2lhAyDtRQi7+YCCSAB8lQb4MWew3AD4onbVx6tfeGHyVuExhwyZrLf2/UqfPMAOjMOuFtBXAFhflbEIQ4YEnwDh+7pGTa/OH/PFFrgNX+qP3A78zXD7hw2bp30AG3fnXNsPCBsIqE715shxOTD4iIg+6VEPy7c1byhYzfpm2BURdwMOXyVGu6rGDhGaAWAZY9bbe0K3f8+fP9wOQ7a/Nt0V2A78TXRtJ0+ezB5/c7evmhrbDzgN4gQ1BbC7DzoBLutZTx9sa0AvdUmFIVjXjHsi0N4AsDcR1Mt9mKgmMHxXt/jbpxzwyUeTJ0/mpY63/e/Jr8B24Ce/ZkX3OHjY9L4IONgiOBA41HoPNK3mpL1VlTbefeW+ESs6+WO36sN945y5/TPZ/CCG1v6csE/hyzBo1RDeIKAl/5o/dtVW/SW72MlvB34n3BBRbrPWpfZFCwdzO6YtJFDWIsO3Ukbq7e1gL+9CCyOQy+f2I077E0CvguEE/Jg0WqL1zL2zvVxY3rUsttV24HfgGh4xYk7PlmzuMEA4iDhUOYeiHDJ4i3NryZsLxn/agcN/6Xc9YOi0XRjTBhOH/QEwJS4IMsgAwet16dTLi+eeu+5Lf5EqvADbgV/BhRMPJIJ2OCAb5GWr8VNNgyX9Wza+vXDhD7dIia2Cr7JV7HLSSbelV9R128+yYDAA7WKftKh+EH+XwHpxu4FNfhu3Az/BNRt81oyBnPBwSeeRMYsBf0tDeGl7SSrBhezApqIUahF8iwPbnzh3Zcf4MUN6cckDY5Z24NBfql23A7+M233g2bMamMmP5gQ7SbpJgK9VpfW/vzJn5MYyDrF9k06+At84995umaz5TQQ6VIZZDOEzrrNFb9w/qqmTP26bO9x24Be5pYPPnrmnZdLRRLCrDXjAFmB88Y6tLUu20/mugQURBnxeWzcYODtC6iMQYbmm46Il94/+oGucZdc7i+3Aj7gngk7mOJwMBF+1/8xYK3JarPXJ/mN7RrnrPcTijOzKyur014nhEcC5U0ZF+CjF4IntYVj4nm0HvnJNhP78i89XHU3AvyGUZXYDDIcX99Jq/j5//vBc13zkt5+VegWGDZuXet9q+yYxOFw0EtnyYGCv7LBj30Vbqq+hK96h7cB378rgYTP2tzicaKvInA6zV3rUw6Ivm6quKz6klZyTKxM+mgC/ISovQhasMXhyyfwxb1VyvG1tny898AefM7ePlc2eSgB72OwQYbnB4NHt9HDbeNRF2JbncJqXp4EPtXT6sSX3jVi9bXzDyr7Flxb4Iibkq6uOdCgh14RGHBk+s2TeqH+i3SG3/bWtXAEiwsHDZx1CnI4TPROiDCtCONYn89cva87mSwl8UY83wU7eiSk2gIyWaNn8M0sendi2rTzs279H+AoMPm1qjZU2jiOOg93k33od4IkvY/3/SwV8ceN5Kn06J9rHSfrCF0aKHn31z2OXb81AGXH7+p7VGXNvS6O9yKTdAWBHQN4bOPa2p+UACc17NRKlANEA9ycBEhI3EVmWA+URxDgtbBUjteypPozWALE1APA56vhvzcL326v0ZXMv6rFVS2W/9r3pu+ZzeBoB7GAXbRDfY7nsw18mw/+lAf7gYbN240TDOKfuiJhlRM9954CP/7E1tX2O+XVz33xV+2Dk/CBEbV8E0e5rA91uaxUZLCKyf4qX/F38dDwcijedn7bhI7TBD85YL/m7+OnsIH6IPzn/RLD/IHZqAcR/A+A7RPQOMXjdyFQvmfGT+q2mg060TT/y5le+zhGPIaI0Y7iBIc5fMn/UJ1uzEyj33Ld54Iv47tDh9xxuET/WLtEhLAcL5r/+0Jj15V6kLbXdBdet6G/WaMdzgqOA+OEAsDuJL+Qi2wM5tROHz1HTxIy7zxnoKzWDrSMTNqDG1jOOG7jOWsmkPGhaPsX0HJA9LFOg2chxMwWWZaCOBjN5LWfUnSzegxiInz05mP2AsR2R086AtCMARs/bA/g3AnsJGSzS26yn7/pp/y7ffnzQGTN6gAbDRPJPlP40ZM++Nu/8F7f1PM82DfzBEx6tMdesHQrEG5yHnF5sYHXPdtUJLyOuX98zXWUdwy3zGEA4nIic85YvZO0I9KEY4IFMf5+Rvowx49+axmzqrQoNNJ6KSFCWkiLYDXC+l8VyhWdE/tUSxoDnd+do7k3c3MseqEGwJ4HoUJQswSYWTUDwItPwuWwm9dzca7pmiCAmJDXxlmOBUBhXkfRp0nv3WrDkztO22ZzPNgv8g4fe9RVi+jDi1A2B2nWNFrw2f1zjlvLecZ97/u9WHIAWOw+AjuTA9/XNQSSWQYQ3AXCJgVWv6nr6PRGUS/h64A4DmmlRwE/+7bnlAd/b2zEB0iiIfyEhM83sPnnKfA0JDiGgA4FRmjihM9kROQC+ywD/Shqffc8l/d9Mfjabdo9Dh909wLRwKAFWI8ONyM35/1pwwceb9lO3zNG3OeDbpZthM4/gAMc46jv2iYaZ+UvmT9ywZS5x+FMvmNbSP9/Seh5xNoyA7yviZhcaFmr4NhJbgsx4raqq+m1ukilgHQXyELhzngFgehj4yf09ADcV4Kf8jMBvFDxjIH5jOuqZTPt+xPOHWmAdCpz2RYa6Ep68S4DzqrrVzr5rfF2XCQkGD5va3aKqYcT5boL6M4DnlswfvXhbo/7bFPAPOO+eWq3VGsoBxCw3ka5d3IA1z3UFaj96MlXxbquHAlnnAOERAssOrcQWAlykM+MFHWveQI0yHtAVIKse3AW4BLe3lR/aWge9vhXy9g64JfwLRkExCEFjIFiB2J4srDKp7UCT54cg0NFAhYGjFiAtBtTuYxtbFsycvPsWH7ttU39qOwY4ifskZoUvs2q1BW/OPl9UPLaJ1zYD/APOvKcf08zziWM3IcbhOlvQFdozR9+48tuWhucB0UlAVA/MLqEJ2vsKYurJdLp2MRDlg2D3efNcDvwgdwAeCWzF60c9oVFMQGzn8+xROwa8vU31C4Yh5TcGkYYgZYcGzhgdNLLZ1iOIcicC0DeIUBrBZgR4kkCfNfvyXou3NMLcduyhjuiHNnJLv+fNB89fuaXPqzM+f5sAvijVWUTnOk0Z7JN0Wpu3pfvkz7955UmI9GNOcIiosombRQTLNEw9qWPVc8xg62PBHgH0EMhjaX2c/3cel7jYPyqW9xN771/F6L9jDKINgfcZnhHged4jz9uO5WCeAAANsnzIEP5JhLfcc3m/hZ3xoFd6DNH3n81awx3qj+0a4pxtoeS31QNfJGQsYsPFGnIIsFTrk5u/pWSYIr8w5ndrziTOL+FEgwTckUEzgvEY09JPGZr+cSmwO7ANePRIkKtbKoDOlZ76pelpX8bfMrOln4NU2j4zCV7PDDi/RRmDICOwt3HZQJQRyFvmV7iVPYEof6rTLMWRkfYOMPr9zMv6LdhScbbT8psaRgADxZqBGvJ5XTFRnMS4lb7hSY62mbc98KxZByPy050kHi05Y79PHt0SgpzJk4m9X7fyHAD4AYqylq2IwfXI2F9q9G4Pc6R2FfAFr+t6dglhn1f3xfEeyL19/QAPgtm5FdFGgFl+4HMtDvgO2NVXyEgoBkE1BlHxv8oGwkbAYwGMsLrNbDkdrNwwAuxhS4sQP+AAf9yrpd99kyeLCsHmfQnBz0Nv73aakPu6S5o9/MYDo/61ec+i8z5tqwX+4GGzjjAtfrxNXxn+9V9/Gf1c512W8o40YSoZbW0rRoEFFwKgPQQSAVYxxuZrRvcndKCsZdfTHeCqgDftrHvOi9NDXj1n72Xvo3jxMMAdcEsw+6Ee7/3lcYp7ew/48jfPSPiNgu84qbTNDGQqMJ4NpECPYQEay6EJmLbyG07mnA8ngD4g4M7wUwB+R019/1l3TsTNvirvwd+deQzndKS45rrGnl4yf9QWz0WU97T6t9rqgO90Ws08wbLgW6JvXiNa+M8FY/5eyZfvyD7n3rL6GI34r0jO0Sf4HHTt/pTW+xkLc6ZTflMAH+fdA549CHY/0LMRAHfAHe3x471+6e8e9vZiHw/gzt/9BsHbp7BdnBFwKX8UCwiGARql9Jy15jgwrbOB4Y4iWYKAH1vIfjbnx302u8E/ZOiMb1qIIlmLmgYvLZk3+qktFYaUvo/RW2xVwBdllvd52xmc6EDRWqlr+MBr95//dqVfvpL9Rv62dUdmtf+KyDrBlbF/ylhqrmb0+CvHHJeAD9P5sHd3Muxhz+6BOAj0KJC77wXou/fdSsf80dchBviFsCAC5JCONARJjIBIC8aFAYxSzMqvP5Lz3AgA2MVuHgDtKa5V/+zeS2s/r+R+VrqPPbiF2FCnpRvf2IvVPNQVysblfp+tBviDhs1Lpa3Ws50aPeV0g923OYcpDptHWvXHqyYRwg9ArIOHkAVk96eMbg9oSKak9KXofLlgd+AaBHoUyMPGwAf1bIXAT4dpfpTHt98LGAOVFYijOOGBc7yiRiDAAsJhQApECGAR6rnsxrOA8bOBQxrsWQrwx/Zd+k6ZPxw324KbYhirmefniMU+RK0/q9Xe/+5WMqJtqwC+7emt1hE26BlrZXpq9r/+fM5n5Vq3jm439qY1h5lo/j8i2Eu0tDFg/9CNujs1xlaGYvhcDqLidx/gLaddLujZJdiD9F7zefNsYb8CpAPgZoGsPUBSTYy7KJB74Xgw6+8aBWkaHDArDEABugd2hw1EGQGuoT8fEGMA1BDANgCc98ubLeM5t74pPochvq+T/r/Tr+j9ckfvebn7H/y9+3biZu48MeBTgH8vrXZuKc8/cNi9+y+dP3KLjgDr8sAXMf0h3501VNB7AXrdMO7eXGOTzpn8WR+9Xv85EJ0mHgTitELTjWlpo+4fTpbeqc87CbgA4AOxu6kk6SSwmQUUBnsWooAeBXIP4H5g63qVv0GnY7gH08wEnhPHMPgMgmIMihkC+TfHCDgqfpUF6K4OQK0KyDyAZADSAFjMWVcrm2/5umWZ4xGhv8j/aYiP5pvNX943eafNMl5LjG8z8/lxNvgR3/jnX0ZFlh6HTH5e//ztj6YS4Agk9u3GB85/rVwD09nbdXngHzJsxol2Ig8ox1LV0zeXpx9188r/4QQ320MsCEyG+FCqtsd806KcL44vJO3cGF4BvIje1ay8A3gnbi8OeMer29so3twBuofiAsDdtzLK3zQjAP4Knxwr74G+Si4P6BICv0GoChkCAe6wEVDB7mcB4TDAjffFuadE57CoFHg5AMcAOGVAXcNUrnW9qLWfTkAGAq5lCJfPurzf3yr86ol2sz1/rn2soP0i4ffP+WOeVA8waNi8Oova5hPRic77+GkqlTr07S20cnKXBr4s2YlEnqbRvZsjphc1+X/XrL6MkI/ngMiQ3tOg6nYjXfVZMI5nHMj2/Jo7qUIxAhLwYTrvUXVhBDzvHgZ7JNADIA8D3NlAMzsJ+LoEvp/+S4OgGoNYQ5B2AK4aAScv4MX9YotQGFCoCPgTfpbleHrOHCMiDYCg//lsZicLMhcR0SAUCiBi03Zv63Pr5qj92wuwWDhSJPzUUt9+58ztn8/nHiciZ+SX+0LAF+t673fUkjsP3exlyS4LfCHOAeJnipKdobP5myN7P+a25r5mvu13ZMFgRFGrSS3Q9Z7zQtn6CFovY3hJ6VXA5+0Y3QO8ZrmGwn1P9ewq2G2PrgDdD/I4gCuMIMbrtwd8WdxUDVPx9narvfKyIgyCMAbRhkBhA5FGwM8CjGAyMJUGXwjgen/h7f303/H+IvvPzXXDLSs3VET+wGiJbtRcMuOHm35C0KFn37Nf3uTD7MVUkT2YYawNyFpIzqSk0AsRpjb+ZcyFiehFJ2zcJYFv90UTO0co8jSAJzZHnV5QewvgegTeiwg3pPSqP+h61Zs+Lx9B64OAt72tS+n9gI/w7i6NjwK7pO0e2DMBL+4AXHfB7Qez9y/Nqq5oYrCltSvPhmca5G+eUfAMgmMMnH/7GEEVKHkCzwik0+lIFiCZgTQAsTmAIvTfFgCZmQNyZuZiAt4dka0FZlx972W9/q8TcFP0EHadH+BkC3GnHNFZgNBDmvrCJDPl6jJkFy79y6ipm/q8/GxjM36aWOSg1AIVzmw8Pkpo7zeHIk9Q+w/qVl5KBKOFLoQBvpvWe/7BNPj6YCwvsvV+Wu9QfebL0mehGOBNYRSiAO9ScwH4aLB7QPdg7fwWBrffDOhGMvCbeRX04hP8nMAzCs774r9BQxA0ApIJmApTKCQH02nQlcqADAPiDICsAnATCtp/Qf+jvL+eZz3yfMPFFln7AopVdWDmni39frupqf+gobOuNZF+BkC6D2L+MYbOIEMx5FTDoxrnjX5xc8Fxs3n8/c6euWfeor8Bsh81zh/1l6gv6LTW8nFOlx0tef0vYx/elBdi3K0bemWtzO8B4UAxhhJAfyit1z1gakAiYy+z9cKri0SdraUvdM7lwE/rZdJOUnrPw2tCuyu+SAHwTjlPUvliYBceXQW6H+TOXyKBHeTzANAGEW8qF7gmAPACqgM3wTMMnkFwjEHQELjeP8AEbCOgsAAx59f+iEIY4FJ/l/ILA6DmAGyDEEP/g8k/kfnXLcCs2XIWkHkGd2aRvpHWqn5092Xd126K52vgd2dczAl+BwROFsKbRhacX+rNMmWwoiptHPrmnJGfbopzCh5zswBflDE+e/ujxUAgljMS9dZbd9j/q1e9MPkoU56QGKLB2s1Jop9edNmdccDHf96UDTfn3rBmF2TWHUC0KyBu0FCfkk7Xvh2k9sW8fLAsJwDueGD3pwL4KDqfNyQBVGl8xqbvDkSDHj0C6C6WJajL8+7BUXI1JZ81CfaCcVBIQNAQqIzAYwNhI2DkAVUDIKyBzQJCBkDmAACDZcByvb+g/tls634WmZOAqDsCfcrJmDjnqt6dBjRReh743Vk3EvHLHUQrQ4ol0uSUYzn5WLEMCPDqjt3gf0qx4pI3q4wNNgvwB3x35v8jLmiPeLnmD+H/dAbD350/5gu7Vn/WzJFCoGOPyuqVmbUpW2tH/m7VAJbjfyKGvYjjcl2vuxkM5qP2Tsbe7+XV8lzxOD4LfkrvefhMJprK6wYUwB706j4wt3ueOwxyB9B6qsYf1ycdGRmwA2auzX1O/H/wGYOQIQizAccIuCAOsoCqqkIeQGUAMgQoSv8jsv+F0h8DVMt+kOc9TLPlckTaFZHWcp19/95L+nZ4FqN4hgcMmzUHOD+nMMY8Gvm+keWey3cuMSLc3fjAmAvKwG6HNtnkwG8YNusI4PQCEHemrKgWDvELDWl4miNyoGPF5JxUlXH7phyiMfr6DV8z9ezNQFCHGi6tNbr/PoPUXpzae7G838sHab1bkoug9CrgNdPz9Kp39wDf7tH3WKC3eQAvANtDeAj8NtUv/ory+x7oxb7uFu4P52/eXlGGwHnPMQIyHAizANcYiKpAhAFQk4CqAXDov1cRCHr/qLq/oP5VhNUtuQ2XgDPFuFU305fPvKb7qx1CEgAMGDrjNwRwVXncvkABAoZAlIfZqe/NH/14R8+n2P6bFPiDh83r3sJb3iAOX5HMJ2jhgMjUmfacQfwfiDD79QfGLNtUX3jULauPMbn5/1CMgiT6V219vzsypuik8+L5ArUvCHGAgrG8SN6VQ+tFDF8K8F5pLwx2v0cPAt3v3f2g9kbD6fnairL6ptGqPBvOcvMK9MHHAooYAjs0cJ2/3wg4w/mdpKAMA6IMQGn678v+u7G/nfgTLzvz70/82eDXU3pr88oLCfFgBpBDxq6d1cFOP5Eovu/NmaJe74p0Iqh+IOgPLnpiZzsIPqvpjvu+PnPTrf2wSYHfcNbMuUB2E0NhNZbA4iyFB4oh/o169Dq1cfrpzZsC+KNuWXNWnls/ZkCMofE3PVU3B8mwRHecKrm1s/aqEEfJ2DsS27CXl7RexvEyaSdj+LCHb1cy8cUA74Jd8ejCk3sgdwAeDW7/XEg9XZ4BMLMq4MXRPdDL++IZBedvAvc+71/j/7cAfLwBaMdqqI40AP4cgGcAoui/9P6y9Od4f0/4E5X1J8xrZq7lXM7z/0MEpKN+86wrez/QkefvoNEzerRvhH+QHPgafOCDWf3ghxVWO2L3NC0YPaoj57JFPP6As2aNJG7NLnniyrJOiNCoM2PoO/NHvltyvwQbnHfTqvEcaIwNEjSeSKdrHlaTeLHxvEUUFcv7kndBWm9WkZell0k7mbCLALxL5T3vroLd8+rOb1FAd98rE9gJLlvkpp5h8AyCagg8I+CahCJGIBgGqAZAlgOlKEiWAWX879B/mf0HjCr9hcHvSn6VuF8k/TKZjWdYnJ8sjsaQTZ99Rd9pHblO+w67d5Bp5v5O7tJmRY8VWNassMSZSIJr2mlL/zLqsY6cS9y+m8TjDxh2z+5kWq8DULekJ42IrYzggvceHPPnpPtGbT/yxlUXAPIxiMg1MOal0jUvFAd9MWovS3Re8k718h6t7zjgPc/eGvDorRDnvY18QSYCLZ1x8QCgTjlO3vACNvXwjjEIGoJaPxPoDANQiP+LeX/AWOqvCn6C4M+2DSHKiUk/ghTOuPfKvnd15BIO+O7008nCB8VSg5UeBwE+S1Wn93tr7rmdvkhpxSdV7MsMOHP6CwRgjycKUftgXTN4IJcKMQ0OX/qXsS9VetHEfufftPpMAn6ZoHGI2qzqqrp/JAF9FLW3a/KKl4+j9TJLH4rhfR7e792TgF2CPBrg3rtGuq6iGD+fbVGeDRX+zh2R7wSNQVIjoIYB0TkAWQVwfqr0P+j9oxJ/as1fCn6iMv7C87dnWr5OZI0SclvGtFvvuaLPgx15/hqGzrgWOE1WI90o5Z7vMwKhADKc3bhgzPkdOY+ofTsd+AOHzhjBieZUfKL2F8cFTQ+OOaviYwDAyJtWDSGyrkUSWm32l5qq+r+qoDc5OCq8QDwflbV3wOtl7Et5+bwto5W03o3hEwM+7NkF2P1Ad/4VC+7mcLrEqKqPNAT5jBhpH3jV24vwhl6eUfAMgvitmBFwwoF4FhBlAGQVwHATgD76H/D+/sy/Q/2js/6BuD/g+dsyzUcC8e8ScOEsfnHvFX1fqPQ5tOv6Z81cQERnlH2MCGUfY/idpQ+MebTsY5SxYacCf8DYh+th7eqlBLiTXFo5mMUnMTFVTLMoLL3s/O4usCaCrP8YWu0B78wfXrGqasyNqw7JI11PFqQYY09VV9c/XgC9BaRm7qUqT8hu1Xjen7VXqb1bkzeryJ+8C8bxXtKurV3+HuXhVSpfHthDQHcBHgdq8Rw0Q3k503pnxe1owEvjEDAIjiFIZgRqoNZLCCphgG0Aqp0ygGQAwgD443/P+/tif0X6axXKfH7qH5f0c8qCzoSf9vbmUzjwExApZxC7ZsaVff9ZBpYiNxGYoHWrXwHCfcQGJZ//CKUfMvw8VZXatzMpf+cC/8yZNzmqJeVVSrLoiwWQEOHYxgfHLqr0Qo+8dcNeYGVv5US1GuLL1VXd768M9E48r8ptmU7kL9F5sbzw8pLWC5pvn387QM79XU8BOYV0B/xtEA94v2cPePUYkKvA9hmAjRVeSSU7o7KBoGEo/M01BkE2EGQCaiggWEDYADigTgmhT6EM6CXxinl/m/orqj+P+lcA/kzz2Zzom4jUBlr6snsv6/5+hVcSBp4xczAhF8k+R9upFLnKjYUR4d7GB8eeV+k5BPfrNODvd+Y9++Qh/wYRGP4PKYV87++IeFPjg2OurPTLjbxu1Y5g8N8DYA8E7W2jKj0LqdYp2SXy9Aros1mIovayROfE8iVovSmUdMkBX/DsEWCXQC+AvABwD+mpqm4Vxffy+ucyG5Xnw7UE7g8JeNUQRBsBhwkkMQCm7giD4ui/4/292N/O/EdSf8BKwU/YquUy7aMAaD8AWt+WZz9a8NO+FQ/0HDBUqFe5aNopqtwL/V3ZHDXtiMYFndPI02nAbzhj+jMAcGwYtCULlzYBQmT/1PTawyodVjh68roeZp31O7L4DsjYh+l09TSgmrys0xeP6Z2OOofex4C+QO39Xl7G8tLLh2m9BLyot8usu0fpg949Duw+oAdAHg3w6MWB09XdI41Btn1DzLPQPXRLPYPgGYOgISjXCPgZAGChHFhTUwgF/PRfgNlRAwa9v0j8OdTfyfrLkl8i8CsxP2Cbkc20jQegPYGxz/UW7ZKZk3uur8QxiWGxVr7lNQKICywOAAAgAElEQVTav7hjDB7dww8CvtT40NjDK/n8TeLxBwyd9V2yzPn2wQN1ybAyCcFbKtlZUA4R28AwDmmcf15FmmmhmPqwdvVNnPgg4vBFTVXd7RxrBNG2xTmlQQ92fC+TeCFBTgD0/ox9OHmn0vqcrZuXtL48wEsvHga7g/gw0B2Qq6BeX9HjGX6kevTw3vOMg98Y+AxBN4BII+ALBcIsQBoAmQRMSTmwHf8DRnt/qf4DlIm/IPgF9fcEP07Sz7DjeWcWQGTMr4CfUVt1W2bjRYCwo8b0d/Zo7XNFpS29+wydfgjn8Aon0kWLoP0KNO2U4gOMsbOWPjhmQUfB32GPP3jCozXNK1cttbvcKnwxxIlLHxp7Z4W7w3k3fTGOxIxzgmY9VfcHnVVvkKAX4hwrJnuvluvCoI+O56OofbyX9+J4Pe3V2LMFz9/iZeSbm0EFvP27jfMosG8oCfJUjfd5lV5XsV+uLVy7DxsDzxBEGQEZDtgGIcIApBV9gJl1Ps8X/0d4/3DizwO/Sv1l3B8Ev6r0C4JfswDFWC/Z3GPy9u4833KxRVCvMb5g9hU73F3pNR1wxoxfEvH/jd2/iKDH8avYuONBu++ndrZWci4dBn7DmTOuA85/UmhDjNPkxp4d+1vTw2Ocmn8Fr/NuWHUoIdgXUmfpGZBOfyC19wVFngUUzN4nAb0Tz/uz9pHU3o3lS3v58gDv9+we2FVvXi7A09nyDEFWTKkv46UaBGkIHEYQNALdAFwWUMwAqDmAOO/vi/0LmX+H+gez/h0Bv6gI2HJfF/xC2w/Z7J4mz44BkX/m+MvZV/WtaELu4AmvGS0r3niNAA5wLnOpHJj/ZghGwBAvanxo7JQyblO8fenIzgcOm7VzW9b8QORSZXtx0GCFynkOtbfpPiCKa3zw0ofHVDRjfMTt63tiS/42IN5N0/RFLF23KAR6LUXSAPhLdnH03u/pJehDWfuIjL2g+F62PprWG9LzF/HwHuDDYC8G9HLBXek9L2YUpCGIMgIOC3DyAflUM0YbAMfgxBkAJ/sPKOSA9k8l819I9GmAXtwPWA74I2k/AwyKfAT4ebbl6HzePJppsJHq0j+ce1GPihR1g86adbCZN4WeXw/jpay7s0JP1e/17vzhFQs0y7Lucacy4PTpvyegH/r+XipIUbOUiLc1Pjz2R2V91cBGIq5fVr3mV0B8IDLto6pU3UxC4F7DjRDoyHn3QFF1+lL0Pgx6L553ynSyLt8GcV4+ROtjAJ+qUj2yA3jp2aPAXgrka8Evg0jX9iorw59tXet7JnpBr6K3J8oYqEYgzAIA4xiAqgeQ9D/S+yvUX5b9POqfFPzhUp/ujvQS4Je/C9qPBCyT2ziaE+yOgO/t3d77Z5XG+wNPn/4LTvTzUg4/BCcxKooANAa/WPrQuMmVYEfyjIr2FSODc22ZfwORfyBbKeYi/85wZb1R17Bk/vDo9HOJszr/prUjLW6eKeqsRrp6CoP6jcyN5f0CHSAzQpxTKeh98bxZQ46X9zL2Mpb3svUerZcyW5G0U2N4x8OX9u5RYFcBXhLcq0usL9GnT3GQK0YhyiAEjUAcCygwgGAI4Mb60gD4vb+M/WXmX2TwlbJftSjxOdl+QSOTeX4/+HUN0ZP3qi29gByau+Uy7WJ15Fpg7ME5V/S5txIACcrfvPLN94DTnv66fuBoMRJ3RGgxqqv3qnQuf8Uef8Dp028iostL1yWjvwhjbMzSh8bMrOSijb5x3UEm5H8iTt7Qqu5Fvf7D6Fq92nAD5C/ZCQWfM/gyKMyJ8/TRoC+WsXdB73r5aMCLbDwUvLtNYZXEXDGwh4AeAHZVXZ+yvHzcPci0rPY/HwHDINlBKSMQzAdk2x0QRxkAmQCMBr8j+/USfx0Hv6Pwczr9RHOP3fGn9vQr/fxS3cet9Xvmzfy54ktoYPx65pU9X6/kOR5wxt3DOaf7C6GvHfEHlKyBA/uUf4h3LHt43KRKPrsi4DecM7cPtmY+IqBws3bJs7Bj/JeXPjT28EqWFh72m7XdU2jdJDr/NI29yNL1L6hxvZrBF0MzxdryolSXt0RM79XpTfF7BaB3SnVBMY4Xz0tqL2N5n5fPCZ38RqUc51H6IJ0PAl549jigxwN8Vcm7UXyDvpF/LhiECEMQNAJRLEDkAdQQQBoAX/xf8P6OkYii/gXVn0393ZJfYs8fFPm4Lb42+AHlyr1qpt+J99uGWJZ5ODC2Mbcar5h/Q6/EzNXW8p8+/RUC+pp3oWNcfGEDta4PJmrGvksfHNWU9EZXBvzT774OOP1EfFhcDBJTpgRkyDUNv/begrEV6Z/Pv3H1xSanbzFky1m67l7DjetLZfBtoIfEOaUSeU5MLz29BL0az8dS+wgv78Xx8TG8CnhJ432AX70aooHugbymvq/f069I+Fj092/f1rxKeU7CxsA2BIoRiGICqgGIywHkMv74v7j3B/TV/CsEf1DkI2J64dmDNf5gpj9PwHh240gg2JUYvTTnyn5/SHiV7c0Hnjn9SG5RbCNQSR0MwLSmR8ZNSPrZiYG//4g5PbPNmY+cWxQJ/cA8Yf8pIcIdjRXSk3NvXjOIROnQ4jydrrmbaXVrvLg+OpkXLNvJttqk9L5i0Ae8vErr4yh9yLtHgt0BegHkCrjjcF7drXhJr31jdCnPZwfcf3jGwG8IooyAygLiDYCf/kvvv3nB7+/qk+CPTvaJOn9L72y+bRwi04Cx6+Zc3ruiATIN35n+KBA/1b6hJer4ob8DtBvp+l2SNrUlBv7AM+6ezC261j4BG/d2Wc75GfEKMIKsbqR3f2/BeYk1z/bCF1Wrr+eM76Rrxku63vP/YuN6XzLPK9t5oHcWnzRNILF4RamYXgW9lN1KTx9H7TMiS+8KcNTkncjUlwV4N173e/dVRYFeCthJvUJwe2kY4g2BZwSC4YBgAcUMgEr/1di/SrAApeU37wp8POrvJf1stV8Cz6/rYt+gvDes7otK9sl43zTXfdu08t9iwD7bs63PNZVk+QedNnNfk/E3gEgLefiibtQ1FAjXND087jdJ7m8i4H/j3Hu7rd8oYnvoGR+TBCcJuEYBUYw1+tPSh8f8IMkJym3Pv2XtqWbeHKbpbAOmus0wiPKidOdX5kUn89QMvmAAthjHleEmB31MPB+i9l4sH+Xlg5S+QOdD3l3x7K4rlx69XKDX9ixPvCOvdeu68kQ8IUPQHyCKCagsIM4A+Om/4v27dbMlwKL273n/uLgfMAn4ffJeTWTvnYU8Ba0vluxT4/08omFlNo4hzrvrhj7/nh/3qmhU1oDv3H0XEY0rjQ1/DsBO9iFbvtMhu++RRM2XCPgDvjP9SiJ+Q6Cv0HeuQQIgyQBjmDMQ93r74bHLS385/xYjrl/fk2n564lTOpUyHmJajw+CFD8o0vEn8wIZfJ/2HsgT58TH9I6nD4I+LmsvQR+dvJOg91H6CMCrNL4csPsA3lnLROzi3YtiBsFnBHzhQIAFuLkA1QAE6X/I+0eC35kBEE76lQd+y/X2EvyqtNef6Q/E+664x6vvC8q/fs9cLn+G6N/nPH313GuSC3uEGK49ay4DEs3I0nlGhNIxOhlkMLzxkQucfpkyXomA33DaXcuIYC9pc6JCktjPRKwoCSGOd94ta7/PLX6IBvCBke79SCmK78X1QIWeeiWDL4yC8PpiKWkhvc3Z/+4E0Pvi+Q3QnnU64SS1L8/Lu3Re8e5xnr0A9BIg757Q428o5fFdYxBnCIQRKIQDBRbgGIAk3r867UiAg1n/YNyfFPwpTVQAlMYe8W8zgwL8arJPeH1V01+M8ueza75jcb4nY+yfs6/s86cysBfapOG0u68DoJ/4cB/cKiabjgxfbHxk3BHlfm7ZwB94xowh3LSeL6U0Cn2wWBSQwARMNTQ+ev6/yz0xud15v1+7n5WxfsQQ82Sk5lSx9IY4ii/KeiJz73h7p9uuWDJPbbgRv0dl78v29Ll6UrP2caCP9/KlAT96CPT82l4wGgEGMXvxqeIvXmqDEn9nZezPCbIE8O6SD2Hm9EV+uWAlBkB6f0n9JfjFqYisf1zSr3zwq9p+Af6wtNcDfyDet9fhyxXEPSrlz/Bsd8znzuVEhlal/X72j3q9Xcbl820y8MxZvblpLgegahmclaqaqWU1puuHLn1o9JJyPrds4A849e57CejcSkYHAYNZTY9cMLqcE1K3GTaPtNS/V/2CgPpqeurllN7jtXIpfiGutxt0wsm8IOi9aTltoJtA6pQcfyLPT+9lEk+CXsbzUQm8aNCXBrzw7BcdCTvt1Q/EaqqBYlvSq7rJtl/56UY4/Nan4D9BJhBnAOK8fzT1l3G/U08SSb94z++U+mSd37RpfU1hqo/t7QuNPR741WSfLoU9hXi/NOW3zPWH5szcYYxwdXaPvj+fPxytpFd7wGl3TSOCCwpZlmQS+NmNj44razBnWcA/6IwZPdpM/jkARXiZ4mf23845S9ONQZWIDOyBmRzOZqCt01KpeRozzGB/vajPSx2+M2UnRqQTk8yzu+wKDTcC9FKG6yjyOgL6SGrvi+U90AtmH6T0NpV3afxNP4Q/aRrYawN01ZdlwT1X3AYX2ue3C0CsAYih/8USf07cXyn4PYWfp+0X4PdLe8PxvifuCdb3vRIfoC67+Hhet3K54Ra3ejId7q9kUOfA02fszy3rTW8mpT/iLzbDEhFzKazZ7e1HRpRUbpQF/IZT7/4+EP+jfUNDwqLiSiNEmNv46AXnJn1Yhapp5C1rfgkW78U047mUUdMkKb69mKXtyZ0sfjkUX43rxZBMhxE4cX3ObrvtCOjDSTwV9K21LnFTQF9TDwQrQPyvKODFdRMx+s9HwSuIspUz6dXcPNsTwTu/nAWH+nIEJQ2AA2bV+9e2elUFlfr7k35JPb8Cft1R+Xm6/lLxfjzlDwp7cvm2BjJzxxLT1tx7Re+fV6JOHXDa3c8R0dGV3DXG8BdLHyndvFMm8O/6FxEdZOPebaktTBAJnl0grY8a+1rjI+MS9y6fe8uab5JpnQvINqb03n/WtBwF5+ap3l5m8YMUX9ehsH6dKN15FF/87lflCYov22oj6/Ruyc5P7+NBr1L7qoyM2uK9vOrhJeDFz48AYPooeA8RvlrJw7AZ91k+ZiY0yJMsZgAK9D/o/asc0Edl/UXcXxr8wVKfQvsF4APSXgFcOcPPH+8LuW4Wi1F+n9c3c47iz0phzlzzPdEqntK1OTN/3PvvSa//gO/c/R2y+MOOo/XK4eKfper8yNhn5wweu2spPUFJ4IsJodw0PeCWHBWkNBkgvtH02DjbYCR52d7+xjU/AeD9dD31N12vboxM6LlCnWAW36fDD1F8IrEqbTnJPNlhZ+vu1Tq9ksgLxvShUl0Mtd8YUNGpoJdZeAF4+ZoxGoQqbPck13Fzbus+Fjbw1c8VRqBgACK8fzehFiyD+oc9v0f7wwk/QNnZ57X1xpX5nHjfyAuEVYEAfxzlL5bl99X2ectAK2d9G4CtvPfK3r9O6vWFWG3ua9OXAdAeYYFcgGEHCbdzI45teuyC54rd/5LA3/vUaVOQ4EKpywt1D0V/sK3kY4gXL33sAidESPAad8u6gzN583yG2Irp3vMMzHEZv4see3/N3uu6i8riexTfq9dHxfW5FJCawd8koG/rS0FqXwrw9c0OU7jtYnivKwLfFmx6z8DyH/0B9hbn21zv0fUQAwgYAOn922pET4C/7Ffc81cC/uLxfqG+H1ni8wt7CiO7lNq+8Pp5SjGeW3M2capJMZhdyVz+htPuuhQ43RrOoPm798LJdrFoF5ux7LFxYysG/uDTHq1p5itEUi/BGnjyKWCZNFTt9Nbjydf9+t6NKy5HYjtqjL2STtW9Gx6Y6fXY+xN6jlBHqvNUSW50vZ6onGSeMAJ2S22Fnj4ung+CXvXwEvDy5nU14EuFtnQItqNhsPwSF/jyvIMGIM77+6m/P+5PDH4DULb1qtLeYDuvmUd78Q4Z73v1fafEV8jyu6o+KexRE32h2r6b6MtkW/blxL+OyD+fe2X/mxP4PXtTWyW7of0/RIK8FBH0hA5s42/DTn31HV6YOSYT97lFPf6AU6d/l3Nrvq9f2B9yhJhIAfYIcxofHz8y6Rc+5zdr9kXGRzNk7bpev8AwjLxY5krQdyehlyKv3VZ4+5iafSKKTxSXwS+A3h5+6Sjyyqf30fF8MS8fBLxz/d6H2y7eq0t4fAFwtSvDHaEmb/PyS//4/t4Ae4VuuzQAxbx/VNwvk36lwG+LfFSFXxHwp3IYoekvTvmjavte777TvisMg4z78/m8Yeaah5pkVms1NTPm/LA+cQNPw6l3/QGIfBL3OGWsbJ2RF54x9t2lj46LXfK7KPAbTrlrJhD51+gODQmLnpvPEI5a+tj4xOuOjbxp7Q/IsnbVDOOfhl79Tjnlu/iEHpBQ58ksvkrxw403jhw3iuI7yTxPhivEOUE1XiGRV4jpywO99PJhwDsLt/TeYS8bZ9cOg6VbguoXQB4CvEPxbeDbwyNsg7D8+gcc1K/54n332fIbAdUARHn/SsDvU/h16xao8ZeO98MlPifLb+XBXagjnOgrp7yXN3P7WvnsIaix5fde0StxyGuX9kzzTZ8VLVHXl4YBABc0PX5B7PqTscC3Ewz/uPsLQOpbXDocsRYewvtNj13QkDSpcd5N63fnljkBhK7f6PWgYUCkt/eX7xxZblxCLzqLH6T4QF0N9BLw8qZvCeAXGi6V5ku/t3fOzga9+A+D5df/xe/uHQPQtcBvGmJ8lzO8U4zvUil/MMtfLNFXGNRpK/qivD4YVn7tmZZlpQHozrnX9P8wKQNuOHmaWGuiwcuxFSf+hd4YxNYd+2p94uh+LPD3OW3aN02LXi41Cijmi1zT9MT4RG2C4jjn3bhmmAV0kK6x9wy99vVi3l4t3wVluaUSep63L4PiF+J6f9kuPnvfEU/v9/LimrzjEsR5124ej68m6wrxu3uTPe+uxpwAXExOFl4fYfl5/89B+b6DvCcjyvt3puePKvMVMv1lUv4oYU95iT5P0Rcl6snkmg8iC/bRCF+ffU3vspto5NUbcMpdvyKinyY1GGJ7jcEp7z02/omofWOB33DKtOv+O7jqJ6UmgIT+LibspKt2SdpzP2Qy6TtVr71GjNFjercn0zrfWMjkK7F9KW9fLKHnCXWAxBQdNYvv9NU7clw1mSdHZcXF9bY4p4QwJy6J56f37xdovQr4njs6IfXUCSAs/yYv54WSdtKbK0+PmtCTCjOb7iMs/9FdsKfYdN3nToIubAA8758M/P6EnxT5RJX5Qk09AfAHS3wFSa8i7IlK9HkdfI6iz2nddWf2RXh9keHPmqwbz284CRBzDe29rp88Gc0kIB508oyD8pT/l9TNlJTMKwdHxKmNj1/gKCkDr3jgnzTtDQI6oKRgJ3hAxJcbH7/gW0m+nNh25G/WHWiBOVRHti5VVfdssG4fJ9aJ8vZej31Ezd7W4fuFOqXi+qKgB1s3bmMhKnuvgn6d2yUXFc9Lai89vAS8vI6bGvhq0k56fec9Gcq5tJ48Mama2JN1/B/d7QBfvoIGoBj17ym7ApVyX2S23xX5lAR/0Xhf1fMLyq/O7ItI9BUt74W9vlrXz2VajuUEPRHYgnuv7vlGUmzsfdK0Zf9dLTecMY0S9CgCO0T8bOlj43aJCrkjgT/o1Fm7mVbuY/sEiytyIybw4E+bFo7/ddIvN+KG1ecB4B7I6M2qVP2yYN0+LpPvGASnzTbW25vVJObgBxN6UTr8cOnOaa+NS+b5FHmBOn1p0PupvQB9EPCbEviq5xafE/y3/Z6LaPFTmAD1ZW/vGgcn0wfLL5nhB75qAKT3L0b9i4HfV+evAozL9HvJPqWbL5by+4U9gvKbuiPnLV7ec7T+ci0+X4Y/WNfPte1tcn6ABuzD2Vf1nJ0UGwNPvft6bllXy3vkb4sPr0WpTsRC1L7W+ERYORsJ/IZT7roIOLd7iqNz9t6pB3MAaMCBjY+M92ciS3zTYX9aWVfVDJeAzoAZ3RamNCMTmqyjqPRkaU+04Jp2GOAMzbTjfne5q7wR9PZeQi+nDNVQvX2pen3RuL4I6IUST2TvS1H7KNDv1ODg8dohICapdgrV93l3997I+F3eKuntZcZeGgHBAEVMX9jO9Q52yAe4/KYXYQ/x1mdN4Sk+wvuXQ/3LAX9cmc+L9yPEPTb4w1n+lOFKeX2JvuJeX5XyxtX1pdfPWfkqnl1/EnCATD38bv73+yVaAWfgKdMGcwJHPVuqnhcALDH42bLHx18XhGAk8AecfNcTRHSSs3Ep6CtGAOGTxicmfCWpRTv/t2sOs3J0NCKuSKfr/q4m9cIqPa9ur2byy/f24YSeKslVS3dRFD+ubLdihddsExXTx4E+jtpLwMNfnat57bUdA75K331e2y3TOQTeeRxCRkB5z5fVV+J/NyRYfvOvHeCDuxpi0ACUov4i7o+T+dq0X5H3BsEfG+9HUP6gsEet7Zfy+v5Y3+/1/Wo+r3Mvm235JhH211K06J5Le7+cFCMNJ0/7kIh2DwllFVIujhn8OyIuanxi/DElgS/UehvzX6xBlC24/kOFk32eEUKE2xufmPD9pF/q3N+sGs9Q60Na6rXqqtrP/IKdsErPX7ev3NvHJfSc3vpoii877YJxvdTedxroXcDLa1kp8D067j0Vfm+uAt4z9E6JzhmkGmYDwTjffeQIlt9yvQt8eeJHhr1/R8DvafvdZF+ReL8cyi8TfZvC66uCnvZM605kZQ61yFz956t3mJYUIwNOnnYjEV1RapHNMCHAzJ6wc4+FC0/Oqp8Z8vgDTpp2NAGItkCHxAWUesUWwUTUTm5aOG5hki915k3N/arN/BiNWSamuz2T1lOWup59WUk9RaXnk+aGYnvP2ydJ6MVRfJnMUxtualsdai7pvfjd8/Ze5j4qng96eXkdBw0CGjYMliWh+oXaunuQUDyuvK8CWy3hyWfAofukDFJ2/u1nCPYqMMsXPgy7v/tugOYX8f7+uN/JX0Vl+1trvWOq4C+H8ktVn394h0r5nURfOV5frev71XxOhj88ktvx+lkzp1F2/XEWN/R23Zjx4BX1K5PgZNDJ079hcvPvQZceAfRCB59zfAKmYUhMFwb+KXdeRRb8Rl7m0IFjxv0iQtuO/Y3exfTBUV/0/FvWHZXP576GmvFJdar27aiknr1SjgWUFQtiuNJdqckXbbf+un15sX3F3l5V5sXE9RWDPuDlBeDFNRPF33llAD+KzhcV3LjKO5mncfb3e3j//g7YnUSf4+WlAXCNx/Lxj8Duw9wbHWUAoqh/WeCPyPTLZJ8Ef1SWvzO9vr+u7yy8ISbzyqm8hfl8srQXSPLlrNb9zBzfzTC0V+/5cc/nkwB/2LB52pstG9YRkJjkUPaq9GJTDeGXSxdOuLaox284cdoDADRUblRu3RABH258cvwZSb6M2PbcG1aPAsA+KaPmNT1VtTouqRcr2OlEb5/KORRfrlQrMvnS2/spviPSiYrro0EvpLcOVqJietvTK6CXgJegFz/LBb6XmXdBahvqiPg9Qo2n5Oxcei/2leB2ga7I+QoswHYfwiDA8gmPOAlICX7xu88ABKh/mPZ7nj3k+YPgV+P9CMofEvakADeX11ebd2SSz8xl+uTybYcC0Oo5V/WZlRQrDSdNe5qIHycNtXPVA2vtRSUBGP6t6YnxLu9yPjXk8RtOmrYciJShysVPT8b8iHRR48KJU5J8mZNuo3TP1rUXaYyToVc/r6VrzWia72/GCZfwwpr8wuBMt26vZvKjvT1RXANOMKEXpPhJ43o1ex8H+qDEKwr4fg/vldu8PIxaonPBr+rrCzG8NA4KuO0YzzMavnBAjf1dhuDYA1w+8VF/5SHS+0eAP8rrS9ofl+wrRvnjEn35FDoz+mNEPV6sH6zrO336UsPv79wLl/ZEki+o5LOyrXo2234UIcN1tb1uX/hD9MXdpbDTcOK0a/97R4oujR1MxTsAx9YD67t3nz9/eGEGoA/4+wydvaPZ2vaZ2o0XPJk4QY+m64PfeyzZenijf79h73xr7hTScX11uv61OKVeqPW2aAnPmawTpdJT6/bBTL709lE1e786bxXUlKD4xTL4lYB+32FA14oWPaWcF6T1MoZ3GmdcwCvAdqI9pRbvUgP1vYIgx63ZqwbE3l9SfCUccPZxfQjB8tuq4KvvzPc7lE4Ff0cpf4TX92f4nbp+UM3nzOdThnUogh5R2gu17MYo+drbmg9Foh6Gnnp85pXdRd6m7FfDiXcdA8CflfdF3hN/92ygru8eXdPY/u89fkFh8q8P+ANOufs7ZFoPFxIIkhP4Yorgkln2ITL1Xzmk25I7D82X/S2ENv+m9Udzon0Zah9VVdd/2BGaH9eB543TUhtxwtJckckvp3wX5+2TxvVRnj7o5QXg5fUUwBflHLl0WUFa694b79/u/XFLbT5JbUGIrxiBQOZegls+TIXjKgIfGed7zwmCmGzOAG3gy3OOMgClaH/SeD+51w+LeuqgzmYAIsNfaOBxx3RFd+75p/TEJfmi6H6mvXkPTtZXNYK377kqWZw/aNi8OrNlw3qx1Ja8xuVK6pHh2MYnxs+Q+/mBf8K0XxHST4talEBMIR4shuzlxifHJ5fp3rDqXETswYzU6ymjfn1xmu914QkG4M3Sc0Q7cjUcb6SWI9iRk3WKeXvZctuehZBCr6S3D2Txo7x9bAbfjevVJJ68MSro4Rd2Hf99IthdLbNJi1/IrvvUd16M7z0kzm+q1NYT4zhUISZp5+wn8wXSHAkxD1c8PsDyP94AXwUljVQU/DGlPgH+oLQ3WN+XWf7g9J7iiT7AuAx/2OsHO/e8qbzObD6lZdftw1f1+0LJF0X3c/nmHjyfO4gRrZ91Vd85SRyl2HbvE6cuQQCa8eAAACAASURBVIJDCrcgGOOHdDdO0I+M3dG4cPykSOA3nHDn0wR0nE8SGMrihzW8yOD3jQsnXJLkSwy7lKrTO64bDdzieqrbSwYAtxV57mgtIdGV2fxIpV4gqdcO7fbkXb3MEl450lwZ25eq2XfE25cDenFdf34tvM857K5WW1QQFzy1zLq7kxl8HXVu1t6j7V6t1pepDyTwnO3du+seVxoMyfRdg7H8Tze6Hj8G/CHaX2a8XyzRF1Xbl3JeNdaPz/CXV9or1rIbqeSLyO7nAZiZ2/gtDhrrn+o587eXYXsS3DSceOdtQHCxl70J6GwKvRXShDvJPwZsSeNT4w8NAV8MuBxw4l1rAXgP/9p4xQU84kAMcGTj0xMSWa+zb9nYwPLmUYzY+pr67m/717f3RDtx2XxVqafS/LKSejkio6qe4lR6vkx+sfKd6+3DzTfx9fpSFL/g6X/hfxz+91poIoI9fXJbJZMTKrvJpJvM/BYGaQTENy5f9zy9RLkizS3E9MHpOy6DkHSA4Ue33xDQ6rsGQPX8AvwdofxS0pvE66tS3qDXFwk/uQ5fWNATl+TzxnP5l96Sc/mcmr6k++oY7rbmDftx5D24oT9//4+7CSl22a8BJ9w5nBPdH7dYdTgHJ5O6lD2wvmetTPAVqP4+p87Y28rnm0IxQ9DjRzTtaEaq4b3HxiRKVIy5dd2RZo43AOifVNV1+1SN7z3Rjszml6L5Xu2+3KSeAL03Qy+s0is3k9+Z3j4O9OKp+Nm1sJBbdHyUks72vsEsvPIoFby+L56XIJZ1ewXEvlbcQK2+WBkQ8bkpN8Lxoac4AP5N7fWLSXmDXt9ehru+HoSGv3SSz9PvV0L3ZVkv07JxFwBzNz3FmmZc1jOg3ihuAw48ddbO7bnMp7HL1BdpqlNxWgD+wBOnDeWcP1CBMmhd45MTeiedtjPiulXfA53VpnT9HSPdrVnG98IAqDTfJ9qR2fyKaX4wqRcu4ZVdty8S26s1+1JZfDWhVxT4P4PvWQBz5P3x1+vFwyLHX3kiG8f6u4k8laornXYqxfdCB0ntnadIZRmeaMej/4VDMzx/yg0QZn4d9vr+2r5a3vN5/bLr+k6sHyzteUm+eCVfKbpfXMzjqPjy2Y31ppXbz7RY85+v6X1/2e7e3bDhhKmfEMGu9l0PrHMRdNzqsRnD0xufnPCI87TIg51452XA6ZaoOqCa1A+eJAI83fj0xBOSnPzoyVSVT68dQRrxcBkvWpvv67tXgN9ZNL/NFu8AFKP5QT1+R719uaC/9lrn3PIcLiGA/+WceqqqOcm0nUBc8dBSZit11z7VnUrbVTWebMvyvyc/wy/ycZ4gBFwPBNf1q4VbxHa/+EVYHyITfrGUv5Ni/VJqvpoUoFiKq7PofpyEN6pjT2r3heLPLutpyIy2XnNnTsbYabhRuBK5OCA6Tt6T4jk57wiIeHXjUxNuCAL/NuJ0can2++CJEOINy56aYPcKl/s6/1fLdza1uuNYSm+uTtctLaeMF+7EqzybXy7NV5N6xVR6aia/Q94+ENeL6ylBH7i2O2bF6g8JXvaTlYNJQHC5T8kHBBrDbxKHVeUeTlWdMAsyfWrg8+C+ceCvPNaP8fqRaj6vgaecJF9xul86uy/EPOGOPU+7H1XWa8ts2AcsqtXyLc/e87Nd/1PutRfbDTjhzimcyJ6sUwqvqiNHgFlNT0+0F68tePwBx099hABOCwE7WLYPlAs01CYufXr8nUlOfNSta/bN5+kQXTNWp6u6fVI6vvfm5Udr8z3RTtQ8veie+wQ0PyjY6WBST2Tyy/H2MaBPcql9227IwVVEcL1svpEUPV2FO9Y6y/h16isE/lKUP6HXL5nkKyrjjaL7JbL77pQeKeYppd13mnb8ZT0Z52czG3czLd7HMPg/Z13W+50kF37g8XdezolusvcpgXyV+iPCP5qevvAbQeC/SQD7h06gBPdnBCcsfWbi00lOfNSNaw+3mPZVnfh/jOoeqzoS3+fk4pdKGS8o2glKdJNk80sJdsqp25eVyS/f2ye51CHgc07XB8OBqs0FfJvCAFTi9YvW9RWvHyXoUZt3YrP7ERLeKDFP1HQele5LFZ9vuS1fWc+N89tb+uZ4fmcD4aNZV/YSy5+X/Wo47s4zAWmB2KGUgCdw0JVNT0+0l1n3Yvzjp24kovpSov/gB2kGG7D0iQmJShLn/mblSQDYM1VV+4HOtZZS9fuk8X1J0U4OKK7nPqp2Xx7NL6+EF6zbxyX0Otvbi5u9Tnh8DtfbVL8g2QWort40Hl98Zimv35EMfyHJ10G6X5UCzGeai2T3o2bySe1+vIqvEOdH1PNNy6rLQWZPsMx1c67ul6iVfcCJ0w4gzp3ZfQHHHLmkVgHoSHvqu1aL3nwb+PuecFevPLfWOMeJmJPvvhc2SUg77WzUJG3FHXHzuqGco1Fl6I0GGXlvlZxy6/dxTTlCredN0BVqvWKjtVSJbmw2f3PQ/IC33xSgt4Gfgas40fVSzy95ogB+HeIXQstRtttJsGEU+Dsryddxuh+U8Abpvqfd9+bvSxWfv2mn3Hq+MAh5zBv5vDmAGOXnXt7T9t7lvg44/p7aDLXb47uS4RUgpcNeby+c+IF9o/c5YeohFoclUR8cPLC6DSJ+3vT0xJ3KPWGx3eCpZOyzbsOZwDSruqb8xF60TFfU78uJ7xOW8QKinSTZ/KA8txjN31zeXpZaV7fT1UR0ve3sFY0/1uCO/RC/kPexsw1AOV6/HEGPSvdLKfmKZfeDdD9RWS8izo+W70YLeSCVEgpT5AywtbVlACNLf69n9weXTMREfS4Nx935BQD1D4/GKy64Yxoe3fjUxOdt4O997B2i/95eZys4cSc84UMdtYUvNz49MZFGf8T163uylHY0csoFG3OihTuCBYiBmmlbny8HavpWyKkwvg9q85OKdpJm88uh+Z3p7YPaCgF8O8Yv9M87+X0WAP6mMAA+8HdI0FM6u19u4051OlDWSxDnh+r5dreet9SWrOcXS/CJhh1imOI5a9Hca3qsS+JAG46b+iIRhbAXq9yTsR3TRjU9Nf4e+xFoOO6Oy/47IcquwZaa6eWLKRDua3rmwhFJTvj8W9t2tqzs1xGNFjFfT03s5SAHzJ6mqyr2JPAFjXfXwRM99gaQSOz51sOL6b0vtwW3ZHy/KbL5m4Dmx4mpbOATXS/7auyfCMAId+xX53n84P3sDAaw2em+LeYps6wX06obJd9Vu/XU8dtxCT4V+ClIgfD0luUk+NraNuwMSLXA+atzrur9aRIcNRx7hxjkcX5SwR1D/MnSpydc7wD/2Km3/ndp3UsjcgWhc/ERCYTrm5658CdJTlj04JuZ/L4609YXy+jLuL8zE3vJ6vcRffdlAP+zdV4rbdJsfmd4+2IKypXS4/um4wLoUBz49nPRCfF/0Osnye7v1NMBcRTdLyfO75x6frxuv6SQJyazb/JsD72q7p2ZP6pKJHlvOHaqPZQjqeAOEG9pembi5a7HnzoNiC4oB8DqBzGESY3PXHhHOfvJbUb9Jrsv17J7MB3Wpii93tRTpGlAQaluFPCLN+aE23ArSuyVGd8nLeNtDppfSjb9RQtdTaAm95ywzcDSwO8M8HcG3U9S1is/zi8nwRcn5BEJvviGnejMvpjVl8McZntwE3pBzvz37J/2KgzJKAdPA46f+kPi9PtSwA+G6oA4fdmzE8dJqj+XOJwTHeNTQQ/s/N2b8MFQG7H0mfH3lXOicpvRN647KK/RLtVQtRpRa64so+/vv49rzKlIuOMCP0n9vhy1XqRopxNpfinQi+svgM+BHAGP0rabQlaU6qv3tyOev/PofmVxfrF6vj/BF5/ZB6gRmXE0xRgueypPxgU+oFTwlRrMIaW7RFZ9O2T6GBZ+OvPKnq8nwdGAY+8cy8m6O/ESd4APNT478Uwb+AOOveMhIjg9iuqHhEHKG6hpZzQ+Nf7hJCd87s0bvgZg9TFAW22wqrZSwJfz9cKDN5Jn9IPCnWL6/PKBH12///VIOKgmDZcCOf3patus+LcVfEOW1pXuN7Ed5+GrK3aVu8s/qxp6P1Cdf9n7EOwMQLu5vzvvix0Zew04uVllZ5qON9zDS//bnxno8/c6AwutOkAieeCMf3CP5Z1DQTriNvLL8xbfo2CPCMgi+qQtw3434wn4p9hbXYUnSPej6vmlhDzimJG6fTfBV7Rhp4OZfQn8PDNr8ma2D+ja6jmXdH81CY4ajrnjbAL4c5JkvOu4/9r4zMQhbow/5RkAPLbwhBRR/fsFPNpxy56b8GySEx59w4Zv5gi6V3evXqnnjaxI6ImSHNOja/gq8MNjtP2DN2IVe6H+e6LgbL2SiT2x4OWnAOX03l83Eg6sS8Nii1Pavjbu3bEn1oaGXLhNNTa+3MYY2yGrS1V5k259TTLuhQ++583jUwCsCHbk/VLn9qmU0d/Ga3+BwiCOqIm9ztw+Z7vwgE51ZHfBADmbKsbPORd1CpB9vFxrBv9HgL8Y8MWWdpxfoZAnl0EEZbWdYH9+nIKvuHRXDuAMa/Zlb75p5NPtG9r7pauM9TMuqXklCY72OXbqKRbRY6E6fqhbz6vUuY/iW03PXniAA/xjprwIgHZpoFjd3rm13jhfprHDlz494aUkJ3zebzYeYSKrrq5OrTTAyFvafxfjzuWgnB78ikt5CvDjhmr6gR8xPjtBYu/WcXA3cBKLgHpeNTigUnrt4JCLWIB6RsPfJusCqDBkM7C6rfSkgj2I9e0KBsXT6kjqL1t41VFeBVYgjZZyvs59dwyU9BWFsX4FcWBw9n6Y/bgEwb1Wrv2Q1wFh7pQFzG4sSZzgC7TpFk3wKZn9JMCvhmqwab/uANwu6ZUxikvU8vMARnt7az9d4+2zL++2OAmOBp44bQg3redDk7ZKH+SjpucutJfigoZj7nidgA4MAjvKEKjAN3TjoHeeGpdo2d/RN7Z/mzRIGRpbpbGUWRz4SilPWRQzbrUcW7WnLIgpNPq+Ul7ZUt3kwFeFO7eMgacBaIgKfM+5uQCW3q1A8RUjURiCo4C9cEP97ykEwvW2zoaqNy/8WzplxbioDKQAcglupZ/fi1XUtl+5zp7LCmTooDgHdQWeAitwDxYyYIFqg2NMcPGUB/Fo8QnS65ed2U8C/AxglHTXV9JTBnBGavYjJu8KzX5cLd/iOT1v8b5oQW7mldX/Vxqz3hYDjrvjUM7p1aDEPuS4A9k/xuCzxmcn7SzLecuAyF6/KCz6V2KvwJkZurH3O09d4Kz1XOZr7M35I3Jk6noVW5OmlFU28Dujhp8E+IpUV87NL9Z/7wP+KHgaGAzxD7lw7oBvpdlCWOxRfEmBZezm86CSHkexAgm64Eo4hak7rkEoLIUVUHgFQFuYpOt6dXXFHHnaIWPmPgOStntzAD0vHzk6zDfxx2+0OKfFdz6ilQR+MM4PDeFUltWOm8NXEvg5R7PfkVq+nLUvPH4Wc5qZ4b11Aisp8BuOnzoQLHqvNF799xkBVzc+N7Gvm9yb8h/OwZbehpN5ocXzPN/DjJ0bnxn3WZmYtzcbeePGbyMYLJWuWqMj8I4CP2rGXtRE3bgafjka/SDwS5Xybh4FzwDCkdLb2fQa4N3VORgirkFtnevymr0rV+csjNSh18Zie7ufxQGe5ET20EX5gYzhvgZBorXcxP7K6Zd93q2typCOOme3dve9WqRnCWl/yWLsJCTHxXc+Eu/x7fNQV9h14/wo4NvX3v0sAX4h3S13FFfcQhtJRTwq8E0Clstmeps8b913dTKqv9/x03fNmtlPQln9QP0u4PABGWxsenZSd0eye8wd6xGge5THL3ZHuzHWY8mzEzeUfdfFLP2b248AyENVVf260uO0S6v2VODHdeUFJ+rGNudUUMOPKuXdKDy+TfWll7UTV29NeBgOFu/YGv0OlvLKKd9F3ZePNtJLxPlhqteu09kO/euwon78pOW9YiW9nwyhVzmRfY0c8Is4iIWAL/6y5ovySnodqeVHj9z2i3gqBb5U72UyzT0BDJh9eXWiGH//U+b0zLRvXJsU+ACYWbbowmrH4x99R46ADOdBCfr8oM3wHqf6vVhqyZ0TEzUXjLyl7VvETKxR5uhL8Q7knEUx1cm6jk7fL9eNG7fVVYB/w/nwNCINcVJeBc/61sRHtjzw/72BXiKgw7y2XBL60R326ALAv3oIvQpEB/uX68LF0wIevysB38nsu8m9vAgFMvY0HrUvX8b4kEqD7jboFGS7+eYeyHW698c1iZLkgydMNZrf57mQR1c6dSPxjMSbnpukyeSeSdxdnSOA+5AZUCbyHNSnt66ux1WO5z/nprbDAEyoq67fWOkAjjDwiy+esbk9vgA+COArsTgidhngc+KHqXG4ZnQN4F91JL1KxA/2kqLC8+Piux/1U/0tC/w2jG7P9ffllzuQo6W9uZsB1XDPFcbL5eBHbiNWz31jzRozuE9Yqee3BIhoNT13oe5Q/aOmtCFCtaRYhdmMEd166gf17t275uX5wxMtCDDu1rav5/MA6drq1jjg2/P1xJLYVjTV3xqATwBDZH3b8fv41oWPbnmP//56LjzLYd5gTgDNwC7h8a8UwOd0cCGxKRKRHBZPf8yf3NuagA+QhljZLgPMtrbXsrROMy9JJRLwHDZsXvWaNWvainXPRhkSImhf9vykGunx1wMnO8Yv1e2jHqybljzGH3F9bnDKyDOjqqZtWwX+rwXVd8t5ylp0b03qEsCnl0h4fPdmi/MzUl3D41/5bf4qARzsEwlxXDz9sa3X45cCfj7TVpPLG3zuNanIeRhxLGDwsVO7N3O+PgT8ANUPCXwY29D03IU9XI9/+0oA7Bsd4cdP5KmtSvf718KxZU9nFccf/duWg4ihltJqMtsq1b9OUH1SknuO1vWt7z++5T3+srX8JUI6TC3XdRXgX/FtepWADraz+YU4iS2esRUDv9TsvZzVVoX/XUVz5qV1ibT6Bxw/pV97nlYEPXVQwhsazYWwctmiSf0dj3/0lE/B1nGXfqnJBETYpWnRpESjgUff2rI/YEozDCMfBP62kty77jwnqy8T044UF976QVcA/np6iXPuAR8RUqmuQfUvP4K/Sgi+5B4nWjyrS1H98lpzy03u5fMicCVr5mXpt0qjz9vigJOm7ZLJmMtDMX6J0XkE8Omy5yft6gB/yO0fAuLuTozv78YLHlgtH6SQ7fX2ookfJDnh836b3Yc4pqrThrmtlvN+JYHvq8xjlwD+0rVKjO+KfdLprkH1LzuCizi3QPWdMIktvqdLefzOLee1Z/N6FaPcXZem30uCo/2OnrpnjrhYOj22ezb6ePRh0/MX7elQ/SFT3kKE/ewNS2QL1A9iBvta4zMXvpbkhMf+lvbglKs1Uile1jz9mGWz5PSdrijg+eW58DRK5Z4LfgR86+InFKovLppSy69kCEcltXwJ/IKqkACqqioDftIavv2V1VV2AiO4Lj1CZvWVxh6Cxfc8Hq/cE8fcWgU8GQaIuRxjVanW6Rfhh0lwJCS7ZIrrVRz4YUeOby97YdL+LtW/46/E+f/YkWiJtbh8TTqonbj0+QlPJTnhETfTV1IMuhliChEH6qhyD9oBcobo0gMSi2l0mla/A5LdXwjgi+SerwMN3/phFwD+eyLG53SYOnevuqsA/3AnuSeZp9utuHh2EeDHDd3cGiS7DvCB5VKwce4P8OMkOBp41JQTLKInS6luQkpcxv7WtOjCI12qP2UBAZ1Zzgf7gM9wxNJFFyYaxDHhd+27tVlaz7RuWIkku1tRk84vRjh1fEmgnG5VfOuSTga+a6gTSX1t4BMcVlhNhwBqqpN7/Eq8fSmPf4kLfF/rMqfF9y4srdWPHL/VxZt0hGQ3a+a1Gs1ad+cl1Z+Ugz+5zcCjbh9hEcwpCfyAIweCB5temDRUAn8aQPLRW8jw4qZFk/6Y5IQvvJV2ziD0BR2sNEGJJp00BfvxNXfQZju023V+vZwJu5u5LXeyC/yCAs0F/qVdAPjvruEvcRJZfa8ZprYCj79pgO9Idn0NQQSL57rA39bacrMIGpigVRGsuuMyTJQkH3j0HRdzzm8rVccPK/vwrqYXJo13Yvwjp9yASFdGhfjh5J7arYeTm16YFLH4U7wpuOB31D/L87saupE3APLb4iCOn4+QdXw5eMKecvPWZS7wxdUJ6vUrifHlVU4S67+9xqX6SpMOVrMd9k8g2a0U9FEeXx24ebHw+IqAx3ke2eK5C/HobXEQh+jHz5t5Q0vnPp35/brCugblONKBR0+ZzDldW1qy6z8aAdyw7IWLrna0+kdNuZJzcpbPDTTjFbMoiDi18flJ9qqd5b4mXU89W6o3NgAnqwqq27fF0VsC+LJJx6lJ27mTty5b6MSvUcAX720O8L+1hl4CtUlH2KSa8oHfaaC3v7B/Hb2LDxfKPUeyq3j9xfct1IoCf2sdvZXTzCpOpl7X3q1pyjWYaK7+gCFT7uBEE0vhNbjgxn+nel/Z+NeLbrKBP/DoKaO5RTNsC1u6DuiJ+xCebHrhopPKBb3Y7rybqBah+QCDk8WMqtZSwFfHaztTdsPLY3e1YZv/ew45bbleId/uzvvxJgD+h+tg1xzCWCA+AAjtRqvCHD7nhnoaD+efR3FOveSf7HuH+DgQZLi9J3OPIH4Ko8VB9HKKyhoCLSfOHh28A7xQ6p7/fQWcBsSP40Q7qsckZYigN07Q+UxOYvwbdVfHcAHiaiL6m6OBElOERKuu0torzhHx49ZWdvf/vQ0ftIoRXABQauZe8dV0Ns+wTQ5Wbd4yNYL6N2dfga2lrqn69wFDbl9IBCeWwmvwmEzDMUsXTZrpdudNOZpb/Dnn2nqjtco4kfea/nrRoDK2K2wyZPLz+s7dB38DOVA1pjdsDeO1rxkOw9Mp+CECDECAlG8Qhbf+ZKG/nQg06Rm9sVZ22cWUHXsFgNr7O+gkeyf8lIg/jj3Yz/YAKNpiv3QDHEIWvQBEdep6eHICXoFt2GO33FsQnHXnWgA1Q1j4fu65iWfCGSAiuw3Z1V/fAW6Mu+9//4L/njhcbH++990KJxCc2+e7nu4XUc9BziKUnxd9/XFjLs9Of3QR/EMCvyMtuWJUQN4ANLOAYuZeyh7CEd+gY+UzkVN2i43Xbs5Z3bW0ibmd6/8+fzhaSXDUMORP7xHBwPAEHp+dDx2SaXhM46JJi+w7aYsBLMuepFNqdI//SNi27G8X1SY5YbHtOb/deBhYoInWXI7Ay52rr66kk7Q1F5qboZIFNSaNheE1aZrueD9vHpzz8Hlg8IBRALE3gNLdUq2pSjLgeDL/OC1xMwHgmb164AnFru27a+hZADpaLRvK0Mw3x849iNotqCyY63wTdVJPYdKP04rp7ScvAOS0Orbz4HqwF1pVX698AftYnL+jjtxy/u6NHCtUFAo7BkeMuROJAscOXX/X6Aq660z7Ze88+BT7eiWlvHyqGasysJlWzAVkIqPf2tzTqgbzvku7JerME5dl7yP/1AYA1aUcdbCOn9Z1W3RnP2GDhs1LmStXiy47h98pr1ICAUCtb9MLE1cnAf+om1sHc56rM6p6rCeAvAR+V1xC69Kh8DcEOqQweTbiYVSNgKczd7yjNA/e/qrndKxJYfquvYsHAs1g++9ZB+/EXdv31sJ6TrybA1yP0oe8Nzn0X5Z+CtsrCT5/D7wLeHn+AmCFZI8LY8aO+Xp/eD54bi99DiM5t+5xsC6n7qqz+dzvGGACqhcvzBH0XT/vWvqfT3fegTgAw9YHn2L9bOB38SW0UAzabGnpkUqxllmX1yZq0BE6/UxW6PSjRuV5615EPDdc79en+t35w3OFp7Phf/70HwJn/Jb6KiXoMTT9m+8+PzHRaOALbsjukwO+g25ozYZutJUn4tkyi2ZeNhQ+J6J6NVR25sZ5nt2bNS9hLsIl+bB7iaqCIbDB7j7IBQrueTnbiott/n973wFmRXX2/54zt2wFdlk6iIosiN1FEUHFaCxRE5VgIvaYaKRZEr8kpnyY5DNfvhSVotGYGGNJhL8lGgtWVIqoi11hsVKWvsv2vffOnPPPe86cmTPtlt2lxDCPj+ydOdPOnN/bi0G/Pro3RLZQfn/7v+y6PhE+jAD4CYEY43B4LyHSAe4V04lTEhv3G2Ccc/QgCPRUWFLPpgGHee4b6mW03XnxivKSGEgiqAE8RI1SRCvs2Rgn9Y89S0f+OzTNzJiZEjNjlSeAbrrrB4WF64488Y5xhFmvhgE/iklIOkw21L00bag923LoqBNuF5VZAhzeX9HDZ0YknFy++uWrhCic7zb1lx3DSRwOMBK8vdgoblLAz6e2fmdnJ7gGvsKbarRAC8TTnCeKevF8SnDdcEm/rcB5kRTNtfrxHm6kg8cmCHqGmcbF5cJ27SgugbD3ayI3J+T8Ayvgwah5fW87E70v/GBRon+AKCjUKPHdFgEEkdEaZUjxURIu+TbyeSXBk9GdAPSc8RHA5xxEbIdebFRcSZ3vSBrudR2iaM8PDg6U3dZsBvp4V5pygZ+/ft9Mdkeb7A7L7G2lUyU8Y3z0wE+KC4raG3XCbZdxbqufPkkum+hPgCxd/fJVE73AP37+fRzgAn+aX646+wYhv1/10rTv5Qt6HHfxTc19TcrHUs5SxcmSrV2z7Nudc+2OuTJmHyvxAE8nSngsAxyLbnapfx4AFHXiMt0KP7KBrzAj/nWIgAZgjSj4jVeuUSyo/ztj/dxOfB2aFfjvbrM5fmhzCptz2lRBPrNOJLwSiwCPRLWdEqs4vFwBCsiKaFFiRAKfMS6B77jlNKKm1BKNcKq59RAwdVwTV3QpwR1rp40LdQTqFzxiVA8AAAf4RfLho9tn5dM3r11U1w2vvNNJrEzh7bNSmfb+KUbiSU5r/3pDr4CtJBueqk+47XfAATtch3jhdMtTwKlz/5qX1GLx5wAAIABJREFUp1/oAX71cbf9iAO/KVfJPb/fkAB5ZvXL07IaofwvMWU2T9CixpMo57wsWbZOAN9I5NU4s7sGvnhROe/Mu8w2wA8vhq3AWZF/8bsGNZfDu8CS3FERCdcgHtJJR6ur73Au+2RCswP/na1MZ4oe9SGS+Chd3QagRw2wBRdBA8Q44Stz+uS4BjpUp8OB/3I9TOPMmqfr6TqgXSlEn4sgkfLYVHwSiafhh5pnfFZG6hc8QqsL0u8j6unjE3kt+vml4+p988It+mmC+1tTrcMYIYR1Vjy/cDZJF8I4q0+Y/wxn8OWwcwKqueaeJ4T8uO6laTd5gD/6hPlnMQ6P5XqAQEAPQH3dK9PzyuXXr33xrxtPNC1eXFxWsZEBpMIs+yksv4VEIaIEV7bGGu3QBpLrl3JsrAHQCvFkmZAA/D30duwASJQA95Tativu/uBivpVwKPK6s8K5pViDKjZaE5e97ii/dTtK3MVgv+zAf3urhU52jz3B4cyO6G6rz0gi7H2y843dAUe17XI+jv58inSpfTYXx0VAjXOOCxH1X65n05jF5zntwGxVwdNPQOfmjrphSyMqgMzxhCj1X1OnfPYJRwLjpP6VR41qsA17na3bCFRVZeH2zW7rLLtnHkAZYHVdbKQR1ToLoBjyqa6bhCRgVx3L1yKbAiQ7WhsHxQzS8dcfVAQMpLkwWH38bfUg4iNyV8zSGTUl8NVVL01/3AP8Ucf/cT/O05+o6dU5gf4ggWwfNE8WJ/u+v+jbDbkeWD8+9X8aD+cGH1ZUXLQ9QYp35DTwxZKcolhvV+EF6ASM28/E89XzAbCrjlt4M4eeb4v7P7gYtnLGi5RY5ReHHTeYsrAqfdgRCbwtpDwcNlTsdTkscvyDsuj4byHHjxCFnefVKv16kl8c8GUBlC4d+GwWQGkE8GGaZVm2ju+6PxUJUR5QRyJSUoYzQG++oUlTHmOpu5J0yQBF/SWPGtX5i/l+/d4fuNNGEmlCoKQEzDQQ2SW3w+6SS0TbLIAi8LbOSonj2TropLnZp7OjpS+xyLoHflxYl9zRJ93T10q3bJN2lmAWvR+DOl4JSey/+uXvfOoBPsaOjD7hthbGoVR3++TK/sGLGEBPW/XKVQWl537zl9uHcaBHxuOkvbS494Z8DHyQSgGW2o6K4HP1/BIeVWq7UH/+f13Et3KOwNd0X1u3EuK/n/uoFa01wNTWtP1dvB111Ad0jHKKSwKZemgV/D2KoL65xRX19UAhryjsGiQdi32Ix8GjZmhuxYAqYEs1JAL4i9exaYx7Ob56/uxESo7yJDYplcMhXl4i5XbsU9+G1i9ZTqvbW+QJnXl0z8nPfx8WuBNsjw1JWVjTC/wUiRmEMBOw1BEmlpG2jqYhLMNLGLCVf/9J30AVnWwMdPTx809hHBys+Rl1EK9SugMCratfmtZL5XW4zmasxHPcfIx6OkpZ9tWHUHqD/OZePyGONSi5cdXL02cXwvFnzuTJrQNavmIYaSiKJdewZIL5u+Yih1eGPz10Nx89Pyw3X4j7gc650rof1TL7p9/tuwVrVTjg1FtQIe6FCC1pqMeK7SEI9nHNsi3nSiMAoQY6OvWR+fBgVAw/At9RQQLne7mlIj5eS73uX9c68gakFSniy8e37Rcx45xJIaI+At/ifJ6zIPEctcpse4bH26CpIMq+6BAALXhIlxgC9guZ/YjBCvXPPtswCqAfhIn5eI3Q1tidLcKyr4v5AKUQ1T0nqpZ+qH5vusDH82gqTTvN1EiTG6T/xj5PzJ1LUoXgpnri/P/+13zOdoxIgSJ73qtphGBF3SvTj1FHfcCf90fO4duRp4Yk8djEYNHql6edVsgL4Njzf7H9NItAaVlJ+ec8Fm/vqp4flqIL7e2QTnAey5Rq1n1Xz8/LrfcvA89Pvs63cA5Fjpjs6w+vc1q52H398exJ8Qal2GMi9Vl5EmN06mN/kO68MPDXbkaO71rkdBuDW5teEQDdNReMMfCqAYrPhzTotN8fOD1n0rCgH/+5z9l0AD5Xl14kK3d1eJeIeiMGva5k23YREvLrJQza+zFS//xzNvBzWvMLdOOJZhlSzPd0yI1oohGl3xMzU9La3jIcLGhd8N99C5KS8b1HHjd/EQE4RX2vXHE26jg16F2rX5r2nVDgjzp+/uWMwV3Z6ur7/fw249pR9/L0ykLSQ/G8Kb/dUUNS1oiSRGJLMlm2pZCW2UF/fjEXxj4TV0o7ilwetx7eT++em2/47o+/zreADXwlWkpY6KK/T5wOcHM3OMXvW9c5mVfUR+DzqY/9wXD8+H7wv7FZZrwEg3hUqK0GYIcA6ftcI6UiWg5H97TDDnbtJWAEgI9ltSZcyqZxBL4eTag9o27hD8QgOATC91xO114VS+G6GpX7Wc4BrX/+WTpKcfusbbE7pRsve5iudOMBlIDU71GM7yDxjNTv0Y1XVFQEhbTGTqU6+7en2/vzpPHxwu/3KShib/ZsTh94/vYGzllvO6w76M6LqKAFAFf8ywj/x1DgjznxzoMymfR7umjv5+KRbXkpjFnz8vSCCgZe9N8N+6QNOJZSaOvVq+LjXLn5wUy9Ii4NfNLyj8APq8EHaOHXrfsR4n6Ydf/HXwcUqF0d39cf3gm31Tl7WCJM1OLX9Vq/AYu7HF//DooAvL6JiTw1r4FLL4cuBTphxcfGnbY131VJNAJmP7PfqOu+n2bZF7g0zjnJ5vh6Hb1jLmbTCLWB75N2wuwQ6vk8EopfxA9Y8eVTegkwzgOpf/E5wwF+tO9es+Z3Q8yPSsxxDXteMT8BCWhubhnBmFmasGDZvTdWFlR158BJtx9sWezdrKp4IMlOEtFYnB/8wYsznPBvj6gvKcptDZxz2U3Tnlyvsc+bvacCfABget2S6bf5CUW232Nmv584JNZ/CoaSl5QUv0dicSubPx+764T10kPA5y/u+6375TxRhGuoCTpSvTm69fCZ0bXXAA1w48WVmxlnYoRaaCpsQvzrRKPpbjUVOOGNeFNz4YBL6bzaJOn+f0bp1Cfmh0fuIfhf24Qqvn21SBVEfkUX0K6kgvt0EV8fKWMPNLuFIygoAiCB72+CicAHyuc6YQBOwJP7kjrX93saXCKmCJj7jO78u/H5QkJxJDBSv/g5Oipfo145lIsMvEwqhzU/TzEfm2egKhDlv+dmxmhv7ziYAFBmblm4cPZBBfnvRx037yrGwYOxSEasvjhODiVNF5w0rXL2bOJkQnuAj/M3cuK8ZwjAl/X1pHl1lEbpLCRFFCgh/1j9yvSzCwE+jv3m/zScQQAq4omij41kcRPq+ZBOgyy5xbm3iaa3FJdX3C/ycf3s/fTQui+CeRDSzc2AIbwdKfAAH59v5oUiGaJIjw33iKvOonNNTipgRzdWOaDPEuev30NwaAR+FTzo76yrrnXaFZYlOKXi1jpntPU1HcAq6k4XseW1tFgCTVoR7+maECQjcAigce6yvwR1fAQ+J2yuVIX0yDKbkURGOLo3C7ObOHPuz3PwGFZJ/aJHG0f7ffd4ZdkSG0i608vtobwcEPjhnXGzW/MLEfOxSWZnqqO31dE5ghrQ+PcfVz5RKFZGHTf/Ec65B2P+uBp/AJ4gDIQvWvPKDI8NLgj84+b//F/VcX6qHirQhtcHfe3GzUPiB/VdvPjEQCO/bC/4jZ9vO8o0YUyyiG4tL6v4LJdbLx/rvlN5NyGr7+rBPDKE12/kk1xfj91XXB+Bj1Z9j8M8RMxUy1bPrpMcVcbNhKXJeoEUAjLDBj4ODClwdtoVzBL30A1gCvD2CvACX4FPgd3m8R5wa5F6eoivjTxhoRd/hwP/6EvZNGCucU9RDqleuMvNBbIGeI8hz5WglJqiEymv8VK9F6lftNQYHabb9+kDkOpA4PtDdFtJGZTZuffhQTvYVVLq9+GdcXVrfpiYr9x4La3N+2bSmf6UwvsP/qyqoF55kya9GNuQeR9De0U2potPd42p9aTb6MSXJmR23ZLpnhUUAP6BE/7wZYuYz3it0NHQ9QQIUGPi6leuWloIJZv6wx0VqZL0OcSgZu9E+UqGwU6iln6CmwZwgyHnl269QCNNrfIuBvT4g3nyMfIprp9Ih4v7My7gmxmoAB4bMPbk6PqwLqKrD6DmwbPIPRzV9nV59HTNsEVg6m9fNhaI+nxq0z7fKd9Bjq/H16v03LB8dm/EoMPN5QXsfHYv8VGSi5AQdA8E6maWce6K+zSOb9fIr/mcTTO4FPU9Ybc2gdK9HuHqhxtV6J2/iHx+TSUBIPXPLDVG67o9XkNy+yYC0BvSCRAGvUxnS5bce79Rzw3aQc8uGvZk0I63JXZonzwzLQgGTQFtSrccyS0WS7YnHnngf/sUVGqretL8iWDyV/wcPoc3TzCeWCx2yocvffdZD8Hwg3TSpLuL6s32RsxIc2mxG02VLaCHEHJj3ZLC/Pl4j8k31k8mnFYkikrrkiVl26LF/aQM3xVqAC7HTrSo2uW4wpJ2iiPr7eshvFGuPXy266bAJo6x+n6R1waM0lGzEgGfAU/Nq04gdN+065unU3/7MixQ38hPAE5Bjm8/mD+CUHFHda/Ac0bo8EpK0ZizFNn190ciYNrAtwGP98HCmRcfza4iFpvrpCrbD+CK7/LJdNHdUUE8yUA2kbVfXhomNYOez81n6/n1/3ym6cBKqIRUUl4se4mt1i747t2kHCQCGJLrBu2kBEFArs8MIvYjt0cxP9XeWpVOd1YbhDU8+NMBkanWUUxz1MR5v2Cc/6TQijuEQKq8Il5Z+/iVWLjD2QIcH4+MnDDvGQCZBBAAur/Flk5yCKlds2T62KiHj9o/dfb6wzM0eXQsHt/eq7T3h10V96Ni98N9+tLIp+v6iusni3tzZeG/9ut8E7OJoGPs0lDuB3yAAIRY+KV04HJ2PZ/fEdtRmCZ86v+9bDjA9xOAk+sty7XF2FzewwFdkMm7aem2PkLmgFHb7xXH3cUg9hM4d8VwQ+Tj65VyLx7LriLI8f0qiG2LENJDQM+3Qe5Je7YDhbxNScSsuQZBrQCJtCnUL3/WOBCvhsB3QR/N7b0ltnwhurZRL1tsfr5ifnNb04FmJtM3CWzFfT8b8HahGKmeMA+bjYzNGUnrEwkIpc/VLZkeSOgJBf6o4+Zdzywua6r58+81S7/kWN4WPkYitt+qxVd9VsiLnXVFfUlyiHGRgbWEiktXkKJ4Osy670nayRq7L336eghvZCSfnbgjuX7Qwn/NZL6Jg8zH19WfKMDbuHEWqB0w6Ri6FCd2QBXmzrMr1xDKp37+L1F/YcRkXj2BmV4guOIwPoBjl9BLe+kPGOLC8xgm1UPq6om9sDLMmHxfbdC4h8AHBXxnwvyJSN7iJK404i7rsPfyzLlcnJK8uB6X+lefNQ7Uub0j4ofo9tGRen6jnuu7zxabHx60kya8M5No7WgbBxZAapN17+N3DvZw31xYGTPhjn0yPC1y9vMN2FGx/BTI9auWTv+t/x6hwD9o4h8Oy3BTtO0NDdjRRYZApw76vbpl036f62X8x6f8YtNXLSs2NJ6MfVRS2nt9UNxP8owFwsqP4n6Uka+7XF9Z+JWh7/qL+EYFfE/ASZjo71jV3bfzAtzmwDrH1zi/y5VtaQDoBc/cCQvGjJGSsZ8AzDqWmX4LuMO5bWCEReTp9gidQYRxeA+xswfgPyaHyffVSo6vtilIuMeyqxiTVn3vsyhO74JVz/1XhTrcdGdbCrCVApUXoaZOn1e5TsX4+hXPSeD7RXzo1QtrLHh0+53F7f1ifntb29BMqvMAw+DrF/60X84MWD82qifedh1n1u/Cge/yZpcUqtkHzG05dNXLMwOdeEOBjwk71RPmbQTABMcwWqHYRrAOP3BYVrdsxoRCgT/5pm2jIQ0nGwRaepeXvxFWnEOP3ff49EONfD3D9b9/Id+ojHvuAnOzzvycXy12pXsr4umK8+7cuVzNdcnJ820uRuCC5+50RX1FABQRmHGsJeIU5RaeBRgFFN37oAPUHa+Ij5Y4o6QTQsDikuMj2NX2wQdAjryQXcWAz9GrFblRBFoOflQ6sO5atC/sGBk9UpdPihBSCal/5RVDVH32GPR6gNtHGfUCvntfbD7q+Tuam46yGJSTIvrsQzdUrSoUGyMnzFtGOMjuR77y9wF0aoyYANSvXjojNGU+FPh4sVHHzvszB7jMf+GcNwbKDSM25MNXrkTCkfc2ZQE32HtbrgBGEqWVZcuNWHFrdBFO18jnzdiTkXz5cn18OD2M1+/XR65/+Zk2x9fEXpWXoyLidAu2E0mnos8cKcAHJO0DCZ3Xub4WYEPoBc/d6Rr31GQqAtB/vGXqZbHUcXkpFxhed5irsngNbt5KO0Kk1ICmxipCRiA2ud0W9RHw6t6HXYiiPpvjFtq031uhV/dgaHOjaQWKeztivL+egZx36SJVmqgU90n90iXGmHy4vddvn59ur0fqeTPxvEY9jNBjFAga9ajZUbZ9R/N4A0iaHvzSnQvPO6+gMtqHTvrj0M50ei0HForVbAE8hJC/1C2dEcCwXB0R28hjbzsDuPXPbBQl7FRcIJQa165eOu2WvFFvD5wye8tpzOJjaNL4tLJX39VhRr6e5vrZSnPhY101hdfLtFy3UYVc/PKhvZlivvxzR46Wpryg2K3p5Jqur65pZfiFL35qx+q/FJzNSZdbmaDdIRhXHxDhPVZ19R7u9V2d2SVWCvAuUTEmv3lvsHALAp8j8O1cBqmTunPlnK+8EVoomDekVzPc+bP6/M9vr2Istrn4GeMg5bPHuwb99nqUXhvxZuGF6/Zd4fbKd9/QvH2U2cn3hRj/8JHZ/Z8uFBOjJsy7hjF+szovl46vW+MNSr+6aoksvBHAcdSDYMntzPrNWwmBXmr9qgXvCRDwmRnt3N936pbOOKzQl/zajzcMo5R+g3KS6V1RtpjH4xndyAdpWZFH6vpRrr18uL5bkw+f0V+hRzf0fffrvN7x42sypwdMfi6mRdMFRV5b9/UsfK+YLuaNEDAz/MK/LZKi/uBqGyEaATjhW1Ym+BzOEnFTaO1dXq7tutSyETIlpju1B9S7AUx+817D1VdPkDc5bAiK+myOWqC6Lu4SKS0FWLYXcwyRAcknS6VdSXh1wiWBn49BD89yS2u1u8U2Iiz5ittnc+FBIgkxC4jk9mlCMpl4U1P7JMatOGPswX/8z5CCcu/xGauPnb+Sc3aEMtY5oZTK9qFJPXLZOGnzzSN679//qae+Epr2G8nx8SKjJsy7HzPEPNl6fqu+5vLTgR6LkZoPX5mxslDwn/vjzRcBZYOSydIPe/Uq/ziYsZfFyJdT13f9+jKaT0/ZDbr30NA388LyDWjcU+BQnNsVhTWdXVP4PdF0thtNLlQl1msEQAs7lWPkx2OWceHfFnlFfYcAAMDxI1jGjdXXw2l9fncdHFrIsHwnn81BJxLac7vEQT4/obHJb651OX59nZQeTz2RfReAz3Hdkt750Y14nnoEWiViD6A9c6okJ9fN7CVmpP7t142DZIReeGiu36BXAqWiuo4sptlBSoqL7Sg9ackP4/ZRLjzdqIcFNzAhJ9XRciBAbOPD/zPg3kKxMGb87UdkwCwYQzbjuH/NshmisGbYlhX4IyfMPxcYe0g/MVeTPkcAIGRu3bIZswp92ck/WTfS5MnJ1GCp8vKy541k3PRH8qFhz7Xwy/j9nLp+vDg0ZTeQuedz702/gK1HY3UU4P3iqTdd1xtOq8RcT0adzvkFRlxR3bLggr8vMqK8efDN01n9v6rdVCmg6BZ6fZ8OJPU9/KqK8q2LyDonLNuXt28/H14jzY1Jz70Ay/zf9+TjrSmE8vv14iTO/bXzlavRoTsh4cF+AqBIiIgitDuEeKIDOX/39VfiJwjQQy/AtFs3EScYrCNbY2lRejm4PTMJcXX7lFNeSxj4VF09O1LPSmVibc1tJzPGE5RkHnrol8PWFIqF0RPmzWOMT9fPc+bA3hnl1yeEnL162YxA3wN1razArznrjpLWbektDGQ5LvUh3AgqW9kNSeAnhG6PDe0/GLt2FPrC5/5067ctZvUvKU68W9Sr4uOCXHs213dr8rnJO3oMvz+oB58xTOS/+utlS4Dw0boLLAged2ZcXT5owXYt7zhez5KzuajH0k3AsuiEP/wF3sDRFYO0sF37Ac471XoQCJzjGOHsD+OK/27upBhjP6ZXPJYHPPtsCuLp1mF/asGxCWna1G7s99ZyaPV/26PHwvBeZdYHhEBcPz+fCEdPspBuwfcnDqm16NgOpITDOL9z5ZL4D8Pi8ZXPHk+VIn7QoOeNyZeltVy/vQzPzYfbi4Sc5sYRne2dhwKlWx755UAnDz5fLIgI2nRbPWeswrFgimXjlnsLA6RM0iQtg5Ol/Rcvvqwz6n5ZgY8nVY+few/n/GJlB8xxX2+kHyEX1y2bUbCIM/nnGw+y0nAuhVh7Re9ei8Li97Nxfb00lydlN14cCOoJJvB4Rf4LzoHvxw3rh+FVaYP6uuRgaqW6VWScGHVfPr8SdxUxdY3fpG5tAz3yk9WQwe/w/gfyE+oE4IyTYHhJnD3DONtPj8rz+9C9Uom3dqCoWOWYxzUJxc/18blxHKWdlsm//exL3ohC7F+Pz3fQGIDRh7EZlPD/45wbHgInCIpXJRG0SAOwuq1utFTtv1wvii/hR1ojP2jYGD9z1fvNTdl99loiTqARZvYKO/lye4zLb2xqPpUxVmIY7OGHfjEosg1aFDBHT5w7lVlwf74cXhFusY4IySrmS7aTYxs1Yf6JnLEXFMXOaVXUoI894euWzzg01z38xzGO4JyfbJoOBPomk8nakt4Vn4Rx/XALv2y15absemP4g1xfGvqUyK9b+TGcd/A+5bFTJrBfxg24DB0WeoCJy93dqQyAzF7ZrqoaVXVXfgrBJTl5y2TWZY8//vmHfQceoGm5LgFQROD4w6C4sq91VixGqi2AuJNwrXW8dttRuzPtjrObY1MKsp6PPBH3UvGv3IfHCKXrUhn63EuvgIjMVGBXgNe/44gxcCCNZSYRiwxUVxXHqWrDDWChMcP3cBbDptxuF0c8zC10ZbltHcU+e+1yBmlm8lVrP40/vWV9s5UL9GjFVyK+Uz03AySYgSdj8p3UW+Gfx6/vy7k3U4G4/PbWxv1T7aka4LD9kV8OnF9oZSp8/ZHj5y4DzseHBM17rGrheKQn1y2fIbpfR205gY8gHDV+7iccyL5hF4nSMdRqjRnkjA+XzniyUPBP/umWIyzLOocYsebKXr2e9nP9MAt/VDSfm7mnB/UUcwzjzVfkrz6wvOiQQeaIBI/FqQEcnbHY8ku8lyn+AwtMoEaMY+aQEYtx3GuI3/Lt8fmcnGXk4yaAIUp8AJ4iHAAdDNYvfg42eefrI/ATADyupABFBAqd466MzwZ2vN72TR8RgAMCl24pl0xGLaImu489DAVQPe1Vl1tZF38r0YtmqlRbvEZUAg6CHrPuwvR6McchIn5Wg55WT88r4rt+e8eSr2XhNTQ3n8ZMVh6LkUcf+kX/Nwud5zET543LmEz0xvMDP4g3veISjqafrV4+ff9cxCYn8PHW1cfMxRys0Cq6uQJ6gJCX1iyfOanQlxdc/6dbrrNYpqK4rHxZaVmvzxTX13vsBVJ27Rh+N3MvxL0XKfJLK79YXL4mHN5YfoCw3H08D6v2JEsrOdgNOXBfSTlw2Az4HxT3cnX10grggKZDAOhdAVxPcChvCer0AKKTeSgR8BMCNd9htoF8voUOcDUexfiwTYIdt2jAK9CHAR6PeUEviYS/dl4U6HF/vnq9a8XXffYdxJ+IE3TfyXr5ntRbLUpPZeG1tTbvm2ptO5YSY8fDv+z/u1wADJvP6mPmYkn1b+CxXPgK9Moj5L/rls/4ea5vnBfwR0+6fV+rw/xEK5TsXDdbyx5JrzAclY+rWz4LS3cXtJ3z083jmWl9lRDa3Keq4p8kBk5pLm9L7WR4DH8ehj6Zs+/W4Y8S+TGqrzvgxz58Je39RDmfbODHCcqXAGQjAmqidamgkMmPArm6hgv2/ACPo3KBXjXC6BbotTx713UnA3WkiI+uu3ZZQDMg4udr0JMWfXTfuVF6acJNMJq2N51hcdbLMMjjj/xiQMF97zEhx7RSH2MavcKPVt4upFeepxQeSyTovu+9PD1nvEBewMcHqB4/91nO+cmBxeO3PvgGyEQz8tCaV2d+vZCFh2OnTFlgpEaecB1nrG9Rwnizsqrfu1HRfG7mnte9pxv6cov82fX9HgF/eT/B/Zs1zo/v6uf++REANaNSEsiHEBT6DfIFuhqnRHr1G0X7KMDjGLeltRTtdy7o3UCdfEV8v0HPycDzcXv02zc0bj0knbKO4EC3J9e89PuFCwsLzxU4O2bebwH49/TUY883y6pbk0VrVszMq8x93sAffcz8sxhYj/l9xf6FFGH8YwaPj/5wxXcL9mVOnv3paLOj6HKg3Kzq0+cRVixj+L11+bxBPW4Cj27oc0V+pzCnI/JLfd8t0+UX+cOCewBUkU49fx/nQ/Xgc8R+p/suHt0KJTb4s3F/HInif2EEIEgI9O8TZifQj3u5uH4kKML7v7sO+IAej4M1XR5/hunzAvR2PfzsOr2dX98JBAtR+bPuxDeIS3VB6fVCxMcgHeT4TqBO0IqPIn6UQU8vq+XPwKMdHWXbmnecAyaJxYo7//TQ7P0KTsapnnRHFUllPmWMlbktsrxp79mM64TSc+uWz3gkH+KeN/CxAu/9T8+tI0BGqFRdvIE/bTeKIAGQO+tWzLwyn4fyjznrhi2XEmYdTClZN2DggGc9ZbiNhCjP5br3ZCivx9DnEfldKz8AttbWA3tKBAHQo/rwWXR931ukMzf48fy2Ultfz0Pvx/E6948iALg/3A7QlRnu2jlh3B2v5HD4EMAHQe/V58X7t7nepqAhLxsQCYSGAAAgAElEQVTo3SCdAOh1Ed+O0kO93q2j15nDZy8Nem6wTlq0xcLzUdzfsnXryVbaHM6N2LuP39T/L12Z0ZHHzPlf4PCDbOdmwdcnU0+fMVKvpJvrOnk/46hxc69mwD3JN7ms+m4kH6QSvHj4eyu+g4yuoO3s2Y19WGfnDZxb8ZJeJc+UlFd8ns29J2vz5RL5g4E9St/vGvijDX74smFGv2zcP4wAZCMCu4IQ+IGO9wzl7nkBPrtoLwhuSPks3I+GvCCnzxP0IXq9E5arWfF1Ed9v0Avk27c0Dm9raT+VgpGmRUU3PTq7YkdBCxxF/El3VEFHCs07pW6Qsz8yP4tzj8DVa16dNSff++bN8fGC48bN6dVIYD1nvFzllweA70sa0CN6CCX/W7d85o/yfTh93Dn/teHLJiVnAkBLvz69FvISN4HHNfRFi/xhVn4p8ksXn/LvqwKdsURJFzh/EPz4DmGiv2v1d0V/HOsX/x0CgH/YHgA1L0oVwN+5Sh7lKx2EgVv/DrpP18PZbbDjP8o9p85zxHrcEeKqEyBvayBYK08HvAB5OxB/tl1hoPeG5Lr++g5PKyyPFd/ns/eL+LpBj7Rn4tt3NE9hDMpjwP/5yP8N8RS1zHetjzpm7q855/8VUKXzAhg0xUuMoR8snh6IpIy6f0HAx4uMGjfvVg5slhtZ5bPuZSvVRaAjZiRHf7D0yoI6iOB9UdVYmdp4AzOtgfHiktr+VZUrPIa+PEV+Gdjj1/ej/PteY59YlJqbT4n9fmu/as6B4/UGHfhb1/t1l5/O/aMIQDYigMd0QpAPMci1KP2BGwGgZwE7HooCPB5Trroo0CPg8ZjKtBNEQC+o4Vjv/Zxet+BHG/P0/neuXh8Wlhsu4qu02y1bGsZZmc4aSsmmw5ODbspX1Nbn/uBxfxyQ5h1oyS/NlQvjDY21o5gI/V3dqzO+n+t76scLBr5wN2RSHwGBeNiNgqW6vCSLACyoe22W8FEWuk3+yZaRqZR5LSY99qns/bd4SfmOKN++buXPpu97inb4jH0yuKcw8API5hzZwN8TBCAXEdDn1k8Qcs17KMD1k4bKH37OroZ0BfCCAGiivQ76QNJNl0Hv99dn0+ulyy7Kio/x+Jn2lj47GpumAiM0mUzc/NAv+xdsvMb3rB43527gcCn+ndNv7y91h0WnY0UjCmWmBQNfPujcOzlndufNALC1KO/gi6BfnxowadXyWSGlJXItSYCzf7ThcsviR1PD2FBVWfmwiOgzEpwy4GEiv1OLP5Z0MviUi8+fyKOMfU7/PSeyrwDwF5U7nXkQ/H6LP75hdtFfzYGtAuBPO/hHgMHnBtRnTBgF1eZTC3LPbMQIG+TZgI7HEOz4r6jVZhdsU9F36sq5uDyOC1TGtdNrnYi8boJeGvM0f31Ar3cDdbKJ+BiPv62h4VzT5INpjL/++K+G/Kkrczz62HnjmcmXcqeZuFeCzllOm/C716y4+luF3rtLwB919Nz9gPA6ziEW4PB+ncT3RHZAzzuH7TPoyK74Ob/6X1vLOem4kXOjLJEseq1fv8plfpHfDed1A3uEi0+L6gv696Wxr3Dwe119Quz3gN/V+3Eq/KI/7osW//HoVjGDygVo0wGxLxsRiCQIeayQKE7uP9UDdhvwEuy4SZ88blGAx2N+Lu/V52VOfRD0ksi4Lrtc4r3k9Ar0fmOeW1wj5cTiS9BLri/DcqUVX4n4W7duOzbdmR5HwGoxO1Ozn5o7sjmPqfUMEZ6yJ+a+QQgc4dZV8GXfOWxUy2SyMYa1WngiPmrNkmmfFHrvLgEfbzJq3Nw/c84v84smOSmUbb0ghEyvWzGzoCab6uUm/3TjQR0d5rUEDCgtiz1cWtkvNJw32sWX1JpxSH1fBvfkC34Ab2ivDX4AwCQfsdhFTz78yxX9s3H/MAKA+4rKqrQkHa8UoOZDuUnyJQSFLhI1PgB0G+z4Tyh3xwNVolyAx3inAx7/DuXyaMGzffQ4Bptbin9TftDb/no7t14l3ui++jDQ+415YbH4wnUXFpbbsHXftnbzXJRni8rozQ/9rPDsO3yX6nFzp3HG5uvfI9iyzvu1PIyWkD+veW3W5V35nl0G/kHj5x+QtqxVIFIvC98IgYa4UTry/eXfbij8bIAzfrh+CljwFSCkvW/finuMYqMVRX5/YA/G8kt9P9y/rxv78gW/COu1q/fgs6uMPtWdx2/0c8Efzv0F90q5YrpHAsCDmv/fnStNEsCdmpM0yl+aizAoYPu/h6fUskeMx5EuZxcEr3UbUWDPB/A4JsDl9SIaPtFeheHieSo4R9TNS4cZ8sI5fS5jnq7Xe113aWI1W2WNzY2XMM5LCDGe+Of/Dfp/XVm/wn3XnqrDTOtscTGBaytuT8EknFavfm3mp125f5eBjzcbedStfwZfJd6ApO8zU+oUiwDcVvf61Z4KI/m+xOzZs+kbbd+6gXE6khp07aABff/uluROePR9byKPFP9TqRTWHOexWJGdwlsY5y8I/EL0V8E++Iau7o+/lPgfRgDEPkz6UVsoEcCDkhDgJtQCfSs0csJXVN0V34NAjwI77lfuOUEAbMMd/q0s9hLwMiBH7Lf981H6/M4FvRTznRbXdrqtcN3ZmXd4bOPm7d9kFtvHoFBXU3LXr2bPnh2W9ZxzGVcffetdnEOAW+eMi7GNe5SQu1a/Nsu2s+W8XSj9KPws+4zDxt8+pN3M1BHgJd6VluclCbEMgxyxanmw4H8+V8DAnkxbx03ArF6JosSS/gP6v+zq+7LpptT3Xf9+aHBPF8Cv+/lVYo9Y4LaoL9pzaaK/cvnp3D/K+OcnAPg7IAXgzm3bxDR51QF95lxikM98Bsd4ubk6Lrg6brYYr/brvnhnnwZ4Bfog4L2lsnBctGiv9Pk2IjPtus7p/UE6ujFPT7d1XHebtxyf7kxPBGo0x0uLb+hKoA6+28hj5o0Diy0XJTPyrGHp+TaEdMbjyVGFWvL1a3SL4+OFRo2b8wvGsJmf3AqtGAJAFq95fdaJXVuYAGdfv/7wNOfX4/mlJaUPlFVVfOpx8QnxX1Xnldw+1NJfAPjDIvx08GcV/W3uHyX+43tESQBqjpAICOKgSwIaIVDjoglCfrPtAFwNDwE6HtI5exjgFYfHY2FiPery+XF5P+jdTLt8dHoZgy999RL0fgt+uDEPXXet2xr3a29ruwBrJiQM8ptHfzNUdJoqdEOD3t+enLuCcR7eYzIHgCTO6K/qXp95Q6H37lngT/hTOc+0fcQZ7x8K/TwiEigh01a/Puv2rr7IWT+on2qa7KuUkrb+FRV3QllxS5h/Xxr7gpZ+VaizELHfC34AWcXHNfoFwO/n/gECIMV/vAY27PQTAAF0zQ7gJwKhhMA/obaEEDnPPmD7xyFHV/tygR3H6SI9/lZivfLL64DH4y6Xl0E5ftEex2BqbQn+q8XedxX0qpqOsuBHGfOgtaN8S2Mj9iYujcXpY4//evADXV2rI4+ecyVw/getg4qH5+cBl800UTZy9dLLW7r6DHhetzk+XmTUUXOwbZK00GcP5As8q9D5KemIceOoD16fUXBtMrwgUtHXWjbeyJk1mtLYxqqq4ntoaXFHmLGvJ8DvCe9NlNhVfFDbkUa/MNHfb/jD53Zdf7r+j0eibQBqAsOIgD65Sipwxvulg4hVo4Mbh4QBXD9V193V/igdXhADnx4vAO8z4Aki5mTXuVzea8Tz59TnZ8hTnD4K9H5jHmvrKN62reMSi1sDUa8/qmzIz7oSnYfvdMjE2/ZPpc03gfNeaq5yBrz5vXsEvlP32tV3dQf0PQb8SZNejG1oe/st4HBQ8IFyaTHyOAH67oh+cNRTT80KbQCQ60Wn/KChd7vVfpNlsYGJOP2s/+Ah91g0bYYF9/jdfMrHnx/nB/DG9gPIEl7yX5XZFy76u24/Zfl3CEC63DaTKPefSwDwrygpQJ+XXMQg1xzmOh4G8jCw4z6v0U7q8ALkdslrHfDib9tN5+XyQdEeSiS3x3P0Qhr42++n91vvg6DXwnF1Y57dEMNgidim+g2XmBm2byxGNhbT0h8v/HVlU655Cjtec8Ud8ZY3U8s4Z2PdVBsFwWxpOe7VCJB3pp4564iuEh79uXqE4+MFRx4173jgbDEBTrK/RrQSQ4DOrXtjZsG1+NULfWXapwNZkfErAqRPLG58MHDAoAfMWFoE5tBY0NKvu/nyAX8sXsQ9iT3ov+6Qqb1K9Md/Mcw3jPuHif8BAhBiA5DvF1QFxOIvCSvRFVx6+RKFbODWr+rX2/1gx9+RIr3N4SXgw8T6EC4PJaAq5yjRHs83M5gaqxJuZAgulsXOB/R+t53Xgp8gmzZvnJpOmWMMg+6AjsyPnrxtP18txPxJQPXYOb/jwK/LZQXLxiYppSetfm3mC/nfNXpkjwEfb1Fdc8vdQMilWfP1fbHGgdhkTs9cUzvria6+3Bk/3Lw/S6du4pyXxGLx14YMG/SwbunXw3r9Pv5s4JfhvUUik0+B3x/lJ8Bvi/5eq7+r+wuA2PYAR/zHnS12xJ9PBUAjoAC4iP9Xm0sEcI+SBvQ5y5cg5JpnHeBqLBro1KZzdhfs+JcMwFFGOwHyEMDjfiXWCyDbnB/r3nut9lK0D+rzepadDXynmIbXkOeK9ylPDL5TQstMO5F5G9ZtPNcyzaM5hTYjnvzxE/87oODoODVHBx495wzT4o8LK37O9R/emooQcm/dG1dfnOt75Xu8Z4GPQQmtHas5kErHeJHTWuF9VELo1hgxDv3g9eldpq5f/f66Q1OmdSMBIx6PG89XDRu0yDX2eTl/drFfRvh5Y/sV+AH0EF/U+9vtwh5K9M+P++P7t0I8WSaB7SMAuEuGAONfYUQA90vpUxkHo4hBvotCHxcEOR6Vfne1Sc7uBTv+wmq32QAfJdY7ujzK9bZoLwCPObXFyOVdfb5Ycf2YnXBjx96LMFwz5VjvddA7BTV8vnpVMLNh3cZTU+nMSUDATMTozx777bB3ujJ3eE71+NuHQDr1FidEhjDmKGEVVmGHUrqds+Toutorpf+2B7YeBT4+z6ixt1zOgdwVWTPM99ChL0roM6ten3laVyqUqsufcf3a46w0/wEHbiSKix6pGjxgSXbw664+PcgnHPwqyg+5vpPT7xf9PdzftfxH6f9+AoDvIkBvSwHObycqPIoQ4MhwVVQnDvqnkJw7bPOCHEd4gG7jXXBzP9jFDhv8tkiPu8IAj/tdi73yzXu5vBhji/ZIATDZRor24aB3w3DtGHw7/l5Z7/2cHt12jZs3T2xvTZ9NsZZmgv/6id/s80pXcYY1I9/+tP4FzuH4qGvk7lMhCtZeWld79T1dfY6w83oc+KIO/9g5L3Hgx+ENs/XvDn8gWTXUAPr9VbWzftedlz3ruvVnphmbgRcsKy25v9fAviu7Bf6Ar18a+vyiv879dd3fL/7rBECAOgPcraTglQJ0IhAgBLjDRwxwl1c9KHwmXYDb6Nb+8QMdD6l9ucAuAJySerwEvCbW+3X5AJd3RXs816/PK07fJdBv3FjT0W5O5YTTZNyY+/hvhgbaxBcyi9U1t9wIQH6WrUqu/3qBctnAX6irveakQu6bz9geBz7e9OCaOSPSnL2NhQX8hQPyjfAhHNJgwMS61695PZ8XiRpz2vfWX8Iy1oVAGC8uSj5UOWTQKwWDHy8eEuKr9H5vjL9t9cdzOgDSWN0H/fu25V/ZAVzrPx5tg1hSVFwSm58AiH2aKuAnAjohCBwrOGfMfgjH4aQBWuPo6lnDwY5Hka97uXsuwIdZ7MU5WC4rYLWP1ueTOFbUw8uf0zds3HhcZ3tqMhADBc37nr55eLc47OixcydZzHoe3VW+PPX8jfpYuCZGDvtwxdVdyvPPhpudAny84aiaW7/Lgd+es5SQ/+k0oz8hZBONJ8avevWqXJWlstKG065bfynLWBdhF6ZEPPF0v30GPpEf+JUeL1N6FfgFkE1ZtBP/Vtl9utVfGf7wuMfyL8R/sVcYArMRgCARwD2aJKDeukXGcii1IGwyMGYgn03p5WFj/SB3wK+J8WFgzw/wYWK90uWDVnt7bogpxHwAPRpP6fOCWOQh3m9du+mMdCotylLTuHHv078f2qVimWo+Dh53y4CMSVZy4IO7tf4pzKx745p5+Xy3QsfsNODjg4ysueVp4HCq/lBBW5+3fHBIy6APkyWJCe8umdZY6Mvp47/y/Q1fs1KZqznWAYnFllQN6vf3ZEnCwmw+v6tPLABfVp8I840l7eQeW+/XRH8/91e6v0MANOOfa/3XCQD+rQKA7L81KSCKCIj9ShrwT5BNEPTdUcTBAbU+2NbP/ZeVLjgFcfcvFXmnxvvFeRQAZdSdBLnk8BrgQ8T6MF1ed9V5RXs9n9613EsCIHvcKZcdGvJS7Wlj26at51vpzASCOn0yfuuTvx0S2Vo6n/U3ZtL8skxzZjEA1ISNz3v9E7Ko7o2rT++OnSvb8+5U4IsknlTqPUKgT2SNvoAu4H1c+wFfHjGAntLV4B51xVOv++xEYpGfWBxiBqVvDx424E88zjMqwk+05nJi+5NcB79K7lGZfYI42Nl90CnCTTXur3R/JTHgaNvfXzABiCYCeCS8uqK7N5Io5FjFLri9AFenSUHeDbMNAzvuQ/29UMALoBpAlMVe/BYtq4UaRKAIew3arjr0ZiQxb14X7b3uOn8hDctKE5Ih8fp1my+3GDuMcDBJnP9y0e/3fTEfcEeNqam5I94Knf9knJ8i21WHGfFzZbNgs2Wy3YCiQz6svXJjd55ntwEfbzxy7M3nAyMPRLn3csX1qYAHAvD31bVXT+0uBTzz+g1HpjutX3HOSmmMrhk4YOA8Wsqd8F4/+PUQXwV+r78/O/f3iv9RBAD3qxgA92+hEXikgHAioD6wKgISTRAKX0YK4GEg7yrYBUEIcc9JwPvF+qAuH+6qC9fnw0DP2kjxpk1bpjOWGUWAtsYJ3PDEnOG1hc+OewYatatrbrkXgFzguOzCkJ+tGK0d8W4YdPKq12c93J3nyXXuTuX46ubVR956BwC/QsyDPz7BrwT5ZSH9DEJ+vab2mh/meqlcx7/yo63VVnv77y2LV9KYsb5v/943F5Ulm1zOH+brR4C7BT3wHn7uj/tQ9+/EYJ94kYgBwKAfEQugRf3J5wuTAIIEQFxT2AIk6MVvkQ+gNnufTy3INQddPS7Fd9ykRR43ydXlPleUx99ecV6M7QrgoQg8urzG5fGaKB2gKI+6PZbLinbXpUlna6r39i1N14LFhnKAhnhZyXVP/qofFsTo1lZdM+e3nLPv+S+Sk7EF1j+9e83KwmvoFfrwuwT4kybdXVTf1LScAz88MDH+SCZM2rH3hb0MBXrV6jev/kOhL+of/+UZawcDgbnAraGE0qbi0sSdlYMGfhBm9MNzUb8PE/2juH+Y+J+VAOBNPGoA7tClAPe3JAK4hREC7zH1S/caZJs7F9hqlAtwtUcHug1vV2+3dzh6vA/sCvwiEieEw4t9IWJ9di7vE+3R2OfT59FH37Bx05iOtvQVnLHeQIz1/+pfP/PZefvUd3ctVdfciv0du+R61v34hJB3y6DomNraK91P3N2Hizh/lwAf742lujJps5Yz1ssL7Jw00fvolFoA5GvdCetVFzz18nWVvMT6DWPkEKQ1iUT8saqhgx6NJ4Gh0Q+37KK/q8ML7o8nCLdfmPivrP84SEkAITaAUAKgEQH5p/qfDBF2fgVB75UO8l9FLrjxHBf8yNEFeIVRzka5vVMHuwK4irYLAl7p8FKU1wEfZrzDBBvlppMEw3bx+az2HtEeByYSmABEt63feHY6k/oaB4r+tXdJu3H9oj8N61LZN30WR9fcOtVi/D7ZFjqo1OcO0LHXP6HNsTiM3Rmuu7CvvsuAjzcfVXPLFMb4gmzLL5+AHwLQFoslDuhOWK96BkzpXd60diZL84sYADEM+LCyf+Vtxb2SO3SjH5IBanGOnF8QBM3qr+v+yvIviYY0aep5/vhbuv9wcwmA6wXA/Srxx5UCxHVEMpDabGkAfzr8wWUUiiDoc52LjShQ6+e4ALdBrv0TBnR5WIbWBsEu3XPSaJcL8LaLzhHrlcXeFeVVko0gBI7VHs+T1XDRiJdpTvXZsqVhGrPgQDH3CfLX8b33mdsTGW4HHjXnZMtiTwKHOAbpdGcjFM6pq7320e5co5BzdynwBfiPvPk3nJPv5ztRYYSAEuPa1StneXr4FfLSYWPPnPX5xA4Lfg7AKoEYTeW9SudXDCx7L6D3a1Z/ZfhTun+Y8S8bAXBtAK4XwEsAfERA/hQ5AUFC4FKAAOhzId4/IT4K4OHu2lgZM+8Fuh/sApSGDnibU9thtuK4llSDv4VPHje7So70y7uA9+vyyOWZlfa46hD0jZuaDm5r7pzOmNULCGmMG+RnT88ZvqS7awXPH10z9xBmmUs5gXJPgI7v4vkwMqA9Y7sq5L12OfBFSO+Rtz7IOZ8iHrQgSZ+gpHbVmpXX3FHIS+Y79vQfbexntqV/wyx2JAptiQR9tGrwPguTJWCJawifPzbuCOP+0tiHw2Tyjm38wz808V8ANlbEdRuATgD8UoC8nuL0IYCXu7IQg7C391OCMF7vPc8Dcjxkc3QX6O5OCXT5O8jdXU6vu+bkeDexJkqsx/3MEfOVb97l8mK628HYVr92SjrNzsYVRg26MlaauP6pXw3qbhFCZ1JGYeWpjpYnOeMTnTUcNtU51jeh5PnDRgw+tSs9JvJd11GP1Z3zu3SuMPbt2PEcB5jgv0BkMh8Qi3Byed1bPZus4L+/EP23b5hlssy3cM1QgA/79u/zh+KK4o069wdIg+7zR25PraRTytvl/l4CgPfTVQAkAK4XAI8qT4D8W3oD1CYTgtxnjuL8UjLwb0pSiPpoQkT3byG7FBHQ0a+4uoK/V5TXxHrk7qjT2754HK9zeC/g/WK9xvXtJhdgV8FVon1HY8eghm1N37UYPxCAM4MYdx9bNezWnhDt/VODwTpmU/pJzkHkpeBWSDIqIWRVSW8+/q3F1xbcXbdLwNNO2uUcX9179NHz+vJMZhnjUK0mSx4LDXBgiYqihYkBFde9+ffzu22FzWfSvnrNhgntZubX3IJKoNyMx+L/qBzS/6GS0risEOTj/rhL6v+yrl9Q/McRbuivJADSCIgbugHx32xEQIzzEQJxXw8xwD1e1HttA7nf3gW2GutFv87RvUDHX8pQFwJ21O3tEFuHu+MpmkiPP7OK9Y7F3svl29syyYaNWyab6czXOCMxQsn2knjsh4/dMmRp7jfu+ohDT/lraee2BuT8ERl43vXsGvvo1mQsccy7rxfeBafrT+ueuduAj48w8qib9weTvAqc9Ysq/0cwz6VX8uZYVXEaKG2LxeN/qv3b1B7LS842iedMX9+3FdgNjFlnyHF0S1mvorsqh/R5I4r750sAvEZAjQDYagASAHEtEQ8gSYKMCVCbTTDs416ou7+CRCG/ZeOCW0FbnqdIgOToLtAFYH16uzzq5e464GXEneTi+QBeWez9XL5hw46xbc1t32FA+mEFKEpj/2RAb3p+/tDt+b1t90aNOfOefcxNTS9w0xqR+0rYR552GsC/tOrNa5fnHr9zRuxW4OMrVY+dczS3rBeBi9gPb4wjgY5/hdaec8iIwc99ZLVNZQAjEfw0lrh3V3F+fKTTZ64/JmNasy2wRmCyVczgr/XuX3VnWZ/E1uziP57tlwB0F54d/y+GSUHCIwXYREDCXgUFeYHvJQZypNpQOghbNn4tIESaF6e54PYC3AW5D/hKjLd3Y1itIg6iKAZujltOB7xyzXmDcMR98LwIsb51R7pf05ZtV2QsfrSYOzA+TsSM2U/NHfrqzoFL8KpHfPNvg5mZvoiYVu/OdS1fs0xrjMddHQhIQ8pEzq9bec2Du+oZw+6z24GPDzXq8N9/jXGCIYpUzRMlpJXE+Fmr3rgWEx5gzJQFiaTV9g0BfuDpWJz+rfbBSz/eVZM3ZQE3ml5ad4VpmdM4IcUoiRQlYwsqhw14pKgoLp3+esKPx/ovCYDXBiD3GUItsP/GJCDxZ5AI4G5lFJTw9ksEaibs/R7poOuzJLl4CPBtji84egDockd2sGvAN1UAjndfmLVevHtnJtGwbvM5nSnzPOCQBMLbYzR2W+8Tht258DwiDbG7YKv5xl9GmBl2PgBJUIA1LRvi/6DpbQ9zxk4Syn647fr6NW9d+9td8HhZb7FHAB+fsPqwW2Zw4HOFjk9IkwH0K6veunqZ/vRY0eQj1n424/wwQqllEPZw7cLL3t2Vk3jqNZ8NyqThRs7YKVhXlFCyobgo+UDlvpUvJ2My2w83J+PPJgC4T9kAJAFwwS6O2Z4A+S5BSUBe01UJ8LcgBAIJ8ixFDMT1Irh9oXOFrjZ1jg5y3OdydPylAR1/hnB23O0G3kiQSyu97qrDoBufew5PxGw6M200rG04vrM9fT5jbCjg9BvGolicz150y747LaElbM5qptx9iMXpuZwxgxLy9gG05FG0zI8fv6B4e2f9PzhjX5bnecz6v1jz9rU/K/Qb7Izxewzw8eWqD/s9UsLLqGGcsmrl1aFJE+gOrDnvL6daFhwLhHCD86dWPnzZLhPt1Ec4ZcZHX8pk6I0c+HAKhFNKNsaKkg/2H9zr+URJaUYnALoHwCUAKgjISwC8UoCPCIifbvVxSQg05NsP5xAE9bCu9J/fGrKZuBrsBbgEOW4OR7eBLv5R4rmtt0uw+zi5A3hdxJeAx3bUjg5vAz7d3hbfUt98kplKfcNibLBtD1obj7GfPTPvgB6pOpvfxMhRR5579zEWIacD5xjwtax2waWL9OQx9Fpt2LHjH8DhFMdYTeDWNW9de00h99mZY/co4COoDzziluGr3ro2Z+GNmin3TDQtdgpODqXkpTf/36XP78yJCrv2FY14OqUAAA4mSURBVFe8Ef8k0f9CyzS/CwBDQZYX3pYsSjxYObzPUyWJUs0DkOBIAFQMgE4AXDXATwTs34464D3ukACNGIj5cAhCzyDfA3AfyAWwNQOdH+j6cZ27u/tVXL1AuWhQidwdt/Z0W7Lh8+bTUx2p8wDQAEwBKF9vGLE79k9vue/OO8dmdvU3P+LrfzmJMX4C3jdm0GdqF14SGhAkXNaNjY9wgNMAyJ/r3rrm293NLO3Jd92jgF/oix02+Z4jCGFf4wwoobz27IPXPt7V7qWF3lsfj77/ZQ3rzsukzRmMwf44qRTIjnhxbGFFv/LHyyp6y2wa2wbgEICAGiCBrasCfgIhfvsIgXcMXkHbfEQh7/dMSku7wLl2kgS5d6/k6O4+fUwU2F1xPgj41sam0u1bW86yOswpDLgo5k0ofBJPxOYdWzlswc7wyeeaF+zO/Oh7+5zFGakhFBjn9B9vP3TJm9nOO/30OcmPNlozDx855OZdHaCT633+rYGPLzd2yp9GWZyexxjEKSEf0r6p/1d755W7nBPgs6DEcsqM9WdbVuZqi2FsuEgJaYkl6D/L+pQ93XdQ5eeKAOC/aAfIhwhIcuD+X+ULyI8rj3iJgf7Zu9SYyAd393p+kOMRP9Bxn9LbPccd3V0Du/hTcvjtGxuGt+5oPc1Mm2cyrM4NBAzKPjSM5K3PzBv66O7imNgFx9qWmMIBRlMKGYOwBW8svHx1LnDtycf/7YGPk1sz5Z59LM4v4IwXE0rXJpPGghX3X9jVMpM98r1OmvbpadyEay0uwn9FYJJhxFYbidii3v2Ln+9TUSlLiWnGwOxEQIIcpQEX7lHEYCcC38fxlTSgA70QsO9obKho2tJxkpmxTuGWORqbqWGdZUrom8SA3z9/235P98gH6eJFxl1wX69UyjqPM7YP9ng0CLm/duEla7t4uT3mtC8E8HE2Dz3nr/2pYV7MGelFCbRzgIfeeuiyHq9OWuiX+/KMzyeYGeti4Pw0BqQMq7MQwhk1jOXxZGLRgH2rXknEE44xEK8fJQkIzh7Q323XX4AgeMmD/7nVdVxuHfZmQXFfAhw3XQHQub5ulfdxdpu7pzPp+LbPth3XnkqfCpY1nnFCxbsR0goEno7Fjb8+O2/4To24y+c7Hj757pEEYDLjUEIob2ZW7K/vPHLxlnzO3dPHfGGAL8B/0V9LjTbrXOnrxxxbeGUklL6wJ+hXp89ckzSt2LlmBr7BiDURGImJZqGUtBoGfT5eHH+x/5D+byeK4tIG75MExC4kCmgXED+8InyQIEQDX0kNanG6YPYvVy+4PZxcDU3IMTI7ztkpjXQ20MXjdmaKNq/ferjZmZ5kWewkzniZsM5TblJuLInF4cGYYT781NyRXdVNegxr6DZeA21f4paMwUcfvVVqPPzOvRdLW80XYPtCAR+/B+rZR06+5zhO+Zek0Y+uNUjnwtqFV3apy+nO+MYnfXvzAIh3XGAxNoVb/CBu5ygTAhZQ+m48DiuLipJvVA7r+264NKDIgCQGYnFGEAT/84cTCB/HDntpDeACzxrIBfAV0G2wI1dvWLf9kM7OzFjTZDXc4gcD8Jg6jRDyAaF0AbWK73/+rgGbd8Y8d+WaNVPu6G3xoilStAdGGHlh5UOXvLK77AtdeYd8zvnCAV+99BHn3jWc09gUzngvAryDx42H3n7wkm7XVstnUgsZc8qstQdn0tZFzOKTgLMxDGUA0TacYBWPFDXo20aMvFFUXvJ61dB+H8QJMHF9WyIQoBdGQrUpUuASBf15HALhe0jk2P7ndsHthbof5Hg0w7HKzdYxnS3tRzELahhjh3HGi5Crc2wWCZxRYrxPDHgpnjDufWbOPu8VMk+7Yuxh37inmmSsyRxIMaGkmTBz4ZsPf1saZL9g2xcW+Pidaq54vMTc3nAucFYtvhvhS6tp2XN7gugfto4mXvV5RZLAScw0v8Q4OZZZ+Nwq8kvEK6Aa8LERj9cZCfJRIp5YU9yn+JM+FeVuzwGNIITdw0sk3BEeMIedaFve8dCOxpaKjh0d+6fTHdVWCg5gnI3kFjuAcZIkhBMuO6UDNUgdJXwZjcVeSHF4fsntw7vVG2FnYQ9F+zrWejJwItPECa2L9a18uPbOswotYbKzHrHHr/uFBj7OFor+Y8/76wSLs5OF6E9gnUFLF9QuPG+PEf2jvupJ3/5kAI8Zp3DGTmQWm8g4Hx4KZgIdQKCeUlJPjdgGQsgWoLAjETN2UCO2gybjO2Ix0h6LGWmejGVKE7E0j8eFy5NkMvG2tJkgKTNumlbCNHkJS2X6MMvskzatPsCwJwLvzyxzCGN8MHAYzHhY4r4A+ueU0CUkTl8kKeuZ5+/af48R4aPmuGbKgt4WazuPcxiGor1B6HNvLLh46RdNtPe//xce+OqF0eXHOMeaf70JISnK+fNfPfTz13ZHwE9XyfdZV9RXtYF5JKfW4ZzxQziHAxnj+xPgoiVtoHS5b0+wIaP3SXK1enCPkxZKySeU0A+A8vcIM94qhdjKx+8cvEvSpbs6f/p5GJDz2DvDj2aEnMQ5T1JKmighC78Irrp85uc/BvhC9D/rjhKWSH6NcazOIoToTfEEf/z1v39rXT6TtaeOQRWhLEEOSHdaB3BK9uMWG8QYqSSEV3HO+xDgfTnHBqYkBownOJA4ITwuW5nTDAGe5gQyBEgGgLcRQhsIkEYOrAELWhCDbowx/qlhGB+1cv7Rniqy5/t9jvrmn4dl0uQsDjBQqCQY+JVO/aP28Z1f1jrfZ9zZ4/6jgO9w/8l3jzYBvgIc7HBQXmukMs/+J334nb2w9sTrI+G3kvEvY9it1OVhRwzgydqHLlu1Jz7vznym/0jgC+5/xR1xtq3oBE5hgkythHZCybO1Cy5Z+UXX73bmgtoTry0zOu85kjP+ZRmMQy3CYCmt6nxpd4V37+55+o8FvsP9z3+gykqlzuQA+wsmQGBdnMLjry+8bNPu/jh779/9GThqyt0DMwzOQuOdrd59YiST/9xV5du6/wY75wr/8cB3CAAWVmBwGudQjjG1BPiKPuXwwuK/XFZoNvvO+VJ7r1rQDEy69O6iHS3wJQ5kHObNEwItBoWnd3XhloIeehcO3gt8bbJPn/lkctPGrV/iwMbJqD/SgSLhAUbJqwsXnudGxuzCD7T3VoXNwJQpCxIfWe3HSBUOk7aAEaArBg7q98JTc7+y28OBC3ubnTd6L/BD5hbFwzQTxr99xWFK2wjjS4yq1Gv/qTrhzluCPXNlmTqbPJpTMhEYk83+CHyWoPDkXrUtOMd7gZ9l3WExRcvkX3L1Q9IKlC0Z1NZa+9RTs/Zyj57BbLeugsUuNpaW1QCjEzlg4o+00xgx8sKuLMbarZfYDSfvBX4ek44x3NRkX2IcBouFRaGTA3mjKBl7dXfn/efx+F/IIZgn35kyjyHAx3ImiwBSAvUsRl/YE3My9rSPsBf4BXyRmsl3j2acTGAgQ2fRLUSBvWsQWLZXnCxgIrsxFNUwi8OxDOgh6IYVgAcMFeZL/xP98V2dyr3A78LMjTv3vqGdkJ4AhI5Bi7G8BFlvGFA7Akre3WsI7MKkZjkFDXYfQ/shlgU1AHyonG7CgbMPiiCxdMXDF67v2Tt+8a+2F/jd+MYTp95f0ZpKjwcChytxE5t9UIO+Y1mZle88/J29C7Ib83vouX8cahjxI5nFDsWmFUrNAg5vlSUTy5c8cMEeme3XjVfeZafuBX4PTLWwKDcmDiIWqVFqgFikABjrjsU03lvxt6l7fKZaD0xFty8x7vwHBqQz6YNFEhJApbogivPc4LVGRfr9vZ6Vbk+zbGiwd+u5GThiyp/7ESA1FofDgIF0KwnDE9/GuPFuUTL+wV4i4J1vBHtnKjOGEusQxkmVc5RCm0HgbQ689s2F3+qx3vY997X/fa+0F/g76dth2ucT7+yzr2nQg4HxMRgjrm6FUWQAsIYDWVNRzj/+T4sOxKi6xhYyggDH2ogjRbSkQyChHSj5IGax9844dO1n/05p0ztpKe2Uy+4F/k6ZVu9FscLLx5DajzHzYOCkWvmbbZ0V67qtAwqfcc7X9imHdV80QmCHzw4jhOwDDPbllA/DyEiHEAJW1+V1lMbeGwHJT/fUCkm7YKnsslvsBf4um2r3RuiSMi2C5cBG+kEg8wRgCwW+llFYFwfYVLr1822LF882d8OjFnzLSZNmx9r6Da/KAAykDIYxIPtwgP6u90PEQUhiB7AmZvC6va7Qgqe52yfsBX63p7B7F0Bu2NIC+5rAhxMg+2BpKw4g/NMOR5Qtm7YRwjYTRjZTwrdQCjuqBg5o3F3x55jXsG3T5grGoA/jpD+nfADndAAhrErn5kKqAbCwNBgHvjYG5PPycvjsiybVdG8V7Pqz9wJ/18951jtOmv1irOmdj4cQaiCnHMI5DOBAKnWO6SUKpINw3ohFJTg3mjnnHZxY7XFKUFduh4zRnjCSqTQ0WuVgWinoZ6UrGs2zBm8UfeQfrx9kJBorYknYarRAzEhAhZG2UkmIWyXAeEmG8RLCjRJCSDEhVi8sXsIJqcAEmNAXkZmNDYTAZgKwgTNrbe9DR2xYPPvEfwuJZQ9bDjvtcfYCf6dNbc9dGN2FZmNR/xilA5jFBgBjVUBF9aA+2DOw5+6U/5WwhxwW3AUGO4DSbdSgm03GNscqOrfsdbflP4+7a+Re4O+ume+h+06aMr+szSiuYBbpw4Bii64SwnmJxXkJUFpCOJRwYAlCqMGBGAQLyXISY7Y6QQEsTrjJgVoEuMU5swhQrMHXDoy1G4S0c0LagZB2CqyVGnxHqdXRuHjh9NYeeoW9l9kNM/D/AeXG4shabsG4AAAAAElFTkSuQmCC"},7875:function(e){"use strict";e.exports="data:image/png;base64,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"},14813:function(e){"use strict";e.exports="data:image/png;base64,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"},79989:function(e){"use strict";e.exports="data:image/png;base64,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"},73486:function(e){"use strict";e.exports="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAANIAAABoCAYAAACEyK5RAAAAAXNSR0IArs4c6QAAGOxJREFUeF7tXflzHMd1ft09vbM3FscSIMEDvEmRlEnRsiwftCz5lBSfieOUk7JzVblS+Q9S5V8SV35TJa5KpZyyncjyWY4d25RKsh3RkilLoWgdBHXwkgiSOIgbi11gjzk69Wa3wcFoFju7WIALoFm1mt3FzOzMm/70vv76e90E1D8VARWBZUeAeM5Q6zPuLnx+1e+7ZV+cOoGKwFqJgBs48r3fd3734waPfK8AtVaevLrOpkbADR4vkPCzH7i8oMHPft819ULVyVQEWjkCXrDIz57tFrp1KxWDg4PyXiR4vFs39VNZqpWfvLq2pkagCnCAVrIRbml7+y5mRru0JADMzY1ZMzMDViULIVjsyssPXH7AauoNqJOpCLRCBLxAkgBiCCB8tbVt1ywrpNlhrgk9yfRQjBFCBRfZYmn6YnFmZkYCyb0Nkqla4f7VNagINCUCbiA5wKm8EEjOKx7v5lYoERI6Z7oW1YSIUcEZDWlRSiizzVKuYE1czGWzQyYAYKZyZyh87waVmxpWUwCbcmPqJCoCqxkBBJLMQvK9BJEGiYQGlsXDoU0618Khos00Hg0zzpMUhEaAc+A8QjiPASkW52YKb8/ODZwteADlBZMSJ1bzCavfWpUIuIHkzkYaAOCLV7aarqdDWqozLGiMayyk4Z+1cJziloRCQtOiADwCQtj5Un44AyPPZxTtW5VnqH6kBSLgByQJItyG3GBCqhcKxTQt0RvWY1t0Q1CqhcOgMZ0QwgXTdEK0qABNA0q4IQoTU9mrL05ms5eMgLRPKX0t0CjUJdQfgaWAhNnI+5K0j3DOqZbYoUfj22Imi1AW1oEAF4yFiBaOAZCQAEEJ4botjNmp0uj50Ykbv59z9aH8+lJKPq//GaojWiAC3j7Srf7RYhBhZnJnKtmvAs45aIneUKhtd4KHO0LA8BQ6aLru6BWM6aDxiACmgyjmZ4vzl4eLN05NVWifFCekjK7UvhZoFOoS6o+An2qHSHD3kdxZSX4v5XF5vAOASLJHC3UdSOqxzXGgGgUnQ0WAaFwI0AgL6cBYCAgReXN2dDhz8+nh7PClkidL+YFKjUfV/2zVEasYAb9xJHdWcgsOElASaG65XFqJnD4O520kuulQMtrVlyIswS0nM3HAbIVAAnxBCDTOLTs/M5Qde+HG1JVnsor2reKTVz/V1Aj4ORsQIF4wuWmdOyu5MxMeh/8WQMU5F3rn0URi054u0FIRyjmxgQNFQFEOQHVnX8bCICA/aky9dXXo3HfHKoBStK+pj1qdbCUj4AaSBIF3YBaBI7OQm/YtDNq6BnLdY1LuLCUiHbvDie7jm7RkdwclIQqECaCYnSgwqhGKwAIGgti5Ym78cu7GyWs+tM9vTErRvpVsIercgSLgdX9X6zPJLCVB5QaRF1D42StiLDR2Hu2kbdvv7QnF+zYRLcqpxqkzJkw0QTVGUOOgmkaoLQzTyF3JDj1/eeqtX8/60D43qJTaF+hxq51WKgLVSidqWYfc9G8pUMns5v6dSj8qCokd7+sKpw72auFEAsFESYhghgLCCDBNOIO+mkaM4vw1I3vx9eE/fGdUuSZWqimo8y4nAn5FfH5ZapEbvEL13GDC9+5s5f2bG1Du0g1H7Yv3vDsZ33p8Ow93pylDJFEQwAjV8JTUyVC4JUJMF+aG+mf7v385mx3CQV6vYVbJ58tpDerYhiPgBpI8Sa0s5e5DvcPk6hIqZKbyA5W3b+ZkqUjHjlBy64kdPLFjG+N6iFKkepWfYIxQ0EBQRhiQQsmYOZ+9/tz5qStPSrWvmjihaF/DzUMdGDQCfkAKCijZD3KDqRblk3/3Sufu6xA8mqTtOz7aq3fu20W0aJISrNzgBAgpA4uiBYkRoNQW1txFM3P5letnvjmsaF/Qx672a3YElgJSNUBJdU9mlVq0z68P5QaUFCf8spTo6HtgU3TzsT003LmFUgoUNPwPIQ6QKtSPUCLAHDLmRl6cfvXRC7Ozg1jSoWhfs1uLOl/VCAQBkvvgZtM+OQ61UEhYUfze0Y9KpO+IxXd+ZL+e2LyLALpjGbERVow6W0IIxSwlKMlapZkzs9d+9dLkpVM5ZZZVrX81IlAvkG4H7ZMZsKz2RTpZ1/6H94ZTew+AFmlzwEMIBcxW+B6oQ/8YI5ZtFl7Jjb72ws1Xvjm0RIbCzKX6UavR2tbxbzQKpKUA5aZ+brXOnXWqSeZegcJNG+V5nUaPron2PQ9tj6SPHmZ621ZBgFBSUfdQlxBI/Qg4HSm7eMWev/m7qVe/8Vomk5GihJx3Qg3yruMGvlq3tlwgLYf2uWldrQHeJeXzVO89bbG+Dx8NxzYfEISECHG6XYRQQtEtge+Eo/6Jabs49czs5ZPPT1w77S3pUGbZ1Wp16/B3mgmkoLSvEXHCnc28oFqgZZFkL0/t/9yRSFvfMdD0JIiyKEEJJbaj+WkEQQUAJdvIvTA/3v/0yMvfQrXPT5iQmUrRvnXY8Jt9SysBpCC0zwumRiV0KcF7aF8UOg5+fm+06/C7WSi+HRA8hOEsLA6oBG4IRQsFgFXqN+dGfj3d/y/9qkaq2c1r45xvJYEUlPb5gSoI7fNmqaryeXL7iXu0WPoIAOHI95DmOZnJyVKMCgEEBIzYxtRTs5dOPjs+8My8qpHaOCBoxp2uFpAaoX1eaXwpgUKOS1U1yybS+yKpfZ+7OxTvvYewUBIAkxKKEggn6lA+J1MB5G1j7jfz4+eeHH7pP0YU7WtGM1v/51htIK007fOOR72zRiqapOlDXzocTh34IAtFt2M2KmcnQpw5JhBc+A0BYlmlF6zsyC+uPvu18wHGo9T85+sfL1Xv8HYBabm0z4/6lW0Ot4oS/WxI8n4dc2vn/s9uS2x7731c7zgKhGpuUKFsjto5fkeJuGrkp3821v+fT+dG+3HePuWa2MCg8bv1VgBSvbQvyHiU1/NX033esfdTJ/RkzwcAWLIsm1PiAMt573A/CkJkbDP3y/zwuZ8PvvpNdyWv3xzoSu3bQGBrJSDVon1SlPCaZWsZZf1sSPJci9W+SCfrPvqX7wmndj1AWHiHMxblAAjQelQBk7O1hVU8VZgb+uH1337tdWWW3UCIqXKrrQikRmlfEKVvKff5ItrXfeQrB+Kb3/Uxprcfw1qrcnIChtoEZiikkIgyYVtvmoWpx8Zf//ffqNL4jQuoVgdSPbTPWydVjw3Jne3cgIK2nSc6O3Y+9DEtlr4fgMbL408o+aHKJ9CEhGofKhVTopT94czYmR+PvfToRABxwk39vO83botco3e+VoAUFFDNrJFaRPsiiS16+uhffUhP9j1IGN9aARAqfI5LFsEEZYOfaVn5k6XMwKPXT/+jon1rFBj1XvZaA1KtfpRfjVQQccJrlnUDcnE/inORftffHoumD32ahZLH0S3hiBFltRCHeNFCUVb8LOOMWZr6zsQLjzylaqTqbZpra/+1CqSg/ahqwkQtgcLbl/J1TXTtfXBLcudHP6uFOz4KhEUQTGX7kVPLwUTZQkEJ2CNWKfet3MjvHht55QczddI+tcD1GsDUegDSStK+WmZZp2+TSO+Ldt7xF5/Uk9s+A5T3ghAMe1E4HVKlULGc8YQ9Z1mFH5gzb3174Ll/vqBcE2sAIQEvcT0BqR7a5ydM1JOlqpplu4//3fujnfv/lGjRu5DeIZiQ/iGqHEefcFY1FMIynjbz49+a+sM/nVJm2YCttYV3W49AWmnaF8gsmz70xV1t2098UdPbPimARAUAVnLYiKGFTCQEfn7bNjLfnrz0+E+nrjzpnQhT1Ui1MHj8GtoaudyGL1P+D8O9dfd73A70es2y1WZEcvo28Z53J9KH/+zzPJb+PCFa2gGREEIQsIkAGwjYCDIAmBXG3I/nxy98b+jFRwYU7Wv4Wd+WA9d7RvIG1Q9QUpVb2RqpaJJuvuvv79dTe/6EMv0QQQAhkMoZCtmfhaBCANlW6TdGbvi7A7/9hzNqQYHbgou6f3SjASko7atWIxXUPbGkt6/7zi/vj/fe8wUtlLwPpXMBokz7CKYq7EPhfC5g27Z1SRQyj2Uu/fQJnxopNddE3c195Q7YyEAKqvZVo31eUPm5z+U+fvI5tG2/N9Wx73Of4dHuhwihKcw+AvtNxOlL2SDARhcSCDFlG/P/PTf20k+q1EipBQVWDiOBzqyAdCtMjdI+CRbvSh1LlXQsHuSNdLLNd331fr1t56eJpu9GQGFGctQ9ISwEkxDEJESYlln8Xys3/COfGim/DKVqpALBYPk7KSD5x3ApcSLo5C24nwRXYLNsz7G/ORzrPvZpTU++1+k9gbCcDFURJhYECtt6szQ/+aOJ1793KnfzlaKqkVo+GJZzBgWkpaMXRO2rxyzrl6V8XRNt2050dex98GEe6/mIICRGHGWP4BhUeT4+pH2UWELYU8LM/Wx28P9+Odr/2FQNccJBZuWWvdvltKMNf6wCUrAmUAtQzTTLLnKf4xRj6SNfuU9P9X2SUL5VEGKhO7YMGOxLOcBCKljEGqn5zMD/DJ7++iVVIxXswTZrLwWk+iK5VD9KgskNqqAqn3s/d4Zyg0r03vXVO8PpQ59gevyoEFSWuyOoLCmnY5aybeO8PT/584mz33hemWXre8CN7q2A1Gjkbi06vdQgbz20z6+S15f2dex+YFOq7+OfYJGuDwChOip8TtWuQOpXfo99KQFi1C5NPzF54+lfT7/xeEaZZRt/2LWOVECqFaHaf18J2lfNLCvVPrkwm54++Ocn9FTf/eC4JhBEFCV0R6DAfpUoU7+CsArPFCbffGLwzL9eUwsK1H6o9e6hgFRvxKrvH4T2ScWvkRopt1q4WD7nXGw68td3Rrru+AgJxQ9IAGF/CmdsEeD0qywhMGsZ50rzw09mXn7k5cqCAtVWOpTLiPoJFM2L2jo5kwLSyjzIWlmqEfd5ILNs+65P9KR23veAFum6G5eKryh9ggCYKE5ghiIEKaA1as1P/Spz5ZfPqgUFlt8IFJCWH8OlzhAEUPWKE7VqpMq0r31/OH34j98fivd+kNBQG1I9B0S3jLIWzoFJCMzbRv7Z+fFzp9TMso03BgWkxmNXz5GNuiZq1UjVnlmWR0nnkS8fiXXt+xDl8R1ScHCcEjjRGFI+h/pRC6zCudLc4NPXfvf1N5RZtp7He0t5qu8otfdyIlCPa8I7gFtr/vMlzbJdex7uTW573wdouP1d5WkmEEDoOne8fRagUAHEpMIeNgtTp0bPf/fs3NhrebWgQO3HrTJS7Rit1B710L56a6Rkibt7mrEF0SCRviPatu8z7w0neu8mjMeEXVb5BDi+PhsIdcQJEJC1zdzzueEXnxs9/4NJVSNVW2laqcaizls7Ao3SvqCDvdXVPlxQ4MCXDoe79t1Dmb5FAK0IEQgozE4IJmIRChaYxVdLmbdPX3vhkasBxqM2nA1JZaTaDX0192gW7at7QYGu/Z/amtjynntYuGM/1kOhl88RJxw/X1k+B8osENZQKX/zuemL3z+nZpa91TQUkFYTJsF/KyjtCzIe5RUsluxHxTcfibfvfOjuUHzLnUC1ULmCl5hlP58jSphAqQXCzlql7JmZq6fPTr31CznXhHuB6w1VI6WAFLxx3449q9E+d99nuTYkeS45yOvQMh7pZJvu+MLBUGrXXYxHOstuiTLdK8vmxHIABVC0jdwb5vTbZ66f/behjWqWVUC6HfBo7DfroX1B+0+BBnmddaQ2Hz3G9PadKJWXSzhQNqcmcQQKDT1+lhDWdTM/enbm1UcvZDLXpWPCvZaUdEusO9eEAlJjjfp2HhWE9i03S/mZZSHeczSR6vv4kVCy56AAopVrpFjZfgRgEkqd/hQFe9YsZV7Kvf1U/8S107gerxtUtaYYW1AXb2eQ6/1tBaR6I9Y6+9cClNsx4a7QrTUWVS1LyTsXPNmtde7+o/3h1J5DVMP1eEl5ULdcK2URSk0hUEInJcvIvZmb6X9l/OXveVfoWFel8QpIrQOMRq8kiFlWgiqIOOFdUGBJs2xy18PbopsOH9L01GaCZRzOPH1I+SqKn+Pro5ZtF6+L7I3+zIX/ersys+y6Wj5UAanR5tuax9XKUo2YZb3zTfjRPhHvOd7WvuO+g1qseycuHABlhc8SlFjEBpMQatn4XpAZUbj52vjFkxdyo/0410Q9tK9lFxRQQGpNQCz3qmoBqhHaF8wsm+zmqV2f2q23bdtHND3iZCcEFZplcWDXZoZgxKQUimY+c7k0du6NkTd/hit0+GUoSf/c/aaWnGtCAWm5Tba1jw9C+5abpSQopXzuNHrOuWjb/WBvpOvQPsYTnc6gLsUpxagtCDGYQwGZaRNiCrs4WBy/crFw7SdDa3VBAQWk1gZCM6+uVpZqBFCB5PNU7/G2SO/7d+uRrm024TYRtk2oZtogLI0y00bFD+1JYM4Y+bFLMwMnr/q4JmqpfbeV9ikgNbOpro1zBQGUV5yoZ1xKHiv7Ugu0DGdESvbd3xdJ7dkhKOMEJ7+k1ASBWYoajh0JnKyVN42Zq3NDp69OXXkmuxZonwLS2mj8K3GVS9G+5SwoEKRGCuJ9H+6JdR3cSXkyDsKyBWUmI8QSKExoGsroJlI/AnPDc2MDb4299ii6z2sJE7fNLKuAtBJNdO2dsx7XRFNrpOK9x9vaet6znca60hRXEXBoHjNtISzKOMroJmHMtCx7RuSuD8xcPDmSzQ4ZrTazrALS2mv0K3nFjdI+N/XzTtPsnbPPt0YKaV9i24neUGLrFqrpOBVSOSvRCpiAmpRSizEolHKTNwpjzw2OD5yVRYe33SyrgLSSzXLtnrtR2lfNNRF8QQEeJfHtH0pHOvdtYSwcxgFewtApgTRPlOkejkdp3DDy2dF85vXB6TceR/e519vn9fWtKO1TQFq7jX21rrwe2lePKOFWCasM8h5NxjYd79GiqZQN1NQqoLItMKmj9gmTMN0UopgpTlwbLg49Pjk7O+uUfPiUx7uB5Tcutax4KiAtK3wb6uAgtK8es2zgBQUiyd5QdPO93XpySwdQhmWHWM5hANUsCsSwGTM5RXuSnS9mJkdzo78dy928UqohTjR1kFcBaUNhoSk3WwtQjbgmqi17Iwd5yzVSPEoSW+9t56mdXYRFuEbAMkCYmlPF64xHGZzpOMhrgDk9WRx5bXzixu+97vMVMcsqIDWlbW3IkwRxTbhBFYT2eSd5cVM++XsORcNK3mjqQCdEOqMao6YtwKICqR6+L1M+CsK0SsVsfvraBEw/n1lJs6wC0obEQNNvulaWasQ1Ecgsi7QvnL6zXY9vTgCltgMih/KBYQvbJJRbRAhTY6RQKtycnB84k8lmh7AfVWtMqq5+lAJS09vUhj5hLUA1QvsCmWWR9sW2HEvosa1JQUOMUAQSToJJLNsUBmYqfDHghlmYyOSnLmcq7vOmmGUVkDZ0u1+xmw9C+7wLCgShfu4sJUEp+1FOBkGzbLh9V0RL7EqycBsntm0SRkzLyU6ahasIUOAlYjNTWFN5KAzNmpm38ss1yyogrVhbUieuRKBWlmqE9gUyy0aSPZrevj9G9PYwocImghqEgGUJYuqMGaawTCaYgZP22dnheSt3Ya6yQkfd8rkCkmrvqxWBIICSWabeSl6/MamFPg7nUQin90a43h2xCLWJjZRPWJYQJdxSjRrEIqZpmwYv5eaN2Rv52dlBuV7vUpO3LAzyKiCtVjNSvyMj0KhrotaCAoFonxbpDenJnjBocSDEsKySaRC0ITEwTdswwgxMwyKGIeYKWma84Fo61CtOLHJOKCCpBn47I1CPa6KpZlke7WRaPM01PcnABhMRBVQzqW2UiClMyoRRMuYNqtklXpouzsxwE2Dcz4bkZD4FpNvZjNRvL5Wl3GNI7rKOpi4owHlUaIlNIdASWFtoIYhMq4RgKhFqGYVSrgSsWIJcDh3nUjZ3r3LoZCYFJNWYWykCjdK+oIqfe7pmr9pnA2+jwCMkRJhpmHaJGHmDRLRSYWa2CDAngeQLJgWkVmpG6lrcEaiH9lXLUtVKOvzmP5d9HjsUitkQCtk4jRg1zWKBlIqQzyOQvGCSQoTKSKrttnwEgqh9zTDLykDIuSFM0HUTikjnimiAlUDyUjxF7Vq+CakLDJqhZH+qHkBV8/XJzCTlbzeAvFlJZSTVRtdsBNzdEXe2coOpXrOsl+rJrIRgwj6RNxvhd+66J0Xt1mxzUhfuFgv8AOX19UmwLFXFK8EoB3Mx40jQSEDJz4vGlZTYoBrkeohArX5UELOsV9HDuCCQJMVzA8rtelB9pPXQgtQ9LIpAI2bZauUa7qwkgePeLrIOqYykWuJ6jUCtLOUVJrz9JAkk2V+S2UluF838qoC0XpuRuq+grgk37XO7KdxyuBtMflMnK7FBtbcNE4EgtM+7jxdMflN8OQ5wlZE2TDtSN+qKQDXa56cESornpnrv+E4BSbWvjRwBvwy0FCbcK14smnBSAWkjNyN1795+lDsiftjwLh2z8FkBSTUmFYEmROD/ASqSbiAtqYRHAAAAAElFTkSuQmCC"},23280:function(e){"use strict";e.exports="data:image/png;base64,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"},63232:function(e){"use strict";e.exports="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAfQAAABQCAYAAADvLIfGAAAAAXNSR0IArs4c6QAAIABJREFUeF7tfQuQXFd55n/uvd23n/OSRqORZEvYsmxLhBgLAnGwLV4hCSRhK1HCViohBLK1iStUoJZskt2NJLLEScBFJYJ4y7vsI5U1BG0WqNSmttgEhB2MbZDxS2PrYVu2JesxoxnNTL/u45yz/s/j3nNv98z06D32uYWZVvd99d+3+7vf/3//9xOwi42AjYCNgI2AjYCNwIqPAFnx78C+ARsBGwEbARsBGwEbAbCAbi8CGwEbARsBGwEbgddABCygvwY+RPsWbARsBGwEbARsBCyg22vARsBGwEbARsBG4DUQAQvor4EP0b4FGwEbARsBGwEbgasC0DnnfZ0HIYTbj8xGwEbARsBGwEbARqA7An0B6aUK3EJAvmcPkF27oCd4W1C/VJ+G3a+NgI2AjYCNwEqOwBUD9DyY7wEguwBg376s8n5ipwT2XZACvAX1lXzJ2XO3EbARsBGwEbgUEbgigG6CuWLjsA+ATOwHMl5PAX3LduDf2Q+wdQfwCQT0PQCauVtQvxSXg92njYCNgI2AjcBKjcBlB/QMmAOQrfuATIxKIB8uAzlVBDJ9HMjIBsnI14bAZ9rAT84D37UD2B4L6iv1WrPnbSNgI2AjYCNwCSNwWQF9ITCHNeCMFIHEk+BUi0D+buJ07cgrs+M7b97y/M1vgmg+Bu7PAkNQ3zoJfGICuGXql/CqsLu2EbARsBGwEVhxEbhsgL4YmMMZcMbr4JQ3APnKA5P1p4/OXc+BOlDy2h+86brDb/gRiLwOMH8zsJP7LaivuKvMnrCNgI2AjYCNwCWPwGUB9MXAfGMFnPAsOHEZnAePTg08+dz89ZQ7Him4DGhMXMKaO3/0uiMDmyGwoH7Jrwd7ABsBGwEbARuBFRqBSw7o/YC5VwP3W89PDz7x3NxmSp3CusHiubdfN3jqm4fOXtdsM89nvPXzb9t4aHwTdIImUMvUV+jVZk/bRsBGwEbARuCSReCSAno/YB4MgvfQwenBwyfnb4DYKawa9hs/f9ua424A5EQM7nceObFprs28is/m3/cTG5+troLAn4fYgvoluybsjm0EbARsBGwEVmAELhmg9wvmPzw4Pfj0K40bXc8pjNX9xntvHj0dueDSCIhbAN5uAvnW4ZPXNDrUcTmbf/8t1z5T2AgdC+or8Gqzp2wjYCNgI2AjcMkicEkAfVlgPtXYQsAtrav6zXe9afWZDkDRd8ClRPajEwfi+RngDx06tX4upIRwNvf+N10zYUH9kl0Tdsc2AjYCNgI2AiswAhcd0PsF82cPTg/+cKq9xQO3NF4vtW6/eWiqRcD3AIpPv9xY90+Pn9p5109tvs/1IfA8CM7NA/3Bocm1s21KHM7n3vemcQvqK/CCs6dsI2AjYCNgI3BpInBRAf18wfytW4fOMgol14HSoZONdfsePP65IKbrh6vFBz/+/hvu9svQZhw6zTZEPzg8tXamGYMF9UtzQdi92gjYCNgI2AiszAhcNEDvG8yfnx586qRk5qP1UuutWySYEwfKR19prv9fDx3/bBjF69AmDrPuw7XCg3f93A1/VqDQgiK05zsQP3loamwmiIFFfO597xifKAzbmvrKvPzsWdsI2AjYCNgIXKwIXBRAXw6YP3OyvcUFtzRigDlnUHppCsH8xOc6Ubyu5nvP/ejm4a88/MzU7zLOqyP10oO/+dPX/WmBQMtxJVN//PDU2rkghsiC+sW6Fux+bARsBGwEbARWcAQuGNCXBeaT7S0ud0trBkqtN18nmTmC+bHpxrqvf/eVe0JK15V97+iHd2zcMzJQbD16eGbzt544/UccoDpS9x/4jZ95w90eg04C6s9JUOcxn3v32y1TX8HXoT11GwEbARsBG4ELjMAFAXr/YN4ePDI5vcXhfmlswGv9iAHmx6cb49945OQ9YczW+7575EO3XfuHa4aKTYcDZxTIwy9M3/jPByf/I3CoDtSKD3zk/W+42w2h7XoQIFN/6rmZtXNBABDzuTstqF/g5WA3txGwEbARsBFYqRE4b0BfHpjPbXG42xPM/+H7p+/pxHR9seAe+aV3bPg3o4P+HJq+EhcYjYE4DrgPHz77xocOTf8ZcC5A/Vffu+lul+ZBnSpQH7U19ZV6NdrzthGwEbARsBE47wicF6D3C+bHnm8PTkzPiZr5qkqWmZ+cbY//w/dP3oNq9mLRPfzBH1//yfEBf4ZzCGbnW84//+MTOz7wCz/+Tc7AcwGK3zs886OPHjn7Oc55dbBeeuBfvuuaDKhPHJtZOx9KUP+Jt1hQP+8rwm5oI2AjYCNgI7AiI7BsQD8fMB+reK2bjTQ7gvk3D5y+J6AxMvPDP7t93SfWDPlnCw60z06H/Ktf+eYXwyC6fWCo9ue/9mvv/ZLrQok5UHrk2Zk3P3Z05h4GrDpY9R/Y+c5uUG+FFKgF9RV5MdqTthGwEbARsBE4/wgsC9CXA+aH52SafTWC+cZUAIdg/q3HzwhmXiiSwz9zy7pPjK/2p2gMrdlzIf3K3/7jvZ0guJMzDo7jwOBA+U8++pH3fSnmUCEulL9/dObWJ4+euwfV7/VK4YFf2JEF9cPHsaZOgVA+97ZbLFM//0vDbmkjYCNgI2AjsJIi0DegLwfMnzfA/AYDzM/Mtse//eTkPQGl6wsF5/BPvmltAubT02H81f/9rXtb7WAHYwxEHzoBAeojg9XP/PqvvudLrgcVxqFy4OjsrU89P3MPEKhWK8UHPviOdUn6PWxD9OzxmbXzAQVqQX0lXYv2XG0EbARsBGwELiACfQH68sC8tcXhTml1pdC6YWMtaU07M98e/85TU/fEjK33POfwu9605hPjw5KZTzfD+Mv7vnNvOwh3cMaAUoauMoCo7rgEHMeFoVr5Mx/7lXcloP7487O3Pv3CuXs4cAHqP3tbL1AHoBTm3nbLsBXKXcBFYje1EbARsBGwEbj6I7AsQN+zB8jWrUAmRoHAGnA2VsAJz4KDI1BRAPdSq7WFMKc07HeD+UMT0/dElEowf+P4J0aH3QTM7//ag/d2omgHjRkgO2ecAyEEOJdpd8ch4DoEhurVz3xs5x0JqD/54uytEy/M3gMA1Uq58MBP/8T43V4k+9TbFOIXXpwZmwsAOIO5W9/YDeq7dgDbswdg1y6REMBjir92sRGwEbARsBGwEVhpEVgS0DU7XwjMvRq4j59sDx6faW0h3CmvqRSa12+oTQs7Vwblk432+KPPTH8uYmx9wSWH79w2/snVQ+6kZub3/5/v3dsJwx0xgjnnAsQZB1g/VIYT59rg4BkSBHQHPNeBoWrlMx/7F7cloH4QQf3FOZF+r5UKD7z3trV/in3qCOphDNGzL8ysbXDgDoO5zTcPP3NzCJ1zlXSeOoK6zAXIxYL6SruE7fnaCNgI2AjYCAj8WioMCaADkK0AZAbAObkf3PE6OHEZnKdm24NnTja3+J7jD9SKrc2ra9NY50YwP9MK1z96aPKzNObrPM85cvsbxz45WHInXQKtyUYY3f/NR+9tBZGomVOWgvnHd7wB/tU7NsFH/+ZxePTFc0AQbwkBhxAouA4MY/r9A2//EjJz/O/Qicath47PfhaFclW/+OCOH1vzp1UGbU6g1Y4gfP4VFMoBDnQ5t3HzyLNrhqHjdYD5s8CGtwObAOC7FKhbQF/qirCv2wjYCNgI2AhcjRHoC9A1O5+5TqTXnbgEjj8H7pGzrfqJqdYWhzj+aLXQvHGkfjYoQpW5UDkzE17z2JGpz1IG61ziHL1t2+inVlXdSSDQPDMfhvd/67EvNjvhDsY4UGTljAFwAr9zx0b4xJ3XiVi1Igof/fKT8MhL54RADtPwCOrI1Ecq5c/c9TNv+W8RgZoDUJt4qXHrkVfm7kZQr5WLD96xbfTPXIAmqUCThxA8/fL02jgAYBHM3/jmkYMDkxBtGAQ6uhXY5D7gO3cKpm4Z+tV4ldpzshGwEbARsBFYMgKLAnovdl48Bu7UHLhnppv1k7PhDR3uFEdrxeaWsfIZbC0DD6pTM+HGx56b/jylfF3Bc5677YbV/65WcaeIB/MzjSj46+888RetMLozpqpmDujzCvDxd1wLn3jHpsxJC1DfdxC+9/I5AeYC1B2AguPCqnr57o+985a/BgfqnEL92OnmLYdOzH8ahXK1svfgj28ZvbtcgNmYQDNgEDxz/Oy6qOkR7pC5W7cNPFt2IUxY+h7gWEu3DH3Ja8auYCNgI2AjYCNwFUagb0CH/eBsXQPO8VlwX2w1B07PhFu8EnGrTrGxbUvlVDwHJacIlVcawaaDz839Vczo+qLrPPfWzas+XfXdafCgeS6MO/c/dPDPG63wHRHFNLusm2PN/ONv3wCfvO3aniFCUP+Nrz0DD5+Yl61syNIx/e65MDZY+dxH3rb1y7EDA8Cg/vJUc9uhE41/T4BXK37xgbfdOLK7XIVzrAWtNoHo4PMz6ykjDolJ4803Dj7b9CDauhWoTbtfhVenPSUbARsBGwEbgb4jsHxAHwD3hRcatVOnohsLPikMOE7zhk0DJ70YSqQAlQcPTf9BuxP9MnaevWG8/sfXj1aeAA4Bc6HxPx5+ZvdsJ7wzjCmElEEsAB3Adwl87Re3wtZRLIn3Xr70xCn49IMvqbQ7gOc4UHAIFD0XNg7V/uSDt1z//ziFmsuh/NiLMx+eaYTvdwjh61aVP3XztfVv+xE0z8QBfeF4tC6kMWGczF9TGzxU2wARnAEGO4DZOnrf141d0UbARsBGwEbgKovA8gF9Flx/ENwT883qK+fCLU7s+MWi075upH6qXIRKm8LAYy/MfKYdxncSDs1rR2uf3ri6PMEItP7phZNvnDg1/dmAsmLEGCBL54D1c4Ah34H7P7AFtq2udIXo/mem4PcfeEko+DRDR3aOgF72vJfes3n9b928ZqDNKNQmXp794PRc+BvgEj5SK+7dtn5gn1uBRtAKoxOnovG5KOauA7OrBwcP3bweonAT0GFIhXE25X6VXaH2dGwEbARsBGwE+opA34CuFe66hj7ig/PyXLN69Gx0Uxkcv1Z1OtcO186EAFWHwcBjz8/sDkJ6OyHQ2Dha/Q/XrCo/DQDNv3/uxC3PTjU+H9DYR4YuBHGiXY3AcMmF+993HWxbVU5O/n8eOgu//90TQumO/ehYQ8d0O/allzzvxR1vWPvRt6webFEE8+PzO8+1gt/EFvaRWvGLW9YPfM31oMGjKDp6OlrbYTEreTA7tnrg2XEKYTAI1NbQ+7pO7EpXeQRQ76K8mLQnU9cZ25vVq/xDtKdnI3CBEViWyn10J5CnjoKrVe60CM5cE+rHXpm90fVIqe46nQ1ralOUQQXZ8pMvn/ujIKK3EyCNa8eqvz8+6D/NHGj9/ZGTbz482/jLkFI/5qBAHQVyAMMlD7787mth20gZ/ubIDPzBIydlbx3h4BJH9KVjT3rZdV9817Vrf/3W1bVGHEH1+VNzvzzdin4LVxyqFL9484baNzArwEkUvXwqGmvHMfcKhZnNa8vP0hgCtwkMVe4TZ4CZvej2R+8Cryi7+WWMABcdnbv3ANkNADsPAtmHf3cCTE7sJwA7YP6VAwRguzin9roJArAVwrNHSXHVZo5/b+hxtrVVmznABBxUr5XHt3I4AFBfl/o1jG6Vj7dNyL/WnOkyfuz2UDYCC0SgL0DHbffoPvQDsnXNnwUX+9C9NrgvNWFgOmreCJz41ZIbjFf9SXABaXb1qZfO7QpjdrsDpDE+XPm9sSH/KXCg/Y0XT996eK61V4K6bF3jHARbH/Yd+JXrh+ALz8y82iGOrnEALqrbAUTLmu+6x965YfTXf2ywNh/FUH3+TONDc+3wt8EhfLjqf+G6NZVvoLFM3IH4+FwwhmayAXVmtwyXnh3eCMFsB2Lbh26/EysxApqJmyCu38fktiyISwDHRYL4DbAZ2vPHyDEA2LRpEwSzxwnABgibJ5PfgWjAIXFL2DmpZVT8pZ0pMlQ9RwBGxL/jAB8PA63MEoAhuU4wRwAGgZXmiePX+eDsLHg+4/P+IIcZAG/dMIez0+CVUTkDUGhwPl0Z5QCnoVBjvDhLuT+4gZfP4k3CUaitCvnzr7R5fd08Hz24g2/bZjtRVuI1a8/58kWgb0BXp0T27AdnfAeQ4KgB6iVwXzoLA1MzzZuKBVIsOm64YdCfxJGnDKBy6MT8riCK7/DAaYwMlz41PuA/jeYy+05MbX+u0dwbMubHoh9dsnW94ENsUXPAAVcwcwCfuMfevWHNh99aKzUoh8oLpxofmguiuxzX4bWSt/e6DdWvexyCsAn0eDMYi2LKOXfODY2Unh2vQ+BXIQ6aRqrdMJXB41qGfvkuPnukfiPACX4XyJ49BGAXIBvffXAf2blzp2LiAPOv1FMmPqOAfJsEcoDNsGHVMQKwCY4dAxgfzgJ51HYIjAHkgZzWpsTvw1A7B+TDw0ADCeQSxAFYSd4EDMAAzITzyeNzUYPU6zVgYVP91tSARvIx80WVQPhDlaMWaUIFysU2aamwlGKZnGMxIYIeoKVj3CEg/tGGOh/G5hVwwiZ3vAp3Qs7doQpvBw3uBJy7hRp3O7O8Uaxz15/hPt3EvPIUn2lw7lUYL8wxXl83zspnj/IzwWaGGYgdr3IK277a73Vp17vaIrAkoIsvERa4kaXnvNxHikCQqaP9q+ODe3QS6o255k3gE9+nbjA24J9Bpo6gfvTk/K4oZncQDo1Vg6VPjY/4TwGF9r4zU9uPNoK9AaW+BnTtxYoHRVaO7Bz/K7nusXevGUnA/KUzrQ81wugu4hBeK7l7r11X/brDodNuApvqBGOUU+ZQZ3ZwuHRopAIdE8xPzgM3le0WzK+2S/P1fj46nZ6COKbUMSqaieNjnVIXbBxz5CaIzx8jkDBxgLCJt8UAsG4coudO9wBxZOKErF4NECsQ10wcN9NsXIO4ZuMI49VwnsyJnQ9ANWoQSEC8N4ALoI5aBECKYDWQpyDeIVAuGwAOwCiCeQn8OCBtKAlYl8+VgRfwLy4lYHEg1uMF/OsnF1KRAgkAoIgiHLEtvq5uFPC5EIB7MsacEuJwzkplzmNeZGEc8LLr84hz5kSce36JdbwWF48ZZ+2Q80KZsQKrsnadMbfDuU8ZK9MRNh8D3iwkNw7XzQD76leBWfLwev+OX/z33xeg9wPqw9eC02yCtxioHzvdwPT7Ha4DjaFa+VNjQwUJ6lOz24+023tDykRNnb3KQ3DqGsHBLAjo+DV13WPvGV714bfWPMHMj0+1PtQM47scl/CK7+3dsLa8LDC3Hu4X/2Kye7zQCMgb592794iaOLJxXBDIBYjvB4Adubo4snEF4phSPwIAG1YBSZm4AeQAgCl13KfJxhHEYbVk4mcBYBWMJCl1GMZU+iyhgU7DDwIL58nAwAAggFN8DANAFYgLoBRs3AByZNhJR2pVAHm5SEhLUfFSsS1AmWn2XTaZOAIvEAniuFYJWrRDSiVJ2bkCeQ3i4rlCamnNBWj7AsSDAMD3JZBzprMDWRDH7YvFIgSdkEBRfp4FSgj+HCXg70YE1Is8eb4IBTckIa6f7LsAnOG6AFxsU5DnzGJSKBQgDCLiFj1KaMgdXmDECTlzPOoUiiyKA+7yInM5ZxFvM5f5LGKcuSXGim6ZukGDx26FFhljbcpYKaas462m9RDYmU0TbNvWrfSrO+1Nw4V+I1fa9n0D+nJBvTPXvIn7xPdyTP34VFMwdYdAY7BS+tRqBep/OzO//WgQ7I1i5lNsZkNXOJy2hszccV9890D1wz9WLc0jmJ+cbn+oHcV3gevwiu/sHR9NwfxcJxiLOWUudWbXDJcO+T2YuQXzlXaZvpbPV6bTccEvI9bG8fFBZONC3Cb/LZk4LtuluO0gQLi2mNTFYROodLon1tNsXAN4FsRVXbw2RVYjuGPKXS1xRQIdDfTftC4uEHwgZePVyDGYuNwBjRT7NdLp+Lxm48jE8d+I5QkbLyhwbSMYa/Ys37cfEwHkPu2QDm5TKgOnOhUfECiVQIK2WFsCJt4A4F8vTBi6ZuMCyBGoFRtHJq7+KbYtGAxdnLcCbI4pQrWkIA5QcBWjZ0SAeREUiBcQuE0Ql9sjsBegABHqgVgkbywKEujxSZ7sT27ruTGJwQMPPyckN+aNCJ4b/ieOFROxgueJx7gF55Tghp7rxjGNuEs8SjHDgJ3ChFO8iYg5Zy4PGCVF6pEijViHFRyfRj5nbrPJik6Zxg6jRcpZ6FJa94Zp4AMdio+y9qrN9Nu7gNpMg74yrvzfZQG6uCCXSL+bTD1qBTfFReqXWDFYVfGS9PvJmeauOIY7HMIb9Yr/qcFy4WkUyv1do7X9uXb0lxGjvgb0okNefPdg+SO3FktzwKA8ORt8qBVhmt3hlYK7d3TUT5j5fIRgDuhWM7umbsH8yl9e9gwWjID6HuHrGYGboVDH15KUusHE8fkN854Qt+EyPtwDxE8D5OviwzVCptQ2QyaIa/BWArdeKXWTic9j1TsBbAPEEyaeGkSxSAIeAjlTNXEBlLiueAHZuAbxDkEGjmwbU+oCogWQl8EXKXWdThfIroA8TakjkBcNEBfHUWCPwKnT6RL0U4BGEBfMWj2XZeMKiA2GLmDbxZuFYsLAEXwRrE0QF8dRAIxAjQAucbsAHgKwZuyKvSfbujERiF+QQB4JgMYbBWOYVnKjgfvBtSSou/rGQ4E7Bhpf5zwm3AEF+ul5ifwnAj8u4mYAiL55wG3wDGLcr+el64ljqRsZBwhxgLvMjymPmOMBcwinLAYqbyAi5uK/iUfxt9mLOGUVHntRkVKHU5e1GSv6cbHDaexUadkFGnnTtO1HdGSqTWHTptjeNPT/O7psQD8fUOdF8AvMzYD65GxnV0zZHUBIY9D3fq9eKTwNHgTfmA/ecigMP8+AFz1wXvqpWu2jW4swywIonWsFv9yO47sAwdxz9o6sMsGcjsU8Zh5zZ0fqnmXm/V8Dds3LFgElblMgLsDcTKnDDnEmC4G4ELcplboGcVxfsvFxiNqyLo6LTqmvWTMKUWtKAHlG3KaYOK6LbDwD4ihqGxjIpNMRxE1xm2biCTgLDJdArlPqOqwayEVKvVxGPVvCxCXopil1BG0B5AVCsul0fFbXxUUlXYB1oFi5rotrEE9S6kUfOJMM3mTjmolrIM+AOAJvAcFagrZc8iCeptPFvhWzFo9ZTPS/kY1roBYsGtm4wcTl+pEUCSkQx+c0E+8Ccc3GEaQFWMtFAHkPENeMXR4nvYkBcb6epP2I1RqgubwBcB11o6DBXoO4hwVQPD9KYp7eYLh4s0DxBZkZSM4b12dUveaCwykRq+G2uCvqynsKaaOQ3DRwIvct1sPVCHCHO7HjAeUhUOZx6uBeGY8x2+AyL2Ykop7rxSzmlLs8dh1OWcgpK7DYL/hxHHAaOYxWIxZjtmHVwHAcTgGFTRDvgD1s9+7dYkDXSl7OC9BF3Ptk6icaUG/NBjfxAvgF7gaDRcXUPaicnensYpTfgX3q9XLx3/plZ8IjEP3fIHrr0YD+znuqpd+9yYXpMIZioxn9YieKf5t4hPuuu3douJAw8xanY5TFzAN3dqBkwXwlX5CvvXOXdXFTpb7z4D4CmE/vSql394sjiOMiVOrHNsHR4ePkGqPVLE2pj0HcmlTf5zSl3qsuLsVtuKBKXbHjkqyFo0J9AADmcDSCUqjjmtm6eBVY3FJ1cQni5QgIU+l0/RkikMu6OK6QCty0uA2fNlPqkNTFjZS6AvhsXVy+brLxTF1cYLAGch84DUVaPVCgVTDS5wxT7Jh+XySlnq2LG+CXqYsTglgdsjSljkDtaRAtGPX0hGlnU+qZur5eJ8PEZWQ1WLoIgsicxQeUMnH5hAR8jjVLsWSZuN6PyzGlj2t7wDWIixclazeZePLdVCCbgLJO74MLHMHbPJ4rbwAkkKubAQR/8Z3oDeLmuTrqWCK7gIu4G0jOpL8H5jaLbI+lCO44sUMo5cwVNwripiHkMSssfNPAaTGmTpvqmwbms7jUYjS9aTh22TIN5w3o8gNZXP2u0++LgfrsfLSLRfQOx3Eavuf9YbXiHMJBqgyAODijnILTaEcfDCn712jnWiRkb33Ignl/V7Jd68pFoLvV7OBWpVJXdXE8t4XYeDzvkU1i8KDuF1+qLo7rjsJwTbNxJX5bpF9c4EAJW8wkG9cK9WxKfWmVulCotwAqFcSVbKuZbjNDEMd0uqiHq7o4Hh9T6gjkeTYua+nZdDoK2ngrJELZlkuniyfybLwIEHRA1MwR0HWavXdKXbJxFMSFIdbGw6xwLqlVZ8VtOtUu2TWm0oHI+rhk41oUJ9bTII0pdZUmF1DLiABVN5dS52I9uchUuAcRp0RiuKdAXFp1yLU0KGs2nk+ny/3J/aSPE7DMsfHkeXECQCSOegAC+FNAzmQRNPCCZOMJ+jooidJgn0vfIxtHoHXkMcRDDrJEsNiyEFD3C/pXYHt508BjvFHgkRtjpsFlPOYUqL5p4IzHbhGomWlY7KYhGgjjG18c6+zbR3SAz/9nbzmgHjaDmxgB38kx9WYz2sWwpY2QRtH1dpdLzlH5hQXSiej7gzj+GHEJ94iztzrgJcw85HQsZjEjlpmf/wdot7y4EXj1Jjetie9Tzm1pv7h0b5M/VNq5DR9vPAtEKNRVq9nRWWTickkEbl394qMAawDoS1Oi1Uym1R0iW82wzUyL3dJ+8XyrGYI4at2qJSAw31C94SmIi++hIXDDdHoVKtBUdXHxulkbx1S5ro+rtjIE8qZoJcOlJNLp0MG0u6yLi31g25h4Lm01S9vMpLgNW84KhgBOi95kSl0L4kIiauIhqtUBAiV6Y0b6XLPxvLhNitrSunjCTgUTxwVBOa19eyrNrlm5ADms1Rvry+dQvKbAOamLE1GrTs5Bg3mSUs8ycQR8AacJyMm6uGbimqkLhqwBHpE/BjCBUdTFXQ/iKFt2dQ7nAAAgAElEQVQXT1Pk5nEhTY9rUV7C+PV66qZBoL0r0u0uuJJIqzQ8dxBnVCZBgTyepyDvXB4DAVzjawbI+2TXC36JXwfbF1znyAfWVp7YvZtgg9iFL8sBddqMb4oKVNTUa65Mv3seVBvNeFfM+e2EkGah6Pyx6zjPs4D+dMDYR7A1zQHyhVLN/ZruM6cOHaMcmAN8tuzZNPuFf4p2D+cbAfP6lzXxfUT4r2LPeEalvh3aStwmgFqYvkiBm9kvbrq39Wozw7r4yRyI436EQn0m7RcXoG6k1DUTx9S6eA1bzQzAztTFu1TqQLRCncWyzUwvTCnTTXFbUgs3VOomExfHXaBffCGVeq+6uABMJWbLi9vEMRZTqReLwDshKYp6uQnaWEPvVqlroDbr4uL4Kl2f1spTFg9C4OaBJ/bXQ2AnmLyuh6fitpSNpyn1hImjeC2MhYJdArpiwhlxm6qF90qpJ0xZpciNGrr4TDUb13VulVLP1MUjKmvgCozlI50RcCEBcZP1G3VxjbNYh0dgT7MM5/stfP1t5zpuTHjnBwfuG3lJv/uLAujiGlhG+h1BnReITxhPQN0hUOtE9I848Ns5J03HhW9zBh8AvOEF+GLRc77hFKCFDnAdC+avv6v3qnvHnMh+cdkrjkAuWs2E8YvZaqbr4vI5DeIypS5y6qDZeJ6J42tpv7isi5spdc3E0YJV9osbrWaDg8AmpbgNF2n8Ik1f0pR6TbyWcW5D6l3Vzm0oc6tAI24TTKfjYqbUUzMXCe6YUZPrBCK9nu0XN+viCtxU6lz8fqht8TEK3FLTF6yFY0+4YuCGwE0zcbFNMZdSF//u0S+OK4qaeUjSfnHFNrF7TAnWUsGZTJtj37hMpS+WUldAjqr0gqfazCSjz6vfsd0sn1KXEfbAdalsR1P/1kxcxEmnu8XNgZFSF/1pqn0N98FBpvHV+qIPOFkkkOdT6vplZNZJfdvMIuDxBNvGBVPqSrAmxGsI8JKhyxPJ1uBxnxrEu1Lqy2XR+ZT663B7x2XzxdLAdx/Zq/yc1Id30QBdXGzLAHXSiW9iBeI7EQ8qnidtYgnUOENQJ7fjLRvOMycOfIFwR3qzU4g7QMdw4qpL+Gyh6h3yebcDnO0zT7+69tHFi4Dpo457FWwc6+L7Uve2XsNQcF0Ect1qlvqoL1UXVzXxKQDp3mbUxYeHQbLxHIgH0nZVu7clKfWoQdLU+cL2q7glWrDi0tVqhkxcKNS1/WoK4mj8ItrKhNGL2DqbUo8Jkel0XHR6PCC+SqVnQVyugyl1My2umTg+p3A522pmgLr4PcL1ZMu5UKFLvbpm42m/uF7XTKfjc5hSRyAW5XEj3Z41iVHA68oWL71ELJ9Sl0xc3jCkqXLRFiZU6iaIi6PnWs00E5cMWh8nBWUE8bQ2n281E3HUWW99s6CYOFWqdhPERfocmX+iXsdnXIhVSj1pdesB4jqeiP94Y6EBvPucF/luLhek87t6DW/vOO7LDp/4wYH73oKXZma5qIAuPsgLAPXYAR8cKHsc0F7jdmDwF7wIXycAaMHE5i2YL/INsC9dmgiY7m2pcxseq6cFq0qpbzx7VNTEUaUezx8TbFwOQ1nauQ37xXE9XRNH97ZBVReXA1Gypi+4riluE85tpQYB0WumfdRzIC6YOG6pW82U8jhuE+3cJvar6uG9QFwzcW38YoK4TKerfvFWkAjZBKTmLFjFcZSjG7LxXv3iCRsvLtUv3i1u63Jvwxp3V+uYTodLNp7Uz1XtO21LM4RuwhRGoqTsF8+BuHhjKq6JwM0Dl0mzGMFqe6nUlTmMBEatBDcEYmobPMeMSh3PdZF+cf390CDbrVJXmQrdaiY20Cp1CcwI5K5SrosbgHxbm66dG+I2sdliKvV+RWy4o17rvk62x2hzzp944j8PHF7ot+6iA/pyQd2N4htJgfhuxIOi652KCPhuAYougbcyCo8ELtBCCyB06TjjwD3CZ4ll5pcGu+xe0wgIcZtMqct0umw1y4I4/sgegPZMWdivCrBWw1A0iONzmalm6KPeOC2+d6b9qjZ9Qee2vLgNuoahDIpjSRBH+1UiWs7EY1EXrwHzpf2qfA4f61az1PQFW820uK2rLi4YtcnEUx91ZOICxAuEdDr41xC39aiLa/tVAebKRz0FcQVahkJdsHOaFbctplCXwKcAD+viqk2tq2Yt6tgGu01MX2SrWdbZLe0lT1PmarCEgnDTvW1h0xfzmCqdrqmyvllAxr1YXVyDvlLCI6NPxG1Uic/ydXETRPP94ur8tepcsncXIKmLpyAuVhVpdvlcptUMgZ0CcEJJcpMg1klNZ5b8SVkOGPfa2etke9dx2oTT7x24b0B7Q/UM7SUB9OWCOqbfwSPFIuPtUsF7JZIySUd6FIDTiukGHDZFGJ8rDNo0+5JfErvCeUVApNRf/Ubs3i3ni+u6eLePOigQx8PoiWapexuavrwMAKhSTwai9PRRHwWcaGaCuGTjipWpuniX6Qse1jR+UWxcp9R7i9vQ8EXXUeVUMwGqOYX6YqYvwsUtY8GadW8TrWYoRVe1cV0X1z7qBc8YhqLBVFmt4rmgU5tg04ZKHYFcCtukbL1XXVx7r6O4TbJx5Z+etJrh9pFhrCJd3YS1qmnPqsxdTJV6L9MXPNcu4xclbktT6oZa3CUkjtGIrbvVLJsKz7NxXRfXJiuS2Yvja8ZrtIYJIZqpatf94g6QmGIJQdnBmjdAifAtm1KX5i+6Lp7tFxe/73njF6yp4/ER4I00ffJF7DcFbhbazX7z1/H2xIUzQ53aw/v/u3A/XnS5ZIC+HFCfbkA9ZrCFMvCLLjR8Di/HRKR4iozAtYyjMRHMQQ0O1yA7AhWnptma+VIfs319oQjoujgYo0kX6heXTLwbxMW+e6TUF/NRX6hfvEvcBikbr4byh1WL2wQgJ2r0/vrFdRwScVuiUE/ZuE9B+qerdLtOqWufddOCNX3OqIv7kmHrWnmXj3pi+pKCuAC2Xv3i2nc9UZKnTBzRO/VSz4N4d7+4p0Bci9vEb1RGoS5uKxbtFxfbmP3iife66s1W/eLaR72/fnEB0UpIlvaSSz92afwi3dvUezfZuGLPiaHLAgr1rvNW+0LuhOeKpi8CP9HlzWiNy6TUCfaJu0BFHR3JuQJxtQ/7K3PxI+By8uzPbfjc0/262F1SQO8H1HH0alwAJ2BQbwdwA4+hWHBh3uFwKnZhE2fgEQ7z5RE43GxAODQAVM8zt2B+8S+g18cedV1cMnFclhxNajBxnGr2jFEXRzY+pkaTChBHH3VMqdfToSdZH3Wcajai6uLDYt1sXRyfGeyuiyuFemrBujCIC7Bfwkd9IXFbXz7qPeri4vu+QEp90bo4wqgC1oV81NMBKgtMNVO9371T6r181E27ViPdrn3UkQmrnvDFfdQV2Oq6uEsFG8cUuvRrN8Rt4qJABtu7Li5Feap1rU8fdf19lRapyvRFsNkcG8/UsLMpdQHQprhNAXtyE2CI2/C5vtzb+mHa+uQXq4svpmh/TW/PIyh6jz7xnyonlvObfMkBvR9Qj8vgeG1wwxpU2yHc4HLwHB84pokKAM1iDQ6vLkN0PADqdYD5s8AsmC/nY7briggowWZmopkKTb7VTPeL6zaz3j7qGyBsnhTfoQTIx7KtZsjE8XVdFxe/6YmoDS1YhySg637xHj7q8hR1XTwdhgI1OYpUvm74qCOzzrWZCYA/j37xRNyW81HH3B+K23C/HRoS33Bv690vrll790QzcW45C1btoy7V7Lou3j0MRYLOwlPNMq8lKXVV4zW2Q0V7LOXsffmoy+NqwEb3NqlWN0HcdG5L+8UNlbohftNtZr191Hv1i2tVOwD2cguLdZHulu1sCWPPObdJfNRmMLrNTOTQU+V8Lp2uDWPkV0h5sPf6SXmd1LMX/DW9WO+fkHPDXvWh/X9FGsv95b4sgN4vqNN5cDoOVIpF2Ow4wpKhWa3AkXIV4qkImAXz5X68dn1R7Xt1PKnp3paK2zA+6XxxcyxpGjmpUu9dF08HonQJ3BDBVwPQ9jki54srZbryUc/MFzfEbQKaI0f0itfxH0qlvtQwFABZFzfHkgqgVDPG07GkqbgNU+nCuU20muk2M2MSWuKjbjqxaR/1FAAyKXXB0g3hmWn6IlLkyjs+M19cK8yVQt1oNZOfQzFbF1dtaPozSieapXXx3q1mRrpcD0PBnSj3ti4RncmYlUo98VFXdXFhpKo80GW/uKohJ6NMVd+26d6WS9vrASR5C9Y026CNWtKbgWQYijhezrAmU8Pu4d5mitvECUvRG4rb8J8Ltpq9jhXm4lq7HO/fZceG1z722P7d79TmgMv6Eb9sgL4QqI/vABIcBScugUOnwal4QFo+VHwK4+DAC0ELqDtiwXxZn+rrfmXpo75HzRbHcKSmL/sJgjguaMFq2q/ic1qlLoah9PBRF1PNBrIq9TUwCieRiS/UL95jvrgA29I80XXx1IJVqdRDqVLPmL6IszZZuSluS93bRKuZGEva3S+eaTUzJprpSyZtU5MgjsasbZrtFxfnbowlxdp3vl9ceKf3AHaRUjfq4tmJZmkaPDV96e4XF78lyoJV18W7+sUTH3U5azxh6obpi7ReJdmRp5p1G21mqclMqlLHPm+xvUp1C8OXXiAupPB50xdzIAr0bP3S4C761HmceJzLOnoPcVsOxBMfdSVU62X6okFcM3azX3xZPur64lkOQ70c4LjY7+BVdnzHAeZw+sMD9w09dyE/35cV0BcE9TqQYBCcOqpbz4Kj31BzDPhwDHw+Bm7T7BfyMb8utsUuTcHE8d2K2vjBfWQnjjRT7m3S9AWX7Rkf9QTElY+67hcXAK9r410+6vjqKNBODx/1xPTFTKnPEVbSNfUB5dyG+5DubWarmQZxAZyGBWs5ahHT9EW8ngxD0SzbZM5mOxkhor1M6GTzpi/SFMb0URffVRxraqTUM+5tYu64MY3LYOIibpL4KTMXacG60EQz3eOd+qgbIGxYsJrTyDBFjixcuLjpueKJj3oOxGWgEvc23I8E89TZLaldG4NTsin1tKdc18VTH3U8gDJ+MVrE8il3zcS754v3TqnjoHjMpOuUek/3tiQFnjLxVMhmMPu8e5vyUccz18I48XmaA1EWqoP3+3Nit5fdfkve6PBW3at/95/vJTP9hnah9S47oOdBfdcugD37wRmvAzlZBjJSzE7YmQ6B37kV2CQAn3j1hngX+iSphRCSPL7QQNjtV2IEpLhNp9QFkKt+8R3bJBPPOLcZPuo4DAXXR3Eb/u2eLw4Q9QBx00c9bktx26ouH3WsiUvwTkE87ReXw1AkiIt1wiZZKKWOII7p9OwwFMnGNZsWIVD1cbG/ZL64Sqcjze50O7cJ+p0biGK2msl95VrNchPN9FWjfdTljQAhaJEqHguxmvRoM9m4Vqcj8KcpdWPEaEY9rgDaleCth6Fk7Fkzo0wjAqotDi1YcZHTzJCNq98XI50uz1PX1WXaXI4m7QHiSb+44dwmr0H1W5pvNZM1Z9QDCXads0SV8VsgpZ5LjSfnboC4OHTGvU31iyfCO8OCdQHntszxcYdLApDxW3GVMV1xZivo/B0GpzZfU3t4327RsXnByxUBdHkRpqNX0Q57KwCZ2A/kzh0Ahw/IL8eW7cC/sx9g6yTwiZ0WzC/4036t7CAnbsO3hSl1afqCi1EXRxDHZVt3v3hPC1YF4gIEWgup1LMWrDSQTLyrX3xAgjjuS7i3ZXzU8dn+UurddXFVM1XGL3q+ONqvYl1c94uL71kC9CU1DMV8zociDUgAaMCaKtS7QHyRurg4hmLniULd8FHPp9QFeLto/Cjr4glIZZi4Hhua7xfHbnLsHVf+6BkQz04005d6V784vmC4t+njixYxtF9F5DdYai+TlIx7WzIgJVWoS/e2Xv3iBnirfnHTkEXbrKYzzI1SxgJ1cWH6QhGpu+eLi88mNxBFerArkF9qPKkOYr894Av9vtjt0xnu2ZuNg4/fV5u4mMT0igG6Cer4eA9IEEdzzX375OOdO4HvUS/u2mWZ+WsFj8/rfXAu0jFEubfhPpCNY0pdu7f18lHPTjTDrVIL1nSqWS9xWzpbHLfCsaQC5NGCFVPqoi7eA8hLSvwWzgv3tvxEMxPERT3cRwaeKtTN0aQZ05eedXHT2KUk5p8JJbsxmlSr1LvnixtjSj1C0tGkeghKtwWrGEfakT7quKSjSXVveArupo+6BvE0ZW7YpxrubaaXOjJmafqCixpbukhdXK6mbVULAk7z7m3pMBQ93Qw3khasovyt6tPytynODC+R567U4XoeuQBls9UMCA5DoTF2jZkzv/PDUPA1fdMi1epykIoulxg+6smXxZgv3tWHno4mFQCuQEOn+LVKvasuvhDQ9stw7fa9gXqJ+BHCw4LnPPz9v6qdOq/fwkU2uqKAngf1ft7cxbyb6ed4dp0rGAFk4q9eodq5Tdzk6dGkYiAKEF0Xb68rEzgombj2Uc8PQ5HubblWM/H2xiBuTarvQgrkCOKpj7ruF8+2mgn71Tk0bhuAGQPE04lmuH9zvrgGcXw+FbiVi4S0WgA41cycaCa+Iz0sWPF5NH5JhqGUysCFWj3HxA3nNrEvTMf7AJ2WbDXLK9RxqpmcL949llRgpmLj+BhbzbLObX34qCNId7HxAqC4LYoA+vNRlyl4PY9cp9PlX6Nk18NHHW8aMqNJTftVudfcRDMznS77y3VtXQ9DkWCcN31J1e75qWauErr1dG7DUzBMX0yhmjR0MdPzuVYzsTKav8isc1/94kt9vS27XohdLxU5+Xoufo5Lph1SfejAfaIh5aIvVxzQ9TvSKfiF3qEF8ov+2V/FO5QqdfKqwE1bsKLxS5aJ4+lnR5NKIO8ehoJrLjqadM0o0FbWghW3ybJxQnRK3RS3CVhWaXU9EGVxC9beo0l7s3FT4AZEp9TRyU18eCU5tlTXvROFOgJyYr8qmXjvlHo6mlSDuAZyFKgFLMxMNUtni6d1cbG+Ak5hwSoc4tB+NddKtRATV6NJ8z7q0MXG05R6Opp0gfniIn2eOrfJC10p1DMpdWn60rtfXLNxT5nBmCl17VWunuvDR11UtlXaPE2p9+oXxxXT0aQ6pZ7MF1cfkPij2HhyM2E4ti2pUr+Kv/2v1VNzOX3u+tlvPr5v3y8hzF+S5aoB9Evy7uxOV1AEZL84LqhU18NQUKQ+OZFtNcN10PglXFs0rt/NsGH+GDmWCNxSJt6r1Qz3kXVvS+vlaPwi0+m4qNr44CDALIrc0pQ69ovjGqJnPJlqpoxf0PTlXIvoiWZSoS7ni6cDUVI2qVvNtJe6rovj/vOtZjqlbori8ir1dKKZtGA1FeoShHtPNRNgLJi3cTORazXTIC5MX0IleHNDIm8CIlLEFHky0UwqyU0Bm9g+SanrOeOyLq5fkwAvziajUMeauEiP90ipC+YfyoljcqKZFLel6XTcX+rEZoJeWg4wgNw4hjlffKGUOqYMuBpwkploJtTj3fPIzVq9ad4ip6DpYSi5+eI9UurCglX3kgv/9SW+9ou5r/WTbrfbp6wdQ71EFsPBNYreD374xfKLl/oH2QL6pY6w3f8iEdBMXE41S0BcbWGm1GWrmQRArIuj/SqOJxX94sc2QTCMo0lNEFfubTAGAKeFwA37xc/g908NRDmdmL7IuriuiesTRvc2nVLHYSjVcJ4kPur1VKGepNQzzm24F2TjONGsBeUe7m3C9KVcTvrFTRDHrUVKvdARE81KIqUu37+si6NEHdPxRi1cM/cerWYCsAT26pS6dG6TLeFFKODscQPExXFywG7WpFGl3nMsqQqeZtypWYscSypvBgyQT56Ts8cTEMcHCPqGQl3fSIh1FhhLii+hIA2V372GoaRsXKvUFfoZo0zTdrWYYFpcKtSzbDwZr2oIy9KatewdR/c23WqWqed3ube5ySAU8R4FOJs1eMnGTR/1JSea2VT5RU2VL3mTlP+VU/EnnDVcZ+C7B+4js5cDCiygX44o22NkIqAHoiQ945l+8f1k/pU6SdPpE6I2nrLxPBOXu16qX1wPQ8F1U4EbIXIYSne/OArasL2MohWrcm/Tb6KflDpUK9BsQm/3NhSutVO1eZ6Ni5Q6ptMTcVvWvU2CuAJnBeLd/eKpuE2ARGLy4kOBoso8tWDV4jaBk6Jf3Gw1M9tI0Xo1JDjVTDJxQ3iWq4sjeGNNXLeDLTzVLDu2VPeL441ADBGgj3oXkCdMPD2+rovjunlxm9jeGDhiDjIR88Nz4jYEZhS7JUxc7MBo/0KkFttQzCrJNjddF8+x8QTIDeDH2rb8vXflaFKq6+K9xW1i/2obBHLhux4bTLwfVq0vXttmlmXXGJdLFD/C+AnXrT964D5hmXBZFgvolyXMr/eDZNPpGA3BxnfuBBDiNg3i+Mp2kU4328yQjbcz6fTeII7Ppq1mprjtHAEYERv19lHPmr50gXg+na4+zm7TF5lSb8RtkhW3Kcc24d6mrE9ph2B7GbaZIePuVRdPfNRLJZAzxYVRq3BuQ6Zd9EISxkWO40kzpi8sFGw8YZEG88Z0usKn5LufB/EMgKo2M/mWpZe62Wqm180o1IXwLR1Nmu0X7/ZRN01fdJtZF4iLNL2qdyshm3BR02M+TcA2LVjFTYeR7lb95ujeJhXq4hZAAKYE/rRWnu8Zx5sCmTGQKnUEcYEFQhGfU6jjzgwmLvad6xeXdXF5/ORYqs1MwL2YgmaI23r5qC8HjHr9DNntuwF+OT/XPeJHCHDP5U/+4N6BQ8vZ1cVY1wL6xYii3ccCEejto44r9241S1PqcoeSjQfJfHFDod6jX1yn1LtGk+IwlBmcaJZl4uZEMzyaTKkbXupdPupVYLEahlI1Ws2qFWjMShA3e8ZTG9UUxHWqXKfNhY96l7hNM/Cse5tOuQtoVVPNJJBrcZu0aNNsXKfQ9Xxx7aOO26cCN0MprRXiciIKcFUX16lwAeSSMKc3CwiWyJgDmVLPjCbN9IubbWSyLm56qEuFei7lnswzX0DghkBoTDRL6uMKqDP94gI3Vf3c2Eb0n2vbVuUzL9+hdm8zhGuGC1zWgtVYJwfkGsTF774C+HxK3RS3aXzI1MUT+1b1NVsMhNMdLKvOm3yB7fa93d36LGE4lHegSr73w731ySsBCxbQr0TUX9PH1D7qewi6Csi6OC7YL56mb9FHHZ816+IJiOd81HVtvNd8ceHc1pITzXAZaks2vnC/uJ4vLoEMQRxtX3S/uB6GslC/eG9x21I+6ulAFAR0MV9cTz7L1MXxjBDEZWykj3oaszwTF8CKtW9z0AnarWb6xdMpZ3kfdROYZfSKAsS7fNTxJaVSz4vbdOtYvi6eVa0ri1VXtoxJ8EbRWkGBuLpLwOOIlH/KnHv5qGsQF+eP7Bjfv85WL9Evrk1fRE1cea9nrFJZfh64PhcNyKmPegL6GeZs9IurWeVyClpvcRumz/H4WvaM6XirUF+ZP5Auhym/fu573/v8NXLu0RVYLKBfgaC/Fg8p6uLK9KUvH/VMXRwAe8Zhk2n6YtTFccZ4zrkNfdTzdfEExLvYuBK3icCnPuqmSr2qPNMzFqyL+Kh3ubflRpMKbNL1bSVuy/qo96qLy7q3ACq1LQrXzH7xhI1n6uK6Z1yK27SHpO4ZX8hHHdvMQmTiqi7eBcIL+KindXF5syFYuWK32Xnk6mZEAblYV/SB5+vikq1n5oHnRpNKEMdFt5r1qosrhbpez0ifd/moyyDLNLu6IUjPPTV+wZq1KW5L1scHubp4Yjwjjr9AvzgeS+nwknMSdXE96EVdAP0wZX2xLFYXX0yRbreXEbgI8XMK5NDPj1ef2r2bsCv5+24B/UpGf2UfWwxDEYsB5Ga/OL6k3dt0XRyf0/3imE7Hfx+DTTAuVOpLi9v0MBT0UU/q4tq9TQB52i8Og4PAAsnAccF+cdNHHT3U5RswLFixxi2y6dL0BWviuOTr4vhcOl88O9VMp9MT5zb1OXf1i2cU6tKCFZdsOh2f6dUvnjJv4coms+TC+IVhDR2L6MKCtTulrhXq6TCUhcVtSSuZ6hfXPup4ViKlbYC+fE75qBfEYFHxfkylu25DE+lxsW0+nb6Ij7oYgCLb0uR+5dhPAcxK3CbK0SpjIdu/JIvP1Kl1RiO3rmbJ6XY96uKGj7qYbyLYtQtuZqqZ2k7fMOTsV7Xhi3gPvYahnO/vgq2HX/R6+FIfhetAXKDuo4/8l8rxpda9HK9bQL8cUX5NHSNbF8e3hiCOf3VKPTPVLCdwi5GJLzQMBZn4aYC4nvaEy9Bl3dvwGSFuU7OJEMTxOWn8MijGksrtBpRKfUAMQ5mfB1iKieNWstUMdU9tgniOkN7t3pY1fRGwGxPhpZ5MNVvIvU2cm1Kha4EbGrIoM5jzdW9brC6u2bjpoy5BUdbFs+xcG7ZIcRsuOGxF1sdNH3V8xVCpY6o8Aljc+EUPbckK3DDBIzA51vPFTcbav3sbgnfaama6t6m+bnETYACpVqlroBbp8R6GNYbALRG3iR2h2lxOOtM1/C6BGzJwQQR7+KgvB4StQv2yKdR7/mTn4u8CmS3T9kPf/a+jaEVxVSwW0K+Kj+EqPgllv5o3fdknvPZ3wuSE/NFcCMSTfvEulboUuJl1cQHUaiAKmr6IfwsmjkuqUu9l+iKYONLvAQniiY96pl9cmb6ocEuVunRuw6ek4YsSsOXGkgqjdAHyht0qas5VTzi2nuFkUtkvbliwlkpdE8206Yt2b1tsGEq+N1ybviAbx7YxXRfvxcQF3GpVt1KoCwBWpi/Zung60QzX0T7qibAMgV21oWX6xY10urZgTW4U8IFmwwkbT33UuyeapSCumWtGoZ5j4yhmE6I2xcB7WbAmaXQ0fVFgnjF9MYeamG14Xfarss4tW82kX71/YAkAAAICSURBVHq+Li7et8HGxb+1kK6fVjML7v0z7F7qcuZyWc7QuZZX3SaJq9KI6jn9klg3XQ+3Irx7e8D1xB7x6koXL+av1DcOHNi/W/gWXTWLBfSr5qO46k7kVVEbl8NqjYEo+iwPblWs3HBxw9e2iJnj2+GAWnH7doADBwCuWzdBGmeLpLZqs/iCNM4eTa69tmLtODgF/4dJ+GD2JEHndXPRvebmc1F7khSufxOPGqfJ2szaYxAm/uzyhUjdJCwW6VgNYUnWWSVvKrzWEI8D0+1LrkHDWeKODfK8KU2vY9QCkrhLSGlebhnELIPMLridDZyGmHFQi6waJAvetLjFOpbYCYg7GVxyKy3wRlEA6BZqPBECqvXkc6qvugDqdWmg07XUlUXeAse4HE+7Bbw69Ylc+Am5Hc5piRC3yHkS0kXeiFgPhIFgsujP1fMHxWvnklfUI/XHLQ5x0CkmtY7nDyvwmU628sojHKbwn+L/kqVQWs0BskLqYmVUbH8K01yn5aqF8lhuxPRJ8XyxOm48L7PF/uAG+RzaLcr/g3J9U277o+J5/T3GxwcPTsh1h7ca68pfgPq67bnt94vnR7fu4NiyKhf5YNu2nca6YiwX7Nq1Szxnrb91rBb/awG9vzjZtWwEbARsBGwEbASu6ghYQL+qPx57cjYCNgI2AjYCNgL9ReD/A632QtaUkseeAAAAAElFTkSuQmCC"},37618:function(e){"use strict";e.exports="data:image/png;base64,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"},14760:function(e){"use strict";e.exports="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAcQAAABECAYAAAAfmEVzAAAAAXNSR0IArs4c6QAAGX5JREFUeF7tXWmQXUd1Pqfv8t6bTYs1sixky2AbgyeWsWy8SXINgYQyECpJlVl+EEhsRobYwA+SquQHOElVUkXxg2CXsRTbQJIqFlelKMKShUVlSV6wLG8Zg8sbshVJ1siSRrO99+69fZJz+/bMvH53pudpZKwRp/98fd/pPn1O9+nzTd973zyEeQoRIf4N4I3DgKbZ/QBwY4EAIyP92N8/Qows7e8fpJGRHcjI1yMDO7B/eJAYc/nwCI0M9COj0Wd1MbL2++FGuDFHIzV1xlxfoZuRr3cMDurBHTsUY95+GPD+ASBrrzt+m6s7/l/JICsyEp8+8V/WX+Jf9r/JA5L/lmL+//kXBzNELPinnfwKoitnxRu/S8HwXTtqqy9ZXdrg8DPDsPqSAWDkUut9i54ae1Ex8vVUdUzV6r2aMZcXdcZcXrRl5Guri5GLqz+Ml1HaHEVGlqfL1mE4up8YTYQOA/QPGCwrVsYIALYvY66vGWMYN4nR2LMaDj9zOMeyIv7L+kv8y/6X/Ld08v8ADE/df/+HsnKCAHvyKxcPfuLn1UO6qzsdeS2Je8brbqvm+CGMe9YQI8tsnZGv16/pwX2Hxokx7/v88wAXXmgQAPb1rKH144eQka9dfRddeCE89/zzwJi3L3Qxnox+1347NmOZPXNNmv1c/Jf1l/iX/S/57/TP/83xnmpYPStas2xyYsc33tXGZTanz3tCHPzc48snRpPehCbGahMjDR9B+OSvAMC5AMDIxdYZy8orsB/OhXXAaNqbOuOCCjfjrra5rRt17aXT9gsyYqaR+C/rL/Ev+1/y328+/4/Xu6pdJ1Z1R31dE7u+tuHYXKl7XkJ8z9DweccaOqol+46GyWRytFqnlfUqMrLCtF7FsFonRr5e3Q9weMQgF1tn5GLbMp5Mf75xeZjHKbyxdcYy/a7Trr2uPQBnA8CrYBBgZX0Uj1aXESNfi/+y/hL/sv8l/51c/n4j878KeiOVnrcqiLLGo1+/yv5N0saLcxIiv1Cz6eY9A0lKpCdH94dxQmlzHMO4J8ecgIrnbYxG80qmjQIBXoOjcBaszJHLsmaMo3GTGMv7+45crfpnxjL63WeA1lZGo9naNld78/xwLn/Ef1l/iX/Z/5L/ll7+T5sRVqpd50Icw+57rhye68WaOQlx8BMvVevxiUvCNMvG9b59TCdZcxKDuIsYc4KDZTAKozlysXXGMvl4nFBPM0JGlvc0J3E87iJGQ1ish/suTF/7eLN7A1jdjGY8MzajGc+OZex1x3ftFf9l/SX+Zf9L/lui+V+tX5+GQVBt9j2z4xtvLn2OOCchXnvT8ErQE2+DSI1l9ZcPlJ3dupIIJ6OEGFlu64y+sx7LF9vfHaOrGuFkPSHG3J6izrgQezpts1j7F9tf/G+dAVl/iX/Z/5L/5sr/QfW8tVES9CYq/tVD9w6Y24ROmZMQN3/qqbdgM31zFmWvwsQr9jFdS/epsEq1tI6MLLB1xrxhdzfAxIRB/ppFI6NaJUDGhbSf7ss6TqY443v1ddhe/Jf1l/iX/S/5b2nkf8xW9CsVrqEkfGnXfRte7JQQr0gb6eoUjr+Ieiq/p1iN61hvVonRKGOiY7IyhFdvZlSNA2TM26d1rIdVYszlRZ1xIXLXYKubsWy8VmsAsrSOQVglxlMzvvgv6y/xL/tf8t9SzP9T8Yq+ilpxAULw6q57NjzWESFe88m9N4RA1cbEwSfDPjJfuZjk+5wFlmirdXXB1OQkMOYnwqLOmJ8IPXJXZSUOsNHMiJFljTCjShogY5k9ner3tre+GnfEf1l/iX/Z/yYPSP5rmwFfPvXJX+/8n6ZYCWtv2kCKGg//08YfL5gQb7jtucrY1NgfIwZNjYcfDRKdE1AWKeQ6I1/bupW7A2RpA4OwQoyGEWsAU1MG+Yv4iaY4UsjI13HUwGZSIUajv0JZ1EDGMuOtjLGsvSsH4HGn2JBcnWu/zz+fXPxvnQFZf4l/2f+S/06n/I+w4mrQKuyt9f7bj++4qO279aXPEK/+6MNnR7XaezHUJ5LmoSeqVZPodKpQhZoY+drWGcvlMem0iSqMc3m9XodqtZpjWbEyRqPP9GXMx0s16VAhY96A27Guor2rPw4VNlNNjMbeVnsA2A4ey9hjVVnzHPXiv6y/xL/sf8l/Szj/U9Z3eYphX6qn/uORe67hL523lFJC3LJ1+BLKmpsVpPtDdeJZ26MZEMUZImP+GfNrpUAmsLCJKo2J0RCYqTPmJ8AQsZkSMZYRYis9AaiASGeIjHn/YmxGvnbtceV1aEAVKsB4Mva4Nor/sv4S/7L/Jf8t3fxPwbKLKQvXBRTv3vn1gWcWSIhPvlsTvR0gHQ7w6H7Dev4S6QQTFRFjWWsrYyyTu/3d9lGYYJJGxMj9bZ0xP1HqBJWKiDEnwKLOWDpemz5NUagwsSfQabYX//2rDyDrL/Ev+1/y3+mc/zPqXgcQDijEX+7cdtlPF0SIm7fu/RNA1R+m47uhmhyHpukWxwDNpsH8hFbUGU+qsB7uW+jDLCIKEmRkfZQliEFEjGX6ffbYvowL0ZfbMcue6br4L+sv8S/7X/Lf0s//UF2W6Npm0Hpk130b/9lLiDfe+N3g4PK3fp40KhWP/jDWkOowLU5cIWmdolJhcSJTqJQmrc0zuhk2sQzZyjC2LaM50bX2d58R8rgqDcmOb5hzhrHSVFMYKmRkfWGYYpqGxFhQuMNw89O2b3z2W/yX9Zf4l/1flr8k/9ncfPrm/1SHAWS1DwACrTn67Jfcn4JqO3kNDj27KoX6rQBqrFI79t+YhUSBIRhbZzTUkgBAVGBZOETQhATivA3LTZ0xP3EWdSv3nTIX279df6v9M74Ye9lv8V/WX+Jf9r/kvzMn/081ut8LQL0R1u7Ysf3iI7N5oY0Qrx966tKMso8qpFfCSvKgPZOVkVUYpJhmITEu4IDYpsL2ZcxPeFmKaRASY8GYLbcwVRaSDlJkzP9CCxBVRsRYRtCuftcA135Xv/v3jq+/e4u17Raso0D8N7Ej6y/xL/tf8t9vKv83GtF1RHhuhMG3Hti+4en5CXHrU+/ToN+tVPpUrZI8TRoRVfFW0fRp0JygEkgggijHkgMjRFEESZLkmLcv6oxc2uSnWB/pFFGFxJj/haeI5vOn0/biv6y/xL/sf8l/Syv/19NgQKfRBoXqZw9s2/CjeQlxy9DTn9KUXFIJ1M/iSnO/vanInTIVUqBTZORrW2fMlYb8G0wF8rWtM7bdYHVvUPr7l51SZ3+WKaJAIzLmJ0iNqBQRY07As2wo88c+H2RcSHvx38SCrL/Ev+x/f/6a/wGNv7/kv/lnYKH5n9J4XZLA7wIEz+zcfunX5iXEzUNPfJkIeror2XfDajiRJgmExQnPPUFlGVEQIDLmBFnUGXPC6VDuW/BO9bv6OrWH/Rb/Zf0l/otn6s4dl073k2//yv6ffwZ88+fKJf+1zsB0vDaha6IRfAgRxndtf8fn5yTETX/2q14Ipr6KiM1lPfRN9y8ad4LdE5fvLyCf3NXva79YuW8Div+zX5lqny1Z/5nXyhZyB8QXrxL/rTPgm6/FymX/zz8DZ3L+Gx3HjxNRDFntM7vve9uYnYmWl2q2bN17Sabxr4MwPNDdp74PaQIQRpAjnwAVYqaJGMum0soYy9qfarlrQ6f2tflgfWXkIv7L+kv8y/6X/HfG5f+JyeCDWZquDRT9/c5tG6f/Y00LsV17yxMfCEh9LAzh6d6uaKdLGCkkEEIEjGXFfYRIASJmRIxlt1BdHVY3Y85HzniufvepYHt7Y+vJ6hP/W2dA1l/iX/a/5L8zIf9PjMMWreHSDJN/eejuK35QekLcvPXJz2qgwThWP+2uxcMuISiVodYBMZYRopUxstxt36ncN75Pn9vf196V+8ZfrH7f/PjG9/mzWPt84y9Wv/jfup86jT9Zf5OL5so3i41Pif/WGTiT8v/EVHOg2dTvVoA7dm277B/LCfGWJ+8iytZ3VSvf6qpFh9pPSCmEEEKavz7KL5WaOiMXUimiDokxPxHqkAKVIqNp3/oSqk9/oAAzDcTIba1uRnOCbLXHbW/7MpYRuE+/zz7xX9Zf4l/2v+S/pZf/61PZmno9+Shi8Otdd1/2522EOHg7hemBJ/89Q42rVvbcqRATl1B8hGPJj7GMgFxK9Ol3v7fhEmyn47k2+cbvXG7IX/yX9Zf4L5uB1j+JfftL9n/r99Yk/7UesBaT/zVRdOTo+K0BKQrXXvYHO27H/JQ3TVxX3fzIm0MV36tQHVt1Vvc9ZeFMChE1EWPe2fmiu/3SO6Pp37qgqAMilSHjQvS7bezYjOZEanQxmhNkq36fve73JMuT2MynPn3iv/knDrL+Ev+y/yX/ne75/8irEzcT0YpEN276xT1Xv9RCiNcP7fn9hNQXojD41Vln9XzPRw6GEGd+sDAnKPvjhbr8GWObzjAESFP+r9zF/inq/NnrUDIVUKAzZGT1ts54MsOJ/7L+NuYl/mX/S/4rfrx2ofn0Dc7/x0dG/6iZ6YtjyP7uge1X/lcLIV479NjniNRHuirhzuXLl5k3TJ2Hfp0ueMDPEZl4CraxdcaFEKpLOEpnqFVAjNzf1hkXkpC8+ooXhuxDevG/9aGvrH9nG17iX/a/5L/TN/8fPzK6ZbKZbkHQ335o+xVfaSHE67Y+vo2Iruzp7frO8r7u51iYZfzfZwxy6fStQN+py+pmLBsvZ9J5Isrb32eAI/fpE/87eyvSN/2++Zb1l/iX/T/3icK7f3wb8Lc8/41NTFw0PjbxYUS158Ftl29tJcShx3dq0n39Z5/11TiKj+cESBo1KmLMCatYG3vCcxekvYHniOgsiB2LsWx8N0FqTaQUIqNpj6iRiDFX7RKqJ0C0VqSURkbxX9Zf4l/2v+S/Mzf/1xvpsiOHX/ssghp9cPvlW6YJ8dqbHlypVWVXgNhYt+6cf7C8Mf3TEAUhunwy/QZFQWBthNnGhxkEEECWMyfzlakz5rc8Z72Vkhs3662dUkJ29Hf4B5G3ufhf/NSJrH/pM+ZO49PGusS/7H/Jf6dH/t+//+BfZUQVpRubH7r3uqP5Rt/06Sc2Z83062EY7lu7bs29likQAyLKkNHc02w9IrpveXoZxmng6rdjMS5El0uobsLxv9Xa+pZqO+GL/7L+Ev+y/yX/nan5/8D+Qzelabo+iMM/3X3XO3blxHPd0N5PZaT/slatPLJ6zeof2BObVkRKIzLmJ7hZv6eUn+BIEaFGxjICszLGsvYKNWpSxMhyW2c8GX3uLVJrO2Ou3+OPS7C+9uK/rL/Ev+x/yX8nl69Ph/z/6sHD7683GtcEqL704PaNX8uJ4tqhvXdnOnt/X2/P91b1r/mFPaEFQQBZlgFjfkAs6oz5kb944ca+FNP+0K71SOm+pNNp/zb9jkKN/DVL/tcCxVunxel2xp+ZF4VygnTeKnVPqOK/rL/Ev+x/yX9nbv5/7cihq0ZPjP9hoIIfPrR94y05IV499NiDpLO3rO5ffWfv8mX/i8W/OiMFyHXGshOblc3VnjQQKkDG/IRY1Bnz60K37a/5xRgmqmIwW2fMT6iOPb7x226BOuO93vrEf1l/iX/Z/5L/Tt/8P3Z89E2HRw7fiip48ZHtV1yHVwztiQLKXiFCdcFFF35BQZgEBQNlWkOgFDCa4lCUy1gOo7GeTPPPRpnePn3t7U1f1pGP3uEtVkOtMxRrfWE09rTq79Redzqc4aZtF/9l/SX+Zf9L/pufT96I/K8hjV547vm/ReRvWQfn4rWf2HNpEqQPhEE4cuGFF3+ZUBEWbxXaOmN+oiONs+UuIZgvPJgvPpS1b9M3/SUJ8wyx0/7uW6BKKdBaA2NemMi5XhC6O37bCdLxT/w3sSDrL/Ev+1/y35ma/1947pd/kWZpf5SF1+M1Q498PMmyO2uVrqfOv+Cif0UKiLD436BFnT8r/sZ3volYdiN15jNCQCQgRrOhTJ2xrGen7X3PLP36Wr+oyH6L/7L+Ev+y/02+MntB8t+Znf9fevG5j001JjdEQXwrXrN1z1fTpHlzT++y/zz3vPN/MkMy/D3A1q8dIAISAX/tfY7fQ8xAqQC0Ni/dKAhAQ5ZjfgJEICRAxoIg8zp/lh/oiraMudwzvrWF0ZwwARGBGM34MzdNy8Z327vfK/GN75I6+y3+y/pL/Mv+l/y3dPL/y/te+L3xsdH3hlF8D171yUd2Z2n2TsNAwNTCdFd6gpv/PMiMVPQtCKlN3/T5kAyhTp8fsXw8nz7XIKd9GwHnJs76iY9O9fsmwKdP/J+5ZyDrL/Ev+3/mnlnpLTNPPpX81zoDi8z/QRg8ilfe9OCxTFOfyU/5KSvH4sQ1/Znhy1ZCseQyF3u67V0FdizzLcd2/e3rPdNmIe39/OXoE/9l/SX+Zf9L/vutzP9BgCcW9B9hfMQicpkBmQGZAZkBmYGlPgNCiEt9BcV+mQGZAZkBmYFTMgNCiKdkGkWJzIDMgMyAzMBSnwEhxKW+gmK/zIDMgMyAzMApmQEhxFMyjaJEZkBmQGZAZmCpz4AQ4lJfQbFfZkBmQGZAZuCUzIAQ4imZRlEiMyAzIDMgM7DUZ0AIcamvoNgvMyAzIDMgM3BKZmBeQrz9dlLDw/eHAAMnNxh3G4aZ7rbOeEqKq9AZ0B3fHbPNHo++Tm0W/2X9Jf5l/9v0KfnPxMIbmP8HvnhJejv/qOEcZV5CvOG2h/uOh71h/m9sSsqJ/QB96wAYS8s6AGAZIxdbt+1Z8QkAKAbo6wM4cQKAkYutM5oPirb22tXvyl2jnPHa7HH0uc1ddeK/rL/Ev+x/yX9LJ//3jwbJ9+9721jHhHjDbT+qnGisPrs70QTpsaOVWpMOAMBaAGDkYuuMb0w5BwAOAgAjF1tnNHbOtte1sVP7xX9Zf4l/2f+S/5Ze/k+mYqyEK1YC1GBVzyuHf3zH+xplnDXnCfE9Q8PnNXW9W0EyVps6as5kKwHgaIFcPQqwcqXBsmJljPkBb6KP+rpPICNf2zojX7v6wkofpY0TyLiQ9o55bfZO227tbevgeGF9naO9+C/rL/Ev+1/y39LI/1NTtT4dr+qN08bET7Zf+fKCCXHw08M9aTO7GCsTFIPaF8bHckKaqHdTd3UCGfna1hkXckJ0b4G6t0gXomO+Nq59WXMCg7ibGHNCdW7JtvnTnMCJuJu6i/b5rdxZt3TFf1l/iX/Z/5L/lmb+76quwOakXk/VbgwxeHbHXQPjLp+UEtn1Q09dmmlaHsTpkVQfea1nuhfXWIf5ZBzGoQd6cuRi64xcpqKMakmAjHxt64xGpdVl+k9FNaolU8ho2ps6YxkRtvZuH9/V367D589sb42H4r+sv8S/7H/Jf0sz/2u16qykGa4ihccf2L7haS8hDn7u8eVZHa9WRLorbvxSB2EGMDnHwawLjIyRi63b9p3K3WFa9XVDF0zAJDBysXVGUxY73vzjt09Cp+P55kf8b50BWf+ZmIY87iX+Zf9L/jv5/K+yNJhsVt6uEVVQpUd2fOXy47NzTtvJ6123/M+mVCf9kcIDYVfzYI1PbkUPW2c0pfWTKZiCGtSAsV1q9LTqM225D5dO+7v0EacKm6EmRpYFoaYsVcho9LeO7/Z3/Wu3d0aH+C/rL/Ev+392Rug0f9lcKfnvN5v/j07G54CmtaGKRn5+9+/snpMQt9y2t5+a8J5AhWlvT/YEVmqpTpuowtj8hG+9AVCtGCwrVW4DAIwAoFNEFRIx8rVKiXSIyFjW3coYF9J+2ha2qcQ+rz6fvWFM4r+sv8S/7H/Jf2dO/k8bgZqoNy8HTSHG8JOdd2wcsXzUckLctPXR9yFUzo4j2tdVi15xSatSAWg0ABjLipUx5oXbcd22t/WFyp1B3PG947lGnuLx29QXcyP+y/pL/Mv+l/x3+ub/yank3GaC6ylrvLr7nnf+qI0QN926dy0k6oMKKetb2ftQrHRWTnvzfRoDQBMAGLnYOiMXn9xlwBig0QSoFPpcQlus/k7t8U6Izz+fXPxvmQFed1l/iX/Z/2ZbSP6bOWQtkl+aWgUnjo5dqwkDiPT3d9+5Mf966fQJ8Zqtj30YCc6JuysvrF6x7NcsVJpIK0RGvrZ1xjI5RACQAORYUnTGTzKJGMv1J6h0RFolRh5EpLMEGXN1VjcjF+94pi/rKCPkTv0T/00syPpL/Mv+b8+P/nwk+e90yv+Hj42e35xoXEAIBx/edsV3pglx09Ce8zLAjyik9Jxz1j5QicK0nNBcgvEemVoatBGc092S3wyBtTZw+7vtfXLXWp89bnuffb7Z8I3n0+/zzycX/+ePJ9/6+dbH11/W3/kDV/Z/ywz44su3v31y2f+tM5BoDA4ePHS9JgoDoG/v3n7ly/nJadPWvTelpNf2dHc9t3bN2ufnOoC5BzRfAvDJ3QOeT7+vvU/u2uNr75P7/PPJO9Xva++Ti/+tM+CbL5/ct74+eaf6fe19cll/Wf/ZM+CLF5/cF98+eaf6fe198rL4P3DgwAXjU5NvDVEd2L1t47143W17Lsim9Me5sQYNClSOpqj8U4Pulc9dv9xqLh9tZuRpOWWoMSBFmbkFigEB1xkXUFz/rK+M4r+sv8S/7H/Jf7+9+T+oqW/iNUO/+EyWJm/c/+eeRWQ+glwA5y3pJuL/zB9dr8cfYKd7cMj6y/rbI4jE/6k/gPn2fxBGB/4P6mOrmSKfLqoAAAAASUVORK5CYII="},87620:function(e){"use strict";e.exports="data:image/png;base64,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"},31537:function(e){"use strict";e.exports="data:image/png;base64,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"},46058:function(e){"use strict";e.exports="data:image/png;base64,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"},71190:function(e){"use strict";e.exports="data:image/png;base64,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"},51889:function(e){"use strict";e.exports="data:image/png;base64,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"},95754:function(e){"use strict";e.exports="data:image/png;base64,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"},9490:function(e){"use strict";e.exports="data:image/png;base64,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"},82670:function(e){"use strict";e.exports="data:image/png;base64,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"},61834:function(e){"use strict";e.exports="data:image/png;base64,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"},8451:function(e){"use strict";e.exports="data:image/png;base64,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"},71463:function(e){"use strict";e.exports="data:image/png;base64,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"},73099:function(e){"use strict";e.exports="data:image/png;base64,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"},39633:function(e){"use strict";e.exports="data:image/png;base64,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"},31434:function(e){"use strict";e.exports="data:image/png;base64,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"},16065:function(e){"use strict";e.exports="data:image/png;base64,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"},69035:function(e){"use strict";e.exports="data:image/png;base64,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"},40181:function(e){"use strict";e.exports="data:image/png;base64,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"},81535:function(e){"use strict";e.exports="data:image/png;base64,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"},64813:function(e){"use strict";e.exports="data:image/png;base64,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"},362:function(e){"use strict";e.exports="data:image/png;base64,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"},16033:function(e){"use strict";e.exports="data:image/png;base64,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"},26358:function(e){"use 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",Oe="data:image/png;base64,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",ze="data:image/png;base64,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e.x===this.x&&e.y===this.y}fromArray(e,t=0){return this.x=e[t],this.y=e[t+1],this}toArray(e=[],t=0){return e[t]=this.x,e[t+1]=this.y,e}fromBufferAttribute(e,t){return this.x=e.getX(t),this.y=e.getY(t),this}rotateAround(e,t){const n=Math.cos(t),i=Math.sin(t),r=this.x-e.x,s=this.y-e.y;return this.x=r*n-s*i+e.x,this.y=r*i+s*n+e.y,this}random(){return this.x=Math.random(),this.y=Math.random(),this}*[Symbol.iterator](){yield this.x,yield this.y}}class Ms{constructor(e=0,t=0,n=0,i=1){this.isQuaternion=!0,this._x=e,this._y=t,this._z=n,this._w=i}static slerpFlat(e,t,n,i,r,s,o){let a=n[i+0],l=n[i+1],u=n[i+2],c=n[i+3];const d=r[s+0],h=r[s+1],f=r[s+2],p=r[s+3];if(0===o)return e[t+0]=a,e[t+1]=l,e[t+2]=u,void(e[t+3]=c);if(1===o)return e[t+0]=d,e[t+1]=h,e[t+2]=f,void(e[t+3]=p);if(c!==p||a!==d||l!==h||u!==f){let e=1-o;const t=a*d+l*h+u*f+c*p,n=t>=0?1:-1,i=1-t*t;if(i>Number.EPSILON){const r=Math.sqrt(i),s=Math.atan2(r,t*n);e=Math.sin(e*s)/r,o=Math.sin(o*s)/r}const r=o*n;if(a=a*e+d*r,l=l*e+h*r,u=u*e+f*r,c=c*e+p*r,e===1-o){const e=1/Math.sqrt(a*a+l*l+u*u+c*c);a*=e,l*=e,u*=e,c*=e}}e[t]=a,e[t+1]=l,e[t+2]=u,e[t+3]=c}static multiplyQuaternionsFlat(e,t,n,i,r,s){const o=n[i],a=n[i+1],l=n[i+2],u=n[i+3],c=r[s],d=r[s+1],h=r[s+2],f=r[s+3];return e[t]=o*f+u*c+a*h-l*d,e[t+1]=a*f+u*d+l*c-o*h,e[t+2]=l*f+u*h+o*d-a*c,e[t+3]=u*f-o*c-a*d-l*h,e}get x(){return this._x}set x(e){this._x=e,this._onChangeCallback()}get y(){return this._y}set y(e){this._y=e,this._onChangeCallback()}get z(){return this._z}set z(e){this._z=e,this._onChangeCallback()}get w(){return this._w}set w(e){this._w=e,this._onChangeCallback()}set(e,t,n,i){return this._x=e,this._y=t,this._z=n,this._w=i,this._onChangeCallback(),this}clone(){return new this.constructor(this._x,this._y,this._z,this._w)}copy(e){return this._x=e.x,this._y=e.y,this._z=e.z,this._w=e.w,this._onChangeCallback(),this}setFromEuler(e,t=!0){const n=e._x,i=e._y,r=e._z,s=e._order,o=Math.cos,a=Math.sin,l=o(n/2),u=o(i/2),c=o(r/2),d=a(n/2),h=a(i/2),f=a(r/2);switch(s){case"XYZ":this._x=d*u*c+l*h*f,this._y=l*h*c-d*u*f,this._z=l*u*f+d*h*c,this._w=l*u*c-d*h*f;break;case"YXZ":this._x=d*u*c+l*h*f,this._y=l*h*c-d*u*f,this._z=l*u*f-d*h*c,this._w=l*u*c+d*h*f;break;case"ZXY":this._x=d*u*c-l*h*f,this._y=l*h*c+d*u*f,this._z=l*u*f+d*h*c,this._w=l*u*c-d*h*f;break;case"ZYX":this._x=d*u*c-l*h*f,this._y=l*h*c+d*u*f,this._z=l*u*f-d*h*c,this._w=l*u*c+d*h*f;break;case"YZX":this._x=d*u*c+l*h*f,this._y=l*h*c+d*u*f,this._z=l*u*f-d*h*c,this._w=l*u*c-d*h*f;break;case"XZY":this._x=d*u*c-l*h*f,this._y=l*h*c-d*u*f,this._z=l*u*f+d*h*c,this._w=l*u*c+d*h*f;break;default:console.warn("THREE.Quaternion: .setFromEuler() encountered an unknown order: "+s)}return!0===t&&this._onChangeCallback(),this}setFromAxisAngle(e,t){const n=t/2,i=Math.sin(n);return this._x=e.x*i,this._y=e.y*i,this._z=e.z*i,this._w=Math.cos(n),this._onChangeCallback(),this}setFromRotationMatrix(e){const t=e.elements,n=t[0],i=t[4],r=t[8],s=t[1],o=t[5],a=t[9],l=t[2],u=t[6],c=t[10],d=n+o+c;if(d>0){const e=.5/Math.sqrt(d+1);this._w=.25/e,this._x=(u-a)*e,this._y=(r-l)*e,this._z=(s-i)*e}else if(n>o&&n>c){const e=2*Math.sqrt(1+n-o-c);this._w=(u-a)/e,this._x=.25*e,this._y=(i+s)/e,this._z=(r+l)/e}else if(o>c){const e=2*Math.sqrt(1+o-n-c);this._w=(r-l)/e,this._x=(i+s)/e,this._y=.25*e,this._z=(a+u)/e}else{const e=2*Math.sqrt(1+c-n-o);this._w=(s-i)/e,this._x=(r+l)/e,this._y=(a+u)/e,this._z=.25*e}return this._onChangeCallback(),this}setFromUnitVectors(e,t){let n=e.dot(t)+1;return n<1e-8?(n=0,Math.abs(e.x)>Math.abs(e.z)?(this._x=-e.y,this._y=e.x,this._z=0,this._w=n):(this._x=0,this._y=-e.z,this._z=e.y,this._w=n)):(this._x=e.y*t.z-e.z*t.y,this._y=e.z*t.x-e.x*t.z,this._z=e.x*t.y-e.y*t.x,this._w=n),this.normalize()}angleTo(e){return 2*Math.acos(Math.abs(vs(this.dot(e),-1,1)))}rotateTowards(e,t){const n=this.angleTo(e);if(0===n)return this;const i=Math.min(1,t/n);return this.slerp(e,i),this}identity(){return this.set(0,0,0,1)}invert(){return this.conjugate()}conjugate(){return this._x*=-1,this._y*=-1,this._z*=-1,this._onChangeCallback(),this}dot(e){return this._x*e._x+this._y*e._y+this._z*e._z+this._w*e._w}lengthSq(){return this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w}length(){return Math.sqrt(this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w)}normalize(){let e=this.length();return 0===e?(this._x=0,this._y=0,this._z=0,this._w=1):(e=1/e,this._x=this._x*e,this._y=this._y*e,this._z=this._z*e,this._w=this._w*e),this._onChangeCallback(),this}multiply(e){return this.multiplyQuaternions(this,e)}premultiply(e){return this.multiplyQuaternions(e,this)}multiplyQuaternions(e,t){const n=e._x,i=e._y,r=e._z,s=e._w,o=t._x,a=t._y,l=t._z,u=t._w;return this._x=n*u+s*o+i*l-r*a,this._y=i*u+s*a+r*o-n*l,this._z=r*u+s*l+n*a-i*o,this._w=s*u-n*o-i*a-r*l,this._onChangeCallback(),this}slerp(e,t){if(0===t)return this;if(1===t)return this.copy(e);const n=this._x,i=this._y,r=this._z,s=this._w;let o=s*e._w+n*e._x+i*e._y+r*e._z;if(o<0?(this._w=-e._w,this._x=-e._x,this._y=-e._y,this._z=-e._z,o=-o):this.copy(e),o>=1)return this._w=s,this._x=n,this._y=i,this._z=r,this;const a=1-o*o;if(a<=Number.EPSILON){const e=1-t;return this._w=e*s+t*this._w,this._x=e*n+t*this._x,this._y=e*i+t*this._y,this._z=e*r+t*this._z,this.normalize(),this}const l=Math.sqrt(a),u=Math.atan2(l,o),c=Math.sin((1-t)*u)/l,d=Math.sin(t*u)/l;return this._w=s*c+this._w*d,this._x=n*c+this._x*d,this._y=i*c+this._y*d,this._z=r*c+this._z*d,this._onChangeCallback(),this}slerpQuaternions(e,t,n){return this.copy(e).slerp(t,n)}random(){const e=2*Math.PI*Math.random(),t=2*Math.PI*Math.random(),n=Math.random(),i=Math.sqrt(1-n),r=Math.sqrt(n);return this.set(i*Math.sin(e),i*Math.cos(e),r*Math.sin(t),r*Math.cos(t))}equals(e){return e._x===this._x&&e._y===this._y&&e._z===this._z&&e._w===this._w}fromArray(e,t=0){return this._x=e[t],this._y=e[t+1],this._z=e[t+2],this._w=e[t+3],this._onChangeCallback(),this}toArray(e=[],t=0){return e[t]=this._x,e[t+1]=this._y,e[t+2]=this._z,e[t+3]=this._w,e}fromBufferAttribute(e,t){return this._x=e.getX(t),this._y=e.getY(t),this._z=e.getZ(t),this._w=e.getW(t),this._onChangeCallback(),this}toJSON(){return this.toArray()}_onChange(e){return this._onChangeCallback=e,this}_onChangeCallback(){}*[Symbol.iterator](){yield this._x,yield this._y,yield this._z,yield this._w}}class Es{constructor(e=0,t=0,n=0){Es.prototype.isVector3=!0,this.x=e,this.y=t,this.z=n}set(e,t,n){return void 0===n&&(n=this.z),this.x=e,this.y=t,this.z=n,this}setScalar(e){return this.x=e,this.y=e,this.z=e,this}setX(e){return this.x=e,this}setY(e){return this.y=e,this}setZ(e){return this.z=e,this}setComponent(e,t){switch(e){case 0:this.x=t;break;case 1:this.y=t;break;case 2:this.z=t;break;default:throw new Error("index is out of range: "+e)}return this}getComponent(e){switch(e){case 0:return this.x;case 1:return this.y;case 2:return this.z;default:throw new Error("index is out of range: "+e)}}clone(){return new this.constructor(this.x,this.y,this.z)}copy(e){return this.x=e.x,this.y=e.y,this.z=e.z,this}add(e){return this.x+=e.x,this.y+=e.y,this.z+=e.z,this}addScalar(e){return this.x+=e,this.y+=e,this.z+=e,this}addVectors(e,t){return this.x=e.x+t.x,this.y=e.y+t.y,this.z=e.z+t.z,this}addScaledVector(e,t){return this.x+=e.x*t,this.y+=e.y*t,this.z+=e.z*t,this}sub(e){return this.x-=e.x,this.y-=e.y,this.z-=e.z,this}subScalar(e){return this.x-=e,this.y-=e,this.z-=e,this}subVectors(e,t){return this.x=e.x-t.x,this.y=e.y-t.y,this.z=e.z-t.z,this}multiply(e){return this.x*=e.x,this.y*=e.y,this.z*=e.z,this}multiplyScalar(e){return this.x*=e,this.y*=e,this.z*=e,this}multiplyVectors(e,t){return this.x=e.x*t.x,this.y=e.y*t.y,this.z=e.z*t.z,this}applyEuler(e){return this.applyQuaternion(Ss.setFromEuler(e))}applyAxisAngle(e,t){return this.applyQuaternion(Ss.setFromAxisAngle(e,t))}applyMatrix3(e){const t=this.x,n=this.y,i=this.z,r=e.elements;return this.x=r[0]*t+r[3]*n+r[6]*i,this.y=r[1]*t+r[4]*n+r[7]*i,this.z=r[2]*t+r[5]*n+r[8]*i,this}applyNormalMatrix(e){return this.applyMatrix3(e).normalize()}applyMatrix4(e){const t=this.x,n=this.y,i=this.z,r=e.elements,s=1/(r[3]*t+r[7]*n+r[11]*i+r[15]);return this.x=(r[0]*t+r[4]*n+r[8]*i+r[12])*s,this.y=(r[1]*t+r[5]*n+r[9]*i+r[13])*s,this.z=(r[2]*t+r[6]*n+r[10]*i+r[14])*s,this}applyQuaternion(e){const t=this.x,n=this.y,i=this.z,r=e.x,s=e.y,o=e.z,a=e.w,l=2*(s*i-o*n),u=2*(o*t-r*i),c=2*(r*n-s*t);return this.x=t+a*l+s*c-o*u,this.y=n+a*u+o*l-r*c,this.z=i+a*c+r*u-s*l,this}project(e){return this.applyMatrix4(e.matrixWorldInverse).applyMatrix4(e.projectionMatrix)}unproject(e){return this.applyMatrix4(e.projectionMatrixInverse).applyMatrix4(e.matrixWorld)}transformDirection(e){const t=this.x,n=this.y,i=this.z,r=e.elements;return this.x=r[0]*t+r[4]*n+r[8]*i,this.y=r[1]*t+r[5]*n+r[9]*i,this.z=r[2]*t+r[6]*n+r[10]*i,this.normalize()}divide(e){return this.x/=e.x,this.y/=e.y,this.z/=e.z,this}divideScalar(e){return this.multiplyScalar(1/e)}min(e){return this.x=Math.min(this.x,e.x),this.y=Math.min(this.y,e.y),this.z=Math.min(this.z,e.z),this}max(e){return this.x=Math.max(this.x,e.x),this.y=Math.max(this.y,e.y),this.z=Math.max(this.z,e.z),this}clamp(e,t){return this.x=vs(this.x,e.x,t.x),this.y=vs(this.y,e.y,t.y),this.z=vs(this.z,e.z,t.z),this}clampScalar(e,t){return this.x=vs(this.x,e,t),this.y=vs(this.y,e,t),this.z=vs(this.z,e,t),this}clampLength(e,t){const n=this.length();return this.divideScalar(n||1).multiplyScalar(vs(n,e,t))}floor(){return this.x=Math.floor(this.x),this.y=Math.floor(this.y),this.z=Math.floor(this.z),this}ceil(){return this.x=Math.ceil(this.x),this.y=Math.ceil(this.y),this.z=Math.ceil(this.z),this}round(){return this.x=Math.round(this.x),this.y=Math.round(this.y),this.z=Math.round(this.z),this}roundToZero(){return this.x=Math.trunc(this.x),this.y=Math.trunc(this.y),this.z=Math.trunc(this.z),this}negate(){return this.x=-this.x,this.y=-this.y,this.z=-this.z,this}dot(e){return this.x*e.x+this.y*e.y+this.z*e.z}lengthSq(){return this.x*this.x+this.y*this.y+this.z*this.z}length(){return Math.sqrt(this.x*this.x+this.y*this.y+this.z*this.z)}manhattanLength(){return Math.abs(this.x)+Math.abs(this.y)+Math.abs(this.z)}normalize(){return this.divideScalar(this.length()||1)}setLength(e){return this.normalize().multiplyScalar(e)}lerp(e,t){return this.x+=(e.x-this.x)*t,this.y+=(e.y-this.y)*t,this.z+=(e.z-this.z)*t,this}lerpVectors(e,t,n){return this.x=e.x+(t.x-e.x)*n,this.y=e.y+(t.y-e.y)*n,this.z=e.z+(t.z-e.z)*n,this}cross(e){return this.crossVectors(this,e)}crossVectors(e,t){const n=e.x,i=e.y,r=e.z,s=t.x,o=t.y,a=t.z;return this.x=i*a-r*o,this.y=r*s-n*a,this.z=n*o-i*s,this}projectOnVector(e){const t=e.lengthSq();if(0===t)return this.set(0,0,0);const n=e.dot(this)/t;return this.copy(e).multiplyScalar(n)}projectOnPlane(e){return Ts.copy(this).projectOnVector(e),this.sub(Ts)}reflect(e){return this.sub(Ts.copy(e).multiplyScalar(2*this.dot(e)))}angleTo(e){const t=Math.sqrt(this.lengthSq()*e.lengthSq());if(0===t)return Math.PI/2;const n=this.dot(e)/t;return Math.acos(vs(n,-1,1))}distanceTo(e){return Math.sqrt(this.distanceToSquared(e))}distanceToSquared(e){const t=this.x-e.x,n=this.y-e.y,i=this.z-e.z;return t*t+n*n+i*i}manhattanDistanceTo(e){return Math.abs(this.x-e.x)+Math.abs(this.y-e.y)+Math.abs(this.z-e.z)}setFromSpherical(e){return this.setFromSphericalCoords(e.radius,e.phi,e.theta)}setFromSphericalCoords(e,t,n){const i=Math.sin(t)*e;return this.x=i*Math.sin(n),this.y=Math.cos(t)*e,this.z=i*Math.cos(n),this}setFromCylindrical(e){return this.setFromCylindricalCoords(e.radius,e.theta,e.y)}setFromCylindricalCoords(e,t,n){return this.x=e*Math.sin(t),this.y=n,this.z=e*Math.cos(t),this}setFromMatrixPosition(e){const t=e.elements;return this.x=t[12],this.y=t[13],this.z=t[14],this}setFromMatrixScale(e){const t=this.setFromMatrixColumn(e,0).length(),n=this.setFromMatrixColumn(e,1).length(),i=this.setFromMatrixColumn(e,2).length();return this.x=t,this.y=n,this.z=i,this}setFromMatrixColumn(e,t){return this.fromArray(e.elements,4*t)}setFromMatrix3Column(e,t){return this.fromArray(e.elements,3*t)}setFromEuler(e){return this.x=e._x,this.y=e._y,this.z=e._z,this}setFromColor(e){return this.x=e.r,this.y=e.g,this.z=e.b,this}equals(e){return e.x===this.x&&e.y===this.y&&e.z===this.z}fromArray(e,t=0){return this.x=e[t],this.y=e[t+1],this.z=e[t+2],this}toArray(e=[],t=0){return e[t]=this.x,e[t+1]=this.y,e[t+2]=this.z,e}fromBufferAttribute(e,t){return this.x=e.getX(t),this.y=e.getY(t),this.z=e.getZ(t),this}random(){return this.x=Math.random(),this.y=Math.random(),this.z=Math.random(),this}randomDirection(){const e=Math.random()*Math.PI*2,t=2*Math.random()-1,n=Math.sqrt(1-t*t);return this.x=n*Math.cos(e),this.y=t,this.z=n*Math.sin(e),this}*[Symbol.iterator](){yield this.x,yield this.y,yield this.z}}const Ts=new Es,Ss=new Ms;class Ps{constructor(e,t,n,i,r,s,o,a,l){Ps.prototype.isMatrix3=!0,this.elements=[1,0,0,0,1,0,0,0,1],void 0!==e&&this.set(e,t,n,i,r,s,o,a,l)}set(e,t,n,i,r,s,o,a,l){const u=this.elements;return u[0]=e,u[1]=i,u[2]=o,u[3]=t,u[4]=r,u[5]=a,u[6]=n,u[7]=s,u[8]=l,this}identity(){return this.set(1,0,0,0,1,0,0,0,1),this}copy(e){const t=this.elements,n=e.elements;return t[0]=n[0],t[1]=n[1],t[2]=n[2],t[3]=n[3],t[4]=n[4],t[5]=n[5],t[6]=n[6],t[7]=n[7],t[8]=n[8],this}extractBasis(e,t,n){return e.setFromMatrix3Column(this,0),t.setFromMatrix3Column(this,1),n.setFromMatrix3Column(this,2),this}setFromMatrix4(e){const t=e.elements;return this.set(t[0],t[4],t[8],t[1],t[5],t[9],t[2],t[6],t[10]),this}multiply(e){return this.multiplyMatrices(this,e)}premultiply(e){return this.multiplyMatrices(e,this)}multiplyMatrices(e,t){const n=e.elements,i=t.elements,r=this.elements,s=n[0],o=n[3],a=n[6],l=n[1],u=n[4],c=n[7],d=n[2],h=n[5],f=n[8],p=i[0],g=i[3],m=i[6],v=i[1],A=i[4],x=i[7],y=i[2],b=i[5],w=i[8];return r[0]=s*p+o*v+a*y,r[3]=s*g+o*A+a*b,r[6]=s*m+o*x+a*w,r[1]=l*p+u*v+c*y,r[4]=l*g+u*A+c*b,r[7]=l*m+u*x+c*w,r[2]=d*p+h*v+f*y,r[5]=d*g+h*A+f*b,r[8]=d*m+h*x+f*w,this}multiplyScalar(e){const t=this.elements;return t[0]*=e,t[3]*=e,t[6]*=e,t[1]*=e,t[4]*=e,t[7]*=e,t[2]*=e,t[5]*=e,t[8]*=e,this}determinant(){const e=this.elements,t=e[0],n=e[1],i=e[2],r=e[3],s=e[4],o=e[5],a=e[6],l=e[7],u=e[8];return t*s*u-t*o*l-n*r*u+n*o*a+i*r*l-i*s*a}invert(){const e=this.elements,t=e[0],n=e[1],i=e[2],r=e[3],s=e[4],o=e[5],a=e[6],l=e[7],u=e[8],c=u*s-o*l,d=o*a-u*r,h=l*r-s*a,f=t*c+n*d+i*h;if(0===f)return this.set(0,0,0,0,0,0,0,0,0);const p=1/f;return e[0]=c*p,e[1]=(i*l-u*n)*p,e[2]=(o*n-i*s)*p,e[3]=d*p,e[4]=(u*t-i*a)*p,e[5]=(i*r-o*t)*p,e[6]=h*p,e[7]=(n*a-l*t)*p,e[8]=(s*t-n*r)*p,this}transpose(){let e;const t=this.elements;return e=t[1],t[1]=t[3],t[3]=e,e=t[2],t[2]=t[6],t[6]=e,e=t[5],t[5]=t[7],t[7]=e,this}getNormalMatrix(e){return this.setFromMatrix4(e).invert().transpose()}transposeIntoArray(e){const t=this.elements;return e[0]=t[0],e[1]=t[3],e[2]=t[6],e[3]=t[1],e[4]=t[4],e[5]=t[7],e[6]=t[2],e[7]=t[5],e[8]=t[8],this}setUvTransform(e,t,n,i,r,s,o){const a=Math.cos(r),l=Math.sin(r);return this.set(n*a,n*l,-n*(a*s+l*o)+s+e,-i*l,i*a,-i*(-l*s+a*o)+o+t,0,0,1),this}scale(e,t){return this.premultiply(Ns.makeScale(e,t)),this}rotate(e){return this.premultiply(Ns.makeRotation(-e)),this}translate(e,t){return this.premultiply(Ns.makeTranslation(e,t)),this}makeTranslation(e,t){return e.isVector2?this.set(1,0,e.x,0,1,e.y,0,0,1):this.set(1,0,e,0,1,t,0,0,1),this}makeRotation(e){const t=Math.cos(e),n=Math.sin(e);return this.set(t,-n,0,n,t,0,0,0,1),this}makeScale(e,t){return this.set(e,0,0,0,t,0,0,0,1),this}equals(e){const t=this.elements,n=e.elements;for(let e=0;e<9;e++)if(t[e]!==n[e])return!1;return!0}fromArray(e,t=0){for(let n=0;n<9;n++)this.elements[n]=e[n+t];return this}toArray(e=[],t=0){const n=this.elements;return e[t]=n[0],e[t+1]=n[1],e[t+2]=n[2],e[t+3]=n[3],e[t+4]=n[4],e[t+5]=n[5],e[t+6]=n[6],e[t+7]=n[7],e[t+8]=n[8],e}clone(){return(new this.constructor).fromArray(this.elements)}}const Ns=new Ps;function Bs(e){for(let t=e.length-1;t>=0;--t)if(e[t]>=65535)return!0;return!1}Int8Array,Uint8Array,Uint8ClampedArray,Int16Array,Uint16Array,Int32Array,Uint32Array,Float32Array,Float64Array;function Ds(e){return document.createElementNS("http://www.w3.org/1999/xhtml",e)}function Is(){const e=Ds("canvas");return e.style.display="block",e}const Ls={};function js(e){e in Ls||(Ls[e]=!0,console.warn(e))}const Os=(new Ps).set(.4123908,.3575843,.1804808,.212639,.7151687,.0721923,.0193308,.1191948,.9505322),zs=(new Ps).set(3.2409699,-1.5373832,-.4986108,-.9692436,1.8759675,.0415551,.0556301,-.203977,1.0569715);function Rs(){const e={enabled:!0,workingColorSpace:_r,spaces:{},convert:function(e,t,n){return!1!==this.enabled&&t!==n&&t&&n?(this.spaces[t].transfer===es&&(e.r=Fs(e.r),e.g=Fs(e.g),e.b=Fs(e.b)),this.spaces[t].primaries!==this.spaces[n].primaries&&(e.applyMatrix3(this.spaces[t].toXYZ),e.applyMatrix3(this.spaces[n].fromXYZ)),this.spaces[n].transfer===es&&(e.r=Hs(e.r),e.g=Hs(e.g),e.b=Hs(e.b)),e):e},workingToColorSpace:function(e,t){return this.convert(e,this.workingColorSpace,t)},colorSpaceToWorking:function(e,t){return this.convert(e,t,this.workingColorSpace)},getPrimaries:function(e){return this.spaces[e].primaries},getTransfer:function(e){return e===Kr?$r:this.spaces[e].transfer},getToneMappingMode:function(e){return this.spaces[e].outputColorSpaceConfig.toneMappingMode||"standard"},getLuminanceCoefficients:function(e,t=this.workingColorSpace){return e.fromArray(this.spaces[t].luminanceCoefficients)},define:function(e){Object.assign(this.spaces,e)},_getMatrix:function(e,t,n){return e.copy(this.spaces[t].toXYZ).multiply(this.spaces[n].fromXYZ)},_getDrawingBufferColorSpace:function(e){return this.spaces[e].outputColorSpaceConfig.drawingBufferColorSpace},_getUnpackColorSpace:function(e=this.workingColorSpace){return this.spaces[e].workingColorSpaceConfig.unpackColorSpace},fromWorkingColorSpace:function(t,n){return js("THREE.ColorManagement: .fromWorkingColorSpace() has been renamed to .workingToColorSpace()."),e.workingToColorSpace(t,n)},toWorkingColorSpace:function(t,n){return js("THREE.ColorManagement: .toWorkingColorSpace() has been renamed to .colorSpaceToWorking()."),e.colorSpaceToWorking(t,n)}},t=[.64,.33,.3,.6,.15,.06],n=[.2126,.7152,.0722],i=[.3127,.329];return e.define({[_r]:{primaries:t,whitePoint:i,transfer:$r,toXYZ:Os,fromXYZ:zs,luminanceCoefficients:n,workingColorSpaceConfig:{unpackColorSpace:qr},outputColorSpaceConfig:{drawingBufferColorSpace:qr}},[qr]:{primaries:t,whitePoint:i,transfer:es,toXYZ:Os,fromXYZ:zs,luminanceCoefficients:n,outputColorSpaceConfig:{drawingBufferColorSpace:qr}}}),e}const ks=Rs();function Fs(e){return e<.04045?.0773993808*e:Math.pow(.9478672986*e+.0521327014,2.4)}function Hs(e){return e<.0031308?12.92*e:1.055*Math.pow(e,.41666)-.055}let Us;class Xs{static getDataURL(e,t="image/png"){if(/^data:/i.test(e.src))return e.src;if("undefined"==typeof HTMLCanvasElement)return e.src;let n;if(e instanceof HTMLCanvasElement)n=e;else{void 0===Us&&(Us=Ds("canvas")),Us.width=e.width,Us.height=e.height;const t=Us.getContext("2d");e instanceof ImageData?t.putImageData(e,0,0):t.drawImage(e,0,0,e.width,e.height),n=Us}return n.toDataURL(t)}static sRGBToLinear(e){if("undefined"!=typeof HTMLImageElement&&e instanceof HTMLImageElement||"undefined"!=typeof HTMLCanvasElement&&e instanceof HTMLCanvasElement||"undefined"!=typeof ImageBitmap&&e instanceof ImageBitmap){const t=Ds("canvas");t.width=e.width,t.height=e.height;const n=t.getContext("2d");n.drawImage(e,0,0,e.width,e.height);const i=n.getImageData(0,0,e.width,e.height),r=i.data;for(let e=0;e<r.length;e++)r[e]=255*Fs(r[e]/255);return n.putImageData(i,0,0),t}if(e.data){const t=e.data.slice(0);for(let e=0;e<t.length;e++)t instanceof Uint8Array||t instanceof Uint8ClampedArray?t[e]=Math.floor(255*Fs(t[e]/255)):t[e]=Fs(t[e]);return{data:t,width:e.width,height:e.height}}return console.warn("THREE.ImageUtils.sRGBToLinear(): Unsupported image type. No color space conversion applied."),e}}let Gs=0;class Vs{constructor(e=null){this.isSource=!0,Object.defineProperty(this,"id",{value:Gs++}),this.uuid=ms(),this.data=e,this.dataReady=!0,this.version=0}getSize(e){const t=this.data;return"undefined"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement?e.set(t.videoWidth,t.videoHeight,0):t instanceof VideoFrame?e.set(t.displayHeight,t.displayWidth,0):null!==t?e.set(t.width,t.height,t.depth||0):e.set(0,0,0),e}set needsUpdate(e){!0===e&&this.version++}toJSON(e){const t=void 0===e||"string"==typeof e;if(!t&&void 0!==e.images[this.uuid])return e.images[this.uuid];const n={uuid:this.uuid,url:""},i=this.data;if(null!==i){let e;if(Array.isArray(i)){e=[];for(let t=0,n=i.length;t<n;t++)i[t].isDataTexture?e.push(Ws(i[t].image)):e.push(Ws(i[t]))}else e=Ws(i);n.url=e}return t||(e.images[this.uuid]=n),n}}function Ws(e){return"undefined"!=typeof HTMLImageElement&&e instanceof HTMLImageElement||"undefined"!=typeof HTMLCanvasElement&&e instanceof HTMLCanvasElement||"undefined"!=typeof ImageBitmap&&e instanceof ImageBitmap?Xs.getDataURL(e):e.data?{data:Array.from(e.data),width:e.width,height:e.height,type:e.data.constructor.name}:(console.warn("THREE.Texture: Unable to serialize Texture."),{})}let Qs=0;const Zs=new Es;class Ys extends ds{constructor(e=Ys.DEFAULT_IMAGE,t=Ys.DEFAULT_MAPPING,n=1001,i=1001,r=1006,s=1008,o=1023,a=1009,l=Ys.DEFAULT_ANISOTROPY,u=""){super(),this.isTexture=!0,Object.defineProperty(this,"id",{value:Qs++}),this.uuid=ms(),this.name="",this.source=new Vs(e),this.mipmaps=[],this.mapping=t,this.channel=0,this.wrapS=n,this.wrapT=i,this.magFilter=r,this.minFilter=s,this.anisotropy=l,this.format=o,this.internalFormat=null,this.type=a,this.offset=new Cs(0,0),this.repeat=new Cs(1,1),this.center=new Cs(0,0),this.rotation=0,this.matrixAutoUpdate=!0,this.matrix=new Ps,this.generateMipmaps=!0,this.premultiplyAlpha=!1,this.flipY=!0,this.unpackAlignment=4,this.colorSpace=u,this.userData={},this.updateRanges=[],this.version=0,this.onUpdate=null,this.renderTarget=null,this.isRenderTargetTexture=!1,this.isArrayTexture=!!(e&&e.depth&&e.depth>1),this.pmremVersion=0}get width(){return this.source.getSize(Zs).x}get height(){return this.source.getSize(Zs).y}get depth(){return this.source.getSize(Zs).z}get image(){return this.source.data}set image(e=null){this.source.data=e}updateMatrix(){this.matrix.setUvTransform(this.offset.x,this.offset.y,this.repeat.x,this.repeat.y,this.rotation,this.center.x,this.center.y)}addUpdateRange(e,t){this.updateRanges.push({start:e,count:t})}clearUpdateRanges(){this.updateRanges.length=0}clone(){return(new this.constructor).copy(this)}copy(e){return this.name=e.name,this.source=e.source,this.mipmaps=e.mipmaps.slice(0),this.mapping=e.mapping,this.channel=e.channel,this.wrapS=e.wrapS,this.wrapT=e.wrapT,this.magFilter=e.magFilter,this.minFilter=e.minFilter,this.anisotropy=e.anisotropy,this.format=e.format,this.internalFormat=e.internalFormat,this.type=e.type,this.offset.copy(e.offset),this.repeat.copy(e.repeat),this.center.copy(e.center),this.rotation=e.rotation,this.matrixAutoUpdate=e.matrixAutoUpdate,this.matrix.copy(e.matrix),this.generateMipmaps=e.generateMipmaps,this.premultiplyAlpha=e.premultiplyAlpha,this.flipY=e.flipY,this.unpackAlignment=e.unpackAlignment,this.colorSpace=e.colorSpace,this.renderTarget=e.renderTarget,this.isRenderTargetTexture=e.isRenderTargetTexture,this.isArrayTexture=e.isArrayTexture,this.userData=JSON.parse(JSON.stringify(e.userData)),this.needsUpdate=!0,this}setValues(e){for(const t in e){const n=e[t];if(void 0===n){console.warn(`THREE.Texture.setValues(): parameter '${t}' has value of undefined.`);continue}const i=this[t];void 0!==i?i&&n&&i.isVector2&&n.isVector2||i&&n&&i.isVector3&&n.isVector3||i&&n&&i.isMatrix3&&n.isMatrix3?i.copy(n):this[t]=n:console.warn(`THREE.Texture.setValues(): property '${t}' does not exist.`)}}toJSON(e){const t=void 0===e||"string"==typeof e;if(!t&&void 0!==e.textures[this.uuid])return e.textures[this.uuid];const n={metadata:{version:4.7,type:"Texture",generator:"Texture.toJSON"},uuid:this.uuid,name:this.name,image:this.source.toJSON(e).uuid,mapping:this.mapping,channel:this.channel,repeat:[this.repeat.x,this.repeat.y],offset:[this.offset.x,this.offset.y],center:[this.center.x,this.center.y],rotation:this.rotation,wrap:[this.wrapS,this.wrapT],format:this.format,internalFormat:this.internalFormat,type:this.type,colorSpace:this.colorSpace,minFilter:this.minFilter,magFilter:this.magFilter,anisotropy:this.anisotropy,flipY:this.flipY,generateMipmaps:this.generateMipmaps,premultiplyAlpha:this.premultiplyAlpha,unpackAlignment:this.unpackAlignment};return Object.keys(this.userData).length>0&&(n.userData=this.userData),t||(e.textures[this.uuid]=n),n}dispose(){this.dispatchEvent({type:"dispose"})}transformUv(e){if(this.mapping!==Pi)return e;if(e.applyMatrix3(this.matrix),e.x<0||e.x>1)switch(this.wrapS){case ji:e.x=e.x-Math.floor(e.x);break;case Oi:e.x=e.x<0?0:1;break;case zi:1===Math.abs(Math.floor(e.x)%2)?e.x=Math.ceil(e.x)-e.x:e.x=e.x-Math.floor(e.x)}if(e.y<0||e.y>1)switch(this.wrapT){case ji:e.y=e.y-Math.floor(e.y);break;case Oi:e.y=e.y<0?0:1;break;case zi:1===Math.abs(Math.floor(e.y)%2)?e.y=Math.ceil(e.y)-e.y:e.y=e.y-Math.floor(e.y)}return this.flipY&&(e.y=1-e.y),e}set needsUpdate(e){!0===e&&(this.version++,this.source.needsUpdate=!0)}set needsPMREMUpdate(e){!0===e&&this.pmremVersion++}}Ys.DEFAULT_IMAGE=null,Ys.DEFAULT_MAPPING=Pi,Ys.DEFAULT_ANISOTROPY=1;class Js{constructor(e=0,t=0,n=0,i=1){Js.prototype.isVector4=!0,this.x=e,this.y=t,this.z=n,this.w=i}get width(){return this.z}set width(e){this.z=e}get height(){return this.w}set height(e){this.w=e}set(e,t,n,i){return this.x=e,this.y=t,this.z=n,this.w=i,this}setScalar(e){return this.x=e,this.y=e,this.z=e,this.w=e,this}setX(e){return this.x=e,this}setY(e){return this.y=e,this}setZ(e){return this.z=e,this}setW(e){return this.w=e,this}setComponent(e,t){switch(e){case 0:this.x=t;break;case 1:this.y=t;break;case 2:this.z=t;break;case 3:this.w=t;break;default:throw new Error("index is out of range: "+e)}return this}getComponent(e){switch(e){case 0:return this.x;case 1:return this.y;case 2:return this.z;case 3:return this.w;default:throw new Error("index is out of range: "+e)}}clone(){return new this.constructor(this.x,this.y,this.z,this.w)}copy(e){return this.x=e.x,this.y=e.y,this.z=e.z,this.w=void 0!==e.w?e.w:1,this}add(e){return this.x+=e.x,this.y+=e.y,this.z+=e.z,this.w+=e.w,this}addScalar(e){return this.x+=e,this.y+=e,this.z+=e,this.w+=e,this}addVectors(e,t){return this.x=e.x+t.x,this.y=e.y+t.y,this.z=e.z+t.z,this.w=e.w+t.w,this}addScaledVector(e,t){return this.x+=e.x*t,this.y+=e.y*t,this.z+=e.z*t,this.w+=e.w*t,this}sub(e){return this.x-=e.x,this.y-=e.y,this.z-=e.z,this.w-=e.w,this}subScalar(e){return this.x-=e,this.y-=e,this.z-=e,this.w-=e,this}subVectors(e,t){return this.x=e.x-t.x,this.y=e.y-t.y,this.z=e.z-t.z,this.w=e.w-t.w,this}multiply(e){return this.x*=e.x,this.y*=e.y,this.z*=e.z,this.w*=e.w,this}multiplyScalar(e){return this.x*=e,this.y*=e,this.z*=e,this.w*=e,this}applyMatrix4(e){const t=this.x,n=this.y,i=this.z,r=this.w,s=e.elements;return this.x=s[0]*t+s[4]*n+s[8]*i+s[12]*r,this.y=s[1]*t+s[5]*n+s[9]*i+s[13]*r,this.z=s[2]*t+s[6]*n+s[10]*i+s[14]*r,this.w=s[3]*t+s[7]*n+s[11]*i+s[15]*r,this}divide(e){return this.x/=e.x,this.y/=e.y,this.z/=e.z,this.w/=e.w,this}divideScalar(e){return this.multiplyScalar(1/e)}setAxisAngleFromQuaternion(e){this.w=2*Math.acos(e.w);const t=Math.sqrt(1-e.w*e.w);return t<1e-4?(this.x=1,this.y=0,this.z=0):(this.x=e.x/t,this.y=e.y/t,this.z=e.z/t),this}setAxisAngleFromRotationMatrix(e){let t,n,i,r;const s=.01,o=.1,a=e.elements,l=a[0],u=a[4],c=a[8],d=a[1],h=a[5],f=a[9],p=a[2],g=a[6],m=a[10];if(Math.abs(u-d)<s&&Math.abs(c-p)<s&&Math.abs(f-g)<s){if(Math.abs(u+d)<o&&Math.abs(c+p)<o&&Math.abs(f+g)<o&&Math.abs(l+h+m-3)<o)return this.set(1,0,0,0),this;t=Math.PI;const e=(l+1)/2,a=(h+1)/2,v=(m+1)/2,A=(u+d)/4,x=(c+p)/4,y=(f+g)/4;return e>a&&e>v?e<s?(n=0,i=.707106781,r=.707106781):(n=Math.sqrt(e),i=A/n,r=x/n):a>v?a<s?(n=.707106781,i=0,r=.707106781):(i=Math.sqrt(a),n=A/i,r=y/i):v<s?(n=.707106781,i=.707106781,r=0):(r=Math.sqrt(v),n=x/r,i=y/r),this.set(n,i,r,t),this}let v=Math.sqrt((g-f)*(g-f)+(c-p)*(c-p)+(d-u)*(d-u));return Math.abs(v)<.001&&(v=1),this.x=(g-f)/v,this.y=(c-p)/v,this.z=(d-u)/v,this.w=Math.acos((l+h+m-1)/2),this}setFromMatrixPosition(e){const t=e.elements;return this.x=t[12],this.y=t[13],this.z=t[14],this.w=t[15],this}min(e){return this.x=Math.min(this.x,e.x),this.y=Math.min(this.y,e.y),this.z=Math.min(this.z,e.z),this.w=Math.min(this.w,e.w),this}max(e){return this.x=Math.max(this.x,e.x),this.y=Math.max(this.y,e.y),this.z=Math.max(this.z,e.z),this.w=Math.max(this.w,e.w),this}clamp(e,t){return this.x=vs(this.x,e.x,t.x),this.y=vs(this.y,e.y,t.y),this.z=vs(this.z,e.z,t.z),this.w=vs(this.w,e.w,t.w),this}clampScalar(e,t){return this.x=vs(this.x,e,t),this.y=vs(this.y,e,t),this.z=vs(this.z,e,t),this.w=vs(this.w,e,t),this}clampLength(e,t){const n=this.length();return this.divideScalar(n||1).multiplyScalar(vs(n,e,t))}floor(){return this.x=Math.floor(this.x),this.y=Math.floor(this.y),this.z=Math.floor(this.z),this.w=Math.floor(this.w),this}ceil(){return this.x=Math.ceil(this.x),this.y=Math.ceil(this.y),this.z=Math.ceil(this.z),this.w=Math.ceil(this.w),this}round(){return this.x=Math.round(this.x),this.y=Math.round(this.y),this.z=Math.round(this.z),this.w=Math.round(this.w),this}roundToZero(){return this.x=Math.trunc(this.x),this.y=Math.trunc(this.y),this.z=Math.trunc(this.z),this.w=Math.trunc(this.w),this}negate(){return this.x=-this.x,this.y=-this.y,this.z=-this.z,this.w=-this.w,this}dot(e){return this.x*e.x+this.y*e.y+this.z*e.z+this.w*e.w}lengthSq(){return this.x*this.x+this.y*this.y+this.z*this.z+this.w*this.w}length(){return Math.sqrt(this.x*this.x+this.y*this.y+this.z*this.z+this.w*this.w)}manhattanLength(){return Math.abs(this.x)+Math.abs(this.y)+Math.abs(this.z)+Math.abs(this.w)}normalize(){return this.divideScalar(this.length()||1)}setLength(e){return this.normalize().multiplyScalar(e)}lerp(e,t){return this.x+=(e.x-this.x)*t,this.y+=(e.y-this.y)*t,this.z+=(e.z-this.z)*t,this.w+=(e.w-this.w)*t,this}lerpVectors(e,t,n){return this.x=e.x+(t.x-e.x)*n,this.y=e.y+(t.y-e.y)*n,this.z=e.z+(t.z-e.z)*n,this.w=e.w+(t.w-e.w)*n,this}equals(e){return e.x===this.x&&e.y===this.y&&e.z===this.z&&e.w===this.w}fromArray(e,t=0){return this.x=e[t],this.y=e[t+1],this.z=e[t+2],this.w=e[t+3],this}toArray(e=[],t=0){return e[t]=this.x,e[t+1]=this.y,e[t+2]=this.z,e[t+3]=this.w,e}fromBufferAttribute(e,t){return this.x=e.getX(t),this.y=e.getY(t),this.z=e.getZ(t),this.w=e.getW(t),this}random(){return this.x=Math.random(),this.y=Math.random(),this.z=Math.random(),this.w=Math.random(),this}*[Symbol.iterator](){yield this.x,yield this.y,yield this.z,yield this.w}}class Ks extends ds{constructor(e=1,t=1,n={}){super(),n=Object.assign({generateMipmaps:!1,internalFormat:null,minFilter:Hi,depthBuffer:!0,stencilBuffer:!1,resolveDepthBuffer:!0,resolveStencilBuffer:!0,depthTexture:null,samples:0,count:1,depth:1,multiview:!1},n),this.isRenderTarget=!0,this.width=e,this.height=t,this.depth=n.depth,this.scissor=new Js(0,0,e,t),this.scissorTest=!1,this.viewport=new Js(0,0,e,t);const i={width:e,height:t,depth:n.depth},r=new Ys(i);this.textures=[];const s=n.count;for(let e=0;e<s;e++)this.textures[e]=r.clone(),this.textures[e].isRenderTargetTexture=!0,this.textures[e].renderTarget=this;this._setTextureOptions(n),this.depthBuffer=n.depthBuffer,this.stencilBuffer=n.stencilBuffer,this.resolveDepthBuffer=n.resolveDepthBuffer,this.resolveStencilBuffer=n.resolveStencilBuffer,this._depthTexture=null,this.depthTexture=n.depthTexture,this.samples=n.samples,this.multiview=n.multiview}_setTextureOptions(e={}){const t={minFilter:Hi,generateMipmaps:!1,flipY:!1,internalFormat:null};void 0!==e.mapping&&(t.mapping=e.mapping),void 0!==e.wrapS&&(t.wrapS=e.wrapS),void 0!==e.wrapT&&(t.wrapT=e.wrapT),void 0!==e.wrapR&&(t.wrapR=e.wrapR),void 0!==e.magFilter&&(t.magFilter=e.magFilter),void 0!==e.minFilter&&(t.minFilter=e.minFilter),void 0!==e.format&&(t.format=e.format),void 0!==e.type&&(t.type=e.type),void 0!==e.anisotropy&&(t.anisotropy=e.anisotropy),void 0!==e.colorSpace&&(t.colorSpace=e.colorSpace),void 0!==e.flipY&&(t.flipY=e.flipY),void 0!==e.generateMipmaps&&(t.generateMipmaps=e.generateMipmaps),void 0!==e.internalFormat&&(t.internalFormat=e.internalFormat);for(let e=0;e<this.textures.length;e++){this.textures[e].setValues(t)}}get texture(){return this.textures[0]}set texture(e){this.textures[0]=e}set depthTexture(e){null!==this._depthTexture&&(this._depthTexture.renderTarget=null),null!==e&&(e.renderTarget=this),this._depthTexture=e}get depthTexture(){return this._depthTexture}setSize(e,t,n=1){if(this.width!==e||this.height!==t||this.depth!==n){this.width=e,this.height=t,this.depth=n;for(let i=0,r=this.textures.length;i<r;i++)this.textures[i].image.width=e,this.textures[i].image.height=t,this.textures[i].image.depth=n,this.textures[i].isArrayTexture=this.textures[i].image.depth>1;this.dispose()}this.viewport.set(0,0,e,t),this.scissor.set(0,0,e,t)}clone(){return(new this.constructor).copy(this)}copy(e){this.width=e.width,this.height=e.height,this.depth=e.depth,this.scissor.copy(e.scissor),this.scissorTest=e.scissorTest,this.viewport.copy(e.viewport),this.textures.length=0;for(let t=0,n=e.textures.length;t<n;t++){this.textures[t]=e.textures[t].clone(),this.textures[t].isRenderTargetTexture=!0,this.textures[t].renderTarget=this;const n=Object.assign({},e.textures[t].image);this.textures[t].source=new Vs(n)}return this.depthBuffer=e.depthBuffer,this.stencilBuffer=e.stencilBuffer,this.resolveDepthBuffer=e.resolveDepthBuffer,this.resolveStencilBuffer=e.resolveStencilBuffer,null!==e.depthTexture&&(this.depthTexture=e.depthTexture.clone()),this.samples=e.samples,this}dispose(){this.dispatchEvent({type:"dispose"})}}class qs extends Ks{constructor(e=1,t=1,n={}){super(e,t,n),this.isWebGLRenderTarget=!0}}class _s extends Ys{constructor(e=null,t=1,n=1,i=1){super(null),this.isDataArrayTexture=!0,this.image={data:e,width:t,height:n,depth:i},this.magFilter=Ri,this.minFilter=Ri,this.wrapR=Oi,this.generateMipmaps=!1,this.flipY=!1,this.unpackAlignment=1,this.layerUpdates=new Set}addLayerUpdate(e){this.layerUpdates.add(e)}clearLayerUpdates(){this.layerUpdates.clear()}}class $s extends Ys{constructor(e=null,t=1,n=1,i=1){super(null),this.isData3DTexture=!0,this.image={data:e,width:t,height:n,depth:i},this.magFilter=Ri,this.minFilter=Ri,this.wrapR=Oi,this.generateMipmaps=!1,this.flipY=!1,this.unpackAlignment=1}}class eo{constructor(e=new Es(1/0,1/0,1/0),t=new Es(-1/0,-1/0,-1/0)){this.isBox3=!0,this.min=e,this.max=t}set(e,t){return this.min.copy(e),this.max.copy(t),this}setFromArray(e){this.makeEmpty();for(let t=0,n=e.length;t<n;t+=3)this.expandByPoint(no.fromArray(e,t));return this}setFromBufferAttribute(e){this.makeEmpty();for(let t=0,n=e.count;t<n;t++)this.expandByPoint(no.fromBufferAttribute(e,t));return this}setFromPoints(e){this.makeEmpty();for(let t=0,n=e.length;t<n;t++)this.expandByPoint(e[t]);return this}setFromCenterAndSize(e,t){const n=no.copy(t).multiplyScalar(.5);return this.min.copy(e).sub(n),this.max.copy(e).add(n),this}setFromObject(e,t=!1){return this.makeEmpty(),this.expandByObject(e,t)}clone(){return(new this.constructor).copy(this)}copy(e){return this.min.copy(e.min),this.max.copy(e.max),this}makeEmpty(){return this.min.x=this.min.y=this.min.z=1/0,this.max.x=this.max.y=this.max.z=-1/0,this}isEmpty(){return this.max.x<this.min.x||this.max.y<this.min.y||this.max.z<this.min.z}getCenter(e){return this.isEmpty()?e.set(0,0,0):e.addVectors(this.min,this.max).multiplyScalar(.5)}getSize(e){return this.isEmpty()?e.set(0,0,0):e.subVectors(this.max,this.min)}expandByPoint(e){return this.min.min(e),this.max.max(e),this}expandByVector(e){return this.min.sub(e),this.max.add(e),this}expandByScalar(e){return this.min.addScalar(-e),this.max.addScalar(e),this}expandByObject(e,t=!1){e.updateWorldMatrix(!1,!1);const n=e.geometry;if(void 0!==n){const i=n.getAttribute("position");if(!0===t&&void 0!==i&&!0!==e.isInstancedMesh)for(let t=0,n=i.count;t<n;t++)!0===e.isMesh?e.getVertexPosition(t,no):no.fromBufferAttribute(i,t),no.applyMatrix4(e.matrixWorld),this.expandByPoint(no);else void 0!==e.boundingBox?(null===e.boundingBox&&e.computeBoundingBox(),io.copy(e.boundingBox)):(null===n.boundingBox&&n.computeBoundingBox(),io.copy(n.boundingBox)),io.applyMatrix4(e.matrixWorld),this.union(io)}const i=e.children;for(let e=0,n=i.length;e<n;e++)this.expandByObject(i[e],t);return this}containsPoint(e){return e.x>=this.min.x&&e.x<=this.max.x&&e.y>=this.min.y&&e.y<=this.max.y&&e.z>=this.min.z&&e.z<=this.max.z}containsBox(e){return this.min.x<=e.min.x&&e.max.x<=this.max.x&&this.min.y<=e.min.y&&e.max.y<=this.max.y&&this.min.z<=e.min.z&&e.max.z<=this.max.z}getParameter(e,t){return t.set((e.x-this.min.x)/(this.max.x-this.min.x),(e.y-this.min.y)/(this.max.y-this.min.y),(e.z-this.min.z)/(this.max.z-this.min.z))}intersectsBox(e){return e.max.x>=this.min.x&&e.min.x<=this.max.x&&e.max.y>=this.min.y&&e.min.y<=this.max.y&&e.max.z>=this.min.z&&e.min.z<=this.max.z}intersectsSphere(e){return this.clampPoint(e.center,no),no.distanceToSquared(e.center)<=e.radius*e.radius}intersectsPlane(e){let t,n;return e.normal.x>0?(t=e.normal.x*this.min.x,n=e.normal.x*this.max.x):(t=e.normal.x*this.max.x,n=e.normal.x*this.min.x),e.normal.y>0?(t+=e.normal.y*this.min.y,n+=e.normal.y*this.max.y):(t+=e.normal.y*this.max.y,n+=e.normal.y*this.min.y),e.normal.z>0?(t+=e.normal.z*this.min.z,n+=e.normal.z*this.max.z):(t+=e.normal.z*this.max.z,n+=e.normal.z*this.min.z),t<=-e.constant&&n>=-e.constant}intersectsTriangle(e){if(this.isEmpty())return!1;this.getCenter(co),ho.subVectors(this.max,co),ro.subVectors(e.a,co),so.subVectors(e.b,co),oo.subVectors(e.c,co),ao.subVectors(so,ro),lo.subVectors(oo,so),uo.subVectors(ro,oo);let t=[0,-ao.z,ao.y,0,-lo.z,lo.y,0,-uo.z,uo.y,ao.z,0,-ao.x,lo.z,0,-lo.x,uo.z,0,-uo.x,-ao.y,ao.x,0,-lo.y,lo.x,0,-uo.y,uo.x,0];return!!go(t,ro,so,oo,ho)&&(t=[1,0,0,0,1,0,0,0,1],!!go(t,ro,so,oo,ho)&&(fo.crossVectors(ao,lo),t=[fo.x,fo.y,fo.z],go(t,ro,so,oo,ho)))}clampPoint(e,t){return t.copy(e).clamp(this.min,this.max)}distanceToPoint(e){return this.clampPoint(e,no).distanceTo(e)}getBoundingSphere(e){return this.isEmpty()?e.makeEmpty():(this.getCenter(e.center),e.radius=.5*this.getSize(no).length()),e}intersect(e){return this.min.max(e.min),this.max.min(e.max),this.isEmpty()&&this.makeEmpty(),this}union(e){return this.min.min(e.min),this.max.max(e.max),this}applyMatrix4(e){return this.isEmpty()||(to[0].set(this.min.x,this.min.y,this.min.z).applyMatrix4(e),to[1].set(this.min.x,this.min.y,this.max.z).applyMatrix4(e),to[2].set(this.min.x,this.max.y,this.min.z).applyMatrix4(e),to[3].set(this.min.x,this.max.y,this.max.z).applyMatrix4(e),to[4].set(this.max.x,this.min.y,this.min.z).applyMatrix4(e),to[5].set(this.max.x,this.min.y,this.max.z).applyMatrix4(e),to[6].set(this.max.x,this.max.y,this.min.z).applyMatrix4(e),to[7].set(this.max.x,this.max.y,this.max.z).applyMatrix4(e),this.setFromPoints(to)),this}translate(e){return this.min.add(e),this.max.add(e),this}equals(e){return e.min.equals(this.min)&&e.max.equals(this.max)}toJSON(){return{min:this.min.toArray(),max:this.max.toArray()}}fromJSON(e){return this.min.fromArray(e.min),this.max.fromArray(e.max),this}}const to=[new Es,new Es,new Es,new Es,new Es,new Es,new Es,new Es],no=new Es,io=new eo,ro=new Es,so=new Es,oo=new Es,ao=new Es,lo=new Es,uo=new Es,co=new Es,ho=new Es,fo=new Es,po=new Es;function go(e,t,n,i,r){for(let s=0,o=e.length-3;s<=o;s+=3){po.fromArray(e,s);const o=r.x*Math.abs(po.x)+r.y*Math.abs(po.y)+r.z*Math.abs(po.z),a=t.dot(po),l=n.dot(po),u=i.dot(po);if(Math.max(-Math.max(a,l,u),Math.min(a,l,u))>o)return!1}return!0}const mo=new eo,vo=new Es,Ao=new Es;class xo{constructor(e=new Es,t=-1){this.isSphere=!0,this.center=e,this.radius=t}set(e,t){return this.center.copy(e),this.radius=t,this}setFromPoints(e,t){const n=this.center;void 0!==t?n.copy(t):mo.setFromPoints(e).getCenter(n);let i=0;for(let t=0,r=e.length;t<r;t++)i=Math.max(i,n.distanceToSquared(e[t]));return this.radius=Math.sqrt(i),this}copy(e){return this.center.copy(e.center),this.radius=e.radius,this}isEmpty(){return this.radius<0}makeEmpty(){return this.center.set(0,0,0),this.radius=-1,this}containsPoint(e){return e.distanceToSquared(this.center)<=this.radius*this.radius}distanceToPoint(e){return e.distanceTo(this.center)-this.radius}intersectsSphere(e){const t=this.radius+e.radius;return e.center.distanceToSquared(this.center)<=t*t}intersectsBox(e){return e.intersectsSphere(this)}intersectsPlane(e){return Math.abs(e.distanceToPoint(this.center))<=this.radius}clampPoint(e,t){const n=this.center.distanceToSquared(e);return t.copy(e),n>this.radius*this.radius&&(t.sub(this.center).normalize(),t.multiplyScalar(this.radius).add(this.center)),t}getBoundingBox(e){return this.isEmpty()?(e.makeEmpty(),e):(e.set(this.center,this.center),e.expandByScalar(this.radius),e)}applyMatrix4(e){return this.center.applyMatrix4(e),this.radius=this.radius*e.getMaxScaleOnAxis(),this}translate(e){return this.center.add(e),this}expandByPoint(e){if(this.isEmpty())return this.center.copy(e),this.radius=0,this;vo.subVectors(e,this.center);const t=vo.lengthSq();if(t>this.radius*this.radius){const e=Math.sqrt(t),n=.5*(e-this.radius);this.center.addScaledVector(vo,n/e),this.radius+=n}return this}union(e){return e.isEmpty()?this:this.isEmpty()?(this.copy(e),this):(!0===this.center.equals(e.center)?this.radius=Math.max(this.radius,e.radius):(Ao.subVectors(e.center,this.center).setLength(e.radius),this.expandByPoint(vo.copy(e.center).add(Ao)),this.expandByPoint(vo.copy(e.center).sub(Ao))),this)}equals(e){return e.center.equals(this.center)&&e.radius===this.radius}clone(){return(new this.constructor).copy(this)}toJSON(){return{radius:this.radius,center:this.center.toArray()}}fromJSON(e){return this.radius=e.radius,this.center.fromArray(e.center),this}}const yo=new Es,bo=new Es,wo=new Es,Co=new Es,Mo=new Es,Eo=new Es,To=new Es;class So{constructor(e=new Es,t=new Es(0,0,-1)){this.origin=e,this.direction=t}set(e,t){return this.origin.copy(e),this.direction.copy(t),this}copy(e){return this.origin.copy(e.origin),this.direction.copy(e.direction),this}at(e,t){return t.copy(this.origin).addScaledVector(this.direction,e)}lookAt(e){return this.direction.copy(e).sub(this.origin).normalize(),this}recast(e){return this.origin.copy(this.at(e,yo)),this}closestPointToPoint(e,t){t.subVectors(e,this.origin);const n=t.dot(this.direction);return n<0?t.copy(this.origin):t.copy(this.origin).addScaledVector(this.direction,n)}distanceToPoint(e){return Math.sqrt(this.distanceSqToPoint(e))}distanceSqToPoint(e){const t=yo.subVectors(e,this.origin).dot(this.direction);return t<0?this.origin.distanceToSquared(e):(yo.copy(this.origin).addScaledVector(this.direction,t),yo.distanceToSquared(e))}distanceSqToSegment(e,t,n,i){bo.copy(e).add(t).multiplyScalar(.5),wo.copy(t).sub(e).normalize(),Co.copy(this.origin).sub(bo);const r=.5*e.distanceTo(t),s=-this.direction.dot(wo),o=Co.dot(this.direction),a=-Co.dot(wo),l=Co.lengthSq(),u=Math.abs(1-s*s);let c,d,h,f;if(u>0)if(c=s*a-o,d=s*o-a,f=r*u,c>=0)if(d>=-f)if(d<=f){const e=1/u;c*=e,d*=e,h=c*(c+s*d+2*o)+d*(s*c+d+2*a)+l}else d=r,c=Math.max(0,-(s*d+o)),h=-c*c+d*(d+2*a)+l;else d=-r,c=Math.max(0,-(s*d+o)),h=-c*c+d*(d+2*a)+l;else d<=-f?(c=Math.max(0,-(-s*r+o)),d=c>0?-r:Math.min(Math.max(-r,-a),r),h=-c*c+d*(d+2*a)+l):d<=f?(c=0,d=Math.min(Math.max(-r,-a),r),h=d*(d+2*a)+l):(c=Math.max(0,-(s*r+o)),d=c>0?r:Math.min(Math.max(-r,-a),r),h=-c*c+d*(d+2*a)+l);else d=s>0?-r:r,c=Math.max(0,-(s*d+o)),h=-c*c+d*(d+2*a)+l;return n&&n.copy(this.origin).addScaledVector(this.direction,c),i&&i.copy(bo).addScaledVector(wo,d),h}intersectSphere(e,t){yo.subVectors(e.center,this.origin);const n=yo.dot(this.direction),i=yo.dot(yo)-n*n,r=e.radius*e.radius;if(i>r)return null;const s=Math.sqrt(r-i),o=n-s,a=n+s;return a<0?null:o<0?this.at(a,t):this.at(o,t)}intersectsSphere(e){return!(e.radius<0)&&this.distanceSqToPoint(e.center)<=e.radius*e.radius}distanceToPlane(e){const t=e.normal.dot(this.direction);if(0===t)return 0===e.distanceToPoint(this.origin)?0:null;const n=-(this.origin.dot(e.normal)+e.constant)/t;return n>=0?n:null}intersectPlane(e,t){const n=this.distanceToPlane(e);return null===n?null:this.at(n,t)}intersectsPlane(e){const t=e.distanceToPoint(this.origin);if(0===t)return!0;return e.normal.dot(this.direction)*t<0}intersectBox(e,t){let n,i,r,s,o,a;const l=1/this.direction.x,u=1/this.direction.y,c=1/this.direction.z,d=this.origin;return l>=0?(n=(e.min.x-d.x)*l,i=(e.max.x-d.x)*l):(n=(e.max.x-d.x)*l,i=(e.min.x-d.x)*l),u>=0?(r=(e.min.y-d.y)*u,s=(e.max.y-d.y)*u):(r=(e.max.y-d.y)*u,s=(e.min.y-d.y)*u),n>s||r>i?null:((r>n||isNaN(n))&&(n=r),(s<i||isNaN(i))&&(i=s),c>=0?(o=(e.min.z-d.z)*c,a=(e.max.z-d.z)*c):(o=(e.max.z-d.z)*c,a=(e.min.z-d.z)*c),n>a||o>i?null:((o>n||n!=n)&&(n=o),(a<i||i!=i)&&(i=a),i<0?null:this.at(n>=0?n:i,t)))}intersectsBox(e){return null!==this.intersectBox(e,yo)}intersectTriangle(e,t,n,i,r){Mo.subVectors(t,e),Eo.subVectors(n,e),To.crossVectors(Mo,Eo);let s,o=this.direction.dot(To);if(o>0){if(i)return null;s=1}else{if(!(o<0))return null;s=-1,o=-o}Co.subVectors(this.origin,e);const a=s*this.direction.dot(Eo.crossVectors(Co,Eo));if(a<0)return null;const l=s*this.direction.dot(Mo.cross(Co));if(l<0)return null;if(a+l>o)return null;const u=-s*Co.dot(To);return u<0?null:this.at(u/o,r)}applyMatrix4(e){return this.origin.applyMatrix4(e),this.direction.transformDirection(e),this}equals(e){return e.origin.equals(this.origin)&&e.direction.equals(this.direction)}clone(){return(new this.constructor).copy(this)}}class Po{constructor(e,t,n,i,r,s,o,a,l,u,c,d,h,f,p,g){Po.prototype.isMatrix4=!0,this.elements=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],void 0!==e&&this.set(e,t,n,i,r,s,o,a,l,u,c,d,h,f,p,g)}set(e,t,n,i,r,s,o,a,l,u,c,d,h,f,p,g){const m=this.elements;return m[0]=e,m[4]=t,m[8]=n,m[12]=i,m[1]=r,m[5]=s,m[9]=o,m[13]=a,m[2]=l,m[6]=u,m[10]=c,m[14]=d,m[3]=h,m[7]=f,m[11]=p,m[15]=g,this}identity(){return this.set(1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1),this}clone(){return(new Po).fromArray(this.elements)}copy(e){const t=this.elements,n=e.elements;return t[0]=n[0],t[1]=n[1],t[2]=n[2],t[3]=n[3],t[4]=n[4],t[5]=n[5],t[6]=n[6],t[7]=n[7],t[8]=n[8],t[9]=n[9],t[10]=n[10],t[11]=n[11],t[12]=n[12],t[13]=n[13],t[14]=n[14],t[15]=n[15],this}copyPosition(e){const t=this.elements,n=e.elements;return t[12]=n[12],t[13]=n[13],t[14]=n[14],this}setFromMatrix3(e){const t=e.elements;return this.set(t[0],t[3],t[6],0,t[1],t[4],t[7],0,t[2],t[5],t[8],0,0,0,0,1),this}extractBasis(e,t,n){return e.setFromMatrixColumn(this,0),t.setFromMatrixColumn(this,1),n.setFromMatrixColumn(this,2),this}makeBasis(e,t,n){return this.set(e.x,t.x,n.x,0,e.y,t.y,n.y,0,e.z,t.z,n.z,0,0,0,0,1),this}extractRotation(e){const t=this.elements,n=e.elements,i=1/No.setFromMatrixColumn(e,0).length(),r=1/No.setFromMatrixColumn(e,1).length(),s=1/No.setFromMatrixColumn(e,2).length();return t[0]=n[0]*i,t[1]=n[1]*i,t[2]=n[2]*i,t[3]=0,t[4]=n[4]*r,t[5]=n[5]*r,t[6]=n[6]*r,t[7]=0,t[8]=n[8]*s,t[9]=n[9]*s,t[10]=n[10]*s,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,this}makeRotationFromEuler(e){const t=this.elements,n=e.x,i=e.y,r=e.z,s=Math.cos(n),o=Math.sin(n),a=Math.cos(i),l=Math.sin(i),u=Math.cos(r),c=Math.sin(r);if("XYZ"===e.order){const e=s*u,n=s*c,i=o*u,r=o*c;t[0]=a*u,t[4]=-a*c,t[8]=l,t[1]=n+i*l,t[5]=e-r*l,t[9]=-o*a,t[2]=r-e*l,t[6]=i+n*l,t[10]=s*a}else if("YXZ"===e.order){const e=a*u,n=a*c,i=l*u,r=l*c;t[0]=e+r*o,t[4]=i*o-n,t[8]=s*l,t[1]=s*c,t[5]=s*u,t[9]=-o,t[2]=n*o-i,t[6]=r+e*o,t[10]=s*a}else if("ZXY"===e.order){const e=a*u,n=a*c,i=l*u,r=l*c;t[0]=e-r*o,t[4]=-s*c,t[8]=i+n*o,t[1]=n+i*o,t[5]=s*u,t[9]=r-e*o,t[2]=-s*l,t[6]=o,t[10]=s*a}else if("ZYX"===e.order){const e=s*u,n=s*c,i=o*u,r=o*c;t[0]=a*u,t[4]=i*l-n,t[8]=e*l+r,t[1]=a*c,t[5]=r*l+e,t[9]=n*l-i,t[2]=-l,t[6]=o*a,t[10]=s*a}else if("YZX"===e.order){const e=s*a,n=s*l,i=o*a,r=o*l;t[0]=a*u,t[4]=r-e*c,t[8]=i*c+n,t[1]=c,t[5]=s*u,t[9]=-o*u,t[2]=-l*u,t[6]=n*c+i,t[10]=e-r*c}else if("XZY"===e.order){const e=s*a,n=s*l,i=o*a,r=o*l;t[0]=a*u,t[4]=-c,t[8]=l*u,t[1]=e*c+r,t[5]=s*u,t[9]=n*c-i,t[2]=i*c-n,t[6]=o*u,t[10]=r*c+e}return t[3]=0,t[7]=0,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,this}makeRotationFromQuaternion(e){return this.compose(Do,e,Io)}lookAt(e,t,n){const i=this.elements;return Oo.subVectors(e,t),0===Oo.lengthSq()&&(Oo.z=1),Oo.normalize(),Lo.crossVectors(n,Oo),0===Lo.lengthSq()&&(1===Math.abs(n.z)?Oo.x+=1e-4:Oo.z+=1e-4,Oo.normalize(),Lo.crossVectors(n,Oo)),Lo.normalize(),jo.crossVectors(Oo,Lo),i[0]=Lo.x,i[4]=jo.x,i[8]=Oo.x,i[1]=Lo.y,i[5]=jo.y,i[9]=Oo.y,i[2]=Lo.z,i[6]=jo.z,i[10]=Oo.z,this}multiply(e){return this.multiplyMatrices(this,e)}premultiply(e){return this.multiplyMatrices(e,this)}multiplyMatrices(e,t){const n=e.elements,i=t.elements,r=this.elements,s=n[0],o=n[4],a=n[8],l=n[12],u=n[1],c=n[5],d=n[9],h=n[13],f=n[2],p=n[6],g=n[10],m=n[14],v=n[3],A=n[7],x=n[11],y=n[15],b=i[0],w=i[4],C=i[8],M=i[12],E=i[1],T=i[5],S=i[9],P=i[13],N=i[2],B=i[6],D=i[10],I=i[14],L=i[3],j=i[7],O=i[11],z=i[15];return r[0]=s*b+o*E+a*N+l*L,r[4]=s*w+o*T+a*B+l*j,r[8]=s*C+o*S+a*D+l*O,r[12]=s*M+o*P+a*I+l*z,r[1]=u*b+c*E+d*N+h*L,r[5]=u*w+c*T+d*B+h*j,r[9]=u*C+c*S+d*D+h*O,r[13]=u*M+c*P+d*I+h*z,r[2]=f*b+p*E+g*N+m*L,r[6]=f*w+p*T+g*B+m*j,r[10]=f*C+p*S+g*D+m*O,r[14]=f*M+p*P+g*I+m*z,r[3]=v*b+A*E+x*N+y*L,r[7]=v*w+A*T+x*B+y*j,r[11]=v*C+A*S+x*D+y*O,r[15]=v*M+A*P+x*I+y*z,this}multiplyScalar(e){const t=this.elements;return t[0]*=e,t[4]*=e,t[8]*=e,t[12]*=e,t[1]*=e,t[5]*=e,t[9]*=e,t[13]*=e,t[2]*=e,t[6]*=e,t[10]*=e,t[14]*=e,t[3]*=e,t[7]*=e,t[11]*=e,t[15]*=e,this}determinant(){const e=this.elements,t=e[0],n=e[4],i=e[8],r=e[12],s=e[1],o=e[5],a=e[9],l=e[13],u=e[2],c=e[6],d=e[10],h=e[14];return e[3]*(+r*a*c-i*l*c-r*o*d+n*l*d+i*o*h-n*a*h)+e[7]*(+t*a*h-t*l*d+r*s*d-i*s*h+i*l*u-r*a*u)+e[11]*(+t*l*c-t*o*h-r*s*c+n*s*h+r*o*u-n*l*u)+e[15]*(-i*o*u-t*a*c+t*o*d+i*s*c-n*s*d+n*a*u)}transpose(){const e=this.elements;let t;return t=e[1],e[1]=e[4],e[4]=t,t=e[2],e[2]=e[8],e[8]=t,t=e[6],e[6]=e[9],e[9]=t,t=e[3],e[3]=e[12],e[12]=t,t=e[7],e[7]=e[13],e[13]=t,t=e[11],e[11]=e[14],e[14]=t,this}setPosition(e,t,n){const i=this.elements;return e.isVector3?(i[12]=e.x,i[13]=e.y,i[14]=e.z):(i[12]=e,i[13]=t,i[14]=n),this}invert(){const e=this.elements,t=e[0],n=e[1],i=e[2],r=e[3],s=e[4],o=e[5],a=e[6],l=e[7],u=e[8],c=e[9],d=e[10],h=e[11],f=e[12],p=e[13],g=e[14],m=e[15],v=c*g*l-p*d*l+p*a*h-o*g*h-c*a*m+o*d*m,A=f*d*l-u*g*l-f*a*h+s*g*h+u*a*m-s*d*m,x=u*p*l-f*c*l+f*o*h-s*p*h-u*o*m+s*c*m,y=f*c*a-u*p*a-f*o*d+s*p*d+u*o*g-s*c*g,b=t*v+n*A+i*x+r*y;if(0===b)return this.set(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0);const w=1/b;return e[0]=v*w,e[1]=(p*d*r-c*g*r-p*i*h+n*g*h+c*i*m-n*d*m)*w,e[2]=(o*g*r-p*a*r+p*i*l-n*g*l-o*i*m+n*a*m)*w,e[3]=(c*a*r-o*d*r-c*i*l+n*d*l+o*i*h-n*a*h)*w,e[4]=A*w,e[5]=(u*g*r-f*d*r+f*i*h-t*g*h-u*i*m+t*d*m)*w,e[6]=(f*a*r-s*g*r-f*i*l+t*g*l+s*i*m-t*a*m)*w,e[7]=(s*d*r-u*a*r+u*i*l-t*d*l-s*i*h+t*a*h)*w,e[8]=x*w,e[9]=(f*c*r-u*p*r-f*n*h+t*p*h+u*n*m-t*c*m)*w,e[10]=(s*p*r-f*o*r+f*n*l-t*p*l-s*n*m+t*o*m)*w,e[11]=(u*o*r-s*c*r-u*n*l+t*c*l+s*n*h-t*o*h)*w,e[12]=y*w,e[13]=(u*p*i-f*c*i+f*n*d-t*p*d-u*n*g+t*c*g)*w,e[14]=(f*o*i-s*p*i-f*n*a+t*p*a+s*n*g-t*o*g)*w,e[15]=(s*c*i-u*o*i+u*n*a-t*c*a-s*n*d+t*o*d)*w,this}scale(e){const t=this.elements,n=e.x,i=e.y,r=e.z;return t[0]*=n,t[4]*=i,t[8]*=r,t[1]*=n,t[5]*=i,t[9]*=r,t[2]*=n,t[6]*=i,t[10]*=r,t[3]*=n,t[7]*=i,t[11]*=r,this}getMaxScaleOnAxis(){const e=this.elements,t=e[0]*e[0]+e[1]*e[1]+e[2]*e[2],n=e[4]*e[4]+e[5]*e[5]+e[6]*e[6],i=e[8]*e[8]+e[9]*e[9]+e[10]*e[10];return Math.sqrt(Math.max(t,n,i))}makeTranslation(e,t,n){return e.isVector3?this.set(1,0,0,e.x,0,1,0,e.y,0,0,1,e.z,0,0,0,1):this.set(1,0,0,e,0,1,0,t,0,0,1,n,0,0,0,1),this}makeRotationX(e){const t=Math.cos(e),n=Math.sin(e);return this.set(1,0,0,0,0,t,-n,0,0,n,t,0,0,0,0,1),this}makeRotationY(e){const t=Math.cos(e),n=Math.sin(e);return this.set(t,0,n,0,0,1,0,0,-n,0,t,0,0,0,0,1),this}makeRotationZ(e){const t=Math.cos(e),n=Math.sin(e);return this.set(t,-n,0,0,n,t,0,0,0,0,1,0,0,0,0,1),this}makeRotationAxis(e,t){const n=Math.cos(t),i=Math.sin(t),r=1-n,s=e.x,o=e.y,a=e.z,l=r*s,u=r*o;return this.set(l*s+n,l*o-i*a,l*a+i*o,0,l*o+i*a,u*o+n,u*a-i*s,0,l*a-i*o,u*a+i*s,r*a*a+n,0,0,0,0,1),this}makeScale(e,t,n){return this.set(e,0,0,0,0,t,0,0,0,0,n,0,0,0,0,1),this}makeShear(e,t,n,i,r,s){return this.set(1,n,r,0,e,1,s,0,t,i,1,0,0,0,0,1),this}compose(e,t,n){const i=this.elements,r=t._x,s=t._y,o=t._z,a=t._w,l=r+r,u=s+s,c=o+o,d=r*l,h=r*u,f=r*c,p=s*u,g=s*c,m=o*c,v=a*l,A=a*u,x=a*c,y=n.x,b=n.y,w=n.z;return i[0]=(1-(p+m))*y,i[1]=(h+x)*y,i[2]=(f-A)*y,i[3]=0,i[4]=(h-x)*b,i[5]=(1-(d+m))*b,i[6]=(g+v)*b,i[7]=0,i[8]=(f+A)*w,i[9]=(g-v)*w,i[10]=(1-(d+p))*w,i[11]=0,i[12]=e.x,i[13]=e.y,i[14]=e.z,i[15]=1,this}decompose(e,t,n){const i=this.elements;let r=No.set(i[0],i[1],i[2]).length();const s=No.set(i[4],i[5],i[6]).length(),o=No.set(i[8],i[9],i[10]).length();this.determinant()<0&&(r=-r),e.x=i[12],e.y=i[13],e.z=i[14],Bo.copy(this);const a=1/r,l=1/s,u=1/o;return Bo.elements[0]*=a,Bo.elements[1]*=a,Bo.elements[2]*=a,Bo.elements[4]*=l,Bo.elements[5]*=l,Bo.elements[6]*=l,Bo.elements[8]*=u,Bo.elements[9]*=u,Bo.elements[10]*=u,t.setFromRotationMatrix(Bo),n.x=r,n.y=s,n.z=o,this}makePerspective(e,t,n,i,r,s,o=2e3,a=!1){const l=this.elements,u=2*r/(t-e),c=2*r/(n-i),d=(t+e)/(t-e),h=(n+i)/(n-i);let f,p;if(a)f=r/(s-r),p=s*r/(s-r);else if(o===as)f=-(s+r)/(s-r),p=-2*s*r/(s-r);else{if(o!==ls)throw new Error("THREE.Matrix4.makePerspective(): Invalid coordinate system: "+o);f=-s/(s-r),p=-s*r/(s-r)}return l[0]=u,l[4]=0,l[8]=d,l[12]=0,l[1]=0,l[5]=c,l[9]=h,l[13]=0,l[2]=0,l[6]=0,l[10]=f,l[14]=p,l[3]=0,l[7]=0,l[11]=-1,l[15]=0,this}makeOrthographic(e,t,n,i,r,s,o=2e3,a=!1){const l=this.elements,u=2/(t-e),c=2/(n-i),d=-(t+e)/(t-e),h=-(n+i)/(n-i);let f,p;if(a)f=1/(s-r),p=s/(s-r);else if(o===as)f=-2/(s-r),p=-(s+r)/(s-r);else{if(o!==ls)throw new Error("THREE.Matrix4.makeOrthographic(): Invalid coordinate system: "+o);f=-1/(s-r),p=-r/(s-r)}return l[0]=u,l[4]=0,l[8]=0,l[12]=d,l[1]=0,l[5]=c,l[9]=0,l[13]=h,l[2]=0,l[6]=0,l[10]=f,l[14]=p,l[3]=0,l[7]=0,l[11]=0,l[15]=1,this}equals(e){const t=this.elements,n=e.elements;for(let e=0;e<16;e++)if(t[e]!==n[e])return!1;return!0}fromArray(e,t=0){for(let n=0;n<16;n++)this.elements[n]=e[n+t];return this}toArray(e=[],t=0){const n=this.elements;return e[t]=n[0],e[t+1]=n[1],e[t+2]=n[2],e[t+3]=n[3],e[t+4]=n[4],e[t+5]=n[5],e[t+6]=n[6],e[t+7]=n[7],e[t+8]=n[8],e[t+9]=n[9],e[t+10]=n[10],e[t+11]=n[11],e[t+12]=n[12],e[t+13]=n[13],e[t+14]=n[14],e[t+15]=n[15],e}}const No=new Es,Bo=new Po,Do=new Es(0,0,0),Io=new Es(1,1,1),Lo=new Es,jo=new Es,Oo=new Es,zo=new Po,Ro=new Ms;class ko{constructor(e=0,t=0,n=0,i=ko.DEFAULT_ORDER){this.isEuler=!0,this._x=e,this._y=t,this._z=n,this._order=i}get x(){return this._x}set x(e){this._x=e,this._onChangeCallback()}get y(){return this._y}set y(e){this._y=e,this._onChangeCallback()}get z(){return this._z}set z(e){this._z=e,this._onChangeCallback()}get order(){return this._order}set order(e){this._order=e,this._onChangeCallback()}set(e,t,n,i=this._order){return this._x=e,this._y=t,this._z=n,this._order=i,this._onChangeCallback(),this}clone(){return new this.constructor(this._x,this._y,this._z,this._order)}copy(e){return this._x=e._x,this._y=e._y,this._z=e._z,this._order=e._order,this._onChangeCallback(),this}setFromRotationMatrix(e,t=this._order,n=!0){const i=e.elements,r=i[0],s=i[4],o=i[8],a=i[1],l=i[5],u=i[9],c=i[2],d=i[6],h=i[10];switch(t){case"XYZ":this._y=Math.asin(vs(o,-1,1)),Math.abs(o)<.9999999?(this._x=Math.atan2(-u,h),this._z=Math.atan2(-s,r)):(this._x=Math.atan2(d,l),this._z=0);break;case"YXZ":this._x=Math.asin(-vs(u,-1,1)),Math.abs(u)<.9999999?(this._y=Math.atan2(o,h),this._z=Math.atan2(a,l)):(this._y=Math.atan2(-c,r),this._z=0);break;case"ZXY":this._x=Math.asin(vs(d,-1,1)),Math.abs(d)<.9999999?(this._y=Math.atan2(-c,h),this._z=Math.atan2(-s,l)):(this._y=0,this._z=Math.atan2(a,r));break;case"ZYX":this._y=Math.asin(-vs(c,-1,1)),Math.abs(c)<.9999999?(this._x=Math.atan2(d,h),this._z=Math.atan2(a,r)):(this._x=0,this._z=Math.atan2(-s,l));break;case"YZX":this._z=Math.asin(vs(a,-1,1)),Math.abs(a)<.9999999?(this._x=Math.atan2(-u,l),this._y=Math.atan2(-c,r)):(this._x=0,this._y=Math.atan2(o,h));break;case"XZY":this._z=Math.asin(-vs(s,-1,1)),Math.abs(s)<.9999999?(this._x=Math.atan2(d,l),this._y=Math.atan2(o,r)):(this._x=Math.atan2(-u,h),this._y=0);break;default:console.warn("THREE.Euler: .setFromRotationMatrix() encountered an unknown order: "+t)}return this._order=t,!0===n&&this._onChangeCallback(),this}setFromQuaternion(e,t,n){return zo.makeRotationFromQuaternion(e),this.setFromRotationMatrix(zo,t,n)}setFromVector3(e,t=this._order){return this.set(e.x,e.y,e.z,t)}reorder(e){return Ro.setFromEuler(this),this.setFromQuaternion(Ro,e)}equals(e){return e._x===this._x&&e._y===this._y&&e._z===this._z&&e._order===this._order}fromArray(e){return this._x=e[0],this._y=e[1],this._z=e[2],void 0!==e[3]&&(this._order=e[3]),this._onChangeCallback(),this}toArray(e=[],t=0){return e[t]=this._x,e[t+1]=this._y,e[t+2]=this._z,e[t+3]=this._order,e}_onChange(e){return this._onChangeCallback=e,this}_onChangeCallback(){}*[Symbol.iterator](){yield this._x,yield this._y,yield this._z,yield this._order}}ko.DEFAULT_ORDER="XYZ";class Fo{constructor(){this.mask=1}set(e){this.mask=(1<<e|0)>>>0}enable(e){this.mask|=1<<e|0}enableAll(){this.mask=-1}toggle(e){this.mask^=1<<e|0}disable(e){this.mask&=~(1<<e|0)}disableAll(){this.mask=0}test(e){return 0!=(this.mask&e.mask)}isEnabled(e){return 0!=(this.mask&(1<<e|0))}}let Ho=0;const Uo=new Es,Xo=new Ms,Go=new Po,Vo=new Es,Wo=new Es,Qo=new Es,Zo=new Ms,Yo=new Es(1,0,0),Jo=new Es(0,1,0),Ko=new Es(0,0,1),qo={type:"added"},_o={type:"removed"},$o={type:"childadded",child:null},ea={type:"childremoved",child:null};class ta extends ds{constructor(){super(),this.isObject3D=!0,Object.defineProperty(this,"id",{value:Ho++}),this.uuid=ms(),this.name="",this.type="Object3D",this.parent=null,this.children=[],this.up=ta.DEFAULT_UP.clone();const e=new Es,t=new ko,n=new Ms,i=new Es(1,1,1);t._onChange((function(){n.setFromEuler(t,!1)})),n._onChange((function(){t.setFromQuaternion(n,void 0,!1)})),Object.defineProperties(this,{position:{configurable:!0,enumerable:!0,value:e},rotation:{configurable:!0,enumerable:!0,value:t},quaternion:{configurable:!0,enumerable:!0,value:n},scale:{configurable:!0,enumerable:!0,value:i},modelViewMatrix:{value:new Po},normalMatrix:{value:new Ps}}),this.matrix=new Po,this.matrixWorld=new Po,this.matrixAutoUpdate=ta.DEFAULT_MATRIX_AUTO_UPDATE,this.matrixWorldAutoUpdate=ta.DEFAULT_MATRIX_WORLD_AUTO_UPDATE,this.matrixWorldNeedsUpdate=!1,this.layers=new Fo,this.visible=!0,this.castShadow=!1,this.receiveShadow=!1,this.frustumCulled=!0,this.renderOrder=0,this.animations=[],this.customDepthMaterial=void 0,this.customDistanceMaterial=void 0,this.userData={}}onBeforeShadow(){}onAfterShadow(){}onBeforeRender(){}onAfterRender(){}applyMatrix4(e){this.matrixAutoUpdate&&this.updateMatrix(),this.matrix.premultiply(e),this.matrix.decompose(this.position,this.quaternion,this.scale)}applyQuaternion(e){return this.quaternion.premultiply(e),this}setRotationFromAxisAngle(e,t){this.quaternion.setFromAxisAngle(e,t)}setRotationFromEuler(e){this.quaternion.setFromEuler(e,!0)}setRotationFromMatrix(e){this.quaternion.setFromRotationMatrix(e)}setRotationFromQuaternion(e){this.quaternion.copy(e)}rotateOnAxis(e,t){return Xo.setFromAxisAngle(e,t),this.quaternion.multiply(Xo),this}rotateOnWorldAxis(e,t){return Xo.setFromAxisAngle(e,t),this.quaternion.premultiply(Xo),this}rotateX(e){return this.rotateOnAxis(Yo,e)}rotateY(e){return this.rotateOnAxis(Jo,e)}rotateZ(e){return this.rotateOnAxis(Ko,e)}translateOnAxis(e,t){return Uo.copy(e).applyQuaternion(this.quaternion),this.position.add(Uo.multiplyScalar(t)),this}translateX(e){return this.translateOnAxis(Yo,e)}translateY(e){return this.translateOnAxis(Jo,e)}translateZ(e){return this.translateOnAxis(Ko,e)}localToWorld(e){return this.updateWorldMatrix(!0,!1),e.applyMatrix4(this.matrixWorld)}worldToLocal(e){return this.updateWorldMatrix(!0,!1),e.applyMatrix4(Go.copy(this.matrixWorld).invert())}lookAt(e,t,n){e.isVector3?Vo.copy(e):Vo.set(e,t,n);const i=this.parent;this.updateWorldMatrix(!0,!1),Wo.setFromMatrixPosition(this.matrixWorld),this.isCamera||this.isLight?Go.lookAt(Wo,Vo,this.up):Go.lookAt(Vo,Wo,this.up),this.quaternion.setFromRotationMatrix(Go),i&&(Go.extractRotation(i.matrixWorld),Xo.setFromRotationMatrix(Go),this.quaternion.premultiply(Xo.invert()))}add(e){if(arguments.length>1){for(let e=0;e<arguments.length;e++)this.add(arguments[e]);return this}return e===this?(console.error("THREE.Object3D.add: object can't be added as a child of itself.",e),this):(e&&e.isObject3D?(e.removeFromParent(),e.parent=this,this.children.push(e),e.dispatchEvent(qo),$o.child=e,this.dispatchEvent($o),$o.child=null):console.error("THREE.Object3D.add: object not an instance of THREE.Object3D.",e),this)}remove(e){if(arguments.length>1){for(let e=0;e<arguments.length;e++)this.remove(arguments[e]);return this}const t=this.children.indexOf(e);return-1!==t&&(e.parent=null,this.children.splice(t,1),e.dispatchEvent(_o),ea.child=e,this.dispatchEvent(ea),ea.child=null),this}removeFromParent(){const e=this.parent;return null!==e&&e.remove(this),this}clear(){return this.remove(...this.children)}attach(e){return this.updateWorldMatrix(!0,!1),Go.copy(this.matrixWorld).invert(),null!==e.parent&&(e.parent.updateWorldMatrix(!0,!1),Go.multiply(e.parent.matrixWorld)),e.applyMatrix4(Go),e.removeFromParent(),e.parent=this,this.children.push(e),e.updateWorldMatrix(!1,!0),e.dispatchEvent(qo),$o.child=e,this.dispatchEvent($o),$o.child=null,this}getObjectById(e){return this.getObjectByProperty("id",e)}getObjectByName(e){return this.getObjectByProperty("name",e)}getObjectByProperty(e,t){if(this[e]===t)return this;for(let n=0,i=this.children.length;n<i;n++){const i=this.children[n].getObjectByProperty(e,t);if(void 0!==i)return i}}getObjectsByProperty(e,t,n=[]){this[e]===t&&n.push(this);const i=this.children;for(let r=0,s=i.length;r<s;r++)i[r].getObjectsByProperty(e,t,n);return n}getWorldPosition(e){return this.updateWorldMatrix(!0,!1),e.setFromMatrixPosition(this.matrixWorld)}getWorldQuaternion(e){return this.updateWorldMatrix(!0,!1),this.matrixWorld.decompose(Wo,e,Qo),e}getWorldScale(e){return this.updateWorldMatrix(!0,!1),this.matrixWorld.decompose(Wo,Zo,e),e}getWorldDirection(e){this.updateWorldMatrix(!0,!1);const t=this.matrixWorld.elements;return e.set(t[8],t[9],t[10]).normalize()}raycast(){}traverse(e){e(this);const t=this.children;for(let n=0,i=t.length;n<i;n++)t[n].traverse(e)}traverseVisible(e){if(!1===this.visible)return;e(this);const t=this.children;for(let n=0,i=t.length;n<i;n++)t[n].traverseVisible(e)}traverseAncestors(e){const t=this.parent;null!==t&&(e(t),t.traverseAncestors(e))}updateMatrix(){this.matrix.compose(this.position,this.quaternion,this.scale),this.matrixWorldNeedsUpdate=!0}updateMatrixWorld(e){this.matrixAutoUpdate&&this.updateMatrix(),(this.matrixWorldNeedsUpdate||e)&&(!0===this.matrixWorldAutoUpdate&&(null===this.parent?this.matrixWorld.copy(this.matrix):this.matrixWorld.multiplyMatrices(this.parent.matrixWorld,this.matrix)),this.matrixWorldNeedsUpdate=!1,e=!0);const t=this.children;for(let n=0,i=t.length;n<i;n++){t[n].updateMatrixWorld(e)}}updateWorldMatrix(e,t){const n=this.parent;if(!0===e&&null!==n&&n.updateWorldMatrix(!0,!1),this.matrixAutoUpdate&&this.updateMatrix(),!0===this.matrixWorldAutoUpdate&&(null===this.parent?this.matrixWorld.copy(this.matrix):this.matrixWorld.multiplyMatrices(this.parent.matrixWorld,this.matrix)),!0===t){const e=this.children;for(let t=0,n=e.length;t<n;t++){e[t].updateWorldMatrix(!1,!0)}}}toJSON(e){const t=void 0===e||"string"==typeof e,n={};t&&(e={geometries:{},materials:{},textures:{},images:{},shapes:{},skeletons:{},animations:{},nodes:{}},n.metadata={version:4.7,type:"Object",generator:"Object3D.toJSON"});const i={};function r(t,n){return void 0===t[n.uuid]&&(t[n.uuid]=n.toJSON(e)),n.uuid}if(i.uuid=this.uuid,i.type=this.type,""!==this.name&&(i.name=this.name),!0===this.castShadow&&(i.castShadow=!0),!0===this.receiveShadow&&(i.receiveShadow=!0),!1===this.visible&&(i.visible=!1),!1===this.frustumCulled&&(i.frustumCulled=!1),0!==this.renderOrder&&(i.renderOrder=this.renderOrder),Object.keys(this.userData).length>0&&(i.userData=this.userData),i.layers=this.layers.mask,i.matrix=this.matrix.toArray(),i.up=this.up.toArray(),!1===this.matrixAutoUpdate&&(i.matrixAutoUpdate=!1),this.isInstancedMesh&&(i.type="InstancedMesh",i.count=this.count,i.instanceMatrix=this.instanceMatrix.toJSON(),null!==this.instanceColor&&(i.instanceColor=this.instanceColor.toJSON())),this.isBatchedMesh&&(i.type="BatchedMesh",i.perObjectFrustumCulled=this.perObjectFrustumCulled,i.sortObjects=this.sortObjects,i.drawRanges=this._drawRanges,i.reservedRanges=this._reservedRanges,i.geometryInfo=this._geometryInfo.map((e=>({...e,boundingBox:e.boundingBox?e.boundingBox.toJSON():void 0,boundingSphere:e.boundingSphere?e.boundingSphere.toJSON():void 0}))),i.instanceInfo=this._instanceInfo.map((e=>({...e}))),i.availableInstanceIds=this._availableInstanceIds.slice(),i.availableGeometryIds=this._availableGeometryIds.slice(),i.nextIndexStart=this._nextIndexStart,i.nextVertexStart=this._nextVertexStart,i.geometryCount=this._geometryCount,i.maxInstanceCount=this._maxInstanceCount,i.maxVertexCount=this._maxVertexCount,i.maxIndexCount=this._maxIndexCount,i.geometryInitialized=this._geometryInitialized,i.matricesTexture=this._matricesTexture.toJSON(e),i.indirectTexture=this._indirectTexture.toJSON(e),null!==this._colorsTexture&&(i.colorsTexture=this._colorsTexture.toJSON(e)),null!==this.boundingSphere&&(i.boundingSphere=this.boundingSphere.toJSON()),null!==this.boundingBox&&(i.boundingBox=this.boundingBox.toJSON())),this.isScene)this.background&&(this.background.isColor?i.background=this.background.toJSON():this.background.isTexture&&(i.background=this.background.toJSON(e).uuid)),this.environment&&this.environment.isTexture&&!0!==this.environment.isRenderTargetTexture&&(i.environment=this.environment.toJSON(e).uuid);else if(this.isMesh||this.isLine||this.isPoints){i.geometry=r(e.geometries,this.geometry);const t=this.geometry.parameters;if(void 0!==t&&void 0!==t.shapes){const n=t.shapes;if(Array.isArray(n))for(let t=0,i=n.length;t<i;t++){const i=n[t];r(e.shapes,i)}else r(e.shapes,n)}}if(this.isSkinnedMesh&&(i.bindMode=this.bindMode,i.bindMatrix=this.bindMatrix.toArray(),void 0!==this.skeleton&&(r(e.skeletons,this.skeleton),i.skeleton=this.skeleton.uuid)),void 0!==this.material)if(Array.isArray(this.material)){const t=[];for(let n=0,i=this.material.length;n<i;n++)t.push(r(e.materials,this.material[n]));i.material=t}else i.material=r(e.materials,this.material);if(this.children.length>0){i.children=[];for(let t=0;t<this.children.length;t++)i.children.push(this.children[t].toJSON(e).object)}if(this.animations.length>0){i.animations=[];for(let t=0;t<this.animations.length;t++){const n=this.animations[t];i.animations.push(r(e.animations,n))}}if(t){const t=s(e.geometries),i=s(e.materials),r=s(e.textures),o=s(e.images),a=s(e.shapes),l=s(e.skeletons),u=s(e.animations),c=s(e.nodes);t.length>0&&(n.geometries=t),i.length>0&&(n.materials=i),r.length>0&&(n.textures=r),o.length>0&&(n.images=o),a.length>0&&(n.shapes=a),l.length>0&&(n.skeletons=l),u.length>0&&(n.animations=u),c.length>0&&(n.nodes=c)}return n.object=i,n;function s(e){const t=[];for(const n in e){const i=e[n];delete i.metadata,t.push(i)}return t}}clone(e){return(new this.constructor).copy(this,e)}copy(e,t=!0){if(this.name=e.name,this.up.copy(e.up),this.position.copy(e.position),this.rotation.order=e.rotation.order,this.quaternion.copy(e.quaternion),this.scale.copy(e.scale),this.matrix.copy(e.matrix),this.matrixWorld.copy(e.matrixWorld),this.matrixAutoUpdate=e.matrixAutoUpdate,this.matrixWorldAutoUpdate=e.matrixWorldAutoUpdate,this.matrixWorldNeedsUpdate=e.matrixWorldNeedsUpdate,this.layers.mask=e.layers.mask,this.visible=e.visible,this.castShadow=e.castShadow,this.receiveShadow=e.receiveShadow,this.frustumCulled=e.frustumCulled,this.renderOrder=e.renderOrder,this.animations=e.animations.slice(),this.userData=JSON.parse(JSON.stringify(e.userData)),!0===t)for(let t=0;t<e.children.length;t++){const n=e.children[t];this.add(n.clone())}return this}}ta.DEFAULT_UP=new Es(0,1,0),ta.DEFAULT_MATRIX_AUTO_UPDATE=!0,ta.DEFAULT_MATRIX_WORLD_AUTO_UPDATE=!0;const na=new Es,ia=new Es,ra=new Es,sa=new Es,oa=new Es,aa=new Es,la=new Es,ua=new Es,ca=new Es,da=new Es,ha=new Js,fa=new Js,pa=new Js;class ga{constructor(e=new Es,t=new Es,n=new Es){this.a=e,this.b=t,this.c=n}static getNormal(e,t,n,i){i.subVectors(n,t),na.subVectors(e,t),i.cross(na);const r=i.lengthSq();return r>0?i.multiplyScalar(1/Math.sqrt(r)):i.set(0,0,0)}static getBarycoord(e,t,n,i,r){na.subVectors(i,t),ia.subVectors(n,t),ra.subVectors(e,t);const s=na.dot(na),o=na.dot(ia),a=na.dot(ra),l=ia.dot(ia),u=ia.dot(ra),c=s*l-o*o;if(0===c)return r.set(0,0,0),null;const d=1/c,h=(l*a-o*u)*d,f=(s*u-o*a)*d;return r.set(1-h-f,f,h)}static containsPoint(e,t,n,i){return null!==this.getBarycoord(e,t,n,i,sa)&&(sa.x>=0&&sa.y>=0&&sa.x+sa.y<=1)}static getInterpolation(e,t,n,i,r,s,o,a){return null===this.getBarycoord(e,t,n,i,sa)?(a.x=0,a.y=0,"z"in a&&(a.z=0),"w"in a&&(a.w=0),null):(a.setScalar(0),a.addScaledVector(r,sa.x),a.addScaledVector(s,sa.y),a.addScaledVector(o,sa.z),a)}static getInterpolatedAttribute(e,t,n,i,r,s){return ha.setScalar(0),fa.setScalar(0),pa.setScalar(0),ha.fromBufferAttribute(e,t),fa.fromBufferAttribute(e,n),pa.fromBufferAttribute(e,i),s.setScalar(0),s.addScaledVector(ha,r.x),s.addScaledVector(fa,r.y),s.addScaledVector(pa,r.z),s}static isFrontFacing(e,t,n,i){return na.subVectors(n,t),ia.subVectors(e,t),na.cross(ia).dot(i)<0}set(e,t,n){return this.a.copy(e),this.b.copy(t),this.c.copy(n),this}setFromPointsAndIndices(e,t,n,i){return this.a.copy(e[t]),this.b.copy(e[n]),this.c.copy(e[i]),this}setFromAttributeAndIndices(e,t,n,i){return this.a.fromBufferAttribute(e,t),this.b.fromBufferAttribute(e,n),this.c.fromBufferAttribute(e,i),this}clone(){return(new this.constructor).copy(this)}copy(e){return this.a.copy(e.a),this.b.copy(e.b),this.c.copy(e.c),this}getArea(){return na.subVectors(this.c,this.b),ia.subVectors(this.a,this.b),.5*na.cross(ia).length()}getMidpoint(e){return e.addVectors(this.a,this.b).add(this.c).multiplyScalar(1/3)}getNormal(e){return ga.getNormal(this.a,this.b,this.c,e)}getPlane(e){return e.setFromCoplanarPoints(this.a,this.b,this.c)}getBarycoord(e,t){return ga.getBarycoord(e,this.a,this.b,this.c,t)}getInterpolation(e,t,n,i,r){return ga.getInterpolation(e,this.a,this.b,this.c,t,n,i,r)}containsPoint(e){return ga.containsPoint(e,this.a,this.b,this.c)}isFrontFacing(e){return ga.isFrontFacing(this.a,this.b,this.c,e)}intersectsBox(e){return e.intersectsTriangle(this)}closestPointToPoint(e,t){const n=this.a,i=this.b,r=this.c;let s,o;oa.subVectors(i,n),aa.subVectors(r,n),ua.subVectors(e,n);const a=oa.dot(ua),l=aa.dot(ua);if(a<=0&&l<=0)return t.copy(n);ca.subVectors(e,i);const u=oa.dot(ca),c=aa.dot(ca);if(u>=0&&c<=u)return t.copy(i);const d=a*c-u*l;if(d<=0&&a>=0&&u<=0)return s=a/(a-u),t.copy(n).addScaledVector(oa,s);da.subVectors(e,r);const h=oa.dot(da),f=aa.dot(da);if(f>=0&&h<=f)return t.copy(r);const p=h*l-a*f;if(p<=0&&l>=0&&f<=0)return o=l/(l-f),t.copy(n).addScaledVector(aa,o);const g=u*f-h*c;if(g<=0&&c-u>=0&&h-f>=0)return la.subVectors(r,i),o=(c-u)/(c-u+(h-f)),t.copy(i).addScaledVector(la,o);const m=1/(g+p+d);return s=p*m,o=d*m,t.copy(n).addScaledVector(oa,s).addScaledVector(aa,o)}equals(e){return e.a.equals(this.a)&&e.b.equals(this.b)&&e.c.equals(this.c)}}const ma={aliceblue:15792383,antiquewhite:16444375,aqua:65535,aquamarine:8388564,azure:15794175,beige:16119260,bisque:16770244,black:0,blanchedalmond:16772045,blue:255,blueviolet:9055202,brown:10824234,burlywood:14596231,cadetblue:6266528,chartreuse:8388352,chocolate:13789470,coral:16744272,cornflowerblue:6591981,cornsilk:16775388,crimson:14423100,cyan:65535,darkblue:139,darkcyan:35723,darkgoldenrod:12092939,darkgray:11119017,darkgreen:25600,darkgrey:11119017,darkkhaki:12433259,darkmagenta:9109643,darkolivegreen:5597999,darkorange:16747520,darkorchid:10040012,darkred:9109504,darksalmon:15308410,darkseagreen:9419919,darkslateblue:4734347,darkslategray:3100495,darkslategrey:3100495,darkturquoise:52945,darkviolet:9699539,deeppink:16716947,deepskyblue:49151,dimgray:6908265,dimgrey:6908265,dodgerblue:2003199,firebrick:11674146,floralwhite:16775920,forestgreen:2263842,fuchsia:16711935,gainsboro:14474460,ghostwhite:16316671,gold:16766720,goldenrod:14329120,gray:8421504,green:32768,greenyellow:11403055,grey:8421504,honeydew:15794160,hotpink:16738740,indianred:13458524,indigo:4915330,ivory:16777200,khaki:15787660,lavender:15132410,lavenderblush:16773365,lawngreen:8190976,lemonchiffon:16775885,lightblue:11393254,lightcoral:15761536,lightcyan:14745599,lightgoldenrodyellow:16448210,lightgray:13882323,lightgreen:9498256,lightgrey:13882323,lightpink:16758465,lightsalmon:16752762,lightseagreen:2142890,lightskyblue:8900346,lightslategray:7833753,lightslategrey:7833753,lightsteelblue:11584734,lightyellow:16777184,lime:65280,limegreen:3329330,linen:16445670,magenta:16711935,maroon:8388608,mediumaquamarine:6737322,mediumblue:205,mediumorchid:12211667,mediumpurple:9662683,mediumseagreen:3978097,mediumslateblue:8087790,mediumspringgreen:64154,mediumturquoise:4772300,mediumvioletred:13047173,midnightblue:1644912,mintcream:16121850,mistyrose:16770273,moccasin:16770229,navajowhite:16768685,navy:128,oldlace:16643558,olive:8421376,olivedrab:7048739,orange:16753920,orangered:16729344,orchid:14315734,palegoldenrod:15657130,palegreen:10025880,paleturquoise:11529966,palevioletred:14381203,papayawhip:16773077,peachpuff:16767673,peru:13468991,pink:16761035,plum:14524637,powderblue:11591910,purple:8388736,rebeccapurple:6697881,red:16711680,rosybrown:12357519,royalblue:4286945,saddlebrown:9127187,salmon:16416882,sandybrown:16032864,seagreen:3050327,seashell:16774638,sienna:10506797,silver:12632256,skyblue:8900331,slateblue:6970061,slategray:7372944,slategrey:7372944,snow:16775930,springgreen:65407,steelblue:4620980,tan:13808780,teal:32896,thistle:14204888,tomato:16737095,turquoise:4251856,violet:15631086,wheat:16113331,white:16777215,whitesmoke:16119285,yellow:16776960,yellowgreen:10145074},va={h:0,s:0,l:0},Aa={h:0,s:0,l:0};function xa(e,t,n){return n<0&&(n+=1),n>1&&(n-=1),n<1/6?e+6*(t-e)*n:n<.5?t:n<2/3?e+6*(t-e)*(2/3-n):e}class ya{constructor(e,t,n){return this.isColor=!0,this.r=1,this.g=1,this.b=1,this.set(e,t,n)}set(e,t,n){if(void 0===t&&void 0===n){const t=e;t&&t.isColor?this.copy(t):"number"==typeof t?this.setHex(t):"string"==typeof t&&this.setStyle(t)}else this.setRGB(e,t,n);return this}setScalar(e){return this.r=e,this.g=e,this.b=e,this}setHex(e,t=qr){return e=Math.floor(e),this.r=(e>>16&255)/255,this.g=(e>>8&255)/255,this.b=(255&e)/255,ks.colorSpaceToWorking(this,t),this}setRGB(e,t,n,i=ks.workingColorSpace){return this.r=e,this.g=t,this.b=n,ks.colorSpaceToWorking(this,i),this}setHSL(e,t,n,i=ks.workingColorSpace){if(e=As(e,1),t=vs(t,0,1),n=vs(n,0,1),0===t)this.r=this.g=this.b=n;else{const i=n<=.5?n*(1+t):n+t-n*t,r=2*n-i;this.r=xa(r,i,e+1/3),this.g=xa(r,i,e),this.b=xa(r,i,e-1/3)}return ks.colorSpaceToWorking(this,i),this}setStyle(e,t=qr){function n(t){void 0!==t&&parseFloat(t)<1&&console.warn("THREE.Color: Alpha component of "+e+" will be ignored.")}let i;if(i=/^(\w+)\(([^\)]*)\)/.exec(e)){let r;const s=i[1],o=i[2];switch(s){case"rgb":case"rgba":if(r=/^\s*(\d+)\s*,\s*(\d+)\s*,\s*(\d+)\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec(o))return n(r[4]),this.setRGB(Math.min(255,parseInt(r[1],10))/255,Math.min(255,parseInt(r[2],10))/255,Math.min(255,parseInt(r[3],10))/255,t);if(r=/^\s*(\d+)\%\s*,\s*(\d+)\%\s*,\s*(\d+)\%\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec(o))return n(r[4]),this.setRGB(Math.min(100,parseInt(r[1],10))/100,Math.min(100,parseInt(r[2],10))/100,Math.min(100,parseInt(r[3],10))/100,t);break;case"hsl":case"hsla":if(r=/^\s*(\d*\.?\d+)\s*,\s*(\d*\.?\d+)\%\s*,\s*(\d*\.?\d+)\%\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec(o))return n(r[4]),this.setHSL(parseFloat(r[1])/360,parseFloat(r[2])/100,parseFloat(r[3])/100,t);break;default:console.warn("THREE.Color: Unknown color model "+e)}}else if(i=/^\#([A-Fa-f\d]+)$/.exec(e)){const n=i[1],r=n.length;if(3===r)return this.setRGB(parseInt(n.charAt(0),16)/15,parseInt(n.charAt(1),16)/15,parseInt(n.charAt(2),16)/15,t);if(6===r)return this.setHex(parseInt(n,16),t);console.warn("THREE.Color: Invalid hex color "+e)}else if(e&&e.length>0)return this.setColorName(e,t);return this}setColorName(e,t=qr){const n=ma[e.toLowerCase()];return void 0!==n?this.setHex(n,t):console.warn("THREE.Color: Unknown color "+e),this}clone(){return new this.constructor(this.r,this.g,this.b)}copy(e){return this.r=e.r,this.g=e.g,this.b=e.b,this}copySRGBToLinear(e){return this.r=Fs(e.r),this.g=Fs(e.g),this.b=Fs(e.b),this}copyLinearToSRGB(e){return this.r=Hs(e.r),this.g=Hs(e.g),this.b=Hs(e.b),this}convertSRGBToLinear(){return this.copySRGBToLinear(this),this}convertLinearToSRGB(){return this.copyLinearToSRGB(this),this}getHex(e=qr){return ks.workingToColorSpace(ba.copy(this),e),65536*Math.round(vs(255*ba.r,0,255))+256*Math.round(vs(255*ba.g,0,255))+Math.round(vs(255*ba.b,0,255))}getHexString(e=qr){return("000000"+this.getHex(e).toString(16)).slice(-6)}getHSL(e,t=ks.workingColorSpace){ks.workingToColorSpace(ba.copy(this),t);const n=ba.r,i=ba.g,r=ba.b,s=Math.max(n,i,r),o=Math.min(n,i,r);let a,l;const u=(o+s)/2;if(o===s)a=0,l=0;else{const e=s-o;switch(l=u<=.5?e/(s+o):e/(2-s-o),s){case n:a=(i-r)/e+(i<r?6:0);break;case i:a=(r-n)/e+2;break;case r:a=(n-i)/e+4}a/=6}return e.h=a,e.s=l,e.l=u,e}getRGB(e,t=ks.workingColorSpace){return ks.workingToColorSpace(ba.copy(this),t),e.r=ba.r,e.g=ba.g,e.b=ba.b,e}getStyle(e=qr){ks.workingToColorSpace(ba.copy(this),e);const t=ba.r,n=ba.g,i=ba.b;return e!==qr?`color(${e} ${t.toFixed(3)} ${n.toFixed(3)} ${i.toFixed(3)})`:`rgb(${Math.round(255*t)},${Math.round(255*n)},${Math.round(255*i)})`}offsetHSL(e,t,n){return this.getHSL(va),this.setHSL(va.h+e,va.s+t,va.l+n)}add(e){return this.r+=e.r,this.g+=e.g,this.b+=e.b,this}addColors(e,t){return this.r=e.r+t.r,this.g=e.g+t.g,this.b=e.b+t.b,this}addScalar(e){return this.r+=e,this.g+=e,this.b+=e,this}sub(e){return this.r=Math.max(0,this.r-e.r),this.g=Math.max(0,this.g-e.g),this.b=Math.max(0,this.b-e.b),this}multiply(e){return this.r*=e.r,this.g*=e.g,this.b*=e.b,this}multiplyScalar(e){return this.r*=e,this.g*=e,this.b*=e,this}lerp(e,t){return this.r+=(e.r-this.r)*t,this.g+=(e.g-this.g)*t,this.b+=(e.b-this.b)*t,this}lerpColors(e,t,n){return this.r=e.r+(t.r-e.r)*n,this.g=e.g+(t.g-e.g)*n,this.b=e.b+(t.b-e.b)*n,this}lerpHSL(e,t){this.getHSL(va),e.getHSL(Aa);const n=xs(va.h,Aa.h,t),i=xs(va.s,Aa.s,t),r=xs(va.l,Aa.l,t);return this.setHSL(n,i,r),this}setFromVector3(e){return this.r=e.x,this.g=e.y,this.b=e.z,this}applyMatrix3(e){const t=this.r,n=this.g,i=this.b,r=e.elements;return this.r=r[0]*t+r[3]*n+r[6]*i,this.g=r[1]*t+r[4]*n+r[7]*i,this.b=r[2]*t+r[5]*n+r[8]*i,this}equals(e){return e.r===this.r&&e.g===this.g&&e.b===this.b}fromArray(e,t=0){return this.r=e[t],this.g=e[t+1],this.b=e[t+2],this}toArray(e=[],t=0){return e[t]=this.r,e[t+1]=this.g,e[t+2]=this.b,e}fromBufferAttribute(e,t){return this.r=e.getX(t),this.g=e.getY(t),this.b=e.getZ(t),this}toJSON(){return this.getHex()}*[Symbol.iterator](){yield this.r,yield this.g,yield this.b}}const ba=new ya;ya.NAMES=ma;let wa=0;class Ca extends ds{constructor(){super(),this.isMaterial=!0,Object.defineProperty(this,"id",{value:wa++}),this.uuid=ms(),this.name="",this.type="Material",this.blending=1,this.side=0,this.vertexColors=!1,this.opacity=1,this.transparent=!1,this.alphaHash=!1,this.blendSrc=Ti,this.blendDst=Si,this.blendEquation=Mi,this.blendSrcAlpha=null,this.blendDstAlpha=null,this.blendEquationAlpha=null,this.blendColor=new ya(0,0,0),this.blendAlpha=0,this.depthFunc=3,this.depthTest=!0,this.depthWrite=!0,this.stencilWriteMask=255,this.stencilFunc=519,this.stencilRef=0,this.stencilFuncMask=255,this.stencilFail=ts,this.stencilZFail=ts,this.stencilZPass=ts,this.stencilWrite=!1,this.clippingPlanes=null,this.clipIntersection=!1,this.clipShadows=!1,this.shadowSide=null,this.colorWrite=!0,this.precision=null,this.polygonOffset=!1,this.polygonOffsetFactor=0,this.polygonOffsetUnits=0,this.dithering=!1,this.alphaToCoverage=!1,this.premultipliedAlpha=!1,this.forceSinglePass=!1,this.allowOverride=!0,this.visible=!0,this.toneMapped=!0,this.userData={},this.version=0,this._alphaTest=0}get alphaTest(){return this._alphaTest}set alphaTest(e){this._alphaTest>0!=e>0&&this.version++,this._alphaTest=e}onBeforeRender(){}onBeforeCompile(){}customProgramCacheKey(){return this.onBeforeCompile.toString()}setValues(e){if(void 0!==e)for(const t in e){const n=e[t];if(void 0===n){console.warn(`THREE.Material: parameter '${t}' has value of undefined.`);continue}const i=this[t];void 0!==i?i&&i.isColor?i.set(n):i&&i.isVector3&&n&&n.isVector3?i.copy(n):this[t]=n:console.warn(`THREE.Material: '${t}' is not a property of THREE.${this.type}.`)}}toJSON(e){const t=void 0===e||"string"==typeof e;t&&(e={textures:{},images:{}});const n={metadata:{version:4.7,type:"Material",generator:"Material.toJSON"}};function i(e){const t=[];for(const n in e){const i=e[n];delete i.metadata,t.push(i)}return t}if(n.uuid=this.uuid,n.type=this.type,""!==this.name&&(n.name=this.name),this.color&&this.color.isColor&&(n.color=this.color.getHex()),void 0!==this.roughness&&(n.roughness=this.roughness),void 0!==this.metalness&&(n.metalness=this.metalness),void 0!==this.sheen&&(n.sheen=this.sheen),this.sheenColor&&this.sheenColor.isColor&&(n.sheenColor=this.sheenColor.getHex()),void 0!==this.sheenRoughness&&(n.sheenRoughness=this.sheenRoughness),this.emissive&&this.emissive.isColor&&(n.emissive=this.emissive.getHex()),void 0!==this.emissiveIntensity&&1!==this.emissiveIntensity&&(n.emissiveIntensity=this.emissiveIntensity),this.specular&&this.specular.isColor&&(n.specular=this.specular.getHex()),void 0!==this.specularIntensity&&(n.specularIntensity=this.specularIntensity),this.specularColor&&this.specularColor.isColor&&(n.specularColor=this.specularColor.getHex()),void 0!==this.shininess&&(n.shininess=this.shininess),void 0!==this.clearcoat&&(n.clearcoat=this.clearcoat),void 0!==this.clearcoatRoughness&&(n.clearcoatRoughness=this.clearcoatRoughness),this.clearcoatMap&&this.clearcoatMap.isTexture&&(n.clearcoatMap=this.clearcoatMap.toJSON(e).uuid),this.clearcoatRoughnessMap&&this.clearcoatRoughnessMap.isTexture&&(n.clearcoatRoughnessMap=this.clearcoatRoughnessMap.toJSON(e).uuid),this.clearcoatNormalMap&&this.clearcoatNormalMap.isTexture&&(n.clearcoatNormalMap=this.clearcoatNormalMap.toJSON(e).uuid,n.clearcoatNormalScale=this.clearcoatNormalScale.toArray()),this.sheenColorMap&&this.sheenColorMap.isTexture&&(n.sheenColorMap=this.sheenColorMap.toJSON(e).uuid),this.sheenRoughnessMap&&this.sheenRoughnessMap.isTexture&&(n.sheenRoughnessMap=this.sheenRoughnessMap.toJSON(e).uuid),void 0!==this.dispersion&&(n.dispersion=this.dispersion),void 0!==this.iridescence&&(n.iridescence=this.iridescence),void 0!==this.iridescenceIOR&&(n.iridescenceIOR=this.iridescenceIOR),void 0!==this.iridescenceThicknessRange&&(n.iridescenceThicknessRange=this.iridescenceThicknessRange),this.iridescenceMap&&this.iridescenceMap.isTexture&&(n.iridescenceMap=this.iridescenceMap.toJSON(e).uuid),this.iridescenceThicknessMap&&this.iridescenceThicknessMap.isTexture&&(n.iridescenceThicknessMap=this.iridescenceThicknessMap.toJSON(e).uuid),void 0!==this.anisotropy&&(n.anisotropy=this.anisotropy),void 0!==this.anisotropyRotation&&(n.anisotropyRotation=this.anisotropyRotation),this.anisotropyMap&&this.anisotropyMap.isTexture&&(n.anisotropyMap=this.anisotropyMap.toJSON(e).uuid),this.map&&this.map.isTexture&&(n.map=this.map.toJSON(e).uuid),this.matcap&&this.matcap.isTexture&&(n.matcap=this.matcap.toJSON(e).uuid),this.alphaMap&&this.alphaMap.isTexture&&(n.alphaMap=this.alphaMap.toJSON(e).uuid),this.lightMap&&this.lightMap.isTexture&&(n.lightMap=this.lightMap.toJSON(e).uuid,n.lightMapIntensity=this.lightMapIntensity),this.aoMap&&this.aoMap.isTexture&&(n.aoMap=this.aoMap.toJSON(e).uuid,n.aoMapIntensity=this.aoMapIntensity),this.bumpMap&&this.bumpMap.isTexture&&(n.bumpMap=this.bumpMap.toJSON(e).uuid,n.bumpScale=this.bumpScale),this.normalMap&&this.normalMap.isTexture&&(n.normalMap=this.normalMap.toJSON(e).uuid,n.normalMapType=this.normalMapType,n.normalScale=this.normalScale.toArray()),this.displacementMap&&this.displacementMap.isTexture&&(n.displacementMap=this.displacementMap.toJSON(e).uuid,n.displacementScale=this.displacementScale,n.displacementBias=this.displacementBias),this.roughnessMap&&this.roughnessMap.isTexture&&(n.roughnessMap=this.roughnessMap.toJSON(e).uuid),this.metalnessMap&&this.metalnessMap.isTexture&&(n.metalnessMap=this.metalnessMap.toJSON(e).uuid),this.emissiveMap&&this.emissiveMap.isTexture&&(n.emissiveMap=this.emissiveMap.toJSON(e).uuid),this.specularMap&&this.specularMap.isTexture&&(n.specularMap=this.specularMap.toJSON(e).uuid),this.specularIntensityMap&&this.specularIntensityMap.isTexture&&(n.specularIntensityMap=this.specularIntensityMap.toJSON(e).uuid),this.specularColorMap&&this.specularColorMap.isTexture&&(n.specularColorMap=this.specularColorMap.toJSON(e).uuid),this.envMap&&this.envMap.isTexture&&(n.envMap=this.envMap.toJSON(e).uuid,void 0!==this.combine&&(n.combine=this.combine)),void 0!==this.envMapRotation&&(n.envMapRotation=this.envMapRotation.toArray()),void 0!==this.envMapIntensity&&(n.envMapIntensity=this.envMapIntensity),void 0!==this.reflectivity&&(n.reflectivity=this.reflectivity),void 0!==this.refractionRatio&&(n.refractionRatio=this.refractionRatio),this.gradientMap&&this.gradientMap.isTexture&&(n.gradientMap=this.gradientMap.toJSON(e).uuid),void 0!==this.transmission&&(n.transmission=this.transmission),this.transmissionMap&&this.transmissionMap.isTexture&&(n.transmissionMap=this.transmissionMap.toJSON(e).uuid),void 0!==this.thickness&&(n.thickness=this.thickness),this.thicknessMap&&this.thicknessMap.isTexture&&(n.thicknessMap=this.thicknessMap.toJSON(e).uuid),void 0!==this.attenuationDistance&&this.attenuationDistance!==1/0&&(n.attenuationDistance=this.attenuationDistance),void 0!==this.attenuationColor&&(n.attenuationColor=this.attenuationColor.getHex()),void 0!==this.size&&(n.size=this.size),null!==this.shadowSide&&(n.shadowSide=this.shadowSide),void 0!==this.sizeAttenuation&&(n.sizeAttenuation=this.sizeAttenuation),1!==this.blending&&(n.blending=this.blending),0!==this.side&&(n.side=this.side),!0===this.vertexColors&&(n.vertexColors=!0),this.opacity<1&&(n.opacity=this.opacity),!0===this.transparent&&(n.transparent=!0),this.blendSrc!==Ti&&(n.blendSrc=this.blendSrc),this.blendDst!==Si&&(n.blendDst=this.blendDst),this.blendEquation!==Mi&&(n.blendEquation=this.blendEquation),null!==this.blendSrcAlpha&&(n.blendSrcAlpha=this.blendSrcAlpha),null!==this.blendDstAlpha&&(n.blendDstAlpha=this.blendDstAlpha),null!==this.blendEquationAlpha&&(n.blendEquationAlpha=this.blendEquationAlpha),this.blendColor&&this.blendColor.isColor&&(n.blendColor=this.blendColor.getHex()),0!==this.blendAlpha&&(n.blendAlpha=this.blendAlpha),3!==this.depthFunc&&(n.depthFunc=this.depthFunc),!1===this.depthTest&&(n.depthTest=this.depthTest),!1===this.depthWrite&&(n.depthWrite=this.depthWrite),!1===this.colorWrite&&(n.colorWrite=this.colorWrite),255!==this.stencilWriteMask&&(n.stencilWriteMask=this.stencilWriteMask),519!==this.stencilFunc&&(n.stencilFunc=this.stencilFunc),0!==this.stencilRef&&(n.stencilRef=this.stencilRef),255!==this.stencilFuncMask&&(n.stencilFuncMask=this.stencilFuncMask),this.stencilFail!==ts&&(n.stencilFail=this.stencilFail),this.stencilZFail!==ts&&(n.stencilZFail=this.stencilZFail),this.stencilZPass!==ts&&(n.stencilZPass=this.stencilZPass),!0===this.stencilWrite&&(n.stencilWrite=this.stencilWrite),void 0!==this.rotation&&0!==this.rotation&&(n.rotation=this.rotation),!0===this.polygonOffset&&(n.polygonOffset=!0),0!==this.polygonOffsetFactor&&(n.polygonOffsetFactor=this.polygonOffsetFactor),0!==this.polygonOffsetUnits&&(n.polygonOffsetUnits=this.polygonOffsetUnits),void 0!==this.linewidth&&1!==this.linewidth&&(n.linewidth=this.linewidth),void 0!==this.dashSize&&(n.dashSize=this.dashSize),void 0!==this.gapSize&&(n.gapSize=this.gapSize),void 0!==this.scale&&(n.scale=this.scale),!0===this.dithering&&(n.dithering=!0),this.alphaTest>0&&(n.alphaTest=this.alphaTest),!0===this.alphaHash&&(n.alphaHash=!0),!0===this.alphaToCoverage&&(n.alphaToCoverage=!0),!0===this.premultipliedAlpha&&(n.premultipliedAlpha=!0),!0===this.forceSinglePass&&(n.forceSinglePass=!0),!0===this.wireframe&&(n.wireframe=!0),this.wireframeLinewidth>1&&(n.wireframeLinewidth=this.wireframeLinewidth),"round"!==this.wireframeLinecap&&(n.wireframeLinecap=this.wireframeLinecap),"round"!==this.wireframeLinejoin&&(n.wireframeLinejoin=this.wireframeLinejoin),!0===this.flatShading&&(n.flatShading=!0),!1===this.visible&&(n.visible=!1),!1===this.toneMapped&&(n.toneMapped=!1),!1===this.fog&&(n.fog=!1),Object.keys(this.userData).length>0&&(n.userData=this.userData),t){const t=i(e.textures),r=i(e.images);t.length>0&&(n.textures=t),r.length>0&&(n.images=r)}return n}clone(){return(new this.constructor).copy(this)}copy(e){this.name=e.name,this.blending=e.blending,this.side=e.side,this.vertexColors=e.vertexColors,this.opacity=e.opacity,this.transparent=e.transparent,this.blendSrc=e.blendSrc,this.blendDst=e.blendDst,this.blendEquation=e.blendEquation,this.blendSrcAlpha=e.blendSrcAlpha,this.blendDstAlpha=e.blendDstAlpha,this.blendEquationAlpha=e.blendEquationAlpha,this.blendColor.copy(e.blendColor),this.blendAlpha=e.blendAlpha,this.depthFunc=e.depthFunc,this.depthTest=e.depthTest,this.depthWrite=e.depthWrite,this.stencilWriteMask=e.stencilWriteMask,this.stencilFunc=e.stencilFunc,this.stencilRef=e.stencilRef,this.stencilFuncMask=e.stencilFuncMask,this.stencilFail=e.stencilFail,this.stencilZFail=e.stencilZFail,this.stencilZPass=e.stencilZPass,this.stencilWrite=e.stencilWrite;const t=e.clippingPlanes;let n=null;if(null!==t){const e=t.length;n=new Array(e);for(let i=0;i!==e;++i)n[i]=t[i].clone()}return this.clippingPlanes=n,this.clipIntersection=e.clipIntersection,this.clipShadows=e.clipShadows,this.shadowSide=e.shadowSide,this.colorWrite=e.colorWrite,this.precision=e.precision,this.polygonOffset=e.polygonOffset,this.polygonOffsetFactor=e.polygonOffsetFactor,this.polygonOffsetUnits=e.polygonOffsetUnits,this.dithering=e.dithering,this.alphaTest=e.alphaTest,this.alphaHash=e.alphaHash,this.alphaToCoverage=e.alphaToCoverage,this.premultipliedAlpha=e.premultipliedAlpha,this.forceSinglePass=e.forceSinglePass,this.visible=e.visible,this.toneMapped=e.toneMapped,this.userData=JSON.parse(JSON.stringify(e.userData)),this}dispose(){this.dispatchEvent({type:"dispose"})}set needsUpdate(e){!0===e&&this.version++}}class Ma extends Ca{constructor(e){super(),this.isMeshBasicMaterial=!0,this.type="MeshBasicMaterial",this.color=new ya(16777215),this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.specularMap=null,this.alphaMap=null,this.envMap=null,this.envMapRotation=new ko,this.combine=0,this.reflectivity=1,this.refractionRatio=.98,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap="round",this.wireframeLinejoin="round",this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.map=e.map,this.lightMap=e.lightMap,this.lightMapIntensity=e.lightMapIntensity,this.aoMap=e.aoMap,this.aoMapIntensity=e.aoMapIntensity,this.specularMap=e.specularMap,this.alphaMap=e.alphaMap,this.envMap=e.envMap,this.envMapRotation.copy(e.envMapRotation),this.combine=e.combine,this.reflectivity=e.reflectivity,this.refractionRatio=e.refractionRatio,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.wireframeLinecap=e.wireframeLinecap,this.wireframeLinejoin=e.wireframeLinejoin,this.fog=e.fog,this}}const Ea=Ta();function Ta(){const e=new ArrayBuffer(4),t=new Float32Array(e),n=new Uint32Array(e),i=new Uint32Array(512),r=new Uint32Array(512);for(let e=0;e<256;++e){const t=e-127;t<-27?(i[e]=0,i[256|e]=32768,r[e]=24,r[256|e]=24):t<-14?(i[e]=1024>>-t-14,i[256|e]=1024>>-t-14|32768,r[e]=-t-1,r[256|e]=-t-1):t<=15?(i[e]=t+15<<10,i[256|e]=t+15<<10|32768,r[e]=13,r[256|e]=13):t<128?(i[e]=31744,i[256|e]=64512,r[e]=24,r[256|e]=24):(i[e]=31744,i[256|e]=64512,r[e]=13,r[256|e]=13)}const s=new Uint32Array(2048),o=new Uint32Array(64),a=new Uint32Array(64);for(let e=1;e<1024;++e){let t=e<<13,n=0;for(;0==(8388608&t);)t<<=1,n-=8388608;t&=-8388609,n+=947912704,s[e]=t|n}for(let e=1024;e<2048;++e)s[e]=939524096+(e-1024<<13);for(let e=1;e<31;++e)o[e]=e<<23;o[31]=1199570944,o[32]=2147483648;for(let e=33;e<63;++e)o[e]=2147483648+(e-32<<23);o[63]=3347054592;for(let e=1;e<64;++e)32!==e&&(a[e]=1024);return{floatView:t,uint32View:n,baseTable:i,shiftTable:r,mantissaTable:s,exponentTable:o,offsetTable:a}}function Sa(e){Math.abs(e)>65504&&console.warn("THREE.DataUtils.toHalfFloat(): Value out of range."),e=vs(e,-65504,65504),Ea.floatView[0]=e;const t=Ea.uint32View[0],n=t>>23&511;return Ea.baseTable[n]+((8388607&t)>>Ea.shiftTable[n])}function Pa(e){const t=e>>10;return Ea.uint32View[0]=Ea.mantissaTable[Ea.offsetTable[t]+(1023&e)]+Ea.exponentTable[t],Ea.floatView[0]}const Na=new Es,Ba=new Cs;let Da=0;class Ia{constructor(e,t,n=!1){if(Array.isArray(e))throw new TypeError("THREE.BufferAttribute: array should be a Typed Array.");this.isBufferAttribute=!0,Object.defineProperty(this,"id",{value:Da++}),this.name="",this.array=e,this.itemSize=t,this.count=void 0!==e?e.length/t:0,this.normalized=n,this.usage=rs,this.updateRanges=[],this.gpuType=Ji,this.version=0}onUploadCallback(){}set needsUpdate(e){!0===e&&this.version++}setUsage(e){return this.usage=e,this}addUpdateRange(e,t){this.updateRanges.push({start:e,count:t})}clearUpdateRanges(){this.updateRanges.length=0}copy(e){return this.name=e.name,this.array=new e.array.constructor(e.array),this.itemSize=e.itemSize,this.count=e.count,this.normalized=e.normalized,this.usage=e.usage,this.gpuType=e.gpuType,this}copyAt(e,t,n){e*=this.itemSize,n*=t.itemSize;for(let i=0,r=this.itemSize;i<r;i++)this.array[e+i]=t.array[n+i];return this}copyArray(e){return this.array.set(e),this}applyMatrix3(e){if(2===this.itemSize)for(let t=0,n=this.count;t<n;t++)Ba.fromBufferAttribute(this,t),Ba.applyMatrix3(e),this.setXY(t,Ba.x,Ba.y);else if(3===this.itemSize)for(let t=0,n=this.count;t<n;t++)Na.fromBufferAttribute(this,t),Na.applyMatrix3(e),this.setXYZ(t,Na.x,Na.y,Na.z);return this}applyMatrix4(e){for(let t=0,n=this.count;t<n;t++)Na.fromBufferAttribute(this,t),Na.applyMatrix4(e),this.setXYZ(t,Na.x,Na.y,Na.z);return this}applyNormalMatrix(e){for(let t=0,n=this.count;t<n;t++)Na.fromBufferAttribute(this,t),Na.applyNormalMatrix(e),this.setXYZ(t,Na.x,Na.y,Na.z);return this}transformDirection(e){for(let t=0,n=this.count;t<n;t++)Na.fromBufferAttribute(this,t),Na.transformDirection(e),this.setXYZ(t,Na.x,Na.y,Na.z);return this}set(e,t=0){return this.array.set(e,t),this}getComponent(e,t){let n=this.array[e*this.itemSize+t];return this.normalized&&(n=ys(n,this.array)),n}setComponent(e,t,n){return this.normalized&&(n=bs(n,this.array)),this.array[e*this.itemSize+t]=n,this}getX(e){let t=this.array[e*this.itemSize];return this.normalized&&(t=ys(t,this.array)),t}setX(e,t){return this.normalized&&(t=bs(t,this.array)),this.array[e*this.itemSize]=t,this}getY(e){let t=this.array[e*this.itemSize+1];return this.normalized&&(t=ys(t,this.array)),t}setY(e,t){return this.normalized&&(t=bs(t,this.array)),this.array[e*this.itemSize+1]=t,this}getZ(e){let t=this.array[e*this.itemSize+2];return this.normalized&&(t=ys(t,this.array)),t}setZ(e,t){return this.normalized&&(t=bs(t,this.array)),this.array[e*this.itemSize+2]=t,this}getW(e){let t=this.array[e*this.itemSize+3];return this.normalized&&(t=ys(t,this.array)),t}setW(e,t){return this.normalized&&(t=bs(t,this.array)),this.array[e*this.itemSize+3]=t,this}setXY(e,t,n){return e*=this.itemSize,this.normalized&&(t=bs(t,this.array),n=bs(n,this.array)),this.array[e+0]=t,this.array[e+1]=n,this}setXYZ(e,t,n,i){return e*=this.itemSize,this.normalized&&(t=bs(t,this.array),n=bs(n,this.array),i=bs(i,this.array)),this.array[e+0]=t,this.array[e+1]=n,this.array[e+2]=i,this}setXYZW(e,t,n,i,r){return e*=this.itemSize,this.normalized&&(t=bs(t,this.array),n=bs(n,this.array),i=bs(i,this.array),r=bs(r,this.array)),this.array[e+0]=t,this.array[e+1]=n,this.array[e+2]=i,this.array[e+3]=r,this}onUpload(e){return this.onUploadCallback=e,this}clone(){return new this.constructor(this.array,this.itemSize).copy(this)}toJSON(){const e={itemSize:this.itemSize,type:this.array.constructor.name,array:Array.from(this.array),normalized:this.normalized};return""!==this.name&&(e.name=this.name),this.usage!==rs&&(e.usage=this.usage),e}}class La extends Ia{constructor(e,t,n){super(new Uint16Array(e),t,n)}}class ja extends Ia{constructor(e,t,n){super(new Uint32Array(e),t,n)}}class Oa extends Ia{constructor(e,t,n){super(new Uint16Array(e),t,n),this.isFloat16BufferAttribute=!0}getX(e){let t=Pa(this.array[e*this.itemSize]);return this.normalized&&(t=ys(t,this.array)),t}setX(e,t){return this.normalized&&(t=bs(t,this.array)),this.array[e*this.itemSize]=Sa(t),this}getY(e){let t=Pa(this.array[e*this.itemSize+1]);return this.normalized&&(t=ys(t,this.array)),t}setY(e,t){return this.normalized&&(t=bs(t,this.array)),this.array[e*this.itemSize+1]=Sa(t),this}getZ(e){let t=Pa(this.array[e*this.itemSize+2]);return this.normalized&&(t=ys(t,this.array)),t}setZ(e,t){return this.normalized&&(t=bs(t,this.array)),this.array[e*this.itemSize+2]=Sa(t),this}getW(e){let t=Pa(this.array[e*this.itemSize+3]);return this.normalized&&(t=ys(t,this.array)),t}setW(e,t){return this.normalized&&(t=bs(t,this.array)),this.array[e*this.itemSize+3]=Sa(t),this}setXY(e,t,n){return e*=this.itemSize,this.normalized&&(t=bs(t,this.array),n=bs(n,this.array)),this.array[e+0]=Sa(t),this.array[e+1]=Sa(n),this}setXYZ(e,t,n,i){return e*=this.itemSize,this.normalized&&(t=bs(t,this.array),n=bs(n,this.array),i=bs(i,this.array)),this.array[e+0]=Sa(t),this.array[e+1]=Sa(n),this.array[e+2]=Sa(i),this}setXYZW(e,t,n,i,r){return e*=this.itemSize,this.normalized&&(t=bs(t,this.array),n=bs(n,this.array),i=bs(i,this.array),r=bs(r,this.array)),this.array[e+0]=Sa(t),this.array[e+1]=Sa(n),this.array[e+2]=Sa(i),this.array[e+3]=Sa(r),this}}class za extends Ia{constructor(e,t,n){super(new Float32Array(e),t,n)}}let Ra=0;const ka=new Po,Fa=new ta,Ha=new Es,Ua=new eo,Xa=new eo,Ga=new Es;class Va extends ds{constructor(){super(),this.isBufferGeometry=!0,Object.defineProperty(this,"id",{value:Ra++}),this.uuid=ms(),this.name="",this.type="BufferGeometry",this.index=null,this.indirect=null,this.attributes={},this.morphAttributes={},this.morphTargetsRelative=!1,this.groups=[],this.boundingBox=null,this.boundingSphere=null,this.drawRange={start:0,count:1/0},this.userData={}}getIndex(){return this.index}setIndex(e){return Array.isArray(e)?this.index=new(Bs(e)?ja:La)(e,1):this.index=e,this}setIndirect(e){return this.indirect=e,this}getIndirect(){return this.indirect}getAttribute(e){return this.attributes[e]}setAttribute(e,t){return this.attributes[e]=t,this}deleteAttribute(e){return delete this.attributes[e],this}hasAttribute(e){return void 0!==this.attributes[e]}addGroup(e,t,n=0){this.groups.push({start:e,count:t,materialIndex:n})}clearGroups(){this.groups=[]}setDrawRange(e,t){this.drawRange.start=e,this.drawRange.count=t}applyMatrix4(e){const t=this.attributes.position;void 0!==t&&(t.applyMatrix4(e),t.needsUpdate=!0);const n=this.attributes.normal;if(void 0!==n){const t=(new Ps).getNormalMatrix(e);n.applyNormalMatrix(t),n.needsUpdate=!0}const i=this.attributes.tangent;return void 0!==i&&(i.transformDirection(e),i.needsUpdate=!0),null!==this.boundingBox&&this.computeBoundingBox(),null!==this.boundingSphere&&this.computeBoundingSphere(),this}applyQuaternion(e){return ka.makeRotationFromQuaternion(e),this.applyMatrix4(ka),this}rotateX(e){return ka.makeRotationX(e),this.applyMatrix4(ka),this}rotateY(e){return ka.makeRotationY(e),this.applyMatrix4(ka),this}rotateZ(e){return ka.makeRotationZ(e),this.applyMatrix4(ka),this}translate(e,t,n){return ka.makeTranslation(e,t,n),this.applyMatrix4(ka),this}scale(e,t,n){return ka.makeScale(e,t,n),this.applyMatrix4(ka),this}lookAt(e){return Fa.lookAt(e),Fa.updateMatrix(),this.applyMatrix4(Fa.matrix),this}center(){return this.computeBoundingBox(),this.boundingBox.getCenter(Ha).negate(),this.translate(Ha.x,Ha.y,Ha.z),this}setFromPoints(e){const t=this.getAttribute("position");if(void 0===t){const t=[];for(let n=0,i=e.length;n<i;n++){const i=e[n];t.push(i.x,i.y,i.z||0)}this.setAttribute("position",new za(t,3))}else{const n=Math.min(e.length,t.count);for(let i=0;i<n;i++){const n=e[i];t.setXYZ(i,n.x,n.y,n.z||0)}e.length>t.count&&console.warn("THREE.BufferGeometry: Buffer size too small for points data. Use .dispose() and create a new geometry."),t.needsUpdate=!0}return this}computeBoundingBox(){null===this.boundingBox&&(this.boundingBox=new eo);const e=this.attributes.position,t=this.morphAttributes.position;if(e&&e.isGLBufferAttribute)return console.error("THREE.BufferGeometry.computeBoundingBox(): GLBufferAttribute requires a manual bounding box.",this),void this.boundingBox.set(new Es(-1/0,-1/0,-1/0),new Es(1/0,1/0,1/0));if(void 0!==e){if(this.boundingBox.setFromBufferAttribute(e),t)for(let e=0,n=t.length;e<n;e++){const n=t[e];Ua.setFromBufferAttribute(n),this.morphTargetsRelative?(Ga.addVectors(this.boundingBox.min,Ua.min),this.boundingBox.expandByPoint(Ga),Ga.addVectors(this.boundingBox.max,Ua.max),this.boundingBox.expandByPoint(Ga)):(this.boundingBox.expandByPoint(Ua.min),this.boundingBox.expandByPoint(Ua.max))}}else this.boundingBox.makeEmpty();(isNaN(this.boundingBox.min.x)||isNaN(this.boundingBox.min.y)||isNaN(this.boundingBox.min.z))&&console.error('THREE.BufferGeometry.computeBoundingBox(): Computed min/max have NaN values. The "position" attribute is likely to have NaN values.',this)}computeBoundingSphere(){null===this.boundingSphere&&(this.boundingSphere=new xo);const e=this.attributes.position,t=this.morphAttributes.position;if(e&&e.isGLBufferAttribute)return console.error("THREE.BufferGeometry.computeBoundingSphere(): GLBufferAttribute requires a manual bounding sphere.",this),void this.boundingSphere.set(new Es,1/0);if(e){const n=this.boundingSphere.center;if(Ua.setFromBufferAttribute(e),t)for(let e=0,n=t.length;e<n;e++){const n=t[e];Xa.setFromBufferAttribute(n),this.morphTargetsRelative?(Ga.addVectors(Ua.min,Xa.min),Ua.expandByPoint(Ga),Ga.addVectors(Ua.max,Xa.max),Ua.expandByPoint(Ga)):(Ua.expandByPoint(Xa.min),Ua.expandByPoint(Xa.max))}Ua.getCenter(n);let i=0;for(let t=0,r=e.count;t<r;t++)Ga.fromBufferAttribute(e,t),i=Math.max(i,n.distanceToSquared(Ga));if(t)for(let r=0,s=t.length;r<s;r++){const s=t[r],o=this.morphTargetsRelative;for(let t=0,r=s.count;t<r;t++)Ga.fromBufferAttribute(s,t),o&&(Ha.fromBufferAttribute(e,t),Ga.add(Ha)),i=Math.max(i,n.distanceToSquared(Ga))}this.boundingSphere.radius=Math.sqrt(i),isNaN(this.boundingSphere.radius)&&console.error('THREE.BufferGeometry.computeBoundingSphere(): Computed radius is NaN. The "position" attribute is likely to have NaN values.',this)}}computeTangents(){const e=this.index,t=this.attributes;if(null===e||void 0===t.position||void 0===t.normal||void 0===t.uv)return void console.error("THREE.BufferGeometry: .computeTangents() failed. Missing required attributes (index, position, normal or uv)");const n=t.position,i=t.normal,r=t.uv;!1===this.hasAttribute("tangent")&&this.setAttribute("tangent",new Ia(new Float32Array(4*n.count),4));const s=this.getAttribute("tangent"),o=[],a=[];for(let e=0;e<n.count;e++)o[e]=new Es,a[e]=new Es;const l=new Es,u=new Es,c=new Es,d=new Cs,h=new Cs,f=new Cs,p=new Es,g=new Es;function m(e,t,i){l.fromBufferAttribute(n,e),u.fromBufferAttribute(n,t),c.fromBufferAttribute(n,i),d.fromBufferAttribute(r,e),h.fromBufferAttribute(r,t),f.fromBufferAttribute(r,i),u.sub(l),c.sub(l),h.sub(d),f.sub(d);const s=1/(h.x*f.y-f.x*h.y);isFinite(s)&&(p.copy(u).multiplyScalar(f.y).addScaledVector(c,-h.y).multiplyScalar(s),g.copy(c).multiplyScalar(h.x).addScaledVector(u,-f.x).multiplyScalar(s),o[e].add(p),o[t].add(p),o[i].add(p),a[e].add(g),a[t].add(g),a[i].add(g))}let v=this.groups;0===v.length&&(v=[{start:0,count:e.count}]);for(let t=0,n=v.length;t<n;++t){const n=v[t],i=n.start;for(let t=i,r=i+n.count;t<r;t+=3)m(e.getX(t+0),e.getX(t+1),e.getX(t+2))}const A=new Es,x=new Es,y=new Es,b=new Es;function w(e){y.fromBufferAttribute(i,e),b.copy(y);const t=o[e];A.copy(t),A.sub(y.multiplyScalar(y.dot(t))).normalize(),x.crossVectors(b,t);const n=x.dot(a[e])<0?-1:1;s.setXYZW(e,A.x,A.y,A.z,n)}for(let t=0,n=v.length;t<n;++t){const n=v[t],i=n.start;for(let t=i,r=i+n.count;t<r;t+=3)w(e.getX(t+0)),w(e.getX(t+1)),w(e.getX(t+2))}}computeVertexNormals(){const e=this.index,t=this.getAttribute("position");if(void 0!==t){let n=this.getAttribute("normal");if(void 0===n)n=new Ia(new Float32Array(3*t.count),3),this.setAttribute("normal",n);else for(let e=0,t=n.count;e<t;e++)n.setXYZ(e,0,0,0);const i=new Es,r=new Es,s=new Es,o=new Es,a=new Es,l=new Es,u=new Es,c=new Es;if(e)for(let d=0,h=e.count;d<h;d+=3){const h=e.getX(d+0),f=e.getX(d+1),p=e.getX(d+2);i.fromBufferAttribute(t,h),r.fromBufferAttribute(t,f),s.fromBufferAttribute(t,p),u.subVectors(s,r),c.subVectors(i,r),u.cross(c),o.fromBufferAttribute(n,h),a.fromBufferAttribute(n,f),l.fromBufferAttribute(n,p),o.add(u),a.add(u),l.add(u),n.setXYZ(h,o.x,o.y,o.z),n.setXYZ(f,a.x,a.y,a.z),n.setXYZ(p,l.x,l.y,l.z)}else for(let e=0,o=t.count;e<o;e+=3)i.fromBufferAttribute(t,e+0),r.fromBufferAttribute(t,e+1),s.fromBufferAttribute(t,e+2),u.subVectors(s,r),c.subVectors(i,r),u.cross(c),n.setXYZ(e+0,u.x,u.y,u.z),n.setXYZ(e+1,u.x,u.y,u.z),n.setXYZ(e+2,u.x,u.y,u.z);this.normalizeNormals(),n.needsUpdate=!0}}normalizeNormals(){const e=this.attributes.normal;for(let t=0,n=e.count;t<n;t++)Ga.fromBufferAttribute(e,t),Ga.normalize(),e.setXYZ(t,Ga.x,Ga.y,Ga.z)}toNonIndexed(){function e(e,t){const n=e.array,i=e.itemSize,r=e.normalized,s=new n.constructor(t.length*i);let o=0,a=0;for(let r=0,l=t.length;r<l;r++){o=e.isInterleavedBufferAttribute?t[r]*e.data.stride+e.offset:t[r]*i;for(let e=0;e<i;e++)s[a++]=n[o++]}return new Ia(s,i,r)}if(null===this.index)return console.warn("THREE.BufferGeometry.toNonIndexed(): BufferGeometry is already non-indexed."),this;const t=new Va,n=this.index.array,i=this.attributes;for(const r in i){const s=e(i[r],n);t.setAttribute(r,s)}const r=this.morphAttributes;for(const i in r){const s=[],o=r[i];for(let t=0,i=o.length;t<i;t++){const i=e(o[t],n);s.push(i)}t.morphAttributes[i]=s}t.morphTargetsRelative=this.morphTargetsRelative;const s=this.groups;for(let e=0,n=s.length;e<n;e++){const n=s[e];t.addGroup(n.start,n.count,n.materialIndex)}return t}toJSON(){const e={metadata:{version:4.7,type:"BufferGeometry",generator:"BufferGeometry.toJSON"}};if(e.uuid=this.uuid,e.type=this.type,""!==this.name&&(e.name=this.name),Object.keys(this.userData).length>0&&(e.userData=this.userData),void 0!==this.parameters){const t=this.parameters;for(const n in t)void 0!==t[n]&&(e[n]=t[n]);return e}e.data={attributes:{}};const t=this.index;null!==t&&(e.data.index={type:t.array.constructor.name,array:Array.prototype.slice.call(t.array)});const n=this.attributes;for(const t in n){const i=n[t];e.data.attributes[t]=i.toJSON(e.data)}const i={};let r=!1;for(const t in this.morphAttributes){const n=this.morphAttributes[t],s=[];for(let t=0,i=n.length;t<i;t++){const i=n[t];s.push(i.toJSON(e.data))}s.length>0&&(i[t]=s,r=!0)}r&&(e.data.morphAttributes=i,e.data.morphTargetsRelative=this.morphTargetsRelative);const s=this.groups;s.length>0&&(e.data.groups=JSON.parse(JSON.stringify(s)));const o=this.boundingSphere;return null!==o&&(e.data.boundingSphere=o.toJSON()),e}clone(){return(new this.constructor).copy(this)}copy(e){this.index=null,this.attributes={},this.morphAttributes={},this.groups=[],this.boundingBox=null,this.boundingSphere=null;const t={};this.name=e.name;const n=e.index;null!==n&&this.setIndex(n.clone());const i=e.attributes;for(const e in i){const n=i[e];this.setAttribute(e,n.clone(t))}const r=e.morphAttributes;for(const e in r){const n=[],i=r[e];for(let e=0,r=i.length;e<r;e++)n.push(i[e].clone(t));this.morphAttributes[e]=n}this.morphTargetsRelative=e.morphTargetsRelative;const s=e.groups;for(let e=0,t=s.length;e<t;e++){const t=s[e];this.addGroup(t.start,t.count,t.materialIndex)}const o=e.boundingBox;null!==o&&(this.boundingBox=o.clone());const a=e.boundingSphere;return null!==a&&(this.boundingSphere=a.clone()),this.drawRange.start=e.drawRange.start,this.drawRange.count=e.drawRange.count,this.userData=e.userData,this}dispose(){this.dispatchEvent({type:"dispose"})}}const Wa=new Po,Qa=new So,Za=new xo,Ya=new Es,Ja=new Es,Ka=new Es,qa=new Es,_a=new Es,$a=new Es,el=new Es,tl=new Es;class nl extends ta{constructor(e=new Va,t=new Ma){super(),this.isMesh=!0,this.type="Mesh",this.geometry=e,this.material=t,this.morphTargetDictionary=void 0,this.morphTargetInfluences=void 0,this.count=1,this.updateMorphTargets()}copy(e,t){return super.copy(e,t),void 0!==e.morphTargetInfluences&&(this.morphTargetInfluences=e.morphTargetInfluences.slice()),void 0!==e.morphTargetDictionary&&(this.morphTargetDictionary=Object.assign({},e.morphTargetDictionary)),this.material=Array.isArray(e.material)?e.material.slice():e.material,this.geometry=e.geometry,this}updateMorphTargets(){const e=this.geometry.morphAttributes,t=Object.keys(e);if(t.length>0){const n=e[t[0]];if(void 0!==n){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,t=n.length;e<t;e++){const t=n[e].name||String(e);this.morphTargetInfluences.push(0),this.morphTargetDictionary[t]=e}}}}getVertexPosition(e,t){const n=this.geometry,i=n.attributes.position,r=n.morphAttributes.position,s=n.morphTargetsRelative;t.fromBufferAttribute(i,e);const o=this.morphTargetInfluences;if(r&&o){$a.set(0,0,0);for(let n=0,i=r.length;n<i;n++){const i=o[n],a=r[n];0!==i&&(_a.fromBufferAttribute(a,e),s?$a.addScaledVector(_a,i):$a.addScaledVector(_a.sub(t),i))}t.add($a)}return t}raycast(e,t){const n=this.geometry,i=this.material,r=this.matrixWorld;if(void 0!==i){if(null===n.boundingSphere&&n.computeBoundingSphere(),Za.copy(n.boundingSphere),Za.applyMatrix4(r),Qa.copy(e.ray).recast(e.near),!1===Za.containsPoint(Qa.origin)){if(null===Qa.intersectSphere(Za,Ya))return;if(Qa.origin.distanceToSquared(Ya)>(e.far-e.near)**2)return}Wa.copy(r).invert(),Qa.copy(e.ray).applyMatrix4(Wa),null!==n.boundingBox&&!1===Qa.intersectsBox(n.boundingBox)||this._computeIntersections(e,t,Qa)}}_computeIntersections(e,t,n){let i;const r=this.geometry,s=this.material,o=r.index,a=r.attributes.position,l=r.attributes.uv,u=r.attributes.uv1,c=r.attributes.normal,d=r.groups,h=r.drawRange;if(null!==o)if(Array.isArray(s))for(let r=0,a=d.length;r<a;r++){const a=d[r],f=s[a.materialIndex];for(let r=Math.max(a.start,h.start),s=Math.min(o.count,Math.min(a.start+a.count,h.start+h.count));r<s;r+=3){i=il(this,f,e,n,l,u,c,o.getX(r),o.getX(r+1),o.getX(r+2)),i&&(i.faceIndex=Math.floor(r/3),i.face.materialIndex=a.materialIndex,t.push(i))}}else{for(let r=Math.max(0,h.start),a=Math.min(o.count,h.start+h.count);r<a;r+=3){i=il(this,s,e,n,l,u,c,o.getX(r),o.getX(r+1),o.getX(r+2)),i&&(i.faceIndex=Math.floor(r/3),t.push(i))}}else if(void 0!==a)if(Array.isArray(s))for(let r=0,o=d.length;r<o;r++){const o=d[r],f=s[o.materialIndex];for(let r=Math.max(o.start,h.start),s=Math.min(a.count,Math.min(o.start+o.count,h.start+h.count));r<s;r+=3){i=il(this,f,e,n,l,u,c,r,r+1,r+2),i&&(i.faceIndex=Math.floor(r/3),i.face.materialIndex=o.materialIndex,t.push(i))}}else{for(let r=Math.max(0,h.start),o=Math.min(a.count,h.start+h.count);r<o;r+=3){i=il(this,s,e,n,l,u,c,r,r+1,r+2),i&&(i.faceIndex=Math.floor(r/3),t.push(i))}}}}function il(e,t,n,i,r,s,o,a,l,u){e.getVertexPosition(a,Ja),e.getVertexPosition(l,Ka),e.getVertexPosition(u,qa);const c=function(e,t,n,i,r,s,o,a){let l;if(l=1===t.side?i.intersectTriangle(o,s,r,!0,a):i.intersectTriangle(r,s,o,0===t.side,a),null===l)return null;tl.copy(a),tl.applyMatrix4(e.matrixWorld);const u=n.ray.origin.distanceTo(tl);return u<n.near||u>n.far?null:{distance:u,point:tl.clone(),object:e}}(e,t,n,i,Ja,Ka,qa,el);if(c){const e=new Es;ga.getBarycoord(el,Ja,Ka,qa,e),r&&(c.uv=ga.getInterpolatedAttribute(r,a,l,u,e,new Cs)),s&&(c.uv1=ga.getInterpolatedAttribute(s,a,l,u,e,new Cs)),o&&(c.normal=ga.getInterpolatedAttribute(o,a,l,u,e,new Es),c.normal.dot(i.direction)>0&&c.normal.multiplyScalar(-1));const t={a:a,b:l,c:u,normal:new Es,materialIndex:0};ga.getNormal(Ja,Ka,qa,t.normal),c.face=t,c.barycoord=e}return c}class rl extends Va{constructor(e=1,t=1,n=1,i=1,r=1,s=1){super(),this.type="BoxGeometry",this.parameters={width:e,height:t,depth:n,widthSegments:i,heightSegments:r,depthSegments:s};const o=this;i=Math.floor(i),r=Math.floor(r),s=Math.floor(s);const a=[],l=[],u=[],c=[];let d=0,h=0;function f(e,t,n,i,r,s,f,p,g,m,v){const A=s/g,x=f/m,y=s/2,b=f/2,w=p/2,C=g+1,M=m+1;let E=0,T=0;const S=new Es;for(let s=0;s<M;s++){const o=s*x-b;for(let a=0;a<C;a++){const d=a*A-y;S[e]=d*i,S[t]=o*r,S[n]=w,l.push(S.x,S.y,S.z),S[e]=0,S[t]=0,S[n]=p>0?1:-1,u.push(S.x,S.y,S.z),c.push(a/g),c.push(1-s/m),E+=1}}for(let e=0;e<m;e++)for(let t=0;t<g;t++){const n=d+t+C*e,i=d+t+C*(e+1),r=d+(t+1)+C*(e+1),s=d+(t+1)+C*e;a.push(n,i,s),a.push(i,r,s),T+=6}o.addGroup(h,T,v),h+=T,d+=E}f("z","y","x",-1,-1,n,t,e,s,r,0),f("z","y","x",1,-1,n,t,-e,s,r,1),f("x","z","y",1,1,e,n,t,i,s,2),f("x","z","y",1,-1,e,n,-t,i,s,3),f("x","y","z",1,-1,e,t,n,i,r,4),f("x","y","z",-1,-1,e,t,-n,i,r,5),this.setIndex(a),this.setAttribute("position",new za(l,3)),this.setAttribute("normal",new za(u,3)),this.setAttribute("uv",new za(c,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new rl(e.width,e.height,e.depth,e.widthSegments,e.heightSegments,e.depthSegments)}}function sl(e){const t={};for(const n in e){t[n]={};for(const i in e[n]){const r=e[n][i];r&&(r.isColor||r.isMatrix3||r.isMatrix4||r.isVector2||r.isVector3||r.isVector4||r.isTexture||r.isQuaternion)?r.isRenderTargetTexture?(console.warn("UniformsUtils: Textures of render targets cannot be cloned via cloneUniforms() or mergeUniforms()."),t[n][i]=null):t[n][i]=r.clone():Array.isArray(r)?t[n][i]=r.slice():t[n][i]=r}}return t}function ol(e){const t={};for(let n=0;n<e.length;n++){const i=sl(e[n]);for(const e in i)t[e]=i[e]}return t}function al(e){const t=e.getRenderTarget();return null===t?e.outputColorSpace:!0===t.isXRRenderTarget?t.texture.colorSpace:ks.workingColorSpace}const ll={clone:sl,merge:ol};class ul extends Ca{constructor(e){super(),this.isShaderMaterial=!0,this.type="ShaderMaterial",this.defines={},this.uniforms={},this.uniformsGroups=[],this.vertexShader="void main() {\n\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\n}",this.fragmentShader="void main() {\n\tgl_FragColor = vec4( 1.0, 0.0, 0.0, 1.0 );\n}",this.linewidth=1,this.wireframe=!1,this.wireframeLinewidth=1,this.fog=!1,this.lights=!1,this.clipping=!1,this.forceSinglePass=!0,this.extensions={clipCullDistance:!1,multiDraw:!1},this.defaultAttributeValues={color:[1,1,1],uv:[0,0],uv1:[0,0]},this.index0AttributeName=void 0,this.uniformsNeedUpdate=!1,this.glslVersion=null,void 0!==e&&this.setValues(e)}copy(e){return super.copy(e),this.fragmentShader=e.fragmentShader,this.vertexShader=e.vertexShader,this.uniforms=sl(e.uniforms),this.uniformsGroups=function(e){const t=[];for(let n=0;n<e.length;n++)t.push(e[n].clone());return t}(e.uniformsGroups),this.defines=Object.assign({},e.defines),this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.fog=e.fog,this.lights=e.lights,this.clipping=e.clipping,this.extensions=Object.assign({},e.extensions),this.glslVersion=e.glslVersion,this}toJSON(e){const t=super.toJSON(e);t.glslVersion=this.glslVersion,t.uniforms={};for(const n in this.uniforms){const i=this.uniforms[n].value;i&&i.isTexture?t.uniforms[n]={type:"t",value:i.toJSON(e).uuid}:i&&i.isColor?t.uniforms[n]={type:"c",value:i.getHex()}:i&&i.isVector2?t.uniforms[n]={type:"v2",value:i.toArray()}:i&&i.isVector3?t.uniforms[n]={type:"v3",value:i.toArray()}:i&&i.isVector4?t.uniforms[n]={type:"v4",value:i.toArray()}:i&&i.isMatrix3?t.uniforms[n]={type:"m3",value:i.toArray()}:i&&i.isMatrix4?t.uniforms[n]={type:"m4",value:i.toArray()}:t.uniforms[n]={value:i}}Object.keys(this.defines).length>0&&(t.defines=this.defines),t.vertexShader=this.vertexShader,t.fragmentShader=this.fragmentShader,t.lights=this.lights,t.clipping=this.clipping;const n={};for(const e in this.extensions)!0===this.extensions[e]&&(n[e]=!0);return Object.keys(n).length>0&&(t.extensions=n),t}}class cl extends ta{constructor(){super(),this.isCamera=!0,this.type="Camera",this.matrixWorldInverse=new Po,this.projectionMatrix=new Po,this.projectionMatrixInverse=new Po,this.coordinateSystem=as,this._reversedDepth=!1}get reversedDepth(){return this._reversedDepth}copy(e,t){return super.copy(e,t),this.matrixWorldInverse.copy(e.matrixWorldInverse),this.projectionMatrix.copy(e.projectionMatrix),this.projectionMatrixInverse.copy(e.projectionMatrixInverse),this.coordinateSystem=e.coordinateSystem,this}getWorldDirection(e){return super.getWorldDirection(e).negate()}updateMatrixWorld(e){super.updateMatrixWorld(e),this.matrixWorldInverse.copy(this.matrixWorld).invert()}updateWorldMatrix(e,t){super.updateWorldMatrix(e,t),this.matrixWorldInverse.copy(this.matrixWorld).invert()}clone(){return(new this.constructor).copy(this)}}const dl=new Es,hl=new Cs,fl=new Cs;class pl extends cl{constructor(e=50,t=1,n=.1,i=2e3){super(),this.isPerspectiveCamera=!0,this.type="PerspectiveCamera",this.fov=e,this.zoom=1,this.near=n,this.far=i,this.focus=10,this.aspect=t,this.view=null,this.filmGauge=35,this.filmOffset=0,this.updateProjectionMatrix()}copy(e,t){return super.copy(e,t),this.fov=e.fov,this.zoom=e.zoom,this.near=e.near,this.far=e.far,this.focus=e.focus,this.aspect=e.aspect,this.view=null===e.view?null:Object.assign({},e.view),this.filmGauge=e.filmGauge,this.filmOffset=e.filmOffset,this}setFocalLength(e){const t=.5*this.getFilmHeight()/e;this.fov=2*gs*Math.atan(t),this.updateProjectionMatrix()}getFocalLength(){const e=Math.tan(.5*ps*this.fov);return.5*this.getFilmHeight()/e}getEffectiveFOV(){return 2*gs*Math.atan(Math.tan(.5*ps*this.fov)/this.zoom)}getFilmWidth(){return this.filmGauge*Math.min(this.aspect,1)}getFilmHeight(){return this.filmGauge/Math.max(this.aspect,1)}getViewBounds(e,t,n){dl.set(-1,-1,.5).applyMatrix4(this.projectionMatrixInverse),t.set(dl.x,dl.y).multiplyScalar(-e/dl.z),dl.set(1,1,.5).applyMatrix4(this.projectionMatrixInverse),n.set(dl.x,dl.y).multiplyScalar(-e/dl.z)}getViewSize(e,t){return this.getViewBounds(e,hl,fl),t.subVectors(fl,hl)}setViewOffset(e,t,n,i,r,s){this.aspect=e/t,null===this.view&&(this.view={enabled:!0,fullWidth:1,fullHeight:1,offsetX:0,offsetY:0,width:1,height:1}),this.view.enabled=!0,this.view.fullWidth=e,this.view.fullHeight=t,this.view.offsetX=n,this.view.offsetY=i,this.view.width=r,this.view.height=s,this.updateProjectionMatrix()}clearViewOffset(){null!==this.view&&(this.view.enabled=!1),this.updateProjectionMatrix()}updateProjectionMatrix(){const e=this.near;let t=e*Math.tan(.5*ps*this.fov)/this.zoom,n=2*t,i=this.aspect*n,r=-.5*i;const s=this.view;if(null!==this.view&&this.view.enabled){const e=s.fullWidth,o=s.fullHeight;r+=s.offsetX*i/e,t-=s.offsetY*n/o,i*=s.width/e,n*=s.height/o}const o=this.filmOffset;0!==o&&(r+=e*o/this.getFilmWidth()),this.projectionMatrix.makePerspective(r,r+i,t,t-n,e,this.far,this.coordinateSystem,this.reversedDepth),this.projectionMatrixInverse.copy(this.projectionMatrix).invert()}toJSON(e){const t=super.toJSON(e);return t.object.fov=this.fov,t.object.zoom=this.zoom,t.object.near=this.near,t.object.far=this.far,t.object.focus=this.focus,t.object.aspect=this.aspect,null!==this.view&&(t.object.view=Object.assign({},this.view)),t.object.filmGauge=this.filmGauge,t.object.filmOffset=this.filmOffset,t}}const gl=-90;class ml extends ta{constructor(e,t,n){super(),this.type="CubeCamera",this.renderTarget=n,this.coordinateSystem=null,this.activeMipmapLevel=0;const i=new pl(gl,1,e,t);i.layers=this.layers,this.add(i);const r=new pl(gl,1,e,t);r.layers=this.layers,this.add(r);const s=new pl(gl,1,e,t);s.layers=this.layers,this.add(s);const o=new pl(gl,1,e,t);o.layers=this.layers,this.add(o);const a=new pl(gl,1,e,t);a.layers=this.layers,this.add(a);const l=new pl(gl,1,e,t);l.layers=this.layers,this.add(l)}updateCoordinateSystem(){const e=this.coordinateSystem,t=this.children.concat(),[n,i,r,s,o,a]=t;for(const e of t)this.remove(e);if(e===as)n.up.set(0,1,0),n.lookAt(1,0,0),i.up.set(0,1,0),i.lookAt(-1,0,0),r.up.set(0,0,-1),r.lookAt(0,1,0),s.up.set(0,0,1),s.lookAt(0,-1,0),o.up.set(0,1,0),o.lookAt(0,0,1),a.up.set(0,1,0),a.lookAt(0,0,-1);else{if(e!==ls)throw new Error("THREE.CubeCamera.updateCoordinateSystem(): Invalid coordinate system: "+e);n.up.set(0,-1,0),n.lookAt(-1,0,0),i.up.set(0,-1,0),i.lookAt(1,0,0),r.up.set(0,0,1),r.lookAt(0,1,0),s.up.set(0,0,-1),s.lookAt(0,-1,0),o.up.set(0,-1,0),o.lookAt(0,0,1),a.up.set(0,-1,0),a.lookAt(0,0,-1)}for(const e of t)this.add(e),e.updateMatrixWorld()}update(e,t){null===this.parent&&this.updateMatrixWorld();const{renderTarget:n,activeMipmapLevel:i}=this;this.coordinateSystem!==e.coordinateSystem&&(this.coordinateSystem=e.coordinateSystem,this.updateCoordinateSystem());const[r,s,o,a,l,u]=this.children,c=e.getRenderTarget(),d=e.getActiveCubeFace(),h=e.getActiveMipmapLevel(),f=e.xr.enabled;e.xr.enabled=!1;const p=n.texture.generateMipmaps;n.texture.generateMipmaps=!1,e.setRenderTarget(n,0,i),e.render(t,r),e.setRenderTarget(n,1,i),e.render(t,s),e.setRenderTarget(n,2,i),e.render(t,o),e.setRenderTarget(n,3,i),e.render(t,a),e.setRenderTarget(n,4,i),e.render(t,l),n.texture.generateMipmaps=p,e.setRenderTarget(n,5,i),e.render(t,u),e.setRenderTarget(c,d,h),e.xr.enabled=f,n.texture.needsPMREMUpdate=!0}}class vl extends Ys{constructor(e=[],t=301,n,i,r,s,o,a,l,u){super(e,t,n,i,r,s,o,a,l,u),this.isCubeTexture=!0,this.flipY=!1}get images(){return this.image}set images(e){this.image=e}}class Al extends qs{constructor(e=1,t={}){super(e,e,t),this.isWebGLCubeRenderTarget=!0;const n={width:e,height:e,depth:1},i=[n,n,n,n,n,n];this.texture=new vl(i),this._setTextureOptions(t),this.texture.isRenderTargetTexture=!0}fromEquirectangularTexture(e,t){this.texture.type=t.type,this.texture.colorSpace=t.colorSpace,this.texture.generateMipmaps=t.generateMipmaps,this.texture.minFilter=t.minFilter,this.texture.magFilter=t.magFilter;const n={uniforms:{tEquirect:{value:null}},vertexShader:"\n\n\t\t\t\tvarying vec3 vWorldDirection;\n\n\t\t\t\tvec3 transformDirection( in vec3 dir, in mat4 matrix ) {\n\n\t\t\t\t\treturn normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );\n\n\t\t\t\t}\n\n\t\t\t\tvoid main() {\n\n\t\t\t\t\tvWorldDirection = transformDirection( position, modelMatrix );\n\n\t\t\t\t\t#include <begin_vertex>\n\t\t\t\t\t#include <project_vertex>\n\n\t\t\t\t}\n\t\t\t",fragmentShader:"\n\n\t\t\t\tuniform sampler2D tEquirect;\n\n\t\t\t\tvarying vec3 vWorldDirection;\n\n\t\t\t\t#include <common>\n\n\t\t\t\tvoid main() {\n\n\t\t\t\t\tvec3 direction = normalize( vWorldDirection );\n\n\t\t\t\t\tvec2 sampleUV = equirectUv( direction );\n\n\t\t\t\t\tgl_FragColor = texture2D( tEquirect, sampleUV );\n\n\t\t\t\t}\n\t\t\t"},i=new rl(5,5,5),r=new ul({name:"CubemapFromEquirect",uniforms:sl(n.uniforms),vertexShader:n.vertexShader,fragmentShader:n.fragmentShader,side:1,blending:0});r.uniforms.tEquirect.value=t;const s=new nl(i,r),o=t.minFilter;t.minFilter===Xi&&(t.minFilter=Hi);return new ml(1,10,this).update(e,s),t.minFilter=o,s.geometry.dispose(),s.material.dispose(),this}clear(e,t=!0,n=!0,i=!0){const r=e.getRenderTarget();for(let r=0;r<6;r++)e.setRenderTarget(this,r),e.clear(t,n,i);e.setRenderTarget(r)}}class xl extends ta{constructor(){super(),this.isGroup=!0,this.type="Group"}}const yl={type:"move"};class bl{constructor(){this._targetRay=null,this._grip=null,this._hand=null}getHandSpace(){return null===this._hand&&(this._hand=new xl,this._hand.matrixAutoUpdate=!1,this._hand.visible=!1,this._hand.joints={},this._hand.inputState={pinching:!1}),this._hand}getTargetRaySpace(){return null===this._targetRay&&(this._targetRay=new xl,this._targetRay.matrixAutoUpdate=!1,this._targetRay.visible=!1,this._targetRay.hasLinearVelocity=!1,this._targetRay.linearVelocity=new Es,this._targetRay.hasAngularVelocity=!1,this._targetRay.angularVelocity=new Es),this._targetRay}getGripSpace(){return null===this._grip&&(this._grip=new xl,this._grip.matrixAutoUpdate=!1,this._grip.visible=!1,this._grip.hasLinearVelocity=!1,this._grip.linearVelocity=new Es,this._grip.hasAngularVelocity=!1,this._grip.angularVelocity=new Es),this._grip}dispatchEvent(e){return null!==this._targetRay&&this._targetRay.dispatchEvent(e),null!==this._grip&&this._grip.dispatchEvent(e),null!==this._hand&&this._hand.dispatchEvent(e),this}connect(e){if(e&&e.hand){const t=this._hand;if(t)for(const n of e.hand.values())this._getHandJoint(t,n)}return this.dispatchEvent({type:"connected",data:e}),this}disconnect(e){return this.dispatchEvent({type:"disconnected",data:e}),null!==this._targetRay&&(this._targetRay.visible=!1),null!==this._grip&&(this._grip.visible=!1),null!==this._hand&&(this._hand.visible=!1),this}update(e,t,n){let i=null,r=null,s=null;const o=this._targetRay,a=this._grip,l=this._hand;if(e&&"visible-blurred"!==t.session.visibilityState){if(l&&e.hand){s=!0;for(const i of e.hand.values()){const e=t.getJointPose(i,n),r=this._getHandJoint(l,i);null!==e&&(r.matrix.fromArray(e.transform.matrix),r.matrix.decompose(r.position,r.rotation,r.scale),r.matrixWorldNeedsUpdate=!0,r.jointRadius=e.radius),r.visible=null!==e}const i=l.joints["index-finger-tip"],r=l.joints["thumb-tip"],o=i.position.distanceTo(r.position),a=.02,u=.005;l.inputState.pinching&&o>a+u?(l.inputState.pinching=!1,this.dispatchEvent({type:"pinchend",handedness:e.handedness,target:this})):!l.inputState.pinching&&o<=a-u&&(l.inputState.pinching=!0,this.dispatchEvent({type:"pinchstart",handedness:e.handedness,target:this}))}else null!==a&&e.gripSpace&&(r=t.getPose(e.gripSpace,n),null!==r&&(a.matrix.fromArray(r.transform.matrix),a.matrix.decompose(a.position,a.rotation,a.scale),a.matrixWorldNeedsUpdate=!0,r.linearVelocity?(a.hasLinearVelocity=!0,a.linearVelocity.copy(r.linearVelocity)):a.hasLinearVelocity=!1,r.angularVelocity?(a.hasAngularVelocity=!0,a.angularVelocity.copy(r.angularVelocity)):a.hasAngularVelocity=!1));null!==o&&(i=t.getPose(e.targetRaySpace,n),null===i&&null!==r&&(i=r),null!==i&&(o.matrix.fromArray(i.transform.matrix),o.matrix.decompose(o.position,o.rotation,o.scale),o.matrixWorldNeedsUpdate=!0,i.linearVelocity?(o.hasLinearVelocity=!0,o.linearVelocity.copy(i.linearVelocity)):o.hasLinearVelocity=!1,i.angularVelocity?(o.hasAngularVelocity=!0,o.angularVelocity.copy(i.angularVelocity)):o.hasAngularVelocity=!1,this.dispatchEvent(yl)))}return null!==o&&(o.visible=null!==i),null!==a&&(a.visible=null!==r),null!==l&&(l.visible=null!==s),this}_getHandJoint(e,t){if(void 0===e.joints[t.jointName]){const n=new xl;n.matrixAutoUpdate=!1,n.visible=!1,e.joints[t.jointName]=n,e.add(n)}return e.joints[t.jointName]}}class wl extends ta{constructor(){super(),this.isScene=!0,this.type="Scene",this.background=null,this.environment=null,this.fog=null,this.backgroundBlurriness=0,this.backgroundIntensity=1,this.backgroundRotation=new ko,this.environmentIntensity=1,this.environmentRotation=new ko,this.overrideMaterial=null,"undefined"!=typeof __THREE_DEVTOOLS__&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent("observe",{detail:this}))}copy(e,t){return super.copy(e,t),null!==e.background&&(this.background=e.background.clone()),null!==e.environment&&(this.environment=e.environment.clone()),null!==e.fog&&(this.fog=e.fog.clone()),this.backgroundBlurriness=e.backgroundBlurriness,this.backgroundIntensity=e.backgroundIntensity,this.backgroundRotation.copy(e.backgroundRotation),this.environmentIntensity=e.environmentIntensity,this.environmentRotation.copy(e.environmentRotation),null!==e.overrideMaterial&&(this.overrideMaterial=e.overrideMaterial.clone()),this.matrixAutoUpdate=e.matrixAutoUpdate,this}toJSON(e){const t=super.toJSON(e);return null!==this.fog&&(t.object.fog=this.fog.toJSON()),this.backgroundBlurriness>0&&(t.object.backgroundBlurriness=this.backgroundBlurriness),1!==this.backgroundIntensity&&(t.object.backgroundIntensity=this.backgroundIntensity),t.object.backgroundRotation=this.backgroundRotation.toArray(),1!==this.environmentIntensity&&(t.object.environmentIntensity=this.environmentIntensity),t.object.environmentRotation=this.environmentRotation.toArray(),t}}class Cl{constructor(e,t){this.isInterleavedBuffer=!0,this.array=e,this.stride=t,this.count=void 0!==e?e.length/t:0,this.usage=rs,this.updateRanges=[],this.version=0,this.uuid=ms()}onUploadCallback(){}set needsUpdate(e){!0===e&&this.version++}setUsage(e){return this.usage=e,this}addUpdateRange(e,t){this.updateRanges.push({start:e,count:t})}clearUpdateRanges(){this.updateRanges.length=0}copy(e){return this.array=new e.array.constructor(e.array),this.count=e.count,this.stride=e.stride,this.usage=e.usage,this}copyAt(e,t,n){e*=this.stride,n*=t.stride;for(let i=0,r=this.stride;i<r;i++)this.array[e+i]=t.array[n+i];return this}set(e,t=0){return this.array.set(e,t),this}clone(e){void 0===e.arrayBuffers&&(e.arrayBuffers={}),void 0===this.array.buffer._uuid&&(this.array.buffer._uuid=ms()),void 0===e.arrayBuffers[this.array.buffer._uuid]&&(e.arrayBuffers[this.array.buffer._uuid]=this.array.slice(0).buffer);const t=new this.array.constructor(e.arrayBuffers[this.array.buffer._uuid]),n=new this.constructor(t,this.stride);return n.setUsage(this.usage),n}onUpload(e){return this.onUploadCallback=e,this}toJSON(e){return void 0===e.arrayBuffers&&(e.arrayBuffers={}),void 0===this.array.buffer._uuid&&(this.array.buffer._uuid=ms()),void 0===e.arrayBuffers[this.array.buffer._uuid]&&(e.arrayBuffers[this.array.buffer._uuid]=Array.from(new Uint32Array(this.array.buffer))),{uuid:this.uuid,buffer:this.array.buffer._uuid,type:this.array.constructor.name,stride:this.stride}}}const Ml=new Es;class El{constructor(e,t,n,i=!1){this.isInterleavedBufferAttribute=!0,this.name="",this.data=e,this.itemSize=t,this.offset=n,this.normalized=i}get count(){return this.data.count}get array(){return this.data.array}set needsUpdate(e){this.data.needsUpdate=e}applyMatrix4(e){for(let t=0,n=this.data.count;t<n;t++)Ml.fromBufferAttribute(this,t),Ml.applyMatrix4(e),this.setXYZ(t,Ml.x,Ml.y,Ml.z);return this}applyNormalMatrix(e){for(let t=0,n=this.count;t<n;t++)Ml.fromBufferAttribute(this,t),Ml.applyNormalMatrix(e),this.setXYZ(t,Ml.x,Ml.y,Ml.z);return this}transformDirection(e){for(let t=0,n=this.count;t<n;t++)Ml.fromBufferAttribute(this,t),Ml.transformDirection(e),this.setXYZ(t,Ml.x,Ml.y,Ml.z);return this}getComponent(e,t){let n=this.array[e*this.data.stride+this.offset+t];return this.normalized&&(n=ys(n,this.array)),n}setComponent(e,t,n){return this.normalized&&(n=bs(n,this.array)),this.data.array[e*this.data.stride+this.offset+t]=n,this}setX(e,t){return this.normalized&&(t=bs(t,this.array)),this.data.array[e*this.data.stride+this.offset]=t,this}setY(e,t){return this.normalized&&(t=bs(t,this.array)),this.data.array[e*this.data.stride+this.offset+1]=t,this}setZ(e,t){return this.normalized&&(t=bs(t,this.array)),this.data.array[e*this.data.stride+this.offset+2]=t,this}setW(e,t){return this.normalized&&(t=bs(t,this.array)),this.data.array[e*this.data.stride+this.offset+3]=t,this}getX(e){let t=this.data.array[e*this.data.stride+this.offset];return this.normalized&&(t=ys(t,this.array)),t}getY(e){let t=this.data.array[e*this.data.stride+this.offset+1];return this.normalized&&(t=ys(t,this.array)),t}getZ(e){let t=this.data.array[e*this.data.stride+this.offset+2];return this.normalized&&(t=ys(t,this.array)),t}getW(e){let t=this.data.array[e*this.data.stride+this.offset+3];return this.normalized&&(t=ys(t,this.array)),t}setXY(e,t,n){return e=e*this.data.stride+this.offset,this.normalized&&(t=bs(t,this.array),n=bs(n,this.array)),this.data.array[e+0]=t,this.data.array[e+1]=n,this}setXYZ(e,t,n,i){return e=e*this.data.stride+this.offset,this.normalized&&(t=bs(t,this.array),n=bs(n,this.array),i=bs(i,this.array)),this.data.array[e+0]=t,this.data.array[e+1]=n,this.data.array[e+2]=i,this}setXYZW(e,t,n,i,r){return e=e*this.data.stride+this.offset,this.normalized&&(t=bs(t,this.array),n=bs(n,this.array),i=bs(i,this.array),r=bs(r,this.array)),this.data.array[e+0]=t,this.data.array[e+1]=n,this.data.array[e+2]=i,this.data.array[e+3]=r,this}clone(e){if(void 0===e){console.log("THREE.InterleavedBufferAttribute.clone(): Cloning an interleaved buffer attribute will de-interleave buffer data.");const e=[];for(let t=0;t<this.count;t++){const n=t*this.data.stride+this.offset;for(let t=0;t<this.itemSize;t++)e.push(this.data.array[n+t])}return new Ia(new this.array.constructor(e),this.itemSize,this.normalized)}return void 0===e.interleavedBuffers&&(e.interleavedBuffers={}),void 0===e.interleavedBuffers[this.data.uuid]&&(e.interleavedBuffers[this.data.uuid]=this.data.clone(e)),new El(e.interleavedBuffers[this.data.uuid],this.itemSize,this.offset,this.normalized)}toJSON(e){if(void 0===e){console.log("THREE.InterleavedBufferAttribute.toJSON(): Serializing an interleaved buffer attribute will de-interleave buffer data.");const e=[];for(let t=0;t<this.count;t++){const n=t*this.data.stride+this.offset;for(let t=0;t<this.itemSize;t++)e.push(this.data.array[n+t])}return{itemSize:this.itemSize,type:this.array.constructor.name,array:e,normalized:this.normalized}}return void 0===e.interleavedBuffers&&(e.interleavedBuffers={}),void 0===e.interleavedBuffers[this.data.uuid]&&(e.interleavedBuffers[this.data.uuid]=this.data.toJSON(e)),{isInterleavedBufferAttribute:!0,itemSize:this.itemSize,data:this.data.uuid,offset:this.offset,normalized:this.normalized}}}class Tl extends Ca{constructor(e){super(),this.isSpriteMaterial=!0,this.type="SpriteMaterial",this.color=new ya(16777215),this.map=null,this.alphaMap=null,this.rotation=0,this.sizeAttenuation=!0,this.transparent=!0,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.map=e.map,this.alphaMap=e.alphaMap,this.rotation=e.rotation,this.sizeAttenuation=e.sizeAttenuation,this.fog=e.fog,this}}class Sl extends Ys{constructor(e=null,t=1,n=1,i,r,s,o,a,l=1003,u=1003,c,d){super(null,s,o,a,l,u,i,r,c,d),this.isDataTexture=!0,this.image={data:e,width:t,height:n},this.generateMipmaps=!1,this.flipY=!1,this.unpackAlignment=1}}class Pl extends Ia{constructor(e,t,n,i=1){super(e,t,n),this.isInstancedBufferAttribute=!0,this.meshPerAttribute=i}copy(e){return super.copy(e),this.meshPerAttribute=e.meshPerAttribute,this}toJSON(){const e=super.toJSON();return e.meshPerAttribute=this.meshPerAttribute,e.isInstancedBufferAttribute=!0,e}}const Nl=new Es,Bl=new Es,Dl=new Ps;class Il{constructor(e=new Es(1,0,0),t=0){this.isPlane=!0,this.normal=e,this.constant=t}set(e,t){return this.normal.copy(e),this.constant=t,this}setComponents(e,t,n,i){return this.normal.set(e,t,n),this.constant=i,this}setFromNormalAndCoplanarPoint(e,t){return this.normal.copy(e),this.constant=-t.dot(this.normal),this}setFromCoplanarPoints(e,t,n){const i=Nl.subVectors(n,t).cross(Bl.subVectors(e,t)).normalize();return this.setFromNormalAndCoplanarPoint(i,e),this}copy(e){return this.normal.copy(e.normal),this.constant=e.constant,this}normalize(){const e=1/this.normal.length();return this.normal.multiplyScalar(e),this.constant*=e,this}negate(){return this.constant*=-1,this.normal.negate(),this}distanceToPoint(e){return this.normal.dot(e)+this.constant}distanceToSphere(e){return this.distanceToPoint(e.center)-e.radius}projectPoint(e,t){return t.copy(e).addScaledVector(this.normal,-this.distanceToPoint(e))}intersectLine(e,t){const n=e.delta(Nl),i=this.normal.dot(n);if(0===i)return 0===this.distanceToPoint(e.start)?t.copy(e.start):null;const r=-(e.start.dot(this.normal)+this.constant)/i;return r<0||r>1?null:t.copy(e.start).addScaledVector(n,r)}intersectsLine(e){const t=this.distanceToPoint(e.start),n=this.distanceToPoint(e.end);return t<0&&n>0||n<0&&t>0}intersectsBox(e){return e.intersectsPlane(this)}intersectsSphere(e){return e.intersectsPlane(this)}coplanarPoint(e){return e.copy(this.normal).multiplyScalar(-this.constant)}applyMatrix4(e,t){const n=t||Dl.getNormalMatrix(e),i=this.coplanarPoint(Nl).applyMatrix4(e),r=this.normal.applyMatrix3(n).normalize();return this.constant=-i.dot(r),this}translate(e){return this.constant-=e.dot(this.normal),this}equals(e){return e.normal.equals(this.normal)&&e.constant===this.constant}clone(){return(new this.constructor).copy(this)}}const Ll=new xo,jl=new Cs(.5,.5),Ol=new Es;class zl{constructor(e=new Il,t=new Il,n=new Il,i=new Il,r=new Il,s=new Il){this.planes=[e,t,n,i,r,s]}set(e,t,n,i,r,s){const o=this.planes;return o[0].copy(e),o[1].copy(t),o[2].copy(n),o[3].copy(i),o[4].copy(r),o[5].copy(s),this}copy(e){const t=this.planes;for(let n=0;n<6;n++)t[n].copy(e.planes[n]);return this}setFromProjectionMatrix(e,t=2e3,n=!1){const i=this.planes,r=e.elements,s=r[0],o=r[1],a=r[2],l=r[3],u=r[4],c=r[5],d=r[6],h=r[7],f=r[8],p=r[9],g=r[10],m=r[11],v=r[12],A=r[13],x=r[14],y=r[15];if(i[0].setComponents(l-s,h-u,m-f,y-v).normalize(),i[1].setComponents(l+s,h+u,m+f,y+v).normalize(),i[2].setComponents(l+o,h+c,m+p,y+A).normalize(),i[3].setComponents(l-o,h-c,m-p,y-A).normalize(),n)i[4].setComponents(a,d,g,x).normalize(),i[5].setComponents(l-a,h-d,m-g,y-x).normalize();else if(i[4].setComponents(l-a,h-d,m-g,y-x).normalize(),t===as)i[5].setComponents(l+a,h+d,m+g,y+x).normalize();else{if(t!==ls)throw new Error("THREE.Frustum.setFromProjectionMatrix(): Invalid coordinate system: "+t);i[5].setComponents(a,d,g,x).normalize()}return this}intersectsObject(e){if(void 0!==e.boundingSphere)null===e.boundingSphere&&e.computeBoundingSphere(),Ll.copy(e.boundingSphere).applyMatrix4(e.matrixWorld);else{const t=e.geometry;null===t.boundingSphere&&t.computeBoundingSphere(),Ll.copy(t.boundingSphere).applyMatrix4(e.matrixWorld)}return this.intersectsSphere(Ll)}intersectsSprite(e){Ll.center.set(0,0,0);const t=jl.distanceTo(e.center);return Ll.radius=.7071067811865476+t,Ll.applyMatrix4(e.matrixWorld),this.intersectsSphere(Ll)}intersectsSphere(e){const t=this.planes,n=e.center,i=-e.radius;for(let e=0;e<6;e++){if(t[e].distanceToPoint(n)<i)return!1}return!0}intersectsBox(e){const t=this.planes;for(let n=0;n<6;n++){const i=t[n];if(Ol.x=i.normal.x>0?e.max.x:e.min.x,Ol.y=i.normal.y>0?e.max.y:e.min.y,Ol.z=i.normal.z>0?e.max.z:e.min.z,i.distanceToPoint(Ol)<0)return!1}return!0}containsPoint(e){const t=this.planes;for(let n=0;n<6;n++)if(t[n].distanceToPoint(e)<0)return!1;return!0}clone(){return(new this.constructor).copy(this)}}const Rl=new Po,kl=new zl;class Fl{constructor(){this.coordinateSystem=as}intersectsObject(e,t){if(!t.isArrayCamera||0===t.cameras.length)return!1;for(let n=0;n<t.cameras.length;n++){const i=t.cameras[n];if(Rl.multiplyMatrices(i.projectionMatrix,i.matrixWorldInverse),kl.setFromProjectionMatrix(Rl,i.coordinateSystem,i.reversedDepth),kl.intersectsObject(e))return!0}return!1}intersectsSprite(e,t){if(!t||!t.cameras||0===t.cameras.length)return!1;for(let n=0;n<t.cameras.length;n++){const i=t.cameras[n];if(Rl.multiplyMatrices(i.projectionMatrix,i.matrixWorldInverse),kl.setFromProjectionMatrix(Rl,i.coordinateSystem,i.reversedDepth),kl.intersectsSprite(e))return!0}return!1}intersectsSphere(e,t){if(!t||!t.cameras||0===t.cameras.length)return!1;for(let n=0;n<t.cameras.length;n++){const i=t.cameras[n];if(Rl.multiplyMatrices(i.projectionMatrix,i.matrixWorldInverse),kl.setFromProjectionMatrix(Rl,i.coordinateSystem,i.reversedDepth),kl.intersectsSphere(e))return!0}return!1}intersectsBox(e,t){if(!t||!t.cameras||0===t.cameras.length)return!1;for(let n=0;n<t.cameras.length;n++){const i=t.cameras[n];if(Rl.multiplyMatrices(i.projectionMatrix,i.matrixWorldInverse),kl.setFromProjectionMatrix(Rl,i.coordinateSystem,i.reversedDepth),kl.intersectsBox(e))return!0}return!1}containsPoint(e,t){if(!t||!t.cameras||0===t.cameras.length)return!1;for(let n=0;n<t.cameras.length;n++){const i=t.cameras[n];if(Rl.multiplyMatrices(i.projectionMatrix,i.matrixWorldInverse),kl.setFromProjectionMatrix(Rl,i.coordinateSystem,i.reversedDepth),kl.containsPoint(e))return!0}return!1}clone(){return new Fl}}class Hl extends Ca{constructor(e){super(),this.isLineBasicMaterial=!0,this.type="LineBasicMaterial",this.color=new ya(16777215),this.map=null,this.linewidth=1,this.linecap="round",this.linejoin="round",this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.map=e.map,this.linewidth=e.linewidth,this.linecap=e.linecap,this.linejoin=e.linejoin,this.fog=e.fog,this}}const Ul=new Es,Xl=new Es,Gl=new Po,Vl=new So,Wl=new xo,Ql=new Es,Zl=new Es;class Yl extends ta{constructor(e=new Va,t=new Hl){super(),this.isLine=!0,this.type="Line",this.geometry=e,this.material=t,this.morphTargetDictionary=void 0,this.morphTargetInfluences=void 0,this.updateMorphTargets()}copy(e,t){return super.copy(e,t),this.material=Array.isArray(e.material)?e.material.slice():e.material,this.geometry=e.geometry,this}computeLineDistances(){const e=this.geometry;if(null===e.index){const t=e.attributes.position,n=[0];for(let e=1,i=t.count;e<i;e++)Ul.fromBufferAttribute(t,e-1),Xl.fromBufferAttribute(t,e),n[e]=n[e-1],n[e]+=Ul.distanceTo(Xl);e.setAttribute("lineDistance",new za(n,1))}else console.warn("THREE.Line.computeLineDistances(): Computation only possible with non-indexed BufferGeometry.");return this}raycast(e,t){const n=this.geometry,i=this.matrixWorld,r=e.params.Line.threshold,s=n.drawRange;if(null===n.boundingSphere&&n.computeBoundingSphere(),Wl.copy(n.boundingSphere),Wl.applyMatrix4(i),Wl.radius+=r,!1===e.ray.intersectsSphere(Wl))return;Gl.copy(i).invert(),Vl.copy(e.ray).applyMatrix4(Gl);const o=r/((this.scale.x+this.scale.y+this.scale.z)/3),a=o*o,l=this.isLineSegments?2:1,u=n.index,c=n.attributes.position;if(null!==u){const n=Math.max(0,s.start),i=Math.min(u.count,s.start+s.count);for(let r=n,s=i-1;r<s;r+=l){const n=u.getX(r),i=u.getX(r+1),s=Jl(this,e,Vl,a,n,i,r);s&&t.push(s)}if(this.isLineLoop){const r=u.getX(i-1),s=u.getX(n),o=Jl(this,e,Vl,a,r,s,i-1);o&&t.push(o)}}else{const n=Math.max(0,s.start),i=Math.min(c.count,s.start+s.count);for(let r=n,s=i-1;r<s;r+=l){const n=Jl(this,e,Vl,a,r,r+1,r);n&&t.push(n)}if(this.isLineLoop){const r=Jl(this,e,Vl,a,i-1,n,i-1);r&&t.push(r)}}}updateMorphTargets(){const e=this.geometry.morphAttributes,t=Object.keys(e);if(t.length>0){const n=e[t[0]];if(void 0!==n){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,t=n.length;e<t;e++){const t=n[e].name||String(e);this.morphTargetInfluences.push(0),this.morphTargetDictionary[t]=e}}}}}function Jl(e,t,n,i,r,s,o){const a=e.geometry.attributes.position;Ul.fromBufferAttribute(a,r),Xl.fromBufferAttribute(a,s);if(n.distanceSqToSegment(Ul,Xl,Ql,Zl)>i)return;Ql.applyMatrix4(e.matrixWorld);const l=t.ray.origin.distanceTo(Ql);return l<t.near||l>t.far?void 0:{distance:l,point:Zl.clone().applyMatrix4(e.matrixWorld),index:o,face:null,faceIndex:null,barycoord:null,object:e}}class Kl extends Ca{constructor(e){super(),this.isPointsMaterial=!0,this.type="PointsMaterial",this.color=new ya(16777215),this.map=null,this.alphaMap=null,this.size=1,this.sizeAttenuation=!0,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.map=e.map,this.alphaMap=e.alphaMap,this.size=e.size,this.sizeAttenuation=e.sizeAttenuation,this.fog=e.fog,this}}class ql extends Ys{constructor(e,t){super({width:e,height:t}),this.isFramebufferTexture=!0,this.magFilter=Ri,this.minFilter=Ri,this.generateMipmaps=!1,this.needsUpdate=!0}}class _l extends Ys{constructor(e,t,n=1014,i,r,s,o=1003,a=1003,l,u=1026,c=1){if(u!==sr&&u!==or)throw new Error("DepthTexture format must be either THREE.DepthFormat or THREE.DepthStencilFormat");super({width:e,height:t,depth:c},i,r,s,o,a,u,n,l),this.isDepthTexture=!0,this.flipY=!1,this.generateMipmaps=!1,this.compareFunction=null}copy(e){return super.copy(e),this.source=new Vs(Object.assign({},e.image)),this.compareFunction=e.compareFunction,this}toJSON(e){const t=super.toJSON(e);return null!==this.compareFunction&&(t.compareFunction=this.compareFunction),t}}class $l extends Ys{constructor(e=null){super(),this.sourceTexture=e,this.isExternalTexture=!0}copy(e){return super.copy(e),this.sourceTexture=e.sourceTexture,this}}class eu extends Va{constructor(e=1,t=1,n=1,i=32,r=1,s=!1,o=0,a=2*Math.PI){super(),this.type="CylinderGeometry",this.parameters={radiusTop:e,radiusBottom:t,height:n,radialSegments:i,heightSegments:r,openEnded:s,thetaStart:o,thetaLength:a};const l=this;i=Math.floor(i),r=Math.floor(r);const u=[],c=[],d=[],h=[];let f=0;const p=[],g=n/2;let m=0;function v(n){const r=f,s=new Cs,p=new Es;let v=0;const A=!0===n?e:t,x=!0===n?1:-1;for(let e=1;e<=i;e++)c.push(0,g*x,0),d.push(0,x,0),h.push(.5,.5),f++;const y=f;for(let e=0;e<=i;e++){const t=e/i*a+o,n=Math.cos(t),r=Math.sin(t);p.x=A*r,p.y=g*x,p.z=A*n,c.push(p.x,p.y,p.z),d.push(0,x,0),s.x=.5*n+.5,s.y=.5*r*x+.5,h.push(s.x,s.y),f++}for(let e=0;e<i;e++){const t=r+e,i=y+e;!0===n?u.push(i,i+1,t):u.push(i+1,i,t),v+=3}l.addGroup(m,v,!0===n?1:2),m+=v}!function(){const s=new Es,v=new Es;let A=0;const x=(t-e)/n;for(let l=0;l<=r;l++){const u=[],m=l/r,A=m*(t-e)+e;for(let e=0;e<=i;e++){const t=e/i,r=t*a+o,l=Math.sin(r),p=Math.cos(r);v.x=A*l,v.y=-m*n+g,v.z=A*p,c.push(v.x,v.y,v.z),s.set(l,x,p).normalize(),d.push(s.x,s.y,s.z),h.push(t,1-m),u.push(f++)}p.push(u)}for(let n=0;n<i;n++)for(let i=0;i<r;i++){const s=p[i][n],o=p[i+1][n],a=p[i+1][n+1],l=p[i][n+1];(e>0||0!==i)&&(u.push(s,o,l),A+=3),(t>0||i!==r-1)&&(u.push(o,a,l),A+=3)}l.addGroup(m,A,0),m+=A}(),!1===s&&(e>0&&v(!0),t>0&&v(!1)),this.setIndex(u),this.setAttribute("position",new za(c,3)),this.setAttribute("normal",new za(d,3)),this.setAttribute("uv",new za(h,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new eu(e.radiusTop,e.radiusBottom,e.height,e.radialSegments,e.heightSegments,e.openEnded,e.thetaStart,e.thetaLength)}}class tu extends eu{constructor(e=1,t=1,n=32,i=1,r=!1,s=0,o=2*Math.PI){super(0,e,t,n,i,r,s,o),this.type="ConeGeometry",this.parameters={radius:e,height:t,radialSegments:n,heightSegments:i,openEnded:r,thetaStart:s,thetaLength:o}}static fromJSON(e){return new tu(e.radius,e.height,e.radialSegments,e.heightSegments,e.openEnded,e.thetaStart,e.thetaLength)}}class nu{constructor(){this.type="Curve",this.arcLengthDivisions=200,this.needsUpdate=!1,this.cacheArcLengths=null}getPoint(){console.warn("THREE.Curve: .getPoint() not implemented.")}getPointAt(e,t){const n=this.getUtoTmapping(e);return this.getPoint(n,t)}getPoints(e=5){const t=[];for(let n=0;n<=e;n++)t.push(this.getPoint(n/e));return t}getSpacedPoints(e=5){const t=[];for(let n=0;n<=e;n++)t.push(this.getPointAt(n/e));return t}getLength(){const e=this.getLengths();return e[e.length-1]}getLengths(e=this.arcLengthDivisions){if(this.cacheArcLengths&&this.cacheArcLengths.length===e+1&&!this.needsUpdate)return this.cacheArcLengths;this.needsUpdate=!1;const t=[];let n,i=this.getPoint(0),r=0;t.push(0);for(let s=1;s<=e;s++)n=this.getPoint(s/e),r+=n.distanceTo(i),t.push(r),i=n;return this.cacheArcLengths=t,t}updateArcLengths(){this.needsUpdate=!0,this.getLengths()}getUtoTmapping(e,t=null){const n=this.getLengths();let i=0;const r=n.length;let s;s=t||e*n[r-1];let o,a=0,l=r-1;for(;a<=l;)if(i=Math.floor(a+(l-a)/2),o=n[i]-s,o<0)a=i+1;else{if(!(o>0)){l=i;break}l=i-1}if(i=l,n[i]===s)return i/(r-1);const u=n[i];return(i+(s-u)/(n[i+1]-u))/(r-1)}getTangent(e,t){const n=1e-4;let i=e-n,r=e+n;i<0&&(i=0),r>1&&(r=1);const s=this.getPoint(i),o=this.getPoint(r),a=t||(s.isVector2?new Cs:new Es);return a.copy(o).sub(s).normalize(),a}getTangentAt(e,t){const n=this.getUtoTmapping(e);return this.getTangent(n,t)}computeFrenetFrames(e,t=!1){const n=new Es,i=[],r=[],s=[],o=new Es,a=new Po;for(let t=0;t<=e;t++){const n=t/e;i[t]=this.getTangentAt(n,new Es)}r[0]=new Es,s[0]=new Es;let l=Number.MAX_VALUE;const u=Math.abs(i[0].x),c=Math.abs(i[0].y),d=Math.abs(i[0].z);u<=l&&(l=u,n.set(1,0,0)),c<=l&&(l=c,n.set(0,1,0)),d<=l&&n.set(0,0,1),o.crossVectors(i[0],n).normalize(),r[0].crossVectors(i[0],o),s[0].crossVectors(i[0],r[0]);for(let t=1;t<=e;t++){if(r[t]=r[t-1].clone(),s[t]=s[t-1].clone(),o.crossVectors(i[t-1],i[t]),o.length()>Number.EPSILON){o.normalize();const e=Math.acos(vs(i[t-1].dot(i[t]),-1,1));r[t].applyMatrix4(a.makeRotationAxis(o,e))}s[t].crossVectors(i[t],r[t])}if(!0===t){let t=Math.acos(vs(r[0].dot(r[e]),-1,1));t/=e,i[0].dot(o.crossVectors(r[0],r[e]))>0&&(t=-t);for(let n=1;n<=e;n++)r[n].applyMatrix4(a.makeRotationAxis(i[n],t*n)),s[n].crossVectors(i[n],r[n])}return{tangents:i,normals:r,binormals:s}}clone(){return(new this.constructor).copy(this)}copy(e){return this.arcLengthDivisions=e.arcLengthDivisions,this}toJSON(){const e={metadata:{version:4.7,type:"Curve",generator:"Curve.toJSON"}};return e.arcLengthDivisions=this.arcLengthDivisions,e.type=this.type,e}fromJSON(e){return this.arcLengthDivisions=e.arcLengthDivisions,this}}class iu extends nu{constructor(e=0,t=0,n=1,i=1,r=0,s=2*Math.PI,o=!1,a=0){super(),this.isEllipseCurve=!0,this.type="EllipseCurve",this.aX=e,this.aY=t,this.xRadius=n,this.yRadius=i,this.aStartAngle=r,this.aEndAngle=s,this.aClockwise=o,this.aRotation=a}getPoint(e,t=new Cs){const n=t,i=2*Math.PI;let r=this.aEndAngle-this.aStartAngle;const s=Math.abs(r)<Number.EPSILON;for(;r<0;)r+=i;for(;r>i;)r-=i;r<Number.EPSILON&&(r=s?0:i),!0!==this.aClockwise||s||(r===i?r=-i:r-=i);const o=this.aStartAngle+e*r;let a=this.aX+this.xRadius*Math.cos(o),l=this.aY+this.yRadius*Math.sin(o);if(0!==this.aRotation){const e=Math.cos(this.aRotation),t=Math.sin(this.aRotation),n=a-this.aX,i=l-this.aY;a=n*e-i*t+this.aX,l=n*t+i*e+this.aY}return n.set(a,l)}copy(e){return super.copy(e),this.aX=e.aX,this.aY=e.aY,this.xRadius=e.xRadius,this.yRadius=e.yRadius,this.aStartAngle=e.aStartAngle,this.aEndAngle=e.aEndAngle,this.aClockwise=e.aClockwise,this.aRotation=e.aRotation,this}toJSON(){const e=super.toJSON();return e.aX=this.aX,e.aY=this.aY,e.xRadius=this.xRadius,e.yRadius=this.yRadius,e.aStartAngle=this.aStartAngle,e.aEndAngle=this.aEndAngle,e.aClockwise=this.aClockwise,e.aRotation=this.aRotation,e}fromJSON(e){return super.fromJSON(e),this.aX=e.aX,this.aY=e.aY,this.xRadius=e.xRadius,this.yRadius=e.yRadius,this.aStartAngle=e.aStartAngle,this.aEndAngle=e.aEndAngle,this.aClockwise=e.aClockwise,this.aRotation=e.aRotation,this}}function ru(){let e=0,t=0,n=0,i=0;function r(r,s,o,a){e=r,t=o,n=-3*r+3*s-2*o-a,i=2*r-2*s+o+a}return{initCatmullRom:function(e,t,n,i,s){r(t,n,s*(n-e),s*(i-t))},initNonuniformCatmullRom:function(e,t,n,i,s,o,a){let l=(t-e)/s-(n-e)/(s+o)+(n-t)/o,u=(n-t)/o-(i-t)/(o+a)+(i-n)/a;l*=o,u*=o,r(t,n,l,u)},calc:function(r){const s=r*r;return e+t*r+n*s+i*(s*r)}}}const su=new Es,ou=new ru,au=new ru,lu=new ru;function uu(e,t,n,i,r){const s=.5*(i-t),o=.5*(r-n),a=e*e;return(2*n-2*i+s+o)*(e*a)+(-3*n+3*i-2*s-o)*a+s*e+n}function cu(e,t,n,i){return function(e,t){const n=1-e;return n*n*t}(e,t)+function(e,t){return 2*(1-e)*e*t}(e,n)+function(e,t){return e*e*t}(e,i)}function du(e,t,n,i,r){return function(e,t){const n=1-e;return n*n*n*t}(e,t)+function(e,t){const n=1-e;return 3*n*n*e*t}(e,n)+function(e,t){return 3*(1-e)*e*e*t}(e,i)+function(e,t){return e*e*e*t}(e,r)}class hu extends nu{constructor(e=new Cs,t=new Cs,n=new Cs,i=new Cs){super(),this.isCubicBezierCurve=!0,this.type="CubicBezierCurve",this.v0=e,this.v1=t,this.v2=n,this.v3=i}getPoint(e,t=new Cs){const n=t,i=this.v0,r=this.v1,s=this.v2,o=this.v3;return n.set(du(e,i.x,r.x,s.x,o.x),du(e,i.y,r.y,s.y,o.y)),n}copy(e){return super.copy(e),this.v0.copy(e.v0),this.v1.copy(e.v1),this.v2.copy(e.v2),this.v3.copy(e.v3),this}toJSON(){const e=super.toJSON();return e.v0=this.v0.toArray(),e.v1=this.v1.toArray(),e.v2=this.v2.toArray(),e.v3=this.v3.toArray(),e}fromJSON(e){return super.fromJSON(e),this.v0.fromArray(e.v0),this.v1.fromArray(e.v1),this.v2.fromArray(e.v2),this.v3.fromArray(e.v3),this}}class fu extends nu{constructor(e=new Es,t=new Es,n=new Es,i=new Es){super(),this.isCubicBezierCurve3=!0,this.type="CubicBezierCurve3",this.v0=e,this.v1=t,this.v2=n,this.v3=i}getPoint(e,t=new Es){const n=t,i=this.v0,r=this.v1,s=this.v2,o=this.v3;return n.set(du(e,i.x,r.x,s.x,o.x),du(e,i.y,r.y,s.y,o.y),du(e,i.z,r.z,s.z,o.z)),n}copy(e){return super.copy(e),this.v0.copy(e.v0),this.v1.copy(e.v1),this.v2.copy(e.v2),this.v3.copy(e.v3),this}toJSON(){const e=super.toJSON();return e.v0=this.v0.toArray(),e.v1=this.v1.toArray(),e.v2=this.v2.toArray(),e.v3=this.v3.toArray(),e}fromJSON(e){return super.fromJSON(e),this.v0.fromArray(e.v0),this.v1.fromArray(e.v1),this.v2.fromArray(e.v2),this.v3.fromArray(e.v3),this}}class pu extends nu{constructor(e=new Cs,t=new Cs){super(),this.isLineCurve=!0,this.type="LineCurve",this.v1=e,this.v2=t}getPoint(e,t=new Cs){const n=t;return 1===e?n.copy(this.v2):(n.copy(this.v2).sub(this.v1),n.multiplyScalar(e).add(this.v1)),n}getPointAt(e,t){return this.getPoint(e,t)}getTangent(e,t=new Cs){return t.subVectors(this.v2,this.v1).normalize()}getTangentAt(e,t){return this.getTangent(e,t)}copy(e){return super.copy(e),this.v1.copy(e.v1),this.v2.copy(e.v2),this}toJSON(){const e=super.toJSON();return e.v1=this.v1.toArray(),e.v2=this.v2.toArray(),e}fromJSON(e){return super.fromJSON(e),this.v1.fromArray(e.v1),this.v2.fromArray(e.v2),this}}class gu extends nu{constructor(e=new Cs,t=new Cs,n=new Cs){super(),this.isQuadraticBezierCurve=!0,this.type="QuadraticBezierCurve",this.v0=e,this.v1=t,this.v2=n}getPoint(e,t=new Cs){const n=t,i=this.v0,r=this.v1,s=this.v2;return n.set(cu(e,i.x,r.x,s.x),cu(e,i.y,r.y,s.y)),n}copy(e){return super.copy(e),this.v0.copy(e.v0),this.v1.copy(e.v1),this.v2.copy(e.v2),this}toJSON(){const e=super.toJSON();return e.v0=this.v0.toArray(),e.v1=this.v1.toArray(),e.v2=this.v2.toArray(),e}fromJSON(e){return super.fromJSON(e),this.v0.fromArray(e.v0),this.v1.fromArray(e.v1),this.v2.fromArray(e.v2),this}}class mu extends nu{constructor(e=new Es,t=new Es,n=new Es){super(),this.isQuadraticBezierCurve3=!0,this.type="QuadraticBezierCurve3",this.v0=e,this.v1=t,this.v2=n}getPoint(e,t=new Es){const n=t,i=this.v0,r=this.v1,s=this.v2;return n.set(cu(e,i.x,r.x,s.x),cu(e,i.y,r.y,s.y),cu(e,i.z,r.z,s.z)),n}copy(e){return super.copy(e),this.v0.copy(e.v0),this.v1.copy(e.v1),this.v2.copy(e.v2),this}toJSON(){const e=super.toJSON();return e.v0=this.v0.toArray(),e.v1=this.v1.toArray(),e.v2=this.v2.toArray(),e}fromJSON(e){return super.fromJSON(e),this.v0.fromArray(e.v0),this.v1.fromArray(e.v1),this.v2.fromArray(e.v2),this}}class vu extends nu{constructor(e=[]){super(),this.isSplineCurve=!0,this.type="SplineCurve",this.points=e}getPoint(e,t=new Cs){const n=t,i=this.points,r=(i.length-1)*e,s=Math.floor(r),o=r-s,a=i[0===s?s:s-1],l=i[s],u=i[s>i.length-2?i.length-1:s+1],c=i[s>i.length-3?i.length-1:s+2];return n.set(uu(o,a.x,l.x,u.x,c.x),uu(o,a.y,l.y,u.y,c.y)),n}copy(e){super.copy(e),this.points=[];for(let t=0,n=e.points.length;t<n;t++){const n=e.points[t];this.points.push(n.clone())}return this}toJSON(){const e=super.toJSON();e.points=[];for(let t=0,n=this.points.length;t<n;t++){const n=this.points[t];e.points.push(n.toArray())}return e}fromJSON(e){super.fromJSON(e),this.points=[];for(let t=0,n=e.points.length;t<n;t++){const n=e.points[t];this.points.push((new Cs).fromArray(n))}return this}}var Au=Object.freeze({__proto__:null,ArcCurve:class extends iu{constructor(e,t,n,i,r,s){super(e,t,n,n,i,r,s),this.isArcCurve=!0,this.type="ArcCurve"}},CatmullRomCurve3:class extends nu{constructor(e=[],t=!1,n="centripetal",i=.5){super(),this.isCatmullRomCurve3=!0,this.type="CatmullRomCurve3",this.points=e,this.closed=t,this.curveType=n,this.tension=i}getPoint(e,t=new Es){const n=t,i=this.points,r=i.length,s=(r-(this.closed?0:1))*e;let o,a,l=Math.floor(s),u=s-l;this.closed?l+=l>0?0:(Math.floor(Math.abs(l)/r)+1)*r:0===u&&l===r-1&&(l=r-2,u=1),this.closed||l>0?o=i[(l-1)%r]:(su.subVectors(i[0],i[1]).add(i[0]),o=su);const c=i[l%r],d=i[(l+1)%r];if(this.closed||l+2<r?a=i[(l+2)%r]:(su.subVectors(i[r-1],i[r-2]).add(i[r-1]),a=su),"centripetal"===this.curveType||"chordal"===this.curveType){const e="chordal"===this.curveType?.5:.25;let t=Math.pow(o.distanceToSquared(c),e),n=Math.pow(c.distanceToSquared(d),e),i=Math.pow(d.distanceToSquared(a),e);n<1e-4&&(n=1),t<1e-4&&(t=n),i<1e-4&&(i=n),ou.initNonuniformCatmullRom(o.x,c.x,d.x,a.x,t,n,i),au.initNonuniformCatmullRom(o.y,c.y,d.y,a.y,t,n,i),lu.initNonuniformCatmullRom(o.z,c.z,d.z,a.z,t,n,i)}else"catmullrom"===this.curveType&&(ou.initCatmullRom(o.x,c.x,d.x,a.x,this.tension),au.initCatmullRom(o.y,c.y,d.y,a.y,this.tension),lu.initCatmullRom(o.z,c.z,d.z,a.z,this.tension));return n.set(ou.calc(u),au.calc(u),lu.calc(u)),n}copy(e){super.copy(e),this.points=[];for(let t=0,n=e.points.length;t<n;t++){const n=e.points[t];this.points.push(n.clone())}return this.closed=e.closed,this.curveType=e.curveType,this.tension=e.tension,this}toJSON(){const e=super.toJSON();e.points=[];for(let t=0,n=this.points.length;t<n;t++){const n=this.points[t];e.points.push(n.toArray())}return e.closed=this.closed,e.curveType=this.curveType,e.tension=this.tension,e}fromJSON(e){super.fromJSON(e),this.points=[];for(let t=0,n=e.points.length;t<n;t++){const n=e.points[t];this.points.push((new Es).fromArray(n))}return this.closed=e.closed,this.curveType=e.curveType,this.tension=e.tension,this}},CubicBezierCurve:hu,CubicBezierCurve3:fu,EllipseCurve:iu,LineCurve:pu,LineCurve3:class extends nu{constructor(e=new Es,t=new Es){super(),this.isLineCurve3=!0,this.type="LineCurve3",this.v1=e,this.v2=t}getPoint(e,t=new Es){const n=t;return 1===e?n.copy(this.v2):(n.copy(this.v2).sub(this.v1),n.multiplyScalar(e).add(this.v1)),n}getPointAt(e,t){return this.getPoint(e,t)}getTangent(e,t=new Es){return t.subVectors(this.v2,this.v1).normalize()}getTangentAt(e,t){return this.getTangent(e,t)}copy(e){return super.copy(e),this.v1.copy(e.v1),this.v2.copy(e.v2),this}toJSON(){const e=super.toJSON();return e.v1=this.v1.toArray(),e.v2=this.v2.toArray(),e}fromJSON(e){return super.fromJSON(e),this.v1.fromArray(e.v1),this.v2.fromArray(e.v2),this}},QuadraticBezierCurve:gu,QuadraticBezierCurve3:mu,SplineCurve:vu});class xu extends Va{constructor(e=1,t=1,n=1,i=1){super(),this.type="PlaneGeometry",this.parameters={width:e,height:t,widthSegments:n,heightSegments:i};const r=e/2,s=t/2,o=Math.floor(n),a=Math.floor(i),l=o+1,u=a+1,c=e/o,d=t/a,h=[],f=[],p=[],g=[];for(let e=0;e<u;e++){const t=e*d-s;for(let n=0;n<l;n++){const i=n*c-r;f.push(i,-t,0),p.push(0,0,1),g.push(n/o),g.push(1-e/a)}}for(let e=0;e<a;e++)for(let t=0;t<o;t++){const n=t+l*e,i=t+l*(e+1),r=t+1+l*(e+1),s=t+1+l*e;h.push(n,i,s),h.push(i,r,s)}this.setIndex(h),this.setAttribute("position",new za(f,3)),this.setAttribute("normal",new za(p,3)),this.setAttribute("uv",new za(g,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new xu(e.width,e.height,e.widthSegments,e.heightSegments)}}class yu extends Va{constructor(e=1,t=32,n=16,i=0,r=2*Math.PI,s=0,o=Math.PI){super(),this.type="SphereGeometry",this.parameters={radius:e,widthSegments:t,heightSegments:n,phiStart:i,phiLength:r,thetaStart:s,thetaLength:o},t=Math.max(3,Math.floor(t)),n=Math.max(2,Math.floor(n));const a=Math.min(s+o,Math.PI);let l=0;const u=[],c=new Es,d=new Es,h=[],f=[],p=[],g=[];for(let h=0;h<=n;h++){const m=[],v=h/n;let A=0;0===h&&0===s?A=.5/t:h===n&&a===Math.PI&&(A=-.5/t);for(let n=0;n<=t;n++){const a=n/t;c.x=-e*Math.cos(i+a*r)*Math.sin(s+v*o),c.y=e*Math.cos(s+v*o),c.z=e*Math.sin(i+a*r)*Math.sin(s+v*o),f.push(c.x,c.y,c.z),d.copy(c).normalize(),p.push(d.x,d.y,d.z),g.push(a+A,1-v),m.push(l++)}u.push(m)}for(let e=0;e<n;e++)for(let i=0;i<t;i++){const t=u[e][i+1],r=u[e][i],o=u[e+1][i],l=u[e+1][i+1];(0!==e||s>0)&&h.push(t,r,l),(e!==n-1||a<Math.PI)&&h.push(r,o,l)}this.setIndex(h),this.setAttribute("position",new za(f,3)),this.setAttribute("normal",new za(p,3)),this.setAttribute("uv",new za(g,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new yu(e.radius,e.widthSegments,e.heightSegments,e.phiStart,e.phiLength,e.thetaStart,e.thetaLength)}}class bu extends Va{constructor(e=new mu(new Es(-1,-1,0),new Es(-1,1,0),new Es(1,1,0)),t=64,n=1,i=8,r=!1){super(),this.type="TubeGeometry",this.parameters={path:e,tubularSegments:t,radius:n,radialSegments:i,closed:r};const s=e.computeFrenetFrames(t,r);this.tangents=s.tangents,this.normals=s.normals,this.binormals=s.binormals;const o=new Es,a=new Es,l=new Cs;let u=new Es;const c=[],d=[],h=[],f=[];function p(r){u=e.getPointAt(r/t,u);const l=s.normals[r],h=s.binormals[r];for(let e=0;e<=i;e++){const t=e/i*Math.PI*2,r=Math.sin(t),s=-Math.cos(t);a.x=s*l.x+r*h.x,a.y=s*l.y+r*h.y,a.z=s*l.z+r*h.z,a.normalize(),d.push(a.x,a.y,a.z),o.x=u.x+n*a.x,o.y=u.y+n*a.y,o.z=u.z+n*a.z,c.push(o.x,o.y,o.z)}}!function(){for(let e=0;e<t;e++)p(e);p(!1===r?t:0),function(){for(let e=0;e<=t;e++)for(let n=0;n<=i;n++)l.x=e/t,l.y=n/i,h.push(l.x,l.y)}(),function(){for(let e=1;e<=t;e++)for(let t=1;t<=i;t++){const n=(i+1)*(e-1)+(t-1),r=(i+1)*e+(t-1),s=(i+1)*e+t,o=(i+1)*(e-1)+t;f.push(n,r,o),f.push(r,s,o)}}()}(),this.setIndex(f),this.setAttribute("position",new za(c,3)),this.setAttribute("normal",new za(d,3)),this.setAttribute("uv",new za(h,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}toJSON(){const e=super.toJSON();return e.path=this.parameters.path.toJSON(),e}static fromJSON(e){return new bu((new Au[e.path.type]).fromJSON(e.path),e.tubularSegments,e.radius,e.radialSegments,e.closed)}}class wu extends Ca{constructor(e){super(),this.isShadowMaterial=!0,this.type="ShadowMaterial",this.color=new ya(0),this.transparent=!0,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.fog=e.fog,this}}class Cu extends Ca{constructor(e){super(),this.isMeshStandardMaterial=!0,this.type="MeshStandardMaterial",this.defines={STANDARD:""},this.color=new ya(16777215),this.roughness=1,this.metalness=0,this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new ya(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new Cs(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.roughnessMap=null,this.metalnessMap=null,this.alphaMap=null,this.envMap=null,this.envMapRotation=new ko,this.envMapIntensity=1,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap="round",this.wireframeLinejoin="round",this.flatShading=!1,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.defines={STANDARD:""},this.color.copy(e.color),this.roughness=e.roughness,this.metalness=e.metalness,this.map=e.map,this.lightMap=e.lightMap,this.lightMapIntensity=e.lightMapIntensity,this.aoMap=e.aoMap,this.aoMapIntensity=e.aoMapIntensity,this.emissive.copy(e.emissive),this.emissiveMap=e.emissiveMap,this.emissiveIntensity=e.emissiveIntensity,this.bumpMap=e.bumpMap,this.bumpScale=e.bumpScale,this.normalMap=e.normalMap,this.normalMapType=e.normalMapType,this.normalScale.copy(e.normalScale),this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this.roughnessMap=e.roughnessMap,this.metalnessMap=e.metalnessMap,this.alphaMap=e.alphaMap,this.envMap=e.envMap,this.envMapRotation.copy(e.envMapRotation),this.envMapIntensity=e.envMapIntensity,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.wireframeLinecap=e.wireframeLinecap,this.wireframeLinejoin=e.wireframeLinejoin,this.flatShading=e.flatShading,this.fog=e.fog,this}}class Mu extends Cu{constructor(e){super(),this.isMeshPhysicalMaterial=!0,this.defines={STANDARD:"",PHYSICAL:""},this.type="MeshPhysicalMaterial",this.anisotropyRotation=0,this.anisotropyMap=null,this.clearcoatMap=null,this.clearcoatRoughness=0,this.clearcoatRoughnessMap=null,this.clearcoatNormalScale=new Cs(1,1),this.clearcoatNormalMap=null,this.ior=1.5,Object.defineProperty(this,"reflectivity",{get:function(){return vs(2.5*(this.ior-1)/(this.ior+1),0,1)},set:function(e){this.ior=(1+.4*e)/(1-.4*e)}}),this.iridescenceMap=null,this.iridescenceIOR=1.3,this.iridescenceThicknessRange=[100,400],this.iridescenceThicknessMap=null,this.sheenColor=new ya(0),this.sheenColorMap=null,this.sheenRoughness=1,this.sheenRoughnessMap=null,this.transmissionMap=null,this.thickness=0,this.thicknessMap=null,this.attenuationDistance=1/0,this.attenuationColor=new ya(1,1,1),this.specularIntensity=1,this.specularIntensityMap=null,this.specularColor=new ya(1,1,1),this.specularColorMap=null,this._anisotropy=0,this._clearcoat=0,this._dispersion=0,this._iridescence=0,this._sheen=0,this._transmission=0,this.setValues(e)}get anisotropy(){return this._anisotropy}set anisotropy(e){this._anisotropy>0!=e>0&&this.version++,this._anisotropy=e}get clearcoat(){return this._clearcoat}set clearcoat(e){this._clearcoat>0!=e>0&&this.version++,this._clearcoat=e}get iridescence(){return this._iridescence}set iridescence(e){this._iridescence>0!=e>0&&this.version++,this._iridescence=e}get dispersion(){return this._dispersion}set dispersion(e){this._dispersion>0!=e>0&&this.version++,this._dispersion=e}get sheen(){return this._sheen}set sheen(e){this._sheen>0!=e>0&&this.version++,this._sheen=e}get transmission(){return this._transmission}set transmission(e){this._transmission>0!=e>0&&this.version++,this._transmission=e}copy(e){return super.copy(e),this.defines={STANDARD:"",PHYSICAL:""},this.anisotropy=e.anisotropy,this.anisotropyRotation=e.anisotropyRotation,this.anisotropyMap=e.anisotropyMap,this.clearcoat=e.clearcoat,this.clearcoatMap=e.clearcoatMap,this.clearcoatRoughness=e.clearcoatRoughness,this.clearcoatRoughnessMap=e.clearcoatRoughnessMap,this.clearcoatNormalMap=e.clearcoatNormalMap,this.clearcoatNormalScale.copy(e.clearcoatNormalScale),this.dispersion=e.dispersion,this.ior=e.ior,this.iridescence=e.iridescence,this.iridescenceMap=e.iridescenceMap,this.iridescenceIOR=e.iridescenceIOR,this.iridescenceThicknessRange=[...e.iridescenceThicknessRange],this.iridescenceThicknessMap=e.iridescenceThicknessMap,this.sheen=e.sheen,this.sheenColor.copy(e.sheenColor),this.sheenColorMap=e.sheenColorMap,this.sheenRoughness=e.sheenRoughness,this.sheenRoughnessMap=e.sheenRoughnessMap,this.transmission=e.transmission,this.transmissionMap=e.transmissionMap,this.thickness=e.thickness,this.thicknessMap=e.thicknessMap,this.attenuationDistance=e.attenuationDistance,this.attenuationColor.copy(e.attenuationColor),this.specularIntensity=e.specularIntensity,this.specularIntensityMap=e.specularIntensityMap,this.specularColor.copy(e.specularColor),this.specularColorMap=e.specularColorMap,this}}class Eu extends Ca{constructor(e){super(),this.isMeshPhongMaterial=!0,this.type="MeshPhongMaterial",this.color=new ya(16777215),this.specular=new ya(1118481),this.shininess=30,this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new ya(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new Cs(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.specularMap=null,this.alphaMap=null,this.envMap=null,this.envMapRotation=new ko,this.combine=0,this.reflectivity=1,this.refractionRatio=.98,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap="round",this.wireframeLinejoin="round",this.flatShading=!1,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.specular.copy(e.specular),this.shininess=e.shininess,this.map=e.map,this.lightMap=e.lightMap,this.lightMapIntensity=e.lightMapIntensity,this.aoMap=e.aoMap,this.aoMapIntensity=e.aoMapIntensity,this.emissive.copy(e.emissive),this.emissiveMap=e.emissiveMap,this.emissiveIntensity=e.emissiveIntensity,this.bumpMap=e.bumpMap,this.bumpScale=e.bumpScale,this.normalMap=e.normalMap,this.normalMapType=e.normalMapType,this.normalScale.copy(e.normalScale),this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this.specularMap=e.specularMap,this.alphaMap=e.alphaMap,this.envMap=e.envMap,this.envMapRotation.copy(e.envMapRotation),this.combine=e.combine,this.reflectivity=e.reflectivity,this.refractionRatio=e.refractionRatio,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.wireframeLinecap=e.wireframeLinecap,this.wireframeLinejoin=e.wireframeLinejoin,this.flatShading=e.flatShading,this.fog=e.fog,this}}class Tu extends Ca{constructor(e){super(),this.isMeshToonMaterial=!0,this.defines={TOON:""},this.type="MeshToonMaterial",this.color=new ya(16777215),this.map=null,this.gradientMap=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new ya(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new Cs(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.alphaMap=null,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap="round",this.wireframeLinejoin="round",this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.map=e.map,this.gradientMap=e.gradientMap,this.lightMap=e.lightMap,this.lightMapIntensity=e.lightMapIntensity,this.aoMap=e.aoMap,this.aoMapIntensity=e.aoMapIntensity,this.emissive.copy(e.emissive),this.emissiveMap=e.emissiveMap,this.emissiveIntensity=e.emissiveIntensity,this.bumpMap=e.bumpMap,this.bumpScale=e.bumpScale,this.normalMap=e.normalMap,this.normalMapType=e.normalMapType,this.normalScale.copy(e.normalScale),this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this.alphaMap=e.alphaMap,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.wireframeLinecap=e.wireframeLinecap,this.wireframeLinejoin=e.wireframeLinejoin,this.fog=e.fog,this}}class Su extends Ca{constructor(e){super(),this.isMeshNormalMaterial=!0,this.type="MeshNormalMaterial",this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new Cs(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.wireframe=!1,this.wireframeLinewidth=1,this.flatShading=!1,this.setValues(e)}copy(e){return super.copy(e),this.bumpMap=e.bumpMap,this.bumpScale=e.bumpScale,this.normalMap=e.normalMap,this.normalMapType=e.normalMapType,this.normalScale.copy(e.normalScale),this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.flatShading=e.flatShading,this}}class Pu extends Ca{constructor(e){super(),this.isMeshLambertMaterial=!0,this.type="MeshLambertMaterial",this.color=new ya(16777215),this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new ya(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new Cs(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.specularMap=null,this.alphaMap=null,this.envMap=null,this.envMapRotation=new ko,this.combine=0,this.reflectivity=1,this.refractionRatio=.98,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap="round",this.wireframeLinejoin="round",this.flatShading=!1,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.map=e.map,this.lightMap=e.lightMap,this.lightMapIntensity=e.lightMapIntensity,this.aoMap=e.aoMap,this.aoMapIntensity=e.aoMapIntensity,this.emissive.copy(e.emissive),this.emissiveMap=e.emissiveMap,this.emissiveIntensity=e.emissiveIntensity,this.bumpMap=e.bumpMap,this.bumpScale=e.bumpScale,this.normalMap=e.normalMap,this.normalMapType=e.normalMapType,this.normalScale.copy(e.normalScale),this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this.specularMap=e.specularMap,this.alphaMap=e.alphaMap,this.envMap=e.envMap,this.envMapRotation.copy(e.envMapRotation),this.combine=e.combine,this.reflectivity=e.reflectivity,this.refractionRatio=e.refractionRatio,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.wireframeLinecap=e.wireframeLinecap,this.wireframeLinejoin=e.wireframeLinejoin,this.flatShading=e.flatShading,this.fog=e.fog,this}}class Nu extends Ca{constructor(e){super(),this.isMeshDepthMaterial=!0,this.type="MeshDepthMaterial",this.depthPacking=3200,this.map=null,this.alphaMap=null,this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.wireframe=!1,this.wireframeLinewidth=1,this.setValues(e)}copy(e){return super.copy(e),this.depthPacking=e.depthPacking,this.map=e.map,this.alphaMap=e.alphaMap,this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this}}class Bu extends Ca{constructor(e){super(),this.isMeshDistanceMaterial=!0,this.type="MeshDistanceMaterial",this.map=null,this.alphaMap=null,this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.setValues(e)}copy(e){return super.copy(e),this.map=e.map,this.alphaMap=e.alphaMap,this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this}}class Du extends Ca{constructor(e){super(),this.isMeshMatcapMaterial=!0,this.defines={MATCAP:""},this.type="MeshMatcapMaterial",this.color=new ya(16777215),this.matcap=null,this.map=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new Cs(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.alphaMap=null,this.flatShading=!1,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.defines={MATCAP:""},this.color.copy(e.color),this.matcap=e.matcap,this.map=e.map,this.bumpMap=e.bumpMap,this.bumpScale=e.bumpScale,this.normalMap=e.normalMap,this.normalMapType=e.normalMapType,this.normalScale.copy(e.normalScale),this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this.alphaMap=e.alphaMap,this.flatShading=e.flatShading,this.fog=e.fog,this}}class Iu extends Hl{constructor(e){super(),this.isLineDashedMaterial=!0,this.type="LineDashedMaterial",this.scale=1,this.dashSize=3,this.gapSize=1,this.setValues(e)}copy(e){return super.copy(e),this.scale=e.scale,this.dashSize=e.dashSize,this.gapSize=e.gapSize,this}}function Lu(e,t){return e&&e.constructor!==t?"number"==typeof t.BYTES_PER_ELEMENT?new t(e):Array.prototype.slice.call(e):e}function ju(e){return ArrayBuffer.isView(e)&&!(e instanceof DataView)}class Ou{constructor(e,t,n,i){this.parameterPositions=e,this._cachedIndex=0,this.resultBuffer=void 0!==i?i:new t.constructor(n),this.sampleValues=t,this.valueSize=n,this.settings=null,this.DefaultSettings_={}}evaluate(e){const t=this.parameterPositions;let n=this._cachedIndex,i=t[n],r=t[n-1];e:{t:{let s;n:{i:if(!(e<i)){for(let s=n+2;;){if(void 0===i){if(e<r)break i;return n=t.length,this._cachedIndex=n,this.copySampleValue_(n-1)}if(n===s)break;if(r=i,i=t[++n],e<i)break t}s=t.length;break n}if(e>=r)break e;{const o=t[1];e<o&&(n=2,r=o);for(let s=n-2;;){if(void 0===r)return this._cachedIndex=0,this.copySampleValue_(0);if(n===s)break;if(i=r,r=t[--n-1],e>=r)break t}s=n,n=0}}for(;n<s;){const i=n+s>>>1;e<t[i]?s=i:n=i+1}if(i=t[n],r=t[n-1],void 0===r)return this._cachedIndex=0,this.copySampleValue_(0);if(void 0===i)return n=t.length,this._cachedIndex=n,this.copySampleValue_(n-1)}this._cachedIndex=n,this.intervalChanged_(n,r,i)}return this.interpolate_(n,r,e,i)}getSettings_(){return this.settings||this.DefaultSettings_}copySampleValue_(e){const t=this.resultBuffer,n=this.sampleValues,i=this.valueSize,r=e*i;for(let e=0;e!==i;++e)t[e]=n[r+e];return t}interpolate_(){throw new Error("call to abstract method")}intervalChanged_(){}}class zu extends Ou{constructor(e,t,n,i){super(e,t,n,i),this._weightPrev=-0,this._offsetPrev=-0,this._weightNext=-0,this._offsetNext=-0,this.DefaultSettings_={endingStart:Zr,endingEnd:Zr}}intervalChanged_(e,t,n){const i=this.parameterPositions;let r=e-2,s=e+1,o=i[r],a=i[s];if(void 0===o)switch(this.getSettings_().endingStart){case Yr:r=e,o=2*t-n;break;case Jr:r=i.length-2,o=t+i[r]-i[r+1];break;default:r=e,o=n}if(void 0===a)switch(this.getSettings_().endingEnd){case Yr:s=e,a=2*n-t;break;case Jr:s=1,a=n+i[1]-i[0];break;default:s=e-1,a=t}const l=.5*(n-t),u=this.valueSize;this._weightPrev=l/(t-o),this._weightNext=l/(a-n),this._offsetPrev=r*u,this._offsetNext=s*u}interpolate_(e,t,n,i){const r=this.resultBuffer,s=this.sampleValues,o=this.valueSize,a=e*o,l=a-o,u=this._offsetPrev,c=this._offsetNext,d=this._weightPrev,h=this._weightNext,f=(n-t)/(i-t),p=f*f,g=p*f,m=-d*g+2*d*p-d*f,v=(1+d)*g+(-1.5-2*d)*p+(-.5+d)*f+1,A=(-1-h)*g+(1.5+h)*p+.5*f,x=h*g-h*p;for(let e=0;e!==o;++e)r[e]=m*s[u+e]+v*s[l+e]+A*s[a+e]+x*s[c+e];return r}}class Ru extends Ou{constructor(e,t,n,i){super(e,t,n,i)}interpolate_(e,t,n,i){const r=this.resultBuffer,s=this.sampleValues,o=this.valueSize,a=e*o,l=a-o,u=(n-t)/(i-t),c=1-u;for(let e=0;e!==o;++e)r[e]=s[l+e]*c+s[a+e]*u;return r}}class ku extends Ou{constructor(e,t,n,i){super(e,t,n,i)}interpolate_(e){return this.copySampleValue_(e-1)}}class Fu{constructor(e,t,n,i){if(void 0===e)throw new Error("THREE.KeyframeTrack: track name is undefined");if(void 0===t||0===t.length)throw new Error("THREE.KeyframeTrack: no keyframes in track named "+e);this.name=e,this.times=Lu(t,this.TimeBufferType),this.values=Lu(n,this.ValueBufferType),this.setInterpolation(i||this.DefaultInterpolation)}static toJSON(e){const t=e.constructor;let n;if(t.toJSON!==this.toJSON)n=t.toJSON(e);else{n={name:e.name,times:Lu(e.times,Array),values:Lu(e.values,Array)};const t=e.getInterpolation();t!==e.DefaultInterpolation&&(n.interpolation=t)}return n.type=e.ValueTypeName,n}InterpolantFactoryMethodDiscrete(e){return new ku(this.times,this.values,this.getValueSize(),e)}InterpolantFactoryMethodLinear(e){return new Ru(this.times,this.values,this.getValueSize(),e)}InterpolantFactoryMethodSmooth(e){return new zu(this.times,this.values,this.getValueSize(),e)}setInterpolation(e){let t;switch(e){case Vr:t=this.InterpolantFactoryMethodDiscrete;break;case Wr:t=this.InterpolantFactoryMethodLinear;break;case Qr:t=this.InterpolantFactoryMethodSmooth}if(void 0===t){const t="unsupported interpolation for "+this.ValueTypeName+" keyframe track named "+this.name;if(void 0===this.createInterpolant){if(e===this.DefaultInterpolation)throw new Error(t);this.setInterpolation(this.DefaultInterpolation)}return console.warn("THREE.KeyframeTrack:",t),this}return this.createInterpolant=t,this}getInterpolation(){switch(this.createInterpolant){case this.InterpolantFactoryMethodDiscrete:return Vr;case this.InterpolantFactoryMethodLinear:return Wr;case this.InterpolantFactoryMethodSmooth:return Qr}}getValueSize(){return this.values.length/this.times.length}shift(e){if(0!==e){const t=this.times;for(let n=0,i=t.length;n!==i;++n)t[n]+=e}return this}scale(e){if(1!==e){const t=this.times;for(let n=0,i=t.length;n!==i;++n)t[n]*=e}return this}trim(e,t){const n=this.times,i=n.length;let r=0,s=i-1;for(;r!==i&&n[r]<e;)++r;for(;-1!==s&&n[s]>t;)--s;if(++s,0!==r||s!==i){r>=s&&(s=Math.max(s,1),r=s-1);const e=this.getValueSize();this.times=n.slice(r,s),this.values=this.values.slice(r*e,s*e)}return this}validate(){let e=!0;const t=this.getValueSize();t-Math.floor(t)!=0&&(console.error("THREE.KeyframeTrack: Invalid value size in track.",this),e=!1);const n=this.times,i=this.values,r=n.length;0===r&&(console.error("THREE.KeyframeTrack: Track is empty.",this),e=!1);let s=null;for(let t=0;t!==r;t++){const i=n[t];if("number"==typeof i&&isNaN(i)){console.error("THREE.KeyframeTrack: Time is not a valid number.",this,t,i),e=!1;break}if(null!==s&&s>i){console.error("THREE.KeyframeTrack: Out of order keys.",this,t,i,s),e=!1;break}s=i}if(void 0!==i&&ju(i))for(let t=0,n=i.length;t!==n;++t){const n=i[t];if(isNaN(n)){console.error("THREE.KeyframeTrack: Value is not a valid number.",this,t,n),e=!1;break}}return e}optimize(){const e=this.times.slice(),t=this.values.slice(),n=this.getValueSize(),i=this.getInterpolation()===Qr,r=e.length-1;let s=1;for(let o=1;o<r;++o){let r=!1;const a=e[o];if(a!==e[o+1]&&(1!==o||a!==e[0]))if(i)r=!0;else{const e=o*n,i=e-n,s=e+n;for(let o=0;o!==n;++o){const n=t[e+o];if(n!==t[i+o]||n!==t[s+o]){r=!0;break}}}if(r){if(o!==s){e[s]=e[o];const i=o*n,r=s*n;for(let e=0;e!==n;++e)t[r+e]=t[i+e]}++s}}if(r>0){e[s]=e[r];for(let e=r*n,i=s*n,o=0;o!==n;++o)t[i+o]=t[e+o];++s}return s!==e.length?(this.times=e.slice(0,s),this.values=t.slice(0,s*n)):(this.times=e,this.values=t),this}clone(){const e=this.times.slice(),t=this.values.slice(),n=new(0,this.constructor)(this.name,e,t);return n.createInterpolant=this.createInterpolant,n}}Fu.prototype.ValueTypeName="",Fu.prototype.TimeBufferType=Float32Array,Fu.prototype.ValueBufferType=Float32Array,Fu.prototype.DefaultInterpolation=Wr;class Hu extends Fu{constructor(e,t,n){super(e,t,n)}}Hu.prototype.ValueTypeName="bool",Hu.prototype.ValueBufferType=Array,Hu.prototype.DefaultInterpolation=Vr,Hu.prototype.InterpolantFactoryMethodLinear=void 0,Hu.prototype.InterpolantFactoryMethodSmooth=void 0;class Uu extends Fu{constructor(e,t,n,i){super(e,t,n,i)}}Uu.prototype.ValueTypeName="color";class Xu extends Fu{constructor(e,t,n,i){super(e,t,n,i)}}Xu.prototype.ValueTypeName="number";class Gu extends Ou{constructor(e,t,n,i){super(e,t,n,i)}interpolate_(e,t,n,i){const r=this.resultBuffer,s=this.sampleValues,o=this.valueSize,a=(n-t)/(i-t);let l=e*o;for(let e=l+o;l!==e;l+=4)Ms.slerpFlat(r,0,s,l-o,s,l,a);return r}}class Vu extends Fu{constructor(e,t,n,i){super(e,t,n,i)}InterpolantFactoryMethodLinear(e){return new Gu(this.times,this.values,this.getValueSize(),e)}}Vu.prototype.ValueTypeName="quaternion",Vu.prototype.InterpolantFactoryMethodSmooth=void 0;class Wu extends Fu{constructor(e,t,n){super(e,t,n)}}Wu.prototype.ValueTypeName="string",Wu.prototype.ValueBufferType=Array,Wu.prototype.DefaultInterpolation=Vr,Wu.prototype.InterpolantFactoryMethodLinear=void 0,Wu.prototype.InterpolantFactoryMethodSmooth=void 0;class Qu extends Fu{constructor(e,t,n,i){super(e,t,n,i)}}Qu.prototype.ValueTypeName="vector";const Zu={enabled:!1,files:{},add:function(e,t){!1!==this.enabled&&(this.files[e]=t)},get:function(e){if(!1!==this.enabled)return this.files[e]},remove:function(e){delete this.files[e]},clear:function(){this.files={}}};class Yu{constructor(e,t,n){const i=this;let r,s=!1,o=0,a=0;const l=[];this.onStart=void 0,this.onLoad=e,this.onProgress=t,this.onError=n,this.abortController=new AbortController,this.itemStart=function(e){a++,!1===s&&void 0!==i.onStart&&i.onStart(e,o,a),s=!0},this.itemEnd=function(e){o++,void 0!==i.onProgress&&i.onProgress(e,o,a),o===a&&(s=!1,void 0!==i.onLoad&&i.onLoad())},this.itemError=function(e){void 0!==i.onError&&i.onError(e)},this.resolveURL=function(e){return r?r(e):e},this.setURLModifier=function(e){return r=e,this},this.addHandler=function(e,t){return l.push(e,t),this},this.removeHandler=function(e){const t=l.indexOf(e);return-1!==t&&l.splice(t,2),this},this.getHandler=function(e){for(let t=0,n=l.length;t<n;t+=2){const n=l[t],i=l[t+1];if(n.global&&(n.lastIndex=0),n.test(e))return i}return null},this.abort=function(){return this.abortController.abort(),this.abortController=new AbortController,this}}}const Ju=new Yu;class Ku{constructor(e){this.manager=void 0!==e?e:Ju,this.crossOrigin="anonymous",this.withCredentials=!1,this.path="",this.resourcePath="",this.requestHeader={}}load(){}loadAsync(e,t){const n=this;return new Promise((function(i,r){n.load(e,i,t,r)}))}parse(){}setCrossOrigin(e){return this.crossOrigin=e,this}setWithCredentials(e){return this.withCredentials=e,this}setPath(e){return this.path=e,this}setResourcePath(e){return this.resourcePath=e,this}setRequestHeader(e){return this.requestHeader=e,this}abort(){return this}}Ku.DEFAULT_MATERIAL_NAME="__DEFAULT";const qu=new WeakMap;class _u extends Ku{constructor(e){super(e)}load(e,t,n,i){void 0!==this.path&&(e=this.path+e),e=this.manager.resolveURL(e);const r=this,s=Zu.get(`image:${e}`);if(void 0!==s){if(!0===s.complete)r.manager.itemStart(e),setTimeout((function(){t&&t(s),r.manager.itemEnd(e)}),0);else{let e=qu.get(s);void 0===e&&(e=[],qu.set(s,e)),e.push({onLoad:t,onError:i})}return s}const o=Ds("img");function a(){u(),t&&t(this);const n=qu.get(this)||[];for(let e=0;e<n.length;e++){const t=n[e];t.onLoad&&t.onLoad(this)}qu.delete(this),r.manager.itemEnd(e)}function l(t){u(),i&&i(t),Zu.remove(`image:${e}`);const n=qu.get(this)||[];for(let e=0;e<n.length;e++){const i=n[e];i.onError&&i.onError(t)}qu.delete(this),r.manager.itemError(e),r.manager.itemEnd(e)}function u(){o.removeEventListener("load",a,!1),o.removeEventListener("error",l,!1)}return o.addEventListener("load",a,!1),o.addEventListener("error",l,!1),"data:"!==e.slice(0,5)&&void 0!==this.crossOrigin&&(o.crossOrigin=this.crossOrigin),Zu.add(`image:${e}`,o),r.manager.itemStart(e),o.src=e,o}}class $u extends ta{constructor(e,t=1){super(),this.isLight=!0,this.type="Light",this.color=new ya(e),this.intensity=t}dispose(){}copy(e,t){return super.copy(e,t),this.color.copy(e.color),this.intensity=e.intensity,this}toJSON(e){const t=super.toJSON(e);return t.object.color=this.color.getHex(),t.object.intensity=this.intensity,void 0!==this.groundColor&&(t.object.groundColor=this.groundColor.getHex()),void 0!==this.distance&&(t.object.distance=this.distance),void 0!==this.angle&&(t.object.angle=this.angle),void 0!==this.decay&&(t.object.decay=this.decay),void 0!==this.penumbra&&(t.object.penumbra=this.penumbra),void 0!==this.shadow&&(t.object.shadow=this.shadow.toJSON()),void 0!==this.target&&(t.object.target=this.target.uuid),t}}class ec extends $u{constructor(e,t,n){super(e,n),this.isHemisphereLight=!0,this.type="HemisphereLight",this.position.copy(ta.DEFAULT_UP),this.updateMatrix(),this.groundColor=new ya(t)}copy(e,t){return super.copy(e,t),this.groundColor.copy(e.groundColor),this}}const tc=new Po,nc=new Es,ic=new Es;class rc{constructor(e){this.camera=e,this.intensity=1,this.bias=0,this.normalBias=0,this.radius=1,this.blurSamples=8,this.mapSize=new Cs(512,512),this.mapType=Gi,this.map=null,this.mapPass=null,this.matrix=new Po,this.autoUpdate=!0,this.needsUpdate=!1,this._frustum=new zl,this._frameExtents=new Cs(1,1),this._viewportCount=1,this._viewports=[new Js(0,0,1,1)]}getViewportCount(){return this._viewportCount}getFrustum(){return this._frustum}updateMatrices(e){const t=this.camera,n=this.matrix;nc.setFromMatrixPosition(e.matrixWorld),t.position.copy(nc),ic.setFromMatrixPosition(e.target.matrixWorld),t.lookAt(ic),t.updateMatrixWorld(),tc.multiplyMatrices(t.projectionMatrix,t.matrixWorldInverse),this._frustum.setFromProjectionMatrix(tc,t.coordinateSystem,t.reversedDepth),t.reversedDepth?n.set(.5,0,0,.5,0,.5,0,.5,0,0,1,0,0,0,0,1):n.set(.5,0,0,.5,0,.5,0,.5,0,0,.5,.5,0,0,0,1),n.multiply(tc)}getViewport(e){return this._viewports[e]}getFrameExtents(){return this._frameExtents}dispose(){this.map&&this.map.dispose(),this.mapPass&&this.mapPass.dispose()}copy(e){return this.camera=e.camera.clone(),this.intensity=e.intensity,this.bias=e.bias,this.radius=e.radius,this.autoUpdate=e.autoUpdate,this.needsUpdate=e.needsUpdate,this.normalBias=e.normalBias,this.blurSamples=e.blurSamples,this.mapSize.copy(e.mapSize),this}clone(){return(new this.constructor).copy(this)}toJSON(){const e={};return 1!==this.intensity&&(e.intensity=this.intensity),0!==this.bias&&(e.bias=this.bias),0!==this.normalBias&&(e.normalBias=this.normalBias),1!==this.radius&&(e.radius=this.radius),512===this.mapSize.x&&512===this.mapSize.y||(e.mapSize=this.mapSize.toArray()),e.camera=this.camera.toJSON(!1).object,delete e.camera.matrix,e}}class sc extends rc{constructor(){super(new pl(50,1,.5,500)),this.isSpotLightShadow=!0,this.focus=1,this.aspect=1}updateMatrices(e){const t=this.camera,n=2*gs*e.angle*this.focus,i=this.mapSize.width/this.mapSize.height*this.aspect,r=e.distance||t.far;n===t.fov&&i===t.aspect&&r===t.far||(t.fov=n,t.aspect=i,t.far=r,t.updateProjectionMatrix()),super.updateMatrices(e)}copy(e){return super.copy(e),this.focus=e.focus,this}}class oc extends $u{constructor(e,t,n=0,i=Math.PI/3,r=0,s=2){super(e,t),this.isSpotLight=!0,this.type="SpotLight",this.position.copy(ta.DEFAULT_UP),this.updateMatrix(),this.target=new ta,this.distance=n,this.angle=i,this.penumbra=r,this.decay=s,this.map=null,this.shadow=new sc}get power(){return this.intensity*Math.PI}set power(e){this.intensity=e/Math.PI}dispose(){this.shadow.dispose()}copy(e,t){return super.copy(e,t),this.distance=e.distance,this.angle=e.angle,this.penumbra=e.penumbra,this.decay=e.decay,this.target=e.target.clone(),this.shadow=e.shadow.clone(),this}}const ac=new Po,lc=new Es,uc=new Es;class cc extends rc{constructor(){super(new pl(90,1,.5,500)),this.isPointLightShadow=!0,this._frameExtents=new Cs(4,2),this._viewportCount=6,this._viewports=[new Js(2,1,1,1),new Js(0,1,1,1),new Js(3,1,1,1),new Js(1,1,1,1),new Js(3,0,1,1),new Js(1,0,1,1)],this._cubeDirections=[new Es(1,0,0),new Es(-1,0,0),new Es(0,0,1),new Es(0,0,-1),new Es(0,1,0),new Es(0,-1,0)],this._cubeUps=[new Es(0,1,0),new Es(0,1,0),new Es(0,1,0),new Es(0,1,0),new Es(0,0,1),new Es(0,0,-1)]}updateMatrices(e,t=0){const n=this.camera,i=this.matrix,r=e.distance||n.far;r!==n.far&&(n.far=r,n.updateProjectionMatrix()),lc.setFromMatrixPosition(e.matrixWorld),n.position.copy(lc),uc.copy(n.position),uc.add(this._cubeDirections[t]),n.up.copy(this._cubeUps[t]),n.lookAt(uc),n.updateMatrixWorld(),i.makeTranslation(-lc.x,-lc.y,-lc.z),ac.multiplyMatrices(n.projectionMatrix,n.matrixWorldInverse),this._frustum.setFromProjectionMatrix(ac,n.coordinateSystem,n.reversedDepth)}}class dc extends $u{constructor(e,t,n=0,i=2){super(e,t),this.isPointLight=!0,this.type="PointLight",this.distance=n,this.decay=i,this.shadow=new cc}get power(){return 4*this.intensity*Math.PI}set power(e){this.intensity=e/(4*Math.PI)}dispose(){this.shadow.dispose()}copy(e,t){return super.copy(e,t),this.distance=e.distance,this.decay=e.decay,this.shadow=e.shadow.clone(),this}}class hc extends cl{constructor(e=-1,t=1,n=1,i=-1,r=.1,s=2e3){super(),this.isOrthographicCamera=!0,this.type="OrthographicCamera",this.zoom=1,this.view=null,this.left=e,this.right=t,this.top=n,this.bottom=i,this.near=r,this.far=s,this.updateProjectionMatrix()}copy(e,t){return super.copy(e,t),this.left=e.left,this.right=e.right,this.top=e.top,this.bottom=e.bottom,this.near=e.near,this.far=e.far,this.zoom=e.zoom,this.view=null===e.view?null:Object.assign({},e.view),this}setViewOffset(e,t,n,i,r,s){null===this.view&&(this.view={enabled:!0,fullWidth:1,fullHeight:1,offsetX:0,offsetY:0,width:1,height:1}),this.view.enabled=!0,this.view.fullWidth=e,this.view.fullHeight=t,this.view.offsetX=n,this.view.offsetY=i,this.view.width=r,this.view.height=s,this.updateProjectionMatrix()}clearViewOffset(){null!==this.view&&(this.view.enabled=!1),this.updateProjectionMatrix()}updateProjectionMatrix(){const e=(this.right-this.left)/(2*this.zoom),t=(this.top-this.bottom)/(2*this.zoom),n=(this.right+this.left)/2,i=(this.top+this.bottom)/2;let r=n-e,s=n+e,o=i+t,a=i-t;if(null!==this.view&&this.view.enabled){const e=(this.right-this.left)/this.view.fullWidth/this.zoom,t=(this.top-this.bottom)/this.view.fullHeight/this.zoom;r+=e*this.view.offsetX,s=r+e*this.view.width,o-=t*this.view.offsetY,a=o-t*this.view.height}this.projectionMatrix.makeOrthographic(r,s,o,a,this.near,this.far,this.coordinateSystem,this.reversedDepth),this.projectionMatrixInverse.copy(this.projectionMatrix).invert()}toJSON(e){const t=super.toJSON(e);return t.object.zoom=this.zoom,t.object.left=this.left,t.object.right=this.right,t.object.top=this.top,t.object.bottom=this.bottom,t.object.near=this.near,t.object.far=this.far,null!==this.view&&(t.object.view=Object.assign({},this.view)),t}}class fc extends rc{constructor(){super(new hc(-5,5,5,-5,.5,500)),this.isDirectionalLightShadow=!0}}class pc extends $u{constructor(e,t){super(e,t),this.isDirectionalLight=!0,this.type="DirectionalLight",this.position.copy(ta.DEFAULT_UP),this.updateMatrix(),this.target=new ta,this.shadow=new fc}dispose(){this.shadow.dispose()}copy(e){return super.copy(e),this.target=e.target.clone(),this.shadow=e.shadow.clone(),this}}class gc extends $u{constructor(e,t){super(e,t),this.isAmbientLight=!0,this.type="AmbientLight"}}class mc extends $u{constructor(e,t,n=10,i=10){super(e,t),this.isRectAreaLight=!0,this.type="RectAreaLight",this.width=n,this.height=i}get power(){return this.intensity*this.width*this.height*Math.PI}set power(e){this.intensity=e/(this.width*this.height*Math.PI)}copy(e){return super.copy(e),this.width=e.width,this.height=e.height,this}toJSON(e){const t=super.toJSON(e);return t.object.width=this.width,t.object.height=this.height,t}}class vc{constructor(){this.isSphericalHarmonics3=!0,this.coefficients=[];for(let e=0;e<9;e++)this.coefficients.push(new Es)}set(e){for(let t=0;t<9;t++)this.coefficients[t].copy(e[t]);return this}zero(){for(let e=0;e<9;e++)this.coefficients[e].set(0,0,0);return this}getAt(e,t){const n=e.x,i=e.y,r=e.z,s=this.coefficients;return t.copy(s[0]).multiplyScalar(.282095),t.addScaledVector(s[1],.488603*i),t.addScaledVector(s[2],.488603*r),t.addScaledVector(s[3],.488603*n),t.addScaledVector(s[4],n*i*1.092548),t.addScaledVector(s[5],i*r*1.092548),t.addScaledVector(s[6],.315392*(3*r*r-1)),t.addScaledVector(s[7],n*r*1.092548),t.addScaledVector(s[8],.546274*(n*n-i*i)),t}getIrradianceAt(e,t){const n=e.x,i=e.y,r=e.z,s=this.coefficients;return t.copy(s[0]).multiplyScalar(.886227),t.addScaledVector(s[1],1.023328*i),t.addScaledVector(s[2],1.023328*r),t.addScaledVector(s[3],1.023328*n),t.addScaledVector(s[4],.858086*n*i),t.addScaledVector(s[5],.858086*i*r),t.addScaledVector(s[6],.743125*r*r-.247708),t.addScaledVector(s[7],.858086*n*r),t.addScaledVector(s[8],.429043*(n*n-i*i)),t}add(e){for(let t=0;t<9;t++)this.coefficients[t].add(e.coefficients[t]);return this}addScaledSH(e,t){for(let n=0;n<9;n++)this.coefficients[n].addScaledVector(e.coefficients[n],t);return this}scale(e){for(let t=0;t<9;t++)this.coefficients[t].multiplyScalar(e);return this}lerp(e,t){for(let n=0;n<9;n++)this.coefficients[n].lerp(e.coefficients[n],t);return this}equals(e){for(let t=0;t<9;t++)if(!this.coefficients[t].equals(e.coefficients[t]))return!1;return!0}copy(e){return this.set(e.coefficients)}clone(){return(new this.constructor).copy(this)}fromArray(e,t=0){const n=this.coefficients;for(let i=0;i<9;i++)n[i].fromArray(e,t+3*i);return this}toArray(e=[],t=0){const n=this.coefficients;for(let i=0;i<9;i++)n[i].toArray(e,t+3*i);return e}static getBasisAt(e,t){const n=e.x,i=e.y,r=e.z;t[0]=.282095,t[1]=.488603*i,t[2]=.488603*r,t[3]=.488603*n,t[4]=1.092548*n*i,t[5]=1.092548*i*r,t[6]=.315392*(3*r*r-1),t[7]=1.092548*n*r,t[8]=.546274*(n*n-i*i)}}class Ac extends $u{constructor(e=new vc,t=1){super(void 0,t),this.isLightProbe=!0,this.sh=e}copy(e){return super.copy(e),this.sh.copy(e.sh),this}fromJSON(e){return this.intensity=e.intensity,this.sh.fromArray(e.sh),this}toJSON(e){const t=super.toJSON(e);return t.object.sh=this.sh.toArray(),t}}new WeakMap;class xc extends pl{constructor(e=[]){super(),this.isArrayCamera=!0,this.isMultiViewCamera=!1,this.cameras=e}}class yc{constructor(e=!0){this.autoStart=e,this.startTime=0,this.oldTime=0,this.elapsedTime=0,this.running=!1}start(){this.startTime=performance.now(),this.oldTime=this.startTime,this.elapsedTime=0,this.running=!0}stop(){this.getElapsedTime(),this.running=!1,this.autoStart=!1}getElapsedTime(){return this.getDelta(),this.elapsedTime}getDelta(){let e=0;if(this.autoStart&&!this.running)return this.start(),0;if(this.running){const t=performance.now();e=(t-this.oldTime)/1e3,this.oldTime=t,this.elapsedTime+=e}return e}}const bc="\\[\\]\\.:\\/",wc=new RegExp("["+bc+"]","g"),Cc="[^"+bc+"]",Mc="[^"+bc.replace("\\.","")+"]",Ec=new RegExp("^"+/((?:WC+[\/:])*)/.source.replace("WC",Cc)+/(WCOD+)?/.source.replace("WCOD",Mc)+/(?:\.(WC+)(?:\[(.+)\])?)?/.source.replace("WC",Cc)+/\.(WC+)(?:\[(.+)\])?/.source.replace("WC",Cc)+"$"),Tc=["material","materials","bones","map"];class Sc{constructor(e,t,n){this.path=t,this.parsedPath=n||Sc.parseTrackName(t),this.node=Sc.findNode(e,this.parsedPath.nodeName),this.rootNode=e,this.getValue=this._getValue_unbound,this.setValue=this._setValue_unbound}static create(e,t,n){return e&&e.isAnimationObjectGroup?new Sc.Composite(e,t,n):new Sc(e,t,n)}static sanitizeNodeName(e){return e.replace(/\s/g,"_").replace(wc,"")}static parseTrackName(e){const t=Ec.exec(e);if(null===t)throw new Error("PropertyBinding: Cannot parse trackName: "+e);const n={nodeName:t[2],objectName:t[3],objectIndex:t[4],propertyName:t[5],propertyIndex:t[6]},i=n.nodeName&&n.nodeName.lastIndexOf(".");if(void 0!==i&&-1!==i){const e=n.nodeName.substring(i+1);-1!==Tc.indexOf(e)&&(n.nodeName=n.nodeName.substring(0,i),n.objectName=e)}if(null===n.propertyName||0===n.propertyName.length)throw new Error("PropertyBinding: can not parse propertyName from trackName: "+e);return n}static findNode(e,t){if(void 0===t||""===t||"."===t||-1===t||t===e.name||t===e.uuid)return e;if(e.skeleton){const n=e.skeleton.getBoneByName(t);if(void 0!==n)return n}if(e.children){const n=function(e){for(let i=0;i<e.length;i++){const r=e[i];if(r.name===t||r.uuid===t)return r;const s=n(r.children);if(s)return s}return null},i=n(e.children);if(i)return i}return null}_getValue_unavailable(){}_setValue_unavailable(){}_getValue_direct(e,t){e[t]=this.targetObject[this.propertyName]}_getValue_array(e,t){const n=this.resolvedProperty;for(let i=0,r=n.length;i!==r;++i)e[t++]=n[i]}_getValue_arrayElement(e,t){e[t]=this.resolvedProperty[this.propertyIndex]}_getValue_toArray(e,t){this.resolvedProperty.toArray(e,t)}_setValue_direct(e,t){this.targetObject[this.propertyName]=e[t]}_setValue_direct_setNeedsUpdate(e,t){this.targetObject[this.propertyName]=e[t],this.targetObject.needsUpdate=!0}_setValue_direct_setMatrixWorldNeedsUpdate(e,t){this.targetObject[this.propertyName]=e[t],this.targetObject.matrixWorldNeedsUpdate=!0}_setValue_array(e,t){const n=this.resolvedProperty;for(let i=0,r=n.length;i!==r;++i)n[i]=e[t++]}_setValue_array_setNeedsUpdate(e,t){const n=this.resolvedProperty;for(let i=0,r=n.length;i!==r;++i)n[i]=e[t++];this.targetObject.needsUpdate=!0}_setValue_array_setMatrixWorldNeedsUpdate(e,t){const n=this.resolvedProperty;for(let i=0,r=n.length;i!==r;++i)n[i]=e[t++];this.targetObject.matrixWorldNeedsUpdate=!0}_setValue_arrayElement(e,t){this.resolvedProperty[this.propertyIndex]=e[t]}_setValue_arrayElement_setNeedsUpdate(e,t){this.resolvedProperty[this.propertyIndex]=e[t],this.targetObject.needsUpdate=!0}_setValue_arrayElement_setMatrixWorldNeedsUpdate(e,t){this.resolvedProperty[this.propertyIndex]=e[t],this.targetObject.matrixWorldNeedsUpdate=!0}_setValue_fromArray(e,t){this.resolvedProperty.fromArray(e,t)}_setValue_fromArray_setNeedsUpdate(e,t){this.resolvedProperty.fromArray(e,t),this.targetObject.needsUpdate=!0}_setValue_fromArray_setMatrixWorldNeedsUpdate(e,t){this.resolvedProperty.fromArray(e,t),this.targetObject.matrixWorldNeedsUpdate=!0}_getValue_unbound(e,t){this.bind(),this.getValue(e,t)}_setValue_unbound(e,t){this.bind(),this.setValue(e,t)}bind(){let e=this.node;const t=this.parsedPath,n=t.objectName,i=t.propertyName;let r=t.propertyIndex;if(e||(e=Sc.findNode(this.rootNode,t.nodeName),this.node=e),this.getValue=this._getValue_unavailable,this.setValue=this._setValue_unavailable,!e)return void console.warn("THREE.PropertyBinding: No target node found for track: "+this.path+".");if(n){let i=t.objectIndex;switch(n){case"materials":if(!e.material)return void console.error("THREE.PropertyBinding: Can not bind to material as node does not have a material.",this);if(!e.material.materials)return void console.error("THREE.PropertyBinding: Can not bind to material.materials as node.material does not have a materials array.",this);e=e.material.materials;break;case"bones":if(!e.skeleton)return void console.error("THREE.PropertyBinding: Can not bind to bones as node does not have a skeleton.",this);e=e.skeleton.bones;for(let t=0;t<e.length;t++)if(e[t].name===i){i=t;break}break;case"map":if("map"in e){e=e.map;break}if(!e.material)return void console.error("THREE.PropertyBinding: Can not bind to material as node does not have a material.",this);if(!e.material.map)return void console.error("THREE.PropertyBinding: Can not bind to material.map as node.material does not have a map.",this);e=e.material.map;break;default:if(void 0===e[n])return void console.error("THREE.PropertyBinding: Can not bind to objectName of node undefined.",this);e=e[n]}if(void 0!==i){if(void 0===e[i])return void console.error("THREE.PropertyBinding: Trying to bind to objectIndex of objectName, but is undefined.",this,e);e=e[i]}}const s=e[i];if(void 0===s){const n=t.nodeName;return void console.error("THREE.PropertyBinding: Trying to update property for track: "+n+"."+i+" but it wasn't found.",e)}let o=this.Versioning.None;this.targetObject=e,!0===e.isMaterial?o=this.Versioning.NeedsUpdate:!0===e.isObject3D&&(o=this.Versioning.MatrixWorldNeedsUpdate);let a=this.BindingType.Direct;if(void 0!==r){if("morphTargetInfluences"===i){if(!e.geometry)return void console.error("THREE.PropertyBinding: Can not bind to morphTargetInfluences because node does not have a geometry.",this);if(!e.geometry.morphAttributes)return void console.error("THREE.PropertyBinding: Can not bind to morphTargetInfluences because node does not have a geometry.morphAttributes.",this);void 0!==e.morphTargetDictionary[r]&&(r=e.morphTargetDictionary[r])}a=this.BindingType.ArrayElement,this.resolvedProperty=s,this.propertyIndex=r}else void 0!==s.fromArray&&void 0!==s.toArray?(a=this.BindingType.HasFromToArray,this.resolvedProperty=s):Array.isArray(s)?(a=this.BindingType.EntireArray,this.resolvedProperty=s):this.propertyName=i;this.getValue=this.GetterByBindingType[a],this.setValue=this.SetterByBindingTypeAndVersioning[a][o]}unbind(){this.node=null,this.getValue=this._getValue_unbound,this.setValue=this._setValue_unbound}}Sc.Composite=class{constructor(e,t,n){const i=n||Sc.parseTrackName(t);this._targetGroup=e,this._bindings=e.subscribe_(t,i)}getValue(e,t){this.bind();const n=this._targetGroup.nCachedObjects_,i=this._bindings[n];void 0!==i&&i.getValue(e,t)}setValue(e,t){const n=this._bindings;for(let i=this._targetGroup.nCachedObjects_,r=n.length;i!==r;++i)n[i].setValue(e,t)}bind(){const e=this._bindings;for(let t=this._targetGroup.nCachedObjects_,n=e.length;t!==n;++t)e[t].bind()}unbind(){const e=this._bindings;for(let t=this._targetGroup.nCachedObjects_,n=e.length;t!==n;++t)e[t].unbind()}},Sc.prototype.BindingType={Direct:0,EntireArray:1,ArrayElement:2,HasFromToArray:3},Sc.prototype.Versioning={None:0,NeedsUpdate:1,MatrixWorldNeedsUpdate:2},Sc.prototype.GetterByBindingType=[Sc.prototype._getValue_direct,Sc.prototype._getValue_array,Sc.prototype._getValue_arrayElement,Sc.prototype._getValue_toArray],Sc.prototype.SetterByBindingTypeAndVersioning=[[Sc.prototype._setValue_direct,Sc.prototype._setValue_direct_setNeedsUpdate,Sc.prototype._setValue_direct_setMatrixWorldNeedsUpdate],[Sc.prototype._setValue_array,Sc.prototype._setValue_array_setNeedsUpdate,Sc.prototype._setValue_array_setMatrixWorldNeedsUpdate],[Sc.prototype._setValue_arrayElement,Sc.prototype._setValue_arrayElement_setNeedsUpdate,Sc.prototype._setValue_arrayElement_setMatrixWorldNeedsUpdate],[Sc.prototype._setValue_fromArray,Sc.prototype._setValue_fromArray_setNeedsUpdate,Sc.prototype._setValue_fromArray_setMatrixWorldNeedsUpdate]];new Float32Array(1);class Pc extends Cl{constructor(e,t,n=1){super(e,t),this.isInstancedInterleavedBuffer=!0,this.meshPerAttribute=n}copy(e){return super.copy(e),this.meshPerAttribute=e.meshPerAttribute,this}clone(e){const t=super.clone(e);return t.meshPerAttribute=this.meshPerAttribute,t}toJSON(e){const t=super.toJSON(e);return t.isInstancedInterleavedBuffer=!0,t.meshPerAttribute=this.meshPerAttribute,t}}const Nc=new Po;class Bc{constructor(e,t,n=0,i=1/0){this.ray=new So(e,t),this.near=n,this.far=i,this.camera=null,this.layers=new Fo,this.params={Mesh:{},Line:{threshold:1},LOD:{},Points:{threshold:1},Sprite:{}}}set(e,t){this.ray.set(e,t)}setFromCamera(e,t){t.isPerspectiveCamera?(this.ray.origin.setFromMatrixPosition(t.matrixWorld),this.ray.direction.set(e.x,e.y,.5).unproject(t).sub(this.ray.origin).normalize(),this.camera=t):t.isOrthographicCamera?(this.ray.origin.set(e.x,e.y,(t.near+t.far)/(t.near-t.far)).unproject(t),this.ray.direction.set(0,0,-1).transformDirection(t.matrixWorld),this.camera=t):console.error("THREE.Raycaster: Unsupported camera type: "+t.type)}setFromXRController(e){return Nc.identity().extractRotation(e.matrixWorld),this.ray.origin.setFromMatrixPosition(e.matrixWorld),this.ray.direction.set(0,0,-1).applyMatrix4(Nc),this}intersectObject(e,t=!0,n=[]){return Ic(e,this,n,t),n.sort(Dc),n}intersectObjects(e,t=!0,n=[]){for(let i=0,r=e.length;i<r;i++)Ic(e[i],this,n,t);return n.sort(Dc),n}}function Dc(e,t){return e.distance-t.distance}function Ic(e,t,n,i){let r=!0;if(e.layers.test(t.layers)){!1===e.raycast(t,n)&&(r=!1)}if(!0===r&&!0===i){const i=e.children;for(let e=0,r=i.length;e<r;e++)Ic(i[e],t,n,!0)}}class Lc{constructor(e=1,t=0,n=0){this.radius=e,this.phi=t,this.theta=n}set(e,t,n){return this.radius=e,this.phi=t,this.theta=n,this}copy(e){return this.radius=e.radius,this.phi=e.phi,this.theta=e.theta,this}makeSafe(){const e=1e-6;return this.phi=vs(this.phi,e,Math.PI-e),this}setFromVector3(e){return this.setFromCartesianCoords(e.x,e.y,e.z)}setFromCartesianCoords(e,t,n){return this.radius=Math.sqrt(e*e+t*t+n*n),0===this.radius?(this.theta=0,this.phi=0):(this.theta=Math.atan2(e,n),this.phi=Math.acos(vs(t/this.radius,-1,1))),this}clone(){return(new this.constructor).copy(this)}}class jc{constructor(e,t,n,i){jc.prototype.isMatrix2=!0,this.elements=[1,0,0,1],void 0!==e&&this.set(e,t,n,i)}identity(){return this.set(1,0,0,1),this}fromArray(e,t=0){for(let n=0;n<4;n++)this.elements[n]=e[n+t];return this}set(e,t,n,i){const r=this.elements;return r[0]=e,r[2]=t,r[1]=n,r[3]=i,this}}class Oc extends ds{constructor(e,t=null){super(),this.object=e,this.domElement=t,this.enabled=!0,this.state=-1,this.keys={},this.mouseButtons={LEFT:null,MIDDLE:null,RIGHT:null},this.touches={ONE:null,TWO:null}}connect(e){void 0!==e?(null!==this.domElement&&this.disconnect(),this.domElement=e):console.warn("THREE.Controls: connect() now requires an element.")}disconnect(){}dispose(){}update(){}}function zc(e,t,n,i){const r=function(e){switch(e){case Gi:case Vi:return{byteLength:1,components:1};case Qi:case Wi:case Ki:return{byteLength:2,components:1};case qi:case _i:return{byteLength:2,components:4};case Yi:case Zi:case Ji:return{byteLength:4,components:1};case er:case tr:return{byteLength:4,components:3}}throw new Error(`Unknown texture type ${e}.`)}(i);switch(n){case nr:return e*t;case ar:case lr:return e*t/r.components*r.byteLength;case ur:case cr:return e*t*2/r.components*r.byteLength;case ir:return e*t*3/r.components*r.byteLength;case rr:case 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Resizing buffer attributes is not supported.");!function(t,n,i){const r=n.array,s=n.updateRanges;if(e.bindBuffer(i,t),0===s.length)e.bufferSubData(i,0,r);else{s.sort(((e,t)=>e.start-t.start));let t=0;for(let e=1;e<s.length;e++){const n=s[t],i=s[e];i.start<=n.start+n.count+1?n.count=Math.max(n.count,i.start+i.count-n.start):(++t,s[t]=i)}s.length=t+1;for(let t=0,n=s.length;t<n;t++){const n=s[t];e.bufferSubData(i,n.start*r.BYTES_PER_ELEMENT,r,n.start,n.count)}n.clearUpdateRanges()}n.onUploadCallback()}(r.buffer,n,i),r.version=n.version}}}}const pp={alphahash_fragment:"#ifdef USE_ALPHAHASH\n\tif ( diffuseColor.a < getAlphaHashThreshold( vPosition ) ) discard;\n#endif",alphahash_pars_fragment:"#ifdef USE_ALPHAHASH\n\tconst float ALPHA_HASH_SCALE = 0.05;\n\tfloat hash2D( vec2 value ) {\n\t\treturn fract( 1.0e4 * sin( 17.0 * value.x + 0.1 * value.y ) * ( 0.1 + abs( sin( 13.0 * value.y + value.x ) ) ) );\n\t}\n\tfloat hash3D( vec3 value ) {\n\t\treturn hash2D( vec2( hash2D( value.xy ), value.z ) );\n\t}\n\tfloat getAlphaHashThreshold( vec3 position ) {\n\t\tfloat maxDeriv = max(\n\t\t\tlength( dFdx( position.xyz ) ),\n\t\t\tlength( dFdy( position.xyz ) )\n\t\t);\n\t\tfloat pixScale = 1.0 / ( ALPHA_HASH_SCALE * maxDeriv );\n\t\tvec2 pixScales = vec2(\n\t\t\texp2( floor( log2( pixScale ) ) ),\n\t\t\texp2( ceil( log2( pixScale ) ) )\n\t\t);\n\t\tvec2 alpha = vec2(\n\t\t\thash3D( floor( pixScales.x * position.xyz ) ),\n\t\t\thash3D( floor( pixScales.y * position.xyz ) )\n\t\t);\n\t\tfloat lerpFactor = fract( log2( pixScale ) );\n\t\tfloat x = ( 1.0 - lerpFactor ) * alpha.x + lerpFactor * alpha.y;\n\t\tfloat a = min( lerpFactor, 1.0 - lerpFactor );\n\t\tvec3 cases = vec3(\n\t\t\tx * x / ( 2.0 * a * ( 1.0 - a ) ),\n\t\t\t( x - 0.5 * a ) / ( 1.0 - a ),\n\t\t\t1.0 - ( ( 1.0 - x ) * ( 1.0 - x ) / ( 2.0 * a * ( 1.0 - a ) ) )\n\t\t);\n\t\tfloat threshold = ( x < ( 1.0 - a ) )\n\t\t\t? ( ( x < a ) ? cases.x : cases.y )\n\t\t\t: cases.z;\n\t\treturn clamp( threshold , 1.0e-6, 1.0 );\n\t}\n#endif",alphamap_fragment:"#ifdef USE_ALPHAMAP\n\tdiffuseColor.a *= texture2D( alphaMap, vAlphaMapUv ).g;\n#endif",alphamap_pars_fragment:"#ifdef USE_ALPHAMAP\n\tuniform sampler2D alphaMap;\n#endif",alphatest_fragment:"#ifdef USE_ALPHATEST\n\t#ifdef ALPHA_TO_COVERAGE\n\tdiffuseColor.a = smoothstep( alphaTest, alphaTest + fwidth( diffuseColor.a ), diffuseColor.a );\n\tif ( diffuseColor.a == 0.0 ) discard;\n\t#else\n\tif ( diffuseColor.a < alphaTest ) discard;\n\t#endif\n#endif",alphatest_pars_fragment:"#ifdef USE_ALPHATEST\n\tuniform float alphaTest;\n#endif",aomap_fragment:"#ifdef USE_AOMAP\n\tfloat ambientOcclusion = ( texture2D( aoMap, vAoMapUv ).r - 1.0 ) * aoMapIntensity + 1.0;\n\treflectedLight.indirectDiffuse *= ambientOcclusion;\n\t#if defined( USE_CLEARCOAT ) \n\t\tclearcoatSpecularIndirect *= ambientOcclusion;\n\t#endif\n\t#if defined( USE_SHEEN ) \n\t\tsheenSpecularIndirect *= ambientOcclusion;\n\t#endif\n\t#if defined( USE_ENVMAP ) && defined( STANDARD )\n\t\tfloat dotNV = saturate( dot( geometryNormal, geometryViewDir ) );\n\t\treflectedLight.indirectSpecular *= computeSpecularOcclusion( dotNV, ambientOcclusion, material.roughness );\n\t#endif\n#endif",aomap_pars_fragment:"#ifdef USE_AOMAP\n\tuniform sampler2D aoMap;\n\tuniform float aoMapIntensity;\n#endif",batching_pars_vertex:"#ifdef USE_BATCHING\n\t#if ! defined( GL_ANGLE_multi_draw )\n\t#define gl_DrawID _gl_DrawID\n\tuniform int _gl_DrawID;\n\t#endif\n\tuniform highp sampler2D batchingTexture;\n\tuniform highp usampler2D batchingIdTexture;\n\tmat4 getBatchingMatrix( const in float i ) {\n\t\tint size = textureSize( batchingTexture, 0 ).x;\n\t\tint j = int( i ) * 4;\n\t\tint x = j % size;\n\t\tint y = j / size;\n\t\tvec4 v1 = texelFetch( batchingTexture, ivec2( x, y ), 0 );\n\t\tvec4 v2 = texelFetch( batchingTexture, ivec2( x + 1, y ), 0 );\n\t\tvec4 v3 = texelFetch( batchingTexture, ivec2( x + 2, y ), 0 );\n\t\tvec4 v4 = texelFetch( batchingTexture, ivec2( x + 3, y ), 0 );\n\t\treturn mat4( v1, v2, v3, v4 );\n\t}\n\tfloat getIndirectIndex( const in int i ) {\n\t\tint size = textureSize( batchingIdTexture, 0 ).x;\n\t\tint x = i % size;\n\t\tint y = i / size;\n\t\treturn float( texelFetch( batchingIdTexture, ivec2( x, y ), 0 ).r );\n\t}\n#endif\n#ifdef USE_BATCHING_COLOR\n\tuniform sampler2D batchingColorTexture;\n\tvec3 getBatchingColor( const in float i ) {\n\t\tint size = textureSize( batchingColorTexture, 0 ).x;\n\t\tint j = int( i );\n\t\tint x = j % size;\n\t\tint y = j / size;\n\t\treturn texelFetch( batchingColorTexture, ivec2( x, y ), 0 ).rgb;\n\t}\n#endif",batching_vertex:"#ifdef USE_BATCHING\n\tmat4 batchingMatrix = getBatchingMatrix( getIndirectIndex( gl_DrawID ) );\n#endif",begin_vertex:"vec3 transformed = vec3( position );\n#ifdef USE_ALPHAHASH\n\tvPosition = vec3( position );\n#endif",beginnormal_vertex:"vec3 objectNormal = vec3( normal );\n#ifdef USE_TANGENT\n\tvec3 objectTangent = vec3( tangent.xyz );\n#endif",bsdfs:"float G_BlinnPhong_Implicit( ) {\n\treturn 0.25;\n}\nfloat D_BlinnPhong( const in float shininess, const in float dotNH ) {\n\treturn RECIPROCAL_PI * ( shininess * 0.5 + 1.0 ) * pow( dotNH, shininess );\n}\nvec3 BRDF_BlinnPhong( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in vec3 specularColor, const in float shininess ) {\n\tvec3 halfDir = normalize( lightDir + viewDir );\n\tfloat dotNH = saturate( dot( normal, halfDir ) );\n\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\n\tvec3 F = F_Schlick( specularColor, 1.0, dotVH );\n\tfloat G = G_BlinnPhong_Implicit( );\n\tfloat D = D_BlinnPhong( shininess, dotNH );\n\treturn F * ( G * D );\n} // validated",iridescence_fragment:"#ifdef USE_IRIDESCENCE\n\tconst mat3 XYZ_TO_REC709 = mat3(\n\t\t 3.2404542, -0.9692660,  0.0556434,\n\t\t-1.5371385,  1.8760108, -0.2040259,\n\t\t-0.4985314,  0.0415560,  1.0572252\n\t);\n\tvec3 Fresnel0ToIor( vec3 fresnel0 ) {\n\t\tvec3 sqrtF0 = sqrt( fresnel0 );\n\t\treturn ( vec3( 1.0 ) + sqrtF0 ) / ( vec3( 1.0 ) - sqrtF0 );\n\t}\n\tvec3 IorToFresnel0( vec3 transmittedIor, float incidentIor ) {\n\t\treturn pow2( ( transmittedIor - vec3( incidentIor ) ) / ( transmittedIor + vec3( incidentIor ) ) );\n\t}\n\tfloat IorToFresnel0( float transmittedIor, float incidentIor ) {\n\t\treturn pow2( ( transmittedIor - incidentIor ) / ( transmittedIor + incidentIor ));\n\t}\n\tvec3 evalSensitivity( float OPD, vec3 shift ) {\n\t\tfloat phase = 2.0 * PI * OPD * 1.0e-9;\n\t\tvec3 val = vec3( 5.4856e-13, 4.4201e-13, 5.2481e-13 );\n\t\tvec3 pos = vec3( 1.6810e+06, 1.7953e+06, 2.2084e+06 );\n\t\tvec3 var = vec3( 4.3278e+09, 9.3046e+09, 6.6121e+09 );\n\t\tvec3 xyz = val * sqrt( 2.0 * PI * var ) * cos( pos * phase + shift ) * exp( - pow2( phase ) * var );\n\t\txyz.x += 9.7470e-14 * sqrt( 2.0 * PI * 4.5282e+09 ) * cos( 2.2399e+06 * phase + shift[ 0 ] ) * exp( - 4.5282e+09 * pow2( phase ) );\n\t\txyz /= 1.0685e-7;\n\t\tvec3 rgb = XYZ_TO_REC709 * xyz;\n\t\treturn rgb;\n\t}\n\tvec3 evalIridescence( float outsideIOR, float eta2, float cosTheta1, float thinFilmThickness, vec3 baseF0 ) {\n\t\tvec3 I;\n\t\tfloat iridescenceIOR = mix( outsideIOR, eta2, smoothstep( 0.0, 0.03, thinFilmThickness ) );\n\t\tfloat sinTheta2Sq = pow2( outsideIOR / iridescenceIOR ) * ( 1.0 - pow2( cosTheta1 ) );\n\t\tfloat cosTheta2Sq = 1.0 - sinTheta2Sq;\n\t\tif ( cosTheta2Sq < 0.0 ) {\n\t\t\treturn vec3( 1.0 );\n\t\t}\n\t\tfloat cosTheta2 = sqrt( cosTheta2Sq );\n\t\tfloat R0 = IorToFresnel0( iridescenceIOR, outsideIOR );\n\t\tfloat R12 = F_Schlick( R0, 1.0, cosTheta1 );\n\t\tfloat T121 = 1.0 - R12;\n\t\tfloat phi12 = 0.0;\n\t\tif ( iridescenceIOR < outsideIOR ) phi12 = PI;\n\t\tfloat phi21 = PI - phi12;\n\t\tvec3 baseIOR = Fresnel0ToIor( clamp( baseF0, 0.0, 0.9999 ) );\t\tvec3 R1 = IorToFresnel0( baseIOR, iridescenceIOR );\n\t\tvec3 R23 = F_Schlick( R1, 1.0, cosTheta2 );\n\t\tvec3 phi23 = vec3( 0.0 );\n\t\tif ( baseIOR[ 0 ] < iridescenceIOR ) phi23[ 0 ] = PI;\n\t\tif ( baseIOR[ 1 ] < iridescenceIOR ) phi23[ 1 ] = PI;\n\t\tif ( baseIOR[ 2 ] < iridescenceIOR ) phi23[ 2 ] = PI;\n\t\tfloat OPD = 2.0 * iridescenceIOR * thinFilmThickness * cosTheta2;\n\t\tvec3 phi = vec3( phi21 ) + phi23;\n\t\tvec3 R123 = clamp( R12 * R23, 1e-5, 0.9999 );\n\t\tvec3 r123 = sqrt( R123 );\n\t\tvec3 Rs = pow2( T121 ) * R23 / ( vec3( 1.0 ) - R123 );\n\t\tvec3 C0 = R12 + Rs;\n\t\tI = C0;\n\t\tvec3 Cm = Rs - T121;\n\t\tfor ( int m = 1; m <= 2; ++ m ) {\n\t\t\tCm *= r123;\n\t\t\tvec3 Sm = 2.0 * evalSensitivity( float( m ) * OPD, float( m ) * phi );\n\t\t\tI += Cm * Sm;\n\t\t}\n\t\treturn max( I, vec3( 0.0 ) );\n\t}\n#endif",bumpmap_pars_fragment:"#ifdef USE_BUMPMAP\n\tuniform sampler2D bumpMap;\n\tuniform float bumpScale;\n\tvec2 dHdxy_fwd() {\n\t\tvec2 dSTdx = dFdx( vBumpMapUv );\n\t\tvec2 dSTdy = dFdy( vBumpMapUv );\n\t\tfloat Hll = bumpScale * texture2D( bumpMap, vBumpMapUv ).x;\n\t\tfloat dBx = bumpScale * texture2D( bumpMap, vBumpMapUv + dSTdx ).x - Hll;\n\t\tfloat dBy = bumpScale * texture2D( bumpMap, vBumpMapUv + dSTdy ).x - Hll;\n\t\treturn vec2( dBx, dBy );\n\t}\n\tvec3 perturbNormalArb( vec3 surf_pos, vec3 surf_norm, vec2 dHdxy, float faceDirection ) {\n\t\tvec3 vSigmaX = normalize( dFdx( surf_pos.xyz ) );\n\t\tvec3 vSigmaY = normalize( dFdy( surf_pos.xyz ) );\n\t\tvec3 vN = surf_norm;\n\t\tvec3 R1 = cross( vSigmaY, vN );\n\t\tvec3 R2 = cross( vN, vSigmaX );\n\t\tfloat fDet = dot( vSigmaX, R1 ) * faceDirection;\n\t\tvec3 vGrad = sign( fDet ) * ( dHdxy.x * R1 + dHdxy.y * R2 );\n\t\treturn normalize( abs( fDet ) * surf_norm - vGrad );\n\t}\n#endif",clipping_planes_fragment:"#if NUM_CLIPPING_PLANES > 0\n\tvec4 plane;\n\t#ifdef ALPHA_TO_COVERAGE\n\t\tfloat distanceToPlane, distanceGradient;\n\t\tfloat clipOpacity = 1.0;\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = 0; i < UNION_CLIPPING_PLANES; i ++ ) {\n\t\t\tplane = clippingPlanes[ i ];\n\t\t\tdistanceToPlane = - dot( vClipPosition, plane.xyz ) + plane.w;\n\t\t\tdistanceGradient = fwidth( distanceToPlane ) / 2.0;\n\t\t\tclipOpacity *= smoothstep( - distanceGradient, distanceGradient, distanceToPlane );\n\t\t\tif ( clipOpacity == 0.0 ) discard;\n\t\t}\n\t\t#pragma unroll_loop_end\n\t\t#if UNION_CLIPPING_PLANES < NUM_CLIPPING_PLANES\n\t\t\tfloat unionClipOpacity = 1.0;\n\t\t\t#pragma unroll_loop_start\n\t\t\tfor ( int i = UNION_CLIPPING_PLANES; i < NUM_CLIPPING_PLANES; i ++ ) {\n\t\t\t\tplane = clippingPlanes[ i ];\n\t\t\t\tdistanceToPlane = - dot( vClipPosition, plane.xyz ) + plane.w;\n\t\t\t\tdistanceGradient = fwidth( distanceToPlane ) / 2.0;\n\t\t\t\tunionClipOpacity *= 1.0 - smoothstep( - distanceGradient, distanceGradient, distanceToPlane );\n\t\t\t}\n\t\t\t#pragma unroll_loop_end\n\t\t\tclipOpacity *= 1.0 - unionClipOpacity;\n\t\t#endif\n\t\tdiffuseColor.a *= clipOpacity;\n\t\tif ( diffuseColor.a == 0.0 ) discard;\n\t#else\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = 0; i < UNION_CLIPPING_PLANES; i ++ ) {\n\t\t\tplane = clippingPlanes[ i ];\n\t\t\tif ( dot( vClipPosition, plane.xyz ) > plane.w ) discard;\n\t\t}\n\t\t#pragma unroll_loop_end\n\t\t#if UNION_CLIPPING_PLANES < NUM_CLIPPING_PLANES\n\t\t\tbool clipped = true;\n\t\t\t#pragma unroll_loop_start\n\t\t\tfor ( int i = UNION_CLIPPING_PLANES; i < NUM_CLIPPING_PLANES; i ++ ) {\n\t\t\t\tplane = clippingPlanes[ i ];\n\t\t\t\tclipped = ( dot( vClipPosition, plane.xyz ) > plane.w ) && clipped;\n\t\t\t}\n\t\t\t#pragma unroll_loop_end\n\t\t\tif ( clipped ) discard;\n\t\t#endif\n\t#endif\n#endif",clipping_planes_pars_fragment:"#if NUM_CLIPPING_PLANES > 0\n\tvarying vec3 vClipPosition;\n\tuniform vec4 clippingPlanes[ NUM_CLIPPING_PLANES ];\n#endif",clipping_planes_pars_vertex:"#if NUM_CLIPPING_PLANES > 0\n\tvarying vec3 vClipPosition;\n#endif",clipping_planes_vertex:"#if NUM_CLIPPING_PLANES > 0\n\tvClipPosition = - mvPosition.xyz;\n#endif",color_fragment:"#if defined( USE_COLOR_ALPHA )\n\tdiffuseColor *= vColor;\n#elif defined( USE_COLOR )\n\tdiffuseColor.rgb *= vColor;\n#endif",color_pars_fragment:"#if defined( USE_COLOR_ALPHA )\n\tvarying vec4 vColor;\n#elif defined( USE_COLOR )\n\tvarying vec3 vColor;\n#endif",color_pars_vertex:"#if defined( USE_COLOR_ALPHA )\n\tvarying vec4 vColor;\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR ) || defined( USE_BATCHING_COLOR )\n\tvarying vec3 vColor;\n#endif",color_vertex:"#if defined( USE_COLOR_ALPHA )\n\tvColor = vec4( 1.0 );\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR ) || defined( USE_BATCHING_COLOR )\n\tvColor = vec3( 1.0 );\n#endif\n#ifdef USE_COLOR\n\tvColor *= color;\n#endif\n#ifdef USE_INSTANCING_COLOR\n\tvColor.xyz *= instanceColor.xyz;\n#endif\n#ifdef USE_BATCHING_COLOR\n\tvec3 batchingColor = getBatchingColor( getIndirectIndex( gl_DrawID ) );\n\tvColor.xyz *= batchingColor.xyz;\n#endif",common:"#define PI 3.141592653589793\n#define PI2 6.283185307179586\n#define PI_HALF 1.5707963267948966\n#define RECIPROCAL_PI 0.3183098861837907\n#define RECIPROCAL_PI2 0.15915494309189535\n#define EPSILON 1e-6\n#ifndef saturate\n#define saturate( a ) clamp( a, 0.0, 1.0 )\n#endif\n#define whiteComplement( a ) ( 1.0 - saturate( a ) )\nfloat pow2( const in float x ) { return x*x; }\nvec3 pow2( const in vec3 x ) { return x*x; }\nfloat pow3( const in float x ) { return x*x*x; }\nfloat pow4( const in float x ) { float x2 = x*x; return x2*x2; }\nfloat max3( const in vec3 v ) { return max( max( v.x, v.y ), v.z ); }\nfloat average( const in vec3 v ) { return dot( v, vec3( 0.3333333 ) ); }\nhighp float rand( const in vec2 uv ) {\n\tconst highp float a = 12.9898, b = 78.233, c = 43758.5453;\n\thighp float dt = dot( uv.xy, vec2( a,b ) ), sn = mod( dt, PI );\n\treturn fract( sin( sn ) * c );\n}\n#ifdef HIGH_PRECISION\n\tfloat precisionSafeLength( vec3 v ) { return length( v ); }\n#else\n\tfloat precisionSafeLength( vec3 v ) {\n\t\tfloat maxComponent = max3( abs( v ) );\n\t\treturn length( v / maxComponent ) * maxComponent;\n\t}\n#endif\nstruct IncidentLight {\n\tvec3 color;\n\tvec3 direction;\n\tbool visible;\n};\nstruct ReflectedLight {\n\tvec3 directDiffuse;\n\tvec3 directSpecular;\n\tvec3 indirectDiffuse;\n\tvec3 indirectSpecular;\n};\n#ifdef USE_ALPHAHASH\n\tvarying vec3 vPosition;\n#endif\nvec3 transformDirection( in vec3 dir, in mat4 matrix ) {\n\treturn normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );\n}\nvec3 inverseTransformDirection( in vec3 dir, in mat4 matrix ) {\n\treturn normalize( ( vec4( dir, 0.0 ) * matrix ).xyz );\n}\nmat3 transposeMat3( const in mat3 m ) {\n\tmat3 tmp;\n\ttmp[ 0 ] = vec3( m[ 0 ].x, m[ 1 ].x, m[ 2 ].x );\n\ttmp[ 1 ] = vec3( m[ 0 ].y, m[ 1 ].y, m[ 2 ].y );\n\ttmp[ 2 ] = vec3( m[ 0 ].z, m[ 1 ].z, m[ 2 ].z );\n\treturn tmp;\n}\nbool isPerspectiveMatrix( mat4 m ) {\n\treturn m[ 2 ][ 3 ] == - 1.0;\n}\nvec2 equirectUv( in vec3 dir ) {\n\tfloat u = atan( dir.z, dir.x ) * RECIPROCAL_PI2 + 0.5;\n\tfloat v = asin( clamp( dir.y, - 1.0, 1.0 ) ) * RECIPROCAL_PI + 0.5;\n\treturn vec2( u, v );\n}\nvec3 BRDF_Lambert( const in vec3 diffuseColor ) {\n\treturn RECIPROCAL_PI * diffuseColor;\n}\nvec3 F_Schlick( const in vec3 f0, const in float f90, const in float dotVH ) {\n\tfloat fresnel = exp2( ( - 5.55473 * dotVH - 6.98316 ) * dotVH );\n\treturn f0 * ( 1.0 - fresnel ) + ( f90 * fresnel );\n}\nfloat F_Schlick( const in float f0, const in float f90, const in float dotVH ) {\n\tfloat fresnel = exp2( ( - 5.55473 * dotVH - 6.98316 ) * dotVH );\n\treturn f0 * ( 1.0 - fresnel ) + ( f90 * fresnel );\n} // validated",cube_uv_reflection_fragment:"#ifdef ENVMAP_TYPE_CUBE_UV\n\t#define cubeUV_minMipLevel 4.0\n\t#define cubeUV_minTileSize 16.0\n\tfloat getFace( vec3 direction ) {\n\t\tvec3 absDirection = abs( direction );\n\t\tfloat face = - 1.0;\n\t\tif ( absDirection.x > absDirection.z ) {\n\t\t\tif ( absDirection.x > absDirection.y )\n\t\t\t\tface = direction.x > 0.0 ? 0.0 : 3.0;\n\t\t\telse\n\t\t\t\tface = direction.y > 0.0 ? 1.0 : 4.0;\n\t\t} else {\n\t\t\tif ( absDirection.z > absDirection.y )\n\t\t\t\tface = direction.z > 0.0 ? 2.0 : 5.0;\n\t\t\telse\n\t\t\t\tface = direction.y > 0.0 ? 1.0 : 4.0;\n\t\t}\n\t\treturn face;\n\t}\n\tvec2 getUV( vec3 direction, float face ) {\n\t\tvec2 uv;\n\t\tif ( face == 0.0 ) {\n\t\t\tuv = vec2( direction.z, direction.y ) / abs( direction.x );\n\t\t} else if ( face == 1.0 ) {\n\t\t\tuv = vec2( - direction.x, - direction.z ) / abs( direction.y );\n\t\t} else if ( face == 2.0 ) {\n\t\t\tuv = vec2( - direction.x, direction.y ) / abs( direction.z );\n\t\t} else if ( face == 3.0 ) {\n\t\t\tuv = vec2( - direction.z, direction.y ) / abs( direction.x );\n\t\t} else if ( face == 4.0 ) {\n\t\t\tuv = vec2( - direction.x, direction.z ) / abs( direction.y );\n\t\t} else {\n\t\t\tuv = vec2( direction.x, direction.y ) / abs( direction.z );\n\t\t}\n\t\treturn 0.5 * ( uv + 1.0 );\n\t}\n\tvec3 bilinearCubeUV( sampler2D envMap, vec3 direction, float mipInt ) {\n\t\tfloat face = getFace( direction );\n\t\tfloat filterInt = max( cubeUV_minMipLevel - mipInt, 0.0 );\n\t\tmipInt = max( mipInt, cubeUV_minMipLevel );\n\t\tfloat faceSize = exp2( mipInt );\n\t\thighp vec2 uv = getUV( direction, face ) * ( faceSize - 2.0 ) + 1.0;\n\t\tif ( face > 2.0 ) {\n\t\t\tuv.y += faceSize;\n\t\t\tface -= 3.0;\n\t\t}\n\t\tuv.x += face * faceSize;\n\t\tuv.x += filterInt * 3.0 * cubeUV_minTileSize;\n\t\tuv.y += 4.0 * ( exp2( CUBEUV_MAX_MIP ) - faceSize );\n\t\tuv.x *= CUBEUV_TEXEL_WIDTH;\n\t\tuv.y *= CUBEUV_TEXEL_HEIGHT;\n\t\t#ifdef texture2DGradEXT\n\t\t\treturn texture2DGradEXT( envMap, uv, vec2( 0.0 ), vec2( 0.0 ) ).rgb;\n\t\t#else\n\t\t\treturn texture2D( envMap, uv ).rgb;\n\t\t#endif\n\t}\n\t#define cubeUV_r0 1.0\n\t#define cubeUV_m0 - 2.0\n\t#define cubeUV_r1 0.8\n\t#define cubeUV_m1 - 1.0\n\t#define cubeUV_r4 0.4\n\t#define cubeUV_m4 2.0\n\t#define cubeUV_r5 0.305\n\t#define cubeUV_m5 3.0\n\t#define cubeUV_r6 0.21\n\t#define cubeUV_m6 4.0\n\tfloat roughnessToMip( float roughness ) {\n\t\tfloat mip = 0.0;\n\t\tif ( roughness >= cubeUV_r1 ) {\n\t\t\tmip = ( cubeUV_r0 - roughness ) * ( cubeUV_m1 - cubeUV_m0 ) / ( cubeUV_r0 - cubeUV_r1 ) + cubeUV_m0;\n\t\t} else if ( roughness >= cubeUV_r4 ) {\n\t\t\tmip = ( cubeUV_r1 - roughness ) * ( cubeUV_m4 - cubeUV_m1 ) / ( cubeUV_r1 - cubeUV_r4 ) + cubeUV_m1;\n\t\t} else if ( roughness >= cubeUV_r5 ) {\n\t\t\tmip = ( cubeUV_r4 - roughness ) * ( cubeUV_m5 - cubeUV_m4 ) / ( cubeUV_r4 - cubeUV_r5 ) + cubeUV_m4;\n\t\t} else if ( roughness >= cubeUV_r6 ) {\n\t\t\tmip = ( cubeUV_r5 - roughness ) * ( cubeUV_m6 - cubeUV_m5 ) / ( cubeUV_r5 - cubeUV_r6 ) + cubeUV_m5;\n\t\t} else {\n\t\t\tmip = - 2.0 * log2( 1.16 * roughness );\t\t}\n\t\treturn mip;\n\t}\n\tvec4 textureCubeUV( sampler2D envMap, vec3 sampleDir, float roughness ) {\n\t\tfloat mip = clamp( roughnessToMip( roughness ), cubeUV_m0, CUBEUV_MAX_MIP );\n\t\tfloat mipF = fract( mip );\n\t\tfloat mipInt = floor( mip );\n\t\tvec3 color0 = bilinearCubeUV( envMap, sampleDir, mipInt );\n\t\tif ( mipF == 0.0 ) {\n\t\t\treturn vec4( color0, 1.0 );\n\t\t} else {\n\t\t\tvec3 color1 = bilinearCubeUV( envMap, sampleDir, mipInt + 1.0 );\n\t\t\treturn vec4( mix( color0, color1, mipF ), 1.0 );\n\t\t}\n\t}\n#endif",defaultnormal_vertex:"vec3 transformedNormal = objectNormal;\n#ifdef USE_TANGENT\n\tvec3 transformedTangent = objectTangent;\n#endif\n#ifdef USE_BATCHING\n\tmat3 bm = mat3( batchingMatrix );\n\ttransformedNormal /= vec3( dot( bm[ 0 ], bm[ 0 ] ), dot( bm[ 1 ], bm[ 1 ] ), dot( bm[ 2 ], bm[ 2 ] ) );\n\ttransformedNormal = bm * transformedNormal;\n\t#ifdef USE_TANGENT\n\t\ttransformedTangent = bm * transformedTangent;\n\t#endif\n#endif\n#ifdef USE_INSTANCING\n\tmat3 im = mat3( instanceMatrix );\n\ttransformedNormal /= vec3( dot( im[ 0 ], im[ 0 ] ), dot( im[ 1 ], im[ 1 ] ), dot( im[ 2 ], im[ 2 ] ) );\n\ttransformedNormal = im * transformedNormal;\n\t#ifdef USE_TANGENT\n\t\ttransformedTangent = im * transformedTangent;\n\t#endif\n#endif\ntransformedNormal = normalMatrix * transformedNormal;\n#ifdef FLIP_SIDED\n\ttransformedNormal = - transformedNormal;\n#endif\n#ifdef USE_TANGENT\n\ttransformedTangent = ( modelViewMatrix * vec4( transformedTangent, 0.0 ) ).xyz;\n\t#ifdef FLIP_SIDED\n\t\ttransformedTangent = - transformedTangent;\n\t#endif\n#endif",displacementmap_pars_vertex:"#ifdef USE_DISPLACEMENTMAP\n\tuniform sampler2D displacementMap;\n\tuniform float displacementScale;\n\tuniform float displacementBias;\n#endif",displacementmap_vertex:"#ifdef USE_DISPLACEMENTMAP\n\ttransformed += normalize( objectNormal ) * ( texture2D( displacementMap, vDisplacementMapUv ).x * displacementScale + displacementBias );\n#endif",emissivemap_fragment:"#ifdef USE_EMISSIVEMAP\n\tvec4 emissiveColor = texture2D( emissiveMap, vEmissiveMapUv );\n\t#ifdef DECODE_VIDEO_TEXTURE_EMISSIVE\n\t\temissiveColor = sRGBTransferEOTF( emissiveColor );\n\t#endif\n\ttotalEmissiveRadiance *= emissiveColor.rgb;\n#endif",emissivemap_pars_fragment:"#ifdef USE_EMISSIVEMAP\n\tuniform sampler2D emissiveMap;\n#endif",colorspace_fragment:"gl_FragColor = linearToOutputTexel( gl_FragColor );",colorspace_pars_fragment:"vec4 LinearTransferOETF( in vec4 value ) {\n\treturn value;\n}\nvec4 sRGBTransferEOTF( in vec4 value ) {\n\treturn vec4( mix( pow( value.rgb * 0.9478672986 + vec3( 0.0521327014 ), vec3( 2.4 ) ), value.rgb * 0.0773993808, vec3( lessThanEqual( value.rgb, vec3( 0.04045 ) ) ) ), value.a );\n}\nvec4 sRGBTransferOETF( in vec4 value ) {\n\treturn vec4( mix( pow( value.rgb, vec3( 0.41666 ) ) * 1.055 - vec3( 0.055 ), value.rgb * 12.92, vec3( lessThanEqual( value.rgb, vec3( 0.0031308 ) ) ) ), value.a );\n}",envmap_fragment:"#ifdef USE_ENVMAP\n\t#ifdef ENV_WORLDPOS\n\t\tvec3 cameraToFrag;\n\t\tif ( isOrthographic ) {\n\t\t\tcameraToFrag = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\n\t\t} else {\n\t\t\tcameraToFrag = normalize( vWorldPosition - cameraPosition );\n\t\t}\n\t\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\n\t\t#ifdef ENVMAP_MODE_REFLECTION\n\t\t\tvec3 reflectVec = reflect( cameraToFrag, worldNormal );\n\t\t#else\n\t\t\tvec3 reflectVec = refract( cameraToFrag, worldNormal, refractionRatio );\n\t\t#endif\n\t#else\n\t\tvec3 reflectVec = vReflect;\n\t#endif\n\t#ifdef ENVMAP_TYPE_CUBE\n\t\tvec4 envColor = textureCube( envMap, envMapRotation * vec3( flipEnvMap * reflectVec.x, reflectVec.yz ) );\n\t#else\n\t\tvec4 envColor = vec4( 0.0 );\n\t#endif\n\t#ifdef ENVMAP_BLENDING_MULTIPLY\n\t\toutgoingLight = mix( outgoingLight, outgoingLight * envColor.xyz, specularStrength * reflectivity );\n\t#elif defined( ENVMAP_BLENDING_MIX )\n\t\toutgoingLight = mix( outgoingLight, envColor.xyz, specularStrength * reflectivity );\n\t#elif defined( ENVMAP_BLENDING_ADD )\n\t\toutgoingLight += envColor.xyz * specularStrength * reflectivity;\n\t#endif\n#endif",envmap_common_pars_fragment:"#ifdef USE_ENVMAP\n\tuniform float envMapIntensity;\n\tuniform float flipEnvMap;\n\tuniform mat3 envMapRotation;\n\t#ifdef ENVMAP_TYPE_CUBE\n\t\tuniform samplerCube envMap;\n\t#else\n\t\tuniform sampler2D envMap;\n\t#endif\n\t\n#endif",envmap_pars_fragment:"#ifdef USE_ENVMAP\n\tuniform float reflectivity;\n\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( PHONG ) || defined( LAMBERT )\n\t\t#define ENV_WORLDPOS\n\t#endif\n\t#ifdef ENV_WORLDPOS\n\t\tvarying vec3 vWorldPosition;\n\t\tuniform float refractionRatio;\n\t#else\n\t\tvarying vec3 vReflect;\n\t#endif\n#endif",envmap_pars_vertex:"#ifdef USE_ENVMAP\n\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( PHONG ) || defined( LAMBERT )\n\t\t#define ENV_WORLDPOS\n\t#endif\n\t#ifdef ENV_WORLDPOS\n\t\t\n\t\tvarying vec3 vWorldPosition;\n\t#else\n\t\tvarying vec3 vReflect;\n\t\tuniform float refractionRatio;\n\t#endif\n#endif",envmap_physical_pars_fragment:"#ifdef USE_ENVMAP\n\tvec3 getIBLIrradiance( const in vec3 normal ) {\n\t\t#ifdef ENVMAP_TYPE_CUBE_UV\n\t\t\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\n\t\t\tvec4 envMapColor = textureCubeUV( envMap, envMapRotation * worldNormal, 1.0 );\n\t\t\treturn PI * envMapColor.rgb * envMapIntensity;\n\t\t#else\n\t\t\treturn vec3( 0.0 );\n\t\t#endif\n\t}\n\tvec3 getIBLRadiance( const in vec3 viewDir, const in vec3 normal, const in float roughness ) {\n\t\t#ifdef ENVMAP_TYPE_CUBE_UV\n\t\t\tvec3 reflectVec = reflect( - viewDir, normal );\n\t\t\treflectVec = normalize( mix( reflectVec, normal, roughness * roughness) );\n\t\t\treflectVec = inverseTransformDirection( reflectVec, viewMatrix );\n\t\t\tvec4 envMapColor = textureCubeUV( envMap, envMapRotation * reflectVec, roughness );\n\t\t\treturn envMapColor.rgb * envMapIntensity;\n\t\t#else\n\t\t\treturn vec3( 0.0 );\n\t\t#endif\n\t}\n\t#ifdef USE_ANISOTROPY\n\t\tvec3 getIBLAnisotropyRadiance( const in vec3 viewDir, const in vec3 normal, const in float roughness, const in vec3 bitangent, const in float anisotropy ) {\n\t\t\t#ifdef ENVMAP_TYPE_CUBE_UV\n\t\t\t\tvec3 bentNormal = cross( bitangent, viewDir );\n\t\t\t\tbentNormal = normalize( cross( bentNormal, bitangent ) );\n\t\t\t\tbentNormal = normalize( mix( bentNormal, normal, pow2( pow2( 1.0 - anisotropy * ( 1.0 - roughness ) ) ) ) );\n\t\t\t\treturn getIBLRadiance( viewDir, bentNormal, roughness );\n\t\t\t#else\n\t\t\t\treturn vec3( 0.0 );\n\t\t\t#endif\n\t\t}\n\t#endif\n#endif",envmap_vertex:"#ifdef USE_ENVMAP\n\t#ifdef ENV_WORLDPOS\n\t\tvWorldPosition = worldPosition.xyz;\n\t#else\n\t\tvec3 cameraToVertex;\n\t\tif ( isOrthographic ) {\n\t\t\tcameraToVertex = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\n\t\t} else {\n\t\t\tcameraToVertex = normalize( worldPosition.xyz - cameraPosition );\n\t\t}\n\t\tvec3 worldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\n\t\t#ifdef ENVMAP_MODE_REFLECTION\n\t\t\tvReflect = reflect( cameraToVertex, worldNormal );\n\t\t#else\n\t\t\tvReflect = refract( cameraToVertex, worldNormal, refractionRatio );\n\t\t#endif\n\t#endif\n#endif",fog_vertex:"#ifdef USE_FOG\n\tvFogDepth = - mvPosition.z;\n#endif",fog_pars_vertex:"#ifdef USE_FOG\n\tvarying float vFogDepth;\n#endif",fog_fragment:"#ifdef USE_FOG\n\t#ifdef FOG_EXP2\n\t\tfloat fogFactor = 1.0 - exp( - fogDensity * fogDensity * vFogDepth * vFogDepth );\n\t#else\n\t\tfloat fogFactor = smoothstep( fogNear, fogFar, vFogDepth );\n\t#endif\n\tgl_FragColor.rgb = mix( gl_FragColor.rgb, fogColor, fogFactor );\n#endif",fog_pars_fragment:"#ifdef USE_FOG\n\tuniform vec3 fogColor;\n\tvarying float vFogDepth;\n\t#ifdef FOG_EXP2\n\t\tuniform float fogDensity;\n\t#else\n\t\tuniform float fogNear;\n\t\tuniform float fogFar;\n\t#endif\n#endif",gradientmap_pars_fragment:"#ifdef USE_GRADIENTMAP\n\tuniform sampler2D gradientMap;\n#endif\nvec3 getGradientIrradiance( vec3 normal, vec3 lightDirection ) {\n\tfloat dotNL = dot( normal, lightDirection );\n\tvec2 coord = vec2( dotNL * 0.5 + 0.5, 0.0 );\n\t#ifdef USE_GRADIENTMAP\n\t\treturn vec3( texture2D( gradientMap, coord ).r );\n\t#else\n\t\tvec2 fw = fwidth( coord ) * 0.5;\n\t\treturn mix( vec3( 0.7 ), vec3( 1.0 ), smoothstep( 0.7 - fw.x, 0.7 + fw.x, coord.x ) );\n\t#endif\n}",lightmap_pars_fragment:"#ifdef USE_LIGHTMAP\n\tuniform sampler2D lightMap;\n\tuniform float lightMapIntensity;\n#endif",lights_lambert_fragment:"LambertMaterial material;\nmaterial.diffuseColor = diffuseColor.rgb;\nmaterial.specularStrength = specularStrength;",lights_lambert_pars_fragment:"varying vec3 vViewPosition;\nstruct LambertMaterial {\n\tvec3 diffuseColor;\n\tfloat specularStrength;\n};\nvoid RE_Direct_Lambert( const in IncidentLight directLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in LambertMaterial material, inout ReflectedLight reflectedLight ) {\n\tfloat dotNL = saturate( dot( geometryNormal, directLight.direction ) );\n\tvec3 irradiance = dotNL * directLight.color;\n\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\nvoid RE_IndirectDiffuse_Lambert( const in vec3 irradiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in LambertMaterial material, inout ReflectedLight reflectedLight ) {\n\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\n#define RE_Direct\t\t\t\tRE_Direct_Lambert\n#define RE_IndirectDiffuse\t\tRE_IndirectDiffuse_Lambert",lights_pars_begin:"uniform bool receiveShadow;\nuniform vec3 ambientLightColor;\n#if defined( USE_LIGHT_PROBES )\n\tuniform vec3 lightProbe[ 9 ];\n#endif\nvec3 shGetIrradianceAt( in vec3 normal, in vec3 shCoefficients[ 9 ] ) {\n\tfloat x = normal.x, y = normal.y, z = normal.z;\n\tvec3 result = shCoefficients[ 0 ] * 0.886227;\n\tresult += shCoefficients[ 1 ] * 2.0 * 0.511664 * y;\n\tresult += shCoefficients[ 2 ] * 2.0 * 0.511664 * z;\n\tresult += shCoefficients[ 3 ] * 2.0 * 0.511664 * x;\n\tresult += shCoefficients[ 4 ] * 2.0 * 0.429043 * x * y;\n\tresult += shCoefficients[ 5 ] * 2.0 * 0.429043 * y * z;\n\tresult += shCoefficients[ 6 ] * ( 0.743125 * z * z - 0.247708 );\n\tresult += shCoefficients[ 7 ] * 2.0 * 0.429043 * x * z;\n\tresult += shCoefficients[ 8 ] * 0.429043 * ( x * x - y * y );\n\treturn result;\n}\nvec3 getLightProbeIrradiance( const in vec3 lightProbe[ 9 ], const in vec3 normal ) {\n\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\n\tvec3 irradiance = shGetIrradianceAt( worldNormal, lightProbe );\n\treturn irradiance;\n}\nvec3 getAmbientLightIrradiance( const in vec3 ambientLightColor ) {\n\tvec3 irradiance = ambientLightColor;\n\treturn irradiance;\n}\nfloat getDistanceAttenuation( const in float lightDistance, const in float cutoffDistance, const in float decayExponent ) {\n\tfloat distanceFalloff = 1.0 / max( pow( lightDistance, decayExponent ), 0.01 );\n\tif ( cutoffDistance > 0.0 ) {\n\t\tdistanceFalloff *= pow2( saturate( 1.0 - pow4( lightDistance / cutoffDistance ) ) );\n\t}\n\treturn distanceFalloff;\n}\nfloat getSpotAttenuation( const in float coneCosine, const in float penumbraCosine, const in float angleCosine ) {\n\treturn smoothstep( coneCosine, penumbraCosine, angleCosine );\n}\n#if NUM_DIR_LIGHTS > 0\n\tstruct DirectionalLight {\n\t\tvec3 direction;\n\t\tvec3 color;\n\t};\n\tuniform DirectionalLight directionalLights[ NUM_DIR_LIGHTS ];\n\tvoid getDirectionalLightInfo( const in DirectionalLight directionalLight, out IncidentLight light ) {\n\t\tlight.color = directionalLight.color;\n\t\tlight.direction = directionalLight.direction;\n\t\tlight.visible = true;\n\t}\n#endif\n#if NUM_POINT_LIGHTS > 0\n\tstruct PointLight {\n\t\tvec3 position;\n\t\tvec3 color;\n\t\tfloat distance;\n\t\tfloat decay;\n\t};\n\tuniform PointLight pointLights[ NUM_POINT_LIGHTS ];\n\tvoid getPointLightInfo( const in PointLight pointLight, const in vec3 geometryPosition, out IncidentLight light ) {\n\t\tvec3 lVector = pointLight.position - geometryPosition;\n\t\tlight.direction = normalize( lVector );\n\t\tfloat lightDistance = length( lVector );\n\t\tlight.color = pointLight.color;\n\t\tlight.color *= getDistanceAttenuation( lightDistance, pointLight.distance, pointLight.decay );\n\t\tlight.visible = ( light.color != vec3( 0.0 ) );\n\t}\n#endif\n#if NUM_SPOT_LIGHTS > 0\n\tstruct SpotLight {\n\t\tvec3 position;\n\t\tvec3 direction;\n\t\tvec3 color;\n\t\tfloat distance;\n\t\tfloat decay;\n\t\tfloat coneCos;\n\t\tfloat penumbraCos;\n\t};\n\tuniform SpotLight spotLights[ NUM_SPOT_LIGHTS ];\n\tvoid getSpotLightInfo( const in SpotLight spotLight, const in vec3 geometryPosition, out IncidentLight light ) {\n\t\tvec3 lVector = spotLight.position - geometryPosition;\n\t\tlight.direction = normalize( lVector );\n\t\tfloat angleCos = dot( light.direction, spotLight.direction );\n\t\tfloat spotAttenuation = getSpotAttenuation( spotLight.coneCos, spotLight.penumbraCos, angleCos );\n\t\tif ( spotAttenuation > 0.0 ) {\n\t\t\tfloat lightDistance = length( lVector );\n\t\t\tlight.color = spotLight.color * spotAttenuation;\n\t\t\tlight.color *= getDistanceAttenuation( lightDistance, spotLight.distance, spotLight.decay );\n\t\t\tlight.visible = ( light.color != vec3( 0.0 ) );\n\t\t} else {\n\t\t\tlight.color = vec3( 0.0 );\n\t\t\tlight.visible = false;\n\t\t}\n\t}\n#endif\n#if NUM_RECT_AREA_LIGHTS > 0\n\tstruct RectAreaLight {\n\t\tvec3 color;\n\t\tvec3 position;\n\t\tvec3 halfWidth;\n\t\tvec3 halfHeight;\n\t};\n\tuniform sampler2D ltc_1;\tuniform sampler2D ltc_2;\n\tuniform RectAreaLight rectAreaLights[ NUM_RECT_AREA_LIGHTS ];\n#endif\n#if NUM_HEMI_LIGHTS > 0\n\tstruct HemisphereLight {\n\t\tvec3 direction;\n\t\tvec3 skyColor;\n\t\tvec3 groundColor;\n\t};\n\tuniform HemisphereLight hemisphereLights[ NUM_HEMI_LIGHTS ];\n\tvec3 getHemisphereLightIrradiance( const in HemisphereLight hemiLight, const in vec3 normal ) {\n\t\tfloat dotNL = dot( normal, hemiLight.direction );\n\t\tfloat hemiDiffuseWeight = 0.5 * dotNL + 0.5;\n\t\tvec3 irradiance = mix( hemiLight.groundColor, hemiLight.skyColor, hemiDiffuseWeight );\n\t\treturn irradiance;\n\t}\n#endif",lights_toon_fragment:"ToonMaterial material;\nmaterial.diffuseColor = diffuseColor.rgb;",lights_toon_pars_fragment:"varying vec3 vViewPosition;\nstruct ToonMaterial {\n\tvec3 diffuseColor;\n};\nvoid RE_Direct_Toon( const in IncidentLight directLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\n\tvec3 irradiance = getGradientIrradiance( geometryNormal, directLight.direction ) * directLight.color;\n\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\nvoid RE_IndirectDiffuse_Toon( const in vec3 irradiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\n\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\n#define RE_Direct\t\t\t\tRE_Direct_Toon\n#define RE_IndirectDiffuse\t\tRE_IndirectDiffuse_Toon",lights_phong_fragment:"BlinnPhongMaterial material;\nmaterial.diffuseColor = diffuseColor.rgb;\nmaterial.specularColor = specular;\nmaterial.specularShininess = shininess;\nmaterial.specularStrength = specularStrength;",lights_phong_pars_fragment:"varying vec3 vViewPosition;\nstruct BlinnPhongMaterial {\n\tvec3 diffuseColor;\n\tvec3 specularColor;\n\tfloat specularShininess;\n\tfloat specularStrength;\n};\nvoid RE_Direct_BlinnPhong( const in IncidentLight directLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\n\tfloat dotNL = saturate( dot( geometryNormal, directLight.direction ) );\n\tvec3 irradiance = dotNL * directLight.color;\n\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n\treflectedLight.directSpecular += irradiance * BRDF_BlinnPhong( directLight.direction, geometryViewDir, geometryNormal, material.specularColor, material.specularShininess ) * material.specularStrength;\n}\nvoid RE_IndirectDiffuse_BlinnPhong( const in vec3 irradiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\n\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\n#define RE_Direct\t\t\t\tRE_Direct_BlinnPhong\n#define RE_IndirectDiffuse\t\tRE_IndirectDiffuse_BlinnPhong",lights_physical_fragment:"PhysicalMaterial material;\nmaterial.diffuseColor = diffuseColor.rgb * ( 1.0 - metalnessFactor );\nvec3 dxy = max( abs( dFdx( nonPerturbedNormal ) ), abs( dFdy( nonPerturbedNormal ) ) );\nfloat geometryRoughness = max( max( dxy.x, dxy.y ), dxy.z );\nmaterial.roughness = max( roughnessFactor, 0.0525 );material.roughness += geometryRoughness;\nmaterial.roughness = min( material.roughness, 1.0 );\n#ifdef IOR\n\tmaterial.ior = ior;\n\t#ifdef USE_SPECULAR\n\t\tfloat specularIntensityFactor = specularIntensity;\n\t\tvec3 specularColorFactor = specularColor;\n\t\t#ifdef USE_SPECULAR_COLORMAP\n\t\t\tspecularColorFactor *= texture2D( specularColorMap, vSpecularColorMapUv ).rgb;\n\t\t#endif\n\t\t#ifdef USE_SPECULAR_INTENSITYMAP\n\t\t\tspecularIntensityFactor *= texture2D( specularIntensityMap, vSpecularIntensityMapUv ).a;\n\t\t#endif\n\t\tmaterial.specularF90 = mix( specularIntensityFactor, 1.0, metalnessFactor );\n\t#else\n\t\tfloat specularIntensityFactor = 1.0;\n\t\tvec3 specularColorFactor = vec3( 1.0 );\n\t\tmaterial.specularF90 = 1.0;\n\t#endif\n\tmaterial.specularColor = mix( min( pow2( ( material.ior - 1.0 ) / ( material.ior + 1.0 ) ) * specularColorFactor, vec3( 1.0 ) ) * specularIntensityFactor, diffuseColor.rgb, metalnessFactor );\n#else\n\tmaterial.specularColor = mix( vec3( 0.04 ), diffuseColor.rgb, metalnessFactor );\n\tmaterial.specularF90 = 1.0;\n#endif\n#ifdef USE_CLEARCOAT\n\tmaterial.clearcoat = clearcoat;\n\tmaterial.clearcoatRoughness = clearcoatRoughness;\n\tmaterial.clearcoatF0 = vec3( 0.04 );\n\tmaterial.clearcoatF90 = 1.0;\n\t#ifdef USE_CLEARCOATMAP\n\t\tmaterial.clearcoat *= texture2D( clearcoatMap, vClearcoatMapUv ).x;\n\t#endif\n\t#ifdef USE_CLEARCOAT_ROUGHNESSMAP\n\t\tmaterial.clearcoatRoughness *= texture2D( clearcoatRoughnessMap, vClearcoatRoughnessMapUv ).y;\n\t#endif\n\tmaterial.clearcoat = saturate( material.clearcoat );\tmaterial.clearcoatRoughness = max( material.clearcoatRoughness, 0.0525 );\n\tmaterial.clearcoatRoughness += geometryRoughness;\n\tmaterial.clearcoatRoughness = min( material.clearcoatRoughness, 1.0 );\n#endif\n#ifdef USE_DISPERSION\n\tmaterial.dispersion = dispersion;\n#endif\n#ifdef USE_IRIDESCENCE\n\tmaterial.iridescence = iridescence;\n\tmaterial.iridescenceIOR = iridescenceIOR;\n\t#ifdef USE_IRIDESCENCEMAP\n\t\tmaterial.iridescence *= texture2D( iridescenceMap, vIridescenceMapUv ).r;\n\t#endif\n\t#ifdef USE_IRIDESCENCE_THICKNESSMAP\n\t\tmaterial.iridescenceThickness = (iridescenceThicknessMaximum - iridescenceThicknessMinimum) * texture2D( iridescenceThicknessMap, vIridescenceThicknessMapUv ).g + iridescenceThicknessMinimum;\n\t#else\n\t\tmaterial.iridescenceThickness = iridescenceThicknessMaximum;\n\t#endif\n#endif\n#ifdef USE_SHEEN\n\tmaterial.sheenColor = sheenColor;\n\t#ifdef USE_SHEEN_COLORMAP\n\t\tmaterial.sheenColor *= texture2D( sheenColorMap, vSheenColorMapUv ).rgb;\n\t#endif\n\tmaterial.sheenRoughness = clamp( sheenRoughness, 0.07, 1.0 );\n\t#ifdef USE_SHEEN_ROUGHNESSMAP\n\t\tmaterial.sheenRoughness *= texture2D( sheenRoughnessMap, vSheenRoughnessMapUv ).a;\n\t#endif\n#endif\n#ifdef USE_ANISOTROPY\n\t#ifdef USE_ANISOTROPYMAP\n\t\tmat2 anisotropyMat = mat2( anisotropyVector.x, anisotropyVector.y, - anisotropyVector.y, anisotropyVector.x );\n\t\tvec3 anisotropyPolar = texture2D( anisotropyMap, vAnisotropyMapUv ).rgb;\n\t\tvec2 anisotropyV = anisotropyMat * normalize( 2.0 * anisotropyPolar.rg - vec2( 1.0 ) ) * anisotropyPolar.b;\n\t#else\n\t\tvec2 anisotropyV = anisotropyVector;\n\t#endif\n\tmaterial.anisotropy = length( anisotropyV );\n\tif( material.anisotropy == 0.0 ) {\n\t\tanisotropyV = vec2( 1.0, 0.0 );\n\t} else {\n\t\tanisotropyV /= material.anisotropy;\n\t\tmaterial.anisotropy = saturate( material.anisotropy );\n\t}\n\tmaterial.alphaT = mix( pow2( material.roughness ), 1.0, pow2( material.anisotropy ) );\n\tmaterial.anisotropyT = tbn[ 0 ] * anisotropyV.x + tbn[ 1 ] * anisotropyV.y;\n\tmaterial.anisotropyB = tbn[ 1 ] * anisotropyV.x - tbn[ 0 ] * anisotropyV.y;\n#endif",lights_physical_pars_fragment:"struct PhysicalMaterial {\n\tvec3 diffuseColor;\n\tfloat roughness;\n\tvec3 specularColor;\n\tfloat specularF90;\n\tfloat dispersion;\n\t#ifdef USE_CLEARCOAT\n\t\tfloat clearcoat;\n\t\tfloat clearcoatRoughness;\n\t\tvec3 clearcoatF0;\n\t\tfloat clearcoatF90;\n\t#endif\n\t#ifdef USE_IRIDESCENCE\n\t\tfloat iridescence;\n\t\tfloat iridescenceIOR;\n\t\tfloat iridescenceThickness;\n\t\tvec3 iridescenceFresnel;\n\t\tvec3 iridescenceF0;\n\t#endif\n\t#ifdef USE_SHEEN\n\t\tvec3 sheenColor;\n\t\tfloat sheenRoughness;\n\t#endif\n\t#ifdef IOR\n\t\tfloat ior;\n\t#endif\n\t#ifdef USE_TRANSMISSION\n\t\tfloat transmission;\n\t\tfloat transmissionAlpha;\n\t\tfloat thickness;\n\t\tfloat attenuationDistance;\n\t\tvec3 attenuationColor;\n\t#endif\n\t#ifdef USE_ANISOTROPY\n\t\tfloat anisotropy;\n\t\tfloat alphaT;\n\t\tvec3 anisotropyT;\n\t\tvec3 anisotropyB;\n\t#endif\n};\nvec3 clearcoatSpecularDirect = vec3( 0.0 );\nvec3 clearcoatSpecularIndirect = vec3( 0.0 );\nvec3 sheenSpecularDirect = vec3( 0.0 );\nvec3 sheenSpecularIndirect = vec3(0.0 );\nvec3 Schlick_to_F0( const in vec3 f, const in float f90, const in float dotVH ) {\n    float x = clamp( 1.0 - dotVH, 0.0, 1.0 );\n    float x2 = x * x;\n    float x5 = clamp( x * x2 * x2, 0.0, 0.9999 );\n    return ( f - vec3( f90 ) * x5 ) / ( 1.0 - x5 );\n}\nfloat V_GGX_SmithCorrelated( const in float alpha, const in float dotNL, const in float dotNV ) {\n\tfloat a2 = pow2( alpha );\n\tfloat gv = dotNL * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNV ) );\n\tfloat gl = dotNV * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNL ) );\n\treturn 0.5 / max( gv + gl, EPSILON );\n}\nfloat D_GGX( const in float alpha, const in float dotNH ) {\n\tfloat a2 = pow2( alpha );\n\tfloat denom = pow2( dotNH ) * ( a2 - 1.0 ) + 1.0;\n\treturn RECIPROCAL_PI * a2 / pow2( denom );\n}\n#ifdef USE_ANISOTROPY\n\tfloat V_GGX_SmithCorrelated_Anisotropic( const in float alphaT, const in float alphaB, const in float dotTV, const in float dotBV, const in float dotTL, const in float dotBL, const in float dotNV, const in float dotNL ) {\n\t\tfloat gv = dotNL * length( vec3( alphaT * dotTV, alphaB * dotBV, dotNV ) );\n\t\tfloat gl = dotNV * length( vec3( alphaT * dotTL, alphaB * dotBL, dotNL ) );\n\t\tfloat v = 0.5 / ( gv + gl );\n\t\treturn saturate(v);\n\t}\n\tfloat D_GGX_Anisotropic( const in float alphaT, const in float alphaB, const in float dotNH, const in float dotTH, const in float dotBH ) {\n\t\tfloat a2 = alphaT * alphaB;\n\t\thighp vec3 v = vec3( alphaB * dotTH, alphaT * dotBH, a2 * dotNH );\n\t\thighp float v2 = dot( v, v );\n\t\tfloat w2 = a2 / v2;\n\t\treturn RECIPROCAL_PI * a2 * pow2 ( w2 );\n\t}\n#endif\n#ifdef USE_CLEARCOAT\n\tvec3 BRDF_GGX_Clearcoat( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in PhysicalMaterial material) {\n\t\tvec3 f0 = material.clearcoatF0;\n\t\tfloat f90 = material.clearcoatF90;\n\t\tfloat roughness = material.clearcoatRoughness;\n\t\tfloat alpha = pow2( roughness );\n\t\tvec3 halfDir = normalize( lightDir + viewDir );\n\t\tfloat dotNL = saturate( dot( normal, lightDir ) );\n\t\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\t\tfloat dotNH = saturate( dot( normal, halfDir ) );\n\t\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\n\t\tvec3 F = F_Schlick( f0, f90, dotVH );\n\t\tfloat V = V_GGX_SmithCorrelated( alpha, dotNL, dotNV );\n\t\tfloat D = D_GGX( alpha, dotNH );\n\t\treturn F * ( V * D );\n\t}\n#endif\nvec3 BRDF_GGX( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in PhysicalMaterial material ) {\n\tvec3 f0 = material.specularColor;\n\tfloat f90 = material.specularF90;\n\tfloat roughness = material.roughness;\n\tfloat alpha = pow2( roughness );\n\tvec3 halfDir = normalize( lightDir + viewDir );\n\tfloat dotNL = saturate( dot( normal, lightDir ) );\n\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\tfloat dotNH = saturate( dot( normal, halfDir ) );\n\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\n\tvec3 F = F_Schlick( f0, f90, dotVH );\n\t#ifdef USE_IRIDESCENCE\n\t\tF = mix( F, material.iridescenceFresnel, material.iridescence );\n\t#endif\n\t#ifdef USE_ANISOTROPY\n\t\tfloat dotTL = dot( material.anisotropyT, lightDir );\n\t\tfloat dotTV = dot( material.anisotropyT, viewDir );\n\t\tfloat dotTH = dot( material.anisotropyT, halfDir );\n\t\tfloat dotBL = dot( material.anisotropyB, lightDir );\n\t\tfloat dotBV = dot( material.anisotropyB, viewDir );\n\t\tfloat dotBH = dot( material.anisotropyB, halfDir );\n\t\tfloat V = V_GGX_SmithCorrelated_Anisotropic( material.alphaT, alpha, dotTV, dotBV, dotTL, dotBL, dotNV, dotNL );\n\t\tfloat D = D_GGX_Anisotropic( material.alphaT, alpha, dotNH, dotTH, dotBH );\n\t#else\n\t\tfloat V = V_GGX_SmithCorrelated( alpha, dotNL, dotNV );\n\t\tfloat D = D_GGX( alpha, dotNH );\n\t#endif\n\treturn F * ( V * D );\n}\nvec2 LTC_Uv( const in vec3 N, const in vec3 V, const in float roughness ) {\n\tconst float LUT_SIZE = 64.0;\n\tconst float LUT_SCALE = ( LUT_SIZE - 1.0 ) / LUT_SIZE;\n\tconst float LUT_BIAS = 0.5 / LUT_SIZE;\n\tfloat dotNV = saturate( dot( N, V ) );\n\tvec2 uv = vec2( roughness, sqrt( 1.0 - dotNV ) );\n\tuv = uv * LUT_SCALE + LUT_BIAS;\n\treturn uv;\n}\nfloat LTC_ClippedSphereFormFactor( const in vec3 f ) {\n\tfloat l = length( f );\n\treturn max( ( l * l + f.z ) / ( l + 1.0 ), 0.0 );\n}\nvec3 LTC_EdgeVectorFormFactor( const in vec3 v1, const in vec3 v2 ) {\n\tfloat x = dot( v1, v2 );\n\tfloat y = abs( x );\n\tfloat a = 0.8543985 + ( 0.4965155 + 0.0145206 * y ) * y;\n\tfloat b = 3.4175940 + ( 4.1616724 + y ) * y;\n\tfloat v = a / b;\n\tfloat theta_sintheta = ( x > 0.0 ) ? v : 0.5 * inversesqrt( max( 1.0 - x * x, 1e-7 ) ) - v;\n\treturn cross( v1, v2 ) * theta_sintheta;\n}\nvec3 LTC_Evaluate( const in vec3 N, const in vec3 V, const in vec3 P, const in mat3 mInv, const in vec3 rectCoords[ 4 ] ) {\n\tvec3 v1 = rectCoords[ 1 ] - rectCoords[ 0 ];\n\tvec3 v2 = rectCoords[ 3 ] - rectCoords[ 0 ];\n\tvec3 lightNormal = cross( v1, v2 );\n\tif( dot( lightNormal, P - rectCoords[ 0 ] ) < 0.0 ) return vec3( 0.0 );\n\tvec3 T1, T2;\n\tT1 = normalize( V - N * dot( V, N ) );\n\tT2 = - cross( N, T1 );\n\tmat3 mat = mInv * transposeMat3( mat3( T1, T2, N ) );\n\tvec3 coords[ 4 ];\n\tcoords[ 0 ] = mat * ( rectCoords[ 0 ] - P );\n\tcoords[ 1 ] = mat * ( rectCoords[ 1 ] - P );\n\tcoords[ 2 ] = mat * ( rectCoords[ 2 ] - P );\n\tcoords[ 3 ] = mat * ( rectCoords[ 3 ] - P );\n\tcoords[ 0 ] = normalize( coords[ 0 ] );\n\tcoords[ 1 ] = normalize( coords[ 1 ] );\n\tcoords[ 2 ] = normalize( coords[ 2 ] );\n\tcoords[ 3 ] = normalize( coords[ 3 ] );\n\tvec3 vectorFormFactor = vec3( 0.0 );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 0 ], coords[ 1 ] );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 1 ], coords[ 2 ] );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 2 ], coords[ 3 ] );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 3 ], coords[ 0 ] );\n\tfloat result = LTC_ClippedSphereFormFactor( vectorFormFactor );\n\treturn vec3( result );\n}\n#if defined( USE_SHEEN )\nfloat D_Charlie( float roughness, float dotNH ) {\n\tfloat alpha = pow2( roughness );\n\tfloat invAlpha = 1.0 / alpha;\n\tfloat cos2h = dotNH * dotNH;\n\tfloat sin2h = max( 1.0 - cos2h, 0.0078125 );\n\treturn ( 2.0 + invAlpha ) * pow( sin2h, invAlpha * 0.5 ) / ( 2.0 * PI );\n}\nfloat V_Neubelt( float dotNV, float dotNL ) {\n\treturn saturate( 1.0 / ( 4.0 * ( dotNL + dotNV - dotNL * dotNV ) ) );\n}\nvec3 BRDF_Sheen( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, vec3 sheenColor, const in float sheenRoughness ) {\n\tvec3 halfDir = normalize( lightDir + viewDir );\n\tfloat dotNL = saturate( dot( normal, lightDir ) );\n\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\tfloat dotNH = saturate( dot( normal, halfDir ) );\n\tfloat D = D_Charlie( sheenRoughness, dotNH );\n\tfloat V = V_Neubelt( dotNV, dotNL );\n\treturn sheenColor * ( D * V );\n}\n#endif\nfloat IBLSheenBRDF( const in vec3 normal, const in vec3 viewDir, const in float roughness ) {\n\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\tfloat r2 = roughness * roughness;\n\tfloat a = roughness < 0.25 ? -339.2 * r2 + 161.4 * roughness - 25.9 : -8.48 * r2 + 14.3 * roughness - 9.95;\n\tfloat b = roughness < 0.25 ? 44.0 * r2 - 23.7 * roughness + 3.26 : 1.97 * r2 - 3.27 * roughness + 0.72;\n\tfloat DG = exp( a * dotNV + b ) + ( roughness < 0.25 ? 0.0 : 0.1 * ( roughness - 0.25 ) );\n\treturn saturate( DG * RECIPROCAL_PI );\n}\nvec2 DFGApprox( const in vec3 normal, const in vec3 viewDir, const in float roughness ) {\n\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\tconst vec4 c0 = vec4( - 1, - 0.0275, - 0.572, 0.022 );\n\tconst vec4 c1 = vec4( 1, 0.0425, 1.04, - 0.04 );\n\tvec4 r = roughness * c0 + c1;\n\tfloat a004 = min( r.x * r.x, exp2( - 9.28 * dotNV ) ) * r.x + r.y;\n\tvec2 fab = vec2( - 1.04, 1.04 ) * a004 + r.zw;\n\treturn fab;\n}\nvec3 EnvironmentBRDF( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness ) {\n\tvec2 fab = DFGApprox( normal, viewDir, roughness );\n\treturn specularColor * fab.x + specularF90 * fab.y;\n}\n#ifdef USE_IRIDESCENCE\nvoid computeMultiscatteringIridescence( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float iridescence, const in vec3 iridescenceF0, const in float roughness, inout vec3 singleScatter, inout vec3 multiScatter ) {\n#else\nvoid computeMultiscattering( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness, inout vec3 singleScatter, inout vec3 multiScatter ) {\n#endif\n\tvec2 fab = DFGApprox( normal, viewDir, roughness );\n\t#ifdef USE_IRIDESCENCE\n\t\tvec3 Fr = mix( specularColor, iridescenceF0, iridescence );\n\t#else\n\t\tvec3 Fr = specularColor;\n\t#endif\n\tvec3 FssEss = Fr * fab.x + specularF90 * fab.y;\n\tfloat Ess = fab.x + fab.y;\n\tfloat Ems = 1.0 - Ess;\n\tvec3 Favg = Fr + ( 1.0 - Fr ) * 0.047619;\tvec3 Fms = FssEss * Favg / ( 1.0 - Ems * Favg );\n\tsingleScatter += FssEss;\n\tmultiScatter += Fms * Ems;\n}\n#if NUM_RECT_AREA_LIGHTS > 0\n\tvoid RE_Direct_RectArea_Physical( const in RectAreaLight rectAreaLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\n\t\tvec3 normal = geometryNormal;\n\t\tvec3 viewDir = geometryViewDir;\n\t\tvec3 position = geometryPosition;\n\t\tvec3 lightPos = rectAreaLight.position;\n\t\tvec3 halfWidth = rectAreaLight.halfWidth;\n\t\tvec3 halfHeight = rectAreaLight.halfHeight;\n\t\tvec3 lightColor = rectAreaLight.color;\n\t\tfloat roughness = material.roughness;\n\t\tvec3 rectCoords[ 4 ];\n\t\trectCoords[ 0 ] = lightPos + halfWidth - halfHeight;\t\trectCoords[ 1 ] = lightPos - halfWidth - halfHeight;\n\t\trectCoords[ 2 ] = lightPos - halfWidth + halfHeight;\n\t\trectCoords[ 3 ] = lightPos + halfWidth + halfHeight;\n\t\tvec2 uv = LTC_Uv( normal, viewDir, roughness );\n\t\tvec4 t1 = texture2D( ltc_1, uv );\n\t\tvec4 t2 = texture2D( ltc_2, uv );\n\t\tmat3 mInv = mat3(\n\t\t\tvec3( t1.x, 0, t1.y ),\n\t\t\tvec3(    0, 1,    0 ),\n\t\t\tvec3( t1.z, 0, t1.w )\n\t\t);\n\t\tvec3 fresnel = ( material.specularColor * t2.x + ( vec3( 1.0 ) - material.specularColor ) * t2.y );\n\t\treflectedLight.directSpecular += lightColor * fresnel * LTC_Evaluate( normal, viewDir, position, mInv, rectCoords );\n\t\treflectedLight.directDiffuse += lightColor * material.diffuseColor * LTC_Evaluate( normal, viewDir, position, mat3( 1.0 ), rectCoords );\n\t}\n#endif\nvoid RE_Direct_Physical( const in IncidentLight directLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\n\tfloat dotNL = saturate( dot( geometryNormal, directLight.direction ) );\n\tvec3 irradiance = dotNL * directLight.color;\n\t#ifdef USE_CLEARCOAT\n\t\tfloat dotNLcc = saturate( dot( geometryClearcoatNormal, directLight.direction ) );\n\t\tvec3 ccIrradiance = dotNLcc * directLight.color;\n\t\tclearcoatSpecularDirect += ccIrradiance * BRDF_GGX_Clearcoat( directLight.direction, geometryViewDir, geometryClearcoatNormal, material );\n\t#endif\n\t#ifdef USE_SHEEN\n\t\tsheenSpecularDirect += irradiance * BRDF_Sheen( directLight.direction, geometryViewDir, geometryNormal, material.sheenColor, material.sheenRoughness );\n\t#endif\n\treflectedLight.directSpecular += irradiance * BRDF_GGX( directLight.direction, geometryViewDir, geometryNormal, material );\n\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\nvoid RE_IndirectDiffuse_Physical( const in vec3 irradiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\n\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\nvoid RE_IndirectSpecular_Physical( const in vec3 radiance, const in vec3 irradiance, const in vec3 clearcoatRadiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in PhysicalMaterial material, inout ReflectedLight reflectedLight) {\n\t#ifdef USE_CLEARCOAT\n\t\tclearcoatSpecularIndirect += clearcoatRadiance * EnvironmentBRDF( geometryClearcoatNormal, geometryViewDir, material.clearcoatF0, material.clearcoatF90, material.clearcoatRoughness );\n\t#endif\n\t#ifdef USE_SHEEN\n\t\tsheenSpecularIndirect += irradiance * material.sheenColor * IBLSheenBRDF( geometryNormal, geometryViewDir, material.sheenRoughness );\n\t#endif\n\tvec3 singleScattering = vec3( 0.0 );\n\tvec3 multiScattering = vec3( 0.0 );\n\tvec3 cosineWeightedIrradiance = irradiance * RECIPROCAL_PI;\n\t#ifdef USE_IRIDESCENCE\n\t\tcomputeMultiscatteringIridescence( geometryNormal, geometryViewDir, material.specularColor, material.specularF90, material.iridescence, material.iridescenceFresnel, material.roughness, singleScattering, multiScattering );\n\t#else\n\t\tcomputeMultiscattering( geometryNormal, geometryViewDir, material.specularColor, material.specularF90, material.roughness, singleScattering, multiScattering );\n\t#endif\n\tvec3 totalScattering = singleScattering + multiScattering;\n\tvec3 diffuse = material.diffuseColor * ( 1.0 - max( max( totalScattering.r, totalScattering.g ), totalScattering.b ) );\n\treflectedLight.indirectSpecular += radiance * singleScattering;\n\treflectedLight.indirectSpecular += multiScattering * cosineWeightedIrradiance;\n\treflectedLight.indirectDiffuse += diffuse * cosineWeightedIrradiance;\n}\n#define RE_Direct\t\t\t\tRE_Direct_Physical\n#define RE_Direct_RectArea\t\tRE_Direct_RectArea_Physical\n#define RE_IndirectDiffuse\t\tRE_IndirectDiffuse_Physical\n#define RE_IndirectSpecular\t\tRE_IndirectSpecular_Physical\nfloat computeSpecularOcclusion( const in float dotNV, const in float ambientOcclusion, const in float roughness ) {\n\treturn saturate( pow( dotNV + ambientOcclusion, exp2( - 16.0 * roughness - 1.0 ) ) - 1.0 + ambientOcclusion );\n}",lights_fragment_begin:"\nvec3 geometryPosition = - vViewPosition;\nvec3 geometryNormal = normal;\nvec3 geometryViewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( vViewPosition );\nvec3 geometryClearcoatNormal = vec3( 0.0 );\n#ifdef USE_CLEARCOAT\n\tgeometryClearcoatNormal = clearcoatNormal;\n#endif\n#ifdef USE_IRIDESCENCE\n\tfloat dotNVi = saturate( dot( normal, geometryViewDir ) );\n\tif ( material.iridescenceThickness == 0.0 ) {\n\t\tmaterial.iridescence = 0.0;\n\t} else {\n\t\tmaterial.iridescence = saturate( material.iridescence );\n\t}\n\tif ( material.iridescence > 0.0 ) {\n\t\tmaterial.iridescenceFresnel = evalIridescence( 1.0, material.iridescenceIOR, dotNVi, material.iridescenceThickness, material.specularColor );\n\t\tmaterial.iridescenceF0 = Schlick_to_F0( material.iridescenceFresnel, 1.0, dotNVi );\n\t}\n#endif\nIncidentLight directLight;\n#if ( NUM_POINT_LIGHTS > 0 ) && defined( RE_Direct )\n\tPointLight pointLight;\n\t#if defined( USE_SHADOWMAP ) && NUM_POINT_LIGHT_SHADOWS > 0\n\tPointLightShadow pointLightShadow;\n\t#endif\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {\n\t\tpointLight = pointLights[ i ];\n\t\tgetPointLightInfo( pointLight, geometryPosition, directLight );\n\t\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_POINT_LIGHT_SHADOWS )\n\t\tpointLightShadow = pointLightShadows[ i ];\n\t\tdirectLight.color *= ( directLight.visible && receiveShadow ) ? getPointShadow( pointShadowMap[ i ], pointLightShadow.shadowMapSize, pointLightShadow.shadowIntensity, pointLightShadow.shadowBias, pointLightShadow.shadowRadius, vPointShadowCoord[ i ], pointLightShadow.shadowCameraNear, pointLightShadow.shadowCameraFar ) : 1.0;\n\t\t#endif\n\t\tRE_Direct( directLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if ( NUM_SPOT_LIGHTS > 0 ) && defined( RE_Direct )\n\tSpotLight spotLight;\n\tvec4 spotColor;\n\tvec3 spotLightCoord;\n\tbool inSpotLightMap;\n\t#if defined( USE_SHADOWMAP ) && NUM_SPOT_LIGHT_SHADOWS > 0\n\tSpotLightShadow spotLightShadow;\n\t#endif\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {\n\t\tspotLight = spotLights[ i ];\n\t\tgetSpotLightInfo( spotLight, geometryPosition, directLight );\n\t\t#if ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS_WITH_MAPS )\n\t\t#define SPOT_LIGHT_MAP_INDEX UNROLLED_LOOP_INDEX\n\t\t#elif ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )\n\t\t#define SPOT_LIGHT_MAP_INDEX NUM_SPOT_LIGHT_MAPS\n\t\t#else\n\t\t#define SPOT_LIGHT_MAP_INDEX ( UNROLLED_LOOP_INDEX - NUM_SPOT_LIGHT_SHADOWS + NUM_SPOT_LIGHT_SHADOWS_WITH_MAPS )\n\t\t#endif\n\t\t#if ( SPOT_LIGHT_MAP_INDEX < NUM_SPOT_LIGHT_MAPS )\n\t\t\tspotLightCoord = vSpotLightCoord[ i ].xyz / vSpotLightCoord[ i ].w;\n\t\t\tinSpotLightMap = all( lessThan( abs( spotLightCoord * 2. - 1. ), vec3( 1.0 ) ) );\n\t\t\tspotColor = texture2D( spotLightMap[ SPOT_LIGHT_MAP_INDEX ], spotLightCoord.xy );\n\t\t\tdirectLight.color = inSpotLightMap ? directLight.color * spotColor.rgb : directLight.color;\n\t\t#endif\n\t\t#undef SPOT_LIGHT_MAP_INDEX\n\t\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )\n\t\tspotLightShadow = spotLightShadows[ i ];\n\t\tdirectLight.color *= ( directLight.visible && receiveShadow ) ? getShadow( spotShadowMap[ i ], spotLightShadow.shadowMapSize, spotLightShadow.shadowIntensity, spotLightShadow.shadowBias, spotLightShadow.shadowRadius, vSpotLightCoord[ i ] ) : 1.0;\n\t\t#endif\n\t\tRE_Direct( directLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if ( NUM_DIR_LIGHTS > 0 ) && defined( RE_Direct )\n\tDirectionalLight directionalLight;\n\t#if defined( USE_SHADOWMAP ) && NUM_DIR_LIGHT_SHADOWS > 0\n\tDirectionalLightShadow directionalLightShadow;\n\t#endif\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {\n\t\tdirectionalLight = directionalLights[ i ];\n\t\tgetDirectionalLightInfo( directionalLight, directLight );\n\t\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_DIR_LIGHT_SHADOWS )\n\t\tdirectionalLightShadow = directionalLightShadows[ i ];\n\t\tdirectLight.color *= ( directLight.visible && receiveShadow ) ? getShadow( directionalShadowMap[ i ], directionalLightShadow.shadowMapSize, directionalLightShadow.shadowIntensity, directionalLightShadow.shadowBias, directionalLightShadow.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\n\t\t#endif\n\t\tRE_Direct( directLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if ( NUM_RECT_AREA_LIGHTS > 0 ) && defined( RE_Direct_RectArea )\n\tRectAreaLight rectAreaLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_RECT_AREA_LIGHTS; i ++ ) {\n\t\trectAreaLight = rectAreaLights[ i ];\n\t\tRE_Direct_RectArea( rectAreaLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if defined( RE_IndirectDiffuse )\n\tvec3 iblIrradiance = vec3( 0.0 );\n\tvec3 irradiance = getAmbientLightIrradiance( ambientLightColor );\n\t#if defined( USE_LIGHT_PROBES )\n\t\tirradiance += getLightProbeIrradiance( lightProbe, geometryNormal );\n\t#endif\n\t#if ( NUM_HEMI_LIGHTS > 0 )\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {\n\t\t\tirradiance += getHemisphereLightIrradiance( hemisphereLights[ i ], geometryNormal );\n\t\t}\n\t\t#pragma unroll_loop_end\n\t#endif\n#endif\n#if defined( RE_IndirectSpecular )\n\tvec3 radiance = vec3( 0.0 );\n\tvec3 clearcoatRadiance = vec3( 0.0 );\n#endif",lights_fragment_maps:"#if defined( RE_IndirectDiffuse )\n\t#ifdef USE_LIGHTMAP\n\t\tvec4 lightMapTexel = texture2D( lightMap, vLightMapUv );\n\t\tvec3 lightMapIrradiance = lightMapTexel.rgb * lightMapIntensity;\n\t\tirradiance += lightMapIrradiance;\n\t#endif\n\t#if defined( USE_ENVMAP ) && defined( STANDARD ) && defined( ENVMAP_TYPE_CUBE_UV )\n\t\tiblIrradiance += getIBLIrradiance( geometryNormal );\n\t#endif\n#endif\n#if defined( USE_ENVMAP ) && defined( RE_IndirectSpecular )\n\t#ifdef USE_ANISOTROPY\n\t\tradiance += getIBLAnisotropyRadiance( geometryViewDir, geometryNormal, material.roughness, material.anisotropyB, material.anisotropy );\n\t#else\n\t\tradiance += getIBLRadiance( geometryViewDir, geometryNormal, material.roughness );\n\t#endif\n\t#ifdef USE_CLEARCOAT\n\t\tclearcoatRadiance += getIBLRadiance( geometryViewDir, geometryClearcoatNormal, material.clearcoatRoughness );\n\t#endif\n#endif",lights_fragment_end:"#if defined( RE_IndirectDiffuse )\n\tRE_IndirectDiffuse( irradiance, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );\n#endif\n#if defined( RE_IndirectSpecular )\n\tRE_IndirectSpecular( radiance, iblIrradiance, clearcoatRadiance, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );\n#endif",logdepthbuf_fragment:"#if defined( USE_LOGARITHMIC_DEPTH_BUFFER )\n\tgl_FragDepth = vIsPerspective == 0.0 ? gl_FragCoord.z : log2( vFragDepth ) * logDepthBufFC * 0.5;\n#endif",logdepthbuf_pars_fragment:"#if defined( USE_LOGARITHMIC_DEPTH_BUFFER )\n\tuniform float logDepthBufFC;\n\tvarying float vFragDepth;\n\tvarying float vIsPerspective;\n#endif",logdepthbuf_pars_vertex:"#ifdef USE_LOGARITHMIC_DEPTH_BUFFER\n\tvarying float vFragDepth;\n\tvarying float vIsPerspective;\n#endif",logdepthbuf_vertex:"#ifdef USE_LOGARITHMIC_DEPTH_BUFFER\n\tvFragDepth = 1.0 + gl_Position.w;\n\tvIsPerspective = float( isPerspectiveMatrix( projectionMatrix ) );\n#endif",map_fragment:"#ifdef USE_MAP\n\tvec4 sampledDiffuseColor = texture2D( map, vMapUv );\n\t#ifdef DECODE_VIDEO_TEXTURE\n\t\tsampledDiffuseColor = sRGBTransferEOTF( sampledDiffuseColor );\n\t#endif\n\tdiffuseColor *= sampledDiffuseColor;\n#endif",map_pars_fragment:"#ifdef USE_MAP\n\tuniform sampler2D map;\n#endif",map_particle_fragment:"#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\n\t#if defined( USE_POINTS_UV )\n\t\tvec2 uv = vUv;\n\t#else\n\t\tvec2 uv = ( uvTransform * vec3( gl_PointCoord.x, 1.0 - gl_PointCoord.y, 1 ) ).xy;\n\t#endif\n#endif\n#ifdef USE_MAP\n\tdiffuseColor *= texture2D( map, uv );\n#endif\n#ifdef USE_ALPHAMAP\n\tdiffuseColor.a *= texture2D( alphaMap, uv ).g;\n#endif",map_particle_pars_fragment:"#if defined( USE_POINTS_UV )\n\tvarying vec2 vUv;\n#else\n\t#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\n\t\tuniform mat3 uvTransform;\n\t#endif\n#endif\n#ifdef USE_MAP\n\tuniform sampler2D map;\n#endif\n#ifdef USE_ALPHAMAP\n\tuniform sampler2D alphaMap;\n#endif",metalnessmap_fragment:"float metalnessFactor = metalness;\n#ifdef USE_METALNESSMAP\n\tvec4 texelMetalness = texture2D( metalnessMap, vMetalnessMapUv );\n\tmetalnessFactor *= texelMetalness.b;\n#endif",metalnessmap_pars_fragment:"#ifdef USE_METALNESSMAP\n\tuniform sampler2D metalnessMap;\n#endif",morphinstance_vertex:"#ifdef USE_INSTANCING_MORPH\n\tfloat morphTargetInfluences[ MORPHTARGETS_COUNT ];\n\tfloat morphTargetBaseInfluence = texelFetch( morphTexture, ivec2( 0, gl_InstanceID ), 0 ).r;\n\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\n\t\tmorphTargetInfluences[i] =  texelFetch( morphTexture, ivec2( i + 1, gl_InstanceID ), 0 ).r;\n\t}\n#endif",morphcolor_vertex:"#if defined( USE_MORPHCOLORS )\n\tvColor *= morphTargetBaseInfluence;\n\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\n\t\t#if defined( USE_COLOR_ALPHA )\n\t\t\tif ( morphTargetInfluences[ i ] != 0.0 ) vColor += getMorph( gl_VertexID, i, 2 ) * morphTargetInfluences[ i ];\n\t\t#elif defined( USE_COLOR )\n\t\t\tif ( morphTargetInfluences[ i ] != 0.0 ) vColor += getMorph( gl_VertexID, i, 2 ).rgb * morphTargetInfluences[ i ];\n\t\t#endif\n\t}\n#endif",morphnormal_vertex:"#ifdef USE_MORPHNORMALS\n\tobjectNormal *= morphTargetBaseInfluence;\n\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\n\t\tif ( morphTargetInfluences[ i ] != 0.0 ) objectNormal += getMorph( gl_VertexID, i, 1 ).xyz * morphTargetInfluences[ i ];\n\t}\n#endif",morphtarget_pars_vertex:"#ifdef USE_MORPHTARGETS\n\t#ifndef USE_INSTANCING_MORPH\n\t\tuniform float morphTargetBaseInfluence;\n\t\tuniform float morphTargetInfluences[ MORPHTARGETS_COUNT ];\n\t#endif\n\tuniform sampler2DArray morphTargetsTexture;\n\tuniform ivec2 morphTargetsTextureSize;\n\tvec4 getMorph( const in int vertexIndex, const in int morphTargetIndex, const in int offset ) {\n\t\tint texelIndex = vertexIndex * MORPHTARGETS_TEXTURE_STRIDE + offset;\n\t\tint y = texelIndex / morphTargetsTextureSize.x;\n\t\tint x = texelIndex - y * morphTargetsTextureSize.x;\n\t\tivec3 morphUV = ivec3( x, y, morphTargetIndex );\n\t\treturn texelFetch( morphTargetsTexture, morphUV, 0 );\n\t}\n#endif",morphtarget_vertex:"#ifdef USE_MORPHTARGETS\n\ttransformed *= morphTargetBaseInfluence;\n\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\n\t\tif ( morphTargetInfluences[ i ] != 0.0 ) transformed += getMorph( gl_VertexID, i, 0 ).xyz * morphTargetInfluences[ i ];\n\t}\n#endif",normal_fragment_begin:"float faceDirection = gl_FrontFacing ? 1.0 : - 1.0;\n#ifdef FLAT_SHADED\n\tvec3 fdx = dFdx( vViewPosition );\n\tvec3 fdy = dFdy( vViewPosition );\n\tvec3 normal = normalize( cross( fdx, fdy ) );\n#else\n\tvec3 normal = normalize( vNormal );\n\t#ifdef DOUBLE_SIDED\n\t\tnormal *= faceDirection;\n\t#endif\n#endif\n#if defined( USE_NORMALMAP_TANGENTSPACE ) || defined( USE_CLEARCOAT_NORMALMAP ) || defined( USE_ANISOTROPY )\n\t#ifdef USE_TANGENT\n\t\tmat3 tbn = mat3( normalize( vTangent ), normalize( vBitangent ), normal );\n\t#else\n\t\tmat3 tbn = getTangentFrame( - vViewPosition, normal,\n\t\t#if defined( USE_NORMALMAP )\n\t\t\tvNormalMapUv\n\t\t#elif defined( USE_CLEARCOAT_NORMALMAP )\n\t\t\tvClearcoatNormalMapUv\n\t\t#else\n\t\t\tvUv\n\t\t#endif\n\t\t);\n\t#endif\n\t#if defined( DOUBLE_SIDED ) && ! defined( FLAT_SHADED )\n\t\ttbn[0] *= faceDirection;\n\t\ttbn[1] *= faceDirection;\n\t#endif\n#endif\n#ifdef USE_CLEARCOAT_NORMALMAP\n\t#ifdef USE_TANGENT\n\t\tmat3 tbn2 = mat3( normalize( vTangent ), normalize( vBitangent ), normal );\n\t#else\n\t\tmat3 tbn2 = getTangentFrame( - vViewPosition, normal, vClearcoatNormalMapUv );\n\t#endif\n\t#if defined( DOUBLE_SIDED ) && ! defined( FLAT_SHADED )\n\t\ttbn2[0] *= faceDirection;\n\t\ttbn2[1] *= faceDirection;\n\t#endif\n#endif\nvec3 nonPerturbedNormal = normal;",normal_fragment_maps:"#ifdef USE_NORMALMAP_OBJECTSPACE\n\tnormal = texture2D( normalMap, vNormalMapUv ).xyz * 2.0 - 1.0;\n\t#ifdef FLIP_SIDED\n\t\tnormal = - normal;\n\t#endif\n\t#ifdef DOUBLE_SIDED\n\t\tnormal = normal * faceDirection;\n\t#endif\n\tnormal = normalize( normalMatrix * normal );\n#elif defined( USE_NORMALMAP_TANGENTSPACE )\n\tvec3 mapN = texture2D( normalMap, vNormalMapUv ).xyz * 2.0 - 1.0;\n\tmapN.xy *= normalScale;\n\tnormal = normalize( tbn * mapN );\n#elif defined( USE_BUMPMAP )\n\tnormal = perturbNormalArb( - vViewPosition, normal, dHdxy_fwd(), faceDirection );\n#endif",normal_pars_fragment:"#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n\t#ifdef USE_TANGENT\n\t\tvarying vec3 vTangent;\n\t\tvarying vec3 vBitangent;\n\t#endif\n#endif",normal_pars_vertex:"#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n\t#ifdef USE_TANGENT\n\t\tvarying vec3 vTangent;\n\t\tvarying vec3 vBitangent;\n\t#endif\n#endif",normal_vertex:"#ifndef FLAT_SHADED\n\tvNormal = normalize( transformedNormal );\n\t#ifdef USE_TANGENT\n\t\tvTangent = normalize( transformedTangent );\n\t\tvBitangent = normalize( cross( vNormal, vTangent ) * tangent.w );\n\t#endif\n#endif",normalmap_pars_fragment:"#ifdef USE_NORMALMAP\n\tuniform sampler2D normalMap;\n\tuniform vec2 normalScale;\n#endif\n#ifdef USE_NORMALMAP_OBJECTSPACE\n\tuniform mat3 normalMatrix;\n#endif\n#if ! defined ( USE_TANGENT ) && ( defined ( USE_NORMALMAP_TANGENTSPACE ) || defined ( USE_CLEARCOAT_NORMALMAP ) || defined( USE_ANISOTROPY ) )\n\tmat3 getTangentFrame( vec3 eye_pos, vec3 surf_norm, vec2 uv ) {\n\t\tvec3 q0 = dFdx( eye_pos.xyz );\n\t\tvec3 q1 = dFdy( eye_pos.xyz );\n\t\tvec2 st0 = dFdx( uv.st );\n\t\tvec2 st1 = dFdy( uv.st );\n\t\tvec3 N = surf_norm;\n\t\tvec3 q1perp = cross( q1, N );\n\t\tvec3 q0perp = cross( N, q0 );\n\t\tvec3 T = q1perp * st0.x + q0perp * st1.x;\n\t\tvec3 B = q1perp * st0.y + q0perp * st1.y;\n\t\tfloat det = max( dot( T, T ), dot( B, B ) );\n\t\tfloat scale = ( det == 0.0 ) ? 0.0 : inversesqrt( det );\n\t\treturn mat3( T * scale, B * scale, N );\n\t}\n#endif",clearcoat_normal_fragment_begin:"#ifdef USE_CLEARCOAT\n\tvec3 clearcoatNormal = nonPerturbedNormal;\n#endif",clearcoat_normal_fragment_maps:"#ifdef USE_CLEARCOAT_NORMALMAP\n\tvec3 clearcoatMapN = texture2D( clearcoatNormalMap, vClearcoatNormalMapUv ).xyz * 2.0 - 1.0;\n\tclearcoatMapN.xy *= clearcoatNormalScale;\n\tclearcoatNormal = normalize( tbn2 * clearcoatMapN );\n#endif",clearcoat_pars_fragment:"#ifdef USE_CLEARCOATMAP\n\tuniform sampler2D clearcoatMap;\n#endif\n#ifdef USE_CLEARCOAT_NORMALMAP\n\tuniform sampler2D clearcoatNormalMap;\n\tuniform vec2 clearcoatNormalScale;\n#endif\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\n\tuniform sampler2D clearcoatRoughnessMap;\n#endif",iridescence_pars_fragment:"#ifdef USE_IRIDESCENCEMAP\n\tuniform sampler2D iridescenceMap;\n#endif\n#ifdef USE_IRIDESCENCE_THICKNESSMAP\n\tuniform sampler2D iridescenceThicknessMap;\n#endif",opaque_fragment:"#ifdef OPAQUE\ndiffuseColor.a = 1.0;\n#endif\n#ifdef USE_TRANSMISSION\ndiffuseColor.a *= material.transmissionAlpha;\n#endif\ngl_FragColor = vec4( outgoingLight, diffuseColor.a );",packing:"vec3 packNormalToRGB( const in vec3 normal ) {\n\treturn normalize( normal ) * 0.5 + 0.5;\n}\nvec3 unpackRGBToNormal( const in vec3 rgb ) {\n\treturn 2.0 * rgb.xyz - 1.0;\n}\nconst float PackUpscale = 256. / 255.;const float UnpackDownscale = 255. / 256.;const float ShiftRight8 = 1. / 256.;\nconst float Inv255 = 1. / 255.;\nconst vec4 PackFactors = vec4( 1.0, 256.0, 256.0 * 256.0, 256.0 * 256.0 * 256.0 );\nconst vec2 UnpackFactors2 = vec2( UnpackDownscale, 1.0 / PackFactors.g );\nconst vec3 UnpackFactors3 = vec3( UnpackDownscale / PackFactors.rg, 1.0 / PackFactors.b );\nconst vec4 UnpackFactors4 = vec4( UnpackDownscale / PackFactors.rgb, 1.0 / PackFactors.a );\nvec4 packDepthToRGBA( const in float v ) {\n\tif( v <= 0.0 )\n\t\treturn vec4( 0., 0., 0., 0. );\n\tif( v >= 1.0 )\n\t\treturn vec4( 1., 1., 1., 1. );\n\tfloat vuf;\n\tfloat af = modf( v * PackFactors.a, vuf );\n\tfloat bf = modf( vuf * ShiftRight8, vuf );\n\tfloat gf = modf( vuf * ShiftRight8, vuf );\n\treturn vec4( vuf * Inv255, gf * PackUpscale, bf * PackUpscale, af );\n}\nvec3 packDepthToRGB( const in float v ) {\n\tif( v <= 0.0 )\n\t\treturn vec3( 0., 0., 0. );\n\tif( v >= 1.0 )\n\t\treturn vec3( 1., 1., 1. );\n\tfloat vuf;\n\tfloat bf = modf( v * PackFactors.b, vuf );\n\tfloat gf = modf( vuf * ShiftRight8, vuf );\n\treturn vec3( vuf * Inv255, gf * PackUpscale, bf );\n}\nvec2 packDepthToRG( const in float v ) {\n\tif( v <= 0.0 )\n\t\treturn vec2( 0., 0. );\n\tif( v >= 1.0 )\n\t\treturn vec2( 1., 1. );\n\tfloat vuf;\n\tfloat gf = modf( v * 256., vuf );\n\treturn vec2( vuf * Inv255, gf );\n}\nfloat unpackRGBAToDepth( const in vec4 v ) {\n\treturn dot( v, UnpackFactors4 );\n}\nfloat unpackRGBToDepth( const in vec3 v ) {\n\treturn dot( v, UnpackFactors3 );\n}\nfloat unpackRGToDepth( const in vec2 v ) {\n\treturn v.r * UnpackFactors2.r + v.g * UnpackFactors2.g;\n}\nvec4 pack2HalfToRGBA( const in vec2 v ) {\n\tvec4 r = vec4( v.x, fract( v.x * 255.0 ), v.y, fract( v.y * 255.0 ) );\n\treturn vec4( r.x - r.y / 255.0, r.y, r.z - r.w / 255.0, r.w );\n}\nvec2 unpackRGBATo2Half( const in vec4 v ) {\n\treturn vec2( v.x + ( v.y / 255.0 ), v.z + ( v.w / 255.0 ) );\n}\nfloat viewZToOrthographicDepth( const in float viewZ, const in float near, const in float far ) {\n\treturn ( viewZ + near ) / ( near - far );\n}\nfloat orthographicDepthToViewZ( const in float depth, const in float near, const in float far ) {\n\treturn depth * ( near - far ) - near;\n}\nfloat viewZToPerspectiveDepth( const in float viewZ, const in float near, const in float far ) {\n\treturn ( ( near + viewZ ) * far ) / ( ( far - near ) * viewZ );\n}\nfloat perspectiveDepthToViewZ( const in float depth, const in float near, const in float far ) {\n\treturn ( near * far ) / ( ( far - near ) * depth - far );\n}",premultiplied_alpha_fragment:"#ifdef PREMULTIPLIED_ALPHA\n\tgl_FragColor.rgb *= gl_FragColor.a;\n#endif",project_vertex:"vec4 mvPosition = vec4( transformed, 1.0 );\n#ifdef USE_BATCHING\n\tmvPosition = batchingMatrix * mvPosition;\n#endif\n#ifdef USE_INSTANCING\n\tmvPosition = instanceMatrix * mvPosition;\n#endif\nmvPosition = modelViewMatrix * mvPosition;\ngl_Position = projectionMatrix * mvPosition;",dithering_fragment:"#ifdef DITHERING\n\tgl_FragColor.rgb = dithering( gl_FragColor.rgb );\n#endif",dithering_pars_fragment:"#ifdef DITHERING\n\tvec3 dithering( vec3 color ) {\n\t\tfloat grid_position = rand( gl_FragCoord.xy );\n\t\tvec3 dither_shift_RGB = vec3( 0.25 / 255.0, -0.25 / 255.0, 0.25 / 255.0 );\n\t\tdither_shift_RGB = mix( 2.0 * dither_shift_RGB, -2.0 * dither_shift_RGB, grid_position );\n\t\treturn color + dither_shift_RGB;\n\t}\n#endif",roughnessmap_fragment:"float roughnessFactor = roughness;\n#ifdef USE_ROUGHNESSMAP\n\tvec4 texelRoughness = texture2D( roughnessMap, vRoughnessMapUv );\n\troughnessFactor *= texelRoughness.g;\n#endif",roughnessmap_pars_fragment:"#ifdef USE_ROUGHNESSMAP\n\tuniform sampler2D roughnessMap;\n#endif",shadowmap_pars_fragment:"#if NUM_SPOT_LIGHT_COORDS > 0\n\tvarying vec4 vSpotLightCoord[ NUM_SPOT_LIGHT_COORDS ];\n#endif\n#if NUM_SPOT_LIGHT_MAPS > 0\n\tuniform sampler2D spotLightMap[ NUM_SPOT_LIGHT_MAPS ];\n#endif\n#ifdef USE_SHADOWMAP\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\t\tuniform sampler2D directionalShadowMap[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tstruct DirectionalLightShadow {\n\t\t\tfloat shadowIntensity;\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_SPOT_LIGHT_SHADOWS > 0\n\t\tuniform sampler2D spotShadowMap[ NUM_SPOT_LIGHT_SHADOWS ];\n\t\tstruct SpotLightShadow {\n\t\t\tfloat shadowIntensity;\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\t\tuniform sampler2D pointShadowMap[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tstruct PointLightShadow {\n\t\t\tfloat shadowIntensity;\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t\tfloat shadowCameraNear;\n\t\t\tfloat shadowCameraFar;\n\t\t};\n\t\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\n\t#endif\n\tfloat texture2DCompare( sampler2D depths, vec2 uv, float compare ) {\n\t\tfloat depth = unpackRGBAToDepth( texture2D( depths, uv ) );\n\t\t#ifdef USE_REVERSED_DEPTH_BUFFER\n\t\t\treturn step( depth, compare );\n\t\t#else\n\t\t\treturn step( compare, depth );\n\t\t#endif\n\t}\n\tvec2 texture2DDistribution( sampler2D shadow, vec2 uv ) {\n\t\treturn unpackRGBATo2Half( texture2D( shadow, uv ) );\n\t}\n\tfloat VSMShadow( sampler2D shadow, vec2 uv, float compare ) {\n\t\tfloat occlusion = 1.0;\n\t\tvec2 distribution = texture2DDistribution( shadow, uv );\n\t\t#ifdef USE_REVERSED_DEPTH_BUFFER\n\t\t\tfloat hard_shadow = step( distribution.x, compare );\n\t\t#else\n\t\t\tfloat hard_shadow = step( compare, distribution.x );\n\t\t#endif\n\t\tif ( hard_shadow != 1.0 ) {\n\t\t\tfloat distance = compare - distribution.x;\n\t\t\tfloat variance = max( 0.00000, distribution.y * distribution.y );\n\t\t\tfloat softness_probability = variance / (variance + distance * distance );\t\t\tsoftness_probability = clamp( ( softness_probability - 0.3 ) / ( 0.95 - 0.3 ), 0.0, 1.0 );\t\t\tocclusion = clamp( max( hard_shadow, softness_probability ), 0.0, 1.0 );\n\t\t}\n\t\treturn occlusion;\n\t}\n\tfloat getShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowIntensity, float shadowBias, float shadowRadius, vec4 shadowCoord ) {\n\t\tfloat shadow = 1.0;\n\t\tshadowCoord.xyz /= shadowCoord.w;\n\t\tshadowCoord.z += shadowBias;\n\t\tbool inFrustum = shadowCoord.x >= 0.0 && shadowCoord.x <= 1.0 && shadowCoord.y >= 0.0 && shadowCoord.y <= 1.0;\n\t\tbool frustumTest = inFrustum && shadowCoord.z <= 1.0;\n\t\tif ( frustumTest ) {\n\t\t#if defined( SHADOWMAP_TYPE_PCF )\n\t\t\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\n\t\t\tfloat dx0 = - texelSize.x * shadowRadius;\n\t\t\tfloat dy0 = - texelSize.y * shadowRadius;\n\t\t\tfloat dx1 = + texelSize.x * shadowRadius;\n\t\t\tfloat dy1 = + texelSize.y * shadowRadius;\n\t\t\tfloat dx2 = dx0 / 2.0;\n\t\t\tfloat dy2 = dy0 / 2.0;\n\t\t\tfloat dx3 = dx1 / 2.0;\n\t\t\tfloat dy3 = dy1 / 2.0;\n\t\t\tshadow = (\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy2 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy2 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy2 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy3 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy3 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy3 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy1 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy1 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy1 ), shadowCoord.z )\n\t\t\t) * ( 1.0 / 17.0 );\n\t\t#elif defined( SHADOWMAP_TYPE_PCF_SOFT )\n\t\t\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\n\t\t\tfloat dx = texelSize.x;\n\t\t\tfloat dy = texelSize.y;\n\t\t\tvec2 uv = shadowCoord.xy;\n\t\t\tvec2 f = fract( uv * shadowMapSize + 0.5 );\n\t\t\tuv -= f * texelSize;\n\t\t\tshadow = (\n\t\t\t\ttexture2DCompare( shadowMap, uv, shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, uv + vec2( dx, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, uv + vec2( 0.0, dy ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, uv + texelSize, shadowCoord.z ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, 0.0 ), shadowCoord.z ),\n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 0.0 ), shadowCoord.z ),\n\t\t\t\t\t f.x ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, dy ), shadowCoord.z ),\n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, dy ), shadowCoord.z ),\n\t\t\t\t\t f.x ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( 0.0, -dy ), shadowCoord.z ),\n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( 0.0, 2.0 * dy ), shadowCoord.z ),\n\t\t\t\t\t f.y ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( dx, -dy ), shadowCoord.z ),\n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( dx, 2.0 * dy ), shadowCoord.z ),\n\t\t\t\t\t f.y ) +\n\t\t\t\tmix( mix( texture2DCompare( shadowMap, uv + vec2( -dx, -dy ), shadowCoord.z ),\n\t\t\t\t\t\t  texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, -dy ), shadowCoord.z ),\n\t\t\t\t\t\t  f.x ),\n\t\t\t\t\t mix( texture2DCompare( shadowMap, uv + vec2( -dx, 2.0 * dy ), shadowCoord.z ),\n\t\t\t\t\t\t  texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 2.0 * dy ), shadowCoord.z ),\n\t\t\t\t\t\t  f.x ),\n\t\t\t\t\t f.y )\n\t\t\t) * ( 1.0 / 9.0 );\n\t\t#elif defined( SHADOWMAP_TYPE_VSM )\n\t\t\tshadow = VSMShadow( shadowMap, shadowCoord.xy, shadowCoord.z );\n\t\t#else\n\t\t\tshadow = texture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z );\n\t\t#endif\n\t\t}\n\t\treturn mix( 1.0, shadow, shadowIntensity );\n\t}\n\tvec2 cubeToUV( vec3 v, float texelSizeY ) {\n\t\tvec3 absV = abs( v );\n\t\tfloat scaleToCube = 1.0 / max( absV.x, max( absV.y, absV.z ) );\n\t\tabsV *= scaleToCube;\n\t\tv *= scaleToCube * ( 1.0 - 2.0 * texelSizeY );\n\t\tvec2 planar = v.xy;\n\t\tfloat almostATexel = 1.5 * texelSizeY;\n\t\tfloat almostOne = 1.0 - almostATexel;\n\t\tif ( absV.z >= almostOne ) {\n\t\t\tif ( v.z > 0.0 )\n\t\t\t\tplanar.x = 4.0 - v.x;\n\t\t} else if ( absV.x >= almostOne ) {\n\t\t\tfloat signX = sign( v.x );\n\t\t\tplanar.x = v.z * signX + 2.0 * signX;\n\t\t} else if ( absV.y >= almostOne ) {\n\t\t\tfloat signY = sign( v.y );\n\t\t\tplanar.x = v.x + 2.0 * signY + 2.0;\n\t\t\tplanar.y = v.z * signY - 2.0;\n\t\t}\n\t\treturn vec2( 0.125, 0.25 ) * planar + vec2( 0.375, 0.75 );\n\t}\n\tfloat getPointShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowIntensity, float shadowBias, float shadowRadius, vec4 shadowCoord, float shadowCameraNear, float shadowCameraFar ) {\n\t\tfloat shadow = 1.0;\n\t\tvec3 lightToPosition = shadowCoord.xyz;\n\t\t\n\t\tfloat lightToPositionLength = length( lightToPosition );\n\t\tif ( lightToPositionLength - shadowCameraFar <= 0.0 && lightToPositionLength - shadowCameraNear >= 0.0 ) {\n\t\t\tfloat dp = ( lightToPositionLength - shadowCameraNear ) / ( shadowCameraFar - shadowCameraNear );\t\t\tdp += shadowBias;\n\t\t\tvec3 bd3D = normalize( lightToPosition );\n\t\t\tvec2 texelSize = vec2( 1.0 ) / ( shadowMapSize * vec2( 4.0, 2.0 ) );\n\t\t\t#if defined( SHADOWMAP_TYPE_PCF ) || defined( SHADOWMAP_TYPE_PCF_SOFT ) || defined( SHADOWMAP_TYPE_VSM )\n\t\t\t\tvec2 offset = vec2( - 1, 1 ) * shadowRadius * texelSize.y;\n\t\t\t\tshadow = (\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyy, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyy, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyx, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyx, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxy, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxy, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxx, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxx, texelSize.y ), dp )\n\t\t\t\t) * ( 1.0 / 9.0 );\n\t\t\t#else\n\t\t\t\tshadow = texture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp );\n\t\t\t#endif\n\t\t}\n\t\treturn mix( 1.0, shadow, shadowIntensity );\n\t}\n#endif",shadowmap_pars_vertex:"#if NUM_SPOT_LIGHT_COORDS > 0\n\tuniform mat4 spotLightMatrix[ NUM_SPOT_LIGHT_COORDS ];\n\tvarying vec4 vSpotLightCoord[ NUM_SPOT_LIGHT_COORDS ];\n#endif\n#ifdef USE_SHADOWMAP\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\t\tuniform mat4 directionalShadowMatrix[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tstruct DirectionalLightShadow {\n\t\t\tfloat shadowIntensity;\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_SPOT_LIGHT_SHADOWS > 0\n\t\tstruct SpotLightShadow {\n\t\t\tfloat shadowIntensity;\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\t\tuniform mat4 pointShadowMatrix[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tstruct PointLightShadow {\n\t\t\tfloat shadowIntensity;\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t\tfloat shadowCameraNear;\n\t\t\tfloat shadowCameraFar;\n\t\t};\n\t\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\n\t#endif\n#endif",shadowmap_vertex:"#if ( defined( USE_SHADOWMAP ) && ( NUM_DIR_LIGHT_SHADOWS > 0 || NUM_POINT_LIGHT_SHADOWS > 0 ) ) || ( NUM_SPOT_LIGHT_COORDS > 0 )\n\tvec3 shadowWorldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\n\tvec4 shadowWorldPosition;\n#endif\n#if defined( USE_SHADOWMAP )\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\n\t\t\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * directionalLightShadows[ i ].shadowNormalBias, 0 );\n\t\t\tvDirectionalShadowCoord[ i ] = directionalShadowMatrix[ i ] * shadowWorldPosition;\n\t\t}\n\t\t#pragma unroll_loop_end\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\n\t\t\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * pointLightShadows[ i ].shadowNormalBias, 0 );\n\t\t\tvPointShadowCoord[ i ] = pointShadowMatrix[ i ] * shadowWorldPosition;\n\t\t}\n\t\t#pragma unroll_loop_end\n\t#endif\n#endif\n#if NUM_SPOT_LIGHT_COORDS > 0\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_SPOT_LIGHT_COORDS; i ++ ) {\n\t\tshadowWorldPosition = worldPosition;\n\t\t#if ( defined( USE_SHADOWMAP ) && UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )\n\t\t\tshadowWorldPosition.xyz += shadowWorldNormal * spotLightShadows[ i ].shadowNormalBias;\n\t\t#endif\n\t\tvSpotLightCoord[ i ] = spotLightMatrix[ i ] * shadowWorldPosition;\n\t}\n\t#pragma unroll_loop_end\n#endif",shadowmask_pars_fragment:"float getShadowMask() {\n\tfloat shadow = 1.0;\n\t#ifdef USE_SHADOWMAP\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\tDirectionalLightShadow directionalLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\n\t\tdirectionalLight = directionalLightShadows[ i ];\n\t\tshadow *= receiveShadow ? getShadow( directionalShadowMap[ i ], directionalLight.shadowMapSize, directionalLight.shadowIntensity, directionalLight.shadowBias, directionalLight.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\n\t}\n\t#pragma unroll_loop_end\n\t#endif\n\t#if NUM_SPOT_LIGHT_SHADOWS > 0\n\tSpotLightShadow spotLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {\n\t\tspotLight = spotLightShadows[ i ];\n\t\tshadow *= receiveShadow ? getShadow( spotShadowMap[ i ], spotLight.shadowMapSize, spotLight.shadowIntensity, spotLight.shadowBias, spotLight.shadowRadius, vSpotLightCoord[ i ] ) : 1.0;\n\t}\n\t#pragma unroll_loop_end\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\tPointLightShadow pointLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\n\t\tpointLight = pointLightShadows[ i ];\n\t\tshadow *= receiveShadow ? getPointShadow( pointShadowMap[ i ], pointLight.shadowMapSize, pointLight.shadowIntensity, pointLight.shadowBias, pointLight.shadowRadius, vPointShadowCoord[ i ], pointLight.shadowCameraNear, pointLight.shadowCameraFar ) : 1.0;\n\t}\n\t#pragma unroll_loop_end\n\t#endif\n\t#endif\n\treturn shadow;\n}",skinbase_vertex:"#ifdef USE_SKINNING\n\tmat4 boneMatX = getBoneMatrix( skinIndex.x );\n\tmat4 boneMatY = getBoneMatrix( skinIndex.y );\n\tmat4 boneMatZ = getBoneMatrix( skinIndex.z );\n\tmat4 boneMatW = getBoneMatrix( skinIndex.w );\n#endif",skinning_pars_vertex:"#ifdef USE_SKINNING\n\tuniform mat4 bindMatrix;\n\tuniform mat4 bindMatrixInverse;\n\tuniform highp sampler2D boneTexture;\n\tmat4 getBoneMatrix( const in float i ) {\n\t\tint size = textureSize( boneTexture, 0 ).x;\n\t\tint j = int( i ) * 4;\n\t\tint x = j % size;\n\t\tint y = j / size;\n\t\tvec4 v1 = texelFetch( boneTexture, ivec2( x, y ), 0 );\n\t\tvec4 v2 = texelFetch( boneTexture, ivec2( x + 1, y ), 0 );\n\t\tvec4 v3 = texelFetch( boneTexture, ivec2( x + 2, y ), 0 );\n\t\tvec4 v4 = texelFetch( boneTexture, ivec2( x + 3, y ), 0 );\n\t\treturn mat4( v1, v2, v3, v4 );\n\t}\n#endif",skinning_vertex:"#ifdef USE_SKINNING\n\tvec4 skinVertex = bindMatrix * vec4( transformed, 1.0 );\n\tvec4 skinned = vec4( 0.0 );\n\tskinned += boneMatX * skinVertex * skinWeight.x;\n\tskinned += boneMatY * skinVertex * skinWeight.y;\n\tskinned += boneMatZ * skinVertex * skinWeight.z;\n\tskinned += boneMatW * skinVertex * skinWeight.w;\n\ttransformed = ( bindMatrixInverse * skinned ).xyz;\n#endif",skinnormal_vertex:"#ifdef USE_SKINNING\n\tmat4 skinMatrix = mat4( 0.0 );\n\tskinMatrix += skinWeight.x * boneMatX;\n\tskinMatrix += skinWeight.y * boneMatY;\n\tskinMatrix += skinWeight.z * boneMatZ;\n\tskinMatrix += skinWeight.w * boneMatW;\n\tskinMatrix = bindMatrixInverse * skinMatrix * bindMatrix;\n\tobjectNormal = vec4( skinMatrix * vec4( objectNormal, 0.0 ) ).xyz;\n\t#ifdef USE_TANGENT\n\t\tobjectTangent = vec4( skinMatrix * vec4( objectTangent, 0.0 ) ).xyz;\n\t#endif\n#endif",specularmap_fragment:"float specularStrength;\n#ifdef USE_SPECULARMAP\n\tvec4 texelSpecular = texture2D( specularMap, vSpecularMapUv );\n\tspecularStrength = texelSpecular.r;\n#else\n\tspecularStrength = 1.0;\n#endif",specularmap_pars_fragment:"#ifdef USE_SPECULARMAP\n\tuniform sampler2D specularMap;\n#endif",tonemapping_fragment:"#if defined( TONE_MAPPING )\n\tgl_FragColor.rgb = toneMapping( gl_FragColor.rgb );\n#endif",tonemapping_pars_fragment:"#ifndef saturate\n#define saturate( a ) clamp( a, 0.0, 1.0 )\n#endif\nuniform float toneMappingExposure;\nvec3 LinearToneMapping( vec3 color ) {\n\treturn saturate( toneMappingExposure * color );\n}\nvec3 ReinhardToneMapping( vec3 color ) {\n\tcolor *= toneMappingExposure;\n\treturn saturate( color / ( vec3( 1.0 ) + color ) );\n}\nvec3 CineonToneMapping( vec3 color ) {\n\tcolor *= toneMappingExposure;\n\tcolor = max( vec3( 0.0 ), color - 0.004 );\n\treturn pow( ( color * ( 6.2 * color + 0.5 ) ) / ( color * ( 6.2 * color + 1.7 ) + 0.06 ), vec3( 2.2 ) );\n}\nvec3 RRTAndODTFit( vec3 v ) {\n\tvec3 a = v * ( v + 0.0245786 ) - 0.000090537;\n\tvec3 b = v * ( 0.983729 * v + 0.4329510 ) + 0.238081;\n\treturn a / b;\n}\nvec3 ACESFilmicToneMapping( vec3 color ) {\n\tconst mat3 ACESInputMat = mat3(\n\t\tvec3( 0.59719, 0.07600, 0.02840 ),\t\tvec3( 0.35458, 0.90834, 0.13383 ),\n\t\tvec3( 0.04823, 0.01566, 0.83777 )\n\t);\n\tconst mat3 ACESOutputMat = mat3(\n\t\tvec3(  1.60475, -0.10208, -0.00327 ),\t\tvec3( -0.53108,  1.10813, -0.07276 ),\n\t\tvec3( -0.07367, -0.00605,  1.07602 )\n\t);\n\tcolor *= toneMappingExposure / 0.6;\n\tcolor = ACESInputMat * color;\n\tcolor = RRTAndODTFit( color );\n\tcolor = ACESOutputMat * color;\n\treturn saturate( color );\n}\nconst mat3 LINEAR_REC2020_TO_LINEAR_SRGB = mat3(\n\tvec3( 1.6605, - 0.1246, - 0.0182 ),\n\tvec3( - 0.5876, 1.1329, - 0.1006 ),\n\tvec3( - 0.0728, - 0.0083, 1.1187 )\n);\nconst mat3 LINEAR_SRGB_TO_LINEAR_REC2020 = mat3(\n\tvec3( 0.6274, 0.0691, 0.0164 ),\n\tvec3( 0.3293, 0.9195, 0.0880 ),\n\tvec3( 0.0433, 0.0113, 0.8956 )\n);\nvec3 agxDefaultContrastApprox( vec3 x ) {\n\tvec3 x2 = x * x;\n\tvec3 x4 = x2 * x2;\n\treturn + 15.5 * x4 * x2\n\t\t- 40.14 * x4 * x\n\t\t+ 31.96 * x4\n\t\t- 6.868 * x2 * x\n\t\t+ 0.4298 * x2\n\t\t+ 0.1191 * x\n\t\t- 0.00232;\n}\nvec3 AgXToneMapping( vec3 color ) {\n\tconst mat3 AgXInsetMatrix = mat3(\n\t\tvec3( 0.856627153315983, 0.137318972929847, 0.11189821299995 ),\n\t\tvec3( 0.0951212405381588, 0.761241990602591, 0.0767994186031903 ),\n\t\tvec3( 0.0482516061458583, 0.101439036467562, 0.811302368396859 )\n\t);\n\tconst mat3 AgXOutsetMatrix = mat3(\n\t\tvec3( 1.1271005818144368, - 0.1413297634984383, - 0.14132976349843826 ),\n\t\tvec3( - 0.11060664309660323, 1.157823702216272, - 0.11060664309660294 ),\n\t\tvec3( - 0.016493938717834573, - 0.016493938717834257, 1.2519364065950405 )\n\t);\n\tconst float AgxMinEv = - 12.47393;\tconst float AgxMaxEv = 4.026069;\n\tcolor *= toneMappingExposure;\n\tcolor = LINEAR_SRGB_TO_LINEAR_REC2020 * color;\n\tcolor = AgXInsetMatrix * color;\n\tcolor = max( color, 1e-10 );\tcolor = log2( color );\n\tcolor = ( color - AgxMinEv ) / ( AgxMaxEv - AgxMinEv );\n\tcolor = clamp( color, 0.0, 1.0 );\n\tcolor = agxDefaultContrastApprox( color );\n\tcolor = AgXOutsetMatrix * color;\n\tcolor = pow( max( vec3( 0.0 ), color ), vec3( 2.2 ) );\n\tcolor = LINEAR_REC2020_TO_LINEAR_SRGB * color;\n\tcolor = clamp( color, 0.0, 1.0 );\n\treturn color;\n}\nvec3 NeutralToneMapping( vec3 color ) {\n\tconst float StartCompression = 0.8 - 0.04;\n\tconst float Desaturation = 0.15;\n\tcolor *= toneMappingExposure;\n\tfloat x = min( color.r, min( color.g, color.b ) );\n\tfloat offset = x < 0.08 ? x - 6.25 * x * x : 0.04;\n\tcolor -= offset;\n\tfloat peak = max( color.r, max( color.g, color.b ) );\n\tif ( peak < StartCompression ) return color;\n\tfloat d = 1. - StartCompression;\n\tfloat newPeak = 1. - d * d / ( peak + d - StartCompression );\n\tcolor *= newPeak / peak;\n\tfloat g = 1. - 1. / ( Desaturation * ( peak - newPeak ) + 1. );\n\treturn mix( color, vec3( newPeak ), g );\n}\nvec3 CustomToneMapping( vec3 color ) { return color; }",transmission_fragment:"#ifdef USE_TRANSMISSION\n\tmaterial.transmission = transmission;\n\tmaterial.transmissionAlpha = 1.0;\n\tmaterial.thickness = thickness;\n\tmaterial.attenuationDistance = attenuationDistance;\n\tmaterial.attenuationColor = attenuationColor;\n\t#ifdef USE_TRANSMISSIONMAP\n\t\tmaterial.transmission *= texture2D( transmissionMap, vTransmissionMapUv ).r;\n\t#endif\n\t#ifdef USE_THICKNESSMAP\n\t\tmaterial.thickness *= texture2D( thicknessMap, vThicknessMapUv ).g;\n\t#endif\n\tvec3 pos = vWorldPosition;\n\tvec3 v = normalize( cameraPosition - pos );\n\tvec3 n = inverseTransformDirection( normal, viewMatrix );\n\tvec4 transmitted = getIBLVolumeRefraction(\n\t\tn, v, material.roughness, material.diffuseColor, material.specularColor, material.specularF90,\n\t\tpos, modelMatrix, viewMatrix, projectionMatrix, material.dispersion, material.ior, material.thickness,\n\t\tmaterial.attenuationColor, material.attenuationDistance );\n\tmaterial.transmissionAlpha = mix( material.transmissionAlpha, transmitted.a, material.transmission );\n\ttotalDiffuse = mix( totalDiffuse, transmitted.rgb, material.transmission );\n#endif",transmission_pars_fragment:"#ifdef USE_TRANSMISSION\n\tuniform float transmission;\n\tuniform float thickness;\n\tuniform float attenuationDistance;\n\tuniform vec3 attenuationColor;\n\t#ifdef USE_TRANSMISSIONMAP\n\t\tuniform sampler2D transmissionMap;\n\t#endif\n\t#ifdef USE_THICKNESSMAP\n\t\tuniform sampler2D thicknessMap;\n\t#endif\n\tuniform vec2 transmissionSamplerSize;\n\tuniform sampler2D transmissionSamplerMap;\n\tuniform mat4 modelMatrix;\n\tuniform mat4 projectionMatrix;\n\tvarying vec3 vWorldPosition;\n\tfloat w0( float a ) {\n\t\treturn ( 1.0 / 6.0 ) * ( a * ( a * ( - a + 3.0 ) - 3.0 ) + 1.0 );\n\t}\n\tfloat w1( float a ) {\n\t\treturn ( 1.0 / 6.0 ) * ( a *  a * ( 3.0 * a - 6.0 ) + 4.0 );\n\t}\n\tfloat w2( float a ){\n\t\treturn ( 1.0 / 6.0 ) * ( a * ( a * ( - 3.0 * a + 3.0 ) + 3.0 ) + 1.0 );\n\t}\n\tfloat w3( float a ) {\n\t\treturn ( 1.0 / 6.0 ) * ( a * a * a );\n\t}\n\tfloat g0( float a ) {\n\t\treturn w0( a ) + w1( a );\n\t}\n\tfloat g1( float a ) {\n\t\treturn w2( a ) + w3( a );\n\t}\n\tfloat h0( float a ) {\n\t\treturn - 1.0 + w1( a ) / ( w0( a ) + w1( a ) );\n\t}\n\tfloat h1( float a ) {\n\t\treturn 1.0 + w3( a ) / ( w2( a ) + w3( a ) );\n\t}\n\tvec4 bicubic( sampler2D tex, vec2 uv, vec4 texelSize, float lod ) {\n\t\tuv = uv * texelSize.zw + 0.5;\n\t\tvec2 iuv = floor( uv );\n\t\tvec2 fuv = fract( uv );\n\t\tfloat g0x = g0( fuv.x );\n\t\tfloat g1x = g1( fuv.x );\n\t\tfloat h0x = h0( fuv.x );\n\t\tfloat h1x = h1( fuv.x );\n\t\tfloat h0y = h0( fuv.y );\n\t\tfloat h1y = h1( fuv.y );\n\t\tvec2 p0 = ( vec2( iuv.x + h0x, iuv.y + h0y ) - 0.5 ) * texelSize.xy;\n\t\tvec2 p1 = ( vec2( iuv.x + h1x, iuv.y + h0y ) - 0.5 ) * texelSize.xy;\n\t\tvec2 p2 = ( vec2( iuv.x + h0x, iuv.y + h1y ) - 0.5 ) * texelSize.xy;\n\t\tvec2 p3 = ( vec2( iuv.x + h1x, iuv.y + h1y ) - 0.5 ) * texelSize.xy;\n\t\treturn g0( fuv.y ) * ( g0x * textureLod( tex, p0, lod ) + g1x * textureLod( tex, p1, lod ) ) +\n\t\t\tg1( fuv.y ) * ( g0x * textureLod( tex, p2, lod ) + g1x * textureLod( tex, p3, lod ) );\n\t}\n\tvec4 textureBicubic( sampler2D sampler, vec2 uv, float lod ) {\n\t\tvec2 fLodSize = vec2( textureSize( sampler, int( lod ) ) );\n\t\tvec2 cLodSize = vec2( textureSize( sampler, int( lod + 1.0 ) ) );\n\t\tvec2 fLodSizeInv = 1.0 / fLodSize;\n\t\tvec2 cLodSizeInv = 1.0 / cLodSize;\n\t\tvec4 fSample = bicubic( sampler, uv, vec4( fLodSizeInv, fLodSize ), floor( lod ) );\n\t\tvec4 cSample = bicubic( sampler, uv, vec4( cLodSizeInv, cLodSize ), ceil( lod ) );\n\t\treturn mix( fSample, cSample, fract( lod ) );\n\t}\n\tvec3 getVolumeTransmissionRay( const in vec3 n, const in vec3 v, const in float thickness, const in float ior, const in mat4 modelMatrix ) {\n\t\tvec3 refractionVector = refract( - v, normalize( n ), 1.0 / ior );\n\t\tvec3 modelScale;\n\t\tmodelScale.x = length( vec3( modelMatrix[ 0 ].xyz ) );\n\t\tmodelScale.y = length( vec3( modelMatrix[ 1 ].xyz ) );\n\t\tmodelScale.z = length( vec3( modelMatrix[ 2 ].xyz ) );\n\t\treturn normalize( refractionVector ) * thickness * modelScale;\n\t}\n\tfloat applyIorToRoughness( const in float roughness, const in float ior ) {\n\t\treturn roughness * clamp( ior * 2.0 - 2.0, 0.0, 1.0 );\n\t}\n\tvec4 getTransmissionSample( const in vec2 fragCoord, const in float roughness, const in float ior ) {\n\t\tfloat lod = log2( transmissionSamplerSize.x ) * applyIorToRoughness( roughness, ior );\n\t\treturn textureBicubic( transmissionSamplerMap, fragCoord.xy, lod );\n\t}\n\tvec3 volumeAttenuation( const in float transmissionDistance, const in vec3 attenuationColor, const in float attenuationDistance ) {\n\t\tif ( isinf( attenuationDistance ) ) {\n\t\t\treturn vec3( 1.0 );\n\t\t} else {\n\t\t\tvec3 attenuationCoefficient = -log( attenuationColor ) / attenuationDistance;\n\t\t\tvec3 transmittance = exp( - attenuationCoefficient * transmissionDistance );\t\t\treturn transmittance;\n\t\t}\n\t}\n\tvec4 getIBLVolumeRefraction( const in vec3 n, const in vec3 v, const in float roughness, const in vec3 diffuseColor,\n\t\tconst in vec3 specularColor, const in float specularF90, const in vec3 position, const in mat4 modelMatrix,\n\t\tconst in mat4 viewMatrix, const in mat4 projMatrix, const in float dispersion, const in float ior, const in float thickness,\n\t\tconst in vec3 attenuationColor, const in float attenuationDistance ) {\n\t\tvec4 transmittedLight;\n\t\tvec3 transmittance;\n\t\t#ifdef USE_DISPERSION\n\t\t\tfloat halfSpread = ( ior - 1.0 ) * 0.025 * dispersion;\n\t\t\tvec3 iors = vec3( ior - halfSpread, ior, ior + halfSpread );\n\t\t\tfor ( int i = 0; i < 3; i ++ ) {\n\t\t\t\tvec3 transmissionRay = getVolumeTransmissionRay( n, v, thickness, iors[ i ], modelMatrix );\n\t\t\t\tvec3 refractedRayExit = position + transmissionRay;\n\t\t\t\tvec4 ndcPos = projMatrix * viewMatrix * vec4( refractedRayExit, 1.0 );\n\t\t\t\tvec2 refractionCoords = ndcPos.xy / ndcPos.w;\n\t\t\t\trefractionCoords += 1.0;\n\t\t\t\trefractionCoords /= 2.0;\n\t\t\t\tvec4 transmissionSample = getTransmissionSample( refractionCoords, roughness, iors[ i ] );\n\t\t\t\ttransmittedLight[ i ] = transmissionSample[ i ];\n\t\t\t\ttransmittedLight.a += transmissionSample.a;\n\t\t\t\ttransmittance[ i ] = diffuseColor[ i ] * volumeAttenuation( length( transmissionRay ), attenuationColor, attenuationDistance )[ i ];\n\t\t\t}\n\t\t\ttransmittedLight.a /= 3.0;\n\t\t#else\n\t\t\tvec3 transmissionRay = getVolumeTransmissionRay( n, v, thickness, ior, modelMatrix );\n\t\t\tvec3 refractedRayExit = position + transmissionRay;\n\t\t\tvec4 ndcPos = projMatrix * viewMatrix * vec4( refractedRayExit, 1.0 );\n\t\t\tvec2 refractionCoords = ndcPos.xy / ndcPos.w;\n\t\t\trefractionCoords += 1.0;\n\t\t\trefractionCoords /= 2.0;\n\t\t\ttransmittedLight = getTransmissionSample( refractionCoords, roughness, ior );\n\t\t\ttransmittance = diffuseColor * volumeAttenuation( length( transmissionRay ), attenuationColor, attenuationDistance );\n\t\t#endif\n\t\tvec3 attenuatedColor = transmittance * transmittedLight.rgb;\n\t\tvec3 F = EnvironmentBRDF( n, v, specularColor, specularF90, roughness );\n\t\tfloat transmittanceFactor = ( transmittance.r + transmittance.g + transmittance.b ) / 3.0;\n\t\treturn vec4( ( 1.0 - F ) * attenuatedColor, 1.0 - ( 1.0 - transmittedLight.a ) * transmittanceFactor );\n\t}\n#endif",uv_pars_fragment:"#if defined( USE_UV ) || defined( USE_ANISOTROPY )\n\tvarying vec2 vUv;\n#endif\n#ifdef USE_MAP\n\tvarying vec2 vMapUv;\n#endif\n#ifdef USE_ALPHAMAP\n\tvarying vec2 vAlphaMapUv;\n#endif\n#ifdef USE_LIGHTMAP\n\tvarying vec2 vLightMapUv;\n#endif\n#ifdef USE_AOMAP\n\tvarying vec2 vAoMapUv;\n#endif\n#ifdef USE_BUMPMAP\n\tvarying vec2 vBumpMapUv;\n#endif\n#ifdef USE_NORMALMAP\n\tvarying vec2 vNormalMapUv;\n#endif\n#ifdef USE_EMISSIVEMAP\n\tvarying vec2 vEmissiveMapUv;\n#endif\n#ifdef USE_METALNESSMAP\n\tvarying vec2 vMetalnessMapUv;\n#endif\n#ifdef USE_ROUGHNESSMAP\n\tvarying vec2 vRoughnessMapUv;\n#endif\n#ifdef USE_ANISOTROPYMAP\n\tvarying vec2 vAnisotropyMapUv;\n#endif\n#ifdef USE_CLEARCOATMAP\n\tvarying vec2 vClearcoatMapUv;\n#endif\n#ifdef USE_CLEARCOAT_NORMALMAP\n\tvarying vec2 vClearcoatNormalMapUv;\n#endif\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\n\tvarying vec2 vClearcoatRoughnessMapUv;\n#endif\n#ifdef USE_IRIDESCENCEMAP\n\tvarying vec2 vIridescenceMapUv;\n#endif\n#ifdef USE_IRIDESCENCE_THICKNESSMAP\n\tvarying vec2 vIridescenceThicknessMapUv;\n#endif\n#ifdef USE_SHEEN_COLORMAP\n\tvarying vec2 vSheenColorMapUv;\n#endif\n#ifdef USE_SHEEN_ROUGHNESSMAP\n\tvarying vec2 vSheenRoughnessMapUv;\n#endif\n#ifdef USE_SPECULARMAP\n\tvarying vec2 vSpecularMapUv;\n#endif\n#ifdef USE_SPECULAR_COLORMAP\n\tvarying vec2 vSpecularColorMapUv;\n#endif\n#ifdef USE_SPECULAR_INTENSITYMAP\n\tvarying vec2 vSpecularIntensityMapUv;\n#endif\n#ifdef USE_TRANSMISSIONMAP\n\tuniform mat3 transmissionMapTransform;\n\tvarying vec2 vTransmissionMapUv;\n#endif\n#ifdef USE_THICKNESSMAP\n\tuniform mat3 thicknessMapTransform;\n\tvarying vec2 vThicknessMapUv;\n#endif",uv_pars_vertex:"#if defined( USE_UV ) || defined( USE_ANISOTROPY )\n\tvarying vec2 vUv;\n#endif\n#ifdef USE_MAP\n\tuniform mat3 mapTransform;\n\tvarying vec2 vMapUv;\n#endif\n#ifdef USE_ALPHAMAP\n\tuniform mat3 alphaMapTransform;\n\tvarying vec2 vAlphaMapUv;\n#endif\n#ifdef USE_LIGHTMAP\n\tuniform mat3 lightMapTransform;\n\tvarying vec2 vLightMapUv;\n#endif\n#ifdef USE_AOMAP\n\tuniform mat3 aoMapTransform;\n\tvarying vec2 vAoMapUv;\n#endif\n#ifdef USE_BUMPMAP\n\tuniform mat3 bumpMapTransform;\n\tvarying vec2 vBumpMapUv;\n#endif\n#ifdef USE_NORMALMAP\n\tuniform mat3 normalMapTransform;\n\tvarying vec2 vNormalMapUv;\n#endif\n#ifdef USE_DISPLACEMENTMAP\n\tuniform mat3 displacementMapTransform;\n\tvarying vec2 vDisplacementMapUv;\n#endif\n#ifdef USE_EMISSIVEMAP\n\tuniform mat3 emissiveMapTransform;\n\tvarying vec2 vEmissiveMapUv;\n#endif\n#ifdef USE_METALNESSMAP\n\tuniform mat3 metalnessMapTransform;\n\tvarying vec2 vMetalnessMapUv;\n#endif\n#ifdef USE_ROUGHNESSMAP\n\tuniform mat3 roughnessMapTransform;\n\tvarying vec2 vRoughnessMapUv;\n#endif\n#ifdef USE_ANISOTROPYMAP\n\tuniform mat3 anisotropyMapTransform;\n\tvarying vec2 vAnisotropyMapUv;\n#endif\n#ifdef USE_CLEARCOATMAP\n\tuniform mat3 clearcoatMapTransform;\n\tvarying vec2 vClearcoatMapUv;\n#endif\n#ifdef USE_CLEARCOAT_NORMALMAP\n\tuniform mat3 clearcoatNormalMapTransform;\n\tvarying vec2 vClearcoatNormalMapUv;\n#endif\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\n\tuniform mat3 clearcoatRoughnessMapTransform;\n\tvarying vec2 vClearcoatRoughnessMapUv;\n#endif\n#ifdef USE_SHEEN_COLORMAP\n\tuniform mat3 sheenColorMapTransform;\n\tvarying vec2 vSheenColorMapUv;\n#endif\n#ifdef USE_SHEEN_ROUGHNESSMAP\n\tuniform mat3 sheenRoughnessMapTransform;\n\tvarying vec2 vSheenRoughnessMapUv;\n#endif\n#ifdef USE_IRIDESCENCEMAP\n\tuniform mat3 iridescenceMapTransform;\n\tvarying vec2 vIridescenceMapUv;\n#endif\n#ifdef USE_IRIDESCENCE_THICKNESSMAP\n\tuniform mat3 iridescenceThicknessMapTransform;\n\tvarying vec2 vIridescenceThicknessMapUv;\n#endif\n#ifdef USE_SPECULARMAP\n\tuniform mat3 specularMapTransform;\n\tvarying vec2 vSpecularMapUv;\n#endif\n#ifdef USE_SPECULAR_COLORMAP\n\tuniform mat3 specularColorMapTransform;\n\tvarying vec2 vSpecularColorMapUv;\n#endif\n#ifdef USE_SPECULAR_INTENSITYMAP\n\tuniform mat3 specularIntensityMapTransform;\n\tvarying vec2 vSpecularIntensityMapUv;\n#endif\n#ifdef USE_TRANSMISSIONMAP\n\tuniform mat3 transmissionMapTransform;\n\tvarying vec2 vTransmissionMapUv;\n#endif\n#ifdef USE_THICKNESSMAP\n\tuniform mat3 thicknessMapTransform;\n\tvarying vec2 vThicknessMapUv;\n#endif",uv_vertex:"#if defined( USE_UV ) || defined( USE_ANISOTROPY )\n\tvUv = vec3( uv, 1 ).xy;\n#endif\n#ifdef USE_MAP\n\tvMapUv = ( mapTransform * vec3( MAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_ALPHAMAP\n\tvAlphaMapUv = ( alphaMapTransform * vec3( ALPHAMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_LIGHTMAP\n\tvLightMapUv = ( lightMapTransform * vec3( LIGHTMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_AOMAP\n\tvAoMapUv = ( aoMapTransform * vec3( AOMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_BUMPMAP\n\tvBumpMapUv = ( bumpMapTransform * vec3( BUMPMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_NORMALMAP\n\tvNormalMapUv = ( normalMapTransform * vec3( NORMALMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_DISPLACEMENTMAP\n\tvDisplacementMapUv = ( displacementMapTransform * vec3( DISPLACEMENTMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_EMISSIVEMAP\n\tvEmissiveMapUv = ( emissiveMapTransform * vec3( EMISSIVEMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_METALNESSMAP\n\tvMetalnessMapUv = ( metalnessMapTransform * vec3( METALNESSMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_ROUGHNESSMAP\n\tvRoughnessMapUv = ( roughnessMapTransform * vec3( ROUGHNESSMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_ANISOTROPYMAP\n\tvAnisotropyMapUv = ( anisotropyMapTransform * vec3( ANISOTROPYMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_CLEARCOATMAP\n\tvClearcoatMapUv = ( clearcoatMapTransform * vec3( CLEARCOATMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_CLEARCOAT_NORMALMAP\n\tvClearcoatNormalMapUv = ( clearcoatNormalMapTransform * vec3( CLEARCOAT_NORMALMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\n\tvClearcoatRoughnessMapUv = ( clearcoatRoughnessMapTransform * vec3( CLEARCOAT_ROUGHNESSMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_IRIDESCENCEMAP\n\tvIridescenceMapUv = ( iridescenceMapTransform * vec3( IRIDESCENCEMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_IRIDESCENCE_THICKNESSMAP\n\tvIridescenceThicknessMapUv = ( iridescenceThicknessMapTransform * vec3( IRIDESCENCE_THICKNESSMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_SHEEN_COLORMAP\n\tvSheenColorMapUv = ( sheenColorMapTransform * vec3( SHEEN_COLORMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_SHEEN_ROUGHNESSMAP\n\tvSheenRoughnessMapUv = ( sheenRoughnessMapTransform * vec3( SHEEN_ROUGHNESSMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_SPECULARMAP\n\tvSpecularMapUv = ( specularMapTransform * vec3( SPECULARMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_SPECULAR_COLORMAP\n\tvSpecularColorMapUv = ( specularColorMapTransform * vec3( SPECULAR_COLORMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_SPECULAR_INTENSITYMAP\n\tvSpecularIntensityMapUv = ( specularIntensityMapTransform * vec3( SPECULAR_INTENSITYMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_TRANSMISSIONMAP\n\tvTransmissionMapUv = ( transmissionMapTransform * vec3( TRANSMISSIONMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_THICKNESSMAP\n\tvThicknessMapUv = ( thicknessMapTransform * vec3( THICKNESSMAP_UV, 1 ) ).xy;\n#endif",worldpos_vertex:"#if defined( USE_ENVMAP ) || defined( DISTANCE ) || defined ( USE_SHADOWMAP ) || defined ( USE_TRANSMISSION ) || NUM_SPOT_LIGHT_COORDS > 0\n\tvec4 worldPosition = vec4( transformed, 1.0 );\n\t#ifdef USE_BATCHING\n\t\tworldPosition = batchingMatrix * worldPosition;\n\t#endif\n\t#ifdef USE_INSTANCING\n\t\tworldPosition = instanceMatrix * worldPosition;\n\t#endif\n\tworldPosition = modelMatrix * worldPosition;\n#endif",background_vert:"varying vec2 vUv;\nuniform mat3 uvTransform;\nvoid main() {\n\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\n\tgl_Position = vec4( position.xy, 1.0, 1.0 );\n}",background_frag:"uniform sampler2D t2D;\nuniform float backgroundIntensity;\nvarying vec2 vUv;\nvoid main() {\n\tvec4 texColor = texture2D( t2D, vUv );\n\t#ifdef DECODE_VIDEO_TEXTURE\n\t\ttexColor = vec4( mix( pow( texColor.rgb * 0.9478672986 + vec3( 0.0521327014 ), vec3( 2.4 ) ), texColor.rgb * 0.0773993808, vec3( lessThanEqual( texColor.rgb, vec3( 0.04045 ) ) ) ), texColor.w );\n\t#endif\n\ttexColor.rgb *= backgroundIntensity;\n\tgl_FragColor = texColor;\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n}",backgroundCube_vert:"varying vec3 vWorldDirection;\n#include <common>\nvoid main() {\n\tvWorldDirection = transformDirection( position, modelMatrix );\n\t#include <begin_vertex>\n\t#include <project_vertex>\n\tgl_Position.z = gl_Position.w;\n}",backgroundCube_frag:"#ifdef ENVMAP_TYPE_CUBE\n\tuniform samplerCube envMap;\n#elif defined( ENVMAP_TYPE_CUBE_UV )\n\tuniform sampler2D envMap;\n#endif\nuniform float flipEnvMap;\nuniform float backgroundBlurriness;\nuniform float backgroundIntensity;\nuniform mat3 backgroundRotation;\nvarying vec3 vWorldDirection;\n#include <cube_uv_reflection_fragment>\nvoid main() {\n\t#ifdef ENVMAP_TYPE_CUBE\n\t\tvec4 texColor = textureCube( envMap, backgroundRotation * vec3( flipEnvMap * vWorldDirection.x, vWorldDirection.yz ) );\n\t#elif defined( ENVMAP_TYPE_CUBE_UV )\n\t\tvec4 texColor = textureCubeUV( envMap, backgroundRotation * vWorldDirection, backgroundBlurriness );\n\t#else\n\t\tvec4 texColor = vec4( 0.0, 0.0, 0.0, 1.0 );\n\t#endif\n\ttexColor.rgb *= backgroundIntensity;\n\tgl_FragColor = texColor;\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n}",cube_vert:"varying vec3 vWorldDirection;\n#include <common>\nvoid main() {\n\tvWorldDirection = transformDirection( position, modelMatrix );\n\t#include <begin_vertex>\n\t#include <project_vertex>\n\tgl_Position.z = gl_Position.w;\n}",cube_frag:"uniform samplerCube tCube;\nuniform float tFlip;\nuniform float opacity;\nvarying vec3 vWorldDirection;\nvoid main() {\n\tvec4 texColor = textureCube( tCube, vec3( tFlip * vWorldDirection.x, vWorldDirection.yz ) );\n\tgl_FragColor = texColor;\n\tgl_FragColor.a *= opacity;\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n}",depth_vert:"#include <common>\n#include <batching_pars_vertex>\n#include <uv_pars_vertex>\n#include <displacementmap_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvarying vec2 vHighPrecisionZW;\nvoid main() {\n\t#include <uv_vertex>\n\t#include <batching_vertex>\n\t#include <skinbase_vertex>\n\t#include <morphinstance_vertex>\n\t#ifdef USE_DISPLACEMENTMAP\n\t\t#include <beginnormal_vertex>\n\t\t#include <morphnormal_vertex>\n\t\t#include <skinnormal_vertex>\n\t#endif\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <displacementmap_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\tvHighPrecisionZW = gl_Position.zw;\n}",depth_frag:"#if DEPTH_PACKING == 3200\n\tuniform float opacity;\n#endif\n#include <common>\n#include <packing>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <alphamap_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvarying vec2 vHighPrecisionZW;\nvoid main() {\n\tvec4 diffuseColor = vec4( 1.0 );\n\t#include <clipping_planes_fragment>\n\t#if DEPTH_PACKING == 3200\n\t\tdiffuseColor.a = opacity;\n\t#endif\n\t#include <map_fragment>\n\t#include <alphamap_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\t#include <logdepthbuf_fragment>\n\t#ifdef USE_REVERSED_DEPTH_BUFFER\n\t\tfloat fragCoordZ = vHighPrecisionZW[ 0 ] / vHighPrecisionZW[ 1 ];\n\t#else\n\t\tfloat fragCoordZ = 0.5 * vHighPrecisionZW[ 0 ] / vHighPrecisionZW[ 1 ] + 0.5;\n\t#endif\n\t#if DEPTH_PACKING == 3200\n\t\tgl_FragColor = vec4( vec3( 1.0 - fragCoordZ ), opacity );\n\t#elif DEPTH_PACKING == 3201\n\t\tgl_FragColor = packDepthToRGBA( fragCoordZ );\n\t#elif DEPTH_PACKING == 3202\n\t\tgl_FragColor = vec4( packDepthToRGB( fragCoordZ ), 1.0 );\n\t#elif DEPTH_PACKING == 3203\n\t\tgl_FragColor = vec4( packDepthToRG( fragCoordZ ), 0.0, 1.0 );\n\t#endif\n}",distanceRGBA_vert:"#define DISTANCE\nvarying vec3 vWorldPosition;\n#include <common>\n#include <batching_pars_vertex>\n#include <uv_pars_vertex>\n#include <displacementmap_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\t#include <uv_vertex>\n\t#include <batching_vertex>\n\t#include <skinbase_vertex>\n\t#include <morphinstance_vertex>\n\t#ifdef USE_DISPLACEMENTMAP\n\t\t#include <beginnormal_vertex>\n\t\t#include <morphnormal_vertex>\n\t\t#include <skinnormal_vertex>\n\t#endif\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <displacementmap_vertex>\n\t#include <project_vertex>\n\t#include <worldpos_vertex>\n\t#include <clipping_planes_vertex>\n\tvWorldPosition = worldPosition.xyz;\n}",distanceRGBA_frag:"#define DISTANCE\nuniform vec3 referencePosition;\nuniform float nearDistance;\nuniform float farDistance;\nvarying vec3 vWorldPosition;\n#include <common>\n#include <packing>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <alphamap_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main () {\n\tvec4 diffuseColor = vec4( 1.0 );\n\t#include <clipping_planes_fragment>\n\t#include <map_fragment>\n\t#include <alphamap_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\tfloat dist = length( vWorldPosition - referencePosition );\n\tdist = ( dist - nearDistance ) / ( farDistance - nearDistance );\n\tdist = saturate( dist );\n\tgl_FragColor = packDepthToRGBA( dist );\n}",equirect_vert:"varying vec3 vWorldDirection;\n#include <common>\nvoid main() {\n\tvWorldDirection = transformDirection( position, modelMatrix );\n\t#include <begin_vertex>\n\t#include <project_vertex>\n}",equirect_frag:"uniform sampler2D tEquirect;\nvarying vec3 vWorldDirection;\n#include <common>\nvoid main() {\n\tvec3 direction = normalize( vWorldDirection );\n\tvec2 sampleUV = equirectUv( direction );\n\tgl_FragColor = texture2D( tEquirect, sampleUV );\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n}",linedashed_vert:"uniform float scale;\nattribute float lineDistance;\nvarying float vLineDistance;\n#include <common>\n#include <uv_pars_vertex>\n#include <color_pars_vertex>\n#include <fog_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\tvLineDistance = scale * lineDistance;\n\t#include <uv_vertex>\n\t#include <color_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphcolor_vertex>\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\t#include <fog_vertex>\n}",linedashed_frag:"uniform vec3 diffuse;\nuniform float opacity;\nuniform float dashSize;\nuniform float totalSize;\nvarying float vLineDistance;\n#include <common>\n#include <color_pars_fragment>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <fog_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include <clipping_planes_fragment>\n\tif ( mod( vLineDistance, totalSize ) > dashSize ) {\n\t\tdiscard;\n\t}\n\tvec3 outgoingLight = vec3( 0.0 );\n\t#include <logdepthbuf_fragment>\n\t#include <map_fragment>\n\t#include <color_fragment>\n\toutgoingLight = diffuseColor.rgb;\n\t#include <opaque_fragment>\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n\t#include <premultiplied_alpha_fragment>\n}",meshbasic_vert:"#include <common>\n#include <batching_pars_vertex>\n#include <uv_pars_vertex>\n#include <envmap_pars_vertex>\n#include <color_pars_vertex>\n#include <fog_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\t#include <uv_vertex>\n\t#include <color_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphcolor_vertex>\n\t#include <batching_vertex>\n\t#if defined ( USE_ENVMAP ) || defined ( USE_SKINNING )\n\t\t#include <beginnormal_vertex>\n\t\t#include <morphnormal_vertex>\n\t\t#include <skinbase_vertex>\n\t\t#include <skinnormal_vertex>\n\t\t#include <defaultnormal_vertex>\n\t#endif\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\t#include <worldpos_vertex>\n\t#include <envmap_vertex>\n\t#include <fog_vertex>\n}",meshbasic_frag:"uniform vec3 diffuse;\nuniform float opacity;\n#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n#endif\n#include <common>\n#include <dithering_pars_fragment>\n#include <color_pars_fragment>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <alphamap_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <aomap_pars_fragment>\n#include <lightmap_pars_fragment>\n#include <envmap_common_pars_fragment>\n#include <envmap_pars_fragment>\n#include <fog_pars_fragment>\n#include <specularmap_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include <clipping_planes_fragment>\n\t#include <logdepthbuf_fragment>\n\t#include <map_fragment>\n\t#include <color_fragment>\n\t#include <alphamap_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\t#include <specularmap_fragment>\n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\t#ifdef USE_LIGHTMAP\n\t\tvec4 lightMapTexel = texture2D( lightMap, vLightMapUv );\n\t\treflectedLight.indirectDiffuse += lightMapTexel.rgb * lightMapIntensity * RECIPROCAL_PI;\n\t#else\n\t\treflectedLight.indirectDiffuse += vec3( 1.0 );\n\t#endif\n\t#include <aomap_fragment>\n\treflectedLight.indirectDiffuse *= diffuseColor.rgb;\n\tvec3 outgoingLight = reflectedLight.indirectDiffuse;\n\t#include <envmap_fragment>\n\t#include <opaque_fragment>\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n\t#include <premultiplied_alpha_fragment>\n\t#include <dithering_fragment>\n}",meshlambert_vert:"#define LAMBERT\nvarying vec3 vViewPosition;\n#include <common>\n#include <batching_pars_vertex>\n#include <uv_pars_vertex>\n#include <displacementmap_pars_vertex>\n#include <envmap_pars_vertex>\n#include <color_pars_vertex>\n#include <fog_pars_vertex>\n#include <normal_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <shadowmap_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\t#include <uv_vertex>\n\t#include <color_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphcolor_vertex>\n\t#include <batching_vertex>\n\t#include <beginnormal_vertex>\n\t#include <morphnormal_vertex>\n\t#include <skinbase_vertex>\n\t#include <skinnormal_vertex>\n\t#include <defaultnormal_vertex>\n\t#include <normal_vertex>\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <displacementmap_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\tvViewPosition = - mvPosition.xyz;\n\t#include <worldpos_vertex>\n\t#include <envmap_vertex>\n\t#include <shadowmap_vertex>\n\t#include <fog_vertex>\n}",meshlambert_frag:"#define LAMBERT\nuniform vec3 diffuse;\nuniform vec3 emissive;\nuniform float opacity;\n#include <common>\n#include <packing>\n#include <dithering_pars_fragment>\n#include <color_pars_fragment>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <alphamap_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <aomap_pars_fragment>\n#include <lightmap_pars_fragment>\n#include <emissivemap_pars_fragment>\n#include <envmap_common_pars_fragment>\n#include <envmap_pars_fragment>\n#include <fog_pars_fragment>\n#include <bsdfs>\n#include <lights_pars_begin>\n#include <normal_pars_fragment>\n#include <lights_lambert_pars_fragment>\n#include <shadowmap_pars_fragment>\n#include <bumpmap_pars_fragment>\n#include <normalmap_pars_fragment>\n#include <specularmap_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include <clipping_planes_fragment>\n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\tvec3 totalEmissiveRadiance = emissive;\n\t#include <logdepthbuf_fragment>\n\t#include <map_fragment>\n\t#include <color_fragment>\n\t#include <alphamap_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\t#include <specularmap_fragment>\n\t#include <normal_fragment_begin>\n\t#include <normal_fragment_maps>\n\t#include <emissivemap_fragment>\n\t#include <lights_lambert_fragment>\n\t#include <lights_fragment_begin>\n\t#include <lights_fragment_maps>\n\t#include <lights_fragment_end>\n\t#include <aomap_fragment>\n\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\n\t#include <envmap_fragment>\n\t#include <opaque_fragment>\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n\t#include <premultiplied_alpha_fragment>\n\t#include <dithering_fragment>\n}",meshmatcap_vert:"#define MATCAP\nvarying vec3 vViewPosition;\n#include <common>\n#include <batching_pars_vertex>\n#include <uv_pars_vertex>\n#include <color_pars_vertex>\n#include <displacementmap_pars_vertex>\n#include <fog_pars_vertex>\n#include <normal_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\t#include <uv_vertex>\n\t#include <color_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphcolor_vertex>\n\t#include <batching_vertex>\n\t#include <beginnormal_vertex>\n\t#include <morphnormal_vertex>\n\t#include <skinbase_vertex>\n\t#include <skinnormal_vertex>\n\t#include <defaultnormal_vertex>\n\t#include <normal_vertex>\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <displacementmap_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\t#include <fog_vertex>\n\tvViewPosition = - mvPosition.xyz;\n}",meshmatcap_frag:"#define MATCAP\nuniform vec3 diffuse;\nuniform float opacity;\nuniform sampler2D matcap;\nvarying vec3 vViewPosition;\n#include <common>\n#include <dithering_pars_fragment>\n#include <color_pars_fragment>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <alphamap_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <fog_pars_fragment>\n#include <normal_pars_fragment>\n#include <bumpmap_pars_fragment>\n#include <normalmap_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include <clipping_planes_fragment>\n\t#include <logdepthbuf_fragment>\n\t#include <map_fragment>\n\t#include <color_fragment>\n\t#include <alphamap_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\t#include <normal_fragment_begin>\n\t#include <normal_fragment_maps>\n\tvec3 viewDir = normalize( vViewPosition );\n\tvec3 x = normalize( vec3( viewDir.z, 0.0, - viewDir.x ) );\n\tvec3 y = cross( viewDir, x );\n\tvec2 uv = vec2( dot( x, normal ), dot( y, normal ) ) * 0.495 + 0.5;\n\t#ifdef USE_MATCAP\n\t\tvec4 matcapColor = texture2D( matcap, uv );\n\t#else\n\t\tvec4 matcapColor = vec4( vec3( mix( 0.2, 0.8, uv.y ) ), 1.0 );\n\t#endif\n\tvec3 outgoingLight = diffuseColor.rgb * matcapColor.rgb;\n\t#include <opaque_fragment>\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n\t#include <premultiplied_alpha_fragment>\n\t#include <dithering_fragment>\n}",meshnormal_vert:"#define NORMAL\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( USE_NORMALMAP_TANGENTSPACE )\n\tvarying vec3 vViewPosition;\n#endif\n#include <common>\n#include <batching_pars_vertex>\n#include <uv_pars_vertex>\n#include <displacementmap_pars_vertex>\n#include <normal_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\t#include <uv_vertex>\n\t#include <batching_vertex>\n\t#include <beginnormal_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphnormal_vertex>\n\t#include <skinbase_vertex>\n\t#include <skinnormal_vertex>\n\t#include <defaultnormal_vertex>\n\t#include <normal_vertex>\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <displacementmap_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( USE_NORMALMAP_TANGENTSPACE )\n\tvViewPosition = - mvPosition.xyz;\n#endif\n}",meshnormal_frag:"#define NORMAL\nuniform float opacity;\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( USE_NORMALMAP_TANGENTSPACE )\n\tvarying vec3 vViewPosition;\n#endif\n#include <packing>\n#include <uv_pars_fragment>\n#include <normal_pars_fragment>\n#include <bumpmap_pars_fragment>\n#include <normalmap_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( 0.0, 0.0, 0.0, opacity );\n\t#include <clipping_planes_fragment>\n\t#include <logdepthbuf_fragment>\n\t#include <normal_fragment_begin>\n\t#include <normal_fragment_maps>\n\tgl_FragColor = vec4( packNormalToRGB( normal ), diffuseColor.a );\n\t#ifdef OPAQUE\n\t\tgl_FragColor.a = 1.0;\n\t#endif\n}",meshphong_vert:"#define PHONG\nvarying vec3 vViewPosition;\n#include <common>\n#include <batching_pars_vertex>\n#include <uv_pars_vertex>\n#include <displacementmap_pars_vertex>\n#include <envmap_pars_vertex>\n#include <color_pars_vertex>\n#include <fog_pars_vertex>\n#include <normal_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <shadowmap_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\t#include <uv_vertex>\n\t#include <color_vertex>\n\t#include <morphcolor_vertex>\n\t#include <batching_vertex>\n\t#include <beginnormal_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphnormal_vertex>\n\t#include <skinbase_vertex>\n\t#include <skinnormal_vertex>\n\t#include <defaultnormal_vertex>\n\t#include <normal_vertex>\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <displacementmap_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\tvViewPosition = - mvPosition.xyz;\n\t#include <worldpos_vertex>\n\t#include <envmap_vertex>\n\t#include <shadowmap_vertex>\n\t#include <fog_vertex>\n}",meshphong_frag:"#define PHONG\nuniform vec3 diffuse;\nuniform vec3 emissive;\nuniform vec3 specular;\nuniform float shininess;\nuniform float opacity;\n#include <common>\n#include <packing>\n#include <dithering_pars_fragment>\n#include <color_pars_fragment>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <alphamap_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <aomap_pars_fragment>\n#include <lightmap_pars_fragment>\n#include <emissivemap_pars_fragment>\n#include <envmap_common_pars_fragment>\n#include <envmap_pars_fragment>\n#include <fog_pars_fragment>\n#include <bsdfs>\n#include <lights_pars_begin>\n#include <normal_pars_fragment>\n#include <lights_phong_pars_fragment>\n#include <shadowmap_pars_fragment>\n#include <bumpmap_pars_fragment>\n#include <normalmap_pars_fragment>\n#include <specularmap_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include <clipping_planes_fragment>\n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\tvec3 totalEmissiveRadiance = emissive;\n\t#include <logdepthbuf_fragment>\n\t#include <map_fragment>\n\t#include <color_fragment>\n\t#include <alphamap_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\t#include <specularmap_fragment>\n\t#include <normal_fragment_begin>\n\t#include <normal_fragment_maps>\n\t#include <emissivemap_fragment>\n\t#include <lights_phong_fragment>\n\t#include <lights_fragment_begin>\n\t#include <lights_fragment_maps>\n\t#include <lights_fragment_end>\n\t#include <aomap_fragment>\n\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + reflectedLight.directSpecular + reflectedLight.indirectSpecular + totalEmissiveRadiance;\n\t#include <envmap_fragment>\n\t#include <opaque_fragment>\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n\t#include <premultiplied_alpha_fragment>\n\t#include <dithering_fragment>\n}",meshphysical_vert:"#define STANDARD\nvarying vec3 vViewPosition;\n#ifdef USE_TRANSMISSION\n\tvarying vec3 vWorldPosition;\n#endif\n#include <common>\n#include <batching_pars_vertex>\n#include <uv_pars_vertex>\n#include <displacementmap_pars_vertex>\n#include <color_pars_vertex>\n#include <fog_pars_vertex>\n#include <normal_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <shadowmap_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\t#include <uv_vertex>\n\t#include <color_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphcolor_vertex>\n\t#include <batching_vertex>\n\t#include <beginnormal_vertex>\n\t#include <morphnormal_vertex>\n\t#include <skinbase_vertex>\n\t#include <skinnormal_vertex>\n\t#include <defaultnormal_vertex>\n\t#include <normal_vertex>\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <displacementmap_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\tvViewPosition = - mvPosition.xyz;\n\t#include <worldpos_vertex>\n\t#include <shadowmap_vertex>\n\t#include <fog_vertex>\n#ifdef USE_TRANSMISSION\n\tvWorldPosition = worldPosition.xyz;\n#endif\n}",meshphysical_frag:"#define STANDARD\n#ifdef PHYSICAL\n\t#define IOR\n\t#define USE_SPECULAR\n#endif\nuniform vec3 diffuse;\nuniform vec3 emissive;\nuniform float roughness;\nuniform float metalness;\nuniform float opacity;\n#ifdef IOR\n\tuniform float ior;\n#endif\n#ifdef USE_SPECULAR\n\tuniform float specularIntensity;\n\tuniform vec3 specularColor;\n\t#ifdef USE_SPECULAR_COLORMAP\n\t\tuniform sampler2D specularColorMap;\n\t#endif\n\t#ifdef USE_SPECULAR_INTENSITYMAP\n\t\tuniform sampler2D specularIntensityMap;\n\t#endif\n#endif\n#ifdef USE_CLEARCOAT\n\tuniform float clearcoat;\n\tuniform float clearcoatRoughness;\n#endif\n#ifdef USE_DISPERSION\n\tuniform float dispersion;\n#endif\n#ifdef USE_IRIDESCENCE\n\tuniform float iridescence;\n\tuniform float iridescenceIOR;\n\tuniform float iridescenceThicknessMinimum;\n\tuniform float iridescenceThicknessMaximum;\n#endif\n#ifdef USE_SHEEN\n\tuniform vec3 sheenColor;\n\tuniform float sheenRoughness;\n\t#ifdef USE_SHEEN_COLORMAP\n\t\tuniform sampler2D sheenColorMap;\n\t#endif\n\t#ifdef USE_SHEEN_ROUGHNESSMAP\n\t\tuniform sampler2D sheenRoughnessMap;\n\t#endif\n#endif\n#ifdef USE_ANISOTROPY\n\tuniform vec2 anisotropyVector;\n\t#ifdef USE_ANISOTROPYMAP\n\t\tuniform sampler2D anisotropyMap;\n\t#endif\n#endif\nvarying vec3 vViewPosition;\n#include <common>\n#include <packing>\n#include <dithering_pars_fragment>\n#include <color_pars_fragment>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <alphamap_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <aomap_pars_fragment>\n#include <lightmap_pars_fragment>\n#include <emissivemap_pars_fragment>\n#include <iridescence_fragment>\n#include <cube_uv_reflection_fragment>\n#include <envmap_common_pars_fragment>\n#include <envmap_physical_pars_fragment>\n#include <fog_pars_fragment>\n#include <lights_pars_begin>\n#include <normal_pars_fragment>\n#include <lights_physical_pars_fragment>\n#include <transmission_pars_fragment>\n#include <shadowmap_pars_fragment>\n#include <bumpmap_pars_fragment>\n#include <normalmap_pars_fragment>\n#include <clearcoat_pars_fragment>\n#include <iridescence_pars_fragment>\n#include <roughnessmap_pars_fragment>\n#include <metalnessmap_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include <clipping_planes_fragment>\n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\tvec3 totalEmissiveRadiance = emissive;\n\t#include <logdepthbuf_fragment>\n\t#include <map_fragment>\n\t#include <color_fragment>\n\t#include <alphamap_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\t#include <roughnessmap_fragment>\n\t#include <metalnessmap_fragment>\n\t#include <normal_fragment_begin>\n\t#include <normal_fragment_maps>\n\t#include <clearcoat_normal_fragment_begin>\n\t#include <clearcoat_normal_fragment_maps>\n\t#include <emissivemap_fragment>\n\t#include <lights_physical_fragment>\n\t#include <lights_fragment_begin>\n\t#include <lights_fragment_maps>\n\t#include <lights_fragment_end>\n\t#include <aomap_fragment>\n\tvec3 totalDiffuse = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse;\n\tvec3 totalSpecular = reflectedLight.directSpecular + reflectedLight.indirectSpecular;\n\t#include <transmission_fragment>\n\tvec3 outgoingLight = totalDiffuse + totalSpecular + totalEmissiveRadiance;\n\t#ifdef USE_SHEEN\n\t\tfloat sheenEnergyComp = 1.0 - 0.157 * max3( material.sheenColor );\n\t\toutgoingLight = outgoingLight * sheenEnergyComp + sheenSpecularDirect + sheenSpecularIndirect;\n\t#endif\n\t#ifdef USE_CLEARCOAT\n\t\tfloat dotNVcc = saturate( dot( geometryClearcoatNormal, geometryViewDir ) );\n\t\tvec3 Fcc = F_Schlick( material.clearcoatF0, material.clearcoatF90, dotNVcc );\n\t\toutgoingLight = outgoingLight * ( 1.0 - material.clearcoat * Fcc ) + ( clearcoatSpecularDirect + clearcoatSpecularIndirect ) * material.clearcoat;\n\t#endif\n\t#include <opaque_fragment>\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n\t#include <premultiplied_alpha_fragment>\n\t#include <dithering_fragment>\n}",meshtoon_vert:"#define TOON\nvarying vec3 vViewPosition;\n#include <common>\n#include <batching_pars_vertex>\n#include <uv_pars_vertex>\n#include <displacementmap_pars_vertex>\n#include <color_pars_vertex>\n#include <fog_pars_vertex>\n#include <normal_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <shadowmap_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\t#include <uv_vertex>\n\t#include <color_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphcolor_vertex>\n\t#include <batching_vertex>\n\t#include <beginnormal_vertex>\n\t#include <morphnormal_vertex>\n\t#include <skinbase_vertex>\n\t#include <skinnormal_vertex>\n\t#include <defaultnormal_vertex>\n\t#include <normal_vertex>\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <displacementmap_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\tvViewPosition = - mvPosition.xyz;\n\t#include <worldpos_vertex>\n\t#include <shadowmap_vertex>\n\t#include <fog_vertex>\n}",meshtoon_frag:"#define TOON\nuniform vec3 diffuse;\nuniform vec3 emissive;\nuniform float opacity;\n#include <common>\n#include <packing>\n#include <dithering_pars_fragment>\n#include <color_pars_fragment>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <alphamap_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <aomap_pars_fragment>\n#include <lightmap_pars_fragment>\n#include <emissivemap_pars_fragment>\n#include <gradientmap_pars_fragment>\n#include <fog_pars_fragment>\n#include <bsdfs>\n#include <lights_pars_begin>\n#include <normal_pars_fragment>\n#include <lights_toon_pars_fragment>\n#include <shadowmap_pars_fragment>\n#include <bumpmap_pars_fragment>\n#include <normalmap_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include <clipping_planes_fragment>\n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\tvec3 totalEmissiveRadiance = emissive;\n\t#include <logdepthbuf_fragment>\n\t#include <map_fragment>\n\t#include <color_fragment>\n\t#include <alphamap_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\t#include <normal_fragment_begin>\n\t#include <normal_fragment_maps>\n\t#include <emissivemap_fragment>\n\t#include <lights_toon_fragment>\n\t#include <lights_fragment_begin>\n\t#include <lights_fragment_maps>\n\t#include <lights_fragment_end>\n\t#include <aomap_fragment>\n\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\n\t#include <opaque_fragment>\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n\t#include <premultiplied_alpha_fragment>\n\t#include <dithering_fragment>\n}",points_vert:"uniform float size;\nuniform float scale;\n#include <common>\n#include <color_pars_vertex>\n#include <fog_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\n#ifdef USE_POINTS_UV\n\tvarying vec2 vUv;\n\tuniform mat3 uvTransform;\n#endif\nvoid main() {\n\t#ifdef USE_POINTS_UV\n\t\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\n\t#endif\n\t#include <color_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphcolor_vertex>\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <project_vertex>\n\tgl_PointSize = size;\n\t#ifdef USE_SIZEATTENUATION\n\t\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\n\t\tif ( isPerspective ) gl_PointSize *= ( scale / - mvPosition.z );\n\t#endif\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\t#include <worldpos_vertex>\n\t#include <fog_vertex>\n}",points_frag:"uniform vec3 diffuse;\nuniform float opacity;\n#include <common>\n#include <color_pars_fragment>\n#include <map_particle_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <fog_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include <clipping_planes_fragment>\n\tvec3 outgoingLight = vec3( 0.0 );\n\t#include <logdepthbuf_fragment>\n\t#include <map_particle_fragment>\n\t#include <color_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\toutgoingLight = diffuseColor.rgb;\n\t#include <opaque_fragment>\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n\t#include <premultiplied_alpha_fragment>\n}",shadow_vert:"#include <common>\n#include <batching_pars_vertex>\n#include <fog_pars_vertex>\n#include <morphtarget_pars_vertex>\n#include <skinning_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <shadowmap_pars_vertex>\nvoid main() {\n\t#include <batching_vertex>\n\t#include <beginnormal_vertex>\n\t#include <morphinstance_vertex>\n\t#include <morphnormal_vertex>\n\t#include <skinbase_vertex>\n\t#include <skinnormal_vertex>\n\t#include <defaultnormal_vertex>\n\t#include <begin_vertex>\n\t#include <morphtarget_vertex>\n\t#include <skinning_vertex>\n\t#include <project_vertex>\n\t#include <logdepthbuf_vertex>\n\t#include <worldpos_vertex>\n\t#include <shadowmap_vertex>\n\t#include <fog_vertex>\n}",shadow_frag:"uniform vec3 color;\nuniform float opacity;\n#include <common>\n#include <packing>\n#include <fog_pars_fragment>\n#include <bsdfs>\n#include <lights_pars_begin>\n#include <logdepthbuf_pars_fragment>\n#include <shadowmap_pars_fragment>\n#include <shadowmask_pars_fragment>\nvoid main() {\n\t#include <logdepthbuf_fragment>\n\tgl_FragColor = vec4( color, opacity * ( 1.0 - getShadowMask() ) );\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n}",sprite_vert:"uniform float rotation;\nuniform vec2 center;\n#include <common>\n#include <uv_pars_vertex>\n#include <fog_pars_vertex>\n#include <logdepthbuf_pars_vertex>\n#include <clipping_planes_pars_vertex>\nvoid main() {\n\t#include <uv_vertex>\n\tvec4 mvPosition = modelViewMatrix[ 3 ];\n\tvec2 scale = vec2( length( modelMatrix[ 0 ].xyz ), length( modelMatrix[ 1 ].xyz ) );\n\t#ifndef USE_SIZEATTENUATION\n\t\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\n\t\tif ( isPerspective ) scale *= - mvPosition.z;\n\t#endif\n\tvec2 alignedPosition = ( position.xy - ( center - vec2( 0.5 ) ) ) * scale;\n\tvec2 rotatedPosition;\n\trotatedPosition.x = cos( rotation ) * alignedPosition.x - sin( rotation ) * alignedPosition.y;\n\trotatedPosition.y = sin( rotation ) * alignedPosition.x + cos( rotation ) * alignedPosition.y;\n\tmvPosition.xy += rotatedPosition;\n\tgl_Position = projectionMatrix * mvPosition;\n\t#include <logdepthbuf_vertex>\n\t#include <clipping_planes_vertex>\n\t#include <fog_vertex>\n}",sprite_frag:"uniform vec3 diffuse;\nuniform float opacity;\n#include <common>\n#include <uv_pars_fragment>\n#include <map_pars_fragment>\n#include <alphamap_pars_fragment>\n#include <alphatest_pars_fragment>\n#include <alphahash_pars_fragment>\n#include <fog_pars_fragment>\n#include <logdepthbuf_pars_fragment>\n#include <clipping_planes_pars_fragment>\nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include <clipping_planes_fragment>\n\tvec3 outgoingLight = vec3( 0.0 );\n\t#include <logdepthbuf_fragment>\n\t#include <map_fragment>\n\t#include <alphamap_fragment>\n\t#include <alphatest_fragment>\n\t#include <alphahash_fragment>\n\toutgoingLight = diffuseColor.rgb;\n\t#include <opaque_fragment>\n\t#include <tonemapping_fragment>\n\t#include <colorspace_fragment>\n\t#include <fog_fragment>\n}"},gp={common:{diffuse:{value:new ya(16777215)},opacity:{value:1},map:{value:null},mapTransform:{value:new Ps},alphaMap:{value:null},alphaMapTransform:{value:new Ps},alphaTest:{value:0}},specularmap:{specularMap:{value:null},specularMapTransform:{value:new Ps}},envmap:{envMap:{value:null},envMapRotation:{value:new Ps},flipEnvMap:{value:-1},reflectivity:{value:1},ior:{value:1.5},refractionRatio:{value:.98}},aomap:{aoMap:{value:null},aoMapIntensity:{value:1},aoMapTransform:{value:new Ps}},lightmap:{lightMap:{value:null},lightMapIntensity:{value:1},lightMapTransform:{value:new Ps}},bumpmap:{bumpMap:{value:null},bumpMapTransform:{value:new Ps},bumpScale:{value:1}},normalmap:{normalMap:{value:null},normalMapTransform:{value:new Ps},normalScale:{value:new Cs(1,1)}},displacementmap:{displacementMap:{value:null},displacementMapTransform:{value:new Ps},displacementScale:{value:1},displacementBias:{value:0}},emissivemap:{emissiveMap:{value:null},emissiveMapTransform:{value:new Ps}},metalnessmap:{metalnessMap:{value:null},metalnessMapTransform:{value:new Ps}},roughnessmap:{roughnessMap:{value:null},roughnessMapTransform:{value:new Ps}},gradientmap:{gradientMap:{value:null}},fog:{fogDensity:{value:25e-5},fogNear:{value:1},fogFar:{value:2e3},fogColor:{value:new ya(16777215)}},lights:{ambientLightColor:{value:[]},lightProbe:{value:[]},directionalLights:{value:[],properties:{direction:{},color:{}}},directionalLightShadows:{value:[],properties:{shadowIntensity:1,shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{}}},directionalShadowMap:{value:[]},directionalShadowMatrix:{value:[]},spotLights:{value:[],properties:{color:{},position:{},direction:{},distance:{},coneCos:{},penumbraCos:{},decay:{}}},spotLightShadows:{value:[],properties:{shadowIntensity:1,shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{}}},spotLightMap:{value:[]},spotShadowMap:{value:[]},spotLightMatrix:{value:[]},pointLights:{value:[],properties:{color:{},position:{},decay:{},distance:{}}},pointLightShadows:{value:[],properties:{shadowIntensity:1,shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{},shadowCameraNear:{},shadowCameraFar:{}}},pointShadowMap:{value:[]},pointShadowMatrix:{value:[]},hemisphereLights:{value:[],properties:{direction:{},skyColor:{},groundColor:{}}},rectAreaLights:{value:[],properties:{color:{},position:{},width:{},height:{}}},ltc_1:{value:null},ltc_2:{value:null}},points:{diffuse:{value:new ya(16777215)},opacity:{value:1},size:{value:1},scale:{value:1},map:{value:null},alphaMap:{value:null},alphaMapTransform:{value:new Ps},alphaTest:{value:0},uvTransform:{value:new Ps}},sprite:{diffuse:{value:new ya(16777215)},opacity:{value:1},center:{value:new Cs(.5,.5)},rotation:{value:0},map:{value:null},mapTransform:{value:new Ps},alphaMap:{value:null},alphaMapTransform:{value:new Ps},alphaTest:{value:0}}},mp={basic:{uniforms:ol([gp.common,gp.specularmap,gp.envmap,gp.aomap,gp.lightmap,gp.fog]),vertexShader:pp.meshbasic_vert,fragmentShader:pp.meshbasic_frag},lambert:{uniforms:ol([gp.common,gp.specularmap,gp.envmap,gp.aomap,gp.lightmap,gp.emissivemap,gp.bumpmap,gp.normalmap,gp.displacementmap,gp.fog,gp.lights,{emissive:{value:new ya(0)}}]),vertexShader:pp.meshlambert_vert,fragmentShader:pp.meshlambert_frag},phong:{uniforms:ol([gp.common,gp.specularmap,gp.envmap,gp.aomap,gp.lightmap,gp.emissivemap,gp.bumpmap,gp.normalmap,gp.displacementmap,gp.fog,gp.lights,{emissive:{value:new 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this._fromTexture(e,t)}compileCubemapShader(){null===this._cubemapMaterial&&(this._cubemapMaterial=Xp(),this._compileMaterial(this._cubemapMaterial))}compileEquirectangularShader(){null===this._equirectMaterial&&(this._equirectMaterial=Up(),this._compileMaterial(this._equirectMaterial))}dispose(){this._dispose(),null!==this._cubemapMaterial&&this._cubemapMaterial.dispose(),null!==this._equirectMaterial&&this._equirectMaterial.dispose()}_setSize(e){this._lodMax=Math.floor(Math.log2(e)),this._cubeSize=Math.pow(2,this._lodMax)}_dispose(){null!==this._blurMaterial&&this._blurMaterial.dispose(),null!==this._pingPongRenderTarget&&this._pingPongRenderTarget.dispose();for(let e=0;e<this._lodPlanes.length;e++)this._lodPlanes[e].dispose()}_cleanup(e){this._renderer.setRenderTarget(Bp,Dp,Ip),this._renderer.xr.enabled=Lp,e.scissorTest=!1,Hp(e,0,0,e.width,e.height)}_fromTexture(e,t){e.mapping===Ni||e.mapping===Bi?this._setSize(0===e.image.length?16:e.image[0].width||e.image[0].image.width):this._setSize(e.image.width/4),Bp=this._renderer.getRenderTarget(),Dp=this._renderer.getActiveCubeFace(),Ip=this._renderer.getActiveMipmapLevel(),Lp=this._renderer.xr.enabled,this._renderer.xr.enabled=!1;const n=t||this._allocateTargets();return this._textureToCubeUV(e,n),this._applyPMREM(n),this._cleanup(n),n}_allocateTargets(){const e=3*Math.max(this._cubeSize,112),t=4*this._cubeSize,n={magFilter:Hi,minFilter:Hi,generateMipmaps:!1,type:Ki,format:rr,colorSpace:_r,depthBuffer:!1},i=Fp(e,t,n);if(null===this._pingPongRenderTarget||this._pingPongRenderTarget.width!==e||this._pingPongRenderTarget.height!==t){null!==this._pingPongRenderTarget&&this._dispose(),this._pingPongRenderTarget=Fp(e,t,n);const{_lodMax:i}=this;({sizeLods:this._sizeLods,lodPlanes:this._lodPlanes,sigmas:this._sigmas}=function(e){const t=[],n=[],i=[];let r=e;const s=e-4+1+Tp.length;for(let o=0;o<s;o++){const s=Math.pow(2,r);n.push(s);let a=1/s;o>e-4?a=Tp[o-e+4-1]:0===o&&(a=0),i.push(a);const l=1/(s-2),u=-l,c=1+l,d=[u,u,c,u,c,c,u,u,c,c,u,c],h=6,f=6,p=3,g=2,m=1,v=new Float32Array(p*f*h),A=new Float32Array(g*f*h),x=new Float32Array(m*f*h);for(let e=0;e<h;e++){const t=e%3*2/3-1,n=e>2?0:-1,i=[t,n,0,t+2/3,n,0,t+2/3,n+1,0,t,n,0,t+2/3,n+1,0,t,n+1,0];v.set(i,p*f*e),A.set(d,g*f*e);const r=[e,e,e,e,e,e];x.set(r,m*f*e)}const y=new Va;y.setAttribute("position",new Ia(v,p)),y.setAttribute("uv",new Ia(A,g)),y.setAttribute("faceIndex",new Ia(x,m)),t.push(y),r>4&&r--}return{lodPlanes:t,sizeLods:n,sigmas:i}}(i)),this._blurMaterial=function(e,t,n){const i=new Float32Array(Sp),r=new Es(0,1,0),s=new ul({name:"SphericalGaussianBlur",defines:{n:Sp,CUBEUV_TEXEL_WIDTH:1/t,CUBEUV_TEXEL_HEIGHT:1/n,CUBEUV_MAX_MIP:`${e}.0`},uniforms:{envMap:{value:null},samples:{value:1},weights:{value:i},latitudinal:{value:!1},dTheta:{value:0},mipInt:{value:0},poleAxis:{value:r}},vertexShader:Gp(),fragmentShader:"\n\n\t\t\tprecision mediump float;\n\t\t\tprecision mediump int;\n\n\t\t\tvarying vec3 vOutputDirection;\n\n\t\t\tuniform sampler2D envMap;\n\t\t\tuniform int samples;\n\t\t\tuniform float weights[ n ];\n\t\t\tuniform bool latitudinal;\n\t\t\tuniform float dTheta;\n\t\t\tuniform float mipInt;\n\t\t\tuniform vec3 poleAxis;\n\n\t\t\t#define ENVMAP_TYPE_CUBE_UV\n\t\t\t#include <cube_uv_reflection_fragment>\n\n\t\t\tvec3 getSample( float theta, vec3 axis ) {\n\n\t\t\t\tfloat cosTheta = cos( theta );\n\t\t\t\t// Rodrigues' axis-angle rotation\n\t\t\t\tvec3 sampleDirection = vOutputDirection * cosTheta\n\t\t\t\t\t+ cross( axis, vOutputDirection ) * sin( theta )\n\t\t\t\t\t+ axis * dot( axis, vOutputDirection ) * ( 1.0 - cosTheta );\n\n\t\t\t\treturn bilinearCubeUV( envMap, sampleDirection, mipInt );\n\n\t\t\t}\n\n\t\t\tvoid main() {\n\n\t\t\t\tvec3 axis = latitudinal ? poleAxis : cross( poleAxis, vOutputDirection );\n\n\t\t\t\tif ( all( equal( axis, vec3( 0.0 ) ) ) ) {\n\n\t\t\t\t\taxis = vec3( vOutputDirection.z, 0.0, - vOutputDirection.x );\n\n\t\t\t\t}\n\n\t\t\t\taxis = normalize( axis );\n\n\t\t\t\tgl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );\n\t\t\t\tgl_FragColor.rgb += weights[ 0 ] * getSample( 0.0, axis );\n\n\t\t\t\tfor ( int i = 1; i < n; i++ ) {\n\n\t\t\t\t\tif ( i >= samples ) {\n\n\t\t\t\t\t\tbreak;\n\n\t\t\t\t\t}\n\n\t\t\t\t\tfloat theta = dTheta * float( i );\n\t\t\t\t\tgl_FragColor.rgb += weights[ i ] * getSample( -1.0 * theta, axis );\n\t\t\t\t\tgl_FragColor.rgb += weights[ i ] * getSample( theta, axis );\n\n\t\t\t\t}\n\n\t\t\t}\n\t\t",blending:0,depthTest:!1,depthWrite:!1});return s}(i,e,t)}return i}_compileMaterial(e){const t=new nl(this._lodPlanes[0],e);this._renderer.compile(t,Pp)}_sceneToCubeUV(e,t,n,i,r){const s=new pl(90,1,t,n),o=[1,-1,1,1,1,1],a=[1,1,1,-1,-1,-1],l=this._renderer,u=l.autoClear,c=l.toneMapping;l.getClearColor(Np),l.toneMapping=0,l.autoClear=!1;l.state.buffers.depth.getReversed()&&(l.setRenderTarget(i),l.clearDepth(),l.setRenderTarget(null));const d=new Ma({name:"PMREM.Background",side:1,depthWrite:!1,depthTest:!1}),h=new nl(new rl,d);let f=!1;const p=e.background;p?p.isColor&&(d.color.copy(p),e.background=null,f=!0):(d.color.copy(Np),f=!0);for(let t=0;t<6;t++){const n=t%3;0===n?(s.up.set(0,o[t],0),s.position.set(r.x,r.y,r.z),s.lookAt(r.x+a[t],r.y,r.z)):1===n?(s.up.set(0,0,o[t]),s.position.set(r.x,r.y,r.z),s.lookAt(r.x,r.y+a[t],r.z)):(s.up.set(0,o[t],0),s.position.set(r.x,r.y,r.z),s.lookAt(r.x,r.y,r.z+a[t]));const u=this._cubeSize;Hp(i,n*u,t>2?u:0,u,u),l.setRenderTarget(i),f&&l.render(h,s),l.render(e,s)}h.geometry.dispose(),h.material.dispose(),l.toneMapping=c,l.autoClear=u,e.background=p}_textureToCubeUV(e,t){const n=this._renderer,i=e.mapping===Ni||e.mapping===Bi;i?(null===this._cubemapMaterial&&(this._cubemapMaterial=Xp()),this._cubemapMaterial.uniforms.flipEnvMap.value=!1===e.isRenderTargetTexture?-1:1):null===this._equirectMaterial&&(this._equirectMaterial=Up());const r=i?this._cubemapMaterial:this._equirectMaterial,s=new nl(this._lodPlanes[0],r);r.uniforms.envMap.value=e;const o=this._cubeSize;Hp(t,0,0,3*o,2*o),n.setRenderTarget(t),n.render(s,Pp)}_applyPMREM(e){const t=this._renderer,n=t.autoClear;t.autoClear=!1;const i=this._lodPlanes.length;for(let t=1;t<i;t++){const n=Math.sqrt(this._sigmas[t]*this._sigmas[t]-this._sigmas[t-1]*this._sigmas[t-1]),r=zp[(i-t-1)%zp.length];this._blur(e,t-1,t,n,r)}t.autoClear=n}_blur(e,t,n,i,r){const s=this._pingPongRenderTarget;this._halfBlur(e,s,t,n,i,"latitudinal",r),this._halfBlur(s,e,n,n,i,"longitudinal",r)}_halfBlur(e,t,n,i,r,s,o){const a=this._renderer,l=this._blurMaterial;"latitudinal"!==s&&"longitudinal"!==s&&console.error("blur direction must be either latitudinal or longitudinal!");const u=new nl(this._lodPlanes[i],l),c=l.uniforms,d=this._sizeLods[n]-1,h=isFinite(r)?Math.PI/(2*d):2*Math.PI/39,f=r/h,p=isFinite(r)?1+Math.floor(3*f):Sp;p>Sp&&console.warn(`sigmaRadians, ${r}, is too large and will clip, as it requested ${p} samples when the maximum is set to 20`);const g=[];let m=0;for(let e=0;e<Sp;++e){const t=e/f,n=Math.exp(-t*t/2);g.push(n),0===e?m+=n:e<p&&(m+=2*n)}for(let e=0;e<g.length;e++)g[e]=g[e]/m;c.envMap.value=e.texture,c.samples.value=p,c.weights.value=g,c.latitudinal.value="latitudinal"===s,o&&(c.poleAxis.value=o);const{_lodMax:v}=this;c.dTheta.value=h,c.mipInt.value=v-n;const A=this._sizeLods[i];Hp(t,3*A*(i>v-4?i-v+4:0),4*(this._cubeSize-A),3*A,2*A),a.setRenderTarget(t),a.render(u,Pp)}}function Fp(e,t,n){const i=new qs(e,t,n);return i.texture.mapping=Li,i.texture.name="PMREM.cubeUv",i.scissorTest=!0,i}function Hp(e,t,n,i,r){e.viewport.set(t,n,i,r),e.scissor.set(t,n,i,r)}function Up(){return new ul({name:"EquirectangularToCubeUV",uniforms:{envMap:{value:null}},vertexShader:Gp(),fragmentShader:"\n\n\t\t\tprecision mediump float;\n\t\t\tprecision mediump int;\n\n\t\t\tvarying vec3 vOutputDirection;\n\n\t\t\tuniform sampler2D envMap;\n\n\t\t\t#include <common>\n\n\t\t\tvoid main() {\n\n\t\t\t\tvec3 outputDirection = normalize( vOutputDirection );\n\t\t\t\tvec2 uv = equirectUv( outputDirection );\n\n\t\t\t\tgl_FragColor = vec4( texture2D ( envMap, uv ).rgb, 1.0 );\n\n\t\t\t}\n\t\t",blending:0,depthTest:!1,depthWrite:!1})}function Xp(){return new ul({name:"CubemapToCubeUV",uniforms:{envMap:{value:null},flipEnvMap:{value:-1}},vertexShader:Gp(),fragmentShader:"\n\n\t\t\tprecision mediump float;\n\t\t\tprecision mediump int;\n\n\t\t\tuniform float flipEnvMap;\n\n\t\t\tvarying vec3 vOutputDirection;\n\n\t\t\tuniform samplerCube envMap;\n\n\t\t\tvoid main() {\n\n\t\t\t\tgl_FragColor = textureCube( envMap, vec3( flipEnvMap * vOutputDirection.x, vOutputDirection.yz ) );\n\n\t\t\t}\n\t\t",blending:0,depthTest:!1,depthWrite:!1})}function Gp(){return"\n\n\t\tprecision mediump float;\n\t\tprecision mediump int;\n\n\t\tattribute float faceIndex;\n\n\t\tvarying vec3 vOutputDirection;\n\n\t\t// RH coordinate system; PMREM face-indexing convention\n\t\tvec3 getDirection( vec2 uv, float face ) {\n\n\t\t\tuv = 2.0 * uv - 1.0;\n\n\t\t\tvec3 direction = vec3( uv, 1.0 );\n\n\t\t\tif ( face == 0.0 ) {\n\n\t\t\t\tdirection = direction.zyx; // ( 1, v, u ) pos x\n\n\t\t\t} else if ( face == 1.0 ) {\n\n\t\t\t\tdirection = direction.xzy;\n\t\t\t\tdirection.xz *= -1.0; // ( -u, 1, -v ) pos y\n\n\t\t\t} else if ( face == 2.0 ) {\n\n\t\t\t\tdirection.x *= -1.0; // ( -u, v, 1 ) pos z\n\n\t\t\t} else if ( face == 3.0 ) {\n\n\t\t\t\tdirection = direction.zyx;\n\t\t\t\tdirection.xz *= -1.0; // ( -1, v, -u ) neg x\n\n\t\t\t} else if ( face == 4.0 ) {\n\n\t\t\t\tdirection = direction.xzy;\n\t\t\t\tdirection.xy *= -1.0; // ( -u, -1, v ) neg y\n\n\t\t\t} else if ( face == 5.0 ) {\n\n\t\t\t\tdirection.z *= -1.0; // ( u, v, -1 ) neg z\n\n\t\t\t}\n\n\t\t\treturn direction;\n\n\t\t}\n\n\t\tvoid main() {\n\n\t\t\tvOutputDirection = getDirection( uv, faceIndex );\n\t\t\tgl_Position = vec4( position, 1.0 );\n\n\t\t}\n\t"}function Vp(e){let t=new WeakMap,n=null;function i(e){const n=e.target;n.removeEventListener("dispose",i);const r=t.get(n);void 0!==r&&(t.delete(n),r.dispose())}return{get:function(r){if(r&&r.isTexture){const s=r.mapping,o=s===Di||s===Ii,a=s===Ni||s===Bi;if(o||a){let s=t.get(r);const l=void 0!==s?s.texture.pmremVersion:0;if(r.isRenderTargetTexture&&r.pmremVersion!==l)return null===n&&(n=new kp(e)),s=o?n.fromEquirectangular(r,s):n.fromCubemap(r,s),s.texture.pmremVersion=r.pmremVersion,t.set(r,s),s.texture;if(void 0!==s)return s.texture;{const l=r.image;return o&&l&&l.height>0||a&&l&&function(e){let t=0;const n=6;for(let i=0;i<n;i++)void 0!==e[i]&&t++;return t===n}(l)?(null===n&&(n=new kp(e)),s=o?n.fromEquirectangular(r):n.fromCubemap(r),s.texture.pmremVersion=r.pmremVersion,t.set(r,s),r.addEventListener("dispose",i),s.texture):null}}}return r},dispose:function(){t=new WeakMap,null!==n&&(n.dispose(),n=null)}}}function Wp(e){const t={};function n(n){if(void 0!==t[n])return t[n];let i;switch(n){case"WEBGL_depth_texture":i=e.getExtension("WEBGL_depth_texture")||e.getExtension("MOZ_WEBGL_depth_texture")||e.getExtension("WEBKIT_WEBGL_depth_texture");break;case"EXT_texture_filter_anisotropic":i=e.getExtension("EXT_texture_filter_anisotropic")||e.getExtension("MOZ_EXT_texture_filter_anisotropic")||e.getExtension("WEBKIT_EXT_texture_filter_anisotropic");break;case"WEBGL_compressed_texture_s3tc":i=e.getExtension("WEBGL_compressed_texture_s3tc")||e.getExtension("MOZ_WEBGL_compressed_texture_s3tc")||e.getExtension("WEBKIT_WEBGL_compressed_texture_s3tc");break;case"WEBGL_compressed_texture_pvrtc":i=e.getExtension("WEBGL_compressed_texture_pvrtc")||e.getExtension("WEBKIT_WEBGL_compressed_texture_pvrtc");break;default:i=e.getExtension(n)}return t[n]=i,i}return{has:function(e){return null!==n(e)},init:function(){n("EXT_color_buffer_float"),n("WEBGL_clip_cull_distance"),n("OES_texture_float_linear"),n("EXT_color_buffer_half_float"),n("WEBGL_multisampled_render_to_texture"),n("WEBGL_render_shared_exponent")},get:function(e){const t=n(e);return null===t&&js("THREE.WebGLRenderer: "+e+" extension not supported."),t}}}function Qp(e,t,n,i){const r={},s=new WeakMap;function o(e){const a=e.target;null!==a.index&&t.remove(a.index);for(const e in a.attributes)t.remove(a.attributes[e]);a.removeEventListener("dispose",o),delete r[a.id];const l=s.get(a);l&&(t.remove(l),s.delete(a)),i.releaseStatesOfGeometry(a),!0===a.isInstancedBufferGeometry&&delete a._maxInstanceCount,n.memory.geometries--}function a(e){const n=[],i=e.index,r=e.attributes.position;let o=0;if(null!==i){const e=i.array;o=i.version;for(let t=0,i=e.length;t<i;t+=3){const i=e[t+0],r=e[t+1],s=e[t+2];n.push(i,r,r,s,s,i)}}else{if(void 0===r)return;{const e=r.array;o=r.version;for(let t=0,i=e.length/3-1;t<i;t+=3){const 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c=t.get("WEBGL_multi_draw");if(null===c)for(let t=0;t<e.length;t++)o(e[t]/s,a[t],u[t]);else{c.multiDrawElementsInstancedWEBGL(i,a,0,r,e,0,u,0,l);let t=0;for(let e=0;e<l;e++)t+=a[e]*u[e];n.update(t,i,1)}}}function Yp(e){const t={frame:0,calls:0,triangles:0,points:0,lines:0};return{memory:{geometries:0,textures:0},render:t,programs:null,autoReset:!0,reset:function(){t.calls=0,t.triangles=0,t.points=0,t.lines=0},update:function(n,i,r){switch(t.calls++,i){case e.TRIANGLES:t.triangles+=r*(n/3);break;case e.LINES:t.lines+=r*(n/2);break;case e.LINE_STRIP:t.lines+=r*(n-1);break;case e.LINE_LOOP:t.lines+=r*n;break;case e.POINTS:t.points+=r*n;break;default:console.error("THREE.WebGLInfo: Unknown draw mode:",i)}}}}function Jp(e,t,n){const i=new WeakMap,r=new Js;return{update:function(s,o,a){const l=s.morphTargetInfluences,u=o.morphAttributes.position||o.morphAttributes.normal||o.morphAttributes.color,c=void 0!==u?u.length:0;let d=i.get(o);if(void 0===d||d.count!==c){void 0!==d&&d.texture.dispose();const h=void 0!==o.morphAttributes.position,f=void 0!==o.morphAttributes.normal,p=void 0!==o.morphAttributes.color,g=o.morphAttributes.position||[],m=o.morphAttributes.normal||[],v=o.morphAttributes.color||[];let A=0;!0===h&&(A=1),!0===f&&(A=2),!0===p&&(A=3);let x=o.attributes.position.count*A,y=1;x>t.maxTextureSize&&(y=Math.ceil(x/t.maxTextureSize),x=t.maxTextureSize);const b=new Float32Array(x*y*4*c),w=new _s(b,x,y,c);w.type=Ji,w.needsUpdate=!0;const C=4*A;for(let E=0;E<c;E++){const T=g[E],S=m[E],P=v[E],N=x*y*4*E;for(let B=0;B<T.count;B++){const D=B*C;!0===h&&(r.fromBufferAttribute(T,B),b[N+D+0]=r.x,b[N+D+1]=r.y,b[N+D+2]=r.z,b[N+D+3]=0),!0===f&&(r.fromBufferAttribute(S,B),b[N+D+4]=r.x,b[N+D+5]=r.y,b[N+D+6]=r.z,b[N+D+7]=0),!0===p&&(r.fromBufferAttribute(P,B),b[N+D+8]=r.x,b[N+D+9]=r.y,b[N+D+10]=r.z,b[N+D+11]=4===P.itemSize?r.w:1)}}function M(){w.dispose(),i.delete(o),o.removeEventListener("dispose",M)}d={count:c,texture:w,size:new 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Int32Array(t),ig[t]=n);for(let i=0;i!==t;++i)n[i]=e.allocateTextureUnit();return n}function dg(e,t){const n=this.cache;n[0]!==t&&(e.uniform1f(this.addr,t),n[0]=t)}function hg(e,t){const n=this.cache;if(void 0!==t.x)n[0]===t.x&&n[1]===t.y||(e.uniform2f(this.addr,t.x,t.y),n[0]=t.x,n[1]=t.y);else{if(lg(n,t))return;e.uniform2fv(this.addr,t),ug(n,t)}}function fg(e,t){const n=this.cache;if(void 0!==t.x)n[0]===t.x&&n[1]===t.y&&n[2]===t.z||(e.uniform3f(this.addr,t.x,t.y,t.z),n[0]=t.x,n[1]=t.y,n[2]=t.z);else if(void 0!==t.r)n[0]===t.r&&n[1]===t.g&&n[2]===t.b||(e.uniform3f(this.addr,t.r,t.g,t.b),n[0]=t.r,n[1]=t.g,n[2]=t.b);else{if(lg(n,t))return;e.uniform3fv(this.addr,t),ug(n,t)}}function pg(e,t){const n=this.cache;if(void 0!==t.x)n[0]===t.x&&n[1]===t.y&&n[2]===t.z&&n[3]===t.w||(e.uniform4f(this.addr,t.x,t.y,t.z,t.w),n[0]=t.x,n[1]=t.y,n[2]=t.z,n[3]=t.w);else{if(lg(n,t))return;e.uniform4fv(this.addr,t),ug(n,t)}}function gg(e,t){const n=this.cache,i=t.elements;if(void 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0!==t.x)n[0]===t.x&&n[1]===t.y&&n[2]===t.z||(e.uniform3i(this.addr,t.x,t.y,t.z),n[0]=t.x,n[1]=t.y,n[2]=t.z);else{if(lg(n,t))return;e.uniform3iv(this.addr,t),ug(n,t)}}function bg(e,t){const n=this.cache;if(void 0!==t.x)n[0]===t.x&&n[1]===t.y&&n[2]===t.z&&n[3]===t.w||(e.uniform4i(this.addr,t.x,t.y,t.z,t.w),n[0]=t.x,n[1]=t.y,n[2]=t.z,n[3]=t.w);else{if(lg(n,t))return;e.uniform4iv(this.addr,t),ug(n,t)}}function wg(e,t){const n=this.cache;n[0]!==t&&(e.uniform1ui(this.addr,t),n[0]=t)}function Cg(e,t){const n=this.cache;if(void 0!==t.x)n[0]===t.x&&n[1]===t.y||(e.uniform2ui(this.addr,t.x,t.y),n[0]=t.x,n[1]=t.y);else{if(lg(n,t))return;e.uniform2uiv(this.addr,t),ug(n,t)}}function Mg(e,t){const n=this.cache;if(void 0!==t.x)n[0]===t.x&&n[1]===t.y&&n[2]===t.z||(e.uniform3ui(this.addr,t.x,t.y,t.z),n[0]=t.x,n[1]=t.y,n[2]=t.z);else{if(lg(n,t))return;e.uniform3uiv(this.addr,t),ug(n,t)}}function Eg(e,t){const n=this.cache;if(void 0!==t.x)n[0]===t.x&&n[1]===t.y&&n[2]===t.z&&n[3]===t.w||(e.uniform4ui(this.addr,t.x,t.y,t.z,t.w),n[0]=t.x,n[1]=t.y,n[2]=t.z,n[3]=t.w);else{if(lg(n,t))return;e.uniform4uiv(this.addr,t),ug(n,t)}}function Tg(e,t,n){const i=this.cache,r=n.allocateTextureUnit();let s;i[0]!==r&&(e.uniform1i(this.addr,r),i[0]=r),this.type===e.SAMPLER_2D_SHADOW?(_p.compareFunction=is,s=_p):s=qp,n.setTexture2D(t||s,r)}function Sg(e,t,n){const i=this.cache,r=n.allocateTextureUnit();i[0]!==r&&(e.uniform1i(this.addr,r),i[0]=r),n.setTexture3D(t||eg,r)}function Pg(e,t,n){const i=this.cache,r=n.allocateTextureUnit();i[0]!==r&&(e.uniform1i(this.addr,r),i[0]=r),n.setTextureCube(t||tg,r)}function Ng(e,t,n){const i=this.cache,r=n.allocateTextureUnit();i[0]!==r&&(e.uniform1i(this.addr,r),i[0]=r),n.setTexture2DArray(t||$p,r)}function Bg(e,t){e.uniform1fv(this.addr,t)}function Dg(e,t){const n=ag(t,this.size,2);e.uniform2fv(this.addr,n)}function Ig(e,t){const n=ag(t,this.size,3);e.uniform3fv(this.addr,n)}function Lg(e,t){const n=ag(t,this.size,4);e.uniform4fv(this.addr,n)}function jg(e,t){const n=ag(t,this.size,4);e.uniformMatrix2fv(this.addr,!1,n)}function Og(e,t){const n=ag(t,this.size,9);e.uniformMatrix3fv(this.addr,!1,n)}function zg(e,t){const n=ag(t,this.size,16);e.uniformMatrix4fv(this.addr,!1,n)}function Rg(e,t){e.uniform1iv(this.addr,t)}function kg(e,t){e.uniform2iv(this.addr,t)}function Fg(e,t){e.uniform3iv(this.addr,t)}function Hg(e,t){e.uniform4iv(this.addr,t)}function Ug(e,t){e.uniform1uiv(this.addr,t)}function Xg(e,t){e.uniform2uiv(this.addr,t)}function Gg(e,t){e.uniform3uiv(this.addr,t)}function Vg(e,t){e.uniform4uiv(this.addr,t)}function Wg(e,t,n){const i=this.cache,r=t.length,s=cg(n,r);lg(i,s)||(e.uniform1iv(this.addr,s),ug(i,s));for(let e=0;e!==r;++e)n.setTexture2D(t[e]||qp,s[e])}function Qg(e,t,n){const i=this.cache,r=t.length,s=cg(n,r);lg(i,s)||(e.uniform1iv(this.addr,s),ug(i,s));for(let e=0;e!==r;++e)n.setTexture3D(t[e]||eg,s[e])}function Zg(e,t,n){const i=this.cache,r=t.length,s=cg(n,r);lg(i,s)||(e.uniform1iv(this.addr,s),ug(i,s));for(let e=0;e!==r;++e)n.setTextureCube(t[e]||tg,s[e])}function Yg(e,t,n){const i=this.cache,r=t.length,s=cg(n,r);lg(i,s)||(e.uniform1iv(this.addr,s),ug(i,s));for(let e=0;e!==r;++e)n.setTexture2DArray(t[e]||$p,s[e])}class Jg{constructor(e,t,n){this.id=e,this.addr=n,this.cache=[],this.type=t.type,this.setValue=function(e){switch(e){case 5126:return dg;case 35664:return hg;case 35665:return fg;case 35666:return pg;case 35674:return gg;case 35675:return mg;case 35676:return vg;case 5124:case 35670:return Ag;case 35667:case 35671:return xg;case 35668:case 35672:return yg;case 35669:case 35673:return bg;case 5125:return wg;case 36294:return Cg;case 36295:return Mg;case 36296:return Eg;case 35678:case 36198:case 36298:case 36306:case 35682:return Tg;case 35679:case 36299:case 36307:return Sg;case 35680:case 36300:case 36308:case 36293:return Pg;case 36289:case 36303:case 36311:case 36292:return Ng}}(t.type)}}class Kg{constructor(e,t,n){this.id=e,this.addr=n,this.cache=[],this.type=t.type,this.size=t.size,this.setValue=function(e){switch(e){case 5126:return Bg;case 35664:return Dg;case 35665:return Ig;case 35666:return Lg;case 35674:return jg;case 35675:return Og;case 35676:return zg;case 5124:case 35670:return Rg;case 35667:case 35671:return kg;case 35668:case 35672:return Fg;case 35669:case 35673:return Hg;case 5125:return Ug;case 36294:return Xg;case 36295:return Gg;case 36296:return Vg;case 35678:case 36198:case 36298:case 36306:case 35682:return Wg;case 35679:case 36299:case 36307:return Qg;case 35680:case 36300:case 36308:case 36293:return Zg;case 36289:case 36303:case 36311:case 36292:return Yg}}(t.type)}}class qg{constructor(e){this.id=e,this.seq=[],this.map={}}setValue(e,t,n){const i=this.seq;for(let r=0,s=i.length;r!==s;++r){const s=i[r];s.setValue(e,t[s.id],n)}}}const _g=/(\w+)(\])?(\[|\.)?/g;function $g(e,t){e.seq.push(t),e.map[t.id]=t}function em(e,t,n){const 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e.replace(/NUM_DIR_LIGHTS/g,t.numDirLights).replace(/NUM_SPOT_LIGHTS/g,t.numSpotLights).replace(/NUM_SPOT_LIGHT_MAPS/g,t.numSpotLightMaps).replace(/NUM_SPOT_LIGHT_COORDS/g,n).replace(/NUM_RECT_AREA_LIGHTS/g,t.numRectAreaLights).replace(/NUM_POINT_LIGHTS/g,t.numPointLights).replace(/NUM_HEMI_LIGHTS/g,t.numHemiLights).replace(/NUM_DIR_LIGHT_SHADOWS/g,t.numDirLightShadows).replace(/NUM_SPOT_LIGHT_SHADOWS_WITH_MAPS/g,t.numSpotLightShadowsWithMaps).replace(/NUM_SPOT_LIGHT_SHADOWS/g,t.numSpotLightShadows).replace(/NUM_POINT_LIGHT_SHADOWS/g,t.numPointLightShadows)}function hm(e,t){return e.replace(/NUM_CLIPPING_PLANES/g,t.numClippingPlanes).replace(/UNION_CLIPPING_PLANES/g,t.numClippingPlanes-t.numClipIntersection)}const fm=/^[ \t]*#include +<([\w\d./]+)>/gm;function pm(e){return e.replace(fm,mm)}const gm=new Map;function mm(e,t){let n=pp[t];if(void 0===n){const e=gm.get(t);if(void 0===e)throw new Error("Can not resolve #include <"+t+">");n=pp[e],console.warn('THREE.WebGLRenderer: Shader 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Use "%s" instead.',t,e)}return pm(n)}const vm=/#pragma unroll_loop_start\s+for\s*\(\s*int\s+i\s*=\s*(\d+)\s*;\s*i\s*<\s*(\d+)\s*;\s*i\s*\+\+\s*\)\s*{([\s\S]+?)}\s+#pragma unroll_loop_end/g;function Am(e){return e.replace(vm,xm)}function xm(e,t,n,i){let r="";for(let e=parseInt(t);e<parseInt(n);e++)r+=i.replace(/\[\s*i\s*\]/g,"[ "+e+" ]").replace(/UNROLLED_LOOP_INDEX/g,e);return r}function ym(e){let t=`precision ${e.precision} float;\n\tprecision ${e.precision} int;\n\tprecision ${e.precision} sampler2D;\n\tprecision ${e.precision} samplerCube;\n\tprecision ${e.precision} sampler3D;\n\tprecision ${e.precision} sampler2DArray;\n\tprecision ${e.precision} sampler2DShadow;\n\tprecision ${e.precision} samplerCubeShadow;\n\tprecision ${e.precision} sampler2DArrayShadow;\n\tprecision ${e.precision} isampler2D;\n\tprecision ${e.precision} isampler3D;\n\tprecision ${e.precision} isamplerCube;\n\tprecision ${e.precision} isampler2DArray;\n\tprecision ${e.precision} usampler2D;\n\tprecision 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t=this.materialCache.get(e);for(const e of t)e.usedTimes--,0===e.usedTimes&&this.shaderCache.delete(e.code);return this.materialCache.delete(e),this}getVertexShaderID(e){return this._getShaderStage(e.vertexShader).id}getFragmentShaderID(e){return this._getShaderStage(e.fragmentShader).id}dispose(){this.shaderCache.clear(),this.materialCache.clear()}_getShaderCacheForMaterial(e){const t=this.materialCache;let n=t.get(e);return void 0===n&&(n=new Set,t.set(e,n)),n}_getShaderStage(e){const t=this.shaderCache;let n=t.get(e);return void 0===n&&(n=new Mm(e),t.set(e,n)),n}}class Mm{constructor(e){this.id=wm++,this.code=e,this.usedTimes=0}}function Em(e,t,n,i,r,s,o){const a=new Fo,l=new Cm,u=new Set,c=[],d=r.logarithmicDepthBuffer,h=r.vertexTextures;let f=r.precision;const p={MeshDepthMaterial:"depth",MeshDistanceMaterial:"distanceRGBA",MeshNormalMaterial:"normal",MeshBasicMaterial:"basic",MeshLambertMaterial:"lambert",MeshPhongMaterial:"phong",MeshToonMaterial:"toon",MeshStandardMaterial:"physical",MeshPhysicalMaterial:"physical",MeshMatcapMaterial:"matcap",LineBasicMaterial:"basic",LineDashedMaterial:"dashed",PointsMaterial:"points",ShadowMaterial:"shadow",SpriteMaterial:"sprite"};function g(e){return u.add(e),0===e?"uv":`uv${e}`}return{getParameters:function(s,a,c,m,v){const A=m.fog,x=v.geometry,y=s.isMeshStandardMaterial?m.environment:null,b=(s.isMeshStandardMaterial?n:t).get(s.envMap||y),w=b&&b.mapping===Li?b.image.height:null,C=p[s.type];null!==s.precision&&(f=r.getMaxPrecision(s.precision),f!==s.precision&&console.warn("THREE.WebGLProgram.getParameters:",s.precision,"not supported, using",f,"instead."));const M=x.morphAttributes.position||x.morphAttributes.normal||x.morphAttributes.color,E=void 0!==M?M.length:0;let T,S,P,N,B=0;if(void 0!==x.morphAttributes.position&&(B=1),void 0!==x.morphAttributes.normal&&(B=2),void 0!==x.morphAttributes.color&&(B=3),C){const e=mp[C];T=e.vertexShader,S=e.fragmentShader}else T=s.vertexShader,S=s.fragmentShader,l.update(s),P=l.getVertexShaderID(s),N=l.getFragmentShaderID(s);const D=e.getRenderTarget(),I=e.state.buffers.depth.getReversed(),L=!0===v.isInstancedMesh,j=!0===v.isBatchedMesh,O=!!s.map,z=!!s.matcap,R=!!b,k=!!s.aoMap,F=!!s.lightMap,H=!!s.bumpMap,U=!!s.normalMap,X=!!s.displacementMap,G=!!s.emissiveMap,V=!!s.metalnessMap,W=!!s.roughnessMap,Q=s.anisotropy>0,Z=s.clearcoat>0,Y=s.dispersion>0,J=s.iridescence>0,K=s.sheen>0,q=s.transmission>0,_=Q&&!!s.anisotropyMap,$=Z&&!!s.clearcoatMap,ee=Z&&!!s.clearcoatNormalMap,te=Z&&!!s.clearcoatRoughnessMap,ne=J&&!!s.iridescenceMap,ie=J&&!!s.iridescenceThicknessMap,re=K&&!!s.sheenColorMap,se=K&&!!s.sheenRoughnessMap,oe=!!s.specularMap,ae=!!s.specularColorMap,le=!!s.specularIntensityMap,ue=q&&!!s.transmissionMap,ce=q&&!!s.thicknessMap,de=!!s.gradientMap,he=!!s.alphaMap,fe=s.alphaTest>0,pe=!!s.alphaHash,ge=!!s.extensions;let me=0;s.toneMapped&&(null!==D&&!0!==D.isXRRenderTarget||(me=e.toneMapping));const ve={shaderID:C,shaderType:s.type,shaderName:s.name,vertexShader:T,fragmentShader:S,defines:s.defines,customVertexShaderID:P,customFragmentShaderID:N,isRawShaderMaterial:!0===s.isRawShaderMaterial,glslVersion:s.glslVersion,precision:f,batching:j,batchingColor:j&&null!==v._colorsTexture,instancing:L,instancingColor:L&&null!==v.instanceColor,instancingMorph:L&&null!==v.morphTexture,supportsVertexTextures:h,outputColorSpace:null===D?e.outputColorSpace:!0===D.isXRRenderTarget?D.texture.colorSpace:_r,alphaToCoverage:!!s.alphaToCoverage,map:O,matcap:z,envMap:R,envMapMode:R&&b.mapping,envMapCubeUVHeight:w,aoMap:k,lightMap:F,bumpMap:H,normalMap:U,displacementMap:h&&X,emissiveMap:G,normalMapObjectSpace:U&&1===s.normalMapType,normalMapTangentSpace:U&&0===s.normalMapType,metalnessMap:V,roughnessMap:W,anisotropy:Q,anisotropyMap:_,clearcoat:Z,clearcoatMap:$,clearcoatNormalMap:ee,clearcoatRoughnessMap:te,dispersion:Y,iridescence:J,iridescenceMap:ne,iridescenceThicknessMap:ie,sheen:K,sheenColorMap:re,sheenRoughnessMap:se,specularMap:oe,specularColorMap:ae,specularIntensityMap:le,transmission:q,transmissionMap:ue,thicknessMap:ce,gradientMap:de,opaque:!1===s.transparent&&1===s.blending&&!1===s.alphaToCoverage,alphaMap:he,alphaTest:fe,alphaHash:pe,combine:s.combine,mapUv:O&&g(s.map.channel),aoMapUv:k&&g(s.aoMap.channel),lightMapUv:F&&g(s.lightMap.channel),bumpMapUv:H&&g(s.bumpMap.channel),normalMapUv:U&&g(s.normalMap.channel),displacementMapUv:X&&g(s.displacementMap.channel),emissiveMapUv:G&&g(s.emissiveMap.channel),metalnessMapUv:V&&g(s.metalnessMap.channel),roughnessMapUv:W&&g(s.roughnessMap.channel),anisotropyMapUv:_&&g(s.anisotropyMap.channel),clearcoatMapUv:$&&g(s.clearcoatMap.channel),clearcoatNormalMapUv:ee&&g(s.clearcoatNormalMap.channel),clearcoatRoughnessMapUv:te&&g(s.clearcoatRoughnessMap.channel),iridescenceMapUv:ne&&g(s.iridescenceMap.channel),iridescenceThicknessMapUv:ie&&g(s.iridescenceThicknessMap.channel),sheenColorMapUv:re&&g(s.sheenColorMap.channel),sheenRoughnessMapUv:se&&g(s.sheenRoughnessMap.channel),specularMapUv:oe&&g(s.specularMap.channel),specularColorMapUv:ae&&g(s.specularColorMap.channel),specularIntensityMapUv:le&&g(s.specularIntensityMap.channel),transmissionMapUv:ue&&g(s.transmissionMap.channel),thicknessMapUv:ce&&g(s.thicknessMap.channel),alphaMapUv:he&&g(s.alphaMap.channel),vertexTangents:!!x.attributes.tangent&&(U||Q),vertexColors:s.vertexColors,vertexAlphas:!0===s.vertexColors&&!!x.attributes.color&&4===x.attributes.color.itemSize,pointsUvs:!0===v.isPoints&&!!x.attributes.uv&&(O||he),fog:!!A,useFog:!0===s.fog,fogExp2:!!A&&A.isFogExp2,flatShading:!0===s.flatShading&&!1===s.wireframe,sizeAttenuation:!0===s.sizeAttenuation,logarithmicDepthBuffer:d,reversedDepthBuffer:I,skinning:!0===v.isSkinnedMesh,morphTargets:void 0!==x.morphAttributes.position,morphNormals:void 0!==x.morphAttributes.normal,morphColors:void 0!==x.morphAttributes.color,morphTargetsCount:E,morphTextureStride:B,numDirLights:a.directional.length,numPointLights:a.point.length,numSpotLights:a.spot.length,numSpotLightMaps:a.spotLightMap.length,numRectAreaLights:a.rectArea.length,numHemiLights:a.hemi.length,numDirLightShadows:a.directionalShadowMap.length,numPointLightShadows:a.pointShadowMap.length,numSpotLightShadows:a.spotShadowMap.length,numSpotLightShadowsWithMaps:a.numSpotLightShadowsWithMaps,numLightProbes:a.numLightProbes,numClippingPlanes:o.numPlanes,numClipIntersection:o.numIntersection,dithering:s.dithering,shadowMapEnabled:e.shadowMap.enabled&&c.length>0,shadowMapType:e.shadowMap.type,toneMapping:me,decodeVideoTexture:O&&!0===s.map.isVideoTexture&&ks.getTransfer(s.map.colorSpace)===es,decodeVideoTextureEmissive:G&&!0===s.emissiveMap.isVideoTexture&&ks.getTransfer(s.emissiveMap.colorSpace)===es,premultipliedAlpha:s.premultipliedAlpha,doubleSided:2===s.side,flipSided:1===s.side,useDepthPacking:s.depthPacking>=0,depthPacking:s.depthPacking||0,index0AttributeName:s.index0AttributeName,extensionClipCullDistance:ge&&!0===s.extensions.clipCullDistance&&i.has("WEBGL_clip_cull_distance"),extensionMultiDraw:(ge&&!0===s.extensions.multiDraw||j)&&i.has("WEBGL_multi_draw"),rendererExtensionParallelShaderCompile:i.has("KHR_parallel_shader_compile"),customProgramCacheKey:s.customProgramCacheKey()};return ve.vertexUv1s=u.has(1),ve.vertexUv2s=u.has(2),ve.vertexUv3s=u.has(3),u.clear(),ve},getProgramCacheKey:function(t){const n=[];if(t.shaderID?n.push(t.shaderID):(n.push(t.customVertexShaderID),n.push(t.customFragmentShaderID)),void 0!==t.defines)for(const e in t.defines)n.push(e),n.push(t.defines[e]);return!1===t.isRawShaderMaterial&&(!function(e,t){e.push(t.precision),e.push(t.outputColorSpace),e.push(t.envMapMode),e.push(t.envMapCubeUVHeight),e.push(t.mapUv),e.push(t.alphaMapUv),e.push(t.lightMapUv),e.push(t.aoMapUv),e.push(t.bumpMapUv),e.push(t.normalMapUv),e.push(t.displacementMapUv),e.push(t.emissiveMapUv),e.push(t.metalnessMapUv),e.push(t.roughnessMapUv),e.push(t.anisotropyMapUv),e.push(t.clearcoatMapUv),e.push(t.clearcoatNormalMapUv),e.push(t.clearcoatRoughnessMapUv),e.push(t.iridescenceMapUv),e.push(t.iridescenceThicknessMapUv),e.push(t.sheenColorMapUv),e.push(t.sheenRoughnessMapUv),e.push(t.specularMapUv),e.push(t.specularColorMapUv),e.push(t.specularIntensityMapUv),e.push(t.transmissionMapUv),e.push(t.thicknessMapUv),e.push(t.combine),e.push(t.fogExp2),e.push(t.sizeAttenuation),e.push(t.morphTargetsCount),e.push(t.morphAttributeCount),e.push(t.numDirLights),e.push(t.numPointLights),e.push(t.numSpotLights),e.push(t.numSpotLightMaps),e.push(t.numHemiLights),e.push(t.numRectAreaLights),e.push(t.numDirLightShadows),e.push(t.numPointLightShadows),e.push(t.numSpotLightShadows),e.push(t.numSpotLightShadowsWithMaps),e.push(t.numLightProbes),e.push(t.shadowMapType),e.push(t.toneMapping),e.push(t.numClippingPlanes),e.push(t.numClipIntersection),e.push(t.depthPacking)}(n,t),function(e,t){a.disableAll(),t.supportsVertexTextures&&a.enable(0);t.instancing&&a.enable(1);t.instancingColor&&a.enable(2);t.instancingMorph&&a.enable(3);t.matcap&&a.enable(4);t.envMap&&a.enable(5);t.normalMapObjectSpace&&a.enable(6);t.normalMapTangentSpace&&a.enable(7);t.clearcoat&&a.enable(8);t.iridescence&&a.enable(9);t.alphaTest&&a.enable(10);t.vertexColors&&a.enable(11);t.vertexAlphas&&a.enable(12);t.vertexUv1s&&a.enable(13);t.vertexUv2s&&a.enable(14);t.vertexUv3s&&a.enable(15);t.vertexTangents&&a.enable(16);t.anisotropy&&a.enable(17);t.alphaHash&&a.enable(18);t.batching&&a.enable(19);t.dispersion&&a.enable(20);t.batchingColor&&a.enable(21);t.gradientMap&&a.enable(22);e.push(a.mask),a.disableAll(),t.fog&&a.enable(0);t.useFog&&a.enable(1);t.flatShading&&a.enable(2);t.logarithmicDepthBuffer&&a.enable(3);t.reversedDepthBuffer&&a.enable(4);t.skinning&&a.enable(5);t.morphTargets&&a.enable(6);t.morphNormals&&a.enable(7);t.morphColors&&a.enable(8);t.premultipliedAlpha&&a.enable(9);t.shadowMapEnabled&&a.enable(10);t.doubleSided&&a.enable(11);t.flipSided&&a.enable(12);t.useDepthPacking&&a.enable(13);t.dithering&&a.enable(14);t.transmission&&a.enable(15);t.sheen&&a.enable(16);t.opaque&&a.enable(17);t.pointsUvs&&a.enable(18);t.decodeVideoTexture&&a.enable(19);t.decodeVideoTextureEmissive&&a.enable(20);t.alphaToCoverage&&a.enable(21);e.push(a.mask)}(n,t),n.push(e.outputColorSpace)),n.push(t.customProgramCacheKey),n.join()},getUniforms:function(e){const t=p[e.type];let n;if(t){const e=mp[t];n=ll.clone(e.uniforms)}else n=e.uniforms;return n},acquireProgram:function(t,n){let i;for(let e=0,t=c.length;e<t;e++){const t=c[e];if(t.cacheKey===n){i=t,++i.usedTimes;break}}return void 0===i&&(i=new bm(e,n,t,s),c.push(i)),i},releaseProgram:function(e){if(0==--e.usedTimes){const t=c.indexOf(e);c[t]=c[c.length-1],c.pop(),e.destroy()}},releaseShaderCache:function(e){l.remove(e)},programs:c,dispose:function(){l.dispose()}}}function Tm(){let e=new WeakMap;return{has:function(t){return e.has(t)},get:function(t){let n=e.get(t);return void 0===n&&(n={},e.set(t,n)),n},remove:function(t){e.delete(t)},update:function(t,n,i){e.get(t)[n]=i},dispose:function(){e=new WeakMap}}}function Sm(e,t){return e.groupOrder!==t.groupOrder?e.groupOrder-t.groupOrder:e.renderOrder!==t.renderOrder?e.renderOrder-t.renderOrder:e.material.id!==t.material.id?e.material.id-t.material.id:e.z!==t.z?e.z-t.z:e.id-t.id}function Pm(e,t){return e.groupOrder!==t.groupOrder?e.groupOrder-t.groupOrder:e.renderOrder!==t.renderOrder?e.renderOrder-t.renderOrder:e.z!==t.z?t.z-e.z:e.id-t.id}function Nm(){const e=[];let t=0;const n=[],i=[],r=[];function s(n,i,r,s,o,a){let l=e[t];return void 0===l?(l={id:n.id,object:n,geometry:i,material:r,groupOrder:s,renderOrder:n.renderOrder,z:o,group:a},e[t]=l):(l.id=n.id,l.object=n,l.geometry=i,l.material=r,l.groupOrder=s,l.renderOrder=n.renderOrder,l.z=o,l.group=a),t++,l}return{opaque:n,transmissive:i,transparent:r,init:function(){t=0,n.length=0,i.length=0,r.length=0},push:function(e,t,o,a,l,u){const c=s(e,t,o,a,l,u);o.transmission>0?i.push(c):!0===o.transparent?r.push(c):n.push(c)},unshift:function(e,t,o,a,l,u){const c=s(e,t,o,a,l,u);o.transmission>0?i.unshift(c):!0===o.transparent?r.unshift(c):n.unshift(c)},finish:function(){for(let n=t,i=e.length;n<i;n++){const t=e[n];if(null===t.id)break;t.id=null,t.object=null,t.geometry=null,t.material=null,t.group=null}},sort:function(e,t){n.length>1&&n.sort(e||Sm),i.length>1&&i.sort(t||Pm),r.length>1&&r.sort(t||Pm)}}}function Bm(){let e=new WeakMap;return{get:function(t,n){const i=e.get(t);let r;return void 0===i?(r=new Nm,e.set(t,[r])):n>=i.length?(r=new Nm,i.push(r)):r=i[n],r},dispose:function(){e=new WeakMap}}}function Dm(){const e={};return{get:function(t){if(void 0!==e[t.id])return e[t.id];let n;switch(t.type){case"DirectionalLight":n={direction:new Es,color:new ya};break;case"SpotLight":n={position:new Es,direction:new Es,color:new ya,distance:0,coneCos:0,penumbraCos:0,decay:0};break;case"PointLight":n={position:new Es,color:new ya,distance:0,decay:0};break;case"HemisphereLight":n={direction:new Es,skyColor:new ya,groundColor:new ya};break;case"RectAreaLight":n={color:new ya,position:new Es,halfWidth:new Es,halfHeight:new Es}}return e[t.id]=n,n}}}let Im=0;function Lm(e,t){return(t.castShadow?2:0)-(e.castShadow?2:0)+(t.map?1:0)-(e.map?1:0)}function jm(e){const t=new Dm,n=function(){const e={};return{get:function(t){if(void 0!==e[t.id])return e[t.id];let n;switch(t.type){case"DirectionalLight":case"SpotLight":n={shadowIntensity:1,shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new Cs};break;case"PointLight":n={shadowIntensity:1,shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new Cs,shadowCameraNear:1,shadowCameraFar:1e3}}return e[t.id]=n,n}}}(),i={version:0,hash:{directionalLength:-1,pointLength:-1,spotLength:-1,rectAreaLength:-1,hemiLength:-1,numDirectionalShadows:-1,numPointShadows:-1,numSpotShadows:-1,numSpotMaps:-1,numLightProbes:-1},ambient:[0,0,0],probe:[],directional:[],directionalShadow:[],directionalShadowMap:[],directionalShadowMatrix:[],spot:[],spotLightMap:[],spotShadow:[],spotShadowMap:[],spotLightMatrix:[],rectArea:[],rectAreaLTC1:null,rectAreaLTC2:null,point:[],pointShadow:[],pointShadowMap:[],pointShadowMatrix:[],hemi:[],numSpotLightShadowsWithMaps:0,numLightProbes:0};for(let e=0;e<9;e++)i.probe.push(new Es);const r=new Es,s=new Po,o=new Po;return{setup:function(r){let s=0,o=0,a=0;for(let e=0;e<9;e++)i.probe[e].set(0,0,0);let l=0,u=0,c=0,d=0,h=0,f=0,p=0,g=0,m=0,v=0,A=0;r.sort(Lm);for(let e=0,x=r.length;e<x;e++){const x=r[e],y=x.color,b=x.intensity,w=x.distance,C=x.shadow&&x.shadow.map?x.shadow.map.texture:null;if(x.isAmbientLight)s+=y.r*b,o+=y.g*b,a+=y.b*b;else if(x.isLightProbe){for(let e=0;e<9;e++)i.probe[e].addScaledVector(x.sh.coefficients[e],b);A++}else if(x.isDirectionalLight){const e=t.get(x);if(e.color.copy(x.color).multiplyScalar(x.intensity),x.castShadow){const e=x.shadow,t=n.get(x);t.shadowIntensity=e.intensity,t.shadowBias=e.bias,t.shadowNormalBias=e.normalBias,t.shadowRadius=e.radius,t.shadowMapSize=e.mapSize,i.directionalShadow[l]=t,i.directionalShadowMap[l]=C,i.directionalShadowMatrix[l]=x.shadow.matrix,f++}i.directional[l]=e,l++}else if(x.isSpotLight){const e=t.get(x);e.position.setFromMatrixPosition(x.matrixWorld),e.color.copy(y).multiplyScalar(b),e.distance=w,e.coneCos=Math.cos(x.angle),e.penumbraCos=Math.cos(x.angle*(1-x.penumbra)),e.decay=x.decay,i.spot[c]=e;const r=x.shadow;if(x.map&&(i.spotLightMap[m]=x.map,m++,r.updateMatrices(x),x.castShadow&&v++),i.spotLightMatrix[c]=r.matrix,x.castShadow){const e=n.get(x);e.shadowIntensity=r.intensity,e.shadowBias=r.bias,e.shadowNormalBias=r.normalBias,e.shadowRadius=r.radius,e.shadowMapSize=r.mapSize,i.spotShadow[c]=e,i.spotShadowMap[c]=C,g++}c++}else if(x.isRectAreaLight){const e=t.get(x);e.color.copy(y).multiplyScalar(b),e.halfWidth.set(.5*x.width,0,0),e.halfHeight.set(0,.5*x.height,0),i.rectArea[d]=e,d++}else if(x.isPointLight){const e=t.get(x);if(e.color.copy(x.color).multiplyScalar(x.intensity),e.distance=x.distance,e.decay=x.decay,x.castShadow){const e=x.shadow,t=n.get(x);t.shadowIntensity=e.intensity,t.shadowBias=e.bias,t.shadowNormalBias=e.normalBias,t.shadowRadius=e.radius,t.shadowMapSize=e.mapSize,t.shadowCameraNear=e.camera.near,t.shadowCameraFar=e.camera.far,i.pointShadow[u]=t,i.pointShadowMap[u]=C,i.pointShadowMatrix[u]=x.shadow.matrix,p++}i.point[u]=e,u++}else if(x.isHemisphereLight){const e=t.get(x);e.skyColor.copy(x.color).multiplyScalar(b),e.groundColor.copy(x.groundColor).multiplyScalar(b),i.hemi[h]=e,h++}}d>0&&(!0===e.has("OES_texture_float_linear")?(i.rectAreaLTC1=gp.LTC_FLOAT_1,i.rectAreaLTC2=gp.LTC_FLOAT_2):(i.rectAreaLTC1=gp.LTC_HALF_1,i.rectAreaLTC2=gp.LTC_HALF_2)),i.ambient[0]=s,i.ambient[1]=o,i.ambient[2]=a;const x=i.hash;x.directionalLength===l&&x.pointLength===u&&x.spotLength===c&&x.rectAreaLength===d&&x.hemiLength===h&&x.numDirectionalShadows===f&&x.numPointShadows===p&&x.numSpotShadows===g&&x.numSpotMaps===m&&x.numLightProbes===A||(i.directional.length=l,i.spot.length=c,i.rectArea.length=d,i.point.length=u,i.hemi.length=h,i.directionalShadow.length=f,i.directionalShadowMap.length=f,i.pointShadow.length=p,i.pointShadowMap.length=p,i.spotShadow.length=g,i.spotShadowMap.length=g,i.directionalShadowMatrix.length=f,i.pointShadowMatrix.length=p,i.spotLightMatrix.length=g+m-v,i.spotLightMap.length=m,i.numSpotLightShadowsWithMaps=v,i.numLightProbes=A,x.directionalLength=l,x.pointLength=u,x.spotLength=c,x.rectAreaLength=d,x.hemiLength=h,x.numDirectionalShadows=f,x.numPointShadows=p,x.numSpotShadows=g,x.numSpotMaps=m,x.numLightProbes=A,i.version=Im++)},setupView:function(e,t){let n=0,a=0,l=0,u=0,c=0;const d=t.matrixWorldInverse;for(let t=0,h=e.length;t<h;t++){const h=e[t];if(h.isDirectionalLight){const e=i.directional[n];e.direction.setFromMatrixPosition(h.matrixWorld),r.setFromMatrixPosition(h.target.matrixWorld),e.direction.sub(r),e.direction.transformDirection(d),n++}else if(h.isSpotLight){const e=i.spot[l];e.position.setFromMatrixPosition(h.matrixWorld),e.position.applyMatrix4(d),e.direction.setFromMatrixPosition(h.matrixWorld),r.setFromMatrixPosition(h.target.matrixWorld),e.direction.sub(r),e.direction.transformDirection(d),l++}else if(h.isRectAreaLight){const e=i.rectArea[u];e.position.setFromMatrixPosition(h.matrixWorld),e.position.applyMatrix4(d),o.identity(),s.copy(h.matrixWorld),s.premultiply(d),o.extractRotation(s),e.halfWidth.set(.5*h.width,0,0),e.halfHeight.set(0,.5*h.height,0),e.halfWidth.applyMatrix4(o),e.halfHeight.applyMatrix4(o),u++}else if(h.isPointLight){const e=i.point[a];e.position.setFromMatrixPosition(h.matrixWorld),e.position.applyMatrix4(d),a++}else if(h.isHemisphereLight){const e=i.hemi[c];e.direction.setFromMatrixPosition(h.matrixWorld),e.direction.transformDirection(d),c++}}},state:i}}function Om(e){const t=new jm(e),n=[],i=[];const r={lightsArray:n,shadowsArray:i,camera:null,lights:t,transmissionRenderTarget:{}};return{init:function(e){r.camera=e,n.length=0,i.length=0},state:r,setupLights:function(){t.setup(n)},setupLightsView:function(e){t.setupView(n,e)},pushLight:function(e){n.push(e)},pushShadow:function(e){i.push(e)}}}function zm(e){let t=new WeakMap;return{get:function(n,i=0){const r=t.get(n);let s;return void 0===r?(s=new Om(e),t.set(n,[s])):i>=r.length?(s=new Om(e),r.push(s)):s=r[i],s},dispose:function(){t=new WeakMap}}}function Rm(e,t,n){let i=new zl;const r=new Cs,s=new Cs,o=new Js,a=new Nu({depthPacking:3201}),l=new Bu,u={},c=n.maxTextureSize,d={0:1,1:0,2:2},h=new ul({defines:{VSM_SAMPLES:8},uniforms:{shadow_pass:{value:null},resolution:{value:new Cs},radius:{value:4}},vertexShader:"void main() {\n\tgl_Position = vec4( position, 1.0 );\n}",fragmentShader:"uniform sampler2D shadow_pass;\nuniform vec2 resolution;\nuniform float radius;\n#include <packing>\nvoid main() {\n\tconst float samples = float( VSM_SAMPLES );\n\tfloat mean = 0.0;\n\tfloat squared_mean = 0.0;\n\tfloat uvStride = samples <= 1.0 ? 0.0 : 2.0 / ( samples - 1.0 );\n\tfloat uvStart = samples <= 1.0 ? 0.0 : - 1.0;\n\tfor ( float i = 0.0; i < samples; i ++ ) {\n\t\tfloat uvOffset = uvStart + i * uvStride;\n\t\t#ifdef HORIZONTAL_PASS\n\t\t\tvec2 distribution = unpackRGBATo2Half( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( uvOffset, 0.0 ) * radius ) / resolution ) );\n\t\t\tmean += distribution.x;\n\t\t\tsquared_mean += distribution.y * distribution.y + distribution.x * distribution.x;\n\t\t#else\n\t\t\tfloat depth = unpackRGBAToDepth( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( 0.0, uvOffset ) * radius ) / resolution ) );\n\t\t\tmean += depth;\n\t\t\tsquared_mean += depth * depth;\n\t\t#endif\n\t}\n\tmean = mean / samples;\n\tsquared_mean = squared_mean / samples;\n\tfloat std_dev = sqrt( squared_mean - mean * mean );\n\tgl_FragColor = pack2HalfToRGBA( vec2( mean, std_dev ) );\n}"}),f=h.clone();f.defines.HORIZONTAL_PASS=1;const p=new Va;p.setAttribute("position",new Ia(new Float32Array([-1,-1,.5,3,-1,.5,-1,3,.5]),3));const g=new nl(p,h),m=this;this.enabled=!1,this.autoUpdate=!0,this.needsUpdate=!1,this.type=1;let v=this.type;function A(n,i){const s=t.update(g);h.defines.VSM_SAMPLES!==n.blurSamples&&(h.defines.VSM_SAMPLES=n.blurSamples,f.defines.VSM_SAMPLES=n.blurSamples,h.needsUpdate=!0,f.needsUpdate=!0),null===n.mapPass&&(n.mapPass=new qs(r.x,r.y)),h.uniforms.shadow_pass.value=n.map.texture,h.uniforms.resolution.value=n.mapSize,h.uniforms.radius.value=n.radius,e.setRenderTarget(n.mapPass),e.clear(),e.renderBufferDirect(i,null,s,h,g,null),f.uniforms.shadow_pass.value=n.mapPass.texture,f.uniforms.resolution.value=n.mapSize,f.uniforms.radius.value=n.radius,e.setRenderTarget(n.map),e.clear(),e.renderBufferDirect(i,null,s,f,g,null)}function x(t,n,i,r){let s=null;const o=!0===i.isPointLight?t.customDistanceMaterial:t.customDepthMaterial;if(void 0!==o)s=o;else if(s=!0===i.isPointLight?l:a,e.localClippingEnabled&&!0===n.clipShadows&&Array.isArray(n.clippingPlanes)&&0!==n.clippingPlanes.length||n.displacementMap&&0!==n.displacementScale||n.alphaMap&&n.alphaTest>0||n.map&&n.alphaTest>0||!0===n.alphaToCoverage){const e=s.uuid,t=n.uuid;let i=u[e];void 0===i&&(i={},u[e]=i);let r=i[t];void 0===r&&(r=s.clone(),i[t]=r,n.addEventListener("dispose",b)),s=r}if(s.visible=n.visible,s.wireframe=n.wireframe,s.side=3===r?null!==n.shadowSide?n.shadowSide:n.side:null!==n.shadowSide?n.shadowSide:d[n.side],s.alphaMap=n.alphaMap,s.alphaTest=!0===n.alphaToCoverage?.5:n.alphaTest,s.map=n.map,s.clipShadows=n.clipShadows,s.clippingPlanes=n.clippingPlanes,s.clipIntersection=n.clipIntersection,s.displacementMap=n.displacementMap,s.displacementScale=n.displacementScale,s.displacementBias=n.displacementBias,s.wireframeLinewidth=n.wireframeLinewidth,s.linewidth=n.linewidth,!0===i.isPointLight&&!0===s.isMeshDistanceMaterial){e.properties.get(s).light=i}return s}function y(n,r,s,o,a){if(!1===n.visible)return;if(n.layers.test(r.layers)&&(n.isMesh||n.isLine||n.isPoints)&&(n.castShadow||n.receiveShadow&&3===a)&&(!n.frustumCulled||i.intersectsObject(n))){n.modelViewMatrix.multiplyMatrices(s.matrixWorldInverse,n.matrixWorld);const i=t.update(n),l=n.material;if(Array.isArray(l)){const t=i.groups;for(let u=0,c=t.length;u<c;u++){const c=t[u],d=l[c.materialIndex];if(d&&d.visible){const t=x(n,d,o,a);n.onBeforeShadow(e,n,r,s,i,t,c),e.renderBufferDirect(s,null,i,t,n,c),n.onAfterShadow(e,n,r,s,i,t,c)}}}else if(l.visible){const t=x(n,l,o,a);n.onBeforeShadow(e,n,r,s,i,t,null),e.renderBufferDirect(s,null,i,t,n,null),n.onAfterShadow(e,n,r,s,i,t,null)}}const l=n.children;for(let e=0,t=l.length;e<t;e++)y(l[e],r,s,o,a)}function b(e){e.target.removeEventListener("dispose",b);for(const t in u){const n=u[t],i=e.target.uuid;if(i in n){n[i].dispose(),delete n[i]}}}this.render=function(t,n,a){if(!1===m.enabled)return;if(!1===m.autoUpdate&&!1===m.needsUpdate)return;if(0===t.length)return;const l=e.getRenderTarget(),u=e.getActiveCubeFace(),d=e.getActiveMipmapLevel(),h=e.state;h.setBlending(0),!0===h.buffers.depth.getReversed()?h.buffers.color.setClear(0,0,0,0):h.buffers.color.setClear(1,1,1,1),h.buffers.depth.setTest(!0),h.setScissorTest(!1);const f=3!==v&&3===this.type,p=3===v&&3!==this.type;for(let l=0,u=t.length;l<u;l++){const u=t[l],d=u.shadow;if(void 0===d){console.warn("THREE.WebGLShadowMap:",u,"has no shadow.");continue}if(!1===d.autoUpdate&&!1===d.needsUpdate)continue;r.copy(d.mapSize);const g=d.getFrameExtents();if(r.multiply(g),s.copy(d.mapSize),(r.x>c||r.y>c)&&(r.x>c&&(s.x=Math.floor(c/g.x),r.x=s.x*g.x,d.mapSize.x=s.x),r.y>c&&(s.y=Math.floor(c/g.y),r.y=s.y*g.y,d.mapSize.y=s.y)),null===d.map||!0===f||!0===p){const e=3!==this.type?{minFilter:Ri,magFilter:Ri}:{};null!==d.map&&d.map.dispose(),d.map=new qs(r.x,r.y,e),d.map.texture.name=u.name+".shadowMap",d.camera.updateProjectionMatrix()}e.setRenderTarget(d.map),e.clear();const m=d.getViewportCount();for(let e=0;e<m;e++){const 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u=D(t,o),c=o.source;n.bindTexture(l,t.__webglTexture,e.TEXTURE0+a);const d=i.get(c);if(c.version!==d.__version||!0===u){n.activeTexture(e.TEXTURE0+a);const t=ks.getPrimaries(ks.workingColorSpace),i=o.colorSpace===Kr?null:ks.getPrimaries(o.colorSpace),h=o.colorSpace===Kr||t===i?e.NONE:e.BROWSER_DEFAULT_WEBGL;e.pixelStorei(e.UNPACK_FLIP_Y_WEBGL,o.flipY),e.pixelStorei(e.UNPACK_PREMULTIPLY_ALPHA_WEBGL,o.premultiplyAlpha),e.pixelStorei(e.UNPACK_ALIGNMENT,o.unpackAlignment),e.pixelStorei(e.UNPACK_COLORSPACE_CONVERSION_WEBGL,h);let f=g(o.image,!1,r.maxTextureSize);f=X(o,f);const p=s.convert(o.format,o.colorSpace),A=s.convert(o.type);let w,C=x(o.internalFormat,p,A,o.colorSpace,o.isVideoTexture);B(l,o);const M=o.mipmaps,E=!0!==o.isVideoTexture,T=void 0===d.__version||!0===u,S=c.dataReady,P=b(o,f);if(o.isDepthTexture)C=y(o.format===or,o.type),T&&(E?n.texStorage2D(e.TEXTURE_2D,1,C,f.width,f.height):n.texImage2D(e.TEXTURE_2D,0,C,f.width,f.height,0,p,A,null));else if(o.isDataTexture)if(M.length>0){E&&T&&n.texStorage2D(e.TEXTURE_2D,P,C,M[0].width,M[0].height);for(let t=0,i=M.length;t<i;t++)w=M[t],E?S&&n.texSubImage2D(e.TEXTURE_2D,t,0,0,w.width,w.height,p,A,w.data):n.texImage2D(e.TEXTURE_2D,t,C,w.width,w.height,0,p,A,w.data);o.generateMipmaps=!1}else E?(T&&n.texStorage2D(e.TEXTURE_2D,P,C,f.width,f.height),S&&function(t,i,r,s){const o=t.updateRanges;if(0===o.length)n.texSubImage2D(e.TEXTURE_2D,0,0,0,i.width,i.height,r,s,i.data);else{o.sort(((e,t)=>e.start-t.start));let a=0;for(let e=1;e<o.length;e++){const t=o[a],n=o[e],r=t.start+t.count,s=I(n.start,i.width,4),l=I(t.start,i.width,4);n.start<=r+1&&s===l&&I(n.start+n.count-1,i.width,4)===s?t.count=Math.max(t.count,n.start+n.count-t.start):(++a,o[a]=n)}o.length=a+1;const l=e.getParameter(e.UNPACK_ROW_LENGTH),u=e.getParameter(e.UNPACK_SKIP_PIXELS),c=e.getParameter(e.UNPACK_SKIP_ROWS);e.pixelStorei(e.UNPACK_ROW_LENGTH,i.width);for(let t=0,a=o.length;t<a;t++){const a=o[t],l=Math.floor(a.start/4),u=Math.ceil(a.count/4),c=l%i.width,d=Math.floor(l/i.width),h=u,f=1;e.pixelStorei(e.UNPACK_SKIP_PIXELS,c),e.pixelStorei(e.UNPACK_SKIP_ROWS,d),n.texSubImage2D(e.TEXTURE_2D,0,c,d,h,f,r,s,i.data)}t.clearUpdateRanges(),e.pixelStorei(e.UNPACK_ROW_LENGTH,l),e.pixelStorei(e.UNPACK_SKIP_PIXELS,u),e.pixelStorei(e.UNPACK_SKIP_ROWS,c)}}(o,f,p,A)):n.texImage2D(e.TEXTURE_2D,0,C,f.width,f.height,0,p,A,f.data);else if(o.isCompressedTexture)if(o.isCompressedArrayTexture){E&&T&&n.texStorage3D(e.TEXTURE_2D_ARRAY,P,C,M[0].width,M[0].height,f.depth);for(let t=0,i=M.length;t<i;t++)if(w=M[t],o.format!==rr)if(null!==p)if(E){if(S)if(o.layerUpdates.size>0){const i=zc(w.width,w.height,o.format,o.type);for(const r of o.layerUpdates){const s=w.data.subarray(r*i/w.data.BYTES_PER_ELEMENT,(r+1)*i/w.data.BYTES_PER_ELEMENT);n.compressedTexSubImage3D(e.TEXTURE_2D_ARRAY,t,0,0,r,w.width,w.height,1,p,s)}o.clearLayerUpdates()}else n.compressedTexSubImage3D(e.TEXTURE_2D_ARRAY,t,0,0,0,w.width,w.height,f.depth,p,w.data)}else n.compressedTexImage3D(e.TEXTURE_2D_ARRAY,t,C,w.width,w.height,f.depth,0,w.data,0,0);else console.warn("THREE.WebGLRenderer: Attempt to load unsupported compressed texture format in .uploadTexture()");else E?S&&n.texSubImage3D(e.TEXTURE_2D_ARRAY,t,0,0,0,w.width,w.height,f.depth,p,A,w.data):n.texImage3D(e.TEXTURE_2D_ARRAY,t,C,w.width,w.height,f.depth,0,p,A,w.data)}else{E&&T&&n.texStorage2D(e.TEXTURE_2D,P,C,M[0].width,M[0].height);for(let t=0,i=M.length;t<i;t++)w=M[t],o.format!==rr?null!==p?E?S&&n.compressedTexSubImage2D(e.TEXTURE_2D,t,0,0,w.width,w.height,p,w.data):n.compressedTexImage2D(e.TEXTURE_2D,t,C,w.width,w.height,0,w.data):console.warn("THREE.WebGLRenderer: Attempt to load unsupported compressed texture format in .uploadTexture()"):E?S&&n.texSubImage2D(e.TEXTURE_2D,t,0,0,w.width,w.height,p,A,w.data):n.texImage2D(e.TEXTURE_2D,t,C,w.width,w.height,0,p,A,w.data)}else if(o.isDataArrayTexture)if(E){if(T&&n.texStorage3D(e.TEXTURE_2D_ARRAY,P,C,f.width,f.height,f.depth),S)if(o.layerUpdates.size>0){const t=zc(f.width,f.height,o.format,o.type);for(const i of o.layerUpdates){const r=f.data.subarray(i*t/f.data.BYTES_PER_ELEMENT,(i+1)*t/f.data.BYTES_PER_ELEMENT);n.texSubImage3D(e.TEXTURE_2D_ARRAY,0,0,0,i,f.width,f.height,1,p,A,r)}o.clearLayerUpdates()}else n.texSubImage3D(e.TEXTURE_2D_ARRAY,0,0,0,0,f.width,f.height,f.depth,p,A,f.data)}else n.texImage3D(e.TEXTURE_2D_ARRAY,0,C,f.width,f.height,f.depth,0,p,A,f.data);else if(o.isData3DTexture)E?(T&&n.texStorage3D(e.TEXTURE_3D,P,C,f.width,f.height,f.depth),S&&n.texSubImage3D(e.TEXTURE_3D,0,0,0,0,f.width,f.height,f.depth,p,A,f.data)):n.texImage3D(e.TEXTURE_3D,0,C,f.width,f.height,f.depth,0,p,A,f.data);else if(o.isFramebufferTexture){if(T)if(E)n.texStorage2D(e.TEXTURE_2D,P,C,f.width,f.height);else{let t=f.width,i=f.height;for(let r=0;r<P;r++)n.texImage2D(e.TEXTURE_2D,r,C,t,i,0,p,A,null),t>>=1,i>>=1}}else if(M.length>0){if(E&&T){const t=G(M[0]);n.texStorage2D(e.TEXTURE_2D,P,C,t.width,t.height)}for(let t=0,i=M.length;t<i;t++)w=M[t],E?S&&n.texSubImage2D(e.TEXTURE_2D,t,0,0,p,A,w):n.texImage2D(e.TEXTURE_2D,t,C,p,A,w);o.generateMipmaps=!1}else if(E){if(T){const t=G(f);n.texStorage2D(e.TEXTURE_2D,P,C,t.width,t.height)}S&&n.texSubImage2D(e.TEXTURE_2D,0,0,0,p,A,f)}else n.texImage2D(e.TEXTURE_2D,0,C,p,A,f);m(o)&&v(l),d.__version=c.version,o.onUpdate&&o.onUpdate(o)}t.__version=o.version}function j(t,r,o,l,u,c){const d=s.convert(o.format,o.colorSpace),h=s.convert(o.type),f=x(o.internalFormat,d,h,o.colorSpace),p=i.get(r),g=i.get(o);if(g.__renderTarget=r,!p.__hasExternalTextures){const t=Math.max(1,r.width>>c),i=Math.max(1,r.height>>c);u===e.TEXTURE_3D||u===e.TEXTURE_2D_ARRAY?n.texImage3D(u,c,f,t,i,r.depth,0,d,h,null):n.texImage2D(u,c,f,t,i,0,d,h,null)}n.bindFramebuffer(e.FRAMEBUFFER,t),U(r)?a.framebufferTexture2DMultisampleEXT(e.FRAMEBUFFER,l,u,g.__webglTexture,0,H(r)):(u===e.TEXTURE_2D||u>=e.TEXTURE_CUBE_MAP_POSITIVE_X&&u<=e.TEXTURE_CUBE_MAP_NEGATIVE_Z)&&e.framebufferTexture2D(e.FRAMEBUFFER,l,u,g.__webglTexture,c),n.bindFramebuffer(e.FRAMEBUFFER,null)}function O(t,n,i){if(e.bindRenderbuffer(e.RENDERBUFFER,t),n.depthBuffer){const r=n.depthTexture,s=r&&r.isDepthTexture?r.type:null,o=y(n.stencilBuffer,s),l=n.stencilBuffer?e.DEPTH_STENCIL_ATTACHMENT:e.DEPTH_ATTACHMENT,u=H(n);U(n)?a.renderbufferStorageMultisampleEXT(e.RENDERBUFFER,u,o,n.width,n.height):i?e.renderbufferStorageMultisample(e.RENDERBUFFER,u,o,n.width,n.height):e.renderbufferStorage(e.RENDERBUFFER,o,n.width,n.height),e.framebufferRenderbuffer(e.FRAMEBUFFER,l,e.RENDERBUFFER,t)}else{const t=n.textures;for(let r=0;r<t.length;r++){const o=t[r],l=s.convert(o.format,o.colorSpace),u=s.convert(o.type),c=x(o.internalFormat,l,u,o.colorSpace),d=H(n);i&&!1===U(n)?e.renderbufferStorageMultisample(e.RENDERBUFFER,d,c,n.width,n.height):U(n)?a.renderbufferStorageMultisampleEXT(e.RENDERBUFFER,d,c,n.width,n.height):e.renderbufferStorage(e.RENDERBUFFER,c,n.width,n.height)}}e.bindRenderbuffer(e.RENDERBUFFER,null)}function z(t,r){if(r&&r.isWebGLCubeRenderTarget)throw new Error("Depth Texture with cube render targets is not supported");if(n.bindFramebuffer(e.FRAMEBUFFER,t),!r.depthTexture||!r.depthTexture.isDepthTexture)throw new Error("renderTarget.depthTexture must be an instance of THREE.DepthTexture");const s=i.get(r.depthTexture);s.__renderTarget=r,s.__webglTexture&&r.depthTexture.image.width===r.width&&r.depthTexture.image.height===r.height||(r.depthTexture.image.width=r.width,r.depthTexture.image.height=r.height,r.depthTexture.needsUpdate=!0),T(r.depthTexture,0);const o=s.__webglTexture,l=H(r);if(r.depthTexture.format===sr)U(r)?a.framebufferTexture2DMultisampleEXT(e.FRAMEBUFFER,e.DEPTH_ATTACHMENT,e.TEXTURE_2D,o,0,l):e.framebufferTexture2D(e.FRAMEBUFFER,e.DEPTH_ATTACHMENT,e.TEXTURE_2D,o,0);else{if(r.depthTexture.format!==or)throw new Error("Unknown depthTexture format");U(r)?a.framebufferTexture2DMultisampleEXT(e.FRAMEBUFFER,e.DEPTH_STENCIL_ATTACHMENT,e.TEXTURE_2D,o,0,l):e.framebufferTexture2D(e.FRAMEBUFFER,e.DEPTH_STENCIL_ATTACHMENT,e.TEXTURE_2D,o,0)}}function R(t){const r=i.get(t),s=!0===t.isWebGLCubeRenderTarget;if(r.__boundDepthTexture!==t.depthTexture){const e=t.depthTexture;if(r.__depthDisposeCallback&&r.__depthDisposeCallback(),e){const t=()=>{delete r.__boundDepthTexture,delete r.__depthDisposeCallback,e.removeEventListener("dispose",t)};e.addEventListener("dispose",t),r.__depthDisposeCallback=t}r.__boundDepthTexture=e}if(t.depthTexture&&!r.__autoAllocateDepthBuffer){if(s)throw new Error("target.depthTexture not supported in Cube render 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n=t.stencilBuffer?e.DEPTH_STENCIL_ATTACHMENT:e.DEPTH_ATTACHMENT,i=r.__webglDepthbuffer;e.bindRenderbuffer(e.RENDERBUFFER,i),e.framebufferRenderbuffer(e.FRAMEBUFFER,n,e.RENDERBUFFER,i)}}n.bindFramebuffer(e.FRAMEBUFFER,null)}const k=[],F=[];function H(e){return Math.min(r.maxSamples,e.samples)}function U(e){const n=i.get(e);return e.samples>0&&!0===t.has("WEBGL_multisampled_render_to_texture")&&!1!==n.__useRenderToTexture}function X(e,t){const n=e.colorSpace,i=e.format,r=e.type;return!0===e.isCompressedTexture||!0===e.isVideoTexture||n!==_r&&n!==Kr&&(ks.getTransfer(n)===es?i===rr&&r===Gi||console.warn("THREE.WebGLTextures: sRGB encoded textures have to use RGBAFormat and UnsignedByteType."):console.error("THREE.WebGLTextures: Unsupported texture color space:",n)),t}function G(e){return"undefined"!=typeof HTMLImageElement&&e instanceof HTMLImageElement?(u.width=e.naturalWidth||e.width,u.height=e.naturalHeight||e.height):"undefined"!=typeof VideoFrame&&e instanceof VideoFrame?(u.width=e.displayWidth,u.height=e.displayHeight):(u.width=e.width,u.height=e.height),u}this.allocateTextureUnit=function(){const e=E;return e>=r.maxTextures&&console.warn("THREE.WebGLTextures: Trying to use "+e+" texture units while this GPU supports only "+r.maxTextures),E+=1,e},this.resetTextureUnits=function(){E=0},this.setTexture2D=T,this.setTexture2DArray=function(t,r){const s=i.get(t);!1===t.isRenderTargetTexture&&t.version>0&&s.__version!==t.version?L(s,t,r):n.bindTexture(e.TEXTURE_2D_ARRAY,s.__webglTexture,e.TEXTURE0+r)},this.setTexture3D=function(t,r){const s=i.get(t);!1===t.isRenderTargetTexture&&t.version>0&&s.__version!==t.version?L(s,t,r):n.bindTexture(e.TEXTURE_3D,s.__webglTexture,e.TEXTURE0+r)},this.setTextureCube=function(t,o){const a=i.get(t);t.version>0&&a.__version!==t.version?function(t,o,a){if(6!==o.image.length)return;const l=D(t,o),u=o.source;n.bindTexture(e.TEXTURE_CUBE_MAP,t.__webglTexture,e.TEXTURE0+a);const c=i.get(u);if(u.version!==c.__version||!0===l){n.activeTexture(e.TEXTURE0+a);const t=ks.getPrimaries(ks.workingColorSpace),i=o.colorSpace===Kr?null:ks.getPrimaries(o.colorSpace),d=o.colorSpace===Kr||t===i?e.NONE:e.BROWSER_DEFAULT_WEBGL;e.pixelStorei(e.UNPACK_FLIP_Y_WEBGL,o.flipY),e.pixelStorei(e.UNPACK_PREMULTIPLY_ALPHA_WEBGL,o.premultiplyAlpha),e.pixelStorei(e.UNPACK_ALIGNMENT,o.unpackAlignment),e.pixelStorei(e.UNPACK_COLORSPACE_CONVERSION_WEBGL,d);const h=o.isCompressedTexture||o.image[0].isCompressedTexture,f=o.image[0]&&o.image[0].isDataTexture,p=[];for(let e=0;e<6;e++)p[e]=h||f?f?o.image[e].image:o.image[e]:g(o.image[e],!0,r.maxCubemapSize),p[e]=X(o,p[e]);const A=p[0],y=s.convert(o.format,o.colorSpace),w=s.convert(o.type),C=x(o.internalFormat,y,w,o.colorSpace),M=!0!==o.isVideoTexture,E=void 0===c.__version||!0===l,T=u.dataReady;let S,P=b(o,A);if(B(e.TEXTURE_CUBE_MAP,o),h){M&&E&&n.texStorage2D(e.TEXTURE_CUBE_MAP,P,C,A.width,A.height);for(let t=0;t<6;t++){S=p[t].mipmaps;for(let i=0;i<S.length;i++){const r=S[i];o.format!==rr?null!==y?M?T&&n.compressedTexSubImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,i,0,0,r.width,r.height,y,r.data):n.compressedTexImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,i,C,r.width,r.height,0,r.data):console.warn("THREE.WebGLRenderer: Attempt to load unsupported compressed texture format in .setTextureCube()"):M?T&&n.texSubImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,i,0,0,r.width,r.height,y,w,r.data):n.texImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,i,C,r.width,r.height,0,y,w,r.data)}}}else{if(S=o.mipmaps,M&&E){S.length>0&&P++;const t=G(p[0]);n.texStorage2D(e.TEXTURE_CUBE_MAP,P,C,t.width,t.height)}for(let t=0;t<6;t++)if(f){M?T&&n.texSubImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,0,0,0,p[t].width,p[t].height,y,w,p[t].data):n.texImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,0,C,p[t].width,p[t].height,0,y,w,p[t].data);for(let i=0;i<S.length;i++){const r=S[i].image[t].image;M?T&&n.texSubImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,i+1,0,0,r.width,r.height,y,w,r.data):n.texImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,i+1,C,r.width,r.height,0,y,w,r.data)}}else{M?T&&n.texSubImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,0,0,0,y,w,p[t]):n.texImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,0,C,y,w,p[t]);for(let i=0;i<S.length;i++){const r=S[i];M?T&&n.texSubImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,i+1,0,0,y,w,r.image[t]):n.texImage2D(e.TEXTURE_CUBE_MAP_POSITIVE_X+t,i+1,C,y,w,r.image[t])}}}m(o)&&v(e.TEXTURE_CUBE_MAP),c.__version=u.version,o.onUpdate&&o.onUpdate(o)}t.__version=o.version}(a,t,o):n.bindTexture(e.TEXTURE_CUBE_MAP,a.__webglTexture,e.TEXTURE0+o)},this.rebindTextures=function(t,n,r){const s=i.get(t);void 0!==n&&j(s.__webglFramebuffer,t,t.texture,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,0),void 0!==r&&R(t)},this.setupRenderTarget=function(t){const r=t.texture,a=i.get(t),l=i.get(r);t.addEventListener("dispose",C);const u=t.textures,c=!0===t.isWebGLCubeRenderTarget,d=u.length>1;if(d||(void 0===l.__webglTexture&&(l.__webglTexture=e.createTexture()),l.__version=r.version,o.memory.textures++),c){a.__webglFramebuffer=[];for(let t=0;t<6;t++)if(r.mipmaps&&r.mipmaps.length>0){a.__webglFramebuffer[t]=[];for(let n=0;n<r.mipmaps.length;n++)a.__webglFramebuffer[t][n]=e.createFramebuffer()}else a.__webglFramebuffer[t]=e.createFramebuffer()}else{if(r.mipmaps&&r.mipmaps.length>0){a.__webglFramebuffer=[];for(let t=0;t<r.mipmaps.length;t++)a.__webglFramebuffer[t]=e.createFramebuffer()}else a.__webglFramebuffer=e.createFramebuffer();if(d)for(let t=0,n=u.length;t<n;t++){const n=i.get(u[t]);void 0===n.__webglTexture&&(n.__webglTexture=e.createTexture(),o.memory.textures++)}if(t.samples>0&&!1===U(t)){a.__webglMultisampledFramebuffer=e.createFramebuffer(),a.__webglColorRenderbuffer=[],n.bindFramebuffer(e.FRAMEBUFFER,a.__webglMultisampledFramebuffer);for(let n=0;n<u.length;n++){const i=u[n];a.__webglColorRenderbuffer[n]=e.createRenderbuffer(),e.bindRenderbuffer(e.RENDERBUFFER,a.__webglColorRenderbuffer[n]);const r=s.convert(i.format,i.colorSpace),o=s.convert(i.type),l=x(i.internalFormat,r,o,i.colorSpace,!0===t.isXRRenderTarget),c=H(t);e.renderbufferStorageMultisample(e.RENDERBUFFER,c,l,t.width,t.height),e.framebufferRenderbuffer(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0+n,e.RENDERBUFFER,a.__webglColorRenderbuffer[n])}e.bindRenderbuffer(e.RENDERBUFFER,null),t.depthBuffer&&(a.__webglDepthRenderbuffer=e.createRenderbuffer(),O(a.__webglDepthRenderbuffer,t,!0)),n.bindFramebuffer(e.FRAMEBUFFER,null)}}if(c){n.bindTexture(e.TEXTURE_CUBE_MAP,l.__webglTexture),B(e.TEXTURE_CUBE_MAP,r);for(let n=0;n<6;n++)if(r.mipmaps&&r.mipmaps.length>0)for(let i=0;i<r.mipmaps.length;i++)j(a.__webglFramebuffer[n][i],t,r,e.COLOR_ATTACHMENT0,e.TEXTURE_CUBE_MAP_POSITIVE_X+n,i);else j(a.__webglFramebuffer[n],t,r,e.COLOR_ATTACHMENT0,e.TEXTURE_CUBE_MAP_POSITIVE_X+n,0);m(r)&&v(e.TEXTURE_CUBE_MAP),n.unbindTexture()}else if(d){for(let r=0,s=u.length;r<s;r++){const s=u[r],o=i.get(s);let l=e.TEXTURE_2D;(t.isWebGL3DRenderTarget||t.isWebGLArrayRenderTarget)&&(l=t.isWebGL3DRenderTarget?e.TEXTURE_3D:e.TEXTURE_2D_ARRAY),n.bindTexture(l,o.__webglTexture),B(l,s),j(a.__webglFramebuffer,t,s,e.COLOR_ATTACHMENT0+r,l,0),m(s)&&v(l)}n.unbindTexture()}else{let i=e.TEXTURE_2D;if((t.isWebGL3DRenderTarget||t.isWebGLArrayRenderTarget)&&(i=t.isWebGL3DRenderTarget?e.TEXTURE_3D:e.TEXTURE_2D_ARRAY),n.bindTexture(i,l.__webglTexture),B(i,r),r.mipmaps&&r.mipmaps.length>0)for(let n=0;n<r.mipmaps.length;n++)j(a.__webglFramebuffer[n],t,r,e.COLOR_ATTACHMENT0,i,n);else j(a.__webglFramebuffer,t,r,e.COLOR_ATTACHMENT0,i,0);m(r)&&v(i),n.unbindTexture()}t.depthBuffer&&R(t)},this.updateRenderTargetMipmap=function(e){const t=e.textures;for(let r=0,s=t.length;r<s;r++){const s=t[r];if(m(s)){const t=A(e),r=i.get(s).__webglTexture;n.bindTexture(t,r),v(t),n.unbindTexture()}}},this.updateMultisampleRenderTarget=function(t){if(t.samples>0)if(!1===U(t)){const r=t.textures,s=t.width,o=t.height;let a=e.COLOR_BUFFER_BIT;const u=t.stencilBuffer?e.DEPTH_STENCIL_ATTACHMENT:e.DEPTH_ATTACHMENT,c=i.get(t),d=r.length>1;if(d)for(let t=0;t<r.length;t++)n.bindFramebuffer(e.FRAMEBUFFER,c.__webglMultisampledFramebuffer),e.framebufferRenderbuffer(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0+t,e.RENDERBUFFER,null),n.bindFramebuffer(e.FRAMEBUFFER,c.__webglFramebuffer),e.framebufferTexture2D(e.DRAW_FRAMEBUFFER,e.COLOR_ATTACHMENT0+t,e.TEXTURE_2D,null,0);n.bindFramebuffer(e.READ_FRAMEBUFFER,c.__webglMultisampledFramebuffer);const h=t.texture.mipmaps;h&&h.length>0?n.bindFramebuffer(e.DRAW_FRAMEBUFFER,c.__webglFramebuffer[0]):n.bindFramebuffer(e.DRAW_FRAMEBUFFER,c.__webglFramebuffer);for(let n=0;n<r.length;n++){if(t.resolveDepthBuffer&&(t.depthBuffer&&(a|=e.DEPTH_BUFFER_BIT),t.stencilBuffer&&t.resolveStencilBuffer&&(a|=e.STENCIL_BUFFER_BIT)),d){e.framebufferRenderbuffer(e.READ_FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.RENDERBUFFER,c.__webglColorRenderbuffer[n]);const t=i.get(r[n]).__webglTexture;e.framebufferTexture2D(e.DRAW_FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0)}e.blitFramebuffer(0,0,s,o,0,0,s,o,a,e.NEAREST),!0===l&&(k.length=0,F.length=0,k.push(e.COLOR_ATTACHMENT0+n),t.depthBuffer&&!1===t.resolveDepthBuffer&&(k.push(u),F.push(u),e.invalidateFramebuffer(e.DRAW_FRAMEBUFFER,F)),e.invalidateFramebuffer(e.READ_FRAMEBUFFER,k))}if(n.bindFramebuffer(e.READ_FRAMEBUFFER,null),n.bindFramebuffer(e.DRAW_FRAMEBUFFER,null),d)for(let t=0;t<r.length;t++){n.bindFramebuffer(e.FRAMEBUFFER,c.__webglMultisampledFramebuffer),e.framebufferRenderbuffer(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0+t,e.RENDERBUFFER,c.__webglColorRenderbuffer[t]);const s=i.get(r[t]).__webglTexture;n.bindFramebuffer(e.FRAMEBUFFER,c.__webglFramebuffer),e.framebufferTexture2D(e.DRAW_FRAMEBUFFER,e.COLOR_ATTACHMENT0+t,e.TEXTURE_2D,s,0)}n.bindFramebuffer(e.DRAW_FRAMEBUFFER,c.__webglMultisampledFramebuffer)}else if(t.depthBuffer&&!1===t.resolveDepthBuffer&&l){const n=t.stencilBuffer?e.DEPTH_STENCIL_ATTACHMENT:e.DEPTH_ATTACHMENT;e.invalidateFramebuffer(e.DRAW_FRAMEBUFFER,[n])}},this.setupDepthRenderbuffer=R,this.setupFrameBufferTexture=j,this.useMultisampledRTT=U}function Um(e,t){return{convert:function(n,i=""){let r;const s=ks.getTransfer(i);if(n===Gi)return e.UNSIGNED_BYTE;if(n===qi)return e.UNSIGNED_SHORT_4_4_4_4;if(n===_i)return e.UNSIGNED_SHORT_5_5_5_1;if(n===er)return e.UNSIGNED_INT_5_9_9_9_REV;if(n===tr)return e.UNSIGNED_INT_10F_11F_11F_REV;if(n===Vi)return e.BYTE;if(n===Wi)return e.SHORT;if(n===Qi)return e.UNSIGNED_SHORT;if(n===Zi)return e.INT;if(n===Yi)return e.UNSIGNED_INT;if(n===Ji)return e.FLOAT;if(n===Ki)return e.HALF_FLOAT;if(n===nr)return e.ALPHA;if(n===ir)return e.RGB;if(n===rr)return e.RGBA;if(n===sr)return e.DEPTH_COMPONENT;if(n===or)return e.DEPTH_STENCIL;if(n===ar)return e.RED;if(n===lr)return e.RED_INTEGER;if(n===ur)return e.RG;if(n===cr)return e.RG_INTEGER;if(n===dr)return e.RGBA_INTEGER;if(n===hr||n===fr||n===pr||n===gr)if(s===es){if(r=t.get("WEBGL_compressed_texture_s3tc_srgb"),null===r)return null;if(n===hr)return r.COMPRESSED_SRGB_S3TC_DXT1_EXT;if(n===fr)return r.COMPRESSED_SRGB_ALPHA_S3TC_DXT1_EXT;if(n===pr)return r.COMPRESSED_SRGB_ALPHA_S3TC_DXT3_EXT;if(n===gr)return r.COMPRESSED_SRGB_ALPHA_S3TC_DXT5_EXT}else{if(r=t.get("WEBGL_compressed_texture_s3tc"),null===r)return null;if(n===hr)return r.COMPRESSED_RGB_S3TC_DXT1_EXT;if(n===fr)return r.COMPRESSED_RGBA_S3TC_DXT1_EXT;if(n===pr)return r.COMPRESSED_RGBA_S3TC_DXT3_EXT;if(n===gr)return r.COMPRESSED_RGBA_S3TC_DXT5_EXT}if(n===mr||n===vr||n===Ar||n===xr){if(r=t.get("WEBGL_compressed_texture_pvrtc"),null===r)return null;if(n===mr)return r.COMPRESSED_RGB_PVRTC_4BPPV1_IMG;if(n===vr)return r.COMPRESSED_RGB_PVRTC_2BPPV1_IMG;if(n===Ar)return r.COMPRESSED_RGBA_PVRTC_4BPPV1_IMG;if(n===xr)return r.COMPRESSED_RGBA_PVRTC_2BPPV1_IMG}if(n===yr||n===br||n===wr){if(r=t.get("WEBGL_compressed_texture_etc"),null===r)return null;if(n===yr||n===br)return s===es?r.COMPRESSED_SRGB8_ETC2:r.COMPRESSED_RGB8_ETC2;if(n===wr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ETC2_EAC:r.COMPRESSED_RGBA8_ETC2_EAC}if(n===Cr||n===Mr||n===Er||n===Tr||n===Sr||n===Pr||n===Nr||n===Br||n===Dr||n===Ir||n===Lr||n===jr||n===Or||n===zr){if(r=t.get("WEBGL_compressed_texture_astc"),null===r)return null;if(n===Cr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_4x4_KHR:r.COMPRESSED_RGBA_ASTC_4x4_KHR;if(n===Mr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_5x4_KHR:r.COMPRESSED_RGBA_ASTC_5x4_KHR;if(n===Er)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_5x5_KHR:r.COMPRESSED_RGBA_ASTC_5x5_KHR;if(n===Tr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_6x5_KHR:r.COMPRESSED_RGBA_ASTC_6x5_KHR;if(n===Sr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_6x6_KHR:r.COMPRESSED_RGBA_ASTC_6x6_KHR;if(n===Pr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_8x5_KHR:r.COMPRESSED_RGBA_ASTC_8x5_KHR;if(n===Nr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_8x6_KHR:r.COMPRESSED_RGBA_ASTC_8x6_KHR;if(n===Br)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_8x8_KHR:r.COMPRESSED_RGBA_ASTC_8x8_KHR;if(n===Dr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_10x5_KHR:r.COMPRESSED_RGBA_ASTC_10x5_KHR;if(n===Ir)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_10x6_KHR:r.COMPRESSED_RGBA_ASTC_10x6_KHR;if(n===Lr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_10x8_KHR:r.COMPRESSED_RGBA_ASTC_10x8_KHR;if(n===jr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_10x10_KHR:r.COMPRESSED_RGBA_ASTC_10x10_KHR;if(n===Or)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_12x10_KHR:r.COMPRESSED_RGBA_ASTC_12x10_KHR;if(n===zr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_12x12_KHR:r.COMPRESSED_RGBA_ASTC_12x12_KHR}if(n===Rr||n===kr||n===Fr){if(r=t.get("EXT_texture_compression_bptc"),null===r)return null;if(n===Rr)return s===es?r.COMPRESSED_SRGB_ALPHA_BPTC_UNORM_EXT:r.COMPRESSED_RGBA_BPTC_UNORM_EXT;if(n===kr)return r.COMPRESSED_RGB_BPTC_SIGNED_FLOAT_EXT;if(n===Fr)return r.COMPRESSED_RGB_BPTC_UNSIGNED_FLOAT_EXT}if(n===Hr||n===Ur||n===Xr||n===Gr){if(r=t.get("EXT_texture_compression_rgtc"),null===r)return null;if(n===Hr)return r.COMPRESSED_RED_RGTC1_EXT;if(n===Ur)return r.COMPRESSED_SIGNED_RED_RGTC1_EXT;if(n===Xr)return r.COMPRESSED_RED_GREEN_RGTC2_EXT;if(n===Gr)return r.COMPRESSED_SIGNED_RED_GREEN_RGTC2_EXT}return n===$i?e.UNSIGNED_INT_24_8:void 0!==e[n]?e[n]:null}}}class Xm{constructor(){this.texture=null,this.mesh=null,this.depthNear=0,this.depthFar=0}init(e,t){if(null===this.texture){const n=new $l(e.texture);e.depthNear===t.depthNear&&e.depthFar===t.depthFar||(this.depthNear=e.depthNear,this.depthFar=e.depthFar),this.texture=n}}getMesh(e){if(null!==this.texture&&null===this.mesh){const t=e.cameras[0].viewport,n=new ul({vertexShader:"\nvoid main() {\n\n\tgl_Position = vec4( position, 1.0 );\n\n}",fragmentShader:"\nuniform sampler2DArray depthColor;\nuniform float depthWidth;\nuniform float depthHeight;\n\nvoid main() {\n\n\tvec2 coord = vec2( gl_FragCoord.x / depthWidth, gl_FragCoord.y / depthHeight );\n\n\tif ( coord.x >= 1.0 ) {\n\n\t\tgl_FragDepth = texture( depthColor, vec3( coord.x - 1.0, coord.y, 1 ) ).r;\n\n\t} else {\n\n\t\tgl_FragDepth = texture( depthColor, vec3( coord.x, coord.y, 0 ) ).r;\n\n\t}\n\n}",uniforms:{depthColor:{value:this.texture},depthWidth:{value:t.z},depthHeight:{value:t.w}}});this.mesh=new nl(new xu(20,20),n)}return this.mesh}reset(){this.texture=null,this.mesh=null}getDepthTexture(){return this.texture}}class Gm extends ds{constructor(e,t){super();const n=this;let i=null,r=1,s=null,o="local-floor",a=1,l=null,u=null,c=null,d=null,h=null,f=null;const p="undefined"!=typeof XRWebGLBinding,g=new Xm,m={},v=t.getContextAttributes();let A=null,x=null;const y=[],b=[],w=new Cs;let C=null;const M=new pl;M.viewport=new Js;const E=new pl;E.viewport=new Js;const T=[M,E],S=new xc;let P=null,N=null;function B(e){const t=b.indexOf(e.inputSource);if(-1===t)return;const n=y[t];void 0!==n&&(n.update(e.inputSource,e.frame,l||s),n.dispatchEvent({type:e.type,data:e.inputSource}))}function D(){i.removeEventListener("select",B),i.removeEventListener("selectstart",B),i.removeEventListener("selectend",B),i.removeEventListener("squeeze",B),i.removeEventListener("squeezestart",B),i.removeEventListener("squeezeend",B),i.removeEventListener("end",D),i.removeEventListener("inputsourceschange",I);for(let e=0;e<y.length;e++){const t=b[e];null!==t&&(b[e]=null,y[e].disconnect(t))}P=null,N=null,g.reset();for(const e in m)delete m[e];e.setRenderTarget(A),h=null,d=null,c=null,i=null,x=null,R.stop(),n.isPresenting=!1,e.setPixelRatio(C),e.setSize(w.width,w.height,!1),n.dispatchEvent({type:"sessionend"})}function I(e){for(let t=0;t<e.removed.length;t++){const n=e.removed[t],i=b.indexOf(n);i>=0&&(b[i]=null,y[i].disconnect(n))}for(let t=0;t<e.added.length;t++){const n=e.added[t];let i=b.indexOf(n);if(-1===i){for(let e=0;e<y.length;e++){if(e>=b.length){b.push(n),i=e;break}if(null===b[e]){b[e]=n,i=e;break}}if(-1===i)break}const r=y[i];r&&r.connect(n)}}this.cameraAutoUpdate=!0,this.enabled=!1,this.isPresenting=!1,this.getController=function(e){let t=y[e];return void 0===t&&(t=new bl,y[e]=t),t.getTargetRaySpace()},this.getControllerGrip=function(e){let t=y[e];return void 0===t&&(t=new bl,y[e]=t),t.getGripSpace()},this.getHand=function(e){let t=y[e];return void 0===t&&(t=new bl,y[e]=t),t.getHandSpace()},this.setFramebufferScaleFactor=function(e){r=e,!0===n.isPresenting&&console.warn("THREE.WebXRManager: Cannot change 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m[e]};let z=null;const R=new hp;R.setAnimationLoop((function(t,r){if(u=r.getViewerPose(l||s),f=r,null!==u){const t=u.views;null!==h&&(e.setRenderTargetFramebuffer(x,h.framebuffer),e.setRenderTarget(x));let r=!1;t.length!==S.cameras.length&&(S.cameras.length=0,r=!0);for(let n=0;n<t.length;n++){const i=t[n];let s=null;if(null!==h)s=h.getViewport(i);else{const t=c.getViewSubImage(d,i);s=t.viewport,0===n&&(e.setRenderTargetTextures(x,t.colorTexture,t.depthStencilTexture),e.setRenderTarget(x))}let o=T[n];void 0===o&&(o=new pl,o.layers.enable(n),o.viewport=new Js,T[n]=o),o.matrix.fromArray(i.transform.matrix),o.matrix.decompose(o.position,o.quaternion,o.scale),o.projectionMatrix.fromArray(i.projectionMatrix),o.projectionMatrixInverse.copy(o.projectionMatrix).invert(),o.viewport.set(s.x,s.y,s.width,s.height),0===n&&(S.matrix.copy(o.matrix),S.matrix.decompose(S.position,S.quaternion,S.scale)),!0===r&&S.cameras.push(o)}const s=i.enabledFeatures;if(s&&s.includes("depth-sensing")&&"gpu-optimized"==i.depthUsage&&p){c=n.getBinding();const e=c.getDepthInformation(t[0]);e&&e.isValid&&e.texture&&g.init(e,i.renderState)}if(s&&s.includes("camera-access")&&p){e.state.unbindTexture(),c=n.getBinding();for(let e=0;e<t.length;e++){const n=t[e].camera;if(n){let e=m[n];e||(e=new $l,m[n]=e);const t=c.getCameraImage(n);e.sourceTexture=t}}}}for(let e=0;e<y.length;e++){const t=b[e],n=y[e];null!==t&&void 0!==n&&n.update(t,r,l||s)}z&&z(t,r),r.detectedPlanes&&n.dispatchEvent({type:"planesdetected",data:r}),f=null})),this.setAnimationLoop=function(e){z=e},this.dispose=function(){}}}const Vm=new ko,Wm=new Po;function Qm(e,t){function n(e,t){!0===e.matrixAutoUpdate&&e.updateMatrix(),t.value.copy(e.matrix)}function i(e,i){e.opacity.value=i.opacity,i.color&&e.diffuse.value.copy(i.color),i.emissive&&e.emissive.value.copy(i.emissive).multiplyScalar(i.emissiveIntensity),i.map&&(e.map.value=i.map,n(i.map,e.mapTransform)),i.alphaMap&&(e.alphaMap.value=i.alphaMap,n(i.alphaMap,e.alphaMapTransform)),i.bumpMap&&(e.bumpMap.value=i.bumpMap,n(i.bumpMap,e.bumpMapTransform),e.bumpScale.value=i.bumpScale,1===i.side&&(e.bumpScale.value*=-1)),i.normalMap&&(e.normalMap.value=i.normalMap,n(i.normalMap,e.normalMapTransform),e.normalScale.value.copy(i.normalScale),1===i.side&&e.normalScale.value.negate()),i.displacementMap&&(e.displacementMap.value=i.displacementMap,n(i.displacementMap,e.displacementMapTransform),e.displacementScale.value=i.displacementScale,e.displacementBias.value=i.displacementBias),i.emissiveMap&&(e.emissiveMap.value=i.emissiveMap,n(i.emissiveMap,e.emissiveMapTransform)),i.specularMap&&(e.specularMap.value=i.specularMap,n(i.specularMap,e.specularMapTransform)),i.alphaTest>0&&(e.alphaTest.value=i.alphaTest);const r=t.get(i),s=r.envMap,o=r.envMapRotation;s&&(e.envMap.value=s,Vm.copy(o),Vm.x*=-1,Vm.y*=-1,Vm.z*=-1,s.isCubeTexture&&!1===s.isRenderTargetTexture&&(Vm.y*=-1,Vm.z*=-1),e.envMapRotation.value.setFromMatrix4(Wm.makeRotationFromEuler(Vm)),e.flipEnvMap.value=s.isCubeTexture&&!1===s.isRenderTargetTexture?-1:1,e.reflectivity.value=i.reflectivity,e.ior.value=i.ior,e.refractionRatio.value=i.refractionRatio),i.lightMap&&(e.lightMap.value=i.lightMap,e.lightMapIntensity.value=i.lightMapIntensity,n(i.lightMap,e.lightMapTransform)),i.aoMap&&(e.aoMap.value=i.aoMap,e.aoMapIntensity.value=i.aoMapIntensity,n(i.aoMap,e.aoMapTransform))}return{refreshFogUniforms:function(t,n){n.color.getRGB(t.fogColor.value,al(e)),n.isFog?(t.fogNear.value=n.near,t.fogFar.value=n.far):n.isFogExp2&&(t.fogDensity.value=n.density)},refreshMaterialUniforms:function(e,r,s,o,a){r.isMeshBasicMaterial||r.isMeshLambertMaterial?i(e,r):r.isMeshToonMaterial?(i(e,r),function(e,t){t.gradientMap&&(e.gradientMap.value=t.gradientMap)}(e,r)):r.isMeshPhongMaterial?(i(e,r),function(e,t){e.specular.value.copy(t.specular),e.shininess.value=Math.max(t.shininess,1e-4)}(e,r)):r.isMeshStandardMaterial?(i(e,r),function(e,t){e.metalness.value=t.metalness,t.metalnessMap&&(e.metalnessMap.value=t.metalnessMap,n(t.metalnessMap,e.metalnessMapTransform));e.roughness.value=t.roughness,t.roughnessMap&&(e.roughnessMap.value=t.roughnessMap,n(t.roughnessMap,e.roughnessMapTransform));t.envMap&&(e.envMapIntensity.value=t.envMapIntensity)}(e,r),r.isMeshPhysicalMaterial&&function(e,t,i){e.ior.value=t.ior,t.sheen>0&&(e.sheenColor.value.copy(t.sheenColor).multiplyScalar(t.sheen),e.sheenRoughness.value=t.sheenRoughness,t.sheenColorMap&&(e.sheenColorMap.value=t.sheenColorMap,n(t.sheenColorMap,e.sheenColorMapTransform)),t.sheenRoughnessMap&&(e.sheenRoughnessMap.value=t.sheenRoughnessMap,n(t.sheenRoughnessMap,e.sheenRoughnessMapTransform)));t.clearcoat>0&&(e.clearcoat.value=t.clearcoat,e.clearcoatRoughness.value=t.clearcoatRoughness,t.clearcoatMap&&(e.clearcoatMap.value=t.clearcoatMap,n(t.clearcoatMap,e.clearcoatMapTransform)),t.clearcoatRoughnessMap&&(e.clearcoatRoughnessMap.value=t.clearcoatRoughnessMap,n(t.clearcoatRoughnessMap,e.clearcoatRoughnessMapTransform)),t.clearcoatNormalMap&&(e.clearcoatNormalMap.value=t.clearcoatNormalMap,n(t.clearcoatNormalMap,e.clearcoatNormalMapTransform),e.clearcoatNormalScale.value.copy(t.clearcoatNormalScale),1===t.side&&e.clearcoatNormalScale.value.negate()));t.dispersion>0&&(e.dispersion.value=t.dispersion);t.iridescence>0&&(e.iridescence.value=t.iridescence,e.iridescenceIOR.value=t.iridescenceIOR,e.iridescenceThicknessMinimum.value=t.iridescenceThicknessRange[0],e.iridescenceThicknessMaximum.value=t.iridescenceThicknessRange[1],t.iridescenceMap&&(e.iridescenceMap.value=t.iridescenceMap,n(t.iridescenceMap,e.iridescenceMapTransform)),t.iridescenceThicknessMap&&(e.iridescenceThicknessMap.value=t.iridescenceThicknessMap,n(t.iridescenceThicknessMap,e.iridescenceThicknessMapTransform)));t.transmission>0&&(e.transmission.value=t.transmission,e.transmissionSamplerMap.value=i.texture,e.transmissionSamplerSize.value.set(i.width,i.height),t.transmissionMap&&(e.transmissionMap.value=t.transmissionMap,n(t.transmissionMap,e.transmissionMapTransform)),e.thickness.value=t.thickness,t.thicknessMap&&(e.thicknessMap.value=t.thicknessMap,n(t.thicknessMap,e.thicknessMapTransform)),e.attenuationDistance.value=t.attenuationDistance,e.attenuationColor.value.copy(t.attenuationColor));t.anisotropy>0&&(e.anisotropyVector.value.set(t.anisotropy*Math.cos(t.anisotropyRotation),t.anisotropy*Math.sin(t.anisotropyRotation)),t.anisotropyMap&&(e.anisotropyMap.value=t.anisotropyMap,n(t.anisotropyMap,e.anisotropyMapTransform)));e.specularIntensity.value=t.specularIntensity,e.specularColor.value.copy(t.specularColor),t.specularColorMap&&(e.specularColorMap.value=t.specularColorMap,n(t.specularColorMap,e.specularColorMapTransform));t.specularIntensityMap&&(e.specularIntensityMap.value=t.specularIntensityMap,n(t.specularIntensityMap,e.specularIntensityMapTransform))}(e,r,a)):r.isMeshMatcapMaterial?(i(e,r),function(e,t){t.matcap&&(e.matcap.value=t.matcap)}(e,r)):r.isMeshDepthMaterial?i(e,r):r.isMeshDistanceMaterial?(i(e,r),function(e,n){const i=t.get(n).light;e.referencePosition.value.setFromMatrixPosition(i.matrixWorld),e.nearDistance.value=i.shadow.camera.near,e.farDistance.value=i.shadow.camera.far}(e,r)):r.isMeshNormalMaterial?i(e,r):r.isLineBasicMaterial?(function(e,t){e.diffuse.value.copy(t.color),e.opacity.value=t.opacity,t.map&&(e.map.value=t.map,n(t.map,e.mapTransform))}(e,r),r.isLineDashedMaterial&&function(e,t){e.dashSize.value=t.dashSize,e.totalSize.value=t.dashSize+t.gapSize,e.scale.value=t.scale}(e,r)):r.isPointsMaterial?function(e,t,i,r){e.diffuse.value.copy(t.color),e.opacity.value=t.opacity,e.size.value=t.size*i,e.scale.value=.5*r,t.map&&(e.map.value=t.map,n(t.map,e.uvTransform));t.alphaMap&&(e.alphaMap.value=t.alphaMap,n(t.alphaMap,e.alphaMapTransform));t.alphaTest>0&&(e.alphaTest.value=t.alphaTest)}(e,r,s,o):r.isSpriteMaterial?function(e,t){e.diffuse.value.copy(t.color),e.opacity.value=t.opacity,e.rotation.value=t.rotation,t.map&&(e.map.value=t.map,n(t.map,e.mapTransform));t.alphaMap&&(e.alphaMap.value=t.alphaMap,n(t.alphaMap,e.alphaMapTransform));t.alphaTest>0&&(e.alphaTest.value=t.alphaTest)}(e,r):r.isShadowMaterial?(e.color.value.copy(r.color),e.opacity.value=r.opacity):r.isShaderMaterial&&(r.uniformsNeedUpdate=!1)}}}function Zm(e,t,n,i){let r={},s={},o=[];const a=e.getParameter(e.MAX_UNIFORM_BUFFER_BINDINGS);function l(e,t,n,i){const r=e.value,s=t+"_"+n;if(void 0===i[s])return i[s]="number"==typeof r||"boolean"==typeof r?r:r.clone(),!0;{const e=i[s];if("number"==typeof r||"boolean"==typeof r){if(e!==r)return i[s]=r,!0}else if(!1===e.equals(r))return e.copy(r),!0}return!1}function u(e){const t={boundary:0,storage:0};return"number"==typeof e||"boolean"==typeof e?(t.boundary=4,t.storage=4):e.isVector2?(t.boundary=8,t.storage=8):e.isVector3||e.isColor?(t.boundary=16,t.storage=12):e.isVector4?(t.boundary=16,t.storage=16):e.isMatrix3?(t.boundary=48,t.storage=48):e.isMatrix4?(t.boundary=64,t.storage=64):e.isTexture?console.warn("THREE.WebGLRenderer: Texture samplers can not be part of an uniforms group."):console.warn("THREE.WebGLRenderer: Unsupported uniform value type.",e),t}function c(t){const n=t.target;n.removeEventListener("dispose",c);const i=o.indexOf(n.__bindingPointIndex);o.splice(i,1),e.deleteBuffer(r[n.id]),delete r[n.id],delete s[n.id]}return{bind:function(e,t){const n=t.program;i.uniformBlockBinding(e,n)},update:function(n,d){let h=r[n.id];void 0===h&&(!function(e){const t=e.uniforms;let n=0;const i=16;for(let e=0,r=t.length;e<r;e++){const r=Array.isArray(t[e])?t[e]:[t[e]];for(let e=0,t=r.length;e<t;e++){const t=r[e],s=Array.isArray(t.value)?t.value:[t.value];for(let e=0,r=s.length;e<r;e++){const r=u(s[e]),o=n%i,a=o%r.boundary,l=o+a;n+=a,0!==l&&i-l<r.storage&&(n+=i-l),t.__data=new Float32Array(r.storage/Float32Array.BYTES_PER_ELEMENT),t.__offset=n,n+=r.storage}}}const r=n%i;r>0&&(n+=i-r);e.__size=n,e.__cache={}}(n),h=function(t){const n=function(){for(let e=0;e<a;e++)if(-1===o.indexOf(e))return o.push(e),e;return console.error("THREE.WebGLRenderer: Maximum number of simultaneously usable uniforms groups reached."),0}();t.__bindingPointIndex=n;const i=e.createBuffer(),r=t.__size,s=t.usage;return e.bindBuffer(e.UNIFORM_BUFFER,i),e.bufferData(e.UNIFORM_BUFFER,r,s),e.bindBuffer(e.UNIFORM_BUFFER,null),e.bindBufferBase(e.UNIFORM_BUFFER,n,i),i}(n),r[n.id]=h,n.addEventListener("dispose",c));const f=d.program;i.updateUBOMapping(n,f);const p=t.render.frame;s[n.id]!==p&&(!function(t){const n=r[t.id],i=t.uniforms,s=t.__cache;e.bindBuffer(e.UNIFORM_BUFFER,n);for(let t=0,n=i.length;t<n;t++){const n=Array.isArray(i[t])?i[t]:[i[t]];for(let i=0,r=n.length;i<r;i++){const r=n[i];if(!0===l(r,t,i,s)){const t=r.__offset,n=Array.isArray(r.value)?r.value:[r.value];let i=0;for(let s=0;s<n.length;s++){const o=n[s],a=u(o);"number"==typeof o||"boolean"==typeof o?(r.__data[0]=o,e.bufferSubData(e.UNIFORM_BUFFER,t+i,r.__data)):o.isMatrix3?(r.__data[0]=o.elements[0],r.__data[1]=o.elements[1],r.__data[2]=o.elements[2],r.__data[3]=0,r.__data[4]=o.elements[3],r.__data[5]=o.elements[4],r.__data[6]=o.elements[5],r.__data[7]=0,r.__data[8]=o.elements[6],r.__data[9]=o.elements[7],r.__data[10]=o.elements[8],r.__data[11]=0):(o.toArray(r.__data,i),i+=a.storage/Float32Array.BYTES_PER_ELEMENT)}e.bufferSubData(e.UNIFORM_BUFFER,t,r.__data)}}}e.bindBuffer(e.UNIFORM_BUFFER,null)}(n),s[n.id]=p)},dispose:function(){for(const t in r)e.deleteBuffer(r[t]);o=[],r={},s={}}}}const Ym=["alphaMap","alphaTest","anisotropy","anisotropyMap","anisotropyRotation","aoMap","aoMapIntensity","attenuationColor","attenuationDistance","bumpMap","clearcoat","clearcoatMap","clearcoatNormalMap","clearcoatNormalScale","clearcoatRoughness","color","dispersion","displacementMap","emissive","emissiveIntensity","emissiveMap","envMap","envMapIntensity","gradientMap","ior","iridescence","iridescenceIOR","iridescenceMap","iridescenceThicknessMap","lightMap","lightMapIntensity","map","matcap","metalness","metalnessMap","normalMap","normalScale","opacity","roughness","roughnessMap","sheen","sheenColor","sheenColorMap","sheenRoughnessMap","shininess","specular","specularColor","specularColorMap","specularIntensity","specularIntensityMap","specularMap","thickness","transmission","transmissionMap"],Jm=new WeakMap;class Km{constructor(e){this.renderObjects=new WeakMap,this.hasNode=this.containsNode(e),this.hasAnimation=!0===e.object.isSkinnedMesh,this.refreshUniforms=Ym,this.renderId=0}firstInitialization(e){return!1===this.renderObjects.has(e)&&(this.getRenderObjectData(e),!0)}needsVelocity(e){const t=e.getMRT();return null!==t&&t.has("velocity")}getRenderObjectData(e){let t=this.renderObjects.get(e);if(void 0===t){const{geometry:n,material:i,object:r}=e;if(t={material:this.getMaterialData(i),geometry:{id:n.id,attributes:this.getAttributesData(n.attributes),indexVersion:n.index?n.index.version:null,drawRange:{start:n.drawRange.start,count:n.drawRange.count}},worldMatrix:r.matrixWorld.clone()},r.center&&(t.center=r.center.clone()),r.morphTargetInfluences&&(t.morphTargetInfluences=r.morphTargetInfluences.slice()),null!==e.bundle&&(t.version=e.bundle.version),t.material.transmission>0){const{width:n,height:i}=e.context;t.bufferWidth=n,t.bufferHeight=i}t.lights=this.getLightsData(e.lightsNode.getLights()),this.renderObjects.set(e,t)}return t}getAttributesData(e){const t={};for(const n in e){const i=e[n];t[n]={version:i.version}}return t}containsNode(e){const t=e.material;for(const e in t)if(t[e]&&t[e].isNode)return!0;return null!==e.renderer.overrideNodes.modelViewMatrix||null!==e.renderer.overrideNodes.modelNormalViewMatrix}getMaterialData(e){const t={};for(const n of this.refreshUniforms){const i=e[n];null!=i&&("object"==typeof i&&void 0!==i.clone?!0===i.isTexture?t[n]={id:i.id,version:i.version}:t[n]=i.clone():t[n]=i)}return t}equals(e,t){const{object:n,material:i,geometry:r}=e,s=this.getRenderObjectData(e);if(!0!==s.worldMatrix.equals(n.matrixWorld))return s.worldMatrix.copy(n.matrixWorld),!1;const o=s.material;for(const e in o){const t=o[e],n=i[e];if(void 0!==t.equals){if(!1===t.equals(n))return t.copy(n),!1}else if(!0===n.isTexture){if(t.id!==n.id||t.version!==n.version)return t.id=n.id,t.version=n.version,!1}else if(t!==n)return o[e]=n,!1}if(o.transmission>0){const{width:t,height:n}=e.context;if(s.bufferWidth!==t||s.bufferHeight!==n)return s.bufferWidth=t,s.bufferHeight=n,!1}const a=s.geometry,l=r.attributes,u=a.attributes,c=Object.keys(u),d=Object.keys(l);if(a.id!==r.id)return a.id=r.id,!1;if(c.length!==d.length)return s.geometry.attributes=this.getAttributesData(l),!1;for(const e of c){const t=u[e],n=l[e];if(void 0===n)return delete u[e],!1;if(t.version!==n.version)return t.version=n.version,!1}const h=r.index,f=a.indexVersion,p=h?h.version:null;if(f!==p)return a.indexVersion=p,!1;if(a.drawRange.start!==r.drawRange.start||a.drawRange.count!==r.drawRange.count)return a.drawRange.start=r.drawRange.start,a.drawRange.count=r.drawRange.count,!1;if(s.morphTargetInfluences){let e=!1;for(let t=0;t<s.morphTargetInfluences.length;t++)s.morphTargetInfluences[t]!==n.morphTargetInfluences[t]&&(e=!0);if(e)return!0}if(s.lights)for(let e=0;e<t.length;e++)if(s.lights[e].map!==t[e].map)return!1;return s.center&&!1===s.center.equals(n.center)?(s.center.copy(n.center),!0):(null!==e.bundle&&(s.version=e.bundle.version),!0)}getLightsData(e){const t=[];for(const n of e)!0===n.isSpotLight&&null!==n.map&&t.push({map:n.map.version});return t}getLights(e,t){if(Jm.has(e)){const n=Jm.get(e);if(n.renderId===t)return n.lightsData}const n=this.getLightsData(e.getLights());return Jm.set(e,{renderId:t,lightsData:n}),n}needsRefresh(e,t){if(this.hasNode||this.hasAnimation||this.firstInitialization(e)||this.needsVelocity(t.renderer))return!0;const{renderId:n}=t;if(this.renderId!==n)return this.renderId=n,!0;const i=!0===e.object.static,r=null!==e.bundle&&!0===e.bundle.static&&this.getRenderObjectData(e).version===e.bundle.version;if(i||r)return!1;const s=this.getLights(e.lightsNode,n);return!0!==this.equals(e,s)}}function qm(e,t=0){let n=3735928559^t,i=1103547991^t;if(e instanceof Array)for(let t,r=0;r<e.length;r++)t=e[r],n=Math.imul(n^t,2654435761),i=Math.imul(i^t,1597334677);else for(let t,r=0;r<e.length;r++)t=e.charCodeAt(r),n=Math.imul(n^t,2654435761),i=Math.imul(i^t,1597334677);return n=Math.imul(n^n>>>16,2246822507),n^=Math.imul(i^i>>>13,3266489909),i=Math.imul(i^i>>>16,2246822507),i^=Math.imul(n^n>>>13,3266489909),4294967296*(2097151&i)+(n>>>0)}const _m=e=>qm(e),$m=e=>qm(e),ev=(...e)=>qm(e);function tv(e,t=!1){const n=[];!0===e.isNode&&n.push(e.id);for(const{property:i,childNode:r}of nv(e))n.push(qm(i.slice(0,-4)),r.getCacheKey(t));return qm(n)}function*nv(e,t=!1){for(const n of Object.getOwnPropertyNames(e)){if(!0===n.startsWith("_"))continue;const i=e[n];if(!0===Array.isArray(i))for(let e=0;e<i.length;e++){const r=i[e];r&&(!0===r.isNode||t&&"function"==typeof r.toJSON)&&(yield{property:n,index:e,childNode:r})}else if(i&&!0===i.isNode)yield{property:n,childNode:i};else if(i&&Object.getPrototypeOf(i)===Object.prototype)for(const e in i){if(!0===e.startsWith("_"))continue;const r=i[e];r&&(!0===r.isNode||t&&"function"==typeof r.toJSON)&&(yield{property:n,index:e,childNode:r})}}}const iv=new Map([[1,"float"],[2,"vec2"],[3,"vec3"],[4,"vec4"],[9,"mat3"],[16,"mat4"]]),rv=new WeakMap;function sv(e){return iv.get(e)}function ov(e){if(null==e)return null;const t=typeof e;return!0===e.isNode?"node":"number"===t?"float":"boolean"===t?"bool":"string"===t?"string":"function"===t?"shader":!0===e.isVector2?"vec2":!0===e.isVector3?"vec3":!0===e.isVector4?"vec4":!0===e.isMatrix2?"mat2":!0===e.isMatrix3?"mat3":!0===e.isMatrix4?"mat4":!0===e.isColor?"color":e instanceof ArrayBuffer?"ArrayBuffer":null}function av(e,...t){const n=e?e.slice(-4):void 0;return 1===t.length&&("vec2"===n?t=[t[0],t[0]]:"vec3"===n?t=[t[0],t[0],t[0]]:"vec4"===n&&(t=[t[0],t[0],t[0],t[0]])),"color"===e?new ya(...t):"vec2"===n?new Cs(...t):"vec3"===n?new Es(...t):"vec4"===n?new Js(...t):"mat2"===n?new jc(...t):"mat3"===n?new Ps(...t):"mat4"===n?new Po(...t):"bool"===e?t[0]||!1:"float"===e||"int"===e||"uint"===e?t[0]||0:"string"===e?t[0]||"":"ArrayBuffer"===e?cv(t[0]):null}function lv(e){let t=rv.get(e);return void 0===t&&(t={},rv.set(e,t)),t}function uv(e){let t="";const n=new Uint8Array(e);for(let e=0;e<n.length;e++)t+=String.fromCharCode(n[e]);return btoa(t)}function cv(e){return Uint8Array.from(atob(e),(e=>e.charCodeAt(0))).buffer}const dv={VERTEX:"vertex",FRAGMENT:"fragment"},hv={NONE:"none",FRAME:"frame",RENDER:"render",OBJECT:"object"},fv={READ_ONLY:"readOnly",WRITE_ONLY:"writeOnly",READ_WRITE:"readWrite"},pv=["fragment","vertex"],gv=["setup","analyze","generate"],mv=[...pv,"compute"],vv=["x","y","z","w"],Av={analyze:"setup",generate:"analyze"};let xv=0;class yv extends ds{static get type(){return"Node"}constructor(e=null){super(),this.nodeType=e,this.updateType=hv.NONE,this.updateBeforeType=hv.NONE,this.updateAfterType=hv.NONE,this.uuid=ws.generateUUID(),this.version=0,this.global=!1,this.parents=!1,this.isNode=!0,this._cacheKey=null,this._cacheKeyVersion=0,Object.defineProperty(this,"id",{value:xv++})}set needsUpdate(e){!0===e&&this.version++}get type(){return this.constructor.type}onUpdate(e,t){return this.updateType=t,this.update=e.bind(this),this}onFrameUpdate(e){return this.onUpdate(e,hv.FRAME)}onRenderUpdate(e){return this.onUpdate(e,hv.RENDER)}onObjectUpdate(e){return this.onUpdate(e,hv.OBJECT)}onReference(e){return this.updateReference=e.bind(this),this}updateReference(){return this}isGlobal(){return this.global}*getChildren(){for(const{childNode:e}of nv(this))yield e}dispose(){this.dispatchEvent({type:"dispose"})}traverse(e){e(this);for(const t of this.getChildren())t.traverse(e)}getCacheKey(e=!1){return!0!==(e=e||this.version!==this._cacheKeyVersion)&&null!==this._cacheKey||(this._cacheKey=ev(tv(this,e),this.customCacheKey()),this._cacheKeyVersion=this.version),this._cacheKey}customCacheKey(){return 0}getScope(){return this}getHash(){return this.uuid}getUpdateType(){return this.updateType}getUpdateBeforeType(){return this.updateBeforeType}getUpdateAfterType(){return this.updateAfterType}getElementType(e){const t=this.getNodeType(e);return e.getElementType(t)}getMemberType(){return"void"}getNodeType(e){const t=e.getNodeProperties(this);return t.outputNode?t.outputNode.getNodeType(e):this.nodeType}getShared(e){const t=this.getHash(e);return e.getNodeFromHash(t)||this}getArrayCount(){return null}setup(e){const t=e.getNodeProperties(this);let n=0;for(const e of this.getChildren())t["node"+n++]=e;return t.outputNode||null}analyze(e,t=null){const n=e.increaseUsage(this);if(!0===this.parents){const n=e.getDataFromNode(this,"any");n.stages=n.stages||{},n.stages[e.shaderStage]=n.stages[e.shaderStage]||[],n.stages[e.shaderStage].push(t)}if(1===n){const t=e.getNodeProperties(this);for(const n of Object.values(t))n&&!0===n.isNode&&n.build(e,this)}}generate(e,t){const{outputNode:n}=e.getNodeProperties(this);if(n&&!0===n.isNode)return n.build(e,t)}updateBefore(){console.warn("Abstract function.")}updateAfter(){console.warn("Abstract function.")}update(){console.warn("Abstract function.")}build(e,t=null){const n=this.getShared(e);if(this!==n)return n.build(e,t);const i=e.getDataFromNode(this);i.buildStages=i.buildStages||{},i.buildStages[e.buildStage]=!0;const r=Av[e.buildStage];if(r&&!0!==i.buildStages[r]){const t=e.getBuildStage();e.setBuildStage(r),this.build(e),e.setBuildStage(t)}e.addNode(this),e.addChain(this);let s=null;const o=e.getBuildStage();if("setup"===o){this.updateReference(e);const t=e.getNodeProperties(this);if(!0!==t.initialized){t.initialized=!0,t.outputNode=this.setup(e)||t.outputNode||null;for(const n of Object.values(t))if(n&&!0===n.isNode){if(!0===n.parents){const t=e.getNodeProperties(n);t.parents=t.parents||[],t.parents.push(this)}n.build(e)}}s=t.outputNode}else if("analyze"===o)this.analyze(e,t);else if("generate"===o){if(1===this.generate.length){const n=this.getNodeType(e),i=e.getDataFromNode(this);s=i.snippet,void 0===s?void 0===i.generated?(i.generated=!0,s=this.generate(e)||"",i.snippet=s):(console.warn("THREE.Node: Recursion detected.",this),s="/* Recursion detected. */"):void 0!==i.flowCodes&&void 0!==e.context.nodeBlock&&e.addFlowCodeHierarchy(this,e.context.nodeBlock),s=e.format(s,n,t)}else s=this.generate(e,t)||"";""===s&&null!==t&&"void"!==t&&"OutputType"!==t&&(console.error(`THREE.TSL: Invalid generated code, expected a "${t}".`),s=e.generateConst(t))}return e.removeChain(this),e.addSequentialNode(this),s}getSerializeChildren(){return nv(this)}serialize(e){const t=this.getSerializeChildren(),n={};for(const{property:i,index:r,childNode:s}of t)void 0!==r?(void 0===n[i]&&(n[i]=Number.isInteger(r)?[]:{}),n[i][r]=s.toJSON(e.meta).uuid):n[i]=s.toJSON(e.meta).uuid;Object.keys(n).length>0&&(e.inputNodes=n)}deserialize(e){if(void 0!==e.inputNodes){const t=e.meta.nodes;for(const n in e.inputNodes)if(Array.isArray(e.inputNodes[n])){const i=[];for(const r of e.inputNodes[n])i.push(t[r]);this[n]=i}else if("object"==typeof e.inputNodes[n]){const i={};for(const r in e.inputNodes[n]){const s=e.inputNodes[n][r];i[r]=t[s]}this[n]=i}else{const i=e.inputNodes[n];this[n]=t[i]}}}toJSON(e){const{uuid:t,type:n}=this,i=void 0===e||"string"==typeof e;i&&(e={textures:{},images:{},nodes:{}});let r=e.nodes[t];function s(e){const t=[];for(const n in e){const i=e[n];delete i.metadata,t.push(i)}return t}if(void 0===r&&(r={uuid:t,type:n,meta:e,metadata:{version:4.7,type:"Node",generator:"Node.toJSON"}},!0!==i&&(e.nodes[r.uuid]=r),this.serialize(r),delete r.meta),i){const t=s(e.textures),n=s(e.images),i=s(e.nodes);t.length>0&&(r.textures=t),n.length>0&&(r.images=n),i.length>0&&(r.nodes=i)}return r}}class bv extends yv{static get type(){return"ArrayElementNode"}constructor(e,t){super(),this.node=e,this.indexNode=t,this.isArrayElementNode=!0}getNodeType(e){return this.node.getElementType(e)}generate(e){const t=this.indexNode.getNodeType(e);return`${this.node.build(e)}[ ${this.indexNode.build(e,!e.isVector(t)&&e.isInteger(t)?t:"uint")} ]`}}class wv extends yv{static get type(){return"ConvertNode"}constructor(e,t){super(),this.node=e,this.convertTo=t}getNodeType(e){const t=this.node.getNodeType(e);let n=null;for(const i of this.convertTo.split("|"))null!==n&&e.getTypeLength(t)!==e.getTypeLength(i)||(n=i);return n}serialize(e){super.serialize(e),e.convertTo=this.convertTo}deserialize(e){super.deserialize(e),this.convertTo=e.convertTo}generate(e,t){const n=this.node,i=this.getNodeType(e),r=n.build(e,i);return e.format(r,i,t)}}class Cv extends yv{static get type(){return"TempNode"}constructor(e=null){super(e),this.isTempNode=!0}hasDependencies(e){return e.getDataFromNode(this).usageCount>1}build(e,t){if("generate"===e.getBuildStage()){const n=e.getVectorType(this.getNodeType(e,t)),i=e.getDataFromNode(this);if(void 0!==i.propertyName)return e.format(i.propertyName,n,t);if("void"!==n&&"void"!==t&&this.hasDependencies(e)){const r=super.build(e,n),s=e.getVarFromNode(this,null,n),o=e.getPropertyName(s);return e.addLineFlowCode(`${o} = ${r}`,this),i.snippet=r,i.propertyName=o,e.format(i.propertyName,n,t)}}return super.build(e,t)}}class Mv extends Cv{static get type(){return"JoinNode"}constructor(e=[],t=null){super(t),this.nodes=e}getNodeType(e){return null!==this.nodeType?e.getVectorType(this.nodeType):e.getTypeFromLength(this.nodes.reduce(((t,n)=>t+e.getTypeLength(n.getNodeType(e))),0))}generate(e,t){const n=this.getNodeType(e),i=e.getTypeLength(n),r=this.nodes,s=e.getComponentType(n),o=[];let a=0;for(const t of r){if(a>=i){console.error(`THREE.TSL: Length of parameters exceeds maximum length of function '${n}()' type.`);break}let r,l=t.getNodeType(e),u=e.getTypeLength(l);a+u>i&&(console.error(`THREE.TSL: Length of '${n}()' data exceeds maximum length of output type.`),u=i-a,l=e.getTypeFromLength(u)),a+=u,r=t.build(e,l);if(e.getComponentType(l)!==s){const t=e.getTypeFromLength(u,s);r=e.format(r,l,t)}o.push(r)}const l=`${e.getType(n)}( ${o.join(", ")} )`;return e.format(l,n,t)}}const Ev=vv.join("");class Tv extends yv{static get type(){return"SplitNode"}constructor(e,t="x"){super(),this.node=e,this.components=t,this.isSplitNode=!0}getVectorLength(){let e=this.components.length;for(const t of this.components)e=Math.max(vv.indexOf(t)+1,e);return e}getComponentType(e){return e.getComponentType(this.node.getNodeType(e))}getNodeType(e){return e.getTypeFromLength(this.components.length,this.getComponentType(e))}getScope(){return this.node.getScope()}generate(e,t){const n=this.node,i=e.getTypeLength(n.getNodeType(e));let r=null;if(i>1){let s=null;this.getVectorLength()>=i&&(s=e.getTypeFromLength(this.getVectorLength(),this.getComponentType(e)));const o=n.build(e,s);r=this.components.length===i&&this.components===Ev.slice(0,this.components.length)?e.format(o,s,t):e.format(`${o}.${this.components}`,this.getNodeType(e),t)}else r=n.build(e,t);return r}serialize(e){super.serialize(e),e.components=this.components}deserialize(e){super.deserialize(e),this.components=e.components}}class Sv extends Cv{static get type(){return"SetNode"}constructor(e,t,n){super(),this.sourceNode=e,this.components=t,this.targetNode=n}getNodeType(e){return this.sourceNode.getNodeType(e)}generate(e){const{sourceNode:t,components:n,targetNode:i}=this,r=this.getNodeType(e),s=e.getComponentType(i.getNodeType(e)),o=e.getTypeFromLength(n.length,s),a=i.build(e,o),l=t.build(e,r),u=e.getTypeLength(r),c=[];for(let e=0;e<u;e++){const t=vv[e];t===n[0]?(c.push(a),e+=n.length-1):c.push(l+"."+t)}return`${e.getType(r)}( ${c.join(", ")} )`}}class Pv extends Cv{static get type(){return"FlipNode"}constructor(e,t){super(),this.sourceNode=e,this.components=t}getNodeType(e){return this.sourceNode.getNodeType(e)}generate(e){const{components:t,sourceNode:n}=this,i=this.getNodeType(e),r=n.build(e),s=e.getVarFromNode(this),o=e.getPropertyName(s);e.addLineFlowCode(o+" = "+r,this);const a=e.getTypeLength(i),l=[];let u=0;for(let e=0;e<a;e++){const n=vv[e];n===t[u]?(l.push("1.0 - "+o+"."+n),u++):l.push(o+"."+n)}return`${e.getType(i)}( ${l.join(", ")} )`}}class Nv extends yv{static get type(){return"InputNode"}constructor(e,t=null){super(t),this.isInputNode=!0,this.value=e,this.precision=null}getNodeType(){return null===this.nodeType?ov(this.value):this.nodeType}getInputType(e){return this.getNodeType(e)}setPrecision(e){return this.precision=e,this}serialize(e){super.serialize(e),e.value=this.value,this.value&&this.value.toArray&&(e.value=this.value.toArray()),e.valueType=ov(this.value),e.nodeType=this.nodeType,"ArrayBuffer"===e.valueType&&(e.value=uv(e.value)),e.precision=this.precision}deserialize(e){super.deserialize(e),this.nodeType=e.nodeType,this.value=Array.isArray(e.value)?av(e.valueType,...e.value):e.value,this.precision=e.precision||null,this.value&&this.value.fromArray&&(this.value=this.value.fromArray(e.value))}generate(){console.warn("Abstract function.")}}const Bv=/float|u?int/;class Dv extends Nv{static get type(){return"ConstNode"}constructor(e,t=null){super(e,t),this.isConstNode=!0}generateConst(e){return e.generateConst(this.getNodeType(e),this.value)}generate(e,t){const n=this.getNodeType(e);return Bv.test(n)&&Bv.test(t)?e.generateConst(t,this.value):e.format(this.generateConst(e),n,t)}}class Iv extends yv{static get type(){return"MemberNode"}constructor(e,t){super(),this.structNode=e,this.property=t,this.isMemberNode=!0}hasMember(e){return(!this.structNode.isMemberNode||!1!==this.structNode.hasMember(e))&&"void"!==this.structNode.getMemberType(e,this.property)}getNodeType(e){return!1===this.hasMember(e)?"float":this.structNode.getMemberType(e,this.property)}getMemberType(e,t){if(!1===this.hasMember(e))return"float";const n=this.getNodeType(e);return e.getStructTypeNode(n).getMemberType(e,t)}generate(e){if(!1===this.hasMember(e)){console.warn(`THREE.TSL: Member "${this.property}" does not exist in struct.`);const t=this.getNodeType(e);return e.generateConst(t)}return this.structNode.build(e)+"."+this.property}}let Lv=null;const jv=new Map;function Ov(e,t){if(jv.has(e))console.warn(`THREE.TSL: Redefinition of method chaining '${e}'.`);else{if("function"!=typeof t)throw new Error(`THREE.TSL: Node element ${e} is not a function`);jv.set(e,t),"assign"!==e&&(yv.prototype[e]=function(...e){return this.isStackNode?this.add(t(...e)):t(this,...e)},yv.prototype[e+"Assign"]=function(...e){return this.isStackNode?this.assign(e[0],t(...e)):this.assign(t(this,...e))})}}const zv=e=>(e=>e.replace(/r|s/g,"x").replace(/g|t/g,"y").replace(/b|p/g,"z").replace(/a|q/g,"w"))(e).split("").sort().join("");yv.prototype.assign=function(...e){if(!0!==this.isStackNode)return null!==Lv?Lv.assign(this,...e):console.error("THREE.TSL: No stack defined for assign operation. 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o=0;o<4;o++)t=Fv[e]+Fv[r]+Fv[s]+Fv[o],n=Hv[e]+Hv[r]+Hv[s]+Hv[o],i=Uv[e]+Uv[r]+Uv[s]+Uv[o],kv(t,n,i)}}}for(let e=0;e<32;e++)Rv[e]={get(){this._cache=this._cache||{};let t=this._cache[e];return void 0===t&&(t=new bv(this,new Dv(e,"uint")),this._cache[e]=t),t},set(t){this[e].assign(cA(t))}};Object.defineProperties(yv.prototype,Rv);const Xv=new WeakMap,Gv=function(e,t=null){for(const n in e)e[n]=cA(e[n],t);return e},Vv=function(e,t=null){const n=e.length;for(let i=0;i<n;i++)e[i]=cA(e[i],t);return e},Wv=function(e,t=null,n=null,i=null){function r(e){return null!==i?(e=cA(Object.assign(e,i)),!0===i.intent&&(e=e.toVarIntent())):e=cA(e),e}let s,o,a,l=t;function u(t){let n;return n=l?/[a-z]/i.test(l)?l+"()":l:e.type,void 0!==o&&t.length<o?(console.error(`THREE.TSL: "${n}" parameter length is less than minimum required.`),t.concat(new Array(o-t.length).fill(0))):void 0!==a&&t.length>a?(console.error(`THREE.TSL: "${n}" parameter length exceeds limit.`),t.slice(0,a)):t}return null===t?s=(...t)=>r(new e(...fA(u(t)))):null!==n?(n=cA(n),s=(...i)=>r(new e(t,...fA(u(i)),n))):s=(...n)=>r(new e(t,...fA(u(n)))),s.setParameterLength=(...e)=>(1===e.length?o=a=e[0]:2===e.length&&([o,a]=e),s),s.setName=e=>(l=e,s),s},Qv=function(e,...t){return cA(new e(...fA(t)))};class Zv extends yv{constructor(e,t){super(),this.shaderNode=e,this.rawInputs=t,this.isShaderCallNodeInternal=!0}getNodeType(e){return this.shaderNode.nodeType||this.getOutputNode(e).getNodeType(e)}getMemberType(e,t){return this.getOutputNode(e).getMemberType(e,t)}call(e){const{shaderNode:t,rawInputs:n}=this,i=e.getNodeProperties(t),r=e.getClosestSubBuild(t.subBuilds)||"",s=r||"default";if(i[s])return i[s];const o=e.subBuildFn;e.subBuildFn=r;let a=null;if(t.layout){let i=Xv.get(e.constructor);void 0===i&&(i=new WeakMap,Xv.set(e.constructor,i));let r=i.get(t);void 0===r&&(r=cA(e.buildFunctionNode(t)),i.set(t,r)),e.addInclude(r);const s=n?function(e){let t;hA(e);t=e[0]&&(e[0].isNode||Object.getPrototypeOf(e[0])!==Object.prototype)?[...e]:e[0];return t}(n):null;a=cA(r.call(s))}else{const i=new Proxy(e,{get:(e,t,n)=>{let i;return i=Symbol.iterator===t?function*(){yield}:Reflect.get(e,t,n),i}}),r=n?function(e){let t=0;return hA(e),new Proxy(e,{get:(n,i,r)=>{let s;if("length"===i)return s=e.length,s;if(Symbol.iterator===i)s=function*(){for(const t of e)yield cA(t)};else{if(e.length>0)if(Object.getPrototypeOf(e[0])===Object.prototype){const n=e[0];s=void 0===n[i]?n[t++]:Reflect.get(n,i,r)}else e[0]instanceof yv&&(s=void 0===e[i]?e[t++]:Reflect.get(e,i,r));else s=Reflect.get(n,i,r);s=cA(s)}return s}})}(n):null,s=Array.isArray(n)?n.length>0:null!==n,o=t.jsFunc,l=s||o.length>1?o(r,i):o(i);a=cA(l)}return e.subBuildFn=o,t.once&&(i[s]=a),a}setupOutput(e){return e.addStack(),e.stack.outputNode=this.call(e),e.removeStack()}getOutputNode(e){const t=e.getNodeProperties(this),n=e.getSubBuildOutput(this);return t[n]=t[n]||this.setupOutput(e),t[n].subBuild=e.getClosestSubBuild(this),t[n]}build(e,t=null){let n=null;const i=e.getBuildStage(),r=e.getNodeProperties(this),s=e.getSubBuildOutput(this),o=this.getOutputNode(e);if("setup"===i){const t=e.getSubBuildProperty("initialized",this);if(!0!==r[t]&&(r[t]=!0,r[s]=this.getOutputNode(e),r[s].build(e),this.shaderNode.subBuilds))for(const t of e.chaining){const n=e.getDataFromNode(t,"any");n.subBuilds=n.subBuilds||new Set;for(const e of this.shaderNode.subBuilds)n.subBuilds.add(e)}n=r[s]}else"analyze"===i?o.build(e,t):"generate"===i&&(n=o.build(e,t)||"");return n}}class Yv extends yv{constructor(e,t){super(t),this.jsFunc=e,this.layout=null,this.global=!0,this.once=!1}setLayout(e){return this.layout=e,this}call(e=null){return cA(new Zv(this,e))}setup(){return this.call()}}const Jv=[!1,!0],Kv=[0,1,2,3],qv=[-1,-2],_v=[.5,1.5,1/3,1e-6,1e6,Math.PI,2*Math.PI,1/Math.PI,2/Math.PI,1/(2*Math.PI),Math.PI/2],$v=new Map;for(const e of Jv)$v.set(e,new Dv(e));const eA=new Map;for(const e of Kv)eA.set(e,new Dv(e,"uint"));const tA=new Map([...eA].map((e=>new Dv(e.value,"int"))));for(const e of qv)tA.set(e,new Dv(e,"int"));const nA=new Map([...tA].map((e=>new Dv(e.value))));for(const e of _v)nA.set(e,new Dv(e));for(const e of _v)nA.set(-e,new Dv(-e));const iA={bool:$v,uint:eA,ints:tA,float:nA},rA=new Map([...$v,...nA]),sA=(e,t)=>rA.has(e)?rA.get(e):!0===e.isNode?e:new Dv(e,t),oA=function(e,t=null){return(...n)=>{for(const t of n)if(void 0===t)return console.error(`THREE.TSL: Invalid parameter for the type "${e}".`),cA(new Dv(0,e));if((0===n.length||!["bool","float","int","uint"].includes(e)&&n.every((e=>{const t=typeof e;return"object"!==t&&"function"!==t})))&&(n=[av(e,...n)]),1===n.length&&null!==t&&t.has(n[0]))return dA(t.get(n[0]));if(1===n.length){const t=sA(n[0],e);return t.nodeType===e?dA(t):dA(new wv(t,e))}const i=n.map((e=>sA(e)));return dA(new Mv(i,e))}},aA=e=>"object"==typeof e&&null!==e?e.value:e,lA=e=>null!=e?e.nodeType||e.convertTo||("string"==typeof e?e:null):null;function uA(e,t){return new Yv(e,t)}const cA=(e,t=null)=>function(e,t=null){const n=ov(e);return"node"===n?e:null===t&&("float"===n||"boolean"===n)||n&&"shader"!==n&&"string"!==n?cA(sA(e,t)):"shader"===n?e.isFn?e:xA(e):e}(e,t),dA=(e,t=null)=>cA(e,t).toVarIntent(),hA=(e,t=null)=>new Gv(e,t),fA=(e,t=null)=>new Vv(e,t),pA=(e,t=null,n=null,i=null)=>new Wv(e,t,n,i),gA=(e,...t)=>new Qv(e,...t),mA=(e,t=null,n=null,i={})=>new Wv(e,t,n,{intent:!0,...i});let vA=0;class AA extends yv{constructor(e,t=null){super();let n=null;null!==t&&("object"==typeof t?n=t.return:("string"==typeof t?n=t:console.error("THREE.TSL: Invalid layout type."),t=null)),this.shaderNode=new uA(e,n),null!==t&&this.setLayout(t),this.isFn=!0}setLayout(e){const t=this.shaderNode.nodeType;if("object"!=typeof e.inputs){const n={name:"fn"+vA++,type:t,inputs:[]};for(const t in e)"return"!==t&&n.inputs.push({name:t,type:e[t]});e=n}return this.shaderNode.setLayout(e),this}getNodeType(e){return this.shaderNode.getNodeType(e)||"float"}call(...e){const t=this.shaderNode.call(e);return"void"===this.shaderNode.nodeType&&t.toStack(),t.toVarIntent()}once(e=null){return this.shaderNode.once=!0,this.shaderNode.subBuilds=e,this}generate(e){const t=this.getNodeType(e);return console.error('THREE.TSL: "Fn()" was declared but not invoked. 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n===e&&(e=av(n)),e=e&&!0===e.isNode?e.node&&e.node.value||e.value:e,cA(new Px(e,n))};class Bx extends Cv{static get type(){return"ArrayNode"}constructor(e,t,n=null){super(e),this.count=t,this.values=n,this.isArrayNode=!0}getArrayCount(){return this.count}getNodeType(e){return null===this.nodeType&&(this.nodeType=this.values[0].getNodeType(e)),this.nodeType}getElementType(e){return this.getNodeType(e)}generate(e){const t=this.getNodeType(e);return e.generateArray(t,this.count,this.values)}}const Dx=(...e)=>{let t;if(1===e.length){const n=e[0];t=new Bx(null,n.length,n)}else{const n=e[0],i=e[1];t=new Bx(n,i)}return cA(t)};Ov("toArray",((e,t)=>Dx(Array(t).fill(e))));class Ix extends Cv{static get type(){return"AssignNode"}constructor(e,t){super(),this.targetNode=e,this.sourceNode=t,this.isAssignNode=!0}hasDependencies(){return!1}getNodeType(e,t){return"void"!==t?this.targetNode.getNodeType(e):"void"}needsSplitAssign(e){const{targetNode:t}=this;if(!1===e.isAvailable("swizzleAssign")&&t.isSplitNode&&t.components.length>1){const n=e.getTypeLength(t.node.getNodeType(e));return vv.join("").slice(0,n)!==t.components}return!1}setup(e){const{targetNode:t,sourceNode:n}=this,i=t.getScope();e.getNodeProperties(i).assign=!0;const r=e.getNodeProperties(this);r.sourceNode=n,r.targetNode=t.context({assign:!0})}generate(e,t){const{targetNode:n,sourceNode:i}=e.getNodeProperties(this),r=this.needsSplitAssign(e),s=n.build(e),o=n.getNodeType(e),a=i.build(e,o),l=i.getNodeType(e),u=e.getDataFromNode(this);let c;if(!0===u.initialized)"void"!==t&&(c=s);else if(r){const i=e.getVarFromNode(this,null,o),r=e.getPropertyName(i);e.addLineFlowCode(`${r} = ${a}`,this);const l=n.node,u=l.node.context({assign:!0}).build(e);for(let t=0;t<l.components.length;t++){const n=l.components[t];e.addLineFlowCode(`${u}.${n} = ${r}[ ${t} ]`,this)}"void"!==t&&(c=s)}else c=`${s} = ${a}`,"void"!==t&&"void"!==l||(e.addLineFlowCode(c,this),"void"!==t&&(c=s));return u.initialized=!0,e.format(c,o,t)}}const Lx=pA(Ix).setParameterLength(2);Ov("assign",Lx);class jx extends Cv{static get type(){return"FunctionCallNode"}constructor(e=null,t={}){super(),this.functionNode=e,this.parameters=t}setParameters(e){return this.parameters=e,this}getParameters(){return this.parameters}getNodeType(e){return this.functionNode.getNodeType(e)}getMemberType(e,t){return this.functionNode.getMemberType(e,t)}generate(e){const t=[],n=this.functionNode,i=n.getInputs(e),r=this.parameters,s=(t,n)=>{const i=n.type;let r;return r="pointer"===i?"&"+t.build(e):t.build(e,i),r};if(Array.isArray(r)){if(r.length>i.length)console.error("THREE.TSL: The number of provided parameters exceeds the expected number of inputs in 'Fn()'."),r.length=i.length;else if(r.length<i.length)for(console.error("THREE.TSL: The number of provided parameters is less than the expected number of inputs in 'Fn()'.");r.length<i.length;)r.push(EA(0));for(let e=0;e<r.length;e++)t.push(s(r[e],i[e]))}else for(const e of i){const n=r[e.name];void 0!==n?t.push(s(n,e)):(console.error(`THREE.TSL: Input '${e.name}' not found in 'Fn()'.`),t.push(s(EA(0),e)))}return`${n.build(e,"property")}( ${t.join(", ")} )`}}const Ox=(e,...t)=>(t=t.length>1||t[0]&&!0===t[0].isNode?fA(t):hA(t[0]),cA(new jx(cA(e),t)));Ov("call",Ox);const zx={"==":"equal","!=":"notEqual","<":"lessThan",">":"greaterThan","<=":"lessThanEqual",">=":"greaterThanEqual","%":"mod"};class Rx extends Cv{static get type(){return"OperatorNode"}constructor(e,t,n,...i){if(super(),i.length>0){let r=new Rx(e,t,n);for(let t=0;t<i.length-1;t++)r=new Rx(e,r,i[t]);t=r,n=i[i.length-1]}this.op=e,this.aNode=t,this.bNode=n,this.isOperatorNode=!0}getOperatorMethod(e,t){return e.getMethod(zx[this.op],t)}getNodeType(e,t=null){const n=this.op,i=this.aNode,r=this.bNode,s=i.getNodeType(e),o=r?r.getNodeType(e):null;if("void"===s||"void"===o)return t||"void";if("%"===n)return s;if("~"===n||"&"===n||"|"===n||"^"===n||">>"===n||"<<"===n)return e.getIntegerType(s);if("!"===n||"&&"===n||"||"===n||"^^"===n)return"bool";if("=="===n||"!="===n||"<"===n||">"===n||"<="===n||">="===n){const t=Math.max(e.getTypeLength(s),e.getTypeLength(o));return t>1?`bvec${t}`:"bool"}if(e.isMatrix(s)){if("float"===o)return s;if(e.isVector(o))return e.getVectorFromMatrix(s);if(e.isMatrix(o))return s}else if(e.isMatrix(o)){if("float"===s)return o;if(e.isVector(s))return e.getVectorFromMatrix(o)}return e.getTypeLength(o)>e.getTypeLength(s)?o:s}generate(e,t){const n=this.op,{aNode:i,bNode:r}=this,s=this.getNodeType(e,t);let o=null,a=null;"void"!==s?(o=i.getNodeType(e),a=r?r.getNodeType(e):null,"<"===n||">"===n||"<="===n||">="===n||"=="===n||"!="===n?e.isVector(o)?a=o:e.isVector(a)?o=a:o!==a&&(o=a="float"):">>"===n||"<<"===n?(o=s,a=e.changeComponentType(a,"uint")):"%"===n?(o=s,a=e.isInteger(o)&&e.isInteger(a)?a:o):e.isMatrix(o)?"float"===a?a="float":e.isVector(a)?a=e.getVectorFromMatrix(o):e.isMatrix(a)||(o=a=s):o=e.isMatrix(a)?"float"===o?"float":e.isVector(o)?e.getVectorFromMatrix(a):a=s:a=s):o=a=s;const l=i.build(e,o),u=r?r.build(e,a):null,c=e.getFunctionOperator(n);if("void"!==t){const i=e.renderer.coordinateSystem===as;if("=="===n||"!="===n||"<"===n||">"===n||"<="===n||">="===n)return i&&e.isVector(o)?e.format(`${this.getOperatorMethod(e,t)}( ${l}, ${u} )`,s,t):e.format(`( ${l} ${n} ${u} )`,s,t);if("%"===n)return e.isInteger(a)?e.format(`( ${l} % ${u} )`,s,t):e.format(`${this.getOperatorMethod(e,s)}( ${l}, ${u} )`,s,t);if("!"===n||"~"===n)return e.format(`(${n}${l})`,o,t);if(c)return e.format(`${c}( ${l}, ${u} )`,s,t);if(e.isMatrix(o)&&"float"===a)return e.format(`( ${u} ${n} ${l} )`,s,t);if("float"===o&&e.isMatrix(a))return e.format(`${l} ${n} ${u}`,s,t);{let r=`( ${l} ${n} ${u} )`;return!i&&"bool"===s&&e.isVector(o)&&e.isVector(a)&&(r=`all${r}`),e.format(r,s,t)}}if("void"!==o)return c?e.format(`${c}( ${l}, ${u} )`,s,t):e.isMatrix(o)&&"float"===a?e.format(`${u} ${n} ${l}`,s,t):e.format(`${l} ${n} ${u}`,s,t)}serialize(e){super.serialize(e),e.op=this.op}deserialize(e){super.deserialize(e),this.op=e.op}}const kx=mA(Rx,"+").setParameterLength(2,1/0).setName("add"),Fx=mA(Rx,"-").setParameterLength(2,1/0).setName("sub"),Hx=mA(Rx,"*").setParameterLength(2,1/0).setName("mul"),Ux=mA(Rx,"/").setParameterLength(2,1/0).setName("div"),Xx=mA(Rx,"%").setParameterLength(2).setName("mod"),Gx=mA(Rx,"==").setParameterLength(2).setName("equal"),Vx=mA(Rx,"!=").setParameterLength(2).setName("notEqual"),Wx=mA(Rx,"<").setParameterLength(2).setName("lessThan"),Qx=mA(Rx,">").setParameterLength(2).setName("greaterThan"),Zx=mA(Rx,"<=").setParameterLength(2).setName("lessThanEqual"),Yx=mA(Rx,">=").setParameterLength(2).setName("greaterThanEqual"),Jx=mA(Rx,"&&").setParameterLength(2,1/0).setName("and"),Kx=mA(Rx,"||").setParameterLength(2,1/0).setName("or"),qx=mA(Rx,"!").setParameterLength(1).setName("not"),_x=mA(Rx,"^^").setParameterLength(2).setName("xor"),$x=mA(Rx,"&").setParameterLength(2).setName("bitAnd"),ey=mA(Rx,"~").setParameterLength(2).setName("bitNot"),ty=mA(Rx,"|").setParameterLength(2).setName("bitOr"),ny=mA(Rx,"^").setParameterLength(2).setName("bitXor"),iy=mA(Rx,"<<").setParameterLength(2).setName("shiftLeft"),ry=mA(Rx,">>").setParameterLength(2).setName("shiftRight"),sy=xA((([e])=>(e.addAssign(1),e))),oy=xA((([e])=>(e.subAssign(1),e))),ay=xA((([e])=>{const t=TA(e).toConst();return e.addAssign(1),t})),ly=xA((([e])=>{const t=TA(e).toConst();return e.subAssign(1),t}));Ov("add",kx),Ov("sub",Fx),Ov("mul",Hx),Ov("div",Ux),Ov("mod",Xx),Ov("equal",Gx),Ov("notEqual",Vx),Ov("lessThan",Wx),Ov("greaterThan",Qx),Ov("lessThanEqual",Zx),Ov("greaterThanEqual",Yx),Ov("and",Jx),Ov("or",Kx),Ov("not",qx),Ov("xor",_x),Ov("bitAnd",$x),Ov("bitNot",ey),Ov("bitOr",ty),Ov("bitXor",ny),Ov("shiftLeft",iy),Ov("shiftRight",ry),Ov("incrementBefore",sy),Ov("decrementBefore",oy),Ov("increment",ay),Ov("decrement",ly);const uy=(e,t)=>(console.warn('THREE.TSL: "modInt()" is deprecated. Use "mod( int( ... ) )" instead.'),Xx(TA(e),TA(t)));Ov("modInt",uy);class cy extends Cv{static get type(){return"MathNode"}constructor(e,t,n=null,i=null){if(super(),(e===cy.MAX||e===cy.MIN)&&arguments.length>3){let r=new cy(e,t,n);for(let t=2;t<arguments.length-1;t++)r=new cy(e,r,arguments[t]);t=r,n=arguments[arguments.length-1],i=null}this.method=e,this.aNode=t,this.bNode=n,this.cNode=i,this.isMathNode=!0}getInputType(e){const t=this.aNode.getNodeType(e),n=this.bNode?this.bNode.getNodeType(e):null,i=this.cNode?this.cNode.getNodeType(e):null,r=e.isMatrix(t)?0:e.getTypeLength(t),s=e.isMatrix(n)?0:e.getTypeLength(n),o=e.isMatrix(i)?0:e.getTypeLength(i);return r>s&&r>o?t:s>o?n:o>r?i:t}getNodeType(e){const t=this.method;return t===cy.LENGTH||t===cy.DISTANCE||t===cy.DOT?"float":t===cy.CROSS?"vec3":t===cy.ALL||t===cy.ANY?"bool":t===cy.EQUALS?e.changeComponentType(this.aNode.getNodeType(e),"bool"):this.getInputType(e)}setup(e){const{aNode:t,bNode:n,method:i}=this;let r=null;if(i===cy.ONE_MINUS)r=Fx(1,t);else if(i===cy.RECIPROCAL)r=Ux(1,t);else if(i===cy.DIFFERENCE)r=Ly(Fx(t,n));else if(i===cy.TRANSFORM_DIRECTION){let i=t,s=n;e.isMatrix(i.getNodeType(e))?s=RA(LA(s),0):i=RA(LA(i),0);const o=Hx(i,s).xyz;r=Ey(o)}return null!==r?r:super.setup(e)}generate(e,t){if(e.getNodeProperties(this).outputNode)return super.generate(e,t);let n=this.method;const i=this.getNodeType(e),r=this.getInputType(e),s=this.aNode,o=this.bNode,a=this.cNode,l=e.renderer.coordinateSystem;if(n===cy.NEGATE)return e.format("( - "+s.build(e,r)+" )",i,t);{const u=[];return n===cy.CROSS?u.push(s.build(e,i),o.build(e,i)):l===as&&n===cy.STEP?u.push(s.build(e,1===e.getTypeLength(s.getNodeType(e))?"float":r),o.build(e,r)):l!==as||n!==cy.MIN&&n!==cy.MAX?n===cy.REFRACT?u.push(s.build(e,r),o.build(e,r),a.build(e,"float")):n===cy.MIX?u.push(s.build(e,r),o.build(e,r),a.build(e,1===e.getTypeLength(a.getNodeType(e))?"float":r)):(l===ls&&n===cy.ATAN&&null!==o&&(n="atan2"),"fragment"===e.shaderStage||n!==cy.DFDX&&n!==cy.DFDY||(console.warn(`THREE.TSL: '${n}' is not supported in the ${e.shaderStage} stage.`),n="/*"+n+"*/"),u.push(s.build(e,r)),null!==o&&u.push(o.build(e,r)),null!==a&&u.push(a.build(e,r))):u.push(s.build(e,r),o.build(e,1===e.getTypeLength(o.getNodeType(e))?"float":r)),e.format(`${e.getMethod(n,i)}( ${u.join(", ")} )`,i,t)}}serialize(e){super.serialize(e),e.method=this.method}deserialize(e){super.deserialize(e),this.method=e.method}}cy.ALL="all",cy.ANY="any",cy.RADIANS="radians",cy.DEGREES="degrees",cy.EXP="exp",cy.EXP2="exp2",cy.LOG="log",cy.LOG2="log2",cy.SQRT="sqrt",cy.INVERSE_SQRT="inversesqrt",cy.FLOOR="floor",cy.CEIL="ceil",cy.NORMALIZE="normalize",cy.FRACT="fract",cy.SIN="sin",cy.COS="cos",cy.TAN="tan",cy.ASIN="asin",cy.ACOS="acos",cy.ATAN="atan",cy.ABS="abs",cy.SIGN="sign",cy.LENGTH="length",cy.NEGATE="negate",cy.ONE_MINUS="oneMinus",cy.DFDX="dFdx",cy.DFDY="dFdy",cy.ROUND="round",cy.RECIPROCAL="reciprocal",cy.TRUNC="trunc",cy.FWIDTH="fwidth",cy.TRANSPOSE="transpose",cy.DETERMINANT="determinant",cy.INVERSE="inverse",cy.EQUALS="equals",cy.MIN="min",cy.MAX="max",cy.STEP="step",cy.REFLECT="reflect",cy.DISTANCE="distance",cy.DIFFERENCE="difference",cy.DOT="dot",cy.CROSS="cross",cy.POW="pow",cy.TRANSFORM_DIRECTION="transformDirection",cy.MIX="mix",cy.CLAMP="clamp",cy.REFRACT="refract",cy.SMOOTHSTEP="smoothstep",cy.FACEFORWARD="faceforward";const dy=EA(1e-6),hy=EA(Math.PI),fy=(Math.PI,mA(cy,cy.ALL).setParameterLength(1)),py=mA(cy,cy.ANY).setParameterLength(1),gy=mA(cy,cy.RADIANS).setParameterLength(1),my=mA(cy,cy.DEGREES).setParameterLength(1),vy=mA(cy,cy.EXP).setParameterLength(1),Ay=mA(cy,cy.EXP2).setParameterLength(1),xy=mA(cy,cy.LOG).setParameterLength(1),yy=mA(cy,cy.LOG2).setParameterLength(1),by=mA(cy,cy.SQRT).setParameterLength(1),wy=mA(cy,cy.INVERSE_SQRT).setParameterLength(1),Cy=mA(cy,cy.FLOOR).setParameterLength(1),My=mA(cy,cy.CEIL).setParameterLength(1),Ey=mA(cy,cy.NORMALIZE).setParameterLength(1),Ty=mA(cy,cy.FRACT).setParameterLength(1),Sy=mA(cy,cy.SIN).setParameterLength(1),Py=mA(cy,cy.COS).setParameterLength(1),Ny=mA(cy,cy.TAN).setParameterLength(1),By=mA(cy,cy.ASIN).setParameterLength(1),Dy=mA(cy,cy.ACOS).setParameterLength(1),Iy=mA(cy,cy.ATAN).setParameterLength(1,2),Ly=mA(cy,cy.ABS).setParameterLength(1),jy=mA(cy,cy.SIGN).setParameterLength(1),Oy=mA(cy,cy.LENGTH).setParameterLength(1),zy=mA(cy,cy.NEGATE).setParameterLength(1),Ry=mA(cy,cy.ONE_MINUS).setParameterLength(1),ky=mA(cy,cy.DFDX).setParameterLength(1),Fy=mA(cy,cy.DFDY).setParameterLength(1),Hy=mA(cy,cy.ROUND).setParameterLength(1),Uy=mA(cy,cy.RECIPROCAL).setParameterLength(1),Xy=mA(cy,cy.TRUNC).setParameterLength(1),Gy=mA(cy,cy.FWIDTH).setParameterLength(1),Vy=mA(cy,cy.TRANSPOSE).setParameterLength(1),Wy=mA(cy,cy.DETERMINANT).setParameterLength(1),Qy=mA(cy,cy.INVERSE).setParameterLength(1),Zy=(e,t)=>(console.warn('THREE.TSL: "equals" is deprecated. Use "equal" inside a vector instead, like: "bvec*( equal( ... ) )"'),Gx(e,t)),Yy=mA(cy,cy.MIN).setParameterLength(2,1/0),Jy=mA(cy,cy.MAX).setParameterLength(2,1/0),Ky=mA(cy,cy.STEP).setParameterLength(2),qy=mA(cy,cy.REFLECT).setParameterLength(2),_y=mA(cy,cy.DISTANCE).setParameterLength(2),$y=mA(cy,cy.DIFFERENCE).setParameterLength(2),eb=mA(cy,cy.DOT).setParameterLength(2),tb=mA(cy,cy.CROSS).setParameterLength(2),nb=mA(cy,cy.POW).setParameterLength(2),ib=e=>Hx(e,e),rb=e=>Hx(e,e,e),sb=e=>Hx(e,e,e,e),ob=mA(cy,cy.TRANSFORM_DIRECTION).setParameterLength(2),ab=e=>Hx(jy(e),nb(Ly(e),1/3)),lb=e=>eb(e,e),ub=mA(cy,cy.MIX).setParameterLength(3),cb=(e,t=0,n=1)=>cA(new cy(cy.CLAMP,cA(e),cA(t),cA(n))),db=e=>cb(e),hb=mA(cy,cy.REFRACT).setParameterLength(3),fb=mA(cy,cy.SMOOTHSTEP).setParameterLength(3),pb=mA(cy,cy.FACEFORWARD).setParameterLength(3),gb=xA((([e])=>{const t=eb(e.xy,NA(12.9898,78.233)),n=Xx(t,hy);return Ty(Sy(n).mul(43758.5453))})),mb=(e,t,n)=>ub(t,n,e),vb=(e,t,n)=>fb(t,n,e),Ab=(e,t)=>Ky(t,e),xb=(e,t)=>(console.warn('THREE.TSL: "atan2" is overloaded. Use "atan" instead.'),Iy(e,t));Ov("all",fy),Ov("any",py),Ov("equals",Zy),Ov("radians",gy),Ov("degrees",my),Ov("exp",vy),Ov("exp2",Ay),Ov("log",xy),Ov("log2",yy),Ov("sqrt",by),Ov("inverseSqrt",wy),Ov("floor",Cy),Ov("ceil",My),Ov("normalize",Ey),Ov("fract",Ty),Ov("sin",Sy),Ov("cos",Py),Ov("tan",Ny),Ov("asin",By),Ov("acos",Dy),Ov("atan",Iy),Ov("abs",Ly),Ov("sign",jy),Ov("length",Oy),Ov("lengthSq",lb),Ov("negate",zy),Ov("oneMinus",Ry),Ov("dFdx",ky),Ov("dFdy",Fy),Ov("round",Hy),Ov("reciprocal",Uy),Ov("trunc",Xy),Ov("fwidth",Gy),Ov("atan2",xb),Ov("min",Yy),Ov("max",Jy),Ov("step",Ab),Ov("reflect",qy),Ov("distance",_y),Ov("dot",eb),Ov("cross",tb),Ov("pow",nb),Ov("pow2",ib),Ov("pow3",rb),Ov("pow4",sb),Ov("transformDirection",ob),Ov("mix",mb),Ov("clamp",cb),Ov("refract",hb),Ov("smoothstep",vb),Ov("faceForward",pb),Ov("difference",$y),Ov("saturate",db),Ov("cbrt",ab),Ov("transpose",Vy),Ov("determinant",Wy),Ov("inverse",Qy),Ov("rand",gb);class yb extends yv{static get type(){return"ConditionalNode"}constructor(e,t,n=null){super(),this.condNode=e,this.ifNode=t,this.elseNode=n}getNodeType(e){const{ifNode:t,elseNode:n}=e.getNodeProperties(this);if(void 0===t)return e.flowBuildStage(this,"setup"),this.getNodeType(e);const i=t.getNodeType(e);if(null!==n){const t=n.getNodeType(e);if(e.getTypeLength(t)>e.getTypeLength(i))return t}return i}setup(e){const t=this.condNode.cache(),n=this.ifNode.cache(),i=this.elseNode?this.elseNode.cache():null,r=e.context.nodeBlock;e.getDataFromNode(n).parentNodeBlock=r,null!==i&&(e.getDataFromNode(i).parentNodeBlock=r);const s=e.context.uniformFlow,o=e.getNodeProperties(this);o.condNode=t,o.ifNode=s?n:n.context({nodeBlock:n}),o.elseNode=i?s?i:i.context({nodeBlock:i}):null}generate(e,t){const n=this.getNodeType(e),i=e.getDataFromNode(this);if(void 0!==i.nodeProperty)return i.nodeProperty;const{condNode:r,ifNode:s,elseNode:o}=e.getNodeProperties(this),a=e.currentFunctionNode,l="void"!==t,u=l?ZA(n).build(e):"";i.nodeProperty=u;const c=r.build(e,"bool");if(e.context.uniformFlow&&null!==o){const i=s.build(e,n),r=o.build(e,n),a=e.getTernary(c,i,r);return e.format(a,n,t)}e.addFlowCode(`\n${e.tab}if ( ${c} ) {\n\n`).addFlowTab();let d=s.build(e,n);if(d&&(l?d=u+" = "+d+";":(d="return "+d+";",null===a&&(console.warn("THREE.TSL: Return statement used in an inline 'Fn()'. Define a layout struct to allow return values."),d="// "+d))),e.removeFlowTab().addFlowCode(e.tab+"\t"+d+"\n\n"+e.tab+"}"),null!==o){e.addFlowCode(" else {\n\n").addFlowTab();let t=o.build(e,n);t&&(l?t=u+" = "+t+";":(t="return "+t+";",null===a&&(console.warn("THREE.TSL: Return statement used in an inline 'Fn()'. Define a layout struct to allow return values."),t="// "+t))),e.removeFlowTab().addFlowCode(e.tab+"\t"+t+"\n\n"+e.tab+"}\n\n")}else e.addFlowCode("\n\n");return e.format(u,n,t)}}const bb=pA(yb).setParameterLength(2,3);Ov("select",bb);class wb extends yv{static get type(){return"ContextNode"}constructor(e,t={}){super(),this.isContextNode=!0,this.node=e,this.value=t}getScope(){return this.node.getScope()}getNodeType(e){return this.node.getNodeType(e)}getMemberType(e,t){return this.node.getMemberType(e,t)}analyze(e){const t=e.getContext();e.setContext({...e.context,...this.value}),this.node.build(e),e.setContext(t)}setup(e){const t=e.getContext();e.setContext({...e.context,...this.value}),this.node.build(e),e.setContext(t)}generate(e,t){const n=e.getContext();e.setContext({...e.context,...this.value});const i=this.node.build(e,t);return e.setContext(n),i}}const Cb=pA(wb).setParameterLength(1,2),Mb=e=>Cb(e,{uniformFlow:!0}),Eb=(e,t)=>Cb(e,{nodeName:t});function Tb(e,t){return console.warn('THREE.TSL: "label()" has been deprecated. Use "setName()" instead.'),Eb(e,t)}Ov("context",Cb),Ov("label",Tb),Ov("uniformFlow",Mb),Ov("setName",Eb);class Sb extends yv{static get type(){return"VarNode"}constructor(e,t=null,n=!1){super(),this.node=e,this.name=t,this.global=!0,this.isVarNode=!0,this.readOnly=n,this.parents=!0,this.intent=!1}setIntent(e){return this.intent=e,this}getIntent(){return this.intent}getMemberType(e,t){return this.node.getMemberType(e,t)}getElementType(e){return this.node.getElementType(e)}getNodeType(e){return this.node.getNodeType(e)}getArrayCount(e){return this.node.getArrayCount(e)}build(...e){if(!0===this.intent){if(!0!==e[0].getNodeProperties(this).assign)return this.node.build(...e)}return super.build(...e)}generate(e){const{node:t,name:n,readOnly:i}=this,{renderer:r}=e,s=!0===r.backend.isWebGPUBackend;let o=!1,a=!1;i&&(o=e.isDeterministic(t),a=s?i:o);const l=e.getVectorType(this.getNodeType(e)),u=t.build(e,l),c=e.getVarFromNode(this,n,l,void 0,a),d=e.getPropertyName(c);let h=d;if(a)if(s)h=o?`const ${d}`:`let ${d}`;else{const n=t.getArrayCount(e);h=`const ${e.getVar(c.type,d,n)}`}return e.addLineFlowCode(`${h} = ${u}`,this),d}}const Pb=pA(Sb),Nb=(e,t=null)=>Pb(e,t).toStack(),Bb=(e,t=null)=>Pb(e,t,!0).toStack(),Db=e=>null===bA()?e:Pb(e).setIntent(!0).toStack();Ov("toVar",Nb),Ov("toConst",Bb),Ov("toVarIntent",Db);class Ib extends yv{static get type(){return"SubBuild"}constructor(e,t,n=null){super(n),this.node=e,this.name=t,this.isSubBuildNode=!0}getNodeType(e){if(null!==this.nodeType)return this.nodeType;e.addSubBuild(this.name);const t=this.node.getNodeType(e);return e.removeSubBuild(),t}build(e,...t){e.addSubBuild(this.name);const n=this.node.build(e,...t);return e.removeSubBuild(),n}}const Lb=(e,t,n=null)=>cA(new Ib(cA(e),t,n));class jb extends yv{static get type(){return"VaryingNode"}constructor(e,t=null){super(),this.node=e,this.name=t,this.isVaryingNode=!0,this.interpolationType=null,this.interpolationSampling=null,this.global=!0}setInterpolation(e,t=null){return this.interpolationType=e,this.interpolationSampling=t,this}getHash(e){return this.name||super.getHash(e)}getNodeType(e){return this.node.getNodeType(e)}setupVarying(e){const t=e.getNodeProperties(this);let n=t.varying;if(void 0===n){const i=this.name,r=this.getNodeType(e),s=this.interpolationType,o=this.interpolationSampling;t.varying=n=e.getVaryingFromNode(this,i,r,s,o),t.node=Lb(this.node,"VERTEX")}return n.needsInterpolation||(n.needsInterpolation="fragment"===e.shaderStage),n}setup(e){this.setupVarying(e),e.flowNodeFromShaderStage(dv.VERTEX,this.node)}analyze(e){this.setupVarying(e),e.flowNodeFromShaderStage(dv.VERTEX,this.node)}generate(e){const t=e.getSubBuildProperty("property",e.currentStack),n=e.getNodeProperties(this),i=this.setupVarying(e);if(void 0===n[t]){const r=this.getNodeType(e),s=e.getPropertyName(i,dv.VERTEX);e.flowNodeFromShaderStage(dv.VERTEX,n.node,r,s),n[t]=s}return e.getPropertyName(i)}}const Ob=pA(jb).setParameterLength(1,2),zb=e=>Ob(e);Ov("toVarying",Ob),Ov("toVertexStage",zb),Ov("varying",((...e)=>(console.warn("THREE.TSL: .varying() has been renamed to .toVarying()."),Ob(...e)))),Ov("vertexStage",((...e)=>(console.warn("THREE.TSL: .vertexStage() has been renamed to .toVertexStage()."),Ob(...e))));const Rb=xA((([e])=>{const t=e.mul(.9478672986).add(.0521327014).pow(2.4),n=e.mul(.0773993808),i=e.lessThanEqual(.04045);return ub(t,n,i)})).setLayout({name:"sRGBTransferEOTF",type:"vec3",inputs:[{name:"color",type:"vec3"}]}),kb=xA((([e])=>{const t=e.pow(.41666).mul(1.055).sub(.055),n=e.mul(12.92),i=e.lessThanEqual(.0031308);return ub(t,n,i)})).setLayout({name:"sRGBTransferOETF",type:"vec3",inputs:[{name:"color",type:"vec3"}]}),Fb="WorkingColorSpace";class Hb extends Cv{static get type(){return"ColorSpaceNode"}constructor(e,t,n){super("vec4"),this.colorNode=e,this.source=t,this.target=n}resolveColorSpace(e,t){return t===Fb?ks.workingColorSpace:"OutputColorSpace"===t?e.context.outputColorSpace||e.renderer.outputColorSpace:t}setup(e){const{colorNode:t}=this,n=this.resolveColorSpace(e,this.source),i=this.resolveColorSpace(e,this.target);let r=t;return!1!==ks.enabled&&n!==i&&n&&i?(ks.getTransfer(n)===es&&(r=RA(Rb(r.rgb),r.a)),ks.getPrimaries(n)!==ks.getPrimaries(i)&&(r=RA(XA(ks._getMatrix(new Ps,n,i)).mul(r.rgb),r.a)),ks.getTransfer(i)===es&&(r=RA(kb(r.rgb),r.a)),r):r}}const Ub=(e,t)=>cA(new Hb(cA(e),Fb,t)),Xb=(e,t)=>cA(new Hb(cA(e),t,Fb));Ov("workingToColorSpace",Ub),Ov("colorSpaceToWorking",Xb);let Gb=class extends bv{static get type(){return"ReferenceElementNode"}constructor(e,t){super(e,t),this.referenceNode=e,this.isReferenceElementNode=!0}getNodeType(){return this.referenceNode.uniformType}generate(e){const t=super.generate(e),n=this.referenceNode.getNodeType(),i=this.getNodeType();return e.format(t,n,i)}};class Vb extends yv{static get type(){return"ReferenceBaseNode"}constructor(e,t,n=null,i=null){super(),this.property=e,this.uniformType=t,this.object=n,this.count=i,this.properties=e.split("."),this.reference=n,this.node=null,this.group=null,this.updateType=hv.OBJECT}setGroup(e){return this.group=e,this}element(e){return cA(new Gb(this,cA(e)))}setNodeType(e){const t=Nx(null,e);null!==this.group&&t.setGroup(this.group),this.node=t}getNodeType(e){return null===this.node&&(this.updateReference(e),this.updateValue()),this.node.getNodeType(e)}getValueFromReference(e=this.reference){const{properties:t}=this;let n=e[t[0]];for(let e=1;e<t.length;e++)n=n[t[e]];return n}updateReference(e){return this.reference=null!==this.object?this.object:e.object,this.reference}setup(){return this.updateValue(),this.node}update(){this.updateValue()}updateValue(){null===this.node&&this.setNodeType(this.uniformType);const e=this.getValueFromReference();Array.isArray(e)?this.node.array=e:this.node.value=e}}class Wb extends Vb{static get type(){return"RendererReferenceNode"}constructor(e,t,n=null){super(e,t,n),this.renderer=n,this.setGroup(Tx)}updateReference(e){return this.reference=null!==this.renderer?this.renderer:e.renderer,this.reference}}const Qb=(e,t,n=null)=>cA(new Wb(e,t,n));class Zb extends Cv{static get type(){return"ToneMappingNode"}constructor(e,t=Jb,n=null){super("vec3"),this.toneMapping=e,this.exposureNode=t,this.colorNode=n}customCacheKey(){return ev(this.toneMapping)}setup(e){const t=this.colorNode||e.context.color,n=this.toneMapping;if(0===n)return t;let i=null;const r=e.renderer.library.getToneMappingFunction(n);return null!==r?i=RA(r(t.rgb,this.exposureNode),t.a):(console.error("ToneMappingNode: Unsupported Tone Mapping configuration.",n),i=t),i}}const Yb=(e,t,n)=>cA(new Zb(e,cA(t),cA(n))),Jb=Qb("toneMappingExposure","float");Ov("toneMapping",((e,t,n)=>Yb(t,n,e)));class Kb extends Nv{static get type(){return"BufferAttributeNode"}constructor(e,t=null,n=0,i=0){super(e,t),this.isBufferNode=!0,this.bufferType=t,this.bufferStride=n,this.bufferOffset=i,this.usage=rs,this.instanced=!1,this.attribute=null,this.global=!0,e&&!0===e.isBufferAttribute&&(this.attribute=e,this.usage=e.usage,this.instanced=e.isInstancedBufferAttribute)}getHash(e){if(0===this.bufferStride&&0===this.bufferOffset){let t=e.globalCache.getData(this.value);return void 0===t&&(t={node:this},e.globalCache.setData(this.value,t)),t.node.uuid}return this.uuid}getNodeType(e){return null===this.bufferType&&(this.bufferType=e.getTypeFromAttribute(this.attribute)),this.bufferType}setup(e){if(null!==this.attribute)return;const t=this.getNodeType(e),n=this.value,i=e.getTypeLength(t),r=this.bufferStride||i,s=this.bufferOffset,o=!0===n.isInterleavedBuffer?n:new Cl(n,r),a=new El(o,i,s);o.setUsage(this.usage),this.attribute=a,this.attribute.isInstancedBufferAttribute=this.instanced}generate(e){const t=this.getNodeType(e),n=e.getBufferAttributeFromNode(this,t),i=e.getPropertyName(n);let r=null;if("vertex"===e.shaderStage||"compute"===e.shaderStage)this.name=i,r=i;else{r=Ob(this).build(e,t)}return r}getInputType(){return"bufferAttribute"}setUsage(e){return this.usage=e,this.attribute&&!0===this.attribute.isBufferAttribute&&(this.attribute.usage=e),this}setInstanced(e){return this.instanced=e,this}}const qb=(e,t=null,n=0,i=0)=>cA(new Kb(e,t,n,i)),_b=(e,t=null,n=0,i=0)=>qb(e,t,n,i).setUsage(ss),$b=(e,t=null,n=0,i=0)=>qb(e,t,n,i).setInstanced(!0),ew=(e,t=null,n=0,i=0)=>_b(e,t,n,i).setInstanced(!0);Ov("toAttribute",(e=>qb(e.value)));class tw extends yv{static get type(){return"ComputeNode"}constructor(e,t){super("void"),this.isComputeNode=!0,this.computeNode=e,this.workgroupSize=t,this.count=null,this.version=1,this.name="",this.updateBeforeType=hv.OBJECT,this.onInitFunction=null}setCount(e){return this.count=e,this}getCount(){return this.count}dispose(){this.dispatchEvent({type:"dispose"})}setName(e){return this.name=e,this}label(e){return console.warn('THREE.TSL: "label()" has been deprecated. Use "setName()" instead.'),this.setName(e)}onInit(e){return this.onInitFunction=e,this}updateBefore({renderer:e}){e.compute(this)}setup(e){const t=this.computeNode.build(e);if(t){e.getNodeProperties(this).outputComputeNode=t.outputNode,t.outputNode=null}return t}generate(e,t){const{shaderStage:n}=e;if("compute"===n){const t=this.computeNode.build(e,"void");""!==t&&e.addLineFlowCode(t,this)}else{const n=e.getNodeProperties(this).outputComputeNode;if(n)return n.build(e,t)}}}const nw=(e,t=[64])=>{(0===t.length||t.length>3)&&console.error("THREE.TSL: compute() workgroupSize must have 1, 2, or 3 elements");for(let e=0;e<t.length;e++){const n=t[e];("number"!=typeof n||n<=0||!Number.isInteger(n))&&console.error(`THREE.TSL: compute() workgroupSize element at index [ ${e} ] must be a positive integer`)}for(;t.length<3;)t.push(1);return cA(new tw(cA(e),t))},iw=(e,t,n)=>nw(e,n).setCount(t);Ov("compute",iw),Ov("computeKernel",nw);class rw extends yv{static get type(){return"CacheNode"}constructor(e,t=!0){super(),this.node=e,this.parent=t,this.isCacheNode=!0}getNodeType(e){const t=e.getCache(),n=e.getCacheFromNode(this,this.parent);e.setCache(n);const i=this.node.getNodeType(e);return e.setCache(t),i}build(e,...t){const n=e.getCache(),i=e.getCacheFromNode(this,this.parent);e.setCache(i);const r=this.node.build(e,...t);return e.setCache(n),r}}const sw=(e,t)=>cA(new rw(cA(e),t));Ov("cache",sw);class ow extends yv{static get type(){return"BypassNode"}constructor(e,t){super(),this.isBypassNode=!0,this.outputNode=e,this.callNode=t}getNodeType(e){return this.outputNode.getNodeType(e)}generate(e){const t=this.callNode.build(e,"void");return""!==t&&e.addLineFlowCode(t,this),this.outputNode.build(e)}}const aw=pA(ow).setParameterLength(2);Ov("bypass",aw);class lw extends yv{static get type(){return"RemapNode"}constructor(e,t,n,i=EA(0),r=EA(1)){super(),this.node=e,this.inLowNode=t,this.inHighNode=n,this.outLowNode=i,this.outHighNode=r,this.doClamp=!0}setup(){const{node:e,inLowNode:t,inHighNode:n,outLowNode:i,outHighNode:r,doClamp:s}=this;let o=e.sub(t).div(n.sub(t));return!0===s&&(o=o.clamp()),o.mul(r.sub(i)).add(i)}}const uw=pA(lw,null,null,{doClamp:!1}).setParameterLength(3,5),cw=pA(lw).setParameterLength(3,5);Ov("remap",uw),Ov("remapClamp",cw);class dw extends yv{static get type(){return"ExpressionNode"}constructor(e="",t="void"){super(t),this.snippet=e}generate(e,t){const n=this.getNodeType(e),i=this.snippet;if("void"!==n)return e.format(i,n,t);e.addLineFlowCode(i,this)}}const hw=pA(dw).setParameterLength(1,2),fw=e=>(e?bb(e,hw("discard")):hw("discard")).toStack();Ov("discard",fw);class pw extends Cv{static get type(){return"RenderOutputNode"}constructor(e,t,n){super("vec4"),this.colorNode=e,this.toneMapping=t,this.outputColorSpace=n,this.isRenderOutputNode=!0}setup({context:e}){let t=this.colorNode||e.color;const n=(null!==this.toneMapping?this.toneMapping:e.toneMapping)||0,i=(null!==this.outputColorSpace?this.outputColorSpace:e.outputColorSpace)||Kr;return 0!==n&&(t=t.toneMapping(n)),i!==Kr&&i!==ks.workingColorSpace&&(t=t.workingToColorSpace(i)),t}}const gw=(e,t=null,n=null)=>cA(new pw(cA(e),t,n));Ov("renderOutput",gw);class mw extends Cv{static get type(){return"DebugNode"}constructor(e,t=null){super(),this.node=e,this.callback=t}getNodeType(e){return this.node.getNodeType(e)}setup(e){return this.node.build(e)}analyze(e){return this.node.build(e)}generate(e){const t=this.callback,n=this.node.build(e),i="--- TSL debug - "+e.shaderStage+" shader ---",r="-".repeat(i.length);let s="";return s+="// #"+i+"#\n",s+=e.flow.code.replace(/^\t/gm,"")+"\n",s+="/* ... */ "+n+" /* ... */\n",s+="// #"+r+"#\n",null!==t?t(e,s):console.log(s),n}}const vw=(e,t=null)=>cA(new mw(cA(e),t)).toStack();Ov("debug",vw);class Aw extends yv{static get type(){return"AttributeNode"}constructor(e,t=null){super(t),this.global=!0,this._attributeName=e}getHash(e){return this.getAttributeName(e)}getNodeType(e){let t=this.nodeType;if(null===t){const n=this.getAttributeName(e);if(e.hasGeometryAttribute(n)){const i=e.geometry.getAttribute(n);t=e.getTypeFromAttribute(i)}else t="float"}return t}setAttributeName(e){return this._attributeName=e,this}getAttributeName(){return this._attributeName}generate(e){const t=this.getAttributeName(e),n=this.getNodeType(e);if(!0===e.hasGeometryAttribute(t)){const i=e.geometry.getAttribute(t),r=e.getTypeFromAttribute(i),s=e.getAttribute(t,r);if("vertex"===e.shaderStage)return e.format(s.name,r,n);return Ob(this).build(e,n)}return console.warn(`AttributeNode: Vertex attribute "${t}" not found on geometry.`),e.generateConst(n)}serialize(e){super.serialize(e),e.global=this.global,e._attributeName=this._attributeName}deserialize(e){super.deserialize(e),this.global=e.global,this._attributeName=e._attributeName}}const xw=(e,t=null)=>cA(new Aw(e,t)),yw=(e=0)=>xw("uv"+(e>0?e:""),"vec2");class bw extends yv{static get type(){return"TextureSizeNode"}constructor(e,t=null){super("uvec2"),this.isTextureSizeNode=!0,this.textureNode=e,this.levelNode=t}generate(e,t){const n=this.textureNode.build(e,"property"),i=null===this.levelNode?"0":this.levelNode.build(e,"int");return e.format(`${e.getMethod("textureDimensions")}( ${n}, ${i} )`,this.getNodeType(e),t)}}const ww=pA(bw).setParameterLength(1,2);class Cw extends Px{static get type(){return"MaxMipLevelNode"}constructor(e){super(0),this._textureNode=e,this.updateType=hv.FRAME}get textureNode(){return this._textureNode}get texture(){return this._textureNode.value}update(){const e=this.texture,t=e.images,n=t&&t.length>0?t[0]&&t[0].image||t[0]:e.image;if(n&&void 0!==n.width){const{width:e,height:t}=n;this.value=Math.log2(Math.max(e,t))}}}const Mw=pA(Cw).setParameterLength(1),Ew=new Ys;class Tw extends Px{static get type(){return"TextureNode"}constructor(e=Ew,t=null,n=null,i=null){super(e),this.isTextureNode=!0,this.uvNode=t,this.levelNode=n,this.biasNode=i,this.compareNode=null,this.depthNode=null,this.gradNode=null,this.offsetNode=null,this.sampler=!0,this.updateMatrix=!1,this.updateType=hv.NONE,this.referenceNode=null,this._value=e,this._matrixUniform=null,this.setUpdateMatrix(null===t)}set value(e){this.referenceNode?this.referenceNode.value=e:this._value=e}get value(){return this.referenceNode?this.referenceNode.value:this._value}getUniformHash(){return this.value.uuid}getNodeType(){return!0===this.value.isDepthTexture?"float":this.value.type===Yi?"uvec4":this.value.type===Zi?"ivec4":"vec4"}getInputType(){return"texture"}getDefaultUV(){return yw(this.value.channel)}updateReference(){return this.value}getTransformedUV(e){return null===this._matrixUniform&&(this._matrixUniform=Nx(this.value.matrix)),this._matrixUniform.mul(LA(e,1)).xy}setUpdateMatrix(e){return this.updateMatrix=e,this.updateType=e?hv.OBJECT:hv.NONE,this}setupUV(e,t){const n=this.value;return e.isFlipY()&&(n.image instanceof ImageBitmap&&!0===n.flipY||!0===n.isRenderTargetTexture||!0===n.isFramebufferTexture||!0===n.isDepthTexture)&&(t=this.sampler?t.flipY():t.setY(TA(ww(this,this.levelNode).y).sub(t.y).sub(1))),t}setup(e){const t=e.getNodeProperties(this);t.referenceNode=this.referenceNode;const n=this.value;if(!n||!0!==n.isTexture)throw new Error("THREE.TSL: `texture( value )` function expects a valid instance of THREE.Texture().");let i=this.uvNode;null!==i&&!0!==e.context.forceUVContext||!e.context.getUV||(i=e.context.getUV(this,e)),i||(i=this.getDefaultUV()),!0===this.updateMatrix&&(i=this.getTransformedUV(i)),i=this.setupUV(e,i);let r=this.levelNode;null===r&&e.context.getTextureLevel&&(r=e.context.getTextureLevel(this)),t.uvNode=i,t.levelNode=r,t.biasNode=this.biasNode,t.compareNode=this.compareNode,t.gradNode=this.gradNode,t.depthNode=this.depthNode,t.offsetNode=this.offsetNode}generateUV(e,t){return t.build(e,!0===this.sampler?"vec2":"ivec2")}generateOffset(e,t){return t.build(e,"ivec2")}generateSnippet(e,t,n,i,r,s,o,a,l){const u=this.value;let c;return c=i?e.generateTextureLevel(u,t,n,i,s,l):r?e.generateTextureBias(u,t,n,r,s,l):a?e.generateTextureGrad(u,t,n,a,s,l):o?e.generateTextureCompare(u,t,n,o,s,l):!1===this.sampler?e.generateTextureLoad(u,t,n,s,l):e.generateTexture(u,t,n,s,l),c}generate(e,t){const n=this.value,i=e.getNodeProperties(this),r=super.generate(e,"property");if(/^sampler/.test(t))return r+"_sampler";if(e.isReference(t))return r;{const s=e.getDataFromNode(this);let o=s.propertyName;if(void 0===o){const{uvNode:t,levelNode:n,biasNode:a,compareNode:l,depthNode:u,gradNode:c,offsetNode:d}=i,h=this.generateUV(e,t),f=n?n.build(e,"float"):null,p=a?a.build(e,"float"):null,g=u?u.build(e,"int"):null,m=l?l.build(e,"float"):null,v=c?[c[0].build(e,"vec2"),c[1].build(e,"vec2")]:null,A=d?this.generateOffset(e,d):null,x=e.getVarFromNode(this);o=e.getPropertyName(x);const y=this.generateSnippet(e,r,h,f,p,g,m,v,A);e.addLineFlowCode(`${o} = ${y}`,this),s.snippet=y,s.propertyName=o}let a=o;const l=this.getNodeType(e);return e.needsToWorkingColorSpace(n)&&(a=Xb(hw(a,l),n.colorSpace).setup(e).build(e,l)),e.format(a,l,t)}}setSampler(e){return this.sampler=e,this}getSampler(){return this.sampler}uv(e){return console.warn("THREE.TextureNode: .uv() has been renamed. Use .sample() instead."),this.sample(e)}sample(e){const t=this.clone();return t.uvNode=cA(e),t.referenceNode=this.getBase(),cA(t)}load(e){return this.sample(e).setSampler(!1)}blur(e){const t=this.clone();t.biasNode=cA(e).mul(Mw(t)),t.referenceNode=this.getBase();const n=t.value;return!1===t.generateMipmaps&&(n&&!1===n.generateMipmaps||n.minFilter===Ri||n.magFilter===Ri)&&(console.warn("THREE.TSL: texture().blur() requires mipmaps and sampling. Use .generateMipmaps=true and .minFilter/.magFilter=THREE.LinearFilter in the Texture."),t.biasNode=null),cA(t)}level(e){const t=this.clone();return t.levelNode=cA(e),t.referenceNode=this.getBase(),cA(t)}size(e){return ww(this,e)}bias(e){const t=this.clone();return t.biasNode=cA(e),t.referenceNode=this.getBase(),cA(t)}getBase(){return this.referenceNode?this.referenceNode.getBase():this}compare(e){const t=this.clone();return t.compareNode=cA(e),t.referenceNode=this.getBase(),cA(t)}grad(e,t){const n=this.clone();return n.gradNode=[cA(e),cA(t)],n.referenceNode=this.getBase(),cA(n)}depth(e){const t=this.clone();return t.depthNode=cA(e),t.referenceNode=this.getBase(),cA(t)}offset(e){const t=this.clone();return t.offsetNode=cA(e),t.referenceNode=this.getBase(),cA(t)}serialize(e){super.serialize(e),e.value=this.value.toJSON(e.meta).uuid,e.sampler=this.sampler,e.updateMatrix=this.updateMatrix,e.updateType=this.updateType}deserialize(e){super.deserialize(e),this.value=e.meta.textures[e.value],this.sampler=e.sampler,this.updateMatrix=e.updateMatrix,this.updateType=e.updateType}update(){const e=this.value,t=this._matrixUniform;null!==t&&(t.value=e.matrix),!0===e.matrixAutoUpdate&&e.updateMatrix()}clone(){const e=new this.constructor(this.value,this.uvNode,this.levelNode,this.biasNode);return e.sampler=this.sampler,e.depthNode=this.depthNode,e.compareNode=this.compareNode,e.gradNode=this.gradNode,e.offsetNode=this.offsetNode,e}}const Sw=pA(Tw).setParameterLength(1,4).setName("texture"),Pw=(e=Ew,t=null,n=null,i=null)=>{let r;return e&&!0===e.isTextureNode?(r=cA(e.clone()),r.referenceNode=e.getBase(),null!==t&&(r.uvNode=cA(t)),null!==n&&(r.levelNode=cA(n)),null!==i&&(r.biasNode=cA(i))):r=Sw(e,t,n,i),r},Nw=(...e)=>Pw(...e).setSampler(!1);class Bw extends Px{static get type(){return"BufferNode"}constructor(e,t,n=0){super(e,t),this.isBufferNode=!0,this.bufferType=t,this.bufferCount=n}getElementType(e){return this.getNodeType(e)}getInputType(){return"buffer"}}const Dw=(e,t,n)=>cA(new Bw(e,t,n));class Iw extends bv{static get type(){return"UniformArrayElementNode"}constructor(e,t){super(e,t),this.isArrayBufferElementNode=!0}generate(e){const t=super.generate(e),n=this.getNodeType(),i=this.node.getPaddedType();return e.format(t,i,n)}}class Lw extends Bw{static get type(){return"UniformArrayNode"}constructor(e,t=null){super(null),this.array=e,this.elementType=null===t?ov(e[0]):t,this.paddedType=this.getPaddedType(),this.updateType=hv.RENDER,this.isArrayBufferNode=!0}getNodeType(){return this.paddedType}getElementType(){return this.elementType}getPaddedType(){const e=this.elementType;let t="vec4";return"mat2"===e?t="mat2":!0===/mat/.test(e)?t="mat4":"i"===e.charAt(0)?t="ivec4":"u"===e.charAt(0)&&(t="uvec4"),t}update(){const{array:e,value:t}=this,n=this.elementType;if("float"===n||"int"===n||"uint"===n)for(let n=0;n<e.length;n++){t[4*n]=e[n]}else if("color"===n)for(let n=0;n<e.length;n++){const i=4*n,r=e[n];t[i]=r.r,t[i+1]=r.g,t[i+2]=r.b||0}else if("mat2"===n)for(let n=0;n<e.length;n++){const i=4*n,r=e[n];t[i]=r.elements[0],t[i+1]=r.elements[1],t[i+2]=r.elements[2],t[i+3]=r.elements[3]}else if("mat3"===n)for(let n=0;n<e.length;n++){const i=16*n,r=e[n];t[i]=r.elements[0],t[i+1]=r.elements[1],t[i+2]=r.elements[2],t[i+4]=r.elements[3],t[i+5]=r.elements[4],t[i+6]=r.elements[5],t[i+8]=r.elements[6],t[i+9]=r.elements[7],t[i+10]=r.elements[8],t[i+15]=1}else if("mat4"===n)for(let n=0;n<e.length;n++){const i=16*n,r=e[n];for(let e=0;e<r.elements.length;e++)t[i+e]=r.elements[e]}else for(let n=0;n<e.length;n++){const i=4*n,r=e[n];t[i]=r.x,t[i+1]=r.y,t[i+2]=r.z||0,t[i+3]=r.w||0}}setup(e){const t=this.array.length,n=this.elementType;let i=Float32Array;const r=this.paddedType,s=e.getTypeLength(r);return"i"===n.charAt(0)&&(i=Int32Array),"u"===n.charAt(0)&&(i=Uint32Array),this.value=new i(t*s),this.bufferCount=t,this.bufferType=r,super.setup(e)}element(e){return cA(new Iw(this,cA(e)))}}const jw=(e,t)=>cA(new Lw(e,t));const Ow=pA(class extends yv{constructor(e){super("float"),this.name=e,this.isBuiltinNode=!0}generate(){return this.name}}).setParameterLength(1);let zw,Rw;class kw extends yv{static get type(){return"ScreenNode"}constructor(e){super(),this.scope=e,this._output=null,this.isViewportNode=!0}getNodeType(){return this.scope===kw.DPR?"float":this.scope===kw.VIEWPORT?"vec4":"vec2"}getUpdateType(){let e=hv.NONE;return this.scope!==kw.SIZE&&this.scope!==kw.VIEWPORT&&this.scope!==kw.DPR||(e=hv.RENDER),this.updateType=e,e}update({renderer:e}){const t=e.getRenderTarget();this.scope===kw.VIEWPORT?null!==t?Rw.copy(t.viewport):(e.getViewport(Rw),Rw.multiplyScalar(e.getPixelRatio())):this.scope===kw.DPR?this._output.value=e.getPixelRatio():null!==t?(zw.width=t.width,zw.height=t.height):e.getDrawingBufferSize(zw)}setup(){const e=this.scope;let t=null;return t=e===kw.SIZE?Nx(zw||(zw=new Cs)):e===kw.VIEWPORT?Nx(Rw||(Rw=new Js)):e===kw.DPR?Nx(1):NA(Xw.div(Uw)),this._output=t,t}generate(e){if(this.scope===kw.COORDINATE){let t=e.getFragCoord();if(e.isFlipY()){const n=e.getNodeProperties(Uw).outputNode.build(e);t=`${e.getType("vec2")}( ${t}.x, ${n}.y - ${t}.y )`}return t}return super.generate(e)}}kw.COORDINATE="coordinate",kw.VIEWPORT="viewport",kw.SIZE="size",kw.UV="uv",kw.DPR="dpr";const Fw=gA(kw,kw.DPR),Hw=gA(kw,kw.UV),Uw=gA(kw,kw.SIZE),Xw=gA(kw,kw.COORDINATE),Gw=gA(kw,kw.VIEWPORT),Vw=Gw.zw,Ww=(Gw.xy,Nx(0,"uint").setName("u_cameraIndex").setGroup(Mx("cameraIndex")).toVarying("v_cameraIndex")),Qw=Nx("float").setName("cameraNear").setGroup(Tx).onRenderUpdate((({camera:e})=>e.near)),Zw=Nx("float").setName("cameraFar").setGroup(Tx).onRenderUpdate((({camera:e})=>e.far)),Yw=xA((({camera:e})=>{let t;if(e.isArrayCamera&&e.cameras.length>0){const n=[];for(const t of e.cameras)n.push(t.projectionMatrix);t=jw(n).setGroup(Tx).setName("cameraProjectionMatrices").element(e.isMultiViewCamera?Ow("gl_ViewID_OVR"):Ww).toConst("cameraProjectionMatrix")}else t=Nx("mat4").setName("cameraProjectionMatrix").setGroup(Tx).onRenderUpdate((({camera:e})=>e.projectionMatrix));return t})).once()(),Jw=xA((({camera:e})=>{let t;if(e.isArrayCamera&&e.cameras.length>0){const n=[];for(const t of e.cameras)n.push(t.matrixWorldInverse);t=jw(n).setGroup(Tx).setName("cameraViewMatrices").element(e.isMultiViewCamera?Ow("gl_ViewID_OVR"):Ww).toConst("cameraViewMatrix")}else t=Nx("mat4").setName("cameraViewMatrix").setGroup(Tx).onRenderUpdate((({camera:e})=>e.matrixWorldInverse));return t})).once()(),Kw=xA((({camera:e})=>{let t;if(e.isArrayCamera&&e.cameras.length>0){const n=[];for(let t=0,i=e.cameras.length;t<i;t++)n.push(new Es);const i=jw(n).setGroup(Tx).setName("cameraPositions").onRenderUpdate((({camera:e},t)=>{const n=e.cameras,i=t.array;for(let e=0,t=n.length;e<t;e++)i[e].setFromMatrixPosition(n[e].matrixWorld)}));t=i.element(e.isMultiViewCamera?Ow("gl_ViewID_OVR"):Ww).toConst("cameraPosition")}else t=Nx(new Es).setName("cameraPosition").setGroup(Tx).onRenderUpdate((({camera:e},t)=>t.value.setFromMatrixPosition(e.matrixWorld)));return t})).once()(),qw=new xo;class _w extends yv{static get type(){return"Object3DNode"}constructor(e,t=null){super(),this.scope=e,this.object3d=t,this.updateType=hv.OBJECT,this.uniformNode=new Px(null)}getNodeType(){const e=this.scope;return e===_w.WORLD_MATRIX?"mat4":e===_w.POSITION||e===_w.VIEW_POSITION||e===_w.DIRECTION||e===_w.SCALE?"vec3":e===_w.RADIUS?"float":void 0}update(e){const t=this.object3d,n=this.uniformNode,i=this.scope;if(i===_w.WORLD_MATRIX)n.value=t.matrixWorld;else if(i===_w.POSITION)n.value=n.value||new Es,n.value.setFromMatrixPosition(t.matrixWorld);else if(i===_w.SCALE)n.value=n.value||new Es,n.value.setFromMatrixScale(t.matrixWorld);else if(i===_w.DIRECTION)n.value=n.value||new Es,t.getWorldDirection(n.value);else if(i===_w.VIEW_POSITION){const i=e.camera;n.value=n.value||new Es,n.value.setFromMatrixPosition(t.matrixWorld),n.value.applyMatrix4(i.matrixWorldInverse)}else if(i===_w.RADIUS){const i=e.object.geometry;null===i.boundingSphere&&i.computeBoundingSphere(),qw.copy(i.boundingSphere).applyMatrix4(t.matrixWorld),n.value=qw.radius}}generate(e){const t=this.scope;return t===_w.WORLD_MATRIX?this.uniformNode.nodeType="mat4":t===_w.POSITION||t===_w.VIEW_POSITION||t===_w.DIRECTION||t===_w.SCALE?this.uniformNode.nodeType="vec3":t===_w.RADIUS&&(this.uniformNode.nodeType="float"),this.uniformNode.build(e)}serialize(e){super.serialize(e),e.scope=this.scope}deserialize(e){super.deserialize(e),this.scope=e.scope}}_w.WORLD_MATRIX="worldMatrix",_w.POSITION="position",_w.SCALE="scale",_w.VIEW_POSITION="viewPosition",_w.DIRECTION="direction",_w.RADIUS="radius";const $w=pA(_w,_w.POSITION).setParameterLength(1);class eC extends _w{static get type(){return"ModelNode"}constructor(e){super(e)}update(e){this.object3d=e.object,super.update(e)}}const tC=gA(eC,eC.WORLD_MATRIX),nC=Nx(new Ps).onObjectUpdate((({object:e},t)=>t.value.getNormalMatrix(e.matrixWorld))),iC=xA((e=>e.renderer.overrideNodes.modelViewMatrix||rC)).once()().toVar("modelViewMatrix"),rC=Jw.mul(tC),sC=xA((e=>(e.context.isHighPrecisionModelViewMatrix=!0,Nx("mat4").onObjectUpdate((({object:e,camera:t})=>e.modelViewMatrix.multiplyMatrices(t.matrixWorldInverse,e.matrixWorld)))))).once()().toVar("highpModelViewMatrix"),oC=xA((e=>{const t=e.context.isHighPrecisionModelViewMatrix;return Nx("mat3").onObjectUpdate((({object:e,camera:n})=>(!0!==t&&e.modelViewMatrix.multiplyMatrices(n.matrixWorldInverse,e.matrixWorld),e.normalMatrix.getNormalMatrix(e.modelViewMatrix))))})).once()().toVar("highpModelNormalViewMatrix"),aC=xw("position","vec3"),lC=aC.toVarying("positionLocal"),uC=aC.toVarying("positionPrevious"),cC=xA((e=>tC.mul(lC).xyz.toVarying(e.getSubBuildProperty("v_positionWorld"))),"vec3").once(["POSITION"])(),dC=xA((()=>lC.transformDirection(tC).toVarying("v_positionWorldDirection").normalize().toVar("positionWorldDirection")),"vec3").once(["POSITION"])(),hC=xA((e=>e.context.setupPositionView().toVarying("v_positionView")),"vec3").once(["POSITION"])(),fC=hC.negate().toVarying("v_positionViewDirection").normalize().toVar("positionViewDirection");class pC extends yv{static get type(){return"FrontFacingNode"}constructor(){super("bool"),this.isFrontFacingNode=!0}generate(e){if("fragment"!==e.shaderStage)return"true";const{material:t}=e;return 1===t.side?"false":e.getFrontFacing()}}const gC=gA(pC),mC=EA(gC).mul(2).sub(1),vC=xA((([e],{material:t})=>{const n=t.side;return 1===n?e=e.mul(-1):2===n&&(e=e.mul(mC)),e})),AC=xw("normal","vec3"),xC=xA((e=>!1===e.geometry.hasAttribute("normal")?(console.warn('THREE.TSL: Vertex attribute "normal" not found on geometry.'),LA(0,1,0)):AC),"vec3").once()().toVar("normalLocal"),yC=hC.dFdx().cross(hC.dFdy()).normalize().toVar("normalFlat"),bC=xA((e=>{let t;return t=!0===e.material.flatShading?yC:SC(xC).toVarying("v_normalViewGeometry").normalize(),t}),"vec3").once()().toVar("normalViewGeometry"),wC=xA((e=>{let t=bC.transformDirection(Jw);return!0!==e.material.flatShading&&(t=t.toVarying("v_normalWorldGeometry")),t.normalize().toVar("normalWorldGeometry")}),"vec3").once()(),CC=xA((({subBuildFn:e,material:t,context:n})=>{let i;return"NORMAL"===e||"VERTEX"===e?(i=bC,!0!==t.flatShading&&(i=vC(i))):i=n.setupNormal().context({getUV:null}),i}),"vec3").once(["NORMAL","VERTEX"])().toVar("normalView"),MC=CC.transformDirection(Jw).toVar("normalWorld"),EC=xA((({subBuildFn:e,context:t})=>{let n;return n="NORMAL"===e||"VERTEX"===e?CC:t.setupClearcoatNormal().context({getUV:null}),n}),"vec3").once(["NORMAL","VERTEX"])().toVar("clearcoatNormalView"),TC=xA((([e,t=tC])=>{const n=XA(t),i=e.div(LA(n[0].dot(n[0]),n[1].dot(n[1]),n[2].dot(n[2])));return n.mul(i).xyz})),SC=xA((([e],t)=>{const n=t.renderer.overrideNodes.modelNormalViewMatrix;if(null!==n)return n.transformDirection(e);const i=nC.mul(e);return Jw.transformDirection(i)})),PC=(xA((()=>(console.warn('THREE.TSL: "transformedNormalView" is deprecated. Use "normalView" instead.'),CC))).once(["NORMAL","VERTEX"])(),xA((()=>(console.warn('THREE.TSL: "transformedNormalWorld" is deprecated. Use "normalWorld" instead.'),MC))).once(["NORMAL","VERTEX"])(),xA((()=>(console.warn('THREE.TSL: "transformedClearcoatNormalView" is deprecated. Use "clearcoatNormalView" instead.'),EC))).once(["NORMAL","VERTEX"])(),new ko),NC=new Po,BC=Nx(0).onReference((({material:e})=>e)).onObjectUpdate((({material:e})=>e.refractionRatio)),DC=Nx(1).onReference((({material:e})=>e)).onObjectUpdate((function({material:e,scene:t}){return e.envMap?e.envMapIntensity:t.environmentIntensity})),IC=Nx(new Po).onReference((function(e){return e.material})).onObjectUpdate((function({material:e,scene:t}){const n=null!==t.environment&&null===e.envMap?t.environmentRotation:e.envMapRotation;return n?(PC.copy(n),NC.makeRotationFromEuler(PC)):NC.identity(),NC})),LC=fC.negate().reflect(CC),jC=fC.negate().refract(CC,BC),OC=LC.transformDirection(Jw).toVar("reflectVector"),zC=jC.transformDirection(Jw).toVar("reflectVector"),RC=new vl;class kC extends Tw{static get type(){return"CubeTextureNode"}constructor(e,t=null,n=null,i=null){super(e,t,n,i),this.isCubeTextureNode=!0}getInputType(){return"cubeTexture"}getDefaultUV(){const e=this.value;return e.mapping===Ni?OC:e.mapping===Bi?zC:(console.error('THREE.CubeTextureNode: Mapping "%s" not supported.',e.mapping),LA(0,0,0))}setUpdateMatrix(){}setupUV(e,t){const n=this.value;return e.renderer.coordinateSystem!==ls&&n.isRenderTargetTexture||(t=LA(t.x.negate(),t.yz)),IC.mul(t)}generateUV(e,t){return t.build(e,"vec3")}}const FC=pA(kC).setParameterLength(1,4).setName("cubeTexture"),HC=(e=RC,t=null,n=null,i=null)=>{let r;return e&&!0===e.isCubeTextureNode?(r=cA(e.clone()),r.referenceNode=e,null!==t&&(r.uvNode=cA(t)),null!==n&&(r.levelNode=cA(n)),null!==i&&(r.biasNode=cA(i))):r=FC(e,t,n,i),r};class UC extends bv{static get type(){return"ReferenceElementNode"}constructor(e,t){super(e,t),this.referenceNode=e,this.isReferenceElementNode=!0}getNodeType(){return this.referenceNode.uniformType}generate(e){const t=super.generate(e),n=this.referenceNode.getNodeType(),i=this.getNodeType();return e.format(t,n,i)}}class XC extends yv{static get type(){return"ReferenceNode"}constructor(e,t,n=null,i=null){super(),this.property=e,this.uniformType=t,this.object=n,this.count=i,this.properties=e.split("."),this.reference=n,this.node=null,this.group=null,this.name=null,this.updateType=hv.OBJECT}element(e){return cA(new UC(this,cA(e)))}setGroup(e){return this.group=e,this}setName(e){return this.name=e,this}label(e){return console.warn('THREE.TSL: "label()" has been deprecated. Use "setName()" instead.'),this.setName(e)}setNodeType(e){let t=null;t=null!==this.count?Dw(null,e,this.count):Array.isArray(this.getValueFromReference())?jw(null,e):"texture"===e?Pw(null):"cubeTexture"===e?HC(null):Nx(null,e),null!==this.group&&t.setGroup(this.group),null!==this.name&&t.setName(this.name),this.node=t}getNodeType(e){return null===this.node&&(this.updateReference(e),this.updateValue()),this.node.getNodeType(e)}getValueFromReference(e=this.reference){const{properties:t}=this;let n=e[t[0]];for(let e=1;e<t.length;e++)n=n[t[e]];return n}updateReference(e){return this.reference=null!==this.object?this.object:e.object,this.reference}setup(){return this.updateValue(),this.node}update(){this.updateValue()}updateValue(){null===this.node&&this.setNodeType(this.uniformType);const e=this.getValueFromReference();Array.isArray(e)?this.node.array=e:this.node.value=e}}const GC=(e,t,n)=>cA(new XC(e,t,n)),VC=(e,t,n,i)=>cA(new XC(e,t,i,n));class WC extends XC{static get type(){return"MaterialReferenceNode"}constructor(e,t,n=null){super(e,t,n),this.material=n,this.isMaterialReferenceNode=!0}updateReference(e){return this.reference=null!==this.material?this.material:e.material,this.reference}}const QC=(e,t,n=null)=>cA(new WC(e,t,n)),ZC=yw(),YC=hC.dFdx(),JC=hC.dFdy(),KC=ZC.dFdx(),qC=ZC.dFdy(),_C=CC,$C=JC.cross(_C),eM=_C.cross(YC),tM=$C.mul(KC.x).add(eM.mul(qC.x)),nM=$C.mul(KC.y).add(eM.mul(qC.y)),iM=tM.dot(tM).max(nM.dot(nM)),rM=iM.equal(0).select(0,iM.inverseSqrt()),sM=tM.mul(rM).toVar("tangentViewFrame"),oM=nM.mul(rM).toVar("bitangentViewFrame"),aM=xA((e=>(!1===e.geometry.hasAttribute("tangent")&&e.geometry.computeTangents(),xw("tangent","vec4"))))(),lM=aM.xyz.toVar("tangentLocal"),uM=xA((({subBuildFn:e,geometry:t,material:n})=>{let i;return i="VERTEX"===e||t.hasAttribute("tangent")?iC.mul(RA(lM,0)).xyz.toVarying("v_tangentView").normalize():sM,!0!==n.flatShading&&(i=vC(i)),i}),"vec3").once(["NORMAL","VERTEX"])().toVar("tangentView"),cM=xA((([e,t],{subBuildFn:n,material:i})=>{let r=e.mul(aM.w).xyz;return"NORMAL"===n&&!0!==i.flatShading&&(r=r.toVarying(t)),r})).once(["NORMAL"]),dM=xA((({subBuildFn:e,geometry:t,material:n})=>{let i;return i="VERTEX"===e||t.hasAttribute("tangent")?cM(CC.cross(uM),"v_bitangentView").normalize():oM,!0!==n.flatShading&&(i=vC(i)),i}),"vec3").once(["NORMAL","VERTEX"])().toVar("bitangentView"),hM=XA(uM,dM,CC).toVar("TBNViewMatrix"),fM=xA((()=>{let e=ux.cross(fC);return e=e.cross(ux).normalize(),e=ub(e,CC,ax.mul(qA.oneMinus()).oneMinus().pow2().pow2()).normalize(),e})).once()();class pM extends Cv{static get type(){return"NormalMapNode"}constructor(e,t=null){super("vec3"),this.node=e,this.scaleNode=t,this.normalMapType=0}setup({material:e}){const{normalMapType:t,scaleNode:n}=this;let i=this.node.mul(2).sub(1);if(null!==n){let t=n;!0===e.flatShading&&(t=vC(t)),i=LA(i.xy.mul(t),i.z)}let r=null;return 1===t?r=SC(i):0===t?r=hM.mul(i).normalize():(console.error(`THREE.NodeMaterial: Unsupported normal map type: ${t}`),r=CC),r}}const gM=pA(pM).setParameterLength(1,2),mM=xA((({textureNode:e,bumpScale:t})=>{const n=t=>e.cache().context({getUV:e=>t(e.uvNode||yw()),forceUVContext:!0}),i=EA(n((e=>e)));return NA(EA(n((e=>e.add(e.dFdx())))).sub(i),EA(n((e=>e.add(e.dFdy())))).sub(i)).mul(t)})),vM=xA((e=>{const{surf_pos:t,surf_norm:n,dHdxy:i}=e,r=t.dFdx().normalize(),s=n,o=t.dFdy().normalize().cross(s),a=s.cross(r),l=r.dot(o).mul(mC),u=l.sign().mul(i.x.mul(o).add(i.y.mul(a)));return l.abs().mul(n).sub(u).normalize()}));class AM extends Cv{static get type(){return"BumpMapNode"}constructor(e,t=null){super("vec3"),this.textureNode=e,this.scaleNode=t}setup(){const e=null!==this.scaleNode?this.scaleNode:1,t=mM({textureNode:this.textureNode,bumpScale:e});return vM({surf_pos:hC,surf_norm:CC,dHdxy:t})}}const xM=pA(AM).setParameterLength(1,2),yM=new Map;class bM extends yv{static get type(){return"MaterialNode"}constructor(e){super(),this.scope=e}getCache(e,t){let n=yM.get(e);return void 0===n&&(n=QC(e,t),yM.set(e,n)),n}getFloat(e){return this.getCache(e,"float")}getColor(e){return this.getCache(e,"color")}getTexture(e){return this.getCache("map"===e?"map":e+"Map","texture")}setup(e){const t=e.context.material,n=this.scope;let i=null;if(n===bM.COLOR){const e=void 0!==t.color?this.getColor(n):LA();i=t.map&&!0===t.map.isTexture?e.mul(this.getTexture("map")):e}else if(n===bM.OPACITY){const e=this.getFloat(n);i=t.alphaMap&&!0===t.alphaMap.isTexture?e.mul(this.getTexture("alpha")):e}else if(n===bM.SPECULAR_STRENGTH)i=t.specularMap&&!0===t.specularMap.isTexture?this.getTexture("specular").r:EA(1);else if(n===bM.SPECULAR_INTENSITY){const e=this.getFloat(n);i=t.specularIntensityMap&&!0===t.specularIntensityMap.isTexture?e.mul(this.getTexture(n).a):e}else if(n===bM.SPECULAR_COLOR){const e=this.getColor(n);i=t.specularColorMap&&!0===t.specularColorMap.isTexture?e.mul(this.getTexture(n).rgb):e}else if(n===bM.ROUGHNESS){const e=this.getFloat(n);i=t.roughnessMap&&!0===t.roughnessMap.isTexture?e.mul(this.getTexture(n).g):e}else if(n===bM.METALNESS){const e=this.getFloat(n);i=t.metalnessMap&&!0===t.metalnessMap.isTexture?e.mul(this.getTexture(n).b):e}else if(n===bM.EMISSIVE){const e=this.getFloat("emissiveIntensity"),r=this.getColor(n).mul(e);i=t.emissiveMap&&!0===t.emissiveMap.isTexture?r.mul(this.getTexture(n)):r}else if(n===bM.NORMAL)t.normalMap?(i=gM(this.getTexture("normal"),this.getCache("normalScale","vec2")),i.normalMapType=t.normalMapType):i=t.bumpMap?xM(this.getTexture("bump").r,this.getFloat("bumpScale")):CC;else if(n===bM.CLEARCOAT){const e=this.getFloat(n);i=t.clearcoatMap&&!0===t.clearcoatMap.isTexture?e.mul(this.getTexture(n).r):e}else if(n===bM.CLEARCOAT_ROUGHNESS){const e=this.getFloat(n);i=t.clearcoatRoughnessMap&&!0===t.clearcoatRoughnessMap.isTexture?e.mul(this.getTexture(n).r):e}else if(n===bM.CLEARCOAT_NORMAL)i=t.clearcoatNormalMap?gM(this.getTexture(n),this.getCache(n+"Scale","vec2")):CC;else if(n===bM.SHEEN){const e=this.getColor("sheenColor").mul(this.getFloat("sheen"));i=t.sheenColorMap&&!0===t.sheenColorMap.isTexture?e.mul(this.getTexture("sheenColor").rgb):e}else if(n===bM.SHEEN_ROUGHNESS){const e=this.getFloat(n);i=t.sheenRoughnessMap&&!0===t.sheenRoughnessMap.isTexture?e.mul(this.getTexture(n).a):e,i=i.clamp(.07,1)}else if(n===bM.ANISOTROPY)if(t.anisotropyMap&&!0===t.anisotropyMap.isTexture){const e=this.getTexture(n);i=UA(rE.x,rE.y,rE.y.negate(),rE.x).mul(e.rg.mul(2).sub(NA(1)).normalize().mul(e.b))}else i=rE;else if(n===bM.IRIDESCENCE_THICKNESS){const e=GC("1","float",t.iridescenceThicknessRange);if(t.iridescenceThicknessMap){const r=GC("0","float",t.iridescenceThicknessRange);i=e.sub(r).mul(this.getTexture(n).g).add(r)}else i=e}else if(n===bM.TRANSMISSION){const e=this.getFloat(n);i=t.transmissionMap?e.mul(this.getTexture(n).r):e}else if(n===bM.THICKNESS){const e=this.getFloat(n);i=t.thicknessMap?e.mul(this.getTexture(n).g):e}else if(n===bM.IOR)i=this.getFloat(n);else if(n===bM.LIGHT_MAP)i=this.getTexture(n).rgb.mul(this.getFloat("lightMapIntensity"));else if(n===bM.AO)i=this.getTexture(n).r.sub(1).mul(this.getFloat("aoMapIntensity")).add(1);else if(n===bM.LINE_DASH_OFFSET)i=t.dashOffset?this.getFloat(n):EA(0);else{const t=this.getNodeType(e);i=this.getCache(n,t)}return i}}bM.ALPHA_TEST="alphaTest",bM.COLOR="color",bM.OPACITY="opacity",bM.SHININESS="shininess",bM.SPECULAR="specular",bM.SPECULAR_STRENGTH="specularStrength",bM.SPECULAR_INTENSITY="specularIntensity",bM.SPECULAR_COLOR="specularColor",bM.REFLECTIVITY="reflectivity",bM.ROUGHNESS="roughness",bM.METALNESS="metalness",bM.NORMAL="normal",bM.CLEARCOAT="clearcoat",bM.CLEARCOAT_ROUGHNESS="clearcoatRoughness",bM.CLEARCOAT_NORMAL="clearcoatNormal",bM.EMISSIVE="emissive",bM.ROTATION="rotation",bM.SHEEN="sheen",bM.SHEEN_ROUGHNESS="sheenRoughness",bM.ANISOTROPY="anisotropy",bM.IRIDESCENCE="iridescence",bM.IRIDESCENCE_IOR="iridescenceIOR",bM.IRIDESCENCE_THICKNESS="iridescenceThickness",bM.IOR="ior",bM.TRANSMISSION="transmission",bM.THICKNESS="thickness",bM.ATTENUATION_DISTANCE="attenuationDistance",bM.ATTENUATION_COLOR="attenuationColor",bM.LINE_SCALE="scale",bM.LINE_DASH_SIZE="dashSize",bM.LINE_GAP_SIZE="gapSize",bM.LINE_WIDTH="linewidth",bM.LINE_DASH_OFFSET="dashOffset",bM.POINT_SIZE="size",bM.DISPERSION="dispersion",bM.LIGHT_MAP="light",bM.AO="ao";const wM=gA(bM,bM.ALPHA_TEST),CM=gA(bM,bM.COLOR),MM=gA(bM,bM.SHININESS),EM=gA(bM,bM.EMISSIVE),TM=gA(bM,bM.OPACITY),SM=gA(bM,bM.SPECULAR),PM=gA(bM,bM.SPECULAR_INTENSITY),NM=gA(bM,bM.SPECULAR_COLOR),BM=gA(bM,bM.SPECULAR_STRENGTH),DM=gA(bM,bM.REFLECTIVITY),IM=gA(bM,bM.ROUGHNESS),LM=gA(bM,bM.METALNESS),jM=gA(bM,bM.NORMAL),OM=gA(bM,bM.CLEARCOAT),zM=gA(bM,bM.CLEARCOAT_ROUGHNESS),RM=gA(bM,bM.CLEARCOAT_NORMAL),kM=gA(bM,bM.ROTATION),FM=gA(bM,bM.SHEEN),HM=gA(bM,bM.SHEEN_ROUGHNESS),UM=gA(bM,bM.ANISOTROPY),XM=gA(bM,bM.IRIDESCENCE),GM=gA(bM,bM.IRIDESCENCE_IOR),VM=gA(bM,bM.IRIDESCENCE_THICKNESS),WM=gA(bM,bM.TRANSMISSION),QM=gA(bM,bM.THICKNESS),ZM=gA(bM,bM.IOR),YM=gA(bM,bM.ATTENUATION_DISTANCE),JM=gA(bM,bM.ATTENUATION_COLOR),KM=gA(bM,bM.LINE_SCALE),qM=gA(bM,bM.LINE_DASH_SIZE),_M=gA(bM,bM.LINE_GAP_SIZE),$M=(bM.LINE_WIDTH,gA(bM,bM.LINE_DASH_OFFSET)),eE=gA(bM,bM.POINT_SIZE),tE=gA(bM,bM.DISPERSION),nE=gA(bM,bM.LIGHT_MAP),iE=gA(bM,bM.AO),rE=Nx(new Cs).onReference((function(e){return e.material})).onRenderUpdate((function({material:e}){this.value.set(e.anisotropy*Math.cos(e.anisotropyRotation),e.anisotropy*Math.sin(e.anisotropyRotation))})),sE=xA((e=>e.context.setupModelViewProjection()),"vec4").once()().toVarying("v_modelViewProjection");class oE extends yv{static get type(){return"IndexNode"}constructor(e){super("uint"),this.scope=e,this.isIndexNode=!0}generate(e){const t=this.getNodeType(e),n=this.scope;let i,r;if(n===oE.VERTEX)i=e.getVertexIndex();else if(n===oE.INSTANCE)i=e.getInstanceIndex();else if(n===oE.DRAW)i=e.getDrawIndex();else if(n===oE.INVOCATION_LOCAL)i=e.getInvocationLocalIndex();else if(n===oE.INVOCATION_SUBGROUP)i=e.getInvocationSubgroupIndex();else{if(n!==oE.SUBGROUP)throw new Error("THREE.IndexNode: Unknown scope: "+n);i=e.getSubgroupIndex()}if("vertex"===e.shaderStage||"compute"===e.shaderStage)r=i;else{r=Ob(this).build(e,t)}return r}}oE.VERTEX="vertex",oE.INSTANCE="instance",oE.SUBGROUP="subgroup",oE.INVOCATION_LOCAL="invocationLocal",oE.INVOCATION_SUBGROUP="invocationSubgroup",oE.DRAW="draw";const aE=gA(oE,oE.VERTEX),lE=gA(oE,oE.INSTANCE),uE=(oE.SUBGROUP,oE.INVOCATION_SUBGROUP,oE.INVOCATION_LOCAL,gA(oE,oE.DRAW));class cE extends yv{static get type(){return"InstanceNode"}constructor(e,t,n=null){super("void"),this.count=e,this.instanceMatrix=t,this.instanceColor=n,this.instanceMatrixNode=null,this.instanceColorNode=null,this.updateType=hv.FRAME,this.buffer=null,this.bufferColor=null}setup(e){const{instanceMatrix:t,instanceColor:n}=this,{count:i}=t;let{instanceMatrixNode:r,instanceColorNode:s}=this;if(null===r){if(i<=1e3)r=Dw(t.array,"mat4",Math.max(i,1)).element(lE);else{const e=new Pc(t.array,16,1);this.buffer=e;const n=t.usage===ss?ew:$b,i=[n(e,"vec4",16,0),n(e,"vec4",16,4),n(e,"vec4",16,8),n(e,"vec4",16,12)];r=GA(...i)}this.instanceMatrixNode=r}if(n&&null===s){const e=new Pl(n.array,3),t=n.usage===ss?ew:$b;this.bufferColor=e,s=LA(t(e,"vec3",3,0)),this.instanceColorNode=s}const o=r.mul(lC).xyz;if(lC.assign(o),e.hasGeometryAttribute("normal")){const e=TC(xC,r);xC.assign(e)}null!==this.instanceColorNode&&YA("vec3","vInstanceColor").assign(this.instanceColorNode)}update(){this.instanceMatrix.usage!==ss&&null!==this.buffer&&this.instanceMatrix.version!==this.buffer.version&&(this.buffer.version=this.instanceMatrix.version),this.instanceColor&&this.instanceColor.usage!==ss&&null!==this.bufferColor&&this.instanceColor.version!==this.bufferColor.version&&(this.bufferColor.version=this.instanceColor.version)}}class dE extends cE{static get type(){return"InstancedMeshNode"}constructor(e){const{count:t,instanceMatrix:n,instanceColor:i}=e;super(t,n,i),this.instancedMesh=e}}const hE=pA(dE).setParameterLength(1);class fE extends yv{static get type(){return"BatchNode"}constructor(e){super("void"),this.batchMesh=e,this.batchingIdNode=null}setup(e){null===this.batchingIdNode&&(null===e.getDrawIndex()?this.batchingIdNode=lE:this.batchingIdNode=uE);const t=xA((([e])=>{const t=TA(ww(Nw(this.batchMesh._indirectTexture),0).x),n=TA(e).mod(t),i=TA(e).div(t);return Nw(this.batchMesh._indirectTexture,BA(n,i)).x})).setLayout({name:"getIndirectIndex",type:"uint",inputs:[{name:"id",type:"int"}]}),n=t(TA(this.batchingIdNode)),i=this.batchMesh._matricesTexture,r=TA(ww(Nw(i),0).x),s=EA(n).mul(4).toInt().toVar(),o=s.mod(r),a=s.div(r),l=GA(Nw(i,BA(o,a)),Nw(i,BA(o.add(1),a)),Nw(i,BA(o.add(2),a)),Nw(i,BA(o.add(3),a))),u=this.batchMesh._colorsTexture;if(null!==u){const e=xA((([e])=>{const t=TA(ww(Nw(u),0).x),n=e,i=n.mod(t),r=n.div(t);return Nw(u,BA(i,r)).rgb})).setLayout({name:"getBatchingColor",type:"vec3",inputs:[{name:"id",type:"int"}]}),t=e(n);YA("vec3","vBatchColor").assign(t)}const c=XA(l);lC.assign(l.mul(lC));const d=xC.div(LA(c[0].dot(c[0]),c[1].dot(c[1]),c[2].dot(c[2]))),h=c.mul(d).xyz;xC.assign(h),e.hasGeometryAttribute("tangent")&&lM.mulAssign(c)}}const pE=pA(fE).setParameterLength(1);const gE=new WeakMap;class mE extends yv{static get type(){return"SkinningNode"}constructor(e){super("void"),this.skinnedMesh=e,this.updateType=hv.OBJECT,this.skinIndexNode=xw("skinIndex","uvec4"),this.skinWeightNode=xw("skinWeight","vec4"),this.bindMatrixNode=GC("bindMatrix","mat4"),this.bindMatrixInverseNode=GC("bindMatrixInverse","mat4"),this.boneMatricesNode=VC("skeleton.boneMatrices","mat4",e.skeleton.bones.length),this.positionNode=lC,this.toPositionNode=lC,this.previousBoneMatricesNode=null}getSkinnedPosition(e=this.boneMatricesNode,t=this.positionNode){const{skinIndexNode:n,skinWeightNode:i,bindMatrixNode:r,bindMatrixInverseNode:s}=this,o=e.element(n.x),a=e.element(n.y),l=e.element(n.z),u=e.element(n.w),c=r.mul(t),d=kx(o.mul(i.x).mul(c),a.mul(i.y).mul(c),l.mul(i.z).mul(c),u.mul(i.w).mul(c));return s.mul(d).xyz}getSkinnedNormal(e=this.boneMatricesNode,t=xC){const{skinIndexNode:n,skinWeightNode:i,bindMatrixNode:r,bindMatrixInverseNode:s}=this,o=e.element(n.x),a=e.element(n.y),l=e.element(n.z),u=e.element(n.w);let c=kx(i.x.mul(o),i.y.mul(a),i.z.mul(l),i.w.mul(u));return c=s.mul(c).mul(r),c.transformDirection(t).xyz}getPreviousSkinnedPosition(e){const t=e.object;return null===this.previousBoneMatricesNode&&(t.skeleton.previousBoneMatrices=new Float32Array(t.skeleton.boneMatrices),this.previousBoneMatricesNode=VC("skeleton.previousBoneMatrices","mat4",t.skeleton.bones.length)),this.getSkinnedPosition(this.previousBoneMatricesNode,uC)}needsPreviousBoneMatrices(e){const t=e.renderer.getMRT();return t&&t.has("velocity")||!0===lv(e.object).useVelocity}setup(e){this.needsPreviousBoneMatrices(e)&&uC.assign(this.getPreviousSkinnedPosition(e));const t=this.getSkinnedPosition();if(this.toPositionNode&&this.toPositionNode.assign(t),e.hasGeometryAttribute("normal")){const t=this.getSkinnedNormal();xC.assign(t),e.hasGeometryAttribute("tangent")&&lM.assign(t)}return t}generate(e,t){if("void"!==t)return super.generate(e,t)}update(e){const t=e.object&&e.object.skeleton?e.object.skeleton:this.skinnedMesh.skeleton;gE.get(t)!==e.frameId&&(gE.set(t,e.frameId),null!==this.previousBoneMatricesNode&&t.previousBoneMatrices.set(t.boneMatrices),t.update())}}const vE=e=>cA(new mE(e));class AE extends yv{static get type(){return"LoopNode"}constructor(e=[]){super(),this.params=e}getVarName(e){return String.fromCharCode("i".charCodeAt(0)+e)}getProperties(e){const t=e.getNodeProperties(this);if(void 0!==t.stackNode)return t;const n={};for(let e=0,t=this.params.length-1;e<t;e++){const t=this.params[e],i=!0!==t.isNode&&t.name||this.getVarName(e),r=!0!==t.isNode&&t.type||"int";n[i]=hw(i,r)}const i=e.addStack();t.returnsNode=this.params[this.params.length-1](n,e),t.stackNode=i;const r=this.params[0];return!0!==r.isNode&&"function"==typeof r.update&&(t.updateNode=xA(this.params[0].update)(n)),e.removeStack(),t}getNodeType(e){const{returnsNode:t}=this.getProperties(e);return t?t.getNodeType(e):"void"}setup(e){this.getProperties(e)}generate(e){const t=this.getProperties(e),n=this.params,i=t.stackNode;for(let i=0,r=n.length-1;i<r;i++){const r=n[i];let s,o=!1,a=null,l=null,u=null,c=null,d=null,h=null;if(r.isNode?"bool"===r.getNodeType(e)?(o=!0,c="bool",l=r.build(e,c)):(c="int",u=this.getVarName(i),a="0",l=r.build(e,c),d="<"):(c=r.type||"int",u=r.name||this.getVarName(i),a=r.start,l=r.end,d=r.condition,h=r.update,"number"==typeof a?a=e.generateConst(c,a):a&&a.isNode&&(a=a.build(e,c)),"number"==typeof l?l=e.generateConst(c,l):l&&l.isNode&&(l=l.build(e,c)),void 0!==a&&void 0===l?(a+=" - 1",l="0",d=">="):void 0!==l&&void 0===a&&(a="0",d="<"),void 0===d&&(d=Number(a)>Number(l)?">=":"<")),o)s=`while ( ${l} )`;else{const n={start:a,end:l},i=n.start,r=n.end;let o;const f=()=>d.includes("<")?"+=":"-=";if(null!=h)switch(typeof h){case"function":o=e.flowStagesNode(t.updateNode,"void").code.replace(/\t|;/g,"");break;case"number":o=u+" "+f()+" "+e.generateConst(c,h);break;case"string":o=u+" "+h;break;default:h.isNode?o=u+" "+f()+" "+h.build(e):(console.error("THREE.TSL: 'Loop( { update: ... } )' is not a function, string or number."),o="break /* invalid update */")}else h="int"===c||"uint"===c?d.includes("<")?"++":"--":f()+" 1.",o=u+" "+h;s=`for ( ${e.getVar(c,u)+" = "+i}; ${u+" "+d+" "+r}; ${o} )`}e.addFlowCode((0===i?"\n":"")+e.tab+s+" {\n\n").addFlowTab()}const r=i.build(e,"void"),s=t.returnsNode?t.returnsNode.build(e):"";e.removeFlowTab().addFlowCode("\n"+e.tab+r);for(let t=0,n=this.params.length-1;t<n;t++)e.addFlowCode((0===t?"":e.tab)+"}\n\n").removeFlowTab();return e.addFlowTab(),s}}const xE=(...e)=>cA(new AE(fA(e,"int"))).toStack(),yE=()=>hw("break").toStack(),bE=new WeakMap,wE=new Js,CE=xA((({bufferMap:e,influence:t,stride:n,width:i,depth:r,offset:s})=>{const o=TA(aE).mul(n).add(s),a=o.div(i),l=o.sub(a.mul(i));return Nw(e,BA(l,a)).depth(r).xyz.mul(t)}));class ME extends yv{static get type(){return"MorphNode"}constructor(e){super("void"),this.mesh=e,this.morphBaseInfluence=Nx(1),this.updateType=hv.OBJECT}setup(e){const{geometry:t}=e,n=void 0!==t.morphAttributes.position,i=t.hasAttribute("normal")&&void 0!==t.morphAttributes.normal,r=t.morphAttributes.position||t.morphAttributes.normal||t.morphAttributes.color,s=void 0!==r?r.length:0,{texture:o,stride:a,size:l}=function(e){const t=void 0!==e.morphAttributes.position,n=void 0!==e.morphAttributes.normal,i=void 0!==e.morphAttributes.color,r=e.morphAttributes.position||e.morphAttributes.normal||e.morphAttributes.color,s=void 0!==r?r.length:0;let o=bE.get(e);if(void 0===o||o.count!==s){void 0!==o&&o.texture.dispose();const a=e.morphAttributes.position||[],l=e.morphAttributes.normal||[],u=e.morphAttributes.color||[];let c=0;!0===t&&(c=1),!0===n&&(c=2),!0===i&&(c=3);let d=e.attributes.position.count*c,h=1;const f=4096;d>f&&(h=Math.ceil(d/f),d=f);const p=new Float32Array(d*h*4*s),g=new _s(p,d,h,s);g.type=Ji,g.needsUpdate=!0;const m=4*c;for(let A=0;A<s;A++){const x=a[A],y=l[A],b=u[A],w=d*h*4*A;for(let C=0;C<x.count;C++){const M=C*m;!0===t&&(wE.fromBufferAttribute(x,C),p[w+M+0]=wE.x,p[w+M+1]=wE.y,p[w+M+2]=wE.z,p[w+M+3]=0),!0===n&&(wE.fromBufferAttribute(y,C),p[w+M+4]=wE.x,p[w+M+5]=wE.y,p[w+M+6]=wE.z,p[w+M+7]=0),!0===i&&(wE.fromBufferAttribute(b,C),p[w+M+8]=wE.x,p[w+M+9]=wE.y,p[w+M+10]=wE.z,p[w+M+11]=4===b.itemSize?wE.w:1)}}function v(){g.dispose(),bE.delete(e),e.removeEventListener("dispose",v)}o={count:s,texture:g,stride:c,size:new Cs(d,h)},bE.set(e,o),e.addEventListener("dispose",v)}return o}(t);!0===n&&lC.mulAssign(this.morphBaseInfluence),!0===i&&xC.mulAssign(this.morphBaseInfluence);const u=TA(l.width);xE(s,(({i:e})=>{const t=EA(0).toVar();this.mesh.count>1&&null!==this.mesh.morphTexture&&void 0!==this.mesh.morphTexture?t.assign(Nw(this.mesh.morphTexture,BA(TA(e).add(1),TA(lE))).r):t.assign(GC("morphTargetInfluences","float").element(e).toVar()),wA(t.notEqual(0),(()=>{!0===n&&lC.addAssign(CE({bufferMap:o,influence:t,stride:a,width:u,depth:e,offset:TA(0)})),!0===i&&xC.addAssign(CE({bufferMap:o,influence:t,stride:a,width:u,depth:e,offset:TA(1)}))}))}))}update(){const e=this.morphBaseInfluence;this.mesh.geometry.morphTargetsRelative?e.value=1:e.value=1-this.mesh.morphTargetInfluences.reduce(((e,t)=>e+t),0)}}const EE=pA(ME).setParameterLength(1);class TE extends yv{static get type(){return"LightingNode"}constructor(){super("vec3"),this.isLightingNode=!0}}class SE extends TE{static get type(){return"AONode"}constructor(e=null){super(),this.aoNode=e}setup(e){e.context.ambientOcclusion.mulAssign(this.aoNode)}}class PE extends wb{static get type(){return"LightingContextNode"}constructor(e,t=null,n=null,i=null){super(e),this.lightingModel=t,this.backdropNode=n,this.backdropAlphaNode=i,this._value=null}getContext(){const{backdropNode:e,backdropAlphaNode:t}=this,n={directDiffuse:LA().toVar("directDiffuse"),directSpecular:LA().toVar("directSpecular"),indirectDiffuse:LA().toVar("indirectDiffuse"),indirectSpecular:LA().toVar("indirectSpecular")};return{radiance:LA().toVar("radiance"),irradiance:LA().toVar("irradiance"),iblIrradiance:LA().toVar("iblIrradiance"),ambientOcclusion:EA(1).toVar("ambientOcclusion"),reflectedLight:n,backdrop:e,backdropAlpha:t}}setup(e){return this.value=this._value||(this._value=this.getContext()),this.value.lightingModel=this.lightingModel||e.context.lightingModel,super.setup(e)}}const NE=pA(PE);class BE extends TE{static get type(){return"IrradianceNode"}constructor(e){super(),this.node=e}setup(e){e.context.irradiance.addAssign(this.node)}}const DE=new Cs;class IE extends Tw{static get type(){return"ViewportTextureNode"}constructor(e=Hw,t=null,n=null){let i=null;null===n?(i=new ql,i.minFilter=Xi,n=i):i=n,super(n,e,t),this.generateMipmaps=!1,this.defaultFramebuffer=i,this.isOutputTextureNode=!0,this.updateBeforeType=hv.FRAME,this._cacheTextures=new WeakMap}getTextureForReference(e=null){let t,n;if(this.referenceNode?(t=this.referenceNode.defaultFramebuffer,n=this.referenceNode._cacheTextures):(t=this.defaultFramebuffer,n=this._cacheTextures),null===e)return t;if(!1===n.has(e)){const i=t.clone();n.set(e,i)}return n.get(e)}updateReference(e){const t=e.renderer.getRenderTarget();return this.value=this.getTextureForReference(t),this.value}updateBefore(e){const t=e.renderer,n=t.getRenderTarget();null===n?t.getDrawingBufferSize(DE):DE.set(n.width,n.height);const i=this.getTextureForReference(n);i.image.width===DE.width&&i.image.height===DE.height||(i.image.width=DE.width,i.image.height=DE.height,i.needsUpdate=!0);const r=i.generateMipmaps;i.generateMipmaps=this.generateMipmaps,t.copyFramebufferToTexture(i),i.generateMipmaps=r}clone(){const e=new this.constructor(this.uvNode,this.levelNode,this.value);return e.generateMipmaps=this.generateMipmaps,e}}const LE=pA(IE,null,null,{generateMipmaps:!0}).setParameterLength(0,3);let jE=null;class OE extends IE{static get type(){return"ViewportDepthTextureNode"}constructor(e=Hw,t=null){null===jE&&(jE=new _l),super(e,t,jE)}getTextureForReference(){return jE}}const zE=pA(OE).setParameterLength(0,2);class RE extends yv{static get type(){return"ViewportDepthNode"}constructor(e,t=null){super("float"),this.scope=e,this.valueNode=t,this.isViewportDepthNode=!0}generate(e){const{scope:t}=this;return t===RE.DEPTH_BASE?e.getFragDepth():super.generate(e)}setup({camera:e}){const{scope:t}=this,n=this.valueNode;let i=null;if(t===RE.DEPTH_BASE)null!==n&&(i=XE().assign(n));else if(t===RE.DEPTH)i=e.isPerspectiveCamera?FE(hC.z,Qw,Zw):kE(hC.z,Qw,Zw);else if(t===RE.LINEAR_DEPTH)if(null!==n)if(e.isPerspectiveCamera){const e=HE(n,Qw,Zw);i=kE(e,Qw,Zw)}else i=n;else i=kE(hC.z,Qw,Zw);return i}}RE.DEPTH_BASE="depthBase",RE.DEPTH="depth",RE.LINEAR_DEPTH="linearDepth";const kE=(e,t,n)=>e.add(t).div(t.sub(n)),FE=(e,t,n)=>t.add(e).mul(n).div(n.sub(t).mul(e)),HE=(e,t,n)=>t.mul(n).div(n.sub(t).mul(e).sub(n)),UE=(e,t,n)=>{t=t.max(1e-6).toVar();const i=yy(e.negate().div(t)),r=yy(n.div(t));return i.div(r)},XE=pA(RE,RE.DEPTH_BASE),GE=gA(RE,RE.DEPTH),VE=pA(RE,RE.LINEAR_DEPTH).setParameterLength(0,1);zE();GE.assign=e=>XE(e);class WE extends yv{static get type(){return"ClippingNode"}constructor(e=WE.DEFAULT){super(),this.scope=e}setup(e){super.setup(e);const t=e.clippingContext,{intersectionPlanes:n,unionPlanes:i}=t;return this.hardwareClipping=e.material.hardwareClipping,this.scope===WE.ALPHA_TO_COVERAGE?this.setupAlphaToCoverage(n,i):this.scope===WE.HARDWARE?this.setupHardwareClipping(i,e):this.setupDefault(n,i)}setupAlphaToCoverage(e,t){return xA((()=>{const n=EA().toVar("distanceToPlane"),i=EA().toVar("distanceToGradient"),r=EA(1).toVar("clipOpacity"),s=t.length;if(!1===this.hardwareClipping&&s>0){const e=jw(t).setGroup(Tx);xE(s,(({i:t})=>{const s=e.element(t);n.assign(hC.dot(s.xyz).negate().add(s.w)),i.assign(n.fwidth().div(2)),r.mulAssign(fb(i.negate(),i,n))}))}const o=e.length;if(o>0){const t=jw(e).setGroup(Tx),s=EA(1).toVar("intersectionClipOpacity");xE(o,(({i:e})=>{const r=t.element(e);n.assign(hC.dot(r.xyz).negate().add(r.w)),i.assign(n.fwidth().div(2)),s.mulAssign(fb(i.negate(),i,n).oneMinus())})),r.mulAssign(s.oneMinus())}JA.a.mulAssign(r),JA.a.equal(0).discard()}))()}setupDefault(e,t){return xA((()=>{const n=t.length;if(!1===this.hardwareClipping&&n>0){const e=jw(t).setGroup(Tx);xE(n,(({i:t})=>{const n=e.element(t);hC.dot(n.xyz).greaterThan(n.w).discard()}))}const i=e.length;if(i>0){const t=jw(e).setGroup(Tx),n=PA(!0).toVar("clipped");xE(i,(({i:e})=>{const i=t.element(e);n.assign(hC.dot(i.xyz).greaterThan(i.w).and(n))})),n.discard()}}))()}setupHardwareClipping(e,t){const n=e.length;return t.enableHardwareClipping(n),xA((()=>{const i=jw(e).setGroup(Tx),r=Ow(t.getClipDistance());xE(n,(({i:e})=>{const t=i.element(e),n=hC.dot(t.xyz).sub(t.w).negate();r.element(e).assign(n)}))}))()}}WE.ALPHA_TO_COVERAGE="alphaToCoverage",WE.DEFAULT="default",WE.HARDWARE="hardware";const QE=xA((([e])=>Ty(Hx(1e4,Sy(Hx(17,e.x).add(Hx(.1,e.y)))).mul(kx(.1,Ly(Sy(Hx(13,e.y).add(e.x)))))))),ZE=xA((([e])=>QE(NA(QE(e.xy),e.z)))),YE=xA((([e])=>{const t=Jy(Oy(ky(e.xyz)),Oy(Fy(e.xyz))),n=EA(1).div(EA(.05).mul(t)).toVar("pixScale"),i=NA(Ay(Cy(yy(n))),Ay(My(yy(n)))),r=NA(ZE(Cy(i.x.mul(e.xyz))),ZE(Cy(i.y.mul(e.xyz)))),s=Ty(yy(n)),o=kx(Hx(s.oneMinus(),r.x),Hx(s,r.y)),a=Yy(s,s.oneMinus()),l=LA(o.mul(o).div(Hx(2,a).mul(Fx(1,a))),o.sub(Hx(.5,a)).div(Fx(1,a)),Fx(1,Fx(1,o).mul(Fx(1,o)).div(Hx(2,a).mul(Fx(1,a))))),u=o.lessThan(a.oneMinus()).select(o.lessThan(a).select(l.x,l.y),l.z);return cb(u,1e-6,1)})).setLayout({name:"getAlphaHashThreshold",type:"float",inputs:[{name:"position",type:"vec3"}]});class JE extends Aw{static get type(){return"VertexColorNode"}constructor(e){super(null,"vec4"),this.isVertexColorNode=!0,this.index=e}getAttributeName(){const e=this.index;return"color"+(e>0?e:"")}generate(e){const t=this.getAttributeName(e);let n;return n=!0===e.hasGeometryAttribute(t)?super.generate(e):e.generateConst(this.nodeType,new Js(1,1,1,1)),n}serialize(e){super.serialize(e),e.index=this.index}deserialize(e){super.deserialize(e),this.index=e.index}}const KE=(e=0)=>cA(new JE(e)),qE=xA((([e])=>RA(e.rgb.mul(e.a),e.a)),{color:"vec4",return:"vec4"});class _E extends Ca{static get type(){return"NodeMaterial"}get type(){return this.constructor.type}set type(e){}constructor(){super(),this.isNodeMaterial=!0,this.fog=!0,this.lights=!1,this.hardwareClipping=!1,this.lightsNode=null,this.envNode=null,this.aoNode=null,this.colorNode=null,this.normalNode=null,this.opacityNode=null,this.backdropNode=null,this.backdropAlphaNode=null,this.alphaTestNode=null,this.maskNode=null,this.positionNode=null,this.geometryNode=null,this.depthNode=null,this.receivedShadowPositionNode=null,this.castShadowPositionNode=null,this.receivedShadowNode=null,this.castShadowNode=null,this.outputNode=null,this.mrtNode=null,this.fragmentNode=null,this.vertexNode=null,Object.defineProperty(this,"shadowPositionNode",{get:()=>this.receivedShadowPositionNode,set:e=>{console.warn('THREE.NodeMaterial: ".shadowPositionNode" was renamed to ".receivedShadowPositionNode".'),this.receivedShadowPositionNode=e}})}customProgramCacheKey(){return this.type+tv(this)}build(e){this.setup(e)}setupObserver(e){return new Km(e)}setup(e){e.context.setupNormal=()=>Lb(this.setupNormal(e),"NORMAL","vec3"),e.context.setupPositionView=()=>this.setupPositionView(e),e.context.setupModelViewProjection=()=>this.setupModelViewProjection(e);const t=e.renderer,n=t.getRenderTarget();e.addStack();const i=Lb(this.setupVertex(e),"VERTEX"),r=this.vertexNode||i;let s;e.stack.outputNode=r,this.setupHardwareClipping(e),null!==this.geometryNode&&(e.stack.outputNode=e.stack.outputNode.bypass(this.geometryNode)),e.addFlow("vertex",e.removeStack()),e.addStack();const o=this.setupClipping(e);if(!0!==this.depthWrite&&!0!==this.depthTest||(null!==n?!0===n.depthBuffer&&this.setupDepth(e):!0===t.depth&&this.setupDepth(e)),null===this.fragmentNode){this.setupDiffuseColor(e),this.setupVariants(e);const i=this.setupLighting(e);null!==o&&e.stack.add(o);const r=RA(i,JA.a).max(0);s=this.setupOutput(e,r),fx.assign(s);const a=null!==this.outputNode;if(a&&(s=this.outputNode),null!==n){const e=t.getMRT(),n=this.mrtNode;null!==e?(a&&fx.assign(s),s=e,null!==n&&(s=e.merge(n))):null!==n&&(s=n)}}else{let t=this.fragmentNode;!0!==t.isOutputStructNode&&(t=RA(t)),s=this.setupOutput(e,t)}e.stack.outputNode=s,e.addFlow("fragment",e.removeStack()),e.observer=this.setupObserver(e)}setupClipping(e){if(null===e.clippingContext)return null;const{unionPlanes:t,intersectionPlanes:n}=e.clippingContext;let i=null;if(t.length>0||n.length>0){const t=e.renderer.samples;this.alphaToCoverage&&t>1?i=cA(new WE(WE.ALPHA_TO_COVERAGE)):e.stack.add(cA(new WE))}return i}setupHardwareClipping(e){if(this.hardwareClipping=!1,null===e.clippingContext)return;const t=e.clippingContext.unionPlanes.length;t>0&&t<=8&&e.isAvailable("clipDistance")&&(e.stack.add(cA(new WE(WE.HARDWARE))),this.hardwareClipping=!0)}setupDepth(e){const{renderer:t,camera:n}=e;let i=this.depthNode;if(null===i){const e=t.getMRT();e&&e.has("depth")?i=e.get("depth"):!0===t.logarithmicDepthBuffer&&(i=n.isPerspectiveCamera?UE(hC.z,Qw,Zw):kE(hC.z,Qw,Zw))}null!==i&&GE.assign(i).toStack()}setupPositionView(){return iC.mul(lC).xyz}setupModelViewProjection(){return Yw.mul(hC)}setupVertex(e){return e.addStack(),this.setupPosition(e),e.context.vertex=e.removeStack(),sE}setupPosition(e){const{object:t,geometry:n}=e;if((n.morphAttributes.position||n.morphAttributes.normal||n.morphAttributes.color)&&EE(t).toStack(),!0===t.isSkinnedMesh&&vE(t).toStack(),this.displacementMap){const e=QC("displacementMap","texture"),t=QC("displacementScale","float"),n=QC("displacementBias","float");lC.addAssign(xC.normalize().mul(e.x.mul(t).add(n)))}return t.isBatchedMesh&&pE(t).toStack(),t.isInstancedMesh&&t.instanceMatrix&&!0===t.instanceMatrix.isInstancedBufferAttribute&&hE(t).toStack(),null!==this.positionNode&&lC.assign(Lb(this.positionNode,"POSITION","vec3")),lC}setupDiffuseColor({object:e,geometry:t}){null!==this.maskNode&&PA(this.maskNode).not().discard();let n=this.colorNode?RA(this.colorNode):CM;if(!0===this.vertexColors&&t.hasAttribute("color")&&(n=n.mul(KE())),e.instanceColor){n=YA("vec3","vInstanceColor").mul(n)}if(e.isBatchedMesh&&e._colorsTexture){n=YA("vec3","vBatchColor").mul(n)}JA.assign(n);const i=this.opacityNode?EA(this.opacityNode):TM;JA.a.assign(JA.a.mul(i));let r=null;(null!==this.alphaTestNode||this.alphaTest>0)&&(r=null!==this.alphaTestNode?EA(this.alphaTestNode):wM,JA.a.lessThanEqual(r).discard()),!0===this.alphaHash&&JA.a.lessThan(YE(lC)).discard();!1===this.transparent&&1===this.blending&&!1===this.alphaToCoverage?JA.a.assign(1):null===r&&JA.a.lessThanEqual(0).discard()}setupVariants(){}setupOutgoingLight(){return!0===this.lights?LA(0):JA.rgb}setupNormal(){return this.normalNode?LA(this.normalNode):jM}setupEnvironment(){let e=null;return this.envNode?e=this.envNode:this.envMap&&(e=this.envMap.isCubeTexture?QC("envMap","cubeTexture"):QC("envMap","texture")),e}setupLightMap(e){let t=null;return e.material.lightMap&&(t=new BE(nE)),t}setupLights(e){const t=[],n=this.setupEnvironment(e);n&&n.isLightingNode&&t.push(n);const i=this.setupLightMap(e);if(i&&i.isLightingNode&&t.push(i),null!==this.aoNode||e.material.aoMap){const e=null!==this.aoNode?this.aoNode:iE;t.push(new SE(e))}let r=this.lightsNode||e.lightsNode;return t.length>0&&(r=e.renderer.lighting.createNode([...r.getLights(),...t])),r}setupLightingModel(){}setupLighting(e){const{material:t}=e,{backdropNode:n,backdropAlphaNode:i,emissiveNode:r}=this,s=!0===this.lights||null!==this.lightsNode?this.setupLights(e):null;let o=this.setupOutgoingLight(e);if(s&&s.getScope().hasLights){const t=this.setupLightingModel(e)||null;o=NE(s,t,n,i)}else null!==n&&(o=LA(null!==i?ub(o,n,i):n));return(r&&!0===r.isNode||t.emissive&&!0===t.emissive.isColor)&&(KA.assign(LA(r||EM)),o=o.add(KA)),o}setupFog(e,t){const n=e.fogNode;return n&&(fx.assign(t),t=RA(n.toVar())),t}setupPremultipliedAlpha(e,t){return qE(t)}setupOutput(e,t){return!0===this.fog&&(t=this.setupFog(e,t)),!0===this.premultipliedAlpha&&(t=this.setupPremultipliedAlpha(e,t)),t}setDefaultValues(e){for(const t in e){const n=e[t];void 0===this[t]&&(this[t]=n,n&&n.clone&&(this[t]=n.clone()))}const t=Object.getOwnPropertyDescriptors(e.constructor.prototype);for(const e in t)void 0===Object.getOwnPropertyDescriptor(this.constructor.prototype,e)&&void 0!==t[e].get&&Object.defineProperty(this.constructor.prototype,e,t[e])}toJSON(e){const t=void 0===e||"string"==typeof e;t&&(e={textures:{},images:{},nodes:{}});const n=Ca.prototype.toJSON.call(this,e),i=nv(this);n.inputNodes={};for(const{property:t,childNode:r}of i)n.inputNodes[t]=r.toJSON(e).uuid;function r(e){const t=[];for(const n in e){const i=e[n];delete i.metadata,t.push(i)}return t}if(t){const t=r(e.textures),i=r(e.images),s=r(e.nodes);t.length>0&&(n.textures=t),i.length>0&&(n.images=i),s.length>0&&(n.nodes=s)}return n}copy(e){return this.lightsNode=e.lightsNode,this.envNode=e.envNode,this.colorNode=e.colorNode,this.normalNode=e.normalNode,this.opacityNode=e.opacityNode,this.backdropNode=e.backdropNode,this.backdropAlphaNode=e.backdropAlphaNode,this.alphaTestNode=e.alphaTestNode,this.maskNode=e.maskNode,this.positionNode=e.positionNode,this.geometryNode=e.geometryNode,this.depthNode=e.depthNode,this.receivedShadowPositionNode=e.receivedShadowPositionNode,this.castShadowPositionNode=e.castShadowPositionNode,this.receivedShadowNode=e.receivedShadowNode,this.castShadowNode=e.castShadowNode,this.outputNode=e.outputNode,this.mrtNode=e.mrtNode,this.fragmentNode=e.fragmentNode,this.vertexNode=e.vertexNode,super.copy(e)}}const $E=new Hl;class eT extends _E{static get type(){return"LineBasicNodeMaterial"}constructor(e){super(),this.isLineBasicNodeMaterial=!0,this.setDefaultValues($E),this.setValues(e)}}const tT=new Iu;class nT extends _E{static get type(){return"LineDashedNodeMaterial"}constructor(e){super(),this.isLineDashedNodeMaterial=!0,this.setDefaultValues(tT),this.dashOffset=0,this.offsetNode=null,this.dashScaleNode=null,this.dashSizeNode=null,this.gapSizeNode=null,this.setValues(e)}setupVariants(){const e=this.offsetNode?EA(this.offsetNode):$M,t=this.dashScaleNode?EA(this.dashScaleNode):KM,n=this.dashSizeNode?EA(this.dashSizeNode):qM,i=this.gapSizeNode?EA(this.gapSizeNode):_M;px.assign(n),gx.assign(i);const r=Ob(xw("lineDistance").mul(t));(e?r.add(e):r).mod(px.add(gx)).greaterThan(px).discard()}}const iT=e=>cA(e).mul(.5).add(.5),rT=new Su;class sT extends _E{static get type(){return"MeshNormalNodeMaterial"}constructor(e){super(),this.isMeshNormalNodeMaterial=!0,this.setDefaultValues(rT),this.setValues(e)}setupDiffuseColor(){const e=this.opacityNode?EA(this.opacityNode):TM;JA.assign(Xb(RA(iT(CC),e),qr))}}const oT=xA((([e=dC])=>{const t=e.z.atan(e.x).mul(1/(2*Math.PI)).add(.5),n=e.y.clamp(-1,1).asin().mul(1/Math.PI).add(.5);return NA(t,n)}));class aT extends Al{constructor(e=1,t={}){super(e,t),this.isCubeRenderTarget=!0}fromEquirectangularTexture(e,t){const n=t.minFilter,i=t.generateMipmaps;t.generateMipmaps=!0,this.texture.type=t.type,this.texture.colorSpace=t.colorSpace,this.texture.generateMipmaps=t.generateMipmaps,this.texture.minFilter=t.minFilter,this.texture.magFilter=t.magFilter;const r=new rl(5,5,5),s=oT(dC),o=new _E;o.colorNode=Pw(t,s,0),o.side=1,o.blending=0;const a=new nl(r,o),l=new wl;l.add(a),t.minFilter===Xi&&(t.minFilter=Hi);const u=new ml(1,10,this),c=e.getMRT();return e.setMRT(null),u.update(e,l),e.setMRT(c),t.minFilter=n,t.currentGenerateMipmaps=i,a.geometry.dispose(),a.material.dispose(),this}}const lT=new WeakMap;class uT extends Cv{static get type(){return"CubeMapNode"}constructor(e){super("vec3"),this.envNode=e,this._cubeTexture=null,this._cubeTextureNode=HC(null);const t=new vl;t.isRenderTargetTexture=!0,this._defaultTexture=t,this.updateBeforeType=hv.RENDER}updateBefore(e){const{renderer:t,material:n}=e,i=this.envNode;if(i.isTextureNode||i.isMaterialReferenceNode){const e=i.isTextureNode?i.value:n[i.property];if(e&&e.isTexture){const n=e.mapping;if(n===Di||n===Ii){if(lT.has(e)){const t=lT.get(e);dT(t,e.mapping),this._cubeTexture=t}else{const n=e.image;if(function(e){return null!=e&&e.height>0}(n)){const i=new aT(n.height);i.fromEquirectangularTexture(t,e),dT(i.texture,e.mapping),this._cubeTexture=i.texture,lT.set(e,i.texture),e.addEventListener("dispose",cT)}else this._cubeTexture=this._defaultTexture}this._cubeTextureNode.value=this._cubeTexture}else this._cubeTextureNode=this.envNode}}}setup(e){return this.updateBefore(e),this._cubeTextureNode}}function cT(e){const t=e.target;t.removeEventListener("dispose",cT);const n=lT.get(t);void 0!==n&&(lT.delete(t),n.dispose())}function dT(e,t){t===Di?e.mapping=Ni:t===Ii&&(e.mapping=Bi)}const hT=pA(uT).setParameterLength(1);class fT extends TE{static get type(){return"BasicEnvironmentNode"}constructor(e=null){super(),this.envNode=e}setup(e){e.context.environment=hT(this.envNode)}}class pT extends TE{static get type(){return"BasicLightMapNode"}constructor(e=null){super(),this.lightMapNode=e}setup(e){const t=EA(1/Math.PI);e.context.irradianceLightMap=this.lightMapNode.mul(t)}}class gT{start(e){e.lightsNode.setupLights(e,e.lightsNode.getLightNodes(e)),this.indirect(e)}finish(){}direct(){}directRectArea(){}indirect(){}ambientOcclusion(){}}class mT extends gT{constructor(){super()}indirect({context:e}){const t=e.ambientOcclusion,n=e.reflectedLight,i=e.irradianceLightMap;n.indirectDiffuse.assign(RA(0)),i?n.indirectDiffuse.addAssign(i):n.indirectDiffuse.addAssign(RA(1,1,1,0)),n.indirectDiffuse.mulAssign(t),n.indirectDiffuse.mulAssign(JA.rgb)}finish(e){const{material:t,context:n}=e,i=n.outgoingLight,r=e.context.environment;if(r)switch(t.combine){case 0:i.rgb.assign(ub(i.rgb,i.rgb.mul(r.rgb),BM.mul(DM)));break;case 1:i.rgb.assign(ub(i.rgb,r.rgb,BM.mul(DM)));break;case 2:i.rgb.addAssign(r.rgb.mul(BM.mul(DM)));break;default:console.warn("THREE.BasicLightingModel: Unsupported .combine value:",t.combine)}}}const vT=new Ma;class AT extends _E{static get type(){return"MeshBasicNodeMaterial"}constructor(e){super(),this.isMeshBasicNodeMaterial=!0,this.lights=!0,this.setDefaultValues(vT),this.setValues(e)}setupNormal(){return vC(bC)}setupEnvironment(e){const t=super.setupEnvironment(e);return t?new fT(t):null}setupLightMap(e){let t=null;return e.material.lightMap&&(t=new pT(nE)),t}setupOutgoingLight(){return JA.rgb}setupLightingModel(){return new mT}}const xT=xA((({f0:e,f90:t,dotVH:n})=>{const i=n.mul(-5.55473).sub(6.98316).mul(n).exp2();return e.mul(i.oneMinus()).add(t.mul(i))})),yT=xA((e=>e.diffuseColor.mul(1/Math.PI))),bT=xA((({dotNH:e})=>hx.mul(EA(.5)).add(1).mul(EA(1/Math.PI)).mul(e.pow(hx)))),wT=xA((({lightDirection:e})=>{const t=e.add(fC).normalize(),n=CC.dot(t).clamp(),i=fC.dot(t).clamp(),r=xT({f0:cx,f90:1,dotVH:i}),s=EA(.25),o=bT({dotNH:n});return r.mul(s).mul(o)}));class CT extends mT{constructor(e=!0){super(),this.specular=e}direct({lightDirection:e,lightColor:t,reflectedLight:n}){const i=CC.dot(e).clamp().mul(t);n.directDiffuse.addAssign(i.mul(yT({diffuseColor:JA.rgb}))),!0===this.specular&&n.directSpecular.addAssign(i.mul(wT({lightDirection:e})).mul(BM))}indirect(e){const{ambientOcclusion:t,irradiance:n,reflectedLight:i}=e.context;i.indirectDiffuse.addAssign(n.mul(yT({diffuseColor:JA}))),i.indirectDiffuse.mulAssign(t)}}const MT=new Pu;class ET extends _E{static get type(){return"MeshLambertNodeMaterial"}constructor(e){super(),this.isMeshLambertNodeMaterial=!0,this.lights=!0,this.setDefaultValues(MT),this.setValues(e)}setupEnvironment(e){const t=super.setupEnvironment(e);return t?new fT(t):null}setupLightingModel(){return new CT(!1)}}const TT=new Eu;class ST extends _E{static get type(){return"MeshPhongNodeMaterial"}constructor(e){super(),this.isMeshPhongNodeMaterial=!0,this.lights=!0,this.shininessNode=null,this.specularNode=null,this.setDefaultValues(TT),this.setValues(e)}setupEnvironment(e){const t=super.setupEnvironment(e);return t?new fT(t):null}setupLightingModel(){return new CT}setupVariants(){const e=(this.shininessNode?EA(this.shininessNode):MM).max(1e-4);hx.assign(e);const t=this.specularNode||SM;cx.assign(t)}copy(e){return this.shininessNode=e.shininessNode,this.specularNode=e.specularNode,super.copy(e)}}const PT=xA((e=>{if(!1===e.geometry.hasAttribute("normal"))return EA(0);const t=bC.dFdx().abs().max(bC.dFdy().abs());return t.x.max(t.y).max(t.z)})),NT=xA((e=>{const{roughness:t}=e,n=PT();let i=t.max(.0525);return i=i.add(n),i=i.min(1),i})),BT=xA((({alpha:e,dotNL:t,dotNV:n})=>{const i=e.pow2(),r=t.mul(i.add(i.oneMinus().mul(n.pow2())).sqrt()),s=n.mul(i.add(i.oneMinus().mul(t.pow2())).sqrt());return Ux(.5,r.add(s).max(dy))})).setLayout({name:"V_GGX_SmithCorrelated",type:"float",inputs:[{name:"alpha",type:"float"},{name:"dotNL",type:"float"},{name:"dotNV",type:"float"}]}),DT=xA((({alphaT:e,alphaB:t,dotTV:n,dotBV:i,dotTL:r,dotBL:s,dotNV:o,dotNL:a})=>{const l=a.mul(LA(e.mul(n),t.mul(i),o).length()),u=o.mul(LA(e.mul(r),t.mul(s),a).length());return Ux(.5,l.add(u)).saturate()})).setLayout({name:"V_GGX_SmithCorrelated_Anisotropic",type:"float",inputs:[{name:"alphaT",type:"float",qualifier:"in"},{name:"alphaB",type:"float",qualifier:"in"},{name:"dotTV",type:"float",qualifier:"in"},{name:"dotBV",type:"float",qualifier:"in"},{name:"dotTL",type:"float",qualifier:"in"},{name:"dotBL",type:"float",qualifier:"in"},{name:"dotNV",type:"float",qualifier:"in"},{name:"dotNL",type:"float",qualifier:"in"}]}),IT=xA((({alpha:e,dotNH:t})=>{const n=e.pow2(),i=t.pow2().mul(n.oneMinus()).oneMinus();return n.div(i.pow2()).mul(1/Math.PI)})).setLayout({name:"D_GGX",type:"float",inputs:[{name:"alpha",type:"float"},{name:"dotNH",type:"float"}]}),LT=EA(1/Math.PI),jT=xA((({alphaT:e,alphaB:t,dotNH:n,dotTH:i,dotBH:r})=>{const s=e.mul(t),o=LA(t.mul(i),e.mul(r),s.mul(n)),a=o.dot(o),l=s.div(a);return LT.mul(s.mul(l.pow2()))})).setLayout({name:"D_GGX_Anisotropic",type:"float",inputs:[{name:"alphaT",type:"float",qualifier:"in"},{name:"alphaB",type:"float",qualifier:"in"},{name:"dotNH",type:"float",qualifier:"in"},{name:"dotTH",type:"float",qualifier:"in"},{name:"dotBH",type:"float",qualifier:"in"}]}),OT=xA((({lightDirection:e,f0:t,f90:n,roughness:i,f:r,normalView:s=CC,USE_IRIDESCENCE:o,USE_ANISOTROPY:a})=>{const l=i.pow2(),u=e.add(fC).normalize(),c=s.dot(e).clamp(),d=s.dot(fC).clamp(),h=s.dot(u).clamp(),f=fC.dot(u).clamp();let p,g,m=xT({f0:t,f90:n,dotVH:f});if(aA(o)&&(m=ix.mix(m,r)),aA(a)){const t=lx.dot(e),n=lx.dot(fC),i=lx.dot(u),r=ux.dot(e),s=ux.dot(fC),o=ux.dot(u);p=DT({alphaT:ox,alphaB:l,dotTV:n,dotBV:s,dotTL:t,dotBL:r,dotNV:d,dotNL:c}),g=jT({alphaT:ox,alphaB:l,dotNH:h,dotTH:i,dotBH:o})}else p=BT({alpha:l,dotNL:c,dotNV:d}),g=IT({alpha:l,dotNH:h});return m.mul(p).mul(g)})),zT=xA((({roughness:e,dotNV:t})=>{const n=RA(-1,-.0275,-.572,.022),i=RA(1,.0425,1.04,-.04),r=e.mul(n).add(i),s=r.x.mul(r.x).min(t.mul(-9.28).exp2()).mul(r.x).add(r.y);return NA(-1.04,1.04).mul(s).add(r.zw)})).setLayout({name:"DFGApprox",type:"vec2",inputs:[{name:"roughness",type:"float"},{name:"dotNV",type:"vec3"}]}),RT=xA((e=>{const{dotNV:t,specularColor:n,specularF90:i,roughness:r}=e,s=zT({dotNV:t,roughness:r});return n.mul(s.x).add(i.mul(s.y))})),kT=xA((({f:e,f90:t,dotVH:n})=>{const i=n.oneMinus().saturate(),r=i.mul(i),s=i.mul(r,r).clamp(0,.9999);return e.sub(LA(t).mul(s)).div(s.oneMinus())})).setLayout({name:"Schlick_to_F0",type:"vec3",inputs:[{name:"f",type:"vec3"},{name:"f90",type:"float"},{name:"dotVH",type:"float"}]}),FT=xA((({roughness:e,dotNH:t})=>{const n=e.pow2(),i=EA(1).div(n),r=t.pow2().oneMinus().max(.0078125);return EA(2).add(i).mul(r.pow(i.mul(.5))).div(2*Math.PI)})).setLayout({name:"D_Charlie",type:"float",inputs:[{name:"roughness",type:"float"},{name:"dotNH",type:"float"}]}),HT=xA((({dotNV:e,dotNL:t})=>EA(1).div(EA(4).mul(t.add(e).sub(t.mul(e)))))).setLayout({name:"V_Neubelt",type:"float",inputs:[{name:"dotNV",type:"float"},{name:"dotNL",type:"float"}]}),UT=xA((({lightDirection:e})=>{const t=e.add(fC).normalize(),n=CC.dot(e).clamp(),i=CC.dot(fC).clamp(),r=CC.dot(t).clamp(),s=FT({roughness:nx,dotNH:r}),o=HT({dotNV:i,dotNL:n});return tx.mul(s).mul(o)})),XT=xA((({N:e,V:t,roughness:n})=>{const i=e.dot(t).saturate(),r=NA(n,i.oneMinus().sqrt());return r.assign(r.mul(.984375).add(.0078125)),r})).setLayout({name:"LTC_Uv",type:"vec2",inputs:[{name:"N",type:"vec3"},{name:"V",type:"vec3"},{name:"roughness",type:"float"}]}),GT=xA((({f:e})=>{const t=e.length();return Jy(t.mul(t).add(e.z).div(t.add(1)),0)})).setLayout({name:"LTC_ClippedSphereFormFactor",type:"float",inputs:[{name:"f",type:"vec3"}]}),VT=xA((({v1:e,v2:t})=>{const n=e.dot(t),i=n.abs().toVar(),r=i.mul(.0145206).add(.4965155).mul(i).add(.8543985).toVar(),s=i.add(4.1616724).mul(i).add(3.417594).toVar(),o=r.div(s),a=n.greaterThan(0).select(o,Jy(n.mul(n).oneMinus(),1e-7).inverseSqrt().mul(.5).sub(o));return e.cross(t).mul(a)})).setLayout({name:"LTC_EdgeVectorFormFactor",type:"vec3",inputs:[{name:"v1",type:"vec3"},{name:"v2",type:"vec3"}]}),WT=xA((({N:e,V:t,P:n,mInv:i,p0:r,p1:s,p2:o,p3:a})=>{const l=s.sub(r).toVar(),u=a.sub(r).toVar(),c=l.cross(u),d=LA().toVar();return wA(c.dot(n.sub(r)).greaterThanEqual(0),(()=>{const l=t.sub(e.mul(t.dot(e))).normalize(),u=e.cross(l).negate(),c=i.mul(XA(l,u,e).transpose()).toVar(),h=c.mul(r.sub(n)).normalize().toVar(),f=c.mul(s.sub(n)).normalize().toVar(),p=c.mul(o.sub(n)).normalize().toVar(),g=c.mul(a.sub(n)).normalize().toVar(),m=LA(0).toVar();m.addAssign(VT({v1:h,v2:f})),m.addAssign(VT({v1:f,v2:p})),m.addAssign(VT({v1:p,v2:g})),m.addAssign(VT({v1:g,v2:h})),d.assign(LA(GT({f:m})))})),d})).setLayout({name:"LTC_Evaluate",type:"vec3",inputs:[{name:"N",type:"vec3"},{name:"V",type:"vec3"},{name:"P",type:"vec3"},{name:"mInv",type:"mat3"},{name:"p0",type:"vec3"},{name:"p1",type:"vec3"},{name:"p2",type:"vec3"},{name:"p3",type:"vec3"}]}),QT=1/6,ZT=e=>Hx(QT,Hx(e,Hx(e,e.negate().add(3)).sub(3)).add(1)),YT=e=>Hx(QT,Hx(e,Hx(e,Hx(3,e).sub(6))).add(4)),JT=e=>Hx(QT,Hx(e,Hx(e,Hx(-3,e).add(3)).add(3)).add(1)),KT=e=>Hx(QT,nb(e,3)),qT=e=>ZT(e).add(YT(e)),_T=e=>JT(e).add(KT(e)),$T=e=>kx(-1,YT(e).div(ZT(e).add(YT(e)))),eS=e=>kx(1,KT(e).div(JT(e).add(KT(e)))),tS=(e,t,n)=>{const i=e.uvNode,r=Hx(i,t.zw).add(.5),s=Cy(r),o=Ty(r),a=qT(o.x),l=_T(o.x),u=$T(o.x),c=eS(o.x),d=$T(o.y),h=eS(o.y),f=NA(s.x.add(u),s.y.add(d)).sub(.5).mul(t.xy),p=NA(s.x.add(c),s.y.add(d)).sub(.5).mul(t.xy),g=NA(s.x.add(u),s.y.add(h)).sub(.5).mul(t.xy),m=NA(s.x.add(c),s.y.add(h)).sub(.5).mul(t.xy),v=qT(o.y).mul(kx(a.mul(e.sample(f).level(n)),l.mul(e.sample(p).level(n)))),A=_T(o.y).mul(kx(a.mul(e.sample(g).level(n)),l.mul(e.sample(m).level(n))));return v.add(A)},nS=xA((([e,t])=>{const n=NA(e.size(TA(t))),i=NA(e.size(TA(t.add(1)))),r=Ux(1,n),s=Ux(1,i),o=tS(e,RA(r,n),Cy(t)),a=tS(e,RA(s,i),My(t));return Ty(t).mix(o,a)})),iS=xA((([e,t,n,i,r])=>{const s=LA(hb(t.negate(),Ey(e),Ux(1,i))),o=LA(Oy(r[0].xyz),Oy(r[1].xyz),Oy(r[2].xyz));return Ey(s).mul(n.mul(o))})).setLayout({name:"getVolumeTransmissionRay",type:"vec3",inputs:[{name:"n",type:"vec3"},{name:"v",type:"vec3"},{name:"thickness",type:"float"},{name:"ior",type:"float"},{name:"modelMatrix",type:"mat4"}]}),rS=xA((([e,t])=>e.mul(cb(t.mul(2).sub(2),0,1)))).setLayout({name:"applyIorToRoughness",type:"float",inputs:[{name:"roughness",type:"float"},{name:"ior",type:"float"}]}),sS=LE(),oS=LE(),aS=xA((([e,t,n],{material:i})=>{const r=(1===i.side?sS:oS).sample(e),s=yy(Uw.x).mul(rS(t,n));return nS(r,s)})),lS=xA((([e,t,n])=>(wA(n.notEqual(0),(()=>{const i=xy(t).negate().div(n);return vy(i.negate().mul(e))})),LA(1)))).setLayout({name:"volumeAttenuation",type:"vec3",inputs:[{name:"transmissionDistance",type:"float"},{name:"attenuationColor",type:"vec3"},{name:"attenuationDistance",type:"float"}]}),uS=xA((([e,t,n,i,r,s,o,a,l,u,c,d,h,f,p])=>{let g,m;if(p){g=RA().toVar(),m=LA().toVar();const r=c.sub(1).mul(p.mul(.025)),s=LA(c.sub(r),c,c.add(r));xE({start:0,end:3},(({i:r})=>{const c=s.element(r),p=iS(e,t,d,c,a),v=o.add(p),A=u.mul(l.mul(RA(v,1))),x=NA(A.xy.div(A.w)).toVar();x.addAssign(1),x.divAssign(2),x.assign(NA(x.x,x.y.oneMinus()));const y=aS(x,n,c);g.element(r).assign(y.element(r)),g.a.addAssign(y.a),m.element(r).assign(i.element(r).mul(lS(Oy(p),h,f).element(r)))})),g.a.divAssign(3)}else{const r=iS(e,t,d,c,a),s=o.add(r),p=u.mul(l.mul(RA(s,1))),v=NA(p.xy.div(p.w)).toVar();v.addAssign(1),v.divAssign(2),v.assign(NA(v.x,v.y.oneMinus())),g=aS(v,n,c),m=i.mul(lS(Oy(r),h,f))}const v=m.rgb.mul(g.rgb),A=e.dot(t).clamp(),x=LA(RT({dotNV:A,specularColor:r,specularF90:s,roughness:n})),y=m.r.add(m.g,m.b).div(3);return RA(x.oneMinus().mul(v),g.a.oneMinus().mul(y).oneMinus())})),cS=XA(3.2404542,-.969266,.0556434,-1.5371385,1.8760108,-.2040259,-.4985314,.041556,1.0572252),dS=(e,t)=>e.sub(t).div(e.add(t)).pow2(),hS=xA((({outsideIOR:e,eta2:t,cosTheta1:n,thinFilmThickness:i,baseF0:r})=>{const s=ub(e,t,fb(0,.03,i)),o=e.div(s).pow2().mul(n.pow2().oneMinus()).oneMinus();wA(o.lessThan(0),(()=>LA(1)));const a=o.sqrt(),l=dS(s,e),u=xT({f0:l,f90:1,dotVH:n}),c=u.oneMinus(),d=s.lessThan(e).select(Math.PI,0),h=EA(Math.PI).sub(d),f=(e=>{const t=e.sqrt();return LA(1).add(t).div(LA(1).sub(t))})(r.clamp(0,.9999)),p=dS(f,s.toVec3()),g=xT({f0:p,f90:1,dotVH:a}),m=LA(f.x.lessThan(s).select(Math.PI,0),f.y.lessThan(s).select(Math.PI,0),f.z.lessThan(s).select(Math.PI,0)),v=s.mul(i,a,2),A=LA(h).add(m),x=u.mul(g).clamp(1e-5,.9999),y=x.sqrt(),b=c.pow2().mul(g).div(LA(1).sub(x)),w=u.add(b).toVar(),C=b.sub(c).toVar();return xE({start:1,end:2,condition:"<=",name:"m"},(({m:e})=>{C.mulAssign(y);const t=((e,t)=>{const n=e.mul(2*Math.PI*1e-9),i=LA(54856e-17,44201e-17,52481e-17),r=LA(1681e3,1795300,2208400),s=LA(43278e5,93046e5,66121e5),o=EA(9747e-17*Math.sqrt(2*Math.PI*45282e5)).mul(n.mul(2239900).add(t.x).cos()).mul(n.pow2().mul(-45282e5).exp());let a=i.mul(s.mul(2*Math.PI).sqrt()).mul(r.mul(n).add(t).cos()).mul(n.pow2().negate().mul(s).exp());return a=LA(a.x.add(o),a.y,a.z).div(1.0685e-7),cS.mul(a)})(EA(e).mul(v),EA(e).mul(A)).mul(2);w.addAssign(C.mul(t))})),w.max(LA(0))})).setLayout({name:"evalIridescence",type:"vec3",inputs:[{name:"outsideIOR",type:"float"},{name:"eta2",type:"float"},{name:"cosTheta1",type:"float"},{name:"thinFilmThickness",type:"float"},{name:"baseF0",type:"vec3"}]}),fS=xA((({normal:e,viewDir:t,roughness:n})=>{const i=e.dot(t).saturate(),r=n.pow2(),s=bb(n.lessThan(.25),EA(-339.2).mul(r).add(EA(161.4).mul(n)).sub(25.9),EA(-8.48).mul(r).add(EA(14.3).mul(n)).sub(9.95)),o=bb(n.lessThan(.25),EA(44).mul(r).sub(EA(23.7).mul(n)).add(3.26),EA(1.97).mul(r).sub(EA(3.27).mul(n)).add(.72));return bb(n.lessThan(.25),0,EA(.1).mul(n).sub(.025)).add(s.mul(i).add(o).exp()).mul(1/Math.PI).saturate()})),pS=LA(.04),gS=EA(1);class mS extends gT{constructor(e=!1,t=!1,n=!1,i=!1,r=!1,s=!1){super(),this.clearcoat=e,this.sheen=t,this.iridescence=n,this.anisotropy=i,this.transmission=r,this.dispersion=s,this.clearcoatRadiance=null,this.clearcoatSpecularDirect=null,this.clearcoatSpecularIndirect=null,this.sheenSpecularDirect=null,this.sheenSpecularIndirect=null,this.iridescenceFresnel=null,this.iridescenceF0=null}start(e){if(!0===this.clearcoat&&(this.clearcoatRadiance=LA().toVar("clearcoatRadiance"),this.clearcoatSpecularDirect=LA().toVar("clearcoatSpecularDirect"),this.clearcoatSpecularIndirect=LA().toVar("clearcoatSpecularIndirect")),!0===this.sheen&&(this.sheenSpecularDirect=LA().toVar("sheenSpecularDirect"),this.sheenSpecularIndirect=LA().toVar("sheenSpecularIndirect")),!0===this.iridescence){const e=CC.dot(fC).clamp();this.iridescenceFresnel=hS({outsideIOR:EA(1),eta2:rx,cosTheta1:e,thinFilmThickness:sx,baseF0:cx}),this.iridescenceF0=kT({f:this.iridescenceFresnel,f90:1,dotVH:e})}if(!0===this.transmission){const t=cC,n=Kw.sub(cC).normalize(),i=MC,r=e.context;r.backdrop=uS(i,n,qA,JA,cx,dx,t,tC,Jw,Yw,mx,Ax,yx,xx,this.dispersion?bx:null),r.backdropAlpha=vx,JA.a.mulAssign(ub(1,r.backdrop.a,vx))}super.start(e)}computeMultiscattering(e,t,n){const i=CC.dot(fC).clamp(),r=zT({roughness:qA,dotNV:i}),s=(this.iridescenceF0?ix.mix(cx,this.iridescenceF0):cx).mul(r.x).add(n.mul(r.y)),o=r.x.add(r.y).oneMinus(),a=cx.add(cx.oneMinus().mul(.047619)),l=s.mul(a).div(o.mul(a).oneMinus());e.addAssign(s),t.addAssign(l.mul(o))}direct({lightDirection:e,lightColor:t,reflectedLight:n}){const i=CC.dot(e).clamp().mul(t);if(!0===this.sheen&&this.sheenSpecularDirect.addAssign(i.mul(UT({lightDirection:e}))),!0===this.clearcoat){const n=EC.dot(e).clamp().mul(t);this.clearcoatSpecularDirect.addAssign(n.mul(OT({lightDirection:e,f0:pS,f90:gS,roughness:ex,normalView:EC})))}n.directDiffuse.addAssign(i.mul(yT({diffuseColor:JA.rgb}))),n.directSpecular.addAssign(i.mul(OT({lightDirection:e,f0:cx,f90:1,roughness:qA,iridescence:this.iridescence,f:this.iridescenceFresnel,USE_IRIDESCENCE:this.iridescence,USE_ANISOTROPY:this.anisotropy})))}directRectArea({lightColor:e,lightPosition:t,halfWidth:n,halfHeight:i,reflectedLight:r,ltc_1:s,ltc_2:o}){const a=t.add(n).sub(i),l=t.sub(n).sub(i),u=t.sub(n).add(i),c=t.add(n).add(i),d=CC,h=fC,f=hC.toVar(),p=XT({N:d,V:h,roughness:qA}),g=s.sample(p).toVar(),m=o.sample(p).toVar(),v=XA(LA(g.x,0,g.y),LA(0,1,0),LA(g.z,0,g.w)).toVar(),A=cx.mul(m.x).add(cx.oneMinus().mul(m.y)).toVar();r.directSpecular.addAssign(e.mul(A).mul(WT({N:d,V:h,P:f,mInv:v,p0:a,p1:l,p2:u,p3:c}))),r.directDiffuse.addAssign(e.mul(JA).mul(WT({N:d,V:h,P:f,mInv:XA(1,0,0,0,1,0,0,0,1),p0:a,p1:l,p2:u,p3:c})))}indirect(e){this.indirectDiffuse(e),this.indirectSpecular(e),this.ambientOcclusion(e)}indirectDiffuse(e){const{irradiance:t,reflectedLight:n}=e.context;n.indirectDiffuse.addAssign(t.mul(yT({diffuseColor:JA})))}indirectSpecular(e){const{radiance:t,iblIrradiance:n,reflectedLight:i}=e.context;if(!0===this.sheen&&this.sheenSpecularIndirect.addAssign(n.mul(tx,fS({normal:CC,viewDir:fC,roughness:nx}))),!0===this.clearcoat){const e=EC.dot(fC).clamp(),t=RT({dotNV:e,specularColor:pS,specularF90:gS,roughness:ex});this.clearcoatSpecularIndirect.addAssign(this.clearcoatRadiance.mul(t))}const r=LA().toVar("singleScattering"),s=LA().toVar("multiScattering"),o=n.mul(1/Math.PI);this.computeMultiscattering(r,s,dx);const a=r.add(s),l=JA.mul(a.r.max(a.g).max(a.b).oneMinus());i.indirectSpecular.addAssign(t.mul(r)),i.indirectSpecular.addAssign(s.mul(o)),i.indirectDiffuse.addAssign(l.mul(o))}ambientOcclusion(e){const{ambientOcclusion:t,reflectedLight:n}=e.context,i=CC.dot(fC).clamp().add(t),r=qA.mul(-16).oneMinus().negate().exp2(),s=t.sub(i.pow(r).oneMinus()).clamp();!0===this.clearcoat&&this.clearcoatSpecularIndirect.mulAssign(t),!0===this.sheen&&this.sheenSpecularIndirect.mulAssign(t),n.indirectDiffuse.mulAssign(t),n.indirectSpecular.mulAssign(s)}finish({context:e}){const{outgoingLight:t}=e;if(!0===this.clearcoat){const e=EC.dot(fC).clamp(),n=xT({dotVH:e,f0:pS,f90:gS}),i=t.mul($A.mul(n).oneMinus()).add(this.clearcoatSpecularDirect.add(this.clearcoatSpecularIndirect).mul($A));t.assign(i)}if(!0===this.sheen){const e=tx.r.max(tx.g).max(tx.b).mul(.157).oneMinus(),n=t.mul(e).add(this.sheenSpecularDirect,this.sheenSpecularIndirect);t.assign(n)}}}const vS=EA(1),AS=EA(-2),xS=EA(.8),yS=EA(-1),bS=EA(.4),wS=EA(2),CS=EA(.305),MS=EA(3),ES=EA(.21),TS=EA(4),SS=EA(4),PS=EA(16),NS=xA((([e])=>{const t=LA(Ly(e)).toVar(),n=EA(-1).toVar();return wA(t.x.greaterThan(t.z),(()=>{wA(t.x.greaterThan(t.y),(()=>{n.assign(bb(e.x.greaterThan(0),0,3))})).Else((()=>{n.assign(bb(e.y.greaterThan(0),1,4))}))})).Else((()=>{wA(t.z.greaterThan(t.y),(()=>{n.assign(bb(e.z.greaterThan(0),2,5))})).Else((()=>{n.assign(bb(e.y.greaterThan(0),1,4))}))})),n})).setLayout({name:"getFace",type:"float",inputs:[{name:"direction",type:"vec3"}]}),BS=xA((([e,t])=>{const n=NA().toVar();return wA(t.equal(0),(()=>{n.assign(NA(e.z,e.y).div(Ly(e.x)))})).ElseIf(t.equal(1),(()=>{n.assign(NA(e.x.negate(),e.z.negate()).div(Ly(e.y)))})).ElseIf(t.equal(2),(()=>{n.assign(NA(e.x.negate(),e.y).div(Ly(e.z)))})).ElseIf(t.equal(3),(()=>{n.assign(NA(e.z.negate(),e.y).div(Ly(e.x)))})).ElseIf(t.equal(4),(()=>{n.assign(NA(e.x.negate(),e.z).div(Ly(e.y)))})).Else((()=>{n.assign(NA(e.x,e.y).div(Ly(e.z)))})),Hx(.5,n.add(1))})).setLayout({name:"getUV",type:"vec2",inputs:[{name:"direction",type:"vec3"},{name:"face",type:"float"}]}),DS=xA((([e])=>{const t=EA(0).toVar();return wA(e.greaterThanEqual(xS),(()=>{t.assign(vS.sub(e).mul(yS.sub(AS)).div(vS.sub(xS)).add(AS))})).ElseIf(e.greaterThanEqual(bS),(()=>{t.assign(xS.sub(e).mul(wS.sub(yS)).div(xS.sub(bS)).add(yS))})).ElseIf(e.greaterThanEqual(CS),(()=>{t.assign(bS.sub(e).mul(MS.sub(wS)).div(bS.sub(CS)).add(wS))})).ElseIf(e.greaterThanEqual(ES),(()=>{t.assign(CS.sub(e).mul(TS.sub(MS)).div(CS.sub(ES)).add(MS))})).Else((()=>{t.assign(EA(-2).mul(yy(Hx(1.16,e))))})),t})).setLayout({name:"roughnessToMip",type:"float",inputs:[{name:"roughness",type:"float"}]}),IS=xA((([e,t])=>{const n=e.toVar();n.assign(Hx(2,n).sub(1));const i=LA(n,1).toVar();return wA(t.equal(0),(()=>{i.assign(i.zyx)})).ElseIf(t.equal(1),(()=>{i.assign(i.xzy),i.xz.mulAssign(-1)})).ElseIf(t.equal(2),(()=>{i.x.mulAssign(-1)})).ElseIf(t.equal(3),(()=>{i.assign(i.zyx),i.xz.mulAssign(-1)})).ElseIf(t.equal(4),(()=>{i.assign(i.xzy),i.xy.mulAssign(-1)})).ElseIf(t.equal(5),(()=>{i.z.mulAssign(-1)})),i})).setLayout({name:"getDirection",type:"vec3",inputs:[{name:"uv",type:"vec2"},{name:"face",type:"float"}]}),LS=xA((([e,t,n,i,r,s])=>{const o=EA(n),a=LA(t),l=cb(DS(o),AS,s),u=Ty(l),c=Cy(l),d=LA(jS(e,a,c,i,r,s)).toVar();return wA(u.notEqual(0),(()=>{const t=LA(jS(e,a,c.add(1),i,r,s)).toVar();d.assign(ub(d,t,u))})),d})),jS=xA((([e,t,n,i,r,s])=>{const o=EA(n).toVar(),a=LA(t),l=EA(NS(a)).toVar(),u=EA(Jy(SS.sub(o),0)).toVar();o.assign(Jy(o,SS));const c=EA(Ay(o)).toVar(),d=NA(BS(a,l).mul(c.sub(2)).add(1)).toVar();return wA(l.greaterThan(2),(()=>{d.y.addAssign(c),l.subAssign(3)})),d.x.addAssign(l.mul(c)),d.x.addAssign(u.mul(Hx(3,PS))),d.y.addAssign(Hx(4,Ay(s).sub(c))),d.x.mulAssign(i),d.y.mulAssign(r),e.sample(d).grad(NA(),NA())})),OS=xA((({envMap:e,mipInt:t,outputDirection:n,theta:i,axis:r,CUBEUV_TEXEL_WIDTH:s,CUBEUV_TEXEL_HEIGHT:o,CUBEUV_MAX_MIP:a})=>{const l=Py(i),u=n.mul(l).add(r.cross(n).mul(Sy(i))).add(r.mul(r.dot(n).mul(l.oneMinus())));return jS(e,u,t,s,o,a)})),zS=xA((({n:e,latitudinal:t,poleAxis:n,outputDirection:i,weights:r,samples:s,dTheta:o,mipInt:a,envMap:l,CUBEUV_TEXEL_WIDTH:u,CUBEUV_TEXEL_HEIGHT:c,CUBEUV_MAX_MIP:d})=>{const h=LA(bb(t,n,tb(n,i))).toVar();wA(h.equal(LA(0)),(()=>{h.assign(LA(i.z,0,i.x.negate()))})),h.assign(Ey(h));const f=LA().toVar();return f.addAssign(r.element(0).mul(OS({theta:0,axis:h,outputDirection:i,mipInt:a,envMap:l,CUBEUV_TEXEL_WIDTH:u,CUBEUV_TEXEL_HEIGHT:c,CUBEUV_MAX_MIP:d}))),xE({start:TA(1),end:e},(({i:e})=>{wA(e.greaterThanEqual(s),(()=>{yE()}));const t=EA(o.mul(EA(e))).toVar();f.addAssign(r.element(e).mul(OS({theta:t.mul(-1),axis:h,outputDirection:i,mipInt:a,envMap:l,CUBEUV_TEXEL_WIDTH:u,CUBEUV_TEXEL_HEIGHT:c,CUBEUV_MAX_MIP:d}))),f.addAssign(r.element(e).mul(OS({theta:t,axis:h,outputDirection:i,mipInt:a,envMap:l,CUBEUV_TEXEL_WIDTH:u,CUBEUV_TEXEL_HEIGHT:c,CUBEUV_MAX_MIP:d})))})),RA(f,1)})),RS=[.125,.215,.35,.446,.526,.582],kS=20,FS=new hc(-1,1,1,-1,0,1),HS=new pl(90,1),US=new ya;let XS=null,GS=0,VS=0;const WS=(1+Math.sqrt(5))/2,QS=1/WS,ZS=[new Es(-WS,QS,0),new Es(WS,QS,0),new Es(-QS,0,WS),new Es(QS,0,WS),new Es(0,WS,-QS),new Es(0,WS,QS),new Es(-1,1,-1),new Es(1,1,-1),new Es(-1,1,1),new Es(1,1,1)],YS=new Es,JS=new WeakMap,KS=[3,1,5,0,4,2],qS=IS(yw(),xw("faceIndex")).normalize(),_S=LA(qS.x,qS.y,qS.z);class $S{constructor(e){this._renderer=e,this._pingPongRenderTarget=null,this._lodMax=0,this._cubeSize=0,this._lodPlanes=[],this._sizeLods=[],this._sigmas=[],this._lodMeshes=[],this._blurMaterial=null,this._cubemapMaterial=null,this._equirectMaterial=null,this._backgroundBox=null}get _hasInitialized(){return this._renderer.hasInitialized()}fromScene(e,t=0,n=.1,i=100,r={}){const{size:s=256,position:o=YS,renderTarget:a=null}=r;if(this._setSize(s),!1===this._hasInitialized){console.warn("THREE.PMREMGenerator: .fromScene() called before the backend is initialized. Try using .fromSceneAsync() instead.");const s=a||this._allocateTarget();return r.renderTarget=s,this.fromSceneAsync(e,t,n,i,r),s}XS=this._renderer.getRenderTarget(),GS=this._renderer.getActiveCubeFace(),VS=this._renderer.getActiveMipmapLevel();const l=a||this._allocateTarget();return l.depthBuffer=!0,this._init(l),this._sceneToCubeUV(e,n,i,l,o),t>0&&this._blur(l,0,0,t),this._applyPMREM(l),this._cleanup(l),l}async fromSceneAsync(e,t=0,n=.1,i=100,r={}){return!1===this._hasInitialized&&await this._renderer.init(),this.fromScene(e,t,n,i,r)}fromEquirectangular(e,t=null){if(!1===this._hasInitialized){console.warn("THREE.PMREMGenerator: .fromEquirectangular() called before the backend is initialized. Try using .fromEquirectangularAsync() instead."),this._setSizeFromTexture(e);const n=t||this._allocateTarget();return this.fromEquirectangularAsync(e,n),n}return this._fromTexture(e,t)}async fromEquirectangularAsync(e,t=null){return!1===this._hasInitialized&&await this._renderer.init(),this._fromTexture(e,t)}fromCubemap(e,t=null){if(!1===this._hasInitialized){console.warn("THREE.PMREMGenerator: .fromCubemap() called before the backend is initialized. Try using .fromCubemapAsync() instead."),this._setSizeFromTexture(e);const n=t||this._allocateTarget();return this.fromCubemapAsync(e,t),n}return this._fromTexture(e,t)}async fromCubemapAsync(e,t=null){return!1===this._hasInitialized&&await this._renderer.init(),this._fromTexture(e,t)}async compileCubemapShader(){null===this._cubemapMaterial&&(this._cubemapMaterial=iP(),await this._compileMaterial(this._cubemapMaterial))}async compileEquirectangularShader(){null===this._equirectMaterial&&(this._equirectMaterial=rP(),await this._compileMaterial(this._equirectMaterial))}dispose(){this._dispose(),null!==this._cubemapMaterial&&this._cubemapMaterial.dispose(),null!==this._equirectMaterial&&this._equirectMaterial.dispose(),null!==this._backgroundBox&&(this._backgroundBox.geometry.dispose(),this._backgroundBox.material.dispose())}_setSizeFromTexture(e){e.mapping===Ni||e.mapping===Bi?this._setSize(0===e.image.length?16:e.image[0].width||e.image[0].image.width):this._setSize(e.image.width/4)}_setSize(e){this._lodMax=Math.floor(Math.log2(e)),this._cubeSize=Math.pow(2,this._lodMax)}_dispose(){null!==this._blurMaterial&&this._blurMaterial.dispose(),null!==this._pingPongRenderTarget&&this._pingPongRenderTarget.dispose();for(let e=0;e<this._lodPlanes.length;e++)this._lodPlanes[e].dispose()}_cleanup(e){this._renderer.setRenderTarget(XS,GS,VS),e.scissorTest=!1,tP(e,0,0,e.width,e.height)}_fromTexture(e,t){this._setSizeFromTexture(e),XS=this._renderer.getRenderTarget(),GS=this._renderer.getActiveCubeFace(),VS=this._renderer.getActiveMipmapLevel();const n=t||this._allocateTarget();return this._init(n),this._textureToCubeUV(e,n),this._applyPMREM(n),this._cleanup(n),n}_allocateTarget(){return eP(3*Math.max(this._cubeSize,112),4*this._cubeSize)}_init(e){if(null===this._pingPongRenderTarget||this._pingPongRenderTarget.width!==e.width||this._pingPongRenderTarget.height!==e.height){null!==this._pingPongRenderTarget&&this._dispose(),this._pingPongRenderTarget=eP(e.width,e.height);const{_lodMax:t}=this;({sizeLods:this._sizeLods,lodPlanes:this._lodPlanes,sigmas:this._sigmas,lodMeshes:this._lodMeshes}=function(e){const t=[],n=[],i=[],r=[];let s=e;const o=e-4+1+RS.length;for(let a=0;a<o;a++){const o=Math.pow(2,s);n.push(o);let l=1/o;a>e-4?l=RS[a-e+4-1]:0===a&&(l=0),i.push(l);const u=1/(o-2),c=-u,d=1+u,h=[c,c,d,c,d,d,c,c,d,d,c,d],f=6,p=6,g=3,m=2,v=1,A=new Float32Array(g*p*f),x=new Float32Array(m*p*f),y=new Float32Array(v*p*f);for(let e=0;e<f;e++){const t=e%3*2/3-1,n=e>2?0:-1,i=[t,n,0,t+2/3,n,0,t+2/3,n+1,0,t,n,0,t+2/3,n+1,0,t,n+1,0],r=KS[e];A.set(i,g*p*r),x.set(h,m*p*r);const s=[r,r,r,r,r,r];y.set(s,v*p*r)}const b=new Va;b.setAttribute("position",new Ia(A,g)),b.setAttribute("uv",new Ia(x,m)),b.setAttribute("faceIndex",new Ia(y,v)),t.push(b),r.push(new nl(b,null)),s>4&&s--}return{lodPlanes:t,sizeLods:n,sigmas:i,lodMeshes:r}}(t)),this._blurMaterial=function(e,t,n){const i=jw(new Array(kS).fill(0)),r=Nx(new Es(0,1,0)),s=Nx(0),o=EA(kS),a=Nx(0),l=Nx(1),u=Pw(null),c=Nx(0),d=EA(1/t),h=EA(1/n),f=EA(e),p={n:o,latitudinal:a,weights:i,poleAxis:r,outputDirection:_S,dTheta:s,samples:l,envMap:u,mipInt:c,CUBEUV_TEXEL_WIDTH:d,CUBEUV_TEXEL_HEIGHT:h,CUBEUV_MAX_MIP:f},g=nP("blur");return g.fragmentNode=zS({...p,latitudinal:a.equal(1)}),JS.set(g,p),g}(t,e.width,e.height)}}async _compileMaterial(e){const t=new nl(this._lodPlanes[0],e);await this._renderer.compile(t,FS)}_sceneToCubeUV(e,t,n,i,r){const s=HS;s.near=t,s.far=n;const o=[1,1,1,1,-1,1],a=[1,-1,1,-1,1,-1],l=this._renderer,u=l.autoClear;l.getClearColor(US),l.autoClear=!1;let c=this._backgroundBox;if(null===c){const e=new Ma({name:"PMREM.Background",side:1,depthWrite:!1,depthTest:!1});c=new nl(new rl,e)}let d=!1;const h=e.background;h?h.isColor&&(c.material.color.copy(h),e.background=null,d=!0):(c.material.color.copy(US),d=!0),l.setRenderTarget(i),l.clear(),d&&l.render(c,s);for(let t=0;t<6;t++){const n=t%3;0===n?(s.up.set(0,o[t],0),s.position.set(r.x,r.y,r.z),s.lookAt(r.x+a[t],r.y,r.z)):1===n?(s.up.set(0,0,o[t]),s.position.set(r.x,r.y,r.z),s.lookAt(r.x,r.y+a[t],r.z)):(s.up.set(0,o[t],0),s.position.set(r.x,r.y,r.z),s.lookAt(r.x,r.y,r.z+a[t]));const u=this._cubeSize;tP(i,n*u,t>2?u:0,u,u),l.render(e,s)}l.autoClear=u,e.background=h}_textureToCubeUV(e,t){const n=this._renderer,i=e.mapping===Ni||e.mapping===Bi;i?null===this._cubemapMaterial&&(this._cubemapMaterial=iP(e)):null===this._equirectMaterial&&(this._equirectMaterial=rP(e));const r=i?this._cubemapMaterial:this._equirectMaterial;r.fragmentNode.value=e;const s=this._lodMeshes[0];s.material=r;const o=this._cubeSize;tP(t,0,0,3*o,2*o),n.setRenderTarget(t),n.render(s,FS)}_applyPMREM(e){const t=this._renderer,n=t.autoClear;t.autoClear=!1;const i=this._lodPlanes.length;for(let t=1;t<i;t++){const n=Math.sqrt(this._sigmas[t]*this._sigmas[t]-this._sigmas[t-1]*this._sigmas[t-1]),r=ZS[(i-t-1)%ZS.length];this._blur(e,t-1,t,n,r)}t.autoClear=n}_blur(e,t,n,i,r){const s=this._pingPongRenderTarget;this._halfBlur(e,s,t,n,i,"latitudinal",r),this._halfBlur(s,e,n,n,i,"longitudinal",r)}_halfBlur(e,t,n,i,r,s,o){const a=this._renderer,l=this._blurMaterial;"latitudinal"!==s&&"longitudinal"!==s&&console.error("blur direction must be either latitudinal or longitudinal!");const u=this._lodMeshes[i];u.material=l;const c=JS.get(l),d=this._sizeLods[n]-1,h=isFinite(r)?Math.PI/(2*d):2*Math.PI/39,f=r/h,p=isFinite(r)?1+Math.floor(3*f):kS;p>kS&&console.warn(`sigmaRadians, ${r}, is too large and will clip, as it requested ${p} samples when the maximum is set to 20`);const g=[];let m=0;for(let e=0;e<kS;++e){const t=e/f,n=Math.exp(-t*t/2);g.push(n),0===e?m+=n:e<p&&(m+=2*n)}for(let e=0;e<g.length;e++)g[e]=g[e]/m;e.texture.frame=(e.texture.frame||0)+1,c.envMap.value=e.texture,c.samples.value=p,c.weights.array=g,c.latitudinal.value="latitudinal"===s?1:0,o&&(c.poleAxis.value=o);const{_lodMax:v}=this;c.dTheta.value=h,c.mipInt.value=v-n;const A=this._sizeLods[i];tP(t,3*A*(i>v-4?i-v+4:0),4*(this._cubeSize-A),3*A,2*A),a.setRenderTarget(t),a.render(u,FS)}}function eP(e,t){const n=new Ks(e,t,{magFilter:Hi,minFilter:Hi,generateMipmaps:!1,type:Ki,format:rr,colorSpace:_r});return n.texture.mapping=Li,n.texture.name="PMREM.cubeUv",n.texture.isPMREMTexture=!0,n.scissorTest=!0,n}function tP(e,t,n,i,r){e.viewport.set(t,n,i,r),e.scissor.set(t,n,i,r)}function nP(e){const t=new _E;return t.depthTest=!1,t.depthWrite=!1,t.blending=0,t.name=`PMREM_${e}`,t}function iP(e){const t=nP("cubemap");return t.fragmentNode=HC(e,_S),t}function rP(e){const t=nP("equirect");return t.fragmentNode=Pw(e,oT(_S),0),t}const sP=new WeakMap;function oP(e,t,n){const i=function(e){let t=sP.get(e);void 0===t&&(t=new WeakMap,sP.set(e,t));return t}(t);let r=i.get(e);if((void 0!==r?r.pmremVersion:-1)!==e.pmremVersion){const t=e.image;if(e.isCubeTexture){if(!function(e){if(null==e)return!1;let t=0;const n=6;for(let i=0;i<n;i++)void 0!==e[i]&&t++;return t===n}(t))return null;r=n.fromCubemap(e,r)}else{if(!function(e){return null!=e&&e.height>0}(t))return null;r=n.fromEquirectangular(e,r)}r.pmremVersion=e.pmremVersion,i.set(e,r)}return r.texture}class aP extends Cv{static get type(){return"PMREMNode"}constructor(e,t=null,n=null){super("vec3"),this._value=e,this._pmrem=null,this.uvNode=t,this.levelNode=n,this._generator=null;const i=new Ys;i.isRenderTargetTexture=!0,this._texture=Pw(i),this._width=Nx(0),this._height=Nx(0),this._maxMip=Nx(0),this.updateBeforeType=hv.RENDER}set value(e){this._value=e,this._pmrem=null}get value(){return this._value}updateFromTexture(e){const t=function(e){const t=Math.log2(e)-2,n=1/e;return{texelWidth:1/(3*Math.max(Math.pow(2,t),112)),texelHeight:n,maxMip:t}}(e.image.height);this._texture.value=e,this._width.value=t.texelWidth,this._height.value=t.texelHeight,this._maxMip.value=t.maxMip}updateBefore(e){let t=this._pmrem;const n=t?t.pmremVersion:-1,i=this._value;n!==i.pmremVersion&&(t=!0===i.isPMREMTexture?i:oP(i,e.renderer,this._generator),null!==t&&(this._pmrem=t,this.updateFromTexture(t)))}setup(e){null===this._generator&&(this._generator=new $S(e.renderer)),this.updateBefore(e);let t=this.uvNode;null===t&&e.context.getUV&&(t=e.context.getUV(this)),t=IC.mul(LA(t.x,t.y.negate(),t.z));let n=this.levelNode;return null===n&&e.context.getTextureLevel&&(n=e.context.getTextureLevel(this)),LS(this._texture,t,n,this._width,this._height,this._maxMip)}dispose(){super.dispose(),null!==this._generator&&this._generator.dispose()}}const lP=pA(aP).setParameterLength(1,3),uP=new WeakMap;class cP extends TE{static get type(){return"EnvironmentNode"}constructor(e=null){super(),this.envNode=e}setup(e){const{material:t}=e;let n=this.envNode;if(n.isTextureNode||n.isMaterialReferenceNode){const e=n.isTextureNode?n.value:t[n.property];let i=uP.get(e);void 0===i&&(i=lP(e),uP.set(e,i)),n=i}const i=!0===t.useAnisotropy||t.anisotropy>0?fM:CC,r=n.context(dP(qA,i)).mul(DC),s=n.context(hP(MC)).mul(Math.PI).mul(DC),o=sw(r),a=sw(s);e.context.radiance.addAssign(o),e.context.iblIrradiance.addAssign(a);const l=e.context.lightingModel.clearcoatRadiance;if(l){const e=n.context(dP(ex,EC)).mul(DC),t=sw(e);l.addAssign(t)}}}const dP=(e,t)=>{let n=null;return{getUV:()=>(null===n&&(n=fC.negate().reflect(t),n=e.mul(e).mix(n,t).normalize(),n=n.transformDirection(Jw)),n),getTextureLevel:()=>e}},hP=e=>({getUV:()=>e,getTextureLevel:()=>EA(1)}),fP=new Cu;class pP extends _E{static get type(){return"MeshStandardNodeMaterial"}constructor(e){super(),this.isMeshStandardNodeMaterial=!0,this.lights=!0,this.emissiveNode=null,this.metalnessNode=null,this.roughnessNode=null,this.setDefaultValues(fP),this.setValues(e)}setupEnvironment(e){let t=super.setupEnvironment(e);return null===t&&e.environmentNode&&(t=e.environmentNode),t?new cP(t):null}setupLightingModel(){return new mS}setupSpecular(){const e=ub(LA(.04),JA.rgb,_A);cx.assign(e),dx.assign(1)}setupVariants(){const e=this.metalnessNode?EA(this.metalnessNode):LM;_A.assign(e);let t=this.roughnessNode?EA(this.roughnessNode):IM;t=NT({roughness:t}),qA.assign(t),this.setupSpecular(),JA.assign(RA(JA.rgb.mul(e.oneMinus()),JA.a))}copy(e){return this.emissiveNode=e.emissiveNode,this.metalnessNode=e.metalnessNode,this.roughnessNode=e.roughnessNode,super.copy(e)}}const gP=new Mu;class mP extends pP{static get type(){return"MeshPhysicalNodeMaterial"}constructor(e){super(),this.isMeshPhysicalNodeMaterial=!0,this.clearcoatNode=null,this.clearcoatRoughnessNode=null,this.clearcoatNormalNode=null,this.sheenNode=null,this.sheenRoughnessNode=null,this.iridescenceNode=null,this.iridescenceIORNode=null,this.iridescenceThicknessNode=null,this.specularIntensityNode=null,this.specularColorNode=null,this.iorNode=null,this.transmissionNode=null,this.thicknessNode=null,this.attenuationDistanceNode=null,this.attenuationColorNode=null,this.dispersionNode=null,this.anisotropyNode=null,this.setDefaultValues(gP),this.setValues(e)}get useClearcoat(){return this.clearcoat>0||null!==this.clearcoatNode}get useIridescence(){return this.iridescence>0||null!==this.iridescenceNode}get useSheen(){return this.sheen>0||null!==this.sheenNode}get useAnisotropy(){return this.anisotropy>0||null!==this.anisotropyNode}get useTransmission(){return this.transmission>0||null!==this.transmissionNode}get useDispersion(){return this.dispersion>0||null!==this.dispersionNode}setupSpecular(){const e=this.iorNode?EA(this.iorNode):ZM;mx.assign(e),cx.assign(ub(Yy(ib(mx.sub(1).div(mx.add(1))).mul(NM),LA(1)).mul(PM),JA.rgb,_A)),dx.assign(ub(PM,1,_A))}setupLightingModel(){return new mS(this.useClearcoat,this.useSheen,this.useIridescence,this.useAnisotropy,this.useTransmission,this.useDispersion)}setupVariants(e){if(super.setupVariants(e),this.useClearcoat){const e=this.clearcoatNode?EA(this.clearcoatNode):OM,t=this.clearcoatRoughnessNode?EA(this.clearcoatRoughnessNode):zM;$A.assign(e),ex.assign(NT({roughness:t}))}if(this.useSheen){const e=this.sheenNode?LA(this.sheenNode):FM,t=this.sheenRoughnessNode?EA(this.sheenRoughnessNode):HM;tx.assign(e),nx.assign(t)}if(this.useIridescence){const e=this.iridescenceNode?EA(this.iridescenceNode):XM,t=this.iridescenceIORNode?EA(this.iridescenceIORNode):GM,n=this.iridescenceThicknessNode?EA(this.iridescenceThicknessNode):VM;ix.assign(e),rx.assign(t),sx.assign(n)}if(this.useAnisotropy){const e=(this.anisotropyNode?NA(this.anisotropyNode):UM).toVar();ax.assign(e.length()),wA(ax.equal(0),(()=>{e.assign(NA(1,0))})).Else((()=>{e.divAssign(NA(ax)),ax.assign(ax.saturate())})),ox.assign(ax.pow2().mix(qA.pow2(),1)),lx.assign(hM[0].mul(e.x).add(hM[1].mul(e.y))),ux.assign(hM[1].mul(e.x).sub(hM[0].mul(e.y)))}if(this.useTransmission){const e=this.transmissionNode?EA(this.transmissionNode):WM,t=this.thicknessNode?EA(this.thicknessNode):QM,n=this.attenuationDistanceNode?EA(this.attenuationDistanceNode):YM,i=this.attenuationColorNode?LA(this.attenuationColorNode):JM;if(vx.assign(e),Ax.assign(t),xx.assign(n),yx.assign(i),this.useDispersion){const e=this.dispersionNode?EA(this.dispersionNode):tE;bx.assign(e)}}}setupClearcoatNormal(){return this.clearcoatNormalNode?LA(this.clearcoatNormalNode):RM}setup(e){e.context.setupClearcoatNormal=()=>Lb(this.setupClearcoatNormal(e),"NORMAL","vec3"),super.setup(e)}copy(e){return this.clearcoatNode=e.clearcoatNode,this.clearcoatRoughnessNode=e.clearcoatRoughnessNode,this.clearcoatNormalNode=e.clearcoatNormalNode,this.sheenNode=e.sheenNode,this.sheenRoughnessNode=e.sheenRoughnessNode,this.iridescenceNode=e.iridescenceNode,this.iridescenceIORNode=e.iridescenceIORNode,this.iridescenceThicknessNode=e.iridescenceThicknessNode,this.specularIntensityNode=e.specularIntensityNode,this.specularColorNode=e.specularColorNode,this.transmissionNode=e.transmissionNode,this.thicknessNode=e.thicknessNode,this.attenuationDistanceNode=e.attenuationDistanceNode,this.attenuationColorNode=e.attenuationColorNode,this.dispersionNode=e.dispersionNode,this.anisotropyNode=e.anisotropyNode,super.copy(e)}}const vP=xA((({normal:e,lightDirection:t,builder:n})=>{const i=e.dot(t),r=NA(i.mul(.5).add(.5),0);if(n.material.gradientMap){const e=QC("gradientMap","texture").context({getUV:()=>r});return LA(e.r)}{const e=r.fwidth().mul(.5);return ub(LA(.7),LA(1),fb(EA(.7).sub(e.x),EA(.7).add(e.x),r.x))}}));class AP extends gT{direct({lightDirection:e,lightColor:t,reflectedLight:n},i){const r=vP({normal:AC,lightDirection:e,builder:i}).mul(t);n.directDiffuse.addAssign(r.mul(yT({diffuseColor:JA.rgb})))}indirect(e){const{ambientOcclusion:t,irradiance:n,reflectedLight:i}=e.context;i.indirectDiffuse.addAssign(n.mul(yT({diffuseColor:JA}))),i.indirectDiffuse.mulAssign(t)}}const xP=new Tu;class yP extends _E{static get type(){return"MeshToonNodeMaterial"}constructor(e){super(),this.isMeshToonNodeMaterial=!0,this.lights=!0,this.setDefaultValues(xP),this.setValues(e)}setupLightingModel(){return new AP}}const bP=xA((()=>{const e=LA(fC.z,0,fC.x.negate()).normalize(),t=fC.cross(e);return NA(e.dot(CC),t.dot(CC)).mul(.495).add(.5)})).once(["NORMAL","VERTEX"])().toVar("matcapUV"),wP=new Du;class CP extends _E{static get type(){return"MeshMatcapNodeMaterial"}constructor(e){super(),this.isMeshMatcapNodeMaterial=!0,this.setDefaultValues(wP),this.setValues(e)}setupVariants(e){const t=bP;let n;n=e.material.matcap?QC("matcap","texture").context({getUV:()=>t}):LA(ub(.2,.8,t.y)),JA.rgb.mulAssign(n.rgb)}}class MP extends Cv{static get type(){return"RotateNode"}constructor(e,t){super(),this.positionNode=e,this.rotationNode=t}getNodeType(e){return this.positionNode.getNodeType(e)}setup(e){const{rotationNode:t,positionNode:n}=this;if("vec2"===this.getNodeType(e)){const e=t.cos(),i=t.sin();return UA(e,i,i.negate(),e).mul(n)}{const e=t,i=GA(RA(1,0,0,0),RA(0,Py(e.x),Sy(e.x).negate(),0),RA(0,Sy(e.x),Py(e.x),0),RA(0,0,0,1)),r=GA(RA(Py(e.y),0,Sy(e.y),0),RA(0,1,0,0),RA(Sy(e.y).negate(),0,Py(e.y),0),RA(0,0,0,1)),s=GA(RA(Py(e.z),Sy(e.z).negate(),0,0),RA(Sy(e.z),Py(e.z),0,0),RA(0,0,1,0),RA(0,0,0,1));return i.mul(r).mul(s).mul(RA(n,1)).xyz}}}const EP=pA(MP).setParameterLength(2),TP=new Tl;class SP extends _E{static get type(){return"SpriteNodeMaterial"}constructor(e){super(),this.isSpriteNodeMaterial=!0,this._useSizeAttenuation=!0,this.positionNode=null,this.rotationNode=null,this.scaleNode=null,this.transparent=!0,this.setDefaultValues(TP),this.setValues(e)}setupPositionView(e){const{object:t,camera:n}=e,{positionNode:i,rotationNode:r,scaleNode:s,sizeAttenuation:o}=this,a=iC.mul(LA(i||0));let l=NA(tC[0].xyz.length(),tC[1].xyz.length());null!==s&&(l=l.mul(NA(s))),n.isPerspectiveCamera&&!1===o&&(l=l.mul(a.z.negate()));let u=aC.xy;if(t.center&&!0===t.center.isVector2){const e=((e,t,n)=>cA(new Vb(e,t,n)))("center","vec2",t);u=u.sub(e.sub(.5))}u=u.mul(l);const c=EA(r||kM),d=EP(u,c);return RA(a.xy.add(d),a.zw)}copy(e){return this.positionNode=e.positionNode,this.rotationNode=e.rotationNode,this.scaleNode=e.scaleNode,super.copy(e)}get sizeAttenuation(){return this._useSizeAttenuation}set sizeAttenuation(e){this._useSizeAttenuation!==e&&(this._useSizeAttenuation=e,this.needsUpdate=!0)}}const PP=new Kl,NP=new Cs;class BP extends SP{static get type(){return"PointsNodeMaterial"}constructor(e){super(),this.sizeNode=null,this.isPointsNodeMaterial=!0,this.setDefaultValues(PP),this.setValues(e)}setupPositionView(){const{positionNode:e}=this;return iC.mul(LA(e||lC)).xyz}setupVertexSprite(e){const{material:t,camera:n}=e,{rotationNode:i,scaleNode:r,sizeNode:s,sizeAttenuation:o}=this;let a=super.setupVertex(e);if(!0!==t.isNodeMaterial)return a;let l=null!==s?NA(s):eE;l=l.mul(Fw),n.isPerspectiveCamera&&!0===o&&(l=l.mul(DP.div(hC.z.negate()))),r&&r.isNode&&(l=l.mul(NA(r)));let u=aC.xy;if(i&&i.isNode){const e=EA(i);u=EP(u,e)}return u=u.mul(l),u=u.div(Vw.div(2)),u=u.mul(a.w),a=a.add(RA(u,0,0)),a}setupVertex(e){return e.object.isPoints?super.setupVertex(e):this.setupVertexSprite(e)}get alphaToCoverage(){return this._useAlphaToCoverage}set alphaToCoverage(e){this._useAlphaToCoverage!==e&&(this._useAlphaToCoverage=e,this.needsUpdate=!0)}}const DP=Nx(1).onFrameUpdate((function({renderer:e}){const t=e.getSize(NP);this.value=.5*t.y}));class IP extends gT{constructor(){super(),this.shadowNode=EA(1).toVar("shadowMask")}direct({lightNode:e}){null!==e.shadowNode&&this.shadowNode.mulAssign(e.shadowNode)}finish({context:e}){JA.a.mulAssign(this.shadowNode.oneMinus()),e.outgoingLight.rgb.assign(JA.rgb)}}const LP=new wu;class jP extends _E{static get type(){return"ShadowNodeMaterial"}constructor(e){super(),this.isShadowNodeMaterial=!0,this.lights=!0,this.transparent=!0,this.setDefaultValues(LP),this.setValues(e)}setupLightingModel(){return new IP}}ZA("vec3"),ZA("vec3"),ZA("vec3");class OP{constructor(e,t){this.nodes=e,this.info=t,this._context="undefined"!=typeof self?self:null,this._animationLoop=null,this._requestId=null}start(){const e=(t,n)=>{this._requestId=this._context.requestAnimationFrame(e),!0===this.info.autoReset&&this.info.reset(),this.nodes.nodeFrame.update(),this.info.frame=this.nodes.nodeFrame.frameId,null!==this._animationLoop&&this._animationLoop(t,n)};e()}stop(){this._context.cancelAnimationFrame(this._requestId),this._requestId=null}getAnimationLoop(){return this._animationLoop}setAnimationLoop(e){this._animationLoop=e}getContext(){return this._context}setContext(e){this._context=e}dispose(){this.stop()}}class zP{constructor(){this.weakMap=new WeakMap}get(e){let t=this.weakMap;for(let n=0;n<e.length-1;n++)if(t=t.get(e[n]),void 0===t)return;return t.get(e[e.length-1])}set(e,t){let n=this.weakMap;for(let t=0;t<e.length-1;t++){const i=e[t];!1===n.has(i)&&n.set(i,new WeakMap),n=n.get(i)}return n.set(e[e.length-1],t),this}delete(e){let t=this.weakMap;for(let n=0;n<e.length-1;n++)if(t=t.get(e[n]),void 0===t)return!1;return t.delete(e[e.length-1])}}let RP=0;class kP{constructor(e,t,n,i,r,s,o,a,l,u){this.id=RP++,this._nodes=e,this._geometries=t,this.renderer=n,this.object=i,this.material=r,this.scene=s,this.camera=o,this.lightsNode=a,this.context=l,this.geometry=i.geometry,this.version=r.version,this.drawRange=null,this.attributes=null,this.attributesId=null,this.pipeline=null,this.group=null,this.vertexBuffers=null,this.drawParams=null,this.bundle=null,this.clippingContext=u,this.clippingContextCacheKey=null!==u?u.cacheKey:"",this.initialNodesCacheKey=this.getDynamicCacheKey(),this.initialCacheKey=this.getCacheKey(),this._nodeBuilderState=null,this._bindings=null,this._monitor=null,this.onDispose=null,this.isRenderObject=!0,this.onMaterialDispose=()=>{this.dispose()},this.onGeometryDispose=()=>{this.attributes=null,this.attributesId=null},this.material.addEventListener("dispose",this.onMaterialDispose),this.geometry.addEventListener("dispose",this.onGeometryDispose)}updateClipping(e){this.clippingContext=e}get clippingNeedsUpdate(){return null!==this.clippingContext&&this.clippingContext.cacheKey!==this.clippingContextCacheKey&&(this.clippingContextCacheKey=this.clippingContext.cacheKey,!0)}get hardwareClippingPlanes(){return!0===this.material.hardwareClipping?this.clippingContext.unionClippingCount:0}getNodeBuilderState(){return this._nodeBuilderState||(this._nodeBuilderState=this._nodes.getForRender(this))}getMonitor(){return this._monitor||(this._monitor=this.getNodeBuilderState().observer)}getBindings(){return this._bindings||(this._bindings=this.getNodeBuilderState().createBindings())}getBindingGroup(e){for(const t of this.getBindings())if(t.name===e)return t}getIndex(){return this._geometries.getIndex(this)}getIndirect(){return this._geometries.getIndirect(this)}getChainArray(){return[this.object,this.material,this.context,this.lightsNode]}setGeometry(e){this.geometry=e,this.attributes=null,this.attributesId=null}getAttributes(){if(null!==this.attributes)return this.attributes;const e=this.getNodeBuilderState().nodeAttributes,t=this.geometry,n=[],i=new Set,r={};for(const s of e){let e;if(s.node&&s.node.attribute?e=s.node.attribute:(e=t.getAttribute(s.name),r[s.name]=e.version),void 0===e)continue;n.push(e);const o=e.isInterleavedBufferAttribute?e.data:e;i.add(o)}return this.attributes=n,this.attributesId=r,this.vertexBuffers=Array.from(i.values()),n}getVertexBuffers(){return null===this.vertexBuffers&&this.getAttributes(),this.vertexBuffers}getDrawParameters(){const{object:e,material:t,geometry:n,group:i,drawRange:r}=this,s=this.drawParams||(this.drawParams={vertexCount:0,firstVertex:0,instanceCount:0,firstInstance:0}),o=this.getIndex(),a=null!==o;let l=1;if(!0===n.isInstancedBufferGeometry?l=n.instanceCount:void 0!==e.count&&(l=Math.max(0,e.count)),0===l)return null;if(s.instanceCount=l,!0===e.isBatchedMesh)return s;let u=1;!0!==t.wireframe||e.isPoints||e.isLineSegments||e.isLine||e.isLineLoop||(u=2);let c=r.start*u,d=(r.start+r.count)*u;null!==i&&(c=Math.max(c,i.start*u),d=Math.min(d,(i.start+i.count)*u));const h=n.attributes.position;let f=1/0;a?f=o.count:null!=h&&(f=h.count),c=Math.max(c,0),d=Math.min(d,f);const p=d-c;return p<0||p===1/0?null:(s.vertexCount=p,s.firstVertex=c,s)}getGeometryCacheKey(){const{geometry:e}=this;let t="";for(const n of Object.keys(e.attributes).sort()){const i=e.attributes[n];t+=n+",",i.data&&(t+=i.data.stride+","),i.offset&&(t+=i.offset+","),i.itemSize&&(t+=i.itemSize+","),i.normalized&&(t+="n,")}for(const n of Object.keys(e.morphAttributes).sort()){const i=e.morphAttributes[n];t+="morph-"+n+",";for(let e=0,n=i.length;e<n;e++){t+=i[e].id+","}}return e.index&&(t+="index,"),t}getMaterialCacheKey(){const{object:e,material:t,renderer:n}=this;let i=t.customProgramCacheKey();for(const e of function(e){const t=Object.keys(e);let n=Object.getPrototypeOf(e);for(;n;){const e=Object.getOwnPropertyDescriptors(n);for(const n in e)if(void 0!==e[n]){const i=e[n];i&&"function"==typeof i.get&&t.push(n)}n=Object.getPrototypeOf(n)}return t}(t)){if(/^(is[A-Z]|_)|^(visible|version|uuid|name|opacity|userData)$/.test(e))continue;const r=t[e];let s;if(null!==r){const e=typeof r;"number"===e?s=0!==r?"1":"0":"object"===e?(s="{",r.isTexture&&(s+=r.mapping,!0===n.backend.isWebGPUBackend&&(s+=r.magFilter,s+=r.minFilter,s+=r.wrapS,s+=r.wrapT,s+=r.wrapR)),s+="}"):s=String(r)}else s=String(r);i+=s+","}return i+=this.clippingContextCacheKey+",",e.geometry&&(i+=this.getGeometryCacheKey()),e.skeleton&&(i+=e.skeleton.bones.length+","),e.isBatchedMesh&&(i+=e._matricesTexture.uuid+",",null!==e._colorsTexture&&(i+=e._colorsTexture.uuid+",")),(e.isInstancedMesh||e.count>1)&&(i+=e.uuid+","),i+=e.receiveShadow+",",_m(i)}get needsGeometryUpdate(){if(this.geometry.id!==this.object.geometry.id)return!0;if(null!==this.attributes){const e=this.attributesId;for(const t in e){const n=this.geometry.getAttribute(t);if(void 0===n||e[t]!==n.id)return!0}}return!1}get needsUpdate(){return this.initialNodesCacheKey!==this.getDynamicCacheKey()||this.clippingNeedsUpdate}getDynamicCacheKey(){let e=0;return!0!==this.material.isShadowPassMaterial&&(e=this._nodes.getCacheKey(this.scene,this.lightsNode)),this.camera.isArrayCamera&&(e=ev(e,this.camera.cameras.length)),this.object.receiveShadow&&(e=ev(e,1)),e}getCacheKey(){return this.getMaterialCacheKey()+this.getDynamicCacheKey()}dispose(){this.material.removeEventListener("dispose",this.onMaterialDispose),this.geometry.removeEventListener("dispose",this.onGeometryDispose),this.onDispose()}}const FP=[];class HP{constructor(e,t,n,i,r,s){this.renderer=e,this.nodes=t,this.geometries=n,this.pipelines=i,this.bindings=r,this.info=s,this.chainMaps={}}get(e,t,n,i,r,s,o,a){const l=this.getChainMap(a);FP[0]=e,FP[1]=t,FP[2]=s,FP[3]=r;let u=l.get(FP);return void 0===u?(u=this.createRenderObject(this.nodes,this.geometries,this.renderer,e,t,n,i,r,s,o,a),l.set(FP,u)):(u.updateClipping(o),u.needsGeometryUpdate&&u.setGeometry(e.geometry),(u.version!==t.version||u.needsUpdate)&&(u.initialCacheKey!==u.getCacheKey()?(u.dispose(),u=this.get(e,t,n,i,r,s,o,a)):u.version=t.version)),FP.length=0,u}getChainMap(e="default"){return this.chainMaps[e]||(this.chainMaps[e]=new zP)}dispose(){this.chainMaps={}}createRenderObject(e,t,n,i,r,s,o,a,l,u,c){const d=this.getChainMap(c),h=new kP(e,t,n,i,r,s,o,a,l,u);return h.onDispose=()=>{this.pipelines.delete(h),this.bindings.delete(h),this.nodes.delete(h),d.delete(h.getChainArray())},h}}class UP{constructor(){this.data=new WeakMap}get(e){let t=this.data.get(e);return void 0===t&&(t={},this.data.set(e,t)),t}delete(e){let t=null;return this.data.has(e)&&(t=this.data.get(e),this.data.delete(e)),t}has(e){return this.data.has(e)}dispose(){this.data=new WeakMap}}const XP=1,GP=2,VP=3,WP=4,QP=16;class ZP extends UP{constructor(e){super(),this.backend=e}delete(e){const t=super.delete(e);return null!==t&&this.backend.destroyAttribute(e),t}update(e,t){const n=this.get(e);if(void 0===n.version)t===XP?this.backend.createAttribute(e):t===GP?this.backend.createIndexAttribute(e):t===VP?this.backend.createStorageAttribute(e):t===WP&&this.backend.createIndirectStorageAttribute(e),n.version=this._getBufferAttribute(e).version;else{const t=this._getBufferAttribute(e);(n.version<t.version||t.usage===ss)&&(this.backend.updateAttribute(e),n.version=t.version)}}_getBufferAttribute(e){return e.isInterleavedBufferAttribute&&(e=e.data),e}}function YP(e){return null!==e.index?e.index.version:e.attributes.position.version}function JP(e){const t=[],n=e.index,i=e.attributes.position;if(null!==n){const e=n.array;for(let n=0,i=e.length;n<i;n+=3){const i=e[n+0],r=e[n+1],s=e[n+2];t.push(i,r,r,s,s,i)}}else{for(let e=0,n=i.array.length/3-1;e<n;e+=3){const n=e+0,i=e+1,r=e+2;t.push(n,i,i,r,r,n)}}const r=new(Bs(t)?ja:La)(t,1);return r.version=YP(e),r}class KP extends UP{constructor(e,t){super(),this.attributes=e,this.info=t,this.wireframes=new WeakMap,this.attributeCall=new WeakMap}has(e){const t=e.geometry;return super.has(t)&&!0===this.get(t).initialized}updateForRender(e){!1===this.has(e)&&this.initGeometry(e),this.updateAttributes(e)}initGeometry(e){const t=e.geometry;this.get(t).initialized=!0,this.info.memory.geometries++;const n=()=>{this.info.memory.geometries--;const i=t.index,r=e.getAttributes();null!==i&&this.attributes.delete(i);for(const e of r)this.attributes.delete(e);const s=this.wireframes.get(t);void 0!==s&&this.attributes.delete(s),t.removeEventListener("dispose",n)};t.addEventListener("dispose",n)}updateAttributes(e){const t=e.getAttributes();for(const e of t)e.isStorageBufferAttribute||e.isStorageInstancedBufferAttribute?this.updateAttribute(e,VP):this.updateAttribute(e,XP);const n=this.getIndex(e);null!==n&&this.updateAttribute(n,GP);const i=e.geometry.indirect;null!==i&&this.updateAttribute(i,WP)}updateAttribute(e,t){const n=this.info.render.calls;e.isInterleavedBufferAttribute?void 0===this.attributeCall.get(e)?(this.attributes.update(e,t),this.attributeCall.set(e,n)):this.attributeCall.get(e.data)!==n&&(this.attributes.update(e,t),this.attributeCall.set(e.data,n),this.attributeCall.set(e,n)):this.attributeCall.get(e)!==n&&(this.attributes.update(e,t),this.attributeCall.set(e,n))}getIndirect(e){return e.geometry.indirect}getIndex(e){const{geometry:t,material:n}=e;let i=t.index;if(!0===n.wireframe){const e=this.wireframes;let n=e.get(t);void 0===n?(n=JP(t),e.set(t,n)):n.version!==YP(t)&&(this.attributes.delete(n),n=JP(t),e.set(t,n)),i=n}return i}}class qP{constructor(){this.autoReset=!0,this.frame=0,this.calls=0,this.render={calls:0,frameCalls:0,drawCalls:0,triangles:0,points:0,lines:0,timestamp:0},this.compute={calls:0,frameCalls:0,timestamp:0},this.memory={geometries:0,textures:0}}update(e,t,n){this.render.drawCalls++,e.isMesh||e.isSprite?this.render.triangles+=n*(t/3):e.isPoints?this.render.points+=n*t:e.isLineSegments?this.render.lines+=n*(t/2):e.isLine?this.render.lines+=n*(t-1):console.error("THREE.WebGPUInfo: Unknown object type.")}reset(){this.render.drawCalls=0,this.render.frameCalls=0,this.compute.frameCalls=0,this.render.triangles=0,this.render.points=0,this.render.lines=0}dispose(){this.reset(),this.calls=0,this.render.calls=0,this.compute.calls=0,this.render.timestamp=0,this.compute.timestamp=0,this.memory.geometries=0,this.memory.textures=0}}class _P{constructor(e){this.cacheKey=e,this.usedTimes=0}}class $P extends _P{constructor(e,t,n){super(e),this.vertexProgram=t,this.fragmentProgram=n}}class eN extends _P{constructor(e,t){super(e),this.computeProgram=t,this.isComputePipeline=!0}}let tN=0;class nN{constructor(e,t,n,i=null,r=null){this.id=tN++,this.code=e,this.stage=t,this.name=n,this.transforms=i,this.attributes=r,this.usedTimes=0}}class iN extends UP{constructor(e,t){super(),this.backend=e,this.nodes=t,this.bindings=null,this.caches=new Map,this.programs={vertex:new Map,fragment:new Map,compute:new Map}}getForCompute(e,t){const{backend:n}=this,i=this.get(e);if(this._needsComputeUpdate(e)){const r=i.pipeline;r&&(r.usedTimes--,r.computeProgram.usedTimes--);const s=this.nodes.getForCompute(e);let o=this.programs.compute.get(s.computeShader);void 0===o&&(r&&0===r.computeProgram.usedTimes&&this._releaseProgram(r.computeProgram),o=new nN(s.computeShader,"compute",e.name,s.transforms,s.nodeAttributes),this.programs.compute.set(s.computeShader,o),n.createProgram(o));const a=this._getComputeCacheKey(e,o);let l=this.caches.get(a);void 0===l&&(r&&0===r.usedTimes&&this._releasePipeline(r),l=this._getComputePipeline(e,o,a,t)),l.usedTimes++,o.usedTimes++,i.version=e.version,i.pipeline=l}return i.pipeline}getForRender(e,t=null){const{backend:n}=this,i=this.get(e);if(this._needsRenderUpdate(e)){const r=i.pipeline;r&&(r.usedTimes--,r.vertexProgram.usedTimes--,r.fragmentProgram.usedTimes--);const s=e.getNodeBuilderState(),o=e.material?e.material.name:"";let a=this.programs.vertex.get(s.vertexShader);void 0===a&&(r&&0===r.vertexProgram.usedTimes&&this._releaseProgram(r.vertexProgram),a=new nN(s.vertexShader,"vertex",o),this.programs.vertex.set(s.vertexShader,a),n.createProgram(a));let l=this.programs.fragment.get(s.fragmentShader);void 0===l&&(r&&0===r.fragmentProgram.usedTimes&&this._releaseProgram(r.fragmentProgram),l=new nN(s.fragmentShader,"fragment",o),this.programs.fragment.set(s.fragmentShader,l),n.createProgram(l));const u=this._getRenderCacheKey(e,a,l);let c=this.caches.get(u);void 0===c?(r&&0===r.usedTimes&&this._releasePipeline(r),c=this._getRenderPipeline(e,a,l,u,t)):e.pipeline=c,c.usedTimes++,a.usedTimes++,l.usedTimes++,i.pipeline=c}return i.pipeline}delete(e){const t=this.get(e).pipeline;return t&&(t.usedTimes--,0===t.usedTimes&&this._releasePipeline(t),t.isComputePipeline?(t.computeProgram.usedTimes--,0===t.computeProgram.usedTimes&&this._releaseProgram(t.computeProgram)):(t.fragmentProgram.usedTimes--,t.vertexProgram.usedTimes--,0===t.vertexProgram.usedTimes&&this._releaseProgram(t.vertexProgram),0===t.fragmentProgram.usedTimes&&this._releaseProgram(t.fragmentProgram))),super.delete(e)}dispose(){super.dispose(),this.caches=new Map,this.programs={vertex:new Map,fragment:new Map,compute:new Map}}updateForRender(e){this.getForRender(e)}_getComputePipeline(e,t,n,i){n=n||this._getComputeCacheKey(e,t);let r=this.caches.get(n);return void 0===r&&(r=new eN(n,t),this.caches.set(n,r),this.backend.createComputePipeline(r,i)),r}_getRenderPipeline(e,t,n,i,r){i=i||this._getRenderCacheKey(e,t,n);let s=this.caches.get(i);return void 0===s&&(s=new $P(i,t,n),this.caches.set(i,s),e.pipeline=s,this.backend.createRenderPipeline(e,r)),s}_getComputeCacheKey(e,t){return e.id+","+t.id}_getRenderCacheKey(e,t,n){return t.id+","+n.id+","+this.backend.getRenderCacheKey(e)}_releasePipeline(e){this.caches.delete(e.cacheKey)}_releaseProgram(e){const t=e.code,n=e.stage;this.programs[n].delete(t)}_needsComputeUpdate(e){const t=this.get(e);return void 0===t.pipeline||t.version!==e.version}_needsRenderUpdate(e){return void 0===this.get(e).pipeline||this.backend.needsRenderUpdate(e)}}class rN extends UP{constructor(e,t,n,i,r,s){super(),this.backend=e,this.textures=n,this.pipelines=r,this.attributes=i,this.nodes=t,this.info=s,this.pipelines.bindings=this}getForRender(e){const t=e.getBindings();for(const e of t){const n=this.get(e);void 0===n.bindGroup&&(this._init(e),this.backend.createBindings(e,t,0),n.bindGroup=e)}return t}getForCompute(e){const t=this.nodes.getForCompute(e).bindings;for(const e of t){const n=this.get(e);void 0===n.bindGroup&&(this._init(e),this.backend.createBindings(e,t,0),n.bindGroup=e)}return t}updateForCompute(e){this._updateBindings(this.getForCompute(e))}updateForRender(e){this._updateBindings(this.getForRender(e))}_updateBindings(e){for(const t of e)this._update(t,e)}_init(e){for(const t of e.bindings)if(t.isSampledTexture)this.textures.updateTexture(t.texture);else if(t.isStorageBuffer){const e=t.attribute,n=e.isIndirectStorageBufferAttribute?WP:VP;this.attributes.update(e,n)}}_update(e,t){const{backend:n}=this;let i=!1,r=!0,s=0,o=0;for(const t of e.bindings){if(t.isNodeUniformsGroup){if(!1===this.nodes.updateGroup(t))continue}if(t.isStorageBuffer){const e=t.attribute,n=e.isIndirectStorageBufferAttribute?WP:VP;this.attributes.update(e,n)}if(t.isUniformBuffer){t.update()&&n.updateBinding(t)}else if(t.isSampledTexture){const e=t.update(),a=t.texture,l=this.textures.get(a);e&&(this.textures.updateTexture(a),t.generation!==l.generation&&(t.generation=l.generation,i=!0,r=!1));if(void 0!==n.get(a).externalTexture||l.isDefaultTexture?r=!1:(s=10*s+a.id,o+=a.version),!0===a.isStorageTexture){const e=this.get(a);!0===t.store?e.needsMipmap=!0:this.textures.needsMipmaps(a)&&!0===e.needsMipmap&&(this.backend.generateMipmaps(a),e.needsMipmap=!1)}}else t.isSampler&&t.update()}!0===i&&this.backend.updateBindings(e,t,r?s:0,o)}}function sN(e,t){return e.groupOrder!==t.groupOrder?e.groupOrder-t.groupOrder:e.renderOrder!==t.renderOrder?e.renderOrder-t.renderOrder:e.z!==t.z?e.z-t.z:e.id-t.id}function oN(e,t){return e.groupOrder!==t.groupOrder?e.groupOrder-t.groupOrder:e.renderOrder!==t.renderOrder?e.renderOrder-t.renderOrder:e.z!==t.z?t.z-e.z:e.id-t.id}function aN(e){return(e.transmission>0||e.transmissionNode)&&2===e.side&&!1===e.forceSinglePass}class lN{constructor(e,t,n){this.renderItems=[],this.renderItemsIndex=0,this.opaque=[],this.transparentDoublePass=[],this.transparent=[],this.bundles=[],this.lightsNode=e.getNode(t,n),this.lightsArray=[],this.scene=t,this.camera=n,this.occlusionQueryCount=0}begin(){return this.renderItemsIndex=0,this.opaque.length=0,this.transparentDoublePass.length=0,this.transparent.length=0,this.bundles.length=0,this.lightsArray.length=0,this.occlusionQueryCount=0,this}getNextRenderItem(e,t,n,i,r,s,o){let a=this.renderItems[this.renderItemsIndex];return void 0===a?(a={id:e.id,object:e,geometry:t,material:n,groupOrder:i,renderOrder:e.renderOrder,z:r,group:s,clippingContext:o},this.renderItems[this.renderItemsIndex]=a):(a.id=e.id,a.object=e,a.geometry=t,a.material=n,a.groupOrder=i,a.renderOrder=e.renderOrder,a.z=r,a.group=s,a.clippingContext=o),this.renderItemsIndex++,a}push(e,t,n,i,r,s,o){const a=this.getNextRenderItem(e,t,n,i,r,s,o);!0===e.occlusionTest&&this.occlusionQueryCount++,!0===n.transparent||n.transmission>0?(aN(n)&&this.transparentDoublePass.push(a),this.transparent.push(a)):this.opaque.push(a)}unshift(e,t,n,i,r,s,o){const a=this.getNextRenderItem(e,t,n,i,r,s,o);!0===n.transparent||n.transmission>0?(aN(n)&&this.transparentDoublePass.unshift(a),this.transparent.unshift(a)):this.opaque.unshift(a)}pushBundle(e){this.bundles.push(e)}pushLight(e){this.lightsArray.push(e)}sort(e,t){this.opaque.length>1&&this.opaque.sort(e||sN),this.transparentDoublePass.length>1&&this.transparentDoublePass.sort(t||oN),this.transparent.length>1&&this.transparent.sort(t||oN)}finish(){this.lightsNode.setLights(this.lightsArray);for(let e=this.renderItemsIndex,t=this.renderItems.length;e<t;e++){const t=this.renderItems[e];if(null===t.id)break;t.id=null,t.object=null,t.geometry=null,t.material=null,t.groupOrder=null,t.renderOrder=null,t.z=null,t.group=null,t.clippingContext=null}}}const uN=[];class cN{constructor(e){this.lighting=e,this.lists=new zP}get(e,t){const n=this.lists;uN[0]=e,uN[1]=t;let i=n.get(uN);return void 0===i&&(i=new lN(this.lighting,e,t),n.set(uN,i)),uN.length=0,i}dispose(){this.lists=new zP}}let dN=0;class hN{constructor(){this.id=dN++,this.color=!0,this.clearColor=!0,this.clearColorValue={r:0,g:0,b:0,a:1},this.depth=!0,this.clearDepth=!0,this.clearDepthValue=1,this.stencil=!1,this.clearStencil=!0,this.clearStencilValue=1,this.viewport=!1,this.viewportValue=new Js,this.scissor=!1,this.scissorValue=new Js,this.renderTarget=null,this.textures=null,this.depthTexture=null,this.activeCubeFace=0,this.activeMipmapLevel=0,this.sampleCount=1,this.width=0,this.height=0,this.occlusionQueryCount=0,this.clippingContext=null,this.isRenderContext=!0}getCacheKey(){return fN(this)}}function fN(e){const{textures:t,activeCubeFace:n,activeMipmapLevel:i}=e,r=[n,i];for(const e of t)r.push(e.id);return $m(r)}const pN=[],gN=new wl,mN=new cl;class vN{constructor(){this.chainMaps={}}get(e,t,n=null){let i;if(pN[0]=e,pN[1]=t,null===n)i="default";else{const e=n.texture.format;i=`${n.textures.length}:${e}:${n.samples}:${n.depthBuffer}:${n.stencilBuffer}`}const r=this._getChainMap(i);let s=r.get(pN);return void 0===s&&(s=new hN,r.set(pN,s)),pN.length=0,null!==n&&(s.sampleCount=0===n.samples?1:n.samples),s}getForClear(e=null){return this.get(gN,mN,e)}_getChainMap(e){return this.chainMaps[e]||(this.chainMaps[e]=new zP)}dispose(){this.chainMaps={}}}const AN=new Es;class xN extends UP{constructor(e,t,n){super(),this.renderer=e,this.backend=t,this.info=n}updateRenderTarget(e,t=0){const n=this.get(e),i=0===e.samples?1:e.samples,r=n.depthTextureMips||(n.depthTextureMips={}),s=e.textures,o=this.getSize(s[0]),a=o.width>>t,l=o.height>>t;let u=e.depthTexture||r[t];const c=!0===e.depthBuffer||!0===e.stencilBuffer;let d=!1;void 0===u&&c&&(u=new _l,u.format=e.stencilBuffer?or:sr,u.type=e.stencilBuffer?$i:Yi,u.image.width=a,u.image.height=l,u.image.depth=o.depth,u.isArrayTexture=!0===e.multiview&&o.depth>1,r[t]=u),n.width===o.width&&o.height===n.height||(d=!0,u&&(u.needsUpdate=!0,u.image.width=a,u.image.height=l,u.image.depth=u.isArrayTexture?u.image.depth:1)),n.width=o.width,n.height=o.height,n.textures=s,n.depthTexture=u||null,n.depth=e.depthBuffer,n.stencil=e.stencilBuffer,n.renderTarget=e,n.sampleCount!==i&&(d=!0,u&&(u.needsUpdate=!0),n.sampleCount=i);const h={sampleCount:i};if(!0!==e.isXRRenderTarget){for(let e=0;e<s.length;e++){const t=s[e];d&&(t.needsUpdate=!0),this.updateTexture(t,h)}u&&this.updateTexture(u,h)}if(!0!==n.initialized){n.initialized=!0;const t=()=>{e.removeEventListener("dispose",t);for(let e=0;e<s.length;e++)this._destroyTexture(s[e]);u&&this._destroyTexture(u),this.delete(e),this.backend.delete(e)};e.addEventListener("dispose",t)}}updateTexture(e,t={}){const n=this.get(e);if(!0===n.initialized&&n.version===e.version)return;const i=e.isRenderTargetTexture||e.isDepthTexture||e.isFramebufferTexture,r=this.backend;if(i&&!0===n.initialized&&(r.destroySampler(e),r.destroyTexture(e)),e.isFramebufferTexture){const t=this.renderer.getRenderTarget();e.type=t?t.texture.type:Gi}const{width:s,height:o,depth:a}=this.getSize(e);if(t.width=s,t.height=o,t.depth=a,t.needsMipmaps=this.needsMipmaps(e),t.levels=t.needsMipmaps?this.getMipLevels(e,s,o):1,e.isCubeTexture&&e.mipmaps.length>0&&t.levels++,i||!0===e.isStorageTexture||!0===e.isExternalTexture)r.createSampler(e),r.createTexture(e,t),n.generation=e.version;else{if(!0!==n.initialized&&r.createSampler(e),e.version>0){const i=e.image;if(void 0===i)console.warn("THREE.Renderer: Texture marked for update but image is undefined.");else if(!1===i.complete)console.warn("THREE.Renderer: Texture marked for update but image is incomplete.");else{if(e.images){const n=[];for(const t of e.images)n.push(t);t.images=n}else t.image=i;void 0!==n.isDefaultTexture&&!0!==n.isDefaultTexture||(r.createTexture(e,t),n.isDefaultTexture=!1,n.generation=e.version),!0===e.source.dataReady&&r.updateTexture(e,t),t.needsMipmaps&&0===e.mipmaps.length&&r.generateMipmaps(e),e.onUpdate&&e.onUpdate(e)}}else r.createDefaultTexture(e),n.isDefaultTexture=!0,n.generation=e.version}if(!0!==n.initialized){n.initialized=!0,n.generation=e.version,this.info.memory.textures++,e.isVideoTexture&&ks.getTransfer(e.colorSpace)!==es&&console.warn("WebGPURenderer: Video textures must use a color space with a sRGB transfer function, e.g. SRGBColorSpace.");const t=()=>{e.removeEventListener("dispose",t),this._destroyTexture(e)};e.addEventListener("dispose",t)}n.version=e.version}getSize(e,t=AN){let n=e.images?e.images[0]:e.image;return n?(void 0!==n.image&&(n=n.image),"undefined"!=typeof HTMLVideoElement&&n instanceof HTMLVideoElement?(t.width=n.videoWidth||1,t.height=n.videoHeight||1,t.depth=1):n instanceof VideoFrame?(t.width=n.displayWidth||1,t.height=n.displayHeight||1,t.depth=1):(t.width=n.width||1,t.height=n.height||1,t.depth=e.isCubeTexture?6:n.depth||1)):t.width=t.height=t.depth=1,t}getMipLevels(e,t,n){let i;return i=e.mipmaps.length>0?e.mipmaps.length:!0===e.isCompressedTexture?1:Math.floor(Math.log2(Math.max(t,n)))+1,i}needsMipmaps(e){return!0===e.generateMipmaps||e.mipmaps.length>0}_destroyTexture(e){!0===this.has(e)&&(this.backend.destroySampler(e),this.backend.destroyTexture(e),this.delete(e),this.info.memory.textures--)}}class yN extends ya{constructor(e,t,n,i=1){super(e,t,n),this.a=i}set(e,t,n,i=1){return this.a=i,super.set(e,t,n)}copy(e){return void 0!==e.a&&(this.a=e.a),super.copy(e)}clone(){return new this.constructor(this.r,this.g,this.b,this.a)}}class bN extends QA{static get type(){return"ParameterNode"}constructor(e,t=null){super(e,t),this.isParameterNode=!0}getHash(){return this.uuid}generate(){return this.name}}class wN extends yv{static get type(){return"StackNode"}constructor(e=null){super(),this.nodes=[],this.outputNode=null,this.parent=e,this._currentCond=null,this._expressionNode=null,this.isStackNode=!0}getNodeType(e){return this.hasOutput?this.outputNode.getNodeType(e):"void"}getMemberType(e,t){return this.hasOutput?this.outputNode.getMemberType(e,t):"void"}add(e){return!0!==e.isNode?(console.error("THREE.TSL: Invalid node added to stack."),this):(this.nodes.push(e),this)}If(e,t){const n=new uA(t);return this._currentCond=bb(e,n),this.add(this._currentCond)}ElseIf(e,t){const n=new uA(t),i=bb(e,n);return this._currentCond.elseNode=i,this._currentCond=i,this}Else(e){return this._currentCond.elseNode=new uA(e),this}Switch(e){return this._expressionNode=cA(e),this}Case(...e){const t=[];if(e.length>=2)for(let n=0;n<e.length-1;n++)t.push(this._expressionNode.equal(cA(e[n])));else console.error("THREE.TSL: Invalid parameter length. Case() requires at least two parameters.");const n=new uA(e[e.length-1]);let i=t[0];for(let e=1;e<t.length;e++)i=i.or(t[e]);const r=bb(i,n);return null===this._currentCond?(this._currentCond=r,this.add(this._currentCond)):(this._currentCond.elseNode=r,this._currentCond=r,this)}Default(e){return this.Else(e),this}setup(e){const t=e.getNodeProperties(this);let n=0;for(const i of this.getChildren()){if(i.isVarNode&&!0===i.intent){if(!0!==e.getNodeProperties(i).assign)continue}t["node"+n++]=i}return t.outputNode||null}get hasOutput(){return this.outputNode&&this.outputNode.isNode}build(e,...t){const n=e.currentStack,i=bA();yA(this),e.currentStack=this;const r=e.buildStage;for(const t of this.nodes){if(t.isVarNode&&!0===t.intent){if(!0!==e.getNodeProperties(t).assign)continue}if("setup"===r)t.build(e);else if("analyze"===r)t.build(e,this);else if("generate"===r){const n=e.getDataFromNode(t,"any").stages,i=n&&n[e.shaderStage];if(t.isVarNode&&i&&1===i.length&&i[0]&&i[0].isStackNode)continue;t.build(e,"void")}}let s;return s=this.hasOutput?this.outputNode.build(e,...t):super.build(e,...t),yA(i),e.currentStack=n,s}}const CN=pA(wN).setParameterLength(0,1);new Il,new Es,new Es,new Es,new Po,new Es(0,0,-1),new Js,new Es,new Es,new Js,new Cs;const MN=new Ks;Hw.flipX();MN.depthTexture=new _l(1,1);const EN=new hc(-1,1,1,-1,0,1);class TN extends Va{constructor(e=!1){super();const t=!1===e?[0,-1,0,1,2,1]:[0,2,0,0,2,0];this.setAttribute("position",new za([-1,3,0,-1,-1,0,3,-1,0],3)),this.setAttribute("uv",new za(t,2))}}const SN=new TN;class PN extends nl{constructor(e=null){super(SN,e),this.camera=EN,this.isQuadMesh=!0}async renderAsync(e){return e.renderAsync(this,EN)}render(e){e.render(this,EN)}}class NN extends yv{static get type(){return"EventNode"}constructor(e,t){super("void"),this.eventType=e,this.callback=t,e===NN.OBJECT?this.updateType=hv.OBJECT:e===NN.MATERIAL&&(this.updateType=hv.RENDER)}update(e){this.callback(e)}}NN.OBJECT="object",NN.MATERIAL="material";const BN=new ko,DN=new Po;class IN extends yv{static get type(){return"SceneNode"}constructor(e=IN.BACKGROUND_BLURRINESS,t=null){super(),this.scope=e,this.scene=t}setup(e){const t=this.scope,n=null!==this.scene?this.scene:e.scene;let i;return t===IN.BACKGROUND_BLURRINESS?i=GC("backgroundBlurriness","float",n):t===IN.BACKGROUND_INTENSITY?i=GC("backgroundIntensity","float",n):t===IN.BACKGROUND_ROTATION?i=Nx("mat4").setName("backgroundRotation").setGroup(Tx).onRenderUpdate((()=>{const e=n.background;return null!==e&&e.isTexture&&e.mapping!==Pi?(BN.copy(n.backgroundRotation),BN.x*=-1,BN.y*=-1,BN.z*=-1,DN.makeRotationFromEuler(BN)):DN.identity(),DN})):console.error("THREE.SceneNode: Unknown scope:",t),i}}IN.BACKGROUND_BLURRINESS="backgroundBlurriness",IN.BACKGROUND_INTENSITY="backgroundIntensity",IN.BACKGROUND_ROTATION="backgroundRotation";const LN=gA(IN,IN.BACKGROUND_BLURRINESS),jN=gA(IN,IN.BACKGROUND_INTENSITY),ON=gA(IN,IN.BACKGROUND_ROTATION);const zN=xA((({texture:e,uv:t})=>{const n=1e-4,i=LA().toVar();return wA(t.x.lessThan(n),(()=>{i.assign(LA(1,0,0))})).ElseIf(t.y.lessThan(n),(()=>{i.assign(LA(0,1,0))})).ElseIf(t.z.lessThan(n),(()=>{i.assign(LA(0,0,1))})).ElseIf(t.x.greaterThan(.9999),(()=>{i.assign(LA(-1,0,0))})).ElseIf(t.y.greaterThan(.9999),(()=>{i.assign(LA(0,-1,0))})).ElseIf(t.z.greaterThan(.9999),(()=>{i.assign(LA(0,0,-1))})).Else((()=>{const n=.01,r=e.sample(t.add(LA(-.01,0,0))).r.sub(e.sample(t.add(LA(n,0,0))).r),s=e.sample(t.add(LA(0,-.01,0))).r.sub(e.sample(t.add(LA(0,n,0))).r),o=e.sample(t.add(LA(0,0,-.01))).r.sub(e.sample(t.add(LA(0,0,n))).r);i.assign(LA(r,s,o))})),i.normalize()}));class RN extends Tw{static get type(){return"Texture3DNode"}constructor(e,t=null,n=null){super(e,t,n),this.isTexture3DNode=!0}getInputType(){return"texture3D"}getDefaultUV(){return LA(.5,.5,.5)}setUpdateMatrix(){}setupUV(e,t){const n=this.value;return!e.isFlipY()||!0!==n.isRenderTargetTexture&&!0!==n.isFramebufferTexture||(t=this.sampler?t.flipY():t.setY(TA(ww(this,this.levelNode).y).sub(t.y).sub(1))),t}generateUV(e,t){return t.build(e,"vec3")}generateOffset(e,t){return t.build(e,"ivec3")}normal(e){return zN({texture:this,uv:e})}}const kN=pA(RN).setParameterLength(1,3);new WeakMap;const FN=new Cs;class HN extends Tw{static get type(){return"PassTextureNode"}constructor(e,t){super(t),this.passNode=e,this.setUpdateMatrix(!1)}setup(e){return this.passNode.build(e),super.setup(e)}clone(){return new this.constructor(this.passNode,this.value)}}class UN extends HN{static get type(){return"PassMultipleTextureNode"}constructor(e,t,n=!1){super(e,null),this.textureName=t,this.previousTexture=n}updateTexture(){this.value=this.previousTexture?this.passNode.getPreviousTexture(this.textureName):this.passNode.getTexture(this.textureName)}setup(e){return this.updateTexture(),super.setup(e)}clone(){const e=new this.constructor(this.passNode,this.textureName,this.previousTexture);return e.uvNode=this.uvNode,e.levelNode=this.levelNode,e.biasNode=this.biasNode,e.sampler=this.sampler,e.depthNode=this.depthNode,e.compareNode=this.compareNode,e.gradNode=this.gradNode,e}}class XN extends Cv{static get type(){return"PassNode"}constructor(e,t,n,i={}){super("vec4"),this.scope=e,this.scene=t,this.camera=n,this.options=i,this._pixelRatio=1,this._width=1,this._height=1;const r=new _l;r.isRenderTargetTexture=!0,r.name="depth";const s=new Ks(this._width*this._pixelRatio,this._height*this._pixelRatio,{type:Ki,...i});s.texture.name="output",s.depthTexture=r,this.renderTarget=s,this._textures={output:s.texture,depth:r},this._textureNodes={},this._linearDepthNodes={},this._viewZNodes={},this._previousTextures={},this._previousTextureNodes={},this._cameraNear=Nx(0),this._cameraFar=Nx(0),this._mrt=null,this._layers=null,this._resolution=1,this._viewport=null,this._scissor=null,this.isPassNode=!0,this.updateBeforeType=hv.FRAME,this.global=!0}setResolution(e){return this._resolution=e,this}getResolution(){return this._resolution}setLayers(e){return this._layers=e,this}getLayers(){return this._layers}setMRT(e){return this._mrt=e,this}getMRT(){return this._mrt}getTexture(e){let t=this._textures[e];if(void 0===t){t=this.renderTarget.texture.clone(),t.name=e,this._textures[e]=t,this.renderTarget.textures.push(t)}return t}getPreviousTexture(e){let t=this._previousTextures[e];return void 0===t&&(t=this.getTexture(e).clone(),this._previousTextures[e]=t),t}toggleTexture(e){const t=this._previousTextures[e];if(void 0!==t){const n=this._textures[e],i=this.renderTarget.textures.indexOf(n);this.renderTarget.textures[i]=t,this._textures[e]=t,this._previousTextures[e]=n,this._textureNodes[e].updateTexture(),this._previousTextureNodes[e].updateTexture()}}getTextureNode(e="output"){let t=this._textureNodes[e];return void 0===t&&(t=cA(new UN(this,e)),t.updateTexture(),this._textureNodes[e]=t),t}getPreviousTextureNode(e="output"){let t=this._previousTextureNodes[e];return void 0===t&&(void 0===this._textureNodes[e]&&this.getTextureNode(e),t=cA(new UN(this,e,!0)),t.updateTexture(),this._previousTextureNodes[e]=t),t}getViewZNode(e="depth"){let t=this._viewZNodes[e];if(void 0===t){const n=this._cameraNear,i=this._cameraFar;this._viewZNodes[e]=t=HE(this.getTextureNode(e),n,i)}return t}getLinearDepthNode(e="depth"){let t=this._linearDepthNodes[e];if(void 0===t){const n=this._cameraNear,i=this._cameraFar,r=this.getViewZNode(e);this._linearDepthNodes[e]=t=kE(r,n,i)}return t}async compileAsync(e){const t=e.getRenderTarget(),n=e.getMRT();e.setRenderTarget(this.renderTarget),e.setMRT(this._mrt),await e.compileAsync(this.scene,this.camera),e.setRenderTarget(t),e.setMRT(n)}setup({renderer:e}){return this.renderTarget.samples=void 0===this.options.samples?e.samples:this.options.samples,this.renderTarget.texture.type=e.getColorBufferType(),this.scope===XN.COLOR?this.getTextureNode():this.getLinearDepthNode()}updateBefore(e){const{renderer:t}=e,{scene:n}=this;let i,r;const s=t.getOutputRenderTarget();s&&!0===s.isXRRenderTarget?(r=1,i=t.xr.getCamera(),t.xr.updateCamera(i),FN.set(s.width,s.height)):(i=this.camera,r=t.getPixelRatio(),t.getSize(FN)),this._pixelRatio=r,this.setSize(FN.width,FN.height);const o=t.getRenderTarget(),a=t.getMRT(),l=i.layers.mask;this._cameraNear.value=i.near,this._cameraFar.value=i.far,null!==this._layers&&(i.layers.mask=this._layers.mask);for(const e in this._previousTextures)this.toggleTexture(e);t.setRenderTarget(this.renderTarget),t.setMRT(this._mrt),t.render(n,i),t.setRenderTarget(o),t.setMRT(a),i.layers.mask=l}setSize(e,t){this._width=e,this._height=t;const n=this._width*this._pixelRatio*this._resolution,i=this._height*this._pixelRatio*this._resolution;this.renderTarget.setSize(n,i),null!==this._scissor&&this.renderTarget.scissor.copy(this._scissor),null!==this._viewport&&this.renderTarget.viewport.copy(this._viewport)}setScissor(e,t,n,i){null===e?this._scissor=null:(null===this._scissor&&(this._scissor=new Js),e.isVector4?this._scissor.copy(e):this._scissor.set(e,t,n,i),this._scissor.multiplyScalar(this._pixelRatio*this._resolution).floor())}setViewport(e,t,n,i){null===e?this._viewport=null:(null===this._viewport&&(this._viewport=new Js),e.isVector4?this._viewport.copy(e):this._viewport.set(e,t,n,i),this._viewport.multiplyScalar(this._pixelRatio*this._resolution).floor())}setPixelRatio(e){this._pixelRatio=e,this.setSize(this._width,this._height)}dispose(){this.renderTarget.dispose()}}XN.COLOR="color",XN.DEPTH="depth";const GN=xA((([e,t])=>e.mul(t).clamp())).setLayout({name:"linearToneMapping",type:"vec3",inputs:[{name:"color",type:"vec3"},{name:"exposure",type:"float"}]}),VN=xA((([e,t])=>(e=e.mul(t)).div(e.add(1)).clamp())).setLayout({name:"reinhardToneMapping",type:"vec3",inputs:[{name:"color",type:"vec3"},{name:"exposure",type:"float"}]}),WN=xA((([e,t])=>{const n=(e=(e=e.mul(t)).sub(.004).max(0)).mul(e.mul(6.2).add(.5)),i=e.mul(e.mul(6.2).add(1.7)).add(.06);return n.div(i).pow(2.2)})).setLayout({name:"cineonToneMapping",type:"vec3",inputs:[{name:"color",type:"vec3"},{name:"exposure",type:"float"}]}),QN=xA((([e])=>{const t=e.mul(e.add(.0245786)).sub(90537e-9),n=e.mul(e.add(.432951).mul(.983729)).add(.238081);return t.div(n)})),ZN=xA((([e,t])=>{const n=XA(.59719,.35458,.04823,.076,.90834,.01566,.0284,.13383,.83777),i=XA(1.60475,-.53108,-.07367,-.10208,1.10813,-.00605,-.00327,-.07276,1.07602);return e=e.mul(t).div(.6),e=n.mul(e),e=QN(e),(e=i.mul(e)).clamp()})).setLayout({name:"acesFilmicToneMapping",type:"vec3",inputs:[{name:"color",type:"vec3"},{name:"exposure",type:"float"}]}),YN=XA(LA(1.6605,-.1246,-.0182),LA(-.5876,1.1329,-.1006),LA(-.0728,-.0083,1.1187)),JN=XA(LA(.6274,.0691,.0164),LA(.3293,.9195,.088),LA(.0433,.0113,.8956)),KN=xA((([e])=>{const t=LA(e).toVar(),n=LA(t.mul(t)).toVar(),i=LA(n.mul(n)).toVar();return EA(15.5).mul(i.mul(n)).sub(Hx(40.14,i.mul(t))).add(Hx(31.96,i).sub(Hx(6.868,n.mul(t))).add(Hx(.4298,n).add(Hx(.1191,t).sub(.00232))))})),qN=xA((([e,t])=>{const n=LA(e).toVar(),i=XA(LA(.856627153315983,.137318972929847,.11189821299995),LA(.0951212405381588,.761241990602591,.0767994186031903),LA(.0482516061458583,.101439036467562,.811302368396859)),r=XA(LA(1.1271005818144368,-.1413297634984383,-.14132976349843826),LA(-.11060664309660323,1.157823702216272,-.11060664309660294),LA(-.016493938717834573,-.016493938717834257,1.2519364065950405)),s=EA(-12.47393),o=EA(4.026069);return n.mulAssign(t),n.assign(JN.mul(n)),n.assign(i.mul(n)),n.assign(Jy(n,1e-10)),n.assign(yy(n)),n.assign(n.sub(s).div(o.sub(s))),n.assign(cb(n,0,1)),n.assign(KN(n)),n.assign(r.mul(n)),n.assign(nb(Jy(LA(0),n),LA(2.2))),n.assign(YN.mul(n)),n.assign(cb(n,0,1)),n})).setLayout({name:"agxToneMapping",type:"vec3",inputs:[{name:"color",type:"vec3"},{name:"exposure",type:"float"}]}),_N=xA((([e,t])=>{const n=EA(.76),i=EA(.15);e=e.mul(t);const r=Yy(e.r,Yy(e.g,e.b)),s=bb(r.lessThan(.08),r.sub(Hx(6.25,r.mul(r))),.04);e.subAssign(s);const o=Jy(e.r,Jy(e.g,e.b));wA(o.lessThan(n),(()=>e));const a=Fx(1,n),l=Fx(1,a.mul(a).div(o.add(a.sub(n))));e.mulAssign(l.div(o));const u=Fx(1,Ux(1,i.mul(o.sub(l)).add(1)));return ub(e,LA(l),u)})).setLayout({name:"neutralToneMapping",type:"vec3",inputs:[{name:"color",type:"vec3"},{name:"exposure",type:"float"}]});class $N extends yv{static get type(){return"CodeNode"}constructor(e="",t=[],n=""){super("code"),this.isCodeNode=!0,this.global=!0,this.code=e,this.includes=t,this.language=n}setIncludes(e){return this.includes=e,this}getIncludes(){return this.includes}generate(e){const t=this.getIncludes(e);for(const n of t)n.build(e);const n=e.getCodeFromNode(this,this.getNodeType(e));return n.code=this.code,n.code}serialize(e){super.serialize(e),e.code=this.code,e.language=this.language}deserialize(e){super.deserialize(e),this.code=e.code,this.language=e.language}}class eB extends $N{static get type(){return"FunctionNode"}constructor(e="",t=[],n=""){super(e,t,n)}getNodeType(e){return this.getNodeFunction(e).type}getMemberType(e,t){const n=this.getNodeType(e);return e.getStructTypeNode(n).getMemberType(e,t)}getInputs(e){return this.getNodeFunction(e).inputs}getNodeFunction(e){const t=e.getDataFromNode(this);let n=t.nodeFunction;return void 0===n&&(n=e.parser.parseFunction(this.code),t.nodeFunction=n),n}generate(e,t){super.generate(e);const n=this.getNodeFunction(e),i=n.name,r=n.type,s=e.getCodeFromNode(this,r);""!==i&&(s.name=i);const o=e.getPropertyName(s),a=this.getNodeFunction(e).getCode(o);return s.code=a+"\n","property"===t?o:e.format(`${o}()`,r,t)}}class tB extends Map{get(e,t=null,...n){if(this.has(e))return super.get(e);if(null!==t){const i=t(...n);return this.set(e,i),i}}}new tB;function nB(e){let t;const n=e.context.getViewZ;return void 0!==n&&(t=n(this)),(t||hC.z).negate()}const iB=xA((([e,t],n)=>{const i=nB(n);return fb(e,t,i)})),rB=xA((([e],t)=>{const n=nB(t);return e.mul(e,n,n).negate().exp().oneMinus()})),sB=xA((([e,t])=>RA(t.toFloat().mix(fx.rgb,e.toVec3()),fx.a)));pA(class extends yv{constructor(e){super(),this.scope=e}generate(e){const{scope:t}=this,{renderer:n}=e;!0===n.backend.isWebGLBackend?e.addFlowCode(`\t// ${t}Barrier \n`):e.addLineFlowCode(`${t}Barrier()`,this)}});class oB extends yv{static get type(){return"AtomicFunctionNode"}constructor(e,t,n){super("uint"),this.method=e,this.pointerNode=t,this.valueNode=n,this.parents=!0}getInputType(e){return this.pointerNode.getNodeType(e)}getNodeType(e){return this.getInputType(e)}generate(e){const t=e.getNodeProperties(this),n=t.parents,i=this.method,r=this.getNodeType(e),s=this.getInputType(e),o=this.pointerNode,a=this.valueNode,l=[];l.push(`&${o.build(e,s)}`),null!==a&&l.push(a.build(e,s));const u=`${e.getMethod(i,r)}( ${l.join(", ")} )`;if(!(!!n&&(1===n.length&&!0===n[0].isStackNode)))return void 0===t.constNode&&(t.constNode=hw(u,r).toConst()),t.constNode.build(e);e.addLineFlowCode(u,this)}}oB.ATOMIC_LOAD="atomicLoad",oB.ATOMIC_STORE="atomicStore",oB.ATOMIC_ADD="atomicAdd",oB.ATOMIC_SUB="atomicSub",oB.ATOMIC_MAX="atomicMax",oB.ATOMIC_MIN="atomicMin",oB.ATOMIC_AND="atomicAnd",oB.ATOMIC_OR="atomicOr",oB.ATOMIC_XOR="atomicXor";pA(oB);class aB extends Cv{static get type(){return"SubgroupFunctionNode"}constructor(e,t=null,n=null){super(),this.method=e,this.aNode=t,this.bNode=n}getInputType(e){const t=this.aNode?this.aNode.getNodeType(e):null,n=this.bNode?this.bNode.getNodeType(e):null;return(e.isMatrix(t)?0:e.getTypeLength(t))>(e.isMatrix(n)?0:e.getTypeLength(n))?t:n}getNodeType(e){const t=this.method;return t===aB.SUBGROUP_ELECT?"bool":t===aB.SUBGROUP_BALLOT?"uvec4":this.getInputType(e)}generate(e,t){const n=this.method,i=this.getNodeType(e),r=this.getInputType(e),s=this.aNode,o=this.bNode,a=[];if(n===aB.SUBGROUP_BROADCAST||n===aB.SUBGROUP_SHUFFLE||n===aB.QUAD_BROADCAST){const t=o.getNodeType(e);a.push(s.build(e,i),o.build(e,"float"===t?"int":i))}else n===aB.SUBGROUP_SHUFFLE_XOR||n===aB.SUBGROUP_SHUFFLE_DOWN||n===aB.SUBGROUP_SHUFFLE_UP?a.push(s.build(e,i),o.build(e,"uint")):(null!==s&&a.push(s.build(e,r)),null!==o&&a.push(o.build(e,r)));const l=0===a.length?"()":`( ${a.join(", ")} )`;return e.format(`${e.getMethod(n,i)}${l}`,i,t)}serialize(e){super.serialize(e),e.method=this.method}deserialize(e){super.deserialize(e),this.method=e.method}}aB.SUBGROUP_ELECT="subgroupElect",aB.SUBGROUP_BALLOT="subgroupBallot",aB.SUBGROUP_ADD="subgroupAdd",aB.SUBGROUP_INCLUSIVE_ADD="subgroupInclusiveAdd",aB.SUBGROUP_EXCLUSIVE_AND="subgroupExclusiveAdd",aB.SUBGROUP_MUL="subgroupMul",aB.SUBGROUP_INCLUSIVE_MUL="subgroupInclusiveMul",aB.SUBGROUP_EXCLUSIVE_MUL="subgroupExclusiveMul",aB.SUBGROUP_AND="subgroupAnd",aB.SUBGROUP_OR="subgroupOr",aB.SUBGROUP_XOR="subgroupXor",aB.SUBGROUP_MIN="subgroupMin",aB.SUBGROUP_MAX="subgroupMax",aB.SUBGROUP_ALL="subgroupAll",aB.SUBGROUP_ANY="subgroupAny",aB.SUBGROUP_BROADCAST_FIRST="subgroupBroadcastFirst",aB.QUAD_SWAP_X="quadSwapX",aB.QUAD_SWAP_Y="quadSwapY",aB.QUAD_SWAP_DIAGONAL="quadSwapDiagonal",aB.SUBGROUP_BROADCAST="subgroupBroadcast",aB.SUBGROUP_SHUFFLE="subgroupShuffle",aB.SUBGROUP_SHUFFLE_XOR="subgroupShuffleXor",aB.SUBGROUP_SHUFFLE_UP="subgroupShuffleUp",aB.SUBGROUP_SHUFFLE_DOWN="subgroupShuffleDown",aB.QUAD_BROADCAST="quadBroadcast";let lB;function uB(e){lB=lB||new WeakMap;let t=lB.get(e);return void 0===t&&lB.set(e,t={}),t}function cB(e){const t=uB(e);return t.shadowMatrix||(t.shadowMatrix=Nx("mat4").setGroup(Tx).onRenderUpdate((t=>(!0===e.castShadow&&!1!==t.renderer.shadowMap.enabled||e.shadow.updateMatrices(e),e.shadow.matrix))))}function dB(e,t=cC){const n=cB(e).mul(t);return n.xyz.div(n.w)}function hB(e){const t=uB(e);return t.position||(t.position=Nx(new Es).setGroup(Tx).onRenderUpdate(((t,n)=>n.value.setFromMatrixPosition(e.matrixWorld))))}function fB(e){const t=uB(e);return t.targetPosition||(t.targetPosition=Nx(new Es).setGroup(Tx).onRenderUpdate(((t,n)=>n.value.setFromMatrixPosition(e.target.matrixWorld))))}function pB(e){const t=uB(e);return t.viewPosition||(t.viewPosition=Nx(new Es).setGroup(Tx).onRenderUpdate((({camera:t},n)=>{n.value=n.value||new Es,n.value.setFromMatrixPosition(e.matrixWorld),n.value.applyMatrix4(t.matrixWorldInverse)})))}const gB=e=>Jw.transformDirection(hB(e).sub(fB(e))),mB=(e,t)=>{for(const n of t)if(n.isAnalyticLightNode&&n.light.id===e)return n;return null},vB=new WeakMap,AB=[];class xB extends yv{static get type(){return"LightsNode"}constructor(){super("vec3"),this.totalDiffuseNode=ZA("vec3","totalDiffuse"),this.totalSpecularNode=ZA("vec3","totalSpecular"),this.outgoingLightNode=ZA("vec3","outgoingLight"),this._lights=[],this._lightNodes=null,this._lightNodesHash=null,this.global=!0}customCacheKey(){const e=this._lights;for(let t=0;t<e.length;t++){const n=e[t];if(AB.push(n.id),AB.push(n.castShadow?1:0),!0===n.isSpotLight){const e=null!==n.map?n.map.id:-1,t=n.colorNode?n.colorNode.getCacheKey():-1;AB.push(e,t)}}const t=$m(AB);return AB.length=0,t}getHash(e){if(null===this._lightNodesHash){null===this._lightNodes&&this.setupLightsNode(e);const t=[];for(const e of this._lightNodes)t.push(e.getHash());this._lightNodesHash="lights-"+t.join(",")}return this._lightNodesHash}analyze(e){const t=e.getNodeProperties(this);for(const n of t.nodes)n.build(e);t.outputNode.build(e)}setupLightsNode(e){const t=[],n=this._lightNodes,i=(e=>e.sort(((e,t)=>e.id-t.id)))(this._lights),r=e.renderer.library;for(const e of i)if(e.isNode)t.push(cA(e));else{let i=null;if(null!==n&&(i=mB(e.id,n)),null===i){const n=r.getLightNodeClass(e.constructor);if(null===n){console.warn(`LightsNode.setupNodeLights: Light node not found for ${e.constructor.name}`);continue}let i=null;vB.has(e)?i=vB.get(e):(i=cA(new n(e)),vB.set(e,i)),t.push(i)}}this._lightNodes=t}setupDirectLight(e,t,n){const{lightingModel:i,reflectedLight:r}=e.context;i.direct({...n,lightNode:t,reflectedLight:r},e)}setupDirectRectAreaLight(e,t,n){const{lightingModel:i,reflectedLight:r}=e.context;i.directRectArea({...n,lightNode:t,reflectedLight:r},e)}setupLights(e,t){for(const n of t)n.build(e)}getLightNodes(e){return null===this._lightNodes&&this.setupLightsNode(e),this._lightNodes}setup(e){const t=e.lightsNode;e.lightsNode=this;let n=this.outgoingLightNode;const i=e.context,r=i.lightingModel,s=e.getNodeProperties(this);if(r){const{totalDiffuseNode:t,totalSpecularNode:o}=this;i.outgoingLight=n;const a=e.addStack();s.nodes=a.nodes,r.start(e);const{backdrop:l,backdropAlpha:u}=i,{directDiffuse:c,directSpecular:d,indirectDiffuse:h,indirectSpecular:f}=i.reflectedLight;let p=c.add(h);null!==l&&(p=LA(null!==u?u.mix(p,l):l),i.material.transparent=!0),t.assign(p),o.assign(d.add(f)),n.assign(t.add(o)),r.finish(e),n=n.bypass(e.removeStack())}else s.nodes=[];return e.lightsNode=t,n}setLights(e){return this._lights=e,this._lightNodes=null,this._lightNodesHash=null,this}getLights(){return this._lights}get hasLights(){return this._lights.length>0}}class yB extends yv{static get type(){return"ShadowBaseNode"}constructor(e){super(),this.light=e,this.updateBeforeType=hv.RENDER,this.isShadowBaseNode=!0}setupShadowPosition({context:e,material:t}){bB.assign(t.receivedShadowPositionNode||e.shadowPositionWorld||cC)}}const bB=ZA("vec3","shadowPositionWorld");function wB(e,t={}){return t.toneMapping=e.toneMapping,t.toneMappingExposure=e.toneMappingExposure,t.outputColorSpace=e.outputColorSpace,t.renderTarget=e.getRenderTarget(),t.activeCubeFace=e.getActiveCubeFace(),t.activeMipmapLevel=e.getActiveMipmapLevel(),t.renderObjectFunction=e.getRenderObjectFunction(),t.pixelRatio=e.getPixelRatio(),t.mrt=e.getMRT(),t.clearColor=e.getClearColor(t.clearColor||new ya),t.clearAlpha=e.getClearAlpha(),t.autoClear=e.autoClear,t.scissorTest=e.getScissorTest(),t}function CB(e,t){return t=wB(e,t),e.setMRT(null),e.setRenderObjectFunction(null),e.setClearColor(0,1),e.autoClear=!0,t}function MB(e,t){e.toneMapping=t.toneMapping,e.toneMappingExposure=t.toneMappingExposure,e.outputColorSpace=t.outputColorSpace,e.setRenderTarget(t.renderTarget,t.activeCubeFace,t.activeMipmapLevel),e.setRenderObjectFunction(t.renderObjectFunction),e.setPixelRatio(t.pixelRatio),e.setMRT(t.mrt),e.setClearColor(t.clearColor,t.clearAlpha),e.autoClear=t.autoClear,e.setScissorTest(t.scissorTest)}function EB(e,t={}){return t.background=e.background,t.backgroundNode=e.backgroundNode,t.overrideMaterial=e.overrideMaterial,t}function TB(e,t){return t=EB(e,t),e.background=null,e.backgroundNode=null,e.overrideMaterial=null,t}function SB(e,t){e.background=t.background,e.backgroundNode=t.backgroundNode,e.overrideMaterial=t.overrideMaterial}function PB(e,t,n){return n=TB(t,n=CB(e,n))}function NB(e,t,n){MB(e,n),SB(t,n)}const BB=new WeakMap,DB=xA((({depthTexture:e,shadowCoord:t,depthLayer:n})=>{let i=Pw(e,t.xy).setName("t_basic");return e.isArrayTexture&&(i=i.depth(n)),i.compare(t.z)})),IB=xA((({depthTexture:e,shadowCoord:t,shadow:n,depthLayer:i})=>{const r=(t,n)=>{let r=Pw(e,t);return e.isArrayTexture&&(r=r.depth(i)),r.compare(n)},s=GC("mapSize","vec2",n).setGroup(Tx),o=GC("radius","float",n).setGroup(Tx),a=NA(1).div(s),l=a.x.negate().mul(o),u=a.y.negate().mul(o),c=a.x.mul(o),d=a.y.mul(o),h=l.div(2),f=u.div(2),p=c.div(2),g=d.div(2);return kx(r(t.xy.add(NA(l,u)),t.z),r(t.xy.add(NA(0,u)),t.z),r(t.xy.add(NA(c,u)),t.z),r(t.xy.add(NA(h,f)),t.z),r(t.xy.add(NA(0,f)),t.z),r(t.xy.add(NA(p,f)),t.z),r(t.xy.add(NA(l,0)),t.z),r(t.xy.add(NA(h,0)),t.z),r(t.xy,t.z),r(t.xy.add(NA(p,0)),t.z),r(t.xy.add(NA(c,0)),t.z),r(t.xy.add(NA(h,g)),t.z),r(t.xy.add(NA(0,g)),t.z),r(t.xy.add(NA(p,g)),t.z),r(t.xy.add(NA(l,d)),t.z),r(t.xy.add(NA(0,d)),t.z),r(t.xy.add(NA(c,d)),t.z)).mul(1/17)})),LB=xA((({depthTexture:e,shadowCoord:t,shadow:n,depthLayer:i})=>{const r=(t,n)=>{let r=Pw(e,t);return e.isArrayTexture&&(r=r.depth(i)),r.compare(n)},s=GC("mapSize","vec2",n).setGroup(Tx),o=NA(1).div(s),a=o.x,l=o.y,u=t.xy,c=Ty(u.mul(s).add(.5));return u.subAssign(c.mul(o)),kx(r(u,t.z),r(u.add(NA(a,0)),t.z),r(u.add(NA(0,l)),t.z),r(u.add(o),t.z),ub(r(u.add(NA(a.negate(),0)),t.z),r(u.add(NA(a.mul(2),0)),t.z),c.x),ub(r(u.add(NA(a.negate(),l)),t.z),r(u.add(NA(a.mul(2),l)),t.z),c.x),ub(r(u.add(NA(0,l.negate())),t.z),r(u.add(NA(0,l.mul(2))),t.z),c.y),ub(r(u.add(NA(a,l.negate())),t.z),r(u.add(NA(a,l.mul(2))),t.z),c.y),ub(ub(r(u.add(NA(a.negate(),l.negate())),t.z),r(u.add(NA(a.mul(2),l.negate())),t.z),c.x),ub(r(u.add(NA(a.negate(),l.mul(2))),t.z),r(u.add(NA(a.mul(2),l.mul(2))),t.z),c.x),c.y)).mul(1/9)})),jB=xA((({depthTexture:e,shadowCoord:t,depthLayer:n})=>{const i=EA(1).toVar();let r=Pw(e).sample(t.xy);e.isArrayTexture&&(r=r.depth(n)),r=r.rg;const s=Ky(t.z,r.x);return wA(s.notEqual(EA(1)),(()=>{const e=t.z.sub(r.x),n=Jy(0,r.y.mul(r.y));let o=n.div(n.add(e.mul(e)));o=cb(Fx(o,.3).div(.95-.3)),i.assign(cb(Jy(s,o)))})),i})),OB=xA((([e,t,n])=>{let i=cC.sub(e).length();return i=i.sub(t).div(n.sub(t)),i=i.saturate(),i})),zB=e=>{let t=BB.get(e);if(void 0===t){const n=e.isPointLight?(e=>{const t=e.shadow.camera,n=GC("near","float",t).setGroup(Tx),i=GC("far","float",t).setGroup(Tx),r=$w(e);return OB(r,n,i)})(e):null;t=new _E,t.colorNode=RA(0,0,0,1),t.depthNode=n,t.isShadowPassMaterial=!0,t.name="ShadowMaterial",t.fog=!1,BB.set(e,t)}return t},RB=new zP,kB=[],FB=(e,t,n,i)=>{kB[0]=e,kB[1]=t;let r=RB.get(kB);return void 0!==r&&r.shadowType===n&&r.useVelocity===i||(r=(r,s,o,a,l,u,...c)=>{(!0===r.castShadow||r.receiveShadow&&3===n)&&(i&&(lv(r).useVelocity=!0),r.onBeforeShadow(e,r,o,t.camera,a,s.overrideMaterial,u),e.renderObject(r,s,o,a,l,u,...c),r.onAfterShadow(e,r,o,t.camera,a,s.overrideMaterial,u))},r.shadowType=n,r.useVelocity=i,RB.set(kB,r)),kB[0]=null,kB[1]=null,r},HB=xA((({samples:e,radius:t,size:n,shadowPass:i,depthLayer:r})=>{const s=EA(0).toVar("meanVertical"),o=EA(0).toVar("squareMeanVertical"),a=e.lessThanEqual(EA(1)).select(EA(0),EA(2).div(e.sub(1))),l=e.lessThanEqual(EA(1)).select(EA(0),EA(-1));xE({start:TA(0),end:TA(e),type:"int",condition:"<"},(({i:e})=>{const u=l.add(EA(e).mul(a));let c=i.sample(kx(Xw.xy,NA(0,u).mul(t)).div(n));i.value.isArrayTexture&&(c=c.depth(r)),c=c.x,s.addAssign(c),o.addAssign(c.mul(c))})),s.divAssign(e),o.divAssign(e);const u=by(o.sub(s.mul(s)));return NA(s,u)})),UB=xA((({samples:e,radius:t,size:n,shadowPass:i,depthLayer:r})=>{const s=EA(0).toVar("meanHorizontal"),o=EA(0).toVar("squareMeanHorizontal"),a=e.lessThanEqual(EA(1)).select(EA(0),EA(2).div(e.sub(1))),l=e.lessThanEqual(EA(1)).select(EA(0),EA(-1));xE({start:TA(0),end:TA(e),type:"int",condition:"<"},(({i:e})=>{const u=l.add(EA(e).mul(a));let c=i.sample(kx(Xw.xy,NA(u,0).mul(t)).div(n));i.value.isArrayTexture&&(c=c.depth(r)),s.addAssign(c.x),o.addAssign(kx(c.y.mul(c.y),c.x.mul(c.x)))})),s.divAssign(e),o.divAssign(e);const u=by(o.sub(s.mul(s)));return NA(s,u)})),XB=[DB,IB,LB,jB];let GB;const VB=new PN;class WB extends yB{static get type(){return"ShadowNode"}constructor(e,t=null){super(e),this.shadow=t||e.shadow,this.shadowMap=null,this.vsmShadowMapVertical=null,this.vsmShadowMapHorizontal=null,this.vsmMaterialVertical=null,this.vsmMaterialHorizontal=null,this._node=null,this._cameraFrameId=new WeakMap,this.isShadowNode=!0,this.depthLayer=0}setupShadowFilter(e,{filterFn:t,depthTexture:n,shadowCoord:i,shadow:r,depthLayer:s}){const o=i.x.greaterThanEqual(0).and(i.x.lessThanEqual(1)).and(i.y.greaterThanEqual(0)).and(i.y.lessThanEqual(1)).and(i.z.lessThanEqual(1)),a=t({depthTexture:n,shadowCoord:i,shadow:r,depthLayer:s});return o.select(a,EA(1))}setupShadowCoord(e,t){const{shadow:n}=this,{renderer:i}=e,r=GC("bias","float",n).setGroup(Tx);let s,o=t;if(n.camera.isOrthographicCamera||!0!==i.logarithmicDepthBuffer)o=o.xyz.div(o.w),s=o.z,i.coordinateSystem===ls&&(s=s.mul(2).sub(1));else{const e=o.w;o=o.xy.div(e);const t=GC("near","float",n.camera).setGroup(Tx),i=GC("far","float",n.camera).setGroup(Tx);s=UE(e.negate(),t,i)}return o=LA(o.x,o.y.oneMinus(),s.add(r)),o}getShadowFilterFn(e){return XB[e]}setupRenderTarget(e,t){const n=new _l(e.mapSize.width,e.mapSize.height);n.name="ShadowDepthTexture",n.compareFunction=ns;const i=t.createRenderTarget(e.mapSize.width,e.mapSize.height);return i.texture.name="ShadowMap",i.texture.type=e.mapType,i.depthTexture=n,{shadowMap:i,depthTexture:n}}setupShadow(e){const{renderer:t}=e,{light:n,shadow:i}=this,r=t.shadowMap.type,{depthTexture:s,shadowMap:o}=this.setupRenderTarget(i,e);if(i.camera.updateProjectionMatrix(),3===r&&!0!==i.isPointLightShadow){s.compareFunction=null,o.depth>1?(o._vsmShadowMapVertical||(o._vsmShadowMapVertical=e.createRenderTarget(i.mapSize.width,i.mapSize.height,{format:ur,type:Ki,depth:o.depth,depthBuffer:!1}),o._vsmShadowMapVertical.texture.name="VSMVertical"),this.vsmShadowMapVertical=o._vsmShadowMapVertical,o._vsmShadowMapHorizontal||(o._vsmShadowMapHorizontal=e.createRenderTarget(i.mapSize.width,i.mapSize.height,{format:ur,type:Ki,depth:o.depth,depthBuffer:!1}),o._vsmShadowMapHorizontal.texture.name="VSMHorizontal"),this.vsmShadowMapHorizontal=o._vsmShadowMapHorizontal):(this.vsmShadowMapVertical=e.createRenderTarget(i.mapSize.width,i.mapSize.height,{format:ur,type:Ki,depthBuffer:!1}),this.vsmShadowMapHorizontal=e.createRenderTarget(i.mapSize.width,i.mapSize.height,{format:ur,type:Ki,depthBuffer:!1}));let t=Pw(s);s.isArrayTexture&&(t=t.depth(this.depthLayer));let n=Pw(this.vsmShadowMapVertical.texture);s.isArrayTexture&&(n=n.depth(this.depthLayer));const r=GC("blurSamples","float",i).setGroup(Tx),a=GC("radius","float",i).setGroup(Tx),l=GC("mapSize","vec2",i).setGroup(Tx);let u=this.vsmMaterialVertical||(this.vsmMaterialVertical=new _E);u.fragmentNode=HB({samples:r,radius:a,size:l,shadowPass:t,depthLayer:this.depthLayer}).context(e.getSharedContext()),u.name="VSMVertical",u=this.vsmMaterialHorizontal||(this.vsmMaterialHorizontal=new _E),u.fragmentNode=UB({samples:r,radius:a,size:l,shadowPass:n,depthLayer:this.depthLayer}).context(e.getSharedContext()),u.name="VSMHorizontal"}const a=GC("intensity","float",i).setGroup(Tx),l=GC("normalBias","float",i).setGroup(Tx),u=cB(n).mul(bB.add(MC.mul(l))),c=this.setupShadowCoord(e,u),d=i.filterNode||this.getShadowFilterFn(t.shadowMap.type)||null;if(null===d)throw new Error("THREE.WebGPURenderer: Shadow map type not supported yet.");const h=3===r&&!0!==i.isPointLightShadow?this.vsmShadowMapHorizontal.texture:s,f=this.setupShadowFilter(e,{filterFn:d,shadowTexture:o.texture,depthTexture:h,shadowCoord:c,shadow:i,depthLayer:this.depthLayer});let p=Pw(o.texture,c);s.isArrayTexture&&(p=p.depth(this.depthLayer));const g=ub(1,f.rgb.mix(p,1),a.mul(p.a)).toVar();return this.shadowMap=o,this.shadow.map=o,g}setup(e){if(!1!==e.renderer.shadowMap.enabled)return xA((()=>{let t=this._node;return this.setupShadowPosition(e),null===t&&(this._node=t=this.setupShadow(e)),e.material.shadowNode&&console.warn('THREE.NodeMaterial: ".shadowNode" is deprecated. Use ".castShadowNode" instead.'),e.material.receivedShadowNode&&(t=e.material.receivedShadowNode(t)),t}))()}renderShadow(e){const{shadow:t,shadowMap:n,light:i}=this,{renderer:r,scene:s}=e;t.updateMatrices(i),n.setSize(t.mapSize.width,t.mapSize.height,n.depth),r.render(s,t.camera)}updateShadow(e){const{shadowMap:t,light:n,shadow:i}=this,{renderer:r,scene:s,camera:o}=e,a=r.shadowMap.type,l=t.depthTexture.version;this._depthVersionCached=l;const u=i.camera.layers.mask;0==(4294967294&i.camera.layers.mask)&&(i.camera.layers.mask=o.layers.mask);const c=r.getRenderObjectFunction(),d=r.getMRT(),h=!!d&&d.has("velocity");GB=PB(r,s,GB),s.overrideMaterial=zB(n),r.setRenderObjectFunction(FB(r,i,a,h)),r.setClearColor(0,0),r.setRenderTarget(t),this.renderShadow(e),r.setRenderObjectFunction(c),3===a&&!0!==i.isPointLightShadow&&this.vsmPass(r),i.camera.layers.mask=u,NB(r,s,GB)}vsmPass(e){const{shadow:t}=this,n=this.shadowMap.depth;this.vsmShadowMapVertical.setSize(t.mapSize.width,t.mapSize.height,n),this.vsmShadowMapHorizontal.setSize(t.mapSize.width,t.mapSize.height,n),e.setRenderTarget(this.vsmShadowMapVertical),VB.material=this.vsmMaterialVertical,VB.render(e),e.setRenderTarget(this.vsmShadowMapHorizontal),VB.material=this.vsmMaterialHorizontal,VB.render(e)}dispose(){this.shadowMap.dispose(),this.shadowMap=null,null!==this.vsmShadowMapVertical&&(this.vsmShadowMapVertical.dispose(),this.vsmShadowMapVertical=null,this.vsmMaterialVertical.dispose(),this.vsmMaterialVertical=null),null!==this.vsmShadowMapHorizontal&&(this.vsmShadowMapHorizontal.dispose(),this.vsmShadowMapHorizontal=null,this.vsmMaterialHorizontal.dispose(),this.vsmMaterialHorizontal=null),super.dispose()}updateBefore(e){const{shadow:t}=this;let n=t.needsUpdate||t.autoUpdate;n&&(this._cameraFrameId[e.camera]===e.frameId&&(n=!1),this._cameraFrameId[e.camera]=e.frameId),n&&(this.updateShadow(e),this.shadowMap.depthTexture.version===this._depthVersionCached&&(t.needsUpdate=!1))}}const QB=(e,t)=>cA(new WB(e,t)),ZB=new ya,YB=xA((([e,t])=>{const n=e.toVar(),i=Ly(n),r=Ux(1,Jy(i.x,Jy(i.y,i.z)));i.mulAssign(r),n.mulAssign(r.mul(t.mul(2).oneMinus()));const s=NA(n.xy).toVar(),o=t.mul(1.5).oneMinus();return wA(i.z.greaterThanEqual(o),(()=>{wA(n.z.greaterThan(0),(()=>{s.x.assign(Fx(4,n.x))}))})).ElseIf(i.x.greaterThanEqual(o),(()=>{const e=jy(n.x);s.x.assign(n.z.mul(e).add(e.mul(2)))})).ElseIf(i.y.greaterThanEqual(o),(()=>{const e=jy(n.y);s.x.assign(n.x.add(e.mul(2)).add(2)),s.y.assign(n.z.mul(e).sub(2))})),NA(.125,.25).mul(s).add(NA(.375,.75)).flipY()})).setLayout({name:"cubeToUV",type:"vec2",inputs:[{name:"pos",type:"vec3"},{name:"texelSizeY",type:"float"}]}),JB=xA((({depthTexture:e,bd3D:t,dp:n,texelSize:i})=>Pw(e,YB(t,i.y)).compare(n))),KB=xA((({depthTexture:e,bd3D:t,dp:n,texelSize:i,shadow:r})=>{const s=GC("radius","float",r).setGroup(Tx),o=NA(-1,1).mul(s).mul(i.y);return Pw(e,YB(t.add(o.xyy),i.y)).compare(n).add(Pw(e,YB(t.add(o.yyy),i.y)).compare(n)).add(Pw(e,YB(t.add(o.xyx),i.y)).compare(n)).add(Pw(e,YB(t.add(o.yyx),i.y)).compare(n)).add(Pw(e,YB(t,i.y)).compare(n)).add(Pw(e,YB(t.add(o.xxy),i.y)).compare(n)).add(Pw(e,YB(t.add(o.yxy),i.y)).compare(n)).add(Pw(e,YB(t.add(o.xxx),i.y)).compare(n)).add(Pw(e,YB(t.add(o.yxx),i.y)).compare(n)).mul(1/9)})),qB=xA((({filterFn:e,depthTexture:t,shadowCoord:n,shadow:i})=>{const r=n.xyz.toVar(),s=r.length(),o=Nx("float").setGroup(Tx).onRenderUpdate((()=>i.camera.near)),a=Nx("float").setGroup(Tx).onRenderUpdate((()=>i.camera.far)),l=GC("bias","float",i).setGroup(Tx),u=Nx(i.mapSize).setGroup(Tx),c=EA(1).toVar();return wA(s.sub(a).lessThanEqual(0).and(s.sub(o).greaterThanEqual(0)),(()=>{const n=s.sub(o).div(a.sub(o)).toVar();n.addAssign(l);const d=r.normalize(),h=NA(1).div(u.mul(NA(4,2)));c.assign(e({depthTexture:t,bd3D:d,dp:n,texelSize:h,shadow:i}))})),c})),_B=new Js,$B=new Cs,eD=new Cs;class tD extends WB{static get type(){return"PointShadowNode"}constructor(e,t=null){super(e,t)}getShadowFilterFn(e){return 0===e?JB:KB}setupShadowCoord(e,t){return t}setupShadowFilter(e,{filterFn:t,shadowTexture:n,depthTexture:i,shadowCoord:r,shadow:s}){return qB({filterFn:t,shadowTexture:n,depthTexture:i,shadowCoord:r,shadow:s})}renderShadow(e){const{shadow:t,shadowMap:n,light:i}=this,{renderer:r,scene:s}=e,o=t.getFrameExtents();eD.copy(t.mapSize),eD.multiply(o),n.setSize(eD.width,eD.height),$B.copy(t.mapSize);const a=r.autoClear,l=r.getClearColor(ZB),u=r.getClearAlpha();r.autoClear=!1,r.setClearColor(t.clearColor,t.clearAlpha),r.clear();const c=t.getViewportCount();for(let e=0;e<c;e++){const o=t.getViewport(e),a=$B.x*o.x,l=eD.y-$B.y-$B.y*o.y;_B.set(a,l,$B.x*o.z,$B.y*o.w),n.viewport.copy(_B),t.updateMatrices(i,e),r.render(s,t.camera)}r.autoClear=a,r.setClearColor(l,u)}}const nD=(e,t)=>cA(new tD(e,t));class iD extends TE{static get type(){return"AnalyticLightNode"}constructor(e=null){super(),this.light=e,this.color=new ya,this.colorNode=e&&e.colorNode||Nx(this.color).setGroup(Tx),this.baseColorNode=null,this.shadowNode=null,this.shadowColorNode=null,this.isAnalyticLightNode=!0,this.updateType=hv.FRAME}getHash(){return this.light.uuid}getLightVector(e){return pB(this.light).sub(e.context.positionView||hC)}setupDirect(){}setupDirectRectArea(){}setupShadowNode(){return QB(this.light)}setupShadow(e){const{renderer:t}=e;if(!1===t.shadowMap.enabled)return;let n=this.shadowColorNode;if(null===n){const e=this.light.shadow.shadowNode;let t;t=void 0!==e?cA(e):this.setupShadowNode(),this.shadowNode=t,this.shadowColorNode=n=this.colorNode.mul(t),this.baseColorNode=this.colorNode}this.colorNode=n}setup(e){this.colorNode=this.baseColorNode||this.colorNode,this.light.castShadow?e.object.receiveShadow&&this.setupShadow(e):null!==this.shadowNode&&(this.shadowNode.dispose(),this.shadowNode=null,this.shadowColorNode=null);const t=this.setupDirect(e),n=this.setupDirectRectArea(e);t&&e.lightsNode.setupDirectLight(e,this,t),n&&e.lightsNode.setupDirectRectAreaLight(e,this,n)}update(){const{light:e}=this;this.color.copy(e.color).multiplyScalar(e.intensity)}}const rD=xA((({lightDistance:e,cutoffDistance:t,decayExponent:n})=>{const i=e.pow(n).max(.01).reciprocal();return t.greaterThan(0).select(i.mul(e.div(t).pow4().oneMinus().clamp().pow2()),i)})),sD=({color:e,lightVector:t,cutoffDistance:n,decayExponent:i})=>{const r=t.normalize(),s=t.length(),o=rD({lightDistance:s,cutoffDistance:n,decayExponent:i});return{lightDirection:r,lightColor:e.mul(o)}};class oD extends iD{static get type(){return"PointLightNode"}constructor(e=null){super(e),this.cutoffDistanceNode=Nx(0).setGroup(Tx),this.decayExponentNode=Nx(2).setGroup(Tx)}update(e){const{light:t}=this;super.update(e),this.cutoffDistanceNode.value=t.distance,this.decayExponentNode.value=t.decay}setupShadowNode(){return nD(this.light)}setupDirect(e){return sD({color:this.colorNode,lightVector:this.getLightVector(e),cutoffDistance:this.cutoffDistanceNode,decayExponent:this.decayExponentNode})}}xA((([e=yw()],{renderer:t,material:n})=>{const i=lb(e.mul(2).sub(1));let r;if(n.alphaToCoverage&&t.samples>1){const e=EA(i.fwidth()).toVar();r=fb(e.oneMinus(),e.add(1),i).oneMinus()}else r=bb(i.greaterThan(1),0,1);return r}));const aD=xA((([e,t])=>{const n=e.x,i=e.y,r=e.z;let s=t.element(0).mul(.886227);return s=s.add(t.element(1).mul(1.023328).mul(i)),s=s.add(t.element(2).mul(1.023328).mul(r)),s=s.add(t.element(3).mul(1.023328).mul(n)),s=s.add(t.element(4).mul(.858086).mul(n).mul(i)),s=s.add(t.element(5).mul(.858086).mul(i).mul(r)),s=s.add(t.element(6).mul(r.mul(r).mul(.743125).sub(.247708))),s=s.add(t.element(7).mul(.858086).mul(n).mul(r)),s=s.add(t.element(8).mul(.429043).mul(Hx(n,n).sub(Hx(i,i)))),s}));const lD=new yN;class uD extends UP{constructor(e,t){super(),this.renderer=e,this.nodes=t}update(e,t,n){const i=this.renderer,r=this.nodes.getBackgroundNode(e)||e.background;let s=!1;if(null===r)i._clearColor.getRGB(lD),lD.a=i._clearColor.a;else if(!0===r.isColor)r.getRGB(lD),lD.a=1,s=!0;else if(!0===r.isNode){const a=this.get(e),l=r;lD.copy(i._clearColor);let u=a.backgroundMesh;if(void 0===u){const d=Cb(RA(l).mul(jN),{getUV:()=>ON.mul(wC),getTextureLevel:()=>LN});let h=sE;h=h.setZ(h.w);const f=new _E;function p(){r.removeEventListener("dispose",p),u.material.dispose(),u.geometry.dispose()}f.name="Background.material",f.side=1,f.depthTest=!1,f.depthWrite=!1,f.allowOverride=!1,f.fog=!1,f.lights=!1,f.vertexNode=h,f.colorNode=d,a.backgroundMeshNode=d,a.backgroundMesh=u=new nl(new yu(1,32,32),f),u.frustumCulled=!1,u.name="Background.mesh",u.onBeforeRender=function(e,t,n){this.matrixWorld.copyPosition(n.matrixWorld)},r.addEventListener("dispose",p)}const c=l.getCacheKey();a.backgroundCacheKey!==c&&(a.backgroundMeshNode.node=RA(l).mul(jN),a.backgroundMeshNode.needsUpdate=!0,u.material.needsUpdate=!0,a.backgroundCacheKey=c),t.unshift(u,u.geometry,u.material,0,0,null,null)}else console.error("THREE.Renderer: Unsupported background configuration.",r);const o=i.xr.getEnvironmentBlendMode();if("additive"===o?lD.set(0,0,0,1):"alpha-blend"===o&&lD.set(0,0,0,0),!0===i.autoClear||!0===s){const g=n.clearColorValue;g.r=lD.r,g.g=lD.g,g.b=lD.b,g.a=lD.a,!0!==i.backend.isWebGLBackend&&!0!==i.alpha||(g.r*=g.a,g.g*=g.a,g.b*=g.a),n.depthClearValue=i._clearDepth,n.stencilClearValue=i._clearStencil,n.clearColor=!0===i.autoClearColor,n.clearDepth=!0===i.autoClearDepth,n.clearStencil=!0===i.autoClearStencil}else n.clearColor=!1,n.clearDepth=!1,n.clearStencil=!1}}let cD=0;class dD{constructor(e="",t=[],n=0,i=[]){this.name=e,this.bindings=t,this.index=n,this.bindingsReference=i,this.id=cD++}}class hD{constructor(e,t,n,i,r,s,o,a,l,u=[]){this.vertexShader=e,this.fragmentShader=t,this.computeShader=n,this.transforms=u,this.nodeAttributes=i,this.bindings=r,this.updateNodes=s,this.updateBeforeNodes=o,this.updateAfterNodes=a,this.observer=l,this.usedTimes=0}createBindings(){const e=[];for(const t of this.bindings){if(!0!==t.bindings[0].groupNode.shared){const n=new dD(t.name,[],t.index,t.bindingsReference);e.push(n);for(const e of t.bindings)n.bindings.push(e.clone())}else e.push(t)}return e}}class fD{constructor(e,t,n=null){this.isNodeAttribute=!0,this.name=e,this.type=t,this.node=n}}class pD{constructor(e,t,n){this.isNodeUniform=!0,this.name=e,this.type=t,this.node=n}get value(){return this.node.value}set value(e){this.node.value=e}get id(){return this.node.id}get groupNode(){return this.node.groupNode}}class gD{constructor(e,t,n=!1,i=null){this.isNodeVar=!0,this.name=e,this.type=t,this.readOnly=n,this.count=i}}class mD extends gD{constructor(e,t,n=null,i=null){super(e,t),this.needsInterpolation=!1,this.isNodeVarying=!0,this.interpolationType=n,this.interpolationSampling=i}}class vD{constructor(e,t,n=""){this.name=e,this.type=t,this.code=n,Object.defineProperty(this,"isNodeCode",{value:!0})}}let AD=0;class xD{constructor(e=null){this.id=AD++,this.nodesData=new WeakMap,this.parent=e}getData(e){let t=this.nodesData.get(e);return void 0===t&&null!==this.parent&&(t=this.parent.getData(e)),t}setData(e,t){this.nodesData.set(e,t)}}class yD{constructor(e,t){this.name=e,this.members=t,this.output=!1}}class bD{constructor(e,t){this.name=e,this.value=t,this.boundary=0,this.itemSize=0,this.offset=0}setValue(e){this.value=e}getValue(){return this.value}}class wD extends bD{constructor(e,t=0){super(e,t),this.isNumberUniform=!0,this.boundary=4,this.itemSize=1}}class CD extends bD{constructor(e,t=new Cs){super(e,t),this.isVector2Uniform=!0,this.boundary=8,this.itemSize=2}}class MD extends bD{constructor(e,t=new Es){super(e,t),this.isVector3Uniform=!0,this.boundary=16,this.itemSize=3}}class ED extends bD{constructor(e,t=new Js){super(e,t),this.isVector4Uniform=!0,this.boundary=16,this.itemSize=4}}class TD extends bD{constructor(e,t=new ya){super(e,t),this.isColorUniform=!0,this.boundary=16,this.itemSize=3}}class SD extends bD{constructor(e,t=new jc){super(e,t),this.isMatrix2Uniform=!0,this.boundary=8,this.itemSize=4}}class PD extends bD{constructor(e,t=new Ps){super(e,t),this.isMatrix3Uniform=!0,this.boundary=48,this.itemSize=12}}class ND extends bD{constructor(e,t=new Po){super(e,t),this.isMatrix4Uniform=!0,this.boundary=64,this.itemSize=16}}class BD extends wD{constructor(e){super(e.name,e.value),this.nodeUniform=e}getValue(){return this.nodeUniform.value}getType(){return this.nodeUniform.type}}class DD extends CD{constructor(e){super(e.name,e.value),this.nodeUniform=e}getValue(){return this.nodeUniform.value}getType(){return this.nodeUniform.type}}class ID extends MD{constructor(e){super(e.name,e.value),this.nodeUniform=e}getValue(){return this.nodeUniform.value}getType(){return this.nodeUniform.type}}class LD extends ED{constructor(e){super(e.name,e.value),this.nodeUniform=e}getValue(){return this.nodeUniform.value}getType(){return this.nodeUniform.type}}class jD extends TD{constructor(e){super(e.name,e.value),this.nodeUniform=e}getValue(){return this.nodeUniform.value}getType(){return this.nodeUniform.type}}class OD extends SD{constructor(e){super(e.name,e.value),this.nodeUniform=e}getValue(){return this.nodeUniform.value}getType(){return this.nodeUniform.type}}class zD extends PD{constructor(e){super(e.name,e.value),this.nodeUniform=e}getValue(){return this.nodeUniform.value}getType(){return this.nodeUniform.type}}class RD extends ND{constructor(e){super(e.name,e.value),this.nodeUniform=e}getValue(){return this.nodeUniform.value}getType(){return this.nodeUniform.type}}const kD=new WeakMap,FD=new Map([[Int8Array,"int"],[Int16Array,"int"],[Int32Array,"int"],[Uint8Array,"uint"],[Uint16Array,"uint"],[Uint32Array,"uint"],[Float32Array,"float"]]),HD=e=>/e/g.test(e)?String(e).replace(/\+/g,""):(e=Number(e))+(e%1?"":".0");class UD{constructor(e,t,n){this.object=e,this.material=e&&e.material||null,this.geometry=e&&e.geometry||null,this.renderer=t,this.parser=n,this.scene=null,this.camera=null,this.nodes=[],this.sequentialNodes=[],this.updateNodes=[],this.updateBeforeNodes=[],this.updateAfterNodes=[],this.hashNodes={},this.observer=null,this.lightsNode=null,this.environmentNode=null,this.fogNode=null,this.clippingContext=null,this.vertexShader=null,this.fragmentShader=null,this.computeShader=null,this.flowNodes={vertex:[],fragment:[],compute:[]},this.flowCode={vertex:"",fragment:"",compute:""},this.uniforms={vertex:[],fragment:[],compute:[],index:0},this.structs={vertex:[],fragment:[],compute:[],index:0},this.types={vertex:[],fragment:[],compute:[],index:0},this.bindings={vertex:{},fragment:{},compute:{}},this.bindingsIndexes={},this.bindGroups=null,this.attributes=[],this.bufferAttributes=[],this.varyings=[],this.codes={},this.vars={},this.declarations={},this.flow={code:""},this.chaining=[],this.stack=CN(),this.stacks=[],this.tab="\t",this.currentFunctionNode=null,this.context={material:this.material},this.cache=new xD,this.globalCache=this.cache,this.flowsData=new WeakMap,this.shaderStage=null,this.buildStage=null,this.subBuildLayers=[],this.currentStack=null,this.subBuildFn=null}getBindGroupsCache(){let e=kD.get(this.renderer);return void 0===e&&(e=new zP,kD.set(this.renderer,e)),e}createRenderTarget(e,t,n){return new Ks(e,t,n)}createCubeRenderTarget(e,t){return new aT(e,t)}includes(e){return this.nodes.includes(e)}getOutputStructName(){}_getBindGroup(e,t){const n=this.getBindGroupsCache(),i=[];let r,s=!0;for(const e of t)i.push(e),s=s&&!0!==e.groupNode.shared;return s?(r=n.get(i),void 0===r&&(r=new dD(e,i,this.bindingsIndexes[e].group,i),n.set(i,r))):r=new dD(e,i,this.bindingsIndexes[e].group,i),r}getBindGroupArray(e,t){const n=this.bindings[t];let i=n[e];return void 0===i&&(void 0===this.bindingsIndexes[e]&&(this.bindingsIndexes[e]={binding:0,group:Object.keys(this.bindingsIndexes).length}),n[e]=i=[]),i}getBindings(){let e=this.bindGroups;if(null===e){const t={},n=this.bindings;for(const e of mv)for(const i in n[e]){const r=n[e][i];(t[i]||(t[i]=[])).push(...r)}e=[];for(const n in t){const i=t[n],r=this._getBindGroup(n,i);e.push(r)}this.bindGroups=e}return e}sortBindingGroups(){const e=this.getBindings();e.sort(((e,t)=>e.bindings[0].groupNode.order-t.bindings[0].groupNode.order));for(let t=0;t<e.length;t++){const n=e[t];this.bindingsIndexes[n.name].group=t,n.index=t}}setHashNode(e,t){this.hashNodes[t]=e}addNode(e){!1===this.nodes.includes(e)&&(this.nodes.push(e),this.setHashNode(e,e.getHash(this)))}addSequentialNode(e){!1===this.sequentialNodes.includes(e)&&this.sequentialNodes.push(e)}buildUpdateNodes(){for(const e of this.nodes){e.getUpdateType()!==hv.NONE&&this.updateNodes.push(e)}for(const e of this.sequentialNodes){const t=e.getUpdateBeforeType(),n=e.getUpdateAfterType();t!==hv.NONE&&this.updateBeforeNodes.push(e),n!==hv.NONE&&this.updateAfterNodes.push(e)}}get currentNode(){return this.chaining[this.chaining.length-1]}isFilteredTexture(e){return e.magFilter===Hi||e.magFilter===Ui||e.magFilter===Fi||e.magFilter===Xi||e.minFilter===Hi||e.minFilter===Ui||e.minFilter===Fi||e.minFilter===Xi}addChain(e){this.chaining.push(e)}removeChain(e){if(this.chaining.pop()!==e)throw new Error("NodeBuilder: Invalid node chaining!")}getMethod(e){return e}getTernary(){return null}getNodeFromHash(e){return this.hashNodes[e]}addFlow(e,t){return this.flowNodes[e].push(t),t}setContext(e){this.context=e}getContext(){return this.context}getSharedContext(){return this.context,this.context}setCache(e){this.cache=e}getCache(){return this.cache}getCacheFromNode(e,t=!0){const n=this.getDataFromNode(e);return void 0===n.cache&&(n.cache=new xD(t?this.getCache():null)),n.cache}isAvailable(){return!1}getVertexIndex(){console.warn("Abstract function.")}getInstanceIndex(){console.warn("Abstract function.")}getDrawIndex(){console.warn("Abstract function.")}getFrontFacing(){console.warn("Abstract function.")}getFragCoord(){console.warn("Abstract 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t>=0?`${Math.round(t)}u`:"0u";if("bool"===e)return t?"true":"false";if("color"===e)return`${this.getType("vec3")}( ${HD(t.r)}, ${HD(t.g)}, ${HD(t.b)} )`;const n=this.getTypeLength(e),i=this.getComponentType(e),r=e=>this.generateConst(i,e);if(2===n)return`${this.getType(e)}( ${r(t.x)}, ${r(t.y)} )`;if(3===n)return`${this.getType(e)}( ${r(t.x)}, ${r(t.y)}, ${r(t.z)} )`;if(4===n&&"mat2"!==e)return`${this.getType(e)}( ${r(t.x)}, ${r(t.y)}, ${r(t.z)}, ${r(t.w)} )`;if(n>=4&&t&&(t.isMatrix2||t.isMatrix3||t.isMatrix4))return`${this.getType(e)}( ${t.elements.map(r).join(", ")} )`;if(n>4)return`${this.getType(e)}()`;throw new Error(`NodeBuilder: Type '${e}' not found in generate constant attempt.`)}getType(e){return"color"===e?"vec3":e}hasGeometryAttribute(e){return this.geometry&&void 0!==this.geometry.getAttribute(e)}getAttribute(e,t){const n=this.attributes;for(const t of n)if(t.name===e)return t;const i=new fD(e,t);return this.registerDeclaration(i),n.push(i),i}getPropertyName(e){return e.name}isVector(e){return/vec\d/.test(e)}isMatrix(e){return/mat\d/.test(e)}isReference(e){return"void"===e||"property"===e||"sampler"===e||"samplerComparison"===e||"texture"===e||"cubeTexture"===e||"storageTexture"===e||"depthTexture"===e||"texture3D"===e}needsToWorkingColorSpace(){return!1}getComponentTypeFromTexture(e){const t=e.type;if(e.isDataTexture){if(t===Zi)return"int";if(t===Yi)return"uint"}return"float"}getElementType(e){return"mat2"===e?"vec2":"mat3"===e?"vec3":"mat4"===e?"vec4":this.getComponentType(e)}getComponentType(e){if("float"===(e=this.getVectorType(e))||"bool"===e||"int"===e||"uint"===e)return e;const t=/(b|i|u|)(vec|mat)([2-4])/.exec(e);return null===t?null:"b"===t[1]?"bool":"i"===t[1]?"int":"u"===t[1]?"uint":"float"}getVectorType(e){return"color"===e?"vec3":"texture"===e||"cubeTexture"===e||"storageTexture"===e||"texture3D"===e?"vec4":e}getTypeFromLength(e,t="float"){if(1===e)return t;let n=sv(e);const i="float"===t?"":t[0];return!0===/mat2/.test(t)&&(n=n.replace("vec","mat")),i+n}getTypeFromArray(e){return FD.get(e.constructor)}isInteger(e){return/int|uint|(i|u)vec/.test(e)}getTypeFromAttribute(e){let t=e;e.isInterleavedBufferAttribute&&(t=e.data);const n=t.array,i=e.itemSize,r=e.normalized;let s;return e instanceof Oa||!0===r||(s=this.getTypeFromArray(n)),this.getTypeFromLength(i,s)}getTypeLength(e){const t=this.getVectorType(e),n=/vec([2-4])/.exec(t);return null!==n?Number(n[1]):"float"===t||"bool"===t||"int"===t||"uint"===t?1:!0===/mat2/.test(e)?4:!0===/mat3/.test(e)?9:!0===/mat4/.test(e)?16:0}getVectorFromMatrix(e){return e.replace("mat","vec")}changeComponentType(e,t){return this.getTypeFromLength(this.getTypeLength(e),t)}getIntegerType(e){const t=this.getComponentType(e);return"int"===t||"uint"===t?e:this.changeComponentType(e,"int")}addStack(){this.stack=CN(this.stack);const e=bA();return this.stacks.push(e),yA(this.stack),this.stack}removeStack(){const e=this.stack;return this.stack=e.parent,yA(this.stacks.pop()),e}getDataFromNode(e,t=this.shaderStage,n=null){let i=(n=null===n?e.isGlobal(this)?this.globalCache:this.cache:n).getData(e);void 0===i&&(i={},n.setData(e,i)),void 0===i[t]&&(i[t]={});let r=i[t];const s=i.any?i.any.subBuilds:null,o=this.getClosestSubBuild(s);return o&&(void 0===r.subBuildsCache&&(r.subBuildsCache={}),r=r.subBuildsCache[o]||(r.subBuildsCache[o]={}),r.subBuilds=s),r}getNodeProperties(e,t="any"){const n=this.getDataFromNode(e,t);return n.properties||(n.properties={outputNode:null})}getBufferAttributeFromNode(e,t){const n=this.getDataFromNode(e);let i=n.bufferAttribute;if(void 0===i){const r=this.uniforms.index++;i=new fD("nodeAttribute"+r,t,e),this.bufferAttributes.push(i),n.bufferAttribute=i}return i}getStructTypeNode(e,t=this.shaderStage){return this.types[t][e]||null}getStructTypeFromNode(e,t,n=null,i=this.shaderStage){const r=this.getDataFromNode(e,i,this.globalCache);let s=r.structType;if(void 0===s){const o=this.structs.index++;null===n&&(n="StructType"+o),s=new yD(n,t),this.structs[i].push(s),this.types[i][n]=e,r.structType=s}return s}getOutputStructTypeFromNode(e,t){const n=this.getStructTypeFromNode(e,t,"OutputType","fragment");return n.output=!0,n}getUniformFromNode(e,t,n=this.shaderStage,i=null){const r=this.getDataFromNode(e,n,this.globalCache);let s=r.uniform;if(void 0===s){const o=this.uniforms.index++;s=new pD(i||"nodeUniform"+o,t,e),this.uniforms[n].push(s),this.registerDeclaration(s),r.uniform=s}return s}getVarFromNode(e,t=null,n=e.getNodeType(this),i=this.shaderStage,r=!1){const s=this.getDataFromNode(e,i),o=this.getSubBuildProperty("variable",s.subBuilds);let a=s[o];if(void 0===a){const l=r?"_const":"_var",u=this.vars[i]||(this.vars[i]=[]),c=this.vars[l]||(this.vars[l]=0);null===t&&(t=(r?"nodeConst":"nodeVar")+c,this.vars[l]++),"variable"!==o&&(t=this.getSubBuildProperty(t,s.subBuilds));const d=e.getArrayCount(this);a=new gD(t,n,r,d),r||u.push(a),this.registerDeclaration(a),s[o]=a}return a}isDeterministic(e){if(e.isMathNode)return this.isDeterministic(e.aNode)&&(!e.bNode||this.isDeterministic(e.bNode))&&(!e.cNode||this.isDeterministic(e.cNode));if(e.isOperatorNode)return this.isDeterministic(e.aNode)&&(!e.bNode||this.isDeterministic(e.bNode));if(e.isArrayNode){if(null!==e.values)for(const t of e.values)if(!this.isDeterministic(t))return!1;return!0}return!!e.isConstNode}getVaryingFromNode(e,t=null,n=e.getNodeType(this),i=null,r=null){const s=this.getDataFromNode(e,"any"),o=this.getSubBuildProperty("varying",s.subBuilds);let a=s[o];if(void 0===a){const e=this.varyings,l=e.length;null===t&&(t="nodeVarying"+l),"varying"!==o&&(t=this.getSubBuildProperty(t,s.subBuilds)),a=new mD(t,n,i,r),e.push(a),this.registerDeclaration(a),s[o]=a}return a}registerDeclaration(e){const t=this.shaderStage,n=this.declarations[t]||(this.declarations[t]={}),i=this.getPropertyName(e);let r=1,s=i;for(;void 0!==n[s];)s=i+"_"+r++;r>1&&(e.name=s,console.warn(`THREE.TSL: Declaration name '${i}' of '${e.type}' already in use. Renamed to '${s}'.`)),n[s]=e}getCodeFromNode(e,t,n=this.shaderStage){const i=this.getDataFromNode(e);let r=i.code;if(void 0===r){const e=this.codes[n]||(this.codes[n]=[]),s=e.length;r=new vD("nodeCode"+s,t),e.push(r),i.code=r}return r}addFlowCodeHierarchy(e,t){const{flowCodes:n,flowCodeBlock:i}=this.getDataFromNode(e);let r=!0,s=t;for(;s;){if(!0===i.get(s)){r=!1;break}s=this.getDataFromNode(s).parentNodeBlock}if(r)for(const e of n)this.addLineFlowCode(e)}addLineFlowCodeBlock(e,t,n){const i=this.getDataFromNode(e),r=i.flowCodes||(i.flowCodes=[]),s=i.flowCodeBlock||(i.flowCodeBlock=new WeakMap);r.push(t),s.set(n,!0)}addLineFlowCode(e,t=null){return""===e||(null!==t&&this.context.nodeBlock&&this.addLineFlowCodeBlock(t,e,this.context.nodeBlock),e=this.tab+e,/;\s*$/.test(e)||(e+=";\n"),this.flow.code+=e),this}addFlowCode(e){return this.flow.code+=e,this}addFlowTab(){return this.tab+="\t",this}removeFlowTab(){return this.tab=this.tab.slice(0,-1),this}getFlowData(e){return this.flowsData.get(e)}flowNode(e){const t=e.getNodeType(this),n=this.flowChildNode(e,t);return this.flowsData.set(e,n),n}addInclude(e){null!==this.currentFunctionNode&&this.currentFunctionNode.includes.push(e)}buildFunctionNode(e){const t=new eB,n=this.currentFunctionNode;return this.currentFunctionNode=t,t.code=this.buildFunctionCode(e),this.currentFunctionNode=n,t}flowShaderNode(e){const t=e.layout,n={[Symbol.iterator](){let e=0;const t=Object.values(this);return{next:()=>({value:t[e],done:e++>=t.length})}}};for(const e of t.inputs)n[e.name]=new bN(e.type,e.name);e.layout=null;const i=e.call(n),r=this.flowStagesNode(i,t.type);return e.layout=t,r}flowBuildStage(e,t,n=null){const i=this.getBuildStage();this.setBuildStage(t);const r=e.build(this,n);return this.setBuildStage(i),r}flowStagesNode(e,t=null){const n=this.flow,i=this.vars,r=this.declarations,s=this.cache,o=this.buildStage,a=this.stack,l={code:""};this.flow=l,this.vars={},this.declarations={},this.cache=new xD,this.stack=CN();for(const n of gv)this.setBuildStage(n),l.result=e.build(this,t);return l.vars=this.getVars(this.shaderStage),this.flow=n,this.vars=i,this.declarations=r,this.cache=s,this.stack=a,this.setBuildStage(o),l}getFunctionOperator(){return null}buildFunctionCode(){console.warn("Abstract function.")}flowChildNode(e,t=null){const n=this.flow,i={code:""};return this.flow=i,i.result=e.build(this,t),this.flow=n,i}flowNodeFromShaderStage(e,t,n=null,i=null){const r=this.tab,s=this.cache,o=this.shaderStage,a=this.context;this.setShaderStage(e);const l={...this.context};delete l.nodeBlock,this.cache=this.globalCache,this.tab="\t",this.context=l;let u=null;if("generate"===this.buildStage){const r=this.flowChildNode(t,n);null!==i&&(r.code+=`${this.tab+i} = ${r.result};\n`),this.flowCode[e]=this.flowCode[e]+r.code,u=r}else u=t.build(this);return this.setShaderStage(o),this.cache=s,this.tab=r,this.context=a,u}getAttributesArray(){return this.attributes.concat(this.bufferAttributes)}getAttributes(){console.warn("Abstract function.")}getVaryings(){console.warn("Abstract function.")}getVar(e,t,n=null){return`${null!==n?this.generateArrayDeclaration(e,n):this.getType(e)} ${t}`}getVars(e){let t="";const n=this.vars[e];if(void 0!==n)for(const e of n)t+=`${this.getVar(e.type,e.name)}; `;return t}getUniforms(){console.warn("Abstract function.")}getCodes(e){const t=this.codes[e];let n="";if(void 0!==t)for(const e of t)n+=e.code+"\n";return n}getHash(){return this.vertexShader+this.fragmentShader+this.computeShader}setShaderStage(e){this.shaderStage=e}getShaderStage(){return this.shaderStage}setBuildStage(e){this.buildStage=e}getBuildStage(){return this.buildStage}buildCode(){console.warn("Abstract function.")}get subBuild(){return this.subBuildLayers[this.subBuildLayers.length-1]||null}addSubBuild(e){this.subBuildLayers.push(e)}removeSubBuild(){return this.subBuildLayers.pop()}getClosestSubBuild(e){let t;if(t=e&&e.isNode?e.isShaderCallNodeInternal?e.shaderNode.subBuilds:e.isStackNode?[e.subBuild]:this.getDataFromNode(e,"any").subBuilds:e instanceof Set?[...e]:e,!t)return null;const n=this.subBuildLayers;for(let e=t.length-1;e>=0;e--){const i=t[e];if(n.includes(i))return i}return null}getSubBuildOutput(e){return this.getSubBuildProperty("outputNode",e)}getSubBuildProperty(e="",t=null){let n,i;return n=null!==t?this.getClosestSubBuild(t):this.subBuildFn,i=n?e?n+"_"+e:n:e,i}build(){const{object:e,material:t,renderer:n}=this;if(null!==t){let e=n.library.fromMaterial(t);null===e&&(console.error(`NodeMaterial: Material "${t.type}" is not compatible.`),e=new _E),e.build(this)}else this.addFlow("compute",e);for(const e of gv){this.setBuildStage(e),this.context.vertex&&this.context.vertex.isNode&&this.flowNodeFromShaderStage("vertex",this.context.vertex);for(const t of mv){this.setShaderStage(t);const n=this.flowNodes[t];for(const t of n)"generate"===e?this.flowNode(t):t.build(this)}}return this.setBuildStage(null),this.setShaderStage(null),this.buildCode(),this.buildUpdateNodes(),this}getNodeUniform(e,t){if("float"===t||"int"===t||"uint"===t)return new BD(e);if("vec2"===t||"ivec2"===t||"uvec2"===t)return new DD(e);if("vec3"===t||"ivec3"===t||"uvec3"===t)return new ID(e);if("vec4"===t||"ivec4"===t||"uvec4"===t)return new LD(e);if("color"===t)return new jD(e);if("mat2"===t)return new OD(e);if("mat3"===t)return new zD(e);if("mat4"===t)return new RD(e);throw new Error(`Uniform "${t}" not declared.`)}format(e,t,n){if((t=this.getVectorType(t))===(n=this.getVectorType(n))||null===n||this.isReference(n))return e;const i=this.getTypeLength(t),r=this.getTypeLength(n);return 16===i&&9===r?`${this.getType(n)}( ${e}[ 0 ].xyz, ${e}[ 1 ].xyz, ${e}[ 2 ].xyz )`:9===i&&4===r?`${this.getType(n)}( ${e}[ 0 ].xy, ${e}[ 1 ].xy )`:i>4||r>4||0===r?e:i===r?`${this.getType(n)}( ${e} )`:i>r?(e="bool"===n?`all( ${e} )`:`${e}.${"xyz".slice(0,r)}`,this.format(e,this.getTypeFromLength(r,this.getComponentType(t)),n)):4===r&&i>1?`${this.getType(n)}( ${this.format(e,t,"vec3")}, 1.0 )`:2===i?`${this.getType(n)}( ${this.format(e,t,"vec2")}, 0.0 )`:(1===i&&r>1&&t!==this.getComponentType(n)&&(e=`${this.getType(this.getComponentType(n))}( ${e} )`),`${this.getType(n)}( ${e} )`)}getSignature(){return`// Three.js r${mi} - Node System\n`}}class XD{constructor(){this.time=0,this.deltaTime=0,this.frameId=0,this.renderId=0,this.updateMap=new WeakMap,this.updateBeforeMap=new WeakMap,this.updateAfterMap=new WeakMap,this.renderer=null,this.material=null,this.camera=null,this.object=null,this.scene=null}_getMaps(e,t){let n=e.get(t);return void 0===n&&(n={renderMap:new WeakMap,frameMap:new WeakMap},e.set(t,n)),n}updateBeforeNode(e){const t=e.getUpdateBeforeType(),n=e.updateReference(this);if(t===hv.FRAME){const{frameMap:t}=this._getMaps(this.updateBeforeMap,n);t.get(n)!==this.frameId&&!1!==e.updateBefore(this)&&t.set(n,this.frameId)}else if(t===hv.RENDER){const{renderMap:t}=this._getMaps(this.updateBeforeMap,n);t.get(n)!==this.renderId&&!1!==e.updateBefore(this)&&t.set(n,this.renderId)}else t===hv.OBJECT&&e.updateBefore(this)}updateAfterNode(e){const t=e.getUpdateAfterType(),n=e.updateReference(this);if(t===hv.FRAME){const{frameMap:t}=this._getMaps(this.updateAfterMap,n);t.get(n)!==this.frameId&&!1!==e.updateAfter(this)&&t.set(n,this.frameId)}else if(t===hv.RENDER){const{renderMap:t}=this._getMaps(this.updateAfterMap,n);t.get(n)!==this.renderId&&!1!==e.updateAfter(this)&&t.set(n,this.renderId)}else t===hv.OBJECT&&e.updateAfter(this)}updateNode(e){const t=e.getUpdateType(),n=e.updateReference(this);if(t===hv.FRAME){const{frameMap:t}=this._getMaps(this.updateMap,n);t.get(n)!==this.frameId&&!1!==e.update(this)&&t.set(n,this.frameId)}else if(t===hv.RENDER){const{renderMap:t}=this._getMaps(this.updateMap,n);t.get(n)!==this.renderId&&!1!==e.update(this)&&t.set(n,this.renderId)}else t===hv.OBJECT&&e.update(this)}update(){this.frameId++,void 0===this.lastTime&&(this.lastTime=performance.now()),this.deltaTime=(performance.now()-this.lastTime)/1e3,this.lastTime=performance.now(),this.time+=this.deltaTime}}class GD{constructor(e,t,n=null,i="",r=!1){this.type=e,this.name=t,this.count=n,this.qualifier=i,this.isConst=r}}GD.isNodeFunctionInput=!0;class VD extends iD{static get type(){return"DirectionalLightNode"}constructor(e=null){super(e)}setupDirect(){const e=this.colorNode;return{lightDirection:gB(this.light),lightColor:e}}}const WD=new Po,QD=new Po;let ZD=null;class YD extends iD{static get type(){return"RectAreaLightNode"}constructor(e=null){super(e),this.halfHeight=Nx(new Es).setGroup(Tx),this.halfWidth=Nx(new Es).setGroup(Tx),this.updateType=hv.RENDER}update(e){super.update(e);const{light:t}=this,n=e.camera.matrixWorldInverse;QD.identity(),WD.copy(t.matrixWorld),WD.premultiply(n),QD.extractRotation(WD),this.halfWidth.value.set(.5*t.width,0,0),this.halfHeight.value.set(0,.5*t.height,0),this.halfWidth.value.applyMatrix4(QD),this.halfHeight.value.applyMatrix4(QD)}setupDirectRectArea(e){let t,n;e.isAvailable("float32Filterable")?(t=Pw(ZD.LTC_FLOAT_1),n=Pw(ZD.LTC_FLOAT_2)):(t=Pw(ZD.LTC_HALF_1),n=Pw(ZD.LTC_HALF_2));const{colorNode:i,light:r}=this;return{lightColor:i,lightPosition:pB(r),halfWidth:this.halfWidth,halfHeight:this.halfHeight,ltc_1:t,ltc_2:n}}static setLTC(e){ZD=e}}class JD extends iD{static get type(){return"SpotLightNode"}constructor(e=null){super(e),this.coneCosNode=Nx(0).setGroup(Tx),this.penumbraCosNode=Nx(0).setGroup(Tx),this.cutoffDistanceNode=Nx(0).setGroup(Tx),this.decayExponentNode=Nx(0).setGroup(Tx),this.colorNode=Nx(this.color).setGroup(Tx)}update(e){super.update(e);const{light:t}=this;this.coneCosNode.value=Math.cos(t.angle),this.penumbraCosNode.value=Math.cos(t.angle*(1-t.penumbra)),this.cutoffDistanceNode.value=t.distance,this.decayExponentNode.value=t.decay}getSpotAttenuation(e,t){const{coneCosNode:n,penumbraCosNode:i}=this;return fb(n,i,t)}getLightCoord(e){const t=e.getNodeProperties(this);let n=t.projectionUV;return void 0===n&&(n=dB(this.light,e.context.positionWorld),t.projectionUV=n),n}setupDirect(e){const{colorNode:t,cutoffDistanceNode:n,decayExponentNode:i,light:r}=this,s=this.getLightVector(e),o=s.normalize(),a=o.dot(gB(r)),l=this.getSpotAttenuation(e,a),u=s.length(),c=rD({lightDistance:u,cutoffDistance:n,decayExponent:i});let d,h,f=t.mul(l).mul(c);if(r.colorNode?(h=this.getLightCoord(e),d=r.colorNode(h)):r.map&&(h=this.getLightCoord(e),d=Pw(r.map,h.xy).onRenderUpdate((()=>r.map))),d){f=h.mul(2).sub(1).abs().lessThan(1).all().select(f.mul(d),f)}return{lightColor:f,lightDirection:o}}}class KD extends JD{static get type(){return"IESSpotLightNode"}getSpotAttenuation(e,t){const n=this.light.iesMap;let i=null;if(n&&!0===n.isTexture){const e=t.acos().mul(1/Math.PI);i=Pw(n,NA(e,0),0).r}else i=super.getSpotAttenuation(t);return i}}const qD=xA((([e,t])=>{const n=e.abs().sub(t);return Oy(Jy(n,0)).add(Yy(Jy(n.x,n.y),0))}));class _D extends JD{static get type(){return"ProjectorLightNode"}update(e){super.update(e);const t=this.light;if(this.penumbraCosNode.value=Math.min(Math.cos(t.angle*(1-t.penumbra)),.99999),null===t.aspect){let e=1;null!==t.map&&(e=t.map.width/t.map.height),t.shadow.aspect=e}else t.shadow.aspect=t.aspect}getSpotAttenuation(e){const t=EA(0),n=this.penumbraCosNode,i=cB(this.light).mul(e.context.positionWorld||cC);return wA(i.w.greaterThan(0),(()=>{const e=i.xyz.div(i.w),r=qD(e.xy.sub(NA(.5)),NA(.5)),s=Ux(-1,Fx(1,Dy(n)).sub(1));t.assign(db(r.mul(-2).mul(s)))})),t}}class $D extends iD{static get type(){return"AmbientLightNode"}constructor(e=null){super(e)}setup({context:e}){e.irradiance.addAssign(this.colorNode)}}class eI extends iD{static get type(){return"HemisphereLightNode"}constructor(e=null){super(e),this.lightPositionNode=hB(e),this.lightDirectionNode=this.lightPositionNode.normalize(),this.groundColorNode=Nx(new ya).setGroup(Tx)}update(e){const{light:t}=this;super.update(e),this.lightPositionNode.object3d=t,this.groundColorNode.value.copy(t.groundColor).multiplyScalar(t.intensity)}setup(e){const{colorNode:t,groundColorNode:n,lightDirectionNode:i}=this,r=MC.dot(i).mul(.5).add(.5),s=ub(n,t,r);e.context.irradiance.addAssign(s)}}class tI extends iD{static get type(){return"LightProbeNode"}constructor(e=null){super(e);const t=[];for(let e=0;e<9;e++)t.push(new Es);this.lightProbe=jw(t)}update(e){const{light:t}=this;super.update(e);for(let e=0;e<9;e++)this.lightProbe.array[e].copy(t.sh.coefficients[e]).multiplyScalar(t.intensity)}setup(e){const t=aD(MC,this.lightProbe);e.context.irradiance.addAssign(t)}}class nI{parseFunction(){console.warn("Abstract function.")}}class iI{constructor(e,t,n="",i=""){this.type=e,this.inputs=t,this.name=n,this.precision=i}getCode(){console.warn("Abstract function.")}}iI.isNodeFunction=!0;const rI=/^\s*(highp|mediump|lowp)?\s*([a-z_0-9]+)\s*([a-z_0-9]+)?\s*\(([\s\S]*?)\)/i,sI=/[a-z_0-9]+/gi,oI="#pragma main";class aI extends iI{constructor(e){const{type:t,inputs:n,name:i,precision:r,inputsCode:s,blockCode:o,headerCode:a}=(e=>{const t=(e=e.trim()).indexOf(oI),n=-1!==t?e.slice(t+oI.length):e,i=n.match(rI);if(null!==i&&5===i.length){const r=i[4],s=[];let o=null;for(;null!==(o=sI.exec(r));)s.push(o);const a=[];let l=0;for(;l<s.length;){const e="const"===s[l][0];!0===e&&l++;let t=s[l][0];"in"===t||"out"===t||"inout"===t?l++:t="";const n=s[l++][0];let i=Number.parseInt(s[l][0]);!1===Number.isNaN(i)?l++:i=null;const r=s[l++][0];a.push(new GD(n,r,i,t,e))}const u=n.substring(i[0].length),c=void 0!==i[3]?i[3]:"";return{type:i[2],inputs:a,name:c,precision:void 0!==i[1]?i[1]:"",inputsCode:r,blockCode:u,headerCode:-1!==t?e.slice(0,t):""}}throw new Error("FunctionNode: Function is not a GLSL code.")})(e);super(t,n,i,r),this.inputsCode=s,this.blockCode=o,this.headerCode=a}getCode(e=this.name){let t;const n=this.blockCode;if(""!==n){const{type:i,inputsCode:r,headerCode:s,precision:o}=this;let a=`${i} ${e} ( ${r.trim()} )`;""!==o&&(a=`${o} ${a}`),t=s+a+n}else t="";return t}}class lI extends nI{parseFunction(e){return new aI(e)}}const uI=new WeakMap,cI=[],dI=[];class hI extends UP{constructor(e,t){super(),this.renderer=e,this.backend=t,this.nodeFrame=new XD,this.nodeBuilderCache=new Map,this.callHashCache=new zP,this.groupsData=new zP,this.cacheLib={}}updateGroup(e){const t=e.groupNode,n=t.name;if(n===Sx.name)return!0;if(n===Tx.name){const t=this.get(e),n=this.nodeFrame.renderId;return t.renderId!==n&&(t.renderId=n,!0)}if(n===Ex.name){const t=this.get(e),n=this.nodeFrame.frameId;return t.frameId!==n&&(t.frameId=n,!0)}cI[0]=t,cI[1]=e;let i=this.groupsData.get(cI);return void 0===i&&this.groupsData.set(cI,i={}),cI.length=0,i.version!==t.version&&(i.version=t.version,!0)}getForRenderCacheKey(e){return e.initialCacheKey}getForRender(e){const t=this.get(e);let n=t.nodeBuilderState;if(void 0===n){const{nodeBuilderCache:i}=this,r=this.getForRenderCacheKey(e);if(n=i.get(r),void 0===n){const t=this.backend.createNodeBuilder(e.object,this.renderer);t.scene=e.scene,t.material=e.material,t.camera=e.camera,t.context.material=e.material,t.lightsNode=e.lightsNode,t.environmentNode=this.getEnvironmentNode(e.scene),t.fogNode=this.getFogNode(e.scene),t.clippingContext=e.clippingContext,this.renderer.getOutputRenderTarget()&&this.renderer.getOutputRenderTarget().multiview&&t.enableMultiview(),t.build(),n=this._createNodeBuilderState(t),i.set(r,n)}n.usedTimes++,t.nodeBuilderState=n}return n}delete(e){if(e.isRenderObject){const t=this.get(e).nodeBuilderState;t.usedTimes--,0===t.usedTimes&&this.nodeBuilderCache.delete(this.getForRenderCacheKey(e))}return super.delete(e)}getForCompute(e){const t=this.get(e);let n=t.nodeBuilderState;if(void 0===n){const i=this.backend.createNodeBuilder(e,this.renderer);i.build(),n=this._createNodeBuilderState(i),t.nodeBuilderState=n}return n}_createNodeBuilderState(e){return new hD(e.vertexShader,e.fragmentShader,e.computeShader,e.getAttributesArray(),e.getBindings(),e.updateNodes,e.updateBeforeNodes,e.updateAfterNodes,e.observer,e.transforms)}getEnvironmentNode(e){this.updateEnvironment(e);let t=null;if(e.environmentNode&&e.environmentNode.isNode)t=e.environmentNode;else{const n=this.get(e);n.environmentNode&&(t=n.environmentNode)}return t}getBackgroundNode(e){this.updateBackground(e);let t=null;if(e.backgroundNode&&e.backgroundNode.isNode)t=e.backgroundNode;else{const n=this.get(e);n.backgroundNode&&(t=n.backgroundNode)}return t}getFogNode(e){return this.updateFog(e),e.fogNode||this.get(e).fogNode||null}getCacheKey(e,t){cI[0]=e,cI[1]=t;const n=this.renderer.info.calls,i=this.callHashCache.get(cI)||{};if(i.callId!==n){const r=this.getEnvironmentNode(e),s=this.getFogNode(e);t&&dI.push(t.getCacheKey(!0)),r&&dI.push(r.getCacheKey()),s&&dI.push(s.getCacheKey()),dI.push(this.renderer.getOutputRenderTarget()&&this.renderer.getOutputRenderTarget().multiview?1:0),dI.push(this.renderer.shadowMap.enabled?1:0),i.callId=n,i.cacheKey=$m(dI),this.callHashCache.set(cI,i),dI.length=0}return cI.length=0,i.cacheKey}get isToneMappingState(){return!this.renderer.getRenderTarget()}updateBackground(e){const t=this.get(e),n=e.background;if(n){const i=0===e.backgroundBlurriness&&t.backgroundBlurriness>0||e.backgroundBlurriness>0&&0===t.backgroundBlurriness;if(t.background!==n||i){const r=this.getCacheNode("background",n,(()=>{if(!0===n.isCubeTexture||n.mapping===Di||n.mapping===Ii||n.mapping===Li){if(e.backgroundBlurriness>0||n.mapping===Li)return lP(n);{let e;return e=!0===n.isCubeTexture?HC(n):Pw(n),hT(e)}}if(!0===n.isTexture)return Pw(n,Hw.flipY()).setUpdateMatrix(!0);!0!==n.isColor&&console.error("WebGPUNodes: Unsupported background configuration.",n)}),i);t.backgroundNode=r,t.background=n,t.backgroundBlurriness=e.backgroundBlurriness}}else t.backgroundNode&&(delete t.backgroundNode,delete t.background)}getCacheNode(e,t,n,i=!1){const r=this.cacheLib[e]||(this.cacheLib[e]=new WeakMap);let s=r.get(t);return(void 0===s||i)&&(s=n(),r.set(t,s)),s}updateFog(e){const t=this.get(e),n=e.fog;if(n){if(t.fog!==n){const e=this.getCacheNode("fog",n,(()=>{if(n.isFogExp2){const e=GC("color","color",n).setGroup(Tx),t=GC("density","float",n).setGroup(Tx);return sB(e,rB(t))}if(n.isFog){const e=GC("color","color",n).setGroup(Tx),t=GC("near","float",n).setGroup(Tx),i=GC("far","float",n).setGroup(Tx);return sB(e,iB(t,i))}console.error("THREE.Renderer: Unsupported fog configuration.",n)}));t.fogNode=e,t.fog=n}}else delete t.fogNode,delete t.fog}updateEnvironment(e){const t=this.get(e),n=e.environment;if(n){if(t.environment!==n){const e=this.getCacheNode("environment",n,(()=>!0===n.isCubeTexture?HC(n):!0===n.isTexture?Pw(n):void console.error("Nodes: Unsupported environment configuration.",n)));t.environmentNode=e,t.environment=n}}else t.environmentNode&&(delete t.environmentNode,delete t.environment)}getNodeFrame(e=this.renderer,t=null,n=null,i=null,r=null){const s=this.nodeFrame;return s.renderer=e,s.scene=t,s.object=n,s.camera=i,s.material=r,s}getNodeFrameForRender(e){return this.getNodeFrame(e.renderer,e.scene,e.object,e.camera,e.material)}getOutputCacheKey(){const e=this.renderer;return e.toneMapping+","+e.currentColorSpace+","+e.xr.isPresenting}hasOutputChange(e){return uI.get(e)!==this.getOutputCacheKey()}getOutputNode(e){const t=this.renderer,n=this.getOutputCacheKey(),i=e.isArrayTexture?kN(e,LA(Hw,Ow("gl_ViewID_OVR"))).renderOutput(t.toneMapping,t.currentColorSpace):Pw(e,Hw).renderOutput(t.toneMapping,t.currentColorSpace);return uI.set(e,n),i}updateBefore(e){const t=e.getNodeBuilderState();for(const n of t.updateBeforeNodes)this.getNodeFrameForRender(e).updateBeforeNode(n)}updateAfter(e){const t=e.getNodeBuilderState();for(const n of t.updateAfterNodes)this.getNodeFrameForRender(e).updateAfterNode(n)}updateForCompute(e){const t=this.getNodeFrame(),n=this.getForCompute(e);for(const e of n.updateNodes)t.updateNode(e)}updateForRender(e){const t=this.getNodeFrameForRender(e),n=e.getNodeBuilderState();for(const e of n.updateNodes)t.updateNode(e)}needsRefresh(e){const t=this.getNodeFrameForRender(e);return e.getMonitor().needsRefresh(e,t)}dispose(){super.dispose(),this.nodeFrame=new XD,this.nodeBuilderCache=new Map,this.cacheLib={}}}const fI=new Il;class pI{constructor(e=null){this.version=0,this.clipIntersection=null,this.cacheKey="",this.shadowPass=!1,this.viewNormalMatrix=new Ps,this.clippingGroupContexts=new WeakMap,this.intersectionPlanes=[],this.unionPlanes=[],this.parentVersion=null,null!==e&&(this.viewNormalMatrix=e.viewNormalMatrix,this.clippingGroupContexts=e.clippingGroupContexts,this.shadowPass=e.shadowPass,this.viewMatrix=e.viewMatrix)}projectPlanes(e,t,n){const i=e.length;for(let r=0;r<i;r++){fI.copy(e[r]).applyMatrix4(this.viewMatrix,this.viewNormalMatrix);const i=t[n+r],s=fI.normal;i.x=-s.x,i.y=-s.y,i.z=-s.z,i.w=fI.constant}}updateGlobal(e,t){this.shadowPass=null!==e.overrideMaterial&&e.overrideMaterial.isShadowPassMaterial,this.viewMatrix=t.matrixWorldInverse,this.viewNormalMatrix.getNormalMatrix(this.viewMatrix)}update(e,t){let n=!1;e.version!==this.parentVersion&&(this.intersectionPlanes=Array.from(e.intersectionPlanes),this.unionPlanes=Array.from(e.unionPlanes),this.parentVersion=e.version),this.clipIntersection!==t.clipIntersection&&(this.clipIntersection=t.clipIntersection,this.clipIntersection?this.unionPlanes.length=e.unionPlanes.length:this.intersectionPlanes.length=e.intersectionPlanes.length);const i=t.clippingPlanes,r=i.length;let s,o;if(this.clipIntersection?(s=this.intersectionPlanes,o=e.intersectionPlanes.length):(s=this.unionPlanes,o=e.unionPlanes.length),s.length!==o+r){s.length=o+r;for(let e=0;e<r;e++)s[o+e]=new Js;n=!0}this.projectPlanes(i,s,o),n&&(this.version++,this.cacheKey=`${this.intersectionPlanes.length}:${this.unionPlanes.length}`)}getGroupContext(e){if(this.shadowPass&&!e.clipShadows)return this;let t=this.clippingGroupContexts.get(e);return void 0===t&&(t=new pI(this),this.clippingGroupContexts.set(e,t)),t.update(this,e),t}get unionClippingCount(){return this.unionPlanes.length}}class gI{constructor(e,t){this.bundleGroup=e,this.camera=t}}const mI=[];class vI{constructor(){this.bundles=new zP}get(e,t){const n=this.bundles;mI[0]=e,mI[1]=t;let i=n.get(mI);return void 0===i&&(i=new gI(e,t),n.set(mI,i)),mI.length=0,i}dispose(){this.bundles=new zP}}class AI{constructor(){this.lightNodes=new WeakMap,this.materialNodes=new Map,this.toneMappingNodes=new Map}fromMaterial(e){if(e.isNodeMaterial)return e;let t=null;const n=this.getMaterialNodeClass(e.type);if(null!==n){t=new n;for(const n in e)t[n]=e[n]}return t}addToneMapping(e,t){this.addType(e,t,this.toneMappingNodes)}getToneMappingFunction(e){return this.toneMappingNodes.get(e)||null}getMaterialNodeClass(e){return this.materialNodes.get(e)||null}addMaterial(e,t){this.addType(e,t,this.materialNodes)}getLightNodeClass(e){return this.lightNodes.get(e)||null}addLight(e,t){this.addClass(e,t,this.lightNodes)}addType(e,t,n){if(n.has(t))console.warn(`Redefinition of node ${t}`);else{if("function"!=typeof e)throw new Error(`Node class ${e.name} is not a class.`);if("function"==typeof t||"object"==typeof t)throw new Error(`Base class ${t} is not a class.`);n.set(t,e)}}addClass(e,t,n){if(n.has(t))console.warn(`Redefinition of node ${t.name}`);else{if("function"!=typeof e)throw new Error(`Node class ${e.name} is not a class.`);if("function"!=typeof t)throw new Error(`Base class ${t.name} is not a class.`);n.set(t,e)}}}const xI=new xB,yI=[];class bI extends zP{constructor(){super()}createNode(e=[]){return(new xB).setLights(e)}getNode(e,t){if(e.isQuadMesh)return xI;yI[0]=e,yI[1]=t;let n=this.get(yI);return void 0===n&&(n=this.createNode(),this.set(yI,n)),yI.length=0,n}}class wI extends Ks{constructor(e=1,t=1,n={}){super(e,t,n),this.isXRRenderTarget=!0,this._hasExternalTextures=!1,this._autoAllocateDepthBuffer=!0,this._isOpaqueFramebuffer=!1}copy(e){return super.copy(e),this._hasExternalTextures=e._hasExternalTextures,this._autoAllocateDepthBuffer=e._autoAllocateDepthBuffer,this._isOpaqueFramebuffer=e._isOpaqueFramebuffer,this}}const CI=new Es,MI=new Es;class EI extends ds{constructor(e,t=!1){super(),this.enabled=!1,this.isPresenting=!1,this.cameraAutoUpdate=!0,this._renderer=e,this._cameraL=new pl,this._cameraL.viewport=new Js,this._cameraR=new pl,this._cameraR.viewport=new Js,this._cameras=[this._cameraL,this._cameraR],this._cameraXR=new xc,this._currentDepthNear=null,this._currentDepthFar=null,this._controllers=[],this._controllerInputSources=[],this._xrRenderTarget=null,this._layers=[],this._sessionUsesLayers=!1,this._supportsGlBinding="undefined"!=typeof XRWebGLBinding,this._frameBufferTargets=null,this._createXRLayer=BI.bind(this),this._gl=null,this._currentAnimationContext=null,this._currentAnimationLoop=null,this._currentPixelRatio=null,this._currentSize=new Cs,this._onSessionEvent=SI.bind(this),this._onSessionEnd=PI.bind(this),this._onInputSourcesChange=NI.bind(this),this._onAnimationFrame=DI.bind(this),this._referenceSpace=null,this._referenceSpaceType="local-floor",this._customReferenceSpace=null,this._framebufferScaleFactor=1,this._foveation=1,this._session=null,this._glBaseLayer=null,this._glBinding=null,this._glProjLayer=null,this._xrFrame=null,this._supportsLayers=this._supportsGlBinding&&"createProjectionLayer"in XRWebGLBinding.prototype,this._useMultiviewIfPossible=t,this._useMultiview=!1}getController(e){return this._getController(e).getTargetRaySpace()}getControllerGrip(e){return this._getController(e).getGripSpace()}getHand(e){return this._getController(e).getHandSpace()}getFoveation(){if(null!==this._glProjLayer||null!==this._glBaseLayer)return this._foveation}setFoveation(e){this._foveation=e,null!==this._glProjLayer&&(this._glProjLayer.fixedFoveation=e),null!==this._glBaseLayer&&void 0!==this._glBaseLayer.fixedFoveation&&(this._glBaseLayer.fixedFoveation=e)}getFramebufferScaleFactor(){return this._framebufferScaleFactor}setFramebufferScaleFactor(e){this._framebufferScaleFactor=e,!0===this.isPresenting&&console.warn("THREE.XRManager: Cannot change framebuffer scale while presenting.")}getReferenceSpaceType(){return this._referenceSpaceType}setReferenceSpaceType(e){this._referenceSpaceType=e,!0===this.isPresenting&&console.warn("THREE.XRManager: Cannot change reference space type while presenting.")}getReferenceSpace(){return this._customReferenceSpace||this._referenceSpace}setReferenceSpace(e){this._customReferenceSpace=e}getCamera(){return this._cameraXR}getEnvironmentBlendMode(){if(null!==this._session)return this._session.environmentBlendMode}getBinding(){return null===this._glBinding&&this._supportsGlBinding&&(this._glBinding=new XRWebGLBinding(this._session,this._gl)),this._glBinding}getFrame(){return this._xrFrame}useMultiview(){return this._useMultiview}createQuadLayer(e,t,n,i,r,s,o,a={}){const l=new xu(e,t),u=new wI(r,s,{format:rr,type:Gi,depthTexture:new _l(r,s,a.stencil?$i:Yi,void 0,void 0,void 0,void 0,void 0,void 0,a.stencil?or:sr),stencilBuffer:a.stencil,resolveDepthBuffer:!1,resolveStencilBuffer:!1});u._autoAllocateDepthBuffer=!0;const c=new Ma({color:16777215,side:0});c.map=u.texture,c.map.offset.y=1,c.map.repeat.y=-1;const d=new nl(l,c);d.position.copy(n),d.quaternion.copy(i);const h={type:"quad",width:e,height:t,translation:n,quaternion:i,pixelwidth:r,pixelheight:s,plane:d,material:c,rendercall:o,renderTarget:u};if(this._layers.push(h),null!==this._session){h.plane.material=new Ma({color:16777215,side:0}),h.plane.material.blending=5,h.plane.material.blendEquation=Mi,h.plane.material.blendSrc=Ei,h.plane.material.blendDst=Ei,h.xrlayer=this._createXRLayer(h);const e=this._session.renderState.layers;e.unshift(h.xrlayer),this._session.updateRenderState({layers:e})}else u.isXRRenderTarget=!1;return d}createCylinderLayer(e,t,n,i,r,s,o,a,l={}){const u=new eu(e,e,e*t/n,64,64,!0,Math.PI-t/2,t),c=new wI(s,o,{format:rr,type:Gi,depthTexture:new _l(s,o,l.stencil?$i:Yi,void 0,void 0,void 0,void 0,void 0,void 0,l.stencil?or:sr),stencilBuffer:l.stencil,resolveDepthBuffer:!1,resolveStencilBuffer:!1});c._autoAllocateDepthBuffer=!0;const d=new Ma({color:16777215,side:1});d.map=c.texture,d.map.offset.y=1,d.map.repeat.y=-1;const h=new nl(u,d);h.position.copy(i),h.quaternion.copy(r);const f={type:"cylinder",radius:e,centralAngle:t,aspectratio:n,translation:i,quaternion:r,pixelwidth:s,pixelheight:o,plane:h,material:d,rendercall:a,renderTarget:c};if(this._layers.push(f),null!==this._session){f.plane.material=new Ma({color:16777215,side:1}),f.plane.material.blending=5,f.plane.material.blendEquation=Mi,f.plane.material.blendSrc=Ei,f.plane.material.blendDst=Ei,f.xrlayer=this._createXRLayer(f);const e=this._session.renderState.layers;e.unshift(f.xrlayer),this._session.updateRenderState({layers:e})}else c.isXRRenderTarget=!1;return h}renderLayers(){const e=new Es,t=new Ms,n=this._renderer,i=this.isPresenting,r=n.getOutputRenderTarget(),s=n._frameBufferTarget;this.isPresenting=!1;const o=new Cs;n.getSize(o);const a=n._quad;for(const i of this._layers)if(i.renderTarget.isXRRenderTarget=null!==this._session,i.renderTarget._hasExternalTextures=i.renderTarget.isXRRenderTarget,i.renderTarget.isXRRenderTarget&&this._sessionUsesLayers){i.xrlayer.transform=new XRRigidTransform(i.plane.getWorldPosition(e),i.plane.getWorldQuaternion(t));const r=this._glBinding.getSubImage(i.xrlayer,this._xrFrame);n.backend.setXRRenderTargetTextures(i.renderTarget,r.colorTexture,void 0),n._setXRLayerSize(i.renderTarget.width,i.renderTarget.height),n.setOutputRenderTarget(i.renderTarget),n.setRenderTarget(null),n._frameBufferTarget=null,this._frameBufferTargets||(this._frameBufferTargets=new WeakMap);const{frameBufferTarget:s,quad:o}=this._frameBufferTargets.get(i.renderTarget)||{frameBufferTarget:null,quad:null};s?(n._frameBufferTarget=s,n._quad=o):(n._quad=new PN(new _E),this._frameBufferTargets.set(i.renderTarget,{frameBufferTarget:n._getFrameBufferTarget(),quad:n._quad})),i.rendercall(),n._frameBufferTarget=null}else n.setRenderTarget(i.renderTarget),i.rendercall();n.setRenderTarget(null),n.setOutputRenderTarget(r),n._frameBufferTarget=s,n._setXRLayerSize(o.x,o.y),n._quad=a,this.isPresenting=i}getSession(){return this._session}async setSession(e){const t=this._renderer,n=t.backend;this._gl=t.getContext();const i=this._gl,r=i.getContextAttributes();if(this._session=e,null!==e){if(!0===n.isWebGPUBackend)throw new Error('THREE.XRManager: XR is currently not supported with a WebGPU backend. Use WebGL by passing "{ forceWebGL: true }" to the constructor of the renderer.');if(e.addEventListener("select",this._onSessionEvent),e.addEventListener("selectstart",this._onSessionEvent),e.addEventListener("selectend",this._onSessionEvent),e.addEventListener("squeeze",this._onSessionEvent),e.addEventListener("squeezestart",this._onSessionEvent),e.addEventListener("squeezeend",this._onSessionEvent),e.addEventListener("end",this._onSessionEnd),e.addEventListener("inputsourceschange",this._onInputSourcesChange),await n.makeXRCompatible(),this._currentPixelRatio=t.getPixelRatio(),t.getSize(this._currentSize),this._currentAnimationContext=t._animation.getContext(),this._currentAnimationLoop=t._animation.getAnimationLoop(),t._animation.stop(),!0===this._supportsLayers){let n=null,s=null,o=null;t.depth&&(o=t.stencil?i.DEPTH24_STENCIL8:i.DEPTH_COMPONENT24,n=t.stencil?or:sr,s=t.stencil?$i:Yi);const a={colorFormat:i.RGBA8,depthFormat:o,scaleFactor:this._framebufferScaleFactor,clearOnAccess:!1};this._useMultiviewIfPossible&&t.hasFeature("OVR_multiview2")&&(a.textureType="texture-array",this._useMultiview=!0),this._glBinding=this.getBinding();const l=this._glBinding.createProjectionLayer(a),u=[l];this._glProjLayer=l,t.setPixelRatio(1),t._setXRLayerSize(l.textureWidth,l.textureHeight);const c=this._useMultiview?2:1,d=new _l(l.textureWidth,l.textureHeight,s,void 0,void 0,void 0,void 0,void 0,void 0,n,c);if(this._xrRenderTarget=new wI(l.textureWidth,l.textureHeight,{format:rr,type:Gi,colorSpace:t.outputColorSpace,depthTexture:d,stencilBuffer:t.stencil,samples:r.antialias?4:0,resolveDepthBuffer:!1===l.ignoreDepthValues,resolveStencilBuffer:!1===l.ignoreDepthValues,depth:this._useMultiview?2:1,multiview:this._useMultiview}),this._xrRenderTarget._hasExternalTextures=!0,this._xrRenderTarget.depth=this._useMultiview?2:1,this._sessionUsesLayers=e.enabledFeatures.includes("layers"),this._referenceSpace=await e.requestReferenceSpace(this.getReferenceSpaceType()),this._sessionUsesLayers)for(const e of this._layers)e.plane.material=new Ma({color:16777215,side:"cylinder"===e.type?1:0}),e.plane.material.blending=5,e.plane.material.blendEquation=Mi,e.plane.material.blendSrc=Ei,e.plane.material.blendDst=Ei,e.xrlayer=this._createXRLayer(e),u.unshift(e.xrlayer);e.updateRenderState({layers:u})}else{const n={antialias:t.samples>0,alpha:!0,depth:t.depth,stencil:t.stencil,framebufferScaleFactor:this.getFramebufferScaleFactor()},r=new XRWebGLLayer(e,i,n);this._glBaseLayer=r,e.updateRenderState({baseLayer:r}),t.setPixelRatio(1),t._setXRLayerSize(r.framebufferWidth,r.framebufferHeight),this._xrRenderTarget=new wI(r.framebufferWidth,r.framebufferHeight,{format:rr,type:Gi,colorSpace:t.outputColorSpace,stencilBuffer:t.stencil,resolveDepthBuffer:!1===r.ignoreDepthValues,resolveStencilBuffer:!1===r.ignoreDepthValues}),this._xrRenderTarget._isOpaqueFramebuffer=!0,this._referenceSpace=await e.requestReferenceSpace(this.getReferenceSpaceType())}this.setFoveation(this.getFoveation()),t._animation.setAnimationLoop(this._onAnimationFrame),t._animation.setContext(e),t._animation.start(),this.isPresenting=!0,this.dispatchEvent({type:"sessionstart"})}}updateCamera(e){const t=this._session;if(null===t)return;const n=e.near,i=e.far,r=this._cameraXR,s=this._cameraL,o=this._cameraR;r.near=o.near=s.near=n,r.far=o.far=s.far=i,r.isMultiViewCamera=this._useMultiview,this._currentDepthNear===r.near&&this._currentDepthFar===r.far||(t.updateRenderState({depthNear:r.near,depthFar:r.far}),this._currentDepthNear=r.near,this._currentDepthFar=r.far),r.layers.mask=6|e.layers.mask,s.layers.mask=3&r.layers.mask,o.layers.mask=5&r.layers.mask;const a=e.parent,l=r.cameras;TI(r,a);for(let e=0;e<l.length;e++)TI(l[e],a);2===l.length?function(e,t,n){CI.setFromMatrixPosition(t.matrixWorld),MI.setFromMatrixPosition(n.matrixWorld);const i=CI.distanceTo(MI),r=t.projectionMatrix.elements,s=n.projectionMatrix.elements,o=r[14]/(r[10]-1),a=r[14]/(r[10]+1),l=(r[9]+1)/r[5],u=(r[9]-1)/r[5],c=(r[8]-1)/r[0],d=(s[8]+1)/s[0],h=o*c,f=o*d,p=i/(-c+d),g=p*-c;if(t.matrixWorld.decompose(e.position,e.quaternion,e.scale),e.translateX(g),e.translateZ(p),e.matrixWorld.compose(e.position,e.quaternion,e.scale),e.matrixWorldInverse.copy(e.matrixWorld).invert(),-1===r[10])e.projectionMatrix.copy(t.projectionMatrix),e.projectionMatrixInverse.copy(t.projectionMatrixInverse);else{const t=o+p,n=a+p,r=h-g,s=f+(i-g),c=l*a/n*t,d=u*a/n*t;e.projectionMatrix.makePerspective(r,s,c,d,t,n),e.projectionMatrixInverse.copy(e.projectionMatrix).invert()}}(r,s,o):r.projectionMatrix.copy(s.projectionMatrix),function(e,t,n){null===n?e.matrix.copy(t.matrixWorld):(e.matrix.copy(n.matrixWorld),e.matrix.invert(),e.matrix.multiply(t.matrixWorld));e.matrix.decompose(e.position,e.quaternion,e.scale),e.updateMatrixWorld(!0),e.projectionMatrix.copy(t.projectionMatrix),e.projectionMatrixInverse.copy(t.projectionMatrixInverse),e.isPerspectiveCamera&&(e.fov=2*gs*Math.atan(1/e.projectionMatrix.elements[5]),e.zoom=1)}(e,r,a)}_getController(e){let t=this._controllers[e];return void 0===t&&(t=new bl,this._controllers[e]=t),t}}function TI(e,t){null===t?e.matrixWorld.copy(e.matrix):e.matrixWorld.multiplyMatrices(t.matrixWorld,e.matrix),e.matrixWorldInverse.copy(e.matrixWorld).invert()}function SI(e){const t=this._controllerInputSources.indexOf(e.inputSource);if(-1===t)return;const n=this._controllers[t];if(void 0!==n){const t=this.getReferenceSpace();n.update(e.inputSource,e.frame,t),n.dispatchEvent({type:e.type,data:e.inputSource})}}function PI(){const e=this._session,t=this._renderer;e.removeEventListener("select",this._onSessionEvent),e.removeEventListener("selectstart",this._onSessionEvent),e.removeEventListener("selectend",this._onSessionEvent),e.removeEventListener("squeeze",this._onSessionEvent),e.removeEventListener("squeezestart",this._onSessionEvent),e.removeEventListener("squeezeend",this._onSessionEvent),e.removeEventListener("end",this._onSessionEnd),e.removeEventListener("inputsourceschange",this._onInputSourcesChange);for(let e=0;e<this._controllers.length;e++){const t=this._controllerInputSources[e];null!==t&&(this._controllerInputSources[e]=null,this._controllers[e].disconnect(t))}if(this._currentDepthNear=null,this._currentDepthFar=null,t._resetXRState(),this._session=null,this._xrRenderTarget=null,!0===this._sessionUsesLayers)for(const e of this._layers)e.renderTarget=new wI(e.pixelwidth,e.pixelheight,{format:rr,type:Gi,depthTexture:new _l(e.pixelwidth,e.pixelheight,e.stencilBuffer?$i:Yi,void 0,void 0,void 0,void 0,void 0,void 0,e.stencilBuffer?or:sr),stencilBuffer:e.stencilBuffer,resolveDepthBuffer:!1,resolveStencilBuffer:!1}),e.renderTarget.isXRRenderTarget=!1,e.plane.material=e.material,e.material.map=e.renderTarget.texture,e.material.map.offset.y=1,e.material.map.repeat.y=-1,delete e.xrlayer;this.isPresenting=!1,this._useMultiview=!1,t._animation.stop(),t._animation.setAnimationLoop(this._currentAnimationLoop),t._animation.setContext(this._currentAnimationContext),t._animation.start(),t.setPixelRatio(this._currentPixelRatio),t.setSize(this._currentSize.width,this._currentSize.height,!1),this.dispatchEvent({type:"sessionend"})}function NI(e){const t=this._controllers,n=this._controllerInputSources;for(let i=0;i<e.removed.length;i++){const r=e.removed[i],s=n.indexOf(r);s>=0&&(n[s]=null,t[s].disconnect(r))}for(let i=0;i<e.added.length;i++){const r=e.added[i];let s=n.indexOf(r);if(-1===s){for(let e=0;e<t.length;e++){if(e>=n.length){n.push(r),s=e;break}if(null===n[e]){n[e]=r,s=e;break}}if(-1===s)break}const o=t[s];o&&o.connect(r)}}function BI(e){return"quad"===e.type?this._glBinding.createQuadLayer({transform:new XRRigidTransform(e.translation,e.quaternion),width:e.width/2,height:e.height/2,space:this._referenceSpace,viewPixelWidth:e.pixelwidth,viewPixelHeight:e.pixelheight,clearOnAccess:!1}):this._glBinding.createCylinderLayer({transform:new XRRigidTransform(e.translation,e.quaternion),radius:e.radius,centralAngle:e.centralAngle,aspectRatio:e.aspectRatio,space:this._referenceSpace,viewPixelWidth:e.pixelwidth,viewPixelHeight:e.pixelheight,clearOnAccess:!1})}function DI(e,t){if(void 0===t)return;const n=this._cameraXR,i=this._renderer,r=i.backend,s=this._glBaseLayer,o=this.getReferenceSpace(),a=t.getViewerPose(o);if(this._xrFrame=t,null!==a){const e=a.views;null!==this._glBaseLayer&&r.setXRTarget(s.framebuffer);let t=!1;e.length!==n.cameras.length&&(n.cameras.length=0,t=!0);for(let i=0;i<e.length;i++){const o=e[i];let a;if(!0===this._supportsLayers){const e=this._glBinding.getViewSubImage(this._glProjLayer,o);a=e.viewport,0===i&&r.setXRRenderTargetTextures(this._xrRenderTarget,e.colorTexture,this._glProjLayer.ignoreDepthValues&&!this._useMultiview?void 0:e.depthStencilTexture)}else a=s.getViewport(o);let l=this._cameras[i];void 0===l&&(l=new pl,l.layers.enable(i),l.viewport=new Js,this._cameras[i]=l),l.matrix.fromArray(o.transform.matrix),l.matrix.decompose(l.position,l.quaternion,l.scale),l.projectionMatrix.fromArray(o.projectionMatrix),l.projectionMatrixInverse.copy(l.projectionMatrix).invert(),l.viewport.set(a.x,a.y,a.width,a.height),0===i&&(n.matrix.copy(l.matrix),n.matrix.decompose(n.position,n.quaternion,n.scale)),!0===t&&n.cameras.push(l)}i.setOutputRenderTarget(this._xrRenderTarget)}for(let e=0;e<this._controllers.length;e++){const n=this._controllerInputSources[e],i=this._controllers[e];null!==n&&void 0!==i&&i.update(n,t,o)}this._currentAnimationLoop&&this._currentAnimationLoop(e,t),t.detectedPlanes&&this.dispatchEvent({type:"planesdetected",data:t}),this._xrFrame=null}const II=new wl,LI=new Cs,jI=new Js,OI=new zl,zI=new Fl,RI=new Po,kI=new Js;class FI{constructor(e,t={}){this.isRenderer=!0;const{logarithmicDepthBuffer:n=!1,alpha:i=!0,depth:r=!0,stencil:s=!1,antialias:o=!1,samples:a=0,getFallback:l=null,colorBufferType:u=Ki,multiview:c=!1}=t;this.domElement=e.getDomElement(),this.backend=e,this.samples=a||!0===o?4:0,this.autoClear=!0,this.autoClearColor=!0,this.autoClearDepth=!0,this.autoClearStencil=!0,this.alpha=i,this.logarithmicDepthBuffer=n,this.outputColorSpace=qr,this.toneMapping=0,this.toneMappingExposure=1,this.sortObjects=!0,this.depth=r,this.stencil=s,this.info=new qP,this.overrideNodes={modelViewMatrix:null,modelNormalViewMatrix:null},this.library=new AI,this.lighting=new bI,this._getFallback=l,this._pixelRatio=1,this._width=this.domElement.width,this._height=this.domElement.height,this._viewport=new Js(0,0,this._width,this._height),this._scissor=new Js(0,0,this._width,this._height),this._scissorTest=!1,this._attributes=null,this._geometries=null,this._nodes=null,this._animation=null,this._bindings=null,this._objects=null,this._pipelines=null,this._bundles=null,this._renderLists=null,this._renderContexts=null,this._textures=null,this._background=null,this._quad=new PN(new _E),this._quad.material.name="Renderer_output",this._currentRenderContext=null,this._opaqueSort=null,this._transparentSort=null,this._frameBufferTarget=null;const d=!0===this.alpha?0:1;this._clearColor=new yN(0,0,0,d),this._clearDepth=1,this._clearStencil=0,this._renderTarget=null,this._activeCubeFace=0,this._activeMipmapLevel=0,this._outputRenderTarget=null,this._mrt=null,this._renderObjectFunction=null,this._currentRenderObjectFunction=null,this._currentRenderBundle=null,this._handleObjectFunction=this._renderObjectDirect,this._isDeviceLost=!1,this.onDeviceLost=this._onDeviceLost,this._colorBufferType=u,this._initialized=!1,this._initPromise=null,this._compilationPromises=null,this.transparent=!0,this.opaque=!0,this.shadowMap={enabled:!1,type:1},this.xr=new EI(this,c),this.debug={checkShaderErrors:!0,onShaderError:null,getShaderAsync:async(e,t,n)=>{await this.compileAsync(e,t);const i=this._renderLists.get(e,t),r=this._renderContexts.get(e,t,this._renderTarget),s=e.overrideMaterial||n.material,o=this._objects.get(n,s,e,t,i.lightsNode,r,r.clippingContext),{fragmentShader:a,vertexShader:l}=o.getNodeBuilderState();return{fragmentShader:a,vertexShader:l}}}}async init(){if(this._initialized)throw new Error("Renderer: Backend has already been initialized.");return null!==this._initPromise||(this._initPromise=new Promise((async(e,t)=>{let n=this.backend;try{await n.init(this)}catch(e){if(null===this._getFallback)return void t(e);try{this.backend=n=this._getFallback(e),await n.init(this)}catch(e){return void t(e)}}this._nodes=new hI(this,n),this._animation=new OP(this._nodes,this.info),this._attributes=new ZP(n),this._background=new uD(this,this._nodes),this._geometries=new KP(this._attributes,this.info),this._textures=new xN(this,n,this.info),this._pipelines=new iN(n,this._nodes),this._bindings=new rN(n,this._nodes,this._textures,this._attributes,this._pipelines,this.info),this._objects=new HP(this,this._nodes,this._geometries,this._pipelines,this._bindings,this.info),this._renderLists=new cN(this.lighting),this._bundles=new vI,this._renderContexts=new vN,this._animation.start(),this._initialized=!0,e(this)}))),this._initPromise}get coordinateSystem(){return this.backend.coordinateSystem}async compileAsync(e,t,n=null){if(!0===this._isDeviceLost)return;!1===this._initialized&&await this.init();const i=this._nodes.nodeFrame,r=i.renderId,s=this._currentRenderContext,o=this._currentRenderObjectFunction,a=this._compilationPromises,l=!0===e.isScene?e:II;null===n&&(n=e);const u=this._renderTarget,c=this._renderContexts.get(n,t,u),d=this._activeMipmapLevel,h=[];this._currentRenderContext=c,this._currentRenderObjectFunction=this.renderObject,this._handleObjectFunction=this._createObjectPipeline,this._compilationPromises=h,i.renderId++,i.update(),c.depth=this.depth,c.stencil=this.stencil,c.clippingContext||(c.clippingContext=new pI),c.clippingContext.updateGlobal(l,t),l.onBeforeRender(this,e,t,u);const f=this._renderLists.get(e,t);if(f.begin(),this._projectObject(e,t,0,f,c.clippingContext),n!==e&&n.traverseVisible((function(e){e.isLight&&e.layers.test(t.layers)&&f.pushLight(e)})),f.finish(),null!==u){this._textures.updateRenderTarget(u,d);const e=this._textures.get(u);c.textures=e.textures,c.depthTexture=e.depthTexture}else c.textures=null,c.depthTexture=null;this._background.update(l,f,c);const p=f.opaque,g=f.transparent,m=f.transparentDoublePass,v=f.lightsNode;!0===this.opaque&&p.length>0&&this._renderObjects(p,t,l,v),!0===this.transparent&&g.length>0&&this._renderTransparents(g,m,t,l,v),i.renderId=r,this._currentRenderContext=s,this._currentRenderObjectFunction=o,this._compilationPromises=a,this._handleObjectFunction=this._renderObjectDirect,await Promise.all(h)}async renderAsync(e,t){!1===this._initialized&&await this.init(),this._renderScene(e,t)}async waitForGPU(){await this.backend.waitForGPU()}set highPrecision(e){!0===e?(this.overrideNodes.modelViewMatrix=sC,this.overrideNodes.modelNormalViewMatrix=oC):this.highPrecision&&(this.overrideNodes.modelViewMatrix=null,this.overrideNodes.modelNormalViewMatrix=null)}get highPrecision(){return this.overrideNodes.modelViewMatrix===sC&&this.overrideNodes.modelNormalViewMatrix===oC}setMRT(e){return this._mrt=e,this}getMRT(){return this._mrt}getColorBufferType(){return this._colorBufferType}_onDeviceLost(e){let t=`THREE.WebGPURenderer: ${e.api} Device Lost:\n\nMessage: ${e.message}`;e.reason&&(t+=`\nReason: ${e.reason}`),console.error(t),this._isDeviceLost=!0}_renderBundle(e,t,n){const{bundleGroup:i,camera:r,renderList:s}=e,o=this._currentRenderContext,a=this._bundles.get(i,r),l=this.backend.get(a);void 0===l.renderContexts&&(l.renderContexts=new Set);const u=i.version!==l.version,c=!1===l.renderContexts.has(o)||u;if(l.renderContexts.add(o),c){this.backend.beginBundle(o),(void 0===l.renderObjects||u)&&(l.renderObjects=[]),this._currentRenderBundle=a;const{transparentDoublePass:e,transparent:c,opaque:d}=s;!0===this.opaque&&d.length>0&&this._renderObjects(d,r,t,n),!0===this.transparent&&c.length>0&&this._renderTransparents(c,e,r,t,n),this._currentRenderBundle=null,this.backend.finishBundle(o,a),l.version=i.version}else{const{renderObjects:e}=l;for(let t=0,n=e.length;t<n;t++){const n=e[t];this._nodes.needsRefresh(n)&&(this._nodes.updateBefore(n),this._nodes.updateForRender(n),this._bindings.updateForRender(n),this._nodes.updateAfter(n))}}this.backend.addBundle(o,a)}render(e,t){if(!1===this._initialized)return console.warn("THREE.Renderer: .render() called before the backend is initialized. Try using .renderAsync() instead."),this.renderAsync(e,t);this._renderScene(e,t)}_getFrameBufferTarget(){const{currentToneMapping:e,currentColorSpace:t}=this,n=0!==e,i=t!==ks.workingColorSpace;if(!1===n&&!1===i)return null;const{width:r,height:s}=this.getDrawingBufferSize(LI),{depth:o,stencil:a}=this;let l=this._frameBufferTarget;null===l&&(l=new Ks(r,s,{depthBuffer:o,stencilBuffer:a,type:this._colorBufferType,format:rr,colorSpace:ks.workingColorSpace,generateMipmaps:!1,minFilter:Hi,magFilter:Hi,samples:this.samples}),l.isPostProcessingRenderTarget=!0,this._frameBufferTarget=l);const u=this.getOutputRenderTarget();return l.depthBuffer=o,l.stencilBuffer=a,null!==u?l.setSize(u.width,u.height,u.depth):l.setSize(r,s,1),l.viewport.copy(this._viewport),l.scissor.copy(this._scissor),l.viewport.multiplyScalar(this._pixelRatio),l.scissor.multiplyScalar(this._pixelRatio),l.scissorTest=this._scissorTest,l.multiview=null!==u&&u.multiview,l.resolveDepthBuffer=null===u||u.resolveDepthBuffer,l._autoAllocateDepthBuffer=null!==u&&u._autoAllocateDepthBuffer,l}_renderScene(e,t,n=!0){if(!0===this._isDeviceLost)return;const i=n?this._getFrameBufferTarget():null,r=this._nodes.nodeFrame,s=r.renderId,o=this._currentRenderContext,a=this._currentRenderObjectFunction,l=!0===e.isScene?e:II,u=this._renderTarget||this._outputRenderTarget,c=this._activeCubeFace,d=this._activeMipmapLevel;let h;null!==i?(h=i,this.setRenderTarget(h)):h=u;const f=this._renderContexts.get(e,t,h);this._currentRenderContext=f,this._currentRenderObjectFunction=this._renderObjectFunction||this.renderObject,this.info.calls++,this.info.render.calls++,this.info.render.frameCalls++,r.renderId=this.info.calls;const p=this.coordinateSystem,g=this.xr;if(t.coordinateSystem!==p&&!1===g.isPresenting&&(t.coordinateSystem=p,t.updateProjectionMatrix(),t.isArrayCamera))for(const e of t.cameras)e.coordinateSystem=p,e.updateProjectionMatrix();!0===e.matrixWorldAutoUpdate&&e.updateMatrixWorld(),null===t.parent&&!0===t.matrixWorldAutoUpdate&&t.updateMatrixWorld(),!0===g.enabled&&!0===g.isPresenting&&(!0===g.cameraAutoUpdate&&g.updateCamera(t),t=g.getCamera());let m=this._viewport,v=this._scissor,A=this._pixelRatio;null!==h&&(m=h.viewport,v=h.scissor,A=1),this.getDrawingBufferSize(LI),jI.set(0,0,LI.width,LI.height);const x=void 0===m.minDepth?0:m.minDepth,y=void 0===m.maxDepth?1:m.maxDepth;f.viewportValue.copy(m).multiplyScalar(A).floor(),f.viewportValue.width>>=d,f.viewportValue.height>>=d,f.viewportValue.minDepth=x,f.viewportValue.maxDepth=y,f.viewport=!1===f.viewportValue.equals(jI),f.scissorValue.copy(v).multiplyScalar(A).floor(),f.scissor=this._scissorTest&&!1===f.scissorValue.equals(jI),f.scissorValue.width>>=d,f.scissorValue.height>>=d,f.clippingContext||(f.clippingContext=new pI),f.clippingContext.updateGlobal(l,t),l.onBeforeRender(this,e,t,h);const b=t.isArrayCamera?zI:OI;t.isArrayCamera||(RI.multiplyMatrices(t.projectionMatrix,t.matrixWorldInverse),b.setFromProjectionMatrix(RI,t.coordinateSystem,t.reversedDepth));const w=this._renderLists.get(e,t);if(w.begin(),this._projectObject(e,t,0,w,f.clippingContext),w.finish(),!0===this.sortObjects&&w.sort(this._opaqueSort,this._transparentSort),null!==h){this._textures.updateRenderTarget(h,d);const e=this._textures.get(h);f.textures=e.textures,f.depthTexture=e.depthTexture,f.width=e.width,f.height=e.height,f.renderTarget=h,f.depth=h.depthBuffer,f.stencil=h.stencilBuffer}else f.textures=null,f.depthTexture=null,f.width=LI.width,f.height=LI.height,f.depth=this.depth,f.stencil=this.stencil;f.width>>=d,f.height>>=d,f.activeCubeFace=c,f.activeMipmapLevel=d,f.occlusionQueryCount=w.occlusionQueryCount,f.scissorValue.max(kI.set(0,0,0,0)),f.scissorValue.x+f.scissorValue.width>f.width&&(f.scissorValue.width=Math.max(f.width-f.scissorValue.x,0)),f.scissorValue.y+f.scissorValue.height>f.height&&(f.scissorValue.height=Math.max(f.height-f.scissorValue.y,0)),this._background.update(l,w,f),f.camera=t,this.backend.beginRender(f);const{bundles:C,lightsNode:M,transparentDoublePass:E,transparent:T,opaque:S}=w;return C.length>0&&this._renderBundles(C,l,M),!0===this.opaque&&S.length>0&&this._renderObjects(S,t,l,M),!0===this.transparent&&T.length>0&&this._renderTransparents(T,E,t,l,M),this.backend.finishRender(f),r.renderId=s,this._currentRenderContext=o,this._currentRenderObjectFunction=a,null!==i&&(this.setRenderTarget(u,c,d),this._renderOutput(h)),l.onAfterRender(this,e,t,h),f}_setXRLayerSize(e,t){this._width=e,this._height=t,this.setViewport(0,0,e,t)}_renderOutput(e){const t=this._quad;this._nodes.hasOutputChange(e.texture)&&(t.material.fragmentNode=this._nodes.getOutputNode(e.texture),t.material.needsUpdate=!0);const n=this.autoClear,i=this.xr.enabled;this.autoClear=!1,this.xr.enabled=!1,this._renderScene(t,t.camera,!1),this.autoClear=n,this.xr.enabled=i}getMaxAnisotropy(){return this.backend.getMaxAnisotropy()}getActiveCubeFace(){return this._activeCubeFace}getActiveMipmapLevel(){return this._activeMipmapLevel}async setAnimationLoop(e){!1===this._initialized&&await this.init(),this._animation.setAnimationLoop(e)}async getArrayBufferAsync(e){return await this.backend.getArrayBufferAsync(e)}getContext(){return this.backend.getContext()}getPixelRatio(){return this._pixelRatio}getDrawingBufferSize(e){return e.set(this._width*this._pixelRatio,this._height*this._pixelRatio).floor()}getSize(e){return e.set(this._width,this._height)}setPixelRatio(e=1){this._pixelRatio!==e&&(this._pixelRatio=e,this.setSize(this._width,this._height,!1))}setDrawingBufferSize(e,t,n){this.xr&&this.xr.isPresenting||(this._width=e,this._height=t,this._pixelRatio=n,this.domElement.width=Math.floor(e*n),this.domElement.height=Math.floor(t*n),this.setViewport(0,0,e,t),this._initialized&&this.backend.updateSize())}setSize(e,t,n=!0){this.xr&&this.xr.isPresenting||(this._width=e,this._height=t,this.domElement.width=Math.floor(e*this._pixelRatio),this.domElement.height=Math.floor(t*this._pixelRatio),!0===n&&(this.domElement.style.width=e+"px",this.domElement.style.height=t+"px"),this.setViewport(0,0,e,t),this._initialized&&this.backend.updateSize())}setOpaqueSort(e){this._opaqueSort=e}setTransparentSort(e){this._transparentSort=e}getScissor(e){const t=this._scissor;return e.x=t.x,e.y=t.y,e.width=t.width,e.height=t.height,e}setScissor(e,t,n,i){const r=this._scissor;e.isVector4?r.copy(e):r.set(e,t,n,i)}getScissorTest(){return this._scissorTest}setScissorTest(e){this._scissorTest=e,this.backend.setScissorTest(e)}getViewport(e){return e.copy(this._viewport)}setViewport(e,t,n,i,r=0,s=1){const o=this._viewport;e.isVector4?o.copy(e):o.set(e,t,n,i),o.minDepth=r,o.maxDepth=s}getClearColor(e){return e.copy(this._clearColor)}setClearColor(e,t=1){this._clearColor.set(e),this._clearColor.a=t}getClearAlpha(){return this._clearColor.a}setClearAlpha(e){this._clearColor.a=e}getClearDepth(){return this._clearDepth}setClearDepth(e){this._clearDepth=e}getClearStencil(){return this._clearStencil}setClearStencil(e){this._clearStencil=e}isOccluded(e){const t=this._currentRenderContext;return t&&this.backend.isOccluded(t,e)}clear(e=!0,t=!0,n=!0){if(!1===this._initialized)return console.warn("THREE.Renderer: .clear() called before the backend is initialized. Try using .clearAsync() instead."),this.clearAsync(e,t,n);const i=this._renderTarget||this._getFrameBufferTarget();let r=null;if(null!==i){this._textures.updateRenderTarget(i);const e=this._textures.get(i);r=this._renderContexts.getForClear(i),r.textures=e.textures,r.depthTexture=e.depthTexture,r.width=e.width,r.height=e.height,r.renderTarget=i,r.depth=i.depthBuffer,r.stencil=i.stencilBuffer,r.clearColorValue=this.backend.getClearColor(),r.activeCubeFace=this.getActiveCubeFace(),r.activeMipmapLevel=this.getActiveMipmapLevel()}this.backend.clear(e,t,n,r),null!==i&&null===this._renderTarget&&this._renderOutput(i)}clearColor(){return this.clear(!0,!1,!1)}clearDepth(){return this.clear(!1,!0,!1)}clearStencil(){return this.clear(!1,!1,!0)}async clearAsync(e=!0,t=!0,n=!0){!1===this._initialized&&await this.init(),this.clear(e,t,n)}async clearColorAsync(){this.clearAsync(!0,!1,!1)}async clearDepthAsync(){this.clearAsync(!1,!0,!1)}async clearStencilAsync(){this.clearAsync(!1,!1,!0)}get currentToneMapping(){return this.isOutputTarget?this.toneMapping:0}get currentColorSpace(){return this.isOutputTarget?this.outputColorSpace:ks.workingColorSpace}get isOutputTarget(){return this._renderTarget===this._outputRenderTarget||null===this._renderTarget}dispose(){!0===this._initialized&&(this.info.dispose(),this.backend.dispose(),this._animation.dispose(),this._objects.dispose(),this._pipelines.dispose(),this._nodes.dispose(),this._bindings.dispose(),this._renderLists.dispose(),this._renderContexts.dispose(),this._textures.dispose(),null!==this._frameBufferTarget&&this._frameBufferTarget.dispose(),Object.values(this.backend.timestampQueryPool).forEach((e=>{null!==e&&e.dispose()}))),this.setRenderTarget(null),this.setAnimationLoop(null)}setRenderTarget(e,t=0,n=0){this._renderTarget=e,this._activeCubeFace=t,this._activeMipmapLevel=n}getRenderTarget(){return this._renderTarget}setOutputRenderTarget(e){this._outputRenderTarget=e}getOutputRenderTarget(){return this._outputRenderTarget}_resetXRState(){this.backend.setXRTarget(null),this.setOutputRenderTarget(null),this.setRenderTarget(null),this._frameBufferTarget.dispose(),this._frameBufferTarget=null}setRenderObjectFunction(e){this._renderObjectFunction=e}getRenderObjectFunction(){return this._renderObjectFunction}compute(e,t=null){if(!0===this._isDeviceLost)return;if(!1===this._initialized)return console.warn("THREE.Renderer: .compute() called before the backend is initialized. Try using .computeAsync() instead."),this.computeAsync(e);const n=this._nodes.nodeFrame,i=n.renderId;this.info.calls++,this.info.compute.calls++,this.info.compute.frameCalls++,n.renderId=this.info.calls;const r=this.backend,s=this._pipelines,o=this._bindings,a=this._nodes,l=Array.isArray(e)?e:[e];if(void 0===l[0]||!0!==l[0].isComputeNode)throw new Error("THREE.Renderer: .compute() expects a ComputeNode.");r.beginCompute(e);for(const n of l){if(!1===s.has(n)){const e=()=>{n.removeEventListener("dispose",e),s.delete(n),o.delete(n),a.delete(n)};n.addEventListener("dispose",e);const t=n.onInitFunction;null!==t&&t.call(n,{renderer:this})}a.updateForCompute(n),o.updateForCompute(n);const i=o.getForCompute(n),l=s.getForCompute(n,i);r.compute(e,n,i,l,t)}r.finishCompute(e),n.renderId=i}async computeAsync(e,t=null){!1===this._initialized&&await this.init(),this.compute(e,t)}async hasFeatureAsync(e){return!1===this._initialized&&await this.init(),this.backend.hasFeature(e)}async resolveTimestampsAsync(e="render"){return!1===this._initialized&&await this.init(),this.backend.resolveTimestampsAsync(e)}hasFeature(e){return!1===this._initialized?(console.warn("THREE.Renderer: .hasFeature() called before the backend is initialized. Try using .hasFeatureAsync() instead."),!1):this.backend.hasFeature(e)}hasInitialized(){return this._initialized}async initTextureAsync(e){!1===this._initialized&&await this.init(),this._textures.updateTexture(e)}initTexture(e){!1===this._initialized&&console.warn("THREE.Renderer: .initTexture() called before the backend is initialized. Try using .initTextureAsync() instead."),this._textures.updateTexture(e)}copyFramebufferToTexture(e,t=null){if(null!==t)if(t.isVector2)t=kI.set(t.x,t.y,e.image.width,e.image.height).floor();else{if(!t.isVector4)return void console.error("THREE.Renderer.copyFramebufferToTexture: Invalid rectangle.");t=kI.copy(t).floor()}else t=kI.set(0,0,e.image.width,e.image.height);let n,i=this._currentRenderContext;null!==i?n=i.renderTarget:(n=this._renderTarget||this._getFrameBufferTarget(),null!==n&&(this._textures.updateRenderTarget(n),i=this._textures.get(n))),this._textures.updateTexture(e,{renderTarget:n}),this.backend.copyFramebufferToTexture(e,i,t)}copyTextureToTexture(e,t,n=null,i=null,r=0,s=0){this._textures.updateTexture(e),this._textures.updateTexture(t),this.backend.copyTextureToTexture(e,t,n,i,r,s)}async readRenderTargetPixelsAsync(e,t,n,i,r,s=0,o=0){return this.backend.copyTextureToBuffer(e.textures[s],t,n,i,r,o)}_projectObject(e,t,n,i,r){if(!1===e.visible)return;if(e.layers.test(t.layers))if(e.isGroup)n=e.renderOrder,e.isClippingGroup&&e.enabled&&(r=r.getGroupContext(e));else if(e.isLOD)!0===e.autoUpdate&&e.update(t);else if(e.isLight)i.pushLight(e);else if(e.isSprite){const s=t.isArrayCamera?zI:OI;if(!e.frustumCulled||s.intersectsSprite(e,t)){!0===this.sortObjects&&kI.setFromMatrixPosition(e.matrixWorld).applyMatrix4(RI);const{geometry:t,material:s}=e;s.visible&&i.push(e,t,s,n,kI.z,null,r)}}else if(e.isLineLoop)console.error("THREE.Renderer: Objects of type THREE.LineLoop are not supported. Please use THREE.Line or THREE.LineSegments.");else if(e.isMesh||e.isLine||e.isPoints){const s=t.isArrayCamera?zI:OI;if(!e.frustumCulled||s.intersectsObject(e,t)){const{geometry:t,material:s}=e;if(!0===this.sortObjects&&(null===t.boundingSphere&&t.computeBoundingSphere(),kI.copy(t.boundingSphere.center).applyMatrix4(e.matrixWorld).applyMatrix4(RI)),Array.isArray(s)){const o=t.groups;for(let a=0,l=o.length;a<l;a++){const l=o[a],u=s[l.materialIndex];u&&u.visible&&i.push(e,t,u,n,kI.z,l,r)}}else s.visible&&i.push(e,t,s,n,kI.z,null,r)}}if(!0===e.isBundleGroup&&void 0!==this.backend.beginBundle){const n=i;(i=this._renderLists.get(e,t)).begin(),n.pushBundle({bundleGroup:e,camera:t,renderList:i}),i.finish()}const s=e.children;for(let e=0,o=s.length;e<o;e++)this._projectObject(s[e],t,n,i,r)}_renderBundles(e,t,n){for(const i of e)this._renderBundle(i,t,n)}_renderTransparents(e,t,n,i,r){if(t.length>0){for(const{material:e}of t)e.side=1;this._renderObjects(t,n,i,r,"backSide");for(const{material:e}of t)e.side=0;this._renderObjects(e,n,i,r);for(const{material:e}of t)e.side=2}else this._renderObjects(e,n,i,r)}_renderObjects(e,t,n,i,r=null){for(let s=0,o=e.length;s<o;s++){const{object:o,geometry:a,material:l,group:u,clippingContext:c}=e[s];this._currentRenderObjectFunction(o,n,t,a,l,u,i,c,r)}}renderObject(e,t,n,i,r,s,o,a=null,l=null){let u,c,d;if(e.onBeforeRender(this,t,n,i,r,s),!0===r.allowOverride&&null!==t.overrideMaterial){const e=t.overrideMaterial;r.positionNode&&r.positionNode.isNode&&(u=e.positionNode,e.positionNode=r.positionNode),e.alphaTest=r.alphaTest,e.alphaMap=r.alphaMap,e.transparent=r.transparent||r.transmission>0,e.isShadowPassMaterial&&(e.side=null===r.shadowSide?r.side:r.shadowSide,r.depthNode&&r.depthNode.isNode&&(d=e.depthNode,e.depthNode=r.depthNode),r.castShadowNode&&r.castShadowNode.isNode&&(c=e.colorNode,e.colorNode=r.castShadowNode),r.castShadowPositionNode&&r.castShadowPositionNode.isNode&&(u=e.positionNode,e.positionNode=r.castShadowPositionNode)),r=e}!0===r.transparent&&2===r.side&&!1===r.forceSinglePass?(r.side=1,this._handleObjectFunction(e,r,t,n,o,s,a,"backSide"),r.side=0,this._handleObjectFunction(e,r,t,n,o,s,a,l),r.side=2):this._handleObjectFunction(e,r,t,n,o,s,a,l),void 0!==u&&(t.overrideMaterial.positionNode=u),void 0!==d&&(t.overrideMaterial.depthNode=d),void 0!==c&&(t.overrideMaterial.colorNode=c),e.onAfterRender(this,t,n,i,r,s)}_renderObjectDirect(e,t,n,i,r,s,o,a){const l=this._objects.get(e,t,n,i,r,this._currentRenderContext,o,a);l.drawRange=e.geometry.drawRange,l.group=s;const u=this._nodes.needsRefresh(l);if(u&&(this._nodes.updateBefore(l),this._geometries.updateForRender(l),this._nodes.updateForRender(l),this._bindings.updateForRender(l)),this._pipelines.updateForRender(l),null!==this._currentRenderBundle){this.backend.get(this._currentRenderBundle).renderObjects.push(l),l.bundle=this._currentRenderBundle.bundleGroup}this.backend.draw(l,this.info),u&&this._nodes.updateAfter(l)}_createObjectPipeline(e,t,n,i,r,s,o,a){const l=this._objects.get(e,t,n,i,r,this._currentRenderContext,o,a);l.drawRange=e.geometry.drawRange,l.group=s,this._nodes.updateBefore(l),this._geometries.updateForRender(l),this._nodes.updateForRender(l),this._bindings.updateForRender(l),this._pipelines.getForRender(l,this._compilationPromises),this._nodes.updateAfter(l)}get compile(){return this.compileAsync}}class HI{constructor(e=""){this.name=e,this.visibility=0}setVisibility(e){this.visibility|=e}clone(){return Object.assign(new this.constructor,this)}}class UI extends HI{constructor(e,t=null){super(e),this.isBuffer=!0,this.bytesPerElement=Float32Array.BYTES_PER_ELEMENT,this._buffer=t}get byteLength(){return(e=this._buffer.byteLength)+(QP-e%QP)%QP;var e}get buffer(){return this._buffer}update(){return!0}}class XI extends UI{constructor(e,t=null){super(e,t),this.isUniformBuffer=!0}}let GI=0;class VI extends XI{constructor(e,t){super("UniformBuffer_"+GI++,e?e.value:null),this.nodeUniform=e,this.groupNode=t}get buffer(){return this.nodeUniform.value}}class WI extends XI{constructor(e){super(e),this.isUniformsGroup=!0,this._values=null,this.uniforms=[]}addUniform(e){return this.uniforms.push(e),this}removeUniform(e){const t=this.uniforms.indexOf(e);return-1!==t&&this.uniforms.splice(t,1),this}get values(){return null===this._values&&(this._values=Array.from(this.buffer)),this._values}get buffer(){let e=this._buffer;if(null===e){const t=this.byteLength;e=new Float32Array(new ArrayBuffer(t)),this._buffer=e}return e}get byteLength(){const e=this.bytesPerElement;let t=0;for(let n=0,i=this.uniforms.length;n<i;n++){const i=this.uniforms[n],r=i.boundary,s=i.itemSize*e,o=t%QP,a=o%r,l=o+a;t+=a,0!==l&&QP-l<s&&(t+=QP-l),i.offset=t/e,t+=s}return Math.ceil(t/QP)*QP}update(){let e=!1;for(const t of this.uniforms)!0===this.updateByType(t)&&(e=!0);return e}updateByType(e){return e.isNumberUniform?this.updateNumber(e):e.isVector2Uniform?this.updateVector2(e):e.isVector3Uniform?this.updateVector3(e):e.isVector4Uniform?this.updateVector4(e):e.isColorUniform?this.updateColor(e):e.isMatrix3Uniform?this.updateMatrix3(e):e.isMatrix4Uniform?this.updateMatrix4(e):void console.error("THREE.WebGPUUniformsGroup: Unsupported uniform type.",e)}updateNumber(e){let t=!1;const n=this.values,i=e.getValue(),r=e.offset,s=e.getType();if(n[r]!==i){this._getBufferForType(s)[r]=n[r]=i,t=!0}return t}updateVector2(e){let t=!1;const n=this.values,i=e.getValue(),r=e.offset,s=e.getType();if(n[r+0]!==i.x||n[r+1]!==i.y){const e=this._getBufferForType(s);e[r+0]=n[r+0]=i.x,e[r+1]=n[r+1]=i.y,t=!0}return t}updateVector3(e){let t=!1;const n=this.values,i=e.getValue(),r=e.offset,s=e.getType();if(n[r+0]!==i.x||n[r+1]!==i.y||n[r+2]!==i.z){const e=this._getBufferForType(s);e[r+0]=n[r+0]=i.x,e[r+1]=n[r+1]=i.y,e[r+2]=n[r+2]=i.z,t=!0}return t}updateVector4(e){let t=!1;const n=this.values,i=e.getValue(),r=e.offset,s=e.getType();if(n[r+0]!==i.x||n[r+1]!==i.y||n[r+2]!==i.z||n[r+4]!==i.w){const e=this._getBufferForType(s);e[r+0]=n[r+0]=i.x,e[r+1]=n[r+1]=i.y,e[r+2]=n[r+2]=i.z,e[r+3]=n[r+3]=i.w,t=!0}return t}updateColor(e){let t=!1;const n=this.values,i=e.getValue(),r=e.offset;if(n[r+0]!==i.r||n[r+1]!==i.g||n[r+2]!==i.b){const e=this.buffer;e[r+0]=n[r+0]=i.r,e[r+1]=n[r+1]=i.g,e[r+2]=n[r+2]=i.b,t=!0}return t}updateMatrix3(e){let t=!1;const n=this.values,i=e.getValue().elements,r=e.offset;if(n[r+0]!==i[0]||n[r+1]!==i[1]||n[r+2]!==i[2]||n[r+4]!==i[3]||n[r+5]!==i[4]||n[r+6]!==i[5]||n[r+8]!==i[6]||n[r+9]!==i[7]||n[r+10]!==i[8]){const e=this.buffer;e[r+0]=n[r+0]=i[0],e[r+1]=n[r+1]=i[1],e[r+2]=n[r+2]=i[2],e[r+4]=n[r+4]=i[3],e[r+5]=n[r+5]=i[4],e[r+6]=n[r+6]=i[5],e[r+8]=n[r+8]=i[6],e[r+9]=n[r+9]=i[7],e[r+10]=n[r+10]=i[8],t=!0}return t}updateMatrix4(e){let t=!1;const n=this.values,i=e.getValue().elements,r=e.offset;if(!1===function(e,t,n){for(let i=0,r=t.length;i<r;i++)if(e[n+i]!==t[i])return!1;return!0}(n,i,r)){this.buffer.set(i,r),function(e,t,n){for(let i=0,r=t.length;i<r;i++)e[n+i]=t[i]}(n,i,r),t=!0}return t}_getBufferForType(e){return"int"===e||"ivec2"===e||"ivec3"===e||"ivec4"===e?new Int32Array(this.buffer.buffer):"uint"===e||"uvec2"===e||"uvec3"===e||"uvec4"===e?new Uint32Array(this.buffer.buffer):this.buffer}}let QI=0;class ZI extends WI{constructor(e,t){super(e),this.id=QI++,this.groupNode=t,this.isNodeUniformsGroup=!0}}class YI extends HI{constructor(e,t){super(e),this.texture=t,this.version=t?t.version:0,this.generation=null,this.isSampler=!0}set texture(e){if(this._texture===e)return;const t=()=>{this._texture=null,this.generation=null,this.version=0};this._texture&&this._texture.removeEventListener("dispose",t),this._texture=e,this.generation=null,this.version=0,this._texture&&this._texture.addEventListener("dispose",t)}get texture(){return this._texture}update(){const{texture:e,version:t}=this;return t!==e.version&&(this.version=e.version,!0)}clone(){const e=super.clone();return e._texture=null,e.texture=this.texture,e}}let JI=0;class KI extends YI{constructor(e,t){super(e,t),this.id=JI++,this.store=!1,this.isSampledTexture=!0}}class qI extends KI{constructor(e,t,n,i=null){super(e,t?t.value:null),this.textureNode=t,this.groupNode=n,this.access=i}update(){const{textureNode:e}=this;return this.texture!==e.value?(this.texture=e.value,!0):super.update()}}class _I extends qI{constructor(e,t,n,i=null){super(e,t,n,i),this.isSampledCubeTexture=!0}}class $I extends qI{constructor(e,t,n,i=null){super(e,t,n,i),this.isSampledTexture3D=!0}}const eL={textureDimensions:"textureSize",equals:"equal",bitcast_float_int:"floatBitsToInt",bitcast_int_float:"intBitsToFloat",bitcast_uint_float:"uintBitsToFloat",bitcast_float_uint:"floatBitsToUint"},tL={low:"lowp",medium:"mediump",high:"highp"},nL={swizzleAssign:!0,storageBuffer:!1},iL={perspective:"smooth",linear:"noperspective"},rL={centroid:"centroid"},sL="\nprecision highp float;\nprecision highp int;\nprecision highp sampler2D;\nprecision highp sampler3D;\nprecision highp samplerCube;\nprecision highp sampler2DArray;\n\nprecision highp usampler2D;\nprecision highp usampler3D;\nprecision highp usamplerCube;\nprecision highp usampler2DArray;\n\nprecision highp isampler2D;\nprecision highp isampler3D;\nprecision highp isamplerCube;\nprecision highp isampler2DArray;\n\nprecision lowp sampler2DShadow;\nprecision lowp sampler2DArrayShadow;\nprecision lowp samplerCubeShadow;\n";class oL extends UD{constructor(e,t){super(e,t,new lI),this.uniformGroups={},this.transforms=[],this.extensions={},this.builtins={vertex:[],fragment:[],compute:[]}}needsToWorkingColorSpace(e){return!0===e.isVideoTexture&&e.colorSpace!==Kr}getMethod(e){return eL[e]||e}getBitcastMethod(e,t){return eL[`bitcast_${t}_${e}`]}getTernary(e,t,n){return`${e} ? ${t} : ${n}`}getOutputStructName(){return""}buildFunctionCode(e){const t=e.layout,n=this.flowShaderNode(e),i=[];for(const e of t.inputs)i.push(this.getType(e.type)+" "+e.name);return`${this.getType(t.type)} ${t.name}( ${i.join(", ")} ) {\n\n\t${n.vars}\n\n${n.code}\n\treturn ${n.result};\n\n}`}setupPBO(e){const t=e.value;if(void 0===t.pbo){const e=t.array,n=t.count*t.itemSize,{itemSize:i}=t,r=t.array.constructor.name.toLowerCase().includes("int");let s=r?lr:ar;2===i?s=r?cr:ur:3===i?s=r?1032:ir:4===i&&(s=r?dr:rr);const o={Float32Array:Ji,Uint8Array:Gi,Uint16Array:Qi,Uint32Array:Yi,Int8Array:Vi,Int16Array:Wi,Int32Array:Zi,Uint8ClampedArray:Gi},a=Math.pow(2,Math.ceil(Math.log2(Math.sqrt(n/i))));let l=Math.ceil(n/i/a);a*l*i<n&&l++;const u=a*l*i,c=new e.constructor(u);c.set(e,0),t.array=c;const d=new Sl(t.array,a,l,s,o[t.array.constructor.name]||Ji);d.needsUpdate=!0,d.isPBOTexture=!0;const h=new Tw(d,null,null);h.setPrecision("high"),t.pboNode=h,t.pbo=h.value,this.getUniformFromNode(t.pboNode,"texture",this.shaderStage,this.context.nodeName)}}getPropertyName(e,t=this.shaderStage){return e.isNodeUniform&&!0!==e.node.isTextureNode&&!0!==e.node.isBufferNode?t.charAt(0)+"_"+e.name:super.getPropertyName(e,t)}generatePBO(e){const{node:t,indexNode:n}=e,i=t.value;if(this.renderer.backend.has(i)){this.renderer.backend.get(i).pbo=i.pbo}const r=this.getUniformFromNode(i.pboNode,"texture",this.shaderStage,this.context.nodeName),s=this.getPropertyName(r);this.increaseUsage(n);const o=n.build(this,"uint"),a=this.getDataFromNode(e);let l=a.propertyName;if(void 0===l){const n=this.getVarFromNode(e);l=this.getPropertyName(n);const r=this.getDataFromNode(t);let u=r.propertySizeName;void 0===u&&(u=l+"Size",this.getVarFromNode(t,u,"uint"),this.addLineFlowCode(`${u} = uint( textureSize( ${s}, 0 ).x )`,e),r.propertySizeName=u);const{itemSize:c}=i,d="."+vv.join("").slice(0,c),h=`ivec2(${o} % ${u}, ${o} / ${u})`,f=this.generateTextureLoad(null,s,h,null,null,"0");let p="vec4";i.pbo.type===Yi?p="uvec4":i.pbo.type===Zi&&(p="ivec4"),this.addLineFlowCode(`${l} = ${p}(${f})${d}`,e),a.propertyName=l}return l}generateTextureLoad(e,t,n,i,r,s="0"){let o;return o=i?r?`texelFetchOffset( ${t}, ivec3( ${n}, ${i} ), ${s}, ${r} )`:`texelFetch( ${t}, ivec3( ${n}, ${i} ), ${s} )`:r?`texelFetchOffset( ${t}, ${n}, ${s}, ${r} )`:`texelFetch( ${t}, ${n}, ${s} )`,null!==e&&e.isDepthTexture&&(o+=".x"),o}generateTexture(e,t,n,i,r){return i&&(n=`vec3( ${n}, ${i} )`),e.isDepthTexture?r?`textureOffset( ${t}, ${n}, ${r} ).x`:`texture( ${t}, ${n} ).x`:r?`textureOffset( ${t}, ${n}, ${r} )`:`texture( ${t}, ${n} )`}generateTextureLevel(e,t,n,i,r){return r?`textureLodOffset( ${t}, ${n}, ${i}, ${r} )`:`textureLod( ${t}, ${n}, ${i} )`}generateTextureBias(e,t,n,i,r){return r?`textureOffset( ${t}, ${n}, ${r}, ${i} )`:`texture( ${t}, ${n}, ${i} )`}generateTextureGrad(e,t,n,i,r){return r?`textureGradOffset( ${t}, ${n}, ${i[0]}, ${i[1]}, ${r} )`:`textureGrad( ${t}, ${n}, ${i[0]}, ${i[1]} )`}generateTextureCompare(e,t,n,i,r,s,o=this.shaderStage){if("fragment"===o)return r?s?`textureOffset( ${t}, vec4( ${n}, ${r}, ${i} ), ${s} )`:`texture( ${t}, vec4( ${n}, ${r}, ${i} ) )`:s?`textureOffset( ${t}, vec3( ${n}, ${i} ), ${s} )`:`texture( ${t}, vec3( ${n}, ${i} ) )`;console.error(`WebGPURenderer: THREE.DepthTexture.compareFunction() does not support ${o} shader.`)}getVars(e){const t=[],n=this.vars[e];if(void 0!==n)for(const e of n)t.push(`${this.getVar(e.type,e.name,e.count)};`);return t.join("\n\t")}getUniforms(e){const t=this.uniforms[e],n=[],i={};for(const r of t){let t=null,s=!1;if("texture"===r.type||"texture3D"===r.type){const e=r.node.value;let n="";!0!==e.isDataTexture&&!0!==e.isData3DTexture||(e.type===Yi?n="u":e.type===Zi&&(n="i")),t="texture3D"===r.type&&!1===e.isArrayTexture?`${n}sampler3D ${r.name};`:e.compareFunction?!0===e.isArrayTexture?`sampler2DArrayShadow ${r.name};`:`sampler2DShadow ${r.name};`:!0===e.isArrayTexture||!0===e.isDataArrayTexture||!0===e.isCompressedArrayTexture?`${n}sampler2DArray ${r.name};`:`${n}sampler2D ${r.name};`}else if("cubeTexture"===r.type)t=`samplerCube ${r.name};`;else if("buffer"===r.type){const e=r.node,n=this.getType(e.bufferType),i=e.bufferCount,s=i>0?i:"";t=`${e.name} {\n\t${n} ${r.name}[${s}];\n};\n`}else{t=`${this.getVectorType(r.type)} ${this.getPropertyName(r,e)};`,s=!0}const o=r.node.precision;if(null!==o&&(t=tL[o]+" "+t),s){t="\t"+t;const e=r.groupNode.name;(i[e]||(i[e]=[])).push(t)}else t="uniform "+t,n.push(t)}let r="";for(const t in i){const n=i[t];r+=this._getGLSLUniformStruct(e+"_"+t,n.join("\n"))+"\n"}return r+=n.join("\n"),r}getTypeFromAttribute(e){let t=super.getTypeFromAttribute(e);if(/^[iu]/.test(t)&&e.gpuType!==Zi){let n=e;e.isInterleavedBufferAttribute&&(n=e.data);const i=n.array;!1==(i instanceof Uint32Array||i instanceof Int32Array)&&(t=t.slice(1))}return t}getAttributes(e){let t="";if("vertex"===e||"compute"===e){const e=this.getAttributesArray();let n=0;for(const i of e)t+=`layout( location = ${n++} ) in ${i.type} ${i.name};\n`}return t}getStructMembers(e){const t=[];for(const n of e.members)t.push(`\t${n.type} ${n.name};`);return t.join("\n")}getStructs(e){const t=[],n=this.structs[e],i=[];for(const e of n)if(e.output)for(const t of e.members)i.push(`layout( location = ${t.index} ) out ${t.type} ${t.name};`);else{let n="struct "+e.name+" {\n";n+=this.getStructMembers(e),n+="\n};\n",t.push(n)}return 0===i.length&&i.push("layout( location = 0 ) out vec4 fragColor;"),"\n"+i.join("\n")+"\n\n"+t.join("\n")}getVaryings(e){let t="";const n=this.varyings;if("vertex"===e||"compute"===e)for(const i of n){"compute"===e&&(i.needsInterpolation=!0);const n=this.getType(i.type);if(i.needsInterpolation)if(i.interpolationType){t+=`${iL[i.interpolationType]||i.interpolationType} ${rL[i.interpolationSampling]||""} out ${n} ${i.name};\n`}else{t+=`${n.includes("int")||n.includes("uv")||n.includes("iv")?"flat ":""}out ${n} ${i.name};\n`}else t+=`${n} ${i.name};\n`}else if("fragment"===e)for(const e of n)if(e.needsInterpolation){const n=this.getType(e.type);if(e.interpolationType){t+=`${iL[e.interpolationType]||e.interpolationType} ${rL[e.interpolationSampling]||""} in ${n} ${e.name};\n`}else{t+=`${n.includes("int")||n.includes("uv")||n.includes("iv")?"flat ":""}in ${n} ${e.name};\n`}}for(const n of this.builtins[e])t+=`${n};\n`;return t}getVertexIndex(){return"uint( gl_VertexID )"}getInstanceIndex(){return"uint( gl_InstanceID )"}getInvocationLocalIndex(){return`uint( gl_InstanceID ) % ${this.object.workgroupSize.reduce(((e,t)=>e*t),1)}u`}getDrawIndex(){return this.renderer.backend.extensions.has("WEBGL_multi_draw")?"uint( gl_DrawID )":null}getFrontFacing(){return"gl_FrontFacing"}getFragCoord(){return"gl_FragCoord.xy"}getFragDepth(){return"gl_FragDepth"}enableExtension(e,t,n=this.shaderStage){const i=this.extensions[n]||(this.extensions[n]=new Map);!1===i.has(e)&&i.set(e,{name:e,behavior:t})}getExtensions(e){const t=[];if("vertex"===e){const t=this.renderer.backend.extensions;this.object.isBatchedMesh&&t.has("WEBGL_multi_draw")&&this.enableExtension("GL_ANGLE_multi_draw","require",e)}const n=this.extensions[e];if(void 0!==n)for(const{name:e,behavior:i}of n.values())t.push(`#extension ${e} : ${i}`);return t.join("\n")}getClipDistance(){return"gl_ClipDistance"}isAvailable(e){let t=nL[e];if(void 0===t){let n;switch(t=!1,e){case"float32Filterable":n="OES_texture_float_linear";break;case"clipDistance":n="WEBGL_clip_cull_distance"}if(void 0!==n){const e=this.renderer.backend.extensions;e.has(n)&&(e.get(n),t=!0)}nL[e]=t}return t}isFlipY(){return!0}enableHardwareClipping(e){this.enableExtension("GL_ANGLE_clip_cull_distance","require"),this.builtins.vertex.push(`out float gl_ClipDistance[ ${e} ]`)}enableMultiview(){this.enableExtension("GL_OVR_multiview2","require","fragment"),this.enableExtension("GL_OVR_multiview2","require","vertex"),this.builtins.vertex.push("layout(num_views = 2) in")}registerTransform(e,t){this.transforms.push({varyingName:e,attributeNode:t})}getTransforms(){const e=this.transforms;let t="";for(let n=0;n<e.length;n++){const i=e[n],r=this.getPropertyName(i.attributeNode);r&&(t+=`${i.varyingName} = ${r};\n\t`)}return t}_getGLSLUniformStruct(e,t){return`\nlayout( std140 ) uniform ${e} {\n${t}\n};`}_getGLSLVertexCode(e){return`#version 300 es\n\n${this.getSignature()}\n\n// extensions\n${e.extensions}\n\n// precision\n${sL}\n\n// uniforms\n${e.uniforms}\n\n// varyings\n${e.varyings}\n\n// attributes\n${e.attributes}\n\n// codes\n${e.codes}\n\nvoid main() {\n\n\t// vars\n\t${e.vars}\n\n\t// transforms\n\t${e.transforms}\n\n\t// flow\n\t${e.flow}\n\n\tgl_PointSize = 1.0;\n\n}\n`}_getGLSLFragmentCode(e){return`#version 300 es\n\n${this.getSignature()}\n\n// extensions\n${e.extensions}\n\n// precision\n${sL}\n\n// uniforms\n${e.uniforms}\n\n// varyings\n${e.varyings}\n\n// codes\n${e.codes}\n\n// structs\n${e.structs}\n\nvoid main() {\n\n\t// vars\n\t${e.vars}\n\n\t// flow\n\t${e.flow}\n\n}\n`}buildCode(){const e=null!==this.material?{fragment:{},vertex:{}}:{compute:{}};this.sortBindingGroups();for(const t in e){let n="// code\n\n";n+=this.flowCode[t];const i=this.flowNodes[t],r=i[i.length-1];for(const e of i){const i=this.getFlowData(e),s=e.name;s&&(n.length>0&&(n+="\n"),n+=`\t// flow -> ${s}\n\t`),n+=`${i.code}\n\t`,e===r&&"compute"!==t&&(n+="// result\n\t","vertex"===t?(n+="gl_Position = ",n+=`${i.result};`):"fragment"===t&&(e.outputNode.isOutputStructNode||(n+="fragColor = ",n+=`${i.result};`)))}const s=e[t];s.extensions=this.getExtensions(t),s.uniforms=this.getUniforms(t),s.attributes=this.getAttributes(t),s.varyings=this.getVaryings(t),s.vars=this.getVars(t),s.structs=this.getStructs(t),s.codes=this.getCodes(t),s.transforms=this.getTransforms(t),s.flow=n}null!==this.material?(this.vertexShader=this._getGLSLVertexCode(e.vertex),this.fragmentShader=this._getGLSLFragmentCode(e.fragment)):this.computeShader=this._getGLSLVertexCode(e.compute)}getUniformFromNode(e,t,n,i=null){const r=super.getUniformFromNode(e,t,n,i),s=this.getDataFromNode(e,n,this.globalCache);let o=s.uniformGPU;if(void 0===o){const i=e.groupNode,a=i.name,l=this.getBindGroupArray(a,n);if("texture"===t)o=new qI(r.name,r.node,i),l.push(o);else if("cubeTexture"===t)o=new _I(r.name,r.node,i),l.push(o);else if("texture3D"===t)o=new $I(r.name,r.node,i),l.push(o);else if("buffer"===t){e.name=`NodeBuffer_${e.id}`,r.name=`buffer${e.id}`;const t=new VI(e,i);t.name=e.name,l.push(t),o=t}else{const e=this.uniformGroups[n]||(this.uniformGroups[n]={});let s=e[a];void 0===s&&(s=new ZI(n+"_"+a,i),e[a]=s,l.push(s)),o=this.getNodeUniform(r,t),s.addUniform(o)}s.uniformGPU=o}return r}}let aL=null,lL=null;class uL{constructor(e={}){this.parameters=Object.assign({},e),this.data=new WeakMap,this.renderer=null,this.domElement=null,this.timestampQueryPool={render:null,compute:null},this.trackTimestamp=!0===e.trackTimestamp}async init(e){this.renderer=e}get coordinateSystem(){}beginRender(){}finishRender(){}beginCompute(){}finishCompute(){}draw(){}compute(){}createProgram(){}destroyProgram(){}createBindings(){}updateBindings(){}updateBinding(){}createRenderPipeline(){}createComputePipeline(){}needsRenderUpdate(){}getRenderCacheKey(){}createNodeBuilder(){}createSampler(){}destroySampler(){}createDefaultTexture(){}createTexture(){}updateTexture(){}generateMipmaps(){}destroyTexture(){}async copyTextureToBuffer(){}copyTextureToTexture(){}copyFramebufferToTexture(){}createAttribute(){}createIndexAttribute(){}createStorageAttribute(){}updateAttribute(){}destroyAttribute(){}getContext(){}updateSize(){}updateViewport(){}getTimestampUID(e){const t=this.get(e);let n=!0===e.isComputeNode?"c":"r";return n+=":"+t.frameCalls+":"+e.id,n}isOccluded(){}async resolveTimestampsAsync(e="render"){if(!this.trackTimestamp)return void js("WebGPURenderer: Timestamp tracking is disabled.");const t=this.timestampQueryPool[e];if(!t)return void js(`WebGPURenderer: No timestamp query pool for type '${e}' found.`);const n=await t.resolveQueriesAsync();return this.renderer.info[e].timestamp=n,n}async waitForGPU(){}async getArrayBufferAsync(){}async hasFeatureAsync(){}hasFeature(){}getMaxAnisotropy(){}getDrawingBufferSize(){return aL=aL||new Cs,this.renderer.getDrawingBufferSize(aL)}setScissorTest(){}getClearColor(){const e=this.renderer;return lL=lL||new yN,e.getClearColor(lL),lL.getRGB(lL),lL}getDomElement(){let e=this.domElement;return null===e&&(e=void 0!==this.parameters.canvas?this.parameters.canvas:Is(),"setAttribute"in e&&e.setAttribute("data-engine",`three.js r${mi} webgpu`),this.domElement=e),e}set(e,t){this.data.set(e,t)}get(e){let t=this.data.get(e);return void 0===t&&(t={},this.data.set(e,t)),t}has(e){return this.data.has(e)}delete(e){this.data.delete(e)}dispose(){}}let cL,dL,hL=0;class fL{constructor(e,t){this.buffers=[e.bufferGPU,t],this.type=e.type,this.bufferType=e.bufferType,this.pbo=e.pbo,this.byteLength=e.byteLength,this.bytesPerElement=e.BYTES_PER_ELEMENT,this.version=e.version,this.isInteger=e.isInteger,this.activeBufferIndex=0,this.baseId=e.id}get id(){return`${this.baseId}|${this.activeBufferIndex}`}get bufferGPU(){return this.buffers[this.activeBufferIndex]}get transformBuffer(){return this.buffers[1^this.activeBufferIndex]}switchBuffers(){this.activeBufferIndex^=1}}class pL{constructor(e){this.backend=e}createAttribute(e,t){const n=this.backend,{gl:i}=n,r=e.array,s=e.usage||i.STATIC_DRAW,o=e.isInterleavedBufferAttribute?e.data:e,a=n.get(o);let l,u=a.bufferGPU;if(void 0===u&&(u=this._createBuffer(i,t,r,s),a.bufferGPU=u,a.bufferType=t,a.version=o.version),r instanceof Float32Array)l=i.FLOAT;else if("undefined"!=typeof Float16Array&&r instanceof Float16Array)l=i.HALF_FLOAT;else if(r instanceof Uint16Array)l=e.isFloat16BufferAttribute?i.HALF_FLOAT:i.UNSIGNED_SHORT;else if(r instanceof Int16Array)l=i.SHORT;else if(r instanceof Uint32Array)l=i.UNSIGNED_INT;else if(r instanceof Int32Array)l=i.INT;else if(r instanceof Int8Array)l=i.BYTE;else if(r instanceof Uint8Array)l=i.UNSIGNED_BYTE;else{if(!(r instanceof Uint8ClampedArray))throw new Error("THREE.WebGLBackend: Unsupported buffer data format: "+r);l=i.UNSIGNED_BYTE}let c={bufferGPU:u,bufferType:t,type:l,byteLength:r.byteLength,bytesPerElement:r.BYTES_PER_ELEMENT,version:e.version,pbo:e.pbo,isInteger:l===i.INT||l===i.UNSIGNED_INT||e.gpuType===Zi,id:hL++};if(e.isStorageBufferAttribute||e.isStorageInstancedBufferAttribute){const e=this._createBuffer(i,t,r,s);c=new fL(c,e)}n.set(e,c)}updateAttribute(e){const t=this.backend,{gl:n}=t,i=e.array,r=e.isInterleavedBufferAttribute?e.data:e,s=t.get(r),o=s.bufferType,a=e.isInterleavedBufferAttribute?e.data.updateRanges:e.updateRanges;if(n.bindBuffer(o,s.bufferGPU),0===a.length)n.bufferSubData(o,0,i);else{for(let e=0,t=a.length;e<t;e++){const t=a[e];n.bufferSubData(o,t.start*i.BYTES_PER_ELEMENT,i,t.start,t.count)}r.clearUpdateRanges()}n.bindBuffer(o,null),s.version=r.version}destroyAttribute(e){const t=this.backend,{gl:n}=t;e.isInterleavedBufferAttribute&&t.delete(e.data);const i=t.get(e);n.deleteBuffer(i.bufferGPU),t.delete(e)}async getArrayBufferAsync(e){const t=this.backend,{gl:n}=t,i=e.isInterleavedBufferAttribute?e.data:e,{bufferGPU:r}=t.get(i),s=e.array,o=s.byteLength;n.bindBuffer(n.COPY_READ_BUFFER,r);const a=n.createBuffer();n.bindBuffer(n.COPY_WRITE_BUFFER,a),n.bufferData(n.COPY_WRITE_BUFFER,o,n.STREAM_READ),n.copyBufferSubData(n.COPY_READ_BUFFER,n.COPY_WRITE_BUFFER,0,0,o),await t.utils._clientWaitAsync();const l=new e.array.constructor(s.length);return n.bindBuffer(n.COPY_WRITE_BUFFER,a),n.getBufferSubData(n.COPY_WRITE_BUFFER,0,l),n.deleteBuffer(a),n.bindBuffer(n.COPY_READ_BUFFER,null),n.bindBuffer(n.COPY_WRITE_BUFFER,null),l.buffer}_createBuffer(e,t,n,i){const r=e.createBuffer();return e.bindBuffer(t,r),e.bufferData(t,n,i),e.bindBuffer(t,null),r}}class gL{constructor(e){this.backend=e,this.gl=this.backend.gl,this.enabled={},this.currentFlipSided=null,this.currentCullFace=null,this.currentProgram=null,this.currentBlendingEnabled=!1,this.currentBlending=null,this.currentBlendSrc=null,this.currentBlendDst=null,this.currentBlendSrcAlpha=null,this.currentBlendDstAlpha=null,this.currentPremultipledAlpha=null,this.currentPolygonOffsetFactor=null,this.currentPolygonOffsetUnits=null,this.currentColorMask=null,this.currentDepthFunc=null,this.currentDepthMask=null,this.currentStencilFunc=null,this.currentStencilRef=null,this.currentStencilFuncMask=null,this.currentStencilFail=null,this.currentStencilZFail=null,this.currentStencilZPass=null,this.currentStencilMask=null,this.currentLineWidth=null,this.currentClippingPlanes=0,this.currentVAO=null,this.currentIndex=null,this.currentBoundFramebuffers={},this.currentDrawbuffers=new WeakMap,this.maxTextures=this.gl.getParameter(this.gl.MAX_TEXTURE_IMAGE_UNITS),this.currentTextureSlot=null,this.currentBoundTextures={},this.currentBoundBufferBases={},this._init()}_init(){const e=this.gl;cL={[Mi]:e.FUNC_ADD,101:e.FUNC_SUBTRACT,102:e.FUNC_REVERSE_SUBTRACT},dL={[Ei]:e.ZERO,201:e.ONE,202:e.SRC_COLOR,[Ti]:e.SRC_ALPHA,210:e.SRC_ALPHA_SATURATE,208:e.DST_COLOR,206:e.DST_ALPHA,203:e.ONE_MINUS_SRC_COLOR,[Si]:e.ONE_MINUS_SRC_ALPHA,209:e.ONE_MINUS_DST_COLOR,207:e.ONE_MINUS_DST_ALPHA};const t=e.getParameter(e.SCISSOR_BOX),n=e.getParameter(e.VIEWPORT);this.currentScissor=(new Js).fromArray(t),this.currentViewport=(new Js).fromArray(n),this._tempVec4=new Js}enable(e){const{enabled:t}=this;!0!==t[e]&&(this.gl.enable(e),t[e]=!0)}disable(e){const{enabled:t}=this;!1!==t[e]&&(this.gl.disable(e),t[e]=!1)}setFlipSided(e){if(this.currentFlipSided!==e){const{gl:t}=this;e?t.frontFace(t.CW):t.frontFace(t.CCW),this.currentFlipSided=e}}setCullFace(e){const{gl:t}=this;0!==e?(this.enable(t.CULL_FACE),e!==this.currentCullFace&&(1===e?t.cullFace(t.BACK):2===e?t.cullFace(t.FRONT):t.cullFace(t.FRONT_AND_BACK))):this.disable(t.CULL_FACE),this.currentCullFace=e}setLineWidth(e){const{currentLineWidth:t,gl:n}=this;e!==t&&(n.lineWidth(e),this.currentLineWidth=e)}setBlending(e,t,n,i,r,s,o,a){const{gl:l}=this;if(0!==e){if(!1===this.currentBlendingEnabled&&(this.enable(l.BLEND),this.currentBlendingEnabled=!0),5===e)r=r||t,s=s||n,o=o||i,t===this.currentBlendEquation&&r===this.currentBlendEquationAlpha||(l.blendEquationSeparate(cL[t],cL[r]),this.currentBlendEquation=t,this.currentBlendEquationAlpha=r),n===this.currentBlendSrc&&i===this.currentBlendDst&&s===this.currentBlendSrcAlpha&&o===this.currentBlendDstAlpha||(l.blendFuncSeparate(dL[n],dL[i],dL[s],dL[o]),this.currentBlendSrc=n,this.currentBlendDst=i,this.currentBlendSrcAlpha=s,this.currentBlendDstAlpha=o),this.currentBlending=e,this.currentPremultipledAlpha=!1;else if(e!==this.currentBlending||a!==this.currentPremultipledAlpha){if(this.currentBlendEquation===Mi&&this.currentBlendEquationAlpha===Mi||(l.blendEquation(l.FUNC_ADD),this.currentBlendEquation=Mi,this.currentBlendEquationAlpha=Mi),a)switch(e){case 1:l.blendFuncSeparate(l.ONE,l.ONE_MINUS_SRC_ALPHA,l.ONE,l.ONE_MINUS_SRC_ALPHA);break;case 2:l.blendFunc(l.ONE,l.ONE);break;case 3:l.blendFuncSeparate(l.ZERO,l.ONE_MINUS_SRC_COLOR,l.ZERO,l.ONE);break;case 4:l.blendFuncSeparate(l.DST_COLOR,l.ONE_MINUS_SRC_ALPHA,l.ZERO,l.ONE);break;default:console.error("THREE.WebGLState: Invalid blending: ",e)}else switch(e){case 1:l.blendFuncSeparate(l.SRC_ALPHA,l.ONE_MINUS_SRC_ALPHA,l.ONE,l.ONE_MINUS_SRC_ALPHA);break;case 2:l.blendFuncSeparate(l.SRC_ALPHA,l.ONE,l.ONE,l.ONE);break;case 3:console.error("THREE.WebGLState: SubtractiveBlending requires material.premultipliedAlpha = true");break;case 4:console.error("THREE.WebGLState: MultiplyBlending requires material.premultipliedAlpha = true");break;default:console.error("THREE.WebGLState: Invalid blending: ",e)}this.currentBlendSrc=null,this.currentBlendDst=null,this.currentBlendSrcAlpha=null,this.currentBlendDstAlpha=null,this.currentBlending=e,this.currentPremultipledAlpha=a}}else!0===this.currentBlendingEnabled&&(this.disable(l.BLEND),this.currentBlendingEnabled=!1)}setColorMask(e){this.currentColorMask!==e&&(this.gl.colorMask(e,e,e,e),this.currentColorMask=e)}setDepthTest(e){const{gl:t}=this;e?this.enable(t.DEPTH_TEST):this.disable(t.DEPTH_TEST)}setDepthMask(e){this.currentDepthMask!==e&&(this.gl.depthMask(e),this.currentDepthMask=e)}setDepthFunc(e){if(this.currentDepthFunc!==e){const{gl:t}=this;switch(e){case 0:t.depthFunc(t.NEVER);break;case 1:t.depthFunc(t.ALWAYS);break;case 2:t.depthFunc(t.LESS);break;case 3:default:t.depthFunc(t.LEQUAL);break;case 4:t.depthFunc(t.EQUAL);break;case 5:t.depthFunc(t.GEQUAL);break;case 6:t.depthFunc(t.GREATER);break;case 7:t.depthFunc(t.NOTEQUAL)}this.currentDepthFunc=e}}scissor(e,t,n,i){const r=this._tempVec4.set(e,t,n,i);if(!1===this.currentScissor.equals(r)){const{gl:e}=this;e.scissor(r.x,r.y,r.z,r.w),this.currentScissor.copy(r)}}viewport(e,t,n,i){const r=this._tempVec4.set(e,t,n,i);if(!1===this.currentViewport.equals(r)){const{gl:e}=this;e.viewport(r.x,r.y,r.z,r.w),this.currentViewport.copy(r)}}setScissorTest(e){const t=this.gl;e?t.enable(t.SCISSOR_TEST):t.disable(t.SCISSOR_TEST)}setStencilTest(e){const{gl:t}=this;e?this.enable(t.STENCIL_TEST):this.disable(t.STENCIL_TEST)}setStencilMask(e){this.currentStencilMask!==e&&(this.gl.stencilMask(e),this.currentStencilMask=e)}setStencilFunc(e,t,n){this.currentStencilFunc===e&&this.currentStencilRef===t&&this.currentStencilFuncMask===n||(this.gl.stencilFunc(e,t,n),this.currentStencilFunc=e,this.currentStencilRef=t,this.currentStencilFuncMask=n)}setStencilOp(e,t,n){this.currentStencilFail===e&&this.currentStencilZFail===t&&this.currentStencilZPass===n||(this.gl.stencilOp(e,t,n),this.currentStencilFail=e,this.currentStencilZFail=t,this.currentStencilZPass=n)}setMaterial(e,t,n){const{gl:i}=this;2===e.side?this.disable(i.CULL_FACE):this.enable(i.CULL_FACE);let r=1===e.side;t&&(r=!r),this.setFlipSided(r),1===e.blending&&!1===e.transparent?this.setBlending(0):this.setBlending(e.blending,e.blendEquation,e.blendSrc,e.blendDst,e.blendEquationAlpha,e.blendSrcAlpha,e.blendDstAlpha,e.premultipliedAlpha),this.setDepthFunc(e.depthFunc),this.setDepthTest(e.depthTest),this.setDepthMask(e.depthWrite),this.setColorMask(e.colorWrite);const s=e.stencilWrite;if(this.setStencilTest(s),s&&(this.setStencilMask(e.stencilWriteMask),this.setStencilFunc(e.stencilFunc,e.stencilRef,e.stencilFuncMask),this.setStencilOp(e.stencilFail,e.stencilZFail,e.stencilZPass)),this.setPolygonOffset(e.polygonOffset,e.polygonOffsetFactor,e.polygonOffsetUnits),!0===e.alphaToCoverage&&this.backend.renderer.samples>1?this.enable(i.SAMPLE_ALPHA_TO_COVERAGE):this.disable(i.SAMPLE_ALPHA_TO_COVERAGE),n>0&&this.currentClippingPlanes!==n){const e=12288;for(let t=0;t<8;t++)t<n?this.enable(e+t):this.disable(e+t)}}setPolygonOffset(e,t,n){const{gl:i}=this;e?(this.enable(i.POLYGON_OFFSET_FILL),this.currentPolygonOffsetFactor===t&&this.currentPolygonOffsetUnits===n||(i.polygonOffset(t,n),this.currentPolygonOffsetFactor=t,this.currentPolygonOffsetUnits=n)):this.disable(i.POLYGON_OFFSET_FILL)}useProgram(e){return this.currentProgram!==e&&(this.gl.useProgram(e),this.currentProgram=e,!0)}setVertexState(e,t=null){const n=this.gl;return(this.currentVAO!==e||this.currentIndex!==t)&&(n.bindVertexArray(e),null!==t&&n.bindBuffer(n.ELEMENT_ARRAY_BUFFER,t),this.currentVAO=e,this.currentIndex=t,!0)}resetVertexState(){const e=this.gl;e.bindVertexArray(null),e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null),this.currentVAO=null,this.currentIndex=null}bindFramebuffer(e,t){const{gl:n,currentBoundFramebuffers:i}=this;return i[e]!==t&&(n.bindFramebuffer(e,t),i[e]=t,e===n.DRAW_FRAMEBUFFER&&(i[n.FRAMEBUFFER]=t),e===n.FRAMEBUFFER&&(i[n.DRAW_FRAMEBUFFER]=t),!0)}drawBuffers(e,t){const{gl:n}=this;let i=[],r=!1;if(null!==e.textures){i=this.currentDrawbuffers.get(t),void 0===i&&(i=[],this.currentDrawbuffers.set(t,i));const s=e.textures;if(i.length!==s.length||i[0]!==n.COLOR_ATTACHMENT0){for(let e=0,t=s.length;e<t;e++)i[e]=n.COLOR_ATTACHMENT0+e;i.length=s.length,r=!0}}else i[0]!==n.BACK&&(i[0]=n.BACK,r=!0);r&&n.drawBuffers(i)}activeTexture(e){const{gl:t,currentTextureSlot:n,maxTextures:i}=this;void 0===e&&(e=t.TEXTURE0+i-1),n!==e&&(t.activeTexture(e),this.currentTextureSlot=e)}bindTexture(e,t,n){const{gl:i,currentTextureSlot:r,currentBoundTextures:s,maxTextures:o}=this;void 0===n&&(n=null===r?i.TEXTURE0+o-1:r);let a=s[n];void 0===a&&(a={type:void 0,texture:void 0},s[n]=a),a.type===e&&a.texture===t||(r!==n&&(i.activeTexture(n),this.currentTextureSlot=n),i.bindTexture(e,t),a.type=e,a.texture=t)}bindBufferBase(e,t,n){const{gl:i}=this,r=`${e}-${t}`;return this.currentBoundBufferBases[r]!==n&&(i.bindBufferBase(e,t,n),this.currentBoundBufferBases[r]=n,!0)}unbindTexture(){const{gl:e,currentTextureSlot:t,currentBoundTextures:n}=this,i=n[t];void 0!==i&&void 0!==i.type&&(e.bindTexture(i.type,null),i.type=void 0,i.texture=void 0)}}class mL{constructor(e){this.backend=e,this.gl=this.backend.gl,this.extensions=e.extensions}convert(e,t=""){const{gl:n,extensions:i}=this;let r;const s=ks.getTransfer(t);if(e===Gi)return n.UNSIGNED_BYTE;if(e===qi)return n.UNSIGNED_SHORT_4_4_4_4;if(e===_i)return n.UNSIGNED_SHORT_5_5_5_1;if(e===er)return n.UNSIGNED_INT_5_9_9_9_REV;if(e===tr)return n.UNSIGNED_INT_10F_11F_11F_REV;if(e===Vi)return n.BYTE;if(e===Wi)return n.SHORT;if(e===Qi)return n.UNSIGNED_SHORT;if(e===Zi)return n.INT;if(e===Yi)return n.UNSIGNED_INT;if(e===Ji)return n.FLOAT;if(e===Ki)return n.HALF_FLOAT;if(e===nr)return n.ALPHA;if(e===ir)return n.RGB;if(e===rr)return n.RGBA;if(e===sr)return n.DEPTH_COMPONENT;if(e===or)return n.DEPTH_STENCIL;if(e===ar)return n.RED;if(e===lr)return n.RED_INTEGER;if(e===ur)return n.RG;if(e===cr)return n.RG_INTEGER;if(e===dr)return n.RGBA_INTEGER;if(e===hr||e===fr||e===pr||e===gr)if(s===es){if(r=i.get("WEBGL_compressed_texture_s3tc_srgb"),null===r)return null;if(e===hr)return r.COMPRESSED_SRGB_S3TC_DXT1_EXT;if(e===fr)return r.COMPRESSED_SRGB_ALPHA_S3TC_DXT1_EXT;if(e===pr)return r.COMPRESSED_SRGB_ALPHA_S3TC_DXT3_EXT;if(e===gr)return r.COMPRESSED_SRGB_ALPHA_S3TC_DXT5_EXT}else{if(r=i.get("WEBGL_compressed_texture_s3tc"),null===r)return null;if(e===hr)return r.COMPRESSED_RGB_S3TC_DXT1_EXT;if(e===fr)return r.COMPRESSED_RGBA_S3TC_DXT1_EXT;if(e===pr)return r.COMPRESSED_RGBA_S3TC_DXT3_EXT;if(e===gr)return r.COMPRESSED_RGBA_S3TC_DXT5_EXT}if(e===mr||e===vr||e===Ar||e===xr){if(r=i.get("WEBGL_compressed_texture_pvrtc"),null===r)return null;if(e===mr)return r.COMPRESSED_RGB_PVRTC_4BPPV1_IMG;if(e===vr)return r.COMPRESSED_RGB_PVRTC_2BPPV1_IMG;if(e===Ar)return r.COMPRESSED_RGBA_PVRTC_4BPPV1_IMG;if(e===xr)return r.COMPRESSED_RGBA_PVRTC_2BPPV1_IMG}if(e===yr||e===br||e===wr){if(r=i.get("WEBGL_compressed_texture_etc"),null===r)return null;if(e===yr||e===br)return s===es?r.COMPRESSED_SRGB8_ETC2:r.COMPRESSED_RGB8_ETC2;if(e===wr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ETC2_EAC:r.COMPRESSED_RGBA8_ETC2_EAC}if(e===Cr||e===Mr||e===Er||e===Tr||e===Sr||e===Pr||e===Nr||e===Br||e===Dr||e===Ir||e===Lr||e===jr||e===Or||e===zr){if(r=i.get("WEBGL_compressed_texture_astc"),null===r)return null;if(e===Cr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_4x4_KHR:r.COMPRESSED_RGBA_ASTC_4x4_KHR;if(e===Mr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_5x4_KHR:r.COMPRESSED_RGBA_ASTC_5x4_KHR;if(e===Er)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_5x5_KHR:r.COMPRESSED_RGBA_ASTC_5x5_KHR;if(e===Tr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_6x5_KHR:r.COMPRESSED_RGBA_ASTC_6x5_KHR;if(e===Sr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_6x6_KHR:r.COMPRESSED_RGBA_ASTC_6x6_KHR;if(e===Pr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_8x5_KHR:r.COMPRESSED_RGBA_ASTC_8x5_KHR;if(e===Nr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_8x6_KHR:r.COMPRESSED_RGBA_ASTC_8x6_KHR;if(e===Br)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_8x8_KHR:r.COMPRESSED_RGBA_ASTC_8x8_KHR;if(e===Dr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_10x5_KHR:r.COMPRESSED_RGBA_ASTC_10x5_KHR;if(e===Ir)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_10x6_KHR:r.COMPRESSED_RGBA_ASTC_10x6_KHR;if(e===Lr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_10x8_KHR:r.COMPRESSED_RGBA_ASTC_10x8_KHR;if(e===jr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_10x10_KHR:r.COMPRESSED_RGBA_ASTC_10x10_KHR;if(e===Or)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_12x10_KHR:r.COMPRESSED_RGBA_ASTC_12x10_KHR;if(e===zr)return s===es?r.COMPRESSED_SRGB8_ALPHA8_ASTC_12x12_KHR:r.COMPRESSED_RGBA_ASTC_12x12_KHR}if(e===Rr){if(r=i.get("EXT_texture_compression_bptc"),null===r)return null;if(e===Rr)return s===es?r.COMPRESSED_SRGB_ALPHA_BPTC_UNORM_EXT:r.COMPRESSED_RGBA_BPTC_UNORM_EXT}if(e===Hr||e===Ur||e===Xr||e===Gr){if(r=i.get("EXT_texture_compression_rgtc"),null===r)return null;if(e===Hr)return r.COMPRESSED_RED_RGTC1_EXT;if(e===Ur)return r.COMPRESSED_SIGNED_RED_RGTC1_EXT;if(e===Xr)return r.COMPRESSED_RED_GREEN_RGTC2_EXT;if(e===Gr)return r.COMPRESSED_SIGNED_RED_GREEN_RGTC2_EXT}return e===$i?n.UNSIGNED_INT_24_8:void 0!==n[e]?n[e]:null}_clientWaitAsync(){const{gl:e}=this,t=e.fenceSync(e.SYNC_GPU_COMMANDS_COMPLETE,0);return e.flush(),new Promise(((n,i)=>{!function r(){const s=e.clientWaitSync(t,e.SYNC_FLUSH_COMMANDS_BIT,0);if(s===e.WAIT_FAILED)return e.deleteSync(t),void i();s!==e.TIMEOUT_EXPIRED?(e.deleteSync(t),n()):requestAnimationFrame(r)}()}))}}let vL,AL,xL,yL=!1;class bL{constructor(e){this.backend=e,this.gl=e.gl,this.extensions=e.extensions,this.defaultTextures={},!1===yL&&(this._init(),yL=!0)}_init(){const e=this.gl;vL={[ji]:e.REPEAT,[Oi]:e.CLAMP_TO_EDGE,[zi]:e.MIRRORED_REPEAT},AL={[Ri]:e.NEAREST,[ki]:e.NEAREST_MIPMAP_NEAREST,[Fi]:e.NEAREST_MIPMAP_LINEAR,[Hi]:e.LINEAR,[Ui]:e.LINEAR_MIPMAP_NEAREST,[Xi]:e.LINEAR_MIPMAP_LINEAR},xL={512:e.NEVER,519:e.ALWAYS,[ns]:e.LESS,[is]:e.LEQUAL,514:e.EQUAL,518:e.GEQUAL,516:e.GREATER,517:e.NOTEQUAL}}getGLTextureType(e){const{gl:t}=this;let n;return n=!0===e.isCubeTexture?t.TEXTURE_CUBE_MAP:!0===e.isArrayTexture||!0===e.isDataArrayTexture||!0===e.isCompressedArrayTexture?t.TEXTURE_2D_ARRAY:!0===e.isData3DTexture?t.TEXTURE_3D:t.TEXTURE_2D,n}getInternalFormat(e,t,n,i,r=!1){const{gl:s,extensions:o}=this;if(null!==e){if(void 0!==s[e])return s[e];console.warn("THREE.WebGLRenderer: Attempt to use non-existing WebGL internal format '"+e+"'")}let a=t;if(t===s.RED&&(n===s.FLOAT&&(a=s.R32F),n===s.HALF_FLOAT&&(a=s.R16F),n===s.UNSIGNED_BYTE&&(a=s.R8),n===s.UNSIGNED_SHORT&&(a=s.R16),n===s.UNSIGNED_INT&&(a=s.R32UI),n===s.BYTE&&(a=s.R8I),n===s.SHORT&&(a=s.R16I),n===s.INT&&(a=s.R32I)),t===s.RED_INTEGER&&(n===s.UNSIGNED_BYTE&&(a=s.R8UI),n===s.UNSIGNED_SHORT&&(a=s.R16UI),n===s.UNSIGNED_INT&&(a=s.R32UI),n===s.BYTE&&(a=s.R8I),n===s.SHORT&&(a=s.R16I),n===s.INT&&(a=s.R32I)),t===s.RG&&(n===s.FLOAT&&(a=s.RG32F),n===s.HALF_FLOAT&&(a=s.RG16F),n===s.UNSIGNED_BYTE&&(a=s.RG8),n===s.UNSIGNED_SHORT&&(a=s.RG16),n===s.UNSIGNED_INT&&(a=s.RG32UI),n===s.BYTE&&(a=s.RG8I),n===s.SHORT&&(a=s.RG16I),n===s.INT&&(a=s.RG32I)),t===s.RG_INTEGER&&(n===s.UNSIGNED_BYTE&&(a=s.RG8UI),n===s.UNSIGNED_SHORT&&(a=s.RG16UI),n===s.UNSIGNED_INT&&(a=s.RG32UI),n===s.BYTE&&(a=s.RG8I),n===s.SHORT&&(a=s.RG16I),n===s.INT&&(a=s.RG32I)),t===s.RGB){const e=r?$r:ks.getTransfer(i);n===s.FLOAT&&(a=s.RGB32F),n===s.HALF_FLOAT&&(a=s.RGB16F),n===s.UNSIGNED_BYTE&&(a=s.RGB8),n===s.UNSIGNED_SHORT&&(a=s.RGB16),n===s.UNSIGNED_INT&&(a=s.RGB32UI),n===s.BYTE&&(a=s.RGB8I),n===s.SHORT&&(a=s.RGB16I),n===s.INT&&(a=s.RGB32I),n===s.UNSIGNED_BYTE&&(a=e===es?s.SRGB8:s.RGB8),n===s.UNSIGNED_SHORT_5_6_5&&(a=s.RGB565),n===s.UNSIGNED_SHORT_5_5_5_1&&(a=s.RGB5_A1),n===s.UNSIGNED_SHORT_4_4_4_4&&(a=s.RGB4),n===s.UNSIGNED_INT_5_9_9_9_REV&&(a=s.RGB9_E5),n===s.UNSIGNED_INT_10F_11F_11F_REV&&(a=s.R11F_G11F_B10F)}if(t===s.RGB_INTEGER&&(n===s.UNSIGNED_BYTE&&(a=s.RGB8UI),n===s.UNSIGNED_SHORT&&(a=s.RGB16UI),n===s.UNSIGNED_INT&&(a=s.RGB32UI),n===s.BYTE&&(a=s.RGB8I),n===s.SHORT&&(a=s.RGB16I),n===s.INT&&(a=s.RGB32I)),t===s.RGBA){const e=r?$r:ks.getTransfer(i);n===s.FLOAT&&(a=s.RGBA32F),n===s.HALF_FLOAT&&(a=s.RGBA16F),n===s.UNSIGNED_BYTE&&(a=s.RGBA8),n===s.UNSIGNED_SHORT&&(a=s.RGBA16),n===s.UNSIGNED_INT&&(a=s.RGBA32UI),n===s.BYTE&&(a=s.RGBA8I),n===s.SHORT&&(a=s.RGBA16I),n===s.INT&&(a=s.RGBA32I),n===s.UNSIGNED_BYTE&&(a=e===es?s.SRGB8_ALPHA8:s.RGBA8),n===s.UNSIGNED_SHORT_4_4_4_4&&(a=s.RGBA4),n===s.UNSIGNED_SHORT_5_5_5_1&&(a=s.RGB5_A1)}return t===s.RGBA_INTEGER&&(n===s.UNSIGNED_BYTE&&(a=s.RGBA8UI),n===s.UNSIGNED_SHORT&&(a=s.RGBA16UI),n===s.UNSIGNED_INT&&(a=s.RGBA32UI),n===s.BYTE&&(a=s.RGBA8I),n===s.SHORT&&(a=s.RGBA16I),n===s.INT&&(a=s.RGBA32I)),t===s.DEPTH_COMPONENT&&(n===s.UNSIGNED_SHORT&&(a=s.DEPTH_COMPONENT16),n===s.UNSIGNED_INT&&(a=s.DEPTH_COMPONENT24),n===s.FLOAT&&(a=s.DEPTH_COMPONENT32F)),t===s.DEPTH_STENCIL&&n===s.UNSIGNED_INT_24_8&&(a=s.DEPTH24_STENCIL8),a!==s.R16F&&a!==s.R32F&&a!==s.RG16F&&a!==s.RG32F&&a!==s.RGBA16F&&a!==s.RGBA32F||o.get("EXT_color_buffer_float"),a}setTextureParameters(e,t){const{gl:n,extensions:i,backend:r}=this,s=ks.getPrimaries(ks.workingColorSpace),o=t.colorSpace===Kr?null:ks.getPrimaries(t.colorSpace),a=t.colorSpace===Kr||s===o?n.NONE:n.BROWSER_DEFAULT_WEBGL;n.pixelStorei(n.UNPACK_FLIP_Y_WEBGL,t.flipY),n.pixelStorei(n.UNPACK_PREMULTIPLY_ALPHA_WEBGL,t.premultiplyAlpha),n.pixelStorei(n.UNPACK_ALIGNMENT,t.unpackAlignment),n.pixelStorei(n.UNPACK_COLORSPACE_CONVERSION_WEBGL,a),n.texParameteri(e,n.TEXTURE_WRAP_S,vL[t.wrapS]),n.texParameteri(e,n.TEXTURE_WRAP_T,vL[t.wrapT]),e!==n.TEXTURE_3D&&e!==n.TEXTURE_2D_ARRAY||t.isArrayTexture||n.texParameteri(e,n.TEXTURE_WRAP_R,vL[t.wrapR]),n.texParameteri(e,n.TEXTURE_MAG_FILTER,AL[t.magFilter]);const l=void 0!==t.mipmaps&&t.mipmaps.length>0,u=t.minFilter===Hi&&l?Xi:t.minFilter;if(n.texParameteri(e,n.TEXTURE_MIN_FILTER,AL[u]),t.compareFunction&&(n.texParameteri(e,n.TEXTURE_COMPARE_MODE,n.COMPARE_REF_TO_TEXTURE),n.texParameteri(e,n.TEXTURE_COMPARE_FUNC,xL[t.compareFunction])),!0===i.has("EXT_texture_filter_anisotropic")){if(t.magFilter===Ri)return;if(t.minFilter!==Fi&&t.minFilter!==Xi)return;if(t.type===Ji&&!1===i.has("OES_texture_float_linear"))return;if(t.anisotropy>1){const s=i.get("EXT_texture_filter_anisotropic");n.texParameterf(e,s.TEXTURE_MAX_ANISOTROPY_EXT,Math.min(t.anisotropy,r.getMaxAnisotropy()))}}}createDefaultTexture(e){const{gl:t,backend:n,defaultTextures:i}=this,r=this.getGLTextureType(e);let s=i[r];void 0===s&&(s=t.createTexture(),n.state.bindTexture(r,s),t.texParameteri(r,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(r,t.TEXTURE_MAG_FILTER,t.NEAREST),i[r]=s),n.set(e,{textureGPU:s,glTextureType:r,isDefault:!0})}createTexture(e,t){const{gl:n,backend:i}=this,{levels:r,width:s,height:o,depth:a}=t,l=i.utils.convert(e.format,e.colorSpace),u=i.utils.convert(e.type),c=this.getInternalFormat(e.internalFormat,l,u,e.colorSpace,e.isVideoTexture),d=n.createTexture(),h=this.getGLTextureType(e);i.state.bindTexture(h,d),this.setTextureParameters(h,e),e.isArrayTexture||e.isDataArrayTexture||e.isCompressedArrayTexture?n.texStorage3D(n.TEXTURE_2D_ARRAY,r,c,s,o,a):e.isData3DTexture?n.texStorage3D(n.TEXTURE_3D,r,c,s,o,a):e.isVideoTexture||n.texStorage2D(h,r,c,s,o),i.set(e,{textureGPU:d,glTextureType:h,glFormat:l,glType:u,glInternalFormat:c})}copyBufferToTexture(e,t){const{gl:n,backend:i}=this,{textureGPU:r,glTextureType:s,glFormat:o,glType:a}=i.get(t),{width:l,height:u}=t.source.data;n.bindBuffer(n.PIXEL_UNPACK_BUFFER,e),i.state.bindTexture(s,r),n.pixelStorei(n.UNPACK_FLIP_Y_WEBGL,!1),n.pixelStorei(n.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!1),n.texSubImage2D(s,0,0,0,l,u,o,a,0),n.bindBuffer(n.PIXEL_UNPACK_BUFFER,null),i.state.unbindTexture()}updateTexture(e,t){const{gl:n}=this,{width:i,height:r}=t,{textureGPU:s,glTextureType:o,glFormat:a,glType:l,glInternalFormat:u}=this.backend.get(e);if(!e.isRenderTargetTexture&&void 0!==s)if(this.backend.state.bindTexture(o,s),this.setTextureParameters(o,e),e.isCompressedTexture){const i=e.mipmaps,r=t.image;for(let t=0;t<i.length;t++){const s=i[t];e.isCompressedArrayTexture?e.format!==n.RGBA?null!==a?n.compressedTexSubImage3D(n.TEXTURE_2D_ARRAY,t,0,0,0,s.width,s.height,r.depth,a,s.data):console.warn("THREE.WebGLRenderer: Attempt to load unsupported compressed texture format in .uploadTexture()"):n.texSubImage3D(n.TEXTURE_2D_ARRAY,t,0,0,0,s.width,s.height,r.depth,a,l,s.data):null!==a?n.compressedTexSubImage2D(n.TEXTURE_2D,t,0,0,s.width,s.height,a,s.data):console.warn("Unsupported compressed texture format")}}else if(e.isCubeTexture){const s=t.images,o=e.mipmaps;for(let e=0;e<6;e++){const t=wL(s[e]);n.texSubImage2D(n.TEXTURE_CUBE_MAP_POSITIVE_X+e,0,0,0,i,r,a,l,t);for(let t=0;t<o.length;t++){const i=wL(o[t].images[e]);n.texSubImage2D(n.TEXTURE_CUBE_MAP_POSITIVE_X+e,t+1,0,0,i.width,i.height,a,l,i)}}}else if(e.isDataArrayTexture||e.isArrayTexture){const i=t.image;if(e.layerUpdates.size>0){const t=zc(i.width,i.height,e.format,e.type);for(const r of e.layerUpdates){const e=i.data.subarray(r*t/i.data.BYTES_PER_ELEMENT,(r+1)*t/i.data.BYTES_PER_ELEMENT);n.texSubImage3D(n.TEXTURE_2D_ARRAY,0,0,0,r,i.width,i.height,1,a,l,e)}e.clearLayerUpdates()}else n.texSubImage3D(n.TEXTURE_2D_ARRAY,0,0,0,0,i.width,i.height,i.depth,a,l,i.data)}else if(e.isData3DTexture){const e=t.image;n.texSubImage3D(n.TEXTURE_3D,0,0,0,0,e.width,e.height,e.depth,a,l,e.data)}else if(e.isVideoTexture)e.update(),n.texImage2D(o,0,u,a,l,t.image);else{const s=e.mipmaps;if(s.length>0)for(let e=0,t=s.length;e<t;e++){const t=s[e],i=wL(t);n.texSubImage2D(o,e,0,0,t.width,t.height,a,l,i)}else{const e=wL(t.image);n.texSubImage2D(o,0,0,0,i,r,a,l,e)}}}generateMipmaps(e){const{gl:t,backend:n}=this,{textureGPU:i,glTextureType:r}=n.get(e);n.state.bindTexture(r,i),t.generateMipmap(r)}deallocateRenderBuffers(e){const{gl:t,backend:n}=this;if(e){const i=n.get(e);if(i.renderBufferStorageSetup=void 0,i.framebuffers){for(const e in i.framebuffers)t.deleteFramebuffer(i.framebuffers[e]);delete i.framebuffers}if(i.depthRenderbuffer&&(t.deleteRenderbuffer(i.depthRenderbuffer),delete i.depthRenderbuffer),i.stencilRenderbuffer&&(t.deleteRenderbuffer(i.stencilRenderbuffer),delete i.stencilRenderbuffer),i.msaaFrameBuffer&&(t.deleteFramebuffer(i.msaaFrameBuffer),delete i.msaaFrameBuffer),i.msaaRenderbuffers){for(let e=0;e<i.msaaRenderbuffers.length;e++)t.deleteRenderbuffer(i.msaaRenderbuffers[e]);delete i.msaaRenderbuffers}}}destroyTexture(e){const{gl:t,backend:n}=this,{textureGPU:i,renderTarget:r}=n.get(e);this.deallocateRenderBuffers(r),t.deleteTexture(i),n.delete(e)}copyTextureToTexture(e,t,n=null,i=null,r=0,s=0){const{gl:o,backend:a}=this,{state:l}=this.backend,{textureGPU:u,glTextureType:c,glType:d,glFormat:h}=a.get(t);let f,p,g,m,v,A,x,y,b;l.bindTexture(c,u);const w=e.isCompressedTexture?e.mipmaps[s]:e.image;if(null!==n)f=n.max.x-n.min.x,p=n.max.y-n.min.y,g=n.isBox3?n.max.z-n.min.z:1,m=n.min.x,v=n.min.y,A=n.isBox3?n.min.z:0;else{const t=Math.pow(2,-r);f=Math.floor(w.width*t),p=Math.floor(w.height*t),g=e.isDataArrayTexture||e.isArrayTexture?w.depth:e.isData3DTexture?Math.floor(w.depth*t):1,m=0,v=0,A=0}null!==i?(x=i.x,y=i.y,b=i.z):(x=0,y=0,b=0),o.pixelStorei(o.UNPACK_FLIP_Y_WEBGL,t.flipY),o.pixelStorei(o.UNPACK_PREMULTIPLY_ALPHA_WEBGL,t.premultiplyAlpha),o.pixelStorei(o.UNPACK_ALIGNMENT,t.unpackAlignment);const C=o.getParameter(o.UNPACK_ROW_LENGTH),M=o.getParameter(o.UNPACK_IMAGE_HEIGHT),E=o.getParameter(o.UNPACK_SKIP_PIXELS),T=o.getParameter(o.UNPACK_SKIP_ROWS),S=o.getParameter(o.UNPACK_SKIP_IMAGES);o.pixelStorei(o.UNPACK_ROW_LENGTH,w.width),o.pixelStorei(o.UNPACK_IMAGE_HEIGHT,w.height),o.pixelStorei(o.UNPACK_SKIP_PIXELS,m),o.pixelStorei(o.UNPACK_SKIP_ROWS,v),o.pixelStorei(o.UNPACK_SKIP_IMAGES,A);const P=t.isDataArrayTexture||t.isData3DTexture||t.isArrayTexture;if(e.isRenderTargetTexture||e.isDepthTexture){const n=a.get(e),i=a.get(t),r=a.get(n.renderTarget),s=a.get(i.renderTarget),u=r.framebuffers[n.cacheKey],c=s.framebuffers[i.cacheKey];l.bindFramebuffer(o.READ_FRAMEBUFFER,u),l.bindFramebuffer(o.DRAW_FRAMEBUFFER,c);let d=o.COLOR_BUFFER_BIT;e.isDepthTexture&&(d=o.DEPTH_BUFFER_BIT),o.blitFramebuffer(m,v,f,p,x,y,f,p,d,o.NEAREST),l.bindFramebuffer(o.READ_FRAMEBUFFER,null),l.bindFramebuffer(o.DRAW_FRAMEBUFFER,null)}else P?e.isDataTexture||e.isData3DTexture?o.texSubImage3D(c,s,x,y,b,f,p,g,h,d,w.data):t.isCompressedArrayTexture?o.compressedTexSubImage3D(c,s,x,y,b,f,p,g,h,w.data):o.texSubImage3D(c,s,x,y,b,f,p,g,h,d,w):e.isDataTexture?o.texSubImage2D(c,s,x,y,f,p,h,d,w.data):e.isCompressedTexture?o.compressedTexSubImage2D(c,s,x,y,w.width,w.height,h,w.data):o.texSubImage2D(c,s,x,y,f,p,h,d,w);o.pixelStorei(o.UNPACK_ROW_LENGTH,C),o.pixelStorei(o.UNPACK_IMAGE_HEIGHT,M),o.pixelStorei(o.UNPACK_SKIP_PIXELS,E),o.pixelStorei(o.UNPACK_SKIP_ROWS,T),o.pixelStorei(o.UNPACK_SKIP_IMAGES,S),0===s&&t.generateMipmaps&&o.generateMipmap(c),l.unbindTexture()}copyFramebufferToTexture(e,t,n){const{gl:i}=this,{state:r}=this.backend,{textureGPU:s}=this.backend.get(e),{x:o,y:a,z:l,w:u}=n,c=!0===e.isDepthTexture||t.renderTarget&&t.renderTarget.samples>0,d=t.renderTarget?t.renderTarget.height:this.backend.getDrawingBufferSize().y;if(c){const n=0!==o||0!==a;let c,h;if(!0===e.isDepthTexture?(c=i.DEPTH_BUFFER_BIT,h=i.DEPTH_ATTACHMENT,t.stencil&&(c|=i.STENCIL_BUFFER_BIT)):(c=i.COLOR_BUFFER_BIT,h=i.COLOR_ATTACHMENT0),n){const e=this.backend.get(t.renderTarget),n=e.framebuffers[t.getCacheKey()],h=e.msaaFrameBuffer;r.bindFramebuffer(i.DRAW_FRAMEBUFFER,n),r.bindFramebuffer(i.READ_FRAMEBUFFER,h);const f=d-a-u;i.blitFramebuffer(o,f,o+l,f+u,o,f,o+l,f+u,c,i.NEAREST),r.bindFramebuffer(i.READ_FRAMEBUFFER,n),r.bindTexture(i.TEXTURE_2D,s),i.copyTexSubImage2D(i.TEXTURE_2D,0,0,0,o,f,l,u),r.unbindTexture()}else{const e=i.createFramebuffer();r.bindFramebuffer(i.DRAW_FRAMEBUFFER,e),i.framebufferTexture2D(i.DRAW_FRAMEBUFFER,h,i.TEXTURE_2D,s,0),i.blitFramebuffer(0,0,l,u,0,0,l,u,c,i.NEAREST),i.deleteFramebuffer(e)}}else r.bindTexture(i.TEXTURE_2D,s),i.copyTexSubImage2D(i.TEXTURE_2D,0,0,0,o,d-u-a,l,u),r.unbindTexture();e.generateMipmaps&&this.generateMipmaps(e),this.backend._setFramebuffer(t)}setupRenderBufferStorage(e,t,n,i=!1){const{gl:r}=this,s=t.renderTarget,{depthTexture:o,depthBuffer:a,stencilBuffer:l,width:u,height:c}=s;if(r.bindRenderbuffer(r.RENDERBUFFER,e),a&&!l){let t=r.DEPTH_COMPONENT24;if(!0===i){this.extensions.get("WEBGL_multisampled_render_to_texture").renderbufferStorageMultisampleEXT(r.RENDERBUFFER,s.samples,t,u,c)}else n>0?(o&&o.isDepthTexture&&o.type===r.FLOAT&&(t=r.DEPTH_COMPONENT32F),r.renderbufferStorageMultisample(r.RENDERBUFFER,n,t,u,c)):r.renderbufferStorage(r.RENDERBUFFER,t,u,c);r.framebufferRenderbuffer(r.FRAMEBUFFER,r.DEPTH_ATTACHMENT,r.RENDERBUFFER,e)}else a&&l&&(n>0?r.renderbufferStorageMultisample(r.RENDERBUFFER,n,r.DEPTH24_STENCIL8,u,c):r.renderbufferStorage(r.RENDERBUFFER,r.DEPTH_STENCIL,u,c),r.framebufferRenderbuffer(r.FRAMEBUFFER,r.DEPTH_STENCIL_ATTACHMENT,r.RENDERBUFFER,e));r.bindRenderbuffer(r.RENDERBUFFER,null)}async copyTextureToBuffer(e,t,n,i,r,s){const{backend:o,gl:a}=this,{textureGPU:l,glFormat:u,glType:c}=this.backend.get(e),d=a.createFramebuffer();a.bindFramebuffer(a.READ_FRAMEBUFFER,d);const h=e.isCubeTexture?a.TEXTURE_CUBE_MAP_POSITIVE_X+s:a.TEXTURE_2D;a.framebufferTexture2D(a.READ_FRAMEBUFFER,a.COLOR_ATTACHMENT0,h,l,0);const f=this._getTypedArrayType(c),p=i*r*this._getBytesPerTexel(c,u),g=a.createBuffer();a.bindBuffer(a.PIXEL_PACK_BUFFER,g),a.bufferData(a.PIXEL_PACK_BUFFER,p,a.STREAM_READ),a.readPixels(t,n,i,r,u,c,0),a.bindBuffer(a.PIXEL_PACK_BUFFER,null),await o.utils._clientWaitAsync();const m=new f(p/f.BYTES_PER_ELEMENT);return a.bindBuffer(a.PIXEL_PACK_BUFFER,g),a.getBufferSubData(a.PIXEL_PACK_BUFFER,0,m),a.bindBuffer(a.PIXEL_PACK_BUFFER,null),a.deleteFramebuffer(d),m}_getTypedArrayType(e){const{gl:t}=this;if(e===t.UNSIGNED_BYTE)return Uint8Array;if(e===t.UNSIGNED_SHORT_4_4_4_4)return Uint16Array;if(e===t.UNSIGNED_SHORT_5_5_5_1)return Uint16Array;if(e===t.UNSIGNED_SHORT_5_6_5)return Uint16Array;if(e===t.UNSIGNED_SHORT)return Uint16Array;if(e===t.UNSIGNED_INT)return Uint32Array;if(e===t.HALF_FLOAT)return Uint16Array;if(e===t.FLOAT)return Float32Array;throw new Error(`Unsupported WebGL type: ${e}`)}_getBytesPerTexel(e,t){const{gl:n}=this;let i=0;return e===n.UNSIGNED_BYTE&&(i=1),e!==n.UNSIGNED_SHORT_4_4_4_4&&e!==n.UNSIGNED_SHORT_5_5_5_1&&e!==n.UNSIGNED_SHORT_5_6_5&&e!==n.UNSIGNED_SHORT&&e!==n.HALF_FLOAT||(i=2),e!==n.UNSIGNED_INT&&e!==n.FLOAT||(i=4),t===n.RGBA?4*i:t===n.RGB?3*i:t===n.ALPHA?i:void 0}}function wL(e){return e.isDataTexture?e.image.data:"undefined"!=typeof HTMLImageElement&&e instanceof HTMLImageElement||"undefined"!=typeof HTMLCanvasElement&&e instanceof HTMLCanvasElement||"undefined"!=typeof ImageBitmap&&e instanceof ImageBitmap||"undefined"!=typeof OffscreenCanvas&&e instanceof OffscreenCanvas?e:e.data}class CL{constructor(e){this.backend=e,this.gl=this.backend.gl,this.availableExtensions=this.gl.getSupportedExtensions(),this.extensions={}}get(e){let t=this.extensions[e];return void 0===t&&(t=this.gl.getExtension(e),this.extensions[e]=t),t}has(e){return this.availableExtensions.includes(e)}}class ML{constructor(e){this.backend=e,this.maxAnisotropy=null}getMaxAnisotropy(){if(null!==this.maxAnisotropy)return this.maxAnisotropy;const e=this.backend.gl,t=this.backend.extensions;if(!0===t.has("EXT_texture_filter_anisotropic")){const n=t.get("EXT_texture_filter_anisotropic");this.maxAnisotropy=e.getParameter(n.MAX_TEXTURE_MAX_ANISOTROPY_EXT)}else this.maxAnisotropy=0;return this.maxAnisotropy}}const EL={WEBGL_multi_draw:"WEBGL_multi_draw",WEBGL_compressed_texture_astc:"texture-compression-astc",WEBGL_compressed_texture_etc:"texture-compression-etc2",WEBGL_compressed_texture_etc1:"texture-compression-etc1",WEBGL_compressed_texture_pvrtc:"texture-compression-pvrtc",WEBKIT_WEBGL_compressed_texture_pvrtc:"texture-compression-pvrtc",WEBGL_compressed_texture_s3tc:"texture-compression-bc",EXT_texture_compression_bptc:"texture-compression-bptc",EXT_disjoint_timer_query_webgl2:"timestamp-query",OVR_multiview2:"OVR_multiview2"};class TL{constructor(e){this.gl=e.gl,this.extensions=e.extensions,this.info=e.renderer.info,this.mode=null,this.index=0,this.type=null,this.object=null}render(e,t){const{gl:n,mode:i,object:r,type:s,info:o,index:a}=this;0!==a?n.drawElements(i,t,s,e):n.drawArrays(i,e,t),o.update(r,t,1)}renderInstances(e,t,n){const{gl:i,mode:r,type:s,index:o,object:a,info:l}=this;0!==n&&(0!==o?i.drawElementsInstanced(r,t,s,e,n):i.drawArraysInstanced(r,e,t,n),l.update(a,t,n))}renderMultiDraw(e,t,n){const{extensions:i,mode:r,object:s,info:o}=this;if(0===n)return;const a=i.get("WEBGL_multi_draw");if(null===a)for(let i=0;i<n;i++)this.render(e[i],t[i]);else{0!==this.index?a.multiDrawElementsWEBGL(r,t,0,this.type,e,0,n):a.multiDrawArraysWEBGL(r,e,0,t,0,n);let i=0;for(let e=0;e<n;e++)i+=t[e];o.update(s,i,1)}}renderMultiDrawInstances(e,t,n,i){const{extensions:r,mode:s,object:o,info:a}=this;if(0===n)return;const l=r.get("WEBGL_multi_draw");if(null===l)for(let r=0;r<n;r++)this.renderInstances(e[r],t[r],i[r]);else{0!==this.index?l.multiDrawElementsInstancedWEBGL(s,t,0,this.type,e,0,i,0,n):l.multiDrawArraysInstancedWEBGL(s,e,0,t,0,i,0,n);let r=0;for(let e=0;e<n;e++)r+=t[e]*i[e];a.update(o,r,1)}}}class SL{constructor(e=256){this.trackTimestamp=!0,this.maxQueries=e,this.currentQueryIndex=0,this.queryOffsets=new Map,this.isDisposed=!1,this.lastValue=0,this.pendingResolve=!1}allocateQueriesForContext(){}async resolveQueriesAsync(){}dispose(){}}class PL extends SL{constructor(e,t,n=2048){if(super(n),this.gl=e,this.type=t,this.ext=e.getExtension("EXT_disjoint_timer_query_webgl2")||e.getExtension("EXT_disjoint_timer_query"),!this.ext)return console.warn("EXT_disjoint_timer_query not supported; timestamps will be disabled."),void(this.trackTimestamp=!1);this.queries=[];for(let t=0;t<this.maxQueries;t++)this.queries.push(e.createQuery());this.activeQuery=null,this.queryStates=new Map}allocateQueriesForContext(e){if(!this.trackTimestamp)return null;if(this.currentQueryIndex+2>this.maxQueries)return js(`WebGPUTimestampQueryPool [${this.type}]: Maximum number of queries exceeded, when using trackTimestamp it is necessary to resolves the queries via renderer.resolveTimestampsAsync( THREE.TimestampQuery.${this.type.toUpperCase()} ).`),null;const t=this.currentQueryIndex;return this.currentQueryIndex+=2,this.queryStates.set(t,"inactive"),this.queryOffsets.set(e,t),t}beginQuery(e){if(!this.trackTimestamp||this.isDisposed)return;const t=this.queryOffsets.get(e);if(null==t)return;if(null!==this.activeQuery)return;const n=this.queries[t];if(n)try{"inactive"===this.queryStates.get(t)&&(this.gl.beginQuery(this.ext.TIME_ELAPSED_EXT,n),this.activeQuery=t,this.queryStates.set(t,"started"))}catch(e){console.error("Error in beginQuery:",e),this.activeQuery=null,this.queryStates.set(t,"inactive")}}endQuery(e){if(!this.trackTimestamp||this.isDisposed)return;const t=this.queryOffsets.get(e);if(null!=t&&this.activeQuery===t)try{this.gl.endQuery(this.ext.TIME_ELAPSED_EXT),this.queryStates.set(t,"ended"),this.activeQuery=null}catch(e){console.error("Error in endQuery:",e),this.queryStates.set(t,"inactive"),this.activeQuery=null}}async resolveQueriesAsync(){if(!this.trackTimestamp||this.pendingResolve)return this.lastValue;this.pendingResolve=!0;try{const e=[];for(const[t,n]of this.queryStates)if("ended"===n){const n=this.queries[t];e.push(this.resolveQuery(n))}if(0===e.length)return this.lastValue;const t=(await Promise.all(e)).reduce(((e,t)=>e+t),0);return this.lastValue=t,this.currentQueryIndex=0,this.queryOffsets.clear(),this.queryStates.clear(),this.activeQuery=null,t}catch(e){return console.error("Error resolving queries:",e),this.lastValue}finally{this.pendingResolve=!1}}async resolveQuery(e){return new Promise((t=>{if(this.isDisposed)return void t(this.lastValue);let n,i=!1;const r=e=>{i||(i=!0,n&&(clearTimeout(n),n=null),t(e))},s=()=>{if(this.isDisposed)r(this.lastValue);else try{if(this.gl.getParameter(this.ext.GPU_DISJOINT_EXT))return void r(this.lastValue);if(!this.gl.getQueryParameter(e,this.gl.QUERY_RESULT_AVAILABLE))return void(n=setTimeout(s,1));const i=this.gl.getQueryParameter(e,this.gl.QUERY_RESULT);t(Number(i)/1e6)}catch(e){console.error("Error checking query:",e),t(this.lastValue)}};s()}))}dispose(){if(!this.isDisposed&&(this.isDisposed=!0,this.trackTimestamp)){for(const e of this.queries)this.gl.deleteQuery(e);this.queries=[],this.queryStates.clear(),this.queryOffsets.clear(),this.lastValue=0,this.activeQuery=null}}}class NL extends uL{constructor(e={}){super(e),this.isWebGLBackend=!0,this.attributeUtils=null,this.extensions=null,this.capabilities=null,this.textureUtils=null,this.bufferRenderer=null,this.gl=null,this.state=null,this.utils=null,this.vaoCache={},this.transformFeedbackCache={},this.discard=!1,this.disjoint=null,this.parallel=null,this._currentContext=null,this._knownBindings=new WeakSet,this._supportsInvalidateFramebuffer="undefined"!=typeof navigator&&/OculusBrowser/g.test(navigator.userAgent),this._xrFramebuffer=null}init(e){super.init(e);const t=this.parameters,n={antialias:e.samples>0,alpha:!0,depth:e.depth,stencil:e.stencil},i=void 0!==t.context?t.context:e.domElement.getContext("webgl2",n);function r(t){t.preventDefault();const n={api:"WebGL",message:t.statusMessage||"Unknown reason",reason:null,originalEvent:t};e.onDeviceLost(n)}this._onContextLost=r,e.domElement.addEventListener("webglcontextlost",r,!1),this.gl=i,this.extensions=new CL(this),this.capabilities=new ML(this),this.attributeUtils=new pL(this),this.textureUtils=new bL(this),this.bufferRenderer=new TL(this),this.state=new gL(this),this.utils=new mL(this),this.extensions.get("EXT_color_buffer_float"),this.extensions.get("WEBGL_clip_cull_distance"),this.extensions.get("OES_texture_float_linear"),this.extensions.get("EXT_color_buffer_half_float"),this.extensions.get("WEBGL_multisampled_render_to_texture"),this.extensions.get("WEBGL_render_shared_exponent"),this.extensions.get("WEBGL_multi_draw"),this.extensions.get("OVR_multiview2"),this.disjoint=this.extensions.get("EXT_disjoint_timer_query_webgl2"),this.parallel=this.extensions.get("KHR_parallel_shader_compile")}get coordinateSystem(){return as}async getArrayBufferAsync(e){return await this.attributeUtils.getArrayBufferAsync(e)}async waitForGPU(){await this.utils._clientWaitAsync()}async makeXRCompatible(){!0!==this.gl.getContextAttributes().xrCompatible&&await this.gl.makeXRCompatible()}setXRTarget(e){this._xrFramebuffer=e}setXRRenderTargetTextures(e,t,n=null){const i=this.gl;if(this.set(e.texture,{textureGPU:t,glInternalFormat:i.RGBA8}),null!==n){const t=e.stencilBuffer?i.DEPTH24_STENCIL8:i.DEPTH_COMPONENT24;this.set(e.depthTexture,{textureGPU:n,glInternalFormat:t}),!0===this.extensions.has("WEBGL_multisampled_render_to_texture")&&!0===e._autoAllocateDepthBuffer&&!1===e.multiview&&console.warn("THREE.WebGLBackend: Render-to-texture extension was disabled because an external texture was provided"),e._autoAllocateDepthBuffer=!1}}initTimestampQuery(e,t){if(!this.disjoint||!this.trackTimestamp)return;this.timestampQueryPool[e]||(this.timestampQueryPool[e]=new PL(this.gl,e,2048));const n=this.timestampQueryPool[e];null!==n.allocateQueriesForContext(t)&&n.beginQuery(t)}prepareTimestampBuffer(e,t){if(!this.disjoint||!this.trackTimestamp)return;this.timestampQueryPool[e].endQuery(t)}getContext(){return this.gl}beginRender(e){const{state:t}=this,n=this.get(e);if(n.frameCalls=this.renderer.info.render.frameCalls,e.viewport)this.updateViewport(e);else{const{width:e,height:n}=this.getDrawingBufferSize();t.viewport(0,0,e,n)}if(e.scissor){const{x:n,y:i,width:r,height:s}=e.scissorValue;t.scissor(n,e.height-s-i,r,s)}this.initTimestampQuery(cs,this.getTimestampUID(e)),n.previousContext=this._currentContext,this._currentContext=e,this._setFramebuffer(e),this.clear(e.clearColor,e.clearDepth,e.clearStencil,e,!1);const i=e.occlusionQueryCount;i>0&&(n.currentOcclusionQueries=n.occlusionQueries,n.currentOcclusionQueryObjects=n.occlusionQueryObjects,n.lastOcclusionObject=null,n.occlusionQueries=new Array(i),n.occlusionQueryObjects=new Array(i),n.occlusionQueryIndex=0)}finishRender(e){const{gl:t,state:n}=this,i=this.get(e),r=i.previousContext;n.resetVertexState();const s=e.occlusionQueryCount;s>0&&(s>i.occlusionQueryIndex&&t.endQuery(t.ANY_SAMPLES_PASSED),this.resolveOccludedAsync(e));const o=e.textures;if(null!==o)for(let e=0;e<o.length;e++){const t=o[e];t.generateMipmaps&&this.generateMipmaps(t)}if(this._currentContext=r,this._resolveRenderTarget(e),null!==r)if(this._setFramebuffer(r),r.viewport)this.updateViewport(r);else{const{width:e,height:t}=this.getDrawingBufferSize();n.viewport(0,0,e,t)}this.prepareTimestampBuffer(cs,this.getTimestampUID(e))}resolveOccludedAsync(e){const t=this.get(e),{currentOcclusionQueries:n,currentOcclusionQueryObjects:i}=t;if(n&&i){const e=new WeakSet,{gl:r}=this;t.currentOcclusionQueryObjects=null,t.currentOcclusionQueries=null;const s=()=>{let o=0;for(let t=0;t<n.length;t++){const s=n[t];null!==s&&(r.getQueryParameter(s,r.QUERY_RESULT_AVAILABLE)&&(0===r.getQueryParameter(s,r.QUERY_RESULT)&&e.add(i[t]),n[t]=null,r.deleteQuery(s),o++))}o<n.length?requestAnimationFrame(s):t.occluded=e};s()}}isOccluded(e,t){const n=this.get(e);return n.occluded&&n.occluded.has(t)}updateViewport(e){const{state:t}=this,{x:n,y:i,width:r,height:s}=e.viewportValue;t.viewport(n,e.height-s-i,r,s)}setScissorTest(e){this.state.setScissorTest(e)}getClearColor(){const e=super.getClearColor();return e.r*=e.a,e.g*=e.a,e.b*=e.a,e}clear(e,t,n,i=null,r=!0,s=!0){const{gl:o,renderer:a}=this;if(null===i){i={textures:null,clearColorValue:this.getClearColor()}}let l=0;if(e&&(l|=o.COLOR_BUFFER_BIT),t&&(l|=o.DEPTH_BUFFER_BIT),n&&(l|=o.STENCIL_BUFFER_BIT),0!==l){let u;u=i.clearColorValue?i.clearColorValue:this.getClearColor();const c=a.getClearDepth(),d=a.getClearStencil();if(t&&this.state.setDepthMask(!0),null===i.textures)o.clearColor(u.r,u.g,u.b,u.a),o.clear(l);else{if(r&&this._setFramebuffer(i),e)for(let e=0;e<i.textures.length;e++)0===e?o.clearBufferfv(o.COLOR,e,[u.r,u.g,u.b,u.a]):o.clearBufferfv(o.COLOR,e,[0,0,0,1]);t&&n?o.clearBufferfi(o.DEPTH_STENCIL,0,c,d):t?o.clearBufferfv(o.DEPTH,0,[c]):n&&o.clearBufferiv(o.STENCIL,0,[d]),r&&s&&this._resolveRenderTarget(i)}}}beginCompute(e){const{state:t,gl:n}=this;this.get(e).frameCalls=this.renderer.info.compute.frameCalls,t.bindFramebuffer(n.FRAMEBUFFER,null),this.initTimestampQuery(us,this.getTimestampUID(e))}compute(e,t,n,i,r=null){const{state:s,gl:o}=this;!1===this.discard&&(o.enable(o.RASTERIZER_DISCARD),this.discard=!0);const{programGPU:a,transformBuffers:l,attributes:u}=this.get(i),c=this._getVaoKey(u),d=this.vaoCache[c];void 0===d?this.vaoCache[c]=this._createVao(u):s.setVertexState(d),s.useProgram(a),this._bindUniforms(n);const h=this._getTransformFeedback(l);o.bindTransformFeedback(o.TRANSFORM_FEEDBACK,h),o.beginTransformFeedback(o.POINTS),r=null!==r?r:t.count,Array.isArray(r)&&(js("WebGLBackend.compute(): The count parameter must be a single number, not an array."),r=r[0]),u[0].isStorageInstancedBufferAttribute?o.drawArraysInstanced(o.POINTS,0,1,r):o.drawArrays(o.POINTS,0,r),o.endTransformFeedback(),o.bindTransformFeedback(o.TRANSFORM_FEEDBACK,null);for(let e=0;e<l.length;e++){const t=l[e];t.pbo&&this.has(t.pbo)&&this.textureUtils.copyBufferToTexture(t.transformBuffer,t.pbo),t.switchBuffers()}}finishCompute(e){const t=this.gl;this.discard=!1,t.disable(t.RASTERIZER_DISCARD),this.prepareTimestampBuffer(us,this.getTimestampUID(e)),this._currentContext&&this._setFramebuffer(this._currentContext)}_isRenderCameraDepthArray(e){return e.depthTexture&&e.depthTexture.isArrayTexture&&e.camera.isArrayCamera}draw(e){const{object:t,pipeline:n,material:i,context:r,hardwareClippingPlanes:s}=e,{programGPU:o}=this.get(n),{gl:a,state:l}=this,u=this.get(r),c=e.getDrawParameters();if(null===c)return;this._bindUniforms(e.getBindings());const d=t.isMesh&&t.matrixWorld.determinant()<0;l.setMaterial(i,d,s),l.useProgram(o);const h=e.getAttributes(),f=this.get(h);let p=f.vaoGPU;if(void 0===p){const e=this._getVaoKey(h);p=this.vaoCache[e],void 0===p&&(p=this._createVao(h),this.vaoCache[e]=p,f.vaoGPU=p)}const g=e.getIndex(),m=null!==g?this.get(g).bufferGPU:null;l.setVertexState(p,m);const v=u.lastOcclusionObject;if(v!==t&&void 0!==v){if(null!==v&&!0===v.occlusionTest&&(a.endQuery(a.ANY_SAMPLES_PASSED),u.occlusionQueryIndex++),!0===t.occlusionTest){const e=a.createQuery();a.beginQuery(a.ANY_SAMPLES_PASSED,e),u.occlusionQueries[u.occlusionQueryIndex]=e,u.occlusionQueryObjects[u.occlusionQueryIndex]=t}u.lastOcclusionObject=t}const A=this.bufferRenderer;t.isPoints?A.mode=a.POINTS:t.isLineSegments?A.mode=a.LINES:t.isLine?A.mode=a.LINE_STRIP:t.isLineLoop?A.mode=a.LINE_LOOP:!0===i.wireframe?(l.setLineWidth(i.wireframeLinewidth*this.renderer.getPixelRatio()),A.mode=a.LINES):A.mode=a.TRIANGLES;const{vertexCount:x,instanceCount:y}=c;let{firstVertex:b}=c;if(A.object=t,null!==g){b*=g.array.BYTES_PER_ELEMENT;const e=this.get(g);A.index=g.count,A.type=e.type}else A.index=0;const w=()=>{t.isBatchedMesh?null!==t._multiDrawInstances?(js("THREE.WebGLBackend: renderMultiDrawInstances has been deprecated and will be removed in r184. Append to renderMultiDraw arguments and use indirection."),A.renderMultiDrawInstances(t._multiDrawStarts,t._multiDrawCounts,t._multiDrawCount,t._multiDrawInstances)):this.hasFeature("WEBGL_multi_draw")?A.renderMultiDraw(t._multiDrawStarts,t._multiDrawCounts,t._multiDrawCount):js("THREE.WebGLRenderer: WEBGL_multi_draw not supported."):y>1?A.renderInstances(b,x,y):A.render(b,x)};if(!0===e.camera.isArrayCamera&&e.camera.cameras.length>0&&!1===e.camera.isMultiViewCamera){const n=this.get(e.camera),i=e.camera.cameras,r=e.getBindingGroup("cameraIndex").bindings[0];if(void 0===n.indexesGPU||n.indexesGPU.length!==i.length){const e=new Uint32Array([0,0,0,0]),t=[];for(let n=0,r=i.length;n<r;n++){const i=a.createBuffer();e[0]=n,a.bindBuffer(a.UNIFORM_BUFFER,i),a.bufferData(a.UNIFORM_BUFFER,e,a.STATIC_DRAW),t.push(i)}n.indexesGPU=t}const s=this.get(r),o=this.renderer.getPixelRatio(),u=this._currentContext.renderTarget,c=this._isRenderCameraDepthArray(this._currentContext),d=this._currentContext.activeCubeFace;if(c){const e=this.get(u.depthTexture);if(e.clearedRenderId!==this.renderer._nodes.nodeFrame.renderId){e.clearedRenderId=this.renderer._nodes.nodeFrame.renderId;const{stencilBuffer:t}=u;for(let e=0,n=i.length;e<n;e++)this.renderer._activeCubeFace=e,this._currentContext.activeCubeFace=e,this._setFramebuffer(this._currentContext),this.clear(!1,!0,t,this._currentContext,!1,!1);this.renderer._activeCubeFace=d,this._currentContext.activeCubeFace=d}}for(let r=0,u=i.length;r<u;r++){const u=i[r];if(t.layers.test(u.layers)){c&&(this.renderer._activeCubeFace=r,this._currentContext.activeCubeFace=r,this._setFramebuffer(this._currentContext));const t=u.viewport;if(void 0!==t){const n=t.x*o,i=t.y*o,r=t.width*o,s=t.height*o;l.viewport(Math.floor(n),Math.floor(e.context.height-s-i),Math.floor(r),Math.floor(s))}l.bindBufferBase(a.UNIFORM_BUFFER,s.index,n.indexesGPU[r]),w()}this._currentContext.activeCubeFace=d,this.renderer._activeCubeFace=d}}else w()}needsRenderUpdate(){return!1}getRenderCacheKey(){return""}createDefaultTexture(e){this.textureUtils.createDefaultTexture(e)}createTexture(e,t){this.textureUtils.createTexture(e,t)}updateTexture(e,t){this.textureUtils.updateTexture(e,t)}generateMipmaps(e){this.textureUtils.generateMipmaps(e)}destroyTexture(e){this.textureUtils.destroyTexture(e)}async copyTextureToBuffer(e,t,n,i,r,s){return this.textureUtils.copyTextureToBuffer(e,t,n,i,r,s)}createSampler(){}destroySampler(){}createNodeBuilder(e,t){return new oL(e,t)}createProgram(e){const t=this.gl,{stage:n,code:i}=e,r="fragment"===n?t.createShader(t.FRAGMENT_SHADER):t.createShader(t.VERTEX_SHADER);t.shaderSource(r,i),t.compileShader(r),this.set(e,{shaderGPU:r})}destroyProgram(e){this.delete(e)}createRenderPipeline(e,t){const n=this.gl,i=e.pipeline,{fragmentProgram:r,vertexProgram:s}=i,o=n.createProgram(),a=this.get(r).shaderGPU,l=this.get(s).shaderGPU;if(n.attachShader(o,a),n.attachShader(o,l),n.linkProgram(o),this.set(i,{programGPU:o,fragmentShader:a,vertexShader:l}),null!==t&&this.parallel){const r=new Promise((t=>{const r=this.parallel,s=()=>{n.getProgramParameter(o,r.COMPLETION_STATUS_KHR)?(this._completeCompile(e,i),t()):requestAnimationFrame(s)};s()}));t.push(r)}else this._completeCompile(e,i)}_handleSource(e,t){const n=e.split("\n"),i=[],r=Math.max(t-6,0),s=Math.min(t+6,n.length);for(let e=r;e<s;e++){const r=e+1;i.push(`${r===t?">":" "} ${r}: ${n[e]}`)}return i.join("\n")}_getShaderErrors(e,t,n){const i=e.getShaderParameter(t,e.COMPILE_STATUS),r=(e.getShaderInfoLog(t)||"").trim();if(i&&""===r)return"";const s=/ERROR: 0:(\d+)/.exec(r);if(s){const i=parseInt(s[1]);return n.toUpperCase()+"\n\n"+r+"\n\n"+this._handleSource(e.getShaderSource(t),i)}return r}_logProgramError(e,t,n){if(this.renderer.debug.checkShaderErrors){const i=this.gl,r=(i.getProgramInfoLog(e)||"").trim();if(!1===i.getProgramParameter(e,i.LINK_STATUS))if("function"==typeof this.renderer.debug.onShaderError)this.renderer.debug.onShaderError(i,e,n,t);else{const s=this._getShaderErrors(i,n,"vertex"),o=this._getShaderErrors(i,t,"fragment");console.error("THREE.WebGLProgram: Shader Error "+i.getError()+" - VALIDATE_STATUS "+i.getProgramParameter(e,i.VALIDATE_STATUS)+"\n\nProgram Info Log: "+r+"\n"+s+"\n"+o)}else""!==r&&console.warn("THREE.WebGLProgram: Program Info Log:",r)}}_completeCompile(e,t){const{state:n,gl:i}=this,r=this.get(t),{programGPU:s,fragmentShader:o,vertexShader:a}=r;!1===i.getProgramParameter(s,i.LINK_STATUS)&&this._logProgramError(s,o,a),n.useProgram(s);const l=e.getBindings();this._setupBindings(l,s),this.set(t,{programGPU:s})}createComputePipeline(e,t){const{state:n,gl:i}=this,r={stage:"fragment",code:"#version 300 es\nprecision highp float;\nvoid main() {}"};this.createProgram(r);const{computeProgram:s}=e,o=i.createProgram(),a=this.get(r).shaderGPU,l=this.get(s).shaderGPU,u=s.transforms,c=[],d=[];for(let e=0;e<u.length;e++){const t=u[e];c.push(t.varyingName),d.push(t.attributeNode)}i.attachShader(o,a),i.attachShader(o,l),i.transformFeedbackVaryings(o,c,i.SEPARATE_ATTRIBS),i.linkProgram(o),!1===i.getProgramParameter(o,i.LINK_STATUS)&&this._logProgramError(o,a,l),n.useProgram(o),this._setupBindings(t,o);const h=s.attributes,f=[],p=[];for(let e=0;e<h.length;e++){const t=h[e].node.attribute;f.push(t),this.has(t)||this.attributeUtils.createAttribute(t,i.ARRAY_BUFFER)}for(let e=0;e<d.length;e++){const t=d[e].attribute;this.has(t)||this.attributeUtils.createAttribute(t,i.ARRAY_BUFFER);const n=this.get(t);p.push(n)}this.set(e,{programGPU:o,transformBuffers:p,attributes:f})}createBindings(e,t){if(!1===this._knownBindings.has(t)){this._knownBindings.add(t);let e=0,n=0;for(const i of t){this.set(i,{textures:n,uniformBuffers:e});for(const t of i.bindings)t.isUniformBuffer&&e++,t.isSampledTexture&&n++}}this.updateBindings(e,t)}updateBindings(e){const{gl:t}=this,n=this.get(e);let i=n.uniformBuffers,r=n.textures;for(const n of e.bindings){const e=this.get(n);if(n.isUniformsGroup||n.isUniformBuffer){const r=n.buffer;let{bufferGPU:s}=this.get(r);void 0===s?(s=t.createBuffer(),t.bindBuffer(t.UNIFORM_BUFFER,s),t.bufferData(t.UNIFORM_BUFFER,r,t.DYNAMIC_DRAW),this.set(r,{bufferGPU:s})):(t.bindBuffer(t.UNIFORM_BUFFER,s),t.bufferSubData(t.UNIFORM_BUFFER,0,r)),e.index=i++,e.bufferGPU=s,this.set(n,e)}else if(n.isSampledTexture){const{textureGPU:t,glTextureType:i}=this.get(n.texture);e.index=r++,e.textureGPU=t,e.glTextureType=i,this.set(n,e)}}}updateBinding(e){const t=this.gl;if(e.isUniformsGroup||e.isUniformBuffer){const n=this.get(e).bufferGPU,i=e.buffer;t.bindBuffer(t.UNIFORM_BUFFER,n),t.bufferData(t.UNIFORM_BUFFER,i,t.DYNAMIC_DRAW)}}createIndexAttribute(e){const t=this.gl;this.attributeUtils.createAttribute(e,t.ELEMENT_ARRAY_BUFFER)}createAttribute(e){if(this.has(e))return;const t=this.gl;this.attributeUtils.createAttribute(e,t.ARRAY_BUFFER)}createStorageAttribute(e){if(this.has(e))return;const t=this.gl;this.attributeUtils.createAttribute(e,t.ARRAY_BUFFER)}updateAttribute(e){this.attributeUtils.updateAttribute(e)}destroyAttribute(e){this.attributeUtils.destroyAttribute(e)}hasFeature(e){const t=Object.keys(EL).filter((t=>EL[t]===e)),n=this.extensions;for(let e=0;e<t.length;e++)if(n.has(t[e]))return!0;return!1}getMaxAnisotropy(){return this.capabilities.getMaxAnisotropy()}copyTextureToTexture(e,t,n=null,i=null,r=0,s=0){this.textureUtils.copyTextureToTexture(e,t,n,i,r,s)}copyFramebufferToTexture(e,t,n){this.textureUtils.copyFramebufferToTexture(e,t,n)}_setFramebuffer(e){const{gl:t,state:n}=this;let i=null;if(null!==e.textures){const r=e.renderTarget,s=this.get(r),{samples:o,depthBuffer:a,stencilBuffer:l}=r,u=!0===r.isWebGLCubeRenderTarget,c=!0===r.isRenderTarget3D,d=r.depth>1,h=!0===r.isXRRenderTarget,f=!0===h&&!0===r._hasExternalTextures;let p=s.msaaFrameBuffer,g=s.depthRenderbuffer;const m=this.extensions.get("WEBGL_multisampled_render_to_texture"),v=this.extensions.get("OVR_multiview2"),A=this._useMultisampledExtension(r),x=fN(e);let y;if(u?(s.cubeFramebuffers||(s.cubeFramebuffers={}),y=s.cubeFramebuffers[x]):h&&!1===f?y=this._xrFramebuffer:(s.framebuffers||(s.framebuffers={}),y=s.framebuffers[x]),void 0===y){y=t.createFramebuffer(),n.bindFramebuffer(t.FRAMEBUFFER,y);const i=e.textures,a=[];if(u){s.cubeFramebuffers[x]=y;const{textureGPU:e}=this.get(i[0]),n=this.renderer._activeCubeFace,r=this.renderer._activeMipmapLevel;t.framebufferTexture2D(t.FRAMEBUFFER,t.COLOR_ATTACHMENT0,t.TEXTURE_CUBE_MAP_POSITIVE_X+n,e,r)}else{s.framebuffers[x]=y;for(let n=0;n<i.length;n++){const s=i[n],a=this.get(s);a.renderTarget=e.renderTarget,a.cacheKey=x;const l=t.COLOR_ATTACHMENT0+n;if(r.multiview)v.framebufferTextureMultisampleMultiviewOVR(t.FRAMEBUFFER,l,a.textureGPU,0,o,0,2);else if(c||d){const e=this.renderer._activeCubeFace,n=this.renderer._activeMipmapLevel;t.framebufferTextureLayer(t.FRAMEBUFFER,l,a.textureGPU,n,e)}else if(A)m.framebufferTexture2DMultisampleEXT(t.FRAMEBUFFER,l,t.TEXTURE_2D,a.textureGPU,0,o);else{const e=this.renderer._activeMipmapLevel;t.framebufferTexture2D(t.FRAMEBUFFER,l,t.TEXTURE_2D,a.textureGPU,e)}}}const h=l?t.DEPTH_STENCIL_ATTACHMENT:t.DEPTH_ATTACHMENT;if(!0===r._autoAllocateDepthBuffer){const n=t.createRenderbuffer();this.textureUtils.setupRenderBufferStorage(n,e,0,A),s.xrDepthRenderbuffer=n,a.push(l?t.DEPTH_STENCIL_ATTACHMENT:t.DEPTH_ATTACHMENT),t.bindRenderbuffer(t.RENDERBUFFER,n),t.framebufferRenderbuffer(t.FRAMEBUFFER,h,t.RENDERBUFFER,n)}else if(null!==e.depthTexture){a.push(l?t.DEPTH_STENCIL_ATTACHMENT:t.DEPTH_ATTACHMENT);const n=this.get(e.depthTexture);if(n.renderTarget=e.renderTarget,n.cacheKey=x,r.multiview)v.framebufferTextureMultisampleMultiviewOVR(t.FRAMEBUFFER,h,n.textureGPU,0,o,0,2);else if(f&&A)m.framebufferTexture2DMultisampleEXT(t.FRAMEBUFFER,h,t.TEXTURE_2D,n.textureGPU,0,o);else if(e.depthTexture.isArrayTexture){const e=this.renderer._activeCubeFace;t.framebufferTextureLayer(t.FRAMEBUFFER,h,n.textureGPU,0,e)}else t.framebufferTexture2D(t.FRAMEBUFFER,h,t.TEXTURE_2D,n.textureGPU,0)}s.depthInvalidationArray=a}else{if(this._isRenderCameraDepthArray(e)){n.bindFramebuffer(t.FRAMEBUFFER,y);const i=this.renderer._activeCubeFace,r=this.get(e.depthTexture),s=l?t.DEPTH_STENCIL_ATTACHMENT:t.DEPTH_ATTACHMENT;t.framebufferTextureLayer(t.FRAMEBUFFER,s,r.textureGPU,0,i)}if((h||A||r.multiview)&&!0!==r._isOpaqueFramebuffer){n.bindFramebuffer(t.FRAMEBUFFER,y);const i=this.get(e.textures[0]);r.multiview?v.framebufferTextureMultisampleMultiviewOVR(t.FRAMEBUFFER,t.COLOR_ATTACHMENT0,i.textureGPU,0,o,0,2):A?m.framebufferTexture2DMultisampleEXT(t.FRAMEBUFFER,t.COLOR_ATTACHMENT0,t.TEXTURE_2D,i.textureGPU,0,o):t.framebufferTexture2D(t.FRAMEBUFFER,t.COLOR_ATTACHMENT0,t.TEXTURE_2D,i.textureGPU,0);const a=l?t.DEPTH_STENCIL_ATTACHMENT:t.DEPTH_ATTACHMENT;if(!0===r._autoAllocateDepthBuffer){const e=s.xrDepthRenderbuffer;t.bindRenderbuffer(t.RENDERBUFFER,e),t.framebufferRenderbuffer(t.FRAMEBUFFER,a,t.RENDERBUFFER,e)}else{const n=this.get(e.depthTexture);r.multiview?v.framebufferTextureMultisampleMultiviewOVR(t.FRAMEBUFFER,a,n.textureGPU,0,o,0,2):A?m.framebufferTexture2DMultisampleEXT(t.FRAMEBUFFER,a,t.TEXTURE_2D,n.textureGPU,0,o):t.framebufferTexture2D(t.FRAMEBUFFER,a,t.TEXTURE_2D,n.textureGPU,0)}}}if(o>0&&!1===A&&!r.multiview){if(void 0===p){const i=[];p=t.createFramebuffer(),n.bindFramebuffer(t.FRAMEBUFFER,p);const r=[],u=e.textures;for(let n=0;n<u.length;n++){r[n]=t.createRenderbuffer(),t.bindRenderbuffer(t.RENDERBUFFER,r[n]),i.push(t.COLOR_ATTACHMENT0+n);const s=e.textures[n],a=this.get(s);t.renderbufferStorageMultisample(t.RENDERBUFFER,o,a.glInternalFormat,e.width,e.height),t.framebufferRenderbuffer(t.FRAMEBUFFER,t.COLOR_ATTACHMENT0+n,t.RENDERBUFFER,r[n])}if(t.bindRenderbuffer(t.RENDERBUFFER,null),s.msaaFrameBuffer=p,s.msaaRenderbuffers=r,a&&void 0===g){g=t.createRenderbuffer(),this.textureUtils.setupRenderBufferStorage(g,e,o),s.depthRenderbuffer=g;const n=l?t.DEPTH_STENCIL_ATTACHMENT:t.DEPTH_ATTACHMENT;i.push(n)}s.invalidationArray=i}i=s.msaaFrameBuffer}else i=y;n.drawBuffers(e,y)}n.bindFramebuffer(t.FRAMEBUFFER,i)}_getVaoKey(e){let t="";for(let n=0;n<e.length;n++){t+=":"+this.get(e[n]).id}return t}_createVao(e){const{gl:t}=this,n=t.createVertexArray();t.bindVertexArray(n);for(let n=0;n<e.length;n++){const i=e[n],r=this.get(i);let s,o;t.bindBuffer(t.ARRAY_BUFFER,r.bufferGPU),t.enableVertexAttribArray(n),!0===i.isInterleavedBufferAttribute?(s=i.data.stride*r.bytesPerElement,o=i.offset*r.bytesPerElement):(s=0,o=0),r.isInteger?t.vertexAttribIPointer(n,i.itemSize,r.type,s,o):t.vertexAttribPointer(n,i.itemSize,r.type,i.normalized,s,o),i.isInstancedBufferAttribute&&!i.isInterleavedBufferAttribute?t.vertexAttribDivisor(n,i.meshPerAttribute):i.isInterleavedBufferAttribute&&i.data.isInstancedInterleavedBuffer&&t.vertexAttribDivisor(n,i.data.meshPerAttribute)}return t.bindBuffer(t.ARRAY_BUFFER,null),n}_getTransformFeedback(e){let t="";for(let n=0;n<e.length;n++)t+=":"+e[n].id;let n=this.transformFeedbackCache[t];if(void 0!==n)return n;const{gl:i}=this;n=i.createTransformFeedback(),i.bindTransformFeedback(i.TRANSFORM_FEEDBACK,n);for(let t=0;t<e.length;t++){const n=e[t];i.bindBufferBase(i.TRANSFORM_FEEDBACK_BUFFER,t,n.transformBuffer)}return i.bindTransformFeedback(i.TRANSFORM_FEEDBACK,null),this.transformFeedbackCache[t]=n,n}_setupBindings(e,t){const n=this.gl;for(const i of e)for(const e of i.bindings){const i=this.get(e).index;if(e.isUniformsGroup||e.isUniformBuffer){const r=n.getUniformBlockIndex(t,e.name);n.uniformBlockBinding(t,r,i)}else if(e.isSampledTexture){const r=n.getUniformLocation(t,e.name);n.uniform1i(r,i)}}}_bindUniforms(e){const{gl:t,state:n}=this;for(const i of e)for(const e of i.bindings){const i=this.get(e),r=i.index;e.isUniformsGroup||e.isUniformBuffer?n.bindBufferBase(t.UNIFORM_BUFFER,r,i.bufferGPU):e.isSampledTexture&&n.bindTexture(i.glTextureType,i.textureGPU,t.TEXTURE0+r)}}_resolveRenderTarget(e){const{gl:t,state:n}=this,i=e.renderTarget;if(null!==e.textures&&i){const r=this.get(i);if(i.samples>0&&!1===this._useMultisampledExtension(i)){const s=r.framebuffers[e.getCacheKey()];let o=t.COLOR_BUFFER_BIT;i.resolveDepthBuffer&&(i.depthBuffer&&(o|=t.DEPTH_BUFFER_BIT),i.stencilBuffer&&i.resolveStencilBuffer&&(o|=t.STENCIL_BUFFER_BIT));const a=r.msaaFrameBuffer,l=r.msaaRenderbuffers,u=e.textures,c=u.length>1;if(n.bindFramebuffer(t.READ_FRAMEBUFFER,a),n.bindFramebuffer(t.DRAW_FRAMEBUFFER,s),c)for(let e=0;e<u.length;e++)t.framebufferRenderbuffer(t.READ_FRAMEBUFFER,t.COLOR_ATTACHMENT0+e,t.RENDERBUFFER,null),t.framebufferTexture2D(t.DRAW_FRAMEBUFFER,t.COLOR_ATTACHMENT0+e,t.TEXTURE_2D,null,0);for(let n=0;n<u.length;n++){if(c){const{textureGPU:e}=this.get(u[n]);t.framebufferRenderbuffer(t.READ_FRAMEBUFFER,t.COLOR_ATTACHMENT0,t.RENDERBUFFER,l[n]),t.framebufferTexture2D(t.DRAW_FRAMEBUFFER,t.COLOR_ATTACHMENT0,t.TEXTURE_2D,e,0)}if(e.scissor){const{x:n,y:i,width:r,height:s}=e.scissorValue,a=e.height-s-i;t.blitFramebuffer(n,a,n+r,a+s,n,a,n+r,a+s,o,t.NEAREST)}else t.blitFramebuffer(0,0,e.width,e.height,0,0,e.width,e.height,o,t.NEAREST)}if(c)for(let e=0;e<u.length;e++){const{textureGPU:n}=this.get(u[e]);t.framebufferRenderbuffer(t.READ_FRAMEBUFFER,t.COLOR_ATTACHMENT0+e,t.RENDERBUFFER,l[e]),t.framebufferTexture2D(t.DRAW_FRAMEBUFFER,t.COLOR_ATTACHMENT0+e,t.TEXTURE_2D,n,0)}!0===this._supportsInvalidateFramebuffer&&t.invalidateFramebuffer(t.READ_FRAMEBUFFER,r.invalidationArray)}else if(!1===i.resolveDepthBuffer&&r.framebuffers){const i=r.framebuffers[e.getCacheKey()];n.bindFramebuffer(t.DRAW_FRAMEBUFFER,i),t.invalidateFramebuffer(t.DRAW_FRAMEBUFFER,r.depthInvalidationArray)}}}_useMultisampledExtension(e){return!0===e.multiview||e.samples>0&&!0===this.extensions.has("WEBGL_multisampled_render_to_texture")&&!1!==e._autoAllocateDepthBuffer}dispose(){const e=this.extensions.get("WEBGL_lose_context");e&&e.loseContext(),this.renderer.domElement.removeEventListener("webglcontextlost",this._onContextLost)}}const BL="point-list",DL="line-list",IL="line-strip",LL="triangle-list",jL="triangle-strip",OL="never",zL="less",RL="equal",kL="less-equal",FL="greater",HL="not-equal",UL="greater-equal",XL="always",GL="store",VL="load",WL="clear",QL="ccw",ZL="cw",YL="none",JL="back",KL="uint16",qL="uint32",_L="r8unorm",$L="r8snorm",ej="r8uint",tj="r8sint",nj="r16uint",ij="r16sint",rj="r16float",sj="rg8unorm",oj="rg8snorm",aj="rg8uint",lj="rg8sint",uj="r32uint",cj="r32sint",dj="r32float",hj="rg16uint",fj="rg16sint",pj="rg16float",gj="rgba8unorm",mj="rgba8unorm-srgb",vj="rgba8snorm",Aj="rgba8uint",xj="rgba8sint",yj="bgra8unorm",bj="bgra8unorm-srgb",wj="rgb9e5ufloat",Cj="rgb10a2unorm",Mj="rg11b10ufloat",Ej="rg32uint",Tj="rg32sint",Sj="rg32float",Pj="rgba16uint",Nj="rgba16sint",Bj="rgba16float",Dj="rgba32uint",Ij="rgba32sint",Lj="rgba32float",jj="depth16unorm",Oj="depth24plus",zj="depth24plus-stencil8",Rj="depth32float",kj="depth32float-stencil8",Fj="bc1-rgba-unorm",Hj="bc1-rgba-unorm-srgb",Uj="bc2-rgba-unorm",Xj="bc2-rgba-unorm-srgb",Gj="bc3-rgba-unorm",Vj="bc3-rgba-unorm-srgb",Wj="bc4-r-unorm",Qj="bc4-r-snorm",Zj="bc5-rg-unorm",Yj="bc5-rg-snorm",Jj="bc6h-rgb-ufloat",Kj="bc6h-rgb-float",qj="bc7-rgba-unorm",_j="bc7-rgba-unorm-srgb",$j="etc2-rgb8unorm",eO="etc2-rgb8unorm-srgb",tO="etc2-rgb8a1unorm",nO="etc2-rgb8a1unorm-srgb",iO="etc2-rgba8unorm",rO="etc2-rgba8unorm-srgb",sO="eac-r11unorm",oO="eac-r11snorm",aO="eac-rg11unorm",lO="eac-rg11snorm",uO="astc-4x4-unorm",cO="astc-4x4-unorm-srgb",dO="astc-5x4-unorm",hO="astc-5x4-unorm-srgb",fO="astc-5x5-unorm",pO="astc-5x5-unorm-srgb",gO="astc-6x5-unorm",mO="astc-6x5-unorm-srgb",vO="astc-6x6-unorm",AO="astc-6x6-unorm-srgb",xO="astc-8x5-unorm",yO="astc-8x5-unorm-srgb",bO="astc-8x6-unorm",wO="astc-8x6-unorm-srgb",CO="astc-8x8-unorm",MO="astc-8x8-unorm-srgb",EO="astc-10x5-unorm",TO="astc-10x5-unorm-srgb",SO="astc-10x6-unorm",PO="astc-10x6-unorm-srgb",NO="astc-10x8-unorm",BO="astc-10x8-unorm-srgb",DO="astc-10x10-unorm",IO="astc-10x10-unorm-srgb",LO="astc-12x10-unorm",jO="astc-12x10-unorm-srgb",OO="astc-12x12-unorm",zO="astc-12x12-unorm-srgb",RO="clamp-to-edge",kO="repeat",FO="mirror-repeat",HO="linear",UO="nearest",XO="zero",GO="one",VO="src",WO="one-minus-src",QO="src-alpha",ZO="one-minus-src-alpha",YO="dst",JO="one-minus-dst",KO="dst-alpha",qO="one-minus-dst-alpha",_O="src-alpha-saturated",$O="constant",ez="one-minus-constant",tz="add",nz="subtract",iz="reverse-subtract",rz="min",sz="max",oz=0,az=15,lz="keep",uz="zero",cz="replace",dz="invert",hz="increment-clamp",fz="decrement-clamp",pz="increment-wrap",gz="decrement-wrap",mz="storage",vz="read-only-storage",Az="write-only",xz="read-only",yz="read-write",bz="non-filtering",wz="comparison",Cz="float",Mz="unfilterable-float",Ez="depth",Tz="sint",Sz="uint",Pz="2d",Nz="3d",Bz="2d",Dz="2d-array",Iz="cube",Lz="3d",jz="all",Oz="vertex",zz="instance",Rz={CoreFeaturesAndLimits:"core-features-and-limits",DepthClipControl:"depth-clip-control",Depth32FloatStencil8:"depth32float-stencil8",TextureCompressionBC:"texture-compression-bc",TextureCompressionBCSliced3D:"texture-compression-bc-sliced-3d",TextureCompressionETC2:"texture-compression-etc2",TextureCompressionASTC:"texture-compression-astc",TextureCompressionASTCSliced3D:"texture-compression-astc-sliced-3d",TimestampQuery:"timestamp-query",IndirectFirstInstance:"indirect-first-instance",ShaderF16:"shader-f16",RG11B10UFloat:"rg11b10ufloat-renderable",BGRA8UNormStorage:"bgra8unorm-storage",Float32Filterable:"float32-filterable",Float32Blendable:"float32-blendable",ClipDistances:"clip-distances",DualSourceBlending:"dual-source-blending",Subgroups:"subgroups",TextureFormatsTier1:"texture-formats-tier1",TextureFormatsTier2:"texture-formats-tier2"};class kz extends YI{constructor(e,t,n){super(e,t?t.value:null),this.textureNode=t,this.groupNode=n}update(){this.texture=this.textureNode.value}}class Fz extends UI{constructor(e,t){super(e,t?t.array:null),this.attribute=t,this.isStorageBuffer=!0}}let Hz=0;class Uz extends Fz{constructor(e,t){super("StorageBuffer_"+Hz++,e?e.value:null),this.nodeUniform=e,this.access=e?e.access:fv.READ_WRITE,this.groupNode=t}get buffer(){return this.nodeUniform.value}}class Xz extends UP{constructor(e){super(),this.device=e;this.mipmapSampler=e.createSampler({minFilter:HO}),this.flipYSampler=e.createSampler({minFilter:UO}),this.transferPipelines={},this.flipYPipelines={},this.mipmapVertexShaderModule=e.createShaderModule({label:"mipmapVertex",code:"\nstruct VarysStruct {\n\t@builtin( position ) Position: vec4<f32>,\n\t@location( 0 ) vTex : vec2<f32>\n};\n\n@vertex\nfn main( @builtin( vertex_index ) vertexIndex : u32 ) -> VarysStruct {\n\n\tvar Varys : VarysStruct;\n\n\tvar pos = array< vec2<f32>, 4 >(\n\t\tvec2<f32>( -1.0,  1.0 ),\n\t\tvec2<f32>(  1.0,  1.0 ),\n\t\tvec2<f32>( -1.0, -1.0 ),\n\t\tvec2<f32>(  1.0, -1.0 )\n\t);\n\n\tvar tex = array< vec2<f32>, 4 >(\n\t\tvec2<f32>( 0.0, 0.0 ),\n\t\tvec2<f32>( 1.0, 0.0 ),\n\t\tvec2<f32>( 0.0, 1.0 ),\n\t\tvec2<f32>( 1.0, 1.0 )\n\t);\n\n\tVarys.vTex = tex[ vertexIndex ];\n\tVarys.Position = vec4<f32>( pos[ vertexIndex ], 0.0, 1.0 );\n\n\treturn Varys;\n\n}\n"}),this.mipmapFragmentShaderModule=e.createShaderModule({label:"mipmapFragment",code:"\n@group( 0 ) @binding( 0 )\nvar imgSampler : sampler;\n\n@group( 0 ) @binding( 1 )\nvar img : texture_2d<f32>;\n\n@fragment\nfn main( @location( 0 ) vTex : vec2<f32> ) -> @location( 0 ) vec4<f32> {\n\n\treturn textureSample( img, imgSampler, vTex );\n\n}\n"}),this.flipYFragmentShaderModule=e.createShaderModule({label:"flipYFragment",code:"\n@group( 0 ) @binding( 0 )\nvar imgSampler : sampler;\n\n@group( 0 ) @binding( 1 )\nvar img : texture_2d<f32>;\n\n@fragment\nfn main( @location( 0 ) vTex : vec2<f32> ) -> @location( 0 ) vec4<f32> {\n\n\treturn textureSample( img, imgSampler, vec2( vTex.x, 1.0 - vTex.y ) );\n\n}\n"})}getTransferPipeline(e){let t=this.transferPipelines[e];return void 0===t&&(t=this.device.createRenderPipeline({label:`mipmap-${e}`,vertex:{module:this.mipmapVertexShaderModule,entryPoint:"main"},fragment:{module:this.mipmapFragmentShaderModule,entryPoint:"main",targets:[{format:e}]},primitive:{topology:jL,stripIndexFormat:qL},layout:"auto"}),this.transferPipelines[e]=t),t}getFlipYPipeline(e){let t=this.flipYPipelines[e];return void 0===t&&(t=this.device.createRenderPipeline({label:`flipY-${e}`,vertex:{module:this.mipmapVertexShaderModule,entryPoint:"main"},fragment:{module:this.flipYFragmentShaderModule,entryPoint:"main",targets:[{format:e}]},primitive:{topology:jL,stripIndexFormat:qL},layout:"auto"}),this.flipYPipelines[e]=t),t}flipY(e,t,n=0){const i=t.format,{width:r,height:s}=t.size,o=this.getTransferPipeline(i),a=this.getFlipYPipeline(i),l=this.device.createTexture({size:{width:r,height:s,depthOrArrayLayers:1},format:i,usage:GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING}),u=e.createView({baseMipLevel:0,mipLevelCount:1,dimension:Bz,baseArrayLayer:n}),c=l.createView({baseMipLevel:0,mipLevelCount:1,dimension:Bz,baseArrayLayer:0}),d=this.device.createCommandEncoder({}),h=(e,t,n)=>{const i=e.getBindGroupLayout(0),r=this.device.createBindGroup({layout:i,entries:[{binding:0,resource:this.flipYSampler},{binding:1,resource:t}]}),s=d.beginRenderPass({colorAttachments:[{view:n,loadOp:WL,storeOp:GL,clearValue:[0,0,0,0]}]});s.setPipeline(e),s.setBindGroup(0,r),s.draw(4,1,0,0),s.end()};h(o,u,c),h(a,c,u),this.device.queue.submit([d.finish()]),l.destroy()}generateMipmaps(e,t,n=0){const i=this.get(e);void 0===i.useCount&&(i.useCount=0,i.layers=[]);const r=i.layers[n]||this._mipmapCreateBundles(e,t,n),s=this.device.createCommandEncoder({});this._mipmapRunBundles(s,r),this.device.queue.submit([s.finish()]),0!==i.useCount&&(i.layers[n]=r),i.useCount++}_mipmapCreateBundles(e,t,n){const i=this.getTransferPipeline(t.format),r=i.getBindGroupLayout(0);let s=e.createView({baseMipLevel:0,mipLevelCount:1,dimension:Bz,baseArrayLayer:n});const o=[];for(let a=1;a<t.mipLevelCount;a++){const l=this.device.createBindGroup({layout:r,entries:[{binding:0,resource:this.mipmapSampler},{binding:1,resource:s}]}),u=e.createView({baseMipLevel:a,mipLevelCount:1,dimension:Bz,baseArrayLayer:n}),c={colorAttachments:[{view:u,loadOp:WL,storeOp:GL,clearValue:[0,0,0,0]}]},d=this.device.createRenderBundleEncoder({colorFormats:[t.format]});d.setPipeline(i),d.setBindGroup(0,l),d.draw(4,1,0,0),o.push({renderBundles:[d.finish()],passDescriptor:c}),s=u}return o}_mipmapRunBundles(e,t){const n=t.length;for(let i=0;i<n;i++){const n=t[i],r=e.beginRenderPass(n.passDescriptor);r.executeBundles(n.renderBundles),r.end()}}}const Gz={512:"never",[ns]:"less",514:"equal",[is]:"less-equal",516:"greater",518:"greater-equal",519:"always",517:"not-equal"},Vz=[0,1,3,2,4,5];class Wz{constructor(e){this.backend=e,this._passUtils=null,this.defaultTexture={},this.defaultCubeTexture={},this.defaultVideoFrame=null,this.colorBuffer=null,this.depthTexture=new _l,this.depthTexture.name="depthBuffer"}createSampler(e){const t=this.backend,n=t.device,i=t.get(e),r={addressModeU:this._convertAddressMode(e.wrapS),addressModeV:this._convertAddressMode(e.wrapT),addressModeW:this._convertAddressMode(e.wrapR),magFilter:this._convertFilterMode(e.magFilter),minFilter:this._convertFilterMode(e.minFilter),mipmapFilter:this._convertFilterMode(e.minFilter),maxAnisotropy:1};r.magFilter===HO&&r.minFilter===HO&&r.mipmapFilter===HO&&(r.maxAnisotropy=e.anisotropy),e.isDepthTexture&&null!==e.compareFunction&&(r.compare=Gz[e.compareFunction]),i.sampler=n.createSampler(r)}createDefaultTexture(e){let t;const n=Qz(e);t=e.isCubeTexture?this._getDefaultCubeTextureGPU(n):this._getDefaultTextureGPU(n),this.backend.get(e).texture=t}createTexture(e,t={}){const n=this.backend,i=n.get(e);if(i.initialized)throw new Error("WebGPUTextureUtils: Texture already initialized.");if(e.isExternalTexture)return i.texture=e.sourceTexture,void(i.initialized=!0);void 0===t.needsMipmaps&&(t.needsMipmaps=!1),void 0===t.levels&&(t.levels=1),void 0===t.depth&&(t.depth=1);const{width:r,height:s,depth:o,levels:a}=t;e.isFramebufferTexture&&(t.renderTarget?t.format=this.backend.utils.getCurrentColorFormat(t.renderTarget):t.format=this.backend.utils.getPreferredCanvasFormat());const l=this._getDimension(e),u=e.internalFormat||t.format||Qz(e,n.device);i.format=u;const{samples:c,primarySamples:d,isMSAA:h}=n.utils.getTextureSampleData(e);let f=GPUTextureUsage.TEXTURE_BINDING|GPUTextureUsage.COPY_DST|GPUTextureUsage.COPY_SRC;!0===e.isStorageTexture&&(f|=GPUTextureUsage.STORAGE_BINDING),!0!==e.isCompressedTexture&&!0!==e.isCompressedArrayTexture&&u!==wj&&(f|=GPUTextureUsage.RENDER_ATTACHMENT);const p={label:e.name,size:{width:r,height:s,depthOrArrayLayers:o},mipLevelCount:a,sampleCount:d,dimension:l,format:u,usage:f};if(void 0===u)return console.warn("WebGPURenderer: Texture format not supported."),void this.createDefaultTexture(e);if(e.isCubeTexture&&(p.textureBindingViewDimension=Iz),i.texture=n.device.createTexture(p),h){const e=Object.assign({},p);e.label=e.label+"-msaa",e.sampleCount=c,e.mipLevelCount=1,i.msaaTexture=n.device.createTexture(e)}i.initialized=!0,i.textureDescriptorGPU=p}destroyTexture(e){const t=this.backend,n=t.get(e);void 0!==n.texture&&n.texture.destroy(),void 0!==n.msaaTexture&&n.msaaTexture.destroy(),t.delete(e)}destroySampler(e){delete this.backend.get(e).sampler}generateMipmaps(e){const t=this.backend.get(e);if(e.isCubeTexture)for(let e=0;e<6;e++)this._generateMipmaps(t.texture,t.textureDescriptorGPU,e);else{const n=e.image.depth||1;for(let e=0;e<n;e++)this._generateMipmaps(t.texture,t.textureDescriptorGPU,e)}}getColorBuffer(){this.colorBuffer&&this.colorBuffer.destroy();const e=this.backend,{width:t,height:n}=e.getDrawingBufferSize();return this.colorBuffer=e.device.createTexture({label:"colorBuffer",size:{width:t,height:n,depthOrArrayLayers:1},sampleCount:e.utils.getSampleCount(e.renderer.samples),format:e.utils.getPreferredCanvasFormat(),usage:GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.COPY_SRC}),this.colorBuffer}getDepthBuffer(e=!0,t=!1){const n=this.backend,{width:i,height:r}=n.getDrawingBufferSize(),s=this.depthTexture,o=n.get(s).texture;let a,l;if(t?(a=or,l=$i):e&&(a=sr,l=Yi),void 0!==o){if(s.image.width===i&&s.image.height===r&&s.format===a&&s.type===l)return o;this.destroyTexture(s)}return s.name="depthBuffer",s.format=a,s.type=l,s.image.width=i,s.image.height=r,this.createTexture(s,{width:i,height:r}),n.get(s).texture}updateTexture(e,t){const n=this.backend.get(e),i=e.mipmaps,{textureDescriptorGPU:r}=n;if(!e.isRenderTargetTexture&&void 0!==r){if(e.isDataTexture)if(i.length>0)for(let t=0,s=i.length;t<s;t++){const s=i[t];this._copyBufferToTexture(s,n.texture,r,0,e.flipY,0,t)}else this._copyBufferToTexture(t.image,n.texture,r,0,e.flipY);else if(e.isArrayTexture||e.isDataArrayTexture||e.isData3DTexture)for(let i=0;i<t.image.depth;i++)this._copyBufferToTexture(t.image,n.texture,r,i,e.flipY,i);else if(e.isCompressedTexture||e.isCompressedArrayTexture)this._copyCompressedBufferToTexture(e.mipmaps,n.texture,r);else if(e.isCubeTexture)this._copyCubeMapToTexture(e,n.texture,r);else if(i.length>0)for(let t=0,s=i.length;t<s;t++){const s=i[t];this._copyImageToTexture(s,n.texture,r,0,e.flipY,e.premultiplyAlpha,t)}else this._copyImageToTexture(t.image,n.texture,r,0,e.flipY,e.premultiplyAlpha);n.version=e.version}}async copyTextureToBuffer(e,t,n,i,r,s){const o=this.backend.device,a=this.backend.get(e),l=a.texture,u=a.textureDescriptorGPU.format,c=this._getBytesPerTexel(u);let d=i*c;d=256*Math.ceil(d/256);const h=o.createBuffer({size:(r-1)*d+i*c,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ}),f=o.createCommandEncoder();f.copyTextureToBuffer({texture:l,origin:{x:t,y:n,z:s}},{buffer:h,bytesPerRow:d},{width:i,height:r});const p=this._getTypedArrayType(u);o.queue.submit([f.finish()]),await h.mapAsync(GPUMapMode.READ);return new p(h.getMappedRange())}_getDefaultTextureGPU(e){let t=this.defaultTexture[e];if(void 0===t){const n=new Ys;n.minFilter=Ri,n.magFilter=Ri,this.createTexture(n,{width:1,height:1,format:e}),this.defaultTexture[e]=t=n}return this.backend.get(t).texture}_getDefaultCubeTextureGPU(e){let t=this.defaultTexture[e];if(void 0===t){const n=new vl;n.minFilter=Ri,n.magFilter=Ri,this.createTexture(n,{width:1,height:1,depth:6}),this.defaultCubeTexture[e]=t=n}return this.backend.get(t).texture}_copyCubeMapToTexture(e,t,n){const i=e.images,r=e.mipmaps;for(let s=0;s<6;s++){const o=i[s],a=!0===e.flipY?Vz[s]:s;o.isDataTexture?this._copyBufferToTexture(o.image,t,n,a,e.flipY):this._copyImageToTexture(o,t,n,a,e.flipY,e.premultiplyAlpha);for(let i=0;i<r.length;i++){const o=r[i].images[s];o.isDataTexture?this._copyBufferToTexture(o.image,t,n,a,e.flipY,0,i+1):this._copyImageToTexture(o,t,n,a,e.flipY,e.premultiplyAlpha,i+1)}}}_copyImageToTexture(e,t,n,i,r,s,o=0){const a=this.backend.device,l=o>0?e.width:n.size.width,u=o>0?e.height:n.size.height;a.queue.copyExternalImageToTexture({source:e,flipY:r},{texture:t,mipLevel:o,origin:{x:0,y:0,z:i},premultipliedAlpha:s},{width:l,height:u,depthOrArrayLayers:1})}_getPassUtils(){let e=this._passUtils;return null===e&&(this._passUtils=e=new Xz(this.backend.device)),e}_generateMipmaps(e,t,n=0){this._getPassUtils().generateMipmaps(e,t,n)}_flipY(e,t,n=0){this._getPassUtils().flipY(e,t,n)}_copyBufferToTexture(e,t,n,i,r,s=0,o=0){const a=this.backend.device,l=e.data,u=this._getBytesPerTexel(n.format),c=e.width*u;a.queue.writeTexture({texture:t,mipLevel:o,origin:{x:0,y:0,z:i}},l,{offset:e.width*e.height*u*s,bytesPerRow:c},{width:e.width,height:e.height,depthOrArrayLayers:1}),!0===r&&this._flipY(t,n,i)}_copyCompressedBufferToTexture(e,t,n){const i=this.backend.device,r=this._getBlockData(n.format),s=n.size.depthOrArrayLayers>1;for(let o=0;o<e.length;o++){const a=e[o],l=a.width,u=a.height,c=s?n.size.depthOrArrayLayers:1,d=Math.ceil(l/r.width)*r.byteLength,h=d*Math.ceil(u/r.height);for(let e=0;e<c;e++)i.queue.writeTexture({texture:t,mipLevel:o,origin:{x:0,y:0,z:e}},a.data,{offset:e*h,bytesPerRow:d,rowsPerImage:Math.ceil(u/r.height)},{width:Math.ceil(l/r.width)*r.width,height:Math.ceil(u/r.height)*r.height,depthOrArrayLayers:1})}}_getBlockData(e){return e===Fj||e===Hj?{byteLength:8,width:4,height:4}:e===Uj||e===Xj||e===Gj||e===Vj?{byteLength:16,width:4,height:4}:e===Wj||e===Qj?{byteLength:8,width:4,height:4}:e===Zj||e===Yj||e===Jj||e===Kj||e===qj||e===_j?{byteLength:16,width:4,height:4}:e===$j||e===eO||e===tO||e===nO?{byteLength:8,width:4,height:4}:e===iO||e===rO?{byteLength:16,width:4,height:4}:e===sO||e===oO?{byteLength:8,width:4,height:4}:e===aO||e===lO||e===uO||e===cO?{byteLength:16,width:4,height:4}:e===dO||e===hO?{byteLength:16,width:5,height:4}:e===fO||e===pO?{byteLength:16,width:5,height:5}:e===gO||e===mO?{byteLength:16,width:6,height:5}:e===vO||e===AO?{byteLength:16,width:6,height:6}:e===xO||e===yO?{byteLength:16,width:8,height:5}:e===bO||e===wO?{byteLength:16,width:8,height:6}:e===CO||e===MO?{byteLength:16,width:8,height:8}:e===EO||e===TO?{byteLength:16,width:10,height:5}:e===SO||e===PO?{byteLength:16,width:10,height:6}:e===NO||e===BO?{byteLength:16,width:10,height:8}:e===DO||e===IO?{byteLength:16,width:10,height:10}:e===LO||e===jO?{byteLength:16,width:12,height:10}:e===OO||e===zO?{byteLength:16,width:12,height:12}:void 0}_convertAddressMode(e){let t=RO;return e===ji?t=kO:e===zi&&(t=FO),t}_convertFilterMode(e){let t=HO;return e!==Ri&&e!==ki&&e!==Fi||(t=UO),t}_getBytesPerTexel(e){return e===_L||e===$L||e===ej||e===tj?1:e===nj||e===ij||e===rj||e===sj||e===oj||e===aj||e===lj?2:e===uj||e===cj||e===dj||e===hj||e===fj||e===pj||e===gj||e===mj||e===vj||e===Aj||e===xj||e===yj||e===bj||e===wj||e===Cj||e===Mj||e===Rj||e===Oj||e===zj||e===kj?4:e===Ej||e===Tj||e===Sj||e===Pj||e===Nj||e===Bj?8:e===Dj||e===Ij||e===Lj?16:void 0}_getTypedArrayType(e){return e===ej?Uint8Array:e===tj?Int8Array:e===_L?Uint8Array:e===$L?Int8Array:e===aj?Uint8Array:e===lj?Int8Array:e===sj?Uint8Array:e===oj?Int8Array:e===Aj?Uint8Array:e===xj?Int8Array:e===gj||e===mj?Uint8Array:e===vj?Int8Array:e===nj?Uint16Array:e===ij?Int16Array:e===hj?Uint16Array:e===fj?Int16Array:e===Pj?Uint16Array:e===Nj?Int16Array:e===rj||e===pj||e===Bj?Uint16Array:e===uj?Uint32Array:e===cj?Int32Array:e===dj?Float32Array:e===Ej?Uint32Array:e===Tj?Int32Array:e===Sj?Float32Array:e===Dj?Uint32Array:e===Ij?Int32Array:e===Lj?Float32Array:e===yj||e===bj?Uint8Array:e===Cj||e===wj||e===Mj?Uint32Array:e===Rj?Float32Array:e===Oj||e===zj?Uint32Array:e===kj?Float32Array:void 0}_getDimension(e){let t;return t=e.is3DTexture||e.isData3DTexture?Nz:Pz,t}}function Qz(e,t=null){const n=e.format,i=e.type,r=e.colorSpace,s=ks.getTransfer(r);let o;if(!0===e.isCompressedTexture||!0===e.isCompressedArrayTexture)switch(n){case hr:case fr:o=s===es?Hj:Fj;break;case pr:o=s===es?Xj:Uj;break;case gr:o=s===es?Vj:Gj;break;case Hr:o=Wj;break;case Ur:o=Qj;break;case Xr:o=Zj;break;case Gr:o=Yj;break;case Rr:o=s===es?_j:qj;break;case br:case yr:o=s===es?eO:$j;break;case wr:o=s===es?rO:iO;break;case Cr:o=s===es?cO:uO;break;case Mr:o=s===es?hO:dO;break;case Er:o=s===es?pO:fO;break;case Tr:o=s===es?mO:gO;break;case Sr:o=s===es?AO:vO;break;case Pr:o=s===es?yO:xO;break;case Nr:o=s===es?wO:bO;break;case Br:o=s===es?MO:CO;break;case Dr:o=s===es?TO:EO;break;case Ir:o=s===es?PO:SO;break;case Lr:o=s===es?BO:NO;break;case jr:o=s===es?IO:DO;break;case Or:o=s===es?jO:LO;break;case zr:o=s===es?zO:OO;break;case rr:o=s===es?mj:gj;break;default:console.error("WebGPURenderer: Unsupported texture format.",n)}else switch(n){case rr:switch(i){case Vi:o=vj;break;case Wi:o=Nj;break;case Qi:o=Pj;break;case Yi:o=Dj;break;case Zi:o=Ij;break;case Gi:o=s===es?mj:gj;break;case Ki:o=Bj;break;case Ji:o=Lj;break;default:console.error("WebGPURenderer: Unsupported texture type with RGBAFormat.",i)}break;case ir:switch(i){case er:o=wj;break;case tr:o=Mj;break;default:console.error("WebGPURenderer: Unsupported texture type with RGBFormat.",i)}break;case ar:switch(i){case Vi:o=$L;break;case Wi:o=ij;break;case Qi:o=nj;break;case Yi:o=uj;break;case Zi:o=cj;break;case Gi:o=_L;break;case Ki:o=rj;break;case Ji:o=dj;break;default:console.error("WebGPURenderer: Unsupported texture type with RedFormat.",i)}break;case ur:switch(i){case Vi:o=oj;break;case Wi:o=fj;break;case Qi:o=hj;break;case Yi:o=Ej;break;case Zi:o=Tj;break;case Gi:o=sj;break;case Ki:o=pj;break;case Ji:o=Sj;break;default:console.error("WebGPURenderer: Unsupported texture type with RGFormat.",i)}break;case sr:switch(i){case Qi:o=jj;break;case Yi:o=Oj;break;case Ji:o=Rj;break;default:console.error("WebGPURenderer: Unsupported texture type with DepthFormat.",i)}break;case or:switch(i){case $i:o=zj;break;case Ji:t&&!1===t.features.has(Rz.Depth32FloatStencil8)&&console.error('WebGPURenderer: Depth textures with DepthStencilFormat + FloatType can only be used with the "depth32float-stencil8" GPU feature.'),o=kj;break;default:console.error("WebGPURenderer: Unsupported texture type with DepthStencilFormat.",i)}break;case lr:switch(i){case Zi:o=cj;break;case Yi:o=uj;break;default:console.error("WebGPURenderer: Unsupported texture type with RedIntegerFormat.",i)}break;case cr:switch(i){case Zi:o=Tj;break;case Yi:o=Ej;break;default:console.error("WebGPURenderer: Unsupported texture type with RGIntegerFormat.",i)}break;case dr:switch(i){case Zi:o=Ij;break;case Yi:o=Dj;break;default:console.error("WebGPURenderer: Unsupported texture type with RGBAIntegerFormat.",i)}break;default:console.error("WebGPURenderer: Unsupported texture format.",n)}return o}const Zz=/^[fn]*\s*([a-z_0-9]+)?\s*\(([\s\S]*?)\)\s*[\-\>]*\s*([a-z_0-9]+(?:<[\s\S]+?>)?)/i,Yz=/([a-z_0-9]+)\s*:\s*([a-z_0-9]+(?:<[\s\S]+?>)?)/gi,Jz={f32:"float",i32:"int",u32:"uint",bool:"bool","vec2<f32>":"vec2","vec2<i32>":"ivec2","vec2<u32>":"uvec2","vec2<bool>":"bvec2",vec2f:"vec2",vec2i:"ivec2",vec2u:"uvec2",vec2b:"bvec2","vec3<f32>":"vec3","vec3<i32>":"ivec3","vec3<u32>":"uvec3","vec3<bool>":"bvec3",vec3f:"vec3",vec3i:"ivec3",vec3u:"uvec3",vec3b:"bvec3","vec4<f32>":"vec4","vec4<i32>":"ivec4","vec4<u32>":"uvec4","vec4<bool>":"bvec4",vec4f:"vec4",vec4i:"ivec4",vec4u:"uvec4",vec4b:"bvec4","mat2x2<f32>":"mat2",mat2x2f:"mat2","mat3x3<f32>":"mat3",mat3x3f:"mat3","mat4x4<f32>":"mat4",mat4x4f:"mat4",sampler:"sampler",texture_1d:"texture",texture_2d:"texture",texture_2d_array:"texture",texture_multisampled_2d:"cubeTexture",texture_depth_2d:"depthTexture",texture_depth_2d_array:"depthTexture",texture_depth_multisampled_2d:"depthTexture",texture_depth_cube:"depthTexture",texture_depth_cube_array:"depthTexture",texture_3d:"texture3D",texture_cube:"cubeTexture",texture_cube_array:"cubeTexture",texture_storage_1d:"storageTexture",texture_storage_2d:"storageTexture",texture_storage_2d_array:"storageTexture",texture_storage_3d:"storageTexture"};class Kz extends iI{constructor(e){const{type:t,inputs:n,name:i,inputsCode:r,blockCode:s,outputType:o}=(e=>{const t=(e=e.trim()).match(Zz);if(null!==t&&4===t.length){const n=t[2],i=[];let r=null;for(;null!==(r=Yz.exec(n));)i.push({name:r[1],type:r[2]});const s=[];for(let e=0;e<i.length;e++){const{name:t,type:n}=i[e];let r=n;r.startsWith("ptr")?r="pointer":(r.startsWith("texture")&&(r=n.split("<")[0]),r=Jz[r]),s.push(new GD(r,t))}const o=e.substring(t[0].length),a=t[3]||"void",l=void 0!==t[1]?t[1]:"";return{type:Jz[a]||a,inputs:s,name:l,inputsCode:n,blockCode:o,outputType:a}}throw new Error("FunctionNode: Function is not a WGSL code.")})(e);super(t,n,i),this.inputsCode=r,this.blockCode=s,this.outputType=o}getCode(e=this.name){const t="void"!==this.outputType?"-> "+this.outputType:"";return`fn ${e} ( ${this.inputsCode.trim()} ) ${t}`+this.blockCode}}class qz extends nI{parseFunction(e){return new Kz(e)}}const _z="undefined"!=typeof self?self.GPUShaderStage:{VERTEX:1,FRAGMENT:2,COMPUTE:4},$z={[fv.READ_ONLY]:"read",[fv.WRITE_ONLY]:"write",[fv.READ_WRITE]:"read_write"},eR={[ji]:"repeat",[Oi]:"clamp",[zi]:"mirror"},tR={vertex:_z?_z.VERTEX:1,fragment:_z?_z.FRAGMENT:2,compute:_z?_z.COMPUTE:4},nR={instance:!0,swizzleAssign:!1,storageBuffer:!0},iR={"^^":"tsl_xor"},rR={float:"f32",int:"i32",uint:"u32",bool:"bool",color:"vec3<f32>",vec2:"vec2<f32>",ivec2:"vec2<i32>",uvec2:"vec2<u32>",bvec2:"vec2<bool>",vec3:"vec3<f32>",ivec3:"vec3<i32>",uvec3:"vec3<u32>",bvec3:"vec3<bool>",vec4:"vec4<f32>",ivec4:"vec4<i32>",uvec4:"vec4<u32>",bvec4:"vec4<bool>",mat2:"mat2x2<f32>",mat3:"mat3x3<f32>",mat4:"mat4x4<f32>"},sR={},oR={tsl_xor:new $N("fn tsl_xor( a : bool, b : bool ) -> bool { return ( a || b ) && !( a && b ); }"),mod_float:new $N("fn tsl_mod_float( x : f32, y : f32 ) -> f32 { return x - y * floor( x / y ); }"),mod_vec2:new $N("fn tsl_mod_vec2( x : vec2f, y : vec2f ) -> vec2f { return x - y * floor( x / y ); }"),mod_vec3:new $N("fn tsl_mod_vec3( x : vec3f, y : vec3f ) -> vec3f { return x - y * floor( x / y ); }"),mod_vec4:new $N("fn tsl_mod_vec4( x : vec4f, y : vec4f ) -> vec4f { return x - y * floor( x / y ); }"),equals_bool:new $N("fn tsl_equals_bool( a : bool, b : bool ) -> bool { return a == b; }"),equals_bvec2:new $N("fn tsl_equals_bvec2( a : vec2f, b : vec2f ) -> vec2<bool> { return vec2<bool>( a.x == b.x, a.y == b.y ); }"),equals_bvec3:new $N("fn tsl_equals_bvec3( a : vec3f, b : vec3f ) -> vec3<bool> { return vec3<bool>( a.x == b.x, a.y == b.y, a.z == b.z ); }"),equals_bvec4:new $N("fn tsl_equals_bvec4( a : vec4f, b : vec4f ) -> vec4<bool> { return vec4<bool>( a.x == b.x, a.y == b.y, a.z == b.z, a.w == b.w ); }"),repeatWrapping_float:new $N("fn tsl_repeatWrapping_float( coord: f32 ) -> f32 { return fract( coord ); }"),mirrorWrapping_float:new $N("fn tsl_mirrorWrapping_float( coord: f32 ) -> f32 { let mirrored = fract( coord * 0.5 ) * 2.0; return 1.0 - abs( 1.0 - mirrored ); }"),clampWrapping_float:new $N("fn tsl_clampWrapping_float( coord: f32 ) -> f32 { return clamp( coord, 0.0, 1.0 ); }"),biquadraticTexture:new $N("\nfn tsl_biquadraticTexture( map : texture_2d<f32>, coord : vec2f, iRes : vec2u, level : u32 ) -> vec4f {\n\n\tlet res = vec2f( iRes );\n\n\tlet uvScaled = coord * res;\n\tlet uvWrapping = ( ( uvScaled % res ) + res ) % res;\n\n\t// https://www.shadertoy.com/view/WtyXRy\n\n\tlet uv = uvWrapping - 0.5;\n\tlet iuv = floor( uv );\n\tlet f = fract( uv );\n\n\tlet rg1 = textureLoad( map, vec2u( iuv + vec2( 0.5, 0.5 ) ) % iRes, level );\n\tlet rg2 = textureLoad( map, vec2u( iuv + vec2( 1.5, 0.5 ) ) % iRes, level );\n\tlet rg3 = textureLoad( map, vec2u( iuv + vec2( 0.5, 1.5 ) ) % iRes, level );\n\tlet rg4 = textureLoad( map, vec2u( iuv + vec2( 1.5, 1.5 ) ) % iRes, level );\n\n\treturn mix( mix( rg1, rg2, f.x ), mix( rg3, rg4, f.x ), f.y );\n\n}\n")},aR={dFdx:"dpdx",dFdy:"- dpdy",mod_float:"tsl_mod_float",mod_vec2:"tsl_mod_vec2",mod_vec3:"tsl_mod_vec3",mod_vec4:"tsl_mod_vec4",equals_bool:"tsl_equals_bool",equals_bvec2:"tsl_equals_bvec2",equals_bvec3:"tsl_equals_bvec3",equals_bvec4:"tsl_equals_bvec4",inversesqrt:"inverseSqrt",bitcast:"bitcast<f32>"};let lR="";!0!==("undefined"!=typeof navigator&&/Firefox|Deno/g.test(navigator.userAgent))&&(lR+="diagnostic( off, derivative_uniformity );\n");class uR extends UD{constructor(e,t){super(e,t,new qz),this.uniformGroups={},this.builtins={},this.directives={},this.scopedArrays=new Map}_generateTextureSample(e,t,n,i,r,s=this.shaderStage){return"fragment"===s?i?r?`textureSample( ${t}, ${t}_sampler, ${n}, ${i}, ${r} )`:`textureSample( ${t}, ${t}_sampler, ${n}, ${i} )`:r?`textureSample( ${t}, ${t}_sampler, ${n}, ${r} )`:`textureSample( ${t}, ${t}_sampler, ${n} )`:this.generateTextureSampleLevel(e,t,n,"0",i)}generateTextureSampleLevel(e,t,n,i,r,s){return!1===this.isUnfilterable(e)?s?`textureSampleLevel( ${t}, ${t}_sampler, ${n}, ${i}, ${s} )`:`textureSampleLevel( ${t}, ${t}_sampler, ${n}, ${i} )`:this.isFilteredTexture(e)?this.generateFilteredTexture(e,t,n,s,i):this.generateTextureLod(e,t,n,r,s,i)}generateWrapFunction(e){const t=`tsl_coord_${eR[e.wrapS]}S_${eR[e.wrapT]}_${e.isData3DTexture?"3d":"2d"}T`;let n=sR[t];if(void 0===n){const i=[],r=e.isData3DTexture?"vec3f":"vec2f";let s=`fn ${t}( coord : ${r} ) -> ${r} {\n\n\treturn ${r}(\n`;const o=(e,t)=>{e===ji?(i.push(oR.repeatWrapping_float),s+=`\t\ttsl_repeatWrapping_float( coord.${t} )`):e===Oi?(i.push(oR.clampWrapping_float),s+=`\t\ttsl_clampWrapping_float( coord.${t} )`):e===zi?(i.push(oR.mirrorWrapping_float),s+=`\t\ttsl_mirrorWrapping_float( coord.${t} )`):(s+=`\t\tcoord.${t}`,console.warn(`WebGPURenderer: Unsupported texture wrap type "${e}" for vertex shader.`))};o(e.wrapS,"x"),s+=",\n",o(e.wrapT,"y"),e.isData3DTexture&&(s+=",\n",o(e.wrapR,"z")),s+="\n\t);\n\n}\n",sR[t]=n=new $N(s,i)}return n.build(this),t}generateArrayDeclaration(e,t){return`array< ${this.getType(e)}, ${t} >`}generateTextureDimension(e,t,n){const i=this.getDataFromNode(e,this.shaderStage,this.globalCache);void 0===i.dimensionsSnippet&&(i.dimensionsSnippet={});let r=i.dimensionsSnippet[n];if(void 0===i.dimensionsSnippet[n]){let s,o;const{primarySamples:a}=this.renderer.backend.utils.getTextureSampleData(e),l=a>1;o=e.isData3DTexture?"vec3<u32>":"vec2<u32>",s=l||e.isStorageTexture?t:`${t}${n?`, u32( ${n} )`:""}`,r=new Sb(new dw(`textureDimensions( ${s} )`,o)),i.dimensionsSnippet[n]=r,(e.isArrayTexture||e.isDataArrayTexture||e.isData3DTexture)&&(i.arrayLayerCount=new Sb(new dw(`textureNumLayers(${t})`,"u32"))),e.isTextureCube&&(i.cubeFaceCount=new Sb(new dw("6u","u32")))}return r.build(this)}generateFilteredTexture(e,t,n,i,r="0u"){this._include("biquadraticTexture");const s=this.generateWrapFunction(e),o=this.generateTextureDimension(e,t,r);return i&&(n=`${n} + vec2<f32>(${i}) / ${o}`),`tsl_biquadraticTexture( ${t}, ${s}( ${n} ), ${o}, u32( ${r} ) )`}generateTextureLod(e,t,n,i,r,s="0u"){const o=this.generateWrapFunction(e),a=this.generateTextureDimension(e,t,s),l=e.isData3DTexture?"vec3":"vec2";r&&(n=`${n} + ${l}<f32>(${r}) / ${l}<f32>( ${a} )`);const u=`${l}<u32>( ${o}( ${n} ) * ${l}<f32>( ${a} ) )`;return this.generateTextureLoad(e,t,u,i,null,s)}generateTextureLoad(e,t,n,i,r,s="0u"){let o;return r&&(n=`${n} + ${r}`),i?o=`textureLoad( ${t}, ${n}, ${i}, u32( ${s} ) )`:(o=`textureLoad( ${t}, ${n}, u32( ${s} ) )`,this.renderer.backend.compatibilityMode&&e.isDepthTexture&&(o+=".x")),o}generateTextureStore(e,t,n,i,r){let s;return s=i?`textureStore( ${t}, ${n}, ${i}, ${r} )`:`textureStore( ${t}, ${n}, ${r} )`,s}isSampleCompare(e){return!0===e.isDepthTexture&&null!==e.compareFunction}isUnfilterable(e){return"float"!==this.getComponentTypeFromTexture(e)||!this.isAvailable("float32Filterable")&&!0===e.isDataTexture&&e.type===Ji||!1===this.isSampleCompare(e)&&e.minFilter===Ri&&e.magFilter===Ri||this.renderer.backend.utils.getTextureSampleData(e).primarySamples>1}generateTexture(e,t,n,i,r,s=this.shaderStage){let o=null;return o=this.isUnfilterable(e)?this.generateTextureLod(e,t,n,i,r,"0",s):this._generateTextureSample(e,t,n,i,r,s),o}generateTextureGrad(e,t,n,i,r,s,o=this.shaderStage){if("fragment"===o)return s?`textureSampleGrad( ${t}, ${t}_sampler, ${n},  ${i[0]}, ${i[1]}, ${s} )`:`textureSampleGrad( ${t}, ${t}_sampler, ${n},  ${i[0]}, ${i[1]} )`;console.error(`WebGPURenderer: THREE.TextureNode.gradient() does not support ${o} shader.`)}generateTextureCompare(e,t,n,i,r,s,o=this.shaderStage){if("fragment"===o)return!0===e.isDepthTexture&&!0===e.isArrayTexture?s?`textureSampleCompare( ${t}, ${t}_sampler, ${n}, ${r}, ${i}, ${s} )`:`textureSampleCompare( ${t}, ${t}_sampler, ${n}, ${r}, ${i} )`:s?`textureSampleCompare( ${t}, ${t}_sampler, ${n}, ${i}, ${s} )`:`textureSampleCompare( ${t}, ${t}_sampler, ${n}, ${i} )`;console.error(`WebGPURenderer: THREE.DepthTexture.compareFunction() does not support ${o} shader.`)}generateTextureLevel(e,t,n,i,r,s){return!1===this.isUnfilterable(e)?s?`textureSampleLevel( ${t}, ${t}_sampler, ${n}, ${i}, ${s} )`:`textureSampleLevel( ${t}, ${t}_sampler, ${n}, ${i} )`:this.isFilteredTexture(e)?this.generateFilteredTexture(e,t,n,s,i):this.generateTextureLod(e,t,n,r,s,i)}generateTextureBias(e,t,n,i,r,s,o=this.shaderStage){if("fragment"===o)return s?`textureSampleBias( ${t}, ${t}_sampler, ${n}, ${i}, ${s} )`:`textureSampleBias( ${t}, ${t}_sampler, ${n}, ${i} )`;console.error(`WebGPURenderer: THREE.TextureNode.biasNode does not support ${o} shader.`)}getPropertyName(e,t=this.shaderStage){if(!0===e.isNodeVarying&&!0===e.needsInterpolation){if("vertex"===t)return`varyings.${e.name}`}else if(!0===e.isNodeUniform){const t=e.name,n=e.type;return"texture"===n||"cubeTexture"===n||"storageTexture"===n||"texture3D"===n?t:"buffer"===n||"storageBuffer"===n||"indirectStorageBuffer"===n?this.isCustomStruct(e)?t:t+".value":e.groupNode.name+"."+t}return super.getPropertyName(e)}getOutputStructName(){return"output"}getFunctionOperator(e){const t=iR[e];return void 0!==t?(this._include(t),t):null}getNodeAccess(e,t){return"compute"!==t?!0===e.isAtomic?(console.warn("WebGPURenderer: Atomic operations are only supported in compute shaders."),fv.READ_WRITE):fv.READ_ONLY:e.access}getStorageAccess(e,t){return $z[this.getNodeAccess(e,t)]}getUniformFromNode(e,t,n,i=null){const r=super.getUniformFromNode(e,t,n,i),s=this.getDataFromNode(e,n,this.globalCache);if(void 0===s.uniformGPU){let o;const a=e.groupNode,l=a.name,u=this.getBindGroupArray(l,n);if("texture"===t||"cubeTexture"===t||"storageTexture"===t||"texture3D"===t){let i=null;const s=this.getNodeAccess(e,n);if("texture"===t||"storageTexture"===t?i=!0===e.value.is3DTexture?new $I(r.name,r.node,a,s):new qI(r.name,r.node,a,s):"cubeTexture"===t?i=new _I(r.name,r.node,a,s):"texture3D"===t&&(i=new $I(r.name,r.node,a,s)),i.store=!0===e.isStorageTextureNode,i.setVisibility(tR[n]),!1===this.isUnfilterable(e.value)&&!1===i.store){const e=new kz(`${r.name}_sampler`,r.node,a);e.setVisibility(tR[n]),u.push(e,i),o=[e,i]}else u.push(i),o=[i]}else if("buffer"===t||"storageBuffer"===t||"indirectStorageBuffer"===t){const s=new("buffer"===t?VI:Uz)(e,a);s.setVisibility(tR[n]),u.push(s),o=s,r.name=i||"NodeBuffer_"+r.id}else{const e=this.uniformGroups[n]||(this.uniformGroups[n]={});let i=e[l];void 0===i&&(i=new ZI(l,a),i.setVisibility(tR[n]),e[l]=i,u.push(i)),o=this.getNodeUniform(r,t),i.addUniform(o)}s.uniformGPU=o}return r}getBuiltin(e,t,n,i=this.shaderStage){const r=this.builtins[i]||(this.builtins[i]=new Map);return!1===r.has(e)&&r.set(e,{name:e,property:t,type:n}),t}hasBuiltin(e,t=this.shaderStage){return void 0!==this.builtins[t]&&this.builtins[t].has(e)}getVertexIndex(){return"vertex"===this.shaderStage?this.getBuiltin("vertex_index","vertexIndex","u32","attribute"):"vertexIndex"}buildFunctionCode(e){const t=e.layout,n=this.flowShaderNode(e),i=[];for(const e of t.inputs)i.push(e.name+" : "+this.getType(e.type));let r=`fn ${t.name}( ${i.join(", ")} ) -> ${this.getType(t.type)} {\n${n.vars}\n${n.code}\n`;return n.result&&(r+=`\treturn ${n.result};\n`),r+="\n}\n",r}getInstanceIndex(){return"vertex"===this.shaderStage?this.getBuiltin("instance_index","instanceIndex","u32","attribute"):"instanceIndex"}getInvocationLocalIndex(){return this.getBuiltin("local_invocation_index","invocationLocalIndex","u32","attribute")}getSubgroupSize(){return this.enableSubGroups(),this.getBuiltin("subgroup_size","subgroupSize","u32","attribute")}getInvocationSubgroupIndex(){return this.enableSubGroups(),this.getBuiltin("subgroup_invocation_id","invocationSubgroupIndex","u32","attribute")}getSubgroupIndex(){return this.enableSubGroups(),this.getBuiltin("subgroup_id","subgroupIndex","u32","attribute")}getDrawIndex(){return null}getFrontFacing(){return this.getBuiltin("front_facing","isFront","bool")}getFragCoord(){return this.getBuiltin("position","fragCoord","vec4<f32>")+".xy"}getFragDepth(){return"output."+this.getBuiltin("frag_depth","depth","f32","output")}getClipDistance(){return"varyings.hw_clip_distances"}isFlipY(){return!1}enableDirective(e,t=this.shaderStage){(this.directives[t]||(this.directives[t]=new Set)).add(e)}getDirectives(e){const t=[],n=this.directives[e];if(void 0!==n)for(const e of n)t.push(`enable ${e};`);return t.join("\n")}enableSubGroups(){this.enableDirective("subgroups")}enableSubgroupsF16(){this.enableDirective("subgroups-f16")}enableClipDistances(){this.enableDirective("clip_distances")}enableShaderF16(){this.enableDirective("f16")}enableDualSourceBlending(){this.enableDirective("dual_source_blending")}enableHardwareClipping(e){this.enableClipDistances(),this.getBuiltin("clip_distances","hw_clip_distances",`array<f32, ${e} >`,"vertex")}getBuiltins(e){const t=[],n=this.builtins[e];if(void 0!==n)for(const{name:e,property:i,type:r}of n.values())t.push(`@builtin( ${e} ) ${i} : ${r}`);return t.join(",\n\t")}getScopedArray(e,t,n,i){return!1===this.scopedArrays.has(e)&&this.scopedArrays.set(e,{name:e,scope:t,bufferType:n,bufferCount:i}),e}getScopedArrays(e){if("compute"!==e)return;const t=[];for(const{name:e,scope:n,bufferType:i,bufferCount:r}of this.scopedArrays.values()){const s=this.getType(i);t.push(`var<${n}> ${e}: array< ${s}, ${r} >;`)}return t.join("\n")}getAttributes(e){const t=[];if("compute"===e&&(this.getBuiltin("global_invocation_id","globalId","vec3<u32>","attribute"),this.getBuiltin("workgroup_id","workgroupId","vec3<u32>","attribute"),this.getBuiltin("local_invocation_id","localId","vec3<u32>","attribute"),this.getBuiltin("num_workgroups","numWorkgroups","vec3<u32>","attribute"),this.renderer.hasFeature("subgroups")&&(this.enableDirective("subgroups",e),this.getBuiltin("subgroup_size","subgroupSize","u32","attribute"))),"vertex"===e||"compute"===e){const e=this.getBuiltins("attribute");e&&t.push(e);const n=this.getAttributesArray();for(let e=0,i=n.length;e<i;e++){const i=n[e],r=i.name,s=this.getType(i.type);t.push(`@location( ${e} ) ${r} : ${s}`)}}return t.join(",\n\t")}getStructMembers(e){const t=[];for(const n of e.members){const i=e.output?"@location( "+n.index+" ) ":"";let r=this.getType(n.type);n.atomic&&(r="atomic< "+r+" >"),t.push(`\t${i+n.name} : ${r}`)}return e.output&&t.push(`\t${this.getBuiltins("output")}`),t.join(",\n")}getStructs(e){let t="";const n=this.structs[e];if(n.length>0){const e=[];for(const t of n){let n=`struct ${t.name} {\n`;n+=this.getStructMembers(t),n+="\n};",e.push(n)}t="\n"+e.join("\n\n")+"\n"}return t}getVar(e,t,n=null){let i=`var ${t} : `;return i+=null!==n?this.generateArrayDeclaration(e,n):this.getType(e),i}getVars(e){const t=[],n=this.vars[e];if(void 0!==n)for(const e of n)t.push(`\t${this.getVar(e.type,e.name,e.count)};`);return`\n${t.join("\n")}\n`}getVaryings(e){const t=[];if("vertex"===e&&this.getBuiltin("position","Vertex","vec4<f32>","vertex"),"vertex"===e||"fragment"===e){const n=this.varyings,i=this.vars[e];for(let r=0;r<n.length;r++){const s=n[r];if(s.needsInterpolation){let e=`@location( ${r} )`;if(s.interpolationType){const t=null!==s.interpolationSampling?`, ${s.interpolationSampling} )`:" )";e+=` @interpolate( ${s.interpolationType}${t}`}else/^(int|uint|ivec|uvec)/.test(s.type)&&(e+=` @interpolate( ${this.renderer.backend.compatibilityMode?"flat, either":"flat"} )`);t.push(`${e} ${s.name} : ${this.getType(s.type)}`)}else"vertex"===e&&!1===i.includes(s)&&i.push(s)}}const n=this.getBuiltins(e);n&&t.push(n);const i=t.join(",\n\t");return"vertex"===e?this._getWGSLStruct("VaryingsStruct","\t"+i):i}isCustomStruct(e){const t=e.value,n=e.node,i=(t.isBufferAttribute||t.isInstancedBufferAttribute)&&null!==n.structTypeNode,r=n.value&&n.value.array&&"number"==typeof n.value.itemSize&&n.value.array.length>n.value.itemSize;return i&&!r}getUniforms(e){const t=this.uniforms[e],n=[],i=[],r=[],s={};for(const r of t){const t=r.groupNode.name,o=this.bindingsIndexes[t];if("texture"===r.type||"cubeTexture"===r.type||"storageTexture"===r.type||"texture3D"===r.type){const t=r.node.value;let i;!1===this.isUnfilterable(t)&&!0!==r.node.isStorageTextureNode&&(this.isSampleCompare(t)?n.push(`@binding( ${o.binding++} ) @group( ${o.group} ) var ${r.name}_sampler : sampler_comparison;`):n.push(`@binding( ${o.binding++} ) @group( ${o.group} ) var ${r.name}_sampler : sampler;`));let s="";const{primarySamples:a}=this.renderer.backend.utils.getTextureSampleData(t);if(a>1&&(s="_multisampled"),!0===t.isCubeTexture)i="texture_cube<f32>";else if(!0===t.isDepthTexture)i=this.renderer.backend.compatibilityMode&&null===t.compareFunction?`texture${s}_2d<f32>`:`texture_depth${s}_2d${!0===t.isArrayTexture?"_array":""}`;else if(!0===r.node.isStorageTextureNode){const n=Qz(t),s=this.getStorageAccess(r.node,e),o=r.node.value.is3DTexture,a=r.node.value.isArrayTexture;i=`texture_storage_${o?"3d":"2d"+(a?"_array":"")}<${n}, ${s}>`}else if(!0===t.isArrayTexture||!0===t.isDataArrayTexture||!0===t.isCompressedArrayTexture)i="texture_2d_array<f32>";else if(!0===t.is3DTexture||!0===t.isData3DTexture)i="texture_3d<f32>";else{i=`texture${s}_2d<${this.getComponentTypeFromTexture(t).charAt(0)}32>`}n.push(`@binding( ${o.binding++} ) @group( ${o.group} ) var ${r.name} : ${i};`)}else if("buffer"===r.type||"storageBuffer"===r.type||"indirectStorageBuffer"===r.type){const t=r.node,n=this.getType(t.getNodeType(this)),s=t.bufferCount,a=s>0&&"buffer"===r.type?", "+s:"",l=t.isStorageBufferNode?`storage, ${this.getStorageAccess(t,e)}`:"uniform";if(this.isCustomStruct(r))i.push(`@binding( ${o.binding++} ) @group( ${o.group} ) var<${l}> ${r.name} : ${n};`);else{const e=`\tvalue : array< ${t.isAtomic?`atomic<${n}>`:`${n}`}${a} >`;i.push(this._getWGSLStructBinding(r.name,e,l,o.binding++,o.group))}}else{const e=this.getType(this.getVectorType(r.type)),t=r.groupNode.name;(s[t]||(s[t]={index:o.binding++,id:o.group,snippets:[]})).snippets.push(`\t${r.name} : ${e}`)}}for(const e in s){const t=s[e];r.push(this._getWGSLStructBinding(e,t.snippets.join(",\n"),"uniform",t.index,t.id))}let o=n.join("\n");return o+=i.join("\n"),o+=r.join("\n"),o}buildCode(){const e=null!==this.material?{fragment:{},vertex:{}}:{compute:{}};this.sortBindingGroups();for(const t in e){this.shaderStage=t;const n=e[t];n.uniforms=this.getUniforms(t),n.attributes=this.getAttributes(t),n.varyings=this.getVaryings(t),n.structs=this.getStructs(t),n.vars=this.getVars(t),n.codes=this.getCodes(t),n.directives=this.getDirectives(t),n.scopedArrays=this.getScopedArrays(t);let i="// code\n\n";i+=this.flowCode[t];const r=this.flowNodes[t],s=r[r.length-1],o=s.outputNode,a=void 0!==o&&!0===o.isOutputStructNode;for(const e of r){const r=this.getFlowData(e),l=e.name;if(l&&(i.length>0&&(i+="\n"),i+=`\t// flow -> ${l}\n`),i+=`${r.code}\n\t`,e===s&&"compute"!==t)if(i+="// result\n\n\t","vertex"===t)i+=`varyings.Vertex = ${r.result};`;else if("fragment"===t)if(a)n.returnType=o.getNodeType(this),n.structs+="var<private> output : "+n.returnType+";",i+=`return ${r.result};`;else{let e="\t@location(0) color: vec4<f32>";const t=this.getBuiltins("output");t&&(e+=",\n\t"+t),n.returnType="OutputStruct",n.structs+=this._getWGSLStruct("OutputStruct",e),n.structs+="\nvar<private> output : OutputStruct;",i+=`output.color = ${r.result};\n\n\treturn output;`}}n.flow=i}if(this.shaderStage=null,null!==this.material)this.vertexShader=this._getWGSLVertexCode(e.vertex),this.fragmentShader=this._getWGSLFragmentCode(e.fragment);else{const t=this.object.workgroupSize;this.computeShader=this._getWGSLComputeCode(e.compute,t)}}getMethod(e,t=null){let n;return null!==t&&(n=this._getWGSLMethod(e+"_"+t)),void 0===n&&(n=this._getWGSLMethod(e)),n||e}getBitcastMethod(e){return`bitcast<${this.getType(e)}>`}getTernary(e,t,n){return`select( ${n}, ${t}, ${e} )`}getType(e){return rR[e]||e}isAvailable(e){let t=nR[e];return void 0===t&&("float32Filterable"===e?t=this.renderer.hasFeature("float32-filterable"):"clipDistance"===e&&(t=this.renderer.hasFeature("clip-distances")),nR[e]=t),t}_getWGSLMethod(e){return void 0!==oR[e]&&this._include(e),aR[e]}_include(e){const t=oR[e];return t.build(this),null!==this.currentFunctionNode&&this.currentFunctionNode.includes.push(t),t}_getWGSLVertexCode(e){return`${this.getSignature()}\n// directives\n${e.directives}\n\n// structs\n${e.structs}\n\n// uniforms\n${e.uniforms}\n\n// varyings\n${e.varyings}\nvar<private> varyings : VaryingsStruct;\n\n// codes\n${e.codes}\n\n@vertex\nfn main( ${e.attributes} ) -> VaryingsStruct {\n\n\t// vars\n\t${e.vars}\n\n\t// flow\n\t${e.flow}\n\n\treturn varyings;\n\n}\n`}_getWGSLFragmentCode(e){return`${this.getSignature()}\n// global\n${lR}\n\n// structs\n${e.structs}\n\n// uniforms\n${e.uniforms}\n\n// codes\n${e.codes}\n\n@fragment\nfn main( ${e.varyings} ) -> ${e.returnType} {\n\n\t// vars\n\t${e.vars}\n\n\t// flow\n\t${e.flow}\n\n}\n`}_getWGSLComputeCode(e,t){const[n,i,r]=t;return`${this.getSignature()}\n// directives\n${e.directives}\n\n// system\nvar<private> instanceIndex : u32;\n\n// locals\n${e.scopedArrays}\n\n// structs\n${e.structs}\n\n// uniforms\n${e.uniforms}\n\n// codes\n${e.codes}\n\n@compute @workgroup_size( ${n}, ${i}, ${r} )\nfn main( ${e.attributes} ) {\n\n\t// system\n\tinstanceIndex = globalId.x\n\t\t+ globalId.y * ( ${n} * numWorkgroups.x )\n\t\t+ globalId.z * ( ${n} * numWorkgroups.x ) * ( ${i} * numWorkgroups.y );\n\n\t// vars\n\t${e.vars}\n\n\t// flow\n\t${e.flow}\n\n}\n`}_getWGSLStruct(e,t){return`\nstruct ${e} {\n${t}\n};`}_getWGSLStructBinding(e,t,n,i=0,r=0){const s=e+"Struct";return`${this._getWGSLStruct(s,t)}\n@binding( ${i} ) @group( ${r} )\nvar<${n}> ${e} : ${s};`}}class cR{constructor(e){this.backend=e}getCurrentDepthStencilFormat(e){let t;return null!==e.depthTexture?t=this.getTextureFormatGPU(e.depthTexture):e.depth&&e.stencil?t=zj:e.depth&&(t=Oj),t}getTextureFormatGPU(e){return this.backend.get(e).format}getTextureSampleData(e){let t;if(e.isFramebufferTexture)t=1;else if(e.isDepthTexture&&!e.renderTarget){const e=this.backend.renderer,n=e.getRenderTarget();t=n?n.samples:e.samples}else e.renderTarget&&(t=e.renderTarget.samples);t=t||1;const n=t>1&&null!==e.renderTarget&&!0!==e.isDepthTexture&&!0!==e.isFramebufferTexture;return{samples:t,primarySamples:n?1:t,isMSAA:n}}getCurrentColorFormat(e){let t;return t=null!==e.textures?this.getTextureFormatGPU(e.textures[0]):this.getPreferredCanvasFormat(),t}getCurrentColorSpace(e){return null!==e.textures?e.textures[0].colorSpace:this.backend.renderer.outputColorSpace}getPrimitiveTopology(e,t){return e.isPoints?BL:e.isLineSegments||e.isMesh&&!0===t.wireframe?DL:e.isLine?IL:e.isMesh?LL:void 0}getSampleCount(e){return e>=4?4:1}getSampleCountRenderContext(e){return null!==e.textures?this.getSampleCount(e.sampleCount):this.getSampleCount(this.backend.renderer.samples)}getPreferredCanvasFormat(){const e=this.backend.parameters.outputType;if(void 0===e)return navigator.gpu.getPreferredCanvasFormat();if(e===Gi)return yj;if(e===Ki)return Bj;throw new Error("Unsupported outputType")}}const dR=new Map([[Int8Array,["sint8","snorm8"]],[Uint8Array,["uint8","unorm8"]],[Int16Array,["sint16","snorm16"]],[Uint16Array,["uint16","unorm16"]],[Int32Array,["sint32","snorm32"]],[Uint32Array,["uint32","unorm32"]],[Float32Array,["float32"]]]);"undefined"!=typeof Float16Array&&dR.set(Float16Array,["float16"]);const hR=new Map([[Oa,["float16"]]]),fR=new Map([[Int32Array,"sint32"],[Int16Array,"sint32"],[Uint32Array,"uint32"],[Uint16Array,"uint32"],[Float32Array,"float32"]]);class pR{constructor(e){this.backend=e}createAttribute(e,t){const n=this._getBufferAttribute(e),i=this.backend,r=i.get(n);let s=r.buffer;if(void 0===s){const o=i.device;let a=n.array;if(!1===e.normalized)if(a.constructor===Int16Array||a.constructor===Int8Array)a=new Int32Array(a);else if((a.constructor===Uint16Array||a.constructor===Uint8Array)&&(a=new Uint32Array(a),t&GPUBufferUsage.INDEX))for(let e=0;e<a.length;e++)65535===a[e]&&(a[e]=4294967295);if(n.array=a,(n.isStorageBufferAttribute||n.isStorageInstancedBufferAttribute)&&3===n.itemSize){a=new a.constructor(4*n.count);for(let e=0;e<n.count;e++)a.set(n.array.subarray(3*e,3*e+3),4*e);n.itemSize=4,n.array=a,r._force3to4BytesAlignment=!0}const l=a.byteLength,u=l+(4-l%4)%4;s=o.createBuffer({label:n.name,size:u,usage:t,mappedAtCreation:!0}),new a.constructor(s.getMappedRange()).set(a),s.unmap(),r.buffer=s}}updateAttribute(e){const t=this._getBufferAttribute(e),n=this.backend,i=n.device,r=n.get(t),s=n.get(t).buffer;let o=t.array;if(!0===r._force3to4BytesAlignment){o=new o.constructor(4*t.count);for(let e=0;e<t.count;e++)o.set(t.array.subarray(3*e,3*e+3),4*e);t.array=o}const a=this._isTypedArray(o),l=t.updateRanges;if(0===l.length)i.queue.writeBuffer(s,0,o,0);else{const e=a?1:o.BYTES_PER_ELEMENT;for(let t=0,n=l.length;t<n;t++){const n=l[t];let u,c;if(!0===r._force3to4BytesAlignment){u=4*Math.floor(n.start/3)*e,c=4*Math.ceil(n.count/3)*e}else u=n.start*e,c=n.count*e;const d=u*(a?o.BYTES_PER_ELEMENT:1);i.queue.writeBuffer(s,d,o,u,c)}t.clearUpdateRanges()}}createShaderVertexBuffers(e){const t=e.getAttributes(),n=new Map;for(let e=0;e<t.length;e++){const i=t[e],r=i.array.BYTES_PER_ELEMENT,s=this._getBufferAttribute(i);let o=n.get(s);if(void 0===o){let e,t;!0===i.isInterleavedBufferAttribute?(e=i.data.stride*r,t=i.data.isInstancedInterleavedBuffer?zz:Oz):(e=i.itemSize*r,t=i.isInstancedBufferAttribute?zz:Oz),!1!==i.normalized||i.array.constructor!==Int16Array&&i.array.constructor!==Uint16Array||(e=4),o={arrayStride:e,attributes:[],stepMode:t},n.set(s,o)}const a=this._getVertexFormat(i),l=!0===i.isInterleavedBufferAttribute?i.offset*r:0;o.attributes.push({shaderLocation:e,offset:l,format:a})}return Array.from(n.values())}destroyAttribute(e){const t=this.backend;t.get(this._getBufferAttribute(e)).buffer.destroy(),t.delete(e)}async getArrayBufferAsync(e){const t=this.backend,n=t.device,i=t.get(this._getBufferAttribute(e)).buffer,r=i.size,s=n.createBuffer({label:`${e.name}_readback`,size:r,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ}),o=n.createCommandEncoder({label:`readback_encoder_${e.name}`});o.copyBufferToBuffer(i,0,s,0,r);const a=o.finish();n.queue.submit([a]),await s.mapAsync(GPUMapMode.READ);const l=s.getMappedRange(),u=new e.array.constructor(l.slice(0));return s.unmap(),u.buffer}_getVertexFormat(e){const{itemSize:t,normalized:n}=e,i=e.array.constructor,r=e.constructor;let s;if(1===t)s=fR.get(i);else{const e=(hR.get(r)||dR.get(i))[n?1:0];if(e){const n=i.BYTES_PER_ELEMENT*t,r=4*Math.floor((n+3)/4)/i.BYTES_PER_ELEMENT;if(r%1)throw new Error("THREE.WebGPUAttributeUtils: Bad vertex format item size.");s=`${e}x${r}`}}return s||console.error("THREE.WebGPUAttributeUtils: Vertex format not supported yet."),s}_isTypedArray(e){return ArrayBuffer.isView(e)&&!(e instanceof DataView)}_getBufferAttribute(e){return e.isInterleavedBufferAttribute&&(e=e.data),e}}class gR{constructor(e){this.backend=e,this.bindGroupLayoutCache=new WeakMap}createBindingsLayout(e){const t=this.backend,n=t.device,i=[];let r=0;for(const n of e.bindings){const e={binding:r++,visibility:n.visibility};if(n.isUniformBuffer||n.isStorageBuffer){const t={};n.isStorageBuffer&&(4&n.visibility&&(n.access===fv.READ_WRITE||n.access===fv.WRITE_ONLY)?t.type=mz:t.type=vz),e.buffer=t}else if(n.isSampledTexture&&n.store){const t={};t.format=this.backend.get(n.texture).texture.format;const i=n.access;t.access=i===fv.READ_WRITE?yz:i===fv.WRITE_ONLY?Az:xz,n.texture.isArrayTexture?t.viewDimension=Dz:n.texture.is3DTexture&&(t.viewDimension=Lz),e.storageTexture=t}else if(n.isSampledTexture){const i={},{primarySamples:r}=t.utils.getTextureSampleData(n.texture);if(r>1&&(i.multisampled=!0,n.texture.isDepthTexture||(i.sampleType=Mz)),n.texture.isDepthTexture)t.compatibilityMode&&null===n.texture.compareFunction?i.sampleType=Mz:i.sampleType=Ez;else if(n.texture.isDataTexture||n.texture.isDataArrayTexture||n.texture.isData3DTexture){const e=n.texture.type;e===Zi?i.sampleType=Tz:e===Yi?i.sampleType=Sz:e===Ji&&(this.backend.hasFeature("float32-filterable")?i.sampleType=Cz:i.sampleType=Mz)}n.isSampledCubeTexture?i.viewDimension=Iz:n.texture.isArrayTexture||n.texture.isDataArrayTexture||n.texture.isCompressedArrayTexture?i.viewDimension=Dz:n.isSampledTexture3D&&(i.viewDimension=Lz),e.texture=i}else if(n.isSampler){const i={};n.texture.isDepthTexture&&(null!==n.texture.compareFunction?i.type=wz:t.compatibilityMode&&(i.type=bz)),e.sampler=i}else console.error(`WebGPUBindingUtils: Unsupported binding "${n}".`);i.push(e)}return n.createBindGroupLayout({entries:i})}createBindings(e,t,n,i=0){const{backend:r,bindGroupLayoutCache:s}=this,o=r.get(e);let a,l=s.get(e.bindingsReference);void 0===l&&(l=this.createBindingsLayout(e),s.set(e.bindingsReference,l)),n>0&&(void 0===o.groups&&(o.groups=[],o.versions=[]),o.versions[n]===i&&(a=o.groups[n])),void 0===a&&(a=this.createBindGroup(e,l),n>0&&(o.groups[n]=a,o.versions[n]=i)),o.group=a,o.layout=l}updateBinding(e){const t=this.backend,n=t.device,i=e.buffer,r=t.get(e).buffer;n.queue.writeBuffer(r,0,i,0)}createBindGroupIndex(e,t){const n=this.backend.device,i=GPUBufferUsage.UNIFORM|GPUBufferUsage.COPY_DST,r=e[0],s=n.createBuffer({label:"bindingCameraIndex_"+r,size:16,usage:i});n.queue.writeBuffer(s,0,e,0);const o=[{binding:0,resource:{buffer:s}}];return n.createBindGroup({label:"bindGroupCameraIndex_"+r,layout:t,entries:o})}createBindGroup(e,t){const n=this.backend,i=n.device;let r=0;const s=[];for(const t of e.bindings){if(t.isUniformBuffer){const e=n.get(t);if(void 0===e.buffer){const n=t.byteLength,r=GPUBufferUsage.UNIFORM|GPUBufferUsage.COPY_DST,s=i.createBuffer({label:"bindingBuffer_"+t.name,size:n,usage:r});e.buffer=s}s.push({binding:r,resource:{buffer:e.buffer}})}else if(t.isStorageBuffer){const e=n.get(t);if(void 0===e.buffer){const i=t.attribute;e.buffer=n.get(i).buffer}s.push({binding:r,resource:{buffer:e.buffer}})}else if(t.isSampledTexture){const e=n.get(t.texture);let o;if(void 0!==e.externalTexture)o=i.importExternalTexture({source:e.externalTexture});else{const n=t.store?1:e.texture.mipLevelCount;let i=`view-${e.texture.width}-${e.texture.height}`;if(e.texture.depthOrArrayLayers>1&&(i+=`-${e.texture.depthOrArrayLayers}`),i+=`-${n}`,o=e[i],void 0===o){const r=jz;let s;s=t.isSampledCubeTexture?Iz:t.isSampledTexture3D?Lz:t.texture.isArrayTexture||t.texture.isDataArrayTexture||t.texture.isCompressedArrayTexture?Dz:Bz,o=e[i]=e.texture.createView({aspect:r,dimension:s,mipLevelCount:n})}}s.push({binding:r,resource:o})}else if(t.isSampler){const e=n.get(t.texture);s.push({binding:r,resource:e.sampler})}r++}return i.createBindGroup({label:"bindGroup_"+e.name,layout:t,entries:s})}}class mR{constructor(e){this.backend=e,this._activePipelines=new WeakMap}setPipeline(e,t){this._activePipelines.get(e)!==t&&(e.setPipeline(t),this._activePipelines.set(e,t))}_getSampleCount(e){return this.backend.utils.getSampleCountRenderContext(e)}createRenderPipeline(e,t){const{object:n,material:i,geometry:r,pipeline:s}=e,{vertexProgram:o,fragmentProgram:a}=s,l=this.backend,u=l.device,c=l.utils,d=l.get(s),h=[];for(const t of e.getBindings()){const e=l.get(t);h.push(e.layout)}const f=l.attributeUtils.createShaderVertexBuffers(e);let p;0===i.blending||1===i.blending&&!1===i.transparent||(p=this._getBlending(i));let g={};!0===i.stencilWrite&&(g={compare:this._getStencilCompare(i),failOp:this._getStencilOperation(i.stencilFail),depthFailOp:this._getStencilOperation(i.stencilZFail),passOp:this._getStencilOperation(i.stencilZPass)});const m=this._getColorWriteMask(i),v=[];if(null!==e.context.textures){const t=e.context.textures;for(let e=0;e<t.length;e++){const n=c.getTextureFormatGPU(t[e]);v.push({format:n,blend:p,writeMask:m})}}else{const t=c.getCurrentColorFormat(e.context);v.push({format:t,blend:p,writeMask:m})}const A=l.get(o).module,x=l.get(a).module,y=this._getPrimitiveState(n,r,i),b=this._getDepthCompare(i),w=c.getCurrentDepthStencilFormat(e.context),C=this._getSampleCount(e.context),M={label:`renderPipeline_${i.name||i.type}_${i.id}`,vertex:Object.assign({},A,{buffers:f}),fragment:Object.assign({},x,{targets:v}),primitive:y,multisample:{count:C,alphaToCoverageEnabled:i.alphaToCoverage&&C>1},layout:u.createPipelineLayout({bindGroupLayouts:h})},E={},T=e.context.depth,S=e.context.stencil;if(!0!==T&&!0!==S||(!0===T&&(E.format=w,E.depthWriteEnabled=i.depthWrite,E.depthCompare=b),!0===S&&(E.stencilFront=g,E.stencilBack={},E.stencilReadMask=i.stencilFuncMask,E.stencilWriteMask=i.stencilWriteMask),!0===i.polygonOffset&&(E.depthBias=i.polygonOffsetUnits,E.depthBiasSlopeScale=i.polygonOffsetFactor,E.depthBiasClamp=0),M.depthStencil=E),null===t)d.pipeline=u.createRenderPipeline(M);else{const e=new Promise((e=>{u.createRenderPipelineAsync(M).then((t=>{d.pipeline=t,e()}))}));t.push(e)}}createBundleEncoder(e,t="renderBundleEncoder"){const n=this.backend,{utils:i,device:r}=n,s=i.getCurrentDepthStencilFormat(e),o={label:t,colorFormats:[i.getCurrentColorFormat(e)],depthStencilFormat:s,sampleCount:this._getSampleCount(e)};return r.createRenderBundleEncoder(o)}createComputePipeline(e,t){const n=this.backend,i=n.device,r=n.get(e.computeProgram).module,s=n.get(e),o=[];for(const e of t){const t=n.get(e);o.push(t.layout)}s.pipeline=i.createComputePipeline({compute:r,layout:i.createPipelineLayout({bindGroupLayouts:o})})}_getBlending(e){let t,n;const i=e.blending,r=e.blendSrc,s=e.blendDst,o=e.blendEquation;if(5===i){const i=null!==e.blendSrcAlpha?e.blendSrcAlpha:r,a=null!==e.blendDstAlpha?e.blendDstAlpha:s,l=null!==e.blendEquationAlpha?e.blendEquationAlpha:o;t={srcFactor:this._getBlendFactor(r),dstFactor:this._getBlendFactor(s),operation:this._getBlendOperation(o)},n={srcFactor:this._getBlendFactor(i),dstFactor:this._getBlendFactor(a),operation:this._getBlendOperation(l)}}else{const r=(e,i,r,s)=>{t={srcFactor:e,dstFactor:i,operation:tz},n={srcFactor:r,dstFactor:s,operation:tz}};if(e.premultipliedAlpha)switch(i){case 1:r(GO,ZO,GO,ZO);break;case 2:r(GO,GO,GO,GO);break;case 3:r(XO,WO,XO,GO);break;case 4:r(YO,ZO,XO,GO)}else switch(i){case 1:r(QO,ZO,GO,ZO);break;case 2:r(QO,GO,GO,GO);break;case 3:console.error("THREE.WebGPURenderer: SubtractiveBlending requires material.premultipliedAlpha = true");break;case 4:console.error("THREE.WebGPURenderer: MultiplyBlending requires material.premultipliedAlpha = true")}}if(void 0!==t&&void 0!==n)return{color:t,alpha:n};console.error("THREE.WebGPURenderer: Invalid blending: ",i)}_getBlendFactor(e){let t;switch(e){case Ei:t=XO;break;case 201:t=GO;break;case 202:t=VO;break;case 203:t=WO;break;case Ti:t=QO;break;case Si:t=ZO;break;case 208:t=YO;break;case 209:t=JO;break;case 206:t=KO;break;case 207:t=qO;break;case 210:t=_O;break;case 211:t=$O;break;case 212:t=ez;break;default:console.error("THREE.WebGPURenderer: Blend factor not supported.",e)}return t}_getStencilCompare(e){let t;const n=e.stencilFunc;switch(n){case 512:t=OL;break;case 519:t=XL;break;case 513:t=zL;break;case 515:t=kL;break;case 514:t=RL;break;case 518:t=UL;break;case 516:t=FL;break;case 517:t=HL;break;default:console.error("THREE.WebGPURenderer: Invalid stencil function.",n)}return t}_getStencilOperation(e){let t;switch(e){case ts:t=lz;break;case 0:t=uz;break;case 7681:t=cz;break;case 5386:t=dz;break;case 7682:t=hz;break;case 7683:t=fz;break;case 34055:t=pz;break;case 34056:t=gz;break;default:console.error("THREE.WebGPURenderer: Invalid stencil operation.",t)}return t}_getBlendOperation(e){let t;switch(e){case Mi:t=tz;break;case 101:t=nz;break;case 102:t=iz;break;case 103:t=rz;break;case 104:t=sz;break;default:console.error("THREE.WebGPUPipelineUtils: Blend equation not supported.",e)}return t}_getPrimitiveState(e,t,n){const i={},r=this.backend.utils;i.topology=r.getPrimitiveTopology(e,n),null!==t.index&&!0===e.isLine&&!0!==e.isLineSegments&&(i.stripIndexFormat=t.index.array instanceof Uint16Array?KL:qL);let s=1===n.side;return e.isMesh&&e.matrixWorld.determinant()<0&&(s=!s),i.frontFace=!0===s?ZL:QL,i.cullMode=2===n.side?YL:JL,i}_getColorWriteMask(e){return!0===e.colorWrite?az:oz}_getDepthCompare(e){let t;if(!1===e.depthTest)t=XL;else{const n=e.depthFunc;switch(n){case 0:t=OL;break;case 1:t=XL;break;case 2:t=zL;break;case 3:t=kL;break;case 4:t=RL;break;case 5:t=UL;break;case 6:t=FL;break;case 7:t=HL;break;default:console.error("THREE.WebGPUPipelineUtils: Invalid depth function.",n)}}return t}}class vR extends SL{constructor(e,t,n=2048){super(n),this.device=e,this.type=t,this.querySet=this.device.createQuerySet({type:"timestamp",count:this.maxQueries,label:`queryset_global_timestamp_${t}`});const i=8*this.maxQueries;this.resolveBuffer=this.device.createBuffer({label:`buffer_timestamp_resolve_${t}`,size:i,usage:GPUBufferUsage.QUERY_RESOLVE|GPUBufferUsage.COPY_SRC}),this.resultBuffer=this.device.createBuffer({label:`buffer_timestamp_result_${t}`,size:i,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ})}allocateQueriesForContext(e){if(!this.trackTimestamp||this.isDisposed)return null;if(this.currentQueryIndex+2>this.maxQueries)return js(`WebGPUTimestampQueryPool [${this.type}]: Maximum number of queries exceeded, when using trackTimestamp it is necessary to resolves the queries via renderer.resolveTimestampsAsync( THREE.TimestampQuery.${this.type.toUpperCase()} ).`),null;const t=this.currentQueryIndex;return this.currentQueryIndex+=2,this.queryOffsets.set(e,t),t}async resolveQueriesAsync(){if(!this.trackTimestamp||0===this.currentQueryIndex||this.isDisposed)return this.lastValue;if(this.pendingResolve)return this.pendingResolve;this.pendingResolve=this._resolveQueries();try{return await this.pendingResolve}finally{this.pendingResolve=null}}async _resolveQueries(){if(this.isDisposed)return this.lastValue;try{if("unmapped"!==this.resultBuffer.mapState)return this.lastValue;const e=new Map(this.queryOffsets),t=this.currentQueryIndex,n=8*t;this.currentQueryIndex=0,this.queryOffsets.clear();const i=this.device.createCommandEncoder();i.resolveQuerySet(this.querySet,0,t,this.resolveBuffer,0),i.copyBufferToBuffer(this.resolveBuffer,0,this.resultBuffer,0,n);const r=i.finish();if(this.device.queue.submit([r]),"unmapped"!==this.resultBuffer.mapState)return this.lastValue;if(await this.resultBuffer.mapAsync(GPUMapMode.READ,0,n),this.isDisposed)return"mapped"===this.resultBuffer.mapState&&this.resultBuffer.unmap(),this.lastValue;const s=new BigUint64Array(this.resultBuffer.getMappedRange(0,n));let o=0;for(const[,t]of e){const e=s[t],n=s[t+1];o+=Number(n-e)/1e6}return this.resultBuffer.unmap(),this.lastValue=o,o}catch(e){return console.error("Error resolving queries:",e),"mapped"===this.resultBuffer.mapState&&this.resultBuffer.unmap(),this.lastValue}}async dispose(){if(!this.isDisposed){if(this.isDisposed=!0,this.pendingResolve)try{await this.pendingResolve}catch(e){console.error("Error waiting for pending resolve:",e)}if(this.resultBuffer&&"mapped"===this.resultBuffer.mapState)try{this.resultBuffer.unmap()}catch(e){console.error("Error unmapping buffer:",e)}this.querySet&&(this.querySet.destroy(),this.querySet=null),this.resolveBuffer&&(this.resolveBuffer.destroy(),this.resolveBuffer=null),this.resultBuffer&&(this.resultBuffer.destroy(),this.resultBuffer=null),this.queryOffsets.clear(),this.pendingResolve=null}}}class AR extends uL{constructor(e={}){super(e),this.isWebGPUBackend=!0,this.parameters.alpha=void 0===e.alpha||e.alpha,this.parameters.compatibilityMode=void 0!==e.compatibilityMode&&e.compatibilityMode,this.parameters.requiredLimits=void 0===e.requiredLimits?{}:e.requiredLimits,this.compatibilityMode=this.parameters.compatibilityMode,this.device=null,this.context=null,this.colorBuffer=null,this.defaultRenderPassdescriptor=null,this.utils=new cR(this),this.attributeUtils=new pR(this),this.bindingUtils=new gR(this),this.pipelineUtils=new mR(this),this.textureUtils=new Wz(this),this.occludedResolveCache=new Map}async init(e){await super.init(e);const t=this.parameters;let n;if(void 0===t.device){const e={powerPreference:t.powerPreference,featureLevel:t.compatibilityMode?"compatibility":void 0},i="undefined"!=typeof navigator?await navigator.gpu.requestAdapter(e):null;if(null===i)throw new Error("WebGPUBackend: Unable to create WebGPU adapter.");const r=Object.values(Rz),s=[];for(const e of r)i.features.has(e)&&s.push(e);const o={requiredFeatures:s,requiredLimits:t.requiredLimits};n=await i.requestDevice(o)}else n=t.device;n.lost.then((t=>{const n={api:"WebGPU",message:t.message||"Unknown reason",reason:t.reason||null,originalEvent:t};e.onDeviceLost(n)}));const i=void 0!==t.context?t.context:e.domElement.getContext("webgpu");this.device=n,this.context=i;const r=t.alpha?"premultiplied":"opaque",s=ks.getToneMappingMode(this.renderer.outputColorSpace);this.context.configure({device:this.device,format:this.utils.getPreferredCanvasFormat(),usage:GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.COPY_SRC,alphaMode:r,toneMapping:{mode:s}}),this.trackTimestamp=this.trackTimestamp&&this.hasFeature(Rz.TimestampQuery),this.updateSize()}get coordinateSystem(){return ls}async getArrayBufferAsync(e){return await this.attributeUtils.getArrayBufferAsync(e)}getContext(){return this.context}_getDefaultRenderPassDescriptor(){let e=this.defaultRenderPassdescriptor;if(null===e){const t=this.renderer;e={colorAttachments:[{view:null}]},!0!==this.renderer.depth&&!0!==this.renderer.stencil||(e.depthStencilAttachment={view:this.textureUtils.getDepthBuffer(t.depth,t.stencil).createView()});const n=e.colorAttachments[0];this.renderer.samples>0?n.view=this.colorBuffer.createView():n.resolveTarget=void 0,this.defaultRenderPassdescriptor=e}const t=e.colorAttachments[0];return this.renderer.samples>0?t.resolveTarget=this.context.getCurrentTexture().createView():t.view=this.context.getCurrentTexture().createView(),e}_isRenderCameraDepthArray(e){return e.depthTexture&&e.depthTexture.image.depth>1&&e.camera.isArrayCamera}_getRenderPassDescriptor(e,t={}){const n=e.renderTarget,i=this.get(n);let r=i.descriptors;void 0!==r&&i.width===n.width&&i.height===n.height&&i.samples===n.samples||(r={},i.descriptors=r);const s=e.getCacheKey();let o=r[s];if(void 0===o){const t=e.textures,a=[];let l;const u=this._isRenderCameraDepthArray(e);for(let i=0;i<t.length;i++){const r=this.get(t[i]),s={label:`colorAttachment_${i}`,baseMipLevel:e.activeMipmapLevel,mipLevelCount:1,baseArrayLayer:e.activeCubeFace,arrayLayerCount:1,dimension:Bz};if(n.isRenderTarget3D)l=e.activeCubeFace,s.baseArrayLayer=0,s.dimension=Lz,s.depthOrArrayLayers=t[i].image.depth;else if(n.isRenderTarget&&t[i].image.depth>1)if(!0===u){const t=e.camera.cameras;for(let e=0;e<t.length;e++){const t={...s,baseArrayLayer:e,arrayLayerCount:1,dimension:Bz},n=r.texture.createView(t);a.push({view:n,resolveTarget:void 0,depthSlice:void 0})}}else s.dimension=Dz,s.depthOrArrayLayers=t[i].image.depth;if(!0!==u){const e=r.texture.createView(s);let t,n;void 0!==r.msaaTexture?(t=r.msaaTexture.createView(),n=e):(t=e,n=void 0),a.push({view:t,resolveTarget:n,depthSlice:l})}}if(o={textureViews:a},e.depth){const t=this.get(e.depthTexture),n={};e.depthTexture.isArrayTexture&&(n.dimension=Bz,n.arrayLayerCount=1,n.baseArrayLayer=e.activeCubeFace),o.depthStencilView=t.texture.createView(n)}r[s]=o,i.width=n.width,i.height=n.height,i.samples=n.samples,i.activeMipmapLevel=e.activeMipmapLevel,i.activeCubeFace=e.activeCubeFace}const a={colorAttachments:[]};for(let e=0;e<o.textureViews.length;e++){const n=o.textureViews[e];let i={r:0,g:0,b:0,a:1};0===e&&t.clearValue&&(i=t.clearValue),a.colorAttachments.push({view:n.view,depthSlice:n.depthSlice,resolveTarget:n.resolveTarget,loadOp:t.loadOp||VL,storeOp:t.storeOp||GL,clearValue:i})}return o.depthStencilView&&(a.depthStencilAttachment={view:o.depthStencilView}),a}beginRender(e){const t=this.get(e);t.frameCalls=this.renderer.info.render.frameCalls;const n=this.device,i=e.occlusionQueryCount;let r,s;i>0&&(t.currentOcclusionQuerySet&&t.currentOcclusionQuerySet.destroy(),t.currentOcclusionQueryBuffer&&t.currentOcclusionQueryBuffer.destroy(),t.currentOcclusionQuerySet=t.occlusionQuerySet,t.currentOcclusionQueryBuffer=t.occlusionQueryBuffer,t.currentOcclusionQueryObjects=t.occlusionQueryObjects,r=n.createQuerySet({type:"occlusion",count:i,label:`occlusionQuerySet_${e.id}`}),t.occlusionQuerySet=r,t.occlusionQueryIndex=0,t.occlusionQueryObjects=new Array(i),t.lastOcclusionObject=null),s=null===e.textures?this._getDefaultRenderPassDescriptor():this._getRenderPassDescriptor(e,{loadOp:VL}),this.initTimestampQuery(cs,this.getTimestampUID(e),s),s.occlusionQuerySet=r;const o=s.depthStencilAttachment;if(null!==e.textures){const t=s.colorAttachments;for(let n=0;n<t.length;n++){const i=t[n];e.clearColor?(i.clearValue=0===n?e.clearColorValue:{r:0,g:0,b:0,a:1},i.loadOp=WL):i.loadOp=VL,i.storeOp=GL}}else{const t=s.colorAttachments[0];e.clearColor?(t.clearValue=e.clearColorValue,t.loadOp=WL):t.loadOp=VL,t.storeOp=GL}e.depth&&(e.clearDepth?(o.depthClearValue=e.clearDepthValue,o.depthLoadOp=WL):o.depthLoadOp=VL,o.depthStoreOp=GL),e.stencil&&(e.clearStencil?(o.stencilClearValue=e.clearStencilValue,o.stencilLoadOp=WL):o.stencilLoadOp=VL,o.stencilStoreOp=GL);const a=n.createCommandEncoder({label:"renderContext_"+e.id});if(!0===this._isRenderCameraDepthArray(e)){const n=e.camera.cameras;t.layerDescriptors&&t.layerDescriptors.length===n.length?this._updateDepthLayerDescriptors(e,t,n):this._createDepthLayerDescriptors(e,t,s,n),t.bundleEncoders=[],t.bundleSets=[];for(let i=0;i<n.length;i++){const n=this.pipelineUtils.createBundleEncoder(e,"renderBundleArrayCamera_"+i),r={attributes:{},bindingGroups:[],pipeline:null,index:null};t.bundleEncoders.push(n),t.bundleSets.push(r)}t.currentPass=null}else{const n=a.beginRenderPass(s);if(t.currentPass=n,e.viewport&&this.updateViewport(e),e.scissor){const{x:t,y:i,width:r,height:s}=e.scissorValue;n.setScissorRect(t,i,r,s)}}t.descriptor=s,t.encoder=a,t.currentSets={attributes:{},bindingGroups:[],pipeline:null,index:null},t.renderBundles=[]}_createDepthLayerDescriptors(e,t,n,i){const r=n.depthStencilAttachment;t.layerDescriptors=[];const s=this.get(e.depthTexture);s.viewCache||(s.viewCache=[]);for(let o=0;o<i.length;o++){const i={...n,colorAttachments:[{...n.colorAttachments[0],view:n.colorAttachments[o].view}]};if(n.depthStencilAttachment){const t=o;s.viewCache[t]||(s.viewCache[t]=s.texture.createView({dimension:Bz,baseArrayLayer:o,arrayLayerCount:1})),i.depthStencilAttachment={view:s.viewCache[t],depthLoadOp:r.depthLoadOp||WL,depthStoreOp:r.depthStoreOp||GL,depthClearValue:r.depthClearValue||1},e.stencil&&(i.depthStencilAttachment.stencilLoadOp=r.stencilLoadOp,i.depthStencilAttachment.stencilStoreOp=r.stencilStoreOp,i.depthStencilAttachment.stencilClearValue=r.stencilClearValue)}else i.depthStencilAttachment={...r};t.layerDescriptors.push(i)}}_updateDepthLayerDescriptors(e,t,n){for(let i=0;i<n.length;i++){const n=t.layerDescriptors[i];if(n.depthStencilAttachment){const t=n.depthStencilAttachment;e.depth&&(e.clearDepth?(t.depthClearValue=e.clearDepthValue,t.depthLoadOp=WL):t.depthLoadOp=VL),e.stencil&&(e.clearStencil?(t.stencilClearValue=e.clearStencilValue,t.stencilLoadOp=WL):t.stencilLoadOp=VL)}}}finishRender(e){const t=this.get(e),n=e.occlusionQueryCount;t.renderBundles.length>0&&t.currentPass.executeBundles(t.renderBundles),n>t.occlusionQueryIndex&&t.currentPass.endOcclusionQuery();const i=t.encoder;if(!0===this._isRenderCameraDepthArray(e)){const n=[];for(let e=0;e<t.bundleEncoders.length;e++){const i=t.bundleEncoders[e];n.push(i.finish())}for(let r=0;r<t.layerDescriptors.length;r++)if(r<n.length){const s=t.layerDescriptors[r],o=i.beginRenderPass(s);if(e.viewport){const{x:t,y:n,width:i,height:r,minDepth:s,maxDepth:a}=e.viewportValue;o.setViewport(t,n,i,r,s,a)}if(e.scissor){const{x:t,y:n,width:i,height:r}=e.scissorValue;o.setScissorRect(t,n,i,r)}o.executeBundles([n[r]]),o.end()}}else t.currentPass&&t.currentPass.end();if(n>0){const i=8*n;let r=this.occludedResolveCache.get(i);void 0===r&&(r=this.device.createBuffer({size:i,usage:GPUBufferUsage.QUERY_RESOLVE|GPUBufferUsage.COPY_SRC}),this.occludedResolveCache.set(i,r));const s=this.device.createBuffer({size:i,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ});t.encoder.resolveQuerySet(t.occlusionQuerySet,0,n,r,0),t.encoder.copyBufferToBuffer(r,0,s,0,i),t.occlusionQueryBuffer=s,this.resolveOccludedAsync(e)}if(this.device.queue.submit([t.encoder.finish()]),null!==e.textures){const t=e.textures;for(let e=0;e<t.length;e++){const n=t[e];!0===n.generateMipmaps&&this.textureUtils.generateMipmaps(n)}}}isOccluded(e,t){const n=this.get(e);return n.occluded&&n.occluded.has(t)}async resolveOccludedAsync(e){const t=this.get(e),{currentOcclusionQueryBuffer:n,currentOcclusionQueryObjects:i}=t;if(n&&i){const e=new WeakSet;t.currentOcclusionQueryObjects=null,t.currentOcclusionQueryBuffer=null,await n.mapAsync(GPUMapMode.READ);const r=n.getMappedRange(),s=new BigUint64Array(r);for(let t=0;t<i.length;t++)s[t]===BigInt(0)&&e.add(i[t]);n.destroy(),t.occluded=e}}updateViewport(e){const{currentPass:t}=this.get(e),{x:n,y:i,width:r,height:s,minDepth:o,maxDepth:a}=e.viewportValue;t.setViewport(n,i,r,s,o,a)}getClearColor(){const e=super.getClearColor();return!0===this.renderer.alpha&&(e.r*=e.a,e.g*=e.a,e.b*=e.a),e}clear(e,t,n,i=null){const r=this.device,s=this.renderer;let o,a,l,u,c=[];if(e){const e=this.getClearColor();a={r:e.r,g:e.g,b:e.b,a:e.a}}if(null===i){l=s.depth,u=s.stencil;const t=this._getDefaultRenderPassDescriptor();if(e){c=t.colorAttachments;const e=c[0];e.clearValue=a,e.loadOp=WL,e.storeOp=GL}(l||u)&&(o=t.depthStencilAttachment)}else{l=i.depth,u=i.stencil;const r={loadOp:e?WL:VL,clearValue:e?a:void 0};l&&(r.depthLoadOp=t?WL:VL,r.depthClearValue=t?s.getClearDepth():void 0,r.depthStoreOp=GL),u&&(r.stencilLoadOp=n?WL:VL,r.stencilClearValue=n?s.getClearStencil():void 0,r.stencilStoreOp=GL);const d=this._getRenderPassDescriptor(i,r);c=d.colorAttachments,o=d.depthStencilAttachment}l&&o&&(t?(o.depthLoadOp=WL,o.depthClearValue=s.getClearDepth(),o.depthStoreOp=GL):(o.depthLoadOp=VL,o.depthStoreOp=GL)),u&&o&&(n?(o.stencilLoadOp=WL,o.stencilClearValue=s.getClearStencil(),o.stencilStoreOp=GL):(o.stencilLoadOp=VL,o.stencilStoreOp=GL));const d=r.createCommandEncoder({label:"clear"});d.beginRenderPass({colorAttachments:c,depthStencilAttachment:o}).end(),r.queue.submit([d.finish()])}beginCompute(e){const t=this.get(e);t.frameCalls=this.renderer.info.compute.frameCalls;const n={label:"computeGroup_"+e.id};this.initTimestampQuery(us,this.getTimestampUID(e),n),t.cmdEncoderGPU=this.device.createCommandEncoder({label:"computeGroup_"+e.id}),t.passEncoderGPU=t.cmdEncoderGPU.beginComputePass(n)}compute(e,t,n,i,r=null){const s=this.get(t),{passEncoderGPU:o}=this.get(e),a=this.get(i).pipeline;this.pipelineUtils.setPipeline(o,a);for(let e=0,t=n.length;e<t;e++){const t=n[e],i=this.get(t);o.setBindGroup(e,i.group)}let l;if(null===r&&(r=t.count),"number"==typeof r){const e=r;if(void 0===s.dispatchSize||s.count!==e){s.dispatchSize=[0,1,1],s.count=e;const n=t.workgroupSize;let i=n[0];for(let e=1;e<n.length;e++)i*=n[e];const r=Math.ceil(e/i),o=this.device.limits.maxComputeWorkgroupsPerDimension;l=[r,1,1],r>o&&(l[0]=Math.min(r,o),l[1]=Math.ceil(r/o)),s.dispatchSize=l}l=s.dispatchSize}else l=r;o.dispatchWorkgroups(l[0],l[1]||1,l[2]||1)}finishCompute(e){const t=this.get(e);t.passEncoderGPU.end(),this.device.queue.submit([t.cmdEncoderGPU.finish()])}async waitForGPU(){await this.device.queue.onSubmittedWorkDone()}draw(e,t){const{object:n,material:i,context:r,pipeline:s}=e,o=e.getBindings(),a=this.get(r),l=this.get(s).pipeline,u=e.getIndex(),c=null!==u,d=e.getDrawParameters();if(null===d)return;const h=(t,n)=>{this.pipelineUtils.setPipeline(t,l),n.pipeline=l;const s=n.bindingGroups;for(let e=0,n=o.length;e<n;e++){const n=o[e],i=this.get(n);s[n.index]!==n.id&&(t.setBindGroup(n.index,i.group),s[n.index]=n.id)}if(!0===c&&n.index!==u){const e=this.get(u).buffer,i=u.array instanceof Uint16Array?KL:qL;t.setIndexBuffer(e,i),n.index=u}const d=e.getVertexBuffers();for(let e=0,i=d.length;e<i;e++){const i=d[e];if(n.attributes[e]!==i){const r=this.get(i).buffer;t.setVertexBuffer(e,r),n.attributes[e]=i}}!0===r.stencil&&!0===i.stencilWrite&&a.currentStencilRef!==i.stencilRef&&(t.setStencilReference(i.stencilRef),a.currentStencilRef=i.stencilRef)},f=(i,r)=>{if(h(i,r),!0===n.isBatchedMesh){const e=n._multiDrawStarts,r=n._multiDrawCounts,s=n._multiDrawCount,o=n._multiDrawInstances;null!==o&&js("THREE.WebGPUBackend: renderMultiDrawInstances has been deprecated and will be removed in r184. Append to renderMultiDraw arguments and use indirection.");for(let a=0;a<s;a++){const s=o?o[a]:1,l=s>1?0:a;!0===c?i.drawIndexed(r[a],s,e[a]/u.array.BYTES_PER_ELEMENT,0,l):i.draw(r[a],s,e[a],l),t.update(n,r[a],s)}}else if(!0===c){const{vertexCount:r,instanceCount:s,firstVertex:o}=d,a=e.getIndirect();if(null!==a){const e=this.get(a).buffer;i.drawIndexedIndirect(e,0)}else i.drawIndexed(r,s,o,0,0);t.update(n,r,s)}else{const{vertexCount:r,instanceCount:s,firstVertex:o}=d,a=e.getIndirect();if(null!==a){const e=this.get(a).buffer;i.drawIndirect(e,0)}else i.draw(r,s,o,0);t.update(n,r,s)}};if(e.camera.isArrayCamera&&e.camera.cameras.length>0){const t=this.get(e.camera),i=e.camera.cameras,s=e.getBindingGroup("cameraIndex");if(void 0===t.indexesGPU||t.indexesGPU.length!==i.length){const e=this.get(s),n=[],r=new Uint32Array([0,0,0,0]);for(let t=0,s=i.length;t<s;t++){r[0]=t;const i=this.bindingUtils.createBindGroupIndex(r,e.layout);n.push(i)}t.indexesGPU=n}const o=this.renderer.getPixelRatio();for(let e=0,l=i.length;e<l;e++){const l=i[e];if(n.layers.test(l.layers)){const n=l.viewport;let i=a.currentPass,u=a.currentSets;if(a.bundleEncoders){i=a.bundleEncoders[e],u=a.bundleSets[e]}n&&i.setViewport(Math.floor(n.x*o),Math.floor(n.y*o),Math.floor(n.width*o),Math.floor(n.height*o),r.viewportValue.minDepth,r.viewportValue.maxDepth),s&&t.indexesGPU&&(i.setBindGroup(s.index,t.indexesGPU[e]),u.bindingGroups[s.index]=s.id),f(i,u)}}}else if(a.currentPass){if(void 0!==a.occlusionQuerySet){const e=a.lastOcclusionObject;e!==n&&(null!==e&&!0===e.occlusionTest&&(a.currentPass.endOcclusionQuery(),a.occlusionQueryIndex++),!0===n.occlusionTest&&(a.currentPass.beginOcclusionQuery(a.occlusionQueryIndex),a.occlusionQueryObjects[a.occlusionQueryIndex]=n),a.lastOcclusionObject=n)}f(a.currentPass,a.currentSets)}}needsRenderUpdate(e){const t=this.get(e),{object:n,material:i}=e,r=this.utils,s=r.getSampleCountRenderContext(e.context),o=r.getCurrentColorSpace(e.context),a=r.getCurrentColorFormat(e.context),l=r.getCurrentDepthStencilFormat(e.context),u=r.getPrimitiveTopology(n,i);let c=!1;return t.material===i&&t.materialVersion===i.version&&t.transparent===i.transparent&&t.blending===i.blending&&t.premultipliedAlpha===i.premultipliedAlpha&&t.blendSrc===i.blendSrc&&t.blendDst===i.blendDst&&t.blendEquation===i.blendEquation&&t.blendSrcAlpha===i.blendSrcAlpha&&t.blendDstAlpha===i.blendDstAlpha&&t.blendEquationAlpha===i.blendEquationAlpha&&t.colorWrite===i.colorWrite&&t.depthWrite===i.depthWrite&&t.depthTest===i.depthTest&&t.depthFunc===i.depthFunc&&t.stencilWrite===i.stencilWrite&&t.stencilFunc===i.stencilFunc&&t.stencilFail===i.stencilFail&&t.stencilZFail===i.stencilZFail&&t.stencilZPass===i.stencilZPass&&t.stencilFuncMask===i.stencilFuncMask&&t.stencilWriteMask===i.stencilWriteMask&&t.side===i.side&&t.alphaToCoverage===i.alphaToCoverage&&t.sampleCount===s&&t.colorSpace===o&&t.colorFormat===a&&t.depthStencilFormat===l&&t.primitiveTopology===u&&t.clippingContextCacheKey===e.clippingContextCacheKey||(t.material=i,t.materialVersion=i.version,t.transparent=i.transparent,t.blending=i.blending,t.premultipliedAlpha=i.premultipliedAlpha,t.blendSrc=i.blendSrc,t.blendDst=i.blendDst,t.blendEquation=i.blendEquation,t.blendSrcAlpha=i.blendSrcAlpha,t.blendDstAlpha=i.blendDstAlpha,t.blendEquationAlpha=i.blendEquationAlpha,t.colorWrite=i.colorWrite,t.depthWrite=i.depthWrite,t.depthTest=i.depthTest,t.depthFunc=i.depthFunc,t.stencilWrite=i.stencilWrite,t.stencilFunc=i.stencilFunc,t.stencilFail=i.stencilFail,t.stencilZFail=i.stencilZFail,t.stencilZPass=i.stencilZPass,t.stencilFuncMask=i.stencilFuncMask,t.stencilWriteMask=i.stencilWriteMask,t.side=i.side,t.alphaToCoverage=i.alphaToCoverage,t.sampleCount=s,t.colorSpace=o,t.colorFormat=a,t.depthStencilFormat=l,t.primitiveTopology=u,t.clippingContextCacheKey=e.clippingContextCacheKey,c=!0),c}getRenderCacheKey(e){const{object:t,material:n}=e,i=this.utils,r=e.context,s=t.isMesh&&t.matrixWorld.determinant()<0;return[n.transparent,n.blending,n.premultipliedAlpha,n.blendSrc,n.blendDst,n.blendEquation,n.blendSrcAlpha,n.blendDstAlpha,n.blendEquationAlpha,n.colorWrite,n.depthWrite,n.depthTest,n.depthFunc,n.stencilWrite,n.stencilFunc,n.stencilFail,n.stencilZFail,n.stencilZPass,n.stencilFuncMask,n.stencilWriteMask,n.side,s,i.getSampleCountRenderContext(r),i.getCurrentColorSpace(r),i.getCurrentColorFormat(r),i.getCurrentDepthStencilFormat(r),i.getPrimitiveTopology(t,n),e.getGeometryCacheKey(),e.clippingContextCacheKey].join()}createSampler(e){this.textureUtils.createSampler(e)}destroySampler(e){this.textureUtils.destroySampler(e)}createDefaultTexture(e){this.textureUtils.createDefaultTexture(e)}createTexture(e,t){this.textureUtils.createTexture(e,t)}updateTexture(e,t){this.textureUtils.updateTexture(e,t)}generateMipmaps(e){this.textureUtils.generateMipmaps(e)}destroyTexture(e){this.textureUtils.destroyTexture(e)}async copyTextureToBuffer(e,t,n,i,r,s){return this.textureUtils.copyTextureToBuffer(e,t,n,i,r,s)}initTimestampQuery(e,t,n){if(!this.trackTimestamp)return;this.timestampQueryPool[e]||(this.timestampQueryPool[e]=new vR(this.device,e,2048));const i=this.timestampQueryPool[e],r=i.allocateQueriesForContext(t);n.timestampWrites={querySet:i.querySet,beginningOfPassWriteIndex:r,endOfPassWriteIndex:r+1}}createNodeBuilder(e,t){return new uR(e,t)}createProgram(e){this.get(e).module={module:this.device.createShaderModule({code:e.code,label:e.stage+(""!==e.name?`_${e.name}`:"")}),entryPoint:"main"}}destroyProgram(e){this.delete(e)}createRenderPipeline(e,t){this.pipelineUtils.createRenderPipeline(e,t)}createComputePipeline(e,t){this.pipelineUtils.createComputePipeline(e,t)}beginBundle(e){const t=this.get(e);t._currentPass=t.currentPass,t._currentSets=t.currentSets,t.currentSets={attributes:{},bindingGroups:[],pipeline:null,index:null},t.currentPass=this.pipelineUtils.createBundleEncoder(e)}finishBundle(e,t){const n=this.get(e),i=n.currentPass.finish();this.get(t).bundleGPU=i,n.currentSets=n._currentSets,n.currentPass=n._currentPass}addBundle(e,t){this.get(e).renderBundles.push(this.get(t).bundleGPU)}createBindings(e,t,n,i){this.bindingUtils.createBindings(e,t,n,i)}updateBindings(e,t,n,i){this.bindingUtils.createBindings(e,t,n,i)}updateBinding(e){this.bindingUtils.updateBinding(e)}createIndexAttribute(e){let t=GPUBufferUsage.INDEX|GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST;(e.isStorageBufferAttribute||e.isStorageInstancedBufferAttribute)&&(t|=GPUBufferUsage.STORAGE),this.attributeUtils.createAttribute(e,t)}createAttribute(e){this.attributeUtils.createAttribute(e,GPUBufferUsage.VERTEX|GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST)}createStorageAttribute(e){this.attributeUtils.createAttribute(e,GPUBufferUsage.STORAGE|GPUBufferUsage.VERTEX|GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST)}createIndirectStorageAttribute(e){this.attributeUtils.createAttribute(e,GPUBufferUsage.STORAGE|GPUBufferUsage.INDIRECT|GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST)}updateAttribute(e){this.attributeUtils.updateAttribute(e)}destroyAttribute(e){this.attributeUtils.destroyAttribute(e)}updateSize(){this.colorBuffer=this.textureUtils.getColorBuffer(),this.defaultRenderPassdescriptor=null}getMaxAnisotropy(){return 16}hasFeature(e){return this.device.features.has(e)}copyTextureToTexture(e,t,n=null,i=null,r=0,s=0){let o=0,a=0,l=0,u=0,c=0,d=0,h=e.image.width,f=e.image.height,p=1;null!==n&&(!0===n.isBox3?(u=n.min.x,c=n.min.y,d=n.min.z,h=n.max.x-n.min.x,f=n.max.y-n.min.y,p=n.max.z-n.min.z):(u=n.min.x,c=n.min.y,h=n.max.x-n.min.x,f=n.max.y-n.min.y,p=1)),null!==i&&(o=i.x,a=i.y,l=i.z||0);const g=this.device.createCommandEncoder({label:"copyTextureToTexture_"+e.id+"_"+t.id}),m=this.get(e).texture,v=this.get(t).texture;g.copyTextureToTexture({texture:m,mipLevel:r,origin:{x:u,y:c,z:d}},{texture:v,mipLevel:s,origin:{x:o,y:a,z:l}},[h,f,p]),this.device.queue.submit([g.finish()]),0===s&&t.generateMipmaps&&this.textureUtils.generateMipmaps(t)}copyFramebufferToTexture(e,t,n){const i=this.get(t);let r=null;r=t.renderTarget?e.isDepthTexture?this.get(t.depthTexture).texture:this.get(t.textures[0]).texture:e.isDepthTexture?this.textureUtils.getDepthBuffer(t.depth,t.stencil):this.context.getCurrentTexture();const s=this.get(e).texture;if(r.format!==s.format)return void console.error("WebGPUBackend: copyFramebufferToTexture: Source and destination formats do not match.",r.format,s.format);let o;if(i.currentPass?(i.currentPass.end(),o=i.encoder):o=this.device.createCommandEncoder({label:"copyFramebufferToTexture_"+e.id}),o.copyTextureToTexture({texture:r,origin:[n.x,n.y,0]},{texture:s},[n.z,n.w]),i.currentPass){const{descriptor:e}=i;for(let t=0;t<e.colorAttachments.length;t++)e.colorAttachments[t].loadOp=VL;if(t.depth&&(e.depthStencilAttachment.depthLoadOp=VL),t.stencil&&(e.depthStencilAttachment.stencilLoadOp=VL),i.currentPass=o.beginRenderPass(e),i.currentSets={attributes:{},bindingGroups:[],pipeline:null,index:null},t.viewport&&this.updateViewport(t),t.scissor){const{x:e,y:n,width:r,height:s}=t.scissorValue;i.currentPass.setScissorRect(e,n,r,s)}}else this.device.queue.submit([o.finish()]);e.generateMipmaps&&this.textureUtils.generateMipmaps(e)}}class xR extends oc{constructor(e,t,n,i,r,s){super(e,t,n,i,r,s),this.iesMap=null}copy(e,t){return super.copy(e,t),this.iesMap=e.iesMap,this}}class yR extends oc{constructor(e,t,n,i,r,s){super(e,t,n,i,r,s),this.aspect=null}copy(e,t){return super.copy(e,t),this.aspect=e.aspect,this}}class bR extends AI{constructor(){super(),this.addMaterial(ST,"MeshPhongMaterial"),this.addMaterial(pP,"MeshStandardMaterial"),this.addMaterial(mP,"MeshPhysicalMaterial"),this.addMaterial(yP,"MeshToonMaterial"),this.addMaterial(AT,"MeshBasicMaterial"),this.addMaterial(ET,"MeshLambertMaterial"),this.addMaterial(sT,"MeshNormalMaterial"),this.addMaterial(CP,"MeshMatcapMaterial"),this.addMaterial(eT,"LineBasicMaterial"),this.addMaterial(nT,"LineDashedMaterial"),this.addMaterial(BP,"PointsMaterial"),this.addMaterial(SP,"SpriteMaterial"),this.addMaterial(jP,"ShadowMaterial"),this.addLight(oD,dc),this.addLight(VD,pc),this.addLight(YD,mc),this.addLight(JD,oc),this.addLight($D,gc),this.addLight(eI,ec),this.addLight(tI,Ac),this.addLight(KD,xR),this.addLight(_D,yR),this.addToneMapping(GN,1),this.addToneMapping(VN,2),this.addToneMapping(WN,3),this.addToneMapping(ZN,4),this.addToneMapping(qN,6),this.addToneMapping(_N,7)}}class wR extends FI{constructor(e={}){let t;e.forceWebGL?t=NL:(t=AR,e.getFallback=()=>(console.warn("THREE.WebGPURenderer: WebGPU is not available, running under WebGL2 backend."),new NL(e)));super(new t(e),e),this.library=new bR,this.isWebGPURenderer=!0,"undefined"!=typeof __THREE_DEVTOOLS__&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent("observe",{detail:this}))}}const CR={type:"change"},MR={type:"start"},ER={type:"end"},TR=1e-6,SR=-1,PR=0,NR=1,BR=2,DR=3,IR=4,LR=new Cs,jR=new Cs,OR=new Es,zR=new Es,RR=new Es,kR=new Ms,FR=new Es,HR=new Es,UR=new Es,XR=new Es;class GR extends Oc{constructor(e,t=null){super(e,t),this.screen={left:0,top:0,width:0,height:0},this.rotateSpeed=1,this.zoomSpeed=1.2,this.panSpeed=.3,this.noRotate=!1,this.noZoom=!1,this.noPan=!1,this.staticMoving=!1,this.dynamicDampingFactor=.2,this.minDistance=0,this.maxDistance=1/0,this.minZoom=0,this.maxZoom=1/0,this.keys=["KeyA","KeyS","KeyD"],this.mouseButtons={LEFT:vi,MIDDLE:Ai,RIGHT:xi},this.target=new Es,this.state=SR,this.keyState=SR,this._lastPosition=new Es,this._lastZoom=1,this._touchZoomDistanceStart=0,this._touchZoomDistanceEnd=0,this._lastAngle=0,this._eye=new Es,this._movePrev=new Cs,this._moveCurr=new Cs,this._lastAxis=new Es,this._zoomStart=new Cs,this._zoomEnd=new Cs,this._panStart=new Cs,this._panEnd=new Cs,this._pointers=[],this._pointerPositions={},this._onPointerMove=WR.bind(this),this._onPointerDown=VR.bind(this),this._onPointerUp=QR.bind(this),this._onPointerCancel=ZR.bind(this),this._onContextMenu=ek.bind(this),this._onMouseWheel=$R.bind(this),this._onKeyDown=JR.bind(this),this._onKeyUp=YR.bind(this),this._onTouchStart=tk.bind(this),this._onTouchMove=nk.bind(this),this._onTouchEnd=ik.bind(this),this._onMouseDown=KR.bind(this),this._onMouseMove=qR.bind(this),this._onMouseUp=_R.bind(this),this._target0=this.target.clone(),this._position0=this.object.position.clone(),this._up0=this.object.up.clone(),this._zoom0=this.object.zoom,null!==t&&(this.connect(t),this.handleResize()),this.update()}connect(e){super.connect(e),window.addEventListener("keydown",this._onKeyDown),window.addEventListener("keyup",this._onKeyUp),this.domElement.addEventListener("pointerdown",this._onPointerDown),this.domElement.addEventListener("pointercancel",this._onPointerCancel),this.domElement.addEventListener("wheel",this._onMouseWheel,{passive:!1}),this.domElement.addEventListener("contextmenu",this._onContextMenu),this.domElement.style.touchAction="none"}disconnect(){window.removeEventListener("keydown",this._onKeyDown),window.removeEventListener("keyup",this._onKeyUp),this.domElement.removeEventListener("pointerdown",this._onPointerDown),this.domElement.removeEventListener("pointermove",this._onPointerMove),this.domElement.removeEventListener("pointerup",this._onPointerUp),this.domElement.removeEventListener("pointercancel",this._onPointerCancel),this.domElement.removeEventListener("wheel",this._onMouseWheel),this.domElement.removeEventListener("contextmenu",this._onContextMenu),this.domElement.style.touchAction="auto"}dispose(){this.disconnect()}handleResize(){const e=this.domElement.getBoundingClientRect(),t=this.domElement.ownerDocument.documentElement;this.screen.left=e.left+window.pageXOffset-t.clientLeft,this.screen.top=e.top+window.pageYOffset-t.clientTop,this.screen.width=e.width,this.screen.height=e.height}update(){this._eye.subVectors(this.object.position,this.target),this.noRotate||this._rotateCamera(),this.noZoom||this._zoomCamera(),this.noPan||this._panCamera(),this.object.position.addVectors(this.target,this._eye),this.object.isPerspectiveCamera?(this._checkDistances(),this.object.lookAt(this.target),this._lastPosition.distanceToSquared(this.object.position)>TR&&(this.dispatchEvent(CR),this._lastPosition.copy(this.object.position))):this.object.isOrthographicCamera?(this.object.lookAt(this.target),(this._lastPosition.distanceToSquared(this.object.position)>TR||this._lastZoom!==this.object.zoom)&&(this.dispatchEvent(CR),this._lastPosition.copy(this.object.position),this._lastZoom=this.object.zoom)):console.warn("THREE.TrackballControls: Unsupported camera type.")}reset(){this.state=SR,this.keyState=SR,this.target.copy(this._target0),this.object.position.copy(this._position0),this.object.up.copy(this._up0),this.object.zoom=this._zoom0,this.object.updateProjectionMatrix(),this._eye.subVectors(this.object.position,this.target),this.object.lookAt(this.target),this.dispatchEvent(CR),this._lastPosition.copy(this.object.position),this._lastZoom=this.object.zoom}_panCamera(){if(jR.copy(this._panEnd).sub(this._panStart),jR.lengthSq()){if(this.object.isOrthographicCamera){const e=(this.object.right-this.object.left)/this.object.zoom/this.domElement.clientWidth,t=(this.object.top-this.object.bottom)/this.object.zoom/this.domElement.clientWidth;jR.x*=e,jR.y*=t}jR.multiplyScalar(this._eye.length()*this.panSpeed),zR.copy(this._eye).cross(this.object.up).setLength(jR.x),zR.add(OR.copy(this.object.up).setLength(jR.y)),this.object.position.add(zR),this.target.add(zR),this.staticMoving?this._panStart.copy(this._panEnd):this._panStart.add(jR.subVectors(this._panEnd,this._panStart).multiplyScalar(this.dynamicDampingFactor))}}_rotateCamera(){XR.set(this._moveCurr.x-this._movePrev.x,this._moveCurr.y-this._movePrev.y,0);let e=XR.length();e?(this._eye.copy(this.object.position).sub(this.target),FR.copy(this._eye).normalize(),HR.copy(this.object.up).normalize(),UR.crossVectors(HR,FR).normalize(),HR.setLength(this._moveCurr.y-this._movePrev.y),UR.setLength(this._moveCurr.x-this._movePrev.x),XR.copy(HR.add(UR)),RR.crossVectors(XR,this._eye).normalize(),e*=this.rotateSpeed,kR.setFromAxisAngle(RR,e),this._eye.applyQuaternion(kR),this.object.up.applyQuaternion(kR),this._lastAxis.copy(RR),this._lastAngle=e):!this.staticMoving&&this._lastAngle&&(this._lastAngle*=Math.sqrt(1-this.dynamicDampingFactor),this._eye.copy(this.object.position).sub(this.target),kR.setFromAxisAngle(this._lastAxis,this._lastAngle),this._eye.applyQuaternion(kR),this.object.up.applyQuaternion(kR)),this._movePrev.copy(this._moveCurr)}_zoomCamera(){let e;this.state===IR?(e=this._touchZoomDistanceStart/this._touchZoomDistanceEnd,this._touchZoomDistanceStart=this._touchZoomDistanceEnd,this.object.isPerspectiveCamera?this._eye.multiplyScalar(e):this.object.isOrthographicCamera?(this.object.zoom=ws.clamp(this.object.zoom/e,this.minZoom,this.maxZoom),this._lastZoom!==this.object.zoom&&this.object.updateProjectionMatrix()):console.warn("THREE.TrackballControls: Unsupported camera type")):(e=1+(this._zoomEnd.y-this._zoomStart.y)*this.zoomSpeed,1!==e&&e>0&&(this.object.isPerspectiveCamera?this._eye.multiplyScalar(e):this.object.isOrthographicCamera?(this.object.zoom=ws.clamp(this.object.zoom/e,this.minZoom,this.maxZoom),this._lastZoom!==this.object.zoom&&this.object.updateProjectionMatrix()):console.warn("THREE.TrackballControls: Unsupported camera type")),this.staticMoving?this._zoomStart.copy(this._zoomEnd):this._zoomStart.y+=(this._zoomEnd.y-this._zoomStart.y)*this.dynamicDampingFactor)}_getMouseOnScreen(e,t){return LR.set((e-this.screen.left)/this.screen.width,(t-this.screen.top)/this.screen.height),LR}_getMouseOnCircle(e,t){return LR.set((e-.5*this.screen.width-this.screen.left)/(.5*this.screen.width),(this.screen.height+2*(this.screen.top-t))/this.screen.width),LR}_addPointer(e){this._pointers.push(e)}_removePointer(e){delete this._pointerPositions[e.pointerId];for(let t=0;t<this._pointers.length;t++)if(this._pointers[t].pointerId==e.pointerId)return void this._pointers.splice(t,1)}_trackPointer(e){let t=this._pointerPositions[e.pointerId];void 0===t&&(t=new Cs,this._pointerPositions[e.pointerId]=t),t.set(e.pageX,e.pageY)}_getSecondPointerPosition(e){const t=e.pointerId===this._pointers[0].pointerId?this._pointers[1]:this._pointers[0];return this._pointerPositions[t.pointerId]}_checkDistances(){this.noZoom&&this.noPan||(this._eye.lengthSq()>this.maxDistance*this.maxDistance&&(this.object.position.addVectors(this.target,this._eye.setLength(this.maxDistance)),this._zoomStart.copy(this._zoomEnd)),this._eye.lengthSq()<this.minDistance*this.minDistance&&(this.object.position.addVectors(this.target,this._eye.setLength(this.minDistance)),this._zoomStart.copy(this._zoomEnd)))}}function VR(e){!1!==this.enabled&&(0===this._pointers.length&&(this.domElement.setPointerCapture(e.pointerId),this.domElement.addEventListener("pointermove",this._onPointerMove),this.domElement.addEventListener("pointerup",this._onPointerUp)),this._addPointer(e),"touch"===e.pointerType?this._onTouchStart(e):this._onMouseDown(e))}function WR(e){!1!==this.enabled&&("touch"===e.pointerType?this._onTouchMove(e):this._onMouseMove(e))}function QR(e){!1!==this.enabled&&("touch"===e.pointerType?this._onTouchEnd(e):this._onMouseUp(),this._removePointer(e),0===this._pointers.length&&(this.domElement.releasePointerCapture(e.pointerId),this.domElement.removeEventListener("pointermove",this._onPointerMove),this.domElement.removeEventListener("pointerup",this._onPointerUp)))}function ZR(e){this._removePointer(e)}function YR(){!1!==this.enabled&&(this.keyState=SR,window.addEventListener("keydown",this._onKeyDown))}function JR(e){!1!==this.enabled&&(window.removeEventListener("keydown",this._onKeyDown),this.keyState===SR&&(e.code!==this.keys[PR]||this.noRotate?e.code!==this.keys[NR]||this.noZoom?e.code!==this.keys[BR]||this.noPan||(this.keyState=BR):this.keyState=NR:this.keyState=PR))}function KR(e){let t;switch(e.button){case 0:t=this.mouseButtons.LEFT;break;case 1:t=this.mouseButtons.MIDDLE;break;case 2:t=this.mouseButtons.RIGHT;break;default:t=-1}switch(t){case Ai:this.state=NR;break;case vi:this.state=PR;break;case xi:this.state=BR;break;default:this.state=SR}const n=this.keyState!==SR?this.keyState:this.state;n!==PR||this.noRotate?n!==NR||this.noZoom?n!==BR||this.noPan||(this._panStart.copy(this._getMouseOnScreen(e.pageX,e.pageY)),this._panEnd.copy(this._panStart)):(this._zoomStart.copy(this._getMouseOnScreen(e.pageX,e.pageY)),this._zoomEnd.copy(this._zoomStart)):(this._moveCurr.copy(this._getMouseOnCircle(e.pageX,e.pageY)),this._movePrev.copy(this._moveCurr)),this.dispatchEvent(MR)}function qR(e){const t=this.keyState!==SR?this.keyState:this.state;t!==PR||this.noRotate?t!==NR||this.noZoom?t!==BR||this.noPan||this._panEnd.copy(this._getMouseOnScreen(e.pageX,e.pageY)):this._zoomEnd.copy(this._getMouseOnScreen(e.pageX,e.pageY)):(this._movePrev.copy(this._moveCurr),this._moveCurr.copy(this._getMouseOnCircle(e.pageX,e.pageY)))}function _R(){this.state=SR,this.dispatchEvent(ER)}function $R(e){if(!1!==this.enabled&&!0!==this.noZoom){switch(e.preventDefault(),e.deltaMode){case 2:this._zoomStart.y-=.025*e.deltaY;break;case 1:this._zoomStart.y-=.01*e.deltaY;break;default:this._zoomStart.y-=25e-5*e.deltaY}this.dispatchEvent(MR),this.dispatchEvent(ER)}}function ek(e){!1!==this.enabled&&e.preventDefault()}function tk(e){if(this._trackPointer(e),1===this._pointers.length)this.state=DR,this._moveCurr.copy(this._getMouseOnCircle(this._pointers[0].pageX,this._pointers[0].pageY)),this._movePrev.copy(this._moveCurr);else{this.state=IR;const e=this._pointers[0].pageX-this._pointers[1].pageX,t=this._pointers[0].pageY-this._pointers[1].pageY;this._touchZoomDistanceEnd=this._touchZoomDistanceStart=Math.sqrt(e*e+t*t);const n=(this._pointers[0].pageX+this._pointers[1].pageX)/2,i=(this._pointers[0].pageY+this._pointers[1].pageY)/2;this._panStart.copy(this._getMouseOnScreen(n,i)),this._panEnd.copy(this._panStart)}this.dispatchEvent(MR)}function nk(e){if(this._trackPointer(e),1===this._pointers.length)this._movePrev.copy(this._moveCurr),this._moveCurr.copy(this._getMouseOnCircle(e.pageX,e.pageY));else{const t=this._getSecondPointerPosition(e),n=e.pageX-t.x,i=e.pageY-t.y;this._touchZoomDistanceEnd=Math.sqrt(n*n+i*i);const r=(e.pageX+t.x)/2,s=(e.pageY+t.y)/2;this._panEnd.copy(this._getMouseOnScreen(r,s))}}function ik(e){switch(this._pointers.length){case 0:this.state=SR;break;case 1:this.state=DR,this._moveCurr.copy(this._getMouseOnCircle(e.pageX,e.pageY)),this._movePrev.copy(this._moveCurr);break;case 2:this.state=IR;for(let t=0;t<this._pointers.length;t++)if(this._pointers[t].pointerId!==e.pointerId){const e=this._pointerPositions[this._pointers[t].pointerId];this._moveCurr.copy(this._getMouseOnCircle(e.x,e.y)),this._movePrev.copy(this._moveCurr);break}}this.dispatchEvent(ER)}const rk={type:"change"},sk={type:"start"},ok={type:"end"},ak=new So,lk=new Il,uk=Math.cos(70*ws.DEG2RAD),ck=new Es,dk=2*Math.PI,hk=-1,fk=0,pk=1,gk=2,mk=3,vk=4,Ak=5,xk=6,yk=1e-6;class bk extends Oc{constructor(e,t=null){super(e,t),this.state=hk,this.target=new Es,this.cursor=new Es,this.minDistance=0,this.maxDistance=1/0,this.minZoom=0,this.maxZoom=1/0,this.minTargetRadius=0,this.maxTargetRadius=1/0,this.minPolarAngle=0,this.maxPolarAngle=Math.PI,this.minAzimuthAngle=-1/0,this.maxAzimuthAngle=1/0,this.enableDamping=!1,this.dampingFactor=.05,this.enableZoom=!0,this.zoomSpeed=1,this.enableRotate=!0,this.rotateSpeed=1,this.keyRotateSpeed=1,this.enablePan=!0,this.panSpeed=1,this.screenSpacePanning=!0,this.keyPanSpeed=7,this.zoomToCursor=!1,this.autoRotate=!1,this.autoRotateSpeed=2,this.keys={LEFT:"ArrowLeft",UP:"ArrowUp",RIGHT:"ArrowRight",BOTTOM:"ArrowDown"},this.mouseButtons={LEFT:vi,MIDDLE:Ai,RIGHT:xi},this.touches={ONE:yi,TWO:wi},this.target0=this.target.clone(),this.position0=this.object.position.clone(),this.zoom0=this.object.zoom,this._domElementKeyEvents=null,this._lastPosition=new Es,this._lastQuaternion=new Ms,this._lastTargetPosition=new Es,this._quat=(new Ms).setFromUnitVectors(e.up,new Es(0,1,0)),this._quatInverse=this._quat.clone().invert(),this._spherical=new Lc,this._sphericalDelta=new Lc,this._scale=1,this._panOffset=new Es,this._rotateStart=new Cs,this._rotateEnd=new Cs,this._rotateDelta=new Cs,this._panStart=new Cs,this._panEnd=new Cs,this._panDelta=new Cs,this._dollyStart=new Cs,this._dollyEnd=new Cs,this._dollyDelta=new Cs,this._dollyDirection=new Es,this._mouse=new Cs,this._performCursorZoom=!1,this._pointers=[],this._pointerPositions={},this._controlActive=!1,this._onPointerMove=Ck.bind(this),this._onPointerDown=wk.bind(this),this._onPointerUp=Mk.bind(this),this._onContextMenu=Dk.bind(this),this._onMouseWheel=Sk.bind(this),this._onKeyDown=Pk.bind(this),this._onTouchStart=Nk.bind(this),this._onTouchMove=Bk.bind(this),this._onMouseDown=Ek.bind(this),this._onMouseMove=Tk.bind(this),this._interceptControlDown=Ik.bind(this),this._interceptControlUp=Lk.bind(this),null!==this.domElement&&this.connect(this.domElement),this.update()}connect(e){super.connect(e),this.domElement.addEventListener("pointerdown",this._onPointerDown),this.domElement.addEventListener("pointercancel",this._onPointerUp),this.domElement.addEventListener("contextmenu",this._onContextMenu),this.domElement.addEventListener("wheel",this._onMouseWheel,{passive:!1});this.domElement.getRootNode().addEventListener("keydown",this._interceptControlDown,{passive:!0,capture:!0}),this.domElement.style.touchAction="none"}disconnect(){this.domElement.removeEventListener("pointerdown",this._onPointerDown),this.domElement.removeEventListener("pointermove",this._onPointerMove),this.domElement.removeEventListener("pointerup",this._onPointerUp),this.domElement.removeEventListener("pointercancel",this._onPointerUp),this.domElement.removeEventListener("wheel",this._onMouseWheel),this.domElement.removeEventListener("contextmenu",this._onContextMenu),this.stopListenToKeyEvents();this.domElement.getRootNode().removeEventListener("keydown",this._interceptControlDown,{capture:!0}),this.domElement.style.touchAction="auto"}dispose(){this.disconnect()}getPolarAngle(){return this._spherical.phi}getAzimuthalAngle(){return this._spherical.theta}getDistance(){return this.object.position.distanceTo(this.target)}listenToKeyEvents(e){e.addEventListener("keydown",this._onKeyDown),this._domElementKeyEvents=e}stopListenToKeyEvents(){null!==this._domElementKeyEvents&&(this._domElementKeyEvents.removeEventListener("keydown",this._onKeyDown),this._domElementKeyEvents=null)}saveState(){this.target0.copy(this.target),this.position0.copy(this.object.position),this.zoom0=this.object.zoom}reset(){this.target.copy(this.target0),this.object.position.copy(this.position0),this.object.zoom=this.zoom0,this.object.updateProjectionMatrix(),this.dispatchEvent(rk),this.update(),this.state=hk}update(e=null){const t=this.object.position;ck.copy(t).sub(this.target),ck.applyQuaternion(this._quat),this._spherical.setFromVector3(ck),this.autoRotate&&this.state===hk&&this._rotateLeft(this._getAutoRotationAngle(e)),this.enableDamping?(this._spherical.theta+=this._sphericalDelta.theta*this.dampingFactor,this._spherical.phi+=this._sphericalDelta.phi*this.dampingFactor):(this._spherical.theta+=this._sphericalDelta.theta,this._spherical.phi+=this._sphericalDelta.phi);let n=this.minAzimuthAngle,i=this.maxAzimuthAngle;isFinite(n)&&isFinite(i)&&(n<-Math.PI?n+=dk:n>Math.PI&&(n-=dk),i<-Math.PI?i+=dk:i>Math.PI&&(i-=dk),this._spherical.theta=n<=i?Math.max(n,Math.min(i,this._spherical.theta)):this._spherical.theta>(n+i)/2?Math.max(n,this._spherical.theta):Math.min(i,this._spherical.theta)),this._spherical.phi=Math.max(this.minPolarAngle,Math.min(this.maxPolarAngle,this._spherical.phi)),this._spherical.makeSafe(),!0===this.enableDamping?this.target.addScaledVector(this._panOffset,this.dampingFactor):this.target.add(this._panOffset),this.target.sub(this.cursor),this.target.clampLength(this.minTargetRadius,this.maxTargetRadius),this.target.add(this.cursor);let r=!1;if(this.zoomToCursor&&this._performCursorZoom||this.object.isOrthographicCamera)this._spherical.radius=this._clampDistance(this._spherical.radius);else{const e=this._spherical.radius;this._spherical.radius=this._clampDistance(this._spherical.radius*this._scale),r=e!=this._spherical.radius}if(ck.setFromSpherical(this._spherical),ck.applyQuaternion(this._quatInverse),t.copy(this.target).add(ck),this.object.lookAt(this.target),!0===this.enableDamping?(this._sphericalDelta.theta*=1-this.dampingFactor,this._sphericalDelta.phi*=1-this.dampingFactor,this._panOffset.multiplyScalar(1-this.dampingFactor)):(this._sphericalDelta.set(0,0,0),this._panOffset.set(0,0,0)),this.zoomToCursor&&this._performCursorZoom){let e=null;if(this.object.isPerspectiveCamera){const t=ck.length();e=this._clampDistance(t*this._scale);const n=t-e;this.object.position.addScaledVector(this._dollyDirection,n),this.object.updateMatrixWorld(),r=!!n}else if(this.object.isOrthographicCamera){const t=new Es(this._mouse.x,this._mouse.y,0);t.unproject(this.object);const n=this.object.zoom;this.object.zoom=Math.max(this.minZoom,Math.min(this.maxZoom,this.object.zoom/this._scale)),this.object.updateProjectionMatrix(),r=n!==this.object.zoom;const i=new Es(this._mouse.x,this._mouse.y,0);i.unproject(this.object),this.object.position.sub(i).add(t),this.object.updateMatrixWorld(),e=ck.length()}else console.warn("WARNING: OrbitControls.js encountered an unknown camera type - zoom to cursor disabled."),this.zoomToCursor=!1;null!==e&&(this.screenSpacePanning?this.target.set(0,0,-1).transformDirection(this.object.matrix).multiplyScalar(e).add(this.object.position):(ak.origin.copy(this.object.position),ak.direction.set(0,0,-1).transformDirection(this.object.matrix),Math.abs(this.object.up.dot(ak.direction))<uk?this.object.lookAt(this.target):(lk.setFromNormalAndCoplanarPoint(this.object.up,this.target),ak.intersectPlane(lk,this.target))))}else if(this.object.isOrthographicCamera){const e=this.object.zoom;this.object.zoom=Math.max(this.minZoom,Math.min(this.maxZoom,this.object.zoom/this._scale)),e!==this.object.zoom&&(this.object.updateProjectionMatrix(),r=!0)}return this._scale=1,this._performCursorZoom=!1,!!(r||this._lastPosition.distanceToSquared(this.object.position)>yk||8*(1-this._lastQuaternion.dot(this.object.quaternion))>yk||this._lastTargetPosition.distanceToSquared(this.target)>yk)&&(this.dispatchEvent(rk),this._lastPosition.copy(this.object.position),this._lastQuaternion.copy(this.object.quaternion),this._lastTargetPosition.copy(this.target),!0)}_getAutoRotationAngle(e){return null!==e?dk/60*this.autoRotateSpeed*e:dk/60/60*this.autoRotateSpeed}_getZoomScale(e){const t=Math.abs(.01*e);return Math.pow(.95,this.zoomSpeed*t)}_rotateLeft(e){this._sphericalDelta.theta-=e}_rotateUp(e){this._sphericalDelta.phi-=e}_panLeft(e,t){ck.setFromMatrixColumn(t,0),ck.multiplyScalar(-e),this._panOffset.add(ck)}_panUp(e,t){!0===this.screenSpacePanning?ck.setFromMatrixColumn(t,1):(ck.setFromMatrixColumn(t,0),ck.crossVectors(this.object.up,ck)),ck.multiplyScalar(e),this._panOffset.add(ck)}_pan(e,t){const n=this.domElement;if(this.object.isPerspectiveCamera){const i=this.object.position;ck.copy(i).sub(this.target);let r=ck.length();r*=Math.tan(this.object.fov/2*Math.PI/180),this._panLeft(2*e*r/n.clientHeight,this.object.matrix),this._panUp(2*t*r/n.clientHeight,this.object.matrix)}else this.object.isOrthographicCamera?(this._panLeft(e*(this.object.right-this.object.left)/this.object.zoom/n.clientWidth,this.object.matrix),this._panUp(t*(this.object.top-this.object.bottom)/this.object.zoom/n.clientHeight,this.object.matrix)):(console.warn("WARNING: OrbitControls.js encountered an unknown camera type - pan disabled."),this.enablePan=!1)}_dollyOut(e){this.object.isPerspectiveCamera||this.object.isOrthographicCamera?this._scale/=e:(console.warn("WARNING: OrbitControls.js encountered an unknown camera type - dolly/zoom disabled."),this.enableZoom=!1)}_dollyIn(e){this.object.isPerspectiveCamera||this.object.isOrthographicCamera?this._scale*=e:(console.warn("WARNING: OrbitControls.js encountered an unknown camera type - dolly/zoom disabled."),this.enableZoom=!1)}_updateZoomParameters(e,t){if(!this.zoomToCursor)return;this._performCursorZoom=!0;const n=this.domElement.getBoundingClientRect(),i=e-n.left,r=t-n.top,s=n.width,o=n.height;this._mouse.x=i/s*2-1,this._mouse.y=-r/o*2+1,this._dollyDirection.set(this._mouse.x,this._mouse.y,1).unproject(this.object).sub(this.object.position).normalize()}_clampDistance(e){return Math.max(this.minDistance,Math.min(this.maxDistance,e))}_handleMouseDownRotate(e){this._rotateStart.set(e.clientX,e.clientY)}_handleMouseDownDolly(e){this._updateZoomParameters(e.clientX,e.clientX),this._dollyStart.set(e.clientX,e.clientY)}_handleMouseDownPan(e){this._panStart.set(e.clientX,e.clientY)}_handleMouseMoveRotate(e){this._rotateEnd.set(e.clientX,e.clientY),this._rotateDelta.subVectors(this._rotateEnd,this._rotateStart).multiplyScalar(this.rotateSpeed);const t=this.domElement;this._rotateLeft(dk*this._rotateDelta.x/t.clientHeight),this._rotateUp(dk*this._rotateDelta.y/t.clientHeight),this._rotateStart.copy(this._rotateEnd),this.update()}_handleMouseMoveDolly(e){this._dollyEnd.set(e.clientX,e.clientY),this._dollyDelta.subVectors(this._dollyEnd,this._dollyStart),this._dollyDelta.y>0?this._dollyOut(this._getZoomScale(this._dollyDelta.y)):this._dollyDelta.y<0&&this._dollyIn(this._getZoomScale(this._dollyDelta.y)),this._dollyStart.copy(this._dollyEnd),this.update()}_handleMouseMovePan(e){this._panEnd.set(e.clientX,e.clientY),this._panDelta.subVectors(this._panEnd,this._panStart).multiplyScalar(this.panSpeed),this._pan(this._panDelta.x,this._panDelta.y),this._panStart.copy(this._panEnd),this.update()}_handleMouseWheel(e){this._updateZoomParameters(e.clientX,e.clientY),e.deltaY<0?this._dollyIn(this._getZoomScale(e.deltaY)):e.deltaY>0&&this._dollyOut(this._getZoomScale(e.deltaY)),this.update()}_handleKeyDown(e){let t=!1;switch(e.code){case this.keys.UP:e.ctrlKey||e.metaKey||e.shiftKey?this.enableRotate&&this._rotateUp(dk*this.keyRotateSpeed/this.domElement.clientHeight):this.enablePan&&this._pan(0,this.keyPanSpeed),t=!0;break;case this.keys.BOTTOM:e.ctrlKey||e.metaKey||e.shiftKey?this.enableRotate&&this._rotateUp(-dk*this.keyRotateSpeed/this.domElement.clientHeight):this.enablePan&&this._pan(0,-this.keyPanSpeed),t=!0;break;case this.keys.LEFT:e.ctrlKey||e.metaKey||e.shiftKey?this.enableRotate&&this._rotateLeft(dk*this.keyRotateSpeed/this.domElement.clientHeight):this.enablePan&&this._pan(this.keyPanSpeed,0),t=!0;break;case this.keys.RIGHT:e.ctrlKey||e.metaKey||e.shiftKey?this.enableRotate&&this._rotateLeft(-dk*this.keyRotateSpeed/this.domElement.clientHeight):this.enablePan&&this._pan(-this.keyPanSpeed,0),t=!0}t&&(e.preventDefault(),this.update())}_handleTouchStartRotate(e){if(1===this._pointers.length)this._rotateStart.set(e.pageX,e.pageY);else{const t=this._getSecondPointerPosition(e),n=.5*(e.pageX+t.x),i=.5*(e.pageY+t.y);this._rotateStart.set(n,i)}}_handleTouchStartPan(e){if(1===this._pointers.length)this._panStart.set(e.pageX,e.pageY);else{const t=this._getSecondPointerPosition(e),n=.5*(e.pageX+t.x),i=.5*(e.pageY+t.y);this._panStart.set(n,i)}}_handleTouchStartDolly(e){const t=this._getSecondPointerPosition(e),n=e.pageX-t.x,i=e.pageY-t.y,r=Math.sqrt(n*n+i*i);this._dollyStart.set(0,r)}_handleTouchStartDollyPan(e){this.enableZoom&&this._handleTouchStartDolly(e),this.enablePan&&this._handleTouchStartPan(e)}_handleTouchStartDollyRotate(e){this.enableZoom&&this._handleTouchStartDolly(e),this.enableRotate&&this._handleTouchStartRotate(e)}_handleTouchMoveRotate(e){if(1==this._pointers.length)this._rotateEnd.set(e.pageX,e.pageY);else{const t=this._getSecondPointerPosition(e),n=.5*(e.pageX+t.x),i=.5*(e.pageY+t.y);this._rotateEnd.set(n,i)}this._rotateDelta.subVectors(this._rotateEnd,this._rotateStart).multiplyScalar(this.rotateSpeed);const t=this.domElement;this._rotateLeft(dk*this._rotateDelta.x/t.clientHeight),this._rotateUp(dk*this._rotateDelta.y/t.clientHeight),this._rotateStart.copy(this._rotateEnd)}_handleTouchMovePan(e){if(1===this._pointers.length)this._panEnd.set(e.pageX,e.pageY);else{const t=this._getSecondPointerPosition(e),n=.5*(e.pageX+t.x),i=.5*(e.pageY+t.y);this._panEnd.set(n,i)}this._panDelta.subVectors(this._panEnd,this._panStart).multiplyScalar(this.panSpeed),this._pan(this._panDelta.x,this._panDelta.y),this._panStart.copy(this._panEnd)}_handleTouchMoveDolly(e){const t=this._getSecondPointerPosition(e),n=e.pageX-t.x,i=e.pageY-t.y,r=Math.sqrt(n*n+i*i);this._dollyEnd.set(0,r),this._dollyDelta.set(0,Math.pow(this._dollyEnd.y/this._dollyStart.y,this.zoomSpeed)),this._dollyOut(this._dollyDelta.y),this._dollyStart.copy(this._dollyEnd);const s=.5*(e.pageX+t.x),o=.5*(e.pageY+t.y);this._updateZoomParameters(s,o)}_handleTouchMoveDollyPan(e){this.enableZoom&&this._handleTouchMoveDolly(e),this.enablePan&&this._handleTouchMovePan(e)}_handleTouchMoveDollyRotate(e){this.enableZoom&&this._handleTouchMoveDolly(e),this.enableRotate&&this._handleTouchMoveRotate(e)}_addPointer(e){this._pointers.push(e.pointerId)}_removePointer(e){delete this._pointerPositions[e.pointerId];for(let t=0;t<this._pointers.length;t++)if(this._pointers[t]==e.pointerId)return void this._pointers.splice(t,1)}_isTrackingPointer(e){for(let t=0;t<this._pointers.length;t++)if(this._pointers[t]==e.pointerId)return!0;return!1}_trackPointer(e){let t=this._pointerPositions[e.pointerId];void 0===t&&(t=new Cs,this._pointerPositions[e.pointerId]=t),t.set(e.pageX,e.pageY)}_getSecondPointerPosition(e){const t=e.pointerId===this._pointers[0]?this._pointers[1]:this._pointers[0];return this._pointerPositions[t]}_customWheelEvent(e){const t=e.deltaMode,n={clientX:e.clientX,clientY:e.clientY,deltaY:e.deltaY};switch(t){case 1:n.deltaY*=16;break;case 2:n.deltaY*=100}return e.ctrlKey&&!this._controlActive&&(n.deltaY*=10),n}}function wk(e){!1!==this.enabled&&(0===this._pointers.length&&(this.domElement.setPointerCapture(e.pointerId),this.domElement.addEventListener("pointermove",this._onPointerMove),this.domElement.addEventListener("pointerup",this._onPointerUp)),this._isTrackingPointer(e)||(this._addPointer(e),"touch"===e.pointerType?this._onTouchStart(e):this._onMouseDown(e)))}function Ck(e){!1!==this.enabled&&("touch"===e.pointerType?this._onTouchMove(e):this._onMouseMove(e))}function Mk(e){switch(this._removePointer(e),this._pointers.length){case 0:this.domElement.releasePointerCapture(e.pointerId),this.domElement.removeEventListener("pointermove",this._onPointerMove),this.domElement.removeEventListener("pointerup",this._onPointerUp),this.dispatchEvent(ok),this.state=hk;break;case 1:const t=this._pointers[0],n=this._pointerPositions[t];this._onTouchStart({pointerId:t,pageX:n.x,pageY:n.y})}}function Ek(e){let t;switch(e.button){case 0:t=this.mouseButtons.LEFT;break;case 1:t=this.mouseButtons.MIDDLE;break;case 2:t=this.mouseButtons.RIGHT;break;default:t=-1}switch(t){case Ai:if(!1===this.enableZoom)return;this._handleMouseDownDolly(e),this.state=pk;break;case vi:if(e.ctrlKey||e.metaKey||e.shiftKey){if(!1===this.enablePan)return;this._handleMouseDownPan(e),this.state=gk}else{if(!1===this.enableRotate)return;this._handleMouseDownRotate(e),this.state=fk}break;case xi:if(e.ctrlKey||e.metaKey||e.shiftKey){if(!1===this.enableRotate)return;this._handleMouseDownRotate(e),this.state=fk}else{if(!1===this.enablePan)return;this._handleMouseDownPan(e),this.state=gk}break;default:this.state=hk}this.state!==hk&&this.dispatchEvent(sk)}function Tk(e){switch(this.state){case fk:if(!1===this.enableRotate)return;this._handleMouseMoveRotate(e);break;case pk:if(!1===this.enableZoom)return;this._handleMouseMoveDolly(e);break;case gk:if(!1===this.enablePan)return;this._handleMouseMovePan(e)}}function Sk(e){!1!==this.enabled&&!1!==this.enableZoom&&this.state===hk&&(e.preventDefault(),this.dispatchEvent(sk),this._handleMouseWheel(this._customWheelEvent(e)),this.dispatchEvent(ok))}function Pk(e){!1!==this.enabled&&this._handleKeyDown(e)}function Nk(e){switch(this._trackPointer(e),this._pointers.length){case 1:switch(this.touches.ONE){case yi:if(!1===this.enableRotate)return;this._handleTouchStartRotate(e),this.state=mk;break;case bi:if(!1===this.enablePan)return;this._handleTouchStartPan(e),this.state=vk;break;default:this.state=hk}break;case 2:switch(this.touches.TWO){case wi:if(!1===this.enableZoom&&!1===this.enablePan)return;this._handleTouchStartDollyPan(e),this.state=Ak;break;case Ci:if(!1===this.enableZoom&&!1===this.enableRotate)return;this._handleTouchStartDollyRotate(e),this.state=xk;break;default:this.state=hk}break;default:this.state=hk}this.state!==hk&&this.dispatchEvent(sk)}function Bk(e){switch(this._trackPointer(e),this.state){case mk:if(!1===this.enableRotate)return;this._handleTouchMoveRotate(e),this.update();break;case vk:if(!1===this.enablePan)return;this._handleTouchMovePan(e),this.update();break;case Ak:if(!1===this.enableZoom&&!1===this.enablePan)return;this._handleTouchMoveDollyPan(e),this.update();break;case xk:if(!1===this.enableZoom&&!1===this.enableRotate)return;this._handleTouchMoveDollyRotate(e),this.update();break;default:this.state=hk}}function Dk(e){!1!==this.enabled&&e.preventDefault()}function Ik(e){if("Control"===e.key){this._controlActive=!0;this.domElement.getRootNode().addEventListener("keyup",this._interceptControlUp,{passive:!0,capture:!0})}}function Lk(e){if("Control"===e.key){this._controlActive=!1;this.domElement.getRootNode().removeEventListener("keyup",this._interceptControlUp,{passive:!0,capture:!0})}}const jk={type:"change"},Ok=1e-6,zk=new Ms;class Rk extends Oc{constructor(e,t=null){super(e,t),this.movementSpeed=1,this.rollSpeed=.005,this.dragToLook=!1,this.autoForward=!1,this._moveState={up:0,down:0,left:0,right:0,forward:0,back:0,pitchUp:0,pitchDown:0,yawLeft:0,yawRight:0,rollLeft:0,rollRight:0},this._moveVector=new Es(0,0,0),this._rotationVector=new Es(0,0,0),this._lastQuaternion=new Ms,this._lastPosition=new Es,this._status=0,this._onKeyDown=kk.bind(this),this._onKeyUp=Fk.bind(this),this._onPointerMove=Uk.bind(this),this._onPointerDown=Hk.bind(this),this._onPointerUp=Xk.bind(this),this._onPointerCancel=Gk.bind(this),this._onContextMenu=Vk.bind(this),null!==t&&this.connect(t)}connect(e){super.connect(e),window.addEventListener("keydown",this._onKeyDown),window.addEventListener("keyup",this._onKeyUp),this.domElement.addEventListener("pointermove",this._onPointerMove),this.domElement.addEventListener("pointerdown",this._onPointerDown),this.domElement.addEventListener("pointerup",this._onPointerUp),this.domElement.addEventListener("pointercancel",this._onPointerCancel),this.domElement.addEventListener("contextmenu",this._onContextMenu)}disconnect(){window.removeEventListener("keydown",this._onKeyDown),window.removeEventListener("keyup",this._onKeyUp),this.domElement.removeEventListener("pointermove",this._onPointerMove),this.domElement.removeEventListener("pointerdown",this._onPointerDown),this.domElement.removeEventListener("pointerup",this._onPointerUp),this.domElement.removeEventListener("pointercancel",this._onPointerCancel),this.domElement.removeEventListener("contextmenu",this._onContextMenu)}dispose(){this.disconnect()}update(e){if(!1===this.enabled)return;const t=this.object,n=e*this.movementSpeed,i=e*this.rollSpeed;t.translateX(this._moveVector.x*n),t.translateY(this._moveVector.y*n),t.translateZ(this._moveVector.z*n),zk.set(this._rotationVector.x*i,this._rotationVector.y*i,this._rotationVector.z*i,1).normalize(),t.quaternion.multiply(zk),(this._lastPosition.distanceToSquared(t.position)>Ok||8*(1-this._lastQuaternion.dot(t.quaternion))>Ok)&&(this.dispatchEvent(jk),this._lastQuaternion.copy(t.quaternion),this._lastPosition.copy(t.position))}_updateMovementVector(){const e=this._moveState.forward||this.autoForward&&!this._moveState.back?1:0;this._moveVector.x=-this._moveState.left+this._moveState.right,this._moveVector.y=-this._moveState.down+this._moveState.up,this._moveVector.z=-e+this._moveState.back}_updateRotationVector(){this._rotationVector.x=-this._moveState.pitchDown+this._moveState.pitchUp,this._rotationVector.y=-this._moveState.yawRight+this._moveState.yawLeft,this._rotationVector.z=-this._moveState.rollRight+this._moveState.rollLeft}_getContainerDimensions(){return this.domElement!=document?{size:[this.domElement.offsetWidth,this.domElement.offsetHeight],offset:[this.domElement.offsetLeft,this.domElement.offsetTop]}:{size:[window.innerWidth,window.innerHeight],offset:[0,0]}}}function kk(e){if(!e.altKey&&!1!==this.enabled){switch(e.code){case"ShiftLeft":case"ShiftRight":this.movementSpeedMultiplier=.1;break;case"KeyW":this._moveState.forward=1;break;case"KeyS":this._moveState.back=1;break;case"KeyA":this._moveState.left=1;break;case"KeyD":this._moveState.right=1;break;case"KeyR":this._moveState.up=1;break;case"KeyF":this._moveState.down=1;break;case"ArrowUp":this._moveState.pitchUp=1;break;case"ArrowDown":this._moveState.pitchDown=1;break;case"ArrowLeft":this._moveState.yawLeft=1;break;case"ArrowRight":this._moveState.yawRight=1;break;case"KeyQ":this._moveState.rollLeft=1;break;case"KeyE":this._moveState.rollRight=1}this._updateMovementVector(),this._updateRotationVector()}}function Fk(e){if(!1!==this.enabled){switch(e.code){case"ShiftLeft":case"ShiftRight":this.movementSpeedMultiplier=1;break;case"KeyW":this._moveState.forward=0;break;case"KeyS":this._moveState.back=0;break;case"KeyA":this._moveState.left=0;break;case"KeyD":this._moveState.right=0;break;case"KeyR":this._moveState.up=0;break;case"KeyF":this._moveState.down=0;break;case"ArrowUp":this._moveState.pitchUp=0;break;case"ArrowDown":this._moveState.pitchDown=0;break;case"ArrowLeft":this._moveState.yawLeft=0;break;case"ArrowRight":this._moveState.yawRight=0;break;case"KeyQ":this._moveState.rollLeft=0;break;case"KeyE":this._moveState.rollRight=0}this._updateMovementVector(),this._updateRotationVector()}}function Hk(e){if(!1!==this.enabled)if(this.dragToLook)this._status++;else{switch(e.button){case 0:this._moveState.forward=1;break;case 2:this._moveState.back=1}this._updateMovementVector()}}function Uk(e){if(!1!==this.enabled&&(!this.dragToLook||this._status>0)){const t=this._getContainerDimensions(),n=t.size[0]/2,i=t.size[1]/2;this._moveState.yawLeft=-(e.pageX-t.offset[0]-n)/n,this._moveState.pitchDown=(e.pageY-t.offset[1]-i)/i,this._updateRotationVector()}}function Xk(e){if(!1!==this.enabled){if(this.dragToLook)this._status--,this._moveState.yawLeft=this._moveState.pitchDown=0;else{switch(e.button){case 0:this._moveState.forward=0;break;case 2:this._moveState.back=0}this._updateMovementVector()}this._updateRotationVector()}}function Gk(){!1!==this.enabled&&(this.dragToLook?(this._status=0,this._moveState.yawLeft=this._moveState.pitchDown=0):(this._moveState.forward=0,this._moveState.back=0,this._updateMovementVector()),this._updateRotationVector())}function Vk(e){!1!==this.enabled&&e.preventDefault()}const Wk={name:"CopyShader",uniforms:{tDiffuse:{value:null},opacity:{value:1}},vertexShader:"\n\n\t\tvarying vec2 vUv;\n\n\t\tvoid main() {\n\n\t\t\tvUv = uv;\n\t\t\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\n\n\t\t}",fragmentShader:"\n\n\t\tuniform float opacity;\n\n\t\tuniform sampler2D tDiffuse;\n\n\t\tvarying vec2 vUv;\n\n\t\tvoid main() {\n\n\t\t\tvec4 texel = texture2D( tDiffuse, vUv );\n\t\t\tgl_FragColor = opacity * texel;\n\n\n\t\t}"};class Qk{constructor(){this.isPass=!0,this.enabled=!0,this.needsSwap=!0,this.clear=!1,this.renderToScreen=!1}setSize(){}render(){console.error("THREE.Pass: .render() must be implemented in derived pass.")}dispose(){}}const Zk=new hc(-1,1,1,-1,0,1);const Yk=new class extends Va{constructor(){super(),this.setAttribute("position",new za([-1,3,0,-1,-1,0,3,-1,0],3)),this.setAttribute("uv",new za([0,2,0,0,2,0],2))}};class Jk{constructor(e){this._mesh=new nl(Yk,e)}dispose(){this._mesh.geometry.dispose()}render(e){e.render(this._mesh,Zk)}get material(){return this._mesh.material}set material(e){this._mesh.material=e}}class Kk extends Qk{constructor(e,t="tDiffuse"){super(),this.textureID=t,this.uniforms=null,this.material=null,e instanceof ul?(this.uniforms=e.uniforms,this.material=e):e&&(this.uniforms=ll.clone(e.uniforms),this.material=new ul({name:void 0!==e.name?e.name:"unspecified",defines:Object.assign({},e.defines),uniforms:this.uniforms,vertexShader:e.vertexShader,fragmentShader:e.fragmentShader})),this._fsQuad=new Jk(this.material)}render(e,t,n){this.uniforms[this.textureID]&&(this.uniforms[this.textureID].value=n.texture),this._fsQuad.material=this.material,this.renderToScreen?(e.setRenderTarget(null),this._fsQuad.render(e)):(e.setRenderTarget(t),this.clear&&e.clear(e.autoClearColor,e.autoClearDepth,e.autoClearStencil),this._fsQuad.render(e))}dispose(){this.material.dispose(),this._fsQuad.dispose()}}class qk extends Qk{constructor(e,t){super(),this.scene=e,this.camera=t,this.clear=!0,this.needsSwap=!1,this.inverse=!1}render(e,t,n){const i=e.getContext(),r=e.state;let s,o;r.buffers.color.setMask(!1),r.buffers.depth.setMask(!1),r.buffers.color.setLocked(!0),r.buffers.depth.setLocked(!0),this.inverse?(s=0,o=1):(s=1,o=0),r.buffers.stencil.setTest(!0),r.buffers.stencil.setOp(i.REPLACE,i.REPLACE,i.REPLACE),r.buffers.stencil.setFunc(i.ALWAYS,s,4294967295),r.buffers.stencil.setClear(o),r.buffers.stencil.setLocked(!0),e.setRenderTarget(n),this.clear&&e.clear(),e.render(this.scene,this.camera),e.setRenderTarget(t),this.clear&&e.clear(),e.render(this.scene,this.camera),r.buffers.color.setLocked(!1),r.buffers.depth.setLocked(!1),r.buffers.color.setMask(!0),r.buffers.depth.setMask(!0),r.buffers.stencil.setLocked(!1),r.buffers.stencil.setFunc(i.EQUAL,1,4294967295),r.buffers.stencil.setOp(i.KEEP,i.KEEP,i.KEEP),r.buffers.stencil.setLocked(!0)}}class _k extends Qk{constructor(){super(),this.needsSwap=!1}render(e){e.state.buffers.stencil.setLocked(!1),e.state.buffers.stencil.setTest(!1)}}class $k{constructor(e,t){if(this.renderer=e,this._pixelRatio=e.getPixelRatio(),void 0===t){const n=e.getSize(new Cs);this._width=n.width,this._height=n.height,(t=new qs(this._width*this._pixelRatio,this._height*this._pixelRatio,{type:Ki})).texture.name="EffectComposer.rt1"}else this._width=t.width,this._height=t.height;this.renderTarget1=t,this.renderTarget2=t.clone(),this.renderTarget2.texture.name="EffectComposer.rt2",this.writeBuffer=this.renderTarget1,this.readBuffer=this.renderTarget2,this.renderToScreen=!0,this.passes=[],this.copyPass=new Kk(Wk),this.copyPass.material.blending=0,this.clock=new yc}swapBuffers(){const e=this.readBuffer;this.readBuffer=this.writeBuffer,this.writeBuffer=e}addPass(e){this.passes.push(e),e.setSize(this._width*this._pixelRatio,this._height*this._pixelRatio)}insertPass(e,t){this.passes.splice(t,0,e),e.setSize(this._width*this._pixelRatio,this._height*this._pixelRatio)}removePass(e){const t=this.passes.indexOf(e);-1!==t&&this.passes.splice(t,1)}isLastEnabledPass(e){for(let t=e+1;t<this.passes.length;t++)if(this.passes[t].enabled)return!1;return!0}render(e){void 0===e&&(e=this.clock.getDelta());const t=this.renderer.getRenderTarget();let n=!1;for(let t=0,i=this.passes.length;t<i;t++){const i=this.passes[t];if(!1!==i.enabled){if(i.renderToScreen=this.renderToScreen&&this.isLastEnabledPass(t),i.render(this.renderer,this.writeBuffer,this.readBuffer,e,n),i.needsSwap){if(n){const t=this.renderer.getContext(),n=this.renderer.state.buffers.stencil;n.setFunc(t.NOTEQUAL,1,4294967295),this.copyPass.render(this.renderer,this.writeBuffer,this.readBuffer,e),n.setFunc(t.EQUAL,1,4294967295)}this.swapBuffers()}void 0!==qk&&(i instanceof qk?n=!0:i instanceof _k&&(n=!1))}}this.renderer.setRenderTarget(t)}reset(e){if(void 0===e){const t=this.renderer.getSize(new Cs);this._pixelRatio=this.renderer.getPixelRatio(),this._width=t.width,this._height=t.height,(e=this.renderTarget1.clone()).setSize(this._width*this._pixelRatio,this._height*this._pixelRatio)}this.renderTarget1.dispose(),this.renderTarget2.dispose(),this.renderTarget1=e,this.renderTarget2=e.clone(),this.writeBuffer=this.renderTarget1,this.readBuffer=this.renderTarget2}setSize(e,t){this._width=e,this._height=t;const n=this._width*this._pixelRatio,i=this._height*this._pixelRatio;this.renderTarget1.setSize(n,i),this.renderTarget2.setSize(n,i);for(let e=0;e<this.passes.length;e++)this.passes[e].setSize(n,i)}setPixelRatio(e){this._pixelRatio=e,this.setSize(this._width,this._height)}dispose(){this.renderTarget1.dispose(),this.renderTarget2.dispose(),this.copyPass.dispose()}}class eF extends 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u=i.programs;i.environment=e.isMeshStandardMaterial?t.environment:null,i.fog=t.fog,i.envMap=(e.isMeshStandardMaterial?te:ee).get(e.envMap||i.environment),i.envMapRotation=null!==i.environment&&null===e.envMap?t.environmentRotation:e.envMapRotation,void 0===u&&(e.addEventListener("dispose",Ee),u=new Map,i.programs=u);let c=u.get(l);if(void 0!==c){if(i.currentProgram===c&&i.lightsStateVersion===o)return ke(e,a),c}else a.uniforms=se.getUniforms(e),e.onBeforeCompile(a,x),c=se.acquireProgram(a,l),u.set(l,c),i.uniforms=a.uniforms;const d=i.uniforms;return(e.isShaderMaterial||e.isRawShaderMaterial)&&!0!==e.clipping||(d.clippingPlanes=ue.uniform),ke(e,a),i.needsLights=function(e){return e.isMeshLambertMaterial||e.isMeshToonMaterial||e.isMeshPhongMaterial||e.isMeshStandardMaterial||e.isShadowMaterial||e.isShaderMaterial&&!0===e.lights}(e),i.lightsStateVersion=o,i.needsLights&&(d.ambientLightColor.value=r.state.ambient,d.lightProbe.value=r.state.probe,d.directionalLights.value=r.state.directional,d.directionalLightShadows.value=r.state.directionalShadow,d.spotLights.value=r.state.spot,d.spotLightShadows.value=r.state.spotShadow,d.rectAreaLights.value=r.state.rectArea,d.ltc_1.value=r.state.rectAreaLTC1,d.ltc_2.value=r.state.rectAreaLTC2,d.pointLights.value=r.state.point,d.pointLightShadows.value=r.state.pointShadow,d.hemisphereLights.value=r.state.hemi,d.directionalShadowMap.value=r.state.directionalShadowMap,d.directionalShadowMatrix.value=r.state.directionalShadowMatrix,d.spotShadowMap.value=r.state.spotShadowMap,d.spotLightMatrix.value=r.state.spotLightMatrix,d.spotLightMap.value=r.state.spotLightMap,d.pointShadowMap.value=r.state.pointShadowMap,d.pointShadowMatrix.value=r.state.pointShadowMatrix),i.currentProgram=c,i.uniformsList=null,c}function Re(e){if(null===e.uniformsList){const t=e.currentProgram.getUniforms();e.uniformsList=tm.seqWithValue(t.seq,e.uniforms)}return e.uniformsList}function ke(e,t){const n=_.get(e);n.outputColorSpace=t.outputColorSpace,n.batching=t.batching,n.batchingColor=t.batchingColor,n.instancing=t.instancing,n.instancingColor=t.instancingColor,n.instancingMorph=t.instancingMorph,n.skinning=t.skinning,n.morphTargets=t.morphTargets,n.morphNormals=t.morphNormals,n.morphColors=t.morphColors,n.morphTargetsCount=t.morphTargetsCount,n.numClippingPlanes=t.numClippingPlanes,n.numIntersection=t.numClipIntersection,n.vertexAlphas=t.vertexAlphas,n.vertexTangents=t.vertexTangents,n.toneMapping=t.toneMapping}Be.setAnimationLoop((function(e){Se&&Se(e)})),"undefined"!=typeof self&&Be.setContext(self),this.setAnimationLoop=function(e){Se=e,be.setAnimationLoop(e),null===e?Be.stop():Be.start()},be.addEventListener("sessionstart",Pe),be.addEventListener("sessionend",Ne),this.render=function(e,t){if(void 0!==t&&!0!==t.isCamera)return void console.error("THREE.WebGLRenderer.render: camera is not an instance of THREE.Camera.");if(!0===y)return;if(!0===e.matrixWorldAutoUpdate&&e.updateMatrixWorld(),null===t.parent&&!0===t.matrixWorldAutoUpdate&&t.updateMatrixWorld(),!0===be.enabled&&!0===be.isPresenting&&(!0===be.cameraAutoUpdate&&be.updateCamera(t),t=be.getCamera()),!0===e.isScene&&e.onBeforeRender(x,e,t,C),m=le.get(e,A.length),m.init(t),A.push(m),X.multiplyMatrices(t.projectionMatrix,t.matrixWorldInverse),F.setFromProjectionMatrix(X,as,t.reversedDepth),U=this.localClippingEnabled,H=ue.init(this.clippingPlanes,U),g=ae.get(e,v.length),g.init(),v.push(g),!0===be.enabled&&!0===be.isPresenting){const e=x.xr.getDepthSensingMesh();null!==e&&De(e,t,-1/0,x.sortObjects)}De(e,t,0,x.sortObjects),g.finish(),!0===x.sortObjects&&g.sort(j,O),Q=!1===be.enabled||!1===be.isPresenting||!1===be.hasDepthSensing(),Q&&de.addToRenderList(g,e),this.info.render.frame++,!0===H&&ue.beginShadows();const n=m.state.shadowsArray;ce.render(n,e,t),!0===H&&ue.endShadows(),!0===this.info.autoReset&&this.info.reset();const i=g.opaque,r=g.transmissive;if(m.setupLights(),t.isArrayCamera){const n=t.cameras;if(r.length>0)for(let t=0,s=n.length;t<s;t++){Le(i,r,e,n[t])}Q&&de.render(e);for(let t=0,i=n.length;t<i;t++){const i=n[t];Ie(g,e,i,i.viewport)}}else r.length>0&&Le(i,r,e,t),Q&&de.render(e),Ie(g,e,t);null!==C&&0===w&&($.updateMultisampleRenderTarget(C),$.updateRenderTargetMipmap(C)),!0===e.isScene&&e.onAfterRender(x,e,t),me.resetDefaultState(),M=-1,E=null,A.pop(),A.length>0?(m=A[A.length-1],!0===H&&ue.setGlobalState(x.clippingPlanes,m.state.camera)):m=null,v.pop(),g=v.length>0?v[v.length-1]:null},this.getActiveCubeFace=function(){return b},this.getActiveMipmapLevel=function(){return w},this.getRenderTarget=function(){return C},this.setRenderTargetTextures=function(e,t,n){const i=_.get(e);i.__autoAllocateDepthBuffer=!1===e.resolveDepthBuffer,!1===i.__autoAllocateDepthBuffer&&(i.__useRenderToTexture=!1),_.get(e.texture).__webglTexture=t,_.get(e.depthTexture).__webglTexture=i.__autoAllocateDepthBuffer?void 0:n,i.__hasExternalTextures=!0},this.setRenderTargetFramebuffer=function(e,t){const n=_.get(e);n.__webglFramebuffer=t,n.__useDefaultFramebuffer=void 0===t};const Fe=Ae.createFramebuffer();this.setRenderTarget=function(e,t=0,n=0){C=e,b=t,w=n;let i=!0,r=null,s=!1,o=!1;if(e){const a=_.get(e);if(void 0!==a.__useDefaultFramebuffer)K.bindFramebuffer(Ae.FRAMEBUFFER,null),i=!1;else if(void 0===a.__webglFramebuffer)$.setupRenderTarget(e);else if(a.__hasExternalTextures)$.rebindTextures(e,_.get(e.texture).__webglTexture,_.get(e.depthTexture).__webglTexture);else if(e.depthBuffer){const t=e.depthTexture;if(a.__boundDepthTexture!==t){if(null!==t&&_.has(t)&&(e.width!==t.image.width||e.height!==t.image.height))throw new Error("WebGLRenderTarget: Attached DepthTexture is 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t=_.get(e.texture);Ae.framebufferTexture2D(Ae.FRAMEBUFFER,Ae.COLOR_ATTACHMENT0,Ae.TEXTURE_2D,t.__webglTexture,n)}M=-1},this.readRenderTargetPixels=function(e,t,n,i,r,s,o,a=0){if(!e||!e.isWebGLRenderTarget)return void console.error("THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not THREE.WebGLRenderTarget.");let l=_.get(e).__webglFramebuffer;if(e.isWebGLCubeRenderTarget&&void 0!==o&&(l=l[o]),l){K.bindFramebuffer(Ae.FRAMEBUFFER,l);try{const o=e.textures[a],l=o.format,u=o.type;if(!J.textureFormatReadable(l))return void console.error("THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not in RGBA or implementation defined format.");if(!J.textureTypeReadable(u))return void console.error("THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not in UnsignedByteType or implementation defined type.");t>=0&&t<=e.width-i&&n>=0&&n<=e.height-r&&(e.textures.length>1&&Ae.readBuffer(Ae.COLOR_ATTACHMENT0+a),Ae.readPixels(t,n,i,r,ge.convert(l),ge.convert(u),s))}finally{const e=null!==C?_.get(C).__webglFramebuffer:null;K.bindFramebuffer(Ae.FRAMEBUFFER,e)}}},this.readRenderTargetPixelsAsync=async function(e,t,n,i,r,s,o,a=0){if(!e||!e.isWebGLRenderTarget)throw new Error("THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not THREE.WebGLRenderTarget.");let l=_.get(e).__webglFramebuffer;if(e.isWebGLCubeRenderTarget&&void 0!==o&&(l=l[o]),l){if(t>=0&&t<=e.width-i&&n>=0&&n<=e.height-r){K.bindFramebuffer(Ae.FRAMEBUFFER,l);const o=e.textures[a],u=o.format,c=o.type;if(!J.textureFormatReadable(u))throw new Error("THREE.WebGLRenderer.readRenderTargetPixelsAsync: renderTarget is not in RGBA or implementation defined format.");if(!J.textureTypeReadable(c))throw new Error("THREE.WebGLRenderer.readRenderTargetPixelsAsync: renderTarget is not in UnsignedByteType or implementation defined type.");const d=Ae.createBuffer();Ae.bindBuffer(Ae.PIXEL_PACK_BUFFER,d),Ae.bufferData(Ae.PIXEL_PACK_BUFFER,s.byteLength,Ae.STREAM_READ),e.textures.length>1&&Ae.readBuffer(Ae.COLOR_ATTACHMENT0+a),Ae.readPixels(t,n,i,r,ge.convert(u),ge.convert(c),0);const h=null!==C?_.get(C).__webglFramebuffer:null;K.bindFramebuffer(Ae.FRAMEBUFFER,h);const f=Ae.fenceSync(Ae.SYNC_GPU_COMMANDS_COMPLETE,0);return Ae.flush(),await function(e,t,n){return new Promise((function(i,r){setTimeout((function s(){switch(e.clientWaitSync(t,e.SYNC_FLUSH_COMMANDS_BIT,0)){case e.WAIT_FAILED:r();break;case e.TIMEOUT_EXPIRED:setTimeout(s,n);break;default:i()}}),n)}))}(Ae,f,4),Ae.bindBuffer(Ae.PIXEL_PACK_BUFFER,d),Ae.getBufferSubData(Ae.PIXEL_PACK_BUFFER,0,s),Ae.deleteBuffer(d),Ae.deleteSync(f),s}throw new Error("THREE.WebGLRenderer.readRenderTargetPixelsAsync: requested read bounds are out of range.")}},this.copyFramebufferToTexture=function(e,t=null,n=0){const i=Math.pow(2,-n),r=Math.floor(e.image.width*i),s=Math.floor(e.image.height*i),o=null!==t?t.x:0,a=null!==t?t.y:0;$.setTexture2D(e,0),Ae.copyTexSubImage2D(Ae.TEXTURE_2D,n,0,0,o,a,r,s),K.unbindTexture()};const He=Ae.createFramebuffer(),Ue=Ae.createFramebuffer();this.copyTextureToTexture=function(e,t,n=null,i=null,r=0,s=null){let o,a,l,u,c,d,h,f,p;null===s&&(0!==r?(js("WebGLRenderer: copyTextureToTexture function signature has changed to support src and dst mipmap levels."),s=r,r=0):s=0);const g=e.isCompressedTexture?e.mipmaps[s]:e.image;if(null!==n)o=n.max.x-n.min.x,a=n.max.y-n.min.y,l=n.isBox3?n.max.z-n.min.z:1,u=n.min.x,c=n.min.y,d=n.isBox3?n.min.z:0;else{const t=Math.pow(2,-r);o=Math.floor(g.width*t),a=Math.floor(g.height*t),l=e.isDataArrayTexture?g.depth:e.isData3DTexture?Math.floor(g.depth*t):1,u=0,c=0,d=0}null!==i?(h=i.x,f=i.y,p=i.z):(h=0,f=0,p=0);const m=ge.convert(t.format),v=ge.convert(t.type);let A;t.isData3DTexture?($.setTexture3D(t,0),A=Ae.TEXTURE_3D):t.isDataArrayTexture||t.isCompressedArrayTexture?($.setTexture2DArray(t,0),A=Ae.TEXTURE_2D_ARRAY):($.setTexture2D(t,0),A=Ae.TEXTURE_2D),Ae.pixelStorei(Ae.UNPACK_FLIP_Y_WEBGL,t.flipY),Ae.pixelStorei(Ae.UNPACK_PREMULTIPLY_ALPHA_WEBGL,t.premultiplyAlpha),Ae.pixelStorei(Ae.UNPACK_ALIGNMENT,t.unpackAlignment);const x=Ae.getParameter(Ae.UNPACK_ROW_LENGTH),y=Ae.getParameter(Ae.UNPACK_IMAGE_HEIGHT),b=Ae.getParameter(Ae.UNPACK_SKIP_PIXELS),w=Ae.getParameter(Ae.UNPACK_SKIP_ROWS),C=Ae.getParameter(Ae.UNPACK_SKIP_IMAGES);Ae.pixelStorei(Ae.UNPACK_ROW_LENGTH,g.width),Ae.pixelStorei(Ae.UNPACK_IMAGE_HEIGHT,g.height),Ae.pixelStorei(Ae.UNPACK_SKIP_PIXELS,u),Ae.pixelStorei(Ae.UNPACK_SKIP_ROWS,c),Ae.pixelStorei(Ae.UNPACK_SKIP_IMAGES,d);const M=e.isDataArrayTexture||e.isData3DTexture,E=t.isDataArrayTexture||t.isData3DTexture;if(e.isDepthTexture){const n=_.get(e),i=_.get(t),g=_.get(n.__renderTarget),m=_.get(i.__renderTarget);K.bindFramebuffer(Ae.READ_FRAMEBUFFER,g.__webglFramebuffer),K.bindFramebuffer(Ae.DRAW_FRAMEBUFFER,m.__webglFramebuffer);for(let n=0;n<l;n++)M&&(Ae.framebufferTextureLayer(Ae.READ_FRAMEBUFFER,Ae.COLOR_ATTACHMENT0,_.get(e).__webglTexture,r,d+n),Ae.framebufferTextureLayer(Ae.DRAW_FRAMEBUFFER,Ae.COLOR_ATTACHMENT0,_.get(t).__webglTexture,s,p+n)),Ae.blitFramebuffer(u,c,o,a,h,f,o,a,Ae.DEPTH_BUFFER_BIT,Ae.NEAREST);K.bindFramebuffer(Ae.READ_FRAMEBUFFER,null),K.bindFramebuffer(Ae.DRAW_FRAMEBUFFER,null)}else if(0!==r||e.isRenderTargetTexture||_.has(e)){const n=_.get(e),i=_.get(t);K.bindFramebuffer(Ae.READ_FRAMEBUFFER,He),K.bindFramebuffer(Ae.DRAW_FRAMEBUFFER,Ue);for(let e=0;e<l;e++)M?Ae.framebufferTextureLayer(Ae.READ_FRAMEBUFFER,Ae.COLOR_ATTACHMENT0,n.__webglTexture,r,d+e):Ae.framebufferTexture2D(Ae.READ_FRAMEBUFFER,Ae.COLOR_ATTACHMENT0,Ae.TEXTURE_2D,n.__webglTexture,r),E?Ae.framebufferTextureLayer(Ae.DRAW_FRAMEBUFFER,Ae.COLOR_ATTACHMENT0,i.__webglTexture,s,p+e):Ae.framebufferTexture2D(Ae.DRAW_FRAMEBUFFER,Ae.COLOR_ATTACHMENT0,Ae.TEXTURE_2D,i.__webglTexture,s),0!==r?Ae.blitFramebuffer(u,c,o,a,h,f,o,a,Ae.COLOR_BUFFER_BIT,Ae.NEAREST):E?Ae.copyTexSubImage3D(A,s,h,f,p+e,u,c,o,a):Ae.copyTexSubImage2D(A,s,h,f,u,c,o,a);K.bindFramebuffer(Ae.READ_FRAMEBUFFER,null),K.bindFramebuffer(Ae.DRAW_FRAMEBUFFER,null)}else E?e.isDataTexture||e.isData3DTexture?Ae.texSubImage3D(A,s,h,f,p,o,a,l,m,v,g.data):t.isCompressedArrayTexture?Ae.compressedTexSubImage3D(A,s,h,f,p,o,a,l,m,g.data):Ae.texSubImage3D(A,s,h,f,p,o,a,l,m,v,g):e.isDataTexture?Ae.texSubImage2D(Ae.TEXTURE_2D,s,h,f,o,a,m,v,g.data):e.isCompressedTexture?Ae.compressedTexSubImage2D(Ae.TEXTURE_2D,s,h,f,g.width,g.height,m,g.data):Ae.texSubImage2D(Ae.TEXTURE_2D,s,h,f,o,a,m,v,g);Ae.pixelStorei(Ae.UNPACK_ROW_LENGTH,x),Ae.pixelStorei(Ae.UNPACK_IMAGE_HEIGHT,y),Ae.pixelStorei(Ae.UNPACK_SKIP_PIXELS,b),Ae.pixelStorei(Ae.UNPACK_SKIP_ROWS,w),Ae.pixelStorei(Ae.UNPACK_SKIP_IMAGES,C),0===s&&t.generateMipmaps&&Ae.generateMipmap(A),K.unbindTexture()},this.initRenderTarget=function(e){void 0===_.get(e).__webglFramebuffer&&$.setupRenderTarget(e)},this.initTexture=function(e){e.isCubeTexture?$.setTextureCube(e,0):e.isData3DTexture?$.setTexture3D(e,0):e.isDataArrayTexture||e.isCompressedArrayTexture?$.setTexture2DArray(e,0):$.setTexture2D(e,0),K.unbindTexture()},this.resetState=function(){b=0,w=0,C=null,K.reset(),me.reset()},"undefined"!=typeof __THREE_DEVTOOLS__&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent("observe",{detail:this}))}get coordinateSystem(){return as}get outputColorSpace(){return this._outputColorSpace}set outputColorSpace(e){this._outputColorSpace=e;const t=this.getContext();t.drawingBufferColorSpace=ks._getDrawingBufferColorSpace(e),t.unpackColorSpace=ks._getUnpackColorSpace()}},Scene:wl,PerspectiveCamera:pl,Raycaster:Bc,SRGBColorSpace:qr,TextureLoader:class extends Ku{constructor(e){super(e)}load(e,t,n,i){const r=new Ys,s=new _u(this.manager);return s.setCrossOrigin(this.crossOrigin),s.setPath(this.path),s.load(e,(function(e){r.image=e,r.needsUpdate=!0,void 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49uTUB6+eW3Huh2LeU0ruzPAGN5ORpCZtYX/fFpAXd4Fq3H6Sr5+fpXdVQ35ATt9WTt87bkbaTe53zUcs6F16/ky21URv+WZbWef/743bLfxWrRl/qYV0so5/N3f3dl37ZtjZIWkml0W+2nM/Gr5Mua0Tmd8hYQylo2Rds2L4SD86nkM02k+zKZsv3O7xybKKrx1abbcECq18tZSKutgIrfva+BPN+Uyc+4Wm+2teTD1pYFpH/5lyv7bFsGJN9nKwQukjd5gsju7Cn2OjdH43quujk0u1uq5mwlvz/9Ey2XnWKtFmCY+ORN8Sr5aQ1YVq/9pS+dvrPWujHx31ALiQASQvb2jXr5Sm6lAa4BxZ0FuNuLlBc5FkcdKMkAWqTevSa/DqzWl750dGsC0g9/ePVB14XUqZ2Y3Wozql1F/oiKL7/r05i4kUVVyefhFYPpfz0grmgoSJFnob2Ld7EMBBEBistXyZESulJYk/eS/J7X/trXTt2OdYcxM1oglMNyeLmq5KJ0vJ7yWW6ohUQAqV63qIVkWjkpukKg6kWtl8c/777K30TP6baafPK+aZ3Ig4lqM2QPNVlwYrJnUq0kFXD5/cvNs2ey5ReztQrDqEBoQtKiekpYIWS1vvbVx7euhWRZwWiRJqho7m0NiJYqtyAQkoNdLUsf5Fr0zUz8TFZylnxPEUqPTwYAZJU7qIaDQHiHGgCkHpHfUgJ4STmRr6PPkyM+mvhc6yEfY9D68u8+FVtI3CwyWS6m+6tVXrRvrAodsZAQCncQZo6jj9TOE8QbvKp/L+mv6MicR5fl2RF7Rt7kqA4kYMjrVAoiECDgRTo+pO+Zytl88P6RH9Zg682f/+fb3/ve97Q7J/JU9+KLL1Ls6rf+hk7ZfvSjTx70vGUKSJ46NOW9eXS/Fg0hVf2CClMtg1XSXz9tqA4ifYNG1qvXiH/S5D+UQXytwwfUxzRZdv21ZPlaOvkBgq1rXzt+y8jtReXO9wrKfVGp+L2oolK+oYD0j/94bX8QMAup/M9kXOs5YSyHA0A4aK7uSr6oadd14xFVHRz4oGFqYxN92XLOn9Tzhfat5Sx3eYohxunLlsfyDfyM738Pyc8FpPIfaqkaDJCIx1z1jpdiU5BYkcMBiXzafK4cN6o6kmtEqPViiIj+iK0nTV1R3kbLL6i9iqygBgLL2tCBtuBj3pNkIYatK19+8uZGPVwCSPwJxKYsOIskZJLBocQ0Si/HDROMwff/6xv7m259B/B6sTMxAQqTX4CVM8zpSUDGAammjQDRrK0IQ2FSlz/t+spPd4A8v4ipyxRdccnrcuXkO05iIamcg8DPBAi1bh495y/WCwILpkY1AEARXoRPETr1vbLemdMW4XsvyfdD3HrvG6c+zesda3VfAqQXfuWQeoFLynBqUTrN/RcAgCCaE4r3TeX/10s/PzDcGFKmbG70BH7xd45NHBfUAKtHAUYot4I2y60jfDiks6Q71UbLB2Ao4+PO85WZfGqWpQcFhGQgKTu9khtJDqhReeU9u7nB5cGkJszBSBsGVjTKeaTJWaNr34PeZz/RQnYcB5PyIAig/pllG9qoo00g33JA69rXnrrB2+LqSy/R7+b4+fOSecLL1TZT6Yp/xIySCnsBY6tsxRi4SH2hsulvHf9j/+2t/Q6EO9P3CCjoACkBC9GDk3QuF3hRPYuOyjVAOpueV9Ybb7B8j6w69vPcZVtx9eh1o7wKdiZQ7OcpCAgFAQEi3YSbjUbJYMP6DQGcfmRl19lc8v0QtP42fDcGpPS7n4+KXupTlby+Wp3xow10HmMbvCQKiCqRf8Ty8+fBcQBipLz6EqnP6onIGKPn+fOp+hE5YQy+bj+xv9YggOQCbsGQTuQBDjykEzHLhv0igPEJWLlRB2PQFHc+NzHTa6BGR0wHu5izpJ3YJ/TRvJKKulfl+8Ahzvg+VyCZXuT5M/uIOeAlmuUfKwPCdHle75PlmKzMfsuF57ECaEX+gaSfKIOX75ImpYMaGZhYnwLACiBUgZ5ZRhCyQS0BMQYzST9kT+BL8LcZ5UPbXfmbr5w0A5KKQyZ8MuFOTkdKACmvx2Xcn75wAe49dy7uyOo1r6qWf/0fLu93uuHumLVLgsnYFMKyIPR9DzRtdh2EzOLhfYR8AGQKYNHy6OfWyBYUekG6kkPqRuYTByJ+00GYdVKp/r0rnwCTmsq1SJOZAv543bz7RWRw4ONgV7ROGTpiEREgYv2A/Wj7Kj9+X71nKk/6lsxIx1ul3YzyLRu3wO+d/oRrw4Q/pra7duECbZ+rAh6Q62y7KOHGp2zOhQsXUjLOnTsXl4n3SXnWNa+kp+N3L4C/8vbsR+1gt1urAb+gg8FW/Cth4ENTfbXcJTEpXvoTvF/kk3dvhAiJwESAO/vDLheewHl5SnvUIseJKb81GSASQJJlmqZupvJYdK0GCAghFFCXAvX/cWPIBYC0ffzuPomY1mtC9BsSK4hYSpQfsZzjn0dlkUsqIrLCycjG2W4J+VZt5dr2qetlBovVoj127hzbOHcOY4f++6v/RFjSXavCVfoEbhLKBNbk2k/880f77aCXWEiK50j15Oj6m9A/Jeam8jzlicb/PSvf8wDCGDcsB+W9z3rdJwDGQWs1ZHYRWbyvZ4Btf0ArPVterEnmi2xO+b4DWx9sezK2kMwqUA0Y01devDccOwcYIH334kX3wJkzBRf5iwtQKe9cugRFOY/8/dUDNRzshgGEWHDiEn+G6ssQeemAQu8Cd4EfDamiQ1PlfT/Lr4cOQqi35m2X1+r9LF1zv1+8NO7WALGGQoPVp7OO854r6z7nJ1laGRW2gnwvBK1Pfv/pjwfRa791jwEBkPRMzgAALuXyP3PmDLh0KZ9OZfT5SeuAjWxqIUWuH0ZSYw5IdqFf/keIOV/JNIwZ1T7lEYYBNJnuhJPtOFhraSnLdveXfACsDkKW5SA17kWdoBaJnSEazYufSfPRed5VE0TflQLLh8QaCi22yNL/T+0rhjlc/wJyat7/8qFjtd798tENBiTMvtED167Bq5HKdx47Jo+6At4caF6DdzrJ/fnmNRarQJxZvD6/f8bM93N/++bBGiCAJNg80aqXDEQun9hT7i5ILJ+oIP6HdQlCz2yjmF3clRT7ilbYHPLJC1shQnULoaLbN4rSxeozzFSIPygFhgoe6WT1kEWwPwYiMqBwWY0mG3SkwSoahELNEj5x+9i2gzkPdWDig1gWqmx1+cABrY9+76mP8jCbzHZ0NAPNtC5ciJb9r16lXef4sWMAXGNirvI/FKBhwHNMvk/rsYockHR0/AVIfSLo4U+9Aw3P2RMDB/FkBYyKWjNR5xIXi3ULx65Sj0MMl6f6hRJFMsmbT74PaoGNCDjJ76rrQrJG08v+Jqe5bA2Qjz0vqFJchevZloVxSJ3Vts1DE9izMFDwafuzJxbLWb9Ieona2uZWF8FG1EQlP9E/mbL9/JCXC0h5gNXP/QPLy9SHBP+XD3ANgA8L8djtHY4tp9nahzFKmsoJU35vtkYAMJHz1DvtA01g75EFm8zepNzGTRxC1mmTnwts7OAQdqTRlnReVm6aAqZjTeTnSUPg/SKfvIcDrZBM5wo17gBExELKC3wkviFkW4mPiC1nRVINSxaimSM1ty80v64NheUxk5hKfkr/Pctr/fIhLIABcduIv6KuGV5PpTeVA3Bg+YwISFxo8izLtxw4MnYoAiBTOQDLznU4EgQxUC07jnQNwGHplZZvXYcjYwF+8r3OwWEf7XFIkKMELj4IQwiZ5eJGI2LSG8lIJ46e7DoJAOyGAWzwUdQBgPIPTPWj+5tZfuACK+whMqFjy9kijLOPmTv/05hUDLCJ/rkFkrQN44ZQaHmOZSWDAisn/jxRnm4aloWRvL5aryjfonSmZ9iM8u26s/Kzr5zIt05MOFN2UBNdQWeIU/tXO/BfuH69nhV4cAgcAteBmcJ0P6/e6TdnDzYR3CvMuOLXIVYNu6ARCSCEXWr50M5OpnWsmJr3DnBAwOd6MQdSCgC2k8hyTq/qbCvJr4UIOX4Y5vUbHOufUUJqkZLEEDKIJOUYu9yaiTCP+IZ0QBSTqeAY3VCK4zgg/fKGAK6GQPCUzR3R+ZV8qRuQ9vMQbP3DkYLTpbxOJNxXfdLz15jfWSq/dAlQQPrOdbY9/tAhAK5fT4Dn0KFDQLiM2R8CQIAnmZ7fEAGM8JHwjDAAADz0rx8cgO3OA8R4caJOIhgytEy8TuCJ1Y/cTfQvCj+Cbzq5F/EWeiWCIbQcO8kCuMXkEz1ZXQ85vhWKlmWJ/pUiJUDFwYlMzbA4NTMyzrK+xHtmL6CedR508VqVfFl/PuiFoPU/nnQ/GKQv9Ft3Z+cYs5D+11u3GqNjY/EHunjrFuTXol0kAxEAEa4AkT7rYVS+p//h7YPDXfxAGIbQthOAUK9jpzOdWjCo4V2JTO3ItVjf9AwmvltVvuVgbIWYWUxFv+EUIWuJet1GdMXMRbawv4daqUEgDg9R6+jMUnXEkUeduFmdyDqWuGpEAIdZyZX84vrHNmj98LFjGwNIx6IpGwGkflFtkHqHX1866HroAdXe0fEMUQBti00XxL+z5Zt6vVgr6t2pKZ/MebPLdyAKCTDZ6gGdBRuYWFq9uuNA6NIBgn8CXLsF2awaWSWfqbKs/j0Htv7pK0++v2oNUYLRThoYGVlIpF5r0o5XqIb3hcboX0In3m9NTrJ6Bw4AEB2gIt8nfNmN4X37Yr6HXlseq8FeBEisF7t87haNxNLALfiOpPfUlQcAEAALLeb70IfIKfFMlXzQcKzQ7aB4Kqf6WUz9i4Zo1LETRoBE6ZJN9/SysBGW14nVBbSYsdIRKvk86UFh/Qc4aP/zN0+/y5uAxBaSnxjOQ655udpUeXTqfbF+DEjfnZho5vUBDjQMeH6130Q4uanjTsPm3r0MaMQTnRQ6Wk/4Hb80ebDhw318VYY4qEXr3rIdbEXOVMmAiQyfOAhOHAYk55HkaAJ2PbKwhOA78jiV/EQvXP8NgMK6BwMTjKgraQS4wprjWLUkbomtbCZDAZ9q5fa1HAJxxZSQxs0fD2aMQSW/D/3buHXx2Pb3Bm0jXn/34SRMiJTNfpiECqkydnses5C+PTk5BCYnhfv7hL/l8uZeFFs4nekkd7G2nLAR+e7bB4DA7tStuwebPmTC6CinMXU0fke2xJwO2EuVUye3YLwrQdpUrrQyU8lXjXwCTE7QDa3QzoxlIoGRYQ072GbBjuynDWMV+tYgNpOuMdUuXslnGjEtCqT1j22n9ebJkdhCWi1gKsJHBiSxRgQaXWcWNnbvTk3durNyeXfWgo3dCVDR+4FQL8I3Us7FkPsn3rs5Nmzb+9hHIJg2ES6gMIDESpI/koTOsm2MQgg5HRmBiQMzrhfQIKToJ5QnRdH9Sn6e/u0gDOu9MKhZcpAlHxhIWhJUdxxsQ8uyklALYnGRzSGs65OIsOgXD0DG+TSwLAcjxOrW6d98r1sStcbKA8ho2f1Kfv/6R9BpXXnm1Dv5AKKGKsmxhulAa/U+l5DwiQHp/LXpYe0D7BVKp1UKoWDvXgBS9wGgxZpyxmkaPPNxZ2yHb1G4UmdaJoXIdIlFQ8sDkgkxXZN8FKw8AR4et8TWYSr5RfVvk834XhiQeCZR08Q6XQZhDVnMqZ31K7LUkMdjkPuVfLm/i7q0arj12pk9ZkBSwxH5UntOg4wEPMCaEZJgavKvWL7bi5za56c5IAkIsheAvWAvmNYhjSicA46Ontyj5TJeEb7k9/il9w7aK539xncRF8BUoFENqsgYiouDaAIolBPryYkQi7KLaCr5Bg1k6B96GDW7vg8jYCKA1LZd18coNz+7PGg4qWX5vHVPNcSDhG2UAahKvqgtWf+Wa7cufmZ3tKO1jFYHpyW7PagP6T/MzGxr4D3x1KwLZyC/Fg2cFLBEFlR3ZgY29rD6okU0AmfgssCXXIt8n3v7vYNwvnuAdhBq2tsYoRCKMziTjzo2eBQ9iE5xNoVLCLgcUoIsFvdE5FXy+9c/7CHU6AW+jWDQBbAWCk7tWPOawWPw7quZ5ZvWuCv5UlNkLS6QKdvFz2zfeEBalQ5SksnJ1z4dczxgtpBK8qvIN04DEMPA8pLgVg72q/VERaZZZEAT5dHBbZV+W0W+5TqtXzx7Mmt1fpU0mmYzEkRTNmIhkdu9hYW4Aes7dhjjkAideD+ptwsAMEcl6e/L5U+8dndsyEMCIBHHM4S28Kzypqv0KhhxbIurcygy303lhLfIk9HxXyW/X/1b2MbIwxgijIiFqzNWVGuXLD4g28HJ4kV2IJ8XBrBG6dVEbowzWQChFnElv2/9Yxu0L33zmbdfPiY1AAAgAElEQVRTcFHUd1SUTgNrIzww8t9/ODdSBvYY7DDgIb/hRQu2RkUAY/d2gV0CVVrC8at3x7b1egfIyEZAQhzRSJkIHvweByssrOQkqyvRlI9Cjg04LbtiU0JVjqm8kl9O/45rI8v3MQwtwdmtblkoGzec3ytNsbKsZiVf1mC+/q2a2/rXz+xIWUhjSlPMC1vNyK3WrVvUmOF0tzg2KHQ7IzrOjtNRHOE+pO9+PL99fn4+FrkzPrpxJ5DLd4KWsLXAs5hFRchbKAEkbzEq38nq1yKwGqa5kpkc8v+TbyyPDXlYCZfkHcmsPBpvxPMbRX0u2STqANXJye6x8ngflGZ7T6Lz7G5eyU/r33Ut5HgYkTNCuP4HdT6rcGTiV7Y8H+b0FGXl3I/vT6ZsHz63J20h9au0EvXmRUDi9RJYAmB4aRHWto+mpm6eUu5Zi7CGEjpyv7WdxyXtpIBFfqScy2ltH8XH37o5TgBJnJ9zPwB1Nue8jEViXwjICaZUgjNJQGSR6QOnruQLzv4S+oeWhZweRg45tEjZTMtXNlV26p5b1dlquq/bq0t4J4ONPNpU8vVfkla/Nmy//7ndV0rgyKqRxoD0nesLowAsaBjvEMrE+6Q865pXy6BbAODQJ0tj23x8MBEiendETxKn4JOvrGt+T5ywkTKFXxDJckweq0p+ukNk6B/ayA19ZPnySbmch+yrA4D4+pKyBECIDyurh+v4FPkiKvmKw9+g/xAHnbePPnTZpNPhffslA6U1OVFo4UDdG8v3zYrlFJAwxvDPKSClfzt2ALCgwynT06r4k0UHADjy8sRYs+2P0SBFzRRKnl7JKK92ZtqRhQAWK84gKW90o07v2OnJgyIr+QPrHwM8ZMMQ+0nm0JwECmkPtik6s2w573eZ03LNVviycvKiSe9D+dgC7beP7jcCUi74cweMuKc1txIjmPdCFof0158u7ugIU7Pm0iLsbE+PdDvADrAgWEbkmvx6S4uwHtUX7zeXoMSHXfOp3QI49PLE2Pa2P0amZ2yqxCZv3IHNY4WoOc7/pzQypRWMGbLaQ0jj8lCIb4oUQ2QlEzpGW8kfUP/QQrUQhdiXM3Rm98W8L7pgT+6brJKfqI4NzsgC7XfOPfhW3yodoOJ8GDIL6T9+uhjPzRYFhqPEbhILlMvYrBoFYFGgE+tJ/JT6R9/+dGyoHTDHPJ+tFZkpDfDSxqqVfKaaPvVPTtKtBVYIEV9lS6bfLBRDXDOVhcjTKV09tdUYjVxPffBKPtdaGf0jK7wHAGmRAZK3vJyaD9ZGRtJO7eVlKJbn1RPvi/XGfnxz3O12pRVF25anZmEom0S2EGERauYE/D7rjgHg1yRtLe3EPHguZJYRtmRLsJLfn/4RBrgWwJAu+0csCERwa5eHXOgSOkRNxb4f0wqEUM6gJxrRUY/kSIl/NrJxJT8ZW8rq36rB9tXPn3pzLcb8PJ7zIWAW0l/eukUXwvwVCN1teqekzGw7AGApLmqsQNjV1pPpEh6s/OE3p8ebHRQBkg0wQpA8EKejLlTdiC2NtgBYZLFZqEfq4ygsAFoWJuYXT2svRyeJFkElfxD9hyFCNYBC0g589UZ1JBMI4QMDHS4EJCG04h42HuBKoUcBKZpBQApoZT3GivyDlfxIH4qOiugfQ9B+59+ffaPDky4aUKSJkkSLIknHYskamzwR44TMgN9X2RL6efLZvvDCC9b0X/7lzuXlPPwCYGQEgC5OLCZ/JW1RiVxItKXIltQX5Tz67vT4cMcft1wb+34SfSumj2AIb9OUEgSc8s7LEIMrCfiEIARWNGqaAi0r+YPrnwCRFXghCC0UA8gqxyUWDQOo5EdfYR/6D3DQufJbh1/PR4PVp+ju24diQKIWUsuC3WGEOYo0rOhakd3gdFG59hol+ZEIEHH+nFUXIfzou4vjjU53nFtBCCGIiUUTMsuIGEzEuqFlwg8iRJLuYAI2BHQIHQUey8LkHifF2KIgxn+Ef2x90VGW8a3kM60MpH+IUY0AEvUhqacsac1cZRMPbQmlp+XxMd3Pqxf3AkVeJR9B0L7yWw9vLCDd+dZ3yW4Q8y9l6qimj3LNOY1sA2B5xch37N2p8XobjWsJYiQROpc2DEaIN5LCmKJy0aQyb5JLP0IlP9JJMf1jHGCr54dAyZNEmPDpGB+wxekYS7LHYpIGKc/qvpV8Nh0uon8LOu23fueh1PG0PLmiLmGjqHsxCSMpN9Hr+C0gRKZs2Lrz3WUBkDiA0P220U9XFt3igEOtIF0dtTzhOvbmzfH6SqAHpGj8ZBiiIpFmICWEBQGH+koUq0vXoROplXz98luCWWRvIZmyke0jeeE3oq7lKLHkjqmcU2RF8VfyM80L6aaqZwSd9qVnxzbEQtq5MyBTNmzd+KuV3a7gFPYhhOK18fUi/PFbenoftqCLh+PplsqXAFJtKXzIRyF0yeoXmab5IeRjMi3L+tFpXQiJEaTSBmSqF6WfcK0aJjI4q5g2cipV8ldB/zU3BJ0ucshu/9RPDxHiNh25iglu8qCmXL1KvhCzFzWA5drtnz99KGUhFYe4/ikZIGFs3bi7srt/Nv3X3P/WzfH6fOdhwsHCsp8o9vdkuB+Iz4jURZD5lETXBSkj92j1EEh+KH5PfPJK/mD6tyFCdQwDkkmy/x6RM/qkfFNrI0nPVVwSWU+5XNb6yPct0Hn9tx++yKWKWazFtzZmplZUY6qv02AQKIAUwFZsRTiCZaNWJnTifbFebFIL9U1891365KHmsv8QBZXIgom3loUAwChdiChfjKsQ68Vyoz/IWBpnoCRLx9wnFLtEiOccACRGdlO6iEElv5T+IYnURjBw/CTXNluYiAYLMi6ovuY+v2t9KEiafyW/vP6xBTs3fvehXyZNwyFFhaCiUJUHSQnfINjLLKSPJif39Nk3aLWg3YbO0FD29EojYP9rdx4aboXUQuI/0mkT/04ILJ5mZJAH1NSNrSth5Y2QVfL71D9EyO1ZoQviGTcNuRB/ZEWUT6PFcjLwFG1eesyMkAtLrieb05X88voPEOzc/OrpX3TnZqhx0tiVpLYm16byou3H66v0RM7yxCSmgHTrk6m9LdASaMRDSORyZygJXAza4s7sYvXFB3n0ytR4s+VTQCKq4501v4OanMxyOeu8pLObndJiToBKPvOz9aN/hAPs9lBY44CkJlvgDW+aghft0WVX+otGAFTyqQZ8DDsffeWRXxjVMavc4c6esuUaAX4YMgvpvU+mqF0VdNrQaSaWTr3Thj3hmvNQy+sQwp7gFFeveT3Cn/xN4I7wHb8yPz603I4PUmHmPQM8SGOQ2E8Xh8TKGNBAiCCJOSK0opkuThHEGCTyTag8Sd1Kfv/6R8AJ3Z4fOjDI9SGRzC9kasytVN7OYhsVwQfCp+ZauJ96lXy9/rHldD748qHXiuh/tWliQLp+ffoB0b7hgsx2EkjZU6b6qt0kXj90ZWp8ZLH3iO7F1GV5slRP4McRluvJtRVNuQi9OBiq5aaQN06nPkMlX3Zy5+kfQITsLiKpGlKAFLvvUj4kVkAsMro+Ztt0lZVkeZDSVJGR209WSdVtunmuqUo+691pH15a/yFA3Y+++tirqw02RfhJgEQrDA+BVqvN/oyuQXStZzgEWoDRU/LhIcDpJSASyrkc8u+Dl26PN+Y7aUAimjPFFNFy4WZId6oBWwxkjHoo2wvHAySTN4CQbKrN8FtU8svr34EItv0Q+OoqW5k5kxTZKnQ5Uzn9zAwpCnj1Sr787WbNmUOAIOh8+IUHBgAkHtKY5NwvAkaExvNG2ZTtwxsz+5yhZuxYDNodKF7nMTTRq+XqNQGk2uzKo3yPGl8VMwYuRrqkI2TUz0R8okVC/7MggkgMJzCsnFbymT4H0j+0EGh5gQhIpB2JylXrNas/5W3e4HVNLiqRdyW/vP6BBbvvP3/453nf/Frc97zIh/ThTHtfMgdLLB5iMckW0hAAgkXEH2poeAi0RUuqYL0Hr049tG2BTdk4mDCDRhz11NGRXfNS1jEZ0iRlYnflsd4Jn6TTJ39V8plS+9Y/xAiu+KFFNoDEDWSnsjXI7bba3VroG/TPSr4aIpGnf2IhaQFJ3VxW1gAqUH90VAQkAECt04YCHEm9RXR2EzpPcHZzZ/VQEwDQYdX4fXJPD2MAjL0+RZzaj6bOKzL1U4N1TmdYytAqZY5UZnnGvZ9FrH+NxVvJB4Acl2a3UWAFybI/STUiWrN58GM66NF8AKTcGGKWCCKrkt+H/m3Yfff3H3slr61Mm19VnCqAQ7GoUb7K9u7MzIOktNbtQqfRoFM3EZgIoIi/oNuFHmZ0tB4U6kWAlCoXGHB+e35556H6nP8oG1BJxjRGZEenwzN8SCNAiBjOO46FqbMVkTqJVUSveb34pPkwjm8idZLHESyoSn7/+rctVOuFAQxgGFIbSbVSWZuJ7ZnYrKaRQOwBnEaNLkpGm8R5XcnvW/+21Z355tmXTYDUW5in305rh5w3jZzBqPuJ5zeS+yY6igHEhUV8SB/fmt0fmzaUKzF1+E9AGFouXpsem5er9PL1njfmxmtzwWOsS4lTMWFSFU3hwjCanMVTOiYj9iVpnQ/iVI7Xj+TEXwOf9FXy2cCQfOD0r4L6d10nrLW9IPAw4itkZD9h/KNL/UzXpjQ9eel7KD8Ba5wI9OJ6kbhKPtN6X/q3YXfiC48bASnvix/kfuBHUzYGSACE3S60IwuJX3MBanmZa86D8Bf5PXjl9rgz3TtMysjSbxzISPaeRSln1ReU6IRgSpFOyjgSARWvZ1JYJX9A/ZOtI10/gCRrJJJDBtiSvkHzAmYhjOiBDRZk9flJVbym8cSqiABZzPKt5A+gfxd0b//Bkz/LBRbxAEdCHB8uG9XMu88FCHQxIH1we+4A6GgsnyazlKhdI94n5cJ1s9mU70fC0uWyhbT33bnxobnuY3QY1m10soWEsyrKCNdkaZ9NE+RfujxnmS3NIJl4VPIT7SjtRfWMMAUkgHw68RWjvXUR8LQsarKY1mbR+vmR4uaofqMs3TNV8mmbSvoHsHfnD4/+NBeQ1oAg4D4kCkgceARBpglaVjmvnjXR4xPCHW9MjdfnV6iFxH9iVB1x/6hRdrFLqOA9Ts8yTJKOjGDCIw1QlfykLcroH5OMkd0wAH5+pLbal/MittX7um+hbLS2yKOSn1hUCKDep789lgtItVH5RGtvMTmVul+s8uPd/nfmDtqNJA4p7Hagjdl1R/AZMYsnEVeDHWEKFtHHBE1A7nsRH1KLXIt891+ZGrcnV46w4MW0hcOLQoBIVm1q9ht9RvyxIjcDuaR8Q+YElVbhaDoStscNIQAr+augf2ghu+0HMIhWHAr3yrylzcKM+iSs5IvzaQRg79bvHv2JWZnqybHi6db9NEHCTwIkPauCTuxGE4BuGWc3k7aTWEizrSPsKi9CIuNl4+8p6Vw4yodEzjkqpqZKPtOTydmTrX8yZat3Qx945S2kYu1TUa2HBpADe7d/+9iP10OWKsMPfrX8TRO0zXUOkptkOV8l4mEAoJvcCUAXOiBZ9ifXqXrRfd09Trv7rTvjjZleBEislOQ7Ej8JaYuHupqr+X6kfEkCvXgaifisuhiXSn6ioaL6J6crOF3ft3qInLxQDthyxwLB7KXxRckJNXJbApakr5Lft/4RJID0RD4gmQwj1YAqgWwxIH10Z56ejRbCLrSF+CITLxJ3pMYhide8nuL7jtlxOQSQmrPtx0X7iBtKYhQL7d66gMSIY0wrboHThgFEdpidcb5F9HFU8plyY6zI0T+zkICP4imbOgUXp4VZS25lLbSsGCaxB1fy82chJBDI7U186/ELZhzhSDQA8hiY+8QRSCykmxML45KvSKiQck4LlhJoMMKizu8maEo+qT0Xp8aH5ruPc3hgxxqpnSj99CwQUlMeDY+MRxJXRPZS8fU6tms9+Vh4FBKrUcnvV/8hCpDrWR7xIWGyfE9Wb6Lle95SvLzEoCmRmviVLa/kmzUAAex98rVjGYDUr/by68UWEgEk+kH2utCrk6kYg6FaD0KbXss/QieW6669ehLJSYCI8+ecyH0CSI253hMid7LKRToY2RqV9woWdDHCvkAnrwsRXhrcymRbye9P/5blhKAV+hYNo9dYR6rJKQwaSYNoTNdkbJHbTTV4JJGV/JSyCuofQ+zd+OqTP8r79tbiPgWk8z/4gT387G+NA9FJFEuLTCB6rZpGWdecAakv0smvsf3K7Fh9pnU0KVUX3fNeW4UcU30dNHFaUyBBESir5HPIxwCGtod8J/SjhVCdrcWP9mQoI8OGSC9Pw5JvSXQ26f9mZxWTXyVf/Hr4rIEdrZqhfwt7n37r+P+X9+WVvr+o1BiNroVyBZBIAt0c3BFxhv+tmcJp8UvzBiOXPh2vT7YpIFGzW1l9Jov9GPs0bghT858u/gt9TRyM2ejKF50tcdUu7ptJJyZ70sn2N/yrgw4q+YPrH1tO6Ha6AQyS+GpNIIfUC8TpMrshZmzgJamxPipIoCcNP/q6ahes5KuaC0FgQe+T33skF5DckRFp5uQvL+fOaPJAbOfwcEgtpMavfekhu16PBYS9HrSFKVfCSEassJekmU3qJwhF7ot8QgihLaS6Hbl0Z7w+3TpKgIdHQFoW/1PXnQs6JmPjR0G4NOIBJq+SP7D+LRjaK63A5juf83pfdf/e1AC0vI++cehfN+ThYkD6zS/Ro4iKWjbph60D0O3JuGV6I45XDQC2X7ozXpvsRFM2RK2k8o5PPrUyxXRnpHimLqekfiV/AP1bKKy1fB9GgCROZuXsCumOoUsXXOSDyDp9uJKf+E9L6Z8C0vEYkLYbGmKpSAOVoCFy7OHtxELCduM3uxSQiGVk4mHXgWBBAahe03qCAcXvU54NAlhpziNv3xlrTLaeFO9ofW95L5bhItKtxhFrIDS4iCr5xaY7UpMgAKALGSB5vuTCkWxU0eg1hGWk4jJNdXSxSxraSr6wxFBE/47lzXz95L+on5wKQEWBykSn+6RjQHI/v8iOIqJTtWTqZsIBlc5UL6989NLEeGNyiQGSZhOZpD8BQMiyv/qj/TtaZItdojyvkkIvgk4MWJX8RKWCHnmhCOw6/UMLhrWu7ztelDGSbtrkK61M43kjdd64o95nFlLiAOcHNvB+U8kvr39sQW/uGyf/B+BIYkKifk2kDCQL2Sobtoc+P3VInHGButD0wkyMlmddKz2GGkbiTE40lHoA7Hp7bowDkjhVQ1H8CunGrJyNczzeJI5zcZLjs7OmeoSfOiCrsTKV/CTMoh/9h9hC9U5A45DY6FJklZJ1GNOpIHnWqh3JSXsbK/n96h/awJ8ggGT4uSNyYjZ/mfmRy5br2FvDYQjPY2xbU1P0bDTXg9CvJQLJNccTSylX6bKuuXDksYcnuEbod12aG6vfXT7G7yfJ/UOAITmgNFk1E/0FnI4vIvORlx7qJmSDpCNklEmSr6ZxWTr/QyUfQW51lNa/BUO3G3i2h1IGFFk4SFnBmmwNeRYS5xMbs4rla/QmVvKL69+y/ck/OPHPeW2xFvdjQKrfmo6PIlINICa4DnqCaaQzlPgDyvWz6+1+c3Ksdrd1XJfmwvTCzEpKRkBi2ST11ZGRexCyR8xKfjrNS2n9WzB0OqHnhGTKplkhlYqiAMhUDiulXBP8aBGrmICZEjhLkrpBzAa8Sn7/+icW0tQ3n/qntQCcPJ4CIC0JZ6NxSKkzU4Zekv+J87iEtQxUKo3AS/M0296+M1a7s3JcvsWUaQneTQRC6Zp2yLhSMkMgdaRBE4V0WZ9M+Wg5Ikf9JNL062+V/P7074Sw3fWhl59+RGwD2ixKu/AWEo+cVOuoibIy1lJTPa+SL6tE1D+0sT/9nWf+0V9ZkRa43G3b5B0big/Jt2T6PPBR7xP+wfw8olM299bSo5awioZ6AMbXepOJ8iN0nHGKvs7uZ/ElgFSfWDkhPZzQs5DQ69IeCcvoqYjtocj0ScdTJ0KsVO8UAUugS3frSr7gKULEQmp5Huh6QgumvUDi2M0To5E9lUmQYrIHUVU5oReT62GUbBvSb7Gt5DMdJlrP0z90sT/xR4f/sSygrAY99IeYD4kAkpahOjczSK3VAfBE4Cr4dNuv3BqvTTALSXVYyyz0AY5iHfI3QXoY5UFi9eV6WTIq+WwqpF8cyNc/wnbotHwPeixSWw8Qho6R573m1QS6rBXsSn7/+scOCCb/+Ol/KPgJAwBWcki3FWYFfRQ5tW/P0JM/6tRXxH8ywti1WmyyOR6EgeDkDgVnNa/N74eeBwnfhGvCd+Ty7Fjz9vyJOH+N1IvT82CIXRwnXotW4ugHFNWTfEEhW3bGKIomJ8nj6awt4kv/iT402tFJdkllW4qiykq+Wf9k2Z9YSKgrpOZXg8Dy9pIYu64at6HYyzHfonSFv5GIsCjfonT3rnxsg2DqW0//97JPuBr0AiAtU0ByYQ9aNRaHFMNGL+09QrAHfZzEK9F60bUIY5nltToeev3OmHNz4aT4MmWidkk2SA5QeQrRrdJRi0A6o40d+yzyyoqdqeQn+ieA5HaCHugyHxL9NPlfkWVD85nzyHiLTchjfZNI1Tg2Q5xks7/JBJ21hQWw2EbxIMLpWOtV8vvTvwVAMKEBpBHlA1s2fHCcLu8+ry7SxYBUn5k5DLy8T3oV7tfIkbYJn/rlO2P1250TZGWedGOMAV0xgzCJCicdi5o5kPkP+Bik+pR05YSfyEvdysY7biV/cP2HECNn2fMsHwVlYmBIi1qRJaW6w03L+GJP5G2XlJWLQarky/q3bDtY+NZjgoXEp1xsatbFw9KA3YAt6kcuW65DEyuIfEgUkAig+j60sZtsEYGJ09B2hXIfQttN4pVCci1smlU30QICRJQ/mT4xRCJyhi9PjTm3lk/yCGuMMIQWZL4MhOkZXclROayc0OKA3YMQYxwQnpYQFQzIkTwxH9qpSR2M42N3SBGRozq/K/n9699yQGBTHxI5l02em1n8VGFlRoOhHGSHo2X7pLPq+XD+qt+Py6nk969/ywbB4p8888NVMD9Ks7CCyIfkTMxKea1VTnm+bdP9vHpDb00erN1YepoCBHFKl4rvTZ6SW06m+lnlPBFcJX8w/WOy23+561kB0Gb5p1Nr6tdj0zzd4QtFLKJofKGNry71Z9Wv5BfTP4IwXP6fTv230miyChU0gCTPqeqgBnqauRwr579kDkbK+U+sJ9MnPqn6WxMHrRsLFJBSPyuCkTiAiFMQfwKLXeE/4o0gy/eSU1uYw8Xl6fV/sxor+Wx4KKh/27EpIGE/cWqrqWUJIGGLBbKKmRV4U3F6Y8R11Fqcnk/lqUWtyTBayVdO3CmifwzDlW+f/vt+8SVosSmcMyxP7Ti/rPvWUGQhNSZWHiep0HilEHjQBmxVLWvrmgO8VHaAIKpHHwp4UL6GkMshfLddvjXmfLr8FAuCjOJPyNQq/qWjj8g0TVQWpwijehBGU7uURk3by3kQZiWfqIzrkamvuP6BjZGz2PVwQHxI7Ef2SlIuykKBqbPzYFgGOFlLcmJbJnTq01byy+uf2FGL336ib0DqF8hIPZLcj8YhEUAahBGrmxFBaWA+dGVizL4x9zTpUpIJn/4O4hGQO7fJyB0bSZQ+KqD+oiRgMx4lRfveAsASRtRK/uD6hwCF1lLPx9SpvTa/ouFKayM9WQTsO3phwAdbj/eHFgiX/vTJ/zrgo/ZVHXKndu3TOZZov5ZMuaTlMDLKYWYxId+DlM7zgOVGZZBbSsmUL6an95Tltehxm5dnDxJAYrv6IaQruCl7nTU/ARa2wmtRBzW3lIipzsrlURNBhz4vT0tCndqRszXpUDZ1jFfyB9c/hHboLHs9Akh8+sTbUpeuRNdji54eIg4moi2lOrkr+UzL5fSP0fJ3zvxdX4gyYCUYYGYh1e6uUEBCwIOWMOUy8Xc8DwZioKQyNeP1VDpezuU0L08cdD+dP6Xdg6FYNKlnIUnWRADLUIYUNyeGuyQPlJ6dVPITjWosVprkTtA/OZfNWQp6ViA4kQbsoGWrr4cFkfVMm0E+JE7tjQakobtzR3VhSKpdQ69FQpNBFZVr6wst2nxj6mDt5sKpuMjQoqLzUu4Qpn36BHUiREnZ1xlrMZX8aEiVtVxE/wjAkAAS4nikCxQzABuV1i+9utTGH71fflmDFBu12S9vSfA+lW8BjOb/6NjfGo2RoaGCR9PrOQTtNnN6a/jEFhIBJKpr34eBEG/kQB9yALJcF3P8QdCHgRCv5EAIAyEOSb0W6/HHJPWbV6YOutcXnqFlwrIZIpG51BcUxA5uZo4rAERXzfgUTuPMTq33mxaKK/kD69+2AmvB6yGyH0k5ILKopWM6YLKqX0wDq6E/y8Jo4TvP/pdiEleZKkQhPPejHznjTz4tnI22ykIy2LmXZw84n8yeZiSmoU5kYLKIij6zrn7eUFfJTzSQqf/QWvF62ANr5tQu2soVXf8asCwLLXzn9L0CSC7J5Si8jXqtvmhReh0dAO7luwIg9a/EqubGa4BM2WgcEl/2z12KknYy57yAiVYoN0d1GHhX8tXDNOlMFEK0+Bdn/98N6VHcQjr45NNPWiDZGkKmbmSKlvdQhE6lEeupfOhBR0K8k/PGrYPOjcXT6kxMK7eMIaNjwPeQcEtMdVrnGWiV/ExDljhDwVLbA0IcEu3gkfUrq1ejzKIrFFHbZvOVbTpifVfyVUtfmZVw/SOM5//kqf8MhiP6Vh4K5Nw38dGVByGbsh188lnhKCLVa23yYisP4gt0rujtNtC5NeC+eeug9fFiNGUDNP11sldc7bSyl5Bvj6JqjXaVswmFznPKnoHxF7ySSpqfSn7/+ocWIhZSzwpQvHWE7u4Xml+3cKnz6qXHBhaFz6f1prGDbEsRJ5WV/PL6Jzqc/4uT/8+AMOMdWWUAACAASURBVNRf9TACpP2Hn44T7Zs48Zgj2i18D6rXtF4Un0Q/fh6jJMQtqbzrV6cOwI8Wz0jlutWJZKgVRmmS95QF9DFnHol2jDhFPRY6JOk/cYxHN6jjnHdZA3BV8uVmUleVYlyQ9U/zIdE4JJ/6kLIW1Ez383oxbz0aU6b5keA03eNy0rxIjko+08Dc//yZl9K6aCtFQwZ1FaXTVA8xsZCws/9YiwJSmala1tQs7gCGqR+X4755+6D90ZwMSKSybpVGs1cp9UqkXhG6vJ5XyU9P1/P0SgGp24O9IHZqlwWA1KJoXjtlpKOJcTPiYbabEyGVfABsCLEOkPgMi2vLNJPLm+ll8uGAtO/YwvGUL5tLzvJxE1+1jo6X6X3Z7K4PQP3qnQPWx4tn6XXe0Kba/nlDMOFJLSghHICnIRGHzOyZIaNUe6qp52rmH1tGPknQttTrwp64daSfT7wACkUk+dzzKYpLS1Pmc8+nuBfle9/9tR+YnksFojwXUZn3gxIgaSwk0Wmd6ayG1KaJR1WTpaXyc968c8DlgFTmyVVaErQkbv8fhFc/dSv5AKMQuUtBF3KndurwEXUZjCtaWe0SB4isKA06UIhLeRH/uL66zFfJ13fttP47BJBi5DFNwQzlMUIVnboldG69EdAp24HjCydiQ0jjw9Yu7nuJ6eTW3MTAUnzbqq87keOD5nvz++33Zp9lZxNFKyGKnZ8YQvyUEUbA8IeNQBQPRKsn+lvGCU4XUUb/sMW3Sv7A+ocwdJeDLuh6uQv+vKlMe9f6GRP6qVPJV9I1R9Py7l999j/1o89B67iNoQCew9jZO71AjyJyAQEWAWhS12mR8owugS5TOePA5nrOlbv7wfvTv0b+JlMbdUCEJJUX3VhL/sLxig11XmqmR2QtBochdXhinoaE+rq5BcUAjDpFLYvyJVZiJX8V9G/D0Fns9kDPC8noIH3syvRazQypZoCEJPFwygLK2K6hWYio5AtgU1L/3l9vDCBBGoeEsfPgnYWTpimZ6kISIal0HJLg5CZ8G2/ePgA/WnjWInlzxJw5CEG2IGZWKtWxkKBfxicLM6Mn4susKdrJdXwr+YPrH1gwtJa6XdATTh2JOotpmZ73pSIOZ93oqxmTtIN0JT/bdlH13/7O038zqLXTT323RqZsBJCm2ycLzblSaURYvBGGPk1vHT8EiUMS52pCJkkxrYlzbfqA8/7ss0mHSWwkk89aLifTOBSlI2HO66zOne+LruTzyW9p/dtWYC92e9hLVtlMgGMCkmyASdqmaP1KPtOAKZJF1Q/Xa/evBwCkjgJFzeLQ5DYiQNo3sfhUXjXosMhtHCTR2aky1wXAZzaVeE+dCnJZ8PLUfvfDmV/jp8eajlTm9Py+tPuc5mVjKWwl6y2a05Hy1G51JEfuVvKZ7gbSv2OF1kK3iz22ysZ8c7KJlGepFPl4StFU8lkDyG7TzE+dqGz5z5/6T3aDGxg83qi8k5oJMsUr8ccQnNoxIM20KSAVjUOyfR+GwlYTG/gwFLeaRPO8VDnvn9HUzb1yd7/1zvRnuNZY4jV1137Uq2K8QQCHjI5bPHE9yQmlZgFIPgdZTtJrK/kD6J/s9l/yulaXABLzayMlnkv0HbE1r7T/W7NuJp7eGfWgKN1wdJWsn8n5Yyr5qtM68s3FGtXrv/0fTv2N3Wjmbh3LM2LK3ncbKJqyTcycEgEmDi9KDB7KWzCAJFmmLbgqvXpduza133p/NgIkgWVe+IbuPsebYnONbF1V8kvPfSEGIVjyOjCykICQOobijsMyeErlCGJg2+TMK5hKa+hEA5MYlU3po6Yj5dLgxfcB8VMpk9Q1lfxy+g/+9PTfhDsaRQzaspiTSQ/RCnNqH5hZpCd/EAuJWjqChcM5ZMYhKRHZMR8+gmk24RI5tbcm9lvvLySAhBGkoxrZlUCOzRF/4mjLo4bVyGzlmvBS053GLA3R2JX8/vQPLSfA8+0ubDOndno7a2KJpn1A2V4OORJEpGVSkpLkr0q+sswjzJ/z9B/+2enve/GUrSzmmKZ4+Xyc2Kk9s3gqcWoL62rEpOG/VMS2Qife53Wo6cRvuGy1P6bzgf3e/IPwnenPxTMtqik2kEKbjJCsg5H/hwSEyHKyHZmhkY+IhAMAntNf7rmMDzkFl63YSXy4HGDBJNlAJb9//UMYWrPdLha2jvBuoE7D+V60eO9Z1G6QtqX5J07TaU8x7GlTOVTyZTdInv79Pzvz/XBHU28h5TituQ9bJQNKQTMi7AjlTu1XG09fwNh5lwAS/RXNb2TqNHn5k0SkAqD29t0HwTt3P6dbZcvqmPIYKVJKTqQMFnz3uDqWF6tfyU9UG7cdBSSvi3tegQRtZdd98kfXchSVfFlfMvYQQKqZACmqOMBimrGpamHkQzp4d+mZkM/x6TQ/gFC45hzUcjsIoNr7xHrkvshXvYaX7+y335v5LERRAKQFMT1COzrqWn1y9ahrHXzwo7gpD4Ev+ZvzpeoXfE6V/FXQv2WFYLbThT2227/63b8aQH9y4m/g9nrhiPtB3lR0nlNAIhbSB3fbzyS9KPnLcR0QSP3LIcf/peTbAJCjiGKvvAMcEEh0+nq1a7MPonemPpd+ocgzQKZpZMpFfsJZaxRNYh8Q2TFL/U3RXE8Z/ZJd6pgGR4r1jJqs5NOJchn9WzAkPiSrG+om74P02aruOmtgPQFJfDW3FjJAev/uUpwkjROoLqPQZaskyA8gn5hZUZnt8xUNeesIuc/pdTq1rkw9iN+b/pxuSUfjDopYmJz/aTNcv1ims6vSS3OV/KTFlAgv7eeBIURgodvBnSQwUgkNy9j/zLStxpKl42dYi6p8+QOp24kq+XJTmfefy/rHf372+3A0tTtaaXdTxGPKe1QYTt2wzgGpQwGJnCZiRQGQUjoShSWlE04dUa/jDqLQSeWOi62rdx9Eb03+esze7JyRngBDBFMn3WpwKkXHuZjkVPITPWcs+ur0TxNRLXY7sIt9jjwpFjiJg2GCollBZLUqcYzpjszrK8epx83KESj68ir5igoL6h//BQGk9ZmySRYSn7K9Mzl3FoIoTqQwnvVBqMzcrGsTD+KrswkgSSwTJ09eWFDhJynms1YsMZ5loLAUM+Fmlk9yas+1u4BO2UxHJrJyNXI+D4gSelNKkXLllXwExc3Hqv7xt49/335gdN19ga4ISPwrEoEJAyG4LOd7VOvl8SH38bWJB8HbM8+p32netfgoujhIau0VSKMqGkzqFC3rupKfaIDrHwOI4EKvLU7ZVgHCKxYboIHw3z31fXuPu+6A5PgogN+9eNFtjR05o3NqA5eYNABQw0ZwbqtOa73zGwDHFeuRWqJLPADg2tw+6+3p51g+7Iw5Am8UhUTdw4binNlRiiMhbxJb6E+gTlhkY+WV/Pyun6F/MmUD816HWUi6H910KCBZBGW6PDK66rpRio88RUYIIrySX0j/4Z+d/b49UltlQDIFCiTlMSAtPnKE5rV2gAsCwXmUvk73lEDofg4NpGQFcrm+i+Jpr4l+duPXQMfbo8Mc0ZQ0WkLCJlpRCu/nsmNThiHDZxMXV/KZKrKmzGwQICe62CGYbXdxD/lJDV5T/VfVfN79PKw0yanky4daZM0bOOJbAP3ps/+3vXe1ASmvDQFwEGYW0vL44yyvtTiARXFIIkwyeyn5oSA9pbOE+CVy33Qtwe8vbo/jj2dPwhAnW4Mj7GBr+UyRZG0/jrpV82MLz0UTuglRvNI15YuSGAXbxiT9W0pdlXyqkuL6hwjPt9qgm04/klpei0eJskCkAxgxpswwbBmX3yr5ImBBC7bRwzsu2d888XHY7Wqj5u1GQ9p0q9Ll3Ve/M5FeAKRjAiCpEJR1zdhjukMj+cajSV4+JNJJHPsF3a4NX739OJhaeULYQpnLg2gndlLS8CRSIOyDi1ZwWMxC4liC6ikamGxJIScmldvkXMln+rcgDNFcuwM5IOU58TTYoU7as/yDYmCrlq6Sn30Wlag0Cwd499BV8JUnroCR2roEROo+bDsMmYW0NP74s3lfPndSk2ht7gziUdmJ81vwEnEco5ijD4zUypxpN/Gl2yfxXOcholG+SRJCO0YKjMMoTQnxDMnu55BaO+SMXGH/DrQAtYLihCXJ1kt1nxMEpD4xv9jTVfKZfvP0jy2I8Gy7jQULCZJgVsH3o254TY2WdPBIJsp0/yKVzVeAo2eJBxMZikgLizwr+fn6t0aHPgmeO3TRObmdpfXPd/UwFRcNQyqRoC0CJOwujXcoICEQQKvA8r9KZ6o3SDl6f3o3emf6adD2drEvIg8yC9zn3VXgpV1yJnScRlOngCQ9yWaWTwIj51ptKARGFlimKKxKnRUkegR1BlEl36xeq2nPWSf3v4aef3SycCP0RdhVajWMXOyQ+pCwO79//jO6vWt9ye+jUtbeOfz6xMPw08UT2EfKm5iiV/KiWtL39YnZ+ItEJ+IaV4NMEw3T57A55RMLCc6220iM1Bb6QvYMSt9myRZopktycANvK+b3Y/YxK2bJ5UTfoQhilXyexRN24diO18M/eOJ9u1Ev55/o49suU0UCJFrRJadPJAGSGCZO61S5srdEvS9dc+e3kM3EdF8nH7dCB//i9lFwt3WEHD5CU47IMzVmRFH3dOKgptfcYZ01xJLK0X1+sKPIhzKP5PETUCr5QlejusMIzHbaxIeENI44FRx0HbUIjTBMxM2S1IsOcqjkp4DGInFiuxvvgC8+8ma4f1v89aqgFHZ7heYiefXy7vN2FOkSQHpoWcjaqFlXoy6gPGe3potJ9dQ1OsnJJFQ2y0dT3WHwy4mnwFLvoORDN83nqP/CNOfKK6cQx55L4sPLxTY3tOHWkh8DkoDfsfp4A4vTrIQuKc2zb3WAJPY8XX0d0Ml0m1z+kHMLPnfotfD4rqVEV3zCUXxKVcbaSdOa5CTlzIeEsTs/HQGS6nt2HBmIVEwhUiX80Di1CU2qnlAgAl1R+e/O7Q2v3H0GdsJR3qlpBxMcqNpy4uiOTH05VkZWn8m8l45vECy0mH4Ly4cWRGC624ZdL8j13USz4BikNLNeqkrBKuXIRttZiXEkVnAZ64rGwQpNrj/jbxPIr9sL9hN7XkNfPXpbBQjVk5MPF4xDDGOK87uhOK9VfkXkMwsJY3dpevmzWXmNODPV10NX3JRfmXxIvGpeXiWdfBxAiF7++DF4a/E4DnA9eQxMfQ3Mx8CykrBrFhEQeSPoKhwDErICh+iBlLLVlawskdUhumIT/fg+ILLal/a2b035zIe00oY0MDL6RYCSrK6p82beAukBQQ6rlu9z31KCYxEfHXspne4WkQ+hZ4+NvoG/evQdd7SeOz7oLB8UxSFZStyRjna1ynwOSHPT3c8mTJP+pEZqpzNKsloWAQcnOZetaD1Gp/5Kyl/2auGrt49b0yuPhRHoxKZSjECK6RKLTLaMxJHd0uNE9VQ+Ijt6Ci71uMZBBVtRPoZWCKdX2qgrZoyMAKDoPExyzNGelbRGnklDKQ0LDFtEPknXDHc03oPPP/K6+8iOPCNltXBk1fiEbt2nFtLMxApNkkZmaPynzqRQFIFNoq/5TI5HYVvcUqIMGMSQ+uQ+p9fxVcOTBpGPJha349cnn0Yrnf1EFrViBIcFCd7TaY74yOmhAurgqYzyIobxQMz0OWYQMKtp68mHAKKAWkhxEvViHVWzOKGtKNKZcm+njtAq8AibRL69rXYHnz74Wu3s/rkCbz04iWn1fgAYjAFpYbpLAQmHAYR2fhoSlc5Ub7XKVe1lyQ+u3t2Pr02fAp43kq/1Mp4Hk2u07LK/+FSbRz6dsk132jgFSCb95LfO6lBsbvnYhivuE7tfc75x4rpeX2vltC7KtygdAGG9wSykubsLzxWOQzJtbsva9GZaUIs0aIpD0iq4gHyyBwS/+snj6NbyMRwiN17+N1lBiiA1nkU7GyCFGTNBkeVWkE+ipPFMpwV7ybZqrR6JYopieMH2MgHXZpaPAfThvublxh+fugxH1j+Z2uoMFjIXCZD4LRGYdE5rSpdaDSOuXSF+CQRQus5xfotyVlM+mmk38KXbJ9BM51G2uib/orAl5fy3yBdGs+sZ19sYI3XOFq3i8dPCyAdBmRuO69lM8qEFUDjVbtE4JKIX4dw7Nh22mDrjqTNfQuObByP0ofdZfURzeif9ivKJjsNi9wOWIz3imRyJvonlE1WOuB85//ahX7jHx9h2D5J7syfHD9l1fdBjHh2/n1dfvZ/Ht8hzenS3P1llm1l5Liv5iX4nmnAYAE3qn/5l72BLzKa8nW6Dyg8+nt8BLk+eAm3vgWR05se1RXiUWosQ4ozot8Lp1HKa+zc2olK+qGiJmn+Tm1U+3cs22Wrjji4fEqI+OjElDEIFzctUt+pnCrY55MOmMwVP7n+19vzBqUQtwgJzptnSU+7yeqZyE7Oy9JxPvvzQrUVTtpmV55jlI8cdOY4DAk02CUrG5QhIROhFpzYnoXwEyGKp2thP4r/G8vGlu2PhezOnsI+HKcTEWw3IZly+eTcJciGbEehGXbKCFlk5JHZA3JArxMoIlhbb3EsNBWoksY+P1+Nn3G8u+RYGMystIABSDB26hWduEAkxRCTMPu4YhiV8KYCIWqlRfj3N97NZ5GMLdsCh0V80v/n0B5mYc5/fDF3MAGlhZuXfqK4ZvoKWFZ8dr64JiuCrcaSI3FevdXwJ3XrJRz1oha9ePxreWjrKQzZ5KpLUBE1IXSLO6+K9t7qVO2jROR+bqgnHLikpUaQ47+je/SyfrLKFM+0W7gip+TCiWf3pSmbBH2kLHudlsoX4iqm8tV8j4z6XDyAIrb0jV+pff+JNJGz3KKjK+47MC9tsyrYw0/03ydMn0IBDYjioeY7SppGeLi+Pki7sm9pM8aOspXw8vTLk/+LuU3i+87B0aqTgcU1tutW5lBA70llMHKftCUIIQnJfDZCRpzH3k3xg2QhRCym97E9CRbO+DkjCTrm1IxJyK0qtz91PvF6O8/t+lA9H6tedL4y/ah3ft3zfIUufD+w6IbOQ5idXfoPyEDFCcQrxcACy5G5Mb6RuNeEPZixXt54Ib7JO8oP353YHb0ychr1wF7VslLQj6tAuflnilEvNhpWZtYQCWzoA5n6WT3fiT3ZXcKcbsGkVQ4lUTCJdCBDvRG2uzzmc7BNR6phmdGyh4f6VDxvOnHtszyvW7xy+k/Vdq54j1UPD65o8RX1iRlxtLeQngDTbpYCEgxBCJ0mEZnpolc4OQhhq6pn4lS1Xn2O15RN+wcVbh8KP55+CAUtzwgEFR1tGMv3aynwuNqQkP3gCQPxT1a7hRUnG7jv5JP3dVGsFdMhuf/YjkcNi27HMC0U2k2cNA0nrqMn12J62JBHE/SQf2lbXeXj0YuOPn7xm1xs4z3Xc6ynxPRFC1OPdZkzzKl29bs5HJLbVRshHIYp8SFOLn0dC2hGTpZQydEwWVVSuJgmwYACRJvDSCgN4L8jHnZ4TvHr7GLq79ARJc0Ic2cwXRFahE4crSSBAovRFK4j+zZ1HUcQwTYbCpxV0Wsc/VJYWRaovXFhR/ftKPsQYTbVX2KkjYoY7UTE6VxLbb8j3HeYDVhZYmfiI5erwtsHysYXsvc1rzu8+frH52C6ToTOoQXNf1I8BaXZq8fPkickxfiJgEKDQJdgldGK5bTvE8xL3FAsEEIlxSWSaJ/xUOXQaeA/JD++sbAt/efMUXuiOmxaIpAkXzShOjlMl5lTiL+FgpPowmIWUHL/K79MwGw5g9BPF0aZfuT+pC+bWPSEf4HC6tQw64l42/tymJf71+k7uTflwuHbT/syBn2/7/JFV2+4R9lhyfmJlrZd2RTmDyE8spNkWBSTyk4Am441MdGp51jVnz885vdfk43cnH/Demj4Nu8EONaUtBSSeLkloenHHHFn3iYErXvxXkgpE5VQXIr160KXi27oH5eNgiji1A1+NxNZNraj6lL1nPCkeT5LH+wdPspdaOFBGizipnlJ+r8kHjrVkH3vglaHfO34DgOJbK5g+ytJzLZZNMGL6+NdOPgqiOKQFDkip/EdKPiT1GYvS6+g4L2kXr5p/aePlE+ut98qtx/DH8ydRGNZlJ20y8iZ+IflrUMsTV68u5b3KL2+Xxb0lP5hcWZGW/XXmpdCHeBKjGM/j1TOGxrRc4EExOTl/Id8AuMfkQ9vynIOjr9e+deKyU+svLUj+S9+/FCiIfEjzc61z6mvoNtnqNrVm1UvTq2EErDafsom87jX54UK75r9y6wSaWD4iHI1BH5l7IZLnZ+5qtdxEl9+F9Px4vXtFPppqLaO2bsqmR4YkrxS3K1NrcvmqkShM6/8bK5841+3djXdrXz7xWu3IDvVcj5LvuHnJEUI+PH/1ag08+Fg8ZVNSQBZ6exYAaYpXUlnk7LSVU1Dec/LRjbnt3qXbp8NFj6Y5iQZtelxS8oElS0lp74U2IEmYvpCkluoHqlk+FzTDZGysfLK51p9cWoHarSOFmnFTEllNZ8I+e+CV5rmHpzflC67iS4XEQiKAhPc8HFlIebvKmHQbOCDU7F6zHQeEmq0mpvL0u9w/8r1rE/t7V+6eBl64PbZUyFCY5KmLXy9twZhasTglcYozLsKhBhssH00uL+N2FKkdGysKJGuMlRiidQZOOlxLUZ5iVaXwfoPk1+wV+/Cenw+ff+LDVfxmNzWrBJAefIwCkrgVRNzyoa6q6baEiPSx5aBsHRHL+d/q1hJd+b0qH/YCy3v1xuPB9bkTGEFXO0ejmEH+ZwAbwVkdU+hIhXVKjJLtFVIP1c0R11F+MN1ahhyQYvdPEm0lHlFENaI4tfMmbCnnNn15RNMQ634Mm9ZXPrZAaO0feX3494+9ae1003vO64bNsD1lxZ/TGfek9hkKeQ/Lp5tr6ZRt79gXEE4CIu2M+KJQULFIJ5Xz3uEAIJZbMITQjuQIfDAM4f0s359eafi/uHsymFp5LD6iO/bAip5a5bMRYo+4YRVHioukSlgPoTXSxeYaHWLo6UT0p4tHXGX5wd2VZdwVcmpv6vE8/XLWaOPDoS8/9op7Yv/KFnv1VXndEOEEkOJ+zAGDOptZOtbcn22T/h4vlqh70HR8YmBS5JjKM5/hHpHvfzy3s/f65Gm81N1nfF5uFRhyJOXqWrIqSPQXlI6rLlx/DeQH060l3CJObTUwMuOpeD4jIa9R7juIBNp66ysf1q2Z2tmDPx368hMTpZ69IpY0EAESroEHW1+odLN6Gui9fnfcf2f6GdALaZoT+hNnFSa/iFQe4bs2FbjwweXNc9ZRfjC1wnxIqp9I2rcnPJB6/hDfg5a5XM/3qvE5oaBYky7WSD6Gdsc9vOvV4T955p383pOfD4jxyMtvlLepw/Qk9778kGwdOX9VAKSicUWZe0u4QqRESebFu77ikAxzSnOipnWXH3o9u/ezT4+im0vHMUIs7SEmyZRUNMq6TncuOT4ycdgqcZNxRal8jeX7ZMom+JBST68GLEZALYUUkxxSvFxHHx2pTXnzE1/y0YBRrJJ8YIPQfmDb5eYfPvVLZ++weIZz0Sep6DQaCEM6ZcM1vL/3b+UYbQDEqROvS6ZeeVMq9b58Tfoai902lXNZm0U+mvManZ/dOIVmWo8kbaAzkVgZc9xa9Lx6NYOAnCZF/sL0Dl/VNONPsDbyw8nWEmr7WclHpW4Ypx2hqaOi46QMn6pEq6QjybqX9eX3I98art1wvnDoZ8NnHl4ohCp5iRn79E0Xkk2I7iP5CiClX7Hf3f+FlZVDuJnke+9P7+69PnEGt7w98mubbBslwZvyKUuHWoqJ4LLotPpePfnBxNIy7goJ2ijC6o+fKttHCgdEqMngVkt+3Z2rndj70+bXj97MenarVpMNPs8r5octqxAD/f0sHzuuRy0ktLf9RfZ+pl1l6turC/HRfccWpkbCLjZaXmibriBIR89v35/ySUR69+LdQ/77M6dggJPDhzO6bPbuB2XJu8weUvGzWSX5wd2VJdzqMgvJlFw8bmH5YenivBS7FBFKfqaIQF3ll5QUXayWfAt2nbGRX27/dyeuoG21nM0oq4QqW5QNAySMa2i+RwFJXA3TTZm4nnRTtyJTLFN9sZz/vZnlo5WO2/nZrWPhnaUnSbwDeWckpw4SuiRDCysGDQxI+hPdzyIpUhDPEBCfJB6R6iuxDS6rIx9NtpaYD4nlJY+/XnJAMMcXKWoo/X3r/f1mBEof1hkB3aDyIcTW7ubVkW+cfNV+aFRz/KFngI1aVJ53X62u0nM+JnTK4593/96TXyeAdObiRffQQ0d+C0MnGSeztt8X2eZvMGQwEHxQAh9aDoTEcFtEvn+3Ney9duN0ONd5iKqM5i/TAEe0qBZPW9TrGNFjOKeeYUaP41X4ZNoT/ZVKWzSYfDS5shi0iA8p2VIsd/v0MhgLW8wr51z4AVP8Wq6XgNlg8q1t9VtDn3/4J+7nH5ndosbKhrx23a2z+e2X7t4d3uY0j2EM9+U5m9mTpjIipRKXiLm4E8srQRr9/Xxn92aU37t6d5//5tQZ1PF3svcT51BZSc2IE5z4aIgTXDCxUokZDXE5tJjtneP78AaRH95dXsKtIEjSqESJ9yHiG/tTHT0VISBSSK9uYQBlf5RqKcZWZJzGpZx86FpLzRN7fzb6J6fi7R4muyXP/ihq7+TRbSX5dafekbwHX1ta2uOE7nGAkXQMtdZjI1g4tq2u0XHYsEEoZFiS+PD6dhre1F67FeQT0G7//M5j3kezTwMvLJZnVFGUDDuJs5qWR9MmCgARCsT0ZXxPGWNnONFZRK2e3vmX5KNjHKJknEKeOrncKAcpqalMO/wVBlnyIfSt8dGLo3984o3ajuEs5yUAIA9C9A8e1OU5udNjr2EqN6t588m3ugBb9frsS9vBfNqdiTH82uTioVqzfl1ZIwAAHaZJREFU8TiEwGVbP0gbJdaNDBBJ+9mCU5uVsv+T8kJbTuhWkwSpyNaUrSbfX/Tc7k8/PunfXnkC0sAlAiAsFyW1nbTuFBIhIDYlO5WR1uLlknMmB4Go6SFkjisoH020F8NlAyBlANmG3SKH5u1svLf9K0debjz5YHwK7IY9zxYUHIJwaW7P0PQFyE5CM66vnMHYfWjFewIi/DCGUaxaEEIkJPO3Ar61JIEo+T6Q0pJYQRKHpNKpuSphlM5EHK6IvK0iP5hYHmm/fOMMmu8epH6WqKU4rmTZBcl2UtbD1esI4wCJwyFZFhNeCiXZphI5yYvID+4sL2LqQ+I/RGIX6eEs6Ziq9Ncnbr6VN97y50r+jdjm8DXLh0PW5NBzD/142/OP392COLDxrzxc7ww3wdT/CaG0YJAbI/F703jEtoITFgyV+JnkndRVt9V626J8i9KVfa6ifIvS9SO/+/bU/t7lu2dRh6U5oQ1G/8ec1aqHKbKjBFGMIkUXtTz98MXUufyEXulhEwdVlnx0d2UBrXhhsr6WfR6bqo9Mf5JALNIRUGWIys/qFq0/jXzXWak9vuflHd8+8W7Z9tDRq3E/qXda4zik+02+hXAAnHD6pV27FnX6zAUkXunLUysP1iz7uIXRsN6pHZ3rFo+PahzSoM2fl61788on1kD7xx894X009xRE2BU1yYCGLakljRmdOBDfoqtqfH1fBid21ncMWmoWgQTIIkkKsonygztLi6hFAIn9YqtK3RvC7iodIsv209l4mqBLJShSlA8tELoHhl/f/scnf+nsHaq2ewz6OZasj2o15LT8+Zf+9/9tFrzwgjGeqzAgUfkvYOub/3HpscCpH7HZcZGsa4UhREKWAF5ushxM8U79xkFtFfl4qVtv/fjG0/7E0hFxui0CSsl+wuFMXKJTWOR3EU7h310mFpKQLFzX7zSbYYnEoiGHsQGkVBCDKuNb7A97tPFh8ytHf7Lt6T1L+ZtXi2owb88H59PvZti857h/5FvAWd65uzn1f0CYOxDk9zaNXn4X4/rQQvsYCsOHAFliIz/N2gRdfRPKLSAAl1q+BnFIm1V+7+P5nd6l22eCpd6DxnjKyAYhJ8qS5mGHKCbfPffRZJXnfRJqzrlwoj2PVrpFoSXGoDio2jRny+KY4Z+HTWem8exDF0a/8sSt+F3y4g3zXrroOrwpPnILybcQ6nVHG5N/D2E7T638fl+AxCt/Yx7vwLh70oFodyggjw1sgGw5P5L4QOxctvR9tdwKgXAunLCaR7ZbCwwZ8Mj3t4L89qWJ8eCd6dOoF2yLvUQUfgSbKXH6MI1J0yddhGVCEJ8CS2d86b0mtHbcgzAIJ1oLgWaVzZQVpFAnJT4tIQeUONEz4RS0YLf++O5Xdvz501fyfCyFnqEiKqcBjMMu7s78cMeO+XIV848JLcTvD2bbY9CxjgMUNmVPjwNCvt6vxhspcUhckGhRkQMok5+8iTxNx+5vNfkwhFbrp9ef9D6ZPwHCUPIvMT8NoltNpKgAFklAf2p5DFgUaDSff5xgjgeAs+wERE4wsbwQLPtanLCiEHQOa+RwTHG3PW9n9VBN8SkIY7WOSA8tGNb3bXtr6A9PvlofH5XmNFZNhmLkRSvHhnJTxzfxyftQtoJ8kp+01qjNPzEMpl+A2jNO89RU6KD1XCaE4DzGNlr2jgCAj4AQ2pkHTpbZGpITppYcNuCw2WNEv9Xkh3O9ZudnN54JJlqPko+Un4CrDQ8wmRnq9KdAwCR3GJHtH8GdxYVgSQ9IUicyb01juSZNJpUp1gEB4I42rm/7wuEfN54bX7VTYAt1/IqIasCxwtbKbHPyH47AgY4DH2jKpmuLr925M+QOjx6H0DmYTmWblQ9J5iZuLYlHz1A+143wV59B3pKiozflY9oc8rvvz+7uXLx5Fq14e9f7W/FvLTKntu5nWkTT76Yt/Oiw5s4Pn37gxyPfPPVx4UoV4appoOZgD3n1yZcegKuSR3zVAYm/6e/fWtoNh5tPAYB29Pv2KqAZzegQQNFn1K88td79Kp+sVnZ+OXGoe+3uaeyhoWQ6RJ0+2uCgyPMd+2tIyKR4UkrKg8SiHWloJeUPIfZvL8SAlMKfrBzeyukjWt+2VB8DYNu9+iM7X931p0+9AXbmbfcAAOXEA+X5mtT6efRqX9ps8msuDgMwMvNfRsCc6OMb9NtbM0DiD/aN+c4hC8PjGMG8ZMEl3yU9KVNX1ThDU3lJgQr5vS8/aHlO++Ubx4Ob88cwYnt/yKqavJGWQ03RrkA247I4aeLQZr5uVjeYWJoPljryllhFa9qo8TINAQGu7Rl5e/vXj748/OTO1OpN3k4v06bYMo9AaE2LZZtdvoVrOMTB4tLbQ1MXnmfbPVbzV7QXDiTzHMbO6HzrSQe6j5EU7RZKTjNBVpJ2xFSuCid0aj3xmtOrdGI5/3sryPcnFra1X7l12p9pPUzem7hi+DYNHhZAYSUCGvJ31ko723CS5Enh1+Ht5YVwuRdXJQ5oISgp2lFbcDOspsdZw7Vbo+ce+9HIFx6dKtohPWUzbM0IJUU5lqPbTPJtC7XDlZnJl8bH1+w48HUBJN6E56fwNmx3nsI22C8uh5FjxsiBPqJFw/+WV9NsaXmfZ0Ex5I+kTm45DkrwKUn5mLaG/O61qX29NyfOhi1vV6JtNjNjlk4Udy30CnGmlFhEUVPRcIBkYhfeWZ4PlyMfkilas58e58Dl4acP/Hj3n516z7jZvmx8UDlcSajLyskzmco+xwbIRy72rXZ7yrTdo+wrZNH30z0Glv/7y8sPYM89BWyW5oTEG8UWixDxTSKwCwnTIFLiU7JpJLnKh0WWM1TaavJXXr15uPvO9Cnshw0SSEQtHK4gxfIppP+IKLizMheudHHqdCO+zUxgpmaY1Z6IZFt+/eEdv9jx7Wd/Wd+rOQW2zMNVtKU1gDBAFqzNvrQNzKymn+ieAyT6QBjD89O9x0IXHAMQ1kwZlZKHV3w2sumkDxXPSiQnxEGZMzJlxCfc5/LRku8u/eSTp/zby0dJmhN+wK2us5i3psQZlWg1/9bSfLjSU/fxsixwqZ8xPSZNW2nvHHp359ef+MnQUweWxapqPI/qzTE5j9cqDmizyg9AuLRvV/Nuke0epZEuo0IxC2Q1JSq86CEDB/zj0LEeQSC0lMhGPU6Znsc4d0tFTEYclDldXiLMPD3ch/J7n85tb79880ww2xkj8T+SecPNGINDic3YopuW9f+3d2VNchzHObO6e2b2ApZYAIIJQRRAQSBAHAQXEEBSMinLZgQPQIIl+EXhCDvC4V/gd+NP+MXv9gseGEGaZlgO0whKEZJtSmE5SBEXce8url3sObsz3VXpqO7pnj6nu2d7ZueoecJ2Z2VWZVV/qKzKA8z7i8/4ShwgJSku6nCEFePR+Gvf+vS5c4dn0tSt3hevAW7RBufluY+ezx7uUWQvthyQ3MFcXFjYznHkBCGzy1A3U+k2d0bONXzzEDy+RLd7OuKYav6gX/m3y63pr+TQhf0vh03+yu8fPl/93expWre223PiS4nr7YP8YRzNbZPzLyIwZ1cWxHIUkOyD7bjrtYZ5yCRfXVurHN79y51/efwLZgRLCRW54BWveA0wgyxDlB//8yTmDvcoUqc9A0geMD2t7hWMnRAMx+TZThb/ojBd0kYlrLg0umGTL+qcVX9199D6jfkTwCk5DLRxmB3WZ312cYFLQPKckNJv1GRakNLebb+d+vmR35T2TW3Ky9fuT9GHyHm/tj6Tb8lwDzQXXh4be9xuuEdeFbWi7zlAavxvy366Uv8ucTgsBITis1qc+CSFjiQ8zwtQLn2rW73Y0JU+k8+XNsprn905sTG7dMjLndsYvAcxKK/0AezdTeNXn1uZ50sxFYMSVqA+Wf564t3Dn06c2Z2tCmyRK1/xAkR9Zf1p5eFmwz2KVGVvAlJjhH9FVFmcXz+uIXzbS3PSqB8XNsVcEyuQ8tZX+jv83FViUsxb07TTnMJpvp80FYdBvnlncXL1N/dPW4u1PYE4Wx6NwJfgZM2tBgDJCeD1Zw+QfyPgiD5fOb33010/O3qnyMUcz6vPtiyFKyQ6fqZRjW0rz13GYsI9iuxyTwOSZ8YtLe0wzdJJprOdAceipEswbysTPLS2PyPW+EL8fkhOwETzy3FzPEk+4du0wN++qYgLAg45QvWr/NXfzX5r/f8eTfMad6rR2OkDosuwfn91nq8m75BQw43ywalf7fqb6f/VRo3MeZMCksIpvtz9c97n7X5FeeUk0W+FfAM4jJcefwDFhnu0O5S4dn0BSG7H//zZ+gsAeIKoGZ9lv4uxodDnAU4+z3CXV9L7tHaxyh8C+aKObOWzW0c2bs8fA97MFmp7fDeyApgzK/PW8obMch3MuiTDPfaM/n7Hz1/55ch3dnTMy7fID2OQeMnLU5OVni3/95XHV374w8LDPYrUVV8Bkhy4THNirdYPI8BLJHgjYVLYqPKrKOBwFLOlCbdtmbgkYUs0PPLNp9WRlc/unjQfLr/YzEXkbJdq95ciZ0jaxOjdiT878B873t7/xD8rwmzkIzLCOS83l1JRmE7x0+hNXdB0GRb5Foe1qe0wF67uUSSIFMmr7wDJHfw5otHyivUKJ+GUobZXoQYgYmynSJ4fH4D46cPtk/h58kJBX0Mkv3pzYar6X/dPW0u13a46aneXFviyswHCkrE4emzPf+7665PXi1ywilc2DZBO9bJVfnh5B8ZW98jGpftUfQtIrqremVvZZYxWphkIuwy1a3L5zbRWz2SbNJPOlSXp0ky6YZO/8uuZ/dUvHk5TnY/W7y3N82qtXvr25K93/e2Z/zFGjZT0et1f8IMuUYZ76Gb9yQffGH/SrXCPInXa94DkKuMnixsvEtOPI8ky1HEu1y5lmkkWdsT0mxTxfJ3qKul0Tg8GTz5fM/Xlz74+un5tfnniT1/4dPzwHzWTdW3OAsu/1of5Uo3xxW+MdD/cI/8kJbcYGECSQ5z+/HNj74vHjwLRIV8h6GTHpSI1KXllDR0pWq7Lb4vlc53d1pgIZA6kulnIGsOSETwo9/gG3dQwlCN7KORrVKVt5dk81T06tQQ3y7eQxbLZThTd3q62q1uvcrK+iRqLBHYSF964/e/9z90+JbUPt8tC55l+AyqfIbvNLbFW9HwqfvEaQALL0kpzH29xuEeR8zOQgOQq6OIq7dkQtVNokROfJb3yYgAKHIDw+SH5nGy4z11GYwDhvz1LMEQXsBB9OcsGWL6m67c8QFJ1yZwVULQJWQfQDBA1LD391zF4DG1W9ygSRIrkNdCAZCuKCM/NrxwCXT+OQqY5afz8wODbsQQAy/+8ldbDQCUdc/xnSnF8BlA+6nSLmFZIsvciF/kg8WKmWDYmK7OXEYvKxttT6hl8QGqo+yJRaaMKJxjxg8R5wM84rdpPu+/T2rkrIY2u3fdp7YqWj8huEdMVIHXgE9d02NDLIIFooPU7NIDkrhG72q5hnULAPfKZaBEawjQt+N7Jk++4O3kmWfPWTNK7Pz9fm49vkQbKog2QfAlIjJN9hpQ3YqLoiIxBkQ9E3NJLDz/ahk87gHM9x3LoAMmdgR/PV/cJozSNDMadkt1NyNCABUp9ezsJLlD4TC3mmWLNvUjwfTB9ipMq15ETphsE+YJbtzRUO6QivnJGRKxSmocReHgZI+m6ihDRkzyGFpAa50vswrP6Ea5pRxlE05yQEIgseksXnklJJ3x0WQJJJI9WdPJ9v8lHpFsap6BJEUkeU/B3EN4Khdn3oXymGysTZZjtl3CPImd0uAGpeb40Unu2/irT9AONIhqt6wAlHc60KlHt2XIh2y3RlmsxzT0qn5N1yyjpgRzY1IhZa44m71mscw+BoZi3KF9HQjpd78pH3ajpZmm238I9FCAVqQEfrwvLNGVZte8hkhef5Q8VcUlJ+NKY2DuZ4N/JdG71k+wejP0kn3Prlq5MttyrkwzijEqPPhiHvgz3yD3gFg3UDilGOefWaT/W6qeAoVeG2jahZIgINHN6B2yumIgQD3Ya7xgEE7u5orOmyu11+ULDr3XXZMubpyhpkYZNrjQTzeXTB/Llbs6sW8/mnhuZ+y1i1pEV+f33HC8FSAlTItOcmGvmMcHpKAnU/TFomiYLVjYbOnnYgg9k7UVvp+SrO2c/05zajHHv/TFxtvnosW3y71X5pOk3de/av93vKwlJsn47/dHe0o01LMPMIIR7ZJ2ZLHQKkFK09DbR2NgGnLJMc79LGg2xldWbogkQ5W1d8PYsufpcbMJJX1rGVnzCcpr97K58AuOmzmCg/WSyfFStaDiBKcZh9mPc2uoemx1Hp9orQMqo2QsrtFswOIPEp/xN8kaShMWlRaYk8Xf59JJ8BvQ1hW/ZMuo3LxkzgsG2wiwmiDdrP/LKl4WgTMt4/G874dGghXtk1VkWOgVIWbTk0RBeWK4d5Ki/SggVJpolwF0SN2e3vLJ3Ek8LcF0H5OG3Syfc3N7S0TKGj+ev5HMnkHRp7bZWPt3sFiDlmrYtJibki5XtlZlBDfcoUr0KkNrQ5jSR8fyy+QoKOIIaYzJLQFy0fxusA02y8s1Kl7c/Wfk26WIAqdP5kNJu8bdQPmm0XtkoPbi8e7DDPfKuq1b0CpA2oc135mmbodXOAGP7ImzSUnnLBq3yyHk2WUwH87RLSxmePV9csyNJ8hFvAqMUP6TWCk/yI0r3L3L4ZqVL6kUh8mvESa/NfrRt21CEe2ziE4o0VYBUgDbfr1b3Grx0hhNM+j0q5S2Z/zbNrR3kmHOND8hnkhEIDJ+Nx3mKSzo/XwaAAlyP8ubhetfl43CbbLKUli6sJ9qOEVnzTKXvbePbUoDUhtJim8g0Jwv1I1jWTpIQZWcDFLzlCp8BuXySnrtnUJ48edbkO3tK63q35aNh3KCa6dyy5fUDyhriUVQUbt7oW1fZCe3QEsvLC+UHV/Zj9tK9aRM4hO8VIBU86e8QlUsr1jQBvUTAHP26O6JGaIl91B1TJpExub9qxs4xEOiR+ehturS/fXy6Jl/DGwZzQkfMULy/EQ0VtFWTRpeMP/FvmjgYfN8x+YJq1njp/ieIywUvpaFkpwCpQ9P+3iI9Z1TgLK+be72dkMwi4NvuOP9kbp3FxpsmhfPGOWsSvvt9+Vz4ODGNBd67pqFTlSnIr5PydcQb2ACksFrzbmyKnpai5RMBhzGY+wBUuEeRc6UAqUhtxvB6d51eMCx+Fhg4ZagDv+jpcDSPki/fUgz/cFk5lyTpeSfl60g3unXtn9cPqKhpllVggfj8wmRl5gpiT1eBLWrM3eSjAKkL2r5ExD5fg2Mo+ElsnK6g5sTEyfi0Vl1w6Vza8N/htnF8sz6L60ce+RrS9W4BUhemLSICK8aKtQAPPnoeq1shfxhkKkDq4iyfm6VRmLBOI9F3XbOqpXh59pQhHxOgQKD0vE25h5pTvmZo171DbVdY1sPq3J1LaNDuYXUL+URUt8ZKD1S4R1GTlMxHAVLndRyR8M4K7TIYfw2EsNPoZvrF+TVFnmVPa5JJpp8og3wGeB0SzpBcVuEQj7DpFe6XS89C+ZBEJM+S0zIrP1dOK3oZ7gHV6qMP/2H0IVxq3i/k1p1qkFkDCpAyq6p4wvNL9B2A+lkiHLO5+50YQ14sAdMJgmlQEDiSPy1Ko6vh55552Aq33GG2IZ/p4rqohTJGFq+2rnDkIBZGZ8oPLr88mNU9uqLENoQoQGpDaUU2eYtIn1g2TwLCCVk1zuEdj0zIASlSsjsOQZz2yDmSfVbloAsCtACucCnwKN80+Sh3SLzhqZ3mh9SuEvNel+U04VBQdWm9dO+KCvdod4Y21U4B0qbUV1zj80+eTMDIxFlC44B7oy93ODHuSiE3AXkaJaua+G/jbNTy8i01+ThbI+lMQEwjVw6Bc7Aefp5XPgO8lmayFaexYjkJAhMFzAxLdY9itVccNwVIxemyEE7vrtIeRvz7ALhTOkB6v1Du7bBjpAsuAbKwA6WdeyD6s+U0XoTb55PPrgGDQCxbIUrpIBMCEAbCY+1fYO7yX6hwjw6qOhNrBUiZ1NRlIiK8sAovcYTvAYqRpvRAfUv7ccBB0pfQLQg90XaJSBepIJdUhcDhEJAv2DUSjdCRhgDUg3mLyHLyFoWfJ2m4XXqXXyv5wqot8W3le58g1ro8w0pcggYUIPXw0rj4JZWs/TDNuTgGjDE7BMTvBuAL0vWG4b73v8v6LE4XYXkt5BMX1wCD0f69qF7BjPXJcbj3Tyrco+emRwFSz01JtEMXibbXl/kbxPCFuO7KM6BA8YGCxpSVr0tHIK6BCAGS7nYmzSEpLQd3UvtQu7DvtE8+AlhAMPvhGDwGRO+MrSB1KTYFaEABUgFK7BaLH1er+4QofR8In3NkJiVdcnsk36eVo8za+3RHJLlDQkPvapCpa9IlmWj2c8sEU/AnG5OVByrcI+t8bw2dAqSt0Xv7Ui9dYuf/7u+PkuCnAdFOc+IUt2xc7Qduz4L5mNzbtGhmOLc7UQclf104Es26coGqKa58xKvetX/7Iyy0JSItVyZKdy8jrhfKWDHriAYUIHVErZ1n+hZRZWIVzggQL0v/oniJEkB8deQcujhTJeF5uH2EX1AssqvATeeWLdEPKW+ZopCpZoZMtCR2mlGjMbinwj06vxaLlKAAqUhtbgGvHy3T1CjwHxDiNwPi/YncYosIJJh89qG15wOQa30QiqvIumuyhVUu04LUAeb+fRTm1DnRFizITYrMteA2KUs176AG3tugA8yCN4jEdk+MxgAidZIaYBPIpR2i8yw4n7tAhnpNWwlIMn2s0GB+bxnu/6OqAtvBldZZ1gqQOqvfrnKX1XarVXiFhDjFNJZ2rQVZq4pkHQQJuIoMunqobe/zOKyur4MK98g6UT1MpwCphyen3a6dIxoVa9bryPSX/KAj/+3ydMs2+Z/FyfOXd0qjBWRfkXuG1G7nc7TTdaNOHO6rcI8cSutxUgVIPT5Bm+neBaLd9VX+Jmi4xxfq1mQpTbpwMInPlItWLYnvjVP1BMgGJNY41PZIUzdquYcoo/DYBjw8uQNmLqFKC5JbgT3cQAFSD09OUV07v0GHOOdvkMDxonjG8kHxFXT4UJsxWOBlUOEeHZ3IrWOuAGnrdN9VyTLNycg6nEIupgHB81+O60TMvgn8IStMCBSBEt9OdRQG4ivOKXCGhEYols10Ytny/gyNquZY6Y6q7pFXc/1F39bi6K8hqt76NXCeaEJU+Q8E4UH3uZMnyeef1Egz4JRragbXptERiK/ABSSjYapF/IbiTTgXIcORH0wHU6vDgw/H8ZGaycHXgAKkwZ/j2BG+/7S6V1RKbxLg7hZZTiKx/y6zYJoSGfcrZGHMP7i3bIkhZaHeJNFxACohPDIqcF9VgR2eRaoAaXjmOjpSInxvFV4GBq8DwuhmVYEM/oAi37V/HCAJDkuj43BHhXtsdkb6r70CpP6bs8J7fJGoVN2AM2SJk6gF0sLlktUOIPkFcAEbaMHdjyfxWS7BinhgNKAAaWCmcvMD+QnRZL0KbwLBAdcdAH2H1xSXf8kW6xyDI4jcOyS7ORFnuvHgQxXusflJ7HMOCpD6fAI70X1ZbRc5vEUgprLUhbNv3YARAnhnSFn6JTMGWAye7CvDPRXukUVjg0+jAGnw57i9ERKx81U4wQFeIxKVABNp1fmTejdS5yLAl1lDR4jDijkOt3+BuNZeB1WrQdSAAqRBnNUCx/TafRrZvhNeZwTHSQj7Qo4BA/JlE5DuAPKWDUF8GT7URl0PpDshgjrjcFeFexQ4SQPESgHSAE1mJ4dyjmgnX+V/Qqjt8+Q0/AVcR0oUyTskWQWWA8z8YgRmQIV7dHKq+pq3AqS+nr7ud/79JTooSvAmcZh0pTsWnADU2Rdx1/7E4CmV4a6q7tH9+eo3iQqQ+m3GeqC/Ms3JugnTwoKzCFByu0QMAoBkCVhjNbj9yRR2PSVJD6hJdaENDShAakNpqomjgbeJxrQq/DFDOCJLrQmCLxnCEicwSwT3VLiHWil5NaAAKa/GFH1EA3a1XYAfCYB5ocHVCRXuoVZJmxpQgNSm4lSzqAZk4YEriBtKN0oD7Wrg/wHwB2J9dMwwWgAAAABJRU5ErkJggg=="}),(0,B.jsx)("img",{style:p()(p()({},m),{},{zIndex:17}),className:BG,src:"data:image/png;base64,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",QV="data:image/png;base64,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r=!i&&n.widgetNode;r&&e.map.push(e.pos,e.pos+t,r),!i&&e.cm.display.input.needsContentAttribute&&(r||(r=e.content.appendChild(document.createElement("span"))),r.setAttribute("cm-marker",n.id)),r&&(e.cm.display.input.setUneditable(r),e.content.appendChild(r)),e.pos+=t,e.trailingSpace=!1}function bn(e,t,n){var i=e.markedSpans,r=e.text,s=0;if(i)for(var o,a,l,u,c,d,h,f=r.length,p=0,g=1,m="",v=0;;){if(v==p){l=u=c=a="",h=null,d=null,v=1/0;for(var A=[],x=void 0,y=0;y<i.length;++y){var b=i[y],w=b.marker;if("bookmark"==w.type&&b.from==p&&w.widgetNode)A.push(w);else if(b.from<=p&&(null==b.to||b.to>p||w.collapsed&&b.to==p&&b.from==p)){if(null!=b.to&&b.to!=p&&v>b.to&&(v=b.to,u=""),w.className&&(l+=" "+w.className),w.css&&(a=(a?a+";":"")+w.css),w.startStyle&&b.from==p&&(c+=" "+w.startStyle),w.endStyle&&b.to==v&&(x||(x=[])).push(w.endStyle,b.to),w.title&&((h||(h={})).title=w.title),w.attributes)for(var C in w.attributes)(h||(h={}))[C]=w.attributes[C];w.collapsed&&(!d||Qt(d.marker,w)<0)&&(d=b)}else 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t=e.delayedCallbacks,n=0;do{for(;n<t.length;n++)t[n].call(null);for(var i=0;i<e.ops.length;i++){var r=e.ops[i];if(r.cursorActivityHandlers)for(;r.cursorActivityCalled<r.cursorActivityHandlers.length;)r.cursorActivityHandlers[r.cursorActivityCalled++].call(null,r.cm)}}while(n<t.length)}function Sn(e,t){var n=e.ownsGroup;if(n)try{Tn(n)}finally{Mn=null,t(n)}}var Pn=null;function Nn(e,t){var n=ge(e,t);if(n.length){var i,r=Array.prototype.slice.call(arguments,2);Mn?i=Mn.delayedCallbacks:Pn?i=Pn:(i=Pn=[],setTimeout(Bn,0));for(var s=function(e){i.push((function(){return n[e].apply(null,r)}))},o=0;o<n.length;++o)s(o)}}function Bn(){var e=Pn;Pn=null;for(var t=0;t<e.length;++t)e[t]()}function Dn(e,t,n,i){for(var r=0;r<t.changes.length;r++){var s=t.changes[r];"text"==s?On(e,t):"gutter"==s?Rn(e,t,n,i):"class"==s?zn(e,t):"widget"==s&&kn(e,t,i)}t.changes=null}function In(e){return e.node==e.text&&(e.node=N("div",null,null,"position: 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zn(e,t){Ln(e,t),t.line.wrapClass?In(t).className=t.line.wrapClass:t.node!=t.text&&(t.node.className="");var n=t.textClass?t.textClass+" "+(t.line.textClass||""):t.line.textClass;t.text.className=n||""}function Rn(e,t,n,i){if(t.gutter&&(t.node.removeChild(t.gutter),t.gutter=null),t.gutterBackground&&(t.node.removeChild(t.gutterBackground),t.gutterBackground=null),t.line.gutterClass){var r=In(t);t.gutterBackground=N("div",null,"CodeMirror-gutter-background "+t.line.gutterClass,"left: "+(e.options.fixedGutter?i.fixedPos:-i.gutterTotalWidth)+"px; width: "+i.gutterTotalWidth+"px"),e.display.input.setUneditable(t.gutterBackground),r.insertBefore(t.gutterBackground,t.text)}var s=t.line.gutterMarkers;if(e.options.lineNumbers||s){var o=In(t),a=t.gutter=N("div",null,"CodeMirror-gutter-wrapper","left: "+(e.options.fixedGutter?i.fixedPos:-i.gutterTotalWidth)+"px");if(e.display.input.setUneditable(a),o.insertBefore(a,t.text),t.line.gutterClass&&(a.className+=" 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Un(e,t,n,i,r){if(t.widgets)for(var s=In(n),o=0,a=t.widgets;o<a.length;++o){var l=a[o],u=N("div",[l.node],"CodeMirror-linewidget"+(l.className?" 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n=Te(t);n!=e.wrapper;n=n.parentNode)if(!n||1==n.nodeType&&"true"==n.getAttribute("cm-ignore-events")||n.parentNode==e.sizer&&n!=e.mover)return!0}function Wn(e){return e.lineSpace.offsetTop}function Qn(e){return e.mover.offsetHeight-e.lineSpace.offsetHeight}function Zn(e){if(e.cachedPaddingH)return e.cachedPaddingH;var t=P(e.measure,N("pre","x","CodeMirror-line-like")),n=window.getComputedStyle?window.getComputedStyle(t):t.currentStyle,i={left:parseInt(n.paddingLeft),right:parseInt(n.paddingRight)};return isNaN(i.left)||isNaN(i.right)||(e.cachedPaddingH=i),i}function Yn(e){return U-e.display.nativeBarWidth}function Jn(e){return e.display.scroller.clientWidth-Yn(e)-e.display.barWidth}function Kn(e){return e.display.scroller.clientHeight-Yn(e)-e.display.barHeight}function qn(e,t,n){var i=e.options.lineWrapping,r=i&&Jn(e);if(!t.measure.heights||i&&t.measure.width!=r){var s=t.measure.heights=[];if(i){t.measure.width=r;for(var o=t.text.firstChild.getClientRects(),a=0;a<o.length-1;a++){var 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n=si;if("left"==t)for(var i=0;i<e.length&&(n=e[i]).left==n.right;i++);else for(var r=e.length-1;r>=0&&(n=e[r]).left==n.right;r--);return n}function li(e,t,n,i){var r,s=oi(t.map,n,i),l=s.node,u=s.start,c=s.end,d=s.collapse;if(3==l.nodeType){for(var h=0;h<4;h++){for(;u&&se(t.line.text.charAt(s.coverStart+u));)--u;for(;s.coverStart+c<s.coverEnd&&se(t.line.text.charAt(s.coverStart+c));)++c;if((r=o&&a<9&&0==u&&c==s.coverEnd-s.coverStart?l.parentNode.getBoundingClientRect():ai(E(l,u,c).getClientRects(),i)).left||r.right||0==u)break;c=u,u-=1,d="right"}o&&a<11&&(r=ui(e.display.measure,r))}else{var f;u>0&&(d=i="right"),r=e.options.lineWrapping&&(f=l.getClientRects()).length>1?f["right"==i?f.length-1:0]:l.getBoundingClientRect()}if(o&&a<9&&!u&&(!r||!r.left&&!r.right)){var p=l.parentNode.getClientRects()[0];r=p?{left:p.left,right:p.left+Bi(e.display),top:p.top,bottom:p.bottom}:si}for(var g=r.top-t.rect.top,m=r.bottom-t.rect.top,v=(g+m)/2,A=t.view.measure.heights,x=0;x<A.length-1&&!(v<A[x]);x++);var y=x?A[x-1]:0,b=A[x],w={left:("right"==d?r.right:r.left)-t.rect.left,right:("left"==d?r.left:r.right)-t.rect.left,top:y,bottom:b};return r.left||r.right||(w.bogus=!0),e.options.singleCursorHeightPerLine||(w.rtop=g,w.rbottom=m),w}function ui(e,t){if(!window.screen||null==screen.logicalXDPI||screen.logicalXDPI==screen.deviceXDPI||!ke(e))return t;var n=screen.logicalXDPI/screen.deviceXDPI,i=screen.logicalYDPI/screen.deviceYDPI;return{left:t.left*n,right:t.right*n,top:t.top*i,bottom:t.bottom*i}}function ci(e){if(e.measure&&(e.measure.cache={},e.measure.heights=null,e.rest))for(var t=0;t<e.rest.length;t++)e.measure.caches[t]={}}function di(e){e.display.externalMeasure=null,S(e.display.lineMeasure);for(var t=0;t<e.display.view.length;t++)ci(e.display.view[t])}function hi(e){di(e),e.display.cachedCharWidth=e.display.cachedTextHeight=e.display.cachedPaddingH=null,e.options.lineWrapping||(e.display.maxLineChanged=!0),e.display.lineNumChars=null}function fi(){return c&&m?-(document.body.getBoundingClientRect().left-parseInt(getComputedStyle(document.body).marginLeft)):window.pageXOffset||(document.documentElement||document.body).scrollLeft}function pi(){return c&&m?-(document.body.getBoundingClientRect().top-parseInt(getComputedStyle(document.body).marginTop)):window.pageYOffset||(document.documentElement||document.body).scrollTop}function gi(e){var t=0;if(e.widgets)for(var n=0;n<e.widgets.length;++n)e.widgets[n].above&&(t+=Gn(e.widgets[n]));return t}function mi(e,t,n,i,r){if(!r){var s=gi(t);n.top+=s,n.bottom+=s}if("line"==i)return n;i||(i="local");var o=on(t);if("local"==i?o+=Wn(e.display):o-=e.display.viewOffset,"page"==i||"window"==i){var a=e.display.lineSpace.getBoundingClientRect();o+=a.top+("window"==i?0:pi());var l=a.left+("window"==i?0:fi());n.left+=l,n.right+=l}return n.top+=o,n.bottom+=o,n}function vi(e,t,n){if("div"==n)return t;var i=t.left,r=t.top;if("page"==n)i-=fi(),r-=pi();else if("local"==n||!n){var s=e.display.sizer.getBoundingClientRect();i+=s.left,r+=s.top}var o=e.display.lineSpace.getBoundingClientRect();return{left:i-o.left,top:r-o.top}}function Ai(e,t,n,i,r){return i||(i=qe(e.doc,t.line)),mi(e,i,ei(e,i,t.ch,r),n)}function xi(e,t,n,i,r,s){function o(t,o){var a=ii(e,r,t,o?"right":"left",s);return o?a.left=a.right:a.right=a.left,mi(e,i,a,n)}i=i||qe(e.doc,t.line),r||(r=ni(e,i));var a=he(i,e.doc.direction),l=t.ch,u=t.sticky;if(l>=i.text.length?(l=i.text.length,u="before"):l<=0&&(l=0,u="after"),!a)return o("before"==u?l-1:l,"before"==u);function c(e,t,n){return o(n?e-1:e,1==a[t].level!=n)}var d=ce(a,l,u),h=ue,f=c(l,d,"before"==u);return null!=h&&(f.other=c(l,h,"before"!=u)),f}function yi(e,t){var n=0;t=ht(e.doc,t),e.options.lineWrapping||(n=Bi(e.display)*t.ch);var 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d=(e.options.lineWrapping?Pi:Si)(e,t,n,s,c,i,r);a=(u=1!=d.level)?d.from:d.to-1,l=u?d.to:d.from-1}var h,f,p=null,g=null,m=ae((function(t){var n=ii(e,s,t);return n.top+=o,n.bottom+=o,!!Ei(n,i,r,!1)&&(n.top<=r&&n.left<=i&&(p=t,g=n),!0)}),a,l),v=!1;if(g){var A=i-g.left<g.right-i,x=A==u;m=p+(x?0:1),f=x?"after":"before",h=A?g.left:g.right}else{u||m!=l&&m!=a||m++,f=0==m?"after":m==t.text.length?"before":ii(e,s,m-(u?1:0)).bottom+o<=r==u?"after":"before";var y=xi(e,st(n,m,f),"line",t,s);h=y.left,v=r<y.top?-1:r>=y.bottom?1:0}return bi(n,m=oe(t.text,m,1),f,v,i-h)}function Si(e,t,n,i,r,s,o){var a=ae((function(a){var l=r[a],u=1!=l.level;return Ei(xi(e,st(n,u?l.to:l.from,u?"before":"after"),"line",t,i),s,o,!0)}),0,r.length-1),l=r[a];if(a>0){var u=1!=l.level,c=xi(e,st(n,u?l.from:l.to,u?"after":"before"),"line",t,i);Ei(c,s,o,!0)&&c.top>o&&(l=r[a-1])}return l}function Pi(e,t,n,i,r,s,o){var a=Ci(e,t,i,o),l=a.begin,u=a.end;/\s/.test(t.text.charAt(u-1))&&u--;for(var c=null,d=null,h=0;h<r.length;h++){var f=r[h];if(!(f.from>=u||f.to<=l)){var p=ii(e,i,1!=f.level?Math.min(u,f.to)-1:Math.max(l,f.from)).right,g=p<s?s-p+1e9:p-s;(!c||d>g)&&(c=f,d=g)}}return c||(c=r[r.length-1]),c.from<l&&(c={from:l,to:c.to,level:c.level}),c.to>u&&(c={from:c.from,to:u,level:c.level}),c}function Ni(e){if(null!=e.cachedTextHeight)return e.cachedTextHeight;if(null==ri){ri=N("pre",null,"CodeMirror-line-like");for(var t=0;t<49;++t)ri.appendChild(document.createTextNode("x")),ri.appendChild(N("br"));ri.appendChild(document.createTextNode("x"))}P(e.measure,ri);var n=ri.offsetHeight/50;return n>3&&(e.cachedTextHeight=n),S(e.measure),n||1}function Bi(e){if(null!=e.cachedCharWidth)return e.cachedCharWidth;var t=N("span","xxxxxxxxxx"),n=N("pre",[t],"CodeMirror-line-like");P(e.measure,n);var i=t.getBoundingClientRect(),r=(i.right-i.left)/10;return r>2&&(e.cachedCharWidth=r),r||10}function Di(e){for(var t=e.display,n={},i={},r=t.gutters.clientLeft,s=t.gutters.firstChild,o=0;s;s=s.nextSibling,++o){var a=e.display.gutterSpecs[o].className;n[a]=s.offsetLeft+s.clientLeft+r,i[a]=s.clientWidth}return{fixedPos:Ii(t),gutterTotalWidth:t.gutters.offsetWidth,gutterLeft:n,gutterWidth:i,wrapperWidth:t.wrapper.clientWidth}}function Ii(e){return e.scroller.getBoundingClientRect().left-e.sizer.getBoundingClientRect().left}function Li(e){var t=Ni(e.display),n=e.options.lineWrapping,i=n&&Math.max(5,e.display.scroller.clientWidth/Bi(e.display)-3);return function(r){if(rn(e.doc,r))return 0;var s=0;if(r.widgets)for(var o=0;o<r.widgets.length;o++)r.widgets[o].height&&(s+=r.widgets[o].height);return n?s+(Math.ceil(r.text.length/i)||1)*t:s+t}}function ji(e){var t=e.doc,n=Li(e);t.iter((function(e){var t=n(e);t!=e.height&&et(e,t)}))}function Oi(e,t,n,i){var r=e.display;if(!n&&"true"==Te(t).getAttribute("cm-not-content"))return null;var s,o,a=r.lineSpace.getBoundingClientRect();try{s=t.clientX-a.left,o=t.clientY-a.top}catch(e){return null}var l,u=wi(e,s,o);if(i&&u.xRel>0&&(l=qe(e.doc,u.line).text).length==u.ch){var c=k(l,l.length,e.options.tabSize)-l.length;u=st(u.line,Math.max(0,Math.round((s-Zn(e.display).left)/Bi(e.display))-c))}return u}function zi(e,t){if(t>=e.display.viewTo)return null;if((t-=e.display.viewFrom)<0)return null;for(var n=e.display.view,i=0;i<n.length;i++)if((t-=n[i].size)<0)return i}function Ri(e,t,n,i){null==t&&(t=e.doc.first),null==n&&(n=e.doc.first+e.doc.size),i||(i=0);var r=e.display;if(i&&n<r.viewTo&&(null==r.updateLineNumbers||r.updateLineNumbers>t)&&(r.updateLineNumbers=t),e.curOp.viewChanged=!0,t>=r.viewTo)Bt&&tn(e.doc,t)<r.viewTo&&Fi(e);else if(n<=r.viewFrom)Bt&&nn(e.doc,n+i)>r.viewFrom?Fi(e):(r.viewFrom+=i,r.viewTo+=i);else if(t<=r.viewFrom&&n>=r.viewTo)Fi(e);else if(t<=r.viewFrom){var s=Hi(e,n,n+i,1);s?(r.view=r.view.slice(s.index),r.viewFrom=s.lineN,r.viewTo+=i):Fi(e)}else if(n>=r.viewTo){var o=Hi(e,t,t,-1);o?(r.view=r.view.slice(0,o.index),r.viewTo=o.lineN):Fi(e)}else{var a=Hi(e,t,t,-1),l=Hi(e,n,n+i,1);a&&l?(r.view=r.view.slice(0,a.index).concat(Cn(e,a.lineN,l.lineN)).concat(r.view.slice(l.index)),r.viewTo+=i):Fi(e)}var u=r.externalMeasured;u&&(n<u.lineN?u.lineN+=i:t<u.lineN+u.size&&(r.externalMeasured=null))}function ki(e,t,n){e.curOp.viewChanged=!0;var i=e.display,r=e.display.externalMeasured;if(r&&t>=r.lineN&&t<r.lineN+r.size&&(i.externalMeasured=null),!(t<i.viewFrom||t>=i.viewTo)){var s=i.view[zi(e,t)];if(null!=s.node){var o=s.changes||(s.changes=[]);-1==H(o,n)&&o.push(n)}}}function Fi(e){e.display.viewFrom=e.display.viewTo=e.doc.first,e.display.view=[],e.display.viewOffset=0}function Hi(e,t,n,i){var r,s=zi(e,t),o=e.display.view;if(!Bt||n==e.doc.first+e.doc.size)return{index:s,lineN:n};for(var a=e.display.viewFrom,l=0;l<s;l++)a+=o[l].size;if(a!=t){if(i>0){if(s==o.length-1)return null;r=a+o[s].size-t,s++}else r=a-t;t+=r,n+=r}for(;tn(e.doc,n)!=n;){if(s==(i<0?0:o.length-1))return null;n+=i*o[s-(i<0?1:0)].size,s+=i}return{index:s,lineN:n}}function Ui(e,t,n){var i=e.display;0==i.view.length||t>=i.viewTo||n<=i.viewFrom?(i.view=Cn(e,t,n),i.viewFrom=t):(i.viewFrom>t?i.view=Cn(e,t,i.viewFrom).concat(i.view):i.viewFrom<t&&(i.view=i.view.slice(zi(e,t))),i.viewFrom=t,i.viewTo<n?i.view=i.view.concat(Cn(e,i.viewTo,n)):i.viewTo>n&&(i.view=i.view.slice(0,zi(e,n)))),i.viewTo=n}function Xi(e){for(var t=e.display.view,n=0,i=0;i<t.length;i++){var r=t[i];r.hidden||r.node&&!r.changes||++n}return n}function Gi(e){e.display.input.showSelection(e.display.input.prepareSelection())}function Vi(e,t){void 0===t&&(t=!0);for(var n=e.doc,i={},r=i.cursors=document.createDocumentFragment(),s=i.selection=document.createDocumentFragment(),o=0;o<n.sel.ranges.length;o++)if(t||o!=n.sel.primIndex){var a=n.sel.ranges[o];if(!(a.from().line>=e.display.viewTo||a.to().line<e.display.viewFrom)){var l=a.empty();(l||e.options.showCursorWhenSelecting)&&Wi(e,a.head,r),l||Zi(e,a,s)}}return i}function Wi(e,t,n){var i=xi(e,t,"div",null,null,!e.options.singleCursorHeightPerLine),r=n.appendChild(N("div"," ","CodeMirror-cursor"));if(r.style.left=i.left+"px",r.style.top=i.top+"px",r.style.height=Math.max(0,i.bottom-i.top)*e.options.cursorHeight+"px",i.other){var s=n.appendChild(N("div"," ","CodeMirror-cursor CodeMirror-secondarycursor"));s.style.display="",s.style.left=i.other.left+"px",s.style.top=i.other.top+"px",s.style.height=.85*(i.other.bottom-i.other.top)+"px"}}function Qi(e,t){return e.top-t.top||e.left-t.left}function Zi(e,t,n){var i=e.display,r=e.doc,s=document.createDocumentFragment(),o=Zn(e.display),a=o.left,l=Math.max(i.sizerWidth,Jn(e)-i.sizer.offsetLeft)-o.right,u="ltr"==r.direction;function c(e,t,n,i){t<0&&(t=0),t=Math.round(t),i=Math.round(i),s.appendChild(N("div",null,"CodeMirror-selected","position: absolute; left: "+e+"px;\n                             top: "+t+"px; width: "+(null==n?l-e:n)+"px;\n                             height: "+(i-t)+"px"))}function d(t,n,i){var s,o,d=qe(r,t),h=d.text.length;function f(n,i){return Ai(e,st(t,n),"div",d,i)}function p(t,n,i){var r=Mi(e,d,null,t),s="ltr"==n==("after"==i)?"left":"right";return f("after"==i?r.begin:r.end-(/\s/.test(d.text.charAt(r.end-1))?2:1),s)[s]}var g=he(d,r.direction);return le(g,n||0,null==i?h:i,(function(e,t,r,d){var m="ltr"==r,v=f(e,m?"left":"right"),A=f(t-1,m?"right":"left"),x=null==n&&0==e,y=null==i&&t==h,b=0==d,w=!g||d==g.length-1;if(A.top-v.top<=3){var C=(u?y:x)&&w,M=(u?x:y)&&b?a:(m?v:A).left,E=C?l:(m?A:v).right;c(M,v.top,E-M,v.bottom)}else{var T,S,P,N;m?(T=u&&x&&b?a:v.left,S=u?l:p(e,r,"before"),P=u?a:p(t,r,"after"),N=u&&y&&w?l:A.right):(T=u?p(e,r,"before"):a,S=!u&&x&&b?l:v.right,P=!u&&y&&w?a:A.left,N=u?p(t,r,"after"):l),c(T,v.top,S-T,v.bottom),v.bottom<A.top&&c(a,v.bottom,null,A.top),c(P,A.top,N-P,A.bottom)}(!s||Qi(v,s)<0)&&(s=v),Qi(A,s)<0&&(s=A),(!o||Qi(v,o)<0)&&(o=v),Qi(A,o)<0&&(o=A)})),{start:s,end:o}}var h=t.from(),f=t.to();if(h.line==f.line)d(h.line,h.ch,f.ch);else{var p=qe(r,h.line),g=qe(r,f.line),m=_t(p)==_t(g),v=d(h.line,h.ch,m?p.text.length+1:null).end,A=d(f.line,m?0:null,f.ch).start;m&&(v.top<A.top-2?(c(v.right,v.top,null,v.bottom),c(a,A.top,A.left,A.bottom)):c(v.right,v.top,A.left-v.right,v.bottom)),v.bottom<A.top&&c(a,v.bottom,null,A.top)}n.appendChild(s)}function Yi(e){if(e.state.focused){var t=e.display;clearInterval(t.blinker);var n=!0;t.cursorDiv.style.visibility="",e.options.cursorBlinkRate>0?t.blinker=setInterval((function(){e.hasFocus()||_i(e),t.cursorDiv.style.visibility=(n=!n)?"":"hidden"}),e.options.cursorBlinkRate):e.options.cursorBlinkRate<0&&(t.cursorDiv.style.visibility="hidden")}}function Ji(e){e.state.focused||(e.display.input.focus(),qi(e))}function Ki(e){e.state.delayingBlurEvent=!0,setTimeout((function(){e.state.delayingBlurEvent&&(e.state.delayingBlurEvent=!1,_i(e))}),100)}function qi(e,t){e.state.delayingBlurEvent&&(e.state.delayingBlurEvent=!1),"nocursor"!=e.options.readOnly&&(e.state.focused||(ve(e,"focus",e,t),e.state.focused=!0,L(e.display.wrapper,"CodeMirror-focused"),e.curOp||e.display.selForContextMenu==e.doc.sel||(e.display.input.reset(),l&&setTimeout((function(){return e.display.input.reset(!0)}),20)),e.display.input.receivedFocus()),Yi(e))}function _i(e,t){e.state.delayingBlurEvent||(e.state.focused&&(ve(e,"blur",e,t),e.state.focused=!1,T(e.display.wrapper,"CodeMirror-focused")),clearInterval(e.display.blinker),setTimeout((function(){e.state.focused||(e.display.shift=!1)}),150))}function $i(e){for(var t=e.display,n=t.lineDiv.offsetTop,i=0;i<t.view.length;i++){var r=t.view[i],s=e.options.lineWrapping,l=void 0,u=0;if(!r.hidden){if(o&&a<8){var c=r.node.offsetTop+r.node.offsetHeight;l=c-n,n=c}else{var d=r.node.getBoundingClientRect();l=d.bottom-d.top,!s&&r.text.firstChild&&(u=r.text.firstChild.getBoundingClientRect().right-d.left-1)}var h=r.line.height-l;if((h>.005||h<-.005)&&(et(r.line,l),er(r.line),r.rest))for(var f=0;f<r.rest.length;f++)er(r.rest[f]);if(u>e.display.sizerWidth){var p=Math.ceil(u/Bi(e.display));p>e.display.maxLineLength&&(e.display.maxLineLength=p,e.display.maxLine=r.line,e.display.maxLineChanged=!0)}}}}function er(e){if(e.widgets)for(var t=0;t<e.widgets.length;++t){var n=e.widgets[t],i=n.node.parentNode;i&&(n.height=i.offsetHeight)}}function tr(e,t,n){var i=n&&null!=n.top?Math.max(0,n.top):e.scroller.scrollTop;i=Math.floor(i-Wn(e));var r=n&&null!=n.bottom?n.bottom:i+e.wrapper.clientHeight,s=nt(t,i),o=nt(t,r);if(n&&n.ensure){var a=n.ensure.from.line,l=n.ensure.to.line;a<s?(s=a,o=nt(t,on(qe(t,a))+e.wrapper.clientHeight)):Math.min(l,t.lastLine())>=o&&(s=nt(t,on(qe(t,l))-e.wrapper.clientHeight),o=l)}return{from:s,to:Math.max(o,s+1)}}function nr(e,t){if(!Ae(e,"scrollCursorIntoView")){var n=e.display,i=n.sizer.getBoundingClientRect(),r=null;if(t.top+i.top<0?r=!0:t.bottom+i.top>(window.innerHeight||document.documentElement.clientHeight)&&(r=!1),null!=r&&!p){var s=N("div","​",null,"position: absolute;\n                         top: "+(t.top-n.viewOffset-Wn(e.display))+"px;\n                         height: "+(t.bottom-t.top+Yn(e)+n.barHeight)+"px;\n                         left: "+t.left+"px; width: "+Math.max(2,t.right-t.left)+"px;");e.display.lineSpace.appendChild(s),s.scrollIntoView(r),e.display.lineSpace.removeChild(s)}}}function ir(e,t,n,i){var r;null==i&&(i=0),e.options.lineWrapping||t!=n||(n="before"==(t=t.ch?st(t.line,"before"==t.sticky?t.ch-1:t.ch,"after"):t).sticky?st(t.line,t.ch+1,"before"):t);for(var s=0;s<5;s++){var o=!1,a=xi(e,t),l=n&&n!=t?xi(e,n):a,u=sr(e,r={left:Math.min(a.left,l.left),top:Math.min(a.top,l.top)-i,right:Math.max(a.left,l.left),bottom:Math.max(a.bottom,l.bottom)+i}),c=e.doc.scrollTop,d=e.doc.scrollLeft;if(null!=u.scrollTop&&(hr(e,u.scrollTop),Math.abs(e.doc.scrollTop-c)>1&&(o=!0)),null!=u.scrollLeft&&(pr(e,u.scrollLeft),Math.abs(e.doc.scrollLeft-d)>1&&(o=!0)),!o)break}return r}function rr(e,t){var n=sr(e,t);null!=n.scrollTop&&hr(e,n.scrollTop),null!=n.scrollLeft&&pr(e,n.scrollLeft)}function sr(e,t){var n=e.display,i=Ni(e.display);t.top<0&&(t.top=0);var r=e.curOp&&null!=e.curOp.scrollTop?e.curOp.scrollTop:n.scroller.scrollTop,s=Kn(e),o={};t.bottom-t.top>s&&(t.bottom=t.top+s);var a=e.doc.height+Qn(n),l=t.top<i,u=t.bottom>a-i;if(t.top<r)o.scrollTop=l?0:t.top;else if(t.bottom>r+s){var c=Math.min(t.top,(u?a:t.bottom)-s);c!=r&&(o.scrollTop=c)}var d=e.options.fixedGutter?0:n.gutters.offsetWidth,h=e.curOp&&null!=e.curOp.scrollLeft?e.curOp.scrollLeft:n.scroller.scrollLeft-d,f=Jn(e)-n.gutters.offsetWidth,p=t.right-t.left>f;return p&&(t.right=t.left+f),t.left<10?o.scrollLeft=0:t.left<h?o.scrollLeft=Math.max(0,t.left+d-(p?0:10)):t.right>f+h-3&&(o.scrollLeft=t.right+(p?0:10)-f),o}function or(e,t){null!=t&&(cr(e),e.curOp.scrollTop=(null==e.curOp.scrollTop?e.doc.scrollTop:e.curOp.scrollTop)+t)}function ar(e){cr(e);var t=e.getCursor();e.curOp.scrollToPos={from:t,to:t,margin:e.options.cursorScrollMargin}}function lr(e,t,n){null==t&&null==n||cr(e),null!=t&&(e.curOp.scrollLeft=t),null!=n&&(e.curOp.scrollTop=n)}function ur(e,t){cr(e),e.curOp.scrollToPos=t}function cr(e){var t=e.curOp.scrollToPos;t&&(e.curOp.scrollToPos=null,dr(e,yi(e,t.from),yi(e,t.to),t.margin))}function dr(e,t,n,i){var r=sr(e,{left:Math.min(t.left,n.left),top:Math.min(t.top,n.top)-i,right:Math.max(t.right,n.right),bottom:Math.max(t.bottom,n.bottom)+i});lr(e,r.scrollLeft,r.scrollTop)}function hr(e,t){Math.abs(e.doc.scrollTop-t)<2||(n||Gr(e,{top:t}),fr(e,t,!0),n&&Gr(e),Or(e,100))}function fr(e,t,n){t=Math.max(0,Math.min(e.display.scroller.scrollHeight-e.display.scroller.clientHeight,t)),(e.display.scroller.scrollTop!=t||n)&&(e.doc.scrollTop=t,e.display.scrollbars.setScrollTop(t),e.display.scroller.scrollTop!=t&&(e.display.scroller.scrollTop=t))}function pr(e,t,n,i){t=Math.max(0,Math.min(t,e.display.scroller.scrollWidth-e.display.scroller.clientWidth)),(n?t==e.doc.scrollLeft:Math.abs(e.doc.scrollLeft-t)<2)&&!i||(e.doc.scrollLeft=t,Zr(e),e.display.scroller.scrollLeft!=t&&(e.display.scroller.scrollLeft=t),e.display.scrollbars.setScrollLeft(t))}function gr(e){var t=e.display,n=t.gutters.offsetWidth,i=Math.round(e.doc.height+Qn(e.display));return{clientHeight:t.scroller.clientHeight,viewHeight:t.wrapper.clientHeight,scrollWidth:t.scroller.scrollWidth,clientWidth:t.scroller.clientWidth,viewWidth:t.wrapper.clientWidth,barLeft:e.options.fixedGutter?n:0,docHeight:i,scrollHeight:i+Yn(e)+t.barHeight,nativeBarWidth:t.nativeBarWidth,gutterWidth:n}}var mr=function(e,t,n){this.cm=n;var i=this.vert=N("div",[N("div",null,null,"min-width: 1px")],"CodeMirror-vscrollbar"),r=this.horiz=N("div",[N("div",null,null,"height: 100%; min-height: 1px")],"CodeMirror-hscrollbar");i.tabIndex=r.tabIndex=-1,e(i),e(r),pe(i,"scroll",(function(){i.clientHeight&&t(i.scrollTop,"vertical")})),pe(r,"scroll",(function(){r.clientWidth&&t(r.scrollLeft,"horizontal")})),this.checkedZeroWidth=!1,o&&a<8&&(this.horiz.style.minHeight=this.vert.style.minWidth="18px")};mr.prototype.update=function(e){var t=e.scrollWidth>e.clientWidth+1,n=e.scrollHeight>e.clientHeight+1,i=e.nativeBarWidth;if(n){this.vert.style.display="block",this.vert.style.bottom=t?i+"px":"0";var r=e.viewHeight-(t?i:0);this.vert.firstChild.style.height=Math.max(0,e.scrollHeight-e.clientHeight+r)+"px"}else this.vert.style.display="",this.vert.firstChild.style.height="0";if(t){this.horiz.style.display="block",this.horiz.style.right=n?i+"px":"0",this.horiz.style.left=e.barLeft+"px";var s=e.viewWidth-e.barLeft-(n?i:0);this.horiz.firstChild.style.width=Math.max(0,e.scrollWidth-e.clientWidth+s)+"px"}else this.horiz.style.display="",this.horiz.firstChild.style.width="0";return!this.checkedZeroWidth&&e.clientHeight>0&&(0==i&&this.zeroWidthHack(),this.checkedZeroWidth=!0),{right:n?i:0,bottom:t?i:0}},mr.prototype.setScrollLeft=function(e){this.horiz.scrollLeft!=e&&(this.horiz.scrollLeft=e),this.disableHoriz&&this.enableZeroWidthBar(this.horiz,this.disableHoriz,"horiz")},mr.prototype.setScrollTop=function(e){this.vert.scrollTop!=e&&(this.vert.scrollTop=e),this.disableVert&&this.enableZeroWidthBar(this.vert,this.disableVert,"vert")},mr.prototype.zeroWidthHack=function(){var e=A&&!f?"12px":"18px";this.horiz.style.height=this.vert.style.width=e,this.horiz.style.pointerEvents=this.vert.style.pointerEvents="none",this.disableHoriz=new F,this.disableVert=new F},mr.prototype.enableZeroWidthBar=function(e,t,n){function i(){var r=e.getBoundingClientRect();("vert"==n?document.elementFromPoint(r.right-1,(r.top+r.bottom)/2):document.elementFromPoint((r.right+r.left)/2,r.bottom-1))!=e?e.style.pointerEvents="none":t.set(1e3,i)}e.style.pointerEvents="auto",t.set(1e3,i)},mr.prototype.clear=function(){var e=this.horiz.parentNode;e.removeChild(this.horiz),e.removeChild(this.vert)};var vr=function(){};function Ar(e,t){t||(t=gr(e));var n=e.display.barWidth,i=e.display.barHeight;xr(e,t);for(var r=0;r<4&&n!=e.display.barWidth||i!=e.display.barHeight;r++)n!=e.display.barWidth&&e.options.lineWrapping&&$i(e),xr(e,gr(e)),n=e.display.barWidth,i=e.display.barHeight}function xr(e,t){var n=e.display,i=n.scrollbars.update(t);n.sizer.style.paddingRight=(n.barWidth=i.right)+"px",n.sizer.style.paddingBottom=(n.barHeight=i.bottom)+"px",n.heightForcer.style.borderBottom=i.bottom+"px solid transparent",i.right&&i.bottom?(n.scrollbarFiller.style.display="block",n.scrollbarFiller.style.height=i.bottom+"px",n.scrollbarFiller.style.width=i.right+"px"):n.scrollbarFiller.style.display="",i.bottom&&e.options.coverGutterNextToScrollbar&&e.options.fixedGutter?(n.gutterFiller.style.display="block",n.gutterFiller.style.height=i.bottom+"px",n.gutterFiller.style.width=t.gutterWidth+"px"):n.gutterFiller.style.display=""}vr.prototype.update=function(){return{bottom:0,right:0}},vr.prototype.setScrollLeft=function(){},vr.prototype.setScrollTop=function(){},vr.prototype.clear=function(){};var yr={native:mr,null:vr};function br(e){e.display.scrollbars&&(e.display.scrollbars.clear(),e.display.scrollbars.addClass&&T(e.display.wrapper,e.display.scrollbars.addClass)),e.display.scrollbars=new yr[e.options.scrollbarStyle]((function(t){e.display.wrapper.insertBefore(t,e.display.scrollbarFiller),pe(t,"mousedown",(function(){e.state.focused&&setTimeout((function(){return e.display.input.focus()}),0)})),t.setAttribute("cm-not-content","true")}),(function(t,n){"horizontal"==n?pr(e,t):hr(e,t)}),e),e.display.scrollbars.addClass&&L(e.display.wrapper,e.display.scrollbars.addClass)}var wr=0;function Cr(e){e.curOp={cm:e,viewChanged:!1,startHeight:e.doc.height,forceUpdate:!1,updateInput:0,typing:!1,changeObjs:null,cursorActivityHandlers:null,cursorActivityCalled:0,selectionChanged:!1,updateMaxLine:!1,scrollLeft:null,scrollTop:null,scrollToPos:null,focus:!1,id:++wr},En(e.curOp)}function Mr(e){var t=e.curOp;t&&Sn(t,(function(e){for(var t=0;t<e.ops.length;t++)e.ops[t].cm.curOp=null;Er(e)}))}function Er(e){for(var t=e.ops,n=0;n<t.length;n++)Tr(t[n]);for(var i=0;i<t.length;i++)Sr(t[i]);for(var r=0;r<t.length;r++)Pr(t[r]);for(var s=0;s<t.length;s++)Nr(t[s]);for(var o=0;o<t.length;o++)Br(t[o])}function Tr(e){var t=e.cm,n=t.display;kr(t),e.updateMaxLine&&ln(t),e.mustUpdate=e.viewChanged||e.forceUpdate||null!=e.scrollTop||e.scrollToPos&&(e.scrollToPos.from.line<n.viewFrom||e.scrollToPos.to.line>=n.viewTo)||n.maxLineChanged&&t.options.lineWrapping,e.update=e.mustUpdate&&new Rr(t,e.mustUpdate&&{top:e.scrollTop,ensure:e.scrollToPos},e.forceUpdate)}function Sr(e){e.updatedDisplay=e.mustUpdate&&Ur(e.cm,e.update)}function Pr(e){var t=e.cm,n=t.display;e.updatedDisplay&&$i(t),e.barMeasure=gr(t),n.maxLineChanged&&!t.options.lineWrapping&&(e.adjustWidthTo=ei(t,n.maxLine,n.maxLine.text.length).left+3,t.display.sizerWidth=e.adjustWidthTo,e.barMeasure.scrollWidth=Math.max(n.scroller.clientWidth,n.sizer.offsetLeft+e.adjustWidthTo+Yn(t)+t.display.barWidth),e.maxScrollLeft=Math.max(0,n.sizer.offsetLeft+e.adjustWidthTo-Jn(t))),(e.updatedDisplay||e.selectionChanged)&&(e.preparedSelection=n.input.prepareSelection())}function Nr(e){var t=e.cm;null!=e.adjustWidthTo&&(t.display.sizer.style.minWidth=e.adjustWidthTo+"px",e.maxScrollLeft<t.doc.scrollLeft&&pr(t,Math.min(t.display.scroller.scrollLeft,e.maxScrollLeft),!0),t.display.maxLineChanged=!1);var n=e.focus&&e.focus==I();e.preparedSelection&&t.display.input.showSelection(e.preparedSelection,n),(e.updatedDisplay||e.startHeight!=t.doc.height)&&Ar(t,e.barMeasure),e.updatedDisplay&&Qr(t,e.barMeasure),e.selectionChanged&&Yi(t),t.state.focused&&e.updateInput&&t.display.input.reset(e.typing),n&&Ji(e.cm)}function Br(e){var t=e.cm,n=t.display,i=t.doc;e.updatedDisplay&&Xr(t,e.update),null==n.wheelStartX||null==e.scrollTop&&null==e.scrollLeft&&!e.scrollToPos||(n.wheelStartX=n.wheelStartY=null),null!=e.scrollTop&&fr(t,e.scrollTop,e.forceScroll),null!=e.scrollLeft&&pr(t,e.scrollLeft,!0,!0),e.scrollToPos&&nr(t,ir(t,ht(i,e.scrollToPos.from),ht(i,e.scrollToPos.to),e.scrollToPos.margin));var r=e.maybeHiddenMarkers,s=e.maybeUnhiddenMarkers;if(r)for(var o=0;o<r.length;++o)r[o].lines.length||ve(r[o],"hide");if(s)for(var a=0;a<s.length;++a)s[a].lines.length&&ve(s[a],"unhide");n.wrapper.offsetHeight&&(i.scrollTop=t.display.scroller.scrollTop),e.changeObjs&&ve(t,"changes",t,e.changeObjs),e.update&&e.update.finish()}function Dr(e,t){if(e.curOp)return t();Cr(e);try{return t()}finally{Mr(e)}}function Ir(e,t){return function(){if(e.curOp)return t.apply(e,arguments);Cr(e);try{return t.apply(e,arguments)}finally{Mr(e)}}}function Lr(e){return function(){if(this.curOp)return e.apply(this,arguments);Cr(this);try{return e.apply(this,arguments)}finally{Mr(this)}}}function jr(e){return function(){var t=this.cm;if(!t||t.curOp)return e.apply(this,arguments);Cr(t);try{return e.apply(this,arguments)}finally{Mr(t)}}}function Or(e,t){e.doc.highlightFrontier<e.display.viewTo&&e.state.highlight.set(t,z(zr,e))}function zr(e){var t=e.doc;if(!(t.highlightFrontier>=e.display.viewTo)){var n=+new Date+e.options.workTime,i=xt(e,t.highlightFrontier),r=[];t.iter(i.line,Math.min(t.first+t.size,e.display.viewTo+500),(function(s){if(i.line>=e.display.viewFrom){var o=s.styles,a=s.text.length>e.options.maxHighlightLength?Ze(t.mode,i.state):null,l=vt(e,s,i,!0);a&&(i.state=a),s.styles=l.styles;var u=s.styleClasses,c=l.classes;c?s.styleClasses=c:u&&(s.styleClasses=null);for(var d=!o||o.length!=s.styles.length||u!=c&&(!u||!c||u.bgClass!=c.bgClass||u.textClass!=c.textClass),h=0;!d&&h<o.length;++h)d=o[h]!=s.styles[h];d&&r.push(i.line),s.stateAfter=i.save(),i.nextLine()}else s.text.length<=e.options.maxHighlightLength&&yt(e,s.text,i),s.stateAfter=i.line%5==0?i.save():null,i.nextLine();if(+new Date>n)return Or(e,e.options.workDelay),!0})),t.highlightFrontier=i.line,t.modeFrontier=Math.max(t.modeFrontier,i.line),r.length&&Dr(e,(function(){for(var t=0;t<r.length;t++)ki(e,r[t],"text")}))}}var Rr=function(e,t,n){var i=e.display;this.viewport=t,this.visible=tr(i,e.doc,t),this.editorIsHidden=!i.wrapper.offsetWidth,this.wrapperHeight=i.wrapper.clientHeight,this.wrapperWidth=i.wrapper.clientWidth,this.oldDisplayWidth=Jn(e),this.force=n,this.dims=Di(e),this.events=[]};function kr(e){var t=e.display;!t.scrollbarsClipped&&t.scroller.offsetWidth&&(t.nativeBarWidth=t.scroller.offsetWidth-t.scroller.clientWidth,t.heightForcer.style.height=Yn(e)+"px",t.sizer.style.marginBottom=-t.nativeBarWidth+"px",t.sizer.style.borderRightWidth=Yn(e)+"px",t.scrollbarsClipped=!0)}function Fr(e){if(e.hasFocus())return null;var t=I();if(!t||!D(e.display.lineDiv,t))return null;var n={activeElt:t};if(window.getSelection){var i=window.getSelection();i.anchorNode&&i.extend&&D(e.display.lineDiv,i.anchorNode)&&(n.anchorNode=i.anchorNode,n.anchorOffset=i.anchorOffset,n.focusNode=i.focusNode,n.focusOffset=i.focusOffset)}return n}function Hr(e){if(e&&e.activeElt&&e.activeElt!=I()&&(e.activeElt.focus(),!/^(INPUT|TEXTAREA)$/.test(e.activeElt.nodeName)&&e.anchorNode&&D(document.body,e.anchorNode)&&D(document.body,e.focusNode))){var t=window.getSelection(),n=document.createRange();n.setEnd(e.anchorNode,e.anchorOffset),n.collapse(!1),t.removeAllRanges(),t.addRange(n),t.extend(e.focusNode,e.focusOffset)}}function Ur(e,t){var n=e.display,i=e.doc;if(t.editorIsHidden)return Fi(e),!1;if(!t.force&&t.visible.from>=n.viewFrom&&t.visible.to<=n.viewTo&&(null==n.updateLineNumbers||n.updateLineNumbers>=n.viewTo)&&n.renderedView==n.view&&0==Xi(e))return!1;Yr(e)&&(Fi(e),t.dims=Di(e));var r=i.first+i.size,s=Math.max(t.visible.from-e.options.viewportMargin,i.first),o=Math.min(r,t.visible.to+e.options.viewportMargin);n.viewFrom<s&&s-n.viewFrom<20&&(s=Math.max(i.first,n.viewFrom)),n.viewTo>o&&n.viewTo-o<20&&(o=Math.min(r,n.viewTo)),Bt&&(s=tn(e.doc,s),o=nn(e.doc,o));var a=s!=n.viewFrom||o!=n.viewTo||n.lastWrapHeight!=t.wrapperHeight||n.lastWrapWidth!=t.wrapperWidth;Ui(e,s,o),n.viewOffset=on(qe(e.doc,n.viewFrom)),e.display.mover.style.top=n.viewOffset+"px";var l=Xi(e);if(!a&&0==l&&!t.force&&n.renderedView==n.view&&(null==n.updateLineNumbers||n.updateLineNumbers>=n.viewTo))return!1;var u=Fr(e);return l>4&&(n.lineDiv.style.display="none"),Vr(e,n.updateLineNumbers,t.dims),l>4&&(n.lineDiv.style.display=""),n.renderedView=n.view,Hr(u),S(n.cursorDiv),S(n.selectionDiv),n.gutters.style.height=n.sizer.style.minHeight=0,a&&(n.lastWrapHeight=t.wrapperHeight,n.lastWrapWidth=t.wrapperWidth,Or(e,400)),n.updateLineNumbers=null,!0}function Xr(e,t){for(var n=t.viewport,i=!0;;i=!1){if(i&&e.options.lineWrapping&&t.oldDisplayWidth!=Jn(e))i&&(t.visible=tr(e.display,e.doc,n));else if(n&&null!=n.top&&(n={top:Math.min(e.doc.height+Qn(e.display)-Kn(e),n.top)}),t.visible=tr(e.display,e.doc,n),t.visible.from>=e.display.viewFrom&&t.visible.to<=e.display.viewTo)break;if(!Ur(e,t))break;$i(e);var r=gr(e);Gi(e),Ar(e,r),Qr(e,r),t.force=!1}t.signal(e,"update",e),e.display.viewFrom==e.display.reportedViewFrom&&e.display.viewTo==e.display.reportedViewTo||(t.signal(e,"viewportChange",e,e.display.viewFrom,e.display.viewTo),e.display.reportedViewFrom=e.display.viewFrom,e.display.reportedViewTo=e.display.viewTo)}function Gr(e,t){var n=new Rr(e,t);if(Ur(e,n)){$i(e),Xr(e,n);var i=gr(e);Gi(e),Ar(e,i),Qr(e,i),n.finish()}}function Vr(e,t,n){var i=e.display,r=e.options.lineNumbers,s=i.lineDiv,o=s.firstChild;function a(t){var n=t.nextSibling;return l&&A&&e.display.currentWheelTarget==t?t.style.display="none":t.parentNode.removeChild(t),n}for(var u=i.view,c=i.viewFrom,d=0;d<u.length;d++){var h=u[d];if(h.hidden);else if(h.node&&h.node.parentNode==s){for(;o!=h.node;)o=a(o);var f=r&&null!=t&&t<=c&&h.lineNumber;h.changes&&(H(h.changes,"gutter")>-1&&(f=!1),Dn(e,h,c,n)),f&&(S(h.lineNumber),h.lineNumber.appendChild(document.createTextNode(rt(e.options,c)))),o=h.node.nextSibling}else{var p=Fn(e,h,c,n);s.insertBefore(p,o)}c+=h.size}for(;o;)o=a(o)}function Wr(e){var t=e.gutters.offsetWidth;e.sizer.style.marginLeft=t+"px"}function Qr(e,t){e.display.sizer.style.minHeight=t.docHeight+"px",e.display.heightForcer.style.top=t.docHeight+"px",e.display.gutters.style.height=t.docHeight+e.display.barHeight+Yn(e)+"px"}function Zr(e){var t=e.display,n=t.view;if(t.alignWidgets||t.gutters.firstChild&&e.options.fixedGutter){for(var i=Ii(t)-t.scroller.scrollLeft+e.doc.scrollLeft,r=t.gutters.offsetWidth,s=i+"px",o=0;o<n.length;o++)if(!n[o].hidden){e.options.fixedGutter&&(n[o].gutter&&(n[o].gutter.style.left=s),n[o].gutterBackground&&(n[o].gutterBackground.style.left=s));var a=n[o].alignable;if(a)for(var l=0;l<a.length;l++)a[l].style.left=s}e.options.fixedGutter&&(t.gutters.style.left=i+r+"px")}}function Yr(e){if(!e.options.lineNumbers)return!1;var t=e.doc,n=rt(e.options,t.first+t.size-1),i=e.display;if(n.length!=i.lineNumChars){var r=i.measure.appendChild(N("div",[N("div",n)],"CodeMirror-linenumber CodeMirror-gutter-elt")),s=r.firstChild.offsetWidth,o=r.offsetWidth-s;return i.lineGutter.style.width="",i.lineNumInnerWidth=Math.max(s,i.lineGutter.offsetWidth-o)+1,i.lineNumWidth=i.lineNumInnerWidth+o,i.lineNumChars=i.lineNumInnerWidth?n.length:-1,i.lineGutter.style.width=i.lineNumWidth+"px",Wr(e.display),!0}return!1}function Jr(e,t){for(var n=[],i=!1,r=0;r<e.length;r++){var s=e[r],o=null;if("string"!=typeof s&&(o=s.style,s=s.className),"CodeMirror-linenumbers"==s){if(!t)continue;i=!0}n.push({className:s,style:o})}return t&&!i&&n.push({className:"CodeMirror-linenumbers",style:null}),n}function Kr(e){var t=e.gutters,n=e.gutterSpecs;S(t),e.lineGutter=null;for(var i=0;i<n.length;++i){var r=n[i],s=r.className,o=r.style,a=t.appendChild(N("div",null,"CodeMirror-gutter "+s));o&&(a.style.cssText=o),"CodeMirror-linenumbers"==s&&(e.lineGutter=a,a.style.width=(e.lineNumWidth||1)+"px")}t.style.display=n.length?"":"none",Wr(e)}function qr(e){Kr(e.display),Ri(e),Zr(e)}function _r(e,t,i,r){var s=this;this.input=i,s.scrollbarFiller=N("div",null,"CodeMirror-scrollbar-filler"),s.scrollbarFiller.setAttribute("cm-not-content","true"),s.gutterFiller=N("div",null,"CodeMirror-gutter-filler"),s.gutterFiller.setAttribute("cm-not-content","true"),s.lineDiv=B("div",null,"CodeMirror-code"),s.selectionDiv=N("div",null,null,"position: relative; z-index: 1"),s.cursorDiv=N("div",null,"CodeMirror-cursors"),s.measure=N("div",null,"CodeMirror-measure"),s.lineMeasure=N("div",null,"CodeMirror-measure"),s.lineSpace=B("div",[s.measure,s.lineMeasure,s.selectionDiv,s.cursorDiv,s.lineDiv],null,"position: relative; outline: none");var u=B("div",[s.lineSpace],"CodeMirror-lines");s.mover=N("div",[u],null,"position: relative"),s.sizer=N("div",[s.mover],"CodeMirror-sizer"),s.sizerWidth=null,s.heightForcer=N("div",null,null,"position: absolute; height: "+U+"px; width: 1px;"),s.gutters=N("div",null,"CodeMirror-gutters"),s.lineGutter=null,s.scroller=N("div",[s.sizer,s.heightForcer,s.gutters],"CodeMirror-scroll"),s.scroller.setAttribute("tabIndex","-1"),s.wrapper=N("div",[s.scrollbarFiller,s.gutterFiller,s.scroller],"CodeMirror"),o&&a<8&&(s.gutters.style.zIndex=-1,s.scroller.style.paddingRight=0),l||n&&v||(s.scroller.draggable=!0),e&&(e.appendChild?e.appendChild(s.wrapper):e(s.wrapper)),s.viewFrom=s.viewTo=t.first,s.reportedViewFrom=s.reportedViewTo=t.first,s.view=[],s.renderedView=null,s.externalMeasured=null,s.viewOffset=0,s.lastWrapHeight=s.lastWrapWidth=0,s.updateLineNumbers=null,s.nativeBarWidth=s.barHeight=s.barWidth=0,s.scrollbarsClipped=!1,s.lineNumWidth=s.lineNumInnerWidth=s.lineNumChars=null,s.alignWidgets=!1,s.cachedCharWidth=s.cachedTextHeight=s.cachedPaddingH=null,s.maxLine=null,s.maxLineLength=0,s.maxLineChanged=!1,s.wheelDX=s.wheelDY=s.wheelStartX=s.wheelStartY=null,s.shift=!1,s.selForContextMenu=null,s.activeTouch=null,s.gutterSpecs=Jr(r.gutters,r.lineNumbers),Kr(s),i.init(s)}Rr.prototype.signal=function(e,t){ye(e,t)&&this.events.push(arguments)},Rr.prototype.finish=function(){for(var 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o=[];vs(e,(function(e,t){t||-1!=H(o,e.history)||(oo(e.history,i),o.push(e.history)),to(e,i,null,Is(e,i))}))},f=r.changes.length-1;f>=0;--f){var p=h(f);if(p)return p.v}}}}function eo(e,t){if(0!=t&&(e.first+=t,e.sel=new rs(K(e.sel.ranges,(function(e){return new ss(st(e.anchor.line+t,e.anchor.ch),st(e.head.line+t,e.head.ch))})),e.sel.primIndex),e.cm)){Ri(e.cm,e.first,e.first-t,t);for(var n=e.cm.display,i=n.viewFrom;i<n.viewTo;i++)ki(e.cm,i,"gutter")}}function to(e,t,n,i){if(e.cm&&!e.cm.curOp)return Ir(e.cm,to)(e,t,n,i);if(t.to.line<e.first)eo(e,t.text.length-1-(t.to.line-t.from.line));else if(!(t.from.line>e.lastLine())){if(t.from.line<e.first){var r=t.text.length-1-(e.first-t.from.line);eo(e,r),t={from:st(e.first,0),to:st(t.to.line+r,t.to.ch),text:[J(t.text)],origin:t.origin}}var s=e.lastLine();t.to.line>s&&(t={from:t.from,to:st(s,qe(e,s).text.length),text:[t.text[0]],origin:t.origin}),t.removed=_e(e,t.from,t.to),n||(n=cs(e,t)),e.cm?no(e.cm,t,i):ms(e,t,i),Xs(e,n,G),e.cantEdit&&Zs(e,st(e.firstLine(),0))&&(e.cantEdit=!1)}}function no(e,t,n){var i=e.doc,r=e.display,s=t.from,o=t.to,a=!1,l=s.line;e.options.lineWrapping||(l=tt(_t(qe(i,s.line))),i.iter(l,o.line+1,(function(e){if(e==r.maxLine)return a=!0,!0}))),i.sel.contains(t.from,t.to)>-1&&xe(e),ms(i,t,n,Li(e)),e.options.lineWrapping||(i.iter(l,s.line+t.text.length,(function(e){var t=an(e);t>r.maxLineLength&&(r.maxLine=e,r.maxLineLength=t,r.maxLineChanged=!0,a=!1)})),a&&(e.curOp.updateMaxLine=!0)),Pt(i,s.line),Or(e,400);var u=t.text.length-(o.line-s.line)-1;t.full?Ri(e):s.line!=o.line||1!=t.text.length||gs(e.doc,t)?Ri(e,s.line,o.line+1,u):ki(e,s.line,"text");var c=ye(e,"changes"),d=ye(e,"change");if(d||c){var h={from:s,to:o,text:t.text,removed:t.removed,origin:t.origin};d&&Nn(e,"change",e,h),c&&(e.curOp.changeObjs||(e.curOp.changeObjs=[])).push(h)}e.display.selForContextMenu=null}function io(e,t,n,i,r){var s;i||(i=n),ot(i,n)<0&&(n=(s=[i,n])[0],i=s[1]),"string"==typeof t&&(t=e.splitLines(t)),qs(e,{from:n,to:i,text:t,origin:r})}function ro(e,t,n,i){n<e.line?e.line+=i:t<e.line&&(e.line=t,e.ch=0)}function so(e,t,n,i){for(var r=0;r<e.length;++r){var s=e[r],o=!0;if(s.ranges){s.copied||((s=e[r]=s.deepCopy()).copied=!0);for(var a=0;a<s.ranges.length;a++)ro(s.ranges[a].anchor,t,n,i),ro(s.ranges[a].head,t,n,i)}else{for(var l=0;l<s.changes.length;++l){var u=s.changes[l];if(n<u.from.line)u.from=st(u.from.line+i,u.from.ch),u.to=st(u.to.line+i,u.to.ch);else if(t<=u.to.line){o=!1;break}}o||(e.splice(0,r+1),r=0)}}}function oo(e,t){var n=t.from.line,i=t.to.line,r=t.text.length-(i-n)-1;so(e.done,n,i,r),so(e.undone,n,i,r)}function ao(e,t,n,i){var r=t,s=t;return"number"==typeof t?s=qe(e,dt(e,t)):r=tt(t),null==r?null:(i(s,r)&&e.cm&&ki(e.cm,r,n),s)}function lo(e){this.lines=e,this.parent=null;for(var t=0,n=0;n<e.length;++n)e[n].parent=this,t+=e[n].height;this.height=t}function uo(e){this.children=e;for(var t=0,n=0,i=0;i<e.length;++i){var r=e[i];t+=r.chunkSize(),n+=r.height,r.parent=this}this.size=t,this.height=n,this.parent=null}ss.prototype.from=function(){return ct(this.anchor,this.head)},ss.prototype.to=function(){return ut(this.anchor,this.head)},ss.prototype.empty=function(){return this.head.line==this.anchor.line&&this.head.ch==this.anchor.ch},lo.prototype={chunkSize:function(){return this.lines.length},removeInner:function(e,t){for(var n=e,i=e+t;n<i;++n){var r=this.lines[n];this.height-=r.height,dn(r),Nn(r,"delete")}this.lines.splice(e,t)},collapse:function(e){e.push.apply(e,this.lines)},insertInner:function(e,t,n){this.height+=n,this.lines=this.lines.slice(0,e).concat(t).concat(this.lines.slice(e));for(var i=0;i<t.length;++i)t[i].parent=this},iterN:function(e,t,n){for(var i=e+t;e<i;++e)if(n(this.lines[e]))return!0}},uo.prototype={chunkSize:function(){return this.size},removeInner:function(e,t){this.size-=t;for(var n=0;n<this.children.length;++n){var i=this.children[n],r=i.chunkSize();if(e<r){var s=Math.min(t,r-e),o=i.height;if(i.removeInner(e,s),this.height-=o-i.height,r==s&&(this.children.splice(n--,1),i.parent=null),0==(t-=s))break;e=0}else e-=r}if(this.size-t<25&&(this.children.length>1||!(this.children[0]instanceof lo))){var a=[];this.collapse(a),this.children=[new lo(a)],this.children[0].parent=this}},collapse:function(e){for(var t=0;t<this.children.length;++t)this.children[t].collapse(e)},insertInner:function(e,t,n){this.size+=t.length,this.height+=n;for(var i=0;i<this.children.length;++i){var r=this.children[i],s=r.chunkSize();if(e<=s){if(r.insertInner(e,t,n),r.lines&&r.lines.length>50){for(var o=r.lines.length%25+25,a=o;a<r.lines.length;){var l=new lo(r.lines.slice(a,a+=25));r.height-=l.height,this.children.splice(++i,0,l),l.parent=this}r.lines=r.lines.slice(0,o),this.maybeSpill()}break}e-=s}},maybeSpill:function(){if(!(this.children.length<=10)){var e=this;do{var t=new uo(e.children.splice(e.children.length-5,5));if(e.parent){e.size-=t.size,e.height-=t.height;var n=H(e.parent.children,e);e.parent.children.splice(n+1,0,t)}else{var i=new uo(e.children);i.parent=e,e.children=[i,t],e=i}t.parent=e.parent}while(e.children.length>10);e.parent.maybeSpill()}},iterN:function(e,t,n){for(var i=0;i<this.children.length;++i){var r=this.children[i],s=r.chunkSize();if(e<s){var o=Math.min(t,s-e);if(r.iterN(e,o,n))return!0;if(0==(t-=o))break;e=0}else e-=s}}};var co=function(e,t,n){if(n)for(var i in n)n.hasOwnProperty(i)&&(this[i]=n[i]);this.doc=e,this.node=t};function ho(e,t,n){on(t)<(e.curOp&&e.curOp.scrollTop||e.doc.scrollTop)&&or(e,n)}function fo(e,t,n,i){var r=new co(e,n,i),s=e.cm;return s&&r.noHScroll&&(s.display.alignWidgets=!0),ao(e,t,"widget",(function(t){var n=t.widgets||(t.widgets=[]);if(null==r.insertAt?n.push(r):n.splice(Math.min(n.length-1,Math.max(0,r.insertAt)),0,r),r.line=t,s&&!rn(e,t)){var i=on(t)<e.scrollTop;et(t,t.height+Gn(r)),i&&or(s,r.height),s.curOp.forceUpdate=!0}return!0})),s&&Nn(s,"lineWidgetAdded",s,r,"number"==typeof t?t:tt(t)),r}co.prototype.clear=function(){var e=this.doc.cm,t=this.line.widgets,n=this.line,i=tt(n);if(null!=i&&t){for(var r=0;r<t.length;++r)t[r]==this&&t.splice(r--,1);t.length||(n.widgets=null);var s=Gn(this);et(n,Math.max(0,n.height-s)),e&&(Dr(e,(function(){ho(e,n,-s),ki(e,i,"widget")})),Nn(e,"lineWidgetCleared",e,this,i))}},co.prototype.changed=function(){var e=this,t=this.height,n=this.doc.cm,i=this.line;this.height=null;var r=Gn(this)-t;r&&(rn(this.doc,i)||et(i,i.height+r),n&&Dr(n,(function(){n.curOp.forceUpdate=!0,ho(n,i,r),Nn(n,"lineWidgetChanged",n,e,tt(i))})))},be(co);var po=0,go=function(e,t){this.lines=[],this.type=t,this.doc=e,this.id=++po};function mo(e,t,n,i,r){if(i&&i.shared)return Ao(e,t,n,i,r);if(e.cm&&!e.cm.curOp)return Ir(e.cm,mo)(e,t,n,i,r);var s=new go(e,r),o=ot(t,n);if(i&&R(i,s,!1),o>0||0==o&&!1!==s.clearWhenEmpty)return s;if(s.replacedWith&&(s.collapsed=!0,s.widgetNode=B("span",[s.replacedWith],"CodeMirror-widget"),i.handleMouseEvents||s.widgetNode.setAttribute("cm-ignore-events","true"),i.insertLeft&&(s.widgetNode.insertLeft=!0)),s.collapsed){if(qt(e,t.line,t,n,s)||t.line!=n.line&&qt(e,n.line,t,n,s))throw new Error("Inserting collapsed marker partially overlapping an existing one");It()}s.addToHistory&&Es(e,{from:t,to:n,origin:"markText"},e.sel,NaN);var a,l=t.line,u=e.cm;if(e.iter(l,n.line+1,(function(e){u&&s.collapsed&&!u.options.lineWrapping&&_t(e)==u.display.maxLine&&(a=!0),s.collapsed&&l!=t.line&&et(e,0),zt(e,new Lt(s,l==t.line?t.ch:null,l==n.line?n.ch:null)),++l})),s.collapsed&&e.iter(t.line,n.line+1,(function(t){rn(e,t)&&et(t,0)})),s.clearOnEnter&&pe(s,"beforeCursorEnter",(function(){return s.clear()})),s.readOnly&&(Dt(),(e.history.done.length||e.history.undone.length)&&e.clearHistory()),s.collapsed&&(s.id=++po,s.atomic=!0),u){if(a&&(u.curOp.updateMaxLine=!0),s.collapsed)Ri(u,t.line,n.line+1);else if(s.className||s.startStyle||s.endStyle||s.css||s.attributes||s.title)for(var c=t.line;c<=n.line;c++)ki(u,c,"text");s.atomic&&Vs(u.doc),Nn(u,"markerAdded",u,s)}return s}go.prototype.clear=function(){if(!this.explicitlyCleared){var e=this.doc.cm,t=e&&!e.curOp;if(t&&Cr(e),ye(this,"clear")){var n=this.find();n&&Nn(this,"clear",n.from,n.to)}for(var i=null,r=null,s=0;s<this.lines.length;++s){var o=this.lines[s],a=jt(o.markedSpans,this);e&&!this.collapsed?ki(e,tt(o),"text"):e&&(null!=a.to&&(r=tt(o)),null!=a.from&&(i=tt(o))),o.markedSpans=Ot(o.markedSpans,a),null==a.from&&this.collapsed&&!rn(this.doc,o)&&e&&et(o,Ni(e.display))}if(e&&this.collapsed&&!e.options.lineWrapping)for(var l=0;l<this.lines.length;++l){var u=_t(this.lines[l]),c=an(u);c>e.display.maxLineLength&&(e.display.maxLine=u,e.display.maxLineLength=c,e.display.maxLineChanged=!0)}null!=i&&e&&this.collapsed&&Ri(e,i,r+1),this.lines.length=0,this.explicitlyCleared=!0,this.atomic&&this.doc.cantEdit&&(this.doc.cantEdit=!1,e&&Vs(e.doc)),e&&Nn(e,"markerCleared",e,this,i,r),t&&Mr(e),this.parent&&this.parent.clear()}},go.prototype.find=function(e,t){var n,i;null==e&&"bookmark"==this.type&&(e=1);for(var r=0;r<this.lines.length;++r){var s=this.lines[r],o=jt(s.markedSpans,this);if(null!=o.from&&(n=st(t?s:tt(s),o.from),-1==e))return n;if(null!=o.to&&(i=st(t?s:tt(s),o.to),1==e))return i}return n&&{from:n,to:i}},go.prototype.changed=function(){var e=this,t=this.find(-1,!0),n=this,i=this.doc.cm;t&&i&&Dr(i,(function(){var r=t.line,s=tt(t.line),o=ti(i,s);if(o&&(ci(o),i.curOp.selectionChanged=i.curOp.forceUpdate=!0),i.curOp.updateMaxLine=!0,!rn(n.doc,r)&&null!=n.height){var a=n.height;n.height=null;var l=Gn(n)-a;l&&et(r,r.height+l)}Nn(i,"markerChanged",i,e)}))},go.prototype.attachLine=function(e){if(!this.lines.length&&this.doc.cm){var t=this.doc.cm.curOp;t.maybeHiddenMarkers&&-1!=H(t.maybeHiddenMarkers,this)||(t.maybeUnhiddenMarkers||(t.maybeUnhiddenMarkers=[])).push(this)}this.lines.push(e)},go.prototype.detachLine=function(e){if(this.lines.splice(H(this.lines,e),1),!this.lines.length&&this.doc.cm){var t=this.doc.cm.curOp;(t.maybeHiddenMarkers||(t.maybeHiddenMarkers=[])).push(this)}},be(go);var vo=function(e,t){this.markers=e,this.primary=t;for(var n=0;n<e.length;++n)e[n].parent=this};function Ao(e,t,n,i,r){(i=R(i)).shared=!1;var s=[mo(e,t,n,i,r)],o=s[0],a=i.widgetNode;return vs(e,(function(e){a&&(i.widgetNode=a.cloneNode(!0)),s.push(mo(e,ht(e,t),ht(e,n),i,r));for(var l=0;l<e.linked.length;++l)if(e.linked[l].isParent)return;o=J(s)})),new vo(s,o)}function xo(e){return e.findMarks(st(e.first,0),e.clipPos(st(e.lastLine())),(function(e){return e.parent}))}function yo(e,t){for(var n=0;n<t.length;n++){var i=t[n],r=i.find(),s=e.clipPos(r.from),o=e.clipPos(r.to);if(ot(s,o)){var a=mo(e,s,o,i.primary,i.primary.type);i.markers.push(a),a.parent=i}}}function bo(e){for(var t=function(t){var n=e[t],i=[n.primary.doc];vs(n.primary.doc,(function(e){return i.push(e)}));for(var r=0;r<n.markers.length;r++){var s=n.markers[r];-1==H(i,s.doc)&&(s.parent=null,n.markers.splice(r--,1))}},n=0;n<e.length;n++)t(n)}vo.prototype.clear=function(){if(!this.explicitlyCleared){this.explicitlyCleared=!0;for(var e=0;e<this.markers.length;++e)this.markers[e].clear();Nn(this,"clear")}},vo.prototype.find=function(e,t){return this.primary.find(e,t)},be(vo);var wo=0,Co=function(e,t,n,i,r){if(!(this instanceof Co))return new Co(e,t,n,i,r);null==n&&(n=0),uo.call(this,[new lo([new un("",null)])]),this.first=n,this.scrollTop=this.scrollLeft=0,this.cantEdit=!1,this.cleanGeneration=1,this.modeFrontier=this.highlightFrontier=n;var s=st(n,0);this.sel=as(s),this.history=new bs(null),this.id=++wo,this.modeOption=t,this.lineSep=i,this.direction="rtl"==r?"rtl":"ltr",this.extend=!1,"string"==typeof e&&(e=this.splitLines(e)),ms(this,{from:s,to:s,text:e}),Us(this,as(s),G)};Co.prototype=$(uo.prototype,{constructor:Co,iter:function(e,t,n){n?this.iterN(e-this.first,t-e,n):this.iterN(this.first,this.first+this.size,e)},insert:function(e,t){for(var n=0,i=0;i<t.length;++i)n+=t[i].height;this.insertInner(e-this.first,t,n)},remove:function(e,t){this.removeInner(e-this.first,t)},getValue:function(e){var t=$e(this,this.first,this.first+this.size);return!1===e?t:t.join(e||this.lineSeparator())},setValue:jr((function(e){var t=st(this.first,0),n=this.first+this.size-1;qs(this,{from:t,to:st(n,qe(this,n).text.length),text:this.splitLines(e),origin:"setValue",full:!0},!0),this.cm&&lr(this.cm,0,0),Us(this,as(t),G)})),replaceRange:function(e,t,n,i){io(this,e,t=ht(this,t),n=n?ht(this,n):t,i)},getRange:function(e,t,n){var i=_e(this,ht(this,e),ht(this,t));return!1===n?i:i.join(n||this.lineSeparator())},getLine:function(e){var t=this.getLineHandle(e);return t&&t.text},getLineHandle:function(e){if(it(this,e))return qe(this,e)},getLineNumber:function(e){return tt(e)},getLineHandleVisualStart:function(e){return"number"==typeof e&&(e=qe(this,e)),_t(e)},lineCount:function(){return this.size},firstLine:function(){return this.first},lastLine:function(){return this.first+this.size-1},clipPos:function(e){return ht(this,e)},getCursor:function(e){var t=this.sel.primary();return null==e||"head"==e?t.head:"anchor"==e?t.anchor:"end"==e||"to"==e||!1===e?t.to():t.from()},listSelections:function(){return this.sel.ranges},somethingSelected:function(){return this.sel.somethingSelected()},setCursor:jr((function(e,t,n){ks(this,ht(this,"number"==typeof e?st(e,t||0):e),null,n)})),setSelection:jr((function(e,t,n){ks(this,ht(this,e),ht(this,t||e),n)})),extendSelection:jr((function(e,t,n){Os(this,ht(this,e),t&&ht(this,t),n)})),extendSelections:jr((function(e,t){zs(this,pt(this,e),t)})),extendSelectionsBy:jr((function(e,t){zs(this,pt(this,K(this.sel.ranges,e)),t)})),setSelections:jr((function(e,t,n){if(e.length){for(var i=[],r=0;r<e.length;r++)i[r]=new ss(ht(this,e[r].anchor),ht(this,e[r].head));null==t&&(t=Math.min(e.length-1,this.sel.primIndex)),Us(this,os(this.cm,i,t),n)}})),addSelection:jr((function(e,t,n){var i=this.sel.ranges.slice(0);i.push(new ss(ht(this,e),ht(this,t||e))),Us(this,os(this.cm,i,i.length-1),n)})),getSelection:function(e){for(var t,n=this.sel.ranges,i=0;i<n.length;i++){var r=_e(this,n[i].from(),n[i].to());t=t?t.concat(r):r}return!1===e?t:t.join(e||this.lineSeparator())},getSelections:function(e){for(var t=[],n=this.sel.ranges,i=0;i<n.length;i++){var r=_e(this,n[i].from(),n[i].to());!1!==e&&(r=r.join(e||this.lineSeparator())),t[i]=r}return t},replaceSelection:function(e,t,n){for(var i=[],r=0;r<this.sel.ranges.length;r++)i[r]=e;this.replaceSelections(i,t,n||"+input")},replaceSelections:jr((function(e,t,n){for(var i=[],r=this.sel,s=0;s<r.ranges.length;s++){var o=r.ranges[s];i[s]={from:o.from(),to:o.to(),text:this.splitLines(e[s]),origin:n}}for(var a=t&&"end"!=t&&hs(this,i,t),l=i.length-1;l>=0;l--)qs(this,i[l]);a?Hs(this,a):this.cm&&ar(this.cm)})),undo:jr((function(){$s(this,"undo")})),redo:jr((function(){$s(this,"redo")})),undoSelection:jr((function(){$s(this,"undo",!0)})),redoSelection:jr((function(){$s(this,"redo",!0)})),setExtending:function(e){this.extend=e},getExtending:function(){return this.extend},historySize:function(){for(var e=this.history,t=0,n=0,i=0;i<e.done.length;i++)e.done[i].ranges||++t;for(var r=0;r<e.undone.length;r++)e.undone[r].ranges||++n;return{undo:t,redo:n}},clearHistory:function(){var e=this;this.history=new bs(this.history.maxGeneration),vs(this,(function(t){return t.history=e.history}),!0)},markClean:function(){this.cleanGeneration=this.changeGeneration(!0)},changeGeneration:function(e){return e&&(this.history.lastOp=this.history.lastSelOp=this.history.lastOrigin=null),this.history.generation},isClean:function(e){return this.history.generation==(e||this.cleanGeneration)},getHistory:function(){return{done:Ls(this.history.done),undone:Ls(this.history.undone)}},setHistory:function(e){var t=this.history=new bs(this.history.maxGeneration);t.done=Ls(e.done.slice(0),null,!0),t.undone=Ls(e.undone.slice(0),null,!0)},setGutterMarker:jr((function(e,t,n){return ao(this,e,"gutter",(function(e){var i=e.gutterMarkers||(e.gutterMarkers={});return i[t]=n,!n&&ie(i)&&(e.gutterMarkers=null),!0}))})),clearGutter:jr((function(e){var t=this;this.iter((function(n){n.gutterMarkers&&n.gutterMarkers[e]&&ao(t,n,"gutter",(function(){return n.gutterMarkers[e]=null,ie(n.gutterMarkers)&&(n.gutterMarkers=null),!0}))}))})),lineInfo:function(e){var t;if("number"==typeof e){if(!it(this,e))return null;if(t=e,!(e=qe(this,e)))return null}else if(null==(t=tt(e)))return null;return{line:t,handle:e,text:e.text,gutterMarkers:e.gutterMarkers,textClass:e.textClass,bgClass:e.bgClass,wrapClass:e.wrapClass,widgets:e.widgets}},addLineClass:jr((function(e,t,n){return ao(this,e,"gutter"==t?"gutter":"class",(function(e){var i="text"==t?"textClass":"background"==t?"bgClass":"gutter"==t?"gutterClass":"wrapClass";if(e[i]){if(M(n).test(e[i]))return!1;e[i]+=" "+n}else e[i]=n;return!0}))})),removeLineClass:jr((function(e,t,n){return ao(this,e,"gutter"==t?"gutter":"class",(function(e){var i="text"==t?"textClass":"background"==t?"bgClass":"gutter"==t?"gutterClass":"wrapClass",r=e[i];if(!r)return!1;if(null==n)e[i]=null;else{var s=r.match(M(n));if(!s)return!1;var o=s.index+s[0].length;e[i]=r.slice(0,s.index)+(s.index&&o!=r.length?" 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n}function ta(e,t,n){if("string"==typeof t&&!(t=qo[t]))return!1;e.display.input.ensurePolled();var i=e.display.shift,r=!1;try{e.isReadOnly()&&(e.state.suppressEdits=!0),n&&(e.display.shift=!1),r=t(e)!=X}finally{e.display.shift=i,e.state.suppressEdits=!1}return r}function na(e,t,n){for(var i=0;i<e.state.keyMaps.length;i++){var r=Uo(t,e.state.keyMaps[i],n,e);if(r)return r}return e.options.extraKeys&&Uo(t,e.options.extraKeys,n,e)||Uo(t,e.options.keyMap,n,e)}var ia=new F;function ra(e,t,n,i){var r=e.state.keySeq;if(r){if(Xo(t))return"handled";if(/\'$/.test(t)?e.state.keySeq=null:ia.set(50,(function(){e.state.keySeq==r&&(e.state.keySeq=null,e.display.input.reset())})),sa(e,r+" "+t,n,i))return!0}return sa(e,t,n,i)}function sa(e,t,n,i){var r=na(e,t,i);return"multi"==r&&(e.state.keySeq=t),"handled"==r&&Nn(e,"keyHandled",e,t,n),"handled"!=r&&"multi"!=r||(we(n),Yi(e)),!!r}function oa(e,t){var n=Vo(t,!0);return!!n&&(t.shiftKey&&!e.state.keySeq?ra(e,"Shift-"+n,t,(function(t){return 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da(e){16==e.keyCode&&(this.doc.sel.shift=!1),Ae(this,e)}function ha(e){var t=this;if(!(e.target&&e.target!=t.display.input.getField()||Vn(t.display,e)||Ae(t,e)||e.ctrlKey&&!e.altKey||A&&e.metaKey)){var n=e.keyCode,i=e.charCode;if(d&&n==la)return la=null,void we(e);if(!d||e.which&&!(e.which<10)||!oa(t,e)){var r=String.fromCharCode(null==i?n:i);"\b"!=r&&(aa(t,e,r)||t.display.input.onKeyPress(e))}}}var fa,pa,ga=400,ma=function(e,t,n){this.time=e,this.pos=t,this.button=n};function va(e,t){var n=+new Date;return pa&&pa.compare(n,e,t)?(fa=pa=null,"triple"):fa&&fa.compare(n,e,t)?(pa=new ma(n,e,t),fa=null,"double"):(fa=new ma(n,e,t),pa=null,"single")}function Aa(e){var t=this,n=t.display;if(!(Ae(t,e)||n.activeTouch&&n.input.supportsTouch()))if(n.input.ensurePolled(),n.shift=e.shiftKey,Vn(n,e))l||(n.scroller.draggable=!1,setTimeout((function(){return n.scroller.draggable=!0}),100));else if(!Sa(t,e)){var i=Oi(t,e),r=Se(e),s=i?va(i,r):"single";window.focus(),1==r&&t.state.selectingText&&t.state.selectingText(e),i&&xa(t,r,i,s,e)||(1==r?i?ba(t,i,s,e):Te(e)==n.scroller&&we(e):2==r?(i&&Os(t.doc,i),setTimeout((function(){return n.input.focus()}),20)):3==r&&(C?t.display.input.onContextMenu(e):Ki(t)))}}function xa(e,t,n,i,r){var s="Click";return"double"==i?s="Double"+s:"triple"==i&&(s="Triple"+s),ra(e,Go(s=(1==t?"Left":2==t?"Middle":"Right")+s,r),r,(function(t){if("string"==typeof t&&(t=qo[t]),!t)return!1;var i=!1;try{e.isReadOnly()&&(e.state.suppressEdits=!0),i=t(e,n)!=X}finally{e.state.suppressEdits=!1}return i}))}function ya(e,t,n){var i=e.getOption("configureMouse"),r=i?i(e,t,n):{};if(null==r.unit){var s=x?n.shiftKey&&n.metaKey:n.altKey;r.unit=s?"rectangle":"single"==t?"char":"double"==t?"word":"line"}return(null==r.extend||e.doc.extend)&&(r.extend=e.doc.extend||n.shiftKey),null==r.addNew&&(r.addNew=A?n.metaKey:n.ctrlKey),null==r.moveOnDrag&&(r.moveOnDrag=!(A?n.altKey:n.ctrlKey)),r}function ba(e,t,n,i){o?setTimeout(z(Ji,e),0):e.curOp.focus=I();var r,s=ya(e,n,i),a=e.doc.sel;e.options.dragDrop&&Be&&!e.isReadOnly()&&"single"==n&&(r=a.contains(t))>-1&&(ot((r=a.ranges[r]).from(),t)<0||t.xRel>0)&&(ot(r.to(),t)>0||t.xRel<0)?wa(e,i,t,s):Ma(e,i,t,s)}function wa(e,t,n,i){var r=e.display,s=!1,u=Ir(e,(function(t){l&&(r.scroller.draggable=!1),e.state.draggingText=!1,me(r.wrapper.ownerDocument,"mouseup",u),me(r.wrapper.ownerDocument,"mousemove",c),me(r.scroller,"dragstart",d),me(r.scroller,"drop",u),s||(we(t),i.addNew||Os(e.doc,n,null,null,i.extend),l&&!h||o&&9==a?setTimeout((function(){r.wrapper.ownerDocument.body.focus({preventScroll:!0}),r.input.focus()}),20):r.input.focus())})),c=function(e){s=s||Math.abs(t.clientX-e.clientX)+Math.abs(t.clientY-e.clientY)>=10},d=function(){return s=!0};l&&(r.scroller.draggable=!0),e.state.draggingText=u,u.copy=!i.moveOnDrag,r.scroller.dragDrop&&r.scroller.dragDrop(),pe(r.wrapper.ownerDocument,"mouseup",u),pe(r.wrapper.ownerDocument,"mousemove",c),pe(r.scroller,"dragstart",d),pe(r.scroller,"drop",u),Ki(e),setTimeout((function(){return r.input.focus()}),20)}function Ca(e,t,n){if("char"==n)return new ss(t,t);if("word"==n)return e.findWordAt(t);if("line"==n)return new ss(st(t.line,0),ht(e.doc,st(t.line+1,0)));var i=n(e,t);return new ss(i.from,i.to)}function Ma(e,t,n,i){var r=e.display,s=e.doc;we(t);var o,a,l=s.sel,u=l.ranges;if(i.addNew&&!i.extend?(a=s.sel.contains(n),o=a>-1?u[a]:new ss(n,n)):(o=s.sel.primary(),a=s.sel.primIndex),"rectangle"==i.unit)i.addNew||(o=new ss(n,n)),n=Oi(e,t,!0,!0),a=-1;else{var c=Ca(e,n,i.unit);o=i.extend?js(o,c.anchor,c.head,i.extend):c}i.addNew?-1==a?(a=u.length,Us(s,os(e,u.concat([o]),a),{scroll:!1,origin:"*mouse"})):u.length>1&&u[a].empty()&&"char"==i.unit&&!i.extend?(Us(s,os(e,u.slice(0,a).concat(u.slice(a+1)),0),{scroll:!1,origin:"*mouse"}),l=s.sel):Rs(s,a,o,V):(a=0,Us(s,new rs([o],0),V),l=s.sel);var d=n;function h(t){if(0!=ot(d,t))if(d=t,"rectangle"==i.unit){for(var r=[],u=e.options.tabSize,c=k(qe(s,n.line).text,n.ch,u),h=k(qe(s,t.line).text,t.ch,u),f=Math.min(c,h),p=Math.max(c,h),g=Math.min(n.line,t.line),m=Math.min(e.lastLine(),Math.max(n.line,t.line));g<=m;g++){var v=qe(s,g).text,A=Q(v,f,u);f==p?r.push(new ss(st(g,A),st(g,A))):v.length>A&&r.push(new ss(st(g,A),st(g,Q(v,p,u))))}r.length||r.push(new ss(n,n)),Us(s,os(e,l.ranges.slice(0,a).concat(r),a),{origin:"*mouse",scroll:!1}),e.scrollIntoView(t)}else{var x,y=o,b=Ca(e,t,i.unit),w=y.anchor;ot(b.anchor,w)>0?(x=b.head,w=ct(y.from(),b.anchor)):(x=b.anchor,w=ut(y.to(),b.head));var C=l.ranges.slice(0);C[a]=Ea(e,new ss(ht(s,w),x)),Us(s,os(e,C,a),V)}}var f=r.wrapper.getBoundingClientRect(),p=0;function g(t){var n=++p,o=Oi(e,t,!0,"rectangle"==i.unit);if(o)if(0!=ot(o,d)){e.curOp.focus=I(),h(o);var a=tr(r,s);(o.line>=a.to||o.line<a.from)&&setTimeout(Ir(e,(function(){p==n&&g(t)})),150)}else{var l=t.clientY<f.top?-20:t.clientY>f.bottom?20:0;l&&setTimeout(Ir(e,(function(){p==n&&(r.scroller.scrollTop+=l,g(t))})),50)}}function m(t){e.state.selectingText=!1,p=1/0,t&&(we(t),r.input.focus()),me(r.wrapper.ownerDocument,"mousemove",v),me(r.wrapper.ownerDocument,"mouseup",A),s.history.lastSelOrigin=null}var v=Ir(e,(function(e){0!==e.buttons&&Se(e)?g(e):m(e)})),A=Ir(e,m);e.state.selectingText=A,pe(r.wrapper.ownerDocument,"mousemove",v),pe(r.wrapper.ownerDocument,"mouseup",A)}function Ea(e,t){var n=t.anchor,i=t.head,r=qe(e.doc,n.line);if(0==ot(n,i)&&n.sticky==i.sticky)return t;var s=he(r);if(!s)return t;var o=ce(s,n.ch,n.sticky),a=s[o];if(a.from!=n.ch&&a.to!=n.ch)return t;var l,u=o+(a.from==n.ch==(1!=a.level)?0:1);if(0==u||u==s.length)return t;if(i.line!=n.line)l=(i.line-n.line)*("ltr"==e.doc.direction?1:-1)>0;else{var c=ce(s,i.ch,i.sticky),d=c-o||(i.ch-n.ch)*(1==a.level?-1:1);l=c==u-1||c==u?d<0:d>0}var h=s[u+(l?-1:0)],f=l==(1==h.level),p=f?h.from:h.to,g=f?"after":"before";return n.ch==p&&n.sticky==g?t:new ss(new st(n.line,p,g),i)}function Ta(e,t,n,i){var r,s;if(t.touches)r=t.touches[0].clientX,s=t.touches[0].clientY;else try{r=t.clientX,s=t.clientY}catch(e){return!1}if(r>=Math.floor(e.display.gutters.getBoundingClientRect().right))return!1;i&&we(t);var o=e.display,a=o.lineDiv.getBoundingClientRect();if(s>a.bottom||!ye(e,n))return Me(t);s-=a.top-o.viewOffset;for(var l=0;l<e.display.gutterSpecs.length;++l){var u=o.gutters.childNodes[l];if(u&&u.getBoundingClientRect().right>=r)return ve(e,n,e,nt(e.doc,s),e.display.gutterSpecs[l].className,t),Me(t)}}function Sa(e,t){return Ta(e,t,"gutterClick",!0)}function Pa(e,t){Vn(e.display,t)||Na(e,t)||Ae(e,t,"contextmenu")||C||e.display.input.onContextMenu(t)}function Na(e,t){return!!ye(e,"gutterContextMenu")&&Ta(e,t,"gutterContextMenu",!1)}function Ba(e){e.display.wrapper.className=e.display.wrapper.className.replace(/\s*cm-s-\S+/g,"")+e.options.theme.replace(/(^|\s)\s*/g," cm-s-"),hi(e)}ma.prototype.compare=function(e,t,n){return this.time+ga>e&&0==ot(t,this.pos)&&n==this.button};var Da={toString:function(){return"CodeMirror.Init"}},Ia={},La={};function ja(e){var t=e.optionHandlers;function n(n,i,r,s){e.defaults[n]=i,r&&(t[n]=s?function(e,t,n){n!=Da&&r(e,t,n)}:r)}e.defineOption=n,e.Init=Da,n("value","",(function(e,t){return e.setValue(t)}),!0),n("mode",null,(function(e,t){e.doc.modeOption=t,fs(e)}),!0),n("indentUnit",2,fs,!0),n("indentWithTabs",!1),n("smartIndent",!0),n("tabSize",4,(function(e){ps(e),hi(e),Ri(e)}),!0),n("lineSeparator",null,(function(e,t){if(e.doc.lineSep=t,t){var n=[],i=e.doc.first;e.doc.iter((function(e){for(var r=0;;){var s=e.text.indexOf(t,r);if(-1==s)break;r=s+t.length,n.push(st(i,s))}i++}));for(var r=n.length-1;r>=0;r--)io(e.doc,t,n[r],st(n[r].line,n[r].ch+t.length))}})),n("specialChars",/[\u0000-\u001f\u007f-\u009f\u00ad\u061c\u200b-\u200c\u200e\u200f\u2028\u2029\ufeff\ufff9-\ufffc]/g,(function(e,t,n){e.state.specialChars=new RegExp(t.source+(t.test("\t")?"":"|\t"),"g"),n!=Da&&e.refresh()})),n("specialCharPlaceholder",mn,(function(e){return e.refresh()}),!0),n("electricChars",!0),n("inputStyle",v?"contenteditable":"textarea",(function(){throw new Error("inputStyle can not (yet) be changed in a running editor")}),!0),n("spellcheck",!1,(function(e,t){return e.getInputField().spellcheck=t}),!0),n("autocorrect",!1,(function(e,t){return e.getInputField().autocorrect=t}),!0),n("autocapitalize",!1,(function(e,t){return e.getInputField().autocapitalize=t}),!0),n("rtlMoveVisually",!y),n("wholeLineUpdateBefore",!0),n("theme","default",(function(e){Ba(e),qr(e)}),!0),n("keyMap","default",(function(e,t,n){var i=Wo(t),r=n!=Da&&Wo(n);r&&r.detach&&r.detach(e,i),i.attach&&i.attach(e,r||null)})),n("extraKeys",null),n("configureMouse",null),n("lineWrapping",!1,za,!0),n("gutters",[],(function(e,t){e.display.gutterSpecs=Jr(t,e.options.lineNumbers),qr(e)}),!0),n("fixedGutter",!0,(function(e,t){e.display.gutters.style.left=t?Ii(e.display)+"px":"0",e.refresh()}),!0),n("coverGutterNextToScrollbar",!1,(function(e){return Ar(e)}),!0),n("scrollbarStyle","native",(function(e){br(e),Ar(e),e.display.scrollbars.setScrollTop(e.doc.scrollTop),e.display.scrollbars.setScrollLeft(e.doc.scrollLeft)}),!0),n("lineNumbers",!1,(function(e,t){e.display.gutterSpecs=Jr(e.options.gutters,t),qr(e)}),!0),n("firstLineNumber",1,qr,!0),n("lineNumberFormatter",(function(e){return e}),qr,!0),n("showCursorWhenSelecting",!1,Gi,!0),n("resetSelectionOnContextMenu",!0),n("lineWiseCopyCut",!0),n("pasteLinesPerSelection",!0),n("selectionsMayTouch",!1),n("readOnly",!1,(function(e,t){"nocursor"==t&&(_i(e),e.display.input.blur()),e.display.input.readOnlyChanged(t)})),n("screenReaderLabel",null,(function(e,t){t=""===t?null:t,e.display.input.screenReaderLabelChanged(t)})),n("disableInput",!1,(function(e,t){t||e.display.input.reset()}),!0),n("dragDrop",!0,Oa),n("allowDropFileTypes",null),n("cursorBlinkRate",530),n("cursorScrollMargin",0),n("cursorHeight",1,Gi,!0),n("singleCursorHeightPerLine",!0,Gi,!0),n("workTime",100),n("workDelay",100),n("flattenSpans",!0,ps,!0),n("addModeClass",!1,ps,!0),n("pollInterval",100),n("undoDepth",200,(function(e,t){return e.doc.history.undoDepth=t})),n("historyEventDelay",1250),n("viewportMargin",10,(function(e){return e.refresh()}),!0),n("maxHighlightLength",1e4,ps,!0),n("moveInputWithCursor",!0,(function(e,t){t||e.display.input.resetPosition()})),n("tabindex",null,(function(e,t){return e.display.input.getField().tabIndex=t||""})),n("autofocus",null),n("direction","ltr",(function(e,t){return e.doc.setDirection(t)}),!0),n("phrases",null)}function Oa(e,t,n){if(!t!=!(n&&n!=Da)){var i=e.display.dragFunctions,r=t?pe:me;r(e.display.scroller,"dragstart",i.start),r(e.display.scroller,"dragenter",i.enter),r(e.display.scroller,"dragover",i.over),r(e.display.scroller,"dragleave",i.leave),r(e.display.scroller,"drop",i.drop)}}function za(e){e.options.lineWrapping?(L(e.display.wrapper,"CodeMirror-wrap"),e.display.sizer.style.minWidth="",e.display.sizerWidth=null):(T(e.display.wrapper,"CodeMirror-wrap"),ln(e)),ji(e),Ri(e),hi(e),setTimeout((function(){return Ar(e)}),100)}function Ra(e,t){var n=this;if(!(this instanceof Ra))return new Ra(e,t);this.options=t=t?R(t):{},R(Ia,t,!1);var i=t.value;"string"==typeof i?i=new Co(i,t.mode,null,t.lineSeparator,t.direction):t.mode&&(i.modeOption=t.mode),this.doc=i;var r=new Ra.inputStyles[t.inputStyle](this),s=this.display=new _r(e,i,r,t);for(var u in s.wrapper.CodeMirror=this,Ba(this),t.lineWrapping&&(this.display.wrapper.className+=" CodeMirror-wrap"),br(this),this.state={keyMaps:[],overlays:[],modeGen:0,overwrite:!1,delayingBlurEvent:!1,focused:!1,suppressEdits:!1,pasteIncoming:-1,cutIncoming:-1,selectingText:!1,draggingText:!1,highlight:new F,keySeq:null,specialChars:null},t.autofocus&&!v&&s.input.focus(),o&&a<11&&setTimeout((function(){return n.display.input.reset(!0)}),20),ka(this),Do(),Cr(this),this.curOp.forceUpdate=!0,As(this,i),t.autofocus&&!v||this.hasFocus()?setTimeout((function(){n.hasFocus()&&!n.state.focused&&qi(n)}),20):_i(this),La)La.hasOwnProperty(u)&&La[u](this,t[u],Da);Yr(this),t.finishInit&&t.finishInit(this);for(var c=0;c<Fa.length;++c)Fa[c](this);Mr(this),l&&t.lineWrapping&&"optimizelegibility"==getComputedStyle(s.lineDiv).textRendering&&(s.lineDiv.style.textRendering="auto")}function ka(e){var t=e.display;pe(t.scroller,"mousedown",Ir(e,Aa)),pe(t.scroller,"dblclick",o&&a<11?Ir(e,(function(t){if(!Ae(e,t)){var n=Oi(e,t);if(n&&!Sa(e,t)&&!Vn(e.display,t)){we(t);var i=e.findWordAt(n);Os(e.doc,i.anchor,i.head)}}})):function(t){return Ae(e,t)||we(t)}),pe(t.scroller,"contextmenu",(function(t){return Pa(e,t)})),pe(t.input.getField(),"contextmenu",(function(n){t.scroller.contains(n.target)||Pa(e,n)}));var n,i={end:0};function r(){t.activeTouch&&(n=setTimeout((function(){return t.activeTouch=null}),1e3),(i=t.activeTouch).end=+new Date)}function s(e){if(1!=e.touches.length)return!1;var t=e.touches[0];return t.radiusX<=1&&t.radiusY<=1}function l(e,t){if(null==t.left)return!0;var n=t.left-e.left,i=t.top-e.top;return n*n+i*i>400}pe(t.scroller,"touchstart",(function(r){if(!Ae(e,r)&&!s(r)&&!Sa(e,r)){t.input.ensurePolled(),clearTimeout(n);var o=+new Date;t.activeTouch={start:o,moved:!1,prev:o-i.end<=300?i:null},1==r.touches.length&&(t.activeTouch.left=r.touches[0].pageX,t.activeTouch.top=r.touches[0].pageY)}})),pe(t.scroller,"touchmove",(function(){t.activeTouch&&(t.activeTouch.moved=!0)})),pe(t.scroller,"touchend",(function(n){var i=t.activeTouch;if(i&&!Vn(t,n)&&null!=i.left&&!i.moved&&new Date-i.start<300){var s,o=e.coordsChar(t.activeTouch,"page");s=!i.prev||l(i,i.prev)?new ss(o,o):!i.prev.prev||l(i,i.prev.prev)?e.findWordAt(o):new ss(st(o.line,0),ht(e.doc,st(o.line+1,0))),e.setSelection(s.anchor,s.head),e.focus(),we(n)}r()})),pe(t.scroller,"touchcancel",r),pe(t.scroller,"scroll",(function(){t.scroller.clientHeight&&(hr(e,t.scroller.scrollTop),pr(e,t.scroller.scrollLeft,!0),ve(e,"scroll",e))})),pe(t.scroller,"mousewheel",(function(t){return is(e,t)})),pe(t.scroller,"DOMMouseScroll",(function(t){return is(e,t)})),pe(t.wrapper,"scroll",(function(){return t.wrapper.scrollTop=t.wrapper.scrollLeft=0})),t.dragFunctions={enter:function(t){Ae(e,t)||Ee(t)},over:function(t){Ae(e,t)||(So(e,t),Ee(t))},start:function(t){return To(e,t)},drop:Ir(e,Eo),leave:function(t){Ae(e,t)||Po(e)}};var u=t.input.getField();pe(u,"keyup",(function(t){return da.call(e,t)})),pe(u,"keydown",Ir(e,ua)),pe(u,"keypress",Ir(e,ha)),pe(u,"focus",(function(t){return qi(e,t)})),pe(u,"blur",(function(t){return _i(e,t)}))}Ra.defaults=Ia,Ra.optionHandlers=La;var Fa=[];function Ha(e,t,n,i){var r,s=e.doc;null==n&&(n="add"),"smart"==n&&(s.mode.indent?r=xt(e,t).state:n="prev");var o=e.options.tabSize,a=qe(s,t),l=k(a.text,null,o);a.stateAfter&&(a.stateAfter=null);var u,c=a.text.match(/^\s*/)[0];if(i||/\S/.test(a.text)){if("smart"==n&&((u=s.mode.indent(r,a.text.slice(c.length),a.text))==X||u>150)){if(!i)return;n="prev"}}else u=0,n="not";"prev"==n?u=t>s.first?k(qe(s,t-1).text,null,o):0:"add"==n?u=l+e.options.indentUnit:"subtract"==n?u=l-e.options.indentUnit:"number"==typeof n&&(u=l+n),u=Math.max(0,u);var d="",h=0;if(e.options.indentWithTabs)for(var f=Math.floor(u/o);f;--f)h+=o,d+="\t";if(h<u&&(d+=Y(u-h)),d!=c)return io(s,d,st(t,0),st(t,c.length),"+input"),a.stateAfter=null,!0;for(var p=0;p<s.sel.ranges.length;p++){var g=s.sel.ranges[p];if(g.head.line==t&&g.head.ch<c.length){var m=st(t,c.length);Rs(s,p,new ss(m,m));break}}}Ra.defineInitHook=function(e){return Fa.push(e)};var Ua=null;function Xa(e){Ua=e}function Ga(e,t,n,i,r){var s=e.doc;e.display.shift=!1,i||(i=s.sel);var o=+new Date-200,a="paste"==r||e.state.pasteIncoming>o,l=je(t),u=null;if(a&&i.ranges.length>1)if(Ua&&Ua.text.join("\n")==t){if(i.ranges.length%Ua.text.length==0){u=[];for(var c=0;c<Ua.text.length;c++)u.push(s.splitLines(Ua.text[c]))}}else l.length==i.ranges.length&&e.options.pasteLinesPerSelection&&(u=K(l,(function(e){return[e]})));for(var d=e.curOp.updateInput,h=i.ranges.length-1;h>=0;h--){var f=i.ranges[h],p=f.from(),g=f.to();f.empty()&&(n&&n>0?p=st(p.line,p.ch-n):e.state.overwrite&&!a?g=st(g.line,Math.min(qe(s,g.line).text.length,g.ch+J(l).length)):a&&Ua&&Ua.lineWise&&Ua.text.join("\n")==l.join("\n")&&(p=g=st(p.line,0)));var m={from:p,to:g,text:u?u[h%u.length]:l,origin:r||(a?"paste":e.state.cutIncoming>o?"cut":"+input")};qs(e.doc,m),Nn(e,"inputRead",e,m)}t&&!a&&Wa(e,t),ar(e),e.curOp.updateInput<2&&(e.curOp.updateInput=d),e.curOp.typing=!0,e.state.pasteIncoming=e.state.cutIncoming=-1}function Va(e,t){var n=e.clipboardData&&e.clipboardData.getData("Text");if(n)return e.preventDefault(),t.isReadOnly()||t.options.disableInput||Dr(t,(function(){return Ga(t,n,0,null,"paste")})),!0}function Wa(e,t){if(e.options.electricChars&&e.options.smartIndent)for(var n=e.doc.sel,i=n.ranges.length-1;i>=0;i--){var r=n.ranges[i];if(!(r.head.ch>100||i&&n.ranges[i-1].head.line==r.head.line)){var s=e.getModeAt(r.head),o=!1;if(s.electricChars){for(var a=0;a<s.electricChars.length;a++)if(t.indexOf(s.electricChars.charAt(a))>-1){o=Ha(e,r.head.line,"smart");break}}else s.electricInput&&s.electricInput.test(qe(e.doc,r.head.line).text.slice(0,r.head.ch))&&(o=Ha(e,r.head.line,"smart"));o&&Nn(e,"electricInput",e,r.head.line)}}}function Qa(e){for(var t=[],n=[],i=0;i<e.doc.sel.ranges.length;i++){var r=e.doc.sel.ranges[i].head.line,s={anchor:st(r,0),head:st(r+1,0)};n.push(s),t.push(e.getRange(s.anchor,s.head))}return{text:t,ranges:n}}function Za(e,t,n,i){e.setAttribute("autocorrect",n?"":"off"),e.setAttribute("autocapitalize",i?"":"off"),e.setAttribute("spellcheck",!!t)}function Ya(){var e=N("textarea",null,null,"position: absolute; bottom: -1em; padding: 0; width: 1px; height: 1em; outline: none"),t=N("div",[e],null,"overflow: hidden; position: relative; width: 3px; height: 0px;");return l?e.style.width="1000px":e.setAttribute("wrap","off"),g&&(e.style.border="1px solid black"),Za(e),t}function Ja(e){var t=e.optionHandlers,n=e.helpers={};e.prototype={constructor:e,focus:function(){window.focus(),this.display.input.focus()},setOption:function(e,n){var i=this.options,r=i[e];i[e]==n&&"mode"!=e||(i[e]=n,t.hasOwnProperty(e)&&Ir(this,t[e])(this,n,r),ve(this,"optionChange",this,e))},getOption:function(e){return this.options[e]},getDoc:function(){return this.doc},addKeyMap:function(e,t){this.state.keyMaps[t?"push":"unshift"](Wo(e))},removeKeyMap:function(e){for(var t=this.state.keyMaps,n=0;n<t.length;++n)if(t[n]==e||t[n].name==e)return t.splice(n,1),!0},addOverlay:Lr((function(t,n){var i=t.token?t:e.getMode(this.options,t);if(i.startState)throw new Error("Overlays may not be stateful.");q(this.state.overlays,{mode:i,modeSpec:t,opaque:n&&n.opaque,priority:n&&n.priority||0},(function(e){return e.priority})),this.state.modeGen++,Ri(this)})),removeOverlay:Lr((function(e){for(var t=this.state.overlays,n=0;n<t.length;++n){var i=t[n].modeSpec;if(i==e||"string"==typeof e&&i.name==e)return t.splice(n,1),this.state.modeGen++,void Ri(this)}})),indentLine:Lr((function(e,t,n){"string"!=typeof t&&"number"!=typeof t&&(t=null==t?this.options.smartIndent?"smart":"prev":t?"add":"subtract"),it(this.doc,e)&&Ha(this,e,t,n)})),indentSelection:Lr((function(e){for(var t=this.doc.sel.ranges,n=-1,i=0;i<t.length;i++){var r=t[i];if(r.empty())r.head.line>n&&(Ha(this,r.head.line,e,!0),n=r.head.line,i==this.doc.sel.primIndex&&ar(this));else{var s=r.from(),o=r.to(),a=Math.max(n,s.line);n=Math.min(this.lastLine(),o.line-(o.ch?0:1))+1;for(var l=a;l<n;++l)Ha(this,l,e);var u=this.doc.sel.ranges;0==s.ch&&t.length==u.length&&u[i].from().ch>0&&Rs(this.doc,i,new ss(s,u[i].to()),G)}}})),getTokenAt:function(e,t){return Mt(this,e,t)},getLineTokens:function(e,t){return Mt(this,st(e),t,!0)},getTokenTypeAt:function(e){e=ht(this.doc,e);var t,n=At(this,qe(this.doc,e.line)),i=0,r=(n.length-1)/2,s=e.ch;if(0==s)t=n[2];else for(;;){var o=i+r>>1;if((o?n[2*o-1]:0)>=s)r=o;else{if(!(n[2*o+1]<s)){t=n[2*o+2];break}i=o+1}}var a=t?t.indexOf("overlay "):-1;return a<0?t:0==a?null:t.slice(0,a-1)},getModeAt:function(t){var n=this.doc.mode;return n.innerMode?e.innerMode(n,this.getTokenAt(t).state).mode:n},getHelper:function(e,t){return this.getHelpers(e,t)[0]},getHelpers:function(e,t){var i=[];if(!n.hasOwnProperty(t))return i;var r=n[t],s=this.getModeAt(e);if("string"==typeof s[t])r[s[t]]&&i.push(r[s[t]]);else if(s[t])for(var o=0;o<s[t].length;o++){var a=r[s[t][o]];a&&i.push(a)}else s.helperType&&r[s.helperType]?i.push(r[s.helperType]):r[s.name]&&i.push(r[s.name]);for(var l=0;l<r._global.length;l++){var u=r._global[l];u.pred(s,this)&&-1==H(i,u.val)&&i.push(u.val)}return i},getStateAfter:function(e,t){var n=this.doc;return xt(this,(e=dt(n,null==e?n.first+n.size-1:e))+1,t).state},cursorCoords:function(e,t){var n=this.doc.sel.primary();return xi(this,null==e?n.head:"object"==typeof e?ht(this.doc,e):e?n.from():n.to(),t||"page")},charCoords:function(e,t){return Ai(this,ht(this.doc,e),t||"page")},coordsChar:function(e,t){return wi(this,(e=vi(this,e,t||"page")).left,e.top)},lineAtHeight:function(e,t){return e=vi(this,{top:e,left:0},t||"page").top,nt(this.doc,e+this.display.viewOffset)},heightAtLine:function(e,t,n){var i,r=!1;if("number"==typeof e){var s=this.doc.first+this.doc.size-1;e<this.doc.first?e=this.doc.first:e>s&&(e=s,r=!0),i=qe(this.doc,e)}else i=e;return mi(this,i,{top:0,left:0},t||"page",n||r).top+(r?this.doc.height-on(i):0)},defaultTextHeight:function(){return Ni(this.display)},defaultCharWidth:function(){return Bi(this.display)},getViewport:function(){return{from:this.display.viewFrom,to:this.display.viewTo}},addWidget:function(e,t,n,i,r){var s=this.display,o=(e=xi(this,ht(this.doc,e))).bottom,a=e.left;if(t.style.position="absolute",t.setAttribute("cm-ignore-events","true"),this.display.input.setUneditable(t),s.sizer.appendChild(t),"over"==i)o=e.top;else if("above"==i||"near"==i){var l=Math.max(s.wrapper.clientHeight,this.doc.height),u=Math.max(s.sizer.clientWidth,s.lineSpace.clientWidth);("above"==i||e.bottom+t.offsetHeight>l)&&e.top>t.offsetHeight?o=e.top-t.offsetHeight:e.bottom+t.offsetHeight<=l&&(o=e.bottom),a+t.offsetWidth>u&&(a=u-t.offsetWidth)}t.style.top=o+"px",t.style.left=t.style.right="","right"==r?(a=s.sizer.clientWidth-t.offsetWidth,t.style.right="0px"):("left"==r?a=0:"middle"==r&&(a=(s.sizer.clientWidth-t.offsetWidth)/2),t.style.left=a+"px"),n&&rr(this,{left:a,top:o,right:a+t.offsetWidth,bottom:o+t.offsetHeight})},triggerOnKeyDown:Lr(ua),triggerOnKeyPress:Lr(ha),triggerOnKeyUp:da,triggerOnMouseDown:Lr(Aa),execCommand:function(e){if(qo.hasOwnProperty(e))return qo[e].call(null,this)},triggerElectric:Lr((function(e){Wa(this,e)})),findPosH:function(e,t,n,i){var r=1;t<0&&(r=-1,t=-t);for(var s=ht(this.doc,e),o=0;o<t&&!(s=Ka(this.doc,s,r,n,i)).hitSide;++o);return s},moveH:Lr((function(e,t){var n=this;this.extendSelectionsBy((function(i){return n.display.shift||n.doc.extend||i.empty()?Ka(n.doc,i.head,e,t,n.options.rtlMoveVisually):e<0?i.from():i.to()}),W)})),deleteH:Lr((function(e,t){var n=this.doc.sel,i=this.doc;n.somethingSelected()?i.replaceSelection("",null,"+delete"):Qo(this,(function(n){var r=Ka(i,n.head,e,t,!1);return e<0?{from:r,to:n.head}:{from:n.head,to:r}}))})),findPosV:function(e,t,n,i){var r=1,s=i;t<0&&(r=-1,t=-t);for(var o=ht(this.doc,e),a=0;a<t;++a){var l=xi(this,o,"div");if(null==s?s=l.left:l.left=s,(o=qa(this,l,r,n)).hitSide)break}return o},moveV:Lr((function(e,t){var n=this,i=this.doc,r=[],s=!this.display.shift&&!i.extend&&i.sel.somethingSelected();if(i.extendSelectionsBy((function(o){if(s)return e<0?o.from():o.to();var a=xi(n,o.head,"div");null!=o.goalColumn&&(a.left=o.goalColumn),r.push(a.left);var l=qa(n,a,e,t);return"page"==t&&o==i.sel.primary()&&or(n,Ai(n,l,"div").top-a.top),l}),W),r.length)for(var o=0;o<i.sel.ranges.length;o++)i.sel.ranges[o].goalColumn=r[o]})),findWordAt:function(e){var t=qe(this.doc,e.line).text,n=e.ch,i=e.ch;if(t){var r=this.getHelper(e,"wordChars");"before"!=e.sticky&&i!=t.length||!n?++i:--n;for(var s=t.charAt(n),o=ne(s,r)?function(e){return ne(e,r)}:/\s/.test(s)?function(e){return/\s/.test(e)}:function(e){return!/\s/.test(e)&&!ne(e)};n>0&&o(t.charAt(n-1));)--n;for(;i<t.length&&o(t.charAt(i));)++i}return new ss(st(e.line,n),st(e.line,i))},toggleOverwrite:function(e){null!=e&&e==this.state.overwrite||((this.state.overwrite=!this.state.overwrite)?L(this.display.cursorDiv,"CodeMirror-overwrite"):T(this.display.cursorDiv,"CodeMirror-overwrite"),ve(this,"overwriteToggle",this,this.state.overwrite))},hasFocus:function(){return this.display.input.getField()==I()},isReadOnly:function(){return!(!this.options.readOnly&&!this.doc.cantEdit)},scrollTo:Lr((function(e,t){lr(this,e,t)})),getScrollInfo:function(){var e=this.display.scroller;return{left:e.scrollLeft,top:e.scrollTop,height:e.scrollHeight-Yn(this)-this.display.barHeight,width:e.scrollWidth-Yn(this)-this.display.barWidth,clientHeight:Kn(this),clientWidth:Jn(this)}},scrollIntoView:Lr((function(e,t){null==e?(e={from:this.doc.sel.primary().head,to:null},null==t&&(t=this.options.cursorScrollMargin)):"number"==typeof e?e={from:st(e,0),to:null}:null==e.from&&(e={from:e,to:null}),e.to||(e.to=e.from),e.margin=t||0,null!=e.from.line?ur(this,e):dr(this,e.from,e.to,e.margin)})),setSize:Lr((function(e,t){var n=this,i=function(e){return"number"==typeof e||/^\d+$/.test(String(e))?e+"px":e};null!=e&&(this.display.wrapper.style.width=i(e)),null!=t&&(this.display.wrapper.style.height=i(t)),this.options.lineWrapping&&di(this);var r=this.display.viewFrom;this.doc.iter(r,this.display.viewTo,(function(e){if(e.widgets)for(var t=0;t<e.widgets.length;t++)if(e.widgets[t].noHScroll){ki(n,r,"widget");break}++r})),this.curOp.forceUpdate=!0,ve(this,"refresh",this)})),operation:function(e){return Dr(this,e)},startOperation:function(){return Cr(this)},endOperation:function(){return Mr(this)},refresh:Lr((function(){var e=this.display.cachedTextHeight;Ri(this),this.curOp.forceUpdate=!0,hi(this),lr(this,this.doc.scrollLeft,this.doc.scrollTop),Wr(this.display),(null==e||Math.abs(e-Ni(this.display))>.5||this.options.lineWrapping)&&ji(this),ve(this,"refresh",this)})),swapDoc:Lr((function(e){var t=this.doc;return t.cm=null,this.state.selectingText&&this.state.selectingText(),As(this,e),hi(this),this.display.input.reset(),lr(this,e.scrollLeft,e.scrollTop),this.curOp.forceScroll=!0,Nn(this,"swapDoc",this,t),t})),phrase:function(e){var t=this.options.phrases;return t&&Object.prototype.hasOwnProperty.call(t,e)?t[e]:e},getInputField:function(){return this.display.input.getField()},getWrapperElement:function(){return this.display.wrapper},getScrollerElement:function(){return this.display.scroller},getGutterElement:function(){return this.display.gutters}},be(e),e.registerHelper=function(t,i,r){n.hasOwnProperty(t)||(n[t]=e[t]={_global:[]}),n[t][i]=r},e.registerGlobalHelper=function(t,i,r,s){e.registerHelper(t,i,s),n[t]._global.push({pred:r,val:s})}}function Ka(e,t,n,i,r){var s=t,o=n,a=qe(e,t.line),l=r&&"rtl"==e.direction?-n:n;function u(){var n=t.line+l;return!(n<e.first||n>=e.first+e.size)&&(t=new st(n,t.ch,t.sticky),a=qe(e,n))}function c(s){var o;if("codepoint"==i){var c=a.text.charCodeAt(t.ch+(i>0?0:-1));o=isNaN(c)?null:new st(t.line,Math.max(0,Math.min(a.text.length,t.ch+n*(c>=55296&&c<56320?2:1))),-n)}else o=r?Ko(e.cm,a,t,n):Yo(a,t,n);if(null==o){if(s||!u())return!1;t=Jo(r,e.cm,a,t.line,l)}else t=o;return!0}if("char"==i||"codepoint"==i)c();else if("column"==i)c(!0);else if("word"==i||"group"==i)for(var d=null,h="group"==i,f=e.cm&&e.cm.getHelper(t,"wordChars"),p=!0;!(n<0)||c(!p);p=!1){var g=a.text.charAt(t.ch)||"\n",m=ne(g,f)?"w":h&&"\n"==g?"n":!h||/\s/.test(g)?null:"p";if(!h||p||m||(m="s"),d&&d!=m){n<0&&(n=1,c(),t.sticky="after");break}if(m&&(d=m),n>0&&!c(!p))break}var v=Zs(e,t,s,o,!0);return at(s,v)&&(v.hitSide=!0),v}function qa(e,t,n,i){var r,s,o=e.doc,a=t.left;if("page"==i){var l=Math.min(e.display.wrapper.clientHeight,window.innerHeight||document.documentElement.clientHeight),u=Math.max(l-.5*Ni(e.display),3);r=(n>0?t.bottom:t.top)+n*u}else"line"==i&&(r=n>0?t.bottom+3:t.top-3);for(;(s=wi(e,a,r)).outside;){if(n<0?r<=0:r>=o.height){s.hitSide=!0;break}r+=5*n}return s}var _a=function(e){this.cm=e,this.lastAnchorNode=this.lastAnchorOffset=this.lastFocusNode=this.lastFocusOffset=null,this.polling=new F,this.composing=null,this.gracePeriod=!1,this.readDOMTimeout=null};function $a(e,t){var n=ti(e,t.line);if(!n||n.hidden)return null;var i=qe(e.doc,t.line),r=_n(n,i,t.line),s=he(i,e.doc.direction),o="left";s&&(o=ce(s,t.ch)%2?"right":"left");var a=oi(r.map,t.ch,o);return a.offset="right"==a.collapse?a.end:a.start,a}function el(e){for(var t=e;t;t=t.parentNode)if(/CodeMirror-gutter-wrapper/.test(t.className))return!0;return!1}function tl(e,t){return t&&(e.bad=!0),e}function nl(e,t,n,i,r){var s="",o=!1,a=e.doc.lineSeparator(),l=!1;function u(e){return function(t){return t.id==e}}function c(){o&&(s+=a,l&&(s+=a),o=l=!1)}function d(e){e&&(c(),s+=e)}function h(t){if(1==t.nodeType){var n=t.getAttribute("cm-text");if(n)return void d(n);var s,f=t.getAttribute("cm-marker");if(f){var p=e.findMarks(st(i,0),st(r+1,0),u(+f));return void(p.length&&(s=p[0].find(0))&&d(_e(e.doc,s.from,s.to).join(a)))}if("false"==t.getAttribute("contenteditable"))return;var g=/^(pre|div|p|li|table|br)$/i.test(t.nodeName);if(!/^br$/i.test(t.nodeName)&&0==t.textContent.length)return;g&&c();for(var m=0;m<t.childNodes.length;m++)h(t.childNodes[m]);/^(pre|p)$/i.test(t.nodeName)&&(l=!0),g&&(o=!0)}else 3==t.nodeType&&d(t.nodeValue.replace(/\u200b/g,"").replace(/\u00a0/g," "))}for(;h(t),t!=n;)t=t.nextSibling,l=!1;return s}function il(e,t,n){var i;if(t==e.display.lineDiv){if(!(i=e.display.lineDiv.childNodes[n]))return tl(e.clipPos(st(e.display.viewTo-1)),!0);t=null,n=0}else for(i=t;;i=i.parentNode){if(!i||i==e.display.lineDiv)return null;if(i.parentNode&&i.parentNode==e.display.lineDiv)break}for(var r=0;r<e.display.view.length;r++){var s=e.display.view[r];if(s.node==i)return rl(s,t,n)}}function rl(e,t,n){var i=e.text.firstChild,r=!1;if(!t||!D(i,t))return tl(st(tt(e.line),0),!0);if(t==i&&(r=!0,t=i.childNodes[n],n=0,!t)){var s=e.rest?J(e.rest):e.line;return tl(st(tt(s),s.text.length),r)}var o=3==t.nodeType?t:null,a=t;for(o||1!=t.childNodes.length||3!=t.firstChild.nodeType||(o=t.firstChild,n&&(n=o.nodeValue.length));a.parentNode!=i;)a=a.parentNode;var l=e.measure,u=l.maps;function c(t,n,i){for(var r=-1;r<(u?u.length:0);r++)for(var s=r<0?l.map:u[r],o=0;o<s.length;o+=3){var a=s[o+2];if(a==t||a==n){var c=tt(r<0?e.line:e.rest[r]),d=s[o]+i;return(i<0||a!=t)&&(d=s[o+(i?1:0)]),st(c,d)}}}var d=c(o,a,n);if(d)return tl(d,r);for(var h=a.nextSibling,f=o?o.nodeValue.length-n:0;h;h=h.nextSibling){if(d=c(h,h.firstChild,0))return tl(st(d.line,d.ch-f),r);f+=h.textContent.length}for(var p=a.previousSibling,g=n;p;p=p.previousSibling){if(d=c(p,p.firstChild,-1))return tl(st(d.line,d.ch+g),r);g+=p.textContent.length}}_a.prototype.init=function(e){var t=this,n=this,i=n.cm,r=n.div=e.lineDiv;function s(e){for(var t=e.target;t;t=t.parentNode){if(t==r)return!0;if(/\bCodeMirror-(?:line)?widget\b/.test(t.className))break}return!1}function o(e){if(s(e)&&!Ae(i,e)){if(i.somethingSelected())Xa({lineWise:!1,text:i.getSelections()}),"cut"==e.type&&i.replaceSelection("",null,"cut");else{if(!i.options.lineWiseCopyCut)return;var t=Qa(i);Xa({lineWise:!0,text:t.text}),"cut"==e.type&&i.operation((function(){i.setSelections(t.ranges,0,G),i.replaceSelection("",null,"cut")}))}if(e.clipboardData){e.clipboardData.clearData();var o=Ua.text.join("\n");if(e.clipboardData.setData("Text",o),e.clipboardData.getData("Text")==o)return void e.preventDefault()}var a=Ya(),l=a.firstChild;i.display.lineSpace.insertBefore(a,i.display.lineSpace.firstChild),l.value=Ua.text.join("\n");var u=document.activeElement;O(l),setTimeout((function(){i.display.lineSpace.removeChild(a),u.focus(),u==r&&n.showPrimarySelection()}),50)}}Za(r,i.options.spellcheck,i.options.autocorrect,i.options.autocapitalize),pe(r,"paste",(function(e){!s(e)||Ae(i,e)||Va(e,i)||a<=11&&setTimeout(Ir(i,(function(){return t.updateFromDOM()})),20)})),pe(r,"compositionstart",(function(e){t.composing={data:e.data,done:!1}})),pe(r,"compositionupdate",(function(e){t.composing||(t.composing={data:e.data,done:!1})})),pe(r,"compositionend",(function(e){t.composing&&(e.data!=t.composing.data&&t.readFromDOMSoon(),t.composing.done=!0)})),pe(r,"touchstart",(function(){return n.forceCompositionEnd()})),pe(r,"input",(function(){t.composing||t.readFromDOMSoon()})),pe(r,"copy",o),pe(r,"cut",o)},_a.prototype.screenReaderLabelChanged=function(e){e?this.div.setAttribute("aria-label",e):this.div.removeAttribute("aria-label")},_a.prototype.prepareSelection=function(){var e=Vi(this.cm,!1);return e.focus=document.activeElement==this.div,e},_a.prototype.showSelection=function(e,t){e&&this.cm.display.view.length&&((e.focus||t)&&this.showPrimarySelection(),this.showMultipleSelections(e))},_a.prototype.getSelection=function(){return this.cm.display.wrapper.ownerDocument.getSelection()},_a.prototype.showPrimarySelection=function(){var e=this.getSelection(),t=this.cm,i=t.doc.sel.primary(),r=i.from(),s=i.to();if(t.display.viewTo==t.display.viewFrom||r.line>=t.display.viewTo||s.line<t.display.viewFrom)e.removeAllRanges();else{var o=il(t,e.anchorNode,e.anchorOffset),a=il(t,e.focusNode,e.focusOffset);if(!o||o.bad||!a||a.bad||0!=ot(ct(o,a),r)||0!=ot(ut(o,a),s)){var l=t.display.view,u=r.line>=t.display.viewFrom&&$a(t,r)||{node:l[0].measure.map[2],offset:0},c=s.line<t.display.viewTo&&$a(t,s);if(!c){var d=l[l.length-1].measure,h=d.maps?d.maps[d.maps.length-1]:d.map;c={node:h[h.length-1],offset:h[h.length-2]-h[h.length-3]}}if(u&&c){var f,p=e.rangeCount&&e.getRangeAt(0);try{f=E(u.node,u.offset,c.offset,c.node)}catch(e){}f&&(!n&&t.state.focused?(e.collapse(u.node,u.offset),f.collapsed||(e.removeAllRanges(),e.addRange(f))):(e.removeAllRanges(),e.addRange(f)),p&&null==e.anchorNode?e.addRange(p):n&&this.startGracePeriod()),this.rememberSelection()}else e.removeAllRanges()}}},_a.prototype.startGracePeriod=function(){var e=this;clearTimeout(this.gracePeriod),this.gracePeriod=setTimeout((function(){e.gracePeriod=!1,e.selectionChanged()&&e.cm.operation((function(){return e.cm.curOp.selectionChanged=!0}))}),20)},_a.prototype.showMultipleSelections=function(e){P(this.cm.display.cursorDiv,e.cursors),P(this.cm.display.selectionDiv,e.selection)},_a.prototype.rememberSelection=function(){var e=this.getSelection();this.lastAnchorNode=e.anchorNode,this.lastAnchorOffset=e.anchorOffset,this.lastFocusNode=e.focusNode,this.lastFocusOffset=e.focusOffset},_a.prototype.selectionInEditor=function(){var e=this.getSelection();if(!e.rangeCount)return!1;var t=e.getRangeAt(0).commonAncestorContainer;return D(this.div,t)},_a.prototype.focus=function(){"nocursor"!=this.cm.options.readOnly&&(this.selectionInEditor()&&document.activeElement==this.div||this.showSelection(this.prepareSelection(),!0),this.div.focus())},_a.prototype.blur=function(){this.div.blur()},_a.prototype.getField=function(){return this.div},_a.prototype.supportsTouch=function(){return!0},_a.prototype.receivedFocus=function(){var e=this;function t(){e.cm.state.focused&&(e.pollSelection(),e.polling.set(e.cm.options.pollInterval,t))}this.selectionInEditor()?this.pollSelection():Dr(this.cm,(function(){return e.cm.curOp.selectionChanged=!0})),this.polling.set(this.cm.options.pollInterval,t)},_a.prototype.selectionChanged=function(){var e=this.getSelection();return e.anchorNode!=this.lastAnchorNode||e.anchorOffset!=this.lastAnchorOffset||e.focusNode!=this.lastFocusNode||e.focusOffset!=this.lastFocusOffset},_a.prototype.pollSelection=function(){if(null==this.readDOMTimeout&&!this.gracePeriod&&this.selectionChanged()){var e=this.getSelection(),t=this.cm;if(m&&c&&this.cm.display.gutterSpecs.length&&el(e.anchorNode))return this.cm.triggerOnKeyDown({type:"keydown",keyCode:8,preventDefault:Math.abs}),this.blur(),void this.focus();if(!this.composing){this.rememberSelection();var n=il(t,e.anchorNode,e.anchorOffset),i=il(t,e.focusNode,e.focusOffset);n&&i&&Dr(t,(function(){Us(t.doc,as(n,i),G),(n.bad||i.bad)&&(t.curOp.selectionChanged=!0)}))}}},_a.prototype.pollContent=function(){null!=this.readDOMTimeout&&(clearTimeout(this.readDOMTimeout),this.readDOMTimeout=null);var e,t,n,i=this.cm,r=i.display,s=i.doc.sel.primary(),o=s.from(),a=s.to();if(0==o.ch&&o.line>i.firstLine()&&(o=st(o.line-1,qe(i.doc,o.line-1).length)),a.ch==qe(i.doc,a.line).text.length&&a.line<i.lastLine()&&(a=st(a.line+1,0)),o.line<r.viewFrom||a.line>r.viewTo-1)return!1;o.line==r.viewFrom||0==(e=zi(i,o.line))?(t=tt(r.view[0].line),n=r.view[0].node):(t=tt(r.view[e].line),n=r.view[e-1].node.nextSibling);var l,u,c=zi(i,a.line);if(c==r.view.length-1?(l=r.viewTo-1,u=r.lineDiv.lastChild):(l=tt(r.view[c+1].line)-1,u=r.view[c+1].node.previousSibling),!n)return!1;for(var d=i.doc.splitLines(nl(i,n,u,t,l)),h=_e(i.doc,st(t,0),st(l,qe(i.doc,l).text.length));d.length>1&&h.length>1;)if(J(d)==J(h))d.pop(),h.pop(),l--;else{if(d[0]!=h[0])break;d.shift(),h.shift(),t++}for(var f=0,p=0,g=d[0],m=h[0],v=Math.min(g.length,m.length);f<v&&g.charCodeAt(f)==m.charCodeAt(f);)++f;for(var A=J(d),x=J(h),y=Math.min(A.length-(1==d.length?f:0),x.length-(1==h.length?f:0));p<y&&A.charCodeAt(A.length-p-1)==x.charCodeAt(x.length-p-1);)++p;if(1==d.length&&1==h.length&&t==o.line)for(;f&&f>o.ch&&A.charCodeAt(A.length-p-1)==x.charCodeAt(x.length-p-1);)f--,p++;d[d.length-1]=A.slice(0,A.length-p).replace(/^\u200b+/,""),d[0]=d[0].slice(f).replace(/\u200b+$/,"");var b=st(t,f),w=st(l,h.length?J(h).length-p:0);return d.length>1||d[0]||ot(b,w)?(io(i.doc,d,b,w,"+input"),!0):void 0},_a.prototype.ensurePolled=function(){this.forceCompositionEnd()},_a.prototype.reset=function(){this.forceCompositionEnd()},_a.prototype.forceCompositionEnd=function(){this.composing&&(clearTimeout(this.readDOMTimeout),this.composing=null,this.updateFromDOM(),this.div.blur(),this.div.focus())},_a.prototype.readFromDOMSoon=function(){var e=this;null==this.readDOMTimeout&&(this.readDOMTimeout=setTimeout((function(){if(e.readDOMTimeout=null,e.composing){if(!e.composing.done)return;e.composing=null}e.updateFromDOM()}),80))},_a.prototype.updateFromDOM=function(){var e=this;!this.cm.isReadOnly()&&this.pollContent()||Dr(this.cm,(function(){return Ri(e.cm)}))},_a.prototype.setUneditable=function(e){e.contentEditable="false"},_a.prototype.onKeyPress=function(e){0==e.charCode||this.composing||(e.preventDefault(),this.cm.isReadOnly()||Ir(this.cm,Ga)(this.cm,String.fromCharCode(null==e.charCode?e.keyCode:e.charCode),0))},_a.prototype.readOnlyChanged=function(e){this.div.contentEditable=String("nocursor"!=e)},_a.prototype.onContextMenu=function(){},_a.prototype.resetPosition=function(){},_a.prototype.needsContentAttribute=!0;var sl=function(e){this.cm=e,this.prevInput="",this.pollingFast=!1,this.polling=new F,this.hasSelection=!1,this.composing=null};function ol(e,t){if((t=t?R(t):{}).value=e.value,!t.tabindex&&e.tabIndex&&(t.tabindex=e.tabIndex),!t.placeholder&&e.placeholder&&(t.placeholder=e.placeholder),null==t.autofocus){var n=I();t.autofocus=n==e||null!=e.getAttribute("autofocus")&&n==document.body}function i(){e.value=a.getValue()}var r;if(e.form&&(pe(e.form,"submit",i),!t.leaveSubmitMethodAlone)){var s=e.form;r=s.submit;try{var o=s.submit=function(){i(),s.submit=r,s.submit(),s.submit=o}}catch(e){}}t.finishInit=function(n){n.save=i,n.getTextArea=function(){return e},n.toTextArea=function(){n.toTextArea=isNaN,i(),e.parentNode.removeChild(n.getWrapperElement()),e.style.display="",e.form&&(me(e.form,"submit",i),t.leaveSubmitMethodAlone||"function"!=typeof e.form.submit||(e.form.submit=r))}},e.style.display="none";var a=Ra((function(t){return e.parentNode.insertBefore(t,e.nextSibling)}),t);return a}function al(e){e.off=me,e.on=pe,e.wheelEventPixels=ns,e.Doc=Co,e.splitLines=je,e.countColumn=k,e.findColumn=Q,e.isWordChar=te,e.Pass=X,e.signal=ve,e.Line=un,e.changeEnd=ls,e.scrollbarModel=yr,e.Pos=st,e.cmpPos=ot,e.modes=Fe,e.mimeModes=He,e.resolveMode=Ge,e.getMode=Ve,e.modeExtensions=We,e.extendMode=Qe,e.copyState=Ze,e.startState=Je,e.innerMode=Ye,e.commands=qo,e.keyMap=ko,e.keyName=Vo,e.isModifierKey=Xo,e.lookupKey=Uo,e.normalizeKeyMap=Ho,e.StringStream=Ke,e.SharedTextMarker=vo,e.TextMarker=go,e.LineWidget=co,e.e_preventDefault=we,e.e_stopPropagation=Ce,e.e_stop=Ee,e.addClass=L,e.contains=D,e.rmClass=T,e.keyNames=jo}sl.prototype.init=function(e){var t=this,n=this,i=this.cm;this.createField(e);var r=this.textarea;function s(e){if(!Ae(i,e)){if(i.somethingSelected())Xa({lineWise:!1,text:i.getSelections()});else{if(!i.options.lineWiseCopyCut)return;var t=Qa(i);Xa({lineWise:!0,text:t.text}),"cut"==e.type?i.setSelections(t.ranges,null,G):(n.prevInput="",r.value=t.text.join("\n"),O(r))}"cut"==e.type&&(i.state.cutIncoming=+new Date)}}e.wrapper.insertBefore(this.wrapper,e.wrapper.firstChild),g&&(r.style.width="0px"),pe(r,"input",(function(){o&&a>=9&&t.hasSelection&&(t.hasSelection=null),n.poll()})),pe(r,"paste",(function(e){Ae(i,e)||Va(e,i)||(i.state.pasteIncoming=+new Date,n.fastPoll())})),pe(r,"cut",s),pe(r,"copy",s),pe(e.scroller,"paste",(function(t){if(!Vn(e,t)&&!Ae(i,t)){if(!r.dispatchEvent)return i.state.pasteIncoming=+new Date,void n.focus();var s=new Event("paste");s.clipboardData=t.clipboardData,r.dispatchEvent(s)}})),pe(e.lineSpace,"selectstart",(function(t){Vn(e,t)||we(t)})),pe(r,"compositionstart",(function(){var e=i.getCursor("from");n.composing&&n.composing.range.clear(),n.composing={start:e,range:i.markText(e,i.getCursor("to"),{className:"CodeMirror-composing"})}})),pe(r,"compositionend",(function(){n.composing&&(n.poll(),n.composing.range.clear(),n.composing=null)}))},sl.prototype.createField=function(e){this.wrapper=Ya(),this.textarea=this.wrapper.firstChild},sl.prototype.screenReaderLabelChanged=function(e){e?this.textarea.setAttribute("aria-label",e):this.textarea.removeAttribute("aria-label")},sl.prototype.prepareSelection=function(){var e=this.cm,t=e.display,n=e.doc,i=Vi(e);if(e.options.moveInputWithCursor){var r=xi(e,n.sel.primary().head,"div"),s=t.wrapper.getBoundingClientRect(),o=t.lineDiv.getBoundingClientRect();i.teTop=Math.max(0,Math.min(t.wrapper.clientHeight-10,r.top+o.top-s.top)),i.teLeft=Math.max(0,Math.min(t.wrapper.clientWidth-10,r.left+o.left-s.left))}return i},sl.prototype.showSelection=function(e){var t=this.cm.display;P(t.cursorDiv,e.cursors),P(t.selectionDiv,e.selection),null!=e.teTop&&(this.wrapper.style.top=e.teTop+"px",this.wrapper.style.left=e.teLeft+"px")},sl.prototype.reset=function(e){if(!this.contextMenuPending&&!this.composing){var t=this.cm;if(t.somethingSelected()){this.prevInput="";var n=t.getSelection();this.textarea.value=n,t.state.focused&&O(this.textarea),o&&a>=9&&(this.hasSelection=n)}else e||(this.prevInput=this.textarea.value="",o&&a>=9&&(this.hasSelection=null))}},sl.prototype.getField=function(){return this.textarea},sl.prototype.supportsTouch=function(){return!1},sl.prototype.focus=function(){if("nocursor"!=this.cm.options.readOnly&&(!v||I()!=this.textarea))try{this.textarea.focus()}catch(e){}},sl.prototype.blur=function(){this.textarea.blur()},sl.prototype.resetPosition=function(){this.wrapper.style.top=this.wrapper.style.left=0},sl.prototype.receivedFocus=function(){this.slowPoll()},sl.prototype.slowPoll=function(){var e=this;this.pollingFast||this.polling.set(this.cm.options.pollInterval,(function(){e.poll(),e.cm.state.focused&&e.slowPoll()}))},sl.prototype.fastPoll=function(){var e=!1,t=this;function n(){t.poll()||e?(t.pollingFast=!1,t.slowPoll()):(e=!0,t.polling.set(60,n))}t.pollingFast=!0,t.polling.set(20,n)},sl.prototype.poll=function(){var e=this,t=this.cm,n=this.textarea,i=this.prevInput;if(this.contextMenuPending||!t.state.focused||Oe(n)&&!i&&!this.composing||t.isReadOnly()||t.options.disableInput||t.state.keySeq)return!1;var r=n.value;if(r==i&&!t.somethingSelected())return!1;if(o&&a>=9&&this.hasSelection===r||A&&/[\uf700-\uf7ff]/.test(r))return t.display.input.reset(),!1;if(t.doc.sel==t.display.selForContextMenu){var s=r.charCodeAt(0);if(8203!=s||i||(i="​"),8666==s)return this.reset(),this.cm.execCommand("undo")}for(var l=0,u=Math.min(i.length,r.length);l<u&&i.charCodeAt(l)==r.charCodeAt(l);)++l;return Dr(t,(function(){Ga(t,r.slice(l),i.length-l,null,e.composing?"*compose":null),r.length>1e3||r.indexOf("\n")>-1?n.value=e.prevInput="":e.prevInput=r,e.composing&&(e.composing.range.clear(),e.composing.range=t.markText(e.composing.start,t.getCursor("to"),{className:"CodeMirror-composing"}))})),!0},sl.prototype.ensurePolled=function(){this.pollingFast&&this.poll()&&(this.pollingFast=!1)},sl.prototype.onKeyPress=function(){o&&a>=9&&(this.hasSelection=null),this.fastPoll()},sl.prototype.onContextMenu=function(e){var t=this,n=t.cm,i=n.display,r=t.textarea;t.contextMenuPending&&t.contextMenuPending();var s=Oi(n,e),u=i.scroller.scrollTop;if(s&&!d){n.options.resetSelectionOnContextMenu&&-1==n.doc.sel.contains(s)&&Ir(n,Us)(n.doc,as(s),G);var c,h=r.style.cssText,f=t.wrapper.style.cssText,p=t.wrapper.offsetParent.getBoundingClientRect();if(t.wrapper.style.cssText="position: static",r.style.cssText="position: absolute; width: 30px; height: 30px;\n      top: "+(e.clientY-p.top-5)+"px; left: 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1.8-.85-2.31-4.98c-.24-.5-.02-1.1.48-1.33l.28-.08 2.3-.45L8 5.12V15.9l1.82-1.47.25-.16m3.57 7.7a.99.99 0 01-1.33-.47l-2.18-4.74-2.51 2.02c-.17.14-.38.22-.62.22a1 1 0 01-1-1V3a1 1 0 011-1c.24 0 .47.09.64.23l.01-.01 11.49 9.64a1.001 1.001 0 01-.44 1.75l-3.16.62 2.2 4.73c.26.5.02 1.09-.48 1.32l-3.62 1.69z"/></svg>',"select"),this.addActionButton(n,'<svg viewBox="0 0 24 24"><path d="M9 3v1H4v2h1v13a2 2 0 002 2h10a2 2 0 002-2V6h1V4h-5V3H9M7 6h10v13H7V6m2 2v9h2V8H9m4 0v9h2V8h-2z"/></svg>',"delete"),this.uiStyleSettings.clearButtonVisible&&this.addActionButton(n,'<svg viewBox="0 0 24 24"><path d="M19.36 2.72l1.42 1.42-5.72 5.71c1.07 1.54 1.22 3.39.32 4.59L9.06 8.12c1.2-.9 3.05-.75 4.59.32l5.71-5.72M5.93 17.57c-2.01-2.01-3.24-4.41-3.58-6.65l4.88-2.09 7.44 7.44-2.09 4.88c-2.24-.34-4.64-1.57-6.65-3.58z"/></svg>',"clear"),this.uiStyleSettings.undoButtonVisible&&this.addActionButton(n,'<svg viewBox="0 0 24 24"><path d="M12.5 8c-2.65 0-5.05 1-6.9 2.6L2 7v9h9l-3.62-3.62c1.39-1.16 3.16-1.88 5.12-1.88 3.54 0 6.55 2.31 7.6 5.5l2.37-.78C21.08 11.03 17.15 8 12.5 8z"/></svg>',"undo"),this.uiStyleSettings.redoButtonVisible&&this.addActionButton(n,'<svg viewBox="0 0 24 24"><path d="M18.4 10.6C16.55 9 14.15 8 11.5 8c-4.65 0-8.58 3.03-9.96 7.22L3.9 16a8.002 8.002 0 017.6-5.5c1.95 0 3.73.72 5.12 1.88L13 16h9V7l-3.6 3.6z"/></svg>',"redo"),this.uiStyleSettings.zoomButtonVisible&&this.addActionButton(n,'<svg viewBox="0 0 24 24"><path d="M15.5 14l5 5-1.5 1.5-5-5v-.79l-.27-.28A6.471 6.471 0 019.5 16 6.5 6.5 0 013 9.5 6.5 6.5 0 019.5 3 6.5 6.5 0 0116 9.5c0 1.61-.59 3.09-1.57 4.23l.28.27h.79m-6 0C12 14 14 12 14 9.5S12 5 9.5 5 5 7 5 9.5 7 14 9.5 14m2.5-4h-2v2H9v-2H7V9h2V7h1v2h2v1z"/></svg>',"zoom"),this.uiStyleSettings.zoomButtonVisible&&this.uiStyleSettings.zoomOutButtonVisible&&this.addActionButton(n,'<svg viewBox="0 0 24 24"><path d="M15.5 14h-.79l-.28-.27A6.471 6.471 0 0016 9.5 6.5 6.5 0 009.5 3 6.5 6.5 0 003 9.5 6.5 6.5 0 009.5 16c1.61 0 3.09-.59 4.23-1.57l.27.28v.79l5 5 1.5-1.5-5-5m-6 0C7 14 5 12 5 9.5S7 5 9.5 5 14 7 14 9.5 12 14 9.5 14M7 9h5v1H7V9z"/></svg>',"zoom-out"),this.uiStyleSettings.notesButtonVisible&&this.addActionButton(n,'<svg viewBox="0 0 24 24"><path d="M18.13 12l1.26-1.26c.44-.44 1-.68 1.61-.74V9l-6-6H5c-1.11 0-2 .89-2 2v14a2 2 0 002 2h6v-1.87l.13-.13H5V5h7v7h6.13M14 4.5l5.5 5.5H14V4.5m5.13 9.33l2.04 2.04L15.04 22H13v-2.04l6.13-6.13m3.72.36l-.98.98-2.04-2.04.98-.98c.19-.2.52-.2.72 0l1.32 1.32c.2.2.2.53 0 .72z"/></svg>',"notes"),this.markerButtonBlock=document.createElement("div"),this.markerButtonBlock.className=this.toolbarBlockStyleClass.name,this.markerButtonBlock.style.flexGrow="2",this.markerButtonBlock.style.textAlign="center",this.uiContainer.appendChild(this.markerButtonBlock),this.markerButtonOverflowBlock=document.createElement("div"),this.markerButtonOverflowBlock.className=this.toolbarOverflowBlockStyleClass.name+" "+(this.uiStyleSettings.toolbarOverflowBlockStyleColorsClassName?this.uiStyleSettings.toolbarOverflowBlockStyleColorsClassName:this.toolbarOverflowBlockStyleColorsClass.name),this.markerButtonOverflowBlock.style.display="none",this.uiContainer.appendChild(this.markerButtonOverflowBlock),this.markerItems&&(this.markerItems.forEach((function(e){var n=document.createElement("div");n.className=""+t.toolbarButtonStyleClass.name,n.setAttribute("data-type-name",e.typeName),n.innerHTML=e.icon,n.addEventListener("click",(function(){t.markerToolbarButtonClicked(n,e)})),t.buttons.push(n),t.markerButtons.push(n)})),this.overflowButton=document.createElement("div"),this.overflowButton.className=this.toolbarButtonStyleClass.name+" "+(this.uiStyleSettings.toolbarButtonStyleColorsClassName?this.uiStyleSettings.toolbarButtonStyleColorsClassName:this.toolbarButtonStyleColorsClass.name),this.overflowButton.innerHTML='<svg viewBox="0 0 24 24"><path d="M12 16a2 2 0 012 2 2 2 0 01-2 2 2 2 0 01-2-2 2 2 0 012-2m0-6a2 2 0 012 2 2 2 0 01-2 2 2 2 0 01-2-2 2 2 0 012-2m0-6a2 2 0 012 2 2 2 0 01-2 2 2 2 0 01-2-2 2 2 0 012-2z"/></svg>',this.overflowButton.addEventListener("click",this.overflowButtonClicked),this.markerButtonBlock.appendChild(this.overflowButton));var i=document.createElement("div");i.className=this.toolbarBlockStyleClass.name,i.style.whiteSpace="nowrap",i.style.display=!1!==this.uiStyleSettings.resultButtonBlockVisible?"":"none",this.uiContainer.appendChild(i),this.addActionButton(i,'<svg viewBox="0 0 24 24"><path d="M9 20.42l-6.21-6.21 2.83-2.83L9 14.77l9.88-9.89 2.83 2.83L9 20.42z"/></svg>',"render"),this.addActionButton(i,'<svg viewBox="0 0 24 24"><path d="M20 6.91L17.09 4 12 9.09 6.91 4 4 6.91 9.09 12 4 17.09 6.91 20 12 14.91 17.09 20 20 17.09 14.91 12 20 6.91z"/></svg>',"close"),this.markerjsContainer.appendChild(this.uiContainer),this.setSelectMode(),this.setCurrentMarker(),this.adjustLayout()},e.prototype.addButtonClickListener=function(e){this.buttonClickListeners.push(e)},e.prototype.removeButtonClickListener=function(e){this.buttonClickListeners.indexOf(e)>-1&&this.buttonClickListeners.splice(this.buttonClickListeners.indexOf(e),1)},e.prototype.setSelectMode=function(){this.resetButtonStyles(),this.setActiveButton(this.buttons[0])},e.prototype.adjustLayout=function(){if(this.markerButtons&&this.markerButtons.length>0){var e=Math.floor(this.markerButtonBlock.clientWidth/this.uiStyleSettings.toolbarHeight)-1;this.markerButtonBlock.innerHTML="",this.markerButtonOverflowBlock.innerHTML="";for(var t=0;t<this.markerButtons.length;t++)t<e||t===e&&this.markerButtons.length-1===e?this.markerButtonBlock.appendChild(this.markerButtons[t]):(t===e&&this.markerButtonBlock.appendChild(this.overflowButton),this.markerButtonOverflowBlock.appendChild(this.markerButtons[t]))}},e.prototype.overflowButtonClicked=function(){"none"!==this.markerButtonOverflowBlock.style.display?(this.markerButtonOverflowBlock.className=this.markerButtonOverflowBlock.className.replace(this.styles.fadeInAnimationClassName,""),this.markerButtonOverflowBlock.style.display="none"):(this.markerButtonOverflowBlock.className+=" "+this.styles.fadeInAnimationClassName,this.markerButtonOverflowBlock.style.top=this.uiContainer.offsetTop+this.overflowButton.offsetHeight+"px",this.markerButtonOverflowBlock.style.right=this.uiContainer.offsetWidth-this.overflowButton.offsetLeft-this.overflowButton.offsetWidth+2*this.uiContainer.offsetLeft+"px",this.markerButtonOverflowBlock.style.display="inline-block")},e.prototype.resetButtonStyles=function(){var e=this;this.buttons.forEach((function(t){t.className=t.className.replace(e.uiStyleSettings.toolbarButtonStyleColorsClassName?e.uiStyleSettings.toolbarButtonStyleColorsClassName:e.toolbarButtonStyleColorsClass.name,"").trim(),t.className=t.className.replace(e.uiStyleSettings.toolbarActiveButtonStyleColorsClassName?e.uiStyleSettings.toolbarActiveButtonStyleColorsClassName:e.toolbarActiveButtonStyleColorsClass.name,"").trim(),t.className+=" "+(e.uiStyleSettings.toolbarButtonStyleColorsClassName?e.uiStyleSettings.toolbarButtonStyleColorsClassName:e.toolbarButtonStyleColorsClass.name)}))},e.prototype.addActionButton=function(e,t,n){var i=this,r=document.createElement("div");switch(r.className=""+this.toolbarButtonStyleClass.name,r.innerHTML=t,r.setAttribute("data-action",n),r.addEventListener("click",(function(){i.actionToolbarButtonClicked(r,n)})),n){case"select":case"undo":case"redo":r.style.fill=this.uiStyleSettings.selectButtonColor;break;case"delete":case"clear":r.style.fill=this.uiStyleSettings.deleteButtonColor;break;case"render":r.style.fill=this.uiStyleSettings.okButtonColor;break;case"close":r.style.fill=this.uiStyleSettings.closeButtonColor}e.appendChild(r),this.buttons.push(r)},e.prototype.addStyles=function(){this.toolbarStyleClass=this.styles.addClass(new p("toolbar","\n      width: 100%;\n      flex-shrink: 0;\n      display: flex;\n      flex-direction: row;\n      justify-content: space-between;      \n      height: "+this.uiStyleSettings.toolbarHeight+"px;\n      box-sizing: content-box;\n      "+("inline"===this.displayMode?"border-top-left-radius: "+Math.round(this.uiStyleSettings.toolbarHeight/10)+"px;":"")+"\n      "+("inline"===this.displayMode?"border-top-right-radius: "+Math.round(this.uiStyleSettings.toolbarHeight/10)+"px;":"")+"\n      overflow: hidden;\n    ")),this.toolbarStyleColorsClass=this.styles.addClass(new p("toolbar_colors","\n      background-color: "+this.uiStyleSettings.toolbarBackgroundColor+";\n      box-shadow: 0px 3px rgba(33, 33, 33, 0.1);\n    ")),this.toolbarBlockStyleClass=this.styles.addClass(new p("toolbar-block","\n        display: inline-block;\n        box-sizing: content-box;\n    ")),this.toolbarOverflowBlockStyleClass=this.styles.addClass(new p("toolbar-overflow-block","\n        position: absolute;\n        top: "+this.uiStyleSettings.toolbarHeight+"px;\n        max-width: "+2*this.uiStyleSettings.toolbarHeight+"px;\n        z-index: 10;\n        box-sizing: content-box;\n      ")),this.toolbarOverflowBlockStyleColorsClass=this.styles.addClass(new p("toolbar-overflow-block_colors","\n        background-color: "+this.uiStyleSettings.toolbarBackgroundColor+";\n      "));var e=this.uiStyleSettings.toolbarHeight/4;this.toolbarButtonStyleClass=this.styles.addClass(new p("toolbar_button","\n      display: inline-block;\n      width: "+(this.uiStyleSettings.toolbarHeight-2*e)+"px;\n      height: "+(this.uiStyleSettings.toolbarHeight-2*e)+"px;\n      padding: "+e+"px;\n      box-sizing: content-box;\n    ")),this.toolbarButtonStyleColorsClass=this.styles.addClass(new p("toolbar_button_colors","\n      fill: "+this.uiStyleSettings.toolbarColor+";\n    ")),this.toolbarActiveButtonStyleColorsClass=this.styles.addClass(new p("toolbar_active_button","\n      fill: "+this.uiStyleSettings.toolbarColor+";\n      background-color: "+this.uiStyleSettings.toolbarBackgroundHoverColor+"\n    ")),this.styles.addRule(new f("."+this.toolbarButtonStyleClass.name+" svg","\n      height: "+this.uiStyleSettings.toolbarHeight/2+"px;\n    ")),this.styles.addRule(new f("."+this.toolbarButtonStyleColorsClass.name+":hover","\n        background-color: "+this.uiStyleSettings.toolbarBackgroundHoverColor+"\n    "))},e.prototype.markerToolbarButtonClicked=function(e,t){this.setActiveButton(e),this.buttonClickListeners&&this.buttonClickListeners.length>0&&this.buttonClickListeners.forEach((function(e){return e("marker",t)})),this.markerButtonOverflowBlock.style.display="none"},e.prototype.actionToolbarButtonClicked=function(e,t){this.buttonClickListeners&&this.buttonClickListeners.length>0&&this.buttonClickListeners.forEach((function(e){return e("action",t)})),this.markerButtonOverflowBlock.style.display="none",this.setActiveButton(this.buttons[0])},e.prototype.setActiveButton=function(e){this.resetButtonStyles(),e.className=e.className.replace(this.uiStyleSettings.toolbarButtonStyleColorsClassName?this.uiStyleSettings.toolbarButtonStyleColorsClassName:this.toolbarButtonStyleColorsClass.name,"").trim(),e.className+=" "+(this.uiStyleSettings.toolbarActiveButtonStyleColorsClassName?this.uiStyleSettings.toolbarActiveButtonStyleColorsClassName:this.toolbarActiveButtonStyleColorsClass.name)},e.prototype.setActiveMarkerButton=function(e){var t=this.markerButtons.find((function(t){return t.getAttribute("data-type-name")===e}));t&&this.setActiveButton(t)},e.prototype.setCurrentMarker=function(e){var t=this;this.currentMarker=e,this.buttons.filter((function(e){return/delete|notes/.test(e.getAttribute("data-action"))})).forEach((function(e){void 0===t.currentMarker?(e.style.fillOpacity="0.4",e.style.pointerEvents="none"):(e.style.fillOpacity="1",e.style.pointerEvents="all")}))},e}(),m=function(){function e(e,t,n,i){this.panels=[],this.panelButtons=[],this.markerjsContainer=e,this.displayMode=t,this.uiStyleSettings=n,this.styles=i,this.panelButtonClick=this.panelButtonClick.bind(this),this.addStyles()}return e.prototype.addStyles=function(){var e;this.toolboxStyleClass=this.styles.addClass(new p("toolbox","\n      width: 100%;\n      flex-shrink: 0;\n      display: flex;\n      flex-direction: column;\n      font-family: sans-serif;\n      "+("popup"===this.displayMode?"height:"+2.5*this.uiStyleSettings.toolbarHeight+"px;":"")+"\n      box-sizing: content-box;\n      "+("popup"===this.displayMode?"background-color: "+this.uiStyleSettings.canvasBackgroundColor+";":"")+"\n      "+("inline"===this.displayMode?"border-bottom-left-radius: "+Math.round(this.uiStyleSettings.toolbarHeight/10)+"px;":"")+"\n      "+("inline"===this.displayMode?"border-bottom-right-radius: "+Math.round(this.uiStyleSettings.toolbarHeight/10)+"px;":"")+"\n      overflow: hidden;\n    ")),this.toolboxStyleColorsClass=this.styles.addClass(new p("toolbox_colors","\n      color: "+this.uiStyleSettings.toolboxColor+";\n    "));var t=this.uiStyleSettings.toolbarHeight/4;this.toolboxButtonRowStyleClass=this.styles.addClass(new p("toolbox-button-row","\n      display: flex;\n      cursor: default;\n      box-sizing: content-box;\n    ")),this.toolboxButtonRowStyleColorsClass=this.styles.addClass(new p("toolbox-button-row_colors","\n      background-color: "+this.uiStyleSettings.toolbarBackgroundColor+";\n    ")),this.toolboxPanelRowStyleClass=this.styles.addClass(new p("toolbox-panel-row","\n      display: flex;\n      "+("inline"===this.displayMode?"position: absolute;":"")+"\n      "+("inline"===this.displayMode?"bottom: "+this.uiStyleSettings.toolbarHeight+"px;":"")+"\n      cursor: default;\n      height: "+1.5*this.uiStyleSettings.toolbarHeight+"px;\n      "+("inline"===this.displayMode?"width: 100%;":"")+"\n      box-sizing: content-box;\n    ")),this.toolboxPanelRowStyleColorsClass=this.styles.addClass(new p("toolbox-panel-row_colors","\n      background-color: "+(null!==(e=this.uiStyleSettings.toolboxBackgroundColor)&&void 0!==e?e:this.uiStyleSettings.toolbarBackgroundHoverColor)+";\n    ")),this.toolboxButtonStyleClass=this.styles.addClass(new p("toolbox_button","\n      display: inline-block;\n      width: "+(this.uiStyleSettings.toolbarHeight-2*t)+"px;\n      height: "+(this.uiStyleSettings.toolbarHeight-2*t)+"px;\n      padding: "+t+"px;\n      box-sizing: content-box;\n    ")),this.toolboxButtonStyleColorsClass=this.styles.addClass(new p("toolbox-button_colors","\n      fill: "+this.uiStyleSettings.toolbarColor+";\n    ")),this.toolboxActiveButtonStyleColorsClass=this.styles.addClass(new p("toolbox-active-button_colors","\n      background-color: "+this.uiStyleSettings.toolbarBackgroundHoverColor+";\n      fill: "+this.uiStyleSettings.toolbarColor+";\n    ")),this.styles.addRule(new f("."+this.toolboxButtonStyleColorsClass.name+":hover","\n        background-color: "+this.uiStyleSettings.toolbarBackgroundHoverColor+"\n    ")),this.styles.addRule(new f("."+this.toolboxButtonStyleClass.name+" svg","\n      height: "+this.uiStyleSettings.toolbarHeight/2+"px;\n    "))},e.prototype.show=function(e){var t;this.uiContainer=document.createElement("div"),this.uiContainer.style.visibility=e,this.uiContainer.className=this.toolboxStyleClass.name+" "+(null!==(t=this.uiStyleSettings.toolboxStyleColorsClassName)&&void 0!==t?t:this.toolboxStyleColorsClass.name),this.markerjsContainer.appendChild(this.uiContainer)},e.prototype.setPanelButtons=function(e){var t,n,i=this;this.panels=e,void 0!==this.uiContainer&&(this.uiContainer.innerHTML="",this.panelRow=document.createElement("div"),this.panelRow.className=this.toolboxPanelRowStyleClass.name+" "+(null!==(t=this.uiStyleSettings.toolboxPanelRowStyleColorsClassName)&&void 0!==t?t:this.toolboxPanelRowStyleColorsClass.name),this.uiContainer.appendChild(this.panelRow),this.buttonRow=document.createElement("div"),this.buttonRow.className=this.toolboxButtonRowStyleClass.name+" "+(null!==(n=this.uiStyleSettings.toolboxButtonRowStyleColorsClassName)&&void 0!==n?n:this.toolboxButtonRowStyleColorsClass.name)+" ",this.uiContainer.appendChild(this.buttonRow),this.panelButtons.splice(0),this.panels.forEach((function(e){var t;e.uiStyleSettings=i.uiStyleSettings;var n=document.createElement("div");n.className=i.toolboxButtonStyleClass.name+" "+(null!==(t=i.uiStyleSettings.toolboxButtonStyleColorsClassName)&&void 0!==t?t:i.toolboxButtonStyleColorsClass.name),n.innerHTML=e.icon,n.title=e.title,n.addEventListener("click",(function(){i.panelButtonClick(e)})),i.panelButtons.push(n),i.buttonRow.appendChild(n)})),"inline"===this.displayMode?this.panelRow.style.display="none":this.panelRow.style.visibility="hidden")},e.prototype.panelButtonClick=function(e){var t=this,n=-1;if(e!==this.activePanel){n=this.panels.indexOf(e),this.panelRow.innerHTML="";var i=e.getUi();i.style.margin=this.uiStyleSettings.toolbarHeight/4+"px",this.panelRow.appendChild(i),this.panelRow.style.display="flex",this.panelRow.style.visibility="visible",this.panelRow.className=this.panelRow.className.replace(this.styles.fadeOutAnimationClassName,""),this.panelRow.className+=" "+this.styles.fadeInAnimationClassName,this.activePanel=e}else this.activePanel=void 0,this.panelRow.className=this.panelRow.className.replace(this.styles.fadeInAnimationClassName,""),this.panelRow.className+=" "+this.styles.fadeOutAnimationClassName,setTimeout((function(){"inline"===t.displayMode?t.panelRow.style.display="none":t.panelRow.style.visibility="hidden"}),200);this.panelButtons.forEach((function(e,i){var r,s;e.className=t.toolboxButtonStyleClass.name+" "+(i===n?""+(null!==(r=t.uiStyleSettings.toolboxActiveButtonStyleColorsClassName)&&void 0!==r?r:t.toolboxActiveButtonStyleColorsClass.name):""+(null!==(s=t.uiStyleSettings.toolboxButtonStyleColorsClassName)&&void 0!==s?s:t.toolboxButtonStyleColorsClass.name))}))},e}(),v=function(e,t){this.title=e,this.icon=t},A=function(e){function t(t,n,i,r){var s=e.call(this,t,r||'<svg viewBox="0 0 24 24"><path d="M17.5 12a1.5 1.5 0 01-1.5-1.5A1.5 1.5 0 0117.5 9a1.5 1.5 0 011.5 1.5 1.5 1.5 0 01-1.5 1.5m-3-4A1.5 1.5 0 0113 6.5 1.5 1.5 0 0114.5 5 1.5 1.5 0 0116 6.5 1.5 1.5 0 0114.5 8m-5 0A1.5 1.5 0 018 6.5 1.5 1.5 0 019.5 5 1.5 1.5 0 0111 6.5 1.5 1.5 0 019.5 8m-3 4A1.5 1.5 0 015 10.5 1.5 1.5 0 016.5 9 1.5 1.5 0 018 10.5 1.5 1.5 0 016.5 12M12 3a9 9 0 00-9 9 9 9 0 009 9 1.5 1.5 0 001.5-1.5c0-.39-.15-.74-.39-1-.23-.27-.38-.62-.38-1a1.5 1.5 0 011.5-1.5H16a5 5 0 005-5c0-4.42-4.03-8-9-8z"/></svg>')||this;return s.colors=[],s.addTransparent=!1,s.colorBoxes=[],s.colors=n,s.currentColor=i,s.setCurrentColor=s.setCurrentColor.bind(s),s.getColorBox=s.getColorBox.bind(s),s}return r(t,e),t.prototype.getUi=function(){var e=this,t=document.createElement("div");return t.style.overflow="hidden",t.style.whiteSpace="nowrap",this.colors.forEach((function(n){var i=e.getColorBox(n);t.appendChild(i),e.colorBoxes.push(i)})),t},t.prototype.getColorBox=function(e){var t=this,n=this.uiStyleSettings.toolbarHeight/4,i=this.uiStyleSettings.toolbarHeight-n,r=document.createElement("div");r.style.display="inline-block",r.style.boxSizing="content-box",r.style.width=i-2+"px",r.style.height=i-2+"px",r.style.padding="1px",r.style.marginRight="2px",r.style.marginBottom="2px",r.style.borderWidth="2px",r.style.borderStyle="solid",r.style.borderRadius=(i+2)/2+"px",r.style.borderColor=e===this.currentColor?this.uiStyleSettings.toolboxAccentColor:"transparent",r.addEventListener("click",(function(){t.setCurrentColor(e,r)}));var s=document.createElement("div");return s.style.display="inline-block",s.style.width=i-2+"px",s.style.height=i-2+"px",s.style.backgroundColor=e,s.style.borderRadius=i/2+"px","transparent"===e&&(s.style.fill=this.uiStyleSettings.toolboxAccentColor,s.innerHTML='<svg viewBox="0 0 24 24">\n        <path d="M2,5.27L3.28,4L20,20.72L18.73,22L15.65,18.92C14.5,19.3 13.28,19.5 12,19.5C7,19.5 2.73,16.39 1,12C1.69,10.24 2.79,8.69 4.19,7.46L2,5.27M12,9A3,3 0 0,1 15,12C15,12.35 14.94,12.69 14.83,13L11,9.17C11.31,9.06 11.65,9 12,9M12,4.5C17,4.5 21.27,7.61 23,12C22.18,14.08 20.79,15.88 19,17.19L17.58,15.76C18.94,14.82 20.06,13.54 20.82,12C19.17,8.64 15.76,6.5 12,6.5C10.91,6.5 9.84,6.68 8.84,7L7.3,5.47C8.74,4.85 10.33,4.5 12,4.5M3.18,12C4.83,15.36 8.24,17.5 12,17.5C12.69,17.5 13.37,17.43 14,17.29L11.72,15C10.29,14.85 9.15,13.71 9,12.28L5.6,8.87C4.61,9.72 3.78,10.78 3.18,12Z" />\n      </svg>'),r.appendChild(s),r},t.prototype.setCurrentColor=function(e,t){var n=this;this.currentColor=e,this.colorBoxes.forEach((function(e){e.style.borderColor=e===t?n.uiStyleSettings.toolboxAccentColor:"transparent"})),this.onColorChanged&&this.onColorChanged(e)},t}(v),x=function(){function e(e,t,n){this._state="new",this._isSelected=!1,this._container=e,this._overlayContainer=t,this.globalSettings=n,this.stateChanged=this.stateChanged.bind(this),this.colorChanged=this.colorChanged.bind(this),this.fillColorChanged=this.fillColorChanged.bind(this)}return Object.defineProperty(e.prototype,"typeName",{get:function(){return Object.getPrototypeOf(this).constructor.typeName},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"container",{get:function(){return this._container},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"overlayContainer",{get:function(){return this._overlayContainer},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"state",{get:function(){return this._state},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"toolboxPanels",{get:function(){return[]},enumerable:!1,configurable:!0}),e.prototype.ownsTarget=function(e){return!1},Object.defineProperty(e.prototype,"isSelected",{get:function(){return this._isSelected},enumerable:!1,configurable:!0}),e.prototype.select=function(){this.container.style.cursor="move",this._isSelected=!0,this.manipulationStartState=this.getState()},e.prototype.deselect=function(){this.container.style.cursor="default",this._isSelected=!1,this.stateChanged()},e.prototype.pointerDown=function(e,t){},e.prototype.dblClick=function(e,t){},e.prototype.manipulate=function(e){},e.prototype.pointerUp=function(e){this.stateChanged()},e.prototype.dispose=function(){},e.prototype.addMarkerVisualToContainer=function(e){this.container.childNodes.length>0?this.container.insertBefore(e,this.container.childNodes[0]):this.container.appendChild(e)},e.prototype.getState=function(){return{typeName:e.typeName,state:this.state,notes:this.notes}},e.prototype.restoreState=function(e){this._state=e.state,this.notes=e.notes},e.prototype.scale=function(e,t){},e.prototype.colorChanged=function(e){this.onColorChanged&&this.onColorChanged(e),this.stateChanged()},e.prototype.fillColorChanged=function(e){this.onFillColorChanged&&this.onFillColorChanged(e),this.stateChanged()},e.prototype.stateChanged=function(){if(this.onStateChanged&&"creating"!==this.state&&"new"!==this.state){var e=this.getState();void 0!==this.manipulationStartState&&(this.manipulationStartState.state="select"),e.state="select",JSON.stringify(this.manipulationStartState)!=JSON.stringify(e)&&this.onStateChanged(this)}},e.typeName="MarkerBase",e}(),y=function(){function e(){this.findGripByVisual=this.findGripByVisual.bind(this)}return e.prototype.findGripByVisual=function(e){return this.topLeft.ownsTarget(e)?this.topLeft:this.topCenter.ownsTarget(e)?this.topCenter:this.topRight.ownsTarget(e)?this.topRight:this.centerLeft.ownsTarget(e)?this.centerLeft:this.centerRight.ownsTarget(e)?this.centerRight:this.bottomLeft.ownsTarget(e)?this.bottomLeft:this.bottomCenter.ownsTarget(e)?this.bottomCenter:this.bottomRight.ownsTarget(e)?this.bottomRight:void 0},e}(),b=function(){function e(){this.GRIP_SIZE=10,this.visual=l.createGroup(),this.visual.appendChild(l.createCircle(1.5*this.GRIP_SIZE,[["fill","transparent"]])),this.visual.appendChild(l.createCircle(this.GRIP_SIZE,[["fill","#cccccc"],["fill-opacity","0.7"],["stroke","#333333"],["stroke-width","2"],["stroke-opacity","0.7"]]))}return e.prototype.ownsTarget=function(e){return e===this.visual||e===this.visual.childNodes[0]||e===this.visual.childNodes[1]},e}(),w=function(){function e(){}return e.toITransformMatrix=function(e){return{a:e.a,b:e.b,c:e.c,d:e.d,e:e.e,f:e.f}},e.toSVGMatrix=function(e,t){return e.a=t.a,e.b=t.b,e.c=t.c,e.d=t.d,e.e=t.e,e.f=t.f,e},e}(),C=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.left=0,r.top=0,r.width=0,r.height=0,r.defaultSize={x:50,y:20},r.offsetX=0,r.offsetY=0,r.rotationAngle=0,r.CB_DISTANCE=10,r._suppressMarkerCreateEvent=!1,r.container.transform.baseVal.appendItem(l.createTransform()),r.setupControlBox(),r}return r(t,e),Object.defineProperty(t.prototype,"centerX",{get:function(){return this.left+this.width/2},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"centerY",{get:function(){return this.top+this.height/2},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"visual",{get:function(){return this._visual},set:function(e){this._visual=e;var t=l.createTransform();this._visual.transform.baseVal.appendItem(t)},enumerable:!1,configurable:!0}),t.prototype.ownsTarget=function(t){return!!e.prototype.ownsTarget.call(this,t)||!!(void 0!==this.controlGrips.findGripByVisual(t)||void 0!==this.rotatorGrip&&this.rotatorGrip.ownsTarget(t))},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),"new"===this.state&&(this.left=t.x,this.top=t.y),this.manipulationStartLeft=this.left,this.manipulationStartTop=this.top,this.manipulationStartWidth=this.width,this.manipulationStartHeight=this.height;var i=this.unrotatePoint(t);if(this.manipulationStartX=i.x,this.manipulationStartY=i.y,this.offsetX=i.x-this.left,this.offsetY=i.y-this.top,"new"!==this.state)if(this.select(),this.activeGrip=this.controlGrips.findGripByVisual(n),void 0!==this.activeGrip)this._state="resize";else if(void 0!==this.rotatorGrip&&this.rotatorGrip.ownsTarget(n)){this.activeGrip=this.rotatorGrip;var r=this.rotatePoint({x:this.centerX,y:this.centerY});this.left=r.x-this.width/2,this.top=r.y-this.height/2,this.moveVisual({x:this.left,y:this.top});var s=this.container.transform.baseVal.getItem(0);s.setRotate(this.rotationAngle,this.centerX,this.centerY),this.container.transform.baseVal.replaceItem(s,0),this.adjustControlBox(),this._state="rotate"}else this._state="move"},t.prototype.pointerUp=function(t){var n=this.state;e.prototype.pointerUp.call(this,t),"creating"===this.state&&this.width<10&&this.height<10?(this.width=this.defaultSize.x,this.height=this.defaultSize.y):this.manipulate(t),this._state="select","creating"===n&&this.onMarkerCreated&&!1===this._suppressMarkerCreateEvent&&this.onMarkerCreated(this)},t.prototype.moveVisual=function(e){this.visual.style.transform="translate("+e.x+"px, "+e.y+"px)"},t.prototype.manipulate=function(e){var t=this.unrotatePoint(e);"creating"===this.state?this.resize(e):"move"===this.state?(this.left=this.manipulationStartLeft+(t.x-this.manipulationStartLeft)-this.offsetX,this.top=this.manipulationStartTop+(t.y-this.manipulationStartTop)-this.offsetY,this.moveVisual({x:this.left,y:this.top}),this.adjustControlBox()):"resize"===this.state?this.resize(t):"rotate"===this.state&&this.rotate(e)},t.prototype.resize=function(e){var t=this.manipulationStartLeft,n=this.manipulationStartWidth,i=this.manipulationStartTop,r=this.manipulationStartHeight;switch(this.activeGrip){case this.controlGrips.bottomLeft:case this.controlGrips.centerLeft:case this.controlGrips.topLeft:t=this.manipulationStartLeft+e.x-this.manipulationStartX,n=this.manipulationStartWidth+this.manipulationStartLeft-t;break;case this.controlGrips.bottomRight:case this.controlGrips.centerRight:case this.controlGrips.topRight:case void 0:n=this.manipulationStartWidth+e.x-this.manipulationStartX}switch(this.activeGrip){case this.controlGrips.topCenter:case this.controlGrips.topLeft:case this.controlGrips.topRight:i=this.manipulationStartTop+e.y-this.manipulationStartY,r=this.manipulationStartHeight+this.manipulationStartTop-i;break;case this.controlGrips.bottomCenter:case this.controlGrips.bottomLeft:case this.controlGrips.bottomRight:case void 0:r=this.manipulationStartHeight+e.y-this.manipulationStartY}n>=0?(this.left=t,this.width=n):(this.left=t+n,this.width=-n),r>=0?(this.top=i,this.height=r):(this.top=i+r,this.height=-r),this.setSize()},t.prototype.setSize=function(){this.moveVisual({x:this.left,y:this.top}),this.adjustControlBox()},t.prototype.rotate=function(e){if(Math.abs(e.x-this.centerX)>.1){var t=Math.sign(e.x-this.centerX);this.rotationAngle=180*Math.atan((e.y-this.centerY)/(e.x-this.centerX))/Math.PI+90*t,this.applyRotation()}},t.prototype.applyRotation=function(){var e=this.container.transform.baseVal.getItem(0);e.setRotate(this.rotationAngle,this.centerX,this.centerY),this.container.transform.baseVal.replaceItem(e,0)},t.prototype.rotatePoint=function(e){if(0===this.rotationAngle)return e;var t=this.container.getCTM(),n=l.createPoint(e.x,e.y);return{x:(n=n.matrixTransform(t)).x,y:n.y}},t.prototype.unrotatePoint=function(e){if(0===this.rotationAngle)return e;var t=this.container.getCTM();t=t.inverse();var n=l.createPoint(e.x,e.y);return{x:(n=n.matrixTransform(t)).x,y:n.y}},t.prototype.select=function(){e.prototype.select.call(this),this.adjustControlBox(),this.controlBox.style.display=""},t.prototype.deselect=function(){e.prototype.deselect.call(this),this.controlBox.style.display="none"},t.prototype.setupControlBox=function(){this.controlBox=l.createGroup();var e=l.createTransform();e.setTranslate(-this.CB_DISTANCE/2,-this.CB_DISTANCE/2),this.controlBox.transform.baseVal.appendItem(e),this.container.appendChild(this.controlBox),this.controlRect=l.createRect(this.width+this.CB_DISTANCE,this.height+this.CB_DISTANCE,[["stroke","black"],["stroke-width","1"],["stroke-opacity","0.5"],["stroke-dasharray","3, 2"],["fill","transparent"],["pointer-events","none"]]),this.controlBox.appendChild(this.controlRect),!0!==this.globalSettings.disableRotation&&(this.rotatorGripLine=l.createLine((this.width+2*this.CB_DISTANCE)/2,this.top-this.CB_DISTANCE,(this.width+2*this.CB_DISTANCE)/2,this.top-3*this.CB_DISTANCE,[["stroke","black"],["stroke-width","1"],["stroke-opacity","0.5"],["stroke-dasharray","3, 2"]]),this.controlBox.appendChild(this.rotatorGripLine)),this.controlGrips=new y,this.addControlGrips(),this.controlBox.style.display="none"},t.prototype.adjustControlBox=function(){var e=this.controlBox.transform.baseVal.getItem(0);e.setTranslate(this.left-this.CB_DISTANCE/2,this.top-this.CB_DISTANCE/2),this.controlBox.transform.baseVal.replaceItem(e,0),this.controlRect.setAttribute("width",(this.width+this.CB_DISTANCE).toString()),this.controlRect.setAttribute("height",(this.height+this.CB_DISTANCE).toString()),void 0!==this.rotatorGripLine&&(this.rotatorGripLine.setAttribute("x1",((this.width+this.CB_DISTANCE)/2).toString()),this.rotatorGripLine.setAttribute("y1",(-this.CB_DISTANCE/2).toString()),this.rotatorGripLine.setAttribute("x2",((this.width+this.CB_DISTANCE)/2).toString()),this.rotatorGripLine.setAttribute("y2",(3*-this.CB_DISTANCE).toString())),this.positionGrips()},t.prototype.addControlGrips=function(){this.controlGrips.topLeft=this.createGrip(),this.controlGrips.topCenter=this.createGrip(),this.controlGrips.topRight=this.createGrip(),this.controlGrips.centerLeft=this.createGrip(),this.controlGrips.centerRight=this.createGrip(),this.controlGrips.bottomLeft=this.createGrip(),this.controlGrips.bottomCenter=this.createGrip(),this.controlGrips.bottomRight=this.createGrip(),!0!==this.globalSettings.disableRotation&&(this.rotatorGrip=this.createGrip()),this.positionGrips()},t.prototype.createGrip=function(){var e=new b;return e.visual.transform.baseVal.appendItem(l.createTransform()),this.controlBox.appendChild(e.visual),e},t.prototype.positionGrips=function(){var e=this.controlGrips.topLeft.GRIP_SIZE,t=-e/2,n=t,i=(this.width+this.CB_DISTANCE)/2-e/2,r=(this.height+this.CB_DISTANCE)/2-e/2,s=this.height+this.CB_DISTANCE-e/2,o=this.width+this.CB_DISTANCE-e/2;this.positionGrip(this.controlGrips.topLeft.visual,t,n),this.positionGrip(this.controlGrips.topCenter.visual,i,n),this.positionGrip(this.controlGrips.topRight.visual,o,n),this.positionGrip(this.controlGrips.centerLeft.visual,t,r),this.positionGrip(this.controlGrips.centerRight.visual,o,r),this.positionGrip(this.controlGrips.bottomLeft.visual,t,s),this.positionGrip(this.controlGrips.bottomCenter.visual,i,s),this.positionGrip(this.controlGrips.bottomRight.visual,o,s),void 0!==this.rotatorGrip&&this.positionGrip(this.rotatorGrip.visual,i,n-3*this.CB_DISTANCE)},t.prototype.positionGrip=function(e,t,n){var i=e.transform.baseVal.getItem(0);i.setTranslate(t,n),e.transform.baseVal.replaceItem(i,0)},t.prototype.hideControlBox=function(){this.controlBox.style.display="none"},t.prototype.showControlBox=function(){this.controlBox.style.display=""},t.prototype.getState=function(){return Object.assign({left:this.left,top:this.top,width:this.width,height:this.height,rotationAngle:this.rotationAngle,visualTransformMatrix:w.toITransformMatrix(this.visual.transform.baseVal.getItem(0).matrix),containerTransformMatrix:w.toITransformMatrix(this.container.transform.baseVal.getItem(0).matrix)},e.prototype.getState.call(this))},t.prototype.restoreState=function(t){e.prototype.restoreState.call(this,t);var n=t;this.left=n.left,this.top=n.top,this.width=n.width,this.height=n.height,this.rotationAngle=n.rotationAngle,this.visual.transform.baseVal.getItem(0).setMatrix(w.toSVGMatrix(this.visual.transform.baseVal.getItem(0).matrix,n.visualTransformMatrix)),this.container.transform.baseVal.getItem(0).setMatrix(w.toSVGMatrix(this.container.transform.baseVal.getItem(0).matrix,n.containerTransformMatrix))},t.prototype.scale=function(t,n){e.prototype.scale.call(this,t,n);var i=this.rotatePoint({x:this.left,y:this.top}),r=this.unrotatePoint({x:i.x*t,y:i.y*n});this.left=r.x,this.top=r.y,this.width=this.width*t,this.height=this.height*n,this.adjustControlBox()},t}(x),M=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.fillColor="transparent",r.strokeColor="transparent",r.strokeWidth=0,r.strokeDasharray="",r.opacity=1,r.setStrokeColor=r.setStrokeColor.bind(r),r.setFillColor=r.setFillColor.bind(r),r.setStrokeWidth=r.setStrokeWidth.bind(r),r.setStrokeDasharray=r.setStrokeDasharray.bind(r),r.createVisual=r.createVisual.bind(r),r}return r(t,e),t.prototype.ownsTarget=function(t){return!(!e.prototype.ownsTarget.call(this,t)&&t!==this.visual)},t.prototype.createVisual=function(){this.visual=l.createRect(1,1,[["fill",this.fillColor],["stroke",this.strokeColor],["stroke-width",this.strokeWidth.toString()],["stroke-dasharray",this.strokeDasharray],["opacity",this.opacity.toString()]]),this.addMarkerVisualToContainer(this.visual)},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),"new"===this.state&&(this.createVisual(),this.moveVisual(t),this._state="creating")},t.prototype.manipulate=function(t){e.prototype.manipulate.call(this,t)},t.prototype.resize=function(t){e.prototype.resize.call(this,t),this.setSize()},t.prototype.setSize=function(){e.prototype.setSize.call(this),l.setAttributes(this.visual,[["width",this.width.toString()],["height",this.height.toString()]])},t.prototype.pointerUp=function(t){e.prototype.pointerUp.call(this,t),this.setSize()},t.prototype.setStrokeColor=function(e){this.strokeColor=e,this.visual&&l.setAttributes(this.visual,[["stroke",this.strokeColor]]),this.colorChanged(e),this.stateChanged()},t.prototype.setFillColor=function(e){this.fillColor=e,this.visual&&l.setAttributes(this.visual,[["fill",this.fillColor]]),this.stateChanged()},t.prototype.setStrokeWidth=function(e){this.strokeWidth=e,this.visual&&l.setAttributes(this.visual,[["stroke-width",this.strokeWidth.toString()]]),this.stateChanged()},t.prototype.setStrokeDasharray=function(e){this.strokeDasharray=e,this.visual&&l.setAttributes(this.visual,[["stroke-dasharray",this.strokeDasharray]]),this.stateChanged()},t.prototype.getState=function(){return Object.assign({fillColor:this.fillColor,strokeColor:this.strokeColor,strokeWidth:this.strokeWidth,strokeDasharray:this.strokeDasharray,opacity:this.opacity},e.prototype.getState.call(this))},t.prototype.restoreState=function(t){var n=t;this.fillColor=n.fillColor,this.strokeColor=n.strokeColor,this.strokeWidth=n.strokeWidth,this.strokeDasharray=n.strokeDasharray,this.opacity=n.opacity,this.createVisual(),e.prototype.restoreState.call(this,t),this.setSize()},t.prototype.scale=function(t,n){e.prototype.scale.call(this,t,n),this.setSize()},t.title="Rectangle marker",t}(C),E=function(e){function t(t,n,i,r){var s=e.call(this,t,r||'<svg viewBox="0 0 24 24"><path d="M3 17h18v-2H3v2m0 3h18v-1H3v1m0-7h18v-3H3v3m0-9v4h18V4H3z"/></svg>')||this;return s.widths=[],s.widthBoxes=[],s.widths=n,s.currentWidth=i,s.setCurrentWidth=s.setCurrentWidth.bind(s),s}return r(t,e),t.prototype.getUi=function(){var e=this,t=document.createElement("div");return t.style.display="flex",t.style.overflow="hidden",t.style.flexGrow="2",this.widths.forEach((function(n){var i=document.createElement("div");i.style.display="flex",i.style.flexGrow="2",i.style.alignItems="center",i.style.justifyContent="space-between",i.style.padding="5px",i.style.borderWidth="2px",i.style.borderStyle="solid",i.style.borderColor=n===e.currentWidth?e.uiStyleSettings.toolboxAccentColor:"transparent",i.addEventListener("click",(function(){e.setCurrentWidth(n,i)})),t.appendChild(i);var r=document.createElement("div");r.innerText=n.toString(),r.style.marginRight="5px",i.appendChild(r);var s=document.createElement("div");s.style.minHeight="20px",s.style.flexGrow="2",s.style.display="flex",s.style.alignItems="center";var o=document.createElement("hr");o.style.minWidth="20px",o.style.border="0px",o.style.borderTop=n+"px solid "+e.uiStyleSettings.toolboxColor,o.style.flexGrow="2",s.appendChild(o),i.appendChild(s),e.widthBoxes.push(i)})),t},t.prototype.setCurrentWidth=function(e,t){var n=this;this.currentWidth=e,this.widthBoxes.forEach((function(e){e.style.borderColor=e===t?n.uiStyleSettings.toolboxAccentColor:"transparent"})),this.onWidthChanged&&this.onWidthChanged(this.currentWidth)},t}(v),T=function(e){function t(t,n,i,r){var s=e.call(this,t,r||'<svg viewBox="0 0 24 24"><path d="M3 16h5v-2H3v2m6.5 0h5v-2h-5v2m6.5 0h5v-2h-5v2M3 20h2v-2H3v2m4 0h2v-2H7v2m4 0h2v-2h-2v2m4 0h2v-2h-2v2m4 0h2v-2h-2v2M3 12h8v-2H3v2m10 0h8v-2h-8v2M3 4v4h18V4H3z"/></svg>')||this;return s.styles=[],s.styleBoxes=[],s.styles=n,s.currentStyle=i,s.setCurrentStyle=s.setCurrentStyle.bind(s),s}return r(t,e),t.prototype.getUi=function(){var e=this,t=document.createElement("div");return t.style.display="flex",t.style.overflow="hidden",t.style.flexGrow="2",this.styles.forEach((function(n){var i=document.createElement("div");i.style.display="flex",i.style.alignItems="center",i.style.justifyContent="space-between",i.style.padding="5px",i.style.borderWidth="2px",i.style.borderStyle="solid",i.style.overflow="hidden",i.style.maxWidth=100/e.styles.length-5+"%",i.style.borderColor=n===e.currentStyle?e.uiStyleSettings.toolboxAccentColor:"transparent",i.addEventListener("click",(function(){e.setCurrentStyle(n,i)})),t.appendChild(i);var r=document.createElement("div");r.style.minHeight="20px",r.style.flexGrow="2",r.style.overflow="hidden";var s='<svg width="100" height="20">\n      <line x1="0" y1="10" x2="100" y2="10" stroke="'+e.uiStyleSettings.toolboxColor+'" stroke-width="3" '+(""!==n?'stroke-dasharray="'+n+'"':"")+" />\n  </svg>";r.innerHTML=s,i.appendChild(r),e.styleBoxes.push(i)})),t},t.prototype.setCurrentStyle=function(e,t){var n=this;this.currentStyle=e,this.styleBoxes.forEach((function(e){e.style.borderColor=e===t?n.uiStyleSettings.toolboxAccentColor:"transparent"})),this.onStyleChanged&&this.onStyleChanged(this.currentStyle)},t}(v),S=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.strokeColor=i.defaultColor,r.strokeWidth=i.defaultStrokeWidth,r.strokeDasharray=i.defaultStrokeDasharray,r.strokePanel=new A("Line color",i.defaultColorSet,i.defaultColor),r.strokePanel.onColorChanged=r.setStrokeColor,r.strokeWidthPanel=new E("Line width",i.defaultStrokeWidths,i.defaultStrokeWidth),r.strokeWidthPanel.onWidthChanged=r.setStrokeWidth,r.strokeStylePanel=new T("Line style",i.defaultStrokeDasharrays,i.defaultStrokeDasharray),r.strokeStylePanel.onStyleChanged=r.setStrokeDasharray,r}return r(t,e),Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.strokePanel,this.strokeWidthPanel,this.strokeStylePanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=e.prototype.getState.call(this);return n.typeName=t.typeName,n},t.typeName="FrameMarker",t.title="Frame marker",t.icon='<svg viewBox="0 0 24 24"><path d="M4 6v13h16V6H4m14 11H6V8h12v9z"/></svg>',t}(M),P=function(){this.defaultColorSet=["#EF4444","#10B981","#2563EB","#FFFF00","#7C3AED","#F472B6","#000000","#FFFFFF"],this.defaultColor=this.defaultColorSet[0],this.defaultFillColor=this.defaultColorSet[0],this.defaultStrokeColor=this.defaultColorSet[7],this.defaultHighlightColor=this.defaultColorSet[3],this.defaultStrokeWidth=3,this.defaultStrokeDasharray="",this.defaultHighlightOpacity=.5,this.defaultFontFamily="Helvetica, Arial, sans-serif",this.defaultStrokeWidths=[1,2,3,5,10],this.defaultStrokeDasharrays=["","3","12 3","9 6 3 6"],this.defaultOpacitySteps=[.1,.25,.5,.75,1],this.displayMode="inline",this.defaultFontFamilies=['Times, "Times New Roman", serif',"Helvetica, Arial, sans-serif",'Courier, "Courier New", monospace',"cursive","fantasy"],this.popupMargin=30,this.newFreehandMarkerOnPointerUp=!1,this.defaultColorsFollowCurrentColors=!1,this.freehandPixelRatio=1,this.disableRotation=!1,this.defaultCaptionFontSize="1rem",this.defaultCaptionText="Text"},N=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.x1=0,r.y1=0,r.x2=0,r.y2=0,r.defaultLength=50,r.manipulationStartX=0,r.manipulationStartY=0,r.manipulationStartX1=0,r.manipulationStartY1=0,r.manipulationStartX2=0,r.manipulationStartY2=0,r.setupControlBox(),r}return r(t,e),t.prototype.ownsTarget=function(t){return!!e.prototype.ownsTarget.call(this,t)||!(!this.grip1.ownsTarget(t)&&!this.grip2.ownsTarget(t))},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),this.manipulationStartX=t.x,this.manipulationStartY=t.y,"new"===this.state&&(this.x1=t.x,this.y1=t.y,this.x2=t.x,this.y2=t.y),this.manipulationStartX1=this.x1,this.manipulationStartY1=this.y1,this.manipulationStartX2=this.x2,this.manipulationStartY2=this.y2,"new"!==this.state&&(this.select(),this.grip1.ownsTarget(n)?this.activeGrip=this.grip1:this.grip2.ownsTarget(n)?this.activeGrip=this.grip2:this.activeGrip=void 0,this.activeGrip?this._state="resize":this._state="move")},t.prototype.pointerUp=function(t){var n=this.state;e.prototype.pointerUp.call(this,t),"creating"===this.state&&Math.abs(this.x1-this.x2)<10&&Math.abs(this.y1-this.y2)<10?(this.x2=this.x1+this.defaultLength,this.adjustVisual(),this.adjustControlBox()):this.manipulate(t),this._state="select","creating"===n&&this.onMarkerCreated&&this.onMarkerCreated(this)},t.prototype.adjustVisual=function(){},t.prototype.manipulate=function(e){"creating"===this.state?this.resize(e):"move"===this.state?(this.x1=this.manipulationStartX1+e.x-this.manipulationStartX,this.y1=this.manipulationStartY1+e.y-this.manipulationStartY,this.x2=this.manipulationStartX2+e.x-this.manipulationStartX,this.y2=this.manipulationStartY2+e.y-this.manipulationStartY,this.adjustVisual(),this.adjustControlBox()):"resize"===this.state&&this.resize(e)},t.prototype.resize=function(e){switch(this.activeGrip){case this.grip1:this.x1=e.x,this.y1=e.y;break;case this.grip2:case void 0:this.x2=e.x,this.y2=e.y}this.adjustVisual(),this.adjustControlBox()},t.prototype.select=function(){e.prototype.select.call(this),this.adjustControlBox(),this.controlBox.style.display=""},t.prototype.deselect=function(){e.prototype.deselect.call(this),this.controlBox.style.display="none"},t.prototype.setupControlBox=function(){this.controlBox=l.createGroup(),this.container.appendChild(this.controlBox),this.addControlGrips(),this.controlBox.style.display="none"},t.prototype.adjustControlBox=function(){this.positionGrips()},t.prototype.addControlGrips=function(){this.grip1=this.createGrip(),this.grip2=this.createGrip(),this.positionGrips()},t.prototype.createGrip=function(){var e=new b;return e.visual.transform.baseVal.appendItem(l.createTransform()),this.controlBox.appendChild(e.visual),e},t.prototype.positionGrips=function(){var e=this.grip1.GRIP_SIZE;this.positionGrip(this.grip1.visual,this.x1-e/2,this.y1-e/2),this.positionGrip(this.grip2.visual,this.x2-e/2,this.y2-e/2)},t.prototype.positionGrip=function(e,t,n){var i=e.transform.baseVal.getItem(0);i.setTranslate(t,n),e.transform.baseVal.replaceItem(i,0)},t.prototype.getState=function(){return Object.assign({x1:this.x1,y1:this.y1,x2:this.x2,y2:this.y2},e.prototype.getState.call(this))},t.prototype.restoreState=function(t){e.prototype.restoreState.call(this,t);var n=t;this.x1=n.x1,this.y1=n.y1,this.x2=n.x2,this.y2=n.y2},t.prototype.scale=function(t,n){e.prototype.scale.call(this,t,n),this.x1=this.x1*t,this.y1=this.y1*n,this.x2=this.x2*t,this.y2=this.y2*n,this.adjustVisual(),this.adjustControlBox()},t}(x),B=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.strokeColor="transparent",r.strokeWidth=0,r.strokeDasharray="",r.setStrokeColor=r.setStrokeColor.bind(r),r.setStrokeWidth=r.setStrokeWidth.bind(r),r.setStrokeDasharray=r.setStrokeDasharray.bind(r),r.strokeColor=i.defaultColor,r.strokeWidth=i.defaultStrokeWidth,r.strokeDasharray=i.defaultStrokeDasharray,r.strokePanel=new A("Line color",i.defaultColorSet,i.defaultColor),r.strokePanel.onColorChanged=r.setStrokeColor,r.strokeWidthPanel=new E("Line width",i.defaultStrokeWidths,i.defaultStrokeWidth),r.strokeWidthPanel.onWidthChanged=r.setStrokeWidth,r.strokeStylePanel=new T("Line style",i.defaultStrokeDasharrays,i.defaultStrokeDasharray),r.strokeStylePanel.onStyleChanged=r.setStrokeDasharray,r}return r(t,e),t.prototype.ownsTarget=function(t){return!(!e.prototype.ownsTarget.call(this,t)&&t!==this.visual&&t!==this.selectorLine&&t!==this.visibleLine)},t.prototype.createVisual=function(){this.visual=l.createGroup(),this.selectorLine=l.createLine(this.x1,this.y1,this.x2,this.y2,[["stroke","transparent"],["stroke-width",(this.strokeWidth+10).toString()]]),this.visibleLine=l.createLine(this.x1,this.y1,this.x2,this.y2,[["stroke",this.strokeColor],["stroke-width",this.strokeWidth.toString()]]),this.visual.appendChild(this.selectorLine),this.visual.appendChild(this.visibleLine),this.addMarkerVisualToContainer(this.visual)},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),"new"===this.state&&(this.createVisual(),this.adjustVisual(),this._state="creating")},t.prototype.adjustVisual=function(){this.selectorLine&&this.visibleLine&&(this.selectorLine.setAttribute("x1",this.x1.toString()),this.selectorLine.setAttribute("y1",this.y1.toString()),this.selectorLine.setAttribute("x2",this.x2.toString()),this.selectorLine.setAttribute("y2",this.y2.toString()),this.visibleLine.setAttribute("x1",this.x1.toString()),this.visibleLine.setAttribute("y1",this.y1.toString()),this.visibleLine.setAttribute("x2",this.x2.toString()),this.visibleLine.setAttribute("y2",this.y2.toString()),l.setAttributes(this.visibleLine,[["stroke",this.strokeColor]]),l.setAttributes(this.visibleLine,[["stroke-width",this.strokeWidth.toString()]]),l.setAttributes(this.visibleLine,[["stroke-dasharray",this.strokeDasharray.toString()]]))},t.prototype.setStrokeColor=function(e){this.strokeColor=e,this.adjustVisual(),this.colorChanged(e)},t.prototype.setStrokeWidth=function(e){this.strokeWidth=e,this.adjustVisual()},t.prototype.setStrokeDasharray=function(e){this.strokeDasharray=e,this.adjustVisual(),this.stateChanged()},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.strokePanel,this.strokeWidthPanel,this.strokeStylePanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=Object.assign({strokeColor:this.strokeColor,strokeWidth:this.strokeWidth,strokeDasharray:this.strokeDasharray},e.prototype.getState.call(this));return n.typeName=t.typeName,n},t.prototype.restoreState=function(t){e.prototype.restoreState.call(this,t);var n=t;this.strokeColor=n.strokeColor,this.strokeWidth=n.strokeWidth,this.strokeDasharray=n.strokeDasharray,this.createVisual(),this.adjustVisual()},t.typeName="LineMarker",t.title="Line marker",t.icon='<svg viewBox="0 0 24 24"><path d="M19 13H5v-2h14v2z"/></svg>',t}(N),D=function(e){function t(t,n,i,r){var s=e.call(this,t,r||'<svg viewBox="0 0 24 24"><path d="M17 8h3v12h1v1h-4v-1h1v-3h-4l-1.5 3H14v1h-4v-1h1l6-12m1 1l-3.5 7H18V9M5 3h5c1.11 0 2 .89 2 2v11H9v-5H6v5H3V5c0-1.11.89-2 2-2m1 2v4h3V5H6z"/></svg>')||this;return s.fonts=[],s.fontBoxes=[],s.fonts=n,s.currentFont=i,s.setCurrentFont=s.setCurrentFont.bind(s),s}return r(t,e),t.prototype.getUi=function(){var e=this,t=document.createElement("div");return t.style.overflow="hidden",t.style.flexGrow="2",this.fonts.forEach((function(n){var i=document.createElement("div");i.style.display="inline-block",i.style.alignItems="center",i.style.justifyContent="space-between",i.style.padding="5px",i.style.borderWidth="2px",i.style.borderStyle="solid",i.style.overflow="hidden",i.style.maxWidth=100/e.fonts.length-5+"%",i.style.borderColor=n===e.currentFont?e.uiStyleSettings.toolboxAccentColor:"transparent",i.addEventListener("click",(function(){e.setCurrentFont(n,i)})),t.appendChild(i);var r=document.createElement("div");r.style.display="flex",r.style.minHeight="20px",r.style.flexGrow="2",r.style.fontFamily=n,r.style.overflow="hidden";var s=document.createElement("div");s.style.whiteSpace="nowrap",s.style.overflow="hidden",s.style.textOverflow="ellipsis",s.innerHTML="The quick brown fox jumps over the lazy dog",r.appendChild(s),i.appendChild(r),e.fontBoxes.push(i)})),t},t.prototype.setCurrentFont=function(e,t){var n=this;this.currentFont=e,this.fontBoxes.forEach((function(e){e.style.borderColor=e===t?n.uiStyleSettings.toolboxAccentColor:"transparent"})),this.onFontChanged&&this.onFontChanged(this.currentFont)},t}(v),I=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.color="transparent",r.padding=5,r.DEFAULT_TEXT="请输入文本",r.text=r.DEFAULT_TEXT,r.isMoved=!1,r.color=i.defaultColor,r.fontFamily=i.defaultFontFamily,r.defaultSize={x:100,y:30},r.setColor=r.setColor.bind(r),r.setFont=r.setFont.bind(r),r.renderText=r.renderText.bind(r),r.sizeText=r.sizeText.bind(r),r.textEditDivClicked=r.textEditDivClicked.bind(r),r.showTextEditor=r.showTextEditor.bind(r),r.setSize=r.setSize.bind(r),r.positionTextEditor=r.positionTextEditor.bind(r),r.colorPanel=new A("Color",i.defaultColorSet,i.defaultColor),r.colorPanel.onColorChanged=r.setColor,r.fontFamilyPanel=new D("Font",i.defaultFontFamilies,i.defaultFontFamily),r.fontFamilyPanel.onFontChanged=r.setFont,r}return r(t,e),t.prototype.ownsTarget=function(t){if(e.prototype.ownsTarget.call(this,t)||t===this.visual||t===this.textElement||t===this.bgRectangle)return!0;var n=!1;return this.textElement.childNodes.forEach((function(e){e===t&&(n=!0)})),n},t.prototype.createVisual=function(){this.visual=l.createGroup(),this.bgRectangle=l.createRect(1,1,[["fill","transparent"]]),this.visual.appendChild(this.bgRectangle),this.textElement=l.createText([["fill",this.color],["font-family",this.fontFamily],["font-size","16px"],["x","0"],["y","0"]]),this.textElement.transform.baseVal.appendItem(l.createTransform()),this.textElement.transform.baseVal.appendItem(l.createTransform()),this.visual.appendChild(this.textElement),this.addMarkerVisualToContainer(this.visual),this.renderText()},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),this.isMoved=!1,this.pointerDownPoint=t,this.pointerDownTimestamp=Date.now(),"new"===this.state&&(this.createVisual(),this.moveVisual(t),this._state="creating")},t.prototype.renderText=function(){var e=this;if(this.textElement){for(;this.textElement.lastChild;)this.textElement.removeChild(this.textElement.lastChild);this.text.split(/\r\n|[\n\v\f\r\x85\u2028\u2029]/).forEach((function(t){e.textElement.appendChild(l.createTSpan(""===t.trim()?" ":t.trim(),[["x","0"],["dy","1.2em"]]))})),setTimeout(this.sizeText,10)}},t.prototype.getTextScale=function(){var e=this.textElement.getBBox(),t=1;if(e.width>0&&e.height>0){var n=(1*this.width-this.width*this.padding*2/100)/e.width,i=(1*this.height-this.height*this.padding*2/100)/e.height;t=Math.min(n,i)}return t},t.prototype.getTextPosition=function(e){var t=this.textElement.getBBox(),n=0,i=0;return t.width>0&&t.height>0&&(n=(this.width-t.width*e)/2,i=this.height/2-t.height*e/2),{x:n,y:i}},t.prototype.sizeText=function(){var e=this.textElement.getBBox(),t=this.getTextScale(),n=this.getTextPosition(t);n.y-=e.y*t,navigator.userAgent.indexOf("Edge/")>-1?this.textElement.style.transform="translate("+n.x+"px, "+n.y+"px) scale("+t+", "+t+")":(this.textElement.transform.baseVal.getItem(0).setTranslate(n.x,n.y),this.textElement.transform.baseVal.getItem(1).setScale(t,t))},t.prototype.manipulate=function(t){e.prototype.manipulate.call(this,t),void 0!==this.pointerDownPoint&&(this.isMoved=Math.abs(t.x-this.pointerDownPoint.x)>5||Math.abs(t.y-this.pointerDownPoint.y)>5)},t.prototype.resize=function(t){e.prototype.resize.call(this,t),this.isMoved=!0,this.setSize(),this.sizeText()},t.prototype.setSize=function(){e.prototype.setSize.call(this),this.visual&&this.bgRectangle&&(l.setAttributes(this.visual,[["width",this.width.toString()],["height",this.height.toString()]]),l.setAttributes(this.bgRectangle,[["width",this.width.toString()],["height",this.height.toString()]]))},t.prototype.pointerUp=function(t){var n=this.state;"creating"===n&&(this._suppressMarkerCreateEvent=!0),e.prototype.pointerUp.call(this,t),this.setSize(),("creating"===n||!this.isMoved&&Date.now()-this.pointerDownTimestamp>500)&&this.showTextEditor(),this.pointerDownPoint=void 0},t.prototype.showTextEditor=function(){var e=this;this._state="edit",this.overlayContainer.innerHTML="",this.textEditDiv=document.createElement("div"),this.textEditDiv.style.flexGrow="2",this.textEditDiv.style.alignItems="center",this.textEditDiv.style.justifyContent="center",this.textEditDiv.style.pointerEvents="auto",this.textEditDiv.style.overflow="hidden",this.textEditor=document.createElement("div"),this.textEditor.style.position="absolute",this.textEditor.style.fontFamily=this.fontFamily,this.textEditor.style.lineHeight="1em",this.textEditor.innerText=this.text,this.textEditor.contentEditable="true",this.textEditor.style.color=this.color,this.textEditor.style.whiteSpace="pre",this.positionTextEditor(),this.textEditor.addEventListener("pointerup",(function(e){e.stopPropagation()})),this.textEditor.addEventListener("input",(function(){for(var t=Number.parseFloat(e.textEditor.style.fontSize);e.textEditor.clientWidth>=Number.parseInt(e.textEditor.style.maxWidth)&&t>.9;)t-=.1,e.textEditor.style.fontSize=Math.max(t,.9)+"em"})),this.textEditor.addEventListener("keyup",(function(e){e.cancelBubble=!0})),this.textEditor.addEventListener("paste",(function(e){if(e.clipboardData){var t=e.clipboardData.getData("text"),n=window.getSelection();if(!n.rangeCount)return!1;n.deleteFromDocument(),n.getRangeAt(0).insertNode(document.createTextNode(t)),e.preventDefault()}})),this.textEditDiv.addEventListener("pointerup",(function(){e.textEditDivClicked(e.textEditor.innerText)})),this.textEditDiv.appendChild(this.textEditor),this.overlayContainer.appendChild(this.textEditDiv),this.hideVisual(),this.textEditor.focus(),document.execCommand("selectAll")},t.prototype.positionTextEditor=function(){if("edit"===this.state)if(void 0===this.textEditor)this.showTextEditor();else{this.textElement.style.display="";var e=this.getTextScale(),t=this.rotatePoint({x:this.left+this.width/2,y:this.top+this.height/2}),n=this.textElement.getBBox(),i={x:n.width*e,y:n.height*e};t.x-=i.x/2,t.y-=i.y/2,this.textEditor.style.top=t.y+"px",this.textEditor.style.left=t.x+"px",this.textEditor.style.maxWidth=this.overlayContainer.offsetWidth-t.x+"px",this.textEditor.style.fontSize=Math.max(16*e,12)+"px",this.textElement.style.display="none"}},t.prototype.textEditDivClicked=function(e){this.text=e.trim(),this.overlayContainer.innerHTML="",this.renderText(),this.showVisual(),this._suppressMarkerCreateEvent&&(this._suppressMarkerCreateEvent=!1,this.onMarkerCreated&&this.onMarkerCreated(this)),this.stateChanged()},t.prototype.select=function(){e.prototype.select.call(this),"edit"===this.state&&this.textEditDivClicked(this.textEditor.innerText)},t.prototype.deselect=function(){"edit"===this.state&&this.textEditDivClicked(this.textEditor.innerText),e.prototype.deselect.call(this)},t.prototype.dblClick=function(t,n){e.prototype.dblClick.call(this,t,n),this.showTextEditor()},t.prototype.setColor=function(e){this.textElement&&l.setAttributes(this.textElement,[["fill",e]]),this.color=e,this.textEditor&&(this.textEditor.style.color=this.color),this.colorChanged(e)},t.prototype.setFont=function(e){this.textElement&&l.setAttributes(this.textElement,[["font-family",e]]),this.fontFamily=e,this.textEditor&&(this.textEditor.style.fontFamily=this.fontFamily),this.renderText(),this.stateChanged()},t.prototype.hideVisual=function(){this.textElement.style.display="none",this.hideControlBox()},t.prototype.showVisual=function(){"edit"===this.state&&(this._state="select"),this.textElement.style.display="",this.showControlBox()},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.colorPanel,this.fontFamilyPanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=Object.assign({color:this.color,fontFamily:this.fontFamily,padding:this.padding,text:this.text},e.prototype.getState.call(this));return n.typeName=t.typeName,n},t.prototype.restoreState=function(t){var n=t;this.color=n.color,this.fontFamily=n.fontFamily,this.padding=n.padding,this.text=n.text,this.createVisual(),e.prototype.restoreState.call(this,t),this.setSize()},t.prototype.scale=function(t,n){e.prototype.scale.call(this,t,n),this.setSize(),this.sizeText(),this.positionTextEditor()},t.typeName="TextMarker",t.title="Text marker",t.icon='<svg viewBox="0 0 24 24"><path d="M9.6 14L12 7.7l2.4 6.3M11 5L5.5 19h2.2l1.1-3H15l1.1 3h2.2L13 5h-2z"/></svg>',t}(C),L=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.color="transparent",r.lineWidth=3,r.drawing=!1,r.pixelRatio=1,r.color=i.defaultColor,r.lineWidth=i.defaultStrokeWidth,r.pixelRatio=i.freehandPixelRatio,r.setColor=r.setColor.bind(r),r.addCanvas=r.addCanvas.bind(r),r.finishCreation=r.finishCreation.bind(r),r.setLineWidth=r.setLineWidth.bind(r),r.colorPanel=new A("Color",i.defaultColorSet,i.defaultColor),r.colorPanel.onColorChanged=r.setColor,r.lineWidthPanel=new E("Line width",i.defaultStrokeWidths,i.defaultStrokeWidth),r.lineWidthPanel.onWidthChanged=r.setLineWidth,r}return r(t,e),t.prototype.ownsTarget=function(t){return!(!e.prototype.ownsTarget.call(this,t)&&t!==this.visual&&t!==this.drawingImage)},t.prototype.createVisual=function(){this.visual=l.createGroup(),this.drawingImage=l.createImage(),this.visual.appendChild(this.drawingImage);var e=l.createTransform();this.visual.transform.baseVal.appendItem(e),this.addMarkerVisualToContainer(this.visual)},t.prototype.pointerDown=function(t,n){"new"===this.state&&(this.addCanvas(),this.createVisual(),this._state="creating"),"creating"===this.state?(this.canvasContext.strokeStyle=this.color,this.canvasContext.lineWidth=this.lineWidth,this.canvasContext.beginPath(),this.canvasContext.moveTo(t.x,t.y),this.drawing=!0):e.prototype.pointerDown.call(this,t,n)},t.prototype.manipulate=function(t){"creating"===this.state?this.drawing&&(this.canvasContext.lineTo(t.x,t.y),this.canvasContext.stroke()):e.prototype.manipulate.call(this,t)},t.prototype.resize=function(t){e.prototype.resize.call(this,t),l.setAttributes(this.visual,[["width",this.width.toString()],["height",this.height.toString()]]),l.setAttributes(this.drawingImage,[["width",this.width.toString()],["height",this.height.toString()]])},t.prototype.pointerUp=function(t){"creating"===this._state?this.drawing&&(this.canvasContext.closePath(),this.drawing=!1,this.globalSettings.newFreehandMarkerOnPointerUp&&this.finishCreation()):e.prototype.pointerUp.call(this,t)},t.prototype.addCanvas=function(){this.overlayContainer.innerHTML="",this.canvasElement=document.createElement("canvas"),this.canvasElement.width=this.overlayContainer.clientWidth*this.pixelRatio,this.canvasElement.height=this.overlayContainer.clientHeight*this.pixelRatio,this.canvasContext=this.canvasElement.getContext("2d"),this.canvasContext.scale(this.pixelRatio,this.pixelRatio),this.overlayContainer.appendChild(this.canvasElement)},t.prototype.select=function(){"creating"===this.state&&this.finishCreation(),e.prototype.select.call(this)},t.prototype.deselect=function(){"creating"===this.state&&this.finishCreation(),e.prototype.deselect.call(this)},t.prototype.finishCreation=function(){for(var e=this.canvasContext.getImageData(0,0,this.canvasElement.width,this.canvasElement.height),t=[this.canvasElement.width+1,this.canvasElement.height+1,-1,-1],n=t[0],i=t[1],r=t[2],s=t[3],o=!1,a=0;a<this.canvasElement.height;a++)for(var l=0;l<this.canvasElement.width;l++)e.data[a*this.canvasElement.width*4+4*l+3]>0&&(o=!0,a<i&&(i=a),l<n&&(n=l),a>s&&(s=a),l>r&&(r=l));if(o){this.left=n/this.pixelRatio,this.top=i/this.pixelRatio,this.width=(r-n)/this.pixelRatio,this.height=(s-i)/this.pixelRatio;var u=document.createElement("canvas");u.width=r-n,u.height=s-i,u.getContext("2d").putImageData(this.canvasContext.getImageData(n,i,r-n,s-i),0,0),this.drawingImgUrl=u.toDataURL("image/png"),this.setDrawingImage(),this._state="select",this.onMarkerCreated&&this.onMarkerCreated(this)}this.overlayContainer.innerHTML=""},t.prototype.setDrawingImage=function(){l.setAttributes(this.drawingImage,[["width",this.width.toString()],["height",this.height.toString()]]),l.setAttributes(this.drawingImage,[["href",this.drawingImgUrl]]),this.moveVisual({x:this.left,y:this.top})},t.prototype.setColor=function(e){this.color=e,this.colorChanged(e)},t.prototype.setLineWidth=function(e){this.lineWidth=e},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return"new"===this.state||"creating"===this.state?[this.colorPanel,this.lineWidthPanel]:[]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=Object.assign({drawingImgUrl:this.drawingImgUrl},e.prototype.getState.call(this));return n.typeName=t.typeName,n},t.prototype.restoreState=function(t){this.createVisual(),e.prototype.restoreState.call(this,t),this.drawingImgUrl=t.drawingImgUrl,this.setDrawingImage()},t.prototype.scale=function(t,n){e.prototype.scale.call(this,t,n),this.setDrawingImage()},t.typeName="FreehandMarker",t.title="Freehand marker",t.icon='<svg viewBox="0 0 24 24"><path d="M9.75 20.85c1.78-.7 1.39-2.63.49-3.85-.89-1.25-2.12-2.11-3.36-2.94A9.817 9.817 0 014.54 12c-.28-.33-.85-.94-.27-1.06.59-.12 1.61.46 2.13.68.91.38 1.81.82 2.65 1.34l1.01-1.7C8.5 10.23 6.5 9.32 4.64 9.05c-1.06-.16-2.18.06-2.54 1.21-.32.99.19 1.99.77 2.77 1.37 1.83 3.5 2.71 5.09 4.29.34.33.75.72.95 1.18.21.44.16.47-.31.47-1.24 0-2.79-.97-3.8-1.61l-1.01 1.7c1.53.94 4.09 2.41 5.96 1.79m11.09-15.6c.22-.22.22-.58 0-.79l-1.3-1.3a.562.562 0 00-.78 0l-1.02 1.02 2.08 2.08M11 10.92V13h2.08l6.15-6.15-2.08-2.08L11 10.92z"/></svg>',t}(C),j=function(e){function t(t,n,i){var r=e.call(this,t,i||'<svg viewBox="0 0 24 24"><path d="M8 14v4l-6-6 6-6v4h8V6l6 6-6 6v-4H8z"/></svg>')||this;return r.typeBoxes=[],r.currentType=n,r.setCurrentType=r.setCurrentType.bind(r),r}return r(t,e),t.prototype.getUi=function(){var e=this,t=document.createElement("div");t.style.display="flex",t.style.overflow="hidden",t.style.flexGrow="2";for(var n=function(n){var r="both";switch(n){case 0:r="both";break;case 1:r="start";break;case 2:r="end";break;case 3:r="none"}var s=document.createElement("div");if(s.style.display="flex",s.style.flexGrow="2",s.style.alignItems="center",s.style.justifyContent="space-between",s.style.padding="5px",s.style.borderWidth="2px",s.style.borderStyle="solid",s.style.borderColor=r===i.currentType?i.uiStyleSettings.toolboxAccentColor:"transparent",s.addEventListener("click",(function(){e.setCurrentType(r,s)})),t.appendChild(s),"both"===r||"start"===r){var o=document.createElement("div");o.style.display="flex",o.style.alignItems="center",o.style.minHeight="20px",o.innerHTML='<svg viewBox="0 0 10 10" width="10" height="10" xmlns="http://www.w3.org/2000/svg">\n          <polygon points="0,5 10,0 10,10" fill="'+(void 0!==i.uiStyleSettings?i.uiStyleSettings.toolboxColor:"#eeeeee")+'" />\n        </svg>',o.style.marginLeft="5px",s.appendChild(o)}var a=document.createElement("div");a.style.display="flex",a.style.alignItems="center",a.style.minHeight="20px",a.style.flexGrow="2";var l=document.createElement("hr");if(l.style.minWidth="20px",l.style.border="0px",l.style.borderTop="3px solid "+(void 0!==i.uiStyleSettings?i.uiStyleSettings.toolboxColor:"#eeeeee"),l.style.flexGrow="2",a.appendChild(l),s.appendChild(a),"both"===r||"end"===r){var u=document.createElement("div");u.style.display="flex",u.style.alignItems="center",u.style.minHeight="20px",u.innerHTML='<svg viewBox="0 0 10 10" width="10" height="10" xmlns="http://www.w3.org/2000/svg">\n          <polygon points="0,0 10,5 0,10" fill="'+(void 0!==i.uiStyleSettings?i.uiStyleSettings.toolboxColor:"#eeeeee")+'" />\n        </svg>',u.style.marginRight="5px",s.appendChild(u)}i.typeBoxes.push(s)},i=this,r=0;r<4;r++)n(r);return t},t.prototype.setCurrentType=function(e,t){var n=this;this.currentType=e,this.typeBoxes.forEach((function(e){e.style.borderColor=e===t?void 0!==n.uiStyleSettings?n.uiStyleSettings.toolboxAccentColor:"#3080c3":"transparent"})),this.onArrowTypeChanged&&this.onArrowTypeChanged(this.currentType)},t}(v),O=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.arrowType="end",r.arrowBaseHeight=10,r.arrowBaseWidth=10,r.getArrowPoints=r.getArrowPoints.bind(r),r.setArrowType=r.setArrowType.bind(r),r.arrowTypePanel=new j("Arrow type","end"),r.arrowTypePanel.onArrowTypeChanged=r.setArrowType,r}return r(t,e),t.prototype.ownsTarget=function(t){return!(!e.prototype.ownsTarget.call(this,t)&&t!==this.arrow1&&t!==this.arrow2)},t.prototype.getArrowPoints=function(e,t){var n=this.arrowBaseWidth+2*this.strokeWidth,i=this.arrowBaseHeight+2*this.strokeWidth;return e-n/2+","+(t+i/2)+" "+e+","+(t-i/2)+" "+(e+n/2)+","+(t+i/2)},t.prototype.createTips=function(){this.arrow1=l.createPolygon(this.getArrowPoints(this.x1,this.y1),[["fill",this.strokeColor]]),this.arrow1.transform.baseVal.appendItem(l.createTransform()),this.visual.appendChild(this.arrow1),this.arrow2=l.createPolygon(this.getArrowPoints(this.x2,this.y2),[["fill",this.strokeColor]]),this.arrow2.transform.baseVal.appendItem(l.createTransform()),this.visual.appendChild(this.arrow2)},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),"creating"===this.state&&this.createTips()},t.prototype.adjustVisual=function(){if(e.prototype.adjustVisual.call(this),this.arrow1&&this.arrow2){this.arrow1.style.display="both"===this.arrowType||"start"===this.arrowType?"":"none",this.arrow2.style.display="both"===this.arrowType||"end"===this.arrowType?"":"none",l.setAttributes(this.arrow1,[["points",this.getArrowPoints(this.x1,this.y1)],["fill",this.strokeColor]]),l.setAttributes(this.arrow2,[["points",this.getArrowPoints(this.x2,this.y2)],["fill",this.strokeColor]]);var t=0;Math.abs(this.x1-this.x2)>.1&&(t=180*Math.atan((this.y2-this.y1)/(this.x2-this.x1))/Math.PI+90*Math.sign(this.x1-this.x2));var n=this.arrow1.transform.baseVal.getItem(0);n.setRotate(t,this.x1,this.y1),this.arrow1.transform.baseVal.replaceItem(n,0);var i=this.arrow2.transform.baseVal.getItem(0);i.setRotate(t+180,this.x2,this.y2),this.arrow2.transform.baseVal.replaceItem(i,0)}},t.prototype.setArrowType=function(e){this.arrowType=e,this.adjustVisual(),this.stateChanged()},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.strokePanel,this.strokeWidthPanel,this.strokeStylePanel,this.arrowTypePanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=Object.assign({arrowType:this.arrowType},e.prototype.getState.call(this));return n.typeName=t.typeName,n},t.prototype.restoreState=function(t){e.prototype.restoreState.call(this,t);var n=t;this.arrowType=n.arrowType,this.createTips(),this.adjustVisual()},t.typeName="ArrowMarker",t.title="Arrow marker",t.icon='<svg viewBox="0 0 24 24"><path d="M19 6.41L17.59 5 7 15.59V9H5v10h10v-2H8.41L19 6.41z"/></svg>',t}(B),z=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.fillColor=i.defaultFillColor,r.strokeWidth=0,r.fillPanel=new A("Color",i.defaultColorSet,i.defaultFillColor),r.fillPanel.onColorChanged=r.setFillColor,r}return r(t,e),Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.fillPanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=e.prototype.getState.call(this);return n.typeName=t.typeName,n},t.typeName="CoverMarker",t.title="Cover marker",t.icon='<svg viewBox="0 0 24 24"><path d="M4 6v13h16V6H4z"/></svg>',t}(M),R=function(e){function t(t,n,i,r){var s=e.call(this,t,r||'<svg viewBox="0 0 24 24"><path d="M17.66 8L12 2.35 6.34 8A8.02 8.02 0 004 13.64c0 2 .78 4.11 2.34 5.67a7.99 7.99 0 0011.32 0c1.56-1.56 2.34-3.67 2.34-5.67S19.22 9.56 17.66 8M6 14c0-2 .62-3.27 1.76-4.4L12 5.27l4.24 4.38C17.38 10.77 18 12 18 14H6z"/></svg>')||this;return s.opacities=[],s.opacityBoxes=[],s.opacities=n,s.currentOpacity=i,s.setCurrentOpacity=s.setCurrentOpacity.bind(s),s}return r(t,e),t.prototype.getUi=function(){var e=this,t=document.createElement("div");return t.style.display="flex",t.style.overflow="hidden",t.style.flexGrow="2",t.style.justifyContent="space-between",this.opacities.forEach((function(n){var i=document.createElement("div");i.style.display="flex",i.style.alignItems="center",i.style.justifyContent="center",i.style.padding="5px",i.style.borderWidth="2px",i.style.borderStyle="solid",i.style.borderColor=n===e.currentOpacity?e.uiStyleSettings.toolboxAccentColor:"transparent",i.addEventListener("click",(function(){e.setCurrentOpacity(n,i)})),t.appendChild(i);var r=document.createElement("div");r.innerText=100*n+"%",i.appendChild(r),e.opacityBoxes.push(i)})),t},t.prototype.setCurrentOpacity=function(e,t){var n=this;this.currentOpacity=e,this.opacityBoxes.forEach((function(e){e.style.borderColor=e===t?n.uiStyleSettings.toolboxAccentColor:"transparent"})),this.onOpacityChanged&&this.onOpacityChanged(this.currentOpacity)},t}(v),k=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.setOpacity=r.setOpacity.bind(r),r.fillColor=i.defaultHighlightColor,r.strokeWidth=0,r.opacity=i.defaultHighlightOpacity,r.fillPanel=new A("Color",i.defaultColorSet,r.fillColor),r.fillPanel.onColorChanged=r.setFillColor,r.opacityPanel=new R("Opacity",i.defaultOpacitySteps,r.opacity),r.opacityPanel.onOpacityChanged=r.setOpacity,r}return r(t,e),t.prototype.setOpacity=function(e){this.opacity=e,this.visual&&l.setAttributes(this.visual,[["opacity",this.opacity.toString()]]),this.stateChanged()},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.fillPanel,this.opacityPanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=e.prototype.getState.call(this);return n.typeName=t.typeName,n},t.typeName="HighlightMarker",t.title="Highlight marker",t.icon='<svg viewBox="0 0 24 24"><path d="M18.5 1.15c-.53 0-1.04.19-1.43.58l-5.81 5.82 5.65 5.65 5.82-5.81c.77-.78.77-2.04 0-2.83l-2.84-2.83c-.39-.39-.89-.58-1.39-.58M10.3 8.5l-5.96 5.96c-.78.78-.78 2.04.02 2.85C3.14 18.54 1.9 19.77.67 21h5.66l.86-.86c.78.76 2.03.75 2.81-.02l5.95-5.96"/></svg>',t}(z),F='<svg viewBox="0 0 24 24"><path d="M9.62 12L12 5.67 14.37 12M11 3L5.5 17h2.25l1.12-3h6.25l1.13 3h2.25L13 3h-2z"/></svg>',H='<svg viewBox="0 0 24 24"><path d="M19 11.5s-2 2.17-2 3.5a2 2 0 002 2 2 2 0 002-2c0-1.33-2-3.5-2-3.5M5.21 10L10 5.21 14.79 10m1.77-1.06L7.62 0 6.21 1.41l2.38 2.38-5.15 5.15c-.59.56-.59 1.53 0 2.12l5.5 5.5c.29.29.68.44 1.06.44s.77-.15 1.06-.44l5.5-5.5c.59-.59.59-1.56 0-2.12z"/></svg>',U=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.bgColor="transparent",r.tipPosition={x:0,y:0},r.tipBase1Position={x:0,y:0},r.tipBase2Position={x:0,y:0},r.tipMoving=!1,r.color=i.defaultStrokeColor,r.bgColor=i.defaultFillColor,r.fontFamily=i.defaultFontFamily,r.defaultSize={x:100,y:30},r.setBgColor=r.setBgColor.bind(r),r.getTipPoints=r.getTipPoints.bind(r),r.positionTip=r.positionTip.bind(r),r.setTipPoints=r.setTipPoints.bind(r),r.colorPanel=new A("Text color",i.defaultColorSet,r.color,F),r.colorPanel.onColorChanged=r.setColor,r.bgColorPanel=new A("Fill color",i.defaultColorSet,r.bgColor,H),r.bgColorPanel.onColorChanged=r.setBgColor,r.fontFamilyPanel=new D("Font",i.defaultFontFamilies,i.defaultFontFamily),r.fontFamilyPanel.onFontChanged=r.setFont,r.tipGrip=new b,r.tipGrip.visual.transform.baseVal.appendItem(l.createTransform()),r.controlBox.appendChild(r.tipGrip.visual),r}return r(t,e),t.prototype.ownsTarget=function(t){return e.prototype.ownsTarget.call(this,t)||this.tipGrip.ownsTarget(t)||this.tip===t},t.prototype.createTip=function(){l.setAttributes(this.bgRectangle,[["fill",this.bgColor],["rx","10px"]]),this.tip=l.createPolygon(this.getTipPoints(),[["fill",this.bgColor]]),this.visual.appendChild(this.tip)},t.prototype.pointerDown=function(t,n){"new"===this.state&&e.prototype.pointerDown.call(this,t,n),"creating"===this.state?this.createTip():this.tipGrip.ownsTarget(n)?(this.manipulationStartLeft=this.left,this.manipulationStartTop=this.top,this.tipMoving=!0):e.prototype.pointerDown.call(this,t,n)},t.prototype.pointerUp=function(t){if(this.tipMoving)this.tipMoving=!1,this.isMoved=!0,e.prototype.pointerUp.call(this,t);else{var n="creating"===this.state;e.prototype.pointerUp.call(this,t),this.setTipPoints(n),this.positionTip()}},t.prototype.manipulate=function(t){if(this.tipMoving){var n=this.unrotatePoint(t);this.tipPosition={x:n.x-this.manipulationStartLeft,y:n.y-this.manipulationStartTop},this.positionTip()}else e.prototype.manipulate.call(this,t)},t.prototype.setBgColor=function(e){this.bgRectangle&&this.tip&&(l.setAttributes(this.bgRectangle,[["fill",e]]),l.setAttributes(this.tip,[["fill",e]])),this.bgColor=e,this.fillColorChanged(e)},t.prototype.getTipPoints=function(){return this.setTipPoints("creating"===this.state),this.tipBase1Position.x+","+this.tipBase1Position.y+" "+this.tipBase2Position.x+","+this.tipBase2Position.y+" "+this.tipPosition.x+","+this.tipPosition.y},t.prototype.setTipPoints=function(e){void 0===e&&(e=!1);var t=Math.min(this.height/2,15),n=this.height/5;e&&(this.tipPosition={x:t+n/2,y:this.height+20});var i=Math.atan(this.height/2/(this.width/2));this.tipPosition.x<this.width/2&&this.tipPosition.y<this.height/2?i<Math.atan((this.height/2-this.tipPosition.y)/(this.width/2-this.tipPosition.x))?(n=this.width/5,t=Math.min(this.width/2,15),this.tipBase1Position={x:t,y:0},this.tipBase2Position={x:t+n,y:0}):(this.tipBase1Position={x:0,y:t},this.tipBase2Position={x:0,y:t+n}):this.tipPosition.x>=this.width/2&&this.tipPosition.y<this.height/2?i<Math.atan((this.height/2-this.tipPosition.y)/(this.tipPosition.x-this.width/2))?(n=this.width/5,t=Math.min(this.width/2,15),this.tipBase1Position={x:this.width-t-n,y:0},this.tipBase2Position={x:this.width-t,y:0}):(this.tipBase1Position={x:this.width,y:t},this.tipBase2Position={x:this.width,y:t+n}):this.tipPosition.x>=this.width/2&&this.tipPosition.y>=this.height/2?i<Math.atan((this.tipPosition.y-this.height/2)/(this.tipPosition.x-this.width/2))?(n=this.width/5,t=Math.min(this.width/2,15),this.tipBase1Position={x:this.width-t-n,y:this.height},this.tipBase2Position={x:this.width-t,y:this.height}):(this.tipBase1Position={x:this.width,y:this.height-t-n},this.tipBase2Position={x:this.width,y:this.height-t}):i<Math.atan((this.tipPosition.y-this.height/2)/(this.width/2-this.tipPosition.x))?(n=this.width/5,t=Math.min(this.width/2,15),this.tipBase1Position={x:t,y:this.height},this.tipBase2Position={x:t+n,y:this.height}):(this.tipBase1Position={x:0,y:this.height-t},this.tipBase2Position={x:0,y:this.height-t-n})},t.prototype.resize=function(t){e.prototype.resize.call(this,t),this.positionTip()},t.prototype.positionTip=function(){l.setAttributes(this.tip,[["points",this.getTipPoints()]]);var e=this.tipGrip.visual.transform.baseVal.getItem(0);e.setTranslate(this.tipPosition.x,this.tipPosition.y),this.tipGrip.visual.transform.baseVal.replaceItem(e,0)},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.colorPanel,this.bgColorPanel,this.fontFamilyPanel]},enumerable:!1,configurable:!0}),t.prototype.select=function(){this.positionTip(),e.prototype.select.call(this)},t.prototype.getState=function(){var n=Object.assign({bgColor:this.bgColor,tipPosition:this.tipPosition},e.prototype.getState.call(this));return n.typeName=t.typeName,n},t.prototype.restoreState=function(t){var n=t;this.bgColor=n.bgColor,this.tipPosition=n.tipPosition,e.prototype.restoreState.call(this,t),this.createTip(),this.setTipPoints()},t.prototype.scale=function(t,n){e.prototype.scale.call(this,t,n),this.tipPosition={x:this.tipPosition.x*t,y:this.tipPosition.y*n},this.positionTip()},t.typeName="CalloutMarker",t.title="Callout marker",t.icon='<svg viewBox="0 0 24 24"><path d="M4 2h16a2 2 0 012 2v12a2 2 0 01-2 2h-4l-4 4-4-4H4a2 2 0 01-2-2V4a2 2 0 012-2m0 2v12h4.83L12 19.17 15.17 16H20V4H4m2 3h12v2H6V7m0 4h10v2H6v-2z"/></svg>',t}(I),X=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.fillColor="transparent",r.strokeColor="transparent",r.strokeWidth=0,r.strokeDasharray="",r.opacity=1,r.strokeColor=i.defaultColor,r.strokeWidth=i.defaultStrokeWidth,r.strokeDasharray=i.defaultStrokeDasharray,r.fillColor=i.defaultFillColor,r.setStrokeColor=r.setStrokeColor.bind(r),r.setFillColor=r.setFillColor.bind(r),r.setStrokeWidth=r.setStrokeWidth.bind(r),r.setStrokeDasharray=r.setStrokeDasharray.bind(r),r.setOpacity=r.setOpacity.bind(r),r.createVisual=r.createVisual.bind(r),r.strokePanel=new A("Line color",a(i.defaultColorSet,["transparent"]),i.defaultColor),r.strokePanel.onColorChanged=r.setStrokeColor,r.fillPanel=new A("Fill color",a(i.defaultColorSet,["transparent"]),r.fillColor,H),r.fillPanel.onColorChanged=r.setFillColor,r.strokeWidthPanel=new E("Line width",i.defaultStrokeWidths,i.defaultStrokeWidth),r.strokeWidthPanel.onWidthChanged=r.setStrokeWidth,r.strokeStylePanel=new T("Line style",i.defaultStrokeDasharrays,i.defaultStrokeDasharray),r.strokeStylePanel.onStyleChanged=r.setStrokeDasharray,r.opacityPanel=new R("Opacity",i.defaultOpacitySteps,r.opacity),r.opacityPanel.onOpacityChanged=r.setOpacity,r}return r(t,e),t.prototype.ownsTarget=function(t){return!(!e.prototype.ownsTarget.call(this,t)&&t!==this.visual)},t.prototype.createVisual=function(){this.visual=l.createEllipse(this.width/2,this.height/2,[["fill",this.fillColor],["stroke",this.strokeColor],["stroke-width",this.strokeWidth.toString()],["stroke-dasharray",this.strokeDasharray],["opacity",this.opacity.toString()]]),this.addMarkerVisualToContainer(this.visual)},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),"new"===this.state&&(this.createVisual(),this.moveVisual(t),this._state="creating")},t.prototype.manipulate=function(t){e.prototype.manipulate.call(this,t)},t.prototype.resize=function(t){e.prototype.resize.call(this,t),this.setSize()},t.prototype.setSize=function(){e.prototype.setSize.call(this),l.setAttributes(this.visual,[["cx",(this.width/2).toString()],["cy",(this.height/2).toString()],["rx",(this.width/2).toString()],["ry",(this.height/2).toString()]])},t.prototype.pointerUp=function(t){e.prototype.pointerUp.call(this,t),this.setSize()},t.prototype.setStrokeColor=function(e){this.strokeColor=e,this.visual&&l.setAttributes(this.visual,[["stroke",this.strokeColor]]),this.colorChanged(e),this.stateChanged()},t.prototype.setFillColor=function(e){this.fillColor=e,this.visual&&l.setAttributes(this.visual,[["fill",this.fillColor]]),this.fillColorChanged(e),this.stateChanged()},t.prototype.setStrokeWidth=function(e){this.strokeWidth=e,this.visual&&l.setAttributes(this.visual,[["stroke-width",this.strokeWidth.toString()]]),this.stateChanged()},t.prototype.setStrokeDasharray=function(e){this.strokeDasharray=e,this.visual&&l.setAttributes(this.visual,[["stroke-dasharray",this.strokeDasharray]]),this.stateChanged()},t.prototype.setOpacity=function(e){this.opacity=e,this.visual&&l.setAttributes(this.visual,[["opacity",this.opacity.toString()]]),this.stateChanged()},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.strokePanel,this.fillPanel,this.strokeWidthPanel,this.strokeStylePanel,this.opacityPanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=Object.assign({fillColor:this.fillColor,strokeColor:this.strokeColor,strokeWidth:this.strokeWidth,strokeDasharray:this.strokeDasharray,opacity:this.opacity},e.prototype.getState.call(this));return n.typeName=t.typeName,n},t.prototype.restoreState=function(t){var n=t;this.fillColor=n.fillColor,this.strokeColor=n.strokeColor,this.strokeWidth=n.strokeWidth,this.strokeDasharray=n.strokeDasharray,this.opacity=n.opacity,this.createVisual(),e.prototype.restoreState.call(this,t),this.setSize()},t.prototype.scale=function(t,n){e.prototype.scale.call(this,t,n),this.setSize()},t.typeName="EllipseMarker",t.title="Ellipse marker",t.icon='<svg viewBox="0 0 24 24"><path d="M12 4C6.5 4 2 7.58 2 12s4.5 8 10 8 10-3.58 10-8-4.5-8-10-8z"/></svg>',t}(C),G=function(e){function t(t,n,i){return e.call(this,t,n,i)||this}return r(t,e),Object.defineProperty(t.prototype,"tipLength",{get:function(){return 10+3*this.strokeWidth},enumerable:!1,configurable:!0}),t.prototype.ownsTarget=function(t){return!(!e.prototype.ownsTarget.call(this,t)&&t!==this.tip1&&t!==this.tip2)},t.prototype.createTips=function(){this.tip1=l.createLine(this.x1-this.tipLength/2,this.y1,this.x1+this.tipLength/2,this.y1,[["stroke",this.strokeColor],["stroke-width",this.strokeWidth.toString()]]),this.tip1.transform.baseVal.appendItem(l.createTransform()),this.visual.appendChild(this.tip1),this.tip2=l.createLine(this.x2-this.tipLength/2,this.y2,this.x2+this.tipLength/2,this.y2,[["stroke",this.strokeColor],["stroke-width",this.strokeWidth.toString()]]),this.tip2.transform.baseVal.appendItem(l.createTransform()),this.visual.appendChild(this.tip2)},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),"creating"===this.state&&this.createTips()},t.prototype.adjustVisual=function(){if(e.prototype.adjustVisual.call(this),this.tip1&&this.tip2&&(l.setAttributes(this.tip1,[["x1",(this.x1-this.tipLength/2).toString()],["y1",this.y1.toString()],["x2",(this.x1+this.tipLength/2).toString()],["y2",this.y1.toString()],["stroke",this.strokeColor],["stroke-width",this.strokeWidth.toString()]]),l.setAttributes(this.tip2,[["x1",(this.x2-this.tipLength/2).toString()],["y1",this.y2.toString()],["x2",(this.x2+this.tipLength/2).toString()],["y2",this.y2.toString()],["stroke",this.strokeColor],["stroke-width",this.strokeWidth.toString()]]),Math.abs(this.x1-this.x2)>.1)){var t=180*Math.atan((this.y2-this.y1)/(this.x2-this.x1))/Math.PI+90*Math.sign(this.x1-this.x2),n=this.tip1.transform.baseVal.getItem(0);n.setRotate(t,this.x1,this.y1),this.tip1.transform.baseVal.replaceItem(n,0);var i=this.tip2.transform.baseVal.getItem(0);i.setRotate(t+180,this.x2,this.y2),this.tip2.transform.baseVal.replaceItem(i,0)}},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.strokePanel,this.strokeWidthPanel,this.strokeStylePanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=e.prototype.getState.call(this);return n.typeName=t.typeName,n},t.prototype.restoreState=function(t){e.prototype.restoreState.call(this,t),this.createTips(),this.adjustVisual()},t.typeName="MeasurementMarker",t.title="Measurement marker",t.icon='<svg viewBox="0 0 24 24"><path d="M1.39 18.36l1.77-1.76L4.58 18l1.06-1.05-1.42-1.41 1.42-1.42 2.47 2.48 1.06-1.06-2.47-2.48 1.41-1.41 1.42 1.41L10.59 12l-1.42-1.41 1.42-1.42 2.47 2.48 1.06-1.06-2.47-2.48 1.41-1.41 1.41 1.41 1.07-1.06-1.42-1.41 1.42-1.42L18 6.7l1.07-1.06-2.47-2.48 1.76-1.77 4.25 4.25L5.64 22.61l-4.25-4.25z"/></svg>',t}(B),V=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.strokePanel.colors=i.defaultColorSet,r.fillColor="transparent",r}return r(t,e),Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.strokePanel,this.strokeWidthPanel,this.strokeStylePanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=e.prototype.getState.call(this);return n.typeName=t.typeName,n},t.typeName="EllipseFrameMarker",t.title="Ellipse frame marker",t.icon='<svg viewBox="0 0 24 24"><path d="M12 6c4.41 0 8 2.69 8 6s-3.59 6-8 6-8-2.69-8-6 3.59-6 8-6m0-2C6.5 4 2 7.58 2 12s4.5 8 10 8 10-3.58 10-8-4.5-8-10-8z"/></svg>',t}(X),W=function(){function e(){this.undoStack=[],this.redoStack=[]}return Object.defineProperty(e.prototype,"isUndoPossible",{get:function(){return this.undoStack.length>0},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"isRedoPossible",{get:function(){return this.redoStack.length>0},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"undoStepCount",{get:function(){return this.undoStack.length},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"redoStepCount",{get:function(){return this.redoStack.length},enumerable:!1,configurable:!0}),e.prototype.addUndoStep=function(e){0!==this.undoStack.length&&JSON.stringify(this.undoStack[this.undoStack.length-1])===JSON.stringify(e)||(this.undoStack.push(e),JSON.stringify(this.lastRedoStep)!==JSON.stringify(e)&&this.redoStack.splice(0,this.redoStack.length))},e.prototype.replaceLastUndoStep=function(e){this.undoStack.length>0&&(this.undoStack[this.undoStack.length-1]=e)},e.prototype.getLastUndoStep=function(){return this.undoStack.length>0?this.undoStack[this.undoStack.length-1]:void 0},e.prototype.undo=function(){if(this.undoStack.length>1){var e=this.undoStack.pop();return void 0!==e&&this.redoStack.push(e),this.undoStack.length>0?this.undoStack[this.undoStack.length-1]:void 0}},e.prototype.redo=function(){return this.lastRedoStep=this.redoStack.pop(),this.lastRedoStep},e}(),Q=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.strokeColor="transparent",r.strokeWidth=0,r.strokeDasharray="",r.curveX=0,r.curveY=0,r.manipulationStartCurveX=0,r.manipulationStartCurveY=0,r.setStrokeColor=r.setStrokeColor.bind(r),r.setStrokeWidth=r.setStrokeWidth.bind(r),r.setStrokeDasharray=r.setStrokeDasharray.bind(r),r.positionGrips=r.positionGrips.bind(r),r.addControlGrips=r.addControlGrips.bind(r),r.adjustVisual=r.adjustVisual.bind(r),r.setupControlBox=r.setupControlBox.bind(r),r.resize=r.resize.bind(r),r.strokeColor=i.defaultColor,r.strokeWidth=i.defaultStrokeWidth,r.strokeDasharray=i.defaultStrokeDasharray,r.strokePanel=new A("Line color",i.defaultColorSet,i.defaultColor),r.strokePanel.onColorChanged=r.setStrokeColor,r.strokeWidthPanel=new E("Line width",i.defaultStrokeWidths,i.defaultStrokeWidth),r.strokeWidthPanel.onWidthChanged=r.setStrokeWidth,r.strokeStylePanel=new T("Line style",i.defaultStrokeDasharrays,i.defaultStrokeDasharray),r.strokeStylePanel.onStyleChanged=r.setStrokeDasharray,r}return r(t,e),t.prototype.ownsTarget=function(t){return!(!e.prototype.ownsTarget.call(this,t)&&t!==this.visual&&t!==this.selectorCurve&&t!==this.visibleCurve&&!this.curveGrip.ownsTarget(t))},t.prototype.getPathD=function(){return"M "+this.x1+" "+this.y1+" Q "+this.curveX+" "+this.curveY+", "+this.x2+" "+this.y2},t.prototype.createVisual=function(){this.visual=l.createGroup(),this.selectorCurve=l.createPath(this.getPathD(),[["stroke","transparent"],["stroke-width",(this.strokeWidth+10).toString()],["fill","transparent"]]),this.visibleCurve=l.createPath(this.getPathD(),[["stroke",this.strokeColor],["stroke-width",this.strokeWidth.toString()],["fill","transparent"]]),this.visual.appendChild(this.selectorCurve),this.visual.appendChild(this.visibleCurve),this.addMarkerVisualToContainer(this.visual)},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),this.manipulationStartCurveX=this.curveX,this.manipulationStartCurveY=this.curveY,"new"===this.state&&(this.curveX=t.x,this.curveY=t.y),"new"===this.state?(this.createVisual(),this.adjustVisual(),this._state="creating"):this.curveGrip.ownsTarget(n)&&(this.activeGrip=this.curveGrip,this._state="resize")},t.prototype.adjustVisual=function(){this.selectorCurve&&this.visibleCurve&&(this.selectorCurve.setAttribute("d",this.getPathD()),this.visibleCurve.setAttribute("d",this.getPathD()),l.setAttributes(this.visibleCurve,[["stroke",this.strokeColor]]),l.setAttributes(this.visibleCurve,[["stroke-width",this.strokeWidth.toString()]]),l.setAttributes(this.visibleCurve,[["stroke-dasharray",this.strokeDasharray.toString()]]))},t.prototype.setupControlBox=function(){e.prototype.setupControlBox.call(this),this.curveControlLine1=l.createLine(this.x1,this.y1,this.curveX,this.curveY,[["stroke","black"],["stroke-width","1"],["stroke-opacity","0.5"],["stroke-dasharray","3, 2"]]),this.curveControlLine2=l.createLine(this.x2,this.y2,this.curveX,this.curveY,[["stroke","black"],["stroke-width","1"],["stroke-opacity","0.5"],["stroke-dasharray","3, 2"]]),this.controlBox.insertBefore(this.curveControlLine1,this.controlBox.firstChild),this.controlBox.insertBefore(this.curveControlLine2,this.controlBox.firstChild)},t.prototype.addControlGrips=function(){this.curveGrip=this.createGrip(),this.curveX=0,this.curveY=0,e.prototype.addControlGrips.call(this)},t.prototype.positionGrips=function(){e.prototype.positionGrips.call(this);var t=this.curveGrip.GRIP_SIZE;this.positionGrip(this.curveGrip.visual,this.curveX-t/2,this.curveY-t/2),this.curveControlLine1&&this.curveControlLine2&&(this.curveControlLine1.setAttribute("x1",this.x1.toString()),this.curveControlLine1.setAttribute("y1",this.y1.toString()),this.curveControlLine1.setAttribute("x2",this.curveX.toString()),this.curveControlLine1.setAttribute("y2",this.curveY.toString()),this.curveControlLine2.setAttribute("x1",this.x2.toString()),this.curveControlLine2.setAttribute("y1",this.y2.toString()),this.curveControlLine2.setAttribute("x2",this.curveX.toString()),this.curveControlLine2.setAttribute("y2",this.curveY.toString()))},t.prototype.manipulate=function(t){"move"===this.state&&(this.curveX=this.manipulationStartCurveX+t.x-this.manipulationStartX,this.curveY=this.manipulationStartCurveY+t.y-this.manipulationStartY),e.prototype.manipulate.call(this,t)},t.prototype.resize=function(t){this.activeGrip===this.curveGrip&&(this.curveX=t.x,this.curveY=t.y),e.prototype.resize.call(this,t),"creating"===this.state&&(this.curveX=this.x1+(this.x2-this.x1)/2,this.curveY=this.y1+(this.y2-this.y1)/2)},t.prototype.setStrokeColor=function(e){this.strokeColor=e,this.adjustVisual(),this.colorChanged(e)},t.prototype.setStrokeWidth=function(e){this.strokeWidth=e,this.adjustVisual()},t.prototype.setStrokeDasharray=function(e){this.strokeDasharray=e,this.adjustVisual()},t.prototype.scale=function(t,n){this.curveX=this.curveX*t,this.curveY=this.curveY*n,e.prototype.scale.call(this,t,n)},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.strokePanel,this.strokeWidthPanel,this.strokeStylePanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var n=Object.assign({strokeColor:this.strokeColor,strokeWidth:this.strokeWidth,strokeDasharray:this.strokeDasharray,curveX:this.curveX,curveY:this.curveY},e.prototype.getState.call(this));return n.typeName=t.typeName,n},t.prototype.restoreState=function(t){e.prototype.restoreState.call(this,t);var n=t;this.strokeColor=n.strokeColor,this.strokeWidth=n.strokeWidth,this.strokeDasharray=n.strokeDasharray,this.curveX=n.curveX,this.curveY=n.curveY,this.createVisual(),this.adjustVisual()},t.typeName="CurveMarker",t.title="Curve marker",t.icon='<svg viewBox="0 0 24 24"><path d="M18.5 2A1.5 1.5 0 0120 3.5 1.5 1.5 0 0118.5 5c-.23 0-.45-.05-.65-.15l-3.69 3.7.34.45c2.19-1.26 4.76-2 7.5-2l1 .03v2.01L22 9c-2.58 0-5 .75-7 2.04A3.96 3.96 0 0111.04 15C9.75 17 9 19.42 9 22l.04 1H7.03L7 22c0-2.74.74-5.31 2-7.5l-.45-.34-3.7 3.69c.1.2.15.42.15.65A1.5 1.5 0 013.5 20 1.5 1.5 0 012 18.5 1.5 1.5 0 013.5 17c.23 0 .45.05.65.15l3.69-3.7C7.31 12.78 7 11.92 7 11a4 4 0 014-4c.92 0 1.78.31 2.45.84l3.7-3.69c-.1-.2-.15-.42-.15-.65A1.5 1.5 0 0118.5 2M11 9a2 2 0 00-2 2 2 2 0 002 2 2 2 0 002-2 2 2 0 00-2-2z"/></svg>',t}(N),Z=function(e){function t(t,n,i){var r=e.call(this,t,n,i)||this;return r.fillColor="transparent",r.strokeColor="transparent",r.strokeWidth=0,r.strokeDasharray="",r.textColor="transparent",r.fontSize="1rem",r.isMoved=!1,r.captionText="Caption",r.PADDING=5,r.captionBoxWidth=0,r.captionBoxHeight=0,r.strokeColor=i.defaultColor,r.strokeWidth=i.defaultStrokeWidth,r.strokeDasharray=i.defaultStrokeDasharray,r.fillColor=i.defaultFillColor,r.textColor=i.defaultStrokeColor,r.fontFamily=i.defaultFontFamily,r.fontSize=i.defaultCaptionFontSize,r.captionText=i.defaultCaptionText,r.setStrokeColor=r.setStrokeColor.bind(r),r.setFillColor=r.setFillColor.bind(r),r.setStrokeWidth=r.setStrokeWidth.bind(r),r.setStrokeDasharray=r.setStrokeDasharray.bind(r),r.createVisual=r.createVisual.bind(r),r.sizeCaption=r.sizeCaption.bind(r),r.setCaptionText=r.setCaptionText.bind(r),r.showTextEditor=r.showTextEditor.bind(r),r.positionTextEditor=r.positionTextEditor.bind(r),r.finishTextEditing=r.finishTextEditing.bind(r),r.setFont=r.setFont.bind(r),r.setTextColor=r.setTextColor.bind(r),r.strokePanel=new A("Line color",a(i.defaultColorSet,["transparent"]),r.strokeColor),r.strokePanel.onColorChanged=r.setStrokeColor,r.fillPanel=new A("Fill color",a(i.defaultColorSet,["transparent"]),r.fillColor,H),r.fillPanel.onColorChanged=r.setFillColor,r.strokeWidthPanel=new E("Line width",i.defaultStrokeWidths,i.defaultStrokeWidth),r.strokeWidthPanel.onWidthChanged=r.setStrokeWidth,r.strokeStylePanel=new T("Line style",i.defaultStrokeDasharrays,i.defaultStrokeDasharray),r.strokeStylePanel.onStyleChanged=r.setStrokeDasharray,r.fontFamilyPanel=new D("Font",i.defaultFontFamilies,i.defaultFontFamily),r.fontFamilyPanel.onFontChanged=r.setFont,r.textColorPanel=new A("Text color",i.defaultColorSet,r.textColor,F),r.textColorPanel.onColorChanged=r.setTextColor,r}return r(t,e),t.prototype.ownsTarget=function(t){return!(!e.prototype.ownsTarget.call(this,t)&&t!==this.visual&&t!==this.frame&&t!==this.captionBg&&t!==this.captionElement)},t.prototype.createVisual=function(){this.visual=l.createGroup(),this.addMarkerVisualToContainer(this.visual),this.captionBg=l.createRect(1,1,[["fill",this.fillColor]]),this.visual.appendChild(this.captionBg),this.captionElement=l.createText([["fill",this.textColor],["font-family",this.fontFamily]]),this.captionElement.style.fontSize=this.fontSize,this.captionElement.style.textAnchor="start",this.captionElement.style.dominantBaseline="text-before-edge",this.captionElement.textContent=this.captionText,this.visual.appendChild(this.captionElement),this.frame=l.createRect(this.width,this.height,[["fill","transparent"],["stroke",this.strokeColor],["stroke-width",this.strokeWidth.toString()],["stroke-dasharray",this.strokeDasharray]]),this.visual.appendChild(this.frame),this.sizeCaption()},t.prototype.setCaptionText=function(e){this.captionText=e,this.captionElement.textContent=this.captionText,this.sizeCaption()},t.prototype.pointerDown=function(t,n){e.prototype.pointerDown.call(this,t,n),this.isMoved=!1,this.pointerDownPoint=t,this.pointerDownTimestamp=Date.now(),"new"===this.state&&(this.createVisual(),this.moveVisual(t),this._state="creating")},t.prototype.manipulate=function(t){e.prototype.manipulate.call(this,t),void 0!==this.pointerDownPoint&&(this.isMoved=Math.abs(t.x-this.pointerDownPoint.x)>5||Math.abs(t.y-this.pointerDownPoint.y)>5)},t.prototype.resize=function(t){e.prototype.resize.call(this,t),this.setSize()},t.prototype.sizeCaption=function(){var e=this.captionElement.getBBox();""!==this.captionText.trim()?(this.captionBoxWidth=e.width+2*this.PADDING,this.captionBoxHeight=e.height+2*this.PADDING):(this.captionBoxWidth=0,this.captionBoxHeight=0),l.setAttributes(this.captionBg,[["width",this.captionBoxWidth.toString()],["height",this.captionBoxHeight.toString()],["clip-path","path('M0,0 H"+this.width+" V"+this.height+" H"+-this.width+" Z')"]]),l.setAttributes(this.captionElement,[["x",this.PADDING.toString()],["y",this.PADDING.toString()],["clip-path","path('M0,0 H"+(this.width-this.PADDING)+" V"+this.height+" H"+(-this.width-this.PADDING)+" Z')"]])},t.prototype.showTextEditor=function(){var e=this;this._state="edit",this.overlayContainer.innerHTML="",this.textEditDiv=document.createElement("div"),this.textEditDiv.style.flexGrow="2",this.textEditDiv.style.alignItems="center",this.textEditDiv.style.justifyContent="center",this.textEditDiv.style.pointerEvents="auto",this.textEditDiv.style.overflow="hidden",this.textEditBox=document.createElement("input"),this.textEditBox.style.position="absolute",this.textEditBox.style.width=this.width+"px",this.captionBoxHeight>0&&(this.textEditBox.style.height=this.captionBoxHeight+"px"),this.textEditBox.style.fontSize=this.fontSize,this.textEditBox.style.fontFamily=this.fontFamily,this.textEditBox.style.backgroundColor=this.fillColor,this.textEditBox.style.color=this.textColor,this.textEditBox.style.borderWidth="0",this.textEditBox.setAttribute("value",this.captionText),this.textEditBox.select(),this.textEditDiv.appendChild(this.textEditBox),this.overlayContainer.appendChild(this.textEditDiv),this.textEditBox.addEventListener("pointerup",(function(e){e.stopPropagation()})),this.textEditBox.addEventListener("keypress",(function(t){"Enter"===t.key&&e.finishTextEditing(e.textEditBox.value)})),this.textEditBox.addEventListener("keyup",(function(e){e.cancelBubble=!0})),this.textEditBox.addEventListener("blur",(function(){e.finishTextEditing(e.textEditBox.value)})),this.textEditDiv.addEventListener("pointerup",(function(){e.finishTextEditing(e.textEditBox.value)})),this.positionTextEditor(),this.textEditBox.focus()},t.prototype.positionTextEditor=function(){"edit"===this.state&&(void 0===this.textEditBox?this.showTextEditor():(this.textEditBox.style.left=this.left+"px",this.textEditBox.style.top=this.top+"px",this.textEditBox.style.transform="rotate("+this.rotationAngle+"deg)",this.textEditBox.style.transformOrigin=this.width/2+"px "+this.height/2+"px"))},t.prototype.finishTextEditing=function(e){this.setCaptionText(e.trim()),this.overlayContainer.innerHTML="",this.stateChanged()},t.prototype.setFont=function(e){this.captionElement&&l.setAttributes(this.captionElement,[["font-family",e]]),this.fontFamily=e,this.textEditBox&&(this.textEditBox.style.fontFamily=this.fontFamily),this.sizeCaption(),this.stateChanged()},t.prototype.setTextColor=function(e){this.captionElement&&l.setAttributes(this.captionElement,[["fill",e]]),this.textColor=e,this.textEditBox&&(this.textEditBox.style.color=this.textColor),this.stateChanged()},t.prototype.setSize=function(){e.prototype.setSize.call(this),l.setAttributes(this.frame,[["width",this.width.toString()],["height",this.height.toString()]]),this.sizeCaption()},t.prototype.pointerUp=function(t){e.prototype.pointerUp.call(this,t),this.setSize(),!this.isMoved&&Date.now()-this.pointerDownTimestamp>500&&this.showTextEditor(),this.pointerDownPoint=void 0},t.prototype.dblClick=function(t,n){e.prototype.dblClick.call(this,t,n),this.showTextEditor()},t.prototype.setStrokeColor=function(e){this.strokeColor=e,this.frame&&l.setAttributes(this.frame,[["stroke",this.strokeColor]]),this.colorChanged(e),this.stateChanged()},t.prototype.setFillColor=function(e){this.fillColor=e,this.captionBg&&l.setAttributes(this.captionBg,[["fill",this.fillColor]]),this.fillColorChanged(e),this.stateChanged()},t.prototype.setStrokeWidth=function(e){this.strokeWidth=e,this.frame&&l.setAttributes(this.frame,[["stroke-width",this.strokeWidth.toString()]]),this.stateChanged()},t.prototype.setStrokeDasharray=function(e){this.strokeDasharray=e,this.frame&&l.setAttributes(this.frame,[["stroke-dasharray",this.strokeDasharray]]),this.stateChanged()},Object.defineProperty(t.prototype,"toolboxPanels",{get:function(){return[this.strokePanel,this.fillPanel,this.strokeWidthPanel,this.strokeStylePanel,this.fontFamilyPanel,this.textColorPanel]},enumerable:!1,configurable:!0}),t.prototype.getState=function(){var t=Object.assign({fillColor:this.fillColor,strokeColor:this.strokeColor,strokeWidth:this.strokeWidth,strokeDasharray:this.strokeDasharray,opacity:1,textColor:this.textColor,fontFamily:this.fontFamily,fontSize:this.fontSize,captionText:this.captionText},e.prototype.getState.call(this));return t.typeName=this.typeName,t},t.prototype.restoreState=function(t){var n=t;this.fillColor=n.fillColor,this.strokeColor=n.strokeColor,this.strokeWidth=n.strokeWidth,this.strokeDasharray=n.strokeDasharray,this.textColor=n.textColor,this.fontFamily=n.fontFamily,this.captionText=n.captionText,this.fontSize=n.fontSize,this.createVisual(),e.prototype.restoreState.call(this,t),this.setSize()},t.prototype.scale=function(t,n){e.prototype.scale.call(this,t,n),this.setSize()},t.typeName="CaptionFrameMarker",t.title="Caption frame marker",t.icon='<svg viewBox="0 0 24 24"><path d="M5 3c-1.11 0-2 .89-2 2v14c0 1.11.89 2 2 2h14c1.11 0 2-.89 2-2V5c0-1.11-.89-2-2-2H5m0 2h14v14H5V5m2 2v2h10V7H7z"/></svg>',t}(C),Y=function(){function e(e,t){void 0===t&&(t=!1),this.cancelable=!1,this._defaultPrevented=!1,this.markerArea=e,this.cancelable=t}return Object.defineProperty(e.prototype,"defaultPrevented",{get:function(){return this._defaultPrevented},enumerable:!1,configurable:!0}),e.prototype.preventDefault=function(){this._defaultPrevented=!0},e}(),J=function(e){function t(t,n,i){var r=e.call(this,t,!1)||this;return r.dataUrl=n,r.state=i,r}return r(t,e),t}(Y),K=function(e){function t(t,n,i){void 0===i&&(i=!1);var r=e.call(this,t,i)||this;return r.marker=n,r}return r(t,e),t}(Y),q=function(){function e(){this.render=[],this.beforeclose=[],this.close=[],this.show=[],this.restorestate=[],this.statechange=[],this.markerselect=[],this.markerdeselect=[],this.markercreating=[],this.markercreate=[],this.markerbeforedelete=[],this.markerdelete=[],this.markerchange=[],this.focus=[],this.blur=[]}return e.prototype.addEventListener=function(e,t){this[e].push(t)},e.prototype.removeEventListener=function(e,t){var n=this[e].indexOf(t);n>-1&&this[e].splice(n,1)},e}(),_=function(){function e(t){this.touchPoints=0,this._availableMarkerTypes=this.DEFAULT_MARKER_TYPES,this.mode="select",this.markers=[],this.isDragging=!1,this.renderEventListeners=[],this.closeEventListeners=[],this.settings=new P,this._isOpen=!1,this.undoRedoManager=new W,this.renderAtNaturalSize=!1,this.renderImageType="image/png",this.renderMarkersOnly=!1,this.zoomSteps=[1,1.5,2,4],this._zoomLevel=1,this._isResizing=!1,this.prevPanPoint={x:0,y:0},this.eventListeners=new q,this._silentRenderMode=!1,this._isFocused=!1,this._instanceNo=e.instanceCounter++,this.styles=new h(this.instanceNo),this.uiStyleSettings=this.styles.settings,this.target=t,this.targetRoot=document.body,this.width=t.clientWidth,this.height=t.clientHeight,this.styles.removeStyleSheet(),this.open=this.open.bind(this),this.setTopLeft=this.setTopLeft.bind(this),this.toolbarButtonClicked=this.toolbarButtonClicked.bind(this),this.createNewMarker=this.createNewMarker.bind(this),this.addNewMarker=this.addNewMarker.bind(this),this.markerCreated=this.markerCreated.bind(this),this.setCurrentMarker=this.setCurrentMarker.bind(this),this.onPointerDown=this.onPointerDown.bind(this),this.onDblClick=this.onDblClick.bind(this),this.onPointerMove=this.onPointerMove.bind(this),this.onPointerUp=this.onPointerUp.bind(this),this.onPointerOut=this.onPointerOut.bind(this),this.onKeyUp=this.onKeyUp.bind(this),this.overrideOverflow=this.overrideOverflow.bind(this),this.restoreOverflow=this.restoreOverflow.bind(this),this.close=this.close.bind(this),this.closeUI=this.closeUI.bind(this),this.addCloseEventListener=this.addCloseEventListener.bind(this),this.removeCloseEventListener=this.removeCloseEventListener.bind(this),this.addRenderEventListener=this.addRenderEventListener.bind(this),this.removeRenderEventListener=this.removeRenderEventListener.bind(this),this.clientToLocalCoordinates=this.clientToLocalCoordinates.bind(this),this.onWindowResize=this.onWindowResize.bind(this),this.deleteSelectedMarker=this.deleteSelectedMarker.bind(this),this.setWindowHeight=this.setWindowHeight.bind(this),this.removeMarker=this.removeMarker.bind(this),this.colorChanged=this.colorChanged.bind(this),this.fillColorChanged=this.fillColorChanged.bind(this),this.onPopupTargetResize=this.onPopupTargetResize.bind(this),this.showNotesEditor=this.showNotesEditor.bind(this),this.hideNotesEditor=this.hideNotesEditor.bind(this),this.stepZoom=this.stepZoom.bind(this),this.focus=this.focus.bind(this),this.blur=this.blur.bind(this),this.markerStateChanged=this.markerStateChanged.bind(this),this.switchToSelectMode=this.switchToSelectMode.bind(this),this.addDefs=this.addDefs.bind(this),this.addDefsToImage=this.addDefsToImage.bind(this)}return Object.defineProperty(e.prototype,"ALL_MARKER_TYPES",{get:function(){return[S,L,O,I,V,X,k,U,G,z,B,Q,Z]},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"DEFAULT_MARKER_TYPES",{get:function(){return[S,L,O,I,X,k,U]},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"BASIC_MARKER_TYPES",{get:function(){return[S,L,O,I,k]},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"availableMarkerTypes",{get:function(){return this._availableMarkerTypes},set:function(e){var t=this;this._availableMarkerTypes.splice(0),e.forEach((function(e){if("string"==typeof e){var n=t.ALL_MARKER_TYPES.find((function(t){return t.typeName===e}));void 0!==n&&t._availableMarkerTypes.push(n)}else t._availableMarkerTypes.push(e)}))},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"currentMarker",{get:function(){return this._currentMarker},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"isOpen",{get:function(){return this._isOpen},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"isUndoPossible",{get:function(){return!(!this.undoRedoManager||!this.undoRedoManager.isUndoPossible)},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"isRedoPossible",{get:function(){return!(!this.undoRedoManager||!this.undoRedoManager.isRedoPossible)},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"zoomLevel",{get:function(){return this._zoomLevel},set:function(e){this._zoomLevel=e,this.editorCanvas&&this.contentDiv&&(this.editorCanvas.style.transform="scale("+this._zoomLevel+")",this.contentDiv.scrollTo({left:(this.editorCanvas.clientWidth*this._zoomLevel-this.contentDiv.clientWidth)/2,top:(this.editorCanvas.clientHeight*this._zoomLevel-this.contentDiv.clientHeight)/2}))},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"instanceNo",{get:function(){return this._instanceNo},enumerable:!1,configurable:!0}),e.prototype.open=function(){this.setupResizeObserver(),this.setEditingTarget(),this.setTopLeft(),this.initMarkerCanvas(),this.initOverlay(),this.attachEvents(),"popup"===this.settings.displayMode&&this.onPopupTargetResize(),u.isLicensed||this.addLogo(),this._isOpen=!0,this._isFocused=!0},e.prototype.show=function(){var e=this;void 0===this.styles.styleSheetRoot&&void 0!==d.styleSheetRoot&&(this.styles.styleSheetRoot=d.styleSheetRoot),this.setWindowHeight(),this.showUI(),this.open(),this.eventListeners.show.forEach((function(t){return t(new Y(e))}))},e.prototype.render=function(){return s(this,void 0,void 0,(function(){var e;return o(this,(function(t){switch(t.label){case 0:return this.setCurrentMarker(),(e=new c).naturalSize=this.renderAtNaturalSize,e.imageType=this.renderImageType,e.imageQuality=this.renderImageQuality,e.markersOnly=this.renderMarkersOnly,e.width=this.renderWidth,e.height=this.renderHeight,[4,e.rasterize(this.target instanceof HTMLImageElement?this.target:null,this.markerImage,this.renderTarget)];case 1:return t.sent(),[4,e.rasterize(this.target instanceof HTMLImageElement?this.target:null,this.markerImage,this.renderTarget)];case 2:return[2,t.sent()]}}))}))},e.prototype.close=function(e){var t=this;if(void 0===e&&(e=!1),this.isOpen){var n=!1;e||this.eventListeners.beforeclose.forEach((function(e){var i=new Y(t,!0);e(i),i.defaultPrevented&&(n=!0)})),n||(this.coverDiv&&this.closeUI(),this.targetObserver&&(this.targetObserver.unobserve(this.target),this.targetObserver.unobserve(this.editorCanvas)),"popup"===this.settings.displayMode&&window.removeEventListener("resize",this.setWindowHeight),this.eventListeners.close.forEach((function(e){return e(new Y(t))})),this.detachEvents(),this._isOpen=!1)}},e.prototype.addMarkersToToolbar=function(){for(var e,t=[],n=0;n<arguments.length;n++)t[n]=arguments[n];(e=this._availableMarkerTypes).push.apply(e,t)},e.prototype.addRenderEventListener=function(e){this.addEventListener("render",(function(t){e(t.dataUrl,t.state)}))},e.prototype.removeRenderEventListener=function(e){},e.prototype.addCloseEventListener=function(e){this.addEventListener("close",(function(){e()}))},e.prototype.removeCloseEventListener=function(e){},e.prototype.setupResizeObserver=function(){var e=this;"inline"===this.settings.displayMode?window.ResizeObserver&&(this.targetObserver=new ResizeObserver((function(){e.resize(e.target.clientWidth,e.target.clientHeight)})),this.targetObserver.observe(this.target)):"popup"===this.settings.displayMode&&(window.ResizeObserver&&(this.targetObserver=new ResizeObserver((function(){return e.onPopupTargetResize()})),this.targetObserver.observe(this.editorCanvas)),window.addEventListener("resize",this.setWindowHeight))},e.prototype.onPopupTargetResize=function(){var e=1*this.target.clientWidth/this.target.clientHeight,t=this.editorCanvas.clientWidth/e>this.editorCanvas.clientHeight?this.editorCanvas.clientHeight*e:this.editorCanvas.clientWidth,n=t<this.editorCanvas.clientWidth?this.editorCanvas.clientHeight:this.editorCanvas.clientWidth/e;this.resize(t,n)},e.prototype.setWindowHeight=function(){this.windowHeight=window.innerHeight},e.prototype.resize=function(e,t){this._isResizing=!0;var n=e/this.imageWidth,i=t/this.imageHeight;this.imageWidth=Math.round(e),this.imageHeight=Math.round(t),this.target instanceof HTMLImageElement&&this.editingTarget instanceof HTMLImageElement&&(this.editingTarget.src=this.target.src),this.editingTarget.width=this.imageWidth,this.editingTarget.height=this.imageHeight,this.editingTarget.style.width=this.imageWidth+"px",this.editingTarget.style.height=this.imageHeight+"px",this.markerImage.setAttribute("width",this.imageWidth.toString()),this.markerImage.setAttribute("height",this.imageHeight.toString()),this.markerImage.setAttribute("viewBox","0 0 "+this.imageWidth.toString()+" "+this.imageHeight.toString()),this.markerImageHolder.style.width=this.imageWidth+"px",this.markerImageHolder.style.height=this.imageHeight+"px",this.overlayContainer.style.width=this.imageWidth+"px",this.overlayContainer.style.height=this.imageHeight+"px","popup"!==this.settings.displayMode?this.coverDiv.style.width=this.imageWidth.toString()+"px":(this.setTopLeft(),this.positionMarkerImage()),void 0!==this.toolbar&&this.toolbar.adjustLayout(),this.positionLogo(),this.scaleMarkers(n,i),this._isResizing=!1},e.prototype.scaleMarkers=function(e,t){var n,i=this;this._currentMarker&&this._currentMarker instanceof I?this._currentMarker.scale(e,t):(n=this._currentMarker,this.setCurrentMarker()),this.markers.forEach((function(n){n!==i._currentMarker&&n.scale(e,t)})),void 0!==n&&this.setCurrentMarker(n)},e.prototype.setEditingTarget=function(){this.imageWidth=Math.round(this.target.clientWidth),this.imageHeight=Math.round(this.target.clientHeight),this.target instanceof HTMLImageElement&&this.editingTarget instanceof HTMLImageElement&&(this.editingTarget.src=this.target.src),this.editingTarget.width=this.imageWidth,this.editingTarget.height=this.imageHeight,this.editingTarget.style.width=this.imageWidth+"px",this.editingTarget.style.height=this.imageHeight+"px"},e.prototype.setTopLeft=function(){var e=this.editingTarget.getBoundingClientRect(),t=this.editorCanvas.getBoundingClientRect();this.left=e.left-t.left,this.top=e.top-t.top},e.prototype.initMarkerCanvas=function(){this.markerImageHolder=document.createElement("div"),this.markerImageHolder.style.setProperty("touch-action","pinch-zoom"),this.markerImage=document.createElementNS("http://www.w3.org/2000/svg","svg"),this.markerImage.setAttribute("xmlns","http://www.w3.org/2000/svg"),this.markerImage.setAttribute("width",this.imageWidth.toString()),this.markerImage.setAttribute("height",this.imageHeight.toString()),this.markerImage.setAttribute("viewBox","0 0 "+this.imageWidth.toString()+" "+this.imageHeight.toString()),this.markerImage.style.pointerEvents="auto",this.markerImageHolder.style.position="absolute",this.markerImageHolder.style.width=this.imageWidth+"px",this.markerImageHolder.style.height=this.imageHeight+"px",this.markerImageHolder.style.transformOrigin="top left",this.positionMarkerImage(),this.markerImageHolder.appendChild(this.markerImage),this.editorCanvas.appendChild(this.markerImageHolder)},e.prototype.addDefs=function(){for(var e,t=[],n=0;n<arguments.length;n++)t[n]=arguments[n];this.defs=l.createDefs(),this.addDefsToImage(),(e=this.defs).append.apply(e,t)},e.prototype.addDefsToImage=function(){this.defs&&this.markerImage.insertBefore(this.defs,this.markerImage.firstChild)},e.prototype.initOverlay=function(){this.overlayContainer=document.createElement("div"),this.overlayContainer.style.position="absolute",this.overlayContainer.style.left="0px",this.overlayContainer.style.top="0px",this.overlayContainer.style.width=this.imageWidth+"px",this.overlayContainer.style.height=this.imageHeight+"px",this.overlayContainer.style.display="flex",this.markerImageHolder.appendChild(this.overlayContainer)},e.prototype.positionMarkerImage=function(){this.markerImageHolder.style.top=this.top/this.zoomLevel+"px",this.markerImageHolder.style.left=this.left/this.zoomLevel+"px"},e.prototype.attachEvents=function(){this.markerImage.addEventListener("pointerdown",this.onPointerDown),this.markerImage.addEventListener("dblclick",this.onDblClick),this.attachWindowEvents()},e.prototype.attachWindowEvents=function(){window.addEventListener("pointermove",this.onPointerMove),window.addEventListener("pointerup",this.onPointerUp),window.addEventListener("pointercancel",this.onPointerOut),window.addEventListener("pointerout",this.onPointerOut),window.addEventListener("pointerleave",this.onPointerUp),window.addEventListener("resize",this.onWindowResize),window.addEventListener("keyup",this.onKeyUp)},e.prototype.detachEvents=function(){this.markerImage.removeEventListener("pointerdown",this.onPointerDown),this.markerImage.removeEventListener("dblclick",this.onDblClick),this.detachWindowEvents()},e.prototype.detachWindowEvents=function(){window.removeEventListener("pointermove",this.onPointerMove),window.removeEventListener("pointerup",this.onPointerUp),window.removeEventListener("pointercancel",this.onPointerOut),window.removeEventListener("pointerout",this.onPointerOut),window.removeEventListener("pointerleave",this.onPointerUp),window.removeEventListener("resize",this.onWindowResize),window.removeEventListener("keyup",this.onKeyUp)},e.prototype.addLogo=function(){this.logoUI=document.createElement("div"),this.logoUI.style.display="inline-block",this.logoUI.style.margin="0px",this.logoUI.style.padding="0px",this.logoUI.style.fill="#333333";var e=document.createElement("a");e.href="https://markerjs.com/",e.target="_blank",e.innerHTML='<svg viewBox="0 0 112 96" xmlns="http://www.w3.org/2000/svg" fill-rule="evenodd" clip-rule="evenodd" stroke-linejoin="round" stroke-miterlimit="1.414"><path fill="#e5f20d" fill-opacity=".647" d="M0 40.386h111.96V95.62H0z"/><path d="M93.61 61.452c0 .987-.328 1.831-.987 2.53-.657.7-1.52 1.048-2.591 1.048-1.481 0-2.222-.74-2.222-2.22 0-16.617-.533-29.347-1.604-38.192-1.068-8.842-2.92-13.265-5.552-13.265-4.443 0-10.94 15.509-19.497 46.52v.124c0 .987-.328 1.831-.987 2.53-.657.7-1.52 1.048-2.592 1.048-1.48 0-2.22-.74-2.22-2.22 0-3.29.165-8.392.493-15.302.33-7.732.494-13.82.494-18.262 0-6.17-.186-10.55-.556-13.142-.37-2.591-1.172-3.887-2.406-3.887-2.796 0-6.333 5.12-10.612 15.363C38.494 34.367 34.01 46.44 29.32 60.34l-1.11 3.209a5.714 5.714 0 01-1.42 2.097c-.617.578-1.295.864-2.036.864-.987 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marker.js",e.style.display="grid",e.style.alignItems="center",e.style.justifyItems="center",e.style.padding="3px",e.style.width="20px",e.style.height="20px",this.logoUI.appendChild(e),this.editorCanvas.appendChild(this.logoUI),this.logoUI.style.position="absolute",this.logoUI.style.pointerEvents="all",this.positionLogo()},e.prototype.positionLogo=function(){this.logoUI&&("right"!==this.uiStyleSettings.logoPosition?this.logoUI.style.left=this.markerImageHolder.offsetLeft+10+"px":this.logoUI.style.left=this.markerImageHolder.offsetLeft+this.markerImageHolder.offsetWidth-this.logoUI.clientWidth-10+"px",this.logoUI.style.top=this.markerImageHolder.offsetTop+this.markerImageHolder.offsetHeight-this.logoUI.clientHeight-10+"px")},e.prototype.overrideOverflow=function(){this.scrollXState=window.scrollX,this.scrollYState=window.scrollY,this.bodyOverflowState=document.body.style.overflow,window.scroll({top:0,left:0}),document.body.style.overflow="hidden"},e.prototype.restoreOverflow=function(){document.body.style.overflow=this.bodyOverflowState,window.scroll({top:this.scrollYState,left:this.scrollXState})},e.prototype.showUI=function(){switch("popup"===this.settings.displayMode&&this.overrideOverflow(),this.coverDiv=document.createElement("div"),this.coverDiv.style.visibility=this._silentRenderMode?"hidden":"visible",this.coverDiv.className=this.styles.classNamePrefixBase+" "+this.styles.classNamePrefix,this.coverDiv.style.fontSize="16px",this.coverDiv.style.userSelect="none",this.settings.displayMode){case"inline":this.coverDiv.style.position="absolute";var e=void 0!==this.settings.uiOffsetTop?this.target.offsetTop+this.settings.uiOffsetTop:this.target.offsetTop>this.styles.settings.toolbarHeight?this.target.offsetTop-this.styles.settings.toolbarHeight:0;this.coverDiv.style.top=e+"px",this.coverDiv.style.left=this.target.offsetLeft.toString()+"px",this.coverDiv.style.width=this.target.offsetWidth.toString()+"px",this.coverDiv.style.zIndex=void 0!==this.uiStyleSettings.zIndex?this.uiStyleSettings.zIndex:"5";break;case"popup":this.coverDiv.style.position="absolute",this.coverDiv.style.top="0px",this.coverDiv.style.left="0px",this.coverDiv.style.width="100vw",this.coverDiv.style.height=window.innerHeight+"px",this.coverDiv.style.backgroundColor="rgba(0, 0, 0, 0.75)",this.coverDiv.style.zIndex=void 0!==this.uiStyleSettings.zIndex?this.uiStyleSettings.zIndex:"1000",this.coverDiv.style.display="flex"}this.targetRoot.appendChild(this.coverDiv),this.uiDiv=document.createElement("div"),this.uiDiv.style.display="flex",this.uiDiv.style.flexDirection="column",this.uiDiv.style.flexGrow="2",this.uiDiv.style.margin="popup"===this.settings.displayMode?this.settings.popupMargin+"px":"0px",this.uiDiv.style.border="0px",this.coverDiv.appendChild(this.uiDiv),this.toolbar=new g(this.uiDiv,this.settings.displayMode,this._availableMarkerTypes,this.uiStyleSettings,this.styles),this.toolbar.addButtonClickListener(this.toolbarButtonClicked),this.toolbar.show(this._silentRenderMode||this.uiStyleSettings.hideToolbar?"hidden":"visible"),this.contentDiv=document.createElement("div"),this.contentDiv.style.display="flex",this.contentDiv.style.flexDirection="row",this.contentDiv.style.flexGrow="2",this.contentDiv.style.flexShrink="1","popup"===this.settings.displayMode&&(this.contentDiv.style.backgroundColor=this.uiStyleSettings.canvasBackgroundColor,this.contentDiv.style.maxHeight=this.windowHeight-2*this.settings.popupMargin-3.5*this.uiStyleSettings.toolbarHeight+"px",this.contentDiv.style.maxWidth="calc(100vw - "+2*this.settings.popupMargin+"px)"),this.contentDiv.style.overflow="auto",this.uiDiv.appendChild(this.contentDiv),this.editorCanvas=document.createElement("div"),this.editorCanvas.style.flexGrow="2",this.editorCanvas.style.flexShrink="1",this.editorCanvas.style.position="relative",this.editorCanvas.style.overflow="hidden",this.editorCanvas.style.display="flex","popup"===this.settings.displayMode&&(this.editorCanvas.style.alignItems="center",this.editorCanvas.style.justifyContent="center"),this.editorCanvas.style.pointerEvents="none",this.editorCanvas.style.transformOrigin="left top",this.editorCanvas.style.transform="scale("+this.zoomLevel+")",this.contentDiv.appendChild(this.editorCanvas),this.editingTarget=this.target instanceof HTMLImageElement?document.createElement("img"):document.createElement("canvas"),void 0===this.settings.uiOffsetTop&&this.target.offsetTop<this.styles.settings.toolbarHeight&&(this.editingTarget.style.marginTop=this.target.offsetTop-this.styles.settings.toolbarHeight+"px"),this.editorCanvas.appendChild(this.editingTarget),this.toolbox=new m(this.uiDiv,this.settings.displayMode,this.uiStyleSettings,this.styles),this.toolbox.show(this._silentRenderMode||this.uiStyleSettings.hideToolbox?"hidden":"visible")},e.prototype.closeUI=function(){"popup"===this.settings.displayMode&&this.restoreOverflow(),this.targetRoot.removeChild(this.coverDiv)},e.prototype.removeMarker=function(e){this.markerImage.removeChild(e.container),this.markers.indexOf(e)>-1&&this.markers.splice(this.markers.indexOf(e),1),e.dispose()},e.prototype.switchToSelectMode=function(){this.mode="select",this.hideNotesEditor(),void 0!==this._currentMarker&&("new"!==this._currentMarker.state?this._currentMarker.select():(this.removeMarker(this._currentMarker),this.setCurrentMarker(),this.markerImage.style.cursor="default"),this.addUndoStep())},e.prototype.toolbarButtonClicked=function(e,t){if("marker"===e&&void 0!==t)this.createNewMarker(t);else if("action"===e)switch(t){case"select":this.switchToSelectMode(),this.switchToSelectMode();break;case"delete":this.deleteSelectedMarker();break;case"clear":this.clear();break;case"undo":this.undo();break;case"redo":this.redo();break;case"zoom":this.stepZoom();break;case"zoom-out":this.zoomLevel=1;break;case"notes":void 0===this.notesArea?(this.switchToSelectMode(),this.zoomLevel=1,this.showNotesEditor()):this.switchToSelectMode();break;case"close":this.close();break;case"render":this.switchToSelectMode(),this.startRenderAndClose()}},e.prototype.deleteSelectedMarker=function(){var e=this;if(void 0!==this._currentMarker){var t=!1;if(this.eventListeners.markerbeforedelete.forEach((function(n){var i=new K(e,e._currentMarker,!0);n(i),i.defaultPrevented&&(t=!0)})),!t){var n=this._currentMarker;this._currentMarker.dispose(),this.markerImage.removeChild(this._currentMarker.container),this.markers.splice(this.markers.indexOf(this._currentMarker),1),this.setCurrentMarker(),this.addUndoStep(),this.eventListeners.markerdelete.forEach((function(t){return t(new K(e,n))}))}}},e.prototype.clear=function(){var e=this,t=!1;if(this.markers.length>0&&(this.eventListeners.markerbeforedelete.forEach((function(n){var i=new K(e,void 0,!0);n(i),i.defaultPrevented&&(t=!0)})),!t)){this.setCurrentMarker();for(var n=function(t){var n=i.markers[t];i.setCurrentMarker(i.markers[t]),i._currentMarker.dispose(),i.markerImage.removeChild(i._currentMarker.container),i.markers.splice(i.markers.indexOf(i._currentMarker),1),i.eventListeners.markerdelete.forEach((function(t){return t(new K(e,n))}))},i=this,r=this.markers.length-1;r>=0;r--)n(r);this.addUndoStep()}},Object.defineProperty(e.prototype,"isNotesAreaOpen",{get:function(){return void 0!==this.notesArea},enumerable:!1,configurable:!0}),e.prototype.showNotesEditor=function(){var e;void 0!==this._currentMarker&&(this.overlayContainer.innerHTML="",this.notesArea=document.createElement("textarea"),this.notesArea.className=this.uiStyleSettings.notesAreaStyleClassName,this.notesArea.style.pointerEvents="auto",this.notesArea.style.alignSelf="stretch",this.notesArea.style.width="100%",this.notesArea.style.margin=this.uiStyleSettings.toolbarHeight/4+"px",this.notesArea.value=null!==(e=this._currentMarker.notes)&&void 0!==e?e:"",this.overlayContainer.appendChild(this.notesArea))},e.prototype.hideNotesEditor=function(){this.isNotesAreaOpen&&(void 0!==this._currentMarker&&(this._currentMarker.notes=""!==this.notesArea.value.trim()?this.notesArea.value:void 0),this.overlayContainer.removeChild(this.notesArea),this.notesArea=void 0)},e.prototype.selectLastMarker=function(){this.markers.length>0?this.setCurrentMarker(this.markers[this.markers.length-1]):this.setCurrentMarker()},e.prototype.addUndoStep=function(){var e=this;if(void 0===this._currentMarker||"edit"!==this._currentMarker.state){var t=this.getState(),n=this.undoRedoManager.getLastUndoStep();if(!n||n.width===t.width&&n.height===t.height){var i=this.undoRedoManager.undoStepCount;this.undoRedoManager.addUndoStep(t),i<this.undoRedoManager.undoStepCount&&this.eventListeners.statechange.forEach((function(t){return t(new Y(e))}))}else this.undoRedoManager.replaceLastUndoStep(t),this.eventListeners.statechange.forEach((function(t){return t(new Y(e))}))}},e.prototype.undo=function(){this.switchToSelectMode(),this.addUndoStep(),this.undoStep()},e.prototype.undoStep=function(){var e=this,t=this.undoRedoManager.undo();void 0!==t&&(this.restoreState(t),this.addDefsToImage(),this.selectLastMarker(),this.eventListeners.statechange.forEach((function(t){return t(new Y(e))})))},e.prototype.redo=function(){this.switchToSelectMode(),this.redoStep()},e.prototype.redoStep=function(){var e=this,t=this.undoRedoManager.redo();void 0!==t&&(this.restoreState(t),this.addDefsToImage(),this.selectLastMarker(),this.eventListeners.statechange.forEach((function(t){return t(new Y(e))})))},e.prototype.stepZoom=function(){var e=this.zoomSteps.indexOf(this.zoomLevel);this.zoomLevel=e<this.zoomSteps.length-1?this.zoomSteps[e+1]:this.zoomSteps[0]},e.prototype.panTo=function(e){this.contentDiv.scrollBy({left:this.prevPanPoint.x-e.x,top:this.prevPanPoint.y-e.y}),this.prevPanPoint=e},e.prototype.startRenderAndClose=function(){return s(this,void 0,void 0,(function(){var e,t,n=this;return o(this,(function(i){switch(i.label){case 0:return[4,this.render()];case 1:return e=i.sent(),t=this.getState(),this.eventListeners.render.forEach((function(i){return i(new J(n,e,t))})),this.close(!0),[2]}}))}))},e.prototype.getState=function(e){!0===e&&this.setCurrentMarker();var t={width:this.imageWidth,height:this.imageHeight,markers:[]};return this.markers.forEach((function(e){return t.markers.push(e.getState())})),t},e.prototype.restoreState=function(e){var t=this;for(this.markers.splice(0);this.markerImage.lastChild;)this.markerImage.removeChild(this.markerImage.lastChild);e.markers.forEach((function(e){var n=t._availableMarkerTypes.find((function(t){return t.typeName===e.typeName}));if(void 0!==n){var i=t.addNewMarker(n);i.restoreState(e),t.markers.push(i)}})),e.width&&e.height&&(e.width!==this.imageWidth||e.height!==this.imageHeight)&&this.scaleMarkers(this.imageWidth/e.width,this.imageHeight/e.height),this.eventListeners.restorestate.forEach((function(e){return e(new Y(t))}))},e.prototype.addNewMarker=function(e){var t=l.createGroup();return this.markerImage.appendChild(t),new e(t,this.overlayContainer,this.settings)},e.prototype.createNewMarker=function(e){var t,n=this;(t="string"==typeof e?this._availableMarkerTypes.find((function(t){return t.typeName===e})):e)&&(this.setCurrentMarker(),this.addUndoStep(),this._currentMarker=this.addNewMarker(t),this._currentMarker.onMarkerCreated=this.markerCreated,this._currentMarker.onColorChanged=this.colorChanged,this._currentMarker.onFillColorChanged=this.fillColorChanged,this._currentMarker.onStateChanged=this.markerStateChanged,this.markerImage.style.cursor="crosshair",this.toolbar.setActiveMarkerButton(t.typeName),this.toolbox.setPanelButtons(this._currentMarker.toolboxPanels),this.eventListeners.markercreating.forEach((function(e){return e(new K(n,n._currentMarker))})))},e.prototype.markerCreated=function(e){var t=this;this.mode="select",this.markerImage.style.cursor="default",this.markers.push(e),this.setCurrentMarker(e),e instanceof L&&this.settings.newFreehandMarkerOnPointerUp?this.createNewMarker(L):this.toolbar.setSelectMode(),this.addUndoStep(),this.eventListeners.markercreate.forEach((function(e){return e(new K(t,t._currentMarker))}))},e.prototype.colorChanged=function(e){this.settings.defaultColorsFollowCurrentColors&&(this.settings.defaultColor=e,this.settings.defaultStrokeColor=e)},e.prototype.fillColorChanged=function(e){this.settings.defaultColorsFollowCurrentColors&&(this.settings.defaultFillColor=e)},e.prototype.markerStateChanged=function(e){var t=this;this.eventListeners.markerchange.forEach((function(n){return n(new K(t,e))}))},e.prototype.setCurrentMarker=function(e){var t=this;this._currentMarker!==e&&void 0!==this._currentMarker&&(this._currentMarker.deselect(),this.toolbar.setCurrentMarker(),this.toolbox.setPanelButtons([]),this._isResizing||this.eventListeners.markerdeselect.forEach((function(e){return e(new K(t,t._currentMarker))}))),this._currentMarker=e,void 0===this._currentMarker||this._currentMarker.isSelected||("new"!==this._currentMarker.state&&this._currentMarker.select(),this.toolbar.setCurrentMarker(this._currentMarker),this.toolbox.setPanelButtons(this._currentMarker.toolboxPanels),this._isResizing||this.eventListeners.markerselect.forEach((function(e){return e(new K(t,t._currentMarker))})))},e.prototype.onPointerDown=function(e){if(this._isFocused||this.focus(),this.touchPoints++,1===this.touchPoints||"touch"!==e.pointerType)if(void 0===this._currentMarker||"new"!==this._currentMarker.state&&"creating"!==this._currentMarker.state){if("select"===this.mode){var t=this.markers.find((function(t){return t.ownsTarget(e.target)}));void 0!==t?(this.setCurrentMarker(t),this.isDragging=!0,this._currentMarker.pointerDown(this.clientToLocalCoordinates(e.clientX,e.clientY),e.target)):(this.setCurrentMarker(),this.isDragging=!0,this.prevPanPoint={x:e.clientX,y:e.clientY})}}else this.isDragging=!0,this._currentMarker.pointerDown(this.clientToLocalCoordinates(e.clientX,e.clientY))},e.prototype.onDblClick=function(e){if(this._isFocused||this.focus(),"select"===this.mode){var t=this.markers.find((function(t){return t.ownsTarget(e.target)}));void 0!==t&&t!==this._currentMarker&&this.setCurrentMarker(t),void 0!==this._currentMarker?this._currentMarker.dblClick(this.clientToLocalCoordinates(e.clientX,e.clientY),e.target):this.setCurrentMarker()}},e.prototype.onPointerMove=function(e){1!==this.touchPoints&&"touch"===e.pointerType||(void 0!==this._currentMarker||this.isDragging)&&(void 0!==this._currentMarker&&"edit"===this._currentMarker.state||e.preventDefault(),void 0!==this._currentMarker?this._currentMarker.manipulate(this.clientToLocalCoordinates(e.clientX,e.clientY)):this.zoomLevel>1&&this.panTo({x:e.clientX,y:e.clientY}))},e.prototype.onPointerUp=function(e){this.touchPoints>0&&this.touchPoints--,0===this.touchPoints&&this.isDragging&&void 0!==this._currentMarker&&this._currentMarker.pointerUp(this.clientToLocalCoordinates(e.clientX,e.clientY)),this.isDragging=!1,this.addUndoStep()},e.prototype.onPointerOut=function(){this.touchPoints>0&&this.touchPoints--},e.prototype.onKeyUp=function(e){void 0===this._currentMarker||void 0!==this.notesArea||"Delete"!==e.key&&"Backspace"!==e.key||this.deleteSelectedMarker()},e.prototype.clientToLocalCoordinates=function(e,t){var n=this.markerImage.getBoundingClientRect();return{x:(e-n.left)/this.zoomLevel,y:(t-n.top)/this.zoomLevel}},e.prototype.onWindowResize=function(){this.positionUI()},e.prototype.positionUI=function(){switch(this.setTopLeft(),this.settings.displayMode){case"inline":var e=this.target.getClientRects().item(0).y>this.styles.settings.toolbarHeight?this.target.offsetTop-this.styles.settings.toolbarHeight:0;this.coverDiv.style.top=e+"px",this.coverDiv.style.left=this.target.offsetLeft.toString()+"px";break;case"popup":this.coverDiv.style.top="0px",this.coverDiv.style.left="0px",this.coverDiv.style.width="100vw",this.coverDiv.style.height=this.windowHeight+"px",this.contentDiv.style.maxHeight=this.windowHeight-2*this.settings.popupMargin-3.5*this.styles.settings.toolbarHeight+"px"}this.positionMarkerImage(),this.positionLogo()},e.prototype.addLicenseKey=function(e){u.addKey(e)},e.prototype.addEventListener=function(e,t){this.eventListeners.addEventListener(e,t)},e.prototype.removeEventListener=function(e,t){this.eventListeners.removeEventListener(e,t)},e.prototype.renderState=function(e){this._silentRenderMode=!0,this.settings.displayMode="inline",this.isOpen||this.show(),this.restoreState(e),this.startRenderAndClose(),this._silentRenderMode=!1},Object.defineProperty(e.prototype,"isFocused",{get:function(){return this._isFocused},enumerable:!1,configurable:!0}),e.prototype.focus=function(){var e=this;this._isFocused||(this.attachWindowEvents(),this._isFocused=!0,void 0!==this._previousCurrentMarker&&this.setCurrentMarker(this._previousCurrentMarker),this.eventListeners.focus.forEach((function(t){return t(new Y(e))})))},e.prototype.blur=function(){var e=this;this._isFocused&&(this.detachWindowEvents(),this._isFocused=!1,this._previousCurrentMarker=this._currentMarker,this.setCurrentMarker(),this.eventListeners.blur.forEach((function(t){return t(new Y(e))})))},e.instanceCounter=0,e}()},91998:function(e,t,n){e.exports=function(e,t){if(!e)throw new Error("Graph structure cannot be undefined");var s=(t&&t.createSimulator||n(72879))(t);if(Array.isArray(t))throw new Error("Physics settings is expected to be an object");var o=e.version>19?function(t){var n=e.getLinks(t);return n?1+n.size/3:1}:function(t){var n=e.getLinks(t);return n?1+n.length/3:1};t&&"function"==typeof t.nodeMass&&(o=t.nodeMass);var a=new Map,l={},u=0,c=s.settings.springTransform||r;u=0,e.forEachNode((function(e){m(e.id),u+=1})),e.forEachLink(A),e.on("changed",g);var d=!1,h={step:function(){if(0===u)return f(!0),!0;var e=s.step();h.lastMove=e,h.fire("step");var t=e/u<=.01;return f(t),t},getNodePosition:function(e){return b(e).pos},setNodePosition:function(e){var t=b(e);t.setPosition.apply(t,Array.prototype.slice.call(arguments,1))},getLinkPosition:function(e){var t=l[e];if(t)return{from:t.from.pos,to:t.to.pos}},getGraphRect:function(){return s.getBBox()},forEachBody:p,pinNode:function(e,t){b(e.id).isPinned=!!t},isNodePinned:function(e){return b(e.id).isPinned},dispose:function(){e.off("changed",g),h.fire("disposed")},getBody:function(e){return a.get(e)},getSpring:function(t,n){var i;if(void 0===n)i="object"!=typeof t?t:t.id;else{var r=e.hasLink(t,n);if(!r)return;i=r.id}return l[i]},getForceVectorLength:function(){var e=0,t=0;return p((function(n){e+=Math.abs(n.force.x),t+=Math.abs(n.force.y)})),Math.sqrt(e*e+t*t)},simulator:s,graph:e,lastMove:0};return i(h),h;function f(e){var t;d!==e&&(d=e,t=e,h.fire("stable",t))}function p(e){a.forEach(e)}function g(t){for(var n=0;n<t.length;++n){var i=t[n];"add"===i.changeType?(i.node&&m(i.node.id),i.link&&A(i.link)):"remove"===i.changeType&&(i.node&&v(i.node),i.link&&x(i.link))}u=e.getNodesCount()}function m(t){var n=a.get(t);if(!n){var i=e.getNode(t);if(!i)throw new Error("initBody() was called with unknown node id");var r=i.position;if(!r){var o=function(e){var t=[];if(!e.links)return t;for(var n=Math.min(e.links.length,2),i=0;i<n;++i){var r=e.links[i],s=r.fromId!==e.id?a.get(r.fromId):a.get(r.toId);s&&s.pos&&t.push(s)}return t}(i);r=s.getBestNewBodyPosition(o)}(n=s.addBodyAt(r)).id=t,a.set(t,n),y(t),function(e){return e&&(e.isPinned||e.data&&e.data.isPinned)}(i)&&(n.isPinned=!0)}}function v(e){var t=e.id,n=a.get(t);n&&(a.delete(t),s.removeBody(n))}function A(e){y(e.fromId),y(e.toId);var t=a.get(e.fromId),n=a.get(e.toId),i=s.addSpring(t,n,e.length);c(e,i),l[e.id]=i}function x(t){var n=l[t.id];if(n){var i=e.getNode(t.fromId),r=e.getNode(t.toId);i&&y(i.id),r&&y(r.id),delete l[t.id],s.removeSpring(n)}}function y(e){var t=a.get(e);if(t.mass=o(e),Number.isNaN(t.mass))throw new Error("Node mass should be a number")}function b(e){var t=a.get(e);return t||(m(e),t=a.get(e)),t}},e.exports.simulator=n(72879);var i=n(82396);function r(){}},98786:function(e,t,n){const i=n(59321);e.exports=function(e){return function(t,n){let r=n&&n.indent||0,s=n&&void 0!==n.join?n.join:"\n",o=Array(r+1).join(" "),a=[];for(let n=0;n<e;++n){let e=i(n),r=0===n?"":o;a.push(r+t.replace(/{var}/g,e))}return a.join(s)}}},41085:function(e,t,n){e.exports=function(e){let t=r(e);return new Function("bodies","settings","random",t)},e.exports.generateFunctionBody=r;const i=n(98786);function r(e){let t=i(e);return`\n  var boundingBox = {\n    ${t("min_{var}: 0, max_{var}: 0,",{indent:4})}\n  };\n\n  return {\n    box: boundingBox,\n\n    update: updateBoundingBox,\n\n    reset: resetBoundingBox,\n\n    getBestNewPosition: function (neighbors) {\n      var ${t("base_{var} = 0",{join:", "})};\n\n      if (neighbors.length) {\n        for (var i = 0; i < neighbors.length; ++i) {\n          let neighborPos = neighbors[i].pos;\n          ${t("base_{var} += neighborPos.{var};",{indent:10})}\n        }\n\n        ${t("base_{var} /= neighbors.length;",{indent:8})}\n      } else {\n        ${t("base_{var} = (boundingBox.min_{var} + boundingBox.max_{var}) / 2;",{indent:8})}\n      }\n\n      var springLength = settings.springLength;\n      return {\n        ${t("{var}: base_{var} + (random.nextDouble() - 0.5) * springLength,",{indent:8})}\n      };\n    }\n  };\n\n  function updateBoundingBox() {\n    var i = bodies.length;\n    if (i === 0) return; // No bodies - no borders.\n\n    ${t("var max_{var} = -Infinity;",{indent:4})}\n    ${t("var min_{var} = Infinity;",{indent:4})}\n\n    while(i--) {\n      // this is O(n), it could be done faster with quadtree, if we check the root node bounds\n      var bodyPos = bodies[i].pos;\n      ${t("if (bodyPos.{var} < min_{var}) min_{var} = bodyPos.{var};",{indent:6})}\n      ${t("if (bodyPos.{var} > max_{var}) max_{var} = bodyPos.{var};",{indent:6})}\n    }\n\n    ${t("boundingBox.min_{var} = min_{var};",{indent:4})}\n    ${t("boundingBox.max_{var} = max_{var};",{indent:4})}\n  }\n\n  function resetBoundingBox() {\n    ${t("boundingBox.min_{var} = boundingBox.max_{var} = 0;",{indent:4})}\n  }\n`}},53623:function(e,t,n){const i=n(98786);function r(e,t){return`\n${o(e,t)}\n${s(e)}\nreturn {Body: Body, Vector: Vector};\n`}function s(e){let t=i(e),n=t("{var}",{join:", "});return`\nfunction Body(${n}) {\n  this.isPinned = false;\n  this.pos = new Vector(${n});\n  this.force = new Vector();\n  this.velocity = new Vector();\n  this.mass = 1;\n\n  this.springCount = 0;\n  this.springLength = 0;\n}\n\nBody.prototype.reset = function() {\n  this.force.reset();\n  this.springCount = 0;\n  this.springLength = 0;\n}\n\nBody.prototype.setPosition = function (${n}) {\n  ${t("this.pos.{var} = {var} || 0;",{indent:2})}\n};`}function o(e,t){let n=i(e),r="";return t&&(r=`${n("\n   var v{var};\nObject.defineProperty(this, '{var}', {\n  set: function(v) { \n    if (!Number.isFinite(v)) throw new Error('Cannot set non-numbers to {var}');\n    v{var} = v; \n  },\n  get: function() { return v{var}; }\n});")}`),`function Vector(${n("{var}",{join:", "})}) {\n  ${r}\n    if (typeof arguments[0] === 'object') {\n      // could be another vector\n      let v = arguments[0];\n      ${n('if (!Number.isFinite(v.{var})) throw new Error("Expected value is not a finite number at Vector constructor ({var})");',{indent:4})}\n      ${n("this.{var} = v.{var};",{indent:4})}\n    } else {\n      ${n('this.{var} = typeof {var} === "number" ? {var} : 0;',{indent:4})}\n    }\n  }\n  \n  Vector.prototype.reset = function () {\n    ${n("this.{var} = ",{join:""})}0;\n  };`}e.exports=function(e,t){let n=r(e,t),{Body:i}=new Function(n)();return i},e.exports.generateCreateBodyFunctionBody=r,e.exports.getVectorCode=o,e.exports.getBodyCode=s},48812:function(e,t,n){const i=n(98786);function r(e){return`\n  if (!Number.isFinite(options.dragCoefficient)) throw new Error('dragCoefficient is not a finite number');\n\n  return {\n    update: function(body) {\n      ${i(e)("body.force.{var} -= options.dragCoefficient * body.velocity.{var};",{indent:6})}\n    }\n  };\n`}e.exports=function(e){let t=r(e);return new Function("options",t)},e.exports.generateCreateDragForceFunctionBody=r},7584:function(e,t,n){const i=n(98786);function r(e){let t=i(e);return`\n  if (!Number.isFinite(options.springCoefficient)) throw new Error('Spring coefficient is not a number');\n  if (!Number.isFinite(options.springLength)) throw new Error('Spring length is not a number');\n\n  return {\n    /**\n     * Updates forces acting on a spring\n     */\n    update: function (spring) {\n      var body1 = spring.from;\n      var body2 = spring.to;\n      var length = spring.length < 0 ? options.springLength : spring.length;\n      ${t("var d{var} = body2.pos.{var} - body1.pos.{var};",{indent:6})}\n      var r = Math.sqrt(${t("d{var} * d{var}",{join:" + "})});\n\n      if (r === 0) {\n        ${t("d{var} = (random.nextDouble() - 0.5) / 50;",{indent:8})}\n        r = Math.sqrt(${t("d{var} * d{var}",{join:" + "})});\n      }\n\n      var d = r - length;\n      var coefficient = ((spring.coefficient > 0) ? spring.coefficient : options.springCoefficient) * d / r;\n\n      ${t("body1.force.{var} += coefficient * d{var}",{indent:6})};\n      body1.springCount += 1;\n      body1.springLength += r;\n\n      ${t("body2.force.{var} -= coefficient * d{var}",{indent:6})};\n      body2.springCount += 1;\n      body2.springLength += r;\n    }\n  };\n`}e.exports=function(e){let t=r(e);return new Function("options","random",t)},e.exports.generateCreateSpringForceFunctionBody=r},26302:function(e,t,n){const i=n(98786);function r(e){let t=i(e);return`\n  var length = bodies.length;\n  if (length === 0) return 0;\n\n  ${t("var d{var} = 0, t{var} = 0;",{indent:2})}\n\n  for (var i = 0; i < length; ++i) {\n    var body = bodies[i];\n    if (body.isPinned) continue;\n\n    if (adaptiveTimeStepWeight && body.springCount) {\n      timeStep = (adaptiveTimeStepWeight * body.springLength/body.springCount);\n    }\n\n    var coeff = timeStep / body.mass;\n\n    ${t("body.velocity.{var} += coeff * body.force.{var};",{indent:4})}\n    ${t("var v{var} = body.velocity.{var};",{indent:4})}\n    var v = Math.sqrt(${t("v{var} * v{var}",{join:" + "})});\n\n    if (v > 1) {\n      // We normalize it so that we move within timeStep range. \n      // for the case when v <= 1 - we let velocity to fade out.\n      ${t("body.velocity.{var} = v{var} / v;",{indent:6})}\n    }\n\n    ${t("d{var} = timeStep * body.velocity.{var};",{indent:4})}\n\n    ${t("body.pos.{var} += d{var};",{indent:4})}\n\n    ${t("t{var} += Math.abs(d{var});",{indent:4})}\n  }\n\n  return (${t("t{var} * t{var}",{join:" + "})})/length;\n`}e.exports=function(e){let t=r(e);return new Function("bodies","timeStep","adaptiveTimeStepWeight",t)},e.exports.generateIntegratorFunctionBody=r},24454:function(e,t,n){const i=n(98786),r=n(59321);function s(e){let t=i(e),n=Math.pow(2,e);return`\n${c()}\n${u(e)}\n${o(e)}\n${l(e)}\n${a(e)}\n\nfunction createQuadTree(options, random) {\n  options = options || {};\n  options.gravity = typeof options.gravity === 'number' ? options.gravity : -1;\n  options.theta = typeof options.theta === 'number' ? options.theta : 0.8;\n\n  var gravity = options.gravity;\n  var updateQueue = [];\n  var insertStack = new InsertStack();\n  var theta = options.theta;\n\n  var nodesCache = [];\n  var currentInCache = 0;\n  var root = newNode();\n\n  return {\n    insertBodies: insertBodies,\n\n    /**\n     * Gets root node if it is present\n     */\n    getRoot: function() {\n      return root;\n    },\n\n    updateBodyForce: update,\n\n    options: function(newOptions) {\n      if (newOptions) {\n        if (typeof newOptions.gravity === 'number') {\n          gravity = newOptions.gravity;\n        }\n        if (typeof newOptions.theta === 'number') {\n          theta = newOptions.theta;\n        }\n\n        return this;\n      }\n\n      return {\n        gravity: gravity,\n        theta: theta\n      };\n    }\n  };\n\n  function newNode() {\n    // To avoid pressure on GC we reuse nodes.\n    var node = nodesCache[currentInCache];\n    if (node) {\n${function(e){let t=[];for(let i=0;i<n;++i)t.push(`${e}quad${i} = null;`);return t.join("\n")}("      node.")}\n      node.body = null;\n      node.mass = ${t("node.mass_{var} = ",{join:""})}0;\n      ${t("node.min_{var} = node.max_{var} = ",{join:""})}0;\n    } else {\n      node = new QuadNode();\n      nodesCache[currentInCache] = node;\n    }\n\n    ++currentInCache;\n    return node;\n  }\n\n  function update(sourceBody) {\n    var queue = updateQueue;\n    var v;\n    ${t("var d{var};",{indent:4})}\n    var r; \n    ${t("var f{var} = 0;",{indent:4})}\n    var queueLength = 1;\n    var shiftIdx = 0;\n    var pushIdx = 1;\n\n    queue[0] = root;\n\n    while (queueLength) {\n      var node = queue[shiftIdx];\n      var body = node.body;\n\n      queueLength -= 1;\n      shiftIdx += 1;\n      var differentBody = (body !== sourceBody);\n      if (body && differentBody) {\n        // If the current node is a leaf node (and it is not source body),\n        // calculate the force exerted by the current node on body, and add this\n        // amount to body's net force.\n        ${t("d{var} = body.pos.{var} - sourceBody.pos.{var};",{indent:8})}\n        r = Math.sqrt(${t("d{var} * d{var}",{join:" + "})});\n\n        if (r === 0) {\n          // Poor man's protection against zero distance.\n          ${t("d{var} = (random.nextDouble() - 0.5) / 50;",{indent:10})}\n          r = Math.sqrt(${t("d{var} * d{var}",{join:" + "})});\n        }\n\n        // This is standard gravitation force calculation but we divide\n        // by r^3 to save two operations when normalizing force vector.\n        v = gravity * body.mass * sourceBody.mass / (r * r * r);\n        ${t("f{var} += v * d{var};",{indent:8})}\n      } else if (differentBody) {\n        // Otherwise, calculate the ratio s / r,  where s is the width of the region\n        // represented by the internal node, and r is the distance between the body\n        // and the node's center-of-mass\n        ${t("d{var} = node.mass_{var} / node.mass - sourceBody.pos.{var};",{indent:8})}\n        r = Math.sqrt(${t("d{var} * d{var}",{join:" + "})});\n\n        if (r === 0) {\n          // Sorry about code duplication. I don't want to create many functions\n          // right away. Just want to see performance first.\n          ${t("d{var} = (random.nextDouble() - 0.5) / 50;",{indent:10})}\n          r = Math.sqrt(${t("d{var} * d{var}",{join:" + "})});\n        }\n        // If s / r < θ, treat this internal node as a single body, and calculate the\n        // force it exerts on sourceBody, and add this amount to sourceBody's net force.\n        if ((node.max_${r(0)} - node.min_${r(0)}) / r < theta) {\n          // in the if statement above we consider node's width only\n          // because the region was made into square during tree creation.\n          // Thus there is no difference between using width or height.\n          v = gravity * node.mass * sourceBody.mass / (r * r * r);\n          ${t("f{var} += v * d{var};",{indent:10})}\n        } else {\n          // Otherwise, run the procedure recursively on each of the current node's children.\n\n          // I intentionally unfolded this loop, to save several CPU cycles.\n${function(){let e=Array(11).join(" "),t=[];for(let i=0;i<n;++i)t.push(e+`if (node.quad${i}) {`),t.push(e+`  queue[pushIdx] = node.quad${i};`),t.push(e+"  queueLength += 1;"),t.push(e+"  pushIdx += 1;"),t.push(e+"}");return t.join("\n")}()}\n        }\n      }\n    }\n\n    ${t("sourceBody.force.{var} += f{var};",{indent:4})}\n  }\n\n  function insertBodies(bodies) {\n    ${t("var {var}min = Number.MAX_VALUE;",{indent:4})}\n    ${t("var {var}max = Number.MIN_VALUE;",{indent:4})}\n    var i = bodies.length;\n\n    // To reduce quad tree depth we are looking for exact bounding box of all particles.\n    while (i--) {\n      var pos = bodies[i].pos;\n      ${t("if (pos.{var} < {var}min) {var}min = pos.{var};",{indent:6})}\n      ${t("if (pos.{var} > {var}max) {var}max = pos.{var};",{indent:6})}\n    }\n\n    // Makes the bounds square.\n    var maxSideLength = -Infinity;\n    ${t("if ({var}max - {var}min > maxSideLength) maxSideLength = {var}max - {var}min ;",{indent:4})}\n\n    currentInCache = 0;\n    root = newNode();\n    ${t("root.min_{var} = {var}min;",{indent:4})}\n    ${t("root.max_{var} = {var}min + maxSideLength;",{indent:4})}\n\n    i = bodies.length - 1;\n    if (i >= 0) {\n      root.body = bodies[i];\n    }\n    while (i--) {\n      insert(bodies[i], root);\n    }\n  }\n\n  function insert(newBody) {\n    insertStack.reset();\n    insertStack.push(root, newBody);\n\n    while (!insertStack.isEmpty()) {\n      var stackItem = insertStack.pop();\n      var node = stackItem.node;\n      var body = stackItem.body;\n\n      if (!node.body) {\n        // This is internal node. Update the total mass of the node and center-of-mass.\n        ${t("var {var} = body.pos.{var};",{indent:8})}\n        node.mass += body.mass;\n        ${t("node.mass_{var} += body.mass * {var};",{indent:8})}\n\n        // Recursively insert the body in the appropriate quadrant.\n        // But first find the appropriate quadrant.\n        var quadIdx = 0; // Assume we are in the 0's quad.\n        ${t("var min_{var} = node.min_{var};",{indent:8})}\n        ${t("var max_{var} = (min_{var} + node.max_{var}) / 2;",{indent:8})}\n\n${function(t){let n=[],i=Array(t+1).join(" ");for(let t=0;t<e;++t)n.push(i+`if (${r(t)} > max_${r(t)}) {`),n.push(i+`  quadIdx = quadIdx + ${Math.pow(2,t)};`),n.push(i+`  min_${r(t)} = max_${r(t)};`),n.push(i+`  max_${r(t)} = node.max_${r(t)};`),n.push(i+"}");return n.join("\n")}(8)}\n\n        var child = getChild(node, quadIdx);\n\n        if (!child) {\n          // The node is internal but this quadrant is not taken. Add\n          // subnode to it.\n          child = newNode();\n          ${t("child.min_{var} = min_{var};",{indent:10})}\n          ${t("child.max_{var} = max_{var};",{indent:10})}\n          child.body = body;\n\n          setChild(node, quadIdx, child);\n        } else {\n          // continue searching in this quadrant.\n          insertStack.push(child, body);\n        }\n      } else {\n        // We are trying to add to the leaf node.\n        // We have to convert current leaf into internal node\n        // and continue adding two nodes.\n        var oldBody = node.body;\n        node.body = null; // internal nodes do not cary bodies\n\n        if (isSamePosition(oldBody.pos, body.pos)) {\n          // Prevent infinite subdivision by bumping one node\n          // anywhere in this quadrant\n          var retriesCount = 3;\n          do {\n            var offset = random.nextDouble();\n            ${t("var d{var} = (node.max_{var} - node.min_{var}) * offset;",{indent:12})}\n\n            ${t("oldBody.pos.{var} = node.min_{var} + d{var};",{indent:12})}\n            retriesCount -= 1;\n            // Make sure we don't bump it out of the box. If we do, next iteration should fix it\n          } while (retriesCount > 0 && isSamePosition(oldBody.pos, body.pos));\n\n          if (retriesCount === 0 && isSamePosition(oldBody.pos, body.pos)) {\n            // This is very bad, we ran out of precision.\n            // if we do not return from the method we'll get into\n            // infinite loop here. So we sacrifice correctness of layout, and keep the app running\n            // Next layout iteration should get larger bounding box in the first step and fix this\n            return;\n          }\n        }\n        // Next iteration should subdivide node further.\n        insertStack.push(node, oldBody);\n        insertStack.push(node, body);\n      }\n    }\n  }\n}\nreturn createQuadTree;\n\n`}function o(e){let t=i(e);return`\n  function isSamePosition(point1, point2) {\n    ${t("var d{var} = Math.abs(point1.{var} - point2.{var});",{indent:2})}\n  \n    return ${t("d{var} < 1e-8",{join:" && "})};\n  }  \n`}function a(e){var t=Math.pow(2,e);return`\nfunction setChild(node, idx, child) {\n  ${function(){let e=[];for(let n=0;n<t;++n){let t=0===n?"  ":"  else ";e.push(`${t}if (idx === ${n}) node.quad${n} = child;`)}return e.join("\n")}()}\n}`}function l(e){return`function getChild(node, idx) {\n${function(){let t=[],n=Math.pow(2,e);for(let e=0;e<n;++e)t.push(`  if (idx === ${e}) return node.quad${e};`);return t.join("\n")}()}\n  return null;\n}`}function u(e){let t=i(e),n=Math.pow(2,e);return`\nfunction QuadNode() {\n  // body stored inside this node. In quad tree only leaf nodes (by construction)\n  // contain bodies:\n  this.body = null;\n\n  // Child nodes are stored in quads. Each quad is presented by number:\n  // 0 | 1\n  // -----\n  // 2 | 3\n${function(e){let t=[];for(let i=0;i<n;++i)t.push(`${e}quad${i} = null;`);return t.join("\n")}("  this.")}\n\n  // Total mass of current node\n  this.mass = 0;\n\n  // Center of mass coordinates\n  ${t("this.mass_{var} = 0;",{indent:2})}\n\n  // bounding box coordinates\n  ${t("this.min_{var} = 0;",{indent:2})}\n  ${t("this.max_{var} = 0;",{indent:2})}\n}\n`}function c(){return"\n/**\n * Our implementation of QuadTree is non-recursive to avoid GC hit\n * This data structure represent stack of elements\n * which we are trying to insert into quad tree.\n */\nfunction InsertStack () {\n    this.stack = [];\n    this.popIdx = 0;\n}\n\nInsertStack.prototype = {\n    isEmpty: function() {\n        return this.popIdx === 0;\n    },\n    push: function (node, body) {\n        var item = this.stack[this.popIdx];\n        if (!item) {\n            // we are trying to avoid memory pressure: create new element\n            // only when absolutely necessary\n            this.stack[this.popIdx] = new InsertStackElement(node, body);\n        } else {\n            item.node = node;\n            item.body = body;\n        }\n        ++this.popIdx;\n    },\n    pop: function () {\n        if (this.popIdx > 0) {\n            return this.stack[--this.popIdx];\n        }\n    },\n    reset: function () {\n        this.popIdx = 0;\n    }\n};\n\nfunction InsertStackElement(node, body) {\n    this.node = node; // QuadTree node\n    this.body = body; // physical body which needs to be inserted to node\n}\n"}e.exports=function(e){let t=s(e);return new Function(t)()},e.exports.generateQuadTreeFunctionBody=s,e.exports.getInsertStackCode=c,e.exports.getQuadNodeCode=u,e.exports.isSamePosition=o,e.exports.getChildBodyCode=l,e.exports.setChildBodyCode=a},59321:function(e){e.exports=function(e){return 0===e?"x":1===e?"y":2===e?"z":"c"+(e+1)}},72879:function(e,t,n){e.exports=function(e){var 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"},11051:function(e){"use 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"},30711:function(e){"use strict";e.exports="data:image/png;base64,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"},64690:function(e){"use strict";e.exports="data:image/png;base64,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"},40517:function(e){"use 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"},89006:function(e){"use strict";e.exports="data:image/png;base64,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"},57581:function(e){"use strict";e.exports="data:image/png;base64,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"},4212:function(e){"use strict";e.exports="data:image/png;base64,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"},50356:function(e){"use strict";e.exports="data:image/png;base64,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"},40362:function(e){"use 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"},74732:function(e){"use strict";e.exports="data:image/png;base64,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"},87017:function(e){"use strict";e.exports="data:image/png;base64,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"},49747:function(e){"use strict";e.exports="data:image/png;base64,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"},7875:function(e){"use strict";e.exports="data:image/png;base64,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"},14813:function(e){"use strict";e.exports="data:image/png;base64,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"},79989:function(e){"use strict";e.exports="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAANIAAABoCAYAAACEyK5RAAAAAXNSR0IArs4c6QAAGQ1JREFUeF7tXflvJMd1ftXXDDkXl1ySWpJ7aS8dq12vZO1mdWtl+YAly7Fh+LZgC7CDOEgQ/xYYyQ8G8h8EQQDnsJEEcATbsWVZkg/JsmRH1mHtai+LKy334HJJajg8ZsiZ6emuquDVsKlms2emm2fPsAgM5uBMd/Wr+vB976tX1QTkn4yAjMCKI0BWfAR5ABmB5o+AHw78PuOeS114L4HU/INAXsHyI+CMfzcO6mHCDSTntXiWQFp+J8hfNm8EvADC936fOVfoBs0iAAEAvucSSM07GGTLw0WgFlAcEHmfYWBgABjrJdev/5E5gKnxLBkpXF/IbzdhBGqxjxs4CgDgQ3zW0bFLpYkeFa+1UJywYWqIAgCCyQHUEmBJRmrCkSGbHCgCjQDkgEc8d3R0KIYxEFMTPfESAJiVOUrMPFXUCp0dn7AAZmwXmBBYKOkWACWBFKhP5JeaJAK1zAOHfRzWcUCkplL9mrr1QFIzknHOqFKxiwwqFlcURk17yiamRdVKoTI7O24BAALIeTgMJcAkgdQkI0Q2s24EGrEP/t/NQGqi+854W9eNaRKLJcCqgGWVOcAckFKZWVaJAaHMsks2scsVpTJrqqppFQoFZCV8uMEkzQY5OJs+Ao0AtES+wZbbM4mOXR021eIAFWJZJQCrCLZtciA2t0tlrhPK7PJMxS7myqaZrcyDBwGErOQG00LeJBmp6cfSpryAegBaKt/69uvp7j/rhFhnF+NcB7sM+LDtEnDLIjaUAajJiU25WRwt24WRcqUy5zCPAxwEkRtU7pxJSrtNOQyb86Lr2dde8Agm2rr97oTRe1uvFk922SaqMRvAKhHbLqNy45ZdIqjSaGWaVgrXi3bhimlZlmMgOPINAeR9OOCSjNScY2lTtjqIfHNyIBXdt9j2E51Gek8/h1gKgcKtEgFqAqUWp9QEzi0ClIJlZs3K9OVZuzBSsSzEivhz3DgHLPiMTOQGkztPkjnSphyWzXPRYeSbkurbb2RueKhPS/f2UQpxBAurWFxggJpg2zYBKBNgNjPnRmcrE2/nS/kxBITj6AlAzFva8/Ql8qFabLRobknmSM0zsDZDS0PLt869D6RSPce3K/H0ANrX1ELyoMCoyTm1qtKNlkGhplWcvjhdvH4ub1kzTpmPcz4HQI5UcxjHAZGf0eAASTLSZhiZTXKNoeQb5j/9h7/So2/ZdyNTjG6V2+iz8SqIGABFFrKAIYjKU3OViXdyc7lTBctCYC1U8zhgclcrOHmRW9Z5Xy+xvuU8UpOMshZuZhAALVjYKN+2bH90p568YR/jJMmYCcAYr4LHFGACTgmjFrVn35sujL8+Xpq8WHbJNycHcss4h4Xck61ui9vt3rnlnANAcUwp7Vp4lEb00hoVjy6a+0H26dzz4XSq/659mp7cawNowCgAs4AA55xWCGM2Z4xyxsq2NTk0PjPyyrhVyuGgxz+3fHOX9TigcAPI+9oBEYLGW2/ngFFKu4gOtFZtViP2WVJ90PfBr/XGUwduBaNtB7psaF8zZiELASBwFkBULJRzfxopXPm/CcsqOvHD47mXPLhLeuqBxwuwRaVAPtXfkpFadcRG7LoaAWgRA6VS/Xr60Bf3Gcm+2whXu4BTLswD2xKyjXPGkI0YZ8yem3ivMPrG8OzYG/mQ8s1hGMedc7/3Yx9vtbcjEReepbSL2KhrkeYEkW8Lcz9Cvu39WCq1457bNC1zkBNoQ/YhjHPGKWe2ABMBAaKyVZ65Mpy/9tKV0uQVdBf85JvbhXObA/WYyM087iUTbgm3BEBu+muRvpOXEYEINGKfJfLthiPf6Gvbuv92RU8cAIpgQflGOaY/CCaOrxkDTkszpdw7Q1NXnhuxinkc6G4SqGUeuJnGD0Re9qm1gK8mgCSQIjDqWqgJjQC0SL6l0wNax+Gv3mwke+/koPUDF8t7OKfIPJj/MM7AZkwQUO56cfTku5OXn3+vjnxDILlzm7AAWrS2yJVbNQSQBFILjeINvJQw1Qdq1/4TyXT/R+5Q2zuOEcZTKNuE9UbRcWNcAYZvOGe2ac+NDs1c+vVgIXt+LkD+E8SB81rXoeVbvTjLHGkDR2GTnrpW/rOwVNuz9ke54cg3+pO9B4+DYhzhAJoi2IeJ/EcwEGe8aiKYM8XJC3+aHPzZux77up77FpZ9li3fJJCadMRGrNlB5Bt+B/c6UDKZjJr+wF8fjCf77mNc30sIetYcGKWcCM+NsyoDMU7NmWuz42+dyQ89PRyw+qAReNzs414W7gaRn2zz7lsXuAskIwUO1ab9Yhj5pmzdeW8ive/Ru5RY5wOEQCdH0wDRwhlH5hG5EKdAOK2U58bfnrv8m1PTI6/OrJJ88zMP/BgocO4TtNclkIJGanN9L3Tx6Lbb/7KvvXv/Q4qePg4ABmq1eckmAIS5D+ZDYJv50szlk9ODPz5Tyo84axf8qg+WM4HqznvWBUDSbNhcwAh6tUHlG+ZDYu3PlkPfPKSldnwYiHEI2YYgaIALGcfRfANkIqzkKVwt5s69Pnn+h+/OVx+4wYPt8xaPNpJv9dhnUR3c/MV7N3YMGpNA35OMFChMLf+lUPKte9cD7Zm9n7iPxLZ8DFTYhoBBAFU9bMFEiAsOYhFq7kz+6ouvNrCvV8I+bgAGmjxdi96UQFqLqDbHMUPLt747vr6tvfvwx1Qj8TBnEAeCuBHsU2UgTIQQVMwslGZHXs1d+PHr5ewF3CYO/1ZSPOpmH/c6oHWVb9K1a46BvV6tDCPfhITbff93blOT2x5TtdhxtNvQMRDGQdV+YwgoLIKjleJweXrw5ey5/z7rqT7wW/vTSLp5J1i9xaPrLt8kkNZriEb7PEEAtFCBkOw9FO859NWH9LYtn2Kc7CaEoFfNRb0O5kLIPcJFYLZdmXqrMPyHF3OD/zscwH3zFoi69z9oVHndsHh0o7pASruNivz6nDdI8agzkSrmfwY+8I2etr7Dn1S0xGMcSLpqAgjbTYCIcKHhGOc0X5kb+93k4FMvBay+dte61WMjh3nc8z+L1v6sh3kQtnskkMJGrDm+34h9lhSP7njwO7fGE/2fJ6pxAgFV9dxw0hQTIKwaBSHhuF2+Up4een781H+8Nl994HXfvPsfLLd8x12IilH3u51KZHpDAikyXbEqDWkEoMVrf/r2G923/MWHtbauLxJFvVUYB5j3cME8C9YbIcS2S9NvlrOnfnX91PfeDiHfGuVBXgu7VvHomlrXqxF5CaTViOLGHsPdh24g4WuHedwMpPbc8fjWjp5jnyVG8vMAamd13odxAoqoHkXmmS/HLtjF7AuTF37+y5nhl3I13Dfv2p9G4FnT4tGN6goJpI2K/MrP24h9fOTb399qJHY9rmrxR4CDLlbLVd03RA5FRlJw+ZxdGTanLz+TPf3vvy0Vrps+O+8sR775TaB6c59Iyzfp2q180EbpCI0AtGTtz9bj3/qoFu/8GiH6Mcx1kIHmXTicRZ0HE2HULLxRnDj7VPat756sUzzqOGdhc59a8z+Rz3+CdL5kpCBRisZ3wlQfqNuOfKEjue2+L6tG6gkOpA+dNsx/gINYu4DEIyQdZyW7NPWL/OVf/mTinWeuB8h/ggBow4pHN6qrJJA2KvLBzhu6+mDgnr+7KZ7Z84SmtX2BE5KobnYwf9tGLLtG9wv1HLWvVfLDP8md/89nC9kLuPWOeyz4Ld0Omvv47f0Wefs6WHfU/pYE0kojuDa/DyLfnBxIFI923fkPD2ptnV8HxXiQAKgcuAKcECAE50+pYCMiqg/+WJ4afHL89X/+/RoXj67Z2p+1CfnKjiqBtLL4rfavw8g33Hkn3bXnkU8r8cwTAGQPKAQXKrhvLIyTrPhh0Tannp25+rsfZM/9YCiAfFsu+0Sm9m21O6bR8SSQGkVo7f8fWr71H/3Wrvbum75EtPbPEqKkgfNF4CEKQQNb4dzOWnPjP8qe/Z8fzY69UahhX7tr2BoBKPLFo2vfXf5nkEDaqMi/n5P4zf14539E+c6uB//xmJ7s+4qiag8DKKpY/kOIQsT9UYWGU5CRGC2fN6cvPjn65j+9EKB4dKXmQaSKRzeqOyWQ1j/yQfKfBQtbrP3Z/+mPk3jmy4qi7kfQMI7JD+6NgDkQqJyLPdwZreRfnB159cnx098fXAX55i0udZiraasP1rKrJZDWMrrvH7uefPNOnAoQ4dqfRM8dn1GM9s9wIB1V1sEaOMyEiFKdOxXP01Zx/OeTF378k5mrr0zXkG/O4Perrvbepdu7M2mthXNNO3m6Fl0ugbQWUa0PIKd0x13C4zCQWPujJ/s/RzTjQwBEF+4bsg8HQgjmPfOAYuZFc+rST0ff/JcXQhSP+sk456bCbgBFeu3P2nbZ8o4ugbS8uDX6VSj5lrzhSKz30JdOqLHOzxFFu5lX8ycEjwIEcBs4ATSC1aNm/g9z4yd/OnbyX8+GkG+OTPOCxo99IrF0u1GAo/Z/CaTV65Eg8m1h7geB0Xvoy52p/mOPqVr6k0whXQS4AI+QbFUmQiNB5ZzNWXPv/Xrynaefnhl+aSIAgNZl4/jVC13zH0kCaeV92Ih9vDmQOnDvt/e3Z3b9OVFjJzgnBgKIARegQQOBAFc45yqn1jVz9vKz2VPfezHg1lXLdeBapnh05d25vCNIIC0vbvirRgBaUjza9cG/ultNdD+mgHYbR/YBnPEBFVcwcAWlHIo3rlKzcHIue/q5sTe/e3odN47Ha5IGwjLHgwRS+MCFqT5Q+255JBMb+NDDerzj4wCkt5r7IPsQhXGmVh04NBCYSUsTv5u++IvnAm5dFYR9WnLtT/guW/tfSCAFi3Gt/KfmxvEDx/5mZ7zrwMeJlrifAGtH9kG5JkpGCVcRSAgorD6oFK68kD37Xy+VJq/g2h+H7WptHN+o+qDW7jtSvgXr62V9SwKpftiCyLcFAwE3js8c+ds74on+j3KiHyaE47wPMpAq5n/mzQMgQFhl7kIpe+5X7535t9PNunH8skZci/5IAsm/Y8PIN7FxfGbvJ+5X2zs/AqD2IngIMG2Bfbhw4RBQtl2eeH360ovPTw09NxbAfVsu+2za4tGNwqkEUv3JU0dmORJukYEwv/PoCUVvu58DtBMuli84NXAIJpWhnc3tmUrh2svZsz/8fWlqsOySb06C7126vRwA+ZXuSPNgnZAlgRTMfVs0/7Pzvm/forUNPKQY8cOcs/m5H6ZxkfegccA1nEhl9tzlcnbwpeyZ75+xrCIOaifeLb/z6DqN38icZjMDKZR8EzuPHvzSUS3eeYIRpa8q3TAHIqrIhRgaCDh5SjkrT72Vv/bKyxPv/CzI0u1G7COLRyMDl9oN2WxAqld94Cvfem/7Qley7+g9ipq8CxRIVaUbyrX5VajANLSvCWdz5cLV12cuPPWHQvY8Lt12zzW5l27j6yDWtVz70wQAcpq4WYAUxn0TRaI7j39rt5a58V5Fix/mwHQED7IOEDEHpAJwlTOucFocLefefTX79qpsHF+Lfbz1b3LyNGIga3UgBQHQgoGQ6ttvbNnzxcNGouceUPV+YLQq14gAjXgNBCsSAKzy5ODc9ddenRh86lpI9w1B0RIbx0dsLG9oc1oRSEGKRxdtHN+557F0x+67j6pG5ijnkCIKqJQicMRDGAei+oDblUph5K2pS8+8MTt6ZjYAgFp64/gNHbkRO3krAakR+ywpHt1x5zf7tcyeo0o8cSun3OCMaVj7hnmQYB+cSBV7H5RypcmhN3Pnn/zTKt623q98p6k2jo/YWN7Q5rQCkBoBaNHcTyazQ+34wOM3qfGeo0TRBwiChXCNMKbhnI+wrnH1qUJUak5dKoyeOhnyvj9BXTi5dHtDh/7qnrxZgeRutxtI+NphHjcDqVt33tuevPGjh7RY5nbgSgZ3jOec6VhtzZkzFwQa5bZlF8ffnh765enZsVO1dt6RG8ev7jhs+qM1G5Aasc8S+TZw+xNb9Y69R1Q9czMHFsMFCwRAQ/DMVyFgAanK7HK+PP3uudzbPxu0SuNoBrhj47fzaFgL281ALb/zaNMjI+QFNAuQGgFokXzDnUfbb/7a7rZk/2GuxHYowFTKuUo413DTEA6gKZj7EK4yKz86O3b6XH7o6eE1Kh71W7ot7euQAzXqX486kMJUH6jJ3kOxLQcevUmPdx9UiNKBjMMZrU6YIgsBSjiu4vqFyuz40NSV354PcdvGsLlPLQbyA1HUx4lsX4MIRBFIoasPtt38qQ6j5/AtWiyzDziJc8JUTtGBY2L+hxOCLpzGmVkyp4YuTA/9/GIpP27VqT5w76LjtrD9XvvdeUGu/dlk0IsSkILINycHEhvHx3d+pj/WufeApscGuJBt8/JNlO0wBdmIqOi+FXKliXMXZi4+M7JK8s0PPF4GkvJtE4EpCkAKI98UrD7o2PXobr2tZz8HrQPX/nAEDqOaAkTlzBZzQcApMUsTw6WR31+cHvnjTIDJ00bSrdbKU7n2ZxMBptalbhSQQsu3zr0PpBL9x3cbsa4bOYc2YKAwzH+AaijbQEg4rnK7YpmFy5fzl56/0mDnHVk8KgGwahFYbyCFkW+ieLTn4ONdic5de7iW6EPAUGaLsp15GadzYotqbNsqFioT5y/PXP7NWID7/qyUfeTG8as2BFvjQOsFpCAAer94NNWvdxx4dJuWGNgNmpbhnGrcohoDpimEqMhCnIGG8o2VJ7MzY69dnV0d+SbX/rTGuF73q1hLINWTb+6JU3wtbluS2HVnW2fPPQNGsms7pRBnYtKUaQqAZjNLSDgEErNNZhaGR2eHX762DPnm3r7Xb1P5WjcNdpw4aV+v+zCN/gnXAkiN2GdJ9UHfLY+kIXPrgG6kejm3dMYQPGgc4PLtag5UnTwtlUq5C9dnr/42W2Pptt9t64NWIMiN46M/XiPbwtUEUiMAeXYeTWux/ke6El07+inX0ggYBYhWNRBAU4BpNgdFAarbxcmpuffOjgWcPPWuLK01D+S1sOV9fyI7TKPfsJUCKYh8czOQmrxhr5HsfbAnluzuAQ7tDJ02iqzDdeG6UcyDmEYpBbNwLVccfW28lB+pBLCv5cbx0R9vLdvC5QKpEfsskW9bt9/dHtt2sBu0LV3MtnRkHwVs3RYrT7kOClGEpKMlqzx9aaJw7ZWpefmGwcfj1dp5NKh025S3rW/ZkRuxCwsLpEYAWlI8ClvuyrRt2blVjcWTjINeZR9bx3kfBA4nqooyjlami8XcuVyDlae17jy3XPkmqw8iNiCbtTlBgRSm+kBNpfq19l3HMorW3QlEaeOEotuGlrXKbFvHOy+gkaASotDZ0cJs9vRUCPnWaA6oVvmOXLrQrKO0CdpdD0ihqw+w+rqtc19Gi2/NULB0ke/g7RuZhYWjukJUrMbWgZqsUhyZmbt+suCRbw5DrMbOo36lO3Ln0SYYlM3YRD8gBZFvTg4kikcrmT1t7fEb00RNtKkG6MwuCxAxRdVUKuSbxrmtElawy9ND+fLUUGkNikdR3rkBWG/exwFUM/aZbHMEI+AGUhAALeRAeOcFNXlTQkn1tVPQYiqhugAMq2gKKDpXuKZQooOiKFZ+rGQWLs6V8mPOylPnXG65tdKlC7J4NIIDbLM0qRF4lrhv6fSAqqe3tylGV3vJLum6qmuqouqcWhpTObKPzhnXNLChUp4ol7PvlOZr3xz3baXyzZ0DyY3jN8tIjfh1uoGEr92PhVvWY/lOOj2g2ZnuuE4ScUZB0xRmcNXQEEAcwUS4zjlRwS6DmR8r26WRyhrIN1l9EPEBtVmb5waOwxguC7tb7eiwNMsYiDEbDEMnepkqmq6BzhTdAGZrqqLrwIlq0zy1Z7FyJ4e5inNcN/vUKt+pt+rUb+7HK+H8LOzN2p/yujcoAl4WWjAR5gtJNYCk3tbWYXBDNThTdV2LGUwFg3OiIS+BlQO7MFWxrKJXJsqN4zeoU+Vp1z8CfnIOK7HxoeGjvb3dKLKYHjMSMV1TDJMpuq4pmlXMcbCKzLIsZ/tfLzMENQ/kxvHr3+/yjKscgVo5kQARAOj4iMczsTLTDMNgGlQqSqUy58g/5/eN3Dfv0gXvsm23hJPFo6vcyfJwax8BR8o5gHCzkQBR9RGLQQxUME0HYG4WcpjIYSBZPLr2/SbPELEIuIHksMwiNnofTAJUDtC8TBR06UK9jePdrCYNhIgNFNmc+hGoB6QFaTcPJnwvVrK6qrG9e2Avt3jUW7rjBpLsQxmByEfAD0gLRoMLQH6Szu3K1QOQ23SQ1QeRHxKygcuJgDdHEjv3uF27edPB+Qz/7/zVYiO58+hyekL+pqkj4OfaucHkAMgt6RzZ5XdrEwdEsni0qYeFbHzYCPjNI+FnDnCcZycv8habemWb3Dg+bA/I77dEBPwqG/zyJnfJj5uR/JhHum8tMTTkRYSJgBsgtUDlBZHXmnYbCH62tVz7E6ZH5HebMgLe6m+8iHqf1QKKXHnalN0vG71aEXBA4wWQc3z3/73ndDON3zzQarVRHkdGIPIR8AKl0Xs3I7kvTsq3yHe1bOBaRqAe46zleeWxZQRaKgL/D0KbsHr4XfysAAAAAElFTkSuQmCC"},73486:function(e){"use strict";e.exports="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAANIAAABoCAYAAACEyK5RAAAAAXNSR0IArs4c6QAAGOxJREFUeF7tXflzHMd1ft09vbM3FscSIMEDvEmRlEnRsiwftCz5lBSfieOUk7JzVblS+Q9S5V8SV35TJa5KpZyyncjyWY4d25RKsh3RkilLoWgdBHXwkgiSOIgbi11gjzk69Wa3wcFoFju7WIALoFm1mt3FzOzMm/70vv76e90E1D8VARWBZUeAeM5Q6zPuLnx+1e+7ZV+cOoGKwFqJgBs48r3fd3734waPfK8AtVaevLrOpkbADR4vkPCzH7i8oMHPft819ULVyVQEWjkCXrDIz57tFrp1KxWDg4PyXiR4vFs39VNZqpWfvLq2pkagCnCAVrIRbml7+y5mRru0JADMzY1ZMzMDViULIVjsyssPXH7AauoNqJOpCLRCBLxAkgBiCCB8tbVt1ywrpNlhrgk9yfRQjBFCBRfZYmn6YnFmZkYCyb0Nkqla4f7VNagINCUCbiA5wKm8EEjOKx7v5lYoERI6Z7oW1YSIUcEZDWlRSiizzVKuYE1czGWzQyYAYKZyZyh87waVmxpWUwCbcmPqJCoCqxkBBJLMQvK9BJEGiYQGlsXDoU0618Khos00Hg0zzpMUhEaAc+A8QjiPASkW52YKb8/ODZwteADlBZMSJ1bzCavfWpUIuIHkzkYaAOCLV7aarqdDWqozLGiMayyk4Z+1cJziloRCQtOiADwCQtj5Un44AyPPZxTtW5VnqH6kBSLgByQJItyG3GBCqhcKxTQt0RvWY1t0Q1CqhcOgMZ0QwgXTdEK0qABNA0q4IQoTU9mrL05ms5eMgLRPKX0t0CjUJdQfgaWAhNnI+5K0j3DOqZbYoUfj22Imi1AW1oEAF4yFiBaOAZCQAEEJ4botjNmp0uj50Ykbv59z9aH8+lJKPq//GaojWiAC3j7Srf7RYhBhZnJnKtmvAs45aIneUKhtd4KHO0LA8BQ6aLru6BWM6aDxiACmgyjmZ4vzl4eLN05NVWifFCekjK7UvhZoFOoS6o+An2qHSHD3kdxZSX4v5XF5vAOASLJHC3UdSOqxzXGgGgUnQ0WAaFwI0AgL6cBYCAgReXN2dDhz8+nh7PClkidL+YFKjUfV/2zVEasYAb9xJHdWcgsOElASaG65XFqJnD4O520kuulQMtrVlyIswS0nM3HAbIVAAnxBCDTOLTs/M5Qde+HG1JVnsor2reKTVz/V1Aj4ORsQIF4wuWmdOyu5MxMeh/8WQMU5F3rn0URi054u0FIRyjmxgQNFQFEOQHVnX8bCICA/aky9dXXo3HfHKoBStK+pj1qdbCUj4AaSBIF3YBaBI7OQm/YtDNq6BnLdY1LuLCUiHbvDie7jm7RkdwclIQqECaCYnSgwqhGKwAIGgti5Ym78cu7GyWs+tM9vTErRvpVsIercgSLgdX9X6zPJLCVB5QaRF1D42StiLDR2Hu2kbdvv7QnF+zYRLcqpxqkzJkw0QTVGUOOgmkaoLQzTyF3JDj1/eeqtX8/60D43qJTaF+hxq51WKgLVSidqWYfc9G8pUMns5v6dSj8qCokd7+sKpw72auFEAsFESYhghgLCCDBNOIO+mkaM4vw1I3vx9eE/fGdUuSZWqimo8y4nAn5FfH5ZapEbvEL13GDC9+5s5f2bG1Du0g1H7Yv3vDsZ33p8Ow93pylDJFEQwAjV8JTUyVC4JUJMF+aG+mf7v385mx3CQV6vYVbJ58tpDerYhiPgBpI8Sa0s5e5DvcPk6hIqZKbyA5W3b+ZkqUjHjlBy64kdPLFjG+N6iFKkepWfYIxQ0EBQRhiQQsmYOZ+9/tz5qStPSrWvmjihaF/DzUMdGDQCfkAKCijZD3KDqRblk3/3Sufu6xA8mqTtOz7aq3fu20W0aJISrNzgBAgpA4uiBYkRoNQW1txFM3P5letnvjmsaF/Qx672a3YElgJSNUBJdU9mlVq0z68P5QaUFCf8spTo6HtgU3TzsT003LmFUgoUNPwPIQ6QKtSPUCLAHDLmRl6cfvXRC7Ozg1jSoWhfs1uLOl/VCAQBkvvgZtM+OQ61UEhYUfze0Y9KpO+IxXd+ZL+e2LyLALpjGbERVow6W0IIxSwlKMlapZkzs9d+9dLkpVM5ZZZVrX81IlAvkG4H7ZMZsKz2RTpZ1/6H94ZTew+AFmlzwEMIBcxW+B6oQ/8YI5ZtFl7Jjb72ws1Xvjm0RIbCzKX6UavR2tbxbzQKpKUA5aZ+brXOnXWqSeZegcJNG+V5nUaPron2PQ9tj6SPHmZ621ZBgFBSUfdQlxBI/Qg4HSm7eMWev/m7qVe/8Vomk5GihJx3Qg3yruMGvlq3tlwgLYf2uWldrQHeJeXzVO89bbG+Dx8NxzYfEISECHG6XYRQQtEtge+Eo/6Jabs49czs5ZPPT1w77S3pUGbZ1Wp16/B3mgmkoLSvEXHCnc28oFqgZZFkL0/t/9yRSFvfMdD0JIiyKEEJJbaj+WkEQQUAJdvIvTA/3v/0yMvfQrXPT5iQmUrRvnXY8Jt9SysBpCC0zwumRiV0KcF7aF8UOg5+fm+06/C7WSi+HRA8hOEsLA6oBG4IRQsFgFXqN+dGfj3d/y/9qkaq2c1r45xvJYEUlPb5gSoI7fNmqaryeXL7iXu0WPoIAOHI95DmOZnJyVKMCgEEBIzYxtRTs5dOPjs+8My8qpHaOCBoxp2uFpAaoX1eaXwpgUKOS1U1yybS+yKpfZ+7OxTvvYewUBIAkxKKEggn6lA+J1MB5G1j7jfz4+eeHH7pP0YU7WtGM1v/51htIK007fOOR72zRiqapOlDXzocTh34IAtFt2M2KmcnQpw5JhBc+A0BYlmlF6zsyC+uPvu18wHGo9T85+sfL1Xv8HYBabm0z4/6lW0Ot4oS/WxI8n4dc2vn/s9uS2x7731c7zgKhGpuUKFsjto5fkeJuGrkp3821v+fT+dG+3HePuWa2MCg8bv1VgBSvbQvyHiU1/NX033esfdTJ/RkzwcAWLIsm1PiAMt573A/CkJkbDP3y/zwuZ8PvvpNdyWv3xzoSu3bQGBrJSDVon1SlPCaZWsZZf1sSPJci9W+SCfrPvqX7wmndj1AWHiHMxblAAjQelQBk7O1hVU8VZgb+uH1337tdWWW3UCIqXKrrQikRmlfEKVvKff5ItrXfeQrB+Kb3/Uxprcfw1qrcnIChtoEZiikkIgyYVtvmoWpx8Zf//ffqNL4jQuoVgdSPbTPWydVjw3Jne3cgIK2nSc6O3Y+9DEtlr4fgMbL408o+aHKJ9CEhGofKhVTopT94czYmR+PvfToRABxwk39vO83botco3e+VoAUFFDNrJFaRPsiiS16+uhffUhP9j1IGN9aARAqfI5LFsEEZYOfaVn5k6XMwKPXT/+jon1rFBj1XvZaA1KtfpRfjVQQccJrlnUDcnE/inORftffHoumD32ahZLH0S3hiBFltRCHeNFCUVb8LOOMWZr6zsQLjzylaqTqbZpra/+1CqSg/ahqwkQtgcLbl/J1TXTtfXBLcudHP6uFOz4KhEUQTGX7kVPLwUTZQkEJ2CNWKfet3MjvHht55QczddI+tcD1GsDUegDSStK+WmZZp2+TSO+Ldt7xF5/Uk9s+A5T3ghAMe1E4HVKlULGc8YQ9Z1mFH5gzb3174Ll/vqBcE2sAIQEvcT0BqR7a5ydM1JOlqpplu4//3fujnfv/lGjRu5DeIZiQ/iGqHEefcFY1FMIynjbz49+a+sM/nVJm2YCttYV3W49AWmnaF8gsmz70xV1t2098UdPbPimARAUAVnLYiKGFTCQEfn7bNjLfnrz0+E+nrjzpnQhT1Ui1MHj8GtoaudyGL1P+D8O9dfd73A70es2y1WZEcvo28Z53J9KH/+zzPJb+PCFa2gGREEIQsIkAGwjYCDIAmBXG3I/nxy98b+jFRwYU7Wv4Wd+WA9d7RvIG1Q9QUpVb2RqpaJJuvuvv79dTe/6EMv0QQQAhkMoZCtmfhaBCANlW6TdGbvi7A7/9hzNqQYHbgou6f3SjASko7atWIxXUPbGkt6/7zi/vj/fe8wUtlLwPpXMBokz7CKYq7EPhfC5g27Z1SRQyj2Uu/fQJnxopNddE3c195Q7YyEAKqvZVo31eUPm5z+U+fvI5tG2/N9Wx73Of4dHuhwihKcw+AvtNxOlL2SDARhcSCDFlG/P/PTf20k+q1EipBQVWDiOBzqyAdCtMjdI+CRbvSh1LlXQsHuSNdLLNd331fr1t56eJpu9GQGFGctQ9ISwEkxDEJESYlln8Xys3/COfGim/DKVqpALBYPk7KSD5x3ApcSLo5C24nwRXYLNsz7G/ORzrPvZpTU++1+k9gbCcDFURJhYECtt6szQ/+aOJ1793KnfzlaKqkVo+GJZzBgWkpaMXRO2rxyzrl6V8XRNt2050dex98GEe6/mIICRGHGWP4BhUeT4+pH2UWELYU8LM/Wx28P9+Odr/2FQNccJBZuWWvdvltKMNf6wCUrAmUAtQzTTLLnKf4xRj6SNfuU9P9X2SUL5VEGKhO7YMGOxLOcBCKljEGqn5zMD/DJ7++iVVIxXswTZrLwWk+iK5VD9KgskNqqAqn3s/d4Zyg0r03vXVO8PpQ59gevyoEFSWuyOoLCmnY5aybeO8PT/584mz33hemWXre8CN7q2A1Gjkbi06vdQgbz20z6+S15f2dex+YFOq7+OfYJGuDwChOip8TtWuQOpXfo99KQFi1C5NPzF54+lfT7/xeEaZZRt/2LWOVECqFaHaf18J2lfNLCvVPrkwm54++Ocn9FTf/eC4JhBEFCV0R6DAfpUoU7+CsArPFCbffGLwzL9eUwsK1H6o9e6hgFRvxKrvH4T2ScWvkRopt1q4WD7nXGw68td3Rrru+AgJxQ9IAGF/CmdsEeD0qywhMGsZ50rzw09mXn7k5cqCAtVWOpTLiPoJFM2L2jo5kwLSyjzIWlmqEfd5ILNs+65P9KR23veAFum6G5eKryh9ggCYKE5ghiIEKaA1as1P/Spz5ZfPqgUFlt8IFJCWH8OlzhAEUPWKE7VqpMq0r31/OH34j98fivd+kNBQG1I9B0S3jLIWzoFJCMzbRv7Z+fFzp9TMso03BgWkxmNXz5GNuiZq1UjVnlmWR0nnkS8fiXXt+xDl8R1ScHCcEjjRGFI+h/pRC6zCudLc4NPXfvf1N5RZtp7He0t5qu8otfdyIlCPa8I7gFtr/vMlzbJdex7uTW573wdouP1d5WkmEEDoOne8fRagUAHEpMIeNgtTp0bPf/fs3NhrebWgQO3HrTJS7Rit1B710L56a6Rkibt7mrEF0SCRviPatu8z7w0neu8mjMeEXVb5BDi+PhsIdcQJEJC1zdzzueEXnxs9/4NJVSNVW2laqcaizls7Ao3SvqCDvdXVPlxQ4MCXDoe79t1Dmb5FAK0IEQgozE4IJmIRChaYxVdLmbdPX3vhkasBxqM2nA1JZaTaDX0192gW7at7QYGu/Z/amtjynntYuGM/1kOhl88RJxw/X1k+B8osENZQKX/zuemL3z+nZpa91TQUkFYTJsF/KyjtCzIe5RUsluxHxTcfibfvfOjuUHzLnUC1ULmCl5hlP58jSphAqQXCzlql7JmZq6fPTr31CznXhHuB6w1VI6WAFLxx3449q9E+d99nuTYkeS45yOvQMh7pZJvu+MLBUGrXXYxHOstuiTLdK8vmxHIABVC0jdwb5vTbZ66f/behjWqWVUC6HfBo7DfroX1B+0+BBnmddaQ2Hz3G9PadKJWXSzhQNqcmcQQKDT1+lhDWdTM/enbm1UcvZDLXpWPCvZaUdEusO9eEAlJjjfp2HhWE9i03S/mZZSHeczSR6vv4kVCy56AAopVrpFjZfgRgEkqd/hQFe9YsZV7Kvf1U/8S107gerxtUtaYYW1AXb2eQ6/1tBaR6I9Y6+9cClNsx4a7QrTUWVS1LyTsXPNmtde7+o/3h1J5DVMP1eEl5ULdcK2URSk0hUEInJcvIvZmb6X9l/OXveVfoWFel8QpIrQOMRq8kiFlWgiqIOOFdUGBJs2xy18PbopsOH9L01GaCZRzOPH1I+SqKn+Pro5ZtF6+L7I3+zIX/ersys+y6Wj5UAanR5tuax9XKUo2YZb3zTfjRPhHvOd7WvuO+g1qseycuHABlhc8SlFjEBpMQatn4XpAZUbj52vjFkxdyo/0410Q9tK9lFxRQQGpNQCz3qmoBqhHaF8wsm+zmqV2f2q23bdtHND3iZCcEFZplcWDXZoZgxKQUimY+c7k0du6NkTd/hit0+GUoSf/c/aaWnGtCAWm5Tba1jw9C+5abpSQopXzuNHrOuWjb/WBvpOvQPsYTnc6gLsUpxagtCDGYQwGZaRNiCrs4WBy/crFw7SdDa3VBAQWk1gZCM6+uVpZqBFCB5PNU7/G2SO/7d+uRrm024TYRtk2oZtogLI0y00bFD+1JYM4Y+bFLMwMnr/q4JmqpfbeV9ikgNbOpro1zBQGUV5yoZ1xKHiv7Ugu0DGdESvbd3xdJ7dkhKOMEJ7+k1ASBWYoajh0JnKyVN42Zq3NDp69OXXkmuxZonwLS2mj8K3GVS9G+5SwoEKRGCuJ9H+6JdR3cSXkyDsKyBWUmI8QSKExoGsroJlI/AnPDc2MDb4299ii6z2sJE7fNLKuAtBJNdO2dsx7XRFNrpOK9x9vaet6znca60hRXEXBoHjNtISzKOMroJmHMtCx7RuSuD8xcPDmSzQ4ZrTazrALS2mv0K3nFjdI+N/XzTtPsnbPPt0YKaV9i24neUGLrFqrpOBVSOSvRCpiAmpRSizEolHKTNwpjzw2OD5yVRYe33SyrgLSSzXLtnrtR2lfNNRF8QQEeJfHtH0pHOvdtYSwcxgFewtApgTRPlOkejkdp3DDy2dF85vXB6TceR/e519vn9fWtKO1TQFq7jX21rrwe2lePKOFWCasM8h5NxjYd79GiqZQN1NQqoLItMKmj9gmTMN0UopgpTlwbLg49Pjk7O+uUfPiUx7uB5Tcutax4KiAtK3wb6uAgtK8es2zgBQUiyd5QdPO93XpySwdQhmWHWM5hANUsCsSwGTM5RXuSnS9mJkdzo78dy928UqohTjR1kFcBaUNhoSk3WwtQjbgmqi17Iwd5yzVSPEoSW+9t56mdXYRFuEbAMkCYmlPF64xHGZzpOMhrgDk9WRx5bXzixu+97vMVMcsqIDWlbW3IkwRxTbhBFYT2eSd5cVM++XsORcNK3mjqQCdEOqMao6YtwKICqR6+L1M+CsK0SsVsfvraBEw/n1lJs6wC0obEQNNvulaWasQ1Ecgsi7QvnL6zXY9vTgCltgMih/KBYQvbJJRbRAhTY6RQKtycnB84k8lmh7AfVWtMqq5+lAJS09vUhj5hLUA1QvsCmWWR9sW2HEvosa1JQUOMUAQSToJJLNsUBmYqfDHghlmYyOSnLmcq7vOmmGUVkDZ0u1+xmw9C+7wLCgShfu4sJUEp+1FOBkGzbLh9V0RL7EqycBsntm0SRkzLyU6ahasIUOAlYjNTWFN5KAzNmpm38ss1yyogrVhbUieuRKBWlmqE9gUyy0aSPZrevj9G9PYwocImghqEgGUJYuqMGaawTCaYgZP22dnheSt3Ya6yQkfd8rkCkmrvqxWBIICSWabeSl6/MamFPg7nUQin90a43h2xCLWJjZRPWJYQJdxSjRrEIqZpmwYv5eaN2Rv52dlBuV7vUpO3LAzyKiCtVjNSvyMj0KhrotaCAoFonxbpDenJnjBocSDEsKySaRC0ITEwTdswwgxMwyKGIeYKWma84Fo61CtOLHJOKCCpBn47I1CPa6KpZlke7WRaPM01PcnABhMRBVQzqW2UiClMyoRRMuYNqtklXpouzsxwE2Dcz4bkZD4FpNvZjNRvL5Wl3GNI7rKOpi4owHlUaIlNIdASWFtoIYhMq4RgKhFqGYVSrgSsWIJcDh3nUjZ3r3LoZCYFJNWYWykCjdK+oIqfe7pmr9pnA2+jwCMkRJhpmHaJGHmDRLRSYWa2CDAngeQLJgWkVmpG6lrcEaiH9lXLUtVKOvzmP5d9HjsUitkQCtk4jRg1zWKBlIqQzyOQvGCSQoTKSKrttnwEgqh9zTDLykDIuSFM0HUTikjnimiAlUDyUjxF7Vq+CakLDJqhZH+qHkBV8/XJzCTlbzeAvFlJZSTVRtdsBNzdEXe2coOpXrOsl+rJrIRgwj6RNxvhd+66J0Xt1mxzUhfuFgv8AOX19UmwLFXFK8EoB3Mx40jQSEDJz4vGlZTYoBrkeohArX5UELOsV9HDuCCQJMVzA8rtelB9pPXQgtQ9LIpAI2bZauUa7qwkgePeLrIOqYykWuJ6jUCtLOUVJrz9JAkk2V+S2UluF838qoC0XpuRuq+grgk37XO7KdxyuBtMflMnK7FBtbcNE4EgtM+7jxdMflN8OQ5wlZE2TDtSN+qKQDXa56cESornpnrv+E4BSbWvjRwBvwy0FCbcK14smnBSAWkjNyN1795+lDsiftjwLh2z8FkBSTUmFYEmROD/ASqSbiAtqYRHAAAAAElFTkSuQmCC"},23280:function(e){"use strict";e.exports="data:image/png;base64,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"},63232:function(e){"use strict";e.exports="data:image/png;base64,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"},37618:function(e){"use strict";e.exports="data:image/png;base64,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"},14760:function(e){"use strict";e.exports="data:image/png;base64,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"},87620:function(e){"use strict";e.exports="data:image/png;base64,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"},31537:function(e){"use strict";e.exports="data:image/png;base64,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"},46058:function(e){"use strict";e.exports="data:image/png;base64,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"},71190:function(e){"use strict";e.exports="data:image/png;base64,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"},51889:function(e){"use strict";e.exports="data:image/png;base64,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"},95754:function(e){"use strict";e.exports="data:image/png;base64,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"},9490:function(e){"use strict";e.exports="data:image/png;base64,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"},82670:function(e){"use strict";e.exports="data:image/png;base64,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"},61834:function(e){"use strict";e.exports="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABwAAAAgCAYAAAABtRhCAAAAAXNSR0IArs4c6QAACHBJREFUSEu1lnuMVNUdx7/nPubembkzszM7w+yDhWXdZYFFAaHRBSultgVbH6StkBLtw0d8G6lWazW6bYIPbDRUTQsm2sTIH8WYFFNsDA9LqSCuQFnYVXaXZXdnn/OeO3Pf9/4aNoU+fCya9vx5c77nc865v+/vexi+0CBx6VaIqy4HOyvLXAL39+/CwSq4AKMLWWpKeG50ANwTu5pF9u0+EyCm07uzZX38MmjaYiqXLvK0cpJMNeTpqs8zS/AM1WGWqnJuOc3xxqCo4DjqpffYvM6Pz65J9GMZaHcZu90+xzgP7CASHutZ+wKdOviacP2L73udW59iAeU2FqipghYAZAnwioA+CmQnYA6qqIxY0AsOyHYRrhYQquHhhWzNc7TXRd/kPVjTscwrHr6bM3bdzFpgnoVOAbd2kvij0M3PSW7qHujjt7OlXducfa0pvqmlnuLXwa1EwIckMJoAjH4gOwAvlYc1UoaRLsMoGPApDMEIgxTUYVtqXtxUqHU7f3ET37v7ZVD+dUTpFtbSZ04B3ZE7f8YN92/GnAaQnZ8kzOjgrK4NSF55BYQrAEgAlQH3DKB1wU7lPOd0hrFMnhlZC7buQJAApd4HUbHgFIpHaNk1W83B/g5JztSKUQfIG5vZmtTDLEVPVsff33tcigXqkEwAug6oGVCqF6xtFRBpB4gHvBxgngaNnYLDX+2WDu7hhfQgjJID13QQCDKE5kjgeQMT76UhNTVCiROEuA7YJjzOU82M3sZIXT/fPtr/d3FWQnQHVHjjhUPCDBZBKTufLW4D4gsBzwX0CdDEGXilGGH+IzT+x6c4ZzAF17DBuR6qYkC4WQI0FWcOqAi0xPrDIW5S4I3LBYkYFxOh5tUrGA2313v9xW4uEQ5bx0YGfL3D83BVU41+Wj/hXzYzhHgt3IwGZiZBQjO4uhXwOD+ld7/I+Ogc6EPdcFNDiAVMhFsl0GQWH3+g64lFviUn7hztb9/edIwrURtL+h1Dyy1iRODor627mI9fTSPFFMuMtGJ2u1wYGHizqn3GV5Go5ZxUBuZkA/iaS0DybPCBANzKKKTqIOxsN0pHTiJoZRBo9sE+NYK+bv29akX87m83xfMPvGIdCzJhvh1hnX1uz4qpoqEjF6/EZGU3HIeHZazO5KOH4kvQSnzgLyzZEEAuDef4KEpWPZTld0Id/gjGaDdkmaCNF+C3Sog2CuDrfXB6Bk2hgVbm9ms9seVVc7NH2cFwvSw4Cm4IrD35xnkf0p/nvgzPvBVlZydbN3J9B3VwT5zYeQi1TV9BqQSv+wwq4lXgWlYjd/BV5DOEaITAlQqIJxz4GmSwEAe7p7fr+PrE0mXsQ3vsyfpXwnLoJ6jj3wqsv2EtYx3ev4B9y2fgxNghaOZshJyr2bWT71DnggfR0PIsDMAbHEax1IbycAZufhIWryCYDCEoaAgnPXC1CuAasLo/+qX0g1RHYUt8aTmrHAjW+iv+BeF2eeX7veeNf67t0IHF38RI/k+OZvQLi812aJIPsXldCMVnYDIDa7AMc8SAoYlgsg++qAwpJkKKC0AiDG8oVbLGehbJRmF8qH/WnkAkuFxpDf7Qf13na59obec+uG8vvI/LFbe4urVDuHViHR1Zch9qGrcgVwHyGtysBUcjMF4Ap/jAR0SwsAxE/HC6Tv5KvKb7iaFH618KKtG7WIP4dOzGo4/8e7/+j+Z9HrpzwYNcTn3WVfVt/P7MXXj0yu2IKOswWQDGS6C0Bc8EmCyASwaB5hlw08U9fPeBq4eGah4LhqOPi3Xyc+Ebmx9ibIc7LXCqcnctXO9mjN+5efMdKz98b2Dlko3aqHpraUCNV4YsaHmC6wHVjXI5eWlse763+1HwTY/J4eAdfI3wUGTd0RfA8InI+tQTntuRuW/pPC5t/MZOa9FK98Tt/pUNm8xA9RprxIBHAoS4H/boZK91vP/7gZbGp4IxOcnXyPcGrj188LOy8XOBUyICozfmrlfPGBuk5vAiX2P1LLtHhQsZ8swA1JFcvngid7i6MbDL36xtY6vOGJ8XxNMD/6mmDgi4/vLNmCxszB22kTPDCCk2qhfLO4XdwxvYrycqXzjxpxNQ74pbqG98m3bM4gqVEPyKh/ClwWfEb3348+m0n2mLzxPSxHea3Gz0uD1WCeb/dhSiCIpfmfgaW/HB/v8P8OTqWE6tPlKpKLPVE0fgK6RKzZfFlrM13Sf/50Cil5Mof/Q44N4BjTgU+4DRU0Bz41tm/byNMnuh/0Kg0xYNqR0LYI89DMjfgMzqMNoHOj0EL5WFpzCIC1vhQsnxIrcXVY3PsMTznV+6Sim7cQ1k+1U4uRpkNZAtgUEEqUU4YxPQx7IwywaC1TwCrdVA3cwCBPluVrdj+5fyIY2uXUqqdpAKnkhyHTzThlXS4GgaSKvAVCswKiZ4lxBNCAi2RoCw9D02f9+bXxhItE9Bee8mnH73HncgzVFoDjw1C7tiQC/wqKgCMnketmbAL3pouliCMi8INiv5FiIX3caUJyc+DfqZ/5CKP70fkv48TaTh5kw4JQ/kCuCYC89yp96ilZwGo1iG4GqIJzzISR5Cax0QrN3CGnbcf8FAog4OH+95AMzbjLwDchQQFwbxARAR4OggXQVpRTCjAjItMMYgKD6wKhF2RntJXHzRA6zl7anX9rRpQembQ5TtP8b0YhMKBpA2YI/ZMIseLIPBcgV4oh8s4Afv58GLgCi48PE2JM6EFeQK0sWzFrG23UMXBDw7yTy8qM1n4yZX832dZ8pM1+Sjrk4ysx14tg3XsmEbJgzNgKMbhuBZuYDM+vxJYb+g0B/YulTXBV/pf98CbUBVqR5xCOEY8WLIE2T5bKpamm7yHitxsp1LBFmGPVLMT2f+fwBgayBhvuifmwAAAABJRU5ErkJggg=="},8451:function(e){"use strict";e.exports="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAAAXNSR0IArs4c6QAACA1JREFUWEfFV2lsFdcZPXf2mbcvfs82eMVmETslYEoJgRRo66CmLGkjRWmi9Ec22kYtrSq1kVETkjZpKpoGiJQobZImCpT2R2nDlkBLwGwxYMAYG7AN3t4z79lvmzdvtluNUyRSFhsqpVcajTTz3e87c+6dc75L8H8eZLT1KaU+XddLbNsuSmUN38BQWhlSDTajmoxBbIvyYsHtkbNFAXdiWliJoaVlgEyerDv5d57sdzX+dXO+oaHB/u961wGglLoTqdzPh3L6gkt9g4fyuv6HuZPKfyEJ7DzCkDClkNSCiWQmj2RGR65goUApLI6FqAgo8kl2uVdKcwSX2vtS69q7B77i9fsekBWhZ0KR6ydlHvmf14K4DkA6q70yqNFnevvjSb/HHezqiScqS8Oh2vIwQClMy0Y6p9H4YBYDKQ1pzUQBFJTn4fLJKCvykVqfCAvAtsaLlqyIrKkXThOGLa+KeLJzy4IzCSHxqyA+B8D5+s6+5Pl9J7r+3tUbX7tgZs3CkMf1+5BPKS3yu6jAstAtC6msivhQDlmHCdWAqluAKEDxSqgo8qLGJ8G0gd1tcb07lly7bd8Hm+6dWn/PrEljd8+uDi+LSvyumwEIn+uKd+w+1vHEmlV17zpBH37SOqGqLLSvNOwtlgSOmqaNoUwOibQKnufQmSogndUAgYPilVEe8aHWJzkMkL3n4j9dPjH6aydPw5/2V0+fXNE+qzbyzQqXtP1mAPiLPYmWIy297z+4dNqzV4NaOvoPjokE5zGgNJ1VQQHougnKMGiNZ6FqBhieBScLqCgJoiYgkoJN0NST+9qScvdOJ8+GvzXdWzMuumv8uPC0WlE8c0MAzsPuvuTGs11X5i6pGz8bGK6F5rbe7RWl4XqWAU0MZaHpJtyKgGRGw+UhDQbDwADAizwqiv2oDkhkKG+hqSsx//5J0YNOjjc/PrNhbFlo6dKa6DRCiBM+PK7bhJd6B2YPpLTGwy09C55cWXfICTrW2r2xPBp8QuIItUGRTKkQeRbdiRwSqgnOJSKjmRBlDqVhHyqDMulLFXKfXuqf+vD0yo5n3tgRvGtq7fniEv8vF5eHfnvLv8B52XKhb1t/IhNePGf8PQ4LjSc6Hg8GfZsUAZRlGLAswWBWx8mLCdgUiES9AM8iZ1qIBjwoDbpJRzx97uM9TTMaHl2kvbbzxIYxpaH7i0uVqXWhUHpEACdbO6tMsCf6Yqn19y2c8qtdB9pmuNziUY/CcTzHUptSXOjJguNZEIYgUzAgexRQgYHXLcPn8ZKOnvgfV0wpeWT91sYVFRXRrX6vVF8/sXTHiEJ0NeB4a9dqy2bf648NPnrfoqnv7jlyvinod8+ktkXzBRM2ZcAQQLcBzabQbQqiCFAUHhZlSSyZW9x2+pw1flzZDo9Xen7F9PLnb6S6t5TiT89eftqy8ZvYQOppixCmuCi4mYVFLQswbBuG6dwpTAAmQ0AFDrJLIrFkZn/r6Qtv1FSWbPJ45I2rv1S59maSP6IXHG3petg0yMb+geR2i+XnlEb8VaZhUd20h8VGt23olMBmGIguAUOqYbe1dp6uKg5M9Pldz62eU/3crfxmRADO5IOnOr9sFew3r6TzE1mRhySKNK8Zw19v2IBJCYjIwWaA7p5BEhAQjwTdT62cX/vnkcxuVACcJHsOnw0JLP9CJm99T7MZksnrwyDSmgFWliAIHNHzGrwi2V7kd/3wW/NrL4xU/IY6MNKkjxrbl2c0Yz3PsZMdlTreeQU6J0Ay9J5oUHnhsfoZrxNCHC8a1Rg1A9dm23e4fd6k6sietFpQDrXFqX9MlOZz6iMP3FXxzqiqXhN0RwCOnOr8sSy7XuobGKQd8TRCY4qJS+Zf+frk6I++EAANb+2VpleXvKiI0g/aY2kUqP1BX3vssZfXLst9IQCcIqqm/Y6CX3Pi0iAiYc+W2qD47dstfkeb0Jl0oKltZVlx6G3NsJSetE4DoYCu6vqT8yoDb5H/OOhowdzWHth7vMNvavrqgFfezLEME0vmaGc8AyIppHhMGLZlPp7Vcu8/VFf7OcP5n4XISdB06sJsj8/9qtcl11FH/UyL9idV9CRVmAyLSJGXRMMemi3YB9R89qm7q6PNo2FhJAbIywevTLBNJjTdld1cEfFP4WGAUkqdznhINTGYM6AaNgjHQvEoxBMIoDuR/iROPGsF0YqtmSh33DEDp5KFaZpFGnWbKKZugiOgMY2iU6XDPqCZNlSLwnQUiWFAORZBiUFtiCW8yIJhaZ+XkFmL3KT/jsyoLWU+KLvZ93Tts50lsMCxpEV39ttgCIFNyfBziwA2ATQAJQrB0nIGqg1iUICamPcdHxnurG7bjpsT1jqXh3lWy4M6a8VzwP6YiY9iNohTlDoXHb6bIDAI4BEJllXx0J13PEghZ333+yXc23cE4NgVc6sss6uMAihhAI4Bdl7W8a+BqwCcpfhsCZwu06AUAsdgSZUEy2FIADEz5ovravmf3TaALVu2sGMXrjrKC2Sm6XTgBGAJsOWihsaEMUy97VixsxcooDqX00ASBsvLZLAcgckRoqX0f7wzV6y/bQB/OZmJSB653eNlvU6h4UGB187kcShpDhcqUCBPCQqUwAABdRaKEtxdKkAAoOn2EAr5D7961PVQQwO57mB6SyV8/VivwjP+b7AsU8UyTCVlaCW1UfzSyUH5bEo3QBgNlBZAGRWEqATI2RbJUMpkqqPyoF9im/Ws1tx8/tVe3OBUfJWRfwO3jclOrKUFDgAAAABJRU5ErkJggg=="},71463:function(e){"use strict";e.exports="data:image/png;base64,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"},73099:function(e){"use strict";e.exports="data:image/png;base64,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"},39633:function(e){"use strict";e.exports="data:image/png;base64,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"},31434:function(e){"use strict";e.exports="data:image/png;base64,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"},16065:function(e){"use strict";e.exports="data:image/png;base64,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"},69035:function(e){"use strict";e.exports="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAEQAAABECAYAAAA4E5OyAAAAAXNSR0IArs4c6QAAIABJREFUeF6lmwmYXNV158+99y21L72qJbV2CSQzbDLIeAEMxMYGvOCw2NgmDl7izyaTOAPYk0yGOI7n8zIOZrBZBBIgBEJIYBAGKWBw4oUAtrxKCEmgpRdJ3eq11rfdO985973qV93VApz3fa2urip1vft7//M/y33NrrjiCjE8PMxglqNUKrV8rVartXzedd1Zfxd+hO/PP+Hr8dMwjH4123nh85ZltXw9mUy2fD6bzZ7w93V2dip2/vnnG60+tBWIVhBaAXijRfu+84ZQDMM+4cm3gtUKUCs4JwIzA8ibAfFmIJxo0bL7xCrCC8SPtb76+ForWNMBTYfzZsE0gPwpIOJKmA5gtkUHnveG6ogUK0yzpUqmw5oO6K3CiSuGgEyHMT004op4sxBaLVz6fhOML33m+tTnPvXnF6RTydOlrw6/uHvPTz79+WsH4iHMDWMGlOmg4oDicE4EZjbFsNWrV5vRCfwpICIlTAegF9/VWJsKmpXx8jNbL+3u7rwpafHTojd5vhyqlOu3/fDeR+/+1zvuKMfBMBGpZYiejoOKA3ozcOLhNB1MA0gcRitFxEMiHg4RiKmr3wXxxcugWRX/tmXdqSuWL/1qwrYv4QLAcyUAKEAZGEKAKQDqjr9r6Pjot844/0OPN6lFTKklDqgVnFZg4oqZzWPYqlWrrOhD3yg0pquhFYQ4ACWnYNzyza93X/KBc6/PJJN/aZsiVXMD5ACMMQAMJAWglI4OyxKAD+v1+o5d+1791gcuv25ndI6MT0HhIaBWcCLVvBUwqJYGkBOpojWIKSW0gqBkwKAAcO7bz7N/+C//cE17vvg3CVv01l0FUkoNQimo1R1wXQ+EwSGVTILgHKRSwIBBIsHBcYN6pebc+8RPn/l/X7n55kEYB2BcNHwlAtQMZ6gRUtPBtPKYuFoISAQjMswoPN4siEgJEQQVBAwgD7/YfN8FCxbOvymTtM7yfCzKfLrQjDOo1eowPDwO5UqtoYyEbUFHRwFy2TQBQ8VwziFhcag5/uDYxMT3//67t93/2PatDv0eIVQcEMJ5q2CmhxFbtmyZHa8gW8GIDDLyBlTEbBAQyqY7v7Pi7FNOuyGdSn1ECM4d1wOG4cE5eJ4HIyMTMD5eAilxwSSUKGrISzLpJHR0FiGVtOk1BGOYBpgGgnR3Huwb/Pa7Lv/EMxquUEyUZ4Ah4xWG0uHUrJgojCK1xKEQkLgyWqlCBUVKl1FoIIwpNWT0YwD4689f2/5XV171hWIx+9mELfK1ug8gtSKkDGBsogSjI+PgeQFgxGDoBAGaqj7wfWis+AxnDAr5LLS3F8CyTIKHRmPbJgS+VJVqddvLv9r1nSuv/+tXUCk6jCZINWxSh9R0xXBjlJ6fLYwQDFu06PzEG6niRCAwPBYvmCe23nHbFd2dnV9JZcwlTh0XGtCi8NKXy1UYHhmDWrVOIaBB+PTYNA0QXIBUEjzfh8APgHMBQuD7FL3e3laAQiFL74/UlEga4LpBaXyydM+GLY/e8Y1b7zzeBKYUQZoCE1fLbFDY/PnnJOnqh+U0plEMkbgqWilC+wTAjo33nLNy+bIbU8nEe6QECgmSK+PgOA4Mj45BabLSUIH2EUVX3TRNEIzreMFzICgBuK4LMlAgDITFQUkFiST6SxEy6TS9V/uLIOOtVN1DwyMj37vq819+ZO+hfrcVmGa1jKkoVSOYeAgREIQRrycQxnRVqGzAlMzQqSOMO777j4suXPOev81mUlcahmHWHZcWiiBw0WNjkzBGPoExw8D3PZCBBMMUBANVQZmmxYH/x/V8yj74DvQPBpx+fyaTgo72AiQSNmUjlAyBFRwqtdoL+/Ye/PZFn/jUz4G8RasEPWZ6GKFa4iEUQWFzV69OTcFoY2icTaaZC5gKtE8giGuu/mj2xs9ed117ofDFZNJsr9V8urIIAsur0iT6xAS4nkcL9oOAVIMnjPFvCGMaiAgKhjcjb8Grj18IBg3Z83wQQoBlmo3MgyFULOZJRaggPOyEie8NKpXqluf+84Xv/dUN//jaidQyPYQQCus+9VTSoPSbYRCAUBVRePzsR5s/3Dt3zv9Ip+yVjuOTT+CicRHoDyMj45RO8Tm9GFQNgB2GR/TelrKY5UlUAfoK/i40YIRiIARShgHFtjxkcxmqW/A5/Ixk0oJazRsbnxy983u333/3vVu2jGswZcVCb4lCaDoUAvJGMO74zteXXvTud38jlUj+GX4wxjj5BMfHHoyNTUCpVNHVJqjw5AOSsmUZZIZksH/igdcfAfueBkOQbVv7i0J/scl4k0myQ3oOFWXbBtRr7qt7Xzvwzxd+/NPbp4dQKyisc9X5mXiYTFfGP331b+Zc86EPP5HPppZUq46+CpRGJUxMlmBirNRQCsLBE8aTwSILv6N8SBl/Iozov1EY4WLRX1yXQlJ/jt0IQfSXYluBVCQVtgYMLNvGlO/t3rPvU++75i+ePREU9BTWcdK7spFnzAgTGbBfbd/2tUULer5SKtXo3BBGtVqjeoJMjwzTpxIcDyyqMpkklMt18gw80CD/q4cGqpsehIPhg/B9PwDbssC2Le0vgkOxkIN8PkspGo9EIgGT5dKvL/vkZy7be+CQx0xLxs02rhTWtmxNLkqrTZ5BJmrzV37540fy2dy5mEJx8dVqFYaOjuirBQoq1RrIQJ8UZo85XUXI5dJwuH+oqQCbqkWnFjb1XNjdNerVN3oPBQaZKdYuddelxadTSV3YSQmFQg7a2ov0mONzgT9536at7/mn791yhHGuZoVSXLI630oZCEMlA7brmacez+dya5w6AgE4OjhEykD/cByXTiaJ8SwwLTIwDIxdE9B0u7vbw6sazyRvVSsaFpkm09/xooyMjFEdQqEkJdSxQRScQjUqbObM7dKZCRjUHafyyI6nzrv5n3/QB6ymZoPCEIhMuxxrDMomoTIQRjLw+a+e/bdH87ncO1zXodA4emQ47C90NYpXRvCwhSdD06aWSiVhfm8PGe1/9aAUHCoCDXp4aASGhkcgmaA2jIBhuUN1EBp4CKq9owCJVBIrWnB9r/LE9iff+79v+WEfc0xJUAxTNjylVNY1S+H00wvSS/JWMEBK9vJPnnk0n8uvQSPzPReOHRuhD0Y4OkbDq9e4LpgRFGTzaZjb093oZONQ8L+dKOtoqIhAZ5cIMj5GIx08cgzGxyYhk0ro12K/HPUkDD1PSWVSYKdS9IZA+pVHHt96wS23391XE4ZkNaGaoYQpOf/f3l2UnstJGVIyFVg8lcTvPlcqwV5+btvWQi6/xnEdCDyPgOAVi0r0RhZAkYRnhieOV6ers2MGkGixVJ6HBVUzLEbSx1oDG0J8jy7S8LsE0zDgcN8gVKp1SIfdcPz/64ETg4nJCtUobR1tBMQP/MqmrVsuuu2utYeBcxVBYcJBk6Gqlps1yXJvO6dNeRgyM2EglBefe3JLW75wNinE92FoSANxPVfHhx52xXKAvqo9c7uhrVDQpXvzGYNTr8Pvd+2FSqVGvhQ/AilhwfweWLywl7IIKSUGxLIsOHiwH7zAh4TZGAfrz0fTr7tQr3uAv2fu3E7IFwv0mh8ElYe3brno1tvv6+fClQSlboTZRkPhmH2yJ5/drnyPg0oyZXs8qTQYUogt2UtPb3+kmM+d7ToOleHDwxoILioa+WFyiNShsK1XChYtmA+ZTLpJBfgaBwaVahX27T9EJT8WVxFUZEMwe7ogn8uSeSMQUgd+Uftvw+sHD5O5mmTkGgSey2S5ChPlKqSTKTCFgM7udsgVcnTd/MCrPrh585/dvvaBPmBcIRQmDFmtccXwcZR5sitWd0QZBU2UYKBaLJ8rafKXdjz+cCGfJyCYXo8Pj9GHV2vVEEiLDMIAFi3sBcvSDRgLh8j0TsahVCqR7E1DN3hR0iUwdGV7wDB4CER7EjVyDCBhmXDwUD95CZo5/v/AlzA+WYFaHesiBelUin53R1cbZPJZrRDfr2546OH337nxvj7uGgQDQdQYV00mm1l2RmfcNyQCCWGoIOAvbn9iU6FYOAuB4MliusMTLFcrLQ0TF4dynSxV6DsxiIUV/oxdL550Oo2m2JyG8L29vfOoocNRQKQQVA6ldNOAQ4cHqANGddXqLsGI+ioM4GwmA5ZhQHtnG6SzKToDBHL/g5suXvvg5j7GPckcVEYIJTRZ9BOWWfrOLgqV0EQxVKRlciV9DkHAf7l920PFQp6AoPbGxsYhQCDlir5qLQ6UN40DsEYIwynuM1hNYn2AVW9zWla06PnzeqBUrVFTF3W9GF4YLiZn0D94jEy3UqlDuarPKxpa4+fkc2mwTQvawrQbKWT9ho0fXLfpkT4mhCQoriFnhE76lDXdjVAhGDpUEIYyDf7Lx7dsjBSCV29yrAS+DGCiVKar15juxMCgUWI9cMIjli6joEPAWFt0dLTB+GSZlIQgEDAqBHsVZHi47yjUHeyb/GZTDvudYj4HCcuCQlsOrGSC/Mb3/OraBx68ZMOmTX1AQAzJXW9G6LDOVWfNIVVMCxUlDa7MgP/i8S0bi23Ft6NCcImT42UIcD46PkknO71twxOfO7cLCrkcgSMR6X9oVqpr/rBRC79H2Srafqg7DmWgKNVqD5FQLOShVqvC3n19VGu0ahlRUe1teapY88U8mAm7AeSu+x+49IHHHu1nvgziKiFDRT/BrNOxcnVPlFWmq0MFvvj5tkc3FAvFt2OlisVUaaJM8ToyNtHSQ/DElyzqpWYLfQAXGZkiehACw+coazReC1UQZhQMFfQfJfH71LAoX8jDxPgEDA4ep76pZbiGQJJJG/KFHAjT0g2o51fvvG/DZRt/9Fg/83xMt1ilNoUO1SYdJ50xt6U6DE+gSn62bfP9xUKBgBg4MA4NDGelrQorlP+SpQuolMa6Jbq6VI+EZX0EpEkBDVA6TPR7dA2CpTcWYvPmdcPkxAQcPTpKw6HZgHTSFkYCcjg4EmbUkVdvX/fAhzc9saWfCSNAKDp0PBnPOqx9xTnz4kaqfF+gd4AMOAL5jycevr+tUFyNQDDNVctVqkeGjo/OLLoU3rthwOIlvVCrYd3ih/GPpodDHYvCjUA2wkaHUGTQlHViIeW6PlRptMAgm0nCgQN9NCjCz5l+6E5CQVdXG3W+mWwalMD3YWr2q3fcu+4jmx57up8JGTAPYfgzVILt//x4mlUGFyqEAYYvfrZ1y/pCPlQIzULqdOWPYcWKC4tVmrgYO2FBb+9cKJWqNLOIsgRKHGuE3Xv20xXX/y/WyVJPpC0mGkFOlqpQoZGkXjq1+MkEdITV52xA5szpgGw6BclMEiRN9RkEnl/94bp7Ln/k8R19GsRMlXDDD1jb0rN6494haaCA6uBCGZI/v2Xz+mKxjRRicQ4OAQngyLFhvclEhZUeEOOVx1lIV3dHuDOngaDnJFNJHNfD6wf6wDAQjp6iTz/0wCmgLU6cdUxx0z2KZQrqZmc78PPm9nRCNpOizwzCDXXfD6p3rb/38oee2jYAvhEQFN/U34WQ3AsCqkuKq1YvwDSLRRhlltA7UB2mFHzHIw+uKxZ1yFgGB6/mguv70H9kCKQvsRZvHJgmce8km83C+MREwz8QXD6XIU/oHzhKNcJUvpyqUHDxONeo1sJRZYs5bFTIRfXNDJUoBfPndpN/4FaFK3WNQkDWrf/Ypqe3DbAISEwlXAQB1iUERAZCRHUHZhYNxhdmwMX2LQ/dXQw9xDYF+A5WkD709R+JVYf6tNA45/R00RhvfKJEGsdsgcrBITAoDcQU05oyrG7DOwFw2yE6ovFC9LOe2k/dPjGbqS7s7YFcLqsHVXjRqLwPqrffffcVj+94pt8TMgD0EPKSMOMYZkB1SWHlOxcqHzOKLsRUwEWkDhUE4ikEUiyeie1/0jRA4rDF8+BQ3yD1NnETQSC9C3povoqle7xL7e7uBK4CODo01rRbh4ui+aiHjRzoHoW+WGNLE0t0HAlMTJZhYqI06waX9hlsLOdCPp8D0zKg5vrUPyGQH9x915VP7ni23+OBJJWgKjD9IhQDwweBnPyORRQukZkGQkTqUIbgT228f22x2KaBoDEGPlWIBw710/4sbS6FlwrFv3DhPBgeHYcq3eYwVWV2drVDLpuBAKvbUO9MMVIZ9izoKTiWxAoXS3qEgM9hZsNyHiG9+NJvwzsGcFOsVY2sgSxeMI/2gg3ThKrj6Z1Dz6/94O51V/54x/YBJkSAKsECDRpA0Fc8yfInnb0Yw6VhpganUEF1IJAnN264q71QPBOHzMmkCZw2oHx47cAhMj9q/UMguJj5vXNhYOAYzjCnWnfcVLJM6kUik0QuGB4+SToiOmWy0SPad7FtMso9r+yjqx1Bi3bs4qGD71+6qBfaCzlghoBJxyWwgefXblt7z1VPPb99gAUi8DFsppsrqiS//Kwl083UQCAiECAF37bhvrva2trOQCCppAmY1R03gL37D+gsEBqfPnELunu64dCh/vDmmOYsEu3c44WpOwH1Km+0YYO/F+cqSxfOg9cP9tHw2jQFLJjfTT41NlGZ+hU0ewVYsaQX2op5vHcEJqo1bKy0Qtbec/XTzz83wAIZKiTMNqG5UtgQkFbhIrAekfyJDffe2R4CwZGdQduUCl7df5BSo96817dBYarr7e2B0fGJWYfL6BdYJOpZ7My3tdqQwIYP5xu797xGoYTgT16+AIZHJ+DIUZzxhvvBoGgT/ZSTl0I6lcDpN4yW8RxDhdy5/uPbf/oMAYnCJjJXjtUmVq75ZauXxmsPE0FguOB3JfljG+67o71YJIUgkGQ4wB0ZHYdX9x+msLBwd55xMttyDb2j2f/1JEyB47ngB9gQNvJGVIq1GEQ240KQqUQSclhsSUm9DCpUb58CjQqwCu6dNweWL+7VA2rOYHSyQuaMCrntrnWf2P7TZwcou8wWNrmlZy6LZxcMF5CSExDJxaP3rr2jva14Os5U0dzacmn6cAyVvoFjsGfvAdoISiYsUkmrXTpcAN411Crmm+If913QcKcdNKXnDJK27ksiRaA2aZzpuFTeY3Y55eQl5DHYDU/WHChX62TICOTWtes/8cxPnxlkXARNYRNlG+yCc0vPWRYvxiL/oPQrudi49rZvzJs378I6XXlFo/9CSl8lPLnJUhle3XeIehscAGO/grdG6ENXqfHbpmarMKeej+8raKlNZbFQegrntkChV63VaU6ycsVimNvdqUMRJ2m+B6MT+kYdBOK4zvCNN3/9mr379000A+GScQwhXcqz3Mo1y6kGiadbUoc21Rv/+5fOff8F53+L9mGw+6TbGwzIp5MU11H1fXRoBF7dd5Dqj2QyobcRAt3IzbrxH+6/RL9EF10CFDdA0fUwqRfBL6W0T1Eq933w3TqAV4dVS+bBycvm02gxCBS4SsFEpUbKiI50JgN79+3f8oUb/u5fMVQIQMxHovSLPqKBTKtOdbgEQmHwSTBu/T/f+NzJy5d/kjPBPNehkTGePDZauUwCTLwbSI/64cChQdiz7xAVZwRGxG6FoOGQ7m8wA4BpAbdTAIkMKDsDykyBL2zwmAW+EuAppr8CAF8qcANUnAIfv3wfuJKQTxmQET70pBV0Jz0wvUmwwNd1CjfAtGw4Njz08jf/7y03796/Z3wGEB5ISr9CBtOA6GaOapAmIEwoHhhf/sxn15x/zjuvzeUzK6sODn4AEgIgYXIyukwqSVDQXEvlKux+9XU4eHiAqlI0QG6YwK0EiFQW7HwRzFyRIEhug4c7awHQwvFGAQ9vyvMV+Eov3gsheLi5jY9x1kLvV+Bglesr6lnwpLKGDwvTLpxSdKFDVI7seuWVzd9ee89TY8PH64wrMlOgEJlmrFEZP6UQLpoyDHa7VIsgEIkJSRSybYkLr7vpizudhZegUrpSDBbnARZnAXoLBizuSENnxoKEwYEJAw4eHYffv3YUjEwREvl2sHAabuNNNLiVibdJ6IUhDLzyCUPR4rA8Ga9rVeCiEUQDDD2H/w/BhK9Hj1FFPkBdAqQsDsIZ3/3rbXd/+/gfdxzGbcBmINpYmws0GeBG1Qpq9+MVaphhpoBwIdBTOBenXX7jBfZJF900PDYOdU/SVbQEg5wtoDtjwJL2BMzJWXQbFWBbZAiwOAAOuAwOYAmAtIXKUmAxgJEagOMDtCUkdCYV1DwJfZMMBiY5lfmohkghjZCRQIogKKgUzGKkGHw/KotujwUjkYGB11956uDuF3ZY5WOjwdCe4fqR1ya0QmJAqNELAhoHvBUgzuKLFy869+q/uOi0Ze8KfN2MoSEaglHomAJ7ENybZWAbjEDhyMASCA33a/FngPlZBW0JbbbDFYD+EofOZABJQ89Px+sM9o3i/o5WiV44egj+rBcdqYRAIJCGioAuEtUmEmDnkAvYMGQM6aUMNZZWzuuqcuSF43949tkjv9o20NToRUAwxfa+99NLFOP2kX9ffwiUYjQgEoHgmZ50/aSLV/g9Z70/sLsv7MymUh9dEd2GoH0cgVghAISCX/QzPYeggMDg8wkToDuDamBQ9hAAAmGQMyXk7fCKBwr2jDCYdBBAGB5Y4ZJatGoiSAgClaOBaGD4PoR9vBbA74YdaDcFZC0BGcuATMKClC3AkvVxd3TgoV8//LV1pWPHqk0KQSALLvjkirYzr17nOO6RSqV0xAl8py6NQpXZC0vcmuczm0GtDllDwRVvy9GGUVSQ4hYMLt7GDSijGQjuv6IqSCEIywBYnFeQNPUesMUU9JUYmXRHUsJETYfg74cYuGistHgMCVx0zDviz4cqicInHIHA7lEX+ks+dCIMk9NX2mSQsHA+m6XyoTo88PyuH3/3fw3u+vnxGSFzyrX3/p05Z+VnKrUq1AMFVU9CxXOh5Png4C6ar8BmAFesykHa0rdZ4xEBofDgWhl4oz4uDOfVdqgQrSSA9pSCrKU95WgFoOowuiHG4grGaoy2Hmo+ptswXOjqB/hnVKSMcs2l0SAlFlQNtgW+1EoJFYSTml8M1Ci02iwO2RBIxhaQsAQId/T52uD+J53axPDIqzsP9e/acWwGkHzX27K9H/n6LTLTtaZSKUENK8FAwmSgoO4rkL4CLhV8bGUO2pNYKEVA9ELJM8IQISAIiExV0WPyEIEhBpAMp4hlV6daXChOVpj0wXfqwKULAr+UByaTkLAMKI8ND2z6Xan/ZX/+GgMkfVbKNCCfNKCYsiFtmaG/SBh1JAFJGgzaTAFpk0PWMlAh5frA72955eGbHmtkmZamKnXaTS9YVex639du8JMdF9c8X9S8AMqBglJYFKGFX7osA705g64SldaoClKBBkKLRmWQoWIIAdiG0JnG0BkHASo/AAsCaLM5pEQAfq0MoyPHAVM6joDQByw7AbV6tbpr956f3L/xgR17ei473Tzl4s9KV98VGXYI5E+d6QQs7chAPmHCruMuvDLiACqiGKojl0qCqBz7+R9v//hXmuqQOJB4HRIvzDo++PfvNRe845tVX5lVnIIHQEWQchVcsDgNKzsskjQBwRMPFREZKs5f8ariPXB4dyYLAK+2zCcY5/UJMLwyMLcGJgtoNIkhgQNmCkOcrlsWVqPqcP/AS5ufePzJF3+9cxBTGnvP9e93us69yh2tU5MjbAVmSgE3sX5RYAsGp/YUYc+YguF6ABmLN4Cgh2STtvSP71v7u/Wfu6tlx9uydDcEn/fn37lGzDntbyv1Gqv6klRSDRRIT8HSggHnLkjpAgzbDy7Asi1tnEyi3BUHrwK+M+ZVxgcnRvr7Bl975WDteF/9sgveeeHiBQvWmIbBsYOOT0UwZOgvIIQBw8eHX9vx3PPbHn3yyV16n4NJYFK5a/7nx5zUmkvBmfoLCxAKjIwCA//CnSswuAE1SEAguAZioKEybaq2gKTJ/ZGdT163b/utv8W0G5XuM5o7MAOO3e7c911/ZuZtl3y/5qts3fOh6mPISKhEYeMpyBgcurJJMis7KB9vV0detmpDA255dLw83Dd2fHD/xFDfvorrOKh9fc8mDlMVsMsu/sDKD1z03su6OruX630b/NsZBoZpweTk5MhLO3c+vf6hB35Zqzj45xANGEwyWTv5S+d53ed9GgROvPFu5fCWLRzl2QaAzXVc4s/cgbTB3DZTsIxtmhgyKSEhjaOK8cGnX/j+1V+NT+B1LxO2/6awjZ41H51fXH7eBbxjyRd8ZeQrrgt1X0ItVEdZcqgrAYB/KlOt1FlpdLcx9Mf/sHb96DfM7asAV9SWYjunH+s2lfb3cMWKhh0ExrYSxrVXXXnOmaef9p6knejwA796oO/wzge3bvnJ6wcOTYTupG8bYFIhDLpxi0np9rxvsdd5zpky0bEQuJ2jFlmAD4ZXAeaNclk5Ipzjh1h1YMD2q5PYcyWL8/LFuSuXZ7t7z83mimdYyhn9zeYbLh3Z84dJ7H5x2BwC0QMiwypYp1x182XJnhVf9MDs9ZQBTsAISNXzoeLUZcl1R51aab8a6d9pHvj331ivP3tECVw4x9uwsLTnOKeikQTCwCaYoOBKFAeOCsEuZmrMwTnj8+b0pCYmx9xJzKdxq8S9TymRIqpMUqJliAZXgANuRrcTMCMhQdYDkFwyfI6aONxLwDBTAcGMGjuTqVWX/8O75iw968vHfvvEV//w47W74lubM0aImXlLUl2nfmilUZy/JAAzV3MdWauMj9eOHzzq9O08poZfrQipuBJMT9ZwcMERAucKhxZxKA2lEAj8c0P6W0RdvOA6cZ4SG5EhAFwoHpJmZ/h2fZNaCAOfx3sDNAwmGf6Ij5mULIgWztHIcNMFgQUMvyOQ8DGm2/lnfLCDW0K+/tLTg03bmjhTpRFifEgkBY+m7rqElziloRkrNng4W8RpGj3fAHFCKBguXPe40Xy5eVZIW7CNcVN4T+MUCAUBKFzYlDJawGB4YzuXM9RBsMK2n17vAGX3AAABK0lEQVTHzpfLljt4rbYhcE832peJJmeYkvUogLxBoEpwBE6QEAqXePswKWFKKfgzSkjgUAl9RXtIQxWN8IlFCskjyucEAm8b0KoIFYNhgledwihQTPIAFaJhaLUEXNDssqGOQI8KAXftAhE0mjru4z2q5B966n7S2Yub7wmJDYoIgtB3AsRVgvuK+KSUOEzCP5/UUMhPYlCikAmzSwMMvmdqA3/6VBkhoF4IShMIDB+CgWGkFw4BU+QbpIJYqARSMvQQDBVfP4+qYH6Au/0EpLFRhbt30W1W0c5dPGww/TarJAwRAhSqIgodzCIRFBBMq0MDwmUpXDz5CllCLGS0KBBSdFA4xI9IEQSCbmwIF6+zjVZD9BgVg8qIGSkCY6iaVuqIngv3dsNbrP4/SaQQ/+V6Ba4AAAAASUVORK5CYII="},40181:function(e){"use strict";e.exports="data:image/png;base64,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"},81535:function(e){"use strict";e.exports="data:image/png;base64,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"},64813:function(e){"use strict";e.exports="data:image/png;base64,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"},362:function(e){"use strict";e.exports="data:image/png;base64,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"},16033:function(e){"use strict";e.exports="data:image/png;base64,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"},26358:function(e){"use 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TH+KqkOb29asZD5YhupOQxqyT/BTRyVh0hQwZbdyaIZfKo09KjE+atXCrVHRciiYPGEfwWN5eE8KhkoyKCTqY2w4bBHRcV6qF0JQF6Maji4BxVE1pNgE6eEqySm2uAs2cIuCBqivmpJCNtD51utO1DLQsbVycSHGSNWLMwA6sFILJfwK2QYQZVz/j9K/TF+ujxAWnLjV42zpTmZi4m71IA8UmOPnMnGWZ2BA3kzVYm6X8HNnG8e+9bz7Gj6Ij1+FfvOnm2eaed3KFnO1tsNGwz/irVuXxNXk2XTxDn8KLW3xG8AmxLQEd07jF9FiOZwR5bWDUIamjFicWYzwOCBoxi4mcM0eFmE6dW81M+ULAESWakwV6ltl1okRV62Bu86tjtwn6ASAkCKaCvAJwc4XDQIKKmpVsGIlB2SqAMhqQyeawcYOAHh8QAtogTkg72wrpl5JkaKdRlH3dHM2fhehc2ytT7kpVHSAn6sUBNbLj0a/RDM2hUGyI6heYyw4dD+HifebyZSvFUrs4d84rcw7qDZY0mmypOSe8fqOz/PYTt3/4XQSNlU0IodAld/Rpv7vcSJt7OoMeW++uls/SZYWugF17tSr1QQcKNP5FOyTBtoSAFO5SqKWcgPbdCVk1NgMUTCQ2odFvEAvERjkYlql75KKa1hjEohUD6A4bRCP5NsSNA+bhxIIA5jDa+Sdn4MhhuRxrKKjikJg3AFaullJBQAf9Qo4L45YnEVB0DLVhYO4LnDpTGhcRSlDJjCGebziDTcQhsWRD+15pEV5ipyNVCNytiU+Ik2YT6vz3zRU07jkJHuiiTplg6swePZDAgGolzmVbGH0YTrc8b86X2Yvldl6ZCzDPxDP02dYCa2ctNhwNVo7/4D/tjQFzfc5F9Tt43U2/s9De80He6fG1R9lo1BPL7olzjI1LpCZw8S8xAPset8UkVXBbOixSpgxVHKFsT2NqghdlpMK6RmhFBAKDGDIobUL7rWaG/mgJSVm8GB2IHNMBcyci04XyTREPyJUjgcux8tsIDCv5rPrwWyCLj8Gi2qZOmQ3+6jwchCs1VqbEAN3iB3BWXVavocjDBOSnqKZgwPbLcqW2jNhhYioFA/HFnAweByF4jQrrBO/2csvfEIoNRQH0IA+UKB4i4GNA0dUECGVOoiJXQZlX5OrVqMXLV9KMpWmL7Zk7TzCz0V1548O3f/hDBPUaTSLczCR96S+96VSWtQ50+x22vvFYeS5dPFNXl82IcKKBegx3HkPvZEDX9rUYmjBkwhw8Rod2YhlKKGqOi05IBFLGAnSi9/oqy7pj60BaO5YAHdWWE+craze7IbYdbyzmYs1qtq8AHbczxTH9KKBinaSCAZZKMshI6zwbqjvnIN1TJKee04RWq4xEB70YCkhRtMVSz9Z050U7lKlF9S0fLaw/tvmPpPdJNXKEwAAdGJiDeM7PnHMQl//yqlxcJJNmbG52H2s1ZniBfPr4337ggjqsU+wG0j1yzW/++szMeZ/m72BfPnuSDQcdbYNc9SxdZot8x55lPsyawPdYF8UoF8rf1veNnRe7YmPjo8qknFzCBomxsm/5Umc04n5zaGg80IcFqguqhLhfsrt1gK4pFnUG3JAmCdg/naCnAXodVyr7iF/8O5dx7kFvCS8ZaLxbLgoP53M+MOMyHd2AvQhFwYCOGDvKF9zGdQAdVE1h02piVGqVx4yrvyksU9V27gDdznZVIujxzfJji2NQgDCguyciEgnioqqrnpvzHe0c0NPGDNuzeEAAfrd/+jceuu1P/7zOHKPYzUv34qe+8cFmc+5It7fO1tbOiM1xskKXVXqiXtpS7HrHjrAZA40B6GFF1AP0cZ3X9hVv0kEdiGrt0qdhU9sVGZWsaIftoA2ep9ZHquGGlC7eglAeCcEqQUgXIFbo5ReFL40w1Bys0jzqcvqLD+SndVxJ9pGG1fvjiRvmOYGl9pJleDeFLQcJjG3FaESqpCVOQ5pq6b5D8gfEG7073AFQsTaAmgmaO2mrN2TC9oPYj9FaSPwQnfGrcw+YKzGpQlDsB9HSJowEcfl/XgALAC+em4t3nScZm1/Yz1rNedYfbD70wP/744uw2eT7nsKul/bhJ7/2he2lg7fwpcLlsyfYoL8pQV3cHMefqcsd7+Ja2PIIG6JJz9dU/eOKCLoRGOZjxyYpNRBwgjJ4M4FALzjqFx1ipdPGGRvQXU3p3AT1SFHyGKKhEwZCdgpPFmG9i3tpjN+mISCvC+ayX5UF6WAwlioD2YD31a+agDYokQAdUJ0hQ2SG4gXzGjaXrMEdveSsLxQ/LmBXgovvTKHhza9jGZeeCNgtoWFNPePRHJ0hPoVSZKbYFgHzauNUdb1rzl+Jyl+RyjKWZA2Wier8kDiT3j175voTP/n4V+pKTmE5SPui695wT6s5f3mvt8HOrj3C8iEHdHklbHkunYN5cYzNO48CCqboPk4BPopjqyMwVeM4dFqP45j++DEeU0FA91utEqX6LcoiFDPVdBosoXADDlIJRORZ5TWugHx4cmO2qCO+7DMhQHfRxNSE9TjI4B4C84I1Uy40o9QlqhLYSOU4YG6YHHNGe10Sa+9xmJobrQ1E19A/lAiMFxRo617e+e5zBMCSYT41QpDKQz5ANZGPhl6dK+fRnp/nWcpSvrudPzvPGmxx8ULWbM6xfn/9pw/c9qErxtE/lXXvGEeufvWz2jMXfpsnnMsrD7FBf6Oo0gtAF2fTiyrd3vGOTKzIeRehhyj4iKBbNR1bsfao4wI6RQqoCrD62ZqDE7Sw5eQwOJiroR3RKcqNdB6qR1TBHQkYBH0rCsY7zQk2cLNGVyGR4hfhUuulYyUNNyuJkerXPk7pJknw4wKHrPVBWOZYIaBTKRJVK23bf2sq0HIj9Wkdm4BuZJsbJGx9aIP5xJipF/Ps4YNvJOTyGh2ozHsmE9Z9nPii+6S2s12ePZd3tStA57fCNZpzbGnpsJBvvfPIs0/e+anvEEKHtwmFdZT+ketuur3VXLi21++w1bMPFRfNyCV3eS5d3vMuZS0mFmHJC9M7yliwAUSdog69n789hRKJfwqhSSoqMrGdLqBzwYDnqlPQiatC+Yk5VMGLjUBlI/ULzSAqsdG726J5RYVQUHMoGgc6ALkAoH9CmK72ZQZ+LLKiN/S8VI2tQoZLrAJoR1YKwCGTz3f2W35eWMX8x6Co4Sf8OWnyA1kBuZ/VcMqA7kwBTxbjTZwdR7cCEQHQ3ci8hYBuG9wAc/Gic8bEW9RSJpfc+c72BltYPMyazVnW76/d8eDt/+26uuZV/SihER3j0LWvvnqmdfBHvOHq2YdZr7duVukiGujXwsrrJEM/sQEJZdJp8MQF9LqS2QhmVCKF/ira8rcnAqDDvmZ+aoDvVgJ6cIa6X9adN86G1Vqb4vAqWAGiwTkg43iAXlcLVZBwLmUqcFz5gZorWC5nz494zuJ7lFJ4QNCfJMVHUQdIbFu6eSKc6NkO4fP7ALCjgE4Rj4qItllspdrVOX9ezjfF8c1w4sx5gzVa82xp8RAb8WK3f+op993xqTspLIbaUNlHxzlyzev/ptVaesZg2GErK7xKl3e8J+pcul2l+9FAAgU64iQb8NEwVcTBJEaNzD2FkMZaSG8UUk6gslHesI128QjRakZABO0MA6mhL4ogEQ7kNnU/wQEdYirMhEHTAAwEWALOEyG2RgU4f0IGdBzEy6BfJELeas7yh2DOb78wBokn1PnmvdymrMbdZXYjvwPmYjyoAzrFfB40PCFVrecwpTpDtjR0XozjG67OrZaSflFYqMHUAIQbB+HMguApjhCWvcqbgPhGOLs6l2fO+f+Xlo6wRtZm/f7qdx+84yPPJIyMNsHcBCWgGlx41cuPzsxcdG+SpMnq6sOs110vroTlR9lG5etVxY53PfgDs3ZMHyPzHNdw5wN6GVgpgnsusDC1MGlA9wMpkFeEpSA6ESHkGUNXb73Spg5Wpnk43S6AbsO5XWzYf1fi1ARzT9TRbeHfPGsF8DKQEw0O2AIGpRLBNfCqUELvA4pjARioU8gvaM82xi55Sm3VV1t58Zkrhq6RaoCQaBMBdG+2EHGmgIKI9jj2c3OukEIgcYmMWGqvqnN+Z3urPc8WFi7kj6Rzxs5cdvzvPnmcEpaxNhT2MRrl94eu+a2vt5tLx4bDntggx8SrVeOr9DF8jMxrfEObK1x1eAuECyoBJPu11ztId6eTAJ0vuVsJWkAkuzrnTbXp7vSsxHeDa1BzRAdym/k7Kl7CgO7hyuM6tj6MKz4LUsYzW4LTEkU3KOmADgVdGNAJYG6YTd9/AAtSelIgYII2qyO00q8Ivjo/Pl8rqi29X9EX8mvRrFCmDp7e2eLPmjTmxhAUc80I0v6qPBSw7OTfZCgK0MskrvoFzYOg/FtL1fRffVIYKoKMqgE5B3RZnWdyH5B4dl5U50mDLe05zBpZi/V6Z2996IcffT5hapOaUCGDRGzh8ldccP7C4YeTJE3X1k+ybmdNnkcXF85UVbo47ao7cNRuVRIr26LR2MqlEtA8DZ6X8lMHIENa8s9aEwxqAjoGprXB3MwSvBKG9AR10vkRv9v6IUUBjTKwJOgHdAd1HBYj4jHQV/aGMKUWmDuYSAdzDQcln9DSutOo3nSn29GzzF6YRQd03Q1UjNNto6aLjgeFoAQhNDsRHhLCdWlNT9G7eeOSZXgLAUM5i2/PQlApmhJRQFeEvMf/CisiMRe0m/qwFIK/fEXNWfPZuazOF9j8/AV8o/jozNqJQ2s//YtTBOOTmlAhg0SMN7rwmt/6q5nm0ksGoz5bWX6Q5bm8PS4Rb2IbujverclZ093I/EGhERtTKQlr52OilpJjOk0V0MNgQq3Q7SrG1GX1lyk2sMRZKDloC4KhsITCtqUTtH0JT4SzOMe3HCC0j075nYIgciAJgAHdCzqhwYCVHRM43VmiyEHH0ixMGHupWYvrZlLmqFb7AP5VkKqSMNvDVYFuPtAwAN1VcCCOVZoo8cPbmho8bENC/aieBThvmSWqlIXyYh6AB/sjiyX72loMDHwnGJwjiUXSZCRk+u4ulaFAgM55FpfHyDepqc1wHNCX9hxhWdpkvf7Zz5/44Ud/DeM35nuq5ck091950+LczMzjaZJlaxtnWHdzpbhkhlalU92HzBDQEPEPp0dEjAbZqqXkmE67gG7qneBEOwXQDcH4Mh4loSFODgMigFi7C+iFIkOArprYKKEpzwCE4g+FBQrqcJPtAnqpo+0I6Hp1rjJYfu68OKYmNsLx6nxmic3Pns9G+XC40e3uO3P3h1dx29NbxMAGmeqFV/7TT87M7Hn1MB+ylZUH2WjUJ1fphFhM5gNqOAmB/Tz6c+eocaMa+4uWihudYyJxo5mvj37nN6wVp+IO7Gyv2prZfmB02BcCToTbDiap119mxUnUJ5RYlmK61Q1IVXvr2iTmiQ4RenXsVsVFqYUNqr8VLvJmMxPgrKV28npqODSUOrV921G2n3m7qfrb2etAAnRMobo81LauLwkq1O68rS4k7Az+Msnbt7hWGOCDNJ8Cmez4FXoxuy0HCYhSbPLWFVt6QrWzXTxHV9V5gyVpU+xs57fEdTsrn3rk7o+9ZiwwIxSrk6F/443ti08cXUtZ1tjoPMY6G8vkKj3G72KZrR96KQUgDTRRHtAGgNTTUBoF0LVAC714xwFoJ66YjJegqY3tqsOcZqDo0YCOKdDcRkgKQIaZ3ETPuMPcEtLrAubAse7vtK9AtLKeF8xDoAAkJpgb6+MYeF0wVeEhZhtTLHg51acqCPzwTESXzfe7REXJu4bt5e/GHiKSJal6CPAfIoEZrBSkLpFCF1Z316UpjFQKiwZzO2ERpPQNj/79HmbSqy1plaZWdNS7ztXO9oaozmdm97CZmfPYiA0HDxw+vsC++MUuyfQRjeK0F0H40FWv++NWe+8bR/mQnV1+kI3yfrHjPfwsneq2OCs2pcDe7lAqhuInxHFYrcFvYy0yOYVZkVH/E2IKeh6G68JsUf1lgL8D6LBSrHCpz3Kve8Dq8iuxTDI0inFBCNaJ8eyVCuhlMIp1Elcdpe40M+rA4yjTpyJNGYrb2himAAAeyUlEQVQrG1TV5waIqwGMK2arFhLX45x7fDDXon1AxTRAlwJWSZP2dylajHxYWyg5sewetCEeUUGBnG6eWKHZW+mlbGl0ofm24SmYaoA9rJKdSmel75oP0g3pgoCuJwZiR5xenWcsTZpsac9FomLvdZc/+PBdH/9nRI1HNaNpL4pk2Ti96Np/vtHIGu3NzjLb3HgMPJdu73ivNlnVG9ScNjYN/zWiVT6t9bEcxfWb8WaIz491cENfOUtw5mhNOl5hZTzomLyB61o+MK+mlhuUIEC1YkPxp0Yd5c9egQwBOjxFvBeQmCEAVL2411kPAFordEK62US0eZW0enUzDpgbAAcIYM8tfazq90mBOQBsIX/AJ6GhX1s81F7F2EYyAys7YEfMoTUufAyRdICAsULiqPV7j1iKn60Cc2gcZzHDPJpoc+4+ltLjHO+r/tbPnfPqPGMzs+exmfYe/uy8+8Dt/3VOXJ06hR/UH8cZ88BVr337XOu8d/DAcXblITYc9cSVsNiOd8x9aTxBVDRAd+aA/MAA0FqAHqfSsrUThxQ/5SwyxZ6MkmBVhkSoOW4IzEOAXgKfN89CjQTKSEvO/Ks63p2ywWBXpCelrc2IQvIcANDB2IjE0dLTdcAJAY2uMM1pHYBDhBBkbJCz1tz1NpS5Tj7DDIcEejoFrGYHxQXAXIgfKyDBp2pddFlNvDLBhPUNzbGagSBoUNIM0J5f497hThdzDlYUwmBe2U32kNLbgK5uheOnH4pn50mDZVmLLS4dEZfLdLrLv3/yrj99J855vRY0DdajLXodvuYNp5uN9v5ef52tr54SVbq4bEa9uKV4eYvu5NOr0n2AXqmhMpT5wBd2XzRCoJqDAd3mR5HRxpvGfFLDTBDQqXorppnCb0dvOrRWNAHqEXrBkgzwxTAq9NWaOWMCuu0sBS9RgF4ucQPShwAd9GQ34Qkte9vkK1zTeSlS6gg7GhvSYn03pkLUAJ1ifvCJgUf/4UDhU4ZTBZDw2GhEkh+KOxEGokdBtKWEUcKlRnqKAgRZJxENLLWX0ddWg57Y8t9z/h9+V3vKcr7Dnd/bnmRsbuEC1mrOs8Gge+ahH/7JAZKQNRtR/LImadntwGWvevHMwv7P84FW106K16vyc+n8/75z6TCg2w6EsQ6DLQ1AXQd2qSGTzNHaOPxYgD7JuQRZNzYoBjyEqjcM0EmXZETqJcybwREMZ5gLAmkJ/6i66hkfww2+vmTPZVG1NOQELmqpgFWGS9oPvHqBArodi93D59XwFivGn8ByqegY67skQJMsiaYUDC0YtTUJJzAUbW8FoBMVF530UeSLm0hUQNftpVmwnH/GVVsYC/a7DQxfU9V99eycpfx95ylrtObYwvxBMas6aydfcvrez3yBopG6bTAx6tI1+h26+vW3tZrz1/El99WVE2ykroT1VOnS8c2sHWaEwr6iYwVPrasKTWCA90xOOPD5+PFPSFqCsU0AnRrrNWOZXfwEQGiLMW9NTw2JRBleB2ichULKItJAN8N5adiOEgG9gmaBJsascoTHDIwnIG4QlRLpSYM/gYCTXlMnehvAQiBAa33sIRwSsNVtucBWnsLRzFkwHUMeEAB0ipNiQwK+hWdVGFF8NlQtKEJoMTBQoMP5WfWpcboESwCLIcHrkAUhrgNtZ7tenSd8I1yDLSwdFpfIDPprtz9050efGqOVOm1jNFmHvujDr4TdO3vBQ2mSNTrds2xz81GgSufXwXIFqSU3CqATLaJxDvtuAIjJgB4L5pKpss4putsh0wHESc6jkEVtcWqOSwF0bbrV9rFxOgbCJZksZYe1bmt1Jzw6AeEIVYGkwSEAdsbRQi1M1wBzjFeb1XIICE9NVCfrGW3o1ZcHBQKA7iNFBXNXxMAk0omCzYBMxMu71db4U4KQ8RPSmd4QMihqEKxBICkL6cGKy+G8zD6Khl9FXKYPPlVqQCI2ucqL28USu6zOMzY7ex5rt5bEMbWV7tlDqz/+xBlMG+N+j83RcemX/fc/+VVvmZvZ/0dcP6trJ9iwv+l9ll5uTCPdE04XAWwJIryL4q5vqU+w8cNIuG0BfUKWl9JjOohPzCbEnkMGCHekoYQXBF3B3L8RD+gu8WCyBIFoYQq/L/tEDb/OBxIbsnj1GeEZaEiXIXcCI7s7nzFAmxyYE0Hcdwegr3sg0XN3HZbwZBm4IBIdwsLzmTRhfJMFdaZQsgLNQUmwmp84mEO5puG70K1wxrPzjGWNWbYwf0iM2+mc+b1TP/mz99L0Ml4rzJTjUbd6H7ryN+9qthauHAx7AtTZcFBcOMNf3DKSL2KYYpXuFRZ1IgySIDVRnB52LsojgIkaZorEMECvVE9zxbqAO0URS9JhUAcAXXue7uUPyRSMQKMTgTDMwdEIHw0oUFkOowbyihrU9gsEnBWfejeMMQscwRw/kK/531CHgTnm84CsYMLiiT9GUlf9YZJALtJxRMCUGZppmLxFX4/JK8oxPNi715GjaVb9UY6ko7zxEhZZnSeMv01NboJjSYMtLh5iWdpi/cHa3Q/f+T+u2or4g9YUk2Zi/kmvPbh3buH+NGm0+oNNtr72sFmli92L/OIZ7fjYBKp01I0IgA7ESkQ9FKfbGYCuS4LqEtSKe5repROmbGuzHh+T9miT3jiA7pNHbJwNlP4OSBpB3JJ3CoAeg5ve5CNolpqAHmNqAqCH/C0a0H0Zg8MzLYbAU07va84/cO55HTA+8sGqj5ix1AyRcpzPSpqr1x+7XJrgLb83q/Vce1uSej1qKgGd39kudrZnojJvNGbZcNTvLW+sXbL+s0+cjHHHcdpGaHmcYaq+By/7Jy9ozR24JUnSpNNZYZsbZ7QqXQI6VyN/7Xu1dMT/wJzbL8qkhcQ40VwBUZpv+Scwu2iDT8ZYBZXxAd25BNOCKE+VEACnSdt0XIXhMTpcocPyJPIkDOGnekxVNbYDlOk6IUdyajgvBzGAHgih1lcVVSE/VCVan6k/ieoCMjH1UeiuCkAN3pfaUHZuVdyWRV900uWpRozi3qr0oRMCT1BAt/NhFNAtVUlULz70LrUXV7yKC2T2s5n2EsvzUd7bOH39yXv/51cJ03diTWr5/7ijH7jsVW+bmdv3Ln5mb2PjFOt2z4KXzcQ9S68mpM3ftIT0h0QK6kqu4AJsfEAH42BNw0HS1NcpkB4Eyx9/Klefh5qKKLu58FEH0HXbO7IUX1I8SbFlH+cxqwtdjz6qvrQC1he5kMLUjRgSqpz0UzD01MTDiDY+vKfFL4DvdlonwYINLGOAR/6Kdpy9hKVtQLdIODcdevICKXnVWZcXjl2QriY8Uy1yDvVgdgcXUbqPGaoyBFYjadW5dsVrq73E5mb5MfOcdTqP3Xz6nj97N+b6k/5+wpqms3fBL7zms+3WvpfloxFbW3+YDfvrjPF3phfL7vqVsDIw8f9Sw5uW+dJZqtXS5Qjj0VQ5DdA95QiQudgGtYN6rJCxoSSKPtH7oMAW3qYVxUWNxlIrDg+IPKq9ughFD6pGV80pMG/SmR8P0P3ME83kpDvqAz3ZodLS5fYBOnXuodHAA+ghXrF5hV7ZrK1RBc/ug8IjnGl9fAkHeHWxTtZENfRa/TC4U62OT0XKaZIwFckLp+P4j7E6Yi2VgMfU+CtRZXXeaM6xhblD4h3ovd7yZ0/++BOvwKWZfIvJaboGbwd/4XU/aTYXruA3x62tPshGw5522YzaIGc/T48JcdMP+9SgItUDqzsM6h557Y9DL1mKUZllx6kAeqzXAbdr1bEsGqCJPgzSQcG8sn8Q0D2RkWZC/XW29vO/UIUeZj7GXBCfSiSS3ozKUhrExTRTzrIVMCecpAKag5GATn1nzCRAHUscTJe1lcdjqOvULiiGZwZVXrQ4gYahOXYJwpU0BTBraSSNlF/Wys8sShy0hRJUMpAwlvIIJI+ppVmbzS8cYWmWsX5v/Z5HfvyxJxNDycSbxczViQ9+8KnXzyf9I4800/bCcNBlq6sPiufpefEcXW2Q0yBdu3CGaj5ARG8mWk9Ek5N4CAxnt3E82dLGBQR4LF2iaIchdFBT06tHmqm9iqqrXzuQeUWJkFFVB+YrG7VUb0sAfTyfCvWOAXRbVNtXFS33MjkdKpEjcAZY65y7X+gQgS+D4zqU/Iec1+TB50b0OWy8uk6OvoWAXvk2oOdwzoAq01zNAoyqZX3hcFH1BdtZCjP3cNhL7cUmuMWLWNZos/6wt5Y3+xeevO1j66hAU2pACEVTGrkgu3DFy56y1DxwW5o2ssFgQ+x858fZ7KX3es/TPbdxbzNAhydCPb1PA9BVWKrlLGinqtZ2JxhQrtVQy/YA9EoRYIVu6AlWGp7XUCv0OCWiJtTIoYDuBVgT+vS46l4aqaIBwT8C44k0yvnef06ZDqxSIVsK6A5zxegooGPWhat8nwd5q39sGCT3MW9VDAN6mFQA0AEd5uXavPWuc+44WYMtLBxiWWOOv3RsuNk//dTH7vnLH8XNrsm2pqh5siMC1M4/+vKXt2YPfCZL03Qw6LKN1RNsNOrJKVE8O3d3vWPZrxzIWJodM0v0KQKv0HE1ly3wpiR7cDJa0krqE2pULTgRSSFyaPBmEAR1iSMZyNTEdOpFKaIuLD8UF0vZYEJk1qsKLRiVla1ij4B7IUliXBIFdDWQgaXSW/V4asigEy3QXbYlOEYUoMvGk6jOzeiE8Wkne641wskEtEqBjakZIujGkYAug672U/xh/gOvWwRYrgA99GyxGtb3uKMawvZqU4faCrt5vWtxI1yattj84mFRmY9Go9Fg8/QrTx3/7GfpEWE6LWPm6nQ4KKjuv/Qlz2/OHbqFXw/LwXxj9SE2HCpQV2fTtWlCOp8eAnQD8uj77QJaUM6SGO5q/uXrTijQ6umfOq/rUYd7YUGUoEPZhHCjWIAWHJihyDJdJZmb4STDkwd0N4TZUlHwD1InNUiEtOjcW6+ZIRcIYGYdJaAbRK1n5xSBLHNX8lVf6Em/F8z10OPxOQAiipZU/0ISCjUuoBOTpbjx/FNI0gknE25v3w76QrpSJw6XANtmnovc8qb1t2dD+RWimjJR1I6oifnKGUnky1f461DnFo+Ii2OG+XCQbzx8/SP3ff7rkwyhdWlR52pd+lH99h598S/NtQ9+J81a7dGoz9YFqHeLwO4D9bCFfFermr3MYBLFNLExNsUcQ0zCMtigRN7JzcYAci1emkGwpgyCFVuHwe3EYLT0hu465qmGdwOT/l1I3151+N6iphEL4x9E2QzBmB+4FKoU19nR72SwBXjoQVknqKFKGXQxhkAwN51USQj6C6C7eu4I9LI/AjJ6211hUHJeX4dpBbujWJe6/J2SO6nGfkA3Z42WLsiuCKDrSTCYPHkAncp7eUokCOZtNr94hCVpg42G/e6ge/JZp49/4e8ISt+SJnXi0lQZ23vVi47O5hfekWXt+dFoICr1wbBTXjhj3CInnIBbEZ5m9nI7FJ6qnuNVgxSlhILBxAC9XsShsI+3cQIo4F5aMWYTnGSSBT7Lo3h7MJX3AFyxCuiovsIz5yIdB0BK3VGYtD3eXRZ1sBAMmEYElObwOCKFqxCgK9oUOuW0LnMsY5YGl9rDwOx5Zh5gynaHetML0DM0myw+fJegGMc4g/5KGCQ4qy29e0DXJmHMPe0P+2SKH9DlN278lvaDzKXle8beBT+YF6M7iZVO3Xxu3shmRGXOwXw47K53kkeuXb7rS8fxwLh1Lajza+s44m9nu+LGAwvJ/ruyxux5fMf75toJ1h9sGKAO73xXHgccaiodAcoSi371ZitZN1GADgZXZKgp8x8c3fd+ar2Trnq0aCka1JSpNqATglYFGtjhOZ150+8c/gqi1AlpJz/GJjLLUHDMp9xkpgh5Epnia7+JnGjpJA2gSxjZSASYl8Q8WtQ+VhLZdrDzTV13YMLCP/SOG/JhXDf2SQg3v3F3tYcjBNW7dCqWpxHmIwzovrH9KwxVDx1YXUCHky4PYAvR4sG82ZgTYM5HHw07j62OTl+1ds8XT5OD/xY1rGPhLWHt8OGnzw3nr/xJo7FwmFfhnc0zrNt9rKzI4Uq9Yg2aY1BYqpyB4KlUyT3ANVVAr8k+grFUiYHMGXCtwGBgsCSAa4hB39IfKlRAl5VfhUGOzlfR0iotA+EPIG1W6AYegjpEkiVn8LphAlJkDC37mbnfIRxbA1qC/EHnRv3u6M/J97UWBqB7rA76EwXQ+bNbV18yebNtSAkAMbov0wdHKGwJ21ehe6HYYL36AwJ0a5pU8Kyhuicf1OQANvoJplVPPYFIWLt9vrjSlT9IHwzWTmTrdz/5xInvb6Bx5Bw0qGPhLWTzWOOCyy/4v83WnqfxQfu9dba58Qg/IiB3xeovcRE+Lg1iCAVk5W7+OeHl9khA9xohxjqU+QwFOcPNxzCts2s5brBtBeiBREKZBAq0VO2ZAU/vFWNw04t9Fboe+6se9LPbsk99vlydRNDSd7QjGySlTp3Jbgxvjuy+dUuR8OFl5aMe/dmikYAcsL8uBgnQKZO/IKrjFtVhrUea0wN0U46xAR00E1CdlzqW2ZnyJb60PsdftNJcEJrq95Z/cOqnp36ZsVs5AG3Ln4jZde74P3DJP35Hc+7Azfx6njwfss31h9mAXxVbgLrxRBG5DUQtkpquM0FAhzQaWxApVcdYhzKnLRMGWI0zNmW5XZfJ4tWxhZtxxfFTtAartjF1qoK+sTPajskxhSlUckRKKwHIgBtBoRaYO/gdo7CA4Wr4ZyVDuLMB5lY27+Pe2aRX+mdxKsXaZGieha8jjNbH7m5XINMAdGhDaLQYmo8F+katjBl0qj+kCor/lvoAXpxjX9dq7ahykw8L0D1g3mjOs5m5QyxNG/z20nyweeZdp+//X78fOTW3vHnd2brljO67+IbntdoHv5Q12nN88F5vmXXEm9oGWixTyKl5iSOhB8ainRtQQUibxKS+pBpjmZq8TwfQ6YzDbAOf1pRPi9EK4k2jYawC40r8NZ+d18bk2h1NMRSg2+yCwYyiSxtgas1261yvRgNTu2pqJyo2G3BVDr8tzclTAI9w9KcNSAN0j3IxnU8b0EmnO6hGtgARCoOQ/wSDjasgCNChHSt6T+jsuQ/QxYJPucyuJQ5Jg83OHWCt9l6BK6Nhd6PbOfmixx/48jeoGjqX7ahz61zyWI199NjMAXb+Fxsz+45x447yAeusn2SD/qoL6iK95++vdcKAPk3L35XhaysE67jNAH1iYF5EyooepojQkf9A5MOCIuKh6LGwCIXw5Xa9OYTLXi0gYBkrZhFewSP7xm5oAyUDytL406Wk86WS6moMra6byH0Plb4NZqt90fbHNaKXARRQFekopAaYQ7HJEan6oBxBZjpSKvNDK2FF5iLFqDoJbSydBUi9lD0NkIeoz+AjauFbJSFxXD6rd5rrYM/5bTQX2cz8QZYmTXHN0aDz+K2n2aM3suO3dmq40Dnpgkffc8JWeNC9F9/48vbMgY+naWueB1f+bL3bOcX4ffCWl3uOtHGxjTBjBJpaSsHmjmfygN1iGaBMTEulEfiFe0BBTM+qfZ38rBKEIDQJMmvwqbe0tGG6h0NSrwxVTxXA6gK5PQhVVP01nTbulGCvEw8R9pwECecCAEHond5UgQAD+nMg+1lP9VwcsoP9mRcALB7MKs9NWJwshSKrb+LbCZX2d4Wn2gC+sSgxBOPTGyTMW/1AQK+QWfuaYoFyob0sxmhxBRbGycW0zW95cVF7o9Fm7dkLWdaYFZsQh4PN9e7Gqdctn7jlnN/8hgdfK4eL7bB92h9r7D+67zPN1r6XsiQVNh/0Vlinc5qNhkMTyJ1K3QJ0yxcoc6HUA7GxbyPJuQB0H8vY/PbangjoYfoRo0c0ddG4+qTSQxygy7OwZpjBAZ3oKEBK6k+OzMDuBK/qQtWKREB3ziqGznJgg5GTL9hjYLuoPAKK4YNq0wHd3OSmd4vxd8U6dn5Z3ydmv/vcGY9seuuctVbmmpXm9gd0A89L+c8xoJfOxPWXiOfj7ZnzWbO9V7Cbj4Z5v/fY584cX3nldt74FsJgsqttHyA3OVm6/IYr2vnCXzQae6/luD7KczboLbPu5uOM3zZXZs8Cwz1Z3C6gS4eua+SxAT1y5MjmhlhGBRSsLYLaULvcFTnoPLMg4A1mYAnjWCEkqv7+c6ddWUjCFTSkEyfBoQK6F1+gapbuZH5ANxyuIGhV5z47e3il5yCuTBMBdM2BKpephAABvW51DmV+lElS9sMrdBjQabZ3rkU2JxJIJHh3uz4584QlacbaM+exRmuvnJ45Y4PB8h3dZO0VZ3/65XtoXG7PVjse0JVaz7v4xusbzcX/njWXDqmXugz6a6zbeYwN+U1zRnCSnqn5p8+dcatRNBhzSohCz+YqAuBC5CPImBwYRP2XrXjSKUlLfTll+e3Y4B8uzIi97G6Dj4njEC1MUMtHNY0bwSv4Xo46FvW//AJfejauexojQyymqx/RwbOpxioJhPman+maseOAX2twNqAnVkYO5/wBhBMEyFUPCegWZxCjmFsZgc/5Q2PQT8iWNxQk0XzW6uy7Hc8XVSoVuMqQm96qnyybYe32eSxrzKvL2dmwf/bhQf/x1z/2wFduwYP99m9BMf/2l0LjcN+RG17SbO35z1lz4ah6bRIH9H5nhfX6ZxljI4kd8vVt4A9ZKdSG0wZ0Y9a7IoGbXAmFW5ThjYoIVowX0O0vqHr1MYjhmK96QwWuOuqBCn75SkHMc+hcYZVZedkM+F64UjlUuNiS35rqtKo+e0if7oPPxcMJMqpWJ6grpjFDWZIBIG6cSirGMcCcgJGym7+hF9AxPy6Yq3wpAKK2o/h8PIigRSdPJeNOQ5cfezUCs61BwSue/2RCRR9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);background-size:100% 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diff --git a/umi.73986acb.js b/umi.ce4030ce.js
similarity index 99%
rename from umi.73986acb.js
rename to umi.ce4030ce.js
index 041d3df364..7ec093164d 100644
--- a/umi.73986acb.js
+++ b/umi.ce4030ce.js
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r(e,t,a)},_map:"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/="}}(),n.enc.Base64)},52695:function(e,t,r){var n;e.exports=(n=r(52952),function(){var e=n,t=e.lib.WordArray;function r(e,r,n){for(var a=[],o=0,i=0;i<r;i++)if(i%4){var u=n[e.charCodeAt(i-1)]<<i%4*2|n[e.charCodeAt(i)]>>>6-i%4*2;a[o>>>2]|=u<<24-o%4*8,o++}return t.create(a,o)}e.enc.Base64url={stringify:function(e,t=!0){var r=e.words,n=e.sigBytes,a=t?this._safe_map:this._map;e.clamp();for(var o=[],i=0;i<n;i+=3)for(var u=(r[i>>>2]>>>24-i%4*8&255)<<16|(r[i+1>>>2]>>>24-(i+1)%4*8&255)<<8|r[i+2>>>2]>>>24-(i+2)%4*8&255,c=0;c<4&&i+.75*c<n;c++)o.push(a.charAt(u>>>6*(3-c)&63));var s=a.charAt(64);if(s)for(;o.length%4;)o.push(s);return o.join("")},parse:function(e,t=!0){var n=e.length,a=t?this._safe_map:this._map,o=this._reverseMap;if(!o){o=this._reverseMap=[];for(var i=0;i<a.length;i++)o[a.charCodeAt(i)]=i}var u=a.charAt(64);if(u){var c=e.indexOf(u);-1!==c&&(n=c)}return r(e,n,o)},_map:"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/=",_safe_map:"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789-_"}}(),n.enc.Base64url)},73323:function(e,t,r){var n;e.exports=(n=r(52952),function(){var e=n,t=e.lib.WordArray,r=e.enc;function a(e){return e<<8&4278255360|e>>>8&16711935}r.Utf16=r.Utf16BE={stringify:function(e){for(var t=e.words,r=e.sigBytes,n=[],a=0;a<r;a+=2){var o=t[a>>>2]>>>16-a%4*8&65535;n.push(String.fromCharCode(o))}return n.join("")},parse:function(e){for(var r=e.length,n=[],a=0;a<r;a++)n[a>>>1]|=e.charCodeAt(a)<<16-a%2*16;return t.create(n,2*r)}},r.Utf16LE={stringify:function(e){for(var t=e.words,r=e.sigBytes,n=[],o=0;o<r;o+=2){var i=a(t[o>>>2]>>>16-o%4*8&65535);n.push(String.fromCharCode(i))}return n.join("")},parse:function(e){for(var r=e.length,n=[],o=0;o<r;o++)n[o>>>1]|=a(e.charCodeAt(o)<<16-o%2*16);return t.create(n,2*r)}}}(),n.enc.Utf16)},28492:function(e,t,r){var n,a,o,i,u,c,s,l;e.exports=(l=r(52952),r(49479),r(83760),a=(n=l).lib,o=a.Base,i=a.WordArray,u=n.algo,c=u.MD5,s=u.EvpKDF=o.extend({cfg:o.extend({keySize:4,hasher:c,iterations:1}),init:function(e){this.cfg=this.cfg.extend(e)},compute:function(e,t){for(var r,n=this.cfg,a=n.hasher.create(),o=i.create(),u=o.words,c=n.keySize,s=n.iterations;u.length<c;){r&&a.update(r),r=a.update(e).finalize(t),a.reset();for(var l=1;l<s;l++)r=a.finalize(r),a.reset();o.concat(r)}return o.sigBytes=4*c,o}}),n.EvpKDF=function(e,t,r){return s.create(r).compute(e,t)},l.EvpKDF)},24408:function(e,t,r){var n,a,o,i;e.exports=(i=r(52952),r(93617),a=(n=i).lib.CipherParams,o=n.enc.Hex,n.format.Hex={stringify:function(e){return e.ciphertext.toString(o)},parse:function(e){var t=o.parse(e);return a.create({ciphertext:t})}},i.format.Hex)},83760:function(e,t,r){var n,a,o,i;e.exports=(n=r(52952),o=(a=n).lib.Base,i=a.enc.Utf8,void(a.algo.HMAC=o.extend({init:function(e,t){e=this._hasher=new e.init,"string"==typeof t&&(t=i.parse(t));var r=e.blockSize,n=4*r;t.sigBytes>n&&(t=e.finalize(t)),t.clamp();for(var a=this._oKey=t.clone(),o=this._iKey=t.clone(),u=a.words,c=o.words,s=0;s<r;s++)u[s]^=1549556828,c[s]^=909522486;a.sigBytes=o.sigBytes=n,this.reset()},reset:function(){var e=this._hasher;e.reset(),e.update(this._iKey)},update:function(e){return this._hasher.update(e),this},finalize:function(e){var t=this._hasher,r=t.finalize(e);return t.reset(),t.finalize(this._oKey.clone().concat(r))}})))},28209:function(e,t,r){var n;e.exports=(n=r(52952),r(41988),r(79183),r(73323),r(35909),r(52695),r(34905),r(49479),r(2481),r(93653),r(12133),r(82307),r(79421),r(25824),r(83760),r(37248),r(28492),r(93617),r(2882),r(98277),r(69972),r(30509),r(79182),r(74990),r(2593),r(10829),r(10265),r(18846),r(24408),r(84452),r(61945),r(22528),r(21865),r(35308),n)},79183:function(e,t,r){var n;e.exports=(n=r(52952),function(){if("function"==typeof ArrayBuffer){var e=n.lib.WordArray,t=e.init,r=e.init=function(e){if(e instanceof ArrayBuffer&&(e=new Uint8Array(e)),(e instanceof Int8Array||"undefined"!=typeof Uint8ClampedArray&&e instanceof Uint8ClampedArray||e instanceof Int16Array||e instanceof Uint16Array||e instanceof Int32Array||e instanceof Uint32Array||e instanceof Float32Array||e instanceof Float64Array)&&(e=new Uint8Array(e.buffer,e.byteOffset,e.byteLength)),e instanceof Uint8Array){for(var r=e.byteLength,n=[],a=0;a<r;a++)n[a>>>2]|=e[a]<<24-a%4*8;t.call(this,n,r)}else t.apply(this,arguments)};r.prototype=e}}(),n.lib.WordArray)},34905:function(e,t,r){var n;e.exports=(n=r(52952),function(e){var t=n,r=t.lib,a=r.WordArray,o=r.Hasher,i=t.algo,u=[];!function(){for(var t=0;t<64;t++)u[t]=4294967296*e.abs(e.sin(t+1))|0}();var c=i.MD5=o.extend({_doReset:function(){this._hash=new a.init([1732584193,4023233417,2562383102,271733878])},_doProcessBlock:function(e,t){for(var r=0;r<16;r++){var n=t+r,a=e[n];e[n]=16711935&(a<<8|a>>>24)|4278255360&(a<<24|a>>>8)}var o=this._hash.words,i=e[t+0],c=e[t+1],_=e[t+2],d=e[t+3],h=e[t+4],m=e[t+5],v=e[t+6],b=e[t+7],y=e[t+8],g=e[t+9],w=e[t+10],x=e[t+11],k=e[t+12],P=e[t+13],E=e[t+14],S=e[t+15],C=o[0],j=o[1],q=o[2],I=o[3];C=s(C,j,q,I,i,7,u[0]),I=s(I,C,j,q,c,12,u[1]),q=s(q,I,C,j,_,17,u[2]),j=s(j,q,I,C,d,22,u[3]),C=s(C,j,q,I,h,7,u[4]),I=s(I,C,j,q,m,12,u[5]),q=s(q,I,C,j,v,17,u[6]),j=s(j,q,I,C,b,22,u[7]),C=s(C,j,q,I,y,7,u[8]),I=s(I,C,j,q,g,12,u[9]),q=s(q,I,C,j,w,17,u[10]),j=s(j,q,I,C,x,22,u[11]),C=s(C,j,q,I,k,7,u[12]),I=s(I,C,j,q,P,12,u[13]),q=s(q,I,C,j,E,17,u[14]),C=l(C,j=s(j,q,I,C,S,22,u[15]),q,I,c,5,u[16]),I=l(I,C,j,q,v,9,u[17]),q=l(q,I,C,j,x,14,u[18]),j=l(j,q,I,C,i,20,u[19]),C=l(C,j,q,I,m,5,u[20]),I=l(I,C,j,q,w,9,u[21]),q=l(q,I,C,j,S,14,u[22]),j=l(j,q,I,C,h,20,u[23]),C=l(C,j,q,I,g,5,u[24]),I=l(I,C,j,q,E,9,u[25]),q=l(q,I,C,j,d,14,u[26]),j=l(j,q,I,C,y,20,u[27]),C=l(C,j,q,I,P,5,u[28]),I=l(I,C,j,q,_,9,u[29]),q=l(q,I,C,j,b,14,u[30]),C=p(C,j=l(j,q,I,C,k,20,u[31]),q,I,m,4,u[32]),I=p(I,C,j,q,y,11,u[33]),q=p(q,I,C,j,x,16,u[34]),j=p(j,q,I,C,E,23,u[35]),C=p(C,j,q,I,c,4,u[36]),I=p(I,C,j,q,h,11,u[37]),q=p(q,I,C,j,b,16,u[38]),j=p(j,q,I,C,w,23,u[39]),C=p(C,j,q,I,P,4,u[40]),I=p(I,C,j,q,i,11,u[41]),q=p(q,I,C,j,d,16,u[42]),j=p(j,q,I,C,v,23,u[43]),C=p(C,j,q,I,g,4,u[44]),I=p(I,C,j,q,k,11,u[45]),q=p(q,I,C,j,S,16,u[46]),C=f(C,j=p(j,q,I,C,_,23,u[47]),q,I,i,6,u[48]),I=f(I,C,j,q,b,10,u[49]),q=f(q,I,C,j,E,15,u[50]),j=f(j,q,I,C,m,21,u[51]),C=f(C,j,q,I,k,6,u[52]),I=f(I,C,j,q,d,10,u[53]),q=f(q,I,C,j,w,15,u[54]),j=f(j,q,I,C,c,21,u[55]),C=f(C,j,q,I,y,6,u[56]),I=f(I,C,j,q,S,10,u[57]),q=f(q,I,C,j,v,15,u[58]),j=f(j,q,I,C,P,21,u[59]),C=f(C,j,q,I,h,6,u[60]),I=f(I,C,j,q,x,10,u[61]),q=f(q,I,C,j,_,15,u[62]),j=f(j,q,I,C,g,21,u[63]),o[0]=o[0]+C|0,o[1]=o[1]+j|0,o[2]=o[2]+q|0,o[3]=o[3]+I|0},_doFinalize:function(){var t=this._data,r=t.words,n=8*this._nDataBytes,a=8*t.sigBytes;r[a>>>5]|=128<<24-a%32;var o=e.floor(n/4294967296),i=n;r[15+(a+64>>>9<<4)]=16711935&(o<<8|o>>>24)|4278255360&(o<<24|o>>>8),r[14+(a+64>>>9<<4)]=16711935&(i<<8|i>>>24)|4278255360&(i<<24|i>>>8),t.sigBytes=4*(r.length+1),this._process();for(var u=this._hash,c=u.words,s=0;s<4;s++){var l=c[s];c[s]=16711935&(l<<8|l>>>24)|4278255360&(l<<24|l>>>8)}return u},clone:function(){var e=o.clone.call(this);return e._hash=this._hash.clone(),e}});function s(e,t,r,n,a,o,i){var u=e+(t&r|~t&n)+a+i;return(u<<o|u>>>32-o)+t}function l(e,t,r,n,a,o,i){var u=e+(t&n|r&~n)+a+i;return(u<<o|u>>>32-o)+t}function p(e,t,r,n,a,o,i){var u=e+(t^r^n)+a+i;return(u<<o|u>>>32-o)+t}function f(e,t,r,n,a,o,i){var u=e+(r^(t|~n))+a+i;return(u<<o|u>>>32-o)+t}t.MD5=o._createHelper(c),t.HmacMD5=o._createHmacHelper(c)}(Math),n.MD5)},2882:function(e,t,r){var n;e.exports=(n=r(52952),r(93617),n.mode.CFB=function(){var e=n.lib.BlockCipherMode.extend();function t(e,t,r,n){var a,o=this._iv;o?(a=o.slice(0),this._iv=void 0):a=this._prevBlock,n.encryptBlock(a,0);for(var i=0;i<r;i++)e[t+i]^=a[i]}return e.Encryptor=e.extend({processBlock:function(e,r){var n=this._cipher,a=n.blockSize;t.call(this,e,r,a,n),this._prevBlock=e.slice(r,r+a)}}),e.Decryptor=e.extend({processBlock:function(e,r){var n=this._cipher,a=n.blockSize,o=e.slice(r,r+a);t.call(this,e,r,a,n),this._prevBlock=o}}),e}(),n.mode.CFB)},69972:function(e,t,r){var n;e.exports=(n=r(52952),r(93617),n.mode.CTRGladman=function(){var e=n.lib.BlockCipherMode.extend();function t(e){if(255==(e>>24&255)){var t=e>>16&255,r=e>>8&255,n=255&e;255===t?(t=0,255===r?(r=0,255===n?n=0:++n):++r):++t,e=0,e+=t<<16,e+=r<<8,e+=n}else e+=1<<24;return e}function r(e){return 0===(e[0]=t(e[0]))&&(e[1]=t(e[1])),e}var a=e.Encryptor=e.extend({processBlock:function(e,t){var n=this._cipher,a=n.blockSize,o=this._iv,i=this._counter;o&&(i=this._counter=o.slice(0),this._iv=void 0),r(i);var u=i.slice(0);n.encryptBlock(u,0);for(var c=0;c<a;c++)e[t+c]^=u[c]}});return e.Decryptor=a,e}(),n.mode.CTRGladman)},98277:function(e,t,r){var n,a,o;e.exports=(o=r(52952),r(93617),o.mode.CTR=(n=o.lib.BlockCipherMode.extend(),a=n.Encryptor=n.extend({processBlock:function(e,t){var r=this._cipher,n=r.blockSize,a=this._iv,o=this._counter;a&&(o=this._counter=a.slice(0),this._iv=void 0);var i=o.slice(0);r.encryptBlock(i,0),o[n-1]=o[n-1]+1|0;for(var u=0;u<n;u++)e[t+u]^=i[u]}}),n.Decryptor=a,n),o.mode.CTR)},79182:function(e,t,r){var n,a;e.exports=(a=r(52952),r(93617),a.mode.ECB=((n=a.lib.BlockCipherMode.extend()).Encryptor=n.extend({processBlock:function(e,t){this._cipher.encryptBlock(e,t)}}),n.Decryptor=n.extend({processBlock:function(e,t){this._cipher.decryptBlock(e,t)}}),n),a.mode.ECB)},30509:function(e,t,r){var n,a,o;e.exports=(o=r(52952),r(93617),o.mode.OFB=(n=o.lib.BlockCipherMode.extend(),a=n.Encryptor=n.extend({processBlock:function(e,t){var r=this._cipher,n=r.blockSize,a=this._iv,o=this._keystream;a&&(o=this._keystream=a.slice(0),this._iv=void 0),r.encryptBlock(o,0);for(var i=0;i<n;i++)e[t+i]^=o[i]}}),n.Decryptor=a,n),o.mode.OFB)},74990:function(e,t,r){var n;e.exports=(n=r(52952),r(93617),n.pad.AnsiX923={pad:function(e,t){var r=e.sigBytes,n=4*t,a=n-r%n,o=r+a-1;e.clamp(),e.words[o>>>2]|=a<<24-o%4*8,e.sigBytes+=a},unpad:function(e){var t=255&e.words[e.sigBytes-1>>>2];e.sigBytes-=t}},n.pad.Ansix923)},2593:function(e,t,r){var n;e.exports=(n=r(52952),r(93617),n.pad.Iso10126={pad:function(e,t){var r=4*t,a=r-e.sigBytes%r;e.concat(n.lib.WordArray.random(a-1)).concat(n.lib.WordArray.create([a<<24],1))},unpad:function(e){var t=255&e.words[e.sigBytes-1>>>2];e.sigBytes-=t}},n.pad.Iso10126)},10829:function(e,t,r){var n;e.exports=(n=r(52952),r(93617),n.pad.Iso97971={pad:function(e,t){e.concat(n.lib.WordArray.create([2147483648],1)),n.pad.ZeroPadding.pad(e,t)},unpad:function(e){n.pad.ZeroPadding.unpad(e),e.sigBytes--}},n.pad.Iso97971)},18846:function(e,t,r){var n;e.exports=(n=r(52952),r(93617),n.pad.NoPadding={pad:function(){},unpad:function(){}},n.pad.NoPadding)},10265:function(e,t,r){var n;e.exports=(n=r(52952),r(93617),n.pad.ZeroPadding={pad:function(e,t){var r=4*t;e.clamp(),e.sigBytes+=r-(e.sigBytes%r||r)},unpad:function(e){var t=e.words,r=e.sigBytes-1;for(r=e.sigBytes-1;r>=0;r--)if(t[r>>>2]>>>24-r%4*8&255){e.sigBytes=r+1;break}}},n.pad.ZeroPadding)},37248:function(e,t,r){var n,a,o,i,u,c,s,l,p;e.exports=(p=r(52952),r(49479),r(83760),a=(n=p).lib,o=a.Base,i=a.WordArray,u=n.algo,c=u.SHA1,s=u.HMAC,l=u.PBKDF2=o.extend({cfg:o.extend({keySize:4,hasher:c,iterations:1}),init:function(e){this.cfg=this.cfg.extend(e)},compute:function(e,t){for(var r=this.cfg,n=s.create(r.hasher,e),a=i.create(),o=i.create([1]),u=a.words,c=o.words,l=r.keySize,p=r.iterations;u.length<l;){var f=n.update(t).finalize(o);n.reset();for(var _=f.words,d=_.length,h=f,m=1;m<p;m++){h=n.finalize(h),n.reset();for(var v=h.words,b=0;b<d;b++)_[b]^=v[b]}a.concat(f),c[0]++}return a.sigBytes=4*l,a}}),n.PBKDF2=function(e,t,r){return l.create(r).compute(e,t)},p.PBKDF2)},35308:function(e,t,r){var n;e.exports=(n=r(52952),r(35909),r(34905),r(28492),r(93617),function(){var e=n,t=e.lib.StreamCipher,r=e.algo,a=[],o=[],i=[],u=r.RabbitLegacy=t.extend({_doReset:function(){var e=this._key.words,t=this.cfg.iv,r=this._X=[e[0],e[3]<<16|e[2]>>>16,e[1],e[0]<<16|e[3]>>>16,e[2],e[1]<<16|e[0]>>>16,e[3],e[2]<<16|e[1]>>>16],n=this._C=[e[2]<<16|e[2]>>>16,4294901760&e[0]|65535&e[1],e[3]<<16|e[3]>>>16,4294901760&e[1]|65535&e[2],e[0]<<16|e[0]>>>16,4294901760&e[2]|65535&e[3],e[1]<<16|e[1]>>>16,4294901760&e[3]|65535&e[0]];this._b=0;for(var a=0;a<4;a++)c.call(this);for(a=0;a<8;a++)n[a]^=r[a+4&7];if(t){var o=t.words,i=o[0],u=o[1],s=16711935&(i<<8|i>>>24)|4278255360&(i<<24|i>>>8),l=16711935&(u<<8|u>>>24)|4278255360&(u<<24|u>>>8),p=s>>>16|4294901760&l,f=l<<16|65535&s;for(n[0]^=s,n[1]^=p,n[2]^=l,n[3]^=f,n[4]^=s,n[5]^=p,n[6]^=l,n[7]^=f,a=0;a<4;a++)c.call(this)}},_doProcessBlock:function(e,t){var r=this._X;c.call(this),a[0]=r[0]^r[5]>>>16^r[3]<<16,a[1]=r[2]^r[7]>>>16^r[5]<<16,a[2]=r[4]^r[1]>>>16^r[7]<<16,a[3]=r[6]^r[3]>>>16^r[1]<<16;for(var n=0;n<4;n++)a[n]=16711935&(a[n]<<8|a[n]>>>24)|4278255360&(a[n]<<24|a[n]>>>8),e[t+n]^=a[n]},blockSize:4,ivSize:2});function c(){for(var e=this._X,t=this._C,r=0;r<8;r++)o[r]=t[r];for(t[0]=t[0]+1295307597+this._b|0,t[1]=t[1]+3545052371+(t[0]>>>0<o[0]>>>0?1:0)|0,t[2]=t[2]+886263092+(t[1]>>>0<o[1]>>>0?1:0)|0,t[3]=t[3]+1295307597+(t[2]>>>0<o[2]>>>0?1:0)|0,t[4]=t[4]+3545052371+(t[3]>>>0<o[3]>>>0?1:0)|0,t[5]=t[5]+886263092+(t[4]>>>0<o[4]>>>0?1:0)|0,t[6]=t[6]+1295307597+(t[5]>>>0<o[5]>>>0?1:0)|0,t[7]=t[7]+3545052371+(t[6]>>>0<o[6]>>>0?1:0)|0,this._b=t[7]>>>0<o[7]>>>0?1:0,r=0;r<8;r++){var n=e[r]+t[r],a=65535&n,u=n>>>16,c=((a*a>>>17)+a*u>>>15)+u*u,s=((4294901760&n)*n|0)+((65535&n)*n|0);i[r]=c^s}e[0]=i[0]+(i[7]<<16|i[7]>>>16)+(i[6]<<16|i[6]>>>16)|0,e[1]=i[1]+(i[0]<<8|i[0]>>>24)+i[7]|0,e[2]=i[2]+(i[1]<<16|i[1]>>>16)+(i[0]<<16|i[0]>>>16)|0,e[3]=i[3]+(i[2]<<8|i[2]>>>24)+i[1]|0,e[4]=i[4]+(i[3]<<16|i[3]>>>16)+(i[2]<<16|i[2]>>>16)|0,e[5]=i[5]+(i[4]<<8|i[4]>>>24)+i[3]|0,e[6]=i[6]+(i[5]<<16|i[5]>>>16)+(i[4]<<16|i[4]>>>16)|0,e[7]=i[7]+(i[6]<<8|i[6]>>>24)+i[5]|0}e.RabbitLegacy=t._createHelper(u)}(),n.RabbitLegacy)},21865:function(e,t,r){var n;e.exports=(n=r(52952),r(35909),r(34905),r(28492),r(93617),function(){var e=n,t=e.lib.StreamCipher,r=e.algo,a=[],o=[],i=[],u=r.Rabbit=t.extend({_doReset:function(){for(var e=this._key.words,t=this.cfg.iv,r=0;r<4;r++)e[r]=16711935&(e[r]<<8|e[r]>>>24)|4278255360&(e[r]<<24|e[r]>>>8);var n=this._X=[e[0],e[3]<<16|e[2]>>>16,e[1],e[0]<<16|e[3]>>>16,e[2],e[1]<<16|e[0]>>>16,e[3],e[2]<<16|e[1]>>>16],a=this._C=[e[2]<<16|e[2]>>>16,4294901760&e[0]|65535&e[1],e[3]<<16|e[3]>>>16,4294901760&e[1]|65535&e[2],e[0]<<16|e[0]>>>16,4294901760&e[2]|65535&e[3],e[1]<<16|e[1]>>>16,4294901760&e[3]|65535&e[0]];for(this._b=0,r=0;r<4;r++)c.call(this);for(r=0;r<8;r++)a[r]^=n[r+4&7];if(t){var o=t.words,i=o[0],u=o[1],s=16711935&(i<<8|i>>>24)|4278255360&(i<<24|i>>>8),l=16711935&(u<<8|u>>>24)|4278255360&(u<<24|u>>>8),p=s>>>16|4294901760&l,f=l<<16|65535&s;for(a[0]^=s,a[1]^=p,a[2]^=l,a[3]^=f,a[4]^=s,a[5]^=p,a[6]^=l,a[7]^=f,r=0;r<4;r++)c.call(this)}},_doProcessBlock:function(e,t){var r=this._X;c.call(this),a[0]=r[0]^r[5]>>>16^r[3]<<16,a[1]=r[2]^r[7]>>>16^r[5]<<16,a[2]=r[4]^r[1]>>>16^r[7]<<16,a[3]=r[6]^r[3]>>>16^r[1]<<16;for(var n=0;n<4;n++)a[n]=16711935&(a[n]<<8|a[n]>>>24)|4278255360&(a[n]<<24|a[n]>>>8),e[t+n]^=a[n]},blockSize:4,ivSize:2});function c(){for(var e=this._X,t=this._C,r=0;r<8;r++)o[r]=t[r];for(t[0]=t[0]+1295307597+this._b|0,t[1]=t[1]+3545052371+(t[0]>>>0<o[0]>>>0?1:0)|0,t[2]=t[2]+886263092+(t[1]>>>0<o[1]>>>0?1:0)|0,t[3]=t[3]+1295307597+(t[2]>>>0<o[2]>>>0?1:0)|0,t[4]=t[4]+3545052371+(t[3]>>>0<o[3]>>>0?1:0)|0,t[5]=t[5]+886263092+(t[4]>>>0<o[4]>>>0?1:0)|0,t[6]=t[6]+1295307597+(t[5]>>>0<o[5]>>>0?1:0)|0,t[7]=t[7]+3545052371+(t[6]>>>0<o[6]>>>0?1:0)|0,this._b=t[7]>>>0<o[7]>>>0?1:0,r=0;r<8;r++){var n=e[r]+t[r],a=65535&n,u=n>>>16,c=((a*a>>>17)+a*u>>>15)+u*u,s=((4294901760&n)*n|0)+((65535&n)*n|0);i[r]=c^s}e[0]=i[0]+(i[7]<<16|i[7]>>>16)+(i[6]<<16|i[6]>>>16)|0,e[1]=i[1]+(i[0]<<8|i[0]>>>24)+i[7]|0,e[2]=i[2]+(i[1]<<16|i[1]>>>16)+(i[0]<<16|i[0]>>>16)|0,e[3]=i[3]+(i[2]<<8|i[2]>>>24)+i[1]|0,e[4]=i[4]+(i[3]<<16|i[3]>>>16)+(i[2]<<16|i[2]>>>16)|0,e[5]=i[5]+(i[4]<<8|i[4]>>>24)+i[3]|0,e[6]=i[6]+(i[5]<<16|i[5]>>>16)+(i[4]<<16|i[4]>>>16)|0,e[7]=i[7]+(i[6]<<8|i[6]>>>24)+i[5]|0}e.Rabbit=t._createHelper(u)}(),n.Rabbit)},22528:function(e,t,r){var n;e.exports=(n=r(52952),r(35909),r(34905),r(28492),r(93617),function(){var e=n,t=e.lib.StreamCipher,r=e.algo,a=r.RC4=t.extend({_doReset:function(){for(var e=this._key,t=e.words,r=e.sigBytes,n=this._S=[],a=0;a<256;a++)n[a]=a;a=0;for(var o=0;a<256;a++){var i=a%r,u=t[i>>>2]>>>24-i%4*8&255;o=(o+n[a]+u)%256;var c=n[a];n[a]=n[o],n[o]=c}this._i=this._j=0},_doProcessBlock:function(e,t){e[t]^=o.call(this)},keySize:8,ivSize:0});function o(){for(var e=this._S,t=this._i,r=this._j,n=0,a=0;a<4;a++){r=(r+e[t=(t+1)%256])%256;var o=e[t];e[t]=e[r],e[r]=o,n|=e[(e[t]+e[r])%256]<<24-8*a}return this._i=t,this._j=r,n}e.RC4=t._createHelper(a);var i=r.RC4Drop=a.extend({cfg:a.cfg.extend({drop:192}),_doReset:function(){a._doReset.call(this);for(var e=this.cfg.drop;e>0;e--)o.call(this)}});e.RC4Drop=t._createHelper(i)}(),n.RC4)},25824:function(e,t,r){var n;e.exports=(n=r(52952),function(e){var t=n,r=t.lib,a=r.WordArray,o=r.Hasher,i=t.algo,u=a.create([0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,7,4,13,1,10,6,15,3,12,0,9,5,2,14,11,8,3,10,14,4,9,15,8,1,2,7,0,6,13,11,5,12,1,9,11,10,0,8,12,4,13,3,7,15,14,5,6,2,4,0,5,9,7,12,2,10,14,1,3,8,11,6,15,13]),c=a.create([5,14,7,0,9,2,11,4,13,6,15,8,1,10,3,12,6,11,3,7,0,13,5,10,14,15,8,12,4,9,1,2,15,5,1,3,7,14,6,9,11,8,12,2,10,0,4,13,8,6,4,1,3,11,15,0,5,12,2,13,9,7,10,14,12,15,10,4,1,5,8,7,6,2,13,14,0,3,9,11]),s=a.create([11,14,15,12,5,8,7,9,11,13,14,15,6,7,9,8,7,6,8,13,11,9,7,15,7,12,15,9,11,7,13,12,11,13,6,7,14,9,13,15,14,8,13,6,5,12,7,5,11,12,14,15,14,15,9,8,9,14,5,6,8,6,5,12,9,15,5,11,6,8,13,12,5,12,13,14,11,8,5,6]),l=a.create([8,9,9,11,13,15,15,5,7,7,8,11,14,14,12,6,9,13,15,7,12,8,9,11,7,7,12,7,6,15,13,11,9,7,15,11,8,6,6,14,12,13,5,14,13,13,7,5,15,5,8,11,14,14,6,14,6,9,12,9,12,5,15,8,8,5,12,9,12,5,14,6,8,13,6,5,15,13,11,11]),p=a.create([0,1518500249,1859775393,2400959708,2840853838]),f=a.create([1352829926,1548603684,1836072691,2053994217,0]),_=i.RIPEMD160=o.extend({_doReset:function(){this._hash=a.create([1732584193,4023233417,2562383102,271733878,3285377520])},_doProcessBlock:function(e,t){for(var r=0;r<16;r++){var n=t+r,a=e[n];e[n]=16711935&(a<<8|a>>>24)|4278255360&(a<<24|a>>>8)}var o,i,_,g,w,x,k,P,E,S,C,j=this._hash.words,q=p.words,I=f.words,O=u.words,A=c.words,D=s.words,T=l.words;for(x=o=j[0],k=i=j[1],P=_=j[2],E=g=j[3],S=w=j[4],r=0;r<80;r+=1)C=o+e[t+O[r]]|0,C+=r<16?d(i,_,g)+q[0]:r<32?h(i,_,g)+q[1]:r<48?m(i,_,g)+q[2]:r<64?v(i,_,g)+q[3]:b(i,_,g)+q[4],C=(C=y(C|=0,D[r]))+w|0,o=w,w=g,g=y(_,10),_=i,i=C,C=x+e[t+A[r]]|0,C+=r<16?b(k,P,E)+I[0]:r<32?v(k,P,E)+I[1]:r<48?m(k,P,E)+I[2]:r<64?h(k,P,E)+I[3]:d(k,P,E)+I[4],C=(C=y(C|=0,T[r]))+S|0,x=S,S=E,E=y(P,10),P=k,k=C;C=j[1]+_+E|0,j[1]=j[2]+g+S|0,j[2]=j[3]+w+x|0,j[3]=j[4]+o+k|0,j[4]=j[0]+i+P|0,j[0]=C},_doFinalize:function(){var e=this._data,t=e.words,r=8*this._nDataBytes,n=8*e.sigBytes;t[n>>>5]|=128<<24-n%32,t[14+(n+64>>>9<<4)]=16711935&(r<<8|r>>>24)|4278255360&(r<<24|r>>>8),e.sigBytes=4*(t.length+1),this._process();for(var a=this._hash,o=a.words,i=0;i<5;i++){var u=o[i];o[i]=16711935&(u<<8|u>>>24)|4278255360&(u<<24|u>>>8)}return a},clone:function(){var e=o.clone.call(this);return e._hash=this._hash.clone(),e}});function d(e,t,r){return e^t^r}function h(e,t,r){return e&t|~e&r}function m(e,t,r){return(e|~t)^r}function v(e,t,r){return e&r|t&~r}function b(e,t,r){return e^(t|~r)}function y(e,t){return e<<t|e>>>32-t}t.RIPEMD160=o._createHelper(_),t.HmacRIPEMD160=o._createHmacHelper(_)}(Math),n.RIPEMD160)},49479:function(e,t,r){var n,a,o,i,u,c,s,l;e.exports=(l=r(52952),a=(n=l).lib,o=a.WordArray,i=a.Hasher,u=n.algo,c=[],s=u.SHA1=i.extend({_doReset:function(){this._hash=new o.init([1732584193,4023233417,2562383102,271733878,3285377520])},_doProcessBlock:function(e,t){for(var r=this._hash.words,n=r[0],a=r[1],o=r[2],i=r[3],u=r[4],s=0;s<80;s++){if(s<16)c[s]=0|e[t+s];else{var l=c[s-3]^c[s-8]^c[s-14]^c[s-16];c[s]=l<<1|l>>>31}var p=(n<<5|n>>>27)+u+c[s];p+=s<20?1518500249+(a&o|~a&i):s<40?1859775393+(a^o^i):s<60?(a&o|a&i|o&i)-1894007588:(a^o^i)-899497514,u=i,i=o,o=a<<30|a>>>2,a=n,n=p}r[0]=r[0]+n|0,r[1]=r[1]+a|0,r[2]=r[2]+o|0,r[3]=r[3]+i|0,r[4]=r[4]+u|0},_doFinalize:function(){var e=this._data,t=e.words,r=8*this._nDataBytes,n=8*e.sigBytes;return t[n>>>5]|=128<<24-n%32,t[14+(n+64>>>9<<4)]=Math.floor(r/4294967296),t[15+(n+64>>>9<<4)]=r,e.sigBytes=4*t.length,this._process(),this._hash},clone:function(){var e=i.clone.call(this);return e._hash=this._hash.clone(),e}}),n.SHA1=i._createHelper(s),n.HmacSHA1=i._createHmacHelper(s),l.SHA1)},93653:function(e,t,r){var n,a,o,i,u,c;e.exports=(c=r(52952),r(2481),a=(n=c).lib.WordArray,o=n.algo,i=o.SHA256,u=o.SHA224=i.extend({_doReset:function(){this._hash=new a.init([3238371032,914150663,812702999,4144912697,4290775857,1750603025,1694076839,3204075428])},_doFinalize:function(){var e=i._doFinalize.call(this);return e.sigBytes-=4,e}}),n.SHA224=i._createHelper(u),n.HmacSHA224=i._createHmacHelper(u),c.SHA224)},2481:function(e,t,r){var n;e.exports=(n=r(52952),function(e){var t=n,r=t.lib,a=r.WordArray,o=r.Hasher,i=t.algo,u=[],c=[];!function(){function t(t){for(var r=e.sqrt(t),n=2;n<=r;n++)if(!(t%n))return!1;return!0}function r(e){return 4294967296*(e-(0|e))|0}for(var n=2,a=0;a<64;)t(n)&&(a<8&&(u[a]=r(e.pow(n,.5))),c[a]=r(e.pow(n,1/3)),a++),n++}();var s=[],l=i.SHA256=o.extend({_doReset:function(){this._hash=new a.init(u.slice(0))},_doProcessBlock:function(e,t){for(var r=this._hash.words,n=r[0],a=r[1],o=r[2],i=r[3],u=r[4],l=r[5],p=r[6],f=r[7],_=0;_<64;_++){if(_<16)s[_]=0|e[t+_];else{var d=s[_-15],h=(d<<25|d>>>7)^(d<<14|d>>>18)^d>>>3,m=s[_-2],v=(m<<15|m>>>17)^(m<<13|m>>>19)^m>>>10;s[_]=h+s[_-7]+v+s[_-16]}var b=n&a^n&o^a&o,y=(n<<30|n>>>2)^(n<<19|n>>>13)^(n<<10|n>>>22),g=f+((u<<26|u>>>6)^(u<<21|u>>>11)^(u<<7|u>>>25))+(u&l^~u&p)+c[_]+s[_];f=p,p=l,l=u,u=i+g|0,i=o,o=a,a=n,n=g+(y+b)|0}r[0]=r[0]+n|0,r[1]=r[1]+a|0,r[2]=r[2]+o|0,r[3]=r[3]+i|0,r[4]=r[4]+u|0,r[5]=r[5]+l|0,r[6]=r[6]+p|0,r[7]=r[7]+f|0},_doFinalize:function(){var t=this._data,r=t.words,n=8*this._nDataBytes,a=8*t.sigBytes;return r[a>>>5]|=128<<24-a%32,r[14+(a+64>>>9<<4)]=e.floor(n/4294967296),r[15+(a+64>>>9<<4)]=n,t.sigBytes=4*r.length,this._process(),this._hash},clone:function(){var e=o.clone.call(this);return e._hash=this._hash.clone(),e}});t.SHA256=o._createHelper(l),t.HmacSHA256=o._createHmacHelper(l)}(Math),n.SHA256)},79421:function(e,t,r){var n;e.exports=(n=r(52952),r(41988),function(e){var t=n,r=t.lib,a=r.WordArray,o=r.Hasher,i=t.x64.Word,u=t.algo,c=[],s=[],l=[];!function(){for(var e=1,t=0,r=0;r<24;r++){c[e+5*t]=(r+1)*(r+2)/2%64;var n=(2*e+3*t)%5;e=t%5,t=n}for(e=0;e<5;e++)for(t=0;t<5;t++)s[e+5*t]=t+(2*e+3*t)%5*5;for(var a=1,o=0;o<24;o++){for(var u=0,p=0,f=0;f<7;f++){if(1&a){var _=(1<<f)-1;_<32?p^=1<<_:u^=1<<_-32}128&a?a=a<<1^113:a<<=1}l[o]=i.create(u,p)}}();var p=[];!function(){for(var e=0;e<25;e++)p[e]=i.create()}();var f=u.SHA3=o.extend({cfg:o.cfg.extend({outputLength:512}),_doReset:function(){for(var e=this._state=[],t=0;t<25;t++)e[t]=new i.init;this.blockSize=(1600-2*this.cfg.outputLength)/32},_doProcessBlock:function(e,t){for(var r=this._state,n=this.blockSize/2,a=0;a<n;a++){var o=e[t+2*a],i=e[t+2*a+1];o=16711935&(o<<8|o>>>24)|4278255360&(o<<24|o>>>8),i=16711935&(i<<8|i>>>24)|4278255360&(i<<24|i>>>8),(j=r[a]).high^=i,j.low^=o}for(var u=0;u<24;u++){for(var f=0;f<5;f++){for(var _=0,d=0,h=0;h<5;h++)_^=(j=r[f+5*h]).high,d^=j.low;var m=p[f];m.high=_,m.low=d}for(f=0;f<5;f++){var v=p[(f+4)%5],b=p[(f+1)%5],y=b.high,g=b.low;for(_=v.high^(y<<1|g>>>31),d=v.low^(g<<1|y>>>31),h=0;h<5;h++)(j=r[f+5*h]).high^=_,j.low^=d}for(var w=1;w<25;w++){var x=(j=r[w]).high,k=j.low,P=c[w];P<32?(_=x<<P|k>>>32-P,d=k<<P|x>>>32-P):(_=k<<P-32|x>>>64-P,d=x<<P-32|k>>>64-P);var E=p[s[w]];E.high=_,E.low=d}var S=p[0],C=r[0];for(S.high=C.high,S.low=C.low,f=0;f<5;f++)for(h=0;h<5;h++){var j=r[w=f+5*h],q=p[w],I=p[(f+1)%5+5*h],O=p[(f+2)%5+5*h];j.high=q.high^~I.high&O.high,j.low=q.low^~I.low&O.low}j=r[0];var A=l[u];j.high^=A.high,j.low^=A.low}},_doFinalize:function(){var t=this._data,r=t.words,n=(this._nDataBytes,8*t.sigBytes),o=32*this.blockSize;r[n>>>5]|=1<<24-n%32,r[(e.ceil((n+1)/o)*o>>>5)-1]|=128,t.sigBytes=4*r.length,this._process();for(var i=this._state,u=this.cfg.outputLength/8,c=u/8,s=[],l=0;l<c;l++){var p=i[l],f=p.high,_=p.low;f=16711935&(f<<8|f>>>24)|4278255360&(f<<24|f>>>8),_=16711935&(_<<8|_>>>24)|4278255360&(_<<24|_>>>8),s.push(_),s.push(f)}return new a.init(s,u)},clone:function(){for(var e=o.clone.call(this),t=e._state=this._state.slice(0),r=0;r<25;r++)t[r]=t[r].clone();return e}});t.SHA3=o._createHelper(f),t.HmacSHA3=o._createHmacHelper(f)}(Math),n.SHA3)},82307:function(e,t,r){var n,a,o,i,u,c,s,l;e.exports=(l=r(52952),r(41988),r(12133),a=(n=l).x64,o=a.Word,i=a.WordArray,u=n.algo,c=u.SHA512,s=u.SHA384=c.extend({_doReset:function(){this._hash=new i.init([new o.init(3418070365,3238371032),new o.init(1654270250,914150663),new o.init(2438529370,812702999),new o.init(355462360,4144912697),new o.init(1731405415,4290775857),new o.init(2394180231,1750603025),new o.init(3675008525,1694076839),new o.init(1203062813,3204075428)])},_doFinalize:function(){var e=c._doFinalize.call(this);return e.sigBytes-=16,e}}),n.SHA384=c._createHelper(s),n.HmacSHA384=c._createHmacHelper(s),l.SHA384)},12133:function(e,t,r){var n;e.exports=(n=r(52952),r(41988),function(){var e=n,t=e.lib.Hasher,r=e.x64,a=r.Word,o=r.WordArray,i=e.algo;function u(){return a.create.apply(a,arguments)}var c=[u(1116352408,3609767458),u(1899447441,602891725),u(3049323471,3964484399),u(3921009573,2173295548),u(961987163,4081628472),u(1508970993,3053834265),u(2453635748,2937671579),u(2870763221,3664609560),u(3624381080,2734883394),u(310598401,1164996542),u(607225278,1323610764),u(1426881987,3590304994),u(1925078388,4068182383),u(2162078206,991336113),u(2614888103,633803317),u(3248222580,3479774868),u(3835390401,2666613458),u(4022224774,944711139),u(264347078,2341262773),u(604807628,2007800933),u(770255983,1495990901),u(1249150122,1856431235),u(1555081692,3175218132),u(1996064986,2198950837),u(2554220882,3999719339),u(2821834349,766784016),u(2952996808,2566594879),u(3210313671,3203337956),u(3336571891,1034457026),u(3584528711,2466948901),u(113926993,3758326383),u(338241895,168717936),u(666307205,1188179964),u(773529912,1546045734),u(1294757372,1522805485),u(1396182291,2643833823),u(1695183700,2343527390),u(1986661051,1014477480),u(2177026350,1206759142),u(2456956037,344077627),u(2730485921,1290863460),u(2820302411,3158454273),u(3259730800,3505952657),u(3345764771,106217008),u(3516065817,3606008344),u(3600352804,1432725776),u(4094571909,1467031594),u(275423344,851169720),u(430227734,3100823752),u(506948616,1363258195),u(659060556,3750685593),u(883997877,3785050280),u(958139571,3318307427),u(1322822218,3812723403),u(1537002063,2003034995),u(1747873779,3602036899),u(1955562222,1575990012),u(2024104815,1125592928),u(2227730452,2716904306),u(2361852424,442776044),u(2428436474,593698344),u(2756734187,3733110249),u(3204031479,2999351573),u(3329325298,3815920427),u(3391569614,3928383900),u(3515267271,566280711),u(3940187606,3454069534),u(4118630271,4000239992),u(116418474,1914138554),u(174292421,2731055270),u(289380356,3203993006),u(460393269,320620315),u(685471733,587496836),u(852142971,1086792851),u(1017036298,365543100),u(1126000580,2618297676),u(1288033470,3409855158),u(1501505948,4234509866),u(1607167915,987167468),u(1816402316,1246189591)],s=[];!function(){for(var e=0;e<80;e++)s[e]=u()}();var l=i.SHA512=t.extend({_doReset:function(){this._hash=new o.init([new a.init(1779033703,4089235720),new a.init(3144134277,2227873595),new a.init(1013904242,4271175723),new a.init(2773480762,1595750129),new a.init(1359893119,2917565137),new a.init(2600822924,725511199),new a.init(528734635,4215389547),new a.init(1541459225,327033209)])},_doProcessBlock:function(e,t){for(var r=this._hash.words,n=r[0],a=r[1],o=r[2],i=r[3],u=r[4],l=r[5],p=r[6],f=r[7],_=n.high,d=n.low,h=a.high,m=a.low,v=o.high,b=o.low,y=i.high,g=i.low,w=u.high,x=u.low,k=l.high,P=l.low,E=p.high,S=p.low,C=f.high,j=f.low,q=_,I=d,O=h,A=m,D=v,T=b,M=y,L=g,R=w,z=x,Z=k,H=P,F=E,N=S,B=C,U=j,X=0;X<80;X++){var W,G,K=s[X];if(X<16)G=K.high=0|e[t+2*X],W=K.low=0|e[t+2*X+1];else{var V=s[X-15],Y=V.high,Q=V.low,J=(Y>>>1|Q<<31)^(Y>>>8|Q<<24)^Y>>>7,$=(Q>>>1|Y<<31)^(Q>>>8|Y<<24)^(Q>>>7|Y<<25),ee=s[X-2],te=ee.high,re=ee.low,ne=(te>>>19|re<<13)^(te<<3|re>>>29)^te>>>6,ae=(re>>>19|te<<13)^(re<<3|te>>>29)^(re>>>6|te<<26),oe=s[X-7],ie=oe.high,ue=oe.low,ce=s[X-16],se=ce.high,le=ce.low;G=(G=(G=J+ie+((W=$+ue)>>>0<$>>>0?1:0))+ne+((W+=ae)>>>0<ae>>>0?1:0))+se+((W+=le)>>>0<le>>>0?1:0),K.high=G,K.low=W}var pe,fe=R&Z^~R&F,_e=z&H^~z&N,de=q&O^q&D^O&D,he=I&A^I&T^A&T,me=(q>>>28|I<<4)^(q<<30|I>>>2)^(q<<25|I>>>7),ve=(I>>>28|q<<4)^(I<<30|q>>>2)^(I<<25|q>>>7),be=(R>>>14|z<<18)^(R>>>18|z<<14)^(R<<23|z>>>9),ye=(z>>>14|R<<18)^(z>>>18|R<<14)^(z<<23|R>>>9),ge=c[X],we=ge.high,xe=ge.low,ke=B+be+((pe=U+ye)>>>0<U>>>0?1:0),Pe=ve+he;B=F,U=N,F=Z,N=H,Z=R,H=z,R=M+(ke=(ke=(ke=ke+fe+((pe+=_e)>>>0<_e>>>0?1:0))+we+((pe+=xe)>>>0<xe>>>0?1:0))+G+((pe+=W)>>>0<W>>>0?1:0))+((z=L+pe|0)>>>0<L>>>0?1:0)|0,M=D,L=T,D=O,T=A,O=q,A=I,q=ke+(me+de+(Pe>>>0<ve>>>0?1:0))+((I=pe+Pe|0)>>>0<pe>>>0?1:0)|0}d=n.low=d+I,n.high=_+q+(d>>>0<I>>>0?1:0),m=a.low=m+A,a.high=h+O+(m>>>0<A>>>0?1:0),b=o.low=b+T,o.high=v+D+(b>>>0<T>>>0?1:0),g=i.low=g+L,i.high=y+M+(g>>>0<L>>>0?1:0),x=u.low=x+z,u.high=w+R+(x>>>0<z>>>0?1:0),P=l.low=P+H,l.high=k+Z+(P>>>0<H>>>0?1:0),S=p.low=S+N,p.high=E+F+(S>>>0<N>>>0?1:0),j=f.low=j+U,f.high=C+B+(j>>>0<U>>>0?1:0)},_doFinalize:function(){var e=this._data,t=e.words,r=8*this._nDataBytes,n=8*e.sigBytes;return t[n>>>5]|=128<<24-n%32,t[30+(n+128>>>10<<5)]=Math.floor(r/4294967296),t[31+(n+128>>>10<<5)]=r,e.sigBytes=4*t.length,this._process(),this._hash.toX32()},clone:function(){var e=t.clone.call(this);return e._hash=this._hash.clone(),e},blockSize:32});e.SHA512=t._createHelper(l),e.HmacSHA512=t._createHmacHelper(l)}(),n.SHA512)},61945:function(e,t,r){var n;e.exports=(n=r(52952),r(35909),r(34905),r(28492),r(93617),function(){var e=n,t=e.lib,r=t.WordArray,a=t.BlockCipher,o=e.algo,i=[57,49,41,33,25,17,9,1,58,50,42,34,26,18,10,2,59,51,43,35,27,19,11,3,60,52,44,36,63,55,47,39,31,23,15,7,62,54,46,38,30,22,14,6,61,53,45,37,29,21,13,5,28,20,12,4],u=[14,17,11,24,1,5,3,28,15,6,21,10,23,19,12,4,26,8,16,7,27,20,13,2,41,52,31,37,47,55,30,40,51,45,33,48,44,49,39,56,34,53,46,42,50,36,29,32],c=[1,2,4,6,8,10,12,14,15,17,19,21,23,25,27,28],s=[{0:8421888,268435456:32768,536870912:8421378,805306368:2,1073741824:512,1342177280:8421890,1610612736:8389122,1879048192:8388608,2147483648:514,2415919104:8389120,2684354560:33280,2952790016:8421376,3221225472:32770,3489660928:8388610,3758096384:0,4026531840:33282,134217728:0,402653184:8421890,671088640:33282,939524096:32768,1207959552:8421888,1476395008:512,1744830464:8421378,2013265920:2,2281701376:8389120,2550136832:33280,2818572288:8421376,3087007744:8389122,3355443200:8388610,3623878656:32770,3892314112:514,4160749568:8388608,1:32768,268435457:2,536870913:8421888,805306369:8388608,1073741825:8421378,1342177281:33280,1610612737:512,1879048193:8389122,2147483649:8421890,2415919105:8421376,2684354561:8388610,2952790017:33282,3221225473:514,3489660929:8389120,3758096385:32770,4026531841:0,134217729:8421890,402653185:8421376,671088641:8388608,939524097:512,1207959553:32768,1476395009:8388610,1744830465:2,2013265921:33282,2281701377:32770,2550136833:8389122,2818572289:514,3087007745:8421888,3355443201:8389120,3623878657:0,3892314113:33280,4160749569:8421378},{0:1074282512,16777216:16384,33554432:524288,50331648:1074266128,67108864:1073741840,83886080:1074282496,100663296:1073758208,117440512:16,134217728:540672,150994944:1073758224,167772160:1073741824,184549376:540688,201326592:524304,218103808:0,234881024:16400,251658240:1074266112,8388608:1073758208,25165824:540688,41943040:16,58720256:1073758224,75497472:1074282512,92274688:1073741824,109051904:524288,125829120:1074266128,142606336:524304,159383552:0,176160768:16384,192937984:1074266112,209715200:1073741840,226492416:540672,243269632:1074282496,260046848:16400,268435456:0,285212672:1074266128,301989888:1073758224,318767104:1074282496,335544320:1074266112,352321536:16,369098752:540688,385875968:16384,402653184:16400,419430400:524288,436207616:524304,452984832:1073741840,469762048:540672,486539264:1073758208,503316480:1073741824,520093696:1074282512,276824064:540688,293601280:524288,310378496:1074266112,327155712:16384,343932928:1073758208,360710144:1074282512,377487360:16,394264576:1073741824,411041792:1074282496,427819008:1073741840,444596224:1073758224,461373440:524304,478150656:0,494927872:16400,511705088:1074266128,528482304:540672},{0:260,1048576:0,2097152:67109120,3145728:65796,4194304:65540,5242880:67108868,6291456:67174660,7340032:67174400,8388608:67108864,9437184:67174656,10485760:65792,11534336:67174404,12582912:67109124,13631488:65536,14680064:4,15728640:256,524288:67174656,1572864:67174404,2621440:0,3670016:67109120,4718592:67108868,5767168:65536,6815744:65540,7864320:260,8912896:4,9961472:256,11010048:67174400,12058624:65796,13107200:65792,14155776:67109124,15204352:67174660,16252928:67108864,16777216:67174656,17825792:65540,18874368:65536,19922944:67109120,20971520:256,22020096:67174660,23068672:67108868,24117248:0,25165824:67109124,26214400:67108864,27262976:4,28311552:65792,29360128:67174400,30408704:260,31457280:65796,32505856:67174404,17301504:67108864,18350080:260,19398656:67174656,20447232:0,21495808:65540,22544384:67109120,23592960:256,24641536:67174404,25690112:65536,26738688:67174660,27787264:65796,28835840:67108868,29884416:67109124,30932992:67174400,31981568:4,33030144:65792},{0:2151682048,65536:2147487808,131072:4198464,196608:2151677952,262144:0,327680:4198400,393216:2147483712,458752:4194368,524288:2147483648,589824:4194304,655360:64,720896:2147487744,786432:2151678016,851968:4160,917504:4096,983040:2151682112,32768:2147487808,98304:64,163840:2151678016,229376:2147487744,294912:4198400,360448:2151682112,425984:0,491520:2151677952,557056:4096,622592:2151682048,688128:4194304,753664:4160,819200:2147483648,884736:4194368,950272:4198464,1015808:2147483712,1048576:4194368,1114112:4198400,1179648:2147483712,1245184:0,1310720:4160,1376256:2151678016,1441792:2151682048,1507328:2147487808,1572864:2151682112,1638400:2147483648,1703936:2151677952,1769472:4198464,1835008:2147487744,1900544:4194304,1966080:64,2031616:4096,1081344:2151677952,1146880:2151682112,1212416:0,1277952:4198400,1343488:4194368,1409024:2147483648,1474560:2147487808,1540096:64,1605632:2147483712,1671168:4096,1736704:2147487744,1802240:2151678016,1867776:4160,1933312:2151682048,1998848:4194304,2064384:4198464},{0:128,4096:17039360,8192:262144,12288:536870912,16384:537133184,20480:16777344,24576:553648256,28672:262272,32768:16777216,36864:537133056,40960:536871040,45056:553910400,49152:553910272,53248:0,57344:17039488,61440:553648128,2048:17039488,6144:553648256,10240:128,14336:17039360,18432:262144,22528:537133184,26624:553910272,30720:536870912,34816:537133056,38912:0,430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e=this._key.words,t=[],r=0;r<56;r++){var n=i[r]-1;t[r]=e[n>>>5]>>>31-n%32&1}for(var a=this._subKeys=[],o=0;o<16;o++){var s=a[o]=[],l=c[o];for(r=0;r<24;r++)s[r/6|0]|=t[(u[r]-1+l)%28]<<31-r%6,s[4+(r/6|0)]|=t[28+(u[r+24]-1+l)%28]<<31-r%6;for(s[0]=s[0]<<1|s[0]>>>31,r=1;r<7;r++)s[r]=s[r]>>>4*(r-1)+3;s[7]=s[7]<<5|s[7]>>>27}var p=this._invSubKeys=[];for(r=0;r<16;r++)p[r]=a[15-r]},encryptBlock:function(e,t){this._doCryptBlock(e,t,this._subKeys)},decryptBlock:function(e,t){this._doCryptBlock(e,t,this._invSubKeys)},_doCryptBlock:function(e,t,r){this._lBlock=e[t],this._rBlock=e[t+1],f.call(this,4,252645135),f.call(this,16,65535),_.call(this,2,858993459),_.call(this,8,16711935),f.call(this,1,1431655765);for(var n=0;n<16;n++){for(var a=r[n],o=this._lBlock,i=this._rBlock,u=0,c=0;c<8;c++)u|=s[c][((i^a[c])&l[c])>>>0];this._lBlock=i,this._rBlock=o^u}var p=this._lBlock;this._lBlock=this._rBlock,this._rBlock=p,f.call(this,1,1431655765),_.call(this,8,16711935),_.call(this,2,858993459),f.call(this,16,65535),f.call(this,4,252645135),e[t]=this._lBlock,e[t+1]=this._rBlock},keySize:2,ivSize:2,blockSize:2});function f(e,t){var r=(this._lBlock>>>e^this._rBlock)&t;this._rBlock^=r,this._lBlock^=r<<e}function _(e,t){var r=(this._rBlock>>>e^this._lBlock)&t;this._lBlock^=r,this._rBlock^=r<<e}e.DES=a._createHelper(p);var d=o.TripleDES=a.extend({_doReset:function(){var e=this._key.words;if(2!==e.length&&4!==e.length&&e.length<6)throw new Error("Invalid key length - 3DES requires the key length to be 64, 128, 192 or >192.");var t=e.slice(0,2),n=e.length<4?e.slice(0,2):e.slice(2,4),a=e.length<6?e.slice(0,2):e.slice(4,6);this._des1=p.createEncryptor(r.create(t)),this._des2=p.createEncryptor(r.create(n)),this._des3=p.createEncryptor(r.create(a))},encryptBlock:function(e,t){this._des1.encryptBlock(e,t),this._des2.decryptBlock(e,t),this._des3.encryptBlock(e,t)},decryptBlock:function(e,t){this._des3.decryptBlock(e,t),this._des2.encryptBlock(e,t),this._des1.decryptBlock(e,t)},keySize:6,ivSize:2,blockSize:2});e.TripleDES=a._createHelper(d)}(),n.TripleDES)},41988:function(e,t,r){var n;e.exports=(n=r(52952),function(e){var t=n,r=t.lib,a=r.Base,o=r.WordArray,i=t.x64={};i.Word=a.extend({init:function(e,t){this.high=e,this.low=t}}),i.WordArray=a.extend({init:function(t,r){t=this.words=t||[],this.sigBytes=r!=e?r:8*t.length},toX32:function(){for(var e=this.words,t=e.length,r=[],n=0;n<t;n++){var a=e[n];r.push(a.high),r.push(a.low)}return o.create(r,this.sigBytes)},clone:function(){for(var e=a.clone.call(this),t=e.words=this.words.slice(0),r=t.length,n=0;n<r;n++)t[n]=t[n].clone();return e}})}(),n)},35413:function(e,t,r){"use strict";var n=r(57046),a=r(69574),o=r(63474),i=r(47095),u=r(99363),c=e.exports=function(e,t){var r,a,c,s,l;return arguments.length<2||"string"!=typeof e?(s=t,t=e,e=null):s=arguments[2],n(e)?(r=u.call(e,"c"),a=u.call(e,"e"),c=u.call(e,"w")):(r=c=!0,a=!1),l={value:t,configurable:r,enumerable:a,writable:c},s?o(i(s),l):l};c.gs=function(e,t,r){var c,s,l,p;return"string"!=typeof e?(l=r,r=t,t=e,e=null):l=arguments[3],n(t)?a(t)?n(r)?a(r)||(l=r,r=void 0):r=void 0:(l=t,t=r=void 0):t=void 0,n(e)?(c=u.call(e,"c"),s=u.call(e,"e")):(c=!0,s=!1),p={get:t,set:r,configurable:c,enumerable:s},l?o(i(l),p):p}},56656:function(e){e.exports=function(){"use strict";var e=1e3,t=6e4,r=36e5,n="millisecond",a="second",o="minute",i="hour",u="day",c="week",s="month",l="quarter",p="year",f="date",_="Invalid 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"},48742:function(e){"use strict";e.exports="data:image/png;base64,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"},70689:function(e){"use strict";e.exports="data:image/png;base64,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"},65985:function(e){"use strict";e.exports="data:image/png;base64,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"},1938:function(e){"use strict";e.exports="data:image/png;base64,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"},89718:function(e){"use strict";e.exports="data:image/png;base64,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"},79390:function(e){"use strict";e.exports="data:image/png;base64,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"},51466:function(e){"use strict";e.exports="data:image/png;base64,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r(e,t,a)},_map:"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/="}}(),n.enc.Base64)},52695:function(e,t,r){var n;e.exports=(n=r(52952),function(){var e=n,t=e.lib.WordArray;function r(e,r,n){for(var a=[],o=0,i=0;i<r;i++)if(i%4){var u=n[e.charCodeAt(i-1)]<<i%4*2|n[e.charCodeAt(i)]>>>6-i%4*2;a[o>>>2]|=u<<24-o%4*8,o++}return t.create(a,o)}e.enc.Base64url={stringify:function(e,t=!0){var r=e.words,n=e.sigBytes,a=t?this._safe_map:this._map;e.clamp();for(var o=[],i=0;i<n;i+=3)for(var u=(r[i>>>2]>>>24-i%4*8&255)<<16|(r[i+1>>>2]>>>24-(i+1)%4*8&255)<<8|r[i+2>>>2]>>>24-(i+2)%4*8&255,c=0;c<4&&i+.75*c<n;c++)o.push(a.charAt(u>>>6*(3-c)&63));var s=a.charAt(64);if(s)for(;o.length%4;)o.push(s);return o.join("")},parse:function(e,t=!0){var n=e.length,a=t?this._safe_map:this._map,o=this._reverseMap;if(!o){o=this._reverseMap=[];for(var i=0;i<a.length;i++)o[a.charCodeAt(i)]=i}var u=a.charAt(64);if(u){var c=e.indexOf(u);-1!==c&&(n=c)}return r(e,n,o)},_map:"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/=",_safe_map:"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789-_"}}(),n.enc.Base64url)},73323:function(e,t,r){var n;e.exports=(n=r(52952),function(){var e=n,t=e.lib.WordArray,r=e.enc;function a(e){return e<<8&4278255360|e>>>8&16711935}r.Utf16=r.Utf16BE={stringify:function(e){for(var t=e.words,r=e.sigBytes,n=[],a=0;a<r;a+=2){var o=t[a>>>2]>>>16-a%4*8&65535;n.push(String.fromCharCode(o))}return n.join("")},parse:function(e){for(var r=e.length,n=[],a=0;a<r;a++)n[a>>>1]|=e.charCodeAt(a)<<16-a%2*16;return t.create(n,2*r)}},r.Utf16LE={stringify:function(e){for(var t=e.words,r=e.sigBytes,n=[],o=0;o<r;o+=2){var i=a(t[o>>>2]>>>16-o%4*8&65535);n.push(String.fromCharCode(i))}return n.join("")},parse:function(e){for(var r=e.length,n=[],o=0;o<r;o++)n[o>>>1]|=a(e.charCodeAt(o)<<16-o%2*16);return t.create(n,2*r)}}}(),n.enc.Utf16)},28492:function(e,t,r){var n,a,o,i,u,c,s,l;e.exports=(l=r(52952),r(49479),r(83760),a=(n=l).lib,o=a.Base,i=a.WordArray,u=n.algo,c=u.MD5,s=u.EvpKDF=o.extend({cfg:o.extend({keySize:4,hasher:c,iterations:1}),init:function(e){this.cfg=this.cfg.extend(e)},compute:function(e,t){for(var r,n=this.cfg,a=n.hasher.create(),o=i.create(),u=o.words,c=n.keySize,s=n.iterations;u.length<c;){r&&a.update(r),r=a.update(e).finalize(t),a.reset();for(var l=1;l<s;l++)r=a.finalize(r),a.reset();o.concat(r)}return o.sigBytes=4*c,o}}),n.EvpKDF=function(e,t,r){return s.create(r).compute(e,t)},l.EvpKDF)},24408:function(e,t,r){var n,a,o,i;e.exports=(i=r(52952),r(93617),a=(n=i).lib.CipherParams,o=n.enc.Hex,n.format.Hex={stringify:function(e){return e.ciphertext.toString(o)},parse:function(e){var t=o.parse(e);return a.create({ciphertext:t})}},i.format.Hex)},83760:function(e,t,r){var n,a,o,i;e.exports=(n=r(52952),o=(a=n).lib.Base,i=a.enc.Utf8,void(a.algo.HMAC=o.extend({init:function(e,t){e=this._hasher=new e.init,"string"==typeof t&&(t=i.parse(t));var r=e.blockSize,n=4*r;t.sigBytes>n&&(t=e.finalize(t)),t.clamp();for(var a=this._oKey=t.clone(),o=this._iKey=t.clone(),u=a.words,c=o.words,s=0;s<r;s++)u[s]^=1549556828,c[s]^=909522486;a.sigBytes=o.sigBytes=n,this.reset()},reset:function(){var e=this._hasher;e.reset(),e.update(this._iKey)},update:function(e){return this._hasher.update(e),this},finalize:function(e){var t=this._hasher,r=t.finalize(e);return t.reset(),t.finalize(this._oKey.clone().concat(r))}})))},28209:function(e,t,r){var n;e.exports=(n=r(52952),r(41988),r(79183),r(73323),r(35909),r(52695),r(34905),r(49479),r(2481),r(93653),r(12133),r(82307),r(79421),r(25824),r(83760),r(37248),r(28492),r(93617),r(2882),r(98277),r(69972),r(30509),r(79182),r(74990),r(2593),r(10829),r(10265),r(18846),r(24408),r(84452),r(61945),r(22528),r(21865),r(35308),n)},79183:function(e,t,r){var n;e.exports=(n=r(52952),function(){if("function"==typeof ArrayBuffer){var e=n.lib.WordArray,t=e.init,r=e.init=function(e){if(e instanceof ArrayBuffer&&(e=new Uint8Array(e)),(e instanceof Int8Array||"undefined"!=typeof Uint8ClampedArray&&e instanceof Uint8ClampedArray||e instanceof Int16Array||e instanceof Uint16Array||e instanceof Int32Array||e instanceof Uint32Array||e instanceof Float32Array||e instanceof Float64Array)&&(e=new Uint8Array(e.buffer,e.byteOffset,e.byteLength)),e instanceof Uint8Array){for(var r=e.byteLength,n=[],a=0;a<r;a++)n[a>>>2]|=e[a]<<24-a%4*8;t.call(this,n,r)}else t.apply(this,arguments)};r.prototype=e}}(),n.lib.WordArray)},34905:function(e,t,r){var n;e.exports=(n=r(52952),function(e){var t=n,r=t.lib,a=r.WordArray,o=r.Hasher,i=t.algo,u=[];!function(){for(var t=0;t<64;t++)u[t]=4294967296*e.abs(e.sin(t+1))|0}();var c=i.MD5=o.extend({_doReset:function(){this._hash=new a.init([1732584193,4023233417,2562383102,271733878])},_doProcessBlock:function(e,t){for(var r=0;r<16;r++){var n=t+r,a=e[n];e[n]=16711935&(a<<8|a>>>24)|4278255360&(a<<24|a>>>8)}var o=this._hash.words,i=e[t+0],c=e[t+1],_=e[t+2],d=e[t+3],h=e[t+4],m=e[t+5],v=e[t+6],b=e[t+7],y=e[t+8],g=e[t+9],w=e[t+10],x=e[t+11],k=e[t+12],P=e[t+13],E=e[t+14],S=e[t+15],C=o[0],j=o[1],q=o[2],I=o[3];C=s(C,j,q,I,i,7,u[0]),I=s(I,C,j,q,c,12,u[1]),q=s(q,I,C,j,_,17,u[2]),j=s(j,q,I,C,d,22,u[3]),C=s(C,j,q,I,h,7,u[4]),I=s(I,C,j,q,m,12,u[5]),q=s(q,I,C,j,v,17,u[6]),j=s(j,q,I,C,b,22,u[7]),C=s(C,j,q,I,y,7,u[8]),I=s(I,C,j,q,g,12,u[9]),q=s(q,I,C,j,w,17,u[10]),j=s(j,q,I,C,x,22,u[11]),C=s(C,j,q,I,k,7,u[12]),I=s(I,C,j,q,P,12,u[13]),q=s(q,I,C,j,E,17,u[14]),C=l(C,j=s(j,q,I,C,S,22,u[15]),q,I,c,5,u[16]),I=l(I,C,j,q,v,9,u[17]),q=l(q,I,C,j,x,14,u[18]),j=l(j,q,I,C,i,20,u[19]),C=l(C,j,q,I,m,5,u[20]),I=l(I,C,j,q,w,9,u[21]),q=l(q,I,C,j,S,14,u[22]),j=l(j,q,I,C,h,20,u[23]),C=l(C,j,q,I,g,5,u[24]),I=l(I,C,j,q,E,9,u[25]),q=l(q,I,C,j,d,14,u[26]),j=l(j,q,I,C,y,20,u[27]),C=l(C,j,q,I,P,5,u[28]),I=l(I,C,j,q,_,9,u[29]),q=l(q,I,C,j,b,14,u[30]),C=p(C,j=l(j,q,I,C,k,20,u[31]),q,I,m,4,u[32]),I=p(I,C,j,q,y,11,u[33]),q=p(q,I,C,j,x,16,u[34]),j=p(j,q,I,C,E,23,u[35]),C=p(C,j,q,I,c,4,u[36]),I=p(I,C,j,q,h,11,u[37]),q=p(q,I,C,j,b,16,u[38]),j=p(j,q,I,C,w,23,u[39]),C=p(C,j,q,I,P,4,u[40]),I=p(I,C,j,q,i,11,u[41]),q=p(q,I,C,j,d,16,u[42]),j=p(j,q,I,C,v,23,u[43]),C=p(C,j,q,I,g,4,u[44]),I=p(I,C,j,q,k,11,u[45]),q=p(q,I,C,j,S,16,u[46]),C=f(C,j=p(j,q,I,C,_,23,u[47]),q,I,i,6,u[48]),I=f(I,C,j,q,b,10,u[49]),q=f(q,I,C,j,E,15,u[50]),j=f(j,q,I,C,m,21,u[51]),C=f(C,j,q,I,k,6,u[52]),I=f(I,C,j,q,d,10,u[53]),q=f(q,I,C,j,w,15,u[54]),j=f(j,q,I,C,c,21,u[55]),C=f(C,j,q,I,y,6,u[56]),I=f(I,C,j,q,S,10,u[57]),q=f(q,I,C,j,v,15,u[58]),j=f(j,q,I,C,P,21,u[59]),C=f(C,j,q,I,h,6,u[60]),I=f(I,C,j,q,x,10,u[61]),q=f(q,I,C,j,_,15,u[62]),j=f(j,q,I,C,g,21,u[63]),o[0]=o[0]+C|0,o[1]=o[1]+j|0,o[2]=o[2]+q|0,o[3]=o[3]+I|0},_doFinalize:function(){var t=this._data,r=t.words,n=8*this._nDataBytes,a=8*t.sigBytes;r[a>>>5]|=128<<24-a%32;var o=e.floor(n/4294967296),i=n;r[15+(a+64>>>9<<4)]=16711935&(o<<8|o>>>24)|4278255360&(o<<24|o>>>8),r[14+(a+64>>>9<<4)]=16711935&(i<<8|i>>>24)|4278255360&(i<<24|i>>>8),t.sigBytes=4*(r.length+1),this._process();for(var u=this._hash,c=u.words,s=0;s<4;s++){var l=c[s];c[s]=16711935&(l<<8|l>>>24)|4278255360&(l<<24|l>>>8)}return u},clone:function(){var e=o.clone.call(this);return e._hash=this._hash.clone(),e}});function s(e,t,r,n,a,o,i){var u=e+(t&r|~t&n)+a+i;return(u<<o|u>>>32-o)+t}function l(e,t,r,n,a,o,i){var u=e+(t&n|r&~n)+a+i;return(u<<o|u>>>32-o)+t}function p(e,t,r,n,a,o,i){var u=e+(t^r^n)+a+i;return(u<<o|u>>>32-o)+t}function f(e,t,r,n,a,o,i){var u=e+(r^(t|~n))+a+i;return(u<<o|u>>>32-o)+t}t.MD5=o._createHelper(c),t.HmacMD5=o._createHmacHelper(c)}(Math),n.MD5)},2882:function(e,t,r){var n;e.exports=(n=r(52952),r(93617),n.mode.CFB=function(){var e=n.lib.BlockCipherMode.extend();function t(e,t,r,n){var a,o=this._iv;o?(a=o.slice(0),this._iv=void 0):a=this._prevBlock,n.encryptBlock(a,0);for(var i=0;i<r;i++)e[t+i]^=a[i]}return e.Encryptor=e.extend({processBlock:function(e,r){var n=this._cipher,a=n.blockSize;t.call(this,e,r,a,n),this._prevBlock=e.slice(r,r+a)}}),e.Decryptor=e.extend({processBlock:function(e,r){var n=this._cipher,a=n.blockSize,o=e.slice(r,r+a);t.call(this,e,r,a,n),this._prevBlock=o}}),e}(),n.mode.CFB)},69972:function(e,t,r){var n;e.exports=(n=r(52952),r(93617),n.mode.CTRGladman=function(){var e=n.lib.BlockCipherMode.extend();function t(e){if(255==(e>>24&255)){var t=e>>16&255,r=e>>8&255,n=255&e;255===t?(t=0,255===r?(r=0,255===n?n=0:++n):++r):++t,e=0,e+=t<<16,e+=r<<8,e+=n}else e+=1<<24;return e}function r(e){return 0===(e[0]=t(e[0]))&&(e[1]=t(e[1])),e}var a=e.Encryptor=e.extend({processBlock:function(e,t){var n=this._cipher,a=n.blockSize,o=this._iv,i=this._counter;o&&(i=this._counter=o.slice(0),this._iv=void 0),r(i);var u=i.slice(0);n.encryptBlock(u,0);for(var c=0;c<a;c++)e[t+c]^=u[c]}});return e.Decryptor=a,e}(),n.mode.CTRGladman)},98277:function(e,t,r){var n,a,o;e.exports=(o=r(52952),r(93617),o.mode.CTR=(n=o.lib.BlockCipherMode.extend(),a=n.Encryptor=n.extend({processBlock:function(e,t){var r=this._cipher,n=r.blockSize,a=this._iv,o=this._counter;a&&(o=this._counter=a.slice(0),this._iv=void 0);var i=o.slice(0);r.encryptBlock(i,0),o[n-1]=o[n-1]+1|0;for(var u=0;u<n;u++)e[t+u]^=i[u]}}),n.Decryptor=a,n),o.mode.CTR)},79182:function(e,t,r){var n,a;e.exports=(a=r(52952),r(93617),a.mode.ECB=((n=a.lib.BlockCipherMode.extend()).Encryptor=n.extend({processBlock:function(e,t){this._cipher.encryptBlock(e,t)}}),n.Decryptor=n.extend({processBlock:function(e,t){this._cipher.decryptBlock(e,t)}}),n),a.mode.ECB)},30509:function(e,t,r){var n,a,o;e.exports=(o=r(52952),r(93617),o.mode.OFB=(n=o.lib.BlockCipherMode.extend(),a=n.Encryptor=n.extend({processBlock:function(e,t){var r=this._cipher,n=r.blockSize,a=this._iv,o=this._keystream;a&&(o=this._keystream=a.slice(0),this._iv=void 0),r.encryptBlock(o,0);for(var i=0;i<n;i++)e[t+i]^=o[i]}}),n.Decryptor=a,n),o.mode.OFB)},74990:function(e,t,r){var n;e.exports=(n=r(52952),r(93617),n.pad.AnsiX923={pad:function(e,t){var r=e.sigBytes,n=4*t,a=n-r%n,o=r+a-1;e.clamp(),e.words[o>>>2]|=a<<24-o%4*8,e.sigBytes+=a},unpad:function(e){var t=255&e.words[e.sigBytes-1>>>2];e.sigBytes-=t}},n.pad.Ansix923)},2593:function(e,t,r){var n;e.exports=(n=r(52952),r(93617),n.pad.Iso10126={pad:function(e,t){var r=4*t,a=r-e.sigBytes%r;e.concat(n.lib.WordArray.random(a-1)).concat(n.lib.WordArray.create([a<<24],1))},unpad:function(e){var t=255&e.words[e.sigBytes-1>>>2];e.sigBytes-=t}},n.pad.Iso10126)},10829:function(e,t,r){var n;e.exports=(n=r(52952),r(93617),n.pad.Iso97971={pad:function(e,t){e.concat(n.lib.WordArray.create([2147483648],1)),n.pad.ZeroPadding.pad(e,t)},unpad:function(e){n.pad.ZeroPadding.unpad(e),e.sigBytes--}},n.pad.Iso97971)},18846:function(e,t,r){var n;e.exports=(n=r(52952),r(93617),n.pad.NoPadding={pad:function(){},unpad:function(){}},n.pad.NoPadding)},10265:function(e,t,r){var n;e.exports=(n=r(52952),r(93617),n.pad.ZeroPadding={pad:function(e,t){var r=4*t;e.clamp(),e.sigBytes+=r-(e.sigBytes%r||r)},unpad:function(e){var t=e.words,r=e.sigBytes-1;for(r=e.sigBytes-1;r>=0;r--)if(t[r>>>2]>>>24-r%4*8&255){e.sigBytes=r+1;break}}},n.pad.ZeroPadding)},37248:function(e,t,r){var n,a,o,i,u,c,s,l,p;e.exports=(p=r(52952),r(49479),r(83760),a=(n=p).lib,o=a.Base,i=a.WordArray,u=n.algo,c=u.SHA1,s=u.HMAC,l=u.PBKDF2=o.extend({cfg:o.extend({keySize:4,hasher:c,iterations:1}),init:function(e){this.cfg=this.cfg.extend(e)},compute:function(e,t){for(var r=this.cfg,n=s.create(r.hasher,e),a=i.create(),o=i.create([1]),u=a.words,c=o.words,l=r.keySize,p=r.iterations;u.length<l;){var f=n.update(t).finalize(o);n.reset();for(var _=f.words,d=_.length,h=f,m=1;m<p;m++){h=n.finalize(h),n.reset();for(var v=h.words,b=0;b<d;b++)_[b]^=v[b]}a.concat(f),c[0]++}return a.sigBytes=4*l,a}}),n.PBKDF2=function(e,t,r){return l.create(r).compute(e,t)},p.PBKDF2)},35308:function(e,t,r){var n;e.exports=(n=r(52952),r(35909),r(34905),r(28492),r(93617),function(){var e=n,t=e.lib.StreamCipher,r=e.algo,a=[],o=[],i=[],u=r.RabbitLegacy=t.extend({_doReset:function(){var e=this._key.words,t=this.cfg.iv,r=this._X=[e[0],e[3]<<16|e[2]>>>16,e[1],e[0]<<16|e[3]>>>16,e[2],e[1]<<16|e[0]>>>16,e[3],e[2]<<16|e[1]>>>16],n=this._C=[e[2]<<16|e[2]>>>16,4294901760&e[0]|65535&e[1],e[3]<<16|e[3]>>>16,4294901760&e[1]|65535&e[2],e[0]<<16|e[0]>>>16,4294901760&e[2]|65535&e[3],e[1]<<16|e[1]>>>16,4294901760&e[3]|65535&e[0]];this._b=0;for(var a=0;a<4;a++)c.call(this);for(a=0;a<8;a++)n[a]^=r[a+4&7];if(t){var o=t.words,i=o[0],u=o[1],s=16711935&(i<<8|i>>>24)|4278255360&(i<<24|i>>>8),l=16711935&(u<<8|u>>>24)|4278255360&(u<<24|u>>>8),p=s>>>16|4294901760&l,f=l<<16|65535&s;for(n[0]^=s,n[1]^=p,n[2]^=l,n[3]^=f,n[4]^=s,n[5]^=p,n[6]^=l,n[7]^=f,a=0;a<4;a++)c.call(this)}},_doProcessBlock:function(e,t){var r=this._X;c.call(this),a[0]=r[0]^r[5]>>>16^r[3]<<16,a[1]=r[2]^r[7]>>>16^r[5]<<16,a[2]=r[4]^r[1]>>>16^r[7]<<16,a[3]=r[6]^r[3]>>>16^r[1]<<16;for(var n=0;n<4;n++)a[n]=16711935&(a[n]<<8|a[n]>>>24)|4278255360&(a[n]<<24|a[n]>>>8),e[t+n]^=a[n]},blockSize:4,ivSize:2});function c(){for(var e=this._X,t=this._C,r=0;r<8;r++)o[r]=t[r];for(t[0]=t[0]+1295307597+this._b|0,t[1]=t[1]+3545052371+(t[0]>>>0<o[0]>>>0?1:0)|0,t[2]=t[2]+886263092+(t[1]>>>0<o[1]>>>0?1:0)|0,t[3]=t[3]+1295307597+(t[2]>>>0<o[2]>>>0?1:0)|0,t[4]=t[4]+3545052371+(t[3]>>>0<o[3]>>>0?1:0)|0,t[5]=t[5]+886263092+(t[4]>>>0<o[4]>>>0?1:0)|0,t[6]=t[6]+1295307597+(t[5]>>>0<o[5]>>>0?1:0)|0,t[7]=t[7]+3545052371+(t[6]>>>0<o[6]>>>0?1:0)|0,this._b=t[7]>>>0<o[7]>>>0?1:0,r=0;r<8;r++){var n=e[r]+t[r],a=65535&n,u=n>>>16,c=((a*a>>>17)+a*u>>>15)+u*u,s=((4294901760&n)*n|0)+((65535&n)*n|0);i[r]=c^s}e[0]=i[0]+(i[7]<<16|i[7]>>>16)+(i[6]<<16|i[6]>>>16)|0,e[1]=i[1]+(i[0]<<8|i[0]>>>24)+i[7]|0,e[2]=i[2]+(i[1]<<16|i[1]>>>16)+(i[0]<<16|i[0]>>>16)|0,e[3]=i[3]+(i[2]<<8|i[2]>>>24)+i[1]|0,e[4]=i[4]+(i[3]<<16|i[3]>>>16)+(i[2]<<16|i[2]>>>16)|0,e[5]=i[5]+(i[4]<<8|i[4]>>>24)+i[3]|0,e[6]=i[6]+(i[5]<<16|i[5]>>>16)+(i[4]<<16|i[4]>>>16)|0,e[7]=i[7]+(i[6]<<8|i[6]>>>24)+i[5]|0}e.RabbitLegacy=t._createHelper(u)}(),n.RabbitLegacy)},21865:function(e,t,r){var n;e.exports=(n=r(52952),r(35909),r(34905),r(28492),r(93617),function(){var e=n,t=e.lib.StreamCipher,r=e.algo,a=[],o=[],i=[],u=r.Rabbit=t.extend({_doReset:function(){for(var e=this._key.words,t=this.cfg.iv,r=0;r<4;r++)e[r]=16711935&(e[r]<<8|e[r]>>>24)|4278255360&(e[r]<<24|e[r]>>>8);var n=this._X=[e[0],e[3]<<16|e[2]>>>16,e[1],e[0]<<16|e[3]>>>16,e[2],e[1]<<16|e[0]>>>16,e[3],e[2]<<16|e[1]>>>16],a=this._C=[e[2]<<16|e[2]>>>16,4294901760&e[0]|65535&e[1],e[3]<<16|e[3]>>>16,4294901760&e[1]|65535&e[2],e[0]<<16|e[0]>>>16,4294901760&e[2]|65535&e[3],e[1]<<16|e[1]>>>16,4294901760&e[3]|65535&e[0]];for(this._b=0,r=0;r<4;r++)c.call(this);for(r=0;r<8;r++)a[r]^=n[r+4&7];if(t){var o=t.words,i=o[0],u=o[1],s=16711935&(i<<8|i>>>24)|4278255360&(i<<24|i>>>8),l=16711935&(u<<8|u>>>24)|4278255360&(u<<24|u>>>8),p=s>>>16|4294901760&l,f=l<<16|65535&s;for(a[0]^=s,a[1]^=p,a[2]^=l,a[3]^=f,a[4]^=s,a[5]^=p,a[6]^=l,a[7]^=f,r=0;r<4;r++)c.call(this)}},_doProcessBlock:function(e,t){var r=this._X;c.call(this),a[0]=r[0]^r[5]>>>16^r[3]<<16,a[1]=r[2]^r[7]>>>16^r[5]<<16,a[2]=r[4]^r[1]>>>16^r[7]<<16,a[3]=r[6]^r[3]>>>16^r[1]<<16;for(var n=0;n<4;n++)a[n]=16711935&(a[n]<<8|a[n]>>>24)|4278255360&(a[n]<<24|a[n]>>>8),e[t+n]^=a[n]},blockSize:4,ivSize:2});function c(){for(var e=this._X,t=this._C,r=0;r<8;r++)o[r]=t[r];for(t[0]=t[0]+1295307597+this._b|0,t[1]=t[1]+3545052371+(t[0]>>>0<o[0]>>>0?1:0)|0,t[2]=t[2]+886263092+(t[1]>>>0<o[1]>>>0?1:0)|0,t[3]=t[3]+1295307597+(t[2]>>>0<o[2]>>>0?1:0)|0,t[4]=t[4]+3545052371+(t[3]>>>0<o[3]>>>0?1:0)|0,t[5]=t[5]+886263092+(t[4]>>>0<o[4]>>>0?1:0)|0,t[6]=t[6]+1295307597+(t[5]>>>0<o[5]>>>0?1:0)|0,t[7]=t[7]+3545052371+(t[6]>>>0<o[6]>>>0?1:0)|0,this._b=t[7]>>>0<o[7]>>>0?1:0,r=0;r<8;r++){var n=e[r]+t[r],a=65535&n,u=n>>>16,c=((a*a>>>17)+a*u>>>15)+u*u,s=((4294901760&n)*n|0)+((65535&n)*n|0);i[r]=c^s}e[0]=i[0]+(i[7]<<16|i[7]>>>16)+(i[6]<<16|i[6]>>>16)|0,e[1]=i[1]+(i[0]<<8|i[0]>>>24)+i[7]|0,e[2]=i[2]+(i[1]<<16|i[1]>>>16)+(i[0]<<16|i[0]>>>16)|0,e[3]=i[3]+(i[2]<<8|i[2]>>>24)+i[1]|0,e[4]=i[4]+(i[3]<<16|i[3]>>>16)+(i[2]<<16|i[2]>>>16)|0,e[5]=i[5]+(i[4]<<8|i[4]>>>24)+i[3]|0,e[6]=i[6]+(i[5]<<16|i[5]>>>16)+(i[4]<<16|i[4]>>>16)|0,e[7]=i[7]+(i[6]<<8|i[6]>>>24)+i[5]|0}e.Rabbit=t._createHelper(u)}(),n.Rabbit)},22528:function(e,t,r){var n;e.exports=(n=r(52952),r(35909),r(34905),r(28492),r(93617),function(){var e=n,t=e.lib.StreamCipher,r=e.algo,a=r.RC4=t.extend({_doReset:function(){for(var e=this._key,t=e.words,r=e.sigBytes,n=this._S=[],a=0;a<256;a++)n[a]=a;a=0;for(var o=0;a<256;a++){var i=a%r,u=t[i>>>2]>>>24-i%4*8&255;o=(o+n[a]+u)%256;var c=n[a];n[a]=n[o],n[o]=c}this._i=this._j=0},_doProcessBlock:function(e,t){e[t]^=o.call(this)},keySize:8,ivSize:0});function o(){for(var e=this._S,t=this._i,r=this._j,n=0,a=0;a<4;a++){r=(r+e[t=(t+1)%256])%256;var o=e[t];e[t]=e[r],e[r]=o,n|=e[(e[t]+e[r])%256]<<24-8*a}return this._i=t,this._j=r,n}e.RC4=t._createHelper(a);var i=r.RC4Drop=a.extend({cfg:a.cfg.extend({drop:192}),_doReset:function(){a._doReset.call(this);for(var e=this.cfg.drop;e>0;e--)o.call(this)}});e.RC4Drop=t._createHelper(i)}(),n.RC4)},25824:function(e,t,r){var n;e.exports=(n=r(52952),function(e){var t=n,r=t.lib,a=r.WordArray,o=r.Hasher,i=t.algo,u=a.create([0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,7,4,13,1,10,6,15,3,12,0,9,5,2,14,11,8,3,10,14,4,9,15,8,1,2,7,0,6,13,11,5,12,1,9,11,10,0,8,12,4,13,3,7,15,14,5,6,2,4,0,5,9,7,12,2,10,14,1,3,8,11,6,15,13]),c=a.create([5,14,7,0,9,2,11,4,13,6,15,8,1,10,3,12,6,11,3,7,0,13,5,10,14,15,8,12,4,9,1,2,15,5,1,3,7,14,6,9,11,8,12,2,10,0,4,13,8,6,4,1,3,11,15,0,5,12,2,13,9,7,10,14,12,15,10,4,1,5,8,7,6,2,13,14,0,3,9,11]),s=a.create([11,14,15,12,5,8,7,9,11,13,14,15,6,7,9,8,7,6,8,13,11,9,7,15,7,12,15,9,11,7,13,12,11,13,6,7,14,9,13,15,14,8,13,6,5,12,7,5,11,12,14,15,14,15,9,8,9,14,5,6,8,6,5,12,9,15,5,11,6,8,13,12,5,12,13,14,11,8,5,6]),l=a.create([8,9,9,11,13,15,15,5,7,7,8,11,14,14,12,6,9,13,15,7,12,8,9,11,7,7,12,7,6,15,13,11,9,7,15,11,8,6,6,14,12,13,5,14,13,13,7,5,15,5,8,11,14,14,6,14,6,9,12,9,12,5,15,8,8,5,12,9,12,5,14,6,8,13,6,5,15,13,11,11]),p=a.create([0,1518500249,1859775393,2400959708,2840853838]),f=a.create([1352829926,1548603684,1836072691,2053994217,0]),_=i.RIPEMD160=o.extend({_doReset:function(){this._hash=a.create([1732584193,4023233417,2562383102,271733878,3285377520])},_doProcessBlock:function(e,t){for(var r=0;r<16;r++){var n=t+r,a=e[n];e[n]=16711935&(a<<8|a>>>24)|4278255360&(a<<24|a>>>8)}var o,i,_,g,w,x,k,P,E,S,C,j=this._hash.words,q=p.words,I=f.words,O=u.words,A=c.words,D=s.words,T=l.words;for(x=o=j[0],k=i=j[1],P=_=j[2],E=g=j[3],S=w=j[4],r=0;r<80;r+=1)C=o+e[t+O[r]]|0,C+=r<16?d(i,_,g)+q[0]:r<32?h(i,_,g)+q[1]:r<48?m(i,_,g)+q[2]:r<64?v(i,_,g)+q[3]:b(i,_,g)+q[4],C=(C=y(C|=0,D[r]))+w|0,o=w,w=g,g=y(_,10),_=i,i=C,C=x+e[t+A[r]]|0,C+=r<16?b(k,P,E)+I[0]:r<32?v(k,P,E)+I[1]:r<48?m(k,P,E)+I[2]:r<64?h(k,P,E)+I[3]:d(k,P,E)+I[4],C=(C=y(C|=0,T[r]))+S|0,x=S,S=E,E=y(P,10),P=k,k=C;C=j[1]+_+E|0,j[1]=j[2]+g+S|0,j[2]=j[3]+w+x|0,j[3]=j[4]+o+k|0,j[4]=j[0]+i+P|0,j[0]=C},_doFinalize:function(){var e=this._data,t=e.words,r=8*this._nDataBytes,n=8*e.sigBytes;t[n>>>5]|=128<<24-n%32,t[14+(n+64>>>9<<4)]=16711935&(r<<8|r>>>24)|4278255360&(r<<24|r>>>8),e.sigBytes=4*(t.length+1),this._process();for(var a=this._hash,o=a.words,i=0;i<5;i++){var u=o[i];o[i]=16711935&(u<<8|u>>>24)|4278255360&(u<<24|u>>>8)}return a},clone:function(){var e=o.clone.call(this);return e._hash=this._hash.clone(),e}});function d(e,t,r){return e^t^r}function h(e,t,r){return e&t|~e&r}function m(e,t,r){return(e|~t)^r}function v(e,t,r){return e&r|t&~r}function b(e,t,r){return e^(t|~r)}function y(e,t){return e<<t|e>>>32-t}t.RIPEMD160=o._createHelper(_),t.HmacRIPEMD160=o._createHmacHelper(_)}(Math),n.RIPEMD160)},49479:function(e,t,r){var n,a,o,i,u,c,s,l;e.exports=(l=r(52952),a=(n=l).lib,o=a.WordArray,i=a.Hasher,u=n.algo,c=[],s=u.SHA1=i.extend({_doReset:function(){this._hash=new o.init([1732584193,4023233417,2562383102,271733878,3285377520])},_doProcessBlock:function(e,t){for(var r=this._hash.words,n=r[0],a=r[1],o=r[2],i=r[3],u=r[4],s=0;s<80;s++){if(s<16)c[s]=0|e[t+s];else{var l=c[s-3]^c[s-8]^c[s-14]^c[s-16];c[s]=l<<1|l>>>31}var p=(n<<5|n>>>27)+u+c[s];p+=s<20?1518500249+(a&o|~a&i):s<40?1859775393+(a^o^i):s<60?(a&o|a&i|o&i)-1894007588:(a^o^i)-899497514,u=i,i=o,o=a<<30|a>>>2,a=n,n=p}r[0]=r[0]+n|0,r[1]=r[1]+a|0,r[2]=r[2]+o|0,r[3]=r[3]+i|0,r[4]=r[4]+u|0},_doFinalize:function(){var e=this._data,t=e.words,r=8*this._nDataBytes,n=8*e.sigBytes;return t[n>>>5]|=128<<24-n%32,t[14+(n+64>>>9<<4)]=Math.floor(r/4294967296),t[15+(n+64>>>9<<4)]=r,e.sigBytes=4*t.length,this._process(),this._hash},clone:function(){var e=i.clone.call(this);return e._hash=this._hash.clone(),e}}),n.SHA1=i._createHelper(s),n.HmacSHA1=i._createHmacHelper(s),l.SHA1)},93653:function(e,t,r){var n,a,o,i,u,c;e.exports=(c=r(52952),r(2481),a=(n=c).lib.WordArray,o=n.algo,i=o.SHA256,u=o.SHA224=i.extend({_doReset:function(){this._hash=new a.init([3238371032,914150663,812702999,4144912697,4290775857,1750603025,1694076839,3204075428])},_doFinalize:function(){var e=i._doFinalize.call(this);return e.sigBytes-=4,e}}),n.SHA224=i._createHelper(u),n.HmacSHA224=i._createHmacHelper(u),c.SHA224)},2481:function(e,t,r){var n;e.exports=(n=r(52952),function(e){var t=n,r=t.lib,a=r.WordArray,o=r.Hasher,i=t.algo,u=[],c=[];!function(){function t(t){for(var r=e.sqrt(t),n=2;n<=r;n++)if(!(t%n))return!1;return!0}function r(e){return 4294967296*(e-(0|e))|0}for(var n=2,a=0;a<64;)t(n)&&(a<8&&(u[a]=r(e.pow(n,.5))),c[a]=r(e.pow(n,1/3)),a++),n++}();var s=[],l=i.SHA256=o.extend({_doReset:function(){this._hash=new a.init(u.slice(0))},_doProcessBlock:function(e,t){for(var r=this._hash.words,n=r[0],a=r[1],o=r[2],i=r[3],u=r[4],l=r[5],p=r[6],f=r[7],_=0;_<64;_++){if(_<16)s[_]=0|e[t+_];else{var d=s[_-15],h=(d<<25|d>>>7)^(d<<14|d>>>18)^d>>>3,m=s[_-2],v=(m<<15|m>>>17)^(m<<13|m>>>19)^m>>>10;s[_]=h+s[_-7]+v+s[_-16]}var b=n&a^n&o^a&o,y=(n<<30|n>>>2)^(n<<19|n>>>13)^(n<<10|n>>>22),g=f+((u<<26|u>>>6)^(u<<21|u>>>11)^(u<<7|u>>>25))+(u&l^~u&p)+c[_]+s[_];f=p,p=l,l=u,u=i+g|0,i=o,o=a,a=n,n=g+(y+b)|0}r[0]=r[0]+n|0,r[1]=r[1]+a|0,r[2]=r[2]+o|0,r[3]=r[3]+i|0,r[4]=r[4]+u|0,r[5]=r[5]+l|0,r[6]=r[6]+p|0,r[7]=r[7]+f|0},_doFinalize:function(){var t=this._data,r=t.words,n=8*this._nDataBytes,a=8*t.sigBytes;return r[a>>>5]|=128<<24-a%32,r[14+(a+64>>>9<<4)]=e.floor(n/4294967296),r[15+(a+64>>>9<<4)]=n,t.sigBytes=4*r.length,this._process(),this._hash},clone:function(){var e=o.clone.call(this);return e._hash=this._hash.clone(),e}});t.SHA256=o._createHelper(l),t.HmacSHA256=o._createHmacHelper(l)}(Math),n.SHA256)},79421:function(e,t,r){var n;e.exports=(n=r(52952),r(41988),function(e){var t=n,r=t.lib,a=r.WordArray,o=r.Hasher,i=t.x64.Word,u=t.algo,c=[],s=[],l=[];!function(){for(var e=1,t=0,r=0;r<24;r++){c[e+5*t]=(r+1)*(r+2)/2%64;var n=(2*e+3*t)%5;e=t%5,t=n}for(e=0;e<5;e++)for(t=0;t<5;t++)s[e+5*t]=t+(2*e+3*t)%5*5;for(var a=1,o=0;o<24;o++){for(var u=0,p=0,f=0;f<7;f++){if(1&a){var _=(1<<f)-1;_<32?p^=1<<_:u^=1<<_-32}128&a?a=a<<1^113:a<<=1}l[o]=i.create(u,p)}}();var p=[];!function(){for(var e=0;e<25;e++)p[e]=i.create()}();var f=u.SHA3=o.extend({cfg:o.cfg.extend({outputLength:512}),_doReset:function(){for(var e=this._state=[],t=0;t<25;t++)e[t]=new i.init;this.blockSize=(1600-2*this.cfg.outputLength)/32},_doProcessBlock:function(e,t){for(var r=this._state,n=this.blockSize/2,a=0;a<n;a++){var o=e[t+2*a],i=e[t+2*a+1];o=16711935&(o<<8|o>>>24)|4278255360&(o<<24|o>>>8),i=16711935&(i<<8|i>>>24)|4278255360&(i<<24|i>>>8),(j=r[a]).high^=i,j.low^=o}for(var u=0;u<24;u++){for(var f=0;f<5;f++){for(var _=0,d=0,h=0;h<5;h++)_^=(j=r[f+5*h]).high,d^=j.low;var m=p[f];m.high=_,m.low=d}for(f=0;f<5;f++){var v=p[(f+4)%5],b=p[(f+1)%5],y=b.high,g=b.low;for(_=v.high^(y<<1|g>>>31),d=v.low^(g<<1|y>>>31),h=0;h<5;h++)(j=r[f+5*h]).high^=_,j.low^=d}for(var w=1;w<25;w++){var x=(j=r[w]).high,k=j.low,P=c[w];P<32?(_=x<<P|k>>>32-P,d=k<<P|x>>>32-P):(_=k<<P-32|x>>>64-P,d=x<<P-32|k>>>64-P);var E=p[s[w]];E.high=_,E.low=d}var S=p[0],C=r[0];for(S.high=C.high,S.low=C.low,f=0;f<5;f++)for(h=0;h<5;h++){var j=r[w=f+5*h],q=p[w],I=p[(f+1)%5+5*h],O=p[(f+2)%5+5*h];j.high=q.high^~I.high&O.high,j.low=q.low^~I.low&O.low}j=r[0];var A=l[u];j.high^=A.high,j.low^=A.low}},_doFinalize:function(){var t=this._data,r=t.words,n=(this._nDataBytes,8*t.sigBytes),o=32*this.blockSize;r[n>>>5]|=1<<24-n%32,r[(e.ceil((n+1)/o)*o>>>5)-1]|=128,t.sigBytes=4*r.length,this._process();for(var i=this._state,u=this.cfg.outputLength/8,c=u/8,s=[],l=0;l<c;l++){var p=i[l],f=p.high,_=p.low;f=16711935&(f<<8|f>>>24)|4278255360&(f<<24|f>>>8),_=16711935&(_<<8|_>>>24)|4278255360&(_<<24|_>>>8),s.push(_),s.push(f)}return new a.init(s,u)},clone:function(){for(var e=o.clone.call(this),t=e._state=this._state.slice(0),r=0;r<25;r++)t[r]=t[r].clone();return e}});t.SHA3=o._createHelper(f),t.HmacSHA3=o._createHmacHelper(f)}(Math),n.SHA3)},82307:function(e,t,r){var n,a,o,i,u,c,s,l;e.exports=(l=r(52952),r(41988),r(12133),a=(n=l).x64,o=a.Word,i=a.WordArray,u=n.algo,c=u.SHA512,s=u.SHA384=c.extend({_doReset:function(){this._hash=new i.init([new o.init(3418070365,3238371032),new o.init(1654270250,914150663),new o.init(2438529370,812702999),new o.init(355462360,4144912697),new o.init(1731405415,4290775857),new o.init(2394180231,1750603025),new o.init(3675008525,1694076839),new o.init(1203062813,3204075428)])},_doFinalize:function(){var e=c._doFinalize.call(this);return e.sigBytes-=16,e}}),n.SHA384=c._createHelper(s),n.HmacSHA384=c._createHmacHelper(s),l.SHA384)},12133:function(e,t,r){var n;e.exports=(n=r(52952),r(41988),function(){var e=n,t=e.lib.Hasher,r=e.x64,a=r.Word,o=r.WordArray,i=e.algo;function u(){return a.create.apply(a,arguments)}var c=[u(1116352408,3609767458),u(1899447441,602891725),u(3049323471,3964484399),u(3921009573,2173295548),u(961987163,4081628472),u(1508970993,3053834265),u(2453635748,2937671579),u(2870763221,3664609560),u(3624381080,2734883394),u(310598401,1164996542),u(607225278,1323610764),u(1426881987,3590304994),u(1925078388,4068182383),u(2162078206,991336113),u(2614888103,633803317),u(3248222580,3479774868),u(3835390401,2666613458),u(4022224774,944711139),u(264347078,2341262773),u(604807628,2007800933),u(770255983,1495990901),u(1249150122,1856431235),u(1555081692,3175218132),u(1996064986,2198950837),u(2554220882,3999719339),u(2821834349,766784016),u(2952996808,2566594879),u(3210313671,3203337956),u(3336571891,1034457026),u(3584528711,2466948901),u(113926993,3758326383),u(338241895,168717936),u(666307205,1188179964),u(773529912,1546045734),u(1294757372,1522805485),u(1396182291,2643833823),u(1695183700,2343527390),u(1986661051,1014477480),u(2177026350,1206759142),u(2456956037,344077627),u(2730485921,1290863460),u(2820302411,3158454273),u(3259730800,3505952657),u(3345764771,106217008),u(3516065817,3606008344),u(3600352804,1432725776),u(4094571909,1467031594),u(275423344,851169720),u(430227734,3100823752),u(506948616,1363258195),u(659060556,3750685593),u(883997877,3785050280),u(958139571,3318307427),u(1322822218,3812723403),u(1537002063,2003034995),u(1747873779,3602036899),u(1955562222,1575990012),u(2024104815,1125592928),u(2227730452,2716904306),u(2361852424,442776044),u(2428436474,593698344),u(2756734187,3733110249),u(3204031479,2999351573),u(3329325298,3815920427),u(3391569614,3928383900),u(3515267271,566280711),u(3940187606,3454069534),u(4118630271,4000239992),u(116418474,1914138554),u(174292421,2731055270),u(289380356,3203993006),u(460393269,320620315),u(685471733,587496836),u(852142971,1086792851),u(1017036298,365543100),u(1126000580,2618297676),u(1288033470,3409855158),u(1501505948,4234509866),u(1607167915,987167468),u(1816402316,1246189591)],s=[];!function(){for(var e=0;e<80;e++)s[e]=u()}();var l=i.SHA512=t.extend({_doReset:function(){this._hash=new o.init([new a.init(1779033703,4089235720),new a.init(3144134277,2227873595),new a.init(1013904242,4271175723),new a.init(2773480762,1595750129),new a.init(1359893119,2917565137),new a.init(2600822924,725511199),new a.init(528734635,4215389547),new a.init(1541459225,327033209)])},_doProcessBlock:function(e,t){for(var r=this._hash.words,n=r[0],a=r[1],o=r[2],i=r[3],u=r[4],l=r[5],p=r[6],f=r[7],_=n.high,d=n.low,h=a.high,m=a.low,v=o.high,b=o.low,y=i.high,g=i.low,w=u.high,x=u.low,k=l.high,P=l.low,E=p.high,S=p.low,C=f.high,j=f.low,q=_,I=d,O=h,A=m,D=v,T=b,M=y,L=g,R=w,z=x,Z=k,H=P,F=E,N=S,B=C,U=j,X=0;X<80;X++){var W,G,K=s[X];if(X<16)G=K.high=0|e[t+2*X],W=K.low=0|e[t+2*X+1];else{var V=s[X-15],Y=V.high,Q=V.low,J=(Y>>>1|Q<<31)^(Y>>>8|Q<<24)^Y>>>7,$=(Q>>>1|Y<<31)^(Q>>>8|Y<<24)^(Q>>>7|Y<<25),ee=s[X-2],te=ee.high,re=ee.low,ne=(te>>>19|re<<13)^(te<<3|re>>>29)^te>>>6,ae=(re>>>19|te<<13)^(re<<3|te>>>29)^(re>>>6|te<<26),oe=s[X-7],ie=oe.high,ue=oe.low,ce=s[X-16],se=ce.high,le=ce.low;G=(G=(G=J+ie+((W=$+ue)>>>0<$>>>0?1:0))+ne+((W+=ae)>>>0<ae>>>0?1:0))+se+((W+=le)>>>0<le>>>0?1:0),K.high=G,K.low=W}var pe,fe=R&Z^~R&F,_e=z&H^~z&N,de=q&O^q&D^O&D,he=I&A^I&T^A&T,me=(q>>>28|I<<4)^(q<<30|I>>>2)^(q<<25|I>>>7),ve=(I>>>28|q<<4)^(I<<30|q>>>2)^(I<<25|q>>>7),be=(R>>>14|z<<18)^(R>>>18|z<<14)^(R<<23|z>>>9),ye=(z>>>14|R<<18)^(z>>>18|R<<14)^(z<<23|R>>>9),ge=c[X],we=ge.high,xe=ge.low,ke=B+be+((pe=U+ye)>>>0<U>>>0?1:0),Pe=ve+he;B=F,U=N,F=Z,N=H,Z=R,H=z,R=M+(ke=(ke=(ke=ke+fe+((pe+=_e)>>>0<_e>>>0?1:0))+we+((pe+=xe)>>>0<xe>>>0?1:0))+G+((pe+=W)>>>0<W>>>0?1:0))+((z=L+pe|0)>>>0<L>>>0?1:0)|0,M=D,L=T,D=O,T=A,O=q,A=I,q=ke+(me+de+(Pe>>>0<ve>>>0?1:0))+((I=pe+Pe|0)>>>0<pe>>>0?1:0)|0}d=n.low=d+I,n.high=_+q+(d>>>0<I>>>0?1:0),m=a.low=m+A,a.high=h+O+(m>>>0<A>>>0?1:0),b=o.low=b+T,o.high=v+D+(b>>>0<T>>>0?1:0),g=i.low=g+L,i.high=y+M+(g>>>0<L>>>0?1:0),x=u.low=x+z,u.high=w+R+(x>>>0<z>>>0?1:0),P=l.low=P+H,l.high=k+Z+(P>>>0<H>>>0?1:0),S=p.low=S+N,p.high=E+F+(S>>>0<N>>>0?1:0),j=f.low=j+U,f.high=C+B+(j>>>0<U>>>0?1:0)},_doFinalize:function(){var e=this._data,t=e.words,r=8*this._nDataBytes,n=8*e.sigBytes;return t[n>>>5]|=128<<24-n%32,t[30+(n+128>>>10<<5)]=Math.floor(r/4294967296),t[31+(n+128>>>10<<5)]=r,e.sigBytes=4*t.length,this._process(),this._hash.toX32()},clone:function(){var e=t.clone.call(this);return e._hash=this._hash.clone(),e},blockSize:32});e.SHA512=t._createHelper(l),e.HmacSHA512=t._createHmacHelper(l)}(),n.SHA512)},61945:function(e,t,r){var n;e.exports=(n=r(52952),r(35909),r(34905),r(28492),r(93617),function(){var e=n,t=e.lib,r=t.WordArray,a=t.BlockCipher,o=e.algo,i=[57,49,41,33,25,17,9,1,58,50,42,34,26,18,10,2,59,51,43,35,27,19,11,3,60,52,44,36,63,55,47,39,31,23,15,7,62,54,46,38,30,22,14,6,61,53,45,37,29,21,13,5,28,20,12,4],u=[14,17,11,24,1,5,3,28,15,6,21,10,23,19,12,4,26,8,16,7,27,20,13,2,41,52,31,37,47,55,30,40,51,45,33,48,44,49,39,56,34,53,46,42,50,36,29,32],c=[1,2,4,6,8,10,12,14,15,17,19,21,23,25,27,28],s=[{0:8421888,268435456:32768,536870912:8421378,805306368:2,1073741824:512,1342177280:8421890,1610612736:8389122,1879048192:8388608,2147483648:514,2415919104:8389120,2684354560:33280,2952790016:8421376,3221225472:32770,3489660928:8388610,3758096384:0,4026531840:33282,134217728:0,402653184:8421890,671088640:33282,939524096:32768,1207959552:8421888,1476395008:512,1744830464:8421378,2013265920:2,2281701376:8389120,2550136832:33280,2818572288:8421376,3087007744:8389122,3355443200:8388610,3623878656:32770,3892314112:514,4160749568:8388608,1:32768,268435457:2,536870913:8421888,805306369:8388608,1073741825:8421378,1342177281:33280,1610612737:512,1879048193:8389122,2147483649:8421890,2415919105:8421376,2684354561:8388610,2952790017:33282,3221225473:514,3489660929:8389120,3758096385:32770,4026531841:0,134217729:8421890,402653185:8421376,671088641:8388608,939524097:512,1207959553:32768,1476395009:8388610,1744830465:2,2013265921:33282,2281701377:32770,2550136833:8389122,2818572289:514,3087007745:8421888,3355443201:8389120,3623878657:0,3892314113:33280,4160749569:8421378},{0:1074282512,16777216:16384,33554432:524288,50331648:1074266128,67108864:1073741840,83886080:1074282496,100663296:1073758208,117440512:16,134217728:540672,150994944:1073758224,167772160:1073741824,184549376:540688,201326592:524304,218103808:0,234881024:16400,251658240:1074266112,8388608:1073758208,25165824:540688,41943040:16,58720256:1073758224,75497472:1074282512,92274688:1073741824,109051904:524288,125829120:1074266128,142606336:524304,159383552:0,176160768:16384,192937984:1074266112,209715200:1073741840,226492416:540672,243269632:1074282496,260046848:16400,268435456:0,285212672:1074266128,301989888:1073758224,318767104:1074282496,335544320:1074266112,352321536:16,369098752:540688,385875968:16384,402653184:16400,419430400:524288,436207616:524304,452984832:1073741840,469762048:540672,486539264:1073758208,503316480:1073741824,520093696:1074282512,276824064:540688,293601280:524288,310378496:1074266112,327155712:16384,343932928:1073758208,360710144:1074282512,377487360:16,394264576:1073741824,411041792:1074282496,427819008:1073741840,444596224:1073758224,461373440:524304,478150656:0,494927872:16400,511705088:1074266128,528482304:540672},{0:260,1048576:0,2097152:67109120,3145728:65796,4194304:65540,5242880:67108868,6291456:67174660,7340032:67174400,8388608:67108864,9437184:67174656,10485760:65792,11534336:67174404,12582912:67109124,13631488:65536,14680064:4,15728640:256,524288:67174656,1572864:67174404,2621440:0,3670016:67109120,4718592:67108868,5767168:65536,6815744:65540,7864320:260,8912896:4,9961472:256,11010048:67174400,12058624:65796,13107200:65792,14155776:67109124,15204352:67174660,16252928:67108864,16777216:67174656,17825792:65540,18874368:65536,19922944:67109120,20971520:256,22020096:67174660,23068672:67108868,24117248:0,25165824:67109124,26214400:67108864,27262976:4,28311552:65792,29360128:67174400,30408704:260,31457280:65796,32505856:67174404,17301504:67108864,18350080:260,19398656:67174656,20447232:0,21495808:65540,22544384:67109120,23592960:256,24641536:67174404,25690112:65536,26738688:67174660,27787264:65796,28835840:67108868,29884416:67109124,30932992:67174400,31981568:4,33030144:65792},{0:2151682048,65536:2147487808,131072:4198464,196608:2151677952,262144:0,327680:4198400,393216:2147483712,458752:4194368,524288:2147483648,589824:4194304,655360:64,720896:2147487744,786432:2151678016,851968:4160,917504:4096,983040:2151682112,32768:2147487808,98304:64,163840:2151678016,229376:2147487744,294912:4198400,360448:2151682112,425984:0,491520:2151677952,557056:4096,622592:2151682048,688128:4194304,753664:4160,819200:2147483648,884736:4194368,950272:4198464,1015808:2147483712,1048576:4194368,1114112:4198400,1179648:2147483712,1245184:0,1310720:4160,1376256:2151678016,1441792:2151682048,1507328:2147487808,1572864:2151682112,1638400:2147483648,1703936:2151677952,1769472:4198464,1835008:2147487744,1900544:4194304,1966080:64,2031616:4096,1081344:2151677952,1146880:2151682112,1212416:0,1277952:4198400,1343488:4194368,1409024:2147483648,1474560:2147487808,1540096:64,1605632:2147483712,1671168:4096,1736704:2147487744,1802240:2151678016,1867776:4160,1933312:2151682048,1998848:4194304,2064384:4198464},{0:128,4096:17039360,8192:262144,12288:536870912,16384:537133184,20480:16777344,24576:553648256,28672:262272,32768:16777216,36864:537133056,40960:536871040,45056:553910400,49152:553910272,53248:0,57344:17039488,61440:553648128,2048:17039488,6144:553648256,10240:128,14336:17039360,18432:262144,22528:537133184,26624:553910272,30720:536870912,34816:537133056,38912:0,430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e=this._key.words,t=[],r=0;r<56;r++){var n=i[r]-1;t[r]=e[n>>>5]>>>31-n%32&1}for(var a=this._subKeys=[],o=0;o<16;o++){var s=a[o]=[],l=c[o];for(r=0;r<24;r++)s[r/6|0]|=t[(u[r]-1+l)%28]<<31-r%6,s[4+(r/6|0)]|=t[28+(u[r+24]-1+l)%28]<<31-r%6;for(s[0]=s[0]<<1|s[0]>>>31,r=1;r<7;r++)s[r]=s[r]>>>4*(r-1)+3;s[7]=s[7]<<5|s[7]>>>27}var p=this._invSubKeys=[];for(r=0;r<16;r++)p[r]=a[15-r]},encryptBlock:function(e,t){this._doCryptBlock(e,t,this._subKeys)},decryptBlock:function(e,t){this._doCryptBlock(e,t,this._invSubKeys)},_doCryptBlock:function(e,t,r){this._lBlock=e[t],this._rBlock=e[t+1],f.call(this,4,252645135),f.call(this,16,65535),_.call(this,2,858993459),_.call(this,8,16711935),f.call(this,1,1431655765);for(var n=0;n<16;n++){for(var a=r[n],o=this._lBlock,i=this._rBlock,u=0,c=0;c<8;c++)u|=s[c][((i^a[c])&l[c])>>>0];this._lBlock=i,this._rBlock=o^u}var p=this._lBlock;this._lBlock=this._rBlock,this._rBlock=p,f.call(this,1,1431655765),_.call(this,8,16711935),_.call(this,2,858993459),f.call(this,16,65535),f.call(this,4,252645135),e[t]=this._lBlock,e[t+1]=this._rBlock},keySize:2,ivSize:2,blockSize:2});function f(e,t){var r=(this._lBlock>>>e^this._rBlock)&t;this._rBlock^=r,this._lBlock^=r<<e}function _(e,t){var r=(this._rBlock>>>e^this._lBlock)&t;this._lBlock^=r,this._rBlock^=r<<e}e.DES=a._createHelper(p);var d=o.TripleDES=a.extend({_doReset:function(){var e=this._key.words;if(2!==e.length&&4!==e.length&&e.length<6)throw new Error("Invalid key length - 3DES requires the key length to be 64, 128, 192 or >192.");var t=e.slice(0,2),n=e.length<4?e.slice(0,2):e.slice(2,4),a=e.length<6?e.slice(0,2):e.slice(4,6);this._des1=p.createEncryptor(r.create(t)),this._des2=p.createEncryptor(r.create(n)),this._des3=p.createEncryptor(r.create(a))},encryptBlock:function(e,t){this._des1.encryptBlock(e,t),this._des2.decryptBlock(e,t),this._des3.encryptBlock(e,t)},decryptBlock:function(e,t){this._des3.decryptBlock(e,t),this._des2.encryptBlock(e,t),this._des1.decryptBlock(e,t)},keySize:6,ivSize:2,blockSize:2});e.TripleDES=a._createHelper(d)}(),n.TripleDES)},41988:function(e,t,r){var n;e.exports=(n=r(52952),function(e){var t=n,r=t.lib,a=r.Base,o=r.WordArray,i=t.x64={};i.Word=a.extend({init:function(e,t){this.high=e,this.low=t}}),i.WordArray=a.extend({init:function(t,r){t=this.words=t||[],this.sigBytes=r!=e?r:8*t.length},toX32:function(){for(var e=this.words,t=e.length,r=[],n=0;n<t;n++){var a=e[n];r.push(a.high),r.push(a.low)}return o.create(r,this.sigBytes)},clone:function(){for(var e=a.clone.call(this),t=e.words=this.words.slice(0),r=t.length,n=0;n<r;n++)t[n]=t[n].clone();return e}})}(),n)},35413:function(e,t,r){"use strict";var n=r(57046),a=r(69574),o=r(63474),i=r(47095),u=r(99363),c=e.exports=function(e,t){var r,a,c,s,l;return arguments.length<2||"string"!=typeof e?(s=t,t=e,e=null):s=arguments[2],n(e)?(r=u.call(e,"c"),a=u.call(e,"e"),c=u.call(e,"w")):(r=c=!0,a=!1),l={value:t,configurable:r,enumerable:a,writable:c},s?o(i(s),l):l};c.gs=function(e,t,r){var c,s,l,p;return"string"!=typeof e?(l=r,r=t,t=e,e=null):l=arguments[3],n(t)?a(t)?n(r)?a(r)||(l=r,r=void 0):r=void 0:(l=t,t=r=void 0):t=void 0,n(e)?(c=u.call(e,"c"),s=u.call(e,"e")):(c=!0,s=!1),p={get:t,set:r,configurable:c,enumerable:s},l?o(i(l),p):p}},56656:function(e){e.exports=function(){"use strict";var e=1e3,t=6e4,r=36e5,n="millisecond",a="second",o="minute",i="hour",u="day",c="week",s="month",l="quarter",p="year",f="date",_="Invalid 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"},48742:function(e){"use strict";e.exports="data:image/png;base64,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"},70689:function(e){"use strict";e.exports="data:image/png;base64,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"},65985:function(e){"use strict";e.exports="data:image/png;base64,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"},1938:function(e){"use strict";e.exports="data:image/png;base64,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"},89718:function(e){"use strict";e.exports="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAAAXNSR0IArs4c6QAAB/NJREFUWEe1V3lsFOcVfzOzl+31JbG79oJvbIopLjFuEGmUoDZtk/jCUYMSOWkrRFsl+ScCURFC7djr9SFEVFQVlArRqidJW+wYYzdypAQ1OKR1TIA6TRvWtWXwsbu+4sXrmd2dqX5vd9Zr4qbQ45NGOzvzve/93u+dI9B/sNbV1KR+6av3VW+/Z1ulQJo2ePlK78X+gXP+7u7Fuz1OuEsBserlpto9NXWHNxUVVcyTyuKpJNJHHs/g2e7O1p79ja8TxV7cweF3DGD7wefKv/X44y9urdhetxgJCTMzMxQOh1mFJEmUmZlJSSaz9pc//bnz591n3Vdbfzx0B/rp3wLI2fuE88nH6vZX7frKPiXFnD7h99Hy8jJJkkiCIBJpGoUjEQZjMZvJ7nCQGpQX+t9661RXZ9fL46fPTHwWkH8N4Nu7LN+8f/fePVW1B2wOe+HIwizdCgRIEEUySBL/8tI0iqgqRWIgVFUla0oKOWx28k9PjXT3nD/26jtdp+lnby+vBWRNAF9rb6iuf6zuheLikp2TwQDNz8/HqRZ1xbHTNE2jlUulcDhCoVCIn8Et6enpNPKxZ+D3Xa+3XzjUfO52EKsAFH736dzv1Ne7dt5/X/0tUiWf38+HGQwSSZKBoBwHw2oVlxoNQn3pQPA8HAqRwrIGstttZDSZI5fevfSr3776iyOeE2fGdZk4APi69QdHzm/LL9r2wcwUBYNBMhoMJBmiigUBCRdVql+2deuYfr/fz8HEbgEjROwSNRJhEDAiOTmZ8vLy6Pp1z+WjbR1VemzEATT0d56of+iRZwamx1nAZDKxYr6gHLkViUR9jcNVlRwOBwefz+djgPp+WKeD5P2hEMmKQmaTiT5XXELn3+g7efzhPc9iHwOw73vS8Yq79T01NTnP6/WS2Wxm6nAorsQDoRAAQ4pCRpOJWVFkmQxGI8vczhbeQwYXssfpdFIoHBo73NC0w3vqN9N8+uef37f5aEf7kHdhwYJNQEoJyhMjHcqxB8BKSkpIURQaGRkhTVUZEGqChFiJORlM4B1cJcsyJSUlkc1uW25obCr/+Ien/soAthz4XmlHW9uQd8ZvjgadgYxGI8dA4NYttlJPMxyCA6F8i8lKNyhMkwtzNDo6yiohB3ksuC7FamXAkAMLcG2Wwy67XI3lw8d++mEcQGube2jGP2NG0IiiQFZrKqWkpNDNmzdZGABgLSwvLi6mbcmZtEgqeSlMEdJobm6ORjwezg6jEQAEslgslJ+fT7Ozs/webDCALIfc8ikArS1DPgBQFKZR32y32eiTxUVamJ9nWuHDTeZUkkljxfMUIYU0SiaRvIFPaHJykq1H/qelpdHkxAQtBYPxggUA2dlZcovLXT587JUVBtwA4PMzAFCHSAf1FRs3UQZJrBALtkFhOAZAIeJ3EhGDwC9otZLE4P547QM2BsEJFhHg2VkO2e1uWxsA6MZmPdgKCgposzWTlaismNjySCzIAGiZNDKTQKZYazGRyB1yKDBDw8PD8ZSOoF8kJTEDre6m1TEABrxer1mRFS4oALC0tESZGRn0xfyNbLWuGNbDSnACxQAD5bDeHGMhnSTqHvmQpiYnWSncCgYQF2sCaGlp5hhYxUAwyErKysooRZAYAFe5hPILS3XXGElkFyWRyPT3DV7iSgjaAQAFCWCczmy5sbGp/PqPErLABQA+PwNAGmHzsixTIBCg0tJSykrLiAdetAlGY8IhGBkYaIdyMAEAQ/ICXRwY4BLMVVUQKAQXMAPZcntb++oYAADvtNeMkgkAetoBgN1up9L8wnggQmHUAQLlk4mph2K4RSSB/f/a+N/I4/FwKutVFXWAgzA7W+5od62OgWZX09D0tJezAAUIlQssIIUABpbgP6xAIdIrHfbq9wheUI1ns3NznHqmGP1gC+XbbLHQeqdTbna1rLgApfglpKHXa1laCnI1w4JiuASgcnNzmUrucgAQmwMS78GKKEosc+PGjWg1NRrjnRTngJHsbOeyy+1eKcVoRh0trveMRkMeKh+E4DNUtWgJDpHNZo+7Bl2RnbBqGInyoKew3+cjEX1BkkjTMDGpbEhOTg4YHHuptX2lGUHw+T/87sTurz/8zJW/f8S06yDgClgJYfhQZ4CHkVjvBxCu6YLAjQiKuTOikwoCy+gzAQK6/83+kyer61faMWQxkHz/8KGewsKCe9DdFhcX460Vh/MEFKMf97r1iRmhZ6c+tulNDHKpaWm0saiIRsdGLx8/dvzTAwmEnc8+kfP0nvqWe3fseEqRZRHuQCdLHDTitCcEYiIT+ntYrRee9evXI//V9wcHf3mm87UjE2uNZAm1hR5sf7F6d23tCwWFhTsxbk1PTXFWwJ/6gKLvjzMRmxOZbjQ0g4EnJpvNRmOj/3j3fG9f24VD7s8eShNB0K5dlm88VbP3kUcrD2RkZBSCDbRULPiZgQgcBvF5QY8PTMMbNmygufnZkf433jx29tfdp+ntuxjLE4EgNiprq/Y/+MAD+0gQ0sfHxzk+9Bkw7mdVpVSrlTbk5JCqqQsX37l4qu9c73/xYbKKDqKyg8+V19bVHNm6devuQCAgTE1Ncb5jIWOyHA5MP9q1a9e6erq7Wq4e/cn/5tPsNhzil4821FZVVh7OzcurUBQAEBjA6OjYYE9fb+uFg83/n4/TRCDr9tak3vuFiurNW8oeRS+8Ony19/0rg+f8p+/+8/yfCNTrXTlApm4AAAAASUVORK5CYII="},79390:function(e){"use strict";e.exports="data:image/png;base64,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"},51466:function(e){"use strict";e.exports="data:image/png;base64,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