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NcviA9H6uT67w6xRE8JkOdyWSY7Xo7U+/LJm+n001ca7jlnjMhOYDS8nQfcXzoHbM6O9t7TwV0cOD0DMNvL1WwDoa/acacQ8akZZRmpOQ44AlxtMJWZjlu+GtrdzA+ngX0yNrvfhMogD300T6gDRSFfp3duX56KhDRI+Be1YmiSugwJwG0Ia/2337TGaJ17rlss+3tDmxUJmPL0dAZCtwXlRb/oLxJ4pvE7bNu3GHGJk1m/VQQWGqd4g9JnyYWtHtgEEgXpxj+8XIFFKH1dlO7iCn23ADb2KljVnypBvlEBVcmgRsAJUrJpdJ08yS18CjKsuzzKYD9gOJ20LDI8eTGlbWZwJXTzBk7ItvrPnzP0vB0r05LlFuYbD/PDOoq57ckzNsOn8q0S86EQX336b/3PIkj0LJTy8rf9ucsu5H6HAPaOPPkzEMpySoMT80An1nwlPb7ahu4FmRs0ybuOlaeHfQgPzWF2zXg/Tg3eD9KrUC9FUCbZSiAvYW9/rFdIqWz/M23S52NI8el50/CjfbHibkSkKlgrphq2KDeDoHdsfnm+mgOYpJ71WHdefQeWcPm2Ff8zrPG53A5xlbeqADnFjy8OO/jkmD4cVOrs5NwS5XVtPuZXEqnPIilUrh2rMoJ1JSEkO5AGnAjW2/KTj3smRTAHrZCD8DvFK218C/e8/2x/dPCKR2QiGYjiVIqscAWxpl4mPZBRJZYmVsMV4Dn66fTMr+Gme4rC9L0gLTm2sRxd9/r6006wnSaQpsI24xB9336nsOYB7oX2ZxJm/3aHMPnFytoM4Y/W+lq4xWwjTdZDOy6BzxXxcash5UDJeX3bTKLEpDt1MFJAYDtUOqCYm8BCB/HJecuSPZGZ+NwFEbTzGNznVAwFfpryZOJD/cwkrXNCdi0NcsNUNc6nlkPzB6KTWXNr11nEe04YvgM25kkrx8zhezRkaX7/Y6WZAlsmVwPPp0qyfrMWQgPHLMVhlOzwLklDWpSlN1sd8FM3SSa8FjGXioDvzKJS6WSiv0gUNPjyqYyMjnBR7JRj/IYC4o9yip9HG2kdA5/E2OyufaY6/NZLjEW2qarPmPKYD5p1avd7aMzz0NIHm+verYUTLnXZdMUWsnIcucSn1ZqsJYyLIvmfjKGrejqsaHl8Nb9nmviH0oFAYAK41icAr54zMOLR3x8v8XwXgvKTm1OMbJRKw4iVpJRPPVBT8hXZtjtfeHGpdhOTVcYrzJ6T/8Sk9ZOUOqCYn8cYB3lnufPu8ee/vqEs77mtzv+I8wRDRmRT3++Gqzn2zxSZqE6C/yMIjmhtvlYypK1vAlZuz2RqXNiInON3HmjGXyC2Qp2fdR0qwAk6ZwSg3fcV7agR3xwdZPFaEDTf6T5nqtw/OaShy8uVvCdJvBWswtqm/02Di77K8ATY2H7WJmvHCtvXAXG1ixZ2sjUKVDT7QpgjwKQ3djmouRHL23MC4GjjuN4ApSUMgPdPJLchwXPPwp6F6Yf2LstLWZZBUFbozJWKhFrp1Npg9OplZJTQ91QD9rKvKQjyAz27IixmDkYBHsb4NkUR0PZcnVPOyhVj6PiQSVGeHXBwyvzPppg+LcrGtR2nza46SB4ZQadJ8qd65NheBU664lNpU2iBKP5VkUBdxLU6pDYjft/z435vHSfOwj20ViwINpi0S3FGcD6sN6jAlatUw4FN6GZKaD07XQYLHIuzLqKJQOxn1z6NMoqrwZ97qcYS3rPxJ2ni+D1gji7nyjbCQH05Tkfv3eyogB+AwxvrEB5lNkSCJ0AJkkCXfNMDfL5SVyfFbluojb73ZP1ZCf3dQHsnVzNLfR17H+TY6G7PiOEnHUZm5OhcDchDaYh008+3uS40rQrfXGiEVfI0yPtasmtASS/xzxtqptNHU36SoN0Nbj4+pzkEUOnmlQhsaqOWNmKSXlXrzAs1jj+2fNlzM/4+M4K8E4LaLatczLmLgy1rvvAqXFsLJdx91AZ17C21sL4eDad0T2TqbPzLoA9dCfcowYXJDt89+5ku1RZYoKK0Alf87hDNj2xgYbdtZMj9Lksa+qh2Qw3V8VzToEp/s6OlOj5PXuy6GuUCi2ObzR2dgN3e9j97cw249E70X4pjLqnXpbG5z9TzgRmfIaX5nycIZPWUgV/tQK8QTJ1DOrkmDJiA1Xy8IFfGkf7qWr7UtXzqHa1cTyxtd+petY7zXoXwL5HON1Mt4cvXCrj5sx0x3efYA7KgiKvBgA6oeAjErosxc0Fch7irUlsjvh3W9umrUwOlt4lslmTrBbMEGYb7aq9PbJRUikP4j/0TbTmm4EcT1454itzVqPG8G4AfG8FuN3WniQG1EaxRn+nKsAzVYSvVnGlEq5fWxWiU61WjRxtKLbJTzZSLPVm9lK/tgXF3olVHK0PB+cvssOHn51oy7HDYO5Bx3V8nffb7GLNZSoZOEvKNkGRk+HkUdwMeHfe9J1VxQ1YnM3IHMYENtpa55SzzegbLE05JQ88UmMK1CRTM4/h+02of2Sntkt2pkBNMvUEgtM13DnkKJna+H7TzAzVpvfG73tbbqIjT71Qnm1mqbbR9rx0l+ZvjN+SlUUXctph3JcRccQarXYQv43x7B1ziWw/l6kRQL2NGaWVctlDJ6Xajsv6MNKA62NENY9PlLwzLI9YJ2uV8SPpbWtNPHPGxKudTJt0fBUAi3WG04d8/JOnKpiZYvjeDeCvV4CbQmcfpSdlJBAaL/1reMCn96H1GGtfmWbirlVyx85PlpKp6cb3mgU3kyso9rZ29/CLyXPs+22MN9fXl+F5DYSB28OijsJR5tOgjFKpF29bpsg91DT+Iu4wX5rOYzRGlB+GLmWmn8wAmIgdU9X4+mkR9EUKnFSVw6cE/j7OzHt4ZYHhZMPHG7eBv24Cl9a1/7dR2tmqhRqBelKEn5hkP696MDJ1Nj+ZDer7BugC2EM30vYbLP7zn/h3J+YPu2E0I7l3IJuWyCh91HYbwGrnjsTWB8UbsO9+HmUqliCfimTuORkGQTprad7ysZIZcXzPgVz+AFnaeLHF3RAwZ2sMZ+Z8fOlxD8szOmUombN+3ALebwMtO4OURbHrDHh2Ep3PzeBqpYSPMmGXRrZOFaEfZfl3uk1BsXd6RQE89wey9NFYc0JE7BFErCGBkr5N7E1tUWiT/aPfMNR2tfdsHjEipj5us2ko5XlhDVyTPHRlNV+217iZ+YDkJvH9UmdbLJ/Y2UfNsNLac02pe5xXcpSR1IZAbVjvc0seTs/6SjH2gybwvdsxqO0qw1ZCtsUa8GINzcVy5/a0G96wSu4YQNNfO0rrvlPqgmLfA0BTl0v/i6ytO8G+0MFx0RHlfql6BlFpM7QEz1k5Ov5hM7qnZLoZpZztbZn8lCiqNkOBLfl5hLVNDqBclr9PBzaC1TlpnXipE82aZLx29DNFWlE+smdnSVHm4fR+H74PvN+CotakLCMHlOQ2VvdHasAX9+HOsVJwpeb75CJqJx2kSwyo77uiLG+1Coo9wiYcqckFyY507ky0171HHeZORw4824Rl21qHst55CrEczdlmpVfbdTvh/oeS+N67ZPFlr0/fMeVx8KmsJ8MGEjuUJMyBxaakHlAG1BRuyYn1Bs7MV/DFRQ9zNY7lhj60LgXA5RZUpBbJ1S3rIDDdUtOXptF+bbL9c08oRZld7dJmv02UlspR9nG+CmBvc/VNrHQkD851InlYOs64y5BOImjdYxio+9qcM+PcFKgzSBzMLQznAwaKumac/QZoc+39bPc9J4fFouQ8r+6Zp2+qNNkm8QHXlPrMER+/tVymqhzKXk2vd1uaStPfBNRxWiOiv9ynYvMCT02w9ucauDbZlanpRnnJ/DeddHCb26/v5QWwt7Wy0nnkDzCx4bUPRmCPuFEYV0nuD7thLLitEzOmlkx8ghrxZoHdw8UOnHcveTXx0wPva1/W73xI8eD9BxGKEDwpmt3liVPrY1Yh1w6oTVQzVGC+wfCbyxW8tuBjrqYjvm8LKA248f+m6pdmnem29PG5qpC/NC3vHEJ0c7qqPMpIpUZUOWujpuYJlb5fJq1Bj7AA9laBfV66xx9ZbawJ96jrsIMabd0oqH7dDvMYTZRl2Sz6GaXvVoA9eKq90O9+0yWz+r6Zu9sgztWiD2OzuyNTCQYVcgjY+lbdqcc3Ul8MWgHKEc5A4ZMvzTG8tlhRAR2LDcq2AqwEwKU28Fc3tLKMQJ3tjdIZ/cMDWD1exQeZMrbU1BwDO5r1ZKtbMe+6AtibXU0pHXzz7dJ8c7kRORuPSycaB2UGtRDbb8uliFifRrlGm5wv+27rPD45Y3vOn7LdYxqIucR3FOpMN0op4gYfRxqvQ9T72cit1GR0/3QwUCDHqVmG3/yFv/dnFipKxqaqHJcD4J2mNmu9S2atDKgpUqsMgV8/wIIXxvGeT9Ga+myxi87TjWzf749N+91v+xbA3gywpXSO/u+tAwhKBwIWHXQdshyb4OTuph2FmqYod2zzSrOZ8cBsUGcE8KH3yWA1n1vIOwm6izLwADHNejTStja9l1obzrlLnQmMRKP78jnZcOmchvFIhc5LtlBn+PxCBeeWKwrglJPIAJr+XiZQUy/JYPR1j5UhX53CraM+blU93IllaQKxAbZdneOehl5uZmtm2xbA3sTqHf2DtYPCc5ciVqohCjWVzuzboWCL76ecQOyas9nIRDOuPrt96H36NMilvgl7nWa57WxkPcvU0799QJjWQyh06ueciY7ActuSgQmhpNxkZxYomKOMM/M+mA+VSfT7K1oLfsMGtRkqB16uAS9M4e6jpeADv2vSMkkHjfZ7YMH5TWyne9q0APaw5SXW+3WwY++hEbKNpShyJtPcn82TJp7Qw3rV+3HAvk9tc4uqjAaZ4dq1/uICHTldijuQDe9LsfOn35sVNWdihoomXfQ7oXq/V2mMyKPsiI9/crqMubqv5GfSev+wCZX7mz4bhKpbxAt9tA75GxPhnafq/BqQUGrT1IRf7gpQ07QKYA+CoJTO4v+BWjtsPQrGpqUQ5XR6eit+eijl7jZQW3IIye3PlloDTucKGHyYdDnVkQ4de4DJUEdkE2wldYKdHurcx587NfEBN8ycikoDXqOsJ56K0Hr5F2z4Wy3g7RWo8EuK0koBOl4FKr2zWEb0qWp48+lxccuPotU4oINubi6hvw+0TF2w4iNua2q29K/W5tbWnXmXe/slsd6pytJZJGeAm9wnZbjt5WhHodo2UrIyd8YBq+/0YtKr/vR1I+0dTO7wcr40ucETZX4Pqc/VIOjhJnMaID8MOAnpnjUf+OS8h986UcFrx32822YqQQJR6xUqZ5s9beJUwU+UhfziAXbrSBmX0Gp14trUxkZt5OldBeqCYvdBAZXQufTR+kERlo5HUtTsLKF6v2akz8wm7o/V/mafPCqeYlQzGzMppRPPYSgxjbmEwTJ2/oKk+k51kH/XXpz2kZ9TRDunr2RRsq6tXYHEZwyU6veVYx6+crKGxVmOFpjKfEKgpqLzvRXB9fWkKPvcfqw/xYOfgWTqZlOgVqPBmn9bLmO7CfpxT5oWrLi1rFQs/tvL8K9GwbwM2THoRAiOlg31xhtMwfrJpvlUe1QWN5ctj4FuAD4SsC1w999N/XvqHW+mrQF9fJ/uuDMz6JlQTj+Z1ba7pqdgyulUfIZTcwz/3Zk6KjUfP2ppRdlVEUdoWfGW5i5k0npkHOKXZ9B8vqqK493K1KY2bPiukakLVnzA+fjY/3m30RHuIccbPyTbAddKWe3s0N2L3S3WH+TdX7oELg3uEQhfaqR9wU2t+rlNm5MoQ/B6x51BZN4a5caMD6DY5DnWz4iVx3rnshLp/rvlBzSwif1envHwe6cqeHWxhj9fgUrkn2i9M/Og3kim/qWakJ/cxz6cFRu3x7oF5/PYbwPsB85OPYzMFxSbVkhK59i/WJl0x8YXZRjN6UWLN5X6o+tDpWvA2K3MBrQQZO3J9PbMUm/9eZhHGt2tB9w5aB9IufuOyb6qn64g3koZE11qg2Vu3mOZHiRLZ9iB9GqnOyaKSzbnF+c85VX26lJNKcoo9JK03kmFDmtwxNkSc8JHAAAgAElEQVRQJNcn6pCvTHSuNRzxUQxqGlVuyZ3tVrwcBr57+XsB7PPSfeo0JtfubpxA5NQlg5tGkEC3oqqh3Gkg60+Z9KH2pkqOhMGOG6aIRb8H3ldTbv3QF9g5FLH7Vf5VGaypYZkZmGONYpsvN0UCJnWN+i8Da83+5E8tGUiykvF9etsTqGsV4POLZSVTE/utIrMoPXAcRx3a6U7iO5J76mJJRL86x1Yec4LLCENKD2xkaRvYRKXVjR8En++tgv+hBvbyBVkNguBAxLAAIcrKOVmh2N6+FiKEzZLbS67bdLclbY2sW+Zwf+nUNh5Iei3qndKwpXiN9J7IJ8rWmPsoqOwzzKrOQQFSlE6IluzWOqI3P2y5AbjiPKgups2B6GirnAllAG1adVffZjF0UAhVvDw16+F/fK2OwPdVdBbJ1HbOwSwYpqiiRxWdJ7zwziem+UfAWgtIQG0rynad9rsf8B9aYC9+S/r8VvuxtiPnXVcJgzYDnktvuw2ylDt7reVmGqcAEaoEziA2V2/nJIxkCLDNAPPY881S7YGU1NxI5dEWqPsMjTLw8iGmsnmSa+Z0CbK1GojX323ztuAIYmArkIe6/G3vK09ot4FsXcG0y2mZiuM1GP7Zy3XMzVR0yGVba77VPfJMWgz49DTCF8Y716ZccWOsm0nUAJpuSv+S4ni7nVqr8W+V1O/a68jp5H96x3P2H3nEdd2jgOMJEQBhmk3uTe5jUZ0k4ih7jU23Y+cV1cQudmVWzlD5/ggeRe42+3mAo3UuA9ybOaV3HDbfQhT6zALQqGhAkxfX1ZZGBMU7H6siunMrkH9ztc1aAcd6O0QgBNoxqlPgzp1YBtTq5t2rZn2Ol+c9fP5EDY0ZotQszvctECTPTq8t5/pKYtsfKwv5lcPs+kRp4zIwRpYv25xlg/qB9fveCtYeKmCTffrWbUxvBBtLcJyq4/KSsNPrJHvJZq1tBrG7+RRxiItgpTXmMZC7Gc5icm6X7UjR5l67eOZJDgN4cv++QniGJmcwnFer2oCatMhUvuZ3lpiqX0WApowjapZxI+puoSIw5UD8zc9ajBLsUzLAdSFURBWB21gYcil37s7VkyFx2WMc5054+J1TddxgPr6/IpQ8TS8CNY9LDdlSySEPmCxBfGEWdx4ZwyUAGzFlzitju6dA/XBRbCmdp/4f1DutjZMSXX/vnDgOvWMsDa7eQ2m1kYGKVqz1qV+VZa1N5sKkaF0a4P1O5gSH8RvGGIi1z3slLGn8Y26rbIc5HdFsZyvAUoNhsQ7cZExFRyXZjKwSN0S2aUpP1CBvXm/Jn95y3GY7QDOI612Fmv9JR1z2nC6x0aF7Opla0y8v+PinL84oVfhfNbUnWSKyKDTrZ2PmfqgG/Mo0WvMV3DpaUnZqotRGQWYotlGSmRxlu1pZln2EDwXFPnte8lsnMR1GnQXhlGaTNMB99Dl6lySaHfUxlZI3/iYF9rivNPXumrYS1j7JOZy+ub5b/3gq1ToBdjwe+0vryfYFd898exfAUOgz8wy1ClOUkRL8XWvFs7VK3arZWZ/JBPXcuBBv/qTJLgcMzZbQ7pwxS247+uSeSlYsNrHRdZ9jcYbhK6fqqM/6+GGT4Ua7y1+QCZJ8DOwXHTBf3A/xfBUfTWpQE6XOK2P7wOQn63egb+f7PQ/s5QvScxAckY48GjlOhUVw0vJe7/Kl5GurcTo/So43malPmxD8LHgzVL8P1e0ndRscx6Wle2VnI8/mxG0n2oDkvOq9CwHz9AzDyVmmsguQtjnmulPwMWoDs3LKusS5Su17vBxGpbVAfvfDNrvWFLgdUEE7LWvTdI1Pec+qWy506nCpcGXSOneqhh8LjndbTLH26UTD6fUsM6X9Fl+a6lxtuOKGVXInT1G259hve033NLCf+4M3Sp19Ty11OvKI6yRVWtKctqKE8YbJw2rmFOjCIY8172q9wwTkNoBszXe2smZXEdcP2IZop0Da51jPUu1uMz3X7v9xbjBfpxGaqxOFZgrUNoy0wNHFFSmout9xvDADOVeRGycn+J2fXFnb+F//w9rsjXVZvh0IValSAzujIVcTTSsGiKum+/yjUzW8dqKGH8PHu8qclV5HMwNz4swy4LlpbCyN4dYj7sY1aI8yJQFkfL8T7fdutlMPo+Z7E9hSOmdfh7+ysnJAiNqy44BnlWS2ZSTDdafWLNl7mYCFbvimDXBr8ynqlP+bbmX9lstSZ8xfOU9yqFKtR5mWPjJMsr+FGsPyLFO1qm4EwIqxV8fDtGeR+H5wrdSiGOhXDyL6/AF2tcTbawc8bwXNZvAPL6Lx3Strx+9sRLwZaF5HU+wYzHbRhPg+KqWRz/H5JQ+vLdewwn281SJ9giWHmLWzDmGqzvHL0wg+WcP1SglXc3J+q9vHCQcVpaZXAexhx8MD9vsnLsjy2tjGASb5PBivi7heS8KFZsY7iDXXUMjQriTFNWXeI6eWrCXYAKhr5uqGNdruqUYJFO9SdZu0aWxYesSB4Dba6GS+elwGnGcOMczXGSoVnbGTNNjmlaLO9kXxEOc84PEp1j5eRvirR/hHHnQNq2YTolZbCV//Dyv4L77nn7y14dZbQRttA2rLCmFW1ZyZi3WO3zlVw+xsGS3GVaLBdsrRh4GlyuhS+VvgzCTCT9Q7VyfD8JpVHC/Lfu9av++twGvPUeyzF2T1lrt+gkl3Wri8lLB6Awrf9dpY02x2z4FgacwV5TV1M/udEH2ptwZ0Qv378OC5X9tnRz/e3RqP4lB0hjZUmMCn5xkaUwzNUKcMMjM2JqwEy/E1iqhSdUrG8SsHEZ49wK5NRO21g1WPWF4SxWkUOszx+nXxQRCIr/xxa/pvN6pPrLdRIV+B1LIlB6betpTO6Cunaji1WMMPAh8tyviaOU+1clG/aLxU8fLZCbSenujcORBFN1XoZa/2+4EoubMVcG7nmj0FbFKUjbH1Z1HyGlKGyuc7AWWaS85ds1wzcAbVioKSQ4SdHjgBp91t9kJjkrG3Zvd9D2eQS4rzteb9qXYaGTNUjK4CpRzzKjq5H6XiJZQoQhijW4VE2v7WDKgxjhOTiJ6bYe2ztdUPq4zdiStimDzbXWDHIH/lf74+9oPm+tE1yGNh5GrWxhxl8dR15hOmMom+9lQd78JXmm87mZyKrrOXXJCjDPArkwie8IP3VMmdtbUOxsezmUTNmOi296029XYAuVPX7g1gS+k898coA+0jUSQfSxZnUOqgkSl4ZqkTnZeFBHUf/VnR4IEJBFhsz7U3r20Wy9xPAaB7KvWj3tnvbZ6D3pMt+uU5phL7URTUusWma612lxIaiqgAT+VmGcfnDsng8YpcOTkj7wAeZe8klNqgNiDq+ls7jqz/9z+vr3Wik9KRk/Y8TDz1fN3Hl07WMDdbVnZqCuYwYkCGYCeUmsrfnqoifHkKlzzgpqUcs81aD2zO750C76B+9gSwX/q/14+1Ec248PcLNyylfIZjMpze+PGWib/MA0sP29hVWmeYyHh5M+x5b582y5AX363HlKbcFnUflrfcLiZnPXGSQY/Vgc8sMKUYe2cdWKEQRquNos6WPZp+8hnH0iSixRoTL9c71+fGSs2a3NiITUg0MANkA3D6bJw90gqq//aHs9ytngrDkGI4dJIElXjQxz99uQ6/XsFVwZQXSU5gVuJhT9fUOPD0BFpPVrDS0Ioy4yZK989GaUV7WUG2p4H94h+uzkaO/7gIRc2lkMv4lcAoh7/uOot0Ob5cSpgXA51pOPA+Pfn67IuJcmeptqHORiNufc7w2z3jjb2/TLOKp11B52vA83MMb8VstwKPJTcr6hwfWoZS+szHSzMiemaCtT41haueh5VMYj+6Pa1s1nsr5cVFdc0UsM5L7rnvLwlXPAIpHLJTz9cYzp0kmXoK7wRMKdfMWCyFtwZ6jPYZBpyeQPNICR9ah4xRktncwwNR8fJ+UOZ+99jFFFs6Zy/Cb62Gp1zGG2EkHLusas/GTzmadNlOw+mODOw0Z5xKv9BNPt8F7Kgea9StkUBtU1hCwfsdKPGTtVlvAs4XFrS2m6jz++s6rDFhsS0wm+9ir0xlbvr0AdZ+caJz85GJ0gpardXVKAqr1WqW9bZDHAe7ZUrpVP+Hn+7b2OBPMuZWF2shzixW8OkTdVwGZZ+Kx5ZDrhWFVzI+8FQVwaOl9iWPTGpdbzKbSu+ZsMvtHgq7EtgUzBEEmEAH+2XUeowERyrilvdK4SEDbkMZ8njrbHTXEJNwcmt1vx6nlrSWXTe22GzlwWpT7+5M8ihzv4euNN4e8JkjDLUalGMH2aYNJU4036aDRCHFsTwFSgoYnpmSzdP7+FUfWM04eBjQ0OwM2009DbULq4qk33jP/7C0vvzlpw7M/fJR3y1P+WjHpj1j4bPHZ1bDOKwcK6P9/AQ+AkB5v+1Kl7YoYJxP9rSNehTQ7z5gS+n80rdxIGqHx1HiExCCK38mCwF5EB8E8NRCjapU68VmMoZ8cNv00r5jFuDmt+6IE8jnY1+boSjCagpYmmGqThVl6ST2lsBim7DofUrhzTjONIBPzbKbx8awWi8pZZSd/8tmdY0t2IB5pLKxBGw4Dr7wB2+U//PPnDjt1Ur1ZuyZZ2RuZY6zDhwTWDLjQ+5zwtUDVX5jvNW6iUolvHv3bjgxMfFQ26mHgXvXAfvX/khWVtjG8xEfm0Q7yI01zqvb1g/YvTCKv4kvyFLMviaxzEqnMGhlZUlYa6vahm3a0fWshiRyiOVpc8tDFSi7dIsD1wJdItZ+GXbWxg3zOWosxIkqj/6TQ+zqFAtu+r5PNmkDGJv1tlncoRQ6b9MRuF9//Rus8tzXJ1fancWOLJEXaMo3z89kFJ0rA/sZblU4iIMgGzVJFHToGHnayPkPlfPJMFDT77sH2NpNdDwMOschonnpws2iOtnPdulV49QVkwT10ZCHXMWaBWyLV09jRcM2w3FnCL9FiVMiQLqWiA3qbgfaptbPJdW0I802KaF+dQF4X+i8X7FZWjUxcrPiFRSfq2OhpiqkWWbtQ6Wwc3pK3q274urYmGivrkoRy9KG3aZJZGXpTbO5imLrl/vee++VLtePzcLBklfCmP0MDdDppqQnOFrBGg+C9+M6WoaLyJWpH1btdz+Q7xpgf/4v5NTK6sYJV0STEaPHnqMNy2bWirGVxW8C0hyA5yrR+rDnA84HxZZr+HfDDNPKNf1I0sq1rIYs69SiryHCRpFYcxWGTx/juNQO8X4Qx0pbrLaWrbuqeca5uuZzjXB9scpvHmXBCnyxDlSyWTppIEaO3hTb3W+jxeB28eab7jsLC+XQqR51fe+wy1CywU1PllxbJxg26n77A68VrhD7HXMSuXZqRaFI+168khXYFcD+7LfkxKrbedx1olldlcOAwqJ3fVhn03Yge55BaK7CylD+PptnEIvey353FWz9UzDl35Ao73KDYaEG5WxCWm+KlzaAV1hO/iNcU56gEBWf43CZyV8/GLaWx8QHvh+tAWVbCWXAbKj0jpqMbKpNlBtA6VqAAyFwnHGUVdQmB8oMwg3DVpXzDwHczWG9s1xEAeqcPflgA1tK59f++Eq5VZ5ZjFx2WOWgz9F+q32dUSzlgXOgUq0P+U31M+TwoGEMYs/NMNVzUA3zQjxsDbqZlG7rATjRYHhlgeMHzVC5gyYMf+wDami8MQATBXykBtngsnN2kq8uTwVXAJ98u40MTXKrrfFOql/sNCW0wE3DdK9cucLZ9MEDnOGxkk5ASnO8TaoCQNnOaXo2N2Fk6j2dJGEnGI8HF9ixTI1OZ9GBMwPOx0XQrwpTl4LbbF0G68l6Zal3zyGQOQFyKXiW7beexjBwdyFtSxQWy04OJImiXzPrDZ8pZxMC9Ru3QxVaqQiz7VzCqfZGfGoQGaQY5RrkrzTYjSkfKzMemlhdbWOwTfqemoxicNO+c99++213eXnZW2tjAS4OMYTtMc5/GgeVZN1VbfFgJG38TgBkt/bxwAL7sz+Rfvvn7aXI9Q4jDLr60gHmKAWYPmi2wZnHltvsfUJRczKRqN+szvoeHrEsHBPmnv3Rw4InDWMWPM5xToT45AzDUoPkasokEir2W0naxoMsDMHjzAcEdHUQVIDlKhNf3o/r5dLGR8BYB6urYQzqPI03dXpfXDBtcJN4fAeoToJ8/RUXQRyEEQMMmO0IrQLUI5w2DySwz168yKvR2dkWxLPMgRPqjPMJWc7k4s8BjfVVBoR2PwNZc9MwX0dnsQjZWOzeVU+6yDkQknPCiALGyzXUtalO1IHlQxxXw7jGc9zOnHQpG3VMwZcnmThUCtuvTsk7M+XwClAmsNDdjRLKyKnmLw3jvgImI3PTPlRUPP5H77Mmtj2ZdHAEjG6pyQMH7HMX3vLW9i1PR2H4ODxngjKf2LhOAbzPlPPkYrvppqi3QaVFvTfLmsfMcepwsmoHJEyA5qo1D0D5w05MAWfmOf66GWJdhYzpnlhKntbfqigsn+GVKQRPVHFtigXNCV/J0tl0uzZLm7Dd1Mf91ixb4DbAVsOI/yVANhT8fo9vS4h6QC56oIB9Xkr3b77TXgoj91AknUqiirKoZlZ+7QFZHrHOaZQFv8o5n2mXfBxFsZaQ3nwKnhT1GzTg2Pa83wdO7geOTHFlxrrZ1sBNOaZaH8ixg2KtPzPNNp6ttj+set4drK2FcW2qflUkHwgKaIHbPLnsnryvnMQDgsttD+OBAvYX/s3aXJu7TwhE43a2jGyVCxvciYzbBzCDqHcPuAcsZ6ptPIBc+bof65/Q25yTRx0qAhXGcGYOmJ3isRkrk2DXVpTF3VDR96VJJhbHwo3PzPAP0Go1UVF2ads7y7DcD3yQRA7Q1UwLar05rD8YwJbS+Qf/5mrFdSdPOaXSlIzClK06NaUYVHlEdFhyP0VUB1DvblXN3pK1PcDup1jL8Px5543N3ZvmpMF+fpZKw3JVk0pXutDGXUOc7USC9B25XJ6YZOuna7gxV1IZg+mfYbWNTG2D+oGg0pvbokXrrazAxw5sOqG/9KfN6Y43djwS0X7HhdsPoGav2xPtYc1zWOoM1vTHQZQ1/i2rXOsB6QhmsSGctwLtXIUynHCcnAXeaQO3rX7teOTkEPAYDntCfm6arR4r4X3fV56kdlogo/U2oE6cTRJ+t/DU2gpeds01Hzuwf/fbH43fLk+fcHhpf9QJdKKEASatBNxWzrE87Xa/Pvqx5j1ste1vnuGec8+OPPY85/Cw5WSSm081qCwsV9kAKazK1KSiWya+03FOMuqOlGoLHqIXp1nrZCl4P07gZ7Td9NdQ7G37eO+aXVwMtGcFPlZgn7sgvY1ZHIIrTjgOUeo0RBXYMiDvRzV7wD3E3p0Q7QGsuVmtPFv0MOqdYQpSXIICLKP0vVTAnePdALhK47WjtsxJYwbBgFnG8EINzSPjaD1aVucAxUwbMGdNWSkqXcioDxf6PzZgn5eSv/Fn67NuqXSMl/hM0B7iVZZBUvIxg+ge9nkYLzxE7rZdVfOUdrkAtqh3djsRqClvFyUXfG2B450QqoJlz8uQdkHJExjmuMBrU+zufCm45Pv+eiaBn077281DRt2p4I0C0A8XoBNR6+OY9rkLknX2bcxjfOx4tB6ME885TPGl8DmMulqKtYREWvW0+mE86dvisXtY855qkb0r16NgyzSh7il446VDHLUyVPw0mbP04WEh2TJyUzLCE2WIl+ps7ZiTsN4GxHms95bipT+OfVDc896twMdCsc9dlNU2D15iDq+EWVvWIPnalJjOWY88Cp5VrA07QJI+tqBY6zl3MqwDwfbULKUt8tFkwCWqadVz0nRPFjL3kefZqXEEJ8Y6t+ZZkhDfKMZsFtw4mhSgvndY2VU9319gS+l89k/gVcfbjwnPWwhFhv2OyeQw6j1QMTaMNe9D+QfJxHnUO5G/h4gI5CRGCREobfZXTnDcZQzvtRCDOlMki6K9iPX2GR4rQz5Xx+2DAte5j1ZZ51Cgu5loJ8N+P/C26V2FiD0y2PsK7HNvyWp4oz0vmTzmAqWUciqPCg+Qj/MUa4OoZg/1ju+3WfY8Ncz44lytfNxw1qP82VxR66maNmcF6oKMbl2lOxHwwXCwDPkPquHKfkdc9rVbqK31tk1ZOxozvUf2dDGN+50a6T/+d8HjkZDHHEeFFve8BgGkLxUfxLpbHeb13U9uNwNLseYZ+Ts7eNu5Rf1GNZ4Z8JUlrtIAfwiGa22T7ijDA4RM5fqmFLtHywiXy1h9YgwfQOf5sllvw34XVLqA78AVuC8U+/x56f74NewLRXgCrlOlZAnDlNWbsU0rSr1pxZq1Ln0Oh54u+7HdNqsQ+3RT1oCvLHIsNBjeUv7eg5MqzDHgExO4u9/H7f1R0ITv26Ysoyyjvyl5utB6FwjPW4H7Auwv/OX1mu9OPiER7Sd79UCvL2uUVnLP5NuB8vcI1Nt4X2dZc1KeZ23m3ZsCuXXsrcQtBtsEaNJ8n1SRWT5+0AIu2+YsdZM4jis+BChd56uT4erxMf4eAGPKMvJ01pRVuIUWWB66Avcc2Of+nSwz1jkB5s4KSak9M7TYqjmVpZA7yZpnTVGb7TuXwzBfxmw6Waxem+M42YCqZvlewFQ+MrtZl7hTqiOmTFmLZbSWxoJLgCoDmydP24kGCtv00G1dNLinwKYwzB99HwdEJzjFXM5EDqizOqQeBVj8jPI8y3pkYft55lDvfnbmPMXaIFEhaxYzJmhyD/3NRY4mY3ibNN/JZIxM3R0gydNPVtE67mFlVmLVC1t34qgsapznRXZfspsUkNgbK3DPgE2gfv+vML421nnUKZUOC+NZNpBU9i+St1kK20/uTg6DIYo11W4Et1RqRgkDl2rAby/6WPGBd1o6zCpxObFwrTzPKBdZGcFyqf1+1RNNK8OJiZ02xe7oyoL13htYu6+zuDfAltL52puYuON2jjkd9zBcEl91+ntF7Qah1CbDAzzSeuTvYYEjgxRf1pg2qz2nyKyTdeDMEV+l2Py+slH3UmiTGWWWCTzhyeCFsegKvPD66mpkJ+nP03o/VAXb7+vu38M3uyfAPv+W9H50p3XCLVcORpSIkLZrppLioGochlr2Y8vt5zEyGz1M8z3MNJY5GOiQoooav0ea7zrDW22ovGTtlHZP02zqmlxD9zERLZXZ6vIYbnrADSuAI+t4YmRqdX2h+d7DCLxHU9txYFN89ZffxlSpJV5yGXh+FUydpSCx5hpQ9dST7qqd+2nDe4BNVD7vRIhvlvdbHhfRl6mI+6FAjt85Ro4nDO8K4IctShNsspbZ76ESZr/gCbFQZpdrYmMlGhvbqOj4aWPGyjqdFAEc92jDPyzd7jiwybus1OwsuZ57iECdh9X04upKFUmuvgGs+iBTVxaImzGL9SjKMp3ZH8k9lHy4Pz/HVUH5qwDeIqfvhCOwgzmoLcNjHqJnS53LlVKJqLRJiJCtaGns00WOr4cFffdwnjsK7K+9IUtrUecZx3X3k1xtqnaMIlLbc+zLphuq20dlnac575eqOJeq5wWQWZ2S3zcpyT4/z9GoMfw4znaSdj3pplKYZJBHfISnSrg5UVK1nY2/N/Vq+3wXnmT3cJM/jF3vKLB/5w15MJLBKbdHoh68tH0VVoMUbZuoYz2IevdjzY2iz/boXiwDv7nAMV9n+N460AzTekBTBICuOeQLPF2W1yelXK+XSpQUwZSozSYZpFkWJWseRvTdwznvDLCVFvxKeY01TjhhdHD08XbzG/UF9wjkPg+4ebJ3X/PVELMW2akpmOMrCz7m68DbbV22lhuloLqZZiNI9z/rA58s4+6UUCVgCdBEnW1TlskiWmQ5GX2zFC03sQI7Auzf/Vs5zjrt+baQR11XRSn2+J0kkmdaBNUlFq2USFui3jGuRvVcy6XgGQ8x0xdps083gJdmOGbrDB9SHep215fMvidNbVIKeaom1x/hyj20uQrIahfUtpLsntbI2sQeKJruwRXYEWD/p9/beExIHHOkGDPV1u3SMyn52XywTb0ZROaCO0UdM0/C9tnMob65snfOw8yzPi/VOP7LJYZ1BmXS0t5k3QHrd0yZs456CGZluPbIGL+JVovqOhs5moZQgHoPAuhBndL2gC2l8/t/Au/uvvA0mDOTJCPMVq3IwWGKcGfJXpwhtJ9GPdfJZYA5y9w+l6vvw4YT27Fc5/j8HMORKeCvWlrzlTDdCbiZymr0tIfOQRfXqmLjxtjYmGG/bXMWvU+VqKW+Chv1gwqN3T2ubQH7978l/dbkxoF17jxeGvN9chtVgLVz7I64PimiPQoFH4jWbsbPLNs9CrjJRfSVWY6XGpT5hOEtgaRsrZajtXbQWOKf8hA96uPDis4gTPi3td4G3Ik5qwDziJuiaLblFdg6sKV0fu8vg4VOmc0hElPS4Q4zvqJbALbNoffMpk+Ob0U9B7HoObJ3rlLNujklMjk9BXzlmK9s1FchlN93N9S0qy/3mcA+j7WXJa5PlnDdArVhvQtQb3lrFhduZwW2DOzzFyX/e3/9WW+iPCvbge4nI6Sm8D1CJlJ7Ij2mauuLHmeUAdR7WP40cy4YRoNiqX9vwQerAD8ORMJ+m/npUGqGBgQOeXJtLoquVj3vllXX2VBrE0edsN8Fpd7OVi2u3cwKbAnY5Db62z+8U3eDsdPM88ugyC0LxX0JdkzsEl2XKgcbZ1Pp43TSj0XflILNHDgDzFrk9rk4wfFyHXh5juGvW0JlPMh7URz1sx5aUxw3S0TU06VqbUWZAXUhS29mVxZtt70CWwL2Vy++O9YuH5wveXgibwQDgZ1ia+NkIsqflOo+988vngDcAqmRd/tS+kG2s/heNFaVIGGW4+VZBt8H3g+p1I6+Y1p5r2uAPspke97nH3jASsZF1LDe9LcwZ217exYdbHUFNg1schtttpvHy9XaYRGKbg3reOiarbkAACAASURBVAQ9oLZduHLY9QQ9isPlyJb5Gcie90ninxwCIzi3UP8nJjj+8XGmEvi/F5oAU31njW8BnzFUAbmfYe0gx0cxqI05y/w1gDYa8IJSb3VnFtdtawW2AuzK3fb6MyXfm6Fyt7YWPBfU/YaXZzQ2bWNkZv28bWLNwEEQtPOn9ZW9Y9Le4xsTV7r82oKPOqUGpiT+SYRp90Sifg9xYI7hbjkIPvR1okHjSUY/20qywj10W1uyuHgnVmBTwKbSPP6B1n5ZZs9wxktEXW1HlFwWfKCGfFDsVyx/95G9beJvs+n9uG8yYRH8FApDgArGn6pzvNxgmK0BN0LiqyncsvdV95k8EoZ36pxfA3DHCuCwHVAKJdlO7Miijx1ZgZGBreKsv4upMQ+PSlfMEjoSEMRvslrw7AjtgIrNjj5JSpID9DwFWxbg5BlGnqAG2K80OD4zp2XqD0Ohw0YzFzFO7LeIGoytTbfb1zwhVlAum7BL26SVRGcVmu/NPtmi/b1YgZGBTdTaO9xedjx2BDLUhHpEQFtNe+YwgCB321psuyk1mzVj9YCbASaJP4HayMvUbs4D/tGij9kK8I6ITVq23YvYccZQEQKPMHbLCYIrvhAtVCp2cfke9pvuUQD7XmzTos/NrsDIwP7qu3IsuLbxSeaWqoa09bDho5i8ekZoVbDPL6iZO6d+9ukswMmMZbTt9NsMAz4z6+P0rFZp3wiEqsKRfjFUSK5mWJsE3o0rctDlhkobubpIjrDZHVe0vy8rMBKwz0nJyt9dP9Bx5LOMs+SanQF2dp5doA+j5in23LKRG5af6ggRtaZ+AgHM+RxfmmNKUUY2ahXQoeTqrqKM5lQGxHSIjZmo/RE8j9xEbVm6UJTdl61Z3GQ7KzASsP+z7zT3rbn8SZc5lOpLOUrnsuIZzVOu3mx4rqRkPsOAbYzMsUUqtQ4EUArkIHATgCvgeG0WODPLFPtNPLXJUdYdp0ADTNYZLlcA8iazY6lNggTbRl3kJtvO7iuuvWcrMBKwz/3l3SXXZY9SeR5OkCZgZ9nuHBTnAZvYXqobYP6qmaW58XzWe8ASZIFN9yUteJlMYircO8TpKR2pRbWpb8bVa7O15msADgA3ysBlK+OJMWvZlFolSCjk6Xu2L4uOt7kCQ4H9+z+R/vUb688A7qzCoE2tCSAGvZYiLc9EreRYo3WOwZ2MnZtoKQvl2aohPfJ3L+k3ijWVcJBT1mNKpsjxYh04OcPA/G6Uln0wcaEyicqDwPo4QAkSTEG8bJRWYdLa5oYrLr8/KzAQ2OcuXGClg1842nHC44zxMriAothGIW7HXedpyK059Cqo0hNUOOYEw+6LgNmvuEAumx4fNATqKUrc3QrxmVmO0w2GJrTziRIilEitG9MhUAWEB9zdB5Vw0DifGGWZSWNUmLTuz54s7rIDKzAQ2FQl05PV51we1VxopZkBqKF4g2zZRh43rPfw8aapsCLwiRkqTeb7yd+kzW74XOXyrrAQ5+Z8CB+4ndjJ4lEwfUiVhcABxm66QfCR7ydF8bLKslSChIIFH/4kixYf7woMptgXVw/IEj/lMJQo+IFIXS6w88xcMXudVwVk8JSNEG5R7j4x1xrccQAJKcg4R8PTCjOqj/V8g2G+JnATTIVfJsMUQtmpqd2BMFytcv4+5SeLuX3b8YTeJ1U5CkB/vJu1uPvoK9AX2F97443S7eaTRwUTS6ykLMFKi8xJIDX65AwrbivLDLUefSj9WmrmPMyRuel7I88TS133uXI+0e6iDLUK0GQi5rr16Ayr7wFyClif0YoyMmkbJZkd0EHdF0Xxtv8Qix7u8wr0BfZvfLu5n42xRem5M66Ao0RThQoB38ipNhXM5DlL+XxkHEDMATDUnJWpI5Kw5plF8jmHhxCHyhxzPrBYA+ZrDFdFnOlbn0vgVHSe2G8ITIdydYzzS36aUtvVOYok/vd5Mxa327kV6A/sv1h92pHOYZRIxaQtvl0FmIi14bElOKs4IzY846JpD9mm7JsDt2a7beJN35Q5V3m/FypAzQNOTWllGZFhuheLgU1jUMXxgPVyu/2B53kU0JHn+11ov3dujxU9fQwrkAvssxcln3TXX2DMa1BuPsKFgrCSm2NPLRvMORrxhBW3TFzGv4vm2fX16kZedr+ju9gvpR9XpiubLTegPlLWoN5fARqkNSMybKi15YhC+cz2CdGpR9Hlkq6jZRL5G823LVMXduqPYUMWt9yZFcgF9rk35GRnPTzlOs6EAnaMRE21Y3PXAFNXwnlbLHiWSud6pcVzGkbFDcX2OQGZY6kCzFeYYsHJ/7PrKmqsW9r3ewpo1YCrHnA7U53DjqlW1LpQlO3MBit6+XhWoAfYZ89f5JVPPv8kH+OHuEsojsMzYyBrdlzHLSsW15BfS94eBuxkqjYJtxRhw4BtbNs1n2O+ApyuMRwiFTeFYILMWKlhocIYsd/tKvChp11FbUWZHdBRpDP6ePZhcdcdXoEeYH/2W9J3vY0XWMmZ0som4xeelrNZrIgy1NzCtwZWH4XZqOM32u5+IC8DWChzLNYYTtQAjwul3iazln1rjzHUASoodrWkHVBMxUs7A0qhKBv1wRTtdsUKpIB9/rx0v/fCrSr8yumSX6pCBKpijwm+thVoWu7uksZBpq6sE0tGgO4ulEXBcwEdy+tezIJT9pMlCsXiAAnMgdUxgZtAXRYimmJstQFcyrFVG2pdZBPdFdu1GOSoK5AC9mf/+U/80uNzM6HHTnBOViFy5IgVZ8zYsWM2tw+wh7LhttbMjDIHxf2ATSa3GuNKWfbajLZVXxZCCc3EomuTHFFthmmGaB9wywOu+mn/b+MuakdqFcqyUXdN0e6BX4EUsM9dvFZthrVnStypR65wFYU2AE5pxjUV70uxjWdoDLL+irL+MZx5wGYhsdxaYXaqDrxEZi0GfEhhmBaoSWig6K5HgPXJIHgXOvmgCejISz5YZD554LdqMcDNrEAK2OQb3m6VX2A+HzcKsi4rbkxeWjlFirMsi20+b0fGzpWtY5t4mQELHseRCvBUjYFXgBuCtOBCJSg01Jq80CYB8ShjJHbbCf2zXmVFPPVmdkvRdtesQALs8+fPu3/xqf96isM7xUsEGW3miq1bGVs2ATvHnh1POy+Sa5B5y16tHmCn5GrSgHOcqDGUYxacnFAsUV95xU1CiNkoujZRKpGyjJIlZCO1bBa8oNa7ZrsWAx11BRJgUyGAn640FzjzHuEuxUdok5aivokCjagiZfTW35GFSb0stnw7oKauUix4DGoaR8UHliq6BA+5i5K9mljw9Ziam4NjDgyzDNdrZPnqZkDJZhQtbNWj7pCi3a5cgQTY5y5I7+Zk8zTn3kzJEdo3PEOxFYZjEq7ydFtx2cl729w0VMZOr5lm8mM0G1DHyjJyGT09pbXglDJY8dixd5m+t3ZCWZBha4ZzkyzBNmmlNOCFA8qu3K/FoEdcARvY7EZ19VP+eHmSzFxGOZZmxTWEVBYVBWyTCDBNtekXW8421DQvs4oZZx6lpt9qPnBMUWqmNOF0XxWOJSh6Q9UCUX7pZc4oq2gwA9yoaHu18QG3Y6uLEMwRN0bRbHevQALsT/9bOSnk6jO+HwM7LlZnA1vRxTiLSirnWTayK6MVt6l53nIloDZ+5YbD58B8rAF/foqhznQo1rtCB3gEMRtOdbWOhGF7jvPLsbsoydV2qmB6XyRL2N17tRj9JlbAAnbwhJDRHOfOOCVVsL1FtWZcG6BJ85ykRzLseNqztOv5lfE+swHeY86KsyDZZwKFYC7VyLSlqTW9yF59SVBJnm4PDZ/hOPmAb2x8NDY2ZjKL2vnKirRGm9gURdPdvwIJsM9++9aTjmRHyT/cmI0UO66DuhLvM/pA5iQF0n5yth22OSB8M1m+tFit7jfjA8/XORYrDMcqOuso+YJShtH3IdCMr/E5w2woOss+o8T+hHtCvInaMtpvlTChkKt3/4YtZjDaCihgn5fS/fN/HTwaue3HPIc5Ctgxe504qcRO4SpFEmnGLVD3pCI2aZGocxvYeSDPgJouoQwoR8ocn25QOCZTaY4UqBF7mcVFNgnUDaBzMOpca4ThVZTL1Myw4Ea2Tqp1FMAebVMUrXb/Cihgk6nr7avNBc7xmOMwl5RjypTVoxknGbsbZJFQbMtInTip5MjZdvrhbPZRK2wbVJXgqRrHqzNM1deiPkm2viyAq2E32+gMh3xUqiqYRK2NvdrWhBcJE3b/Hi1msIUVUMA+e1GOyY31U3Blw3XgmNzhttto4oEW5xXXtmztfda3lG6WJc8M0BBwW2dG1JpMWy/XucqEQtSa+GgK8iBgk2xN6m6PMywwBIvAldi7LKssS5xQCkq9hZ1RXLKrV0DL2FI6v/Qnq2e4404SUimBgS1DJzZrw35bTioDgR0vTeK0ktF6Zz4msvXJGsfLRK19zVcban0zodbAPg6xKOXtac7JEYVKcdlyNV2mFGYFqHf1/iwGv8UVUMCmonvX/nXrWRc4qDIgxVTZUGKlLIsVaRrbcRpiI4fnsOKpsj2m0geV9uktQ50MnX6bj23WL05pd9YsC05kuC5CPFnxr09ram1AbXuXFdR6ixuiuGxvrIACNiVXuOu2F5kbHjdupCRLx/qy2AONKf9wBetYc5ZEfmU15JtcG+W4InSiwcUKV4XzKHkCacKuCnJIEViJFWZ0MjwBREcZ+6mn0wZnkxESpRaO46gAj+JVrMDDuAKaYl+4VL5WmTwtGZtS5q2YFe9VoBG4ydWr60du0iOZQyAm7iOvpalzTew+sd6n6xynKSe4T6YtoUKzboQavfQaA+RzTLYqnc7fl8tl+pr+9XiXFSz4yI+gaLgHV8BixddfkJD7Eru1JWcnJq9ETU7UPM4tZhRoZnEyXmiD1kzR/9jPhJRkSzXg1YaPOco4SIAmD7MY1MRnUzXMQ4ytLXKQh5lJ8m9rwQsWfA9u0mJKm18BoxXn66t3F/zxiSdY2Er8vA3FNlSYyuIkJi5yLU1s2+l62XoYlh95zrgSv7G4kF6DA6Q0O0NVMStdt1FKoEAv+rPIGY4wvF8HrluU2o6xLnzBN78Hiiv24ArErPhb3tXJA7PSHT/JpVBw7VGgZd1HlWacXE8tTxW7rK5dJSQVjhmHgliB1yRbk8voqRrHcoPhJmVFCYTSiiX2bQ48DYijjP0dgLX4JyNfG0pNWvBCtt6DG7WY0uZWIAa2ZB9Wg2Oexx51orYi1ImcbQE6dkjT9mtVw4s0191MKracbai2lUCpOzLLUZyuOVQBXqxzLNR0DetLoVDacAXqWKM+RRlRpFw9wPnP4kyjxrxlwjEL89bmnn3Reg+vQNdX/OLdRqftPc8cUbI144lrqfIZN6y4DgbRwDbQjQ1hlumrWzIvs4IWsElpRgkUXpllaNSAd2K5OrFxc2COMcyF4a0DnFNiQsoLnqswK/zB9/BOLaa2qRVIgP2JC5fKbq3xHGOlaV10NmbHM7ZqCpE02VWMz7jBsim1qy5OATwf2NRkigFPTXG8NMMgKhrYKhwzftEZcNJnOAy8N65BTYOzgV0ozDb1yIvGD8MKJMB++Q+v1xy//Ijr8qMaoL3AtllxbfLScnY3NVK6SF/PAsaU2ojXpAk3Jq7FBlP26ptx+Ka5lu550mftY8BPAdy1so3aSjNV6rYwcT0MW7aY4ygrkMqgcnmi/bjH5DHYCjTLfNV1LSW+3MqJFlNoI20nxDpLtYWxbgl4YCnZ+oavTVuaV9AvkvPHgegkYyv7gA8spZkxcdEZUYRkjvKkizYP1Qqk0g+f/aO7DTHmPedIoTBsUiDZ/uAm9bDCcpKcPx0IknDiimuP6bPm4JNC9aQJJ/fRMw2gUgYu8TgjisWC13yGR4Hm4SC47Pu+KXlLHRIrnoC6oNYP1Z4tJjvCCqQLBlyQ3kcTrScdzz/MwqDH5JVKusAZKIE/Ue6uUq1bHzdPxDY6M1K7T1GB+jLH8lQM7IwPObWd9RmeAa5O9PqEp2KtCxZ8hCddNHmoViAD7Avs7sR/NBkw76TDnAldC9uixrr0dCxTx0o05aVCzipWAYHMEsbEWn1L70m2nqvoMj2kCfcqFGdt+O/uxYcZEyeAD8ZbreuoVIzCzLDhRbqjh2qrFpPdzArkVttcK7WWGWNzHNpZxcRlG1+UhB03gSIxsBNteawSp/bGF9wMiqg1KcwWa1ylO5qfAW7yriOKaVdjDMeAlSMIPvSRlOixHVKUNryg1pt53EXbh2UFeoBNEz97UVbdaOMF5kRVO8LLsOIpLbiSs03xvkS6Tq9fTLLpD4GZ0gkT1W74wOysTqKQfc0yxYb/fBy4ZsVaF9T6YdmZxTy3tQK5wKYcaN/5s2CBgy9LJ3AMO94LbKNAoxxoxojV34Rt2HCqvUXv52sctYaOubZfdFYcBOTzjL0TpzozGUdNzHXhZbatx15cvNdXIBfYNOkv/OH12tp49Rm3VJoihxWjDEtnUzFytnYt7dJroybrqtDINl5hOitKIIDFOscUhWtVMmx4GMLnHIelDJ4WgiplUuZRG9iFiWuv78pifttegb7APntRch6uPuowd4ExSq3QdUQx6cJ1bDYpzYzfuIa2hnMcERJjnL4j1ttjQCsAXp7l4HUgVJ1105fSx31AtE/Km4s67ZEJ+KCeCm34th950cHDsAJ9gU2Tp+yl791tnYTDDrpUL9tkLbXzjFNDVfJHm73ypGxzKDRIgx47obw6y8EaaYcUhCE45zgChMvr6+961SpRa5NMgYBd5DJ7GHZlMcdtr8BAYFPvZ9+VY/7P1k86XB7oyVqqQB1TbMbIpK1zHFmO4lo+F6h16bhKL/zSfg42lQF2XPPrKGPB00HwM/g+JVPIk68L99FtP/qig728AkOBTRlMf+315kyHlZ5mrjNul9fVrLheHiNNa1lb89+aKdeydZlDV+8QwPMNjrkZIIhLitgJDv0wxDHGmieE+Dl8n/RqRhNesOF7eScWc9vRFRgObMqJdlFWV93Wo8xlhynvuDJvxWjWbqWWnG2hnL41Ji6yXzcV3gXONHzMznXzmNlpiPcD0VIUfbCvVCIzl6nsUZi5dvSxF53t9RUYCdi0CJ/9TnOfG/EnwR0yQaeiukzWUr1Y2gvNUHaPWHRV7pYpZxXSqp+a4licS5u5DLgPA9EzQvzM63RuYnzcJFOwqXXhlLLXd2Uxv22vwMjAJpb8119fmQz52DMudyY4odTEaptCXvFwTCgnRXARkAm0bd1cacaXqNjerM5GmH0dAKIXBtuvC/l624+96GCvr8DowP7FSpDjyg/+ojUbcu9pTimUYsHaUGyTaMGw6WTaoiYEasOhz1WAl+c5hJ8kKFW/Efgp9/Eh4PZR4Kq/unob1aqdgdRoxAtg7/VdWcxv2yuwKWDT3b76rhy7da3zpBNFBxng6OqbRs7W49EUmymbNRF2EWcsNRT73BLH5czQCbXkRnoK+KCi3UjtCh/GKUUdEYV/+Lafe9HBHl+BTQObWPIv/OnafrfiP+k6YjxJh2Rpx7V7qVGpdb3QTADIa8c4VkyR7ZheE7AbzKdMpJe99fUr5XLZFLBPKc4KUO/xHVlMb0dWYPPAjm/7pe+sHZTMfcJxnarOWNr1ODPupapprAnXNnCGk3VgcZYDfqh063ZI5xiDfLoTXZ8Nww9QLtuF9grHlB153EUnD8sKbBnY589L99+/trbPi9iTTons20aO7nqgKUdRhVzKP67l7VMNhhNzHC0WZkI6ORoM4rFOdKVRKn2Uk2K4CPx4WHZlMc9tr8CWgU13JpfTO0FwpMPF40w5nOrSP90XRX0ZwGvqvVwHXl3keF+E4JmSnI8xFh1ut39a9Tw7xXDhmLLtx1x08LCtwLaATfL2ub9YbUifP+7yUl1GoQrx1C+jCic7tqbWTAhVFOBMLGPHonjcMsQ88ynH2U+rOkSbAG2nGS6qfDxsu7OY75ZXYHvAjm/769+/Xecb/BnHL08wYVxN0j7jRLlJeUaF94gVp/pchFoCN7mv0GuC+dEp4KNJgKK6svnDiRUvTF1bftTFhQ/TCuwIsBXlfvP2hBuOPRExd39X3u5SbhP59VQdODXP0eZxqCaZxAjYgsI1ebTI2If7Wq2PUKkYrbhJrkC5wwuvs4dpdxZz3fIK7AywVY1tyfDIxiFEzjI49xBTbps1J5Z8vsLwynGOdsrcRfq1EHOM4xGwn06vrZE7KVFs41Kq8psVFHvLz7m48CFbgR0DtlamXa7cweTjkGzWYbxEYDXmLBMIVvOAzx/hYPW05xm1LQM4IdnNqMPfO9z5YB0Th03ywsLr7CHbmMV0t7cCOwpsGspXL8qxZmn1OPfLRyKEJQXfMM6NFlLaYYbn5zjqjVjGjrl1YsdJBp8OePTHfyubj5RXf/6F6o1b04uLqeIAhYPK9h54cfXDsQI7DmxatvMXJf9h+e4CL40vRe3AtWXuCgdeO8ZQayjH025aJEHpz0Js3Obyb36O6FIzuvlko/3uP63fvourV0P87GcRzp0rZOzN7kspHTgO6SeK10O0AvcE2KRM++p78O9eXX+Gl7x9YZvMYBrGPqeyuQwvLnG0EwGcvNC01nw68KM/+vcB3mpSyR92VzrRjboIrp09WLvztdNO6ADFJh1xg56Xkk+/o0N1/EVEU0B0rlBAjrh6u7vZvQE2Ue3z592//cx/03CEfBQlNsNUDRHKdspUeZ/XFjkYZSlNqLZ+Nwkur/wM0f/19yFrCl8lZ2i3Nm5LFv5o8u3q7dfPO3Zeht29+vdi9L+g0OcBB29ijBYzCJsl1GrwOxDjZXSO3kTn7WVEbwHyQgHye/EEHog+7xmwzex+6427jY2w9Dgcp+50dEJEynl2Zt5XxQK67Li+whOAvMujf/m9wL0tGJoB0GwLrAl3LRDRLZe7t5gcu33Kw9o3v+zYbm4PxIJ+XIO4ICV7+z2U0AJv8uaY5zqOP16VQQRJidsnDiK6c+cOxiIpMVGPIK5HuH69vby8LL75zW/ixLlz8jxxQwXb/nE9wh297z0HNo2WUittlNafdCD3k8mLsqq8PAssLujcKuZFKCXNeOc2j/7ft0Ln7+/AIWC3BGVb4WgLBkcEURTJpt+JflIN/+76m197LnxoNyNR52/AOfh1sPd+1JxY5Y5bY1V3DWsoRVJWK9Wo2WzCi2rSr96VqE5EWFnB2GRd3r59G+VIynI9kq5oRKyD6O5hZV6M8A3g618vnIF2FGn3ubP7AmxJoZ6vN2ckc5/2SuPjTASYr2l2vF0xOcU1wAnc0wHkn/4t5A9uwb3dhqbaQqAdAiGB2xVSRizg6Gwwx216kbxSfmr85punHdqYe/3lSCnxX70Dz2+Bsyp4ELQqlQpNu4KOXJMlOS69aFUGEtKPqjIYJ6rdhKzUorEJyDEJidvARv2WLEfTsiohWxHkWgQ5ISDvhu/JXz52LPxzIPp6rNMorBG7a1vdF2Arqv2W9IImptj6xqOiFE1PUFKFBvDUQlqJRm1V1pUPufhXPwzYSpup7KYrbVKmUcoGQj+V/VTJzOEIISQx7050QwTRWqUkAjdcXf3B78629hIlJwegE8+jdNmHO9FarW6ELudRRXqlddaJIEuyLHnUkp2y1MCuQAObQNxsIhivSf8O5Eb1jiR2nKj2hoQsR5DVBuT169cxHkVyLZqVqmrxwYPRNCAPAPI2IEnx9mWi5gWrvisQft+ATatBlPuLf7q2H567WHLk9PEJ5ry4AFRqJu9ply2vBpDf/zseXfwoZM02sEIseSDQJtgLzcDrxC0MppC3IyCcSLZciJ9Plf07t1q3OpWoI6bnZ4PXz0Lsqk1JbPbrYK/j/2/vXHrjuPIrfuo+6tHN5kMiJdHiILai8XiEAFk4QDYB4lllM1n6K2QZZJmsMvMF5osMAmSRZYAombw2WuQBA+NRbFnRSKFFkxSb7O563X/m3Fu3WWyStsYDSbSnG2p0F6tbXV1dvzrn/7i3gHt4nrtrxSAbrSQiyGw5S+osFyMQI1OpXSGWzx0kLSCVwIN9fHwM/j2qNiGfOcipah9g5jZk6y4cngNU7dWbkGfPAK/cOxA8Aq41EGbV8QB49j7kHiDL7PrV5vu1gs1dwXHc//FH443G2t/Pkaz84B3gnbeCCPdvTKKNn5v2nx42yUf7UDHWLhs2tnQpN87K1A0WDbOiEvJ4/W5A6raBTY/Stv4sGRXHg8P9trh9rdp6jvqqJd64X57+EPrjMeRtPDL5tc3VJFmpy3RSZErnYOc8v5qINA6iM4gWSJ7mboopCLUVkcoNxBa045DKUb0hMYnWB9vH2k5ktr4hhduTFdn0dhzYBVWbYANPcNTs+PIi4b5VQQ7uQd4F5Dkt+k+Bjz6E0K4vrfrVAv21g+3h/gcx/+lmt0tXvbexspr9yXstNtdDLbt/W2sh//WJcX//caP3CLpX7Q7ss4PHTt/mr9l9OptLQiuqtJB5qzATST63Nt2rT07aLEtUldWz9NbasY/Pu2TUj/76FWaHu4aRD0U0/u1Jemtrx5UvkNduutpkbYlZO8yz3JYlkHX99NbCeZhlJloyaVI+z/1yk/Fx6tXaFiK057UQcghOTiCbQ4fjY4yKkEjLVkRmtOL+vi6z9WDHOVI2wr3KeHsbgidPcLSzM1ftW3eDLadyv/s+5B+9m4B89CszFmNx/hBLyN885G8EbH5tlmf+9p9frJaN/d07G/rWH78HpRdmLuXr1ATyN/8OPD5GMmnCRQcIt4+2Pdz9yZW6K5IsXMQgIdgKEqZli2cEPkqlEvUCSp9o1Lz24CzXs8/NZK2us70k0daY4dqUCv98635STD/Qn9+A+9P30bI09GcPYKiw93+QNAwzfnAfeus55Kcfwn1wH/ptwDz6AM27D5AcHBwMMNzQODlo9fWNoarKF2x5sAAAEWFJREFUoUuzEzMpR3WWWKPhTFMlyqQiBg5VCWtSpwSiUwSYpwRaOrAD3CaD1HOwC8FkgqpTb0tbTtUeMtYWKZkd99YcUs6TaLTjzI5fk6lAhlsQ7FK1nay226d2/G3IPiC8vHEEm3vTKzcAws3HxWQb98sS9NcP+hsBmz82kl999I9+lPzlD/98tFfl3/vD31G3vnPToNVn+084Xnv3/0x7/+eN+mUH9zyRNgf7FFjvzD3BtObh5lXb6q5jrYWhiT1zhVAgUdppaZpEdCmpUZpb2NaVTvShstCiEqtaOCPtvjFQs7rJlTbTVZtPZ+1s4JTKVepmqcrbtjxe0SqzXNZtouqkKZSxYp1UUE0KWIYQziVVYrT18Da01QJRhs8rscY6qjOberheVuAINjBDZtccVZl2HLMZZC13jLe9Sk8m3pbXIhLAHnZgo6tpj7G6PXJMrMXs+MBBpuvw2fHnAIa9DHm049fehuAhsF9Btjs73gf7w1/Z8R/3wI67vnv0Vt3/7ktFfy2UvxGw+c3ij/zgwQPzk8Pf+87GQN75g+/mg1ubbdKvbXvVLiGfPYb89y7w8T7UHu04E2iNnsfbcW/NQ/Uw2ZqH2ys2QVZafId6B3aiIH691oKmDY88L6hGgoU3AhVmhRHoVhvTKmmUv1BCi1YsWqWgdItE2H2jjFMuUToVp5wfZgolRrSCawyhrEGQ+X8TYAKrRE6fW/j42au0DesYR6s0Ey1liK29gos/Efjnkkvj4+3OjkshVU7IQ9kr2nEqdWhWOQU71rQHApl2dnwqm0Kwacef4Rmo2hs7kM+6JNpldpzflXD3jtp4bMW/zdctFfzVs/3GwfZf8f6P9V+ZvxjV2eDue99xW9u3jAmXEAg3gpW2kP/5JeRnD5F8coiETSucs5z2vCuCnXm9X+iuBBrADiruLbkHOywbBSHQhNxPke6XeYA2oD7zeaJFuGj53MX1wQmE9d1dRFKBtNqKLzZjCq0Ll2pIXdfQOZwSKwkhrwPkyogH2Sv2AthzO55mgvIIYjIXVZpqLjafLzdOJFsvXFRtyQbhOU6QstssNquw7OWz4yx7rUm+xpr2AZI7Gw57Ic5m6Wt7Y8s946w2C9nxOdjcfTHWvg/c+8Bnyi+7nYN7qdyvFu43Bnb/a1G0cP+++rvvfZA+3Ctv3Xk3+36atXpRuQneJ48hP/t5m+xWmse970qbxPp270QQwQ7wag+tn4dJOtXuVLyv2kGlGYs3aMUIIfcHoA4ZZz62qrO83uI3kugOfg+5eKVXc7AbeNAN1xlJpA4qbQh+VO2qU2zbAc7lNKi2lKJsGlTb2/HM8TlmJTKbudlshnQ1d7TjhkF0VjhMpmBNu3ITn0wLzSqsaR+faVbJCPtbXSdaL4nm7Thr2tdDTfsM2J0dZ3b8zj3IAwDMkHMffXD2OF0cqNNfPrNuqd6vBvCrAja3g3f1008w3E/qt29cT7aLVZMGPe7F3SXwdA/uwadt8tk+kr1S+0sIcboVvoylsGDHu9JXP9YmqEp7qMJr2rlNN1TtmEH3M543ITZX51W7ZXJqrtJB3VWae4uNpvYnAsX1hJ01ZdpuJ0I7TkD91nm1jsuVV29UNYyx3rYrG6z23I5T1ZlAi3a8n0TzNe2pr2ufNqtA6iJY8tQNffdZaFYBaMmzlbOqHe14ABsYXt+VVXdTLlJtbj+Ve8F6Xwqvj2TC7dzIvCXY336w+Q05dju5/xz52GErXWt2GpuszqtXHeCE8mRi5OHTBv/6EMkXk6DctOYlTwT+PBDBPp0S2dttH0N73fNx97k422ofGxNWqxljE1aCq93cjtOuSwCe67wVn9vys6pNqOu6gc6Mo3rXC3E26goEPIJNkBsLMUXqONujNeK0t+IhiabTUsSuOsxeINpxJtT4jSTNXSh7hWaVyWQCOg1bDEUKuDNgu64LbXWtS6LF7LgLNe0uO064Y+lrg6UvXooJkO8CuHsxsBdBzL9dONx2Cfa3GGx/Ku8ypl65HzzQeL9I/mVyb3OcNu+KSUYJdNIGXe702GBSNvjFUyMf/2+ZPB1rXwbzwzzDpC2dJgdl/qokmgd+rtrhIPQxancy8GBHFSf0Mf72JwiCb4Jie+tee/AJooe+U+aE7zGdHfexdi0xxmbsrZg4Y5zdS64RbH+a6ux4k5aiHZNpofRlUmbAL0ii+Zp2lx2XoVTuWOxwxau2V+xzXWjAYB2yvw8U66FhJVjyLZ9IewvANqHehuycBXoR5EXlXkL9atj90v/1Sljx/hZ2gHtb/ugRzBc3sHEyqG+VTbLVmiSPahoeWddq0JRGPv2iwYNPkXy626l3V7EuKePdbZ5EYxzNP3toL7DjwTt4u01FntvxLs720LsYXxtfglIqd6cKHlU7QJ2KkTbG44S/rr1K044zU064Q9mLsXUVYu3uZHAmOx5r2rHzbHoW7MWadl+1h9nQHSO0mI5urrjxETCvabPN1CfRAtwxQ/4ek2ebm3LjOXB9C0Kl7nZlH9bLnnfOZ6nUb4BrH9deqdsZ5SZeDx9q3L2rPwVGn6O6+aLVt52G7WfNgyaDSV38/GmLp4fA3gQ4nOhg0Tvt9pfsjHF02yXVurXepmstNta4u4YWD6svBUXLrb0KW2/HO4W+IDsekmjBstOO83OZHSfIXpEJqQeb5w0uE2jbK4NFuCuvzNaMXKxp+4aVKSRdyXz9ul/T9tnxtHC04+ebVU5r2vOBIV3DCvvHy3XInYNwONzhfcOTLBwMshAnx+VF0P1Msr37pcfW0oK/WuyuHNj8uufgBpJnz57Zo+3t9c9R78yQrAuSzPmE2/kJVZgtfzEx8uBRmXz0lJ1qYWImqrcHm4OOCbANJa4Ya/symOkaWrqsuVftOdiMq4Mae8t9URJNGQ8ry108ARBmfmbMgidO5tbcW3XTh/lr1LTP9I6zpj31jSY+iVZwxBcdw4lUrGmzbBiHcw5XfE37ne2RPzFcS5B8nzPajMdYkZHsrJ4BdBHgPrx87q+rFqeIvuyQXcL8amHu/+9XEuy4gT1bzrhb4f33GSpnnwGDfWDjBXCjAlacT7qR0NMx3Vw8mkAOJsDeGNg9An7xrE3GMy1xEIkHLta4YzLNx9mxoSXEyOYSOx7BjrH35aWv2is1FZqvoRVn6cvkg7PNKl1N25fEYk2b2fGSkDF5loo1mQtxdjcQxGUhG+63n0m0XIybisljhjzE2mkx8KO+ePVEjvy6nSC5ewPJZmeveZUHqjMfVgKk/hzb3ReXI8xxvveo1PE9547gJdSvD2ovLK/34379T7tAvX0ebH9/P318bXBtDHOb03kJTFqjmc+I2v8kHn2TCfDR0xYvJlqOJsBxA3l8gJBBp6qy84xwdN1ntOZBmWnBTafa8Nnx+d87xfY7UrNbLZbGQtnLd6Kxpm1EUDeISbRUh84xb8fzgYsxd4yvWec+jbV7NW1Ju460Uxs+m5V+xBfh1Sx7ZWzAgdS++wzCGWn4aJNpcmdQqFtF+NtO4X97PmcnjQd48bED3K87PDyUZn293QzQc6/5ZvveCWAJ9a9/eL+yd1x5sPvf3DeyhJNR4mPv0cjg5k1DBd+rqrWjNL3t0BYOWs270eK1xDRlnYmuBuMJ8Oke8GgP4keLceTYDMK7b1X1VlpLYuH4dtM1pszLXVq8vbZsOe0y5aclr7Nw+waVGIPHmrY20lzYrEJQzta02ayipfIlsMLXrrNQCy+PwFibGXLCrNlwwqx1nqORmWwWeXIvZ3kdwkFiN4EkY295B3C+AHOEnHb6hP3iYb231y8AtxamgZ9fp3wB6AuhXqr0K+P2K//jbxrYcXvnDS1dx6k6ODiw042N1X1gpQIGDZrBIczaqU2nxpzG40ob4dVHKDuzxsjj3QbP9iGMw6eNlt0XkElDqx5UiTY2KrVSLH21aBWTbaGrjNlzZr5Z++63mIYEGjvNWNo6rX1rH4vXoTY9z44HpW7FSsasec+Sh+w4hFM0s1ecNeyNrEwYFlcCt1Mk+s4oVYKKVhrbK3xlxX+Spqm30lGRM8BxeHd2Cq8Q9GmA3vE+DIocL9YQ5kK7OCu+hPorMXv9L/hGgb2g3n24qeCK2XMmmZ8cHaWHq9nGMdRm0yRFbVgGTlKKbz/hFhU8zGlO9WWCjba9waP9zpp2TS+f7Om2PGmQZEY4vmQ8hRvPQrmJcDsNadisEu14p9JsOPGdaL6NNNS3rW9ZpXUOcLPsxGW+ZmA5cIRwQ9bTFLdXoMZO2qEFdlSi1cC6poS7nUHfGCIZV3DDFNiwjCRqsX6z0y42rlg+cFwm1CnHqc4tdykZMpkBjoDn4Tpp5Xg8ltFoxIaB+WWVLrHcFzac+LBkOX3S6yd54RO/6WDHr+Pr3rEt1T8+f26wtaUxHpu90Sj7DNX1CdS1umkzBa0qkxjnY/JQC1dRjXqzPRjdckQHlZvt2cKJD+oWsvdCuy9OWhlmwMBoHMxatzsWlxtgaAym0sjhuPGJsuuFSaDhHu83biU32CiA8aR2TiCbhU2uD+rkiwptYQzeGiRqVAD7E2n5/GZhkr1J7UbWypr1Y818Jt/b6LoGrOUYcz4PGf5OlS2ss4S4qmCDWkuFihdk8IqcInUl4FaBkipdhI7cSU+V+2WrviIvxtR+/y9BfuMcn9uAbyzY8Zv0kmv+GOvdCXofdja36C8wtYelKvYzfaMGcmla3RqdVEhsg0brDnRpaZGDisdse1D4cGVQP9Ua17RsE2XmHOBEEdJo4UnAmBZKa2nDPG1uxTB3xpGjxh2XM6xoA2MaSANJ89zZhhc58fLqmNyCX8esm58gQowJ8bxfbsJyg5ofLoW1PgEn1goVurPcIPBibWtRiUVaC2ZT9tK4PC8HHHp2el1EqvVirTpmwiPYFyr0EuqrB3UE4Wpu2dfcql6JrA+6wpMnGjs7EXx9DGQrfoIW6L2yzA8ytdkgobzpsoGtTZuRVQ0jDWNzHQeOGB+rM0afXyrYnwDCNb79ycCv5xhvfzHCAIQP71toozkARZrm9LnnuHMMXCcwfraXBo3nO/wf/BvB9ieXoNQhweDVla/nlgG1o6kurJ2mQYUZnhDiCDLft5jRvqzhpK/W819kCfPXPDhf49u+8Yr9VfvqTC38VMEXrbuhZcdoJCcnJ2bXmNVWqeHAWlpYGSMdTNGMXNMqY3TDhFyFhPMtchKGAL7vNSd6DUeHerVv2ybhoyKrXd6OkPI9Efb5cjftKtfN18MgAz+OJwIkQ2OaGlMxjUVupFU1Sljr4SuAiXAcZ56rPFhrghwy27twuHmu4WRRoReXz+zaJcxfdaRdrfXferD7u3sB8kXbfnb54EBhY8OL4t5kkg0HvE4o8Lws7Umm1oewiaLZrSocpGrNehFHmzZo99EUKRJtoRvCP0NrDXTCMajspKkMhdwkCg2XG8dTQtMkuUEpDZwz3tW3KcysBWwOtK6qZoM0nVRVldo0nebsRjltJOlnrRe7wqLqXtRkEndPH2r/tziV0RLoqwXsy27NbxXYizvlEtD5stN6eXiTxt5egs1NgMArpbC2RhiS8XisR6yn40Q4W9hkMjF6MCiY7p5Op9IWRZ4DxgJTjjg5BoocUCNguj+dii4KgptkwHQK6BrI7HQ6K4qiOgGSYdiWqqslL3aCXQQrf9OLkl/9GPkcyP19s4T5ZfG5uq/7rQb7JUCPL+l3tHGfxanVIiz9WdGj8p9hpVcyunCfcwbQbrCF7wi7YPzyZcmsxfg4KvRLgbyE+OrC+Zts2RLsL9l7C4m4+MpFcL9s2at6d4+g8STRBzf+BpeBeBHo8f1xXd9SR7DPxcjLqYB/E1S+We9dgv2Sv9dCWW1RjV92OYJ+0adGsBdhXYT2S8GN8bF/0XK635f8db99L1uC/TV/00XQo6X9khPAZdb8a23BMrn1tXbbb82b/h9jkBzrCo8J3AAAAABJRU5ErkJggg==",dr="data:image/png;base64,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",gr="data:image/png;base64,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",Tl="data:image/png;base64,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",uo="data:image/png;base64,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",Na="data:image/png;base64,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",Po="data:image/png;base64,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",pc="data:image/png;base64,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n=e._x,i=e._y,s=e._z,a=e._w,o=this.dot(e);o<0&&(n=-n,i=-i,s=-s,a=-a,o=-o);let l=1-t;if(o<.9995){const u=Math.acos(o),c=Math.sin(u);l=Math.sin(l*u)/c,t=Math.sin(t*u)/c,this._x=this._x*l+n*t,this._y=this._y*l+i*t,this._z=this._z*l+s*t,this._w=this._w*l+a*t,this._onChangeCallback()}else this._x=this._x*l+n*t,this._y=this._y*l+i*t,this._z=this._z*l+s*t,this._w=this._w*l+a*t,this.normalize();return 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),s=Math.sqrt(n);return this.set(i*Math.sin(e),i*Math.cos(e),s*Math.sin(t),s*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 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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(ES.setFromEuler(e))}applyAxisAngle(e,t){return this.applyQuaternion(ES.setFromAxisAngle(e,t))}applyMatrix3(e){const t=this.x,n=this.y,i=this.z,s=e.elements;return this.x=s[0]*t+s[3]*n+s[6]*i,this.y=s[1]*t+s[4]*n+s[7]*i,this.z=s[2]*t+s[5]*n+s[8]*i,this}applyNormalMatrix(e){return this.applyMatrix3(e).normalize()}applyMatrix4(e){const t=this.x,n=this.y,i=this.z,s=e.elements,a=1/(s[3]*t+s[7]*n+s[11]*i+s[15]);return this.x=(s[0]*t+s[4]*n+s[8]*i+s[12])*a,this.y=(s[1]*t+s[5]*n+s[9]*i+s[13])*a,this.z=(s[2]*t+s[6]*n+s[10]*i+s[14])*a,this}applyQuaternion(e){const t=this.x,n=this.y,i=this.z,s=e.x,a=e.y,o=e.z,l=e.w,u=2*(a*i-o*n),c=2*(o*t-s*i),d=2*(s*n-a*t);return this.x=t+l*u+a*d-o*c,this.y=n+l*c+o*u-s*d,this.z=i+l*d+s*c-a*u,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,s=e.elements;return this.x=s[0]*t+s[4]*n+s[8]*i,this.y=s[1]*t+s[5]*n+s[9]*i,this.z=s[2]*t+s[6]*n+s[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=ii(this.x,e.x,t.x),this.y=ii(this.y,e.y,t.y),this.z=ii(this.z,e.z,t.z),this}clampScalar(e,t){return this.x=ii(this.x,e,t),this.y=ii(this.y,e,t),this.z=ii(this.z,e,t),this}clampLength(e,t){const n=this.length();return this.divideScalar(n||1).multiplyScalar(ii(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,s=e.z,a=t.x,o=t.y,l=t.z;return this.x=i*l-s*o,this.y=s*a-n*l,this.z=n*o-i*a,this}projectOnVector(e){const t=e.lengthSq();if(t===0)return this.set(0,0,0);const n=e.dot(this)/t;return this.copy(e).multiplyScalar(n)}projectOnPlane(e){return wC.copy(this).projectOnVector(e),this.sub(wC)}reflect(e){return this.sub(wC.copy(e).multiplyScalar(2*this.dot(e)))}angleTo(e){const t=Math.sqrt(this.lengthSq()*e.lengthSq());if(t===0)return Math.PI/2;const n=this.dot(e)/t;return Math.acos(ii(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,t*4)}setFromMatrix3Column(e,t){return this.fromArray(e.elements,t*3)}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=Math.random()*2-1,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 wC=new J,ES=new Wo;class zi{constructor(e,t,n,i,s,a,o,l,u){zi.prototype.isMatrix3=!0,this.elements=[1,0,0,0,1,0,0,0,1],e!==void 0&&this.set(e,t,n,i,s,a,o,l,u)}set(e,t,n,i,s,a,o,l,u){const c=this.elements;return c[0]=e,c[1]=i,c[2]=o,c[3]=t,c[4]=s,c[5]=l,c[6]=n,c[7]=a,c[8]=u,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,s=this.elements,a=n[0],o=n[3],l=n[6],u=n[1],c=n[4],d=n[7],f=n[2],h=n[5],p=n[8],x=i[0],v=i[3],m=i[6],C=i[1],w=i[4],P=i[7],B=i[2],S=i[5],I=i[8];return s[0]=a*x+o*C+l*B,s[3]=a*v+o*w+l*S,s[6]=a*m+o*P+l*I,s[1]=u*x+c*C+d*B,s[4]=u*v+c*w+d*S,s[7]=u*m+c*P+d*I,s[2]=f*x+h*C+p*B,s[5]=f*v+h*w+p*S,s[8]=f*m+h*P+p*I,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],s=e[3],a=e[4],o=e[5],l=e[6],u=e[7],c=e[8];return t*a*c-t*o*u-n*s*c+n*o*l+i*s*u-i*a*l}invert(){const e=this.elements,t=e[0],n=e[1],i=e[2],s=e[3],a=e[4],o=e[5],l=e[6],u=e[7],c=e[8],d=c*a-o*u,f=o*l-c*s,h=u*s-a*l,p=t*d+n*f+i*h;if(p===0)return this.set(0,0,0,0,0,0,0,0,0);const x=1/p;return e[0]=d*x,e[1]=(i*u-c*n)*x,e[2]=(o*n-i*a)*x,e[3]=f*x,e[4]=(c*t-i*l)*x,e[5]=(i*s-o*t)*x,e[6]=h*x,e[7]=(n*l-u*t)*x,e[8]=(a*t-n*s)*x,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,s,a,o){const l=Math.cos(s),u=Math.sin(s);return this.set(n*l,n*u,-n*(l*a+u*o)+a+e,-i*u,i*l,-i*(-u*a+l*o)+o+t,0,0,1),this}scale(e,t){return this.premultiply(CC.makeScale(e,t)),this}rotate(e){return this.premultiply(CC.makeRotation(-e)),this}translate(e,t){return this.premultiply(CC.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 i=0;i<9;i++)if(t[i]!==n[i])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 CC=new zi,wS=new zi().set(.4123908,.3575843,.1804808,.212639,.7151687,.0721923,.0193308,.1191948,.9505322),CS=new zi().set(3.2409699,-1.5373832,-.4986108,-.9692436,1.8759675,.0415551,.0556301,-.203977,1.0569715);function cR(){const r={enabled:!0,workingColorSpace:af,spaces:{},convert:function(i,s,a){return this.enabled===!1||s===a||!s||!a||(this.spaces[s].transfer===$n&&(i.r=ih(i.r),i.g=ih(i.g),i.b=ih(i.b)),this.spaces[s].primaries!==this.spaces[a].primaries&&(i.applyMatrix3(this.spaces[s].toXYZ),i.applyMatrix3(this.spaces[a].fromXYZ)),this.spaces[a].transfer===$n&&(i.r=Pv(i.r),i.g=Pv(i.g),i.b=Pv(i.b))),i},workingToColorSpace:function(i,s){return this.convert(i,this.workingColorSpace,s)},colorSpaceToWorking:function(i,s){return this.convert(i,s,this.workingColorSpace)},getPrimaries:function(i){return this.spaces[i].primaries},getTransfer:function(i){return i===Ol?yp:this.spaces[i].transfer},getToneMappingMode:function(i){return this.spaces[i].outputColorSpaceConfig.toneMappingMode||"standard"},getLuminanceCoefficients:function(i,s=this.workingColorSpace){return i.fromArray(this.spaces[s].luminanceCoefficients)},define:function(i){Object.assign(this.spaces,i)},_getMatrix:function(i,s,a){return i.copy(this.spaces[s].toXYZ).multiply(this.spaces[a].fromXYZ)},_getDrawingBufferColorSpace:function(i){return this.spaces[i].outputColorSpaceConfig.drawingBufferColorSpace},_getUnpackColorSpace:function(i=this.workingColorSpace){return this.spaces[i].workingColorSpaceConfig.unpackColorSpace},fromWorkingColorSpace:function(i,s){return rs("ColorManagement: .fromWorkingColorSpace() has been renamed to .workingToColorSpace()."),r.workingToColorSpace(i,s)},toWorkingColorSpace:function(i,s){return rs("ColorManagement: .toWorkingColorSpace() has been renamed to .colorSpaceToWorking()."),r.colorSpaceToWorking(i,s)}},e=[.64,.33,.3,.6,.15,.06],t=[.2126,.7152,.0722],n=[.3127,.329];return r.define({[af]:{primaries:e,whitePoint:n,transfer:yp,toXYZ:wS,fromXYZ:CS,luminanceCoefficients:t,workingColorSpaceConfig:{unpackColorSpace:nl},outputColorSpaceConfig:{drawingBufferColorSpace:nl}},[nl]:{primaries:e,whitePoint:n,transfer:$n,toXYZ:wS,fromXYZ:CS,luminanceCoefficients:t,outputColorSpaceConfig:{drawingBufferColorSpace:nl}}}),r}const $r=cR();function ih(r){return r<.04045?r*.0773993808:Math.pow(r*.9478672986+.0521327014,2.4)}function Pv(r){return r<.0031308?r*12.92:1.055*Math.pow(r,.41666)-.055}let Bv;class dR{static getDataURL(e,t="image/png"){if(/^data:/i.test(e.src)||typeof HTMLCanvasElement=="undefined")return e.src;let n;if(e instanceof HTMLCanvasElement)n=e;else{Bv===void 0&&(Bv=ua("canvas")),Bv.width=e.width,Bv.height=e.height;const i=Bv.getContext("2d");e instanceof ImageData?i.putImageData(e,0,0):i.drawImage(e,0,0,e.width,e.height),n=Bv}return n.toDataURL(t)}static sRGBToLinear(e){if(typeof HTMLImageElement!="undefined"&&e instanceof HTMLImageElement||typeof HTMLCanvasElement!="undefined"&&e instanceof HTMLCanvasElement||typeof ImageBitmap!="undefined"&&e instanceof ImageBitmap){const t=ua("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),s=i.data;for(let a=0;a<s.length;a++)s[a]=ih(s[a]/255)*255;return n.putImageData(i,0,0),t}else if(e.data){const t=e.data.slice(0);for(let n=0;n<t.length;n++)t instanceof Uint8Array||t instanceof Uint8ClampedArray?t[n]=Math.floor(ih(t[n]/255)*255):t[n]=ih(t[n]);return{data:t,width:e.width,height:e.height}}else return ze("ImageUtils.sRGBToLinear(): Unsupported image type. No color space conversion applied."),e}}let fR=0;class Om{constructor(e=null){this.isSource=!0,Object.defineProperty(this,"id",{value:fR++}),this.uuid=Ga(),this.data=e,this.dataReady=!0,this.version=0}getSize(e){const t=this.data;return typeof HTMLVideoElement!="undefined"&&t instanceof HTMLVideoElement?e.set(t.videoWidth,t.videoHeight,0):typeof VideoFrame!="undefined"&&t instanceof VideoFrame?e.set(t.displayHeight,t.displayWidth,0):t!==null?e.set(t.width,t.height,t.depth||0):e.set(0,0,0),e}set needsUpdate(e){e===!0&&this.version++}toJSON(e){const t=e===void 0||typeof e=="string";if(!t&&e.images[this.uuid]!==void 0)return e.images[this.uuid];const n={uuid:this.uuid,url:""},i=this.data;if(i!==null){let s;if(Array.isArray(i)){s=[];for(let a=0,o=i.length;a<o;a++)i[a].isDataTexture?s.push(PC(i[a].image)):s.push(PC(i[a]))}else s=PC(i);n.url=s}return t||(e.images[this.uuid]=n),n}}function PC(r){return typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement||typeof HTMLCanvasElement!="undefined"&&r instanceof HTMLCanvasElement||typeof ImageBitmap!="undefined"&&r instanceof ImageBitmap?dR.getDataURL(r):r.data?{data:Array.from(r.data),width:r.width,height:r.height,type:r.data.constructor.name}:(ze("Texture: Unable to serialize Texture."),{})}let hR=0;const BC=new J;class yo extends Go{constructor(e=yo.DEFAULT_IMAGE,t=yo.DEFAULT_MAPPING,n=So,i=So,s=ms,a=tl,o=ma,l=fa,u=yo.DEFAULT_ANISOTROPY,c=Ol){super(),this.isTexture=!0,Object.defineProperty(this,"id",{value:hR++}),this.uuid=Ga(),this.name="",this.source=new Om(e),this.mipmaps=[],this.mapping=t,this.channel=0,this.wrapS=n,this.wrapT=i,this.magFilter=s,this.minFilter=a,this.anisotropy=u,this.format=o,this.internalFormat=null,this.type=l,this.offset=new ct(0,0),this.repeat=new ct(1,1),this.center=new ct(0,0),this.rotation=0,this.matrixAutoUpdate=!0,this.matrix=new zi,this.generateMipmaps=!0,this.premultiplyAlpha=!1,this.flipY=!0,this.unpackAlignment=4,this.colorSpace=c,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(BC).x}get height(){return this.source.getSize(BC).y}get depth(){return this.source.getSize(BC).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(n===void 0){ze(`Texture.setValues(): parameter '${t}' has value of undefined.`);continue}const i=this[t];if(i===void 0){ze(`Texture.setValues(): property '${t}' does not exist.`);continue}i&&n&&i.isVector2&&n.isVector2||i&&n&&i.isVector3&&n.isVector3||i&&n&&i.isMatrix3&&n.isMatrix3?i.copy(n):this[t]=n}}toJSON(e){const t=e===void 0||typeof e=="string";if(!t&&e.textures[this.uuid]!==void 0)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!==mi)return e;if(e.applyMatrix3(this.matrix),e.x<0||e.x>1)switch(this.wrapS){case Zu:e.x=e.x-Math.floor(e.x);break;case So:e.x=e.x<0?0:1;break;case ud:Math.abs(Math.floor(e.x)%2)===1?e.x=Math.ceil(e.x)-e.x:e.x=e.x-Math.floor(e.x);break}if(e.y<0||e.y>1)switch(this.wrapT){case Zu:e.y=e.y-Math.floor(e.y);break;case So:e.y=e.y<0?0:1;break;case ud:Math.abs(Math.floor(e.y)%2)===1?e.y=Math.ceil(e.y)-e.y:e.y=e.y-Math.floor(e.y);break}return this.flipY&&(e.y=1-e.y),e}set needsUpdate(e){e===!0&&(this.version++,this.source.needsUpdate=!0)}set needsPMREMUpdate(e){e===!0&&this.pmremVersion++}}yo.DEFAULT_IMAGE=null,yo.DEFAULT_MAPPING=mi,yo.DEFAULT_ANISOTROPY=1;class Ei{constructor(e=0,t=0,n=0,i=1){Ei.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=e.w!==void 0?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,s=this.w,a=e.elements;return this.x=a[0]*t+a[4]*n+a[8]*i+a[12]*s,this.y=a[1]*t+a[5]*n+a[9]*i+a[13]*s,this.z=a[2]*t+a[6]*n+a[10]*i+a[14]*s,this.w=a[3]*t+a[7]*n+a[11]*i+a[15]*s,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,s;const l=e.elements,u=l[0],c=l[4],d=l[8],f=l[1],h=l[5],p=l[9],x=l[2],v=l[6],m=l[10];if(Math.abs(c-f)<.01&&Math.abs(d-x)<.01&&Math.abs(p-v)<.01){if(Math.abs(c+f)<.1&&Math.abs(d+x)<.1&&Math.abs(p+v)<.1&&Math.abs(u+h+m-3)<.1)return this.set(1,0,0,0),this;t=Math.PI;const w=(u+1)/2,P=(h+1)/2,B=(m+1)/2,S=(c+f)/4,I=(d+x)/4,N=(p+v)/4;return w>P&&w>B?w<.01?(n=0,i=.707106781,s=.707106781):(n=Math.sqrt(w),i=S/n,s=I/n):P>B?P<.01?(n=.707106781,i=0,s=.707106781):(i=Math.sqrt(P),n=S/i,s=N/i):B<.01?(n=.707106781,i=.707106781,s=0):(s=Math.sqrt(B),n=I/s,i=N/s),this.set(n,i,s,t),this}let C=Math.sqrt((v-p)*(v-p)+(d-x)*(d-x)+(f-c)*(f-c));return Math.abs(C)<.001&&(C=1),this.x=(v-p)/C,this.y=(d-x)/C,this.z=(f-c)/C,this.w=Math.acos((u+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=ii(this.x,e.x,t.x),this.y=ii(this.y,e.y,t.y),this.z=ii(this.z,e.z,t.z),this.w=ii(this.w,e.w,t.w),this}clampScalar(e,t){return this.x=ii(this.x,e,t),this.y=ii(this.y,e,t),this.z=ii(this.z,e,t),this.w=ii(this.w,e,t),this}clampLength(e,t){const n=this.length();return this.divideScalar(n||1).multiplyScalar(ii(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 sh extends Go{constructor(e=1,t=1,n={}){super(),n=Object.assign({generateMipmaps:!1,internalFormat:null,minFilter:ms,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 Ei(0,0,e,t),this.scissorTest=!1,this.viewport=new Ei(0,0,e,t);const i={width:e,height:t,depth:n.depth},s=new yo(i);this.textures=[];const a=n.count;for(let o=0;o<a;o++)this.textures[o]=s.clone(),this.textures[o].isRenderTargetTexture=!0,this.textures[o].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:ms,generateMipmaps:!1,flipY:!1,internalFormat:null};e.mapping!==void 0&&(t.mapping=e.mapping),e.wrapS!==void 0&&(t.wrapS=e.wrapS),e.wrapT!==void 0&&(t.wrapT=e.wrapT),e.wrapR!==void 0&&(t.wrapR=e.wrapR),e.magFilter!==void 0&&(t.magFilter=e.magFilter),e.minFilter!==void 0&&(t.minFilter=e.minFilter),e.format!==void 0&&(t.format=e.format),e.type!==void 0&&(t.type=e.type),e.anisotropy!==void 0&&(t.anisotropy=e.anisotropy),e.colorSpace!==void 0&&(t.colorSpace=e.colorSpace),e.flipY!==void 0&&(t.flipY=e.flipY),e.generateMipmaps!==void 0&&(t.generateMipmaps=e.generateMipmaps),e.internalFormat!==void 0&&(t.internalFormat=e.internalFormat);for(let n=0;n<this.textures.length;n++)this.textures[n].setValues(t)}get texture(){return this.textures[0]}set texture(e){this.textures[0]=e}set depthTexture(e){this._depthTexture!==null&&(this._depthTexture.renderTarget=null),e!==null&&(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,s=this.textures.length;i<s;i++)this.textures[i].image.width=e,this.textures[i].image.height=t,this.textures[i].image.depth=n,this.textures[i].isData3DTexture!==!0&&(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 i=Object.assign({},e.textures[t].image);this.textures[t].source=new Om(i)}return this.depthBuffer=e.depthBuffer,this.stencilBuffer=e.stencilBuffer,this.resolveDepthBuffer=e.resolveDepthBuffer,this.resolveStencilBuffer=e.resolveStencilBuffer,e.depthTexture!==null&&(this.depthTexture=e.depthTexture.clone()),this.samples=e.samples,this}dispose(){this.dispatchEvent({type:"dispose"})}}class fd extends sh{constructor(e=1,t=1,n={}){super(e,t,n),this.isWebGLRenderTarget=!0}}class Py extends yo{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=Cs,this.minFilter=Cs,this.wrapR=So,this.generateMipmaps=!1,this.flipY=!1,this.unpackAlignment=1,this.layerUpdates=new Set}addLayerUpdate(e){this.layerUpdates.add(e)}clearLayerUpdates(){this.layerUpdates.clear()}}class Que extends null{constructor(e=1,t=1,n=1,i={}){super(e,t,i),this.isWebGLArrayRenderTarget=!0,this.depth=n,this.texture=new Py(null,e,t,n),this._setTextureOptions(i),this.texture.isRenderTargetTexture=!0}}class MC extends yo{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=Cs,this.minFilter=Cs,this.wrapR=So,this.generateMipmaps=!1,this.flipY=!1,this.unpackAlignment=1}}class Zue extends null{constructor(e=1,t=1,n=1,i={}){super(e,t,i),this.isWebGL3DRenderTarget=!0,this.depth=n,this.texture=new MC(null,e,t,n),this._setTextureOptions(i),this.texture.isRenderTargetTexture=!0}}class xl{constructor(e=new J(1/0,1/0,1/0),t=new J(-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(hd.fromArray(e,t));return this}setFromBufferAttribute(e){this.makeEmpty();for(let t=0,n=e.count;t<n;t++)this.expandByPoint(hd.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=hd.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(n!==void 0){const s=n.getAttribute("position");if(t===!0&&s!==void 0&&e.isInstancedMesh!==!0)for(let a=0,o=s.count;a<o;a++)e.isMesh===!0?e.getVertexPosition(a,hd):hd.fromBufferAttribute(s,a),hd.applyMatrix4(e.matrixWorld),this.expandByPoint(hd);else e.boundingBox!==void 0?(e.boundingBox===null&&e.computeBoundingBox(),By.copy(e.boundingBox)):(n.boundingBox===null&&n.computeBoundingBox(),By.copy(n.boundingBox)),By.applyMatrix4(e.matrixWorld),this.union(By)}const i=e.children;for(let s=0,a=i.length;s<a;s++)this.expandByObject(i[s],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,hd),hd.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(D0),My.subVectors(this.max,D0),Mv.subVectors(e.a,D0),Sv.subVectors(e.b,D0),Dv.subVectors(e.c,D0),Cp.subVectors(Sv,Mv),Pp.subVectors(Dv,Sv),zm.subVectors(Mv,Dv);let t=[0,-Cp.z,Cp.y,0,-Pp.z,Pp.y,0,-zm.z,zm.y,Cp.z,0,-Cp.x,Pp.z,0,-Pp.x,zm.z,0,-zm.x,-Cp.y,Cp.x,0,-Pp.y,Pp.x,0,-zm.y,zm.x,0];return!SC(t,Mv,Sv,Dv,My)||(t=[1,0,0,0,1,0,0,0,1],!SC(t,Mv,Sv,Dv,My))?!1:(Sy.crossVectors(Cp,Pp),t=[Sy.x,Sy.y,Sy.z],SC(t,Mv,Sv,Dv,My))}clampPoint(e,t){return t.copy(e).clamp(this.min,this.max)}distanceToPoint(e){return this.clampPoint(e,hd).distanceTo(e)}getBoundingSphere(e){return this.isEmpty()?e.makeEmpty():(this.getCenter(e.center),e.radius=this.getSize(hd).length()*.5),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()?this:(ah[0].set(this.min.x,this.min.y,this.min.z).applyMatrix4(e),ah[1].set(this.min.x,this.min.y,this.max.z).applyMatrix4(e),ah[2].set(this.min.x,this.max.y,this.min.z).applyMatrix4(e),ah[3].set(this.min.x,this.max.y,this.max.z).applyMatrix4(e),ah[4].set(this.max.x,this.min.y,this.min.z).applyMatrix4(e),ah[5].set(this.max.x,this.min.y,this.max.z).applyMatrix4(e),ah[6].set(this.max.x,this.max.y,this.min.z).applyMatrix4(e),ah[7].set(this.max.x,this.max.y,this.max.z).applyMatrix4(e),this.setFromPoints(ah),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 ah=[new J,new J,new J,new J,new J,new J,new J,new J],hd=new J,By=new xl,Mv=new J,Sv=new J,Dv=new J,Cp=new J,Pp=new J,zm=new J,D0=new J,My=new J,Sy=new J,Hm=new J;function SC(r,e,t,n,i){for(let s=0,a=r.length-3;s<=a;s+=3){Hm.fromArray(r,s);const o=i.x*Math.abs(Hm.x)+i.y*Math.abs(Hm.y)+i.z*Math.abs(Hm.z),l=e.dot(Hm),u=t.dot(Hm),c=n.dot(Hm);if(Math.max(-Math.max(l,u,c),Math.min(l,u,c))>o)return!1}return!0}const pR=new xl,T0=new J,DC=new J;class yl{constructor(e=new J,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;t!==void 0?n.copy(t):pR.setFromPoints(e).getCenter(n);let i=0;for(let s=0,a=e.length;s<a;s++)i=Math.max(i,n.distanceToSquared(e[s]));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;T0.subVectors(e,this.center);const t=T0.lengthSq();if(t>this.radius*this.radius){const n=Math.sqrt(t),i=(n-this.radius)*.5;this.center.addScaledVector(T0,i/n),this.radius+=i}return this}union(e){return e.isEmpty()?this:this.isEmpty()?(this.copy(e),this):(this.center.equals(e.center)===!0?this.radius=Math.max(this.radius,e.radius):(DC.subVectors(e.center,this.center).setLength(e.radius),this.expandByPoint(T0.copy(e.center).add(DC)),this.expandByPoint(T0.copy(e.center).sub(DC))),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 oh=new J,TC=new J,Dy=new J,Bp=new J,IC=new J,Ty=new J,NC=new J;class Tv{constructor(e=new J,t=new J(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,oh)),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=oh.subVectors(e,this.origin).dot(this.direction);return t<0?this.origin.distanceToSquared(e):(oh.copy(this.origin).addScaledVector(this.direction,t),oh.distanceToSquared(e))}distanceSqToSegment(e,t,n,i){TC.copy(e).add(t).multiplyScalar(.5),Dy.copy(t).sub(e).normalize(),Bp.copy(this.origin).sub(TC);const s=e.distanceTo(t)*.5,a=-this.direction.dot(Dy),o=Bp.dot(this.direction),l=-Bp.dot(Dy),u=Bp.lengthSq(),c=Math.abs(1-a*a);let d,f,h,p;if(c>0)if(d=a*l-o,f=a*o-l,p=s*c,d>=0)if(f>=-p)if(f<=p){const x=1/c;d*=x,f*=x,h=d*(d+a*f+2*o)+f*(a*d+f+2*l)+u}else f=s,d=Math.max(0,-(a*f+o)),h=-d*d+f*(f+2*l)+u;else f=-s,d=Math.max(0,-(a*f+o)),h=-d*d+f*(f+2*l)+u;else f<=-p?(d=Math.max(0,-(-a*s+o)),f=d>0?-s:Math.min(Math.max(-s,-l),s),h=-d*d+f*(f+2*l)+u):f<=p?(d=0,f=Math.min(Math.max(-s,-l),s),h=f*(f+2*l)+u):(d=Math.max(0,-(a*s+o)),f=d>0?s:Math.min(Math.max(-s,-l),s),h=-d*d+f*(f+2*l)+u);else f=a>0?-s:s,d=Math.max(0,-(a*f+o)),h=-d*d+f*(f+2*l)+u;return n&&n.copy(this.origin).addScaledVector(this.direction,d),i&&i.copy(TC).addScaledVector(Dy,f),h}intersectSphere(e,t){oh.subVectors(e.center,this.origin);const n=oh.dot(this.direction),i=oh.dot(oh)-n*n,s=e.radius*e.radius;if(i>s)return null;const a=Math.sqrt(s-i),o=n-a,l=n+a;return l<0?null:o<0?this.at(l,t):this.at(o,t)}intersectsSphere(e){return e.radius<0?!1:this.distanceSqToPoint(e.center)<=e.radius*e.radius}distanceToPlane(e){const t=e.normal.dot(this.direction);if(t===0)return e.distanceToPoint(this.origin)===0?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 n===null?null:this.at(n,t)}intersectsPlane(e){const t=e.distanceToPoint(this.origin);return t===0||e.normal.dot(this.direction)*t<0}intersectBox(e,t){let n,i,s,a,o,l;const u=1/this.direction.x,c=1/this.direction.y,d=1/this.direction.z,f=this.origin;return u>=0?(n=(e.min.x-f.x)*u,i=(e.max.x-f.x)*u):(n=(e.max.x-f.x)*u,i=(e.min.x-f.x)*u),c>=0?(s=(e.min.y-f.y)*c,a=(e.max.y-f.y)*c):(s=(e.max.y-f.y)*c,a=(e.min.y-f.y)*c),n>a||s>i||((s>n||isNaN(n))&&(n=s),(a<i||isNaN(i))&&(i=a),d>=0?(o=(e.min.z-f.z)*d,l=(e.max.z-f.z)*d):(o=(e.max.z-f.z)*d,l=(e.min.z-f.z)*d),n>l||o>i)||((o>n||n!==n)&&(n=o),(l<i||i!==i)&&(i=l),i<0)?null:this.at(n>=0?n:i,t)}intersectsBox(e){return this.intersectBox(e,oh)!==null}intersectTriangle(e,t,n,i,s){IC.subVectors(t,e),Ty.subVectors(n,e),NC.crossVectors(IC,Ty);let a=this.direction.dot(NC),o;if(a>0){if(i)return null;o=1}else if(a<0)o=-1,a=-a;else return null;Bp.subVectors(this.origin,e);const l=o*this.direction.dot(Ty.crossVectors(Bp,Ty));if(l<0)return null;const u=o*this.direction.dot(IC.cross(Bp));if(u<0||l+u>a)return null;const c=-o*Bp.dot(NC);return c<0?null:this.at(c/a,s)}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 Cr{constructor(e,t,n,i,s,a,o,l,u,c,d,f,h,p,x,v){Cr.prototype.isMatrix4=!0,this.elements=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],e!==void 0&&this.set(e,t,n,i,s,a,o,l,u,c,d,f,h,p,x,v)}set(e,t,n,i,s,a,o,l,u,c,d,f,h,p,x,v){const m=this.elements;return m[0]=e,m[4]=t,m[8]=n,m[12]=i,m[1]=s,m[5]=a,m[9]=o,m[13]=l,m[2]=u,m[6]=c,m[10]=d,m[14]=f,m[3]=h,m[7]=p,m[11]=x,m[15]=v,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 Cr().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 this.determinant()===0?(e.set(1,0,0),t.set(0,1,0),n.set(0,0,1),this):(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){if(e.determinant()===0)return this.identity();const t=this.elements,n=e.elements,i=1/Iv.setFromMatrixColumn(e,0).length(),s=1/Iv.setFromMatrixColumn(e,1).length(),a=1/Iv.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]*s,t[5]=n[5]*s,t[6]=n[6]*s,t[7]=0,t[8]=n[8]*a,t[9]=n[9]*a,t[10]=n[10]*a,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,s=e.z,a=Math.cos(n),o=Math.sin(n),l=Math.cos(i),u=Math.sin(i),c=Math.cos(s),d=Math.sin(s);if(e.order==="XYZ"){const f=a*c,h=a*d,p=o*c,x=o*d;t[0]=l*c,t[4]=-l*d,t[8]=u,t[1]=h+p*u,t[5]=f-x*u,t[9]=-o*l,t[2]=x-f*u,t[6]=p+h*u,t[10]=a*l}else if(e.order==="YXZ"){const f=l*c,h=l*d,p=u*c,x=u*d;t[0]=f+x*o,t[4]=p*o-h,t[8]=a*u,t[1]=a*d,t[5]=a*c,t[9]=-o,t[2]=h*o-p,t[6]=x+f*o,t[10]=a*l}else if(e.order==="ZXY"){const f=l*c,h=l*d,p=u*c,x=u*d;t[0]=f-x*o,t[4]=-a*d,t[8]=p+h*o,t[1]=h+p*o,t[5]=a*c,t[9]=x-f*o,t[2]=-a*u,t[6]=o,t[10]=a*l}else if(e.order==="ZYX"){const f=a*c,h=a*d,p=o*c,x=o*d;t[0]=l*c,t[4]=p*u-h,t[8]=f*u+x,t[1]=l*d,t[5]=x*u+f,t[9]=h*u-p,t[2]=-u,t[6]=o*l,t[10]=a*l}else if(e.order==="YZX"){const f=a*l,h=a*u,p=o*l,x=o*u;t[0]=l*c,t[4]=x-f*d,t[8]=p*d+h,t[1]=d,t[5]=a*c,t[9]=-o*c,t[2]=-u*c,t[6]=h*d+p,t[10]=f-x*d}else if(e.order==="XZY"){const f=a*l,h=a*u,p=o*l,x=o*u;t[0]=l*c,t[4]=-d,t[8]=u*c,t[1]=f*d+x,t[5]=a*c,t[9]=h*d-p,t[2]=p*d-h,t[6]=o*c,t[10]=x*d+f}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(mR,e,gR)}lookAt(e,t,n){const i=this.elements;return Ku.subVectors(e,t),Ku.lengthSq()===0&&(Ku.z=1),Ku.normalize(),Mp.crossVectors(n,Ku),Mp.lengthSq()===0&&(Math.abs(n.z)===1?Ku.x+=1e-4:Ku.z+=1e-4,Ku.normalize(),Mp.crossVectors(n,Ku)),Mp.normalize(),Iy.crossVectors(Ku,Mp),i[0]=Mp.x,i[4]=Iy.x,i[8]=Ku.x,i[1]=Mp.y,i[5]=Iy.y,i[9]=Ku.y,i[2]=Mp.z,i[6]=Iy.z,i[10]=Ku.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,s=this.elements,a=n[0],o=n[4],l=n[8],u=n[12],c=n[1],d=n[5],f=n[9],h=n[13],p=n[2],x=n[6],v=n[10],m=n[14],C=n[3],w=n[7],P=n[11],B=n[15],S=i[0],I=i[4],N=i[8],T=i[12],R=i[1],D=i[5],j=i[9],q=i[13],Q=i[2],re=i[6],de=i[10],we=i[14],ge=i[3],Y=i[7],Se=i[11],W=i[15];return s[0]=a*S+o*R+l*Q+u*ge,s[4]=a*I+o*D+l*re+u*Y,s[8]=a*N+o*j+l*de+u*Se,s[12]=a*T+o*q+l*we+u*W,s[1]=c*S+d*R+f*Q+h*ge,s[5]=c*I+d*D+f*re+h*Y,s[9]=c*N+d*j+f*de+h*Se,s[13]=c*T+d*q+f*we+h*W,s[2]=p*S+x*R+v*Q+m*ge,s[6]=p*I+x*D+v*re+m*Y,s[10]=p*N+x*j+v*de+m*Se,s[14]=p*T+x*q+v*we+m*W,s[3]=C*S+w*R+P*Q+B*ge,s[7]=C*I+w*D+P*re+B*Y,s[11]=C*N+w*j+P*de+B*Se,s[15]=C*T+w*q+P*we+B*W,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],s=e[12],a=e[1],o=e[5],l=e[9],u=e[13],c=e[2],d=e[6],f=e[10],h=e[14],p=e[3],x=e[7],v=e[11],m=e[15],C=l*h-u*f,w=o*h-u*d,P=o*f-l*d,B=a*h-u*c,S=a*f-l*c,I=a*d-o*c;return t*(x*C-v*w+m*P)-n*(p*C-v*B+m*S)+i*(p*w-x*B+m*I)-s*(p*P-x*S+v*I)}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],s=e[3],a=e[4],o=e[5],l=e[6],u=e[7],c=e[8],d=e[9],f=e[10],h=e[11],p=e[12],x=e[13],v=e[14],m=e[15],C=d*v*u-x*f*u+x*l*h-o*v*h-d*l*m+o*f*m,w=p*f*u-c*v*u-p*l*h+a*v*h+c*l*m-a*f*m,P=c*x*u-p*d*u+p*o*h-a*x*h-c*o*m+a*d*m,B=p*d*l-c*x*l-p*o*f+a*x*f+c*o*v-a*d*v,S=t*C+n*w+i*P+s*B;if(S===0)return this.set(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0);const I=1/S;return e[0]=C*I,e[1]=(x*f*s-d*v*s-x*i*h+n*v*h+d*i*m-n*f*m)*I,e[2]=(o*v*s-x*l*s+x*i*u-n*v*u-o*i*m+n*l*m)*I,e[3]=(d*l*s-o*f*s-d*i*u+n*f*u+o*i*h-n*l*h)*I,e[4]=w*I,e[5]=(c*v*s-p*f*s+p*i*h-t*v*h-c*i*m+t*f*m)*I,e[6]=(p*l*s-a*v*s-p*i*u+t*v*u+a*i*m-t*l*m)*I,e[7]=(a*f*s-c*l*s+c*i*u-t*f*u-a*i*h+t*l*h)*I,e[8]=P*I,e[9]=(p*d*s-c*x*s-p*n*h+t*x*h+c*n*m-t*d*m)*I,e[10]=(a*x*s-p*o*s+p*n*u-t*x*u-a*n*m+t*o*m)*I,e[11]=(c*o*s-a*d*s-c*n*u+t*d*u+a*n*h-t*o*h)*I,e[12]=B*I,e[13]=(c*x*i-p*d*i+p*n*f-t*x*f-c*n*v+t*d*v)*I,e[14]=(p*o*i-a*x*i-p*n*l+t*x*l+a*n*v-t*o*v)*I,e[15]=(a*d*i-c*o*i+c*n*l-t*d*l-a*n*f+t*o*f)*I,this}scale(e){const t=this.elements,n=e.x,i=e.y,s=e.z;return t[0]*=n,t[4]*=i,t[8]*=s,t[1]*=n,t[5]*=i,t[9]*=s,t[2]*=n,t[6]*=i,t[10]*=s,t[3]*=n,t[7]*=i,t[11]*=s,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),s=1-n,a=e.x,o=e.y,l=e.z,u=s*a,c=s*o;return this.set(u*a+n,u*o-i*l,u*l+i*o,0,u*o+i*l,c*o+n,c*l-i*a,0,u*l-i*o,c*l+i*a,s*l*l+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,s,a){return this.set(1,n,s,0,e,1,a,0,t,i,1,0,0,0,0,1),this}compose(e,t,n){const i=this.elements,s=t._x,a=t._y,o=t._z,l=t._w,u=s+s,c=a+a,d=o+o,f=s*u,h=s*c,p=s*d,x=a*c,v=a*d,m=o*d,C=l*u,w=l*c,P=l*d,B=n.x,S=n.y,I=n.z;return i[0]=(1-(x+m))*B,i[1]=(h+P)*B,i[2]=(p-w)*B,i[3]=0,i[4]=(h-P)*S,i[5]=(1-(f+m))*S,i[6]=(v+C)*S,i[7]=0,i[8]=(p+w)*I,i[9]=(v-C)*I,i[10]=(1-(f+x))*I,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;if(e.x=i[12],e.y=i[13],e.z=i[14],this.determinant()===0)return n.set(1,1,1),t.identity(),this;let s=Iv.set(i[0],i[1],i[2]).length();const a=Iv.set(i[4],i[5],i[6]).length(),o=Iv.set(i[8],i[9],i[10]).length();this.determinant()<0&&(s=-s),pd.copy(this);const u=1/s,c=1/a,d=1/o;return pd.elements[0]*=u,pd.elements[1]*=u,pd.elements[2]*=u,pd.elements[4]*=c,pd.elements[5]*=c,pd.elements[6]*=c,pd.elements[8]*=d,pd.elements[9]*=d,pd.elements[10]*=d,t.setFromRotationMatrix(pd),n.x=s,n.y=a,n.z=o,this}makePerspective(e,t,n,i,s,a,o=Gt,l=!1){const u=this.elements,c=2*s/(t-e),d=2*s/(n-i),f=(t+e)/(t-e),h=(n+i)/(n-i);let p,x;if(l)p=s/(a-s),x=a*s/(a-s);else if(o===Gt)p=-(a+s)/(a-s),x=-2*a*s/(a-s);else if(o===gn)p=-a/(a-s),x=-a*s/(a-s);else throw new Error("THREE.Matrix4.makePerspective(): Invalid coordinate system: "+o);return u[0]=c,u[4]=0,u[8]=f,u[12]=0,u[1]=0,u[5]=d,u[9]=h,u[13]=0,u[2]=0,u[6]=0,u[10]=p,u[14]=x,u[3]=0,u[7]=0,u[11]=-1,u[15]=0,this}makeOrthographic(e,t,n,i,s,a,o=Gt,l=!1){const u=this.elements,c=2/(t-e),d=2/(n-i),f=-(t+e)/(t-e),h=-(n+i)/(n-i);let p,x;if(l)p=1/(a-s),x=a/(a-s);else if(o===Gt)p=-2/(a-s),x=-(a+s)/(a-s);else if(o===gn)p=-1/(a-s),x=-s/(a-s);else throw new Error("THREE.Matrix4.makeOrthographic(): Invalid coordinate system: "+o);return u[0]=c,u[4]=0,u[8]=0,u[12]=f,u[1]=0,u[5]=d,u[9]=0,u[13]=h,u[2]=0,u[6]=0,u[10]=p,u[14]=x,u[3]=0,u[7]=0,u[11]=0,u[15]=1,this}equals(e){const t=this.elements,n=e.elements;for(let i=0;i<16;i++)if(t[i]!==n[i])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 Iv=new J,pd=new Cr,mR=new J(0,0,0),gR=new J(1,1,1),Mp=new J,Iy=new J,Ku=new J,PS=new Cr,BS=new Wo;class bu{constructor(e=0,t=0,n=0,i=bu.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,s=i[0],a=i[4],o=i[8],l=i[1],u=i[5],c=i[9],d=i[2],f=i[6],h=i[10];switch(t){case"XYZ":this._y=Math.asin(ii(o,-1,1)),Math.abs(o)<.9999999?(this._x=Math.atan2(-c,h),this._z=Math.atan2(-a,s)):(this._x=Math.atan2(f,u),this._z=0);break;case"YXZ":this._x=Math.asin(-ii(c,-1,1)),Math.abs(c)<.9999999?(this._y=Math.atan2(o,h),this._z=Math.atan2(l,u)):(this._y=Math.atan2(-d,s),this._z=0);break;case"ZXY":this._x=Math.asin(ii(f,-1,1)),Math.abs(f)<.9999999?(this._y=Math.atan2(-d,h),this._z=Math.atan2(-a,u)):(this._y=0,this._z=Math.atan2(l,s));break;case"ZYX":this._y=Math.asin(-ii(d,-1,1)),Math.abs(d)<.9999999?(this._x=Math.atan2(f,h),this._z=Math.atan2(l,s)):(this._x=0,this._z=Math.atan2(-a,u));break;case"YZX":this._z=Math.asin(ii(l,-1,1)),Math.abs(l)<.9999999?(this._x=Math.atan2(-c,u),this._y=Math.atan2(-d,s)):(this._x=0,this._y=Math.atan2(o,h));break;case"XZY":this._z=Math.asin(-ii(a,-1,1)),Math.abs(a)<.9999999?(this._x=Math.atan2(f,u),this._y=Math.atan2(o,s)):(this._x=Math.atan2(-c,h),this._y=0);break;default:ze("Euler: .setFromRotationMatrix() encountered an unknown order: "+t)}return this._order=t,n===!0&&this._onChangeCallback(),this}setFromQuaternion(e,t,n){return PS.makeRotationFromQuaternion(e),this.setFromRotationMatrix(PS,t,n)}setFromVector3(e,t=this._order){return this.set(e.x,e.y,e.z,t)}reorder(e){return BS.setFromEuler(this),this.setFromQuaternion(BS,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],e[3]!==void 0&&(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}}bu.DEFAULT_ORDER="XYZ";class FC{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(this.mask&e.mask)!==0}isEnabled(e){return(this.mask&(1<<e|0))!==0}}let vR=0;const MS=new J,Nv=new Wo,lh=new Cr,Ny=new J,I0=new J,AR=new J,xR=new Wo,SS=new J(1,0,0),DS=new J(0,1,0),TS=new J(0,0,1),IS={type:"added"},yR={type:"removed"},Fv={type:"childadded",child:null},RC={type:"childremoved",child:null};class so extends Go{constructor(){super(),this.isObject3D=!0,Object.defineProperty(this,"id",{value:vR++}),this.uuid=Ga(),this.name="",this.type="Object3D",this.parent=null,this.children=[],this.up=so.DEFAULT_UP.clone();const e=new J,t=new bu,n=new Wo,i=new J(1,1,1);function s(){n.setFromEuler(t,!1)}function a(){t.setFromQuaternion(n,void 0,!1)}t._onChange(s),n._onChange(a),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 Cr},normalMatrix:{value:new zi}}),this.matrix=new Cr,this.matrixWorld=new Cr,this.matrixAutoUpdate=so.DEFAULT_MATRIX_AUTO_UPDATE,this.matrixWorldAutoUpdate=so.DEFAULT_MATRIX_WORLD_AUTO_UPDATE,this.matrixWorldNeedsUpdate=!1,this.layers=new FC,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 Nv.setFromAxisAngle(e,t),this.quaternion.multiply(Nv),this}rotateOnWorldAxis(e,t){return Nv.setFromAxisAngle(e,t),this.quaternion.premultiply(Nv),this}rotateX(e){return this.rotateOnAxis(SS,e)}rotateY(e){return this.rotateOnAxis(DS,e)}rotateZ(e){return this.rotateOnAxis(TS,e)}translateOnAxis(e,t){return MS.copy(e).applyQuaternion(this.quaternion),this.position.add(MS.multiplyScalar(t)),this}translateX(e){return this.translateOnAxis(SS,e)}translateY(e){return this.translateOnAxis(DS,e)}translateZ(e){return this.translateOnAxis(TS,e)}localToWorld(e){return this.updateWorldMatrix(!0,!1),e.applyMatrix4(this.matrixWorld)}worldToLocal(e){return this.updateWorldMatrix(!0,!1),e.applyMatrix4(lh.copy(this.matrixWorld).invert())}lookAt(e,t,n){e.isVector3?Ny.copy(e):Ny.set(e,t,n);const i=this.parent;this.updateWorldMatrix(!0,!1),I0.setFromMatrixPosition(this.matrixWorld),this.isCamera||this.isLight?lh.lookAt(I0,Ny,this.up):lh.lookAt(Ny,I0,this.up),this.quaternion.setFromRotationMatrix(lh),i&&(lh.extractRotation(i.matrixWorld),Nv.setFromRotationMatrix(lh),this.quaternion.premultiply(Nv.invert()))}add(e){if(arguments.length>1){for(let t=0;t<arguments.length;t++)this.add(arguments[t]);return this}return e===this?(rt("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(IS),Fv.child=e,this.dispatchEvent(Fv),Fv.child=null):rt("Object3D.add: object not an instance of THREE.Object3D.",e),this)}remove(e){if(arguments.length>1){for(let n=0;n<arguments.length;n++)this.remove(arguments[n]);return this}const t=this.children.indexOf(e);return t!==-1&&(e.parent=null,this.children.splice(t,1),e.dispatchEvent(yR),RC.child=e,this.dispatchEvent(RC),RC.child=null),this}removeFromParent(){const e=this.parent;return e!==null&&e.remove(this),this}clear(){return this.remove(...this.children)}attach(e){return this.updateWorldMatrix(!0,!1),lh.copy(this.matrixWorld).invert(),e.parent!==null&&(e.parent.updateWorldMatrix(!0,!1),lh.multiply(e.parent.matrixWorld)),e.applyMatrix4(lh),e.removeFromParent(),e.parent=this,this.children.push(e),e.updateWorldMatrix(!1,!0),e.dispatchEvent(IS),Fv.child=e,this.dispatchEvent(Fv),Fv.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 a=this.children[n].getObjectByProperty(e,t);if(a!==void 0)return a}}getObjectsByProperty(e,t,n=[]){this[e]===t&&n.push(this);const i=this.children;for(let s=0,a=i.length;s<a;s++)i[s].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(I0,e,AR),e}getWorldScale(e){return this.updateWorldMatrix(!0,!1),this.matrixWorld.decompose(I0,xR,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(this.visible===!1)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;t!==null&&(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)&&(this.matrixWorldAutoUpdate===!0&&(this.parent===null?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(e===!0&&n!==null&&n.updateWorldMatrix(!0,!1),this.matrixAutoUpdate&&this.updateMatrix(),this.matrixWorldAutoUpdate===!0&&(this.parent===null?this.matrixWorld.copy(this.matrix):this.matrixWorld.multiplyMatrices(this.parent.matrixWorld,this.matrix)),t===!0){const i=this.children;for(let s=0,a=i.length;s<a;s++)i[s].updateWorldMatrix(!1,!0)}}toJSON(e){const t=e===void 0||typeof e=="string",n={};t&&(e={geometries:{},materials:{},textures:{},images:{},shapes:{},skeletons:{},animations:{},nodes:{}},n.metadata={version:4.7,type:"Object",generator:"Object3D.toJSON"});const i={};i.uuid=this.uuid,i.type=this.type,this.name!==""&&(i.name=this.name),this.castShadow===!0&&(i.castShadow=!0),this.receiveShadow===!0&&(i.receiveShadow=!0),this.visible===!1&&(i.visible=!1),this.frustumCulled===!1&&(i.frustumCulled=!1),this.renderOrder!==0&&(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(),this.matrixAutoUpdate===!1&&(i.matrixAutoUpdate=!1),this.isInstancedMesh&&(i.type="InstancedMesh",i.count=this.count,i.instanceMatrix=this.instanceMatrix.toJSON(),this.instanceColor!==null&&(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(o=>Gc(ba({},o),{boundingBox:o.boundingBox?o.boundingBox.toJSON():void 0,boundingSphere:o.boundingSphere?o.boundingSphere.toJSON():void 0})),i.instanceInfo=this._instanceInfo.map(o=>ba({},o)),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),this._colorsTexture!==null&&(i.colorsTexture=this._colorsTexture.toJSON(e)),this.boundingSphere!==null&&(i.boundingSphere=this.boundingSphere.toJSON()),this.boundingBox!==null&&(i.boundingBox=this.boundingBox.toJSON()));function s(o,l){return o[l.uuid]===void 0&&(o[l.uuid]=l.toJSON(e)),l.uuid}if(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&&this.environment.isRenderTargetTexture!==!0&&(i.environment=this.environment.toJSON(e).uuid);else if(this.isMesh||this.isLine||this.isPoints){i.geometry=s(e.geometries,this.geometry);const o=this.geometry.parameters;if(o!==void 0&&o.shapes!==void 0){const l=o.shapes;if(Array.isArray(l))for(let u=0,c=l.length;u<c;u++){const d=l[u];s(e.shapes,d)}else s(e.shapes,l)}}if(this.isSkinnedMesh&&(i.bindMode=this.bindMode,i.bindMatrix=this.bindMatrix.toArray(),this.skeleton!==void 0&&(s(e.skeletons,this.skeleton),i.skeleton=this.skeleton.uuid)),this.material!==void 0)if(Array.isArray(this.material)){const o=[];for(let l=0,u=this.material.length;l<u;l++)o.push(s(e.materials,this.material[l]));i.material=o}else i.material=s(e.materials,this.material);if(this.children.length>0){i.children=[];for(let o=0;o<this.children.length;o++)i.children.push(this.children[o].toJSON(e).object)}if(this.animations.length>0){i.animations=[];for(let o=0;o<this.animations.length;o++){const l=this.animations[o];i.animations.push(s(e.animations,l))}}if(t){const o=a(e.geometries),l=a(e.materials),u=a(e.textures),c=a(e.images),d=a(e.shapes),f=a(e.skeletons),h=a(e.animations),p=a(e.nodes);o.length>0&&(n.geometries=o),l.length>0&&(n.materials=l),u.length>0&&(n.textures=u),c.length>0&&(n.images=c),d.length>0&&(n.shapes=d),f.length>0&&(n.skeletons=f),h.length>0&&(n.animations=h),p.length>0&&(n.nodes=p)}return n.object=i,n;function a(o){const l=[];for(const u in o){const c=o[u];delete c.metadata,l.push(c)}return l}}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)),t===!0)for(let n=0;n<e.children.length;n++){const i=e.children[n];this.add(i.clone())}return this}}so.DEFAULT_UP=new J(0,1,0),so.DEFAULT_MATRIX_AUTO_UPDATE=!0,so.DEFAULT_MATRIX_WORLD_AUTO_UPDATE=!0;const md=new J,uh=new J,LC=new J,ch=new J,Rv=new J,Lv=new J,NS=new J,OC=new J,zC=new J,HC=new J,UC=new Ei,kC=new Ei,VC=new Ei;class qu{constructor(e=new J,t=new J,n=new J){this.a=e,this.b=t,this.c=n}static getNormal(e,t,n,i){i.subVectors(n,t),md.subVectors(e,t),i.cross(md);const s=i.lengthSq();return s>0?i.multiplyScalar(1/Math.sqrt(s)):i.set(0,0,0)}static getBarycoord(e,t,n,i,s){md.subVectors(i,t),uh.subVectors(n,t),LC.subVectors(e,t);const a=md.dot(md),o=md.dot(uh),l=md.dot(LC),u=uh.dot(uh),c=uh.dot(LC),d=a*u-o*o;if(d===0)return s.set(0,0,0),null;const f=1/d,h=(u*l-o*c)*f,p=(a*c-o*l)*f;return s.set(1-h-p,p,h)}static containsPoint(e,t,n,i){return this.getBarycoord(e,t,n,i,ch)===null?!1:ch.x>=0&&ch.y>=0&&ch.x+ch.y<=1}static getInterpolation(e,t,n,i,s,a,o,l){return this.getBarycoord(e,t,n,i,ch)===null?(l.x=0,l.y=0,"z"in l&&(l.z=0),"w"in l&&(l.w=0),null):(l.setScalar(0),l.addScaledVector(s,ch.x),l.addScaledVector(a,ch.y),l.addScaledVector(o,ch.z),l)}static getInterpolatedAttribute(e,t,n,i,s,a){return UC.setScalar(0),kC.setScalar(0),VC.setScalar(0),UC.fromBufferAttribute(e,t),kC.fromBufferAttribute(e,n),VC.fromBufferAttribute(e,i),a.setScalar(0),a.addScaledVector(UC,s.x),a.addScaledVector(kC,s.y),a.addScaledVector(VC,s.z),a}static isFrontFacing(e,t,n,i){return md.subVectors(n,t),uh.subVectors(e,t),md.cross(uh).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 md.subVectors(this.c,this.b),uh.subVectors(this.a,this.b),md.cross(uh).length()*.5}getMidpoint(e){return e.addVectors(this.a,this.b).add(this.c).multiplyScalar(1/3)}getNormal(e){return qu.getNormal(this.a,this.b,this.c,e)}getPlane(e){return e.setFromCoplanarPoints(this.a,this.b,this.c)}getBarycoord(e,t){return qu.getBarycoord(e,this.a,this.b,this.c,t)}getInterpolation(e,t,n,i,s){return qu.getInterpolation(e,this.a,this.b,this.c,t,n,i,s)}containsPoint(e){return qu.containsPoint(e,this.a,this.b,this.c)}isFrontFacing(e){return qu.isFrontFacing(this.a,this.b,this.c,e)}intersectsBox(e){return e.intersectsTriangle(this)}closestPointToPoint(e,t){const n=this.a,i=this.b,s=this.c;let a,o;Rv.subVectors(i,n),Lv.subVectors(s,n),OC.subVectors(e,n);const l=Rv.dot(OC),u=Lv.dot(OC);if(l<=0&&u<=0)return t.copy(n);zC.subVectors(e,i);const c=Rv.dot(zC),d=Lv.dot(zC);if(c>=0&&d<=c)return t.copy(i);const f=l*d-c*u;if(f<=0&&l>=0&&c<=0)return a=l/(l-c),t.copy(n).addScaledVector(Rv,a);HC.subVectors(e,s);const h=Rv.dot(HC),p=Lv.dot(HC);if(p>=0&&h<=p)return t.copy(s);const x=h*u-l*p;if(x<=0&&u>=0&&p<=0)return o=u/(u-p),t.copy(n).addScaledVector(Lv,o);const v=c*p-h*d;if(v<=0&&d-c>=0&&h-p>=0)return NS.subVectors(s,i),o=(d-c)/(d-c+(h-p)),t.copy(i).addScaledVector(NS,o);const m=1/(v+x+f);return a=x*m,o=f*m,t.copy(n).addScaledVector(Rv,a).addScaledVector(Lv,o)}equals(e){return e.a.equals(this.a)&&e.b.equals(this.b)&&e.c.equals(this.c)}}const FS={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},Sp={h:0,s:0,l:0},Fy={h:0,s:0,l:0};function jC(r,e,t){return t<0&&(t+=1),t>1&&(t-=1),t<1/6?r+(e-r)*6*t:t<1/2?e:t<2/3?r+(e-r)*6*(2/3-t):r}class Vn{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(t===void 0&&n===void 0){const i=e;i&&i.isColor?this.copy(i):typeof i=="number"?this.setHex(i):typeof i=="string"&&this.setStyle(i)}else this.setRGB(e,t,n);return this}setScalar(e){return this.r=e,this.g=e,this.b=e,this}setHex(e,t=nl){return e=Math.floor(e),this.r=(e>>16&255)/255,this.g=(e>>8&255)/255,this.b=(e&255)/255,$r.colorSpaceToWorking(this,t),this}setRGB(e,t,n,i=$r.workingColorSpace){return this.r=e,this.g=t,this.b=n,$r.colorSpaceToWorking(this,i),this}setHSL(e,t,n,i=$r.workingColorSpace){if(e=Ep(e,1),t=ii(t,0,1),n=ii(n,0,1),t===0)this.r=this.g=this.b=n;else{const s=n<=.5?n*(1+t):n+t-n*t,a=2*n-s;this.r=jC(a,s,e+1/3),this.g=jC(a,s,e),this.b=jC(a,s,e-1/3)}return $r.colorSpaceToWorking(this,i),this}setStyle(e,t=nl){function n(s){s!==void 0&&parseFloat(s)<1&&ze("Color: Alpha component of "+e+" will be ignored.")}let i;if(i=/^(\w+)\(([^\)]*)\)/.exec(e)){let s;const a=i[1],o=i[2];switch(a){case"rgb":case"rgba":if(s=/^\s*(\d+)\s*,\s*(\d+)\s*,\s*(\d+)\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec(o))return n(s[4]),this.setRGB(Math.min(255,parseInt(s[1],10))/255,Math.min(255,parseInt(s[2],10))/255,Math.min(255,parseInt(s[3],10))/255,t);if(s=/^\s*(\d+)\%\s*,\s*(\d+)\%\s*,\s*(\d+)\%\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec(o))return n(s[4]),this.setRGB(Math.min(100,parseInt(s[1],10))/100,Math.min(100,parseInt(s[2],10))/100,Math.min(100,parseInt(s[3],10))/100,t);break;case"hsl":case"hsla":if(s=/^\s*(\d*\.?\d+)\s*,\s*(\d*\.?\d+)\%\s*,\s*(\d*\.?\d+)\%\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec(o))return n(s[4]),this.setHSL(parseFloat(s[1])/360,parseFloat(s[2])/100,parseFloat(s[3])/100,t);break;default:ze("Color: Unknown color model "+e)}}else if(i=/^\#([A-Fa-f\d]+)$/.exec(e)){const s=i[1],a=s.length;if(a===3)return this.setRGB(parseInt(s.charAt(0),16)/15,parseInt(s.charAt(1),16)/15,parseInt(s.charAt(2),16)/15,t);if(a===6)return this.setHex(parseInt(s,16),t);ze("Color: Invalid hex color "+e)}else if(e&&e.length>0)return this.setColorName(e,t);return this}setColorName(e,t=nl){const n=FS[e.toLowerCase()];return n!==void 0?this.setHex(n,t):ze("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=ih(e.r),this.g=ih(e.g),this.b=ih(e.b),this}copyLinearToSRGB(e){return this.r=Pv(e.r),this.g=Pv(e.g),this.b=Pv(e.b),this}convertSRGBToLinear(){return this.copySRGBToLinear(this),this}convertLinearToSRGB(){return this.copyLinearToSRGB(this),this}getHex(e=nl){return $r.workingToColorSpace(Hl.copy(this),e),Math.round(ii(Hl.r*255,0,255))*65536+Math.round(ii(Hl.g*255,0,255))*256+Math.round(ii(Hl.b*255,0,255))}getHexString(e=nl){return("000000"+this.getHex(e).toString(16)).slice(-6)}getHSL(e,t=$r.workingColorSpace){$r.workingToColorSpace(Hl.copy(this),t);const n=Hl.r,i=Hl.g,s=Hl.b,a=Math.max(n,i,s),o=Math.min(n,i,s);let l,u;const c=(o+a)/2;if(o===a)l=0,u=0;else{const d=a-o;switch(u=c<=.5?d/(a+o):d/(2-a-o),a){case n:l=(i-s)/d+(i<s?6:0);break;case i:l=(s-n)/d+2;break;case s:l=(n-i)/d+4;break}l/=6}return e.h=l,e.s=u,e.l=c,e}getRGB(e,t=$r.workingColorSpace){return $r.workingToColorSpace(Hl.copy(this),t),e.r=Hl.r,e.g=Hl.g,e.b=Hl.b,e}getStyle(e=nl){$r.workingToColorSpace(Hl.copy(this),e);const t=Hl.r,n=Hl.g,i=Hl.b;return e!==nl?`color(${e} ${t.toFixed(3)} ${n.toFixed(3)} ${i.toFixed(3)})`:`rgb(${Math.round(t*255)},${Math.round(n*255)},${Math.round(i*255)})`}offsetHSL(e,t,n){return this.getHSL(Sp),this.setHSL(Sp.h+e,Sp.s+t,Sp.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(Sp),e.getHSL(Fy);const n=of(Sp.h,Fy.h,t),i=of(Sp.s,Fy.s,t),s=of(Sp.l,Fy.l,t);return this.setHSL(n,i,s),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,s=e.elements;return this.r=s[0]*t+s[3]*n+s[6]*i,this.g=s[1]*t+s[4]*n+s[7]*i,this.b=s[2]*t+s[5]*n+s[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 Hl=new Vn;Vn.NAMES=FS;let bR=0;class bl extends Go{constructor(){super(),this.isMaterial=!0,Object.defineProperty(this,"id",{value:bR++}),this.uuid=Ga(),this.name="",this.type="Material",this.blending=Vo,this.side=ja,this.vertexColors=!1,this.opacity=1,this.transparent=!1,this.alphaHash=!1,this.blendSrc=Qu,this.blendDst=gl,this.blendEquation=io,this.blendSrcAlpha=null,this.blendDstAlpha=null,this.blendEquationAlpha=null,this.blendColor=new Vn(0,0,0),this.blendAlpha=0,this.depthFunc=xu,this.depthTest=!0,this.depthWrite=!0,this.stencilWriteMask=255,this.stencilFunc=E0,this.stencilRef=0,this.stencilFuncMask=255,this.stencilFail=rh,this.stencilZFail=rh,this.stencilZPass=rh,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(e!==void 0)for(const t in e){const n=e[t];if(n===void 0){ze(`Material: parameter '${t}' has value of undefined.`);continue}const i=this[t];if(i===void 0){ze(`Material: '${t}' is not a property of THREE.${this.type}.`);continue}i&&i.isColor?i.set(n):i&&i.isVector3&&n&&n.isVector3?i.copy(n):this[t]=n}}toJSON(e){const t=e===void 0||typeof e=="string";t&&(e={textures:{},images:{}});const n={metadata:{version:4.7,type:"Material",generator:"Material.toJSON"}};n.uuid=this.uuid,n.type=this.type,this.name!==""&&(n.name=this.name),this.color&&this.color.isColor&&(n.color=this.color.getHex()),this.roughness!==void 0&&(n.roughness=this.roughness),this.metalness!==void 0&&(n.metalness=this.metalness),this.sheen!==void 0&&(n.sheen=this.sheen),this.sheenColor&&this.sheenColor.isColor&&(n.sheenColor=this.sheenColor.getHex()),this.sheenRoughness!==void 0&&(n.sheenRoughness=this.sheenRoughness),this.emissive&&this.emissive.isColor&&(n.emissive=this.emissive.getHex()),this.emissiveIntensity!==void 0&&this.emissiveIntensity!==1&&(n.emissiveIntensity=this.emissiveIntensity),this.specular&&this.specular.isColor&&(n.specular=this.specular.getHex()),this.specularIntensity!==void 0&&(n.specularIntensity=this.specularIntensity),this.specularColor&&this.specularColor.isColor&&(n.specularColor=this.specularColor.getHex()),this.shininess!==void 0&&(n.shininess=this.shininess),this.clearcoat!==void 0&&(n.clearcoat=this.clearcoat),this.clearcoatRoughness!==void 0&&(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),this.dispersion!==void 0&&(n.dispersion=this.dispersion),this.iridescence!==void 0&&(n.iridescence=this.iridescence),this.iridescenceIOR!==void 0&&(n.iridescenceIOR=this.iridescenceIOR),this.iridescenceThicknessRange!==void 0&&(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),this.anisotropy!==void 0&&(n.anisotropy=this.anisotropy),this.anisotropyRotation!==void 0&&(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,this.combine!==void 0&&(n.combine=this.combine)),this.envMapRotation!==void 0&&(n.envMapRotation=this.envMapRotation.toArray()),this.envMapIntensity!==void 0&&(n.envMapIntensity=this.envMapIntensity),this.reflectivity!==void 0&&(n.reflectivity=this.reflectivity),this.refractionRatio!==void 0&&(n.refractionRatio=this.refractionRatio),this.gradientMap&&this.gradientMap.isTexture&&(n.gradientMap=this.gradientMap.toJSON(e).uuid),this.transmission!==void 0&&(n.transmission=this.transmission),this.transmissionMap&&this.transmissionMap.isTexture&&(n.transmissionMap=this.transmissionMap.toJSON(e).uuid),this.thickness!==void 0&&(n.thickness=this.thickness),this.thicknessMap&&this.thicknessMap.isTexture&&(n.thicknessMap=this.thicknessMap.toJSON(e).uuid),this.attenuationDistance!==void 0&&this.attenuationDistance!==1/0&&(n.attenuationDistance=this.attenuationDistance),this.attenuationColor!==void 0&&(n.attenuationColor=this.attenuationColor.getHex()),this.size!==void 0&&(n.size=this.size),this.shadowSide!==null&&(n.shadowSide=this.shadowSide),this.sizeAttenuation!==void 0&&(n.sizeAttenuation=this.sizeAttenuation),this.blending!==Vo&&(n.blending=this.blending),this.side!==ja&&(n.side=this.side),this.vertexColors===!0&&(n.vertexColors=!0),this.opacity<1&&(n.opacity=this.opacity),this.transparent===!0&&(n.transparent=!0),this.blendSrc!==Qu&&(n.blendSrc=this.blendSrc),this.blendDst!==gl&&(n.blendDst=this.blendDst),this.blendEquation!==io&&(n.blendEquation=this.blendEquation),this.blendSrcAlpha!==null&&(n.blendSrcAlpha=this.blendSrcAlpha),this.blendDstAlpha!==null&&(n.blendDstAlpha=this.blendDstAlpha),this.blendEquationAlpha!==null&&(n.blendEquationAlpha=this.blendEquationAlpha),this.blendColor&&this.blendColor.isColor&&(n.blendColor=this.blendColor.getHex()),this.blendAlpha!==0&&(n.blendAlpha=this.blendAlpha),this.depthFunc!==xu&&(n.depthFunc=this.depthFunc),this.depthTest===!1&&(n.depthTest=this.depthTest),this.depthWrite===!1&&(n.depthWrite=this.depthWrite),this.colorWrite===!1&&(n.colorWrite=this.colorWrite),this.stencilWriteMask!==255&&(n.stencilWriteMask=this.stencilWriteMask),this.stencilFunc!==E0&&(n.stencilFunc=this.stencilFunc),this.stencilRef!==0&&(n.stencilRef=this.stencilRef),this.stencilFuncMask!==255&&(n.stencilFuncMask=this.stencilFuncMask),this.stencilFail!==rh&&(n.stencilFail=this.stencilFail),this.stencilZFail!==rh&&(n.stencilZFail=this.stencilZFail),this.stencilZPass!==rh&&(n.stencilZPass=this.stencilZPass),this.stencilWrite===!0&&(n.stencilWrite=this.stencilWrite),this.rotation!==void 0&&this.rotation!==0&&(n.rotation=this.rotation),this.polygonOffset===!0&&(n.polygonOffset=!0),this.polygonOffsetFactor!==0&&(n.polygonOffsetFactor=this.polygonOffsetFactor),this.polygonOffsetUnits!==0&&(n.polygonOffsetUnits=this.polygonOffsetUnits),this.linewidth!==void 0&&this.linewidth!==1&&(n.linewidth=this.linewidth),this.dashSize!==void 0&&(n.dashSize=this.dashSize),this.gapSize!==void 0&&(n.gapSize=this.gapSize),this.scale!==void 0&&(n.scale=this.scale),this.dithering===!0&&(n.dithering=!0),this.alphaTest>0&&(n.alphaTest=this.alphaTest),this.alphaHash===!0&&(n.alphaHash=!0),this.alphaToCoverage===!0&&(n.alphaToCoverage=!0),this.premultipliedAlpha===!0&&(n.premultipliedAlpha=!0),this.forceSinglePass===!0&&(n.forceSinglePass=!0),this.allowOverride===!1&&(n.allowOverride=!1),this.wireframe===!0&&(n.wireframe=!0),this.wireframeLinewidth>1&&(n.wireframeLinewidth=this.wireframeLinewidth),this.wireframeLinecap!=="round"&&(n.wireframeLinecap=this.wireframeLinecap),this.wireframeLinejoin!=="round"&&(n.wireframeLinejoin=this.wireframeLinejoin),this.flatShading===!0&&(n.flatShading=!0),this.visible===!1&&(n.visible=!1),this.toneMapped===!1&&(n.toneMapped=!1),this.fog===!1&&(n.fog=!1),Object.keys(this.userData).length>0&&(n.userData=this.userData);function i(s){const a=[];for(const o in s){const l=s[o];delete l.metadata,a.push(l)}return a}if(t){const s=i(e.textures),a=i(e.images);s.length>0&&(n.textures=s),a.length>0&&(n.images=a)}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(t!==null){const i=t.length;n=new Array(i);for(let s=0;s!==i;++s)n[s]=t[s].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.allowOverride=e.allowOverride,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){e===!0&&this.version++}}class rl extends bl{constructor(e){super(),this.isMeshBasicMaterial=!0,this.type="MeshBasicMaterial",this.color=new Vn(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 bu,this.combine=Zd,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 dh=ER();function ER(){const r=new ArrayBuffer(4),e=new Float32Array(r),t=new Uint32Array(r),n=new Uint32Array(512),i=new Uint32Array(512);for(let l=0;l<256;++l){const u=l-127;u<-27?(n[l]=0,n[l|256]=32768,i[l]=24,i[l|256]=24):u<-14?(n[l]=1024>>-u-14,n[l|256]=1024>>-u-14|32768,i[l]=-u-1,i[l|256]=-u-1):u<=15?(n[l]=u+15<<10,n[l|256]=u+15<<10|32768,i[l]=13,i[l|256]=13):u<128?(n[l]=31744,n[l|256]=64512,i[l]=24,i[l|256]=24):(n[l]=31744,n[l|256]=64512,i[l]=13,i[l|256]=13)}const s=new Uint32Array(2048),a=new Uint32Array(64),o=new Uint32Array(64);for(let l=1;l<1024;++l){let u=l<<13,c=0;for(;!(u&8388608);)u<<=1,c-=8388608;u&=-8388609,c+=947912704,s[l]=u|c}for(let l=1024;l<2048;++l)s[l]=939524096+(l-1024<<13);for(let l=1;l<31;++l)a[l]=l<<23;a[31]=1199570944,a[32]=2147483648;for(let l=33;l<63;++l)a[l]=2147483648+(l-32<<23);a[63]=3347054592;for(let l=1;l<64;++l)l!==32&&(o[l]=1024);return{floatView:e,uint32View:t,baseTable:n,shiftTable:i,mantissaTable:s,exponentTable:a,offsetTable:o}}function Eu(r){Math.abs(r)>65504&&ze("DataUtils.toHalfFloat(): Value out of range."),r=ii(r,-65504,65504),dh.floatView[0]=r;const e=dh.uint32View[0],t=e>>23&511;return dh.baseTable[t]+((e&8388607)>>dh.shiftTable[t])}function N0(r){const e=r>>10;return dh.uint32View[0]=dh.mantissaTable[dh.offsetTable[e]+(r&1023)]+dh.exponentTable[e],dh.floatView[0]}class Yue{static toHalfFloat(e){return Eu(e)}static fromHalfFloat(e){return N0(e)}}const Io=new J,Ry=new ct;let wR=0;class ga{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:wR++}),this.name="",this.array=e,this.itemSize=t,this.count=e!==void 0?e.length/t:0,this.normalized=n,this.usage=U,this.updateRanges=[],this.gpuType=ha,this.version=0}onUploadCallback(){}set needsUpdate(e){e===!0&&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,s=this.itemSize;i<s;i++)this.array[e+i]=t.array[n+i];return this}copyArray(e){return this.array.set(e),this}applyMatrix3(e){if(this.itemSize===2)for(let t=0,n=this.count;t<n;t++)Ry.fromBufferAttribute(this,t),Ry.applyMatrix3(e),this.setXY(t,Ry.x,Ry.y);else if(this.itemSize===3)for(let t=0,n=this.count;t<n;t++)Io.fromBufferAttribute(this,t),Io.applyMatrix3(e),this.setXYZ(t,Io.x,Io.y,Io.z);return this}applyMatrix4(e){for(let t=0,n=this.count;t<n;t++)Io.fromBufferAttribute(this,t),Io.applyMatrix4(e),this.setXYZ(t,Io.x,Io.y,Io.z);return this}applyNormalMatrix(e){for(let t=0,n=this.count;t<n;t++)Io.fromBufferAttribute(this,t),Io.applyNormalMatrix(e),this.setXYZ(t,Io.x,Io.y,Io.z);return this}transformDirection(e){for(let t=0,n=this.count;t<n;t++)Io.fromBufferAttribute(this,t),Io.transformDirection(e),this.setXYZ(t,Io.x,Io.y,Io.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=ru(n,this.array)),n}setComponent(e,t,n){return this.normalized&&(n=$i(n,this.array)),this.array[e*this.itemSize+t]=n,this}getX(e){let t=this.array[e*this.itemSize];return this.normalized&&(t=ru(t,this.array)),t}setX(e,t){return this.normalized&&(t=$i(t,this.array)),this.array[e*this.itemSize]=t,this}getY(e){let t=this.array[e*this.itemSize+1];return this.normalized&&(t=ru(t,this.array)),t}setY(e,t){return this.normalized&&(t=$i(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=ru(t,this.array)),t}setZ(e,t){return this.normalized&&(t=$i(t,this.array)),this.array[e*this.itemSize+2]=t,this}getW(e){let t=this.array[e*this.itemSize+3];return this.normalized&&(t=ru(t,this.array)),t}setW(e,t){return this.normalized&&(t=$i(t,this.array)),this.array[e*this.itemSize+3]=t,this}setXY(e,t,n){return e*=this.itemSize,this.normalized&&(t=$i(t,this.array),n=$i(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=$i(t,this.array),n=$i(n,this.array),i=$i(i,this.array)),this.array[e+0]=t,this.array[e+1]=n,this.array[e+2]=i,this}setXYZW(e,t,n,i,s){return e*=this.itemSize,this.normalized&&(t=$i(t,this.array),n=$i(n,this.array),i=$i(i,this.array),s=$i(s,this.array)),this.array[e+0]=t,this.array[e+1]=n,this.array[e+2]=i,this.array[e+3]=s,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!==U&&(e.usage=this.usage),e}}class Jue extends null{constructor(e,t,n){super(new Int8Array(e),t,n)}}class Kue extends null{constructor(e,t,n){super(new Uint8Array(e),t,n)}}class que extends null{constructor(e,t,n){super(new Uint8ClampedArray(e),t,n)}}class _ue extends null{constructor(e,t,n){super(new Int16Array(e),t,n)}}class XC extends ga{constructor(e,t,n){super(new Uint16Array(e),t,n)}}class $ue extends null{constructor(e,t,n){super(new Int32Array(e),t,n)}}class GC extends ga{constructor(e,t,n){super(new Uint32Array(e),t,n)}}class RS extends ga{constructor(e,t,n){super(new Uint16Array(e),t,n),this.isFloat16BufferAttribute=!0}getX(e){let t=N0(this.array[e*this.itemSize]);return this.normalized&&(t=ru(t,this.array)),t}setX(e,t){return this.normalized&&(t=$i(t,this.array)),this.array[e*this.itemSize]=Eu(t),this}getY(e){let t=N0(this.array[e*this.itemSize+1]);return this.normalized&&(t=ru(t,this.array)),t}setY(e,t){return this.normalized&&(t=$i(t,this.array)),this.array[e*this.itemSize+1]=Eu(t),this}getZ(e){let t=N0(this.array[e*this.itemSize+2]);return this.normalized&&(t=ru(t,this.array)),t}setZ(e,t){return this.normalized&&(t=$i(t,this.array)),this.array[e*this.itemSize+2]=Eu(t),this}getW(e){let t=N0(this.array[e*this.itemSize+3]);return this.normalized&&(t=ru(t,this.array)),t}setW(e,t){return this.normalized&&(t=$i(t,this.array)),this.array[e*this.itemSize+3]=Eu(t),this}setXY(e,t,n){return e*=this.itemSize,this.normalized&&(t=$i(t,this.array),n=$i(n,this.array)),this.array[e+0]=Eu(t),this.array[e+1]=Eu(n),this}setXYZ(e,t,n,i){return e*=this.itemSize,this.normalized&&(t=$i(t,this.array),n=$i(n,this.array),i=$i(i,this.array)),this.array[e+0]=Eu(t),this.array[e+1]=Eu(n),this.array[e+2]=Eu(i),this}setXYZW(e,t,n,i,s){return e*=this.itemSize,this.normalized&&(t=$i(t,this.array),n=$i(n,this.array),i=$i(i,this.array),s=$i(s,this.array)),this.array[e+0]=Eu(t),this.array[e+1]=Eu(n),this.array[e+2]=Eu(i),this.array[e+3]=Eu(s),this}}class yr extends ga{constructor(e,t,n){super(new Float32Array(e),t,n)}}let CR=0;const Mc=new Cr,WC=new so,Ov=new J,_u=new xl,F0=new xl,il=new J;class Ni extends Go{constructor(){super(),this.isBufferGeometry=!0,Object.defineProperty(this,"id",{value:CR++}),this.uuid=Ga(),this.name="",this.type="BufferGeometry",this.index=null,this.indirect=null,this.indirectOffset=0,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(gi(e)?GC:XC)(e,1):this.index=e,this}setIndirect(e,t=0){return this.indirect=e,this.indirectOffset=t,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 this.attributes[e]!==void 0}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;t!==void 0&&(t.applyMatrix4(e),t.needsUpdate=!0);const n=this.attributes.normal;if(n!==void 0){const s=new zi().getNormalMatrix(e);n.applyNormalMatrix(s),n.needsUpdate=!0}const i=this.attributes.tangent;return i!==void 0&&(i.transformDirection(e),i.needsUpdate=!0),this.boundingBox!==null&&this.computeBoundingBox(),this.boundingSphere!==null&&this.computeBoundingSphere(),this}applyQuaternion(e){return Mc.makeRotationFromQuaternion(e),this.applyMatrix4(Mc),this}rotateX(e){return Mc.makeRotationX(e),this.applyMatrix4(Mc),this}rotateY(e){return Mc.makeRotationY(e),this.applyMatrix4(Mc),this}rotateZ(e){return Mc.makeRotationZ(e),this.applyMatrix4(Mc),this}translate(e,t,n){return Mc.makeTranslation(e,t,n),this.applyMatrix4(Mc),this}scale(e,t,n){return Mc.makeScale(e,t,n),this.applyMatrix4(Mc),this}lookAt(e){return WC.lookAt(e),WC.updateMatrix(),this.applyMatrix4(WC.matrix),this}center(){return this.computeBoundingBox(),this.boundingBox.getCenter(Ov).negate(),this.translate(Ov.x,Ov.y,Ov.z),this}setFromPoints(e){const t=this.getAttribute("position");if(t===void 0){const n=[];for(let i=0,s=e.length;i<s;i++){const a=e[i];n.push(a.x,a.y,a.z||0)}this.setAttribute("position",new yr(n,3))}else{const n=Math.min(e.length,t.count);for(let i=0;i<n;i++){const s=e[i];t.setXYZ(i,s.x,s.y,s.z||0)}e.length>t.count&&ze("BufferGeometry: Buffer size too small for points data. Use .dispose() and create a new geometry."),t.needsUpdate=!0}return this}computeBoundingBox(){this.boundingBox===null&&(this.boundingBox=new xl);const e=this.attributes.position,t=this.morphAttributes.position;if(e&&e.isGLBufferAttribute){rt("BufferGeometry.computeBoundingBox(): GLBufferAttribute requires a manual bounding box.",this),this.boundingBox.set(new J(-1/0,-1/0,-1/0),new J(1/0,1/0,1/0));return}if(e!==void 0){if(this.boundingBox.setFromBufferAttribute(e),t)for(let n=0,i=t.length;n<i;n++){const s=t[n];_u.setFromBufferAttribute(s),this.morphTargetsRelative?(il.addVectors(this.boundingBox.min,_u.min),this.boundingBox.expandByPoint(il),il.addVectors(this.boundingBox.max,_u.max),this.boundingBox.expandByPoint(il)):(this.boundingBox.expandByPoint(_u.min),this.boundingBox.expandByPoint(_u.max))}}else this.boundingBox.makeEmpty();(isNaN(this.boundingBox.min.x)||isNaN(this.boundingBox.min.y)||isNaN(this.boundingBox.min.z))&&rt('BufferGeometry.computeBoundingBox(): Computed min/max have NaN values. The "position" attribute is likely to have NaN values.',this)}computeBoundingSphere(){this.boundingSphere===null&&(this.boundingSphere=new yl);const e=this.attributes.position,t=this.morphAttributes.position;if(e&&e.isGLBufferAttribute){rt("BufferGeometry.computeBoundingSphere(): GLBufferAttribute requires a manual bounding sphere.",this),this.boundingSphere.set(new J,1/0);return}if(e){const n=this.boundingSphere.center;if(_u.setFromBufferAttribute(e),t)for(let s=0,a=t.length;s<a;s++){const o=t[s];F0.setFromBufferAttribute(o),this.morphTargetsRelative?(il.addVectors(_u.min,F0.min),_u.expandByPoint(il),il.addVectors(_u.max,F0.max),_u.expandByPoint(il)):(_u.expandByPoint(F0.min),_u.expandByPoint(F0.max))}_u.getCenter(n);let i=0;for(let s=0,a=e.count;s<a;s++)il.fromBufferAttribute(e,s),i=Math.max(i,n.distanceToSquared(il));if(t)for(let s=0,a=t.length;s<a;s++){const o=t[s],l=this.morphTargetsRelative;for(let u=0,c=o.count;u<c;u++)il.fromBufferAttribute(o,u),l&&(Ov.fromBufferAttribute(e,u),il.add(Ov)),i=Math.max(i,n.distanceToSquared(il))}this.boundingSphere.radius=Math.sqrt(i),isNaN(this.boundingSphere.radius)&&rt('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(e===null||t.position===void 0||t.normal===void 0||t.uv===void 0){rt("BufferGeometry: .computeTangents() failed. Missing required attributes (index, position, normal or uv)");return}const n=t.position,i=t.normal,s=t.uv;this.hasAttribute("tangent")===!1&&this.setAttribute("tangent",new ga(new Float32Array(4*n.count),4));const a=this.getAttribute("tangent"),o=[],l=[];for(let N=0;N<n.count;N++)o[N]=new J,l[N]=new J;const u=new J,c=new J,d=new J,f=new ct,h=new ct,p=new ct,x=new J,v=new J;function m(N,T,R){u.fromBufferAttribute(n,N),c.fromBufferAttribute(n,T),d.fromBufferAttribute(n,R),f.fromBufferAttribute(s,N),h.fromBufferAttribute(s,T),p.fromBufferAttribute(s,R),c.sub(u),d.sub(u),h.sub(f),p.sub(f);const D=1/(h.x*p.y-p.x*h.y);isFinite(D)&&(x.copy(c).multiplyScalar(p.y).addScaledVector(d,-h.y).multiplyScalar(D),v.copy(d).multiplyScalar(h.x).addScaledVector(c,-p.x).multiplyScalar(D),o[N].add(x),o[T].add(x),o[R].add(x),l[N].add(v),l[T].add(v),l[R].add(v))}let C=this.groups;C.length===0&&(C=[{start:0,count:e.count}]);for(let N=0,T=C.length;N<T;++N){const R=C[N],D=R.start,j=R.count;for(let q=D,Q=D+j;q<Q;q+=3)m(e.getX(q+0),e.getX(q+1),e.getX(q+2))}const w=new J,P=new J,B=new J,S=new J;function I(N){B.fromBufferAttribute(i,N),S.copy(B);const T=o[N];w.copy(T),w.sub(B.multiplyScalar(B.dot(T))).normalize(),P.crossVectors(S,T);const D=P.dot(l[N])<0?-1:1;a.setXYZW(N,w.x,w.y,w.z,D)}for(let N=0,T=C.length;N<T;++N){const R=C[N],D=R.start,j=R.count;for(let q=D,Q=D+j;q<Q;q+=3)I(e.getX(q+0)),I(e.getX(q+1)),I(e.getX(q+2))}}computeVertexNormals(){const e=this.index,t=this.getAttribute("position");if(t!==void 0){let n=this.getAttribute("normal");if(n===void 0)n=new ga(new Float32Array(t.count*3),3),this.setAttribute("normal",n);else for(let f=0,h=n.count;f<h;f++)n.setXYZ(f,0,0,0);const i=new J,s=new J,a=new J,o=new J,l=new J,u=new J,c=new J,d=new J;if(e)for(let f=0,h=e.count;f<h;f+=3){const p=e.getX(f+0),x=e.getX(f+1),v=e.getX(f+2);i.fromBufferAttribute(t,p),s.fromBufferAttribute(t,x),a.fromBufferAttribute(t,v),c.subVectors(a,s),d.subVectors(i,s),c.cross(d),o.fromBufferAttribute(n,p),l.fromBufferAttribute(n,x),u.fromBufferAttribute(n,v),o.add(c),l.add(c),u.add(c),n.setXYZ(p,o.x,o.y,o.z),n.setXYZ(x,l.x,l.y,l.z),n.setXYZ(v,u.x,u.y,u.z)}else for(let f=0,h=t.count;f<h;f+=3)i.fromBufferAttribute(t,f+0),s.fromBufferAttribute(t,f+1),a.fromBufferAttribute(t,f+2),c.subVectors(a,s),d.subVectors(i,s),c.cross(d),n.setXYZ(f+0,c.x,c.y,c.z),n.setXYZ(f+1,c.x,c.y,c.z),n.setXYZ(f+2,c.x,c.y,c.z);this.normalizeNormals(),n.needsUpdate=!0}}normalizeNormals(){const e=this.attributes.normal;for(let t=0,n=e.count;t<n;t++)il.fromBufferAttribute(e,t),il.normalize(),e.setXYZ(t,il.x,il.y,il.z)}toNonIndexed(){function e(o,l){const u=o.array,c=o.itemSize,d=o.normalized,f=new u.constructor(l.length*c);let h=0,p=0;for(let x=0,v=l.length;x<v;x++){o.isInterleavedBufferAttribute?h=l[x]*o.data.stride+o.offset:h=l[x]*c;for(let m=0;m<c;m++)f[p++]=u[h++]}return new ga(f,c,d)}if(this.index===null)return ze("BufferGeometry.toNonIndexed(): BufferGeometry is already non-indexed."),this;const t=new Ni,n=this.index.array,i=this.attributes;for(const o in i){const l=i[o],u=e(l,n);t.setAttribute(o,u)}const s=this.morphAttributes;for(const o in s){const l=[],u=s[o];for(let c=0,d=u.length;c<d;c++){const f=u[c],h=e(f,n);l.push(h)}t.morphAttributes[o]=l}t.morphTargetsRelative=this.morphTargetsRelative;const a=this.groups;for(let o=0,l=a.length;o<l;o++){const u=a[o];t.addGroup(u.start,u.count,u.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),this.parameters!==void 0){const l=this.parameters;for(const u in l)l[u]!==void 0&&(e[u]=l[u]);return e}e.data={attributes:{}};const t=this.index;t!==null&&(e.data.index={type:t.array.constructor.name,array:Array.prototype.slice.call(t.array)});const n=this.attributes;for(const l in n){const u=n[l];e.data.attributes[l]=u.toJSON(e.data)}const i={};let s=!1;for(const l in this.morphAttributes){const u=this.morphAttributes[l],c=[];for(let d=0,f=u.length;d<f;d++){const h=u[d];c.push(h.toJSON(e.data))}c.length>0&&(i[l]=c,s=!0)}s&&(e.data.morphAttributes=i,e.data.morphTargetsRelative=this.morphTargetsRelative);const a=this.groups;a.length>0&&(e.data.groups=JSON.parse(JSON.stringify(a)));const o=this.boundingSphere;return o!==null&&(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;n!==null&&this.setIndex(n.clone());const i=e.attributes;for(const u in i){const c=i[u];this.setAttribute(u,c.clone(t))}const s=e.morphAttributes;for(const u in s){const c=[],d=s[u];for(let f=0,h=d.length;f<h;f++)c.push(d[f].clone(t));this.morphAttributes[u]=c}this.morphTargetsRelative=e.morphTargetsRelative;const a=e.groups;for(let u=0,c=a.length;u<c;u++){const d=a[u];this.addGroup(d.start,d.count,d.materialIndex)}const o=e.boundingBox;o!==null&&(this.boundingBox=o.clone());const l=e.boundingSphere;return l!==null&&(this.boundingSphere=l.clone()),this.drawRange.start=e.drawRange.start,this.drawRange.count=e.drawRange.count,this.userData=e.userData,this}dispose(){this.dispatchEvent({type:"dispose"})}}const LS=new Cr,Um=new Tv,Ly=new yl,OS=new J,Oy=new J,zy=new J,Hy=new J,QC=new J,Uy=new J,zS=new J,ky=new J;class Gs extends so{constructor(e=new Ni,t=new rl){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),e.morphTargetInfluences!==void 0&&(this.morphTargetInfluences=e.morphTargetInfluences.slice()),e.morphTargetDictionary!==void 0&&(this.morphTargetDictionary=Object.assign({},e.morphTargetDictionary)),this.material=Array.isArray(e.material)?e.material.slice():e.material,this.geometry=e.geometry,this}updateMorphTargets(){const t=this.geometry.morphAttributes,n=Object.keys(t);if(n.length>0){const i=t[n[0]];if(i!==void 0){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let s=0,a=i.length;s<a;s++){const o=i[s].name||String(s);this.morphTargetInfluences.push(0),this.morphTargetDictionary[o]=s}}}}getVertexPosition(e,t){const n=this.geometry,i=n.attributes.position,s=n.morphAttributes.position,a=n.morphTargetsRelative;t.fromBufferAttribute(i,e);const o=this.morphTargetInfluences;if(s&&o){Uy.set(0,0,0);for(let l=0,u=s.length;l<u;l++){const c=o[l],d=s[l];c!==0&&(QC.fromBufferAttribute(d,e),a?Uy.addScaledVector(QC,c):Uy.addScaledVector(QC.sub(t),c))}t.add(Uy)}return t}raycast(e,t){const n=this.geometry,i=this.material,s=this.matrixWorld;i!==void 0&&(n.boundingSphere===null&&n.computeBoundingSphere(),Ly.copy(n.boundingSphere),Ly.applyMatrix4(s),Um.copy(e.ray).recast(e.near),!(Ly.containsPoint(Um.origin)===!1&&(Um.intersectSphere(Ly,OS)===null||Um.origin.distanceToSquared(OS)>gS(e.far-e.near,2)))&&(LS.copy(s).invert(),Um.copy(e.ray).applyMatrix4(LS),!(n.boundingBox!==null&&Um.intersectsBox(n.boundingBox)===!1)&&this._computeIntersections(e,t,Um)))}_computeIntersections(e,t,n){let i;const s=this.geometry,a=this.material,o=s.index,l=s.attributes.position,u=s.attributes.uv,c=s.attributes.uv1,d=s.attributes.normal,f=s.groups,h=s.drawRange;if(o!==null)if(Array.isArray(a))for(let p=0,x=f.length;p<x;p++){const v=f[p],m=a[v.materialIndex],C=Math.max(v.start,h.start),w=Math.min(o.count,Math.min(v.start+v.count,h.start+h.count));for(let P=C,B=w;P<B;P+=3){const S=o.getX(P),I=o.getX(P+1),N=o.getX(P+2);i=Vy(this,m,e,n,u,c,d,S,I,N),i&&(i.faceIndex=Math.floor(P/3),i.face.materialIndex=v.materialIndex,t.push(i))}}else{const p=Math.max(0,h.start),x=Math.min(o.count,h.start+h.count);for(let v=p,m=x;v<m;v+=3){const C=o.getX(v),w=o.getX(v+1),P=o.getX(v+2);i=Vy(this,a,e,n,u,c,d,C,w,P),i&&(i.faceIndex=Math.floor(v/3),t.push(i))}}else if(l!==void 0)if(Array.isArray(a))for(let p=0,x=f.length;p<x;p++){const v=f[p],m=a[v.materialIndex],C=Math.max(v.start,h.start),w=Math.min(l.count,Math.min(v.start+v.count,h.start+h.count));for(let P=C,B=w;P<B;P+=3){const S=P,I=P+1,N=P+2;i=Vy(this,m,e,n,u,c,d,S,I,N),i&&(i.faceIndex=Math.floor(P/3),i.face.materialIndex=v.materialIndex,t.push(i))}}else{const p=Math.max(0,h.start),x=Math.min(l.count,h.start+h.count);for(let v=p,m=x;v<m;v+=3){const C=v,w=v+1,P=v+2;i=Vy(this,a,e,n,u,c,d,C,w,P),i&&(i.faceIndex=Math.floor(v/3),t.push(i))}}}}function PR(r,e,t,n,i,s,a,o){let l;if(e.side===Qi?l=n.intersectTriangle(a,s,i,!0,o):l=n.intersectTriangle(i,s,a,e.side===ja,o),l===null)return null;ky.copy(o),ky.applyMatrix4(r.matrixWorld);const u=t.ray.origin.distanceTo(ky);return u<t.near||u>t.far?null:{distance:u,point:ky.clone(),object:r}}function Vy(r,e,t,n,i,s,a,o,l,u){r.getVertexPosition(o,Oy),r.getVertexPosition(l,zy),r.getVertexPosition(u,Hy);const c=PR(r,e,t,n,Oy,zy,Hy,zS);if(c){const d=new J;qu.getBarycoord(zS,Oy,zy,Hy,d),i&&(c.uv=qu.getInterpolatedAttribute(i,o,l,u,d,new ct)),s&&(c.uv1=qu.getInterpolatedAttribute(s,o,l,u,d,new ct)),a&&(c.normal=qu.getInterpolatedAttribute(a,o,l,u,d,new J),c.normal.dot(n.direction)>0&&c.normal.multiplyScalar(-1));const f={a:o,b:l,c:u,normal:new J,materialIndex:0};qu.getNormal(Oy,zy,Hy,f.normal),c.face=f,c.barycoord=d}return c}class Dp extends Ni{constructor(e=1,t=1,n=1,i=1,s=1,a=1){super(),this.type="BoxGeometry",this.parameters={width:e,height:t,depth:n,widthSegments:i,heightSegments:s,depthSegments:a};const o=this;i=Math.floor(i),s=Math.floor(s),a=Math.floor(a);const l=[],u=[],c=[],d=[];let f=0,h=0;p("z","y","x",-1,-1,n,t,e,a,s,0),p("z","y","x",1,-1,n,t,-e,a,s,1),p("x","z","y",1,1,e,n,t,i,a,2),p("x","z","y",1,-1,e,n,-t,i,a,3),p("x","y","z",1,-1,e,t,n,i,s,4),p("x","y","z",-1,-1,e,t,-n,i,s,5),this.setIndex(l),this.setAttribute("position",new yr(u,3)),this.setAttribute("normal",new yr(c,3)),this.setAttribute("uv",new yr(d,2));function p(x,v,m,C,w,P,B,S,I,N,T){const R=P/I,D=B/N,j=P/2,q=B/2,Q=S/2,re=I+1,de=N+1;let we=0,ge=0;const Y=new J;for(let Se=0;Se<de;Se++){const W=Se*D-q;for(let fe=0;fe<re;fe++){const xe=fe*R-j;Y[x]=xe*C,Y[v]=W*w,Y[m]=Q,u.push(Y.x,Y.y,Y.z),Y[x]=0,Y[v]=0,Y[m]=S>0?1:-1,c.push(Y.x,Y.y,Y.z),d.push(fe/I),d.push(1-Se/N),we+=1}}for(let Se=0;Se<N;Se++)for(let W=0;W<I;W++){const fe=f+W+re*Se,xe=f+W+re*(Se+1),dt=f+(W+1)+re*(Se+1),ve=f+(W+1)+re*Se;l.push(fe,xe,ve),l.push(xe,dt,ve),ge+=6}o.addGroup(h,ge,T),h+=ge,f+=we}}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new Dp(e.width,e.height,e.depth,e.widthSegments,e.heightSegments,e.depthSegments)}}function zv(r){const e={};for(const t in r){e[t]={};for(const n in r[t]){const i=r[t][n];i&&(i.isColor||i.isMatrix3||i.isMatrix4||i.isVector2||i.isVector3||i.isVector4||i.isTexture||i.isQuaternion)?i.isRenderTargetTexture?(ze("UniformsUtils: Textures of render targets cannot be cloned via cloneUniforms() or mergeUniforms()."),e[t][n]=null):e[t][n]=i.clone():Array.isArray(i)?e[t][n]=i.slice():e[t][n]=i}}return e}function iu(r){const e={};for(let t=0;t<r.length;t++){const n=zv(r[t]);for(const i in n)e[i]=n[i]}return e}function BR(r){const e=[];for(let t=0;t<r.length;t++)e.push(r[t].clone());return e}function HS(r){const e=r.getRenderTarget();return e===null?r.outputColorSpace:e.isXRRenderTarget===!0?e.texture.colorSpace:$r.workingColorSpace}const US={clone:zv,merge:iu};var MR=`void main() {
	gl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );
}`,SR=`void main() {
	gl_FragColor = vec4( 1.0, 0.0, 0.0, 1.0 );
}`;class $u extends bl{constructor(e){super(),this.isShaderMaterial=!0,this.type="ShaderMaterial",this.defines={},this.uniforms={},this.uniformsGroups=[],this.vertexShader=MR,this.fragmentShader=SR,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,e!==void 0&&this.setValues(e)}copy(e){return super.copy(e),this.fragmentShader=e.fragmentShader,this.vertexShader=e.vertexShader,this.uniforms=zv(e.uniforms),this.uniformsGroups=BR(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.defaultAttributeValues=Object.assign({},e.defaultAttributeValues),this.index0AttributeName=e.index0AttributeName,this.uniformsNeedUpdate=e.uniformsNeedUpdate,this}toJSON(e){const t=super.toJSON(e);t.glslVersion=this.glslVersion,t.uniforms={};for(const i in this.uniforms){const a=this.uniforms[i].value;a&&a.isTexture?t.uniforms[i]={type:"t",value:a.toJSON(e).uuid}:a&&a.isColor?t.uniforms[i]={type:"c",value:a.getHex()}:a&&a.isVector2?t.uniforms[i]={type:"v2",value:a.toArray()}:a&&a.isVector3?t.uniforms[i]={type:"v3",value:a.toArray()}:a&&a.isVector4?t.uniforms[i]={type:"v4",value:a.toArray()}:a&&a.isMatrix3?t.uniforms[i]={type:"m3",value:a.toArray()}:a&&a.isMatrix4?t.uniforms[i]={type:"m4",value:a.toArray()}:t.uniforms[i]={value:a}}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 i in this.extensions)this.extensions[i]===!0&&(n[i]=!0);return Object.keys(n).length>0&&(t.extensions=n),t}}class jy extends so{constructor(){super(),this.isCamera=!0,this.type="Camera",this.matrixWorldInverse=new Cr,this.projectionMatrix=new Cr,this.projectionMatrixInverse=new Cr,this.coordinateSystem=Gt,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 Tp=new J,kS=new ct,VS=new ct;class bo extends jy{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=e.view===null?null:Object.assign({},e.view),this.filmGauge=e.filmGauge,this.filmOffset=e.filmOffset,this}setFocalLength(e){const t=.5*this.getFilmHeight()/e;this.fov=Bc*2*Math.atan(t),this.updateProjectionMatrix()}getFocalLength(){const e=Math.tan(nu*.5*this.fov);return .5*this.getFilmHeight()/e}getEffectiveFOV(){return Bc*2*Math.atan(Math.tan(nu*.5*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){Tp.set(-1,-1,.5).applyMatrix4(this.projectionMatrixInverse),t.set(Tp.x,Tp.y).multiplyScalar(-e/Tp.z),Tp.set(1,1,.5).applyMatrix4(this.projectionMatrixInverse),n.set(Tp.x,Tp.y).multiplyScalar(-e/Tp.z)}getViewSize(e,t){return this.getViewBounds(e,kS,VS),t.subVectors(VS,kS)}setViewOffset(e,t,n,i,s,a){this.aspect=e/t,this.view===null&&(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=s,this.view.height=a,this.updateProjectionMatrix()}clearViewOffset(){this.view!==null&&(this.view.enabled=!1),this.updateProjectionMatrix()}updateProjectionMatrix(){const e=this.near;let t=e*Math.tan(nu*.5*this.fov)/this.zoom,n=2*t,i=this.aspect*n,s=-.5*i;const a=this.view;if(this.view!==null&&this.view.enabled){const l=a.fullWidth,u=a.fullHeight;s+=a.offsetX*i/l,t-=a.offsetY*n/u,i*=a.width/l,n*=a.height/u}const o=this.filmOffset;o!==0&&(s+=e*o/this.getFilmWidth()),this.projectionMatrix.makePerspective(s,s+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,this.view!==null&&(t.object.view=Object.assign({},this.view)),t.object.filmGauge=this.filmGauge,t.object.filmOffset=this.filmOffset,t}}const Hv=-90,Uv=1;class jS extends so{constructor(e,t,n){super(),this.type="CubeCamera",this.renderTarget=n,this.coordinateSystem=null,this.activeMipmapLevel=0;const i=new bo(Hv,Uv,e,t);i.layers=this.layers,this.add(i);const s=new bo(Hv,Uv,e,t);s.layers=this.layers,this.add(s);const a=new bo(Hv,Uv,e,t);a.layers=this.layers,this.add(a);const o=new bo(Hv,Uv,e,t);o.layers=this.layers,this.add(o);const l=new bo(Hv,Uv,e,t);l.layers=this.layers,this.add(l);const u=new bo(Hv,Uv,e,t);u.layers=this.layers,this.add(u)}updateCoordinateSystem(){const e=this.coordinateSystem,t=this.children.concat(),[n,i,s,a,o,l]=t;for(const u of t)this.remove(u);if(e===Gt)n.up.set(0,1,0),n.lookAt(1,0,0),i.up.set(0,1,0),i.lookAt(-1,0,0),s.up.set(0,0,-1),s.lookAt(0,1,0),a.up.set(0,0,1),a.lookAt(0,-1,0),o.up.set(0,1,0),o.lookAt(0,0,1),l.up.set(0,1,0),l.lookAt(0,0,-1);else if(e===gn)n.up.set(0,-1,0),n.lookAt(-1,0,0),i.up.set(0,-1,0),i.lookAt(1,0,0),s.up.set(0,0,1),s.lookAt(0,1,0),a.up.set(0,0,-1),a.lookAt(0,-1,0),o.up.set(0,-1,0),o.lookAt(0,0,1),l.up.set(0,-1,0),l.lookAt(0,0,-1);else throw new Error("THREE.CubeCamera.updateCoordinateSystem(): Invalid coordinate system: "+e);for(const u of t)this.add(u),u.updateMatrixWorld()}update(e,t){this.parent===null&&this.updateMatrixWorld();const{renderTarget:n,activeMipmapLevel:i}=this;this.coordinateSystem!==e.coordinateSystem&&(this.coordinateSystem=e.coordinateSystem,this.updateCoordinateSystem());const[s,a,o,l,u,c]=this.children,d=e.getRenderTarget(),f=e.getActiveCubeFace(),h=e.getActiveMipmapLevel(),p=e.xr.enabled;e.xr.enabled=!1;const x=n.texture.generateMipmaps;n.texture.generateMipmaps=!1,e.setRenderTarget(n,0,i),e.render(t,s),e.setRenderTarget(n,1,i),e.render(t,a),e.setRenderTarget(n,2,i),e.render(t,o),e.setRenderTarget(n,3,i),e.render(t,l),e.setRenderTarget(n,4,i),e.render(t,u),n.texture.generateMipmaps=x,e.setRenderTarget(n,5,i),e.render(t,c),e.setRenderTarget(d,f,h),e.xr.enabled=p,n.texture.needsPMREMUpdate=!0}}class km extends yo{constructor(e=[],t=ai,n,i,s,a,o,l,u,c){super(e,t,n,i,s,a,o,l,u,c),this.isCubeTexture=!0,this.flipY=!1}get images(){return this.image}set images(e){this.image=e}}class ZC extends fd{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 km(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:`

				varying vec3 vWorldDirection;

				vec3 transformDirection( in vec3 dir, in mat4 matrix ) {

					return normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );

				}

				void main() {

					vWorldDirection = transformDirection( position, modelMatrix );

					#include <begin_vertex>
					#include <project_vertex>

				}
			`,fragmentShader:`

				uniform sampler2D tEquirect;

				varying vec3 vWorldDirection;

				#include <common>

				void main() {

					vec3 direction = normalize( vWorldDirection );

					vec2 sampleUV = equirectUv( direction );

					gl_FragColor = texture2D( tEquirect, sampleUV );

				}
			`},i=new Dp(5,5,5),s=new $u({name:"CubemapFromEquirect",uniforms:zv(n.uniforms),vertexShader:n.vertexShader,fragmentShader:n.fragmentShader,side:Qi,blending:Xa});s.uniforms.tEquirect.value=t;const a=new Gs(i,s),o=t.minFilter;return t.minFilter===tl&&(t.minFilter=ms),new jS(1,10,this).update(e,a),t.minFilter=o,a.geometry.dispose(),a.material.dispose(),this}clear(e,t=!0,n=!0,i=!0){const s=e.getRenderTarget();for(let a=0;a<6;a++)e.setRenderTarget(this,a),e.clear(t,n,i);e.setRenderTarget(s)}}class Vm extends so{constructor(){super(),this.isGroup=!0,this.type="Group"}}const DR={type:"move"};class Xy{constructor(){this._targetRay=null,this._grip=null,this._hand=null}getHandSpace(){return this._hand===null&&(this._hand=new Vm,this._hand.matrixAutoUpdate=!1,this._hand.visible=!1,this._hand.joints={},this._hand.inputState={pinching:!1}),this._hand}getTargetRaySpace(){return this._targetRay===null&&(this._targetRay=new Vm,this._targetRay.matrixAutoUpdate=!1,this._targetRay.visible=!1,this._targetRay.hasLinearVelocity=!1,this._targetRay.linearVelocity=new J,this._targetRay.hasAngularVelocity=!1,this._targetRay.angularVelocity=new J),this._targetRay}getGripSpace(){return this._grip===null&&(this._grip=new Vm,this._grip.matrixAutoUpdate=!1,this._grip.visible=!1,this._grip.hasLinearVelocity=!1,this._grip.linearVelocity=new J,this._grip.hasAngularVelocity=!1,this._grip.angularVelocity=new J),this._grip}dispatchEvent(e){return this._targetRay!==null&&this._targetRay.dispatchEvent(e),this._grip!==null&&this._grip.dispatchEvent(e),this._hand!==null&&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}),this._targetRay!==null&&(this._targetRay.visible=!1),this._grip!==null&&(this._grip.visible=!1),this._hand!==null&&(this._hand.visible=!1),this}update(e,t,n){let i=null,s=null,a=null;const o=this._targetRay,l=this._grip,u=this._hand;if(e&&t.session.visibilityState!=="visible-blurred"){if(u&&e.hand){a=!0;for(const x of e.hand.values()){const v=t.getJointPose(x,n),m=this._getHandJoint(u,x);v!==null&&(m.matrix.fromArray(v.transform.matrix),m.matrix.decompose(m.position,m.rotation,m.scale),m.matrixWorldNeedsUpdate=!0,m.jointRadius=v.radius),m.visible=v!==null}const c=u.joints["index-finger-tip"],d=u.joints["thumb-tip"],f=c.position.distanceTo(d.position),h=.02,p=.005;u.inputState.pinching&&f>h+p?(u.inputState.pinching=!1,this.dispatchEvent({type:"pinchend",handedness:e.handedness,target:this})):!u.inputState.pinching&&f<=h-p&&(u.inputState.pinching=!0,this.dispatchEvent({type:"pinchstart",handedness:e.handedness,target:this}))}else l!==null&&e.gripSpace&&(s=t.getPose(e.gripSpace,n),s!==null&&(l.matrix.fromArray(s.transform.matrix),l.matrix.decompose(l.position,l.rotation,l.scale),l.matrixWorldNeedsUpdate=!0,s.linearVelocity?(l.hasLinearVelocity=!0,l.linearVelocity.copy(s.linearVelocity)):l.hasLinearVelocity=!1,s.angularVelocity?(l.hasAngularVelocity=!0,l.angularVelocity.copy(s.angularVelocity)):l.hasAngularVelocity=!1));o!==null&&(i=t.getPose(e.targetRaySpace,n),i===null&&s!==null&&(i=s),i!==null&&(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(DR)))}return o!==null&&(o.visible=i!==null),l!==null&&(l.visible=s!==null),u!==null&&(u.visible=a!==null),this}_getHandJoint(e,t){if(e.joints[t.jointName]===void 0){const n=new Vm;n.matrixAutoUpdate=!1,n.visible=!1,e.joints[t.jointName]=n,e.add(n)}return e.joints[t.jointName]}}class YC{constructor(e,t=25e-5){this.isFogExp2=!0,this.name="",this.color=new Vn(e),this.density=t}clone(){return new YC(this.color,this.density)}toJSON(){return{type:"FogExp2",name:this.name,color:this.color.getHex(),density:this.density}}}class JC{constructor(e,t=1,n=1e3){this.isFog=!0,this.name="",this.color=new Vn(e),this.near=t,this.far=n}clone(){return new JC(this.color,this.near,this.far)}toJSON(){return{type:"Fog",name:this.name,color:this.color.getHex(),near:this.near,far:this.far}}}class R0 extends so{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 bu,this.environmentIntensity=1,this.environmentRotation=new bu,this.overrideMaterial=null,typeof __THREE_DEVTOOLS__!="undefined"&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent("observe",{detail:this}))}copy(e,t){return super.copy(e,t),e.background!==null&&(this.background=e.background.clone()),e.environment!==null&&(this.environment=e.environment.clone()),e.fog!==null&&(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),e.overrideMaterial!==null&&(this.overrideMaterial=e.overrideMaterial.clone()),this.matrixAutoUpdate=e.matrixAutoUpdate,this}toJSON(e){const t=super.toJSON(e);return this.fog!==null&&(t.object.fog=this.fog.toJSON()),this.backgroundBlurriness>0&&(t.object.backgroundBlurriness=this.backgroundBlurriness),this.backgroundIntensity!==1&&(t.object.backgroundIntensity=this.backgroundIntensity),t.object.backgroundRotation=this.backgroundRotation.toArray(),this.environmentIntensity!==1&&(t.object.environmentIntensity=this.environmentIntensity),t.object.environmentRotation=this.environmentRotation.toArray(),t}}class Gy{constructor(e,t){this.isInterleavedBuffer=!0,this.array=e,this.stride=t,this.count=e!==void 0?e.length/t:0,this.usage=U,this.updateRanges=[],this.version=0,this.uuid=Ga()}onUploadCallback(){}set needsUpdate(e){e===!0&&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,s=this.stride;i<s;i++)this.array[e+i]=t.array[n+i];return this}set(e,t=0){return this.array.set(e,t),this}clone(e){e.arrayBuffers===void 0&&(e.arrayBuffers={}),this.array.buffer._uuid===void 0&&(this.array.buffer._uuid=Ga()),e.arrayBuffers[this.array.buffer._uuid]===void 0&&(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 e.arrayBuffers===void 0&&(e.arrayBuffers={}),this.array.buffer._uuid===void 0&&(this.array.buffer._uuid=Ga()),e.arrayBuffers[this.array.buffer._uuid]===void 0&&(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 su=new J;class jm{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++)su.fromBufferAttribute(this,t),su.applyMatrix4(e),this.setXYZ(t,su.x,su.y,su.z);return this}applyNormalMatrix(e){for(let t=0,n=this.count;t<n;t++)su.fromBufferAttribute(this,t),su.applyNormalMatrix(e),this.setXYZ(t,su.x,su.y,su.z);return this}transformDirection(e){for(let t=0,n=this.count;t<n;t++)su.fromBufferAttribute(this,t),su.transformDirection(e),this.setXYZ(t,su.x,su.y,su.z);return this}getComponent(e,t){let n=this.array[e*this.data.stride+this.offset+t];return this.normalized&&(n=ru(n,this.array)),n}setComponent(e,t,n){return this.normalized&&(n=$i(n,this.array)),this.data.array[e*this.data.stride+this.offset+t]=n,this}setX(e,t){return this.normalized&&(t=$i(t,this.array)),this.data.array[e*this.data.stride+this.offset]=t,this}setY(e,t){return this.normalized&&(t=$i(t,this.array)),this.data.array[e*this.data.stride+this.offset+1]=t,this}setZ(e,t){return this.normalized&&(t=$i(t,this.array)),this.data.array[e*this.data.stride+this.offset+2]=t,this}setW(e,t){return this.normalized&&(t=$i(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=ru(t,this.array)),t}getY(e){let t=this.data.array[e*this.data.stride+this.offset+1];return this.normalized&&(t=ru(t,this.array)),t}getZ(e){let t=this.data.array[e*this.data.stride+this.offset+2];return this.normalized&&(t=ru(t,this.array)),t}getW(e){let t=this.data.array[e*this.data.stride+this.offset+3];return this.normalized&&(t=ru(t,this.array)),t}setXY(e,t,n){return e=e*this.data.stride+this.offset,this.normalized&&(t=$i(t,this.array),n=$i(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=$i(t,this.array),n=$i(n,this.array),i=$i(i,this.array)),this.data.array[e+0]=t,this.data.array[e+1]=n,this.data.array[e+2]=i,this}setXYZW(e,t,n,i,s){return e=e*this.data.stride+this.offset,this.normalized&&(t=$i(t,this.array),n=$i(n,this.array),i=$i(i,this.array),s=$i(s,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]=s,this}clone(e){if(e===void 0){zl("InterleavedBufferAttribute.clone(): Cloning an interleaved buffer attribute will de-interleave buffer data.");const t=[];for(let n=0;n<this.count;n++){const i=n*this.data.stride+this.offset;for(let s=0;s<this.itemSize;s++)t.push(this.data.array[i+s])}return new ga(new this.array.constructor(t),this.itemSize,this.normalized)}else return e.interleavedBuffers===void 0&&(e.interleavedBuffers={}),e.interleavedBuffers[this.data.uuid]===void 0&&(e.interleavedBuffers[this.data.uuid]=this.data.clone(e)),new jm(e.interleavedBuffers[this.data.uuid],this.itemSize,this.offset,this.normalized)}toJSON(e){if(e===void 0){zl("InterleavedBufferAttribute.toJSON(): Serializing an interleaved buffer attribute will de-interleave buffer data.");const t=[];for(let n=0;n<this.count;n++){const i=n*this.data.stride+this.offset;for(let s=0;s<this.itemSize;s++)t.push(this.data.array[i+s])}return{itemSize:this.itemSize,type:this.array.constructor.name,array:t,normalized:this.normalized}}else return e.interleavedBuffers===void 0&&(e.interleavedBuffers={}),e.interleavedBuffers[this.data.uuid]===void 0&&(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 KC extends bl{constructor(e){super(),this.isSpriteMaterial=!0,this.type="SpriteMaterial",this.color=new Vn(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}}let kv;const L0=new J,Vv=new J,jv=new J,Xv=new ct,O0=new ct,XS=new Cr,Wy=new J,z0=new J,Qy=new J,GS=new ct,qC=new ct,WS=new ct;class TR extends null{constructor(e=new KC){if(super(),this.isSprite=!0,this.type="Sprite",kv===void 0){kv=new Ni;const t=new Float32Array([-.5,-.5,0,0,0,.5,-.5,0,1,0,.5,.5,0,1,1,-.5,.5,0,0,1]),n=new Gy(t,5);kv.setIndex([0,1,2,0,2,3]),kv.setAttribute("position",new jm(n,3,0,!1)),kv.setAttribute("uv",new jm(n,2,3,!1))}this.geometry=kv,this.material=e,this.center=new ct(.5,.5),this.count=1}raycast(e,t){e.camera===null&&rt('Sprite: "Raycaster.camera" needs to be set in order to raycast against sprites.'),Vv.setFromMatrixScale(this.matrixWorld),XS.copy(e.camera.matrixWorld),this.modelViewMatrix.multiplyMatrices(e.camera.matrixWorldInverse,this.matrixWorld),jv.setFromMatrixPosition(this.modelViewMatrix),e.camera.isPerspectiveCamera&&this.material.sizeAttenuation===!1&&Vv.multiplyScalar(-jv.z);const n=this.material.rotation;let i,s;n!==0&&(s=Math.cos(n),i=Math.sin(n));const a=this.center;Zy(Wy.set(-.5,-.5,0),jv,a,Vv,i,s),Zy(z0.set(.5,-.5,0),jv,a,Vv,i,s),Zy(Qy.set(.5,.5,0),jv,a,Vv,i,s),GS.set(0,0),qC.set(1,0),WS.set(1,1);let o=e.ray.intersectTriangle(Wy,z0,Qy,!1,L0);if(o===null&&(Zy(z0.set(-.5,.5,0),jv,a,Vv,i,s),qC.set(0,1),o=e.ray.intersectTriangle(Wy,Qy,z0,!1,L0),o===null))return;const l=e.ray.origin.distanceTo(L0);l<e.near||l>e.far||t.push({distance:l,point:L0.clone(),uv:qu.getInterpolation(L0,Wy,z0,Qy,GS,qC,WS,new ct),face:null,object:this})}copy(e,t){return super.copy(e,t),e.center!==void 0&&this.center.copy(e.center),this.material=e.material,this}}function Zy(r,e,t,n,i,s){Xv.subVectors(r,t).addScalar(.5).multiply(n),i!==void 0?(O0.x=s*Xv.x-i*Xv.y,O0.y=i*Xv.x+s*Xv.y):O0.copy(Xv),r.copy(e),r.x+=O0.x,r.y+=O0.y,r.applyMatrix4(XS)}const Yy=new J,QS=new J;class IR extends null{constructor(){super(),this.isLOD=!0,this._currentLevel=0,this.type="LOD",Object.defineProperties(this,{levels:{enumerable:!0,value:[]}}),this.autoUpdate=!0}copy(e){super.copy(e,!1);const t=e.levels;for(let n=0,i=t.length;n<i;n++){const s=t[n];this.addLevel(s.object.clone(),s.distance,s.hysteresis)}return this.autoUpdate=e.autoUpdate,this}addLevel(e,t=0,n=0){t=Math.abs(t);const i=this.levels;let s;for(s=0;s<i.length&&!(t<i[s].distance);s++);return i.splice(s,0,{distance:t,hysteresis:n,object:e}),this.add(e),this}removeLevel(e){const t=this.levels;for(let n=0;n<t.length;n++)if(t[n].distance===e){const i=t.splice(n,1);return this.remove(i[0].object),!0}return!1}getCurrentLevel(){return this._currentLevel}getObjectForDistance(e){const t=this.levels;if(t.length>0){let n,i;for(n=1,i=t.length;n<i;n++){let s=t[n].distance;if(t[n].object.visible&&(s-=s*t[n].hysteresis),e<s)break}return t[n-1].object}return null}raycast(e,t){if(this.levels.length>0){Yy.setFromMatrixPosition(this.matrixWorld);const i=e.ray.origin.distanceTo(Yy);this.getObjectForDistance(i).raycast(e,t)}}update(e){const t=this.levels;if(t.length>1){Yy.setFromMatrixPosition(e.matrixWorld),QS.setFromMatrixPosition(this.matrixWorld);const n=Yy.distanceTo(QS)/e.zoom;t[0].object.visible=!0;let i,s;for(i=1,s=t.length;i<s;i++){let a=t[i].distance;if(t[i].object.visible&&(a-=a*t[i].hysteresis),n>=a)t[i-1].object.visible=!1,t[i].object.visible=!0;else break}for(this._currentLevel=i-1;i<s;i++)t[i].object.visible=!1}}toJSON(e){const t=super.toJSON(e);this.autoUpdate===!1&&(t.object.autoUpdate=!1),t.object.levels=[];const n=this.levels;for(let i=0,s=n.length;i<s;i++){const a=n[i];t.object.levels.push({object:a.object.uuid,distance:a.distance,hysteresis:a.hysteresis})}return t}}const ZS=new J,YS=new Ei,JS=new Ei,NR=new J,KS=new Cr,Jy=new J,_C=new yl,qS=new Cr,$C=new Tv;class FR extends null{constructor(e,t){super(e,t),this.isSkinnedMesh=!0,this.type="SkinnedMesh",this.bindMode=v0,this.bindMatrix=new Cr,this.bindMatrixInverse=new Cr,this.boundingBox=null,this.boundingSphere=null}computeBoundingBox(){const e=this.geometry;this.boundingBox===null&&(this.boundingBox=new xl),this.boundingBox.makeEmpty();const t=e.getAttribute("position");for(let n=0;n<t.count;n++)this.getVertexPosition(n,Jy),this.boundingBox.expandByPoint(Jy)}computeBoundingSphere(){const e=this.geometry;this.boundingSphere===null&&(this.boundingSphere=new yl),this.boundingSphere.makeEmpty();const t=e.getAttribute("position");for(let n=0;n<t.count;n++)this.getVertexPosition(n,Jy),this.boundingSphere.expandByPoint(Jy)}copy(e,t){return super.copy(e,t),this.bindMode=e.bindMode,this.bindMatrix.copy(e.bindMatrix),this.bindMatrixInverse.copy(e.bindMatrixInverse),this.skeleton=e.skeleton,e.boundingBox!==null&&(this.boundingBox=e.boundingBox.clone()),e.boundingSphere!==null&&(this.boundingSphere=e.boundingSphere.clone()),this}raycast(e,t){const n=this.material,i=this.matrixWorld;n!==void 0&&(this.boundingSphere===null&&this.computeBoundingSphere(),_C.copy(this.boundingSphere),_C.applyMatrix4(i),e.ray.intersectsSphere(_C)!==!1&&(qS.copy(i).invert(),$C.copy(e.ray).applyMatrix4(qS),!(this.boundingBox!==null&&$C.intersectsBox(this.boundingBox)===!1)&&this._computeIntersections(e,t,$C)))}getVertexPosition(e,t){return super.getVertexPosition(e,t),this.applyBoneTransform(e,t),t}bind(e,t){this.skeleton=e,t===void 0&&(this.updateMatrixWorld(!0),this.skeleton.calculateInverses(),t=this.matrixWorld),this.bindMatrix.copy(t),this.bindMatrixInverse.copy(t).invert()}pose(){this.skeleton.pose()}normalizeSkinWeights(){const e=new Ei,t=this.geometry.attributes.skinWeight;for(let n=0,i=t.count;n<i;n++){e.fromBufferAttribute(t,n);const s=1/e.manhattanLength();s!==1/0?e.multiplyScalar(s):e.set(1,0,0,0),t.setXYZW(n,e.x,e.y,e.z,e.w)}}updateMatrixWorld(e){super.updateMatrixWorld(e),this.bindMode===v0?this.bindMatrixInverse.copy(this.matrixWorld).invert():this.bindMode===ls?this.bindMatrixInverse.copy(this.bindMatrix).invert():ze("SkinnedMesh: Unrecognized bindMode: "+this.bindMode)}applyBoneTransform(e,t){const n=this.skeleton,i=this.geometry;YS.fromBufferAttribute(i.attributes.skinIndex,e),JS.fromBufferAttribute(i.attributes.skinWeight,e),ZS.copy(t).applyMatrix4(this.bindMatrix),t.set(0,0,0);for(let s=0;s<4;s++){const a=JS.getComponent(s);if(a!==0){const o=YS.getComponent(s);KS.multiplyMatrices(n.bones[o].matrixWorld,n.boneInverses[o]),t.addScaledVector(NR.copy(ZS).applyMatrix4(KS),a)}}return t.applyMatrix4(this.bindMatrixInverse)}}class _S extends null{constructor(){super(),this.isBone=!0,this.type="Bone"}}class Sc extends yo{constructor(e=null,t=1,n=1,i,s,a,o,l,u=Cs,c=Cs,d,f){super(null,a,o,l,u,c,i,s,d,f),this.isDataTexture=!0,this.image={data:e,width:t,height:n},this.generateMipmaps=!1,this.flipY=!1,this.unpackAlignment=1}}const $S=new Cr,RR=new Cr;class e1{constructor(e=[],t=[]){this.uuid=Ga(),this.bones=e.slice(0),this.boneInverses=t,this.boneMatrices=null,this.previousBoneMatrices=null,this.boneTexture=null,this.init()}init(){const e=this.bones,t=this.boneInverses;if(this.boneMatrices=new Float32Array(e.length*16),t.length===0)this.calculateInverses();else if(e.length!==t.length){ze("Skeleton: Number of inverse bone matrices does not match amount of bones."),this.boneInverses=[];for(let n=0,i=this.bones.length;n<i;n++)this.boneInverses.push(new Cr)}}calculateInverses(){this.boneInverses.length=0;for(let e=0,t=this.bones.length;e<t;e++){const n=new Cr;this.bones[e]&&n.copy(this.bones[e].matrixWorld).invert(),this.boneInverses.push(n)}}pose(){for(let e=0,t=this.bones.length;e<t;e++){const n=this.bones[e];n&&n.matrixWorld.copy(this.boneInverses[e]).invert()}for(let e=0,t=this.bones.length;e<t;e++){const n=this.bones[e];n&&(n.parent&&n.parent.isBone?(n.matrix.copy(n.parent.matrixWorld).invert(),n.matrix.multiply(n.matrixWorld)):n.matrix.copy(n.matrixWorld),n.matrix.decompose(n.position,n.quaternion,n.scale))}}update(){const e=this.bones,t=this.boneInverses,n=this.boneMatrices,i=this.boneTexture;for(let s=0,a=e.length;s<a;s++){const o=e[s]?e[s].matrixWorld:RR;$S.multiplyMatrices(o,t[s]),$S.toArray(n,s*16)}i!==null&&(i.needsUpdate=!0)}clone(){return new e1(this.bones,this.boneInverses)}computeBoneTexture(){let e=Math.sqrt(this.bones.length*4);e=Math.ceil(e/4)*4,e=Math.max(e,4);const t=new Float32Array(e*e*4);t.set(this.boneMatrices);const n=new Sc(t,e,e,ma,ha);return n.needsUpdate=!0,this.boneMatrices=t,this.boneTexture=n,this}getBoneByName(e){for(let t=0,n=this.bones.length;t<n;t++){const i=this.bones[t];if(i.name===e)return i}}dispose(){this.boneTexture!==null&&(this.boneTexture.dispose(),this.boneTexture=null)}fromJSON(e,t){this.uuid=e.uuid;for(let n=0,i=e.bones.length;n<i;n++){const s=e.bones[n];let a=t[s];a===void 0&&(ze("Skeleton: No bone found with UUID:",s),a=new _S),this.bones.push(a),this.boneInverses.push(new Cr().fromArray(e.boneInverses[n]))}return this.init(),this}toJSON(){const e={metadata:{version:4.7,type:"Skeleton",generator:"Skeleton.toJSON"},bones:[],boneInverses:[]};e.uuid=this.uuid;const t=this.bones,n=this.boneInverses;for(let i=0,s=t.length;i<s;i++){const a=t[i];e.bones.push(a.uuid);const o=n[i];e.boneInverses.push(o.toArray())}return e}}class gd extends ga{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 Gv=new Cr,e5=new Cr,Ky=null,t5=new xl,LR=new Cr,H0=new Gs,U0=new yl;class OR extends null{constructor(e,t,n){super(e,t),this.isInstancedMesh=!0,this.instanceMatrix=new gd(new Float32Array(n*16),16),this.instanceColor=null,this.morphTexture=null,this.count=n,this.boundingBox=null,this.boundingSphere=null;for(let i=0;i<n;i++)this.setMatrixAt(i,LR)}computeBoundingBox(){const e=this.geometry,t=this.count;this.boundingBox===null&&(this.boundingBox=new xl),e.boundingBox===null&&e.computeBoundingBox(),this.boundingBox.makeEmpty();for(let n=0;n<t;n++)this.getMatrixAt(n,Gv),t5.copy(e.boundingBox).applyMatrix4(Gv),this.boundingBox.union(t5)}computeBoundingSphere(){const e=this.geometry,t=this.count;this.boundingSphere===null&&(this.boundingSphere=new yl),e.boundingSphere===null&&e.computeBoundingSphere(),this.boundingSphere.makeEmpty();for(let n=0;n<t;n++)this.getMatrixAt(n,Gv),U0.copy(e.boundingSphere).applyMatrix4(Gv),this.boundingSphere.union(U0)}copy(e,t){return super.copy(e,t),this.instanceMatrix.copy(e.instanceMatrix),e.morphTexture!==null&&(this.morphTexture=e.morphTexture.clone()),e.instanceColor!==null&&(this.instanceColor=e.instanceColor.clone()),this.count=e.count,e.boundingBox!==null&&(this.boundingBox=e.boundingBox.clone()),e.boundingSphere!==null&&(this.boundingSphere=e.boundingSphere.clone()),this}getColorAt(e,t){t.fromArray(this.instanceColor.array,e*3)}getMatrixAt(e,t){t.fromArray(this.instanceMatrix.array,e*16)}getMorphAt(e,t){const n=t.morphTargetInfluences,i=this.morphTexture.source.data.data,s=n.length+1,a=e*s+1;for(let o=0;o<n.length;o++)n[o]=i[a+o]}raycast(e,t){const n=this.matrixWorld,i=this.count;if(H0.geometry=this.geometry,H0.material=this.material,H0.material!==void 0&&(this.boundingSphere===null&&this.computeBoundingSphere(),U0.copy(this.boundingSphere),U0.applyMatrix4(n),e.ray.intersectsSphere(U0)!==!1))for(let s=0;s<i;s++){this.getMatrixAt(s,Gv),e5.multiplyMatrices(n,Gv),H0.matrixWorld=e5,H0.raycast(e,Ky);for(let a=0,o=Ky.length;a<o;a++){const l=Ky[a];l.instanceId=s,l.object=this,t.push(l)}Ky.length=0}}setColorAt(e,t){this.instanceColor===null&&(this.instanceColor=new gd(new Float32Array(this.instanceMatrix.count*3).fill(1),3)),t.toArray(this.instanceColor.array,e*3)}setMatrixAt(e,t){t.toArray(this.instanceMatrix.array,e*16)}setMorphAt(e,t){const n=t.morphTargetInfluences,i=n.length+1;this.morphTexture===null&&(this.morphTexture=new Sc(new Float32Array(i*this.count),i,this.count,_h,ha));const s=this.morphTexture.source.data.data;let a=0;for(let u=0;u<n.length;u++)a+=n[u];const o=this.geometry.morphTargetsRelative?1:1-a,l=i*e;s[l]=o,s.set(n,l+1)}updateMorphTargets(){}dispose(){this.dispatchEvent({type:"dispose"}),this.morphTexture!==null&&(this.morphTexture.dispose(),this.morphTexture=null)}}const t1=new J,zR=new J,HR=new zi;class vd{constructor(e=new J(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=t1.subVectors(n,t).cross(zR.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(t1),i=this.normal.dot(n);if(i===0)return this.distanceToPoint(e.start)===0?t.copy(e.start):null;const s=-(e.start.dot(this.normal)+this.constant)/i;return s<0||s>1?null:t.copy(e.start).addScaledVector(n,s)}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||HR.getNormalMatrix(e),i=this.coplanarPoint(t1).applyMatrix4(e),s=this.normal.applyMatrix3(n).normalize();return this.constant=-i.dot(s),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 Xm=new yl,UR=new ct(.5,.5),qy=new J;class Wv{constructor(e=new vd,t=new vd,n=new vd,i=new vd,s=new vd,a=new vd){this.planes=[e,t,n,i,s,a]}set(e,t,n,i,s,a){const o=this.planes;return o[0].copy(e),o[1].copy(t),o[2].copy(n),o[3].copy(i),o[4].copy(s),o[5].copy(a),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=Gt,n=!1){const i=this.planes,s=e.elements,a=s[0],o=s[1],l=s[2],u=s[3],c=s[4],d=s[5],f=s[6],h=s[7],p=s[8],x=s[9],v=s[10],m=s[11],C=s[12],w=s[13],P=s[14],B=s[15];if(i[0].setComponents(u-a,h-c,m-p,B-C).normalize(),i[1].setComponents(u+a,h+c,m+p,B+C).normalize(),i[2].setComponents(u+o,h+d,m+x,B+w).normalize(),i[3].setComponents(u-o,h-d,m-x,B-w).normalize(),n)i[4].setComponents(l,f,v,P).normalize(),i[5].setComponents(u-l,h-f,m-v,B-P).normalize();else if(i[4].setComponents(u-l,h-f,m-v,B-P).normalize(),t===Gt)i[5].setComponents(u+l,h+f,m+v,B+P).normalize();else if(t===gn)i[5].setComponents(l,f,v,P).normalize();else throw new Error("THREE.Frustum.setFromProjectionMatrix(): Invalid coordinate system: "+t);return this}intersectsObject(e){if(e.boundingSphere!==void 0)e.boundingSphere===null&&e.computeBoundingSphere(),Xm.copy(e.boundingSphere).applyMatrix4(e.matrixWorld);else{const t=e.geometry;t.boundingSphere===null&&t.computeBoundingSphere(),Xm.copy(t.boundingSphere).applyMatrix4(e.matrixWorld)}return this.intersectsSphere(Xm)}intersectsSprite(e){Xm.center.set(0,0,0);const t=UR.distanceTo(e.center);return Xm.radius=.7071067811865476+t,Xm.applyMatrix4(e.matrixWorld),this.intersectsSphere(Xm)}intersectsSphere(e){const t=this.planes,n=e.center,i=-e.radius;for(let s=0;s<6;s++)if(t[s].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(qy.x=i.normal.x>0?e.max.x:e.min.x,qy.y=i.normal.y>0?e.max.y:e.min.y,qy.z=i.normal.z>0?e.max.z:e.min.z,i.distanceToPoint(qy)<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 lf=new Cr,uf=new Wv;class _y{constructor(){this.coordinateSystem=Gt}intersectsObject(e,t){if(!t.isArrayCamera||t.cameras.length===0)return!1;for(let n=0;n<t.cameras.length;n++){const i=t.cameras[n];if(lf.multiplyMatrices(i.projectionMatrix,i.matrixWorldInverse),uf.setFromProjectionMatrix(lf,i.coordinateSystem,i.reversedDepth),uf.intersectsObject(e))return!0}return!1}intersectsSprite(e,t){if(!t||!t.cameras||t.cameras.length===0)return!1;for(let n=0;n<t.cameras.length;n++){const i=t.cameras[n];if(lf.multiplyMatrices(i.projectionMatrix,i.matrixWorldInverse),uf.setFromProjectionMatrix(lf,i.coordinateSystem,i.reversedDepth),uf.intersectsSprite(e))return!0}return!1}intersectsSphere(e,t){if(!t||!t.cameras||t.cameras.length===0)return!1;for(let n=0;n<t.cameras.length;n++){const i=t.cameras[n];if(lf.multiplyMatrices(i.projectionMatrix,i.matrixWorldInverse),uf.setFromProjectionMatrix(lf,i.coordinateSystem,i.reversedDepth),uf.intersectsSphere(e))return!0}return!1}intersectsBox(e,t){if(!t||!t.cameras||t.cameras.length===0)return!1;for(let n=0;n<t.cameras.length;n++){const i=t.cameras[n];if(lf.multiplyMatrices(i.projectionMatrix,i.matrixWorldInverse),uf.setFromProjectionMatrix(lf,i.coordinateSystem,i.reversedDepth),uf.intersectsBox(e))return!0}return!1}containsPoint(e,t){if(!t||!t.cameras||t.cameras.length===0)return!1;for(let n=0;n<t.cameras.length;n++){const i=t.cameras[n];if(lf.multiplyMatrices(i.projectionMatrix,i.matrixWorldInverse),uf.setFromProjectionMatrix(lf,i.coordinateSystem,i.reversedDepth),uf.containsPoint(e))return!0}return!1}clone(){return new _y}}function n1(r,e){return r-e}function kR(r,e){return r.z-e.z}function VR(r,e){return e.z-r.z}class jR{constructor(){this.index=0,this.pool=[],this.list=[]}push(e,t,n,i){const s=this.pool,a=this.list;this.index>=s.length&&s.push({start:-1,count:-1,z:-1,index:-1});const o=s[this.index];a.push(o),this.index++,o.start=e,o.count=t,o.z=n,o.index=i}reset(){this.list.length=0,this.index=0}}const wu=new Cr,XR=new Vn(1,1,1),n5=new Wv,GR=new _y,$y=new xl,Gm=new yl,k0=new J,r5=new J,WR=new J,r1=new jR,Ul=new Gs,eb=null;function QR(r,e,t=0){const n=e.itemSize;if(r.isInterleavedBufferAttribute||r.array.constructor!==e.array.constructor){const i=r.count;for(let s=0;s<i;s++)for(let a=0;a<n;a++)e.setComponent(s+t,a,r.getComponent(s,a))}else e.array.set(r.array,t*n);e.needsUpdate=!0}function Wm(r,e){if(r.constructor!==e.constructor){const t=Math.min(r.length,e.length);for(let n=0;n<t;n++)e[n]=r[n]}else{const t=Math.min(r.length,e.length);e.set(new r.constructor(r.buffer,0,t))}}class ZR extends null{constructor(e,t,n=t*2,i){super(new Ni,i),this.isBatchedMesh=!0,this.perObjectFrustumCulled=!0,this.sortObjects=!0,this.boundingBox=null,this.boundingSphere=null,this.customSort=null,this._instanceInfo=[],this._geometryInfo=[],this._availableInstanceIds=[],this._availableGeometryIds=[],this._nextIndexStart=0,this._nextVertexStart=0,this._geometryCount=0,this._visibilityChanged=!0,this._geometryInitialized=!1,this._maxInstanceCount=e,this._maxVertexCount=t,this._maxIndexCount=n,this._multiDrawCounts=new Int32Array(e),this._multiDrawStarts=new Int32Array(e),this._multiDrawCount=0,this._multiDrawInstances=null,this._matricesTexture=null,this._indirectTexture=null,this._colorsTexture=null,this._initMatricesTexture(),this._initIndirectTexture()}get maxInstanceCount(){return this._maxInstanceCount}get instanceCount(){return this._instanceInfo.length-this._availableInstanceIds.length}get unusedVertexCount(){return this._maxVertexCount-this._nextVertexStart}get unusedIndexCount(){return this._maxIndexCount-this._nextIndexStart}_initMatricesTexture(){let e=Math.sqrt(this._maxInstanceCount*4);e=Math.ceil(e/4)*4,e=Math.max(e,4);const t=new Float32Array(e*e*4),n=new Sc(t,e,e,ma,ha);this._matricesTexture=n}_initIndirectTexture(){let e=Math.sqrt(this._maxInstanceCount);e=Math.ceil(e);const t=new Uint32Array(e*e),n=new Sc(t,e,e,Kf,Ls);this._indirectTexture=n}_initColorsTexture(){let e=Math.sqrt(this._maxInstanceCount);e=Math.ceil(e);const t=new Float32Array(e*e*4).fill(1),n=new Sc(t,e,e,ma,ha);n.colorSpace=$r.workingColorSpace,this._colorsTexture=n}_initializeGeometry(e){const t=this.geometry,n=this._maxVertexCount,i=this._maxIndexCount;if(this._geometryInitialized===!1){for(const s in e.attributes){const a=e.getAttribute(s),{array:o,itemSize:l,normalized:u}=a,c=new o.constructor(n*l),d=new ga(c,l,u);t.setAttribute(s,d)}if(e.getIndex()!==null){const s=n>65535?new Uint32Array(i):new Uint16Array(i);t.setIndex(new ga(s,1))}this._geometryInitialized=!0}}_validateGeometry(e){const t=this.geometry;if(!!e.getIndex()!=!!t.getIndex())throw new Error('THREE.BatchedMesh: All geometries must consistently have "index".');for(const n in t.attributes){if(!e.hasAttribute(n))throw new Error(`THREE.BatchedMesh: Added geometry missing "${n}". All geometries must have consistent attributes.`);const i=e.getAttribute(n),s=t.getAttribute(n);if(i.itemSize!==s.itemSize||i.normalized!==s.normalized)throw new Error("THREE.BatchedMesh: All attributes must have a consistent itemSize and normalized value.")}}validateInstanceId(e){const t=this._instanceInfo;if(e<0||e>=t.length||t[e].active===!1)throw new Error(`THREE.BatchedMesh: Invalid instanceId ${e}. Instance is either out of range or has been deleted.`)}validateGeometryId(e){const t=this._geometryInfo;if(e<0||e>=t.length||t[e].active===!1)throw new Error(`THREE.BatchedMesh: Invalid geometryId ${e}. Geometry is either out of range or has been deleted.`)}setCustomSort(e){return this.customSort=e,this}computeBoundingBox(){this.boundingBox===null&&(this.boundingBox=new xl);const e=this.boundingBox,t=this._instanceInfo;e.makeEmpty();for(let n=0,i=t.length;n<i;n++){if(t[n].active===!1)continue;const s=t[n].geometryIndex;this.getMatrixAt(n,wu),this.getBoundingBoxAt(s,$y).applyMatrix4(wu),e.union($y)}}computeBoundingSphere(){this.boundingSphere===null&&(this.boundingSphere=new yl);const e=this.boundingSphere,t=this._instanceInfo;e.makeEmpty();for(let n=0,i=t.length;n<i;n++){if(t[n].active===!1)continue;const s=t[n].geometryIndex;this.getMatrixAt(n,wu),this.getBoundingSphereAt(s,Gm).applyMatrix4(wu),e.union(Gm)}}addInstance(e){if(this._instanceInfo.length>=this.maxInstanceCount&&this._availableInstanceIds.length===0)throw new Error("THREE.BatchedMesh: Maximum item count reached.");const n={visible:!0,active:!0,geometryIndex:e};let i=null;this._availableInstanceIds.length>0?(this._availableInstanceIds.sort(n1),i=this._availableInstanceIds.shift(),this._instanceInfo[i]=n):(i=this._instanceInfo.length,this._instanceInfo.push(n));const s=this._matricesTexture;wu.identity().toArray(s.image.data,i*16),s.needsUpdate=!0;const a=this._colorsTexture;return a&&(XR.toArray(a.image.data,i*4),a.needsUpdate=!0),this._visibilityChanged=!0,i}addGeometry(e,t=-1,n=-1){this._initializeGeometry(e),this._validateGeometry(e);const i={vertexStart:-1,vertexCount:-1,reservedVertexCount:-1,indexStart:-1,indexCount:-1,reservedIndexCount:-1,start:-1,count:-1,boundingBox:null,boundingSphere:null,active:!0},s=this._geometryInfo;i.vertexStart=this._nextVertexStart,i.reservedVertexCount=t===-1?e.getAttribute("position").count:t;const a=e.getIndex();if(a!==null&&(i.indexStart=this._nextIndexStart,i.reservedIndexCount=n===-1?a.count:n),i.indexStart!==-1&&i.indexStart+i.reservedIndexCount>this._maxIndexCount||i.vertexStart+i.reservedVertexCount>this._maxVertexCount)throw new Error("THREE.BatchedMesh: Reserved space request exceeds the maximum buffer size.");let l;return this._availableGeometryIds.length>0?(this._availableGeometryIds.sort(n1),l=this._availableGeometryIds.shift(),s[l]=i):(l=this._geometryCount,this._geometryCount++,s.push(i)),this.setGeometryAt(l,e),this._nextIndexStart=i.indexStart+i.reservedIndexCount,this._nextVertexStart=i.vertexStart+i.reservedVertexCount,l}setGeometryAt(e,t){if(e>=this._geometryCount)throw new Error("THREE.BatchedMesh: Maximum geometry count reached.");this._validateGeometry(t);const n=this.geometry,i=n.getIndex()!==null,s=n.getIndex(),a=t.getIndex(),o=this._geometryInfo[e];if(i&&a.count>o.reservedIndexCount||t.attributes.position.count>o.reservedVertexCount)throw new Error("THREE.BatchedMesh: Reserved space not large enough for provided geometry.");const l=o.vertexStart,u=o.reservedVertexCount;o.vertexCount=t.getAttribute("position").count;for(const c in n.attributes){const d=t.getAttribute(c),f=n.getAttribute(c);QR(d,f,l);const h=d.itemSize;for(let p=d.count,x=u;p<x;p++){const v=l+p;for(let m=0;m<h;m++)f.setComponent(v,m,0)}f.needsUpdate=!0,f.addUpdateRange(l*h,u*h)}if(i){const c=o.indexStart,d=o.reservedIndexCount;o.indexCount=t.getIndex().count;for(let f=0;f<a.count;f++)s.setX(c+f,l+a.getX(f));for(let f=a.count,h=d;f<h;f++)s.setX(c+f,l);s.needsUpdate=!0,s.addUpdateRange(c,o.reservedIndexCount)}return o.start=i?o.indexStart:o.vertexStart,o.count=i?o.indexCount:o.vertexCount,o.boundingBox=null,t.boundingBox!==null&&(o.boundingBox=t.boundingBox.clone()),o.boundingSphere=null,t.boundingSphere!==null&&(o.boundingSphere=t.boundingSphere.clone()),this._visibilityChanged=!0,e}deleteGeometry(e){const t=this._geometryInfo;if(e>=t.length||t[e].active===!1)return this;const n=this._instanceInfo;for(let i=0,s=n.length;i<s;i++)n[i].active&&n[i].geometryIndex===e&&this.deleteInstance(i);return t[e].active=!1,this._availableGeometryIds.push(e),this._visibilityChanged=!0,this}deleteInstance(e){return this.validateInstanceId(e),this._instanceInfo[e].active=!1,this._availableInstanceIds.push(e),this._visibilityChanged=!0,this}optimize(){let e=0,t=0;const n=this._geometryInfo,i=n.map((a,o)=>o).sort((a,o)=>n[a].vertexStart-n[o].vertexStart),s=this.geometry;for(let a=0,o=n.length;a<o;a++){const l=i[a],u=n[l];if(u.active!==!1){if(s.index!==null){if(u.indexStart!==t){const{indexStart:c,vertexStart:d,reservedIndexCount:f}=u,h=s.index,p=h.array,x=e-d;for(let v=c;v<c+f;v++)p[v]=p[v]+x;h.array.copyWithin(t,c,c+f),h.addUpdateRange(t,f),h.needsUpdate=!0,u.indexStart=t}t+=u.reservedIndexCount}if(u.vertexStart!==e){const{vertexStart:c,reservedVertexCount:d}=u,f=s.attributes;for(const h in f){const p=f[h],{array:x,itemSize:v}=p;x.copyWithin(e*v,c*v,(c+d)*v),p.addUpdateRange(e*v,d*v),p.needsUpdate=!0}u.vertexStart=e}e+=u.reservedVertexCount,u.start=s.index?u.indexStart:u.vertexStart,this._nextIndexStart=s.index?u.indexStart+u.reservedIndexCount:0,this._nextVertexStart=u.vertexStart+u.reservedVertexCount}}return this._visibilityChanged=!0,this}getBoundingBoxAt(e,t){if(e>=this._geometryCount)return null;const n=this.geometry,i=this._geometryInfo[e];if(i.boundingBox===null){const s=new xl,a=n.index,o=n.attributes.position;for(let l=i.start,u=i.start+i.count;l<u;l++){let c=l;a&&(c=a.getX(c)),s.expandByPoint(k0.fromBufferAttribute(o,c))}i.boundingBox=s}return t.copy(i.boundingBox),t}getBoundingSphereAt(e,t){if(e>=this._geometryCount)return null;const n=this.geometry,i=this._geometryInfo[e];if(i.boundingSphere===null){const s=new yl;this.getBoundingBoxAt(e,$y),$y.getCenter(s.center);const a=n.index,o=n.attributes.position;let l=0;for(let u=i.start,c=i.start+i.count;u<c;u++){let d=u;a&&(d=a.getX(d)),k0.fromBufferAttribute(o,d),l=Math.max(l,s.center.distanceToSquared(k0))}s.radius=Math.sqrt(l),i.boundingSphere=s}return t.copy(i.boundingSphere),t}setMatrixAt(e,t){this.validateInstanceId(e);const n=this._matricesTexture,i=this._matricesTexture.image.data;return t.toArray(i,e*16),n.needsUpdate=!0,this}getMatrixAt(e,t){return this.validateInstanceId(e),t.fromArray(this._matricesTexture.image.data,e*16)}setColorAt(e,t){return this.validateInstanceId(e),this._colorsTexture===null&&this._initColorsTexture(),t.toArray(this._colorsTexture.image.data,e*4),this._colorsTexture.needsUpdate=!0,this}getColorAt(e,t){return this.validateInstanceId(e),t.fromArray(this._colorsTexture.image.data,e*4)}setVisibleAt(e,t){return this.validateInstanceId(e),this._instanceInfo[e].visible===t?this:(this._instanceInfo[e].visible=t,this._visibilityChanged=!0,this)}getVisibleAt(e){return this.validateInstanceId(e),this._instanceInfo[e].visible}setGeometryIdAt(e,t){return this.validateInstanceId(e),this.validateGeometryId(t),this._instanceInfo[e].geometryIndex=t,this}getGeometryIdAt(e){return this.validateInstanceId(e),this._instanceInfo[e].geometryIndex}getGeometryRangeAt(e,t={}){this.validateGeometryId(e);const n=this._geometryInfo[e];return t.vertexStart=n.vertexStart,t.vertexCount=n.vertexCount,t.reservedVertexCount=n.reservedVertexCount,t.indexStart=n.indexStart,t.indexCount=n.indexCount,t.reservedIndexCount=n.reservedIndexCount,t.start=n.start,t.count=n.count,t}setInstanceCount(e){const t=this._availableInstanceIds,n=this._instanceInfo;for(t.sort(n1);t[t.length-1]===n.length-1;)n.pop(),t.pop();if(e<n.length)throw new Error(`BatchedMesh: Instance ids outside the range ${e} are being used. Cannot shrink instance count.`);const i=new Int32Array(e),s=new Int32Array(e);Wm(this._multiDrawCounts,i),Wm(this._multiDrawStarts,s),this._multiDrawCounts=i,this._multiDrawStarts=s,this._maxInstanceCount=e;const a=this._indirectTexture,o=this._matricesTexture,l=this._colorsTexture;a.dispose(),this._initIndirectTexture(),Wm(a.image.data,this._indirectTexture.image.data),o.dispose(),this._initMatricesTexture(),Wm(o.image.data,this._matricesTexture.image.data),l&&(l.dispose(),this._initColorsTexture(),Wm(l.image.data,this._colorsTexture.image.data))}setGeometrySize(e,t){const n=[...this._geometryInfo].filter(o=>o.active);if(Math.max(...n.map(o=>o.vertexStart+o.reservedVertexCount))>e)throw new Error(`BatchedMesh: Geometry vertex values are being used outside the range ${t}. Cannot shrink further.`);if(this.geometry.index&&Math.max(...n.map(l=>l.indexStart+l.reservedIndexCount))>t)throw new Error(`BatchedMesh: Geometry index values are being used outside the range ${t}. Cannot shrink further.`);const s=this.geometry;s.dispose(),this._maxVertexCount=e,this._maxIndexCount=t,this._geometryInitialized&&(this._geometryInitialized=!1,this.geometry=new Ni,this._initializeGeometry(s));const a=this.geometry;s.index&&Wm(s.index.array,a.index.array);for(const o in s.attributes)Wm(s.attributes[o].array,a.attributes[o].array)}raycast(e,t){const n=this._instanceInfo,i=this._geometryInfo,s=this.matrixWorld,a=this.geometry;Ul.material=this.material,Ul.geometry.index=a.index,Ul.geometry.attributes=a.attributes,Ul.geometry.boundingBox===null&&(Ul.geometry.boundingBox=new xl),Ul.geometry.boundingSphere===null&&(Ul.geometry.boundingSphere=new yl);for(let o=0,l=n.length;o<l;o++){if(!n[o].visible||!n[o].active)continue;const u=n[o].geometryIndex,c=i[u];Ul.geometry.setDrawRange(c.start,c.count),this.getMatrixAt(o,Ul.matrixWorld).premultiply(s),this.getBoundingBoxAt(u,Ul.geometry.boundingBox),this.getBoundingSphereAt(u,Ul.geometry.boundingSphere),Ul.raycast(e,eb);for(let d=0,f=eb.length;d<f;d++){const h=eb[d];h.object=this,h.batchId=o,t.push(h)}eb.length=0}Ul.material=null,Ul.geometry.index=null,Ul.geometry.attributes={},Ul.geometry.setDrawRange(0,1/0)}copy(e){return super.copy(e),this.geometry=e.geometry.clone(),this.perObjectFrustumCulled=e.perObjectFrustumCulled,this.sortObjects=e.sortObjects,this.boundingBox=e.boundingBox!==null?e.boundingBox.clone():null,this.boundingSphere=e.boundingSphere!==null?e.boundingSphere.clone():null,this._geometryInfo=e._geometryInfo.map(t=>Gc(ba({},t),{boundingBox:t.boundingBox!==null?t.boundingBox.clone():null,boundingSphere:t.boundingSphere!==null?t.boundingSphere.clone():null})),this._instanceInfo=e._instanceInfo.map(t=>ba({},t)),this._availableInstanceIds=e._availableInstanceIds.slice(),this._availableGeometryIds=e._availableGeometryIds.slice(),this._nextIndexStart=e._nextIndexStart,this._nextVertexStart=e._nextVertexStart,this._geometryCount=e._geometryCount,this._maxInstanceCount=e._maxInstanceCount,this._maxVertexCount=e._maxVertexCount,this._maxIndexCount=e._maxIndexCount,this._geometryInitialized=e._geometryInitialized,this._multiDrawCounts=e._multiDrawCounts.slice(),this._multiDrawStarts=e._multiDrawStarts.slice(),this._indirectTexture=e._indirectTexture.clone(),this._indirectTexture.image.data=this._indirectTexture.image.data.slice(),this._matricesTexture=e._matricesTexture.clone(),this._matricesTexture.image.data=this._matricesTexture.image.data.slice(),this._colorsTexture!==null&&(this._colorsTexture=e._colorsTexture.clone(),this._colorsTexture.image.data=this._colorsTexture.image.data.slice()),this}dispose(){this.geometry.dispose(),this._matricesTexture.dispose(),this._matricesTexture=null,this._indirectTexture.dispose(),this._indirectTexture=null,this._colorsTexture!==null&&(this._colorsTexture.dispose(),this._colorsTexture=null)}onBeforeRender(e,t,n,i,s){if(!this._visibilityChanged&&!this.perObjectFrustumCulled&&!this.sortObjects)return;const a=i.getIndex(),o=a===null?1:a.array.BYTES_PER_ELEMENT,l=this._instanceInfo,u=this._multiDrawStarts,c=this._multiDrawCounts,d=this._geometryInfo,f=this.perObjectFrustumCulled,h=this._indirectTexture,p=h.image.data,x=n.isArrayCamera?GR:n5;f&&!n.isArrayCamera&&(wu.multiplyMatrices(n.projectionMatrix,n.matrixWorldInverse).multiply(this.matrixWorld),n5.setFromProjectionMatrix(wu,n.coordinateSystem,n.reversedDepth));let v=0;if(this.sortObjects){wu.copy(this.matrixWorld).invert(),k0.setFromMatrixPosition(n.matrixWorld).applyMatrix4(wu),r5.set(0,0,-1).transformDirection(n.matrixWorld).transformDirection(wu);for(let w=0,P=l.length;w<P;w++)if(l[w].visible&&l[w].active){const B=l[w].geometryIndex;this.getMatrixAt(w,wu),this.getBoundingSphereAt(B,Gm).applyMatrix4(wu);let S=!1;if(f&&(S=!x.intersectsSphere(Gm,n)),!S){const I=d[B],N=WR.subVectors(Gm.center,k0).dot(r5);r1.push(I.start,I.count,N,w)}}const m=r1.list,C=this.customSort;C===null?m.sort(s.transparent?VR:kR):C.call(this,m,n);for(let w=0,P=m.length;w<P;w++){const B=m[w];u[v]=B.start*o,c[v]=B.count,p[v]=B.index,v++}r1.reset()}else for(let m=0,C=l.length;m<C;m++)if(l[m].visible&&l[m].active){const w=l[m].geometryIndex;let P=!1;if(f&&(this.getMatrixAt(m,wu),this.getBoundingSphereAt(w,Gm).applyMatrix4(wu),P=!x.intersectsSphere(Gm,n)),!P){const B=d[w];u[v]=B.start*o,c[v]=B.count,p[v]=m,v++}}h.needsUpdate=!0,this._multiDrawCount=v,this._visibilityChanged=!1}onBeforeShadow(e,t,n,i,s,a){this.onBeforeRender(e,null,i,s,a)}}class kl extends bl{constructor(e){super(),this.isLineBasicMaterial=!0,this.type="LineBasicMaterial",this.color=new Vn(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 tb=new J,nb=new J,i5=new Cr,V0=new Tv,rb=new yl,i1=new J,s5=new J;class j0 extends so{constructor(e=new Ni,t=new kl){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(e.index===null){const t=e.attributes.position,n=[0];for(let i=1,s=t.count;i<s;i++)tb.fromBufferAttribute(t,i-1),nb.fromBufferAttribute(t,i),n[i]=n[i-1],n[i]+=tb.distanceTo(nb);e.setAttribute("lineDistance",new yr(n,1))}else ze("Line.computeLineDistances(): Computation only possible with non-indexed BufferGeometry.");return this}raycast(e,t){const n=this.geometry,i=this.matrixWorld,s=e.params.Line.threshold,a=n.drawRange;if(n.boundingSphere===null&&n.computeBoundingSphere(),rb.copy(n.boundingSphere),rb.applyMatrix4(i),rb.radius+=s,e.ray.intersectsSphere(rb)===!1)return;i5.copy(i).invert(),V0.copy(e.ray).applyMatrix4(i5);const o=s/((this.scale.x+this.scale.y+this.scale.z)/3),l=o*o,u=this.isLineSegments?2:1,c=n.index,f=n.attributes.position;if(c!==null){const h=Math.max(0,a.start),p=Math.min(c.count,a.start+a.count);for(let x=h,v=p-1;x<v;x+=u){const m=c.getX(x),C=c.getX(x+1),w=ib(this,e,V0,l,m,C,x);w&&t.push(w)}if(this.isLineLoop){const x=c.getX(p-1),v=c.getX(h),m=ib(this,e,V0,l,x,v,p-1);m&&t.push(m)}}else{const h=Math.max(0,a.start),p=Math.min(f.count,a.start+a.count);for(let x=h,v=p-1;x<v;x+=u){const m=ib(this,e,V0,l,x,x+1,x);m&&t.push(m)}if(this.isLineLoop){const x=ib(this,e,V0,l,p-1,h,p-1);x&&t.push(x)}}}updateMorphTargets(){const t=this.geometry.morphAttributes,n=Object.keys(t);if(n.length>0){const i=t[n[0]];if(i!==void 0){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let s=0,a=i.length;s<a;s++){const o=i[s].name||String(s);this.morphTargetInfluences.push(0),this.morphTargetDictionary[o]=s}}}}}function ib(r,e,t,n,i,s,a){const o=r.geometry.attributes.position;if(tb.fromBufferAttribute(o,i),nb.fromBufferAttribute(o,s),t.distanceSqToSegment(tb,nb,i1,s5)>n)return;i1.applyMatrix4(r.matrixWorld);const u=e.ray.origin.distanceTo(i1);if(!(u<e.near||u>e.far))return{distance:u,point:s5.clone().applyMatrix4(r.matrixWorld),index:a,face:null,faceIndex:null,barycoord:null,object:r}}const a5=new J,o5=new J;class l5 extends null{constructor(e,t){super(e,t),this.isLineSegments=!0,this.type="LineSegments"}computeLineDistances(){const e=this.geometry;if(e.index===null){const t=e.attributes.position,n=[];for(let i=0,s=t.count;i<s;i+=2)a5.fromBufferAttribute(t,i),o5.fromBufferAttribute(t,i+1),n[i]=i===0?0:n[i-1],n[i+1]=n[i]+a5.distanceTo(o5);e.setAttribute("lineDistance",new yr(n,1))}else ze("LineSegments.computeLineDistances(): Computation only possible with non-indexed BufferGeometry.");return this}}class YR extends null{constructor(e,t){super(e,t),this.isLineLoop=!0,this.type="LineLoop"}}class s1 extends bl{constructor(e){super(),this.isPointsMaterial=!0,this.type="PointsMaterial",this.color=new Vn(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}}const u5=new Cr,a1=new Tv,sb=new yl,ab=new J;class JR extends null{constructor(e=new Ni,t=new s1){super(),this.isPoints=!0,this.type="Points",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}raycast(e,t){const n=this.geometry,i=this.matrixWorld,s=e.params.Points.threshold,a=n.drawRange;if(n.boundingSphere===null&&n.computeBoundingSphere(),sb.copy(n.boundingSphere),sb.applyMatrix4(i),sb.radius+=s,e.ray.intersectsSphere(sb)===!1)return;u5.copy(i).invert(),a1.copy(e.ray).applyMatrix4(u5);const o=s/((this.scale.x+this.scale.y+this.scale.z)/3),l=o*o,u=n.index,d=n.attributes.position;if(u!==null){const f=Math.max(0,a.start),h=Math.min(u.count,a.start+a.count);for(let p=f,x=h;p<x;p++){const v=u.getX(p);ab.fromBufferAttribute(d,v),c5(ab,v,l,i,e,t,this)}}else{const f=Math.max(0,a.start),h=Math.min(d.count,a.start+a.count);for(let p=f,x=h;p<x;p++)ab.fromBufferAttribute(d,p),c5(ab,p,l,i,e,t,this)}}updateMorphTargets(){const t=this.geometry.morphAttributes,n=Object.keys(t);if(n.length>0){const i=t[n[0]];if(i!==void 0){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let s=0,a=i.length;s<a;s++){const o=i[s].name||String(s);this.morphTargetInfluences.push(0),this.morphTargetDictionary[o]=s}}}}}function c5(r,e,t,n,i,s,a){const o=a1.distanceSqToPoint(r);if(o<t){const l=new J;a1.closestPointToPoint(r,l),l.applyMatrix4(n);const u=i.ray.origin.distanceTo(l);if(u<i.near||u>i.far)return;s.push({distance:u,distanceToRay:Math.sqrt(o),point:l,index:e,face:null,faceIndex:null,barycoord:null,object:a})}}class ece extends null{constructor(e,t,n,i,s=ms,a=ms,o,l,u){super(e,t,n,i,s,a,o,l,u),this.isVideoTexture=!0,this.generateMipmaps=!1,this._requestVideoFrameCallbackId=0;const c=this;function d(){c.needsUpdate=!0,c._requestVideoFrameCallbackId=e.requestVideoFrameCallback(d)}"requestVideoFrameCallback"in e&&(this._requestVideoFrameCallbackId=e.requestVideoFrameCallback(d))}clone(){return new this.constructor(this.image).copy(this)}update(){const e=this.image;"requestVideoFrameCallback"in e===!1&&e.readyState>=e.HAVE_CURRENT_DATA&&(this.needsUpdate=!0)}dispose(){this._requestVideoFrameCallbackId!==0&&(this.source.data.cancelVideoFrameCallback(this._requestVideoFrameCallbackId),this._requestVideoFrameCallbackId=0),super.dispose()}}class tce extends null{constructor(e,t,n,i,s,a,o,l){super({},e,t,n,i,s,a,o,l),this.isVideoFrameTexture=!0}update(){}clone(){return new this.constructor().copy(this)}setFrame(e){this.image=e,this.needsUpdate=!0}}class o1 extends yo{constructor(e,t){super({width:e,height:t}),this.isFramebufferTexture=!0,this.magFilter=Cs,this.minFilter=Cs,this.generateMipmaps=!1,this.needsUpdate=!0}}class KR extends null{constructor(e,t,n,i,s,a,o,l,u,c,d,f){super(null,a,o,l,u,c,i,s,d,f),this.isCompressedTexture=!0,this.image={width:t,height:n},this.mipmaps=e,this.flipY=!1,this.generateMipmaps=!1}}class nce extends null{constructor(e,t,n,i,s,a){super(e,t,n,s,a),this.isCompressedArrayTexture=!0,this.image.depth=i,this.wrapR=So,this.layerUpdates=new Set}addLayerUpdate(e){this.layerUpdates.add(e)}clearLayerUpdates(){this.layerUpdates.clear()}}class rce extends null{constructor(e,t,n){super(void 0,e[0].width,e[0].height,t,n,ai),this.isCompressedCubeTexture=!0,this.isCubeTexture=!0,this.image=e}}class ice extends null{constructor(e,t,n,i,s,a,o,l,u){super(e,t,n,i,s,a,o,l,u),this.isCanvasTexture=!0,this.needsUpdate=!0}}class Vl extends yo{constructor(e,t,n=Ls,i,s,a,o=Cs,l=Cs,u,c=jo,d=1){if(c!==jo&&c!==vl)throw new Error("DepthTexture format must be either THREE.DepthFormat or THREE.DepthStencilFormat");const f={width:e,height:t,depth:d};super(f,i,s,a,o,l,c,n,u),this.isDepthTexture=!0,this.flipY=!1,this.generateMipmaps=!1,this.compareFunction=null}copy(e){return super.copy(e),this.source=new Om(Object.assign({},e.image)),this.compareFunction=e.compareFunction,this}toJSON(e){const t=super.toJSON(e);return this.compareFunction!==null&&(t.compareFunction=this.compareFunction),t}}class d5 extends Vl{constructor(e,t=Ls,n=ai,i,s,a=Cs,o=Cs,l,u=jo){const c={width:e,height:e,depth:1},d=[c,c,c,c,c,c];super(e,e,t,n,i,s,a,o,l,u),this.image=d,this.isCubeDepthTexture=!0,this.isCubeTexture=!0}get images(){return this.image}set images(e){this.image=e}}class f5 extends yo{constructor(e=null){super(),this.sourceTexture=e,this.isExternalTexture=!0}copy(e){return super.copy(e),this.sourceTexture=e.sourceTexture,this}}class l1 extends Ni{constructor(e=1,t=1,n=4,i=8,s=1){super(),this.type="CapsuleGeometry",this.parameters={radius:e,height:t,capSegments:n,radialSegments:i,heightSegments:s},t=Math.max(0,t),n=Math.max(1,Math.floor(n)),i=Math.max(3,Math.floor(i)),s=Math.max(1,Math.floor(s));const a=[],o=[],l=[],u=[],c=t/2,d=Math.PI/2*e,f=t,h=2*d+f,p=n*2+s,x=i+1,v=new J,m=new J;for(let C=0;C<=p;C++){let w=0,P=0,B=0,S=0;if(C<=n){const T=C/n,R=T*Math.PI/2;P=-c-e*Math.cos(R),B=e*Math.sin(R),S=-e*Math.cos(R),w=T*d}else if(C<=n+s){const T=(C-n)/s;P=-c+T*t,B=e,S=0,w=d+T*f}else{const T=(C-n-s)/n,R=T*Math.PI/2;P=c+e*Math.sin(R),B=e*Math.cos(R),S=e*Math.sin(R),w=d+f+T*d}const I=Math.max(0,Math.min(1,w/h));let N=0;C===0?N=.5/i:C===p&&(N=-.5/i);for(let T=0;T<=i;T++){const R=T/i,D=R*Math.PI*2,j=Math.sin(D),q=Math.cos(D);m.x=-B*q,m.y=P,m.z=B*j,o.push(m.x,m.y,m.z),v.set(-B*q,S,B*j),v.normalize(),l.push(v.x,v.y,v.z),u.push(R+N,I)}if(C>0){const T=(C-1)*x;for(let R=0;R<i;R++){const D=T+R,j=T+R+1,q=C*x+R,Q=C*x+R+1;a.push(D,j,q),a.push(j,Q,q)}}}this.setIndex(a),this.setAttribute("position",new yr(o,3)),this.setAttribute("normal",new yr(l,3)),this.setAttribute("uv",new yr(u,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new l1(e.radius,e.height,e.capSegments,e.radialSegments,e.heightSegments)}}class u1 extends Ni{constructor(e=1,t=32,n=0,i=Math.PI*2){super(),this.type="CircleGeometry",this.parameters={radius:e,segments:t,thetaStart:n,thetaLength:i},t=Math.max(3,t);const s=[],a=[],o=[],l=[],u=new J,c=new ct;a.push(0,0,0),o.push(0,0,1),l.push(.5,.5);for(let d=0,f=3;d<=t;d++,f+=3){const h=n+d/t*i;u.x=e*Math.cos(h),u.y=e*Math.sin(h),a.push(u.x,u.y,u.z),o.push(0,0,1),c.x=(a[f]/e+1)/2,c.y=(a[f+1]/e+1)/2,l.push(c.x,c.y)}for(let d=1;d<=t;d++)s.push(d,d+1,0);this.setIndex(s),this.setAttribute("position",new yr(a,3)),this.setAttribute("normal",new yr(o,3)),this.setAttribute("uv",new yr(l,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new u1(e.radius,e.segments,e.thetaStart,e.thetaLength)}}class Qv extends Ni{constructor(e=1,t=1,n=1,i=32,s=1,a=!1,o=0,l=Math.PI*2){super(),this.type="CylinderGeometry",this.parameters={radiusTop:e,radiusBottom:t,height:n,radialSegments:i,heightSegments:s,openEnded:a,thetaStart:o,thetaLength:l};const u=this;i=Math.floor(i),s=Math.floor(s);const c=[],d=[],f=[],h=[];let p=0;const x=[],v=n/2;let m=0;C(),a===!1&&(e>0&&w(!0),t>0&&w(!1)),this.setIndex(c),this.setAttribute("position",new yr(d,3)),this.setAttribute("normal",new yr(f,3)),this.setAttribute("uv",new yr(h,2));function C(){const P=new J,B=new J;let S=0;const I=(t-e)/n;for(let N=0;N<=s;N++){const T=[],R=N/s,D=R*(t-e)+e;for(let j=0;j<=i;j++){const q=j/i,Q=q*l+o,re=Math.sin(Q),de=Math.cos(Q);B.x=D*re,B.y=-R*n+v,B.z=D*de,d.push(B.x,B.y,B.z),P.set(re,I,de).normalize(),f.push(P.x,P.y,P.z),h.push(q,1-R),T.push(p++)}x.push(T)}for(let N=0;N<i;N++)for(let T=0;T<s;T++){const R=x[T][N],D=x[T+1][N],j=x[T+1][N+1],q=x[T][N+1];(e>0||T!==0)&&(c.push(R,D,q),S+=3),(t>0||T!==s-1)&&(c.push(D,j,q),S+=3)}u.addGroup(m,S,0),m+=S}function w(P){const B=p,S=new ct,I=new J;let N=0;const T=P===!0?e:t,R=P===!0?1:-1;for(let j=1;j<=i;j++)d.push(0,v*R,0),f.push(0,R,0),h.push(.5,.5),p++;const D=p;for(let j=0;j<=i;j++){const Q=j/i*l+o,re=Math.cos(Q),de=Math.sin(Q);I.x=T*de,I.y=v*R,I.z=T*re,d.push(I.x,I.y,I.z),f.push(0,R,0),S.x=re*.5+.5,S.y=de*.5*R+.5,h.push(S.x,S.y),p++}for(let j=0;j<i;j++){const q=B+j,Q=D+j;P===!0?c.push(Q,Q+1,q):c.push(Q+1,Q,q),N+=3}u.addGroup(m,N,P===!0?1:2),m+=N}}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new Qv(e.radiusTop,e.radiusBottom,e.height,e.radialSegments,e.heightSegments,e.openEnded,e.thetaStart,e.thetaLength)}}class X0 extends Qv{constructor(e=1,t=1,n=32,i=1,s=!1,a=0,o=Math.PI*2){super(0,e,t,n,i,s,a,o),this.type="ConeGeometry",this.parameters={radius:e,height:t,radialSegments:n,heightSegments:i,openEnded:s,thetaStart:a,thetaLength:o}}static fromJSON(e){return new X0(e.radius,e.height,e.radialSegments,e.heightSegments,e.openEnded,e.thetaStart,e.thetaLength)}}class Qm extends Ni{constructor(e=[],t=[],n=1,i=0){super(),this.type="PolyhedronGeometry",this.parameters={vertices:e,indices:t,radius:n,detail:i};const s=[],a=[];o(i),u(n),c(),this.setAttribute("position",new yr(s,3)),this.setAttribute("normal",new yr(s.slice(),3)),this.setAttribute("uv",new yr(a,2)),i===0?this.computeVertexNormals():this.normalizeNormals();function o(C){const w=new J,P=new J,B=new J;for(let S=0;S<t.length;S+=3)h(t[S+0],w),h(t[S+1],P),h(t[S+2],B),l(w,P,B,C)}function l(C,w,P,B){const S=B+1,I=[];for(let N=0;N<=S;N++){I[N]=[];const T=C.clone().lerp(P,N/S),R=w.clone().lerp(P,N/S),D=S-N;for(let j=0;j<=D;j++)j===0&&N===S?I[N][j]=T:I[N][j]=T.clone().lerp(R,j/D)}for(let N=0;N<S;N++)for(let T=0;T<2*(S-N)-1;T++){const R=Math.floor(T/2);T%2===0?(f(I[N][R+1]),f(I[N+1][R]),f(I[N][R])):(f(I[N][R+1]),f(I[N+1][R+1]),f(I[N+1][R]))}}function u(C){const w=new J;for(let P=0;P<s.length;P+=3)w.x=s[P+0],w.y=s[P+1],w.z=s[P+2],w.normalize().multiplyScalar(C),s[P+0]=w.x,s[P+1]=w.y,s[P+2]=w.z}function c(){const C=new J;for(let w=0;w<s.length;w+=3){C.x=s[w+0],C.y=s[w+1],C.z=s[w+2];const P=v(C)/2/Math.PI+.5,B=m(C)/Math.PI+.5;a.push(P,1-B)}p(),d()}function d(){for(let C=0;C<a.length;C+=6){const w=a[C+0],P=a[C+2],B=a[C+4],S=Math.max(w,P,B),I=Math.min(w,P,B);S>.9&&I<.1&&(w<.2&&(a[C+0]+=1),P<.2&&(a[C+2]+=1),B<.2&&(a[C+4]+=1))}}function f(C){s.push(C.x,C.y,C.z)}function h(C,w){const P=C*3;w.x=e[P+0],w.y=e[P+1],w.z=e[P+2]}function p(){const C=new J,w=new J,P=new J,B=new J,S=new ct,I=new ct,N=new ct;for(let T=0,R=0;T<s.length;T+=9,R+=6){C.set(s[T+0],s[T+1],s[T+2]),w.set(s[T+3],s[T+4],s[T+5]),P.set(s[T+6],s[T+7],s[T+8]),S.set(a[R+0],a[R+1]),I.set(a[R+2],a[R+3]),N.set(a[R+4],a[R+5]),B.copy(C).add(w).add(P).divideScalar(3);const D=v(B);x(S,R+0,C,D),x(I,R+2,w,D),x(N,R+4,P,D)}}function x(C,w,P,B){B<0&&C.x===1&&(a[w]=C.x-1),P.x===0&&P.z===0&&(a[w]=B/2/Math.PI+.5)}function v(C){return Math.atan2(C.z,-C.x)}function m(C){return Math.atan2(-C.y,Math.sqrt(C.x*C.x+C.z*C.z))}}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new Qm(e.vertices,e.indices,e.radius,e.detail)}}class c1 extends Qm{constructor(e=1,t=0){const n=(1+Math.sqrt(5))/2,i=1/n,s=[-1,-1,-1,-1,-1,1,-1,1,-1,-1,1,1,1,-1,-1,1,-1,1,1,1,-1,1,1,1,0,-i,-n,0,-i,n,0,i,-n,0,i,n,-i,-n,0,-i,n,0,i,-n,0,i,n,0,-n,0,-i,n,0,-i,-n,0,i,n,0,i],a=[3,11,7,3,7,15,3,15,13,7,19,17,7,17,6,7,6,15,17,4,8,17,8,10,17,10,6,8,0,16,8,16,2,8,2,10,0,12,1,0,1,18,0,18,16,6,10,2,6,2,13,6,13,15,2,16,18,2,18,3,2,3,13,18,1,9,18,9,11,18,11,3,4,14,12,4,12,0,4,0,8,11,9,5,11,5,19,11,19,7,19,5,14,19,14,4,19,4,17,1,12,14,1,14,5,1,5,9];super(s,a,e,t),this.type="DodecahedronGeometry",this.parameters={radius:e,detail:t}}static fromJSON(e){return new c1(e.radius,e.detail)}}const ob=new J,lb=new J,d1=new J,ub=new qu;class qR extends Ni{constructor(e=null,t=1){if(super(),this.type="EdgesGeometry",this.parameters={geometry:e,thresholdAngle:t},e!==null){const i=Math.pow(10,4),s=Math.cos(nu*t),a=e.getIndex(),o=e.getAttribute("position"),l=a?a.count:o.count,u=[0,0,0],c=["a","b","c"],d=new Array(3),f={},h=[];for(let p=0;p<l;p+=3){a?(u[0]=a.getX(p),u[1]=a.getX(p+1),u[2]=a.getX(p+2)):(u[0]=p,u[1]=p+1,u[2]=p+2);const{a:x,b:v,c:m}=ub;if(x.fromBufferAttribute(o,u[0]),v.fromBufferAttribute(o,u[1]),m.fromBufferAttribute(o,u[2]),ub.getNormal(d1),d[0]=`${Math.round(x.x*i)},${Math.round(x.y*i)},${Math.round(x.z*i)}`,d[1]=`${Math.round(v.x*i)},${Math.round(v.y*i)},${Math.round(v.z*i)}`,d[2]=`${Math.round(m.x*i)},${Math.round(m.y*i)},${Math.round(m.z*i)}`,!(d[0]===d[1]||d[1]===d[2]||d[2]===d[0]))for(let C=0;C<3;C++){const w=(C+1)%3,P=d[C],B=d[w],S=ub[c[C]],I=ub[c[w]],N=`${P}_${B}`,T=`${B}_${P}`;T in f&&f[T]?(d1.dot(f[T].normal)<=s&&(h.push(S.x,S.y,S.z),h.push(I.x,I.y,I.z)),f[T]=null):N in f||(f[N]={index0:u[C],index1:u[w],normal:d1.clone()})}}for(const p in f)if(f[p]){const{index0:x,index1:v}=f[p];ob.fromBufferAttribute(o,x),lb.fromBufferAttribute(o,v),h.push(ob.x,ob.y,ob.z),h.push(lb.x,lb.y,lb.z)}this.setAttribute("position",new yr(h,3))}}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}}class cf{constructor(){this.type="Curve",this.arcLengthDivisions=200,this.needsUpdate=!1,this.cacheArcLengths=null}getPoint(){ze("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),s=0;t.push(0);for(let a=1;a<=e;a++)n=this.getPoint(a/e),s+=n.distanceTo(i),t.push(s),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 s=n.length;let a;t?a=t:a=e*n[s-1];let o=0,l=s-1,u;for(;o<=l;)if(i=Math.floor(o+(l-o)/2),u=n[i]-a,u<0)o=i+1;else if(u>0)l=i-1;else{l=i;break}if(i=l,n[i]===a)return i/(s-1);const c=n[i],f=n[i+1]-c,h=(a-c)/f;return(i+h)/(s-1)}getTangent(e,t){let i=e-1e-4,s=e+1e-4;i<0&&(i=0),s>1&&(s=1);const a=this.getPoint(i),o=this.getPoint(s),l=t||(a.isVector2?new ct:new J);return l.copy(o).sub(a).normalize(),l}getTangentAt(e,t){const n=this.getUtoTmapping(e);return this.getTangent(n,t)}computeFrenetFrames(e,t=!1){const n=new J,i=[],s=[],a=[],o=new J,l=new Cr;for(let h=0;h<=e;h++){const p=h/e;i[h]=this.getTangentAt(p,new J)}s[0]=new J,a[0]=new J;let u=Number.MAX_VALUE;const c=Math.abs(i[0].x),d=Math.abs(i[0].y),f=Math.abs(i[0].z);c<=u&&(u=c,n.set(1,0,0)),d<=u&&(u=d,n.set(0,1,0)),f<=u&&n.set(0,0,1),o.crossVectors(i[0],n).normalize(),s[0].crossVectors(i[0],o),a[0].crossVectors(i[0],s[0]);for(let h=1;h<=e;h++){if(s[h]=s[h-1].clone(),a[h]=a[h-1].clone(),o.crossVectors(i[h-1],i[h]),o.length()>Number.EPSILON){o.normalize();const p=Math.acos(ii(i[h-1].dot(i[h]),-1,1));s[h].applyMatrix4(l.makeRotationAxis(o,p))}a[h].crossVectors(i[h],s[h])}if(t===!0){let h=Math.acos(ii(s[0].dot(s[e]),-1,1));h/=e,i[0].dot(o.crossVectors(s[0],s[e]))>0&&(h=-h);for(let p=1;p<=e;p++)s[p].applyMatrix4(l.makeRotationAxis(i[p],h*p)),a[p].crossVectors(i[p],s[p])}return{tangents:i,normals:s,binormals:a}}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 f1 extends cf{constructor(e=0,t=0,n=1,i=1,s=0,a=Math.PI*2,o=!1,l=0){super(),this.isEllipseCurve=!0,this.type="EllipseCurve",this.aX=e,this.aY=t,this.xRadius=n,this.yRadius=i,this.aStartAngle=s,this.aEndAngle=a,this.aClockwise=o,this.aRotation=l}getPoint(e,t=new ct){const n=t,i=Math.PI*2;let s=this.aEndAngle-this.aStartAngle;const a=Math.abs(s)<Number.EPSILON;for(;s<0;)s+=i;for(;s>i;)s-=i;s<Number.EPSILON&&(a?s=0:s=i),this.aClockwise===!0&&!a&&(s===i?s=-i:s=s-i);const o=this.aStartAngle+e*s;let l=this.aX+this.xRadius*Math.cos(o),u=this.aY+this.yRadius*Math.sin(o);if(this.aRotation!==0){const c=Math.cos(this.aRotation),d=Math.sin(this.aRotation),f=l-this.aX,h=u-this.aY;l=f*c-h*d+this.aX,u=f*d+h*c+this.aY}return n.set(l,u)}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}}class _R extends f1{constructor(e,t,n,i,s,a){super(e,t,n,n,i,s,a),this.isArcCurve=!0,this.type="ArcCurve"}}function h1(){let r=0,e=0,t=0,n=0;function i(s,a,o,l){r=s,e=o,t=-3*s+3*a-2*o-l,n=2*s-2*a+o+l}return{initCatmullRom:function(s,a,o,l,u){i(a,o,u*(o-s),u*(l-a))},initNonuniformCatmullRom:function(s,a,o,l,u,c,d){let f=(a-s)/u-(o-s)/(u+c)+(o-a)/c,h=(o-a)/c-(l-a)/(c+d)+(l-o)/d;f*=c,h*=c,i(a,o,f,h)},calc:function(s){const a=s*s,o=a*s;return r+e*s+t*a+n*o}}}const cb=new J,p1=new h1,m1=new h1,g1=new h1;class $R extends cf{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 J){const n=t,i=this.points,s=i.length,a=(s-(this.closed?0:1))*e;let o=Math.floor(a),l=a-o;this.closed?o+=o>0?0:(Math.floor(Math.abs(o)/s)+1)*s:l===0&&o===s-1&&(o=s-2,l=1);let u,c;this.closed||o>0?u=i[(o-1)%s]:(cb.subVectors(i[0],i[1]).add(i[0]),u=cb);const d=i[o%s],f=i[(o+1)%s];if(this.closed||o+2<s?c=i[(o+2)%s]:(cb.subVectors(i[s-1],i[s-2]).add(i[s-1]),c=cb),this.curveType==="centripetal"||this.curveType==="chordal"){const h=this.curveType==="chordal"?.5:.25;let p=Math.pow(u.distanceToSquared(d),h),x=Math.pow(d.distanceToSquared(f),h),v=Math.pow(f.distanceToSquared(c),h);x<1e-4&&(x=1),p<1e-4&&(p=x),v<1e-4&&(v=x),p1.initNonuniformCatmullRom(u.x,d.x,f.x,c.x,p,x,v),m1.initNonuniformCatmullRom(u.y,d.y,f.y,c.y,p,x,v),g1.initNonuniformCatmullRom(u.z,d.z,f.z,c.z,p,x,v)}else this.curveType==="catmullrom"&&(p1.initCatmullRom(u.x,d.x,f.x,c.x,this.tension),m1.initCatmullRom(u.y,d.y,f.y,c.y,this.tension),g1.initCatmullRom(u.z,d.z,f.z,c.z,this.tension));return n.set(p1.calc(l),m1.calc(l),g1.calc(l)),n}copy(e){super.copy(e),this.points=[];for(let t=0,n=e.points.length;t<n;t++){const i=e.points[t];this.points.push(i.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 i=this.points[t];e.points.push(i.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 i=e.points[t];this.points.push(new J().fromArray(i))}return this.closed=e.closed,this.curveType=e.curveType,this.tension=e.tension,this}}function h5(r,e,t,n,i){const s=(n-e)*.5,a=(i-t)*.5,o=r*r,l=r*o;return(2*t-2*n+s+a)*l+(-3*t+3*n-2*s-a)*o+s*r+t}function eL(r,e){const t=1-r;return t*t*e}function tL(r,e){return 2*(1-r)*r*e}function nL(r,e){return r*r*e}function G0(r,e,t,n){return eL(r,e)+tL(r,t)+nL(r,n)}function rL(r,e){const t=1-r;return t*t*t*e}function iL(r,e){const t=1-r;return 3*t*t*r*e}function sL(r,e){return 3*(1-r)*r*r*e}function aL(r,e){return r*r*r*e}function W0(r,e,t,n,i){return rL(r,e)+iL(r,t)+sL(r,n)+aL(r,i)}class p5 extends cf{constructor(e=new ct,t=new ct,n=new ct,i=new ct){super(),this.isCubicBezierCurve=!0,this.type="CubicBezierCurve",this.v0=e,this.v1=t,this.v2=n,this.v3=i}getPoint(e,t=new ct){const n=t,i=this.v0,s=this.v1,a=this.v2,o=this.v3;return n.set(W0(e,i.x,s.x,a.x,o.x),W0(e,i.y,s.y,a.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 m5 extends cf{constructor(e=new J,t=new J,n=new J,i=new J){super(),this.isCubicBezierCurve3=!0,this.type="CubicBezierCurve3",this.v0=e,this.v1=t,this.v2=n,this.v3=i}getPoint(e,t=new J){const n=t,i=this.v0,s=this.v1,a=this.v2,o=this.v3;return n.set(W0(e,i.x,s.x,a.x,o.x),W0(e,i.y,s.y,a.y,o.y),W0(e,i.z,s.z,a.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 g5 extends cf{constructor(e=new ct,t=new ct){super(),this.isLineCurve=!0,this.type="LineCurve",this.v1=e,this.v2=t}getPoint(e,t=new ct){const n=t;return e===1?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 ct){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 oL extends cf{constructor(e=new J,t=new J){super(),this.isLineCurve3=!0,this.type="LineCurve3",this.v1=e,this.v2=t}getPoint(e,t=new J){const n=t;return e===1?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 J){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 v5 extends cf{constructor(e=new ct,t=new ct,n=new ct){super(),this.isQuadraticBezierCurve=!0,this.type="QuadraticBezierCurve",this.v0=e,this.v1=t,this.v2=n}getPoint(e,t=new ct){const n=t,i=this.v0,s=this.v1,a=this.v2;return n.set(G0(e,i.x,s.x,a.x),G0(e,i.y,s.y,a.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 v1 extends cf{constructor(e=new J,t=new J,n=new J){super(),this.isQuadraticBezierCurve3=!0,this.type="QuadraticBezierCurve3",this.v0=e,this.v1=t,this.v2=n}getPoint(e,t=new J){const n=t,i=this.v0,s=this.v1,a=this.v2;return n.set(G0(e,i.x,s.x,a.x),G0(e,i.y,s.y,a.y),G0(e,i.z,s.z,a.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 A5 extends cf{constructor(e=[]){super(),this.isSplineCurve=!0,this.type="SplineCurve",this.points=e}getPoint(e,t=new ct){const n=t,i=this.points,s=(i.length-1)*e,a=Math.floor(s),o=s-a,l=i[a===0?a:a-1],u=i[a],c=i[a>i.length-2?i.length-1:a+1],d=i[a>i.length-3?i.length-1:a+2];return n.set(h5(o,l.x,u.x,c.x,d.x),h5(o,l.y,u.y,c.y,d.y)),n}copy(e){super.copy(e),this.points=[];for(let t=0,n=e.points.length;t<n;t++){const i=e.points[t];this.points.push(i.clone())}return this}toJSON(){const e=super.toJSON();e.points=[];for(let t=0,n=this.points.length;t<n;t++){const i=this.points[t];e.points.push(i.toArray())}return e}fromJSON(e){super.fromJSON(e),this.points=[];for(let t=0,n=e.points.length;t<n;t++){const i=e.points[t];this.points.push(new ct().fromArray(i))}return this}}var db=Object.freeze({__proto__:null,ArcCurve:_R,CatmullRomCurve3:$R,CubicBezierCurve:p5,CubicBezierCurve3:m5,EllipseCurve:f1,LineCurve:g5,LineCurve3:oL,QuadraticBezierCurve:v5,QuadraticBezierCurve3:v1,SplineCurve:A5});class lL extends cf{constructor(){super(),this.type="CurvePath",this.curves=[],this.autoClose=!1}add(e){this.curves.push(e)}closePath(){const e=this.curves[0].getPoint(0),t=this.curves[this.curves.length-1].getPoint(1);if(!e.equals(t)){const n=e.isVector2===!0?"LineCurve":"LineCurve3";this.curves.push(new db[n](t,e))}return this}getPoint(e,t){const n=e*this.getLength(),i=this.getCurveLengths();let s=0;for(;s<i.length;){if(i[s]>=n){const a=i[s]-n,o=this.curves[s],l=o.getLength(),u=l===0?0:1-a/l;return o.getPointAt(u,t)}s++}return null}getLength(){const e=this.getCurveLengths();return e[e.length-1]}updateArcLengths(){this.needsUpdate=!0,this.cacheLengths=null,this.getCurveLengths()}getCurveLengths(){if(this.cacheLengths&&this.cacheLengths.length===this.curves.length)return this.cacheLengths;const e=[];let t=0;for(let n=0,i=this.curves.length;n<i;n++)t+=this.curves[n].getLength(),e.push(t);return this.cacheLengths=e,e}getSpacedPoints(e=40){const t=[];for(let n=0;n<=e;n++)t.push(this.getPoint(n/e));return this.autoClose&&t.push(t[0]),t}getPoints(e=12){const t=[];let n;for(let i=0,s=this.curves;i<s.length;i++){const a=s[i],o=a.isEllipseCurve?e*2:a.isLineCurve||a.isLineCurve3?1:a.isSplineCurve?e*a.points.length:e,l=a.getPoints(o);for(let u=0;u<l.length;u++){const c=l[u];n&&n.equals(c)||(t.push(c),n=c)}}return this.autoClose&&t.length>1&&!t[t.length-1].equals(t[0])&&t.push(t[0]),t}copy(e){super.copy(e),this.curves=[];for(let t=0,n=e.curves.length;t<n;t++){const i=e.curves[t];this.curves.push(i.clone())}return this.autoClose=e.autoClose,this}toJSON(){const e=super.toJSON();e.autoClose=this.autoClose,e.curves=[];for(let t=0,n=this.curves.length;t<n;t++){const i=this.curves[t];e.curves.push(i.toJSON())}return e}fromJSON(e){super.fromJSON(e),this.autoClose=e.autoClose,this.curves=[];for(let t=0,n=e.curves.length;t<n;t++){const i=e.curves[t];this.curves.push(new db[i.type]().fromJSON(i))}return this}}class A1 extends lL{constructor(e){super(),this.type="Path",this.currentPoint=new ct,e&&this.setFromPoints(e)}setFromPoints(e){this.moveTo(e[0].x,e[0].y);for(let t=1,n=e.length;t<n;t++)this.lineTo(e[t].x,e[t].y);return this}moveTo(e,t){return this.currentPoint.set(e,t),this}lineTo(e,t){const n=new g5(this.currentPoint.clone(),new ct(e,t));return this.curves.push(n),this.currentPoint.set(e,t),this}quadraticCurveTo(e,t,n,i){const s=new v5(this.currentPoint.clone(),new ct(e,t),new ct(n,i));return this.curves.push(s),this.currentPoint.set(n,i),this}bezierCurveTo(e,t,n,i,s,a){const o=new p5(this.currentPoint.clone(),new ct(e,t),new ct(n,i),new ct(s,a));return this.curves.push(o),this.currentPoint.set(s,a),this}splineThru(e){const t=[this.currentPoint.clone()].concat(e),n=new A5(t);return this.curves.push(n),this.currentPoint.copy(e[e.length-1]),this}arc(e,t,n,i,s,a){const o=this.currentPoint.x,l=this.currentPoint.y;return this.absarc(e+o,t+l,n,i,s,a),this}absarc(e,t,n,i,s,a){return this.absellipse(e,t,n,n,i,s,a),this}ellipse(e,t,n,i,s,a,o,l){const u=this.currentPoint.x,c=this.currentPoint.y;return this.absellipse(e+u,t+c,n,i,s,a,o,l),this}absellipse(e,t,n,i,s,a,o,l){const u=new f1(e,t,n,i,s,a,o,l);if(this.curves.length>0){const d=u.getPoint(0);d.equals(this.currentPoint)||this.lineTo(d.x,d.y)}this.curves.push(u);const c=u.getPoint(1);return this.currentPoint.copy(c),this}copy(e){return super.copy(e),this.currentPoint.copy(e.currentPoint),this}toJSON(){const e=super.toJSON();return e.currentPoint=this.currentPoint.toArray(),e}fromJSON(e){return super.fromJSON(e),this.currentPoint.fromArray(e.currentPoint),this}}class Zv 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Z0(r,e,t,n,i,s,a,o){return!(r===a&&e===o)&&y5(r,e,t,n,i,s,a,o)}function EL(r,e){return r.next.i!==e.i&&r.prev.i!==e.i&&!wL(r,e)&&(Y0(r,e)&&Y0(e,r)&&CL(r,e)&&(ao(r.prev,r,e.prev)||ao(r,e.prev,e))||Yv(r,e)&&ao(r.prev,r,r.next)>0&&ao(e.prev,e,e.next)>0)}function ao(r,e,t){return(e.y-r.y)*(t.x-e.x)-(e.x-r.x)*(t.y-e.y)}function Yv(r,e){return r.x===e.x&&r.y===e.y}function b5(r,e,t,n){const i=hb(ao(r,e,t)),s=hb(ao(r,e,n)),a=hb(ao(t,n,r)),o=hb(ao(t,n,e));return!!(i!==s&&a!==o||i===0&&fb(r,t,e)||s===0&&fb(r,n,e)||a===0&&fb(t,r,n)||o===0&&fb(t,e,n))}function fb(r,e,t){return e.x<=Math.max(r.x,t.x)&&e.x>=Math.min(r.x,t.x)&&e.y<=Math.max(r.y,t.y)&&e.y>=Math.min(r.y,t.y)}function hb(r){return r>0?1:r<0?-1:0}function wL(r,e){let t=r;do{if(t.i!==r.i&&t.next.i!==r.i&&t.i!==e.i&&t.next.i!==e.i&&b5(t,t.next,r,e))return!0;t=t.next}while(t!==r);return!1}function Y0(r,e){return ao(r.prev,r,r.next)<0?ao(r,e,r.next)>=0&&ao(r,r.prev,e)>=0:ao(r,e,r.prev)<0||ao(r,r.next,e)<0}function CL(r,e){let t=r,n=!1;const i=(r.x+e.x)/2,s=(r.y+e.y)/2;do t.y>s!=t.next.y>s&&t.next.y!==t.y&&i<(t.next.x-t.x)*(s-t.y)/(t.next.y-t.y)+t.x&&(n=!n),t=t.next;while(t!==r);return n}function E5(r,e){const t=y1(r.i,r.x,r.y),n=y1(e.i,e.x,e.y),i=r.next,s=e.prev;return r.next=e,e.prev=r,t.next=i,i.prev=t,n.next=t,t.prev=n,s.next=n,n.prev=s,n}function w5(r,e,t,n){const i=y1(r,e,t);return n?(i.next=n.next,i.prev=n,n.next.prev=i,n.next=i):(i.prev=i,i.next=i),i}function J0(r){r.next.prev=r.prev,r.prev.next=r.next,r.prevZ&&(r.prevZ.nextZ=r.nextZ),r.nextZ&&(r.nextZ.prevZ=r.prevZ)}function y1(r,e,t){return{i:r,x:e,y:t,prev:null,next:null,z:0,prevZ:null,nextZ:null,steiner:!1}}function PL(r,e,t,n){let i=0;for(let s=e,a=t-n;s<t;s+=n)i+=(r[a]-r[s])*(r[s+1]+r[a+1]),a=s;return i}class BL{static triangulate(e,t,n=2){return uL(e,t,n)}}class df{static area(e){const t=e.length;let n=0;for(let i=t-1,s=0;s<t;i=s++)n+=e[i].x*e[s].y-e[s].x*e[i].y;return n*.5}static isClockWise(e){return df.area(e)<0}static triangulateShape(e,t){const n=[],i=[],s=[];C5(e),P5(n,e);let a=e.length;t.forEach(C5);for(let l=0;l<t.length;l++)i.push(a),a+=t[l].length,P5(n,t[l]);const o=BL.triangulate(n,i);for(let l=0;l<o.length;l+=3)s.push(o.slice(l,l+3));return s}}function C5(r){const e=r.length;e>2&&r[e-1].equals(r[0])&&r.pop()}function P5(r,e){for(let t=0;t<e.length;t++)r.push(e[t].x),r.push(e[t].y)}class b1 extends Ni{constructor(e=new Zv([new ct(.5,.5),new ct(-.5,.5),new ct(-.5,-.5),new ct(.5,-.5)]),t={}){super(),this.type="ExtrudeGeometry",this.parameters={shapes:e,options:t},e=Array.isArray(e)?e:[e];const n=this,i=[],s=[];for(let o=0,l=e.length;o<l;o++){const u=e[o];a(u)}this.setAttribute("position",new yr(i,3)),this.setAttribute("uv",new yr(s,2)),this.computeVertexNormals();function a(o){const l=[],u=t.curveSegments!==void 0?t.curveSegments:12,c=t.steps!==void 0?t.steps:1,d=t.depth!==void 0?t.depth:1;let f=t.bevelEnabled!==void 0?t.bevelEnabled:!0,h=t.bevelThickness!==void 0?t.bevelThickness:.2,p=t.bevelSize!==void 0?t.bevelSize:h-.1,x=t.bevelOffset!==void 0?t.bevelOffset:0,v=t.bevelSegments!==void 0?t.bevelSegments:3;const m=t.extrudePath,C=t.UVGenerator!==void 0?t.UVGenerator:ML;let w,P=!1,B,S,I,N;if(m){w=m.getSpacedPoints(c),P=!0,f=!1;const Me=m.isCatmullRomCurve3?m.closed:!1;B=m.computeFrenetFrames(c,Me),S=new J,I=new J,N=new J}f||(v=0,h=0,p=0,x=0);const T=o.extractPoints(u);let R=T.shape;const D=T.holes;if(!df.isClockWise(R)){R=R.reverse();for(let Me=0,Et=D.length;Me<Et;Me++){const ft=D[Me];df.isClockWise(ft)&&(D[Me]=ft.reverse())}}function q(Me){const ft=10000000000000001e-36;let Yt=Me[0];for(let se=1;se<=Me.length;se++){const br=se%Me.length,vn=Me[br],er=vn.x-Yt.x,Jt=vn.y-Yt.y,$=er*er+Jt*Jt,V=Math.max(Math.abs(vn.x),Math.abs(vn.y),Math.abs(Yt.x),Math.abs(Yt.y)),Be=ft*V*V;if($<=Be){Me.splice(br,1),se--;continue}Yt=vn}}q(R),D.forEach(q);const Q=D.length,re=R;for(let Me=0;Me<Q;Me++){const Et=D[Me];R=R.concat(Et)}function de(Me,Et,ft){return Et||rt("ExtrudeGeometry: vec does not exist"),Me.clone().addScaledVector(Et,ft)}const we=R.length;function ge(Me,Et,ft){let Yt,se,br;const vn=Me.x-Et.x,er=Me.y-Et.y,Jt=ft.x-Me.x,$=ft.y-Me.y,V=vn*vn+er*er,Be=vn*$-er*Jt;if(Math.abs(Be)>Number.EPSILON){const at=Math.sqrt(V),De=Math.sqrt(Jt*Jt+$*$),Qe=Et.x-er/at,Cn=Et.y+vn/at,kt=ft.x-$/De,yn=ft.y+Jt/De,Vr=((kt-Qe)*$-(yn-Cn)*Jt)/(vn*$-er*Jt);Yt=Qe+vn*Vr-Me.x,se=Cn+er*Vr-Me.y;const jt=Yt*Yt+se*se;if(jt<=2)return new ct(Yt,se);br=Math.sqrt(jt/2)}else{let at=!1;vn>Number.EPSILON?Jt>Number.EPSILON&&(at=!0):vn<-Number.EPSILON?Jt<-Number.EPSILON&&(at=!0):Math.sign(er)===Math.sign($)&&(at=!0),at?(Yt=-er,se=vn,br=Math.sqrt(V)):(Yt=vn,se=er,br=Math.sqrt(V/2))}return new ct(Yt/br,se/br)}const Y=[];for(let Me=0,Et=re.length,ft=Et-1,Yt=Me+1;Me<Et;Me++,ft++,Yt++)ft===Et&&(ft=0),Yt===Et&&(Yt=0),Y[Me]=ge(re[Me],re[ft],re[Yt]);const Se=[];let W,fe=Y.concat();for(let Me=0,Et=Q;Me<Et;Me++){const ft=D[Me];W=[];for(let Yt=0,se=ft.length,br=se-1,vn=Yt+1;Yt<se;Yt++,br++,vn++)br===se&&(br=0),vn===se&&(vn=0),W[Yt]=ge(ft[Yt],ft[br],ft[vn]);Se.push(W),fe=fe.concat(W)}let xe;if(v===0)xe=df.triangulateShape(re,D);else{const Me=[],Et=[];for(let ft=0;ft<v;ft++){const Yt=ft/v,se=h*Math.cos(Yt*Math.PI/2),br=p*Math.sin(Yt*Math.PI/2)+x;for(let vn=0,er=re.length;vn<er;vn++){const Jt=de(re[vn],Y[vn],br);$e(Jt.x,Jt.y,-se),Yt===0&&Me.push(Jt)}for(let vn=0,er=Q;vn<er;vn++){const Jt=D[vn];W=Se[vn];const $=[];for(let V=0,Be=Jt.length;V<Be;V++){const at=de(Jt[V],W[V],br);$e(at.x,at.y,-se),Yt===0&&$.push(at)}Yt===0&&Et.push($)}}xe=df.triangulateShape(Me,Et)}const dt=xe.length,ve=p+x;for(let Me=0;Me<we;Me++){const Et=f?de(R[Me],fe[Me],ve):R[Me];P?(I.copy(B.normals[0]).multiplyScalar(Et.x),S.copy(B.binormals[0]).multiplyScalar(Et.y),N.copy(w[0]).add(I).add(S),$e(N.x,N.y,N.z)):$e(Et.x,Et.y,0)}for(let Me=1;Me<=c;Me++)for(let Et=0;Et<we;Et++){const ft=f?de(R[Et],fe[Et],ve):R[Et];P?(I.copy(B.normals[Me]).multiplyScalar(ft.x),S.copy(B.binormals[Me]).multiplyScalar(ft.y),N.copy(w[Me]).add(I).add(S),$e(N.x,N.y,N.z)):$e(ft.x,ft.y,d/c*Me)}for(let Me=v-1;Me>=0;Me--){const Et=Me/v,ft=h*Math.cos(Et*Math.PI/2),Yt=p*Math.sin(Et*Math.PI/2)+x;for(let se=0,br=re.length;se<br;se++){const vn=de(re[se],Y[se],Yt);$e(vn.x,vn.y,d+ft)}for(let se=0,br=D.length;se<br;se++){const vn=D[se];W=Se[se];for(let er=0,Jt=vn.length;er<Jt;er++){const $=de(vn[er],W[er],Yt);P?$e($.x,$.y+w[c-1].y,w[c-1].x+ft):$e($.x,$.y,d+ft)}}}ee(),ue();function ee(){const Me=i.length/3;if(f){let Et=0,ft=we*Et;for(let Yt=0;Yt<dt;Yt++){const se=xe[Yt];He(se[2]+ft,se[1]+ft,se[0]+ft)}Et=c+v*2,ft=we*Et;for(let Yt=0;Yt<dt;Yt++){const se=xe[Yt];He(se[0]+ft,se[1]+ft,se[2]+ft)}}else{for(let Et=0;Et<dt;Et++){const ft=xe[Et];He(ft[2],ft[1],ft[0])}for(let Et=0;Et<dt;Et++){const ft=xe[Et];He(ft[0]+we*c,ft[1]+we*c,ft[2]+we*c)}}n.addGroup(Me,i.length/3-Me,0)}function ue(){const Me=i.length/3;let Et=0;Ue(re,Et),Et+=re.length;for(let ft=0,Yt=D.length;ft<Yt;ft++){const se=D[ft];Ue(se,Et),Et+=se.length}n.addGroup(Me,i.length/3-Me,1)}function Ue(Me,Et){let ft=Me.length;for(;--ft>=0;){const Yt=ft;let se=ft-1;se<0&&(se=Me.length-1);for(let br=0,vn=c+v*2;br<vn;br++){const er=we*br,Jt=we*(br+1),$=Et+Yt+er,V=Et+se+er,Be=Et+se+Jt,at=Et+Yt+Jt;bt($,V,Be,at)}}}function $e(Me,Et,ft){l.push(Me),l.push(Et),l.push(ft)}function He(Me,Et,ft){$t(Me),$t(Et),$t(ft);const Yt=i.length/3,se=C.generateTopUV(n,i,Yt-3,Yt-2,Yt-1);zn(se[0]),zn(se[1]),zn(se[2])}function bt(Me,Et,ft,Yt){$t(Me),$t(Et),$t(Yt),$t(Et),$t(ft),$t(Yt);const se=i.length/3,br=C.generateSideWallUV(n,i,se-6,se-3,se-2,se-1);zn(br[0]),zn(br[1]),zn(br[3]),zn(br[1]),zn(br[2]),zn(br[3])}function $t(Me){i.push(l[Me*3+0]),i.push(l[Me*3+1]),i.push(l[Me*3+2])}function zn(Me){s.push(Me.x),s.push(Me.y)}}}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}toJSON(){const e=super.toJSON(),t=this.parameters.shapes,n=this.parameters.options;return SL(t,n,e)}static fromJSON(e,t){const n=[];for(let s=0,a=e.shapes.length;s<a;s++){const o=t[e.shapes[s]];n.push(o)}const i=e.options.extrudePath;return i!==void 0&&(e.options.extrudePath=new db[i.type]().fromJSON(i)),new b1(n,e.options)}}const ML={generateTopUV:function(r,e,t,n,i){const s=e[t*3],a=e[t*3+1],o=e[n*3],l=e[n*3+1],u=e[i*3],c=e[i*3+1];return[new ct(s,a),new ct(o,l),new ct(u,c)]},generateSideWallUV:function(r,e,t,n,i,s){const a=e[t*3],o=e[t*3+1],l=e[t*3+2],u=e[n*3],c=e[n*3+1],d=e[n*3+2],f=e[i*3],h=e[i*3+1],p=e[i*3+2],x=e[s*3],v=e[s*3+1],m=e[s*3+2];return Math.abs(o-c)<Math.abs(a-u)?[new ct(a,1-l),new ct(u,1-d),new ct(f,1-p),new ct(x,1-m)]:[new ct(o,1-l),new ct(c,1-d),new ct(h,1-p),new ct(v,1-m)]}};function SL(r,e,t){if(t.shapes=[],Array.isArray(r))for(let n=0,i=r.length;n<i;n++){const s=r[n];t.shapes.push(s.uuid)}else t.shapes.push(r.uuid);return t.options=Object.assign({},e),e.extrudePath!==void 0&&(t.options.extrudePath=e.extrudePath.toJSON()),t}class E1 extends Qm{constructor(e=1,t=0){const n=(1+Math.sqrt(5))/2,i=[-1,n,0,1,n,0,-1,-n,0,1,-n,0,0,-1,n,0,1,n,0,-1,-n,0,1,-n,n,0,-1,n,0,1,-n,0,-1,-n,0,1],s=[0,11,5,0,5,1,0,1,7,0,7,10,0,10,11,1,5,9,5,11,4,11,10,2,10,7,6,7,1,8,3,9,4,3,4,2,3,2,6,3,6,8,3,8,9,4,9,5,2,4,11,6,2,10,8,6,7,9,8,1];super(i,s,e,t),this.type="IcosahedronGeometry",this.parameters={radius:e,detail:t}}static fromJSON(e){return new E1(e.radius,e.detail)}}class w1 extends Ni{constructor(e=[new ct(0,-.5),new ct(.5,0),new ct(0,.5)],t=12,n=0,i=Math.PI*2){super(),this.type="LatheGeometry",this.parameters={points:e,segments:t,phiStart:n,phiLength:i},t=Math.floor(t),i=ii(i,0,Math.PI*2);const s=[],a=[],o=[],l=[],u=[],c=1/t,d=new J,f=new ct,h=new J,p=new J,x=new J;let v=0,m=0;for(let C=0;C<=e.length-1;C++)switch(C){case 0:v=e[C+1].x-e[C].x,m=e[C+1].y-e[C].y,h.x=m*1,h.y=-v,h.z=m*0,x.copy(h),h.normalize(),l.push(h.x,h.y,h.z);break;case e.length-1:l.push(x.x,x.y,x.z);break;default:v=e[C+1].x-e[C].x,m=e[C+1].y-e[C].y,h.x=m*1,h.y=-v,h.z=m*0,p.copy(h),h.x+=x.x,h.y+=x.y,h.z+=x.z,h.normalize(),l.push(h.x,h.y,h.z),x.copy(p)}for(let C=0;C<=t;C++){const w=n+C*c*i,P=Math.sin(w),B=Math.cos(w);for(let S=0;S<=e.length-1;S++){d.x=e[S].x*P,d.y=e[S].y,d.z=e[S].x*B,a.push(d.x,d.y,d.z),f.x=C/t,f.y=S/(e.length-1),o.push(f.x,f.y);const I=l[3*S+0]*P,N=l[3*S+1],T=l[3*S+0]*B;u.push(I,N,T)}}for(let C=0;C<t;C++)for(let w=0;w<e.length-1;w++){const P=w+C*e.length,B=P,S=P+e.length,I=P+e.length+1,N=P+1;s.push(B,S,N),s.push(I,N,S)}this.setIndex(s),this.setAttribute("position",new yr(a,3)),this.setAttribute("uv",new yr(o,2)),this.setAttribute("normal",new yr(u,3))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new w1(e.points,e.segments,e.phiStart,e.phiLength)}}class pb extends Qm{constructor(e=1,t=0){const n=[1,0,0,-1,0,0,0,1,0,0,-1,0,0,0,1,0,0,-1],i=[0,2,4,0,4,3,0,3,5,0,5,2,1,2,5,1,5,3,1,3,4,1,4,2];super(n,i,e,t),this.type="OctahedronGeometry",this.parameters={radius:e,detail:t}}static fromJSON(e){return new pb(e.radius,e.detail)}}class Jv extends Ni{constructor(e=1,t=1,n=1,i=1){super(),this.type="PlaneGeometry",this.parameters={width:e,height:t,widthSegments:n,heightSegments:i};const s=e/2,a=t/2,o=Math.floor(n),l=Math.floor(i),u=o+1,c=l+1,d=e/o,f=t/l,h=[],p=[],x=[],v=[];for(let m=0;m<c;m++){const C=m*f-a;for(let w=0;w<u;w++){const P=w*d-s;p.push(P,-C,0),x.push(0,0,1),v.push(w/o),v.push(1-m/l)}}for(let m=0;m<l;m++)for(let C=0;C<o;C++){const w=C+u*m,P=C+u*(m+1),B=C+1+u*(m+1),S=C+1+u*m;h.push(w,P,S),h.push(P,B,S)}this.setIndex(h),this.setAttribute("position",new yr(p,3)),this.setAttribute("normal",new yr(x,3)),this.setAttribute("uv",new yr(v,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new Jv(e.width,e.height,e.widthSegments,e.heightSegments)}}class C1 extends Ni{constructor(e=.5,t=1,n=32,i=1,s=0,a=Math.PI*2){super(),this.type="RingGeometry",this.parameters={innerRadius:e,outerRadius:t,thetaSegments:n,phiSegments:i,thetaStart:s,thetaLength:a},n=Math.max(3,n),i=Math.max(1,i);const o=[],l=[],u=[],c=[];let d=e;const f=(t-e)/i,h=new J,p=new ct;for(let x=0;x<=i;x++){for(let v=0;v<=n;v++){const m=s+v/n*a;h.x=d*Math.cos(m),h.y=d*Math.sin(m),l.push(h.x,h.y,h.z),u.push(0,0,1),p.x=(h.x/t+1)/2,p.y=(h.y/t+1)/2,c.push(p.x,p.y)}d+=f}for(let x=0;x<i;x++){const v=x*(n+1);for(let m=0;m<n;m++){const C=m+v,w=C,P=C+n+1,B=C+n+2,S=C+1;o.push(w,P,S),o.push(P,B,S)}}this.setIndex(o),this.setAttribute("position",new yr(l,3)),this.setAttribute("normal",new yr(u,3)),this.setAttribute("uv",new yr(c,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new C1(e.innerRadius,e.outerRadius,e.thetaSegments,e.phiSegments,e.thetaStart,e.thetaLength)}}class P1 extends Ni{constructor(e=new Zv([new ct(0,.5),new ct(-.5,-.5),new ct(.5,-.5)]),t=12){super(),this.type="ShapeGeometry",this.parameters={shapes:e,curveSegments:t};const n=[],i=[],s=[],a=[];let o=0,l=0;if(Array.isArray(e)===!1)u(e);else for(let c=0;c<e.length;c++)u(e[c]),this.addGroup(o,l,c),o+=l,l=0;this.setIndex(n),this.setAttribute("position",new yr(i,3)),this.setAttribute("normal",new yr(s,3)),this.setAttribute("uv",new yr(a,2));function u(c){const d=i.length/3,f=c.extractPoints(t);let h=f.shape;const p=f.holes;df.isClockWise(h)===!1&&(h=h.reverse());for(let v=0,m=p.length;v<m;v++){const C=p[v];df.isClockWise(C)===!0&&(p[v]=C.reverse())}const x=df.triangulateShape(h,p);for(let v=0,m=p.length;v<m;v++){const C=p[v];h=h.concat(C)}for(let v=0,m=h.length;v<m;v++){const C=h[v];i.push(C.x,C.y,0),s.push(0,0,1),a.push(C.x,C.y)}for(let v=0,m=x.length;v<m;v++){const C=x[v],w=C[0]+d,P=C[1]+d,B=C[2]+d;n.push(w,P,B),l+=3}}}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}toJSON(){const e=super.toJSON(),t=this.parameters.shapes;return DL(t,e)}static fromJSON(e,t){const n=[];for(let i=0,s=e.shapes.length;i<s;i++){const a=t[e.shapes[i]];n.push(a)}return new P1(n,e.curveSegments)}}function DL(r,e){if(e.shapes=[],Array.isArray(r))for(let t=0,n=r.length;t<n;t++){const i=r[t];e.shapes.push(i.uuid)}else e.shapes.push(r.uuid);return e}class Ad extends Ni{constructor(e=1,t=32,n=16,i=0,s=Math.PI*2,a=0,o=Math.PI){super(),this.type="SphereGeometry",this.parameters={radius:e,widthSegments:t,heightSegments:n,phiStart:i,phiLength:s,thetaStart:a,thetaLength:o},t=Math.max(3,Math.floor(t)),n=Math.max(2,Math.floor(n));const l=Math.min(a+o,Math.PI);let u=0;const c=[],d=new J,f=new J,h=[],p=[],x=[],v=[];for(let m=0;m<=n;m++){const C=[],w=m/n;let P=0;m===0&&a===0?P=.5/t:m===n&&l===Math.PI&&(P=-.5/t);for(let B=0;B<=t;B++){const S=B/t;d.x=-e*Math.cos(i+S*s)*Math.sin(a+w*o),d.y=e*Math.cos(a+w*o),d.z=e*Math.sin(i+S*s)*Math.sin(a+w*o),p.push(d.x,d.y,d.z),f.copy(d).normalize(),x.push(f.x,f.y,f.z),v.push(S+P,1-w),C.push(u++)}c.push(C)}for(let m=0;m<n;m++)for(let C=0;C<t;C++){const w=c[m][C+1],P=c[m][C],B=c[m+1][C],S=c[m+1][C+1];(m!==0||a>0)&&h.push(w,P,S),(m!==n-1||l<Math.PI)&&h.push(P,B,S)}this.setIndex(h),this.setAttribute("position",new yr(p,3)),this.setAttribute("normal",new yr(x,3)),this.setAttribute("uv",new yr(v,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new Ad(e.radius,e.widthSegments,e.heightSegments,e.phiStart,e.phiLength,e.thetaStart,e.thetaLength)}}class B1 extends Qm{constructor(e=1,t=0){const n=[1,1,1,-1,-1,1,-1,1,-1,1,-1,-1],i=[2,1,0,0,3,2,1,3,0,2,3,1];super(n,i,e,t),this.type="TetrahedronGeometry",this.parameters={radius:e,detail:t}}static fromJSON(e){return new B1(e.radius,e.detail)}}class M1 extends Ni{constructor(e=1,t=.4,n=12,i=48,s=Math.PI*2){super(),this.type="TorusGeometry",this.parameters={radius:e,tube:t,radialSegments:n,tubularSegments:i,arc:s},n=Math.floor(n),i=Math.floor(i);const a=[],o=[],l=[],u=[],c=new J,d=new J,f=new J;for(let h=0;h<=n;h++)for(let p=0;p<=i;p++){const x=p/i*s,v=h/n*Math.PI*2;d.x=(e+t*Math.cos(v))*Math.cos(x),d.y=(e+t*Math.cos(v))*Math.sin(x),d.z=t*Math.sin(v),o.push(d.x,d.y,d.z),c.x=e*Math.cos(x),c.y=e*Math.sin(x),f.subVectors(d,c).normalize(),l.push(f.x,f.y,f.z),u.push(p/i),u.push(h/n)}for(let h=1;h<=n;h++)for(let p=1;p<=i;p++){const x=(i+1)*h+p-1,v=(i+1)*(h-1)+p-1,m=(i+1)*(h-1)+p,C=(i+1)*h+p;a.push(x,v,C),a.push(v,m,C)}this.setIndex(a),this.setAttribute("position",new yr(o,3)),this.setAttribute("normal",new yr(l,3)),this.setAttribute("uv",new yr(u,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new M1(e.radius,e.tube,e.radialSegments,e.tubularSegments,e.arc)}}class S1 extends Ni{constructor(e=1,t=.4,n=64,i=8,s=2,a=3){super(),this.type="TorusKnotGeometry",this.parameters={radius:e,tube:t,tubularSegments:n,radialSegments:i,p:s,q:a},n=Math.floor(n),i=Math.floor(i);const o=[],l=[],u=[],c=[],d=new J,f=new J,h=new J,p=new J,x=new J,v=new J,m=new J;for(let w=0;w<=n;++w){const P=w/n*s*Math.PI*2;C(P,s,a,e,h),C(P+.01,s,a,e,p),v.subVectors(p,h),m.addVectors(p,h),x.crossVectors(v,m),m.crossVectors(x,v),x.normalize(),m.normalize();for(let B=0;B<=i;++B){const S=B/i*Math.PI*2,I=-t*Math.cos(S),N=t*Math.sin(S);d.x=h.x+(I*m.x+N*x.x),d.y=h.y+(I*m.y+N*x.y),d.z=h.z+(I*m.z+N*x.z),l.push(d.x,d.y,d.z),f.subVectors(d,h).normalize(),u.push(f.x,f.y,f.z),c.push(w/n),c.push(B/i)}}for(let w=1;w<=n;w++)for(let P=1;P<=i;P++){const B=(i+1)*(w-1)+(P-1),S=(i+1)*w+(P-1),I=(i+1)*w+P,N=(i+1)*(w-1)+P;o.push(B,S,N),o.push(S,I,N)}this.setIndex(o),this.setAttribute("position",new yr(l,3)),this.setAttribute("normal",new yr(u,3)),this.setAttribute("uv",new yr(c,2));function C(w,P,B,S,I){const N=Math.cos(w),T=Math.sin(w),R=B/P*w,D=Math.cos(R);I.x=S*(2+D)*.5*N,I.y=S*(2+D)*T*.5,I.z=S*Math.sin(R)*.5}}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new S1(e.radius,e.tube,e.tubularSegments,e.radialSegments,e.p,e.q)}}class mb extends Ni{constructor(e=new v1(new J(-1,-1,0),new J(-1,1,0),new J(1,1,0)),t=64,n=1,i=8,s=!1){super(),this.type="TubeGeometry",this.parameters={path:e,tubularSegments:t,radius:n,radialSegments:i,closed:s};const a=e.computeFrenetFrames(t,s);this.tangents=a.tangents,this.normals=a.normals,this.binormals=a.binormals;const o=new J,l=new J,u=new ct;let c=new J;const d=[],f=[],h=[],p=[];x(),this.setIndex(p),this.setAttribute("position",new yr(d,3)),this.setAttribute("normal",new yr(f,3)),this.setAttribute("uv",new yr(h,2));function x(){for(let w=0;w<t;w++)v(w);v(s===!1?t:0),C(),m()}function v(w){c=e.getPointAt(w/t,c);const P=a.normals[w],B=a.binormals[w];for(let S=0;S<=i;S++){const I=S/i*Math.PI*2,N=Math.sin(I),T=-Math.cos(I);l.x=T*P.x+N*B.x,l.y=T*P.y+N*B.y,l.z=T*P.z+N*B.z,l.normalize(),f.push(l.x,l.y,l.z),o.x=c.x+n*l.x,o.y=c.y+n*l.y,o.z=c.z+n*l.z,d.push(o.x,o.y,o.z)}}function m(){for(let w=1;w<=t;w++)for(let P=1;P<=i;P++){const B=(i+1)*(w-1)+(P-1),S=(i+1)*w+(P-1),I=(i+1)*w+P,N=(i+1)*(w-1)+P;p.push(B,S,N),p.push(S,I,N)}}function C(){for(let w=0;w<=t;w++)for(let P=0;P<=i;P++)u.x=w/t,u.y=P/i,h.push(u.x,u.y)}}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 mb(new db[e.path.type]().fromJSON(e.path),e.tubularSegments,e.radius,e.radialSegments,e.closed)}}class TL extends Ni{constructor(e=null){if(super(),this.type="WireframeGeometry",this.parameters={geometry:e},e!==null){const t=[],n=new Set,i=new J,s=new J;if(e.index!==null){const a=e.attributes.position,o=e.index;let l=e.groups;l.length===0&&(l=[{start:0,count:o.count,materialIndex:0}]);for(let u=0,c=l.length;u<c;++u){const d=l[u],f=d.start,h=d.count;for(let p=f,x=f+h;p<x;p+=3)for(let v=0;v<3;v++){const m=o.getX(p+v),C=o.getX(p+(v+1)%3);i.fromBufferAttribute(a,m),s.fromBufferAttribute(a,C),B5(i,s,n)===!0&&(t.push(i.x,i.y,i.z),t.push(s.x,s.y,s.z))}}}else{const a=e.attributes.position;for(let o=0,l=a.count/3;o<l;o++)for(let u=0;u<3;u++){const c=3*o+u,d=3*o+(u+1)%3;i.fromBufferAttribute(a,c),s.fromBufferAttribute(a,d),B5(i,s,n)===!0&&(t.push(i.x,i.y,i.z),t.push(s.x,s.y,s.z))}}this.setAttribute("position",new yr(t,3))}}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}}function B5(r,e,t){const n=`${r.x},${r.y},${r.z}-${e.x},${e.y},${e.z}`,i=`${e.x},${e.y},${e.z}-${r.x},${r.y},${r.z}`;return t.has(n)===!0||t.has(i)===!0?!1:(t.add(n),t.add(i),!0)}var M5=Object.freeze({__proto__:null,BoxGeometry:Dp,CapsuleGeometry:l1,CircleGeometry:u1,ConeGeometry:X0,CylinderGeometry:Qv,DodecahedronGeometry:c1,EdgesGeometry:qR,ExtrudeGeometry:b1,IcosahedronGeometry:E1,LatheGeometry:w1,OctahedronGeometry:pb,PlaneGeometry:Jv,PolyhedronGeometry:Qm,RingGeometry:C1,ShapeGeometry:P1,SphereGeometry:Ad,TetrahedronGeometry:B1,TorusGeometry:M1,TorusKnotGeometry:S1,TubeGeometry:mb,WireframeGeometry:TL});class S5 extends bl{constructor(e){super(),this.isShadowMaterial=!0,this.type="ShadowMaterial",this.color=new Vn(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 D5 extends $u{constructor(e){super(e),this.isRawShaderMaterial=!0,this.type="RawShaderMaterial"}}class D1 extends bl{constructor(e){super(),this.isMeshStandardMaterial=!0,this.type="MeshStandardMaterial",this.defines={STANDARD:""},this.color=new Vn(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 Vn(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=Cc,this.normalScale=new ct(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 bu,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 T5 extends D1{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 ct(1,1),this.clearcoatNormalMap=null,this.ior=1.5,Object.defineProperty(this,"reflectivity",{get:function(){return ii(2.5*(this.ior-1)/(this.ior+1),0,1)},set:function(t){this.ior=(1+.4*t)/(1-.4*t)}}),this.iridescenceMap=null,this.iridescenceIOR=1.3,this.iridescenceThicknessRange=[100,400],this.iridescenceThicknessMap=null,this.sheenColor=new Vn(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 Vn(1,1,1),this.specularIntensity=1,this.specularIntensityMap=null,this.specularColor=new Vn(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 T1 extends bl{constructor(e){super(),this.isMeshPhongMaterial=!0,this.type="MeshPhongMaterial",this.color=new Vn(16777215),this.specular=new Vn(1118481),this.shininess=30,this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new Vn(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=Cc,this.normalScale=new ct(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.specularMap=null,this.alphaMap=null,this.envMap=null,this.envMapRotation=new bu,this.combine=Zd,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 I5 extends bl{constructor(e){super(),this.isMeshToonMaterial=!0,this.defines={TOON:""},this.type="MeshToonMaterial",this.color=new Vn(16777215),this.map=null,this.gradientMap=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new Vn(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=Cc,this.normalScale=new ct(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 N5 extends bl{constructor(e){super(),this.isMeshNormalMaterial=!0,this.type="MeshNormalMaterial",this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=Cc,this.normalScale=new ct(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 I1 extends bl{constructor(e){super(),this.isMeshLambertMaterial=!0,this.type="MeshLambertMaterial",this.color=new Vn(16777215),this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new Vn(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=Cc,this.normalScale=new ct(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.specularMap=null,this.alphaMap=null,this.envMap=null,this.envMapRotation=new bu,this.combine=Zd,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 F5 extends bl{constructor(e){super(),this.isMeshDepthMaterial=!0,this.type="MeshDepthMaterial",this.depthPacking=lC,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 R5 extends bl{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 L5 extends bl{constructor(e){super(),this.isMeshMatcapMaterial=!0,this.defines={MATCAP:""},this.type="MeshMatcapMaterial",this.color=new Vn(16777215),this.matcap=null,this.map=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=Cc,this.normalScale=new ct(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.alphaMap=null,this.wireframe=!1,this.wireframeLinewidth=1,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.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.flatShading=e.flatShading,this.fog=e.fog,this}}class N1 extends kl{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 Ym(r,e){return!r||r.constructor===e?r:typeof e.BYTES_PER_ELEMENT=="number"?new e(r):Array.prototype.slice.call(r)}function O5(r){function e(i,s){return r[i]-r[s]}const t=r.length,n=new Array(t);for(let i=0;i!==t;++i)n[i]=i;return n.sort(e),n}function F1(r,e,t){const n=r.length,i=new r.constructor(n);for(let s=0,a=0;a!==n;++s){const o=t[s]*e;for(let l=0;l!==e;++l)i[a++]=r[o+l]}return i}function R1(r,e,t,n){let i=1,s=r[0];for(;s!==void 0&&s[n]===void 0;)s=r[i++];if(s===void 0)return;let a=s[n];if(a!==void 0)if(Array.isArray(a))do a=s[n],a!==void 0&&(e.push(s.time),t.push(...a)),s=r[i++];while(s!==void 0);else if(a.toArray!==void 0)do a=s[n],a!==void 0&&(e.push(s.time),a.toArray(t,t.length)),s=r[i++];while(s!==void 0);else do a=s[n],a!==void 0&&(e.push(s.time),t.push(a)),s=r[i++];while(s!==void 0)}function IL(r,e,t,n,i=30){const s=r.clone();s.name=e;const a=[];for(let l=0;l<s.tracks.length;++l){const u=s.tracks[l],c=u.getValueSize(),d=[],f=[];for(let h=0;h<u.times.length;++h){const p=u.times[h]*i;if(!(p<t||p>=n)){d.push(u.times[h]);for(let x=0;x<c;++x)f.push(u.values[h*c+x])}}d.length!==0&&(u.times=Ym(d,u.times.constructor),u.values=Ym(f,u.values.constructor),a.push(u))}s.tracks=a;let o=1/0;for(let l=0;l<s.tracks.length;++l)o>s.tracks[l].times[0]&&(o=s.tracks[l].times[0]);for(let l=0;l<s.tracks.length;++l)s.tracks[l].shift(-1*o);return s.resetDuration(),s}function NL(r,e=0,t=r,n=30){n<=0&&(n=30);const i=t.tracks.length,s=e/n;for(let a=0;a<i;++a){const o=t.tracks[a],l=o.ValueTypeName;if(l==="bool"||l==="string")continue;const u=r.tracks.find(function(m){return m.name===o.name&&m.ValueTypeName===l});if(u===void 0)continue;let c=0;const d=o.getValueSize();o.createInterpolant.isInterpolantFactoryMethodGLTFCubicSpline&&(c=d/3);let f=0;const h=u.getValueSize();u.createInterpolant.isInterpolantFactoryMethodGLTFCubicSpline&&(f=h/3);const p=o.times.length-1;let x;if(s<=o.times[0]){const m=c,C=d-c;x=o.values.slice(m,C)}else if(s>=o.times[p]){const m=p*d+c,C=m+d-c;x=o.values.slice(m,C)}else{const m=o.createInterpolant(),C=c,w=d-c;m.evaluate(s),x=m.resultBuffer.slice(C,w)}l==="quaternion"&&new Wo().fromArray(x).normalize().conjugate().toArray(x);const v=u.times.length;for(let m=0;m<v;++m){const C=m*h+f;if(l==="quaternion")Wo.multiplyQuaternionsFlat(u.values,C,x,0,u.values,C);else{const w=h-f*2;for(let P=0;P<w;++P)u.values[C+P]-=x[P]}}}return r.blendMode=vy,r}class sce{static convertArray(e,t){return Ym(e,t)}static isTypedArray(e){return Wi(e)}static getKeyframeOrder(e){return O5(e)}static sortedArray(e,t,n){return F1(e,t,n)}static flattenJSON(e,t,n,i){R1(e,t,n,i)}static subclip(e,t,n,i,s=30){return IL(e,t,n,i,s)}static makeClipAdditive(e,t=0,n=e,i=30){return NL(e,t,n,i)}}class gb{constructor(e,t,n,i){this.parameterPositions=e,this._cachedIndex=0,this.resultBuffer=i!==void 0?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],s=t[n-1];e:{t:{let a;n:{r:if(!(e<i)){for(let o=n+2;;){if(i===void 0){if(e<s)break r;return n=t.length,this._cachedIndex=n,this.copySampleValue_(n-1)}if(n===o)break;if(s=i,i=t[++n],e<i)break t}a=t.length;break n}if(!(e>=s)){const o=t[1];e<o&&(n=2,s=o);for(let l=n-2;;){if(s===void 0)return this._cachedIndex=0,this.copySampleValue_(0);if(n===l)break;if(i=s,s=t[--n-1],e>=s)break t}a=n,n=0;break n}break e}for(;n<a;){const o=n+a>>>1;e<t[o]?a=o:n=o+1}if(i=t[n],s=t[n-1],s===void 0)return this._cachedIndex=0,this.copySampleValue_(0);if(i===void 0)return n=t.length,this._cachedIndex=n,this.copySampleValue_(n-1)}this._cachedIndex=n,this.intervalChanged_(n,s,i)}return this.interpolate_(n,s,e,i)}getSettings_(){return this.settings||this.DefaultSettings_}copySampleValue_(e){const t=this.resultBuffer,n=this.sampleValues,i=this.valueSize,s=e*i;for(let a=0;a!==i;++a)t[a]=n[s+a];return t}interpolate_(){throw new Error("call to abstract method")}intervalChanged_(){}}class FL extends gb{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:sf,endingEnd:sf}}intervalChanged_(e,t,n){const i=this.parameterPositions;let s=e-2,a=e+1,o=i[s],l=i[a];if(o===void 0)switch(this.getSettings_().endingStart){case xp:s=e,o=2*t-n;break;case yv:s=i.length-2,o=t+i[s]-i[s+1];break;default:s=e,o=n}if(l===void 0)switch(this.getSettings_().endingEnd){case xp:a=e,l=2*n-t;break;case yv:a=1,l=n+i[1]-i[0];break;default:a=e-1,l=t}const u=(n-t)*.5,c=this.valueSize;this._weightPrev=u/(t-o),this._weightNext=u/(l-n),this._offsetPrev=s*c,this._offsetNext=a*c}interpolate_(e,t,n,i){const s=this.resultBuffer,a=this.sampleValues,o=this.valueSize,l=e*o,u=l-o,c=this._offsetPrev,d=this._offsetNext,f=this._weightPrev,h=this._weightNext,p=(n-t)/(i-t),x=p*p,v=x*p,m=-f*v+2*f*x-f*p,C=(1+f)*v+(-1.5-2*f)*x+(-.5+f)*p+1,w=(-1-h)*v+(1.5+h)*x+.5*p,P=h*v-h*x;for(let B=0;B!==o;++B)s[B]=m*a[c+B]+C*a[u+B]+w*a[l+B]+P*a[d+B];return s}}class z5 extends gb{constructor(e,t,n,i){super(e,t,n,i)}interpolate_(e,t,n,i){const s=this.resultBuffer,a=this.sampleValues,o=this.valueSize,l=e*o,u=l-o,c=(n-t)/(i-t),d=1-c;for(let f=0;f!==o;++f)s[f]=a[u+f]*d+a[l+f]*c;return s}}class RL extends gb{constructor(e,t,n,i){super(e,t,n,i)}interpolate_(e){return this.copySampleValue_(e-1)}}class xd{constructor(e,t,n,i){if(e===void 0)throw new Error("THREE.KeyframeTrack: track name is undefined");if(t===void 0||t.length===0)throw new Error("THREE.KeyframeTrack: no keyframes in track named "+e);this.name=e,this.times=Ym(t,this.TimeBufferType),this.values=Ym(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:Ym(e.times,Array),values:Ym(e.values,Array)};const i=e.getInterpolation();i!==e.DefaultInterpolation&&(n.interpolation=i)}return n.type=e.ValueTypeName,n}InterpolantFactoryMethodDiscrete(e){return new RL(this.times,this.values,this.getValueSize(),e)}InterpolantFactoryMethodLinear(e){return new z5(this.times,this.values,this.getValueSize(),e)}InterpolantFactoryMethodSmooth(e){return new FL(this.times,this.values,this.getValueSize(),e)}setInterpolation(e){let t;switch(e){case Ap:t=this.InterpolantFactoryMethodDiscrete;break;case xv:t=this.InterpolantFactoryMethodLinear;break;case Fm:t=this.InterpolantFactoryMethodSmooth;break}if(t===void 0){const n="unsupported interpolation for "+this.ValueTypeName+" keyframe track named "+this.name;if(this.createInterpolant===void 0)if(e!==this.DefaultInterpolation)this.setInterpolation(this.DefaultInterpolation);else throw new Error(n);return ze("KeyframeTrack:",n),this}return this.createInterpolant=t,this}getInterpolation(){switch(this.createInterpolant){case this.InterpolantFactoryMethodDiscrete:return Ap;case this.InterpolantFactoryMethodLinear:return xv;case this.InterpolantFactoryMethodSmooth:return Fm}}getValueSize(){return this.values.length/this.times.length}shift(e){if(e!==0){const t=this.times;for(let n=0,i=t.length;n!==i;++n)t[n]+=e}return this}scale(e){if(e!==1){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 s=0,a=i-1;for(;s!==i&&n[s]<e;)++s;for(;a!==-1&&n[a]>t;)--a;if(++a,s!==0||a!==i){s>=a&&(a=Math.max(a,1),s=a-1);const o=this.getValueSize();this.times=n.slice(s,a),this.values=this.values.slice(s*o,a*o)}return this}validate(){let e=!0;const t=this.getValueSize();t-Math.floor(t)!==0&&(rt("KeyframeTrack: Invalid value size in track.",this),e=!1);const n=this.times,i=this.values,s=n.length;s===0&&(rt("KeyframeTrack: Track is empty.",this),e=!1);let a=null;for(let o=0;o!==s;o++){const l=n[o];if(typeof l=="number"&&isNaN(l)){rt("KeyframeTrack: Time is not a valid number.",this,o,l),e=!1;break}if(a!==null&&a>l){rt("KeyframeTrack: Out of order keys.",this,o,l,a),e=!1;break}a=l}if(i!==void 0&&Wi(i))for(let o=0,l=i.length;o!==l;++o){const u=i[o];if(isNaN(u)){rt("KeyframeTrack: Value is not a valid number.",this,o,u),e=!1;break}}return e}optimize(){const e=this.times.slice(),t=this.values.slice(),n=this.getValueSize(),i=this.getInterpolation()===Fm,s=e.length-1;let a=1;for(let o=1;o<s;++o){let l=!1;const u=e[o],c=e[o+1];if(u!==c&&(o!==1||u!==e[0]))if(i)l=!0;else{const d=o*n,f=d-n,h=d+n;for(let p=0;p!==n;++p){const x=t[d+p];if(x!==t[f+p]||x!==t[h+p]){l=!0;break}}}if(l){if(o!==a){e[a]=e[o];const d=o*n,f=a*n;for(let h=0;h!==n;++h)t[f+h]=t[d+h]}++a}}if(s>0){e[a]=e[s];for(let o=s*n,l=a*n,u=0;u!==n;++u)t[l+u]=t[o+u];++a}return a!==e.length?(this.times=e.slice(0,a),this.values=t.slice(0,a*n)):(this.times=e,this.values=t),this}clone(){const e=this.times.slice(),t=this.values.slice(),n=this.constructor,i=new n(this.name,e,t);return i.createInterpolant=this.createInterpolant,i}}xd.prototype.ValueTypeName="",xd.prototype.TimeBufferType=Float32Array,xd.prototype.ValueBufferType=Float32Array,xd.prototype.DefaultInterpolation=xv;class Kv extends xd{constructor(e,t,n){super(e,t,n)}}Kv.prototype.ValueTypeName="bool",Kv.prototype.ValueBufferType=Array,Kv.prototype.DefaultInterpolation=Ap,Kv.prototype.InterpolantFactoryMethodLinear=void 0,Kv.prototype.InterpolantFactoryMethodSmooth=void 0;class H5 extends xd{constructor(e,t,n,i){super(e,t,n,i)}}H5.prototype.ValueTypeName="color";class vb extends xd{constructor(e,t,n,i){super(e,t,n,i)}}vb.prototype.ValueTypeName="number";class LL extends gb{constructor(e,t,n,i){super(e,t,n,i)}interpolate_(e,t,n,i){const s=this.resultBuffer,a=this.sampleValues,o=this.valueSize,l=(n-t)/(i-t);let u=e*o;for(let c=u+o;u!==c;u+=4)Wo.slerpFlat(s,0,a,u-o,a,u,l);return s}}class Ab extends xd{constructor(e,t,n,i){super(e,t,n,i)}InterpolantFactoryMethodLinear(e){return new LL(this.times,this.values,this.getValueSize(),e)}}Ab.prototype.ValueTypeName="quaternion",Ab.prototype.InterpolantFactoryMethodSmooth=void 0;class qv extends xd{constructor(e,t,n){super(e,t,n)}}qv.prototype.ValueTypeName="string",qv.prototype.ValueBufferType=Array,qv.prototype.DefaultInterpolation=Ap,qv.prototype.InterpolantFactoryMethodLinear=void 0,qv.prototype.InterpolantFactoryMethodSmooth=void 0;class xb extends xd{constructor(e,t,n,i){super(e,t,n,i)}}xb.prototype.ValueTypeName="vector";class yb{constructor(e="",t=-1,n=[],i=x0){this.name=e,this.tracks=n,this.duration=t,this.blendMode=i,this.uuid=Ga(),this.userData={},this.duration<0&&this.resetDuration()}static parse(e){const t=[],n=e.tracks,i=1/(e.fps||1);for(let a=0,o=n.length;a!==o;++a)t.push(zL(n[a]).scale(i));const s=new this(e.name,e.duration,t,e.blendMode);return s.uuid=e.uuid,s.userData=JSON.parse(e.userData||"{}"),s}static toJSON(e){const t=[],n=e.tracks,i={name:e.name,duration:e.duration,tracks:t,uuid:e.uuid,blendMode:e.blendMode,userData:JSON.stringify(e.userData)};for(let s=0,a=n.length;s!==a;++s)t.push(xd.toJSON(n[s]));return i}static CreateFromMorphTargetSequence(e,t,n,i){const s=t.length,a=[];for(let o=0;o<s;o++){let l=[],u=[];l.push((o+s-1)%s,o,(o+1)%s),u.push(0,1,0);const c=O5(l);l=F1(l,1,c),u=F1(u,1,c),!i&&l[0]===0&&(l.push(s),u.push(u[0])),a.push(new vb(".morphTargetInfluences["+t[o].name+"]",l,u).scale(1/n))}return new this(e,-1,a)}static findByName(e,t){let n=e;if(!Array.isArray(e)){const i=e;n=i.geometry&&i.geometry.animations||i.animations}for(let i=0;i<n.length;i++)if(n[i].name===t)return n[i];return null}static CreateClipsFromMorphTargetSequences(e,t,n){const i={},s=/^([\w-]*?)([\d]+)$/;for(let o=0,l=e.length;o<l;o++){const u=e[o],c=u.name.match(s);if(c&&c.length>1){const d=c[1];let f=i[d];f||(i[d]=f=[]),f.push(u)}}const a=[];for(const o in i)a.push(this.CreateFromMorphTargetSequence(o,i[o],t,n));return a}static parseAnimation(e,t){if(ze("AnimationClip: parseAnimation() is deprecated and will be removed with r185"),!e)return rt("AnimationClip: No animation in JSONLoader data."),null;const n=function(d,f,h,p,x){if(h.length!==0){const v=[],m=[];R1(h,v,m,p),v.length!==0&&x.push(new d(f,v,m))}},i=[],s=e.name||"default",a=e.fps||30,o=e.blendMode;let l=e.length||-1;const u=e.hierarchy||[];for(let d=0;d<u.length;d++){const f=u[d].keys;if(!(!f||f.length===0))if(f[0].morphTargets){const h={};let p;for(p=0;p<f.length;p++)if(f[p].morphTargets)for(let x=0;x<f[p].morphTargets.length;x++)h[f[p].morphTargets[x]]=-1;for(const x in h){const v=[],m=[];for(let C=0;C!==f[p].morphTargets.length;++C){const w=f[p];v.push(w.time),m.push(w.morphTarget===x?1:0)}i.push(new vb(".morphTargetInfluence["+x+"]",v,m))}l=h.length*a}else{const h=".bones["+t[d].name+"]";n(xb,h+".position",f,"pos",i),n(Ab,h+".quaternion",f,"rot",i),n(xb,h+".scale",f,"scl",i)}}return i.length===0?null:new this(s,l,i,o)}resetDuration(){const e=this.tracks;let t=0;for(let n=0,i=e.length;n!==i;++n){const s=this.tracks[n];t=Math.max(t,s.times[s.times.length-1])}return this.duration=t,this}trim(){for(let e=0;e<this.tracks.length;e++)this.tracks[e].trim(0,this.duration);return this}validate(){let e=!0;for(let t=0;t<this.tracks.length;t++)e=e&&this.tracks[t].validate();return e}optimize(){for(let e=0;e<this.tracks.length;e++)this.tracks[e].optimize();return this}clone(){const e=[];for(let n=0;n<this.tracks.length;n++)e.push(this.tracks[n].clone());const t=new this.constructor(this.name,this.duration,e,this.blendMode);return t.userData=JSON.parse(JSON.stringify(this.userData)),t}toJSON(){return this.constructor.toJSON(this)}}function OL(r){switch(r.toLowerCase()){case"scalar":case"double":case"float":case"number":case"integer":return vb;case"vector":case"vector2":case"vector3":case"vector4":return xb;case"color":return H5;case"quaternion":return Ab;case"bool":case"boolean":return Kv;case"string":return qv}throw new Error("THREE.KeyframeTrack: Unsupported typeName: "+r)}function zL(r){if(r.type===void 0)throw new Error("THREE.KeyframeTrack: track type undefined, can not parse");const 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o.image.width=f.width,o.image.height=f.height,o.mipmaps=f.mipmaps;f.mipmapCount===1&&(o.minFilter=ms),o.format=f.format,o.needsUpdate=!0,t&&t(o)},n,i);return o}}const _v=new WeakMap;class bb extends L1{constructor(e){super(e)}load(e,t,n,i){this.path!==void 0&&(e=this.path+e),e=this.manager.resolveURL(e);const s=this,a=fh.get(`image:${e}`);if(a!==void 0){if(a.complete===!0)s.manager.itemStart(e),setTimeout(function(){t&&t(a),s.manager.itemEnd(e)},0);else{let d=_v.get(a);d===void 0&&(d=[],_v.set(a,d)),d.push({onLoad:t,onError:i})}return a}const o=ua("img");function l(){c(),t&&t(this);const d=_v.get(this)||[];for(let f=0;f<d.length;f++){const h=d[f];h.onLoad&&h.onLoad(this)}_v.delete(this),s.manager.itemEnd(e)}function u(d){c(),i&&i(d),fh.remove(`image:${e}`);const f=_v.get(this)||[];for(let h=0;h<f.length;h++){const p=f[h];p.onError&&p.onError(d)}_v.delete(this),s.manager.itemError(e),s.manager.itemEnd(e)}function 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Vn(e),this.intensity=t}dispose(){this.dispatchEvent({type:"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,t}}class k5 extends Jm{constructor(e,t,n){super(e,n),this.isHemisphereLight=!0,this.type="HemisphereLight",this.position.copy(so.DEFAULT_UP),this.updateMatrix(),this.groundColor=new Vn(t)}copy(e,t){return super.copy(e,t),this.groundColor.copy(e.groundColor),this}toJSON(e){const t=super.toJSON(e);return t.object.groundColor=this.groundColor.getHex(),t}}const O1=new Cr,V5=new J,j5=new J;class z1{constructor(e){this.camera=e,this.intensity=1,this.bias=0,this.normalBias=0,this.radius=1,this.blurSamples=8,this.mapSize=new ct(512,512),this.mapType=fa,this.map=null,this.mapPass=null,this.matrix=new Cr,this.autoUpdate=!0,this.needsUpdate=!1,this._frustum=new Wv,this._frameExtents=new ct(1,1),this._viewportCount=1,this._viewports=[new Ei(0,0,1,1)]}getViewportCount(){return this._viewportCount}getFrustum(){return this._frustum}updateMatrices(e){const t=this.camera,n=this.matrix;V5.setFromMatrixPosition(e.matrixWorld),t.position.copy(V5),j5.setFromMatrixPosition(e.target.matrixWorld),t.lookAt(j5),t.updateMatrixWorld(),O1.multiplyMatrices(t.projectionMatrix,t.matrixWorldInverse),this._frustum.setFromProjectionMatrix(O1,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(O1)}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 this.intensity!==1&&(e.intensity=this.intensity),this.bias!==0&&(e.bias=this.bias),this.normalBias!==0&&(e.normalBias=this.normalBias),this.radius!==1&&(e.radius=this.radius),(this.mapSize.x!==512||this.mapSize.y!==512)&&(e.mapSize=this.mapSize.toArray()),e.camera=this.camera.toJSON(!1).object,delete e.camera.matrix,e}}class VL extends z1{constructor(){super(new bo(50,1,.5,500)),this.isSpotLightShadow=!0,this.focus=1,this.aspect=1}updateMatrices(e){const t=this.camera,n=Bc*2*e.angle*this.focus,i=this.mapSize.width/this.mapSize.height*this.aspect,s=e.distance||t.far;(n!==t.fov||i!==t.aspect||s!==t.far)&&(t.fov=n,t.aspect=i,t.far=s,t.updateProjectionMatrix()),super.updateMatrices(e)}copy(e){return super.copy(e),this.focus=e.focus,this}}class Eb extends Jm{constructor(e,t,n=0,i=Math.PI/3,s=0,a=2){super(e,t),this.isSpotLight=!0,this.type="SpotLight",this.position.copy(so.DEFAULT_UP),this.updateMatrix(),this.target=new so,this.distance=n,this.angle=i,this.penumbra=s,this.decay=a,this.map=null,this.shadow=new VL}get power(){return this.intensity*Math.PI}set power(e){this.intensity=e/Math.PI}dispose(){super.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.map=e.map,this.shadow=e.shadow.clone(),this}toJSON(e){const t=super.toJSON(e);return t.object.distance=this.distance,t.object.angle=this.angle,t.object.decay=this.decay,t.object.penumbra=this.penumbra,t.object.target=this.target.uuid,this.map&&this.map.isTexture&&(t.object.map=this.map.toJSON(e).uuid),t.object.shadow=this.shadow.toJSON(),t}}class jL extends z1{constructor(){super(new bo(90,1,.5,500)),this.isPointLightShadow=!0}}class X5 extends Jm{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 jL}get power(){return this.intensity*4*Math.PI}set power(e){this.intensity=e/(4*Math.PI)}dispose(){super.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}toJSON(e){const t=super.toJSON(e);return t.object.distance=this.distance,t.object.decay=this.decay,t.object.shadow=this.shadow.toJSON(),t}}class Km extends jy{constructor(e=-1,t=1,n=1,i=-1,s=.1,a=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=s,this.far=a,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=e.view===null?null:Object.assign({},e.view),this}setViewOffset(e,t,n,i,s,a){this.view===null&&(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=s,this.view.height=a,this.updateProjectionMatrix()}clearViewOffset(){this.view!==null&&(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 s=n-e,a=n+e,o=i+t,l=i-t;if(this.view!==null&&this.view.enabled){const u=(this.right-this.left)/this.view.fullWidth/this.zoom,c=(this.top-this.bottom)/this.view.fullHeight/this.zoom;s+=u*this.view.offsetX,a=s+u*this.view.width,o-=c*this.view.offsetY,l=o-c*this.view.height}this.projectionMatrix.makeOrthographic(s,a,o,l,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,this.view!==null&&(t.object.view=Object.assign({},this.view)),t}}class XL extends z1{constructor(){super(new Km(-5,5,5,-5,.5,500)),this.isDirectionalLightShadow=!0}}class H1 extends Jm{constructor(e,t){super(e,t),this.isDirectionalLight=!0,this.type="DirectionalLight",this.position.copy(so.DEFAULT_UP),this.updateMatrix(),this.target=new so,this.shadow=new XL}dispose(){super.dispose(),this.shadow.dispose()}copy(e){return super.copy(e),this.target=e.target.clone(),this.shadow=e.shadow.clone(),this}toJSON(e){const t=super.toJSON(e);return t.object.shadow=this.shadow.toJSON(),t.object.target=this.target.uuid,t}}class U1 extends Jm{constructor(e,t){super(e,t),this.isAmbientLight=!0,this.type="AmbientLight"}}class G5 extends Jm{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 W5{constructor(){this.isSphericalHarmonics3=!0,this.coefficients=[];for(let e=0;e<9;e++)this.coefficients.push(new J)}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,s=e.z,a=this.coefficients;return t.copy(a[0]).multiplyScalar(.282095),t.addScaledVector(a[1],.488603*i),t.addScaledVector(a[2],.488603*s),t.addScaledVector(a[3],.488603*n),t.addScaledVector(a[4],1.092548*(n*i)),t.addScaledVector(a[5],1.092548*(i*s)),t.addScaledVector(a[6],.315392*(3*s*s-1)),t.addScaledVector(a[7],1.092548*(n*s)),t.addScaledVector(a[8],.546274*(n*n-i*i)),t}getIrradianceAt(e,t){const n=e.x,i=e.y,s=e.z,a=this.coefficients;return t.copy(a[0]).multiplyScalar(.886227),t.addScaledVector(a[1],2*.511664*i),t.addScaledVector(a[2],2*.511664*s),t.addScaledVector(a[3],2*.511664*n),t.addScaledVector(a[4],2*.429043*n*i),t.addScaledVector(a[5],2*.429043*i*s),t.addScaledVector(a[6],.743125*s*s-.247708),t.addScaledVector(a[7],2*.429043*n*s),t.addScaledVector(a[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+i*3);return this}toArray(e=[],t=0){const n=this.coefficients;for(let i=0;i<9;i++)n[i].toArray(e,t+i*3);return e}static getBasisAt(e,t){const n=e.x,i=e.y,s=e.z;t[0]=.282095,t[1]=.488603*i,t[2]=.488603*s,t[3]=.488603*n,t[4]=1.092548*n*i,t[5]=1.092548*i*s,t[6]=.315392*(3*s*s-1),t[7]=1.092548*n*s,t[8]=.546274*(n*n-i*i)}}class Q5 extends Jm{constructor(e=new W5,t=1){super(void 0,t),this.isLightProbe=!0,this.sh=e}copy(e){return super.copy(e),this.sh.copy(e.sh),this}toJSON(e){const t=super.toJSON(e);return t.object.sh=this.sh.toArray(),t}}class k1 extends null{constructor(e){super(e),this.textures={}}load(e,t,n,i){const s=this,a=new Ip(s.manager);a.setPath(s.path),a.setRequestHeader(s.requestHeader),a.setWithCredentials(s.withCredentials),a.load(e,function(o){try{t(s.parse(JSON.parse(o)))}catch(l){i?i(l):rt(l),s.manager.itemError(e)}},n,i)}parse(e){const t=this.textures;function n(s){return t[s]===void 0&&ze("MaterialLoader: Undefined texture",s),t[s]}const i=this.createMaterialFromType(e.type);if(e.uuid!==void 0&&(i.uuid=e.uuid),e.name!==void 0&&(i.name=e.name),e.color!==void 0&&i.color!==void 0&&i.color.setHex(e.color),e.roughness!==void 0&&(i.roughness=e.roughness),e.metalness!==void 0&&(i.metalness=e.metalness),e.sheen!==void 0&&(i.sheen=e.sheen),e.sheenColor!==void 0&&(i.sheenColor=new Vn().setHex(e.sheenColor)),e.sheenRoughness!==void 0&&(i.sheenRoughness=e.sheenRoughness),e.emissive!==void 0&&i.emissive!==void 0&&i.emissive.setHex(e.emissive),e.specular!==void 0&&i.specular!==void 0&&i.specular.setHex(e.specular),e.specularIntensity!==void 0&&(i.specularIntensity=e.specularIntensity),e.specularColor!==void 0&&i.specularColor!==void 0&&i.specularColor.setHex(e.specularColor),e.shininess!==void 0&&(i.shininess=e.shininess),e.clearcoat!==void 0&&(i.clearcoat=e.clearcoat),e.clearcoatRoughness!==void 0&&(i.clearcoatRoughness=e.clearcoatRoughness),e.dispersion!==void 0&&(i.dispersion=e.dispersion),e.iridescence!==void 0&&(i.iridescence=e.iridescence),e.iridescenceIOR!==void 0&&(i.iridescenceIOR=e.iridescenceIOR),e.iridescenceThicknessRange!==void 0&&(i.iridescenceThicknessRange=e.iridescenceThicknessRange),e.transmission!==void 0&&(i.transmission=e.transmission),e.thickness!==void 0&&(i.thickness=e.thickness),e.attenuationDistance!==void 0&&(i.attenuationDistance=e.attenuationDistance),e.attenuationColor!==void 0&&i.attenuationColor!==void 0&&i.attenuationColor.setHex(e.attenuationColor),e.anisotropy!==void 0&&(i.anisotropy=e.anisotropy),e.anisotropyRotation!==void 0&&(i.anisotropyRotation=e.anisotropyRotation),e.fog!==void 0&&(i.fog=e.fog),e.flatShading!==void 0&&(i.flatShading=e.flatShading),e.blending!==void 0&&(i.blending=e.blending),e.combine!==void 0&&(i.combine=e.combine),e.side!==void 0&&(i.side=e.side),e.shadowSide!==void 0&&(i.shadowSide=e.shadowSide),e.opacity!==void 0&&(i.opacity=e.opacity),e.transparent!==void 0&&(i.transparent=e.transparent),e.alphaTest!==void 0&&(i.alphaTest=e.alphaTest),e.alphaHash!==void 0&&(i.alphaHash=e.alphaHash),e.depthFunc!==void 0&&(i.depthFunc=e.depthFunc),e.depthTest!==void 0&&(i.depthTest=e.depthTest),e.depthWrite!==void 0&&(i.depthWrite=e.depthWrite),e.colorWrite!==void 0&&(i.colorWrite=e.colorWrite),e.blendSrc!==void 0&&(i.blendSrc=e.blendSrc),e.blendDst!==void 0&&(i.blendDst=e.blendDst),e.blendEquation!==void 0&&(i.blendEquation=e.blendEquation),e.blendSrcAlpha!==void 0&&(i.blendSrcAlpha=e.blendSrcAlpha),e.blendDstAlpha!==void 0&&(i.blendDstAlpha=e.blendDstAlpha),e.blendEquationAlpha!==void 0&&(i.blendEquationAlpha=e.blendEquationAlpha),e.blendColor!==void 0&&i.blendColor!==void 0&&i.blendColor.setHex(e.blendColor),e.blendAlpha!==void 0&&(i.blendAlpha=e.blendAlpha),e.stencilWriteMask!==void 0&&(i.stencilWriteMask=e.stencilWriteMask),e.stencilFunc!==void 0&&(i.stencilFunc=e.stencilFunc),e.stencilRef!==void 0&&(i.stencilRef=e.stencilRef),e.stencilFuncMask!==void 0&&(i.stencilFuncMask=e.stencilFuncMask),e.stencilFail!==void 0&&(i.stencilFail=e.stencilFail),e.stencilZFail!==void 0&&(i.stencilZFail=e.stencilZFail),e.stencilZPass!==void 0&&(i.stencilZPass=e.stencilZPass),e.stencilWrite!==void 0&&(i.stencilWrite=e.stencilWrite),e.wireframe!==void 0&&(i.wireframe=e.wireframe),e.wireframeLinewidth!==void 0&&(i.wireframeLinewidth=e.wireframeLinewidth),e.wireframeLinecap!==void 0&&(i.wireframeLinecap=e.wireframeLinecap),e.wireframeLinejoin!==void 0&&(i.wireframeLinejoin=e.wireframeLinejoin),e.rotation!==void 0&&(i.rotation=e.rotation),e.linewidth!==void 0&&(i.linewidth=e.linewidth),e.dashSize!==void 0&&(i.dashSize=e.dashSize),e.gapSize!==void 0&&(i.gapSize=e.gapSize),e.scale!==void 0&&(i.scale=e.scale),e.polygonOffset!==void 0&&(i.polygonOffset=e.polygonOffset),e.polygonOffsetFactor!==void 0&&(i.polygonOffsetFactor=e.polygonOffsetFactor),e.polygonOffsetUnits!==void 0&&(i.polygonOffsetUnits=e.polygonOffsetUnits),e.dithering!==void 0&&(i.dithering=e.dithering),e.alphaToCoverage!==void 0&&(i.alphaToCoverage=e.alphaToCoverage),e.premultipliedAlpha!==void 0&&(i.premultipliedAlpha=e.premultipliedAlpha),e.forceSinglePass!==void 0&&(i.forceSinglePass=e.forceSinglePass),e.allowOverride!==void 0&&(i.allowOverride=e.allowOverride),e.visible!==void 0&&(i.visible=e.visible),e.toneMapped!==void 0&&(i.toneMapped=e.toneMapped),e.userData!==void 0&&(i.userData=e.userData),e.vertexColors!==void 0&&(typeof e.vertexColors=="number"?i.vertexColors=e.vertexColors>0:i.vertexColors=e.vertexColors),e.uniforms!==void 0)for(const s in e.uniforms){const a=e.uniforms[s];switch(i.uniforms[s]={},a.type){case"t":i.uniforms[s].value=n(a.value);break;case"c":i.uniforms[s].value=new Vn().setHex(a.value);break;case"v2":i.uniforms[s].value=new ct().fromArray(a.value);break;case"v3":i.uniforms[s].value=new J().fromArray(a.value);break;case"v4":i.uniforms[s].value=new Ei().fromArray(a.value);break;case"m3":i.uniforms[s].value=new zi().fromArray(a.value);break;case"m4":i.uniforms[s].value=new Cr().fromArray(a.value);break;default:i.uniforms[s].value=a.value}}if(e.defines!==void 0&&(i.defines=e.defines),e.vertexShader!==void 0&&(i.vertexShader=e.vertexShader),e.fragmentShader!==void 0&&(i.fragmentShader=e.fragmentShader),e.glslVersion!==void 0&&(i.glslVersion=e.glslVersion),e.extensions!==void 0)for(const s in e.extensions)i.extensions[s]=e.extensions[s];if(e.lights!==void 0&&(i.lights=e.lights),e.clipping!==void 0&&(i.clipping=e.clipping),e.size!==void 0&&(i.size=e.size),e.sizeAttenuation!==void 0&&(i.sizeAttenuation=e.sizeAttenuation),e.map!==void 0&&(i.map=n(e.map)),e.matcap!==void 0&&(i.matcap=n(e.matcap)),e.alphaMap!==void 0&&(i.alphaMap=n(e.alphaMap)),e.bumpMap!==void 0&&(i.bumpMap=n(e.bumpMap)),e.bumpScale!==void 0&&(i.bumpScale=e.bumpScale),e.normalMap!==void 0&&(i.normalMap=n(e.normalMap)),e.normalMapType!==void 0&&(i.normalMapType=e.normalMapType),e.normalScale!==void 0){let s=e.normalScale;Array.isArray(s)===!1&&(s=[s,s]),i.normalScale=new ct().fromArray(s)}return e.displacementMap!==void 0&&(i.displacementMap=n(e.displacementMap)),e.displacementScale!==void 0&&(i.displacementScale=e.displacementScale),e.displacementBias!==void 0&&(i.displacementBias=e.displacementBias),e.roughnessMap!==void 0&&(i.roughnessMap=n(e.roughnessMap)),e.metalnessMap!==void 0&&(i.metalnessMap=n(e.metalnessMap)),e.emissiveMap!==void 0&&(i.emissiveMap=n(e.emissiveMap)),e.emissiveIntensity!==void 0&&(i.emissiveIntensity=e.emissiveIntensity),e.specularMap!==void 0&&(i.specularMap=n(e.specularMap)),e.specularIntensityMap!==void 0&&(i.specularIntensityMap=n(e.specularIntensityMap)),e.specularColorMap!==void 0&&(i.specularColorMap=n(e.specularColorMap)),e.envMap!==void 0&&(i.envMap=n(e.envMap)),e.envMapRotation!==void 0&&i.envMapRotation.fromArray(e.envMapRotation),e.envMapIntensity!==void 0&&(i.envMapIntensity=e.envMapIntensity),e.reflectivity!==void 0&&(i.reflectivity=e.reflectivity),e.refractionRatio!==void 0&&(i.refractionRatio=e.refractionRatio),e.lightMap!==void 0&&(i.lightMap=n(e.lightMap)),e.lightMapIntensity!==void 0&&(i.lightMapIntensity=e.lightMapIntensity),e.aoMap!==void 0&&(i.aoMap=n(e.aoMap)),e.aoMapIntensity!==void 0&&(i.aoMapIntensity=e.aoMapIntensity),e.gradientMap!==void 0&&(i.gradientMap=n(e.gradientMap)),e.clearcoatMap!==void 0&&(i.clearcoatMap=n(e.clearcoatMap)),e.clearcoatRoughnessMap!==void 0&&(i.clearcoatRoughnessMap=n(e.clearcoatRoughnessMap)),e.clearcoatNormalMap!==void 0&&(i.clearcoatNormalMap=n(e.clearcoatNormalMap)),e.clearcoatNormalScale!==void 0&&(i.clearcoatNormalScale=new ct().fromArray(e.clearcoatNormalScale)),e.iridescenceMap!==void 0&&(i.iridescenceMap=n(e.iridescenceMap)),e.iridescenceThicknessMap!==void 0&&(i.iridescenceThicknessMap=n(e.iridescenceThicknessMap)),e.transmissionMap!==void 0&&(i.transmissionMap=n(e.transmissionMap)),e.thicknessMap!==void 0&&(i.thicknessMap=n(e.thicknessMap)),e.anisotropyMap!==void 0&&(i.anisotropyMap=n(e.anisotropyMap)),e.sheenColorMap!==void 0&&(i.sheenColorMap=n(e.sheenColorMap)),e.sheenRoughnessMap!==void 0&&(i.sheenRoughnessMap=n(e.sheenRoughnessMap)),i}setTextures(e){return this.textures=e,this}createMaterialFromType(e){return k1.createMaterialFromType(e)}static createMaterialFromType(e){const t={ShadowMaterial:S5,SpriteMaterial:KC,RawShaderMaterial:D5,ShaderMaterial:$u,PointsMaterial:s1,MeshPhysicalMaterial:T5,MeshStandardMaterial:D1,MeshPhongMaterial:T1,MeshToonMaterial:I5,MeshNormalMaterial:N5,MeshLambertMaterial:I1,MeshDepthMaterial:F5,MeshDistanceMaterial:R5,MeshBasicMaterial:rl,MeshMatcapMaterial:L5,LineDashedMaterial:N1,LineBasicMaterial:kl,Material:bl};return new t[e]}}class Z5{static extractUrlBase(e){const t=e.lastIndexOf("/");return t===-1?"./":e.slice(0,t+1)}static resolveURL(e,t){return typeof e!="string"||e===""?"":(/^https?:\/\//i.test(t)&&/^\//.test(e)&&(t=t.replace(/(^https?:\/\/[^\/]+).*/i,"$1")),/^(https?:)?\/\//i.test(e)||/^data:.*,.*$/i.test(e)||/^blob:.*$/i.test(e)?e:t+e)}}class GL extends null{constructor(){super(),this.isInstancedBufferGeometry=!0,this.type="InstancedBufferGeometry",this.instanceCount=1/0}copy(e){return super.copy(e),this.instanceCount=e.instanceCount,this}toJSON(){const e=super.toJSON();return e.instanceCount=this.instanceCount,e.isInstancedBufferGeometry=!0,e}}class WL extends null{constructor(e){super(e)}load(e,t,n,i){const s=this,a=new Ip(s.manager);a.setPath(s.path),a.setRequestHeader(s.requestHeader),a.setWithCredentials(s.withCredentials),a.load(e,function(o){try{t(s.parse(JSON.parse(o)))}catch(l){i?i(l):rt(l),s.manager.itemError(e)}},n,i)}parse(e){const t={},n={};function i(h,p){if(t[p]!==void 0)return t[p];const v=h.interleavedBuffers[p],m=s(h,v.buffer),C=qs(v.type,m),w=new Gy(C,v.stride);return w.uuid=v.uuid,t[p]=w,w}function s(h,p){if(n[p]!==void 0)return n[p];const v=h.arrayBuffers[p],m=new Uint32Array(v).buffer;return n[p]=m,m}const a=e.isInstancedBufferGeometry?new GL:new Ni,o=e.data.index;if(o!==void 0){const h=qs(o.type,o.array);a.setIndex(new ga(h,1))}const l=e.data.attributes;for(const h in l){const p=l[h];let x;if(p.isInterleavedBufferAttribute){const v=i(e.data,p.data);x=new jm(v,p.itemSize,p.offset,p.normalized)}else{const v=qs(p.type,p.array),m=p.isInstancedBufferAttribute?gd:ga;x=new m(v,p.itemSize,p.normalized)}p.name!==void 0&&(x.name=p.name),p.usage!==void 0&&x.setUsage(p.usage),a.setAttribute(h,x)}const u=e.data.morphAttributes;if(u)for(const h in u){const p=u[h],x=[];for(let v=0,m=p.length;v<m;v++){const C=p[v];let w;if(C.isInterleavedBufferAttribute){const P=i(e.data,C.data);w=new jm(P,C.itemSize,C.offset,C.normalized)}else{const P=qs(C.type,C.array);w=new ga(P,C.itemSize,C.normalized)}C.name!==void 0&&(w.name=C.name),x.push(w)}a.morphAttributes[h]=x}e.data.morphTargetsRelative&&(a.morphTargetsRelative=!0);const d=e.data.groups||e.data.drawcalls||e.data.offsets;if(d!==void 0)for(let h=0,p=d.length;h!==p;++h){const x=d[h];a.addGroup(x.start,x.count,x.materialIndex)}const f=e.data.boundingSphere;return f!==void 0&&(a.boundingSphere=new yl().fromJSON(f)),e.name&&(a.name=e.name),e.userData&&(a.userData=e.userData),a}}class cce extends null{constructor(e){super(e)}load(e,t,n,i){const s=this,a=this.path===""?Z5.extractUrlBase(e):this.path;this.resourcePath=this.resourcePath||a;const o=new Ip(this.manager);o.setPath(this.path),o.setRequestHeader(this.requestHeader),o.setWithCredentials(this.withCredentials),o.load(e,function(l){let u=null;try{u=JSON.parse(l)}catch(d){i!==void 0&&i(d),d("ObjectLoader: Can't parse "+e+".",d.message);return}const c=u.metadata;if(c===void 0||c.type===void 0||c.type.toLowerCase()==="geometry"){i!==void 0&&i(new Error("THREE.ObjectLoader: Can't load "+e)),rt("ObjectLoader: Can't load "+e);return}s.parse(u,t)},n,i)}loadAsync(e,t){return Kr(this,null,function*(){const n=this,i=this.path===""?Z5.extractUrlBase(e):this.path;this.resourcePath=this.resourcePath||i;const s=new Ip(this.manager);s.setPath(this.path),s.setRequestHeader(this.requestHeader),s.setWithCredentials(this.withCredentials);const a=yield s.loadAsync(e,t),o=JSON.parse(a),l=o.metadata;if(l===void 0||l.type===void 0||l.type.toLowerCase()==="geometry")throw new Error("THREE.ObjectLoader: Can't load "+e);return yield n.parseAsync(o)})}parse(e,t){const n=this.parseAnimations(e.animations),i=this.parseShapes(e.shapes),s=this.parseGeometries(e.geometries,i),a=this.parseImages(e.images,function(){t!==void 0&&t(u)}),o=this.parseTextures(e.textures,a),l=this.parseMaterials(e.materials,o),u=this.parseObject(e.object,s,l,o,n),c=this.parseSkeletons(e.skeletons,u);if(this.bindSkeletons(u,c),this.bindLightTargets(u),t!==void 0){let d=!1;for(const f in a)if(a[f].data instanceof HTMLImageElement){d=!0;break}d===!1&&t(u)}return u}parseAsync(e){return Kr(this,null,function*(){const t=this.parseAnimations(e.animations),n=this.parseShapes(e.shapes),i=this.parseGeometries(e.geometries,n),s=yield this.parseImagesAsync(e.images),a=this.parseTextures(e.textures,s),o=this.parseMaterials(e.materials,a),l=this.parseObject(e.object,i,o,a,t),u=this.parseSkeletons(e.skeletons,l);return this.bindSkeletons(l,u),this.bindLightTargets(l),l})}parseShapes(e){const t={};if(e!==void 0)for(let n=0,i=e.length;n<i;n++){const s=new Zv().fromJSON(e[n]);t[s.uuid]=s}return t}parseSkeletons(e,t){const n={},i={};if(t.traverse(function(s){s.isBone&&(i[s.uuid]=s)}),e!==void 0)for(let s=0,a=e.length;s<a;s++){const o=new e1().fromJSON(e[s],i);n[o.uuid]=o}return n}parseGeometries(e,t){const n={};if(e!==void 0){const i=new WL;for(let s=0,a=e.length;s<a;s++){let o;const l=e[s];switch(l.type){case"BufferGeometry":case"InstancedBufferGeometry":o=i.parse(l);break;default:l.type in M5?o=M5[l.type].fromJSON(l,t):ze(`ObjectLoader: Unsupported geometry type "${l.type}"`)}o.uuid=l.uuid,l.name!==void 0&&(o.name=l.name),l.userData!==void 0&&(o.userData=l.userData),n[l.uuid]=o}}return n}parseMaterials(e,t){const n={},i={};if(e!==void 0){const s=new k1;s.setTextures(t);for(let a=0,o=e.length;a<o;a++){const l=e[a];n[l.uuid]===void 0&&(n[l.uuid]=s.parse(l)),i[l.uuid]=n[l.uuid]}}return i}parseAnimations(e){const t={};if(e!==void 0)for(let n=0;n<e.length;n++){const i=e[n],s=yb.parse(i);t[s.uuid]=s}return t}parseImages(e,t){const n=this,i={};let s;function a(l){return n.manager.itemStart(l),s.load(l,function(){n.manager.itemEnd(l)},void 0,function(){n.manager.itemError(l),n.manager.itemEnd(l)})}function o(l){if(typeof l=="string"){const u=l,c=/^(\/\/)|([a-z]+:(\/\/)?)/i.test(u)?u:n.resourcePath+u;return a(c)}else return l.data?{data:qs(l.type,l.data),width:l.width,height:l.height}:null}if(e!==void 0&&e.length>0){const l=new U5(t);s=new bb(l),s.setCrossOrigin(this.crossOrigin);for(let u=0,c=e.length;u<c;u++){const d=e[u],f=d.url;if(Array.isArray(f)){const h=[];for(let p=0,x=f.length;p<x;p++){const v=f[p],m=o(v);m!==null&&(m instanceof HTMLImageElement?h.push(m):h.push(new Sc(m.data,m.width,m.height)))}i[d.uuid]=new Om(h)}else{const h=o(d.url);i[d.uuid]=new Om(h)}}}return i}parseImagesAsync(e){return Kr(this,null,function*(){const t=this,n={};let i;function s(a){return Kr(this,null,function*(){if(typeof a=="string"){const o=a,l=/^(\/\/)|([a-z]+:(\/\/)?)/i.test(o)?o:t.resourcePath+o;return yield i.loadAsync(l)}else return a.data?{data:qs(a.type,a.data),width:a.width,height:a.height}:null})}if(e!==void 0&&e.length>0){i=new bb(this.manager),i.setCrossOrigin(this.crossOrigin);for(let a=0,o=e.length;a<o;a++){const l=e[a],u=l.url;if(Array.isArray(u)){const c=[];for(let d=0,f=u.length;d<f;d++){const h=u[d],p=yield s(h);p!==null&&(p instanceof HTMLImageElement?c.push(p):c.push(new Sc(p.data,p.width,p.height)))}n[l.uuid]=new Om(c)}else{const c=yield s(l.url);n[l.uuid]=new Om(c)}}}return n})}parseTextures(e,t){function n(s,a){return typeof s=="number"?s:(ze("ObjectLoader.parseTexture: Constant should be in numeric form.",s),a[s])}const i={};if(e!==void 0)for(let s=0,a=e.length;s<a;s++){const o=e[s];o.image===void 0&&ze('ObjectLoader: No "image" specified for',o.uuid),t[o.image]===void 0&&ze("ObjectLoader: Undefined image",o.image);const l=t[o.image],u=l.data;let c;Array.isArray(u)?(c=new km,u.length===6&&(c.needsUpdate=!0)):(u&&u.data?c=new Sc:c=new yo,u&&(c.needsUpdate=!0)),c.source=l,c.uuid=o.uuid,o.name!==void 0&&(c.name=o.name),o.mapping!==void 0&&(c.mapping=n(o.mapping,QL)),o.channel!==void 0&&(c.channel=o.channel),o.offset!==void 0&&c.offset.fromArray(o.offset),o.repeat!==void 0&&c.repeat.fromArray(o.repeat),o.center!==void 0&&c.center.fromArray(o.center),o.rotation!==void 0&&(c.rotation=o.rotation),o.wrap!==void 0&&(c.wrapS=n(o.wrap[0],Y5),c.wrapT=n(o.wrap[1],Y5)),o.format!==void 0&&(c.format=o.format),o.internalFormat!==void 0&&(c.internalFormat=o.internalFormat),o.type!==void 0&&(c.type=o.type),o.colorSpace!==void 0&&(c.colorSpace=o.colorSpace),o.minFilter!==void 0&&(c.minFilter=n(o.minFilter,J5)),o.magFilter!==void 0&&(c.magFilter=n(o.magFilter,J5)),o.anisotropy!==void 0&&(c.anisotropy=o.anisotropy),o.flipY!==void 0&&(c.flipY=o.flipY),o.generateMipmaps!==void 0&&(c.generateMipmaps=o.generateMipmaps),o.premultiplyAlpha!==void 0&&(c.premultiplyAlpha=o.premultiplyAlpha),o.unpackAlignment!==void 0&&(c.unpackAlignment=o.unpackAlignment),o.compareFunction!==void 0&&(c.compareFunction=o.compareFunction),o.userData!==void 0&&(c.userData=o.userData),i[o.uuid]=c}return i}parseObject(e,t,n,i,s){let a;function o(f){return t[f]===void 0&&ze("ObjectLoader: Undefined geometry",f),t[f]}function l(f){if(f!==void 0){if(Array.isArray(f)){const h=[];for(let p=0,x=f.length;p<x;p++){const v=f[p];n[v]===void 0&&ze("ObjectLoader: Undefined material",v),h.push(n[v])}return h}return n[f]===void 0&&ze("ObjectLoader: Undefined material",f),n[f]}}function u(f){return i[f]===void 0&&ze("ObjectLoader: Undefined texture",f),i[f]}let c,d;switch(e.type){case"Scene":a=new R0,e.background!==void 0&&(Number.isInteger(e.background)?a.background=new Vn(e.background):a.background=u(e.background)),e.environment!==void 0&&(a.environment=u(e.environment)),e.fog!==void 0&&(e.fog.type==="Fog"?a.fog=new JC(e.fog.color,e.fog.near,e.fog.far):e.fog.type==="FogExp2"&&(a.fog=new YC(e.fog.color,e.fog.density)),e.fog.name!==""&&(a.fog.name=e.fog.name)),e.backgroundBlurriness!==void 0&&(a.backgroundBlurriness=e.backgroundBlurriness),e.backgroundIntensity!==void 0&&(a.backgroundIntensity=e.backgroundIntensity),e.backgroundRotation!==void 0&&a.backgroundRotation.fromArray(e.backgroundRotation),e.environmentIntensity!==void 0&&(a.environmentIntensity=e.environmentIntensity),e.environmentRotation!==void 0&&a.environmentRotation.fromArray(e.environmentRotation);break;case"PerspectiveCamera":a=new bo(e.fov,e.aspect,e.near,e.far),e.focus!==void 0&&(a.focus=e.focus),e.zoom!==void 0&&(a.zoom=e.zoom),e.filmGauge!==void 0&&(a.filmGauge=e.filmGauge),e.filmOffset!==void 0&&(a.filmOffset=e.filmOffset),e.view!==void 0&&(a.view=Object.assign({},e.view));break;case"OrthographicCamera":a=new Km(e.left,e.right,e.top,e.bottom,e.near,e.far),e.zoom!==void 0&&(a.zoom=e.zoom),e.view!==void 0&&(a.view=Object.assign({},e.view));break;case"AmbientLight":a=new U1(e.color,e.intensity);break;case"DirectionalLight":a=new H1(e.color,e.intensity),a.target=e.target||"";break;case"PointLight":a=new X5(e.color,e.intensity,e.distance,e.decay);break;case"RectAreaLight":a=new G5(e.color,e.intensity,e.width,e.height);break;case"SpotLight":a=new Eb(e.color,e.intensity,e.distance,e.angle,e.penumbra,e.decay),a.target=e.target||"";break;case"HemisphereLight":a=new k5(e.color,e.groundColor,e.intensity);break;case"LightProbe":const f=new W5().fromArray(e.sh);a=new Q5(f,e.intensity);break;case"SkinnedMesh":c=o(e.geometry),d=l(e.material),a=new FR(c,d),e.bindMode!==void 0&&(a.bindMode=e.bindMode),e.bindMatrix!==void 0&&a.bindMatrix.fromArray(e.bindMatrix),e.skeleton!==void 0&&(a.skeleton=e.skeleton);break;case"Mesh":c=o(e.geometry),d=l(e.material),a=new Gs(c,d);break;case"InstancedMesh":c=o(e.geometry),d=l(e.material);const h=e.count,p=e.instanceMatrix,x=e.instanceColor;a=new OR(c,d,h),a.instanceMatrix=new gd(new Float32Array(p.array),16),x!==void 0&&(a.instanceColor=new gd(new Float32Array(x.array),x.itemSize));break;case"BatchedMesh":c=o(e.geometry),d=l(e.material),a=new ZR(e.maxInstanceCount,e.maxVertexCount,e.maxIndexCount,d),a.geometry=c,a.perObjectFrustumCulled=e.perObjectFrustumCulled,a.sortObjects=e.sortObjects,a._drawRanges=e.drawRanges,a._reservedRanges=e.reservedRanges,a._geometryInfo=e.geometryInfo.map(v=>{let m=null,C=null;return v.boundingBox!==void 0&&(m=new xl().fromJSON(v.boundingBox)),v.boundingSphere!==void 0&&(C=new yl().fromJSON(v.boundingSphere)),Gc(ba({},v),{boundingBox:m,boundingSphere:C})}),a._instanceInfo=e.instanceInfo,a._availableInstanceIds=e._availableInstanceIds,a._availableGeometryIds=e._availableGeometryIds,a._nextIndexStart=e.nextIndexStart,a._nextVertexStart=e.nextVertexStart,a._geometryCount=e.geometryCount,a._maxInstanceCount=e.maxInstanceCount,a._maxVertexCount=e.maxVertexCount,a._maxIndexCount=e.maxIndexCount,a._geometryInitialized=e.geometryInitialized,a._matricesTexture=u(e.matricesTexture.uuid),a._indirectTexture=u(e.indirectTexture.uuid),e.colorsTexture!==void 0&&(a._colorsTexture=u(e.colorsTexture.uuid)),e.boundingSphere!==void 0&&(a.boundingSphere=new yl().fromJSON(e.boundingSphere)),e.boundingBox!==void 0&&(a.boundingBox=new xl().fromJSON(e.boundingBox));break;case"LOD":a=new IR;break;case"Line":a=new j0(o(e.geometry),l(e.material));break;case"LineLoop":a=new YR(o(e.geometry),l(e.material));break;case"LineSegments":a=new l5(o(e.geometry),l(e.material));break;case"PointCloud":case"Points":a=new JR(o(e.geometry),l(e.material));break;case"Sprite":a=new TR(l(e.material));break;case"Group":a=new Vm;break;case"Bone":a=new _S;break;default:a=new so}if(a.uuid=e.uuid,e.name!==void 0&&(a.name=e.name),e.matrix!==void 0?(a.matrix.fromArray(e.matrix),e.matrixAutoUpdate!==void 0&&(a.matrixAutoUpdate=e.matrixAutoUpdate),a.matrixAutoUpdate&&a.matrix.decompose(a.position,a.quaternion,a.scale)):(e.position!==void 0&&a.position.fromArray(e.position),e.rotation!==void 0&&a.rotation.fromArray(e.rotation),e.quaternion!==void 0&&a.quaternion.fromArray(e.quaternion),e.scale!==void 0&&a.scale.fromArray(e.scale)),e.up!==void 0&&a.up.fromArray(e.up),e.castShadow!==void 0&&(a.castShadow=e.castShadow),e.receiveShadow!==void 0&&(a.receiveShadow=e.receiveShadow),e.shadow&&(e.shadow.intensity!==void 0&&(a.shadow.intensity=e.shadow.intensity),e.shadow.bias!==void 0&&(a.shadow.bias=e.shadow.bias),e.shadow.normalBias!==void 0&&(a.shadow.normalBias=e.shadow.normalBias),e.shadow.radius!==void 0&&(a.shadow.radius=e.shadow.radius),e.shadow.mapSize!==void 0&&a.shadow.mapSize.fromArray(e.shadow.mapSize),e.shadow.camera!==void 0&&(a.shadow.camera=this.parseObject(e.shadow.camera))),e.visible!==void 0&&(a.visible=e.visible),e.frustumCulled!==void 0&&(a.frustumCulled=e.frustumCulled),e.renderOrder!==void 0&&(a.renderOrder=e.renderOrder),e.userData!==void 0&&(a.userData=e.userData),e.layers!==void 0&&(a.layers.mask=e.layers),e.children!==void 0){const f=e.children;for(let h=0;h<f.length;h++)a.add(this.parseObject(f[h],t,n,i,s))}if(e.animations!==void 0){const f=e.animations;for(let h=0;h<f.length;h++){const p=f[h];a.animations.push(s[p])}}if(e.type==="LOD"){e.autoUpdate!==void 0&&(a.autoUpdate=e.autoUpdate);const f=e.levels;for(let h=0;h<f.length;h++){const p=f[h],x=a.getObjectByProperty("uuid",p.object);x!==void 0&&a.addLevel(x,p.distance,p.hysteresis)}}return a}bindSkeletons(e,t){Object.keys(t).length!==0&&e.traverse(function(n){if(n.isSkinnedMesh===!0&&n.skeleton!==void 0){const i=t[n.skeleton];i===void 0?ze("ObjectLoader: No skeleton found with UUID:",n.skeleton):n.bind(i,n.bindMatrix)}})}bindLightTargets(e){e.traverse(function(t){if(t.isDirectionalLight||t.isSpotLight){const n=t.target,i=e.getObjectByProperty("uuid",n);i!==void 0?t.target=i:t.target=new so}})}}const QL={UVMapping:mi,CubeReflectionMapping:ai,CubeRefractionMapping:ps,EquirectangularReflectionMapping:Pa,EquirectangularRefractionMapping:ld,CubeUVReflectionMapping:Jd},Y5={RepeatWrapping:Zu,ClampToEdgeWrapping:So,MirroredRepeatWrapping:ud},J5={NearestFilter:Cs,NearestMipmapNearestFilter:Bm,NearestMipmapLinearFilter:wc,LinearFilter:ms,LinearMipmapNearestFilter:Yf,LinearMipmapLinearFilter:tl},V1=new WeakMap;class dce extends null{constructor(e){super(e),this.isImageBitmapLoader=!0,typeof createImageBitmap=="undefined"&&ze("ImageBitmapLoader: createImageBitmap() not supported."),typeof fetch=="undefined"&&ze("ImageBitmapLoader: fetch() not supported."),this.options={premultiplyAlpha:"none"},this._abortController=new AbortController}setOptions(e){return this.options=e,this}load(e,t,n,i){e===void 0&&(e=""),this.path!==void 0&&(e=this.path+e),e=this.manager.resolveURL(e);const s=this,a=fh.get(`image-bitmap:${e}`);if(a!==void 0){if(s.manager.itemStart(e),a.then){a.then(u=>{if(V1.has(a)===!0)i&&i(V1.get(a)),s.manager.itemError(e),s.manager.itemEnd(e);else return t&&t(u),s.manager.itemEnd(e),u});return}return setTimeout(function(){t&&t(a),s.manager.itemEnd(e)},0),a}const o={};o.credentials=this.crossOrigin==="anonymous"?"same-origin":"include",o.headers=this.requestHeader,o.signal=typeof AbortSignal.any=="function"?AbortSignal.any([this._abortController.signal,this.manager.abortController.signal]):this._abortController.signal;const l=fetch(e,o).then(function(u){return u.blob()}).then(function(u){return createImageBitmap(u,Object.assign(s.options,{colorSpaceConversion:"none"}))}).then(function(u){return fh.add(`image-bitmap:${e}`,u),t&&t(u),s.manager.itemEnd(e),u}).catch(function(u){i&&i(u),V1.set(l,u),fh.remove(`image-bitmap:${e}`),s.manager.itemError(e),s.manager.itemEnd(e)});fh.add(`image-bitmap:${e}`,l),s.manager.itemStart(e)}abort(){return this._abortController.abort(),this._abortController=new AbortController,this}}let wb;class K5{static getContext(){return wb===void 0&&(wb=new(window.AudioContext||window.webkitAudioContext)),wb}static setContext(e){wb=e}}class fce extends null{constructor(e){super(e)}load(e,t,n,i){const s=this,a=new Ip(this.manager);a.setResponseType("arraybuffer"),a.setPath(this.path),a.setRequestHeader(this.requestHeader),a.setWithCredentials(this.withCredentials),a.load(e,function(l){try{const u=l.slice(0);K5.getContext().decodeAudioData(u,function(d){t(d)}).catch(o)}catch(u){o(u)}},n,i);function o(l){i?i(l):rt(l),s.manager.itemError(e)}}}const q5=new Cr,_5=new Cr,qm=new Cr;class hce{constructor(){this.type="StereoCamera",this.aspect=1,this.eyeSep=.064,this.cameraL=new bo,this.cameraL.layers.enable(1),this.cameraL.matrixAutoUpdate=!1,this.cameraR=new bo,this.cameraR.layers.enable(2),this.cameraR.matrixAutoUpdate=!1,this._cache={focus:null,fov:null,aspect:null,near:null,far:null,zoom:null,eyeSep:null}}update(e){const t=this._cache;if(t.focus!==e.focus||t.fov!==e.fov||t.aspect!==e.aspect*this.aspect||t.near!==e.near||t.far!==e.far||t.zoom!==e.zoom||t.eyeSep!==this.eyeSep){t.focus=e.focus,t.fov=e.fov,t.aspect=e.aspect*this.aspect,t.near=e.near,t.far=e.far,t.zoom=e.zoom,t.eyeSep=this.eyeSep,qm.copy(e.projectionMatrix);const i=t.eyeSep/2,s=i*t.near/t.focus,a=t.near*Math.tan(nu*t.fov*.5)/t.zoom;let o,l;_5.elements[12]=-i,q5.elements[12]=i,o=-a*t.aspect+s,l=a*t.aspect+s,qm.elements[0]=2*t.near/(l-o),qm.elements[8]=(l+o)/(l-o),this.cameraL.projectionMatrix.copy(qm),o=-a*t.aspect-s,l=a*t.aspect-s,qm.elements[0]=2*t.near/(l-o),qm.elements[8]=(l+o)/(l-o),this.cameraR.projectionMatrix.copy(qm)}this.cameraL.matrixWorld.copy(e.matrixWorld).multiply(_5),this.cameraR.matrixWorld.copy(e.matrixWorld).multiply(q5)}}class $5 extends bo{constructor(e=[]){super(),this.isArrayCamera=!0,this.isMultiViewCamera=!1,this.cameras=e}}class j1{constructor(e=!0){this.autoStart=e,this.startTime=0,this.oldTime=0,this.elapsedTime=0,this.running=!1}start(){this.startTime=performance.now(),this.oldTime=this.startTime,this.elapsedTime=0,this.running=!0}stop(){this.getElapsedTime(),this.running=!1,this.autoStart=!1}getElapsedTime(){return this.getDelta(),this.elapsedTime}getDelta(){let e=0;if(this.autoStart&&!this.running)return this.start(),0;if(this.running){const t=performance.now();e=(t-this.oldTime)/1e3,this.oldTime=t,this.elapsedTime+=e}return e}}const _m=new J,X1=new Wo,ZL=new J,$m=new J,eg=new J;class pce extends null{constructor(){super(),this.type="AudioListener",this.context=K5.getContext(),this.gain=this.context.createGain(),this.gain.connect(this.context.destination),this.filter=null,this.timeDelta=0,this._clock=new j1}getInput(){return this.gain}removeFilter(){return this.filter!==null&&(this.gain.disconnect(this.filter),this.filter.disconnect(this.context.destination),this.gain.connect(this.context.destination),this.filter=null),this}getFilter(){return this.filter}setFilter(e){return this.filter!==null?(this.gain.disconnect(this.filter),this.filter.disconnect(this.context.destination)):this.gain.disconnect(this.context.destination),this.filter=e,this.gain.connect(this.filter),this.filter.connect(this.context.destination),this}getMasterVolume(){return this.gain.gain.value}setMasterVolume(e){return this.gain.gain.setTargetAtTime(e,this.context.currentTime,.01),this}updateMatrixWorld(e){super.updateMatrixWorld(e);const t=this.context.listener;if(this.timeDelta=this._clock.getDelta(),this.matrixWorld.decompose(_m,X1,ZL),$m.set(0,0,-1).applyQuaternion(X1),eg.set(0,1,0).applyQuaternion(X1),t.positionX){const n=this.context.currentTime+this.timeDelta;t.positionX.linearRampToValueAtTime(_m.x,n),t.positionY.linearRampToValueAtTime(_m.y,n),t.positionZ.linearRampToValueAtTime(_m.z,n),t.forwardX.linearRampToValueAtTime($m.x,n),t.forwardY.linearRampToValueAtTime($m.y,n),t.forwardZ.linearRampToValueAtTime($m.z,n),t.upX.linearRampToValueAtTime(eg.x,n),t.upY.linearRampToValueAtTime(eg.y,n),t.upZ.linearRampToValueAtTime(eg.z,n)}else t.setPosition(_m.x,_m.y,_m.z),t.setOrientation($m.x,$m.y,$m.z,eg.x,eg.y,eg.z)}}class mce extends null{constructor(e){super(),this.type="Audio",this.listener=e,this.context=e.context,this.gain=this.context.createGain(),this.gain.connect(e.getInput()),this.autoplay=!1,this.buffer=null,this.detune=0,this.loop=!1,this.loopStart=0,this.loopEnd=0,this.offset=0,this.duration=void 0,this.playbackRate=1,this.isPlaying=!1,this.hasPlaybackControl=!0,this.source=null,this.sourceType="empty",this._startedAt=0,this._progress=0,this._connected=!1,this.filters=[]}getOutput(){return this.gain}setNodeSource(e){return this.hasPlaybackControl=!1,this.sourceType="audioNode",this.source=e,this.connect(),this}setMediaElementSource(e){return this.hasPlaybackControl=!1,this.sourceType="mediaNode",this.source=this.context.createMediaElementSource(e),this.connect(),this}setMediaStreamSource(e){return this.hasPlaybackControl=!1,this.sourceType="mediaStreamNode",this.source=this.context.createMediaStreamSource(e),this.connect(),this}setBuffer(e){return this.buffer=e,this.sourceType="buffer",this.autoplay&&this.play(),this}play(e=0){if(this.isPlaying===!0){ze("Audio: Audio is already playing.");return}if(this.hasPlaybackControl===!1){ze("Audio: this Audio has no playback control.");return}this._startedAt=this.context.currentTime+e;const t=this.context.createBufferSource();return t.buffer=this.buffer,t.loop=this.loop,t.loopStart=this.loopStart,t.loopEnd=this.loopEnd,t.onended=this.onEnded.bind(this),t.start(this._startedAt,this._progress+this.offset,this.duration),this.isPlaying=!0,this.source=t,this.setDetune(this.detune),this.setPlaybackRate(this.playbackRate),this.connect()}pause(){if(this.hasPlaybackControl===!1){ze("Audio: this Audio has no playback control.");return}return this.isPlaying===!0&&(this._progress+=Math.max(this.context.currentTime-this._startedAt,0)*this.playbackRate,this.loop===!0&&(this._progress=this._progress%(this.duration||this.buffer.duration)),this.source.stop(),this.source.onended=null,this.isPlaying=!1),this}stop(e=0){if(this.hasPlaybackControl===!1){ze("Audio: this Audio has no playback control.");return}return this._progress=0,this.source!==null&&(this.source.stop(this.context.currentTime+e),this.source.onended=null),this.isPlaying=!1,this}connect(){if(this.filters.length>0){this.source.connect(this.filters[0]);for(let e=1,t=this.filters.length;e<t;e++)this.filters[e-1].connect(this.filters[e]);this.filters[this.filters.length-1].connect(this.getOutput())}else this.source.connect(this.getOutput());return this._connected=!0,this}disconnect(){if(this._connected!==!1){if(this.filters.length>0){this.source.disconnect(this.filters[0]);for(let e=1,t=this.filters.length;e<t;e++)this.filters[e-1].disconnect(this.filters[e]);this.filters[this.filters.length-1].disconnect(this.getOutput())}else this.source.disconnect(this.getOutput());return this._connected=!1,this}}getFilters(){return this.filters}setFilters(e){return e||(e=[]),this._connected===!0?(this.disconnect(),this.filters=e.slice(),this.connect()):this.filters=e.slice(),this}setDetune(e){return this.detune=e,this.isPlaying===!0&&this.source.detune!==void 0&&this.source.detune.setTargetAtTime(this.detune,this.context.currentTime,.01),this}getDetune(){return this.detune}getFilter(){return this.getFilters()[0]}setFilter(e){return this.setFilters(e?[e]:[])}setPlaybackRate(e){if(this.hasPlaybackControl===!1){ze("Audio: this Audio has no playback control.");return}return this.playbackRate=e,this.isPlaying===!0&&this.source.playbackRate.setTargetAtTime(this.playbackRate,this.context.currentTime,.01),this}getPlaybackRate(){return this.playbackRate}onEnded(){this.isPlaying=!1,this._progress=0}getLoop(){return this.hasPlaybackControl===!1?(ze("Audio: this Audio has no playback control."),!1):this.loop}setLoop(e){if(this.hasPlaybackControl===!1){ze("Audio: this Audio has no playback control.");return}return this.loop=e,this.isPlaying===!0&&(this.source.loop=this.loop),this}setLoopStart(e){return this.loopStart=e,this}setLoopEnd(e){return this.loopEnd=e,this}getVolume(){return this.gain.gain.value}setVolume(e){return this.gain.gain.setTargetAtTime(e,this.context.currentTime,.01),this}copy(e,t){return super.copy(e,t),e.sourceType!=="buffer"?(ze("Audio: Audio source type cannot be copied."),this):(this.autoplay=e.autoplay,this.buffer=e.buffer,this.detune=e.detune,this.loop=e.loop,this.loopStart=e.loopStart,this.loopEnd=e.loopEnd,this.offset=e.offset,this.duration=e.duration,this.playbackRate=e.playbackRate,this.hasPlaybackControl=e.hasPlaybackControl,this.sourceType=e.sourceType,this.filters=e.filters.slice(),this)}clone(e){return new this.constructor(this.listener).copy(this,e)}}const tg=new J,eD=new Wo,YL=new J,ng=new J;class gce extends null{constructor(e){super(e),this.panner=this.context.createPanner(),this.panner.panningModel="HRTF",this.panner.connect(this.gain)}connect(){return super.connect(),this.panner.connect(this.gain),this}disconnect(){return super.disconnect(),this.panner.disconnect(this.gain),this}getOutput(){return this.panner}getRefDistance(){return this.panner.refDistance}setRefDistance(e){return this.panner.refDistance=e,this}getRolloffFactor(){return this.panner.rolloffFactor}setRolloffFactor(e){return this.panner.rolloffFactor=e,this}getDistanceModel(){return this.panner.distanceModel}setDistanceModel(e){return this.panner.distanceModel=e,this}getMaxDistance(){return this.panner.maxDistance}setMaxDistance(e){return this.panner.maxDistance=e,this}setDirectionalCone(e,t,n){return this.panner.coneInnerAngle=e,this.panner.coneOuterAngle=t,this.panner.coneOuterGain=n,this}updateMatrixWorld(e){if(super.updateMatrixWorld(e),this.hasPlaybackControl===!0&&this.isPlaying===!1)return;this.matrixWorld.decompose(tg,eD,YL),ng.set(0,0,1).applyQuaternion(eD);const t=this.panner;if(t.positionX){const n=this.context.currentTime+this.listener.timeDelta;t.positionX.linearRampToValueAtTime(tg.x,n),t.positionY.linearRampToValueAtTime(tg.y,n),t.positionZ.linearRampToValueAtTime(tg.z,n),t.orientationX.linearRampToValueAtTime(ng.x,n),t.orientationY.linearRampToValueAtTime(ng.y,n),t.orientationZ.linearRampToValueAtTime(ng.z,n)}else t.setPosition(tg.x,tg.y,tg.z),t.setOrientation(ng.x,ng.y,ng.z)}}class vce{constructor(e,t=2048){this.analyser=e.context.createAnalyser(),this.analyser.fftSize=t,this.data=new Uint8Array(this.analyser.frequencyBinCount),e.getOutput().connect(this.analyser)}getFrequencyData(){return this.analyser.getByteFrequencyData(this.data),this.data}getAverageFrequency(){let e=0;const t=this.getFrequencyData();for(let n=0;n<t.length;n++)e+=t[n];return e/t.length}}class JL{constructor(e,t,n){this.binding=e,this.valueSize=n;let i,s,a;switch(t){case"quaternion":i=this._slerp,s=this._slerpAdditive,a=this._setAdditiveIdentityQuaternion,this.buffer=new Float64Array(n*6),this._workIndex=5;break;case"string":case"bool":i=this._select,s=this._select,a=this._setAdditiveIdentityOther,this.buffer=new Array(n*5);break;default:i=this._lerp,s=this._lerpAdditive,a=this._setAdditiveIdentityNumeric,this.buffer=new Float64Array(n*5)}this._mixBufferRegion=i,this._mixBufferRegionAdditive=s,this._setIdentity=a,this._origIndex=3,this._addIndex=4,this.cumulativeWeight=0,this.cumulativeWeightAdditive=0,this.useCount=0,this.referenceCount=0}accumulate(e,t){const n=this.buffer,i=this.valueSize,s=e*i+i;let a=this.cumulativeWeight;if(a===0){for(let o=0;o!==i;++o)n[s+o]=n[o];a=t}else{a+=t;const o=t/a;this._mixBufferRegion(n,s,0,o,i)}this.cumulativeWeight=a}accumulateAdditive(e){const t=this.buffer,n=this.valueSize,i=n*this._addIndex;this.cumulativeWeightAdditive===0&&this._setIdentity(),this._mixBufferRegionAdditive(t,i,0,e,n),this.cumulativeWeightAdditive+=e}apply(e){const t=this.valueSize,n=this.buffer,i=e*t+t,s=this.cumulativeWeight,a=this.cumulativeWeightAdditive,o=this.binding;if(this.cumulativeWeight=0,this.cumulativeWeightAdditive=0,s<1){const l=t*this._origIndex;this._mixBufferRegion(n,i,l,1-s,t)}a>0&&this._mixBufferRegionAdditive(n,i,this._addIndex*t,1,t);for(let l=t,u=t+t;l!==u;++l)if(n[l]!==n[l+t]){o.setValue(n,i);break}}saveOriginalState(){const e=this.binding,t=this.buffer,n=this.valueSize,i=n*this._origIndex;e.getValue(t,i);for(let s=n,a=i;s!==a;++s)t[s]=t[i+s%n];this._setIdentity(),this.cumulativeWeight=0,this.cumulativeWeightAdditive=0}restoreOriginalState(){const e=this.valueSize*3;this.binding.setValue(this.buffer,e)}_setAdditiveIdentityNumeric(){const e=this._addIndex*this.valueSize,t=e+this.valueSize;for(let n=e;n<t;n++)this.buffer[n]=0}_setAdditiveIdentityQuaternion(){this._setAdditiveIdentityNumeric(),this.buffer[this._addIndex*this.valueSize+3]=1}_setAdditiveIdentityOther(){const e=this._origIndex*this.valueSize,t=this._addIndex*this.valueSize;for(let n=0;n<this.valueSize;n++)this.buffer[t+n]=this.buffer[e+n]}_select(e,t,n,i,s){if(i>=.5)for(let a=0;a!==s;++a)e[t+a]=e[n+a]}_slerp(e,t,n,i){Wo.slerpFlat(e,t,e,t,e,n,i)}_slerpAdditive(e,t,n,i,s){const a=this._workIndex*s;Wo.multiplyQuaternionsFlat(e,a,e,t,e,n),Wo.slerpFlat(e,t,e,t,e,a,i)}_lerp(e,t,n,i,s){const a=1-i;for(let o=0;o!==s;++o){const l=t+o;e[l]=e[l]*a+e[n+o]*i}}_lerpAdditive(e,t,n,i,s){for(let a=0;a!==s;++a){const o=t+a;e[o]=e[o]+e[n+a]*i}}}const G1="\\[\\]\\.:\\/",KL=new RegExp("["+G1+"]","g"),W1="[^"+G1+"]",qL="[^"+G1.replace("\\.","")+"]",_L=/((?:WC+[\/:])*)/.source.replace("WC",W1),$L=/(WCOD+)?/.source.replace("WCOD",qL),eO=/(?:\.(WC+)(?:\[(.+)\])?)?/.source.replace("WC",W1),tO=/\.(WC+)(?:\[(.+)\])?/.source.replace("WC",W1),nO=new RegExp("^"+_L+$L+eO+tO+"$"),rO=["material","materials","bones","map"];class iO{constructor(e,t,n){const i=n||ks.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];i!==void 0&&i.getValue(e,t)}setValue(e,t){const n=this._bindings;for(let i=this._targetGroup.nCachedObjects_,s=n.length;i!==s;++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()}}class ks{constructor(e,t,n){this.path=t,this.parsedPath=n||ks.parseTrackName(t),this.node=ks.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 ks.Composite(e,t,n):new ks(e,t,n)}static sanitizeNodeName(e){return e.replace(/\s/g,"_").replace(KL,"")}static parseTrackName(e){const t=nO.exec(e);if(t===null)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(i!==void 0&&i!==-1){const s=n.nodeName.substring(i+1);rO.indexOf(s)!==-1&&(n.nodeName=n.nodeName.substring(0,i),n.objectName=s)}if(n.propertyName===null||n.propertyName.length===0)throw new Error("PropertyBinding: can not parse propertyName from trackName: "+e);return n}static findNode(e,t){if(t===void 0||t===""||t==="."||t===-1||t===e.name||t===e.uuid)return e;if(e.skeleton){const n=e.skeleton.getBoneByName(t);if(n!==void 0)return n}if(e.children){const n=function(s){for(let a=0;a<s.length;a++){const o=s[a];if(o.name===t||o.uuid===t)return o;const l=n(o.children);if(l)return l}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,s=n.length;i!==s;++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,s=n.length;i!==s;++i)n[i]=e[t++]}_setValue_array_setNeedsUpdate(e,t){const n=this.resolvedProperty;for(let i=0,s=n.length;i!==s;++i)n[i]=e[t++];this.targetObject.needsUpdate=!0}_setValue_array_setMatrixWorldNeedsUpdate(e,t){const n=this.resolvedProperty;for(let i=0,s=n.length;i!==s;++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 s=t.propertyIndex;if(e||(e=ks.findNode(this.rootNode,t.nodeName),this.node=e),this.getValue=this._getValue_unavailable,this.setValue=this._setValue_unavailable,!e){ze("PropertyBinding: No target node found for track: "+this.path+".");return}if(n){let u=t.objectIndex;switch(n){case"materials":if(!e.material){rt("PropertyBinding: Can not bind to material as node does not have a material.",this);return}if(!e.material.materials){rt("PropertyBinding: Can not bind to material.materials as node.material does not have a materials array.",this);return}e=e.material.materials;break;case"bones":if(!e.skeleton){rt("PropertyBinding: Can not bind to bones as node does not have a skeleton.",this);return}e=e.skeleton.bones;for(let c=0;c<e.length;c++)if(e[c].name===u){u=c;break}break;case"map":if("map"in e){e=e.map;break}if(!e.material){rt("PropertyBinding: Can not bind to material as node does not have a material.",this);return}if(!e.material.map){rt("PropertyBinding: Can not bind to material.map as node.material does not have a map.",this);return}e=e.material.map;break;default:if(e[n]===void 0){rt("PropertyBinding: Can not bind to objectName of node undefined.",this);return}e=e[n]}if(u!==void 0){if(e[u]===void 0){rt("PropertyBinding: Trying to bind to objectIndex of objectName, but is undefined.",this,e);return}e=e[u]}}const a=e[i];if(a===void 0){const u=t.nodeName;rt("PropertyBinding: Trying to update property for track: "+u+"."+i+" but it wasn't found.",e);return}let o=this.Versioning.None;this.targetObject=e,e.isMaterial===!0?o=this.Versioning.NeedsUpdate:e.isObject3D===!0&&(o=this.Versioning.MatrixWorldNeedsUpdate);let l=this.BindingType.Direct;if(s!==void 0){if(i==="morphTargetInfluences"){if(!e.geometry){rt("PropertyBinding: Can not bind to morphTargetInfluences because node does not have a geometry.",this);return}if(!e.geometry.morphAttributes){rt("PropertyBinding: Can not bind to morphTargetInfluences because node does not have a geometry.morphAttributes.",this);return}e.morphTargetDictionary[s]!==void 0&&(s=e.morphTargetDictionary[s])}l=this.BindingType.ArrayElement,this.resolvedProperty=a,this.propertyIndex=s}else a.fromArray!==void 0&&a.toArray!==void 0?(l=this.BindingType.HasFromToArray,this.resolvedProperty=a):Array.isArray(a)?(l=this.BindingType.EntireArray,this.resolvedProperty=a):this.propertyName=i;this.getValue=this.GetterByBindingType[l],this.setValue=this.SetterByBindingTypeAndVersioning[l][o]}unbind(){this.node=null,this.getValue=this._getValue_unbound,this.setValue=this._setValue_unbound}}ks.Composite=iO,ks.prototype.BindingType={Direct:0,EntireArray:1,ArrayElement:2,HasFromToArray:3},ks.prototype.Versioning={None:0,NeedsUpdate:1,MatrixWorldNeedsUpdate:2},ks.prototype.GetterByBindingType=[ks.prototype._getValue_direct,ks.prototype._getValue_array,ks.prototype._getValue_arrayElement,ks.prototype._getValue_toArray],ks.prototype.SetterByBindingTypeAndVersioning=[[ks.prototype._setValue_direct,ks.prototype._setValue_direct_setNeedsUpdate,ks.prototype._setValue_direct_setMatrixWorldNeedsUpdate],[ks.prototype._setValue_array,ks.prototype._setValue_array_setNeedsUpdate,ks.prototype._setValue_array_setMatrixWorldNeedsUpdate],[ks.prototype._setValue_arrayElement,ks.prototype._setValue_arrayElement_setNeedsUpdate,ks.prototype._setValue_arrayElement_setMatrixWorldNeedsUpdate],[ks.prototype._setValue_fromArray,ks.prototype._setValue_fromArray_setNeedsUpdate,ks.prototype._setValue_fromArray_setMatrixWorldNeedsUpdate]];class Ace{constructor(){this.isAnimationObjectGroup=!0,this.uuid=Ga(),this._objects=Array.prototype.slice.call(arguments),this.nCachedObjects_=0;const e={};this._indicesByUUID=e;for(let n=0,i=arguments.length;n!==i;++n)e[arguments[n].uuid]=n;this._paths=[],this._parsedPaths=[],this._bindings=[],this._bindingsIndicesByPath={};const t=this;this.stats={objects:{get total(){return t._objects.length},get inUse(){return this.total-t.nCachedObjects_}},get bindingsPerObject(){return t._bindings.length}}}add(){const e=this._objects,t=this._indicesByUUID,n=this._paths,i=this._parsedPaths,s=this._bindings,a=s.length;let o,l=e.length,u=this.nCachedObjects_;for(let c=0,d=arguments.length;c!==d;++c){const f=arguments[c],h=f.uuid;let p=t[h];if(p===void 0){p=l++,t[h]=p,e.push(f);for(let x=0,v=a;x!==v;++x)s[x].push(new ks(f,n[x],i[x]))}else if(p<u){o=e[p];const x=--u,v=e[x];t[v.uuid]=p,e[p]=v,t[h]=x,e[x]=f;for(let m=0,C=a;m!==C;++m){const w=s[m],P=w[x];let B=w[p];w[p]=P,B===void 0&&(B=new ks(f,n[m],i[m])),w[x]=B}}else e[p]!==o&&rt("AnimationObjectGroup: Different objects with the same UUID detected. Clean the caches or recreate your infrastructure when reloading scenes.")}this.nCachedObjects_=u}remove(){const e=this._objects,t=this._indicesByUUID,n=this._bindings,i=n.length;let s=this.nCachedObjects_;for(let a=0,o=arguments.length;a!==o;++a){const l=arguments[a],u=l.uuid,c=t[u];if(c!==void 0&&c>=s){const d=s++,f=e[d];t[f.uuid]=c,e[c]=f,t[u]=d,e[d]=l;for(let h=0,p=i;h!==p;++h){const x=n[h],v=x[d],m=x[c];x[c]=v,x[d]=m}}}this.nCachedObjects_=s}uncache(){const e=this._objects,t=this._indicesByUUID,n=this._bindings,i=n.length;let s=this.nCachedObjects_,a=e.length;for(let o=0,l=arguments.length;o!==l;++o){const u=arguments[o],c=u.uuid,d=t[c];if(d!==void 0)if(delete t[c],d<s){const f=--s,h=e[f],p=--a,x=e[p];t[h.uuid]=d,e[d]=h,t[x.uuid]=f,e[f]=x,e.pop();for(let v=0,m=i;v!==m;++v){const C=n[v],w=C[f],P=C[p];C[d]=w,C[f]=P,C.pop()}}else{const f=--a,h=e[f];f>0&&(t[h.uuid]=d),e[d]=h,e.pop();for(let p=0,x=i;p!==x;++p){const v=n[p];v[d]=v[f],v.pop()}}}this.nCachedObjects_=s}subscribe_(e,t){const n=this._bindingsIndicesByPath;let i=n[e];const s=this._bindings;if(i!==void 0)return s[i];const a=this._paths,o=this._parsedPaths,l=this._objects,u=l.length,c=this.nCachedObjects_,d=new Array(u);i=s.length,n[e]=i,a.push(e),o.push(t),s.push(d);for(let f=c,h=l.length;f!==h;++f){const p=l[f];d[f]=new ks(p,e,t)}return d}unsubscribe_(e){const t=this._bindingsIndicesByPath,n=t[e];if(n!==void 0){const i=this._paths,s=this._parsedPaths,a=this._bindings,o=a.length-1,l=a[o],u=e[o];t[u]=n,a[n]=l,a.pop(),s[n]=s[o],s.pop(),i[n]=i[o],i.pop()}}}class sO{constructor(e,t,n=null,i=t.blendMode){this._mixer=e,this._clip=t,this._localRoot=n,this.blendMode=i;const s=t.tracks,a=s.length,o=new Array(a),l={endingStart:sf,endingEnd:sf};for(let u=0;u!==a;++u){const c=s[u].createInterpolant(null);o[u]=c,c.settings=l}this._interpolantSettings=l,this._interpolants=o,this._propertyBindings=new Array(a),this._cacheIndex=null,this._byClipCacheIndex=null,this._timeScaleInterpolant=null,this._weightInterpolant=null,this.loop=sC,this._loopCount=-1,this._startTime=null,this.time=0,this.timeScale=1,this._effectiveTimeScale=1,this.weight=1,this._effectiveWeight=1,this.repetitions=1/0,this.paused=!1,this.enabled=!0,this.clampWhenFinished=!1,this.zeroSlopeAtStart=!0,this.zeroSlopeAtEnd=!0}play(){return this._mixer._activateAction(this),this}stop(){return this._mixer._deactivateAction(this),this.reset()}reset(){return this.paused=!1,this.enabled=!0,this.time=0,this._loopCount=-1,this._startTime=null,this.stopFading().stopWarping()}isRunning(){return this.enabled&&!this.paused&&this.timeScale!==0&&this._startTime===null&&this._mixer._isActiveAction(this)}isScheduled(){return this._mixer._isActiveAction(this)}startAt(e){return this._startTime=e,this}setLoop(e,t){return this.loop=e,this.repetitions=t,this}setEffectiveWeight(e){return this.weight=e,this._effectiveWeight=this.enabled?e:0,this.stopFading()}getEffectiveWeight(){return this._effectiveWeight}fadeIn(e){return this._scheduleFading(e,0,1)}fadeOut(e){return this._scheduleFading(e,1,0)}crossFadeFrom(e,t,n=!1){if(e.fadeOut(t),this.fadeIn(t),n===!0){const i=this._clip.duration,s=e._clip.duration,a=s/i,o=i/s;e.warp(1,a,t),this.warp(o,1,t)}return this}crossFadeTo(e,t,n=!1){return e.crossFadeFrom(this,t,n)}stopFading(){const e=this._weightInterpolant;return e!==null&&(this._weightInterpolant=null,this._mixer._takeBackControlInterpolant(e)),this}setEffectiveTimeScale(e){return this.timeScale=e,this._effectiveTimeScale=this.paused?0:e,this.stopWarping()}getEffectiveTimeScale(){return this._effectiveTimeScale}setDuration(e){return this.timeScale=this._clip.duration/e,this.stopWarping()}syncWith(e){return this.time=e.time,this.timeScale=e.timeScale,this.stopWarping()}halt(e){return this.warp(this._effectiveTimeScale,0,e)}warp(e,t,n){const i=this._mixer,s=i.time,a=this.timeScale;let o=this._timeScaleInterpolant;o===null&&(o=i._lendControlInterpolant(),this._timeScaleInterpolant=o);const l=o.parameterPositions,u=o.sampleValues;return l[0]=s,l[1]=s+n,u[0]=e/a,u[1]=t/a,this}stopWarping(){const e=this._timeScaleInterpolant;return e!==null&&(this._timeScaleInterpolant=null,this._mixer._takeBackControlInterpolant(e)),this}getMixer(){return this._mixer}getClip(){return this._clip}getRoot(){return this._localRoot||this._mixer._root}_update(e,t,n,i){if(!this.enabled){this._updateWeight(e);return}const s=this._startTime;if(s!==null){const l=(e-s)*n;l<0||n===0?t=0:(this._startTime=null,t=n*l)}t*=this._updateTimeScale(e);const a=this._updateTime(t),o=this._updateWeight(e);if(o>0){const l=this._interpolants,u=this._propertyBindings;switch(this.blendMode){case vy:for(let c=0,d=l.length;c!==d;++c)l[c].evaluate(a),u[c].accumulateAdditive(o);break;case x0:default:for(let c=0,d=l.length;c!==d;++c)l[c].evaluate(a),u[c].accumulate(i,o)}}}_updateWeight(e){let t=0;if(this.enabled){t=this.weight;const n=this._weightInterpolant;if(n!==null){const i=n.evaluate(e)[0];t*=i,e>n.parameterPositions[1]&&(this.stopFading(),i===0&&(this.enabled=!1))}}return this._effectiveWeight=t,t}_updateTimeScale(e){let t=0;if(!this.paused){t=this.timeScale;const n=this._timeScaleInterpolant;if(n!==null){const i=n.evaluate(e)[0];t*=i,e>n.parameterPositions[1]&&(this.stopWarping(),t===0?this.paused=!0:this.timeScale=t)}}return this._effectiveTimeScale=t,t}_updateTime(e){const t=this._clip.duration,n=this.loop;let i=this.time+e,s=this._loopCount;const a=n===aC;if(e===0)return s===-1?i:a&&(s&1)===1?t-i:i;if(n===iC){s===-1&&(this._loopCount=0,this._setEndings(!0,!0,!1));e:{if(i>=t)i=t;else if(i<0)i=0;else{this.time=i;break e}this.clampWhenFinished?this.paused=!0:this.enabled=!1,this.time=i,this._mixer.dispatchEvent({type:"finished",action:this,direction:e<0?-1:1})}}else{if(s===-1&&(e>=0?(s=0,this._setEndings(!0,this.repetitions===0,a)):this._setEndings(this.repetitions===0,!0,a)),i>=t||i<0){const o=Math.floor(i/t);i-=t*o,s+=Math.abs(o);const l=this.repetitions-s;if(l<=0)this.clampWhenFinished?this.paused=!0:this.enabled=!1,i=e>0?t:0,this.time=i,this._mixer.dispatchEvent({type:"finished",action:this,direction:e>0?1:-1});else{if(l===1){const u=e<0;this._setEndings(u,!u,a)}else this._setEndings(!1,!1,a);this._loopCount=s,this.time=i,this._mixer.dispatchEvent({type:"loop",action:this,loopDelta:o})}}else this.time=i;if(a&&(s&1)===1)return t-i}return i}_setEndings(e,t,n){const i=this._interpolantSettings;n?(i.endingStart=xp,i.endingEnd=xp):(e?i.endingStart=this.zeroSlopeAtStart?xp:sf:i.endingStart=yv,t?i.endingEnd=this.zeroSlopeAtEnd?xp:sf:i.endingEnd=yv)}_scheduleFading(e,t,n){const i=this._mixer,s=i.time;let a=this._weightInterpolant;a===null&&(a=i._lendControlInterpolant(),this._weightInterpolant=a);const o=a.parameterPositions,l=a.sampleValues;return o[0]=s,l[0]=t,o[1]=s+e,l[1]=n,this}}const aO=new Float32Array(1);class xce extends null{constructor(e){super(),this._root=e,this._initMemoryManager(),this._accuIndex=0,this.time=0,this.timeScale=1}_bindAction(e,t){const n=e._localRoot||this._root,i=e._clip.tracks,s=i.length,a=e._propertyBindings,o=e._interpolants,l=n.uuid,u=this._bindingsByRootAndName;let c=u[l];c===void 0&&(c={},u[l]=c);for(let d=0;d!==s;++d){const f=i[d],h=f.name;let p=c[h];if(p!==void 0)++p.referenceCount,a[d]=p;else{if(p=a[d],p!==void 0){p._cacheIndex===null&&(++p.referenceCount,this._addInactiveBinding(p,l,h));continue}const x=t&&t._propertyBindings[d].binding.parsedPath;p=new JL(ks.create(n,h,x),f.ValueTypeName,f.getValueSize()),++p.referenceCount,this._addInactiveBinding(p,l,h),a[d]=p}o[d].resultBuffer=p.buffer}}_activateAction(e){if(!this._isActiveAction(e)){if(e._cacheIndex===null){const n=(e._localRoot||this._root).uuid,i=e._clip.uuid,s=this._actionsByClip[i];this._bindAction(e,s&&s.knownActions[0]),this._addInactiveAction(e,i,n)}const t=e._propertyBindings;for(let n=0,i=t.length;n!==i;++n){const s=t[n];s.useCount++===0&&(this._lendBinding(s),s.saveOriginalState())}this._lendAction(e)}}_deactivateAction(e){if(this._isActiveAction(e)){const t=e._propertyBindings;for(let n=0,i=t.length;n!==i;++n){const s=t[n];--s.useCount===0&&(s.restoreOriginalState(),this._takeBackBinding(s))}this._takeBackAction(e)}}_initMemoryManager(){this._actions=[],this._nActiveActions=0,this._actionsByClip={},this._bindings=[],this._nActiveBindings=0,this._bindingsByRootAndName={},this._controlInterpolants=[],this._nActiveControlInterpolants=0;const e=this;this.stats={actions:{get total(){return e._actions.length},get inUse(){return e._nActiveActions}},bindings:{get total(){return e._bindings.length},get inUse(){return e._nActiveBindings}},controlInterpolants:{get total(){return e._controlInterpolants.length},get inUse(){return e._nActiveControlInterpolants}}}}_isActiveAction(e){const t=e._cacheIndex;return t!==null&&t<this._nActiveActions}_addInactiveAction(e,t,n){const i=this._actions,s=this._actionsByClip;let a=s[t];if(a===void 0)a={knownActions:[e],actionByRoot:{}},e._byClipCacheIndex=0,s[t]=a;else{const o=a.knownActions;e._byClipCacheIndex=o.length,o.push(e)}e._cacheIndex=i.length,i.push(e),a.actionByRoot[n]=e}_removeInactiveAction(e){const t=this._actions,n=t[t.length-1],i=e._cacheIndex;n._cacheIndex=i,t[i]=n,t.pop(),e._cacheIndex=null;const s=e._clip.uuid,a=this._actionsByClip,o=a[s],l=o.knownActions,u=l[l.length-1],c=e._byClipCacheIndex;u._byClipCacheIndex=c,l[c]=u,l.pop(),e._byClipCacheIndex=null;const d=o.actionByRoot,f=(e._localRoot||this._root).uuid;delete d[f],l.length===0&&delete a[s],this._removeInactiveBindingsForAction(e)}_removeInactiveBindingsForAction(e){const t=e._propertyBindings;for(let n=0,i=t.length;n!==i;++n){const s=t[n];--s.referenceCount===0&&this._removeInactiveBinding(s)}}_lendAction(e){const t=this._actions,n=e._cacheIndex,i=this._nActiveActions++,s=t[i];e._cacheIndex=i,t[i]=e,s._cacheIndex=n,t[n]=s}_takeBackAction(e){const t=this._actions,n=e._cacheIndex,i=--this._nActiveActions,s=t[i];e._cacheIndex=i,t[i]=e,s._cacheIndex=n,t[n]=s}_addInactiveBinding(e,t,n){const i=this._bindingsByRootAndName,s=this._bindings;let a=i[t];a===void 0&&(a={},i[t]=a),a[n]=e,e._cacheIndex=s.length,s.push(e)}_removeInactiveBinding(e){const t=this._bindings,n=e.binding,i=n.rootNode.uuid,s=n.path,a=this._bindingsByRootAndName,o=a[i],l=t[t.length-1],u=e._cacheIndex;l._cacheIndex=u,t[u]=l,t.pop(),delete o[s],Object.keys(o).length===0&&delete a[i]}_lendBinding(e){const t=this._bindings,n=e._cacheIndex,i=this._nActiveBindings++,s=t[i];e._cacheIndex=i,t[i]=e,s._cacheIndex=n,t[n]=s}_takeBackBinding(e){const t=this._bindings,n=e._cacheIndex,i=--this._nActiveBindings,s=t[i];e._cacheIndex=i,t[i]=e,s._cacheIndex=n,t[n]=s}_lendControlInterpolant(){const e=this._controlInterpolants,t=this._nActiveControlInterpolants++;let n=e[t];return n===void 0&&(n=new z5(new Float32Array(2),new Float32Array(2),1,aO),n.__cacheIndex=t,e[t]=n),n}_takeBackControlInterpolant(e){const t=this._controlInterpolants,n=e.__cacheIndex,i=--this._nActiveControlInterpolants,s=t[i];e.__cacheIndex=i,t[i]=e,s.__cacheIndex=n,t[n]=s}clipAction(e,t,n){const i=t||this._root,s=i.uuid;let a=typeof e=="string"?yb.findByName(i,e):e;const o=a!==null?a.uuid:e,l=this._actionsByClip[o];let u=null;if(n===void 0&&(a!==null?n=a.blendMode:n=x0),l!==void 0){const d=l.actionByRoot[s];if(d!==void 0&&d.blendMode===n)return d;u=l.knownActions[0],a===null&&(a=u._clip)}if(a===null)return null;const c=new sO(this,a,t,n);return this._bindAction(c,u),this._addInactiveAction(c,o,s),c}existingAction(e,t){const n=t||this._root,i=n.uuid,s=typeof e=="string"?yb.findByName(n,e):e,a=s?s.uuid:e,o=this._actionsByClip[a];return o!==void 0&&o.actionByRoot[i]||null}stopAllAction(){const e=this._actions,t=this._nActiveActions;for(let n=t-1;n>=0;--n)e[n].stop();return this}update(e){e*=this.timeScale;const t=this._actions,n=this._nActiveActions,i=this.time+=e,s=Math.sign(e),a=this._accuIndex^=1;for(let u=0;u!==n;++u)t[u]._update(i,e,s,a);const o=this._bindings,l=this._nActiveBindings;for(let u=0;u!==l;++u)o[u].apply(a);return this}setTime(e){this.time=0;for(let t=0;t<this._actions.length;t++)this._actions[t].time=0;return this.update(e)}getRoot(){return this._root}uncacheClip(e){const t=this._actions,n=e.uuid,i=this._actionsByClip,s=i[n];if(s!==void 0){const a=s.knownActions;for(let o=0,l=a.length;o!==l;++o){const u=a[o];this._deactivateAction(u);const c=u._cacheIndex,d=t[t.length-1];u._cacheIndex=null,u._byClipCacheIndex=null,d._cacheIndex=c,t[c]=d,t.pop(),this._removeInactiveBindingsForAction(u)}delete i[n]}}uncacheRoot(e){const t=e.uuid,n=this._actionsByClip;for(const a in n){const o=n[a].actionByRoot,l=o[t];l!==void 0&&(this._deactivateAction(l),this._removeInactiveAction(l))}const i=this._bindingsByRootAndName,s=i[t];if(s!==void 0)for(const a in s){const o=s[a];o.restoreOriginalState(),this._removeInactiveBinding(o)}}uncacheAction(e,t){const n=this.existingAction(e,t);n!==null&&(this._deactivateAction(n),this._removeInactiveAction(n))}}class yce extends null{constructor(e=1,t=1,n=1,i={}){super(e,t,i),this.isRenderTarget3D=!0,this.depth=n,this.texture=new MC(null,e,t,n),this._setTextureOptions(i),this.texture.isRenderTargetTexture=!0}}class tD{constructor(e){this.value=e}clone(){return new tD(this.value.clone===void 0?this.value:this.value.clone())}}let oO=0;class bce extends null{constructor(){super(),this.isUniformsGroup=!0,Object.defineProperty(this,"id",{value:oO++}),this.name="",this.usage=U,this.uniforms=[]}add(e){return this.uniforms.push(e),this}remove(e){const t=this.uniforms.indexOf(e);return t!==-1&&this.uniforms.splice(t,1),this}setName(e){return this.name=e,this}setUsage(e){return this.usage=e,this}dispose(){this.dispatchEvent({type:"dispose"})}copy(e){this.name=e.name,this.usage=e.usage;const t=e.uniforms;this.uniforms.length=0;for(let n=0,i=t.length;n<i;n++){const s=Array.isArray(t[n])?t[n]:[t[n]];for(let a=0;a<s.length;a++)this.uniforms.push(s[a].clone())}return this}clone(){return new this.constructor().copy(this)}}class lO extends Gy{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}}class Ece{constructor(e,t,n,i,s,a=!1){this.isGLBufferAttribute=!0,this.name="",this.buffer=e,this.type=t,this.itemSize=n,this.elementSize=i,this.count=s,this.normalized=a,this.version=0}set needsUpdate(e){e===!0&&this.version++}setBuffer(e){return this.buffer=e,this}setType(e,t){return this.type=e,this.elementSize=t,this}setItemSize(e){return this.itemSize=e,this}setCount(e){return this.count=e,this}}const nD=new Cr;class rD{constructor(e,t,n=0,i=1/0){this.ray=new Tv(e,t),this.near=n,this.far=i,this.camera=null,this.layers=new FC,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):rt("Raycaster: Unsupported camera type: "+t.type)}setFromXRController(e){return nD.identity().extractRotation(e.matrixWorld),this.ray.origin.setFromMatrixPosition(e.matrixWorld),this.ray.direction.set(0,0,-1).applyMatrix4(nD),this}intersectObject(e,t=!0,n=[]){return Q1(e,this,n,t),n.sort(iD),n}intersectObjects(e,t=!0,n=[]){for(let i=0,s=e.length;i<s;i++)Q1(e[i],this,n,t);return n.sort(iD),n}}function iD(r,e){return r.distance-e.distance}function Q1(r,e,t,n){let i=!0;if(r.layers.test(e.layers)&&r.raycast(e,t)===!1&&(i=!1),i===!0&&n===!0){const s=r.children;for(let a=0,o=s.length;a<o;a++)Q1(s[a],e,t,!0)}}class wce{constructor(){this._previousTime=0,this._currentTime=0,this._startTime=performance.now(),this._delta=0,this._elapsed=0,this._timescale=1,this._document=null,this._pageVisibilityHandler=null}connect(e){this._document=e,e.hidden!==void 0&&(this._pageVisibilityHandler=uO.bind(this),e.addEventListener("visibilitychange",this._pageVisibilityHandler,!1))}disconnect(){this._pageVisibilityHandler!==null&&(this._document.removeEventListener("visibilitychange",this._pageVisibilityHandler),this._pageVisibilityHandler=null),this._document=null}getDelta(){return this._delta/1e3}getElapsed(){return this._elapsed/1e3}getTimescale(){return this._timescale}setTimescale(e){return this._timescale=e,this}reset(){return this._currentTime=performance.now()-this._startTime,this}dispose(){this.disconnect()}update(e){return this._pageVisibilityHandler!==null&&this._document.hidden===!0?this._delta=0:(this._previousTime=this._currentTime,this._currentTime=(e!==void 0?e:performance.now())-this._startTime,this._delta=(this._currentTime-this._previousTime)*this._timescale,this._elapsed+=this._delta),this}}function uO(){this._document.hidden===!1&&this.reset()}class sD{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(){return this.phi=ii(this.phi,1e-6,Math.PI-1e-6),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),this.radius===0?(this.theta=0,this.phi=0):(this.theta=Math.atan2(e,n),this.phi=Math.acos(ii(t/this.radius,-1,1))),this}clone(){return new this.constructor().copy(this)}}class Cce{constructor(e=1,t=0,n=0){this.radius=e,this.theta=t,this.y=n}set(e,t,n){return this.radius=e,this.theta=t,this.y=n,this}copy(e){return this.radius=e.radius,this.theta=e.theta,this.y=e.y,this}setFromVector3(e){return this.setFromCartesianCoords(e.x,e.y,e.z)}setFromCartesianCoords(e,t,n){return this.radius=Math.sqrt(e*e+n*n),this.theta=Math.atan2(e,n),this.y=t,this}clone(){return new this.constructor().copy(this)}}class Cb{constructor(e,t,n,i){Cb.prototype.isMatrix2=!0,this.elements=[1,0,0,1],e!==void 0&&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 s=this.elements;return s[0]=e,s[2]=t,s[1]=n,s[3]=i,this}}const aD=new ct;class Pce{constructor(e=new ct(1/0,1/0),t=new ct(-1/0,-1/0)){this.isBox2=!0,this.min=e,this.max=t}set(e,t){return this.min.copy(e),this.max.copy(t),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=aD.copy(t).multiplyScalar(.5);return this.min.copy(e).sub(n),this.max.copy(e).add(n),this}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=1/0,this.max.x=this.max.y=-1/0,this}isEmpty(){return this.max.x<this.min.x||this.max.y<this.min.y}getCenter(e){return this.isEmpty()?e.set(0,0):e.addVectors(this.min,this.max).multiplyScalar(.5)}getSize(e){return this.isEmpty()?e.set(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}containsPoint(e){return e.x>=this.min.x&&e.x<=this.max.x&&e.y>=this.min.y&&e.y<=this.max.y}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}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))}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}clampPoint(e,t){return t.copy(e).clamp(this.min,this.max)}distanceToPoint(e){return this.clampPoint(e,aD).distanceTo(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}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)}}const oD=new J,Pb=new J,$v=new J,eA=new J,Z1=new J,cO=new J,dO=new J;class Bce{constructor(e=new J,t=new J){this.start=e,this.end=t}set(e,t){return this.start.copy(e),this.end.copy(t),this}copy(e){return this.start.copy(e.start),this.end.copy(e.end),this}getCenter(e){return e.addVectors(this.start,this.end).multiplyScalar(.5)}delta(e){return e.subVectors(this.end,this.start)}distanceSq(){return this.start.distanceToSquared(this.end)}distance(){return this.start.distanceTo(this.end)}at(e,t){return this.delta(t).multiplyScalar(e).add(this.start)}closestPointToPointParameter(e,t){oD.subVectors(e,this.start),Pb.subVectors(this.end,this.start);const n=Pb.dot(Pb);let s=Pb.dot(oD)/n;return t&&(s=ii(s,0,1)),s}closestPointToPoint(e,t,n){const i=this.closestPointToPointParameter(e,t);return this.delta(n).multiplyScalar(i).add(this.start)}distanceSqToLine3(e,t=cO,n=dO){const i=10000000000000001e-32;let s,a;const o=this.start,l=e.start,u=this.end,c=e.end;$v.subVectors(u,o),eA.subVectors(c,l),Z1.subVectors(o,l);const d=$v.dot($v),f=eA.dot(eA),h=eA.dot(Z1);if(d<=i&&f<=i)return t.copy(o),n.copy(l),t.sub(n),t.dot(t);if(d<=i)s=0,a=h/f,a=ii(a,0,1);else{const p=$v.dot(Z1);if(f<=i)a=0,s=ii(-p/d,0,1);else{const x=$v.dot(eA),v=d*f-x*x;v!==0?s=ii((x*h-p*f)/v,0,1):s=0,a=(x*s+h)/f,a<0?(a=0,s=ii(-p/d,0,1)):a>1&&(a=1,s=ii((x-p)/d,0,1))}}return t.copy(o).add($v.multiplyScalar(s)),n.copy(l).add(eA.multiplyScalar(a)),t.sub(n),t.dot(t)}applyMatrix4(e){return this.start.applyMatrix4(e),this.end.applyMatrix4(e),this}equals(e){return e.start.equals(this.start)&&e.end.equals(this.end)}clone(){return new this.constructor().copy(this)}}const lD=new J;class Mce extends null{constructor(e,t){super(),this.light=e,this.matrixAutoUpdate=!1,this.color=t,this.type="SpotLightHelper";const n=new Ni,i=[0,0,0,0,0,1,0,0,0,1,0,1,0,0,0,-1,0,1,0,0,0,0,1,1,0,0,0,0,-1,1];for(let a=0,o=1,l=32;a<l;a++,o++){const u=a/l*Math.PI*2,c=o/l*Math.PI*2;i.push(Math.cos(u),Math.sin(u),1,Math.cos(c),Math.sin(c),1)}n.setAttribute("position",new yr(i,3));const s=new kl({fog:!1,toneMapped:!1});this.cone=new l5(n,s),this.add(this.cone),this.update()}dispose(){this.cone.geometry.dispose(),this.cone.material.dispose()}update(){this.light.updateWorldMatrix(!0,!1),this.light.target.updateWorldMatrix(!0,!1),this.parent?(this.parent.updateWorldMatrix(!0),this.matrix.copy(this.parent.matrixWorld).invert().multiply(this.light.matrixWorld)):this.matrix.copy(this.light.matrixWorld),this.matrixWorld.copy(this.light.matrixWorld);const e=this.light.distance?this.light.distance:1e3,t=e*Math.tan(this.light.angle);this.cone.scale.set(t,t,e),lD.setFromMatrixPosition(this.light.target.matrixWorld),this.cone.lookAt(lD),this.color!==void 0?this.cone.material.color.set(this.color):this.cone.material.color.copy(this.light.color)}}const Np=new J,Bb=new Cr,Y1=new Cr;class Sce extends null{constructor(e){const t=uD(e),n=new Ni,i=[],s=[];for(let u=0;u<t.length;u++){const c=t[u];c.parent&&c.parent.isBone&&(i.push(0,0,0),i.push(0,0,0),s.push(0,0,0),s.push(0,0,0))}n.setAttribute("position",new yr(i,3)),n.setAttribute("color",new yr(s,3));const a=new kl({vertexColors:!0,depthTest:!1,depthWrite:!1,toneMapped:!1,transparent:!0});super(n,a),this.isSkeletonHelper=!0,this.type="SkeletonHelper",this.root=e,this.bones=t,this.matrix=e.matrixWorld,this.matrixAutoUpdate=!1;const o=new Vn(255),l=new Vn(65280);this.setColors(o,l)}updateMatrixWorld(e){const t=this.bones,n=this.geometry,i=n.getAttribute("position");Y1.copy(this.root.matrixWorld).invert();for(let s=0,a=0;s<t.length;s++){const o=t[s];o.parent&&o.parent.isBone&&(Bb.multiplyMatrices(Y1,o.matrixWorld),Np.setFromMatrixPosition(Bb),i.setXYZ(a,Np.x,Np.y,Np.z),Bb.multiplyMatrices(Y1,o.parent.matrixWorld),Np.setFromMatrixPosition(Bb),i.setXYZ(a+1,Np.x,Np.y,Np.z),a+=2)}n.getAttribute("position").needsUpdate=!0,super.updateMatrixWorld(e)}setColors(e,t){const i=this.geometry.getAttribute("color");for(let s=0;s<i.count;s+=2)i.setXYZ(s,e.r,e.g,e.b),i.setXYZ(s+1,t.r,t.g,t.b);return i.needsUpdate=!0,this}dispose(){this.geometry.dispose(),this.material.dispose()}}function uD(r){const e=[];r.isBone===!0&&e.push(r);for(let t=0;t<r.children.length;t++)e.push(...uD(r.children[t]));return e}class Dce extends null{constructor(e,t,n){const i=new Ad(t,4,2),s=new rl({wireframe:!0,fog:!1,toneMapped:!1});super(i,s),this.light=e,this.color=n,this.type="PointLightHelper",this.matrix=this.light.matrixWorld,this.matrixAutoUpdate=!1,this.update()}dispose(){this.geometry.dispose(),this.material.dispose()}update(){this.light.updateWorldMatrix(!0,!1),this.color!==void 0?this.material.color.set(this.color):this.material.color.copy(this.light.color)}}const fO=new J,cD=new Vn,dD=new Vn;class Tce extends null{constructor(e,t,n){super(),this.light=e,this.matrix=e.matrixWorld,this.matrixAutoUpdate=!1,this.color=n,this.type="HemisphereLightHelper";const i=new pb(t);i.rotateY(Math.PI*.5),this.material=new rl({wireframe:!0,fog:!1,toneMapped:!1}),this.color===void 0&&(this.material.vertexColors=!0);const s=i.getAttribute("position"),a=new Float32Array(s.count*3);i.setAttribute("color",new ga(a,3)),this.add(new Gs(i,this.material)),this.update()}dispose(){this.children[0].geometry.dispose(),this.children[0].material.dispose()}update(){const e=this.children[0];if(this.color!==void 0)this.material.color.set(this.color);else{const t=e.geometry.getAttribute("color");cD.copy(this.light.color),dD.copy(this.light.groundColor);for(let n=0,i=t.count;n<i;n++){const s=n<i/2?cD:dD;t.setXYZ(n,s.r,s.g,s.b)}t.needsUpdate=!0}this.light.updateWorldMatrix(!0,!1),e.lookAt(fO.setFromMatrixPosition(this.light.matrixWorld).negate())}}class Ice extends null{constructor(e=10,t=10,n=4473924,i=8947848){n=new Vn(n),i=new Vn(i);const s=t/2,a=e/t,o=e/2,l=[],u=[];for(let f=0,h=0,p=-o;f<=t;f++,p+=a){l.push(-o,0,p,o,0,p),l.push(p,0,-o,p,0,o);const x=f===s?n:i;x.toArray(u,h),h+=3,x.toArray(u,h),h+=3,x.toArray(u,h),h+=3,x.toArray(u,h),h+=3}const c=new Ni;c.setAttribute("position",new yr(l,3)),c.setAttribute("color",new yr(u,3));const d=new kl({vertexColors:!0,toneMapped:!1});super(c,d),this.type="GridHelper"}dispose(){this.geometry.dispose(),this.material.dispose()}}class Nce extends null{constructor(e=10,t=16,n=8,i=64,s=4473924,a=8947848){s=new Vn(s),a=new Vn(a);const o=[],l=[];if(t>1)for(let d=0;d<t;d++){const f=d/t*(Math.PI*2),h=Math.sin(f)*e,p=Math.cos(f)*e;o.push(0,0,0),o.push(h,0,p);const x=d&1?s:a;l.push(x.r,x.g,x.b),l.push(x.r,x.g,x.b)}for(let d=0;d<n;d++){const f=d&1?s:a,h=e-e/n*d;for(let p=0;p<i;p++){let x=p/i*(Math.PI*2),v=Math.sin(x)*h,m=Math.cos(x)*h;o.push(v,0,m),l.push(f.r,f.g,f.b),x=(p+1)/i*(Math.PI*2),v=Math.sin(x)*h,m=Math.cos(x)*h,o.push(v,0,m),l.push(f.r,f.g,f.b)}}const u=new Ni;u.setAttribute("position",new yr(o,3)),u.setAttribute("color",new yr(l,3));const c=new kl({vertexColors:!0,toneMapped:!1});super(u,c),this.type="PolarGridHelper"}dispose(){this.geometry.dispose(),this.material.dispose()}}const fD=new J,Mb=new J,hD=new J;class Fce extends null{constructor(e,t,n){super(),this.light=e,this.matrix=e.matrixWorld,this.matrixAutoUpdate=!1,this.color=n,this.type="DirectionalLightHelper",t===void 0&&(t=1);let i=new Ni;i.setAttribute("position",new yr([-t,t,0,t,t,0,t,-t,0,-t,-t,0,-t,t,0],3));const s=new kl({fog:!1,toneMapped:!1});this.lightPlane=new j0(i,s),this.add(this.lightPlane),i=new Ni,i.setAttribute("position",new yr([0,0,0,0,0,1],3)),this.targetLine=new j0(i,s),this.add(this.targetLine),this.update()}dispose(){this.lightPlane.geometry.dispose(),this.lightPlane.material.dispose(),this.targetLine.geometry.dispose(),this.targetLine.material.dispose()}update(){this.light.updateWorldMatrix(!0,!1),this.light.target.updateWorldMatrix(!0,!1),fD.setFromMatrixPosition(this.light.matrixWorld),Mb.setFromMatrixPosition(this.light.target.matrixWorld),hD.subVectors(Mb,fD),this.lightPlane.lookAt(Mb),this.color!==void 0?(this.lightPlane.material.color.set(this.color),this.targetLine.material.color.set(this.color)):(this.lightPlane.material.color.copy(this.light.color),this.targetLine.material.color.copy(this.light.color)),this.targetLine.lookAt(Mb),this.targetLine.scale.z=hD.length()}}const Sb=new J,ho=new jy;class Rce extends null{constructor(e){const t=new Ni,n=new kl({color:16777215,vertexColors:!0,toneMapped:!1}),i=[],s=[],a={};o("n1","n2"),o("n2","n4"),o("n4","n3"),o("n3","n1"),o("f1","f2"),o("f2","f4"),o("f4","f3"),o("f3","f1"),o("n1","f1"),o("n2","f2"),o("n3","f3"),o("n4","f4"),o("p","n1"),o("p","n2"),o("p","n3"),o("p","n4"),o("u1","u2"),o("u2","u3"),o("u3","u1"),o("c","t"),o("p","c"),o("cn1","cn2"),o("cn3","cn4"),o("cf1","cf2"),o("cf3","cf4");function o(p,x){l(p),l(x)}function l(p){i.push(0,0,0),s.push(0,0,0),a[p]===void 0&&(a[p]=[]),a[p].push(i.length/3-1)}t.setAttribute("position",new yr(i,3)),t.setAttribute("color",new yr(s,3)),super(t,n),this.type="CameraHelper",this.camera=e,this.camera.updateProjectionMatrix&&this.camera.updateProjectionMatrix(),this.matrix=e.matrixWorld,this.matrixAutoUpdate=!1,this.pointMap=a,this.update();const u=new Vn(16755200),c=new Vn(16711680),d=new Vn(43775),f=new Vn(16777215),h=new Vn(3355443);this.setColors(u,c,d,f,h)}setColors(e,t,n,i,s){const o=this.geometry.getAttribute("color");return o.setXYZ(0,e.r,e.g,e.b),o.setXYZ(1,e.r,e.g,e.b),o.setXYZ(2,e.r,e.g,e.b),o.setXYZ(3,e.r,e.g,e.b),o.setXYZ(4,e.r,e.g,e.b),o.setXYZ(5,e.r,e.g,e.b),o.setXYZ(6,e.r,e.g,e.b),o.setXYZ(7,e.r,e.g,e.b),o.setXYZ(8,e.r,e.g,e.b),o.setXYZ(9,e.r,e.g,e.b),o.setXYZ(10,e.r,e.g,e.b),o.setXYZ(11,e.r,e.g,e.b),o.setXYZ(12,e.r,e.g,e.b),o.setXYZ(13,e.r,e.g,e.b),o.setXYZ(14,e.r,e.g,e.b),o.setXYZ(15,e.r,e.g,e.b),o.setXYZ(16,e.r,e.g,e.b),o.setXYZ(17,e.r,e.g,e.b),o.setXYZ(18,e.r,e.g,e.b),o.setXYZ(19,e.r,e.g,e.b),o.setXYZ(20,e.r,e.g,e.b),o.setXYZ(21,e.r,e.g,e.b),o.setXYZ(22,e.r,e.g,e.b),o.setXYZ(23,e.r,e.g,e.b),o.setXYZ(24,t.r,t.g,t.b),o.setXYZ(25,t.r,t.g,t.b),o.setXYZ(26,t.r,t.g,t.b),o.setXYZ(27,t.r,t.g,t.b),o.setXYZ(28,t.r,t.g,t.b),o.setXYZ(29,t.r,t.g,t.b),o.setXYZ(30,t.r,t.g,t.b),o.setXYZ(31,t.r,t.g,t.b),o.setXYZ(32,n.r,n.g,n.b),o.setXYZ(33,n.r,n.g,n.b),o.setXYZ(34,n.r,n.g,n.b),o.setXYZ(35,n.r,n.g,n.b),o.setXYZ(36,n.r,n.g,n.b),o.setXYZ(37,n.r,n.g,n.b),o.setXYZ(38,i.r,i.g,i.b),o.setXYZ(39,i.r,i.g,i.b),o.setXYZ(40,s.r,s.g,s.b),o.setXYZ(41,s.r,s.g,s.b),o.setXYZ(42,s.r,s.g,s.b),o.setXYZ(43,s.r,s.g,s.b),o.setXYZ(44,s.r,s.g,s.b),o.setXYZ(45,s.r,s.g,s.b),o.setXYZ(46,s.r,s.g,s.b),o.setXYZ(47,s.r,s.g,s.b),o.setXYZ(48,s.r,s.g,s.b),o.setXYZ(49,s.r,s.g,s.b),o.needsUpdate=!0,this}update(){const e=this.geometry,t=this.pointMap,n=1,i=1;let s,a;if(ho.projectionMatrixInverse.copy(this.camera.projectionMatrixInverse),this.camera.reversedDepth===!0)s=1,a=0;else if(this.camera.coordinateSystem===Gt)s=-1,a=1;else if(this.camera.coordinateSystem===gn)s=0,a=1;else throw new Error("THREE.CameraHelper.update(): Invalid coordinate system: "+this.camera.coordinateSystem);Eo("c",t,e,ho,0,0,s),Eo("t",t,e,ho,0,0,a),Eo("n1",t,e,ho,-n,-i,s),Eo("n2",t,e,ho,n,-i,s),Eo("n3",t,e,ho,-n,i,s),Eo("n4",t,e,ho,n,i,s),Eo("f1",t,e,ho,-n,-i,a),Eo("f2",t,e,ho,n,-i,a),Eo("f3",t,e,ho,-n,i,a),Eo("f4",t,e,ho,n,i,a),Eo("u1",t,e,ho,n*.7,i*1.1,s),Eo("u2",t,e,ho,-n*.7,i*1.1,s),Eo("u3",t,e,ho,0,i*2,s),Eo("cf1",t,e,ho,-n,0,a),Eo("cf2",t,e,ho,n,0,a),Eo("cf3",t,e,ho,0,-i,a),Eo("cf4",t,e,ho,0,i,a),Eo("cn1",t,e,ho,-n,0,s),Eo("cn2",t,e,ho,n,0,s),Eo("cn3",t,e,ho,0,-i,s),Eo("cn4",t,e,ho,0,i,s),e.getAttribute("position").needsUpdate=!0}dispose(){this.geometry.dispose(),this.material.dispose()}}function Eo(r,e,t,n,i,s,a){Sb.set(i,s,a).unproject(n);const o=e[r];if(o!==void 0){const l=t.getAttribute("position");for(let u=0,c=o.length;u<c;u++)l.setXYZ(o[u],Sb.x,Sb.y,Sb.z)}}const Db=new xl;class Lce extends null{constructor(e,t=16776960){const n=new Uint16Array([0,1,1,2,2,3,3,0,4,5,5,6,6,7,7,4,0,4,1,5,2,6,3,7]),i=new Float32Array(8*3),s=new Ni;s.setIndex(new ga(n,1)),s.setAttribute("position",new ga(i,3)),super(s,new kl({color:t,toneMapped:!1})),this.object=e,this.type="BoxHelper",this.matrixAutoUpdate=!1,this.update()}update(){if(this.object!==void 0&&Db.setFromObject(this.object),Db.isEmpty())return;const e=Db.min,t=Db.max,n=this.geometry.attributes.position,i=n.array;i[0]=t.x,i[1]=t.y,i[2]=t.z,i[3]=e.x,i[4]=t.y,i[5]=t.z,i[6]=e.x,i[7]=e.y,i[8]=t.z,i[9]=t.x,i[10]=e.y,i[11]=t.z,i[12]=t.x,i[13]=t.y,i[14]=e.z,i[15]=e.x,i[16]=t.y,i[17]=e.z,i[18]=e.x,i[19]=e.y,i[20]=e.z,i[21]=t.x,i[22]=e.y,i[23]=e.z,n.needsUpdate=!0,this.geometry.computeBoundingSphere()}setFromObject(e){return this.object=e,this.update(),this}copy(e,t){return super.copy(e,t),this.object=e.object,this}dispose(){this.geometry.dispose(),this.material.dispose()}}class Oce extends null{constructor(e,t=16776960){const n=new Uint16Array([0,1,1,2,2,3,3,0,4,5,5,6,6,7,7,4,0,4,1,5,2,6,3,7]),i=[1,1,1,-1,1,1,-1,-1,1,1,-1,1,1,1,-1,-1,1,-1,-1,-1,-1,1,-1,-1],s=new Ni;s.setIndex(new ga(n,1)),s.setAttribute("position",new yr(i,3)),super(s,new kl({color:t,toneMapped:!1})),this.box=e,this.type="Box3Helper",this.geometry.computeBoundingSphere()}updateMatrixWorld(e){const t=this.box;t.isEmpty()||(t.getCenter(this.position),t.getSize(this.scale),this.scale.multiplyScalar(.5),super.updateMatrixWorld(e))}dispose(){this.geometry.dispose(),this.material.dispose()}}class zce extends null{constructor(e,t=1,n=16776960){const i=n,s=[1,-1,0,-1,1,0,-1,-1,0,1,1,0,-1,1,0,-1,-1,0,1,-1,0,1,1,0],a=new Ni;a.setAttribute("position",new yr(s,3)),a.computeBoundingSphere(),super(a,new kl({color:i,toneMapped:!1})),this.type="PlaneHelper",this.plane=e,this.size=t;const o=[1,1,0,-1,1,0,-1,-1,0,1,1,0,-1,-1,0,1,-1,0],l=new Ni;l.setAttribute("position",new yr(o,3)),l.computeBoundingSphere(),this.add(new Gs(l,new rl({color:i,opacity:.2,transparent:!0,depthWrite:!1,toneMapped:!1})))}updateMatrixWorld(e){this.position.set(0,0,0),this.scale.set(.5*this.size,.5*this.size,1),this.lookAt(this.plane.normal),this.translateZ(-this.plane.constant),super.updateMatrixWorld(e)}dispose(){this.geometry.dispose(),this.material.dispose(),this.children[0].geometry.dispose(),this.children[0].material.dispose()}}const pD=new J;let Tb,J1;class Hce extends null{constructor(e=new J(0,0,1),t=new J(0,0,0),n=1,i=16776960,s=n*.2,a=s*.2){super(),this.type="ArrowHelper",Tb===void 0&&(Tb=new Ni,Tb.setAttribute("position",new yr([0,0,0,0,1,0],3)),J1=new X0(.5,1,5,1),J1.translate(0,-.5,0)),this.position.copy(t),this.line=new j0(Tb,new kl({color:i,toneMapped:!1})),this.line.matrixAutoUpdate=!1,this.add(this.line),this.cone=new Gs(J1,new rl({color:i,toneMapped:!1})),this.cone.matrixAutoUpdate=!1,this.add(this.cone),this.setDirection(e),this.setLength(n,s,a)}setDirection(e){if(e.y>.99999)this.quaternion.set(0,0,0,1);else if(e.y<-.99999)this.quaternion.set(1,0,0,0);else{pD.set(e.z,0,-e.x).normalize();const t=Math.acos(e.y);this.quaternion.setFromAxisAngle(pD,t)}}setLength(e,t=e*.2,n=t*.2){this.line.scale.set(1,Math.max(1e-4,e-t),1),this.line.updateMatrix(),this.cone.scale.set(n,t,n),this.cone.position.y=e,this.cone.updateMatrix()}setColor(e){this.line.material.color.set(e),this.cone.material.color.set(e)}copy(e){return super.copy(e,!1),this.line.copy(e.line),this.cone.copy(e.cone),this}dispose(){this.line.geometry.dispose(),this.line.material.dispose(),this.cone.geometry.dispose(),this.cone.material.dispose()}}class Uce extends null{constructor(e=1){const t=[0,0,0,e,0,0,0,0,0,0,e,0,0,0,0,0,0,e],n=[1,0,0,1,.6,0,0,1,0,.6,1,0,0,0,1,0,.6,1],i=new Ni;i.setAttribute("position",new yr(t,3)),i.setAttribute("color",new yr(n,3));const s=new kl({vertexColors:!0,toneMapped:!1});super(i,s),this.type="AxesHelper"}setColors(e,t,n){const i=new Vn,s=this.geometry.attributes.color.array;return i.set(e),i.toArray(s,0),i.toArray(s,3),i.set(t),i.toArray(s,6),i.toArray(s,9),i.set(n),i.toArray(s,12),i.toArray(s,15),this.geometry.attributes.color.needsUpdate=!0,this}dispose(){this.geometry.dispose(),this.material.dispose()}}class kce{constructor(){this.type="ShapePath",this.color=new Vn,this.subPaths=[],this.currentPath=null}moveTo(e,t){return this.currentPath=new A1,this.subPaths.push(this.currentPath),this.currentPath.moveTo(e,t),this}lineTo(e,t){return this.currentPath.lineTo(e,t),this}quadraticCurveTo(e,t,n,i){return this.currentPath.quadraticCurveTo(e,t,n,i),this}bezierCurveTo(e,t,n,i,s,a){return this.currentPath.bezierCurveTo(e,t,n,i,s,a),this}splineThru(e){return this.currentPath.splineThru(e),this}toShapes(e){function t(m){const C=[];for(let w=0,P=m.length;w<P;w++){const B=m[w],S=new Zv;S.curves=B.curves,C.push(S)}return C}function n(m,C){const w=C.length;let P=!1;for(let B=w-1,S=0;S<w;B=S++){let I=C[B],N=C[S],T=N.x-I.x,R=N.y-I.y;if(Math.abs(R)>Number.EPSILON){if(R<0&&(I=C[S],T=-T,N=C[B],R=-R),m.y<I.y||m.y>N.y)continue;if(m.y===I.y){if(m.x===I.x)return!0}else{const D=R*(m.x-I.x)-T*(m.y-I.y);if(D===0)return!0;if(D<0)continue;P=!P}}else{if(m.y!==I.y)continue;if(N.x<=m.x&&m.x<=I.x||I.x<=m.x&&m.x<=N.x)return!0}}return P}const i=df.isClockWise,s=this.subPaths;if(s.length===0)return[];let a,o,l;const u=[];if(s.length===1)return o=s[0],l=new Zv,l.curves=o.curves,u.push(l),u;let c=!i(s[0].getPoints());c=e?!c:c;const d=[],f=[];let h=[],p=0,x;f[p]=void 0,h[p]=[];for(let m=0,C=s.length;m<C;m++)o=s[m],x=o.getPoints(),a=i(x),a=e?!a:a,a?(!c&&f[p]&&p++,f[p]={s:new Zv,p:x},f[p].s.curves=o.curves,c&&p++,h[p]=[]):h[p].push({h:o,p:x[0]});if(!f[0])return t(s);if(f.length>1){let m=!1,C=0;for(let w=0,P=f.length;w<P;w++)d[w]=[];for(let w=0,P=f.length;w<P;w++){const B=h[w];for(let S=0;S<B.length;S++){const I=B[S];let N=!0;for(let T=0;T<f.length;T++)n(I.p,f[T].p)&&(w!==T&&C++,N?(N=!1,d[T].push(I)):m=!0);N&&d[w].push(I)}}C>0&&m===!1&&(h=d)}let v;for(let m=0,C=f.length;m<C;m++){l=f[m].s,u.push(l),v=h[m];for(let w=0,P=v.length;w<P;w++)l.holes.push(v[w].h)}return u}}class Ib extends Go{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){if(e===void 0){ze("Controls: connect() now requires an element.");return}this.domElement!==null&&this.disconnect(),this.domElement=e}disconnect(){}dispose(){}update(){}}function hO(r,e){const t=r.image&&r.image.width?r.image.width/r.image.height:1;return t>e?(r.repeat.x=1,r.repeat.y=t/e,r.offset.x=0,r.offset.y=(1-r.repeat.y)/2):(r.repeat.x=e/t,r.repeat.y=1,r.offset.x=(1-r.repeat.x)/2,r.offset.y=0),r}function pO(r,e){const t=r.image&&r.image.width?r.image.width/r.image.height:1;return t>e?(r.repeat.x=e/t,r.repeat.y=1,r.offset.x=(1-r.repeat.x)/2,r.offset.y=0):(r.repeat.x=1,r.repeat.y=t/e,r.offset.x=0,r.offset.y=(1-r.repeat.y)/2),r}function mO(r){return r.repeat.x=1,r.repeat.y=1,r.offset.x=0,r.offset.y=0,r}function Nb(r,e,t,n){const i=gO(n);switch(t){case A0:return r*e;case _h:return r*e/i.components*i.byteLength;case Kf:return r*e/i.components*i.byteLength;case Al:return r*e*2/i.components*i.byteLength;case $h:return r*e*2/i.components*i.byteLength;case Sm:return r*e*3/i.components*i.byteLength;case ma:return r*e*4/i.components*i.byteLength;case qf:return r*e*4/i.components*i.byteLength;case Kd:case qd:return Math.floor((r+3)/4)*Math.floor((e+3)/4)*8;case _d:case $d:return Math.floor((r+3)/4)*Math.floor((e+3)/4)*16;case Dm:case Tm:return Math.max(r,16)*Math.max(e,8)/4;case dd:case ep:return Math.max(r,8)*Math.max(e,8)/2;case tp:case Im:case ef:case rp:return Math.floor((r+3)/4)*Math.floor((e+3)/4)*8;case np:case _f:case ip:return Math.floor((r+3)/4)*Math.floor((e+3)/4)*16;case $f:return Math.floor((r+3)/4)*Math.floor((e+3)/4)*16;case sp:return Math.floor((r+4)/5)*Math.floor((e+3)/4)*16;case eh:return Math.floor((r+4)/5)*Math.floor((e+4)/5)*16;case ap:return Math.floor((r+5)/6)*Math.floor((e+4)/5)*16;case th:return Math.floor((r+5)/6)*Math.floor((e+5)/6)*16;case Nm:return Math.floor((r+7)/8)*Math.floor((e+4)/5)*16;case tf:return Math.floor((r+7)/8)*Math.floor((e+5)/6)*16;case op:return Math.floor((r+7)/8)*Math.floor((e+7)/8)*16;case lp:return Math.floor((r+9)/10)*Math.floor((e+4)/5)*16;case up:return Math.floor((r+9)/10)*Math.floor((e+5)/6)*16;case cp:return Math.floor((r+9)/10)*Math.floor((e+7)/8)*16;case dp:return Math.floor((r+9)/10)*Math.floor((e+9)/10)*16;case fp:return Math.floor((r+11)/12)*Math.floor((e+9)/10)*16;case hp:return Math.floor((r+11)/12)*Math.floor((e+11)/12)*16;case nh:case pp:case mp:return Math.ceil(r/4)*Math.ceil(e/4)*16;case gp:case nf:return Math.ceil(r/4)*Math.ceil(e/4)*8;case rf:case vp:return Math.ceil(r/4)*Math.ceil(e/4)*16}throw new Error(`Unable to determine texture byte length for ${t} format.`)}function gO(r){switch(r){case fa:case Jf:return{byteLength:1,components:1};case Yu:case cd:case pa:return{byteLength:2,components:1};case pv:case mv:return{byteLength:2,components:4};case Ls:case Do:case ha:return{byteLength:4,components:1};case gv:case vv:return{byteLength:4,components:3}}throw new Error(`Unknown texture type ${r}.`)}class Vce{static contain(e,t){return hO(e,t)}static cover(e,t){return pO(e,t)}static fill(e){return mO(e)}static getByteLength(e,t,n,i){return Nb(e,t,n,i)}}typeof __THREE_DEVTOOLS__!="undefined"&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent("register",{detail:{revision:Fs}})),typeof window!="undefined"&&(window.__THREE__?ze("WARNING: Multiple instances of Three.js being imported."):window.__THREE__=Fs);const tA=new vd,ph=new ct,mD=new J,K1=new ct,Fb=new ct,Rb=new J,q1=new J,gD=new Cr,vD=new J,AD=new J;let jl=null,ff=null;const mh=[],Fp={NONE:-1,PAN:0,ROTATE:1};class vO extends Ib{constructor(e,t,n=null){super(t,n),this.objects=e,this.recursive=!0,this.transformGroup=!1,this.rotateSpeed=1,this.raycaster=new rD,this.mouseButtons={LEFT:Rs.PAN,MIDDLE:Rs.PAN,RIGHT:Rs.ROTATE},this.touches={ONE:la.PAN},this._onPointerMove=AO.bind(this),this._onPointerDown=xO.bind(this),this._onPointerCancel=yO.bind(this),this._onContextMenu=bO.bind(this),n!==null&&this.connect(n)}connect(e){super.connect(e),this.domElement.addEventListener("pointermove",this._onPointerMove),this.domElement.addEventListener("pointerdown",this._onPointerDown),this.domElement.addEventListener("pointerup",this._onPointerCancel),this.domElement.addEventListener("pointerleave",this._onPointerCancel),this.domElement.addEventListener("contextmenu",this._onContextMenu),this.domElement.style.touchAction="none"}disconnect(){this.domElement.removeEventListener("pointermove",this._onPointerMove),this.domElement.removeEventListener("pointerdown",this._onPointerDown),this.domElement.removeEventListener("pointerup",this._onPointerCancel),this.domElement.removeEventListener("pointerleave",this._onPointerCancel),this.domElement.removeEventListener("contextmenu",this._onContextMenu),this.domElement.style.touchAction="auto",this.domElement.style.cursor=""}dispose(){this.disconnect()}_updatePointer(e){const t=this.domElement.getBoundingClientRect();ph.x=(e.clientX-t.left)/t.width*2-1,ph.y=-(e.clientY-t.top)/t.height*2+1}_updateState(e){let t;if(e.pointerType==="touch")t=this.touches.ONE;else 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=null}switch(t){case Rs.PAN:case la.PAN:this.state=Fp.PAN;break;case Rs.ROTATE:case la.ROTATE:this.state=Fp.ROTATE;break;default:this.state=Fp.NONE}}}function AO(r){const e=this.object,t=this.domElement,n=this.raycaster;if(this.enabled!==!1){if(this._updatePointer(r),n.setFromCamera(ph,e),jl)this.state===Fp.PAN?n.ray.intersectPlane(tA,Rb)&&(jl.position.copy(Rb.sub(mD).applyMatrix4(gD)),this.dispatchEvent({type:"drag",object:jl})):this.state===Fp.ROTATE&&(K1.subVectors(ph,Fb).multiplyScalar(this.rotateSpeed),jl.rotateOnWorldAxis(vD,K1.x),jl.rotateOnWorldAxis(AD.normalize(),-K1.y),this.dispatchEvent({type:"drag",object:jl})),Fb.copy(ph);else if(r.pointerType==="mouse"||r.pointerType==="pen")if(mh.length=0,n.setFromCamera(ph,e),n.intersectObjects(this.objects,this.recursive,mh),mh.length>0){const i=mh[0].object;tA.setFromNormalAndCoplanarPoint(e.getWorldDirection(tA.normal),q1.setFromMatrixPosition(i.matrixWorld)),ff!==i&&ff!==null&&(this.dispatchEvent({type:"hoveroff",object:ff}),t.style.cursor="auto",ff=null),ff!==i&&(this.dispatchEvent({type:"hoveron",object:i}),t.style.cursor="pointer",ff=i)}else ff!==null&&(this.dispatchEvent({type:"hoveroff",object:ff}),t.style.cursor="auto",ff=null);Fb.copy(ph)}}function xO(r){const e=this.object,t=this.domElement,n=this.raycaster;this.enabled!==!1&&(this._updatePointer(r),this._updateState(r),mh.length=0,n.setFromCamera(ph,e),n.intersectObjects(this.objects,this.recursive,mh),mh.length>0&&(this.transformGroup===!0?jl=xD(mh[0].object):jl=mh[0].object,tA.setFromNormalAndCoplanarPoint(e.getWorldDirection(tA.normal),q1.setFromMatrixPosition(jl.matrixWorld)),n.ray.intersectPlane(tA,Rb)&&(this.state===Fp.PAN?(gD.copy(jl.parent.matrixWorld).invert(),mD.copy(Rb).sub(q1.setFromMatrixPosition(jl.matrixWorld)),t.style.cursor="move",this.dispatchEvent({type:"dragstart",object:jl})):this.state===Fp.ROTATE&&(vD.set(0,1,0).applyQuaternion(e.quaternion).normalize(),AD.set(1,0,0).applyQuaternion(e.quaternion).normalize(),t.style.cursor="move",this.dispatchEvent({type:"dragstart",object:jl})))),Fb.copy(ph))}function yO(){this.enabled!==!1&&(jl&&(this.dispatchEvent({type:"dragend",object:jl}),jl=null),this.domElement.style.cursor=ff?"pointer":"auto",this.state=Fp.NONE)}function bO(r){this.enabled!==!1&&r.preventDefault()}function xD(r,e=null){return r.isGroup&&(e=r),r.parent===null?e:xD(r.parent,e)}var EO=O(34949),wO=O(83833);const CO=1664525,PO=1013904223,yD=4294967296;function BO(){let r=1;return()=>(r=(CO*r+PO)%yD)/yD}var bD=3;function _1(r){return r.x}function ED(r){return r.y}function MO(r){return r.z}var SO=10,DO=Math.PI*(3-Math.sqrt(5)),TO=Math.PI*20/(9+Math.sqrt(221));function wD(r,e){e=e||2;var t=Math.min(bD,Math.max(1,Math.round(e))),n,i=1,s=.001,a=1-Math.pow(s,1/300),o=0,l=.6,u=new Map,c=(0,wO.HT)(h),d=(0,EO.Z)("tick","end"),f=BO();r==null&&(r=[]);function h(){p(),d.call("tick",n),i<s&&(c.stop(),d.call("end",n))}function p(m){var C,w=r.length,P;m===void 0&&(m=1);for(var B=0;B<m;++B)for(i+=(o-i)*a,u.forEach(function(S){S(i)}),C=0;C<w;++C)P=r[C],P.fx==null?P.x+=P.vx*=l:(P.x=P.fx,P.vx=0),t>1&&(P.fy==null?P.y+=P.vy*=l:(P.y=P.fy,P.vy=0)),t>2&&(P.fz==null?P.z+=P.vz*=l:(P.z=P.fz,P.vz=0));return n}function x(){for(var m=0,C=r.length,w;m<C;++m){if(w=r[m],w.index=m,w.fx!=null&&(w.x=w.fx),w.fy!=null&&(w.y=w.fy),w.fz!=null&&(w.z=w.fz),isNaN(w.x)||t>1&&isNaN(w.y)||t>2&&isNaN(w.z)){var P=SO*(t>2?Math.cbrt(.5+m):t>1?Math.sqrt(.5+m):m),B=m*DO,S=m*TO;t===1?w.x=P:t===2?(w.x=P*Math.cos(B),w.y=P*Math.sin(B)):(w.x=P*Math.sin(B)*Math.cos(S),w.y=P*Math.cos(B),w.z=P*Math.sin(B)*Math.sin(S))}(isNaN(w.vx)||t>1&&isNaN(w.vy)||t>2&&isNaN(w.vz))&&(w.vx=0,t>1&&(w.vy=0),t>2&&(w.vz=0))}}function v(m){return m.initialize&&m.initialize(r,f,t),m}return x(),n={tick:p,restart:function(){return c.restart(h),n},stop:function(){return c.stop(),n},numDimensions:function(m){return arguments.length?(t=Math.min(bD,Math.max(1,Math.round(m))),u.forEach(v),n):t},nodes:function(m){return arguments.length?(r=m,x(),u.forEach(v),n):r},alpha:function(m){return arguments.length?(i=+m,n):i},alphaMin:function(m){return arguments.length?(s=+m,n):s},alphaDecay:function(m){return arguments.length?(a=+m,n):+a},alphaTarget:function(m){return arguments.length?(o=+m,n):o},velocityDecay:function(m){return arguments.length?(l=1-m,n):1-l},randomSource:function(m){return arguments.length?(f=m,u.forEach(v),n):f},force:function(m,C){return arguments.length>1?(C==null?u.delete(m):u.set(m,v(C)),n):u.get(m)},find:function(){var m=Array.prototype.slice.call(arguments),C=m.shift()||0,w=(t>1?m.shift():null)||0,P=(t>2?m.shift():null)||0,B=m.shift()||1/0,S=0,I=r.length,N,T,R,D,j,q;for(B*=B,S=0;S<I;++S)j=r[S],N=C-j.x,T=w-(j.y||0),R=P-(j.z||0),D=N*N+T*T+R*R,D<B&&(q=j,B=D);return q},on:function(m,C){return arguments.length>1?(d.on(m,C),n):d.on(m)}}}function yd(r){return function(){return r}}function Dc(r){return(r()-.5)*1e-6}function IO(r){return r.index}function CD(r,e){var t=r.get(e);if(!t)throw new Error("node not found: "+e);return t}function PD(r){var e=IO,t=f,n,i=yd(30),s,a,o,l,u,c,d=1;r==null&&(r=[]);function f(m){return 1/Math.min(l[m.source.index],l[m.target.index])}function h(m){for(var C=0,w=r.length;C<d;++C)for(var 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Pi.Box3;o.copy(s.geometry.boundingBox).applyMatrix4(s.matrixWorld),a.push(o)}return a.concat.apply(a,wd((s.children||[]).filter(function(l){return!l.hasOwnProperty("__graphObjType")||l.__graphObjType==="node"&&t(l.__data)}).map(i)))}(e.graphScene);return n.length?Object.assign.apply(Object,wd(["x","y","z"].map(function(i){return Vb({},i,[Yz(n,function(s){return s.min[i]}),Jz(n,function(s){return s.max[i]})])}))):null}},stateInit:function(){return{d3ForceLayout:wD().force("link",PD()).force("charge",TD()).force("center",ID()).force("dagRadial",null).stop(),engineRunning:!1}},init:function(e,t){t.graphScene=e,t.nodeDataMapper=new ex(e,{objBindAttr:"__threeObj"}),t.linkDataMapper=new ex(e,{objBindAttr:"__lineObj"}),t.arrowDataMapper=new ex(e,{objBindAttr:"__arrowObj"}),t.particlesDataMapper=new ex(e,{objBindAttr:"__photonsObj"})},update:function(e,t){var n=function(ee){return ee.some(function(ue){return t.hasOwnProperty(ue)})};if(e.engineRunning=!1,typeof e.onUpdate=="function"&&e.onUpdate(),e.nodeAutoColorBy!==null&&n(["nodeAutoColorBy","graphData","nodeColor"])&&mT(e.graphData.nodes,gs(e.nodeAutoColorBy),e.nodeColor),e.linkAutoColorBy!==null&&n(["linkAutoColorBy","graphData","linkColor"])&&mT(e.graphData.links,gs(e.linkAutoColorBy),e.linkColor),e._flushObjects||n(["graphData","nodeThreeObject","nodeThreeObjectExtend","nodeVal","nodeColor","nodeVisibility","nodeRelSize","nodeResolution","nodeOpacity"])){var i=gs(e.nodeThreeObject),s=gs(e.nodeThreeObjectExtend),a=gs(e.nodeVal),o=gs(e.nodeColor),l=gs(e.nodeVisibility),u={},c={};(e._flushObjects||n(["nodeThreeObject","nodeThreeObjectExtend"]))&&e.nodeDataMapper.clear(),e.nodeDataMapper.onCreateObj(function(ve){var ee=i(ve),ue=s(ve);ee&&e.nodeThreeObject===ee&&(ee=ee.clone());var Ue;return ee&&!ue?Ue=ee:(Ue=new Pi.Mesh,Ue.__graphDefaultObj=!0,ee&&ue&&Ue.add(ee)),Ue.__graphObjType="node",Ue}).onUpdateObj(function(ve,ee){if(ve.__graphDefaultObj){var ue=a(ee)||1,Ue=Math.cbrt(ue)*e.nodeRelSize,$e=e.nodeResolution;(!ve.geometry.type.match(/^Sphere(Buffer)?Geometry$/)||ve.geometry.parameters.radius!==Ue||ve.geometry.parameters.widthSegments!==$e)&&(u.hasOwnProperty(ue)||(u[ue]=new Pi.SphereGeometry(Ue,$e,$e)),ve.geometry.dispose(),ve.geometry=u[ue]);var He=o(ee),bt=new Pi.Color(tx(He||"#ffffaa")),$t=e.nodeOpacity*AP(He);(ve.material.type!=="MeshLambertMaterial"||!ve.material.color.equals(bt)||ve.material.opacity!==$t)&&(c.hasOwnProperty(He)||(c[He]=new Pi.MeshLambertMaterial({color:bt,transparent:!0,opacity:$t})),ve.material.dispose(),ve.material=c[He])}}).digest(e.graphData.nodes.filter(l))}if(e._flushObjects||n(["graphData","linkThreeObject","linkThreeObjectExtend","linkMaterial","linkColor","linkWidth","linkVisibility","linkResolution","linkOpacity","linkDirectionalArrowLength","linkDirectionalArrowColor","linkDirectionalArrowResolution","linkDirectionalParticles","linkDirectionalParticleWidth","linkDirectionalParticleColor","linkDirectionalParticleResolution","linkDirectionalParticleThreeObject"])){var d=gs(e.linkThreeObject),f=gs(e.linkThreeObjectExtend),h=gs(e.linkMaterial),p=gs(e.linkVisibility),x=gs(e.linkColor),v=gs(e.linkWidth),m={},C={},w={},P=e.graphData.links.filter(p);if((e._flushObjects||n(["linkThreeObject","linkThreeObjectExtend","linkWidth"]))&&e.linkDataMapper.clear(),e.linkDataMapper.onRemoveObj(function(ve){var ee=ve.__data&&ve.__data.__singleHopPhotonsObj;ee&&(ee.parent.remove(ee),gP(ee),delete ve.__data.__singleHopPhotonsObj)}).onCreateObj(function(ve){var ee=d(ve),ue=f(ve);ee&&e.linkThreeObject===ee&&(ee=ee.clone());var Ue;if(!ee||ue){var $e=!!v(ve);if($e)Ue=new Pi.Mesh;else{var He=new Pi.BufferGeometry;He[xP]("position",new Pi.BufferAttribute(new Float32Array(2*3),3)),Ue=new Pi.Line(He)}}var bt;return ee?ue?(bt=new Pi.Group,bt.__graphDefaultObj=!0,bt.add(Ue),bt.add(ee)):bt=ee:(bt=Ue,bt.__graphDefaultObj=!0),bt.renderOrder=10,bt.__graphObjType="link",bt}).onUpdateObj(function(ve,ee){if(ve.__graphDefaultObj){var ue=ve.children.length?ve.children[0]:ve,Ue=Math.ceil(v(ee)*10)/10,$e=!!Ue;if($e){var He=Ue/2,bt=e.linkResolution;if(!ue.geometry.type.match(/^Cylinder(Buffer)?Geometry$/)||ue.geometry.parameters.radiusTop!==He||ue.geometry.parameters.radialSegments!==bt){if(!m.hasOwnProperty(Ue)){var $t=new Pi.CylinderGeometry(He,He,1,bt,1,!1);$t[Xb](new Pi.Matrix4().makeTranslation(0,1/2,0)),$t[Xb](new Pi.Matrix4().makeRotationX(Math.PI/2)),m[Ue]=$t}ue.geometry.dispose(),ue.geometry=m[Ue]}}var zn=h(ee);if(zn)ue.material=zn;else{var Me=x(ee),Et=new Pi.Color(tx(Me||"#f0f0f0")),ft=e.linkOpacity*AP(Me),Yt=$e?"MeshLambertMaterial":"LineBasicMaterial";if(ue.material.type!==Yt||!ue.material.color.equals(Et)||ue.material.opacity!==ft){var se=$e?C:w;se.hasOwnProperty(Me)||(se[Me]=new Pi[Yt]({color:Et,transparent:ft<1,opacity:ft,depthWrite:ft>=1})),ue.material.dispose(),ue.material=se[Me]}}}}).digest(P),e.linkDirectionalArrowLength||t.hasOwnProperty("linkDirectionalArrowLength")){var B=gs(e.linkDirectionalArrowLength),S=gs(e.linkDirectionalArrowColor);e.arrowDataMapper.onCreateObj(function(){var ve=new Pi.Mesh(void 0,new Pi.MeshLambertMaterial({transparent:!0}));return ve.__linkThreeObjType="arrow",ve}).onUpdateObj(function(ve,ee){var ue=B(ee),Ue=e.linkDirectionalArrowResolution;if(!ve.geometry.type.match(/^Cone(Buffer)?Geometry$/)||ve.geometry.parameters.height!==ue||ve.geometry.parameters.radialSegments!==Ue){var $e=new Pi.ConeGeometry(ue*.25,ue,Ue);$e.translate(0,ue/2,0),$e.rotateX(Math.PI/2),ve.geometry.dispose(),ve.geometry=$e}var He=S(ee)||x(ee)||"#f0f0f0";ve.material.color=new Pi.Color(tx(He)),ve.material.opacity=e.linkOpacity*3*AP(He)}).digest(P.filter(B))}if(e.linkDirectionalParticles||t.hasOwnProperty("linkDirectionalParticles")){var I=gs(e.linkDirectionalParticles),N=gs(e.linkDirectionalParticleWidth),T=gs(e.linkDirectionalParticleColor),R=gs(e.linkDirectionalParticleThreeObject),D={},j={};e.particlesDataMapper.onCreateObj(function(){var ve=new Pi.Group;return ve.__linkThreeObjType="photons",ve.__photonDataMapper=new ex(ve),ve}).onUpdateObj(function(ve,ee){var ue=!!ve.children.length&&ve.children[0],Ue=R(ee),$e,He;if(Ue)$e=Ue.geometry,He=Ue.material;else{var bt=Math.ceil(N(ee)*10)/10/2,$t=e.linkDirectionalParticleResolution;ue&&ue.geometry.parameters.radius===bt&&ue.geometry.parameters.widthSegments===$t?$e=ue.geometry:(j.hasOwnProperty(bt)||(j[bt]=new Pi.SphereGeometry(bt,$t,$t)),$e=j[bt]);var zn=T(ee)||x(ee)||"#f0f0f0",Me=new Pi.Color(tx(zn)),Et=e.linkOpacity*3;ue&&ue.material.color.equals(Me)&&ue.material.opacity===Et?He=ue.material:(D.hasOwnProperty(zn)||(D[zn]=new Pi.MeshLambertMaterial({color:Me,transparent:!0,opacity:Et})),He=D[zn])}ue&&(ue.geometry!==$e&&ue.geometry.dispose(),ue.material!==He&&ue.material.dispose());var ft=Math.round(Math.abs(I(ee)));ve.__photonDataMapper.id(function(Yt){return Yt.idx}).onCreateObj(function(){return new Pi.Mesh($e,He)}).onUpdateObj(function(Yt){Yt.geometry=$e,Yt.material=He}).digest(wd(new Array(ft)).map(function(Yt,se){return{idx:se}}))}).digest(P.filter(I))}}if(e._flushObjects=!1,n(["graphData","nodeId","linkSource","linkTarget","numDimensions","forceEngine","dagMode","dagNodeFilter","dagLevelDistance"])){e.engineRunning=!1,e.graphData.links.forEach(function(ve){ve.source=ve[e.linkSource],ve.target=ve[e.linkTarget]});var q=e.forceEngine!=="ngraph",Q;if(q){(Q=e.d3ForceLayout).stop().alpha(1).numDimensions(e.numDimensions).nodes(e.graphData.nodes);var re=e.d3ForceLayout.force("link");re&&re.id(function(ve){return ve[e.nodeId]}).links(e.graphData.links);var de=e.dagMode&&_H(e.graphData,function(ve){return ve[e.nodeId]},{nodeFilter:e.dagNodeFilter,onLoopError:e.onDagError||void 0}),we=Math.max.apply(Math,wd(Object.values(de||[]))),ge=e.dagLevelDistance||e.graphData.nodes.length/(we||1)*$H*(["radialin","radialout"].indexOf(e.dagMode)!==-1?.7:1);if(["lr","rl","td","bu","zin","zout"].includes(t.dagMode)){var Y=["lr","rl"].includes(t.dagMode)?"fx":["td","bu"].includes(t.dagMode)?"fy":"fz";e.graphData.nodes.filter(e.dagNodeFilter).forEach(function(ve){return delete ve[Y]})}if(["lr","rl","td","bu","zin","zout"].includes(e.dagMode)){var Se=["rl","td","zout"].includes(e.dagMode),W=function(ee){return(de[ee[e.nodeId]]-we/2)*ge*(Se?-1:1)},fe=["lr","rl"].includes(e.dagMode)?"fx":["td","bu"].includes(e.dagMode)?"fy":"fz";e.graphData.nodes.filter(e.dagNodeFilter).forEach(function(ve){return ve[fe]=W(ve)})}e.d3ForceLayout.force("dagRadial",["radialin","radialout"].indexOf(e.dagMode)!==-1?QO(function(ve){var ee=de[ve[e.nodeId]]||-1;return(e.dagMode==="radialin"?we-ee:ee)*ge}).strength(function(ve){return e.dagNodeFilter(ve)?1:0}):null)}else{var xe=gT.graph();e.graphData.nodes.forEach(function(ve){xe.addNode(ve[e.nodeId])}),e.graphData.links.forEach(function(ve){xe.addLink(ve.source,ve.target)}),Q=gT.forcelayout(xe,ZH({dimensions:e.numDimensions},e.ngraphPhysics)),Q.graph=xe}for(var dt=0;dt<e.warmupTicks&&!(q&&e.d3AlphaMin>0&&e.d3ForceLayout.alpha()<e.d3AlphaMin);dt++)Q[q?"tick":"step"]();e.layout=Q,this.resetCountdown()}e.engineRunning=!0,e.onFinishUpdate()}});function tU(r){var e=arguments.length>1&&arguments[1]!==void 0?arguments[1]:Object,t=arguments.length>2&&arguments[2]!==void 0?arguments[2]:!1,n=function(i){function s(){var a;iT(this,s);for(var o=arguments.length,l=new Array(o),u=0;u<o;u++)l[u]=arguments[u];return a=rT(this,s,[].concat(l)),a.__kapsuleInstance=oT(r,[].concat(wd(t?[a]:[]),l)),a}return uT(s,i),lT(s)}(e);return Object.keys(r()).forEach(function(i){return n.prototype[i]=function(){var s,a=(s=this.__kapsuleInstance)[i].apply(s,arguments);return a===this.__kapsuleInstance?this:a}}),n}var nU=window.THREE?window.THREE:{Group:Vm},vT=tU(eU,nU.Group,!0);function AT(){let r=null,e=!1,t=null,n=null;function i(s,a){t(s,a),n=r.requestAnimationFrame(i)}return{start:function(){e!==!0&&t!==null&&(n=r.requestAnimationFrame(i),e=!0)},stop:function(){r.cancelAnimationFrame(n),e=!1},setAnimationLoop:function(s){t=s},setContext:function(s){r=s}}}function rU(r){const e=new WeakMap;function t(o,l){const u=o.array,c=o.usage,d=u.byteLength,f=r.createBuffer();r.bindBuffer(l,f),r.bufferData(l,u,c),o.onUploadCallback();let h;if(u instanceof Float32Array)h=r.FLOAT;else if(typeof Float16Array!="undefined"&&u instanceof Float16Array)h=r.HALF_FLOAT;else if(u instanceof Uint16Array)o.isFloat16BufferAttribute?h=r.HALF_FLOAT:h=r.UNSIGNED_SHORT;else if(u instanceof Int16Array)h=r.SHORT;else if(u instanceof Uint32Array)h=r.UNSIGNED_INT;else if(u instanceof Int32Array)h=r.INT;else if(u instanceof Int8Array)h=r.BYTE;else if(u instanceof Uint8Array)h=r.UNSIGNED_BYTE;else if(u instanceof Uint8ClampedArray)h=r.UNSIGNED_BYTE;else throw new Error("THREE.WebGLAttributes: Unsupported buffer data format: "+u);return{buffer:f,type:h,bytesPerElement:u.BYTES_PER_ELEMENT,version:o.version,size:d}}function n(o,l,u){const c=l.array,d=l.updateRanges;if(r.bindBuffer(u,o),d.length===0)r.bufferSubData(u,0,c);else{d.sort((h,p)=>h.start-p.start);let f=0;for(let h=1;h<d.length;h++){const p=d[f],x=d[h];x.start<=p.start+p.count+1?p.count=Math.max(p.count,x.start+x.count-p.start):(++f,d[f]=x)}d.length=f+1;for(let h=0,p=d.length;h<p;h++){const x=d[h];r.bufferSubData(u,x.start*c.BYTES_PER_ELEMENT,c,x.start,x.count)}l.clearUpdateRanges()}l.onUploadCallback()}function i(o){return o.isInterleavedBufferAttribute&&(o=o.data),e.get(o)}function s(o){o.isInterleavedBufferAttribute&&(o=o.data);const l=e.get(o);l&&(r.deleteBuffer(l.buffer),e.delete(o))}function a(o,l){if(o.isInterleavedBufferAttribute&&(o=o.data),o.isGLBufferAttribute){const c=e.get(o);(!c||c.version<o.version)&&e.set(o,{buffer:o.buffer,type:o.type,bytesPerElement:o.elementSize,version:o.version});return}const u=e.get(o);if(u===void 0)e.set(o,t(o,l));else if(u.version<o.version){if(u.size!==o.array.byteLength)throw new Error("THREE.WebGLAttributes: The size of the buffer attribute's array buffer does not match the original size. Resizing buffer attributes is not supported.");n(u.buffer,o,l),u.version=o.version}}return{get:i,remove:s,update:a}}var iU=`#ifdef USE_ALPHAHASH
	if ( diffuseColor.a < getAlphaHashThreshold( vPosition ) ) discard;
#endif`,sU=`#ifdef USE_ALPHAHASH
	const float ALPHA_HASH_SCALE = 0.05;
	float hash2D( vec2 value ) {
		return fract( 1.0e4 * sin( 17.0 * value.x + 0.1 * value.y ) * ( 0.1 + abs( sin( 13.0 * value.y + value.x ) ) ) );
	}
	float hash3D( vec3 value ) {
		return hash2D( vec2( hash2D( value.xy ), value.z ) );
	}
	float getAlphaHashThreshold( vec3 position ) {
		float maxDeriv = max(
			length( dFdx( position.xyz ) ),
			length( dFdy( position.xyz ) )
		);
		float pixScale = 1.0 / ( ALPHA_HASH_SCALE * maxDeriv );
		vec2 pixScales = vec2(
			exp2( floor( log2( pixScale ) ) ),
			exp2( ceil( log2( pixScale ) ) )
		);
		vec2 alpha = vec2(
			hash3D( floor( pixScales.x * position.xyz ) ),
			hash3D( floor( pixScales.y * position.xyz ) )
		);
		float lerpFactor = fract( log2( pixScale ) );
		float x = ( 1.0 - lerpFactor ) * alpha.x + lerpFactor * alpha.y;
		float a = min( lerpFactor, 1.0 - lerpFactor );
		vec3 cases = vec3(
			x * x / ( 2.0 * a * ( 1.0 - a ) ),
			( x - 0.5 * a ) / ( 1.0 - a ),
			1.0 - ( ( 1.0 - x ) * ( 1.0 - x ) / ( 2.0 * a * ( 1.0 - a ) ) )
		);
		float threshold = ( x < ( 1.0 - a ) )
			? ( ( x < a ) ? cases.x : cases.y )
			: cases.z;
		return clamp( threshold , 1.0e-6, 1.0 );
	}
#endif`,aU=`#ifdef USE_ALPHAMAP
	diffuseColor.a *= texture2D( alphaMap, vAlphaMapUv ).g;
#endif`,oU=`#ifdef USE_ALPHAMAP
	uniform sampler2D alphaMap;
#endif`,lU=`#ifdef USE_ALPHATEST
	#ifdef ALPHA_TO_COVERAGE
	diffuseColor.a = smoothstep( alphaTest, alphaTest + fwidth( diffuseColor.a ), diffuseColor.a );
	if ( diffuseColor.a == 0.0 ) discard;
	#else
	if ( diffuseColor.a < alphaTest ) discard;
	#endif
#endif`,uU=`#ifdef USE_ALPHATEST
	uniform float alphaTest;
#endif`,cU=`#ifdef USE_AOMAP
	float ambientOcclusion = ( texture2D( aoMap, vAoMapUv ).r - 1.0 ) * aoMapIntensity + 1.0;
	reflectedLight.indirectDiffuse *= ambientOcclusion;
	#if defined( USE_CLEARCOAT ) 
		clearcoatSpecularIndirect *= ambientOcclusion;
	#endif
	#if defined( USE_SHEEN ) 
		sheenSpecularIndirect *= ambientOcclusion;
	#endif
	#if defined( USE_ENVMAP ) && defined( STANDARD )
		float dotNV = saturate( dot( geometryNormal, geometryViewDir ) );
		reflectedLight.indirectSpecular *= computeSpecularOcclusion( dotNV, ambientOcclusion, material.roughness );
	#endif
#endif`,dU=`#ifdef USE_AOMAP
	uniform sampler2D aoMap;
	uniform float aoMapIntensity;
#endif`,fU=`#ifdef USE_BATCHING
	#if ! defined( GL_ANGLE_multi_draw )
	#define gl_DrawID _gl_DrawID
	uniform int _gl_DrawID;
	#endif
	uniform highp sampler2D batchingTexture;
	uniform highp usampler2D batchingIdTexture;
	mat4 getBatchingMatrix( const in float i ) {
		int size = textureSize( batchingTexture, 0 ).x;
		int j = int( i ) * 4;
		int x = j % size;
		int y = j / size;
		vec4 v1 = texelFetch( batchingTexture, ivec2( x, y ), 0 );
		vec4 v2 = texelFetch( batchingTexture, ivec2( x + 1, y ), 0 );
		vec4 v3 = texelFetch( batchingTexture, ivec2( x + 2, y ), 0 );
		vec4 v4 = texelFetch( batchingTexture, ivec2( x + 3, y ), 0 );
		return mat4( v1, v2, v3, v4 );
	}
	float getIndirectIndex( const in int i ) {
		int size = textureSize( batchingIdTexture, 0 ).x;
		int x = i % size;
		int y = i / size;
		return float( texelFetch( batchingIdTexture, ivec2( x, y ), 0 ).r );
	}
#endif
#ifdef USE_BATCHING_COLOR
	uniform sampler2D batchingColorTexture;
	vec3 getBatchingColor( const in float i ) {
		int size = textureSize( batchingColorTexture, 0 ).x;
		int j = int( i );
		int x = j % size;
		int y = j / size;
		return texelFetch( batchingColorTexture, ivec2( x, y ), 0 ).rgb;
	}
#endif`,hU=`#ifdef USE_BATCHING
	mat4 batchingMatrix = getBatchingMatrix( getIndirectIndex( gl_DrawID ) );
#endif`,pU=`vec3 transformed = vec3( position );
#ifdef USE_ALPHAHASH
	vPosition = vec3( position );
#endif`,mU=`vec3 objectNormal = vec3( normal );
#ifdef USE_TANGENT
	vec3 objectTangent = vec3( tangent.xyz );
#endif`,gU=`float G_BlinnPhong_Implicit( ) {
	return 0.25;
}
float D_BlinnPhong( const in float shininess, const in float dotNH ) {
	return RECIPROCAL_PI * ( shininess * 0.5 + 1.0 ) * pow( dotNH, shininess );
}
vec3 BRDF_BlinnPhong( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in vec3 specularColor, const in float shininess ) {
	vec3 halfDir = normalize( lightDir + viewDir );
	float dotNH = saturate( dot( normal, halfDir ) );
	float dotVH = saturate( dot( viewDir, halfDir ) );
	vec3 F = F_Schlick( specularColor, 1.0, dotVH );
	float G = G_BlinnPhong_Implicit( );
	float D = D_BlinnPhong( shininess, dotNH );
	return F * ( G * D );
} // validated`,vU=`#ifdef USE_IRIDESCENCE
	const mat3 XYZ_TO_REC709 = mat3(
		 3.2404542, -0.9692660,  0.0556434,
		-1.5371385,  1.8760108, -0.2040259,
		-0.4985314,  0.0415560,  1.0572252
	);
	vec3 Fresnel0ToIor( vec3 fresnel0 ) {
		vec3 sqrtF0 = sqrt( fresnel0 );
		return ( vec3( 1.0 ) + sqrtF0 ) / ( vec3( 1.0 ) - sqrtF0 );
	}
	vec3 IorToFresnel0( vec3 transmittedIor, float incidentIor ) {
		return pow2( ( transmittedIor - vec3( incidentIor ) ) / ( transmittedIor + vec3( incidentIor ) ) );
	}
	float IorToFresnel0( float transmittedIor, float incidentIor ) {
		return pow2( ( transmittedIor - incidentIor ) / ( transmittedIor + incidentIor ));
	}
	vec3 evalSensitivity( float OPD, vec3 shift ) {
		float phase = 2.0 * PI * OPD * 1.0e-9;
		vec3 val = vec3( 5.4856e-13, 4.4201e-13, 5.2481e-13 );
		vec3 pos = vec3( 1.6810e+06, 1.7953e+06, 2.2084e+06 );
		vec3 var = vec3( 4.3278e+09, 9.3046e+09, 6.6121e+09 );
		vec3 xyz = val * sqrt( 2.0 * PI * var ) * cos( pos * phase + shift ) * exp( - pow2( phase ) * var );
		xyz.x += 9.7470e-14 * sqrt( 2.0 * PI * 4.5282e+09 ) * cos( 2.2399e+06 * phase + shift[ 0 ] ) * exp( - 4.5282e+09 * pow2( phase ) );
		xyz /= 1.0685e-7;
		vec3 rgb = XYZ_TO_REC709 * xyz;
		return rgb;
	}
	vec3 evalIridescence( float outsideIOR, float eta2, float cosTheta1, float thinFilmThickness, vec3 baseF0 ) {
		vec3 I;
		float iridescenceIOR = mix( outsideIOR, eta2, smoothstep( 0.0, 0.03, thinFilmThickness ) );
		float sinTheta2Sq = pow2( outsideIOR / iridescenceIOR ) * ( 1.0 - pow2( cosTheta1 ) );
		float cosTheta2Sq = 1.0 - sinTheta2Sq;
		if ( cosTheta2Sq < 0.0 ) {
			return vec3( 1.0 );
		}
		float cosTheta2 = sqrt( cosTheta2Sq );
		float R0 = IorToFresnel0( iridescenceIOR, outsideIOR );
		float R12 = F_Schlick( R0, 1.0, cosTheta1 );
		float T121 = 1.0 - R12;
		float phi12 = 0.0;
		if ( iridescenceIOR < outsideIOR ) phi12 = PI;
		float phi21 = PI - phi12;
		vec3 baseIOR = Fresnel0ToIor( clamp( baseF0, 0.0, 0.9999 ) );		vec3 R1 = IorToFresnel0( baseIOR, iridescenceIOR );
		vec3 R23 = F_Schlick( R1, 1.0, cosTheta2 );
		vec3 phi23 = vec3( 0.0 );
		if ( baseIOR[ 0 ] < iridescenceIOR ) phi23[ 0 ] = PI;
		if ( baseIOR[ 1 ] < iridescenceIOR ) phi23[ 1 ] = PI;
		if ( baseIOR[ 2 ] < iridescenceIOR ) phi23[ 2 ] = PI;
		float OPD = 2.0 * iridescenceIOR * thinFilmThickness * cosTheta2;
		vec3 phi = vec3( phi21 ) + phi23;
		vec3 R123 = clamp( R12 * R23, 1e-5, 0.9999 );
		vec3 r123 = sqrt( R123 );
		vec3 Rs = pow2( T121 ) * R23 / ( vec3( 1.0 ) - R123 );
		vec3 C0 = R12 + Rs;
		I = C0;
		vec3 Cm = Rs - T121;
		for ( int m = 1; m <= 2; ++ m ) {
			Cm *= r123;
			vec3 Sm = 2.0 * evalSensitivity( float( m ) * OPD, float( m ) * phi );
			I += Cm * Sm;
		}
		return max( I, vec3( 0.0 ) );
	}
#endif`,AU=`#ifdef USE_BUMPMAP
	uniform sampler2D bumpMap;
	uniform float bumpScale;
	vec2 dHdxy_fwd() {
		vec2 dSTdx = dFdx( vBumpMapUv );
		vec2 dSTdy = dFdy( vBumpMapUv );
		float Hll = bumpScale * texture2D( bumpMap, vBumpMapUv ).x;
		float dBx = bumpScale * texture2D( bumpMap, vBumpMapUv + dSTdx ).x - Hll;
		float dBy = bumpScale * texture2D( bumpMap, vBumpMapUv + dSTdy ).x - Hll;
		return vec2( dBx, dBy );
	}
	vec3 perturbNormalArb( vec3 surf_pos, vec3 surf_norm, vec2 dHdxy, float faceDirection ) {
		vec3 vSigmaX = normalize( dFdx( surf_pos.xyz ) );
		vec3 vSigmaY = normalize( dFdy( surf_pos.xyz ) );
		vec3 vN = surf_norm;
		vec3 R1 = cross( vSigmaY, vN );
		vec3 R2 = cross( vN, vSigmaX );
		float fDet = dot( vSigmaX, R1 ) * faceDirection;
		vec3 vGrad = sign( fDet ) * ( dHdxy.x * R1 + dHdxy.y * R2 );
		return normalize( abs( fDet ) * surf_norm - vGrad );
	}
#endif`,xU=`#if NUM_CLIPPING_PLANES > 0
	vec4 plane;
	#ifdef ALPHA_TO_COVERAGE
		float distanceToPlane, distanceGradient;
		float clipOpacity = 1.0;
		#pragma unroll_loop_start
		for ( int i = 0; i < UNION_CLIPPING_PLANES; i ++ ) {
			plane = clippingPlanes[ i ];
			distanceToPlane = - dot( vClipPosition, plane.xyz ) + plane.w;
			distanceGradient = fwidth( distanceToPlane ) / 2.0;
			clipOpacity *= smoothstep( - distanceGradient, distanceGradient, distanceToPlane );
			if ( clipOpacity == 0.0 ) discard;
		}
		#pragma unroll_loop_end
		#if UNION_CLIPPING_PLANES < NUM_CLIPPING_PLANES
			float unionClipOpacity = 1.0;
			#pragma unroll_loop_start
			for ( int i = UNION_CLIPPING_PLANES; i < NUM_CLIPPING_PLANES; i ++ ) {
				plane = clippingPlanes[ i ];
				distanceToPlane = - dot( vClipPosition, plane.xyz ) + plane.w;
				distanceGradient = fwidth( distanceToPlane ) / 2.0;
				unionClipOpacity *= 1.0 - smoothstep( - distanceGradient, distanceGradient, distanceToPlane );
			}
			#pragma unroll_loop_end
			clipOpacity *= 1.0 - unionClipOpacity;
		#endif
		diffuseColor.a *= clipOpacity;
		if ( diffuseColor.a == 0.0 ) discard;
	#else
		#pragma unroll_loop_start
		for ( int i = 0; i < UNION_CLIPPING_PLANES; i ++ ) {
			plane = clippingPlanes[ i ];
			if ( dot( vClipPosition, plane.xyz ) > plane.w ) discard;
		}
		#pragma unroll_loop_end
		#if UNION_CLIPPING_PLANES < NUM_CLIPPING_PLANES
			bool clipped = true;
			#pragma unroll_loop_start
			for ( int i = UNION_CLIPPING_PLANES; i < NUM_CLIPPING_PLANES; i ++ ) {
				plane = clippingPlanes[ i ];
				clipped = ( dot( vClipPosition, plane.xyz ) > plane.w ) && clipped;
			}
			#pragma unroll_loop_end
			if ( clipped ) discard;
		#endif
	#endif
#endif`,yU=`#if NUM_CLIPPING_PLANES > 0
	varying vec3 vClipPosition;
	uniform vec4 clippingPlanes[ NUM_CLIPPING_PLANES ];
#endif`,bU=`#if NUM_CLIPPING_PLANES > 0
	varying vec3 vClipPosition;
#endif`,EU=`#if NUM_CLIPPING_PLANES > 0
	vClipPosition = - mvPosition.xyz;
#endif`,wU=`#if defined( USE_COLOR_ALPHA )
	diffuseColor *= vColor;
#elif defined( USE_COLOR )
	diffuseColor.rgb *= vColor;
#endif`,CU=`#if defined( USE_COLOR_ALPHA )
	varying vec4 vColor;
#elif defined( USE_COLOR )
	varying vec3 vColor;
#endif`,PU=`#if defined( USE_COLOR_ALPHA )
	varying vec4 vColor;
#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR ) || defined( USE_BATCHING_COLOR )
	varying vec3 vColor;
#endif`,BU=`#if defined( USE_COLOR_ALPHA )
	vColor = vec4( 1.0 );
#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR ) || defined( USE_BATCHING_COLOR )
	vColor = vec3( 1.0 );
#endif
#ifdef USE_COLOR
	vColor *= color;
#endif
#ifdef USE_INSTANCING_COLOR
	vColor.xyz *= instanceColor.xyz;
#endif
#ifdef USE_BATCHING_COLOR
	vec3 batchingColor = getBatchingColor( getIndirectIndex( gl_DrawID ) );
	vColor.xyz *= batchingColor.xyz;
#endif`,MU=`#define PI 3.141592653589793
#define PI2 6.283185307179586
#define PI_HALF 1.5707963267948966
#define RECIPROCAL_PI 0.3183098861837907
#define RECIPROCAL_PI2 0.15915494309189535
#define EPSILON 1e-6
#ifndef saturate
#define saturate( a ) clamp( a, 0.0, 1.0 )
#endif
#define whiteComplement( a ) ( 1.0 - saturate( a ) )
float pow2( const in float x ) { return x*x; }
vec3 pow2( const in vec3 x ) { return x*x; }
float pow3( const in float x ) { return x*x*x; }
float pow4( const in float x ) { float x2 = x*x; return x2*x2; }
float max3( const in vec3 v ) { return max( max( v.x, v.y ), v.z ); }
float average( const in vec3 v ) { return dot( v, vec3( 0.3333333 ) ); }
highp float rand( const in vec2 uv ) {
	const highp float a = 12.9898, b = 78.233, c = 43758.5453;
	highp float dt = dot( uv.xy, vec2( a,b ) ), sn = mod( dt, PI );
	return fract( sin( sn ) * c );
}
#ifdef HIGH_PRECISION
	float precisionSafeLength( vec3 v ) { return length( v ); }
#else
	float precisionSafeLength( vec3 v ) {
		float maxComponent = max3( abs( v ) );
		return length( v / maxComponent ) * maxComponent;
	}
#endif
struct IncidentLight {
	vec3 color;
	vec3 direction;
	bool visible;
};
struct ReflectedLight {
	vec3 directDiffuse;
	vec3 directSpecular;
	vec3 indirectDiffuse;
	vec3 indirectSpecular;
};
#ifdef USE_ALPHAHASH
	varying vec3 vPosition;
#endif
vec3 transformDirection( in vec3 dir, in mat4 matrix ) {
	return normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );
}
vec3 inverseTransformDirection( in vec3 dir, in mat4 matrix ) {
	return normalize( ( vec4( dir, 0.0 ) * matrix ).xyz );
}
bool isPerspectiveMatrix( mat4 m ) {
	return m[ 2 ][ 3 ] == - 1.0;
}
vec2 equirectUv( in vec3 dir ) {
	float u = atan( dir.z, dir.x ) * RECIPROCAL_PI2 + 0.5;
	float v = asin( clamp( dir.y, - 1.0, 1.0 ) ) * RECIPROCAL_PI + 0.5;
	return vec2( u, v );
}
vec3 BRDF_Lambert( const in vec3 diffuseColor ) {
	return RECIPROCAL_PI * diffuseColor;
}
vec3 F_Schlick( const in vec3 f0, const in float f90, const in float dotVH ) {
	float fresnel = exp2( ( - 5.55473 * dotVH - 6.98316 ) * dotVH );
	return f0 * ( 1.0 - fresnel ) + ( f90 * fresnel );
}
float F_Schlick( const in float f0, const in float f90, const in float dotVH ) {
	float fresnel = exp2( ( - 5.55473 * dotVH - 6.98316 ) * dotVH );
	return f0 * ( 1.0 - fresnel ) + ( f90 * fresnel );
} // validated`,SU=`#ifdef ENVMAP_TYPE_CUBE_UV
	#define cubeUV_minMipLevel 4.0
	#define cubeUV_minTileSize 16.0
	float getFace( vec3 direction ) {
		vec3 absDirection = abs( direction );
		float face = - 1.0;
		if ( absDirection.x > absDirection.z ) {
			if ( absDirection.x > absDirection.y )
				face = direction.x > 0.0 ? 0.0 : 3.0;
			else
				face = direction.y > 0.0 ? 1.0 : 4.0;
		} else {
			if ( absDirection.z > absDirection.y )
				face = direction.z > 0.0 ? 2.0 : 5.0;
			else
				face = direction.y > 0.0 ? 1.0 : 4.0;
		}
		return face;
	}
	vec2 getUV( vec3 direction, float face ) {
		vec2 uv;
		if ( face == 0.0 ) {
			uv = vec2( direction.z, direction.y ) / abs( direction.x );
		} else if ( face == 1.0 ) {
			uv = vec2( - direction.x, - direction.z ) / abs( direction.y );
		} else if ( face == 2.0 ) {
			uv = vec2( - direction.x, direction.y ) / abs( direction.z );
		} else if ( face == 3.0 ) {
			uv = vec2( - direction.z, direction.y ) / abs( direction.x );
		} else if ( face == 4.0 ) {
			uv = vec2( - direction.x, direction.z ) / abs( direction.y );
		} else {
			uv = vec2( direction.x, direction.y ) / abs( direction.z );
		}
		return 0.5 * ( uv + 1.0 );
	}
	vec3 bilinearCubeUV( sampler2D envMap, vec3 direction, float mipInt ) {
		float face = getFace( direction );
		float filterInt = max( cubeUV_minMipLevel - mipInt, 0.0 );
		mipInt = max( mipInt, cubeUV_minMipLevel );
		float faceSize = exp2( mipInt );
		highp vec2 uv = getUV( direction, face ) * ( faceSize - 2.0 ) + 1.0;
		if ( face > 2.0 ) {
			uv.y += faceSize;
			face -= 3.0;
		}
		uv.x += face * faceSize;
		uv.x += filterInt * 3.0 * cubeUV_minTileSize;
		uv.y += 4.0 * ( exp2( CUBEUV_MAX_MIP ) - faceSize );
		uv.x *= CUBEUV_TEXEL_WIDTH;
		uv.y *= CUBEUV_TEXEL_HEIGHT;
		#ifdef texture2DGradEXT
			return texture2DGradEXT( envMap, uv, vec2( 0.0 ), vec2( 0.0 ) ).rgb;
		#else
			return texture2D( envMap, uv ).rgb;
		#endif
	}
	#define cubeUV_r0 1.0
	#define cubeUV_m0 - 2.0
	#define cubeUV_r1 0.8
	#define cubeUV_m1 - 1.0
	#define cubeUV_r4 0.4
	#define cubeUV_m4 2.0
	#define cubeUV_r5 0.305
	#define cubeUV_m5 3.0
	#define cubeUV_r6 0.21
	#define cubeUV_m6 4.0
	float roughnessToMip( float roughness ) {
		float mip = 0.0;
		if ( roughness >= cubeUV_r1 ) {
			mip = ( cubeUV_r0 - roughness ) * ( cubeUV_m1 - cubeUV_m0 ) / ( cubeUV_r0 - cubeUV_r1 ) + cubeUV_m0;
		} else if ( roughness >= cubeUV_r4 ) {
			mip = ( cubeUV_r1 - roughness ) * ( cubeUV_m4 - cubeUV_m1 ) / ( cubeUV_r1 - cubeUV_r4 ) + cubeUV_m1;
		} else if ( roughness >= cubeUV_r5 ) {
			mip = ( cubeUV_r4 - roughness ) * ( cubeUV_m5 - cubeUV_m4 ) / ( cubeUV_r4 - cubeUV_r5 ) + cubeUV_m4;
		} else if ( roughness >= cubeUV_r6 ) {
			mip = ( cubeUV_r5 - roughness ) * ( cubeUV_m6 - cubeUV_m5 ) / ( cubeUV_r5 - cubeUV_r6 ) + cubeUV_m5;
		} else {
			mip = - 2.0 * log2( 1.16 * roughness );		}
		return mip;
	}
	vec4 textureCubeUV( sampler2D envMap, vec3 sampleDir, float roughness ) {
		float mip = clamp( roughnessToMip( roughness ), cubeUV_m0, CUBEUV_MAX_MIP );
		float mipF = fract( mip );
		float mipInt = floor( mip );
		vec3 color0 = bilinearCubeUV( envMap, sampleDir, mipInt );
		if ( mipF == 0.0 ) {
			return vec4( color0, 1.0 );
		} else {
			vec3 color1 = bilinearCubeUV( envMap, sampleDir, mipInt + 1.0 );
			return vec4( mix( color0, color1, mipF ), 1.0 );
		}
	}
#endif`,DU=`vec3 transformedNormal = objectNormal;
#ifdef USE_TANGENT
	vec3 transformedTangent = objectTangent;
#endif
#ifdef USE_BATCHING
	mat3 bm = mat3( batchingMatrix );
	transformedNormal /= vec3( dot( bm[ 0 ], bm[ 0 ] ), dot( bm[ 1 ], bm[ 1 ] ), dot( bm[ 2 ], bm[ 2 ] ) );
	transformedNormal = bm * transformedNormal;
	#ifdef USE_TANGENT
		transformedTangent = bm * transformedTangent;
	#endif
#endif
#ifdef USE_INSTANCING
	mat3 im = mat3( instanceMatrix );
	transformedNormal /= vec3( dot( im[ 0 ], im[ 0 ] ), dot( im[ 1 ], im[ 1 ] ), dot( im[ 2 ], im[ 2 ] ) );
	transformedNormal = im * transformedNormal;
	#ifdef USE_TANGENT
		transformedTangent = im * transformedTangent;
	#endif
#endif
transformedNormal = normalMatrix * transformedNormal;
#ifdef FLIP_SIDED
	transformedNormal = - transformedNormal;
#endif
#ifdef USE_TANGENT
	transformedTangent = ( modelViewMatrix * vec4( transformedTangent, 0.0 ) ).xyz;
	#ifdef FLIP_SIDED
		transformedTangent = - transformedTangent;
	#endif
#endif`,TU=`#ifdef USE_DISPLACEMENTMAP
	uniform sampler2D displacementMap;
	uniform float displacementScale;
	uniform float displacementBias;
#endif`,IU=`#ifdef USE_DISPLACEMENTMAP
	transformed += normalize( objectNormal ) * ( texture2D( displacementMap, vDisplacementMapUv ).x * displacementScale + displacementBias );
#endif`,NU=`#ifdef USE_EMISSIVEMAP
	vec4 emissiveColor = texture2D( emissiveMap, vEmissiveMapUv );
	#ifdef DECODE_VIDEO_TEXTURE_EMISSIVE
		emissiveColor = sRGBTransferEOTF( emissiveColor );
	#endif
	totalEmissiveRadiance *= emissiveColor.rgb;
#endif`,FU=`#ifdef USE_EMISSIVEMAP
	uniform sampler2D emissiveMap;
#endif`,RU="gl_FragColor = linearToOutputTexel( gl_FragColor );",LU=`vec4 LinearTransferOETF( in vec4 value ) {
	return value;
}
vec4 sRGBTransferEOTF( in vec4 value ) {
	return 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 );
}
vec4 sRGBTransferOETF( in vec4 value ) {
	return 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 );
}`,OU=`#ifdef USE_ENVMAP
	#ifdef ENV_WORLDPOS
		vec3 cameraToFrag;
		if ( isOrthographic ) {
			cameraToFrag = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );
		} else {
			cameraToFrag = normalize( vWorldPosition - cameraPosition );
		}
		vec3 worldNormal = inverseTransformDirection( normal, viewMatrix );
		#ifdef ENVMAP_MODE_REFLECTION
			vec3 reflectVec = reflect( cameraToFrag, worldNormal );
		#else
			vec3 reflectVec = refract( cameraToFrag, worldNormal, refractionRatio );
		#endif
	#else
		vec3 reflectVec = vReflect;
	#endif
	#ifdef ENVMAP_TYPE_CUBE
		vec4 envColor = textureCube( envMap, envMapRotation * vec3( flipEnvMap * reflectVec.x, reflectVec.yz ) );
	#else
		vec4 envColor = vec4( 0.0 );
	#endif
	#ifdef ENVMAP_BLENDING_MULTIPLY
		outgoingLight = mix( outgoingLight, outgoingLight * envColor.xyz, specularStrength * reflectivity );
	#elif defined( ENVMAP_BLENDING_MIX )
		outgoingLight = mix( outgoingLight, envColor.xyz, specularStrength * reflectivity );
	#elif defined( ENVMAP_BLENDING_ADD )
		outgoingLight += envColor.xyz * specularStrength * reflectivity;
	#endif
#endif`,zU=`#ifdef USE_ENVMAP
	uniform float envMapIntensity;
	uniform float flipEnvMap;
	uniform mat3 envMapRotation;
	#ifdef ENVMAP_TYPE_CUBE
		uniform samplerCube envMap;
	#else
		uniform sampler2D envMap;
	#endif
#endif`,HU=`#ifdef USE_ENVMAP
	uniform float reflectivity;
	#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( PHONG ) || defined( LAMBERT )
		#define ENV_WORLDPOS
	#endif
	#ifdef ENV_WORLDPOS
		varying vec3 vWorldPosition;
		uniform float refractionRatio;
	#else
		varying vec3 vReflect;
	#endif
#endif`,UU=`#ifdef USE_ENVMAP
	#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( PHONG ) || defined( LAMBERT )
		#define ENV_WORLDPOS
	#endif
	#ifdef ENV_WORLDPOS
		
		varying vec3 vWorldPosition;
	#else
		varying vec3 vReflect;
		uniform float refractionRatio;
	#endif
#endif`,kU=`#ifdef USE_ENVMAP
	#ifdef ENV_WORLDPOS
		vWorldPosition = worldPosition.xyz;
	#else
		vec3 cameraToVertex;
		if ( isOrthographic ) {
			cameraToVertex = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );
		} else {
			cameraToVertex = normalize( worldPosition.xyz - cameraPosition );
		}
		vec3 worldNormal = inverseTransformDirection( transformedNormal, viewMatrix );
		#ifdef ENVMAP_MODE_REFLECTION
			vReflect = reflect( cameraToVertex, worldNormal );
		#else
			vReflect = refract( cameraToVertex, worldNormal, refractionRatio );
		#endif
	#endif
#endif`,VU=`#ifdef USE_FOG
	vFogDepth = - mvPosition.z;
#endif`,jU=`#ifdef USE_FOG
	varying float vFogDepth;
#endif`,XU=`#ifdef USE_FOG
	#ifdef FOG_EXP2
		float fogFactor = 1.0 - exp( - fogDensity * fogDensity * vFogDepth * vFogDepth );
	#else
		float fogFactor = smoothstep( fogNear, fogFar, vFogDepth );
	#endif
	gl_FragColor.rgb = mix( gl_FragColor.rgb, fogColor, fogFactor );
#endif`,GU=`#ifdef USE_FOG
	uniform vec3 fogColor;
	varying float vFogDepth;
	#ifdef FOG_EXP2
		uniform float fogDensity;
	#else
		uniform float fogNear;
		uniform float fogFar;
	#endif
#endif`,WU=`#ifdef USE_GRADIENTMAP
	uniform sampler2D gradientMap;
#endif
vec3 getGradientIrradiance( vec3 normal, vec3 lightDirection ) {
	float dotNL = dot( normal, lightDirection );
	vec2 coord = vec2( dotNL * 0.5 + 0.5, 0.0 );
	#ifdef USE_GRADIENTMAP
		return vec3( texture2D( gradientMap, coord ).r );
	#else
		vec2 fw = fwidth( coord ) * 0.5;
		return mix( vec3( 0.7 ), vec3( 1.0 ), smoothstep( 0.7 - fw.x, 0.7 + fw.x, coord.x ) );
	#endif
}`,QU=`#ifdef USE_LIGHTMAP
	uniform sampler2D lightMap;
	uniform float lightMapIntensity;
#endif`,ZU=`LambertMaterial material;
material.diffuseColor = diffuseColor.rgb;
material.specularStrength = specularStrength;`,YU=`varying vec3 vViewPosition;
struct LambertMaterial {
	vec3 diffuseColor;
	float specularStrength;
};
void 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 ) {
	float dotNL = saturate( dot( geometryNormal, directLight.direction ) );
	vec3 irradiance = dotNL * directLight.color;
	reflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );
}
void 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 ) {
	reflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );
}
#define RE_Direct				RE_Direct_Lambert
#define RE_IndirectDiffuse		RE_IndirectDiffuse_Lambert`,JU=`uniform bool receiveShadow;
uniform vec3 ambientLightColor;
#if defined( USE_LIGHT_PROBES )
	uniform vec3 lightProbe[ 9 ];
#endif
vec3 shGetIrradianceAt( in vec3 normal, in vec3 shCoefficients[ 9 ] ) {
	float x = normal.x, y = normal.y, z = normal.z;
	vec3 result = shCoefficients[ 0 ] * 0.886227;
	result += shCoefficients[ 1 ] * 2.0 * 0.511664 * y;
	result += shCoefficients[ 2 ] * 2.0 * 0.511664 * z;
	result += shCoefficients[ 3 ] * 2.0 * 0.511664 * x;
	result += shCoefficients[ 4 ] * 2.0 * 0.429043 * x * y;
	result += shCoefficients[ 5 ] * 2.0 * 0.429043 * y * z;
	result += shCoefficients[ 6 ] * ( 0.743125 * z * z - 0.247708 );
	result += shCoefficients[ 7 ] * 2.0 * 0.429043 * x * z;
	result += shCoefficients[ 8 ] * 0.429043 * ( x * x - y * y );
	return result;
}
vec3 getLightProbeIrradiance( const in vec3 lightProbe[ 9 ], const in vec3 normal ) {
	vec3 worldNormal = inverseTransformDirection( normal, viewMatrix );
	vec3 irradiance = shGetIrradianceAt( worldNormal, lightProbe );
	return irradiance;
}
vec3 getAmbientLightIrradiance( const in vec3 ambientLightColor ) {
	vec3 irradiance = ambientLightColor;
	return irradiance;
}
float getDistanceAttenuation( const in float lightDistance, const in float cutoffDistance, const in float decayExponent ) {
	float distanceFalloff = 1.0 / max( pow( lightDistance, decayExponent ), 0.01 );
	if ( cutoffDistance > 0.0 ) {
		distanceFalloff *= pow2( saturate( 1.0 - pow4( lightDistance / cutoffDistance ) ) );
	}
	return distanceFalloff;
}
float getSpotAttenuation( const in float coneCosine, const in float penumbraCosine, const in float angleCosine ) {
	return smoothstep( coneCosine, penumbraCosine, angleCosine );
}
#if NUM_DIR_LIGHTS > 0
	struct DirectionalLight {
		vec3 direction;
		vec3 color;
	};
	uniform DirectionalLight directionalLights[ NUM_DIR_LIGHTS ];
	void getDirectionalLightInfo( const in DirectionalLight directionalLight, out IncidentLight light ) {
		light.color = directionalLight.color;
		light.direction = directionalLight.direction;
		light.visible = true;
	}
#endif
#if NUM_POINT_LIGHTS > 0
	struct PointLight {
		vec3 position;
		vec3 color;
		float distance;
		float decay;
	};
	uniform PointLight pointLights[ NUM_POINT_LIGHTS ];
	void getPointLightInfo( const in PointLight pointLight, const in vec3 geometryPosition, out IncidentLight light ) {
		vec3 lVector = pointLight.position - geometryPosition;
		light.direction = normalize( lVector );
		float lightDistance = length( lVector );
		light.color = pointLight.color;
		light.color *= getDistanceAttenuation( lightDistance, pointLight.distance, pointLight.decay );
		light.visible = ( light.color != vec3( 0.0 ) );
	}
#endif
#if NUM_SPOT_LIGHTS > 0
	struct SpotLight {
		vec3 position;
		vec3 direction;
		vec3 color;
		float distance;
		float decay;
		float coneCos;
		float penumbraCos;
	};
	uniform SpotLight spotLights[ NUM_SPOT_LIGHTS ];
	void getSpotLightInfo( const in SpotLight spotLight, const in vec3 geometryPosition, out IncidentLight light ) {
		vec3 lVector = spotLight.position - geometryPosition;
		light.direction = normalize( lVector );
		float angleCos = dot( light.direction, spotLight.direction );
		float spotAttenuation = getSpotAttenuation( spotLight.coneCos, spotLight.penumbraCos, angleCos );
		if ( spotAttenuation > 0.0 ) {
			float lightDistance = length( lVector );
			light.color = spotLight.color * spotAttenuation;
			light.color *= getDistanceAttenuation( lightDistance, spotLight.distance, spotLight.decay );
			light.visible = ( light.color != vec3( 0.0 ) );
		} else {
			light.color = vec3( 0.0 );
			light.visible = false;
		}
	}
#endif
#if NUM_RECT_AREA_LIGHTS > 0
	struct RectAreaLight {
		vec3 color;
		vec3 position;
		vec3 halfWidth;
		vec3 halfHeight;
	};
	uniform sampler2D ltc_1;	uniform sampler2D ltc_2;
	uniform RectAreaLight rectAreaLights[ NUM_RECT_AREA_LIGHTS ];
#endif
#if NUM_HEMI_LIGHTS > 0
	struct HemisphereLight {
		vec3 direction;
		vec3 skyColor;
		vec3 groundColor;
	};
	uniform HemisphereLight hemisphereLights[ NUM_HEMI_LIGHTS ];
	vec3 getHemisphereLightIrradiance( const in HemisphereLight hemiLight, const in vec3 normal ) {
		float dotNL = dot( normal, hemiLight.direction );
		float hemiDiffuseWeight = 0.5 * dotNL + 0.5;
		vec3 irradiance = mix( hemiLight.groundColor, hemiLight.skyColor, hemiDiffuseWeight );
		return irradiance;
	}
#endif`,KU=`#ifdef USE_ENVMAP
	vec3 getIBLIrradiance( const in vec3 normal ) {
		#ifdef ENVMAP_TYPE_CUBE_UV
			vec3 worldNormal = inverseTransformDirection( normal, viewMatrix );
			vec4 envMapColor = textureCubeUV( envMap, envMapRotation * worldNormal, 1.0 );
			return PI * envMapColor.rgb * envMapIntensity;
		#else
			return vec3( 0.0 );
		#endif
	}
	vec3 getIBLRadiance( const in vec3 viewDir, const in vec3 normal, const in float roughness ) {
		#ifdef ENVMAP_TYPE_CUBE_UV
			vec3 reflectVec = reflect( - viewDir, normal );
			reflectVec = normalize( mix( reflectVec, normal, pow4( roughness ) ) );
			reflectVec = inverseTransformDirection( reflectVec, viewMatrix );
			vec4 envMapColor = textureCubeUV( envMap, envMapRotation * reflectVec, roughness );
			return envMapColor.rgb * envMapIntensity;
		#else
			return vec3( 0.0 );
		#endif
	}
	#ifdef USE_ANISOTROPY
		vec3 getIBLAnisotropyRadiance( const in vec3 viewDir, const in vec3 normal, const in float roughness, const in vec3 bitangent, const in float anisotropy ) {
			#ifdef ENVMAP_TYPE_CUBE_UV
				vec3 bentNormal = cross( bitangent, viewDir );
				bentNormal = normalize( cross( bentNormal, bitangent ) );
				bentNormal = normalize( mix( bentNormal, normal, pow2( pow2( 1.0 - anisotropy * ( 1.0 - roughness ) ) ) ) );
				return getIBLRadiance( viewDir, bentNormal, roughness );
			#else
				return vec3( 0.0 );
			#endif
		}
	#endif
#endif`,qU=`ToonMaterial material;
material.diffuseColor = diffuseColor.rgb;`,_U=`varying vec3 vViewPosition;
struct ToonMaterial {
	vec3 diffuseColor;
};
void 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 ) {
	vec3 irradiance = getGradientIrradiance( geometryNormal, directLight.direction ) * directLight.color;
	reflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );
}
void 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 ) {
	reflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );
}
#define RE_Direct				RE_Direct_Toon
#define RE_IndirectDiffuse		RE_IndirectDiffuse_Toon`,$U=`BlinnPhongMaterial material;
material.diffuseColor = diffuseColor.rgb;
material.specularColor = specular;
material.specularShininess = shininess;
material.specularStrength = specularStrength;`,ek=`varying vec3 vViewPosition;
struct BlinnPhongMaterial {
	vec3 diffuseColor;
	vec3 specularColor;
	float specularShininess;
	float specularStrength;
};
void 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 ) {
	float dotNL = saturate( dot( geometryNormal, directLight.direction ) );
	vec3 irradiance = dotNL * directLight.color;
	reflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );
	reflectedLight.directSpecular += irradiance * BRDF_BlinnPhong( directLight.direction, geometryViewDir, geometryNormal, material.specularColor, material.specularShininess ) * material.specularStrength;
}
void 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 ) {
	reflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );
}
#define RE_Direct				RE_Direct_BlinnPhong
#define RE_IndirectDiffuse		RE_IndirectDiffuse_BlinnPhong`,tk=`PhysicalMaterial material;
material.diffuseColor = diffuseColor.rgb;
material.diffuseContribution = diffuseColor.rgb * ( 1.0 - metalnessFactor );
material.metalness = metalnessFactor;
vec3 dxy = max( abs( dFdx( nonPerturbedNormal ) ), abs( dFdy( nonPerturbedNormal ) ) );
float geometryRoughness = max( max( dxy.x, dxy.y ), dxy.z );
material.roughness = max( roughnessFactor, 0.0525 );material.roughness += geometryRoughness;
material.roughness = min( material.roughness, 1.0 );
#ifdef IOR
	material.ior = ior;
	#ifdef USE_SPECULAR
		float specularIntensityFactor = specularIntensity;
		vec3 specularColorFactor = specularColor;
		#ifdef USE_SPECULAR_COLORMAP
			specularColorFactor *= texture2D( specularColorMap, vSpecularColorMapUv ).rgb;
		#endif
		#ifdef USE_SPECULAR_INTENSITYMAP
			specularIntensityFactor *= texture2D( specularIntensityMap, vSpecularIntensityMapUv ).a;
		#endif
		material.specularF90 = mix( specularIntensityFactor, 1.0, metalnessFactor );
	#else
		float specularIntensityFactor = 1.0;
		vec3 specularColorFactor = vec3( 1.0 );
		material.specularF90 = 1.0;
	#endif
	material.specularColor = min( pow2( ( material.ior - 1.0 ) / ( material.ior + 1.0 ) ) * specularColorFactor, vec3( 1.0 ) ) * specularIntensityFactor;
	material.specularColorBlended = mix( material.specularColor, diffuseColor.rgb, metalnessFactor );
#else
	material.specularColor = vec3( 0.04 );
	material.specularColorBlended = mix( material.specularColor, diffuseColor.rgb, metalnessFactor );
	material.specularF90 = 1.0;
#endif
#ifdef USE_CLEARCOAT
	material.clearcoat = clearcoat;
	material.clearcoatRoughness = clearcoatRoughness;
	material.clearcoatF0 = vec3( 0.04 );
	material.clearcoatF90 = 1.0;
	#ifdef USE_CLEARCOATMAP
		material.clearcoat *= texture2D( clearcoatMap, vClearcoatMapUv ).x;
	#endif
	#ifdef USE_CLEARCOAT_ROUGHNESSMAP
		material.clearcoatRoughness *= texture2D( clearcoatRoughnessMap, vClearcoatRoughnessMapUv ).y;
	#endif
	material.clearcoat = saturate( material.clearcoat );	material.clearcoatRoughness = max( material.clearcoatRoughness, 0.0525 );
	material.clearcoatRoughness += geometryRoughness;
	material.clearcoatRoughness = min( material.clearcoatRoughness, 1.0 );
#endif
#ifdef USE_DISPERSION
	material.dispersion = dispersion;
#endif
#ifdef USE_IRIDESCENCE
	material.iridescence = iridescence;
	material.iridescenceIOR = iridescenceIOR;
	#ifdef USE_IRIDESCENCEMAP
		material.iridescence *= texture2D( iridescenceMap, vIridescenceMapUv ).r;
	#endif
	#ifdef USE_IRIDESCENCE_THICKNESSMAP
		material.iridescenceThickness = (iridescenceThicknessMaximum - iridescenceThicknessMinimum) * texture2D( iridescenceThicknessMap, vIridescenceThicknessMapUv ).g + iridescenceThicknessMinimum;
	#else
		material.iridescenceThickness = iridescenceThicknessMaximum;
	#endif
#endif
#ifdef USE_SHEEN
	material.sheenColor = sheenColor;
	#ifdef USE_SHEEN_COLORMAP
		material.sheenColor *= texture2D( sheenColorMap, vSheenColorMapUv ).rgb;
	#endif
	material.sheenRoughness = clamp( sheenRoughness, 0.0001, 1.0 );
	#ifdef USE_SHEEN_ROUGHNESSMAP
		material.sheenRoughness *= texture2D( sheenRoughnessMap, vSheenRoughnessMapUv ).a;
	#endif
#endif
#ifdef USE_ANISOTROPY
	#ifdef USE_ANISOTROPYMAP
		mat2 anisotropyMat = mat2( anisotropyVector.x, anisotropyVector.y, - anisotropyVector.y, anisotropyVector.x );
		vec3 anisotropyPolar = texture2D( anisotropyMap, vAnisotropyMapUv ).rgb;
		vec2 anisotropyV = anisotropyMat * normalize( 2.0 * anisotropyPolar.rg - vec2( 1.0 ) ) * anisotropyPolar.b;
	#else
		vec2 anisotropyV = anisotropyVector;
	#endif
	material.anisotropy = length( anisotropyV );
	if( material.anisotropy == 0.0 ) {
		anisotropyV = vec2( 1.0, 0.0 );
	} else {
		anisotropyV /= material.anisotropy;
		material.anisotropy = saturate( material.anisotropy );
	}
	material.alphaT = mix( pow2( material.roughness ), 1.0, pow2( material.anisotropy ) );
	material.anisotropyT = tbn[ 0 ] * anisotropyV.x + tbn[ 1 ] * anisotropyV.y;
	material.anisotropyB = tbn[ 1 ] * anisotropyV.x - tbn[ 0 ] * anisotropyV.y;
#endif`,nk=`uniform sampler2D dfgLUT;
struct PhysicalMaterial {
	vec3 diffuseColor;
	vec3 diffuseContribution;
	vec3 specularColor;
	vec3 specularColorBlended;
	float roughness;
	float metalness;
	float specularF90;
	float dispersion;
	#ifdef USE_CLEARCOAT
		float clearcoat;
		float clearcoatRoughness;
		vec3 clearcoatF0;
		float clearcoatF90;
	#endif
	#ifdef USE_IRIDESCENCE
		float iridescence;
		float iridescenceIOR;
		float iridescenceThickness;
		vec3 iridescenceFresnel;
		vec3 iridescenceF0;
		vec3 iridescenceFresnelDielectric;
		vec3 iridescenceFresnelMetallic;
	#endif
	#ifdef USE_SHEEN
		vec3 sheenColor;
		float sheenRoughness;
	#endif
	#ifdef IOR
		float ior;
	#endif
	#ifdef USE_TRANSMISSION
		float transmission;
		float transmissionAlpha;
		float thickness;
		float attenuationDistance;
		vec3 attenuationColor;
	#endif
	#ifdef USE_ANISOTROPY
		float anisotropy;
		float alphaT;
		vec3 anisotropyT;
		vec3 anisotropyB;
	#endif
};
vec3 clearcoatSpecularDirect = vec3( 0.0 );
vec3 clearcoatSpecularIndirect = vec3( 0.0 );
vec3 sheenSpecularDirect = vec3( 0.0 );
vec3 sheenSpecularIndirect = vec3(0.0 );
vec3 Schlick_to_F0( const in vec3 f, const in float f90, const in float dotVH ) {
    float x = clamp( 1.0 - dotVH, 0.0, 1.0 );
    float x2 = x * x;
    float x5 = clamp( x * x2 * x2, 0.0, 0.9999 );
    return ( f - vec3( f90 ) * x5 ) / ( 1.0 - x5 );
}
float V_GGX_SmithCorrelated( const in float alpha, const in float dotNL, const in float dotNV ) {
	float a2 = pow2( alpha );
	float gv = dotNL * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNV ) );
	float gl = dotNV * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNL ) );
	return 0.5 / max( gv + gl, EPSILON );
}
float D_GGX( const in float alpha, const in float dotNH ) {
	float a2 = pow2( alpha );
	float denom = pow2( dotNH ) * ( a2 - 1.0 ) + 1.0;
	return RECIPROCAL_PI * a2 / pow2( denom );
}
#ifdef USE_ANISOTROPY
	float 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 ) {
		float gv = dotNL * length( vec3( alphaT * dotTV, alphaB * dotBV, dotNV ) );
		float gl = dotNV * length( vec3( alphaT * dotTL, alphaB * dotBL, dotNL ) );
		float v = 0.5 / ( gv + gl );
		return v;
	}
	float D_GGX_Anisotropic( const in float alphaT, const in float alphaB, const in float dotNH, const in float dotTH, const in float dotBH ) {
		float a2 = alphaT * alphaB;
		highp vec3 v = vec3( alphaB * dotTH, alphaT * dotBH, a2 * dotNH );
		highp float v2 = dot( v, v );
		float w2 = a2 / v2;
		return RECIPROCAL_PI * a2 * pow2 ( w2 );
	}
#endif
#ifdef USE_CLEARCOAT
	vec3 BRDF_GGX_Clearcoat( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in PhysicalMaterial material) {
		vec3 f0 = material.clearcoatF0;
		float f90 = material.clearcoatF90;
		float roughness = material.clearcoatRoughness;
		float alpha = pow2( roughness );
		vec3 halfDir = normalize( lightDir + viewDir );
		float dotNL = saturate( dot( normal, lightDir ) );
		float dotNV = saturate( dot( normal, viewDir ) );
		float dotNH = saturate( dot( normal, halfDir ) );
		float dotVH = saturate( dot( viewDir, halfDir ) );
		vec3 F = F_Schlick( f0, f90, dotVH );
		float V = V_GGX_SmithCorrelated( alpha, dotNL, dotNV );
		float D = D_GGX( alpha, dotNH );
		return F * ( V * D );
	}
#endif
vec3 BRDF_GGX( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in PhysicalMaterial material ) {
	vec3 f0 = material.specularColorBlended;
	float f90 = material.specularF90;
	float roughness = material.roughness;
	float alpha = pow2( roughness );
	vec3 halfDir = normalize( lightDir + viewDir );
	float dotNL = saturate( dot( normal, lightDir ) );
	float dotNV = saturate( dot( normal, viewDir ) );
	float dotNH = saturate( dot( normal, halfDir ) );
	float dotVH = saturate( dot( viewDir, halfDir ) );
	vec3 F = F_Schlick( f0, f90, dotVH );
	#ifdef USE_IRIDESCENCE
		F = mix( F, material.iridescenceFresnel, material.iridescence );
	#endif
	#ifdef USE_ANISOTROPY
		float dotTL = dot( material.anisotropyT, lightDir );
		float dotTV = dot( material.anisotropyT, viewDir );
		float dotTH = dot( material.anisotropyT, halfDir );
		float dotBL = dot( material.anisotropyB, lightDir );
		float dotBV = dot( material.anisotropyB, viewDir );
		float dotBH = dot( material.anisotropyB, halfDir );
		float V = V_GGX_SmithCorrelated_Anisotropic( material.alphaT, alpha, dotTV, dotBV, dotTL, dotBL, dotNV, dotNL );
		float D = D_GGX_Anisotropic( material.alphaT, alpha, dotNH, dotTH, dotBH );
	#else
		float V = V_GGX_SmithCorrelated( alpha, dotNL, dotNV );
		float D = D_GGX( alpha, dotNH );
	#endif
	return F * ( V * D );
}
vec2 LTC_Uv( const in vec3 N, const in vec3 V, const in float roughness ) {
	const float LUT_SIZE = 64.0;
	const float LUT_SCALE = ( LUT_SIZE - 1.0 ) / LUT_SIZE;
	const float LUT_BIAS = 0.5 / LUT_SIZE;
	float dotNV = saturate( dot( N, V ) );
	vec2 uv = vec2( roughness, sqrt( 1.0 - dotNV ) );
	uv = uv * LUT_SCALE + LUT_BIAS;
	return uv;
}
float LTC_ClippedSphereFormFactor( const in vec3 f ) {
	float l = length( f );
	return max( ( l * l + f.z ) / ( l + 1.0 ), 0.0 );
}
vec3 LTC_EdgeVectorFormFactor( const in vec3 v1, const in vec3 v2 ) {
	float x = dot( v1, v2 );
	float y = abs( x );
	float a = 0.8543985 + ( 0.4965155 + 0.0145206 * y ) * y;
	float b = 3.4175940 + ( 4.1616724 + y ) * y;
	float v = a / b;
	float theta_sintheta = ( x > 0.0 ) ? v : 0.5 * inversesqrt( max( 1.0 - x * x, 1e-7 ) ) - v;
	return cross( v1, v2 ) * theta_sintheta;
}
vec3 LTC_Evaluate( const in vec3 N, const in vec3 V, const in vec3 P, const in mat3 mInv, const in vec3 rectCoords[ 4 ] ) {
	vec3 v1 = rectCoords[ 1 ] - rectCoords[ 0 ];
	vec3 v2 = rectCoords[ 3 ] - rectCoords[ 0 ];
	vec3 lightNormal = cross( v1, v2 );
	if( dot( lightNormal, P - rectCoords[ 0 ] ) < 0.0 ) return vec3( 0.0 );
	vec3 T1, T2;
	T1 = normalize( V - N * dot( V, N ) );
	T2 = - cross( N, T1 );
	mat3 mat = mInv * transpose( mat3( T1, T2, N ) );
	vec3 coords[ 4 ];
	coords[ 0 ] = mat * ( rectCoords[ 0 ] - P );
	coords[ 1 ] = mat * ( rectCoords[ 1 ] - P );
	coords[ 2 ] = mat * ( rectCoords[ 2 ] - P );
	coords[ 3 ] = mat * ( rectCoords[ 3 ] - P );
	coords[ 0 ] = normalize( coords[ 0 ] );
	coords[ 1 ] = normalize( coords[ 1 ] );
	coords[ 2 ] = normalize( coords[ 2 ] );
	coords[ 3 ] = normalize( coords[ 3 ] );
	vec3 vectorFormFactor = vec3( 0.0 );
	vectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 0 ], coords[ 1 ] );
	vectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 1 ], coords[ 2 ] );
	vectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 2 ], coords[ 3 ] );
	vectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 3 ], coords[ 0 ] );
	float result = LTC_ClippedSphereFormFactor( vectorFormFactor );
	return vec3( result );
}
#if defined( USE_SHEEN )
float D_Charlie( float roughness, float dotNH ) {
	float alpha = pow2( roughness );
	float invAlpha = 1.0 / alpha;
	float cos2h = dotNH * dotNH;
	float sin2h = max( 1.0 - cos2h, 0.0078125 );
	return ( 2.0 + invAlpha ) * pow( sin2h, invAlpha * 0.5 ) / ( 2.0 * PI );
}
float V_Neubelt( float dotNV, float dotNL ) {
	return saturate( 1.0 / ( 4.0 * ( dotNL + dotNV - dotNL * dotNV ) ) );
}
vec3 BRDF_Sheen( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, vec3 sheenColor, const in float sheenRoughness ) {
	vec3 halfDir = normalize( lightDir + viewDir );
	float dotNL = saturate( dot( normal, lightDir ) );
	float dotNV = saturate( dot( normal, viewDir ) );
	float dotNH = saturate( dot( normal, halfDir ) );
	float D = D_Charlie( sheenRoughness, dotNH );
	float V = V_Neubelt( dotNV, dotNL );
	return sheenColor * ( D * V );
}
#endif
float IBLSheenBRDF( const in vec3 normal, const in vec3 viewDir, const in float roughness ) {
	float dotNV = saturate( dot( normal, viewDir ) );
	float r2 = roughness * roughness;
	float rInv = 1.0 / ( roughness + 0.1 );
	float a = -1.9362 + 1.0678 * roughness + 0.4573 * r2 - 0.8469 * rInv;
	float b = -0.6014 + 0.5538 * roughness - 0.4670 * r2 - 0.1255 * rInv;
	float DG = exp( a * dotNV + b );
	return saturate( DG );
}
vec3 EnvironmentBRDF( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness ) {
	float dotNV = saturate( dot( normal, viewDir ) );
	vec2 fab = texture2D( dfgLUT, vec2( roughness, dotNV ) ).rg;
	return specularColor * fab.x + specularF90 * fab.y;
}
#ifdef USE_IRIDESCENCE
void 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 ) {
#else
void 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 ) {
#endif
	float dotNV = saturate( dot( normal, viewDir ) );
	vec2 fab = texture2D( dfgLUT, vec2( roughness, dotNV ) ).rg;
	#ifdef USE_IRIDESCENCE
		vec3 Fr = mix( specularColor, iridescenceF0, iridescence );
	#else
		vec3 Fr = specularColor;
	#endif
	vec3 FssEss = Fr * fab.x + specularF90 * fab.y;
	float Ess = fab.x + fab.y;
	float Ems = 1.0 - Ess;
	vec3 Favg = Fr + ( 1.0 - Fr ) * 0.047619;	vec3 Fms = FssEss * Favg / ( 1.0 - Ems * Favg );
	singleScatter += FssEss;
	multiScatter += Fms * Ems;
}
vec3 BRDF_GGX_Multiscatter( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in PhysicalMaterial material ) {
	vec3 singleScatter = BRDF_GGX( lightDir, viewDir, normal, material );
	float dotNL = saturate( dot( normal, lightDir ) );
	float dotNV = saturate( dot( normal, viewDir ) );
	vec2 dfgV = texture2D( dfgLUT, vec2( material.roughness, dotNV ) ).rg;
	vec2 dfgL = texture2D( dfgLUT, vec2( material.roughness, dotNL ) ).rg;
	vec3 FssEss_V = material.specularColorBlended * dfgV.x + material.specularF90 * dfgV.y;
	vec3 FssEss_L = material.specularColorBlended * dfgL.x + material.specularF90 * dfgL.y;
	float Ess_V = dfgV.x + dfgV.y;
	float Ess_L = dfgL.x + dfgL.y;
	float Ems_V = 1.0 - Ess_V;
	float Ems_L = 1.0 - Ess_L;
	vec3 Favg = material.specularColorBlended + ( 1.0 - material.specularColorBlended ) * 0.047619;
	vec3 Fms = FssEss_V * FssEss_L * Favg / ( 1.0 - Ems_V * Ems_L * Favg + EPSILON );
	float compensationFactor = Ems_V * Ems_L;
	vec3 multiScatter = Fms * compensationFactor;
	return singleScatter + multiScatter;
}
#if NUM_RECT_AREA_LIGHTS > 0
	void 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 ) {
		vec3 normal = geometryNormal;
		vec3 viewDir = geometryViewDir;
		vec3 position = geometryPosition;
		vec3 lightPos = rectAreaLight.position;
		vec3 halfWidth = rectAreaLight.halfWidth;
		vec3 halfHeight = rectAreaLight.halfHeight;
		vec3 lightColor = rectAreaLight.color;
		float roughness = material.roughness;
		vec3 rectCoords[ 4 ];
		rectCoords[ 0 ] = lightPos + halfWidth - halfHeight;		rectCoords[ 1 ] = lightPos - halfWidth - halfHeight;
		rectCoords[ 2 ] = lightPos - halfWidth + halfHeight;
		rectCoords[ 3 ] = lightPos + halfWidth + halfHeight;
		vec2 uv = LTC_Uv( normal, viewDir, roughness );
		vec4 t1 = texture2D( ltc_1, uv );
		vec4 t2 = texture2D( ltc_2, uv );
		mat3 mInv = mat3(
			vec3( t1.x, 0, t1.y ),
			vec3(    0, 1,    0 ),
			vec3( t1.z, 0, t1.w )
		);
		vec3 fresnel = ( material.specularColorBlended * t2.x + ( vec3( 1.0 ) - material.specularColorBlended ) * t2.y );
		reflectedLight.directSpecular += lightColor * fresnel * LTC_Evaluate( normal, viewDir, position, mInv, rectCoords );
		reflectedLight.directDiffuse += lightColor * material.diffuseContribution * LTC_Evaluate( normal, viewDir, position, mat3( 1.0 ), rectCoords );
	}
#endif
void 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 ) {
	float dotNL = saturate( dot( geometryNormal, directLight.direction ) );
	vec3 irradiance = dotNL * directLight.color;
	#ifdef USE_CLEARCOAT
		float dotNLcc = saturate( dot( geometryClearcoatNormal, directLight.direction ) );
		vec3 ccIrradiance = dotNLcc * directLight.color;
		clearcoatSpecularDirect += ccIrradiance * BRDF_GGX_Clearcoat( directLight.direction, geometryViewDir, geometryClearcoatNormal, material );
	#endif
	#ifdef USE_SHEEN
 
 		sheenSpecularDirect += irradiance * BRDF_Sheen( directLight.direction, geometryViewDir, geometryNormal, material.sheenColor, material.sheenRoughness );
 
 		float sheenAlbedoV = IBLSheenBRDF( geometryNormal, geometryViewDir, material.sheenRoughness );
 		float sheenAlbedoL = IBLSheenBRDF( geometryNormal, directLight.direction, material.sheenRoughness );
 
 		float sheenEnergyComp = 1.0 - max3( material.sheenColor ) * max( sheenAlbedoV, sheenAlbedoL );
 
 		irradiance *= sheenEnergyComp;
 
 	#endif
	reflectedLight.directSpecular += irradiance * BRDF_GGX_Multiscatter( directLight.direction, geometryViewDir, geometryNormal, material );
	reflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseContribution );
}
void 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 ) {
	vec3 diffuse = irradiance * BRDF_Lambert( material.diffuseContribution );
	#ifdef USE_SHEEN
		float sheenAlbedo = IBLSheenBRDF( geometryNormal, geometryViewDir, material.sheenRoughness );
		float sheenEnergyComp = 1.0 - max3( material.sheenColor ) * sheenAlbedo;
		diffuse *= sheenEnergyComp;
	#endif
	reflectedLight.indirectDiffuse += diffuse;
}
void 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) {
	#ifdef USE_CLEARCOAT
		clearcoatSpecularIndirect += clearcoatRadiance * EnvironmentBRDF( geometryClearcoatNormal, geometryViewDir, material.clearcoatF0, material.clearcoatF90, material.clearcoatRoughness );
	#endif
	#ifdef USE_SHEEN
		sheenSpecularIndirect += irradiance * material.sheenColor * IBLSheenBRDF( geometryNormal, geometryViewDir, material.sheenRoughness ) * RECIPROCAL_PI;
 	#endif
	vec3 singleScatteringDielectric = vec3( 0.0 );
	vec3 multiScatteringDielectric = vec3( 0.0 );
	vec3 singleScatteringMetallic = vec3( 0.0 );
	vec3 multiScatteringMetallic = vec3( 0.0 );
	#ifdef USE_IRIDESCENCE
		computeMultiscatteringIridescence( geometryNormal, geometryViewDir, material.specularColor, material.specularF90, material.iridescence, material.iridescenceFresnelDielectric, material.roughness, singleScatteringDielectric, multiScatteringDielectric );
		computeMultiscatteringIridescence( geometryNormal, geometryViewDir, material.diffuseColor, material.specularF90, material.iridescence, material.iridescenceFresnelMetallic, material.roughness, singleScatteringMetallic, multiScatteringMetallic );
	#else
		computeMultiscattering( geometryNormal, geometryViewDir, material.specularColor, material.specularF90, material.roughness, singleScatteringDielectric, multiScatteringDielectric );
		computeMultiscattering( geometryNormal, geometryViewDir, material.diffuseColor, material.specularF90, material.roughness, singleScatteringMetallic, multiScatteringMetallic );
	#endif
	vec3 singleScattering = mix( singleScatteringDielectric, singleScatteringMetallic, material.metalness );
	vec3 multiScattering = mix( multiScatteringDielectric, multiScatteringMetallic, material.metalness );
	vec3 totalScatteringDielectric = singleScatteringDielectric + multiScatteringDielectric;
	vec3 diffuse = material.diffuseContribution * ( 1.0 - totalScatteringDielectric );
	vec3 cosineWeightedIrradiance = irradiance * RECIPROCAL_PI;
	vec3 indirectSpecular = radiance * singleScattering;
	indirectSpecular += multiScattering * cosineWeightedIrradiance;
	vec3 indirectDiffuse = diffuse * cosineWeightedIrradiance;
	#ifdef USE_SHEEN
		float sheenAlbedo = IBLSheenBRDF( geometryNormal, geometryViewDir, material.sheenRoughness );
		float sheenEnergyComp = 1.0 - max3( material.sheenColor ) * sheenAlbedo;
		indirectSpecular *= sheenEnergyComp;
		indirectDiffuse *= sheenEnergyComp;
	#endif
	reflectedLight.indirectSpecular += indirectSpecular;
	reflectedLight.indirectDiffuse += indirectDiffuse;
}
#define RE_Direct				RE_Direct_Physical
#define RE_Direct_RectArea		RE_Direct_RectArea_Physical
#define RE_IndirectDiffuse		RE_IndirectDiffuse_Physical
#define RE_IndirectSpecular		RE_IndirectSpecular_Physical
float computeSpecularOcclusion( const in float dotNV, const in float ambientOcclusion, const in float roughness ) {
	return saturate( pow( dotNV + ambientOcclusion, exp2( - 16.0 * roughness - 1.0 ) ) - 1.0 + ambientOcclusion );
}`,rk=`
vec3 geometryPosition = - vViewPosition;
vec3 geometryNormal = normal;
vec3 geometryViewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( vViewPosition );
vec3 geometryClearcoatNormal = vec3( 0.0 );
#ifdef USE_CLEARCOAT
	geometryClearcoatNormal = clearcoatNormal;
#endif
#ifdef USE_IRIDESCENCE
	float dotNVi = saturate( dot( normal, geometryViewDir ) );
	if ( material.iridescenceThickness == 0.0 ) {
		material.iridescence = 0.0;
	} else {
		material.iridescence = saturate( material.iridescence );
	}
	if ( material.iridescence > 0.0 ) {
		material.iridescenceFresnelDielectric = evalIridescence( 1.0, material.iridescenceIOR, dotNVi, material.iridescenceThickness, material.specularColor );
		material.iridescenceFresnelMetallic = evalIridescence( 1.0, material.iridescenceIOR, dotNVi, material.iridescenceThickness, material.diffuseColor );
		material.iridescenceFresnel = mix( material.iridescenceFresnelDielectric, material.iridescenceFresnelMetallic, material.metalness );
		material.iridescenceF0 = Schlick_to_F0( material.iridescenceFresnel, 1.0, dotNVi );
	}
#endif
IncidentLight directLight;
#if ( NUM_POINT_LIGHTS > 0 ) && defined( RE_Direct )
	PointLight pointLight;
	#if defined( USE_SHADOWMAP ) && NUM_POINT_LIGHT_SHADOWS > 0
	PointLightShadow pointLightShadow;
	#endif
	#pragma unroll_loop_start
	for ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {
		pointLight = pointLights[ i ];
		getPointLightInfo( pointLight, geometryPosition, directLight );
		#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_POINT_LIGHT_SHADOWS ) && ( defined( SHADOWMAP_TYPE_PCF ) || defined( SHADOWMAP_TYPE_BASIC ) )
		pointLightShadow = pointLightShadows[ i ];
		directLight.color *= ( directLight.visible && receiveShadow ) ? getPointShadow( pointShadowMap[ i ], pointLightShadow.shadowMapSize, pointLightShadow.shadowIntensity, pointLightShadow.shadowBias, pointLightShadow.shadowRadius, vPointShadowCoord[ i ], pointLightShadow.shadowCameraNear, pointLightShadow.shadowCameraFar ) : 1.0;
		#endif
		RE_Direct( directLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );
	}
	#pragma unroll_loop_end
#endif
#if ( NUM_SPOT_LIGHTS > 0 ) && defined( RE_Direct )
	SpotLight spotLight;
	vec4 spotColor;
	vec3 spotLightCoord;
	bool inSpotLightMap;
	#if defined( USE_SHADOWMAP ) && NUM_SPOT_LIGHT_SHADOWS > 0
	SpotLightShadow spotLightShadow;
	#endif
	#pragma unroll_loop_start
	for ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {
		spotLight = spotLights[ i ];
		getSpotLightInfo( spotLight, geometryPosition, directLight );
		#if ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS_WITH_MAPS )
		#define SPOT_LIGHT_MAP_INDEX UNROLLED_LOOP_INDEX
		#elif ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )
		#define SPOT_LIGHT_MAP_INDEX NUM_SPOT_LIGHT_MAPS
		#else
		#define SPOT_LIGHT_MAP_INDEX ( UNROLLED_LOOP_INDEX - NUM_SPOT_LIGHT_SHADOWS + NUM_SPOT_LIGHT_SHADOWS_WITH_MAPS )
		#endif
		#if ( SPOT_LIGHT_MAP_INDEX < NUM_SPOT_LIGHT_MAPS )
			spotLightCoord = vSpotLightCoord[ i ].xyz / vSpotLightCoord[ i ].w;
			inSpotLightMap = all( lessThan( abs( spotLightCoord * 2. - 1. ), vec3( 1.0 ) ) );
			spotColor = texture2D( spotLightMap[ SPOT_LIGHT_MAP_INDEX ], spotLightCoord.xy );
			directLight.color = inSpotLightMap ? directLight.color * spotColor.rgb : directLight.color;
		#endif
		#undef SPOT_LIGHT_MAP_INDEX
		#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )
		spotLightShadow = spotLightShadows[ i ];
		directLight.color *= ( directLight.visible && receiveShadow ) ? getShadow( spotShadowMap[ i ], spotLightShadow.shadowMapSize, spotLightShadow.shadowIntensity, spotLightShadow.shadowBias, spotLightShadow.shadowRadius, vSpotLightCoord[ i ] ) : 1.0;
		#endif
		RE_Direct( directLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );
	}
	#pragma unroll_loop_end
#endif
#if ( NUM_DIR_LIGHTS > 0 ) && defined( RE_Direct )
	DirectionalLight directionalLight;
	#if defined( USE_SHADOWMAP ) && NUM_DIR_LIGHT_SHADOWS > 0
	DirectionalLightShadow directionalLightShadow;
	#endif
	#pragma unroll_loop_start
	for ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {
		directionalLight = directionalLights[ i ];
		getDirectionalLightInfo( directionalLight, directLight );
		#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_DIR_LIGHT_SHADOWS )
		directionalLightShadow = directionalLightShadows[ i ];
		directLight.color *= ( directLight.visible && receiveShadow ) ? getShadow( directionalShadowMap[ i ], directionalLightShadow.shadowMapSize, directionalLightShadow.shadowIntensity, directionalLightShadow.shadowBias, directionalLightShadow.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;
		#endif
		RE_Direct( directLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );
	}
	#pragma unroll_loop_end
#endif
#if ( NUM_RECT_AREA_LIGHTS > 0 ) && defined( RE_Direct_RectArea )
	RectAreaLight rectAreaLight;
	#pragma unroll_loop_start
	for ( int i = 0; i < NUM_RECT_AREA_LIGHTS; i ++ ) {
		rectAreaLight = rectAreaLights[ i ];
		RE_Direct_RectArea( rectAreaLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );
	}
	#pragma unroll_loop_end
#endif
#if defined( RE_IndirectDiffuse )
	vec3 iblIrradiance = vec3( 0.0 );
	vec3 irradiance = getAmbientLightIrradiance( ambientLightColor );
	#if defined( USE_LIGHT_PROBES )
		irradiance += getLightProbeIrradiance( lightProbe, geometryNormal );
	#endif
	#if ( NUM_HEMI_LIGHTS > 0 )
		#pragma unroll_loop_start
		for ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {
			irradiance += getHemisphereLightIrradiance( hemisphereLights[ i ], geometryNormal );
		}
		#pragma unroll_loop_end
	#endif
#endif
#if defined( RE_IndirectSpecular )
	vec3 radiance = vec3( 0.0 );
	vec3 clearcoatRadiance = vec3( 0.0 );
#endif`,ik=`#if defined( RE_IndirectDiffuse )
	#ifdef USE_LIGHTMAP
		vec4 lightMapTexel = texture2D( lightMap, vLightMapUv );
		vec3 lightMapIrradiance = lightMapTexel.rgb * lightMapIntensity;
		irradiance += lightMapIrradiance;
	#endif
	#if defined( USE_ENVMAP ) && defined( STANDARD ) && defined( ENVMAP_TYPE_CUBE_UV )
		iblIrradiance += getIBLIrradiance( geometryNormal );
	#endif
#endif
#if defined( USE_ENVMAP ) && defined( RE_IndirectSpecular )
	#ifdef USE_ANISOTROPY
		radiance += getIBLAnisotropyRadiance( geometryViewDir, geometryNormal, material.roughness, material.anisotropyB, material.anisotropy );
	#else
		radiance += getIBLRadiance( geometryViewDir, geometryNormal, material.roughness );
	#endif
	#ifdef USE_CLEARCOAT
		clearcoatRadiance += getIBLRadiance( geometryViewDir, geometryClearcoatNormal, material.clearcoatRoughness );
	#endif
#endif`,sk=`#if defined( RE_IndirectDiffuse )
	RE_IndirectDiffuse( irradiance, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );
#endif
#if defined( RE_IndirectSpecular )
	RE_IndirectSpecular( radiance, iblIrradiance, clearcoatRadiance, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );
#endif`,ak=`#if defined( USE_LOGARITHMIC_DEPTH_BUFFER )
	gl_FragDepth = vIsPerspective == 0.0 ? gl_FragCoord.z : log2( vFragDepth ) * logDepthBufFC * 0.5;
#endif`,ok=`#if defined( USE_LOGARITHMIC_DEPTH_BUFFER )
	uniform float logDepthBufFC;
	varying float vFragDepth;
	varying float vIsPerspective;
#endif`,lk=`#ifdef USE_LOGARITHMIC_DEPTH_BUFFER
	varying float vFragDepth;
	varying float vIsPerspective;
#endif`,uk=`#ifdef USE_LOGARITHMIC_DEPTH_BUFFER
	vFragDepth = 1.0 + gl_Position.w;
	vIsPerspective = float( isPerspectiveMatrix( projectionMatrix ) );
#endif`,ck=`#ifdef USE_MAP
	vec4 sampledDiffuseColor = texture2D( map, vMapUv );
	#ifdef DECODE_VIDEO_TEXTURE
		sampledDiffuseColor = sRGBTransferEOTF( sampledDiffuseColor );
	#endif
	diffuseColor *= sampledDiffuseColor;
#endif`,dk=`#ifdef USE_MAP
	uniform sampler2D map;
#endif`,fk=`#if defined( USE_MAP ) || defined( USE_ALPHAMAP )
	#if defined( USE_POINTS_UV )
		vec2 uv = vUv;
	#else
		vec2 uv = ( uvTransform * vec3( gl_PointCoord.x, 1.0 - gl_PointCoord.y, 1 ) ).xy;
	#endif
#endif
#ifdef USE_MAP
	diffuseColor *= texture2D( map, uv );
#endif
#ifdef USE_ALPHAMAP
	diffuseColor.a *= texture2D( alphaMap, uv ).g;
#endif`,hk=`#if defined( USE_POINTS_UV )
	varying vec2 vUv;
#else
	#if defined( USE_MAP ) || defined( USE_ALPHAMAP )
		uniform mat3 uvTransform;
	#endif
#endif
#ifdef USE_MAP
	uniform sampler2D map;
#endif
#ifdef USE_ALPHAMAP
	uniform sampler2D alphaMap;
#endif`,pk=`float metalnessFactor = metalness;
#ifdef USE_METALNESSMAP
	vec4 texelMetalness = texture2D( metalnessMap, vMetalnessMapUv );
	metalnessFactor *= texelMetalness.b;
#endif`,mk=`#ifdef USE_METALNESSMAP
	uniform sampler2D metalnessMap;
#endif`,gk=`#ifdef USE_INSTANCING_MORPH
	float morphTargetInfluences[ MORPHTARGETS_COUNT ];
	float morphTargetBaseInfluence = texelFetch( morphTexture, ivec2( 0, gl_InstanceID ), 0 ).r;
	for ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {
		morphTargetInfluences[i] =  texelFetch( morphTexture, ivec2( i + 1, gl_InstanceID ), 0 ).r;
	}
#endif`,vk=`#if defined( USE_MORPHCOLORS )
	vColor *= morphTargetBaseInfluence;
	for ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {
		#if defined( USE_COLOR_ALPHA )
			if ( morphTargetInfluences[ i ] != 0.0 ) vColor += getMorph( gl_VertexID, i, 2 ) * morphTargetInfluences[ i ];
		#elif defined( USE_COLOR )
			if ( morphTargetInfluences[ i ] != 0.0 ) vColor += getMorph( gl_VertexID, i, 2 ).rgb * morphTargetInfluences[ i ];
		#endif
	}
#endif`,Ak=`#ifdef USE_MORPHNORMALS
	objectNormal *= morphTargetBaseInfluence;
	for ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {
		if ( morphTargetInfluences[ i ] != 0.0 ) objectNormal += getMorph( gl_VertexID, i, 1 ).xyz * morphTargetInfluences[ i ];
	}
#endif`,xk=`#ifdef USE_MORPHTARGETS
	#ifndef USE_INSTANCING_MORPH
		uniform float morphTargetBaseInfluence;
		uniform float morphTargetInfluences[ MORPHTARGETS_COUNT ];
	#endif
	uniform sampler2DArray morphTargetsTexture;
	uniform ivec2 morphTargetsTextureSize;
	vec4 getMorph( const in int vertexIndex, const in int morphTargetIndex, const in int offset ) {
		int texelIndex = vertexIndex * MORPHTARGETS_TEXTURE_STRIDE + offset;
		int y = texelIndex / morphTargetsTextureSize.x;
		int x = texelIndex - y * morphTargetsTextureSize.x;
		ivec3 morphUV = ivec3( x, y, morphTargetIndex );
		return texelFetch( morphTargetsTexture, morphUV, 0 );
	}
#endif`,yk=`#ifdef USE_MORPHTARGETS
	transformed *= morphTargetBaseInfluence;
	for ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {
		if ( morphTargetInfluences[ i ] != 0.0 ) transformed += getMorph( gl_VertexID, i, 0 ).xyz * morphTargetInfluences[ i ];
	}
#endif`,bk=`float faceDirection = gl_FrontFacing ? 1.0 : - 1.0;
#ifdef FLAT_SHADED
	vec3 fdx = dFdx( vViewPosition );
	vec3 fdy = dFdy( vViewPosition );
	vec3 normal = normalize( cross( fdx, fdy ) );
#else
	vec3 normal = normalize( vNormal );
	#ifdef DOUBLE_SIDED
		normal *= faceDirection;
	#endif
#endif
#if defined( USE_NORMALMAP_TANGENTSPACE ) || defined( USE_CLEARCOAT_NORMALMAP ) || defined( USE_ANISOTROPY )
	#ifdef USE_TANGENT
		mat3 tbn = mat3( normalize( vTangent ), normalize( vBitangent ), normal );
	#else
		mat3 tbn = getTangentFrame( - vViewPosition, normal,
		#if defined( USE_NORMALMAP )
			vNormalMapUv
		#elif defined( USE_CLEARCOAT_NORMALMAP )
			vClearcoatNormalMapUv
		#else
			vUv
		#endif
		);
	#endif
	#if defined( DOUBLE_SIDED ) && ! defined( FLAT_SHADED )
		tbn[0] *= faceDirection;
		tbn[1] *= faceDirection;
	#endif
#endif
#ifdef USE_CLEARCOAT_NORMALMAP
	#ifdef USE_TANGENT
		mat3 tbn2 = mat3( normalize( vTangent ), normalize( vBitangent ), normal );
	#else
		mat3 tbn2 = getTangentFrame( - vViewPosition, normal, vClearcoatNormalMapUv );
	#endif
	#if defined( DOUBLE_SIDED ) && ! defined( FLAT_SHADED )
		tbn2[0] *= faceDirection;
		tbn2[1] *= faceDirection;
	#endif
#endif
vec3 nonPerturbedNormal = normal;`,Ek=`#ifdef USE_NORMALMAP_OBJECTSPACE
	normal = texture2D( normalMap, vNormalMapUv ).xyz * 2.0 - 1.0;
	#ifdef FLIP_SIDED
		normal = - normal;
	#endif
	#ifdef DOUBLE_SIDED
		normal = normal * faceDirection;
	#endif
	normal = normalize( normalMatrix * normal );
#elif defined( USE_NORMALMAP_TANGENTSPACE )
	vec3 mapN = texture2D( normalMap, vNormalMapUv ).xyz * 2.0 - 1.0;
	mapN.xy *= normalScale;
	normal = normalize( tbn * mapN );
#elif defined( USE_BUMPMAP )
	normal = perturbNormalArb( - vViewPosition, normal, dHdxy_fwd(), faceDirection );
#endif`,wk=`#ifndef FLAT_SHADED
	varying vec3 vNormal;
	#ifdef USE_TANGENT
		varying vec3 vTangent;
		varying vec3 vBitangent;
	#endif
#endif`,Ck=`#ifndef FLAT_SHADED
	varying vec3 vNormal;
	#ifdef USE_TANGENT
		varying vec3 vTangent;
		varying vec3 vBitangent;
	#endif
#endif`,Pk=`#ifndef FLAT_SHADED
	vNormal = normalize( transformedNormal );
	#ifdef USE_TANGENT
		vTangent = normalize( transformedTangent );
		vBitangent = normalize( cross( vNormal, vTangent ) * tangent.w );
	#endif
#endif`,Bk=`#ifdef USE_NORMALMAP
	uniform sampler2D normalMap;
	uniform vec2 normalScale;
#endif
#ifdef USE_NORMALMAP_OBJECTSPACE
	uniform mat3 normalMatrix;
#endif
#if ! defined ( USE_TANGENT ) && ( defined ( USE_NORMALMAP_TANGENTSPACE ) || defined ( USE_CLEARCOAT_NORMALMAP ) || defined( USE_ANISOTROPY ) )
	mat3 getTangentFrame( vec3 eye_pos, vec3 surf_norm, vec2 uv ) {
		vec3 q0 = dFdx( eye_pos.xyz );
		vec3 q1 = dFdy( eye_pos.xyz );
		vec2 st0 = dFdx( uv.st );
		vec2 st1 = dFdy( uv.st );
		vec3 N = surf_norm;
		vec3 q1perp = cross( q1, N );
		vec3 q0perp = cross( N, q0 );
		vec3 T = q1perp * st0.x + q0perp * st1.x;
		vec3 B = q1perp * st0.y + q0perp * st1.y;
		float det = max( dot( T, T ), dot( B, B ) );
		float scale = ( det == 0.0 ) ? 0.0 : inversesqrt( det );
		return mat3( T * scale, B * scale, N );
	}
#endif`,Mk=`#ifdef USE_CLEARCOAT
	vec3 clearcoatNormal = nonPerturbedNormal;
#endif`,Sk=`#ifdef USE_CLEARCOAT_NORMALMAP
	vec3 clearcoatMapN = texture2D( clearcoatNormalMap, vClearcoatNormalMapUv ).xyz * 2.0 - 1.0;
	clearcoatMapN.xy *= clearcoatNormalScale;
	clearcoatNormal = normalize( tbn2 * clearcoatMapN );
#endif`,Dk=`#ifdef USE_CLEARCOATMAP
	uniform sampler2D clearcoatMap;
#endif
#ifdef USE_CLEARCOAT_NORMALMAP
	uniform sampler2D clearcoatNormalMap;
	uniform vec2 clearcoatNormalScale;
#endif
#ifdef USE_CLEARCOAT_ROUGHNESSMAP
	uniform sampler2D clearcoatRoughnessMap;
#endif`,Tk=`#ifdef USE_IRIDESCENCEMAP
	uniform sampler2D iridescenceMap;
#endif
#ifdef USE_IRIDESCENCE_THICKNESSMAP
	uniform sampler2D iridescenceThicknessMap;
#endif`,Ik=`#ifdef OPAQUE
diffuseColor.a = 1.0;
#endif
#ifdef USE_TRANSMISSION
diffuseColor.a *= material.transmissionAlpha;
#endif
gl_FragColor = vec4( outgoingLight, diffuseColor.a );`,Nk=`vec3 packNormalToRGB( const in vec3 normal ) {
	return normalize( normal ) * 0.5 + 0.5;
}
vec3 unpackRGBToNormal( const in vec3 rgb ) {
	return 2.0 * rgb.xyz - 1.0;
}
const float PackUpscale = 256. / 255.;const float UnpackDownscale = 255. / 256.;const float ShiftRight8 = 1. / 256.;
const float Inv255 = 1. / 255.;
const vec4 PackFactors = vec4( 1.0, 256.0, 256.0 * 256.0, 256.0 * 256.0 * 256.0 );
const vec2 UnpackFactors2 = vec2( UnpackDownscale, 1.0 / PackFactors.g );
const vec3 UnpackFactors3 = vec3( UnpackDownscale / PackFactors.rg, 1.0 / PackFactors.b );
const vec4 UnpackFactors4 = vec4( UnpackDownscale / PackFactors.rgb, 1.0 / PackFactors.a );
vec4 packDepthToRGBA( const in float v ) {
	if( v <= 0.0 )
		return vec4( 0., 0., 0., 0. );
	if( v >= 1.0 )
		return vec4( 1., 1., 1., 1. );
	float vuf;
	float af = modf( v * PackFactors.a, vuf );
	float bf = modf( vuf * ShiftRight8, vuf );
	float gf = modf( vuf * ShiftRight8, vuf );
	return vec4( vuf * Inv255, gf * PackUpscale, bf * PackUpscale, af );
}
vec3 packDepthToRGB( const in float v ) {
	if( v <= 0.0 )
		return vec3( 0., 0., 0. );
	if( v >= 1.0 )
		return vec3( 1., 1., 1. );
	float vuf;
	float bf = modf( v * PackFactors.b, vuf );
	float gf = modf( vuf * ShiftRight8, vuf );
	return vec3( vuf * Inv255, gf * PackUpscale, bf );
}
vec2 packDepthToRG( const in float v ) {
	if( v <= 0.0 )
		return vec2( 0., 0. );
	if( v >= 1.0 )
		return vec2( 1., 1. );
	float vuf;
	float gf = modf( v * 256., vuf );
	return vec2( vuf * Inv255, gf );
}
float unpackRGBAToDepth( const in vec4 v ) {
	return dot( v, UnpackFactors4 );
}
float unpackRGBToDepth( const in vec3 v ) {
	return dot( v, UnpackFactors3 );
}
float unpackRGToDepth( const in vec2 v ) {
	return v.r * UnpackFactors2.r + v.g * UnpackFactors2.g;
}
vec4 pack2HalfToRGBA( const in vec2 v ) {
	vec4 r = vec4( v.x, fract( v.x * 255.0 ), v.y, fract( v.y * 255.0 ) );
	return vec4( r.x - r.y / 255.0, r.y, r.z - r.w / 255.0, r.w );
}
vec2 unpackRGBATo2Half( const in vec4 v ) {
	return vec2( v.x + ( v.y / 255.0 ), v.z + ( v.w / 255.0 ) );
}
float viewZToOrthographicDepth( const in float viewZ, const in float near, const in float far ) {
	return ( viewZ + near ) / ( near - far );
}
float orthographicDepthToViewZ( const in float depth, const in float near, const in float far ) {
	return depth * ( near - far ) - near;
}
float viewZToPerspectiveDepth( const in float viewZ, const in float near, const in float far ) {
	return ( ( near + viewZ ) * far ) / ( ( far - near ) * viewZ );
}
float perspectiveDepthToViewZ( const in float depth, const in float near, const in float far ) {
	return ( near * far ) / ( ( far - near ) * depth - far );
}`,Fk=`#ifdef PREMULTIPLIED_ALPHA
	gl_FragColor.rgb *= gl_FragColor.a;
#endif`,Rk=`vec4 mvPosition = vec4( transformed, 1.0 );
#ifdef USE_BATCHING
	mvPosition = batchingMatrix * mvPosition;
#endif
#ifdef USE_INSTANCING
	mvPosition = instanceMatrix * mvPosition;
#endif
mvPosition = modelViewMatrix * mvPosition;
gl_Position = projectionMatrix * mvPosition;`,Lk=`#ifdef DITHERING
	gl_FragColor.rgb = dithering( gl_FragColor.rgb );
#endif`,Ok=`#ifdef DITHERING
	vec3 dithering( vec3 color ) {
		float grid_position = rand( gl_FragCoord.xy );
		vec3 dither_shift_RGB = vec3( 0.25 / 255.0, -0.25 / 255.0, 0.25 / 255.0 );
		dither_shift_RGB = mix( 2.0 * dither_shift_RGB, -2.0 * dither_shift_RGB, grid_position );
		return color + dither_shift_RGB;
	}
#endif`,zk=`float roughnessFactor = roughness;
#ifdef USE_ROUGHNESSMAP
	vec4 texelRoughness = texture2D( roughnessMap, vRoughnessMapUv );
	roughnessFactor *= texelRoughness.g;
#endif`,Hk=`#ifdef USE_ROUGHNESSMAP
	uniform sampler2D roughnessMap;
#endif`,Uk=`#if NUM_SPOT_LIGHT_COORDS > 0
	varying vec4 vSpotLightCoord[ NUM_SPOT_LIGHT_COORDS ];
#endif
#if NUM_SPOT_LIGHT_MAPS > 0
	uniform sampler2D spotLightMap[ NUM_SPOT_LIGHT_MAPS ];
#endif
#ifdef USE_SHADOWMAP
	#if NUM_DIR_LIGHT_SHADOWS > 0
		#if defined( SHADOWMAP_TYPE_PCF )
			uniform sampler2DShadow directionalShadowMap[ NUM_DIR_LIGHT_SHADOWS ];
		#else
			uniform sampler2D directionalShadowMap[ NUM_DIR_LIGHT_SHADOWS ];
		#endif
		varying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];
		struct DirectionalLightShadow {
			float shadowIntensity;
			float shadowBias;
			float shadowNormalBias;
			float shadowRadius;
			vec2 shadowMapSize;
		};
		uniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];
	#endif
	#if NUM_SPOT_LIGHT_SHADOWS > 0
		#if defined( SHADOWMAP_TYPE_PCF )
			uniform sampler2DShadow spotShadowMap[ NUM_SPOT_LIGHT_SHADOWS ];
		#else
			uniform sampler2D spotShadowMap[ NUM_SPOT_LIGHT_SHADOWS ];
		#endif
		struct SpotLightShadow {
			float shadowIntensity;
			float shadowBias;
			float shadowNormalBias;
			float shadowRadius;
			vec2 shadowMapSize;
		};
		uniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];
	#endif
	#if NUM_POINT_LIGHT_SHADOWS > 0
		#if defined( SHADOWMAP_TYPE_PCF )
			uniform samplerCubeShadow pointShadowMap[ NUM_POINT_LIGHT_SHADOWS ];
		#elif defined( SHADOWMAP_TYPE_BASIC )
			uniform samplerCube pointShadowMap[ NUM_POINT_LIGHT_SHADOWS ];
		#endif
		varying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];
		struct PointLightShadow {
			float shadowIntensity;
			float shadowBias;
			float shadowNormalBias;
			float shadowRadius;
			vec2 shadowMapSize;
			float shadowCameraNear;
			float shadowCameraFar;
		};
		uniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];
	#endif
	#if defined( SHADOWMAP_TYPE_PCF )
		float interleavedGradientNoise( vec2 position ) {
			return fract( 52.9829189 * fract( dot( position, vec2( 0.06711056, 0.00583715 ) ) ) );
		}
		vec2 vogelDiskSample( int sampleIndex, int samplesCount, float phi ) {
			const float goldenAngle = 2.399963229728653;
			float r = sqrt( ( float( sampleIndex ) + 0.5 ) / float( samplesCount ) );
			float theta = float( sampleIndex ) * goldenAngle + phi;
			return vec2( cos( theta ), sin( theta ) ) * r;
		}
	#endif
	#if defined( SHADOWMAP_TYPE_PCF )
		float getShadow( sampler2DShadow shadowMap, vec2 shadowMapSize, float shadowIntensity, float shadowBias, float shadowRadius, vec4 shadowCoord ) {
			float shadow = 1.0;
			shadowCoord.xyz /= shadowCoord.w;
			shadowCoord.z += shadowBias;
			bool inFrustum = shadowCoord.x >= 0.0 && shadowCoord.x <= 1.0 && shadowCoord.y >= 0.0 && shadowCoord.y <= 1.0;
			bool frustumTest = inFrustum && shadowCoord.z <= 1.0;
			if ( frustumTest ) {
				vec2 texelSize = vec2( 1.0 ) / shadowMapSize;
				float radius = shadowRadius * texelSize.x;
				float phi = interleavedGradientNoise( gl_FragCoord.xy ) * 6.28318530718;
				shadow = (
					texture( shadowMap, vec3( shadowCoord.xy + vogelDiskSample( 0, 5, phi ) * radius, shadowCoord.z ) ) +
					texture( shadowMap, vec3( shadowCoord.xy + vogelDiskSample( 1, 5, phi ) * radius, shadowCoord.z ) ) +
					texture( shadowMap, vec3( shadowCoord.xy + vogelDiskSample( 2, 5, phi ) * radius, shadowCoord.z ) ) +
					texture( shadowMap, vec3( shadowCoord.xy + vogelDiskSample( 3, 5, phi ) * radius, shadowCoord.z ) ) +
					texture( shadowMap, vec3( shadowCoord.xy + vogelDiskSample( 4, 5, phi ) * radius, shadowCoord.z ) )
				) * 0.2;
			}
			return mix( 1.0, shadow, shadowIntensity );
		}
	#elif defined( SHADOWMAP_TYPE_VSM )
		float getShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowIntensity, float shadowBias, float shadowRadius, vec4 shadowCoord ) {
			float shadow = 1.0;
			shadowCoord.xyz /= shadowCoord.w;
			shadowCoord.z += shadowBias;
			bool inFrustum = shadowCoord.x >= 0.0 && shadowCoord.x <= 1.0 && shadowCoord.y >= 0.0 && shadowCoord.y <= 1.0;
			bool frustumTest = inFrustum && shadowCoord.z <= 1.0;
			if ( frustumTest ) {
				vec2 distribution = texture2D( shadowMap, shadowCoord.xy ).rg;
				float mean = distribution.x;
				float variance = distribution.y * distribution.y;
				#ifdef USE_REVERSED_DEPTH_BUFFER
					float hard_shadow = step( mean, shadowCoord.z );
				#else
					float hard_shadow = step( shadowCoord.z, mean );
				#endif
				if ( hard_shadow == 1.0 ) {
					shadow = 1.0;
				} else {
					variance = max( variance, 0.0000001 );
					float d = shadowCoord.z - mean;
					float p_max = variance / ( variance + d * d );
					p_max = clamp( ( p_max - 0.3 ) / 0.65, 0.0, 1.0 );
					shadow = max( hard_shadow, p_max );
				}
			}
			return mix( 1.0, shadow, shadowIntensity );
		}
	#else
		float getShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowIntensity, float shadowBias, float shadowRadius, vec4 shadowCoord ) {
			float shadow = 1.0;
			shadowCoord.xyz /= shadowCoord.w;
			shadowCoord.z += shadowBias;
			bool inFrustum = shadowCoord.x >= 0.0 && shadowCoord.x <= 1.0 && shadowCoord.y >= 0.0 && shadowCoord.y <= 1.0;
			bool frustumTest = inFrustum && shadowCoord.z <= 1.0;
			if ( frustumTest ) {
				float depth = texture2D( shadowMap, shadowCoord.xy ).r;
				#ifdef USE_REVERSED_DEPTH_BUFFER
					shadow = step( depth, shadowCoord.z );
				#else
					shadow = step( shadowCoord.z, depth );
				#endif
			}
			return mix( 1.0, shadow, shadowIntensity );
		}
	#endif
	#if NUM_POINT_LIGHT_SHADOWS > 0
	#if defined( SHADOWMAP_TYPE_PCF )
	float getPointShadow( samplerCubeShadow shadowMap, vec2 shadowMapSize, float shadowIntensity, float shadowBias, float shadowRadius, vec4 shadowCoord, float shadowCameraNear, float shadowCameraFar ) {
		float shadow = 1.0;
		vec3 lightToPosition = shadowCoord.xyz;
		vec3 bd3D = normalize( lightToPosition );
		vec3 absVec = abs( lightToPosition );
		float viewSpaceZ = max( max( absVec.x, absVec.y ), absVec.z );
		if ( viewSpaceZ - shadowCameraFar <= 0.0 && viewSpaceZ - shadowCameraNear >= 0.0 ) {
			float dp = ( shadowCameraFar * ( viewSpaceZ - shadowCameraNear ) ) / ( viewSpaceZ * ( shadowCameraFar - shadowCameraNear ) );
			dp += shadowBias;
			float texelSize = shadowRadius / shadowMapSize.x;
			vec3 absDir = abs( bd3D );
			vec3 tangent = absDir.x > absDir.z ? vec3( 0.0, 1.0, 0.0 ) : vec3( 1.0, 0.0, 0.0 );
			tangent = normalize( cross( bd3D, tangent ) );
			vec3 bitangent = cross( bd3D, tangent );
			float phi = interleavedGradientNoise( gl_FragCoord.xy ) * 6.28318530718;
			shadow = (
				texture( shadowMap, vec4( bd3D + ( tangent * vogelDiskSample( 0, 5, phi ).x + bitangent * vogelDiskSample( 0, 5, phi ).y ) * texelSize, dp ) ) +
				texture( shadowMap, vec4( bd3D + ( tangent * vogelDiskSample( 1, 5, phi ).x + bitangent * vogelDiskSample( 1, 5, phi ).y ) * texelSize, dp ) ) +
				texture( shadowMap, vec4( bd3D + ( tangent * vogelDiskSample( 2, 5, phi ).x + bitangent * vogelDiskSample( 2, 5, phi ).y ) * texelSize, dp ) ) +
				texture( shadowMap, vec4( bd3D + ( tangent * vogelDiskSample( 3, 5, phi ).x + bitangent * vogelDiskSample( 3, 5, phi ).y ) * texelSize, dp ) ) +
				texture( shadowMap, vec4( bd3D + ( tangent * vogelDiskSample( 4, 5, phi ).x + bitangent * vogelDiskSample( 4, 5, phi ).y ) * texelSize, dp ) )
			) * 0.2;
		}
		return mix( 1.0, shadow, shadowIntensity );
	}
	#elif defined( SHADOWMAP_TYPE_BASIC )
	float getPointShadow( samplerCube shadowMap, vec2 shadowMapSize, float shadowIntensity, float shadowBias, float shadowRadius, vec4 shadowCoord, float shadowCameraNear, float shadowCameraFar ) {
		float shadow = 1.0;
		vec3 lightToPosition = shadowCoord.xyz;
		vec3 bd3D = normalize( lightToPosition );
		vec3 absVec = abs( lightToPosition );
		float viewSpaceZ = max( max( absVec.x, absVec.y ), absVec.z );
		if ( viewSpaceZ - shadowCameraFar <= 0.0 && viewSpaceZ - shadowCameraNear >= 0.0 ) {
			float dp = ( shadowCameraFar * ( viewSpaceZ - shadowCameraNear ) ) / ( viewSpaceZ * ( shadowCameraFar - shadowCameraNear ) );
			dp += shadowBias;
			float depth = textureCube( shadowMap, bd3D ).r;
			#ifdef USE_REVERSED_DEPTH_BUFFER
				shadow = step( depth, dp );
			#else
				shadow = step( dp, depth );
			#endif
		}
		return mix( 1.0, shadow, shadowIntensity );
	}
	#endif
	#endif
#endif`,kk=`#if NUM_SPOT_LIGHT_COORDS > 0
	uniform mat4 spotLightMatrix[ NUM_SPOT_LIGHT_COORDS ];
	varying vec4 vSpotLightCoord[ NUM_SPOT_LIGHT_COORDS ];
#endif
#ifdef USE_SHADOWMAP
	#if NUM_DIR_LIGHT_SHADOWS > 0
		uniform mat4 directionalShadowMatrix[ NUM_DIR_LIGHT_SHADOWS ];
		varying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];
		struct DirectionalLightShadow {
			float shadowIntensity;
			float shadowBias;
			float shadowNormalBias;
			float shadowRadius;
			vec2 shadowMapSize;
		};
		uniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];
	#endif
	#if NUM_SPOT_LIGHT_SHADOWS > 0
		struct SpotLightShadow {
			float shadowIntensity;
			float shadowBias;
			float shadowNormalBias;
			float shadowRadius;
			vec2 shadowMapSize;
		};
		uniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];
	#endif
	#if NUM_POINT_LIGHT_SHADOWS > 0
		uniform mat4 pointShadowMatrix[ NUM_POINT_LIGHT_SHADOWS ];
		varying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];
		struct PointLightShadow {
			float shadowIntensity;
			float shadowBias;
			float shadowNormalBias;
			float shadowRadius;
			vec2 shadowMapSize;
			float shadowCameraNear;
			float shadowCameraFar;
		};
		uniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];
	#endif
#endif`,Vk=`#if ( defined( USE_SHADOWMAP ) && ( NUM_DIR_LIGHT_SHADOWS > 0 || NUM_POINT_LIGHT_SHADOWS > 0 ) ) || ( NUM_SPOT_LIGHT_COORDS > 0 )
	vec3 shadowWorldNormal = inverseTransformDirection( transformedNormal, viewMatrix );
	vec4 shadowWorldPosition;
#endif
#if defined( USE_SHADOWMAP )
	#if NUM_DIR_LIGHT_SHADOWS > 0
		#pragma unroll_loop_start
		for ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {
			shadowWorldPosition = worldPosition + vec4( shadowWorldNormal * directionalLightShadows[ i ].shadowNormalBias, 0 );
			vDirectionalShadowCoord[ i ] = directionalShadowMatrix[ i ] * shadowWorldPosition;
		}
		#pragma unroll_loop_end
	#endif
	#if NUM_POINT_LIGHT_SHADOWS > 0
		#pragma unroll_loop_start
		for ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {
			shadowWorldPosition = worldPosition + vec4( shadowWorldNormal * pointLightShadows[ i ].shadowNormalBias, 0 );
			vPointShadowCoord[ i ] = pointShadowMatrix[ i ] * shadowWorldPosition;
		}
		#pragma unroll_loop_end
	#endif
#endif
#if NUM_SPOT_LIGHT_COORDS > 0
	#pragma unroll_loop_start
	for ( int i = 0; i < NUM_SPOT_LIGHT_COORDS; i ++ ) {
		shadowWorldPosition = worldPosition;
		#if ( defined( USE_SHADOWMAP ) && UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )
			shadowWorldPosition.xyz += shadowWorldNormal * spotLightShadows[ i ].shadowNormalBias;
		#endif
		vSpotLightCoord[ i ] = spotLightMatrix[ i ] * shadowWorldPosition;
	}
	#pragma unroll_loop_end
#endif`,jk=`float getShadowMask() {
	float shadow = 1.0;
	#ifdef USE_SHADOWMAP
	#if NUM_DIR_LIGHT_SHADOWS > 0
	DirectionalLightShadow directionalLight;
	#pragma unroll_loop_start
	for ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {
		directionalLight = directionalLightShadows[ i ];
		shadow *= receiveShadow ? getShadow( directionalShadowMap[ i ], directionalLight.shadowMapSize, directionalLight.shadowIntensity, directionalLight.shadowBias, directionalLight.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;
	}
	#pragma unroll_loop_end
	#endif
	#if NUM_SPOT_LIGHT_SHADOWS > 0
	SpotLightShadow spotLight;
	#pragma unroll_loop_start
	for ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {
		spotLight = spotLightShadows[ i ];
		shadow *= receiveShadow ? getShadow( spotShadowMap[ i ], spotLight.shadowMapSize, spotLight.shadowIntensity, spotLight.shadowBias, spotLight.shadowRadius, vSpotLightCoord[ i ] ) : 1.0;
	}
	#pragma unroll_loop_end
	#endif
	#if NUM_POINT_LIGHT_SHADOWS > 0 && ( defined( SHADOWMAP_TYPE_PCF ) || defined( SHADOWMAP_TYPE_BASIC ) )
	PointLightShadow pointLight;
	#pragma unroll_loop_start
	for ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {
		pointLight = pointLightShadows[ i ];
		shadow *= receiveShadow ? getPointShadow( pointShadowMap[ i ], pointLight.shadowMapSize, pointLight.shadowIntensity, pointLight.shadowBias, pointLight.shadowRadius, vPointShadowCoord[ i ], pointLight.shadowCameraNear, pointLight.shadowCameraFar ) : 1.0;
	}
	#pragma unroll_loop_end
	#endif
	#endif
	return shadow;
}`,Xk=`#ifdef USE_SKINNING
	mat4 boneMatX = getBoneMatrix( skinIndex.x );
	mat4 boneMatY = getBoneMatrix( skinIndex.y );
	mat4 boneMatZ = getBoneMatrix( skinIndex.z );
	mat4 boneMatW = getBoneMatrix( skinIndex.w );
#endif`,Gk=`#ifdef USE_SKINNING
	uniform mat4 bindMatrix;
	uniform mat4 bindMatrixInverse;
	uniform highp sampler2D boneTexture;
	mat4 getBoneMatrix( const in float i ) {
		int size = textureSize( boneTexture, 0 ).x;
		int j = int( i ) * 4;
		int x = j % size;
		int y = j / size;
		vec4 v1 = texelFetch( boneTexture, ivec2( x, y ), 0 );
		vec4 v2 = texelFetch( boneTexture, ivec2( x + 1, y ), 0 );
		vec4 v3 = texelFetch( boneTexture, ivec2( x + 2, y ), 0 );
		vec4 v4 = texelFetch( boneTexture, ivec2( x + 3, y ), 0 );
		return mat4( v1, v2, v3, v4 );
	}
#endif`,Wk=`#ifdef USE_SKINNING
	vec4 skinVertex = bindMatrix * vec4( transformed, 1.0 );
	vec4 skinned = vec4( 0.0 );
	skinned += boneMatX * skinVertex * skinWeight.x;
	skinned += boneMatY * skinVertex * skinWeight.y;
	skinned += boneMatZ * skinVertex * skinWeight.z;
	skinned += boneMatW * skinVertex * skinWeight.w;
	transformed = ( bindMatrixInverse * skinned ).xyz;
#endif`,Qk=`#ifdef USE_SKINNING
	mat4 skinMatrix = mat4( 0.0 );
	skinMatrix += skinWeight.x * boneMatX;
	skinMatrix += skinWeight.y * boneMatY;
	skinMatrix += skinWeight.z * boneMatZ;
	skinMatrix += skinWeight.w * boneMatW;
	skinMatrix = bindMatrixInverse * skinMatrix * bindMatrix;
	objectNormal = vec4( skinMatrix * vec4( objectNormal, 0.0 ) ).xyz;
	#ifdef USE_TANGENT
		objectTangent = vec4( skinMatrix * vec4( objectTangent, 0.0 ) ).xyz;
	#endif
#endif`,Zk=`float specularStrength;
#ifdef USE_SPECULARMAP
	vec4 texelSpecular = texture2D( specularMap, vSpecularMapUv );
	specularStrength = texelSpecular.r;
#else
	specularStrength = 1.0;
#endif`,Yk=`#ifdef USE_SPECULARMAP
	uniform sampler2D specularMap;
#endif`,Jk=`#if defined( TONE_MAPPING )
	gl_FragColor.rgb = toneMapping( gl_FragColor.rgb );
#endif`,Kk=`#ifndef saturate
#define saturate( a ) clamp( a, 0.0, 1.0 )
#endif
uniform float toneMappingExposure;
vec3 LinearToneMapping( vec3 color ) {
	return saturate( toneMappingExposure * color );
}
vec3 ReinhardToneMapping( vec3 color ) {
	color *= toneMappingExposure;
	return saturate( color / ( vec3( 1.0 ) + color ) );
}
vec3 CineonToneMapping( vec3 color ) {
	color *= toneMappingExposure;
	color = max( vec3( 0.0 ), color - 0.004 );
	return pow( ( color * ( 6.2 * color + 0.5 ) ) / ( color * ( 6.2 * color + 1.7 ) + 0.06 ), vec3( 2.2 ) );
}
vec3 RRTAndODTFit( vec3 v ) {
	vec3 a = v * ( v + 0.0245786 ) - 0.000090537;
	vec3 b = v * ( 0.983729 * v + 0.4329510 ) + 0.238081;
	return a / b;
}
vec3 ACESFilmicToneMapping( vec3 color ) {
	const mat3 ACESInputMat = mat3(
		vec3( 0.59719, 0.07600, 0.02840 ),		vec3( 0.35458, 0.90834, 0.13383 ),
		vec3( 0.04823, 0.01566, 0.83777 )
	);
	const mat3 ACESOutputMat = mat3(
		vec3(  1.60475, -0.10208, -0.00327 ),		vec3( -0.53108,  1.10813, -0.07276 ),
		vec3( -0.07367, -0.00605,  1.07602 )
	);
	color *= toneMappingExposure / 0.6;
	color = ACESInputMat * color;
	color = RRTAndODTFit( color );
	color = ACESOutputMat * color;
	return saturate( color );
}
const mat3 LINEAR_REC2020_TO_LINEAR_SRGB = mat3(
	vec3( 1.6605, - 0.1246, - 0.0182 ),
	vec3( - 0.5876, 1.1329, - 0.1006 ),
	vec3( - 0.0728, - 0.0083, 1.1187 )
);
const mat3 LINEAR_SRGB_TO_LINEAR_REC2020 = mat3(
	vec3( 0.6274, 0.0691, 0.0164 ),
	vec3( 0.3293, 0.9195, 0.0880 ),
	vec3( 0.0433, 0.0113, 0.8956 )
);
vec3 agxDefaultContrastApprox( vec3 x ) {
	vec3 x2 = x * x;
	vec3 x4 = x2 * x2;
	return + 15.5 * x4 * x2
		- 40.14 * x4 * x
		+ 31.96 * x4
		- 6.868 * x2 * x
		+ 0.4298 * x2
		+ 0.1191 * x
		- 0.00232;
}
vec3 AgXToneMapping( vec3 color ) {
	const mat3 AgXInsetMatrix = mat3(
		vec3( 0.856627153315983, 0.137318972929847, 0.11189821299995 ),
		vec3( 0.0951212405381588, 0.761241990602591, 0.0767994186031903 ),
		vec3( 0.0482516061458583, 0.101439036467562, 0.811302368396859 )
	);
	const mat3 AgXOutsetMatrix = mat3(
		vec3( 1.1271005818144368, - 0.1413297634984383, - 0.14132976349843826 ),
		vec3( - 0.11060664309660323, 1.157823702216272, - 0.11060664309660294 ),
		vec3( - 0.016493938717834573, - 0.016493938717834257, 1.2519364065950405 )
	);
	const float AgxMinEv = - 12.47393;	const float AgxMaxEv = 4.026069;
	color *= toneMappingExposure;
	color = LINEAR_SRGB_TO_LINEAR_REC2020 * color;
	color = AgXInsetMatrix * color;
	color = max( color, 1e-10 );	color = log2( color );
	color = ( color - AgxMinEv ) / ( AgxMaxEv - AgxMinEv );
	color = clamp( color, 0.0, 1.0 );
	color = agxDefaultContrastApprox( color );
	color = AgXOutsetMatrix * color;
	color = pow( max( vec3( 0.0 ), color ), vec3( 2.2 ) );
	color = LINEAR_REC2020_TO_LINEAR_SRGB * color;
	color = clamp( color, 0.0, 1.0 );
	return color;
}
vec3 NeutralToneMapping( vec3 color ) {
	const float StartCompression = 0.8 - 0.04;
	const float Desaturation = 0.15;
	color *= toneMappingExposure;
	float x = min( color.r, min( color.g, color.b ) );
	float offset = x < 0.08 ? x - 6.25 * x * x : 0.04;
	color -= offset;
	float peak = max( color.r, max( color.g, color.b ) );
	if ( peak < StartCompression ) return color;
	float d = 1. - StartCompression;
	float newPeak = 1. - d * d / ( peak + d - StartCompression );
	color *= newPeak / peak;
	float g = 1. - 1. / ( Desaturation * ( peak - newPeak ) + 1. );
	return mix( color, vec3( newPeak ), g );
}
vec3 CustomToneMapping( vec3 color ) { return color; }`,qk=`#ifdef USE_TRANSMISSION
	material.transmission = transmission;
	material.transmissionAlpha = 1.0;
	material.thickness = thickness;
	material.attenuationDistance = attenuationDistance;
	material.attenuationColor = attenuationColor;
	#ifdef USE_TRANSMISSIONMAP
		material.transmission *= texture2D( transmissionMap, vTransmissionMapUv ).r;
	#endif
	#ifdef USE_THICKNESSMAP
		material.thickness *= texture2D( thicknessMap, vThicknessMapUv ).g;
	#endif
	vec3 pos = vWorldPosition;
	vec3 v = normalize( cameraPosition - pos );
	vec3 n = inverseTransformDirection( normal, viewMatrix );
	vec4 transmitted = getIBLVolumeRefraction(
		n, v, material.roughness, material.diffuseContribution, material.specularColorBlended, material.specularF90,
		pos, modelMatrix, viewMatrix, projectionMatrix, material.dispersion, material.ior, material.thickness,
		material.attenuationColor, material.attenuationDistance );
	material.transmissionAlpha = mix( material.transmissionAlpha, transmitted.a, material.transmission );
	totalDiffuse = mix( totalDiffuse, transmitted.rgb, material.transmission );
#endif`,_k=`#ifdef USE_TRANSMISSION
	uniform float transmission;
	uniform float thickness;
	uniform float attenuationDistance;
	uniform vec3 attenuationColor;
	#ifdef USE_TRANSMISSIONMAP
		uniform sampler2D transmissionMap;
	#endif
	#ifdef USE_THICKNESSMAP
		uniform sampler2D thicknessMap;
	#endif
	uniform vec2 transmissionSamplerSize;
	uniform sampler2D transmissionSamplerMap;
	uniform mat4 modelMatrix;
	uniform mat4 projectionMatrix;
	varying vec3 vWorldPosition;
	float w0( float a ) {
		return ( 1.0 / 6.0 ) * ( a * ( a * ( - a + 3.0 ) - 3.0 ) + 1.0 );
	}
	float w1( float a ) {
		return ( 1.0 / 6.0 ) * ( a *  a * ( 3.0 * a - 6.0 ) + 4.0 );
	}
	float w2( float a ){
		return ( 1.0 / 6.0 ) * ( a * ( a * ( - 3.0 * a + 3.0 ) + 3.0 ) + 1.0 );
	}
	float w3( float a ) {
		return ( 1.0 / 6.0 ) * ( a * a * a );
	}
	float g0( float a ) {
		return w0( a ) + w1( a );
	}
	float g1( float a ) {
		return w2( a ) + w3( a );
	}
	float h0( float a ) {
		return - 1.0 + w1( a ) / ( w0( a ) + w1( a ) );
	}
	float h1( float a ) {
		return 1.0 + w3( a ) / ( w2( a ) + w3( a ) );
	}
	vec4 bicubic( sampler2D tex, vec2 uv, vec4 texelSize, float lod ) {
		uv = uv * texelSize.zw + 0.5;
		vec2 iuv = floor( uv );
		vec2 fuv = fract( uv );
		float g0x = g0( fuv.x );
		float g1x = g1( fuv.x );
		float h0x = h0( fuv.x );
		float h1x = h1( fuv.x );
		float h0y = h0( fuv.y );
		float h1y = h1( fuv.y );
		vec2 p0 = ( vec2( iuv.x + h0x, iuv.y + h0y ) - 0.5 ) * texelSize.xy;
		vec2 p1 = ( vec2( iuv.x + h1x, iuv.y + h0y ) - 0.5 ) * texelSize.xy;
		vec2 p2 = ( vec2( iuv.x + h0x, iuv.y + h1y ) - 0.5 ) * texelSize.xy;
		vec2 p3 = ( vec2( iuv.x + h1x, iuv.y + h1y ) - 0.5 ) * texelSize.xy;
		return g0( fuv.y ) * ( g0x * textureLod( tex, p0, lod ) + g1x * textureLod( tex, p1, lod ) ) +
			g1( fuv.y ) * ( g0x * textureLod( tex, p2, lod ) + g1x * textureLod( tex, p3, lod ) );
	}
	vec4 textureBicubic( sampler2D sampler, vec2 uv, float lod ) {
		vec2 fLodSize = vec2( textureSize( sampler, int( lod ) ) );
		vec2 cLodSize = vec2( textureSize( sampler, int( lod + 1.0 ) ) );
		vec2 fLodSizeInv = 1.0 / fLodSize;
		vec2 cLodSizeInv = 1.0 / cLodSize;
		vec4 fSample = bicubic( sampler, uv, vec4( fLodSizeInv, fLodSize ), floor( lod ) );
		vec4 cSample = bicubic( sampler, uv, vec4( cLodSizeInv, cLodSize ), ceil( lod ) );
		return mix( fSample, cSample, fract( lod ) );
	}
	vec3 getVolumeTransmissionRay( const in vec3 n, const in vec3 v, const in float thickness, const in float ior, const in mat4 modelMatrix ) {
		vec3 refractionVector = refract( - v, normalize( n ), 1.0 / ior );
		vec3 modelScale;
		modelScale.x = length( vec3( modelMatrix[ 0 ].xyz ) );
		modelScale.y = length( vec3( modelMatrix[ 1 ].xyz ) );
		modelScale.z = length( vec3( modelMatrix[ 2 ].xyz ) );
		return normalize( refractionVector ) * thickness * modelScale;
	}
	float applyIorToRoughness( const in float roughness, const in float ior ) {
		return roughness * clamp( ior * 2.0 - 2.0, 0.0, 1.0 );
	}
	vec4 getTransmissionSample( const in vec2 fragCoord, const in float roughness, const in float ior ) {
		float lod = log2( transmissionSamplerSize.x ) * applyIorToRoughness( roughness, ior );
		return textureBicubic( transmissionSamplerMap, fragCoord.xy, lod );
	}
	vec3 volumeAttenuation( const in float transmissionDistance, const in vec3 attenuationColor, const in float attenuationDistance ) {
		if ( isinf( attenuationDistance ) ) {
			return vec3( 1.0 );
		} else {
			vec3 attenuationCoefficient = -log( attenuationColor ) / attenuationDistance;
			vec3 transmittance = exp( - attenuationCoefficient * transmissionDistance );			return transmittance;
		}
	}
	vec4 getIBLVolumeRefraction( const in vec3 n, const in vec3 v, const in float roughness, const in vec3 diffuseColor,
		const in vec3 specularColor, const in float specularF90, const in vec3 position, const in mat4 modelMatrix,
		const in mat4 viewMatrix, const in mat4 projMatrix, const in float dispersion, const in float ior, const in float thickness,
		const in vec3 attenuationColor, const in float attenuationDistance ) {
		vec4 transmittedLight;
		vec3 transmittance;
		#ifdef USE_DISPERSION
			float halfSpread = ( ior - 1.0 ) * 0.025 * dispersion;
			vec3 iors = vec3( ior - halfSpread, ior, ior + halfSpread );
			for ( int i = 0; i < 3; i ++ ) {
				vec3 transmissionRay = getVolumeTransmissionRay( n, v, thickness, iors[ i ], modelMatrix );
				vec3 refractedRayExit = position + transmissionRay;
				vec4 ndcPos = projMatrix * viewMatrix * vec4( refractedRayExit, 1.0 );
				vec2 refractionCoords = ndcPos.xy / ndcPos.w;
				refractionCoords += 1.0;
				refractionCoords /= 2.0;
				vec4 transmissionSample = getTransmissionSample( refractionCoords, roughness, iors[ i ] );
				transmittedLight[ i ] = transmissionSample[ i ];
				transmittedLight.a += transmissionSample.a;
				transmittance[ i ] = diffuseColor[ i ] * volumeAttenuation( length( transmissionRay ), attenuationColor, attenuationDistance )[ i ];
			}
			transmittedLight.a /= 3.0;
		#else
			vec3 transmissionRay = getVolumeTransmissionRay( n, v, thickness, ior, modelMatrix );
			vec3 refractedRayExit = position + transmissionRay;
			vec4 ndcPos = projMatrix * viewMatrix * vec4( refractedRayExit, 1.0 );
			vec2 refractionCoords = ndcPos.xy / ndcPos.w;
			refractionCoords += 1.0;
			refractionCoords /= 2.0;
			transmittedLight = getTransmissionSample( refractionCoords, roughness, ior );
			transmittance = diffuseColor * volumeAttenuation( length( transmissionRay ), attenuationColor, attenuationDistance );
		#endif
		vec3 attenuatedColor = transmittance * transmittedLight.rgb;
		vec3 F = EnvironmentBRDF( n, v, specularColor, specularF90, roughness );
		float transmittanceFactor = ( transmittance.r + transmittance.g + transmittance.b ) / 3.0;
		return vec4( ( 1.0 - F ) * attenuatedColor, 1.0 - ( 1.0 - transmittedLight.a ) * transmittanceFactor );
	}
#endif`,$k=`#if defined( USE_UV ) || defined( USE_ANISOTROPY )
	varying vec2 vUv;
#endif
#ifdef USE_MAP
	varying vec2 vMapUv;
#endif
#ifdef USE_ALPHAMAP
	varying vec2 vAlphaMapUv;
#endif
#ifdef USE_LIGHTMAP
	varying vec2 vLightMapUv;
#endif
#ifdef USE_AOMAP
	varying vec2 vAoMapUv;
#endif
#ifdef USE_BUMPMAP
	varying vec2 vBumpMapUv;
#endif
#ifdef USE_NORMALMAP
	varying vec2 vNormalMapUv;
#endif
#ifdef USE_EMISSIVEMAP
	varying vec2 vEmissiveMapUv;
#endif
#ifdef USE_METALNESSMAP
	varying vec2 vMetalnessMapUv;
#endif
#ifdef USE_ROUGHNESSMAP
	varying vec2 vRoughnessMapUv;
#endif
#ifdef USE_ANISOTROPYMAP
	varying vec2 vAnisotropyMapUv;
#endif
#ifdef USE_CLEARCOATMAP
	varying vec2 vClearcoatMapUv;
#endif
#ifdef USE_CLEARCOAT_NORMALMAP
	varying vec2 vClearcoatNormalMapUv;
#endif
#ifdef USE_CLEARCOAT_ROUGHNESSMAP
	varying vec2 vClearcoatRoughnessMapUv;
#endif
#ifdef USE_IRIDESCENCEMAP
	varying vec2 vIridescenceMapUv;
#endif
#ifdef USE_IRIDESCENCE_THICKNESSMAP
	varying vec2 vIridescenceThicknessMapUv;
#endif
#ifdef USE_SHEEN_COLORMAP
	varying vec2 vSheenColorMapUv;
#endif
#ifdef USE_SHEEN_ROUGHNESSMAP
	varying vec2 vSheenRoughnessMapUv;
#endif
#ifdef USE_SPECULARMAP
	varying vec2 vSpecularMapUv;
#endif
#ifdef USE_SPECULAR_COLORMAP
	varying vec2 vSpecularColorMapUv;
#endif
#ifdef USE_SPECULAR_INTENSITYMAP
	varying vec2 vSpecularIntensityMapUv;
#endif
#ifdef USE_TRANSMISSIONMAP
	uniform mat3 transmissionMapTransform;
	varying vec2 vTransmissionMapUv;
#endif
#ifdef USE_THICKNESSMAP
	uniform mat3 thicknessMapTransform;
	varying vec2 vThicknessMapUv;
#endif`,eV=`#if defined( USE_UV ) || defined( USE_ANISOTROPY )
	varying vec2 vUv;
#endif
#ifdef USE_MAP
	uniform mat3 mapTransform;
	varying vec2 vMapUv;
#endif
#ifdef USE_ALPHAMAP
	uniform mat3 alphaMapTransform;
	varying vec2 vAlphaMapUv;
#endif
#ifdef USE_LIGHTMAP
	uniform mat3 lightMapTransform;
	varying vec2 vLightMapUv;
#endif
#ifdef USE_AOMAP
	uniform mat3 aoMapTransform;
	varying vec2 vAoMapUv;
#endif
#ifdef USE_BUMPMAP
	uniform mat3 bumpMapTransform;
	varying vec2 vBumpMapUv;
#endif
#ifdef USE_NORMALMAP
	uniform mat3 normalMapTransform;
	varying vec2 vNormalMapUv;
#endif
#ifdef USE_DISPLACEMENTMAP
	uniform mat3 displacementMapTransform;
	varying vec2 vDisplacementMapUv;
#endif
#ifdef USE_EMISSIVEMAP
	uniform mat3 emissiveMapTransform;
	varying vec2 vEmissiveMapUv;
#endif
#ifdef USE_METALNESSMAP
	uniform mat3 metalnessMapTransform;
	varying vec2 vMetalnessMapUv;
#endif
#ifdef USE_ROUGHNESSMAP
	uniform mat3 roughnessMapTransform;
	varying vec2 vRoughnessMapUv;
#endif
#ifdef USE_ANISOTROPYMAP
	uniform mat3 anisotropyMapTransform;
	varying vec2 vAnisotropyMapUv;
#endif
#ifdef USE_CLEARCOATMAP
	uniform mat3 clearcoatMapTransform;
	varying vec2 vClearcoatMapUv;
#endif
#ifdef USE_CLEARCOAT_NORMALMAP
	uniform mat3 clearcoatNormalMapTransform;
	varying vec2 vClearcoatNormalMapUv;
#endif
#ifdef USE_CLEARCOAT_ROUGHNESSMAP
	uniform mat3 clearcoatRoughnessMapTransform;
	varying vec2 vClearcoatRoughnessMapUv;
#endif
#ifdef USE_SHEEN_COLORMAP
	uniform mat3 sheenColorMapTransform;
	varying vec2 vSheenColorMapUv;
#endif
#ifdef USE_SHEEN_ROUGHNESSMAP
	uniform mat3 sheenRoughnessMapTransform;
	varying vec2 vSheenRoughnessMapUv;
#endif
#ifdef USE_IRIDESCENCEMAP
	uniform mat3 iridescenceMapTransform;
	varying vec2 vIridescenceMapUv;
#endif
#ifdef USE_IRIDESCENCE_THICKNESSMAP
	uniform mat3 iridescenceThicknessMapTransform;
	varying vec2 vIridescenceThicknessMapUv;
#endif
#ifdef USE_SPECULARMAP
	uniform mat3 specularMapTransform;
	varying vec2 vSpecularMapUv;
#endif
#ifdef USE_SPECULAR_COLORMAP
	uniform mat3 specularColorMapTransform;
	varying vec2 vSpecularColorMapUv;
#endif
#ifdef USE_SPECULAR_INTENSITYMAP
	uniform mat3 specularIntensityMapTransform;
	varying vec2 vSpecularIntensityMapUv;
#endif
#ifdef USE_TRANSMISSIONMAP
	uniform mat3 transmissionMapTransform;
	varying vec2 vTransmissionMapUv;
#endif
#ifdef USE_THICKNESSMAP
	uniform mat3 thicknessMapTransform;
	varying vec2 vThicknessMapUv;
#endif`,tV=`#if defined( USE_UV ) || defined( USE_ANISOTROPY )
	vUv = vec3( uv, 1 ).xy;
#endif
#ifdef USE_MAP
	vMapUv = ( mapTransform * vec3( MAP_UV, 1 ) ).xy;
#endif
#ifdef USE_ALPHAMAP
	vAlphaMapUv = ( alphaMapTransform * vec3( ALPHAMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_LIGHTMAP
	vLightMapUv = ( lightMapTransform * vec3( LIGHTMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_AOMAP
	vAoMapUv = ( aoMapTransform * vec3( AOMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_BUMPMAP
	vBumpMapUv = ( bumpMapTransform * vec3( BUMPMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_NORMALMAP
	vNormalMapUv = ( normalMapTransform * vec3( NORMALMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_DISPLACEMENTMAP
	vDisplacementMapUv = ( displacementMapTransform * vec3( DISPLACEMENTMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_EMISSIVEMAP
	vEmissiveMapUv = ( emissiveMapTransform * vec3( EMISSIVEMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_METALNESSMAP
	vMetalnessMapUv = ( metalnessMapTransform * vec3( METALNESSMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_ROUGHNESSMAP
	vRoughnessMapUv = ( roughnessMapTransform * vec3( ROUGHNESSMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_ANISOTROPYMAP
	vAnisotropyMapUv = ( anisotropyMapTransform * vec3( ANISOTROPYMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_CLEARCOATMAP
	vClearcoatMapUv = ( clearcoatMapTransform * vec3( CLEARCOATMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_CLEARCOAT_NORMALMAP
	vClearcoatNormalMapUv = ( clearcoatNormalMapTransform * vec3( CLEARCOAT_NORMALMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_CLEARCOAT_ROUGHNESSMAP
	vClearcoatRoughnessMapUv = ( clearcoatRoughnessMapTransform * vec3( CLEARCOAT_ROUGHNESSMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_IRIDESCENCEMAP
	vIridescenceMapUv = ( iridescenceMapTransform * vec3( IRIDESCENCEMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_IRIDESCENCE_THICKNESSMAP
	vIridescenceThicknessMapUv = ( iridescenceThicknessMapTransform * vec3( IRIDESCENCE_THICKNESSMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_SHEEN_COLORMAP
	vSheenColorMapUv = ( sheenColorMapTransform * vec3( SHEEN_COLORMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_SHEEN_ROUGHNESSMAP
	vSheenRoughnessMapUv = ( sheenRoughnessMapTransform * vec3( SHEEN_ROUGHNESSMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_SPECULARMAP
	vSpecularMapUv = ( specularMapTransform * vec3( SPECULARMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_SPECULAR_COLORMAP
	vSpecularColorMapUv = ( specularColorMapTransform * vec3( SPECULAR_COLORMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_SPECULAR_INTENSITYMAP
	vSpecularIntensityMapUv = ( specularIntensityMapTransform * vec3( SPECULAR_INTENSITYMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_TRANSMISSIONMAP
	vTransmissionMapUv = ( transmissionMapTransform * vec3( TRANSMISSIONMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_THICKNESSMAP
	vThicknessMapUv = ( thicknessMapTransform * vec3( THICKNESSMAP_UV, 1 ) ).xy;
#endif`,nV=`#if defined( USE_ENVMAP ) || defined( DISTANCE ) || defined ( USE_SHADOWMAP ) || defined ( USE_TRANSMISSION ) || NUM_SPOT_LIGHT_COORDS > 0
	vec4 worldPosition = vec4( transformed, 1.0 );
	#ifdef USE_BATCHING
		worldPosition = batchingMatrix * worldPosition;
	#endif
	#ifdef USE_INSTANCING
		worldPosition = instanceMatrix * worldPosition;
	#endif
	worldPosition = modelMatrix * worldPosition;
#endif`;const is={alphahash_fragment:iU,alphahash_pars_fragment:sU,alphamap_fragment:aU,alphamap_pars_fragment:oU,alphatest_fragment:lU,alphatest_pars_fragment:uU,aomap_fragment:cU,aomap_pars_fragment:dU,batching_pars_vertex:fU,batching_vertex:hU,begin_vertex:pU,beginnormal_vertex:mU,bsdfs:gU,iridescence_fragment:vU,bumpmap_pars_fragment:AU,clipping_planes_fragment:xU,clipping_planes_pars_fragment:yU,clipping_planes_pars_vertex:bU,clipping_planes_vertex:EU,color_fragment:wU,color_pars_fragment:CU,color_pars_vertex:PU,color_vertex:BU,common:MU,cube_uv_reflection_fragment:SU,defaultnormal_vertex:DU,displacementmap_pars_vertex:TU,displacementmap_vertex:IU,emissivemap_fragment:NU,emissivemap_pars_fragment:FU,colorspace_fragment:RU,colorspace_pars_fragment:LU,envmap_fragment:OU,envmap_common_pars_fragment:zU,envmap_pars_fragment:HU,envmap_pars_vertex:UU,envmap_physical_pars_fragment:KU,envmap_vertex:kU,fog_vertex:VU,fog_pars_vertex:jU,fog_fragment:XU,fog_pars_fragment:GU,gradientmap_pars_fragment:WU,lightmap_pars_fragment:QU,lights_lambert_fragment:ZU,lights_lambert_pars_fragment:YU,lights_pars_begin:JU,lights_toon_fragment:qU,lights_toon_pars_fragment:_U,lights_phong_fragment:$U,lights_phong_pars_fragment:ek,lights_physical_fragment:tk,lights_physical_pars_fragment:nk,lights_fragment_begin:rk,lights_fragment_maps:ik,lights_fragment_end:sk,logdepthbuf_fragment:ak,logdepthbuf_pars_fragment:ok,logdepthbuf_pars_vertex:lk,logdepthbuf_vertex:uk,map_fragment:ck,map_pars_fragment:dk,map_particle_fragment:fk,map_particle_pars_fragment:hk,metalnessmap_fragment:pk,metalnessmap_pars_fragment:mk,morphinstance_vertex:gk,morphcolor_vertex:vk,morphnormal_vertex:Ak,morphtarget_pars_vertex:xk,morphtarget_vertex:yk,normal_fragment_begin:bk,normal_fragment_maps:Ek,normal_pars_fragment:wk,normal_pars_vertex:Ck,normal_vertex:Pk,normalmap_pars_fragment:Bk,clearcoat_normal_fragment_begin:Mk,clearcoat_normal_fragment_maps:Sk,clearcoat_pars_fragment:Dk,iridescence_pars_fragment:Tk,opaque_fragment:Ik,packing:Nk,premultiplied_alpha_fragment:Fk,project_vertex:Rk,dithering_fragment:Lk,dithering_pars_fragment:Ok,roughnessmap_fragment:zk,roughnessmap_pars_fragment:Hk,shadowmap_pars_fragment:Uk,shadowmap_pars_vertex:kk,shadowmap_vertex:Vk,shadowmask_pars_fragment:jk,skinbase_vertex:Xk,skinning_pars_vertex:Gk,skinning_vertex:Wk,skinnormal_vertex:Qk,specularmap_fragment:Zk,specularmap_pars_fragment:Yk,tonemapping_fragment:Jk,tonemapping_pars_fragment:Kk,transmission_fragment:qk,transmission_pars_fragment:_k,uv_pars_fragment:$k,uv_pars_vertex:eV,uv_vertex:tV,worldpos_vertex:nV,background_vert:`varying vec2 vUv;
uniform mat3 uvTransform;
void main() {
	vUv = ( uvTransform * vec3( uv, 1 ) ).xy;
	gl_Position = vec4( position.xy, 1.0, 1.0 );
}`,background_frag:`uniform sampler2D t2D;
uniform float backgroundIntensity;
varying vec2 vUv;
void main() {
	vec4 texColor = texture2D( t2D, vUv );
	#ifdef DECODE_VIDEO_TEXTURE
		texColor = 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 );
	#endif
	texColor.rgb *= backgroundIntensity;
	gl_FragColor = texColor;
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
}`,backgroundCube_vert:`varying vec3 vWorldDirection;
#include <common>
void main() {
	vWorldDirection = transformDirection( position, modelMatrix );
	#include <begin_vertex>
	#include <project_vertex>
	gl_Position.z = gl_Position.w;
}`,backgroundCube_frag:`#ifdef ENVMAP_TYPE_CUBE
	uniform samplerCube envMap;
#elif defined( ENVMAP_TYPE_CUBE_UV )
	uniform sampler2D envMap;
#endif
uniform float flipEnvMap;
uniform float backgroundBlurriness;
uniform float backgroundIntensity;
uniform mat3 backgroundRotation;
varying vec3 vWorldDirection;
#include <cube_uv_reflection_fragment>
void main() {
	#ifdef ENVMAP_TYPE_CUBE
		vec4 texColor = textureCube( envMap, backgroundRotation * vec3( flipEnvMap * vWorldDirection.x, vWorldDirection.yz ) );
	#elif defined( ENVMAP_TYPE_CUBE_UV )
		vec4 texColor = textureCubeUV( envMap, backgroundRotation * vWorldDirection, backgroundBlurriness );
	#else
		vec4 texColor = vec4( 0.0, 0.0, 0.0, 1.0 );
	#endif
	texColor.rgb *= backgroundIntensity;
	gl_FragColor = texColor;
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
}`,cube_vert:`varying vec3 vWorldDirection;
#include <common>
void main() {
	vWorldDirection = transformDirection( position, modelMatrix );
	#include <begin_vertex>
	#include <project_vertex>
	gl_Position.z = gl_Position.w;
}`,cube_frag:`uniform samplerCube tCube;
uniform float tFlip;
uniform float opacity;
varying vec3 vWorldDirection;
void main() {
	vec4 texColor = textureCube( tCube, vec3( tFlip * vWorldDirection.x, vWorldDirection.yz ) );
	gl_FragColor = texColor;
	gl_FragColor.a *= opacity;
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
}`,depth_vert:`#include <common>
#include <batching_pars_vertex>
#include <uv_pars_vertex>
#include <displacementmap_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
varying vec2 vHighPrecisionZW;
void main() {
	#include <uv_vertex>
	#include <batching_vertex>
	#include <skinbase_vertex>
	#include <morphinstance_vertex>
	#ifdef USE_DISPLACEMENTMAP
		#include <beginnormal_vertex>
		#include <morphnormal_vertex>
		#include <skinnormal_vertex>
	#endif
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <displacementmap_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	vHighPrecisionZW = gl_Position.zw;
}`,depth_frag:`#if DEPTH_PACKING == 3200
	uniform float opacity;
#endif
#include <common>
#include <packing>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <alphamap_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
varying vec2 vHighPrecisionZW;
void main() {
	vec4 diffuseColor = vec4( 1.0 );
	#include <clipping_planes_fragment>
	#if DEPTH_PACKING == 3200
		diffuseColor.a = opacity;
	#endif
	#include <map_fragment>
	#include <alphamap_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	#include <logdepthbuf_fragment>
	#ifdef USE_REVERSED_DEPTH_BUFFER
		float fragCoordZ = vHighPrecisionZW[ 0 ] / vHighPrecisionZW[ 1 ];
	#else
		float fragCoordZ = 0.5 * vHighPrecisionZW[ 0 ] / vHighPrecisionZW[ 1 ] + 0.5;
	#endif
	#if DEPTH_PACKING == 3200
		gl_FragColor = vec4( vec3( 1.0 - fragCoordZ ), opacity );
	#elif DEPTH_PACKING == 3201
		gl_FragColor = packDepthToRGBA( fragCoordZ );
	#elif DEPTH_PACKING == 3202
		gl_FragColor = vec4( packDepthToRGB( fragCoordZ ), 1.0 );
	#elif DEPTH_PACKING == 3203
		gl_FragColor = vec4( packDepthToRG( fragCoordZ ), 0.0, 1.0 );
	#endif
}`,distance_vert:`#define DISTANCE
varying vec3 vWorldPosition;
#include <common>
#include <batching_pars_vertex>
#include <uv_pars_vertex>
#include <displacementmap_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	#include <uv_vertex>
	#include <batching_vertex>
	#include <skinbase_vertex>
	#include <morphinstance_vertex>
	#ifdef USE_DISPLACEMENTMAP
		#include <beginnormal_vertex>
		#include <morphnormal_vertex>
		#include <skinnormal_vertex>
	#endif
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <displacementmap_vertex>
	#include <project_vertex>
	#include <worldpos_vertex>
	#include <clipping_planes_vertex>
	vWorldPosition = worldPosition.xyz;
}`,distance_frag:`#define DISTANCE
uniform vec3 referencePosition;
uniform float nearDistance;
uniform float farDistance;
varying vec3 vWorldPosition;
#include <common>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <alphamap_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <clipping_planes_pars_fragment>
void main () {
	vec4 diffuseColor = vec4( 1.0 );
	#include <clipping_planes_fragment>
	#include <map_fragment>
	#include <alphamap_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	float dist = length( vWorldPosition - referencePosition );
	dist = ( dist - nearDistance ) / ( farDistance - nearDistance );
	dist = saturate( dist );
	gl_FragColor = vec4( dist, 0.0, 0.0, 1.0 );
}`,equirect_vert:`varying vec3 vWorldDirection;
#include <common>
void main() {
	vWorldDirection = transformDirection( position, modelMatrix );
	#include <begin_vertex>
	#include <project_vertex>
}`,equirect_frag:`uniform sampler2D tEquirect;
varying vec3 vWorldDirection;
#include <common>
void main() {
	vec3 direction = normalize( vWorldDirection );
	vec2 sampleUV = equirectUv( direction );
	gl_FragColor = texture2D( tEquirect, sampleUV );
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
}`,linedashed_vert:`uniform float scale;
attribute float lineDistance;
varying float vLineDistance;
#include <common>
#include <uv_pars_vertex>
#include <color_pars_vertex>
#include <fog_pars_vertex>
#include <morphtarget_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	vLineDistance = scale * lineDistance;
	#include <uv_vertex>
	#include <color_vertex>
	#include <morphinstance_vertex>
	#include <morphcolor_vertex>
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	#include <fog_vertex>
}`,linedashed_frag:`uniform vec3 diffuse;
uniform float opacity;
uniform float dashSize;
uniform float totalSize;
varying float vLineDistance;
#include <common>
#include <color_pars_fragment>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <fog_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	vec4 diffuseColor = vec4( diffuse, opacity );
	#include <clipping_planes_fragment>
	if ( mod( vLineDistance, totalSize ) > dashSize ) {
		discard;
	}
	vec3 outgoingLight = vec3( 0.0 );
	#include <logdepthbuf_fragment>
	#include <map_fragment>
	#include <color_fragment>
	outgoingLight = diffuseColor.rgb;
	#include <opaque_fragment>
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
	#include <premultiplied_alpha_fragment>
}`,meshbasic_vert:`#include <common>
#include <batching_pars_vertex>
#include <uv_pars_vertex>
#include <envmap_pars_vertex>
#include <color_pars_vertex>
#include <fog_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	#include <uv_vertex>
	#include <color_vertex>
	#include <morphinstance_vertex>
	#include <morphcolor_vertex>
	#include <batching_vertex>
	#if defined ( USE_ENVMAP ) || defined ( USE_SKINNING )
		#include <beginnormal_vertex>
		#include <morphnormal_vertex>
		#include <skinbase_vertex>
		#include <skinnormal_vertex>
		#include <defaultnormal_vertex>
	#endif
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	#include <worldpos_vertex>
	#include <envmap_vertex>
	#include <fog_vertex>
}`,meshbasic_frag:`uniform vec3 diffuse;
uniform float opacity;
#ifndef FLAT_SHADED
	varying vec3 vNormal;
#endif
#include <common>
#include <dithering_pars_fragment>
#include <color_pars_fragment>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <alphamap_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <aomap_pars_fragment>
#include <lightmap_pars_fragment>
#include <envmap_common_pars_fragment>
#include <envmap_pars_fragment>
#include <fog_pars_fragment>
#include <specularmap_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	vec4 diffuseColor = vec4( diffuse, opacity );
	#include <clipping_planes_fragment>
	#include <logdepthbuf_fragment>
	#include <map_fragment>
	#include <color_fragment>
	#include <alphamap_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	#include <specularmap_fragment>
	ReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );
	#ifdef USE_LIGHTMAP
		vec4 lightMapTexel = texture2D( lightMap, vLightMapUv );
		reflectedLight.indirectDiffuse += lightMapTexel.rgb * lightMapIntensity * RECIPROCAL_PI;
	#else
		reflectedLight.indirectDiffuse += vec3( 1.0 );
	#endif
	#include <aomap_fragment>
	reflectedLight.indirectDiffuse *= diffuseColor.rgb;
	vec3 outgoingLight = reflectedLight.indirectDiffuse;
	#include <envmap_fragment>
	#include <opaque_fragment>
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
	#include <premultiplied_alpha_fragment>
	#include <dithering_fragment>
}`,meshlambert_vert:`#define LAMBERT
varying vec3 vViewPosition;
#include <common>
#include <batching_pars_vertex>
#include <uv_pars_vertex>
#include <displacementmap_pars_vertex>
#include <envmap_pars_vertex>
#include <color_pars_vertex>
#include <fog_pars_vertex>
#include <normal_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <shadowmap_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	#include <uv_vertex>
	#include <color_vertex>
	#include <morphinstance_vertex>
	#include <morphcolor_vertex>
	#include <batching_vertex>
	#include <beginnormal_vertex>
	#include <morphnormal_vertex>
	#include <skinbase_vertex>
	#include <skinnormal_vertex>
	#include <defaultnormal_vertex>
	#include <normal_vertex>
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <displacementmap_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	vViewPosition = - mvPosition.xyz;
	#include <worldpos_vertex>
	#include <envmap_vertex>
	#include <shadowmap_vertex>
	#include <fog_vertex>
}`,meshlambert_frag:`#define LAMBERT
uniform vec3 diffuse;
uniform vec3 emissive;
uniform float opacity;
#include <common>
#include <dithering_pars_fragment>
#include <color_pars_fragment>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <alphamap_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <aomap_pars_fragment>
#include <lightmap_pars_fragment>
#include <emissivemap_pars_fragment>
#include <envmap_common_pars_fragment>
#include <envmap_pars_fragment>
#include <fog_pars_fragment>
#include <bsdfs>
#include <lights_pars_begin>
#include <normal_pars_fragment>
#include <lights_lambert_pars_fragment>
#include <shadowmap_pars_fragment>
#include <bumpmap_pars_fragment>
#include <normalmap_pars_fragment>
#include <specularmap_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	vec4 diffuseColor = vec4( diffuse, opacity );
	#include <clipping_planes_fragment>
	ReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );
	vec3 totalEmissiveRadiance = emissive;
	#include <logdepthbuf_fragment>
	#include <map_fragment>
	#include <color_fragment>
	#include <alphamap_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	#include <specularmap_fragment>
	#include <normal_fragment_begin>
	#include <normal_fragment_maps>
	#include <emissivemap_fragment>
	#include <lights_lambert_fragment>
	#include <lights_fragment_begin>
	#include <lights_fragment_maps>
	#include <lights_fragment_end>
	#include <aomap_fragment>
	vec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;
	#include <envmap_fragment>
	#include <opaque_fragment>
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
	#include <premultiplied_alpha_fragment>
	#include <dithering_fragment>
}`,meshmatcap_vert:`#define MATCAP
varying vec3 vViewPosition;
#include <common>
#include <batching_pars_vertex>
#include <uv_pars_vertex>
#include <color_pars_vertex>
#include <displacementmap_pars_vertex>
#include <fog_pars_vertex>
#include <normal_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	#include <uv_vertex>
	#include <color_vertex>
	#include <morphinstance_vertex>
	#include <morphcolor_vertex>
	#include <batching_vertex>
	#include <beginnormal_vertex>
	#include <morphnormal_vertex>
	#include <skinbase_vertex>
	#include <skinnormal_vertex>
	#include <defaultnormal_vertex>
	#include <normal_vertex>
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <displacementmap_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	#include <fog_vertex>
	vViewPosition = - mvPosition.xyz;
}`,meshmatcap_frag:`#define MATCAP
uniform vec3 diffuse;
uniform float opacity;
uniform sampler2D matcap;
varying vec3 vViewPosition;
#include <common>
#include <dithering_pars_fragment>
#include <color_pars_fragment>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <alphamap_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <fog_pars_fragment>
#include <normal_pars_fragment>
#include <bumpmap_pars_fragment>
#include <normalmap_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	vec4 diffuseColor = vec4( diffuse, opacity );
	#include <clipping_planes_fragment>
	#include <logdepthbuf_fragment>
	#include <map_fragment>
	#include <color_fragment>
	#include <alphamap_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	#include <normal_fragment_begin>
	#include <normal_fragment_maps>
	vec3 viewDir = normalize( vViewPosition );
	vec3 x = normalize( vec3( viewDir.z, 0.0, - viewDir.x ) );
	vec3 y = cross( viewDir, x );
	vec2 uv = vec2( dot( x, normal ), dot( y, normal ) ) * 0.495 + 0.5;
	#ifdef USE_MATCAP
		vec4 matcapColor = texture2D( matcap, uv );
	#else
		vec4 matcapColor = vec4( vec3( mix( 0.2, 0.8, uv.y ) ), 1.0 );
	#endif
	vec3 outgoingLight = diffuseColor.rgb * matcapColor.rgb;
	#include <opaque_fragment>
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
	#include <premultiplied_alpha_fragment>
	#include <dithering_fragment>
}`,meshnormal_vert:`#define NORMAL
#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( USE_NORMALMAP_TANGENTSPACE )
	varying vec3 vViewPosition;
#endif
#include <common>
#include <batching_pars_vertex>
#include <uv_pars_vertex>
#include <displacementmap_pars_vertex>
#include <normal_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	#include <uv_vertex>
	#include <batching_vertex>
	#include <beginnormal_vertex>
	#include <morphinstance_vertex>
	#include <morphnormal_vertex>
	#include <skinbase_vertex>
	#include <skinnormal_vertex>
	#include <defaultnormal_vertex>
	#include <normal_vertex>
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <displacementmap_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( USE_NORMALMAP_TANGENTSPACE )
	vViewPosition = - mvPosition.xyz;
#endif
}`,meshnormal_frag:`#define NORMAL
uniform float opacity;
#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( USE_NORMALMAP_TANGENTSPACE )
	varying vec3 vViewPosition;
#endif
#include <uv_pars_fragment>
#include <normal_pars_fragment>
#include <bumpmap_pars_fragment>
#include <normalmap_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	vec4 diffuseColor = vec4( 0.0, 0.0, 0.0, opacity );
	#include <clipping_planes_fragment>
	#include <logdepthbuf_fragment>
	#include <normal_fragment_begin>
	#include <normal_fragment_maps>
	gl_FragColor = vec4( normalize( normal ) * 0.5 + 0.5, diffuseColor.a );
	#ifdef OPAQUE
		gl_FragColor.a = 1.0;
	#endif
}`,meshphong_vert:`#define PHONG
varying vec3 vViewPosition;
#include <common>
#include <batching_pars_vertex>
#include <uv_pars_vertex>
#include <displacementmap_pars_vertex>
#include <envmap_pars_vertex>
#include <color_pars_vertex>
#include <fog_pars_vertex>
#include <normal_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <shadowmap_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	#include <uv_vertex>
	#include <color_vertex>
	#include <morphcolor_vertex>
	#include <batching_vertex>
	#include <beginnormal_vertex>
	#include <morphinstance_vertex>
	#include <morphnormal_vertex>
	#include <skinbase_vertex>
	#include <skinnormal_vertex>
	#include <defaultnormal_vertex>
	#include <normal_vertex>
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <displacementmap_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	vViewPosition = - mvPosition.xyz;
	#include <worldpos_vertex>
	#include <envmap_vertex>
	#include <shadowmap_vertex>
	#include <fog_vertex>
}`,meshphong_frag:`#define PHONG
uniform vec3 diffuse;
uniform vec3 emissive;
uniform vec3 specular;
uniform float shininess;
uniform float opacity;
#include <common>
#include <dithering_pars_fragment>
#include <color_pars_fragment>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <alphamap_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <aomap_pars_fragment>
#include <lightmap_pars_fragment>
#include <emissivemap_pars_fragment>
#include <envmap_common_pars_fragment>
#include <envmap_pars_fragment>
#include <fog_pars_fragment>
#include <bsdfs>
#include <lights_pars_begin>
#include <normal_pars_fragment>
#include <lights_phong_pars_fragment>
#include <shadowmap_pars_fragment>
#include <bumpmap_pars_fragment>
#include <normalmap_pars_fragment>
#include <specularmap_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	vec4 diffuseColor = vec4( diffuse, opacity );
	#include <clipping_planes_fragment>
	ReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );
	vec3 totalEmissiveRadiance = emissive;
	#include <logdepthbuf_fragment>
	#include <map_fragment>
	#include <color_fragment>
	#include <alphamap_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	#include <specularmap_fragment>
	#include <normal_fragment_begin>
	#include <normal_fragment_maps>
	#include <emissivemap_fragment>
	#include <lights_phong_fragment>
	#include <lights_fragment_begin>
	#include <lights_fragment_maps>
	#include <lights_fragment_end>
	#include <aomap_fragment>
	vec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + reflectedLight.directSpecular + reflectedLight.indirectSpecular + totalEmissiveRadiance;
	#include <envmap_fragment>
	#include <opaque_fragment>
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
	#include <premultiplied_alpha_fragment>
	#include <dithering_fragment>
}`,meshphysical_vert:`#define STANDARD
varying vec3 vViewPosition;
#ifdef USE_TRANSMISSION
	varying vec3 vWorldPosition;
#endif
#include <common>
#include <batching_pars_vertex>
#include <uv_pars_vertex>
#include <displacementmap_pars_vertex>
#include <color_pars_vertex>
#include <fog_pars_vertex>
#include <normal_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <shadowmap_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	#include <uv_vertex>
	#include <color_vertex>
	#include <morphinstance_vertex>
	#include <morphcolor_vertex>
	#include <batching_vertex>
	#include <beginnormal_vertex>
	#include <morphnormal_vertex>
	#include <skinbase_vertex>
	#include <skinnormal_vertex>
	#include <defaultnormal_vertex>
	#include <normal_vertex>
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <displacementmap_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	vViewPosition = - mvPosition.xyz;
	#include <worldpos_vertex>
	#include <shadowmap_vertex>
	#include <fog_vertex>
#ifdef USE_TRANSMISSION
	vWorldPosition = worldPosition.xyz;
#endif
}`,meshphysical_frag:`#define STANDARD
#ifdef PHYSICAL
	#define IOR
	#define USE_SPECULAR
#endif
uniform vec3 diffuse;
uniform vec3 emissive;
uniform float roughness;
uniform float metalness;
uniform float opacity;
#ifdef IOR
	uniform float ior;
#endif
#ifdef USE_SPECULAR
	uniform float specularIntensity;
	uniform vec3 specularColor;
	#ifdef USE_SPECULAR_COLORMAP
		uniform sampler2D specularColorMap;
	#endif
	#ifdef USE_SPECULAR_INTENSITYMAP
		uniform sampler2D specularIntensityMap;
	#endif
#endif
#ifdef USE_CLEARCOAT
	uniform float clearcoat;
	uniform float clearcoatRoughness;
#endif
#ifdef USE_DISPERSION
	uniform float dispersion;
#endif
#ifdef USE_IRIDESCENCE
	uniform float iridescence;
	uniform float iridescenceIOR;
	uniform float iridescenceThicknessMinimum;
	uniform float iridescenceThicknessMaximum;
#endif
#ifdef USE_SHEEN
	uniform vec3 sheenColor;
	uniform float sheenRoughness;
	#ifdef USE_SHEEN_COLORMAP
		uniform sampler2D sheenColorMap;
	#endif
	#ifdef USE_SHEEN_ROUGHNESSMAP
		uniform sampler2D sheenRoughnessMap;
	#endif
#endif
#ifdef USE_ANISOTROPY
	uniform vec2 anisotropyVector;
	#ifdef USE_ANISOTROPYMAP
		uniform sampler2D anisotropyMap;
	#endif
#endif
varying vec3 vViewPosition;
#include <common>
#include <dithering_pars_fragment>
#include <color_pars_fragment>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <alphamap_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <aomap_pars_fragment>
#include <lightmap_pars_fragment>
#include <emissivemap_pars_fragment>
#include <iridescence_fragment>
#include <cube_uv_reflection_fragment>
#include <envmap_common_pars_fragment>
#include <envmap_physical_pars_fragment>
#include <fog_pars_fragment>
#include <lights_pars_begin>
#include <normal_pars_fragment>
#include <lights_physical_pars_fragment>
#include <transmission_pars_fragment>
#include <shadowmap_pars_fragment>
#include <bumpmap_pars_fragment>
#include <normalmap_pars_fragment>
#include <clearcoat_pars_fragment>
#include <iridescence_pars_fragment>
#include <roughnessmap_pars_fragment>
#include <metalnessmap_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	vec4 diffuseColor = vec4( diffuse, opacity );
	#include <clipping_planes_fragment>
	ReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );
	vec3 totalEmissiveRadiance = emissive;
	#include <logdepthbuf_fragment>
	#include <map_fragment>
	#include <color_fragment>
	#include <alphamap_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	#include <roughnessmap_fragment>
	#include <metalnessmap_fragment>
	#include <normal_fragment_begin>
	#include <normal_fragment_maps>
	#include <clearcoat_normal_fragment_begin>
	#include <clearcoat_normal_fragment_maps>
	#include <emissivemap_fragment>
	#include <lights_physical_fragment>
	#include <lights_fragment_begin>
	#include <lights_fragment_maps>
	#include <lights_fragment_end>
	#include <aomap_fragment>
	vec3 totalDiffuse = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse;
	vec3 totalSpecular = reflectedLight.directSpecular + reflectedLight.indirectSpecular;
	#include <transmission_fragment>
	vec3 outgoingLight = totalDiffuse + totalSpecular + totalEmissiveRadiance;
	#ifdef USE_SHEEN
 
		outgoingLight = outgoingLight + sheenSpecularDirect + sheenSpecularIndirect;
 
 	#endif
	#ifdef USE_CLEARCOAT
		float dotNVcc = saturate( dot( geometryClearcoatNormal, geometryViewDir ) );
		vec3 Fcc = F_Schlick( material.clearcoatF0, material.clearcoatF90, dotNVcc );
		outgoingLight = outgoingLight * ( 1.0 - material.clearcoat * Fcc ) + ( clearcoatSpecularDirect + clearcoatSpecularIndirect ) * material.clearcoat;
	#endif
	#include <opaque_fragment>
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
	#include <premultiplied_alpha_fragment>
	#include <dithering_fragment>
}`,meshtoon_vert:`#define TOON
varying vec3 vViewPosition;
#include <common>
#include <batching_pars_vertex>
#include <uv_pars_vertex>
#include <displacementmap_pars_vertex>
#include <color_pars_vertex>
#include <fog_pars_vertex>
#include <normal_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <shadowmap_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	#include <uv_vertex>
	#include <color_vertex>
	#include <morphinstance_vertex>
	#include <morphcolor_vertex>
	#include <batching_vertex>
	#include <beginnormal_vertex>
	#include <morphnormal_vertex>
	#include <skinbase_vertex>
	#include <skinnormal_vertex>
	#include <defaultnormal_vertex>
	#include <normal_vertex>
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <displacementmap_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	vViewPosition = - mvPosition.xyz;
	#include <worldpos_vertex>
	#include <shadowmap_vertex>
	#include <fog_vertex>
}`,meshtoon_frag:`#define TOON
uniform vec3 diffuse;
uniform vec3 emissive;
uniform float opacity;
#include <common>
#include <dithering_pars_fragment>
#include <color_pars_fragment>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <alphamap_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <aomap_pars_fragment>
#include <lightmap_pars_fragment>
#include <emissivemap_pars_fragment>
#include <gradientmap_pars_fragment>
#include <fog_pars_fragment>
#include <bsdfs>
#include <lights_pars_begin>
#include <normal_pars_fragment>
#include <lights_toon_pars_fragment>
#include <shadowmap_pars_fragment>
#include <bumpmap_pars_fragment>
#include <normalmap_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	vec4 diffuseColor = vec4( diffuse, opacity );
	#include <clipping_planes_fragment>
	ReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );
	vec3 totalEmissiveRadiance = emissive;
	#include <logdepthbuf_fragment>
	#include <map_fragment>
	#include <color_fragment>
	#include <alphamap_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	#include <normal_fragment_begin>
	#include <normal_fragment_maps>
	#include <emissivemap_fragment>
	#include <lights_toon_fragment>
	#include <lights_fragment_begin>
	#include <lights_fragment_maps>
	#include <lights_fragment_end>
	#include <aomap_fragment>
	vec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;
	#include <opaque_fragment>
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
	#include <premultiplied_alpha_fragment>
	#include <dithering_fragment>
}`,points_vert:`uniform float size;
uniform float scale;
#include <common>
#include <color_pars_vertex>
#include <fog_pars_vertex>
#include <morphtarget_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
#ifdef USE_POINTS_UV
	varying vec2 vUv;
	uniform mat3 uvTransform;
#endif
void main() {
	#ifdef USE_POINTS_UV
		vUv = ( uvTransform * vec3( uv, 1 ) ).xy;
	#endif
	#include <color_vertex>
	#include <morphinstance_vertex>
	#include <morphcolor_vertex>
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <project_vertex>
	gl_PointSize = size;
	#ifdef USE_SIZEATTENUATION
		bool isPerspective = isPerspectiveMatrix( projectionMatrix );
		if ( isPerspective ) gl_PointSize *= ( scale / - mvPosition.z );
	#endif
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	#include <worldpos_vertex>
	#include <fog_vertex>
}`,points_frag:`uniform vec3 diffuse;
uniform float opacity;
#include <common>
#include <color_pars_fragment>
#include <map_particle_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <fog_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	vec4 diffuseColor = vec4( diffuse, opacity );
	#include <clipping_planes_fragment>
	vec3 outgoingLight = vec3( 0.0 );
	#include <logdepthbuf_fragment>
	#include <map_particle_fragment>
	#include <color_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	outgoingLight = diffuseColor.rgb;
	#include <opaque_fragment>
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
	#include <premultiplied_alpha_fragment>
}`,shadow_vert:`#include <common>
#include <batching_pars_vertex>
#include <fog_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <shadowmap_pars_vertex>
void main() {
	#include <batching_vertex>
	#include <beginnormal_vertex>
	#include <morphinstance_vertex>
	#include <morphnormal_vertex>
	#include <skinbase_vertex>
	#include <skinnormal_vertex>
	#include <defaultnormal_vertex>
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <worldpos_vertex>
	#include <shadowmap_vertex>
	#include <fog_vertex>
}`,shadow_frag:`uniform vec3 color;
uniform float opacity;
#include <common>
#include <fog_pars_fragment>
#include <bsdfs>
#include <lights_pars_begin>
#include <logdepthbuf_pars_fragment>
#include <shadowmap_pars_fragment>
#include <shadowmask_pars_fragment>
void main() {
	#include <logdepthbuf_fragment>
	gl_FragColor = vec4( color, opacity * ( 1.0 - getShadowMask() ) );
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
}`,sprite_vert:`uniform float rotation;
uniform vec2 center;
#include <common>
#include <uv_pars_vertex>
#include <fog_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	#include <uv_vertex>
	vec4 mvPosition = modelViewMatrix[ 3 ];
	vec2 scale = vec2( length( modelMatrix[ 0 ].xyz ), length( modelMatrix[ 1 ].xyz ) );
	#ifndef USE_SIZEATTENUATION
		bool isPerspective = isPerspectiveMatrix( projectionMatrix );
		if ( isPerspective ) scale *= - mvPosition.z;
	#endif
	vec2 alignedPosition = ( position.xy - ( center - vec2( 0.5 ) ) ) * scale;
	vec2 rotatedPosition;
	rotatedPosition.x = cos( rotation ) * alignedPosition.x - sin( rotation ) * alignedPosition.y;
	rotatedPosition.y = sin( rotation ) * alignedPosition.x + cos( rotation ) * alignedPosition.y;
	mvPosition.xy += rotatedPosition;
	gl_Position = projectionMatrix * mvPosition;
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	#include <fog_vertex>
}`,sprite_frag:`uniform vec3 diffuse;
uniform float opacity;
#include <common>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <alphamap_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <fog_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	vec4 diffuseColor = vec4( diffuse, opacity );
	#include <clipping_planes_fragment>
	vec3 outgoingLight = vec3( 0.0 );
	#include <logdepthbuf_fragment>
	#include <map_fragment>
	#include <alphamap_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	outgoingLight = diffuseColor.rgb;
	#include <opaque_fragment>
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
}`},rr={common:{diffuse:{value:new Vn(16777215)},opacity:{value:1},map:{value:null},mapTransform:{value:new zi},alphaMap:{value:null},alphaMapTransform:{value:new zi},alphaTest:{value:0}},specularmap:{specularMap:{value:null},specularMapTransform:{value:new zi}},envmap:{envMap:{value:null},envMapRotation:{value:new zi},flipEnvMap:{value:-1},reflectivity:{value:1},ior:{value:1.5},refractionRatio:{value:.98},dfgLUT:{value:null}},aomap:{aoMap:{value:null},aoMapIntensity:{value:1},aoMapTransform:{value:new zi}},lightmap:{lightMap:{value:null},lightMapIntensity:{value:1},lightMapTransform:{value:new zi}},bumpmap:{bumpMap:{value:null},bumpMapTransform:{value:new zi},bumpScale:{value:1}},normalmap:{normalMap:{value:null},normalMapTransform:{value:new zi},normalScale:{value:new ct(1,1)}},displacementmap:{displacementMap:{value:null},displacementMapTransform:{value:new zi},displacementScale:{value:1},displacementBias:{value:0}},emissivemap:{emissiveMap:{value:null},emissiveMapTransform:{value:new zi}},metalnessmap:{metalnessMap:{value:null},metalnessMapTransform:{value:new zi}},roughnessmap:{roughnessMap:{value:null},roughnessMapTransform:{value:new zi}},gradientmap:{gradientMap:{value:null}},fog:{fogDensity:{value:25e-5},fogNear:{value:1},fogFar:{value:2e3},fogColor:{value:new Vn(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 Vn(16777215)},opacity:{value:1},size:{value:1},scale:{value:1},map:{value:null},alphaMap:{value:null},alphaMapTransform:{value:new zi},alphaTest:{value:0},uvTransform:{value:new zi}},sprite:{diffuse:{value:new Vn(16777215)},opacity:{value:1},center:{value:new ct(.5,.5)},rotation:{value:0},map:{value:null},mapTransform:{value:new zi},alphaMap:{value:null},alphaMapTransform:{value:new zi},alphaTest:{value:0}}},hf={basic:{uniforms:iu([rr.common,rr.specularmap,rr.envmap,rr.aomap,rr.lightmap,rr.fog]),vertexShader:is.meshbasic_vert,fragmentShader:is.meshbasic_frag},lambert:{uniforms:iu([rr.common,rr.specularmap,rr.envmap,rr.aomap,rr.lightmap,rr.emissivemap,rr.bumpmap,rr.normalmap,rr.displacementmap,rr.fog,rr.lights,{emissive:{value:new Vn(0)}}]),vertexShader:is.meshlambert_vert,fragmentShader:is.meshlambert_frag},phong:{uniforms:iu([rr.common,rr.specularmap,rr.envmap,rr.aomap,rr.lightmap,rr.emissivemap,rr.bumpmap,rr.normalmap,rr.displacementmap,rr.fog,rr.lights,{emissive:{value:new Vn(0)},specular:{value:new Vn(1118481)},shininess:{value:30}}]),vertexShader:is.meshphong_vert,fragmentShader:is.meshphong_frag},standard:{uniforms:iu([rr.common,rr.envmap,rr.aomap,rr.lightmap,rr.emissivemap,rr.bumpmap,rr.normalmap,rr.displacementmap,rr.roughnessmap,rr.metalnessmap,rr.fog,rr.lights,{emissive:{value:new Vn(0)},roughness:{value:1},metalness:{value:0},envMapIntensity:{value:1}}]),vertexShader:is.meshphysical_vert,fragmentShader:is.meshphysical_frag},toon:{uniforms:iu([rr.common,rr.aomap,rr.lightmap,rr.emissivemap,rr.bumpmap,rr.normalmap,rr.displacementmap,rr.gradientmap,rr.fog,rr.lights,{emissive:{value:new Vn(0)}}]),vertexShader:is.meshtoon_vert,fragmentShader:is.meshtoon_frag},matcap:{uniforms:iu([rr.common,rr.bumpmap,rr.normalmap,rr.displacementmap,rr.fog,{matcap:{value:null}}]),vertexShader:is.meshmatcap_vert,fragmentShader:is.meshmatcap_frag},points:{uniforms:iu([rr.points,rr.fog]),vertexShader:is.points_vert,fragmentShader:is.points_frag},dashed:{uniforms:iu([rr.common,rr.fog,{scale:{value:1},dashSize:{value:1},totalSize:{value:2}}]),vertexShader:is.linedashed_vert,fragmentShader:is.linedashed_frag},depth:{uniforms:iu([rr.common,rr.displacementmap]),vertexShader:is.depth_vert,fragmentShader:is.depth_frag},normal:{uniforms:iu([rr.common,rr.bumpmap,rr.normalmap,rr.displacementmap,{opacity:{value:1}}]),vertexShader:is.meshnormal_vert,fragmentShader:is.meshnormal_frag},sprite:{uniforms:iu([rr.sprite,rr.fog]),vertexShader:is.sprite_vert,fragmentShader:is.sprite_frag},background:{uniforms:{uvTransform:{value:new zi},t2D:{value:null},backgroundIntensity:{value:1}},vertexShader:is.background_vert,fragmentShader:is.background_frag},backgroundCube:{uniforms:{envMap:{value:null},flipEnvMap:{value:-1},backgroundBlurriness:{value:0},backgroundIntensity:{value:1},backgroundRotation:{value:new zi}},vertexShader:is.backgroundCube_vert,fragmentShader:is.backgroundCube_frag},cube:{uniforms:{tCube:{value:null},tFlip:{value:-1},opacity:{value:1}},vertexShader:is.cube_vert,fragmentShader:is.cube_frag},equirect:{uniforms:{tEquirect:{value:null}},vertexShader:is.equirect_vert,fragmentShader:is.equirect_frag},distance:{uniforms:iu([rr.common,rr.displacementmap,{referencePosition:{value:new J},nearDistance:{value:1},farDistance:{value:1e3}}]),vertexShader:is.distance_vert,fragmentShader:is.distance_frag},shadow:{uniforms:iu([rr.lights,rr.fog,{color:{value:new Vn(0)},opacity:{value:1}}]),vertexShader:is.shadow_vert,fragmentShader:is.shadow_frag}};hf.physical={uniforms:iu([hf.standard.uniforms,{clearcoat:{value:0},clearcoatMap:{value:null},clearcoatMapTransform:{value:new zi},clearcoatNormalMap:{value:null},clearcoatNormalMapTransform:{value:new zi},clearcoatNormalScale:{value:new ct(1,1)},clearcoatRoughness:{value:0},clearcoatRoughnessMap:{value:null},clearcoatRoughnessMapTransform:{value:new zi},dispersion:{value:0},iridescence:{value:0},iridescenceMap:{value:null},iridescenceMapTransform:{value:new zi},iridescenceIOR:{value:1.3},iridescenceThicknessMinimum:{value:100},iridescenceThicknessMaximum:{value:400},iridescenceThicknessMap:{value:null},iridescenceThicknessMapTransform:{value:new zi},sheen:{value:0},sheenColor:{value:new Vn(0)},sheenColorMap:{value:null},sheenColorMapTransform:{value:new zi},sheenRoughness:{value:1},sheenRoughnessMap:{value:null},sheenRoughnessMapTransform:{value:new zi},transmission:{value:0},transmissionMap:{value:null},transmissionMapTransform:{value:new zi},transmissionSamplerSize:{value:new ct},transmissionSamplerMap:{value:null},thickness:{value:0},thicknessMap:{value:null},thicknessMapTransform:{value:new zi},attenuationDistance:{value:0},attenuationColor:{value:new Vn(0)},specularColor:{value:new Vn(1,1,1)},specularColorMap:{value:null},specularColorMapTransform:{value:new zi},specularIntensity:{value:1},specularIntensityMap:{value:null},specularIntensityMapTransform:{value:new zi},anisotropyVector:{value:new ct},anisotropyMap:{value:null},anisotropyMapTransform:{value:new zi}}]),vertexShader:is.meshphysical_vert,fragmentShader:is.meshphysical_frag};const Gb={r:0,b:0,g:0},rg=new bu,rV=new Cr;function iV(r,e,t,n,i,s,a){const o=new Vn(0);let l=s===!0?0:1,u,c,d=null,f=0,h=null;function p(w){let P=w.isScene===!0?w.background:null;return P&&P.isTexture&&(P=(w.backgroundBlurriness>0?t:e).get(P)),P}function x(w){let P=!1;const B=p(w);B===null?m(o,l):B&&B.isColor&&(m(B,1),P=!0);const S=r.xr.getEnvironmentBlendMode();S==="additive"?n.buffers.color.setClear(0,0,0,1,a):S==="alpha-blend"&&n.buffers.color.setClear(0,0,0,0,a),(r.autoClear||P)&&(n.buffers.depth.setTest(!0),n.buffers.depth.setMask(!0),n.buffers.color.setMask(!0),r.clear(r.autoClearColor,r.autoClearDepth,r.autoClearStencil))}function v(w,P){const B=p(P);B&&(B.isCubeTexture||B.mapping===Jd)?(c===void 0&&(c=new Gs(new Dp(1,1,1),new $u({name:"BackgroundCubeMaterial",uniforms:zv(hf.backgroundCube.uniforms),vertexShader:hf.backgroundCube.vertexShader,fragmentShader:hf.backgroundCube.fragmentShader,side:Qi,depthTest:!1,depthWrite:!1,fog:!1,allowOverride:!1})),c.geometry.deleteAttribute("normal"),c.geometry.deleteAttribute("uv"),c.onBeforeRender=function(S,I,N){this.matrixWorld.copyPosition(N.matrixWorld)},Object.defineProperty(c.material,"envMap",{get:function(){return this.uniforms.envMap.value}}),i.update(c)),rg.copy(P.backgroundRotation),rg.x*=-1,rg.y*=-1,rg.z*=-1,B.isCubeTexture&&B.isRenderTargetTexture===!1&&(rg.y*=-1,rg.z*=-1),c.material.uniforms.envMap.value=B,c.material.uniforms.flipEnvMap.value=B.isCubeTexture&&B.isRenderTargetTexture===!1?-1:1,c.material.uniforms.backgroundBlurriness.value=P.backgroundBlurriness,c.material.uniforms.backgroundIntensity.value=P.backgroundIntensity,c.material.uniforms.backgroundRotation.value.setFromMatrix4(rV.makeRotationFromEuler(rg)),c.material.toneMapped=$r.getTransfer(B.colorSpace)!==$n,(d!==B||f!==B.version||h!==r.toneMapping)&&(c.material.needsUpdate=!0,d=B,f=B.version,h=r.toneMapping),c.layers.enableAll(),w.unshift(c,c.geometry,c.material,0,0,null)):B&&B.isTexture&&(u===void 0&&(u=new Gs(new Jv(2,2),new 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bT{constructor(e){this._renderer=e,this._pingPongRenderTarget=null,this._lodMax=0,this._cubeSize=0,this._sizeLods=[],this._sigmas=[],this._lodMeshes=[],this._backgroundBox=null,this._cubemapMaterial=null,this._equirectMaterial=null,this._blurMaterial=null,this._ggxMaterial=null}fromScene(e,t=0,n=.1,i=100,s={}){const{size:a=256,position:o=dV}=s;yP=this._renderer.getRenderTarget(),bP=this._renderer.getActiveCubeFace(),EP=this._renderer.getActiveMipmapLevel(),wP=this._renderer.xr.enabled,this._renderer.xr.enabled=!1,this._setSize(a);const l=this._allocateTargets();return l.depthBuffer=!0,this._sceneToCubeUV(e,n,i,l,o),t>0&&this._blur(l,0,0,t),this._applyPMREM(l),this._cleanup(l),l}fromEquirectangular(e,t=null){return this._fromTexture(e,t)}fromCubemap(e,t=null){return this._fromTexture(e,t)}compileCubemapShader(){this._cubemapMaterial===null&&(this._cubemapMaterial=CT(),this._compileMaterial(this._cubemapMaterial))}compileEquirectangularShader(){this._equirectMaterial===null&&(this._equirectMaterial=wT(),this._compileMaterial(this._equirectMaterial))}dispose(){this._dispose(),this._cubemapMaterial!==null&&this._cubemapMaterial.dispose(),this._equirectMaterial!==null&&this._equirectMaterial.dispose(),this._backgroundBox!==null&&(this._backgroundBox.geometry.dispose(),this._backgroundBox.material.dispose())}_setSize(e){this._lodMax=Math.floor(Math.log2(e)),this._cubeSize=Math.pow(2,this._lodMax)}_dispose(){this._blurMaterial!==null&&this._blurMaterial.dispose(),this._ggxMaterial!==null&&this._ggxMaterial.dispose(),this._pingPongRenderTarget!==null&&this._pingPongRenderTarget.dispose();for(let e=0;e<this._lodMeshes.length;e++)this._lodMeshes[e].geometry.dispose()}_cleanup(e){this._renderer.setRenderTarget(yP,bP,EP),this._renderer.xr.enabled=wP,e.scissorTest=!1,aA(e,0,0,e.width,e.height)}_fromTexture(e,t){e.mapping===ai||e.mapping===ps?this._setSize(e.image.length===0?16:e.image[0].width||e.image[0].image.width):this._setSize(e.image.width/4),yP=this._renderer.getRenderTarget(),bP=this._renderer.getActiveCubeFace(),EP=this._renderer.getActiveMipmapLevel(),wP=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:ms,minFilter:ms,generateMipmaps:!1,type:pa,format:ma,colorSpace:af,depthBuffer:!1},i=ET(e,t,n);if(this._pingPongRenderTarget===null||this._pingPongRenderTarget.width!==e||this._pingPongRenderTarget.height!==t){this._pingPongRenderTarget!==null&&this._dispose(),this._pingPongRenderTarget=ET(e,t,n);const{_lodMax:s}=this;({lodMeshes:this._lodMeshes,sizeLods:this._sizeLods,sigmas:this._sigmas}=fV(s)),this._blurMaterial=pV(s,e,t),this._ggxMaterial=hV(s,e,t)}return i}_compileMaterial(e){const t=new Gs(new Ni,e);this._renderer.compile(t,nx)}_sceneToCubeUV(e,t,n,i,s){const l=new bo(90,1,t,n),u=[1,-1,1,1,1,1],c=[1,1,1,-1,-1,-1],d=this._renderer,f=d.autoClear,h=d.toneMapping;d.getClearColor(yT),d.toneMapping=Fr,d.autoClear=!1,d.state.buffers.depth.getReversed()&&(d.setRenderTarget(i),d.clearDepth(),d.setRenderTarget(null)),this._backgroundBox===null&&(this._backgroundBox=new Gs(new Dp,new rl({name:"PMREM.Background",side:Qi,depthWrite:!1,depthTest:!1})));const x=this._backgroundBox,v=x.material;let m=!1;const C=e.background;C?C.isColor&&(v.color.copy(C),e.background=null,m=!0):(v.color.copy(yT),m=!0);for(let w=0;w<6;w++){const P=w%3;P===0?(l.up.set(0,u[w],0),l.position.set(s.x,s.y,s.z),l.lookAt(s.x+c[w],s.y,s.z)):P===1?(l.up.set(0,0,u[w]),l.position.set(s.x,s.y,s.z),l.lookAt(s.x,s.y+c[w],s.z)):(l.up.set(0,u[w],0),l.position.set(s.x,s.y,s.z),l.lookAt(s.x,s.y,s.z+c[w]));const B=this._cubeSize;aA(i,P*B,w>2?B:0,B,B),d.setRenderTarget(i),m&&d.render(x,l),d.render(e,l)}d.toneMapping=h,d.autoClear=f,e.background=C}_textureToCubeUV(e,t){const n=this._renderer,i=e.mapping===ai||e.mapping===ps;i?(this._cubemapMaterial===null&&(this._cubemapMaterial=CT()),this._cubemapMaterial.uniforms.flipEnvMap.value=e.isRenderTargetTexture===!1?-1:1):this._equirectMaterial===null&&(this._equirectMaterial=wT());const s=i?this._cubemapMaterial:this._equirectMaterial,a=this._lodMeshes[0];a.material=s;const o=s.uniforms;o.envMap.value=e;const l=this._cubeSize;aA(t,0,0,3*l,2*l),n.setRenderTarget(t),n.render(a,nx)}_applyPMREM(e){const t=this._renderer,n=t.autoClear;t.autoClear=!1;const i=this._lodMeshes.length;for(let s=1;s<i;s++)this._applyGGXFilter(e,s-1,s);t.autoClear=n}_applyGGXFilter(e,t,n){const i=this._renderer,s=this._pingPongRenderTarget,a=this._ggxMaterial,o=this._lodMeshes[n];o.material=a;const l=a.uniforms,u=n/(this._lodMeshes.length-1),c=t/(this._lodMeshes.length-1),d=Math.sqrt(u*u-c*c),f=0+u*1.25,h=d*f,{_lodMax:p}=this,x=this._sizeLods[n],v=3*x*(n>p-Rp?n-p+Rp:0),m=4*(this._cubeSize-x);l.envMap.value=e.texture,l.roughness.value=h,l.mipInt.value=p-t,aA(s,v,m,3*x,2*x),i.setRenderTarget(s),i.render(o,nx),l.envMap.value=s.texture,l.roughness.value=0,l.mipInt.value=p-n,aA(e,v,m,3*x,2*x),i.setRenderTarget(e),i.render(o,nx)}_blur(e,t,n,i,s){const a=this._pingPongRenderTarget;this._halfBlur(e,a,t,n,i,"latitudinal",s),this._halfBlur(a,e,n,n,i,"longitudinal",s)}_halfBlur(e,t,n,i,s,a,o){const l=this._renderer,u=this._blurMaterial;a!=="latitudinal"&&a!=="longitudinal"&&rt("blur direction must be either latitudinal or longitudinal!");const c=3,d=this._lodMeshes[i];d.material=u;const f=u.uniforms,h=this._sizeLods[n]-1,p=isFinite(s)?Math.PI/(2*h):2*Math.PI/(2*ig-1),x=s/p,v=isFinite(s)?1+Math.floor(c*x):ig;v>ig&&ze(`sigmaRadians, ${s}, is too large and will clip, as it requested ${v} samples when the maximum is set to ${ig}`);const m=[];let C=0;for(let I=0;I<ig;++I){const N=I/x,T=Math.exp(-N*N/2);m.push(T),I===0?C+=T:I<v&&(C+=2*T)}for(let I=0;I<m.length;I++)m[I]=m[I]/C;f.envMap.value=e.texture,f.samples.value=v,f.weights.value=m,f.latitudinal.value=a==="latitudinal",o&&(f.poleAxis.value=o);const{_lodMax:w}=this;f.dTheta.value=p,f.mipInt.value=w-n;const P=this._sizeLods[i],B=3*P*(i>w-Rp?i-w+Rp:0),S=4*(this._cubeSize-P);aA(t,B,S,3*P,2*P),l.setRenderTarget(t),l.render(d,nx)}}function fV(r){const e=[],t=[],n=[];let i=r;const s=r-Rp+1+xT.length;for(let a=0;a<s;a++){const o=Math.pow(2,i);e.push(o);let l=1/o;a>r-Rp?l=xT[a-r+Rp-1]:a===0&&(l=0),t.push(l);const u=1/(o-2),c=-u,d=1+u,f=[c,c,d,c,d,d,c,c,d,d,c,d],h=6,p=6,x=3,v=2,m=1,C=new Float32Array(x*p*h),w=new Float32Array(v*p*h),P=new Float32Array(m*p*h);for(let S=0;S<h;S++){const I=S%3*2/3-1,N=S>2?0:-1,T=[I,N,0,I+2/3,N,0,I+2/3,N+1,0,I,N,0,I+2/3,N+1,0,I,N+1,0];C.set(T,x*p*S),w.set(f,v*p*S);const R=[S,S,S,S,S,S];P.set(R,m*p*S)}const B=new Ni;B.setAttribute("position",new ga(C,x)),B.setAttribute("uv",new ga(w,v)),B.setAttribute("faceIndex",new ga(P,m)),n.push(new Gs(B,null)),i>Rp&&i--}return{lodMeshes:n,sizeLods:e,sigmas:t}}function ET(r,e,t){const n=new fd(r,e,t);return n.texture.mapping=Jd,n.texture.name="PMREM.cubeUv",n.scissorTest=!0,n}function aA(r,e,t,n,i){r.viewport.set(e,t,n,i),r.scissor.set(e,t,n,i)}function hV(r,e,t){return new $u({name:"PMREMGGXConvolution",defines:{GGX_SAMPLES:cV,CUBEUV_TEXEL_WIDTH:1/e,CUBEUV_TEXEL_HEIGHT:1/t,CUBEUV_MAX_MIP:`${r}.0`},uniforms:{envMap:{value:null},roughness:{value:0},mipInt:{value:0}},vertexShader:Wb(),fragmentShader:`

			precision highp float;
			precision highp int;

			varying vec3 vOutputDirection;

			uniform sampler2D envMap;
			uniform float roughness;
			uniform float mipInt;

			#define ENVMAP_TYPE_CUBE_UV
			#include <cube_uv_reflection_fragment>

			#define PI 3.14159265359

			// Van der Corput radical inverse
			float radicalInverse_VdC(uint bits) {
				bits = (bits << 16u) | (bits >> 16u);
				bits = ((bits & 0x55555555u) << 1u) | ((bits & 0xAAAAAAAAu) >> 1u);
				bits = ((bits & 0x33333333u) << 2u) | ((bits & 0xCCCCCCCCu) >> 2u);
				bits = ((bits & 0x0F0F0F0Fu) << 4u) | ((bits & 0xF0F0F0F0u) >> 4u);
				bits = ((bits & 0x00FF00FFu) << 8u) | ((bits & 0xFF00FF00u) >> 8u);
				return float(bits) * 2.3283064365386963e-10; // / 0x100000000
			}

			// Hammersley sequence
			vec2 hammersley(uint i, uint N) {
				return vec2(float(i) / float(N), radicalInverse_VdC(i));
			}

			// GGX VNDF importance sampling (Eric Heitz 2018)
			// "Sampling the GGX Distribution of Visible Normals"
			// https://jcgt.org/published/0007/04/01/
			vec3 importanceSampleGGX_VNDF(vec2 Xi, vec3 V, float roughness) {
				float alpha = roughness * roughness;

				// Section 3.2: Transform view direction to hemisphere configuration
				vec3 Vh = normalize(vec3(alpha * V.x, alpha * V.y, V.z));

				// Section 4.1: Orthonormal basis
				float lensq = Vh.x * Vh.x + Vh.y * Vh.y;
				vec3 T1 = lensq > 0.0 ? vec3(-Vh.y, Vh.x, 0.0) / sqrt(lensq) : vec3(1.0, 0.0, 0.0);
				vec3 T2 = cross(Vh, T1);

				// Section 4.2: Parameterization of projected area
				float r = sqrt(Xi.x);
				float phi = 2.0 * PI * Xi.y;
				float t1 = r * cos(phi);
				float t2 = r * sin(phi);
				float s = 0.5 * (1.0 + Vh.z);
				t2 = (1.0 - s) * sqrt(1.0 - t1 * t1) + s * t2;

				// Section 4.3: Reprojection onto hemisphere
				vec3 Nh = t1 * T1 + t2 * T2 + sqrt(max(0.0, 1.0 - t1 * t1 - t2 * t2)) * Vh;

				// Section 3.4: Transform back to ellipsoid configuration
				return normalize(vec3(alpha * Nh.x, alpha * Nh.y, max(0.0, Nh.z)));
			}

			void main() {
				vec3 N = normalize(vOutputDirection);
				vec3 V = N; // Assume view direction equals normal for pre-filtering

				vec3 prefilteredColor = vec3(0.0);
				float totalWeight = 0.0;

				// For very low roughness, just sample the environment directly
				if (roughness < 0.001) {
					gl_FragColor = vec4(bilinearCubeUV(envMap, N, mipInt), 1.0);
					return;
				}

				// Tangent space basis for VNDF sampling
				vec3 up = abs(N.z) < 0.999 ? vec3(0.0, 0.0, 1.0) : vec3(1.0, 0.0, 0.0);
				vec3 tangent = normalize(cross(up, N));
				vec3 bitangent = cross(N, tangent);

				for(uint i = 0u; i < uint(GGX_SAMPLES); i++) {
					vec2 Xi = hammersley(i, uint(GGX_SAMPLES));

					// For PMREM, V = N, so in tangent space V is always (0, 0, 1)
					vec3 H_tangent = importanceSampleGGX_VNDF(Xi, vec3(0.0, 0.0, 1.0), roughness);

					// Transform H back to world space
					vec3 H = normalize(tangent * H_tangent.x + bitangent * H_tangent.y + N * H_tangent.z);
					vec3 L = normalize(2.0 * dot(V, H) * H - V);

					float NdotL = max(dot(N, L), 0.0);

					if(NdotL > 0.0) {
						// Sample environment at fixed mip level
						// VNDF importance sampling handles the distribution filtering
						vec3 sampleColor = bilinearCubeUV(envMap, L, mipInt);

						// Weight by NdotL for the split-sum approximation
						// VNDF PDF naturally accounts for the visible microfacet distribution
						prefilteredColor += sampleColor * NdotL;
						totalWeight += NdotL;
					}
				}

				if (totalWeight > 0.0) {
					prefilteredColor = prefilteredColor / totalWeight;
				}

				gl_FragColor = vec4(prefilteredColor, 1.0);
			}
		`,blending:Xa,depthTest:!1,depthWrite:!1})}function pV(r,e,t){const n=new Float32Array(ig),i=new J(0,1,0);return new $u({name:"SphericalGaussianBlur",defines:{n:ig,CUBEUV_TEXEL_WIDTH:1/e,CUBEUV_TEXEL_HEIGHT:1/t,CUBEUV_MAX_MIP:`${r}.0`},uniforms:{envMap:{value:null},samples:{value:1},weights:{value:n},latitudinal:{value:!1},dTheta:{value:0},mipInt:{value:0},poleAxis:{value:i}},vertexShader:Wb(),fragmentShader:`

			precision mediump float;
			precision mediump int;

			varying vec3 vOutputDirection;

			uniform sampler2D envMap;
			uniform int samples;
			uniform float weights[ n ];
			uniform bool latitudinal;
			uniform float dTheta;
			uniform float mipInt;
			uniform vec3 poleAxis;

			#define ENVMAP_TYPE_CUBE_UV
			#include <cube_uv_reflection_fragment>

			vec3 getSample( float theta, vec3 axis ) {

				float cosTheta = cos( theta );
				// Rodrigues' axis-angle rotation
				vec3 sampleDirection = vOutputDirection * cosTheta
					+ cross( axis, vOutputDirection ) * sin( theta )
					+ axis * dot( axis, vOutputDirection ) * ( 1.0 - cosTheta );

				return bilinearCubeUV( envMap, sampleDirection, mipInt );

			}

			void main() {

				vec3 axis = latitudinal ? poleAxis : cross( poleAxis, vOutputDirection );

				if ( all( equal( axis, vec3( 0.0 ) ) ) ) {

					axis = vec3( vOutputDirection.z, 0.0, - vOutputDirection.x );

				}

				axis = normalize( axis );

				gl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );
				gl_FragColor.rgb += weights[ 0 ] * getSample( 0.0, axis );

				for ( int i = 1; i < n; i++ ) {

					if ( i >= samples ) {

						break;

					}

					float theta = dTheta * float( i );
					gl_FragColor.rgb += weights[ i ] * getSample( -1.0 * theta, axis );
					gl_FragColor.rgb += weights[ i ] * getSample( theta, axis );

				}

			}
		`,blending:Xa,depthTest:!1,depthWrite:!1})}function wT(){return new $u({name:"EquirectangularToCubeUV",uniforms:{envMap:{value:null}},vertexShader:Wb(),fragmentShader:`

			precision mediump float;
			precision mediump int;

			varying vec3 vOutputDirection;

			uniform sampler2D envMap;

			#include <common>

			void main() {

				vec3 outputDirection = normalize( vOutputDirection );
				vec2 uv = equirectUv( outputDirection );

				gl_FragColor = vec4( texture2D ( envMap, uv ).rgb, 1.0 );

			}
		`,blending:Xa,depthTest:!1,depthWrite:!1})}function CT(){return new $u({name:"CubemapToCubeUV",uniforms:{envMap:{value:null},flipEnvMap:{value:-1}},vertexShader:Wb(),fragmentShader:`

			precision mediump float;
			precision mediump int;

			uniform float flipEnvMap;

			varying vec3 vOutputDirection;

			uniform samplerCube envMap;

			void main() {

				gl_FragColor = textureCube( envMap, vec3( flipEnvMap * vOutputDirection.x, vOutputDirection.yz ) );

			}
		`,blending:Xa,depthTest:!1,depthWrite:!1})}function Wb(){return`

		precision mediump float;
		precision mediump int;

		attribute float faceIndex;

		varying vec3 vOutputDirection;

		// RH coordinate system; PMREM face-indexing convention
		vec3 getDirection( vec2 uv, float face ) {

			uv = 2.0 * uv - 1.0;

			vec3 direction = vec3( uv, 1.0 );

			if ( face == 0.0 ) {

				direction = direction.zyx; // ( 1, v, u ) pos x

			} else if ( face == 1.0 ) {

				direction = direction.xzy;
				direction.xz *= -1.0; // ( -u, 1, -v ) pos y

			} else if ( face == 2.0 ) {

				direction.x *= -1.0; // ( -u, v, 1 ) pos z

			} else if ( face == 3.0 ) {

				direction = direction.zyx;
				direction.xz *= -1.0; // ( -1, v, -u ) neg x

			} else if ( face == 4.0 ) {

				direction = direction.xzy;
				direction.xy *= -1.0; // ( -u, -1, v ) neg y

			} else if ( face == 5.0 ) {

				direction.z *= -1.0; // ( u, v, -1 ) neg z

			}

			return direction;

		}

		void main() {

			vOutputDirection = getDirection( uv, faceIndex );
			gl_Position = vec4( position, 1.0 );

		}
	`}function mV(r){let e=new WeakMap,t=null;function n(o){if(o&&o.isTexture){const l=o.mapping,u=l===Pa||l===ld,c=l===ai||l===ps;if(u||c){let d=e.get(o);const f=d!==void 0?d.texture.pmremVersion:0;if(o.isRenderTargetTexture&&o.pmremVersion!==f)return t===null&&(t=new bT(r)),d=u?t.fromEquirectangular(o,d):t.fromCubemap(o,d),d.texture.pmremVersion=o.pmremVersion,e.set(o,d),d.texture;if(d!==void 0)return d.texture;{const h=o.image;return u&&h&&h.height>0||c&&h&&i(h)?(t===null&&(t=new bT(r)),d=u?t.fromEquirectangular(o):t.fromCubemap(o),d.texture.pmremVersion=o.pmremVersion,e.set(o,d),o.addEventListener("dispose",s),d.texture):null}}}return o}function i(o){let l=0;const u=6;for(let c=0;c<u;c++)o[c]!==void 0&&l++;return l===u}function s(o){const l=o.target;l.removeEventListener("dispose",s);const u=e.get(l);u!==void 0&&(e.delete(l),u.dispose())}function a(){e=new WeakMap,t!==null&&(t.dispose(),t=null)}return{get:n,dispose:a}}function gV(r){const e={};function t(n){if(e[n]!==void 0)return e[n];const i=r.getExtension(n);return e[n]=i,i}return{has:function(n){return t(n)!==null},init:function(){t("EXT_color_buffer_float"),t("WEBGL_clip_cull_distance"),t("OES_texture_float_linear"),t("EXT_color_buffer_half_float"),t("WEBGL_multisampled_render_to_texture"),t("WEBGL_render_shared_exponent")},get:function(n){const i=t(n);return i===null&&rs("WebGLRenderer: "+n+" extension not supported."),i}}}function vV(r,e,t,n){const i={},s=new WeakMap;function a(d){const f=d.target;f.index!==null&&e.remove(f.index);for(const p in f.attributes)e.remove(f.attributes[p]);f.removeEventListener("dispose",a),delete i[f.id];const h=s.get(f);h&&(e.remove(h),s.delete(f)),n.releaseStatesOfGeometry(f),f.isInstancedBufferGeometry===!0&&delete f._maxInstanceCount,t.memory.geometries--}function o(d,f){return i[f.id]===!0||(f.addEventListener("dispose",a),i[f.id]=!0,t.memory.geometries++),f}function l(d){const f=d.attributes;for(const h in f)e.update(f[h],r.ARRAY_BUFFER)}function u(d){const f=[],h=d.index,p=d.attributes.position;let x=0;if(h!==null){const C=h.array;x=h.version;for(let w=0,P=C.length;w<P;w+=3){const B=C[w+0],S=C[w+1],I=C[w+2];f.push(B,S,S,I,I,B)}}else if(p!==void 0){const C=p.array;x=p.version;for(let w=0,P=C.length/3-1;w<P;w+=3){const B=w+0,S=w+1,I=w+2;f.push(B,S,S,I,I,B)}}else return;const v=new(gi(f)?GC:XC)(f,1);v.version=x;const m=s.get(d);m&&e.remove(m),s.set(d,v)}function c(d){const f=s.get(d);if(f){const h=d.index;h!==null&&f.version<h.version&&u(d)}else u(d);return s.get(d)}return{get:o,update:l,getWireframeAttribute:c}}function AV(r,e,t){let n;function i(f){n=f}let s,a;function o(f){s=f.type,a=f.bytesPerElement}function l(f,h){r.drawElements(n,h,s,f*a),t.update(h,n,1)}function u(f,h,p){p!==0&&(r.drawElementsInstanced(n,h,s,f*a,p),t.update(h,n,p))}function c(f,h,p){if(p===0)return;e.get("WEBGL_multi_draw").multiDrawElementsWEBGL(n,h,0,s,f,0,p);let v=0;for(let m=0;m<p;m++)v+=h[m];t.update(v,n,1)}function d(f,h,p,x){if(p===0)return;const v=e.get("WEBGL_multi_draw");if(v===null)for(let m=0;m<f.length;m++)u(f[m]/a,h[m],x[m]);else{v.multiDrawElementsInstancedWEBGL(n,h,0,s,f,0,x,0,p);let m=0;for(let C=0;C<p;C++)m+=h[C]*x[C];t.update(m,n,1)}}this.setMode=i,this.setIndex=o,this.render=l,this.renderInstances=u,this.renderMultiDraw=c,this.renderMultiDrawInstances=d}function xV(r){const e={geometries:0,textures:0},t={frame:0,calls:0,triangles:0,points:0,lines:0};function n(s,a,o){switch(t.calls++,a){case r.TRIANGLES:t.triangles+=o*(s/3);break;case r.LINES:t.lines+=o*(s/2);break;case r.LINE_STRIP:t.lines+=o*(s-1);break;case r.LINE_LOOP:t.lines+=o*s;break;case r.POINTS:t.points+=o*s;break;default:rt("WebGLInfo: Unknown draw mode:",a);break}}function i(){t.calls=0,t.triangles=0,t.points=0,t.lines=0}return{memory:e,render:t,programs:null,autoReset:!0,reset:i,update:n}}function yV(r,e,t){const n=new WeakMap,i=new Ei;function s(a,o,l){const u=a.morphTargetInfluences,c=o.morphAttributes.position||o.morphAttributes.normal||o.morphAttributes.color,d=c!==void 0?c.length:0;let f=n.get(o);if(f===void 0||f.count!==d){let T=function(){I.dispose(),n.delete(o),o.removeEventListener("dispose",T)};f!==void 0&&f.texture.dispose();const h=o.morphAttributes.position!==void 0,p=o.morphAttributes.normal!==void 0,x=o.morphAttributes.color!==void 0,v=o.morphAttributes.position||[],m=o.morphAttributes.normal||[],C=o.morphAttributes.color||[];let w=0;h===!0&&(w=1),p===!0&&(w=2),x===!0&&(w=3);let P=o.attributes.position.count*w,B=1;P>e.maxTextureSize&&(B=Math.ceil(P/e.maxTextureSize),P=e.maxTextureSize);const S=new Float32Array(P*B*4*d),I=new Py(S,P,B,d);I.type=ha,I.needsUpdate=!0;const N=w*4;for(let R=0;R<d;R++){const D=v[R],j=m[R],q=C[R],Q=P*B*4*R;for(let re=0;re<D.count;re++){const de=re*N;h===!0&&(i.fromBufferAttribute(D,re),S[Q+de+0]=i.x,S[Q+de+1]=i.y,S[Q+de+2]=i.z,S[Q+de+3]=0),p===!0&&(i.fromBufferAttribute(j,re),S[Q+de+4]=i.x,S[Q+de+5]=i.y,S[Q+de+6]=i.z,S[Q+de+7]=0),x===!0&&(i.fromBufferAttribute(q,re),S[Q+de+8]=i.x,S[Q+de+9]=i.y,S[Q+de+10]=i.z,S[Q+de+11]=q.itemSize===4?i.w:1)}}f={count:d,texture:I,size:new ct(P,B)},n.set(o,f),o.addEventListener("dispose",T)}if(a.isInstancedMesh===!0&&a.morphTexture!==null)l.getUniforms().setValue(r,"morphTexture",a.morphTexture,t);else{let h=0;for(let x=0;x<u.length;x++)h+=u[x];const p=o.morphTargetsRelative?1:1-h;l.getUniforms().setValue(r,"morphTargetBaseInfluence",p),l.getUniforms().setValue(r,"morphTargetInfluences",u)}l.getUniforms().setValue(r,"morphTargetsTexture",f.texture,t),l.getUniforms().setValue(r,"morphTargetsTextureSize",f.size)}return{update:s}}function bV(r,e,t,n){let i=new WeakMap;function s(l){const u=n.render.frame,c=l.geometry,d=e.get(l,c);if(i.get(d)!==u&&(e.update(d),i.set(d,u)),l.isInstancedMesh&&(l.hasEventListener("dispose",o)===!1&&l.addEventListener("dispose",o),i.get(l)!==u&&(t.update(l.instanceMatrix,r.ARRAY_BUFFER),l.instanceColor!==null&&t.update(l.instanceColor,r.ARRAY_BUFFER),i.set(l,u))),l.isSkinnedMesh){const f=l.skeleton;i.get(f)!==u&&(f.update(),i.set(f,u))}return d}function a(){i=new WeakMap}function o(l){const u=l.target;u.removeEventListener("dispose",o),t.remove(u.instanceMatrix),u.instanceColor!==null&&t.remove(u.instanceColor)}return{update:s,dispose:a}}const EV={[ci]:"LINEAR_TONE_MAPPING",[fo]:"REINHARD_TONE_MAPPING",[Rl]:"CINEON_TONE_MAPPING",[Yd]:"ACES_FILMIC_TONE_MAPPING",[Zf]:"AGX_TONE_MAPPING",[qh]:"NEUTRAL_TONE_MAPPING",[hv]:"CUSTOM_TONE_MAPPING"};function wV(r,e,t,n,i){const s=new fd(e,t,{type:r,depthBuffer:n,stencilBuffer:i}),a=new fd(e,t,{type:pa,depthBuffer:!1,stencilBuffer:!1}),o=new Ni;o.setAttribute("position",new yr([-1,3,0,-1,-1,0,3,-1,0],3)),o.setAttribute("uv",new yr([0,2,0,0,2,0],2));const l=new D5({uniforms:{tDiffuse:{value:null}},vertexShader:`
			precision highp float;

			uniform mat4 modelViewMatrix;
			uniform mat4 projectionMatrix;

			attribute vec3 position;
			attribute vec2 uv;

			varying vec2 vUv;

			void main() {
				vUv = uv;
				gl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );
			}`,fragmentShader:`
			precision highp float;

			uniform sampler2D tDiffuse;

			varying vec2 vUv;

			#include <tonemapping_pars_fragment>
			#include <colorspace_pars_fragment>

			void main() {
				gl_FragColor = texture2D( tDiffuse, vUv );

				#ifdef LINEAR_TONE_MAPPING
					gl_FragColor.rgb = LinearToneMapping( gl_FragColor.rgb );
				#elif defined( REINHARD_TONE_MAPPING )
					gl_FragColor.rgb = ReinhardToneMapping( gl_FragColor.rgb );
				#elif defined( CINEON_TONE_MAPPING )
					gl_FragColor.rgb = CineonToneMapping( gl_FragColor.rgb );
				#elif defined( ACES_FILMIC_TONE_MAPPING )
					gl_FragColor.rgb = ACESFilmicToneMapping( gl_FragColor.rgb );
				#elif defined( AGX_TONE_MAPPING )
					gl_FragColor.rgb = AgXToneMapping( gl_FragColor.rgb );
				#elif defined( NEUTRAL_TONE_MAPPING )
					gl_FragColor.rgb = NeutralToneMapping( gl_FragColor.rgb );
				#elif defined( CUSTOM_TONE_MAPPING )
					gl_FragColor.rgb = CustomToneMapping( gl_FragColor.rgb );
				#endif

				#ifdef SRGB_TRANSFER
					gl_FragColor = sRGBTransferOETF( gl_FragColor );
				#endif
			}`,depthTest:!1,depthWrite:!1}),u=new Gs(o,l),c=new Km(-1,1,1,-1,0,1);let d=null,f=null,h=!1,p,x=null,v=[],m=!1;this.setSize=function(C,w){s.setSize(C,w),a.setSize(C,w);for(let P=0;P<v.length;P++){const B=v[P];B.setSize&&B.setSize(C,w)}},this.setEffects=function(C){v=C,m=v.length>0&&v[0].isRenderPass===!0;const w=s.width,P=s.height;for(let B=0;B<v.length;B++){const S=v[B];S.setSize&&S.setSize(w,P)}},this.begin=function(C,w){if(h||C.toneMapping===Fr&&v.length===0)return!1;if(x=w,w!==null){const P=w.width,B=w.height;(s.width!==P||s.height!==B)&&this.setSize(P,B)}return m===!1&&C.setRenderTarget(s),p=C.toneMapping,C.toneMapping=Fr,!0},this.hasRenderPass=function(){return m},this.end=function(C,w){C.toneMapping=p,h=!0;let P=s,B=a;for(let S=0;S<v.length;S++){const I=v[S];if(I.enabled!==!1&&(I.render(C,B,P,w),I.needsSwap!==!1)){const 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USE_ANISOTROPYMAP":"",t.clearcoatMap?"#define USE_CLEARCOATMAP":"",t.clearcoatRoughnessMap?"#define USE_CLEARCOAT_ROUGHNESSMAP":"",t.clearcoatNormalMap?"#define USE_CLEARCOAT_NORMALMAP":"",t.iridescenceMap?"#define USE_IRIDESCENCEMAP":"",t.iridescenceThicknessMap?"#define USE_IRIDESCENCE_THICKNESSMAP":"",t.specularMap?"#define USE_SPECULARMAP":"",t.specularColorMap?"#define USE_SPECULAR_COLORMAP":"",t.specularIntensityMap?"#define USE_SPECULAR_INTENSITYMAP":"",t.roughnessMap?"#define USE_ROUGHNESSMAP":"",t.metalnessMap?"#define USE_METALNESSMAP":"",t.alphaMap?"#define USE_ALPHAMAP":"",t.alphaHash?"#define USE_ALPHAHASH":"",t.transmission?"#define USE_TRANSMISSION":"",t.transmissionMap?"#define USE_TRANSMISSIONMAP":"",t.thicknessMap?"#define USE_THICKNESSMAP":"",t.sheenColorMap?"#define USE_SHEEN_COLORMAP":"",t.sheenRoughnessMap?"#define USE_SHEEN_ROUGHNESSMAP":"",t.mapUv?"#define MAP_UV "+t.mapUv:"",t.alphaMapUv?"#define ALPHAMAP_UV "+t.alphaMapUv:"",t.lightMapUv?"#define LIGHTMAP_UV 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SHEEN_ROUGHNESSMAP_UV "+t.sheenRoughnessMapUv:"",t.specularMapUv?"#define SPECULARMAP_UV "+t.specularMapUv:"",t.specularColorMapUv?"#define SPECULAR_COLORMAP_UV "+t.specularColorMapUv:"",t.specularIntensityMapUv?"#define SPECULAR_INTENSITYMAP_UV "+t.specularIntensityMapUv:"",t.transmissionMapUv?"#define TRANSMISSIONMAP_UV "+t.transmissionMapUv:"",t.thicknessMapUv?"#define THICKNESSMAP_UV "+t.thicknessMapUv:"",t.vertexTangents&&t.flatShading===!1?"#define USE_TANGENT":"",t.vertexColors?"#define USE_COLOR":"",t.vertexAlphas?"#define USE_COLOR_ALPHA":"",t.vertexUv1s?"#define USE_UV1":"",t.vertexUv2s?"#define USE_UV2":"",t.vertexUv3s?"#define USE_UV3":"",t.pointsUvs?"#define USE_POINTS_UV":"",t.flatShading?"#define FLAT_SHADED":"",t.skinning?"#define USE_SKINNING":"",t.morphTargets?"#define USE_MORPHTARGETS":"",t.morphNormals&&t.flatShading===!1?"#define USE_MORPHNORMALS":"",t.morphColors?"#define USE_MORPHCOLORS":"",t.morphTargetsCount>0?"#define MORPHTARGETS_TEXTURE_STRIDE "+t.morphTextureStride:"",t.morphTargetsCount>0?"#define MORPHTARGETS_COUNT "+t.morphTargetsCount:"",t.doubleSided?"#define DOUBLE_SIDED":"",t.flipSided?"#define FLIP_SIDED":"",t.shadowMapEnabled?"#define USE_SHADOWMAP":"",t.shadowMapEnabled?"#define "+l:"",t.sizeAttenuation?"#define USE_SIZEATTENUATION":"",t.numLightProbes>0?"#define USE_LIGHT_PROBES":"",t.logarithmicDepthBuffer?"#define USE_LOGARITHMIC_DEPTH_BUFFER":"",t.reversedDepthBuffer?"#define USE_REVERSED_DEPTH_BUFFER":"","uniform mat4 modelMatrix;","uniform mat4 modelViewMatrix;","uniform mat4 projectionMatrix;","uniform mat4 viewMatrix;","uniform mat3 normalMatrix;","uniform vec3 cameraPosition;","uniform bool isOrthographic;","#ifdef USE_INSTANCING","	attribute mat4 instanceMatrix;","#endif","#ifdef USE_INSTANCING_COLOR","	attribute vec3 instanceColor;","#endif","#ifdef USE_INSTANCING_MORPH","	uniform sampler2D morphTexture;","#endif","attribute vec3 position;","attribute vec3 normal;","attribute vec2 uv;","#ifdef USE_UV1","	attribute vec2 uv1;","#endif","#ifdef USE_UV2","	attribute vec2 uv2;","#endif","#ifdef USE_UV3","	attribute vec2 uv3;","#endif","#ifdef USE_TANGENT","	attribute vec4 tangent;","#endif","#if defined( USE_COLOR_ALPHA )","	attribute vec4 color;","#elif defined( USE_COLOR )","	attribute vec3 color;","#endif","#ifdef USE_SKINNING","	attribute vec4 skinIndex;","	attribute vec4 skinWeight;","#endif",`
`].filter(rx).join(`
`),m=[VT(t),"#define SHADER_TYPE "+t.shaderType,"#define SHADER_NAME "+t.shaderName,p,t.useFog&&t.fog?"#define USE_FOG":"",t.useFog&&t.fogExp2?"#define FOG_EXP2":"",t.alphaToCoverage?"#define ALPHA_TO_COVERAGE":"",t.map?"#define USE_MAP":"",t.matcap?"#define USE_MATCAP":"",t.envMap?"#define USE_ENVMAP":"",t.envMap?"#define "+u:"",t.envMap?"#define "+c:"",t.envMap?"#define "+d:"",f?"#define CUBEUV_TEXEL_WIDTH "+f.texelWidth:"",f?"#define CUBEUV_TEXEL_HEIGHT "+f.texelHeight:"",f?"#define CUBEUV_MAX_MIP "+f.maxMip+".0":"",t.lightMap?"#define USE_LIGHTMAP":"",t.aoMap?"#define USE_AOMAP":"",t.bumpMap?"#define USE_BUMPMAP":"",t.normalMap?"#define USE_NORMALMAP":"",t.normalMapObjectSpace?"#define USE_NORMALMAP_OBJECTSPACE":"",t.normalMapTangentSpace?"#define USE_NORMALMAP_TANGENTSPACE":"",t.emissiveMap?"#define USE_EMISSIVEMAP":"",t.anisotropy?"#define USE_ANISOTROPY":"",t.anisotropyMap?"#define USE_ANISOTROPYMAP":"",t.clearcoat?"#define USE_CLEARCOAT":"",t.clearcoatMap?"#define USE_CLEARCOATMAP":"",t.clearcoatRoughnessMap?"#define USE_CLEARCOAT_ROUGHNESSMAP":"",t.clearcoatNormalMap?"#define USE_CLEARCOAT_NORMALMAP":"",t.dispersion?"#define USE_DISPERSION":"",t.iridescence?"#define USE_IRIDESCENCE":"",t.iridescenceMap?"#define USE_IRIDESCENCEMAP":"",t.iridescenceThicknessMap?"#define USE_IRIDESCENCE_THICKNESSMAP":"",t.specularMap?"#define USE_SPECULARMAP":"",t.specularColorMap?"#define USE_SPECULAR_COLORMAP":"",t.specularIntensityMap?"#define USE_SPECULAR_INTENSITYMAP":"",t.roughnessMap?"#define USE_ROUGHNESSMAP":"",t.metalnessMap?"#define USE_METALNESSMAP":"",t.alphaMap?"#define USE_ALPHAMAP":"",t.alphaTest?"#define USE_ALPHATEST":"",t.alphaHash?"#define USE_ALPHAHASH":"",t.sheen?"#define USE_SHEEN":"",t.sheenColorMap?"#define USE_SHEEN_COLORMAP":"",t.sheenRoughnessMap?"#define USE_SHEEN_ROUGHNESSMAP":"",t.transmission?"#define USE_TRANSMISSION":"",t.transmissionMap?"#define USE_TRANSMISSIONMAP":"",t.thicknessMap?"#define USE_THICKNESSMAP":"",t.vertexTangents&&t.flatShading===!1?"#define USE_TANGENT":"",t.vertexColors||t.instancingColor||t.batchingColor?"#define USE_COLOR":"",t.vertexAlphas?"#define USE_COLOR_ALPHA":"",t.vertexUv1s?"#define USE_UV1":"",t.vertexUv2s?"#define USE_UV2":"",t.vertexUv3s?"#define USE_UV3":"",t.pointsUvs?"#define USE_POINTS_UV":"",t.gradientMap?"#define USE_GRADIENTMAP":"",t.flatShading?"#define FLAT_SHADED":"",t.doubleSided?"#define DOUBLE_SIDED":"",t.flipSided?"#define FLIP_SIDED":"",t.shadowMapEnabled?"#define USE_SHADOWMAP":"",t.shadowMapEnabled?"#define "+l:"",t.premultipliedAlpha?"#define PREMULTIPLIED_ALPHA":"",t.numLightProbes>0?"#define USE_LIGHT_PROBES":"",t.decodeVideoTexture?"#define DECODE_VIDEO_TEXTURE":"",t.decodeVideoTextureEmissive?"#define DECODE_VIDEO_TEXTURE_EMISSIVE":"",t.logarithmicDepthBuffer?"#define USE_LOGARITHMIC_DEPTH_BUFFER":"",t.reversedDepthBuffer?"#define USE_REVERSED_DEPTH_BUFFER":"","uniform mat4 viewMatrix;","uniform vec3 cameraPosition;","uniform bool isOrthographic;",t.toneMapping!==Fr?"#define TONE_MAPPING":"",t.toneMapping!==Fr?is.tonemapping_pars_fragment:"",t.toneMapping!==Fr?yj("toneMapping",t.toneMapping):"",t.dithering?"#define DITHERING":"",t.opaque?"#define OPAQUE":"",is.colorspace_pars_fragment,Aj("linearToOutputTexel",t.outputColorSpace),bj(),t.useDepthPacking?"#define DEPTH_PACKING "+t.depthPacking:"",`
`].filter(rx).join(`
`)),a=BP(a),a=HT(a,t),a=UT(a,t),o=BP(o),o=HT(o,t),o=UT(o,t),a=kT(a),o=kT(o),t.isRawShaderMaterial!==!0&&(C=`#version 300 es
`,v=[h,"#define attribute in","#define varying out","#define texture2D texture"].join(`
`)+`
`+v,m=["#define varying in",t.glslVersion===on?"":"layout(location = 0) out highp vec4 pc_fragColor;",t.glslVersion===on?"":"#define gl_FragColor pc_fragColor","#define gl_FragDepthEXT gl_FragDepth","#define texture2D texture","#define textureCube texture","#define texture2DProj textureProj","#define texture2DLodEXT textureLod","#define texture2DProjLodEXT textureProjLod","#define textureCubeLodEXT textureLod","#define texture2DGradEXT textureGrad","#define texture2DProjGradEXT textureProjGrad","#define textureCubeGradEXT textureGrad"].join(`
`)+`
`+m);const w=C+v+a,P=C+m+o,B=LT(i,i.VERTEX_SHADER,w),S=LT(i,i.FRAGMENT_SHADER,P);i.attachShader(x,B),i.attachShader(x,S),t.index0AttributeName!==void 0?i.bindAttribLocation(x,0,t.index0AttributeName):t.morphTargets===!0&&i.bindAttribLocation(x,0,"position"),i.linkProgram(x);function I(D){if(r.debug.checkShaderErrors){const j=i.getProgramInfoLog(x)||"",q=i.getShaderInfoLog(B)||"",Q=i.getShaderInfoLog(S)||"",re=j.trim(),de=q.trim(),we=Q.trim();let ge=!0,Y=!0;if(i.getProgramParameter(x,i.LINK_STATUS)===!1)if(ge=!1,typeof r.debug.onShaderError=="function")r.debug.onShaderError(i,x,B,S);else{const Se=zT(i,B,"vertex"),W=zT(i,S,"fragment");rt("THREE.WebGLProgram: Shader Error "+i.getError()+" - VALIDATE_STATUS "+i.getProgramParameter(x,i.VALIDATE_STATUS)+`

Material Name: `+D.name+`
Material Type: `+D.type+`

Program Info Log: `+re+`
`+Se+`
`+W)}else re!==""?ze("WebGLProgram: Program Info Log:",re):(de===""||we==="")&&(Y=!1);Y&&(D.diagnostics={runnable:ge,programLog:re,vertexShader:{log:de,prefix:v},fragmentShader:{log:we,prefix:m}})}i.deleteShader(B),i.deleteShader(S),N=new Zb(i,x),T=Cj(i,x)}let N;this.getUniforms=function(){return N===void 0&&I(this),N};let T;this.getAttributes=function(){return T===void 0&&I(this),T};let R=t.rendererExtensionParallelShaderCompile===!1;return this.isReady=function(){return R===!1&&(R=i.getProgramParameter(x,pj)),R},this.destroy=function(){n.releaseStatesOfProgram(this),i.deleteProgram(x),this.program=void 0},this.type=t.shaderType,this.name=t.shaderName,this.id=mj++,this.cacheKey=e,this.usedTimes=1,this.program=x,this.vertexShader=B,this.fragmentShader=S,this}let kj=0;class Vj{constructor(){this.shaderCache=new Map,this.materialCache=new Map}update(e){const t=e.vertexShader,n=e.fragmentShader,i=this._getShaderStage(t),s=this._getShaderStage(n),a=this._getShaderCacheForMaterial(e);return a.has(i)===!1&&(a.add(i),i.usedTimes++),a.has(s)===!1&&(a.add(s),s.usedTimes++),this}remove(e){const t=this.materialCache.get(e);for(const n of t)n.usedTimes--,n.usedTimes===0&&this.shaderCache.delete(n.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 n===void 0&&(n=new Set,t.set(e,n)),n}_getShaderStage(e){const t=this.shaderCache;let n=t.get(e);return n===void 0&&(n=new jj(e),t.set(e,n)),n}}class jj{constructor(e){this.id=kj++,this.code=e,this.usedTimes=0}}function Xj(r,e,t,n,i,s,a){const o=new FC,l=new Vj,u=new Set,c=[],d=new Map,f=i.logarithmicDepthBuffer;let h=i.precision;const p={MeshDepthMaterial:"depth",MeshDistanceMaterial:"distance",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 x(T){return u.add(T),T===0?"uv":`uv${T}`}function v(T,R,D,j,q){const Q=j.fog,re=q.geometry,de=T.isMeshStandardMaterial?j.environment:null,we=(T.isMeshStandardMaterial?t:e).get(T.envMap||de),ge=we&&we.mapping===Jd?we.image.height:null,Y=p[T.type];T.precision!==null&&(h=i.getMaxPrecision(T.precision),h!==T.precision&&ze("WebGLProgram.getParameters:",T.precision,"not supported, using",h,"instead."));const Se=re.morphAttributes.position||re.morphAttributes.normal||re.morphAttributes.color,W=Se!==void 0?Se.length:0;let fe=0;re.morphAttributes.position!==void 0&&(fe=1),re.morphAttributes.normal!==void 0&&(fe=2),re.morphAttributes.color!==void 0&&(fe=3);let xe,dt,ve,ee;if(Y){const Ms=hf[Y];xe=Ms.vertexShader,dt=Ms.fragmentShader}else xe=T.vertexShader,dt=T.fragmentShader,l.update(T),ve=l.getVertexShaderID(T),ee=l.getFragmentShaderID(T);const ue=r.getRenderTarget(),Ue=r.state.buffers.depth.getReversed(),$e=q.isInstancedMesh===!0,He=q.isBatchedMesh===!0,bt=!!T.map,$t=!!T.matcap,zn=!!we,Me=!!T.aoMap,Et=!!T.lightMap,ft=!!T.bumpMap,Yt=!!T.normalMap,se=!!T.displacementMap,br=!!T.emissiveMap,vn=!!T.metalnessMap,er=!!T.roughnessMap,Jt=T.anisotropy>0,$=T.clearcoat>0,V=T.dispersion>0,Be=T.iridescence>0,at=T.sheen>0,De=T.transmission>0,Qe=Jt&&!!T.anisotropyMap,Cn=$&&!!T.clearcoatMap,kt=$&&!!T.clearcoatNormalMap,yn=$&&!!T.clearcoatRoughnessMap,Vr=Be&&!!T.iridescenceMap,jt=Be&&!!T.iridescenceThicknessMap,Bn=at&&!!T.sheenColorMap,ir=at&&!!T.sheenRoughnessMap,Lr=!!T.specularMap,Kt=!!T.specularColorMap,di=!!T.specularIntensityMap,Te=De&&!!T.transmissionMap,Gn=De&&!!T.thicknessMap,rn=!!T.gradientMap,cn=!!T.alphaMap,sn=T.alphaTest>0,Vt=!!T.alphaHash,Mn=!!T.extensions;let Ti=Fr;T.toneMapped&&(ue===null||ue.isXRRenderTarget===!0)&&(Ti=r.toneMapping);const Js={shaderID:Y,shaderType:T.type,shaderName:T.name,vertexShader:xe,fragmentShader:dt,defines:T.defines,customVertexShaderID:ve,customFragmentShaderID:ee,isRawShaderMaterial:T.isRawShaderMaterial===!0,glslVersion:T.glslVersion,precision:h,batching:He,batchingColor:He&&q._colorsTexture!==null,instancing:$e,instancingColor:$e&&q.instanceColor!==null,instancingMorph:$e&&q.morphTexture!==null,outputColorSpace:ue===null?r.outputColorSpace:ue.isXRRenderTarget===!0?ue.texture.colorSpace:af,alphaToCoverage:!!T.alphaToCoverage,map:bt,matcap:$t,envMap:zn,envMapMode:zn&&we.mapping,envMapCubeUVHeight:ge,aoMap:Me,lightMap:Et,bumpMap:ft,normalMap:Yt,displacementMap:se,emissiveMap:br,normalMapObjectSpace:Yt&&T.normalMapType===Ay,normalMapTangentSpace:Yt&&T.normalMapType===Cc,metalnessMap:vn,roughnessMap:er,anisotropy:Jt,anisotropyMap:Qe,clearcoat:$,clearcoatMap:Cn,clearcoatNormalMap:kt,clearcoatRoughnessMap:yn,dispersion:V,iridescence:Be,iridescenceMap:Vr,iridescenceThicknessMap:jt,sheen:at,sheenColorMap:Bn,sheenRoughnessMap:ir,specularMap:Lr,specularColorMap:Kt,specularIntensityMap:di,transmission:De,transmissionMap:Te,thicknessMap:Gn,gradientMap:rn,opaque:T.transparent===!1&&T.blending===Vo&&T.alphaToCoverage===!1,alphaMap:cn,alphaTest:sn,alphaHash:Vt,combine:T.combine,mapUv:bt&&x(T.map.channel),aoMapUv:Me&&x(T.aoMap.channel),lightMapUv:Et&&x(T.lightMap.channel),bumpMapUv:ft&&x(T.bumpMap.channel),normalMapUv:Yt&&x(T.normalMap.channel),displacementMapUv:se&&x(T.displacementMap.channel),emissiveMapUv:br&&x(T.emissiveMap.channel),metalnessMapUv:vn&&x(T.metalnessMap.channel),roughnessMapUv:er&&x(T.roughnessMap.channel),anisotropyMapUv:Qe&&x(T.anisotropyMap.channel),clearcoatMapUv:Cn&&x(T.clearcoatMap.channel),clearcoatNormalMapUv:kt&&x(T.clearcoatNormalMap.channel),clearcoatRoughnessMapUv:yn&&x(T.clearcoatRoughnessMap.channel),iridescenceMapUv:Vr&&x(T.iridescenceMap.channel),iridescenceThicknessMapUv:jt&&x(T.iridescenceThicknessMap.channel),sheenColorMapUv:Bn&&x(T.sheenColorMap.channel),sheenRoughnessMapUv:ir&&x(T.sheenRoughnessMap.channel),specularMapUv:Lr&&x(T.specularMap.channel),specularColorMapUv:Kt&&x(T.specularColorMap.channel),specularIntensityMapUv:di&&x(T.specularIntensityMap.channel),transmissionMapUv:Te&&x(T.transmissionMap.channel),thicknessMapUv:Gn&&x(T.thicknessMap.channel),alphaMapUv:cn&&x(T.alphaMap.channel),vertexTangents:!!re.attributes.tangent&&(Yt||Jt),vertexColors:T.vertexColors,vertexAlphas:T.vertexColors===!0&&!!re.attributes.color&&re.attributes.color.itemSize===4,pointsUvs:q.isPoints===!0&&!!re.attributes.uv&&(bt||cn),fog:!!Q,useFog:T.fog===!0,fogExp2:!!Q&&Q.isFogExp2,flatShading:T.flatShading===!0&&T.wireframe===!1,sizeAttenuation:T.sizeAttenuation===!0,logarithmicDepthBuffer:f,reversedDepthBuffer:Ue,skinning:q.isSkinnedMesh===!0,morphTargets:re.morphAttributes.position!==void 0,morphNormals:re.morphAttributes.normal!==void 0,morphColors:re.morphAttributes.color!==void 0,morphTargetsCount:W,morphTextureStride:fe,numDirLights:R.directional.length,numPointLights:R.point.length,numSpotLights:R.spot.length,numSpotLightMaps:R.spotLightMap.length,numRectAreaLights:R.rectArea.length,numHemiLights:R.hemi.length,numDirLightShadows:R.directionalShadowMap.length,numPointLightShadows:R.pointShadowMap.length,numSpotLightShadows:R.spotShadowMap.length,numSpotLightShadowsWithMaps:R.numSpotLightShadowsWithMaps,numLightProbes:R.numLightProbes,numClippingPlanes:a.numPlanes,numClipIntersection:a.numIntersection,dithering:T.dithering,shadowMapEnabled:r.shadowMap.enabled&&D.length>0,shadowMapType:r.shadowMap.type,toneMapping:Ti,decodeVideoTexture:bt&&T.map.isVideoTexture===!0&&$r.getTransfer(T.map.colorSpace)===$n,decodeVideoTextureEmissive:br&&T.emissiveMap.isVideoTexture===!0&&$r.getTransfer(T.emissiveMap.colorSpace)===$n,premultipliedAlpha:T.premultipliedAlpha,doubleSided:T.side===Xs,flipSided:T.side===Qi,useDepthPacking:T.depthPacking>=0,depthPacking:T.depthPacking||0,index0AttributeName:T.index0AttributeName,extensionClipCullDistance:Mn&&T.extensions.clipCullDistance===!0&&n.has("WEBGL_clip_cull_distance"),extensionMultiDraw:(Mn&&T.extensions.multiDraw===!0||He)&&n.has("WEBGL_multi_draw"),rendererExtensionParallelShaderCompile:n.has("KHR_parallel_shader_compile"),customProgramCacheKey:T.customProgramCacheKey()};return Js.vertexUv1s=u.has(1),Js.vertexUv2s=u.has(2),Js.vertexUv3s=u.has(3),u.clear(),Js}function m(T){const R=[];if(T.shaderID?R.push(T.shaderID):(R.push(T.customVertexShaderID),R.push(T.customFragmentShaderID)),T.defines!==void 0)for(const D in T.defines)R.push(D),R.push(T.defines[D]);return T.isRawShaderMaterial===!1&&(C(R,T),w(R,T),R.push(r.outputColorSpace)),R.push(T.customProgramCacheKey),R.join()}function C(T,R){T.push(R.precision),T.push(R.outputColorSpace),T.push(R.envMapMode),T.push(R.envMapCubeUVHeight),T.push(R.mapUv),T.push(R.alphaMapUv),T.push(R.lightMapUv),T.push(R.aoMapUv),T.push(R.bumpMapUv),T.push(R.normalMapUv),T.push(R.displacementMapUv),T.push(R.emissiveMapUv),T.push(R.metalnessMapUv),T.push(R.roughnessMapUv),T.push(R.anisotropyMapUv),T.push(R.clearcoatMapUv),T.push(R.clearcoatNormalMapUv),T.push(R.clearcoatRoughnessMapUv),T.push(R.iridescenceMapUv),T.push(R.iridescenceThicknessMapUv),T.push(R.sheenColorMapUv),T.push(R.sheenRoughnessMapUv),T.push(R.specularMapUv),T.push(R.specularColorMapUv),T.push(R.specularIntensityMapUv),T.push(R.transmissionMapUv),T.push(R.thicknessMapUv),T.push(R.combine),T.push(R.fogExp2),T.push(R.sizeAttenuation),T.push(R.morphTargetsCount),T.push(R.morphAttributeCount),T.push(R.numDirLights),T.push(R.numPointLights),T.push(R.numSpotLights),T.push(R.numSpotLightMaps),T.push(R.numHemiLights),T.push(R.numRectAreaLights),T.push(R.numDirLightShadows),T.push(R.numPointLightShadows),T.push(R.numSpotLightShadows),T.push(R.numSpotLightShadowsWithMaps),T.push(R.numLightProbes),T.push(R.shadowMapType),T.push(R.toneMapping),T.push(R.numClippingPlanes),T.push(R.numClipIntersection),T.push(R.depthPacking)}function w(T,R){o.disableAll(),R.instancing&&o.enable(0),R.instancingColor&&o.enable(1),R.instancingMorph&&o.enable(2),R.matcap&&o.enable(3),R.envMap&&o.enable(4),R.normalMapObjectSpace&&o.enable(5),R.normalMapTangentSpace&&o.enable(6),R.clearcoat&&o.enable(7),R.iridescence&&o.enable(8),R.alphaTest&&o.enable(9),R.vertexColors&&o.enable(10),R.vertexAlphas&&o.enable(11),R.vertexUv1s&&o.enable(12),R.vertexUv2s&&o.enable(13),R.vertexUv3s&&o.enable(14),R.vertexTangents&&o.enable(15),R.anisotropy&&o.enable(16),R.alphaHash&&o.enable(17),R.batching&&o.enable(18),R.dispersion&&o.enable(19),R.batchingColor&&o.enable(20),R.gradientMap&&o.enable(21),T.push(o.mask),o.disableAll(),R.fog&&o.enable(0),R.useFog&&o.enable(1),R.flatShading&&o.enable(2),R.logarithmicDepthBuffer&&o.enable(3),R.reversedDepthBuffer&&o.enable(4),R.skinning&&o.enable(5),R.morphTargets&&o.enable(6),R.morphNormals&&o.enable(7),R.morphColors&&o.enable(8),R.premultipliedAlpha&&o.enable(9),R.shadowMapEnabled&&o.enable(10),R.doubleSided&&o.enable(11),R.flipSided&&o.enable(12),R.useDepthPacking&&o.enable(13),R.dithering&&o.enable(14),R.transmission&&o.enable(15),R.sheen&&o.enable(16),R.opaque&&o.enable(17),R.pointsUvs&&o.enable(18),R.decodeVideoTexture&&o.enable(19),R.decodeVideoTextureEmissive&&o.enable(20),R.alphaToCoverage&&o.enable(21),T.push(o.mask)}function P(T){const R=p[T.type];let D;if(R){const j=hf[R];D=US.clone(j.uniforms)}else D=T.uniforms;return D}function B(T,R){let D=d.get(R);return D!==void 0?++D.usedTimes:(D=new Uj(r,R,T,s),c.push(D),d.set(R,D)),D}function S(T){if(--T.usedTimes===0){const R=c.indexOf(T);c[R]=c[c.length-1],c.pop(),d.delete(T.cacheKey),T.destroy()}}function I(T){l.remove(T)}function N(){l.dispose()}return{getParameters:v,getProgramCacheKey:m,getUniforms:P,acquireProgram:B,releaseProgram:S,releaseShaderCache:I,programs:c,dispose:N}}function Gj(){let r=new WeakMap;function e(a){return r.has(a)}function t(a){let o=r.get(a);return o===void 0&&(o={},r.set(a,o)),o}function n(a){r.delete(a)}function i(a,o,l){r.get(a)[o]=l}function s(){r=new WeakMap}return{has:e,get:t,remove:n,update:i,dispose:s}}function Wj(r,e){return 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u(d,f){t.length>1&&t.sort(d||Wj),n.length>1&&n.sort(f||jT),i.length>1&&i.sort(f||jT)}function c(){for(let d=e,f=r.length;d<f;d++){const h=r[d];if(h.id===null)break;h.id=null,h.object=null,h.geometry=null,h.material=null,h.group=null}}return{opaque:t,transmissive:n,transparent:i,init:s,push:o,unshift:l,finish:c,sort:u}}function Qj(){let r=new WeakMap;function e(n,i){const s=r.get(n);let a;return s===void 0?(a=new XT,r.set(n,[a])):i>=s.length?(a=new XT,s.push(a)):a=s[i],a}function t(){r=new WeakMap}return{get:e,dispose:t}}function Zj(){const r={};return{get:function(e){if(r[e.id]!==void 0)return r[e.id];let t;switch(e.type){case"DirectionalLight":t={direction:new J,color:new Vn};break;case"SpotLight":t={position:new J,direction:new J,color:new Vn,distance:0,coneCos:0,penumbraCos:0,decay:0};break;case"PointLight":t={position:new J,color:new Vn,distance:0,decay:0};break;case"HemisphereLight":t={direction:new J,skyColor:new Vn,groundColor:new Vn};break;case"RectAreaLight":t={color:new Vn,position:new J,halfWidth:new J,halfHeight:new J};break}return r[e.id]=t,t}}}function Yj(){const r={};return{get:function(e){if(r[e.id]!==void 0)return r[e.id];let t;switch(e.type){case"DirectionalLight":t={shadowIntensity:1,shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new ct};break;case"SpotLight":t={shadowIntensity:1,shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new ct};break;case"PointLight":t={shadowIntensity:1,shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new ct,shadowCameraNear:1,shadowCameraFar:1e3};break}return r[e.id]=t,t}}}let Jj=0;function Kj(r,e){return(e.castShadow?2:0)-(r.castShadow?2:0)+(e.map?1:0)-(r.map?1:0)}function qj(r){const e=new 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re=null;if(D.shadow&&D.shadow.map&&(D.shadow.map.texture.format===Al?re=D.shadow.map.texture:re=D.shadow.map.depthTexture||D.shadow.map.texture),D.isAmbientLight)c+=j.r*q,d+=j.g*q,f+=j.b*q;else if(D.isLightProbe){for(let de=0;de<9;de++)n.probe[de].addScaledVector(D.sh.coefficients[de],q);I++}else if(D.isDirectionalLight){const de=e.get(D);if(de.color.copy(D.color).multiplyScalar(D.intensity),D.castShadow){const we=D.shadow,ge=t.get(D);ge.shadowIntensity=we.intensity,ge.shadowBias=we.bias,ge.shadowNormalBias=we.normalBias,ge.shadowRadius=we.radius,ge.shadowMapSize=we.mapSize,n.directionalShadow[h]=ge,n.directionalShadowMap[h]=re,n.directionalShadowMatrix[h]=D.shadow.matrix,C++}n.directional[h]=de,h++}else if(D.isSpotLight){const de=e.get(D);de.position.setFromMatrixPosition(D.matrixWorld),de.color.copy(j).multiplyScalar(q),de.distance=Q,de.coneCos=Math.cos(D.angle),de.penumbraCos=Math.cos(D.angle*(1-D.penumbra)),de.decay=D.decay,n.spot[x]=de;const we=D.shadow;if(D.map&&(n.spotLightMap[B]=D.map,B++,we.updateMatrices(D),D.castShadow&&S++),n.spotLightMatrix[x]=we.matrix,D.castShadow){const ge=t.get(D);ge.shadowIntensity=we.intensity,ge.shadowBias=we.bias,ge.shadowNormalBias=we.normalBias,ge.shadowRadius=we.radius,ge.shadowMapSize=we.mapSize,n.spotShadow[x]=ge,n.spotShadowMap[x]=re,P++}x++}else if(D.isRectAreaLight){const de=e.get(D);de.color.copy(j).multiplyScalar(q),de.halfWidth.set(D.width*.5,0,0),de.halfHeight.set(0,D.height*.5,0),n.rectArea[v]=de,v++}else if(D.isPointLight){const de=e.get(D);if(de.color.copy(D.color).multiplyScalar(D.intensity),de.distance=D.distance,de.decay=D.decay,D.castShadow){const 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N=n.hash;(N.directionalLength!==h||N.pointLength!==p||N.spotLength!==x||N.rectAreaLength!==v||N.hemiLength!==m||N.numDirectionalShadows!==C||N.numPointShadows!==w||N.numSpotShadows!==P||N.numSpotMaps!==B||N.numLightProbes!==I)&&(n.directional.length=h,n.spot.length=x,n.rectArea.length=v,n.point.length=p,n.hemi.length=m,n.directionalShadow.length=C,n.directionalShadowMap.length=C,n.pointShadow.length=w,n.pointShadowMap.length=w,n.spotShadow.length=P,n.spotShadowMap.length=P,n.directionalShadowMatrix.length=C,n.pointShadowMatrix.length=w,n.spotLightMatrix.length=P+B-S,n.spotLightMap.length=B,n.numSpotLightShadowsWithMaps=S,n.numLightProbes=I,N.directionalLength=h,N.pointLength=p,N.spotLength=x,N.rectAreaLength=v,N.hemiLength=m,N.numDirectionalShadows=C,N.numPointShadows=w,N.numSpotShadows=P,N.numSpotMaps=B,N.numLightProbes=I,n.version=Jj++)}function l(u,c){let d=0,f=0,h=0,p=0,x=0;const v=c.matrixWorldInverse;for(let m=0,C=u.length;m<C;m++){const w=u[m];if(w.isDirectionalLight){const P=n.directional[d];P.direction.setFromMatrixPosition(w.matrixWorld),i.setFromMatrixPosition(w.target.matrixWorld),P.direction.sub(i),P.direction.transformDirection(v),d++}else if(w.isSpotLight){const P=n.spot[h];P.position.setFromMatrixPosition(w.matrixWorld),P.position.applyMatrix4(v),P.direction.setFromMatrixPosition(w.matrixWorld),i.setFromMatrixPosition(w.target.matrixWorld),P.direction.sub(i),P.direction.transformDirection(v),h++}else if(w.isRectAreaLight){const P=n.rectArea[p];P.position.setFromMatrixPosition(w.matrixWorld),P.position.applyMatrix4(v),a.identity(),s.copy(w.matrixWorld),s.premultiply(v),a.extractRotation(s),P.halfWidth.set(w.width*.5,0,0),P.halfHeight.set(0,w.height*.5,0),P.halfWidth.applyMatrix4(a),P.halfHeight.applyMatrix4(a),p++}else if(w.isPointLight){const P=n.point[f];P.position.setFromMatrixPosition(w.matrixWorld),P.position.applyMatrix4(v),f++}else if(w.isHemisphereLight){const P=n.hemi[x];P.direction.setFromMatrixPosition(w.matrixWorld),P.direction.transformDirection(v),x++}}}return{setup:o,setupView:l,state:n}}function GT(r){const e=new qj(r),t=[],n=[];function i(c){u.camera=c,t.length=0,n.length=0}function s(c){t.push(c)}function a(c){n.push(c)}function o(){e.setup(t)}function l(c){e.setupView(t,c)}const u={lightsArray:t,shadowsArray:n,camera:null,lights:e,transmissionRenderTarget:{}};return{init:i,state:u,setupLights:o,setupLightsView:l,pushLight:s,pushShadow:a}}function _j(r){let e=new WeakMap;function t(i,s=0){const a=e.get(i);let o;return a===void 0?(o=new GT(r),e.set(i,[o])):s>=a.length?(o=new GT(r),a.push(o)):o=a[s],o}function n(){e=new WeakMap}return{get:t,dispose:n}}const $j=`void main() {
	gl_Position = vec4( position, 1.0 );
}`,eX=`uniform sampler2D shadow_pass;
uniform vec2 resolution;
uniform float radius;
void main() {
	const float samples = float( VSM_SAMPLES );
	float mean = 0.0;
	float squared_mean = 0.0;
	float uvStride = samples <= 1.0 ? 0.0 : 2.0 / ( samples - 1.0 );
	float uvStart = samples <= 1.0 ? 0.0 : - 1.0;
	for ( float i = 0.0; i < samples; i ++ ) {
		float uvOffset = uvStart + i * uvStride;
		#ifdef HORIZONTAL_PASS
			vec2 distribution = texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( uvOffset, 0.0 ) * radius ) / resolution ).rg;
			mean += distribution.x;
			squared_mean += distribution.y * distribution.y + distribution.x * distribution.x;
		#else
			float depth = texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( 0.0, uvOffset ) * radius ) / resolution ).r;
			mean += depth;
			squared_mean += depth * depth;
		#endif
	}
	mean = mean / samples;
	squared_mean = squared_mean / samples;
	float std_dev = sqrt( max( 0.0, squared_mean - mean * mean ) );
	gl_FragColor = vec4( mean, std_dev, 0.0, 1.0 );
}`,tX=[new J(1,0,0),new J(-1,0,0),new J(0,1,0),new J(0,-1,0),new J(0,0,1),new J(0,0,-1)],nX=[new J(0,-1,0),new J(0,-1,0),new J(0,0,1),new J(0,0,-1),new J(0,-1,0),new J(0,-1,0)],WT=new Cr,ix=new J,MP=new J;function rX(r,e,t){let n=new Wv;const i=new ct,s=new ct,a=new Ei,o=new F5,l=new R5,u={},c=t.maxTextureSize,d={[ja]:Qi,[Qi]:ja,[Xs]:Xs},f=new $u({defines:{VSM_SAMPLES:8},uniforms:{shadow_pass:{value:null},resolution:{value:new ct},radius:{value:4}},vertexShader:$j,fragmentShader:eX}),h=f.clone();h.defines.HORIZONTAL_PASS=1;const p=new Ni;p.setAttribute("position",new ga(new Float32Array([-1,-1,.5,3,-1,.5,-1,3,.5]),3));const x=new Gs(p,f),v=this;this.enabled=!1,this.autoUpdate=!0,this.needsUpdate=!1,this.type=tu;let m=this.type;this.render=function(S,I,N){if(v.enabled===!1||v.autoUpdate===!1&&v.needsUpdate===!1||S.length===0)return;S.type===Vu&&(ze("WebGLShadowMap: PCFSoftShadowMap has been deprecated. Using PCFShadowMap instead."),S.type=tu);const T=r.getRenderTarget(),R=r.getActiveCubeFace(),D=r.getActiveMipmapLevel(),j=r.state;j.setBlending(Xa),j.buffers.depth.getReversed()===!0?j.buffers.color.setClear(0,0,0,0):j.buffers.color.setClear(1,1,1,1),j.buffers.depth.setTest(!0),j.setScissorTest(!1);const q=m!==this.type;q&&I.traverse(function(Q){Q.material&&(Array.isArray(Q.material)?Q.material.forEach(re=>re.needsUpdate=!0):Q.material.needsUpdate=!0)});for(let Q=0,re=S.length;Q<re;Q++){const de=S[Q],we=de.shadow;if(we===void 0){ze("WebGLShadowMap:",de,"has no shadow.");continue}if(we.autoUpdate===!1&&we.needsUpdate===!1)continue;i.copy(we.mapSize);const ge=we.getFrameExtents();if(i.multiply(ge),s.copy(we.mapSize),(i.x>c||i.y>c)&&(i.x>c&&(s.x=Math.floor(c/ge.x),i.x=s.x*ge.x,we.mapSize.x=s.x),i.y>c&&(s.y=Math.floor(c/ge.y),i.y=s.y*ge.y,we.mapSize.y=s.y)),we.map===null||q===!0){if(we.map!==null&&(we.map.depthTexture!==null&&(we.map.depthTexture.dispose(),we.map.depthTexture=null),we.map.dispose()),this.type===el){if(de.isPointLight){ze("WebGLShadowMap: VSM shadow maps are not supported for PointLights. Use PCF or BasicShadowMap instead.");continue}we.map=new fd(i.x,i.y,{format:Al,type:pa,minFilter:ms,magFilter:ms,generateMipmaps:!1}),we.map.texture.name=de.name+".shadowMap",we.map.depthTexture=new Vl(i.x,i.y,ha),we.map.depthTexture.name=de.name+".shadowMapDepth",we.map.depthTexture.format=jo,we.map.depthTexture.compareFunction=null,we.map.depthTexture.minFilter=Cs,we.map.depthTexture.magFilter=Cs}else{de.isPointLight?(we.map=new ZC(i.x),we.map.depthTexture=new d5(i.x,Ls)):(we.map=new fd(i.x,i.y),we.map.depthTexture=new Vl(i.x,i.y,Ls)),we.map.depthTexture.name=de.name+".shadowMap",we.map.depthTexture.format=jo;const Se=r.state.buffers.depth.getReversed();this.type===tu?(we.map.depthTexture.compareFunction=Se?z:A,we.map.depthTexture.minFilter=ms,we.map.depthTexture.magFilter=ms):(we.map.depthTexture.compareFunction=null,we.map.depthTexture.minFilter=Cs,we.map.depthTexture.magFilter=Cs)}we.camera.updateProjectionMatrix()}const Y=we.map.isWebGLCubeRenderTarget?6:1;for(let Se=0;Se<Y;Se++){if(we.map.isWebGLCubeRenderTarget)r.setRenderTarget(we.map,Se),r.clear();else{Se===0&&(r.setRenderTarget(we.map),r.clear());const W=we.getViewport(Se);a.set(s.x*W.x,s.y*W.y,s.x*W.z,s.y*W.w),j.viewport(a)}if(de.isPointLight){const W=we.camera,fe=we.matrix,xe=de.distance||W.far;xe!==W.far&&(W.far=xe,W.updateProjectionMatrix()),ix.setFromMatrixPosition(de.matrixWorld),W.position.copy(ix),MP.copy(W.position),MP.add(tX[Se]),W.up.copy(nX[Se]),W.lookAt(MP),W.updateMatrixWorld(),fe.makeTranslation(-ix.x,-ix.y,-ix.z),WT.multiplyMatrices(W.projectionMatrix,W.matrixWorldInverse),we._frustum.setFromProjectionMatrix(WT,W.coordinateSystem,W.reversedDepth)}else we.updateMatrices(de);n=we.getFrustum(),P(I,N,we.camera,de,this.type)}we.isPointLightShadow!==!0&&this.type===el&&C(we,N),we.needsUpdate=!1}m=this.type,v.needsUpdate=!1,r.setRenderTarget(T,R,D)};function C(S,I){const 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at=V.isWebGLCubeRenderTarget===!0;if(t.bindFramebuffer(r.FRAMEBUFFER,$),!(V.depthTexture&&V.depthTexture.isDepthTexture))throw new Error("renderTarget.depthTexture must be an instance of THREE.DepthTexture");const De=n.get(V.depthTexture);if(De.__renderTarget=V,(!De.__webglTexture||V.depthTexture.image.width!==V.width||V.depthTexture.image.height!==V.height)&&(V.depthTexture.image.width=V.width,V.depthTexture.image.height=V.height,V.depthTexture.needsUpdate=!0),at){if(De.__webglInit===void 0&&(De.__webglInit=!0,V.depthTexture.addEventListener("dispose",S)),De.__webglTexture===void 0){De.__webglTexture=r.createTexture(),t.bindTexture(r.TEXTURE_CUBE_MAP,De.__webglTexture),fe(r.TEXTURE_CUBE_MAP,V.depthTexture);const Vr=s.convert(V.depthTexture.format),jt=s.convert(V.depthTexture.type);let Bn;V.depthTexture.format===jo?Bn=r.DEPTH_COMPONENT24:V.depthTexture.format===vl&&(Bn=r.DEPTH24_STENCIL8);for(let 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Be.__webglFramebuffer[kt]=r.createFramebuffer()}else{if(V.mipmaps&&V.mipmaps.length>0){Be.__webglFramebuffer=[];for(let kt=0;kt<V.mipmaps.length;kt++)Be.__webglFramebuffer[kt]=r.createFramebuffer()}else Be.__webglFramebuffer=r.createFramebuffer();if(Cn)for(let kt=0,yn=De.length;kt<yn;kt++){const Vr=n.get(De[kt]);Vr.__webglTexture===void 0&&(Vr.__webglTexture=r.createTexture(),a.memory.textures++)}if($.samples>0&&br($)===!1){Be.__webglMultisampledFramebuffer=r.createFramebuffer(),Be.__webglColorRenderbuffer=[],t.bindFramebuffer(r.FRAMEBUFFER,Be.__webglMultisampledFramebuffer);for(let kt=0;kt<De.length;kt++){const yn=De[kt];Be.__webglColorRenderbuffer[kt]=r.createRenderbuffer(),r.bindRenderbuffer(r.RENDERBUFFER,Be.__webglColorRenderbuffer[kt]);const Vr=s.convert(yn.format,yn.colorSpace),jt=s.convert(yn.type),Bn=w(yn.internalFormat,Vr,jt,yn.colorSpace,$.isXRRenderTarget===!0),ir=se($);r.renderbufferStorageMultisample(r.RENDERBUFFER,ir,Bn,$.width,$.height),r.framebufferRenderbuffer(r.FRAMEBUFFER,r.COLOR_ATTACHMENT0+kt,r.RENDERBUFFER,Be.__webglColorRenderbuffer[kt])}r.bindRenderbuffer(r.RENDERBUFFER,null),$.depthBuffer&&(Be.__webglDepthRenderbuffer=r.createRenderbuffer(),$e(Be.__webglDepthRenderbuffer,$,!0)),t.bindFramebuffer(r.FRAMEBUFFER,null)}}if(Qe){t.bindTexture(r.TEXTURE_CUBE_MAP,at.__webglTexture),fe(r.TEXTURE_CUBE_MAP,V);for(let kt=0;kt<6;kt++)if(V.mipmaps&&V.mipmaps.length>0)for(let yn=0;yn<V.mipmaps.length;yn++)Ue(Be.__webglFramebuffer[kt][yn],$,V,r.COLOR_ATTACHMENT0,r.TEXTURE_CUBE_MAP_POSITIVE_X+kt,yn);else Ue(Be.__webglFramebuffer[kt],$,V,r.COLOR_ATTACHMENT0,r.TEXTURE_CUBE_MAP_POSITIVE_X+kt,0);v(V)&&m(r.TEXTURE_CUBE_MAP),t.unbindTexture()}else if(Cn){for(let kt=0,yn=De.length;kt<yn;kt++){const Vr=De[kt],jt=n.get(Vr);let Bn=r.TEXTURE_2D;($.isWebGL3DRenderTarget||$.isWebGLArrayRenderTarget)&&(Bn=$.isWebGL3DRenderTarget?r.TEXTURE_3D:r.TEXTURE_2D_ARRAY),t.bindTexture(Bn,jt.__webglTexture),fe(Bn,Vr),Ue(Be.__webglFramebuffer,$,Vr,r.COLOR_ATTACHMENT0+kt,Bn,0),v(Vr)&&m(Bn)}t.unbindTexture()}else{let kt=r.TEXTURE_2D;if(($.isWebGL3DRenderTarget||$.isWebGLArrayRenderTarget)&&(kt=$.isWebGL3DRenderTarget?r.TEXTURE_3D:r.TEXTURE_2D_ARRAY),t.bindTexture(kt,at.__webglTexture),fe(kt,V),V.mipmaps&&V.mipmaps.length>0)for(let yn=0;yn<V.mipmaps.length;yn++)Ue(Be.__webglFramebuffer[yn],$,V,r.COLOR_ATTACHMENT0,kt,yn);else Ue(Be.__webglFramebuffer,$,V,r.COLOR_ATTACHMENT0,kt,0);v(V)&&m(kt),t.unbindTexture()}$.depthBuffer&&bt($)}function Me($){const V=$.textures;for(let Be=0,at=V.length;Be<at;Be++){const De=V[Be];if(v(De)){const Qe=C($),Cn=n.get(De).__webglTexture;t.bindTexture(Qe,Cn),m(Qe),t.unbindTexture()}}}const Et=[],ft=[];function Yt($){if($.samples>0){if(br($)===!1){const V=$.textures,Be=$.width,at=$.height;let De=r.COLOR_BUFFER_BIT;const Qe=$.stencilBuffer?r.DEPTH_STENCIL_ATTACHMENT:r.DEPTH_ATTACHMENT,Cn=n.get($),kt=V.length>1;if(kt)for(let Vr=0;Vr<V.length;Vr++)t.bindFramebuffer(r.FRAMEBUFFER,Cn.__webglMultisampledFramebuffer),r.framebufferRenderbuffer(r.FRAMEBUFFER,r.COLOR_ATTACHMENT0+Vr,r.RENDERBUFFER,null),t.bindFramebuffer(r.FRAMEBUFFER,Cn.__webglFramebuffer),r.framebufferTexture2D(r.DRAW_FRAMEBUFFER,r.COLOR_ATTACHMENT0+Vr,r.TEXTURE_2D,null,0);t.bindFramebuffer(r.READ_FRAMEBUFFER,Cn.__webglMultisampledFramebuffer);const yn=$.texture.mipmaps;yn&&yn.length>0?t.bindFramebuffer(r.DRAW_FRAMEBUFFER,Cn.__webglFramebuffer[0]):t.bindFramebuffer(r.DRAW_FRAMEBUFFER,Cn.__webglFramebuffer);for(let Vr=0;Vr<V.length;Vr++){if($.resolveDepthBuffer&&($.depthBuffer&&(De|=r.DEPTH_BUFFER_BIT),$.stencilBuffer&&$.resolveStencilBuffer&&(De|=r.STENCIL_BUFFER_BIT)),kt){r.framebufferRenderbuffer(r.READ_FRAMEBUFFER,r.COLOR_ATTACHMENT0,r.RENDERBUFFER,Cn.__webglColorRenderbuffer[Vr]);const jt=n.get(V[Vr]).__webglTexture;r.framebufferTexture2D(r.DRAW_FRAMEBUFFER,r.COLOR_ATTACHMENT0,r.TEXTURE_2D,jt,0)}r.blitFramebuffer(0,0,Be,at,0,0,Be,at,De,r.NEAREST),l===!0&&(Et.length=0,ft.length=0,Et.push(r.COLOR_ATTACHMENT0+Vr),$.depthBuffer&&$.resolveDepthBuffer===!1&&(Et.push(Qe),ft.push(Qe),r.invalidateFramebuffer(r.DRAW_FRAMEBUFFER,ft)),r.invalidateFramebuffer(r.READ_FRAMEBUFFER,Et))}if(t.bindFramebuffer(r.READ_FRAMEBUFFER,null),t.bindFramebuffer(r.DRAW_FRAMEBUFFER,null),kt)for(let Vr=0;Vr<V.length;Vr++){t.bindFramebuffer(r.FRAMEBUFFER,Cn.__webglMultisampledFramebuffer),r.framebufferRenderbuffer(r.FRAMEBUFFER,r.COLOR_ATTACHMENT0+Vr,r.RENDERBUFFER,Cn.__webglColorRenderbuffer[Vr]);const jt=n.get(V[Vr]).__webglTexture;t.bindFramebuffer(r.FRAMEBUFFER,Cn.__webglFramebuffer),r.framebufferTexture2D(r.DRAW_FRAMEBUFFER,r.COLOR_ATTACHMENT0+Vr,r.TEXTURE_2D,jt,0)}t.bindFramebuffer(r.DRAW_FRAMEBUFFER,Cn.__webglMultisampledFramebuffer)}else if($.depthBuffer&&$.resolveDepthBuffer===!1&&l){const V=$.stencilBuffer?r.DEPTH_STENCIL_ATTACHMENT:r.DEPTH_ATTACHMENT;r.invalidateFramebuffer(r.DRAW_FRAMEBUFFER,[V])}}}function se($){return Math.min(i.maxSamples,$.samples)}function br($){const V=n.get($);return $.samples>0&&e.has("WEBGL_multisampled_render_to_texture")===!0&&V.__useRenderToTexture!==!1}function vn($){const V=a.render.frame;c.get($)!==V&&(c.set($,V),$.update())}function er($,V){const Be=$.colorSpace,at=$.format,De=$.type;return $.isCompressedTexture===!0||$.isVideoTexture===!0||Be!==af&&Be!==Ol&&($r.getTransfer(Be)===$n?(at!==ma||De!==fa)&&ze("WebGLTextures: sRGB encoded textures have to use RGBAFormat and UnsignedByteType."):rt("WebGLTextures: Unsupported texture color space:",Be)),V}function Jt($){return typeof HTMLImageElement!="undefined"&&$ instanceof HTMLImageElement?(u.width=$.naturalWidth||$.width,u.height=$.naturalHeight||$.height):typeof VideoFrame!="undefined"&&$ instanceof VideoFrame?(u.width=$.displayWidth,u.height=$.displayHeight):(u.width=$.width,u.height=$.height),u}this.allocateTextureUnit=q,this.resetTextureUnits=j,this.setTexture2D=re,this.setTexture2DArray=de,this.setTexture3D=we,this.setTextureCube=ge,this.rebindTextures=$t,this.setupRenderTarget=zn,this.updateRenderTargetMipmap=Me,this.updateMultisampleRenderTarget=Yt,this.setupDepthRenderbuffer=bt,this.setupFrameBufferTexture=Ue,this.useMultisampledRTT=br,this.isReversedDepthBuffer=function(){return t.buffers.depth.getReversed()}}function oX(r,e){function t(n,i=Ol){let s;const a=$r.getTransfer(i);if(n===fa)return r.UNSIGNED_BYTE;if(n===pv)return r.UNSIGNED_SHORT_4_4_4_4;if(n===mv)return r.UNSIGNED_SHORT_5_5_5_1;if(n===gv)return r.UNSIGNED_INT_5_9_9_9_REV;if(n===vv)return r.UNSIGNED_INT_10F_11F_11F_REV;if(n===Jf)return r.BYTE;if(n===cd)return r.SHORT;if(n===Yu)return r.UNSIGNED_SHORT;if(n===Do)return r.INT;if(n===Ls)return r.UNSIGNED_INT;if(n===ha)return r.FLOAT;if(n===pa)return r.HALF_FLOAT;if(n===A0)return r.ALPHA;if(n===Sm)return r.RGB;if(n===ma)return r.RGBA;if(n===jo)return r.DEPTH_COMPONENT;if(n===vl)return r.DEPTH_STENCIL;if(n===_h)return r.RED;if(n===Kf)return r.RED_INTEGER;if(n===Al)return r.RG;if(n===$h)return r.RG_INTEGER;if(n===qf)return r.RGBA_INTEGER;if(n===Kd||n===qd||n===_d||n===$d)if(a===$n)if(s=e.get("WEBGL_compressed_texture_s3tc_srgb"),s!==null){if(n===Kd)return s.COMPRESSED_SRGB_S3TC_DXT1_EXT;if(n===qd)return s.COMPRESSED_SRGB_ALPHA_S3TC_DXT1_EXT;if(n===_d)return s.COMPRESSED_SRGB_ALPHA_S3TC_DXT3_EXT;if(n===$d)return s.COMPRESSED_SRGB_ALPHA_S3TC_DXT5_EXT}else return null;else if(s=e.get("WEBGL_compressed_texture_s3tc"),s!==null){if(n===Kd)return s.COMPRESSED_RGB_S3TC_DXT1_EXT;if(n===qd)return s.COMPRESSED_RGBA_S3TC_DXT1_EXT;if(n===_d)return s.COMPRESSED_RGBA_S3TC_DXT3_EXT;if(n===$d)return s.COMPRESSED_RGBA_S3TC_DXT5_EXT}else return null;if(n===dd||n===Dm||n===ep||n===Tm)if(s=e.get("WEBGL_compressed_texture_pvrtc"),s!==null){if(n===dd)return s.COMPRESSED_RGB_PVRTC_4BPPV1_IMG;if(n===Dm)return s.COMPRESSED_RGB_PVRTC_2BPPV1_IMG;if(n===ep)return s.COMPRESSED_RGBA_PVRTC_4BPPV1_IMG;if(n===Tm)return s.COMPRESSED_RGBA_PVRTC_2BPPV1_IMG}else return null;if(n===tp||n===Im||n===np||n===ef||n===rp||n===_f||n===ip)if(s=e.get("WEBGL_compressed_texture_etc"),s!==null){if(n===tp||n===Im)return a===$n?s.COMPRESSED_SRGB8_ETC2:s.COMPRESSED_RGB8_ETC2;if(n===np)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ETC2_EAC:s.COMPRESSED_RGBA8_ETC2_EAC;if(n===ef)return s.COMPRESSED_R11_EAC;if(n===rp)return s.COMPRESSED_SIGNED_R11_EAC;if(n===_f)return s.COMPRESSED_RG11_EAC;if(n===ip)return s.COMPRESSED_SIGNED_RG11_EAC}else return null;if(n===$f||n===sp||n===eh||n===ap||n===th||n===Nm||n===tf||n===op||n===lp||n===up||n===cp||n===dp||n===fp||n===hp)if(s=e.get("WEBGL_compressed_texture_astc"),s!==null){if(n===$f)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_4x4_KHR:s.COMPRESSED_RGBA_ASTC_4x4_KHR;if(n===sp)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_5x4_KHR:s.COMPRESSED_RGBA_ASTC_5x4_KHR;if(n===eh)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_5x5_KHR:s.COMPRESSED_RGBA_ASTC_5x5_KHR;if(n===ap)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_6x5_KHR:s.COMPRESSED_RGBA_ASTC_6x5_KHR;if(n===th)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_6x6_KHR:s.COMPRESSED_RGBA_ASTC_6x6_KHR;if(n===Nm)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_8x5_KHR:s.COMPRESSED_RGBA_ASTC_8x5_KHR;if(n===tf)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_8x6_KHR:s.COMPRESSED_RGBA_ASTC_8x6_KHR;if(n===op)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_8x8_KHR:s.COMPRESSED_RGBA_ASTC_8x8_KHR;if(n===lp)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_10x5_KHR:s.COMPRESSED_RGBA_ASTC_10x5_KHR;if(n===up)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_10x6_KHR:s.COMPRESSED_RGBA_ASTC_10x6_KHR;if(n===cp)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_10x8_KHR:s.COMPRESSED_RGBA_ASTC_10x8_KHR;if(n===dp)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_10x10_KHR:s.COMPRESSED_RGBA_ASTC_10x10_KHR;if(n===fp)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_12x10_KHR:s.COMPRESSED_RGBA_ASTC_12x10_KHR;if(n===hp)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_12x12_KHR:s.COMPRESSED_RGBA_ASTC_12x12_KHR}else return null;if(n===nh||n===pp||n===mp)if(s=e.get("EXT_texture_compression_bptc"),s!==null){if(n===nh)return a===$n?s.COMPRESSED_SRGB_ALPHA_BPTC_UNORM_EXT:s.COMPRESSED_RGBA_BPTC_UNORM_EXT;if(n===pp)return s.COMPRESSED_RGB_BPTC_SIGNED_FLOAT_EXT;if(n===mp)return s.COMPRESSED_RGB_BPTC_UNSIGNED_FLOAT_EXT}else return null;if(n===gp||n===nf||n===rf||n===vp)if(s=e.get("EXT_texture_compression_rgtc"),s!==null){if(n===gp)return s.COMPRESSED_RED_RGTC1_EXT;if(n===nf)return s.COMPRESSED_SIGNED_RED_RGTC1_EXT;if(n===rf)return s.COMPRESSED_RED_GREEN_RGTC2_EXT;if(n===vp)return s.COMPRESSED_SIGNED_RED_GREEN_RGTC2_EXT}else return null;return n===Ll?r.UNSIGNED_INT_24_8:r[n]!==void 0?r[n]:null}return{convert:t}}const lX=`
void main() {

	gl_Position = vec4( position, 1.0 );

}`,uX=`
uniform sampler2DArray depthColor;
uniform float depthWidth;
uniform float depthHeight;

void main() {

	vec2 coord = vec2( gl_FragCoord.x / depthWidth, gl_FragCoord.y / depthHeight );

	if ( coord.x >= 1.0 ) {

		gl_FragDepth = texture( depthColor, vec3( coord.x - 1.0, coord.y, 1 ) ).r;

	} else {

		gl_FragDepth = texture( depthColor, vec3( coord.x, coord.y, 0 ) ).r;

	}

}`;class cX{constructor(){this.texture=null,this.mesh=null,this.depthNear=0,this.depthFar=0}init(e,t){if(this.texture===null){const n=new f5(e.texture);(e.depthNear!==t.depthNear||e.depthFar!==t.depthFar)&&(this.depthNear=e.depthNear,this.depthFar=e.depthFar),this.texture=n}}getMesh(e){if(this.texture!==null&&this.mesh===null){const t=e.cameras[0].viewport,n=new $u({vertexShader:lX,fragmentShader:uX,uniforms:{depthColor:{value:this.texture},depthWidth:{value:t.z},depthHeight:{value:t.w}}});this.mesh=new Gs(new Jv(20,20),n)}return this.mesh}reset(){this.texture=null,this.mesh=null}getDepthTexture(){return this.texture}}class dX extends Go{constructor(e,t){super();const n=this;let i=null,s=1,a=null,o="local-floor",l=1,u=null,c=null,d=null,f=null,h=null,p=null;const x=typeof XRWebGLBinding!="undefined",v=new cX,m={},C=t.getContextAttributes();let w=null,P=null;const B=[],S=[],I=new ct;let N=null;const T=new bo;T.viewport=new Ei;const R=new bo;R.viewport=new Ei;const D=[T,R],j=new $5;let q=null,Q=null;this.cameraAutoUpdate=!0,this.enabled=!1,this.isPresenting=!1,this.getController=function(ee){let ue=B[ee];return ue===void 0&&(ue=new Xy,B[ee]=ue),ue.getTargetRaySpace()},this.getControllerGrip=function(ee){let ue=B[ee];return ue===void 0&&(ue=new Xy,B[ee]=ue),ue.getGripSpace()},this.getHand=function(ee){let ue=B[ee];return ue===void 0&&(ue=new Xy,B[ee]=ue),ue.getHandSpace()};function re(ee){const ue=S.indexOf(ee.inputSource);if(ue===-1)return;const Ue=B[ue];Ue!==void 0&&(Ue.update(ee.inputSource,ee.frame,u||a),Ue.dispatchEvent({type:ee.type,data:ee.inputSource}))}function de(){i.removeEventListener("select",re),i.removeEventListener("selectstart",re),i.removeEventListener("selectend",re),i.removeEventListener("squeeze",re),i.removeEventListener("squeezestart",re),i.removeEventListener("squeezeend",re),i.removeEventListener("end",de),i.removeEventListener("inputsourceschange",we);for(let ee=0;ee<B.length;ee++){const ue=S[ee];ue!==null&&(S[ee]=null,B[ee].disconnect(ue))}q=null,Q=null,v.reset();for(const ee in m)delete m[ee];e.setRenderTarget(w),h=null,f=null,d=null,i=null,P=null,ve.stop(),n.isPresenting=!1,e.setPixelRatio(N),e.setSize(I.width,I.height,!1),n.dispatchEvent({type:"sessionend"})}this.setFramebufferScaleFactor=function(ee){s=ee,n.isPresenting===!0&&ze("WebXRManager: Cannot change framebuffer scale while presenting.")},this.setReferenceSpaceType=function(ee){o=ee,n.isPresenting===!0&&ze("WebXRManager: Cannot change reference space type while presenting.")},this.getReferenceSpace=function(){return u||a},this.setReferenceSpace=function(ee){u=ee},this.getBaseLayer=function(){return f!==null?f:h},this.getBinding=function(){return d===null&&x&&(d=new XRWebGLBinding(i,t)),d},this.getFrame=function(){return p},this.getSession=function(){return i},this.setSession=function(ee){return Kr(this,null,function*(){if(i=ee,i!==null){if(w=e.getRenderTarget(),i.addEventListener("select",re),i.addEventListener("selectstart",re),i.addEventListener("selectend",re),i.addEventListener("squeeze",re),i.addEventListener("squeezestart",re),i.addEventListener("squeezeend",re),i.addEventListener("end",de),i.addEventListener("inputsourceschange",we),C.xrCompatible!==!0&&(yield t.makeXRCompatible()),N=e.getPixelRatio(),e.getSize(I),x&&"createProjectionLayer"in XRWebGLBinding.prototype){let Ue=null,$e=null,He=null;C.depth&&(He=C.stencil?t.DEPTH24_STENCIL8:t.DEPTH_COMPONENT24,Ue=C.stencil?vl:jo,$e=C.stencil?Ll:Ls);const bt={colorFormat:t.RGBA8,depthFormat:He,scaleFactor:s};d=this.getBinding(),f=d.createProjectionLayer(bt),i.updateRenderState({layers:[f]}),e.setPixelRatio(1),e.setSize(f.textureWidth,f.textureHeight,!1),P=new fd(f.textureWidth,f.textureHeight,{format:ma,type:fa,depthTexture:new Vl(f.textureWidth,f.textureHeight,$e,void 0,void 0,void 0,void 0,void 0,void 0,Ue),stencilBuffer:C.stencil,colorSpace:e.outputColorSpace,samples:C.antialias?4:0,resolveDepthBuffer:f.ignoreDepthValues===!1,resolveStencilBuffer:f.ignoreDepthValues===!1})}else{const Ue={antialias:C.antialias,alpha:!0,depth:C.depth,stencil:C.stencil,framebufferScaleFactor:s};h=new XRWebGLLayer(i,t,Ue),i.updateRenderState({baseLayer:h}),e.setPixelRatio(1),e.setSize(h.framebufferWidth,h.framebufferHeight,!1),P=new fd(h.framebufferWidth,h.framebufferHeight,{format:ma,type:fa,colorSpace:e.outputColorSpace,stencilBuffer:C.stencil,resolveDepthBuffer:h.ignoreDepthValues===!1,resolveStencilBuffer:h.ignoreDepthValues===!1})}P.isXRRenderTarget=!0,this.setFoveation(l),u=null,a=yield i.requestReferenceSpace(o),ve.setContext(i),ve.start(),n.isPresenting=!0,n.dispatchEvent({type:"sessionstart"})}})},this.getEnvironmentBlendMode=function(){if(i!==null)return i.environmentBlendMode},this.getDepthTexture=function(){return v.getDepthTexture()};function we(ee){for(let ue=0;ue<ee.removed.length;ue++){const Ue=ee.removed[ue],$e=S.indexOf(Ue);$e>=0&&(S[$e]=null,B[$e].disconnect(Ue))}for(let ue=0;ue<ee.added.length;ue++){const Ue=ee.added[ue];let $e=S.indexOf(Ue);if($e===-1){for(let bt=0;bt<B.length;bt++)if(bt>=S.length){S.push(Ue),$e=bt;break}else if(S[bt]===null){S[bt]=Ue,$e=bt;break}if($e===-1)break}const He=B[$e];He&&He.connect(Ue)}}const ge=new J,Y=new J;function Se(ee,ue,Ue){ge.setFromMatrixPosition(ue.matrixWorld),Y.setFromMatrixPosition(Ue.matrixWorld);const $e=ge.distanceTo(Y),He=ue.projectionMatrix.elements,bt=Ue.projectionMatrix.elements,$t=He[14]/(He[10]-1),zn=He[14]/(He[10]+1),Me=(He[9]+1)/He[5],Et=(He[9]-1)/He[5],ft=(He[8]-1)/He[0],Yt=(bt[8]+1)/bt[0],se=$t*ft,br=$t*Yt,vn=$e/(-ft+Yt),er=vn*-ft;if(ue.matrixWorld.decompose(ee.position,ee.quaternion,ee.scale),ee.translateX(er),ee.translateZ(vn),ee.matrixWorld.compose(ee.position,ee.quaternion,ee.scale),ee.matrixWorldInverse.copy(ee.matrixWorld).invert(),He[10]===-1)ee.projectionMatrix.copy(ue.projectionMatrix),ee.projectionMatrixInverse.copy(ue.projectionMatrixInverse);else{const Jt=$t+vn,$=zn+vn,V=se-er,Be=br+($e-er),at=Me*zn/$*Jt,De=Et*zn/$*Jt;ee.projectionMatrix.makePerspective(V,Be,at,De,Jt,$),ee.projectionMatrixInverse.copy(ee.projectionMatrix).invert()}}function W(ee,ue){ue===null?ee.matrixWorld.copy(ee.matrix):ee.matrixWorld.multiplyMatrices(ue.matrixWorld,ee.matrix),ee.matrixWorldInverse.copy(ee.matrixWorld).invert()}this.updateCamera=function(ee){if(i===null)return;let ue=ee.near,Ue=ee.far;v.texture!==null&&(v.depthNear>0&&(ue=v.depthNear),v.depthFar>0&&(Ue=v.depthFar)),j.near=R.near=T.near=ue,j.far=R.far=T.far=Ue,(q!==j.near||Q!==j.far)&&(i.updateRenderState({depthNear:j.near,depthFar:j.far}),q=j.near,Q=j.far),j.layers.mask=ee.layers.mask|6,T.layers.mask=j.layers.mask&3,R.layers.mask=j.layers.mask&5;const $e=ee.parent,He=j.cameras;W(j,$e);for(let bt=0;bt<He.length;bt++)W(He[bt],$e);He.length===2?Se(j,T,R):j.projectionMatrix.copy(T.projectionMatrix),fe(ee,j,$e)};function fe(ee,ue,Ue){Ue===null?ee.matrix.copy(ue.matrixWorld):(ee.matrix.copy(Ue.matrixWorld),ee.matrix.invert(),ee.matrix.multiply(ue.matrixWorld)),ee.matrix.decompose(ee.position,ee.quaternion,ee.scale),ee.updateMatrixWorld(!0),ee.projectionMatrix.copy(ue.projectionMatrix),ee.projectionMatrixInverse.copy(ue.projectionMatrixInverse),ee.isPerspectiveCamera&&(ee.fov=Bc*2*Math.atan(1/ee.projectionMatrix.elements[5]),ee.zoom=1)}this.getCamera=function(){return j},this.getFoveation=function(){if(!(f===null&&h===null))return l},this.setFoveation=function(ee){l=ee,f!==null&&(f.fixedFoveation=ee),h!==null&&h.fixedFoveation!==void 0&&(h.fixedFoveation=ee)},this.hasDepthSensing=function(){return v.texture!==null},this.getDepthSensingMesh=function(){return v.getMesh(j)},this.getCameraTexture=function(ee){return m[ee]};let xe=null;function dt(ee,ue){if(c=ue.getViewerPose(u||a),p=ue,c!==null){const Ue=c.views;h!==null&&(e.setRenderTargetFramebuffer(P,h.framebuffer),e.setRenderTarget(P));let $e=!1;Ue.length!==j.cameras.length&&(j.cameras.length=0,$e=!0);for(let zn=0;zn<Ue.length;zn++){const Me=Ue[zn];let Et=null;if(h!==null)Et=h.getViewport(Me);else{const Yt=d.getViewSubImage(f,Me);Et=Yt.viewport,zn===0&&(e.setRenderTargetTextures(P,Yt.colorTexture,Yt.depthStencilTexture),e.setRenderTarget(P))}let ft=D[zn];ft===void 0&&(ft=new bo,ft.layers.enable(zn),ft.viewport=new Ei,D[zn]=ft),ft.matrix.fromArray(Me.transform.matrix),ft.matrix.decompose(ft.position,ft.quaternion,ft.scale),ft.projectionMatrix.fromArray(Me.projectionMatrix),ft.projectionMatrixInverse.copy(ft.projectionMatrix).invert(),ft.viewport.set(Et.x,Et.y,Et.width,Et.height),zn===0&&(j.matrix.copy(ft.matrix),j.matrix.decompose(j.position,j.quaternion,j.scale)),$e===!0&&j.cameras.push(ft)}const He=i.enabledFeatures;if(He&&He.includes("depth-sensing")&&i.depthUsage=="gpu-optimized"&&x){d=n.getBinding();const zn=d.getDepthInformation(Ue[0]);zn&&zn.isValid&&zn.texture&&v.init(zn,i.renderState)}if(He&&He.includes("camera-access")&&x){e.state.unbindTexture(),d=n.getBinding();for(let zn=0;zn<Ue.length;zn++){const Me=Ue[zn].camera;if(Me){let Et=m[Me];Et||(Et=new f5,m[Me]=Et);const ft=d.getCameraImage(Me);Et.sourceTexture=ft}}}}for(let Ue=0;Ue<B.length;Ue++){const $e=S[Ue],He=B[Ue];$e!==null&&He!==void 0&&He.update($e,ue,u||a)}xe&&xe(ee,ue),ue.detectedPlanes&&n.dispatchEvent({type:"planesdetected",data:ue}),p=null}const ve=new AT;ve.setAnimationLoop(dt),this.setAnimationLoop=function(ee){xe=ee},this.dispose=function(){}}}const sg=new bu,fX=new Cr;function hX(r,e){function t(v,m){v.matrixAutoUpdate===!0&&v.updateMatrix(),m.value.copy(v.matrix)}function n(v,m){m.color.getRGB(v.fogColor.value,HS(r)),m.isFog?(v.fogNear.value=m.near,v.fogFar.value=m.far):m.isFogExp2&&(v.fogDensity.value=m.density)}function i(v,m,C,w,P){m.isMeshBasicMaterial||m.isMeshLambertMaterial?s(v,m):m.isMeshToonMaterial?(s(v,m),d(v,m)):m.isMeshPhongMaterial?(s(v,m),c(v,m)):m.isMeshStandardMaterial?(s(v,m),f(v,m),m.isMeshPhysicalMaterial&&h(v,m,P)):m.isMeshMatcapMaterial?(s(v,m),p(v,m)):m.isMeshDepthMaterial?s(v,m):m.isMeshDistanceMaterial?(s(v,m),x(v,m)):m.isMeshNormalMaterial?s(v,m):m.isLineBasicMaterial?(a(v,m),m.isLineDashedMaterial&&o(v,m)):m.isPointsMaterial?l(v,m,C,w):m.isSpriteMaterial?u(v,m):m.isShadowMaterial?(v.color.value.copy(m.color),v.opacity.value=m.opacity):m.isShaderMaterial&&(m.uniformsNeedUpdate=!1)}function s(v,m){v.opacity.value=m.opacity,m.color&&v.diffuse.value.copy(m.color),m.emissive&&v.emissive.value.copy(m.emissive).multiplyScalar(m.emissiveIntensity),m.map&&(v.map.value=m.map,t(m.map,v.mapTransform)),m.alphaMap&&(v.alphaMap.value=m.alphaMap,t(m.alphaMap,v.alphaMapTransform)),m.bumpMap&&(v.bumpMap.value=m.bumpMap,t(m.bumpMap,v.bumpMapTransform),v.bumpScale.value=m.bumpScale,m.side===Qi&&(v.bumpScale.value*=-1)),m.normalMap&&(v.normalMap.value=m.normalMap,t(m.normalMap,v.normalMapTransform),v.normalScale.value.copy(m.normalScale),m.side===Qi&&v.normalScale.value.negate()),m.displacementMap&&(v.displacementMap.value=m.displacementMap,t(m.displacementMap,v.displacementMapTransform),v.displacementScale.value=m.displacementScale,v.displacementBias.value=m.displacementBias),m.emissiveMap&&(v.emissiveMap.value=m.emissiveMap,t(m.emissiveMap,v.emissiveMapTransform)),m.specularMap&&(v.specularMap.value=m.specularMap,t(m.specularMap,v.specularMapTransform)),m.alphaTest>0&&(v.alphaTest.value=m.alphaTest);const C=e.get(m),w=C.envMap,P=C.envMapRotation;w&&(v.envMap.value=w,sg.copy(P),sg.x*=-1,sg.y*=-1,sg.z*=-1,w.isCubeTexture&&w.isRenderTargetTexture===!1&&(sg.y*=-1,sg.z*=-1),v.envMapRotation.value.setFromMatrix4(fX.makeRotationFromEuler(sg)),v.flipEnvMap.value=w.isCubeTexture&&w.isRenderTargetTexture===!1?-1:1,v.reflectivity.value=m.reflectivity,v.ior.value=m.ior,v.refractionRatio.value=m.refractionRatio),m.lightMap&&(v.lightMap.value=m.lightMap,v.lightMapIntensity.value=m.lightMapIntensity,t(m.lightMap,v.lightMapTransform)),m.aoMap&&(v.aoMap.value=m.aoMap,v.aoMapIntensity.value=m.aoMapIntensity,t(m.aoMap,v.aoMapTransform))}function a(v,m){v.diffuse.value.copy(m.color),v.opacity.value=m.opacity,m.map&&(v.map.value=m.map,t(m.map,v.mapTransform))}function o(v,m){v.dashSize.value=m.dashSize,v.totalSize.value=m.dashSize+m.gapSize,v.scale.value=m.scale}function l(v,m,C,w){v.diffuse.value.copy(m.color),v.opacity.value=m.opacity,v.size.value=m.size*C,v.scale.value=w*.5,m.map&&(v.map.value=m.map,t(m.map,v.uvTransform)),m.alphaMap&&(v.alphaMap.value=m.alphaMap,t(m.alphaMap,v.alphaMapTransform)),m.alphaTest>0&&(v.alphaTest.value=m.alphaTest)}function u(v,m){v.diffuse.value.copy(m.color),v.opacity.value=m.opacity,v.rotation.value=m.rotation,m.map&&(v.map.value=m.map,t(m.map,v.mapTransform)),m.alphaMap&&(v.alphaMap.value=m.alphaMap,t(m.alphaMap,v.alphaMapTransform)),m.alphaTest>0&&(v.alphaTest.value=m.alphaTest)}function c(v,m){v.specular.value.copy(m.specular),v.shininess.value=Math.max(m.shininess,1e-4)}function d(v,m){m.gradientMap&&(v.gradientMap.value=m.gradientMap)}function f(v,m){v.metalness.value=m.metalness,m.metalnessMap&&(v.metalnessMap.value=m.metalnessMap,t(m.metalnessMap,v.metalnessMapTransform)),v.roughness.value=m.roughness,m.roughnessMap&&(v.roughnessMap.value=m.roughnessMap,t(m.roughnessMap,v.roughnessMapTransform)),m.envMap&&(v.envMapIntensity.value=m.envMapIntensity)}function h(v,m,C){v.ior.value=m.ior,m.sheen>0&&(v.sheenColor.value.copy(m.sheenColor).multiplyScalar(m.sheen),v.sheenRoughness.value=m.sheenRoughness,m.sheenColorMap&&(v.sheenColorMap.value=m.sheenColorMap,t(m.sheenColorMap,v.sheenColorMapTransform)),m.sheenRoughnessMap&&(v.sheenRoughnessMap.value=m.sheenRoughnessMap,t(m.sheenRoughnessMap,v.sheenRoughnessMapTransform))),m.clearcoat>0&&(v.clearcoat.value=m.clearcoat,v.clearcoatRoughness.value=m.clearcoatRoughness,m.clearcoatMap&&(v.clearcoatMap.value=m.clearcoatMap,t(m.clearcoatMap,v.clearcoatMapTransform)),m.clearcoatRoughnessMap&&(v.clearcoatRoughnessMap.value=m.clearcoatRoughnessMap,t(m.clearcoatRoughnessMap,v.clearcoatRoughnessMapTransform)),m.clearcoatNormalMap&&(v.clearcoatNormalMap.value=m.clearcoatNormalMap,t(m.clearcoatNormalMap,v.clearcoatNormalMapTransform),v.clearcoatNormalScale.value.copy(m.clearcoatNormalScale),m.side===Qi&&v.clearcoatNormalScale.value.negate())),m.dispersion>0&&(v.dispersion.value=m.dispersion),m.iridescence>0&&(v.iridescence.value=m.iridescence,v.iridescenceIOR.value=m.iridescenceIOR,v.iridescenceThicknessMinimum.value=m.iridescenceThicknessRange[0],v.iridescenceThicknessMaximum.value=m.iridescenceThicknessRange[1],m.iridescenceMap&&(v.iridescenceMap.value=m.iridescenceMap,t(m.iridescenceMap,v.iridescenceMapTransform)),m.iridescenceThicknessMap&&(v.iridescenceThicknessMap.value=m.iridescenceThicknessMap,t(m.iridescenceThicknessMap,v.iridescenceThicknessMapTransform))),m.transmission>0&&(v.transmission.value=m.transmission,v.transmissionSamplerMap.value=C.texture,v.transmissionSamplerSize.value.set(C.width,C.height),m.transmissionMap&&(v.transmissionMap.value=m.transmissionMap,t(m.transmissionMap,v.transmissionMapTransform)),v.thickness.value=m.thickness,m.thicknessMap&&(v.thicknessMap.value=m.thicknessMap,t(m.thicknessMap,v.thicknessMapTransform)),v.attenuationDistance.value=m.attenuationDistance,v.attenuationColor.value.copy(m.attenuationColor)),m.anisotropy>0&&(v.anisotropyVector.value.set(m.anisotropy*Math.cos(m.anisotropyRotation),m.anisotropy*Math.sin(m.anisotropyRotation)),m.anisotropyMap&&(v.anisotropyMap.value=m.anisotropyMap,t(m.anisotropyMap,v.anisotropyMapTransform))),v.specularIntensity.value=m.specularIntensity,v.specularColor.value.copy(m.specularColor),m.specularColorMap&&(v.specularColorMap.value=m.specularColorMap,t(m.specularColorMap,v.specularColorMapTransform)),m.specularIntensityMap&&(v.specularIntensityMap.value=m.specularIntensityMap,t(m.specularIntensityMap,v.specularIntensityMapTransform))}function p(v,m){m.matcap&&(v.matcap.value=m.matcap)}function x(v,m){const C=e.get(m).light;v.referencePosition.value.setFromMatrixPosition(C.matrixWorld),v.nearDistance.value=C.shadow.camera.near,v.farDistance.value=C.shadow.camera.far}return{refreshFogUniforms:n,refreshMaterialUniforms:i}}function pX(r,e,t,n){let i={},s={},a=[];const o=r.getParameter(r.MAX_UNIFORM_BUFFER_BINDINGS);function l(C,w){const P=w.program;n.uniformBlockBinding(C,P)}function u(C,w){let P=i[C.id];P===void 0&&(p(C),P=c(C),i[C.id]=P,C.addEventListener("dispose",v));const B=w.program;n.updateUBOMapping(C,B);const S=e.render.frame;s[C.id]!==S&&(f(C),s[C.id]=S)}function c(C){const w=d();C.__bindingPointIndex=w;const P=r.createBuffer(),B=C.__size,S=C.usage;return r.bindBuffer(r.UNIFORM_BUFFER,P),r.bufferData(r.UNIFORM_BUFFER,B,S),r.bindBuffer(r.UNIFORM_BUFFER,null),r.bindBufferBase(r.UNIFORM_BUFFER,w,P),P}function d(){for(let C=0;C<o;C++)if(a.indexOf(C)===-1)return a.push(C),C;return rt("WebGLRenderer: Maximum number of 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Je=B.state.shadowsArray;if(Lr.render(Je,_,Le),He===!0&&ir.endShadows(),this.info.autoReset===!0&&this.info.reset(),(lt&&N.hasRenderPass())===!1){const Mr=P.opaque,tr=P.transmissive;if(B.setupLights(),Le.isArrayCamera){const Or=Le.cameras;if(tr.length>0)for(let qe=0,Tr=Or.length;qe<Tr;qe++){const xr=Or[qe];Br(Mr,tr,_,xr)}ft&&Kt.render(_);for(let qe=0,Tr=Or.length;qe<Tr;qe++){const xr=Or[qe];fi(P,_,xr,xr.viewport)}}else tr.length>0&&Br(Mr,tr,_,Le),ft&&Kt.render(_),fi(P,_,Le)}q!==null&&j===0&&(Be.updateMultisampleRenderTarget(q),Be.updateRenderTargetMipmap(q)),lt&&N.end(T),_.isScene===!0&&_.onAfterRender(T,_,Le),cn.resetDefaultState(),Q=-1,re=null,I.pop(),I.length>0?(B=I[I.length-1],He===!0&&ir.setGlobalState(T.clippingPlanes,B.state.camera)):B=null,S.pop(),S.length>0?P=S[S.length-1]:P=null};function yi(_,Le,mt,lt){if(_.visible===!1)return;if(_.layers.test(Le.layers)){if(_.isGroup)mt=_.renderOrder;else if(_.isLOD)_.autoUpdate===!0&&_.update(Le);else if(_.isLight)B.pushLight(_),_.castShadow&&B.pushShadow(_);else if(_.isSprite){if(!_.frustumCulled||$e.intersectsSprite(_)){lt&&Me.setFromMatrixPosition(_.matrixWorld).applyMatrix4($t);const Mr=kt.update(_),tr=_.material;tr.visible&&P.push(_,Mr,tr,mt,Me.z,null)}}else if((_.isMesh||_.isLine||_.isPoints)&&(!_.frustumCulled||$e.intersectsObject(_))){const Mr=kt.update(_),tr=_.material;if(lt&&(_.boundingSphere!==void 0?(_.boundingSphere===null&&_.computeBoundingSphere(),Me.copy(_.boundingSphere.center)):(Mr.boundingSphere===null&&Mr.computeBoundingSphere(),Me.copy(Mr.boundingSphere.center)),Me.applyMatrix4(_.matrixWorld).applyMatrix4($t)),Array.isArray(tr)){const Or=Mr.groups;for(let qe=0,Tr=Or.length;qe<Tr;qe++){const xr=Or[qe],ni=tr[xr.materialIndex];ni&&ni.visible&&P.push(_,Mr,ni,mt,Me.z,xr)}}else tr.visible&&P.push(_,Mr,tr,mt,Me.z,null)}}const Jn=_.children;for(let Mr=0,tr=Jn.length;Mr<tr;Mr++)yi(Jn[Mr],Le,mt,lt)}function fi(_,Le,mt,lt){const{opaque:Je,transmissive:Jn,transparent:Mr}=_;B.setupLightsView(mt),He===!0&&ir.setGlobalState(T.clippingPlanes,mt),lt&&Jt.viewport(de.copy(lt)),Je.length>0&&fc(Je,Le,mt),Jn.length>0&&fc(Jn,Le,mt),Mr.length>0&&fc(Mr,Le,mt),Jt.buffers.depth.setTest(!0),Jt.buffers.depth.setMask(!0),Jt.buffers.color.setMask(!0),Jt.setPolygonOffset(!1)}function Br(_,Le,mt,lt){if((mt.isScene===!0?mt.overrideMaterial:null)!==null)return;if(B.state.transmissionRenderTarget[lt.id]===void 0){const ni=vn.has("EXT_color_buffer_half_float")||vn.has("EXT_color_buffer_float");B.state.transmissionRenderTarget[lt.id]=new fd(1,1,{generateMipmaps:!0,type:ni?pa:fa,minFilter:tl,samples:er.samples,stencilBuffer:s,resolveDepthBuffer:!1,resolveStencilBuffer:!1,colorSpace:$r.workingColorSpace})}const Jn=B.state.transmissionRenderTarget[lt.id],Mr=lt.viewport||de;Jn.setSize(Mr.z*T.transmissionResolutionScale,Mr.w*T.transmissionResolutionScale);const tr=T.getRenderTarget(),Or=T.getActiveCubeFace(),qe=T.getActiveMipmapLevel();T.setRenderTarget(Jn),T.getClearColor(Y),Se=T.getClearAlpha(),Se<1&&T.setClearColor(16777215,.5),T.clear(),ft&&Kt.render(mt);const Tr=T.toneMapping;T.toneMapping=Fr;const xr=lt.viewport;if(lt.viewport!==void 0&&(lt.viewport=void 0),B.setupLightsView(lt),He===!0&&ir.setGlobalState(T.clippingPlanes,lt),fc(_,mt,lt),Be.updateMultisampleRenderTarget(Jn),Be.updateRenderTargetMipmap(Jn),vn.has("WEBGL_multisampled_render_to_texture")===!1){let ni=!1;for(let ds=0,ya=Le.length;ds<ya;ds++){const Ds=Le[ds],{object:Hs,geometry:ti,material:Ts,group:xs}=Ds;if(Ts.side===Xs&&Hs.layers.test(lt.layers)){const Kl=Ts.side;Ts.side=Qi,Ts.needsUpdate=!0,Of(Hs,mt,lt,ti,Ts,xs),Ts.side=Kl,Ts.needsUpdate=!0,ni=!0}}ni===!0&&(Be.updateMultisampleRenderTarget(Jn),Be.updateRenderTargetMipmap(Jn))}T.setRenderTarget(tr,Or,qe),T.setClearColor(Y,Se),xr!==void 0&&(lt.viewport=xr),T.toneMapping=Tr}function fc(_,Le,mt){const lt=Le.isScene===!0?Le.overrideMaterial:null;for(let Je=0,Jn=_.length;Je<Jn;Je++){const Mr=_[Je],{object:tr,geometry:Or,group:qe}=Mr;let Tr=Mr.material;Tr.allowOverride===!0&&lt!==null&&(Tr=lt),tr.layers.test(mt.layers)&&Of(tr,Le,mt,Or,Tr,qe)}}function Of(_,Le,mt,lt,Je,Jn){_.onBeforeRender(T,Le,mt,lt,Je,Jn),_.modelViewMatrix.multiplyMatrices(mt.matrixWorldInverse,_.matrixWorld),_.normalMatrix.getNormalMatrix(_.modelViewMatrix),Je.onBeforeRender(T,Le,mt,lt,_,Jn),Je.transparent===!0&&Je.side===Xs&&Je.forceSinglePass===!1?(Je.side=Qi,Je.needsUpdate=!0,T.renderBufferDirect(mt,Le,lt,Je,_,Jn),Je.side=ja,Je.needsUpdate=!0,T.renderBufferDirect(mt,Le,lt,Je,_,Jn),Je.side=Xs):T.renderBufferDirect(mt,Le,lt,Je,_,Jn),_.onAfterRender(T,Le,mt,lt,Je,Jn)}function zf(_,Le,mt){Le.isScene!==!0&&(Le=Et);const lt=V.get(_),Je=B.state.lights,Jn=B.state.shadowsArray,Mr=Je.state.version,tr=yn.getParameters(_,Je.state,Jn,Le,mt),Or=yn.getProgramCacheKey(tr);let qe=lt.programs;lt.environment=_.isMeshStandardMaterial?Le.environment:null,lt.fog=Le.fog,lt.envMap=(_.isMeshStandardMaterial?De:at).get(_.envMap||lt.environment),lt.envMapRotation=lt.environment!==null&&_.envMap===null?Le.environmentRotation:_.envMapRotation,qe===void 0&&(_.addEventListener("dispose",Jl),qe=new Map,lt.programs=qe);let Tr=qe.get(Or);if(Tr!==void 0){if(lt.currentProgram===Tr&&lt.lightsStateVersion===Mr)return oy(_,tr),Tr}else tr.uniforms=yn.getUniforms(_),_.onBeforeCompile(tr,T),Tr=yn.acquireProgram(tr,Or),qe.set(Or,Tr),lt.uniforms=tr.uniforms;const xr=lt.uniforms;return(!_.isShaderMaterial&&!_.isRawShaderMaterial||_.clipping===!0)&&(xr.clippingPlanes=ir.uniform),oy(_,tr),lt.needsLights=$w(_),lt.lightsStateVersion=Mr,lt.needsLights&&(xr.ambientLightColor.value=Je.state.ambient,xr.lightProbe.value=Je.state.probe,xr.directionalLights.value=Je.state.directional,xr.directionalLightShadows.value=Je.state.directionalShadow,xr.spotLights.value=Je.state.spot,xr.spotLightShadows.value=Je.state.spotShadow,xr.rectAreaLights.value=Je.state.rectArea,xr.ltc_1.value=Je.state.rectAreaLTC1,xr.ltc_2.value=Je.state.rectAreaLTC2,xr.pointLights.value=Je.state.point,xr.pointLightShadows.value=Je.state.pointShadow,xr.hemisphereLights.value=Je.state.hemi,xr.directionalShadowMap.value=Je.state.directionalShadowMap,xr.directionalShadowMatrix.value=Je.state.directionalShadowMatrix,xr.spotShadowMap.value=Je.state.spotShadowMap,xr.spotLightMatrix.value=Je.state.spotLightMatrix,xr.spotLightMap.value=Je.state.spotLightMap,xr.pointShadowMap.value=Je.state.pointShadowMap,xr.pointShadowMatrix.value=Je.state.pointShadowMatrix),lt.currentProgram=Tr,lt.uniformsList=null,Tr}function ay(_){if(_.uniformsList===null){const Le=_.currentProgram.getUniforms();_.uniformsList=Zb.seqWithValue(Le.seq,_.uniforms)}return _.uniformsList}function oy(_,Le){const mt=V.get(_);mt.outputColorSpace=Le.outputColorSpace,mt.batching=Le.batching,mt.batchingColor=Le.batchingColor,mt.instancing=Le.instancing,mt.instancingColor=Le.instancingColor,mt.instancingMorph=Le.instancingMorph,mt.skinning=Le.skinning,mt.morphTargets=Le.morphTargets,mt.morphNormals=Le.morphNormals,mt.morphColors=Le.morphColors,mt.morphTargetsCount=Le.morphTargetsCount,mt.numClippingPlanes=Le.numClippingPlanes,mt.numIntersection=Le.numClipIntersection,mt.vertexAlphas=Le.vertexAlphas,mt.vertexTangents=Le.vertexTangents,mt.toneMapping=Le.toneMapping}function qw(_,Le,mt,lt,Je){Le.isScene!==!0&&(Le=Et),Be.resetTextureUnits();const Jn=Le.fog,Mr=lt.isMeshStandardMaterial?Le.environment:null,tr=q===null?T.outputColorSpace:q.isXRRenderTarget===!0?q.texture.colorSpace:af,Or=(lt.isMeshStandardMaterial?De:at).get(lt.envMap||Mr),qe=lt.vertexColors===!0&&!!mt.attributes.color&&mt.attributes.color.itemSize===4,Tr=!!mt.attributes.tangent&&(!!lt.normalMap||lt.anisotropy>0),xr=!!mt.morphAttributes.position,ni=!!mt.morphAttributes.normal,ds=!!mt.morphAttributes.color;let ya=Fr;lt.toneMapped&&(q===null||q.isXRRenderTarget===!0)&&(ya=T.toneMapping);const Ds=mt.morphAttributes.position||mt.morphAttributes.normal||mt.morphAttributes.color,Hs=Ds!==void 0?Ds.length:0,ti=V.get(lt),Ts=B.state.lights;if(He===!0&&(bt===!0||_!==re)){const ll=_===re&&lt.id===Q;ir.setState(lt,_,ll)}let xs=!1;lt.version===ti.__version?(ti.needsLights&&ti.lightsStateVersion!==Ts.state.version||ti.outputColorSpace!==tr||Je.isBatchedMesh&&ti.batching===!1||!Je.isBatchedMesh&&ti.batching===!0||Je.isBatchedMesh&&ti.batchingColor===!0&&Je.colorTexture===null||Je.isBatchedMesh&&ti.batchingColor===!1&&Je.colorTexture!==null||Je.isInstancedMesh&&ti.instancing===!1||!Je.isInstancedMesh&&ti.instancing===!0||Je.isSkinnedMesh&&ti.skinning===!1||!Je.isSkinnedMesh&&ti.skinning===!0||Je.isInstancedMesh&&ti.instancingColor===!0&&Je.instanceColor===null||Je.isInstancedMesh&&ti.instancingColor===!1&&Je.instanceColor!==null||Je.isInstancedMesh&&ti.instancingMorph===!0&&Je.morphTexture===null||Je.isInstancedMesh&&ti.instancingMorph===!1&&Je.morphTexture!==null||ti.envMap!==Or||lt.fog===!0&&ti.fog!==Jn||ti.numClippingPlanes!==void 0&&(ti.numClippingPlanes!==ir.numPlanes||ti.numIntersection!==ir.numIntersection)||ti.vertexAlphas!==qe||ti.vertexTangents!==Tr||ti.morphTargets!==xr||ti.morphNormals!==ni||ti.morphColors!==ds||ti.toneMapping!==ya||ti.morphTargetsCount!==Hs)&&(xs=!0):(xs=!0,ti.__version=lt.version);let Kl=ti.currentProgram;xs===!0&&(Kl=zf(lt,Le,Je));let Oh=!1,ql=!1,tm=!1;const ca=Kl.getUniforms(),Sl=ti.uniforms;if(Jt.useProgram(Kl.program)&&(Oh=!0,ql=!0,tm=!0),lt.id!==Q&&(Q=lt.id,ql=!0),Oh||re!==_){Jt.buffers.depth.getReversed()&&_.reversedDepth!==!0&&(_._reversedDepth=!0,_.updateProjectionMatrix()),ca.setValue(se,"projectionMatrix",_.projectionMatrix),ca.setValue(se,"viewMatrix",_.matrixWorldInverse);const Dl=ca.map.cameraPosition;Dl!==void 0&&Dl.setValue(se,zn.setFromMatrixPosition(_.matrixWorld)),er.logarithmicDepthBuffer&&ca.setValue(se,"logDepthBufFC",2/(Math.log(_.far+1)/Math.LN2)),(lt.isMeshPhongMaterial||lt.isMeshToonMaterial||lt.isMeshLambertMaterial||lt.isMeshBasicMaterial||lt.isMeshStandardMaterial||lt.isShaderMaterial)&&ca.setValue(se,"isOrthographic",_.isOrthographicCamera===!0),re!==_&&(re=_,ql=!0,tm=!0)}if(ti.needsLights&&(Ts.state.directionalShadowMap.length>0&&ca.setValue(se,"directionalShadowMap",Ts.state.directionalShadowMap,Be),Ts.state.spotShadowMap.length>0&&ca.setValue(se,"spotShadowMap",Ts.state.spotShadowMap,Be),Ts.state.pointShadowMap.length>0&&ca.setValue(se,"pointShadowMap",Ts.state.pointShadowMap,Be)),Je.isSkinnedMesh){ca.setOptional(se,Je,"bindMatrix"),ca.setOptional(se,Je,"bindMatrixInverse");const ll=Je.skeleton;ll&&(ll.boneTexture===null&&ll.computeBoneTexture(),ca.setValue(se,"boneTexture",ll.boneTexture,Be))}Je.isBatchedMesh&&(ca.setOptional(se,Je,"batchingTexture"),ca.setValue(se,"batchingTexture",Je._matricesTexture,Be),ca.setOptional(se,Je,"batchingIdTexture"),ca.setValue(se,"batchingIdTexture",Je._indirectTexture,Be),ca.setOptional(se,Je,"batchingColorTexture"),Je._colorsTexture!==null&&ca.setValue(se,"batchingColorTexture",Je._colorsTexture,Be));const fu=mt.morphAttributes;if((fu.position!==void 0||fu.normal!==void 0||fu.color!==void 0)&&di.update(Je,mt,Kl),(ql||ti.receiveShadow!==Je.receiveShadow)&&(ti.receiveShadow=Je.receiveShadow,ca.setValue(se,"receiveShadow",Je.receiveShadow)),lt.isMeshGouraudMaterial&&lt.envMap!==null&&(Sl.envMap.value=Or,Sl.flipEnvMap.value=Or.isCubeTexture&&Or.isRenderTargetTexture===!1?-1:1),lt.isMeshStandardMaterial&&lt.envMap===null&&Le.environment!==null&&(Sl.envMapIntensity.value=Le.environmentIntensity),Sl.dfgLUT!==void 0&&(Sl.dfgLUT.value=gX()),ql&&(ca.setValue(se,"toneMappingExposure",T.toneMappingExposure),ti.needsLights&&_w(Sl,tm),Jn&&lt.fog===!0&&Vr.refreshFogUniforms(Sl,Jn),Vr.refreshMaterialUniforms(Sl,lt,xe,fe,B.state.transmissionRenderTarget[_.id]),Zb.upload(se,ay(ti),Sl,Be)),lt.isShaderMaterial&&lt.uniformsNeedUpdate===!0&&(Zb.upload(se,ay(ti),Sl,Be),lt.uniformsNeedUpdate=!1),lt.isSpriteMaterial&&ca.setValue(se,"center",Je.center),ca.setValue(se,"modelViewMatrix",Je.modelViewMatrix),ca.setValue(se,"normalMatrix",Je.normalMatrix),ca.setValue(se,"modelMatrix",Je.matrixWorld),lt.isShaderMaterial||lt.isRawShaderMaterial){const ll=lt.uniformsGroups;for(let Dl=0,Fu=ll.length;Dl<Fu;Dl++){const _l=ll[Dl];sn.update(_l,Kl),sn.bind(_l,Kl)}}return Kl}function _w(_,Le){_.ambientLightColor.needsUpdate=Le,_.lightProbe.needsUpdate=Le,_.directionalLights.needsUpdate=Le,_.directionalLightShadows.needsUpdate=Le,_.pointLights.needsUpdate=Le,_.pointLightShadows.needsUpdate=Le,_.spotLights.needsUpdate=Le,_.spotLightShadows.needsUpdate=Le,_.rectAreaLights.needsUpdate=Le,_.hemisphereLights.needsUpdate=Le}function $w(_){return _.isMeshLambertMaterial||_.isMeshToonMaterial||_.isMeshPhongMaterial||_.isMeshStandardMaterial||_.isShadowMaterial||_.isShaderMaterial&&_.lights===!0}this.getActiveCubeFace=function(){return D},this.getActiveMipmapLevel=function(){return j},this.getRenderTarget=function(){return q},this.setRenderTargetTextures=function(_,Le,mt){const lt=V.get(_);lt.__autoAllocateDepthBuffer=_.resolveDepthBuffer===!1,lt.__autoAllocateDepthBuffer===!1&&(lt.__useRenderToTexture=!1),V.get(_.texture).__webglTexture=Le,V.get(_.depthTexture).__webglTexture=lt.__autoAllocateDepthBuffer?void 0:mt,lt.__hasExternalTextures=!0},this.setRenderTargetFramebuffer=function(_,Le){const mt=V.get(_);mt.__webglFramebuffer=Le,mt.__useDefaultFramebuffer=Le===void 0};const em=se.createFramebuffer();this.setRenderTarget=function(_,Le=0,mt=0){q=_,D=Le,j=mt;let lt=null,Je=!1,Jn=!1;if(_){const tr=V.get(_);if(tr.__useDefaultFramebuffer!==void 0){Jt.bindFramebuffer(se.FRAMEBUFFER,tr.__webglFramebuffer),de.copy(_.viewport),we.copy(_.scissor),ge=_.scissorTest,Jt.viewport(de),Jt.scissor(we),Jt.setScissorTest(ge),Q=-1;return}else if(tr.__webglFramebuffer===void 0)Be.setupRenderTarget(_);else if(tr.__hasExternalTextures)Be.rebindTextures(_,V.get(_.texture).__webglTexture,V.get(_.depthTexture).__webglTexture);else if(_.depthBuffer){const Tr=_.depthTexture;if(tr.__boundDepthTexture!==Tr){if(Tr!==null&&V.has(Tr)&&(_.width!==Tr.image.width||_.height!==Tr.image.height))throw new Error("WebGLRenderTarget: Attached DepthTexture is initialized to the incorrect size.");Be.setupDepthRenderbuffer(_)}}const Or=_.texture;(Or.isData3DTexture||Or.isDataArrayTexture||Or.isCompressedArrayTexture)&&(Jn=!0);const qe=V.get(_).__webglFramebuffer;_.isWebGLCubeRenderTarget?(Array.isArray(qe[Le])?lt=qe[Le][mt]:lt=qe[Le],Je=!0):_.samples>0&&Be.useMultisampledRTT(_)===!1?lt=V.get(_).__webglMultisampledFramebuffer:Array.isArray(qe)?lt=qe[mt]:lt=qe,de.copy(_.viewport),we.copy(_.scissor),ge=_.scissorTest}else de.copy(ee).multiplyScalar(xe).floor(),we.copy(ue).multiplyScalar(xe).floor(),ge=Ue;if(mt!==0&&(lt=em),Jt.bindFramebuffer(se.FRAMEBUFFER,lt)&&Jt.drawBuffers(_,lt),Jt.viewport(de),Jt.scissor(we),Jt.setScissorTest(ge),Je){const tr=V.get(_.texture);se.framebufferTexture2D(se.FRAMEBUFFER,se.COLOR_ATTACHMENT0,se.TEXTURE_CUBE_MAP_POSITIVE_X+Le,tr.__webglTexture,mt)}else if(Jn){const tr=Le;for(let Or=0;Or<_.textures.length;Or++){const qe=V.get(_.textures[Or]);se.framebufferTextureLayer(se.FRAMEBUFFER,se.COLOR_ATTACHMENT0+Or,qe.__webglTexture,mt,tr)}}else if(_!==null&&mt!==0){const tr=V.get(_.texture);se.framebufferTexture2D(se.FRAMEBUFFER,se.COLOR_ATTACHMENT0,se.TEXTURE_2D,tr.__webglTexture,mt)}Q=-1},this.readRenderTargetPixels=function(_,Le,mt,lt,Je,Jn,Mr,tr=0){if(!(_&&_.isWebGLRenderTarget)){rt("WebGLRenderer.readRenderTargetPixels: renderTarget is not THREE.WebGLRenderTarget.");return}let Or=V.get(_).__webglFramebuffer;if(_.isWebGLCubeRenderTarget&&Mr!==void 0&&(Or=Or[Mr]),Or){Jt.bindFramebuffer(se.FRAMEBUFFER,Or);try{const qe=_.textures[tr],Tr=qe.format,xr=qe.type;if(!er.textureFormatReadable(Tr)){rt("WebGLRenderer.readRenderTargetPixels: renderTarget is not in RGBA or implementation defined format.");return}if(!er.textureTypeReadable(xr)){rt("WebGLRenderer.readRenderTargetPixels: renderTarget is not in UnsignedByteType or implementation defined type.");return}Le>=0&&Le<=_.width-lt&&mt>=0&&mt<=_.height-Je&&(_.textures.length>1&&se.readBuffer(se.COLOR_ATTACHMENT0+tr),se.readPixels(Le,mt,lt,Je,rn.convert(Tr),rn.convert(xr),Jn))}finally{const qe=q!==null?V.get(q).__webglFramebuffer:null;Jt.bindFramebuffer(se.FRAMEBUFFER,qe)}}},this.readRenderTargetPixelsAsync=function(_,Le,mt,lt,Je,Jn,Mr,tr=0){return Kr(this,null,function*(){if(!(_&&_.isWebGLRenderTarget))throw new Error("THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not THREE.WebGLRenderTarget.");let Or=V.get(_).__webglFramebuffer;if(_.isWebGLCubeRenderTarget&&Mr!==void 0&&(Or=Or[Mr]),Or)if(Le>=0&&Le<=_.width-lt&&mt>=0&&mt<=_.height-Je){Jt.bindFramebuffer(se.FRAMEBUFFER,Or);const qe=_.textures[tr],Tr=qe.format,xr=qe.type;if(!er.textureFormatReadable(Tr))throw new Error("THREE.WebGLRenderer.readRenderTargetPixelsAsync: renderTarget is not in RGBA or implementation defined format.");if(!er.textureTypeReadable(xr))throw new Error("THREE.WebGLRenderer.readRenderTargetPixelsAsync: renderTarget is not in UnsignedByteType or implementation defined type.");const ni=se.createBuffer();se.bindBuffer(se.PIXEL_PACK_BUFFER,ni),se.bufferData(se.PIXEL_PACK_BUFFER,Jn.byteLength,se.STREAM_READ),_.textures.length>1&&se.readBuffer(se.COLOR_ATTACHMENT0+tr),se.readPixels(Le,mt,lt,Je,rn.convert(Tr),rn.convert(xr),0);const ds=q!==null?V.get(q).__webglFramebuffer:null;Jt.bindFramebuffer(se.FRAMEBUFFER,ds);const ya=se.fenceSync(se.SYNC_GPU_COMMANDS_COMPLETE,0);return se.flush(),yield Rm(se,ya,4),se.bindBuffer(se.PIXEL_PACK_BUFFER,ni),se.getBufferSubData(se.PIXEL_PACK_BUFFER,0,Jn),se.deleteBuffer(ni),se.deleteSync(ya),Jn}else throw new Error("THREE.WebGLRenderer.readRenderTargetPixelsAsync: requested read bounds are out of range.")})},this.copyFramebufferToTexture=function(_,Le=null,mt=0){const lt=Math.pow(2,-mt),Je=Math.floor(_.image.width*lt),Jn=Math.floor(_.image.height*lt),Mr=Le!==null?Le.x:0,tr=Le!==null?Le.y:0;Be.setTexture2D(_,0),se.copyTexSubImage2D(se.TEXTURE_2D,mt,0,0,Mr,tr,Je,Jn),Jt.unbindTexture()};const GA=se.createFramebuffer(),eC=se.createFramebuffer();this.copyTextureToTexture=function(_,Le,mt=null,lt=null,Je=0,Jn=null){Jn===null&&(Je!==0?(rs("WebGLRenderer: copyTextureToTexture function signature has changed to support src and dst mipmap levels."),Jn=Je,Je=0):Jn=0);let Mr,tr,Or,qe,Tr,xr,ni,ds,ya;const Ds=_.isCompressedTexture?_.mipmaps[Jn]:_.image;if(mt!==null)Mr=mt.max.x-mt.min.x,tr=mt.max.y-mt.min.y,Or=mt.isBox3?mt.max.z-mt.min.z:1,qe=mt.min.x,Tr=mt.min.y,xr=mt.isBox3?mt.min.z:0;else{const fu=Math.pow(2,-Je);Mr=Math.floor(Ds.width*fu),tr=Math.floor(Ds.height*fu),_.isDataArrayTexture?Or=Ds.depth:_.isData3DTexture?Or=Math.floor(Ds.depth*fu):Or=1,qe=0,Tr=0,xr=0}lt!==null?(ni=lt.x,ds=lt.y,ya=lt.z):(ni=0,ds=0,ya=0);const Hs=rn.convert(Le.format),ti=rn.convert(Le.type);let Ts;Le.isData3DTexture?(Be.setTexture3D(Le,0),Ts=se.TEXTURE_3D):Le.isDataArrayTexture||Le.isCompressedArrayTexture?(Be.setTexture2DArray(Le,0),Ts=se.TEXTURE_2D_ARRAY):(Be.setTexture2D(Le,0),Ts=se.TEXTURE_2D),se.pixelStorei(se.UNPACK_FLIP_Y_WEBGL,Le.flipY),se.pixelStorei(se.UNPACK_PREMULTIPLY_ALPHA_WEBGL,Le.premultiplyAlpha),se.pixelStorei(se.UNPACK_ALIGNMENT,Le.unpackAlignment);const xs=se.getParameter(se.UNPACK_ROW_LENGTH),Kl=se.getParameter(se.UNPACK_IMAGE_HEIGHT),Oh=se.getParameter(se.UNPACK_SKIP_PIXELS),ql=se.getParameter(se.UNPACK_SKIP_ROWS),tm=se.getParameter(se.UNPACK_SKIP_IMAGES);se.pixelStorei(se.UNPACK_ROW_LENGTH,Ds.width),se.pixelStorei(se.UNPACK_IMAGE_HEIGHT,Ds.height),se.pixelStorei(se.UNPACK_SKIP_PIXELS,qe),se.pixelStorei(se.UNPACK_SKIP_ROWS,Tr),se.pixelStorei(se.UNPACK_SKIP_IMAGES,xr);const ca=_.isDataArrayTexture||_.isData3DTexture,Sl=Le.isDataArrayTexture||Le.isData3DTexture;if(_.isDepthTexture){const fu=V.get(_),ll=V.get(Le),Dl=V.get(fu.__renderTarget),Fu=V.get(ll.__renderTarget);Jt.bindFramebuffer(se.READ_FRAMEBUFFER,Dl.__webglFramebuffer),Jt.bindFramebuffer(se.DRAW_FRAMEBUFFER,Fu.__webglFramebuffer);for(let _l=0;_l<Or;_l++)ca&&(se.framebufferTextureLayer(se.READ_FRAMEBUFFER,se.COLOR_ATTACHMENT0,V.get(_).__webglTexture,Je,xr+_l),se.framebufferTextureLayer(se.DRAW_FRAMEBUFFER,se.COLOR_ATTACHMENT0,V.get(Le).__webglTexture,Jn,ya+_l)),se.blitFramebuffer(qe,Tr,Mr,tr,ni,ds,Mr,tr,se.DEPTH_BUFFER_BIT,se.NEAREST);Jt.bindFramebuffer(se.READ_FRAMEBUFFER,null),Jt.bindFramebuffer(se.DRAW_FRAMEBUFFER,null)}else if(Je!==0||_.isRenderTargetTexture||V.has(_)){const fu=V.get(_),ll=V.get(Le);Jt.bindFramebuffer(se.READ_FRAMEBUFFER,GA),Jt.bindFramebuffer(se.DRAW_FRAMEBUFFER,eC);for(let Dl=0;Dl<Or;Dl++)ca?se.framebufferTextureLayer(se.READ_FRAMEBUFFER,se.COLOR_ATTACHMENT0,fu.__webglTexture,Je,xr+Dl):se.framebufferTexture2D(se.READ_FRAMEBUFFER,se.COLOR_ATTACHMENT0,se.TEXTURE_2D,fu.__webglTexture,Je),Sl?se.framebufferTextureLayer(se.DRAW_FRAMEBUFFER,se.COLOR_ATTACHMENT0,ll.__webglTexture,Jn,ya+Dl):se.framebufferTexture2D(se.DRAW_FRAMEBUFFER,se.COLOR_ATTACHMENT0,se.TEXTURE_2D,ll.__webglTexture,Jn),Je!==0?se.blitFramebuffer(qe,Tr,Mr,tr,ni,ds,Mr,tr,se.COLOR_BUFFER_BIT,se.NEAREST):Sl?se.copyTexSubImage3D(Ts,Jn,ni,ds,ya+Dl,qe,Tr,Mr,tr):se.copyTexSubImage2D(Ts,Jn,ni,ds,qe,Tr,Mr,tr);Jt.bindFramebuffer(se.READ_FRAMEBUFFER,null),Jt.bindFramebuffer(se.DRAW_FRAMEBUFFER,null)}else Sl?_.isDataTexture||_.isData3DTexture?se.texSubImage3D(Ts,Jn,ni,ds,ya,Mr,tr,Or,Hs,ti,Ds.data):Le.isCompressedArrayTexture?se.compressedTexSubImage3D(Ts,Jn,ni,ds,ya,Mr,tr,Or,Hs,Ds.data):se.texSubImage3D(Ts,Jn,ni,ds,ya,Mr,tr,Or,Hs,ti,Ds):_.isDataTexture?se.texSubImage2D(se.TEXTURE_2D,Jn,ni,ds,Mr,tr,Hs,ti,Ds.data):_.isCompressedTexture?se.compressedTexSubImage2D(se.TEXTURE_2D,Jn,ni,ds,Ds.width,Ds.height,Hs,Ds.data):se.texSubImage2D(se.TEXTURE_2D,Jn,ni,ds,Mr,tr,Hs,ti,Ds);se.pixelStorei(se.UNPACK_ROW_LENGTH,xs),se.pixelStorei(se.UNPACK_IMAGE_HEIGHT,Kl),se.pixelStorei(se.UNPACK_SKIP_PIXELS,Oh),se.pixelStorei(se.UNPACK_SKIP_ROWS,ql),se.pixelStorei(se.UNPACK_SKIP_IMAGES,tm),Jn===0&&Le.generateMipmaps&&se.generateMipmap(Ts),Jt.unbindTexture()},this.initRenderTarget=function(_){V.get(_).__webglFramebuffer===void 0&&Be.setupRenderTarget(_)},this.initTexture=function(_){_.isCubeTexture?Be.setTextureCube(_,0):_.isData3DTexture?Be.setTexture3D(_,0):_.isDataArrayTexture||_.isCompressedArrayTexture?Be.setTexture2DArray(_,0):Be.setTexture2D(_,0),Jt.unbindTexture()},this.resetState=function(){D=0,j=0,q=null,Jt.reset(),cn.reset()},typeof __THREE_DEVTOOLS__!="undefined"&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent("observe",{detail:this}))}get coordinateSystem(){return Gt}get outputColorSpace(){return this._outputColorSpace}set outputColorSpace(e){this._outputColorSpace=e;const t=this.getContext();t.drawingBufferColorSpace=$r._getDrawingBufferColorSpace(e),t.unpackColorSpace=$r._getUnpackColorSpace()}}const AX=["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"],SP=new WeakMap;class xX{constructor(e){this.renderObjects=new WeakMap,this.hasNode=this.containsNode(e),this.hasAnimation=e.object.isSkinnedMesh===!0,this.refreshUniforms=AX,this.renderId=0}firstInitialization(e){return this.renderObjects.has(e)===!1?(this.getRenderObjectData(e),!0):!1}needsVelocity(e){const t=e.getMRT();return t!==null&&t.has("velocity")}getRenderObjectData(e){let t=this.renderObjects.get(e);if(t===void 0){const{geometry:n,material:i,object:s}=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:s.matrixWorld.clone()},s.center&&(t.center=s.center.clone()),s.morphTargetInfluences&&(t.morphTargetInfluences=s.morphTargetInfluences.slice()),e.bundle!==null&&(t.version=e.bundle.version),t.material.transmission>0){const{width:a,height:o}=e.context;t.bufferWidth=a,t.bufferHeight=o}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 n in t)if(t[n]&&t[n].isNode)return!0;return!!(e.context.modelViewMatrix||e.context.modelNormalViewMatrix||e.context.getAO||e.context.getShadow)}getMaterialData(e){const t={};for(const n of this.refreshUniforms){const i=e[n];i!=null&&(typeof i=="object"&&i.clone!==void 0?i.isTexture===!0?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:s}=e,a=this.getRenderObjectData(e);if(a.worldMatrix.equals(n.matrixWorld)!==!0)return a.worldMatrix.copy(n.matrixWorld),!1;const o=a.material;for(const v in o){const m=o[v],C=i[v];if(m.equals!==void 0){if(m.equals(C)===!1)return m.copy(C),!1}else if(C.isTexture===!0){if(m.id!==C.id||m.version!==C.version)return m.id=C.id,m.version=C.version,!1}else if(m!==C)return o[v]=C,!1}if(o.transmission>0){const{width:v,height:m}=e.context;if(a.bufferWidth!==v||a.bufferHeight!==m)return a.bufferWidth=v,a.bufferHeight=m,!1}const l=a.geometry,u=s.attributes,c=l.attributes,d=Object.keys(c),f=Object.keys(u);if(l.id!==s.id)return l.id=s.id,!1;if(d.length!==f.length)return a.geometry.attributes=this.getAttributesData(u),!1;for(const v of d){const m=c[v],C=u[v];if(C===void 0)return delete c[v],!1;if(m.version!==C.version)return m.version=C.version,!1}const h=s.index,p=l.indexVersion,x=h?h.version:null;if(p!==x)return l.indexVersion=x,!1;if(l.drawRange.start!==s.drawRange.start||l.drawRange.count!==s.drawRange.count)return l.drawRange.start=s.drawRange.start,l.drawRange.count=s.drawRange.count,!1;if(a.morphTargetInfluences){let v=!1;for(let m=0;m<a.morphTargetInfluences.length;m++)a.morphTargetInfluences[m]!==n.morphTargetInfluences[m]&&(a.morphTargetInfluences[m]=n.morphTargetInfluences[m],v=!0);if(v)return!1}if(a.lights){for(let v=0;v<t.length;v++)if(a.lights[v].map!==t[v].map)return!1}return a.center&&a.center.equals(n.center)===!1?(a.center.copy(n.center),!0):(e.bundle!==null&&(a.version=e.bundle.version),!0)}getLightsData(e){const t=[];for(const n of e)n.isSpotLight===!0&&n.map!==null&&t.push({map:n.map.version});return t}getLights(e,t){if(SP.has(e)){const i=SP.get(e);if(i.renderId===t)return i.lightsData}const n=this.getLightsData(e.getLights());return SP.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=e.object.static===!0,s=e.bundle!==null&&e.bundle.static===!0&&this.getRenderObjectData(e).version===e.bundle.version;if(i||s)return!1;const a=this.getLights(e.lightsNode,n);return this.equals(e,a)!==!0}}function DP(r,e=0){let t=3735928559^e,n=1103547991^e;if(r instanceof Array)for(let i=0,s;i<r.length;i++)s=r[i],t=Math.imul(t^s,2654435761),n=Math.imul(n^s,1597334677);else for(let i=0,s;i<r.length;i++)s=r.charCodeAt(i),t=Math.imul(t^s,2654435761),n=Math.imul(n^s,1597334677);return t=Math.imul(t^t>>>16,2246822507),t^=Math.imul(n^n>>>13,3266489909),n=Math.imul(n^n>>>16,2246822507),n^=Math.imul(t^t>>>13,3266489909),4294967296*(2097151&n)+(t>>>0)}const lA=r=>DP(r),ag=r=>DP(r),uA=(...r)=>DP(r),yX=new Map([[1,"float"],[2,"vec2"],[3,"vec3"],[4,"vec4"],[9,"mat3"],[16,"mat4"]]),QT=new WeakMap;function TP(r){return yX.get(r)}function sx(r){if(/[iu]?vec\d/.test(r))return r.startsWith("ivec")?Int32Array:r.startsWith("uvec")?Uint32Array:Float32Array;if(/mat\d/.test(r)||/float/.test(r))return Float32Array;if(/uint/.test(r))return Uint32Array;if(/int/.test(r))return Int32Array;throw new Error(`THREE.NodeUtils: Unsupported type: ${r}`)}function IP(r){if(/float|int|uint/.test(r))return 1;if(/vec2/.test(r))return 2;if(/vec3/.test(r))return 3;if(/vec4/.test(r)||/mat2/.test(r))return 4;if(/mat3/.test(r))return 9;if(/mat4/.test(r))return 16;rt("TSL: Unsupported type:",r)}function ZT(r){if(/float|int|uint/.test(r))return 1;if(/vec2/.test(r))return 2;if(/vec3/.test(r))return 3;if(/vec4/.test(r)||/mat2/.test(r))return 4;if(/mat3/.test(r))return 12;if(/mat4/.test(r))return 16;rt("TSL: Unsupported type:",r)}function YT(r){if(/float|int|uint/.test(r))return 4;if(/vec2/.test(r))return 8;if(/vec3/.test(r)||/vec4/.test(r))return 16;if(/mat2/.test(r))return 8;if(/mat3/.test(r)||/mat4/.test(r))return 16;rt("TSL: Unsupported type:",r)}function Ah(r){if(r==null)return null;const e=typeof r;return r.isNode===!0?"node":e==="number"?"float":e==="boolean"?"bool":e==="string"?"string":e==="function"?"shader":r.isVector2===!0?"vec2":r.isVector3===!0?"vec3":r.isVector4===!0?"vec4":r.isMatrix2===!0?"mat2":r.isMatrix3===!0?"mat3":r.isMatrix4===!0?"mat4":r.isColor===!0?"color":r instanceof ArrayBuffer?"ArrayBuffer":null}function Jb(r,...e){const t=r?r.slice(-4):void 0;return e.length===1&&(t==="vec2"?e=[e[0],e[0]]:t==="vec3"?e=[e[0],e[0],e[0]]:t==="vec4"&&(e=[e[0],e[0],e[0],e[0]])),r==="color"?new Vn(...e):t==="vec2"?new ct(...e):t==="vec3"?new J(...e):t==="vec4"?new Ei(...e):t==="mat2"?new Cb(...e):t==="mat3"?new zi(...e):t==="mat4"?new Cr(...e):r==="bool"?e[0]||!1:r==="float"||r==="int"||r==="uint"?e[0]||0:r==="string"?e[0]||"":r==="ArrayBuffer"?RP(e[0]):null}function NP(r){let e=QT.get(r);return e===void 0&&(e={},QT.set(r,e)),e}function FP(r){let e="";const t=new Uint8Array(r);for(let n=0;n<t.length;n++)e+=String.fromCharCode(t[n]);return btoa(e)}function RP(r){return Uint8Array.from(atob(r),e=>e.charCodeAt(0)).buffer}var Cde=Object.freeze({__proto__:null,arrayBufferToBase64:FP,base64ToArrayBuffer:RP,getAlignmentFromType:YT,getDataFromObject:NP,getLengthFromType:IP,getMemoryLengthFromType:ZT,getTypeFromLength:TP,getTypedArrayFromType:sx,getValueFromType:Jb,getValueType:Ah,hash:uA,hashArray:ag,hashString:lA});const ax={VERTEX:"vertex",FRAGMENT:"fragment"},Bi={NONE:"none",FRAME:"frame",RENDER:"render",OBJECT:"object"},bX={BOOLEAN:"bool",INTEGER:"int",FLOAT:"float",VECTOR2:"vec2",VECTOR3:"vec3",VECTOR4:"vec4",MATRIX2:"mat2",MATRIX3:"mat3",MATRIX4:"mat4"},El={READ_ONLY:"readOnly",WRITE_ONLY:"writeOnly",READ_WRITE:"readWrite"},JT=["fragment","vertex"],LP=["setup","analyze","generate"],OP=[...JT,"compute"],og=["x","y","z","w"],EX={analyze:"setup",generate:"analyze"};let wX=0;class ar extends Go{static get type(){return"Node"}constructor(e=null){super(),this.nodeType=e,this.updateType=Bi.NONE,this.updateBeforeType=Bi.NONE,this.updateAfterType=Bi.NONE,this.uuid=S0.generateUUID(),this.version=0,this.name="",this.global=!1,this.parents=!1,this.isNode=!0,this._beforeNodes=null,this._cacheKey=null,this._cacheKeyVersion=0,Object.defineProperty(this,"id",{value:wX++})}set needsUpdate(e){e===!0&&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,Bi.FRAME)}onRenderUpdate(e){return this.onUpdate(e,Bi.RENDER)}onObjectUpdate(e){return this.onUpdate(e,Bi.OBJECT)}onReference(e){return this.updateReference=e.bind(this),this}updateReference(){return this}isGlobal(){return this.global}*getChildren(){for(const{childNode:e}of this._getChildren())yield e}dispose(){this.dispatchEvent({type:"dispose"})}traverse(e){e(this);for(const t of this.getChildren())t.traverse(e)}_getChildren(e=new Set){const t=[];e.add(this);for(const n of Object.getOwnPropertyNames(this)){const i=this[n];if(!(n.startsWith("_")===!0||e.has(i))){if(Array.isArray(i)===!0)for(let s=0;s<i.length;s++){const a=i[s];a&&a.isNode===!0&&t.push({property:n,index:s,childNode:a})}else if(i&&i.isNode===!0)t.push({property:n,childNode:i});else if(i&&Object.getPrototypeOf(i)===Object.prototype)for(const s in i){if(s.startsWith("_")===!0)continue;const a=i[s];a&&a.isNode===!0&&t.push({property:n,index:s,childNode:a})}}}return t}getCacheKey(e=!1,t=null){if(e=e||this.version!==this._cacheKeyVersion,e===!0||this._cacheKey===null){t===null&&(t=new Set);const n=[];for(const{property:i,childNode:s}of this._getChildren(t))n.push(lA(i.slice(0,-4)),s.getCacheKey(e,t));this._cacheKey=uA(ag(n),this.customCacheKey()),this._cacheKeyVersion=this.version}return this._cacheKey}customCacheKey(){return this.id}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 i of this.getChildren())t["node"+n++]=i;return t.outputNode||null}analyze(e,t=null){const n=e.increaseUsage(this);if(this.parents===!0){const i=e.getDataFromNode(this,"any");i.stages=i.stages||{},i.stages[e.shaderStage]=i.stages[e.shaderStage]||[],i.stages[e.shaderStage].push(t)}if(n===1){const i=e.getNodeProperties(this);for(const s of Object.values(i))s&&s.isNode===!0&&s.build(e,this)}}generate(e,t){const{outputNode:n}=e.getNodeProperties(this);if(n&&n.isNode===!0)return n.build(e,t)}updateBefore(){ze("Abstract function.")}updateAfter(){ze("Abstract function.")}update(){ze("Abstract function.")}before(e){return this._beforeNodes===null&&(this._beforeNodes=[]),this._beforeNodes.push(e),this}build(e,t=null){const n=this.getShared(e);if(this!==n)return n.build(e,t);if(this._beforeNodes!==null){const l=this._beforeNodes;this._beforeNodes=null;for(const u of l)u.build(e,t);this._beforeNodes=l}const i=e.getDataFromNode(this);i.buildStages=i.buildStages||{},i.buildStages[e.buildStage]=!0;const s=EX[e.buildStage];if(s&&i.buildStages[s]!==!0){const l=e.getBuildStage();e.setBuildStage(s),this.build(e),e.setBuildStage(l)}e.addNode(this),e.addChain(this);let a=null;const o=e.getBuildStage();if(o==="setup"){this.updateReference(e);const l=e.getNodeProperties(this);if(l.initialized!==!0){l.initialized=!0,l.outputNode=this.setup(e)||l.outputNode||null;for(const u of Object.values(l))if(u&&u.isNode===!0){if(u.parents===!0){const c=e.getNodeProperties(u);c.parents=c.parents||[],c.parents.push(this)}u.build(e)}}a=l.outputNode}else if(o==="analyze")this.analyze(e,t);else if(o==="generate"){if(this.generate.length<2){const u=this.getNodeType(e),c=e.getDataFromNode(this);a=c.snippet,a===void 0?c.generated===void 0?(c.generated=!0,a=this.generate(e)||"",c.snippet=a):(ze("Node: Recursion detected.",this),a="/* Recursion detected. */"):c.flowCodes!==void 0&&e.context.nodeBlock!==void 0&&e.addFlowCodeHierarchy(this,e.context.nodeBlock),a=e.format(a,u,t)}else a=this.generate(e,t)||"";a===""&&t!==null&&t!=="void"&&t!=="OutputType"&&(rt(`TSL: Invalid generated code, expected a "${t}".`),a=e.generateConst(t))}return e.removeChain(this),e.addSequentialNode(this),a}getSerializeChildren(){return this._getChildren()}serialize(e){const t=this.getSerializeChildren(),n={};for(const{property:i,index:s,childNode:a}of t)s!==void 0?(n[i]===void 0&&(n[i]=Number.isInteger(s)?[]:{}),n[i][s]=a.toJSON(e.meta).uuid):n[i]=a.toJSON(e.meta).uuid;Object.keys(n).length>0&&(e.inputNodes=n)}deserialize(e){if(e.inputNodes!==void 0){const t=e.meta.nodes;for(const n in e.inputNodes)if(Array.isArray(e.inputNodes[n])){const i=[];for(const s of e.inputNodes[n])i.push(t[s]);this[n]=i}else if(typeof e.inputNodes[n]=="object"){const i={};for(const s in e.inputNodes[n]){const a=e.inputNodes[n][s];i[s]=t[a]}this[n]=i}else{const i=e.inputNodes[n];this[n]=t[i]}}}toJSON(e){const{uuid:t,type:n}=this,i=e===void 0||typeof e=="string";i&&(e={textures:{},images:{},nodes:{}});let s=e.nodes[t];s===void 0&&(s={uuid:t,type:n,meta:e,metadata:{version:4.7,type:"Node",generator:"Node.toJSON"}},i!==!0&&(e.nodes[s.uuid]=s),this.serialize(s),delete s.meta);function a(o){const l=[];for(const u in o){const c=o[u];delete c.metadata,l.push(c)}return l}if(i){const o=a(e.textures),l=a(e.images),u=a(e.nodes);o.length>0&&(s.textures=o),l.length>0&&(s.images=l),u.length>0&&(s.nodes=u)}return s}}class lg extends ar{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)}getMemberType(e,t){return this.node.getMemberType(e,t)}generate(e){const t=this.indexNode.getNodeType(e),n=this.node.build(e),i=this.indexNode.build(e,!e.isVector(t)&&e.isInteger(t)?t:"uint");return`${n}[ ${i} ]`}}class KT extends ar{static get type(){return"ConvertNode"}constructor(e,t){super(),this.node=e,this.convertTo=t}getNodeType(e){const t=this.node.getNodeType(e);let n=null;for(const i of this.convertTo.split("|"))(n===null||e.getTypeLength(t)===e.getTypeLength(i))&&(n=i);return n}serialize(e){super.serialize(e),e.convertTo=this.convertTo}deserialize(e){super.deserialize(e),this.convertTo=e.convertTo}generate(e,t){const n=this.node,i=this.getNodeType(e),s=n.build(e,i);return e.format(s,i,t)}}class Qa extends ar{static get type(){return"TempNode"}constructor(e=null){super(e),this.isTempNode=!0}hasDependencies(e){return e.getDataFromNode(this).usageCount>1}build(e,t){if(e.getBuildStage()==="generate"){const i=e.getVectorType(this.getNodeType(e,t)),s=e.getDataFromNode(this);if(s.propertyName!==void 0)return e.format(s.propertyName,i,t);if(i!=="void"&&t!=="void"&&this.hasDependencies(e)){const a=super.build(e,i),o=e.getVarFromNode(this,null,i),l=e.getPropertyName(o);return e.addLineFlowCode(`${l} = ${a}`,this),s.snippet=a,s.propertyName=l,e.format(s.propertyName,i,t)}}return super.build(e,t)}}class CX extends Qa{static get type(){return"JoinNode"}constructor(e=[],t=null){super(t),this.nodes=e}getNodeType(e){return this.nodeType!==null?e.getVectorType(this.nodeType):e.getTypeFromLength(this.nodes.reduce((t,n)=>t+e.getTypeLength(n.getNodeType(e)),0))}generate(e,t){const n=this.getNodeType(e),i=e.getTypeLength(n),s=this.nodes,a=e.getComponentType(n),o=[];let l=0;for(const c of s){if(l>=i){rt(`TSL: Length of parameters exceeds maximum length of function '${n}()' type.`);break}let d=c.getNodeType(e),f=e.getTypeLength(d),h;if(l+f>i&&(rt(`TSL: Length of '${n}()' data exceeds maximum length of output type.`),f=i-l,d=e.getTypeFromLength(f)),l+=f,h=c.build(e,d),e.getComponentType(d)!==a){const x=e.getTypeFromLength(f,a);h=e.format(h,d,x)}o.push(h)}const u=`${e.getType(n)}( ${o.join(", ")} )`;return e.format(u,n,t)}}const PX=og.join("");class qT extends ar{static get type(){return"SplitNode"}constructor(e,t="x"){super(),this.node=e,this.components=t,this.isSplitNode=!0}getVectorLength(){let e=this.components.length;for(const t of this.components)e=Math.max(og.indexOf(t)+1,e);return e}getComponentType(e){return e.getComponentType(this.node.getNodeType(e))}getNodeType(e){return e.getTypeFromLength(this.components.length,this.getComponentType(e))}getScope(){return this.node.getScope()}generate(e,t){const n=this.node,i=e.getTypeLength(n.getNodeType(e));let s=null;if(i>1){let a=null;this.getVectorLength()>=i&&(a=e.getTypeFromLength(this.getVectorLength(),this.getComponentType(e)));const l=n.build(e,a);this.components.length===i&&this.components===PX.slice(0,this.components.length)?s=e.format(l,a,t):s=e.format(`${l}.${this.components}`,this.getNodeType(e),t)}else s=n.build(e,t);return s}serialize(e){super.serialize(e),e.components=this.components}deserialize(e){super.deserialize(e),this.components=e.components}}class BX extends Qa{static get type(){return"SetNode"}constructor(e,t,n){super(),this.sourceNode=e,this.components=t,this.targetNode=n}getNodeType(e){return this.sourceNode.getNodeType(e)}generate(e){const{sourceNode:t,components:n,targetNode:i}=this,s=this.getNodeType(e),a=e.getComponentType(i.getNodeType(e)),o=e.getTypeFromLength(n.length,a),l=i.build(e,o),u=t.build(e,s),c=e.getTypeLength(s),d=[];for(let f=0;f<c;f++){const h=og[f];h===n[0]?(d.push(l),f+=n.length-1):d.push(u+"."+h)}return`${e.getType(s)}( ${d.join(", ")} )`}}class MX extends Qa{static get type(){return"FlipNode"}constructor(e,t){super(),this.sourceNode=e,this.components=t}getNodeType(e){return this.sourceNode.getNodeType(e)}generate(e){const{components:t,sourceNode:n}=this,i=this.getNodeType(e),s=n.build(e),a=e.getVarFromNode(this),o=e.getPropertyName(a);e.addLineFlowCode(o+" = "+s,this);const l=e.getTypeLength(i),u=[];let c=0;for(let d=0;d<l;d++){const f=og[d];f===t[c]?(u.push("1.0 - "+(o+"."+f)),c++):u.push(o+"."+f)}return`${e.getType(i)}( ${u.join(", ")} )`}}class zP extends ar{static get type(){return"InputNode"}constructor(e,t=null){super(t),this.isInputNode=!0,this.value=e,this.precision=null}getNodeType(){return this.nodeType===null?Ah(this.value):this.nodeType}getInputType(e){return this.getNodeType(e)}setPrecision(e){return this.precision=e,this}serialize(e){super.serialize(e),e.value=this.value,this.value&&this.value.toArray&&(e.value=this.value.toArray()),e.valueType=Ah(this.value),e.nodeType=this.nodeType,e.valueType==="ArrayBuffer"&&(e.value=FP(e.value)),e.precision=this.precision}deserialize(e){super.deserialize(e),this.nodeType=e.nodeType,this.value=Array.isArray(e.value)?Jb(e.valueType,...e.value):e.value,this.precision=e.precision||null,this.value&&this.value.fromArray&&(this.value=this.value.fromArray(e.value))}generate(){ze("Abstract function.")}}const _T=/float|u?int/;class Tc extends zP{static get type(){return"ConstNode"}constructor(e,t=null){super(e,t),this.isConstNode=!0}generateConst(e){return e.generateConst(this.getNodeType(e),this.value)}generate(e,t){const n=this.getNodeType(e);return _T.test(n)&&_T.test(t)?e.generateConst(t,this.value):e.format(this.generateConst(e),n,t)}}class SX extends ar{static get type(){return"MemberNode"}constructor(e,t){super(),this.structNode=e,this.property=t,this.isMemberNode=!0}hasMember(e){return this.structNode.isMemberNode&&this.structNode.hasMember(e)===!1?!1:this.structNode.getMemberType(e,this.property)!=="void"}getNodeType(e){return this.hasMember(e)===!1?"float":this.structNode.getMemberType(e,this.property)}getMemberType(e,t){if(this.hasMember(e)===!1)return"float";const n=this.getNodeType(e);return e.getStructTypeNode(n).getMemberType(e,t)}generate(e){if(this.hasMember(e)===!1){ze(`TSL: Member "${this.property}" does not exist in struct.`);const n=this.getNodeType(e);return e.generateConst(n)}return this.structNode.build(e)+"."+this.property}}let Lp=null;const HP=new Map;function vt(r,e){if(HP.has(r)){ze(`TSL: Redefinition of method chaining '${r}'.`);return}if(typeof e!="function")throw new Error(`THREE.TSL: Node element ${r} is not a function`);HP.set(r,e),r!=="assign"&&(ar.prototype[r]=function(...t){return this.isStackNode?this.addToStack(e(...t)):e(this,...t)},ar.prototype[r+"Assign"]=function(...t){return this.isStackNode?this.assign(t[0],e(...t)):this.assign(e(this,...t))})}const DX=r=>r.replace(/r|s/g,"x").replace(/g|t/g,"y").replace(/b|p/g,"z").replace(/a|q/g,"w"),$T=r=>DX(r).split("").sort().join("");ar.prototype.assign=function(...r){if(this.isStackNode!==!0)return Lp!==null?Lp.assign(this,...r):rt("TSL: No stack defined for assign operation. Make sure the assign is inside a Fn()."),this;{const e=HP.get("assign");return this.addToStack(e(...r))}},ar.prototype.toVarIntent=function(){return this},ar.prototype.get=function(r){return new SX(this,r)};const ox={};function Kb(r,e,t){ox[r]=ox[e]=ox[t]={get(){this._cache=this._cache||{};let a=this._cache[r];return a===void 0&&(a=new qT(this,r),this._cache[r]=a),a},set(a){this[r].assign(wn(a))}};const n=r.toUpperCase(),i=e.toUpperCase(),s=t.toUpperCase();ar.prototype["set"+n]=ar.prototype["set"+i]=ar.prototype["set"+s]=function(a){const o=$T(r);return new BX(this,o,wn(a))},ar.prototype["flip"+n]=ar.prototype["flip"+i]=ar.prototype["flip"+s]=function(){const a=$T(r);return new MX(this,a)}}const mf=["x","y","z","w"],gf=["r","g","b","a"],vf=["s","t","p","q"];for(let r=0;r<4;r++){let e=mf[r],t=gf[r],n=vf[r];Kb(e,t,n);for(let i=0;i<4;i++){e=mf[r]+mf[i],t=gf[r]+gf[i],n=vf[r]+vf[i],Kb(e,t,n);for(let s=0;s<4;s++){e=mf[r]+mf[i]+mf[s],t=gf[r]+gf[i]+gf[s],n=vf[r]+vf[i]+vf[s],Kb(e,t,n);for(let a=0;a<4;a++)e=mf[r]+mf[i]+mf[s]+mf[a],t=gf[r]+gf[i]+gf[s]+gf[a],n=vf[r]+vf[i]+vf[s]+vf[a],Kb(e,t,n)}}}for(let r=0;r<32;r++)ox[r]={get(){this._cache=this._cache||{};let e=this._cache[r];return e===void 0&&(e=new lg(this,new Tc(r,"uint")),this._cache[r]=e),e},set(e){this[r].assign(wn(e))}};Object.defineProperties(ar.prototype,ox);const e8=new WeakMap,TX=function(r,e=null){const t=Ah(r);return t==="node"?r:e===null&&(t==="float"||t==="boolean")||t&&t!=="shader"&&t!=="string"?wn(jP(r,e)):t==="shader"?r.isFn?r:be(r):r},IX=function(r,e=null){for(const t in r)r[t]=wn(r[t],e);return r},NX=function(r,e=null){const t=r.length;for(let n=0;n<t;n++)r[n]=wn(r[n],e);return r},t8=function(r,e=null,t=null,n=null){function i(c){return n!==null?(c=wn(Object.assign(c,n)),n.intent===!0&&(c=c.toVarIntent())):c=wn(c),c}let s,a=e,o,l;function u(c){let d;return a?d=/[a-z]/i.test(a)?a+"()":a:d=r.type,o!==void 0&&c.length<o?(rt(`TSL: "${d}" parameter length is less than minimum required.`),c.concat(new Array(o-c.length).fill(0))):l!==void 0&&c.length>l?(rt(`TSL: "${d}" parameter length exceeds limit.`),c.slice(0,l)):c}return e===null?s=(...c)=>i(new r(...ug(u(c)))):t!==null?(t=wn(t),s=(...c)=>i(new r(e,...ug(u(c)),t))):s=(...c)=>i(new r(e,...ug(u(c)))),s.setParameterLength=(...c)=>(c.length===1?o=l=c[0]:c.length===2&&([o,l]=c),s),s.setName=c=>(a=c,s),s},FX=function(r,...e){return new r(...ug(e))};class RX extends ar{constructor(e,t){super(),this.shaderNode=e,this.rawInputs=t,this.isShaderCallNodeInternal=!0}getNodeType(e){return this.shaderNode.nodeType||this.getOutputNode(e).getNodeType(e)}getElementType(e){return this.getOutputNode(e).getElementType(e)}getMemberType(e,t){return this.getOutputNode(e).getMemberType(e,t)}call(e){const{shaderNode:t,rawInputs:n}=this,i=e.getNodeProperties(t),s=e.getClosestSubBuild(t.subBuilds)||"",a=s||"default";if(i[a])return i[a];const o=e.subBuildFn,l=e.fnCall;e.subBuildFn=s,e.fnCall=this;let u=null;if(t.layout){let c=e8.get(e.constructor);c===void 0&&(c=new WeakMap,e8.set(e.constructor,c));let d=c.get(t);d===void 0&&(d=wn(e.buildFunctionNode(t)),c.set(t,d)),e.addInclude(d);const f=n?LX(n):null;u=wn(d.call(f))}else{const c=new Proxy(e,{get:(x,v,m)=>{let C;return Symbol.iterator===v?C=function*(){yield void 0}:C=Reflect.get(x,v,m),C}}),d=n?OX(n):null,f=Array.isArray(n)?n.length>0:n!==null,h=t.jsFunc,p=f||h.length>1?h(d,c):h(c);u=wn(p)}return e.subBuildFn=o,e.fnCall=l,t.once&&(i[a]=u),u}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(),s=e.getNodeProperties(this),a=e.getSubBuildOutput(this),o=this.getOutputNode(e),l=e.fnCall;if(e.fnCall=this,i==="setup"){const u=e.getSubBuildProperty("initialized",this);if(s[u]!==!0&&(s[u]=!0,s[a]=this.getOutputNode(e),s[a].build(e),this.shaderNode.subBuilds))for(const c of e.chaining){const d=e.getDataFromNode(c,"any");d.subBuilds=d.subBuilds||new Set;for(const f of this.shaderNode.subBuilds)d.subBuilds.add(f)}n=s[a]}else i==="analyze"?o.build(e,t):i==="generate"&&(n=o.build(e,t)||"");return e.fnCall=l,n}}function LX(r){let e;return $b(r),r[0]&&(r[0].isNode||Object.getPrototypeOf(r[0])!==Object.prototype)?e=[...r]:e=r[0],e}function OX(r){let e=0;return $b(r),new Proxy(r,{get:(t,n,i)=>{let s;if(n==="length")return s=r.length,s;if(Symbol.iterator===n)s=function*(){for(const a of r)yield wn(a)};else{if(r.length>0)if(Object.getPrototypeOf(r[0])===Object.prototype){const a=r[0];a[n]===void 0?s=a[e++]:s=Reflect.get(a,n,i)}else r[0]instanceof ar&&(r[n]===void 0?s=r[e++]:s=Reflect.get(r,n,i));else s=Reflect.get(t,n,i);s=wn(s)}return s}})}class zX extends ar{constructor(e,t){super(t),this.jsFunc=e,this.layout=null,this.global=!0,this.once=!1}setLayout(e){return this.layout=e,this}getLayout(){return this.layout}call(e=null){return new RX(this,e)}setup(){return this.call()}}const HX=[!1,!0],UX=[0,1,2,3],kX=[-1,-2],n8=[.5,1.5,1/3,1e-6,1e6,Math.PI,Math.PI*2,1/Math.PI,2/Math.PI,1/(Math.PI*2),Math.PI/2],UP=new Map;for(const r of HX)UP.set(r,new Tc(r));const kP=new Map;for(const r of UX)kP.set(r,new Tc(r,"uint"));const VP=new Map([...kP].map(r=>new Tc(r.value,"int")));for(const r of kX)VP.set(r,new Tc(r,"int"));const qb=new Map([...VP].map(r=>new Tc(r.value)));for(const r of n8)qb.set(r,new Tc(r));for(const r of n8)qb.set(-r,new Tc(-r));const _b={bool:UP,uint:kP,ints:VP,float:qb},r8=new Map([...UP,...qb]),jP=(r,e)=>r8.has(r)?r8.get(r):r.isNode===!0?r:new Tc(r,e),No=function(r,e=null){return(...t)=>{for(const i of t)if(i===void 0)return rt(`TSL: Invalid parameter for the type "${r}".`),new Tc(0,r);if((t.length===0||!["bool","float","int","uint"].includes(r)&&t.every(i=>{const s=typeof i;return s!=="object"&&s!=="function"}))&&(t=[Jb(r,...t)]),t.length===1&&e!==null&&e.has(t[0]))return ux(e.get(t[0]));if(t.length===1){const i=jP(t[0],r);return i.nodeType===r?ux(i):ux(new KT(i,r))}const n=t.map(i=>jP(i));return ux(new CX(n,r))}},lx=r=>typeof r=="object"&&r!==null?r.value:r,i8=r=>r!=null?r.nodeType||r.convertTo||(typeof r=="string"?r:null):null;function cA(r,e){return new zX(r,e)}const wn=(r,e=null)=>TX(r,e),ux=(r,e=null)=>wn(r,e).toVarIntent(),$b=(r,e=null)=>new IX(r,e),ug=(r,e=null)=>new NX(r,e),vi=(r,e=null,t=null,n=null)=>new t8(r,e,t,n),An=(r,...e)=>new FX(r,...e),en=(r,e=null,t=null,n={})=>new t8(r,e,t,Gc(ba({},n),{intent:!0}));let VX=0;class jX extends ar{constructor(e,t=null){super();let n=null;t!==null&&(typeof t=="object"?n=t.return:(typeof t=="string"?n=t:rt("TSL: Invalid layout type."),t=null)),this.shaderNode=new cA(e,n),t!==null&&this.setLayout(t),this.isFn=!0}setLayout(e){const t=this.shaderNode.nodeType;if(typeof e.inputs!="object"){const n={name:"fn"+VX++,type:t,inputs:[]};for(const i in e)i!=="return"&&n.inputs.push({name:i,type:e[i]});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 this.shaderNode.nodeType==="void"&&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 rt('TSL: "Fn()" was declared but not invoked. Try calling it like "Fn()( ...params )".'),e.generateConst(t)}}function be(r,e=null){const t=new jX(r,e);return new Proxy(()=>{},{apply(n,i,s){return t.call(...s)},get(n,i,s){return Reflect.get(t,i,s)},set(n,i,s,a){return Reflect.set(t,i,s,a)}})}const cx=r=>{Lp=r},XP=()=>Lp,cr=(...r)=>Lp.If(...r),XX=(...r)=>Lp.Switch(...r);function eE(r){return Lp&&Lp.addToStack(r),r}vt("toStack",eE);const s8=new No("color"),K=new No("float",_b.float),ce=new No("int",_b.ints),Ut=new No("uint",_b.uint),Ic=new No("bool",_b.bool),Wt=new No("vec2"),Fo=new No("ivec2"),GP=new No("uvec2"),a8=new No("bvec2"),he=new No("vec3"),WP=new No("ivec3"),cg=new No("uvec3"),QP=new No("bvec3"),Yn=new No("vec4"),ZP=new No("ivec4"),YP=new No("uvec4"),o8=new No("bvec4"),tE=new No("mat2"),wl=new No("mat3"),Op=new No("mat4"),GX=(r="")=>new Tc(r,"string"),WX=r=>new Tc(r,"ArrayBuffer");vt("toColor",s8),vt("toFloat",K),vt("toInt",ce),vt("toUint",Ut),vt("toBool",Ic),vt("toVec2",Wt),vt("toIVec2",Fo),vt("toUVec2",GP),vt("toBVec2",a8),vt("toVec3",he),vt("toIVec3",WP),vt("toUVec3",cg),vt("toBVec3",QP),vt("toVec4",Yn),vt("toIVec4",ZP),vt("toUVec4",YP),vt("toBVec4",o8),vt("toMat2",tE),vt("toMat3",wl),vt("toMat4",Op);const l8=vi(lg).setParameterLength(2),u8=(r,e)=>wn(new KT(wn(r),e)),QX=(r,e)=>wn(new qT(wn(r),e));vt("element",l8),vt("convert",u8);const ZX=r=>(ze("TSL: append() has been renamed to Stack()."),eE(r));vt("append",r=>(ze("TSL: .append() has been renamed to .toStack()."),eE(r)));class Os extends ar{static get type(){return"PropertyNode"}constructor(e,t=null,n=!1){super(e),this.name=t,this.varying=n,this.isPropertyNode=!0,this.global=!0}customCacheKey(){return lA(this.type+":"+(this.name||"")+":"+(this.varying?"1":"0"))}getHash(e){return this.name||super.getHash(e)}generate(e){let t;return this.varying===!0?(t=e.getVaryingFromNode(this,this.name),t.needsInterpolation=!0):t=e.getVarFromNode(this,this.name),e.getPropertyName(t)}}const Cd=(r,e)=>new Os(r,e),tc=(r,e)=>new Os(r,e,!0),Ws=An(Os,"vec4","DiffuseColor"),dg=An(Os,"vec3","DiffuseContribution"),JP=An(Os,"vec3","EmissiveColor"),Af=An(Os,"float","Roughness"),xh=An(Os,"float","Metalness"),nE=An(Os,"float","Clearcoat"),dx=An(Os,"float","ClearcoatRoughness"),nc=An(Os,"vec3","Sheen"),zp=An(Os,"float","SheenRoughness"),rE=An(Os,"float","Iridescence"),iE=An(Os,"float","IridescenceIOR"),sE=An(Os,"float","IridescenceThickness"),aE=An(Os,"float","AlphaT"),Hp=An(Os,"float","Anisotropy"),fx=An(Os,"vec3","AnisotropyT"),fg=An(Os,"vec3","AnisotropyB"),Up=An(Os,"color","SpecularColor"),hg=An(Os,"color","SpecularColorBlended"),dA=An(Os,"float","SpecularF90"),oE=An(Os,"float","Shininess"),fA=An(Os,"vec4","Output"),pg=An(Os,"float","dashSize"),hx=An(Os,"float","gapSize"),YX=An(Os,"float","pointWidth"),px=An(Os,"float","IOR"),lE=An(Os,"float","Transmission"),KP=An(Os,"float","Thickness"),qP=An(Os,"float","AttenuationDistance"),_P=An(Os,"color","AttenuationColor"),$P=An(Os,"float","Dispersion");class c8 extends ar{static get type(){return"UniformGroupNode"}constructor(e,t=!1,n=1){super("string"),this.name=e,this.shared=t,this.order=n,this.isUniformGroup=!0}serialize(e){super.serialize(e),e.name=this.name,e.version=this.version,e.shared=this.shared}deserialize(e){super.deserialize(e),this.name=e.name,this.version=e.version,this.shared=e.shared}}const d8=r=>new c8(r),uE=(r,e=0)=>new c8(r,!0,e),f8=uE("frame"),Rr=uE("render"),e3=d8("object");class mx extends zP{static get type(){return"UniformNode"}constructor(e,t=null){super(e,t),this.isUniformNode=!0,this.name="",this.groupNode=e3}setName(e){return this.name=e,this}label(e){return ze('TSL: "label()" has been deprecated. 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n=r.value;r.traverse(i=>{i.isConstNode===!0&&(n=i.value)}),r=n}return new mx(r,t)};class h8 extends Qa{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 this.nodeType===null?this.values[0].getNodeType(e):this.nodeType}getElementType(e){return this.getNodeType(e)}getMemberType(e,t){return this.nodeType===null?this.values[0].getMemberType(e,t):super.getMemberType(e,t)}generate(e){const t=this.getNodeType(e);return e.generateArray(t,this.count,this.values)}}const p8=(...r)=>{let e;if(r.length===1){const t=r[0];e=new h8(null,t.length,t)}else{const t=r[0],n=r[1];e=new h8(t,n)}return wn(e)};vt("toArray",(r,e)=>p8(Array(e).fill(r)));class JX extends Qa{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 t!=="void"?this.targetNode.getNodeType(e):"void"}needsSplitAssign(e){const{targetNode:t}=this;if(e.isAvailable("swizzleAssign")===!1&&t.isSplitNode&&t.components.length>1){const n=e.getTypeLength(t.node.getNodeType(e));return og.join("").slice(0,n)!==t.components}return!1}setup(e){const{targetNode:t,sourceNode:n}=this,i=t.getScope(),s=e.getDataFromNode(i);s.assign=!0;const a=e.getNodeProperties(this);a.sourceNode=n,a.targetNode=t.context({assign:!0})}generate(e,t){const{targetNode:n,sourceNode:i}=e.getNodeProperties(this),s=this.needsSplitAssign(e),a=n.build(e),o=n.getNodeType(e),l=i.build(e,o),u=i.getNodeType(e),c=e.getDataFromNode(this);let d;if(c.initialized===!0)t!=="void"&&(d=a);else if(s){const f=e.getVarFromNode(this,null,o),h=e.getPropertyName(f);e.addLineFlowCode(`${h} = ${l}`,this);const p=n.node,v=p.node.context({assign:!0}).build(e);for(let m=0;m<p.components.length;m++){const C=p.components[m];e.addLineFlowCode(`${v}.${C} = ${h}[ ${m} ]`,this)}t!=="void"&&(d=a)}else d=`${a} = ${l}`,(t==="void"||u==="void")&&(e.addLineFlowCode(d,this),t!=="void"&&(d=a));return c.initialized=!0,e.format(d,o,t)}}const m8=vi(JX).setParameterLength(2);vt("assign",m8);class KX extends Qa{static get type(){return"FunctionCallNode"}constructor(e=null,t={}){super(),this.functionNode=e,this.parameters=t}setParameters(e){return this.parameters=e,this}getParameters(){return this.parameters}getNodeType(e){return this.functionNode.getNodeType(e)}getMemberType(e,t){return this.functionNode.getMemberType(e,t)}generate(e){const t=[],n=this.functionNode,i=n.getInputs(e),s=this.parameters,a=(l,u)=>{const c=u.type,d=c==="pointer";let f;return d?f="&"+l.build(e):f=l.build(e,c),f};if(Array.isArray(s)){if(s.length>i.length)rt("TSL: The number of provided parameters exceeds the expected number of inputs in 'Fn()'."),s.length=i.length;else if(s.length<i.length)for(rt("TSL: The number of provided parameters is less than the expected number of inputs in 'Fn()'.");s.length<i.length;)s.push(K(0));for(let l=0;l<s.length;l++)t.push(a(s[l],i[l]))}else for(const l of i){const u=s[l.name];u!==void 0?t.push(a(u,l)):(rt(`TSL: Input '${l.name}' not found in 'Fn()'.`),t.push(a(K(0),l)))}return`${n.build(e,"property")}( ${t.join(", ")} )`}}const g8=(r,...e)=>(e=e.length>1||e[0]&&e[0].isNode===!0?ug(e):$b(e[0]),new KX(wn(r),e));vt("call",g8);const qX={"==":"equal","!=":"notEqual","<":"lessThan",">":"greaterThan","<=":"lessThanEqual",">=":"greaterThanEqual","%":"mod"};class Za extends Qa{static get type(){return"OperatorNode"}constructor(e,t,n,...i){if(super(),i.length>0){let s=new Za(e,t,n);for(let a=0;a<i.length-1;a++)s=new Za(e,s,i[a]);t=s,n=i[i.length-1]}this.op=e,this.aNode=t,this.bNode=n,this.isOperatorNode=!0}getOperatorMethod(e,t){return e.getMethod(qX[this.op],t)}getNodeType(e,t=null){const n=this.op,i=this.aNode,s=this.bNode,a=i.getNodeType(e),o=s?s.getNodeType(e):null;if(a==="void"||o==="void")return t||"void";if(n==="%")return a;if(n==="~"||n==="&"||n==="|"||n==="^"||n===">>"||n==="<<")return e.getIntegerType(a);if(n==="!"||n==="&&"||n==="||"||n==="^^")return"bool";if(n==="=="||n==="!="||n==="<"||n===">"||n==="<="||n===">="){const l=Math.max(e.getTypeLength(a),e.getTypeLength(o));return l>1?`bvec${l}`:"bool"}else{if(e.isMatrix(a)){if(o==="float")return a;if(e.isVector(o))return e.getVectorFromMatrix(a);if(e.isMatrix(o))return a}else if(e.isMatrix(o)){if(a==="float")return o;if(e.isVector(a))return e.getVectorFromMatrix(o)}return e.getTypeLength(o)>e.getTypeLength(a)?o:a}}generate(e,t){const n=this.op,{aNode:i,bNode:s}=this,a=this.getNodeType(e,t);let o=null,l=null;a!=="void"?(o=i.getNodeType(e),l=s?s.getNodeType(e):null,n==="<"||n===">"||n==="<="||n===">="||n==="=="||n==="!="?e.isVector(o)?l=o:e.isVector(l)?o=l:o!==l&&(o=l="float"):n===">>"||n==="<<"?(o=a,l=e.changeComponentType(l,"uint")):n==="%"?(o=a,l=e.isInteger(o)&&e.isInteger(l)?l:o):e.isMatrix(o)?l==="float"?l="float":e.isVector(l)?l=e.getVectorFromMatrix(o):e.isMatrix(l)||(o=l=a):e.isMatrix(l)?o==="float"?o="float":e.isVector(o)?o=e.getVectorFromMatrix(l):o=l=a:o=l=a):o=l=a;const u=i.build(e,o),c=s?s.build(e,l):null,d=e.getFunctionOperator(n);if(t!=="void"){const f=e.renderer.coordinateSystem===Gt;if(n==="=="||n==="!="||n==="<"||n===">"||n==="<="||n===">=")return f?e.isVector(o)?e.format(`${this.getOperatorMethod(e,t)}( ${u}, ${c} )`,a,t):e.format(`( ${u} ${n} ${c} )`,a,t):e.format(`( ${u} ${n} ${c} )`,a,t);if(n==="%")return e.isInteger(l)?e.format(`( ${u} % ${c} )`,a,t):e.format(`${this.getOperatorMethod(e,a)}( ${u}, ${c} )`,a,t);if(n==="!"||n==="~")return e.format(`(${n}${u})`,o,t);if(d)return e.format(`${d}( ${u}, ${c} )`,a,t);if(e.isMatrix(o)&&l==="float")return e.format(`( ${c} ${n} ${u} )`,a,t);if(o==="float"&&e.isMatrix(l))return e.format(`${u} ${n} ${c}`,a,t);{let h=`( ${u} ${n} ${c} )`;return!f&&a==="bool"&&e.isVector(o)&&e.isVector(l)&&(h=`all${h}`),e.format(h,a,t)}}else if(o!=="void")return d?e.format(`${d}( ${u}, ${c} )`,a,t):e.isMatrix(o)&&l==="float"?e.format(`${c} ${n} ${u}`,a,t):e.format(`${u} ${n} ${c}`,a,t)}serialize(e){super.serialize(e),e.op=this.op}deserialize(e){super.deserialize(e),this.op=e.op}}const wo=en(Za,"+").setParameterLength(2,1/0).setName("add"),us=en(Za,"-").setParameterLength(2,1/0).setName("sub"),Ai=en(Za,"*").setParameterLength(2,1/0).setName("mul"),rc=en(Za,"/").setParameterLength(2,1/0).setName("div"),gx=en(Za,"%").setParameterLength(2).setName("mod"),t3=en(Za,"==").setParameterLength(2).setName("equal"),v8=en(Za,"!=").setParameterLength(2).setName("notEqual"),A8=en(Za,"<").setParameterLength(2).setName("lessThan"),n3=en(Za,">").setParameterLength(2).setName("greaterThan"),x8=en(Za,"<=").setParameterLength(2).setName("lessThanEqual"),y8=en(Za,">=").setParameterLength(2).setName("greaterThanEqual"),b8=en(Za,"&&").setParameterLength(2,1/0).setName("and"),E8=en(Za,"||").setParameterLength(2,1/0).setName("or"),w8=en(Za,"!").setParameterLength(1).setName("not"),C8=en(Za,"^^").setParameterLength(2).setName("xor"),P8=en(Za,"&").setParameterLength(2).setName("bitAnd"),B8=en(Za,"~").setParameterLength(1).setName("bitNot"),M8=en(Za,"|").setParameterLength(2).setName("bitOr"),S8=en(Za,"^").setParameterLength(2).setName("bitXor"),D8=en(Za,"<<").setParameterLength(2).setName("shiftLeft"),T8=en(Za,">>").setParameterLength(2).setName("shiftRight"),I8=be(([r])=>(r.addAssign(1),r)),N8=be(([r])=>(r.subAssign(1),r)),F8=be(([r])=>{const e=ce(r).toConst();return r.addAssign(1),e}),R8=be(([r])=>{const e=ce(r).toConst();return r.subAssign(1),e});vt("add",wo),vt("sub",us),vt("mul",Ai),vt("div",rc),vt("mod",gx),vt("equal",t3),vt("notEqual",v8),vt("lessThan",A8),vt("greaterThan",n3),vt("lessThanEqual",x8),vt("greaterThanEqual",y8),vt("and",b8),vt("or",E8),vt("not",w8),vt("xor",C8),vt("bitAnd",P8),vt("bitNot",B8),vt("bitOr",M8),vt("bitXor",S8),vt("shiftLeft",D8),vt("shiftRight",T8),vt("incrementBefore",I8),vt("decrementBefore",N8),vt("increment",F8),vt("decrement",R8);const L8=(r,e)=>(ze('TSL: "modInt()" is deprecated. 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Use "equal" inside a vector instead, like: "bvec*( equal( ... ) )"'),t3(r,e)),Pu=en(Ve,Ve.MIN).setParameterLength(2,1/0),Ya=en(Ve,Ve.MAX).setParameterLength(2,1/0),pE=en(Ve,Ve.STEP).setParameterLength(2),J8=en(Ve,Ve.REFLECT).setParameterLength(2),K8=en(Ve,Ve.DISTANCE).setParameterLength(2),q8=en(Ve,Ve.DIFFERENCE).setParameterLength(2),Nc=en(Ve,Ve.DOT).setParameterLength(2),yh=en(Ve,Ve.CROSS).setParameterLength(2),Fc=en(Ve,Ve.POW).setParameterLength(2),h3=r=>Ai(r,r),_8=r=>Ai(r,r,r),p3=r=>Ai(r,r,r,r),$8=en(Ve,Ve.TRANSFORM_DIRECTION).setParameterLength(2),e2=r=>Ai(o3(r),Fc(va(r),1/3)),m3=r=>Nc(r,r),ss=en(Ve,Ve.MIX).setParameterLength(3),Md=(r,e=0,t=1)=>wn(new Ve(Ve.CLAMP,wn(r),wn(e),wn(t))),mE=r=>Md(r),g3=en(Ve,Ve.REFRACT).setParameterLength(3),ic=en(Ve,Ve.SMOOTHSTEP).setParameterLength(3),v3=en(Ve,Ve.FACEFORWARD).setParameterLength(3),t2=be(([r])=>{const n=43758.5453,i=Nc(r.xy,Wt(12.9898,78.233)),s=gx(i,cE);return Pd(ou(s).mul(n))}),n2=(r,e,t)=>ss(e,t,r),r2=(r,e,t)=>ic(e,t,r),i2=(r,e)=>pE(e,r),s2=(r,e)=>(ze('TSL: "atan2" is overloaded. Use "atan" instead.'),hE(r,e)),nG=v3,rG=s3;vt("all",O8),vt("any",z8),vt("equals",Y8),vt("radians",H8),vt("degrees",U8),vt("exp",i3),vt("exp2",hA),vt("log",dE),vt("log2",xf),vt("sqrt",Gl),vt("inverseSqrt",s3),vt("floor",yf),vt("ceil",fE),vt("normalize",au),vt("fract",Pd),vt("sin",ou),vt("cos",Bd),vt("tan",k8),vt("asin",V8),vt("acos",a3),vt("atan",hE),vt("abs",va),vt("sign",o3),vt("length",bf),vt("lengthSq",m3),vt("negate",l3),vt("oneMinus",j8),vt("dFdx",u3),vt("dFdy",c3),vt("round",X8),vt("reciprocal",G8),vt("trunc",d3),vt("fwidth",f3),vt("atan2",s2),vt("min",Pu),vt("max",Ya),vt("step",i2),vt("reflect",J8),vt("distance",K8),vt("dot",Nc),vt("cross",yh),vt("pow",Fc),vt("pow2",h3),vt("pow3",_8),vt("pow4",p3),vt("transformDirection",$8),vt("mix",n2),vt("clamp",Md),vt("refract",g3),vt("smoothstep",r2),vt("faceForward",v3),vt("difference",q8),vt("saturate",mE),vt("cbrt",e2),vt("transpose",W8),vt("determinant",Q8),vt("inverse",Z8),vt("rand",t2);class iG extends ar{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(t===void 0)return e.flowBuildStage(this,"setup"),this.getNodeType(e);const i=t.getNodeType(e);if(n!==null){const s=n.getNodeType(e);if(e.getTypeLength(s)>e.getTypeLength(i))return s}return i}setup(e){const t=this.condNode,n=this.ifNode.isolate(),i=this.elseNode?this.elseNode.isolate():null,s=e.context.nodeBlock;e.getDataFromNode(n).parentNodeBlock=s,i!==null&&(e.getDataFromNode(i).parentNodeBlock=s);const a=e.context.uniformFlow,o=e.getNodeProperties(this);o.condNode=t,o.ifNode=a?n:n.context({nodeBlock:n}),o.elseNode=i?a?i:i.context({nodeBlock:i}):null}generate(e,t){const n=this.getNodeType(e),i=e.getDataFromNode(this);if(i.nodeProperty!==void 0)return i.nodeProperty;const{condNode:s,ifNode:a,elseNode:o}=e.getNodeProperties(this),l=e.currentFunctionNode,u=t!=="void",c=u?Cd(n).build(e):"";i.nodeProperty=c;const d=s.build(e,"bool");if(e.context.uniformFlow&&o!==null){const p=a.build(e,n),x=o.build(e,n),v=e.getTernary(d,p,x);return e.format(v,n,t)}e.addFlowCode(`
${e.tab}if ( ${d} ) {

`).addFlowTab();let h=a.build(e,n);if(h&&(u?h=c+" = "+h+";":(h="return "+h+";",l===null&&(ze("TSL: Return statement used in an inline 'Fn()'. Define a layout struct to allow return values."),h="// "+h))),e.removeFlowTab().addFlowCode(e.tab+"	"+h+`

`+e.tab+"}"),o!==null){e.addFlowCode(` else {

`).addFlowTab();let p=o.build(e,n);p&&(u?p=c+" = "+p+";":(p="return "+p+";",l===null&&(ze("TSL: Return statement used in an inline 'Fn()'. Define a layout struct to allow return values."),p="// "+p))),e.removeFlowTab().addFlowCode(e.tab+"	"+p+`

`+e.tab+`}

`)}else e.addFlowCode(`

`);return e.format(c,n,t)}}const Cl=vi(iG).setParameterLength(2,3);vt("select",Cl);class a2 extends ar{static get type(){return"ContextNode"}constructor(e=null,t={}){super(),this.isContextNode=!0,this.node=e,this.value=t}getScope(){return this.node.getScope()}getNodeType(e){return this.node.getNodeType(e)}getFlowContextData(){const e=[];return this.traverse(t=>{t.isContextNode===!0&&e.push(t.value)}),Object.assign({},...e)}getMemberType(e,t){return this.node.getMemberType(e,t)}analyze(e){const t=e.addContext(this.value);this.node.build(e),e.setContext(t)}setup(e){const t=e.addContext(this.value);this.node.build(e),e.setContext(t)}generate(e,t){const n=e.addContext(this.value),i=this.node.build(e,t);return e.setContext(n),i}}const bh=(r=null,e={})=>{let t=r;return(t===null||t.isNode!==!0)&&(e=t||e,t=null),new a2(t,e)},o2=r=>bh(r,{uniformFlow:!0}),A3=(r,e)=>bh(r,{nodeName:e});function l2(r,e,t=null){return bh(t,{getShadow:({light:n,shadowColorNode:i})=>e===n?i.mul(r):i})}function u2(r,e=null){return bh(e,{getAO:(t,{material:n})=>n.transparent===!0?t:t!==null?t.mul(r):r})}function c2(r,e){return ze('TSL: "label()" has been deprecated. Use "setName()" instead.'),A3(r,e)}vt("context",bh),vt("label",c2),vt("uniformFlow",o2),vt("setName",A3),vt("builtinShadowContext",(r,e,t)=>l2(e,t,r)),vt("builtinAOContext",(r,e)=>u2(e,r));class gE extends ar{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}isIntent(e){return e.getDataFromNode(this).forceDeclaration===!0?!1:this.intent}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)}isAssign(e){return e.getDataFromNode(this).assign}build(...e){const t=e[0];if(this._hasStack(t)===!1&&t.buildStage==="setup"&&(t.context.nodeLoop||t.context.nodeBlock)){let n=!1;if(this.node.isShaderCallNodeInternal&&this.node.shaderNode.getLayout()===null&&t.fnCall&&t.fnCall.shaderNode&&t.getDataFromNode(this.node.shaderNode).hasLoop){const a=t.getDataFromNode(this);a.forceDeclaration=!0,n=!0}const i=t.getBaseStack();n?i.addToStackBefore(this):i.addToStack(this)}return this.isIntent(t)&&this.isAssign(t)!==!0?this.node.build(...e):super.build(...e)}generate(e){const{node:t,name:n,readOnly:i}=this,{renderer:s}=e,a=s.backend.isWebGPUBackend===!0;let o=!1,l=!1;i&&(o=e.isDeterministic(t),l=a?i:o);const u=this.getNodeType(e);if(u=="void")return this.isIntent(e)!==!0&&rt('TSL: ".toVar()" can not be used with void type.'),t.build(e);const c=e.getVectorType(u),d=t.build(e,c),f=e.getVarFromNode(this,n,c,void 0,l),h=e.getPropertyName(f);let p=h;if(l)if(a)p=o?`const ${h}`:`let ${h}`;else{const x=t.getArrayCount(e);p=`const ${e.getVar(f.type,h,x)}`}return e.addLineFlowCode(`${p} = ${d}`,this),h}_hasStack(e){return e.getDataFromNode(this).stack!==void 0}}const x3=vi(gE),d2=(r,e=null)=>x3(r,e).toStack(),f2=(r,e=null)=>x3(r,e,!0).toStack(),h2=r=>x3(r).setIntent(!0).toStack();vt("toVar",d2),vt("toConst",f2),vt("toVarIntent",h2);class sG extends ar{static get type(){return"SubBuild"}constructor(e,t,n=null){super(n),this.node=e,this.name=t,this.isSubBuildNode=!0}getNodeType(e){if(this.nodeType!==null)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 pA=(r,e,t=null)=>wn(new sG(wn(r),e,t));class aG extends ar{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(n===void 0){const i=this.name,s=this.getNodeType(e),a=this.interpolationType,o=this.interpolationSampling;t.varying=n=e.getVaryingFromNode(this,i,s,a,o),t.node=pA(this.node,"VERTEX")}return n.needsInterpolation||(n.needsInterpolation=e.shaderStage==="fragment"),n}setup(e){this.setupVarying(e),e.flowNodeFromShaderStage(ax.VERTEX,this.node)}analyze(e){this.setupVarying(e),e.flowNodeFromShaderStage(ax.VERTEX,this.node)}generate(e){const t=e.getSubBuildProperty("property",e.currentStack),n=e.getNodeProperties(this),i=this.setupVarying(e);if(n[t]===void 0){const s=this.getNodeType(e),a=e.getPropertyName(i,ax.VERTEX);e.flowNodeFromShaderStage(ax.VERTEX,n.node,s,a),n[t]=a}return e.getPropertyName(i)}}const Ef=vi(aG).setParameterLength(1,2),p2=r=>Ef(r);vt("toVarying",Ef),vt("toVertexStage",p2),vt("varying",(...r)=>(ze("TSL: .varying() has been renamed to .toVarying()."),Ef(...r))),vt("vertexStage",(...r)=>(ze("TSL: .vertexStage() has been renamed to .toVertexStage()."),Ef(...r)));const m2=be(([r])=>{const e=r.mul(.9478672986).add(.0521327014).pow(2.4),t=r.mul(.0773993808),n=r.lessThanEqual(.04045);return ss(e,t,n)}).setLayout({name:"sRGBTransferEOTF",type:"vec3",inputs:[{name:"color",type:"vec3"}]}),g2=be(([r])=>{const e=r.pow(.41666).mul(1.055).sub(.055),t=r.mul(12.92),n=r.lessThanEqual(.0031308);return ss(e,t,n)}).setLayout({name:"sRGBTransferOETF",type:"vec3",inputs:[{name:"color",type:"vec3"}]}),y3="WorkingColorSpace",oG="OutputColorSpace";class b3 extends Qa{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===y3?$r.workingColorSpace:t===oG?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 s=t;return $r.enabled===!1||n===i||!n||!i||($r.getTransfer(n)===$n&&(s=Yn(m2(s.rgb),s.a)),$r.getPrimaries(n)!==$r.getPrimaries(i)&&(s=Yn(wl($r._getMatrix(new zi,n,i)).mul(s.rgb),s.a)),$r.getTransfer(i)===$n&&(s=Yn(g2(s.rgb),s.a))),s}}const v2=(r,e)=>wn(new b3(wn(r),y3,e)),vE=(r,e)=>wn(new b3(wn(r),e,y3)),lG=(r,e,t)=>wn(new b3(wn(r),e,t));vt("workingToColorSpace",v2),vt("colorSpaceToWorking",vE);let uG=class extends lg{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 A2 extends ar{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=Bi.OBJECT}setGroup(e){return this.group=e,this}element(e){return new uG(this,wn(e))}setNodeType(e){const t=Dr(null,e);this.group!==null&&t.setGroup(this.group),this.node=t}getNodeType(e){return this.node===null&&(this.updateReference(e),this.updateValue()),this.node.getNodeType(e)}getValueFromReference(e=this.reference){const{properties:t}=this;let n=e[t[0]];for(let i=1;i<t.length;i++)n=n[t[i]];return n}updateReference(e){return this.reference=this.object!==null?this.object:e.object,this.reference}setup(){return this.updateValue(),this.node}update(){this.updateValue()}updateValue(){this.node===null&&this.setNodeType(this.uniformType);const e=this.getValueFromReference();Array.isArray(e)?this.node.array=e:this.node.value=e}}const cG=(r,e,t)=>new A2(r,e,t);class dG extends A2{static get type(){return"RendererReferenceNode"}constructor(e,t,n=null){super(e,t,n),this.renderer=n,this.setGroup(Rr)}updateReference(e){return this.reference=this.renderer!==null?this.renderer:e.renderer,this.reference}}const x2=(r,e,t=null)=>new dG(r,e,t);class fG extends Qa{static get type(){return"ToneMappingNode"}constructor(e,t=b2,n=null){super("vec3"),this._toneMapping=e,this.exposureNode=t,this.colorNode=n}customCacheKey(){return uA(this._toneMapping)}setToneMapping(e){return this._toneMapping=e,this}getToneMapping(){return this._toneMapping}setup(e){const t=this.colorNode||e.context.color,n=this._toneMapping;if(n===Fr)return t;let i=null;const s=e.renderer.library.getToneMappingFunction(n);return s!==null?i=Yn(s(t.rgb,this.exposureNode),t.a):(rt("ToneMappingNode: Unsupported Tone Mapping configuration.",n),i=t),i}}const y2=(r,e,t)=>wn(new fG(r,wn(e),wn(t))),b2=x2("toneMappingExposure","float");vt("toneMapping",(r,e,t)=>y2(e,t,r));const E2=new WeakMap;function w2(r,e){let t=E2.get(r);return t===void 0&&(t=new Gy(r,e),E2.set(r,t)),t}class kp extends zP{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=U,this.instanced=!1,this.attribute=null,this.global=!0,e&&e.isBufferAttribute===!0&&e.itemSize<=4&&(this.attribute=e,this.usage=e.usage,this.instanced=e.isInstancedBufferAttribute)}getHash(e){if(this.bufferStride===0&&this.bufferOffset===0){let t=e.globalCache.getData(this.value);return t===void 0&&(t={node:this},e.globalCache.setData(this.value,t)),t.node.uuid}return this.uuid}getNodeType(e){return this.bufferType===null&&(this.bufferType=e.getTypeFromAttribute(this.attribute)),this.bufferType}setup(e){if(this.attribute!==null)return;const t=this.getNodeType(e),n=e.getTypeLength(t),i=this.value,s=this.bufferStride||n,a=this.bufferOffset;let o;i.isInterleavedBuffer===!0?o=i:i.isBufferAttribute===!0?o=w2(i.array,s):o=w2(i,s);const l=new jm(o,n,a);o.setUsage(this.usage),this.attribute=l,this.attribute.isInstancedBufferAttribute=this.instanced}generate(e){const t=this.getNodeType(e),n=e.getBufferAttributeFromNode(this,t),i=e.getPropertyName(n);let s=null;return e.shaderStage==="vertex"||e.shaderStage==="compute"?(this.name=i,s=i):s=Ef(this).build(e,t),s}getInputType(){return"bufferAttribute"}setUsage(e){return this.usage=e,this.attribute&&this.attribute.isBufferAttribute===!0&&(this.attribute.usage=e),this}setInstanced(e){return this.instanced=e,this}}function AE(r,e=null,t=0,n=0,i=U,s=!1){return e==="mat3"||e===null&&r.itemSize===9?wl(new kp(r,"vec3",9,0).setUsage(i).setInstanced(s),new kp(r,"vec3",9,3).setUsage(i).setInstanced(s),new kp(r,"vec3",9,6).setUsage(i).setInstanced(s)):e==="mat4"||e===null&&r.itemSize===16?Op(new kp(r,"vec4",16,0).setUsage(i).setInstanced(s),new kp(r,"vec4",16,4).setUsage(i).setInstanced(s),new kp(r,"vec4",16,8).setUsage(i).setInstanced(s),new kp(r,"vec4",16,12).setUsage(i).setInstanced(s)):new kp(r,e,t,n)}const E3=(r,e=null,t=0,n=0)=>AE(r,e,t,n),hG=(r,e=null,t=0,n=0)=>AE(r,e,t,n,k),xE=(r,e=null,t=0,n=0)=>AE(r,e,t,n,U,!0),w3=(r,e=null,t=0,n=0)=>AE(r,e,t,n,k,!0);vt("toAttribute",r=>E3(r.value));class pG extends ar{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=Bi.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 ze('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){const n=e.getNodeProperties(this);n.outputComputeNode=t.outputNode,t.outputNode=null}return t}generate(e,t){const{shaderStage:n}=e;if(n==="compute"){const i=this.computeNode.build(e,"void");i!==""&&e.addLineFlowCode(i,this)}else{const s=e.getNodeProperties(this).outputComputeNode;if(s)return s.build(e,t)}}}const C3=(r,e=[64])=>{(e.length===0||e.length>3)&&rt("TSL: compute() workgroupSize must have 1, 2, or 3 elements");for(let t=0;t<e.length;t++){const n=e[t];(typeof n!="number"||n<=0||!Number.isInteger(n))&&rt(`TSL: compute() workgroupSize element at index [ ${t} ] must be a positive integer`)}for(;e.length<3;)e.push(1);return wn(new pG(wn(r),e))},C2=(r,e,t)=>C3(r,t).setCount(e);vt("compute",C2),vt("computeKernel",C3);class mG extends ar{static get type(){return"IsolateNode"}constructor(e,t=!0){super(),this.node=e,this.parent=t,this.isIsolateNode=!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 s=this.node.build(e,...t);return e.setCache(n),s}setParent(e){return this.parent=e,this}getParent(){return this.parent}}const mA=r=>new mG(wn(r));function P2(r,e=!0){return ze('TSL: "cache()" has been deprecated. Use "isolate()" instead.'),mA(r).setParent(e)}vt("cache",P2),vt("isolate",mA);class gG extends ar{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 B2=vi(gG).setParameterLength(2);vt("bypass",B2);class M2 extends ar{static get type(){return"RemapNode"}constructor(e,t,n,i=K(0),s=K(1)){super(),this.node=e,this.inLowNode=t,this.inHighNode=n,this.outLowNode=i,this.outHighNode=s,this.doClamp=!0}setup(){const{node:e,inLowNode:t,inHighNode:n,outLowNode:i,outHighNode:s,doClamp:a}=this;let o=e.sub(t).div(n.sub(t));return a===!0&&(o=o.clamp()),o.mul(s.sub(i)).add(i)}}const S2=vi(M2,null,null,{doClamp:!1}).setParameterLength(3,5),D2=vi(M2).setParameterLength(3,5);vt("remap",S2),vt("remapClamp",D2);class yE extends ar{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(n==="void")e.addLineFlowCode(i,this);else return e.format(i,n,t)}}const Eh=vi(yE).setParameterLength(1,2),T2=r=>(r?Cl(r,Eh("discard")):Eh("discard")).toStack(),vG=()=>Eh("return").toStack();vt("discard",T2);class AG extends Qa{static get type(){return"RenderOutputNode"}constructor(e,t,n){super("vec4"),this.colorNode=e,this._toneMapping=t,this.outputColorSpace=n,this.isRenderOutputNode=!0}setToneMapping(e){return this._toneMapping=e,this}getToneMapping(){return this._toneMapping}setup({context:e}){let t=this.colorNode||e.color;const n=(this._toneMapping!==null?this._toneMapping:e.toneMapping)||Fr,i=(this.outputColorSpace!==null?this.outputColorSpace:e.outputColorSpace)||Ol;return n!==Fr&&(t=t.toneMapping(n)),i!==Ol&&i!==$r.workingColorSpace&&(t=t.workingToColorSpace(i)),t}}const P3=(r,e=null,t=null)=>wn(new AG(wn(r),e,t));vt("renderOutput",P3);class xG extends Qa{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 ---",s="-".repeat(i.length);let a="";return a+="// #"+i+`#
`,a+=e.flow.code.replace(/^\t/mg,"")+`
`,a+="/* ... */ "+n+` /* ... */
`,a+="// #"+s+`#
`,t!==null?t(e,a):zl(a),n}}const I2=(r,e=null)=>wn(new xG(wn(r),e)).toStack();vt("debug",I2);class N2{constructor(){this._renderer=null,this.currentFrame=null}get nodeFrame(){return this._renderer._nodes.nodeFrame}setRenderer(e){return this._renderer=e,this}getRenderer(){return this._renderer}init(){}begin(){}finish(){}inspect(){}computeAsync(){}beginCompute(){}finishCompute(){}beginRender(){}finishRender(){}copyTextureToTexture(){}copyFramebufferToTexture(){}}class yG extends ar{static get type(){return"InspectorNode"}constructor(e,t="",n=null){super(),this.node=e,this.name=t,this.callback=n,this.updateType=Bi.FRAME,this.isInspectorNode=!0}getName(){return this.name||this.node.name}update(e){e.renderer.inspector.inspect(this)}getNodeType(e){return this.node.getNodeType(e)}setup(e){let t=this.node;return e.context.inspector===!0&&this.callback!==null&&(t=this.callback(t)),e.renderer.backend.isWebGPUBackend!==!0&&e.renderer.inspector.constructor!==N2&&rs('TSL: ".toInspector()" is only available with WebGPU.'),t}}function F2(r,e="",t=null){return r=wn(r),r.before(new yG(r,e,t))}vt("toInspector",F2);function bG(r){ze("TSL: AddNodeElement has been removed in favor of tree-shaking. Trying add",r)}class R2 extends ar{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(t===null){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(e.hasGeometryAttribute(t)===!0){const s=e.geometry.getAttribute(t),a=e.getTypeFromAttribute(s),o=e.getAttribute(t,a);return e.shaderStage==="vertex"?e.format(o.name,a,n):Ef(this).build(e,n)}else return ze(`AttributeNode: Vertex attribute "${t}" not found on geometry.`),e.generateConst(n)}serialize(e){super.serialize(e),e.global=this.global,e._attributeName=this._attributeName}deserialize(e){super.deserialize(e),this.global=e.global,this._attributeName=e._attributeName}}const lu=(r,e=null)=>new R2(r,e),Qs=(r=0)=>lu("uv"+(r>0?r:""),"vec2");class EG extends ar{static get type(){return"TextureSizeNode"}constructor(e,t=null){super("uvec2"),this.isTextureSizeNode=!0,this.textureNode=e,this.levelNode=t}generate(e,t){const n=this.textureNode.build(e,"property"),i=this.levelNode===null?"0":this.levelNode.build(e,"int");return e.format(`${e.getMethod("textureDimensions")}( ${n}, ${i} )`,this.getNodeType(e),t)}}const wh=vi(EG).setParameterLength(1,2);class wG extends mx{static get type(){return"MaxMipLevelNode"}constructor(e){super(0),this._textureNode=e,this.updateType=Bi.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&&n.width!==void 0){const{width:i,height:s}=n;this.value=Math.log2(Math.max(i,s))}}}const B3=vi(wG).setParameterLength(1),M3=new yo;class wf extends mx{static get type(){return"TextureNode"}constructor(e=M3,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=Bi.NONE,this.referenceNode=null,this._value=e,this._matrixUniform=null,this._flipYUniform=null,this.setUpdateMatrix(t===null)}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 this.value.isDepthTexture===!0?"float":this.value.type===Ls?"uvec4":this.value.type===Do?"ivec4":"vec4"}getInputType(){return"texture"}getDefaultUV(){return Qs(this.value.channel)}updateReference(){return this.value}getTransformedUV(e){return this._matrixUniform===null&&(this._matrixUniform=Dr(this.value.matrix)),this._matrixUniform.mul(he(e,1)).xy}setUpdateMatrix(e){return this.updateMatrix=e,this}setupUV(e,t){return e.isFlipY()&&(this._flipYUniform===null&&(this._flipYUniform=Dr(!1)),t=t.toVar(),this.sampler?t=this._flipYUniform.select(t.flipY(),t):t=this._flipYUniform.select(t.setY(ce(wh(this,this.levelNode).y).sub(t.y).sub(1)),t)),t}setup(e){const t=e.getNodeProperties(this);t.referenceNode=this.referenceNode;const n=this.value;if(!n||n.isTexture!==!0)throw new Error("THREE.TSL: `texture( value )` function expects a valid instance of THREE.Texture().");const i=be(()=>{let a=this.uvNode;return(a===null||e.context.forceUVContext===!0)&&e.context.getUV&&(a=e.context.getUV(this,e)),a||(a=this.getDefaultUV()),this.updateMatrix===!0&&(a=this.getTransformedUV(a)),a=this.setupUV(e,a),this.updateType=this._matrixUniform!==null||this._flipYUniform!==null?Bi.OBJECT:Bi.NONE,a})();let s=this.levelNode;s===null&&e.context.getTextureLevel&&(s=e.context.getTextureLevel(this)),t.uvNode=i,t.levelNode=s,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,this.sampler===!0?"vec2":"ivec2")}generateOffset(e,t){return t.build(e,"ivec2")}generateSnippet(e,t,n,i,s,a,o,l,u){const c=this.value;let d;return s?d=e.generateTextureBias(c,t,n,s,a,u):l?d=e.generateTextureGrad(c,t,n,l,a,u):o?d=e.generateTextureCompare(c,t,n,o,a,u):this.sampler===!1?d=e.generateTextureLoad(c,t,n,i,a,u):i?d=e.generateTextureLevel(c,t,n,i,a,u):d=e.generateTexture(c,t,n,a,u),d}generate(e,t){const n=this.value,i=e.getNodeProperties(this),s=super.generate(e,"property");if(/^sampler/.test(t))return s+"_sampler";if(e.isReference(t))return s;{const a=e.getDataFromNode(this);let o=a.propertyName;if(o===void 0){const{uvNode:c,levelNode:d,biasNode:f,compareNode:h,depthNode:p,gradNode:x,offsetNode:v}=i,m=this.generateUV(e,c),C=d?d.build(e,"float"):null,w=f?f.build(e,"float"):null,P=p?p.build(e,"int"):null,B=h?h.build(e,"float"):null,S=x?[x[0].build(e,"vec2"),x[1].build(e,"vec2")]:null,I=v?this.generateOffset(e,v):null,N=e.getVarFromNode(this);o=e.getPropertyName(N);const T=this.generateSnippet(e,s,m,C,w,P,B,S,I);e.addLineFlowCode(`${o} = ${T}`,this),a.snippet=T,a.propertyName=o}let l=o;const u=this.getNodeType(e);return e.needsToWorkingColorSpace(n)&&(l=vE(Eh(l,u),n.colorSpace).setup(e).build(e,u)),e.format(l,u,t)}}setSampler(e){return this.sampler=e,this}getSampler(){return this.sampler}uv(e){return ze("TextureNode: .uv() has been renamed. Use .sample() instead."),this.sample(e)}sample(e){const t=this.clone();return t.uvNode=wn(e),t.referenceNode=this.getBase(),wn(t)}load(e){return this.sample(e).setSampler(!1)}blur(e){const t=this.clone();t.biasNode=wn(e).mul(B3(t)),t.referenceNode=this.getBase();const n=t.value;return t.generateMipmaps===!1&&(n&&n.generateMipmaps===!1||n.minFilter===Cs||n.magFilter===Cs)&&(ze("TSL: texture().blur() requires mipmaps and sampling. Use .generateMipmaps=true and .minFilter/.magFilter=THREE.LinearFilter in the Texture."),t.biasNode=null),wn(t)}level(e){const t=this.clone();return t.levelNode=wn(e),t.referenceNode=this.getBase(),wn(t)}size(e){return wh(this,e)}bias(e){const t=this.clone();return t.biasNode=wn(e),t.referenceNode=this.getBase(),wn(t)}getBase(){return this.referenceNode?this.referenceNode.getBase():this}compare(e){const t=this.clone();return t.compareNode=wn(e),t.referenceNode=this.getBase(),wn(t)}grad(e,t){const n=this.clone();return n.gradNode=[wn(e),wn(t)],n.referenceNode=this.getBase(),wn(n)}depth(e){const t=this.clone();return t.depthNode=wn(e),t.referenceNode=this.getBase(),wn(t)}offset(e){const t=this.clone();return t.offsetNode=wn(e),t.referenceNode=this.getBase(),wn(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;t!==null&&(t.value=e.matrix),e.matrixAutoUpdate===!0&&e.updateMatrix();const n=this._flipYUniform;n!==null&&(n.value=e.image instanceof ImageBitmap&&e.flipY===!0||e.isRenderTargetTexture===!0||e.isFramebufferTexture===!0||e.isDepthTexture===!0)}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 CG=vi(wf).setParameterLength(1,4).setName("texture"),Bs=(r=M3,e=null,t=null,n=null)=>{let i;return r&&r.isTextureNode===!0?(i=wn(r.clone()),i.referenceNode=r.getBase(),e!==null&&(i.uvNode=wn(e)),t!==null&&(i.levelNode=wn(t)),n!==null&&(i.biasNode=wn(n))):i=CG(r,e,t,n),i},PG=(r=M3)=>Bs(r),oo=(...r)=>Bs(...r).setSampler(!1),BG=(r,e,t)=>Bs(r,e).level(t),MG=r=>(r.isNode===!0?r:Bs(r)).convert("sampler"),SG=r=>(r.isNode===!0?r:Bs(r)).convert("samplerComparison");class S3 extends mx{static get type(){return"BufferNode"}constructor(e,t,n=0){super(e,t),this.isBufferNode=!0,this.bufferType=t,this.bufferCount=n,this.updateRanges=[]}addUpdateRange(e,t){this.updateRanges.push({start:e,count:t})}clearUpdateRanges(){this.updateRanges.length=0}getElementType(e){return this.getNodeType(e)}getInputType(){return"buffer"}}const vx=(r,e,t)=>new S3(r,e,t);class DG extends lg{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 TG extends S3{static get type(){return"UniformArrayNode"}constructor(e,t=null){super(null),this.array=e,this.elementType=t===null?Ah(e[0]):t,this.paddedType=this.getPaddedType(),this.updateType=Bi.RENDER,this.isArrayBufferNode=!0}getNodeType(){return this.paddedType}getElementType(){return this.elementType}getPaddedType(){const e=this.elementType;let t="vec4";return e==="mat2"?t="mat2":/mat/.test(e)===!0?t="mat4":e.charAt(0)==="i"?t="ivec4":e.charAt(0)==="u"&&(t="uvec4"),t}update(){const{array:e,value:t}=this,n=this.elementType;if(n==="float"||n==="int"||n==="uint")for(let i=0;i<e.length;i++){const s=i*4;t[s]=e[i]}else if(n==="color")for(let i=0;i<e.length;i++){const s=i*4,a=e[i];t[s]=a.r,t[s+1]=a.g,t[s+2]=a.b||0}else if(n==="mat2")for(let i=0;i<e.length;i++){const s=i*4,a=e[i];t[s]=a.elements[0],t[s+1]=a.elements[1],t[s+2]=a.elements[2],t[s+3]=a.elements[3]}else if(n==="mat3")for(let i=0;i<e.length;i++){const s=i*16,a=e[i];t[s]=a.elements[0],t[s+1]=a.elements[1],t[s+2]=a.elements[2],t[s+4]=a.elements[3],t[s+5]=a.elements[4],t[s+6]=a.elements[5],t[s+8]=a.elements[6],t[s+9]=a.elements[7],t[s+10]=a.elements[8],t[s+15]=1}else if(n==="mat4")for(let i=0;i<e.length;i++){const s=i*16,a=e[i];for(let o=0;o<a.elements.length;o++)t[s+o]=a.elements[o]}else for(let i=0;i<e.length;i++){const s=i*4,a=e[i];t[s]=a.x,t[s+1]=a.y,t[s+2]=a.z||0,t[s+3]=a.w||0}}setup(e){const t=this.array.length,n=this.elementType;let i=Float32Array;const s=this.paddedType,a=e.getTypeLength(s);return n.charAt(0)==="i"&&(i=Int32Array),n.charAt(0)==="u"&&(i=Uint32Array),this.value=new i(t*a),this.bufferCount=t,this.bufferType=s,super.setup(e)}element(e){return new DG(this,wn(e))}}const Wl=(r,e)=>new TG(r,e);class IG extends ar{constructor(e){super("float"),this.name=e,this.isBuiltinNode=!0}generate(){return this.name}}const Ch=vi(IG).setParameterLength(1);let Ax,xx;class Ba extends ar{static get type(){return"ScreenNode"}constructor(e){super(),this.scope=e,this._output=null,this.isViewportNode=!0}getNodeType(){return this.scope===Ba.DPR?"float":this.scope===Ba.VIEWPORT?"vec4":"vec2"}getUpdateType(){let e=Bi.NONE;return(this.scope===Ba.SIZE||this.scope===Ba.VIEWPORT||this.scope===Ba.DPR)&&(e=Bi.RENDER),this.updateType=e,e}update({renderer:e}){const t=e.getRenderTarget();this.scope===Ba.VIEWPORT?t!==null?xx.copy(t.viewport):(e.getViewport(xx),xx.multiplyScalar(e.getPixelRatio())):this.scope===Ba.DPR?this._output.value=e.getPixelRatio():t!==null?(Ax.width=t.width,Ax.height=t.height):e.getDrawingBufferSize(Ax)}setup(){const e=this.scope;let t=null;return e===Ba.SIZE?t=Dr(Ax||(Ax=new ct)):e===Ba.VIEWPORT?t=Dr(xx||(xx=new Ei)):e===Ba.DPR?t=Dr(1):t=Wt(gg.div(mg)),this._output=t,t}generate(e){if(this.scope===Ba.COORDINATE){let t=e.getFragCoord();if(e.isFlipY()){const n=e.getNodeProperties(mg).outputNode.build(e);t=`${e.getType("vec2")}( ${t}.x, ${n}.y - ${t}.y )`}return t}return super.generate(e)}}Ba.COORDINATE="coordinate",Ba.VIEWPORT="viewport",Ba.SIZE="size",Ba.UV="uv",Ba.DPR="dpr";const D3=An(Ba,Ba.DPR),Ph=An(Ba,Ba.UV),mg=An(Ba,Ba.SIZE),gg=An(Ba,Ba.COORDINATE),gA=An(Ba,Ba.VIEWPORT),T3=gA.zw,L2=gg.sub(gA.xy),NG=L2.div(T3),FG=be(()=>(ze('TSL: "viewportResolution" is deprecated. Use "screenSize" instead.'),mg),"vec2").once()(),Vp=Dr(0,"uint").setName("u_cameraIndex").setGroup(uE("cameraIndex")).toVarying("v_cameraIndex"),Bh=Dr("float").setName("cameraNear").setGroup(Rr).onRenderUpdate(({camera:r})=>r.near),Mh=Dr("float").setName("cameraFar").setGroup(Rr).onRenderUpdate(({camera:r})=>r.far),uu=be(({camera:r})=>{let e;if(r.isArrayCamera&&r.cameras.length>0){const t=[];for(const i of r.cameras)t.push(i.projectionMatrix);e=Wl(t).setGroup(Rr).setName("cameraProjectionMatrices").element(r.isMultiViewCamera?Ch("gl_ViewID_OVR"):Vp).toConst("cameraProjectionMatrix")}else e=Dr("mat4").setName("cameraProjectionMatrix").setGroup(Rr).onRenderUpdate(({camera:t})=>t.projectionMatrix);return e}).once()(),RG=be(({camera:r})=>{let e;if(r.isArrayCamera&&r.cameras.length>0){const t=[];for(const i of r.cameras)t.push(i.projectionMatrixInverse);e=Wl(t).setGroup(Rr).setName("cameraProjectionMatricesInverse").element(r.isMultiViewCamera?Ch("gl_ViewID_OVR"):Vp).toConst("cameraProjectionMatrixInverse")}else e=Dr("mat4").setName("cameraProjectionMatrixInverse").setGroup(Rr).onRenderUpdate(({camera:t})=>t.projectionMatrixInverse);return e}).once()(),sc=be(({camera:r})=>{let e;if(r.isArrayCamera&&r.cameras.length>0){const t=[];for(const i of r.cameras)t.push(i.matrixWorldInverse);e=Wl(t).setGroup(Rr).setName("cameraViewMatrices").element(r.isMultiViewCamera?Ch("gl_ViewID_OVR"):Vp).toConst("cameraViewMatrix")}else e=Dr("mat4").setName("cameraViewMatrix").setGroup(Rr).onRenderUpdate(({camera:t})=>t.matrixWorldInverse);return e}).once()(),LG=be(({camera:r})=>{let e;if(r.isArrayCamera&&r.cameras.length>0){const t=[];for(const i of r.cameras)t.push(i.matrixWorld);e=Wl(t).setGroup(Rr).setName("cameraWorldMatrices").element(r.isMultiViewCamera?Ch("gl_ViewID_OVR"):Vp).toConst("cameraWorldMatrix")}else e=Dr("mat4").setName("cameraWorldMatrix").setGroup(Rr).onRenderUpdate(({camera:t})=>t.matrixWorld);return e}).once()(),OG=be(({camera:r})=>{let e;if(r.isArrayCamera&&r.cameras.length>0){const t=[];for(const i of r.cameras)t.push(i.normalMatrix);e=Wl(t).setGroup(Rr).setName("cameraNormalMatrices").element(r.isMultiViewCamera?Ch("gl_ViewID_OVR"):Vp).toConst("cameraNormalMatrix")}else e=Dr("mat3").setName("cameraNormalMatrix").setGroup(Rr).onRenderUpdate(({camera:t})=>t.normalMatrix);return e}).once()(),yx=be(({camera:r})=>{let e;if(r.isArrayCamera&&r.cameras.length>0){const t=[];for(let i=0,s=r.cameras.length;i<s;i++)t.push(new J);e=Wl(t).setGroup(Rr).setName("cameraPositions").onRenderUpdate(({camera:i},s)=>{const a=i.cameras,o=s.array;for(let l=0,u=a.length;l<u;l++)o[l].setFromMatrixPosition(a[l].matrixWorld)}).element(r.isMultiViewCamera?Ch("gl_ViewID_OVR"):Vp).toConst("cameraPosition")}else e=Dr(new J).setName("cameraPosition").setGroup(Rr).onRenderUpdate(({camera:t},n)=>n.value.setFromMatrixPosition(t.matrixWorld));return e}).once()(),zG=be(({camera:r})=>{let e;if(r.isArrayCamera&&r.cameras.length>0){const t=[];for(const i of r.cameras)t.push(i.viewport);e=Wl(t,"vec4").setGroup(Rr).setName("cameraViewports").element(Vp).toConst("cameraViewport")}else e=Yn(0,0,mg.x,mg.y).toConst("cameraViewport");return e}).once()(),O2=new yl;class cs extends ar{static get type(){return"Object3DNode"}constructor(e,t=null){super(),this.scope=e,this.object3d=t,this.updateType=Bi.OBJECT,this.uniformNode=new mx(null)}getNodeType(){const e=this.scope;if(e===cs.WORLD_MATRIX)return"mat4";if(e===cs.POSITION||e===cs.VIEW_POSITION||e===cs.DIRECTION||e===cs.SCALE)return"vec3";if(e===cs.RADIUS)return"float"}update(e){const t=this.object3d,n=this.uniformNode,i=this.scope;if(i===cs.WORLD_MATRIX)n.value=t.matrixWorld;else if(i===cs.POSITION)n.value=n.value||new J,n.value.setFromMatrixPosition(t.matrixWorld);else if(i===cs.SCALE)n.value=n.value||new J,n.value.setFromMatrixScale(t.matrixWorld);else if(i===cs.DIRECTION)n.value=n.value||new J,t.getWorldDirection(n.value);else if(i===cs.VIEW_POSITION){const s=e.camera;n.value=n.value||new J,n.value.setFromMatrixPosition(t.matrixWorld),n.value.applyMatrix4(s.matrixWorldInverse)}else if(i===cs.RADIUS){const s=e.object.geometry;s.boundingSphere===null&&s.computeBoundingSphere(),O2.copy(s.boundingSphere).applyMatrix4(t.matrixWorld),n.value=O2.radius}}generate(e){const t=this.scope;return t===cs.WORLD_MATRIX?this.uniformNode.nodeType="mat4":t===cs.POSITION||t===cs.VIEW_POSITION||t===cs.DIRECTION||t===cs.SCALE?this.uniformNode.nodeType="vec3":t===cs.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}}cs.WORLD_MATRIX="worldMatrix",cs.POSITION="position",cs.SCALE="scale",cs.VIEW_POSITION="viewPosition",cs.DIRECTION="direction",cs.RADIUS="radius";const HG=vi(cs,cs.DIRECTION).setParameterLength(1),UG=vi(cs,cs.WORLD_MATRIX).setParameterLength(1),z2=vi(cs,cs.POSITION).setParameterLength(1),kG=vi(cs,cs.SCALE).setParameterLength(1),VG=vi(cs,cs.VIEW_POSITION).setParameterLength(1),jG=vi(cs,cs.RADIUS).setParameterLength(1);class Rc extends cs{static get type(){return"ModelNode"}constructor(e){super(e)}update(e){this.object3d=e.object,super.update(e)}}const XG=An(Rc,Rc.DIRECTION),Lc=An(Rc,Rc.WORLD_MATRIX),GG=An(Rc,Rc.POSITION),WG=An(Rc,Rc.SCALE),QG=An(Rc,Rc.VIEW_POSITION),H2=An(Rc,Rc.RADIUS),U2=Dr(new zi).onObjectUpdate(({object:r},e)=>e.value.getNormalMatrix(r.matrixWorld)),ZG=Dr(new Cr).onObjectUpdate(({object:r},e)=>e.value.copy(r.matrixWorld).invert()),Cf=be(r=>r.context.modelViewMatrix||k2).once()().toVar("modelViewMatrix"),k2=sc.mul(Lc),I3=be(r=>(r.context.isHighPrecisionModelViewMatrix=!0,Dr("mat4").onObjectUpdate(({object:e,camera:t})=>e.modelViewMatrix.multiplyMatrices(t.matrixWorldInverse,e.matrixWorld)))).once()().toVar("highpModelViewMatrix"),N3=be(r=>{const e=r.context.isHighPrecisionModelViewMatrix;return Dr("mat3").onObjectUpdate(({object:t,camera:n})=>(e!==!0&&t.modelViewMatrix.multiplyMatrices(n.matrixWorldInverse,t.matrixWorld),t.normalMatrix.getNormalMatrix(t.modelViewMatrix)))}).once()().toVar("highpModelNormalViewMatrix"),Pl=lu("position","vec3"),Ja=Pl.toVarying("positionLocal"),bE=Pl.toVarying("positionPrevious"),ac=be(r=>Lc.mul(Ja).xyz.toVarying(r.getSubBuildProperty("v_positionWorld")),"vec3").once(["POSITION"])(),F3=be(()=>Ja.transformDirection(Lc).toVarying("v_positionWorldDirection").normalize().toVar("positionWorldDirection"),"vec3").once(["POSITION"])(),po=be(r=>r.context.setupPositionView().toVarying("v_positionView"),"vec3").once(["POSITION"])(),_s=be(r=>{let e;return r.camera.isOrthographicCamera?e=he(0,0,1):e=po.negate().toVarying("v_positionViewDirection").normalize(),e.toVar("positionViewDirection")},"vec3").once(["POSITION"])();class YG extends ar{static get type(){return"FrontFacingNode"}constructor(){super("bool"),this.isFrontFacingNode=!0}generate(e){if(e.shaderStage!=="fragment")return"true";const{material:t}=e;return t.side===Qi?"false":e.getFrontFacing()}}const V2=An(YG),R3=K(V2).mul(2).sub(1),vA=be(([r],{material:e})=>{const t=e.side;return t===Qi?r=r.mul(-1):t===Xs&&(r=r.mul(R3)),r}),EE=lu("normal","vec3"),Bu=be(r=>r.geometry.hasAttribute("normal")===!1?(ze('TSL: Vertex attribute "normal" not found on geometry.'),he(0,1,0)):EE,"vec3").once()().toVar("normalLocal"),j2=po.dFdx().cross(po.dFdy()).normalize().toVar("normalFlat"),AA=be(r=>{let e;return r.material.flatShading===!0?e=j2:e=L3(Bu).toVarying("v_normalViewGeometry").normalize(),e},"vec3").once()().toVar("normalViewGeometry"),X2=be(r=>{let e=AA.transformDirection(sc);return r.material.flatShading!==!0&&(e=e.toVarying("v_normalWorldGeometry")),e.normalize().toVar("normalWorldGeometry")},"vec3").once()(),vs=be(({subBuildFn:r,material:e,context:t})=>{let n;return r==="NORMAL"||r==="VERTEX"?(n=AA,e.flatShading!==!0&&(n=vA(n))):n=t.setupNormal().context({getUV:null}),n},"vec3").once(["NORMAL","VERTEX"])().toVar("normalView"),jp=vs.transformDirection(sc).toVar("normalWorld"),vg=be(({subBuildFn:r,context:e})=>{let t;return r==="NORMAL"||r==="VERTEX"?t=vs:t=e.setupClearcoatNormal().context({getUV:null}),t},"vec3").once(["NORMAL","VERTEX"])().toVar("clearcoatNormalView"),G2=be(([r,e=Lc])=>{const t=wl(e),n=r.div(he(t[0].dot(t[0]),t[1].dot(t[1]),t[2].dot(t[2])));return t.mul(n).xyz}),L3=be(([r],e)=>{const t=e.context.modelNormalViewMatrix;if(t)return t.transformDirection(r);const n=U2.mul(r);return sc.transformDirection(n)}),JG=be(()=>(ze('TSL: "transformedNormalView" is deprecated. Use "normalView" instead.'),vs)).once(["NORMAL","VERTEX"])(),KG=be(()=>(ze('TSL: "transformedNormalWorld" is deprecated. Use "normalWorld" instead.'),jp)).once(["NORMAL","VERTEX"])(),qG=be(()=>(ze('TSL: "transformedClearcoatNormalView" is deprecated. Use "clearcoatNormalView" instead.'),vg)).once(["NORMAL","VERTEX"])(),W2=new bu,O3=new Cr,Q2=Dr(0).onReference(({material:r})=>r).onObjectUpdate(({material:r})=>r.refractionRatio),wE=Dr(1).onReference(({material:r})=>r).onObjectUpdate(function({material:r,scene:e}){return r.envMap?r.envMapIntensity:e.environmentIntensity}),z3=Dr(new Cr).onReference(function(r){return r.material}).onObjectUpdate(function({material:r,scene:e}){const t=e.environment!==null&&r.envMap===null?e.environmentRotation:r.envMapRotation;return t?(W2.copy(t),O3.makeRotationFromEuler(W2)):O3.identity(),O3}),Z2=_s.negate().reflect(vs),Y2=_s.negate().refract(vs,Q2),J2=Z2.transformDirection(sc).toVar("reflectVector"),K2=Y2.transformDirection(sc).toVar("reflectVector"),q2=new km;class _G extends wf{static get type(){return"CubeTextureNode"}constructor(e,t=null,n=null,i=null){super(e,t,n,i),this.isCubeTextureNode=!0}getInputType(){return this.value.isDepthTexture===!0?"cubeDepthTexture":"cubeTexture"}getDefaultUV(){const e=this.value;return e.mapping===ai?J2:e.mapping===ps?K2:(rt('CubeTextureNode: Mapping "%s" not supported.',e.mapping),he(0,0,0))}setUpdateMatrix(){}setupUV(e,t){const n=this.value;return n.isDepthTexture===!0?e.renderer.coordinateSystem===gn?he(t.x,t.y.negate(),t.z):t:((e.renderer.coordinateSystem===gn||!n.isRenderTargetTexture)&&(t=he(t.x.negate(),t.yz)),z3.mul(t))}generateUV(e,t){return t.build(e,this.sampler===!0?"vec3":"ivec3")}}const H3=vi(_G).setParameterLength(1,4).setName("cubeTexture"),cu=(r=q2,e=null,t=null,n=null)=>{let i;return r&&r.isCubeTextureNode===!0?(i=wn(r.clone()),i.referenceNode=r,e!==null&&(i.uvNode=wn(e)),t!==null&&(i.levelNode=wn(t)),n!==null&&(i.biasNode=wn(n))):i=H3(r,e,t,n),i},$G=(r=q2)=>H3(r);class eW extends lg{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 CE extends ar{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=Bi.OBJECT}element(e){return new eW(this,wn(e))}setGroup(e){return this.group=e,this}setName(e){return this.name=e,this}label(e){return ze('TSL: "label()" has been deprecated. Use "setName()" instead.'),this.setName(e)}setNodeType(e){let t=null;this.count!==null?t=vx(null,e,this.count):Array.isArray(this.getValueFromReference())?t=Wl(null,e):e==="texture"?t=Bs(null):e==="cubeTexture"?t=cu(null):t=Dr(null,e),this.group!==null&&t.setGroup(this.group),this.name!==null&&t.setName(this.name),this.node=t}getNodeType(e){return this.node===null&&(this.updateReference(e),this.updateValue()),this.node.getNodeType(e)}getValueFromReference(e=this.reference){const{properties:t}=this;let n=e[t[0]];for(let i=1;i<t.length;i++)n=n[t[i]];return n}updateReference(e){return this.reference=this.object!==null?this.object:e.object,this.reference}setup(){return this.updateValue(),this.node}update(){this.updateValue()}updateValue(){this.node===null&&this.setNodeType(this.uniformType);const e=this.getValueFromReference();Array.isArray(e)?this.node.array=e:this.node.value=e}}const $s=(r,e,t)=>new CE(r,e,t),U3=(r,e,t,n)=>new CE(r,e,n,t);class tW extends CE{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=this.material!==null?this.material:e.material,this.reference}}const Sh=(r,e,t=null)=>new tW(r,e,t),_2=Qs(),nW=po.dFdx(),rW=po.dFdy(),$2=_2.dFdx(),eI=_2.dFdy(),tI=vs,nI=rW.cross(tI),rI=tI.cross(nW),k3=nI.mul($2.x).add(rI.mul(eI.x)),V3=nI.mul($2.y).add(rI.mul(eI.y)),iI=k3.dot(k3).max(V3.dot(V3)),sI=iI.equal(0).select(0,iI.inverseSqrt()),iW=k3.mul(sI).toVar("tangentViewFrame"),sW=V3.mul(sI).toVar("bitangentViewFrame"),PE=lu("tangent","vec4"),bx=PE.xyz.toVar("tangentLocal"),BE=be(({subBuildFn:r,geometry:e,material:t})=>{let n;return r==="VERTEX"||e.hasAttribute("tangent")?n=Cf.mul(Yn(bx,0)).xyz.toVarying("v_tangentView").normalize():n=iW,t.flatShading!==!0&&(n=vA(n)),n},"vec3").once(["NORMAL","VERTEX"])().toVar("tangentView"),aI=BE.transformDirection(sc).toVarying("v_tangentWorld").normalize().toVar("tangentWorld"),ME=be(([r,e],{subBuildFn:t,material:n})=>{let i=r.mul(PE.w).xyz;return t==="NORMAL"&&n.flatShading!==!0&&(i=i.toVarying(e)),i}).once(["NORMAL"]),aW=ME(EE.cross(PE),"v_bitangentGeometry").normalize().toVar("bitangentGeometry"),oW=ME(Bu.cross(bx),"v_bitangentLocal").normalize().toVar("bitangentLocal"),oI=be(({subBuildFn:r,geometry:e,material:t})=>{let n;return r==="VERTEX"||e.hasAttribute("tangent")?n=ME(vs.cross(BE),"v_bitangentView").normalize():n=sW,t.flatShading!==!0&&(n=vA(n)),n},"vec3").once(["NORMAL","VERTEX"])().toVar("bitangentView"),lW=ME(jp.cross(aI),"v_bitangentWorld").normalize().toVar("bitangentWorld"),Ag=wl(BE,oI,vs).toVar("TBNViewMatrix"),lI=_s.mul(Ag),uW=(r,e)=>r.sub(lI.mul(e)),uI=be(()=>{let r=fg.cross(_s);return r=r.cross(fg).normalize(),r=ss(r,vs,Hp.mul(Af.oneMinus()).oneMinus().pow2().pow2()).normalize(),r}).once()(),cI=r=>wn(r).mul(.5).add(.5),cW=r=>wn(r).mul(2).sub(1),j3=r=>he(r,Gl(mE(K(1).sub(Nc(r,r)))));class dW extends Qa{static get type(){return"NormalMapNode"}constructor(e,t=null){super("vec3"),this.node=e,this.scaleNode=t,this.normalMapType=Cc,this.unpackNormalMode=bv}setup({material:e}){const{normalMapType:t,scaleNode:n,unpackNormalMode:i}=this;let s=this.node.mul(2).sub(1);if(t===Cc?i===y0?s=j3(s.xy):i===uC?s=j3(s.yw):i!==bv&&console.error(`THREE.NodeMaterial: Unexpected unpack normal mode: ${i}`):i!==bv&&console.error(`THREE.NodeMaterial: Normal map type '${t}' is not compatible with unpack normal mode '${i}'`),n!==null){let o=n;e.flatShading===!0&&(o=vA(o)),s=he(s.xy.mul(o),s.z)}let a=null;return t===Ay?a=L3(s):t===Cc?a=Ag.mul(s).normalize():(rt(`NodeMaterial: Unsupported normal map type: ${t}`),a=vs),a}}const X3=vi(dW).setParameterLength(1,2),fW=be(({textureNode:r,bumpScale:e})=>{const t=i=>r.isolate().context({getUV:s=>i(s.uvNode||Qs()),forceUVContext:!0}),n=K(t(i=>i));return Wt(K(t(i=>i.add(i.dFdx()))).sub(n),K(t(i=>i.add(i.dFdy()))).sub(n)).mul(e)}),hW=be(r=>{const{surf_pos:e,surf_norm:t,dHdxy:n}=r,i=e.dFdx().normalize(),s=e.dFdy().normalize(),a=t,o=s.cross(a),l=a.cross(i),u=i.dot(o).mul(R3),c=u.sign().mul(n.x.mul(o).add(n.y.mul(l)));return u.abs().mul(t).sub(c).normalize()});class pW extends Qa{static get type(){return"BumpMapNode"}constructor(e,t=null){super("vec3"),this.textureNode=e,this.scaleNode=t}setup(){const e=this.scaleNode!==null?this.scaleNode:1,t=fW({textureNode:this.textureNode,bumpScale:e});return hW({surf_pos:po,surf_norm:vs,dHdxy:t})}}const G3=vi(pW).setParameterLength(1,2),dI=new Map;class yt extends ar{static get type(){return"MaterialNode"}constructor(e){super(),this.scope=e}getCache(e,t){let n=dI.get(e);return n===void 0&&(n=Sh(e,t),dI.set(e,n)),n}getFloat(e){return this.getCache(e,"float")}getColor(e){return this.getCache(e,"color")}getTexture(e){return this.getCache(e==="map"?"map":e+"Map","texture")}setup(e){const t=e.context.material,n=this.scope;let i=null;if(n===yt.COLOR){const s=t.color!==void 0?this.getColor(n):he();t.map&&t.map.isTexture===!0?i=s.mul(this.getTexture("map")):i=s}else if(n===yt.OPACITY){const s=this.getFloat(n);t.alphaMap&&t.alphaMap.isTexture===!0?i=s.mul(this.getTexture("alpha")):i=s}else if(n===yt.SPECULAR_STRENGTH)t.specularMap&&t.specularMap.isTexture===!0?i=this.getTexture("specular").r:i=K(1);else if(n===yt.SPECULAR_INTENSITY){const s=this.getFloat(n);t.specularIntensityMap&&t.specularIntensityMap.isTexture===!0?i=s.mul(this.getTexture(n).a):i=s}else if(n===yt.SPECULAR_COLOR){const s=this.getColor(n);t.specularColorMap&&t.specularColorMap.isTexture===!0?i=s.mul(this.getTexture(n).rgb):i=s}else if(n===yt.ROUGHNESS){const s=this.getFloat(n);t.roughnessMap&&t.roughnessMap.isTexture===!0?i=s.mul(this.getTexture(n).g):i=s}else if(n===yt.METALNESS){const s=this.getFloat(n);t.metalnessMap&&t.metalnessMap.isTexture===!0?i=s.mul(this.getTexture(n).b):i=s}else if(n===yt.EMISSIVE){const s=this.getFloat("emissiveIntensity"),a=this.getColor(n).mul(s);t.emissiveMap&&t.emissiveMap.isTexture===!0?i=a.mul(this.getTexture(n)):i=a}else if(n===yt.NORMAL)t.normalMap?(i=X3(this.getTexture("normal"),this.getCache("normalScale","vec2")),i.normalMapType=t.normalMapType,(t.normalMap.format==Al||t.normalMap.format==rf||t.normalMap.format==_f)&&(i.unpackNormalMode=y0)):t.bumpMap?i=G3(this.getTexture("bump").r,this.getFloat("bumpScale")):i=vs;else if(n===yt.CLEARCOAT){const s=this.getFloat(n);t.clearcoatMap&&t.clearcoatMap.isTexture===!0?i=s.mul(this.getTexture(n).r):i=s}else if(n===yt.CLEARCOAT_ROUGHNESS){const s=this.getFloat(n);t.clearcoatRoughnessMap&&t.clearcoatRoughnessMap.isTexture===!0?i=s.mul(this.getTexture(n).r):i=s}else if(n===yt.CLEARCOAT_NORMAL)t.clearcoatNormalMap?i=X3(this.getTexture(n),this.getCache(n+"Scale","vec2")):i=vs;else if(n===yt.SHEEN){const s=this.getColor("sheenColor").mul(this.getFloat("sheen"));t.sheenColorMap&&t.sheenColorMap.isTexture===!0?i=s.mul(this.getTexture("sheenColor").rgb):i=s}else if(n===yt.SHEEN_ROUGHNESS){const s=this.getFloat(n);t.sheenRoughnessMap&&t.sheenRoughnessMap.isTexture===!0?i=s.mul(this.getTexture(n).a):i=s,i=i.clamp(1e-4,1)}else if(n===yt.ANISOTROPY)if(t.anisotropyMap&&t.anisotropyMap.isTexture===!0){const s=this.getTexture(n);i=tE(xA.x,xA.y,xA.y.negate(),xA.x).mul(s.rg.mul(2).sub(Wt(1)).normalize().mul(s.b))}else i=xA;else if(n===yt.IRIDESCENCE_THICKNESS){const s=$s("1","float",t.iridescenceThicknessRange);if(t.iridescenceThicknessMap){const a=$s("0","float",t.iridescenceThicknessRange);i=s.sub(a).mul(this.getTexture(n).g).add(a)}else i=s}else if(n===yt.TRANSMISSION){const s=this.getFloat(n);t.transmissionMap?i=s.mul(this.getTexture(n).r):i=s}else if(n===yt.THICKNESS){const s=this.getFloat(n);t.thicknessMap?i=s.mul(this.getTexture(n).g):i=s}else if(n===yt.IOR)i=this.getFloat(n);else if(n===yt.LIGHT_MAP)i=this.getTexture(n).rgb.mul(this.getFloat("lightMapIntensity"));else if(n===yt.AO)i=this.getTexture(n).r.sub(1).mul(this.getFloat("aoMapIntensity")).add(1);else if(n===yt.LINE_DASH_OFFSET)i=t.dashOffset?this.getFloat(n):K(0);else{const s=this.getNodeType(e);i=this.getCache(n,s)}return i}}yt.ALPHA_TEST="alphaTest",yt.COLOR="color",yt.OPACITY="opacity",yt.SHININESS="shininess",yt.SPECULAR="specular",yt.SPECULAR_STRENGTH="specularStrength",yt.SPECULAR_INTENSITY="specularIntensity",yt.SPECULAR_COLOR="specularColor",yt.REFLECTIVITY="reflectivity",yt.ROUGHNESS="roughness",yt.METALNESS="metalness",yt.NORMAL="normal",yt.CLEARCOAT="clearcoat",yt.CLEARCOAT_ROUGHNESS="clearcoatRoughness",yt.CLEARCOAT_NORMAL="clearcoatNormal",yt.EMISSIVE="emissive",yt.ROTATION="rotation",yt.SHEEN="sheen",yt.SHEEN_ROUGHNESS="sheenRoughness",yt.ANISOTROPY="anisotropy",yt.IRIDESCENCE="iridescence",yt.IRIDESCENCE_IOR="iridescenceIOR",yt.IRIDESCENCE_THICKNESS="iridescenceThickness",yt.IOR="ior",yt.TRANSMISSION="transmission",yt.THICKNESS="thickness",yt.ATTENUATION_DISTANCE="attenuationDistance",yt.ATTENUATION_COLOR="attenuationColor",yt.LINE_SCALE="scale",yt.LINE_DASH_SIZE="dashSize",yt.LINE_GAP_SIZE="gapSize",yt.LINE_WIDTH="linewidth",yt.LINE_DASH_OFFSET="dashOffset",yt.POINT_SIZE="size",yt.DISPERSION="dispersion",yt.LIGHT_MAP="light",yt.AO="ao";const fI=An(yt,yt.ALPHA_TEST),SE=An(yt,yt.COLOR),hI=An(yt,yt.SHININESS),pI=An(yt,yt.EMISSIVE),DE=An(yt,yt.OPACITY),mI=An(yt,yt.SPECULAR),W3=An(yt,yt.SPECULAR_INTENSITY),gI=An(yt,yt.SPECULAR_COLOR),Ex=An(yt,yt.SPECULAR_STRENGTH),TE=An(yt,yt.REFLECTIVITY),vI=An(yt,yt.ROUGHNESS),AI=An(yt,yt.METALNESS),xI=An(yt,yt.NORMAL),yI=An(yt,yt.CLEARCOAT),bI=An(yt,yt.CLEARCOAT_ROUGHNESS),EI=An(yt,yt.CLEARCOAT_NORMAL),wI=An(yt,yt.ROTATION),CI=An(yt,yt.SHEEN),PI=An(yt,yt.SHEEN_ROUGHNESS),BI=An(yt,yt.ANISOTROPY),MI=An(yt,yt.IRIDESCENCE),SI=An(yt,yt.IRIDESCENCE_IOR),DI=An(yt,yt.IRIDESCENCE_THICKNESS),TI=An(yt,yt.TRANSMISSION),II=An(yt,yt.THICKNESS),NI=An(yt,yt.IOR),FI=An(yt,yt.ATTENUATION_DISTANCE),RI=An(yt,yt.ATTENUATION_COLOR),Q3=An(yt,yt.LINE_SCALE),Z3=An(yt,yt.LINE_DASH_SIZE),Y3=An(yt,yt.LINE_GAP_SIZE),IE=An(yt,yt.LINE_WIDTH),J3=An(yt,yt.LINE_DASH_OFFSET),LI=An(yt,yt.POINT_SIZE),OI=An(yt,yt.DISPERSION),K3=An(yt,yt.LIGHT_MAP),zI=An(yt,yt.AO),xA=Dr(new ct).onReference(function(r){return r.material}).onRenderUpdate(function({material:r}){this.value.set(r.anisotropy*Math.cos(r.anisotropyRotation),r.anisotropy*Math.sin(r.anisotropyRotation))}),HI=be(r=>r.context.setupModelViewProjection(),"vec4").once()().toVarying("v_modelViewProjection");class mW extends lg{static get type(){return"StorageArrayElementNode"}constructor(e,t){super(e,t),this.isStorageArrayElementNode=!0}set storageBufferNode(e){this.node=e}get storageBufferNode(){return this.node}getMemberType(e,t){const n=this.storageBufferNode.structTypeNode;return n?n.getMemberType(e,t):"void"}setup(e){return e.isAvailable("storageBuffer")===!1&&this.node.isPBO===!0&&e.setupPBO(this.node),super.setup(e)}generate(e,t){let n;const i=e.context.assign;if(e.isAvailable("storageBuffer")===!1?this.node.isPBO===!0&&i!==!0&&(this.node.value.isInstancedBufferAttribute||e.shaderStage!=="compute")?n=e.generatePBO(this):n=this.node.build(e):n=super.generate(e),i!==!0){const s=this.getNodeType(e);n=e.format(n,s,t)}return n}}const gW=vi(mW).setParameterLength(2);class vW extends S3{static get type(){return"StorageBufferNode"}constructor(e,t=null,n=0){let i,s=null;t&&t.isStruct?(i="struct",s=t.layout,(e.isStorageBufferAttribute||e.isStorageInstancedBufferAttribute)&&(n=e.count)):t===null&&(e.isStorageBufferAttribute||e.isStorageInstancedBufferAttribute)?(i=TP(e.itemSize),n=e.count):i=t,super(e,i,n),this.isStorageBufferNode=!0,this.structTypeNode=s,this.access=El.READ_WRITE,this.isAtomic=!1,this.isPBO=!1,this._attribute=null,this._varying=null,this.global=!0,e.isStorageBufferAttribute!==!0&&e.isStorageInstancedBufferAttribute!==!0&&(e.isInstancedBufferAttribute?e.isStorageInstancedBufferAttribute=!0:e.isStorageBufferAttribute=!0)}getHash(e){if(this.bufferCount===0){let t=e.globalCache.getData(this.value);return t===void 0&&(t={node:this},e.globalCache.setData(this.value,t)),t.node.uuid}return this.uuid}getInputType(){return this.value.isIndirectStorageBufferAttribute?"indirectStorageBuffer":"storageBuffer"}element(e){return gW(this,e)}setPBO(e){return this.isPBO=e,this}getPBO(){return this.isPBO}setAccess(e){return this.access=e,this}toReadOnly(){return this.setAccess(El.READ_ONLY)}setAtomic(e){return this.isAtomic=e,this}toAtomic(){return this.setAtomic(!0)}getAttributeData(){return this._attribute===null&&(this._attribute=E3(this.value),this._varying=Ef(this._attribute)),{attribute:this._attribute,varying:this._varying}}getNodeType(e){if(this.structTypeNode!==null)return this.structTypeNode.getNodeType(e);if(e.isAvailable("storageBuffer")||e.isAvailable("indirectStorageBuffer"))return super.getNodeType(e);const{attribute:t}=this.getAttributeData();return t.getNodeType(e)}getMemberType(e,t){return this.structTypeNode!==null?this.structTypeNode.getMemberType(e,t):"void"}generate(e){if(this.structTypeNode!==null&&this.structTypeNode.build(e),e.isAvailable("storageBuffer")||e.isAvailable("indirectStorageBuffer"))return super.generate(e);const{attribute:t,varying:n}=this.getAttributeData(),i=n.build(e);return e.registerTransform(i,t),i}}const Dh=(r,e=null,t=0)=>new vW(r,e,t),AW=(r,e,t)=>(ze('TSL: "storageObject()" is deprecated. Use "storage().setPBO( true )" instead.'),Dh(r,e,t).setPBO(!0));class Ra extends ar{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;if(n===Ra.VERTEX)i=e.getVertexIndex();else if(n===Ra.INSTANCE)i=e.getInstanceIndex();else if(n===Ra.DRAW)i=e.getDrawIndex();else if(n===Ra.INVOCATION_LOCAL)i=e.getInvocationLocalIndex();else if(n===Ra.INVOCATION_SUBGROUP)i=e.getInvocationSubgroupIndex();else if(n===Ra.SUBGROUP)i=e.getSubgroupIndex();else throw new Error("THREE.IndexNode: Unknown scope: "+n);let s;return e.shaderStage==="vertex"||e.shaderStage==="compute"?s=i:s=Ef(this).build(e,t),s}}Ra.VERTEX="vertex",Ra.INSTANCE="instance",Ra.SUBGROUP="subgroup",Ra.INVOCATION_LOCAL="invocationLocal",Ra.INVOCATION_SUBGROUP="invocationSubgroup",Ra.DRAW="draw";const UI=An(Ra,Ra.VERTEX),Pf=An(Ra,Ra.INSTANCE),xW=An(Ra,Ra.SUBGROUP),yW=An(Ra,Ra.INVOCATION_SUBGROUP),bW=An(Ra,Ra.INVOCATION_LOCAL),kI=An(Ra,Ra.DRAW);class VI extends ar{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=Bi.FRAME,this.buffer=null,this.bufferColor=null}get isStorageMatrix(){const{instanceMatrix:e}=this;return e&&e.isStorageInstancedBufferAttribute===!0}get isStorageColor(){const{instanceColor:e}=this;return e&&e.isStorageInstancedBufferAttribute===!0}setup(e){const{instanceMatrix:t,instanceColor:n,isStorageMatrix:i,isStorageColor:s}=this,{count:a}=t;let{instanceMatrixNode:o,instanceColorNode:l}=this;if(o===null){if(i)o=Dh(t,"mat4",Math.max(a,1)).element(Pf);else if(a<=1e3)o=vx(t.array,"mat4",Math.max(a,1)).element(Pf);else{const c=new lO(t.array,16,1);this.buffer=c;const d=t.usage===k?w3:xE,f=[d(c,"vec4",16,0),d(c,"vec4",16,4),d(c,"vec4",16,8),d(c,"vec4",16,12)];o=Op(...f)}this.instanceMatrixNode=o}if(n&&l===null){if(s)l=Dh(n,"vec3",Math.max(n.count,1)).element(Pf);else{const c=new gd(n.array,3),d=n.usage===k?w3:xE;this.bufferColor=c,l=he(d(c,"vec3",3,0))}this.instanceColorNode=l}const u=o.mul(Ja).xyz;if(Ja.assign(u),e.hasGeometryAttribute("normal")){const c=G2(Bu,o);Bu.assign(c)}this.instanceColorNode!==null&&tc("vec3","vInstanceColor").assign(this.instanceColorNode)}update(){this.buffer!==null&&this.isStorageMatrix!==!0&&(this.buffer.clearUpdateRanges(),this.buffer.updateRanges.push(...this.instanceMatrix.updateRanges),this.instanceMatrix.usage!==k&&this.instanceMatrix.version!==this.buffer.version&&(this.buffer.version=this.instanceMatrix.version)),this.instanceColor&&this.bufferColor!==null&&this.isStorageColor!==!0&&(this.bufferColor.clearUpdateRanges(),this.bufferColor.updateRanges.push(...this.instanceColor.updateRanges),this.instanceColor.usage!==k&&this.instanceColor.version!==this.bufferColor.version&&(this.bufferColor.version=this.instanceColor.version))}}const EW=vi(VI).setParameterLength(2,3);class wW extends VI{static get type(){return"InstancedMeshNode"}constructor(e){const{count:t,instanceMatrix:n,instanceColor:i}=e;super(t,n,i),this.instancedMesh=e}}const jI=vi(wW).setParameterLength(1);class CW extends ar{static get type(){return"BatchNode"}constructor(e){super("void"),this.batchMesh=e,this.batchingIdNode=null}setup(e){this.batchingIdNode===null&&(e.getDrawIndex()===null?this.batchingIdNode=Pf:this.batchingIdNode=kI);const n=be(([p])=>{const x=ce(wh(oo(this.batchMesh._indirectTexture),0).x).toConst(),v=ce(p).mod(x).toConst(),m=ce(p).div(x).toConst();return oo(this.batchMesh._indirectTexture,Fo(v,m)).x}).setLayout({name:"getIndirectIndex",type:"uint",inputs:[{name:"id",type:"int"}]})(ce(this.batchingIdNode)),i=this.batchMesh._matricesTexture,s=ce(wh(oo(i),0).x).toConst(),a=K(n).mul(4).toInt().toConst(),o=a.mod(s).toConst(),l=a.div(s).toConst(),u=Op(oo(i,Fo(o,l)),oo(i,Fo(o.add(1),l)),oo(i,Fo(o.add(2),l)),oo(i,Fo(o.add(3),l))),c=this.batchMesh._colorsTexture;if(c!==null){const x=be(([v])=>{const m=ce(wh(oo(c),0).x).toConst(),C=v,w=C.mod(m).toConst(),P=C.div(m).toConst();return oo(c,Fo(w,P)).rgb}).setLayout({name:"getBatchingColor",type:"vec3",inputs:[{name:"id",type:"int"}]})(n);tc("vec3","vBatchColor").assign(x)}const d=wl(u);Ja.assign(u.mul(Ja));const f=Bu.div(he(d[0].dot(d[0]),d[1].dot(d[1]),d[2].dot(d[2]))),h=d.mul(f).xyz;Bu.assign(h),e.hasGeometryAttribute("tangent")&&bx.mulAssign(d)}}const XI=vi(CW).setParameterLength(1),GI=new WeakMap;class WI extends ar{static get type(){return"SkinningNode"}constructor(e){super("void"),this.skinnedMesh=e,this.updateType=Bi.OBJECT,this.skinIndexNode=lu("skinIndex","uvec4"),this.skinWeightNode=lu("skinWeight","vec4"),this.bindMatrixNode=$s("bindMatrix","mat4"),this.bindMatrixInverseNode=$s("bindMatrixInverse","mat4"),this.boneMatricesNode=U3("skeleton.boneMatrices","mat4",e.skeleton.bones.length),this.positionNode=Ja,this.toPositionNode=Ja,this.previousBoneMatricesNode=null}getSkinnedPosition(e=this.boneMatricesNode,t=this.positionNode){const{skinIndexNode:n,skinWeightNode:i,bindMatrixNode:s,bindMatrixInverseNode:a}=this,o=e.element(n.x),l=e.element(n.y),u=e.element(n.z),c=e.element(n.w),d=s.mul(t),f=wo(o.mul(i.x).mul(d),l.mul(i.y).mul(d),u.mul(i.z).mul(d),c.mul(i.w).mul(d));return a.mul(f).xyz}getSkinnedNormal(e=this.boneMatricesNode,t=Bu){const{skinIndexNode:n,skinWeightNode:i,bindMatrixNode:s,bindMatrixInverseNode:a}=this,o=e.element(n.x),l=e.element(n.y),u=e.element(n.z),c=e.element(n.w);let d=wo(i.x.mul(o),i.y.mul(l),i.z.mul(u),i.w.mul(c));return d=a.mul(d).mul(s),d.transformDirection(t).xyz}getPreviousSkinnedPosition(e){const t=e.object;return this.previousBoneMatricesNode===null&&(t.skeleton.previousBoneMatrices=new Float32Array(t.skeleton.boneMatrices),this.previousBoneMatricesNode=U3("skeleton.previousBoneMatrices","mat4",t.skeleton.bones.length)),this.getSkinnedPosition(this.previousBoneMatricesNode,bE)}needsPreviousBoneMatrices(e){const t=e.renderer.getMRT();return t&&t.has("velocity")||NP(e.object).useVelocity===!0}setup(e){this.needsPreviousBoneMatrices(e)&&bE.assign(this.getPreviousSkinnedPosition(e));const t=this.getSkinnedPosition();if(this.toPositionNode&&this.toPositionNode.assign(t),e.hasGeometryAttribute("normal")){const n=this.getSkinnedNormal();Bu.assign(n),e.hasGeometryAttribute("tangent")&&bx.assign(n)}return t}generate(e,t){if(t!=="void")return super.generate(e,t)}update(e){const t=e.object&&e.object.skeleton?e.object.skeleton:this.skinnedMesh.skeleton;GI.get(t)!==e.frameId&&(GI.set(t,e.frameId),this.previousBoneMatricesNode!==null&&(t.previousBoneMatrices===null&&(t.previousBoneMatrices=new Float32Array(t.boneMatrices)),t.previousBoneMatrices.set(t.boneMatrices)),t.update())}}const QI=r=>new WI(r),PW=(r,e=null)=>{const t=new WI(r);return t.positionNode=Dh(new gd(r.geometry.getAttribute("position").array,3),"vec3").setPBO(!0).toReadOnly().element(Pf).toVar(),t.skinIndexNode=Dh(new gd(new Uint32Array(r.geometry.getAttribute("skinIndex").array),4),"uvec4").setPBO(!0).toReadOnly().element(Pf).toVar(),t.skinWeightNode=Dh(new gd(r.geometry.getAttribute("skinWeight").array,4),"vec4").setPBO(!0).toReadOnly().element(Pf).toVar(),t.bindMatrixNode=Dr(r.bindMatrix,"mat4"),t.bindMatrixInverseNode=Dr(r.bindMatrixInverse,"mat4"),t.boneMatricesNode=vx(r.skeleton.boneMatrices,"mat4",r.skeleton.bones.length),t.toPositionNode=e,wn(t)};class BW extends ar{static get type(){return"LoopNode"}constructor(e=[]){super("void"),this.params=e}getVarName(e){return String.fromCharCode(105+e)}getProperties(e){const t=e.getNodeProperties(this);if(t.stackNode!==void 0)return t;const n={};for(let o=0,l=this.params.length-1;o<l;o++){const u=this.params[o],c=u.isNode!==!0&&u.name||this.getVarName(o),d=u.isNode!==!0&&u.type||"int";n[c]=Eh(c,d)}const i=e.addStack(),s=this.params[this.params.length-1](n);t.returnsNode=s.context({nodeLoop:s}),t.stackNode=i;const a=this.params[0];if(a.isNode!==!0&&typeof a.update=="function"){const o=be(this.params[0].update)(n);t.updateNode=o.context({nodeLoop:o})}return e.removeStack(),t}setup(e){if(this.getProperties(e),e.fnCall){const t=e.getDataFromNode(e.fnCall.shaderNode);t.hasLoop=!0}}generate(e){const t=this.getProperties(e),n=this.params,i=t.stackNode;for(let a=0,o=n.length-1;a<o;a++){const l=n[a];let u=!1,c=null,d=null,f=null,h=null,p=null,x=null;l.isNode?l.getNodeType(e)==="bool"?(u=!0,h="bool",d=l.build(e,h)):(h="int",f=this.getVarName(a),c="0",d=l.build(e,h),p="<"):(h=l.type||"int",f=l.name||this.getVarName(a),c=l.start,d=l.end,p=l.condition,x=l.update,typeof c=="number"?c=e.generateConst(h,c):c&&c.isNode&&(c=c.build(e,h)),typeof d=="number"?d=e.generateConst(h,d):d&&d.isNode&&(d=d.build(e,h)),c!==void 0&&d===void 0?(c=c+" - 1",d="0",p=">="):d!==void 0&&c===void 0&&(c="0",p="<"),p===void 0&&(Number(c)>Number(d)?p=">=":p="<"));let v;if(u)v=`while ( ${d} )`;else{const m={start:c,end:d},C=m.start,w=m.end;let P;const B=()=>p.includes("<")?"+=":"-=";if(x!=null)switch(typeof x){case"function":P=e.flowStagesNode(t.updateNode,"void").code.replace(/\t|;/g,"");break;case"number":P=f+" "+B()+" "+e.generateConst(h,x);break;case"string":P=f+" "+x;break;default:x.isNode?P=f+" "+B()+" "+x.build(e):(rt("TSL: 'Loop( { update: ... } )' is not a function, string or number."),P="break /* invalid update */")}else h==="int"||h==="uint"?x=p.includes("<")?"++":"--":x=B()+" 1.",P=f+" "+x;const S=e.getVar(h,f)+" = "+C,I=f+" "+p+" "+w;v=`for ( ${S}; ${I}; ${P} )`}e.addFlowCode((a===0?`
`:"")+e.tab+v+` {

`).addFlowTab()}const s=i.build(e,"void");t.returnsNode.build(e,"void"),e.removeFlowTab().addFlowCode(`
`+e.tab+s);for(let a=0,o=this.params.length-1;a<o;a++)e.addFlowCode((a===0?"":e.tab)+`}

`).removeFlowTab();e.addFlowTab()}}const Vs=(...r)=>new BW(ug(r,"int")).toStack(),MW=()=>Eh("continue").toStack(),ZI=()=>Eh("break").toStack(),q3=new WeakMap,oc=new Ei,YI=be(({bufferMap:r,influence:e,stride:t,width:n,depth:i,offset:s})=>{const a=ce(UI).mul(t).add(s),o=a.div(n),l=a.sub(o.mul(n));return oo(r,Fo(l,o)).depth(i).xyz.mul(e)});function SW(r){const e=r.morphAttributes.position!==void 0,t=r.morphAttributes.normal!==void 0,n=r.morphAttributes.color!==void 0,i=r.morphAttributes.position||r.morphAttributes.normal||r.morphAttributes.color,s=i!==void 0?i.length:0;let a=q3.get(r);if(a===void 0||a.count!==s){let m=function(){x.dispose(),q3.delete(r),r.removeEventListener("dispose",m)};a!==void 0&&a.texture.dispose();const o=r.morphAttributes.position||[],l=r.morphAttributes.normal||[],u=r.morphAttributes.color||[];let c=0;e===!0&&(c=1),t===!0&&(c=2),n===!0&&(c=3);let d=r.attributes.position.count*c,f=1;const h=4096;d>h&&(f=Math.ceil(d/h),d=h);const p=new Float32Array(d*f*4*s),x=new Py(p,d,f,s);x.type=ha,x.needsUpdate=!0;const v=c*4;for(let C=0;C<s;C++){const w=o[C],P=l[C],B=u[C],S=d*f*4*C;for(let I=0;I<w.count;I++){const N=I*v;e===!0&&(oc.fromBufferAttribute(w,I),p[S+N+0]=oc.x,p[S+N+1]=oc.y,p[S+N+2]=oc.z,p[S+N+3]=0),t===!0&&(oc.fromBufferAttribute(P,I),p[S+N+4]=oc.x,p[S+N+5]=oc.y,p[S+N+6]=oc.z,p[S+N+7]=0),n===!0&&(oc.fromBufferAttribute(B,I),p[S+N+8]=oc.x,p[S+N+9]=oc.y,p[S+N+10]=oc.z,p[S+N+11]=B.itemSize===4?oc.w:1)}}a={count:s,texture:x,stride:c,size:new ct(d,f)},q3.set(r,a),r.addEventListener("dispose",m)}return a}class DW extends ar{static get type(){return"MorphNode"}constructor(e){super("void"),this.mesh=e,this.morphBaseInfluence=Dr(1),this.updateType=Bi.OBJECT}setup(e){const{geometry:t}=e,n=t.morphAttributes.position!==void 0,i=t.hasAttribute("normal")&&t.morphAttributes.normal!==void 0,s=t.morphAttributes.position||t.morphAttributes.normal||t.morphAttributes.color,a=s!==void 0?s.length:0,{texture:o,stride:l,size:u}=SW(t);n===!0&&Ja.mulAssign(this.morphBaseInfluence),i===!0&&Bu.mulAssign(this.morphBaseInfluence);const c=ce(u.width);Vs(a,({i:d})=>{const f=K(0).toVar();this.mesh.count>1&&this.mesh.morphTexture!==null&&this.mesh.morphTexture!==void 0?f.assign(oo(this.mesh.morphTexture,Fo(ce(d).add(1),ce(Pf))).r):f.assign($s("morphTargetInfluences","float").element(d).toVar()),cr(f.notEqual(0),()=>{n===!0&&Ja.addAssign(YI({bufferMap:o,influence:f,stride:l,width:c,depth:d,offset:ce(0)})),i===!0&&Bu.addAssign(YI({bufferMap:o,influence:f,stride:l,width:c,depth:d,offset:ce(1)}))})})}update(){const e=this.morphBaseInfluence;this.mesh.geometry.morphTargetsRelative?e.value=1:e.value=1-this.mesh.morphTargetInfluences.reduce((t,n)=>t+n,0)}}const JI=vi(DW).setParameterLength(1);class yA extends ar{static get type(){return"LightingNode"}constructor(){super("vec3"),this.isLightingNode=!0}}class TW extends yA{static get type(){return"AONode"}constructor(e=null){super(),this.aoNode=e}setup(e){e.context.ambientOcclusion.mulAssign(this.aoNode)}}class IW extends a2{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=he().toVar("directDiffuse"),i=he().toVar("directSpecular"),s=he().toVar("indirectDiffuse"),a=he().toVar("indirectSpecular"),o={directDiffuse:n,directSpecular:i,indirectDiffuse:s,indirectSpecular:a};return{radiance:he().toVar("radiance"),irradiance:he().toVar("irradiance"),iblIrradiance:he().toVar("iblIrradiance"),ambientOcclusion:K(1).toVar("ambientOcclusion"),reflectedLight:o,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 KI=vi(IW);class NW extends yA{static get type(){return"IrradianceNode"}constructor(e){super(),this.node=e}setup(e){e.context.irradiance.addAssign(this.node)}}const bA=new ct;class NE extends wf{static get type(){return"ViewportTextureNode"}constructor(e=Ph,t=null,n=null){let i=null;n===null?(i=new o1,i.minFilter=tl,n=i):i=n,super(n,e,t),this.generateMipmaps=!1,this.defaultFramebuffer=i,this.isOutputTextureNode=!0,this.updateBeforeType=Bi.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),e===null)return t;if(n.has(e)===!1){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();n===null?t.getDrawingBufferSize(bA):bA.set(n.width,n.height);const i=this.getTextureForReference(n);(i.image.width!==bA.width||i.image.height!==bA.height)&&(i.image.width=bA.width,i.image.height=bA.height,i.needsUpdate=!0);const s=i.generateMipmaps;i.generateMipmaps=this.generateMipmaps,t.copyFramebufferToTexture(i),i.generateMipmaps=s}clone(){const e=new this.constructor(this.uvNode,this.levelNode,this.value);return e.generateMipmaps=this.generateMipmaps,e}}const FW=vi(NE).setParameterLength(0,3),_3=vi(NE,null,null,{generateMipmaps:!0}).setParameterLength(0,3);let FE=null;class RW extends NE{static get type(){return"ViewportDepthTextureNode"}constructor(e=Ph,t=null){FE===null&&(FE=new Vl),super(e,t,FE)}getTextureForReference(){return FE}}const $3=vi(RW).setParameterLength(0,2);class Mu extends ar{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===Mu.DEPTH_BASE?e.getFragDepth():super.generate(e)}setup({camera:e}){const{scope:t}=this,n=this.valueNode;let i=null;if(t===Mu.DEPTH_BASE)n!==null&&(i=qI().assign(n));else if(t===Mu.DEPTH)e.isPerspectiveCamera?i=eB(po.z,Bh,Mh):i=EA(po.z,Bh,Mh);else if(t===Mu.LINEAR_DEPTH)if(n!==null)if(e.isPerspectiveCamera){const s=tB(n,Bh,Mh);i=EA(s,Bh,Mh)}else i=n;else i=EA(po.z,Bh,Mh);return i}}Mu.DEPTH_BASE="depthBase",Mu.DEPTH="depth",Mu.LINEAR_DEPTH="linearDepth";const EA=(r,e,t)=>r.add(e).div(e.sub(t)),LW=(r,e,t)=>e.sub(t).mul(r).sub(e),eB=(r,e,t)=>e.add(r).mul(t).div(t.sub(e).mul(r)),tB=(r,e,t)=>e.mul(t).div(t.sub(e).mul(r).sub(t)),nB=(r,e,t)=>{e=e.max(1e-6).toVar();const n=xf(r.negate().div(e)),i=xf(t.div(e));return n.div(i)},OW=(r,e,t)=>{const n=r.mul(dE(t.div(e)));return K(Math.E).pow(n).mul(e).negate()},qI=vi(Mu,Mu.DEPTH_BASE),rB=An(Mu,Mu.DEPTH),wA=vi(Mu,Mu.LINEAR_DEPTH).setParameterLength(0,1),zW=wA($3());rB.assign=r=>qI(r);class Oc extends ar{static get type(){return"ClippingNode"}constructor(e=Oc.DEFAULT){super(),this.scope=e}setup(e){super.setup(e);const t=e.clippingContext,{intersectionPlanes:n,unionPlanes:i}=t;return this.hardwareClipping=e.material.hardwareClipping,this.scope===Oc.ALPHA_TO_COVERAGE?this.setupAlphaToCoverage(n,i):this.scope===Oc.HARDWARE?this.setupHardwareClipping(i,e):this.setupDefault(n,i)}setupAlphaToCoverage(e,t){return be(()=>{const n=K().toVar("distanceToPlane"),i=K().toVar("distanceToGradient"),s=K(1).toVar("clipOpacity"),a=t.length;if(this.hardwareClipping===!1&&a>0){const l=Wl(t).setGroup(Rr);Vs(a,({i:u})=>{const c=l.element(u);n.assign(po.dot(c.xyz).negate().add(c.w)),i.assign(n.fwidth().div(2)),s.mulAssign(ic(i.negate(),i,n))})}const o=e.length;if(o>0){const l=Wl(e).setGroup(Rr),u=K(1).toVar("intersectionClipOpacity");Vs(o,({i:c})=>{const d=l.element(c);n.assign(po.dot(d.xyz).negate().add(d.w)),i.assign(n.fwidth().div(2)),u.mulAssign(ic(i.negate(),i,n).oneMinus())}),s.mulAssign(u.oneMinus())}Ws.a.mulAssign(s),Ws.a.equal(0).discard()})()}setupDefault(e,t){return be(()=>{const n=t.length;if(this.hardwareClipping===!1&&n>0){const s=Wl(t).setGroup(Rr);Vs(n,({i:a})=>{const o=s.element(a);po.dot(o.xyz).greaterThan(o.w).discard()})}const i=e.length;if(i>0){const s=Wl(e).setGroup(Rr),a=Ic(!0).toVar("clipped");Vs(i,({i:o})=>{const l=s.element(o);a.assign(po.dot(l.xyz).greaterThan(l.w).and(a))}),a.discard()}})()}setupHardwareClipping(e,t){const n=e.length;return t.enableHardwareClipping(n),be(()=>{const i=Wl(e).setGroup(Rr),s=Ch(t.getClipDistance());Vs(n,({i:a})=>{const o=i.element(a),l=po.dot(o.xyz).sub(o.w).negate();s.element(a).assign(l)})})()}}Oc.ALPHA_TO_COVERAGE="alphaToCoverage",Oc.DEFAULT="default",Oc.HARDWARE="hardware";const HW=()=>new Oc,UW=()=>new Oc(Oc.ALPHA_TO_COVERAGE),kW=()=>new Oc(Oc.HARDWARE),VW=.05,_I=be(([r])=>Pd(Ai(1e4,ou(Ai(17,r.x).add(Ai(.1,r.y)))).mul(wo(.1,va(ou(Ai(13,r.y).add(r.x))))))),$I=be(([r])=>_I(Wt(_I(r.xy),r.z))),jW=be(([r])=>{const e=Ya(bf(u3(r.xyz)),bf(c3(r.xyz))),t=K(1).div(K(VW).mul(e)).toVar("pixScale"),n=Wt(hA(yf(xf(t))),hA(fE(xf(t)))),i=Wt($I(yf(n.x.mul(r.xyz))),$I(yf(n.y.mul(r.xyz)))),s=Pd(xf(t)),a=wo(Ai(s.oneMinus(),i.x),Ai(s,i.y)),o=Pu(s,s.oneMinus()),l=he(a.mul(a).div(Ai(2,o).mul(us(1,o))),a.sub(Ai(.5,o)).div(us(1,o)),us(1,us(1,a).mul(us(1,a)).div(Ai(2,o).mul(us(1,o))))),u=a.lessThan(o.oneMinus()).select(a.lessThan(o).select(l.x,l.y),l.z);return Md(u,1e-6,1)}).setLayout({name:"getAlphaHashThreshold",type:"float",inputs:[{name:"position",type:"vec3"}]});class XW extends R2{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),n=e.hasGeometryAttribute(t);let i;return n===!0?i=super.generate(e):i=e.generateConst(this.nodeType,new Ei(1,1,1,1)),i}serialize(e){super.serialize(e),e.index=this.index}deserialize(e){super.deserialize(e),this.index=e.index}}const e4=(r=0)=>new XW(r),t4=be(([r,e])=>Pu(1,r.oneMinus().div(e)).oneMinus()).setLayout({name:"blendBurn",type:"vec3",inputs:[{name:"base",type:"vec3"},{name:"blend",type:"vec3"}]}),n4=be(([r,e])=>Pu(r.div(e.oneMinus()),1)).setLayout({name:"blendDodge",type:"vec3",inputs:[{name:"base",type:"vec3"},{name:"blend",type:"vec3"}]}),r4=be(([r,e])=>r.oneMinus().mul(e.oneMinus()).oneMinus()).setLayout({name:"blendScreen",type:"vec3",inputs:[{name:"base",type:"vec3"},{name:"blend",type:"vec3"}]}),i4=be(([r,e])=>ss(r.mul(2).mul(e),r.oneMinus().mul(2).mul(e.oneMinus()).oneMinus(),pE(.5,r))).setLayout({name:"blendOverlay",type:"vec3",inputs:[{name:"base",type:"vec3"},{name:"blend",type:"vec3"}]}),GW=be(([r,e])=>{const t=e.a.add(r.a.mul(e.a.oneMinus()));return Yn(e.rgb.mul(e.a).add(r.rgb.mul(r.a).mul(e.a.oneMinus())).div(t),t)}).setLayout({name:"blendColor",type:"vec4",inputs:[{name:"base",type:"vec4"},{name:"blend",type:"vec4"}]}),s4=be(([r])=>Yn(r.rgb.mul(r.a),r.a),{color:"vec4",return:"vec4"}),WW=be(([r])=>(cr(r.a.equal(0),()=>Yn(0)),Yn(r.rgb.div(r.a),r.a)),{color:"vec4",return:"vec4"}),QW=(...r)=>(ze('TSL: "burn" has been renamed. Use "blendBurn" instead.'),t4(r)),ZW=(...r)=>(ze('TSL: "dodge" has been renamed. Use "blendDodge" instead.'),n4(r)),YW=(...r)=>(ze('TSL: "screen" has been renamed. Use "blendScreen" instead.'),r4(r)),JW=(...r)=>(ze('TSL: "overlay" has been renamed. Use "blendOverlay" instead.'),i4(r));class Ka extends bl{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,this.contextNode=null,Object.defineProperty(this,"shadowPositionNode",{get:()=>this.receivedShadowPositionNode,set:e=>{ze('NodeMaterial: ".shadowPositionNode" was renamed to ".receivedShadowPositionNode".'),this.receivedShadowPositionNode=e}})}_getNodeChildren(){const e=[];for(const t of Object.getOwnPropertyNames(this)){if(t.startsWith("_")===!0)continue;const n=this[t];n&&n.isNode===!0&&e.push({property:t,childNode:n})}return e}customProgramCacheKey(){const e=[];for(const{property:t,childNode:n}of this._getNodeChildren())e.push(lA(t.slice(0,-4)),n.getCacheKey());return this.type+ag(e)}build(e){this.setup(e)}setupObserver(e){return new xX(e)}setup(e){e.context.setupNormal=()=>pA(this.setupNormal(e),"NORMAL","vec3"),e.context.setupPositionView=()=>this.setupPositionView(e),e.context.setupModelViewProjection=()=>this.setupModelViewProjection(e);const t=e.renderer,n=t.getRenderTarget();t.contextNode.isContextNode===!0?e.context=ba(ba({},e.context),t.contextNode.getFlowContextData()):rt('NodeMaterial: "renderer.contextNode" must be an instance of `context()`.'),this.contextNode!==null&&(this.contextNode.isContextNode===!0?e.context=ba(ba({},e.context),this.contextNode.getFlowContextData()):rt('NodeMaterial: "material.contextNode" must be an instance of `context()`.')),e.addStack();const i=pA(this.setupVertex(e),"VERTEX"),s=this.vertexNode||i;e.stack.outputNode=s,this.setupHardwareClipping(e),this.geometryNode!==null&&(e.stack.outputNode=e.stack.outputNode.bypass(this.geometryNode)),e.addFlow("vertex",e.removeStack()),e.addStack();let a;const o=this.setupClipping(e);if((this.depthWrite===!0||this.depthTest===!0)&&(n!==null?n.depthBuffer===!0&&this.setupDepth(e):t.depth===!0&&this.setupDepth(e)),this.fragmentNode===null){this.setupDiffuseColor(e),this.setupVariants(e);const l=this.setupLighting(e);o!==null&&e.stack.addToStack(o);const u=Yn(l,Ws.a).max(0);a=this.setupOutput(e,u),fA.assign(a);const c=this.outputNode!==null;if(c&&(a=this.outputNode),e.context.getOutput&&(a=e.context.getOutput(a,e)),n!==null){const d=t.getMRT(),f=this.mrtNode;d!==null?(c&&fA.assign(a),a=d,f!==null&&(a=d.merge(f))):f!==null&&(a=f)}}else{let l=this.fragmentNode;l.isOutputStructNode!==!0&&(l=Yn(l)),a=this.setupOutput(e,l)}e.stack.outputNode=a,e.addFlow("fragment",e.removeStack()),e.observer=this.setupObserver(e)}setupClipping(e){if(e.clippingContext===null)return null;const{unionPlanes:t,intersectionPlanes:n}=e.clippingContext;let i=null;if(t.length>0||n.length>0){const s=e.renderer.currentSamples;this.alphaToCoverage&&s>1?i=UW():e.stack.addToStack(HW())}return i}setupHardwareClipping(e){if(this.hardwareClipping=!1,e.clippingContext===null)return;const t=e.clippingContext.unionPlanes.length;t>0&&t<=8&&e.isAvailable("clipDistance")&&(e.stack.addToStack(kW()),this.hardwareClipping=!0)}setupDepth(e){const{renderer:t,camera:n}=e;let i=this.depthNode;if(i===null){const s=t.getMRT();s&&s.has("depth")?i=s.get("depth"):t.logarithmicDepthBuffer===!0&&(n.isPerspectiveCamera?i=nB(po.z,Bh,Mh):i=EA(po.z,Bh,Mh))}i!==null&&rB.assign(i).toStack()}setupPositionView(){return Cf.mul(Ja).xyz}setupModelViewProjection(){return uu.mul(po)}setupVertex(e){return e.addStack(),this.setupPosition(e),e.context.vertex=e.removeStack(),HI}setupPosition(e){const{object:t,geometry:n}=e;if((n.morphAttributes.position||n.morphAttributes.normal||n.morphAttributes.color)&&JI(t).toStack(),t.isSkinnedMesh===!0&&QI(t).toStack(),this.displacementMap){const i=Sh("displacementMap","texture"),s=Sh("displacementScale","float"),a=Sh("displacementBias","float");Ja.addAssign(Bu.normalize().mul(i.x.mul(s).add(a)))}return t.isBatchedMesh&&XI(t).toStack(),t.isInstancedMesh&&t.instanceMatrix&&t.instanceMatrix.isInstancedBufferAttribute===!0&&jI(t).toStack(),this.positionNode!==null&&Ja.assign(pA(this.positionNode,"POSITION","vec3")),Ja}setupDiffuseColor(e){const{object:t,geometry:n}=e;this.maskNode!==null&&Ic(this.maskNode).not().discard();let i=this.colorNode?Yn(this.colorNode):SE;this.vertexColors===!0&&n.hasAttribute("color")&&(i=i.mul(e4())),t.instanceColor&&(i=tc("vec3","vInstanceColor").mul(i)),t.isBatchedMesh&&t._colorsTexture&&(i=tc("vec3","vBatchColor").mul(i)),Ws.assign(i);const s=this.opacityNode?K(this.opacityNode):DE;Ws.a.assign(Ws.a.mul(s));let a=null;(this.alphaTestNode!==null||this.alphaTest>0)&&(a=this.alphaTestNode!==null?K(this.alphaTestNode):fI,this.alphaToCoverage===!0?(Ws.a=ic(a,a.add(f3(Ws.a)),Ws.a),Ws.a.lessThanEqual(0).discard()):Ws.a.lessThanEqual(a).discard()),this.alphaHash===!0&&Ws.a.lessThan(jW(Ja)).discard(),e.isOpaque()&&Ws.a.assign(1)}setupVariants(){}setupOutgoingLight(){return this.lights===!0?he(0):Ws.rgb}setupNormal(){return this.normalNode?he(this.normalNode):xI}setupEnvironment(){let e=null;return this.envNode?e=this.envNode:this.envMap&&(e=this.envMap.isCubeTexture?Sh("envMap","cubeTexture"):Sh("envMap","texture")),e}setupLightMap(e){let t=null;return e.material.lightMap&&(t=new NW(K3)),t}setupLights(e){const t=[],n=this.setupEnvironment(e);n&&n.isLightingNode&&t.push(n);const i=this.setupLightMap(e);i&&i.isLightingNode&&t.push(i);let s=this.aoNode;s===null&&e.material.aoMap&&(s=zI),e.context.getAO&&(s=e.context.getAO(s,e)),s&&t.push(new TW(s));let a=this.lightsNode||e.lightsNode;return t.length>0&&(a=e.renderer.lighting.createNode([...a.getLights(),...t])),a}setupLightingModel(){}setupLighting(e){const{material:t}=e,{backdropNode:n,backdropAlphaNode:i,emissiveNode:s}=this,o=this.lights===!0||this.lightsNode!==null?this.setupLights(e):null;let l=this.setupOutgoingLight(e);if(o&&o.getScope().hasLights){const u=this.setupLightingModel(e)||null;l=KI(o,u,n,i)}else n!==null&&(l=he(i!==null?ss(l,n,i):n));return(s&&s.isNode===!0||t.emissive&&t.emissive.isColor===!0)&&(JP.assign(he(s||pI)),l=l.add(JP)),l}setupFog(e,t){const n=e.fogNode;return n&&(fA.assign(t),t=Yn(n.toVar())),t}setupPremultipliedAlpha(e,t){return s4(t)}setupOutput(e,t){return this.fog===!0&&(t=this.setupFog(e,t)),this.premultipliedAlpha===!0&&(t=this.setupPremultipliedAlpha(e,t)),t}setDefaultValues(e){for(const n in e){const i=e[n];this[n]===void 0&&(this[n]=i,i&&i.clone&&(this[n]=i.clone()))}const t=Object.getOwnPropertyDescriptors(e.constructor.prototype);for(const n in t)Object.getOwnPropertyDescriptor(this.constructor.prototype,n)===void 0&&t[n].get!==void 0&&Object.defineProperty(this.constructor.prototype,n,t[n])}toJSON(e){const t=e===void 0||typeof e=="string";t&&(e={textures:{},images:{},nodes:{}});const n=bl.prototype.toJSON.call(this,e);n.inputNodes={};for(const{property:s,childNode:a}of this._getNodeChildren())n.inputNodes[s]=a.toJSON(e).uuid;function i(s){const a=[];for(const o in s){const l=s[o];delete l.metadata,a.push(l)}return a}if(t){const s=i(e.textures),a=i(e.images),o=i(e.nodes);s.length>0&&(n.textures=s),a.length>0&&(n.images=a),o.length>0&&(n.nodes=o)}return n}copy(e){return this.lightsNode=e.lightsNode,this.envNode=e.envNode,this.aoNode=e.aoNode,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,this.contextNode=e.contextNode,super.copy(e)}}const KW=new kl;class qW extends Ka{static get type(){return"LineBasicNodeMaterial"}constructor(e){super(),this.isLineBasicNodeMaterial=!0,this.setDefaultValues(KW),this.setValues(e)}}const _W=new N1;class $W extends Ka{static get type(){return"LineDashedNodeMaterial"}constructor(e){super(),this.isLineDashedNodeMaterial=!0,this.setDefaultValues(_W),this.dashOffset=0,this.offsetNode=null,this.dashScaleNode=null,this.dashSizeNode=null,this.gapSizeNode=null,this.setValues(e)}setupVariants(){const e=this.offsetNode?K(this.offsetNode):J3,t=this.dashScaleNode?K(this.dashScaleNode):Q3,n=this.dashSizeNode?K(this.dashSizeNode):Z3,i=this.gapSizeNode?K(this.gapSizeNode):Y3;pg.assign(n),hx.assign(i);const s=Ef(lu("lineDistance").mul(t));(e?s.add(e):s).mod(pg.add(hx)).greaterThan(pg).discard()}}let RE=null;class eQ extends NE{static get type(){return"ViewportSharedTextureNode"}constructor(e=Ph,t=null){RE===null&&(RE=new o1),super(e,t,RE)}getTextureForReference(){return RE}updateReference(){return this}}const a4=vi(eQ).setParameterLength(0,2),tQ=new N1;class Pde extends null{static get type(){return"Line2NodeMaterial"}constructor(e={}){super(),this.isLine2NodeMaterial=!0,this.setDefaultValues(tQ),this.useColor=e.vertexColors,this.dashOffset=0,this.lineColorNode=null,this.offsetNode=null,this.dashScaleNode=null,this.dashSizeNode=null,this.gapSizeNode=null,this.blending=NoBlending,this._useDash=e.dashed,this._useAlphaToCoverage=!0,this._useWorldUnits=!1,this.setValues(e)}setup(e){const{renderer:t}=e,n=this._useAlphaToCoverage,i=this.useColor,s=this._useDash,a=this._useWorldUnits,o=be(({start:u,end:c})=>{const d=uu.element(2).element(2),p=uu.element(3).element(2).mul(-.5).div(d).sub(u.z).div(c.z.sub(u.z));return Yn(ss(u.xyz,c.xyz,p),c.w)}).setLayout({name:"trimSegment",type:"vec4",inputs:[{name:"start",type:"vec4"},{name:"end",type:"vec4"}]});this.vertexNode=be(()=>{const u=lu("instanceStart"),c=lu("instanceEnd"),d=Yn(Cf.mul(Yn(u,1))).toVar("start"),f=Yn(Cf.mul(Yn(c,1))).toVar("end");if(s){const B=this.dashScaleNode?K(this.dashScaleNode):Q3,S=this.offsetNode?K(this.offsetNode):J3,I=lu("instanceDistanceStart"),N=lu("instanceDistanceEnd");let T=Pl.y.lessThan(.5).select(B.mul(I),B.mul(N));T=T.add(S),tc("float","lineDistance").assign(T)}a&&(tc("vec3","worldStart").assign(d.xyz),tc("vec3","worldEnd").assign(f.xyz));const h=gA.z.div(gA.w),p=uu.element(2).element(3).equal(-1);cr(p,()=>{cr(d.z.lessThan(0).and(f.z.greaterThan(0)),()=>{f.assign(o({start:d,end:f}))}).ElseIf(f.z.lessThan(0).and(d.z.greaterThanEqual(0)),()=>{d.assign(o({start:f,end:d}))})});const x=uu.mul(d),v=uu.mul(f),m=x.xyz.div(x.w),C=v.xyz.div(v.w),w=C.xy.sub(m.xy).toVar();w.x.assign(w.x.mul(h)),w.assign(w.normalize());const P=Yn().toVar();if(a){const B=f.xyz.sub(d.xyz).normalize(),S=ss(d.xyz,f.xyz,.5).normalize(),I=B.cross(S).normalize(),N=B.cross(I),T=tc("vec4","worldPos");T.assign(Pl.y.lessThan(.5).select(d,f));const R=IE.mul(.5);T.addAssign(Yn(Pl.x.lessThan(0).select(I.mul(R),I.mul(R).negate()),0)),s||(T.addAssign(Yn(Pl.y.lessThan(.5).select(B.mul(R).negate(),B.mul(R)),0)),T.addAssign(Yn(N.mul(R),0)),cr(Pl.y.greaterThan(1).or(Pl.y.lessThan(0)),()=>{T.subAssign(Yn(N.mul(2).mul(R),0))})),P.assign(uu.mul(T));const D=he().toVar();D.assign(Pl.y.lessThan(.5).select(m,C)),P.z.assign(D.z.mul(P.w))}else{const B=Wt(w.y,w.x.negate()).toVar("offset");w.x.assign(w.x.div(h)),B.x.assign(B.x.div(h)),B.assign(Pl.x.lessThan(0).select(B.negate(),B)),cr(Pl.y.lessThan(0),()=>{B.assign(B.sub(w))}).ElseIf(Pl.y.greaterThan(1),()=>{B.assign(B.add(w))}),B.assign(B.mul(IE)),B.assign(B.div(gA.w.div(D3))),P.assign(Pl.y.lessThan(.5).select(x,v)),B.assign(B.mul(P.w)),P.assign(P.add(Yn(B,0,0)))}return P})();const l=be(({p1:u,p2:c,p3:d,p4:f})=>{const h=u.sub(d),p=f.sub(d),x=c.sub(u),v=h.dot(p),m=p.dot(x),C=h.dot(x),w=p.dot(p),B=x.dot(x).mul(w).sub(m.mul(m)),I=v.mul(m).sub(C.mul(w)).div(B).clamp(),N=v.add(m.mul(I)).div(w).clamp();return Wt(I,N)});if(this.colorNode=be(()=>{const u=Qs();if(s){const f=this.dashSizeNode?K(this.dashSizeNode):Z3,h=this.gapSizeNode?K(this.gapSizeNode):Y3;pg.assign(f),hx.assign(h);const p=tc("float","lineDistance");u.y.lessThan(-1).or(u.y.greaterThan(1)).discard(),p.mod(pg.add(hx)).greaterThan(pg).discard()}const c=K(1).toVar("alpha");if(a){const f=tc("vec3","worldStart"),h=tc("vec3","worldEnd"),p=tc("vec4","worldPos").xyz.normalize().mul(1e5),x=h.sub(f),v=l({p1:f,p2:h,p3:he(0,0,0),p4:p}),m=f.add(x.mul(v.x)),C=p.mul(v.y),B=m.sub(C).length().div(IE);if(!s)if(n&&t.currentSamples>0){const S=B.fwidth();c.assign(ic(S.negate().add(.5),S.add(.5),B).oneMinus())}else B.greaterThan(.5).discard()}else if(n&&t.currentSamples>0){const f=u.x,h=u.y.greaterThan(0).select(u.y.sub(1),u.y.add(1)),p=f.mul(f).add(h.mul(h)),x=K(p.fwidth()).toVar("dlen");cr(u.y.abs().greaterThan(1),()=>{c.assign(ic(x.oneMinus(),x.add(1),p).oneMinus())})}else cr(u.y.abs().greaterThan(1),()=>{const f=u.x,h=u.y.greaterThan(0).select(u.y.sub(1),u.y.add(1));f.mul(f).add(h.mul(h)).greaterThan(1).discard()});let d;if(this.lineColorNode)d=this.lineColorNode;else if(i){const f=lu("instanceColorStart"),h=lu("instanceColorEnd");d=Pl.y.lessThan(.5).select(f,h).mul(SE)}else d=SE;return Yn(d,c)})(),this.transparent){const u=this.opacityNode?K(this.opacityNode):DE;this.outputNode=Yn(this.colorNode.rgb.mul(u).add(a4().rgb.mul(u.oneMinus())),this.colorNode.a)}super.setup(e)}get worldUnits(){return this._useWorldUnits}set worldUnits(e){this._useWorldUnits!==e&&(this._useWorldUnits=e,this.needsUpdate=!0)}get dashed(){return this._useDash}set dashed(e){this._useDash!==e&&(this._useDash=e,this.needsUpdate=!0)}get alphaToCoverage(){return this._useAlphaToCoverage}set alphaToCoverage(e){this._useAlphaToCoverage!==e&&(this._useAlphaToCoverage=e,this.needsUpdate=!0)}}const nQ=new N5;class rQ extends Ka{static get type(){return"MeshNormalNodeMaterial"}constructor(e){super(),this.isMeshNormalNodeMaterial=!0,this.setDefaultValues(nQ),this.setValues(e)}setupDiffuseColor(){const e=this.opacityNode?K(this.opacityNode):DE;Ws.assign(vE(Yn(cI(vs),e),nl))}}const iB=be(([r=F3])=>{const e=r.z.atan(r.x).mul(1/(Math.PI*2)).add(.5),t=r.y.clamp(-1,1).asin().mul(1/Math.PI).add(.5);return Wt(e,t)});class o4 extends ZC{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 s=new Dp(5,5,5),a=iB(F3),o=new Ka;o.colorNode=Bs(t,a,0),o.side=Qi,o.blending=Xa;const l=new Gs(s,o),u=new R0;u.add(l),t.minFilter===tl&&(t.minFilter=ms);const c=new jS(1,10,this),d=e.getMRT();return e.setMRT(null),c.update(e,u),e.setMRT(d),t.minFilter=n,t.currentGenerateMipmaps=i,l.geometry.dispose(),l.material.dispose(),this}}const wx=new WeakMap;class iQ extends Qa{static get type(){return"CubeMapNode"}constructor(e){super("vec3"),this.envNode=e,this._cubeTexture=null,this._cubeTextureNode=cu(null);const t=new km;t.isRenderTargetTexture=!0,this._defaultTexture=t,this.updateBeforeType=Bi.RENDER}updateBefore(e){const{renderer:t,material:n}=e,i=this.envNode;if(i.isTextureNode||i.isMaterialReferenceNode){const s=i.isTextureNode?i.value:n[i.property];if(s&&s.isTexture){const a=s.mapping;if(a===Pa||a===ld){if(wx.has(s)){const o=wx.get(s);u4(o,s.mapping),this._cubeTexture=o}else{const o=s.image;if(sQ(o)){const l=new o4(o.height);l.fromEquirectangularTexture(t,s),u4(l.texture,s.mapping),this._cubeTexture=l.texture,wx.set(s,l.texture),s.addEventListener("dispose",l4)}else this._cubeTexture=this._defaultTexture}this._cubeTextureNode.value=this._cubeTexture}else this._cubeTextureNode=this.envNode}}}setup(e){return this.updateBefore(e),this._cubeTextureNode}}function sQ(r){return r==null?!1:r.height>0}function l4(r){const e=r.target;e.removeEventListener("dispose",l4);const t=wx.get(e);t!==void 0&&(wx.delete(e),t.dispose())}function u4(r,e){e===Pa?r.mapping=ai:e===ld&&(r.mapping=ps)}const c4=vi(iQ).setParameterLength(1);class sB extends yA{static get type(){return"BasicEnvironmentNode"}constructor(e=null){super(),this.envNode=e}setup(e){e.context.environment=c4(this.envNode)}}class aQ extends yA{static get type(){return"BasicLightMapNode"}constructor(e=null){super(),this.lightMapNode=e}setup(e){const t=K(1/Math.PI);e.context.irradianceLightMap=this.lightMapNode.mul(t)}}class LE{start(e){e.lightsNode.setupLights(e,e.lightsNode.getLightNodes(e)),this.indirect(e)}finish(){}direct(){}directRectArea(){}indirect(){}ambientOcclusion(){}}class d4 extends LE{constructor(){super()}indirect({context:e}){const t=e.ambientOcclusion,n=e.reflectedLight,i=e.irradianceLightMap;n.indirectDiffuse.assign(Yn(0)),i?n.indirectDiffuse.addAssign(i):n.indirectDiffuse.addAssign(Yn(1,1,1,0)),n.indirectDiffuse.mulAssign(t),n.indirectDiffuse.mulAssign(Ws.rgb)}finish(e){const{material:t,context:n}=e,i=n.outgoingLight,s=e.context.environment;if(s)switch(t.combine){case Zd:i.rgb.assign(ss(i.rgb,i.rgb.mul(s.rgb),Ex.mul(TE)));break;case Kh:i.rgb.assign(ss(i.rgb,s.rgb,Ex.mul(TE)));break;case Pm:i.rgb.addAssign(s.rgb.mul(Ex.mul(TE)));break;default:ze("BasicLightingModel: Unsupported .combine value:",t.combine);break}}}const oQ=new rl;class lQ extends Ka{static get type(){return"MeshBasicNodeMaterial"}constructor(e){super(),this.isMeshBasicNodeMaterial=!0,this.lights=!0,this.setDefaultValues(oQ),this.setValues(e)}setupNormal(){return vA(AA)}setupEnvironment(e){const t=super.setupEnvironment(e);return t?new sB(t):null}setupLightMap(e){let t=null;return e.material.lightMap&&(t=new aQ(K3)),t}setupOutgoingLight(){return Ws.rgb}setupLightingModel(){return new d4}}const CA=be(({f0:r,f90:e,dotVH:t})=>{const n=t.mul(-5.55473).sub(6.98316).mul(t).exp2();return r.mul(n.oneMinus()).add(e.mul(n))}),xg=be(r=>r.diffuseColor.mul(1/Math.PI)),uQ=()=>K(.25),cQ=be(({dotNH:r})=>oE.mul(K(.5)).add(1).mul(K(1/Math.PI)).mul(r.pow(oE))),dQ=be(({lightDirection:r})=>{const e=r.add(_s).normalize(),t=vs.dot(e).clamp(),n=_s.dot(e).clamp(),i=CA({f0:Up,f90:1,dotVH:n}),s=uQ(),a=cQ({dotNH:t});return i.mul(s).mul(a)});class f4 extends d4{constructor(e=!0){super(),this.specular=e}direct({lightDirection:e,lightColor:t,reflectedLight:n}){const s=vs.dot(e).clamp().mul(t);n.directDiffuse.addAssign(s.mul(xg({diffuseColor:Ws.rgb}))),this.specular===!0&&n.directSpecular.addAssign(s.mul(dQ({lightDirection:e})).mul(Ex))}indirect(e){const{ambientOcclusion:t,irradiance:n,reflectedLight:i}=e.context;i.indirectDiffuse.addAssign(n.mul(xg({diffuseColor:Ws}))),i.indirectDiffuse.mulAssign(t)}}const fQ=new I1;class hQ extends Ka{static get type(){return"MeshLambertNodeMaterial"}constructor(e){super(),this.isMeshLambertNodeMaterial=!0,this.lights=!0,this.setDefaultValues(fQ),this.setValues(e)}setupEnvironment(e){const t=super.setupEnvironment(e);return t?new sB(t):null}setupLightingModel(){return new f4(!1)}}const pQ=new T1;class mQ extends Ka{static get type(){return"MeshPhongNodeMaterial"}constructor(e){super(),this.isMeshPhongNodeMaterial=!0,this.lights=!0,this.shininessNode=null,this.specularNode=null,this.setDefaultValues(pQ),this.setValues(e)}setupEnvironment(e){const t=super.setupEnvironment(e);return t?new sB(t):null}setupLightingModel(){return new f4}setupVariants(){const e=(this.shininessNode?K(this.shininessNode):hI).max(1e-4);oE.assign(e);const t=this.specularNode||mI;Up.assign(t)}copy(e){return this.shininessNode=e.shininessNode,this.specularNode=e.specularNode,super.copy(e)}}const h4=be(r=>{if(r.geometry.hasAttribute("normal")===!1)return K(0);const e=AA.dFdx().abs().max(AA.dFdy().abs());return e.x.max(e.y).max(e.z)}),aB=be(r=>{const{roughness:e}=r,t=h4();let n=e.max(.0525);return n=n.add(t),n=n.min(1),n}),p4=be(({alpha:r,dotNL:e,dotNV:t})=>{const n=r.pow2(),i=e.mul(n.add(n.oneMinus().mul(t.pow2())).sqrt()),s=t.mul(n.add(n.oneMinus().mul(e.pow2())).sqrt());return rc(.5,i.add(s).max(r3))}).setLayout({name:"V_GGX_SmithCorrelated",type:"float",inputs:[{name:"alpha",type:"float"},{name:"dotNL",type:"float"},{name:"dotNV",type:"float"}]}),gQ=be(({alphaT:r,alphaB:e,dotTV:t,dotBV:n,dotTL:i,dotBL:s,dotNV:a,dotNL:o})=>{const l=o.mul(he(r.mul(t),e.mul(n),a).length()),u=a.mul(he(r.mul(i),e.mul(s),o).length());return rc(.5,l.add(u))}).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"}]}),m4=be(({alpha:r,dotNH:e})=>{const t=r.pow2(),n=e.pow2().mul(t.oneMinus()).oneMinus();return t.div(n.pow2()).mul(1/Math.PI)}).setLayout({name:"D_GGX",type:"float",inputs:[{name:"alpha",type:"float"},{name:"dotNH",type:"float"}]}),vQ=K(1/Math.PI),AQ=be(({alphaT:r,alphaB:e,dotNH:t,dotTH:n,dotBH:i})=>{const s=r.mul(e),a=he(e.mul(n),r.mul(i),s.mul(t)),o=a.dot(a),l=s.div(o);return vQ.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"}]}),oB=be(({lightDirection:r,f0:e,f90:t,roughness:n,f:i,normalView:s=vs,USE_IRIDESCENCE:a,USE_ANISOTROPY:o})=>{const l=n.pow2(),u=r.add(_s).normalize(),c=s.dot(r).clamp(),d=s.dot(_s).clamp(),f=s.dot(u).clamp(),h=_s.dot(u).clamp();let p=CA({f0:e,f90:t,dotVH:h}),x,v;if(lx(a)&&(p=rE.mix(p,i)),lx(o)){const m=fx.dot(r),C=fx.dot(_s),w=fx.dot(u),P=fg.dot(r),B=fg.dot(_s),S=fg.dot(u);x=gQ({alphaT:aE,alphaB:l,dotTV:C,dotBV:B,dotTL:m,dotBL:P,dotNV:d,dotNL:c}),v=AQ({alphaT:aE,alphaB:l,dotNH:f,dotTH:w,dotBH:S})}else x=p4({alpha:l,dotNL:c,dotNV:d}),v=m4({alpha:l,dotNH:f});return p.mul(x).mul(v)}),xQ=new 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Bf=null;const Cx=be(({roughness:r,dotNV:e})=>{Bf===null&&(Bf=new Sc(xQ,16,16,Al,pa),Bf.name="DFG_LUT",Bf.minFilter=ms,Bf.magFilter=ms,Bf.wrapS=So,Bf.wrapT=So,Bf.generateMipmaps=!1,Bf.needsUpdate=!0);const t=Wt(r,e);return Bs(Bf,t).rg}),yQ=be(({lightDirection:r,f0:e,f90:t,roughness:n,f:i,USE_IRIDESCENCE:s,USE_ANISOTROPY:a})=>{const o=oB({lightDirection:r,f0:e,f90:t,roughness:n,f:i,USE_IRIDESCENCE:s,USE_ANISOTROPY:a}),l=vs.dot(r).clamp(),u=vs.dot(_s).clamp(),c=Cx({roughness:n,dotNV:u}),d=Cx({roughness:n,dotNV:l}),f=e.mul(c.x).add(t.mul(c.y)),h=e.mul(d.x).add(t.mul(d.y)),p=c.x.add(c.y),x=d.x.add(d.y),v=K(1).sub(p),m=K(1).sub(x),C=e.add(e.oneMinus().mul(.047619)),w=f.mul(h).mul(C).div(K(1).sub(v.mul(m).mul(C).mul(C)).add(r3)),P=v.mul(m),B=w.mul(P);return o.add(B)}),g4=be(r=>{const{dotNV:e,specularColor:t,specularF90:n,roughness:i}=r,s=Cx({dotNV:e,roughness:i});return t.mul(s.x).add(n.mul(s.y))}),lB=be(({f:r,f90:e,dotVH:t})=>{const n=t.oneMinus().saturate(),i=n.mul(n),s=n.mul(i,i).clamp(0,.9999);return r.sub(he(e).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"}]}),bQ=be(({roughness:r,dotNH:e})=>{const t=r.pow2(),n=K(1).div(t),s=e.pow2().oneMinus().max(.0078125);return K(2).add(n).mul(s.pow(n.mul(.5))).div(2*Math.PI)}).setLayout({name:"D_Charlie",type:"float",inputs:[{name:"roughness",type:"float"},{name:"dotNH",type:"float"}]}),EQ=be(({dotNV:r,dotNL:e})=>K(1).div(K(4).mul(e.add(r).sub(e.mul(r))))).setLayout({name:"V_Neubelt",type:"float",inputs:[{name:"dotNV",type:"float"},{name:"dotNL",type:"float"}]}),wQ=be(({lightDirection:r})=>{const e=r.add(_s).normalize(),t=vs.dot(r).clamp(),n=vs.dot(_s).clamp(),i=vs.dot(e).clamp(),s=bQ({roughness:zp,dotNH:i}),a=EQ({dotNV:n,dotNL:t});return nc.mul(s).mul(a)}),CQ=be(({N:r,V:e,roughness:t})=>{const s=.0078125,a=r.dot(e).saturate(),o=Wt(t,a.oneMinus().sqrt());return o.assign(o.mul(.984375).add(s)),o}).setLayout({name:"LTC_Uv",type:"vec2",inputs:[{name:"N",type:"vec3"},{name:"V",type:"vec3"},{name:"roughness",type:"float"}]}),v4=be(({f:r})=>{const e=r.length();return Ya(e.mul(e).add(r.z).div(e.add(1)),0)}).setLayout({name:"LTC_ClippedSphereFormFactor",type:"float",inputs:[{name:"f",type:"vec3"}]}),Xp=be(({v1:r,v2:e})=>{const t=r.dot(e),n=t.abs().toVar(),i=n.mul(.0145206).add(.4965155).mul(n).add(.8543985).toVar(),s=n.add(4.1616724).mul(n).add(3.417594).toVar(),a=i.div(s),o=t.greaterThan(0).select(a,Ya(t.mul(t).oneMinus(),1e-7).inverseSqrt().mul(.5).sub(a));return r.cross(e).mul(o)}).setLayout({name:"LTC_EdgeVectorFormFactor",type:"vec3",inputs:[{name:"v1",type:"vec3"},{name:"v2",type:"vec3"}]}),A4=be(({N:r,V:e,P:t,mInv:n,p0:i,p1:s,p2:a,p3:o})=>{const l=s.sub(i).toVar(),u=o.sub(i).toVar(),c=l.cross(u),d=he().toVar();return cr(c.dot(t.sub(i)).greaterThanEqual(0),()=>{const f=e.sub(r.mul(e.dot(r))).normalize(),h=r.cross(f).negate(),p=n.mul(wl(f,h,r).transpose()).toVar(),x=p.mul(i.sub(t)).normalize().toVar(),v=p.mul(s.sub(t)).normalize().toVar(),m=p.mul(a.sub(t)).normalize().toVar(),C=p.mul(o.sub(t)).normalize().toVar(),w=he(0).toVar();w.addAssign(Xp({v1:x,v2:v})),w.addAssign(Xp({v1:v,v2:m})),w.addAssign(Xp({v1:m,v2:C})),w.addAssign(Xp({v1:C,v2:x})),d.assign(he(v4({f:w})))}),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"}]}),PQ=be(({P:r,p0:e,p1:t,p2:n,p3:i})=>{const s=t.sub(e).toVar(),a=i.sub(e).toVar(),o=s.cross(a),l=he().toVar();return cr(o.dot(r.sub(e)).greaterThanEqual(0),()=>{const u=e.sub(r).normalize().toVar(),c=t.sub(r).normalize().toVar(),d=n.sub(r).normalize().toVar(),f=i.sub(r).normalize().toVar(),h=he(0).toVar();h.addAssign(Xp({v1:u,v2:c})),h.addAssign(Xp({v1:c,v2:d})),h.addAssign(Xp({v1:d,v2:f})),h.addAssign(Xp({v1:f,v2:u})),l.assign(he(v4({f:h.abs()})))}),l}).setLayout({name:"LTC_Evaluate",type:"vec3",inputs:[{name:"P",type:"vec3"},{name:"p0",type:"vec3"},{name:"p1",type:"vec3"},{name:"p2",type:"vec3"},{name:"p3",type:"vec3"}]}),OE=1/6,x4=r=>Ai(OE,Ai(r,Ai(r,r.negate().add(3)).sub(3)).add(1)),uB=r=>Ai(OE,Ai(r,Ai(r,Ai(3,r).sub(6))).add(4)),y4=r=>Ai(OE,Ai(r,Ai(r,Ai(-3,r).add(3)).add(3)).add(1)),cB=r=>Ai(OE,Fc(r,3)),b4=r=>x4(r).add(uB(r)),E4=r=>y4(r).add(cB(r)),w4=r=>wo(-1,uB(r).div(x4(r).add(uB(r)))),C4=r=>wo(1,cB(r).div(y4(r).add(cB(r)))),P4=(r,e,t)=>{const n=r.uvNode,i=Ai(n,e.zw).add(.5),s=yf(i),a=Pd(i),o=b4(a.x),l=E4(a.x),u=w4(a.x),c=C4(a.x),d=w4(a.y),f=C4(a.y),h=Wt(s.x.add(u),s.y.add(d)).sub(.5).mul(e.xy),p=Wt(s.x.add(c),s.y.add(d)).sub(.5).mul(e.xy),x=Wt(s.x.add(u),s.y.add(f)).sub(.5).mul(e.xy),v=Wt(s.x.add(c),s.y.add(f)).sub(.5).mul(e.xy),m=b4(a.y).mul(wo(o.mul(r.sample(h).level(t)),l.mul(r.sample(p).level(t)))),C=E4(a.y).mul(wo(o.mul(r.sample(x).level(t)),l.mul(r.sample(v).level(t))));return m.add(C)},dB=be(([r,e])=>{const t=Wt(r.size(ce(e))),n=Wt(r.size(ce(e.add(1)))),i=rc(1,t),s=rc(1,n),a=P4(r,Yn(i,t),yf(e)),o=P4(r,Yn(s,n),fE(e));return Pd(e).mix(a,o)}),BQ=be(([r,e])=>{const t=e.mul(B3(r));return dB(r,t)}),B4=be(([r,e,t,n,i])=>{const s=he(g3(e.negate(),au(r),rc(1,n))),a=he(bf(i[0].xyz),bf(i[1].xyz),bf(i[2].xyz));return au(s).mul(t.mul(a))}).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"}]}),MQ=be(([r,e])=>r.mul(Md(e.mul(2).sub(2),0,1))).setLayout({name:"applyIorToRoughness",type:"float",inputs:[{name:"roughness",type:"float"},{name:"ior",type:"float"}]}),SQ=_3(),DQ=_3(),M4=be(([r,e,t],{material:n})=>{const s=(n.side===Qi?SQ:DQ).sample(r),a=xf(mg.x).mul(MQ(e,t));return dB(s,a)}),S4=be(([r,e,t])=>(cr(t.notEqual(0),()=>{const n=dE(e).negate().div(t);return i3(n.negate().mul(r))}),he(1))).setLayout({name:"volumeAttenuation",type:"vec3",inputs:[{name:"transmissionDistance",type:"float"},{name:"attenuationColor",type:"vec3"},{name:"attenuationDistance",type:"float"}]}),TQ=be(([r,e,t,n,i,s,a,o,l,u,c,d,f,h,p])=>{let x,v;if(p){x=Yn().toVar(),v=he().toVar();const B=c.sub(1).mul(p.mul(.025)),S=he(c.sub(B),c,c.add(B));Vs({start:0,end:3},({i:I})=>{const N=S.element(I),T=B4(r,e,d,N,o),R=a.add(T),D=u.mul(l.mul(Yn(R,1))),j=Wt(D.xy.div(D.w)).toVar();j.addAssign(1),j.divAssign(2),j.assign(Wt(j.x,j.y.oneMinus()));const q=M4(j,t,N);x.element(I).assign(q.element(I)),x.a.addAssign(q.a),v.element(I).assign(n.element(I).mul(S4(bf(T),f,h).element(I)))}),x.a.divAssign(3)}else{const B=B4(r,e,d,c,o),S=a.add(B),I=u.mul(l.mul(Yn(S,1))),N=Wt(I.xy.div(I.w)).toVar();N.addAssign(1),N.divAssign(2),N.assign(Wt(N.x,N.y.oneMinus())),x=M4(N,t,c),v=n.mul(S4(bf(B),f,h))}const m=v.rgb.mul(x.rgb),C=r.dot(e).clamp(),w=he(g4({dotNV:C,specularColor:i,specularF90:s,roughness:t})),P=v.r.add(v.g,v.b).div(3);return Yn(w.oneMinus().mul(m),x.a.oneMinus().mul(P).oneMinus())}),IQ=wl(3.2404542,-.969266,.0556434,-1.5371385,1.8760108,-.2040259,-.4985314,.041556,1.0572252),NQ=r=>{const e=r.sqrt();return he(1).add(e).div(he(1).sub(e))},D4=(r,e)=>r.sub(e).div(r.add(e)).pow2(),FQ=(r,e)=>{const t=r.mul(2*Math.PI*1e-9),n=he(54856e-17,44201e-17,52481e-17),i=he(1681e3,1795300,2208400),s=he(43278e5,93046e5,66121e5),a=K(9747e-17*Math.sqrt(2*Math.PI*45282e5)).mul(t.mul(2239900).add(e.x).cos()).mul(t.pow2().mul(-45282e5).exp());let o=n.mul(s.mul(2*Math.PI).sqrt()).mul(i.mul(t).add(e).cos()).mul(t.pow2().negate().mul(s).exp());return o=he(o.x.add(a),o.y,o.z).div(10685e-11),IQ.mul(o)},T4=be(({outsideIOR:r,eta2:e,cosTheta1:t,thinFilmThickness:n,baseF0:i})=>{const s=ss(r,e,ic(0,.03,n)),o=r.div(s).pow2().mul(t.pow2().oneMinus()).oneMinus();cr(o.lessThan(0),()=>he(1));const l=o.sqrt(),u=D4(s,r),c=CA({f0:u,f90:1,dotVH:t}),d=c.oneMinus(),f=s.lessThan(r).select(Math.PI,0),h=K(Math.PI).sub(f),p=NQ(i.clamp(0,.9999)),x=D4(p,s.toVec3()),v=CA({f0:x,f90:1,dotVH:l}),m=he(p.x.lessThan(s).select(Math.PI,0),p.y.lessThan(s).select(Math.PI,0),p.z.lessThan(s).select(Math.PI,0)),C=s.mul(n,l,2),w=he(h).add(m),P=c.mul(v).clamp(1e-5,.9999),B=P.sqrt(),S=d.pow2().mul(v).div(he(1).sub(P)),N=c.add(S).toVar(),T=S.sub(d).toVar();return Vs({start:1,end:2,condition:"<=",name:"m"},({m:R})=>{T.mulAssign(B);const D=FQ(K(R).mul(C),K(R).mul(w)).mul(2);N.addAssign(T.mul(D))}),N.max(he(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"}]}),Px=be(({normal:r,viewDir:e,roughness:t})=>{const n=r.dot(e).saturate(),i=t.mul(t),s=t.add(.1).reciprocal(),a=K(-1.9362).add(t.mul(1.0678)).add(i.mul(.4573)).sub(s.mul(.8469)),o=K(-.6014).add(t.mul(.5538)).sub(i.mul(.467)).sub(s.mul(.1255));return a.mul(n).add(o).exp().saturate()}),fB=he(.04),hB=K(1);class I4 extends LE{constructor(e=!1,t=!1,n=!1,i=!1,s=!1,a=!1){super(),this.clearcoat=e,this.sheen=t,this.iridescence=n,this.anisotropy=i,this.transmission=s,this.dispersion=a,this.clearcoatRadiance=null,this.clearcoatSpecularDirect=null,this.clearcoatSpecularIndirect=null,this.sheenSpecularDirect=null,this.sheenSpecularIndirect=null,this.iridescenceFresnel=null,this.iridescenceF0=null,this.iridescenceF0Dielectric=null,this.iridescenceF0Metallic=null}start(e){if(this.clearcoat===!0&&(this.clearcoatRadiance=he().toVar("clearcoatRadiance"),this.clearcoatSpecularDirect=he().toVar("clearcoatSpecularDirect"),this.clearcoatSpecularIndirect=he().toVar("clearcoatSpecularIndirect")),this.sheen===!0&&(this.sheenSpecularDirect=he().toVar("sheenSpecularDirect"),this.sheenSpecularIndirect=he().toVar("sheenSpecularIndirect")),this.iridescence===!0){const t=vs.dot(_s).clamp(),n=T4({outsideIOR:K(1),eta2:iE,cosTheta1:t,thinFilmThickness:sE,baseF0:Up}),i=T4({outsideIOR:K(1),eta2:iE,cosTheta1:t,thinFilmThickness:sE,baseF0:Ws.rgb});this.iridescenceFresnel=ss(n,i,xh),this.iridescenceF0Dielectric=lB({f:n,f90:1,dotVH:t}),this.iridescenceF0Metallic=lB({f:i,f90:1,dotVH:t}),this.iridescenceF0=ss(this.iridescenceF0Dielectric,this.iridescenceF0Metallic,xh)}if(this.transmission===!0){const t=ac,n=yx.sub(ac).normalize(),i=jp,s=e.context;s.backdrop=TQ(i,n,Af,dg,hg,dA,t,Lc,sc,uu,px,KP,_P,qP,this.dispersion?$P:null),s.backdropAlpha=lE,Ws.a.mulAssign(ss(1,s.backdrop.a,lE))}super.start(e)}computeMultiscattering(e,t,n,i,s=null){const a=vs.dot(_s).clamp(),o=Cx({roughness:Af,dotNV:a}),l=s?rE.mix(i,s):i,u=l.mul(o.x).add(n.mul(o.y)),d=o.x.add(o.y).oneMinus(),f=l.add(l.oneMinus().mul(.047619)),h=u.mul(f).div(d.mul(f).oneMinus());e.addAssign(u),t.addAssign(h.mul(d))}direct({lightDirection:e,lightColor:t,reflectedLight:n}){const s=vs.dot(e).clamp().mul(t).toVar();if(this.sheen===!0){this.sheenSpecularDirect.addAssign(s.mul(wQ({lightDirection:e})));const a=Px({normal:vs,viewDir:_s,roughness:zp}),o=Px({normal:vs,viewDir:e,roughness:zp}),l=nc.r.max(nc.g).max(nc.b).mul(a.max(o)).oneMinus();s.mulAssign(l)}if(this.clearcoat===!0){const o=vg.dot(e).clamp().mul(t);this.clearcoatSpecularDirect.addAssign(o.mul(oB({lightDirection:e,f0:fB,f90:hB,roughness:dx,normalView:vg})))}n.directDiffuse.addAssign(s.mul(xg({diffuseColor:dg}))),n.directSpecular.addAssign(s.mul(yQ({lightDirection:e,f0:hg,f90:1,roughness:Af,f:this.iridescenceFresnel,USE_IRIDESCENCE:this.iridescence,USE_ANISOTROPY:this.anisotropy})))}directRectArea({lightColor:e,lightPosition:t,halfWidth:n,halfHeight:i,reflectedLight:s,ltc_1:a,ltc_2:o}){const l=t.add(n).sub(i),u=t.sub(n).sub(i),c=t.sub(n).add(i),d=t.add(n).add(i),f=vs,h=_s,p=po.toVar(),x=CQ({N:f,V:h,roughness:Af}),v=a.sample(x).toVar(),m=o.sample(x).toVar(),C=wl(he(v.x,0,v.y),he(0,1,0),he(v.z,0,v.w)).toVar(),w=hg.mul(m.x).add(hg.oneMinus().mul(m.y)).toVar();s.directSpecular.addAssign(e.mul(w).mul(A4({N:f,V:h,P:p,mInv:C,p0:l,p1:u,p2:c,p3:d}))),s.directDiffuse.addAssign(e.mul(dg).mul(A4({N:f,V:h,P:p,mInv:wl(1,0,0,0,1,0,0,0,1),p0:l,p1:u,p2:c,p3:d})))}indirect(e){this.indirectDiffuse(e),this.indirectSpecular(e),this.ambientOcclusion(e)}indirectDiffuse(e){const{irradiance:t,reflectedLight:n}=e.context,i=t.mul(xg({diffuseColor:dg})).toVar();if(this.sheen===!0){const s=Px({normal:vs,viewDir:_s,roughness:zp}),a=nc.r.max(nc.g).max(nc.b).mul(s).oneMinus();i.mulAssign(a)}n.indirectDiffuse.addAssign(i)}indirectSpecular(e){const{radiance:t,iblIrradiance:n,reflectedLight:i}=e.context;if(this.sheen===!0&&this.sheenSpecularIndirect.addAssign(n.mul(nc,Px({normal:vs,viewDir:_s,roughness:zp}))),this.clearcoat===!0){const v=vg.dot(_s).clamp(),m=g4({dotNV:v,specularColor:fB,specularF90:hB,roughness:dx});this.clearcoatSpecularIndirect.addAssign(this.clearcoatRadiance.mul(m))}const s=he().toVar("singleScatteringDielectric"),a=he().toVar("multiScatteringDielectric"),o=he().toVar("singleScatteringMetallic"),l=he().toVar("multiScatteringMetallic");this.computeMultiscattering(s,a,dA,Up,this.iridescenceF0Dielectric),this.computeMultiscattering(o,l,dA,Ws.rgb,this.iridescenceF0Metallic);const u=ss(s,o,xh),c=ss(a,l,xh),d=s.add(a),f=dg.mul(d.oneMinus()),h=n.mul(1/Math.PI),p=t.mul(u).add(c.mul(h)).toVar(),x=f.mul(h).toVar();if(this.sheen===!0){const v=Px({normal:vs,viewDir:_s,roughness:zp}),m=nc.r.max(nc.g).max(nc.b).mul(v).oneMinus();p.mulAssign(m),x.mulAssign(m)}i.indirectSpecular.addAssign(p),i.indirectDiffuse.addAssign(x)}ambientOcclusion(e){const{ambientOcclusion:t,reflectedLight:n}=e.context,s=vs.dot(_s).clamp().add(t),a=Af.mul(-16).oneMinus().negate().exp2(),o=t.sub(s.pow(a).oneMinus()).clamp();this.clearcoat===!0&&this.clearcoatSpecularIndirect.mulAssign(t),this.sheen===!0&&this.sheenSpecularIndirect.mulAssign(t),n.indirectDiffuse.mulAssign(t),n.indirectSpecular.mulAssign(o)}finish({context:e}){const{outgoingLight:t}=e;if(this.clearcoat===!0){const n=vg.dot(_s).clamp(),i=CA({dotVH:n,f0:fB,f90:hB}),s=t.mul(nE.mul(i).oneMinus()).add(this.clearcoatSpecularDirect.add(this.clearcoatSpecularIndirect).mul(nE));t.assign(s)}if(this.sheen===!0){const n=t.add(this.sheenSpecularDirect,this.sheenSpecularIndirect.mul(1/Math.PI));t.assign(n)}}}const N4=K(1),pB=K(-2),zE=K(.8),mB=K(-1),HE=K(.4),gB=K(2),UE=K(.305),vB=K(3),F4=K(.21),RQ=K(4),R4=K(4),LQ=K(16),OQ=be(([r])=>{const e=he(va(r)).toVar(),t=K(-1).toVar();return cr(e.x.greaterThan(e.z),()=>{cr(e.x.greaterThan(e.y),()=>{t.assign(Cl(r.x.greaterThan(0),0,3))}).Else(()=>{t.assign(Cl(r.y.greaterThan(0),1,4))})}).Else(()=>{cr(e.z.greaterThan(e.y),()=>{t.assign(Cl(r.z.greaterThan(0),2,5))}).Else(()=>{t.assign(Cl(r.y.greaterThan(0),1,4))})}),t}).setLayout({name:"getFace",type:"float",inputs:[{name:"direction",type:"vec3"}]}),zQ=be(([r,e])=>{const t=Wt().toVar();return cr(e.equal(0),()=>{t.assign(Wt(r.z,r.y).div(va(r.x)))}).ElseIf(e.equal(1),()=>{t.assign(Wt(r.x.negate(),r.z.negate()).div(va(r.y)))}).ElseIf(e.equal(2),()=>{t.assign(Wt(r.x.negate(),r.y).div(va(r.z)))}).ElseIf(e.equal(3),()=>{t.assign(Wt(r.z.negate(),r.y).div(va(r.x)))}).ElseIf(e.equal(4),()=>{t.assign(Wt(r.x.negate(),r.z).div(va(r.y)))}).Else(()=>{t.assign(Wt(r.x,r.y).div(va(r.z)))}),Ai(.5,t.add(1))}).setLayout({name:"getUV",type:"vec2",inputs:[{name:"direction",type:"vec3"},{name:"face",type:"float"}]}),HQ=be(([r])=>{const e=K(0).toVar();return cr(r.greaterThanEqual(zE),()=>{e.assign(N4.sub(r).mul(mB.sub(pB)).div(N4.sub(zE)).add(pB))}).ElseIf(r.greaterThanEqual(HE),()=>{e.assign(zE.sub(r).mul(gB.sub(mB)).div(zE.sub(HE)).add(mB))}).ElseIf(r.greaterThanEqual(UE),()=>{e.assign(HE.sub(r).mul(vB.sub(gB)).div(HE.sub(UE)).add(gB))}).ElseIf(r.greaterThanEqual(F4),()=>{e.assign(UE.sub(r).mul(RQ.sub(vB)).div(UE.sub(F4)).add(vB))}).Else(()=>{e.assign(K(-2).mul(xf(Ai(1.16,r))))}),e}).setLayout({name:"roughnessToMip",type:"float",inputs:[{name:"roughness",type:"float"}]}),L4=be(([r,e])=>{const t=r.toVar();t.assign(Ai(2,t).sub(1));const n=he(t,1).toVar();return cr(e.equal(0),()=>{n.assign(n.zyx)}).ElseIf(e.equal(1),()=>{n.assign(n.xzy),n.xz.mulAssign(-1)}).ElseIf(e.equal(2),()=>{n.x.mulAssign(-1)}).ElseIf(e.equal(3),()=>{n.assign(n.zyx),n.xz.mulAssign(-1)}).ElseIf(e.equal(4),()=>{n.assign(n.xzy),n.xy.mulAssign(-1)}).ElseIf(e.equal(5),()=>{n.z.mulAssign(-1)}),n}).setLayout({name:"getDirection",type:"vec3",inputs:[{name:"uv",type:"vec2"},{name:"face",type:"float"}]}),O4=be(([r,e,t,n,i,s])=>{const a=K(t),o=he(e),l=Md(HQ(a),pB,s),u=Pd(l),c=yf(l),d=he(Bx(r,o,c,n,i,s)).toVar();return cr(u.notEqual(0),()=>{const f=he(Bx(r,o,c.add(1),n,i,s)).toVar();d.assign(ss(d,f,u))}),d}),Bx=be(([r,e,t,n,i,s])=>{const a=K(t).toVar(),o=he(e),l=K(OQ(o)).toVar(),u=K(Ya(R4.sub(a),0)).toVar();a.assign(Ya(a,R4));const c=K(hA(a)).toVar(),d=Wt(zQ(o,l).mul(c.sub(2)).add(1)).toVar();return cr(l.greaterThan(2),()=>{d.y.addAssign(c),l.subAssign(3)}),d.x.addAssign(l.mul(c)),d.x.addAssign(u.mul(Ai(3,LQ))),d.y.addAssign(Ai(4,hA(s).sub(c))),d.x.mulAssign(n),d.y.mulAssign(i),r.sample(d).grad(Wt(),Wt())}),AB=be(({envMap:r,mipInt:e,outputDirection:t,theta:n,axis:i,CUBEUV_TEXEL_WIDTH:s,CUBEUV_TEXEL_HEIGHT:a,CUBEUV_MAX_MIP:o})=>{const l=Bd(n),u=t.mul(l).add(i.cross(t).mul(ou(n))).add(i.mul(i.dot(t).mul(l.oneMinus())));return Bx(r,u,e,s,a,o)}),z4=be(({n:r,latitudinal:e,poleAxis:t,outputDirection:n,weights:i,samples:s,dTheta:a,mipInt:o,envMap:l,CUBEUV_TEXEL_WIDTH:u,CUBEUV_TEXEL_HEIGHT:c,CUBEUV_MAX_MIP:d})=>{const f=he(Cl(e,t,yh(t,n))).toVar();cr(f.equal(he(0)),()=>{f.assign(he(n.z,0,n.x.negate()))}),f.assign(au(f));const h=he().toVar();return h.addAssign(i.element(0).mul(AB({theta:0,axis:f,outputDirection:n,mipInt:o,envMap:l,CUBEUV_TEXEL_WIDTH:u,CUBEUV_TEXEL_HEIGHT:c,CUBEUV_MAX_MIP:d}))),Vs({start:ce(1),end:r},({i:p})=>{cr(p.greaterThanEqual(s),()=>{ZI()});const x=K(a.mul(K(p))).toVar();h.addAssign(i.element(p).mul(AB({theta:x.mul(-1),axis:f,outputDirection:n,mipInt:o,envMap:l,CUBEUV_TEXEL_WIDTH:u,CUBEUV_TEXEL_HEIGHT:c,CUBEUV_MAX_MIP:d}))),h.addAssign(i.element(p).mul(AB({theta:x,axis:f,outputDirection:n,mipInt:o,envMap:l,CUBEUV_TEXEL_WIDTH:u,CUBEUV_TEXEL_HEIGHT:c,CUBEUV_MAX_MIP:d})))}),Yn(h,1)}),UQ=be(([r])=>{const e=Ut(r).toVar();return e.assign(e.shiftLeft(Ut(16)).bitOr(e.shiftRight(Ut(16)))),e.assign(e.bitAnd(Ut(1431655765)).shiftLeft(Ut(1)).bitOr(e.bitAnd(Ut(2863311530)).shiftRight(Ut(1)))),e.assign(e.bitAnd(Ut(858993459)).shiftLeft(Ut(2)).bitOr(e.bitAnd(Ut(3435973836)).shiftRight(Ut(2)))),e.assign(e.bitAnd(Ut(252645135)).shiftLeft(Ut(4)).bitOr(e.bitAnd(Ut(4042322160)).shiftRight(Ut(4)))),e.assign(e.bitAnd(Ut(16711935)).shiftLeft(Ut(8)).bitOr(e.bitAnd(Ut(4278255360)).shiftRight(Ut(8)))),K(e).mul(23283064365386963e-26)}),kQ=be(([r,e])=>Wt(K(r).div(K(e)),UQ(r))),VQ=be(([r,e,t])=>{const n=he(e).toVar(),i=K(t),s=i.mul(i).toVar(),a=au(he(s.mul(n.x),s.mul(n.y),n.z)).toVar(),o=a.x.mul(a.x).add(a.y.mul(a.y)),l=Cl(o.greaterThan(0),he(a.y.negate(),a.x,0).div(Gl(o)),he(1,0,0)).toVar(),u=yh(a,l).toVar(),c=Gl(r.x),d=Ai(2,3.14159265359).mul(r.y),f=c.mul(Bd(d)).toVar(),h=c.mul(ou(d)).toVar(),p=Ai(.5,a.z.add(1));h.assign(p.oneMinus().mul(Gl(f.mul(f).oneMinus())).add(p.mul(h)));const x=l.mul(f).add(u.mul(h)).add(a.mul(Gl(Ya(0,f.mul(f).add(h.mul(h)).oneMinus()))));return au(he(s.mul(x.x),s.mul(x.y),Ya(0,x.z)))}),H4=be(({roughness:r,mipInt:e,envMap:t,N_immutable:n,GGX_SAMPLES:i,CUBEUV_TEXEL_WIDTH:s,CUBEUV_TEXEL_HEIGHT:a,CUBEUV_MAX_MIP:o})=>{const l=he(n).toVar(),u=he(0).toVar(),c=K(0).toVar();return cr(r.lessThan(.001),()=>{u.assign(Bx(t,l,e,s,a,o))}).Else(()=>{const d=Cl(va(l.z).lessThan(.999),he(0,0,1),he(1,0,0)),f=au(yh(d,l)).toVar(),h=yh(l,f).toVar();Vs({start:Ut(0),end:i},({i:p})=>{const x=kQ(p,i),v=VQ(x,he(0,0,1),r),m=au(f.mul(v.x).add(h.mul(v.y)).add(l.mul(v.z))),C=au(m.mul(Nc(l,m).mul(2)).sub(l)),w=Ya(Nc(l,C),0);cr(w.greaterThan(0),()=>{const P=Bx(t,C,e,s,a,o);u.addAssign(P.mul(w)),c.addAssign(w)})}),cr(c.greaterThan(0),()=>{u.assign(u.div(c))})}),Yn(u,1)}),Gp=4,U4=[.125,.215,.35,.446,.526,.582],yg=20,jQ=512,Mx=new Km(-1,1,1,-1,0,1),XQ=new bo(90,1),k4=new Vn;let xB=null,yB=0,bB=0;const GQ=new J,kE=new WeakMap,WQ=[3,1,5,0,4,2],EB=L4(Qs(),lu("faceIndex")).normalize(),VE=he(EB.x,EB.y,EB.z);class QQ{constructor(e){this._renderer=e,this._pingPongRenderTarget=null,this._lodMax=0,this._cubeSize=0,this._sizeLods=[],this._sigmas=[],this._lodMeshes=[],this._blurMaterial=null,this._ggxMaterial=null,this._cubemapMaterial=null,this._equirectMaterial=null,this._backgroundBox=null}get _hasInitialized(){return this._renderer.hasInitialized()}fromScene(e,t=0,n=.1,i=100,s={}){const{size:a=256,position:o=GQ,renderTarget:l=null}=s;if(this._setSize(a),this._hasInitialized===!1){ze('PMREMGenerator: ".fromScene()" called before the backend is initialized. Try using "await renderer.init()" instead.');const c=l||this._allocateTarget();return s.renderTarget=c,this.fromSceneAsync(e,t,n,i,s),c}xB=this._renderer.getRenderTarget(),yB=this._renderer.getActiveCubeFace(),bB=this._renderer.getActiveMipmapLevel();const u=l||this._allocateTarget();return u.depthBuffer=!0,this._init(u),this._sceneToCubeUV(e,n,i,u,o),t>0&&this._blur(u,0,0,t),this._applyPMREM(u),this._cleanup(u),u}fromSceneAsync(a){return Kr(this,arguments,function*(e,t=0,n=.1,i=100,s={}){return rs('PMREMGenerator: ".fromSceneAsync()" is deprecated. Use "await renderer.init()" instead.'),yield this._renderer.init(),this.fromScene(e,t,n,i,s)})}fromEquirectangular(e,t=null){if(this._hasInitialized===!1){ze('PMREMGenerator: .fromEquirectangular() called before the backend is initialized. Try using "await renderer.init()" instead.'),this._setSizeFromTexture(e);const n=t||this._allocateTarget();return this.fromEquirectangularAsync(e,n),n}return this._fromTexture(e,t)}fromEquirectangularAsync(e,t=null){return Kr(this,null,function*(){return rs('PMREMGenerator: ".fromEquirectangularAsync()" is deprecated. Use "await renderer.init()" instead.'),yield this._renderer.init(),this._fromTexture(e,t)})}fromCubemap(e,t=null){if(this._hasInitialized===!1){ze("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)}fromCubemapAsync(e,t=null){return Kr(this,null,function*(){return rs('PMREMGenerator: ".fromCubemapAsync()" is deprecated. Use "await renderer.init()" instead.'),yield this._renderer.init(),this._fromTexture(e,t)})}compileCubemapShader(){return Kr(this,null,function*(){this._cubemapMaterial===null&&(this._cubemapMaterial=j4(),yield this._compileMaterial(this._cubemapMaterial))})}compileEquirectangularShader(){return Kr(this,null,function*(){this._equirectMaterial===null&&(this._equirectMaterial=X4(),yield this._compileMaterial(this._equirectMaterial))})}dispose(){this._dispose(),this._cubemapMaterial!==null&&this._cubemapMaterial.dispose(),this._equirectMaterial!==null&&this._equirectMaterial.dispose(),this._backgroundBox!==null&&(this._backgroundBox.geometry.dispose(),this._backgroundBox.material.dispose())}_setSizeFromTexture(e){e.mapping===ai||e.mapping===ps?this._setSize(e.image.length===0?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(){this._blurMaterial!==null&&this._blurMaterial.dispose(),this._ggxMaterial!==null&&this._ggxMaterial.dispose(),this._pingPongRenderTarget!==null&&this._pingPongRenderTarget.dispose();for(let e=0;e<this._lodMeshes.length;e++)this._lodMeshes[e].geometry.dispose()}_cleanup(e){this._renderer.setRenderTarget(xB,yB,bB),e.scissorTest=!1,PA(e,0,0,e.width,e.height)}_fromTexture(e,t){this._setSizeFromTexture(e),xB=this._renderer.getRenderTarget(),yB=this._renderer.getActiveCubeFace(),bB=this._renderer.getActiveMipmapLevel();const n=t||this._allocateTarget();return this._init(n),this._textureToCubeUV(e,n),this._applyPMREM(n),this._cleanup(n),n}_allocateTarget(){const e=3*Math.max(this._cubeSize,112),t=4*this._cubeSize;return V4(e,t)}_init(e){if(this._pingPongRenderTarget===null||this._pingPongRenderTarget.width!==e.width||this._pingPongRenderTarget.height!==e.height){this._pingPongRenderTarget!==null&&this._dispose(),this._pingPongRenderTarget=V4(e.width,e.height);const{_lodMax:t}=this;({lodMeshes:this._lodMeshes,sizeLods:this._sizeLods,sigmas:this._sigmas}=ZQ(t)),this._blurMaterial=YQ(t,e.width,e.height),this._ggxMaterial=JQ(t,e.width,e.height)}}_compileMaterial(e){return Kr(this,null,function*(){const t=new Gs(new Ni,e);yield this._renderer.compile(t,Mx)})}_sceneToCubeUV(e,t,n,i,s){const a=XQ;a.near=t,a.far=n;const o=[1,1,1,1,-1,1],l=[1,-1,1,-1,1,-1],u=this._renderer,c=u.autoClear;u.getClearColor(k4),u.autoClear=!1,this._backgroundBox===null&&(this._backgroundBox=new Gs(new Dp,new rl({name:"PMREM.Background",side:Qi,depthWrite:!1,depthTest:!1})));const d=this._backgroundBox,f=d.material;let h=!1;const p=e.background;p?p.isColor&&(f.color.copy(p),e.background=null,h=!0):(f.color.copy(k4),h=!0),u.setRenderTarget(i),u.clear(),h&&u.render(d,a);for(let x=0;x<6;x++){const v=x%3;v===0?(a.up.set(0,o[x],0),a.position.set(s.x,s.y,s.z),a.lookAt(s.x+l[x],s.y,s.z)):v===1?(a.up.set(0,0,o[x]),a.position.set(s.x,s.y,s.z),a.lookAt(s.x,s.y+l[x],s.z)):(a.up.set(0,o[x],0),a.position.set(s.x,s.y,s.z),a.lookAt(s.x,s.y,s.z+l[x]));const m=this._cubeSize;PA(i,v*m,x>2?m:0,m,m),u.render(e,a)}u.autoClear=c,e.background=p}_textureToCubeUV(e,t){const n=this._renderer,i=e.mapping===ai||e.mapping===ps;i?this._cubemapMaterial===null&&(this._cubemapMaterial=j4(e)):this._equirectMaterial===null&&(this._equirectMaterial=X4(e));const s=i?this._cubemapMaterial:this._equirectMaterial;s.fragmentNode.value=e;const a=this._lodMeshes[0];a.material=s;const o=this._cubeSize;PA(t,0,0,3*o,2*o),n.setRenderTarget(t),n.render(a,Mx)}_applyPMREM(e){const t=this._renderer,n=t.autoClear;t.autoClear=!1;const i=this._lodMeshes.length;for(let s=1;s<i;s++)this._applyGGXFilter(e,s-1,s);t.autoClear=n}_applyGGXFilter(e,t,n){const i=this._renderer,s=this._pingPongRenderTarget,a=this._ggxMaterial,o=this._lodMeshes[n];o.material=a;const l=kE.get(a),u=n/(this._lodMeshes.length-1),c=t/(this._lodMeshes.length-1),d=Math.sqrt(u*u-c*c),f=0+u*1.25,h=d*f,{_lodMax:p}=this,x=this._sizeLods[n],v=3*x*(n>p-Gp?n-p+Gp:0),m=4*(this._cubeSize-x);e.texture.frame=(e.texture.frame||0)+1,l.envMap.value=e.texture,l.roughness.value=h,l.mipInt.value=p-t,PA(s,v,m,3*x,2*x),i.setRenderTarget(s),i.render(o,Mx),s.texture.frame=(s.texture.frame||0)+1,l.envMap.value=s.texture,l.roughness.value=0,l.mipInt.value=p-n,PA(e,v,m,3*x,2*x),i.setRenderTarget(e),i.render(o,Mx)}_blur(e,t,n,i,s){const a=this._pingPongRenderTarget;this._halfBlur(e,a,t,n,i,"latitudinal",s),this._halfBlur(a,e,n,n,i,"longitudinal",s)}_halfBlur(e,t,n,i,s,a,o){const l=this._renderer,u=this._blurMaterial;a!=="latitudinal"&&a!=="longitudinal"&&rt("blur direction must be either latitudinal or longitudinal!");const c=3,d=this._lodMeshes[i];d.material=u;const f=kE.get(u),h=this._sizeLods[n]-1,p=isFinite(s)?Math.PI/(2*h):2*Math.PI/(2*yg-1),x=s/p,v=isFinite(s)?1+Math.floor(c*x):yg;v>yg&&ze(`sigmaRadians, ${s}, is too large and will clip, as it requested ${v} samples when the maximum is set to ${yg}`);const m=[];let C=0;for(let I=0;I<yg;++I){const N=I/x,T=Math.exp(-N*N/2);m.push(T),I===0?C+=T:I<v&&(C+=2*T)}for(let I=0;I<m.length;I++)m[I]=m[I]/C;e.texture.frame=(e.texture.frame||0)+1,f.envMap.value=e.texture,f.samples.value=v,f.weights.array=m,f.latitudinal.value=a==="latitudinal"?1:0,o&&(f.poleAxis.value=o);const{_lodMax:w}=this;f.dTheta.value=p,f.mipInt.value=w-n;const P=this._sizeLods[i],B=3*P*(i>w-Gp?i-w+Gp:0),S=4*(this._cubeSize-P);PA(t,B,S,3*P,2*P),l.setRenderTarget(t),l.render(d,Mx)}}function ZQ(r){const e=[],t=[],n=[];let i=r;const s=r-Gp+1+U4.length;for(let a=0;a<s;a++){const o=Math.pow(2,i);e.push(o);let l=1/o;a>r-Gp?l=U4[a-r+Gp-1]:a===0&&(l=0),t.push(l);const u=1/(o-2),c=-u,d=1+u,f=[c,c,d,c,d,d,c,c,d,d,c,d],h=6,p=6,x=3,v=2,m=1,C=new Float32Array(x*p*h),w=new Float32Array(v*p*h),P=new Float32Array(m*p*h);for(let S=0;S<h;S++){const I=S%3*2/3-1,N=S>2?0:-1,T=[I,N,0,I+2/3,N,0,I+2/3,N+1,0,I,N,0,I+2/3,N+1,0,I,N+1,0],R=WQ[S];C.set(T,x*p*R),w.set(f,v*p*R);const D=[R,R,R,R,R,R];P.set(D,m*p*R)}const B=new Ni;B.setAttribute("position",new ga(C,x)),B.setAttribute("uv",new ga(w,v)),B.setAttribute("faceIndex",new ga(P,m)),n.push(new Gs(B,null)),i>Gp&&i--}return{lodMeshes:n,sizeLods:e,sigmas:t}}function V4(r,e){const t={magFilter:ms,minFilter:ms,generateMipmaps:!1,type:pa,format:ma,colorSpace:af},n=new sh(r,e,t);return n.texture.mapping=Jd,n.texture.name="PMREM.cubeUv",n.texture.isPMREMTexture=!0,n.scissorTest=!0,n}function PA(r,e,t,n,i){r.viewport.set(e,t,n,i),r.scissor.set(e,t,n,i)}function jE(r){const e=new Ka;return e.depthTest=!1,e.depthWrite=!1,e.blending=Xa,e.name=`PMREM_${r}`,e}function YQ(r,e,t){const n=Wl(new Array(yg).fill(0)),i=Dr(new J(0,1,0)),s=Dr(0),a=K(yg),o=Dr(0),l=Dr(1),u=Bs(),c=Dr(0),d=K(1/e),f=K(1/t),h=K(r),p={n:a,latitudinal:o,weights:n,poleAxis:i,outputDirection:VE,dTheta:s,samples:l,envMap:u,mipInt:c,CUBEUV_TEXEL_WIDTH:d,CUBEUV_TEXEL_HEIGHT:f,CUBEUV_MAX_MIP:h},x=jE("blur");return x.fragmentNode=z4(Gc(ba({},p),{latitudinal:o.equal(1)})),kE.set(x,p),x}function JQ(r,e,t){const n=Bs(),i=Dr(0),s=Dr(0),a=K(1/e),o=K(1/t),l=K(r),u={envMap:n,roughness:i,mipInt:s,CUBEUV_TEXEL_WIDTH:a,CUBEUV_TEXEL_HEIGHT:o,CUBEUV_MAX_MIP:l},c=jE("ggx");return c.fragmentNode=H4(Gc(ba({},u),{N_immutable:VE,GGX_SAMPLES:Ut(jQ)})),kE.set(c,u),c}function j4(r){const e=jE("cubemap");return e.fragmentNode=cu(r,VE),e}function X4(r){const e=jE("equirect");return e.fragmentNode=Bs(r,iB(VE),0),e}const G4=new WeakMap;function KQ(r){const e=Math.log2(r)-2,t=1/r;return{texelWidth:1/(3*Math.max(Math.pow(2,e),7*16)),texelHeight:t,maxMip:e}}function qQ(r,e,t){const n=_Q(e);let i=n.get(r);if((i!==void 0?i.pmremVersion:-1)!==r.pmremVersion){const a=r.image;if(r.isCubeTexture)if(eZ(a))i=t.fromCubemap(r,i);else return null;else if(tZ(a))i=t.fromEquirectangular(r,i);else return null;i.pmremVersion=r.pmremVersion,n.set(r,i)}return i.texture}function _Q(r){let e=G4.get(r);return e===void 0&&(e=new WeakMap,G4.set(r,e)),e}class $Q extends Qa{static get type(){return"PMREMNode"}constructor(e,t=null,n=null){super("vec3"),this._value=e,this._pmrem=null,this.uvNode=t,this.levelNode=n,this._generator=null;const i=new yo;i.isRenderTargetTexture=!0,this._texture=Bs(i),this._width=Dr(0),this._height=Dr(0),this._maxMip=Dr(0),this.updateBeforeType=Bi.RENDER}set value(e){this._value=e,this._pmrem=null}get value(){return this._value}updateFromTexture(e){const t=KQ(e.image.height);this._texture.value=e,this._width.value=t.texelWidth,this._height.value=t.texelHeight,this._maxMip.value=t.maxMip}updateBefore(e){let t=this._pmrem;const n=t?t.pmremVersion:-1,i=this._value;n!==i.pmremVersion&&(i.isPMREMTexture===!0?t=i:t=qQ(i,e.renderer,this._generator),t!==null&&(this._pmrem=t,this.updateFromTexture(t)))}setup(e){this._generator===null&&(this._generator=new QQ(e.renderer)),this.updateBefore(e);let t=this.uvNode;t===null&&e.context.getUV&&(t=e.context.getUV(this,e)),t=z3.mul(he(t.x,t.y.negate(),t.z));let n=this.levelNode;return n===null&&e.context.getTextureLevel&&(n=e.context.getTextureLevel(this)),O4(this._texture,t,n,this._width,this._height,this._maxMip)}dispose(){super.dispose(),this._generator!==null&&this._generator.dispose()}}function eZ(r){if(r==null)return!1;let e=0;const t=6;for(let n=0;n<t;n++)r[n]!==void 0&&e++;return e===t}function tZ(r){return r==null?!1:r.height>0}const wB=vi($Q).setParameterLength(1,3),W4=new WeakMap;class nZ extends yA{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 d=n.isTextureNode?n.value:t[n.property];let f=W4.get(d);f===void 0&&(f=wB(d),W4.set(d,f)),n=f}const s=t.useAnisotropy===!0||t.anisotropy>0?uI:vs,a=n.context(Q4(Af,s)).mul(wE),o=n.context(rZ(jp)).mul(Math.PI).mul(wE),l=mA(a),u=mA(o);e.context.radiance.addAssign(l),e.context.iblIrradiance.addAssign(u);const c=e.context.lightingModel.clearcoatRadiance;if(c){const d=n.context(Q4(dx,vg)).mul(wE),f=mA(d);c.addAssign(f)}}}const Q4=(r,e)=>{let t=null;return{getUV:()=>(t===null&&(t=_s.negate().reflect(e),t=p3(r).mix(t,e).normalize(),t=t.transformDirection(sc)),t),getTextureLevel:()=>r}},rZ=r=>({getUV:()=>r,getTextureLevel:()=>K(1)}),iZ=new D1;class Z4 extends Ka{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(iZ),this.setValues(e)}setupEnvironment(e){let t=super.setupEnvironment(e);return t===null&&e.environmentNode&&(t=e.environmentNode),t?new nZ(t):null}setupLightingModel(){return new I4}setupSpecular(){const e=ss(he(.04),Ws.rgb,xh);Up.assign(he(.04)),hg.assign(e),dA.assign(1)}setupVariants(){const e=this.metalnessNode?K(this.metalnessNode):AI;xh.assign(e);let t=this.roughnessNode?K(this.roughnessNode):vI;t=aB({roughness:t}),Af.assign(t),this.setupSpecular(),dg.assign(Ws.rgb.mul(e.oneMinus()))}copy(e){return this.emissiveNode=e.emissiveNode,this.metalnessNode=e.metalnessNode,this.roughnessNode=e.roughnessNode,super.copy(e)}}const sZ=new T5;class aZ extends Z4{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(sZ),this.setValues(e)}get useClearcoat(){return this.clearcoat>0||this.clearcoatNode!==null}get useIridescence(){return this.iridescence>0||this.iridescenceNode!==null}get useSheen(){return this.sheen>0||this.sheenNode!==null}get useAnisotropy(){return this.anisotropy>0||this.anisotropyNode!==null}get useTransmission(){return this.transmission>0||this.transmissionNode!==null}get useDispersion(){return this.dispersion>0||this.dispersionNode!==null}setupSpecular(){const e=this.iorNode?K(this.iorNode):NI;px.assign(e),Up.assign(Pu(h3(px.sub(1).div(px.add(1))).mul(gI),he(1)).mul(W3)),hg.assign(ss(Up,Ws.rgb,xh)),dA.assign(ss(W3,1,xh))}setupLightingModel(){return new I4(this.useClearcoat,this.useSheen,this.useIridescence,this.useAnisotropy,this.useTransmission,this.useDispersion)}setupVariants(e){if(super.setupVariants(e),this.useClearcoat){const t=this.clearcoatNode?K(this.clearcoatNode):yI,n=this.clearcoatRoughnessNode?K(this.clearcoatRoughnessNode):bI;nE.assign(t),dx.assign(aB({roughness:n}))}if(this.useSheen){const t=this.sheenNode?he(this.sheenNode):CI,n=this.sheenRoughnessNode?K(this.sheenRoughnessNode):PI;nc.assign(t),zp.assign(n)}if(this.useIridescence){const t=this.iridescenceNode?K(this.iridescenceNode):MI,n=this.iridescenceIORNode?K(this.iridescenceIORNode):SI,i=this.iridescenceThicknessNode?K(this.iridescenceThicknessNode):DI;rE.assign(t),iE.assign(n),sE.assign(i)}if(this.useAnisotropy){const t=(this.anisotropyNode?Wt(this.anisotropyNode):BI).toVar();Hp.assign(t.length()),cr(Hp.equal(0),()=>{t.assign(Wt(1,0))}).Else(()=>{t.divAssign(Wt(Hp)),Hp.assign(Hp.saturate())}),aE.assign(Hp.pow2().mix(Af.pow2(),1)),fx.assign(Ag[0].mul(t.x).add(Ag[1].mul(t.y))),fg.assign(Ag[1].mul(t.x).sub(Ag[0].mul(t.y)))}if(this.useTransmission){const t=this.transmissionNode?K(this.transmissionNode):TI,n=this.thicknessNode?K(this.thicknessNode):II,i=this.attenuationDistanceNode?K(this.attenuationDistanceNode):FI,s=this.attenuationColorNode?he(this.attenuationColorNode):RI;if(lE.assign(t),KP.assign(n),qP.assign(i),_P.assign(s),this.useDispersion){const a=this.dispersionNode?K(this.dispersionNode):OI;$P.assign(a)}}}setupClearcoatNormal(){return this.clearcoatNormalNode?he(this.clearcoatNormalNode):EI}setup(e){e.context.setupClearcoatNormal=()=>pA(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)}}class oZ extends null{constructor(e=!1,t=!1,n=!1,i=!1,s=!1,a=!1,o=!1){super(e,t,n,i,s,a),this.useSSS=o}direct({lightDirection:e,lightColor:t,reflectedLight:n},i){if(this.useSSS===!0){const s=i.material,{thicknessColorNode:a,thicknessDistortionNode:o,thicknessAmbientNode:l,thicknessAttenuationNode:u,thicknessPowerNode:c,thicknessScaleNode:d}=s,f=e.add(vs.mul(o)).normalize(),h=K(_s.dot(f.negate()).saturate().pow(c).mul(d)),p=he(h.add(l).mul(a));n.directDiffuse.addAssign(p.mul(u.mul(t)))}super.direct({lightDirection:e,lightColor:t,reflectedLight:n},i)}}class Bde extends null{static get type(){return"MeshSSSNodeMaterial"}constructor(e){super(e),this.thicknessColorNode=null,this.thicknessDistortionNode=K(.1),this.thicknessAmbientNode=K(0),this.thicknessAttenuationNode=K(.1),this.thicknessPowerNode=K(2),this.thicknessScaleNode=K(10)}get useSSS(){return this.thicknessColorNode!==null}setupLightingModel(){return new oZ(this.useClearcoat,this.useSheen,this.useIridescence,this.useAnisotropy,this.useTransmission,this.useDispersion,this.useSSS)}copy(e){return this.thicknessColorNode=e.thicknessColorNode,this.thicknessDistortionNode=e.thicknessDistortionNode,this.thicknessAmbientNode=e.thicknessAmbientNode,this.thicknessAttenuationNode=e.thicknessAttenuationNode,this.thicknessPowerNode=e.thicknessPowerNode,this.thicknessScaleNode=e.thicknessScaleNode,super.copy(e)}}const lZ=be(({normal:r,lightDirection:e,builder:t})=>{const n=r.dot(e),i=Wt(n.mul(.5).add(.5),0);if(t.material.gradientMap){const s=Sh("gradientMap","texture").context({getUV:()=>i});return he(s.r)}else{const s=i.fwidth().mul(.5);return ss(he(.7),he(1),ic(K(.7).sub(s.x),K(.7).add(s.x),i.x))}});class uZ extends LE{direct({lightDirection:e,lightColor:t,reflectedLight:n},i){const s=lZ({normal:EE,lightDirection:e,builder:i}).mul(t);n.directDiffuse.addAssign(s.mul(xg({diffuseColor:Ws.rgb})))}indirect(e){const{ambientOcclusion:t,irradiance:n,reflectedLight:i}=e.context;i.indirectDiffuse.addAssign(n.mul(xg({diffuseColor:Ws}))),i.indirectDiffuse.mulAssign(t)}}const cZ=new I5;class dZ extends Ka{static get type(){return"MeshToonNodeMaterial"}constructor(e){super(),this.isMeshToonNodeMaterial=!0,this.lights=!0,this.setDefaultValues(cZ),this.setValues(e)}setupLightingModel(){return new uZ}}const Y4=be(()=>{const r=he(_s.z,0,_s.x.negate()).normalize(),e=_s.cross(r);return Wt(r.dot(vs),e.dot(vs)).mul(.495).add(.5)}).once(["NORMAL","VERTEX"])().toVar("matcapUV"),fZ=new L5;class hZ extends Ka{static get type(){return"MeshMatcapNodeMaterial"}constructor(e){super(),this.isMeshMatcapNodeMaterial=!0,this.setDefaultValues(fZ),this.setValues(e)}setupVariants(e){const t=Y4;let n;e.material.matcap?n=Sh("matcap","texture").context({getUV:()=>t}):n=he(ss(.2,.8,t.y)),Ws.rgb.mulAssign(n.rgb)}}class pZ extends Qa{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(this.getNodeType(e)==="vec2"){const s=t.cos(),a=t.sin();return tE(s,a,a.negate(),s).mul(n)}else{const s=t,a=Op(Yn(1,0,0,0),Yn(0,Bd(s.x),ou(s.x).negate(),0),Yn(0,ou(s.x),Bd(s.x),0),Yn(0,0,0,1)),o=Op(Yn(Bd(s.y),0,ou(s.y),0),Yn(0,1,0,0),Yn(ou(s.y).negate(),0,Bd(s.y),0),Yn(0,0,0,1)),l=Op(Yn(Bd(s.z),ou(s.z).negate(),0,0),Yn(ou(s.z),Bd(s.z),0,0),Yn(0,0,1,0),Yn(0,0,0,1));return a.mul(o).mul(l).mul(Yn(n,1)).xyz}}}const Sx=vi(pZ).setParameterLength(2),mZ=new KC;class J4 extends Ka{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(mZ),this.setValues(e)}setupPositionView(e){const{object:t,camera:n}=e,{positionNode:i,rotationNode:s,scaleNode:a,sizeAttenuation:o}=this,l=Cf.mul(he(i||0));let u=Wt(Lc[0].xyz.length(),Lc[1].xyz.length());a!==null&&(u=u.mul(Wt(a))),n.isPerspectiveCamera&&o===!1&&(u=u.mul(l.z.negate()));let c=Pl.xy;if(t.center&&t.center.isVector2===!0){const h=cG("center","vec2",t);c=c.sub(h.sub(.5))}c=c.mul(u);const d=K(s||wI),f=Sx(c,d);return Yn(l.xy.add(f),l.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 gZ=new s1,vZ=new ct;class AZ extends J4{static get type(){return"PointsNodeMaterial"}constructor(e){super(),this.sizeNode=null,this.isPointsNodeMaterial=!0,this.setDefaultValues(gZ),this.setValues(e)}setupPositionView(){const{positionNode:e}=this;return Cf.mul(he(e||Ja)).xyz}setupVertexSprite(e){const{material:t,camera:n}=e,{rotationNode:i,scaleNode:s,sizeNode:a,sizeAttenuation:o}=this;let l=super.setupVertex(e);if(t.isNodeMaterial!==!0)return l;let u=a!==null?Wt(a):LI;u=u.mul(D3),n.isPerspectiveCamera&&o===!0&&(u=u.mul(xZ.div(po.z.negate()))),s&&s.isNode&&(u=u.mul(Wt(s)));let c=Pl.xy;if(i&&i.isNode){const d=K(i);c=Sx(c,d)}return c=c.mul(u),c=c.div(T3.div(2)),c=c.mul(l.w),l=l.add(Yn(c,0,0)),l}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 xZ=Dr(1).onFrameUpdate(function({renderer:r}){const e=r.getSize(vZ);this.value=.5*e.y});class yZ extends LE{constructor(){super(),this.shadowNode=K(1).toVar("shadowMask")}direct({lightNode:e}){e.shadowNode!==null&&this.shadowNode.mulAssign(e.shadowNode)}finish({context:e}){Ws.a.mulAssign(this.shadowNode.oneMinus()),e.outgoingLight.rgb.assign(Ws.rgb)}}const bZ=new S5;class EZ extends Ka{static get type(){return"ShadowNodeMaterial"}constructor(e){super(),this.isShadowNodeMaterial=!0,this.lights=!0,this.transparent=!0,this.setDefaultValues(bZ),this.setValues(e)}setupLightingModel(){return new yZ}}const Dx=Cd("vec3"),K4=Cd("vec3"),q4=Cd("vec3");class wZ extends null{constructor(){super()}start(e){const{material:t}=e,n=Cd("vec3"),i=Cd("vec3");cr(yx.sub(ac).length().greaterThan(H2.mul(2)),()=>{n.assign(yx),i.assign(ac)}).Else(()=>{n.assign(ac),i.assign(yx)});const s=i.sub(n),a=Dr("int").onRenderUpdate(({material:d})=>d.steps),o=s.length().div(a).toVar(),l=s.normalize().toVar(),u=K(0).toVar(),c=he(1).toVar();t.offsetNode&&u.addAssign(t.offsetNode.mul(o)),Vs(a,()=>{const d=n.add(l.mul(u)),f=sc.mul(Yn(d,1)).xyz;t.depthNode!==null&&(K4.assign(wA(eB(f.z,Bh,Mh))),e.context.sceneDepthNode=wA(t.depthNode).toVar()),e.context.positionWorld=d,e.context.shadowPositionWorld=d,e.context.positionView=f,Dx.assign(0);let h;t.scatteringNode&&(h=t.scatteringNode({positionRay:d})),super.start(e),h&&Dx.mulAssign(h);const p=Dx.mul(.01).negate().mul(o).exp();c.mulAssign(p),u.addAssign(o)}),q4.addAssign(c.saturate().oneMinus())}scatteringLight(e,t){const n=t.context.sceneDepthNode;n?cr(n.greaterThanEqual(K4),()=>{Dx.addAssign(e)}):Dx.addAssign(e)}direct({lightNode:e,lightColor:t},n){if(e.light.distance===void 0)return;const i=t.xyz.toVar();i.mulAssign(e.shadowNode),this.scatteringLight(i,n)}directRectArea({lightColor:e,lightPosition:t,halfWidth:n,halfHeight:i},s){const a=t.add(n).sub(i),o=t.sub(n).sub(i),l=t.sub(n).add(i),u=t.add(n).add(i),c=s.context.positionView,d=e.xyz.mul(PQ({P:c,p0:a,p1:o,p2:l,p3:u})).pow(1.5);this.scatteringLight(d,s)}finish(e){e.context.outgoingLight.assign(q4)}}class Mde extends null{static get type(){return"VolumeNodeMaterial"}constructor(e){super(),this.isVolumeNodeMaterial=!0,this.steps=25,this.offsetNode=null,this.scatteringNode=null,this.lights=!0,this.transparent=!0,this.side=BackSide,this.depthTest=!1,this.depthWrite=!1,this.setValues(e)}setupLightingModel(){return new wZ}}class CZ{constructor(e,t,n){this.renderer=e,this.nodes=t,this.info=n,this._context=typeof self!="undefined"?self:null,this._animationLoop=null,this._requestId=null}start(){const e=(t,n)=>{this._requestId=this._context.requestAnimationFrame(e),this.info.autoReset===!0&&this.info.reset(),this.nodes.nodeFrame.update(),this.info.frame=this.nodes.nodeFrame.frameId,this.renderer._inspector.begin(),this._animationLoop!==null&&this._animationLoop(t,n),this.renderer._inspector.finish()};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 Sd{constructor(){this.weakMaps={}}_getWeakMap(e){const t=e.length;let n=this.weakMaps[t];return n===void 0&&(n=new WeakMap,this.weakMaps[t]=n),n}get(e){let t=this._getWeakMap(e);for(let n=0;n<e.length-1;n++)if(t=t.get(e[n]),t===void 0)return;return t.get(e[e.length-1])}set(e,t){let n=this._getWeakMap(e);for(let i=0;i<e.length-1;i++){const s=e[i];n.has(s)===!1&&n.set(s,new WeakMap),n=n.get(s)}return n.set(e[e.length-1],t),this}delete(e){let t=this._getWeakMap(e);for(let n=0;n<e.length-1;n++)if(t=t.get(e[n]),t===void 0)return!1;return t.delete(e[e.length-1])}}let PZ=0;function BZ(r){const e=Object.keys(r);let t=Object.getPrototypeOf(r);for(;t;){const n=Object.getOwnPropertyDescriptors(t);for(const i in n)if(n[i]!==void 0){const s=n[i];s&&typeof s.get=="function"&&e.push(i)}t=Object.getPrototypeOf(t)}return e}class MZ{constructor(e,t,n,i,s,a,o,l,u,c){this.id=PZ++,this._nodes=e,this._geometries=t,this.renderer=n,this.object=i,this.material=s,this.scene=a,this.camera=o,this.lightsNode=l,this.context=u,this.geometry=i.geometry,this.version=s.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=c,this.clippingContextCacheKey=c!==null?c.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 this.clippingContext===null||this.clippingContext.cacheKey===this.clippingContextCacheKey?!1:(this.clippingContextCacheKey=this.clippingContext.cacheKey,!0)}get hardwareClippingPlanes(){return this.material.hardwareClipping===!0?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)}getIndirectOffset(){return this._geometries.getIndirectOffset(this)}getChainArray(){return[this.object,this.material,this.context,this.lightsNode]}setGeometry(e){this.geometry=e,this.attributes=null,this.attributesId=null}getAttributes(){if(this.attributes!==null)return this.attributes;const e=this.getNodeBuilderState().nodeAttributes,t=this.geometry,n=[],i=new Set,s={};for(const a of e){let o;if(a.node&&a.node.attribute?o=a.node.attribute:(o=t.getAttribute(a.name),s[a.name]=o.version),o===void 0)continue;n.push(o);const l=o.isInterleavedBufferAttribute?o.data:o;i.add(l)}return this.attributes=n,this.attributesId=s,this.vertexBuffers=Array.from(i.values()),n}getVertexBuffers(){return this.vertexBuffers===null&&this.getAttributes(),this.vertexBuffers}getDrawParameters(){const{object:e,material:t,geometry:n,group:i,drawRange:s}=this,a=this.drawParams||(this.drawParams={vertexCount:0,firstVertex:0,instanceCount:0,firstInstance:0}),o=this.getIndex(),l=o!==null;let u=1;if(n.isInstancedBufferGeometry===!0?u=n.instanceCount:e.count!==void 0&&(u=Math.max(0,e.count)),u===0)return null;if(a.instanceCount=u,e.isBatchedMesh===!0)return a;let c=1;t.wireframe===!0&&!e.isPoints&&!e.isLineSegments&&!e.isLine&&!e.isLineLoop&&(c=2);let d=s.start*c,f=(s.start+s.count)*c;i!==null&&(d=Math.max(d,i.start*c),f=Math.min(f,(i.start+i.count)*c));const h=n.attributes.position;let p=1/0;l?p=o.count:h!=null&&(p=h.count),d=Math.max(d,0),f=Math.min(f,p);const x=f-d;return x<0||x===1/0?null:(a.vertexCount=x,a.firstVertex=d,a)}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 s=0,a=i.length;s<a;s++){const o=i[s];t+=o.id+","}}return e.index&&(t+="index,"),t}getMaterialCacheKey(){const{object:e,material:t,renderer:n}=this;let i=t.customProgramCacheKey();for(const s of BZ(t)){if(/^(is[A-Z]|_)|^(visible|version|uuid|name|opacity|userData)$/.test(s))continue;const a=t[s];let o;if(a!==null){const l=typeof a;l==="number"?o=a!==0?"1":"0":l==="object"?(o="{",a.isTexture&&(o+=a.mapping,n.backend.isWebGPUBackend===!0&&(o+=a.magFilter,o+=a.minFilter,o+=a.wrapS,o+=a.wrapT,o+=a.wrapR)),o+="}"):o=String(a)}else o=String(a);i+=o+","}return i+=this.clippingContextCacheKey+",",e.geometry&&(i+=this.getGeometryCacheKey()),e.skeleton&&(i+=e.skeleton.bones.length+","),e.isBatchedMesh&&(i+=e._matricesTexture.uuid+",",e._colorsTexture!==null&&(i+=e._colorsTexture.uuid+",")),(e.isInstancedMesh||e.count>1||Array.isArray(e.morphTargetInfluences))&&(i+=e.uuid+","),i+=this.context.id+",",i+=e.receiveShadow+",",lA(i)}get needsGeometryUpdate(){if(this.geometry.id!==this.object.geometry.id)return!0;if(this.attributes!==null){const e=this.attributesId;for(const t in e){const n=this.geometry.getAttribute(t);if(n===void 0||e[t]!==n.id)return!0}}return!1}get needsUpdate(){return this.initialNodesCacheKey!==this.getDynamicCacheKey()||this.clippingNeedsUpdate}getDynamicCacheKey(){let e=0;return this.material.isShadowPassMaterial!==!0&&(e=this._nodes.getCacheKey(this.scene,this.lightsNode)),this.camera.isArrayCamera&&(e=uA(e,this.camera.cameras.length)),this.object.receiveShadow&&(e=uA(e,1)),e=uA(e,this.camera.id,this.renderer.contextNode.id,this.renderer.contextNode.version),e}getCacheKey(){return this.getMaterialCacheKey()+this.getDynamicCacheKey()}dispose(){this.material.removeEventListener("dispose",this.onMaterialDispose),this.geometry.removeEventListener("dispose",this.onGeometryDispose),this.onDispose()}}const bg=[];class SZ{constructor(e,t,n,i,s,a){this.renderer=e,this.nodes=t,this.geometries=n,this.pipelines=i,this.bindings=s,this.info=a,this.chainMaps={}}get(e,t,n,i,s,a,o,l){const u=this.getChainMap(l);bg[0]=e,bg[1]=t,bg[2]=a,bg[3]=s;let c=u.get(bg);return c===void 0?(c=this.createRenderObject(this.nodes,this.geometries,this.renderer,e,t,n,i,s,a,o,l),u.set(bg,c)):(c.updateClipping(o),c.needsGeometryUpdate&&c.setGeometry(e.geometry),(c.version!==t.version||c.needsUpdate)&&(c.initialCacheKey!==c.getCacheKey()?(c.dispose(),c=this.get(e,t,n,i,s,a,o,l)):c.version=t.version)),bg.length=0,c}getChainMap(e="default"){return this.chainMaps[e]||(this.chainMaps[e]=new Sd)}dispose(){this.chainMaps={}}createRenderObject(e,t,n,i,s,a,o,l,u,c,d){const f=this.getChainMap(d),h=new MZ(e,t,n,i,s,a,o,l,u,c);return h.onDispose=()=>{this.pipelines.delete(h),this.bindings.deleteForRender(h),this.nodes.delete(h),f.delete(h.getChainArray())},h}}class Wp{constructor(){this.data=new WeakMap}get(e){let t=this.data.get(e);return t===void 0&&(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 zc={VERTEX:1,INDEX:2,STORAGE:3,INDIRECT:4},Qp=16,DZ=211,TZ=212;class IZ extends Wp{constructor(e){super(),this.backend=e}delete(e){const t=super.delete(e);return t!==null&&this.backend.destroyAttribute(e),t}update(e,t){const n=this.get(e);if(n.version===void 0)t===zc.VERTEX?this.backend.createAttribute(e):t===zc.INDEX?this.backend.createIndexAttribute(e):t===zc.STORAGE?this.backend.createStorageAttribute(e):t===zc.INDIRECT&&this.backend.createIndirectStorageAttribute(e),n.version=this._getBufferAttribute(e).version;else{const i=this._getBufferAttribute(e);(n.version<i.version||i.usage===k)&&(this.backend.updateAttribute(e),n.version=i.version)}}_getBufferAttribute(e){return e.isInterleavedBufferAttribute&&(e=e.data),e}}function _4(r){return r.index!==null?r.index.version:r.attributes.position.version}function $4(r){const e=[],t=r.index,n=r.attributes.position;if(t!==null){const s=t.array;for(let a=0,o=s.length;a<o;a+=3){const l=s[a+0],u=s[a+1],c=s[a+2];e.push(l,u,u,c,c,l)}}else{const s=n.array;for(let a=0,o=s.length/3-1;a<o;a+=3){const l=a+0,u=a+1,c=a+2;e.push(l,u,u,c,c,l)}}const i=new(gi(e)?GC:XC)(e,1);return i.version=_4(r),i}class NZ extends Wp{constructor(e,t){super(),this.attributes=e,this.info=t,this.wireframes=new WeakMap,this.attributeCall=new WeakMap,this._geometryDisposeListeners=new Map}has(e){const t=e.geometry;return super.has(t)&&this.get(t).initialized===!0}updateForRender(e){this.has(e)===!1&&this.initGeometry(e),this.updateAttributes(e)}initGeometry(e){const t=e.geometry,n=this.get(t);n.initialized=!0,this.info.memory.geometries++;const i=()=>{this.info.memory.geometries--;const s=t.index,a=e.getAttributes();s!==null&&this.attributes.delete(s);for(const l of a)this.attributes.delete(l);const o=this.wireframes.get(t);o!==void 0&&this.attributes.delete(o),t.removeEventListener("dispose",i),this._geometryDisposeListeners.delete(t)};t.addEventListener("dispose",i),this._geometryDisposeListeners.set(t,i)}updateAttributes(e){const t=e.getAttributes();for(const s of t)s.isStorageBufferAttribute||s.isStorageInstancedBufferAttribute?this.updateAttribute(s,zc.STORAGE):this.updateAttribute(s,zc.VERTEX);const n=this.getIndex(e);n!==null&&this.updateAttribute(n,zc.INDEX);const i=e.geometry.indirect;i!==null&&this.updateAttribute(i,zc.INDIRECT)}updateAttribute(e,t){const n=this.info.render.calls;e.isInterleavedBufferAttribute?this.attributeCall.get(e)===void 0?(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}getIndirectOffset(e){return e.geometry.indirectOffset}getIndex(e){const{geometry:t,material:n}=e;let i=t.index;if(n.wireframe===!0){const s=this.wireframes;let a=s.get(t);a===void 0?(a=$4(t),s.set(t,a)):a.version!==_4(t)&&(this.attributes.delete(a),a=$4(t),s.set(t,a)),i=a}return i}dispose(){for(const[e,t]of this._geometryDisposeListeners.entries())e.removeEventListener("dispose",t);this._geometryDisposeListeners.clear()}}class FZ{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):rt("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 e9{constructor(e){this.cacheKey=e,this.usedTimes=0}}class RZ extends e9{constructor(e,t,n){super(e),this.vertexProgram=t,this.fragmentProgram=n}}class LZ extends e9{constructor(e,t){super(e),this.computeProgram=t,this.isComputePipeline=!0}}let OZ=0;class CB{constructor(e,t,n,i=null,s=null){this.id=OZ++,this.code=e,this.stage=t,this.name=n,this.transforms=i,this.attributes=s,this.usedTimes=0}}class zZ extends Wp{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 s=i.pipeline;s&&(s.usedTimes--,s.computeProgram.usedTimes--);const a=this.nodes.getForCompute(e);let o=this.programs.compute.get(a.computeShader);o===void 0&&(s&&s.computeProgram.usedTimes===0&&this._releaseProgram(s.computeProgram),o=new CB(a.computeShader,"compute",e.name,a.transforms,a.nodeAttributes),this.programs.compute.set(a.computeShader,o),n.createProgram(o));const l=this._getComputeCacheKey(e,o);let u=this.caches.get(l);u===void 0&&(s&&s.usedTimes===0&&this._releasePipeline(s),u=this._getComputePipeline(e,o,l,t)),u.usedTimes++,o.usedTimes++,i.version=e.version,i.pipeline=u}return i.pipeline}getForRender(e,t=null){const{backend:n}=this,i=this.get(e);if(this._needsRenderUpdate(e)){const s=i.pipeline;s&&(s.usedTimes--,s.vertexProgram.usedTimes--,s.fragmentProgram.usedTimes--);const a=e.getNodeBuilderState(),o=e.material?e.material.name:"";let l=this.programs.vertex.get(a.vertexShader);l===void 0&&(s&&s.vertexProgram.usedTimes===0&&this._releaseProgram(s.vertexProgram),l=new CB(a.vertexShader,"vertex",o),this.programs.vertex.set(a.vertexShader,l),n.createProgram(l));let u=this.programs.fragment.get(a.fragmentShader);u===void 0&&(s&&s.fragmentProgram.usedTimes===0&&this._releaseProgram(s.fragmentProgram),u=new CB(a.fragmentShader,"fragment",o),this.programs.fragment.set(a.fragmentShader,u),n.createProgram(u));const c=this._getRenderCacheKey(e,l,u);let d=this.caches.get(c);d===void 0?(s&&s.usedTimes===0&&this._releasePipeline(s),d=this._getRenderPipeline(e,l,u,c,t)):e.pipeline=d,d.usedTimes++,l.usedTimes++,u.usedTimes++,i.pipeline=d}return i.pipeline}delete(e){const t=this.get(e).pipeline;return t&&(t.usedTimes--,t.usedTimes===0&&this._releasePipeline(t),t.isComputePipeline?(t.computeProgram.usedTimes--,t.computeProgram.usedTimes===0&&this._releaseProgram(t.computeProgram)):(t.fragmentProgram.usedTimes--,t.vertexProgram.usedTimes--,t.vertexProgram.usedTimes===0&&this._releaseProgram(t.vertexProgram),t.fragmentProgram.usedTimes===0&&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 s=this.caches.get(n);return s===void 0&&(s=new LZ(n,t),this.caches.set(n,s),this.backend.createComputePipeline(s,i)),s}_getRenderPipeline(e,t,n,i,s){i=i||this._getRenderCacheKey(e,t,n);let a=this.caches.get(i);return a===void 0&&(a=new RZ(i,t,n),this.caches.set(i,a),e.pipeline=a,this.backend.createRenderPipeline(e,s)),a}_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 t.pipeline===void 0||t.version!==e.version}_needsRenderUpdate(e){return this.get(e).pipeline===void 0||this.backend.needsRenderUpdate(e)}}class HZ extends Wp{constructor(e,t,n,i,s,a){super(),this.backend=e,this.textures=n,this.pipelines=s,this.attributes=i,this.nodes=t,this.info=a,this.pipelines.bindings=this}getForRender(e){const t=e.getBindings();for(const n of t){const i=this.get(n);i.bindGroup===void 0&&(this._init(n),this.backend.createBindings(n,t,0),i.bindGroup=n)}return t}getForCompute(e){const t=this.nodes.getForCompute(e).bindings;for(const n of t){const i=this.get(n);i.bindGroup===void 0&&(this._init(n),this.backend.createBindings(n,t,0),i.bindGroup=n)}return t}updateForCompute(e){this._updateBindings(this.getForCompute(e))}updateForRender(e){this._updateBindings(this.getForRender(e))}deleteForCompute(e){const t=this.nodes.getForCompute(e).bindings;for(const n of t)this.backend.deleteBindGroupData(n),this.delete(n)}deleteForRender(e){const t=e.getBindings();for(const n of t)this.backend.deleteBindGroupData(n),this.delete(n)}_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.isSampler)this.textures.updateSampler(t.texture);else if(t.isStorageBuffer){const n=t.attribute,i=n.isIndirectStorageBufferAttribute?zc.INDIRECT:zc.STORAGE;this.attributes.update(n,i)}}_update(e,t){const{backend:n}=this;let i=!1,s=!0,a=0,o=0;for(const l of e.bindings)if(this.nodes.updateGroup(l)!==!1){if(l.isStorageBuffer){const c=l.attribute,d=c.isIndirectStorageBufferAttribute?zc.INDIRECT:zc.STORAGE;this.attributes.update(c,d)}if(l.isUniformBuffer)l.update()&&n.updateBinding(l);else if(l.isSampledTexture){const c=l.update(),d=l.texture,f=this.textures.get(d);if(c&&(this.textures.updateTexture(d),l.generation!==f.generation&&(l.generation=f.generation,i=!0,s=!1)),n.get(d).externalTexture!==void 0||f.isDefaultTexture?s=!1:(a=a*10+d.id,o+=d.version),d.isStorageTexture===!0&&d.mipmapsAutoUpdate===!0){const p=this.get(d);l.store===!0?p.needsMipmap=!0:this.textures.needsMipmaps(d)&&p.needsMipmap===!0&&(this.backend.generateMipmaps(d),p.needsMipmap=!1)}}else if(l.isSampler&&l.update()){const d=this.textures.updateSampler(l.texture);l.samplerKey!==d&&(l.samplerKey=d,i=!0,s=!1)}}i===!0&&this.backend.updateBindings(e,t,s?a:0,o)}}function UZ(r,e){return r.groupOrder!==e.groupOrder?r.groupOrder-e.groupOrder:r.renderOrder!==e.renderOrder?r.renderOrder-e.renderOrder:r.z!==e.z?r.z-e.z:r.id-e.id}function t9(r,e){return r.groupOrder!==e.groupOrder?r.groupOrder-e.groupOrder:r.renderOrder!==e.renderOrder?r.renderOrder-e.renderOrder:r.z!==e.z?e.z-r.z:r.id-e.id}function n9(r){return(r.transmission>0||r.transmissionNode&&r.transmissionNode.isNode)&&r.side===Xs&&r.forceSinglePass===!1}class kZ{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,s,a,o){let l=this.renderItems[this.renderItemsIndex];return l===void 0?(l={id:e.id,object:e,geometry:t,material:n,groupOrder:i,renderOrder:e.renderOrder,z:s,group:a,clippingContext:o},this.renderItems[this.renderItemsIndex]=l):(l.id=e.id,l.object=e,l.geometry=t,l.material=n,l.groupOrder=i,l.renderOrder=e.renderOrder,l.z=s,l.group=a,l.clippingContext=o),this.renderItemsIndex++,l}push(e,t,n,i,s,a,o){const l=this.getNextRenderItem(e,t,n,i,s,a,o);e.occlusionTest===!0&&this.occlusionQueryCount++,n.transparent===!0||n.transmission>0||n.transmissionNode&&n.transmissionNode.isNode||n.backdropNode&&n.backdropNode.isNode?(n9(n)&&this.transparentDoublePass.push(l),this.transparent.push(l)):this.opaque.push(l)}unshift(e,t,n,i,s,a,o){const l=this.getNextRenderItem(e,t,n,i,s,a,o);n.transparent===!0||n.transmission>0||n.transmissionNode&&n.transmissionNode.isNode||n.backdropNode&&n.backdropNode.isNode?(n9(n)&&this.transparentDoublePass.unshift(l),this.transparent.unshift(l)):this.opaque.unshift(l)}pushBundle(e){this.bundles.push(e)}pushLight(e){this.lightsArray.push(e)}sort(e,t){this.opaque.length>1&&this.opaque.sort(e||UZ),this.transparentDoublePass.length>1&&this.transparentDoublePass.sort(t||t9),this.transparent.length>1&&this.transparent.sort(t||t9)}finish(){this.lightsNode.setLights(this.lightsArray);for(let e=this.renderItemsIndex,t=this.renderItems.length;e<t;e++){const n=this.renderItems[e];if(n.id===null)break;n.id=null,n.object=null,n.geometry=null,n.material=null,n.groupOrder=null,n.renderOrder=null,n.z=null,n.group=null,n.clippingContext=null}}}const Tx=[];class VZ{constructor(e){this.lighting=e,this.lists=new Sd}get(e,t){const n=this.lists;Tx[0]=e,Tx[1]=t;let i=n.get(Tx);return i===void 0&&(i=new kZ(this.lighting,e,t),n.set(Tx,i)),Tx.length=0,i}dispose(){this.lists=new Sd}}let jZ=0;class XZ{constructor(){this.id=jZ++,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 Ei,this.scissor=!1,this.scissorValue=new Ei,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 r9(this)}}function r9(r){const{textures:e,activeCubeFace:t,activeMipmapLevel:n}=r,i=[t,n];for(const s of e)i.push(s.id);return ag(i)}const BA=[],GZ=new R0,WZ=new jy;class QZ{constructor(){this.chainMaps={}}get(e,t,n=null,i=null){BA[0]=e,BA[1]=t,i!==null&&(BA[2]=i);let s;if(n===null)s="default";else{const l=n.texture.format;s=`${n.textures.length}:${l}:${n.samples}:${n.depthBuffer}:${n.stencilBuffer}`}const a=this._getChainMap(s);let o=a.get(BA);return o===void 0&&(o=new XZ,a.set(BA,o)),BA.length=0,n!==null&&(o.sampleCount=n.samples===0?1:n.samples),o}getForClear(e=null){return this.get(GZ,WZ,e)}_getChainMap(e){return this.chainMaps[e]||(this.chainMaps[e]=new Sd)}dispose(){this.chainMaps={}}}const ZZ=new J;class YZ extends Wp{constructor(e,t,n){super(),this.renderer=e,this.backend=t,this.info=n}updateRenderTarget(e,t=0){const n=this.get(e),i=e.samples===0?1:e.samples,s=n.depthTextureMips||(n.depthTextureMips={}),a=e.textures,o=this.getSize(a[0]),l=o.width>>t,u=o.height>>t;let c=e.depthTexture||s[t];const d=e.depthBuffer===!0||e.stencilBuffer===!0;let f=!1;c===void 0&&d&&(c=new Vl,c.format=e.stencilBuffer?vl:jo,c.type=e.stencilBuffer?Ll:Ls,c.image.width=l,c.image.height=u,c.image.depth=o.depth,c.renderTarget=e,c.isArrayTexture=e.multiview===!0&&o.depth>1,s[t]=c),(n.width!==o.width||o.height!==n.height)&&(f=!0,c&&(c.needsUpdate=!0,c.image.width=l,c.image.height=u,c.image.depth=c.isArrayTexture?c.image.depth:1)),n.width=o.width,n.height=o.height,n.textures=a,n.depthTexture=c||null,n.depth=e.depthBuffer,n.stencil=e.stencilBuffer,n.renderTarget=e,n.sampleCount!==i&&(f=!0,c&&(c.needsUpdate=!0),n.sampleCount=i);const h={sampleCount:i};if(e.isXRRenderTarget!==!0){for(let p=0;p<a.length;p++){const x=a[p];f&&(x.needsUpdate=!0),this.updateTexture(x,h)}c&&this.updateTexture(c,h)}n.initialized!==!0&&(n.initialized=!0,n.onDispose=()=>{this._destroyRenderTarget(e)},e.addEventListener("dispose",n.onDispose))}updateTexture(e,t={}){const n=this.get(e);if(n.initialized===!0&&n.version===e.version)return;const i=e.isRenderTargetTexture||e.isDepthTexture||e.isFramebufferTexture,s=this.backend;if(i&&n.initialized===!0&&s.destroyTexture(e),e.isFramebufferTexture){const u=this.renderer.getRenderTarget();u?e.type=u.texture.type:e.type=fa}const{width:a,height:o,depth:l}=this.getSize(e);if(t.width=a,t.height=o,t.depth=l,t.needsMipmaps=this.needsMipmaps(e),t.levels=t.needsMipmaps?this.getMipLevels(e,a,o):1,e.isCubeTexture&&e.mipmaps.length>0&&t.levels++,i||e.isStorageTexture===!0||e.isExternalTexture===!0)s.createTexture(e,t),n.generation=e.version;else if(e.version>0){const u=e.image;if(u===void 0)ze("Renderer: Texture marked for update but image is undefined.");else if(u.complete===!1)ze("Renderer: Texture marked for update but image is incomplete.");else{if(e.images){const d=[];for(const f of e.images)d.push(f);t.images=d}else t.image=u;(n.isDefaultTexture===void 0||n.isDefaultTexture===!0)&&(s.createTexture(e,t),n.isDefaultTexture=!1,n.generation=e.version),e.source.dataReady===!0&&s.updateTexture(e,t);const c=e.isStorageTexture===!0&&e.mipmapsAutoUpdate===!1;t.needsMipmaps&&e.mipmaps.length===0&&!c&&s.generateMipmaps(e),e.onUpdate&&e.onUpdate(e)}}else s.createDefaultTexture(e),n.isDefaultTexture=!0,n.generation=e.version;n.initialized!==!0&&(n.initialized=!0,n.generation=e.version,this.info.memory.textures++,e.isVideoTexture&&$r.enabled===!0&&$r.getTransfer(e.colorSpace)!==$n&&ze("WebGPURenderer: Video textures must use a color space with a sRGB transfer function, e.g. SRGBColorSpace."),n.onDispose=()=>{this._destroyTexture(e)},e.addEventListener("dispose",n.onDispose)),n.version=e.version}updateSampler(e){return this.backend.updateSampler(e)}getSize(e,t=ZZ){let n=e.images?e.images[0]:e.image;return n?(n.image!==void 0&&(n=n.image),typeof HTMLVideoElement!="undefined"&&n instanceof HTMLVideoElement?(t.width=n.videoWidth||1,t.height=n.videoHeight||1,t.depth=1):typeof VideoFrame!="undefined"&&n instanceof VideoFrame?(t.width=n.displayWidth||1,t.height=n.displayHeight||1,t.depth=1):(t.width=n.width||1,t.height=n.height||1,t.depth=e.isCubeTexture?6:n.depth||1)):t.width=t.height=t.depth=1,t}getMipLevels(e,t,n){let i;return e.mipmaps.length>0?i=e.mipmaps.length:e.isCompressedTexture===!0?i=1:i=Math.floor(Math.log2(Math.max(t,n)))+1,i}needsMipmaps(e){return e.generateMipmaps===!0||e.mipmaps.length>0}_destroyRenderTarget(e){if(this.has(e)===!0){const t=this.get(e),n=t.textures,i=t.depthTexture;e.removeEventListener("dispose",t.onDispose);for(let s=0;s<n.length;s++)this._destroyTexture(n[s]);i&&this._destroyTexture(i),this.delete(e),this.backend.delete(e)}}_destroyTexture(e){if(this.has(e)===!0){const t=this.get(e);e.removeEventListener("dispose",t.onDispose);const n=t.isDefaultTexture;this.backend.destroyTexture(e,n),this.delete(e),this.info.memory.textures--}}}class PB extends Vn{constructor(e,t,n,i=1){super(e,t,n),this.a=i}set(e,t,n,i=1){return this.a=i,super.set(e,t,n)}copy(e){return e.a!==void 0&&(this.a=e.a),super.copy(e)}clone(){return new this.constructor(this.r,this.g,this.b,this.a)}}class i9 extends Os{static get type(){return"ParameterNode"}constructor(e,t=null){super(e,t),this.isParameterNode=!0}getMemberType(e,t){const n=this.getNodeType(e),i=e.getStructTypeNode(n);let s;return i!==null?s=i.getMemberType(e,t):(rt(`TSL: Member "${t}" not found in struct "${n}".`),s="float"),s}getHash(){return this.uuid}generate(){return this.name}}const JZ=(r,e)=>new i9(r,e);class KZ extends ar{static get type(){return"StackNode"}constructor(e=null){super(),this.nodes=[],this.outputNode=null,this.parent=e,this._currentCond=null,this._expressionNode=null,this._currentNode=null,this.isStackNode=!0}getElementType(e){return this.hasOutput?this.outputNode.getElementType(e):"void"}getNodeType(e){return this.hasOutput?this.outputNode.getNodeType(e):"void"}getMemberType(e,t){return this.hasOutput?this.outputNode.getMemberType(e,t):"void"}addToStack(e,t=this.nodes.length){return e.isNode!==!0?(rt("TSL: Invalid node added to stack."),this):(this.nodes.splice(t,0,e),this)}addToStackBefore(e){const t=this._currentNode?this.nodes.indexOf(this._currentNode):0;return this.addToStack(e,t)}If(e,t){const n=new cA(t);return this._currentCond=Cl(e,n),this.addToStack(this._currentCond)}ElseIf(e,t){const n=new cA(t),i=Cl(e,n);return this._currentCond.elseNode=i,this._currentCond=i,this}Else(e){return this._currentCond.elseNode=new cA(e),this}Switch(e){return this._expressionNode=wn(e),this}Case(...e){const t=[];if(e.length>=2)for(let o=0;o<e.length-1;o++)t.push(this._expressionNode.equal(wn(e[o])));else rt("TSL: Invalid parameter length. Case() requires at least two parameters.");const n=e[e.length-1],i=new cA(n);let s=t[0];for(let o=1;o<t.length;o++)s=s.or(t[o]);const a=Cl(s,i);return this._currentCond===null?(this._currentCond=a,this.addToStack(this._currentCond)):(this._currentCond.elseNode=a,this._currentCond=a,this)}Default(e){return this.Else(e),this}setup(e){const t=e.getNodeProperties(this);let n=0;for(const i of this.getChildren())i.isVarNode&&i.isIntent(e)&&i.isAssign(e)!==!0||(t["node"+n++]=i);return t.outputNode||null}get hasOutput(){return this.outputNode&&this.outputNode.isNode}build(e,...t){const n=XP(),i=e.buildStage;cx(this),e.setActiveStack(this);const s=u=>{if(this._currentNode=u,!(u.isVarNode&&u.isIntent(e)&&u.isAssign(e)!==!0)){if(i==="setup")u.build(e);else if(i==="analyze")u.build(e,this);else if(i==="generate"){const c=e.getDataFromNode(u,"any").stages,d=c&&c[e.shaderStage];if(u.isVarNode&&d&&d.length===1&&d[0]&&d[0].isStackNode)return;u.build(e,"void")}}},a=[...this.nodes];for(const u of a)s(u);this._currentNode=null;const o=this.nodes.filter(u=>a.indexOf(u)===-1);for(const u of o)s(u);let l;return this.hasOutput?l=this.outputNode.build(e,...t):l=super.build(e,...t),cx(n),e.removeActiveStack(this),l}}const XE=vi(KZ).setParameterLength(0,1);function qZ(r){return Object.entries(r).map(([e,t])=>typeof t=="string"?{name:e,type:t,atomic:!1}:{name:e,type:t.type,atomic:t.atomic||!1})}class _Z extends ar{static get type(){return"StructTypeNode"}constructor(e,t=null){super("struct"),this.membersLayout=qZ(e),this.name=t,this.isStructLayoutNode=!0}getLength(){const e=Float32Array.BYTES_PER_ELEMENT;let t=1,n=0;for(const i of this.membersLayout){const s=i.type,a=ZT(s),o=YT(s)/e;t=Math.max(t,o);const u=n%t%o;u!==0&&(n+=o-u),n+=a}return Math.ceil(n/t)*t}getMemberType(e,t){const n=this.membersLayout.find(i=>i.name===t);return n?n.type:"void"}getNodeType(e){return e.getStructTypeFromNode(this,this.membersLayout,this.name).name}setup(e){e.getStructTypeFromNode(this,this.membersLayout,this.name),e.addInclude(this)}generate(e){return this.getNodeType(e)}}class $Z extends ar{static get type(){return"StructNode"}constructor(e,t){super("vec3"),this.structTypeNode=e,this.values=t,this.isStructNode=!0}getNodeType(e){return this.structTypeNode.getNodeType(e)}getMemberType(e,t){return this.structTypeNode.getMemberType(e,t)}generate(e){const t=e.getVarFromNode(this),n=t.type,i=e.getPropertyName(t);return e.addLineFlowCode(`${i} = ${e.generateStruct(n,this.structTypeNode.membersLayout,this.values)}`,this),t.name}}const eY=(r,e=null)=>{const t=new _Z(r,e),n=(...i)=>{let s=null;if(i.length>0)if(i[0].isNode){s={};const a=Object.keys(r);for(let o=0;o<i.length;o++)s[a[o]]=i[o]}else s=i[0];return new $Z(t,s)};return n.layout=t,n.isStruct=!0,n};class s9 extends ar{static get type(){return"OutputStructNode"}constructor(...e){super(),this.members=e,this.isOutputStructNode=!0}getNodeType(e){const t=e.getNodeProperties(this);if(t.membersLayout===void 0){const n=this.members,i=[];for(let s=0;s<n.length;s++){const a="m"+s,o=n[s].getNodeType(e);i.push({name:a,type:o,index:s})}t.membersLayout=i,t.structType=e.getOutputStructTypeFromNode(this,t.membersLayout)}return t.structType.name}generate(e){const t=e.getOutputStructName(),n=this.members,i=t!==""?t+".":"";for(let s=0;s<n.length;s++){const a=n[s].build(e);e.addLineFlowCode(`${i}m${s} = ${a}`,this)}return t}}const tY=vi(s9);function a9(r,e){for(let t=0;t<r.length;t++)if(r[t].name===e)return t;return-1}class nY extends s9{static get type(){return"MRTNode"}constructor(e){super(),this.outputNodes=e,this.isMRTNode=!0}has(e){return this.outputNodes[e]!==void 0}get(e){return this.outputNodes[e]}merge(e){const t=ba(ba({},this.outputNodes),e.outputNodes);return o9(t)}setup(e){const t=this.outputNodes,n=e.renderer.getRenderTarget(),i=[],s=n.textures;for(const a in t){const o=a9(s,a);i[o]=Yn(t[a])}return this.members=i,super.setup(e)}}const o9=vi(nY);class Ix extends Qa{static get type(){return"BitcastNode"}constructor(e,t,n=null){super(),this.valueNode=e,this.conversionType=t,this.inputType=n,this.isBitcastNode=!0}getNodeType(e){if(this.inputType!==null){const t=this.valueNode.getNodeType(e),n=e.getTypeLength(t);return e.getTypeFromLength(n,this.conversionType)}return this.conversionType}generate(e){const t=this.getNodeType(e);let n="";if(this.inputType!==null){const i=this.valueNode.getNodeType(e);n=e.getTypeLength(i)===1?this.inputType:e.changeComponentType(i,this.inputType)}else n=this.valueNode.getNodeType(e);return`${e.getBitcastMethod(t,n)}( ${this.valueNode.build(e,n)} )`}}const l9=en(Ix).setParameterLength(2),rY=r=>new Ix(r,"int","float"),u9=r=>new Ix(r,"uint","float"),iY=r=>new Ix(r,"float","int"),sY=r=>new Ix(r,"float","uint"),GE={};class lc extends Ve{static get type(){return"BitcountNode"}constructor(e,t){super(e,t),this.isBitcountNode=!0}_resolveElementType(e,t,n){n==="int"?t.assign(l9(e,"uint")):t.assign(e)}_returnDataNode(e){switch(e){case"uint":return Ut;case"int":return ce;case"uvec2":return GP;case"uvec3":return cg;case"uvec4":return YP;case"ivec2":return Fo;case"ivec3":return WP;case"ivec4":return ZP}}_createTrailingZerosBaseLayout(e,t){const n=this._returnDataNode(t);return be(([s])=>{const a=Ut(0);this._resolveElementType(s,a,t);const o=K(a.bitAnd(l3(a))),u=u9(o).shiftRight(23).sub(127);return n(u)}).setLayout({name:e,type:t,inputs:[{name:"value",type:t}]})}_createLeadingZerosBaseLayout(e,t){const n=this._returnDataNode(t);return be(([s])=>{cr(s.equal(Ut(0)),()=>Ut(32));const a=Ut(0),o=Ut(0);return this._resolveElementType(s,a,t),cr(a.shiftRight(16).equal(0),()=>{o.addAssign(16),a.shiftLeftAssign(16)}),cr(a.shiftRight(24).equal(0),()=>{o.addAssign(8),a.shiftLeftAssign(8)}),cr(a.shiftRight(28).equal(0),()=>{o.addAssign(4),a.shiftLeftAssign(4)}),cr(a.shiftRight(30).equal(0),()=>{o.addAssign(2),a.shiftLeftAssign(2)}),cr(a.shiftRight(31).equal(0),()=>{o.addAssign(1)}),n(o)}).setLayout({name:e,type:t,inputs:[{name:"value",type:t}]})}_createOneBitsBaseLayout(e,t){const n=this._returnDataNode(t);return be(([s])=>{const a=Ut(0);this._resolveElementType(s,a,t),a.assign(a.sub(a.shiftRight(Ut(1)).bitAnd(Ut(1431655765)))),a.assign(a.bitAnd(Ut(858993459)).add(a.shiftRight(Ut(2)).bitAnd(Ut(858993459))));const o=a.add(a.shiftRight(Ut(4))).bitAnd(Ut(252645135)).mul(Ut(16843009)).shiftRight(Ut(24));return n(o)}).setLayout({name:e,type:t,inputs:[{name:"value",type:t}]})}_createMainLayout(e,t,n,i){const s=this._returnDataNode(t);return be(([o])=>{if(n===1)return s(i(o));{const l=s(0),u=["x","y","z","w"];for(let c=0;c<n;c++){const d=u[c];l[d].assign(i(o[d]))}return l}}).setLayout({name:e,type:t,inputs:[{name:"value",type:t}]})}setup(e){const{method:t,aNode:n}=this,{renderer:i}=e;if(i.backend.isWebGPUBackend)return super.setup(e);const s=this.getInputType(e),a=e.getElementType(s),o=e.getTypeLength(s),l=`${t}_base_${a}`,u=`${t}_${s}`;let c=GE[l];if(c===void 0){switch(t){case lc.COUNT_LEADING_ZEROS:{c=this._createLeadingZerosBaseLayout(l,a);break}case lc.COUNT_TRAILING_ZEROS:{c=this._createTrailingZerosBaseLayout(l,a);break}case lc.COUNT_ONE_BITS:{c=this._createOneBitsBaseLayout(l,a);break}}GE[l]=c}let d=GE[u];return d===void 0&&(d=this._createMainLayout(u,s,o,c),GE[u]=d),be(()=>d(n))()}}lc.COUNT_TRAILING_ZEROS="countTrailingZeros",lc.COUNT_LEADING_ZEROS="countLeadingZeros",lc.COUNT_ONE_BITS="countOneBits";const aY=en(lc,lc.COUNT_TRAILING_ZEROS).setParameterLength(1),oY=en(lc,lc.COUNT_LEADING_ZEROS).setParameterLength(1),lY=en(lc,lc.COUNT_ONE_BITS).setParameterLength(1),uY=be(([r])=>{const e=r.toUint().mul(747796405).add(2891336453),t=e.shiftRight(e.shiftRight(28).add(4)).bitXor(e).mul(277803737);return t.shiftRight(22).bitXor(t).toFloat().mul(1/gS(2,32))}),BB=(r,e)=>Fc(Ai(4,r.mul(us(1,r))),e),cY=(r,e)=>r.lessThan(.5)?BB(r.mul(2),e).div(2):us(1,BB(Ai(us(1,r),2),e).div(2)),dY=(r,e,t)=>Fc(rc(Fc(r,e),wo(Fc(r,e),Fc(us(1,r),t))),1/e),fY=(r,e)=>ou(cE.mul(e.mul(r).sub(1))).div(cE.mul(e.mul(r).sub(1)));class MB extends Qa{static get type(){return"PackFloatNode"}constructor(e,t){super(),this.vectorNode=t,this.encoding=e,this.isPackFloatNode=!0}getNodeType(){return"uint"}generate(e){const t=this.vectorNode.getNodeType(e);return`${e.getFloatPackingMethod(this.encoding)}(${this.vectorNode.build(e,t)})`}}const hY=en(MB,"snorm").setParameterLength(1),pY=en(MB,"unorm").setParameterLength(1),mY=en(MB,"float16").setParameterLength(1);class SB extends Qa{static get type(){return"UnpackFloatNode"}constructor(e,t){super(),this.uintNode=t,this.encoding=e,this.isUnpackFloatNode=!0}getNodeType(){return"vec2"}generate(e){const t=this.uintNode.getNodeType(e);return`${e.getFloatUnpackingMethod(this.encoding)}(${this.uintNode.build(e,t)})`}}const gY=en(SB,"snorm").setParameterLength(1),vY=en(SB,"unorm").setParameterLength(1),AY=en(SB,"float16").setParameterLength(1),Th=be(([r])=>r.fract().sub(.5).abs()).setLayout({name:"tri",type:"float",inputs:[{name:"x",type:"float"}]}),xY=be(([r])=>he(Th(r.z.add(Th(r.y.mul(1)))),Th(r.z.add(Th(r.x.mul(1)))),Th(r.y.add(Th(r.x.mul(1)))))).setLayout({name:"tri3",type:"vec3",inputs:[{name:"p",type:"vec3"}]}),yY=be(([r,e,t])=>{const n=he(r).toVar(),i=K(1.4).toVar(),s=K(0).toVar(),a=he(n).toVar();return Vs({start:K(0),end:K(3),type:"float",condition:"<="},()=>{const o=he(xY(a.mul(2))).toVar();n.addAssign(o.add(t.mul(K(.1).mul(e)))),a.mulAssign(1.8),i.mulAssign(1.5),n.mulAssign(1.2);const l=K(Th(n.z.add(Th(n.x.add(Th(n.y)))))).toVar();s.addAssign(l.div(i)),a.addAssign(.14)}),s}).setLayout({name:"triNoise3D",type:"float",inputs:[{name:"position",type:"vec3"},{name:"speed",type:"float"},{name:"time",type:"float"}]});class bY extends ar{static get type(){return"FunctionOverloadingNode"}constructor(e=[],...t){super(),this.functionNodes=e,this.parametersNodes=t,this._candidateFn=null,this.global=!0}getNodeType(e){return this.getCandidateFn(e).shaderNode.layout.type}getCandidateFn(e){const t=this.parametersNodes;let n=this._candidateFn;if(n===null){let i=null,s=-1;for(const a of this.functionNodes){const l=a.shaderNode.layout;if(l===null)throw new Error("FunctionOverloadingNode: FunctionNode must be a layout.");const u=l.inputs;if(t.length===u.length){let c=0;for(let d=0;d<t.length;d++){const f=t[d],h=u[d];f.getNodeType(e)===h.type&&c++}c>s&&(i=a,s=c)}}this._candidateFn=n=i}return n}setup(e){return this.getCandidateFn(e)(...this.parametersNodes)}}const EY=vi(bY),Bl=r=>(...e)=>EY(r,...e),MA=Dr(0).setGroup(Rr).onRenderUpdate(r=>r.time),wY=Dr(0).setGroup(Rr).onRenderUpdate(r=>r.deltaTime),c9=Dr(0,"uint").setGroup(Rr).onRenderUpdate(r=>r.frameId),CY=(r=MA)=>r.add(.75).mul(Math.PI*2).sin().mul(.5).add(.5),PY=(r=MA)=>r.fract().round(),BY=(r=MA)=>r.add(.5).fract().mul(2).sub(1).abs(),MY=(r=MA)=>r.fract();function SY(r,e=null){return bh(e,{getUV:r})}const DY=be(([r,e,t=Wt(.5)])=>Sx(r.sub(t),e).add(t)),TY=be(([r,e,t=Wt(.5)])=>{const n=r.sub(t),i=n.dot(n),a=i.mul(i).mul(e);return r.add(n.mul(a))}),IY=be(({position:r=null,horizontal:e=!0,vertical:t=!1})=>{let n;r!==null?(n=Lc.toVar(),n[3][0]=r.x,n[3][1]=r.y,n[3][2]=r.z):n=Lc;const i=sc.mul(n);return lx(e)&&(i[0][0]=Lc[0].length(),i[0][1]=0,i[0][2]=0),lx(t)&&(i[1][0]=0,i[1][1]=Lc[1].length(),i[1][2]=0),i[2][0]=0,i[2][1]=0,i[2][2]=1,uu.mul(i).mul(Ja)}),NY=be(([r=null])=>{const e=wA();return wA($3(r)).sub(e).lessThan(0).select(Ph,r)});class FY extends ar{static get type(){return"SpriteSheetUVNode"}constructor(e,t=Qs(),n=K(0)){super("vec2"),this.countNode=e,this.uvNode=t,this.frameNode=n}setup(){const{frameNode:e,uvNode:t,countNode:n}=this,{width:i,height:s}=n,a=e.mod(i.mul(s)).floor(),o=a.mod(i),l=s.sub(a.add(1).div(i).ceil()),u=n.reciprocal(),c=Wt(o,l);return t.add(c).mul(u)}}const RY=vi(FY).setParameterLength(3),d9=be(([r,e=null,t=null,n=K(1),i=Ja,s=Bu])=>{let a=s.abs().normalize();a=a.div(a.dot(he(1)));const o=i.yz.mul(n),l=i.zx.mul(n),u=i.xy.mul(n),c=r.value,d=e!==null?e.value:c,f=t!==null?t.value:c,h=Bs(c,o).mul(a.x),p=Bs(d,l).mul(a.y),x=Bs(f,u).mul(a.z);return wo(h,p,x)}),LY=(...r)=>d9(...r),SA=new vd,Eg=new J,DA=new J,DB=new J,Nx=new Cr,WE=new J(0,0,-1),Mf=new Ei,Fx=new J,QE=new J,Rx=new Ei,ZE=new ct,YE=new sh,OY=Ph.flipX();YE.depthTexture=new Vl(1,1);let JE=!1;class TB extends wf{static get type(){return"ReflectorNode"}constructor(e={}){super(e.defaultTexture||YE.texture,OY),this._reflectorBaseNode=e.reflector||new zY(this,e),this._depthNode=null,this.setUpdateMatrix(!1)}get reflector(){return this._reflectorBaseNode}get target(){return this._reflectorBaseNode.target}getDepthNode(){if(this._depthNode===null){if(this._reflectorBaseNode.depth!==!0)throw new Error("THREE.ReflectorNode: Depth node can only be requested when the reflector is created with { depth: true }. ");this._depthNode=wn(new TB({defaultTexture:YE.depthTexture,reflector:this._reflectorBaseNode}))}return this._depthNode}setup(e){return e.object.isQuadMesh||this._reflectorBaseNode.build(e),super.setup(e)}clone(){const e=new this.constructor(this.reflectorNode);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.offsetNode=this.offsetNode,e._reflectorBaseNode=this._reflectorBaseNode,e}dispose(){super.dispose(),this._reflectorBaseNode.dispose()}}class zY extends ar{static get type(){return"ReflectorBaseNode"}constructor(e,t={}){super();const{target:n=new so,resolutionScale:i=1,generateMipmaps:s=!1,bounces:a=!0,depth:o=!1,samples:l=0}=t;this.textureNode=e,this.target=n,this.resolutionScale=i,t.resolution!==void 0&&(rs('ReflectorNode: The "resolution" parameter has been renamed to "resolutionScale".'),this.resolutionScale=t.resolution),this.generateMipmaps=s,this.bounces=a,this.depth=o,this.samples=l,this.updateBeforeType=a?Bi.RENDER:Bi.FRAME,this.virtualCameras=new WeakMap,this.renderTargets=new Map,this.forceUpdate=!1,this.hasOutput=!1}_updateResolution(e,t){const n=this.resolutionScale;t.getDrawingBufferSize(ZE),e.setSize(Math.round(ZE.width*n),Math.round(ZE.height*n))}setup(e){return this._updateResolution(YE,e.renderer),super.setup(e)}dispose(){super.dispose();for(const e of this.renderTargets.values())e.dispose()}getVirtualCamera(e){let t=this.virtualCameras.get(e);return t===void 0&&(t=e.clone(),this.virtualCameras.set(e,t)),t}getRenderTarget(e){let t=this.renderTargets.get(e);return t===void 0&&(t=new sh(0,0,{type:pa,samples:this.samples}),this.generateMipmaps===!0&&(t.texture.minFilter=rC,t.texture.generateMipmaps=!0),this.depth===!0&&(t.depthTexture=new Vl),this.renderTargets.set(e,t)),t}updateBefore(e){if(this.bounces===!1&&JE)return!1;JE=!0;const{scene:t,camera:n,renderer:i,material:s}=e,{target:a}=this,o=this.getVirtualCamera(n),l=this.getRenderTarget(o);i.getDrawingBufferSize(ZE),this._updateResolution(l,i),DA.setFromMatrixPosition(a.matrixWorld),DB.setFromMatrixPosition(n.matrixWorld),Nx.extractRotation(a.matrixWorld),Eg.set(0,0,1),Eg.applyMatrix4(Nx),Fx.subVectors(DA,DB);const u=Fx.dot(Eg)>0;let c=!1;if(u===!0&&this.forceUpdate===!1){if(this.hasOutput===!1){JE=!1;return}c=!0}Fx.reflect(Eg).negate(),Fx.add(DA),Nx.extractRotation(n.matrixWorld),WE.set(0,0,-1),WE.applyMatrix4(Nx),WE.add(DB),QE.subVectors(DA,WE),QE.reflect(Eg).negate(),QE.add(DA),o.coordinateSystem=n.coordinateSystem,o.position.copy(Fx),o.up.set(0,1,0),o.up.applyMatrix4(Nx),o.up.reflect(Eg),o.lookAt(QE),o.near=n.near,o.far=n.far,o.updateMatrixWorld(),o.projectionMatrix.copy(n.projectionMatrix),SA.setFromNormalAndCoplanarPoint(Eg,DA),SA.applyMatrix4(o.matrixWorldInverse),Mf.set(SA.normal.x,SA.normal.y,SA.normal.z,SA.constant);const d=o.projectionMatrix;Rx.x=(Math.sign(Mf.x)+d.elements[8])/d.elements[0],Rx.y=(Math.sign(Mf.y)+d.elements[9])/d.elements[5],Rx.z=-1,Rx.w=(1+d.elements[10])/d.elements[14],Mf.multiplyScalar(1/Mf.dot(Rx));const f=0;d.elements[2]=Mf.x,d.elements[6]=Mf.y,d.elements[10]=i.coordinateSystem===gn?Mf.z-f:Mf.z+1-f,d.elements[14]=Mf.w,this.textureNode.value=l.texture,this.depth===!0&&(this.textureNode.getDepthNode().value=l.depthTexture),s.visible=!1;const h=i.getRenderTarget(),p=i.getMRT(),x=i.autoClear;i.setMRT(null),i.setRenderTarget(l),i.autoClear=!0;const v=t.name;t.name=(t.name||"Scene")+" [ Reflector ]",c?(i.clear(),this.hasOutput=!1):(i.render(t,o),this.hasOutput=!0),t.name=v,i.setMRT(p),i.setRenderTarget(h),i.autoClear=x,s.visible=!0,JE=!1,this.forceUpdate=!1}get resolution(){return rs('ReflectorNode: The "resolution" property has been renamed to "resolutionScale".'),this.resolutionScale}set resolution(e){rs('ReflectorNode: The "resolution" property has been renamed to "resolutionScale".'),this.resolutionScale=e}}const HY=r=>new TB(r),IB=new Km(-1,1,1,-1,0,1);class UY extends Ni{constructor(e=!1){super();const t=e===!1?[0,-1,0,1,2,1]:[0,2,0,0,2,0];this.setAttribute("position",new yr([-1,3,0,-1,-1,0,3,-1,0],3)),this.setAttribute("uv",new yr(t,2))}}const kY=new UY;class Lx extends Gs{constructor(e=null){super(kY,e),this.camera=IB,this.isQuadMesh=!0}renderAsync(e){return Kr(this,null,function*(){rs('QuadMesh: "renderAsync()" has been deprecated. Use "render()" and "await renderer.init();" when creating the renderer.'),yield e.init(),e.render(this,IB)})}render(e){e.render(this,IB)}}const VY=new ct;class jY extends wf{static get type(){return"RTTNode"}constructor(e,t=null,n=null,i={type:pa}){const s=new sh(t,n,i);super(s.texture,Qs()),this.isRTTNode=!0,this.node=e,this.width=t,this.height=n,this.pixelRatio=1,this.renderTarget=s,this.textureNeedsUpdate=!0,this.autoUpdate=!0,this._rttNode=null,this._quadMesh=new Lx(new Ka),this.updateBeforeType=Bi.RENDER}get autoResize(){return this.width===null}setup(e){return this._rttNode=this.node.context(e.getSharedContext()),this._quadMesh.material.name="RTT",this._quadMesh.material.needsUpdate=!0,super.setup(e)}setSize(e,t){this.width=e,this.height=t;const n=e*this.pixelRatio,i=t*this.pixelRatio;this.renderTarget.setSize(n,i),this.textureNeedsUpdate=!0}setPixelRatio(e){this.pixelRatio=e,this.setSize(this.width,this.height)}updateBefore({renderer:e}){if(this.textureNeedsUpdate===!1&&this.autoUpdate===!1)return;if(this.textureNeedsUpdate=!1,this.autoResize===!0){const i=e.getPixelRatio(),s=e.getSize(VY),a=Math.floor(s.width*i),o=Math.floor(s.height*i);(a!==this.renderTarget.width||o!==this.renderTarget.height)&&(this.renderTarget.setSize(a,o),this.textureNeedsUpdate=!0)}let t="RTT";this.node.name&&(t=this.node.name+" [ "+t+" ]"),this._quadMesh.material.fragmentNode=this._rttNode,this._quadMesh.name=t;const n=e.getRenderTarget();e.setRenderTarget(this.renderTarget),this._quadMesh.render(e),e.setRenderTarget(n)}clone(){const e=new wf(this.value,this.uvNode,this.levelNode);return e.sampler=this.sampler,e.referenceNode=this,e}}const f9=(r,...e)=>wn(new jY(wn(r),...e)),XY=(r,...e)=>r.isSampleNode||r.isTextureNode?r:r.isPassNode?r.getTextureNode():f9(r,...e),TA=be(([r,e,t],n)=>{let i;n.renderer.coordinateSystem===gn?(r=Wt(r.x,r.y.oneMinus()).mul(2).sub(1),i=Yn(he(r,e),1)):i=Yn(he(r.x,r.y.oneMinus(),e).mul(2).sub(1),1);const s=Yn(t.mul(i));return s.xyz.div(s.w)}),GY=be(([r,e])=>{const t=e.mul(Yn(r,1)),n=t.xy.div(t.w).mul(.5).add(.5).toVar();return Wt(n.x,n.y.oneMinus())}),WY=be(([r,e,t])=>{const n=wh(oo(e)),i=Fo(r.mul(n)).toVar(),s=oo(e,i).toVar(),a=oo(e,i.sub(Fo(2,0))).toVar(),o=oo(e,i.sub(Fo(1,0))).toVar(),l=oo(e,i.add(Fo(1,0))).toVar(),u=oo(e,i.add(Fo(2,0))).toVar(),c=oo(e,i.add(Fo(0,2))).toVar(),d=oo(e,i.add(Fo(0,1))).toVar(),f=oo(e,i.sub(Fo(0,1))).toVar(),h=oo(e,i.sub(Fo(0,2))).toVar(),p=va(us(K(2).mul(o).sub(a),s)).toVar(),x=va(us(K(2).mul(l).sub(u),s)).toVar(),v=va(us(K(2).mul(d).sub(c),s)).toVar(),m=va(us(K(2).mul(f).sub(h),s)).toVar(),C=TA(r,s,t).toVar(),w=p.lessThan(x).select(C.sub(TA(r.sub(Wt(K(1).div(n.x),0)),o,t)),C.negate().add(TA(r.add(Wt(K(1).div(n.x),0)),l,t))),P=v.lessThan(m).select(C.sub(TA(r.add(Wt(0,K(1).div(n.y))),d,t)),C.negate().add(TA(r.sub(Wt(0,K(1).div(n.y))),f,t)));return au(yh(w,P))}),NB=be(([r])=>Pd(K(52.9829189).mul(Pd(Nc(r,Wt(.06711056,.00583715)))))).setLayout({name:"interleavedGradientNoise",type:"float",inputs:[{name:"position",type:"vec2"}]}),Dd=be(([r,e,t])=>{const n=K(2.399963229728653),i=Gl(K(r).add(.5).div(K(e))),s=K(r).mul(n).add(t);return Wt(Bd(s),ou(s)).mul(i)}).setLayout({name:"vogelDiskSample",type:"vec2",inputs:[{name:"sampleIndex",type:"int"},{name:"samplesCount",type:"int"},{name:"phi",type:"float"}]});class QY extends ar{static get type(){return"SampleNode"}constructor(e,t=null){super(),this.callback=e,this.uvNode=t,this.isSampleNode=!0}setup(){return this.sample(Qs())}sample(e){return this.callback(e)}}const ZY=(r,e=null)=>new QY(r,wn(e));class Su extends ar{static get type(){return"EventNode"}constructor(e,t){super("void"),this.eventType=e,this.callback=t,e===Su.OBJECT?this.updateType=Bi.OBJECT:e===Su.MATERIAL?this.updateType=Bi.RENDER:e===Su.BEFORE_OBJECT?this.updateBeforeType=Bi.OBJECT:e===Su.BEFORE_MATERIAL&&(this.updateBeforeType=Bi.RENDER)}update(e){this.callback(e)}updateBefore(e){this.callback(e)}}Su.OBJECT="object",Su.MATERIAL="material",Su.BEFORE_OBJECT="beforeObject",Su.BEFORE_MATERIAL="beforeMaterial";const KE=(r,e)=>new Su(r,e).toStack(),YY=r=>KE(Su.OBJECT,r),JY=r=>KE(Su.MATERIAL,r),KY=r=>KE(Su.BEFORE_OBJECT,r),qY=r=>KE(Su.BEFORE_MATERIAL,r);class _Y extends gd{constructor(e,t,n=Float32Array){const i=ArrayBuffer.isView(e)?e:new n(e*t);super(i,t),this.isStorageInstancedBufferAttribute=!0}}class $Y extends ga{constructor(e,t,n=Float32Array){const i=ArrayBuffer.isView(e)?e:new n(e*t);super(i,t),this.isStorageBufferAttribute=!0}}const eJ=(r,e="float")=>{let t,n;e.isStruct===!0?(t=e.layout.getLength(),n=sx("float")):(t=IP(e),n=sx(e));const i=new $Y(r,t,n);return Dh(i,e,r)},tJ=(r,e="float")=>{let t,n;e.isStruct===!0?(t=e.layout.getLength(),n=sx("float")):(t=IP(e),n=sx(e));const i=new _Y(r,t,n);return Dh(i,e,r)};class nJ extends ar{static get type(){return"PointUVNode"}constructor(){super("vec2"),this.isPointUVNode=!0}generate(){return"vec2( gl_PointCoord.x, 1.0 - gl_PointCoord.y )"}}const rJ=An(nJ),Ox=new bu,FB=new Cr;class Du extends ar{static get type(){return"SceneNode"}constructor(e=Du.BACKGROUND_BLURRINESS,t=null){super(),this.scope=e,this.scene=t}setup(e){const t=this.scope,n=this.scene!==null?this.scene:e.scene;let i;return t===Du.BACKGROUND_BLURRINESS?i=$s("backgroundBlurriness","float",n):t===Du.BACKGROUND_INTENSITY?i=$s("backgroundIntensity","float",n):t===Du.BACKGROUND_ROTATION?i=Dr("mat4").setName("backgroundRotation").setGroup(Rr).onRenderUpdate(()=>{const s=n.background;return s!==null&&s.isTexture&&s.mapping!==mi?(Ox.copy(n.backgroundRotation),Ox.x*=-1,Ox.y*=-1,Ox.z*=-1,FB.makeRotationFromEuler(Ox)):FB.identity(),FB}):rt("SceneNode: Unknown scope:",t),i}}Du.BACKGROUND_BLURRINESS="backgroundBlurriness",Du.BACKGROUND_INTENSITY="backgroundIntensity",Du.BACKGROUND_ROTATION="backgroundRotation";const h9=An(Du,Du.BACKGROUND_BLURRINESS),RB=An(Du,Du.BACKGROUND_INTENSITY),p9=An(Du,Du.BACKGROUND_ROTATION);class iJ extends wf{static get type(){return"StorageTextureNode"}constructor(e,t,n=null){super(e,t),this.storeNode=n,this.mipLevel=0,this.isStorageTextureNode=!0,this.access=El.WRITE_ONLY}getInputType(){return"storageTexture"}setup(e){super.setup(e);const t=e.getNodeProperties(this);return t.storeNode=this.storeNode,t}setAccess(e){return this.access=e,this}setMipLevel(e){return this.mipLevel=e,this}generate(e,t){let n;return this.storeNode!==null?n=this.generateStore(e):n=super.generate(e,t),n}toReadWrite(){return this.setAccess(El.READ_WRITE)}toReadOnly(){return this.setAccess(El.READ_ONLY)}toWriteOnly(){return this.setAccess(El.WRITE_ONLY)}generateStore(e){const t=e.getNodeProperties(this),{uvNode:n,storeNode:i,depthNode:s}=t,a=super.generate(e,"property"),o=n.build(e,this.value.is3DTexture===!0?"uvec3":"uvec2"),l=i.build(e,"vec4"),u=s?s.build(e,"int"):null,c=e.generateTextureStore(e,a,o,u,l);e.addLineFlowCode(c,this)}clone(){const e=super.clone();return e.storeNode=this.storeNode,e.mipLevel=this.mipLevel,e}}const m9=vi(iJ).setParameterLength(1,3),sJ=(r,e,t)=>{const n=m9(r,e,t);return t!==null&&n.toStack(),n},aJ=be(({texture:r,uv:e})=>{const n=he().toVar();return cr(e.x.lessThan(1e-4),()=>{n.assign(he(1,0,0))}).ElseIf(e.y.lessThan(1e-4),()=>{n.assign(he(0,1,0))}).ElseIf(e.z.lessThan(1e-4),()=>{n.assign(he(0,0,1))}).ElseIf(e.x.greaterThan(1-1e-4),()=>{n.assign(he(-1,0,0))}).ElseIf(e.y.greaterThan(1-1e-4),()=>{n.assign(he(0,-1,0))}).ElseIf(e.z.greaterThan(1-1e-4),()=>{n.assign(he(0,0,-1))}).Else(()=>{const s=r.sample(e.add(he(-.01,0,0))).r.sub(r.sample(e.add(he(.01,0,0))).r),a=r.sample(e.add(he(0,-.01,0))).r.sub(r.sample(e.add(he(0,.01,0))).r),o=r.sample(e.add(he(0,0,-.01))).r.sub(r.sample(e.add(he(0,0,.01))).r);n.assign(he(s,a,o))}),n.normalize()});class oJ extends wf{static get type(){return"Texture3DNode"}constructor(e,t=null,n=null){super(e,t,n),this.isTexture3DNode=!0}getInputType(){return"texture3D"}getDefaultUV(){return he(.5,.5,.5)}setUpdateMatrix(){}setupUV(e,t){const n=this.value;return e.isFlipY()&&(n.isRenderTargetTexture===!0||n.isFramebufferTexture===!0)&&(this.sampler?t=t.flipY():t=t.setY(ce(wh(this,this.levelNode).y).sub(t.y).sub(1))),t}generateUV(e,t){return t.build(e,this.sampler===!0?"vec3":"ivec3")}generateOffset(e,t){return t.build(e,"ivec3")}normal(e){return aJ({texture:this,uv:e})}}const qE=vi(oJ).setParameterLength(1,3),lJ=(...r)=>qE(...r).setSampler(!1),uJ=(r,e,t)=>qE(r,e).level(t);class cJ extends CE{static get type(){return"UserDataNode"}constructor(e,t,n=null){super(e,t,n),this.userData=n}updateReference(e){return this.reference=this.userData!==null?this.userData:e.object.userData,this.reference}}const dJ=(r,e,t)=>new cJ(r,e,t),g9=new WeakMap;class fJ extends Qa{static get type(){return"VelocityNode"}constructor(){super("vec2"),this.projectionMatrix=null,this.updateType=Bi.OBJECT,this.updateAfterType=Bi.OBJECT,this.previousModelWorldMatrix=Dr(new Cr),this.previousProjectionMatrix=Dr(new Cr).setGroup(Rr),this.previousCameraViewMatrix=Dr(new Cr)}setProjectionMatrix(e){this.projectionMatrix=e}update({frameId:e,camera:t,object:n}){const i=A9(n);this.previousModelWorldMatrix.value.copy(i);const s=v9(t);s.frameId!==e&&(s.frameId=e,s.previousProjectionMatrix===void 0?(s.previousProjectionMatrix=new Cr,s.previousCameraViewMatrix=new Cr,s.currentProjectionMatrix=new Cr,s.currentCameraViewMatrix=new Cr,s.previousProjectionMatrix.copy(this.projectionMatrix||t.projectionMatrix),s.previousCameraViewMatrix.copy(t.matrixWorldInverse)):(s.previousProjectionMatrix.copy(s.currentProjectionMatrix),s.previousCameraViewMatrix.copy(s.currentCameraViewMatrix)),s.currentProjectionMatrix.copy(this.projectionMatrix||t.projectionMatrix),s.currentCameraViewMatrix.copy(t.matrixWorldInverse),this.previousProjectionMatrix.value.copy(s.previousProjectionMatrix),this.previousCameraViewMatrix.value.copy(s.previousCameraViewMatrix))}updateAfter({object:e}){A9(e).copy(e.matrixWorld)}setup(){const e=this.projectionMatrix===null?uu:Dr(this.projectionMatrix),t=this.previousCameraViewMatrix.mul(this.previousModelWorldMatrix),n=e.mul(Cf).mul(Ja),i=this.previousProjectionMatrix.mul(t).mul(bE),s=n.xy.div(n.w),a=i.xy.div(i.w);return us(s,a)}}function v9(r){let e=g9.get(r);return e===void 0&&(e={},g9.set(r,e)),e}function A9(r,e=0){const t=v9(r);let n=t[e];return n===void 0&&(t[e]=n=new Cr,t[e].copy(r.matrixWorld)),n}const hJ=An(fJ),pJ=be(([r])=>LB(r.rgb)),mJ=be(([r,e=K(1)])=>e.mix(LB(r.rgb),r.rgb)),gJ=be(([r,e=K(1)])=>{const t=wo(r.r,r.g,r.b).div(3),n=r.r.max(r.g.max(r.b)),i=n.sub(t).mul(e).mul(-3);return ss(r.rgb,n,i)}),vJ=be(([r,e=K(1)])=>{const t=he(.57735,.57735,.57735),n=e.cos();return he(r.rgb.mul(n).add(t.cross(r.rgb).mul(e.sin()).add(t.mul(Nc(t,r.rgb).mul(n.oneMinus())))))}),LB=(r,e=he($r.getLuminanceCoefficients(new J)))=>Nc(r,e),AJ=be(([r,e=he(1),t=he(0),n=he(1),i=K(1),s=he($r.getLuminanceCoefficients(new J,af))])=>{const a=r.rgb.dot(he(s)),o=Ya(r.rgb.mul(e).add(t),0).toVar(),l=o.pow(n).toVar();return cr(o.r.greaterThan(0),()=>{o.r.assign(l.r)}),cr(o.g.greaterThan(0),()=>{o.g.assign(l.g)}),cr(o.b.greaterThan(0),()=>{o.b.assign(l.b)}),o.assign(a.add(o.sub(a).mul(i))),Yn(o.rgb,r.a)});class xJ extends Qa{static get type(){return"PosterizeNode"}constructor(e,t){super(),this.sourceNode=e,this.stepsNode=t}setup(){const{sourceNode:e,stepsNode:t}=this;return e.mul(t).floor().div(t)}}const yJ=vi(xJ).setParameterLength(2),_E=new ct;class x9 extends wf{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 y9 extends x9{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.offsetNode=this.offsetNode,e}}class Sf extends Qa{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 s=new Vl;s.isRenderTargetTexture=!0,s.name="depth";const a=new sh(this._width*this._pixelRatio,this._height*this._pixelRatio,ba({type:pa},i));a.texture.name="output",a.depthTexture=s,this.renderTarget=a,this.overrideMaterial=null,this.transparent=!0,this.opaque=!0,this.contextNode=null,this._contextNodeCache=null,this._textures={output:a.texture,depth:s},this._textureNodes={},this._linearDepthNodes={},this._viewZNodes={},this._previousTextures={},this._previousTextureNodes={},this._cameraNear=Dr(0),this._cameraFar=Dr(0),this._mrt=null,this._layers=null,this._resolutionScale=1,this._viewport=null,this._scissor=null,this.isPassNode=!0,this.updateBeforeType=Bi.FRAME,this.global=!0}setResolutionScale(e){return this._resolutionScale=e,this}getResolutionScale(){return this._resolutionScale}setResolution(e){return ze("PassNode: .setResolution() is deprecated. Use .setResolutionScale() instead."),this.setResolutionScale(e)}getResolution(){return ze("PassNode: .getResolution() is deprecated. Use .getResolutionScale() instead."),this.getResolutionScale()}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];return t===void 0&&(t=this.renderTarget.texture.clone(),t.name=e,this._textures[e]=t,this.renderTarget.textures.push(t)),t}getPreviousTexture(e){let t=this._previousTextures[e];return t===void 0&&(t=this.getTexture(e).clone(),this._previousTextures[e]=t),t}toggleTexture(e){const t=this._previousTextures[e];if(t!==void 0){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 t===void 0&&(t=new y9(this,e),t.updateTexture(),this._textureNodes[e]=t),t}getPreviousTextureNode(e="output"){let t=this._previousTextureNodes[e];return t===void 0&&(this._textureNodes[e]===void 0&&this.getTextureNode(e),t=new y9(this,e,!0),t.updateTexture(),this._previousTextureNodes[e]=t),t}getViewZNode(e="depth"){let t=this._viewZNodes[e];if(t===void 0){const n=this._cameraNear,i=this._cameraFar;this._viewZNodes[e]=t=tB(this.getTextureNode(e),n,i)}return t}getLinearDepthNode(e="depth"){let t=this._linearDepthNodes[e];if(t===void 0){const n=this._cameraNear,i=this._cameraFar,s=this.getViewZNode(e);this._linearDepthNodes[e]=t=EA(s,n,i)}return t}compileAsync(e){return Kr(this,null,function*(){const t=e.getRenderTarget(),n=e.getMRT();e.setRenderTarget(this.renderTarget),e.setMRT(this._mrt),yield e.compileAsync(this.scene,this.camera),e.setRenderTarget(t),e.setMRT(n)})}setup({renderer:e}){return this.renderTarget.samples=this.options.samples===void 0?e.samples:this.options.samples,this.renderTarget.texture.type=e.getOutputBufferType(),this.scope===Sf.COLOR?this.getTextureNode():this.getLinearDepthNode()}updateBefore(e){const{renderer:t}=e,{scene:n}=this;let i,s;const a=t.getOutputRenderTarget();a&&a.isXRRenderTarget===!0?(s=1,i=t.xr.getCamera(),t.xr.updateCamera(i),_E.set(a.width,a.height)):(i=this.camera,s=t.getPixelRatio(),t.getSize(_E)),this._pixelRatio=s,this.setSize(_E.width,_E.height);const o=t.getRenderTarget(),l=t.getMRT(),u=t.autoClear,c=t.transparent,d=t.opaque,f=i.layers.mask,h=t.contextNode,p=n.overrideMaterial;this._cameraNear.value=i.near,this._cameraFar.value=i.far,this._layers!==null&&(i.layers.mask=this._layers.mask);for(const v in this._previousTextures)this.toggleTexture(v);this.overrideMaterial!==null&&(n.overrideMaterial=this.overrideMaterial),t.setRenderTarget(this.renderTarget),t.setMRT(this._mrt),t.autoClear=!0,t.transparent=this.transparent,t.opaque=this.opaque,this.contextNode!==null&&((this._contextNodeCache===null||this._contextNodeCache.version!==this.version)&&(this._contextNodeCache={version:this.version,context:bh(ba(ba({},t.contextNode.getFlowContextData()),this.contextNode.getFlowContextData()))}),t.contextNode=this._contextNodeCache.context);const x=n.name;n.name=this.name?this.name:n.name,t.render(n,i),n.name=x,n.overrideMaterial=p,t.setRenderTarget(o),t.setMRT(l),t.autoClear=u,t.transparent=c,t.opaque=d,t.contextNode=h,i.layers.mask=f}setSize(e,t){this._width=e,this._height=t;const n=Math.floor(this._width*this._pixelRatio*this._resolutionScale),i=Math.floor(this._height*this._pixelRatio*this._resolutionScale);this.renderTarget.setSize(n,i),this._scissor!==null&&this.renderTarget.scissor.copy(this._scissor),this._viewport!==null&&this.renderTarget.viewport.copy(this._viewport)}setScissor(e,t,n,i){e===null?this._scissor=null:(this._scissor===null&&(this._scissor=new Ei),e.isVector4?this._scissor.copy(e):this._scissor.set(e,t,n,i),this._scissor.multiplyScalar(this._pixelRatio*this._resolutionScale).floor())}setViewport(e,t,n,i){e===null?this._viewport=null:(this._viewport===null&&(this._viewport=new Ei),e.isVector4?this._viewport.copy(e):this._viewport.set(e,t,n,i),this._viewport.multiplyScalar(this._pixelRatio*this._resolutionScale).floor())}setPixelRatio(e){this._pixelRatio=e,this.setSize(this._width,this._height)}dispose(){this.renderTarget.dispose()}}Sf.COLOR="color",Sf.DEPTH="depth";const bJ=(r,e,t)=>new Sf(Sf.COLOR,r,e,t),EJ=(r,e)=>new x9(r,e),wJ=(r,e,t)=>new Sf(Sf.DEPTH,r,e,t);class CJ extends Sf{static get type(){return"ToonOutlinePassNode"}constructor(e,t,n,i,s){super(Sf.COLOR,e,t),this.colorNode=n,this.thicknessNode=i,this.alphaNode=s,this._materialCache=new WeakMap,this.name="Outline Pass"}updateBefore(e){const{renderer:t}=e,n=t.getRenderObjectFunction();t.setRenderObjectFunction((i,s,a,o,l,u,c,d)=>{if((l.isMeshToonMaterial||l.isMeshToonNodeMaterial)&&l.wireframe===!1){const f=this._getOutlineMaterial(l);t.renderObject(i,s,a,o,f,u,c,d)}t.renderObject(i,s,a,o,l,u,c,d)}),super.updateBefore(e),t.setRenderObjectFunction(n)}_createMaterial(){const e=new Ka;e.isMeshToonOutlineMaterial=!0,e.name="Toon_Outline",e.side=Qi;const t=Bu.negate(),n=uu.mul(Cf),i=K(1),s=n.mul(Yn(Ja,1)),a=n.mul(Yn(Ja.add(t),1)),o=au(s.sub(a));return e.vertexNode=s.add(o.mul(this.thicknessNode).mul(s.w).mul(i)),e.colorNode=Yn(this.colorNode,this.alphaNode),e}_getOutlineMaterial(e){let t=this._materialCache.get(e);return t===void 0&&(t=this._createMaterial(),this._materialCache.set(e,t)),t}}const PJ=(r,e,t=new Vn(0,0,0),n=.003,i=1)=>wn(new CJ(r,e,wn(t),wn(n),wn(i))),b9=be(([r,e])=>r.mul(e).clamp()).setLayout({name:"linearToneMapping",type:"vec3",inputs:[{name:"color",type:"vec3"},{name:"exposure",type:"float"}]}),E9=be(([r,e])=>(r=r.mul(e),r.div(r.add(1)).clamp())).setLayout({name:"reinhardToneMapping",type:"vec3",inputs:[{name:"color",type:"vec3"},{name:"exposure",type:"float"}]}),w9=be(([r,e])=>{r=r.mul(e),r=r.sub(.004).max(0);const t=r.mul(r.mul(6.2).add(.5)),n=r.mul(r.mul(6.2).add(1.7)).add(.06);return t.div(n).pow(2.2)}).setLayout({name:"cineonToneMapping",type:"vec3",inputs:[{name:"color",type:"vec3"},{name:"exposure",type:"float"}]}),BJ=be(([r])=>{const e=r.mul(r.add(.0245786)).sub(90537e-9),t=r.mul(r.add(.432951).mul(.983729)).add(.238081);return e.div(t)}),C9=be(([r,e])=>{const t=wl(.59719,.35458,.04823,.076,.90834,.01566,.0284,.13383,.83777),n=wl(1.60475,-.53108,-.07367,-.10208,1.10813,-.00605,-.00327,-.07276,1.07602);return r=r.mul(e).div(.6),r=t.mul(r),r=BJ(r),r=n.mul(r),r.clamp()}).setLayout({name:"acesFilmicToneMapping",type:"vec3",inputs:[{name:"color",type:"vec3"},{name:"exposure",type:"float"}]}),MJ=wl(he(1.6605,-.1246,-.0182),he(-.5876,1.1329,-.1006),he(-.0728,-.0083,1.1187)),SJ=wl(he(.6274,.0691,.0164),he(.3293,.9195,.088),he(.0433,.0113,.8956)),DJ=be(([r])=>{const e=he(r).toVar(),t=he(e.mul(e)).toVar(),n=he(t.mul(t)).toVar();return K(15.5).mul(n.mul(t)).sub(Ai(40.14,n.mul(e))).add(Ai(31.96,n).sub(Ai(6.868,t.mul(e))).add(Ai(.4298,t).add(Ai(.1191,e).sub(.00232))))}),P9=be(([r,e])=>{const t=he(r).toVar(),n=wl(he(.856627153315983,.137318972929847,.11189821299995),he(.0951212405381588,.761241990602591,.0767994186031903),he(.0482516061458583,.101439036467562,.811302368396859)),i=wl(he(1.1271005818144368,-.1413297634984383,-.14132976349843826),he(-.11060664309660323,1.157823702216272,-.11060664309660294),he(-.016493938717834573,-.016493938717834257,1.2519364065950405)),s=K(-12.47393),a=K(4.026069);return t.mulAssign(e),t.assign(SJ.mul(t)),t.assign(n.mul(t)),t.assign(Ya(t,1e-10)),t.assign(xf(t)),t.assign(t.sub(s).div(a.sub(s))),t.assign(Md(t,0,1)),t.assign(DJ(t)),t.assign(i.mul(t)),t.assign(Fc(Ya(he(0),t),he(2.2))),t.assign(MJ.mul(t)),t.assign(Md(t,0,1)),t}).setLayout({name:"agxToneMapping",type:"vec3",inputs:[{name:"color",type:"vec3"},{name:"exposure",type:"float"}]}),B9=be(([r,e])=>{const t=K(.76),n=K(.15);r=r.mul(e);const i=Pu(r.r,Pu(r.g,r.b)),s=Cl(i.lessThan(.08),i.sub(Ai(6.25,i.mul(i))),.04);r.subAssign(s);const a=Ya(r.r,Ya(r.g,r.b));cr(a.lessThan(t),()=>r);const o=us(1,t),l=us(1,o.mul(o).div(a.add(o.sub(t))));r.mulAssign(l.div(a));const u=us(1,rc(1,n.mul(a.sub(l)).add(1)));return ss(r,he(l),u)}).setLayout({name:"neutralToneMapping",type:"vec3",inputs:[{name:"color",type:"vec3"},{name:"exposure",type:"float"}]});class sl extends ar{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 i of t)i.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}}const $E=vi(sl).setParameterLength(1,3),TJ=(r,e)=>$E(r,e,"js"),IJ=(r,e)=>$E(r,e,"wgsl"),NJ=(r,e)=>$E(r,e,"glsl");class M9 extends sl{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 n===void 0&&(n=e.parser.parseFunction(this.code),t.nodeFunction=n),n}generate(e,t){super.generate(e);const n=this.getNodeFunction(e),i=n.name,s=n.type,a=e.getCodeFromNode(this,s);i!==""&&(a.name=i);const o=e.getPropertyName(a),l=this.getNodeFunction(e).getCode(o);return a.code=l+`
`,t==="property"?o:e.format(`${o}()`,s,t)}}const S9=(r,e=[],t="")=>{for(let s=0;s<e.length;s++){const a=e[s];typeof a=="function"&&(e[s]=a.functionNode)}const n=new M9(r,e,t),i=(...s)=>n.call(...s);return i.functionNode=n,i},FJ=(r,e)=>S9(r,e,"glsl"),RJ=(r,e)=>S9(r,e,"wgsl");class LJ extends ar{static get type(){return"ScriptableValueNode"}constructor(e=null){super(),this._value=e,this._cache=null,this.inputType=null,this.outputType=null,this.events=new Go,this.isScriptableValueNode=!0}get isScriptableOutputNode(){return this.outputType!==null}set value(e){this._value!==e&&(this._cache&&this.inputType==="URL"&&this.value.value instanceof ArrayBuffer&&(URL.revokeObjectURL(this._cache),this._cache=null),this._value=e,this.events.dispatchEvent({type:"change"}),this.refresh())}get value(){return this._value}refresh(){this.events.dispatchEvent({type:"refresh"})}getValue(){const e=this.value;if(e&&this._cache===null&&this.inputType==="URL"&&e.value instanceof ArrayBuffer)this._cache=URL.createObjectURL(new Blob([e.value]));else if(e&&e.value!==null&&e.value!==void 0&&((this.inputType==="URL"||this.inputType==="String")&&typeof e.value=="string"||this.inputType==="Number"&&typeof e.value=="number"||this.inputType==="Vector2"&&e.value.isVector2||this.inputType==="Vector3"&&e.value.isVector3||this.inputType==="Vector4"&&e.value.isVector4||this.inputType==="Color"&&e.value.isColor||this.inputType==="Matrix3"&&e.value.isMatrix3||this.inputType==="Matrix4"&&e.value.isMatrix4))return e.value;return this._cache||e}getNodeType(e){return this.value&&this.value.isNode?this.value.getNodeType(e):"float"}setup(){return this.value&&this.value.isNode?this.value:K()}serialize(e){super.serialize(e),this.value!==null?this.inputType==="ArrayBuffer"?e.value=FP(this.value):e.value=this.value?this.value.toJSON(e.meta).uuid:null:e.value=null,e.inputType=this.inputType,e.outputType=this.outputType}deserialize(e){super.deserialize(e);let t=null;e.value!==null&&(e.inputType==="ArrayBuffer"?t=RP(e.value):e.inputType==="Texture"?t=e.meta.textures[e.value]:t=e.meta.nodes[e.value]||null),this.value=t,this.inputType=e.inputType,this.outputType=e.outputType}}const ew=vi(LJ).setParameterLength(1);class D9 extends Map{get(e,t=null,...n){if(this.has(e))return super.get(e);if(t!==null){const i=t(...n);return this.set(e,i),i}}}class OJ{constructor(e){this.scriptableNode=e}get parameters(){return this.scriptableNode.parameters}get layout(){return this.scriptableNode.getLayout()}getInputLayout(e){return this.scriptableNode.getInputLayout(e)}get(e){const t=this.parameters[e];return t?t.getValue():null}}const tw=new D9;class zJ extends ar{static get type(){return"ScriptableNode"}constructor(e=null,t={}){super(),this.codeNode=e,this.parameters=t,this._local=new D9,this._output=ew(null),this._outputs={},this._source=this.source,this._method=null,this._object=null,this._value=null,this._needsOutputUpdate=!0,this.onRefresh=this.onRefresh.bind(this),this.isScriptableNode=!0}get source(){return this.codeNode?this.codeNode.code:""}setLocal(e,t){return this._local.set(e,t)}getLocal(e){return this._local.get(e)}onRefresh(){this._refresh()}getInputLayout(e){for(const t of this.getLayout())if(t.inputType&&(t.id===e||t.name===e))return t}getOutputLayout(e){for(const t of this.getLayout())if(t.outputType&&(t.id===e||t.name===e))return t}setOutput(e,t){const n=this._outputs;return n[e]===void 0?n[e]=ew(t):n[e].value=t,this}getOutput(e){return this._outputs[e]}getParameter(e){return this.parameters[e]}setParameter(e,t){const n=this.parameters;return t&&t.isScriptableNode?(this.deleteParameter(e),n[e]=t,n[e].getDefaultOutput().events.addEventListener("refresh",this.onRefresh)):t&&t.isScriptableValueNode?(this.deleteParameter(e),n[e]=t,n[e].events.addEventListener("refresh",this.onRefresh)):n[e]===void 0?(n[e]=ew(t),n[e].events.addEventListener("refresh",this.onRefresh)):n[e].value=t,this}getValue(){return this.getDefaultOutput().getValue()}deleteParameter(e){let t=this.parameters[e];return t&&(t.isScriptableNode&&(t=t.getDefaultOutput()),t.events.removeEventListener("refresh",this.onRefresh)),this}clearParameters(){for(const e of Object.keys(this.parameters))this.deleteParameter(e);return this.needsUpdate=!0,this}call(e,...t){const i=this.getObject()[e];if(typeof i=="function")return i(...t)}callAsync(e,...t){return Kr(this,null,function*(){const i=this.getObject()[e];if(typeof i=="function")return i.constructor.name==="AsyncFunction"?yield i(...t):i(...t)})}getNodeType(e){return this.getDefaultOutputNode().getNodeType(e)}refresh(e=null){e!==null?this.getOutput(e).refresh():this._refresh()}getObject(){if(this.needsUpdate&&this.dispose(),this._object!==null)return this._object;const e=()=>this.refresh(),t=(u,c)=>this.setOutput(u,c),n=new OJ(this),i=tw.get("THREE"),s=tw.get("TSL"),a=this.getMethod(),o=[n,this._local,tw,e,t,i,s];this._object=a(...o);const l=this._object.layout;if(l&&(l.cache===!1&&this._local.clear(),this._output.outputType=l.outputType||null,Array.isArray(l.elements)))for(const u of l.elements){const c=u.id||u.name;u.inputType&&(this.getParameter(c)===void 0&&this.setParameter(c,null),this.getParameter(c).inputType=u.inputType),u.outputType&&(this.getOutput(c)===void 0&&this.setOutput(c,null),this.getOutput(c).outputType=u.outputType)}return this._object}deserialize(e){super.deserialize(e);for(const t in this.parameters){let n=this.parameters[t];n.isScriptableNode&&(n=n.getDefaultOutput()),n.events.addEventListener("refresh",this.onRefresh)}}getLayout(){return this.getObject().layout}getDefaultOutputNode(){const e=this.getDefaultOutput().value;return e&&e.isNode?e:K()}getDefaultOutput(){return this._exec()._output}getMethod(){if(this.needsUpdate&&this.dispose(),this._method!==null)return this._method;const e=["parameters","local","global","refresh","setOutput","THREE","TSL"],n=["layout","init","main","dispose"].join(", "),i="var "+n+`; var output = {};
`,s=`
return { ...output, `+n+" };",a=i+this.codeNode.code+s;return this._method=new Function(...e,a),this._method}dispose(){this._method!==null&&(this._object&&typeof this._object.dispose=="function"&&this._object.dispose(),this._method=null,this._object=null,this._source=null,this._value=null,this._needsOutputUpdate=!0,this._output.value=null,this._outputs={})}setup(){return this.getDefaultOutputNode()}getCacheKey(e){const t=[lA(this.source),this.getDefaultOutputNode().getCacheKey(e)];for(const n in this.parameters)t.push(this.parameters[n].getCacheKey(e));return ag(t)}set needsUpdate(e){e===!0&&this.dispose()}get needsUpdate(){return this.source!==this._source}_exec(){return this.codeNode===null?this:(this._needsOutputUpdate===!0&&(this._value=this.call("main"),this._needsOutputUpdate=!1),this._output.value=this._value,this)}_refresh(){this.needsUpdate=!0,this._exec(),this._output.refresh()}}const HJ=vi(zJ).setParameterLength(1,2);function T9(r){let e;const t=r.context.getViewZ;return t!==void 0&&(e=t(this)),(e||po.z).negate()}const OB=be(([r,e],t)=>{const n=T9(t);return ic(r,e,n)}),zB=be(([r],e)=>{const t=T9(e);return r.mul(r,t,t).negate().exp().oneMinus()}),zx=be(([r,e])=>Yn(e.toFloat().mix(fA.rgb,r.toVec3()),fA.a));function UJ(r,e,t){return ze('TSL: "rangeFog( color, near, far )" is deprecated. Use "fog( color, rangeFogFactor( near, far ) )" instead.'),zx(r,OB(e,t))}function kJ(r,e){return ze('TSL: "densityFog( color, density )" is deprecated. Use "fog( color, densityFogFactor( density ) )" instead.'),zx(r,zB(e))}let wg=null,Cg=null;class VJ extends ar{static get type(){return"RangeNode"}constructor(e=K(),t=K()){super(),this.minNode=e,this.maxNode=t}getVectorLength(e){const t=this.getConstNode(this.minNode),n=this.getConstNode(this.maxNode),i=e.getTypeLength(Ah(t.value)),s=e.getTypeLength(Ah(n.value));return i>s?i:s}getNodeType(e){return e.object.count>1?e.getTypeFromLength(this.getVectorLength(e)):"float"}getConstNode(e){let t=null;if(e.traverse(n=>{n.isConstNode===!0&&(t=n)}),t===null)throw new Error('THREE.TSL: No "ConstNode" found in node graph.');return t}setup(e){const t=e.object;let n=null;if(t.count>1){const i=this.getConstNode(this.minNode),s=this.getConstNode(this.maxNode),a=i.value,o=s.value,l=e.getTypeLength(Ah(a)),u=e.getTypeLength(Ah(o));wg=wg||new Ei,Cg=Cg||new Ei,wg.setScalar(0),Cg.setScalar(0),l===1?wg.setScalar(a):a.isColor?wg.set(a.r,a.g,a.b,1):wg.set(a.x,a.y,a.z||0,a.w||0),u===1?Cg.setScalar(o):o.isColor?Cg.set(o.r,o.g,o.b,1):Cg.set(o.x,o.y,o.z||0,o.w||0);const c=4,d=c*t.count,f=new Float32Array(d);for(let p=0;p<d;p++){const x=p%c,v=wg.getComponent(x),m=Cg.getComponent(x);f[p]=S0.lerp(v,m,Math.random())}const h=this.getNodeType(e);if(t.count<=4096)n=vx(f,"vec4",t.count).element(Pf).convert(h);else{const p=new gd(f,4);e.geometry.setAttribute("__range"+this.id,p),n=xE(p).convert(h)}}else n=K(0);return n}}const jJ=vi(VJ).setParameterLength(2);class XJ extends ar{static get type(){return"ComputeBuiltinNode"}constructor(e,t){super(t),this._builtinName=e}getHash(e){return this.getBuiltinName(e)}getNodeType(){return this.nodeType}setBuiltinName(e){return this._builtinName=e,this}getBuiltinName(){return this._builtinName}hasBuiltin(e){return e.hasBuiltin(this._builtinName)}generate(e,t){const n=this.getBuiltinName(e),i=this.getNodeType(e);return e.shaderStage==="compute"?e.format(n,i,t):(ze(`ComputeBuiltinNode: Compute built-in value ${n} can not be accessed in the ${e.shaderStage} stage`),e.generateConst(i))}serialize(e){super.serialize(e),e.global=this.global,e._builtinName=this._builtinName}deserialize(e){super.deserialize(e),this.global=e.global,this._builtinName=e._builtinName}}const Hx=(r,e)=>new XJ(r,e),GJ=Hx("numWorkgroups","uvec3"),WJ=Hx("workgroupId","uvec3"),QJ=Hx("globalId","uvec3"),ZJ=Hx("localId","uvec3"),YJ=Hx("subgroupSize","uint");class JJ extends ar{constructor(e){super(),this.scope=e}generate(e){const{scope:t}=this,{renderer:n}=e;n.backend.isWebGLBackend===!0?e.addFlowCode(`	// ${t}Barrier 
`):e.addLineFlowCode(`${t}Barrier()`,this)}}const HB=vi(JJ),KJ=()=>HB("workgroup").toStack(),qJ=()=>HB("storage").toStack(),_J=()=>HB("texture").toStack();class $J extends lg{constructor(e,t){super(e,t),this.isWorkgroupInfoElementNode=!0}generate(e,t){let n;const i=e.context.assign;if(n=super.generate(e),i!==!0){const s=this.getNodeType(e);n=e.format(n,s,t)}return n}}class eK extends ar{constructor(e,t,n=0){super(t),this.bufferType=t,this.bufferCount=n,this.isWorkgroupInfoNode=!0,this.elementType=t,this.scope=e,this.name=""}setName(e){return this.name=e,this}label(e){return ze('TSL: "label()" has been deprecated. Use "setName()" instead.'),this.setName(e)}setScope(e){return this.scope=e,this}getElementType(){return this.elementType}getInputType(){return`${this.scope}Array`}element(e){return new $J(this,e)}generate(e){const t=this.name!==""?this.name:`${this.scope}Array_${this.id}`;return e.getScopedArray(t,this.scope.toLowerCase(),this.bufferType,this.bufferCount)}}const tK=(r,e)=>new eK("Workgroup",r,e);class Yo extends ar{static get type(){return"AtomicFunctionNode"}constructor(e,t,n){super("uint"),this.method=e,this.pointerNode=t,this.valueNode=n,this.parents=!0}getInputType(e){return this.pointerNode.getNodeType(e)}getNodeType(e){return this.getInputType(e)}generate(e){const t=e.getNodeProperties(this),n=t.parents,i=this.method,s=this.getNodeType(e),a=this.getInputType(e),o=this.pointerNode,l=this.valueNode,u=[];u.push(`&${o.build(e,a)}`),l!==null&&u.push(l.build(e,a));const c=`${e.getMethod(i,s)}( ${u.join(", ")} )`;if(n?n.length===1&&n[0].isStackNode===!0:!1)e.addLineFlowCode(c,this);else return t.constNode===void 0&&(t.constNode=Eh(c,s).toConst()),t.constNode.build(e)}}Yo.ATOMIC_LOAD="atomicLoad",Yo.ATOMIC_STORE="atomicStore",Yo.ATOMIC_ADD="atomicAdd",Yo.ATOMIC_SUB="atomicSub",Yo.ATOMIC_MAX="atomicMax",Yo.ATOMIC_MIN="atomicMin",Yo.ATOMIC_AND="atomicAnd",Yo.ATOMIC_OR="atomicOr",Yo.ATOMIC_XOR="atomicXor";const nK=vi(Yo),Df=(r,e,t)=>nK(r,e,t).toStack(),rK=r=>Df(Yo.ATOMIC_LOAD,r,null),iK=(r,e)=>Df(Yo.ATOMIC_STORE,r,e),sK=(r,e)=>Df(Yo.ATOMIC_ADD,r,e),aK=(r,e)=>Df(Yo.ATOMIC_SUB,r,e),oK=(r,e)=>Df(Yo.ATOMIC_MAX,r,e),lK=(r,e)=>Df(Yo.ATOMIC_MIN,r,e),uK=(r,e)=>Df(Yo.ATOMIC_AND,r,e),cK=(r,e)=>Df(Yo.ATOMIC_OR,r,e),dK=(r,e)=>Df(Yo.ATOMIC_XOR,r,e);class Nn extends Qa{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,i=e.isMatrix(t)?0:e.getTypeLength(t),s=e.isMatrix(n)?0:e.getTypeLength(n);return i>s?t:n}getNodeType(e){const t=this.method;return t===Nn.SUBGROUP_ELECT?"bool":t===Nn.SUBGROUP_BALLOT?"uvec4":this.getInputType(e)}generate(e,t){const n=this.method,i=this.getNodeType(e),s=this.getInputType(e),a=this.aNode,o=this.bNode,l=[];if(n===Nn.SUBGROUP_BROADCAST||n===Nn.SUBGROUP_SHUFFLE||n===Nn.QUAD_BROADCAST){const c=o.getNodeType(e);l.push(a.build(e,i),o.build(e,c==="float"?"int":i))}else n===Nn.SUBGROUP_SHUFFLE_XOR||n===Nn.SUBGROUP_SHUFFLE_DOWN||n===Nn.SUBGROUP_SHUFFLE_UP?l.push(a.build(e,i),o.build(e,"uint")):(a!==null&&l.push(a.build(e,s)),o!==null&&l.push(o.build(e,s)));const u=l.length===0?"()":`( ${l.join(", ")} )`;return e.format(`${e.getMethod(n,i)}${u}`,i,t)}serialize(e){super.serialize(e),e.method=this.method}deserialize(e){super.deserialize(e),this.method=e.method}}Nn.SUBGROUP_ELECT="subgroupElect",Nn.SUBGROUP_BALLOT="subgroupBallot",Nn.SUBGROUP_ADD="subgroupAdd",Nn.SUBGROUP_INCLUSIVE_ADD="subgroupInclusiveAdd",Nn.SUBGROUP_EXCLUSIVE_AND="subgroupExclusiveAdd",Nn.SUBGROUP_MUL="subgroupMul",Nn.SUBGROUP_INCLUSIVE_MUL="subgroupInclusiveMul",Nn.SUBGROUP_EXCLUSIVE_MUL="subgroupExclusiveMul",Nn.SUBGROUP_AND="subgroupAnd",Nn.SUBGROUP_OR="subgroupOr",Nn.SUBGROUP_XOR="subgroupXor",Nn.SUBGROUP_MIN="subgroupMin",Nn.SUBGROUP_MAX="subgroupMax",Nn.SUBGROUP_ALL="subgroupAll",Nn.SUBGROUP_ANY="subgroupAny",Nn.SUBGROUP_BROADCAST_FIRST="subgroupBroadcastFirst",Nn.QUAD_SWAP_X="quadSwapX",Nn.QUAD_SWAP_Y="quadSwapY",Nn.QUAD_SWAP_DIAGONAL="quadSwapDiagonal",Nn.SUBGROUP_BROADCAST="subgroupBroadcast",Nn.SUBGROUP_SHUFFLE="subgroupShuffle",Nn.SUBGROUP_SHUFFLE_XOR="subgroupShuffleXor",Nn.SUBGROUP_SHUFFLE_UP="subgroupShuffleUp",Nn.SUBGROUP_SHUFFLE_DOWN="subgroupShuffleDown",Nn.QUAD_BROADCAST="quadBroadcast";const fK=en(Nn,Nn.SUBGROUP_ELECT).setParameterLength(0),hK=en(Nn,Nn.SUBGROUP_BALLOT).setParameterLength(1),pK=en(Nn,Nn.SUBGROUP_ADD).setParameterLength(1),mK=en(Nn,Nn.SUBGROUP_INCLUSIVE_ADD).setParameterLength(1),gK=en(Nn,Nn.SUBGROUP_EXCLUSIVE_AND).setParameterLength(1),vK=en(Nn,Nn.SUBGROUP_MUL).setParameterLength(1),AK=en(Nn,Nn.SUBGROUP_INCLUSIVE_MUL).setParameterLength(1),xK=en(Nn,Nn.SUBGROUP_EXCLUSIVE_MUL).setParameterLength(1),yK=en(Nn,Nn.SUBGROUP_AND).setParameterLength(1),bK=en(Nn,Nn.SUBGROUP_OR).setParameterLength(1),EK=en(Nn,Nn.SUBGROUP_XOR).setParameterLength(1),wK=en(Nn,Nn.SUBGROUP_MIN).setParameterLength(1),CK=en(Nn,Nn.SUBGROUP_MAX).setParameterLength(1),PK=en(Nn,Nn.SUBGROUP_ALL).setParameterLength(0),BK=en(Nn,Nn.SUBGROUP_ANY).setParameterLength(0),MK=en(Nn,Nn.SUBGROUP_BROADCAST_FIRST).setParameterLength(2),SK=en(Nn,Nn.QUAD_SWAP_X).setParameterLength(1),DK=en(Nn,Nn.QUAD_SWAP_Y).setParameterLength(1),TK=en(Nn,Nn.QUAD_SWAP_DIAGONAL).setParameterLength(1),IK=en(Nn,Nn.SUBGROUP_BROADCAST).setParameterLength(2),NK=en(Nn,Nn.SUBGROUP_SHUFFLE).setParameterLength(2),FK=en(Nn,Nn.SUBGROUP_SHUFFLE_XOR).setParameterLength(2),RK=en(Nn,Nn.SUBGROUP_SHUFFLE_UP).setParameterLength(2),LK=en(Nn,Nn.SUBGROUP_SHUFFLE_DOWN).setParameterLength(2),OK=en(Nn,Nn.QUAD_BROADCAST).setParameterLength(1);let nw;function rw(r){nw=nw||new WeakMap;let e=nw.get(r);return e===void 0&&nw.set(r,e={}),e}function iw(r){const e=rw(r);return e.shadowMatrix||(e.shadowMatrix=Dr("mat4").setGroup(Rr).onRenderUpdate(t=>((r.castShadow!==!0||t.renderer.shadowMap.enabled===!1)&&(r.shadow.camera.coordinateSystem!==t.camera.coordinateSystem&&(r.shadow.camera.coordinateSystem=t.camera.coordinateSystem,r.shadow.camera.updateProjectionMatrix()),r.shadow.updateMatrices(r)),r.shadow.matrix)))}function I9(r,e=ac){const t=iw(r).mul(e);return t.xyz.div(t.w)}function UB(r){const e=rw(r);return e.position||(e.position=Dr(new J).setGroup(Rr).onRenderUpdate((t,n)=>n.value.setFromMatrixPosition(r.matrixWorld)))}function N9(r){const e=rw(r);return e.targetPosition||(e.targetPosition=Dr(new J).setGroup(Rr).onRenderUpdate((t,n)=>n.value.setFromMatrixPosition(r.target.matrixWorld)))}function kB(r){const e=rw(r);return e.viewPosition||(e.viewPosition=Dr(new J).setGroup(Rr).onRenderUpdate(({camera:t},n)=>{n.value=n.value||new J,n.value.setFromMatrixPosition(r.matrixWorld),n.value.applyMatrix4(t.matrixWorldInverse)}))}const VB=r=>sc.transformDirection(UB(r).sub(N9(r))),zK=r=>r.sort((e,t)=>e.id-t.id),HK=(r,e)=>{for(const t of e)if(t.isAnalyticLightNode&&t.light.id===r)return t;return null},jB=new WeakMap,Ux=[];class XB extends ar{static get type(){return"LightsNode"}constructor(){super("vec3"),this.totalDiffuseNode=Cd("vec3","totalDiffuse"),this.totalSpecularNode=Cd("vec3","totalSpecular"),this.outgoingLightNode=Cd("vec3","outgoingLight"),this._lights=[],this._lightNodes=null,this._lightNodesHash=null,this.global=!0}customCacheKey(){const e=this._lights;for(let n=0;n<e.length;n++){const i=e[n];if(Ux.push(i.id),Ux.push(i.castShadow?1:0),i.isSpotLight===!0){const s=i.map!==null?i.map.id:-1,a=i.colorNode?i.colorNode.getCacheKey():-1;Ux.push(s,a)}}const t=ag(Ux);return Ux.length=0,t}getHash(e){if(this._lightNodesHash===null){this._lightNodes===null&&this.setupLightsNode(e);const t=[];for(const n of this._lightNodes)t.push(n.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=zK(this._lights),s=e.renderer.library;for(const a of i)if(a.isNode)t.push(wn(a));else{let o=null;if(n!==null&&(o=HK(a.id,n)),o===null){const l=s.getLightNodeClass(a.constructor);if(l===null){ze(`LightsNode.setupNodeLights: Light node not found for ${a.constructor.name}`);continue}let u=null;jB.has(a)?u=jB.get(a):(u=new l(a),jB.set(a,u)),t.push(u)}}this._lightNodes=t}setupDirectLight(e,t,n){const{lightingModel:i,reflectedLight:s}=e.context;i.direct(Gc(ba({},n),{lightNode:t,reflectedLight:s}),e)}setupDirectRectAreaLight(e,t,n){const{lightingModel:i,reflectedLight:s}=e.context;i.directRectArea(Gc(ba({},n),{lightNode:t,reflectedLight:s}),e)}setupLights(e,t){for(const n of t)n.build(e)}getLightNodes(e){return this._lightNodes===null&&this.setupLightsNode(e),this._lightNodes}setup(e){const t=e.lightsNode;e.lightsNode=this;let n=this.outgoingLightNode;const i=e.context,s=i.lightingModel,a=e.getNodeProperties(this);if(s){const{totalDiffuseNode:o,totalSpecularNode:l}=this;i.outgoingLight=n;const u=e.addStack();a.nodes=u.nodes,s.start(e);const{backdrop:c,backdropAlpha:d}=i,{directDiffuse:f,directSpecular:h,indirectDiffuse:p,indirectSpecular:x}=i.reflectedLight;let v=f.add(p);c!==null&&(d!==null?v=he(d.mix(v,c)):v=he(c)),o.assign(v),l.assign(h.add(x)),n.assign(o.add(l)),s.finish(e),n=n.bypass(e.removeStack())}else a.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}}const UK=(r=[])=>new XB().setLights(r);class kK extends ar{static get type(){return"ShadowBaseNode"}constructor(e){super(),this.light=e,this.updateBeforeType=Bi.RENDER,this.isShadowBaseNode=!0}setupShadowPosition({context:e,material:t}){GB.assign(t.receivedShadowPositionNode||e.shadowPositionWorld||ac)}}const GB=Cd("vec3","shadowPositionWorld");function WB(r,e={}){return e.toneMapping=r.toneMapping,e.toneMappingExposure=r.toneMappingExposure,e.outputColorSpace=r.outputColorSpace,e.renderTarget=r.getRenderTarget(),e.activeCubeFace=r.getActiveCubeFace(),e.activeMipmapLevel=r.getActiveMipmapLevel(),e.renderObjectFunction=r.getRenderObjectFunction(),e.pixelRatio=r.getPixelRatio(),e.mrt=r.getMRT(),e.clearColor=r.getClearColor(e.clearColor||new Vn),e.clearAlpha=r.getClearAlpha(),e.autoClear=r.autoClear,e.scissorTest=r.getScissorTest(),e}function F9(r,e){return e=WB(r,e),r.setMRT(null),r.setRenderObjectFunction(null),r.setClearColor(0,1),r.autoClear=!0,e}function R9(r,e){r.toneMapping=e.toneMapping,r.toneMappingExposure=e.toneMappingExposure,r.outputColorSpace=e.outputColorSpace,r.setRenderTarget(e.renderTarget,e.activeCubeFace,e.activeMipmapLevel),r.setRenderObjectFunction(e.renderObjectFunction),r.setPixelRatio(e.pixelRatio),r.setMRT(e.mrt),r.setClearColor(e.clearColor,e.clearAlpha),r.autoClear=e.autoClear,r.setScissorTest(e.scissorTest)}function QB(r,e={}){return e.background=r.background,e.backgroundNode=r.backgroundNode,e.overrideMaterial=r.overrideMaterial,e}function L9(r,e){return e=QB(r,e),r.background=null,r.backgroundNode=null,r.overrideMaterial=null,e}function O9(r,e){r.background=e.background,r.backgroundNode=e.backgroundNode,r.overrideMaterial=e.overrideMaterial}function VK(r,e,t={}){return t=WB(r,t),t=QB(e,t),t}function z9(r,e,t){return t=F9(r,t),t=L9(e,t),t}function H9(r,e,t){R9(r,t),O9(e,t)}var Sde=Object.freeze({__proto__:null,resetRendererAndSceneState:z9,resetRendererState:F9,resetSceneState:L9,restoreRendererAndSceneState:H9,restoreRendererState:R9,restoreSceneState:O9,saveRendererAndSceneState:VK,saveRendererState:WB,saveSceneState:QB});const sw=new WeakMap,U9=be(({depthTexture:r,shadowCoord:e,depthLayer:t})=>{let n=Bs(r,e.xy).setName("t_basic");return r.isArrayTexture&&(n=n.depth(t)),n.compare(e.z)}),k9=be(({depthTexture:r,shadowCoord:e,shadow:t,depthLayer:n})=>{const i=(c,d)=>{let f=Bs(r,c);return r.isArrayTexture&&(f=f.depth(n)),f.compare(d)},s=$s("mapSize","vec2",t).setGroup(Rr),a=$s("radius","float",t).setGroup(Rr),o=Wt(1).div(s),l=a.mul(o.x),u=NB(gg.xy).mul(6.28318530718);return wo(i(e.xy.add(Dd(0,5,u).mul(l)),e.z),i(e.xy.add(Dd(1,5,u).mul(l)),e.z),i(e.xy.add(Dd(2,5,u).mul(l)),e.z),i(e.xy.add(Dd(3,5,u).mul(l)),e.z),i(e.xy.add(Dd(4,5,u).mul(l)),e.z)).mul(1/5)}),V9=be(({depthTexture:r,shadowCoord:e,shadow:t,depthLayer:n})=>{const i=(d,f)=>{let h=Bs(r,d);return r.isArrayTexture&&(h=h.depth(n)),h.compare(f)},s=$s("mapSize","vec2",t).setGroup(Rr),a=Wt(1).div(s),o=a.x,l=a.y,u=e.xy,c=Pd(u.mul(s).add(.5));return u.subAssign(c.mul(a)),wo(i(u,e.z),i(u.add(Wt(o,0)),e.z),i(u.add(Wt(0,l)),e.z),i(u.add(a),e.z),ss(i(u.add(Wt(o.negate(),0)),e.z),i(u.add(Wt(o.mul(2),0)),e.z),c.x),ss(i(u.add(Wt(o.negate(),l)),e.z),i(u.add(Wt(o.mul(2),l)),e.z),c.x),ss(i(u.add(Wt(0,l.negate())),e.z),i(u.add(Wt(0,l.mul(2))),e.z),c.y),ss(i(u.add(Wt(o,l.negate())),e.z),i(u.add(Wt(o,l.mul(2))),e.z),c.y),ss(ss(i(u.add(Wt(o.negate(),l.negate())),e.z),i(u.add(Wt(o.mul(2),l.negate())),e.z),c.x),ss(i(u.add(Wt(o.negate(),l.mul(2))),e.z),i(u.add(Wt(o.mul(2),l.mul(2))),e.z),c.x),c.y)).mul(1/9)}),j9=be(({depthTexture:r,shadowCoord:e,depthLayer:t})=>{let n=Bs(r).sample(e.xy);r.isArrayTexture&&(n=n.depth(t)),n=n.rg;const i=n.x,s=Ya(1e-7,n.y.mul(n.y)),a=pE(e.z,i);cr(a.equal(1),()=>K(1));const o=e.z.sub(i);let l=s.div(s.add(o.mul(o)));return l=Md(us(l,.3).div(.65)),Ya(a,l)}),jK=be(([r,e,t])=>{let n=ac.sub(r).length();return n=n.sub(e).div(t.sub(e)),n=n.saturate(),n}),XK=r=>{const e=r.shadow.camera,t=$s("near","float",e).setGroup(Rr),n=$s("far","float",e).setGroup(Rr),i=z2(r);return jK(i,t,n)},X9=r=>{let e=sw.get(r);if(e===void 0){const t=r.isPointLight?XK(r):null;e=new Ka,e.colorNode=Yn(0,0,0,1),e.depthNode=t,e.isShadowPassMaterial=!0,e.name="ShadowMaterial",e.fog=!1,sw.set(r,e)}return e},G9=r=>{const e=sw.get(r);e!==void 0&&(e.dispose(),sw.delete(r))},W9=new Sd,IA=[],Q9=(r,e,t,n)=>{IA[0]=r,IA[1]=e;let i=W9.get(IA);return(i===void 0||i.shadowType!==t||i.useVelocity!==n)&&(i=(s,a,o,l,u,c,...d)=>{(s.castShadow===!0||s.receiveShadow&&t===el)&&(n&&(NP(s).useVelocity=!0),s.onBeforeShadow(r,s,o,e.camera,l,a.overrideMaterial,c),r.renderObject(s,a,o,l,u,c,...d),s.onAfterShadow(r,s,o,e.camera,l,a.overrideMaterial,c))},i.shadowType=t,i.useVelocity=n,W9.set(IA,i)),IA[0]=null,IA[1]=null,i},GK=be(({samples:r,radius:e,size:t,shadowPass:n,depthLayer:i})=>{const s=K(0).toVar("meanVertical"),a=K(0).toVar("squareMeanVertical"),o=r.lessThanEqual(K(1)).select(K(0),K(2).div(r.sub(1))),l=r.lessThanEqual(K(1)).select(K(0),K(-1));Vs({start:ce(0),end:ce(r),type:"int",condition:"<"},({i:c})=>{const d=l.add(K(c).mul(o));let f=n.sample(wo(gg.xy,Wt(0,d).mul(e)).div(t));n.value.isArrayTexture&&(f=f.depth(i)),f=f.x,s.addAssign(f),a.addAssign(f.mul(f))}),s.divAssign(r),a.divAssign(r);const u=Gl(a.sub(s.mul(s)).max(0));return Wt(s,u)}),WK=be(({samples:r,radius:e,size:t,shadowPass:n,depthLayer:i})=>{const s=K(0).toVar("meanHorizontal"),a=K(0).toVar("squareMeanHorizontal"),o=r.lessThanEqual(K(1)).select(K(0),K(2).div(r.sub(1))),l=r.lessThanEqual(K(1)).select(K(0),K(-1));Vs({start:ce(0),end:ce(r),type:"int",condition:"<"},({i:c})=>{const d=l.add(K(c).mul(o));let f=n.sample(wo(gg.xy,Wt(d,0).mul(e)).div(t));n.value.isArrayTexture&&(f=f.depth(i)),s.addAssign(f.x),a.addAssign(wo(f.y.mul(f.y),f.x.mul(f.x)))}),s.divAssign(r),a.divAssign(r);const u=Gl(a.sub(s.mul(s)).max(0));return Wt(s,u)}),QK=[U9,k9,V9,j9];let ZB;const aw=new Lx;class Z9 extends kK{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._currentShadowType=null,this._cameraFrameId=new WeakMap,this.isShadowNode=!0,this.depthLayer=0}setupShadowFilter(e,{filterFn:t,depthTexture:n,shadowCoord:i,shadow:s,depthLayer:a}){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)),l=t({depthTexture:n,shadowCoord:i,shadow:s,depthLayer:a});return o.select(l,K(1))}setupShadowCoord(e,t){const{shadow:n}=this,{renderer:i}=e,s=$s("bias","float",n).setGroup(Rr);let a=t,o;if(n.camera.isOrthographicCamera||i.logarithmicDepthBuffer!==!0)a=a.xyz.div(a.w),o=a.z,i.coordinateSystem===gn&&(o=o.mul(2).sub(1));else{const l=a.w;a=a.xy.div(l);const u=$s("near","float",n.camera).setGroup(Rr),c=$s("far","float",n.camera).setGroup(Rr);o=nB(l.negate(),u,c)}return a=he(a.x,a.y.oneMinus(),o.add(s)),a}getShadowFilterFn(e){return QK[e]}setupRenderTarget(e,t){const n=new Vl(e.mapSize.width,e.mapSize.height);n.name="ShadowDepthTexture",n.compareFunction=bp;const i=t.createRenderTarget(e.mapSize.width,e.mapSize.height);return i.texture.name="ShadowMap",i.texture.type=e.mapType,i.depthTexture=n,{shadowMap:i,depthTexture:n}}setupShadow(e){const{renderer:t,camera:n}=e,{light:i,shadow:s}=this,a=t.shadowMap.type,{depthTexture:o,shadowMap:l}=this.setupRenderTarget(s,e);if(s.camera.coordinateSystem=n.coordinateSystem,s.camera.updateProjectionMatrix(),a===el&&s.isPointLightShadow!==!0){o.compareFunction=null,l.depth>1?(l._vsmShadowMapVertical||(l._vsmShadowMapVertical=e.createRenderTarget(s.mapSize.width,s.mapSize.height,{format:Al,type:pa,depth:l.depth,depthBuffer:!1}),l._vsmShadowMapVertical.texture.name="VSMVertical"),this.vsmShadowMapVertical=l._vsmShadowMapVertical,l._vsmShadowMapHorizontal||(l._vsmShadowMapHorizontal=e.createRenderTarget(s.mapSize.width,s.mapSize.height,{format:Al,type:pa,depth:l.depth,depthBuffer:!1}),l._vsmShadowMapHorizontal.texture.name="VSMHorizontal"),this.vsmShadowMapHorizontal=l._vsmShadowMapHorizontal):(this.vsmShadowMapVertical=e.createRenderTarget(s.mapSize.width,s.mapSize.height,{format:Al,type:pa,depthBuffer:!1}),this.vsmShadowMapHorizontal=e.createRenderTarget(s.mapSize.width,s.mapSize.height,{format:Al,type:pa,depthBuffer:!1}));let w=Bs(o);o.isArrayTexture&&(w=w.depth(this.depthLayer));let P=Bs(this.vsmShadowMapVertical.texture);o.isArrayTexture&&(P=P.depth(this.depthLayer));const B=$s("blurSamples","float",s).setGroup(Rr),S=$s("radius","float",s).setGroup(Rr),I=$s("mapSize","vec2",s).setGroup(Rr);let N=this.vsmMaterialVertical||(this.vsmMaterialVertical=new Ka);N.fragmentNode=GK({samples:B,radius:S,size:I,shadowPass:w,depthLayer:this.depthLayer}).context(e.getSharedContext()),N.name="VSMVertical",N=this.vsmMaterialHorizontal||(this.vsmMaterialHorizontal=new Ka),N.fragmentNode=WK({samples:B,radius:S,size:I,shadowPass:P,depthLayer:this.depthLayer}).context(e.getSharedContext()),N.name="VSMHorizontal"}const u=$s("intensity","float",s).setGroup(Rr),c=$s("normalBias","float",s).setGroup(Rr),d=iw(i).mul(GB.add(jp.mul(c))),f=this.setupShadowCoord(e,d),h=s.filterNode||this.getShadowFilterFn(t.shadowMap.type)||null;if(h===null)throw new Error("THREE.WebGPURenderer: Shadow map type not supported yet.");const p=a===el&&s.isPointLightShadow!==!0?this.vsmShadowMapHorizontal.texture:o,x=this.setupShadowFilter(e,{filterFn:h,shadowTexture:l.texture,depthTexture:p,shadowCoord:f,shadow:s,depthLayer:this.depthLayer});let v;l.texture.isCubeTexture?v=cu(l.texture,f.xyz):(v=Bs(l.texture,f),o.isArrayTexture&&(v=v.depth(this.depthLayer)));const m=ss(1,x.rgb.mix(v,1),u.mul(v.a)).toVar();this.shadowMap=l,this.shadow.map=l;const C=`${this.light.type} Shadow [ ${this.light.name||"ID: "+this.light.id} ]`;return m.toInspector(`${C} / Color`,()=>this.shadowMap.texture.isCubeTexture?cu(this.shadowMap.texture):Bs(this.shadowMap.texture)).toInspector(`${C} / Depth`,()=>this.shadowMap.texture.isCubeTexture?cu(this.shadowMap.texture).r.oneMinus():oo(this.shadowMap.depthTexture,Qs().mul(wh(Bs(this.shadowMap.depthTexture)))).r.oneMinus())}setup(e){if(e.renderer.shadowMap.enabled!==!1)return be(()=>{const t=e.renderer.shadowMap.type;this._currentShadowType!==t&&(this._reset(),this._node=null);let n=this._node;return this.setupShadowPosition(e),n===null&&(this._node=n=this.setupShadow(e),this._currentShadowType=t),e.material.shadowNode&&ze('NodeMaterial: ".shadowNode" is deprecated. Use ".castShadowNode" instead.'),e.material.receivedShadowNode&&(n=e.material.receivedShadowNode(n)),n})()}renderShadow(e){const{shadow:t,shadowMap:n,light:i}=this,{renderer:s,scene:a}=e;t.updateMatrices(i),n.setSize(t.mapSize.width,t.mapSize.height,n.depth);const o=a.name;a.name=`Shadow Map [ ${i.name||"ID: "+i.id} ]`,s.render(a,t.camera),a.name=o}updateShadow(e){const{shadowMap:t,light:n,shadow:i}=this,{renderer:s,scene:a,camera:o}=e,l=s.shadowMap.type,u=t.depthTexture.version;this._depthVersionCached=u;const c=i.camera.layers.mask;i.camera.layers.mask&4294967294||(i.camera.layers.mask=o.layers.mask);const d=s.getRenderObjectFunction(),f=s.getMRT(),h=f?f.has("velocity"):!1;ZB=z9(s,a,ZB),a.overrideMaterial=X9(n),s.setRenderObjectFunction(Q9(s,i,l,h)),s.setClearColor(0,0),s.setRenderTarget(t),this.renderShadow(e),s.setRenderObjectFunction(d),l===el&&i.isPointLightShadow!==!0&&this.vsmPass(s),i.camera.layers.mask=c,H9(s,a,ZB)}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),aw.material=this.vsmMaterialVertical,aw.render(e),e.setRenderTarget(this.vsmShadowMapHorizontal),aw.material=this.vsmMaterialHorizontal,aw.render(e)}dispose(){this._reset(),super.dispose()}_reset(){this._currentShadowType=null,G9(this.light),this.shadowMap&&(this.shadowMap.dispose(),this.shadowMap=null),this.vsmShadowMapVertical!==null&&(this.vsmShadowMapVertical.dispose(),this.vsmShadowMapVertical=null,this.vsmMaterialVertical.dispose(),this.vsmMaterialVertical=null),this.vsmShadowMapHorizontal!==null&&(this.vsmShadowMapHorizontal.dispose(),this.vsmShadowMapHorizontal=null,this.vsmMaterialHorizontal.dispose(),this.vsmMaterialHorizontal=null)}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 Y9=(r,e)=>new Z9(r,e),ZK=new Vn,J9=new Cr,kx=new J,YB=new J,YK=[new J(1,0,0),new J(-1,0,0),new J(0,-1,0),new J(0,1,0),new J(0,0,1),new J(0,0,-1)],JK=[new J(0,-1,0),new J(0,-1,0),new J(0,0,-1),new J(0,0,1),new J(0,-1,0),new J(0,-1,0)],KK=[new J(1,0,0),new J(-1,0,0),new J(0,1,0),new J(0,-1,0),new J(0,0,1),new J(0,0,-1)],qK=[new J(0,-1,0),new J(0,-1,0),new J(0,0,1),new J(0,0,-1),new J(0,-1,0),new J(0,-1,0)],K9=be(({depthTexture:r,bd3D:e,dp:t})=>cu(r,e).compare(t)),q9=be(({depthTexture:r,bd3D:e,dp:t,shadow:n})=>{const i=$s("radius","float",n).setGroup(Rr),s=$s("mapSize","vec2",n).setGroup(Rr),a=i.div(s.x),o=va(e),l=au(yh(e,o.x.greaterThan(o.z).select(he(0,1,0),he(1,0,0)))),u=yh(e,l),c=NB(gg.xy).mul(6.28318530718),d=Dd(0,5,c),f=Dd(1,5,c),h=Dd(2,5,c),p=Dd(3,5,c),x=Dd(4,5,c);return cu(r,e.add(l.mul(d.x).add(u.mul(d.y)).mul(a))).compare(t).add(cu(r,e.add(l.mul(f.x).add(u.mul(f.y)).mul(a))).compare(t)).add(cu(r,e.add(l.mul(h.x).add(u.mul(h.y)).mul(a))).compare(t)).add(cu(r,e.add(l.mul(p.x).add(u.mul(p.y)).mul(a))).compare(t)).add(cu(r,e.add(l.mul(x.x).add(u.mul(x.y)).mul(a))).compare(t)).mul(1/5)}),_K=be(({filterFn:r,depthTexture:e,shadowCoord:t,shadow:n})=>{const i=t.xyz.toVar(),s=i.length(),a=Dr("float").setGroup(Rr).onRenderUpdate(()=>n.camera.near),o=Dr("float").setGroup(Rr).onRenderUpdate(()=>n.camera.far),l=$s("bias","float",n).setGroup(Rr),u=K(1).toVar();return cr(s.sub(o).lessThanEqual(0).and(s.sub(a).greaterThanEqual(0)),()=>{const c=s.sub(a).div(o.sub(a)).toVar();c.addAssign(l);const d=i.normalize();u.assign(r({depthTexture:e,bd3D:d,dp:c,shadow:n}))}),u});class $K extends Z9{static get type(){return"PointShadowNode"}constructor(e,t=null){super(e,t)}getShadowFilterFn(e){return e===xc?K9:q9}setupShadowCoord(e,t){return t}setupShadowFilter(e,{filterFn:t,depthTexture:n,shadowCoord:i,shadow:s}){return _K({filterFn:t,depthTexture:n,shadowCoord:i,shadow:s})}setupRenderTarget(e,t){const n=new d5(e.mapSize.width);n.name="PointShadowDepthTexture",n.compareFunction=bp;const i=t.createCubeRenderTarget(e.mapSize.width);return i.texture.name="PointShadowMap",i.depthTexture=n,{shadowMap:i,depthTexture:n}}renderShadow(e){const{shadow:t,shadowMap:n,light:i}=this,{renderer:s,scene:a}=e,o=t.camera,l=t.matrix,u=s.coordinateSystem===gn,c=u?YK:KK,d=u?JK:qK;n.setSize(t.mapSize.width,t.mapSize.width);const f=s.autoClear,h=s.getClearColor(ZK),p=s.getClearAlpha();s.autoClear=!1,s.setClearColor(t.clearColor,t.clearAlpha);for(let x=0;x<6;x++){s.setRenderTarget(n,x),s.clear();const v=i.distance||o.far;v!==o.far&&(o.far=v,o.updateProjectionMatrix()),kx.setFromMatrixPosition(i.matrixWorld),o.position.copy(kx),YB.copy(o.position),YB.add(c[x]),o.up.copy(d[x]),o.lookAt(YB),o.updateMatrixWorld(),l.makeTranslation(-kx.x,-kx.y,-kx.z),J9.multiplyMatrices(o.projectionMatrix,o.matrixWorldInverse),t._frustum.setFromProjectionMatrix(J9,o.coordinateSystem,o.reversedDepth);const m=a.name;a.name=`Point Light Shadow [ ${i.name||"ID: "+i.id} ] - Face ${x+1}`,s.render(a,o),a.name=m}s.autoClear=f,s.setClearColor(h,p)}}const _9=(r,e)=>new $K(r,e);class Pg extends yA{static get type(){return"AnalyticLightNode"}constructor(e=null){super(),this.light=e,this.color=new Vn,this.colorNode=e&&e.colorNode||Dr(this.color).setGroup(Rr),this.baseColorNode=null,this.shadowNode=null,this.shadowColorNode=null,this.isAnalyticLightNode=!0,this.updateType=Bi.FRAME,e&&e.shadow&&(this._shadowDisposeListener=()=>{this.disposeShadow()},e.addEventListener("dispose",this._shadowDisposeListener))}dispose(){this._shadowDisposeListener&&this.light.removeEventListener("dispose",this._shadowDisposeListener),super.dispose()}disposeShadow(){this.shadowNode!==null&&(this.shadowNode.dispose(),this.shadowNode=null),this.shadowColorNode=null,this.baseColorNode!==null&&(this.colorNode=this.baseColorNode,this.baseColorNode=null)}getHash(){return this.light.uuid}getLightVector(e){return kB(this.light).sub(e.context.positionView||po)}setupDirect(){}setupDirectRectArea(){}setupShadowNode(){return Y9(this.light)}setupShadow(e){const{renderer:t}=e;if(t.shadowMap.enabled===!1)return;let n=this.shadowColorNode;if(n===null){const i=this.light.shadow.shadowNode;let s;i!==void 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`),this.flow.code+=e,this)}addFlowCode(e){return this.flow.code+=e,this}addFlowTab(){return this.tab+="	",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){this.currentFunctionNode!==null&&this.currentFunctionNode.includes.push(e)}buildFunctionNode(e){const t=new M9,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 a=0;const o=Object.values(this);return{next:()=>({value:o[a],done:a++>=o.length})}}};for(const a of t.inputs)n[a.name]=new i9(a.type,a.name);e.layout=null;const i=e.call(n),s=this.flowStagesNode(i,t.type);return e.layout=t,s}flowBuildStage(e,t,n=null){const i=this.getBuildStage();this.setBuildStage(t);const s=e.build(this,n);return this.setBuildStage(i),s}flowStagesNode(e,t=null){const n=this.flow,i=this.vars,s=this.declarations,a=this.cache,o=this.buildStage,l=this.stack,u={code:""};this.flow=u,this.vars={},this.declarations={},this.cache=new $B,this.stack=XE();for(const c of LP)this.setBuildStage(c),u.result=e.build(this,t);return u.vars=this.getVars(this.shaderStage),this.flow=n,this.vars=i,this.declarations=s,this.cache=a,this.stack=l,this.setBuildStage(o),u}getFunctionOperator(){return null}buildFunctionCode(){ze("Abstract function.")}flowChildNode(e,t=null){const n=this.flow,i={code:""};return this.flow=i,i.result=e.build(this,t),this.flow=n,i}flowNodeFromShaderStage(e,t,n=null,i=null){const s=this.tab,a=this.cache,o=this.shaderStage,l=this.context;this.setShaderStage(e);const u=ba({},this.context);delete u.nodeBlock,this.cache=this.globalCache,this.tab="	",this.context=u;let c=null;if(this.buildStage==="generate"){const d=this.flowChildNode(t,n);i!==null&&(d.code+=`${this.tab+i} = ${d.result};
`),this.flowCode[e]=this.flowCode[e]+d.code,c=d}else c=t.build(this);return this.setShaderStage(o),this.cache=a,this.tab=s,this.context=l,c}getAttributesArray(){return this.attributes.concat(this.bufferAttributes)}getAttributes(){ze("Abstract function.")}getVaryings(){ze("Abstract function.")}getVar(e,t,n=null){return`${n!==null?this.generateArrayDeclaration(e,n):this.getType(e)} ${t}`}getVars(e){let t="";const n=this.vars[e];if(n!==void 0)for(const i of n)t+=`${this.getVar(i.type,i.name)}; `;return t}getUniforms(){ze("Abstract function.")}getCodes(e){const t=this.codes[e];let n="";if(t!==void 0)for(const i of t)n+=i.code+`
`;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(){ze("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(e&&e.isNode?e.isShaderCallNodeInternal?t=e.shaderNode.subBuilds:e.isStackNode?t=[e.subBuild]:t=this.getDataFromNode(e,"any").subBuilds:e instanceof Set?t=[...e]:t=e,!t)return null;const n=this.subBuildLayers;for(let i=t.length-1;i>=0;i--){const s=t[i];if(n.includes(s))return s}return null}getSubBuildOutput(e){return this.getSubBuildProperty("outputNode",e)}getSubBuildProperty(e="",t=null){let n;t!==null?n=this.getClosestSubBuild(t):n=this.subBuildFn;let i;return n?i=e?n+"_"+e:n:i=e,i}build(){const{object:e,material:t,renderer:n}=this;if(t!==null){let i=n.library.fromMaterial(t);i===null&&(rt(`NodeMaterial: Material "${t.type}" is not compatible.`),i=new Ka),i.build(this)}else this.addFlow("compute",e);for(const i of LP){this.setBuildStage(i),this.context.vertex&&this.context.vertex.isNode&&this.flowNodeFromShaderStage("vertex",this.context.vertex);for(const s of OP){this.setShaderStage(s);const a=this.flowNodes[s];for(const o of a)i==="generate"?this.flowNode(o):o.build(this)}}return this.setBuildStage(null),this.setShaderStage(null),this.buildCode(),this.buildUpdateNodes(),this}getSharedDataFromNode(e){let t=D_.get(e);return t===void 0&&(t={}),t}getNodeUniform(e,t){const n=this.getSharedDataFromNode(e);let i=n.cache;if(i===void 0){if(t==="float"||t==="int"||t==="uint")i=new y_(e);else if(t==="vec2"||t==="ivec2"||t==="uvec2")i=new b_(e);else if(t==="vec3"||t==="ivec3"||t==="uvec3")i=new E_(e);else if(t==="vec4"||t==="ivec4"||t==="uvec4")i=new w_(e);else if(t==="color")i=new C_(e);else if(t==="mat2")i=new P_(e);else if(t==="mat3")i=new B_(e);else if(t==="mat4")i=new M_(e);else throw new Error(`Uniform "${t}" not implemented.`);n.cache=i}return i}format(e,t,n){if(t=this.getVectorType(t),n=this.getVectorType(n),t===n||n===null||this.isReference(n))return e;const i=this.getTypeLength(t),s=this.getTypeLength(n);return i===16&&s===9?`${this.getType(n)}( ${e}[ 0 ].xyz, ${e}[ 1 ].xyz, ${e}[ 2 ].xyz )`:i===9&&s===4?`${this.getType(n)}( ${e}[ 0 ].xy, ${e}[ 1 ].xy )`:i>4||s>4||s===0?e:i===s?`${this.getType(n)}( ${e} )`:i>s?(e=n==="bool"?`all( ${e} )`:`${e}.${"xyz".slice(0,s)}`,this.format(e,this.getTypeFromLength(s,this.getComponentType(t)),n)):s===4&&i>1?`${this.getType(n)}( ${this.format(e,t,"vec3")}, 1.0 )`:i===2?`${this.getType(n)}( ${this.format(e,t,"vec2")}, 0.0 )`:(i===1&&s>1&&t!==this.getComponentType(n)&&(e=`${this.getType(this.getComponentType(n))}( ${e} )`),`${this.getType(n)}( ${e} )`)}getSignature(){return`// Three.js r${Fs} - Node System
`}}class hN{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 n===void 0&&(n={renderId:0,frameId:0},e.set(t,n)),n}updateBeforeNode(e){const t=e.getUpdateBeforeType(),n=e.updateReference(this);if(t===Bi.FRAME){const i=this._getMaps(this.updateBeforeMap,n);if(i.frameId!==this.frameId){const s=i.frameId;i.frameId=this.frameId,e.updateBefore(this)===!1&&(i.frameId=s)}}else if(t===Bi.RENDER){const i=this._getMaps(this.updateBeforeMap,n);if(i.renderId!==this.renderId){const s=i.renderId;i.renderId=this.renderId,e.updateBefore(this)===!1&&(i.renderId=s)}}else t===Bi.OBJECT&&e.updateBefore(this)}updateAfterNode(e){const t=e.getUpdateAfterType(),n=e.updateReference(this);if(t===Bi.FRAME){const i=this._getMaps(this.updateAfterMap,n);i.frameId!==this.frameId&&e.updateAfter(this)!==!1&&(i.frameId=this.frameId)}else if(t===Bi.RENDER){const i=this._getMaps(this.updateAfterMap,n);i.renderId!==this.renderId&&e.updateAfter(this)!==!1&&(i.renderId=this.renderId)}else t===Bi.OBJECT&&e.updateAfter(this)}updateNode(e){const t=e.getUpdateType(),n=e.updateReference(this);if(t===Bi.FRAME){const i=this._getMaps(this.updateMap,n);i.frameId!==this.frameId&&e.update(this)!==!1&&(i.frameId=this.frameId)}else if(t===Bi.RENDER){const i=this._getMaps(this.updateMap,n);i.renderId!==this.renderId&&e.update(this)!==!1&&(i.renderId=this.renderId)}else t===Bi.OBJECT&&e.update(this)}update(){this.frameId++,this.lastTime===void 0&&(this.lastTime=performance.now()),this.deltaTime=(performance.now()-this.lastTime)/1e3,this.lastTime=performance.now(),this.time+=this.deltaTime}}class eM{constructor(e,t,n=null,i="",s=!1){this.type=e,this.name=t,this.count=n,this.qualifier=i,this.isConst=s}}eM.isNodeFunctionInput=!0;class I_ extends Pg{static get type(){return"DirectionalLightNode"}constructor(e=null){super(e)}setupDirect(){const e=this.colorNode;return{lightDirection:VB(this.light),lightColor:e}}}const tM=new Cr,fw=new Cr;let Gx=null;class N_ extends Pg{static get type(){return"RectAreaLightNode"}constructor(e=null){super(e),this.halfHeight=Dr(new J).setGroup(Rr),this.halfWidth=Dr(new J).setGroup(Rr),this.updateType=Bi.RENDER}update(e){super.update(e);const{light:t}=this,n=e.camera.matrixWorldInverse;fw.identity(),tM.copy(t.matrixWorld),tM.premultiply(n),fw.extractRotation(tM),this.halfWidth.value.set(t.width*.5,0,0),this.halfHeight.value.set(0,t.height*.5,0),this.halfWidth.value.applyMatrix4(fw),this.halfHeight.value.applyMatrix4(fw)}setupDirectRectArea(e){let t,n;e.isAvailable("float32Filterable")?(t=Bs(Gx.LTC_FLOAT_1),n=Bs(Gx.LTC_FLOAT_2)):(t=Bs(Gx.LTC_HALF_1),n=Bs(Gx.LTC_HALF_2));const{colorNode:i,light:s}=this,a=kB(s);return{lightColor:i,lightPosition:a,halfWidth:this.halfWidth,halfHeight:this.halfHeight,ltc_1:t,ltc_2:n}}static setLTC(e){Gx=e}}class nM extends Pg{static get type(){return"SpotLightNode"}constructor(e=null){super(e),this.coneCosNode=Dr(0).setGroup(Rr),this.penumbraCosNode=Dr(0).setGroup(Rr),this.cutoffDistanceNode=Dr(0).setGroup(Rr),this.decayExponentNode=Dr(0).setGroup(Rr),this.colorNode=Dr(this.color).setGroup(Rr)}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 ic(n,i,t)}getLightCoord(e){const t=e.getNodeProperties(this);let n=t.projectionUV;return n===void 0&&(n=I9(this.light,e.context.positionWorld),t.projectionUV=n),n}setupDirect(e){const{colorNode:t,cutoffDistanceNode:n,decayExponentNode:i,light:s}=this,a=this.getLightVector(e),o=a.normalize(),l=o.dot(VB(s)),u=this.getSpotAttenuation(e,l),c=a.length(),d=JB({lightDistance:c,cutoffDistance:n,decayExponent:i});let f=t.mul(u).mul(d),h,p;return s.colorNode?(p=this.getLightCoord(e),h=s.colorNode(p)):s.map&&(p=this.getLightCoord(e),h=Bs(s.map,p.xy).onRenderUpdate(()=>s.map)),h&&(f=p.mul(2).sub(1).abs().lessThan(1).all().select(f.mul(h),f)),{lightColor:f,lightDirection:o}}}class F_ extends nM{static get type(){return"IESSpotLightNode"}getSpotAttenuation(e,t){const n=this.light.iesMap;let i=null;if(n&&n.isTexture===!0){const s=t.acos().mul(1/Math.PI);i=Bs(n,Wt(s,0),0).r}else i=super.getSpotAttenuation(t);return i}}const R_=be(([r,e])=>{const t=r.abs().sub(e);return bf(Ya(t,0)).add(Pu(Ya(t.x,t.y),0))});class L_ extends nM{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),t.aspect===null){let n=1;t.map!==null&&(n=t.map.width/t.map.height),t.shadow.aspect=n}else t.shadow.aspect=t.aspect}getSpotAttenuation(e){const t=K(0),n=this.penumbraCosNode,i=iw(this.light).mul(e.context.positionWorld||ac);return cr(i.w.greaterThan(0),()=>{const s=i.xyz.div(i.w),a=R_(s.xy.sub(Wt(.5)),Wt(.5)),o=rc(-1,us(1,a3(n)).sub(1));t.assign(mE(a.mul(-2).mul(o)))}),t}}class O_ extends Pg{static get type(){return"AmbientLightNode"}constructor(e=null){super(e)}setup({context:e}){e.irradiance.addAssign(this.colorNode)}}class z_ extends Pg{static get type(){return"HemisphereLightNode"}constructor(e=null){super(e),this.lightPositionNode=UB(e),this.lightDirectionNode=this.lightPositionNode.normalize(),this.groundColorNode=Dr(new Vn).setGroup(Rr)}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,a=jp.dot(i).mul(.5).add(.5),o=ss(n,t,a);e.context.irradiance.addAssign(o)}}class H_ extends Pg{static get type(){return"LightProbeNode"}constructor(e=null){super(e);const t=[];for(let n=0;n<9;n++)t.push(new J);this.lightProbe=Wl(t)}update(e){const{light:t}=this;super.update(e);for(let n=0;n<9;n++)this.lightProbe.array[n].copy(t.sh.coefficients[n]).multiplyScalar(t.intensity)}setup(e){const t=lN(jp,this.lightProbe);e.context.irradiance.addAssign(t)}}class pN{parseFunction(){ze("Abstract function.")}}class rM{constructor(e,t,n="",i=""){this.type=e,this.inputs=t,this.name=n,this.precision=i}getCode(){ze("Abstract function.")}}rM.isNodeFunction=!0;const U_=/^\s*(highp|mediump|lowp)?\s*([a-z_0-9]+)\s*([a-z_0-9]+)?\s*\(([\s\S]*?)\)/i,k_=/[a-z_0-9]+/ig,mN="#pragma main",V_=r=>{r=r.trim();const e=r.indexOf(mN),t=e!==-1?r.slice(e+mN.length):r,n=t.match(U_);if(n!==null&&n.length===5){const i=n[4],s=[];let a=null;for(;(a=k_.exec(i))!==null;)s.push(a);const o=[];let l=0;for(;l<s.length;){const p=s[l][0]==="const";p===!0&&l++;let x=s[l][0];x==="in"||x==="out"||x==="inout"?l++:x="";const v=s[l++][0];let m=Number.parseInt(s[l][0]);Number.isNaN(m)===!1?l++:m=null;const C=s[l++][0];o.push(new eM(v,C,m,x,p))}const u=t.substring(n[0].length),c=n[3]!==void 0?n[3]:"",d=n[2],f=n[1]!==void 0?n[1]:"",h=e!==-1?r.slice(0,e):"";return{type:d,inputs:o,name:c,precision:f,inputsCode:i,blockCode:u,headerCode:h}}else throw new Error("FunctionNode: Function is not a GLSL code.")};class j_ extends rM{constructor(e){const{type:t,inputs:n,name:i,precision:s,inputsCode:a,blockCode:o,headerCode:l}=V_(e);super(t,n,i,s),this.inputsCode=a,this.blockCode=o,this.headerCode=l}getCode(e=this.name){let t;const n=this.blockCode;if(n!==""){const{type:i,inputsCode:s,headerCode:a,precision:o}=this;let l=`${i} ${e} ( ${s.trim()} )`;o!==""&&(l=`${o} ${l}`),t=a+l+n}else t="";return t}}class X_ extends pN{parseFunction(e){return new j_(e)}}const gN=new WeakMap,If=[],Yp=[];class G_ extends Wp{constructor(e,t){super(),this.renderer=e,this.backend=t,this.nodeFrame=new hN,this.nodeBuilderCache=new Map,this.callHashCache=new Sd,this.groupsData=new Sd,this.cacheLib={}}updateGroup(e){const t=e.groupNode,n=t.name;if(n===e3.name)return!0;if(n===Rr.name){const s=this.get(e),a=this.nodeFrame.renderId;return s.renderId!==a?(s.renderId=a,!0):!1}if(n===f8.name){const s=this.get(e),a=this.nodeFrame.frameId;return s.frameId!==a?(s.frameId=a,!0):!1}If[0]=t,If[1]=e;let i=this.groupsData.get(If);return i===void 0&&this.groupsData.set(If,i={}),If.length=0,i.version!==t.version?(i.version=t.version,!0):!1}getForRenderCacheKey(e){return e.initialCacheKey}getForRender(e){const t=this.get(e);let n=t.nodeBuilderState;if(n===void 0){const{nodeBuilderCache:i}=this,s=this.getForRenderCacheKey(e);if(n=i.get(s),n===void 0){const a=l=>{const u=this.backend.createNodeBuilder(e.object,this.renderer);return u.scene=e.scene,u.material=l,u.camera=e.camera,u.context.material=l,u.lightsNode=e.lightsNode,u.environmentNode=this.getEnvironmentNode(e.scene),u.fogNode=this.getFogNode(e.scene),u.clippingContext=e.clippingContext,this.renderer.getOutputRenderTarget()&&this.renderer.getOutputRenderTarget().multiview&&u.enableMultiview(),u};let o=a(e.material);try{o.build()}catch(l){o=a(new Ka),o.build(),rt("TSL: "+l)}n=this._createNodeBuilderState(o),i.set(s,n)}n.usedTimes++,t.nodeBuilderState=n}return n}delete(e){if(e.isRenderObject){const t=this.get(e).nodeBuilderState;t.usedTimes--,t.usedTimes===0&&this.nodeBuilderCache.delete(this.getForRenderCacheKey(e))}return super.delete(e)}getForCompute(e){const t=this.get(e);let n=t.nodeBuilderState;if(n===void 0){const i=this.backend.createNodeBuilder(e,this.renderer);i.build(),n=this._createNodeBuilderState(i),t.nodeBuilderState=n}return n}_createNodeBuilderState(e){return new a_(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){If[0]=e,If[1]=t;const n=this.renderer.info.calls,i=this.callHashCache.get(If)||{};if(i.callId!==n){const s=this.getEnvironmentNode(e),a=this.getFogNode(e);t&&Yp.push(t.getCacheKey(!0)),s&&Yp.push(s.getCacheKey()),a&&Yp.push(a.getCacheKey()),Yp.push(this.renderer.getOutputRenderTarget()&&this.renderer.getOutputRenderTarget().multiview?1:0),Yp.push(this.renderer.shadowMap.enabled?1:0),Yp.push(this.renderer.shadowMap.type),i.callId=n,i.cacheKey=ag(Yp),this.callHashCache.set(If,i),Yp.length=0}return If.length=0,i.cacheKey}get isToneMappingState(){return!this.renderer.getRenderTarget()}updateBackground(e){const t=this.get(e),n=e.background;if(n){const i=e.backgroundBlurriness===0&&t.backgroundBlurriness>0||e.backgroundBlurriness>0&&t.backgroundBlurriness===0;if(t.background!==n||i){const s=this.getCacheNode("background",n,()=>{if(n.isCubeTexture===!0||n.mapping===Pa||n.mapping===ld||n.mapping===Jd){if(e.backgroundBlurriness>0||n.mapping===Jd)return wB(n);{let a;return n.isCubeTexture===!0?a=cu(n):a=Bs(n),c4(a)}}else{if(n.isTexture===!0)return Bs(n,Ph.flipY()).setUpdateMatrix(!0);n.isColor!==!0&&rt("WebGPUNodes: Unsupported background configuration.",n)}},i);t.backgroundNode=s,t.background=n,t.backgroundBlurriness=e.backgroundBlurriness}}else t.backgroundNode&&(delete t.backgroundNode,delete t.background)}getCacheNode(e,t,n,i=!1){const s=this.cacheLib[e]||(this.cacheLib[e]=new WeakMap);let a=s.get(t);return(a===void 0||i)&&(a=n(),s.set(t,a)),a}updateFog(e){const t=this.get(e),n=e.fog;if(n){if(t.fog!==n){const i=this.getCacheNode("fog",n,()=>{if(n.isFogExp2){const s=$s("color","color",n).setGroup(Rr),a=$s("density","float",n).setGroup(Rr);return zx(s,zB(a))}else if(n.isFog){const s=$s("color","color",n).setGroup(Rr),a=$s("near","float",n).setGroup(Rr),o=$s("far","float",n).setGroup(Rr);return zx(s,OB(a,o))}else rt("Renderer: Unsupported fog configuration.",n)});t.fogNode=i,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 i=this.getCacheNode("environment",n,()=>{if(n.isCubeTexture===!0)return cu(n);if(n.isTexture===!0)return Bs(n);rt("Nodes: Unsupported environment configuration.",n)});t.environmentNode=i,t.environment=n}}else t.environmentNode&&(delete t.environmentNode,delete t.environment)}getNodeFrame(e=this.renderer,t=null,n=null,i=null,s=null){const a=this.nodeFrame;return a.renderer=e,a.scene=t,a.object=n,a.camera=i,a.material=s,a}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 gN.get(e)!==this.getOutputCacheKey()}getOutputNode(e){const t=this.renderer,n=this.getOutputCacheKey(),i=e.isArrayTexture?qE(e,he(Ph,Ch("gl_ViewID_OVR"))).renderOutput(t.toneMapping,t.currentColorSpace):Bs(e,Ph).renderOutput(t.toneMapping,t.currentColorSpace);return gN.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 i of n.updateNodes)t.updateNode(i)}updateForRender(e){const t=this.getNodeFrameForRender(e),n=e.getNodeBuilderState();for(const i of n.updateNodes)t.updateNode(i)}needsRefresh(e){const t=this.getNodeFrameForRender(e);return e.getMonitor().needsRefresh(e,t)}dispose(){super.dispose(),this.nodeFrame=new hN,this.nodeBuilderCache=new Map,this.cacheLib={}}}const iM=new vd;class hw{constructor(e=null){this.version=0,this.clipIntersection=null,this.cacheKey="",this.shadowPass=!1,this.viewNormalMatrix=new zi,this.clippingGroupContexts=new WeakMap,this.intersectionPlanes=[],this.unionPlanes=[],this.parentVersion=null,e!==null&&(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 s=0;s<i;s++){iM.copy(e[s]).applyMatrix4(this.viewMatrix,this.viewNormalMatrix);const a=t[n+s],o=iM.normal;a.x=-o.x,a.y=-o.y,a.z=-o.z,a.w=iM.constant}}updateGlobal(e,t){this.shadowPass=e.overrideMaterial!==null&&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,s=i.length;let a,o;if(this.clipIntersection?(a=this.intersectionPlanes,o=e.intersectionPlanes.length):(a=this.unionPlanes,o=e.unionPlanes.length),a.length!==o+s){a.length=o+s;for(let l=0;l<s;l++)a[o+l]=new Ei;n=!0}this.projectPlanes(i,a,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 t===void 0&&(t=new hw(this),this.clippingGroupContexts.set(e,t)),t.update(this,e),t}get unionClippingCount(){return this.unionPlanes.length}}class W_{constructor(e,t){this.bundleGroup=e,this.camera=t}}const Wx=[];class Q_{constructor(){this.bundles=new Sd}get(e,t){const n=this.bundles;Wx[0]=e,Wx[1]=t;let i=n.get(Wx);return i===void 0&&(i=new W_(e,t),n.set(Wx,i)),Wx.length=0,i}dispose(){this.bundles=new Sd}}class vN{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(n!==null){t=new n;for(const i in e)t[i]=e[i]}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)){ze(`Redefinition of node ${t}`);return}if(typeof e!="function")throw new Error(`Node class ${e.name} is not a class.`);if(typeof t=="function"||typeof t=="object")throw new Error(`Base class ${t} is not a class.`);n.set(t,e)}addClass(e,t,n){if(n.has(t)){ze(`Redefinition of node ${t.name}`);return}if(typeof e!="function")throw new Error(`Node class ${e.name} is not a class.`);if(typeof t!="function")throw new Error(`Base class ${t.name} is not a class.`);n.set(t,e)}}const Z_=new XB,Qx=[];class Y_ extends Sd{constructor(){super()}createNode(e=[]){return new XB().setLights(e)}getNode(e,t){if(e.isQuadMesh)return Z_;Qx[0]=e,Qx[1]=t;let n=this.get(Qx);return n===void 0&&(n=this.createNode(),this.set(Qx,n)),Qx.length=0,n}}class Zx extends sh{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 AN=new J,xN=new J;class J_ extends Go{constructor(e,t=!1){super(),this.enabled=!1,this.isPresenting=!1,this.cameraAutoUpdate=!0,this._renderer=e,this._cameraL=new bo,this._cameraL.viewport=new Ei,this._cameraR=new bo,this._cameraR.viewport=new Ei,this._cameras=[this._cameraL,this._cameraR],this._cameraXR=new $5,this._currentDepthNear=null,this._currentDepthFar=null,this._controllers=[],this._controllerInputSources=[],this._xrRenderTarget=null,this._layers=[],this._sessionUsesLayers=!1,this._supportsGlBinding=typeof XRWebGLBinding!="undefined",this._frameBufferTargets=null,this._createXRLayer=t$.bind(this),this._gl=null,this._currentAnimationContext=null,this._currentAnimationLoop=null,this._currentPixelRatio=null,this._currentSize=new ct,this._onSessionEvent=__.bind(this),this._onSessionEnd=$_.bind(this),this._onInputSourcesChange=e$.bind(this),this._onAnimationFrame=n$.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(!(this._glProjLayer===null&&this._glBaseLayer===null))return this._foveation}setFoveation(e){this._foveation=e,this._glProjLayer!==null&&(this._glProjLayer.fixedFoveation=e),this._glBaseLayer!==null&&this._glBaseLayer.fixedFoveation!==void 0&&(this._glBaseLayer.fixedFoveation=e)}getFramebufferScaleFactor(){return this._framebufferScaleFactor}setFramebufferScaleFactor(e){this._framebufferScaleFactor=e,this.isPresenting===!0&&ze("XRManager: Cannot change framebuffer scale while presenting.")}getReferenceSpaceType(){return this._referenceSpaceType}setReferenceSpaceType(e){this._referenceSpaceType=e,this.isPresenting===!0&&ze("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(this._session!==null)return this._session.environmentBlendMode}getBinding(){return this._glBinding===null&&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,s,a,o,l={}){const u=new Jv(e,t),c=new Zx(s,a,{format:ma,type:fa,depthTexture:new Vl(s,a,l.stencil?Ll:Ls,void 0,void 0,void 0,void 0,void 0,void 0,l.stencil?vl:jo),stencilBuffer:l.stencil,resolveDepthBuffer:!1,resolveStencilBuffer:!1});c._autoAllocateDepthBuffer=!0;const d=new rl({color:16777215,side:ja});d.map=c.texture,d.map.offset.y=1,d.map.repeat.y=-1;const f=new Gs(u,d);f.position.copy(n),f.quaternion.copy(i);const h={type:"quad",width:e,height:t,translation:n,quaternion:i,pixelwidth:s,pixelheight:a,plane:f,material:d,rendercall:o,renderTarget:c};if(this._layers.push(h),this._session!==null){h.plane.material=new rl({color:16777215,side:ja}),h.plane.material.blending=yc,h.plane.material.blendEquation=io,h.plane.material.blendSrc=ml,h.plane.material.blendDst=ml,h.xrlayer=this._createXRLayer(h);const p=this._session.renderState.layers;p.unshift(h.xrlayer),this._session.updateRenderState({layers:p})}else c.isXRRenderTarget=!1;return f}createCylinderLayer(e,t,n,i,s,a,o,l,u={}){const c=new Qv(e,e,e*t/n,64,64,!0,Math.PI-t/2,t),d=new Zx(a,o,{format:ma,type:fa,depthTexture:new Vl(a,o,u.stencil?Ll:Ls,void 0,void 0,void 0,void 0,void 0,void 0,u.stencil?vl:jo),stencilBuffer:u.stencil,resolveDepthBuffer:!1,resolveStencilBuffer:!1});d._autoAllocateDepthBuffer=!0;const f=new rl({color:16777215,side:Qi});f.map=d.texture,f.map.offset.y=1,f.map.repeat.y=-1;const h=new Gs(c,f);h.position.copy(i),h.quaternion.copy(s);const p={type:"cylinder",radius:e,centralAngle:t,aspectratio:n,translation:i,quaternion:s,pixelwidth:a,pixelheight:o,plane:h,material:f,rendercall:l,renderTarget:d};if(this._layers.push(p),this._session!==null){p.plane.material=new rl({color:16777215,side:Qi}),p.plane.material.blending=yc,p.plane.material.blendEquation=io,p.plane.material.blendSrc=ml,p.plane.material.blendDst=ml,p.xrlayer=this._createXRLayer(p);const x=this._session.renderState.layers;x.unshift(p.xrlayer),this._session.updateRenderState({layers:x})}else d.isXRRenderTarget=!1;return h}renderLayers(){const e=new J,t=new Wo,n=this._renderer,i=this.isPresenting,s=n.getOutputRenderTarget(),a=n._frameBufferTarget;this.isPresenting=!1;const o=new ct;n.getSize(o);const l=n._quad;for(const u of this._layers)if(u.renderTarget.isXRRenderTarget=this._session!==null,u.renderTarget._hasExternalTextures=u.renderTarget.isXRRenderTarget,u.renderTarget.isXRRenderTarget&&this._sessionUsesLayers){u.xrlayer.transform=new XRRigidTransform(u.plane.getWorldPosition(e),u.plane.getWorldQuaternion(t));const c=this._glBinding.getSubImage(u.xrlayer,this._xrFrame);n.backend.setXRRenderTargetTextures(u.renderTarget,c.colorTexture,void 0),n._setXRLayerSize(u.renderTarget.width,u.renderTarget.height),n.setOutputRenderTarget(u.renderTarget),n.setRenderTarget(null),n._frameBufferTarget=null,this._frameBufferTargets||(this._frameBufferTargets=new WeakMap);const{frameBufferTarget:d,quad:f}=this._frameBufferTargets.get(u.renderTarget)||{frameBufferTarget:null,quad:null};d?(n._frameBufferTarget=d,n._quad=f):(n._quad=new Lx(new Ka),this._frameBufferTargets.set(u.renderTarget,{frameBufferTarget:n._getFrameBufferTarget(),quad:n._quad})),u.rendercall(),n._frameBufferTarget=null}else n.setRenderTarget(u.renderTarget),u.rendercall();n.setRenderTarget(null),n.setOutputRenderTarget(s),n._frameBufferTarget=a,n._setXRLayerSize(o.x,o.y),n._quad=l,this.isPresenting=i}getSession(){return this._session}setSession(e){return Kr(this,null,function*(){const t=this._renderer,n=t.backend;this._gl=t.getContext();const i=this._gl,s=i.getContextAttributes();if(this._session=e,e!==null){if(n.isWebGPUBackend===!0)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),yield n.makeXRCompatible(),this._currentPixelRatio=t.getPixelRatio(),t.getSize(this._currentSize),this._currentAnimationContext=t._animation.getContext(),this._currentAnimationLoop=t._animation.getAnimationLoop(),t._animation.stop(),this._supportsLayers===!0){let a=null,o=null,l=null;t.depth&&(l=t.stencil?i.DEPTH24_STENCIL8:i.DEPTH_COMPONENT24,a=t.stencil?vl:jo,o=t.stencil?Ll:Ls);const u={colorFormat:i.RGBA8,depthFormat:l,scaleFactor:this._framebufferScaleFactor,clearOnAccess:!1};this._useMultiviewIfPossible&&t.hasFeature("OVR_multiview2")&&(u.textureType="texture-array",this._useMultiview=!0),this._glBinding=this.getBinding();const c=this._glBinding.createProjectionLayer(u),d=[c];this._glProjLayer=c,t.setPixelRatio(1),t._setXRLayerSize(c.textureWidth,c.textureHeight);const f=this._useMultiview?2:1,h=new Vl(c.textureWidth,c.textureHeight,o,void 0,void 0,void 0,void 0,void 0,void 0,a,f);if(this._xrRenderTarget=new Zx(c.textureWidth,c.textureHeight,{format:ma,type:fa,colorSpace:t.outputColorSpace,depthTexture:h,stencilBuffer:t.stencil,samples:s.antialias?4:0,resolveDepthBuffer:c.ignoreDepthValues===!1,resolveStencilBuffer:c.ignoreDepthValues===!1,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=yield e.requestReferenceSpace(this.getReferenceSpaceType()),this._sessionUsesLayers)for(const p of this._layers)p.plane.material=new rl({color:16777215,side:p.type==="cylinder"?Qi:ja}),p.plane.material.blending=yc,p.plane.material.blendEquation=io,p.plane.material.blendSrc=ml,p.plane.material.blendDst=ml,p.xrlayer=this._createXRLayer(p),d.unshift(p.xrlayer);e.updateRenderState({layers:d})}else{const a={antialias:t.currentSamples>0,alpha:!0,depth:t.depth,stencil:t.stencil,framebufferScaleFactor:this.getFramebufferScaleFactor()},o=new XRWebGLLayer(e,i,a);this._glBaseLayer=o,e.updateRenderState({baseLayer:o}),t.setPixelRatio(1),t._setXRLayerSize(o.framebufferWidth,o.framebufferHeight),this._xrRenderTarget=new Zx(o.framebufferWidth,o.framebufferHeight,{format:ma,type:fa,colorSpace:t.outputColorSpace,stencilBuffer:t.stencil,resolveDepthBuffer:o.ignoreDepthValues===!1,resolveStencilBuffer:o.ignoreDepthValues===!1}),this._xrRenderTarget._isOpaqueFramebuffer=!0,this._referenceSpace=yield 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(t===null)return;const n=e.near,i=e.far,s=this._cameraXR,a=this._cameraL,o=this._cameraR;s.near=o.near=a.near=n,s.far=o.far=a.far=i,s.isMultiViewCamera=this._useMultiview,(this._currentDepthNear!==s.near||this._currentDepthFar!==s.far)&&(t.updateRenderState({depthNear:s.near,depthFar:s.far}),this._currentDepthNear=s.near,this._currentDepthFar=s.far),s.layers.mask=e.layers.mask|6,a.layers.mask=s.layers.mask&3,o.layers.mask=s.layers.mask&5;const l=e.parent,u=s.cameras;yN(s,l);for(let c=0;c<u.length;c++)yN(u[c],l);u.length===2?K_(s,a,o):s.projectionMatrix.copy(a.projectionMatrix),q_(e,s,l)}_getController(e){let t=this._controllers[e];return t===void 0&&(t=new Xy,this._controllers[e]=t),t}}function K_(r,e,t){AN.setFromMatrixPosition(e.matrixWorld),xN.setFromMatrixPosition(t.matrixWorld);const n=AN.distanceTo(xN),i=e.projectionMatrix.elements,s=t.projectionMatrix.elements,a=i[14]/(i[10]-1),o=i[14]/(i[10]+1),l=(i[9]+1)/i[5],u=(i[9]-1)/i[5],c=(i[8]-1)/i[0],d=(s[8]+1)/s[0],f=a*c,h=a*d,p=n/(-c+d),x=p*-c;if(e.matrixWorld.decompose(r.position,r.quaternion,r.scale),r.translateX(x),r.translateZ(p),r.matrixWorld.compose(r.position,r.quaternion,r.scale),r.matrixWorldInverse.copy(r.matrixWorld).invert(),i[10]===-1)r.projectionMatrix.copy(e.projectionMatrix),r.projectionMatrixInverse.copy(e.projectionMatrixInverse);else{const v=a+p,m=o+p,C=f-x,w=h+(n-x),P=l*o/m*v,B=u*o/m*v;r.projectionMatrix.makePerspective(C,w,P,B,v,m),r.projectionMatrixInverse.copy(r.projectionMatrix).invert()}}function yN(r,e){e===null?r.matrixWorld.copy(r.matrix):r.matrixWorld.multiplyMatrices(e.matrixWorld,r.matrix),r.matrixWorldInverse.copy(r.matrixWorld).invert()}function q_(r,e,t){t===null?r.matrix.copy(e.matrixWorld):(r.matrix.copy(t.matrixWorld),r.matrix.invert(),r.matrix.multiply(e.matrixWorld)),r.matrix.decompose(r.position,r.quaternion,r.scale),r.updateMatrixWorld(!0),r.projectionMatrix.copy(e.projectionMatrix),r.projectionMatrixInverse.copy(e.projectionMatrixInverse),r.isPerspectiveCamera&&(r.fov=Bc*2*Math.atan(1/r.projectionMatrix.elements[5]),r.zoom=1)}function __(r){const e=this._controllerInputSources.indexOf(r.inputSource);if(e===-1)return;const t=this._controllers[e];if(t!==void 0){const n=this.getReferenceSpace();t.update(r.inputSource,r.frame,n),t.dispatchEvent({type:r.type,data:r.inputSource})}}function $_(){const r=this._session,e=this._renderer;r.removeEventListener("select",this._onSessionEvent),r.removeEventListener("selectstart",this._onSessionEvent),r.removeEventListener("selectend",this._onSessionEvent),r.removeEventListener("squeeze",this._onSessionEvent),r.removeEventListener("squeezestart",this._onSessionEvent),r.removeEventListener("squeezeend",this._onSessionEvent),r.removeEventListener("end",this._onSessionEnd),r.removeEventListener("inputsourceschange",this._onInputSourcesChange);for(let t=0;t<this._controllers.length;t++){const n=this._controllerInputSources[t];n!==null&&(this._controllerInputSources[t]=null,this._controllers[t].disconnect(n))}if(this._currentDepthNear=null,this._currentDepthFar=null,e._resetXRState(),this._session=null,this._xrRenderTarget=null,this._glBinding=null,this._glBaseLayer=null,this._glProjLayer=null,this._sessionUsesLayers===!0)for(const t of this._layers)t.renderTarget=new Zx(t.pixelwidth,t.pixelheight,{format:ma,type:fa,depthTexture:new Vl(t.pixelwidth,t.pixelheight,t.stencilBuffer?Ll:Ls,void 0,void 0,void 0,void 0,void 0,void 0,t.stencilBuffer?vl:jo),stencilBuffer:t.stencilBuffer,resolveDepthBuffer:!1,resolveStencilBuffer:!1}),t.renderTarget.isXRRenderTarget=!1,t.plane.material=t.material,t.material.map=t.renderTarget.texture,t.material.map.offset.y=1,t.material.map.repeat.y=-1,delete t.xrlayer;this.isPresenting=!1,this._useMultiview=!1,e._animation.stop(),e._animation.setAnimationLoop(this._currentAnimationLoop),e._animation.setContext(this._currentAnimationContext),e._animation.start(),e.setPixelRatio(this._currentPixelRatio),e.setSize(this._currentSize.width,this._currentSize.height,!1),this.dispatchEvent({type:"sessionend"})}function e$(r){const e=this._controllers,t=this._controllerInputSources;for(let n=0;n<r.removed.length;n++){const i=r.removed[n],s=t.indexOf(i);s>=0&&(t[s]=null,e[s].disconnect(i))}for(let n=0;n<r.added.length;n++){const i=r.added[n];let s=t.indexOf(i);if(s===-1){for(let o=0;o<e.length;o++)if(o>=t.length){t.push(i),s=o;break}else if(t[o]===null){t[o]=i,s=o;break}if(s===-1)break}const a=e[s];a&&a.connect(i)}}function t$(r){return r.type==="quad"?this._glBinding.createQuadLayer({transform:new XRRigidTransform(r.translation,r.quaternion),width:r.width/2,height:r.height/2,space:this._referenceSpace,viewPixelWidth:r.pixelwidth,viewPixelHeight:r.pixelheight,clearOnAccess:!1}):this._glBinding.createCylinderLayer({transform:new XRRigidTransform(r.translation,r.quaternion),radius:r.radius,centralAngle:r.centralAngle,aspectRatio:r.aspectRatio,space:this._referenceSpace,viewPixelWidth:r.pixelwidth,viewPixelHeight:r.pixelheight,clearOnAccess:!1})}function n$(r,e){if(e===void 0)return;const t=this._cameraXR,n=this._renderer,i=n.backend,s=this._glBaseLayer,a=this.getReferenceSpace(),o=e.getViewerPose(a);if(this._xrFrame=e,o!==null){const l=o.views;this._glBaseLayer!==null&&i.setXRTarget(s.framebuffer);let u=!1;l.length!==t.cameras.length&&(t.cameras.length=0,u=!0);for(let c=0;c<l.length;c++){const d=l[c];let f;if(this._supportsLayers===!0){const p=this._glBinding.getViewSubImage(this._glProjLayer,d);f=p.viewport,c===0&&i.setXRRenderTargetTextures(this._xrRenderTarget,p.colorTexture,this._glProjLayer.ignoreDepthValues&&!this._useMultiview?void 0:p.depthStencilTexture)}else f=s.getViewport(d);let h=this._cameras[c];h===void 0&&(h=new bo,h.layers.enable(c),h.viewport=new Ei,this._cameras[c]=h),h.matrix.fromArray(d.transform.matrix),h.matrix.decompose(h.position,h.quaternion,h.scale),h.projectionMatrix.fromArray(d.projectionMatrix),h.projectionMatrixInverse.copy(h.projectionMatrix).invert(),h.viewport.set(f.x,f.y,f.width,f.height),c===0&&(t.matrix.copy(h.matrix),t.matrix.decompose(t.position,t.quaternion,t.scale)),u===!0&&t.cameras.push(h)}n.setOutputRenderTarget(this._xrRenderTarget)}for(let l=0;l<this._controllers.length;l++){const u=this._controllerInputSources[l],c=this._controllers[l];u!==null&&c!==void 0&&c.update(u,e,a)}this._currentAnimationLoop&&this._currentAnimationLoop(r,e),e.detectedPlanes&&this.dispatchEvent({type:"planesdetected",data:e}),this._xrFrame=null}class r$ extends Go{constructor(e){super(),this.domElement=e,this._pixelRatio=1,this._width=this.domElement.width,this._height=this.domElement.height,this._viewport=new Ei(0,0,this._width,this._height),this._scissor=new Ei(0,0,this._width,this._height),this._scissorTest=!1,this.colorTexture=new o1,this.depthTexture=new Vl}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._dispatchResize())}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),n===!0&&(this.domElement.style.width=e+"px",this.domElement.style.height=t+"px"),this.setViewport(0,0,e,t),this._dispatchResize())}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 s=this._scissor;e.isVector4?s.copy(e):s.set(e,t,n,i)}getScissorTest(){return this._scissorTest}setScissorTest(e){this._scissorTest=e}getViewport(e){return e.copy(this._viewport)}setViewport(e,t,n,i,s=0,a=1){const o=this._viewport;e.isVector4?o.copy(e):o.set(e,t,n,i),o.minDepth=s,o.maxDepth=a}_dispatchResize(){this.dispatchEvent({type:"resize"})}dispose(){this.dispatchEvent({type:"dispose"})}}const bN=new R0,FA=new ct,sM=new Ei,aM=new Wv,oM=new _y,pw=new Cr,Ih=new Ei;class i${constructor(e,t={}){this.isRenderer=!0;const{logarithmicDepthBuffer:n=!1,alpha:i=!0,depth:s=!0,stencil:a=!1,antialias:o=!1,samples:l=0,getFallback:u=null,outputBufferType:c=pa,multiview:d=!1}=t;this.backend=e,this.autoClear=!0,this.autoClearColor=!0,this.autoClearDepth=!0,this.autoClearStencil=!0,this.alpha=i,this.logarithmicDepthBuffer=n,this.outputColorSpace=nl,this.toneMapping=Fr,this.toneMappingExposure=1,this.sortObjects=!0,this.depth=s,this.stencil=a,this.info=new FZ,this.contextNode=bh(),this.library=new vN,this.lighting=new Y_,this._samples=l||o===!0?4:0,this._onCanvasTargetResize=this._onCanvasTargetResize.bind(this),this._canvasTarget=new r$(e.getDomElement()),this._canvasTarget.addEventListener("resize",this._onCanvasTargetResize),this._canvasTarget.isDefaultCanvasTarget=!0,this._inspector=new N2,this._inspector.setRenderer(this),this._getFallback=u,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 Lx(new Ka),this._quad.name="Output Color Transform",this._quad.material.name="outputColorTransform",this._currentRenderContext=null,this._opaqueSort=null,this._transparentSort=null,this._frameBufferTarget=null;const f=this.alpha===!0?0:1;this._clearColor=new PB(0,0,0,f),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._outputBufferType=c,this._cacheShadowNodes=new WeakMap,this._initialized=!1,this._initPromise=null,this._compilationPromises=null,this.transparent=!0,this.opaque=!0,this.shadowMap={enabled:!1,type:tu},this.xr=new J_(this,d),this.debug={checkShaderErrors:!0,onShaderError:null,getShaderAsync:(h,p,x)=>Kr(this,null,function*(){yield this.compileAsync(h,p);const v=this._renderLists.get(h,p),m=this._renderContexts.get(h,p,this._renderTarget,this._mrt),C=h.overrideMaterial||x.material,w=this._objects.get(x,C,h,p,v.lightsNode,m,m.clippingContext),{fragmentShader:P,vertexShader:B}=w.getNodeBuilderState();return{fragmentShader:P,vertexShader:B}})}}init(){return Kr(this,null,function*(){return this._initPromise!==null?this._initPromise:(this._initPromise=new Promise((e,t)=>Kr(this,null,function*(){let n=this.backend;try{yield n.init(this)}catch(i){if(this._getFallback!==null)try{this.backend=n=this._getFallback(i),yield n.init(this)}catch(s){t(s);return}else{t(i);return}}this._nodes=new G_(this,n),this._animation=new CZ(this,this._nodes,this.info),this._attributes=new IZ(n),this._background=new i_(this,this._nodes),this._geometries=new NZ(this._attributes,this.info),this._textures=new YZ(this,n,this.info),this._pipelines=new zZ(n,this._nodes),this._bindings=new HZ(n,this._nodes,this._textures,this._attributes,this._pipelines,this.info),this._objects=new SZ(this,this._nodes,this._geometries,this._pipelines,this._bindings,this.info),this._renderLists=new VZ(this.lighting),this._bundles=new Q_,this._renderContexts=new QZ,this._animation.start(),this._initialized=!0,this._inspector.init(),e(this)})),this._initPromise)})}get domElement(){return this._canvasTarget.domElement}get coordinateSystem(){return this.backend.coordinateSystem}compileAsync(e,t,n=null){return Kr(this,null,function*(){if(this._isDeviceLost===!0)return;this._initialized===!1&&(yield this.init());const i=this._nodes.nodeFrame,s=i.renderId,a=this._currentRenderContext,o=this._currentRenderObjectFunction,l=this._compilationPromises,u=e.isScene===!0?e:bN;n===null&&(n=e);const c=this._renderTarget,d=this._renderContexts.get(n,t,c,this._mrt),f=this._activeMipmapLevel,h=[];this._currentRenderContext=d,this._currentRenderObjectFunction=this.renderObject,this._handleObjectFunction=this._createObjectPipeline,this._compilationPromises=h,i.renderId++,i.update(),d.depth=this.depth,d.stencil=this.stencil,d.clippingContext||(d.clippingContext=new hw),d.clippingContext.updateGlobal(u,t),u.onBeforeRender(this,e,t,c);const p=this._renderLists.get(e,t);if(p.begin(),this._projectObject(e,t,0,p,d.clippingContext),n!==e&&n.traverseVisible(function(w){w.isLight&&w.layers.test(t.layers)&&p.pushLight(w)}),p.finish(),c!==null){this._textures.updateRenderTarget(c,f);const w=this._textures.get(c);d.textures=w.textures,d.depthTexture=w.depthTexture}else d.textures=null,d.depthTexture=null;this._background.update(u,p,d);const x=p.opaque,v=p.transparent,m=p.transparentDoublePass,C=p.lightsNode;this.opaque===!0&&x.length>0&&this._renderObjects(x,t,u,C),this.transparent===!0&&v.length>0&&this._renderTransparents(v,m,t,u,C),i.renderId=s,this._currentRenderContext=a,this._currentRenderObjectFunction=o,this._compilationPromises=l,this._handleObjectFunction=this._renderObjectDirect,yield Promise.all(h)})}renderAsync(e,t){return Kr(this,null,function*(){rs('Renderer: "renderAsync()" has been deprecated. Use "render()" and "await renderer.init();" when creating the renderer.'),yield this.init(),this.render(e,t)})}waitForGPU(){return Kr(this,null,function*(){rt("Renderer: waitForGPU() has been removed. Read https://github.com/mrdoob/three.js/issues/32012 for more information.")})}set inspector(e){this._inspector!==null&&this._inspector.setRenderer(null),this._inspector=e,this._inspector.setRenderer(this)}get inspector(){return this._inspector}set highPrecision(e){const t=this.contextNode.value;e===!0?(t.modelViewMatrix=I3,t.modelNormalViewMatrix=N3):this.highPrecision&&(delete t.modelViewMatrix,delete t.modelNormalViewMatrix)}get highPrecision(){const e=this.contextNode.value;return e.modelViewMatrix===I3&&e.modelNormalViewMatrix===N3}setMRT(e){return this._mrt=e,this}getMRT(){return this._mrt}getOutputBufferType(){return this._outputBufferType}getColorBufferType(){return rs('Renderer: ".getColorBufferType()" has been renamed to ".getOutputBufferType()".'),this.getOutputBufferType()}_onDeviceLost(e){let t=`THREE.WebGPURenderer: ${e.api} Device Lost:

Message: ${e.message}`;e.reason&&(t+=`
Reason: ${e.reason}`),rt(t),this._isDeviceLost=!0}_renderBundle(e,t,n){const{bundleGroup:i,camera:s,renderList:a}=e,o=this._currentRenderContext,l=this._bundles.get(i,s),u=this.backend.get(l);u.renderContexts===void 0&&(u.renderContexts=new Set);const c=i.version!==u.version,d=u.renderContexts.has(o)===!1||c;if(u.renderContexts.add(o),d){this.backend.beginBundle(o),(u.renderObjects===void 0||c)&&(u.renderObjects=[]),this._currentRenderBundle=l;const{transparentDoublePass:f,transparent:h,opaque:p}=a;this.opaque===!0&&p.length>0&&this._renderObjects(p,s,t,n),this.transparent===!0&&h.length>0&&this._renderTransparents(h,f,s,t,n),this._currentRenderBundle=null,this.backend.finishBundle(o,l),u.version=i.version}else{const{renderObjects:f}=u;for(let h=0,p=f.length;h<p;h++){const x=f[h];this._nodes.needsRefresh(x)&&(this._nodes.updateBefore(x),this._nodes.updateForRender(x),this._bindings.updateForRender(x),this._nodes.updateAfter(x))}}this.backend.addBundle(o,l)}render(e,t){if(this._initialized===!1)throw new Error('Renderer: .render() called before the backend is initialized. Use "await renderer.init();" before rendering.');this._renderScene(e,t)}get initialized(){return this._initialized}_getFrameBufferTarget(){const{currentToneMapping:e,currentColorSpace:t}=this,n=e!==Fr,i=t!==$r.workingColorSpace;if(n===!1&&i===!1)return null;const{width:s,height:a}=this.getDrawingBufferSize(FA),{depth:o,stencil:l}=this;let u=this._frameBufferTarget;u===null&&(u=new sh(s,a,{depthBuffer:o,stencilBuffer:l,type:this._outputBufferType,format:ma,colorSpace:$r.workingColorSpace,generateMipmaps:!1,minFilter:ms,magFilter:ms,samples:this.samples}),u.isPostProcessingRenderTarget=!0,this._frameBufferTarget=u);const c=this.getOutputRenderTarget();u.depthBuffer=o,u.stencilBuffer=l,c!==null?u.setSize(c.width,c.height,c.depth):u.setSize(s,a,1);const d=this._canvasTarget;return u.viewport.copy(d._viewport),u.scissor.copy(d._scissor),u.viewport.multiplyScalar(d._pixelRatio),u.scissor.multiplyScalar(d._pixelRatio),u.scissorTest=d._scissorTest,u.multiview=c!==null?c.multiview:!1,u.resolveDepthBuffer=c!==null?c.resolveDepthBuffer:!0,u._autoAllocateDepthBuffer=c!==null?c._autoAllocateDepthBuffer:!1,u}_renderScene(e,t,n=!0){if(this._isDeviceLost===!0)return;const i=n?this._getFrameBufferTarget():null,s=this._nodes.nodeFrame,a=s.renderId,o=this._currentRenderContext,l=this._currentRenderObjectFunction,u=e.isScene===!0?e:bN,c=this._renderTarget||this._outputRenderTarget,d=this._activeCubeFace,f=this._activeMipmapLevel;let h;i!==null?(h=i,this.setRenderTarget(h)):h=c;const p=this._renderContexts.get(e,t,h,this._mrt);this._currentRenderContext=p,this._currentRenderObjectFunction=this._renderObjectFunction||this.renderObject,this.info.calls++,this.info.render.calls++,this.info.render.frameCalls++,s.renderId=this.info.calls,this.backend.updateTimeStampUID(p),this.inspector.beginRender(this.backend.getTimestampUID(p),e,t,h);const x=this.coordinateSystem,v=this.xr;if(t.coordinateSystem!==x&&v.isPresenting===!1&&(t.coordinateSystem=x,t.updateProjectionMatrix(),t.isArrayCamera))for(const Q of t.cameras)Q.coordinateSystem=x,Q.updateProjectionMatrix();e.matrixWorldAutoUpdate===!0&&e.updateMatrixWorld(),t.parent===null&&t.matrixWorldAutoUpdate===!0&&t.updateMatrixWorld(),v.enabled===!0&&v.isPresenting===!0&&(v.cameraAutoUpdate===!0&&v.updateCamera(t),t=v.getCamera());const m=this._canvasTarget;let C=m._viewport,w=m._scissor,P=m._pixelRatio;h!==null&&(C=h.viewport,w=h.scissor,P=1),this.getDrawingBufferSize(FA),sM.set(0,0,FA.width,FA.height);const B=C.minDepth===void 0?0:C.minDepth,S=C.maxDepth===void 0?1:C.maxDepth;p.viewportValue.copy(C).multiplyScalar(P).floor(),p.viewportValue.width>>=f,p.viewportValue.height>>=f,p.viewportValue.minDepth=B,p.viewportValue.maxDepth=S,p.viewport=p.viewportValue.equals(sM)===!1,p.scissorValue.copy(w).multiplyScalar(P).floor(),p.scissor=m._scissorTest&&p.scissorValue.equals(sM)===!1,p.scissorValue.width>>=f,p.scissorValue.height>>=f,p.clippingContext||(p.clippingContext=new hw),p.clippingContext.updateGlobal(u,t),u.onBeforeRender(this,e,t,h);const I=t.isArrayCamera?oM:aM;t.isArrayCamera||(pw.multiplyMatrices(t.projectionMatrix,t.matrixWorldInverse),I.setFromProjectionMatrix(pw,t.coordinateSystem,t.reversedDepth));const N=this._renderLists.get(e,t);if(N.begin(),this._projectObject(e,t,0,N,p.clippingContext),N.finish(),this.sortObjects===!0&&N.sort(this._opaqueSort,this._transparentSort),h!==null){this._textures.updateRenderTarget(h,f);const Q=this._textures.get(h);p.textures=Q.textures,p.depthTexture=Q.depthTexture,p.width=Q.width,p.height=Q.height,p.renderTarget=h,p.depth=h.depthBuffer,p.stencil=h.stencilBuffer}else p.textures=null,p.depthTexture=null,p.width=FA.width,p.height=FA.height,p.depth=this.depth,p.stencil=this.stencil;p.width>>=f,p.height>>=f,p.activeCubeFace=d,p.activeMipmapLevel=f,p.occlusionQueryCount=N.occlusionQueryCount,p.scissorValue.max(Ih.set(0,0,0,0)),p.scissorValue.x+p.scissorValue.width>p.width&&(p.scissorValue.width=Math.max(p.width-p.scissorValue.x,0)),p.scissorValue.y+p.scissorValue.height>p.height&&(p.scissorValue.height=Math.max(p.height-p.scissorValue.y,0)),this._background.update(u,N,p),p.camera=t,this.backend.beginRender(p);const{bundles:T,lightsNode:R,transparentDoublePass:D,transparent:j,opaque:q}=N;return T.length>0&&this._renderBundles(T,u,R),this.opaque===!0&&q.length>0&&this._renderObjects(q,t,u,R),this.transparent===!0&&j.length>0&&this._renderTransparents(j,D,t,u,R),this.backend.finishRender(p),s.renderId=a,this._currentRenderContext=o,this._currentRenderObjectFunction=l,i!==null&&(this.setRenderTarget(c,d,f),this._renderOutput(h)),u.onAfterRender(this,e,t,h),this.inspector.finishRender(this.backend.getTimestampUID(p)),p}_setXRLayerSize(e,t){this._canvasTarget._width=e,this._canvasTarget._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}setAnimationLoop(e){return Kr(this,null,function*(){this._initialized===!1&&(yield this.init()),this._animation.setAnimationLoop(e)})}getAnimationLoop(){return this._animation.getAnimationLoop()}getArrayBufferAsync(e){return Kr(this,null,function*(){return yield this.backend.getArrayBufferAsync(e)})}getContext(){return this.backend.getContext()}getPixelRatio(){return this._canvasTarget.getPixelRatio()}getDrawingBufferSize(e){return this._canvasTarget.getDrawingBufferSize(e)}getSize(e){return this._canvasTarget.getSize(e)}setPixelRatio(e=1){this._canvasTarget.setPixelRatio(e)}setDrawingBufferSize(e,t,n){this.xr&&this.xr.isPresenting||this._canvasTarget.setDrawingBufferSize(e,t,n)}setSize(e,t,n=!0){this.xr&&this.xr.isPresenting||this._canvasTarget.setSize(e,t,n)}setOpaqueSort(e){this._opaqueSort=e}setTransparentSort(e){this._transparentSort=e}getScissor(e){return this._canvasTarget.getScissor(e)}setScissor(e,t,n,i){this._canvasTarget.setScissor(e,t,n,i)}getScissorTest(){return this._canvasTarget.getScissorTest()}setScissorTest(e){this._canvasTarget.setScissorTest(e),this.backend.setScissorTest(e)}getViewport(e){return this._canvasTarget.getViewport(e)}setViewport(e,t,n,i,s=0,a=1){this._canvasTarget.setViewport(e,t,n,i,s,a)}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(this._initialized===!1)throw new Error('Renderer: .clear() called before the backend is initialized. Use "await renderer.init();" before before using this method.');const i=this._renderTarget||this._getFrameBufferTarget();let s=null;if(i!==null){this._textures.updateRenderTarget(i);const a=this._textures.get(i);s=this._renderContexts.getForClear(i),s.textures=a.textures,s.depthTexture=a.depthTexture,s.width=a.width,s.height=a.height,s.renderTarget=i,s.depth=i.depthBuffer,s.stencil=i.stencilBuffer,s.clearColorValue=this.backend.getClearColor(),s.activeCubeFace=this.getActiveCubeFace(),s.activeMipmapLevel=this.getActiveMipmapLevel()}this.backend.clear(e,t,n,s),i!==null&&this._renderTarget===null&&this._renderOutput(i)}clearColor(){this.clear(!0,!1,!1)}clearDepth(){this.clear(!1,!0,!1)}clearStencil(){this.clear(!1,!1,!0)}clearAsync(e=!0,t=!0,n=!0){return Kr(this,null,function*(){rs('Renderer: "clearAsync()" has been deprecated. Use "clear()" and "await renderer.init();" when creating the renderer.'),yield this.init(),this.clear(e,t,n)})}clearColorAsync(){return Kr(this,null,function*(){rs('Renderer: "clearColorAsync()" has been deprecated. Use "clearColor()" and "await renderer.init();" when creating the renderer.'),this.clear(!0,!1,!1)})}clearDepthAsync(){return Kr(this,null,function*(){rs('Renderer: "clearDepthAsync()" has been deprecated. Use "clearDepth()" and "await renderer.init();" when creating the renderer.'),this.clear(!1,!0,!1)})}clearStencilAsync(){return Kr(this,null,function*(){rs('Renderer: "clearStencilAsync()" has been deprecated. Use "clearStencil()" and "await renderer.init();" when creating the renderer.'),this.clear(!1,!1,!0)})}get needsFrameBufferTarget(){const e=this.currentToneMapping!==Fr,t=this.currentColorSpace!==$r.workingColorSpace;return e||t}get samples(){return this._samples}get currentSamples(){let e=this._samples;return this._renderTarget!==null?e=this._renderTarget.samples:this.needsFrameBufferTarget&&(e=0),e}get currentToneMapping(){return this.isOutputTarget?this.toneMapping:Fr}get currentColorSpace(){return this.isOutputTarget?this.outputColorSpace:$r.workingColorSpace}get isOutputTarget(){return this._renderTarget===this._outputRenderTarget||this._renderTarget===null}dispose(){this._initialized===!0&&(this.info.dispose(),this.backend.dispose(),this._animation.dispose(),this._objects.dispose(),this._geometries.dispose(),this._pipelines.dispose(),this._nodes.dispose(),this._bindings.dispose(),this._renderLists.dispose(),this._renderContexts.dispose(),this._textures.dispose(),this._frameBufferTarget!==null&&this._frameBufferTarget.dispose(),Object.values(this.backend.timestampQueryPool).forEach(e=>{e!==null&&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}setCanvasTarget(e){this._canvasTarget.removeEventListener("resize",this._onCanvasTargetResize),this._canvasTarget=e,this._canvasTarget.addEventListener("resize",this._onCanvasTargetResize)}getCanvasTarget(){return this._canvasTarget}_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(this._isDeviceLost===!0)return;if(this._initialized===!1)return ze("Renderer: .compute() called before the backend is initialized. Try using .computeAsync() instead."),this.computeAsync(e,t);const n=this._nodes.nodeFrame,i=n.renderId;this.info.calls++,this.info.compute.calls++,this.info.compute.frameCalls++,n.renderId=this.info.calls,this.backend.updateTimeStampUID(e),this.inspector.beginCompute(this.backend.getTimestampUID(e),e);const s=this.backend,a=this._pipelines,o=this._bindings,l=this._nodes,u=Array.isArray(e)?e:[e];if(u[0]===void 0||u[0].isComputeNode!==!0)throw new Error("THREE.Renderer: .compute() expects a ComputeNode.");s.beginCompute(e);for(const c of u){if(a.has(c)===!1){const h=()=>{c.removeEventListener("dispose",h),a.delete(c),o.deleteForCompute(c),l.delete(c)};c.addEventListener("dispose",h);const p=c.onInitFunction;p!==null&&p.call(c,{renderer:this})}l.updateForCompute(c),o.updateForCompute(c);const d=o.getForCompute(c),f=a.getForCompute(c,d);s.compute(e,c,d,f,t)}s.finishCompute(e),n.renderId=i,this.inspector.finishCompute(this.backend.getTimestampUID(e))}computeAsync(e,t=null){return Kr(this,null,function*(){this._initialized===!1&&(yield this.init()),this.compute(e,t)})}hasFeatureAsync(e){return Kr(this,null,function*(){return rs('Renderer: "hasFeatureAsync()" has been deprecated. Use "hasFeature()" and "await renderer.init();" when creating the renderer.'),yield this.init(),this.hasFeature(e)})}resolveTimestampsAsync(e="render"){return Kr(this,null,function*(){return this._initialized===!1&&(yield this.init()),this.backend.resolveTimestampsAsync(e)})}hasFeature(e){if(this._initialized===!1)throw new Error('Renderer: .hasFeature() called before the backend is initialized. Use "await renderer.init();" before before using this method.');return this.backend.hasFeature(e)}hasInitialized(){return this._initialized}initTextureAsync(e){return Kr(this,null,function*(){rs('Renderer: "initTextureAsync()" has been deprecated. Use "initTexture()" and "await renderer.init();" when creating the renderer.'),yield this.init(),this.initTexture(e)})}initTexture(e){if(this._initialized===!1)throw new Error('Renderer: .initTexture() called before the backend is initialized. Use "await renderer.init();" before before using this method.');this._textures.updateTexture(e)}copyFramebufferToTexture(e,t=null){if(t!==null)if(t.isVector2)t=Ih.set(t.x,t.y,e.image.width,e.image.height).floor();else if(t.isVector4)t=Ih.copy(t).floor();else{rt("Renderer.copyFramebufferToTexture: Invalid rectangle.");return}else t=Ih.set(0,0,e.image.width,e.image.height);let n=this._currentRenderContext,i;n!==null?i=n.renderTarget:(i=this._renderTarget||this._getFrameBufferTarget(),i!==null&&(this._textures.updateRenderTarget(i),n=this._textures.get(i))),this._textures.updateTexture(e,{renderTarget:i}),this.backend.copyFramebufferToTexture(e,n,t),this._inspector.copyFramebufferToTexture(e)}copyTextureToTexture(e,t,n=null,i=null,s=0,a=0){this._textures.updateTexture(e),this._textures.updateTexture(t),this.backend.copyTextureToTexture(e,t,n,i,s,a),this._inspector.copyTextureToTexture(e,t)}readRenderTargetPixelsAsync(e,t,n,i,s,a=0,o=0){return Kr(this,null,function*(){return this.backend.copyTextureToBuffer(e.textures[a],t,n,i,s,o)})}_projectObject(e,t,n,i,s){if(e.visible===!1)return;if(e.layers.test(t.layers)){if(e.isGroup)n=e.renderOrder,e.isClippingGroup&&e.enabled&&(s=s.getGroupContext(e));else if(e.isLOD)e.autoUpdate===!0&&e.update(t);else if(e.isLight)i.pushLight(e);else if(e.isSprite){const l=t.isArrayCamera?oM:aM;if(!e.frustumCulled||l.intersectsSprite(e,t)){this.sortObjects===!0&&Ih.setFromMatrixPosition(e.matrixWorld).applyMatrix4(pw);const{geometry:u,material:c}=e;c.visible&&i.push(e,u,c,n,Ih.z,null,s)}}else if(e.isLineLoop)rt("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 l=t.isArrayCamera?oM:aM;if(!e.frustumCulled||l.intersectsObject(e,t)){const{geometry:u,material:c}=e;if(this.sortObjects===!0&&(u.boundingSphere===null&&u.computeBoundingSphere(),Ih.copy(u.boundingSphere.center).applyMatrix4(e.matrixWorld).applyMatrix4(pw)),Array.isArray(c)){const d=u.groups;for(let f=0,h=d.length;f<h;f++){const p=d[f],x=c[p.materialIndex];x&&x.visible&&i.push(e,u,x,n,Ih.z,p,s)}}else c.visible&&i.push(e,u,c,n,Ih.z,null,s)}}}if(e.isBundleGroup===!0&&this.backend.beginBundle!==void 0){const l=i;i=this._renderLists.get(e,t),i.begin(),l.pushBundle({bundleGroup:e,camera:t,renderList:i}),i.finish()}const o=e.children;for(let l=0,u=o.length;l<u;l++)this._projectObject(o[l],t,n,i,s)}_renderBundles(e,t,n){for(const i of e)this._renderBundle(i,t,n)}_renderTransparents(e,t,n,i,s){if(t.length>0){for(const{material:a}of t)a.side=Qi;this._renderObjects(t,n,i,s,"backSide");for(const{material:a}of t)a.side=ja;this._renderObjects(e,n,i,s);for(const{material:a}of t)a.side=Xs}else this._renderObjects(e,n,i,s)}_renderObjects(e,t,n,i,s=null){for(let a=0,o=e.length;a<o;a++){const{object:l,geometry:u,material:c,group:d,clippingContext:f}=e[a];this._currentRenderObjectFunction(l,n,t,u,c,d,i,f,s)}}_getShadowNodes(e){const t=e.version;let n=this._cacheShadowNodes.get(e);if(n===void 0||n.version!==t){const i=e.map!==null,s=e.colorNode&&e.colorNode.isNode,a=e.castShadowNode&&e.castShadowNode.isNode;let o=null,l=null,u=null;if(i||s||a){let c,d;a?(c=e.castShadowNode.rgb,d=e.castShadowNode.a):(c=he(0),d=K(1)),i&&(d=d.mul($s("map","texture",e).a)),s&&(d=d.mul(e.colorNode.a)),l=Yn(c,d)}e.depthNode&&e.depthNode.isNode&&(u=e.depthNode),e.castShadowPositionNode&&e.castShadowPositionNode.isNode?o=e.castShadowPositionNode:e.positionNode&&e.positionNode.isNode&&(o=e.positionNode),n={version:t,colorNode:l,depthNode:u,positionNode:o},this._cacheShadowNodes.set(e,n)}return n}renderObject(e,t,n,i,s,a,o,l=null,u=null){let c=!1,d,f,h,p;if(e.onBeforeRender(this,t,n,i,s,a),s.allowOverride===!0&&t.overrideMaterial!==null){const x=t.overrideMaterial;if(c=!0,d=t.overrideMaterial.colorNode,f=t.overrideMaterial.depthNode,h=t.overrideMaterial.positionNode,p=t.overrideMaterial.side,s.positionNode&&s.positionNode.isNode&&(x.positionNode=s.positionNode),x.alphaTest=s.alphaTest,x.alphaMap=s.alphaMap,x.transparent=s.transparent||s.transmission>0||s.transmissionNode&&s.transmissionNode.isNode||s.backdropNode&&s.backdropNode.isNode,x.isShadowPassMaterial){const{colorNode:v,depthNode:m,positionNode:C}=this._getShadowNodes(s);x.side=s.shadowSide===null?s.side:s.shadowSide,v!==null&&(x.colorNode=v),m!==null&&(x.depthNode=m),C!==null&&(x.positionNode=C)}s=x}s.transparent===!0&&s.side===Xs&&s.forceSinglePass===!1?(s.side=Qi,this._handleObjectFunction(e,s,t,n,o,a,l,"backSide"),s.side=ja,this._handleObjectFunction(e,s,t,n,o,a,l,u),s.side=Xs):this._handleObjectFunction(e,s,t,n,o,a,l,u),c&&(t.overrideMaterial.colorNode=d,t.overrideMaterial.depthNode=f,t.overrideMaterial.positionNode=h,t.overrideMaterial.side=p),e.onAfterRender(this,t,n,i,s,a)}_renderObjectDirect(e,t,n,i,s,a,o,l){const u=this._objects.get(e,t,n,i,s,this._currentRenderContext,o,l);u.drawRange=e.geometry.drawRange,u.group=a;const c=this._nodes.needsRefresh(u);c&&(this._nodes.updateBefore(u),this._geometries.updateForRender(u),this._nodes.updateForRender(u),this._bindings.updateForRender(u)),this._pipelines.updateForRender(u),this._currentRenderBundle!==null&&(this.backend.get(this._currentRenderBundle).renderObjects.push(u),u.bundle=this._currentRenderBundle.bundleGroup),this.backend.draw(u,this.info),c&&this._nodes.updateAfter(u)}_createObjectPipeline(e,t,n,i,s,a,o,l){const u=this._objects.get(e,t,n,i,s,this._currentRenderContext,o,l);u.drawRange=e.geometry.drawRange,u.group=a,this._nodes.updateBefore(u),this._geometries.updateForRender(u),this._nodes.updateForRender(u),this._bindings.updateForRender(u),this._pipelines.getForRender(u,this._compilationPromises),this._nodes.updateAfter(u)}_onCanvasTargetResize(){this._initialized&&this.backend.updateSize()}get compile(){return this.compileAsync}}class EN{constructor(e=""){this.name=e,this.visibility=0}setVisibility(e){this.visibility|=e}getVisibility(){return this.visibility}clone(){return Object.assign(new this.constructor,this)}}function s$(r){return r+(Qp-r%Qp)%Qp}class wN extends EN{constructor(e,t=null){super(e),this.isBuffer=!0,this.bytesPerElement=Float32Array.BYTES_PER_ELEMENT,this._buffer=t,this._updateRanges=[]}get updateRanges(){return this._updateRanges}addUpdateRange(e,t){this.updateRanges.push({start:e,count:t})}clearUpdateRanges(){this.updateRanges.length=0}get byteLength(){return s$(this._buffer.byteLength)}get buffer(){return this._buffer}update(){return!0}}class CN extends wN{constructor(e,t=null){super(e,t),this.isUniformBuffer=!0}}let a$=0;class PN extends CN{constructor(e,t){super("UniformBuffer_"+a$++,e?e.value:null),this.nodeUniform=e,this.groupNode=t,this.isNodeUniformBuffer=!0}set updateRanges(e){this.nodeUniform.updateRanges=e}get updateRanges(){return this.nodeUniform.updateRanges}addUpdateRange(e,t){this.nodeUniform.addUpdateRange(e,t)}clearUpdateRanges(){this.nodeUniform.clearUpdateRanges()}get buffer(){return this.nodeUniform.value}}class o$ extends CN{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 t!==-1&&this.uniforms.splice(t,1),this}get values(){return this._values===null&&(this._values=Array.from(this.buffer)),this._values}get buffer(){let e=this._buffer;if(e===null){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 s=this.uniforms[n],a=s.boundary,o=s.itemSize*e,l=t%Qp,u=l%a,c=l+u;t+=u,c!==0&&Qp-c<o&&(t+=Qp-c),s.offset=t/e,t+=o}return Math.ceil(t/Qp)*Qp}update(){let e=!1;for(const t of this.uniforms)this.updateByType(t)===!0&&(e=!0);return e}updateByType(e){if(e.isNumberUniform)return this.updateNumber(e);if(e.isVector2Uniform)return this.updateVector2(e);if(e.isVector3Uniform)return this.updateVector3(e);if(e.isVector4Uniform)return this.updateVector4(e);if(e.isColorUniform)return this.updateColor(e);if(e.isMatrix3Uniform)return this.updateMatrix3(e);if(e.isMatrix4Uniform)return this.updateMatrix4(e);rt("WebGPUUniformsGroup: Unsupported uniform type.",e)}updateNumber(e){let t=!1;const n=this.values,i=e.getValue(),s=e.offset,a=e.getType();if(n[s]!==i){const o=this._getBufferForType(a);o[s]=n[s]=i,t=!0}return t}updateVector2(e){let t=!1;const n=this.values,i=e.getValue(),s=e.offset,a=e.getType();if(n[s+0]!==i.x||n[s+1]!==i.y){const o=this._getBufferForType(a);o[s+0]=n[s+0]=i.x,o[s+1]=n[s+1]=i.y,t=!0}return t}updateVector3(e){let t=!1;const n=this.values,i=e.getValue(),s=e.offset,a=e.getType();if(n[s+0]!==i.x||n[s+1]!==i.y||n[s+2]!==i.z){const o=this._getBufferForType(a);o[s+0]=n[s+0]=i.x,o[s+1]=n[s+1]=i.y,o[s+2]=n[s+2]=i.z,t=!0}return t}updateVector4(e){let t=!1;const n=this.values,i=e.getValue(),s=e.offset,a=e.getType();if(n[s+0]!==i.x||n[s+1]!==i.y||n[s+2]!==i.z||n[s+4]!==i.w){const o=this._getBufferForType(a);o[s+0]=n[s+0]=i.x,o[s+1]=n[s+1]=i.y,o[s+2]=n[s+2]=i.z,o[s+3]=n[s+3]=i.w,t=!0}return t}updateColor(e){let t=!1;const n=this.values,i=e.getValue(),s=e.offset;if(n[s+0]!==i.r||n[s+1]!==i.g||n[s+2]!==i.b){const a=this.buffer;a[s+0]=n[s+0]=i.r,a[s+1]=n[s+1]=i.g,a[s+2]=n[s+2]=i.b,t=!0}return t}updateMatrix3(e){let t=!1;const n=this.values,i=e.getValue().elements,s=e.offset;if(n[s+0]!==i[0]||n[s+1]!==i[1]||n[s+2]!==i[2]||n[s+4]!==i[3]||n[s+5]!==i[4]||n[s+6]!==i[5]||n[s+8]!==i[6]||n[s+9]!==i[7]||n[s+10]!==i[8]){const a=this.buffer;a[s+0]=n[s+0]=i[0],a[s+1]=n[s+1]=i[1],a[s+2]=n[s+2]=i[2],a[s+4]=n[s+4]=i[3],a[s+5]=n[s+5]=i[4],a[s+6]=n[s+6]=i[5],a[s+8]=n[s+8]=i[6],a[s+9]=n[s+9]=i[7],a[s+10]=n[s+10]=i[8],t=!0}return t}updateMatrix4(e){let t=!1;const n=this.values,i=e.getValue().elements,s=e.offset;return u$(n,i,s)===!1&&(this.buffer.set(i,s),l$(n,i,s),t=!0),t}_getBufferForType(e){return e==="int"||e==="ivec2"||e==="ivec3"||e==="ivec4"?new Int32Array(this.buffer.buffer):e==="uint"||e==="uvec2"||e==="uvec3"||e==="uvec4"?new Uint32Array(this.buffer.buffer):this.buffer}}function l$(r,e,t){for(let n=0,i=e.length;n<i;n++)r[t+n]=e[n]}function u$(r,e,t){for(let n=0,i=e.length;n<i;n++)if(r[t+n]!==e[n])return!1;return!0}let c$=0;class BN extends o${constructor(e,t){super(e),this.id=c$++,this.groupNode=t,this.isNodeUniformsGroup=!0}}class MN extends EN{constructor(e,t){super(e),this._texture=null,this._onTextureDispose=()=>{this.generation=null,this.version=0},this.texture=t,this.version=t?t.version:0,this.generation=null,this.samplerKey="",this.isSampler=!0}set texture(e){this._texture!==e&&(this._texture&&this._texture.removeEventListener("dispose",this._onTextureDispose),this._texture=e,this.generation=null,this.version=0,this._texture&&this._texture.addEventListener("dispose",this._onTextureDispose))}get texture(){return this._texture}update(){const{texture:e,version:t}=this;return t!==e.version?(this.version=e.version,!0):!1}clone(){const e=super.clone();return e._texture=null,e._onTextureDispose=()=>{e.generation=null,e.version=0},e.texture=this.texture,e}}let d$=0;class f$ extends MN{constructor(e,t){super(e,t),this.id=d$++,this.store=!1,this.mipLevel=0,this.isSampledTexture=!0}}class mw extends f${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 SN extends mw{constructor(e,t,n,i=null){super(e,t,n,i),this.isSampledCubeTexture=!0}}class lM extends mw{constructor(e,t,n,i=null){super(e,t,n,i),this.isSampledTexture3D=!0}}const DN={bitcast_int_uint:new sl("uint tsl_bitcast_int_to_uint ( int x ) { return floatBitsToUint( intBitsToFloat ( x ) ); }"),bitcast_uint_int:new sl("uint tsl_bitcast_uint_to_int ( uint x ) { return floatBitsToInt( uintBitsToFloat ( x ) ); }")},h$={textureDimensions:"textureSize",equals:"equal",bitcast_float_int:"floatBitsToInt",bitcast_int_float:"intBitsToFloat",bitcast_uint_float:"uintBitsToFloat",bitcast_float_uint:"floatBitsToUint",bitcast_uint_int:"tsl_bitcast_uint_to_int",bitcast_int_uint:"tsl_bitcast_int_to_uint",floatpack_snorm_2x16:"packSnorm2x16",floatpack_unorm_2x16:"packUnorm2x16",floatpack_float16_2x16:"packHalf2x16",floatunpack_snorm_2x16:"unpackSnorm2x16",floatunpack_unorm_2x16:"unpackUnorm2x16",floatunpack_float16_2x16:"unpackHalf2x16"},p$={low:"lowp",medium:"mediump",high:"highp"},TN={swizzleAssign:!0,storageBuffer:!1},IN={perspective:"smooth",linear:"noperspective"},NN={centroid:"centroid"},FN=`
precision highp float;
precision highp int;
precision highp sampler2D;
precision highp sampler3D;
precision highp samplerCube;
precision highp sampler2DArray;

precision highp usampler2D;
precision highp usampler3D;
precision highp usamplerCube;
precision highp usampler2DArray;

precision highp isampler2D;
precision highp isampler3D;
precision highp isamplerCube;
precision highp isampler2DArray;

precision lowp sampler2DShadow;
precision lowp sampler2DArrayShadow;
precision lowp samplerCubeShadow;
`;class m$ extends fN{constructor(e,t){super(e,t,new X_),this.uniformGroups={},this.transforms=[],this.extensions={},this.builtins={vertex:[],fragment:[],compute:[]}}needsToWorkingColorSpace(e){return e.isVideoTexture===!0&&e.colorSpace!==Ol}_include(e){const t=DN[e];return t.build(this),this.addInclude(t),t}getMethod(e){return DN[e]!==void 0&&this._include(e),h$[e]||e}getBitcastMethod(e,t){return this.getMethod(`bitcast_${t}_${e}`)}getFloatPackingMethod(e){return this.getMethod(`floatpack_${e}_2x16`)}getFloatUnpackingMethod(e){return this.getMethod(`floatunpack_${e}_2x16`)}getTernary(e,t,n){return`${e} ? ${t} : ${n}`}getOutputStructName(){return""}buildFunctionCode(e){const t=e.layout,n=this.flowShaderNode(e),i=[];for(const a of t.inputs)i.push(this.getType(a.type)+" "+a.name);return`${this.getType(t.type)} ${t.name}( ${i.join(", ")} ) {

	${n.vars}

${n.code}
	return ${n.result};

}`}setupPBO(e){const t=e.value;if(t.pbo===void 0){const n=t.array,i=t.count*t.itemSize,{itemSize:s}=t,a=t.array.constructor.name.toLowerCase().includes("int");let o=a?Kf:_h;s===2?o=a?$h:Al:s===3?o=a?Av:Sm:s===4&&(o=a?qf:ma);const l={Float32Array:ha,Uint8Array:fa,Uint16Array:Yu,Uint32Array:Ls,Int8Array:Jf,Int16Array:cd,Int32Array:Do,Uint8ClampedArray:fa},u=Math.pow(2,Math.ceil(Math.log2(Math.sqrt(i/s))));let c=Math.ceil(i/s/u);u*c*s<i&&c++;const d=u*c*s,f=new n.constructor(d);f.set(n,0),t.array=f;const h=new Sc(t.array,u,c,o,l[t.array.constructor.name]||ha);h.needsUpdate=!0,h.isPBOTexture=!0;const p=new wf(h,null,null);p.setPrecision("high"),t.pboNode=p,t.pbo=p.value,this.getUniformFromNode(t.pboNode,"texture",this.shaderStage,this.context.nodeName)}}getPropertyName(e,t=this.shaderStage){return e.isNodeUniform&&e.node.isTextureNode!==!0&&e.node.isBufferNode!==!0?t.charAt(0)+"_"+e.name:super.getPropertyName(e,t)}generatePBO(e){const{node:t,indexNode:n}=e,i=t.value;if(this.renderer.backend.has(i)){const c=this.renderer.backend.get(i);c.pbo=i.pbo}const s=this.getUniformFromNode(i.pboNode,"texture",this.shaderStage,this.context.nodeName),a=this.getPropertyName(s);this.increaseUsage(n);const o=n.build(this,"uint"),l=this.getDataFromNode(e);let u=l.propertyName;if(u===void 0){const c=this.getVarFromNode(e);u=this.getPropertyName(c);const d=this.getDataFromNode(t);let f=d.propertySizeName;f===void 0&&(f=u+"Size",this.getVarFromNode(t,f,"uint"),this.addLineFlowCode(`${f} = uint( textureSize( ${a}, 0 ).x )`,e),d.propertySizeName=f);const{itemSize:h}=i,p="."+og.join("").slice(0,h),x=`ivec2(${o} % ${f}, ${o} / ${f})`,v=this.generateTextureLoad(null,a,x,"0",null,null);let m="vec4";i.pbo.type===Ls?m="uvec4":i.pbo.type===Do&&(m="ivec4"),this.addLineFlowCode(`${u} = ${m}(${v})${p}`,e),l.propertyName=u}return u}generateTextureLoad(e,t,n,i,s,a){i===null&&(i="0");let o;return s?a?o=`texelFetchOffset( ${t}, ivec3( ${n}, ${s} ), ${i}, ${a} )`:o=`texelFetch( ${t}, ivec3( ${n}, ${s} ), ${i} )`:a?o=`texelFetchOffset( ${t}, ${n}, ${i}, ${a} )`:o=`texelFetch( ${t}, ${n}, ${i} )`,e!==null&&e.isDepthTexture&&(o+=".x"),o}generateTexture(e,t,n,i,s){return i&&(n=`vec3( ${n}, ${i} )`),e.isDepthTexture?s?`textureOffset( ${t}, ${n}, ${s} ).x`:`texture( ${t}, ${n} ).x`:s?`textureOffset( ${t}, ${n}, ${s} )`:`texture( ${t}, ${n} )`}generateTextureLevel(e,t,n,i,s){return s?`textureLodOffset( ${t}, ${n}, ${i}, ${s} )`:`textureLod( ${t}, ${n}, ${i} )`}generateTextureBias(e,t,n,i,s){return s?`textureOffset( ${t}, ${n}, ${s}, ${i} )`:`texture( ${t}, ${n}, ${i} )`}generateTextureGrad(e,t,n,i,s){return s?`textureGradOffset( ${t}, ${n}, ${i[0]}, ${i[1]}, ${s} )`:`textureGrad( ${t}, ${n}, ${i[0]}, ${i[1]} )`}generateTextureCompare(e,t,n,i,s,a,o=this.shaderStage){if(o==="fragment")return e.isCubeTexture?`texture( ${t}, vec4( ${n}, ${i} ) )`:s?a?`textureOffset( ${t}, vec4( ${n}, ${s}, ${i} ), ${a} )`:`texture( ${t}, vec4( ${n}, ${s}, ${i} ) )`:a?`textureOffset( ${t}, vec3( ${n}, ${i} ), ${a} )`:`texture( ${t}, vec3( ${n}, ${i} ) )`;rt(`WebGPURenderer: THREE.DepthTexture.compareFunction() does not support ${o} shader.`)}getVars(e){const t=[],n=this.vars[e];if(n!==void 0)for(const i of n)t.push(`${this.getVar(i.type,i.name,i.count)};`);return t.join(`
	`)}getUniforms(e){const t=this.uniforms[e],n=[],i={};for(const a of t){let o=null,l=!1;if(a.type==="texture"||a.type==="texture3D"){const c=a.node.value;let d="";(c.isDataTexture===!0||c.isData3DTexture===!0)&&(c.type===Ls?d="u":c.type===Do&&(d="i")),a.type==="texture3D"&&c.isArrayTexture===!1?o=`${d}sampler3D ${a.name};`:c.compareFunction?c.isArrayTexture===!0?o=`sampler2DArrayShadow ${a.name};`:o=`sampler2DShadow ${a.name};`:c.isArrayTexture===!0||c.isDataArrayTexture===!0||c.isCompressedArrayTexture===!0?o=`${d}sampler2DArray ${a.name};`:o=`${d}sampler2D ${a.name};`}else if(a.type==="cubeTexture")o=`samplerCube ${a.name};`;else if(a.type==="cubeDepthTexture")o=`samplerCubeShadow ${a.name};`;else if(a.type==="buffer"){const c=a.node,d=this.getType(c.bufferType),f=c.bufferCount,h=f>0?f:"";o=`${c.name} {
	${d} ${a.name}[${h}];
};
`}else o=`${this.getVectorType(a.type)} ${this.getPropertyName(a,e)};`,l=!0;const u=a.node.precision;if(u!==null&&(o=p$[u]+" "+o),l){o="	"+o;const c=a.groupNode.name;(i[c]||(i[c]=[])).push(o)}else o="uniform "+o,n.push(o)}let s="";for(const a in i){const o=i[a];s+=this._getGLSLUniformStruct(e+"_"+a,o.join(`
`))+`
`}return s+=n.join(`
`),s}getTypeFromAttribute(e){let t=super.getTypeFromAttribute(e);if(/^[iu]/.test(t)&&e.gpuType!==Do){let n=e;e.isInterleavedBufferAttribute&&(n=e.data);const i=n.array;i instanceof Uint32Array||i instanceof Int32Array||(t=t.slice(1))}return t}getAttributes(e){let t="";if(e==="vertex"||e==="compute"){const n=this.getAttributesArray();let i=0;for(const s of n)t+=`layout( location = ${i++} ) in ${s.type} ${s.name};
`}return t}getStructMembers(e){const t=[];for(const n of e.members)t.push(`	${n.type} ${n.name};`);return t.join(`
`)}getStructs(e){const t=[],n=this.structs[e],i=[];for(const s of n)if(s.output)for(const a of s.members)i.push(`layout( location = ${a.index} ) out ${a.type} ${a.name};`);else{let a="struct "+s.name+` {
`;a+=this.getStructMembers(s),a+=`
};
`,t.push(a)}return i.length===0&&i.push("layout( location = 0 ) out vec4 fragColor;"),`
`+i.join(`
`)+`

`+t.join(`
`)}getVaryings(e){let t="";const n=this.varyings;if(e==="vertex"||e==="compute")for(const i of n){e==="compute"&&(i.needsInterpolation=!0);const s=this.getType(i.type);if(i.needsInterpolation)if(i.interpolationType){const a=IN[i.interpolationType]||i.interpolationType,o=NN[i.interpolationSampling]||"";t+=`${a} ${o} out ${s} ${i.name};
`}else{const a=s.includes("int")||s.includes("uv")||s.includes("iv")?"flat ":"";t+=`${a}out ${s} ${i.name};
`}else t+=`${s} ${i.name};
`}else if(e==="fragment"){for(const i of n)if(i.needsInterpolation){const s=this.getType(i.type);if(i.interpolationType){const a=IN[i.interpolationType]||i.interpolationType,o=NN[i.interpolationSampling]||"";t+=`${a} ${o} in ${s} ${i.name};
`}else{const a=s.includes("int")||s.includes("uv")||s.includes("iv")?"flat ":"";t+=`${a}in ${s} ${i.name};
`}}}for(const i of this.builtins[e])t+=`${i};
`;return t}getVertexIndex(){return"uint( gl_VertexID )"}getInstanceIndex(){return"uint( gl_InstanceID )"}getInvocationLocalIndex(){return`uint( gl_InstanceID ) % ${this.object.workgroupSize.reduce((n,i)=>n*i,1)}u`}getSubgroupSize(){rt("GLSLNodeBuilder: WebGLBackend does not support the subgroupSize node")}getInvocationSubgroupIndex(){rt("GLSLNodeBuilder: WebGLBackend does not support the invocationSubgroupIndex node")}getSubgroupIndex(){rt("GLSLNodeBuilder: WebGLBackend does not support the subgroupIndex node")}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);i.has(e)===!1&&i.set(e,{name:e,behavior:t})}getExtensions(e){const t=[];if(e==="vertex"){const i=this.renderer.backend.extensions;this.object.isBatchedMesh&&i.has("WEBGL_multi_draw")&&this.enableExtension("GL_ANGLE_multi_draw","require",e)}const n=this.extensions[e];if(n!==void 0)for(const{name:i,behavior:s}of n.values())t.push(`#extension ${i} : ${s}`);return t.join(`
`)}getClipDistance(){return"gl_ClipDistance"}isAvailable(e){let t=TN[e];if(t===void 0){let n;switch(t=!1,e){case"float32Filterable":n="OES_texture_float_linear";break;case"clipDistance":n="WEBGL_clip_cull_distance";break}if(n!==void 0){const i=this.renderer.backend.extensions;i.has(n)&&(i.get(n),t=!0)}TN[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[ ${e} ]`)}enableMultiview(){this.enableExtension("GL_OVR_multiview2","require","fragment"),this.enableExtension("GL_OVR_multiview2","require","vertex"),this.builtins.vertex.push("layout(num_views = 2) in")}registerTransform(e,t){this.transforms.push({varyingName:e,attributeNode:t})}getTransforms(){const e=this.transforms;let t="";for(let n=0;n<e.length;n++){const i=e[n],s=this.getPropertyName(i.attributeNode);s&&(t+=`${i.varyingName} = ${s};
	`)}return t}_getGLSLUniformStruct(e,t){return`
layout( std140 ) uniform ${e} {
${t}
};`}_getGLSLVertexCode(e){return`#version 300 es

${this.getSignature()}

// extensions
${e.extensions}

// precision
${FN}

// uniforms
${e.uniforms}

// varyings
${e.varyings}

// attributes
${e.attributes}

// codes
${e.codes}

void main() {

	// vars
	${e.vars}

	// transforms
	${e.transforms}

	// flow
	${e.flow}

	gl_PointSize = 1.0;

}
`}_getGLSLFragmentCode(e){return`#version 300 es

${this.getSignature()}

// extensions
${e.extensions}

// precision
${FN}

// structs
${e.structs}

// uniforms
${e.uniforms}

// varyings
${e.varyings}

// codes
${e.codes}

void main() {

	// vars
	${e.vars}

	// flow
	${e.flow}

}
`}buildCode(){const e=this.material!==null?{fragment:{},vertex:{}}:{compute:{}};this.sortBindingGroups();for(const t in e){let n=`// code

`;n+=this.flowCode[t];const i=this.flowNodes[t],s=i[i.length-1];for(const o of i){const l=this.getFlowData(o),u=o.name;u&&(n.length>0&&(n+=`
`),n+=`	// flow -> ${u}
	`),n+=`${l.code}
	`,o===s&&t!=="compute"&&(n+=`// result
	`,t==="vertex"?(n+="gl_Position = ",n+=`${l.result};`):t==="fragment"&&(o.outputNode.isOutputStructNode||(n+="fragColor = ",n+=`${l.result};`)))}const a=e[t];a.extensions=this.getExtensions(t),a.uniforms=this.getUniforms(t),a.attributes=this.getAttributes(t),a.varyings=this.getVaryings(t),a.vars=this.getVars(t),a.structs=this.getStructs(t),a.codes=this.getCodes(t),a.transforms=this.getTransforms(t),a.flow=n}this.material!==null?(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 s=super.getUniformFromNode(e,t,n,i),a=this.getDataFromNode(e,n,this.globalCache);let o=a.uniformGPU;if(o===void 0){const l=e.groupNode,u=l.name,c=this.getBindGroupArray(u,n);if(t==="texture")o=new mw(s.name,s.node,l),c.push(o);else if(t==="cubeTexture"||t==="cubeDepthTexture")o=new SN(s.name,s.node,l),c.push(o);else if(t==="texture3D")o=new lM(s.name,s.node,l),c.push(o);else if(t==="buffer"){s.name=`buffer${e.id}`;const d=this.getSharedDataFromNode(e);let f=d.buffer;f===void 0&&(e.name=`NodeBuffer_${e.id}`,f=new PN(e,l),f.name=e.name,d.buffer=f),c.push(f),o=f}else{const d=this.uniformGroups[n]||(this.uniformGroups[n]={});let f=d[u];f===void 0&&(f=new BN(n+"_"+u,l),d[u]=f,c.push(f)),o=this.getNodeUniform(s,t),f.addUniform(o)}a.uniformGPU=o}return s}}let uM=null,RA=null;class RN{constructor(e={}){this.parameters=Object.assign({},e),this.data=new WeakMap,this.renderer=null,this.domElement=null,this.timestampQueryPool={[On.RENDER]:null,[On.COMPUTE]:null},this.trackTimestamp=e.trackTimestamp===!0}init(e){return Kr(this,null,function*(){this.renderer=e})}get coordinateSystem(){}beginRender(){}finishRender(){}beginCompute(){}finishCompute(){}draw(){}compute(){}createProgram(){}destroyProgram(){}createBindings(){}updateBindings(){}updateBinding(){}createRenderPipeline(){}createComputePipeline(){}needsRenderUpdate(){}getRenderCacheKey(){}createNodeBuilder(){}updateSampler(){}createDefaultTexture(){}createTexture(){}updateTexture(){}generateMipmaps(){}destroyTexture(){}copyTextureToBuffer(){return Kr(this,null,function*(){})}copyTextureToTexture(){}copyFramebufferToTexture(){}createAttribute(){}createIndexAttribute(){}createStorageAttribute(){}updateAttribute(){}destroyAttribute(){}getContext(){}updateSize(){}updateViewport(){}updateTimeStampUID(e){const t=this.get(e),n=this.renderer.info.frame;let i;e.isComputeNode===!0?i="c:"+this.renderer.info.compute.frameCalls:i="r:"+this.renderer.info.render.frameCalls,t.timestampUID=i+":"+e.id+":f"+n}getTimestampUID(e){return this.get(e).timestampUID}getTimestampFrames(e){const t=this.timestampQueryPool[e];return t?t.getTimestampFrames():[]}_getQueryPool(e){const t=e.startsWith("c:")?On.COMPUTE:On.RENDER;return this.timestampQueryPool[t]}getTimestamp(e){return this._getQueryPool(e).getTimestamp(e)}hasTimestamp(e){return this._getQueryPool(e).hasTimestamp(e)}isOccluded(){}resolveTimestampsAsync(e="render"){return Kr(this,null,function*(){if(!this.trackTimestamp){rs("WebGPURenderer: Timestamp tracking is disabled.");return}const t=this.timestampQueryPool[e];if(!t)return;const n=yield t.resolveQueriesAsync();return this.renderer.info[e].timestamp=n,n})}getArrayBufferAsync(){return Kr(this,null,function*(){})}hasFeatureAsync(){return Kr(this,null,function*(){})}hasFeature(){}getMaxAnisotropy(){}getDrawingBufferSize(){return uM=uM||new ct,this.renderer.getDrawingBufferSize(uM)}setScissorTest(){}getClearColor(){const e=this.renderer;return RA=RA||new PB,e.getClearColor(RA),RA.getRGB(RA),RA}getDomElement(){let e=this.domElement;return e===null&&(e=this.parameters.canvas!==void 0?this.parameters.canvas:xo(),"setAttribute"in e&&e.setAttribute("data-engine",`three.js r${Fs} webgpu`),this.domElement=e),e}set(e,t){this.data.set(e,t)}get(e){let t=this.data.get(e);return t===void 0&&(t={},this.data.set(e,t)),t}has(e){return this.data.has(e)}delete(e){this.data.delete(e)}deleteBindGroupData(){}dispose(){}}let g$=0;class v${constructor(e,t){this.buffers=[e.bufferGPU,t],this.type=e.type,this.bufferType=e.bufferType,this.pbo=e.pbo,this.byteLength=e.byteLength,this.bytesPerElement=e.BYTES_PER_ELEMENT,this.version=e.version,this.isInteger=e.isInteger,this.activeBufferIndex=0,this.baseId=e.id}get id(){return`${this.baseId}|${this.activeBufferIndex}`}get bufferGPU(){return this.buffers[this.activeBufferIndex]}get transformBuffer(){return this.buffers[this.activeBufferIndex^1]}switchBuffers(){this.activeBufferIndex^=1}}class A${constructor(e){this.backend=e}createAttribute(e,t){const n=this.backend,{gl:i}=n,s=e.array,a=e.usage||i.STATIC_DRAW,o=e.isInterleavedBufferAttribute?e.data:e,l=n.get(o);let u=l.bufferGPU;u===void 0&&(u=this._createBuffer(i,t,s,a),l.bufferGPU=u,l.bufferType=t,l.version=o.version);let c;if(s instanceof Float32Array)c=i.FLOAT;else if(typeof Float16Array!="undefined"&&s instanceof Float16Array)c=i.HALF_FLOAT;else if(s instanceof Uint16Array)e.isFloat16BufferAttribute?c=i.HALF_FLOAT:c=i.UNSIGNED_SHORT;else if(s instanceof Int16Array)c=i.SHORT;else if(s instanceof Uint32Array)c=i.UNSIGNED_INT;else if(s instanceof Int32Array)c=i.INT;else if(s instanceof Int8Array)c=i.BYTE;else if(s instanceof Uint8Array)c=i.UNSIGNED_BYTE;else if(s instanceof Uint8ClampedArray)c=i.UNSIGNED_BYTE;else throw new Error("THREE.WebGLBackend: Unsupported buffer data format: "+s);let d={bufferGPU:u,bufferType:t,type:c,byteLength:s.byteLength,bytesPerElement:s.BYTES_PER_ELEMENT,version:e.version,pbo:e.pbo,isInteger:c===i.INT||c===i.UNSIGNED_INT||e.gpuType===Do,id:g$++};if(e.isStorageBufferAttribute||e.isStorageInstancedBufferAttribute){const f=this._createBuffer(i,t,s,a);d=new v$(d,f)}n.set(e,d)}updateAttribute(e){const t=this.backend,{gl:n}=t,i=e.array,s=e.isInterleavedBufferAttribute?e.data:e,a=t.get(s),o=a.bufferType,l=e.isInterleavedBufferAttribute?e.data.updateRanges:e.updateRanges;if(n.bindBuffer(o,a.bufferGPU),l.length===0)n.bufferSubData(o,0,i);else{for(let u=0,c=l.length;u<c;u++){const d=l[u];n.bufferSubData(o,d.start*i.BYTES_PER_ELEMENT,i,d.start,d.count)}s.clearUpdateRanges()}n.bindBuffer(o,null),a.version=s.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)}getArrayBufferAsync(e){return Kr(this,null,function*(){const t=this.backend,{gl:n}=t,i=e.isInterleavedBufferAttribute?e.data:e,{bufferGPU:s}=t.get(i),a=e.array,o=a.byteLength;n.bindBuffer(n.COPY_READ_BUFFER,s);const l=n.createBuffer();n.bindBuffer(n.COPY_WRITE_BUFFER,l),n.bufferData(n.COPY_WRITE_BUFFER,o,n.STREAM_READ),n.copyBufferSubData(n.COPY_READ_BUFFER,n.COPY_WRITE_BUFFER,0,0,o),yield t.utils._clientWaitAsync();const u=new e.array.constructor(a.length);return n.bindBuffer(n.COPY_WRITE_BUFFER,l),n.getBufferSubData(n.COPY_WRITE_BUFFER,0,u),n.deleteBuffer(l),n.bindBuffer(n.COPY_READ_BUFFER,null),n.bindBuffer(n.COPY_WRITE_BUFFER,null),u.buffer})}_createBuffer(e,t,n,i){const s=e.createBuffer();return e.bindBuffer(t,s),e.bufferData(t,n,i),e.bindBuffer(t,null),s}}let cM,Yx;class x${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;cM={[io]:e.FUNC_ADD,[Ca]:e.FUNC_SUBTRACT,[Gu]:e.FUNC_REVERSE_SUBTRACT},Yx={[ml]:e.ZERO,[Wu]:e.ONE,[bc]:e.SRC_COLOR,[Qu]:e.SRC_ALPHA,[Wf]:e.SRC_ALPHA_SATURATE,[nd]:e.DST_COLOR,[vu]:e.DST_ALPHA,[Gf]:e.ONE_MINUS_SRC_COLOR,[gl]:e.ONE_MINUS_SRC_ALPHA,[Wd]:e.ONE_MINUS_DST_COLOR,[Fl]:e.ONE_MINUS_DST_ALPHA};const t=e.getParameter(e.SCISSOR_BOX),n=e.getParameter(e.VIEWPORT);this.currentScissor=new Ei().fromArray(t),this.currentViewport=new Ei().fromArray(n),this._tempVec4=new Ei}enable(e){const{enabled:t}=this;t[e]!==!0&&(this.gl.enable(e),t[e]=!0)}disable(e){const{enabled:t}=this;t[e]!==!1&&(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;e!==ku?(this.enable(t.CULL_FACE),e!==this.currentCullFace&&(e===Ao?t.cullFace(t.BACK):e===eu?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)}setMRTBlending(e){const t=this.gl,n=this.backend.drawBuffersIndexedExt;if(n)for(let i=1;i<e.length;i++)n.blendFuncSeparateiOES(i,t.ONE,t.ZERO,t.ONE,t.ZERO)}setBlending(e,t,n,i,s,a,o,l){const{gl:u}=this;if(e===Xa){this.currentBlendingEnabled===!0&&(this.disable(u.BLEND),this.currentBlendingEnabled=!1);return}if(this.currentBlendingEnabled===!1&&(this.enable(u.BLEND),this.currentBlendingEnabled=!0),e!==yc){if(e!==this.currentBlending||l!==this.currentPremultipledAlpha){if((this.currentBlendEquation!==io||this.currentBlendEquationAlpha!==io)&&(u.blendEquation(u.FUNC_ADD),this.currentBlendEquation=io,this.currentBlendEquationAlpha=io),l)switch(e){case Vo:u.blendFuncSeparate(u.ONE,u.ONE_MINUS_SRC_ALPHA,u.ONE,u.ONE_MINUS_SRC_ALPHA);break;case ju:u.blendFunc(u.ONE,u.ONE);break;case Xu:u.blendFuncSeparate(u.ZERO,u.ONE_MINUS_SRC_COLOR,u.ZERO,u.ONE);break;case pl:u.blendFuncSeparate(u.DST_COLOR,u.ONE_MINUS_SRC_ALPHA,u.ZERO,u.ONE);break;default:rt("WebGLState: Invalid blending: ",e);break}else switch(e){case Vo:u.blendFuncSeparate(u.SRC_ALPHA,u.ONE_MINUS_SRC_ALPHA,u.ONE,u.ONE_MINUS_SRC_ALPHA);break;case ju:u.blendFuncSeparate(u.SRC_ALPHA,u.ONE,u.ONE,u.ONE);break;case Xu:rt("WebGLState: SubtractiveBlending requires material.premultipliedAlpha = true");break;case pl:rt("WebGLState: MultiplyBlending requires material.premultipliedAlpha = true");break;default:rt("WebGLState: Invalid blending: ",e);break}this.currentBlendSrc=null,this.currentBlendDst=null,this.currentBlendSrcAlpha=null,this.currentBlendDstAlpha=null,this.currentBlending=e,this.currentPremultipledAlpha=l}return}s=s||t,a=a||n,o=o||i,(t!==this.currentBlendEquation||s!==this.currentBlendEquationAlpha)&&(u.blendEquationSeparate(cM[t],cM[s]),this.currentBlendEquation=t,this.currentBlendEquationAlpha=s),(n!==this.currentBlendSrc||i!==this.currentBlendDst||a!==this.currentBlendSrcAlpha||o!==this.currentBlendDstAlpha)&&(u.blendFuncSeparate(Yx[n],Yx[i],Yx[a],Yx[o]),this.currentBlendSrc=n,this.currentBlendDst=i,this.currentBlendSrcAlpha=a,this.currentBlendDstAlpha=o),this.currentBlending=e,this.currentPremultipledAlpha=!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 rd:t.depthFunc(t.NEVER);break;case id:t.depthFunc(t.ALWAYS);break;case Au:t.depthFunc(t.LESS);break;case xu:t.depthFunc(t.LEQUAL);break;case sd:t.depthFunc(t.EQUAL);break;case Ec:t.depthFunc(t.GEQUAL);break;case ad:t.depthFunc(t.GREATER);break;case od:t.depthFunc(t.NOTEQUAL);break;default:t.depthFunc(t.LEQUAL)}this.currentDepthFunc=e}}scissor(e,t,n,i){const s=this._tempVec4.set(e,t,n,i);if(this.currentScissor.equals(s)===!1){const{gl:a}=this;a.scissor(s.x,s.y,s.z,s.w),this.currentScissor.copy(s)}}viewport(e,t,n,i){const s=this._tempVec4.set(e,t,n,i);if(this.currentViewport.equals(s)===!1){const{gl:a}=this;a.viewport(s.x,s.y,s.z,s.w),this.currentViewport.copy(s)}}setScissorTest(e){const t=this.gl;e?this.enable(t.SCISSOR_TEST):this.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;e.side===Xs?this.disable(i.CULL_FACE):this.enable(i.CULL_FACE);let s=e.side===Qi;t&&(s=!s),this.setFlipSided(s),e.blending===Vo&&e.transparent===!1?this.setBlending(Xa):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 a=e.stencilWrite;if(this.setStencilTest(a),a&&(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),e.alphaToCoverage===!0&&this.backend.renderer.currentSamples>0?this.enable(i.SAMPLE_ALPHA_TO_COVERAGE):this.disable(i.SAMPLE_ALPHA_TO_COVERAGE),n>0&&this.currentClippingPlanes!==n)for(let l=0;l<8;l++)l<n?this.enable(12288+l):this.disable(12288+l)}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):!1}setVertexState(e,t=null){const n=this.gl;return this.currentVAO!==e||this.currentIndex!==t?(n.bindVertexArray(e),t!==null&&n.bindBuffer(n.ELEMENT_ARRAY_BUFFER,t),this.currentVAO=e,this.currentIndex=t,!0):!1}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):!1}drawBuffers(e,t){const{gl:n}=this;let i=[],s=!1;if(e.textures!==null){i=this.currentDrawbuffers.get(t),i===void 0&&(i=[],this.currentDrawbuffers.set(t,i));const a=e.textures;if(i.length!==a.length||i[0]!==n.COLOR_ATTACHMENT0){for(let o=0,l=a.length;o<l;o++)i[o]=n.COLOR_ATTACHMENT0+o;i.length=a.length,s=!0}}else i[0]!==n.BACK&&(i[0]=n.BACK,s=!0);s&&n.drawBuffers(i)}activeTexture(e){const{gl:t,currentTextureSlot:n,maxTextures:i}=this;e===void 0&&(e=t.TEXTURE0+i-1),n!==e&&(t.activeTexture(e),this.currentTextureSlot=e)}bindTexture(e,t,n){const{gl:i,currentTextureSlot:s,currentBoundTextures:a,maxTextures:o}=this;n===void 0&&(s===null?n=i.TEXTURE0+o-1:n=s);let l=a[n];l===void 0&&(l={type:void 0,texture:void 0},a[n]=l),(l.type!==e||l.texture!==t)&&(s!==n&&(i.activeTexture(n),this.currentTextureSlot=n),i.bindTexture(e,t),l.type=e,l.texture=t)}bindBufferBase(e,t,n){const{gl:i}=this,s=`${e}-${t}`;return this.currentBoundBufferBases[s]!==n?(i.bindBufferBase(e,t,n),this.currentBoundBufferBases[s]=n,!0):!1}unbindTexture(){const{gl:e,currentTextureSlot:t,currentBoundTextures:n}=this,i=n[t];i!==void 0&&i.type!==void 0&&(e.bindTexture(i.type,null),i.type=void 0,i.texture=void 0)}}class y${constructor(e){this.backend=e,this.gl=this.backend.gl,this.extensions=e.extensions}convert(e,t=Ol){const{gl:n,extensions:i}=this;let s;const a=$r.getTransfer(t);if(e===fa)return n.UNSIGNED_BYTE;if(e===pv)return n.UNSIGNED_SHORT_4_4_4_4;if(e===mv)return n.UNSIGNED_SHORT_5_5_5_1;if(e===gv)return n.UNSIGNED_INT_5_9_9_9_REV;if(e===vv)return n.UNSIGNED_INT_10F_11F_11F_REV;if(e===Jf)return n.BYTE;if(e===cd)return n.SHORT;if(e===Yu)return n.UNSIGNED_SHORT;if(e===Do)return n.INT;if(e===Ls)return n.UNSIGNED_INT;if(e===ha)return n.FLOAT;if(e===pa)return n.HALF_FLOAT;if(e===A0)return n.ALPHA;if(e===Sm)return n.RGB;if(e===ma)return n.RGBA;if(e===jo)return n.DEPTH_COMPONENT;if(e===vl)return n.DEPTH_STENCIL;if(e===_h)return n.RED;if(e===Kf)return n.RED_INTEGER;if(e===Al)return n.RG;if(e===$h)return n.RG_INTEGER;if(e===qf)return n.RGBA_INTEGER;if(e===Kd||e===qd||e===_d||e===$d)if(a===$n)if(s=i.get("WEBGL_compressed_texture_s3tc_srgb"),s!==null){if(e===Kd)return s.COMPRESSED_SRGB_S3TC_DXT1_EXT;if(e===qd)return s.COMPRESSED_SRGB_ALPHA_S3TC_DXT1_EXT;if(e===_d)return s.COMPRESSED_SRGB_ALPHA_S3TC_DXT3_EXT;if(e===$d)return s.COMPRESSED_SRGB_ALPHA_S3TC_DXT5_EXT}else return null;else if(s=i.get("WEBGL_compressed_texture_s3tc"),s!==null){if(e===Kd)return s.COMPRESSED_RGB_S3TC_DXT1_EXT;if(e===qd)return s.COMPRESSED_RGBA_S3TC_DXT1_EXT;if(e===_d)return s.COMPRESSED_RGBA_S3TC_DXT3_EXT;if(e===$d)return s.COMPRESSED_RGBA_S3TC_DXT5_EXT}else return null;if(e===dd||e===Dm||e===ep||e===Tm)if(s=i.get("WEBGL_compressed_texture_pvrtc"),s!==null){if(e===dd)return s.COMPRESSED_RGB_PVRTC_4BPPV1_IMG;if(e===Dm)return s.COMPRESSED_RGB_PVRTC_2BPPV1_IMG;if(e===ep)return s.COMPRESSED_RGBA_PVRTC_4BPPV1_IMG;if(e===Tm)return s.COMPRESSED_RGBA_PVRTC_2BPPV1_IMG}else return null;if(e===tp||e===Im||e===np||e===ef||e===rp||e===_f||e===ip)if(s=i.get("WEBGL_compressed_texture_etc"),s!==null){if(e===tp||e===Im)return a===$n?s.COMPRESSED_SRGB8_ETC2:s.COMPRESSED_RGB8_ETC2;if(e===np)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ETC2_EAC:s.COMPRESSED_RGBA8_ETC2_EAC;if(e===ef)return s.COMPRESSED_R11_EAC;if(e===rp)return s.COMPRESSED_SIGNED_R11_EAC;if(e===_f)return s.COMPRESSED_RG11_EAC;if(e===ip)return s.COMPRESSED_SIGNED_RG11_EAC}else return null;if(e===$f||e===sp||e===eh||e===ap||e===th||e===Nm||e===tf||e===op||e===lp||e===up||e===cp||e===dp||e===fp||e===hp)if(s=i.get("WEBGL_compressed_texture_astc"),s!==null){if(e===$f)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_4x4_KHR:s.COMPRESSED_RGBA_ASTC_4x4_KHR;if(e===sp)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_5x4_KHR:s.COMPRESSED_RGBA_ASTC_5x4_KHR;if(e===eh)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_5x5_KHR:s.COMPRESSED_RGBA_ASTC_5x5_KHR;if(e===ap)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_6x5_KHR:s.COMPRESSED_RGBA_ASTC_6x5_KHR;if(e===th)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_6x6_KHR:s.COMPRESSED_RGBA_ASTC_6x6_KHR;if(e===Nm)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_8x5_KHR:s.COMPRESSED_RGBA_ASTC_8x5_KHR;if(e===tf)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_8x6_KHR:s.COMPRESSED_RGBA_ASTC_8x6_KHR;if(e===op)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_8x8_KHR:s.COMPRESSED_RGBA_ASTC_8x8_KHR;if(e===lp)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_10x5_KHR:s.COMPRESSED_RGBA_ASTC_10x5_KHR;if(e===up)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_10x6_KHR:s.COMPRESSED_RGBA_ASTC_10x6_KHR;if(e===cp)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_10x8_KHR:s.COMPRESSED_RGBA_ASTC_10x8_KHR;if(e===dp)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_10x10_KHR:s.COMPRESSED_RGBA_ASTC_10x10_KHR;if(e===fp)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_12x10_KHR:s.COMPRESSED_RGBA_ASTC_12x10_KHR;if(e===hp)return a===$n?s.COMPRESSED_SRGB8_ALPHA8_ASTC_12x12_KHR:s.COMPRESSED_RGBA_ASTC_12x12_KHR}else return null;if(e===nh)if(s=i.get("EXT_texture_compression_bptc"),s!==null){if(e===nh)return a===$n?s.COMPRESSED_SRGB_ALPHA_BPTC_UNORM_EXT:s.COMPRESSED_RGBA_BPTC_UNORM_EXT}else return null;if(e===gp||e===nf||e===rf||e===vp)if(s=i.get("EXT_texture_compression_rgtc"),s!==null){if(e===gp)return s.COMPRESSED_RED_RGTC1_EXT;if(e===nf)return s.COMPRESSED_SIGNED_RED_RGTC1_EXT;if(e===rf)return s.COMPRESSED_RED_GREEN_RGTC2_EXT;if(e===vp)return s.COMPRESSED_SIGNED_RED_GREEN_RGTC2_EXT}else return null;return e===Ll?n.UNSIGNED_INT_24_8:n[e]!==void 0?n[e]:null}_clientWaitAsync(){const{gl:e}=this,t=e.fenceSync(e.SYNC_GPU_COMMANDS_COMPLETE,0);return e.flush(),new Promise((n,i)=>{function s(){const a=e.clientWaitSync(t,e.SYNC_FLUSH_COMMANDS_BIT,0);if(a===e.WAIT_FAILED){e.deleteSync(t),i();return}if(a===e.TIMEOUT_EXPIRED){requestAnimationFrame(s);return}e.deleteSync(t),n()}s()})}}let LN=!1,gw,dM,ON;class b${constructor(e){this.backend=e,this.gl=e.gl,this.extensions=e.extensions,this.defaultTextures={},this._srcFramebuffer=null,this._dstFramebuffer=null,LN===!1&&(this._init(),LN=!0)}_init(){const e=this.gl;gw={[Zu]:e.REPEAT,[So]:e.CLAMP_TO_EDGE,[ud]:e.MIRRORED_REPEAT},dM={[Cs]:e.NEAREST,[Bm]:e.NEAREST_MIPMAP_NEAREST,[wc]:e.NEAREST_MIPMAP_LINEAR,[ms]:e.LINEAR,[Yf]:e.LINEAR_MIPMAP_NEAREST,[tl]:e.LINEAR_MIPMAP_LINEAR},ON={[w0]:e.NEVER,[H]:e.ALWAYS,[bp]:e.LESS,[A]:e.LEQUAL,[g]:e.EQUAL,[z]:e.GEQUAL,[b]:e.GREATER,[M]:e.NOTEQUAL}}getGLTextureType(e){const{gl:t}=this;let n;return e.isCubeTexture===!0?n=t.TEXTURE_CUBE_MAP:e.isArrayTexture===!0||e.isDataArrayTexture===!0||e.isCompressedArrayTexture===!0?n=t.TEXTURE_2D_ARRAY:e.isData3DTexture===!0?n=t.TEXTURE_3D:n=t.TEXTURE_2D,n}getInternalFormat(e,t,n,i,s=!1){const{gl:a,extensions:o}=this;if(e!==null){if(a[e]!==void 0)return a[e];ze("WebGLBackend: Attempt to use non-existing WebGL internal format '"+e+"'")}let l=t;if(t===a.RED&&(n===a.FLOAT&&(l=a.R32F),n===a.HALF_FLOAT&&(l=a.R16F),n===a.UNSIGNED_BYTE&&(l=a.R8),n===a.UNSIGNED_SHORT&&(l=a.R16),n===a.UNSIGNED_INT&&(l=a.R32UI),n===a.BYTE&&(l=a.R8I),n===a.SHORT&&(l=a.R16I),n===a.INT&&(l=a.R32I)),t===a.RED_INTEGER&&(n===a.UNSIGNED_BYTE&&(l=a.R8UI),n===a.UNSIGNED_SHORT&&(l=a.R16UI),n===a.UNSIGNED_INT&&(l=a.R32UI),n===a.BYTE&&(l=a.R8I),n===a.SHORT&&(l=a.R16I),n===a.INT&&(l=a.R32I)),t===a.RG&&(n===a.FLOAT&&(l=a.RG32F),n===a.HALF_FLOAT&&(l=a.RG16F),n===a.UNSIGNED_BYTE&&(l=a.RG8),n===a.UNSIGNED_SHORT&&(l=a.RG16),n===a.UNSIGNED_INT&&(l=a.RG32UI),n===a.BYTE&&(l=a.RG8I),n===a.SHORT&&(l=a.RG16I),n===a.INT&&(l=a.RG32I)),t===a.RG_INTEGER&&(n===a.UNSIGNED_BYTE&&(l=a.RG8UI),n===a.UNSIGNED_SHORT&&(l=a.RG16UI),n===a.UNSIGNED_INT&&(l=a.RG32UI),n===a.BYTE&&(l=a.RG8I),n===a.SHORT&&(l=a.RG16I),n===a.INT&&(l=a.RG32I)),t===a.RGB){const u=s?yp:$r.getTransfer(i);n===a.FLOAT&&(l=a.RGB32F),n===a.HALF_FLOAT&&(l=a.RGB16F),n===a.UNSIGNED_BYTE&&(l=a.RGB8),n===a.UNSIGNED_SHORT&&(l=a.RGB16),n===a.UNSIGNED_INT&&(l=a.RGB32UI),n===a.BYTE&&(l=a.RGB8I),n===a.SHORT&&(l=a.RGB16I),n===a.INT&&(l=a.RGB32I),n===a.UNSIGNED_BYTE&&(l=u===$n?a.SRGB8:a.RGB8),n===a.UNSIGNED_SHORT_5_6_5&&(l=a.RGB565),n===a.UNSIGNED_SHORT_5_5_5_1&&(l=a.RGB5_A1),n===a.UNSIGNED_SHORT_4_4_4_4&&(l=a.RGB4),n===a.UNSIGNED_INT_5_9_9_9_REV&&(l=a.RGB9_E5),n===a.UNSIGNED_INT_10F_11F_11F_REV&&(l=a.R11F_G11F_B10F)}if(t===a.RGB_INTEGER&&(n===a.UNSIGNED_BYTE&&(l=a.RGB8UI),n===a.UNSIGNED_SHORT&&(l=a.RGB16UI),n===a.UNSIGNED_INT&&(l=a.RGB32UI),n===a.BYTE&&(l=a.RGB8I),n===a.SHORT&&(l=a.RGB16I),n===a.INT&&(l=a.RGB32I)),t===a.RGBA){const u=s?yp:$r.getTransfer(i);n===a.FLOAT&&(l=a.RGBA32F),n===a.HALF_FLOAT&&(l=a.RGBA16F),n===a.UNSIGNED_BYTE&&(l=a.RGBA8),n===a.UNSIGNED_SHORT&&(l=a.RGBA16),n===a.UNSIGNED_INT&&(l=a.RGBA32UI),n===a.BYTE&&(l=a.RGBA8I),n===a.SHORT&&(l=a.RGBA16I),n===a.INT&&(l=a.RGBA32I),n===a.UNSIGNED_BYTE&&(l=u===$n?a.SRGB8_ALPHA8:a.RGBA8),n===a.UNSIGNED_SHORT_4_4_4_4&&(l=a.RGBA4),n===a.UNSIGNED_SHORT_5_5_5_1&&(l=a.RGB5_A1)}return t===a.RGBA_INTEGER&&(n===a.UNSIGNED_BYTE&&(l=a.RGBA8UI),n===a.UNSIGNED_SHORT&&(l=a.RGBA16UI),n===a.UNSIGNED_INT&&(l=a.RGBA32UI),n===a.BYTE&&(l=a.RGBA8I),n===a.SHORT&&(l=a.RGBA16I),n===a.INT&&(l=a.RGBA32I)),t===a.DEPTH_COMPONENT&&(n===a.UNSIGNED_SHORT&&(l=a.DEPTH_COMPONENT16),n===a.UNSIGNED_INT&&(l=a.DEPTH_COMPONENT24),n===a.FLOAT&&(l=a.DEPTH_COMPONENT32F)),t===a.DEPTH_STENCIL&&n===a.UNSIGNED_INT_24_8&&(l=a.DEPTH24_STENCIL8),(l===a.R16F||l===a.R32F||l===a.RG16F||l===a.RG32F||l===a.RGBA16F||l===a.RGBA32F)&&o.get("EXT_color_buffer_float"),l}setTextureParameters(e,t){const{gl:n,extensions:i,backend:s}=this,a=$r.getPrimaries($r.workingColorSpace),o=t.colorSpace===Ol?null:$r.getPrimaries(t.colorSpace),l=t.colorSpace===Ol||a===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,l),n.texParameteri(e,n.TEXTURE_WRAP_S,gw[t.wrapS]),n.texParameteri(e,n.TEXTURE_WRAP_T,gw[t.wrapT]),(e===n.TEXTURE_3D||e===n.TEXTURE_2D_ARRAY)&&(t.isArrayTexture||n.texParameteri(e,n.TEXTURE_WRAP_R,gw[t.wrapR])),n.texParameteri(e,n.TEXTURE_MAG_FILTER,dM[t.magFilter]);const u=t.mipmaps!==void 0&&t.mipmaps.length>0,c=t.minFilter===ms&&u?tl:t.minFilter;if(n.texParameteri(e,n.TEXTURE_MIN_FILTER,dM[c]),t.compareFunction&&(n.texParameteri(e,n.TEXTURE_COMPARE_MODE,n.COMPARE_REF_TO_TEXTURE),n.texParameteri(e,n.TEXTURE_COMPARE_FUNC,ON[t.compareFunction])),i.has("EXT_texture_filter_anisotropic")===!0){if(t.magFilter===Cs||t.minFilter!==wc&&t.minFilter!==tl||t.type===ha&&i.has("OES_texture_float_linear")===!1)return;if(t.anisotropy>1){const d=i.get("EXT_texture_filter_anisotropic");n.texParameterf(e,d.TEXTURE_MAX_ANISOTROPY_EXT,Math.min(t.anisotropy,s.getMaxAnisotropy()))}}}createDefaultTexture(e){const{gl:t,backend:n,defaultTextures:i}=this,s=this.getGLTextureType(e);let a=i[s];a===void 0&&(a=t.createTexture(),n.state.bindTexture(s,a),t.texParameteri(s,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(s,t.TEXTURE_MAG_FILTER,t.NEAREST),i[s]=a),n.set(e,{textureGPU:a,glTextureType:s})}createTexture(e,t){const{gl:n,backend:i}=this,{levels:s,width:a,height:o,depth:l}=t,u=i.utils.convert(e.format,e.colorSpace),c=i.utils.convert(e.type),d=this.getInternalFormat(e.internalFormat,u,c,e.colorSpace,e.isVideoTexture),f=n.createTexture(),h=this.getGLTextureType(e);i.state.bindTexture(h,f),this.setTextureParameters(h,e),e.isArrayTexture||e.isDataArrayTexture||e.isCompressedArrayTexture?n.texStorage3D(n.TEXTURE_2D_ARRAY,s,d,a,o,l):e.isData3DTexture?n.texStorage3D(n.TEXTURE_3D,s,d,a,o,l):e.isVideoTexture||n.texStorage2D(h,s,d,a,o),i.set(e,{textureGPU:f,glTextureType:h,glFormat:u,glType:c,glInternalFormat:d})}copyBufferToTexture(e,t){const{gl:n,backend:i}=this,{textureGPU:s,glTextureType:a,glFormat:o,glType:l}=i.get(t),{width:u,height:c}=t.source.data;n.bindBuffer(n.PIXEL_UNPACK_BUFFER,e),i.state.bindTexture(a,s),n.pixelStorei(n.UNPACK_FLIP_Y_WEBGL,!1),n.pixelStorei(n.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!1),n.texSubImage2D(a,0,0,0,u,c,o,l,0),n.bindBuffer(n.PIXEL_UNPACK_BUFFER,null),i.state.unbindTexture()}updateTexture(e,t){const{gl:n}=this,{width:i,height:s}=t,{textureGPU:a,glTextureType:o,glFormat:l,glType:u,glInternalFormat:c}=this.backend.get(e);if(!(e.isRenderTargetTexture||a===void 0))if(this.backend.state.bindTexture(o,a),this.setTextureParameters(o,e),e.isCompressedTexture){const d=e.mipmaps,f=t.image;for(let h=0;h<d.length;h++){const p=d[h];e.isCompressedArrayTexture?e.format!==n.RGBA?l!==null?n.compressedTexSubImage3D(n.TEXTURE_2D_ARRAY,h,0,0,0,p.width,p.height,f.depth,l,p.data):ze("WebGLBackend: Attempt to load unsupported compressed texture format in .uploadTexture()"):n.texSubImage3D(n.TEXTURE_2D_ARRAY,h,0,0,0,p.width,p.height,f.depth,l,u,p.data):l!==null?n.compressedTexSubImage2D(n.TEXTURE_2D,h,0,0,p.width,p.height,l,p.data):ze("WebGLBackend: Unsupported compressed texture format")}}else if(e.isCubeTexture){const d=t.images,f=e.mipmaps;for(let h=0;h<6;h++){const p=vw(d[h]);n.texSubImage2D(n.TEXTURE_CUBE_MAP_POSITIVE_X+h,0,0,0,i,s,l,u,p);for(let x=0;x<f.length;x++){const v=f[x],m=vw(v.images[h]);n.texSubImage2D(n.TEXTURE_CUBE_MAP_POSITIVE_X+h,x+1,0,0,m.width,m.height,l,u,m)}}}else if(e.isDataArrayTexture||e.isArrayTexture){const d=t.image;if(e.layerUpdates.size>0){const f=Nb(d.width,d.height,e.format,e.type);for(const h of e.layerUpdates){const p=d.data.subarray(h*f/d.data.BYTES_PER_ELEMENT,(h+1)*f/d.data.BYTES_PER_ELEMENT);n.texSubImage3D(n.TEXTURE_2D_ARRAY,0,0,0,h,d.width,d.height,1,l,u,p)}e.clearLayerUpdates()}else n.texSubImage3D(n.TEXTURE_2D_ARRAY,0,0,0,0,d.width,d.height,d.depth,l,u,d.data)}else if(e.isData3DTexture){const d=t.image;n.texSubImage3D(n.TEXTURE_3D,0,0,0,0,d.width,d.height,d.depth,l,u,d.data)}else if(e.isVideoTexture)e.update(),n.texImage2D(o,0,c,l,u,t.image);else{const d=e.mipmaps;if(d.length>0)for(let f=0,h=d.length;f<h;f++){const p=d[f],x=vw(p);n.texSubImage2D(o,f,0,0,p.width,p.height,l,u,x)}else{const f=vw(t.image);n.texSubImage2D(o,0,0,0,i,s,l,u,f)}}}generateMipmaps(e){const{gl:t,backend:n}=this,{textureGPU:i,glTextureType:s}=n.get(e);n.state.bindTexture(s,i),t.generateMipmap(s)}deallocateRenderBuffers(e){const{gl:t,backend:n}=this;if(e){const i=n.get(e);if(i.renderBufferStorageSetup=void 0,i.framebuffers){for(const s in i.framebuffers)t.deleteFramebuffer(i.framebuffers[s]);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 s=0;s<i.msaaRenderbuffers.length;s++)t.deleteRenderbuffer(i.msaaRenderbuffers[s]);delete i.msaaRenderbuffers}}}destroyTexture(e,t=!1){const{gl:n,backend:i}=this,{textureGPU:s,renderTarget:a}=i.get(e);this.deallocateRenderBuffers(a),t===!1&&n.deleteTexture(s),i.delete(e)}copyTextureToTexture(e,t,n=null,i=null,s=0,a=0){const{gl:o,backend:l}=this,{state:u}=this.backend,{textureGPU:c,glTextureType:d,glType:f,glFormat:h}=l.get(t);u.bindTexture(d,c);let p,x,v,m,C,w,P,B,S;const I=e.isCompressedTexture?e.mipmaps[a]:e.image;if(n!==null)p=n.max.x-n.min.x,x=n.max.y-n.min.y,v=n.isBox3?n.max.z-n.min.z:1,m=n.min.x,C=n.min.y,w=n.isBox3?n.min.z:0;else{const re=Math.pow(2,-s);p=Math.floor(I.width*re),x=Math.floor(I.height*re),e.isDataArrayTexture||e.isArrayTexture?v=I.depth:e.isData3DTexture?v=Math.floor(I.depth*re):v=1,m=0,C=0,w=0}i!==null?(P=i.x,B=i.y,S=i.z):(P=0,B=0,S=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 N=o.getParameter(o.UNPACK_ROW_LENGTH),T=o.getParameter(o.UNPACK_IMAGE_HEIGHT),R=o.getParameter(o.UNPACK_SKIP_PIXELS),D=o.getParameter(o.UNPACK_SKIP_ROWS),j=o.getParameter(o.UNPACK_SKIP_IMAGES);o.pixelStorei(o.UNPACK_ROW_LENGTH,I.width),o.pixelStorei(o.UNPACK_IMAGE_HEIGHT,I.height),o.pixelStorei(o.UNPACK_SKIP_PIXELS,m),o.pixelStorei(o.UNPACK_SKIP_ROWS,C),o.pixelStorei(o.UNPACK_SKIP_IMAGES,w);const q=e.isDataArrayTexture||e.isData3DTexture||t.isArrayTexture,Q=t.isDataArrayTexture||t.isData3DTexture||t.isArrayTexture;if(e.isDepthTexture){const re=l.get(e),de=l.get(t),we=l.get(re.renderTarget),ge=l.get(de.renderTarget),Y=we.framebuffers[re.cacheKey],Se=ge.framebuffers[de.cacheKey];u.bindFramebuffer(o.READ_FRAMEBUFFER,Y),u.bindFramebuffer(o.DRAW_FRAMEBUFFER,Se);for(let W=0;W<v;W++)q&&(o.framebufferTextureLayer(o.READ_FRAMEBUFFER,o.COLOR_ATTACHMENT0,re.textureGPU,s,w+W),o.framebufferTextureLayer(o.DRAW_FRAMEBUFFER,o.COLOR_ATTACHMENT0,c,a,S+W)),o.blitFramebuffer(m,C,p,x,P,B,p,x,o.DEPTH_BUFFER_BIT,o.NEAREST);u.bindFramebuffer(o.READ_FRAMEBUFFER,null),u.bindFramebuffer(o.DRAW_FRAMEBUFFER,null)}else if(s!==0||e.isRenderTargetTexture||l.has(e)){const re=l.get(e);this._srcFramebuffer===null&&(this._srcFramebuffer=o.createFramebuffer()),this._dstFramebuffer===null&&(this._dstFramebuffer=o.createFramebuffer()),u.bindFramebuffer(o.READ_FRAMEBUFFER,this._srcFramebuffer),u.bindFramebuffer(o.DRAW_FRAMEBUFFER,this._dstFramebuffer);for(let de=0;de<v;de++)q?o.framebufferTextureLayer(o.READ_FRAMEBUFFER,o.COLOR_ATTACHMENT0,re.textureGPU,s,w+de):o.framebufferTexture2D(o.READ_FRAMEBUFFER,o.COLOR_ATTACHMENT0,o.TEXTURE_2D,re.textureGPU,s),Q?o.framebufferTextureLayer(o.DRAW_FRAMEBUFFER,o.COLOR_ATTACHMENT0,c,a,S+de):o.framebufferTexture2D(o.DRAW_FRAMEBUFFER,o.COLOR_ATTACHMENT0,o.TEXTURE_2D,c,a),s!==0?o.blitFramebuffer(m,C,p,x,P,B,p,x,o.COLOR_BUFFER_BIT,o.NEAREST):Q?o.copyTexSubImage3D(d,a,P,B,S+de,m,C,p,x):o.copyTexSubImage2D(d,a,P,B,m,C,p,x);u.bindFramebuffer(o.READ_FRAMEBUFFER,null),u.bindFramebuffer(o.DRAW_FRAMEBUFFER,null)}else Q?e.isDataTexture||e.isData3DTexture?o.texSubImage3D(d,a,P,B,S,p,x,v,h,f,I.data):t.isCompressedArrayTexture?o.compressedTexSubImage3D(d,a,P,B,S,p,x,v,h,I.data):o.texSubImage3D(d,a,P,B,S,p,x,v,h,f,I):e.isDataTexture?o.texSubImage2D(o.TEXTURE_2D,a,P,B,p,x,h,f,I.data):e.isCompressedTexture?o.compressedTexSubImage2D(o.TEXTURE_2D,a,P,B,I.width,I.height,h,I.data):o.texSubImage2D(o.TEXTURE_2D,a,P,B,p,x,h,f,I);o.pixelStorei(o.UNPACK_ROW_LENGTH,N),o.pixelStorei(o.UNPACK_IMAGE_HEIGHT,T),o.pixelStorei(o.UNPACK_SKIP_PIXELS,R),o.pixelStorei(o.UNPACK_SKIP_ROWS,D),o.pixelStorei(o.UNPACK_SKIP_IMAGES,j),a===0&&t.generateMipmaps&&o.generateMipmap(d),u.unbindTexture()}copyFramebufferToTexture(e,t,n){const{gl:i}=this,{state:s}=this.backend,{textureGPU:a}=this.backend.get(e),{x:o,y:l,z:u,w:c}=n,d=e.isDepthTexture===!0||t.renderTarget&&t.renderTarget.samples>0,f=t.renderTarget?t.renderTarget.height:this.backend.getDrawingBufferSize().y;if(d){const h=o!==0||l!==0;let p,x;if(e.isDepthTexture===!0?(p=i.DEPTH_BUFFER_BIT,x=i.DEPTH_ATTACHMENT,t.stencil&&(p|=i.STENCIL_BUFFER_BIT)):(p=i.COLOR_BUFFER_BIT,x=i.COLOR_ATTACHMENT0),h){const v=this.backend.get(t.renderTarget),m=v.framebuffers[t.getCacheKey()],C=v.msaaFrameBuffer;s.bindFramebuffer(i.DRAW_FRAMEBUFFER,m),s.bindFramebuffer(i.READ_FRAMEBUFFER,C);const w=f-l-c;i.blitFramebuffer(o,w,o+u,w+c,o,w,o+u,w+c,p,i.NEAREST),s.bindFramebuffer(i.READ_FRAMEBUFFER,m),s.bindTexture(i.TEXTURE_2D,a),i.copyTexSubImage2D(i.TEXTURE_2D,0,0,0,o,w,u,c),s.unbindTexture()}else{const v=i.createFramebuffer();s.bindFramebuffer(i.DRAW_FRAMEBUFFER,v),i.framebufferTexture2D(i.DRAW_FRAMEBUFFER,x,i.TEXTURE_2D,a,0),i.blitFramebuffer(0,0,u,c,0,0,u,c,p,i.NEAREST),i.deleteFramebuffer(v)}}else s.bindTexture(i.TEXTURE_2D,a),i.copyTexSubImage2D(i.TEXTURE_2D,0,0,0,o,f-c-l,u,c),s.unbindTexture();e.generateMipmaps&&this.generateMipmaps(e),this.backend._setFramebuffer(t)}setupRenderBufferStorage(e,t,n,i=!1){const{gl:s}=this,a=t.renderTarget,{depthTexture:o,depthBuffer:l,stencilBuffer:u,width:c,height:d}=a;if(s.bindRenderbuffer(s.RENDERBUFFER,e),l&&!u){let f=s.DEPTH_COMPONENT24;i===!0?this.extensions.get("WEBGL_multisampled_render_to_texture").renderbufferStorageMultisampleEXT(s.RENDERBUFFER,a.samples,f,c,d):n>0?(o&&o.isDepthTexture&&o.type===s.FLOAT&&(f=s.DEPTH_COMPONENT32F),s.renderbufferStorageMultisample(s.RENDERBUFFER,n,f,c,d)):s.renderbufferStorage(s.RENDERBUFFER,f,c,d),s.framebufferRenderbuffer(s.FRAMEBUFFER,s.DEPTH_ATTACHMENT,s.RENDERBUFFER,e)}else l&&u&&(n>0?s.renderbufferStorageMultisample(s.RENDERBUFFER,n,s.DEPTH24_STENCIL8,c,d):s.renderbufferStorage(s.RENDERBUFFER,s.DEPTH_STENCIL,c,d),s.framebufferRenderbuffer(s.FRAMEBUFFER,s.DEPTH_STENCIL_ATTACHMENT,s.RENDERBUFFER,e));s.bindRenderbuffer(s.RENDERBUFFER,null)}copyTextureToBuffer(e,t,n,i,s,a){return Kr(this,null,function*(){const{backend:o,gl:l}=this,{textureGPU:u,glFormat:c,glType:d}=this.backend.get(e),f=l.createFramebuffer();o.state.bindFramebuffer(l.READ_FRAMEBUFFER,f);const h=e.isCubeTexture?l.TEXTURE_CUBE_MAP_POSITIVE_X+a:l.TEXTURE_2D;l.framebufferTexture2D(l.READ_FRAMEBUFFER,l.COLOR_ATTACHMENT0,h,u,0);const p=this._getTypedArrayType(d),x=this._getBytesPerTexel(d,c),m=i*s*x,C=l.createBuffer();l.bindBuffer(l.PIXEL_PACK_BUFFER,C),l.bufferData(l.PIXEL_PACK_BUFFER,m,l.STREAM_READ),l.readPixels(t,n,i,s,c,d,0),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),yield o.utils._clientWaitAsync();const w=new p(m/p.BYTES_PER_ELEMENT);return l.bindBuffer(l.PIXEL_PACK_BUFFER,C),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,w),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),o.state.bindFramebuffer(l.READ_FRAMEBUFFER,null),l.deleteFramebuffer(f),w})}_getTypedArrayType(e){const{gl:t}=this;if(e===t.UNSIGNED_BYTE)return Uint8Array;if(e===t.UNSIGNED_SHORT_4_4_4_4||e===t.UNSIGNED_SHORT_5_5_5_1||e===t.UNSIGNED_SHORT_5_6_5||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: ${e}`)}_getBytesPerTexel(e,t){const{gl:n}=this;let i=0;if(e===n.UNSIGNED_BYTE&&(i=1),(e===n.UNSIGNED_SHORT_4_4_4_4||e===n.UNSIGNED_SHORT_5_5_5_1||e===n.UNSIGNED_SHORT_5_6_5||e===n.UNSIGNED_SHORT||e===n.HALF_FLOAT)&&(i=2),(e===n.UNSIGNED_INT||e===n.FLOAT)&&(i=4),t===n.RGBA)return i*4;if(t===n.RGB)return i*3;if(t===n.ALPHA)return i}dispose(){const{gl:e}=this;this._srcFramebuffer!==null&&e.deleteFramebuffer(this._srcFramebuffer),this._dstFramebuffer!==null&&e.deleteFramebuffer(this._dstFramebuffer)}}function vw(r){return r.isDataTexture?r.image.data:typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement||typeof HTMLCanvasElement!="undefined"&&r instanceof HTMLCanvasElement||typeof ImageBitmap!="undefined"&&r instanceof ImageBitmap||typeof OffscreenCanvas!="undefined"&&r instanceof OffscreenCanvas?r:r.data}class E${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 t===void 0&&(t=this.gl.getExtension(e),this.extensions[e]=t),t}has(e){return this.availableExtensions.includes(e)}}class w${constructor(e){this.backend=e,this.maxAnisotropy=null}getMaxAnisotropy(){if(this.maxAnisotropy!==null)return this.maxAnisotropy;const e=this.backend.gl,t=this.backend.extensions;if(t.has("EXT_texture_filter_anisotropic")===!0){const n=t.get("EXT_texture_filter_anisotropic");this.maxAnisotropy=e.getParameter(n.MAX_TEXTURE_MAX_ANISOTROPY_EXT)}else this.maxAnisotropy=0;return this.maxAnisotropy}}const zN={WEBGL_multi_draw:"WEBGL_multi_draw",WEBGL_compressed_texture_astc:"texture-compression-astc",WEBGL_compressed_texture_etc:"texture-compression-etc2",WEBGL_compressed_texture_etc1:"texture-compression-etc1",WEBGL_compressed_texture_pvrtc:"texture-compression-pvrtc",WEBGL_compressed_texture_s3tc:"texture-compression-s3tc",EXT_texture_compression_bptc:"texture-compression-bc",EXT_disjoint_timer_query_webgl2:"timestamp-query",OVR_multiview2:"OVR_multiview2"};class C${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:s,type:a,info:o,index:l}=this;l!==0?n.drawElements(i,t,a,e):n.drawArrays(i,e,t),o.update(s,t,1)}renderInstances(e,t,n){const{gl:i,mode:s,type:a,index:o,object:l,info:u}=this;n!==0&&(o!==0?i.drawElementsInstanced(s,t,a,e,n):i.drawArraysInstanced(s,e,t,n),u.update(l,t,n))}renderMultiDraw(e,t,n){const{extensions:i,mode:s,object:a,info:o}=this;if(n===0)return;const l=i.get("WEBGL_multi_draw");if(l===null)for(let u=0;u<n;u++)this.render(e[u],t[u]);else{this.index!==0?l.multiDrawElementsWEBGL(s,t,0,this.type,e,0,n):l.multiDrawArraysWEBGL(s,e,0,t,0,n);let u=0;for(let c=0;c<n;c++)u+=t[c];o.update(a,u,1)}}renderMultiDrawInstances(e,t,n,i){const{extensions:s,mode:a,object:o,info:l}=this;if(n===0)return;const u=s.get("WEBGL_multi_draw");if(u===null)for(let c=0;c<n;c++)this.renderInstances(e[c],t[c],i[c]);else{this.index!==0?u.multiDrawElementsInstancedWEBGL(a,t,0,this.type,e,0,i,0,n):u.multiDrawArraysInstancedWEBGL(a,e,0,t,0,i,0,n);let c=0;for(let d=0;d<n;d++)c+=t[d]*i[d];l.update(o,c,1)}}}class HN{constructor(e=256){this.trackTimestamp=!0,this.maxQueries=e,this.currentQueryIndex=0,this.queryOffsets=new Map,this.isDisposed=!1,this.lastValue=0,this.frames=[],this.pendingResolve=!1,this.timestamps=new Map}getTimestampFrames(){return this.frames}getTimestamp(e){let t=this.timestamps.get(e);return t===void 0&&(ze(`TimestampQueryPool: No timestamp available for uid ${e}.`),t=0),t}hasTimestamp(e){return this.timestamps.has(e)}allocateQueriesForContext(){}resolveQueriesAsync(){return Kr(this,null,function*(){})}dispose(){}}class P$ extends HN{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){ze("EXT_disjoint_timer_query not supported; timestamps will be disabled."),this.trackTimestamp=!1;return}this.queries=[];for(let i=0;i<this.maxQueries;i++)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 rs(`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(t==null||this.activeQuery!==null)return;const n=this.queries[t];if(n)try{this.queryStates.get(t)==="inactive"&&(this.gl.beginQuery(this.ext.TIME_ELAPSED_EXT,n),this.activeQuery=t,this.queryStates.set(t,"started"))}catch(i){rt("Error in beginQuery:",i),this.activeQuery=null,this.queryStates.set(t,"inactive")}}endQuery(e){if(!this.trackTimestamp||this.isDisposed)return;const t=this.queryOffsets.get(e);if(t!=null&&this.activeQuery===t)try{this.gl.endQuery(this.ext.TIME_ELAPSED_EXT),this.queryStates.set(t,"ended"),this.activeQuery=null}catch(n){rt("Error in endQuery:",n),this.queryStates.set(t,"inactive"),this.activeQuery=null}}resolveQueriesAsync(){return Kr(this,null,function*(){if(!this.trackTimestamp||this.pendingResolve)return this.lastValue;this.pendingResolve=!0;try{const e=new Map;for(const[s,a]of this.queryOffsets)if(this.queryStates.get(a)==="ended"){const l=this.queries[a];e.set(s,this.resolveQuery(l))}if(e.size===0)return this.lastValue;const t={},n=[];for(const[s,a]of e){const o=s.match(/^(.*):f(\d+)$/),l=parseInt(o[2]);n.includes(l)===!1&&n.push(l),t[l]===void 0&&(t[l]=0);const u=yield a;this.timestamps.set(s,u),t[l]+=u}const i=t[n[n.length-1]];return this.lastValue=i,this.frames=n,this.currentQueryIndex=0,this.queryOffsets.clear(),this.queryStates.clear(),this.activeQuery=null,i}catch(e){return rt("Error resolving queries:",e),this.lastValue}finally{this.pendingResolve=!1}})}resolveQuery(e){return Kr(this,null,function*(){return new Promise(t=>{if(this.isDisposed){t(this.lastValue);return}let n,i=!1;const s=()=>{n&&(clearTimeout(n),n=null)},a=l=>{i||(i=!0,s(),t(l))},o=()=>{if(this.isDisposed){a(this.lastValue);return}try{if(this.gl.getParameter(this.ext.GPU_DISJOINT_EXT)){a(this.lastValue);return}if(!this.gl.getQueryParameter(e,this.gl.QUERY_RESULT_AVAILABLE)){n=setTimeout(o,1);return}const c=this.gl.getQueryParameter(e,this.gl.QUERY_RESULT);t(Number(c)/1e6)}catch(l){rt("Error checking query:",l),t(this.lastValue)}};o()})})}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 UN extends RN{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=typeof navigator=="undefined"?!1:/OculusBrowser/g.test(navigator.userAgent),this._xrFramebuffer=null}init(e){super.init(e);const t=this.parameters,n={antialias:e.currentSamples>0,alpha:!0,depth:e.depth,stencil:e.stencil},i=t.context!==void 0?t.context:e.domElement.getContext("webgl2",n);function s(a){a.preventDefault();const o={api:"WebGL",message:a.statusMessage||"Unknown reason",reason:null,originalEvent:a};e.onDeviceLost(o)}this._onContextLost=s,e.domElement.addEventListener("webglcontextlost",s,!1),this.gl=i,this.extensions=new E$(this),this.capabilities=new w$(this),this.attributeUtils=new A$(this),this.textureUtils=new b$(this),this.bufferRenderer=new C$(this),this.state=new x$(this),this.utils=new y$(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"),this.drawBuffersIndexedExt=this.extensions.get("OES_draw_buffers_indexed")}get coordinateSystem(){return Gt}getArrayBufferAsync(e){return Kr(this,null,function*(){return yield this.attributeUtils.getArrayBufferAsync(e)})}makeXRCompatible(){return Kr(this,null,function*(){this.gl.getContextAttributes().xrCompatible!==!0&&(yield 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}),n!==null){const s=e.stencilBuffer?i.DEPTH24_STENCIL8:i.DEPTH_COMPONENT24;this.set(e.depthTexture,{textureGPU:n,glInternalFormat:s}),this.extensions.has("WEBGL_multisampled_render_to_texture")===!0&&e._autoAllocateDepthBuffer===!0&&e.multiview===!1&&ze("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 P$(this.gl,e,2048));const n=this.timestampQueryPool[e];n.allocateQueriesForContext(t)!==null&&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(e.viewport)this.updateViewport(e);else{const{width:s,height:a}=this.getDrawingBufferSize();t.viewport(0,0,s,a)}if(e.scissor){const{x:s,y:a,width:o,height:l}=e.scissorValue;t.scissor(s,e.height-l-a,o,l)}this.initTimestampQuery(On.RENDER,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),s=i.previousContext;n.resetVertexState();const a=e.occlusionQueryCount;a>0&&(a>i.occlusionQueryIndex&&t.endQuery(t.ANY_SAMPLES_PASSED),this.resolveOccludedAsync(e));const o=e.textures;if(o!==null)for(let l=0;l<o.length;l++){const u=o[l];u.generateMipmaps&&this.generateMipmaps(u)}if(this._currentContext=s,this._resolveRenderTarget(e),s!==null)if(this._setFramebuffer(s),s.viewport)this.updateViewport(s);else{const{width:l,height:u}=this.getDrawingBufferSize();n.viewport(0,0,l,u)}this.prepareTimestampBuffer(On.RENDER,this.getTimestampUID(e))}resolveOccludedAsync(e){const t=this.get(e),{currentOcclusionQueries:n,currentOcclusionQueryObjects:i}=t;if(n&&i){const s=new WeakSet,{gl:a}=this;t.currentOcclusionQueryObjects=null,t.currentOcclusionQueries=null;const o=()=>{let l=0;for(let u=0;u<n.length;u++){const c=n[u];c!==null&&a.getQueryParameter(c,a.QUERY_RESULT_AVAILABLE)&&(a.getQueryParameter(c,a.QUERY_RESULT)===0&&s.add(i[u]),n[u]=null,a.deleteQuery(c),l++)}l<n.length?requestAnimationFrame(o):t.occluded=s};o()}}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:s,height:a}=e.viewportValue;t.viewport(n,e.height-a-i,s,a)}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,s=!0,a=!0){const{gl:o,renderer:l}=this;i===null&&(i={textures:null,clearColorValue:this.getClearColor()});let u=0;if(e&&(u|=o.COLOR_BUFFER_BIT),t&&(u|=o.DEPTH_BUFFER_BIT),n&&(u|=o.STENCIL_BUFFER_BIT),u!==0){let c;i.clearColorValue?c=i.clearColorValue:c=this.getClearColor();const d=l.getClearDepth(),f=l.getClearStencil();if(t&&this.state.setDepthMask(!0),i.textures===null)o.clearColor(c.r,c.g,c.b,c.a),o.clear(u);else{if(s&&this._setFramebuffer(i),e)for(let h=0;h<i.textures.length;h++)h===0?o.clearBufferfv(o.COLOR,h,[c.r,c.g,c.b,c.a]):o.clearBufferfv(o.COLOR,h,[0,0,0,1]);t&&n?o.clearBufferfi(o.DEPTH_STENCIL,0,d,f):t?o.clearBufferfv(o.DEPTH,0,[d]):n&&o.clearBufferiv(o.STENCIL,0,[f]),s&&a&&this._resolveRenderTarget(i)}}}beginCompute(e){const{state:t,gl:n}=this;t.bindFramebuffer(n.FRAMEBUFFER,null),this.initTimestampQuery(On.COMPUTE,this.getTimestampUID(e))}compute(e,t,n,i,s=null){const{state:a,gl:o}=this;this.discard===!1&&(a.enable(o.RASTERIZER_DISCARD),this.discard=!0);const{programGPU:l,transformBuffers:u,attributes:c}=this.get(i),d=this._getVaoKey(c),f=this.vaoCache[d];f===void 0?this.vaoCache[d]=this._createVao(c):a.setVertexState(f),a.useProgram(l),this._bindUniforms(n);const h=this._getTransformFeedback(u);o.bindTransformFeedback(o.TRANSFORM_FEEDBACK,h),o.beginTransformFeedback(o.POINTS),s=s!==null?s:t.count,Array.isArray(s)?(rs("WebGLBackend.compute(): The count parameter must be a single number, not an array."),s=s[0]):s&&typeof s=="object"&&s.isIndirectStorageBufferAttribute&&(rs("WebGLBackend.compute(): The count parameter must be a single number, not IndirectStorageBufferAttribute"),s=t.count),c[0].isStorageInstancedBufferAttribute?o.drawArraysInstanced(o.POINTS,0,1,s):o.drawArrays(o.POINTS,0,s),o.endTransformFeedback(),o.bindTransformFeedback(o.TRANSFORM_FEEDBACK,null);for(let p=0;p<u.length;p++){const x=u[p];x.pbo&&this.has(x.pbo)&&this.textureUtils.copyBufferToTexture(x.transformBuffer,x.pbo),x.switchBuffers()}}finishCompute(e){const{state:t,gl:n}=this;this.discard=!1,t.disable(n.RASTERIZER_DISCARD),this.prepareTimestampBuffer(On.COMPUTE,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:s,hardwareClippingPlanes:a}=e,{programGPU:o}=this.get(n),{gl:l,state:u}=this,c=this.get(s),d=e.getDrawParameters();if(d===null)return;this._bindUniforms(e.getBindings());const f=t.isMesh&&t.matrixWorld.determinant()<0;u.setMaterial(i,f,a),s.textures!==null&&s.textures.length>1&&u.setMRTBlending(s.textures),u.useProgram(o);const h=e.getAttributes(),p=this.get(h);let x=p.vaoGPU;if(x===void 0){const N=this._getVaoKey(h);x=this.vaoCache[N],x===void 0&&(x=this._createVao(h),this.vaoCache[N]=x,p.vaoGPU=x)}const v=e.getIndex(),m=v!==null?this.get(v).bufferGPU:null;u.setVertexState(x,m);const C=c.lastOcclusionObject;if(C!==t&&C!==void 0){if(C!==null&&C.occlusionTest===!0&&(l.endQuery(l.ANY_SAMPLES_PASSED),c.occlusionQueryIndex++),t.occlusionTest===!0){const N=l.createQuery();l.beginQuery(l.ANY_SAMPLES_PASSED,N),c.occlusionQueries[c.occlusionQueryIndex]=N,c.occlusionQueryObjects[c.occlusionQueryIndex]=t}c.lastOcclusionObject=t}const w=this.bufferRenderer;t.isPoints?w.mode=l.POINTS:t.isLineSegments?w.mode=l.LINES:t.isLine?w.mode=l.LINE_STRIP:t.isLineLoop?w.mode=l.LINE_LOOP:i.wireframe===!0?(u.setLineWidth(i.wireframeLinewidth*this.renderer.getPixelRatio()),w.mode=l.LINES):w.mode=l.TRIANGLES;const{vertexCount:P,instanceCount:B}=d;let{firstVertex:S}=d;if(w.object=t,v!==null){S*=v.array.BYTES_PER_ELEMENT;const N=this.get(v);w.index=v.count,w.type=N.type}else w.index=0;const I=()=>{t.isBatchedMesh?t._multiDrawInstances!==null?(rs("WebGLBackend: renderMultiDrawInstances has been deprecated and will be removed in r184. Append to renderMultiDraw arguments and use indirection."),w.renderMultiDrawInstances(t._multiDrawStarts,t._multiDrawCounts,t._multiDrawCount,t._multiDrawInstances)):this.hasFeature("WEBGL_multi_draw")?w.renderMultiDraw(t._multiDrawStarts,t._multiDrawCounts,t._multiDrawCount):rs("WebGLBackend: WEBGL_multi_draw not supported."):B>1?w.renderInstances(S,P,B):w.render(S,P)};if(e.camera.isArrayCamera===!0&&e.camera.cameras.length>0&&e.camera.isMultiViewCamera===!1){const N=this.get(e.camera),T=e.camera.cameras,R=e.getBindingGroup("cameraIndex").bindings[0];if(N.indexesGPU===void 0||N.indexesGPU.length!==T.length){const de=new Uint32Array([0,0,0,0]),we=[];for(let ge=0,Y=T.length;ge<Y;ge++){const Se=l.createBuffer();de[0]=ge,l.bindBuffer(l.UNIFORM_BUFFER,Se),l.bufferData(l.UNIFORM_BUFFER,de,l.STATIC_DRAW),we.push(Se)}N.indexesGPU=we}const D=this.get(R),j=this.renderer.getPixelRatio(),q=this._currentContext.renderTarget,Q=this._isRenderCameraDepthArray(this._currentContext),re=this._currentContext.activeCubeFace;if(Q){const de=this.get(q.depthTexture);if(de.clearedRenderId!==this.renderer._nodes.nodeFrame.renderId){de.clearedRenderId=this.renderer._nodes.nodeFrame.renderId;const{stencilBuffer:we}=q;for(let ge=0,Y=T.length;ge<Y;ge++)this.renderer._activeCubeFace=ge,this._currentContext.activeCubeFace=ge,this._setFramebuffer(this._currentContext),this.clear(!1,!0,we,this._currentContext,!1,!1);this.renderer._activeCubeFace=re,this._currentContext.activeCubeFace=re}}for(let de=0,we=T.length;de<we;de++){const ge=T[de];if(t.layers.test(ge.layers)){Q&&(this.renderer._activeCubeFace=de,this._currentContext.activeCubeFace=de,this._setFramebuffer(this._currentContext));const Y=ge.viewport;if(Y!==void 0){const Se=Y.x*j,W=Y.y*j,fe=Y.width*j,xe=Y.height*j;u.viewport(Math.floor(Se),Math.floor(e.context.height-xe-W),Math.floor(fe),Math.floor(xe))}u.bindBufferBase(l.UNIFORM_BUFFER,D.index,N.indexesGPU[de]),I()}this._currentContext.activeCubeFace=re,this.renderer._activeCubeFace=re}}else I()}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,t=!1){this.textureUtils.destroyTexture(e,t)}copyTextureToBuffer(e,t,n,i,s,a){return Kr(this,null,function*(){return this.textureUtils.copyTextureToBuffer(e,t,n,i,s,a)})}updateSampler(){return""}createNodeBuilder(e,t){return new m$(e,t)}createProgram(e){const t=this.gl,{stage:n,code:i}=e,s=n==="fragment"?t.createShader(t.FRAGMENT_SHADER):t.createShader(t.VERTEX_SHADER);t.shaderSource(s,i),t.compileShader(s),this.set(e,{shaderGPU:s})}destroyProgram(e){this.delete(e)}createRenderPipeline(e,t){const n=this.gl,i=e.pipeline,{fragmentProgram:s,vertexProgram:a}=i,o=n.createProgram(),l=this.get(s).shaderGPU,u=this.get(a).shaderGPU;if(n.attachShader(o,l),n.attachShader(o,u),n.linkProgram(o),this.set(i,{programGPU:o,fragmentShader:l,vertexShader:u}),t!==null&&this.parallel){const c=new Promise(d=>{const f=this.parallel,h=()=>{n.getProgramParameter(o,f.COMPLETION_STATUS_KHR)?(this._completeCompile(e,i),d()):requestAnimationFrame(h)};h()});t.push(c);return}this._completeCompile(e,i)}_handleSource(e,t){const n=e.split(`
`),i=[],s=Math.max(t-6,0),a=Math.min(t+6,n.length);for(let o=s;o<a;o++){const l=o+1;i.push(`${l===t?">":" "} ${l}: ${n[o]}`)}return i.join(`
`)}_getShaderErrors(e,t,n){const i=e.getShaderParameter(t,e.COMPILE_STATUS),a=(e.getShaderInfoLog(t)||"").trim();if(i&&a==="")return"";const o=/ERROR: 0:(\d+)/.exec(a);if(o){const l=parseInt(o[1]);return n.toUpperCase()+`

`+a+`

`+this._handleSource(e.getShaderSource(t),l)}else return a}_logProgramError(e,t,n){if(this.renderer.debug.checkShaderErrors){const i=this.gl,a=(i.getProgramInfoLog(e)||"").trim();if(i.getProgramParameter(e,i.LINK_STATUS)===!1)if(typeof this.renderer.debug.onShaderError=="function")this.renderer.debug.onShaderError(i,e,n,t);else{const o=this._getShaderErrors(i,n,"vertex"),l=this._getShaderErrors(i,t,"fragment");rt("THREE.WebGLProgram: Shader Error "+i.getError()+" - VALIDATE_STATUS "+i.getProgramParameter(e,i.VALIDATE_STATUS)+`

Program Info Log: `+a+`
`+o+`
`+l)}else a!==""&&ze("WebGLProgram: Program Info Log:",a)}}_completeCompile(e,t){const{state:n,gl:i}=this,s=this.get(t),{programGPU:a,fragmentShader:o,vertexShader:l}=s;i.getProgramParameter(a,i.LINK_STATUS)===!1&&this._logProgramError(a,o,l),n.useProgram(a);const u=e.getBindings();this._setupBindings(u,a),this.set(t,{programGPU:a})}createComputePipeline(e,t){const{state:n,gl:i}=this,s={stage:"fragment",code:`#version 300 es
precision highp float;
void main() {}`};this.createProgram(s);const{computeProgram:a}=e,o=i.createProgram(),l=this.get(s).shaderGPU,u=this.get(a).shaderGPU,c=a.transforms,d=[],f=[];for(let v=0;v<c.length;v++){const m=c[v];d.push(m.varyingName),f.push(m.attributeNode)}i.attachShader(o,l),i.attachShader(o,u),i.transformFeedbackVaryings(o,d,i.SEPARATE_ATTRIBS),i.linkProgram(o),i.getProgramParameter(o,i.LINK_STATUS)===!1&&this._logProgramError(o,l,u),n.useProgram(o),this._setupBindings(t,o);const h=a.attributes,p=[],x=[];for(let v=0;v<h.length;v++){const m=h[v].node.attribute;p.push(m),this.has(m)||this.attributeUtils.createAttribute(m,i.ARRAY_BUFFER)}for(let v=0;v<f.length;v++){const m=f[v].attribute;this.has(m)||this.attributeUtils.createAttribute(m,i.ARRAY_BUFFER);const C=this.get(m);x.push(C)}this.set(e,{programGPU:o,transformBuffers:x,attributes:p})}createBindings(e,t){if(this._knownBindings.has(t)===!1){this._knownBindings.add(t);let n=0,i=0;for(const s of t){this.set(s,{textures:i,uniformBuffers:n});for(const a of s.bindings)a.isUniformBuffer&&n++,a.isSampledTexture&&i++}}this.updateBindings(e,t)}updateBindings(e){const{gl:t}=this,n=this.get(e);let i=n.uniformBuffers,s=n.textures;for(const a of e.bindings){const o=this.get(a);if(a.isUniformsGroup||a.isUniformBuffer){const l=a.buffer;let{bufferGPU:u}=this.get(l);u===void 0?(u=t.createBuffer(),t.bindBuffer(t.UNIFORM_BUFFER,u),t.bufferData(t.UNIFORM_BUFFER,l.byteLength,t.DYNAMIC_DRAW),this.set(l,{bufferGPU:u})):t.bindBuffer(t.UNIFORM_BUFFER,u);const c=a.updateRanges;if(t.bindBuffer(t.UNIFORM_BUFFER,u),c.length===0)t.bufferData(t.UNIFORM_BUFFER,l,t.DYNAMIC_DRAW);else{const d=Wi(l),f=d?1:l.BYTES_PER_ELEMENT;for(let h=0,p=c.length;h<p;h++){const x=c[h],v=x.start*f,m=x.count*f,C=v*(d?l.BYTES_PER_ELEMENT:1);t.bufferSubData(t.UNIFORM_BUFFER,C,l,v,m)}}o.index=i++,o.bufferGPU=u,this.set(a,o)}else if(a.isSampledTexture){const{textureGPU:l,glTextureType:u}=this.get(a.texture);o.index=s++,o.textureGPU=l,o.glTextureType=u,this.set(a,o)}}}updateBinding(e){const t=this.gl;if(e.isUniformsGroup||e.isUniformBuffer){const i=this.get(e).bufferGPU,s=e.buffer,a=e.updateRanges;if(t.bindBuffer(t.UNIFORM_BUFFER,i),a.length===0)t.bufferData(t.UNIFORM_BUFFER,s,t.DYNAMIC_DRAW);else{const o=Wi(s),l=o?1:s.BYTES_PER_ELEMENT;for(let u=0,c=a.length;u<c;u++){const d=a[u],f=d.start*l,h=d.count*l,p=f*(o?s.BYTES_PER_ELEMENT:1);t.bufferSubData(t.UNIFORM_BUFFER,p,s,f,h)}}}}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(zN).filter(i=>zN[i]===e),n=this.extensions;for(let i=0;i<t.length;i++)if(n.has(t[i]))return!0;return!1}getMaxAnisotropy(){return this.capabilities.getMaxAnisotropy()}copyTextureToTexture(e,t,n=null,i=null,s=0,a=0){this.textureUtils.copyTextureToTexture(e,t,n,i,s,a)}copyFramebufferToTexture(e,t,n){this.textureUtils.copyFramebufferToTexture(e,t,n)}_setFramebuffer(e){const{gl:t,state:n}=this;let i=null;if(e.textures!==null){const s=e.renderTarget,a=this.get(s),{samples:o,depthBuffer:l,stencilBuffer:u}=s,c=s.isWebGLCubeRenderTarget===!0,d=s.isRenderTarget3D===!0,f=s.depth>1,h=s.isXRRenderTarget===!0,p=h===!0&&s._hasExternalTextures===!0;let x=a.msaaFrameBuffer,v=a.depthRenderbuffer;const m=this.extensions.get("WEBGL_multisampled_render_to_texture"),C=this.extensions.get("OVR_multiview2"),w=this._useMultisampledExtension(s),P=r9(e);let B;if(c?(a.cubeFramebuffers||(a.cubeFramebuffers={}),B=a.cubeFramebuffers[P]):h&&p===!1?B=this._xrFramebuffer:(a.framebuffers||(a.framebuffers={}),B=a.framebuffers[P]),B===void 0){B=t.createFramebuffer(),n.bindFramebuffer(t.FRAMEBUFFER,B);const S=e.textures,I=[];if(c){a.cubeFramebuffers[P]=B;const{textureGPU:T}=this.get(S[0]),R=this.renderer._activeCubeFace,D=this.renderer._activeMipmapLevel;t.framebufferTexture2D(t.FRAMEBUFFER,t.COLOR_ATTACHMENT0,t.TEXTURE_CUBE_MAP_POSITIVE_X+R,T,D)}else{a.framebuffers[P]=B;for(let T=0;T<S.length;T++){const R=S[T],D=this.get(R);D.renderTarget=e.renderTarget,D.cacheKey=P;const j=t.COLOR_ATTACHMENT0+T;if(s.multiview)C.framebufferTextureMultisampleMultiviewOVR(t.FRAMEBUFFER,j,D.textureGPU,0,o,0,2);else if(d||f){const q=this.renderer._activeCubeFace,Q=this.renderer._activeMipmapLevel;t.framebufferTextureLayer(t.FRAMEBUFFER,j,D.textureGPU,Q,q)}else if(w)m.framebufferTexture2DMultisampleEXT(t.FRAMEBUFFER,j,t.TEXTURE_2D,D.textureGPU,0,o);else{const q=this.renderer._activeMipmapLevel;t.framebufferTexture2D(t.FRAMEBUFFER,j,t.TEXTURE_2D,D.textureGPU,q)}}}const N=u?t.DEPTH_STENCIL_ATTACHMENT:t.DEPTH_ATTACHMENT;if(s._autoAllocateDepthBuffer===!0){const T=t.createRenderbuffer();this.textureUtils.setupRenderBufferStorage(T,e,0,w),a.xrDepthRenderbuffer=T,I.push(u?t.DEPTH_STENCIL_ATTACHMENT:t.DEPTH_ATTACHMENT),t.bindRenderbuffer(t.RENDERBUFFER,T),t.framebufferRenderbuffer(t.FRAMEBUFFER,N,t.RENDERBUFFER,T)}else if(e.depthTexture!==null){I.push(u?t.DEPTH_STENCIL_ATTACHMENT:t.DEPTH_ATTACHMENT);const T=this.get(e.depthTexture);if(T.renderTarget=e.renderTarget,T.cacheKey=P,s.multiview)C.framebufferTextureMultisampleMultiviewOVR(t.FRAMEBUFFER,N,T.textureGPU,0,o,0,2);else if(p&&w)m.framebufferTexture2DMultisampleEXT(t.FRAMEBUFFER,N,t.TEXTURE_2D,T.textureGPU,0,o);else if(e.depthTexture.isArrayTexture){const R=this.renderer._activeCubeFace;t.framebufferTextureLayer(t.FRAMEBUFFER,N,T.textureGPU,0,R)}else if(e.depthTexture.isCubeTexture){const R=this.renderer._activeCubeFace;t.framebufferTexture2D(t.FRAMEBUFFER,N,t.TEXTURE_CUBE_MAP_POSITIVE_X+R,T.textureGPU,0)}else t.framebufferTexture2D(t.FRAMEBUFFER,N,t.TEXTURE_2D,T.textureGPU,0)}a.depthInvalidationArray=I}else{if(this._isRenderCameraDepthArray(e)){n.bindFramebuffer(t.FRAMEBUFFER,B);const I=this.renderer._activeCubeFace,N=this.get(e.depthTexture),T=u?t.DEPTH_STENCIL_ATTACHMENT:t.DEPTH_ATTACHMENT;t.framebufferTextureLayer(t.FRAMEBUFFER,T,N.textureGPU,0,I)}if((h||w||s.multiview)&&s._isOpaqueFramebuffer!==!0){n.bindFramebuffer(t.FRAMEBUFFER,B);const I=this.get(e.textures[0]);s.multiview?C.framebufferTextureMultisampleMultiviewOVR(t.FRAMEBUFFER,t.COLOR_ATTACHMENT0,I.textureGPU,0,o,0,2):w?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 N=u?t.DEPTH_STENCIL_ATTACHMENT:t.DEPTH_ATTACHMENT;if(s._autoAllocateDepthBuffer===!0){const T=a.xrDepthRenderbuffer;t.bindRenderbuffer(t.RENDERBUFFER,T),t.framebufferRenderbuffer(t.FRAMEBUFFER,N,t.RENDERBUFFER,T)}else{const T=this.get(e.depthTexture);s.multiview?C.framebufferTextureMultisampleMultiviewOVR(t.FRAMEBUFFER,N,T.textureGPU,0,o,0,2):w?m.framebufferTexture2DMultisampleEXT(t.FRAMEBUFFER,N,t.TEXTURE_2D,T.textureGPU,0,o):t.framebufferTexture2D(t.FRAMEBUFFER,N,t.TEXTURE_2D,T.textureGPU,0)}}}if(o>0&&w===!1&&!s.multiview){if(x===void 0){const S=[];x=t.createFramebuffer(),n.bindFramebuffer(t.FRAMEBUFFER,x);const I=[],N=e.textures;for(let T=0;T<N.length;T++){I[T]=t.createRenderbuffer(),t.bindRenderbuffer(t.RENDERBUFFER,I[T]),S.push(t.COLOR_ATTACHMENT0+T);const R=e.textures[T],D=this.get(R);t.renderbufferStorageMultisample(t.RENDERBUFFER,o,D.glInternalFormat,e.width,e.height),t.framebufferRenderbuffer(t.FRAMEBUFFER,t.COLOR_ATTACHMENT0+T,t.RENDERBUFFER,I[T])}if(t.bindRenderbuffer(t.RENDERBUFFER,null),a.msaaFrameBuffer=x,a.msaaRenderbuffers=I,l&&v===void 0){v=t.createRenderbuffer(),this.textureUtils.setupRenderBufferStorage(v,e,o),a.depthRenderbuffer=v;const T=u?t.DEPTH_STENCIL_ATTACHMENT:t.DEPTH_ATTACHMENT;S.push(T)}a.invalidationArray=S}i=a.msaaFrameBuffer}else i=B;n.drawBuffers(e,B)}n.bindFramebuffer(t.FRAMEBUFFER,i)}_getVaoKey(e){let t="";for(let n=0;n<e.length;n++){const i=this.get(e[n]);t+=":"+i.id}return t}_createVao(e){const{gl:t}=this,n=t.createVertexArray();t.bindVertexArray(n);for(let i=0;i<e.length;i++){const s=e[i],a=this.get(s);t.bindBuffer(t.ARRAY_BUFFER,a.bufferGPU),t.enableVertexAttribArray(i);let o,l;s.isInterleavedBufferAttribute===!0?(o=s.data.stride*a.bytesPerElement,l=s.offset*a.bytesPerElement):(o=0,l=0),a.isInteger?t.vertexAttribIPointer(i,s.itemSize,a.type,o,l):t.vertexAttribPointer(i,s.itemSize,a.type,s.normalized,o,l),s.isInstancedBufferAttribute&&!s.isInterleavedBufferAttribute?t.vertexAttribDivisor(i,s.meshPerAttribute):s.isInterleavedBufferAttribute&&s.data.isInstancedInterleavedBuffer&&t.vertexAttribDivisor(i,s.data.meshPerAttribute)}return t.bindBuffer(t.ARRAY_BUFFER,null),n}_getTransformFeedback(e){let t="";for(let s=0;s<e.length;s++)t+=":"+e[s].id;let n=this.transformFeedbackCache[t];if(n!==void 0)return n;const{gl:i}=this;n=i.createTransformFeedback(),i.bindTransformFeedback(i.TRANSFORM_FEEDBACK,n);for(let s=0;s<e.length;s++){const a=e[s];i.bindBufferBase(i.TRANSFORM_FEEDBACK_BUFFER,s,a.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 s of i.bindings){const o=this.get(s).index;if(s.isUniformsGroup||s.isUniformBuffer){const l=n.getUniformBlockIndex(t,s.name);n.uniformBlockBinding(t,l,o)}else if(s.isSampledTexture){const l=n.getUniformLocation(t,s.name);n.uniform1i(l,o)}}}_bindUniforms(e){const{gl:t,state:n}=this;for(const i of e)for(const s of i.bindings){const a=this.get(s),o=a.index;s.isUniformsGroup||s.isUniformBuffer?n.bindBufferBase(t.UNIFORM_BUFFER,o,a.bufferGPU):s.isSampledTexture&&n.bindTexture(a.glTextureType,a.textureGPU,t.TEXTURE0+o)}}_resolveRenderTarget(e){const{gl:t,state:n}=this,i=e.renderTarget;if(e.textures!==null&&i){const s=this.get(i);if(i.samples>0&&this._useMultisampledExtension(i)===!1){const a=s.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 l=s.msaaFrameBuffer,u=s.msaaRenderbuffers,c=e.textures,d=c.length>1;if(n.bindFramebuffer(t.READ_FRAMEBUFFER,l),n.bindFramebuffer(t.DRAW_FRAMEBUFFER,a),d)for(let f=0;f<c.length;f++)t.framebufferRenderbuffer(t.READ_FRAMEBUFFER,t.COLOR_ATTACHMENT0+f,t.RENDERBUFFER,null),t.framebufferTexture2D(t.DRAW_FRAMEBUFFER,t.COLOR_ATTACHMENT0+f,t.TEXTURE_2D,null,0);for(let f=0;f<c.length;f++){if(d){const{textureGPU:h}=this.get(c[f]);t.framebufferRenderbuffer(t.READ_FRAMEBUFFER,t.COLOR_ATTACHMENT0,t.RENDERBUFFER,u[f]),t.framebufferTexture2D(t.DRAW_FRAMEBUFFER,t.COLOR_ATTACHMENT0,t.TEXTURE_2D,h,0)}if(e.scissor){const{x:h,y:p,width:x,height:v}=e.scissorValue,m=e.height-v-p;t.blitFramebuffer(h,m,h+x,m+v,h,m,h+x,m+v,o,t.NEAREST)}else t.blitFramebuffer(0,0,e.width,e.height,0,0,e.width,e.height,o,t.NEAREST)}if(d)for(let f=0;f<c.length;f++){const{textureGPU:h}=this.get(c[f]);t.framebufferRenderbuffer(t.READ_FRAMEBUFFER,t.COLOR_ATTACHMENT0+f,t.RENDERBUFFER,u[f]),t.framebufferTexture2D(t.DRAW_FRAMEBUFFER,t.COLOR_ATTACHMENT0+f,t.TEXTURE_2D,h,0)}this._supportsInvalidateFramebuffer===!0&&t.invalidateFramebuffer(t.READ_FRAMEBUFFER,s.invalidationArray)}else if(i.resolveDepthBuffer===!1&&s.framebuffers){const a=s.framebuffers[e.getCacheKey()];n.bindFramebuffer(t.DRAW_FRAMEBUFFER,a),t.invalidateFramebuffer(t.DRAW_FRAMEBUFFER,s.depthInvalidationArray)}}}_useMultisampledExtension(e){return e.multiview===!0?!0:e.samples>0&&this.extensions.has("WEBGL_multisampled_render_to_texture")===!0&&e._autoAllocateDepthBuffer!==!1}dispose(){this.textureUtils!==null&&this.textureUtils.dispose();const e=this.extensions.get("WEBGL_lose_context");e&&e.loseContext(),this.renderer.domElement.removeEventListener("webglcontextlost",this._onContextLost)}}const LA={PointList:"point-list",LineList:"line-list",LineStrip:"line-strip",TriangleList:"triangle-list",TriangleStrip:"triangle-strip"},Bg=typeof self!="undefined"?self.GPUShaderStage:{VERTEX:1,FRAGMENT:2,COMPUTE:4},Ml={Never:"never",Less:"less",Equal:"equal",LessEqual:"less-equal",Greater:"greater",NotEqual:"not-equal",GreaterEqual:"greater-equal",Always:"always"},du={Store:"store"},Zs={Load:"load",Clear:"clear"},kN={CCW:"ccw",CW:"cw"},VN={None:"none",Back:"back"},OA={Uint16:"uint16",Uint32:"uint32"},ye={R8Unorm:"r8unorm",R8Snorm:"r8snorm",R8Uint:"r8uint",R8Sint:"r8sint",R16Uint:"r16uint",R16Sint:"r16sint",R16Float:"r16float",RG8Unorm:"rg8unorm",RG8Snorm:"rg8snorm",RG8Uint:"rg8uint",RG8Sint:"rg8sint",R32Uint:"r32uint",R32Sint:"r32sint",R32Float:"r32float",RG16Uint:"rg16uint",RG16Sint:"rg16sint",RG16Float:"rg16float",RGBA8Unorm:"rgba8unorm",RGBA8UnormSRGB:"rgba8unorm-srgb",RGBA8Snorm:"rgba8snorm",RGBA8Uint:"rgba8uint",RGBA8Sint:"rgba8sint",BGRA8Unorm:"bgra8unorm",BGRA8UnormSRGB:"bgra8unorm-srgb",RGB9E5UFloat:"rgb9e5ufloat",RGB10A2Unorm:"rgb10a2unorm",RG11B10UFloat:"rg11b10ufloat",RG32Uint:"rg32uint",RG32Sint:"rg32sint",RG32Float:"rg32float",RGBA16Uint:"rgba16uint",RGBA16Sint:"rgba16sint",RGBA16Float:"rgba16float",RGBA32Uint:"rgba32uint",RGBA32Sint:"rgba32sint",RGBA32Float:"rgba32float",Depth16Unorm:"depth16unorm",Depth24Plus:"depth24plus",Depth24PlusStencil8:"depth24plus-stencil8",Depth32Float:"depth32float",Depth32FloatStencil8:"depth32float-stencil8",BC1RGBAUnorm:"bc1-rgba-unorm",BC1RGBAUnormSRGB:"bc1-rgba-unorm-srgb",BC2RGBAUnorm:"bc2-rgba-unorm",BC2RGBAUnormSRGB:"bc2-rgba-unorm-srgb",BC3RGBAUnorm:"bc3-rgba-unorm",BC3RGBAUnormSRGB:"bc3-rgba-unorm-srgb",BC4RUnorm:"bc4-r-unorm",BC4RSnorm:"bc4-r-snorm",BC5RGUnorm:"bc5-rg-unorm",BC5RGSnorm:"bc5-rg-snorm",BC6HRGBUFloat:"bc6h-rgb-ufloat",BC6HRGBFloat:"bc6h-rgb-float",BC7RGBAUnorm:"bc7-rgba-unorm",BC7RGBAUnormSRGB:"bc7-rgba-unorm-srgb",ETC2RGB8Unorm:"etc2-rgb8unorm",ETC2RGB8UnormSRGB:"etc2-rgb8unorm-srgb",ETC2RGB8A1Unorm:"etc2-rgb8a1unorm",ETC2RGB8A1UnormSRGB:"etc2-rgb8a1unorm-srgb",ETC2RGBA8Unorm:"etc2-rgba8unorm",ETC2RGBA8UnormSRGB:"etc2-rgba8unorm-srgb",EACR11Unorm:"eac-r11unorm",EACR11Snorm:"eac-r11snorm",EACRG11Unorm:"eac-rg11unorm",EACRG11Snorm:"eac-rg11snorm",ASTC4x4Unorm:"astc-4x4-unorm",ASTC4x4UnormSRGB:"astc-4x4-unorm-srgb",ASTC5x4Unorm:"astc-5x4-unorm",ASTC5x4UnormSRGB:"astc-5x4-unorm-srgb",ASTC5x5Unorm:"astc-5x5-unorm",ASTC5x5UnormSRGB:"astc-5x5-unorm-srgb",ASTC6x5Unorm:"astc-6x5-unorm",ASTC6x5UnormSRGB:"astc-6x5-unorm-srgb",ASTC6x6Unorm:"astc-6x6-unorm",ASTC6x6UnormSRGB:"astc-6x6-unorm-srgb",ASTC8x5Unorm:"astc-8x5-unorm",ASTC8x5UnormSRGB:"astc-8x5-unorm-srgb",ASTC8x6Unorm:"astc-8x6-unorm",ASTC8x6UnormSRGB:"astc-8x6-unorm-srgb",ASTC8x8Unorm:"astc-8x8-unorm",ASTC8x8UnormSRGB:"astc-8x8-unorm-srgb",ASTC10x5Unorm:"astc-10x5-unorm",ASTC10x5UnormSRGB:"astc-10x5-unorm-srgb",ASTC10x6Unorm:"astc-10x6-unorm",ASTC10x6UnormSRGB:"astc-10x6-unorm-srgb",ASTC10x8Unorm:"astc-10x8-unorm",ASTC10x8UnormSRGB:"astc-10x8-unorm-srgb",ASTC10x10Unorm:"astc-10x10-unorm",ASTC10x10UnormSRGB:"astc-10x10-unorm-srgb",ASTC12x10Unorm:"astc-12x10-unorm",ASTC12x10UnormSRGB:"astc-12x10-unorm-srgb",ASTC12x12Unorm:"astc-12x12-unorm",ASTC12x12UnormSRGB:"astc-12x12-unorm-srgb"},fM={ClampToEdge:"clamp-to-edge",Repeat:"repeat",MirrorRepeat:"mirror-repeat"},Mg={Linear:"linear",Nearest:"nearest"},As={Zero:"zero",One:"one",Src:"src",OneMinusSrc:"one-minus-src",SrcAlpha:"src-alpha",OneMinusSrcAlpha:"one-minus-src-alpha",Dst:"dst",OneMinusDst:"one-minus-dst",DstAlpha:"dst-alpha",OneMinusDstAlpha:"one-minus-dst-alpha",SrcAlphaSaturated:"src-alpha-saturated",Constant:"constant",OneMinusConstant:"one-minus-constant"},Sg={Add:"add",Subtract:"subtract",ReverseSubtract:"reverse-subtract",Min:"min",Max:"max"},jN={None:0,All:15},Jp={Keep:"keep",Zero:"zero",Replace:"replace",Invert:"invert",IncrementClamp:"increment-clamp",DecrementClamp:"decrement-clamp",IncrementWrap:"increment-wrap",DecrementWrap:"decrement-wrap"},hM={Storage:"storage",ReadOnlyStorage:"read-only-storage"},pM={WriteOnly:"write-only",ReadOnly:"read-only",ReadWrite:"read-write"},XN={NonFiltering:"non-filtering",Comparison:"comparison"},Dg={Float:"float",UnfilterableFloat:"unfilterable-float",Depth:"depth",SInt:"sint",UInt:"uint"},GN={TwoD:"2d",ThreeD:"3d"},Ro={TwoD:"2d",TwoDArray:"2d-array",Cube:"cube",ThreeD:"3d"},B$={All:"all"},Aw={Vertex:"vertex",Instance:"instance"},mM={CoreFeaturesAndLimits:"core-features-and-limits",DepthClipControl:"depth-clip-control",Depth32FloatStencil8:"depth32float-stencil8",TextureCompressionBC:"texture-compression-bc",TextureCompressionBCSliced3D:"texture-compression-bc-sliced-3d",TextureCompressionETC2:"texture-compression-etc2",TextureCompressionASTC:"texture-compression-astc",TextureCompressionASTCSliced3D:"texture-compression-astc-sliced-3d",TimestampQuery:"timestamp-query",IndirectFirstInstance:"indirect-first-instance",ShaderF16:"shader-f16",RG11B10UFloat:"rg11b10ufloat-renderable",BGRA8UNormStorage:"bgra8unorm-storage",Float32Filterable:"float32-filterable",Float32Blendable:"float32-blendable",ClipDistances:"clip-distances",DualSourceBlending:"dual-source-blending",Subgroups:"subgroups",TextureFormatsTier1:"texture-formats-tier1",TextureFormatsTier2:"texture-formats-tier2"},WN={"texture-compression-s3tc":"texture-compression-bc","texture-compression-etc1":"texture-compression-etc2"};class M$ extends MN{constructor(e,t,n){super(e,t?t.value:null),this.textureNode=t,this.groupNode=n}update(){const{textureNode:e}=this;return this.texture!==e.value?(this.texture=e.value,!0):super.update()}}class S$ extends wN{constructor(e,t){super(e,t?t.array:null),this.attribute=t,this.isStorageBuffer=!0}}let D$=0;class T$ extends S${constructor(e,t){super("StorageBuffer_"+D$++,e?e.value:null),this.nodeUniform=e,this.access=e?e.access:El.READ_WRITE,this.groupNode=t}get buffer(){return this.nodeUniform.value}}class I$ extends Wp{constructor(e){super(),this.device=e;const t=`
struct VarysStruct {
	@builtin( position ) Position: vec4<f32>,
	@location( 0 ) vTex : vec2<f32>
};

@vertex
fn main( @builtin( vertex_index ) vertexIndex : u32 ) -> VarysStruct {

	var Varys : VarysStruct;

	var pos = array< vec2<f32>, 4 >(
		vec2<f32>( -1.0,  1.0 ),
		vec2<f32>(  1.0,  1.0 ),
		vec2<f32>( -1.0, -1.0 ),
		vec2<f32>(  1.0, -1.0 )
	);

	var tex = array< vec2<f32>, 4 >(
		vec2<f32>( 0.0, 0.0 ),
		vec2<f32>( 1.0, 0.0 ),
		vec2<f32>( 0.0, 1.0 ),
		vec2<f32>( 1.0, 1.0 )
	);

	Varys.vTex = tex[ vertexIndex ];
	Varys.Position = vec4<f32>( pos[ vertexIndex ], 0.0, 1.0 );

	return Varys;

}
`,n=`
@group( 0 ) @binding( 0 )
var imgSampler : sampler;

@group( 0 ) @binding( 1 )
var img : texture_2d<f32>;

@fragment
fn main( @location( 0 ) vTex : vec2<f32> ) -> @location( 0 ) vec4<f32> {

	return textureSample( img, imgSampler, vTex );

}
`,i=`
@group( 0 ) @binding( 0 )
var imgSampler : sampler;

@group( 0 ) @binding( 1 )
var img : texture_2d<f32>;

@fragment
fn main( @location( 0 ) vTex : vec2<f32> ) -> @location( 0 ) vec4<f32> {

	return textureSample( img, imgSampler, vec2( vTex.x, 1.0 - vTex.y ) );

}
`;this.mipmapSampler=e.createSampler({minFilter:Mg.Linear}),this.flipYSampler=e.createSampler({minFilter:Mg.Nearest}),this.transferPipelines={},this.flipYPipelines={},this.mipmapVertexShaderModule=e.createShaderModule({label:"mipmapVertex",code:t}),this.mipmapFragmentShaderModule=e.createShaderModule({label:"mipmapFragment",code:n}),this.flipYFragmentShaderModule=e.createShaderModule({label:"flipYFragment",code:i})}getTransferPipeline(e){let t=this.transferPipelines[e];return t===void 0&&(t=this.device.createRenderPipeline({label:`mipmap-${e}`,vertex:{module:this.mipmapVertexShaderModule,entryPoint:"main"},fragment:{module:this.mipmapFragmentShaderModule,entryPoint:"main",targets:[{format:e}]},primitive:{topology:LA.TriangleStrip,stripIndexFormat:OA.Uint32},layout:"auto"}),this.transferPipelines[e]=t),t}getFlipYPipeline(e){let t=this.flipYPipelines[e];return t===void 0&&(t=this.device.createRenderPipeline({label:`flipY-${e}`,vertex:{module:this.mipmapVertexShaderModule,entryPoint:"main"},fragment:{module:this.flipYFragmentShaderModule,entryPoint:"main",targets:[{format:e}]},primitive:{topology:LA.TriangleStrip,stripIndexFormat:OA.Uint32},layout:"auto"}),this.flipYPipelines[e]=t),t}flipY(e,t,n=0){const i=t.format,{width:s,height:a}=t.size,o=this.getTransferPipeline(i),l=this.getFlipYPipeline(i),u=this.device.createTexture({size:{width:s,height:a,depthOrArrayLayers:1},format:i,usage:GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING}),c=e.createView({baseMipLevel:0,mipLevelCount:1,dimension:Ro.TwoD,baseArrayLayer:n}),d=u.createView({baseMipLevel:0,mipLevelCount:1,dimension:Ro.TwoD,baseArrayLayer:0}),f=this.device.createCommandEncoder({}),h=(p,x,v)=>{const m=p.getBindGroupLayout(0),C=this.device.createBindGroup({layout:m,entries:[{binding:0,resource:this.flipYSampler},{binding:1,resource:x}]}),w=f.beginRenderPass({colorAttachments:[{view:v,loadOp:Zs.Clear,storeOp:du.Store,clearValue:[0,0,0,0]}]});w.setPipeline(p),w.setBindGroup(0,C),w.draw(4,1,0,0),w.end()};h(o,c,d),h(l,d,c),this.device.queue.submit([f.finish()]),u.destroy()}generateMipmaps(e,t,n=0,i=null){const s=this.get(e);s.layers===void 0&&(s.layers=[]);const a=s.layers[n]||this._mipmapCreateBundles(e,t,n),o=i||this.device.createCommandEncoder({label:"mipmapEncoder"});this._mipmapRunBundles(o,a),i===null&&this.device.queue.submit([o.finish()]),s.layers[n]=a}_mipmapCreateBundles(e,t,n){const i=this.getTransferPipeline(t.format),s=i.getBindGroupLayout(0);let a=e.createView({baseMipLevel:0,mipLevelCount:1,dimension:Ro.TwoD,baseArrayLayer:n});const o=[];for(let l=1;l<t.mipLevelCount;l++){const u=this.device.createBindGroup({layout:s,entries:[{binding:0,resource:this.mipmapSampler},{binding:1,resource:a}]}),c=e.createView({baseMipLevel:l,mipLevelCount:1,dimension:Ro.TwoD,baseArrayLayer:n}),d={colorAttachments:[{view:c,loadOp:Zs.Clear,storeOp:du.Store,clearValue:[0,0,0,0]}]},f=this.device.createRenderBundleEncoder({colorFormats:[t.format]});f.setPipeline(i),f.setBindGroup(0,u),f.draw(4,1,0,0),o.push({renderBundles:[f.finish()],passDescriptor:d}),a=c}return o}_mipmapRunBundles(e,t){const n=t.length;for(let i=0;i<n;i++){const s=t[i],a=e.beginRenderPass(s.passDescriptor);a.executeBundles(s.renderBundles),a.end()}}}const N$={[w0]:"never",[bp]:"less",[g]:"equal",[A]:"less-equal",[b]:"greater",[z]:"greater-equal",[H]:"always",[M]:"not-equal"},F$=[0,1,3,2,4,5];class R${constructor(e){this.backend=e,this._passUtils=null,this.defaultTexture={},this.defaultCubeTexture={},this.defaultVideoFrame=null,this._samplerCache=new Map}updateSampler(e){const t=this.backend,n=e.minFilter+"-"+e.magFilter+"-"+e.wrapS+"-"+e.wrapT+"-"+(e.wrapR||"0")+"-"+e.anisotropy+"-"+(e.compareFunction||0);let i=this._samplerCache.get(n);if(i===void 0){const a={addressModeU:this._convertAddressMode(e.wrapS),addressModeV:this._convertAddressMode(e.wrapT),addressModeW:this._convertAddressMode(e.wrapR),magFilter:this._convertFilterMode(e.magFilter),minFilter:this._convertFilterMode(e.minFilter),mipmapFilter:this._convertFilterMode(e.minFilter),maxAnisotropy:1};a.magFilter===Mg.Linear&&a.minFilter===Mg.Linear&&a.mipmapFilter===Mg.Linear&&(a.maxAnisotropy=e.anisotropy),e.isDepthTexture&&e.compareFunction!==null&&(a.compare=N$[e.compareFunction]),i={sampler:t.device.createSampler(a),usedTimes:0},this._samplerCache.set(n,i)}const s=t.get(e);if(s.sampler!==i.sampler){if(s.sampler!==void 0){const a=this._samplerCache.get(s.samplerKey);a.usedTimes--,a.usedTimes===0&&this._samplerCache.delete(s.samplerKey)}s.samplerKey=n,s.sampler=i.sampler,i.usedTimes++}return n}createDefaultTexture(e){let t;const n=gM(e);e.isCubeTexture?t=this._getDefaultCubeTextureGPU(n):t=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){i.texture=e.sourceTexture,i.initialized=!0;return}t.needsMipmaps===void 0&&(t.needsMipmaps=!1),t.levels===void 0&&(t.levels=1),t.depth===void 0&&(t.depth=1);const{width:s,height:a,depth:o,levels:l}=t;e.isFramebufferTexture&&(t.renderTarget?t.format=this.backend.utils.getCurrentColorFormat(t.renderTarget):t.format=this.backend.utils.getPreferredCanvasFormat());const u=this._getDimension(e),c=e.internalFormat||t.format||gM(e,n.device);i.format=c;const{samples:d,primarySamples:f,isMSAA:h}=n.utils.getTextureSampleData(e);let p=GPUTextureUsage.TEXTURE_BINDING|GPUTextureUsage.COPY_DST|GPUTextureUsage.COPY_SRC;e.isStorageTexture===!0&&(p|=GPUTextureUsage.STORAGE_BINDING),e.isCompressedTexture!==!0&&e.isCompressedArrayTexture!==!0&&c!==ye.RGB9E5UFloat&&(p|=GPUTextureUsage.RENDER_ATTACHMENT);const x={label:e.name,size:{width:s,height:a,depthOrArrayLayers:o},mipLevelCount:l,sampleCount:f,dimension:u,format:c,usage:p};if(c===void 0){ze("WebGPURenderer: Texture format not supported."),this.createDefaultTexture(e);return}if(e.isCubeTexture&&(x.textureBindingViewDimension=Ro.Cube),i.texture=n.device.createTexture(x),h){const v=Object.assign({},x);v.label=v.label+"-msaa",v.sampleCount=d,v.mipLevelCount=1,i.msaaTexture=n.device.createTexture(v)}i.initialized=!0,i.textureDescriptorGPU=x}destroyTexture(e,t=!1){const n=this.backend,i=n.get(e);i.texture!==void 0&&t===!1&&i.texture.destroy(),i.msaaTexture!==void 0&&i.msaaTexture.destroy(),n.delete(e)}generateMipmaps(e,t=null){const n=this.backend.get(e);if(e.isCubeTexture)for(let i=0;i<6;i++)this._generateMipmaps(n.texture,n.textureDescriptorGPU,i,t);else{const i=e.image.depth||1;for(let s=0;s<i;s++)this._generateMipmaps(n.texture,n.textureDescriptorGPU,s,t)}}getColorBuffer(){const e=this.backend,t=e.renderer.getCanvasTarget(),{width:n,height:i}=e.getDrawingBufferSize(),s=e.renderer.currentSamples,a=t.colorTexture,o=e.get(a);if(a.width===n&&a.height===i&&a.samples===s)return o.texture;let l=o.texture;return l&&l.destroy(),l=e.device.createTexture({label:"colorBuffer",size:{width:n,height:i,depthOrArrayLayers:1},sampleCount:e.utils.getSampleCount(e.renderer.currentSamples),format:e.utils.getPreferredCanvasFormat(),usage:GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.COPY_SRC}),a.source.width=n,a.source.height=i,a.samples=s,o.texture=l,l}getDepthBuffer(e=!0,t=!1){const n=this.backend,i=n.renderer.getCanvasTarget(),{width:s,height:a}=n.getDrawingBufferSize(),o=n.renderer.currentSamples,l=i.depthTexture;if(l.width===s&&l.height===a&&l.samples===o&&l.depth===e&&l.stencil===t)return n.get(l).texture;const u=n.get(l).texture;let c,d;if(t?(c=vl,d=Ll):e&&(c=jo,d=Ls),u!==void 0){if(l.image.width===s&&l.image.height===a&&l.format===c&&l.type===d&&l.samples===o)return u;this.destroyTexture(l)}return l.name="depthBuffer",l.format=c,l.type=d,l.image.width=s,l.image.height=a,l.samples=o,this.createTexture(l,{width:s,height:a}),n.get(l).texture}updateTexture(e,t){const n=this.backend.get(e),i=e.mipmaps,{textureDescriptorGPU:s}=n;if(!(e.isRenderTargetTexture||s===void 0)){if(e.isDataTexture)if(i.length>0)for(let a=0,o=i.length;a<o;a++){const l=i[a];this._copyBufferToTexture(l,n.texture,s,0,e.flipY,0,a)}else this._copyBufferToTexture(t.image,n.texture,s,0,e.flipY);else if(e.isArrayTexture||e.isDataArrayTexture||e.isData3DTexture)for(let a=0;a<t.image.depth;a++)this._copyBufferToTexture(t.image,n.texture,s,a,e.flipY,a);else if(e.isCompressedTexture||e.isCompressedArrayTexture)this._copyCompressedBufferToTexture(e.mipmaps,n.texture,s);else if(e.isCubeTexture)this._copyCubeMapToTexture(e,n.texture,s);else if(i.length>0)for(let a=0,o=i.length;a<o;a++){const l=i[a];this._copyImageToTexture(l,n.texture,s,0,e.flipY,e.premultiplyAlpha,a)}else this._copyImageToTexture(t.image,n.texture,s,0,e.flipY,e.premultiplyAlpha);n.version=e.version}}copyTextureToBuffer(e,t,n,i,s,a){return Kr(this,null,function*(){const o=this.backend.device,l=this.backend.get(e),u=l.texture,c=l.textureDescriptorGPU.format,d=this._getBytesPerTexel(c);let f=i*d;f=Math.ceil(f/256)*256;const h=o.createBuffer({size:(s-1)*f+i*d,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ}),p=o.createCommandEncoder();p.copyTextureToBuffer({texture:u,origin:{x:t,y:n,z:a}},{buffer:h,bytesPerRow:f},{width:i,height:s});const x=this._getTypedArrayType(c);o.queue.submit([p.finish()]),yield h.mapAsync(GPUMapMode.READ);const v=h.getMappedRange();return new x(v)})}dispose(){this._samplerCache.clear()}_getDefaultTextureGPU(e){let t=this.defaultTexture[e];if(t===void 0){const n=new yo;n.minFilter=Cs,n.magFilter=Cs,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.defaultCubeTexture[e];if(t===void 0){const n=new km;n.minFilter=Cs,n.magFilter=Cs,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,s=e.mipmaps;for(let a=0;a<6;a++){const o=i[a],l=e.flipY===!0?F$[a]:a;o.isDataTexture?this._copyBufferToTexture(o.image,t,n,l,e.flipY):this._copyImageToTexture(o,t,n,l,e.flipY,e.premultiplyAlpha);for(let u=0;u<s.length;u++){const d=s[u].images[a];d.isDataTexture?this._copyBufferToTexture(d.image,t,n,l,e.flipY,0,u+1):this._copyImageToTexture(d,t,n,l,e.flipY,e.premultiplyAlpha,u+1)}}}_copyImageToTexture(e,t,n,i,s,a,o=0){const l=this.backend.device,u=o>0?e.width:n.size.width,c=o>0?e.height:n.size.height;try{l.queue.copyExternalImageToTexture({source:e,flipY:s},{texture:t,mipLevel:o,origin:{x:0,y:0,z:i},premultipliedAlpha:a},{width:u,height:c,depthOrArrayLayers:1})}catch(d){}}_getPassUtils(){let e=this._passUtils;return e===null&&(this._passUtils=e=new I$(this.backend.device)),e}_generateMipmaps(e,t,n=0,i=null){this._getPassUtils().generateMipmaps(e,t,n,i)}_flipY(e,t,n=0){this._getPassUtils().flipY(e,t,n)}_copyBufferToTexture(e,t,n,i,s,a=0,o=0){const l=this.backend.device,u=e.data,c=this._getBytesPerTexel(n.format),d=e.width*c;l.queue.writeTexture({texture:t,mipLevel:o,origin:{x:0,y:0,z:i}},u,{offset:e.width*e.height*c*a,bytesPerRow:d},{width:e.width,height:e.height,depthOrArrayLayers:1}),s===!0&&this._flipY(t,n,i)}_copyCompressedBufferToTexture(e,t,n){const i=this.backend.device,s=this._getBlockData(n.format),a=n.size.depthOrArrayLayers>1;for(let o=0;o<e.length;o++){const l=e[o],u=l.width,c=l.height,d=a?n.size.depthOrArrayLayers:1,f=Math.ceil(u/s.width)*s.byteLength,h=f*Math.ceil(c/s.height);for(let p=0;p<d;p++)i.queue.writeTexture({texture:t,mipLevel:o,origin:{x:0,y:0,z:p}},l.data,{offset:p*h,bytesPerRow:f,rowsPerImage:Math.ceil(c/s.height)},{width:Math.ceil(u/s.width)*s.width,height:Math.ceil(c/s.height)*s.height,depthOrArrayLayers:1})}}_getBlockData(e){if(e===ye.BC1RGBAUnorm||e===ye.BC1RGBAUnormSRGB)return{byteLength:8,width:4,height:4};if(e===ye.BC2RGBAUnorm||e===ye.BC2RGBAUnormSRGB)return{byteLength:16,width:4,height:4};if(e===ye.BC3RGBAUnorm||e===ye.BC3RGBAUnormSRGB)return{byteLength:16,width:4,height:4};if(e===ye.BC4RUnorm||e===ye.BC4RSnorm)return{byteLength:8,width:4,height:4};if(e===ye.BC5RGUnorm||e===ye.BC5RGSnorm)return{byteLength:16,width:4,height:4};if(e===ye.BC6HRGBUFloat||e===ye.BC6HRGBFloat)return{byteLength:16,width:4,height:4};if(e===ye.BC7RGBAUnorm||e===ye.BC7RGBAUnormSRGB)return{byteLength:16,width:4,height:4};if(e===ye.ETC2RGB8Unorm||e===ye.ETC2RGB8UnormSRGB)return{byteLength:8,width:4,height:4};if(e===ye.ETC2RGB8A1Unorm||e===ye.ETC2RGB8A1UnormSRGB)return{byteLength:8,width:4,height:4};if(e===ye.ETC2RGBA8Unorm||e===ye.ETC2RGBA8UnormSRGB)return{byteLength:16,width:4,height:4};if(e===ye.EACR11Unorm)return{byteLength:8,width:4,height:4};if(e===ye.EACR11Snorm)return{byteLength:8,width:4,height:4};if(e===ye.EACRG11Unorm)return{byteLength:16,width:4,height:4};if(e===ye.EACRG11Snorm)return{byteLength:16,width:4,height:4};if(e===ye.ASTC4x4Unorm||e===ye.ASTC4x4UnormSRGB)return{byteLength:16,width:4,height:4};if(e===ye.ASTC5x4Unorm||e===ye.ASTC5x4UnormSRGB)return{byteLength:16,width:5,height:4};if(e===ye.ASTC5x5Unorm||e===ye.ASTC5x5UnormSRGB)return{byteLength:16,width:5,height:5};if(e===ye.ASTC6x5Unorm||e===ye.ASTC6x5UnormSRGB)return{byteLength:16,width:6,height:5};if(e===ye.ASTC6x6Unorm||e===ye.ASTC6x6UnormSRGB)return{byteLength:16,width:6,height:6};if(e===ye.ASTC8x5Unorm||e===ye.ASTC8x5UnormSRGB)return{byteLength:16,width:8,height:5};if(e===ye.ASTC8x6Unorm||e===ye.ASTC8x6UnormSRGB)return{byteLength:16,width:8,height:6};if(e===ye.ASTC8x8Unorm||e===ye.ASTC8x8UnormSRGB)return{byteLength:16,width:8,height:8};if(e===ye.ASTC10x5Unorm||e===ye.ASTC10x5UnormSRGB)return{byteLength:16,width:10,height:5};if(e===ye.ASTC10x6Unorm||e===ye.ASTC10x6UnormSRGB)return{byteLength:16,width:10,height:6};if(e===ye.ASTC10x8Unorm||e===ye.ASTC10x8UnormSRGB)return{byteLength:16,width:10,height:8};if(e===ye.ASTC10x10Unorm||e===ye.ASTC10x10UnormSRGB)return{byteLength:16,width:10,height:10};if(e===ye.ASTC12x10Unorm||e===ye.ASTC12x10UnormSRGB)return{byteLength:16,width:12,height:10};if(e===ye.ASTC12x12Unorm||e===ye.ASTC12x12UnormSRGB)return{byteLength:16,width:12,height:12}}_convertAddressMode(e){let t=fM.ClampToEdge;return e===Zu?t=fM.Repeat:e===ud&&(t=fM.MirrorRepeat),t}_convertFilterMode(e){let t=Mg.Linear;return(e===Cs||e===Bm||e===wc)&&(t=Mg.Nearest),t}_getBytesPerTexel(e){if(e===ye.R8Unorm||e===ye.R8Snorm||e===ye.R8Uint||e===ye.R8Sint)return 1;if(e===ye.R16Uint||e===ye.R16Sint||e===ye.R16Float||e===ye.RG8Unorm||e===ye.RG8Snorm||e===ye.RG8Uint||e===ye.RG8Sint)return 2;if(e===ye.R32Uint||e===ye.R32Sint||e===ye.R32Float||e===ye.RG16Uint||e===ye.RG16Sint||e===ye.RG16Float||e===ye.RGBA8Unorm||e===ye.RGBA8UnormSRGB||e===ye.RGBA8Snorm||e===ye.RGBA8Uint||e===ye.RGBA8Sint||e===ye.BGRA8Unorm||e===ye.BGRA8UnormSRGB||e===ye.RGB9E5UFloat||e===ye.RGB10A2Unorm||e===ye.RG11B10UFloat||e===ye.Depth32Float||e===ye.Depth24Plus||e===ye.Depth24PlusStencil8||e===ye.Depth32FloatStencil8)return 4;if(e===ye.RG32Uint||e===ye.RG32Sint||e===ye.RG32Float||e===ye.RGBA16Uint||e===ye.RGBA16Sint||e===ye.RGBA16Float)return 8;if(e===ye.RGBA32Uint||e===ye.RGBA32Sint||e===ye.RGBA32Float)return 16}_getTypedArrayType(e){if(e===ye.R8Uint)return Uint8Array;if(e===ye.R8Sint)return Int8Array;if(e===ye.R8Unorm)return Uint8Array;if(e===ye.R8Snorm)return Int8Array;if(e===ye.RG8Uint)return Uint8Array;if(e===ye.RG8Sint)return Int8Array;if(e===ye.RG8Unorm)return Uint8Array;if(e===ye.RG8Snorm)return Int8Array;if(e===ye.RGBA8Uint)return Uint8Array;if(e===ye.RGBA8Sint)return Int8Array;if(e===ye.RGBA8Unorm||e===ye.RGBA8UnormSRGB)return Uint8Array;if(e===ye.RGBA8Snorm)return Int8Array;if(e===ye.R16Uint)return Uint16Array;if(e===ye.R16Sint)return Int16Array;if(e===ye.RG16Uint)return Uint16Array;if(e===ye.RG16Sint)return Int16Array;if(e===ye.RGBA16Uint)return Uint16Array;if(e===ye.RGBA16Sint)return Int16Array;if(e===ye.R16Float||e===ye.RG16Float||e===ye.RGBA16Float)return Uint16Array;if(e===ye.R32Uint)return Uint32Array;if(e===ye.R32Sint)return Int32Array;if(e===ye.R32Float)return Float32Array;if(e===ye.RG32Uint)return Uint32Array;if(e===ye.RG32Sint)return Int32Array;if(e===ye.RG32Float)return Float32Array;if(e===ye.RGBA32Uint)return Uint32Array;if(e===ye.RGBA32Sint)return Int32Array;if(e===ye.RGBA32Float)return Float32Array;if(e===ye.BGRA8Unorm||e===ye.BGRA8UnormSRGB)return Uint8Array;if(e===ye.RGB10A2Unorm||e===ye.RGB9E5UFloat||e===ye.RG11B10UFloat)return Uint32Array;if(e===ye.Depth32Float)return Float32Array;if(e===ye.Depth24Plus||e===ye.Depth24PlusStencil8)return Uint32Array;if(e===ye.Depth32FloatStencil8)return Float32Array}_getDimension(e){let t;return e.is3DTexture||e.isData3DTexture?t=GN.ThreeD:t=GN.TwoD,t}}function gM(r,e=null){const t=r.format,n=r.type,i=r.colorSpace,s=$r.getTransfer(i);let a;if(r.isCompressedTexture===!0||r.isCompressedArrayTexture===!0)switch(t){case Kd:case qd:a=s===$n?ye.BC1RGBAUnormSRGB:ye.BC1RGBAUnorm;break;case _d:a=s===$n?ye.BC2RGBAUnormSRGB:ye.BC2RGBAUnorm;break;case $d:a=s===$n?ye.BC3RGBAUnormSRGB:ye.BC3RGBAUnorm;break;case gp:a=ye.BC4RUnorm;break;case nf:a=ye.BC4RSnorm;break;case rf:a=ye.BC5RGUnorm;break;case vp:a=ye.BC5RGSnorm;break;case nh:a=s===$n?ye.BC7RGBAUnormSRGB:ye.BC7RGBAUnorm;break;case Im:case tp:a=s===$n?ye.ETC2RGB8UnormSRGB:ye.ETC2RGB8Unorm;break;case np:a=s===$n?ye.ETC2RGBA8UnormSRGB:ye.ETC2RGBA8Unorm;break;case ef:a=ye.EACR11Unorm;break;case rp:a=ye.EACR11Snorm;break;case _f:a=ye.EACRG11Unorm;break;case ip:a=ye.EACRG11Snorm;break;case $f:a=s===$n?ye.ASTC4x4UnormSRGB:ye.ASTC4x4Unorm;break;case sp:a=s===$n?ye.ASTC5x4UnormSRGB:ye.ASTC5x4Unorm;break;case eh:a=s===$n?ye.ASTC5x5UnormSRGB:ye.ASTC5x5Unorm;break;case ap:a=s===$n?ye.ASTC6x5UnormSRGB:ye.ASTC6x5Unorm;break;case th:a=s===$n?ye.ASTC6x6UnormSRGB:ye.ASTC6x6Unorm;break;case Nm:a=s===$n?ye.ASTC8x5UnormSRGB:ye.ASTC8x5Unorm;break;case tf:a=s===$n?ye.ASTC8x6UnormSRGB:ye.ASTC8x6Unorm;break;case op:a=s===$n?ye.ASTC8x8UnormSRGB:ye.ASTC8x8Unorm;break;case lp:a=s===$n?ye.ASTC10x5UnormSRGB:ye.ASTC10x5Unorm;break;case up:a=s===$n?ye.ASTC10x6UnormSRGB:ye.ASTC10x6Unorm;break;case cp:a=s===$n?ye.ASTC10x8UnormSRGB:ye.ASTC10x8Unorm;break;case dp:a=s===$n?ye.ASTC10x10UnormSRGB:ye.ASTC10x10Unorm;break;case fp:a=s===$n?ye.ASTC12x10UnormSRGB:ye.ASTC12x10Unorm;break;case hp:a=s===$n?ye.ASTC12x12UnormSRGB:ye.ASTC12x12Unorm;break;case ma:a=s===$n?ye.RGBA8UnormSRGB:ye.RGBA8Unorm;break;default:rt("WebGPURenderer: Unsupported texture format.",t)}else switch(t){case ma:switch(n){case Jf:a=ye.RGBA8Snorm;break;case cd:a=ye.RGBA16Sint;break;case Yu:a=ye.RGBA16Uint;break;case Ls:a=ye.RGBA32Uint;break;case Do:a=ye.RGBA32Sint;break;case fa:a=s===$n?ye.RGBA8UnormSRGB:ye.RGBA8Unorm;break;case pa:a=ye.RGBA16Float;break;case ha:a=ye.RGBA32Float;break;default:rt("WebGPURenderer: Unsupported texture type with RGBAFormat.",n)}break;case Sm:switch(n){case gv:a=ye.RGB9E5UFloat;break;case vv:a=ye.RG11B10UFloat;break;default:rt("WebGPURenderer: Unsupported texture type with RGBFormat.",n)}break;case _h:switch(n){case Jf:a=ye.R8Snorm;break;case cd:a=ye.R16Sint;break;case Yu:a=ye.R16Uint;break;case Ls:a=ye.R32Uint;break;case Do:a=ye.R32Sint;break;case fa:a=ye.R8Unorm;break;case pa:a=ye.R16Float;break;case ha:a=ye.R32Float;break;default:rt("WebGPURenderer: Unsupported texture type with RedFormat.",n)}break;case Al:switch(n){case Jf:a=ye.RG8Snorm;break;case cd:a=ye.RG16Sint;break;case Yu:a=ye.RG16Uint;break;case Ls:a=ye.RG32Uint;break;case Do:a=ye.RG32Sint;break;case fa:a=ye.RG8Unorm;break;case pa:a=ye.RG16Float;break;case ha:a=ye.RG32Float;break;default:rt("WebGPURenderer: Unsupported texture type with RGFormat.",n)}break;case jo:switch(n){case Yu:a=ye.Depth16Unorm;break;case Ls:a=ye.Depth24Plus;break;case ha:a=ye.Depth32Float;break;default:rt("WebGPURenderer: Unsupported texture type with DepthFormat.",n)}break;case vl:switch(n){case Ll:a=ye.Depth24PlusStencil8;break;case ha:e&&e.features.has(mM.Depth32FloatStencil8)===!1&&rt('WebGPURenderer: Depth textures with DepthStencilFormat + FloatType can only be used with the "depth32float-stencil8" GPU feature.'),a=ye.Depth32FloatStencil8;break;default:rt("WebGPURenderer: Unsupported texture type with DepthStencilFormat.",n)}break;case Kf:switch(n){case Do:a=ye.R32Sint;break;case Ls:a=ye.R32Uint;break;default:rt("WebGPURenderer: Unsupported texture type with RedIntegerFormat.",n)}break;case $h:switch(n){case Do:a=ye.RG32Sint;break;case Ls:a=ye.RG32Uint;break;default:rt("WebGPURenderer: Unsupported texture type with RGIntegerFormat.",n)}break;case qf:switch(n){case Do:a=ye.RGBA32Sint;break;case Ls:a=ye.RGBA32Uint;break;default:rt("WebGPURenderer: Unsupported texture type with RGBAIntegerFormat.",n)}break;default:rt("WebGPURenderer: Unsupported texture format.",t)}return a}const L$=/^[fn]*\s*([a-z_0-9]+)?\s*\(([\s\S]*?)\)\s*[\-\>]*\s*([a-z_0-9]+(?:<[\s\S]+?>)?)/i,O$=/([a-z_0-9]+)\s*:\s*([a-z_0-9]+(?:<[\s\S]+?>)?)/ig,QN={f32:"float",i32:"int",u32:"uint",bool:"bool","vec2<f32>":"vec2","vec2<i32>":"ivec2","vec2<u32>":"uvec2","vec2<bool>":"bvec2",vec2f:"vec2",vec2i:"ivec2",vec2u:"uvec2",vec2b:"bvec2","vec3<f32>":"vec3","vec3<i32>":"ivec3","vec3<u32>":"uvec3","vec3<bool>":"bvec3",vec3f:"vec3",vec3i:"ivec3",vec3u:"uvec3",vec3b:"bvec3","vec4<f32>":"vec4","vec4<i32>":"ivec4","vec4<u32>":"uvec4","vec4<bool>":"bvec4",vec4f:"vec4",vec4i:"ivec4",vec4u:"uvec4",vec4b:"bvec4","mat2x2<f32>":"mat2",mat2x2f:"mat2","mat3x3<f32>":"mat3",mat3x3f:"mat3","mat4x4<f32>":"mat4",mat4x4f:"mat4",sampler:"sampler",texture_1d:"texture",texture_2d:"texture",texture_2d_array:"texture",texture_multisampled_2d:"cubeTexture",texture_depth_2d:"depthTexture",texture_depth_2d_array:"depthTexture",texture_depth_multisampled_2d:"depthTexture",texture_depth_cube:"depthTexture",texture_depth_cube_array:"depthTexture",texture_3d:"texture3D",texture_cube:"cubeTexture",texture_cube_array:"cubeTexture",texture_storage_1d:"storageTexture",texture_storage_2d:"storageTexture",texture_storage_2d_array:"storageTexture",texture_storage_3d:"storageTexture"},z$=r=>{r=r.trim();const e=r.match(L$);if(e!==null&&e.length===4){const t=e[2],n=[];let i=null;for(;(i=O$.exec(t))!==null;)n.push({name:i[1],type:i[2]});const s=[];for(let c=0;c<n.length;c++){const{name:d,type:f}=n[c];let h=f;h.startsWith("ptr")?h="pointer":(h.startsWith("texture")&&(h=f.split("<")[0]),h=QN[h]),s.push(new eM(h,d))}const a=r.substring(e[0].length),o=e[3]||"void",l=e[1]!==void 0?e[1]:"";return{type:QN[o]||o,inputs:s,name:l,inputsCode:t,blockCode:a,outputType:o}}else throw new Error("FunctionNode: Function is not a WGSL code.")};class H$ extends rM{constructor(e){const{type:t,inputs:n,name:i,inputsCode:s,blockCode:a,outputType:o}=z$(e);super(t,n,i),this.inputsCode=s,this.blockCode=a,this.outputType=o}getCode(e=this.name){const t=this.outputType!=="void"?"-> "+this.outputType:"";return`fn ${e} ( ${this.inputsCode.trim()} ) ${t}`+this.blockCode}}class U$ extends pN{parseFunction(e){return new H$(e)}}const k$={[El.READ_ONLY]:"read",[El.WRITE_ONLY]:"write",[El.READ_WRITE]:"read_write"},ZN={[Zu]:"repeat",[So]:"clamp",[ud]:"mirror"},xw={vertex:Bg.VERTEX,fragment:Bg.FRAGMENT,compute:Bg.COMPUTE},YN={instance:!0,swizzleAssign:!1,storageBuffer:!0},V$={"^^":"tsl_xor"},j$={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>"},JN={},Jx={tsl_xor:new sl("fn tsl_xor( a : bool, b : bool ) -> bool { return ( a || b ) && !( a && b ); }"),mod_float:new sl("fn tsl_mod_float( x : f32, y : f32 ) -> f32 { return x - y * floor( x / y ); }"),mod_vec2:new sl("fn tsl_mod_vec2( x : vec2f, y : vec2f ) -> vec2f { return x - y * floor( x / y ); }"),mod_vec3:new sl("fn tsl_mod_vec3( x : vec3f, y : vec3f ) -> vec3f { return x - y * floor( x / y ); }"),mod_vec4:new sl("fn tsl_mod_vec4( x : vec4f, y : vec4f ) -> vec4f { return x - y * floor( x / y ); }"),equals_bool:new sl("fn tsl_equals_bool( a : bool, b : bool ) -> bool { return a == b; }"),equals_bvec2:new sl("fn tsl_equals_bvec2( a : vec2f, b : vec2f ) -> vec2<bool> { return vec2<bool>( a.x == b.x, a.y == b.y ); }"),equals_bvec3:new sl("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 sl("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 sl("fn tsl_repeatWrapping_float( coord: f32 ) -> f32 { return fract( coord ); }"),mirrorWrapping_float:new sl("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 sl("fn tsl_clampWrapping_float( coord: f32 ) -> f32 { return clamp( coord, 0.0, 1.0 ); }"),biquadraticTexture:new sl(`
fn tsl_biquadraticTexture( map : texture_2d<f32>, coord : vec2f, iRes : vec2u, level : u32 ) -> vec4f {

	let res = vec2f( iRes );

	let uvScaled = coord * res;
	let uvWrapping = ( ( uvScaled % res ) + res ) % res;

	// https://www.shadertoy.com/view/WtyXRy

	let uv = uvWrapping - 0.5;
	let iuv = floor( uv );
	let f = fract( uv );

	let rg1 = textureLoad( map, vec2u( iuv + vec2( 0.5, 0.5 ) ) % iRes, level );
	let rg2 = textureLoad( map, vec2u( iuv + vec2( 1.5, 0.5 ) ) % iRes, level );
	let rg3 = textureLoad( map, vec2u( iuv + vec2( 0.5, 1.5 ) ) % iRes, level );
	let rg4 = textureLoad( map, vec2u( iuv + vec2( 1.5, 1.5 ) ) % iRes, level );

	return mix( mix( rg1, rg2, f.x ), mix( rg3, rg4, f.x ), f.y );

}
`)},X$={dFdx:"dpdx",dFdy:"- dpdy",mod_float:"tsl_mod_float",mod_vec2:"tsl_mod_vec2",mod_vec3:"tsl_mod_vec3",mod_vec4:"tsl_mod_vec4",equals_bool:"tsl_equals_bool",equals_bvec2:"tsl_equals_bvec2",equals_bvec3:"tsl_equals_bvec3",equals_bvec4:"tsl_equals_bvec4",inversesqrt:"inverseSqrt",bitcast:"bitcast<f32>",floatpack_snorm_2x16:"pack2x16snorm",floatpack_unorm_2x16:"pack2x16unorm",floatpack_float16_2x16:"pack2x16float",floatunpack_snorm_2x16:"unpack2x16snorm",floatunpack_unorm_2x16:"unpack2x16unorm",floatunpack_float16_2x16:"unpack2x16float"};let KN="";(typeof navigator!="undefined"&&/Firefox|Deno/g.test(navigator.userAgent))!==!0&&(KN+=`diagnostic( off, derivative_uniformity );
`);class G$ extends fN{constructor(e,t){super(e,t,new U$),this.uniformGroups={},this.builtins={},this.directives={},this.scopedArrays=new Map}_generateTextureSample(e,t,n,i,s,a=this.shaderStage){return a==="fragment"?i?s?`textureSample( ${t}, ${t}_sampler, ${n}, ${i}, ${s} )`:`textureSample( ${t}, ${t}_sampler, ${n}, ${i} )`:s?`textureSample( ${t}, ${t}_sampler, ${n}, ${s} )`:`textureSample( ${t}, ${t}_sampler, ${n} )`:this.generateTextureSampleLevel(e,t,n,"0",i)}generateTextureSampleLevel(e,t,n,i,s,a){return this.isUnfilterable(e)===!1?a?`textureSampleLevel( ${t}, ${t}_sampler, ${n}, ${i}, ${a} )`:`textureSampleLevel( ${t}, ${t}_sampler, ${n}, ${i} )`:this.isFilteredTexture(e)?this.generateFilteredTexture(e,t,n,a,i):this.generateTextureLod(e,t,n,s,a,i)}generateWrapFunction(e){const t=`tsl_coord_${ZN[e.wrapS]}S_${ZN[e.wrapT]}_${e.is3DTexture||e.isData3DTexture?"3d":"2d"}T`;let n=JN[t];if(n===void 0){const i=[],s=e.is3DTexture||e.isData3DTexture?"vec3f":"vec2f";let a=`fn ${t}( coord : ${s} ) -> ${s} {

	return ${s}(
`;const o=(l,u)=>{l===Zu?(i.push(Jx.repeatWrapping_float),a+=`		tsl_repeatWrapping_float( coord.${u} )`):l===So?(i.push(Jx.clampWrapping_float),a+=`		tsl_clampWrapping_float( coord.${u} )`):l===ud?(i.push(Jx.mirrorWrapping_float),a+=`		tsl_mirrorWrapping_float( coord.${u} )`):(a+=`		coord.${u}`,ze(`WebGPURenderer: Unsupported texture wrap type "${l}" for vertex shader.`))};o(e.wrapS,"x"),a+=`,
`,o(e.wrapT,"y"),(e.is3DTexture||e.isData3DTexture)&&(a+=`,
`,o(e.wrapR,"z")),a+=`
	);

}
`,JN[t]=n=new sl(a,i)}return n.build(this),t}generateArrayDeclaration(e,t){return`array< ${this.getType(e)}, ${t} >`}generateTextureDimension(e,t,n){const i=this.getDataFromNode(e,this.shaderStage,this.globalCache);i.dimensionsSnippet===void 0&&(i.dimensionsSnippet={});let s=i.dimensionsSnippet[n];if(i.dimensionsSnippet[n]===void 0){let a,o;const{primarySamples:l}=this.renderer.backend.utils.getTextureSampleData(e),u=l>1;e.is3DTexture||e.isData3DTexture?o="vec3<u32>":o="vec2<u32>",u||e.isStorageTexture?a=t:a=`${t}${n?`, u32( ${n} )`:""}`,s=new gE(new yE(`textureDimensions( ${a} )`,o)),i.dimensionsSnippet[n]=s,(e.isArrayTexture||e.isDataArrayTexture||e.is3DTexture||e.isData3DTexture)&&(i.arrayLayerCount=new gE(new yE(`textureNumLayers(${t})`,"u32"))),e.isTextureCube&&(i.cubeFaceCount=new gE(new yE("6u","u32")))}return s.build(this)}generateFilteredTexture(e,t,n,i,s="0u"){this._include("biquadraticTexture");const a=this.generateWrapFunction(e),o=this.generateTextureDimension(e,t,s);return i&&(n=`${n} + vec2<f32>(${i}) / ${o}`),`tsl_biquadraticTexture( ${t}, ${a}( ${n} ), ${o}, u32( ${s} ) )`}generateTextureLod(e,t,n,i,s,a="0u"){const o=this.generateWrapFunction(e),l=this.generateTextureDimension(e,t,a),u=e.is3DTexture||e.isData3DTexture?"vec3":"vec2";s&&(n=`${n} + ${u}<f32>(${s}) / ${u}<f32>( ${l} )`);const c=`${u}<u32>( ${o}( ${n} ) * ${u}<f32>( ${l} ) )`;return this.generateTextureLoad(e,t,c,a,i,null)}generateTextureLoad(e,t,n,i,s,a){i===null&&(i="0u"),a&&(n=`${n} + ${a}`);let o;return s?o=`textureLoad( ${t}, ${n}, ${s}, u32( ${i} ) )`:(o=`textureLoad( ${t}, ${n}, u32( ${i} ) )`,this.renderer.backend.compatibilityMode&&e.isDepthTexture&&(o+=".x")),o}generateTextureStore(e,t,n,i,s){let a;return i?a=`textureStore( ${t}, ${n}, ${i}, ${s} )`:a=`textureStore( ${t}, ${n}, ${s} )`,a}isSampleCompare(e){return e.isDepthTexture===!0&&e.compareFunction!==null}isUnfilterable(e){return this.getComponentTypeFromTexture(e)!=="float"||!this.isAvailable("float32Filterable")&&e.isDataTexture===!0&&e.type===ha||this.isSampleCompare(e)===!1&&e.minFilter===Cs&&e.magFilter===Cs||this.renderer.backend.utils.getTextureSampleData(e).primarySamples>1}generateTexture(e,t,n,i,s,a=this.shaderStage){let o=null;return this.isUnfilterable(e)?o=this.generateTextureLod(e,t,n,i,s,"0",a):o=this._generateTextureSample(e,t,n,i,s,a),o}generateTextureGrad(e,t,n,i,s,a,o=this.shaderStage){if(o==="fragment")return a?`textureSampleGrad( ${t}, ${t}_sampler, ${n},  ${i[0]}, ${i[1]}, ${a} )`:`textureSampleGrad( ${t}, ${t}_sampler, ${n},  ${i[0]}, ${i[1]} )`;rt(`WebGPURenderer: THREE.TextureNode.gradient() does not support ${o} shader.`)}generateTextureCompare(e,t,n,i,s,a,o=this.shaderStage){if(o==="fragment")return e.isDepthTexture===!0&&e.isArrayTexture===!0?a?`textureSampleCompare( ${t}, ${t}_sampler, ${n}, ${s}, ${i}, ${a} )`:`textureSampleCompare( ${t}, ${t}_sampler, ${n}, ${s}, ${i} )`:a?`textureSampleCompare( ${t}, ${t}_sampler, ${n}, ${i}, ${a} )`:`textureSampleCompare( ${t}, ${t}_sampler, ${n}, ${i} )`;rt(`WebGPURenderer: THREE.DepthTexture.compareFunction() does not support ${o} shader.`)}generateTextureLevel(e,t,n,i,s,a){return this.isUnfilterable(e)===!1?a?`textureSampleLevel( ${t}, ${t}_sampler, ${n}, ${i}, ${a} )`:`textureSampleLevel( ${t}, ${t}_sampler, ${n}, ${i} )`:this.isFilteredTexture(e)?this.generateFilteredTexture(e,t,n,a,i):this.generateTextureLod(e,t,n,s,a,i)}generateTextureBias(e,t,n,i,s,a,o=this.shaderStage){if(o==="fragment")return a?`textureSampleBias( ${t}, ${t}_sampler, ${n}, ${i}, ${a} )`:`textureSampleBias( ${t}, ${t}_sampler, ${n}, ${i} )`;rt(`WebGPURenderer: THREE.TextureNode.biasNode does not support ${o} shader.`)}getPropertyName(e,t=this.shaderStage){if(e.isNodeVarying===!0&&e.needsInterpolation===!0){if(t==="vertex")return`varyings.${e.name}`}else if(e.isNodeUniform===!0){const n=e.name,i=e.type;return i==="texture"||i==="cubeTexture"||i==="cubeDepthTexture"||i==="storageTexture"||i==="texture3D"?n:i==="buffer"||i==="storageBuffer"||i==="indirectStorageBuffer"?this.isCustomStruct(e)?n:n+".value":e.groupNode.name+"."+n}return super.getPropertyName(e)}getOutputStructName(){return"output"}getFunctionOperator(e){const t=V$[e];return t!==void 0?(this._include(t),t):null}getNodeAccess(e,t){return t!=="compute"?e.isAtomic===!0?(ze("WebGPURenderer: Atomic operations are only supported in compute shaders."),El.READ_WRITE):El.READ_ONLY:e.access}getStorageAccess(e,t){return k$[this.getNodeAccess(e,t)]}getUniformFromNode(e,t,n,i=null){const s=super.getUniformFromNode(e,t,n,i),a=this.getDataFromNode(e,n,this.globalCache);if(a.uniformGPU===void 0){let o;const l=e.groupNode,u=l.name,c=this.getBindGroupArray(u,n);if(t==="texture"||t==="cubeTexture"||t==="cubeDepthTexture"||t==="storageTexture"||t==="texture3D"){let d=null;const f=this.getNodeAccess(e,n);if(t==="texture"||t==="storageTexture"?e.value.is3DTexture===!0?d=new lM(s.name,s.node,l,f):d=new mw(s.name,s.node,l,f):t==="cubeTexture"||t==="cubeDepthTexture"?d=new SN(s.name,s.node,l,f):t==="texture3D"&&(d=new lM(s.name,s.node,l,f)),d.store=e.isStorageTextureNode===!0,d.mipLevel=d.store?e.mipLevel:0,d.setVisibility(xw[n]),this.isUnfilterable(e.value)===!1&&d.store===!1){const h=new M$(`${s.name}_sampler`,s.node,l);h.setVisibility(xw[n]),c.push(h,d),o=[h,d]}else c.push(d),o=[d]}else if(t==="buffer"||t==="storageBuffer"||t==="indirectStorageBuffer"){const d=this.getSharedDataFromNode(e);let f=d.buffer;if(f===void 0){const h=t==="buffer"?PN:T$;f=new h(e,l),d.buffer=f}f.setVisibility(f.getVisibility()|xw[n]),c.push(f),o=f,s.name=i||"NodeBuffer_"+s.id}else{const d=this.uniformGroups[n]||(this.uniformGroups[n]={});let f=d[u];f===void 0&&(f=new BN(u,l),f.setVisibility(xw[n]),d[u]=f,c.push(f)),o=this.getNodeUniform(s,t),f.addUniform(o)}a.uniformGPU=o}return s}getBuiltin(e,t,n,i=this.shaderStage){const s=this.builtins[i]||(this.builtins[i]=new Map);return s.has(e)===!1&&s.set(e,{name:e,property:t,type:n}),t}hasBuiltin(e,t=this.shaderStage){return this.builtins[t]!==void 0&&this.builtins[t].has(e)}getVertexIndex(){return this.shaderStage==="vertex"?this.getBuiltin("vertex_index","vertexIndex","u32","attribute"):"vertexIndex"}buildFunctionCode(e){const t=e.layout,n=this.flowShaderNode(e),i=[];for(const a of t.inputs)i.push(a.name+" : "+this.getType(a.type));let s=`fn ${t.name}( ${i.join(", ")} ) -> ${this.getType(t.type)} {
${n.vars}
${n.code}
`;return n.result&&(s+=`	return ${n.result};
`),s+=`
}
`,s}getInstanceIndex(){return this.shaderStage==="vertex"?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(n!==void 0)for(const i of n)t.push(`enable ${i};`);return t.join(`
`)}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(n!==void 0)for(const{name:i,property:s,type:a}of n.values())t.push(`@builtin( ${i} ) ${s} : ${a}`);return t.join(`,
	`)}getScopedArray(e,t,n,i){return this.scopedArrays.has(e)===!1&&this.scopedArrays.set(e,{name:e,scope:t,bufferType:n,bufferCount:i}),e}getScopedArrays(e){if(e!=="compute")return;const t=[];for(const{name:n,scope:i,bufferType:s,bufferCount:a}of this.scopedArrays.values()){const o=this.getType(s);t.push(`var<${i}> ${n}: array< ${o}, ${a} >;`)}return t.join(`
`)}getAttributes(e){const t=[];if(e==="compute"&&(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"))),e==="vertex"||e==="compute"){const n=this.getBuiltins("attribute");n&&t.push(n);const i=this.getAttributesArray();for(let s=0,a=i.length;s<a;s++){const o=i[s],l=o.name,u=this.getType(o.type);t.push(`@location( ${s} ) ${l} : ${u}`)}}return t.join(`,
	`)}getStructMembers(e){const t=[];for(const n of e.members){const i=e.output?"@location( "+n.index+" ) ":"";let s=this.getType(n.type);n.atomic&&(s="atomic< "+s+" >"),t.push(`	${i+n.name} : ${s}`)}return e.output&&t.push(`	${this.getBuiltins("output")}`),t.join(`,
`)}getStructs(e){let t="";const n=this.structs[e];if(n.length>0){const i=[];for(const s of n){let a=`struct ${s.name} {
`;a+=this.getStructMembers(s),a+=`
};`,i.push(a)}t=`
`+i.join(`

`)+`
`}return t}getVar(e,t,n=null){let i=`var ${t} : `;return n!==null?i+=this.generateArrayDeclaration(e,n):i+=this.getType(e),i}getVars(e){const t=[],n=this.vars[e];if(n!==void 0)for(const i of n)t.push(`	${this.getVar(i.type,i.name,i.count)};`);return`
${t.join(`
`)}
`}getVaryings(e){const t=[];if(e==="vertex"&&this.getBuiltin("position","Vertex","vec4<f32>","vertex"),e==="vertex"||e==="fragment"){const s=this.varyings,a=this.vars[e];for(let o=0;o<s.length;o++){const l=s[o];if(l.needsInterpolation){let u=`@location( ${o} )`;if(l.interpolationType){const c=l.interpolationSampling!==null?`, ${l.interpolationSampling} )`:" )";u+=` @interpolate( ${l.interpolationType}${c}`}else/^(int|uint|ivec|uvec)/.test(l.type)&&(u+=` @interpolate( ${this.renderer.backend.compatibilityMode?"flat, either":"flat"} )`);t.push(`${u} ${l.name} : ${this.getType(l.type)}`)}else e==="vertex"&&a.includes(l)===!1&&a.push(l)}}const n=this.getBuiltins(e);n&&t.push(n);const i=t.join(`,
	`);return e==="vertex"?this._getWGSLStruct("VaryingsStruct","	"+i):i}isCustomStruct(e){const t=e.value,n=e.node,i=(t.isBufferAttribute||t.isInstancedBufferAttribute)&&n.structTypeNode!==null,s=n.value&&n.value.array&&typeof n.value.itemSize=="number"&&n.value.array.length>n.value.itemSize;return i&&!s}getUniforms(e){const t=this.uniforms[e],n=[],i=[],s=[],a={};for(const l of t){const u=l.groupNode.name,c=this.bindingsIndexes[u];if(l.type==="texture"||l.type==="cubeTexture"||l.type==="cubeDepthTexture"||l.type==="storageTexture"||l.type==="texture3D"){const d=l.node.value;this.isUnfilterable(d)===!1&&l.node.isStorageTextureNode!==!0&&(this.isSampleCompare(d)?n.push(`@binding( ${c.binding++} ) @group( ${c.group} ) var ${l.name}_sampler : sampler_comparison;`):n.push(`@binding( ${c.binding++} ) @group( ${c.group} ) var ${l.name}_sampler : sampler;`));let f,h="";const{primarySamples:p}=this.renderer.backend.utils.getTextureSampleData(d);if(p>1&&(h="_multisampled"),d.isCubeTexture===!0&&d.isDepthTexture===!0)f="texture_depth_cube";else if(d.isCubeTexture===!0)f="texture_cube<f32>";else if(d.isDepthTexture===!0)this.renderer.backend.compatibilityMode&&d.compareFunction===null?f=`texture${h}_2d<f32>`:f=`texture_depth${h}_2d${d.isArrayTexture===!0?"_array":""}`;else if(l.node.isStorageTextureNode===!0){const x=gM(d),v=this.getStorageAccess(l.node,e),m=l.node.value.is3DTexture,C=l.node.value.isArrayTexture;f=`texture_storage_${m?"3d":`2d${C?"_array":""}`}<${x}, ${v}>`}else if(d.isArrayTexture===!0||d.isDataArrayTexture===!0||d.isCompressedArrayTexture===!0)f="texture_2d_array<f32>";else if(d.is3DTexture===!0||d.isData3DTexture===!0)f="texture_3d<f32>";else{const x=this.getComponentTypeFromTexture(d).charAt(0);f=`texture${h}_2d<${x}32>`}n.push(`@binding( ${c.binding++} ) @group( ${c.group} ) var ${l.name} : ${f};`)}else if(l.type==="buffer"||l.type==="storageBuffer"||l.type==="indirectStorageBuffer"){const d=l.node,f=this.getType(d.getNodeType(this)),h=d.bufferCount,p=h>0&&l.type==="buffer"?", "+h:"",x=d.isStorageBufferNode?`storage, ${this.getStorageAccess(d,e)}`:"uniform";if(this.isCustomStruct(l))i.push(`@binding( ${c.binding++} ) @group( ${c.group} ) var<${x}> ${l.name} : ${f};`);else{const m=`	value : array< ${d.isAtomic?`atomic<${f}>`:`${f}`}${p} >`;i.push(this._getWGSLStructBinding(l.name,m,x,c.binding++,c.group))}}else{const d=this.getType(this.getVectorType(l.type)),f=l.groupNode.name;(a[f]||(a[f]={index:c.binding++,id:c.group,snippets:[]})).snippets.push(`	${l.name} : ${d}`)}}for(const l in a){const u=a[l];s.push(this._getWGSLStructBinding(l,u.snippets.join(`,
`),"uniform",u.index,u.id))}return[...n,...i,...s].join(`
`)}buildCode(){const e=this.material!==null?{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

`;i+=this.flowCode[t];const s=this.flowNodes[t],a=s[s.length-1],o=a.outputNode,l=o!==void 0&&o.isOutputStructNode===!0;for(const u of s){const c=this.getFlowData(u),d=u.name;if(d&&(i.length>0&&(i+=`
`),i+=`	// flow -> ${d}
`),i+=`${c.code}
	`,u===a&&t!=="compute"){if(i+=`// result

	`,t==="vertex")i+=`varyings.Vertex = ${c.result};`;else if(t==="fragment")if(l)n.returnType=o.getNodeType(this),n.structs+="var<private> output : "+n.returnType+";",i+=`return ${c.result};`;else{let f="	@location(0) color: vec4<f32>";const h=this.getBuiltins("output");h&&(f+=`,
	`+h),n.returnType="OutputStruct",n.structs+=this._getWGSLStruct("OutputStruct",f),n.structs+=`
var<private> output : OutputStruct;`,i+=`output.color = ${c.result};

	return output;`}}}n.flow=i}if(this.shaderStage=null,this.material!==null)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 t!==null&&(n=this._getWGSLMethod(e+"_"+t)),n===void 0&&(n=this._getWGSLMethod(e)),n||e}getBitcastMethod(e){return`bitcast<${this.getType(e)}>`}getFloatPackingMethod(e){return this.getMethod(`floatpack_${e}_2x16`)}getFloatUnpackingMethod(e){return this.getMethod(`floatunpack_${e}_2x16`)}getTernary(e,t,n){return`select( ${n}, ${t}, ${e} )`}getType(e){return j$[e]||e}isAvailable(e){let t=YN[e];return t===void 0&&(e==="float32Filterable"?t=this.renderer.hasFeature("float32-filterable"):e==="clipDistance"&&(t=this.renderer.hasFeature("clip-distances")),YN[e]=t),t}_getWGSLMethod(e){return Jx[e]!==void 0&&this._include(e),X$[e]}_include(e){const t=Jx[e];return t.build(this),this.addInclude(t),t}_getWGSLVertexCode(e){return`${this.getSignature()}
// directives
${e.directives}

// structs
${e.structs}

// uniforms
${e.uniforms}

// varyings
${e.varyings}
var<private> varyings : VaryingsStruct;

// codes
${e.codes}

@vertex
fn main( ${e.attributes} ) -> VaryingsStruct {

	// vars
	${e.vars}

	// flow
	${e.flow}

	return varyings;

}
`}_getWGSLFragmentCode(e){return`${this.getSignature()}
// global
${KN}

// structs
${e.structs}

// uniforms
${e.uniforms}

// codes
${e.codes}

@fragment
fn main( ${e.varyings} ) -> ${e.returnType} {

	// vars
	${e.vars}

	// flow
	${e.flow}

}
`}_getWGSLComputeCode(e,t){const[n,i,s]=t;return`${this.getSignature()}
// directives
${e.directives}

// system
var<private> instanceIndex : u32;

// locals
${e.scopedArrays}

// structs
${e.structs}

// uniforms
${e.uniforms}

// codes
${e.codes}

@compute @workgroup_size( ${n}, ${i}, ${s} )
fn main( ${e.attributes} ) {

	// system
	instanceIndex = globalId.x
		+ globalId.y * ( ${n} * numWorkgroups.x )
		+ globalId.z * ( ${n} * numWorkgroups.x ) * ( ${i} * numWorkgroups.y );

	// vars
	${e.vars}

	// flow
	${e.flow}

}
`}_getWGSLStruct(e,t){return`
struct ${e} {
${t}
};`}_getWGSLStructBinding(e,t,n,i=0,s=0){const a=e+"Struct";return`${this._getWGSLStruct(a,t)}
@binding( ${i} ) @group( ${s} )
var<${n}> ${e} : ${a};`}}class W${constructor(e){this.backend=e}getCurrentDepthStencilFormat(e){let t;return e.depthTexture!==null?t=this.getTextureFormatGPU(e.depthTexture):e.depth&&e.stencil?t=ye.Depth24PlusStencil8:e.depth&&(t=ye.Depth24Plus),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 s=this.backend.renderer,a=s.getRenderTarget();t=a?a.samples:s.currentSamples}else e.renderTarget&&(t=e.renderTarget.samples);t=t||1;const n=t>1&&e.renderTarget!==null&&e.isDepthTexture!==!0&&e.isFramebufferTexture!==!0;return{samples:t,primarySamples:n?1:t,isMSAA:n}}getCurrentColorFormat(e){let t;return e.textures!==null?t=this.getTextureFormatGPU(e.textures[0]):t=this.getPreferredCanvasFormat(),t}getCurrentColorFormats(e){return e.textures!==null?e.textures.map(t=>this.getTextureFormatGPU(t)):[this.getPreferredCanvasFormat()]}getCurrentColorSpace(e){return e.textures!==null?e.textures[0].colorSpace:this.backend.renderer.outputColorSpace}getPrimitiveTopology(e,t){if(e.isPoints)return LA.PointList;if(e.isLineSegments||e.isMesh&&t.wireframe===!0)return LA.LineList;if(e.isLine)return LA.LineStrip;if(e.isMesh)return LA.TriangleList}getSampleCount(e){return e>=4?4:1}getSampleCountRenderContext(e){return e.textures!==null?this.getSampleCount(e.sampleCount):this.getSampleCount(this.backend.renderer.currentSamples)}getPreferredCanvasFormat(){const t=this.backend.parameters.outputType;if(t===void 0)return navigator.gpu.getPreferredCanvasFormat();if(t===fa)return ye.BGRA8Unorm;if(t===pa)return ye.RGBA16Float;throw new Error("Unsupported output buffer type.")}}const qN=new Map([[Int8Array,["sint8","snorm8"]],[Uint8Array,["uint8","unorm8"]],[Int16Array,["sint16","snorm16"]],[Uint16Array,["uint16","unorm16"]],[Int32Array,["sint32","snorm32"]],[Uint32Array,["uint32","unorm32"]],[Float32Array,["float32"]]]);typeof Float16Array!="undefined"&&qN.set(Float16Array,["float16"]);const Q$=new Map([[RS,["float16"]]]),Z$=new Map([[Int32Array,"sint32"],[Int16Array,"sint32"],[Uint32Array,"uint32"],[Uint16Array,"uint32"],[Float32Array,"float32"]]);class Y${constructor(e){this.backend=e}createAttribute(e,t){const n=this._getBufferAttribute(e),i=this.backend,s=i.get(n);let a=s.buffer;if(a===void 0){const o=i.device;let l=n.array;if(e.normalized===!1){if(l.constructor===Int16Array||l.constructor===Int8Array)l=new Int32Array(l);else if((l.constructor===Uint16Array||l.constructor===Uint8Array)&&(l=new Uint32Array(l),t&GPUBufferUsage.INDEX))for(let d=0;d<l.length;d++)l[d]===65535&&(l[d]=4294967295)}if(n.array=l,(n.isStorageBufferAttribute||n.isStorageInstancedBufferAttribute)&&n.itemSize===3){l=new l.constructor(n.count*4);for(let d=0;d<n.count;d++)l.set(n.array.subarray(d*3,d*3+3),d*4);n.itemSize=4,n.array=l,s._force3to4BytesAlignment=!0}const u=l.byteLength,c=u+(4-u%4)%4;a=o.createBuffer({label:n.name,size:c,usage:t,mappedAtCreation:!0}),new l.constructor(a.getMappedRange()).set(l),a.unmap(),s.buffer=a}}updateAttribute(e){const t=this._getBufferAttribute(e),n=this.backend,i=n.device,s=n.get(t),a=n.get(t).buffer;let o=t.array;if(s._force3to4BytesAlignment===!0){o=new o.constructor(t.count*4);for(let u=0;u<t.count;u++)o.set(t.array.subarray(u*3,u*3+3),u*4);t.array=o}const l=t.updateRanges;if(l.length===0)i.queue.writeBuffer(a,0,o,0);else{const u=Wi(o),c=u?1:o.BYTES_PER_ELEMENT;for(let d=0,f=l.length;d<f;d++){const h=l[d];let p,x;if(s._force3to4BytesAlignment===!0){const m=Math.floor(h.start/3),C=Math.ceil(h.count/3);p=m*4*c,x=C*4*c}else p=h.start*c,x=h.count*c;const v=p*(u?o.BYTES_PER_ELEMENT:1);i.queue.writeBuffer(a,v,o,p,x)}t.clearUpdateRanges()}}createShaderVertexBuffers(e){const t=e.getAttributes(),n=new Map;for(let i=0;i<t.length;i++){const s=t[i],a=s.array.BYTES_PER_ELEMENT,o=this._getBufferAttribute(s);let l=n.get(o);if(l===void 0){let d,f;s.isInterleavedBufferAttribute===!0?(d=s.data.stride*a,f=s.data.isInstancedInterleavedBuffer?Aw.Instance:Aw.Vertex):(d=s.itemSize*a,f=s.isInstancedBufferAttribute?Aw.Instance:Aw.Vertex),s.normalized===!1&&(s.array.constructor===Int16Array||s.array.constructor===Uint16Array)&&(d=4),l={arrayStride:d,attributes:[],stepMode:f},n.set(o,l)}const u=this._getVertexFormat(s),c=s.isInterleavedBufferAttribute===!0?s.offset*a:0;l.attributes.push({shaderLocation:i,offset:c,format:u})}return Array.from(n.values())}destroyAttribute(e){const t=this.backend;t.get(this._getBufferAttribute(e)).buffer.destroy(),t.delete(e)}getArrayBufferAsync(e){return Kr(this,null,function*(){const t=this.backend,n=t.device,s=t.get(this._getBufferAttribute(e)).buffer,a=s.size,o=n.createBuffer({label:`${e.name}_readback`,size:a,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ}),l=n.createCommandEncoder({label:`readback_encoder_${e.name}`});l.copyBufferToBuffer(s,0,o,0,a);const u=l.finish();n.queue.submit([u]),yield o.mapAsync(GPUMapMode.READ);const c=o.getMappedRange(),d=new e.array.constructor(c.slice(0));return o.unmap(),d.buffer})}_getVertexFormat(e){const{itemSize:t,normalized:n}=e,i=e.array.constructor,s=e.constructor;let a;if(t===1)a=Z$.get(i);else{const l=(Q$.get(s)||qN.get(i))[n?1:0];if(l){const u=i.BYTES_PER_ELEMENT*t,d=Math.floor((u+3)/4)*4/i.BYTES_PER_ELEMENT;if(d%1)throw new Error("THREE.WebGPUAttributeUtils: Bad vertex format item size.");a=`${l}x${d}`}}return a||rt("WebGPUAttributeUtils: Vertex format not supported yet."),a}_getBufferAttribute(e){return e.isInterleavedBufferAttribute&&(e=e.data),e}}class J${constructor(e){this.layoutGPU=e,this.usedTimes=0}}class K${constructor(e){this.backend=e,this._bindGroupLayoutCache=new Map}createBindingsLayout(e){const t=this.backend,n=t.device,i=t.get(e);if(i.layout)return i.layout.layoutGPU;const s=this._createLayoutEntries(e),a=JSON.stringify(s);let o=this._bindGroupLayoutCache.get(a);return o===void 0&&(o=new J$(n.createBindGroupLayout({entries:s})),this._bindGroupLayoutCache.set(a,o)),o.usedTimes++,i.layout=o,i.layoutKey=a,o.layoutGPU}createBindings(e,t,n,i=0){const{backend:s}=this,a=s.get(e),o=this.createBindingsLayout(e);let l;n>0&&(a.groups===void 0&&(a.groups=[],a.versions=[]),a.versions[n]===i&&(l=a.groups[n])),l===void 0&&(l=this.createBindGroup(e,o),n>0&&(a.groups[n]=l,a.versions[n]=i)),a.group=l}updateBinding(e){const t=this.backend,n=t.device,i=e.buffer,s=t.get(e).buffer,a=e.updateRanges;if(a.length===0)n.queue.writeBuffer(s,0,i,0);else{const o=Wi(i),l=o?1:i.BYTES_PER_ELEMENT;for(let u=0,c=a.length;u<c;u++){const d=a[u],f=d.start*l,h=d.count*l,p=f*(o?i.BYTES_PER_ELEMENT:1);n.queue.writeBuffer(s,p,i,f,h)}e.clearUpdateRanges()}}createBindGroupIndex(e,t){const i=this.backend.device,s=GPUBufferUsage.UNIFORM|GPUBufferUsage.COPY_DST,a=e[0],o=i.createBuffer({label:"bindingCameraIndex_"+a,size:16,usage:s});i.queue.writeBuffer(o,0,e,0);const l=[{binding:0,resource:{buffer:o}}];return i.createBindGroup({label:"bindGroupCameraIndex_"+a,layout:t,entries:l})}createBindGroup(e,t){const n=this.backend,i=n.device;let s=0;const a=[];for(const o of e.bindings){if(o.isUniformBuffer){const l=n.get(o);if(l.buffer===void 0){const u=o.byteLength,c=GPUBufferUsage.UNIFORM|GPUBufferUsage.COPY_DST,d=[];o.visibility&Bg.VERTEX&&d.push("vertex"),o.visibility&Bg.FRAGMENT&&d.push("fragment"),o.visibility&Bg.COMPUTE&&d.push("compute");const f=`(${d.join(",")})`,h=i.createBuffer({label:`bindingBuffer${o.id}_${o.name}_${f}`,size:u,usage:c});l.buffer=h}a.push({binding:s,resource:{buffer:l.buffer}})}else if(o.isStorageBuffer){const l=n.get(o);if(l.buffer===void 0){const u=o.attribute;l.buffer=n.get(u).buffer}a.push({binding:s,resource:{buffer:l.buffer}})}else if(o.isSampledTexture){const l=n.get(o.texture);let u;if(l.externalTexture!==void 0)u=i.importExternalTexture({source:l.externalTexture});else{const c=o.store?1:l.texture.mipLevelCount,d=o.store?o.mipLevel:0;let f=`view-${l.texture.width}-${l.texture.height}`;if(l.texture.depthOrArrayLayers>1&&(f+=`-${l.texture.depthOrArrayLayers}`),f+=`-${c}-${d}`,u=l[f],u===void 0){const h=B$.All;let p;o.isSampledCubeTexture?p=Ro.Cube:o.isSampledTexture3D?p=Ro.ThreeD:o.texture.isArrayTexture||o.texture.isDataArrayTexture||o.texture.isCompressedArrayTexture?p=Ro.TwoDArray:p=Ro.TwoD,u=l[f]=l.texture.createView({aspect:h,dimension:p,mipLevelCount:c,baseMipLevel:d})}}a.push({binding:s,resource:u})}else if(o.isSampler){const l=n.get(o.texture);a.push({binding:s,resource:l.sampler})}s++}return i.createBindGroup({label:"bindGroup_"+e.name,layout:t,entries:a})}_createLayoutEntries(e){const t=[];let n=0;for(const i of e.bindings){const s=this.backend,a={binding:n,visibility:i.visibility};if(i.isUniformBuffer||i.isStorageBuffer){const o={};i.isStorageBuffer&&(i.visibility&Bg.COMPUTE&&(i.access===El.READ_WRITE||i.access===El.WRITE_ONLY)?o.type=hM.Storage:o.type=hM.ReadOnlyStorage),a.buffer=o}else if(i.isSampledTexture&&i.store){const o={};o.format=this.backend.get(i.texture).texture.format;const l=i.access;l===El.READ_WRITE?o.access=pM.ReadWrite:l===El.WRITE_ONLY?o.access=pM.WriteOnly:o.access=pM.ReadOnly,i.texture.isArrayTexture?o.viewDimension=Ro.TwoDArray:i.texture.is3DTexture&&(o.viewDimension=Ro.ThreeD),a.storageTexture=o}else if(i.isSampledTexture){const o={},{primarySamples:l}=s.utils.getTextureSampleData(i.texture);if(l>1&&(o.multisampled=!0,i.texture.isDepthTexture||(o.sampleType=Dg.UnfilterableFloat)),i.texture.isDepthTexture)s.compatibilityMode&&i.texture.compareFunction===null?o.sampleType=Dg.UnfilterableFloat:o.sampleType=Dg.Depth;else if(i.texture.isDataTexture||i.texture.isDataArrayTexture||i.texture.isData3DTexture){const u=i.texture.type;u===Do?o.sampleType=Dg.SInt:u===Ls?o.sampleType=Dg.UInt:u===ha&&(this.backend.hasFeature("float32-filterable")?o.sampleType=Dg.Float:o.sampleType=Dg.UnfilterableFloat)}i.isSampledCubeTexture?o.viewDimension=Ro.Cube:i.texture.isArrayTexture||i.texture.isDataArrayTexture||i.texture.isCompressedArrayTexture?o.viewDimension=Ro.TwoDArray:i.isSampledTexture3D&&(o.viewDimension=Ro.ThreeD),a.texture=o}else if(i.isSampler){const o={};i.texture.isDepthTexture&&(i.texture.compareFunction!==null?o.type=XN.Comparison:s.compatibilityMode&&(o.type=XN.NonFiltering)),a.sampler=o}else rt(`WebGPUBindingUtils: Unsupported binding "${i}".`);t.push(a),n++}return t}deleteBindGroupData(e){const{backend:t}=this,n=t.get(e);n.layout&&(n.layout.usedTimes--,n.layout.usedTimes===0&&this._bindGroupLayoutCache.delete(n.layoutKey),n.layout=void 0,n.layoutKey=void 0)}dispose(){this._bindGroupLayoutCache.clear()}}class q${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:s,pipeline:a}=e,{vertexProgram:o,fragmentProgram:l}=a,u=this.backend,c=u.device,d=u.utils,f=u.get(a),h=[];for(const q of e.getBindings()){const Q=u.get(q),{layoutGPU:re}=Q.layout;h.push(re)}const p=u.attributeUtils.createShaderVertexBuffers(e);let x;i.blending!==Xa&&(i.blending!==Vo||i.transparent!==!1)&&(x=this._getBlending(i));let v={};i.stencilWrite===!0&&(v={compare:this._getStencilCompare(i),failOp:this._getStencilOperation(i.stencilFail),depthFailOp:this._getStencilOperation(i.stencilZFail),passOp:this._getStencilOperation(i.stencilZPass)});const m=this._getColorWriteMask(i),C=[];if(e.context.textures!==null){const q=e.context.textures;for(let Q=0;Q<q.length;Q++){const re=d.getTextureFormatGPU(q[Q]);Q===0?C.push({format:re,blend:x,writeMask:m}):C.push({format:re,writeMask:m})}}else{const q=d.getCurrentColorFormat(e.context);C.push({format:q,blend:x,writeMask:m})}const w=u.get(o).module,P=u.get(l).module,B=this._getPrimitiveState(n,s,i),S=this._getDepthCompare(i),I=d.getCurrentDepthStencilFormat(e.context),N=this._getSampleCount(e.context),T={label:`renderPipeline_${i.name||i.type}_${i.id}`,vertex:Object.assign({},w,{buffers:p}),fragment:Object.assign({},P,{targets:C}),primitive:B,multisample:{count:N,alphaToCoverageEnabled:i.alphaToCoverage&&N>1},layout:c.createPipelineLayout({bindGroupLayouts:h})},R={},D=e.context.depth,j=e.context.stencil;if((D===!0||j===!0)&&(D===!0&&(R.format=I,R.depthWriteEnabled=i.depthWrite,R.depthCompare=S),j===!0&&(R.stencilFront=v,R.stencilBack={},R.stencilReadMask=i.stencilFuncMask,R.stencilWriteMask=i.stencilWriteMask),i.polygonOffset===!0&&(R.depthBias=i.polygonOffsetUnits,R.depthBiasSlopeScale=i.polygonOffsetFactor,R.depthBiasClamp=0),T.depthStencil=R),c.pushErrorScope("validation"),t===null)f.pipeline=c.createRenderPipeline(T),c.popErrorScope().then(q=>{q!==null&&(f.error=!0,rt(q.message))});else{const q=new Promise(Q=>Kr(this,null,function*(){try{f.pipeline=yield c.createRenderPipelineAsync(T)}catch(de){}const re=yield c.popErrorScope();re!==null&&(f.error=!0,rt(re.message)),Q()}));t.push(q)}}createBundleEncoder(e,t="renderBundleEncoder"){const n=this.backend,{utils:i,device:s}=n,a=i.getCurrentDepthStencilFormat(e),o=i.getCurrentColorFormats(e),l=this._getSampleCount(e),u={label:t,colorFormats:o,depthStencilFormat:a,sampleCount:l};return s.createRenderBundleEncoder(u)}createComputePipeline(e,t){const n=this.backend,i=n.device,s=n.get(e.computeProgram).module,a=n.get(e),o=[];for(const l of t){const u=n.get(l),{layoutGPU:c}=u.layout;o.push(c)}a.pipeline=i.createComputePipeline({compute:s,layout:i.createPipelineLayout({bindGroupLayouts:o})})}_getBlending(e){let t,n;const i=e.blending,s=e.blendSrc,a=e.blendDst,o=e.blendEquation;if(i===yc){const l=e.blendSrcAlpha!==null?e.blendSrcAlpha:s,u=e.blendDstAlpha!==null?e.blendDstAlpha:a,c=e.blendEquationAlpha!==null?e.blendEquationAlpha:o;t={srcFactor:this._getBlendFactor(s),dstFactor:this._getBlendFactor(a),operation:this._getBlendOperation(o)},n={srcFactor:this._getBlendFactor(l),dstFactor:this._getBlendFactor(u),operation:this._getBlendOperation(c)}}else{const l=e.premultipliedAlpha,u=(c,d,f,h)=>{t={srcFactor:c,dstFactor:d,operation:Sg.Add},n={srcFactor:f,dstFactor:h,operation:Sg.Add}};if(l)switch(i){case Vo:u(As.One,As.OneMinusSrcAlpha,As.One,As.OneMinusSrcAlpha);break;case ju:u(As.One,As.One,As.One,As.One);break;case Xu:u(As.Zero,As.OneMinusSrc,As.Zero,As.One);break;case pl:u(As.Dst,As.OneMinusSrcAlpha,As.Zero,As.One);break}else switch(i){case Vo:u(As.SrcAlpha,As.OneMinusSrcAlpha,As.One,As.OneMinusSrcAlpha);break;case ju:u(As.SrcAlpha,As.One,As.One,As.One);break;case Xu:rt("WebGPURenderer: SubtractiveBlending requires material.premultipliedAlpha = true");break;case pl:rt("WebGPURenderer: MultiplyBlending requires material.premultipliedAlpha = true");break}}if(t!==void 0&&n!==void 0)return{color:t,alpha:n};rt("WebGPURenderer: Invalid blending: ",i)}_getBlendFactor(e){let t;switch(e){case ml:t=As.Zero;break;case Wu:t=As.One;break;case bc:t=As.Src;break;case Gf:t=As.OneMinusSrc;break;case Qu:t=As.SrcAlpha;break;case gl:t=As.OneMinusSrcAlpha;break;case nd:t=As.Dst;break;case Wd:t=As.OneMinusDst;break;case vu:t=As.DstAlpha;break;case Fl:t=As.OneMinusDstAlpha;break;case Wf:t=As.SrcAlphaSaturated;break;case DZ:t=As.Constant;break;case TZ:t=As.OneMinusConstant;break;default:rt("WebGPURenderer: Blend factor not supported.",e)}return t}_getStencilCompare(e){let t;const n=e.stencilFunc;switch(n){case yy:t=Ml.Never;break;case E0:t=Ml.Always;break;case gC:t=Ml.Less;break;case b0:t=Ml.LessEqual;break;case vC:t=Ml.Equal;break;case xC:t=Ml.GreaterEqual;break;case by:t=Ml.Greater;break;case AC:t=Ml.NotEqual;break;default:rt("WebGPURenderer: Invalid stencil function.",n)}return t}_getStencilOperation(e){let t;switch(e){case rh:t=Jp.Keep;break;case cC:t=Jp.Zero;break;case xy:t=Jp.Replace;break;case mC:t=Jp.Invert;break;case dC:t=Jp.IncrementClamp;break;case fC:t=Jp.DecrementClamp;break;case hC:t=Jp.IncrementWrap;break;case pC:t=Jp.DecrementWrap;break;default:rt("WebGPURenderer: Invalid stencil operation.",t)}return t}_getBlendOperation(e){let t;switch(e){case io:t=Sg.Add;break;case Ca:t=Sg.Subtract;break;case Gu:t=Sg.ReverseSubtract;break;case Nl:t=Sg.Min;break;case Jh:t=Sg.Max;break;default:rt("WebGPUPipelineUtils: Blend equation not supported.",e)}return t}_getPrimitiveState(e,t,n){const i={},s=this.backend.utils;i.topology=s.getPrimitiveTopology(e,n),t.index!==null&&e.isLine===!0&&e.isLineSegments!==!0&&(i.stripIndexFormat=t.index.array instanceof Uint16Array?OA.Uint16:OA.Uint32);let a=n.side===Qi;return e.isMesh&&e.matrixWorld.determinant()<0&&(a=!a),i.frontFace=a===!0?kN.CW:kN.CCW,i.cullMode=n.side===Xs?VN.None:VN.Back,i}_getColorWriteMask(e){return e.colorWrite===!0?jN.All:jN.None}_getDepthCompare(e){let t;if(e.depthTest===!1)t=Ml.Always;else{const n=e.depthFunc;switch(n){case rd:t=Ml.Never;break;case id:t=Ml.Always;break;case Au:t=Ml.Less;break;case xu:t=Ml.LessEqual;break;case sd:t=Ml.Equal;break;case Ec:t=Ml.GreaterEqual;break;case ad:t=Ml.Greater;break;case od:t=Ml.NotEqual;break;default:rt("WebGPUPipelineUtils: Invalid depth function.",n)}}return t}}class _$ extends HN{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_${t}`});const i=this.maxQueries*8;this.resolveBuffer=this.device.createBuffer({label:`buffer_timestamp_resolve_${t}`,size:i,usage:GPUBufferUsage.QUERY_RESOLVE|GPUBufferUsage.COPY_SRC}),this.resultBuffer=this.device.createBuffer({label:`buffer_timestamp_result_${t}`,size:i,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ})}allocateQueriesForContext(e){if(!this.trackTimestamp||this.isDisposed)return null;if(this.currentQueryIndex+2>this.maxQueries)return rs(`WebGPUTimestampQueryPool [${this.type}]: Maximum number of queries exceeded, when using trackTimestamp it is necessary to resolves the queries via renderer.resolveTimestampsAsync( THREE.TimestampQuery.${this.type.toUpperCase()} ).`),null;const t=this.currentQueryIndex;return this.currentQueryIndex+=2,this.queryOffsets.set(e,t),t}resolveQueriesAsync(){return Kr(this,null,function*(){if(!this.trackTimestamp||this.currentQueryIndex===0||this.isDisposed)return this.lastValue;if(this.pendingResolve)return this.pendingResolve;this.pendingResolve=this._resolveQueries();try{return yield this.pendingResolve}finally{this.pendingResolve=null}})}_resolveQueries(){return Kr(this,null,function*(){if(this.isDisposed)return this.lastValue;try{if(this.resultBuffer.mapState!=="unmapped")return this.lastValue;const e=new Map(this.queryOffsets),t=this.currentQueryIndex,n=t*8;this.currentQueryIndex=0,this.queryOffsets.clear();const i=this.device.createCommandEncoder();i.resolveQuerySet(this.querySet,0,t,this.resolveBuffer,0),i.copyBufferToBuffer(this.resolveBuffer,0,this.resultBuffer,0,n);const s=i.finish();if(this.device.queue.submit([s]),this.resultBuffer.mapState!=="unmapped")return this.lastValue;if(yield this.resultBuffer.mapAsync(GPUMapMode.READ,0,n),this.isDisposed)return this.resultBuffer.mapState==="mapped"&&this.resultBuffer.unmap(),this.lastValue;const a=new BigUint64Array(this.resultBuffer.getMappedRange(0,n)),o={},l=[];for(const[c,d]of e){const f=c.match(/^(.*):f(\d+)$/),h=parseInt(f[2]);l.includes(h)===!1&&l.push(h),o[h]===void 0&&(o[h]=0);const p=a[d],x=a[d+1],v=Number(x-p)/1e6;this.timestamps.set(c,v),o[h]+=v}const u=o[l[l.length-1]];return this.resultBuffer.unmap(),this.lastValue=u,this.frames=l,u}catch(e){return rt("Error resolving queries:",e),this.resultBuffer.mapState==="mapped"&&this.resultBuffer.unmap(),this.lastValue}})}dispose(){return Kr(this,null,function*(){if(!this.isDisposed){if(this.isDisposed=!0,this.pendingResolve)try{yield this.pendingResolve}catch(e){rt("Error waiting for pending resolve:",e)}if(this.resultBuffer&&this.resultBuffer.mapState==="mapped")try{this.resultBuffer.unmap()}catch(e){rt("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 vM extends RN{constructor(e={}){super(e),this.isWebGPUBackend=!0,this.parameters.alpha=e.alpha===void 0?!0:e.alpha,this.parameters.compatibilityMode=e.compatibilityMode===void 0?!1:e.compatibilityMode,this.parameters.requiredLimits=e.requiredLimits===void 0?{}:e.requiredLimits,this.compatibilityMode=this.parameters.compatibilityMode,this.device=null,this.defaultRenderPassdescriptor=null,this.utils=new W$(this),this.attributeUtils=new Y$(this),this.bindingUtils=new K$(this),this.pipelineUtils=new q$(this),this.textureUtils=new R$(this),this.occludedResolveCache=new Map}init(e){return Kr(this,null,function*(){yield lR(vM.prototype,this,"init").call(this,e);const t=this.parameters;let n;if(t.device===void 0){const i={powerPreference:t.powerPreference,featureLevel:t.compatibilityMode?"compatibility":void 0},s=typeof navigator!="undefined"?yield navigator.gpu.requestAdapter(i):null;if(s===null)throw new Error("WebGPUBackend: Unable to create WebGPU adapter.");const a=Object.values(mM),o=[];for(const u of a)s.features.has(u)&&o.push(u);const l={requiredFeatures:o,requiredLimits:t.requiredLimits};n=yield s.requestDevice(l)}else n=t.device;n.lost.then(i=>{if(i.reason==="destroyed")return;const s={api:"WebGPU",message:i.message||"Unknown reason",reason:i.reason||null,originalEvent:i};e.onDeviceLost(s)}),this.device=n,this.trackTimestamp=this.trackTimestamp&&this.hasFeature(mM.TimestampQuery),this.updateSize()})}get context(){const e=this.renderer.getCanvasTarget(),t=this.get(e);let n=t.context;if(n===void 0){const i=this.parameters;e.isDefaultCanvasTarget===!0&&i.context!==void 0?n=i.context:n=e.domElement.getContext("webgpu"),"setAttribute"in e.domElement&&e.domElement.setAttribute("data-engine",`three.js r${Fs} webgpu`);const s=i.alpha?"premultiplied":"opaque",a=i.outputType===pa?"extended":"standard";n.configure({device:this.device,format:this.utils.getPreferredCanvasFormat(),usage:GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.COPY_SRC,alphaMode:s,toneMapping:{mode:a}}),t.context=n}return n}get coordinateSystem(){return gn}getArrayBufferAsync(e){return Kr(this,null,function*(){return yield this.attributeUtils.getArrayBufferAsync(e)})}getContext(){return this.context}_getDefaultRenderPassDescriptor(){const e=this.renderer,t=e.getCanvasTarget(),n=this.get(t),i=e.currentSamples;let s=n.descriptor;if(s===void 0||n.samples!==i){s={colorAttachments:[{view:null}]},(e.depth===!0||e.stencil===!0)&&(s.depthStencilAttachment={view:this.textureUtils.getDepthBuffer(e.depth,e.stencil).createView()});const o=s.colorAttachments[0];i>0?o.view=this.textureUtils.getColorBuffer().createView():o.resolveTarget=void 0,n.descriptor=s,n.samples=i}const a=s.colorAttachments[0];return i>0?a.resolveTarget=this.context.getCurrentTexture().createView():a.view=this.context.getCurrentTexture().createView(),s}_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 s=i.descriptors;(s===void 0||i.width!==n.width||i.height!==n.height||i.samples!==n.samples)&&(s={},i.descriptors=s);const a=e.getCacheKey();let o=s[a];if(o===void 0){const u=e.textures,c=[];let d;const f=this._isRenderCameraDepthArray(e);for(let h=0;h<u.length;h++){const p=this.get(u[h]),x={label:`colorAttachment_${h}`,baseMipLevel:e.activeMipmapLevel,mipLevelCount:1,baseArrayLayer:e.activeCubeFace,arrayLayerCount:1,dimension:Ro.TwoD};if(n.isRenderTarget3D)d=e.activeCubeFace,x.baseArrayLayer=0,x.dimension=Ro.ThreeD,x.depthOrArrayLayers=u[h].image.depth;else if(n.isRenderTarget&&u[h].image.depth>1)if(f===!0){const v=e.camera.cameras;for(let m=0;m<v.length;m++){const C=Gc(ba({},x),{baseArrayLayer:m,arrayLayerCount:1,dimension:Ro.TwoD}),w=p.texture.createView(C);c.push({view:w,resolveTarget:void 0,depthSlice:void 0})}}else x.dimension=Ro.TwoDArray,x.depthOrArrayLayers=u[h].image.depth;if(f!==!0){const v=p.texture.createView(x);let m,C;p.msaaTexture!==void 0?(m=p.msaaTexture.createView(),C=v):(m=v,C=void 0),c.push({view:m,resolveTarget:C,depthSlice:d})}}if(o={textureViews:c},e.depth){const h=this.get(e.depthTexture),p={};(e.depthTexture.isArrayTexture||e.depthTexture.isCubeTexture)&&(p.dimension=Ro.TwoD,p.arrayLayerCount=1,p.baseArrayLayer=e.activeCubeFace),o.depthStencilView=h.texture.createView(p)}s[a]=o,i.width=n.width,i.height=n.height,i.samples=n.samples,i.activeMipmapLevel=e.activeMipmapLevel,i.activeCubeFace=e.activeCubeFace}const l={colorAttachments:[]};for(let u=0;u<o.textureViews.length;u++){const c=o.textureViews[u];let d={r:0,g:0,b:0,a:1};u===0&&t.clearValue&&(d=t.clearValue),l.colorAttachments.push({view:c.view,depthSlice:c.depthSlice,resolveTarget:c.resolveTarget,loadOp:t.loadOp||Zs.Load,storeOp:t.storeOp||du.Store,clearValue:d})}return o.depthStencilView&&(l.depthStencilAttachment={view:o.depthStencilView}),l}beginRender(e){const t=this.get(e),n=this.device,i=e.occlusionQueryCount;let s;i>0&&(t.currentOcclusionQuerySet&&t.currentOcclusionQuerySet.destroy(),t.currentOcclusionQueryBuffer&&t.currentOcclusionQueryBuffer.destroy(),t.currentOcclusionQuerySet=t.occlusionQuerySet,t.currentOcclusionQueryBuffer=t.occlusionQueryBuffer,t.currentOcclusionQueryObjects=t.occlusionQueryObjects,s=n.createQuerySet({type:"occlusion",count:i,label:`occlusionQuerySet_${e.id}`}),t.occlusionQuerySet=s,t.occlusionQueryIndex=0,t.occlusionQueryObjects=new Array(i),t.lastOcclusionObject=null);let a;e.textures===null?a=this._getDefaultRenderPassDescriptor():a=this._getRenderPassDescriptor(e,{loadOp:Zs.Load}),this.initTimestampQuery(On.RENDER,this.getTimestampUID(e),a),a.occlusionQuerySet=s;const o=a.depthStencilAttachment;if(e.textures!==null){const u=a.colorAttachments;for(let c=0;c<u.length;c++){const d=u[c];e.clearColor?(d.clearValue=c===0?e.clearColorValue:{r:0,g:0,b:0,a:1},d.loadOp=Zs.Clear):d.loadOp=Zs.Load,d.storeOp=du.Store}}else{const u=a.colorAttachments[0];e.clearColor?(u.clearValue=e.clearColorValue,u.loadOp=Zs.Clear):u.loadOp=Zs.Load,u.storeOp=du.Store}e.depth&&(e.clearDepth?(o.depthClearValue=e.clearDepthValue,o.depthLoadOp=Zs.Clear):o.depthLoadOp=Zs.Load,o.depthStoreOp=du.Store),e.stencil&&(e.clearStencil?(o.stencilClearValue=e.clearStencilValue,o.stencilLoadOp=Zs.Clear):o.stencilLoadOp=Zs.Load,o.stencilStoreOp=du.Store);const l=n.createCommandEncoder({label:"renderContext_"+e.id});if(this._isRenderCameraDepthArray(e)===!0){const u=e.camera.cameras;!t.layerDescriptors||t.layerDescriptors.length!==u.length?this._createDepthLayerDescriptors(e,t,a,u):this._updateDepthLayerDescriptors(e,t,u),t.bundleEncoders=[],t.bundleSets=[];for(let c=0;c<u.length;c++){const d=this.pipelineUtils.createBundleEncoder(e,"renderBundleArrayCamera_"+c),f={attributes:{},bindingGroups:[],pipeline:null,index:null};t.bundleEncoders.push(d),t.bundleSets.push(f)}t.currentPass=null}else{const u=l.beginRenderPass(a);t.currentPass=u,e.viewport&&this.updateViewport(e),e.scissor&&this.updateScissor(e)}t.descriptor=a,t.encoder=l,t.currentSets={attributes:{},bindingGroups:[],pipeline:null,index:null},t.renderBundles=[]}_createDepthLayerDescriptors(e,t,n,i){const s=n.depthStencilAttachment;t.layerDescriptors=[];const a=this.get(e.depthTexture);a.viewCache||(a.viewCache=[]);for(let o=0;o<i.length;o++){const l=Gc(ba({},n),{colorAttachments:[Gc(ba({},n.colorAttachments[0]),{view:n.colorAttachments[o].view})]});if(n.depthStencilAttachment){const u=o;a.viewCache[u]||(a.viewCache[u]=a.texture.createView({dimension:Ro.TwoD,baseArrayLayer:o,arrayLayerCount:1})),l.depthStencilAttachment={view:a.viewCache[u],depthLoadOp:s.depthLoadOp||Zs.Clear,depthStoreOp:s.depthStoreOp||du.Store,depthClearValue:s.depthClearValue||1},e.stencil&&(l.depthStencilAttachment.stencilLoadOp=s.stencilLoadOp,l.depthStencilAttachment.stencilStoreOp=s.stencilStoreOp,l.depthStencilAttachment.stencilClearValue=s.stencilClearValue)}else l.depthStencilAttachment=ba({},s);t.layerDescriptors.push(l)}}_updateDepthLayerDescriptors(e,t,n){for(let i=0;i<n.length;i++){const s=t.layerDescriptors[i];if(s.depthStencilAttachment){const a=s.depthStencilAttachment;e.depth&&(e.clearDepth?(a.depthClearValue=e.clearDepthValue,a.depthLoadOp=Zs.Clear):a.depthLoadOp=Zs.Load),e.stencil&&(e.clearStencil?(a.stencilClearValue=e.clearStencilValue,a.stencilLoadOp=Zs.Clear):a.stencilLoadOp=Zs.Load)}}}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(this._isRenderCameraDepthArray(e)===!0){const s=[];for(let a=0;a<t.bundleEncoders.length;a++){const o=t.bundleEncoders[a];s.push(o.finish())}for(let a=0;a<t.layerDescriptors.length;a++)if(a<s.length){const o=t.layerDescriptors[a],l=i.beginRenderPass(o);if(e.viewport){const{x:u,y:c,width:d,height:f,minDepth:h,maxDepth:p}=e.viewportValue;l.setViewport(u,c,d,f,h,p)}if(e.scissor){const{x:u,y:c,width:d,height:f}=e.scissorValue;l.setScissorRect(u,c,d,f)}l.executeBundles([s[a]]),l.end()}}else t.currentPass&&t.currentPass.end();if(n>0){const s=n*8;let a=this.occludedResolveCache.get(s);a===void 0&&(a=this.device.createBuffer({size:s,usage:GPUBufferUsage.QUERY_RESOLVE|GPUBufferUsage.COPY_SRC}),this.occludedResolveCache.set(s,a));const o=this.device.createBuffer({size:s,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ});t.encoder.resolveQuerySet(t.occlusionQuerySet,0,n,a,0),t.encoder.copyBufferToBuffer(a,0,o,0,s),t.occlusionQueryBuffer=o,this.resolveOccludedAsync(e)}if(this.device.queue.submit([t.encoder.finish()]),e.textures!==null){const s=e.textures;for(let a=0;a<s.length;a++){const o=s[a];o.generateMipmaps===!0&&this.textureUtils.generateMipmaps(o)}}}isOccluded(e,t){const n=this.get(e);return n.occluded&&n.occluded.has(t)}resolveOccludedAsync(e){return Kr(this,null,function*(){const t=this.get(e),{currentOcclusionQueryBuffer:n,currentOcclusionQueryObjects:i}=t;if(n&&i){const s=new WeakSet;t.currentOcclusionQueryObjects=null,t.currentOcclusionQueryBuffer=null,yield n.mapAsync(GPUMapMode.READ);const a=n.getMappedRange(),o=new BigUint64Array(a);for(let l=0;l<i.length;l++)o[l]===BigInt(0)&&s.add(i[l]);n.destroy(),t.occluded=s}})}updateViewport(e){const{currentPass:t}=this.get(e),{x:n,y:i,width:s,height:a,minDepth:o,maxDepth:l}=e.viewportValue;t.setViewport(n,i,s,a,o,l)}updateScissor(e){const{currentPass:t}=this.get(e),{x:n,y:i,width:s,height:a}=e.scissorValue;t.setScissorRect(n,i,s,a)}getClearColor(){const e=super.getClearColor();return this.renderer.alpha===!0&&(e.r*=e.a,e.g*=e.a,e.b*=e.a),e}clear(e,t,n,i=null){const s=this.device,a=this.renderer;let o=[],l,u,c,d;if(e){const p=this.getClearColor();u={r:p.r,g:p.g,b:p.b,a:p.a}}if(i===null){c=a.depth,d=a.stencil;const p=this._getDefaultRenderPassDescriptor();if(e){o=p.colorAttachments;const x=o[0];x.clearValue=u,x.loadOp=Zs.Clear,x.storeOp=du.Store}(c||d)&&(l=p.depthStencilAttachment)}else{c=i.depth,d=i.stencil;const p={loadOp:e?Zs.Clear:Zs.Load,clearValue:e?u:void 0};c&&(p.depthLoadOp=t?Zs.Clear:Zs.Load,p.depthClearValue=t?a.getClearDepth():void 0,p.depthStoreOp=du.Store),d&&(p.stencilLoadOp=n?Zs.Clear:Zs.Load,p.stencilClearValue=n?a.getClearStencil():void 0,p.stencilStoreOp=du.Store);const x=this._getRenderPassDescriptor(i,p);o=x.colorAttachments,l=x.depthStencilAttachment}c&&l&&(t?(l.depthLoadOp=Zs.Clear,l.depthClearValue=a.getClearDepth(),l.depthStoreOp=du.Store):(l.depthLoadOp=Zs.Load,l.depthStoreOp=du.Store)),d&&l&&(n?(l.stencilLoadOp=Zs.Clear,l.stencilClearValue=a.getClearStencil(),l.stencilStoreOp=du.Store):(l.stencilLoadOp=Zs.Load,l.stencilStoreOp=du.Store));const f=s.createCommandEncoder({label:"clear"});f.beginRenderPass({colorAttachments:o,depthStencilAttachment:l}).end(),s.queue.submit([f.finish()])}beginCompute(e){const t=this.get(e),n={label:"computeGroup_"+e.id};this.initTimestampQuery(On.COMPUTE,this.getTimestampUID(e),n),t.cmdEncoderGPU=this.device.createCommandEncoder({label:"computeGroup_"+e.id}),t.passEncoderGPU=t.cmdEncoderGPU.beginComputePass(n)}compute(e,t,n,i,s=null){const a=this.get(t),{passEncoderGPU:o}=this.get(e),l=this.get(i).pipeline;this.pipelineUtils.setPipeline(o,l);for(let u=0,c=n.length;u<c;u++){const d=n[u],f=this.get(d);o.setBindGroup(u,f.group)}if(s===null&&(s=t.count),s&&typeof s=="object"&&s.isIndirectStorageBufferAttribute){const u=this.get(s).buffer;o.dispatchWorkgroupsIndirect(u,0);return}if(typeof s=="number"){const u=s;if(a.dispatchSize===void 0||a.count!==u){a.dispatchSize=[0,1,1],a.count=u;const c=t.workgroupSize;let d=c[0];for(let p=1;p<c.length;p++)d*=c[p];const f=Math.ceil(u/d),h=this.device.limits.maxComputeWorkgroupsPerDimension;s=[f,1,1],f>h&&(s[0]=Math.min(f,h),s[1]=Math.ceil(f/h)),a.dispatchSize=s}s=a.dispatchSize}o.dispatchWorkgroups(s[0],s[1]||1,s[2]||1)}finishCompute(e){const t=this.get(e);t.passEncoderGPU.end(),this.device.queue.submit([t.cmdEncoderGPU.finish()])}draw(e,t){const{object:n,material:i,context:s,pipeline:a}=e,o=e.getBindings(),l=this.get(s),u=this.get(a),c=u.pipeline;if(u.error===!0)return;const d=e.getIndex(),f=d!==null,h=e.getDrawParameters();if(h===null)return;const p=(v,m)=>{this.pipelineUtils.setPipeline(v,c),m.pipeline=c;const C=m.bindingGroups;for(let P=0,B=o.length;P<B;P++){const S=o[P],I=this.get(S);C[S.index]!==S.id&&(v.setBindGroup(S.index,I.group),C[S.index]=S.id)}if(f===!0&&m.index!==d){const P=this.get(d).buffer,B=d.array instanceof Uint16Array?OA.Uint16:OA.Uint32;v.setIndexBuffer(P,B),m.index=d}const w=e.getVertexBuffers();for(let P=0,B=w.length;P<B;P++){const S=w[P];if(m.attributes[P]!==S){const I=this.get(S).buffer;v.setVertexBuffer(P,I),m.attributes[P]=S}}s.stencil===!0&&i.stencilWrite===!0&&l.currentStencilRef!==i.stencilRef&&(v.setStencilReference(i.stencilRef),l.currentStencilRef=i.stencilRef)},x=(v,m)=>{if(p(v,m),n.isBatchedMesh===!0){const C=n._multiDrawStarts,w=n._multiDrawCounts,P=n._multiDrawCount,B=n._multiDrawInstances;B!==null&&rs("WebGPUBackend: renderMultiDrawInstances has been deprecated and will be removed in r184. Append to renderMultiDraw arguments and use indirection.");for(let S=0;S<P;S++){const I=B?B[S]:1,N=I>1?0:S;f===!0?v.drawIndexed(w[S],I,C[S]/d.array.BYTES_PER_ELEMENT,0,N):v.draw(w[S],I,C[S],N),t.update(n,w[S],I)}}else if(f===!0){const{vertexCount:C,instanceCount:w,firstVertex:P}=h,B=e.getIndirect();if(B!==null){const S=this.get(B).buffer,I=e.getIndirectOffset(),N=Array.isArray(I)?I:[I];for(let T=0;T<N.length;T++)v.drawIndexedIndirect(S,N[T])}else v.drawIndexed(C,w,P,0,0);t.update(n,C,w)}else{const{vertexCount:C,instanceCount:w,firstVertex:P}=h,B=e.getIndirect();if(B!==null){const S=this.get(B).buffer,I=e.getIndirectOffset(),N=Array.isArray(I)?I:[I];for(let T=0;T<N.length;T++)v.drawIndirect(S,N[T])}else v.draw(C,w,P,0);t.update(n,C,w)}};if(e.camera.isArrayCamera&&e.camera.cameras.length>0){const v=this.get(e.camera),m=e.camera.cameras,C=e.getBindingGroup("cameraIndex");if(v.indexesGPU===void 0||v.indexesGPU.length!==m.length){const P=this.get(C),B=[],S=new Uint32Array([0,0,0,0]);for(let I=0,N=m.length;I<N;I++){S[0]=I;const{layoutGPU:T}=P.layout,R=this.bindingUtils.createBindGroupIndex(S,T);B.push(R)}v.indexesGPU=B}const w=this.renderer.getPixelRatio();for(let P=0,B=m.length;P<B;P++){const S=m[P];if(n.layers.test(S.layers)){const I=S.viewport;let N=l.currentPass,T=l.currentSets;if(l.bundleEncoders){const R=l.bundleEncoders[P],D=l.bundleSets[P];N=R,T=D}I&&N.setViewport(Math.floor(I.x*w),Math.floor(I.y*w),Math.floor(I.width*w),Math.floor(I.height*w),s.viewportValue.minDepth,s.viewportValue.maxDepth),C&&v.indexesGPU&&(N.setBindGroup(C.index,v.indexesGPU[P]),T.bindingGroups[C.index]=C.id),x(N,T)}}}else if(l.currentPass){if(l.occlusionQuerySet!==void 0){const v=l.lastOcclusionObject;v!==n&&(v!==null&&v.occlusionTest===!0&&(l.currentPass.endOcclusionQuery(),l.occlusionQueryIndex++),n.occlusionTest===!0&&(l.currentPass.beginOcclusionQuery(l.occlusionQueryIndex),l.occlusionQueryObjects[l.occlusionQueryIndex]=n),l.lastOcclusionObject=n)}x(l.currentPass,l.currentSets)}}needsRenderUpdate(e){const t=this.get(e),{object:n,material:i}=e,s=this.utils,a=s.getSampleCountRenderContext(e.context),o=s.getCurrentColorSpace(e.context),l=s.getCurrentColorFormat(e.context),u=s.getCurrentDepthStencilFormat(e.context),c=s.getPrimitiveTopology(n,i);let d=!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!==a||t.colorSpace!==o||t.colorFormat!==l||t.depthStencilFormat!==u||t.primitiveTopology!==c||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=a,t.colorSpace=o,t.colorFormat=l,t.depthStencilFormat=u,t.primitiveTopology=c,t.clippingContextCacheKey=e.clippingContextCacheKey,d=!0),d}getRenderCacheKey(e){const{object:t,material:n}=e,i=this.utils,s=e.context,a=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,a,i.getSampleCountRenderContext(s),i.getCurrentColorSpace(s),i.getCurrentColorFormat(s),i.getCurrentDepthStencilFormat(s),i.getPrimitiveTopology(t,n),e.getGeometryCacheKey(),e.clippingContextCacheKey].join()}updateSampler(e){return this.textureUtils.updateSampler(e)}createDefaultTexture(e){return 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,t=!1){this.textureUtils.destroyTexture(e,t)}copyTextureToBuffer(e,t,n,i,s,a){return Kr(this,null,function*(){return this.textureUtils.copyTextureToBuffer(e,t,n,i,s,a)})}initTimestampQuery(e,t,n){if(!this.trackTimestamp)return;this.timestampQueryPool[e]||(this.timestampQueryPool[e]=new _$(this.device,e,2048));const i=this.timestampQueryPool[e],s=i.allocateQueriesForContext(t);n.timestampWrites={querySet:i.querySet,beginningOfPassWriteIndex:s,endOfPassWriteIndex:s+1}}createNodeBuilder(e,t){return new G$(e,t)}createProgram(e){const t=this.get(e);t.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),s=n.currentPass.finish();this.get(t).bundleGPU=s,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)}deleteBindGroupData(e){this.bindingUtils.deleteBindGroupData(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.delete(this.renderer.getCanvasTarget())}getMaxAnisotropy(){return 16}hasFeature(e){return WN[e]!==void 0&&(e=WN[e]),this.device.features.has(e)}copyTextureToTexture(e,t,n=null,i=null,s=0,a=0){let o=0,l=0,u=0,c=0,d=0,f=0,h=e.image.width,p=e.image.height,x=1;n!==null&&(n.isBox3===!0?(c=n.min.x,d=n.min.y,f=n.min.z,h=n.max.x-n.min.x,p=n.max.y-n.min.y,x=n.max.z-n.min.z):(c=n.min.x,d=n.min.y,h=n.max.x-n.min.x,p=n.max.y-n.min.y,x=1)),i!==null&&(o=i.x,l=i.y,u=i.z||0);const v=this.device.createCommandEncoder({label:"copyTextureToTexture_"+e.id+"_"+t.id}),m=this.get(e).texture,C=this.get(t).texture;v.copyTextureToTexture({texture:m,mipLevel:s,origin:{x:c,y:d,z:f}},{texture:C,mipLevel:a,origin:{x:o,y:l,z:u}},[h,p,x]),this.device.queue.submit([v.finish()]),a===0&&t.generateMipmaps&&this.textureUtils.generateMipmaps(t)}copyFramebufferToTexture(e,t,n){const i=this.get(t);let s=null;t.renderTarget?e.isDepthTexture?s=this.get(t.depthTexture).texture:s=this.get(t.textures[0]).texture:e.isDepthTexture?s=this.textureUtils.getDepthBuffer(t.depth,t.stencil):s=this.context.getCurrentTexture();const a=this.get(e).texture;if(s.format!==a.format){rt("WebGPUBackend: copyFramebufferToTexture: Source and destination formats do not match.",s.format,a.format);return}let o;if(i.currentPass?(i.currentPass.end(),o=i.encoder):o=this.device.createCommandEncoder({label:"copyFramebufferToTexture_"+e.id}),o.copyTextureToTexture({texture:s,origin:[n.x,n.y,0]},{texture:a},[n.z,n.w]),e.generateMipmaps&&this.textureUtils.generateMipmaps(e,o),i.currentPass){const{descriptor:l}=i;for(let u=0;u<l.colorAttachments.length;u++)l.colorAttachments[u].loadOp=Zs.Load;t.depth&&(l.depthStencilAttachment.depthLoadOp=Zs.Load),t.stencil&&(l.depthStencilAttachment.stencilLoadOp=Zs.Load),i.currentPass=o.beginRenderPass(l),i.currentSets={attributes:{},bindingGroups:[],pipeline:null,index:null},t.viewport&&this.updateViewport(t),t.scissor&&this.updateScissor(t)}else this.device.queue.submit([o.finish()])}dispose(){if(this.bindingUtils.dispose(),this.textureUtils.dispose(),this.occludedResolveCache){for(const e of this.occludedResolveCache.values())e.destroy();this.occludedResolveCache.clear()}if(this.timestampQueryPool)for(const e of Object.values(this.timestampQueryPool))e!==null&&e.dispose();this.parameters.device===void 0&&this.device!==null&&this.device.destroy()}}class $$ extends Eb{constructor(e,t,n,i,s,a){super(e,t,n,i,s,a),this.iesMap=null}copy(e,t){return super.copy(e,t),this.iesMap=e.iesMap,this}}class eee extends Eb{constructor(e,t,n,i,s,a){super(e,t,n,i,s,a),this.aspect=null}copy(e,t){return super.copy(e,t),this.aspect=e.aspect,this}}class tee extends vN{constructor(){super(),this.addMaterial(mQ,"MeshPhongMaterial"),this.addMaterial(Z4,"MeshStandardMaterial"),this.addMaterial(aZ,"MeshPhysicalMaterial"),this.addMaterial(dZ,"MeshToonMaterial"),this.addMaterial(lQ,"MeshBasicMaterial"),this.addMaterial(hQ,"MeshLambertMaterial"),this.addMaterial(rQ,"MeshNormalMaterial"),this.addMaterial(hZ,"MeshMatcapMaterial"),this.addMaterial(qW,"LineBasicMaterial"),this.addMaterial($W,"LineDashedMaterial"),this.addMaterial(AZ,"PointsMaterial"),this.addMaterial(J4,"SpriteMaterial"),this.addMaterial(EZ,"ShadowMaterial"),this.addLight(eq,X5),this.addLight(I_,H1),this.addLight(N_,G5),this.addLight(nM,Eb),this.addLight(O_,U1),this.addLight(z_,k5),this.addLight(H_,Q5),this.addLight(F_,$$),this.addLight(L_,eee),this.addToneMapping(b9,ci),this.addToneMapping(E9,fo),this.addToneMapping(w9,Rl),this.addToneMapping(C9,Yd),this.addToneMapping(P9,Zf),this.addToneMapping(B9,qh)}}class nee extends i${constructor(e={}){let t;e.forceWebGL?t=UN:(t=vM,e.getFallback=()=>(ze("WebGPURenderer: WebGPU is not available, running under WebGL2 backend."),new UN(e)));const n=new t(e);super(n,e),this.library=new tee,this.isWebGPURenderer=!0,typeof __THREE_DEVTOOLS__!="undefined"&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent("observe",{detail:this}))}}class cfe extends null{constructor(){super(),this.isBundleGroup=!0,this.type="BundleGroup",this.static=!0,this.version=0}set needsUpdate(e){e===!0&&this.version++}}class dfe{constructor(e,t=Yn(0,0,1,1)){this.renderer=e,this.outputNode=t,this.outputColorTransform=!0,this.needsUpdate=!0;const n=new Ka;n.name="PostProcessing",this._quadMesh=new Lx(n),this._quadMesh.name="Post-Processing",this._context=null}render(){const e=this.renderer;this._update(),this._context.onBeforePostProcessing!==null&&this._context.onBeforePostProcessing();const t=e.toneMapping,n=e.outputColorSpace;e.toneMapping=NoToneMapping,e.outputColorSpace=ColorManagement.workingColorSpace;const i=e.xr.enabled;e.xr.enabled=!1,this._quadMesh.render(e),e.xr.enabled=i,e.toneMapping=t,e.outputColorSpace=n,this._context.onAfterPostProcessing!==null&&this._context.onAfterPostProcessing()}get context(){return this._context}dispose(){this._quadMesh.material.dispose()}_update(){if(this.needsUpdate===!0){const e=this.renderer,t=e.toneMapping,n=e.outputColorSpace,i={postProcessing:this,onBeforePostProcessing:null,onAfterPostProcessing:null};let s=this.outputNode;this.outputColorTransform===!0?(s=s.context(i),s=P3(s,t,n)):(i.toneMapping=t,i.outputColorSpace=n,s=s.context(i)),this._context=i,this._quadMesh.material.fragmentNode=s,this._quadMesh.material.needsUpdate=!0,this.needsUpdate=!1}}renderAsync(){return Kr(this,null,function*(){warnOnce('PostProcessing: "renderAsync()" has been deprecated. Use "render()" and "await renderer.init();" when creating the renderer.'),yield this.renderer.init(),this.render()})}}class ffe extends null{constructor(e=1,t=1){super(),this.image={width:e,height:t},this.magFilter=LinearFilter,this.minFilter=LinearFilter,this.isStorageTexture=!0,this.mipmapsAutoUpdate=!0}setSize(e,t){(this.image.width!==e||this.image.height!==t)&&(this.image.width=e,this.image.height=t,this.dispose())}}class hfe extends null{constructor(e=1,t=1,n=1){super(),this.isArrayTexture=!1,this.image={width:e,height:t,depth:n},this.magFilter=LinearFilter,this.minFilter=LinearFilter,this.wrapR=ClampToEdgeWrapping,this.isStorageTexture=!0,this.is3DTexture=!0}setSize(e,t,n){(this.image.width!==e||this.image.height!==t||this.image.depth!==n)&&(this.image.width=e,this.image.height=t,this.image.depth=n,this.dispose())}}class pfe extends null{constructor(e=1,t=1,n=1){super(),this.isArrayTexture=!0,this.image={width:e,height:t,depth:n},this.magFilter=LinearFilter,this.minFilter=LinearFilter,this.isStorageTexture=!0}setSize(e,t,n){(this.image.width!==e||this.image.height!==t||this.image.depth!==n)&&(this.image.width=e,this.image.height=t,this.image.depth=n,this.dispose())}}class mfe extends null{constructor(e,t){super(e,t,Uint32Array),this.isIndirectStorageBufferAttribute=!0}}class ree extends null{constructor(e){super(e),this.textures={},this.nodes={}}load(e,t,n,i){const s=new FileLoader(this.manager);s.setPath(this.path),s.setRequestHeader(this.requestHeader),s.setWithCredentials(this.withCredentials),s.load(e,a=>{try{t(this.parse(JSON.parse(a)))}catch(o){i?i(o):error(o),this.manager.itemError(e)}},n,i)}parseNodes(e){const t={};if(e!==void 0){for(const i of e){const{uuid:s,type:a}=i;t[s]=this.createNodeFromType(a),t[s].uuid=s}const n={nodes:t,textures:this.textures};for(const i of e)i.meta=n,t[i.uuid].deserialize(i),delete i.meta}return t}parse(e){const t=this.createNodeFromType(e.type);t.uuid=e.uuid;const i={nodes:this.parseNodes(e.nodes),textures:this.textures};return e.meta=i,t.deserialize(e),delete e.meta,t}setTextures(e){return this.textures=e,this}setNodes(e){return this.nodes=e,this}createNodeFromType(e){return this.nodes[e]===void 0?(error("NodeLoader: Node type not found:",e),K()):new this.nodes[e]}}class iee extends null{constructor(e){super(e),this.nodes={},this.nodeMaterials={}}parse(e){const t=super.parse(e),n=this.nodes,i=e.inputNodes;for(const s in i){const a=i[s];t[s]=n[a]}return t}setNodes(e){return this.nodes=e,this}setNodeMaterials(e){return this.nodeMaterials=e,this}createMaterialFromType(e){const t=this.nodeMaterials[e];return t!==void 0?new t:super.createMaterialFromType(e)}}class gfe extends null{constructor(e){super(e),this.nodes={},this.nodeMaterials={},this._nodesJSON=null}setNodes(e){return this.nodes=e,this}setNodeMaterials(e){return this.nodeMaterials=e,this}parse(e,t){this._nodesJSON=e.nodes;const n=super.parse(e,t);return this._nodesJSON=null,n}parseNodes(e,t){if(e!==void 0){const n=new ree;return n.setNodes(this.nodes),n.setTextures(t),n.parseNodes(e)}return{}}parseMaterials(e,t){const n={};if(e!==void 0){const i=this.parseNodes(this._nodesJSON,t),s=new iee;s.setTextures(t),s.setNodes(i),s.setNodeMaterials(this.nodeMaterials);for(let a=0,o=e.length;a<o;a++){const l=e[a];n[l.uuid]=s.parse(l)}}return n}}class vfe extends null{constructor(){super(),this.isClippingGroup=!0,this.clippingPlanes=[],this.enabled=!0,this.clipIntersection=!1,this.clipShadows=!1}}const AM={type:"change"},xM={type:"start"},yM={type:"end"},_N=1e-6,Ys={NONE:-1,ROTATE:0,ZOOM:1,PAN:2,TOUCH_ROTATE:3,TOUCH_ZOOM_PAN:4},yw=new ct,Kp=new ct,see=new J,bw=new J,bM=new J,zA=new Wo,$N=new J,Ew=new J,EM=new J,ww=new J;class aee extends Ib{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:Rs.ROTATE,MIDDLE:Rs.DOLLY,RIGHT:Rs.PAN},this.target=new J,this.state=Ys.NONE,this.keyState=Ys.NONE,this._lastPosition=new J,this._lastZoom=1,this._touchZoomDistanceStart=0,this._touchZoomDistanceEnd=0,this._lastAngle=0,this._eye=new J,this._movePrev=new ct,this._moveCurr=new ct,this._lastAxis=new J,this._zoomStart=new ct,this._zoomEnd=new ct,this._panStart=new ct,this._panEnd=new ct,this._pointers=[],this._pointerPositions={},this._onPointerMove=lee.bind(this),this._onPointerDown=oee.bind(this),this._onPointerUp=uee.bind(this),this._onPointerCancel=cee.bind(this),this._onContextMenu=vee.bind(this),this._onMouseWheel=gee.bind(this),this._onKeyDown=fee.bind(this),this._onKeyUp=dee.bind(this),this._onTouchStart=Aee.bind(this),this._onTouchMove=xee.bind(this),this._onTouchEnd=yee.bind(this),this._onMouseDown=hee.bind(this),this._onMouseMove=pee.bind(this),this._onMouseUp=mee.bind(this),this._target0=this.target.clone(),this._position0=this.object.position.clone(),this._up0=this.object.up.clone(),this._zoom0=this.object.zoom,t!==null&&(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.ownerDocument.removeEventListener("pointermove",this._onPointerMove),this.domElement.ownerDocument.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)>_N&&(this.dispatchEvent(AM),this._lastPosition.copy(this.object.position))):this.object.isOrthographicCamera?(this.object.lookAt(this.target),(this._lastPosition.distanceToSquared(this.object.position)>_N||this._lastZoom!==this.object.zoom)&&(this.dispatchEvent(AM),this._lastPosition.copy(this.object.position),this._lastZoom=this.object.zoom)):console.warn("THREE.TrackballControls: Unsupported camera type.")}reset(){this.state=Ys.NONE,this.keyState=Ys.NONE,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(AM),this._lastPosition.copy(this.object.position),this._lastZoom=this.object.zoom}_panCamera(){if(Kp.copy(this._panEnd).sub(this._panStart),Kp.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;Kp.x*=e,Kp.y*=t}Kp.multiplyScalar(this._eye.length()*this.panSpeed),bw.copy(this._eye).cross(this.object.up).setLength(Kp.x),bw.add(see.copy(this.object.up).setLength(Kp.y)),this.object.position.add(bw),this.target.add(bw),this.staticMoving?this._panStart.copy(this._panEnd):this._panStart.add(Kp.subVectors(this._panEnd,this._panStart).multiplyScalar(this.dynamicDampingFactor))}}_rotateCamera(){ww.set(this._moveCurr.x-this._movePrev.x,this._moveCurr.y-this._movePrev.y,0);let e=ww.length();e?(this._eye.copy(this.object.position).sub(this.target),$N.copy(this._eye).normalize(),Ew.copy(this.object.up).normalize(),EM.crossVectors(Ew,$N).normalize(),Ew.setLength(this._moveCurr.y-this._movePrev.y),EM.setLength(this._moveCurr.x-this._movePrev.x),ww.copy(Ew.add(EM)),bM.crossVectors(ww,this._eye).normalize(),e*=this.rotateSpeed,zA.setFromAxisAngle(bM,e),this._eye.applyQuaternion(zA),this.object.up.applyQuaternion(zA),this._lastAxis.copy(bM),this._lastAngle=e):!this.staticMoving&&this._lastAngle&&(this._lastAngle*=Math.sqrt(1-this.dynamicDampingFactor),this._eye.copy(this.object.position).sub(this.target),zA.setFromAxisAngle(this._lastAxis,this._lastAngle),this._eye.applyQuaternion(zA),this.object.up.applyQuaternion(zA)),this._movePrev.copy(this._moveCurr)}_zoomCamera(){let e;this.state===Ys.TOUCH_ZOOM_PAN?(e=this._touchZoomDistanceStart/this._touchZoomDistanceEnd,this._touchZoomDistanceStart=this._touchZoomDistanceEnd,this.object.isPerspectiveCamera?this._eye.multiplyScalar(e):this.object.isOrthographicCamera?(this.object.zoom=S0.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,e!==1&&e>0&&(this.object.isPerspectiveCamera?this._eye.multiplyScalar(e):this.object.isOrthographicCamera?(this.object.zoom=S0.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 yw.set((e-this.screen.left)/this.screen.width,(t-this.screen.top)/this.screen.height),yw}_getMouseOnCircle(e,t){return yw.set((e-this.screen.width*.5-this.screen.left)/(this.screen.width*.5),(this.screen.height+2*(this.screen.top-t))/this.screen.width),yw}_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){this._pointers.splice(t,1);return}}_trackPointer(e){let t=this._pointerPositions[e.pointerId];t===void 0&&(t=new ct,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 oee(r){this.enabled!==!1&&(this._pointers.length===0&&(this.domElement.setPointerCapture(r.pointerId),this.domElement.ownerDocument.addEventListener("pointermove",this._onPointerMove),this.domElement.ownerDocument.addEventListener("pointerup",this._onPointerUp)),this._addPointer(r),r.pointerType==="touch"?this._onTouchStart(r):this._onMouseDown(r))}function lee(r){this.enabled!==!1&&(r.pointerType==="touch"?this._onTouchMove(r):this._onMouseMove(r))}function uee(r){this.enabled!==!1&&(r.pointerType==="touch"?this._onTouchEnd(r):this._onMouseUp(),this._removePointer(r),this._pointers.length===0&&(this.domElement.releasePointerCapture(r.pointerId),this.domElement.ownerDocument.removeEventListener("pointermove",this._onPointerMove),this.domElement.ownerDocument.removeEventListener("pointerup",this._onPointerUp)))}function cee(r){this._removePointer(r)}function dee(){this.enabled!==!1&&(this.keyState=Ys.NONE,window.addEventListener("keydown",this._onKeyDown))}function fee(r){this.enabled!==!1&&(window.removeEventListener("keydown",this._onKeyDown),this.keyState===Ys.NONE&&(r.code===this.keys[Ys.ROTATE]&&!this.noRotate?this.keyState=Ys.ROTATE:r.code===this.keys[Ys.ZOOM]&&!this.noZoom?this.keyState=Ys.ZOOM:r.code===this.keys[Ys.PAN]&&!this.noPan&&(this.keyState=Ys.PAN)))}function hee(r){let e;switch(r.button){case 0:e=this.mouseButtons.LEFT;break;case 1:e=this.mouseButtons.MIDDLE;break;case 2:e=this.mouseButtons.RIGHT;break;default:e=-1}switch(e){case Rs.DOLLY:this.state=Ys.ZOOM;break;case Rs.ROTATE:this.state=Ys.ROTATE;break;case Rs.PAN:this.state=Ys.PAN;break;default:this.state=Ys.NONE}const t=this.keyState!==Ys.NONE?this.keyState:this.state;t===Ys.ROTATE&&!this.noRotate?(this._moveCurr.copy(this._getMouseOnCircle(r.pageX,r.pageY)),this._movePrev.copy(this._moveCurr)):t===Ys.ZOOM&&!this.noZoom?(this._zoomStart.copy(this._getMouseOnScreen(r.pageX,r.pageY)),this._zoomEnd.copy(this._zoomStart)):t===Ys.PAN&&!this.noPan&&(this._panStart.copy(this._getMouseOnScreen(r.pageX,r.pageY)),this._panEnd.copy(this._panStart)),this.dispatchEvent(xM)}function pee(r){const e=this.keyState!==Ys.NONE?this.keyState:this.state;e===Ys.ROTATE&&!this.noRotate?(this._movePrev.copy(this._moveCurr),this._moveCurr.copy(this._getMouseOnCircle(r.pageX,r.pageY))):e===Ys.ZOOM&&!this.noZoom?this._zoomEnd.copy(this._getMouseOnScreen(r.pageX,r.pageY)):e===Ys.PAN&&!this.noPan&&this._panEnd.copy(this._getMouseOnScreen(r.pageX,r.pageY))}function mee(){this.state=Ys.NONE,this.dispatchEvent(yM)}function gee(r){if(this.enabled!==!1&&this.noZoom!==!0){switch(r.preventDefault(),r.deltaMode){case 2:this._zoomStart.y-=r.deltaY*.025;break;case 1:this._zoomStart.y-=r.deltaY*.01;break;default:this._zoomStart.y-=r.deltaY*25e-5;break}this.dispatchEvent(xM),this.dispatchEvent(yM)}}function vee(r){this.enabled!==!1&&r.preventDefault()}function Aee(r){switch(this._trackPointer(r),this._pointers.length){case 1:this.state=Ys.TOUCH_ROTATE,this._moveCurr.copy(this._getMouseOnCircle(this._pointers[0].pageX,this._pointers[0].pageY)),this._movePrev.copy(this._moveCurr);break;default:this.state=Ys.TOUCH_ZOOM_PAN;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);break}this.dispatchEvent(xM)}function xee(r){switch(this._trackPointer(r),this._pointers.length){case 1:this._movePrev.copy(this._moveCurr),this._moveCurr.copy(this._getMouseOnCircle(r.pageX,r.pageY));break;default:const e=this._getSecondPointerPosition(r),t=r.pageX-e.x,n=r.pageY-e.y;this._touchZoomDistanceEnd=Math.sqrt(t*t+n*n);const i=(r.pageX+e.x)/2,s=(r.pageY+e.y)/2;this._panEnd.copy(this._getMouseOnScreen(i,s));break}}function yee(r){switch(this._pointers.length){case 0:this.state=Ys.NONE;break;case 1:this.state=Ys.TOUCH_ROTATE,this._moveCurr.copy(this._getMouseOnCircle(r.pageX,r.pageY)),this._movePrev.copy(this._moveCurr);break;case 2:this.state=Ys.TOUCH_ZOOM_PAN;for(let e=0;e<this._pointers.length;e++)if(this._pointers[e].pointerId!==r.pointerId){const t=this._pointerPositions[this._pointers[e].pointerId];this._moveCurr.copy(this._getMouseOnCircle(t.x,t.y)),this._movePrev.copy(this._moveCurr);break}break}this.dispatchEvent(yM)}const e7={type:"change"},wM={type:"start"},t7={type:"end"},Cw=new Tv,n7=new vd,bee=Math.cos(70*S0.DEG2RAD),Jo=new J,Tu=2*Math.PI,Aa={NONE:-1,ROTATE:0,DOLLY:1,PAN:2,TOUCH_ROTATE:3,TOUCH_PAN:4,TOUCH_DOLLY_PAN:5,TOUCH_DOLLY_ROTATE:6},CM=1e-6;class Eee extends Ib{constructor(e,t=null){super(e,t),this.state=Aa.NONE,this.target=new J,this.cursor=new J,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:Rs.ROTATE,MIDDLE:Rs.DOLLY,RIGHT:Rs.PAN},this.touches={ONE:la.ROTATE,TWO:la.DOLLY_PAN},this.target0=this.target.clone(),this.position0=this.object.position.clone(),this.zoom0=this.object.zoom,this._domElementKeyEvents=null,this._lastPosition=new J,this._lastQuaternion=new Wo,this._lastTargetPosition=new J,this._quat=new Wo().setFromUnitVectors(e.up,new J(0,1,0)),this._quatInverse=this._quat.clone().invert(),this._spherical=new sD,this._sphericalDelta=new sD,this._scale=1,this._panOffset=new J,this._rotateStart=new ct,this._rotateEnd=new ct,this._rotateDelta=new ct,this._panStart=new ct,this._panEnd=new ct,this._panDelta=new ct,this._dollyStart=new ct,this._dollyEnd=new ct,this._dollyDelta=new ct,this._dollyDirection=new J,this._mouse=new ct,this._performCursorZoom=!1,this._pointers=[],this._pointerPositions={},this._controlActive=!1,this._onPointerMove=Cee.bind(this),this._onPointerDown=wee.bind(this),this._onPointerUp=Pee.bind(this),this._onContextMenu=Nee.bind(this),this._onMouseWheel=See.bind(this),this._onKeyDown=Dee.bind(this),this._onTouchStart=Tee.bind(this),this._onTouchMove=Iee.bind(this),this._onMouseDown=Bee.bind(this),this._onMouseMove=Mee.bind(this),this._interceptControlDown=Fee.bind(this),this._interceptControlUp=Ree.bind(this),this.domElement!==null&&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.ownerDocument.removeEventListener("pointermove",this._onPointerMove),this.domElement.ownerDocument.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(){this._domElementKeyEvents!==null&&(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(e7),this.update(),this.state=Aa.NONE}update(e=null){const t=this.object.position;Jo.copy(t).sub(this.target),Jo.applyQuaternion(this._quat),this._spherical.setFromVector3(Jo),this.autoRotate&&this.state===Aa.NONE&&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+=Tu:n>Math.PI&&(n-=Tu),i<-Math.PI?i+=Tu:i>Math.PI&&(i-=Tu),n<=i?this._spherical.theta=Math.max(n,Math.min(i,this._spherical.theta)):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(),this.enableDamping===!0?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 s=!1;if(this.zoomToCursor&&this._performCursorZoom||this.object.isOrthographicCamera)this._spherical.radius=this._clampDistance(this._spherical.radius);else{const a=this._spherical.radius;this._spherical.radius=this._clampDistance(this._spherical.radius*this._scale),s=a!=this._spherical.radius}if(Jo.setFromSpherical(this._spherical),Jo.applyQuaternion(this._quatInverse),t.copy(this.target).add(Jo),this.object.lookAt(this.target),this.enableDamping===!0?(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 a=null;if(this.object.isPerspectiveCamera){const o=Jo.length();a=this._clampDistance(o*this._scale);const l=o-a;this.object.position.addScaledVector(this._dollyDirection,l),this.object.updateMatrixWorld(),s=!!l}else if(this.object.isOrthographicCamera){const o=new J(this._mouse.x,this._mouse.y,0);o.unproject(this.object);const l=this.object.zoom;this.object.zoom=Math.max(this.minZoom,Math.min(this.maxZoom,this.object.zoom/this._scale)),this.object.updateProjectionMatrix(),s=l!==this.object.zoom;const u=new J(this._mouse.x,this._mouse.y,0);u.unproject(this.object),this.object.position.sub(u).add(o),this.object.updateMatrixWorld(),a=Jo.length()}else console.warn("WARNING: OrbitControls.js encountered an unknown camera type - zoom to cursor disabled."),this.zoomToCursor=!1;a!==null&&(this.screenSpacePanning?this.target.set(0,0,-1).transformDirection(this.object.matrix).multiplyScalar(a).add(this.object.position):(Cw.origin.copy(this.object.position),Cw.direction.set(0,0,-1).transformDirection(this.object.matrix),Math.abs(this.object.up.dot(Cw.direction))<bee?this.object.lookAt(this.target):(n7.setFromNormalAndCoplanarPoint(this.object.up,this.target),Cw.intersectPlane(n7,this.target))))}else if(this.object.isOrthographicCamera){const a=this.object.zoom;this.object.zoom=Math.max(this.minZoom,Math.min(this.maxZoom,this.object.zoom/this._scale)),a!==this.object.zoom&&(this.object.updateProjectionMatrix(),s=!0)}return this._scale=1,this._performCursorZoom=!1,s||this._lastPosition.distanceToSquared(this.object.position)>CM||8*(1-this._lastQuaternion.dot(this.object.quaternion))>CM||this._lastTargetPosition.distanceToSquared(this.target)>CM?(this.dispatchEvent(e7),this._lastPosition.copy(this.object.position),this._lastQuaternion.copy(this.object.quaternion),this._lastTargetPosition.copy(this.target),!0):!1}_getAutoRotationAngle(e){return e!==null?Tu/60*this.autoRotateSpeed*e:Tu/60/60*this.autoRotateSpeed}_getZoomScale(e){const t=Math.abs(e*.01);return Math.pow(.95,this.zoomSpeed*t)}_rotateLeft(e){this._sphericalDelta.theta-=e}_rotateUp(e){this._sphericalDelta.phi-=e}_panLeft(e,t){Jo.setFromMatrixColumn(t,0),Jo.multiplyScalar(-e),this._panOffset.add(Jo)}_panUp(e,t){this.screenSpacePanning===!0?Jo.setFromMatrixColumn(t,1):(Jo.setFromMatrixColumn(t,0),Jo.crossVectors(this.object.up,Jo)),Jo.multiplyScalar(e),this._panOffset.add(Jo)}_pan(e,t){const n=this.domElement;if(this.object.isPerspectiveCamera){const i=this.object.position;Jo.copy(i).sub(this.target);let s=Jo.length();s*=Math.tan(this.object.fov/2*Math.PI/180),this._panLeft(2*e*s/n.clientHeight,this.object.matrix),this._panUp(2*t*s/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,s=t-n.top,a=n.width,o=n.height;this._mouse.x=i/a*2-1,this._mouse.y=-(s/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(Tu*this._rotateDelta.x/t.clientHeight),this._rotateUp(Tu*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(Tu*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(-Tu*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(Tu*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(-Tu*this.keyRotateSpeed/this.domElement.clientHeight):this.enablePan&&this._pan(-this.keyPanSpeed,0),t=!0;break}t&&(e.preventDefault(),this.update())}_handleTouchStartRotate(e){if(this._pointers.length===1)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(this._pointers.length===1)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,s=Math.sqrt(n*n+i*i);this._dollyStart.set(0,s)}_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(this._pointers.length==1)this._rotateEnd.set(e.pageX,e.pageY);else{const n=this._getSecondPointerPosition(e),i=.5*(e.pageX+n.x),s=.5*(e.pageY+n.y);this._rotateEnd.set(i,s)}this._rotateDelta.subVectors(this._rotateEnd,this._rotateStart).multiplyScalar(this.rotateSpeed);const t=this.domElement;this._rotateLeft(Tu*this._rotateDelta.x/t.clientHeight),this._rotateUp(Tu*this._rotateDelta.y/t.clientHeight),this._rotateStart.copy(this._rotateEnd)}_handleTouchMovePan(e){if(this._pointers.length===1)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,s=Math.sqrt(n*n+i*i);this._dollyEnd.set(0,s),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 a=(e.pageX+t.x)*.5,o=(e.pageY+t.y)*.5;this._updateZoomParameters(a,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){this._pointers.splice(t,1);return}}_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];t===void 0&&(t=new ct,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;break}return e.ctrlKey&&!this._controlActive&&(n.deltaY*=10),n}}function wee(r){this.enabled!==!1&&(this._pointers.length===0&&(this.domElement.setPointerCapture(r.pointerId),this.domElement.ownerDocument.addEventListener("pointermove",this._onPointerMove),this.domElement.ownerDocument.addEventListener("pointerup",this._onPointerUp)),!this._isTrackingPointer(r)&&(this._addPointer(r),r.pointerType==="touch"?this._onTouchStart(r):this._onMouseDown(r)))}function Cee(r){this.enabled!==!1&&(r.pointerType==="touch"?this._onTouchMove(r):this._onMouseMove(r))}function Pee(r){switch(this._removePointer(r),this._pointers.length){case 0:this.domElement.releasePointerCapture(r.pointerId),this.domElement.ownerDocument.removeEventListener("pointermove",this._onPointerMove),this.domElement.ownerDocument.removeEventListener("pointerup",this._onPointerUp),this.dispatchEvent(t7),this.state=Aa.NONE;break;case 1:const e=this._pointers[0],t=this._pointerPositions[e];this._onTouchStart({pointerId:e,pageX:t.x,pageY:t.y});break}}function Bee(r){let e;switch(r.button){case 0:e=this.mouseButtons.LEFT;break;case 1:e=this.mouseButtons.MIDDLE;break;case 2:e=this.mouseButtons.RIGHT;break;default:e=-1}switch(e){case Rs.DOLLY:if(this.enableZoom===!1)return;this._handleMouseDownDolly(r),this.state=Aa.DOLLY;break;case Rs.ROTATE:if(r.ctrlKey||r.metaKey||r.shiftKey){if(this.enablePan===!1)return;this._handleMouseDownPan(r),this.state=Aa.PAN}else{if(this.enableRotate===!1)return;this._handleMouseDownRotate(r),this.state=Aa.ROTATE}break;case Rs.PAN:if(r.ctrlKey||r.metaKey||r.shiftKey){if(this.enableRotate===!1)return;this._handleMouseDownRotate(r),this.state=Aa.ROTATE}else{if(this.enablePan===!1)return;this._handleMouseDownPan(r),this.state=Aa.PAN}break;default:this.state=Aa.NONE}this.state!==Aa.NONE&&this.dispatchEvent(wM)}function Mee(r){switch(this.state){case Aa.ROTATE:if(this.enableRotate===!1)return;this._handleMouseMoveRotate(r);break;case Aa.DOLLY:if(this.enableZoom===!1)return;this._handleMouseMoveDolly(r);break;case Aa.PAN:if(this.enablePan===!1)return;this._handleMouseMovePan(r);break}}function See(r){this.enabled===!1||this.enableZoom===!1||this.state!==Aa.NONE||(r.preventDefault(),this.dispatchEvent(wM),this._handleMouseWheel(this._customWheelEvent(r)),this.dispatchEvent(t7))}function Dee(r){this.enabled!==!1&&this._handleKeyDown(r)}function Tee(r){switch(this._trackPointer(r),this._pointers.length){case 1:switch(this.touches.ONE){case la.ROTATE:if(this.enableRotate===!1)return;this._handleTouchStartRotate(r),this.state=Aa.TOUCH_ROTATE;break;case la.PAN:if(this.enablePan===!1)return;this._handleTouchStartPan(r),this.state=Aa.TOUCH_PAN;break;default:this.state=Aa.NONE}break;case 2:switch(this.touches.TWO){case la.DOLLY_PAN:if(this.enableZoom===!1&&this.enablePan===!1)return;this._handleTouchStartDollyPan(r),this.state=Aa.TOUCH_DOLLY_PAN;break;case la.DOLLY_ROTATE:if(this.enableZoom===!1&&this.enableRotate===!1)return;this._handleTouchStartDollyRotate(r),this.state=Aa.TOUCH_DOLLY_ROTATE;break;default:this.state=Aa.NONE}break;default:this.state=Aa.NONE}this.state!==Aa.NONE&&this.dispatchEvent(wM)}function Iee(r){switch(this._trackPointer(r),this.state){case Aa.TOUCH_ROTATE:if(this.enableRotate===!1)return;this._handleTouchMoveRotate(r),this.update();break;case Aa.TOUCH_PAN:if(this.enablePan===!1)return;this._handleTouchMovePan(r),this.update();break;case Aa.TOUCH_DOLLY_PAN:if(this.enableZoom===!1&&this.enablePan===!1)return;this._handleTouchMoveDollyPan(r),this.update();break;case Aa.TOUCH_DOLLY_ROTATE:if(this.enableZoom===!1&&this.enableRotate===!1)return;this._handleTouchMoveDollyRotate(r),this.update();break;default:this.state=Aa.NONE}}function Nee(r){this.enabled!==!1&&r.preventDefault()}function Fee(r){r.key==="Control"&&(this._controlActive=!0,this.domElement.getRootNode().addEventListener("keyup",this._interceptControlUp,{passive:!0,capture:!0}))}function Ree(r){r.key==="Control"&&(this._controlActive=!1,this.domElement.getRootNode().removeEventListener("keyup",this._interceptControlUp,{passive:!0,capture:!0}))}const Lee={type:"change"},r7=1e-6,i7=new Wo;class Oee extends Ib{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 J(0,0,0),this._rotationVector=new J(0,0,0),this._lastQuaternion=new Wo,this._lastPosition=new J,this._status=0,this._onKeyDown=zee.bind(this),this._onKeyUp=Hee.bind(this),this._onPointerMove=kee.bind(this),this._onPointerDown=Uee.bind(this),this._onPointerUp=Vee.bind(this),this._onPointerCancel=jee.bind(this),this._onContextMenu=Xee.bind(this),t!==null&&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(this.enabled===!1)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),i7.set(this._rotationVector.x*i,this._rotationVector.y*i,this._rotationVector.z*i,1).normalize(),t.quaternion.multiply(i7),(this._lastPosition.distanceToSquared(t.position)>r7||8*(1-this._lastQuaternion.dot(t.quaternion))>r7)&&(this.dispatchEvent(Lee),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 zee(r){if(!(r.altKey||this.enabled===!1)){switch(r.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;break}this._updateMovementVector(),this._updateRotationVector()}}function Hee(r){if(this.enabled!==!1){switch(r.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;break}this._updateMovementVector(),this._updateRotationVector()}}function Uee(r){if(this.enabled!==!1)if(this.dragToLook)this._status++;else{switch(r.button){case 0:this._moveState.forward=1;break;case 2:this._moveState.back=1;break}this._updateMovementVector()}}function kee(r){if(this.enabled!==!1&&(!this.dragToLook||this._status>0)){const e=this._getContainerDimensions(),t=e.size[0]/2,n=e.size[1]/2;this._moveState.yawLeft=-(r.pageX-e.offset[0]-t)/t,this._moveState.pitchDown=(r.pageY-e.offset[1]-n)/n,this._updateRotationVector()}}function Vee(r){if(this.enabled!==!1){if(this.dragToLook)this._status--,this._moveState.yawLeft=this._moveState.pitchDown=0;else{switch(r.button){case 0:this._moveState.forward=0;break;case 2:this._moveState.back=0;break}this._updateMovementVector()}this._updateRotationVector()}}function jee(){this.enabled!==!1&&(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 Xee(r){this.enabled!==!1&&r.preventDefault()}const Gee={name:"CopyShader",uniforms:{tDiffuse:{value:null},opacity:{value:1}},vertexShader:`

		varying vec2 vUv;

		void main() {

			vUv = uv;
			gl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );

		}`,fragmentShader:`

		uniform float opacity;

		uniform sampler2D tDiffuse;

		varying vec2 vUv;

		void main() {

			vec4 texel = texture2D( tDiffuse, vUv );
			gl_FragColor = opacity * texel;


		}`};class Pw{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 Wee=new Km(-1,1,1,-1,0,1);class Qee extends Ni{constructor(){super(),this.setAttribute("position",new yr([-1,3,0,-1,-1,0,3,-1,0],3)),this.setAttribute("uv",new yr([0,2,0,0,2,0],2))}}const Zee=new Qee;class Yee{constructor(e){this._mesh=new Gs(Zee,e)}dispose(){this._mesh.geometry.dispose()}render(e){e.render(this._mesh,Wee)}get material(){return this._mesh.material}set material(e){this._mesh.material=e}}class Jee extends Pw{constructor(e,t="tDiffuse"){super(),this.textureID=t,this.uniforms=null,this.material=null,e instanceof $u?(this.uniforms=e.uniforms,this.material=e):e&&(this.uniforms=US.clone(e.uniforms),this.material=new $u({name:e.name!==void 0?e.name:"unspecified",defines:Object.assign({},e.defines),uniforms:this.uniforms,vertexShader:e.vertexShader,fragmentShader:e.fragmentShader})),this._fsQuad=new Yee(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 s7 extends Pw{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(),s=e.state;s.buffers.color.setMask(!1),s.buffers.depth.setMask(!1),s.buffers.color.setLocked(!0),s.buffers.depth.setLocked(!0);let a,o;this.inverse?(a=0,o=1):(a=1,o=0),s.buffers.stencil.setTest(!0),s.buffers.stencil.setOp(i.REPLACE,i.REPLACE,i.REPLACE),s.buffers.stencil.setFunc(i.ALWAYS,a,4294967295),s.buffers.stencil.setClear(o),s.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),s.buffers.color.setLocked(!1),s.buffers.depth.setLocked(!1),s.buffers.color.setMask(!0),s.buffers.depth.setMask(!0),s.buffers.stencil.setLocked(!1),s.buffers.stencil.setFunc(i.EQUAL,1,4294967295),s.buffers.stencil.setOp(i.KEEP,i.KEEP,i.KEEP),s.buffers.stencil.setLocked(!0)}}class Kee extends Pw{constructor(){super(),this.needsSwap=!1}render(e){e.state.buffers.stencil.setLocked(!1),e.state.buffers.stencil.setTest(!1)}}class qee{constructor(e,t){if(this.renderer=e,this._pixelRatio=e.getPixelRatio(),t===void 0){const n=e.getSize(new ct);this._width=n.width,this._height=n.height,t=new fd(this._width*this._pixelRatio,this._height*this._pixelRatio,{type:pa}),t.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 Jee(Gee),this.copyPass.material.blending=Xa,this.clock=new j1}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);t!==-1&&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){e===void 0&&(e=this.clock.getDelta());const t=this.renderer.getRenderTarget();let n=!1;for(let i=0,s=this.passes.length;i<s;i++){const a=this.passes[i];if(a.enabled!==!1){if(a.renderToScreen=this.renderToScreen&&this.isLastEnabledPass(i),a.render(this.renderer,this.writeBuffer,this.readBuffer,e,n),a.needsSwap){if(n){const o=this.renderer.getContext(),l=this.renderer.state.buffers.stencil;l.setFunc(o.NOTEQUAL,1,4294967295),this.copyPass.render(this.renderer,this.writeBuffer,this.readBuffer,e),l.setFunc(o.EQUAL,1,4294967295)}this.swapBuffers()}s7!==void 0&&(a instanceof s7?n=!0:a instanceof Kee&&(n=!1))}}this.renderer.setRenderTarget(t)}reset(e){if(e===void 0){const t=this.renderer.getSize(new ct);this._pixelRatio=this.renderer.getPixelRatio(),this._width=t.width,this._height=t.height,e=this.renderTarget1.clone(),e.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 s=0;s<this.passes.length;s++)this.passes[s].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 _ee extends Pw{constructor(e,t,n=null,i=null,s=null){super(),this.scene=e,this.camera=t,this.overrideMaterial=n,this.clearColor=i,this.clearAlpha=s,this.clear=!0,this.clearDepth=!1,this.needsSwap=!1,this.isRenderPass=!0,this._oldClearColor=new Vn}render(e,t,n){const i=e.autoClear;e.autoClear=!1;let s,a;this.overrideMaterial!==null&&(a=this.scene.overrideMaterial,this.scene.overrideMaterial=this.overrideMaterial),this.clearColor!==null&&(e.getClearColor(this._oldClearColor),e.setClearColor(this.clearColor,e.getClearAlpha())),this.clearAlpha!==null&&(s=e.getClearAlpha(),e.setClearAlpha(this.clearAlpha)),this.clearDepth==!0&&e.clearDepth(),e.setRenderTarget(this.renderToScreen?null:n),this.clear===!0&&e.clear(e.autoClearColor,e.autoClearDepth,e.autoClearStencil),e.render(this.scene,this.camera),this.clearColor!==null&&e.setClearColor(this._oldClearColor),this.clearAlpha!==null&&e.setClearAlpha(s),this.overrideMaterial!==null&&(this.scene.overrideMaterial=a),e.autoClear=i}}var kc=O(60499),$ee=O(15793),ete=O(84255),tte=O(78419);function a7(){var r;return r=arguments.length-1,r<0||arguments.length<=r?void 0:arguments[r]}function nte(r){return-r}function rte(r,e){return r+e}function ite(r,e){return r-e}function ste(r,e){return r*e}function ate(r,e){return r/e}function ote(){return Math.max.apply(Math,arguments)}function lte(){return Math.min.apply(Math,arguments)}function ute(){return Array.of.apply(Array,arguments)}var Afe={symbols:{"*":{infix:{symbol:"*",f:ste,notation:"infix",precedence:4,rightToLeft:0,argCount:2},symbol:"*",regSymbol:"\\*"},"/":{infix:{symbol:"/",f:ate,notation:"infix",precedence:4,rightToLeft:0,argCount:2},symbol:"/",regSymbol:"/"},"+":{infix:{symbol:"+",f:rte,notation:"infix",precedence:2,rightToLeft:0,argCount:2},prefix:{symbol:"+",f:a7,notation:"prefix",precedence:3,rightToLeft:0,argCount:1},symbol:"+",regSymbol:"\\+"},"-":{infix:{symbol:"-",f:ite,notation:"infix",precedence:2,rightToLeft:0,argCount:2},prefix:{symbol:"-",f:nte,notation:"prefix",precedence:3,rightToLeft:0,argCount:1},symbol:"-",regSymbol:"-"},",":{infix:{symbol:",",f:ute,notation:"infix",precedence:1,rightToLeft:0,argCount:2},symbol:",",regSymbol:","},"(":{prefix:{symbol:"(",f:a7,notation:"prefix",precedence:0,rightToLeft:0,argCount:1},symbol:"(",regSymbol:"\\("},")":{postfix:{symbol:")",f:void 0,notation:"postfix",precedence:0,rightToLeft:0,argCount:1},symbol:")",regSymbol:"\\)"},min:{func:{symbol:"min",f:lte,notation:"func",precedence:0,rightToLeft:0,argCount:1},symbol:"min",regSymbol:"min\\b"},max:{func:{symbol:"max",f:ote,notation:"func",precedence:0,rightToLeft:0,argCount:1},symbol:"max",regSymbol:"max\\b"}}},o7=null,xfe={1:`Passed invalid arguments to hsl, please pass multiple numbers e.g. hsl(360, 0.75, 0.4) or an object e.g. rgb({ hue: 255, saturation: 0.4, lightness: 0.75 }).

`,2:`Passed invalid arguments to hsla, please pass multiple numbers e.g. hsla(360, 0.75, 0.4, 0.7) or an object e.g. rgb({ hue: 255, saturation: 0.4, lightness: 0.75, alpha: 0.7 }).

`,3:`Passed an incorrect argument to a color function, please pass a string representation of a color.

`,4:`Couldn't generate valid rgb string from %s, it returned %s.

`,5:`Couldn't parse the color string. Please provide the color as a string in hex, rgb, rgba, hsl or hsla notation.

`,6:`Passed invalid arguments to rgb, please pass multiple numbers e.g. rgb(255, 205, 100) or an object e.g. rgb({ red: 255, green: 205, blue: 100 }).

`,7:`Passed invalid arguments to rgba, please pass multiple numbers e.g. rgb(255, 205, 100, 0.75) or an object e.g. rgb({ red: 255, green: 205, blue: 100, alpha: 0.75 }).

`,8:`Passed invalid argument to toColorString, please pass a RgbColor, RgbaColor, HslColor or HslaColor object.

`,9:`Please provide a number of steps to the modularScale helper.

`,10:`Please pass a number or one of the predefined scales to the modularScale helper as the ratio.

`,11:`Invalid value passed as base to modularScale, expected number or em string but got "%s"

`,12:`Expected a string ending in "px" or a number passed as the first argument to %s(), got "%s" instead.

`,13:`Expected a string ending in "px" or a number passed as the second argument to %s(), got "%s" instead.

`,14:`Passed invalid pixel value ("%s") to %s(), please pass a value like "12px" or 12.

`,15:`Passed invalid base value ("%s") to %s(), please pass a value like "12px" or 12.

`,16:`You must provide a template to this method.

`,17:`You passed an unsupported selector state to this method.

`,18:`minScreen and maxScreen must be provided as stringified numbers with the same units.

`,19:`fromSize and toSize must be provided as stringified numbers with the same units.

`,20:`expects either an array of objects or a single object with the properties prop, fromSize, and toSize.

`,21:"expects the objects in the first argument array to have the properties `prop`, `fromSize`, and `toSize`.\n\n",22:"expects the first argument object to have the properties `prop`, `fromSize`, and `toSize`.\n\n",23:`fontFace expects a name of a font-family.

`,24:`fontFace expects either the path to the font file(s) or a name of a local copy.

`,25:`fontFace expects localFonts to be an array.

`,26:`fontFace expects fileFormats to be an array.

`,27:`radialGradient requries at least 2 color-stops to properly render.

`,28:`Please supply a filename to retinaImage() as the first argument.

`,29:`Passed invalid argument to triangle, please pass correct pointingDirection e.g. 'right'.

`,30:"Passed an invalid value to `height` or `width`. Please provide a pixel based unit.\n\n",31:`The animation shorthand only takes 8 arguments. See the specification for more information: http://mdn.io/animation

`,32:`To pass multiple animations please supply them in arrays, e.g. animation(['rotate', '2s'], ['move', '1s'])
To pass a single animation please supply them in simple values, e.g. animation('rotate', '2s')

`,33:`The animation shorthand arrays can only have 8 elements. See the specification for more information: http://mdn.io/animation

`,34:`borderRadius expects a radius value as a string or number as the second argument.

`,35:`borderRadius expects one of "top", "bottom", "left" or "right" as the first argument.

`,36:`Property must be a string value.

`,37:`Syntax Error at %s.

`,38:`Formula contains a function that needs parentheses at %s.

`,39:`Formula is missing closing parenthesis at %s.

`,40:`Formula has too many closing parentheses at %s.

`,41:`All values in a formula must have the same unit or be unitless.

`,42:`Please provide a number of steps to the modularScale helper.

`,43:`Please pass a number or one of the predefined scales to the modularScale helper as the ratio.

`,44:`Invalid value passed as base to modularScale, expected number or em/rem string but got %s.

`,45:`Passed invalid argument to hslToColorString, please pass a HslColor or HslaColor object.

`,46:`Passed invalid argument to rgbToColorString, please pass a RgbColor or RgbaColor object.

`,47:`minScreen and maxScreen must be provided as stringified numbers with the same units.

`,48:`fromSize and toSize must be provided as stringified numbers with the same units.

`,49:`Expects either an array of objects or a single object with the properties prop, fromSize, and toSize.

`,50:`Expects the objects in the first argument array to have the properties prop, fromSize, and toSize.

`,51:`Expects the first argument object to have the properties prop, fromSize, and toSize.

`,52:`fontFace expects either the path to the font file(s) or a name of a local copy.

`,53:`fontFace expects localFonts to be an array.

`,54:`fontFace expects fileFormats to be an array.

`,55:`fontFace expects a name of a font-family.

`,56:`linearGradient requries at least 2 color-stops to properly render.

`,57:`radialGradient requries at least 2 color-stops to properly render.

`,58:`Please supply a filename to retinaImage() as the first argument.

`,59:`Passed invalid argument to triangle, please pass correct pointingDirection e.g. 'right'.

`,60:"Passed an invalid value to `height` or `width`. Please provide a pixel based unit.\n\n",61:`Property must be a string value.

`,62:`borderRadius expects a radius value as a string or number as the second argument.

`,63:`borderRadius expects one of "top", "bottom", "left" or "right" as the first argument.

`,64:`The animation shorthand only takes 8 arguments. See the specification for more information: http://mdn.io/animation.

`,65:`To pass multiple animations please supply them in arrays, e.g. animation(['rotate', '2s'], ['move', '1s'])\\nTo pass a single animation please supply them in simple values, e.g. animation('rotate', '2s').

`,66:`The animation shorthand arrays can only have 8 elements. See the specification for more information: http://mdn.io/animation.

`,67:`You must provide a template to this method.

`,68:`You passed an unsupported selector state to this method.

`,69:`Expected a string ending in "px" or a number passed as the first argument to %s(), got %s instead.

`,70:`Expected a string ending in "px" or a number passed as the second argument to %s(), got %s instead.

`,71:`Passed invalid pixel value %s to %s(), please pass a value like "12px" or 12.

`,72:`Passed invalid base value %s to %s(), please pass a value like "12px" or 12.

`,73:`Please provide a valid CSS variable.

`,74:`CSS variable not found and no default was provided.

`,75:`important requires a valid style object, got a %s instead.

`,76:`fromSize and toSize must be provided as stringified numbers with the same units as minScreen and maxScreen.

`,77:`remToPx expects a value in "rem" but you provided it in "%s".

`,78:`base must be set in "px" or "%" but you set it in "%s".
`};function yfe(){for(var r=arguments.length,e=new Array(r),t=0;t<r;t++)e[t]=arguments[t];var n=e[0],i=[],s;for(s=1;s<e.length;s+=1)i.push(e[s]);return i.forEach(function(a){n=n.replace(/%[a-z]/,a)}),n}var xi=function(r){(0,ete.Z)(e,r);function e(t){var n;if(1)n=r.call(this,"An error occurred. 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",eae="data:image/png;base64,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",Cae="data:image/png;base64,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",Pae="data:image/png;base64,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",Bae="data:image/png;base64,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",Coe="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAUwAAAFACAYAAADXrEUkAAAAAXNSR0IArs4c6QAAIABJREFUeF7svduPJNl95/f7nRPXvNW9q2umhtNo9QylniV3id5dL1dase01DAsg7Kde7C5gQIABGjDgB/th/UjOP+AHPxKw18YCBuz2iwEZhGUIaK60S4tyWxSpae0MW6MeTc3UVFfXNS9xPednfc+JqMqqvkx1T8/wFsFhR2RkRGTmychPfX/Xw9Qt3Qh0I9CNQDcCFxoBvtBR3UHdCHQj0I1ANwLUAbO7CboR6EagG4ELjkAHzAsOVHdYNwLdCHQj0AGzuwe6EehGoBuBC45AB8wLDlR3WDcC3Qh0I9ABs7sHuhHoRqAbgQuOQAfMCw5Ud1g3At0IdCPQAbO7B7oR6EagG4ELjkAHzAsOVHdYNwLdCHQj0AGzuwe6EehGoBuBC45AB8wLDlR3WDcC3Qh0I9ABs7sHuhHoRqAbgQuOQAfMCw5Ud1g3At0IdCPQAbO7B7oR6EagG4ELjkAHzAsOVHdYNwLdCHQj0AGzuwe6EehGoBuBC45AB8wLDlR3WDcC3Qh0I9ABs7sHvuARkGffc/IFv51nvpvHnvyi390XPBjdy33aCHTA/LQR6p5/ySPQAfMlD2h3uS9wBDpgfoGD3b0URqADZncf/OKOQAfMX9zv7hf0nXfA/AX94rq3TdTN6dPdBfMjcA5m5zx2nQPvxe6Wx1TJ4zu6oX2xof3Cz+oU5hc+5D/PL9gB8/P4djpgfh6j+rO5ZgfMn824/5y+agfMz+OL6YD5eYzqz+aaHTB/NuP+xb6qnIKws/2+2KF/3ld7Nly5+/qed0Bf8vEdMF/ygP5cXu4LBubbb3+Kb/zbTx6lp+x+qUP69vNe7SknfPvb9LnAqwPm835BX+zxHTC/2PH+2bxaB8yTce+A+bO5BX9ZXrUD5i/LN/msz9EBswPmr8J9/gV8xg6YX8Agfz4vMeeXfInG4Rlzes5Gfh5z+fbt50hXu3Xx0XnWobcvfpmzRz7HibduPd0M/1TlOnfAyzLn+cyvt/Nvvugt8DzndcB8ntH6uTq2A+b81/Ec3OuA+XN1H/9ivZkOmL9Y39fcu+2A2QFzfgQ6hflF/JQ7YH4Ro/y5vMbFgPlYxPqcbf08pvazPsZ5M/zevTmz/BtPOfMm0TfuENHNTx+gZx3SXgLriyzfP3/Q/ImPPekPvn6dBJ8J6/b0Z5noF3kfOObtZ9jyn2a6dyb5RUf55R3XAfPljeXncKWLQfFZL/xZgPmYL3LOiTjvT7xz5xk+S5DuKVDEU9+9S3zjcxi5p13y7rkn3rwx55d8DvLevEnyTDfA3JPP9H1+BmCe0ZfnP3BXfvm53FUdMD+XYX1ZF+2A+bJGsr1OB8yXPaK/WtfrgPlz/X13wHzZX08HzJc9or9a1+uA+TP/vj87FBtf2Ml3+e1nOCYvamY/a1hggsMkPTHFbxK9d/fULN9+/3T7OhHde4sI6yctg+g5UpBexnf1U6L7dP/kSpdfvyb35q/7zvkXaZ69R7TxzetCc8R9882zaUYYkye9xcdM92fY8vPm++P+zbP2+7e//e0LJ5R1/s6XcfN07d1ezih+pqv8fAHzqf7IuajLE32Pc47I9+cDPkT01jPG54OfATCBzHaZvH7tU6BzitOr2fWTYz9Vqc59ZsSRrs/DtAPmZ/rF/CxP7hTm5zj6Mldhw8yCx1iffckOmJ/jV/D4pX+KXR0wv9Ax/yV6sQ6Yn+OXOQ/MJ7wMxl7aKPZ3vvM2iXyb3m7sMJhbb7/9Nl/U7JqPhj/JJL9NxLfwendIffwe8SvbJB9/k/iVuSgxsn8ukOHjPsrdORPc7ZhTmP/2e6TmP++1J3z4NCV+8IDoyu8S7W4Rb324RZuvbRLWWJY2NuVge4uxfhlf0UFAvFSTuyZtbdLS9IHQlSv0wYMHtLx+5SmvAbA6wrrlH176Hfu093JjPtp+7iAE30+ylZoUpo33iLe3STY27rrf4N27d+mf/bNvyfe//zZdv35dbt26Jf/kn9zmt966NffePoNJjoYo32ldBl3O5oveUx0wX3TkLnBeA8wzY9z6pQDI73wHzkb/I3gCIB1Q2674532Pt55RJwiz+vvfv0Pf+MZN8muimzdv0p07d9z6BHbn8nlgSs+bz+fN5TfmPjMwkgbEWU2C/VtbD3hz84pgTVeIrly5Qg8ePHDrdtneIv76pv/R/uAHW/zaa5v0YQPIjY1N2QbMmiWKNJflhkQvaLJvb9+ljY1XaHv7Y1pZWZf2tdz65B0Bzpt4927PxuambG9tMdZuxwP33xOX7C9I6A2iSek/zycf3Gf4Q7HG43/8+jV555179NZb3nt74hp9h+jqLZK7371LN27coLt3v+vcoq+8+aZ/ze8j5/OmrK0R7+6SrK3dORmT3Zs3z4L9nGl/1v/5Nu6p+T/Abhv32Vl/Jl60A+gFfs7ukA6YFx2pFzjuWcBsL/esAM38Sz4vMOfPvXlONr4MYG4Fp/fOKRKJtreJN75OAjg+aciinbn9rxDRx6CFP3Jvd+fcOesvMOo4ZefMeStr66eg+Zhou31dd9T22WPXN5pjt4g+3GxQukVrG5uyu73FWLcwzRr4P+lNvt6AtH3uPDBPg0d3TzbfvHFD3vvuXX7zzRtzYDzNqn8eYD5j4DpgvuBd1QHzMwzcRU59FjDfecebW9ev33aQgAl2+/ZtxvpJ175zh5RXHB44TUS2VaFnToHCfO89/8PD+sYNatSMVzWoWMkykvQGceZVLL1/7x4jlj1oFNLrr1+T/+udLb20dmoSt2Dc3SVeu0UCUxrnQqOdLJtEr7XC7dwHwXF3t/054e4Or62ty24DSWy/++49tby8Mvf5T4EZBMR1TYI1zm+3sX58vHZof3+Pca12vb6+Tjs7O0Tr64SrblmSUBFXdtudv7e7yytra9Lic8VsyJ7e5mxjQxpqUitN1zZIID3/dJd4ae3JkfG/f4nOmO/ngfn+7Xt89ep1ef/924yw0sbVq/5z3CV6EjCHwyG/f+OGXWtEzi6RrN3xKrT9/PMKs72XsG7uL7p9+7a7z5jPv+dOYV7k99wB86Kj9ILHiYiC7xCn374NKGLDXwzbJ/uecH0cNnc44ccBP1hbZehBCJMOEDwLxPnLtSWKrXn4B39wn+ka0bU3rhH99D698TunHkZsPXjg3y/8i/E1+BaJDva2+ZUNoqzckDTaZqIN2ngFaNk4ealGJLpd794hRZfOfqjdh0RvXSJ656Hfj+2HD4kuzfkADvgRHx8q9/r7RLTs1vi33fZr9/zePi2vLLu1e77Zxpqafdg/WlwWokdUGZFLa2v0zu4ureE9XFqj3Ye7tHZp7Ynf7i4I99Yu5bUV+oRo/TLRg2pdXnEftMHqx/j827SyviF7P9rmlZVWnRJtAKrNArP+JzXJtWtE97/nd2Ks798nwr42CPX666XgjxbKL2Gmw2Py3eYabvvuqavY+TzfvCFwuWCB+2V39zZ8n0/8PA0sYZbLeb94l3L0xCF74s7OJL/4WD33kfPAbE++aDezO+fcJeeDMfNBFwCzXdp65xaU16+7H+bp93wuAhM0gHQYgPp7zV9pb4f479wg2WkUodvXmszrRJd31slJNQev0+uDk/c18cr8aM09WCWiw8Onu4LG6iW5iQ5O38Bw4ayi8ohtlj1A1T+/R0R4q1hjGZm58x4Slb9BctbaPzX9y+rU7F9ZJ8H4YY3rFDDd55yhm3Oq+DSk5ONLr/8OCTWZTC04T97ruVym8flA01xN/NNyQhu/+BlV3gHz4j/tDpgXH6vnPhLAfPvOnTMR41Yh3rx5U+7cucNY48LtNtZ4/N7Nm4zojJOPf+Pq+xY51YG6a3f87dv3lDfp7vFbcyrtgw8ihlL5ILrOrYLcekCMHyn8jptX/Plu3xWS3R/4iDYU0Z//OamVv+Ofv39vR/37/9G6vffjHff85fV1evcv7rFTZBBl70AdrtHD3V06PmAeLa3K8cEjvra0KgBmeLjPUHfHh/vsKNQs4dEhT8aKB8MFmYyPeDD0EerJ+JCJFmkWHPl7cmGB6OjIr4moZ0hmmhhrPJ5Njrg3WBCsn/zFnJ7fG5AMDMlEE2N9QAc0HTP3hyJ0sESDIQmg+eCQ+MoiCYA5PtznV4fLFp8J11+hVfp4aVfW3IenRp36NZZ0eN0e7O3w0sq6AJQYv2vX1+3ezjZn60bmIk20VtTSBsiyTf/5d7Ye8Hp2ReiN+z4w/8Y1er28J+/gLx4RXSUSBOWuZo0L5f17vHbrun3vro+yu2U+qf5bN4Tu3HG+Gyw3iQR/hG+ScxV0wHzyTfOpeztgfuoQvfgBAOYdOptic9G0HdeU4oZL33HLt5pt7GvV4wcfeDX2xhsnvzFn3eH3Bku7NflaM9tdaD5CAzV117+/vT3ila+Q7LUKb53ob0NANSoSm8HuLjtrlogO9tfca0MxYjmjGt8AcOaU4tLpGAZHAOPpskiLJw8mc+qyZSXWWM7x87Ev5czxDWfbffXwLCAO6fDk/IFdPOsDnVOmdEA0bM5FgtHfXSR5tznz2jLJO7Tr8blLVF5fO6s+G/G5skZyD77O6vQ9/K2Vs/7N9s1AhN68QuKSme4TgvD0vUaCXnvDm/PXrvkcUviY36F7dPW6T6Z3f1ubtbtfvuUqsVpezo9XB8wX/0m/JPPnM7yBX8pTm4T17/xNvsa3zwFz/vOez2U8a1rfY+Tj3XPBGN9f7IP79/n1a74y5Wmlhvdhyt8naqPY8Tbxa42ZjfPu7ZM6motwrzUuvON9YkDgYL+5J1aIPv4RKZqD3XTsnwPiDq/4NZbZmLgRgu5xMDl7X80/zmbENHz8W89mE3ftdH0g2XTCeUacpCR5NmWiPiXpQPJswlg/+56Z+KcnA/xDaW8gJ9fuPX5u1Seh49Mr7g9OwZbOmeTlkCTaIi7nnl8vGvDtE42uktCj0+sMr/nn1tZJdn9MXM0Hh5AZ0CzwhmaN6Q4V2gaUdne3+Gtf27Stf/PatWvyvbnv350+V9P5LPP9XI7o48CcH9DHJFQXEHrm8PxSAuyL/lANMG/dvq3+21u3vEnemtetZKQbBHP6FH1tzt6ZyuaTd+5MbFehco12toh/a/O+bG1d45NMQZfv+ICu0BX6E5jeLrS7STAJT0MzRO+PAzUOmWl1labv7/Prf29ZWjUYHZ2CbokOaEsv8WKrxhYXabZ1xJB62YT48uBIZnqB6eiYRoCmPvWE5YDiK0Oi8dhJtGBKTJMJ0cBDzC8DGtCEJm5NlGc7TIM+JT2SfOYhSTRtjsV2ey7Wjohz+/z1Tq7dvgSi6SlJkE0Zu5K0fwrb4YBo7F//5HJEVPVIaIw9Y6LJkJJ07M8ZDqkyx0ILI8fXZP9I3nhlwR4ceEk6qOX02vtE1d9bFnr3EWGc4Qt1pvulNVqod+ToXcULC2vi05/WqVwBpLfpY9qgr5Rb4rNCfXro2lrdXPcKPZhzhK5v1rLzRwGvr/vnW8V5cj+9g/vIVfLT1avZyXt7//337a1bt85E8M8wsgPmM2nRmeSfB0wbYP5vROpqY/K25nWrIsFNVLu80+SbtH7IxmUFsxui0q2xfHDdK0eEV3ceEP/uFZI7D4hPLOxmA6sfQGVuEb22SfSju8TRHvHly0Tvvktc/mNS00Ni/MyXloiW3IZfbynixcZaXVwk+nhOOcIyDifEgEU+IX5lRLQ7JYZYDADIlmMOfsRAXaCJpxOi5TWSQBFPp0R9sK9PhO1LfaKH2Iddzb5gAFgSTWdE/V7frd3SA5Wbtb+EwynWT1qmu1N3zd0p0RJA2Vzfvf7cuYjUY4kbNbmfEUeGBGyvjvwaC4C7sEbWsRRuCaQllWRfG3lFumBPlSl8oDWut0K09y7RqGnSsbsLAHr/L7a//GWSTz4hun+0y9e+bOXHnxD90+vrFon1yE5AGlZRNNe94jMX6IqPHv3WlSvyR3ce8G81PtBr1+hME5F3bhPhnsL9dfUqydz9B1h2wHzB330HzBccuGeeNgfMW+dM8vlO5C0cca379+8zzC6sn3TtrSDg3e3A5z3CxP6QqDW1d3Y0r69vyM7Otl9vnipFZMGoHeK9vV1GtOad5EA/miqveheIoo+Ysb48GMmD2VgNG3s5n4557fJQsPbvZ0hH+UTFjVmb7E0VFJszmftEReN/LDPmKBWJ076M92dqKe1JwcTgnVt6RGX+uCuozDOOklQmh/v+vaWwVVMqi4zdtv/n3JIRZX5XtJhKeZhxFKeC65w8geeSVNrrl/ketwx2501SweMoISnzGQ+WVm2rbGdTonK/uWbalzqdSPv5i9mEe/nApFCdLigl0h94lYm/ORuDRfvXRwc8qJccOOcj7ksNnFdWSKAx33XfzS4trKwI/dnpRyxXrKwgYNQsTnmelCl9SLTV3AhE9LWvrTkI4h7C+oydco/ogw/uM1Tow4dkb94kMz+QncJ8wq31lF0dMC8+Vk8/cq7JBg6ac7Kpe/dIz5/YBmqwD8Ga0+U+nTGx8cRcgAab2w0wAcof/UjzRmtrv4KUnw1uTbwIPkooGW8F+qj2LtEBE+9OSO/NEOg5JhqN6OFPJhrq0BnIgwmFetDcExNaVNj2ZnGp+hxkiBj3vNjr+S1ABjs8cDwIA4Z57ojnQKdbQAKWB8RVkTcQTEgXCAIl0KUwdM+McaXyc/fn2ef9Oc2Sn14jjBI5eXlcOc1P+JnnOQURwOZfL4wzieJE2vdbC2CLZY+iZFNms5n7bPi0h/v+80dJz+/XPXMpGBuozkvmSFpXaDqw0tv7kjh0Hi7S4DUSBJDaJX3NK7ylZRII3OP3iEdLu4Ivqqx3Tm6fcs2Kq4RqFgfPOWBuuRywZsfWa4357m+aDN2RGovErV3knSjdInMemPOD/rhF3vkwnzk+L4Mfv3LXeAYwiTwwWxP7e99r1NUbPgrqMpib1byJ7awvmGHNYCK6/oMtYvxENjd98wufRO3zx3fnSg5h/uKHGDYBnKUvk+hHxI9WiT6+R+HBEin8yHH6ezNSrYcQl8K5WAOTC0wnaixgYsARsAxy5uPlVFxOZUYOmBVeqzGbtSJO0waXKZE+JHZ4SjymqoK4ZaRmD8VT3Hko+uPzEyT655NzSJ0H5vxdl5zgF0cAku31cZUwTsRdPyfKk5yCOJGWqaH1KtHjNKOJTSVMSID/vSx1HxGPjyckr4VkBpFXa/UB/JtEdERUDUSuDxeQpkRwbQwtCVydcIEcvE9UNaldSLDfXyEammVZQXL98qrAVl9eWZNPkMq0TrLd5Mjjb2O5QeKqqNyyRR/O1cGDm6jHb5/9iyu+xr9tztRud8D8bHTqFOZnGz9/9lOAeefOHb25uXlGYW5tNWb15hUJggd85YrPw3vw4AFDUp40oHhtk1Cat4LSPJiM29t8Y2NDtrdRaeMpibJCV16oiNvk8eMD4mu/SfLB/X01urYswf4+r+wTLV5bFrW/z//7o+UIJYEwKaErx8XUmcBR2pdQTTla9YGRkqc8etTnUs0Y5uyiM2vbwE5KZT9r3kfqTOxA5QwQVZyzboNHjn0JpQlRCUi2S3KqJVsk6qLgMF4Qpz4BpTiRrDpSQRS791OXBQfRgmDtwB6J226fnxeb7cvgGpMi57goKIximTTXmMMshQL1CHL6sw4BUEmkLnJOw0VbFQfu9UycyGhKUicw+cmZ8eqY7JcWqMbzY3qPEtuXfOp9sMvl5VM/4TF8tB7E8AVffsXaenFJxn91wNXCkssBPf7LfX796rL90/93Xw1HVpDXCrPgy0ve1MZ3/dWvrtu7zfe/bjbkR7g/TFNd5IRm00RkY1P+ZPsH/LWvf91u4b56gD+yTWMUulJ3CvPFf/QdMF947D69j+WdO6Q3N0lvuZprpxnpSuO09/b2A9revnLyHcyn/5x/WzvOD+mhgwDO/j7xpab88OCAeLVJiEQ+5K/9GonLi1wmOjokHv81MS0eEnIe/4/FaRI6k7lHVT7jkdv2S5CnXKG+2sEtp3AxOQFYkiRUOzXoabcyB8X6mLhiDzIHN47ddtw8LhJsF1SXMWONJ7BNzb72PFUVTNH8J2+v8OlfUjl3SBCR4GXcUhAVMf4pqXAXH1M/igRPu+PymE6g68ag8ajkBZlRLDkQlxPVowVnYpvY520GGcmrGVWXQjJpj+TRQ2QCIBLvz8/XvNkNJb9uSY4dzEbO1zn7eMy9GmrwiPr9BamHB+6c4YLI/t7yaeXRIxR1nuYqbQ5XLco0/bLjujC1ZZoQoijRPBmG05ZM7pXXNh4I7rn39u6a7d+7ccaHOT875eMm+fmx/9U20Ttgfvpv8SlHXACYRHrzfgNMz0e60mSuB1tbXG9uyt7dbafwcMPfeMU37/HLBu2pHV6xvuRub5f48jwUNoidX1J7iDrzuNkOALOrPvJ9rIgPF4lWjo/YjBbkh0ez9LBiXSWphHnGFTfKLyMKeoCnN4mTtDWLT18UZjkeVTnx4CEg2TTCKAuuU+LWDnbABBcdGIlNRKJjYiqJ3Bp+iqpkE0Yi09J9fgBvEBNlVemft5EYRYz1E78AsBTUa5hatttY43WQL9nsK4vSvV4WRgJkRlRQFmG7JCNDCaAym2ODw1MXdEEFaSSuF0RhRDKJYgli/7yJSTZqqjZLqtP+HDAv+bQkg6g5UgjGyK4aU3LZ53vWr4iMPkQi1jHVZiQLdET1puAPnMtr3TVeibpgEe3jDyNBcWLfleGqPeElADmX27ntuj5tuxvI1bbvbPNKuSFwc/oEsy0qNjdlSGR+7+2zQZ8OmBeHQAfMi4/VuSMvBswrDyhwNdrNbfta44SCAIA/8kc7+uQ72DjpYEEUKsX4cbSQ3N9TPN/PQmtU2jyiw8NVd/7KiqskZKQI6WNA8pCu0CJtjY/4aIHoS405eE/CBMBsgxzVGNtYckqSRaJFb5vCWzjmnJ3XMCEChOHzw7YuifO4IN2qRC4YYGwHCMCMnaYsSHPMPSGpnQKNyXDJgBYA6fTe9LQSqlb+OSynx5yRnHPfwfxV/PXaJbAkJZUUEZBYUllOTq6XhpGYEFCCsiwE0X8HzIaYQY59eBRTXBxTEMYnavQhzgEwc6JplMvrg6RaqKbOJK93PEiTVARKM88GjKg6gmm1mUjaQz7ngKr+sYw+GtF+T2QEgPZFqk2RNt0VTUJwHdQLVLUISkYHQw/M14cLtsmCInq4Rsu/sSOEmn7043T/+vIitLO795Mf8/WVr8q2y+8k+sq6cfmdVzc36w6YL/yj7yp9Xnzong5MdErHdb/5zW/qslwPXEJks8wV3fhbvAnW7IXEX1kj54/EfvwMfCqQXw4cIE+X9UZNtpDEM+NjYgQZJltzlTcLRAjC4PnJhPiPh5SWpQ9EIbDcb1UigAg2Jk1Qxudb+hSf2EPSiboYhiVRxqQAKYiour1G5V9HqrPloNEc88qIKGmOqyIihaT25nlTlRzOfUYze7zVbQtaHDa/bXvhiRLV4alKLEvAt6Sy8heuqCId+GNxvnawbN5ARRT3yIKdNiKpJ17tmuZ6ZRhZ95qFN+eXicov5eSuHNZk4deMG5MceaateQ6TfTI+zaaPqoEz1xFVR507kv9dhP2YaO3L1rbwRAlnZeDjPqDBwpLQT/dpNEL3Jd8g5N+7RrZt/+GAOVeOufcTYqQttcO53lQTbW5S/XanMOd/Ss+13SnMiw/XmbGSucKO85dogXn9+vVgc/Preh6YbQPdvXCHV6p1CTfbprlA5Gnx9vjwXYWWD8fa116HauXM67uKxSWi8QfMvkRxkXZ2jlX/lZFMJ8SzpTFftkMpgrHKFDPyr1GW+P+Ngh4pVlCEAGA4IvE+S6QDEQOM4Ec98dt1xe44iiIa16VyCg1R8D6JaUCpqGTNJWuJBAqyriKnFE1VsQ77IkeVIgodl8yMHBRNVLGWULB2IKtCt28xCG1eERsY/BWRWz9pAaZwoQaEnPSsqSvWAYk/jxgwDEOiceavkQCUeA7VPI0kjVOxZXMRHYYynVake6EAtDqMhEpoVKI4jGxxWKpYRw52cUC2T1TCj4nsqf3lfRrGiS3yDD1G6VW9Uhdqyotx3z565McXAEUif7hKdnc64cQOJJ99wokRSYwv26x7R9IzQ5npMS+tb5rJ8SEPRv5ma6uK/DbRW6+N7F7j4rxybdXu/8UuLy+voWeq/NHBrrq6tGbh1nHD18DUfDSuf/jDa82o+YGdN8nPD3XXnf3siHTA/JyBefXqbwX0ygbBNNqAX/JcV/HLTXOLQK1zbXcEa/eD2H+XA73G+64zJNEldY3RZWeJlpySHL5+IPpoyZnewYfMerLAxwvH9BqNaNspyjEhCX2mxqyVv+2fBEyoRwN4xrGLRPdgZkdE06rgYRTTrCodMBVHnHHJA4oQFvamc6sMmbieTjmikAAfwErVETsNF0akZyFT5AlnqHLAzOsGIoCXg2vIUH8xhx6gVJGqye1zfzAodPuwbp9v9+GxDnpy5vlq1pwzIys9by4Dpg7OFakwdNDUvVIq9xIR6aAUmvYJCrWiknQQSRbCvCeKHGBLZGG6x7FpgAmsZ0S7cSYLSSpZlrns0/U6tVOa0XLaEyTAT2lKy2lfptMpFStiXeUlLjmZ0FoPQIS5Dj/nMfUGQ4Hm7JlNqYaHzlx/bbQoP/nrB7w5RPCJ6H06oG8Mrtp3m6DQteVVQeeoS7QG94z8671d/rJLT2pI2QHz4r/0ZxzZAfPiw/gCCvNWcPXqkgNmu4S7Z90g6w0w0SVoxZ52C9L7j/hQ+2a64yPmpSUPSncduBrn1tgPc9s3QiOa7/pTZKR0Y74f7pN6f4PSrEfKjL3CrEc+GAPbujcmVhPieOgV5iwh1hPiujHpI7DKR01Iw6xutovdUqnoVItUWaUc2BoFqABBKLuaOGlKCQ3yN7HgTVdEUIIALcoqse04GVbN+lRJNrw83e8AiPMB1GZvH9oqAAAgAElEQVTBDk9BdxzUJ9Y6BQiJ8NrOFA+JbFCJM9eb14zS0B2LxQKwAVn3OSdQnF6ZOnZOiV6tqbgMex/WdEjWJbg3xUejRbKulBOvh9eaNub6lAh+yKSp9kmcf9MrSNMfCh1/RPVg6NWmGUkfQSdXrnpIh4jeNfZ6NVyUL9X7UrsGyT4JHkFALADmX+wRL8+Z5C03P/qI6h/+8HSocHynMNsb59PXHTA/fYz8EU9PTn/sCqcm+a3A4aVtCYT0jiZyg+Tk/b1d/o0VNGEgun/4SC0tr8oHR740MFTMwV8f8UlLIDgnm98LejkiiDOZsOsStD1hhnocDKEimS+ti8ygKsdEekROYaa2Lw+OZ8H7KzqpatJFVSqYnPqQNYDQQ6pNXSqY3uBDXZYcRRHBrwjQhU0NtqmgHis2HLEmbzbnDDM7PDGfQ+oRzGNPIZew6ExyDIaLkIQBxUEoVV6pOAkF17d1xSoIBWt3Tghfan6ml+izvqpQJWfqo6sGgICeqmtmCazh2oHSBoGYumYdiJjSq0+Y8iarGAB1rgK8Dx3a1uaHmZ5PSsEaJr2ekCyVUm3ULiZEPZ2YAjmfNpEoJoFlENlUUNoZxSLWisQA6ozoOEllIe5blJUurfQt/JvYDld7Vu9M2QCgQ6Lq0Er9CiDqSy+R4dRvmnyAoYPhvpwUEB0QDSqf8jQaWdlbRTmmSNO+k5a312Q/2OXsg7XquYB5ftAfmyb6oj+gX47jOmBe9Ht8HmA23dKvEwV0j6IzkyDMPTjm087kq/SIfnysFboE+WWJAkDvkGg6YX71by3I5EPfLQiqrHiXFKIvCLrMFDFaog3QgYcmVO6xnyJiSjS4BHMaaq5POweZfi9Q/UKxgq/RVBEn04gb9yJlcelA6P2PxEkNX2KTBkQVO6Xo5CCR5KScQgNYQqinnsBnCU7N8kxB8WGBmkt7Kdm69gEUNzZAZ/N3qPABImvwfEBK12LNqQoPQFgc3tL29FQPX/dPuwREtY/y1wG2a1JxIHUNmY2Sx4o0hWI1THNvwMcyE9sEgbCvDkYOkoB3kc3cHwRs1/jYSWhhzrfBomVT5JfC0AEzzERCmwjl/vWrIVnKmtLQMLFRkkmciGBPPOmJmQsO+UARjHaixUoseijhv7TXlwpKFMmcwyFF5ZFtGypDeX68hSbKTRrSI5HqypK46TlctyQrhOadAOeyCO36+tgsWqt+eO2swmwmLj0ZxWenGXV5mBdFxq/2cS8IzLV7FIFdbePdh08B5vrhPv+pYl47bjqILy5SMPZmLoC5/hsjm318rMxg5ErwondJjUdEr+J5lEIqn6eJNpDjD0lrNeMp9WioZrz8GipTejQpMn1vXw9mmnQbuW4BiTxFqEvJEKAhqsKQelmlsMYC6E5NE/0OK+rlpGwaiuSVcnXbYe18jjoIZJazwi6wDPuQ01nWxJ5hARkAMfAMtNiP40zNVgfi1o1/k9lDFovoQNjUjHW7r2WpAy6ReKbif1gCAhiDOqA6qAmqEvDFvrr2R+DfqCIHUGUqthKKTSoXGHLmeB0Q9qmAnJ9TB1Xj7wxJlTNZiILs12xWoHbdSixxntMMdexQfya3+NOXZER2UcSgvHLm5yparVIDOLog0JSoyNGcZEbHicgrlViPTpjtfXFqc4y2c0PpmWOp8f0jqDQkubd1xK80wKzNomAqDufxdnNt7FNllsV3vrdSmVUJDx7x8fpq2QHzxVHWKcyLjt0LAPPv378fVjuLUTtDw3Gg3M173PgmMaHX/Nw3WxOYrn6Z6iXnkwQsAUiXjoR8nmb1k79Suu2oNsAEZW0C+oDIvKc0ip5z/BBR/LxKVGTMY03q/rEeFmEVpC4AElJp2L2mcpFpYt1cB5icKlKuyxDMY6gxRKwDDznJa4VjCoPzao7DJtIOFVlDiQZUh404NLWqAw9PlXjgQUUCcDDHPd78vvmvozS1O6aF25y4PPOtOfA51egXgBf7WqAK8kDxGgBmUAvUrmp7pKjEtscBpEqLAL64Tl7VpCRwwMwqotEwsB6cJIWEMjJltmZypzCXwtgWTXUR8vHzTwoyaPKRE9kRSRiL82+ixPLSeGZNnErSlFge5MTO/zkjGixY07YMdSp04vSmU5yj13vG1Va65ZiOj30CfA++zyNUDVkZDhecme6qhtpDAdDmwWQyq27TZvnWrbkeMW+fGc4zPs3HANGZ5GcHq3vUjsBpniX2PCOLiN5+++wPvZ1r/P59CnfMIx9LXlkl2ntEq1hj2XtEH4ZaTRpFubi46OaZWWhal+uPtnhwfVMmH20xugoV91n5zmtD0rMJT94YkH44ca3VooKVzvoMQAKUCQIANKNc9Xiwn3FVkkLzzUmVq3sjNURJdRtkKQg+SWIESVQUnuRB6pCc7xJmuFOBoQee2w6IKksKayyKiFvYWa45wFy4ec7UHlDWioLEmcg2CFgDZaBUEpAtan+cA7E/F0tQ1zQDvGvTGPBIHUVFnzv7xEQHiLFEqNdpF1MTgWNO0ubEesGSrt3pdaM83aFQmiqw7s3UNWk05UDyaRAITPrEgr2BCxRhmVW+Wa+CH1Qq6akgv1Jb32Cuig2qgRwzi4KWBrEt4tzlw+eHR9QfLlg6yMksJJKnCZlp5joqRdNMgjqx+N7iCcnu6sz1/YytSLC8Zlc/nogH5oDMpW2hsf8zmV4mqQ+G0n/Vg68euXJYvxxC4aLcEt0+Dmg4FKl/bVlwz1XxarX7J2dN8nvz8EQQ6NycPyfjSkS/6hOmdQpz/m44s/2SgLl4Wh2NMsWrluSwiToHhwc8blJ+puNjXlj4Ek0nx15xQVmOjimbYsIwomw6dGssCPDA5IZqxGOt+tzr9ejoMFNLSSqzVd9vF30o60NSqiAuVc6oB/9DmS5VmoNYyPWpTMPQ+SFdwCXPdND0nQT4Yk7ZUM3KmdAeam7b5WzWypm9XLNMaxU0284PGXh/pFsCIA7H+fM8XOu2vIgyZH+6D2WU0lp0XJMt/efyfs0nL6fF0H4rUD1rTcGUxhZgVEXBNtangDOGcf3aGPzxO4GrqmuxOpbWIVpHgQUQoW7jXmIAUqdAdWCndc5QnFCYtiKJa8lerYscTs0oCQ1yNl2Nuo1kYYnMpMy5N4htXiQU2typTQSEpnEiUdNwGCWURjLXr3MYJS75HcCE4jR2KgCnM9An6B4/Fpjp7YgEcd8FuuDHhKk+++iY1zZGFtx8DR2S2gMPkPruk98nu1Td+32qMKVF+3QHzKdC4LEnOmB+zsDco32X9w2LCJHvoRUBJH0+5QMO9JL7DrYnY95c2KRPJr5h72gESE7c/Dcu6VwNXfL5eWDmOXO/1yOFDkQ5u/Zrh2vEy5RSlmYUHqUqeEgKbczCmtUfLavRTFMQ+lwcikN0HQpcWo/krMKcFHyMgMQwCZ3JDdMbym/MtUoAP0Oswpo5Dxj+QUA0gbnbQFFCc+JasATTW7vnoBErg3ATcVgEgDHpRlFWBIgGrYj81Dv4TPcILzz9uY0HM5RYDBWk4lh4VrAhQyqKxIo5MblxtOTeh3kSQerF1ilh+EqxFtTBB6IoECu5AJh4jWklMqzTbLWa5IEgX3Psas6DMJK+kIxSawBPqM6kQG2577qECqJ9IRlCzWY5RTYRE2cuf3PBpt6MzgBWkcjOJIisg6LzeZqx1O00GxOiYK1vXQR9IL4X55HfhtV+3SzIA/INV6A4d4cHgnvuoKSyA+an3l5PPaAD5tOG5nl8ludM8uuYTgIpRGsUbn7VK0wEL4MVYvRDxHSvyBBCRc6y9orSLa81Tkr8/pl4NPYBHQjLR5qUfuS7myPiXeqZgo5s/ZTwVeY9Yucn2/Glj+hJOYY53pQ8Ptym4P4CDbOUQqTXuPQgW7tjLcFfmJLiwCnAOA6kMrUKwkYpmloJgj5QmYh018GJxS22VnUT7XafwxpFsSaGUsTVY+1gFsRE5YxYGcPa76IwOK2lB4htaebuybnOeE+Ikp9+dcaXgjdmt40CFGJ5BWU8pNymgY8yELR0wzackQUcjy19Q20VaVEIAjV+T4oCC0drrQOyk1wkbkx/ITswQfZKRTNXu15OIDApCEmCEPOFRuA1lXFB68HIWvE16jaKZTo7FNToI6COOJseJdZB0pJMoDwz17hEakuSmKlXmM00Gq5WvVnKVV9iiaqr44/8TkxDDHi+kZJTmm45JBp+yTcxLtep/P3/oVOYp/fO8211wHzaeD0DmE/zWbaXun278WlubkVX1/vR+NibmEil/GjL505iQUAnmJs8bIiQd7PsZawGY6IMc2njng8ypRsTHPb2IF/lQkEdppSuIIqNqRxSGh/mqneUMPpPoi68THMep8xDiWX7sAg/HsajXJGGGR7i172Xw5r2QZiBhyPUIFRjVdTKpSQFSCY1HNQxWYSGAk3CpJzSRIDFkiJTKKTwyKxWroMQzOImvYqqwO9DiZAl1qAlFk0oSGc8Z8vSQRQ7rTFMRpMNSrc+6Vnfgg3nKS22Mow1Xszg9QBG4x4R5B1HkXtctwEhvL6uhdPA2rJmq0jCOkBy+omZXtW1O8e5NSNtlfgpIqBCRbRYNN+oYS0EZmiz7JVKz1w6kg1tkEeCkiCAE4oTyhMpSIkmuxiIdYpTRIojrzwBVNWPrV3wDT3QAWkwFucUhUm+j67uVlzvTZjpwzC17dxDmB7kKJ1I2h8IgPnwkzEnBgnvY99Sbq4DPEotL6cLdqwPOc4Wi9//FJN8Ps3ofFJ758N8PsD+6hz9UoBJ0dV1inyFziEhsPPR1tETgQm/5KU3CGV0Dq4wwRHcob6fVfGwmDpgIgXFA7PHbh4ddDRXxKrxUZaF91UCmKrMuUoTRpu18rjgIxPrn46qxeKIw6qukD9OEYI6CNRQQjaETQ6fYkBI7A4AwkZ9KsMcIuUHndfBItNnwFM35ja4xk26kC6NU6JYxBDrXgNB0qTnQGqtYasNW9v4NwHKEzrCjJ9/fO7WO2OTA3gAG4hbgsgObtgWigQvat1jpCeRMKCIBUmhITmfp1WBQEmSQSoRFGlNIrFUUIYGeabaZtqIjrTFYYiyL3CVrdaB41mdlxYJ7/gbBGBaS75tHAIlWqwKCltSTH2L+LpIq3rVILb+9VxWAy1pMQ6Ykko226OjQ3aJ73iRL6kVg1kw3XufEBWvkyuxBDDRQo7GQ0p6Y/HAhJkOrYkenCPpDw4FlQ8Ts13e/b2N8lk+zA6YT8dcpzCfNjYvCEyoy3ais40bFL25SVFbrQMz/CPMxIiATDZWx+MhLS2OGdU5eBtIDzpdBjQ+mGpMJuZ012DqgjwAZtoj0vs9ht8SwKwrUqXyihKLSskpTNdhKEEABDM2Fuo4iPV7Ub1kiUKLdBmukaTO8Fm6tJ4wYKcotetwrkKOuTCFAog0DihnSulYAM2QAgdPFwSKAURE1JuAEExrBz8ESzTV1iioSgfGRjACpA40yvs7AVI8JyUgDNNVC9Sn4+KZnvUwrYlak95BD8GcrGSsPQcNhaoxw+G7VKlgn1tKqNESjTUsV4brWBtvfjfZm6pn6+ZYqWsxGBzANgqsU5gROR9obMkOCsouaZ80ObOlhWmO8kkAE6qyBWaWF6KCyClMNDJeWxyaSXnMvcHIIqJuolxCG4uNEwn3crGxiI5SWx7sM3yaACZOXS1WTv5MAJxIO6qbaYFr1KGDlGNyUxVjiuNeU3KJgJDruzlckGFM5e+9SyV93w8HwHk+6NMBswPm00fgzDOf3uMSh7/dmprNuddbE7x5fOuW3/jBFkXm4ChxuZSYc+w1ok+2mUdD39rr1ZGv0sGx2ZRZZ6il9vAcbcx4a495rclCineUhsldNm3Y8lcBQnb9L3uHxICiM8HLgvdUoibjwjXUAFStKlUUR7Sj42CrrJckosAWPj1IBQEjWRwZNnFI6GKknKlsCTzhMPDBGoIJTtptCxsWFM80DYIZ2SZtwMcYDgLNFvXr8LABhwKT3dVik82JxZoTcNbWOmC6faQRTUIdIWutqDLViZneZBSd+htxkru+Z4hotGyzkNrO/1hWhsJQS2kATK8yDaQxTGvlzWy3XWt3PK4SkJbMlC5tiCM8R+KPFwdOHWqLtSO2iepeINlwUmZBFJhBQbatGCpBTEUGqzQQsfBrIrjUx1qQ12mNFXRSEhuJmCwR5G66psOUE8CJWYkmeyJR5EstUTS0ui6mnXYYvsz9DzOOY8zQiW5Hvnoo7YtLQxp/PHFlYBCeibGy3hvK8THmaRoVP4iouI5J0trl9umP4NYtkrfn8jIfM8nnfy+/gjmZncJ8ycCEuvzGN/xFUc32qKTENZhoEs4/UcSun+TU134Ph0TODB8QlR+Qaifa1mrKxwUqZnwHh7Dsu4oa55vEjldTUsh1TBNSh8T1OFfOFC8L3laFqpSfDiKsY5XEmA6ipN1+FG4V9VKhKUS01wWouVZQidb4YI+2gQMmFGLAWsFsdsCMNBk2qjXBW7PbK0uDSLi7lyrvo/RRcpjpFbGAvM0fGadKnQnuS79VU0nUHE7Wopbcny5o8KHPlIjPfVuKjGmJTCSNolQK6Tjt1aAmNSllvMI0mkQbseIb8jotqty0Z86cZ22ErbaAJMAI/6iOyJvMRlNZoJW6JiVaakV2qPV07VhmQZ9MZMlK0w0JAbWydgx2zYktfJll6aqHYLKzEesgCrWaxRJmJPBpojN9GEFhwqeZk0EE3YoDprtWLCcNPeqkJ/ToERlMKTwlWlgWazAF8nhCgObuDvNp02KSnpvcbYT0h+IHX6WC7vgRcODsgHmGAs960AHzcwRmWe7EMlyP54H5IMPc30QHxUytXuqLSxli4rX+QLY/nOqVxgQ/LGbKpwplXBbMA5U687tAIw1Ylr3EN/zFtSaFVuOYFSYIi2OqVMFZXapgEAlllbYmUojV74ccHiW8WGuXF+6CMpkEztq2ZFz3Ig2FiSAQBJiC2GrUo9aQTEoH2gWjSZFyPktgxxrFmNrXF4qzsaRCHQmu2YCIpfFTMtQj5FdtVRAoKWuLbkpOGeKYM9a3ghk/HzU//bIcExuWWpTnVBWLwtv1ZZIOxm1AKG/grEgQ6IGIhUh07722tj0PoKxFizY+iKRDY3VIVnAdQzQrjYOlU50sZlDr6Xop00iRRWV6lITWNfBAKlIV1gj4wJBHyzvWoXUR9ADKFTAtSfUjW8LUKOCHjG2eF7TwihgAszzK2WIytqn/LDDLnQJ1KUckJhGhRzOqmwqhSxurZkoT8n01J/Rod8ptRL1uyiuT3kDqWV7cu7mWd8C8MCPPHNgB84LAnI+Mt5U87aknUXFMp7tG/I1m3p7yxzvxNFpPQihI2EbDIWXqEzfmufZNfZEllCvmfr9PR/uskFOJpTrcU7rfYzRwcAGcfq8BpYdUD01/F/1UsQ9nHGQ6VlFR0DSJuT8rVY3a8EFENisVelkCmEfM0aOAF+rARKaJRocWBHRBChe9DiqoSA9Mw2gN1wRfUNmDfj9aezO5MopRSOkKwzUbyZ36BIWVQGHC3jSsQoSoK2ZnhmuvOBt44mALTyhOcl2FNcEcdxEV17k4diB0A3Ja6OPNcp+e6N8oh1IBuuA7xCmeQs82R3wrDsYOotbZ1x6oFn5Xl3vvcjQJkRklykCNetO+FgOyCoDs/LhiLMx7RMyRzxmLmmxUNFUzkioSo5t8Tqsr4SK06HyEtwhYhrPQaNe4eEIzQwCx2FAk0ZGFuR4OYtcLsxrE1s9iWZAajKzdz901wgWRydTXqXsTPaNBmFjMj+4gukSiXc4m7qgp1UcisFrQnLgtrURkPTsuig//k9XsmcCc+02cr/o5A4zOJH8x6v7SnDUX6Dl18PhP90xgzvk07xFxY5FTuUPxtCYHTN9HiGih8VlilsGR9lOyFvBdDv1MjuXAA/ESEz8sM4V688L5KhM3zws6HOH51V1SY0XMJfFBjxTmzFEccz0tkQakAUlAMxpE7ieEgMwuUfRXpl4RzSF+9CGS0gE9/KiNcYDk2mgEZDjSgnzKNgXIWK008iubtKOAiAWqEte2pNhqBzqkDcHHCWQCwk41ar9GJD008Fd6Py3UKJLYHazdKMOuBkC9UY4gvWpkZGt8Y+3yNy2w1i6ajK0oUKEYdBpSSBn1LZecnAxcFhRAiTchPqLuI+aq9uiFK9TiijHEtkHekIXPs5IIXlYBw1kZNPgQZ/4L2cDQbKGUaViSlYiMLUXAfZjeEaCIph0IbNnKDimoXUMPtMMLSPICAXy0/IzMSkoGU38MMpLdomhms4R/WWx/6OUxeiDVFsnumILYB4FWgtTrZLSMszOJV0SmD2cEn2ZtLgl6bdJg4O67NUsuep7lVHz4m/SygHn+p3/+Z/NLg4b2g3QKc/4r/RyAWR6NUz31gEDPw/6gT3k2Y7N6SeL9Xe+s6/coPMjUeHNVosPMR41R1li1/SBTqnqJS3Y/5hy14bxRMo/hDyyJ98mlSDIaaLgGF8OIVVWi1w8rZszhiAly2QRh8F5ZrNqYwlAhGlFzxIGCSHMSzpYKYAT0ECRJSLvUIUHEm5HymJBUyEZ3IR4F09pyhex0X3Pu/I+I7FRKubA3Ou5adhCF1U3I6fFmOgCKSBBez31ebLsI+qlR7s1x/3gemO1XZp1EhMLUgqTQE4C6nJ4mpQcBHRU6VemEsa3wbt2h7gxRFqqTSYumiooGjgq94zmx7s8GuYRTpzZZSABaUtqmeT1ZtDJFkEhxUKP1G1KL4LHo6crWKrAuoGYEfgg7jIK6QsqRVFLp0KLXaBIP6lSTraqCkZM53sXEaz5HMw3EKnRnRwOPOHGJ7ACmk5Ro+KETPwCuqYdIncxcAw8oTF2uWqyTtOcU5nQyJbh7xmqQd8B8cY53wPzcgUmpbnIr0U28PwA4ift9Ip1NfTmj6yw0Y1pdJeezzDMoNFaq13w/CZn+oYK/ss2xDPYShbnAqyrmKQzLQUmYS0epEgnZLuFc1czoks4OpiHvcRVtW7VaRNCghpTVHLmWbRolNiyBRkmkewxzOrJGWdYMxRlGLhKkYDJDGVpWrCoY1IoDxEvCJm3ITZFrlc+tRDNH7cxxwftB4wwHT7RIAh3hGEAiJFRlA9i5OXxOTffHb3DPygaj1qJxiBOISKoE3FDf6QFqqUZ1eLPNHNoaUfImMCSQ1gAmgjNO2VYgrTPBrTLWMJoI4y+KFQPQAp9w0rIyI9bjfibTMA6smY5theIhIelFqbUBkpBqqSigABmsUJmReGAGiOL7d9RnMhGqgqggG8Zy/OgRhaEICpAS5MlvRMbJS8qpDC+7iqBmAmQa1Ps2ipd9j007E/gzZyDmjAhpSX6e9NYkH1CSTjpgvjgr/R/nz3j+L9Xpci73cv7DzacSfZuI5v2WbRoRjr9DxO/d9eO6lFI8KChFupC7zQHK9akzwWEnI4UoyHsuEb0uM5WmKUFVuknJlvwMjm7BNLe7iTKTIzWMEuT5OTMc6rKuYq4HZWBVpTAvThhFxOMZ6odcF/TMVtpEPZdneaTqeC8IXB4morKuFNF5FtFM0nBQaRYunc4D0EydBwCay3msrTIQjnBTIl/SWq1DJba2XpFaUhZCSsGMdqU1rm8cQAnRisdeVdrGbPdjwk17NwSavDl/OumZZ7MX4TCzrbWMdQs/A2pCJKKPus9ecr5JHFPXFqlODowWIhquAOfLRAYq/JQ++bxWqOBBEMeyEoWQlHduOhVaQZdaWOiCiSZYW0tGrNHEgZgFpkm/kmnM2lQcmKKoOYSqdKlINbwDTumqspLABCaNKgNYhnXP2ABzCXk73krpKoL6PDBlPCb4NdHQAzEvNfCzWCLtqDJkw8aP6ZLbbSZoE+cVZiaoCvIKc0YaVUFtk2LXuMOb8dXKIKsnlNNdP4pvvkmyO5didOtvhvNMt7dnpRg9Ro9f/ubCHTDnqPhZgHnnjgfAzZtEdxtgfpQ/SpJhkra5lQBl/5IHZb/nG8dCYSIRvcyJB31i+CsBzOQcMIu/KgJYw6jawZw9mWblzXZm0+cAPTBqwCckSiHgmnZslWVtotQ10DjiOt4lXq4ripDYjRQfGyFVEwAEDoyCWgSo8DgQl9TjgjxSKbR7U4AlXKeMlElHHMPWOAcmQ30qrZACrtpmGw52zqPZRN5tm5ppGZpNK3RL8n5LnzTabDtL/NwMFXPVPRbv7KTphiWDNHEvMR2kkD7kAkJKS43GSh7ewgSz2jo16byXaKTUzK9DQWCRxwNYIjIOIPtWbt5vWWPScHQqUshOIjskNR5YmURGI73fmc4OljgnrNFbhFB0xBbqt7Ipl7i6JIu9GpC00nfpRmU1JWtD0VJKmAxMYAs3d1Cl0Qy+cCWWUKCoT49iH/gBJGsHycQpTMATwGwt9vRyYubnEfINi0VmWZn/erCc3W2ASXSXtt/EnOl+ub67K/du3Tr1RXbAnCNEpzDPDMbLBmaeUzIdThww+9Sn/WzKa5f6XmH2ZqTyHh/mWQPMlMMA6jJx8EiWckoWUeKYMxRm9FGBpuinwKzZmd0AZtaPgihnnWUVY2qIVJGqQj8DY6FIGQ6RgE5Hpo7342C5KiluK2uQW+l9lj7K4kI3yivKEGFj9soQZjjMa+/wdAa5Ulw50xoWqhUIOz+cbEijiBJqswUhgtg+uOLNddjP7oUAXfF/bOBTZesnfhOpmTkRabuun0vHdPZ3Y3QzQzkqwdrBX1mpYabDxwp/ZgyT19nZgkRRgNLXQ7rcKQOAeqBbIh3XeK45AeWOzvrHzGiGgdCKQhVaFIqmNU0WrEy4RJFU4Bq5A5jYKGxuIx1IKZVAdSYqMEFdGfg4wwGZXEpJJZRpOaUcQHTllBMZDddrABOT+1ZBZAN7LAFq4guiKshtEMU42qnK2rWJ85BcQJs4OxPX2A87LlvTn/apTqcuT3NKfWeSz7JB/lkaseoAACAASURBVOsBdcA888u/+INOYb4shdn88UFGUaswHz6kNFqepkeHrEzcE61nTHBY9oiG+YwP8x6bKnPTOSDHMqzSJjk9Z60KjheIEOABMGW71JXLtCFCMCcziQcm1GYIAzFSYiql01DYkvYNgms09lXoa1maTM10GuxRuVbBmHZJ4a50kZmNK0GMWKsK9ibgWWiluYJucj5N7/N01T4u5INtpO1oC4Gm2EnQtiZcPFcBQodMV1IEYiKEpBhOxUZQ4lfulWqjLEFda+A99OBsVaZWiFL7QI6H5ena0Q1mt0sxgumOXnP+bJdjqdsgjxKnKqvToBDyKV04350HmR0ihC4IOCmXq+96R5+Y7iVZCvEnxJCNVHi8UtdT9MbkQNdQowgIAZj1jCzSjLAdRGKTJKn6k9qyCmw5IIP2ekqFtqxKKmwpmNMdE6X1R5FBsjvKKNFfxOY+2d016ghy65LbYXojEBQlElpywNSYqujogCeoDLKpqAWxse2JM8sxDUY25WC5b5OM8ksAZnvf3yXafvO06uf67rlSyU5hdgrzdASe3SS4nf3RHT+XfOl8mHPqfO3OHX5vOHQ/8BuYMzq94bbLMSVLatprUuNcvuUQZnjB3FvxJvmkYoU5b7D0e15dQlXO6kKlJfEEQWlklFvWBUU0iomymlUCc9ogncgDM0AfSxcVJ640aUx76zqmh6gprxW288jED3v9pZpN7LoJwaeYWSQhOWBxBLOadWWMAhCV1JoFKUYQmmj0o1jFMGvh+0RUvFbwQQYKDsgajkoEnNCZHW2RnaKEGkXNENuavcndllHiQJTllAhRebUHzVrUGuWS1sJ6xlv0vjxY/EopG2llAc75xPU22N1Y5AA6jj01u10qqfd9og1HZS0FgtQjH7xxeZoAsiip6gITIiEZVEr2x7Jxue0ShL269ZPW1piU6/GwVBNtA4P2bVFdS4X3huT2QNdtUw04bjmUOkYiQEnCVhxMESDihGyNpPZCxPYiMXsHrj3cpCSK68hO8ZwlcTMaM5lwiGogD8xplJ+Y5CMcY2eNeZ7KZGkm0SSVCN33EQd6RBRjMrSjfnZ1iWZPAyZqzN+Zay781r1TmD67cxFGt/NhXlyr/kIe+fkCkz6mVMezHhpjoNchciwHB+wqdnq91EXEJ0Hqot+VIl50YXAi5CaacaFmE3Jt0VRVsE1jtK90MzoiGahnSoV1bkp1XHPU62F+nsrP1miRh+mnmEBySxg6eHFmKT5QdqWOdIgqHRfMKREx92CTWuu6qMLa2mAlkqVvfaX3LwCm7/5o8t8dm/AwjkIbROh0pshKjZpDl0tJyOf2yYqufrzpgtk6LTGthXL2OpRkBbAqpkARbPNKKadCAUprraqsBG8t8/Xf/lL8W8OEUbZCRzM7/TcfVn/4Z4/qfxcHQQ0WBhp+xkAYdTWuBadXiR6ernq9CQihNgfa0bsHAEwxjVq1luowMOA2/AreRCeDdCWkGSFx3QeMXJE30lcxcS1uGqmYbGrr8cDosVZkdVkj498pSldqHge1qnygBWWUIVV1j9LaVpWkLCghEprNiJPQyqBnkGiv0tCa8cR/njASNmQrE7kKISjMUUrGl0+SVMcFlwOkHOUuiL4SLlrKDtycQVCYkwQ+zVTauYKQ3+6m+VWUXaUOmC+Kq19xk/zzBeb04WFvpKMUwMQXBGu8PmKFxr5OSSpiAzcgljShHrIlE8Js32wmhZpN2QFTo1AmJYWIuAcmcU9DXVZcGLSU7IeYoMxlS6L9mjDamTOmoIhQEW5yBbN4pkzySAUrdZ9Crqyv6caECwgKs+KsKsJqUsf5rEr/q787+s9fXVBX8JN/sG/++n/68/G/jKKo6vWiCgnZWilGZBnRby2KoTRdzqVYFhWwM2LdAunmdGdjliufl9kk4DsFKgh+mbCs6vAfbARf+w+uxv8IoRdfE+7nkYHR/3//tPjXf/Kw/rM4DqowDlHc4yt23GBijQ8EZWlJQqQK+ah5ABer9goTYfK69P5PHFuFLvTuGw5bSyEi5bgu/JxouYkqH3gxoTqLWhR7hQujXJMap5VMokAM5aUNlLboeiQVie71qro2KJWS2taIipmBBJV1jecyseg8B09CFBiJkc6PPsti86ISbUPXsMPmpZg8ctvwcS4OpAYwXR84+DRXYouKoDqKBQqT8gOqnUmeyMQFhDC1sK8EUuGKLfNHPFxendL797KDq9d9YOecSd4pzGejtAPm3Picn+hs3iR/5/q3T8bKNSNqOhJhc+0O8XtDD0WY5A8fejlzYKmnFqkBZkbUSyk6ypyfEsycApYpem9DVebcB1hjqE3mfJu0NWOFOjhdITWHVa0wZ3hJURSRVZFSXLLNI3UQU6xCP294Oa1VompV1AFj6lv4M41rMlRTRUF0oIPVOkQdiwuKMCMnB0EYo3RZFNF0WvXf6Ntf/+d/e/TPIdqg32Di/qs/Pb79USE/7Q/SvB9Htdbghq/GERQLNl2HYJYjC7StM3e15cql+LDARQBfpoNl4wZQAZdVEUxnVaRLu/Rf//bon4qgQtMHsfH6OCdwwSGp//t/c/i/WhUeJklY6ggu0SaVqElG900unVh1XYBZAqkQkmr8m0grUtwWVrqQukE4G6/lk9KVS+CEioReNqpy4MVjo0PjJmxHwJ2VSS2No0xNAmWssDbWF4mTVoi258a10EPUHFP5msqMbFBSJBDDVjVz+rCtbBD5wiRrS1H9hRoT0qHzkSlKYYOu6iXBLMc3lfbIomM85TGVg9xiLnQozMjNGZRTRhlhXzlMLKyaCM05YJKjGXHSk9ocZl8ZLk47k/zFNGYHzGcC8zRPtZ12Aoe7fpdt/SMRbbxH7Ej5FGAiCR3PYe36VCr833caCrWv5lHHzNUicsy9eT4pY9bHkwCmGQI0VvsGGlCYMLfb5HSbkzpQFNcx4afu8i1nWR24DkSYoCxiFSUxsym40HG4K/m6dcXl0FIER56G4qutCWbHs954Ug//m68v/heDSC8WFRFa7QJWh5k5+u6fHv3PywvJOOklVRq6H73Lt2S0fnMeSifNmEzgLHAEbzhAuzWvNvEPAkSIqCPRSKylIpOwrKrweFal/9lX0//49eVoo6jdPOaYMNLJMFwr1ERxQPT+o/Lj/+Uns98f9aIsjnUV4pMC2wHCH03wBloTvkenHBFBx6eA0sVLumRQQQ6+z0OH69firUCVurQi2wSJXHUn2i8FPn9TCBnvxqtRVqZH6rifI8tLm1kxEVdO6ToUGQm0rjENhg4DayrkdpJdqKVAnblK0hqyD801bJlJaCurNeYMIlG9AH/ZCJVAAXI1s8in2AtJmETGhoX0IaCjWGZZISkmWXMNh3M3BQUCQBgJH/zB8GWu9hzXqFHT1O/Nxn94P9u/fM0rzHtE9I25KtPv+x6Z7c/iXufDPEPWDpifMzDD5awHQOJGHijio4I5AEDzhNRy7pr8Il0ISeqzihSAiUg47L3JUaUHkWsQzEky4JpLxjZchwjqAJYI/BzGHFdRoDAVrhS5Qn/cemac7xIT6WBSMtSNT5iicawuGUWRC3LAUCxMYEqrZ9M6meVV/x9e0r/9jV8b/vY4I5qW6ETkgdmPib7/l5N/++8m9f8zGvVmcUg2DgPwBwdp+C+hLp2Jzui1icRFwNSb7Q6kMMSdrYkIumWEXMo8j8bjKrmUyJd+9x8s/IcF5lYrXZ9fQuWMAyZ6wGuiBDmmIdn/8Y8P/2C/pg/7vTgPw6BG+03fwRhiGVEqb1LjM7q2Qk4RIpdSCeoL4YjwWUbop4S0Ip/g7qqCtPJ+SpxbKdEAJc51efFBjfQi5GjCE9qvzDgp1SQgXZdSWlOjgFwkZjRw16aqSbSuMcuasRSbJVuXpa5FUPIOiz9JxB7VQoUHppvvnEuX8K5TJNMHJkWrOJ9oIKEKjQlLZ56HzsfpFaYZIQhUUDhDJ/fEKc1dm8goEsnyzM0bFMWpzLIZJcsr0w6YL6YunXvoxU/9ZTjz03yYF1eYNxqF+f77xIMB8c4OcXSNUqmpn6KDBlSCm+6WEO72DSZ6Xm1Wx74z+q4hDQXpppTIxlrFQ1bVhKEre9oHeZCcjrjOrGDNXLGYUB3GYVzoWmNmRwDTImGyYDezo3CgFA5lwzMO4kloV2tDKWCClCBbqSAvyyg/NulknC3/i3+09q3aqvhwRjTG/GDoQ6GFRimm8pHiX9599K8Gw/h4OOoVUQhb2zWiQL82F+0GCBGi90ntPrWIAvg2fT5nm2oEiFaFCWZFER8d5f3/8jcXv7mQBMNZRZQBmHMKE4OFPFIozBRdl7L6+Lt/Mv4/R0M166VJGYVBjd5nqCl3ARuUrLs8es9BNAJ29d++LAghMfcMfJi105yWNOp/ENiBTndZSW7OcsO29sBEpMn4VnAuBclY2xN11MdMEPCLGnTQRNmkIbQpIR3VMMf93OdkI9HVyFKJpifGZq73EwDJBdliGkiCbRXa2hy6RsQmqCSMe0YXvgqoBaYLACFnM4wlNYXFbJRmBBP9iMJZ3Ex9kdPELkoYZ0JZ2rSDy4RmKdmUpuM/pGz/cqMiO4X5XCD71Qbmp8wMOV8OOd9Vfb5JMEb7+7uk6C0/7tehJCMPxI//8ri/fnmUmiNSZenn2pnWaPSL/MrCwTJeSKga5xxTQru2RBNzN5VgmbOGrxJRcDftJKq/mV1zDZdjOa0C5xfUrPYsx8iehKmOfYEKIMrcthUD2eXSfDIbxOOYV2sy6CEGwHCd26go6vhgfzL6T68NvvnGWvLr+1OigynRGBNzCVEUCA0TouU+0Xu7xf0//njyB8NhmvXSsMJ83VrVDFgjKv//s/dmT3bm53nY+1u/5ZzTC3ZghgNwOCBHABeRFClGJKWJTFuWFNllp2Sp4ovcpJxyJa7KX2CKl7nMjS+UG1dUlaQ8UVWsKplRJFtDk6ZoSyS1kKBIgsMZEoO9t7N822+Ln/f7Tp/TDcx4BiRlKtMQIfT0jkb3c573fZ9FJC9wEUqO7yODARGGmT7GDUceoaRwTVSdC3qx8Pl7z8rrf/va+INVi8xJosb1DJNHcnBBMEyJz4OotD3b/eyN6Ve/uUc3xiPdGKO8lnppEGfdTn/Vxpg7KO1xjgJeRtxrmIYmzMAINsIrMwPlICWevVkIn4RPsEsmBSaNJSIu6IiIw4NEjIVQB7kLcxMlcop9z2ghTwK5Vc6FVmiDMgsYe3zYINXiip4K3TNMxYQ3+tCDJxqEkiiDioiLc1QIE2K76AEzwhrZxWDSUOeLkGIbR8j2RM5mnZKxecLLse/EXQijOXznwSLlPY8Yz51WC//VB9X6SH774pcPR/BLdz6cTkby18fQE8BcH8mPfZ3eCmBeGwDz7qsknrtKdO8WiZBNy5HeGPEOs25IyVx0KCvDnvIYYMouFw/TTEmE/3D3Kqw0yLG0+B+F1gEFGTC9dwJunjZ6dPnI/WRzsEqAFrIkhFUDeApBUcngWsWCQyKza8Q5H0SOWAmIW7wPebvoJr/wzOiX3nXavuegEnJnQbSP4BvsMENi3fk4F7RVJNoqKN582L38lfvV58pxUeVawkCdMsNggSR1Ebs+GBNXocTGSFzCJY/hrOfEKO6iahpn59PF5H964cwv47FjAcAEWHrEba6OPsP+l0ETYzkAk1Js/5d/9/BfTSbFoshtC7wmASoLTOR1JmeIACWRZcTXdCAiFKZAbw3Ci08YHko+4oB7pi62yPNkgBRGIoKdrZIgpy7Bw4kK34h9pc/aNCtCmLH7XEksSvuA4j7BHaSTQ4yFpmDbxk2E6qLDSJ4H/Am2CU0m5EPoQQff1QKaTkqx6CPiROjiCjD7HE1cyJGlKTzfhh4FTEup2R+aKfGgZynJSeLgDqe7hf/qZrXOME8A882TzBPA/FEC5jkqRwtiwHRoc6ScOozhXSPYqaGhA28IO0wpM3EQOildJjJLGJ36qzjoJXaT+2TY2VNDnO6EykiG4MVCk26NsdF5JQT6eYJIhZLo6kkdHM5aBty0NRKDlH3o3cWYRF5VXnvns49fNJ/4yEX7MymJbK8i2pkn2quJ5m0/GntwLQGgwlhOtF0KOoNwT6LuK7e7r3x/Hr+qrQjaygRtJNuPAnsVuV6CR3E8M3gplMZuUYYuKOelOjhYjP7Wu4uPvu9ifgX7Unw8HsehYxwu5KB9rLTE8Wk4/AAwxxnRn73WvPL5V9s/Hpe6MeO81fAl9TnvzBC5KxfwBWQcdJoRL9Mo+IGpHTUXeITpw9rBNSG26ve7uIpHHIdYRsRpRo41SgyYYJuZ0gcj180AwFIa51nfOXQEqc5zIDLS1/Gv0La+1LINvqUYsiCkhx8JcA3RZ8RFHQA6glYTfnUAZoOeoA7pncwa67bjPzGShxElI0zoe9Aphf0mmclm0rHhqgvsyAMu55T3gLlBPWCWtPAv0QlgvnmMPDn6HH4Fjo3kv/GZzxx9AFlz9xwZyddS1Xkkv0ESozh+gWH+4lWiW7dIPDhHpbu7P1nqMAGY6hQAU/DeUhYtZ1hCkL7ISZgaiWyo0yby+Vgk2UlmlMKJUlp21bB7B+N1qpUQRlRJ6JTpTMPKAo0Pp2cI5RGk3gW02Sj4w10Kah5isefkxbYN5TtLeven3ln+0mYhNzF6H1S4hBPtVYmmDUbjRA1aZ/nakfhKjXG4B83+91YhaLdOs3//vfYL+z7czjMTND4RqYVSIJRYE8I/Dl1OnxockpRt50y16DId/Kn/4RPbP995oZYAjQs5RnF8XGaEa4CJd4DPA3tMAGZhU/jNL+z9Ycrt7iizrTYwxkvEHCPxgsdMXJeRI9lfzLFCDSx2T2jbYXyFDDQlgCarM1FPBgE8SClU7pALRc/vJxgZFB4LIlSmMeQUpmUnpkIpFKl7SEDRMAlm2UYKkP+w20eqqMj7MqQW1siIjetgo5RCB1zJOcW9o5TbFDD1M2h2LlGmuVOIw4jrvsqXd5iaUrlh2EaJMrVQc5cRi9ohZS/8ZmRJ+8AwxcAwxXYxB2BeGHaYN24QvSHD/NU1p89Q/bH8+TnaUY7nnjh9nhCH/3q82fGwjSNWSPwV1gHzWKr6xSGRCK/2tfskrw5/5d17fUXFgzsk6m0q9W4z5gpcvDzPSVStQpujm/XXbp8j05JEJTux7Sey8h0DJmRDATmWXnAQsG1d7w/nyzPSikoF2VCLgVlSJmILGim99iiYUR1k7I64AC2ZoF1Far9tJ0nL53/pSv4Pnt5QT9cdCYDjtO73lftNojksdx2qgNhyDSlKL6gRAmE+VBrB+0wcgbYKgCbRJBPpWw/D/T+/1/5bUnqaa5GMgQtHJPwPSWsshUpIn8Qo7u102pS/9oHRJ5/etqcAlry7REIPPibG8T6UsgfMoaQHT2MszzCWW6JJQfTagdv5v29Mv7g5yhcQsxvUikfRp6ID6ns05Bs4QFQEfF588UmIeu8krJHDVb3vB8eWMympUhsctpGYyRNClfA0zPNcc4HE9ZQONjqasi7JdQHHHhSuodKiFYmv78wwsa8MypfkWhx7TFIehyDsMw0OQnnua1+TkUX07ZQBEtd2pBzBQgkhU39BNwHADcDU2iahZpE96GCZsMfXWaomLe8tTbcZ+qqLfiRHLGDTNLQ9yuc3vknVqfM9EH77JtF7kTI//Lpzh47uMN8IMI//mL8NKive1iP5XwVg2rvNBKVkwWYJwvQKPvA1wFR5KxbQWQYnCzHmHSUAs4udCll/5AFgipaUFU54MoyiXhnQGtEl0h2FHLFBBiM7aU7qRRd4jDh7dCoGMjMnzO6s2f4nH9/8n5UUObPKOtGsETRloEwE/zKAsvaJJT0wxPSA2bNMbCiRI4zjCxgegBMs81RJdHoksHvsfudm9S9GWe6tlaC2KPxCoBGHEAO5Oud1tWiLMxk99Q8/PPnooiOBz2U5ijO7HAASH3cdLAGYLDGSROUwlm+UlP7FV/f/ZLdTt/JSdjZjBT/S3xKYZg8FKKUQy/COKKLsr+acoYGqSCA5B9LFGNskhIaTnY9DHlcqPGKg2SLBA9AflKDJNC5Mxx1NkXjkDTmJWl5+NdzZ0Jim+hxOz5DnxpjHBWSemYPIHcAIwOQeDu8omSKIUEWjCi5VE8FElRzWsClgdSoMVzEBMJnPKXShJ+5Cl2oSadqSOJXFllramqe4sJT0rBXeZEmO86imDapOZrdOAPOJGd0JYK596V6PYX79RRIICb4xZF7SC0RLhnnn5RtiZ3xNnL73Sv+1vHKFrmW3BL3jaSruzUZzZcastZwJgfZIMycJRglHDy7gCMWBGl05K3K0oDpi+yMM27gz410CMFXHtxdqbZ9AlHCbyIRsO1JOi8Igu7IjEYGXuYbuBTOmRGuZ92QPZlVxv2rO/ONPnvmnFEWBo84+2GUDdtkzSvxuAJbQQGIDGBMffTAeQ77IqRuYMHGxHkZ0AObpEdGFCRdXtH/w7cXvjHLlisJ6o/mgwkwaNA3JFdW0zmeLrvzvP7b5wsiqEuwSx57lZZzBcm0UXx/Lh5RgGAAOQXuz5DbH6n/7yt7nxqOsZttkrh0DF68+4eAE2GBc7J2UEUDG47hKcNv3MqGegaK4h89GnGCEtGEdkLAOEMY/i9RgnMjGjDEP8qDwaYphwCNnmFnnkJ0ZA2McTt4KlisKvgiuJaeiybRHDjH2lgDM6OZ9YAeeJgS7U8y0TrHlXnQGfwS0C2hOkdaOHSb2mthvNmCURKK0MV/YqMd90lGxoNjkxNpMb/pRHWzTZG7+3e9PFocMk4jee26NYWIj+7m+g/fatRfSi/QiXR/yMd+wEI0/iZOR/ImR+Mf3DVfay0etkCvd5de/3oPk4a+1p//gy1+Wl14uDh9sTn3wmnhueEVcx0cZib0dEmaTRro+GPuSEJTGPeFKnBNStgKXzkaRNPUcQyb5bCx02JNBjlg25FqnfLIKMWBgkiNbimBr9ovLoIWjwAEaNWntS525FHp3j+7ZKKpvcTRHqdm8ifms6sr7B/U5F9P7Xri69YnzG+XZg4oExnCM4ACsFmAZBftiAJQuLsESNxOksvXjOWAcoJVrQRt5otNjkRaLZv/WXvP1cWF2N7fzJrfKm0xhLGV26T0khUFXTZu//5x5z89fHV0FWGIFgHF8eRkf6h0PbZE8Iw+Mk73lS6vkANhgutinvnRz/u1v7oVvj0vTWqs79i/1dsiIgrQ+LxNOd+wl+wANvqjzxpBtR8w6IRbnMZ4lpewQgrITeIvDDzCRd6FRcRf5QeHSFIEdskseL2OgRv8PAvQ45T0ChzFK+yykRogs+rjALQdypSTJBWOxp4QEqk4623bo/AEDRXd8bKt+Dwpja144hAyDYYrNUYzTLolizJdz7j+v+wMQGGYRmthATXDQYpma9MYmP0LKXM3vvDKZv+5I/m5K3FU+/Lqxtrc8Acy3pXD9rQMmdJfXPk1pyTBvT74sloC5c/dVcfUXf5Emt1YMs/vaHUkXL9J2RaO5aCe8q+TOcKIClRKyYzF644UU7RxDbi/ebJwKstdZJmWln/d7S5zJRY4rOFdKiNSiWKFgK+Q8BhMKypLRXFmB/h6PBCLU3OB41JFuapfNq668uz8//6Dq3j2ddec3jHrqo1fPPTMejfJ52x94cHBxA1D2oNkfX5hp4gZyCJioPUss8Uld0969v3NPyrizvVkcbG0W8+2tssmMCMaoAI+k81EFyIi6aKpFNfonP7v9cylKg1F8qbsEq11exo+wymPHH/a2D3ZJCNkBmJsFx2G6//WPdz8/LopFXugWlkRmiH3mG1CxN4hDMCTh5MTIPbC/XpiJ/yVHvi8667M3o1A6YKCG/zx0LNmELYD9TVbIg6ILUxFlEB6heP01nRPbtUTXBoMnuS4KEULmZSNzCqFGGAcQmlcG0YKJ85XcpxhSwOeNBanh/DkdUa6GX7rQMFly8yQQl8Iown8OwOTe85pSXmIkh27zIAWbJz9rRLBt0iZjhmmtnB0BzOMM88OU6KWBYb7wQnrxxROGuU7+3oYj+X8uwOzHcIPOcOgyLUZyIU1NvUfcWjQa8l4SOW4pWqmD4aoJAGY0U40GSLZ8DICZYiMdGT0VoVBGSw68kEhNV4geh2hG+E7prot2VlX5XuXOPFzU75pO2/OLebtdt2Hj6e3JuevPnttSJlO1S9QMlsQO7HLYYYbUs0s++KLHEQHD3ocHd+/NqsVivyzMYmMzn29u5rPNjbzaKDKX54hh470huSCUazuzmLfZp54rf/LahewiVgFgl9hdAqjfECwHlrkE0kFozjIjvtznRNsjom/cre9+8XbzZ6Mib4wxrrdngzVC5QSXN7yZEvFtw1UcvBNfcj4M8etgY8jHdNzFuS8D/nG8HIHwAF5P0HsCeXNK+7kXByxCT9I57EoAtIrQA+TZXskCeoi7ksvaxIDZ1Qmm1Mh7VAAm7jr8yXrcq3gkRwAHzlfKFAFPAzKtSR6AGZNJ64DJP9Aqxdz3UXA9YPZMU8MJZJs+hLjJyFp3Apg/wPh7AphHdpiPH8mPM8yLExLbL/eve/cuied+sReq9ztMou5rJOkiMcPcc+1GQjNjy7mIoig6USGtJ8sYPHMPcXofqFFBwzIApo4kM2tEEI7LzGZxbg3U2TySG6wSOVa300LPYyilzkRKQbLwJYfyr3f38Ou0wXYp2r2q2dqt2ysH8/ZUNXMbVd1utFW36VwYP/f02VPveOrMuPWIeUvUhp5VLpnlMgQDwW37Dx5WOzs7B4XVdT4yi0me1eNNW2+Uph6NszbLbMyUQEEQ9DMS2RKLus1M8Kf+0ce3Plp1QrJXHWuJNRnR+kV8efjB89afXsqMlhdzPkABMEv8meJv/cn+fwjK7uWZ7mymPWSXUeDwzPlDbNBk0w5kPCzKTAyYzEEBrBIyI9gAJHIzWeTOrOduZAAAIABJREFUozoMPpK4PQ0GczzfktjPfZoqoKgkRBX1HnR8nICSj6EXiCiYLHWy9c5Kci7YXpwufbJCBwuZEXrio46NrCMqLXB1i0IHZfQAmIa0WPDTAfFv6D43Wx6dQMw+M8tdQMwwWyJ0AfGfWIri+DMwzBTm89174xnRK/x2O+evJLr5WTp94TKP4befrdOl2Yf5aYzmL75IdH15Kf/MkXo0+o1Pf/pwdOd3drLD/AGg+Mf2TZ+MYSJtell0NpmQeLkYAPPVm+K5q8/RvbWRXH3+nqLz52lMNJqO20nyw6EHXFEJWQ3pRQbHm9oxw0wKUboj0aHT25MAWGbWsXEHx54pqsQBgCg3g0B91mABJp0Wei+JkXIDQCIiwoBvsCpQyEzKEKJ2VdQL5Uf7XXjHtPEb7bwrF4t20lTdRlO5SdN0k3c+dfbcpYtnJvCQ115Q6wCa/SgLYTd2lvsPHiz2dvZ2ytJWRWmqcWHrSZk15ch0o8J0xppgIfxUCK5AgEZQlfd2MW/yX3v/xk+d3zAbkDFhfwkZEesu+5qdfgZekxD11G6lxVwf1Tn2bdBl9vrQRKdGgu7P3fR3/3LxJ6OJbaxVXnFBOjgl/z0Y+KhPBEECEZw//V4STh/sOD0iltAOyR8YMzsuPuz84Q1FxOv1x6GM0n7m0ky4GILEoWnwq+NhCrYgFrljV6qCMp3XXYLlyguc4aLG8Snpmvs6EF+SYJh0CDRGohE+P6ODEjrIaPqjTzyIKiau6MX7HuvSBy5II4rNPCFPE/IjYGhe2AE4oR8Fhe33kqXKpndeodUOE+HD8xuHwHccMP/ZZ14SZ6896F+O8fz69cPXPQHMH1uQ+2F+Yj9swFxZIZcMU32eFJ0nGo9pNM1okhYk3bwV6JcAq2TAHBOZA0yEA2CiwzYbia4ZAHNkhEaDNrKAvRciN4qZKjIeAZiN114GGVSm9n0ckwwSYz0fewIAU7FYXGrulkWKraxELKeBLlXBjbrO2XYWinrRbCzm3aRadJt15Td/+iffeaUOWgM0KwDmAEy5TmRl8C9/++XXRkU2m2zki1Ghm9HYNvCUF9YGbVRAiK7SOIwH6HpE54NeVE3+VCku/f2f3Lg2rXsZ0fIyjt3lIWtcG72XOsxDIF1KjAZ9Zi9LJ96lZkaAXbIL6dSY0r/8s9mNnSBuF5nutNZeaI7NgICViSL7eLDbBFRa4ftnsmcdCU7YQLCZB0l0GMsZOiFchw+Agz3gIkreum6aR3WAUnWZJCSk/WfFzh2IG4YGSUVBhc7rIFsVktfW+7AETPQUw3d0DDD7ABAKtph4SI4CSnsWB0lFh/C4hO6mzBgPHSY+ZMOAaaMybeq403wS27YlMMseMHFNz0h189lbYZgngHkUe05G8jc5kr8+w3x9wNRqMa5KPYkVybbupBrZZIKQNcZq2QkEA+toJcZuHIbgy+tHclzYDYnOK8T0cJK6WgdMEr7trZJtDOZA6FKgukwEaWHjDqS1UJzBjqpHZRHLE2UnVTYV8WKXUuF81H7hrGtcOZu2o/ms3ZxN6+2Ncf7UM++4eP7hIhGOQWB5WiXazAU9vHvvgWvbe5PNfL4xzqvJ2DZ5rl1ubYB5HT06miOJA8Cdq3CaurPzOuT/6KMbHzNa5kt2CQkTmFJvwF4J1deZ5mNBcwDKJcj27p/E7h8cfyBx6mJs//c/3f/SaJQ3eSadFJyk3EMt4jhxOWfNFTs1PXaXnELEIzv3aUY2VvaRRhGMEsOAiOwbGPAzgmEe5D4dSCm97zxakCIeKPjIpKVjaRK4IgDUd65IEsIIcPcApSh850aoEDofLTI6nU+qzBzAk0OODMritVfKMEOMXZVUC00mJWc62tRbDu2SfDWH/Ch1KVMm9oC5HM17hqkt8Yjuw3y+uD2eLr/tdyBgv3mTTl/oHjuSnwDmCWAePki8WVnRMp3oWwgKJqLtbRJ3xzf56d17Wlx+4Qrt3Rl2mO8gOnODJF0g0vVi3LZ6A4BZeYRq8P7r8OhjgpO5g58PWmsr6q5SXImLq3iqFVptuaER9mwXFOomUDuB/1YazWJatCGYRoqSNH7kArZfwqEKkhd0iNzhG42ChLKJlNeZON8pyqJLMganUyOzRVUX02kzme4329NZc+r5K08918gs36+5zgYZlGRT29597c4rm5vFwSYAc5Q1xci4TKmg4CPnJh90biDnkhTrLl1Ss6rLP3ROPffxZ8tnDgZH0QINC5hvkUi0NoKzUH1tDF+O5Mvn994dtuLwdzGQCNQPxx+rBY0ysExir/sfvbL4/o1d/x0cgKxJTiicSxIFHsc5J4T3jQHckyXsOH6rGPCFY3dPRL5Sv8PECI5R3OCM3X9YSjJk3h1kJPbxOkH0DJN1mFyaRt4n1JhDWIks5dCNk2w4bI61TIrZqkEdZ+fZGikRzGEzh1g47R1bxo3ER4Zk1CRqO96/osNcFpQyo/kIhK9FgGYTnnUcfTCSwyiLeD6wS/abN6lBrYXbnbvddx682R3mP/sMibPLQGEeyVfj+8lI/sOcfH9s39cbjORrMisWqw9/hxvwjhPRsoYCB5/XA8ypJXH2ZZJ0ltt0x66iDVWQqBD86zqhNqyQno2LAmlEOrieVUJ61ELjDO81iZQZzLP9EYgB0yvVkUQqplaaZB4YMDtBZh5FyQFwCIzjQDWndVTCK87Z0WCZuO0GEvlMxvMe4iPErUO6GZzFUWg2b8vZfrM5nVanYhDnL19+6pn9Cj1cfIlO927duWV13NneLqebY1uNx6Muz6yXGiVjAeHk+NgIoAMrVTh5VHVn29aV/+PPbH3EBaHhV+fd5ZBINPSOPbK/XFZTrGsyOQdpORsPQDkI03mmR15moRNtlL2QPjfJ//M/3v8Tm2VVUahOKhHUoMPEHaqX0ksYtznGCGFKvJuMsLvzeYg1mwjj6Ped/PIlIebdSO7EgQ10IJOLZIoOfiLYI2FPxzl9kA0hMzmQl10ZqYYMvq/2BbhpyIeCa0LKDTyXPgmnPeRFyNH0IqFsOCAGDgwzpyK4uiIAph2X0YX9aGXZVxoFbEXhOe94hzkpTJx1HY2CTaLM4sK0KW+JZs7P3e7o4M0zzHXAJLp+faXR/I1Pr57uVxEnwvUfW9h78k/srw4wdUsTF2giCxLtkGsJfaUSczTKCumMSAV2lkI4MqRcrR0hV1IIqYnDNSh6idi2SF5T7XHvEVorchS0MVrMHdlO6SIRTNJKkHdSScS7BYCyFAH5bgT8RId5NlXygscpiNEGIKe1a71umi6rZvXkYL/dOjioty6eP/WsLUcTqLyr2Xy+s7P36vZmPtveymeTcdaOitwrY0JfOInTfJ+4DqLpnDOtj7qa++xvXs2vXT1nT4NdYhyH7pJlROuJRGvHniM7y2H8XvnK8Yw+sHL553JKwAEIF3NmmSNBZ8dENx+6nS++Un0jL2WjtApGa04G4mQOBGwIBFYERklunITDB21E0GmGSEHzLhKMk8ETTUUsRWXHk/Q2hIMi0D6yipNERyQUST3DTDpzuPzIIFOHw1EgXwS5sK6L0qAcE4kkSE4CibcoAU4SC846+aR80tDFagRzVFFy6XhKZdrgfSbbJjMTKSwiQofZKqm4K4g95T1gpv7og+N/YWMYt4mmSMRUsxPAfHL0ONlhru8wjzHM6zde6r8+P/cCXfzWlwUNsepvxDBHloR/meTZs0R7LU1AejwyN3wnlOAkcqFE19dMQISe94AZvBEi1ipII1p0fUeSCpHmbR/Oy7WPdSOF1tw13iKFSGo5d8F2GTrVOOVWSPwfguMoCPAdeFK0RGQECa8p2yd5KQrKOAkN8Ja0QjSc64JpWlfM9qrN6bTbqBdu6z1XLz6H4fVb37n3clma2eZWNt/ayOtRbjtjZUK32kBp+W+FJWyALbsLpmq8Lcht/7cf3XrfvCEJwFzqLuFRZxb5mIv4kYSiYfxeXlLwuRyCJzvEeenY/wvy7kGssUwez9P/8ZX9v+ik2i3yrNOaF5nIuUPqOgtNvQJ5622TXPWOER3HHwYzVEvgC8WnbrwV5EP8YYGKluQeAyYS19EfrAc2yp1B2jEu42HJSyxIXB5llYUuSGkdVqfwnjNgatUDJiC7xZkeogmOeAuor8CIjrzMMqELCJ4f7Cwde9CRl8mAmZuI0jSEcvSA2ca2y0jrNsE2Geo2QQdcT9XMbYwOBlUR/ad3mCcMcx1e336AuRbpdlRERrQeGPx1WhvJ6T8mEL10fCTvf1KRTnTtPbfE3g7WhERTK0VslKTTRGav2TD2HDt9cPSxZCkVC6mgvTSGfAeSVoJtMXhqRTye82VBeG0N+n6g/4blMWikD3lE82LFWQkttBKtj7YtbYnADbZ5KyLdRIM/O5zKkUMslYwxSK9Vtp/cUyFJKzngNwqLdnJ2VCfVLOpiMW1Hs0U7qubtuGsB9RBMKzeZ5PV4q6zHmemK0njb1+ZyIDDuJ0i0AMMMPsnWOVstXPYP3j95/5mRHiE2DoAJkTrG8ePhGod7S2aaPQgyAV4mFjEZZtAa0GpIMmJA7YGTOR/K0mTigGGkw58ZC9qv/OJf/uX8z0p83kXGMSdcq45zDOvGhWf9JT4kKJpimzYeSziRiLVH7IskkEI+1DB4UvRFEvsm0AEiNnxC4CeChrHBlRilEevZm4v4ah5cHkWFkZy88hKNGAGTuQop65ON8HnJNoXhDkWqHDs3qwl9PyRNzMgFhcEfRx/ORwbYJrZK2q0RazJxKWfAVBSxy+wZJnEgB0Ts0+liTmdH+4cj+dOU6LNEp4e4t9vPUroEP/mgwzy6wzwZyU8A8/UYJpG4/tLAMF94gS7+5nGG+XjALKwUdxolz5wmOtgTG5nINmB3hGhdIcsys1wSBlaJAxBHuNXI3CVRDIDZBvyICiVSA/hjUbuXwdigRRCe/eKpQxOFEgsXrc9VyfYT6DRTkDlHhbOfCAIY1COyrbIlkS9kuuhhUhnqIoCmDHrI6Widrau2qCuXN63PfesylONYI32ZGzeaFCwGN1IklPzCOQjrI/A+dV7h47suqap2+TOjdOHvfmDjWfjVEUyMgGAuN+vlMj27XJMILUOC+xvGYU/E6uneRr4C0YFtLhvN2OMOFxKHHfdJSthlnt+Q6Xe/Pnv5fhXuFkXeYhxmKowAeE45Fj5wViYnvgEMcUDn/GGmkWnFGpNCfggX6aLcJ+ShOzBeHOgkUTzhodlEfTEL2BV1+AAIFA4gsUq2YJgaxT+pz87kzGK+qEOWxNlZUbYUEqLd8PiQaR8q9AxxxnsqFKH2nIvWgOocU8fBSERqbJARkhD/xoApiYGTbZNFP67jW73a9zP6yGj/kGGeAOZbms9PAPMtAibSiU7dtYKee452kVB05QpdnH9Z0sVL/J6KHSnujJQ8g9wDBszJ6wAm+ngeB5hOADCVDzpBRBk8g6kyQsPFg6ehv0wtaalJLJKwzqqRkFEl7Dy9k6gyR+04fJVgnik5hfIfXMcXPl7y+BHCuIizB5RAgA0chXwwXZOsD0F3bZdFzopDSI6IJtcR8iEkEPVsmCGH95YuoEM9KA922XnzjnG69Deuji6jSQaHHtggmV0OFsh1t8567uWKUfajd680H54GPA/sEy/pjdgD41wD05WYPdEW0uFHKFBL/vMv16/cndNdm+lOavJ9Vid0lsgVGa7mXG8BbxRqLPhuzjvLXk+JvSQaJSHTZO9ksN7v51HsI6Aj+uA5tFghDg6PUbLjdSfK09i0DsBMPWAC+NBNzoi8BEyUrekoW/86gGlSoZzHKpuL1JJLQpiIPxWayvMugoWuABNMsyOFdskCd/klYNKMPkIngPmWYHL1yieA+RYBE6/e7zDfiGGeHxgmbWjVbfbecUvQXSbVSRx8erZpUKrKzh4XncT+s8LCCwwTLZCxQKoDj+uGEGKOORhtW1h5EZegzb3IGiVG2FMGZHtjrlPRkI+YxGFqUSKCRQoBtUlt5QXvU8F/bQRodslwh3iKzEaRAhFxduhrvQyAFJ5whQR3fHSNXR4GfQTwCJGwjQtJY66dmLDxC1eLd18YyxEE6gDLAwRstEToOOeeniMHnseA3qD65rXkoYRo2XN79HksKT+8nvcv42COpZidZUZ9pcbpkUh3DkL1h99tvjkPdJApHaQWaGVHUc8Q/QYgxOUGGSe9PBSfcu/gGayRLGpHDJJ0Nop948OBFtpHiCjR58MFRhHA6xA0jLeFrEio1OouNIUyHbnANbz99T2FlnOVAuF5pqUAJMV/C/wzFDnEVySCjlbUQXV9lUXPMHvA5FreERRSLiGR3XWA8C7FaJMF/ZQp6o1J8K4V3SKbngDmE6Ll27Jmd22H+UaVFNhhXl/Lv6TP3JBcCYndzvVrdHdohty9ReLaEOfGDNOSePnBrjp1iqiui400UptAK868RBhwcgqltywdCk5SWZIMTkhvhBMzrRG0gZdZklquAFOR0EYoTivyLmAQ1kiSqBK0PbFMMRiOcEQJNq7kUKTwUQfbTK8xgnsl8rlWF2Pi+nOE7gghIPtGDS6Gb9TlQp2CcA1U0WDC6xPewSQRNQ7URlVGFIQuBum7pISI9m9eLZ7/iXPqNHrFcdyBUwh+cciIAJYYxZe1E+s7y54t9l/Xoa6xR6fl+H2YvL6+21wy0ONjev8++h5z0Y/mWc80l7UahRHpL+74nS98v/5mFLJTRjrJqet9p4WA6+ZwnymhKgVfZGMkGGffUQ5qrb2huG/btK+k9Ej0wNpTKhMR8xTFcDVHLSWLYkNrnKwtea+jxfm8F8qr5AGYXJwmUsxS5gGIAMnU+BBglcx08s6T9FXIhu4f1GeQLPrwYSw0xx0+xai0ScjtAGACOAvNHwPZVRFHn273BDCfHC7fjvFuPyBgcpwbaiGvPke78I9jJB/i3PqRnMTLYVehirymYiPJMACmJeWdQMYl7zBrxyM5jj8MmLYUrp5pXRSYAaGohMlZSewsAwmrtY5oF+uYEkmpMZsJuUhknRSjhKICtgs5FVOOntvDHSY7jxVi1kKxKLMLKEEDHnFp4cBU8coiorULBA0VX2wMXArnQYFQgqNDEibFYLuYis6F4mOXzIVPXranlBASTBK7StgeuXbimOayB8yeBy4BsR+tjwLfEkSXV/Ajf64fgoZj0LJfYQm8fACC+FT2/T8jm2izkJzdicDjSc6K9PDvXmlv//k9f1Mr6RRy6bWN3GyOK7ng3SNG6SDF4I8E5g8ME7IiI+Se6eIBvOBJIHM5crcwZEghOOQls7YTwi5FqVUu1Jak10I5pLBjv4nYpzZQlAqE3cdMDYDZb0UDyoJ6wCSSfhqyVDDDRGampI0Q2XcOr/k+KWsClgkATONTbDyJMcewpEhbk0htSx1lU7p2MpI/KWi+rUfyJ2GYO3etuPrcc0RXicAukU50cUgnOg6Y0442hbabYJRgmNQ4CR0mRSfh5pHCCKe8NMNhp2kboxHnpg1uDooj2hjHIBNEYDDicHExRzhYh3cg20i2tXpEQek+jYxkClLxwQfkEnpmz94ftLLmiyw7H6XImd0gm0dCbYgPxWs7/CgaVp8LpjqjKFORhMBcmMPEjP0mmOyVPBW/8ly2vZ1LzWntAEtHBBcPZ1z6tY6e4dDTB2kM1+4+FffRa/iy9GxtHF86e5b7zhUbXQLvUfa5rs1Eadqyz3xZq7GR971Ek4xotyb/2Vea+3fmcVcZVWdKzBXcq0n6mKAWhTOVFasiCSjLsQ3h6I+gXNrPQtrHbTzhyMNlwga1uclHh1sYHtow2kOv2uogKh0DsqYc6jD4Sq59gHAA5WnJ+WSz3k3EEqOATwAME+4enaidxgzRbnz0cUnRRsAngR1m0Au+shtpIgCTQzqwg9G9A4gKw48rdRWm9kPl3snR58kg820OmKs4N3z5vn5t7b9/lejoSE48ku/cvSmuPkd0mFB05Qo9HNKJ8D7KAxLf295T2/jmrGmziKNNO8JPBMZuy3FrrMH0RgTrBCnPO0w8ryMDySWbdlLjNVSCGlnAOPXE3jt+GCIMXWYkWRFZb2iUhOeRnN9T9NqggDt5KZWWUhq+0zuhs1lyF1Eqw0wIij9KWSAaBSHHUYmJJzFKlCxbMjF8p9ipmFqopWPn04YK2a88V1y9clqNm44EwJF/D0VmAE8I09knPsTD9bvIlW5ynTEeXsQPdZW9InIdJI+L1NdHeO6RWILvOvtcSo2YaQr2myNwGOVpo5xzUBg0NwtB40ykbz7wze+90txbgMgrgdUDvFmNiGlhSMxlSJUgqoeqSUiHYMPaL0JgayRGcLRLQlKENbCE7RzuSrSFRAoyuk4HyYAptHRYNHMUXGCLpIezB2HBWnoeyeGf8l0DE/ugw0wJGe7LkbwHzOJ1ATOPJi26jjZQloaLeZGipYwOquoEMJ8MK/mtTgBz7Yv35gCTBsAcMjCvED0c0okeBcxiczPKTZk54TB6LypFZgspC8wwgyURUq3AMINrVMomUoqGGaWKuewBE1cHEtEF2wNmEEFiTZepJNCMoOyC/AYC1Tj/Ehce2CFhJ09w/RjmmiJ6hA/rPQqXOy1OOSEmPqVTgmiC9SWM5fgMFaVGpdjYoFo4CKPHydjL0LjsF57Nr73/KXPGB5JglBUY5dBfzkA5gCWS2jlH8zCabW0MH4BxBXrL/eXaHvPY9Rs3luURaH2UX99/rkuUDhlof/3vK8vgaVK4mPNej0f1jaxnmgBNhBBnWsQv32offP6W/yZliF2SJiiVkaA8qYRmNCcTzXWMBybSvonxThnSDs/3iIkDecbpLCLR3SFCpT/mkMSXpLMuVKiqENo43K3Zy84X9OT7qkwVhfaclamRVdWhMARxb5jOPexantuBOMvTJaM3vKOKEP8WVIUNQLTSRDxY4c+6cmKUG3ycCD+50jbVFU3th+iEYT4haJ4A5o8YMIsoN1WG3CBUS0AQaXCKlZi8kUAbUg+KYJpJTqQFYLJ3XMOhA8G5gLBdyIFhhscDJkXQUicBlJq0koy0BBiVrYrjudDnFyo921C6LJXUIsXaRJpmPlU6poWIMJwoCBQlonkgKexCMsF7/eFz+sonrtgrVgp9yCjRMAlmieK0tU4evoSv6SuP7iGHKLcB/ZYj+fLYc7i7HB7LjxyB+H2uXdUHb06/WVjtRpc70eOslOMwhy4iLcE2Bae1j6zgwxDGdKQdATy7mPznXu5e+cZu+I6x7BVIwWpcdnJv5MgLGifkkUhaZCG9lnfhVhbkPSllBdYOgJcqOewymUVyylHo8iAXJsEtJNFFEZHODsAEmTR4ulNR5J5dP6ghwrN8iws7nD6UpE8hg/n8TQAmRvHFnGijxMMhxU7ZiMqS+dwenADmE6LlCcM8yrCvHRvJ11si6TPLkfzxDHORP+AHn7N0lpYjOdXFplVyE5mXTXAiXwYED4lELtYSIZIAT4fg3+XOEkef4HUUGspKZpxBBrN6WsMogmu4bCXZJgkcl5TsBSnJaqM6QcVU0lNznd7VUToP5ZBNYl8l6myiClU7MnDhrIGwkLPGSQjnkwFF8p3X7xiLc790NX/+VCkKBsfl6O1WPeK4fsPSsuz/6ZOFeq/MkukxeA3Adqi1HABwXW85xAAdXs2Xek22yxy+334wWr2/tf3l4WX9MfvRQ0cQwpB7Rb/hIjdU9gI0UXUhaJMZZ//0g0WqP3tzceNBkx5Yi4Bg4YRG4yR4PCmvWOwwCipteUhqI7066cKreSf2SIoaKkxhYcEM0XvXjcjMVQgo1A3YQgvU71oL3aXnKzmP8FydlCw84SEFhAoDMDs8D2/HbBLyBZdIFx4J7PCaN6pKlq/hphesDwJ2vpJjhwk/u7XUzekEMJ8cL09G8vWv3VsBzEnxith7oAU9TRRuPi3XAXO2TbzD3KtpkxR+O4kkdR7DHWRFXhSkaY7Jmxkm3DwgkauiM1K5FPjR0CiIwWYStwJOHxLw4AkXDNTjtYy2FmKiI0oknaqMOjvX6icaTZfRm5gFd3cSwmuToPZQ1jCX9JTQysLzDcOLgqwIUT0ocvCd7ZpgxjqVf+c95fvedVpt4tJ6BCwHeyNLhdD/M4RorOyOa06d4Yu7HL9Xu8zHjN+H8qG+zvc4a+xJ6bDbXGewx3afPaNdJbX3Tx89CvUfvb+k85iuenfQ2CKImGhryTZxGMpF+sv7Yf/3X178RSfMVGrhCZF2QjgT454NtB9FMgsjtmqrnnWUtmVMiyLJvyzr8L1cqVnn0DQZfE5yrmIXhM4d9Fg4vCljvUeI8ACYyWLU4FxODhb2wfcME15zAsPsAdP7mrJs4pYFaUm4iJ6fnMqAkZyT1+foisJ5PUWb274cbeYPDi7v7tGt/quwd9anyV9cSSfWyDeHoicj+drX6UcBmCrRVtJONsKJ3JeiSxWryMEqGwZMfG9jT3kUMHOVyy4FBe2lg75SdIZ1mEhs1LqPN0LiOgk9z9XmvlRX9nX6gJfyTOHCwwmJb2249AAeFAWpEGyLUhZzik+REtkyYxzNO3BIex908NH8wjv1ez/0lL0IE9Aje8oBLBkoB10l7sjrsp5+RF6/Xq+xw+Hx+cjYPBxsjhx/hpF93c1zFHRXO9H1bMz1Ef5wv8lXmgE0j6W1DwtOxEIxaOIo1Gs3e4a5URBtFz3rNIril77nXvvine5rFoXggrwl2i2k2OG83yRxrsaSczSX6unG6stBJFsk+fKoCTeyzt8vvVwk0cV1wKQ1wESNpbKKY+EMaGcij4xMjO5t8ilXqrdGQiDPGk6Nf9uEkrx+h7m6krOUiOt+esBMue1j4Gb+wJ0A5ptDx8e81glg/hABs5rtitN0mtIzZ2Q23xet2tog77YxkmMvaaik4KZK4hDDfTfQMKPf3JGFxCg0iAEWDKFKs5SQa3UxK0cwShLkgwS4KlKog7F9pzG7AAAgAElEQVR7hXzmXqF+zid5rgj03W0SNyZ1N7dKQq6CdR10MJAkCpdisVB0CUcM2J0xwJEj433SHzwvL//8O827Cy0MGCX0lLh845jDTh3IhFDDO3TwMKM8Euh7LHbtmO97FajRs71DoDsuI+Ju3H4vuT6+H3f0rLPGQ8cPD8vrF3l8EsPHGoI71o9Nyx0quCseURDGYQ2f06jEbhPjeS5oC8BZAjgF1S65P/xO+61vHoTv5IJ2RkrvIBvfKenwDtD+g/5yr7Sc2XSxsvJ6F9PEhnjjfJW+NOraaX/0QbNkIMosP81echyA0OfOdiMOI/bdAJhw9miVPMvlGTBdIlV4Hs3JEEZyw5rL/ugzkini33CEbzTsMHMb4VaYzejAXb51wjCfEDLfDoB55O/YJ9v0vz7zmbeww3yRJF0n2nmVxNWrRJNbJPYeEI/kZ2YkZ3a1w3zZ9yM5ZEVT4bYxkkPHBylRrGoGTHgTa8h9cljCcVX2UrVNH6ChNWWC88EUmifAKmEMB0tUuKiLIHesPne7UD9bi/jcKIjvbrvw9dKFOd5l8sJoowmTHiWv4V4WQkIjlFdaXvIJ6mckRnj9VC7O/p33ZO8/P1Elg+O6RGg5fmNPCbDkbvJVKvpxdnfI6gawPMI81zWYy7F5Ge+2Bq6v+z57Pc8QxrE20q+P8o8Zv9f95ocsdQ3oe1DGt0j/fcEuIaQeDdf0UdZLkDbhFiqIhe8A0Fv7cfEH3+m+MJ11386sbkmJRisNO06SUSIhtJMItRdCzVW6MM3pfUmobNy4L52aib8YU6qhw5S58iF6VkapATAxwJtIzDAjDJZ85OEQDg9ZLB5g2wiJV+6b2ANmqysO70DjJHSYW5LivCNURzHDpIFhUm336WO0e6LDfDLEPAHMN8sw/5OA2YPvWSJaAibvMC0xw2yDE5koRXvQM0zsMGtEVw6ASejdOWg0woaR20Vd0DFprgDHjd1IbSJcP0Kb71v5np1cfMomuX+mDl8apzTDVBlcVGw6T0axNxxuodBbwHkcS7GsKD7tUixt9MXfv1p+8Plz+jTyNw/3lMNxZ9kXzkA5XL65TuIw9GL59KoqYj1N6EjI77AzfOTqfWy3uHr7VajGciznKX15+DnuDFpWW6wD5gDK66P8+tsfAfcj6Ug9aGKpAH9AphMVBrKjXnqE/SZslrBbTjKRvn7X3/rCt+rfc0ruKm2cQeA8dhzGtojWhEmVPGLWfZrl9pkDmz5iSd0+c+D/cNy6h8ZYj0c2zsBkFZfyhmt9fVJK+ar2DJhS6gRlu1UATKK2q9NGPvFNWzFgxsKlzrtY5mWEJdIgc4n/0XuGmXJsJiyFmvbLE8B8MrR8m1zJ/4oYJon5lARSih6UJLM5iWCbzcqrU2CYXD0BhlnXCg4frJaiIUVFQWiFVFaLOJ0blff7TAtvuMgEpVZiRI+OTGdT+WpmP3xgxMfOEv2HS3X6Cs5FdfJbSSISF02RKD4zSmrQHJ40QVFxP1W1c+OpEE9/+Aw9/yvPl88jc/dxQLkcvTkZfQj6habyKMgcHX1Xh5ZjrhsGseNC9JXD5/DavQTVw53mSp50xCG0HNcfYaX93nQpYj++E33UZjnIlNZWAsu357m+F3Ay27SDWwgSJLiFwDK5oRK/Ed2syP/eN+rPf2c3/YnNyGlSTiC5t6+eBM+MKYY2U3pRpbB5f5J9EtKk0wv3/56q1HcVxOpgmPgySeUBkBxoFJTrvxyQaepotAs6FpDHs/HWigk8ViRjkea6SlzPS2VghpmlOF/gkNUDJjI0ocN08/rAfKTYOWGYT4aZJwzzTTDMn3uB6HMvkrx2nejuqyRgi3x0JB8A8zTRg5xkNiOxqJrNVqhTvFkyRBGOntrDeCKQpE6ZZrFQjF4YaC4br5RteUdpCR65INFJgTF9QWlyZ6Q/OlX0U6e69PuXo7wp4XaW2jYxbqIiBhpPnB1wwoBypk9UJxVdNF0Ium67jWfP2o/8Nx8ofqp2JCA6Xx/BEe4LkASjZPH5ceH5od5xBWY9rKynpx9PIFqLYFvXSw4yo/U8S7yjPgFjFcTxKPAdzcRc7kaPOoOOBguvs9RD7/r6jnSNmR6vvwDbxK+lxRKHofEwpnMS0qj/vVVQ+u0/rT57e9beMDJvxEjXwDzIWqG51H34xtwKZGJY9b1N+pRTdO7cLP6r7aZ7VXHwfUBiOpySBG+5St77wDIm6pJPmdR8QQdgYoepVe5lxAqgSFMzxcI6psEauSVNhNNn5CxHPHcbFG1naR7r/c2zxc7y237nJA/zLSHnCWC+DmDeOPuSuP2tCX990EzxtS9uSlgi0RIJ//jlK0NT5NASObMAzIcCwcEP8jMym+2LRdza9IvqNCvh4A/nRpmlNdILUkZGqwUyL6XRwi0ajTR17DBRlYsfN+wtF5LMPSPe/yAXnzrXhZcuL+LXhOWucbR72SrFTTBMBYYJx12UWrLEkq2SyvtonXd2Xrfb//jjm7++matymSS07AcHq8T4zXbGYQRfMspHxOdLJ86x/eEbjeH9++olP0ftkI9JJjoS67bKxly9/Tr7XMqIuMrxyKHoiCtozUK56gU6CvxHMjbXbJbL3DgchXrgFFQOIcW4op+bCLowEbRo08GLX57+VpbphbXZQmjymq2SAeLWxjj41IPDlbwK0X5/S/4yEqfOV/H3Ntr0gNOO+A7eX8IzRb5p+9Ga84yt8xbvib8+AMyJR6QbnD61qcCGDwGzlBTxYIh2vKWsiN+uoX1zllYMk2t2TxLX3yxqngDmDxUwaQDMgWFG2myn1RmAZMwNTNuQCHFMpfQ9YEqM4mg9c57zLAW1fBnPZS47z3Xf4m4pL9wtzC/mwT949yz+a/iMk3IWxbDgqVVMm1IjaYOTIYRmDbxHVyx+xpWPwlaLttiv6zOf/qVzv75ohERO5Ry1EYOlkfWUSGHko87quHKoa3yjyLV17eMxH3gPZ5g1h7PKkmW+ngd8GKsPmeuwClivq+iv4r2H/IiXfPi3XNVcrMXArQHg4aV8+fZrY/4jYL4WVIyXcao7RO8sQ+oPQAgpvrQh6cJEht986d4/H5XlQTHWUyk16D7KyZGv2eZNmguVOiFyhz7ifS027ozlrxWU/vz8nvtjI+TCtCEIpVhKBEmE7wjBpixcN7oJWuT9SO5rEnbbkcNIrlObI7XIJWH6kTyPXWqiTSVXgnRJbY+CqjpRS7u3uaAVwzwBzDeLlcND/Vt69b+Wr/xEO8wnY5iPA0zHgIkdJtshHbIg+jxMSIdgj8TTPjZSeK2CwkjuxWgATCe1ea2U792z4hPPzt1vn+nkHuTm3jRGkxGViFkdxabm+xCqZHrAxNM4/ECM0gWXHUwXk/25O/dPf/nC35sCMNcqb9mlw21fA1ge2g5XHeBHEtDXRtgVc1zr28HbD+LzJTs9jHXjkpzVWL1ksUfZ7FvJw3x05F+y2CNHosNRfylqX7qBlm+/Sndf6ih6oX3/l+E/B8lTH1LcX9PLjOh0KeipTQHQDL/1+e//nxvj8c5oku2r3LZYJQMcVaTOdmIGhhlF7hI8lInSdyfqk21Gz5yp/GdP1XRbueCjUmypRLCm6hQfhMA7U+Y9wNEmSrWrKc+2PY4/UmneX7bJpcKWfCWHxAh/ZvC545Of9CN5LekEMH8AGHsbMMxVrS6zlpWq6A1lRW8FMLM/eqDmmRD1TAoEB+8WUmYLIXykrUUoeYeppBf4xo6LBgnn/HXH3rK1BY/kqLkKoIkysAQJT8UmqFkmJt8r5X8Rozj33oPut7lUQSnkOmA2Ey6pvKa4QQLFZwbuY2WkVgmbz+BVIKuqui2rqh7vzOsL/90nLnyqtKY8WBBBdgLHDnvxDgMv1kTn60LvY+6bdQ3mUbtj/93YM8pj7/ewh2ft6HOEnfZvu9RpPjbV6JiHnEFxrQdolbW5YpdHtJeHwLf8HFZj/CGor13kV+P7Uh/aAyfeDeQHuKJjLH96S5AVYfq5P733/2xsjR5kG+VumSF9TyNZPaoYOuP1VMfOC2GcUMQlaDuFPnd/LP+r7Sr9m1N1/KbqkgO7BEgabiNOiJjj6vSgfbCDlxx1u1rmXibsMHVyVHPa0TIPs9gofaydCNHwza0o+77yTIY9s1jbYZ6ndPMm0XgoQdt+pATtJXH22oP+p+ZFlKD96uFP0Ekv+Q+AvD++b/qfFzBnnTmNXeSSYfqGNADTBi867CuVkSpgPIc/XEgkreNYoyJJ50nNVNp6baQ+gQnwvQf+d5fxbqSFphhkk1TeiLQhJMI3BL+t5LQiTl+XiQHTlfNqvrE3686dH4v3/9c/dfHytBYCIb984FmmAa27YtYeXI727hwTnh8RqB+rkDgc7Y/ZFTlg8jEM7zBIYwW6Swa7Pirz8x6j4Ty0QT6izVxvmVyzbi4v/8P83zPKYzF0x5oqV1rOPtm9NIK2SqJLExm/fvP+ny8a963x1uhBMcr3ylw3AapMzoIOnfViKmOABZ1HdZ+ggYj5a2eyXy+r+KUzVfiadalVRkXBRWzwm6OjjeOM+HQOwETlrvM1WdIBqUXYYbYcJAxBQq/DHBsTIC+CGiNlKeaQHUFuRO1e6U49fGX4gZ28JcB8ka5fv74GmJ9eox/YvKCu+P/fv04Y5tq/77o18ofBMBeRtlIqT/NIrpGCDaeMYMDEGI5x3IN9YiRPXuY2l/gT+ZecVNSSmpm08dpY/UxK8sz7pt3/xRU96ADPnMZ2q0kib5TYUApBwTiu8iJTcwRwQPmOVnXr8sWimexNu3P71eJd79w0l/7L9108FaKSnUcfLKwluDOtGPg6SPLV+nGBv489+gwMcUCWo+L1RxnnYw9A66PwIy2SRystXu/tV6x39TEf1WQOF/kjDBvfEAObPP71GPaZwAXWa4lEY4QR2xhe+/697x/M22+PJ8X9ycZ4pxibA2vzBo8NCBsWAMyQZgqFEgNg4t0dZOns3VL93UkT//X5lv5SLjw8kBFCdTiANKGnHKFww0je5YjJZwAFYPLRByN58qmNKRWjPkCYARPVFR3eDtUVHdfxJgp7pStOAPMJcf0EMH+kgJlteRfPIJMS37sZWKUzigET0iLU46geMLXykmQuJR99vDAiF13Xauww747l9amkn71ShRdPdXEfDbykAZhK1kplTorNGD2nDgEwKcqeYfKaTKvOh6xd1MVe7U5PF/W75lW7FWs//sTzZ7eff8fpzEchHDgQmikGYGRwOWJ9XArU+1GbGd5yT3kEWNbY5LHR9lFh+zr4rY/ya6J47oRYSx86/j6PtEeu6z17oOzZ6IrNLhnraqd6vBeof90j3vWhEx38iSPiRN9/nhmRFnv71e0791/TRj8oC7szGY8fjib5vs1ornXeoaKij0wRTR7CTDjTSZG8UNxImb63RT/bSHr2bOV/d6OjW1kbEOvM4RuwSmZWeWQLcxGa0a7rGoG7u1AmUXARuZn43sKfuJxzyQg8sXnpUYMSMZJnkPwuCOO5ofnAMHuOOTl/Jd28eZPGF55jdvjGI/kJwzwBzNcFTBK3v9X/xPWyIhpkRSQORrfEO54mmu4oQReJzr6s5eN2mIuYbdUDYMJqx9rLYDTAkj+sItn2Cb3CGhLRDxmYICRoYkHTgAhix6iLDwr1KybGez8xC78HwAwDYHYATIpbQgmNI8/SpKKRGYxucqll6JJtXZ1Nq7S9cO3lxcJtVYu2bKu23Mx0+cnrF8dPnZnoXn8JP95w1X5sBuVRMHld981jU9aPpQixn6bfNfaW1RWzW8+zXAfanjku946rfet6CvshUA7X72EH+MbdQceCOdYlSVz3DkErgHII6eiqyt2+dW+/c+FhbvSBLbOdstB7xaQ4KMp8TjI1xlgHqoiSNSNEY2I60B4bkBBw9KmN3rg9sf8wc+GrZ+fx3yOXtIiKE9edRMSbR3svH31QYYHoN+k0cp17YAxQeMIJpPuK3lQnbfuRfJN1mI6QvB60SbVaJOsMLVTYffoRhgnA7HrA3KvTpTsf5qevXaP04n9cXV7/1V4N9umlf3T4mYFi4Oivk5H8CYnrj9ObPekO8wcHTB+zrYVTZyAjcpooa0k0mLYhG0JakeqLxrinx3hhfa689DLKIPKIHoM+7q0TQj/I5Qd2Cvpbp2v6t1dq8ZUlYNaKoFbaShjJ+7UaOA2HePCVHAZJT9p5ZyrnN+Y+PlPX7WZd+6xZtGVXu7Jrnb18tiw/8RNPlWWRyQ4mZr4M9wehw/zJY3vDdV3lKgxjCYBLxrh8+6OJQceDO46EaQyXuTfMwzx2LBoI8RDasabNXHYI8cGpB9rltXsZ8MGAOnzL9uC92nkCkjF+s78cPWXBhbt37lWzWbMwAEolHxZFdmByvZcXdpaP7aKQtok6dthdclq81EGp1BQxHZCTDuKyLinz2in99/DQeWaaPjsK6S4COBBvD8DElVx4CkqkQ/OSUtqDbgIwhdLJsxcWmxiwfRML6WIzMMwCV3J0+gBcGTC7BEn8Qs13n+Yd5jrD/CyNL1w+Acw3AVsnDPNHyDAPWtpug2XAxA5TNhCYCI3iHhtINMpLkbTEPlOaVsgwAufkfWf0pAT2mDy6B+GT2XhtRB9dKPHTpx39/qW2/Qa2aLXk5KEtVJ1zDCIqfdgG3bPNwC0zAtJBufBuXFF6pmv9uGm8bWuXdVVXtJ3LutZnrnXFB951pvzgs+cywAQzThyChsCNR5nasWPOseKypbxnlUy0Cv498r4eY3d8o+v3CmzXx/ghVm4NII9f7x9hqmt+8+W1YjmqLyM5cAmHNRL6870Hu82DB7tzZXVrbVZro3YKpe9lmZ3pUs2yXNfawqoVIXhoI84wvYgKNRNN7uOUfHKdFPb+Zva3nU4XTs/j72xM6WWtIO5Sw84ypE6plHucAxHMgXOgwiM/j/FLwHTB9Vdxgpi+CDJVKVnDtbtyOAYhYDgokzgfs+tIiXb3nDj14AQw3wQ6PuZVTgDzTQAmfZgo+yJJeo5odo/E9pscyQ/afDsGuWKYDYmGARNngH5/CbH64wDTQpMpPTt9khAiejK1ieO7mfrw3KqPT3z40/OL8EWjVewonhaEzhkJPomfdZOwy2RxigSDVUIgiZHKStHT3ruy86TbrhsHgGfnN5vGFb51tm28NDGIn373BfOuS9uqg9ieHUCYAI8GbSytjCuwedw+cKVvxJd6qW08BNPH5WEur9eHR6U1B8/x/eIwyh8P1mAtzbCEPZ6HeUQEP3ysQzDl/h/BkiFk49l+Txlu392psYe0Vi90pmqb2UWm9IPCqHsqN1WudSU0oWfOowpJiIgvGyef41MRUtRFl6bTLJ3dKe0vJJH0VhM/u7Gg76BZXEifbFAxqBCk8knELCFYGP5ydFgESakgHZqBYWZWx0VXp3xgmNhhWjKBR3Xcejz2lgS8RN9IQvYVjj6dmO1eXgfM2ZV0d/dG2r54jd/u0h1KL9FL/FNx9toLiV7E3rKXEn3604NR62QkfzK0/evxVj/4SP6DAGY7ACb6xRHLkFwwh82Q5FUnYY0Ew/QiBQ0IlcQpYXi6lxjBW258MEJCRqTznZF+956hvyGTaLe79IXC0Z7GUI97BEuSoiY57DMRwMFSeQIb3W6kutpQPB+JRr4LGbkQQxs633TeVa1wtdNN4yzG9M3SZB97/lJ5erNUXRBDC2SPAP2o/gYyorWxdh2gjgrZjwdzLPeYx/aUy/3mof98abNcBW4c6iUPcy+P1WQM2slH7Zv9UajXVvYJRQyUiqhr6nDntft1F4JXhUVqOZnCRJXZ1hiaGqm+V0Z6tbR65n1q4K8iLQNqdgXyMdHtIzgw35FSYpqL52uVPqKTeuXswv/+uPL3nVFeBOJDDwCzIx9YtA43VwjRaPz/HqgyjOTOs01SSJ3AMJdHH4DiOmCGFtdzk2LjBF4mtkxgXabwO/0OcxjJTwDzLcHYCcP8ETPMuotnkbDOaUUtCZSsMsOUWoToJYJmuQQttbi7KimCiALjeYbGGIleH4BmnoJB1AZ6fULScidLF3Zy87ONoPdkKX5vq01/nru0h+u4DIhFxKk1Kk9qXGl50Sm66IjOwpwiU2oo0VTHVKM6N/okOh+1b9rMdSFztbNN02ZNi1E92Ctnx/mHnjufG2slMjE5F3Ot7KxnZ68TDHwY6LteFbE2Ph+Lalu/Xh8RpB8J5ljtRx8Zu48A9dEgkNfLw2QaDw8p4tywp4w+3rtzv5nO6koZ1dpctzYzrc7x2waVWyNyVeAKJKVeqEi7VopXc+fvEMkOgIl8YE7XE9HMrbpc5eqDIpHNXPj89kH4ainFFJ0+QamAEx/KlCymhZaCQDW5zNBqEbXCY5NKxmKnqbEk4R0miDkioFHDy1dyoyP6f5YMM3k0VjoidIEqSuYUxW5BZEW9c/oEMN8SSK6/8glg/rABk4h2R1JmlRAHlG97Kc/iyOMNZEVCNC3KbgGYXoRIA2BCZMc+cMVMVGtmmEl5hcDgzgdpNWnhMZgFCfrjW2FaK8o9o67M8vTJJOicCeLWxIUbBnXhgs5VWrwzCjqliJospnvax4Oo5EbCRhWdPhFTe9LCo5AQay9nOtdZVwfTdd62jcvapsva1tvgvXnv5dPF88+ctSCty4s6pEiHI++RyLU1UOMn15LUl683gGy/z3xUo3lc3nPc6ji4FpnmHtGNPvL+VquEdTcPnst6ymH81jKl/Ye73f17ewuTqc5Y3WrsK4usMVY5k2XIfPYqM05K5SjEqVaq9YrOdlacxu5Yx3Sr9OlV4UVVa3q6ycX7vZQj7elrp9v0RdP4+3knG45W8ch6phgtwQ2UcOAJHs4gAGY/yhM6fcAorUrGU+D2yIgsdiJEQ8uu32HqMkXdmBjyno2mGk32RFT1I3kaY/AnEhk9vLCgnR14yPHrJlGbHd68eCT/+rXV6H39xurpk5H8bdFL/sMayW8OO0wtrhxLK5r+0QNVDdbI06eI9gsp84UQizmdIrJnFeyMw97SeaGAmBoYqUk1aIsEnGRBykYpWQQRQ4AwUkutBFgl11socJ+OE9ghK0reGfxZJZFHm87MBV0+sPKno5SXpRQLPBJmPn1jy4tvFi7MU0rCSyobq57GgkwAMNkOKTSOQ+gaFzKK2AYTXNCdd7qrXNYCONvOdnWXdY1HUI/90Lsv5k+d29ItmClkSEOvzzL38sjF+rG6yXVr5MpCycD5pvIwj3YGrYPg6+dhrj4mwzeHaPR6SqNFqg6m/vbt+xUl6kxhWm1MazLdmtw2JjOdsspJqzspQfBV0EJ4HdND48RDkYLzUNAadaHKxAeDpPMchClIGxe+OnLxK5mju0UQ+6jjTFhYIl2drQLQYyYewy1oKakgok+BH1RLn3D0iXlCqHDs5iwfAoDy10pCpOQ43gjXcuw+8XK8TGIkZ/csflWUxpo7fnx1sHO5vLQ6+pyM5G+JbZ4wzDfNMN8kYBLR/kjKvBJi4egU6fIsVogrwCTFDLP1QmS5bBJ0mB4NEjj+KMS7pRAgbF/tMKMQWuPOGViCBIaZ2miSJtGQKP4/9t6tSbLzuhLb+7ucczKzqvqGvqGBboC4EOrmRRwNJY00JqkJS2ONNTF+EMdhRzj84if9gnHEOEj+A/vN4TdH2BETpuXQzZKtEDWQOeKMxaFCIxGgQEBgA2hUX6q7uuuSmefyXTxr7+9UZXUDbQAkJ4JCJRnoqsqsrMyTmeusvffaa+1V5sX9in56YDpvE923hqH4vJyI6ybmm5OQbjRDvolfbr29FJkaKAvlkowjDIoivicThx6R5AhFs2CVQxv80Afftj2As+4wXe+CPznz9edefLLeWJtaeGhCioShEAALD/FQbH7UHGN1A0elPKt9yBUheynzj/phCiN+RE85DpLEJKMQolEepOxVwVKDKHSoA6BEnzL2Xby5eXu5bIfOe9cDIKuJ63xV9a7ynavNYJ0LxqGxzMDFlOCdlzj4nLdcoO3Iabqs/KXWmxejpZM2xjs25ZuD4yfgQVyn/FrT0l9u9OkmNn1SDjFLh1O0uAKY0qMkG0OkZDz+BnqYNpnKhYjmtDz+AJmSpE3i9tg1wNfij2lytjAKLkMfB4aJn8sBGSiveQHMHMLdp9zk7jHD/FA4eXDjY8D8kQLmAz4jgPmEaRa7PB/OnyaXzqqsSP0wsR8ugCkg6Qy0mDDf4IzYHrIGonWL2Q8GrNFaqyW5ryrLOZqIsryC+oj9gwk9ca82f6+j/FJNaXNtiK9NIm+jtdYzr7WGL3SGn49szoHtuARHMWoN09IOsEdiGNxKfIXQTaRXwxAHIZVoIwzBw3MzDNGiLO+6rhra6JdgnF2ohq73V86dqF969lxtnOfRoR09zoeNeFfL7lUQE2B9j93vURc5luGP7JKvTtAFoFcjM44GqInvOfoisJiH8NyymInevn23e3B/t7VV1Ve162v0KCcY6Nje1dVgLcDSIFYXLxZWCQBsUFn5ZLjJxvjItBEonyRjO5/ojWqgN6sh3mVOi0BU9Y19aok0KGYzGfK3TmBfPOY5GCbALjvcX44ulWl6tBEG+wBBJhujddGqxToeRpABUPkegAmGCY7pfJNQyudKGaZb4lXA+wws8xgwPxo8Pvpbx4D5HwAwsXqsDNOzyIhMYJTh6Fn2Xg2EMcipqLNZmmoWc1VnjZppJCCYi86UmN3epelWVX9m4fPPu8QP1kJ+pQn5AQdi9oZdCBaTccx+UyYfmNd7m5/ojHk6mPhsJq6YMtjJojb2AXK0DaKDEkUjhh2wUcCmUHTw8M45maGNbojBDV30XSsletXj627wIUT/0jOnmysXn/Axg94q28RgSKjTqhRo1XX9fcTnMrVe2QLC76+C6oHV2iiqX1mdlL817oaXXxSZEKuHJUrbB3fvDbduby+ds4NvPNhk5yvf1xPfG29663yWQ8IAACAASURBVKveewNGGbO1KWNkZ6kOZGfRmhOZ0gx8PFPaqyK/ZYd8o+Z8swq8j4ci0XMJqRAGtiu5I3KdT0+3lb1mYr5/YhFfXl/SO4iuwNCHAcQRbWybHDCSrQAmyvMhUkL7BsMemjR4jbR/SQHXJp2gB5hlJpNdthWY5UBmn8TyDUMf6DClh9lL4uSWSXQPphvywhz3MD8Ulh4D5vsC5qHjusqKThztYdIzNKZGxj0y84p4sUvCMLenhABw3lnQ6bYfzoE9ypQ8EvJxoZUUkGTQF4ApBVTEprIwEYasCMJ2C/WcGRkm2p64bm7o1J316h/0bC6dbtO/2oj5+pDyCbbGxYRdcgPTDYdVH830QQGJvTriaGi6MPnZYOhUzBkf+nUybiPn7JgpmJg6S7TkRAvL3MpeplSxiPWKJqbsYj+4rot+6AJYpuv6zvfLUPV9Xzlj/NXnzjZnT5002t9UJyTg2sPT7xEAV8H00CloZW/9vUB1JSpjNRVy3AwadaF4cwPWvISZUW739uLmza02pdxhiFPVVeca17qq6q130dc+mMpDM+nZmyYaMwuWG8qpTmxg5twaMruc0x7H/MD09E4d802ONDgERKqHCVyFEGuGKTlsV0S4zjl11lDeruznu9o/N2nz/3PyQfpL52jh0MMs0bqwfQMoRgo09OD8NqJJ7BDNBFdoWZN0ApJsG5moS0ne52zZJwx4hFEeTMmJ8sxLpg9KcgHMH1y/t34aKwlE9DpR96mdkdAT1iIfN/Q5AhjHq5EfCmx/Qm78UYc+HwUw7xbAfMJM9h/wvZ3JmZDTWTBM8bgkD3og5hsjw4RPxnsBpkU1DvC04CnEwUS/W5lzt2v7y2SoPr9Pf7SR870hpbqr+BRK7hxQYcMUzFiHvIKIj2uyxkaD9md0NFlmupyYaiFwhrAQVGVsC3Fej0TrnFFqwoqRIUcEYHaQIXHKAyP6MEbMalMYEvVtcMMwuK7tPXqbfdf7vhv8yVldf+qFSxU7b7rEBGMP0DSU349Ke1Y1l/qWenR4NOozV3fID6VJh2uNIzNVfopVp8Zh3WlIN2/c7hbLtvN11fvGDb6pkmgqq4pMZS17UxnnfPa2Fmd10eSkjpnnJuQ9zrwvMzYsLAL+wcYD3a1TvoO/ACkSI5VcxJdwAnCAO4IQwVhKuR+GJtM2h5S31+qXFlP7xaZNf7axyH82TXlfnC9huAGzYbIJ0/B+GdBDiMowUWc7+GgeMExvmxgtgE+M18m7SfR42ADT7GKKCzZpmo8B80cHVccM80fKMB8GzJNn+rg8pyW59jBHhok/C4ZJMMjQBr6xFl1+tX6zkay1jERp6Sc+qPKFOxP7y9mSu7gff289miXacktO097bkxCPpIjNIANS5WTlB8UhBSybYCDMgzOTLsUrkU0NKMV03CDqXGEKCndsLvuYszdsfDLUENM06ep7TbLqTMwpIb6XUoQdYwyxD2lYdgBQ6pa96Za925h6//lPX6nnHfFywG568bAs05fVsvkRYftDRhjvaQD8PsMf0bhLr5KpsZlmjc0/+Ju3h8UwpKbxZGcNVbVn2/jkPJzNXYQkltksLdsFU14wcceZhmypQ1fBhISJSmZw9cwYugAyA4Vwt058J6ecfEoBXFx2xx2lbM0grBEHzMZEkfo6pvsVNhQHn/bX7PM7U/MrTU9/ur6b/nxCuU0DZVtTtNBTYksnkugsPdKZIEVoZoOU5kjzRLIkgiVrAeQMwJRtH9klH2S3XNZ8cDjAMMs0LGba8u9ev3vMMD8aiH7sAHN1ueurXyuuQeXYvZ8fppTk//MJg7TIvW3Hz1whomeeoZ0tYnqK6Mk3yMwb4sVeAczLI8MEYIZzttJgMwjXB2qFYY6mwRCwYyqejGUr1m6YqFvinpwDYGoI2uzemv2F1uQXLuzF/+NE4AfskoM3Zmtp0hk+jV4liA34jQNzNGLvxgkDVnzUiczANBkcX46ZG9mgREQNSvZ84J9kjASnCX4WaSBmJRA2gbAZn2AEzuxjij4nqmJOPoZUhZB8D7a5GGzfdtTNO/6ZT5wza+szM++ZQJbwmT9YQXyvKfhq7s5KH3Msu1eB82gpf9RSDu4mMMpAumNq5+mNG1uhanxoZnXnfNVh+m2d6b21HTvTMtPAmVOWtq+Q4fLXWYixPFRjcoL1ELYQAD5oYSS66/q8ZTGozibIEEeUWsI0tcwGxiZk08W2zum+g3IygE9a2j5pPres+POzNv/+6b30NxCqV3U14Fr0QQUwEYImmw2RsjsETDDQOgxlKg7S7/IBYFKgHvIiAUxP2C+XfibupQ9b28vJ1uiwTq8SXfvioQ6T/oTouCR/fzA9BsyVY/PK1UMA3Tr7Mr9YUiM/GGBu8WJvm8/QGdpeBUwO5zgPJtY++96ZbmiNmG+kwHAjqgCYKTLcGuCJGQ280zEFJ+sqZZj3Kn72TsP/6GSbvnW2ja8C3tAAxSy7szRZGj5NGcaHgFvgWrIWOCgKFQyN4DhMPBgApr2SRsA0GZpPuJaJttNiQk+yjU4MxQrGHkqo2EDllBPasdjdwXqeEbKFuJpAsOCBxNB3ffDDoq3ni2XDMTVf+NyV6c4SSnqirmScH8iAVoZBR1jkyubQI9PvR3SdIwiP/pcqF5pWkh+ev/vajR1r8rKZNstqgp5l1RlXDUgAMXKqUA2kADD25eGyAR5pcJ7IGYE4bK0QR5TaGfwd9I8hK+Ktasi3U06JjRMrt8wIgTe5BwnMRVTOCffZTgLfNwS1LVrWNiFl4vYZ+nUimp/ZTX887dM2wBqrj2CEAtyxpEZWUARR5EpF6wKYYKLy2AdCLmXqcgbDBKCXfQKZkqvUaBCJUXTHgPnRuKX+1jFg/ggBE3d1ls7S26fIniKid+/RE/2cztkqiFmw6RxH2xqwSpjCWhcQ+6gAhT06DIS8luS5J1tP2CwyNVtT83dapquXdsK/qGFyCZLjrANidokm+zWfzjF5GTAkY5zYwhnAIVTpgAVEmHNwNO2tvZyJm6JJBP8B44W2hb0YdojAiLHDKbCBR14qdgMU0ek+Brv4XMvX0MYg4DWKdjPatm39Yq9tlvO2fv7SxonzZ0/XD5aZlv3otbkSTzGaEZfX4ZEo3veMmyhU7mCtUnujGk6WaSKxEUz7D+53m1u79ydr02U9bdp6WvXW+UHOBhAuwvkHsgDsT5XVeEQ8SuwZro5ytkh5vN5xVAMS0HYefLZbto93hP5BFIANcGGkJkdMbbBhE7HBAzOO2NXzdN9ZCMIqFa5bS3fqdK2t0t9b7/Lvn9hN16EkYmwZFNAbc8l9ptxait4oYPaW8iwQpnRZ+prouPZ4xdTNyMJ5fUHkEQwkQWhDxte5C3e26ZhhflTQPAbMHzFgAjKXp0RnTHu36Gyb6OxkQgTXH+6DiTjRQ1bkHCiDndiIxTyK6GVWzgwmCmBiSm4ax/tEJ+42/IuJ8uwTD+LvSBntYMhhxVdzmXm6tOmMDHAEvAB2waFvCsCEHl5CW2XcRLOe+XIyZiIdTinKZeEFbT8gt7RAUXAmECvOwnCBRMjwjaCfpVwXSxDwGDnrGqaIHfdkUkim63rfLrtqsd/X7XLZfOGzl08tojW7y6xNwRUX9Ueczw8s4o4ac4ysVK0yj0ZIjGU+HhuMmtdrohM+p3/32jvbzbReNLO6rSeTtp5UAyJvcUrCkxXT+AwwA0QVJ3n8GPp4eV+AMhrsRMmfgAURgovRrYDmvQp0x4Z8R3igNwGUVMmxyalPssaIshweznEZ+2lK24zcO1tF6C/RB+5qWt9eo39at/mbT+zxqy3NB5gFe/wdVOZcC6DjfgbGVK+sRUJllAmadnShhZHKSdjjRaBsK42qwBBIAZOy9wPlju9s07tbo8P6cUn+4aDzGDDfBzDpy0TXXi4M/Ev//l35NTJ0lejeLeIXnkcy5HXe2XKlh/mUmTcrJfm6NZP5Dt+JF59YmnQuDMF4h/UNxx6rkGpXJBDGBMAEiATDZqZORWoO5pyP5oE1J7fX7C8y5ebZB/3vhQKYPmGkir4kT5benM5WsEIg0KAhik81BkgQo0PogtmpBcOkKynTtCzYCKDKY8mQDIpuE5Apjc+MKTvuQ0tnKIzUPU5EiFqqo07VuG61A0opmRCDbbvg2r222d9fNufXq43nr5yb3ke0L1hmWaU83P9emX6vyIhWxeuH65aH7HL02RzjNJwlmvhMZ6aG7tzamt+fdzvTtemimjZtVde99TYilrPo3PHEhMsBEHUBWyKApW+JJydmlmIKD0DFPzqqgugB/hdVyrc50G0rMgd1HALDBKtETKgMfDDWizFbMq1b5vu1zTpIwsyMIrXGrT04U//nzTz+6akd/i4aG+KuDseiocsIIpFTBB6AdXEETJEPIXmyAKbpXUbIPEp08ctsvIIk3luyf152zA3d2V6+sTU6rAMwt7549UBWhB7m2cfskh/Lij4cwP4E3vqorOhxQ5/VHuZHAUw9OGdpSfeVYe5Oz87Jnhd8dERhP9jGNQSGiR9YAczugGGyqQ0MaSAjgnIuO8stpdn2zH2+t/zc5Xvdv4DdMFYiEVgAcGyZp53l04xtP+FECXZuJkcZH0koGuioLJYYM1nY/ImM1UhpTgIaLEAREx6kTAInhEQK4JKiaUnkFuaJvqXsoYswSkQzuIWArFwPwXqOdmijbZfLajHv6/nOYvrz1y6ehIXITkukU3ONBxtNN4TPrYClfr8yJFoRpz+ctyMctxj9nmiIGh7C9964ud2sN8vp2nTp4TRUVwOW5UEYJb1DERinB5wjFC+xWFkUUIApxhqkwCi6D0I2ATsZMzJKFEzId6pEt3DmM3jahVHqmg4Yp0ywUdNninHp5/lBbU03+BhcsiJw31szL+5V/EvTRfr9k/vD33CuUPbjKOIBRaIWjkjZiOTIiRBeBuVYI5pS6DsS+7aqd3mA9ZsVKUNO02IkbA9zfsSEw/g728s/2Bod1o8B88NB2jHD/GEZJkxX26fMfG9Lj+XZs7S8f9/SqQKYTgEzd7qx4yElEikzsfXBQu8Mw8QUUJJjeC32XWwdllPUeGNrjZ/bqf2vnVykPzq9iG8wg2iw5YD6jiddZc5wIGcgVm+DpQqAGdArldG2iRGfTgjXJ8uKn83AFN0mxBj+EDAT6Ja0AUVyJDikuIaiVOa/So0zBubjNF0Tb8DLSoGekwjwoc+slou+nu8uJ1PHk89+8qm1e/uJkYcO0w7VZh5dozwEyhInUcrvg5iMoko/AFNlX+JjOfWZnliz+QfXN3f6mPeataZt1iay0eMczkQCjIU16gsPWX9h23ieGhdUWqw4RjgllJ8rYGpvUYoC09Mdn/Itk5DPqYAp1wtQmiBME70P6P4DdW6RtgGY0YIIWmF1d07bfwq6emo3/d91P9w1aSqeVFKSc0ihnQtgRmwX1I2U4EBLAU48JwxzjM/VAgMm9HtK5s+az9xRNutajotrUSPs905/4lX0XfVyzDA/FGJ+DADzocGWFl9yeVhW9GEYJiRG2zeI6Rmi2Tdv23lzrxzLs0RrsJ0kurPZnZsP9rzzjrIPHPeC8bX2MIka8kiKBGCRJcuRWxhuWOz/RoZw3cEPMxHvubzxYH3ypWDy5Qt79L9MQ1wmyIqy4dbkWU98mi05NCC1tE42AjBBa8EykcKKqTlMIox5Bv+KigaTb6nEswzXUXZjJ1KbewQKC1mSajTxD5PFkAj/QvcJmpwM8tGzx+dZPZkyzJkMXMlijNQvArf7+67d7+y1K2eaejJzMgCCVaNSqSNSo6M9zRWPzdEPczV/p2gxsYIzcVkGPbFdxOu3t9vJ+myoptXgat977zvshQNqUuaBmQOnFOE1khIwCGIseYZiMilMESYiBuc4dCtEa4W+JmSy6GFKwwIMsw75Npa4pasijFUOJr4SbEPvEdnkbGJb7aftmkwHTbmJNt1d58/sN+6XT3T022v78a/Zu5CWc+x3KWAmXZLS+7Hoq6B1LfeM8DPfNBGsEpPxgCgKGWLplBwVjJbhCAbKOaRphmtR6Ke3e/8Hd44wTDosyVGOj6FnckC+dognsHc7WpL/7Q89exhNjwFz5Yh8VMDc/+ZtS+f1jhY7hs8dACad24vhgseqhnM0zFtb+4bHkpzhVOS1Y4ghTYi9pRogFplzLcxQu4mR97x7+v6a+SeU8/6le+E3qwZGEMm0bKe959N5gGmww6eFTQiyConxBkJ+MCTKUAIxT1rOz2bOU9UIotATG7IySpEqFNwFxBOfN58zNZmpIko1zCaw/65GHdJ7lWKTAEIG6W1iThEwBEkJHjyZu7Zz/XKolvvLJvbD5Gc//fSp+y3xXkskZh0PM8YjvpiPSagsgyMcvdoxzSqi09Ocv/fau/ddXS2qtbpvplV0tSd2FbEnn1L20BJJb7HMlEzOQ8YWU8odG+4QQyFgp8ZIELKKmEpeXHZ4rjCpBDePJuVbfsi30Vsx2G7NOMQopCV+Dj76OIwwAs7subWLuF0n01kT415trjxYs/+FT/n/3djP33R9WJCtI3Vz6fHCTBiDIbioyt8OgVxupESXjHJqUqzbHFMjUiI4scPiDYwzSJzuQAPiLNDTRGBaMeEIvb9dPf3q7VP3NZKC6Dv0/Zt7Byzi7NWtfO3LGkmhgHmImF/5yleOAfNhBP1b+P3Rk8KPmmES0f476PsXwGwMn+vPGjhh3tkEYJIAJpgiynJhmPjaFIcigA9UOSgM0Z6HBlM0z9bCMNiIXSVs1Hu3M6mf3p7wP+Yc2yf38283qZ+3ppoGm88gwgWMMjPuV6MtUFaj4DYpW7IW23xrnbXPJk6NOGMwemO4msAOJyGnqaU8yUx1wk4SaCdEorCAp4w87cGkjHpQkmLFU6lgLWShlBLUTHCSl/JdPDiHYPt2qBb7bb3cb5vLZ2cnzjxxutleEs27jG2WYsl2WJ7rp/WhSfjD7kRCB2HvlKnxRGemTPOdB8tb9/YfTGbNUibjddWZqgpssM4oOsoMSaqIbzjjwVu4ogVKNdzeouMK3ijQGWTOg43UJt0vXHJyna5F4qWWJLJkQrrjh3hTXIxyJT1LAUkRcGL6riV+hMLL5Nb05m6Tqd+th6uLmfnP3MD/7uRO/w2b0gMVvdsEL0wZ+iSXs0eSUp0Alhjc1K1LWIUU6ZBpcmfb7FOj/VcOSYyFHwZMbAIl9Dc9sR0yAPP8F+kWfWd8xx4D5ofBvGOG+aEZ5hsyJacXnqftG9eZ6Bnaf+cvLRWKuXgPwLSmlZiJtCD2M+i/AY6Y3CBMsJbyN+YOvUOTfATrg7QIcx3WTqEsI4tU6EHjLtyfmF/LOZ061eXfXxvCO8uKz8TMtfbLkkzJySXogGAsh7xBaUFGlyc9m2ejpQ3OeRLJrCVLa7L2CCmK5GSgyqcWdrVEJhgxoERQEABQRuGo+6HwhHEneqzyRzQUR9SmouSEllsWouNg+6F3cDdSbeay+dlrl0/vB2t22kQtotqLjyZeiocF7Pqz0Y39qIUbKG7liDYaphM+xFe+f2MbAvVm1rTNbNIaCF29iegzJGNFUIr6Gn1JWW80gCZR3QiNBM0HdUyGfaTYwN0CJ49M5KHLDBGLVbzPlPYp89zFfMP18RbuE39L1O0iQwJgipi92ARDA1ntpz528w3zhWj471YD/cnGbvzTKvLOgCg89a4sQ51Aorus6lhD4B4CJQQvty1RbqKpsPQa4DGdYNOpjJOSrXKipSzB04SCtD2qNQXMtvMiK2pbf2sVMJ98kfIrW4ej0CPl+DHDfARLjwHzCGB+/fB4fPnLD8mKXi2yoopfQHwkpEW3S3/0CW3x4bJfEXevbVswzNjOzu3FfME3YnoImQ5WIoWNQvIDwBEROkpnMQaaoa0o8/OlWTgXenQ7BTCddw5AC3VkcGltu/Z/v/X5F3yit2dd/PNJzDuRjQ0p2dom0WBCRimiwcw+e7O+dPTMQOaT2fI6VIAmmyVx3rcpzZH5ZcjK7XXik8Qqd5yaizZTd88VlEXELptFmvWdRcQk6k4dGCEYPaE6NSFG23eD6+ZdvdhfTs6sVetPP3V27d48i8yoly7iQ0bDK73NR4PLxsAyklL8iSnT7Ztb+/vtsIMhT9XUrZu4wTkvVFeYm0gBhPnhwaUo242AfxlX6cQqQR1URS7rjBhMSw0KqzsAJ+dZJJplwxPpYkS6U0X6vuvjJuW8Az+qDG9h6B56ExmjtmziAIo+cc91nn+eKXeT1v7ubKd7rUpVLx6WLoo3JoY/ziINBDuRlKFvhx5dhjy2zrFvs/VNGvfJqW6ilOrkqEtDroxu9cCReBICrJVyXQyFY5pkMExr/a3Z575z+yjDfPFoSf7qYUn+1YeSIo9OBI57mB+Gnf6k3PZDlOQfBDDf4hcw8Xn+edq+rQyTnrhpiC4+Apj9vjs/T3zBTbxMxWVKjnI5YfOHWYyFi1cmD9FUZsYDyBxaVi5Y6pcopQWDTO1swvwU5sIo2ZmreWWv3J/YX8lknvYx/nUzxFfrnO/DQBjSoo7zmZbMlYHpaZTclBkWY9Eyz2EGgSajqihFKCMeITDgUKEllOoYSqENpwMhMWkXCTzODwGQL6WzaDLRdpWtIMVbAahSWoehtzFG2827arns6/29xeRzL1441XPl7y+LzEj1O0J1Hg1Ce9gPU+Mlagx6GkMT6oY3rt/Zbtbq5WRWt7aZdNb7wThdU5K9GblnQUZ0WMWiXGt6TL+cjuTxzBGOK90BHBQIrcQeFDpM3D6mHCDPAvv3rE3LOlOeJqYHfoiv+yFsUswLS25AU7Hz9nLn8s9mS6dNl761sZf+eBrTfeybi3LIWihlxQ+TUxRwF4DEI2pKD3W0kc82ylZPcRDOQXuWLnjRX0K0ztnLBKpKg/w7rn1i11zSIync2vi5Vw9K8idf3MuvbH3pADCFYa4Meo4B8yjMHTPMD8kwcfOrdJVurem5Fixz45PEu/f0+1WGubcfz/c0uSgeY8GRQfKLCbCJlaweEbDnYDDUwe9WqbY65pGb2xQQIQMHIWZTWys2b1LuRvacbMoRI9e13Q37M0vLn6dEM8d500W6m7y9mCitm8QPXJ/fqdNwB9w11PaZaBh2sgg3MBZtAFkpxP4fQFAHRxa6TUmx0G6oaDZl6wfjknGnfGwMRiMor3eE/gKan7o4KQvYugHUt4Nrl329mC8ntcnTl164dOLePPNOq71MeGceOLDL3zmqzRw3enAVIibWakNn1ji//YPNB0Oi+WS9XtaTprO178m4CP9J7D4KXRPuDBJsQDMVLNFoxO64kOayJoWHKw+bRYCOWxm2sAvCDqJ0ZuVpJhOqIWy6RDdjztOu4QvB0nPMtiJ4ZFJeRssvREMnbciv123+N3Xff382+CUINQLQZP0SgEkQpMOdBCkkcwSfEXLJBTCNy5ifJdkAg/d6QJCZ9DhFi1kC0eBa5CwsUwMHGqiOLvWxZWWkOlU3Fu3p5TFg/hBU72MOmF878vxfuXr1fUvyi/8TMUw4cLn5JvG9Aph7t4lPffIGn7gnHha0Xxk2N84beoLo3lZ3PoT85ABcRNkNZ/WATR+seYj221jsncDJiAOAUabkWCcOKUItAx6i0+6JMzC5kHaimMm24sAeKTVLV51srbm0cPkL0ZpPQRjEmWEn9uezLvyFS9iwRLlpN7qanktspkz4tAK8yQDeULSCL6EE1xEykUirZYcQFa1sUTLYsSy+A0MxFxIhJQbGuoRe9kn0OIKNYg8Sq5+YHQW04Za+XbTNcq+dPP/UqVNuulbdmydaDizaTHWyXAFKXcCRy2gwLDIiT3RqwkTtbn/j9u69Ccw11uq2rpreeBvIY5MTIAjAlFaiqO7BxMQsXa60GUQbncwiE0BfQVYb0YBQZFUFqt4eTDXJ4cCEzhNt+i6+C/vexMl0zjw11PwfJQzWpOHLSz/Qv6yW4Tt1SPdNhEtf7KOpImJ1Cbm4g4VgKOJrn2weYid9TM41+pQiERL1FNaJ4M4u3lP6eFwraiiVGUGU7uFQhGsGuF0JE8WEHK5FQbZ9PHq2N19fe/XWiBnrL+7ls8cM8wND6McBMI8ejFF2/O9/+tWvfXDA3CyAef/NV3n/VsXPP/887ZWS/N4T3zEX6Un5O8vK8MW/sAKYO/vVhbaeXsTcFZECwtVaSB+jWLghHI1lt5wYa31D6NC+lNVI+GaKg5AsMRN7rIaAbUK0DvsIqNSZ7MKbC/cm9EvB5U+YSFuTSN81fRgG71/sTX6BTF5zFG/7ZN7GNHagfCZjQISNQGPRrrPjVBqPE/IjLLYoJCjD1O8EJSRTV0v0Q084RUqMoLGiLdeVPij6gkkiNyIs7FI2Q9+7bt7Xy/miCe0w/ezVp07fWxre7TK1g8qMDpTj7+GLCeyqPdN6RXRmktP3X9/ctrVbNOuTRd3UYJcB64/SOcDhwsxapjG6rZMg8xH6O/Jf1TmWfXFogcoOElZmZHYzSq7EvQgHTAAMrswp303wzfTmyUD0bGQ+bVPexPzJsX+rt/xUsPxprFRWbfx2s5//rE5512A+hKoeLc/B5tTCbx/yT6Lka53oKw1NNQqNkvMRJI7XwepELrEPorvEbY3PKcDWPxQPTF/0m3K95pOjh2naeHPr505tjh+Ks1+iTF8//Igcl+SPx85jwFw5Po9jmCNg4ub33yS+sMIw55+8wacKw1wFzDv7+UL060+CQUo/KbcGw25hZ6Zj5xq4xyB6nBAKOYSFszD81v1gyH0koey9ALO1Zn1nYn9u6fjzls2DKsa/qPt8F6G9NgeZMsVsfKzS+d6ZTwRj4OI5Q76BibRriXZMyktDuS+ibDAilNLQbCNYiJgGLArJ4wGQFmIm+AhBorjMKf/D+qWQOWV12J4E6oN/An/wNoMDfNQB0LIHy6zbxWJy/uTs5MkzpyZ3cIT0tQAAIABJREFUMQDqiCRATf/eoahdWKa2GXFimUFGNGPa376/uLe7fNCsTRb1pO6quuq5cgHREMBEKErF0RKWx4B00frAvk1m5KP4tACmPnI89MKTxccyo2IX8TmkPIioixOCuoD5RGJaF7d1yg9szG/6Pn/Xx3gfHYiEnQEYXLKtBksvDI37NCV60LT0h9O2fdPABgBg1kX0t5NDcyR2lJqpjr0FMCnBwg22R5gwhco+BJhtxhaQAqaTjUxtb2L7h2QAJOA6wC8zy155GuLmMWB+YEL5yA2PAfPHCJj32up88tNLAaL1ruWqIh4Wom6UPqQYCXMtSyduVtOwv+tsXVOAATg0mN5yGhC5G7mupgY/t7G3u756anfN/yeUcj2N9l9VIeyEnDwoq3CokCBPFB6F+a64r9vsW2svLk3+dCJ7PhOtiWCT7cA57LvMuzlmuLij5pZcGVFnYiEIdWAKQkq1FpcMSuzZ6TIkYAZfatC5uFUI01Qfo2LcUQY6kC92wS0FMNu6nbeTz7x06fTOYO2DcQCk7cXDDaCRDbJk8xD2xTd8jK+/uXlvMpOp+LJeazpIe4yVJywrioLTKMfF4E5KW+1lgnVKjzQTozN84FUkpbo8E1gFI4YuEoSQeT0Zs2EyTRITVg3Q3dwxKb3hA/11FXgr912fLZyD1XLdVC4mNGUtfPXqIZlIQ+Neah19puq7v5q1+eUqDntgmIjTdZXNseuIZxshUEf4P+J2eQkWWWdnAy2YUmVcHrd9OLUHCZKZnGwBjfQUWilTl32jYZBtILgXWcubW59tjhnmR8TMjzVgHq4z6NH72oo/6CtfJ772ahFRfJFo8/uHPUxlmG/Isdu77WQ98hSci+AEO7Hs3r5o6CzRg+3di2kwlzDcSQnT1cixJQM2GZxo7QyBZXLgKsFg0bHDJBw9SgtLYf0a4JrZ2T6lanfmr7UV/0oV83dPz4c/SdLboouUcsXspOmWKCEJCGlaiLqQ2IqMEVHKs6FyzyEADVqlzGaaiNYS55OZDX4G9Tk+cx0nxPDaJee8NCl1GU1WTTMTqonBvfQvDdw90OiDBKkoMlE5CkMsXppyGFGYChflNCTRZqI0b/fnk7Xablx6+sL61n6i3Raka6WPKcCp4AY7pplnOjtjunPz9u6yj7sVepezpq0qNxjvYYKh8IoaV9xAxDFDN3CEpIL/ojuAAZc0NAXf0TQk5iZZmqqbEzeYgEvMB0PdyHuUaJcS7UmMheHWDmmzimETNBSFurGV8mPIIRB6xFCCoRXjsiEzN217d5j4s+1s8p8mon5jkX6nac3N0M3FVD2bOjqCmwbBT5Mw7xFrtlKjZ2wCYdBTQDOElqxr8CfQDKLELmUk0ktAGsAz6G1xH9ZlL9pf/+6tLbp5UJKLM9FhTS5bPsdT8veF02PAXDk0jwLmy+X4fIk2L36HqUx97p96HGDeZvf25QKYdNEMk0tgY30K3DhH+4vOAjDFDxO+mBmBEoROFSMQDcwSIGlcyf8BFbJYI+wnD6bVpxae/8GkC986G+jbObU2eDdt2Z81oBhwQhc3YKwvFkk5IwIDOGLgjbQWXHo+mzwFaGAgA3E5YirgX8HMFdm8FonXKOcp4mUlXA0JNbIto8J2JuopZmTWyF621NrYjtHmY5n+iMOIiu4FL1XbrnLHbIYQXVh2VbtYQsw+efHKuTOdqf29RaYF3IxWQFOW2E3GPIxOTeAD2Q1vvrN1r5k2CxgDV9Oms94N1uJcAW8z9B/hdy47kFi8gcWdi4y1qezIWiBZna1sNDWZreQVYaKVmYacUk9M+ybxrqG8L1aUxAFtWFTssieUTbQxbfpE75ohBaqaSAZboTpksn2XoMcEYAPPMplF08ctbCgMtWn215tfTzb7tXn+7enu8ham4QBHrETKcioAU0zgx5FXxMuqxu/Sl1RQ1L1x9L0HeEhrv7XOMkGX2+F7sE0Mf4Rwx82tB2CYL8s7/+xVSIqOAfODEs5jwPwxAububn0hzdPTUr6CbziirmVhmOKLEYLhSpuEoq0EYLYR6Y4CmN5XWrq7mm/z4qfm0+YfTYb07bPz9t8YxnWDDZ6nrTNnTRS/NZEEMVfilD4KzFOE5RvlwH6tt/GFzHEqW+Ay2CmyIi2kxSoM3T64dSSKnpkRdVlhUJQsTTJzQzE3aJ6NdkXK5GQ0hJku8GGQexZAhcYQgs8MuIlgemBMSLgc+mD7ZeeX+4vGxjR97vlLG7f3Eu+iIi3Z5jo3lzxxWm+Yzs04v/Xmu7vZ2mU9a/qqcsFOmmQ8vOUJfiFYlII2Cv7iPsEURPSuxZxS3/E4TD2Z1HI2c068pEw4EYREQ2/gPocSHr8o2lNZdkQ3VvaCBIlg6Takmy6Fd2lIwdWVeFXKQAjsOmk3ViNxwXHjskp0x/XcgUEOlv3O+uS/JBP3JnvtH0736H6sKFexAKaKDBKCOuX9ASnvoPM5tXgLJJIhIKOAYsgIx5CvNc5COin63qLMEK1iHsT87jFgflB4fPR2x4D5GMD8crnuVZTmY1mOoc9jGCZ+xbZPCQhuJbow7OxfzghBg8YOrcFBd8OBbliNTFYHO2JpDtmQAGcE1zOVraCyNovKnN12/A8p5/mTi/C7+FnDFQ+UTGfSWnD2LIKAUNprzWngnAGrS4QCMQ3JkDdYkJ72np7PhqZStiKRctzsUWTSvXWBqEFYqa47omwdRyeaYmFysomtJ7BQSj5j6V17AhLRC+MOJtkNtMLwhCcDgdR5E1YV6PENHQLTWm7nC376zIbhycxgALSAzCjoJBsidbFumxmKi/18e2eeqmlDftKQq3AAbWKMstREcpAjCb9KsEUYg2SwYfw1+C1DsC/MeLR100JdBAIivRe3oYxWboYwXBrBhedhao7XTRqzwSbaNCJUD9HZaQDDzOR02ZLxnwJgGQ+jWvrYbVWpWcbYwSA/LYw/vXeS/yvf9f+62eu/UwfTQYAg/VZxi8pq54Zj4JxMy1mm69qbtBj0CGBCtzn6IwW8cXKErEgGT2r3Jl8j3yeGze395t1Vk+BjhvnBAfQYMFcBcyVF8pVXiGEiLMD3KvGXvvgybZZQtPunJnwN9uukDuxYkzwzrkk+U8w4zhPdemdyMQzVU9BSDiloFrlnNij48HXlGI5FSnmIPQLRekiONOMnpN6iGt6b2p9qa/9LJ9rF19d7upeTZaT24t8l59ngq3MZk3F83BNmxL1gsER8WYyM1OptMGkW2b3Azk4kAwfrOdJ2LHr0KH5uQDPRWgpIytxc1YiIrdD7lXaBMBeMnLH4Is+gtHwBMbIrpOJzFP8yXoINhewoZgRvg3NGF0J0fdtV7bytY9fXL73w1PrWgvg+4iwKWnhs9EwMnW1yeu2NzR3b+LZpmtbN6oXzvjfGYs9I4F9QTzFdnS3Lz5RlCvlD9V1GSmqBLAAuLwKauLJvIxMzSFRlRK7f4E51dp8NehSRKWz6YG5gSdL1QdoBUoZbBrhlRh9BrfLQK2mrdriDLiNKa8bcPQTaOT39lVS5i81+9/vTQDdtn0uwGcpnhyUktXeD/lK0lbiImUv2Vst4/cnhVo9UCThtFHnpeBvcLma+sf+g2Xw/V/Wv4kYPr0Ou4olsdx1cHh4DfHDk+Qm95TFg/qgBE+J1q+5Ft/rJxX5unsYK5CBj2QD5BwLO1K/cy362Ue/yyJIg2YcCmKBMvemNX9uvzc9Fb8+f31n+bwBf6BqFeBk4svO0r+J5rB4LMxI/HgeRuECWcDuRCQlwrkXvn09EM50Mi7BStiPx8GR2jGmO2I3D8AO4Ix9XGeyIbUVZhZTx96hp1alPKXZ1T17BE21E+eOyk4gyVyFHzN7lP/0wWKRN9otlg4n5tPEb5y+dW99eZJ732jWYOqbTU8633r29t+zjTj2dLH3ju6qBjMgHeZDgloBiGeRrk2BUvKvGUkFSFU9oEGJOpfrLMhDSd4JKoRDlDsWQWKzruF796bW8lq3QaHLatEO6YagaMkpndCPgIioVu+xnqR8lIjVdtfBhuOODaVGrQ0KOnfHF1F5q1+yv+eXwR+uL4fuQGB2uM+YsQx0wSDBLiN3LRfqdYiysAnVslOvv4baQGqmxsILkoUVXYn7nGDA/OlofA+YPDZhvMPbKz4iIHZdnaN+qexEAMy7NZbCtgBUfLDZiKt6DbboCmBHKSYq2N03ayCnM1fc3OxPc0g6m2XhQu1+0Jldn9xa/J5s/4H9uIp/ZlutZ7/tzWfqN8D0MBt7CoCCBgjFVBcduWXtMJq9Hts9n5ikARO2BC2BCpQ4PYOjZhXDB0FHGNQp+YMJisqshNxZDGemXqsGHqjXVmENKeXHZFL2jArfs2aCvWhxxcXNQM5hzdIMLfYfgtKZbdE1Tuemp0ydnVNWY3BANfdy+u73o+zSvZg1kRJ1rms55F9hZsZgTeNbgIZ3fi+uGGicpUoqpr3hZgnhrZo8U/MWGGMZu8K7ULR8WeoYjMEpJkTKhOBxzZG+qwVDa9IFuIPI9D60SazeySojRXcI2FcribOtFE7st0+V2iDFhDwEGy6FxzfyU/69dF741mw9/ZTKMjiFtQHqxNG+wzp4z5GV4hqhA8Ko5m2BUJNs9ukqrZTl+iN8LLiVIPVGGHwPmR0fIh37z4weYK6bRK9aYcli+9piS/De+QvnVEoq2uU4MaRF+Z/8W8fOrJTkRbfY6yFnY7slub7iMjZ7RMMH4RlkktHqGeJE7AUzwwypZNQIXwES6eG8669f3Pf8CG3Pq7CJ8HR9ndUOPwE4zsJu1Lp7DyFSNfcXCDBrrMd5QnIVkpc/YtY7yi+RoCt2KOGmIzYZ82JRIqtBboESjfkZpkN6f3Bq+l1JuS465AmW5H92slF6qenMI3hiQNX2vSeasRtYoZko2ukFpPiy7qlv0dd91deyGCoYd8ivOBVu5wVVglU1nJ66vfTUYiZ2QIFzAshoLFQ+68X2u5bRu+gicSg9VzCelSyCcHKk9KpIqUZo6ucG0XXyEit2IBg8ri0eT0ia64YbwLrqHkv8D/yd4tAmDddKgzuIaYKjKtLQp3mlybocephpoY0SaV/bsct39uu/jN6b3w2uuhrsHDhkYqOZWYoiD51NhnlUuOh2XOBP5txt0AwhcUximAKj+K2FoQW3fKqJ3Hu5hXnt1LPWJHinJH0GIj59D0SpmHgPmB2SYRwHzO3z/TSwyAzDf4uef/9WyJgl++Qxt9t8xRE/SfTt7kvbyZUy/ocOUD7+U5IG9gWV6gDZFcinAFjFC0ZIbYwsxCeJF5mp/aj4TvPu508vhf616v59NL5pzDH8GY2ZDRecgmTERHULUvY6dQciMlNeQVoqDbc5ho62qFzLldUb3C5k/WotLWhdnyaRUpEvCrQRStcAtzBE/Y5asB0lZK6U3xFACuiVQTXfOQRCLn3t5p6GsRwNUWJ4aDmP7kMPQu9hnO7RtNfRDFYfBgX2qhICTdW6oajfYuuqrqh5knd5Y0GN5dBIFWV7LElmm/FGelWh0pHMJzzVxBjmAHmWeGVbCiMnUuY7eAI8fNa/EeYA143SF20NDFaIP8YYJ8QaWcFCfe9F8gv3hNjKEEkcSAKwLeWmGfgvJyB6+cQ6uRETzE/Xf7yx9em0v/VbdxXd0oCNm7fIvBj2YkOPfaVOnrkRlSj88EBaKBCZbmPqj/C5i9bqxCcZL2O4BUEJyZNPAg/FvLx4a+hwD5gcnoMeA+WMEzIWdPRn3TAFMbPbA7aYT1uSwvUjRRF9n0WAm5moCXAoCmDGwAeMEx9r1dKmdVP/YpvzGE3vhZZmiC2D2pie71tXm3MAMviW7iiCvUvKDd+FnAFIrEbprfeU+qVNyXW0ft3eEZQraFQHkmBCpe9ZSpVKAxUTpagqjlMGQpvgUQNVZszgUaZnOwOughFSG5COzPNwSALCBnkWE34RoAZZDiJYC8FCyK5ND6V05ZA8H7zzwUYMm8Cxl3jROZwQbD3uPZfpzwMx04l+SH2XfEW1khX1R25fEXYnLHZmmSK0g30StrmuanKLp47supRucTQ/0s1g/IGgXcD+VhgkDZAcU7V3vOnPLpNT62oogvfdpun9i+t+YIX1vbW/4pg9pP7taYzGqACt46kJH3lpxMgLTVGYKJhzZJRv1RByoh9YSL8ME+gCiumnSEAbykkw+rkyK4uDtY4b5wQHy4VseA+YHAsyX+Te+8qX86ssqZMe0/P5NZZi4XDh9VSbluGBavjO7wfP7lvdbdymF6rKe+zVBy2JhBvI+kESAkNNNHnEmgts6hq8ATOSXx1o8E7Dh0zn3uW5i/+O1FoFZi9dMXUkpO9R51nF1ASoTWYMU7SD6jVhd1OhclOQxi+XHWnTmxcSMrR7JxsV6I3Y0U9Tf1VJey2cdOOOBaW9SH6ctzj+4jUxZRHpU4s0FetK4MlnmQDJUkm1u7QCMTFBmQeW7qCZr4toeE5axYQmHab2YfWAdMIrBHVn0GKU0FoNknfPI2QBWbmNv8iDpUR3hFUB1zx2PTsKBSz/2cNIrhk26QilAr5mW4KmColC/j+2KlBhu9DdMnxCFh7zknGQVqoSuSxaPkkwsB5jYt66jW4bcsvHgp5F2npj9es759GSn+62my5vSpJTzjc08oRzmgaJD3CikSkS+qg+E6lKOQ9hUvDFFXgSxeqUCdeyWj+9PmaAXZmpNfNtePnljFQiOGeYHB9CPNWAedm70gK2mSL7yytdXZEVn+TeufimLHhMXaDLX9Wu4F124VfHe9g35HiX5ztWbTPQ0be2evRTm4Uos0iEAZ6K55JCLtAiL0RCpoxmZwD4RwOpUk4nVyA7DIAkbo8XEbMwr/sJg3E9PlsPXz+b8JgyF08RN58lfCCF4axEuEyQAN+eA7CCyQDsJRocFGGOL58VsaCaooJkWCmQywB79f7W8xsKg6m5GvbQCJETxusYio3/1Ll9xgdIjI1pFKffl69FPWKbkCoSCtSpfEkWULMkEAKtgIWpbedwyWkcpDC0SGJvG5WpiOHqKSfBE708YqZr/Fq6ok3CBD0EjBT1hkyIxzWIoLM0HEpm4njN01GVEWqpFunJvkd3DGwV+eTdc39/A3KoywPd8MPSRW0mOHBSVEKJmhKDd9sTLTNHsbNS/mqz9jOvDb86W4Xs21zGnjnOeyvojNbDccMkWQMQ/bCFOH18Mm0OLh+2yRFYk9HAAlgqcY2k+QoFkBKXANrq3/J8371y7ttq3XNmFxC985SurJ5GH0OS4h/nB4fVvxS1Xgu8eUpG9P2C+yr9x9Sv51VdXVyUP6BPV333DwIQdlzPbTkTuO1uOt7bOXgqhvaIBZ/r5VGE6sSzfOSfuO5ruCFsabCDq0Ec8LgYndm5A0Oh6JO+u7fvqC8G7z6/3+f86sRz+bfY82SW6hB6mReMLJhloiUoPEhrJCgohxtYKoin6FD9JnNfEN3ismcdcCh2IjUnksuVyAH4AsTIZKvuGKjMSFyA8oRK7JrT2ILFD7g6tgcMCfHwTjdLH8Zyt5fXRCxjk4e0PvhFKKQGOatsmSWO60iIMVBBYhzhyweCmtBLUOn2UYRYvuXIzwVGRAgHrEwTxYh4sjBMaS6GxkmAH7RLOSDfMkN6RoU+SbvABYA7oQxYyLecljku3CDfJunqxUf8Tsny5Wg7/u18Of+1lMo5LpDhUenZSEJS43REzEWchAx25BIo94oYicYXnXBhmuR5ORQdguXIfjtxbn9lv3lk9zl9dXR4/BszHotwxw1w5PD8awLzB9MVnaGfrJt++ee2pkIYrOWK7B3IW9bcMBt6QOtxxriZIRSz2zfvOqsQSNkHRWFsR5CTiJ8m9xUdy8KlZTpqfHoz5h5b5zabN3wTjC7GbYH8IUp9YAFPKc2vEuBi0C4Ab2H0y5TzD9FZU6YVl6lR7nIhr6Sy+liOGjhJvJXIwa1PnNxVd6m3lk86KWwe69RLzI4xRh0IyyS/HvRTKR76Tu9F4oHI78V46KN9FgK5OQwXcIA6CgZCwRFxEoq49WdEFHQLreLWwaZBWZUygblK8I8dHG6f6wDH4UeGOaCxVpSQPBl3IG26gd2CaxskldroGCRIahkHADc1K50zMPneR7MVQm1+hlHarZfzNppu/g16nbP/Lc7Y5LPRQYCEVgAkXoxEwDZb/ZUlAReqhRV+zeB8Xx/axRJd99PFEAPCE7gh91khv/XR38u1jwHwsLr7vlceAeQQwDw2FX3nlFaZx1Qe3+fK4KEkEF6PNi+/NMKU0v/IMze/f5BSuPZVy+4xF5ScrG8GwqbOYcYSFATrast3jqjr3/aIAJqbIgDjHI2CqThqkLzFs3+ZsLneN/7Vg+JKL6a/qYfieS7wgk1HEIwQN2z3QPqJDKSA8UDoRnXsxGzPTtDMsK+tkXTjouPajNFNs2USQhIm4oEqZmYOHlWK8uMjp7Q7KeyCdfmKlE4iESZUQHZTuKHMxLdcocx0Gyc9KjC3+HASIJamiDGUUA0DlYBYqMRKHIKzGnDKQ0faqngSUfSoZ1YaniNeltYB49XIgSpcTLB0mJgBKeAdrIIeuJ+mgDLJzg4XP6FJ8xwcG+AyiddTHIijMmtkDMRWnyl0YKvN30e52kf6k3u3+pYn9nvQqcXgQq2tQMnc8GmyIkVKyUm4fACb8N1Yusi9+AJja/xyvlhhnlOH4F/c1OKQEswt0/RHAfOxmz8PYcVySfzSo/Yn9rceV5Ecd2LEjNl5euXoIkAqYcC/Sy5M3f4bLpuTBqiSiK/a2dp8ObK+IYB2qZ0+MbDNMueWDL94OCoquBtNcsIUlDzQz0onrdW0SxCdU6j8pJXzEh9Ck0E2WzeSzfVX9KlluXKRXXIzfc0PcFa2gNRaCdXEwMoZCCieir17MhmfKwlDZop+o2YrgiuPwRjmigqaYGIMGSfevLEEWFimPTxzWS69SnhgepzI0nZ+oG/sBbTwM2VyhQSUX4/Awl6NbMAAdAREdCiLh4CnTKzAmgZc691drYPijOZUFyUWQU8E0jTueMuRC4lAxScavYExWBPDQdhZRlMRjWBnEl716whnMvG1jAmCG0Hd4nhg6QUggWrHI/PRQu79DzJc4ptftYvidZr99m50RraU8LCAvJt8OmzqaOY6foxQHINoiP8LPdKtnvGgJLps9ZdAjHpiFgarOCFlS0GVCOaFfu6a5/tM7zVGGuQqYj1CoR37wUCPrJxYIPtIDP2aYK4ft4ciKjwaYuvmD+Iqd7TOXYxiuSByOgA42fBpCpjS+h2tRj7w/2TfBbSQkUgER0FXC0cR8MiNP5xAwc1MzHI5C6Gd901wZvH8pGPfpbPLMxfSui/G7LsUt7FdShU6pVIonBuM+mTmvK5KInr2I14HFgCLlU3IB0dI+pwIfNNUYd5RBj0aRl5pWdOP6dsKOkH6qSok8XgUJjIFjnJTAekwO6vRS64/sFhNv8RAtCRoC3spG8cDAhqOApu5EIr1jhV+VAQ8YXOmVyrPFs7MC4zLYETML8Usrcx1NjtSzFAjiISjjcWISrkcNlXE9UBhuuEzX2Zgh9kOCeTBbux68e44sfyoRneScrps+fsek8Kafp83Kmg5THRWeIxADgFllBzpqbPamE0Y5lt4j45SXY+UZoseZFzBpGUvyw71yeW8VPBWTFzw9DIcwGKqaHxwD5kfCSj3vfvRf/Un9zR8TwxwPx1WiMSDtxvf2rlAwVyAlwkhVNnq0lpWsBQBiH2BKRtLHdIJrUQDTe/yWGFRSTj0zMhDFOBMeZJEZtSMT9xlu4Hxe07usH2x+Onl3NTNfJspLl/N1DuZ1T/1dIjvtDP1UZt4Y9YYYM+k7QcFPbdCQqCXbLwWFxim4DFXk5io9wq8W1Cl3A7DBsHgEVd3zBqhquX1IT3T6XtbMD5miIvhhCV+c0VF+q/fH2CYUVafUzOIDCuYpO+MFQEf2Kc8L3BJgi80b7Pgc1M6YvGlfUB44NJ1a9crtMSEvs3c9Y6AnokMlxDTlRG/5FN5OYnfuzvcuf47YPAVRg2F6zYX0ikvpXoqwF85tM+TbJuRldAvU6ZrpkyY5RHj5BTENnjjIVjVrHIFtCEaTl6eYCo9bP1h+kJ31lVVJOSmOAWkByv6Q1RdLAi7EIyubeP1n5ifeWv30HonSPWaYjwW2jyFgrpwkHtqNfLjWOLIq+VBJjkn4eDnqxn4oM9qpPnV54PQM3vx42w6yvuNkCq4X+GRqeS6T8kaTJyEtirkzNquLuwIaHIhKBi/e+t3SQCKdfTPra3sRYS9WUrtiZmthPHkyOPOJzPzJnOkUMy1syrcS54qIB04Jcmod9IjdRiLZgdEJhG5SS1+gzDegfJeen07GDwVI+uAL7yvsU1nnQT9Re6PaAlWFTnlOyqYLQsG9/YBDHWJjkfyIifqhq5DqLsvd6JxF/JCAoJIgPG7qaKtTOgZoAUp7V1PQpMaWYU+hbmCpiJWU85p0K/FHMe2G3hHAK40LIK4UuRK7CY7H+Wn4hnLO7/iQXzGR3sppWKLnEihZaEZNji23w80m+yWyx0WADmU6HjnWVMtmj3frCd/j+YCF9hjmyAWsdHaQSS7eqgZTdJ2ao6wfWeUjn/gQEUss/Nwb+sFvdf/DkZL8WEb0WIw8cuUxYK4cjh8KMMf7+Rmi+ltvyEf5xv7JK9n5ZyxAAc6GVgsvXJcqm0WIgs8M2ksAJ18AMzjyNpohR65KOW+8xu1izJnhfpMcD3FpQjObBZeeLIZr0quEByZkQwJiMbjkzKls6VIw5qWU+RLqWc7UUco7xqR9TrmFxQXMIrDAkuDQibbngJVKZZRi0VbeLcorVYMpYK/S8IP30pgzedDVlGXEslxeZixaXI+uSGMdPjI7jPl1bnQg3xxfnCQCKRSzumdUJEwapIsLpmVJ+pDimqwyUQH7iJ9phxhLkCOLFR2nPo/SztXcuLRHAAAgAElEQVTYTDBudTJinLmsT8ZMiN06GzqREux+Y0spv0sxfd/n/BYT3dNOKfoJAZm+0I2S4OoQly7Fm25ILaVpRPltTad7VQUwAZDe1BlGLRZLWDBL0sOv+6nyTVeep6Ms1m969hVx+8EFoWe4/yiunHiPOQdLOLznuuu/G//HIwzzGDCPAfNxR+DwJPGjZJjvCZjnr2SXFDDLJbryCS+uwToFHz/qruADyvVOjIQFVGVzwzKAUj7YwvzwGexN8M0sVOkSmmcyBXDww4SQs+yyYP8ktTKQSEwbA/nPZuPOU85r2dJ6zoirMEOmNJhMCyKeU04LhoOwMSLmLP5sBKH86JMprg+lLC9m5geAVVaBDo9zOQ+M8HpkKfIAZ3UGvdIwOWSiKlsCRBbhuDJiVaaPtpsF5ApsWO0qlD85mm7g4AXpOoh+U+ZMCO0Z7w8nLcMxJg+be6KEbNC1zKbhTFWy0hNdUM67JucH1KfvmRhfpzQE7wxMNkpaps8pIcWsgBjE+AmO6/Fdl1Ob43rhxJAPZWxZatmNhHKcjEqurmjqi5ZT2gbSVSgr6ug8NLqP/l6AqUBarpSeaOH1gX7wu/G/PwbMD46RR255zDBXDscHZZjyK4cqI7r2MrGU5bgIw/yDwjA/cyVV/lnVwOEt7Kh3CwOzjRH4tFjHB8FSt1wiqVA4kOFeIi2kVJfJ9FQgUerF3EM0LvY7rTVr2fKThGAL6BJhuhHUrYhkz1hsI0Q0j+TDaN1LmfLMoLw0mJSQp5w3iM1aJuT4cJ1TRhYwdEwd5Yx9klaWOXPu2Ji+CFiE642iSinRV0pt6S6Wq1W2VEpxYW7j6iVgS2XtekDQCyhl+Xj7UTaE69Hkw0GQ8AedmIsTkUEzYeSsor9Uy00U5pIPrONxdRoaHyak3eyxAM7Z1AhBi5QnhgwMKBtdfeI+G1oy531KeZ8M7VOU3B8wz+iGdCNnvm5SHNQ3f1yLTNgKOrT3QPe6j60J3abJtORc5YjgD7RJOWY/giGeI5IjV7SWkSFO14l37OYHPWSxgHPIsFMA1R3z0Z/9ECvHt7cK3lHWuzd/95+fuP6+ePFoD/NjPRV/+Dh9HAFzFSKPPv+Vtwa+PNrD/PpDx2pFl3n2ZR7d2AGYo5PR/I1zzziXP4E9Nej6EGsDMw2V6egGjwm9hKDh6556oyzSkhNTDux5V8I6urB0zkM7U34P1pUxmdab9WT9Bc6Sp6AfHgqiHYce0BlHSSyKkdrgN5KPV7EaqTbqRtpoOjQR62EgCrx2fDRUk4FvJs0y5UZGQNLaFOVMtsZ2mXIngWgpIThsYGMwHgdKy0oMI3wXGh4pJ8s648FoHg9QEfX9PpE6IV/J6ZWb49aq8xRRuiyPlxVNII1au+OPoSELgaONFByzuOk2hDkaQs/UyEdFk1KU44TAXU5x32SeZ+IOB1J8o6SdCZM2SBhA7QR/EZT0tu3768lVA/XdAULKXufqfEuObLWgxXLTkF/a0FF0AFdMxdHLPFg7hy70QMQuu/sEUMTT7WR7VFo7MgQqAHjAYq2wyLEnjN1xfD2Cbyy3S4ne/MOHAfOxKPDx1l0eA+aRI3CkADxSAv5oAPPEM85VnxCIxIp454CdEniGj6KoYcZy3VpCz1IUjUNkVbCPzNRSTEuL7DSFW6RKRk59Mn1j1we2F43wzzIvtgll5bigiEETReABuY3k6GoiN8Mej3TtsgTU6N2q3ka1ltIEFAaHDx2u8kBcJEmKQ6NJOAvUSF8kpgq0SD7YMouRavjATUgQVqteIAAgQVzQdJdH9q2BAGIVdDASkgpdTC5lzIJbyIKjGidhfo8cYcxmnEQzapcCOFGyiGSRSffSBbAjQhvQAOyZTEtSM0PLTwhDkxwg3FBW2sHpgaNFrS7VMn4OrJTjJDAdLZm3TNdfJ1cNKQxk2ZcZuyjly3lA1pVAwJe2De8ym9aZLseS96NT8BXALA0DBUV1KRpNgRMjGe7wDXxQZgvD1DXJg0sJRxu/R88UX4cY3/zGV8794MjH4Bgw35dwHwPmf2DAtKZ6ToBPANNSrBHTiC0MbUWOA/MMGVEXCcY2AoslaVIfLpjoEpxPP6aIva6ZeRnNUNn1WNmLlpGrCLoI/UkP5Z32Pis4yaoZWrQOEqSrmc3amNTAKB51r0f0TWqVNqrTEf5Y2gdq1KtwJf1Q9BBlAIy2IKBNwUuyzYVfIQTb5ozkdAxNZA6MaQ5G88BUrPHIlrUuemuhq2IpJZKilBLkEakQxvNKL1HTQ2UkskqwWIF3bNXA+hLanyHjiSXIEigkEXAazIl0HQlrQqKr1/m5moyAHEvGujoalVg0kXnhmGCvXGpouCXp7qWJ+W0X03UmBO1qrq2aFQuka0a5czn1FueJjhbDDY6m9dOAIl5mZR4KXCw1iA9IyMkeltlyNAHrY7XvA0Z1ehGDYDmiyjgHbJBhJ3N8g68IMWWKXsyEB/s33/jKiWPA/MAQefSGxyX56vF4TEm+svQjv/HK1w/lSSjOV52MXtl6VUBv/s65ZyhmYZjiXwgZkRfHGGEPCeX4ASBpzs9QxOpwYy+VpgYVaANTreBM5AEKJdNzz7wRXXVRKClImrg7qju6tvg0IgJla7ZufSBz1Vi3Jh4UuEifEzfAQxHpTPkEYs9Fx7PygVRfn3Jd2copc3IZJqvFjxquYef6QORbpDmaowZklcGITN8BwBLAUxikvBtXFs7FcB2rRpD1oMjX6YVoRpE6KY9bHH4z+rda4EtcZpl4S2NAfOkPBk0ivRqbF0UJWhyMRIqJklf3PAXsZAUTdBkOUvhNyGHxh1MKJqa3bczX8cA0v6doqQrTVpItKZJsaOioize4j20znQDgS8lMB0FmcoKL8NQslzLgkVONdEi7Q6f6BCvA9XhQgqMbkTpZwZXbPtTp0IcoESZv/vE/P/fmERg4ggLHJfjjsPQYMB8LmKurkodrkgDP9wVM+GWWPfMb9+4+SyxaSDF5HbPJlQUgoqLT7R3RY8KxqNAFlE5SmrNwNgFbDxcbgIxO1TlGk7nnaKv11plLsDGXQU9hishWEGlQSgzndQUwsxE8XSMyM8lEFDqFvynaGfXmLh5vIhaSUbO6Eku/UdYb9WcyOT84waAUhgJfpTqQ7MhfkynO4bCn2FsUneQI03onwujK9vkoRxJJj+rYFdtlmV56qKtGG6o/skX3JHUqGKkQ1QLxK71SdYEvJwEFWH2kgoKwlFP4Bt8ECI2DK0AzDWRQdqsrSLKJ3uI+/0CM3LnLJAMaNR7iPClfg7V2II9Lsxw2jYsLl/BalmENVt0FEJ36hBR7Pzkmsaw1jkdIyurDwY6W4SuDnpXJuDDKolkbw9HwN6IJf/ONf/a4kvwYMI8B832PwP9fD/OHB0yb83P47EqgleyCI2RFxZfY9FHAVKC0rtJJq0AX9JqaZa7wiuuK0BvlWFgabA0lY9fbqn6SUh41SWR0b1hMNZQ1qcEGADM6ey0Tr0kPU8x5UTFL727sXR6uNUpeBmY9AlRSmgrtTLCvtAT3TfyrPE0hWVSIsl2jwKaoje2l4kAk7b9RXbnSNi72Hg+/VHpLbOAULWf5PmcAgmQFs0boIEsHIF8idIuDm8RhQEokHQDVxaMNq1FuMkQpzFmDLeT1KS4WeBo4aQhZw8/0uYFHgy3DQPgtCrEwTPXOPKCAJXJX/NyNoSHkZb0MApg6HS8rnxCpY0mpgKGAoLwkmJcBSA/7kqs9S514vxdg6hGMxTBYXpUV56Lk6I1jwHwcJD7+umOGuXp8HinJPzhgjneD0nxkmFv39p5tc/ucMEvrJKCqEg00QCwiq4Vj6GTIi3XvSBXVOtmhZVwYOzCHUpY5OzkETPnQLzEL4cFW68HZp5C5i880snzgNCbVYOldglMBUzJqOHbXkknrih0Hdmh636WfKaAig2i4bZQuK0o6aTninvCJPkjSFRNiSBAR/iXu6AAUDSMrDh/q5CGAixVxLBWJ0UchqarnhMv6gfkHonAPnIuKF7vaq5eoXiMdPDG0hAxfq3l9bDJOZsCaWNSpWfA4zDp4vYtfZgoHPkQympFto0KLhWlqW0ACMdEROAgugkdfvE4xvwUzNxx3EDrrkVFEBDMO4yy0q0TOg6UvzGKxOamm8zwsGCJyOXd2PSVXJRQXclM8vgDb4OLWfrDpMwLfOCUfbd/09UF1Av3mWKX0fcjOOcKapQJmUUq4+o1v/LPH9TCPGebjIPNjDpgra5KCGO8vOVv1ynyvfubW6MZORF8qa5N/9e3dZ+ehe2GUWoJNAgTHUqmoibRHifEt7BfKq6U2k+q+Lg+t0w0haDDxr5ut5RSWJvrJesj0FHbtQDFTEDcJMUFTVzcjQbqwmOvYnDDEVzPRhvi+qXhS7k9W8aTWV5s13FeEnZL4jBeHIOk3ao6CuBoVV3Yd6MjY1wgFS9qkNdhLymzh5iH9BNA8dfKVhUv98wV5S9MASZQH/cCVolqbs1bTzOV3sZ+tC4swewvQWEHUKKY+mJ9jc1RE92gXRh1ZaTqISrO0PQtGKh7y8tprKY7/GQy2xKJJMsxLT3P0xpR+ZsyB3jI5/sATBA7lvaSCLtBN3bSSu2QOlJau7TYrU89jXBwyTLmxLYmP+lrDC1P+fZhhlsm63kp340cGiqLFwZyqENIAvVi5CU4Co4y9NvXr/+d/+xBgHv0YHOsuH4OYx4C5enB+CMAc7wbAOQLmv/327rN56F/U63Q1khej7nL8GaSO2CWGaw3GqaM7z6ENHD4XZpFMsKOVAhHVVsrytpqsM9NThBrVVolzayihfNf9lSJYB6XLg6GTyZhrxtCalIGAE810gKiTIT3BPp9+4C10oDKGRVuAsxX3t5QSnN2xQ1kV6yE4VOjGoUp6xLTu8LCObG10OR9PTCsMtXxg1XVzpe95+NE9oKvjHcvmD9i09DXFcUhPeON9jDa/0klgGA8F1oYl6vM+E/U5xcjGB0JKHIbh2sBQHBe3JLjj4/VAD8JSdjFzULAnxt4hvUVpeNPAZVJSxMXKLoMpy/lEU4dAvQG5i6of3jVEiySeR+ht6r9QPuD1sAPxMJXo9HJfhyW5qpmwCaRXatYods5LOwfLqrL6qCcDvZW2fsZyX9pAlF//g//uoaHPMWA+BiKPXnUMmD9GwPyzf333E5w1vELeupjZLKLon0duUByD5ftgeo3ZlQtQ8mBdm1KvrhDjVfg9AFmo8glys4s5BK8bf6iaD7PEpT4t4qVkaCOa6hpzXh9Ta5BYqYvjCN4tgwhhtyCGMp2oc84VhN+ITYSwXRQ3B7MYtfgdZ9ZKjSTGpmzB6zq33v4gS0cklsXBUstqiWsrbublNZGOgpoXaytVu44iQZIfy/+KQZFsCJVMDckplxF8GeZosFtRS6GEH809QYAHCUDKNGTmLsahN4TICNBnCS3X1oZM0uVUUjQDFFPHb3nKb9KQwv/H3pvAyXFX56LnnH9V9TKbpJFGuy1LsrxiA8I2xmAExjYQE0iIA9nuJTcJyc27DiEhwOMmZBIwkATHSUh4iV9+hNzcJC92Fr8AxjbYFmBiCJjFWPJujy1ZkjWSZkaz9FL1P+f6nH9Vd09rRjOSFzb1Dzyj6erauuqrs3zn+zjigqQQ2LAmRJxXa80eDWuVtLlbAGYEHBdgZ9+ohYUKnAC+HHpWdhotle5s8uSczeIiaEWZ+bId/Z8g31Gspy2RdwIwF42Ncy74ww6YXSdlcX4/R6bk7Smg0Z0rcBtss/V+Gw5sbMZZ7vYT7glu6HhNKwQIFTJposYLWeTtp73s/m4DpKbzam1RIGas0Y+mek4GOKmsBnGROkOGOy3obYYYU2mPudEZub7M0dkMrs/iMdV2MB1JS0IdosSesYQOSyBSUh6KV3nd0CYPyBc2kP83pK+FxWJguWt/y/hN2kfSuE15PxoGKivfGx8ouKdpi6ZA0pC7BjZmjvp5l6jokocxlnzTBiVGaxflJ2nKLxKF1F+Pwx4b2oHJPTg0Ew9+uy35T9vvYBHZ0lMPTSqtCaQiNoBfF69cBWnmjKUA0haJg8es8Th4eYw9Zy6OrKNfUJsyLGhO+XAq+3op87tQmjX90iyrwODfY0iZXxPqU9/COlNk7057CiAMH2hN8uSraV/QHUCLkfmaW1rO9ODtHzwiwjyRhi8SR08A5qwTNT9gdl5RnSOT+vEdZ849Njn98IFNnuBUK8vnakUmtmHd7oA6CpChLtmWbjPIcClpqmZdci0tUiLmR27TiR6Nw6nW3SRLfFJdizoS7ZuEEqwIAqXI/mOhnVlIRlF/Bu4sQeizAI+JJJISIPUIcxmIYmsBW6FP2885aNkOG8Bod1ibxjpjox5oKZE0QRNVkcya7cq+MWK5MhjD5y2ysznw0D1vg27RX29pErW/DV2qg1KkB1RQgMLuWB0116sMg5dKpg+7rmOcRuayuipSRMJZbHOmAJEwxyplZLTRgj9ZKF8GYn5Or7K5JZ1hbKJQDVQ4A1zDqrj6APDZ48TpCCinSv18tDNusgCRuk+KVgGMh0kqA4y1qOl3UVav6fdmjx0sao45YIZnRc550tpxGyxt6tNGHbUznvNx1agjT8E1Xc9LJyHI1zporoRlG2uEOXyXyoOfPQGYi4THIxc7AZjPMWBm4Le05C87gNIueh2NzAMGEwmOK6I/DUhD86QdZXbk8QqcesulnslHUb9PSmvVDEZlxGzKUTmbGmOlbJ0Hs8iQSGPW/sxF5wjicgauELoKgyQWg1o2nFOHrB3TSj0V1TRKVA9YBcem2JhhpPplKvUTgK1dRsxHMjuoQ3mTpU3KbJ/0uUObvJZpeFe8zCI3TFN2NK8D8miHKgfkXMEoDCYFfY7gS54T+i3wtTOvEWmcMZdJrTVZErFOugK6pt+5qVpLDUmfPZaiNwWkhkCHAflB18geYZ0wyqWMbXec+Te1d92YVa4WN9NdhDAjabM942373fGcaEuYhEJO0ehp9XgKsRad7mlP+hRZfSudz8U9WuvOrzMC9+AtwysemQ0FJzrji0XQE4D5XAMm+9NCoV5vIM10QzRpJlteJRFyUCha5vnN4zl16vEiOn1tCKpvhDSMFFypV9BPUzOq9GeA61ENbEQnWgBcqZRPFHKw+zYmIVYE3UlM9CIhWtri+bSoAdYyDpM1qpTL1ABStSKoozLkVU7SapxWTmyr5uTmZ6aBkZ9LZ92VlkFk4Ga2q4n5UgEUi+ayPUBmvZPXPFvfj75rrY8gvJEP/LT14Art4RAhBrhvKxoVf7PnUJADDpGaTlya7JLWZl1JwFcQXSI6O6+t7jwIDscX6PVWDBBICWCXE9gBPtsHXupGLQjBOLI++KKceG/KnDgdZc3d1FQJvWBNYVYkuqstwDSxYqtbWlXXEUNaiEjP7orbuTAX9UJRffYtr4NkxhHII1YVddHfTwDmYqFx7uVOAOYiAXPWYr/3ezg86w8dU0CWood0W1PyLPWndS6aTziGP+XybXaTmchwkZ4HolEY/Al3U0FgDzekpukVYF+nNEr6Pbp1wfMitxrXSNO0zTLwlFQxLq1RVXDAaBlgNihhCjPn9egazXBXdYWaBFITNl3MVMdTWiTzMLwTXgY1HaGlrSKPKIsosFhYy5+tccsOVCxOyqx1hnJoC8P1vda/2xBoWzfPnWKXjAOV/6NLAcmKtUr77KzA5tQf2+9iNlyLopqCR6jpO1GUiKS9ai4HoU4aFDhyOlIuTDyNng8Lyjhk2W4SGBHxTWvgt2T1zbAN0fkZV2/udphM24hjDpLB8qKjQZNbUoTT0yGmYcIZba+fuW7nTiv2I97PV+XIPXDL8NDDzww2fng/fQIwn0PAnHxgz2bv4bT2ha8mZ0WkkGNP0RXXgKEeRiEDgDYxaqXo2jFvN3yso27GaKih3wCXK2uIm7Ha0hqYeC25UcJE68AlJ6OKbrA2PsylZxmCqg4F1zKdX0HhGRGYJpFaEI0oUDGCEFXm+GgAloNe4UNuABKcw2YldsVynee3Cxw7ue+tTRafO+LzOUDnwJyHiZ1xadtPrSO8tYaOcSML7cx8h4JNbwBTA86iTpv7kecNJhFOALFXAHqQIk3j80YXMbCfBpCp0KpXCZDsADA8gpzuRx8G+zFW8Y2mo8hNu3ptN2VuxpdyjmRex2xfHxp5tscmZ+XqSiIyoeEiHO2OOIPZ2bxQlvuSEyQPfO6DQw/98ELeMzvyE4D5nALmgc0ZN09vpWDaArAUKYhxmACHssP1lQDItAmlhftXnJCNF2vq1kRIbDzIgNM66ppiAVMKST9USmutqWFNABUQ50FPySaKaMhCP1PwMZmfGJ1bZlqQgf+tskmHRXDS9CWMz5irF9k4drAMC3ukHfhIa3uFX0/r2tGpRYuUzHAhj9h0vFp/12jYOJI2ehjoOeGJoH83YYrQpWiVTfMTYDJI1pEOYV2x7rB9HTQ14RBdX05cCj2e4sFiM5z6BAqG4fmcffhcHiYGg7Q8YvbWI7JTYv2tcDyiwh+221wSjHpRsj5tKtn5Y55CgEmrlprynYo6YxOAn8Ase1TTcDvrKt3Mbhoa00+6NJlWxSpt/rU5t8rRDfSi0DnPU3abRA2ArhkGe8eFRbMKBlsTMI9ITZ0fdKC+IOXPbgK1vM2BTgDmM8DME4B5PIDZlVke0TXfEfLRydMObM6oeXpnjSrUIgN1xLiUKk9r9782adp2FdbRbFGMmgh6I+VTPgXgGiPbRQM+cuu0MMqR4jGt85hsIeSqYaQCSiG6q3cjuaUiHIPwNAqOq25xQJygixnQqGjY5AYJIbJsESuLaLAdzswV2HRcWh1+P7PS+rwTbnjYGVnm30mrg90KP2df6e2tFsIdRQMqfydk8cFGt0jf7ZdQUdWjNGq49dWDkvusNLjD4teYn0ZlcmVBWSoZJOh4ihgPG3NK5xx1ZUoKYETvszES3ElZNqpgzZzWXJrtQvS1tt1Ezp7IaUUF+LWiyNkZecsRsjgLRpQqXnOUODtomq3DchzffyLCPH7EPAGY8567+YU5uj8ya2yy482vZHtOTcGfEdLsQtxQRS2DW6BTgUtzDgzvd3bFbTSyuGFUrchoJXr7F8UorXemmFFpiUSlNeJ8FTDaAARbmMx7ItQoAy28CN+UNrQECergcRwh41z3VwuYNqVi0UyhhK7ZrJIlSWnY2gtS8rxpV5q3j0ZUJrWmEz6hTpkPkpuUUWEsqWk/KlfJsv+8bWK7FzhK+TVo3hXtWqgGwLMKvi3VMyObGu3JPllEwDnp3czHjV5ZmJ8F+x8TBjYagIhPAV2sKuqKcDrGYyR6Azz7ex52BtXifEOFCYcNwKvfzxJRjoNaV7REf8M+ahOeIdNzNE0Z7xDhfSQyBVltN4GbCXP8BeenELjsaJUXdRmTNy3S7DkQkY6Somet0Yj8+tLtREA+vf+2D2968Pgh44f7kycA8zkGzKbwmbMizA7WukWQRfHf0nOv3YG8ezt7Xi3KuXsGaLnEm+pKZoBLvCtthHK0CQBPNeOasFCYdCnI3iIOnPpVSBkIp8yxJoSV2ifW/q72VZVuoz60yrJ05FxQkrAZbGUfZpaNBtGLkC4H45yCOxiQJp+waU3zhPHs8D9tMIdTnttHBoTWNkmhL1TElwXitYj3rT66ArTtQ0GoV5F0l0u/heosK0YbEV77+9rQLqTs8hBaBTuC627OidX8V+HJqRAoK8GRTA9EnySa5xvp3iuX3zj/kiUI6hnC2uRRRquhZeGWblUQ8+3lmvP+XuF0hLLGCKqnzyytymK6yjSf9ZnV6nwHPei565JW0om0XJCXIDQa1t+LqLhT9c12TLMUJycA85kB/gnA/B4BzDCK3SH1ZndoR9nf6HoOMk51vtnI7CypA1ca8En0EomiF4LHShhbMbDQ4p8y39Wx1UDQiIwhPbZJ69DAMLDTglomnKkfhRHTreCotBbdjM9s1C9oVOScHAM4TeHDz1zjLaxxFtbrJtuumTlY2rR2qD8a77Gj6x7KAZat20xi8YlCIiP4mym2BQfLIvIsPhf+7SXMOZnyiIKO8i+trpCPTxovSdvXQbUzPCz0eEwfTs+fhtBOxLsgcywOSCmrhal5sYfa/NEdsmhVibCqRcccxD/MplfAH3Cev8q1mfsQ/IwWmdW8J9QwOyd3iosxFGO0ZF2k3R4yY07oz+I1W+6t60K2B2znFaTDSkqkSO87EWEeP2ieAMz5z13Xuemq083fj4QiRf+PxsgWiaMz7AY20RvVa7B/5VstuJWzd0I8kyupe3Yzt3EAiKNSnGbc4yKqAmGvh1IfgO9jilYg0hmItLxIO7Xyr0SbEF4qW8gUdTXk8cZi1w0EHR6mIA9RaPcG/YyiaYxtWV/z1bGsXVHMBr81OtME2HwkyBXyPhazkfXjxZJ5+2llSnVFC6yAwglC403buuJYe06yk10U8D1/Nx8It2hUP2mebEH6KOTVJt5pgnmK7dbvYYic14nMEN2apa1YWTFYTyr5PswoKbAGx9tQeLD5oXAZhGzeadVYO0A5WqfqPWJKTfpEMbkn9e0wBjwrez2oAehDyPPjKP5+8XwIBKYF/DTpz2Y6DVLXEUwGG7TS4qqNVbZqELp9c2xiMUk4u4KClkvhidbNQDqCklRoFsSQ3XfzBzc+cPyQ8cP9yROA+VwCJoxsydIAmHrBG2jGuZqMTlxHSNrt1ogxdkipp4QiqZBzfezjJS7hpV7cgIpliJrKqDOjWt1G0OCMpgjTaS88QHH1PERIWLxXWUzVrMwDt4JHWdQJRW0e7B+BVdO+K+0fFjZam8S41lkW0ngFA7YWuebjyqQuZrNNb01dcQww8yRZeeot4aBAEddGeihzhs5JLmqhXWp9eOR2550lTMuEi3pq3mUrGE+56LEl9bnOZrDTCdr2IW7WufZANg3Nfi1BmPWoSasAACAASURBVCmG/QwPE3uamLulCX0Gx0s9Qd6kijSKDSmxTXTnIqOh/Gqhuc6sBgsQVG8eQ9a8JpuFwXKN05FQHSpHodm8m2JU47U+BtTSSMlEULUkgtxghgkAmQD2Y+z9JALPYAq1TDKvrTuL+FVHNUT+s15FRFqUfVVvtbjm7PorBcunuJTdd/PvnADM44X9E4D5nALm3i1p5s+0Ap1JMiKpaLAgxUiuH9AtFVSaDy1FgD5RCUmROAzP8GECP8bsD5LgQWJ/2PssI84UVhmaTklFTuLSZin3XMGintotibK8yZSL/RoQBS67iT+GGWXlFEYgEptnq0hwfhQFRoko2JtZ6BacF0O4ZOEcWz4drBwCKTzMxATECLW8PJ3O52nyjknoPuUKvcWZz1s3bUUjy+9zC4z884V2RkcnzgwlbR2BRJ6rBttfCuS14yXDtNCcUh1hrRFYhdE20a6oKvIXBmdmsgZCWa5clKrCOkrmTdpSi7nq/KEScGZSlCt5hCMp9qh1ZQlqaYT3YL3278TZU8UbXthpIRJFShBHSzziMnTJUgEZRKSyTVdpsdhGUuUwM487kUPkmxPMvmaiAlbbIM6aTYhdwp0qRe3GEkDiwrxZEtPOm39n7YkI8zgR8wRgPtuA+Xvb3YaRDVG2NMLNA+4sAnwpIw2Ci5YI0CAi94JGF+EOnxDOxkTkICAewLQxAxRPI6epXt42tpe/Qoe8o5OqGoo6N1fq2QRx6QoCVLtBnfMz4Q1TPdcaplHhUUURVb0nYRXLZFP20ZVpemldGGOGKvfTgM/+0/akCDhiSBhUOfI03GqCiju5L05oX1tOn2uz52pMQXGjqG4qezAgd1uR3eLUlh5aXpos3DFCnNgqk4amloa1Yd/Nx0g708FxyOA235bWZPMyp42Hhn5VDpMmQtfGuGDZYec579BrE065TariLkp/D3iq0ahFqoKZIKSqrYkCTUBUQx9t1agHvUa1Ftva44rhSUmnP+3SNmDarlt1xlvXSP2XUu3S5y9GKKOjqtojO5csEZJlQk4HD3pM7ARwGsVPAsMYpelYxtmhiH1N2/yk1mrK6yyiUaOpaVYjO28dPuX+48SLH/qPnQDMRV8CXTQj/dy27Q4q69zKV/dFK5q9vRUXL48iWudQNgvimihtbMTM9xHIpJfmIfRuVLL0kHBjwoFMGffSmhGhoRNK9AUohiJ9UZwqrAfUBUJnvr2BHjqIkpO9S96ASMs0MgSCBFjjWBP4tXpi+JLDpAyZWm6QLA/2PAFgnBCpQ49Fkbl0mnV5zb02n6PMjSlUhihEmAVlPKBQyL1NmNhqjZoGh/ZSMBsLTCnjM+bRoQnxFl45lvda6TMHRFtHsNrIIbNz3jwIELeAvNBCDp/Nc1YN2C1lLjC8MDsPI+F59ytodCjUKilWf5rmmyGk1+PXfQwmQOFoTK3EKqhBtN4O1z6nAFx01fULbCKIGupq2/2BKKvdkmbNUbUSCUrxrY4VRNrQA98aqPTW0OstI+IAJG4pNJu7KE0n7NGmGYvDPqFoGTo3KIiDSNgHiD2hfMATINkBJ7DfZ+mEE5kUtRpG8c43d9724VN3LvqyP7HgrDNwAjAXfUFc72DrRlq3cWWUbOxJVvRWh+I4Oh1QtkAM65GxBChTjLSfWB5rAj9Wqo+WolqmSkKGAR45AojLAFxn9hIpkyjffoDGNlxqaoWeidWES9jFDiNwcZmptByI1hLiKkE3CIIDQrRKRAbsBlSQ0htSSUKFoYO1WLT/rT0e67tacm26Y+JZQOc1w6xjUMnN64whgdYqpeWz9k4wtdFw06iOqt8TaoDGPzKnMItqioAu5MchXrWcONfPKLwxCgdyg8s2AT3UHg3uQx02Fw7OmUSBlFTofIb83dDMVhva6xo+KgkqtOA1Gg2+6NrdMfm3UFK1NnoevdoTIUhm6nHr8yZ/oOWD97oujdjzWoCVNk3+qDirLZEnDXo1FbeXdaBGEWCvRoMCvF8yv5d8uq/p/RRB1tQpLY0MY40MNUyt9G4ldBtNYUNwH6Qz90k9nTB+LkbKeaigUEk4nXAW2Sq0S0xR3A8uXuGi0hA4WkYMVSGINRoF39yPkfuSr5S/PDMxMTFxcNo/PLjbw/Cr9DI8Shtz0TfJD/yCJwBzvq94+I7oTBiigYl+l61eOkDNZEMS0WYmORUBB22yhmU/AT7EyPdPUuOJe57YNwF/trkJT4tzwMGfiS/o86dVvTs9gGWELimflMXJeQjYdD59ijEbocaM1bTMg9wl1ouJCF0Gvp9cRTvfQ4C4SrvgELnlIFhWmwUTvfTcANWjRJcA4BpBLuUBj5L6VPc31B8tm7aZRuUHaQppXVgrgVnd0lL3gtgY2iYaX5H3xks0MUuT2tW5QftpDM8879W0NafshJvO5NbMQ9z60iHtDRPXBSoH8G3nzmG/83Ayj0ktVssFjlv5fBGUKeYFvc6QStuOaUlPZ7otvze01a62Hp458WrRz2bKdYeNrqldG1XpdGrtqNxTmzUMXCPrcJuoZ47EgsTIRvbJdYBUTxMi1c4zqSctR+Sa8MgWmgczTtHxU3jKOvcmbApap1YQ0yhzXDgbJXT7xftR9s1RzNKDEKlakjaI0gYhWWnSI/ZCXD0D0K0mB32Q8QHxM18hzxOafrOSI9B0lFl3yvRChSvs4qq4ko7JroVqFdklNRCYEpQ9JDQinD3cmJl+6ik43ByBkQx2jArc8JNdc0Y/8Fi4qAM8AZjFabryerd51YuileuWJDH3DgpFp4CTM0BQCeF9ADKJQI955vuE/WMj3xjdu/uGdXVLy7ePCsCVofa0bbu78LKXbXZxdBmlM/3QmC5Jlh1En40icJNUpNeV1mCUDAnBDNQnH0KiEkfxIEXJCr2oBWEZeC5rqGbMmQA9RZSm3ZdQ7bMBGtRRvaqILDfNtxBhNZFUt5IbZNFjnizbjY2xVugMY7TIFox/UuuwY5QJp4p0iqQ6V60l0MAl1DJkoA6FayZvcJgksOW0Jndu4KUMmZylbhPkOWkptMmtQFAEM52/Fystqo9iupLFombZa3x1fRV41Yr1dArJjCFN2jc/MP2Ms+jRht2Dw4VVeAMn0zCbSCXg7Sw74xqFWXojTXm22q+pACs7wJEq16kspoamyl31wl419fRBpCUORUBdviQgZQVe65YBHBSQcRU5ASRVsQxRuu4Vq6ycArt6FgexT5sKEJmwqLTp94FPDzDLJDpMwEVr2HPNid+P4Gs2XitQ8URLKS4v8SJDKDKNzcZ9INlUkbPYDLrZEdO9Y739e8rQs46c20wkm5hhbe5Tsg9QHiLmR2FmemQExusbYCTbDl9gGB4+ojO/KIT5AVvohxcwh4fpTLgyiqYG4yVL+peRizcJyTmItAUQyiwySoAPeOGdWa328F3DA4dmf/eCm6861LdyZf85amAFzezJ+nh9/FtP7plZt67frVq14qRKo/4KlPQl5jDIzXvAp+PkM6XpxEDJIETlDaCKQuQGRLCB4CfBw2Ed0EMnsUjUQ+j7w3aNhq2BQwkJe0TsptQYalx8tkuAnwSgXnLuhSJYBRQ1NS8FOQ+VcytY3pZCpyqEa4ZgSHpzhs62GqCFiUVNWXPDhQBQQQrHbHdCnz0fcjRSY9uYNidZ5pT4okrYQthuoCwuv4C0ViZsmUi2/9Y677OSxg6CfGdHKd+Wxb8tLlMgVtped3R5AmQZgudClnYWrHxRmAAVD4TQUTepJMVgjQ7DeVWPo9A9U9BtAkqKgg1VDgGUA5Kl9ygTAV20DpBWC2KPWXUg10CkDoBNrXAyOqWDijBPCuMMIafKSELhPixqk5wdEPEjkKV7FQzVhgm9sJR7zgRX2kCSZcx4AH1jL/vGfm13EVLMRCoc0qeg6Cm740vDG74x61q+8nq37SVXrGaKtyDK6Sh4EgNq7X2UgXcKwr1uambP7oMHausGd/vtw6/qniP6AYPF+Q/nhwowtw3fEQFsiBqwrFouVU4RgBcA4ekAqKnvDDDfBwJfrzcmH/gqfGyq86m69e1fj/vWDLrdBzNJBpuycwfACzat7env773QEb5YxMQuGgL45GHf/Oy3/2dlz0XvffhMjOgcB1FkEQAl64lovSCtMIoewygK70b2Y+JI7SNXoqMhENcjYazDJk4EoApIFRO5tcjD7wHgxyBrPCy+eYi0m45JD1BlA0TxBSB4hoJ+yHq13Y5NIGiKDp+zpEFW1wYjLZW28qap3mqDA9VdoUAO65iH2UErXubEoo5hHkO6FmJ1tL4LRY18VcU8e+dgjlUL8+Va/mf5ugwP24Bql3COzjmbqN12N0sJxXdbWbFgAWMtw7bw8bw9nwO9PggCeT+fPg910aLTr0RMm5LKhTq0ZKkLaFnCHDGYVPAElUupqbZqTalJnG7mMHB2t6TNb4rPdqslKDmMPJbWRLHbBI42CJCWW8oEGuHztF4/gZBvNc8mihwWhn2Q+QPKhBWUIXTxGgDoB8Eagd8nkj6BPt0vLCo1p6WS/OEHFUj6zgXCVQJYUv4XMI8QpDcwPPif+2GImgcTHGhM8N3XvUQBsPU4OnN4RzIYbxh0SXIWCr2YQdYZhYlgFwrsbDaz+6bGJw5kvQfTnTt2+B+m9P0HGzCHh2nrnitc2r8uWTY4sAIkPhsifCGInBzoH/gAC3+j4RsPfPV/9u5vXTTDw7QNXknbtZZz1k7ZCm8v9yYrtoKDbSQ0rfWf1GeTwPjone+/8euWjm/b7s5+2XmDVXLVZlQfqyfOLU8bl5HIJYjuJItIRA6SZI9Ks75LlcyBogFIolMQ43WquRhI4UYAjMlRjwj0iBLVtf4F2cOSNR/0IAecT+vqHE4OqozJOozdKYi4ErQJEJQwUgDtmOLSwJ60mpsmz+oVrnU3vaWDOVmoz1m9KmBJm75TYFSRgxdYY4mmVujaQ0EBqCw8LCK/guBYgGIHr6hzxQVodv5NP2qjNkWRdBYGdgX6s8C7jZetkfUCCKxg2ppXD9l5a8DJVmIpvHH0Q0dft289H6NpWYxJ+j+trFo10lrpeg5FryXdL61NNljkoACrnUdZwQ9FpkT8kz71j4s095HWJTWzR+rHOFmLlJwGzm0QgWVhQIqnwNwljWCvz9YmMIyDZCOcNXcBcw0pGSC9dsitB5AKAIyB5xHxzSfAZ+Nm4YvxErN5Y50q8nXBOJFypQnlZTUEHgB0S0SyQ+Kbt37pfX2j88VVF75zV6U0tHwlU3wOIZ6DIGtYtVMBd2ae7wWceXDfntGZh/d9M/tBB88fPMDMU+0+WFWuxL0noXMvFpAXoeBSQdkrgt+QLPvW9K57R+6+7iXKm5v12nzVQ6X1a0/aDOA2APOBFHgsavKMj8ULuQoy9jqiZSC4RLvihw4evOuej/5lDV73M/FZpw/1LBmobIkSdzGAnA6+1ie+MQ1Z8yHhxpOcZSm4pJeS8kYCt1GcW6ZE9TzsUTBTjqb+P0XkJ3za3EnsHwHfHDVdyZAcJ+LcoEt6NgrwyYRJfx45TaPwHvbpiGRNayRRVDkTo/g8IFgRDLZZa23Bn9sIMVYZDDm1sgatK5z7NloTxUZ4wn3rvelvtE3M8tOWi2kEW1mbcwzFwdBpD3hc5NlHzJkHivpcN2qw4Q1qFHnxtiP0DElwG5yt0aSVjHy2Ud9rDd6EPr9xqUKxoWP4s7UenRKyvk/eFdemevE33Y52kjTU1J8h67fgPHTNVZEdUP1EHpO0+RXh2mPCrkrl6hpC1ExmJZKr6KQWIIwKZ49z1ngMvZ8g5aYrxwCghFFpFcTx6YTxGUBumeUgSIdD6m7WvTrYXyeQp3yWPQLZzC4imRFJlmIcnwyUbAKQ5QIyg+wfEp8+Klk6Djqy5SJVThmCUl8ZSn2jInQIQcaaqd87NTG+b6YxaWn2usEIJ8sDpT4Vs4ZvTc2Vfl/07tG+ZOnAFnCwFRhPF8QKsIwwwNeI0gcna+OHYM+edK776/s9d//BAMwcJCvl1ZWq790UIbxckF5gsYHIDiT4eq0+c++Rdcin/SSuvN6dedZZrrKnJnePPcrbzjovZrd6PRFuBYqWA3APKkhp/wDlsUmauvHu9y6b0Ftm69u/HvWt2dTTpJ5T4wgvRcAzWWAKgP+zVpev4vSTUSnmM8Tme5IhikqnIrmTELEaSDSGVmVBm/RxKP4J4OzbPm0+4NiPdYonMPgEo55V6NwWJFoPQGVV3wWhgyL8KHPtMccw5n0jQtL0nJaGfkzERMkKcO4sJFwNomN6BrEGFsELvOhAFL2QkK8qzVP7ygZNefTYtqTtjCRDKjxnCyc/yLaIW8FQCqSe0CsvbiNTvyj6zMYdaCX8AfZCk70TgFvqR8anz4duwvo6CgXtNlOrfNC5/yHMLsjxebSsc1mGWa212e6YTHt4JFhJkzWN3ite7hff2MMYlUi82puPUog2HcXJECXJKQi0Acn12Vcv2WFheZT9zIPSSMcdqT1xeLECcFJe76LSWULuLERUDVMTKyaENMjkKdXUj7NGlWn9AZT0sHbTBbkqrnoSUXwqRrRWGOogmp2k9wE3JjHlb27/6OZ7i21tG97fK/GyV4DjzU5wkFGl6+wkP+Cl8ZmuyLOrRhLun5ed+4Z1EcXnOpSXCOBqIDkIHr8Crvn1xr6DB0sDD6c/KHXP72vA1LoiLN1Y7e/p3YARnC9CW/Mmx/3C/ou1bHLnV4cHD8/3VDvnXft6li0ZfBE4ORtZDgnTYXQyFqLK2v7tw0vHwdLzX602oVL1MWIl/drBxsTmuDSwfCUl7hUC9ApmKIvItzMvt43sOfDgnutW13Sb57/z0a2lcvJqjEtbAN16EKioGU2QIIceJSWLQEPY3ydp/RuYNXcb0VlfOWddSGJwpaUUJWdo5x4BK+bGBTwukj4EUnsYGCdNTyOiXvBqcGbC3xOY8qRqQ9j177HHxdWTBaMzkKI1oBNHIfUtjMmt8ZLroR8ZC2qIlvuPFaFuS2c4D7pabZhcRMiWK7j3uSZxR6um7f6Y81Tb7wW+kWF5AXABWs35186eIUu+fsMvPea2anuut9m2HrJjDcyl1ucLVNWj1WMrZiUDeb8gArTR14ag7NHA4nnaE+zGLHvApzMjKDITFpQY49KATXUxT3vf0OZhEL2MkhXootPJJSeLZRL2TFBK0AOS1R+ULJtq+fLk540p6nFJ6Qx0pa3kcL1480ifAAI1qMufCjwJnD0CPn3YN+rjzqFKGwFnUQ+VS6cKRWcgqHB09hRIfFOt7P7djzx4WGuXWz9yqH8A+s5lgcSzHIqZJ9hn0zVozNDETDqa1XlFVCYeqMZJXO7xKfvGngfG5oweh4fpgvhdKypYPg9FXiYOh5DlSQH8mpfG3dmBQ+N37b6r+f2ctn/fAaY2bibhtKQPlg5RFJ8nCNtQtCmiT3jZ3pya2PnlP1wxOQdI4pnDO2ItdGvTRiNKbeJksHpN4txm0IkKgV5G7tGJCRLZc2D80L/e89FV07ou227t3J6+vt4zkPAyADwdWHYxws0To1Pf/NafLNGo014b3jZSWr1hzYYYZt4K4i9EkKrK3OTzL32ANBAK+uk3fDrzTYTsoKbDOhpXyFkaJFLUg1TaAhSdiY4GcgJ0AyV7zDemdiDwwfwejXVkDkjKqGo4HieVCBOGh/PbOE9vfeZjiqMV5MobRGiTWVagnj8LN1v+Y/lQTxDVtVdxqXQGGR0xZatBky/eocTR+nh3k7zzSzri8x0hom2+TeLMQ952CFlsoLU7Qfltdjk1R5cWKhcZ/hy3gGX0QdStKFGE5pdX76NRlGwk45nHIMsO6Bi37Z6LVdSt9f15LxFFpSEt4XhqHkCfThg5Xdi5qGcNUnwukFsFSLENCIns46z+HfFNteJttJTZcjakB4niuOckLEUvA3RbwkMTxgHEwDgMHfnDkvmHhZsPojQOk3bjc+q8AK2AqOcMjKsrKKqMC/OXPPsvpYcO7Lvr2vX17qbP8uS01zjQjjn0e4EKBVc3tTT5Vq1Rv2XObK3rprvwgzNrS5S8SMETEIcA5An0cCf72j27Dz41+fDg36ffb3Sl7xfANLDrbazv661WzhWBy9HhSSAyggw3eR775vbhIS2Uz/fCi363tj6J3RWIrk/Aj4mXw4jusCAfIvB7b//2p3Z3Pfnsjgrd8S0D6KrnA8EVKLBEgO9MM775zuHyo7M2eOX17pJTX7+8mdCrIoouZG5sEJ+q2pCl3gBuEEBm2Ne/Is361wGyyfZ4eId+oWXDySC50ouBog0WBxpNXKZY0u9AY+b+MLesGEwJYWlIEGPI0t2AaV6XzdfXUi2fbb6m+63DRhQlQ+SSzQDJOgBebrxOVmnuMMMSpsbDPKDxKFtCvwWIFijY1eyZVWMsaordGV1nEt9Vk5x1Yuf6fHcB4MgSQUcbPQ9Hu7ZvD4miORXCU+2H53VX7YSnCDIt4p8S5ifY1/eAl1FEbap18bqtsNAeZS1+F4h6AMvLgRtj6NPJvM+k0+a9UannxUDxRkAp2xiryAxhdp9vzOwgVCX3zleH4jqW1kPc83IiOksAatYQIk6t5Gxy83BIwO+UbPJRFMoj3/D5lPx9cfkUBcArkPAUALkny/gz44fHHr2n9y9rCmAaHJC78OQMMImQZ5pTjcOHyk9a4KABh/4cGOxxEZSiuO5cVFb5qINT24dPUfBuFVg69/7iD86sd5CcjyQvF8F+AL5XAO5IJyYeqY8/Xv9+qXd+TwNmEU32u2XrUehViPRSvY0Z+QtUyz5/+9XVJ+dBSNw2fIdT6oRGkrbMmjVxj1u6MvJuBTvsR+FlCNgvpL/LGNaaN932od6Wkoxu2zdesjQqV14GBG+wWE38p9OZ2ufu/MiSsa7t4rbh/T0AS852EV7GXjZqJU643i9ZYyWiWwIAZeD0Hp/NfAF82u5IdjoThJlrQiqvclH1PNB6UGsUkadBsm9xY/q+Qjg2LBsPAFBFfPaU8vKOOB9F+tp644g/2Dvqwy0YLSMsrVEqCiKtAKQlBKIm5ypErMT1ICdpV03exS4iw5A/553trp5Md5Ba7Es3xs1arlh/EbF2BLmtz+f70r2ewFUK+1Jc4VYN7T47Oehad0v7PYpjNI3MYyJ+PwPv8Vl9n9YHNTrs/LT1pFpNqfwdVcvPm3Ody4qovXHUzz57ykFm5Rp9ecZyXO45HzDZCGQqUSakiZw96LPpb6H4ectJ9n3EldPJVS4RwJUIPKbjjxoSmygdanPPP8FZ7TusZYG8Rkouu2f7h87UGiZe/IHG6Y7oTQh4jtb6heVTwuOPbB8eUnCcBXzbhqdWOYpf45FWKqnfBKpDH4p0tpa9/Pv07nvuXQj4lLK0GjZvlggvE6BziGQsY7yTsfGVg+nIwZ3DZ+kDf07QnS8aej7//j0JmCGq29SD2LvVIbwWENeIyAMI8qk9/NCOncNnaR1n3tdr3nNowFf7XgooK4mkId7NIEgdEOopyBRxc+/24d5984HthcMTS0tQPZ8I36wXBAj8m/eHts8ZxVqN811DejExupcTQIV1UFxLcL6xBiHdJMIHfVq/VbKp+wvFoXDDIVrqXGCC3gRRaci50kUI0ZCSWvKRwlR8+gCn0//ZCYoiGIuLBpWiZClfcKQIcJb/rtTq2cc5N2B2nwsGVyLCPnHRMmJcpRGvCKjAQy8BVM1HIQye5w2TUHXMWeyzuy/dT5dceaiItgL8hi72Yl5tseH20vN+vpBECrXQToZ8AwBnlHKD4CdEYL/4xv6UeQwhm1Zy/9H3pfvZ5IJuXuE0VHy/+iDR8oorr0LfnFa+pJFZ8/cZsCeKk5UIZM0WirQTziJZYw8KH24L0M29N16iSpRULkYqX6jezIA8phaTIcA3guoEc/NenzYedpjVOgCztcJXf7B2skjy4wRyAaDcAxnf6GHPo50RozaH0PWv9YIqLpiy4wZ5SX3DN0R8Vjv08NRCYNl9BNuGx5Y47D1PCC5BxFUMco9kfNOhqbFdRbS7mOvh+VzmewowldKzcnDNYIzRqxy61+iJEPG3sqR3HAXg7H7TjnVtTcWOxyhF0LeRkFZrZCfiK0hYhTDDyxniPV94f3xX93184Tt3lSsDK88AxJ9FwCEguNH7QzfPl+4HYH/BJiK6AgXPzs0L7K5X/2+R5mZOZx7Lmoc/S8BW41Rh19mvdojJ4pbESeV8pGgjUrjo9Q5kgTHOaneCNPZ2fpYFSkTxMh3bNPrSnK+2oMexXFjKcUdUBXCd/AsvgbhERH2AcS9B3AckSzV6Fuf6EZRYD9qBV7FcFRlWaweTkAt2lK2VtESLcx0O68WEztTsPQzxX/hjKCuG0mQI9UxZI/DVrXGdm64Z3VQhSs+fKQUpY7QBYqn1hGYTnlWkN51kHXflup63ecGxbYU7x9lb9LS1ViDLK9U6Unx9Io7iRX9y0d+Zq5xOUflHAFDHZA8iQvjigmSURq0PZNn0PVEkX9z+oXaXvHP9F/927ZSoFP00iEac/PmGpJ/58o7PPPV8NGlePlzfkiBdDkQvFZERjXYBxu8F2FH/Xuqwfy8AJm4bfqwEsGqVQ3c5Ar1SBMYA5cbxJ7+9fTFPLUsXML5ExDxtGsLSQHI6eqY3g/qsjHvY8+D24VO0uH3kK48SI0heL4SvA4GvNOv1//WlD89P5lVwXzd48hkE+GYCPFkIVNwi3PcoS1FgFfPMVxrT++8l8IU1IPhCn6iFFjlgMkVYKp8aYeXCIDmhzJGwq977/dycuB0cThb+OHojC0uCrjxo4yfp4QNIkd0b9qFWSVQn+TrsXfJb1dy2OlLKlgNX/vkj3id1fSDV5Ajr7yipiWNSUjTpOB2VqgDUg0qcRyVUU9lGNB3FYJMwKrUjsU4yIaOaeSvcme6kIeYsWmaOoGFyRgfR1YhMddXVlT0DVsK46lCCeoGry5eq4i3JnAAAIABJREFUQOm/ZxhhWtLmjGA2JZBNmxlS5EKrxBC48EnPI/zCM73Ns7RJUHOXtO80+KwXvt9tR898dWjSHqq4F66B/HfzadIHdVRezdw4gJLNOC35dVnuFOsufMi7L9LCx37299/2Ng+maD1rKSq/GQUHAOGAKOMiVCaCEB+mI8jp//5C8je3Ha3Z8urh5vlI9Au6DwzyD8Jjd8+Vpi8azI9hwUveN7USSsmbEOliFtmLAjd7mPr6fJzQY1j1s7LodxMwcevwnsrSbPBkcfQGQjiPAe4D4H++bbj0nQXqGAjDw619P2fqVyrLeped6rymkBADYwkJSig+0dEzYJqeodqX/mO4T6d5Zr22DT9WRr/23MjRz9vQiee/+vwHkm8e7exqHWYITj3HAV4JgKva3rd2v+vEjgpo3FSrjdwUCZyVo575VPi0u5qQA2YU90dUvQAp2aiFMIu5tGaoNzDLgYynt4NvjgVf8/ZLEKsIldXCtYMgzcMtr+oWoOWA6VRBiAH0pwFe/ntQEwt/P5b3Lc7LUd9ufvWd7LQryj058v0VnxJS5JT+ZCJCKqlpPHKVI2ICFwM0bVgz7KCFjuaQmXsRBUk5NuERc8hlJNLsVQu5qoWX23GE47Hn0qz9me/4ih7Z7P01PxEz0skBtfB76GyitYzG8rC3Hf6aeJHthM6DU7weIGt6nx4g4MwAs/vVvf5i+0VGcsT2u1cQDpgoWYOuqtdlBZDHwWMW1PFU3UlNL+Ovp1T58zvhIyNHA02d7ukZGPoxBvdGQr6Tm9m/3h7/4d7nq6tt5Pjq0lcBwo/aBSHw6UZ96gvHk/o/K0iZr+S7Apj6ZVQHVqwHdm8GgK1I8K0M/P+3fbj88IIHNzxMl8JvrRJvtbtM1N7KgScnKWfiOWbfAN+8C65VDuXRFFZw2/DYAHH1UiL3ZgH+Yn1m4u/moSS1dkubQZF/2RlA9NMqqaYD2Lleo8ZGiaCsFsHHGo2pd5PsXcdCL+w8JlMHM8Aqbuhw82CUDFLUcwkpNzNM6YUbXuMpgOlM6t/k5tT9FiXN+rzFZRUXVYZYuMZQO2CuhB2vuSLM7ginm8Zi72c+JNVzvRQsjgDITpvLBb7JIwCty+TQ3m/O9ovrbPR3f76IHouAfW48Wfz6uiLAI46miFRnC5q2RPFzbkEZXXW1FiRBGqobYE9LMvDrBvS5jr/LL+9ox9+xv4ianlffBCjK1QwUuzz3IVcec658RzPN/uWLV1d3L9RguWS4cSaA+7+srOL9dWNPfef+xWR9C97Hi1zAJu+Wbni5I9R7tMRAn0nrU3dE5W9OfjdS9ecVMM+8ckeyasvG1c5FPyEILweGrzYl+6cvfrDy2CLPH+gJPGlgw0WI8JJcCUJldPJyjdXL9Hm6n31209G66K943/SqkovfAkgvZZLrbh+Ob1/EPuC299ZOjuLorUB4Rs6FK7RuFNzUPqD6tOji73/+6vjOi99z3wuY5UUBEfMOap6yWTe1o6uKrjKIUr4UiXptkMPuKKW+GStbI639zLUvMze6VJPCjSeUlIi1g+li4eY+5mwm2JKFl6aK86aMcxy4Ls8WFRZU9tkLhWxeZTfbNhpHO3/Fsm3b9MBZLD4/9/um3rOoa5SUBzlfSny049eHwjzH37m+7kXCe0E/Wd9zeeRuuqY6bICVFURYEUnH2TfHiKKs9Z0bgM3+/he6Pha8NruuL6K+HyOXnC7CytVMg1iVWulVDiFVxhH5DmnUP3Pbh/sDl/coL22iSqnvF5HwXGH5G0+775q3vLXQyo73/Suvd5ee/mMvF4dvUTEaYfgXpskvbd/xucnno8bauo+Od/+P5XPbtt0RuQu3DlBUfgMCXiHAj6QZ/M32D5cW5S2izZXaWGjozPca6qlaINVYqv0GgKNMFKCBJSU/i4RnifhrPv8BKwEs+LrwnRPLqn3l1xHgpYGl2NZnDI0OHBLAJ6Yn977jrmvX1y5+zyMvYG4EwDwipOveXLKUqPRKhGhFsCfMxSVDw8PEKUXSPZmvf024OR5mrPOQw6IqLe/pOLTrJ5esULUbZj8J4CdFJAtAdbQQpXt/1OVH+wZFiDlXSNT5mY4Wjv25I2W3f3e/v9DpLoLk+fojs0PA8HDoDHmPPJ45j/+IJlzxue4Qs/v4i2MMyxPGKlqcEFWVQrQEpDkuvnkQyec1mIVC1u79nWt7ncscff+QejY5qr5ZlNiOOq4bWmiOKoecK40LQF0Y/+Hx8ZH/fPhjp7Zq7Ef5VvA172++DYguBc7+dmzfoS/dfd2anOO50Hf57L2vWLBk6OzLkegnEXHMZ/BPPDZ2z/aPH0mFeva22l7Top7ex7/hYbrgqqt6e/p6LnIU/ZQgTxPAX9/6geTuxa5TaxmVuP8yIrTmRufnjMQShLyb6OGez30o+dZC69WiMlHyVhQ6x/vs6ts+0kU+n2cF+kUNLD/nBc7hfwXAfsOzvByoMzzgoIdZVj49EXnT5z8Y/5GuZtt7d2xOU7pooX3S94WiKkHpXITkbDTuZYcjmK0g0GJE/Kj3zW96nt6rArYtLOrYiGilj+JeomiAMCozZzWRTBVz9AJPC33LBferaIDMueDi6EkLbuOoCxyDZq09QI7jdQybmLX24tyoToCS0KO4R8+19+kUQHYATDHqu/cScQNJeclPCetsuDU/7fyQq+6PXEUV4DXl2ZFy+o9fvLq6a7F7esn7Gz9D6NSl9Lq99z345Z03HJ3it9j1HutyigvV8sCbAOgNjHIfNP3f+717n9j+yXkau8e6gXmWf84A02oPlfUbosT9EgCuR4H/feuD/3rTsYbP2972WDleu/ZsYOwpCNudx5LzDjNP2e7br648frTzYic57r8C0L0+Q/+ROz5Q2rHY86jRZU9P5Y0o8CoV3bXPmaWC2oEpcJsb5CoQ+cfPXZ38pb590bvv7wMvP26L5h3pIoU7ogvNTOQqa5zrucgU3lsGsJ17GKIEFJhhbj6cSeNB8A2lx3Td9h1UJZbIuWQpQtxDhLE6zIo0Jxh14ihtko5sdshfzAkKc5wkcw86Skrd/ZFibHC+FHzu7+EY0Ox4AbNrYmfOhkxgcAZ+q5rPuThhkF6kWMWAVTSlyciHOasfJhfNGRIv9P0v9jpc7HIsrlwqLfkpAB355eki2HBR3y6CpGFaI9pRY/z7mdq+r2hGtNh1v/p3mm+LkF6WCv/FHR/40NPZ2XdPjX3bb02tisqltyHA+QLy6emp2o13Xft0/+I52qfnADCHaduvv6M/7um7FEV+BgC+Olmb+au7ru1WLD/K15PbRRRLrJsMaXb3a/sn//bpdGdxX5aWBeiCl5/vIvxFEfmnz38ovmWxF4jeJ5e8t36Kc/hLgG5NTkVupZm5ZEWPCK9CwM/c+qEQYRpovus7Pyls4sBdryNTWL3IE9ej4hgvzLXWTFTCPlioh5sco1kbqGDNGGfpw00/84RwY0pzwvBQUcDsWr9yFjMdhYyqDuMlLFQ2RTZWky2ZZk6n1SpWJGOrp6kJ26z6ZXeKvfDxtPdhrjN9jCn8QosvVAKY9/OzQZmU3NmSqGMSiGKnTAv1CZeoBORjBKc+8zMM2QT7Zi1M0Sy4gwt+/7PPV9f6FqwQzP5+EJIlcdL/VhFVhpdpHa5VM44oGXzEdiQ87CMU/kqNGzccjULX/e1pL2LtaZt/W4B8U9JPHEuEegz33DEtetn/3bxAHPwyIE0D899OzTy141geAovd2LMKmHoiV2/evJnA/XcQXoIIf37rh5OvLnZndDldx5otp74YGF6qdXSdZtH6YK5tq4OsakmYANA0s//7xabUr/7N2slRKfolFf+99cPxR451n9ZtPvVFgPRftKnDZmfdmZKqKpnKv+EqANwFjQPvuDUX7XjFb337xV6ic0HvPeUw6s9wwao9gnH97N/5DYFAPVHUey5ifGrQVwvsxHA/6tHnmad+XOk4ip3sJzyku9lnIx5mxoEhRTUx6yjpzdVUsTl0cCWgSKd3egjjiNnrnLR5bTMYa70hnDYEM48SqzFa2N+uqBSDarmaBOX92PC7/s0W734/F6poNXWO4CUe4/rybRfb6+5Cdx5/2Ga7NmseRwgJYZQguRKhUzGTGEWpafqE8g0BP80sNYFGA0l5n12v7u+3+K4L3uoiv//Wbh3r+rq2h1w9NU563iQsGjlO6xfmMJpyUf++jnKPWp48Dph94tYPVkYW6ph3HvFr3lM7CaP49wTgxumZvbc+F+B0LPeoLqtZ7caBk38WBN8AKJ+ayWb+9c6PLHk62lzkCNkiNvisAaZ20oj6XwUg/xUR7hyfPPz/fvVj80urzbtvV17vLlt/xRqfRKuApMGZNGKWphA3kDljlzbGxuppbWws23nD4uZO9USe0rP+lUj0FmL/gZs/YhfHol9b376nOrh82UUg9BZ1WTQzgznmVRBkabAPgKtv/Uh8h35Rr/uzh0oTj6c/aR47na+j1PTVkyeKe89ykJxuHVdtLpk6b76CrtlpFq/xg6JSg312UJif9NDY6z1PIqVNaxB1p91z9HCUoKXpJmo0xVBCogQYY03lddusRHFUiwtMwcSQ1dVQnSVZxeWYdCTU1B9y55wj0uSOaE4B4Th6NK0MWgGi1cNSjmWHJJ4+hHTd6vUWacosOgjg1FRObT7UiA4ySjByMTKX7OmHkiFIEx2oUnoqPmsypdPI+YjkQhHe89vTObKH2Hn8zJSUlr0JMdks4MfNfVLHsFzfbqQkH96w74II8KDP+JOff/T/33ms5bJL39d8GyKeljX9X9/+R+UQuX4PvC57X+NsQfyNEFRlH9v78CMjz1at9dkATLzsXZMrJCr/MgqcCwB/dusfxF88xvOGOpbYD/0V9RQtPhs7lxC5qmRYFnNH1J/gXXrwniKCW8x2XvHr06ur5eSnddlbPhJfs5jPdC5z2bv29Ui8/JUk8GYVXdPIUJUajGOdZ042wAiQIOA6IHwim66/+7Y/DWIeL//Ne7Z6QT037dcRTeTWnJ8to/4wEVY3OFd6AaJTdZdgFMmaKgeLMrNOKPy79O/qHVFEWiA64zsuyPuZ0/2S1Q96lLrmkrYudWTsFJcsfi8EczszQjWwUbQh0nS0hBglBJRIqIkq2KCkmTpYanip/okESlH32p3Xj6olu/esqat5WwB71tEZdckw5wgRiliyDF0SBXC3oI9VYM0ae2qho7inW0NrajkjvqvaOSqxUT3A7d8So9pN6npRddOc0t3DE04n3H2mIrtNIGoqKOqD2KZlWR148+/AoKSj0W/fyAJd/qOdv7kuuAW+/yM/shDrIH9fGF3Uc0aMPW8Q0IgYjYeJ4mpxtGS3fff5cQZdVplAlk80vvrlHdu3H5u5md5X5Z7S1STydwcOfPvO55OfudA9vO1X9/eWBpb8oiBejAzXNQ6P3bn940dVNFtolfb+MwJMrQuWz79wExP9mp58L+mHP/8HlScWteWOhSyUrmy4GAleqVMfui5mibQhISqlJVRXjUDWkUeUfdM4p2LQvJt9zbsbZ0TO/fc0kxtu+6P4S8e6f0q07y+tukhE3hpyOSv+GWDqz3A7BZwXkD4i2CAMnxJ/8BoF9iuvv949edfpVwjg8nm33RrVa3d7RbVzXHlZhOUzUeikMKenKbG6yeRqtq1Za8WLsC+KKrqcTR2aFK/OVEsNkA8yZAc4yw5pkwI5mxFHikSq3t0eF5xrJ7v3r6OkoIIT6iAD7CMgBTpDbqdjPKbwbuM84lT1SOt/VlhQ9FPwM5kQw3o2dXLKA3GzVmu5nwf0EpcFszI2uoCZ/mrpQbxHwow12lXPdN0dSZXyr1wrkxWy5lbn6yjHM+d3tNDyC72/0EU3x/c/6yPdJZzu9SmvioUiqqx1rvfHQbgMRAf00aQPipJb9rhYpEk5XoauHaowDMhxRZiqtn75pjf+rgjubWb1G7Zf039gocN8vt9/zXvqP0LofhlAPo2N2j/fciy9lDl29rgB0wq/p9h44LsZ4RuTzX1/+gzqGLjtbY+VopUDpZGZg/WHP/a0sKi+rjzT9m/b6ArcvuJ4zeWH6bW/+b6tENPbOEs/eutHF0+SL86XUooGl51zDgr8vM5Jm7yDIVOnfIQW0QN0gqgoBZwMAjdkOPnxz//BssMXvfvOXvEDbxIuJH2P4dLROXMqrYuovAXBrRCUXBY4bD8wqzq10Tpz9jAWp0uqfFjYqqgzZE0niFijUJMySyeBfU2jUBAVxTU7BgPSwPk8+su3rBwWWvLo76s3+HfrZUpD6iQcwFqLsAse93drX7u3q2DpXO/6mKo/Cqi0N9kvYh5CELuBpxyUDnc+5O0sm+e6fxSAP3msZapi+5e9t/l2zaoakH1i+zGWup6vc3f5expnAbr/CaIi4/W/vPWjphFxXN/tcQGmUn2SoXWvIIGrBOWGW/4w+bvjOXiNLE/mlb2+StrYAahTVHYYpYRJAtSjaTgDVEB8SRyNfu4PP/S0n/LiuuLF/iiwrz9l40Ug7o2Q1X7/eJ8w2jSKHf0CICoQmiPY7AuwHW1aogg4KCybkOgO9um1tz7+qSe2bThrRT2Ty1WM4cjztdCsnAFdTNizxlGymZQkL1gKkKk9IadRZStp6BxrzkFylkilRZ9K92w1r7RbzgqitcDX9FMZyCSIEt/TGQRqeMzUBVtVgAQ1tcY4r+Xm0emsg3qmRb2FPr+Y89WxQ9a/0tOu35o2y1TUUTtUsUJ0DOjKRr0C7EOkHgCeyny6x8vMZOiCL1TE7P5GF9r/7uWP8Xg6irZaLim5vtMdlV8HQAkL70eAVBWcYlcZi6hndLbnSPFQYgcIX2qk9RuPNzq87N3ZT4D4CwTkus/9Ufmh48GB5+Mzl71rcghd5f0IzM1m9ge3X1vdczygecyAqWBZHlz3SnBwFXr+5GevKf3z8RywpvOl8y46B7WjZVmhKjJwLJyHGMgNEpphlDoKTInHB2+59uovHytganS4ov/cixDlTVBvXP3Zj82vQHS049j262NLylH1tYL4uhB9hLJYG3Jm17hUFUI5cISwRQRGBLNrG/v33eX7dvV51/9ahqjU6pQf6wk0bmV1iCDeQEBqc9AbRkKDNVf4GaJOs4vtmruZ3d/vgEzrfSuQmlQaB38GMyZToGwiwowIzwiyEuBrDL6BDA0Gn6JkqRA1xPuMiTMFVuMeqoKS3tydKaXVF0PUupjo9YhoKmcWWG2zeOka7cBDV16c0/pnghBFWnPVqFzrrqg0GxdpU0uVraooVAUVMFHFeqMToYKIVilY9SgZ+PEMGo+L1CdAMDsqZ7WT9bBQir5QCr6Ia0IHFBzGfTH1vpQouVDV10X4gDawlFUSUflQiUKafMTD3RzjuJkh/t3IzMjXFjntc8ReXf6exk8iw3mSyV/dcu0itCAWcVzP1SIXXHWwf2m593eAXAUa6Udv/hPjbR9TpHlMgKlgWVmx7mJguErA//nN15SPhct4xHmw2iD0V6Ymmml/z3jzsx87NadrDKOm45qKT27pw7uv+/TTj99jiyw7NoaXvrO5NYrgF5qer73tj8sPHtcXot37k994BgH9FwAZCg61nSBp04yzqsJmzApcAoGNCNAnIp+GTD45Wnv8YKk3fSV7XnZc+5J/yKhWFPc6iFcTJWtRcDAAQO7qXRhv5/rj9rFcUNeAvlNcVz24u1sb+fumW97q0JvRTcjoNGVXMA2EJ1VY0oaSMkQ1j9eOelOYFWRSm2cGztiaPWzLCjgv5FlViMRUiOZ+aY9fywkqbqQFZCWK5m7hUaiTSqxScYykdW8NexOyPrkO0IPKBWkzKDL9p8AvsiMzjlZo1uXcLXtchOpwoLsWb8x4yfZ4qY+INFU2TYnfx3SjPZPv+cgHhj3SkgR6T3VU2YZIKjY9KsKTGnVoZJlEPaMx9o4ZVLb7PKA8U7MK1vMC8PU6Nq/f/kfzimkvuNuXv6v5P5BwedNnf3P7NUcfHFlwZc/DAhbwrVjzu9pPSNl/8PZrrOey6O9y0YBpNcu1W86LHLwHxV930x+XP328x6fRJWzY0KbZVHuiiqtUUowqSYTllKkamWqPH1CXRPHyrZv/tPzA8W7vst80Kf5fEfaffSYg/7qrDvZD0vtqEbzCaG0hSujaLYvpTNxF3wmkdr1icYWwbESEMdbaJs98asqPKAn+rFlz4TlvZiGxjO732bNzrtxHkgw5pDXmec5YQcSkLXCuRblCzMIQoS1yPkuZvECQAjNy98aWi2No4yuqdK7P+tkF2d2CU5v5DHVW7QPlkm12wow3Xczi53/IO9E5TOXntajTWryshPr8mlV9YlbR0ILXOtsUrViJ4ntOZlWv85apWxc1q8OUt3gc5WTTXKCz4GMK788kfUy4ts9LVjfy/5ziHsGWvZgQWvjanZ2Sz/X9W40VIYmhelLkei4gdKexyBQaWEIaQD5OS9S7lzDK6UP5Q73FALBGmgLuOHv4+0PT93z7eLvbIXt7wdUA+ID42r8db7lr4XPz7C6hgdqAG/p9IYoa0viDY3lgLA4wr7zevX7dG898+gH/AUb+p5uvKf3j8R6CIfyy1a9GdC8ENs9v8gRNI1ojNOySFmkSwaRnOQwghzj1Oz/35z1acziu1+uumlzBUektRLjis0/82+8fK9+sc6OXvGNqZUzJm1W/s/h7iNbsyd0inxiWIGldMFWVbwZ8nIj2gfh+EXwVohpQwW0NGLtzprlvPRP0mgBxq7zUEe7phhZgtXTuo0VQHFXIJcucuOUIyXIyn3JMzItltkrvLJ2M1mCRqB+wxsg5IBUANBcXdI5vpfis/rTd715f92cWWn/3+wtdCbP7XvPhYSu2mGt/1Qm9tRn9LfgCBSkpkUMemiOZ1B7XOu8RUWAXkb6buH/E7s8zKCReHwpKoqI4gt5NjpLzEd0mAKmLyCiC1ML158BhMl6CntFQjsmbkp0P9OBbolemrvXT02OHb/vyJ+Z0WF3o7Nr7r31H/TSK6be9x+tu2f1v//FM7qtFbfBZXEiDHyn1/SEI7hae+fhiwX5RgHnp/5hekyTxb3vBx26+tj32dzz7b02YtaeerVa24nks8zzJ4htR1qxlzYlGx/B85615PJtqfcaehNWzLiJ0v5AKXPO5P1lYpGP+DQ7T66567ykUu7cyyqktlfVwO+mM+SQA7hcv+xH8E+Dx8cPTk/vrUdsZ77Kf29dDQ4MvR5C3AOPJSHz3jB//dp33VTxyYjQfs7Jq+TEc+/F3NvBBHPmkShQtcxIvJ3QDoFYTDFUgjBQEWv2fEC+FiaKOntARgXSxRwUwzXPDz+L3d4olFesu+lQLfV6311XyOOpJWWh9He/bhRZQJ+Tj+fEXXFfbjkbEwe0hE4AZAZ4WSccyae7yXD+IkQ6gdfTQFkmbnMuvw7anE/4OIvLlgdjFmwnLWxHcKrXVFeRRneAxf3SVbaF4KqG+UYRElee7nrTFWQpgaVEvwpfTWv3G2/5iYWm3ec+xBlHrf+wdjLy0CfzX3w/pePexXPYb6mQZ/5kA/8vo1MF/XYz60oKAqUiMUd/Ps8DZE08+9Wt33bD4If0F7vKw7SuvJ61V7l8xRIVEW+IrDgf7+sm7qh8f33fr3wVv8GfyUtCP4+S/AXD/zNie9z8jVZMrr3evXfOjmwHcjxJxvwA+hUwjDP4JwWz0MB4aXwzFSqPt0tK15zjBNwHCBQIwVueJB+oyOpaxNlGaWWCiL0zrWVBOrcP+yzpC6HocuIrDaAAgXuGMHA9lAFTyvdZdlQig/X5zh7BybPA507xe7dtCGXAOKq9ZjeWvljnZERFfbkdh8ZNVMLpM0EJIGST0jl5iss+bZmiBqgH0g71xfol3Hn8n9lrMmEdk5gtkW9XCnxeSJgo2VLzCY3MSGDWqPMyYzYg1I1WifpE0qK7tKxE/lGXbep9WkwZl5FMPUXVNBPELHJU2gkifCEwA8iEGqFtZQccnOJlOourBCMrBGrV76ED/prM8bdUpLwx3M6Q33vInPbP8oY713rr8N5rnOoD3eOH/RdmuOz67OIm4Y93Mc778Zb+RvixCeJ9n+f3GN7/8jYXI+0cFTI3MhpJzz6cI3i2p/62b/uI4Gyatwx6my37uVyq+v1qOUpdgxfU7cYMCvEIIBxFxCJmXWNEJqY4sh1iyf/vsx0wZ+pm+8PW/3tRpm3d4httv2XvjP3SnEOsufGdlZjSLDz30Z5Otm2jerQ7Ttl/91WpaR3wmaU1Y/TBd8o53rShBfAkQvgYAT/NQH63z4SebMHWAuT4mxp00Y5m50WOhiGaBs2cOloRl4qgH0VURXBW1+y5Ks4mqCqIYDM6UkqMIrsHK3Ggxuwg5Ox1eTHn9aJ+fjYntcr0ef8HkUQAkQY3Tra7XWp/+y5wdtQPORpbXOkroKmv3fxqEpxj8FIufEfRqWzuts/XP9OKb6/MhPdZHj45sRpWYkpMclE8jdBu1gQchktXvftJsS6ybh+wgPuywdywCpzP/rVe7alGQzYrmlUWXuuyXMWvcdLxMkWJDl//CxDLXV/kQII6Mjo198mufHJrPgfW4TptmoUNr11STg4206Wq+0pdJ7Tu7fc7F1m96MVfRorf9+nc2f0UAXtzk5u8U03nzffiogHn526dXu3L8fhH42mc/lnxi0Xsw14IalS3/0c2u5H5CWKXEuaSXMgmNMYjK9+/3RPuh4UdTl056qTcmsycax1uQnmsXLrxyV2VgzYpLHbqfA84+/pm9n/piJ2gueeHwkvH6qNvac87hu+/+5efkJlnoHFr5oHL2RgS6lAAvFshOSqExlcrU7ibMqHr3Xk++JpBxqPs+x+RqvaGVakMQk0RVFFclF1VQsCpAJW0qoUiCoqY8EiOQGpup4ZmWdXPzLctx7dCVwtmK+rrroaFRNPuatNFINdbtuE3s97zXU0QuhA2VAAAgAElEQVSHWhEpTOg0VQ2tcO3MpwKonMQmiE+BoMHIdWCYYUnrAjKlzRugLLNSyKKi+YW+xXnet0hPWUs29UQRlQYdlNYRJBsIabMKryjDQIjHgM1lNNV4Xjm2hNE0SWkywcpkUJOam1TQivk7fNhFYApQbktnpu/4/HXLzL30eF9aTooHB38dUE6eqfM1d/w/pQf1Wz3e9c31uR/5tdqr2EXvUk4wsDwBiLuZeQ8j7Ykyv28mru1XMJ2sp7xkVZ0NTLd/4ekTcnxMGh2jrCZLPu4BPnf4yaf++WhZ9LyAqeCybPXQGwHwjenYoV98FtJivOi/jfb2VHuXe0kPJ/TU1HcjjN/2trEl1f6enyDA1wrAH0/fc+d/tsLwzVf191GSDAzy9O67rl20PuCzebF0rkuftBuGNm3ACM9HwVd74I0M9WoKjcOpTO1jSfem2BhTOwod/WMFiYKeM48L4ryAcMzLh2gtt3E1cQv7vw5ECmqsF6v6kTpFirLDQQU81DHSKfg6e1bq8oECpXSDfGbPnMW0gJd7nCsPVLtUOgapOEgMJJkG3AKUijmNmXukjn9mQtAAzjKx2XWXadpsLHtRd+VQW5jz+3oGx188CUI82+FCCToZyoTqOuVKkQO3JLAYopMcxhtAcOn/ae9L4Oyoqrz/59yqt/WSztbZgJAQtoRVEEFRwk6ABIFpENRh0XHGccQZZcZxZr5vevzGTx11XHAb1NFZAKE/BQkkQwSMogaEsCcsWYCQdHe60+vrt1XVPefrW90dsqdf0p2FvPoR3uvuulX3nnvrX+ee5X+IXD1y58Cx3Q68FXHdH3VecgMvn+BMr0Gyb6Bsye6PwYSKza8iAr2u0IfyPRue2yszlMu4+/O26ip/7CdcHS4R/dfFt933ZGPjSm3cde2s3Xd6mzPmfTJ/mJJ3viE9RpmPhegUsEtggVtPzubuTFXNCl0DNz6S1xBxC6j3hcV7QvjjHFh/WZjL6n2S2P71g19PuZI5O5T3TgHTddqQ92Ur2rT428n7yh71AdzAbSm8dPoDxHRJJPY76zau+VXMZnLaxzI12ZoMjRfpXfb17Wvn7NcxNfL5n/j02ASnT2DG6RA5M6JglkUUqhSLIQXdzgERSdAmJHmCI5VwVPAuhzoO6xnWA7fzIe55JsrANXeX+VLu9ff1ZOy6f/H22uXRO2IQuJRDR1Li1xnypxn1jmDyJxIwDsRphZQU6IU4Yl/Ng1zmmOOcSxY9JPJEfj6BZOz9Hjp26MMa9FFtDqx4izDQmXVz1uIPkYYP//LbX+nfMu+Z9jVw/0aee+OnajO11Z8iwhwovtFafO7J5V1rBU3XjPgWOb5lwz3mrWs38kV/9pkJnpeYRKSTlHgKQDNBNJNUZoAwrd/U1hVa/dCSb3+xP866/LG6nd2k1EnfIMbysKPz7p0piDsEzHnzViXNzMPPV+IPdW7c+JERdPTs61W+0/td9vHuseRl/khBV0Dlp50b2352GD4dNL1QX1cdpk1tXXVf8/LGfV6zZPgCauTzP3rrxETaO5nVvBMqx0cmmqUI66yGPVYLXRGiXouoQzTaZBH2wtEBkeeIghyHxaC2tdN48eF3ZT+cubu66tt2qdzzdzok5/ZyEf9x6FbMm8eGTcrArzPwJ7uaTEymHjCTmbgmDpJzAfxAHiq9MUCq4+MzJQO/YNgPDBIFpoTLaNv8UtvS4b5tX7b9m8TOos1HSESvhaqP9LZufGFvn904I2/2WUd6Ht8CYKJafCO/4nfLl879tWApGEsb3ZtkL1/GW4/wgo91jvGTNaeIyKYIpVbTmy86W2ZbLi8rscJuBdIN95h5k8+vEltV/2b7mnV7Q+N2yS2F85nMH6tEf78zv8kOAdOBCTjz9yC89OC3Ez/aD8/DPrmlMzvUTZg41xj6mBJeQaS3P/HoN9s3Ra+lM4mUmXrkzM7Vi28ZToGofdLfXd9kQAtIpdOTPKbZAN4B6HEhRZOAaKzVKCEc9VgtdUUadgPSZdX2CaKsxk6OSJmMlYGSP+poP4dd++cAGP1ed2FwS+5ILAYUYgZZa+DYk2JLh+/SLKsNcQ2pN4ZhxhK4nsETAR4DIp+JWCQ2EeRjDdIRmQgV2Hh5VhRZk6HHXsCaKA4m8g92eyiUaZswsq0SybY/562g+DjSIBKl9UT2d6VS/smHbx/Xu5dARvM+uSpB9vBzyThCcF0ngXxj8e39NbAaGwmNzQZzp+poAOa8T5ZmM/FX+su9HAtFAKK1EH2ZGK9AZIMQvVnSUvNWQNrU1G+WaXRC2mPwdry3k5MTfiyQH73RumbpjsB3R4BJl328OIOY/qWfJvYfFt4+vMqOe71g99cF3Btq3BXHsk+fgOg0Vvzk2ed//oeOTc9ANaTalOne+PxX9zqsaf8Mr5Ev+NgtNWlUTYlYpho2RynjeBI5zrKd7BQdlx7tCNAihAVF2CMa9kUIelWiHiEqgKIQKoEaDsSGLpBvKJVQ1XPhNwPsH+6LcdnJm+nutgrj3C7yfkf0eEO/27GsdhcGsOO/x9kxsWM/pqt3ZeQHAHEgCTKuo8hgH8zOqeXKOaSITLWnXAd4Y5nNWIYZAyBDcAXFOEVEjm8zAmsBzrsO6oMgZ4izAOeZ/MAIBUypkJ1N2Vlh3bFl8P22EVlDj/lm6+PgCdsE7Mf7gi24AZQRxcHXsI/ngmD50tv/td+UVP6WdEuZx45HnjPN8/hGEJ8tqv/PFgr3PPSjMZ2Y2+gd+Tq81zMrZG79HFk6Chqm2+GGhx82yTdmKrMeCcJsgE8g6CwFPCY4j38JoFaCrFTQysjSWk/C1x7oeKB1bwLoL/9E+DmwZPqy+a8t/clYx9a+1bEdYLrO8vTD5xLTNWvbV398b1Tc/QMSe3bXeR/sqPVqqy93ZggiXb1x46qmV179+XoKuwXJmp6uZ/6xZzNY7NktDqhWsdnl8MMmqecdxipHgngqSKdBaZogOkxJ6h3ZpCIqCaTgAqZFg0iJ3M9FQamkisBSWARJQZTyokFJQQXADvBQxmARK6oD4DqUyTTwu83ZSzuS60CO0UD+jRNc/H2zl30oQNwxKMdxjANMRGTNQNUOdqqeD+N77NJDQSlmTpNQhslkwJwh64rqsXMkpAFKkVLKlR8BsYtDjTlEiUyRlV2KYZGZ8yrIEUwfAX3s/oZEwOrsG5u1GodlmwM/34pR3VG86u6i8N/6u9vUOyvAYI57HGagiqLTvAR4Igizz42ARhnbDS8Ye0F1wqu6lAg3MKhVLb67tmPVsyvumR3SnH/yJ3l9/sbeTRbjExbL/y0aaQ+5k9+8eati+sLF1c9EW26/3ZrV6YdNIWAms5nBpDMFfAxBjyEiV1r6v4th7gt7EwlwyScK5/tkbiwi/OyOsgu3A0wXNpCsGvchkB6x8HvJvz+gnvLR7ozLXqhbcBR79FECn5YrdT7WuvGZR9ZveLLVmL7SmJp02+tLGwdzdEe7M/vn+s5mlTj8+CQl0kk2ybFszFSoTOO4XpFOdgtToLWknI49lyIZS5oh0bSypmKSiwFyjYKQDQYe7LjkbKCuxAW7LSvCAaoS6yjRnY3PgYBTdB03hON5Gohk31zIKE57cpXHjMakt06ZjYk1PMc4LHGhL1dKA0moC7p3tHeciMk2XMhLHHLvNOPNOT3OJe+S0kOAnIboat7kDDjLZHIqWnSJ6s4ZM0giauMSSjFwO/KPOAp1q0inXc3WdhFRcUmoLcJDd9I47vkWh4slYkK3WnlVhZ/s87pfHQkWcQeU88eenYx47JmGzQ1ENMWq3pnP5+5zWtbcuY3eiy359KaOTYAJZVZNXbR61bfcVnmPt787k1fskE1mPkHQXlVZTYJXi5pvy3Xlgh702m1tmE4bTkXTU9WpmkmuhkDupWXrdhd8vqu5uujPsvUJTn1HoF9Y1H7fC9tqq9sBpgu7qUlW36KkLQ98P/GD/fPY7t+7ugycqvRh72TYG6IoOqwv2/aHtq6Vv9qw/vmNqVRf13Rs2rR8+e37JU5z/0rmrbs7YE1POyljaxIplEwykeCUKKWMUkrIVjNxrRKqCRT/s5AMEdKs5NiUXB2dpLr4zXh76z4dJ2qc/ZIG61RSGhdnGDn/SlyyQqwzEbr4yhjIXAhAXFaCHJVcRI4dSV3cIkIQBQN8kBIS4trtcUqjY1CK2TsGgNDl+cc0cwOE7PFGl5wuFwNjnDgT33+zDWKI/Omt8FGHaHHnNn8OaZUDIDn0+9gGMHjOlnrn9u0HcXhA0IPAqkCfqq5n6PMlkheDlU+07A0oDM2im8Nw5gnpsX71GcTmOgVmAfSwwt754Pe+9HpjI/Cde9oy7X3qj/Vqpau3XU6b7hVHc+3Puyk70aSS/0SM01TVaf8uWaIHKi8Q8TOR2JeVaAP15lq6g3wYg+iA/XJEvJdOJjWz3/OfAvuD19rXbld3fTvAPP+Pe8dn0ql/EJWHH7w99eCB8oDuj344bTuRrnsPM11fLPXNLBQ3PduZff2XG9peXMda6Bw3obbt4HEK7Q8Jln/PeR/NH+YZ70oiPWUg2XHbZKLtfMRbJHBveb+YAX+LgPmtt8pvcWnubGu8rVFx6Nq720pveZ77vu0jtk37IS1yW6ZARY5IW0jxkipWRm+ue23x4qNHwAHZyLMbGrwp6cNrMpnkXICuBuFwVXpYI7knt/r3qyZObNdH1q2sCjb1pcioI86TXmNKjVdVF0Y65nJnK8Rtv3H44YcxYxYxHwfFyQScBNXxxJRVpQ6orlbgOQg9C0TrOro2te9tVICbsPkfD24XyMJcoWXJtrGr2wHm/I/1TgBSX4DSnQt/4P+6/CX/9msx/2PNGcjYM62EHwqi3OxCqfeVbKn1N62tK18uarYtmc63tC9t7Hv7jXzfj+iSPysc6SldRcQnbS5StDlnfQuw2ZJqLu7mlgC3rUd5qN2WYLUrr8soto9V5sH+bpWOLxGUC6rUzJA1DiRBHa8tvH3qSIS29fPL3sNn4axE3diJUw34XGK9AnB2Xfw6Unv3ou7718zGSrN+ZU+1Z/xMqddVCA00p2NLGD8lh32Q+ea241yMooLfG2QTHXZbHtwhEPWUTgHhVDJ8jEJdAsBUF/UBq3+zpnvNI3vrd7n8Y8FtxPrYpo62hdsC8A4Bk5H6Zyv2pw/8ML103z8yB+4d48ybsbOORal4TSC5c8KoaPPF7sd7ihuezZfWv5YrlVqnTO1uXdnUuH3d6gN3WAdUzy67uTjTeOZKQE8c0DAHl+iWhsAhgBzi8Ix/3mIpbz53C1Acbvu39ttb0yOV2z7GRJcfug0R1GaOkXi7X4KoIyRuYeBVS/rqoJbk7OR7bx90ESB9p3r+tCl1wt7JAM9nwikg6lSr95INl/Su/Urbs92o5iiskciakmcsgrx4NVyaVB9kVy++bQS02t0vsXg3VzXuK6yYA8KTKvq0pejVfClYXcr1lXay9abLru+u06rURAMcY0VfWNS7cP3eeMldT6/40+A7qrq0vavtgd0CpkP5FKc+p4pl9/8w+fPdD/VQPKOR5930mfFWihdZCS4Pw8J0i6gtX+x+Phu0rQqLPWso4TVn1pnmlSuvqYBnGUtkwUeKs0C4EkxzYtag7bTLHWiSW52z5c12FMczOu0dMA5Qww1mecfFPlycVQz6zqkVCSFPoj1CupEFr6uh16WvsPHBO7/Rn989IjY4mt2wwp86dko6YdN17GEWWT6XmU8SdeFS+rhAlgSFV5956tV7XepVbVQyaRehQzaypSi0dalEPjUmmd3Xzk2njEyvPXqO58nZpPRuBR01+O4qEGGtqixXNS+E1rZKGHYZCYpvBK3FvdUmd7A0af7HSj8WaJO8+ebD25pBttMwL2joHJOprflzJlu474epb5Sx1g/JU0877Sm//rgZRwecmxeExblQnRJp2FyMsq/mCx0ri7b3dWa7IZsNmjf97iPbEc0ekkLbxaAvv7F4tPHNVap6vMZ15Qa0xAHC8Le+bwamQceIO4/ZubaHHDZDXwY80kNOnKHv27XfgqpuKxrSwesPtY+Bcctj8O+uKlVsNHVJ8YRIYg+85lXRQcB6Ba8na1vDUq5l8R239ZtvRgQg41CguVXv9IG6VHUiVUtKc1jpPUp8IqBjCHjeaUsdbRsfX/Pmf4fqBTWBcFUYiiYMJLSRNew5LbL7wqNnZ5uartm6HPEoL1CXPFI1tirBhSDqSK8Phsh2Lru+eyylqo4j1tlgnETAKaQ6EaAuZawnoRVKdjksXlETdC/s+p+uvdUs3VDdtt8/4sj/RoTbNpjnlm1L/rP9lnx+c4YnTbhWBSfd/++JT4/I1mCUhX6gXH7+/OZMT1VwigddECB4h6iMtxK1l4Ls6lzU/bq1ubXsc3O+YJvrmle2rlxZ2bpvO3fzbywdR4avBOTYuG7SINflQF2aAY1x6LsD0IHfDRwDgDpwXvy3+Idt2gzudOPK7rtoH9PsxsfWQUEDwBhDo8QqJXHscQdpQQXtAuok0nZEUTMxNmh7T/fChVMdkcveb7Hj/jTyaaddbmpmHpFMV6fTzIlJHuE4AKeCcLqqIzjBOlH7603Z15evfeOBPlKbyYdBxhUFcP/CEqJUQkJmdPuC3v2ZAnzZnxQv9kHnANQSqX0Bga7SKMjnEl2FpT/5j/7dWfxioXkf7KjhVPURBnQG4moHdCSRTFOliBmPaxh98Rc/jmkg90rO824oHpVImC8jkv/9ix9/8eVtX2zbAabTmKadcvJZDP3TUjH78cV3jHcpVpWjTAm40CSO6B1RGJyrJGdbG05QIIy02JILs2sizbWKFNapJpqVgvVjW7pa9helXJlDG9XTL/to6XhP2HnJj4lDiN6qvraFnXLbbfVQ1OaWW3DXzW2cPEPa4RAj3haRlDF1+RApsovajLPFHdFRHDjv/rnwy5LTGsFxmE8fiDpEtA3gjbYUdRSCvu6lTd/td9KMkPY4iNinnfaUN+3k6alclEwkkRjPvh7OoBOI2JVJmeTILpV0VSHf+URr9uV1LRtX5MjLZSI7AJCu9hyJsaJSYF+7kkHUteGpfywcCIkYl9+cP4vgfYAIpzDB0dt1g/RpITylEa0WDZqDXFBoRkthZdMcF8oXT77bCVdVVznSjdlgPbwQhHcs+a89rzc+tKjn/0npGhaapxT87f0/rN647WLfDjDdCVfclD+cYL5Klr9x73/6y0b1CTkELu5eQoljxh9FNngvk32XkJ4o1jrWmt4IpU2FqPBGJL0tlqMWDXSDGm0rhNLSsqhh04GwqPflFM2/oTTHGL4KKke5wOgtqrRtBsChGMfBuKFBRvbtwsO3iI0ciDQfrNw2yJs5CKauZMOAzhpSHMcZlxN2W+o8CTmyjE6wdpEYV4GxOwhsL1DoXRw8khuJLeB2sh3cYqfD2gQSiSTEr016eqTCO5UgJwA8lUhroqjYnA96V/QWN65tya1sDQpdgihOc7UDIGmFYUKrUReFUXcqke5ev+zT+52ycGdryW3BOZE4lonPIjZnOTIZJSqSaqsAzyh0mQpWUynoKnn5QvDmS6WRiEXduj+NfMVNn/symDcFxd7v7UhZ3CFgOvSurqr6SwJK9/4k+eW9VXP35QN3ENyL5ja0VREVTrZcOtfCvsNKMF1i8tiw1yJsC7W4KZTSpkiDdiXZSFZaLJtWyQdtEza5oPn9Q268L2R7xY2lE5lwpQIzXa7jwD23DAuKf4rRL2bHHKxt7rRBVnYcaS6nx8W8x7XjY1dMXPVNXf5xUYASD2yfCwTOW9a8p5qPC+6pyTpeSo/C3tZCT34ZlgWjRl8G0Ny5vzLp9GHGn1KXcNpjVWCSnPSnwOhRojjKgI5WllmRDTNhVGgrRtmWvrD9jZ7chg19pTZHmlJy1ZgotGI1skImTCi61ZOOIG06OxZ90pXd3ast6kjP+dyGtuokkglNFUodK9cHy5efvl0CiFMwpsyZXe955kyAzlLS4wk0A25sKitc7CWpPtcn4cpH/rPW0TCOyBgv+nC2PpNI/TDS6F9anlvxxI76tkPAjLflJ7htufxVwUZ//tB/7139j5EW+tvreo089/031EYpHAsOz4Tqu1TDIyONapUdF1uUswg3Wg06IwQ9EUVuO9gKpk0em7a+Ur4lxX7LYe1/6Fq6tNER6R7Ux/wPF2YQ87uJeQrEuqycgUo9yuoSxNXllrvNsUu/dFk8gsCBYZx6SRqAEEikRfZMUa0WDLQoRgqFyJaoKBEnosjrLUXNzc3h8uWnO3mNyMO2C6HHMZCnrZ3JU6dO9aUmkwyN8X3rV3OC6z3oVGWdQYrjQomODVGoCqNiZG0pXxAHkB3ri6XellLY1xVRsRhTeairrKGuXEnWqnR6YjozHnf98dkt2X0VWL6ni+z9N5WuU6L3EeQViD4bWay1ku8e9Hhv3nJvef0FC9prTF3NFGvoDAa9F6BjFOJK2vx7d7b7h0ub6kciBpquuDn4MCnek49K/2vJf9W07WiMOwRMd6JD2yqT/LwKXrrvP//vbSNsl9lTeR8S7dwLq+rISUdqKjxZNTpZICeqyoxIS1UuFdAxjFtIVlDqCjXqDhHmwFQiVyTL8Ca21EGG2y15bcy5tmpvXPtIlvoY3UkYyESZ3peI12ZbW4/U1GR1tOq5jOBYyNkaEzMneXWJjC+B5zHYJKu8qigyYzxjJ4gxMyMtnRBFhVkKOz7SsMpKKRXaUl9R8+2RLTQHNrcxiPKbAsm5XGpnJogB0tURB6JOUepKGb8jU1XVubLp4AtZe/8NwWmAXg2m95JqRok3QuUpgf6eFavCsNg54PCZsVPOhiv/uHc8NH18ZGRT9vXfrx6JrXl8TU5/T1Xu7qbmB3d2/50CpouLOjZ51Dn9Qa63lKz8xaI702+M4OKqXKpMCQyGL00qmMIpasMTQw2OUZYjBTJVYGsUMUltEWRLEWneFfJSjvpCx74+YJPrMczdYOpSRZcCncbjLg5lU3KM315Tk+1e2njuQa+hlinW4Z7e/5w09m+hz2G3hfa8KpNNeVwX+p5NGy9wGqOY6pDzx1gKjhYK3Zb6MCE7UTWqU0itSORFWspFjodUgo5Io87IFjYFUa49opKLz4zz3IEozxHaXIVI46OjGPmdx2SndI8EKAx3sCN23gBr+g7DlJzZryaVPhGGzoLS2UqYQaBuBZ4mq79R1ucceHaG2eKyph/1hz2NqCNtmyE28pV//Hc3wuBcWwg/e/9Pq5p3JoOdAqZr8P73d9VRTeazjnGm1LHuSyOTyzpi03HIX8i91Gb406ryYViPZOlkJTlRIceqkcmhhmMsbK2Scy7FO9qCEApCWozr3sCGyq4wDkfqIXBcakzIK3u9BqZX1WYViW4ythdE3aLc4xvuEpWelF/dm0mGuaWNO9cCDuDJGVzzjf1b5dnxd7ddLsxM01HFsd4QELakg2Q6E9QEHFUjJgIJJoPNRFKpV9XxqjIBwDhVGgvYOlGtGrCqumJr7uUlBZEwGyHqCDVoFyl1WSkVBLaoxL0SSQcROkhKXazoJCS6k17UfTBqjTuaaxfPmJpwxMySlbxSvqvt5dcKO7IJurbOrjkmMWYGWM9lovNANF0VJQaeFOgTAjyPMNzYHnX1jkCu+Hbdvez64syER98U1duDTW8u2RXO7RIwXVDsFYkrZhvCF0j0Oz+780u/HF2kP4Afs4Oqa40874OfrE5rZmyegvqQC0eB9GjLMpNIjrDQiZZtRijyQ44SA+XHyHEFRTHbD2soTCGTq2AI64oxwJGqOY5Kl+pnBgu+ukwcj1yuc5Hh5ZQoZxxvJJBj52Vmv6TG8WhSyQMVlbyAjaNO84tkoyAyXGA1JSOeY3oXSyoMX4yBVVErEliFH1lbtMaVNvMC4yHFVAo9L52gSEJjbWQSYM+5uUms40lnUUmKalIQpUg5qdCktY4RSVKkSMFKmoC0gqqgtgqCakCrRGwNKVWBNAPrqOI0wQrfsbA718lAyTcHi47PM7ab5kRD5yjKhs5hJ2GWWLM2DFrV01YV6YJKt4C6EEmPctRjJvjdq2+7dJ+kG+7PJbvgur5JXsL7AoSni+oygj4Wkr7i7JWFDc/nd6Yxz537Wqpm+tSjjNA7ifViEpoxUIUdq1X0ZxtLbYtGEjRdSmY1xv2TK8ocRIUvPnhnXdeu5LZrwATgIvEnJ+uvYkWDjfQz992dWrM/J6Jy7xGRAF304dZMtR0zIRIzLkwVp1sNjlCWycI6xbJOYML4iGQsWGssa0pY2Bolx0gZVyQnjrnM40KJjttxEFAdYWRcBtZlAzrKNDLxfw7P1MGZoxV2xcJcdHlciNdFljvGX3ZYzO53MT9FXDHcVRZ3/7cDcCUOSG3MnwkbR6m7TKD4IGudP8TVKhqMmoybuOh0l54YM144ok13qqtDGQcsOWJe92NMy+6KUiJSV4NctaSOMFmkJGqLRMhCtFMVbYKgTTRqtbAbScNeUu6JnBbOyazHpZ6V3z13JBwQIzLJ+/MibvdzjH/0iWTkfUzmQkCmqGIjlJepjR4pRXZ1lOrLLin+prir8KxLry9MTxG/Qw2do6rNJen7/kjFhsd9TB39YSJ13AWfvvc/v7R6dwrhbgFz89a8KnMrgcaGUvzHhXfVbtqfk1G596hLIA55KU2c5SeRNDVeKkVRoo59GScs46yPScIyEZCJYnicstQJU7UYdVyWGSGk4BmfSBNi1HcluJXhwbCJPxnGUQW7IkKu4EBcv9zVB3ZQbBxeDnBMqojTYdV9xt/jwrt2oBimgzvnC4mDhsT5jh1eShxTad0ZGrJIpEoBiZYgUoJqnpT6JA46dwS1tkfVbopE28UE7aK2UyC9YUGyXOf3jqWu3NTT35NvumYovGnU5X7Q3cCBTn17m+zKxuq0uKpozKnEfDGYziRoPYBXxOpvFfy4aPCG9vVmFy8TRrMAABy/SURBVKZ+W9oFeMbRBiMW+9pwj7nSm382ed7noPa2Qsf2eeM7moxhAaYLdbvqqvw0TpkvCLCu0NX3lcWLKxlAB93q3icdHvByO3sgkW9KyYTvvMUEMu7TVSWPvzNxFIJ9HxS6T28gRzvGSPfPA3kuRyUVZzqydXqp+mEpLNlMXKlNrUtdsdY1cSqoWvZtZPrCSDW0a1Jd0ZaZIftk6IfYTRxYHpeY4bKNbGR1XW9rW+fSpTOcuWGnoVpXXtk7Hin/ZGJzqUvlJGitAq/0h6UuFcFTVCi+3tXVkVu6dBTt4w33mAXeFXM8xv9V0C9y7Z13LlkyeVh1u4YLmP1LoZGvaPjccb6PRlF9ojPq/bcRin86xJZZZbgVCbw9JOA83WP86s8TcKZAV/fneD8YBfqHsC/Xtrh695lQlzb0Tc4kvFNV+RIQ3hXbKlWeV9CibJh75OGmcf0sTiN9NPKV137uWDb4ZxCeznf23VaO8lcGYAKOvn3cpDNOJfL+t5IuKXTn/qOcm4300CvXq0igIoFRl0BMGbeTbTdd3NAzttpLvQ+kl0PpdACtCvya1D6at3ZtN7r7ljUdvlt+z8sb8tN838xlxWVw9aNUP/mzu7740u5simWN3mmWWDDL9+jzIKyTQulL995b21HONcoCTHdhB5rjx7/rNPbN3ynwRCFb+N6DD+7as1ROhyrnViRQkcCBIwHn9J1CE98Dkj4N7Np1617p2lF4UEPDikTEs44ixnwCziNgkoupVMUSUX1KCtm23t4XC7uLJ41Z1asn17atfaV7Z2FIeyKd2MGDo2cbo/8LhJf6ouK/PtQ0xqVVlnWUDZju6g0uIBXvP1FJPwvoG0HRfiuZfHDjvubSK2uklZMrEqhIoGwJzJ/fOyGVSX0ejDNEZJkqfmE0erGvr6VrZ/GKDQ3ZiRb+WWzoKgXNIVfEjPQRqP11kJc1vb3tPbuzdZbd0V00aGh4M61mwrtU6TNK9FQpW/jWnip5ewSYA31r5IaGz05Xor9jUEIVX+7rW7emEtw+klNduVZFAqMqgS0pnnZ6o4aGnnEWqXOYcR0pzVToClL9WalknwrD5o7Fi492VQW2c/Q4xUrkiuPI13mqfBkPOHheJMGi0MgTvl3b3NQ0Z1QrEsyb11FbPabmChHcBMjPst3dPxmug2dHAtkLwBy43JVXZuuN8f6SiI5XxfeCILvs/vsnVpjFR3WdVy5ekcDeS8Bpj0QmkUzmepua6p2XeJdEJA0NbdVCteeS0DXEOFGBFxS4j1WebG9vbduV1uhAF0idp4TLSfEOAK+JRP+H+cFnRmNnGvtbxp0xkT3vJgKdK9AfdLQ137+33ve9Bkw3bRdd1FpVVzPueoX+EaCLIgnv6up6qnN39oq9n/LKFSoSqEhgTyXQ0FC6HsDVqvqYKh4Mgs4Nw2GHd8/7mDFj3kXEHwJwsirWAnQ/YH/b09PTtmTJZJf9tUPwdZk848dPO55IzlClXzP/YtVIA6arfJBIjJlN5P0FXEaXRl/p6PjDsyOBRyMCmG7CHDnEzCNmn05s/lKhWYH9fhD0rFy4cETKhO7pmqi0q0igIoGdSKChoTCDlK9RoqtUpZuV747UPlIorG8djmktfuZnzj4d8K4F9Gwo2hT6C1U8ms12Ny9Z8v1+wuLRJM3YemDOBJDPX1SbTmfmE+EGUn2iGETfvv/+mJ5yRGj8RgwwB7tOV12Vm2yUbyHiU6F0lxZLi9a2jazHq/IEVCRQkcCOJeC8zNWYXNtjc/ldaXpbtr766tJJhugmqJ7rMnAscFcYRn/YsOGl9uF5qhv56qv/+h0Mcx0TnauqbUS4X4r6AB5YuKEJo19YzWm9NTXVRxlKfFQhx4Ho9vb25gf2dgu+rZRHGjDj67tJq0oefg4zfZygHRrJj7Nh4YXFi0ewWl7lialIoCKB7SRw7VX5MwH+qECXWehDnZ1PtA5nK+psfhPr3vUOYv4TMJ2uosuhuDtC+NxwzWsNuMdgwYJZlKDrVPUcFv5xbzF732jGasdVHv2p45O+uYLBV6viBY3kO033f2ntaGi3owKYQ9rmggW5KSnybmSmuRb62wj6U6+rt7lp6YgwJFcel4oE3vYScCDUPnciLV16ruOV3O22suHy/DTyzE3EuByg50Sjn5Rs7sX775/oSEF2297ZGCfUTXkfE/4ERDMh+htRaaJi+HLTQ1/vHi4INVxeOAJh0FdOm3ImMzYHTDi6BpnkGQS6AYSMAj9p72xePNJa5Zb9Gk3AjO8TB7rXnnGKx/7NRDpDrP4iCuWBzsLGTaM5sHKEXzm3IoEDVQJXX1482iMZn0e0euHCOCtlt6DnuB8ariy8j8G3xFkzIk0l6H1vvrliw/C22IArC5EwtRcawo0AOQ7QRwh0j3R1r2laOuKVMYctfvcC6Zt3flVVIn2CMd6HSDFbIL8IEd5x7717XzVydx0ZdcAc6oB7c00cM3UeQz8YV/uztsmK/Lo9395dAc7dTVPZf4/ZhoarlZR99UqDvZDAQF3x4dYTunZB4YMg+mh/4PiisKT3mEUL1w/XJrhgQd+kFPkfIeCPiLAigvyI+grPND38rf6wv+E5Y1zoUZoSf8SGG0TEEUn9PCzYn/38oarWYYL3XsjqraZDQJnxq4/0GVcJdC6BnxEN/h2/WLRyuDLZ287sM8Ac2qY3XNwzlpKJ+Qy6CkR9Imhiiv5g2zu7mpYdfsCWAd1bQe+79o28YMGtE9NKR0g291LF/LHvJD+cOzXMy04k3zteRdc0PfAv/d7bXQNXw9y2aq6ru54UNyvJ05HQ93n16pebVg434LuRr1nwN6507adIcYSq/kyAe7F6zbrhXwP4wBX5wwFzvRJOk8h+FQ88sHxfgNQQUFYnqqczsABEc1X1TYb8eNX6FY8PV2MeztwM55x9DZhDfaIrL8pO9BPeFUx8pSp6nVctX4yWaqqnezixYMMZ3KF4zoILc1PTKe+j/fJ8h1X5q6aF6dfKkAM1nPVmyp3ftGz3hAllXPdteGojz517Q2JiW17KAZ5r5+feSeR/QaHPINTb7178pf752b2217CgeKEB/y0gfRD9VmfQ8/hwveBO+Fee3zs+UZX4EBFdr4o31OqPglzhifuWfrN3OPcfmsDLLusem3ltQ66cMe/J5Mc2yrEzM5yqPgpkrwDRe0H0hkLvyAZvPjacsKc9ue/u2uwvwNwMnNed31cvGe9qVrpYCUUSWhSF9jelXN+mXn/3yfq7G+Ch9HenjZiauisJ+Lio/cHGvsf/azge0iEZNVzcM46TqfNVtFigzkfKj6FtdGXC+49GZ2cbjq1tf09PbLrIZmuoXE3FAVAylXiPAPm2XMtvh2tWcjb9+pp3X8GgWwFZFiq+xw/cv3Y42lrDvNJs9uFSkQ9TxY9KpdJD9y75Wj+Z9+4Bd0jQDrCZvL9QpWNcqqAl3Nfeu+z1ctbJaE6a83p73qSaNHnHQulSQ+Zsha4T0bva+loeHa6cR6uP+xswt9I4EwnvEla+XKGZfn/RUiV+tE/zr4m05/fXG2W0BD/S13Vv5GPq57xXDf0dqT4evbb282VqAXTdpcWL1eDPSPBYR9j9/TJzbqnhgsLhnOQqyfW8Wa4pwAFJInF80phsVM5cN8xekSiNrU+Gtd1BOe2c/OOYRZ56AjNYNnW+WI5J6MqLsvXJZOJTUD1eVG/TBxf+ZjigNzTvH7iseBkx/406/kel78qDv3h1OO3dlt5j71PKfCkUPw9U7zQP3v/GcNpufjFe0DmGUulrmM2NEF2jii/e/eAXXykHeEd2/TZyw1kfSdracXUJz7wTRFeAdDqIV1mxd/TZ9U+WO7cj27+3rnagAObmHrkA1AmJunMguEqBacT8KiJZJNa+kM/ns8nf/SpfzuIYLcEdWNdt5IZLb53js//X6op2BdFnfvrLnZcK3VHfGy7oHOMl058G+Kj+0rDf+OmiqqfKGeOC97TXVI2t/TgpTQbJ9+58ILWqnPbXXVQ6Tjw5W1Vfumdx5vfD1VCvvST3TrB5r0KfumdR+jfl3NMRM4yh6luIMVNtdNtPF1c9U077hktLJxrCZwAtWYt/bfqfVD/oDP+47tLihSD8A4jWRBJ+vT3/5EvD0fScA3VK1eRric2fiMoLVqJ/69OWl8oFlQ9cmjtdybwjBB7++YMpZ7rZp7sC97LLz5hWlbGpevb43QS9AKCpRPqryIb3t+effHE48hi+xPf+zAMOMIeG5DSmo+tPOoGh80B6jrNzgrBMonCJkDT3cVtuZywpey+Wg+oKsWbn+/xJkJ5mrb317oeqni5zBHTdvMK5IP5Thf6uNd9ye7lbn4aLi7N8E4PHpny++LX7lo7tj9kb/vGBSwrnk+GPQuWRuxalfzTch/cDFxfeC8MfA/Rxu+j+75f7MnWgpaCPAPpYj775wzJBh66/rHiRKP6CiJ6MOtu+Uo6W6qRz3SWFs/tLcf4TEW2MNPyXckDimksL7zNEn1NXdw74Zrfmfr948XhHfLNPgW/4sww4J07PRe9LjbfV1TblnejBmeL0nVDqFOjDYWTv/flDX9m4/7TdXY/mgAXMt7rdyFdd/NeTkoYvIeULAJ0E4udF9DFAnumhfGdbW1zzODqQF0o5i6qcc98/t6sunUpfC6abGPKtOxal7yynvTvXaVpjUf0pBWaRjb5155Kq5eVe47p5hfMI/BGBPPLTxel/35P2YL5ZRR796eL0j4c7l9efX5ypSdwC1Z5Igm82PVQeKayzRaaS/mcIPEUtvnrXQ8kV5fR9/mnNmZr6cTcDuLS/ulBj+FD53uPrL86foYb/CaAukejrq9tfena4NlWnmcPD3xN0hoC+m+/pXXj/7w4strA4A+issxJRZkwm4ZnpZMwZrv54XN+dsIYEC4tB8Pt7H6l1hL4HLNi7dXEQAOZbyzfWOscdfzJ53qUEPVMVEUC/B+S3UaCvlUq53kPJUeRscHVy+LnM/FkXWByuW/0vZdotY+E6LYeI/0JVl0c97d8uV0ty6+i6S4ofA+hsK/KDe5aUtzWO+zCvcB6UXehMWYAZm3DM2E8DdBgi+eqdvyzPFOD6fv3FpQVg3Cgii1ZtWvGT4YLV0Mq86uLclLTx/sqqVnOEr9/5y1R/udbyHvzrLwpOUyOfh6JkSb6WxYanhqvtXje3dwLSyT9X1awtRnc1La12MZL7+RiwS/rjalIamakgcxIRz1VgBhHyUDysEv6qm1tXD3ec+3lA8e0PKsDcQmDUcEFnrU+Z94AxD4TZUGoH8IyofSwgfc2Uclm0tQd7AiAHwsTsvg+N/IF5f30yi/kHgHpCFG8tV7ty93AvoeMmnnirKE4E2dvu+p/Mst3fe+sznHfd08StzFStgX7tzkfTb5R7jesuKpxHzDdLmYAZg+3FhZtAfB5EfnzXkvSj5d77AxfmprIxtwKogsWegC4aLuw7xTf+dx2xrpSC/7hrafmlqK+7ODuHyP88gZIC+dKr7SueGC54u3l0496fO62BNM53+lOjsWmkUxPUyOlE/D6Aj4FKRESPW5GHO7Xn6TIdiuVO6aidf7AC5maBxKQBiTMP94HzQHw2VI9gUJslfQKiz5SK8qpJlvJobik0rWzq37YPPwRj1KQ+Ahd2ThqfM9cy43IbRv9w1yPVz+/JZT84N3+YpsyXVPBSLtf7rT3Zzl13ft9J5HufUGB1h3R/d08ehs2A6bbkS4a/JXdj/sCFhfOZ+QaF/Oquh+K2ZR/XXVy6mqDXQfXeO5d8+a49WCd0/cXFW0D4Iyh9NextW7IHmjquPb94jPHob6Hyu3xQ/Fm5tuCyB76XDdzzV5M9NlFdU52JTLI+YeyJynyGIwlWRgiLl4SwhErBE3ctHXZq5172avSaH/SAuaVonNfNn3bUdKieRcTnEulkJSpB8LTzolrB6gBBh5fvyWPZsqBcB8HoTUP5V45fFPyuSb7hzB5sQ+MbOq3k2LoTziGPblaV79+5B1vpWMO7qDifla4B2QfuWJK5u/zRuGsUzjPgmxX06B1LEsO2Ybp7fejc4rHi49OstL6ns+NrC5eXz8F6/XmF6WzoVjWsVqKv/HRJ5s1yxzHvXR214+tqvqSQaVFk/1keefDpPVljzi5ts4Vg4fKpLvPtALPpNXLD7Aavr2ZyKp1IVSXSdIRHdKIIvxusR7oS8oC8qIJfhmH0NJYuat8TGZQr+311/tsKMLcUWpwpUDXnMD/Jrlj82fG2XVAEYb1CnxCV52ykLYlCKd/Z0VlavPqOcA+0in01T6NyH+fwqOLEhwSUot6+793xxPj+rI/yDhficpg/5c+VaI4i+u6eOIwGQHcQMEUevePh8jRMN460538KQrUh6TeblpSV3RQP2G0n/QvnX89EV4jQnXc+/MX79mQ9xODt0f8h6KNaKN59528P/oqqQ1pkKlGV4nRyrGdwVH+Z7Xcz+GQF6kGaVaVlavX3sMEzdy39137nzdtjJ7ft0/C2BcxtBkoN781OSCb9MxR6JpTmEGM8QK+p4mWovhgBr0oQdpWkWEx2tZWwcoV9O70ZdwSDsROtZs40A43uWJpZXx5UDpzdMLdvctLz/gaKIIfgK/c+Ul6d56F7fvDCwvkgvhkij5QLmO6BnmbO+lPH4yhib7/rkfLtsK4fbjvsET5FrO19QfEbe7odbphbnAUb9uCxxZ0H4Rqi0057ypuKqX5NOpMME4mMAaZ7hmYr6ESneJBSjavJA9KnI8hvOtH74p6YYfZkve3vNocKYG4pZ/rwSa2ZoK7qiITvvVtB71TgMHIGf9B6In1aBC+L0GteEHSKDYpBtrV4KADonizGhvdmJyZ8c7YSdYcta3+3p062688rvI+JPqzQX9/xSPqOcreiHzy/eDkTLlPggf9+OPXgnoxl3qxVyfFHTJ0jIC/b0/3inmzt9+S++7eNy4k/h50d0mmQxverKEGO6OIYcrsGxckgpEjRo4qXlOgxiDz7Ss+K5uE6pPbv+Eb27ociYG4lwThG7L3zxiV9c/RgWY13EetUUQ1JuROKF0X1BaLozSigditRsRjkitmaV4IKfdrILUZnt6smM6mk3LMnYTENZ/WM85KpeveS+6/f17SNXM/ebldq5HmzPuiPGz8uGSQSSU74Y30X2ww6XgmnEjCTgEy8/kEvAfp7iH2xpPl+HszdV5Z8u0nrUN2SlzGPjXzd3E+PI/Zns9DxIJwE6Gxi8lTRSsB696YFyYsC2lDoC/syFIYb0r0B8Hp0oKVylTHwyqlvMwnEysDsOSbljfdtbSoh6qeN0fFk/GMIcpISH03QyQoaR6StRHghEn1eInnR786++l/PT3aldyvHFhI45DXM3a8GF4D7V3Vp35subM4gwhwA06CoJxc2IVgjoNUM+7oSXkdALdCo6Lbyb4Hor+XtagTfvfwqZ+wDCVAD7uG+Wad6EzI1XrEqnUx6XlJJJ5DxjgBhBgFHQXEMMU0VkTxALQSsUZJnofx0SXs3VDTI3c9UBTB3L6PttPKGuW1VSdROZuBIKE5V6AkgqodqAiABk9sSvqJiV4nSBgNuj0phZ8Q2LHEQbuFU6gfSAy1spHyBVFrsMwn0P6+N/U6Zy81mpwwZj61fa4yMN6yTlMxMJhyrwNGO9YtBkSpKSvoaKT2jIs+TpfXFrrWte2pv3mejPQBvVAHMkZkUciDqhenpvu/PgOAoddt491YnzhC0T4E+ENoEshowq00UvWk901NC1BciLPoII5RKdm2wMVq+/IH+gldvz7CMkRH32/4qW2uMfsJLG89T36+CH9US/MmqOkOZjiaNbY51AFUrkADUvaxfUsHLzG73g9dLbeWxq7/tpbsXA6wA5l4IbzdNY/ZynybUG0PHAXD20OlM5Bb7FAVqCegG0QaotoKkRSxaiKg5isKNyqbXsoS+2ijsDML2fC5Ke5FWr34masLK/mDmCqCO3tSN+pVjQFx72kyu7xnDbhstad8Y9f1Chv2UmDRE68mYqQKdTKrTiHiKQqYSeKrrnapsYuYWq9pM0FUKvFzK21XIvdFZ0RxHb/4qgDl6st3hlV02Urr68JqIdJznJ6eDcBwIs0hpqpJWAUgDlIFqiaDN6kKdgGYl3ahKHVDptiF3KqLeKKHiALVPwygpxaivvSgOUN2Nm3BNZbu/j+d28HbxtrkBs6kdEwlHHulNzFR5YcL30sZ48NgombTn2TFszDgRHcfMk9xLlIinkephCppABIFKHkQ5VeoBxPFVrlKLV2GwwUqpO/ztkt6DMM5z/8zKCN21ApgjJMi9v0wjX3/2X45BSBM8408AYzIROxvpkQCOAHQiiKCqEQGRggKQ9jJRq7XaSgYtsNIGpW5hyUto85L0i35kSxSpjRIiYUEkFQbRm70FOzGTl8HY0gqwDm/yYiCci3N44ux6LqbHeqmCx4kawwF7nhcQa8okfMNJRFGVgNOGzRglmUDKk5R0kgFPFdJ6Uk0ryCMiD47wGVIg4mZVfQOK14XsG2rRxh5vKm7KtjetrITzDG+KRv+sCmCOvoxH5A4uqHrixGkTAK0Hm8msjheUJgpQT7HDSSaDeDxB0wNaifYRoaCKnPuZVHsUuslxLhJJh424iyBdIaJeIr8g5Lb/EkUlFae5VhVEwqRIkLWS8kSLVaG0t0TqzAJtY3ocyGLm8rXx56A2OzTOAyz3eYCRy22B3afbBrtPtxV2n9UTU1wMDNWFTD01hpNFw36a2QuY1SOjJTYRk5f0OSEI00reWCKqI9ZxEBoP1fFMNF5AtURaC0UGRFVQrQbgKeKXWhtA7aLayopWIW0TpXaVqDXwtPUgzQgakXV9sF2kApgH24xt3984lW1m4YhkujqVVPi15OlkFUwh5slELigZ9VBUE1FGgTSRZhScJtG0MjyAsoC6PPI+qPukrCr6iDSvSs5ZlYPVIhktqGpJ1RSN0RJUi5HVwBgpaeiHkaclTzWSQGMgtd7Apzuiwd+l/bd+VzCOKxzwBz+3GloPgDEDvwktbV6n6S2+F0IaKLpWDTgNz3010cAnJ4iVybCSLxImDFNSlBPClGSiJCxSRJIkUEaZ0rFcRKuFUEWgaqhWETsQRA1Ua0Tj7wkoQrhifYo8oEWA8kqUB2kPiTYL0AKhVmXbGga00XphziU6NKM5PBQzYw7+x2vrEVQA8+02ozsfDzXMXuH7ZlqV1PppT0yGJcowOKOe1qvlscw0XkjrWMl5XesU6iCrhpymRErkbALuUCVXFYHBEIj77QBwKRNIlJQF0EDIZUtRAMD9C4kpUnHmBOmPAoDjR7RxVJWqVbAzNexYO2X4UDWOvlUVBlBPAWPAToNz3x0X5MA/0gQRJ0hhRMWA2HXa2QPjHg90X9xg1P2sIgOg7myGREUIskTU7RjcBdrFiEsndClJJyl1wUougi147OcLCAt97W25xauPduM70DTrQ2dl78ORVgBzHwr7YL2Vc1RVJaZm4PspGJMKlTMeojQzJUGUsiJJo15C2SbczyRIClGSFEkHYENgJrEySb4aGBXxCOw5sFUoAeyrCg+ApgM2AZjRX/bB/VUJFKqq+xRlRCSISGHVqEseCIk4sLBD30ux9seubLMGIhoYNkWnHYtoiT0pQKUI9YuwthhyKb/hiefzS3Fu7DCrHBUJ7EwCFcCsrI39LQG3Bl2Y1GBN8x11Z3Od88Fz93eXK/c/VCVQAcxDdeYr465IoCKBsiVQAcyyRVZpUJFARQKHqgQqgHmoznxl3BUJVCRQtgQqgFm2yCoNKhKoSOBQlUAFMA/Vma+MuyKBigTKlkAFMMsWWaVBRQIVCRyqEvj/hQ3qJJfeffgAAAAASUVORK5CYII=",Poe=O(37426),Boe=O(19150),Moe=O(55303),Soe=O(92691),Doe=O(99755),Toe=O(46016),Ioe="data:image/png;base64,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",Noe=O.p+"static/nltpbg.f01aad4b.png",Foe=O.p+"static/nltpbg2.303fcb0b.png",cS={title:"title___m9Fww",bg:"bg___f9tLu"},Roe="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAnMAAAJzCAYAAABksJUOAAAAAXNSR0IArs4c6QAAAERlWElmTU0AKgAAAAgAAYdpAAQAAAABAAAAGgAAAAAAA6ABAAMAAAABAAEAAKACAAQAAAABAAACc6ADAAQAAAABAAACcwAAAACCpLptAABAAElEQVR4Aey9abAtR3UumLWnM10NVwIkIRAgkIQEZhAzGISfgfcEZuaAhMFBvI6GX+1o0w9LQryI4zCSGBx0B/0L/eggHma8ZjRYz8bGYGMGM5lRgBgMPEACS1fSvWfcQ/X3rcpVO3edfe6Z9q5h18ob92RWDrsyv1y51leZWVmRM2cIGAKGQKEIxNHyO9x8b8MtDgZuMY7dYruV+AxHkVvoD1yz0XStuO9akXMN/GvFzrVc7Jouwn+m++sYaSjTlDTE898gdj2kD5C3j3v0GvCR3pfryPXwmz383iBCWuzToqbr4V+fPuqxjt9c4/9uL/EbDbfWmndrx17vNpyLUNycIWAIGALFIAAdZs4QMAQMgckisLISN74y586Yd+5oPHBn9iO31AYpA2MiOVsCaVrwRG0J/rwQL7AtOtAiFBE/ArECN3MOfpTG+zDzMh7lY6RFIHji0nyIy6M8SSHuuTEAuRPCF7vVAUhfEwSw14ffdKtRw90Nxnf8CZvunpUVtN6cIWAIGAITRMDI3ATBtJ8yBGqDQIzZtLe607uxOzrouqOtpjsTDOwopqeONlruzKjvTgehaRIPkq2QkJGAaTx9EKCUqPEaM16cQxOixutZKt8A8QPpOwEAjmOW8Xi/4Y5jfvDuRtsdB9k9fuwad6+gwYabMwQMAUNgjwgYmdsjUJbNEKgdAphdW+64szGbdg7o19kgH0ehMI6CjJwJlnYGlzk5Cya4eALGsE47aZT6TNMwfZ1tY3yagGCty2OJt+/cPQDh7hYI36AJshe7O7G2fMexLXens1k9ERf7YwgYAqMIGJkbxcOuDIFaIrC8Eh/pNt052Ft2brPlzgHZOgczYvfDdYvEKyRbvBxHuDQ+zM984TXz0Fn5BAdik2IUhn1CmsZr7PvDLOZvEHdHv+fuwL6/29t9kLyV6GTya/bXEDAE6oqAkbm69ry1u5YIPHMlbp3VdvfFHq5z8VLBuQDhHBCEc0HcFrEEKPvOQOBihrFMGoMwRHhhAGuhoBKIE47BeOaFE7KBSC1D5qZhK58PfuiUVXTFr9GHv8FbILdjufv2u7rut59diXrsI3OGgCEw+wgYmZv9PrYW1hSB5eW46R7tzt1y7kFYFn0g1kM543Y2lvGSbWkBKSNEJF9K2BQyIWQhcWM+/M+SOua38uXBD4qdHPxOLGXfDpL3vzrO/cx9091+7Bh2M5ozBAyBmUPAyNzMdak1qK4IvGYlnj/RdA9E+x+EvVYPxH62B8Cgt9NZNs62ka6BicnMGsibzLqRmdEhs7A85iPRS6Ikr5I6K19d/CAPPdT+F+jYn0dd94sznPv5u1civGRrzhAwBKqOgJG5qveg1b+2CLzypvjoeuQuAOm6AGb6QSBp9+1zFi0kZQF5U4JGwJBlSNIYwXIkdwxb+SGpnWX82NVcmm25n+Gti18sNtzP3ndddJwiYM4QMASqhYCRuWr1l9W2rgis4M3SljsPJ99egNm0C7CX7QIM3tM4s8bZtHEkTOI1XTL4vAyjjMy8aTpx9WESO9n3xt/VdJaB09+08rOJH/bcnUBX/wLHpfwMb778/FjP/dreoE1k3/4aAmVGwMhcmXvH6lZrBPiG6WDOXYQXFS4CEA8Ft1ogIEqwsBcKp735lxIQL+SMGeA0rL7G0bfyCSk1/PYkP+sgdz/GcTS3zW262+zNWY4gc4ZA+RAwMle+PrEa1RQBfjXhWy3Z63YRzna7GIfvnoN9TskXDvhWKXDhuW566C6JGh1JCQ/eDX2E5c1U5tF4K2/4HUZ+IHcxzhq8Hcuyt8G/7VE994uVFfuahQxC+2MIFIyAkbmCO8BuX28ErlyJT19ou4dhafMi0K8LgcYCSVdI1IgQyRp9JWbqaxx9Ouaz8oZfHvKDJdlN7NH8CQTzh+td96NbVqJ7Eym0v4aAIZA3Akbm8kbc7ldrBHhcSPdy90Cc7n/xoO8exuNCsrNqWYA0XeJppcHWwjgNq2/lRxEYwcXwm5r8YB8nDzT+Id6Wva39dfcLOwZlVA7tyhCYJgJG5qaJrv22IQAElj+E895+6h6Gj64/AgbvUpC4TrqpDenjyAZfNOBSKZe29MUE7nVL83pSQoDTOF74eCtv+BUpP5y1w6vRP+i23XfmHuJ+dOzldr4dh6c5Q2BaCBiZmxay9ru1RoAzcINHuQtBxh7ZaLqH4+iHeQUkfSNUIwJ/XFo2LnsdFB++bRpEZvNnr4OsVh5kmKQ5dFm8stenysu0bP7s9ayXbzbdBh5gvo/9et9pfMv9xGbswh63sCEwGQSMzE0GR/sVQ8DxBYZ/a7qHtNrukfh25qUw2gvjiAH3u3HWhEadzs+4SRyv1dirzzh1jLPyhl+F5WcdWwu+B3L33cf03U/tBQod2eYbAodDwMjc4fCz0nVHgOe/Nd2DtjAD1266y/CW36IsjQIXGlwsgcJ2JUuhWdLGNM2TGmfMCln5BDPFxvCbUfnBN2Vx7M6tHczYHcO5dnaeHSXdnCFwMASMzB0MNytVZwRwOMhLbsBXF0DgQLwuxZ6205S0ERYlIVhWSo4T8aSNE3EkatzjpsQuzM8wnZVPSLDhVx/5wV7PE+jvW0Hjv/OR693PIQHyEJSMCPtrCBgCuyFgZG43hCzdEPAILL8lPqPbdY+NGvjv3BkkGzqLFoazgCk5y8aHZcJwNp+VH85whtiEmIXhMA/Dhl+18AOLuwcvT3yj3XbfOHZtdE+2P+3aEDAEtiNgZG47JhZjCKQIcB/ctzvuYswYPB5G5qFISMYMN8n7PW982zQbzpKL7PW4MnJT/1vZ/NlrK78dc8MPCMyW/AxwzMmPGrH72u9suR/a/jqRcPtjCIxFwMjcWFgssu4I4FNaZ8Vt99h+hFm42B1RIym4hOQNEeR08qIDAmF4xzJWfkh+Db8RmTH5GY6lcPxgdvVkM3LfiLqYrVuJ7pJxaH8MAUMgRcDIXAqFBeqOAM+D692GPXCRexz2tT0YxoTjg3t3dhon2bTsNSEdF8d4umxa9npcHino/2TzZ6+t/HaMDb8hAll5yV6XT34a8tLQv2PkfK11kbvVzq8bdqaF6o3ATkaq3qhY62uFwPKN8X0HsbscT/+PBm1b9I1XwzbOZxYdO0ynyxK/ceU0j+anb+WJguGnshHKVRgXypPiRb++8hO5NcyafxMHcX/92Buj3xIMc4ZAXRFQxVHX9lu7a4qAzML9BAf69t3jYA0vCGAIjSOj42QdzJM1WQcbIW5qZPUnrHyChOoWwy+UmTC8ncAm8mb4EYF9yQ8y/3zQxGzdhTjmxL42kUiQ/a0VAjpgatVoa2x9EVj+k3ihd7Ysoz4JJG24F4772BKnY0JJiN8Ip8kpkRvGJwZaM1j5BAnDT+VC/aF8JYRf49UfpjNk+Cku6g/xORV+J/HxvC+fseG++u6VaCMpYn8NgdlHQA3P7LfUWlhrBF60Ep8ZzbknQ+Afi71w8m1UvrRAO+Fn3kbxUQOivuaj719gsPKGn8kPxkM4Rjg+6DROfY2jn8/42Yp77hs4xPtLH1uJ7uZtzRkCs4yAkblZ7l1rm1t+c3x+v+GegtN7L8OZcHIuHI/5SKFRYwMfe+ZiPQIkzRPEs4wc+mvlDT8VIJOflJyVcfzwMG9M432vOXBfPPam6JfabeYbArOGwFApz1rLrD21RmD5z+NLes49FR+5fyCBgEaPOFsAkjb8hBbIncwSIF2Uvs+jMwf0GW/lDT+Tn+qPHzyI/bzVd1849t+jH3BMmzMEZgkBI3Oz1Js1b8szV+LWfefco3sD92S84XY2V3Nkhs3Pnuismvokamkej53G6YSLlU+MOImt4qa+YpXOYhJvj6nhl0xYmfyUUH6c+49Ww33pt5vum59difDMZ84QqD4CRuaq34e1b8HzV+LFVsc9oencE3DEyBIJhcykeGT0WnzMxsHAprNzzMK8JCgkIAxrfl9cCEoab+UNP5OfmRg/eOBb7Tv3ld6W+8pfr0RrOt7NNwSqiICRuSr2mtVZEFh+R7zgNt1T+gP3JBCwts6yKTHjNZ3MEuGigQDjeE0XhvWaMylWPiG2hp+IickPx8oMjx88qHWbDfdlN4d9da+P1pNet7+GQLUQMDJXrf6y2gKBK98Zzx056Z4MJfxkEK85gqLGZieAQuKGcjHI34jsW/mE7Bp+4xEw+Rk+BM3q+MHnwjahF7508oj70i1/HG2OlwSLNQTKicCIQStnFa1WhkCCAL6X2um13BOjhnsqBHdeDaz6ihOvuZRKwpY1POG1llPfyicIGH4mP3UeP1h63cDb719o9dy/4juwW6oXzDcEyoyAkbky947VTRB47bvi9vE73ePxWunTBpFb4FIoE0jM6OssW/aaaXQhgeMSqpU3/FQu6Jv8jJcHYkNX1/EDJbOG//9y9Gz31ZtfF3UTNOyvIVBOBIzMlbNfrFZAgJ/c6v7QPQ77WX4XBmWJoGRn23Cdvuyg4ZDUqSEaF+d/z8p7cmz4JbI0TlbGxZn8yHisw/hZxb7cz7cvdl+zT4VR6s2VEQEjc2XslZrXaWUlbnx3zj0Ws3C/ixPcT+eLCzCm6VumJB3c40YnLzVkwmF+3Qtn5Q0/JasmPzZ+DqI/8CbMPY3Yff4Rm+4bKytYiDVnCJQIASNzJeqM2lcljqPlG92jsWfl6SBkZyoRU8VLfJS80adjGoyz7I0L48J8Vj7Bin9DXHht+Jn82PjZt/64G8cg/fOxN7pvQvnIVg+OJXOGQJEIGJkrEn27d4rAVTfFD96K3X/GLrj7hYSDZEN4G/5IeIyvP6KkzcpnsCJAY3BTPA2/BAGTnwQHGz97HD+x+00ncn/7geuif9cxZL4hUBQCRuaKQt7uKwg876b4KA6Ieza4xiXYhh1jGUM+uyVEAzm4liHGBS87MA1Lr3ztIWIcE/VafszKG34mPzZ+9MElJ/2Bg8p/2G24T3/quui46CH7YwgUgICRuQJAt1vi5QYcMxK33dOhCJ+Ek9ibycmsCXkbIXWkbp68KcGTWSaSOyyvhnFC7ghuSOqsfKXww9vGopOweNXg8h/JPP40oqYsheFUGjg11sO8QmDY/33ICvLKG8u6fEj5YcHk2224YrgP+dHf4T1QZoAPO8n9GnhGGJLCgUQinWXwmyzPpTVmTWaLGcBvMUYiTf6GDxV1GX+Rg3S4L+Od13+240w4IMzljYCRubwRr/v9sC/uRdgXB8H7Pew7OSIzawEm6cwcyRriaRzTGblThPUnrLyf2SwRfiRjJDskaPAa6HO+zBJpvH85hdSMO5CEmPHtUSonsibG8UgZ9vFOYabR5V4eIip1Rf3wYJJ8Eo51jV0fdYn7EUQYQowE4Xk7yXJS+0TWiZX+lsl/tcY/ZHoND5mfsf10KtHm54WAkbm8kLb7uOW3xBdgduM5MObnjjNqSt4IlaaPxNHcw0DuZOBG8oIAkCiOxFn5qeHHGTWcoB9hZgy2LCFtJGfAX8gb+5QEjv23E0FT8iZ5PYEbiatyebRbZvVA8oBR8q+BiUTG4/82WTX5rfr4vR2zvX937Nro55Rnc4bAtBEwMjdthO33SeLOAAP7fZCwy7JwKNnK+ppP4oW9acyony2n15rLymOWZ1L4gWBwjg3kIyFsXB4HWSNpU9KlvuIv16e4v+bP+nUrL/SOE9Eke5yYS2b0BgA6OYaHgjzGqbxnfc1q8j9B+VdQAz+Lu15rFlx/D080/wBSd4/GmW8ITAMB6lBzhsBUEOCXG357p3sqFNpTIGgt3kTteuiHN1dlqL6m8ZouLJfNw3SNU59xdFY+wWGv+IGlNTBrxOVR7hBr8pr/ZFYNPxX6yS8nf09FypgjLKd5rfwQAcVEfTwEYcXVkdT1IfwDLtsiLeXn7M/Qqdyrr2km/wkSe5X/SeKH/urh976IL0l8wb4koRJp/qQRoM4wZwhMHIEX/3l8KQzQs7HOeboqRi4ncTmOPpfcqFjDMPPJ3igkaD76Vj4hsdPCr9HEDNvANdFfTcEde9zQbyRxnItLZ930mj77j8QsDAsB4UKqdGyypGrlJ48fBs4A+GPHAvyB68XoPXyhYGDjp+T6Y+DuBTP/9Ef/e3Qrh445Q2CSCBiZmySa9lvuBW+NT+sM3H+B0rokJWEwPJjlkS84gAHIZnZeEy4lc9w7BPrADVXplx6svCdxk8QvmaQkUWuRvLE/ZMbN44940DT8ZT+gf4Sw+WvGa/9JPnagEjsrL/IruBSAH2ft+JIFpuwG6Kce+PQA06jJC7yoj44r7T8bf0AJrgj9gzv/YKvh/ucnrolOsA7mDIFJIGBkbhIo2m8IAi+5Ib4cy3HcG9cJIZFZHDX2SEyvmYmMTV02zcen+T27S6+ZbuUVPWF+I9ggBQO8gVdIOfPGuTYudcuRH0KeWdLwIwqJmzX5I7HDEh/6mCSvT7LHmBEZsf7X3h87fpiY4jVB/YN+2MB6+Wc+cn309WEFLGQIHBwBI3MHx85KegRefGN8NmYkngfS8EAxH95A6CyAZKNZUcPhw7zkDIEurUp6kM/Ke2wIYICLhsfhh2U3krUWWBxeLoWfwZw/darymsZshv/+8S8zfjLO8IIF/2Fptgf54LEqNv44k6rjS/285H/gfoF9kJ/66BujOznmzBkCB0XAyNxBkbNybmUlbnyrg5cbBu7pmPtpkjdQFyZ/4KcRCCIsu7aZHsSnYcSl0fIjo/ms/Hj8YJSjRh/YN5NlU0DnTzQz/IYCZfK3w/jhkmx/0MeybNP1m35Z1sYvlRRcqpCmLD8k1w33z4/acl9cWYE2NWcIHAABI3MHAM2KOO6Nuz/2xj0Xm3LOCZUeZoXkJQcaBDEgBIvqiYqRLojnfhXZuxMoTSu/O35gzQ3MsrSwJwr218++hSbA47kb/uOMtvSRlR+R053kd+bw46xd5LoQpT7fot1Nfmz8Tlh/Re433ab7FPbS/UrGof0xBPaBgJG5fYBlWZ3jcSN33uWuiPruiZwVGmfQSMiIFYmakjMq/pE4pIUkMAxb+VGsgE1Dl0+BaRv4JOM2IMEhftvkNMwXJobxYTjMw/BOaWF8GLbyowjshE0YH4ZHSxeFv5x5h0Hb9Xvt5HEhHdM2fqeiv4QgN92/nn2W+5wdY5IdCHZ9KgSMzJ0KHUsbQeClN8UXIuK5UDinjyT4CznWwpM2Eg4o/pTA8Smf12Ge7G+EaXUvD7zwfQDXwrksLYDYklkSmtM9Gv00vwc5vbbyyUxxVvh4HWCT4mX4CQI85w7LsV0sx/bwABfOA3uEML4x5vWhre7jdwLtvxcg/82Hr4t+kgJsAUPgFAgYmTsFOJaUIPCalXh+teOeA1LxSMUkVNzjwukTfKDgtSz9cWXC+DqWpwHAgGzjvxA4wSsgGHKtf8L4ncLMG6Zp2Wx8mCcMZ/NZ+SECIU47hWcUP8hnD7qA/7vZBzQd13Ucv+zuSbcf4/e7Rzbc3757JdoYCp+FDIHtCBiZ246JxQQI8HuqODPuBTobp8oqyLKvoJUfzl4QOE/gWiRxnIHbFcyQOOyaeUwGK7/zzNwYuLZFGX4j+Hli1xVy52fit2EWRNj4Hx3/ATQ7BoHZvZgZ/YR953VHiCwBCBiZMzEYiwDfVP3OnHsGFlSeAilJ5UQ+CJ7dL+N/IU0b+4tJZJpnjFFM02a8vHwqC8uneIGBJK7FWQw2GUpbDuU9RfOHecbgZ+UNPzx0pWN1nBylMjJh+cFDSYwjNrrQF/Awa7cDsUvH+Jj7p2njKu7j0jx1K088G+6Lj9x0/2RvvJ5CQGqcdMqBX2Ncat305ZX4rLjjXggQzsOsXIynwu1ywpccdjAcYZkwPAJqzcrLspMSuOTwXnlBZAQTf0FDyBk7XobhMC+NJ38zjNNwWCYMazp9K2/4TUt+IF7y8gSIV4/77Lj/cJur2fifYPt/HW25jx9bie7a9psWUWsExg2zWgNS98Yv3xA/ZtB2/xtowrkjWED5kphJHH1PJNK4RDlLupA/XoeupuXBthqYgZtvN9wSZk3mgWsbpi4lciRbhInkKtw8zusR+HCd5kUZNcRpnJU3/IayJG+RFyU/uG+DL+7AuCxg6vkI5R/yHKW6gvU0/SEPYikmHO++/3bRn+fFLfdfqafD/rWwITD2yd5gqR8Cy++IFwabeFPVuYul9VS2iYJJfEbqTJCPpyKSp+6d8ta1PBCDAeOLDLIPTomZEjBeM0wiRvwY1rgw77g4doPGW3nDr0ryA/3RxxNKFzN2XI7F5ydMfxxGf+IswB80Ft3fHHt9tE69YK7eCNjMXL37X1r/opviBw/W3P8O5SBETr7U4J8SmSH9cgNISPgkqYpI4kBINK225TEjgW9ozeOLDEf8LBy2xw3x8yQsnYlTQ0xSRkJHX/PrLJ1e07fygpPh52WhavKDh8MmZHwer2ofwcHXc/hqSZMPiKY/gILigL7dq/6Mmu5i6m3qbxQzV3MEbGauxgKw/CEc+/tjdwVI3JNSGDL0XomcEDdmwhM1j7tg/Eic/kDNysuSSD+ZhaOxkqNAFAvCRbzgRrAy/Ex+bPwkY4KzdQPM1PHLE6Q0NdMfohy8jkgUhfxN/+xVf2BZ+8vu6+5zx47hOHdztUTAyFwtu925F98Yn42lwBdCid4PMz6pHFB5cAYIM0PyAe40DfHyJhzycgZJ4oM4hbE25bEnqDnwy6g84Ne72rSfMlPn/rf2T7T/ORMN/dLFt8S6UEY90z/717+Ysr4DhPjjH31jdKfqI/Prg0BqxOvTZGvpS2+IH4WZov+MJ+JWSNDISHCdfKIrpScgd4miHcbDiAt9CYw5CV4dygM3HinSQWNbIZmpS/u139U3+UkebKz/Jzf+8em6HvbVbUG99KitTf8I0d2T/oX27uOB8m8/fH30LWJnrj4IGJmrT1+75eW42bvcPRsbuR5L48OmK2cjiWMcZ9zUMJGz0Wlc+LRcq/JcJeUSah9vo+J7tIoHsTH8iELyEGDyY+NHxwbHxWH1Rx+fDcPy4SZmm/jixKC2+kd1c7Basqv+jdy/Ydn107bsKuqpFn+MzNWim517wVvj0zo992Kwj/OVrMksnG+/xvGS8fo0LL5XIjrzpnlnvTwMCTgcDvYFiRug8XVrfyoHNe1/a7/XAwX3P1lhv+k2oIuwCgv9FK4CmP4SBBQTXqjcAqtfd5vuI5+4JjrhYTJvhhEwMjfDnatN4ye5sHTxIjzdLlIZhk/NGlaiQvLGPHSaJmF/UYfywIkzcR0eL4LlHhkj8gIDGl+H9te9/639MvzLN/770E081iR2W9jlL92kOsr01wiJkw702KxBd33MPgWWyPQs/2V/m5thBJbfHD8x7rurSeTSZqLXteNDcsKnOzzVyd43zav50jUTJsxoebC2BpaJ5nnQKVrZAY3D5Jx3auF5eYr2w9gcCj8rb/ilMpeIWiKAJn/Y7yEPVh0caXIEHzFe4NYH01+JLicOO+jvRep/2oFEkOzvrCJgM3Mz2rP4JFcn6rjnghxcgtk2TMzJ3rfhW6qIY9NVGYZhxtHRqJDczXp5kDccD+fm0G6eWp/yVgmTnHn8gFgS9j4x2g0/IWdWXuTP8DP5kbE02fHTw9iVfXU6Fuumv5T879r+hrs12nC34FNgW9Rd5mYLAZWD2WpVzVsj31adc3+EpYiHKxTsaDy5CYGjHz7FMayKQGfmhMhoYfgzWR574vCZhkW0n8vPCZGjofHtVaNAGBjHgz3p0eeZWDqLJmFEC2ZW3vBTWaCseGfyAyCmM35aHL+YUV/kTF2t9JfXNXvW3wN3aQy7QPugcmn+7CAgOmZ2mmMtecWN8cXxgvsjzKbdh/vfOKtGBccBD4WH1dbkVX++daZpPqxpkj/NN4vlwbsg+Es8iR6ErAkjQGSk/TpzIJKEOL0mYZNcTGA8l2ARI4TOyht+Jj9Fj58m3tJfagzcEp4mxK6Z/tuu/4HJfeKO+yPaCdFx9mdmEEhmGmamOXVuSBy9+Eb3DKwXPpmaTGfaeIgtVZvGKYETpJAmG/txAbIns3VhXikzW+UbTXxOCMoeW27ggvaTqglhC7Aa134lcFbe8DP5GeqP0o0fvPkKCd2E/huEOq3m+g9KPnm4p/7CeS9f+ugb3T/J4z0jzFUaASNzle6+pPJXvjOeW1h1L8JT6YNTxeVJmBockjoSNyF3KMbZOM7YMV2cMBeE4Etwtso30E5+C7Kt7efMGmfVDtp+K2/4mfxUYPz0Qep4Vh1IXY31X/r5PNV/qv8Hfffv66e7j93yx9GmtwTmVRQBI3MV7TitNo4dOQOzRctY4zibcTJYSVK4DMjrZHkwCftCStZUuens3AyWZ1P5VmpH2rzH9kPR8a1ewYzL0xoe4b0BOc7iZ+WHmBl+QyxMfpIBuJv+mcr4wUwdPidBwsIjI0fITXb8ynaKGunPZsPdiQeTYzi+5B6vIs2rIAJG5irYaVrll9wQn4eB+FIQuSXQt2TPCpQQ05XEMV5mkYJ0TROlxniWCdKrXp5PnZhx6+BrDR3OvPGapILt0rASNCUbWH5I05kvjNcyVt7wU1kw+Rl92KnC+EHfodtcF8uLmyTWs6r/qKdUx1Ov70X/A5dVfHHjwx+5Pvo1y5urHgKUZ3MVROCVb4svwv64q0E6FqUTE0qWvGXJWSNP0GQg+ykBCfu2pooM17NUHkqphc9uHcG02pwSuXBpwUMhbVaCx/YjzGVnIX3MT6NNA0XfyidCI1gE8mP4JQ8AJj/VGD9UdXjDfw568AiOI2oL4WEkZbrm+hPHGSxFTXf1S/88vohwmKseAjKLU71q17vGL31z/Hjs//o9EhAhaOHTlydxipCm63XW13T1w1k65k3jswX9taarX1R5ENs2FHKHLzfoLAGrSAKipGNcEzRdfRI6K5+QFMPP5EfHxbixE8qH5qvU+ME3X6GvtjBT1y1af5Xm/mC2cc995sNvir66U59bfDkRkIeSclbNarUdgTjCk9OzMOv0n0Iix3wjT5m4pnII4/n4qXGMp0sVCMJVLS84YHYSTVhAi7HqnDgaF4ZSIocEjfNZRoie5rPyhh8RUFlRueD40TiTn6GMKD7qV2r8JG+1L2DPMc+aFH2h9VddqXpxVvWntk99vq1P+/Lym+JnQXvaZI8O9gr41lkV6CRW8bXvitt33emej+DDpMrUOrpmKBE7/9EXHUZyVLw8ZiYjfKZmDuytrYp4pH3BxSy2X9aGatz/1n4IuPV/MMp3Du5l/IOox9gz1oXPr0nI/ln9xb2U17zj/AqX/9FZZ7u/vvl1EY95MVdyBIzMlbyDWL1Xvz1eWu+7l0J5nztOMZCX4RmKBwPv2p+zUB7LoG3uicM+D3mQrlv7dQ+fiq61v17yb/2vkp/4k5R/6JUB9Moml15H7+LvhZvVCv+Gu32h6T78njdEq+PwsLjyIMBxYK7ECFy9Et9nredeDQJzDqupyxl8kuR/xvEBnUSO1+xQjQ/zaFyVy2Ppo8klETRxAS2X9iJcm/azrVXuP6u/9V/Z5RcfEW5AV87zaxKY9WdY33IXv+z1n7j+h92h/aEd4vg1V14EjMyVt2/cS94cP6jfca8EkTtdqwllkm7QZ1jjddN+OEMXpmu+Kpbn/hUo1nk0dgkaNX3BIWzfLLdf+45+FfvP6j9EwPqvIvoLD46gcUeod3T/XF3HH+0P7RDt0VCSLVQ2BFIyULaK1b0+yzfGl4GYXcknRS4mihHgUyKn4Xag4Epu5GlS83m/quXR/hY+ujiPfSzNkXaNEZBZbL/2d1X7z+qfjFfrPz+TrnqpQuOXS6/YT7cJfdxVeR5TfdHRjB/RUxXXv9pe0a2R64PY3XLsjdH3xrXf4opFwMhcsfiPvfvyDfFjQNievZMBGInnLyi5g+IQ3eGvR/JpHmQfiS9peShEUtcFPBW3VKGwqnRVqP+2elYMf6t/Rs6s/ygS4uo6/rAq0MX/De6ZSwkbEVHZmCH9y2aN9LO2kQkD9+lj10f/xqC58iBgZK48fSE1ecVN8ROgLJ4pFxxAws68z8gwjtfjHMvQhXnHxSW5tv8dl3dc3PaSScy4vOPidiiPp782SNw86By/5DBsB/OHbdqhvJTJ5t3H/a28BzbE2vBLQAkxMfkbj8A4WRkXN750ovOYFmJdlvJYfMX3TDdklq6K9Q8xPUT98SLdZz94XfSVnX7C4vNHwMhc/pjveMeXvSV+KojEU2VWSnNRiXEAZhyemmKQnohp28L+jDUpUqHyWM7ghuM5CGU7be4O9cesHf9J+7eF99D+bWXC37LyQ71g+I8dfyY/gkBtx5/M0vWx9Mq3X7O6eA/6Y1uZUJdXpDxs1Rf+6k3RF1JdbYFCERhDEwqtT21vjj1yV4CcPY1EDj50RULSSNZ47Qd/Gi+Ez6cxzBcfWKaq5dHODmbjjpDI4Y1VaYuYC7RRrhE3Ek+Fp2kM+/YzNJJP81h5wy+UK5MfGz+qGw6gP0RPNd0R/ERnFvTvQewHPv/1NNot2h1zxSMAWTRXNALYI/dskJAnkrQJcYNykTB8kjjWT8ibryg7DddpXk2vZHmcwi7HAGBZlSSM/wdotxAyKlnffpI033xyOH69Is0r8b6MlTf8TH5s/OSlP6CH5RgTrCrIW/Z109+0W2K/VDmbXxgCRuYKgx43juMIS6tXQiE8mkqAK1qhYxw7CE9NKalTcgdfyI3O2FWxPPZddJo4Nw5tbAgJCxuPMOPYfhrnlNR5coe3WxNyxzz+fxY/K2/4mfzY+Jm6/oCqavP8S+izUIXNuv5mW8X+wH69AnaM9ixsv4XzRcDAzxfv9G4rK3HjuwvuD6K+u1giaXXowEh0m5KSOEkSq5Rk4dQU36ji1xwkM6MlU3JdgfKYWMMTrb6pukP9VQlL0zJt3Uv7rXxCgg0/Pz44MOgAiMnP7vrDxs/+xw/ITa87cBsUsRnW32PHD9r7w0esu0+urOBAKXO5IyB6Pve71vyGz1yJW7d23ItI5KAwZRmVxkW/CSif3EI8n+xEnQAvSde8nIkihiyjcRUpz+UIMLlFzMjJkSNQAGn7+ZTHZrH9jOfMGpeTpalon+ZlPm2/xhEfK2/4mfzY+ClSf0Bnt9ott4Qjh5uzqL9FFwf6N7Q/WFq6iHaN9o35zOWLgM3M5Yu3e+274vad/+FejFmpCzgQhJTokiHqInHBdVo9khouN3oCB6ITVao8GgolO9/ouw4JGBSdvLTB9oOEpXKoaWm7fYCkDmnSfs1D38obfiY/Nn5UX6hu0Gv1i9Af0M9b+MbrZkrqqqy/92N/Bu4XZ97HffTm10Vjv2+rfWL+ZBFIjehkf9Z+bRwCV74znjtt1b0EtOx8qF/OQwn+SuBCn+WV6HHGDrNZ/Cf76kjkGK5MeTSlxdk41BpcFCwO72+g/mqEVQGHvrafefCfM3RSxsobfiY/Nn6qoj9A5uJe7NagyweV1d8HsD9o769OLLmP3PLH0SZ1ubnpIyB8Yfq3sTtwRu7ICfdSkJH7Ew2SEnEkZXDpLBvC7BQhbCAyjE/3w5HEeVeV8qh7p91wS2hTQ8kbm6D1p1Lmtc6yMcz2y8wdiVzQfiu/vf8NP5MfjhkbP36Vo2T6gw+h1H/w5yCpldPfB7U/aOv5tHe0e5RPc9NHIBWu6d+qvnfgHoL7td1LQGAeKPvhEOBMmwwUhpVSK3kj02GcplEJgNTopm3xS16eBwDjyBF5yYEkjKQjrD+VnBA1bSOay3waF7bfyht+Jj82fqquPzBLh0k6t4HvvA5mXf+n+tu5X/ym6z7y2ZWoV18GkE/LjcxNGWe+tfodbArF4H1IwNFE1nlrVVAgLLInTHldWK1sOb0ua3mQ0xbascDZNakj/nhuOuKXtf6sV+gU76zPPLPYf2HbpY34Y/2XzCaHOAg2EAo+jM3S+LX+H0UgO+71+iD9z4cSsJp1PKgLuamF/ojdTx+55T5mb7mOytWkr6ibzE0LAdCzb7fc80jkqOx5G/piEKARJA4XVA6cqQL5SfNwkDNdBrsvV4XyaOtcY+AW4j5m2SpYf8W4qvhb/YfjxuSvevpj1uWXyl7OpIvd3Czq/7H9B/uHCY3nwqDZ5BEBmpIzcKcELH+WByliav0ykjcOXBI2xjMMscZK5NBpuj6paQqJXhXKs76YjlsEiWuly8aIq0r9q46/1T8ZX1UdP9Z/9es/2IMeXm5b5wtudeh/2IVbP3htdAtthbnJI2BkbvKYyi++7Ib49/HtukcLm0EMiRwHLBPHhsHYdFlS86VrWzuVCeOLLA++2QSRw9lxwk8rV3/2S5H42f0Nf5O/6uq/Q4xfPuz2nVvFY36/svp/H+2HbfjmX10f/QOabW7CCGCPurlJI8CPD4OwPRZMmRv/U8KsYfoa5r0lLDQvqYmmVaR8p8O3tapb/6rjb/XnGDP5S9VYxfRHreWXxgHHNs3hpQhKMHidtwf0Z9N+nPOI31/pfO8f/uxnbKu5ySFAWTI3QQRA5J6Cn+P/1HHZkcs/WRfGh+FT5QvTwjJhOMzD8E5pYXwY3kt5PGFFnTZet8chwKe6x6nSwnuG4b3cP/u7Vn68jGVxCrENMQvDYR4rP53xk8XV8Df5xauuW70+DhkeeTSZWfn74rE3Rl/M6hq7PjgCsix28OJWMkTglTfFj8NAfDLjqJzVhft4NJ4DVgmehllEB7Lm42+UrTyeABqttltQIoclyvRFDYZZ593qr2WYV8MCmZU3/Ex+bPzsoj9VZ8yS/mjFrkO9Sv26m/5Um8H2a7gq9sPX+cnLsJfSf/ZnIggEQ2Yiv1fbH3npDfGjurHj8iqXUGPulaOvg5L7yHTQ0cd/mRXVsKQBPcYzXNbyqFmz2XKLUDzJ9/dAviBEkShX1F/D/s2HtP2Ag/uiEgKrZSgtGmaalTf8vCyZ/Pix4TW0jZ966A/qVepXHBrfpB2YNfvBiQm2i3YOPXoF7SbNgLnDI2DLrIfH0L3irfGlmKW6Ug68xe9xCZICG/q8jQoxiZ2mcdOrJzGQcIh3icvjc1xtvLG6IIaFH6chEYOv9R/gmvWHIZa0EZ/xnrhZeeBk+Jn82Pgx/XEK/dnHkitswiZtBdVn1e3HTvV3TXfLB6+JbmUbzR0cAZuZOzh2UnL5LfEFeLX8OUrEGKmgUnj1mmEOShI5jaPPcpLm84ZpZSrfauL8OBwELEQMldQ2CoGDUUqJXJBG8pa2h+FEcQ3jkGjlgYvhZ/Ljx0o6XpLAcKzY+Kmd/mhC5+KUgHnq2qrbj1PVn/aTdpQib+7gCKhNPvgv1Ljki2+Mz8Z0+B9gdq2hr5UTDiVsEkf2Q8LmZ+sUrpD8Ma6s5eWpsOkWmgO87BAYnJC8sf6coaNPlxI+xuGCeSXdyotxFowCLHht+Jn8UA7obPz4h0DTHxGWPTqYuVqAWDT04Z4yUhX7IcK8i/2D7Ws0++75tKdsm7mDIZAa4IMVr2+pV789XtoYuKvwxbnTh9NUwAP0mAwZCjlxDChl1rD6zDEmXJbyUB4Rzo5bQv2TFmhd1S95/Vm9cfiOjQvylgV/q7/131hZtfG3XafO/vgdYNl1VUjcjPY/Jg7unW+7D7znDdGq6D77sy8EjMztC64k82vfFbePH3fLmE25HwaXfMmB42s3N0ISkBlPJOmXIEpYvoE9ckskdNqubP3V0GyL1wIZf1s+r5S2xWfK6eW2fFZ++8ODgjXGN/yChyziY/Jj8oNBsW1cjBk7jNqWL2f5ob3AS3YkOrxz2e0HqzjisviNs3+wp3ccPeqO3fy6qDtS2C52RYD4mtsXAnF0z3H3XAjiOSRyLBosq8oyGoWU//VnNcwRqGEpV9LyfJOKn+ZKiZyoDq9BfFja5qVHj1hJVAxSmCfMZ+UFLoEhxMXwS3BRTEJfw8zhw+KF8Yaf4UfxUJkIfQ3PkPzQ3ohexjnDbNYs2h/Yx3PuvdNdKa1jI83tGQEjc3uGKsl41U3uCpC3C0NSxhS59t/T4CDTgZbNp7fLxpelPASi02hiaTV5EE0NqdY79UNlyUheqzTR13A2H/PSZeOt/BAzw2+IRVZOEukx+cniYuNnKDOzPH4G6acT2zoU6JfFfrAuh7V/g8g99OU3uGfyt8ztHYF0CW3vReqb86qb4sfiULUr+NEVCiwHEL+/0vDhMC79ThoCOEBN8gpyTChpeRCweeyRmwvtwjZSRkWpGeBLcFycNBZ/mEbHjHTj8o6LS3JbecMvkQSTnwSHcWNlXJyNnyFeDM2g/GBGcgNfjdicFfuTtZ9YGfrcB66LvqGibP6pEVBTcepclupe8bb4oRC2Z5CYEQ5slJNlVHIzDevTkRA5/pFA5qmphOV9exZJ5Ei2RCj4R6VDGBtzbXeaRVJ8PisPNAw/kx8dHDZ+hrKQUSEKkekPILBP/Qns5rnsqpBW1f7sZD/jpnsG7a62z/xTIzAylk6dtb6py2+Lzx3gUGAMtmSGjSQNs2uclRPHgCduPiZJZLxPw5tI4nTAlaU8n4ZQ9UU83Y1M24tioXLxCmZkXwqlBvFMEufz6GUax3ifZuU9OooVfAbFaZxe02ec/gfehp8HR7GCz6A4jdNr+ozT/4afyY8Ki8oKfI2SQNYSMlH/l1h+sL+5Tf0dt4YvqlH8xe5UwP6kdR1nP3toE+wu7a/ksz+nRCArwqfMXMfEP1yJT8cZOC8A2UnEDX9xyGEyK8cYL4Qap+RNsPJpjMPhj8kLESUq34IC4KdjMNXY0pc4RhSbSgeUGt5sTeqPOM0rn5rxeTTOyqPnFTf1DT+THxs/pj9oFKagP6m/cbLCgryw5icPqmB/cCjy7vaTnzeD/aUdljbZnx0RUHOzY4Y6J1z5znhua8G9EERlEc8IsrxK0pYe8EpSx8EDoiZxKpyIl0N1kZYerluy8hz4WFZdxDl5LYTlUGNdGuTsIWbs5Puw4qOJnMGjLJC0IV3CMssIomLlDT+RCWoT/Df5sfFj+iNf/ckZOr64FnGGrgL2h7aE9dyL/aT97c27F9EeSzn7MxYBI3NjYWFkHJ1+0j2v0XdnCyGj4MEJYH7GTWbhOePGfXDwSfRkhg7XCixJXtnKc8BjpnEJdW1S6WKw6LdkGZZrrT+NNPMIcdP2+0S238obfiY/Nn74QOd1h+kP6MxC9CfedIWeXsR/WTQRe1VC+5OuZqGCYhv3Yj+dO0p7LBaHDTO3DQGZYdkWaxHuZW+JnwrO9gQSFh2YGlZfSZzA5QVSodM86jNew+oXUR6zcQ1omkWeJadGmHULw2PrOqb+YZkwbOXH9LXht03+Q5kJwyY/Jj+qI9UfJxOhzIThcXnHxYVlwvC4vOPiwjJheFzecXFhmTA8Lu+4uLBMGMbUQr87cGsg2LLVdqbsl3Nf+cC10ReIh7lRBLSfR2NrfsU3aPAt0icShhQgkDUN08cLEUyU2bptYSaR3EkW/oUrQXkSOc7IkchxlPNpWqqWCTOOM3L0tc1UFhqW9mfKhL9l5Q0/kx8bP6Y/CtKfPPTduSPhDF0Z7M+I/Tig/YTBeoK94cqRtd0pvttTahrzypvio4Oeew6JGo4hEbJDKBAYvlAIQcT+BHHy5IiwEDrEMF7JXZnKS2W5pwJVZEN0Hl7qDynQxjFeiZ7se0maiQJpFglY+QQYwy+RJZOfRB5s/Jj+KIn+jLgCQ0JHyay6/RqpP+wz7XQy4uyvImDLrIoEfPnm6p3uKijkszSahAyDQnASw60J8MM0RvMahwqnM1gaV4LyLX5nNZxdk7ole+FSGdD9byHD9/vlxrffyqcvgyiep8J4m/wYfoafnwE3+YH+xHiw8ZOxH4GOOIj+4Dt4IEJrkK/+tvKBbRP5K6/92mZ/ooG76/Sz3QfsG67sucSFdlvjauvjm6vPUiIXzqoREF4TLCFsCDOOs3B6rcuMCmhZyvNIFRI5qS/rT4WJ/3KNyuo1DptL4pgAp3mSq+Ra2m/lDT+THxs/UAychTT9kejTsupP6P+I+l+XXNVeUa9XwX6l9idjf2GMz6K91nTz0Z8GQoIA1uEvR+hiFXZdRmUqFRZn15jGeA3zKZLpco1wGu/zMY2uqPLo3CZquMRe5h4m1oMKWMP4FllSf6YhnMb7fEntUX8QPU2z8oafyoLJj40f6giRB9MfpdWf1P/Q28keugrZr9T+7GB/kX7xK24Qu61Za+2jm8394VvjB7iue1pI1rjvLZxtY5oipWFNp8+4UpUf4JxWvrWKJzN2MolcWn8f1qdJ+kwPyZ7s+whm66y84WfykyCgY8HGTzImTH+UX3+K5PLBHis1lbBfe7e/TxP7rcqpxn7tydzySnykH7sroaAjzrqRxCkpY1jjKCPhbF0Yr/KjcUWX55tLLbzsAFUbcSYt3Jye1jWIz8YpqWM5K2/4mfwkI4RjQV04LrJxNn6SFQDTH+XSn7AJfLCXl+DUVqns0te4ou3Xfu5Pu037TTsetqWO4UA91a/5y8txszXvnospq3kKMpZNZV8cJD6WN1I9JLwmUEL0/OHBmp6WK0l5VKPBT3SRyKU9ilk3qT/ImRxqzLZwNyycGCW2GxmYJgKB/Joumay84QdBoEyY/CSzUTo+0nFj48f0RwX0p+h8POhji4So+rLZL1Zq3/YX9pt2nPZc7FVN/0iH1rTtrnW5uwJPAfIRXxI5hOULrPQp5ASH8YoP4+hU4OQas3d0ZSiPGbkm6sQZuSaNDOupxpd1ZJz4/EOCJhkkKslHAsg4P6Nn5Q0/k59g/Nv4EWUhMJj+qKz+lAd+bMHBt1Eb8jktqvyK2z88Z57jYM8Ta1bPv8PZm5q1f/nG+DKQmd9ns/Gac4Spl1j9LBTYExcpqSPR45NDmFfD6hdRnp9IwUHHp+HZZFufct9capRJ2KiI4Q/gs64aVj9bfytv+Jn8eFJn48f0x6zoT3wZFTbgJAld1e1fWv+m+/QHr4luzdqwOlz7Z806NHXYRqyvnwUit43FUyA0F4kZ//OaRE7DCliYV8uEcXmWR1siELEjIZEjMeN/1o2GWMNafyVyWnfJ58kdw1be8FOZMfmx8aOyYPoj0ZgzoT8bWKyB3aD9YKuKsl8JohO6f+yeSfuuv1knf9sszqw3XvbJXe5ejsF4n3FtJQkLhZp5qMD8FjMpMi6PJODPuLRpluesISbllrARFN5wlk3rQ58JfjVYoqmYxykjJo5Ls/KGn8mPDB0bPzvoCEXH9Md23Vp2/YmjZfoY36s6aVEl+6dyp763v78ZfM0dO3YsCtWWZplZXx+0ZraB2xr2OPcUELOzGc/GpwD4vXGhIGtaSORYDsRJooouL0QudoskchiQMqsYkjRhd6hvVqKRUerPdM1j5Q0/yrbJz3B2XseGjR9KxtCZ/pgt/Sn2oy92ZGQio+z27xT2974Odn4osfUI1Wpm7qo3xw/EUuQLMak82m4uL3JZ0ve5GDTSHdkdwpQkTRiQ5Cy+PPfuNfntvYZryTl3qKUaH60/BikPsuT5cZJGo6TXoXhbeWBk+Jn8ZMa/jR/TH6ovqVtnXX9iVquHb36twUYOhK6W2P6F9gvWeKz9xrzcxz/wpugXI3ln+EL5yww3MWnaa1bi+UHTPZtTcWmjKQLJPxFb7g2Sjd6kb5rPC7QQOf6UxjOspYXuJWXzKo8zgxbwYoLMyJGIkJBp/XnNelIBqUFKZxd8PKtPRSXKysobfiY/Nn68/jP9UU/9iVY3MUEwD7tWevtH+7Wb/YUBfDbtvuStwR+Y9nq4tY77T5iOk/PXhHDBePEtzZTZeQFGTMLzwd5GZuIC4lZ0edSwwxm5sP6qgJW8sfLhk2RI3Fh/kj8rP+x/wy/BwuQnmY2y8WP6o5b6s+E6sAsdyn9Z7d9e7S902RLtfj0YTjBJNcsN/sO/iC/DE8dDU+JGCkthJUGjC4iahJEuRIe0ji5DfOR3CioP0tHB20fzYf1DosYw68f6k7BJ9Xepv5UPZigNP5MfGz+mP2qsP2lfMATmaPfKZv+kPqhcaP9QS/3HGqf6i/WHDbyQ9l/Kzfif0b1jM9jYF63EZ87Nu1egi9vSPC8IKbHj48ducfKI4sHZLS+zZX9zQuXxplir2cFGVXzUuor1FwQLxM/uDwQM/+H4pEBkx+q4uAmNX/604Q8MFHPioWH1x8UZ/kQlcTmNX2ygjftbbg1bk3rSRznff2ScHLb/Y9fd3HAf/NhKdLc2YxZ9isbMupWVuDE3h31yJHLZllJAVIGEfhhGGZnpIkIFl8eyagP/F2U5kPWpWP2Lxs/uT6EJnMlPpca/yW8guwya/E5VfjlhEOGzkDxqRpAv2P4dSv5h/zvz7jnkAxkpmqnLmW7cdzvuSZhmvR8FQUkZyJDsF1PhSK+hHLDGnkwro4tliZIKg67g8vhEV9SM8OYqpv7T+vqeS69LXP+i8bP7V1v+rf+s/6qsv6sqv8A8wpLrEu1P1fGHubwv+UBi0Gfzr55mMXOtW35zfH6z7X4P++I4lkjUwIVA1pInjSTMLycwzb/8QOEliRNG5+MYLrI8jhmJsD68hEq0qlj/ovGz+xcrv4a/4V+k/jT5O7T8RU1s7+k3XK/q9gf75s+99Jkrv/reZ/7sxMwRHjQomUKdsZZd+c547sx1dxVY2RFOrilJC8NsMkkcZ+OobNQFxI56QGbziywPcrmI+nVIMqtY/7DOYZjYVgH/sM5h2Opv/WfyW379GY7ZMGzjd5/j17mtrditqS2sKn5YNl69Z8m9/5Y/jjbZhllyIY+ZmXYdXXVPh6I9wgaxgSRCDIeCyGslckLgGAHHvMgn+XldZHncewHLq+2q1r9o/Oz+xcqv4W/4F6k/Tf4mKH+wQ5ih41af1DaW3X6O639MXy2RHzBt1hzH2ky55bfEF2A++JKwUSBrCZmDIGqY6dp4CiWvNY1PcKHTeAqyhpk+zfJ4guARJB3eR++Z5/15X3V2/+rJj/Ydfes/6z/KgemP/PQ38VY3K+Ov2ZSJheRUCDRumvZPsaM/afywdekS8oTwHrMQnqll1te+Nm6fvNBdDTJ2mnYOiRqEQfbGaRx9xnOmTuNI4FQ4NY5+EeVxRlwT/2VmsYj7F91+u/8QAev/ZPzKbDnHch/bIhpugANdk2cuvtCE/zp+028rIwMGfSyftgOc+lYeP4PHT6MwvtkfDvk+9qbK2YzUFQgPBnh7HBu/+btQErjlqCuz/ghravJTPf1f9v7DPvSTGF69strPveCHQX3v6T92H7j55qgb5q9yuFXlymfrfuJC9yQo6SNQ83xjNXnzUx5Ik5xk+CPxUOhQ2nxiTckelR/NxEg+f6OcyrPei7Qgcr/q1b9o/Oz+xcrvvvHn8AJZIm8aYKN1H6EBCVo/dn1sWk4P9wYRk/GL70eKjzHKT3DJWOVv8AdwmdwfLzfxUHAMI3lgkzReI15/h8RPxz8zYbwJycPvJ+MfxFH0AH8cOoLx2PbQxI9SSzQR5m/hF+XhS+5TAv2xb/xLpv+s/ip/Xn5FsBL5LIv94j7uVch9X8ePPuxUSP5PJ18ArJ/n8J4Fp31Q+ba8+u3x/QYN9zt8WtDHaCopNkwEDL7Gqw/lreNEiBPzFVmeBgeTBkv47qrUq2r1Lxo/u3+x8rsb/iBSoGGuC38TRG2txyf82N3L/92BO4FH5FXMvHFj8hbGQg/yL99L5e8irtDxS2IIvUHb1WP9oDs2egO3rm1A+J4unvaRYZ3tYzsxiqXeZah/0fjZ/YuV30niT/uEsbkIWU/5Aycedhv/anfVL9r+Ynw+iryB2MyCm4mjSXgY4G/a7nl4ptez2Eb6BsxIz2eTp28kyjUzUbAgVIk/fCIqpDyWghYwE9FmfUJXlfpjlkJnNMPqk5lWAn+r/+T6D+SnDzy7UPBboDRbIGzrEOtNE2A1AQAAQABJREFUzG51Id99/58EqTTj79D9j5k8CP4Abeyh/V3832SbIf/geiCBMHiI4xhpov3MWyr9c+j22/ivjf6D6PJRJcKDS4/2SsZxxfqf9cZK3jkve9rKrZ/97J/JeOSYrKqbiWXW7y+4y/FEfzYFCk8LYiDYIeis5LBDiB07jm5cHsTJcsu4NC73UGynXh7Hj3RarlPZ+mMgF4qf3b8w/DE+Br2e62OPWa8PH8/rfc6qYchF2HQW8+yf5GK8jJRi/E1RfkBoexjXaDz+g9ltYc6u1cIkPEndwLXoI11WFGz8V1R/T1F+IB/Ttz8HqD/GbaeLj33B36R8V1L/D9x9yB8wMr+K/5V2UC3Vdq+8KT6Kp/6X86UBnfQVxYlmUXfKBmjQMS9o0thxYeYtrDz233R4lIqn1pWrPwdykfjZ/XPFn8ulIG093BTvDYDAYY+b9f/h9AeWSBr4fFILC9E4AUIOCKeaqob+svGX6/grlf2CjOL8uZNYVUpfJ6qc/epjb27kPvS+66LjNGNVdaKDq1p51htP/VfgcyNN6BPZKI1ljHRmjiOMb6bxyYa7o0U7+sZKGPGav6jyrE67if0HqCvrovWRalag/lrfovCz+yfyPm38Y5A3zDBxn9gJkLcTGFvrwJ573/piXCCw7AvtD5NfILCP8cu3c3vYL4g9eGsgcycEZ+CNlQF8JbO8+kv7e9ryV1b9Xfv2QzZpv6Ab5IUjxaNS4z/hD8+UOlf4T6Vn5q5+S/wICM8V0JmiOGWqF0GZjWMUZuQYlqMGuFwaxnHxlAQKWqjI8lBSSy18qiusS5XqXzR+dv/pyC+WRWMskfZA1rqQTu5/o70ejqmSjJ869D9mQrEzCS/SQk/wEHEaTjlqpQT6qw74l9l+lAV/GNceXmJapS2tqv0CQ/jc+6+Nvks9V0VXWTKHt1CWIDz8ZJccrEvwlbxJ2D8pMMy3PPTJIczDtNCFaeEAnlZ5vOwwjw6Y0zrkfX+9r/p2/4T8E488+l9xV79o/Lk/FIqYb5JuSdg/AE1L/rXd6hfd/qrcP8ZuOxjNDnQHD3CVZ1FiWJX6q7HXflff6l9t/YOHP2wHdesiixWwvyp36kP+utjL+v73vCFa1bgq+akiqFKlWVecGvoMgC9EjoZX4jgLxxkDOHlxAT6vsYSRnlXFjdlMZzyNFF0R5XFvvO+QELki7l90++3+xcqf4i8zcCBwPGKjiyNCeDQIZ+HKPn60/kWN3yLvz/7x/XSC/QadxqNS5IBk1ouYWP8N9XwZ9X+R8iNjZgr2D1ueOrRrFZa/NnkF619FJwO/ahV/xdvih2LR5zmsNwkZB6v6+4nbT179ffVZlk6v1d9LHFd2QeCOQAkLoaxa/Vlfddpu9RmvYfV3itspXsupv1O+neK1nPo75dspXsupv1O+neK1nPo75dspXsupv1O+neK1nPrZfCAANPk8LqSL3fZ9k7+hzGaxUllXLNVnPjq9Vn8/cfvJq7+vPsvS6bX4eAmMy7AgCh2uRGjatnxSMvmjedTfKa+mq68/odfqW/lMn3igFB/1ZxU/eTjEAwYOYxyEbdWw+mVuP+a6/+6Dfxr9WOtYFb9yM3M4U45vfD2NQkHHDZf0qXT1aZTXdFlFzDjNX2R5gL7Q0tnECtafOBaJn93/YPhjRqfX7bpVkLh7MYY2MHL6Oh6qNH6s/3fof+5xRL+iT+/F28ZreImCBxynhI9h7W8bv0RjiIfJ/2TsJycoMEO0QGzLan9Zt1PJP96mfBo/Dcp8VXKVI3PfTc6EWaJSkg7xLWCYT6OQJHmjjp3AOBI8CpV2HvMwrajysk8OG5mLun/R7bf75yt/IG3yliT8ExgHq3hcFgNv8ldN/bHX8YMlL35zchXLRvfyLVl90N1reerIMupPq3+++uMg9hM1bGKyYq7C8rN4/KHusRwDVXKVInMveGt8GpaFHi2KCTUX5i/v2CXkjPGY5tUPZguJ086g8VKFVlh5LK9C0OcLuz8wIB52f+BQRfnZT/9xMzLeLuMsHA6D24DfL1z+91N/5NUne8psKcZvBeuPAT9g/2OW7h4AehKS37XxX4PxX/T4wX5wyJ3OoVRu/LYG7lHkG9Q9VXGVInOnDdxTyPoJLjeQqnFKIhiZEBW+LcUnOM7SqS9lfFwR5VmPdsMtsU5F3L/o9tv9IZ5Tlj+RLXwzlC8y8K0yyBw/pyXjwPCfPv5l1j/sf+hO7o9c5TmB0J1bDX/cTBX0p8lv9eQX9m4BM8SN1OaFuqjk9hscor3k3JNl3FTkT2VegHjVDfF5vYZ7oeBKCsoZOaWiCIvR4pOzpjEjwiR9fKrPxuddHgcbL3BjMquV1qVC9U/rbPUvXf/hde24hxcaYKA35dgHP1tdJvk3+cHACfolb/0zDn/oJOr/DvYIzeHQ8obO2IX1LIv+HFd/iaM+qoD+r2v9sXzW5UHYVW1/q+c+/pfXR7+mmJXdKZ0oeT3jqNdyT0sHr69tOoeL63GzdMwmRM7nL6o8nkzamJXpZO8fgq/1lzj+8Ymnqr+V144d9n+d8JM3UaEo5UiRZOP7cB/pHuSnKuMn7eVQ4BFp9U+ROZD+o86Bftmk/ODw2VU88vbrNH5CcTL961eMKFIExoNzWPuDx4U27Z9Iagg4IqowfvGQ/DSZKpIGlPtPBt5yVvbqv3CX4OnrPjrgxEfNsVyQ7v+SmiOOwifpmsYEtjK4zrM8Hn0b+MLDwrj78/RurYvW37/aLZ8fk7RT1N/K1xM/vpUK0Vnd5B4o7I1TxUu/bPKvcj1O/qswfutSf+idLgzXSazDnqR8hf21k/40/VNP/aM2a6/9T/uHA4WTmV8MKC1fifEfufsI/xBFUO4/pDmldq99V9yOeu6JocHiSw5UNqHjujyFhGmSjpZx6ZV5VHgkP+NzLI/vVspr2lWtf9H42f2H8guiRv3HPU+rUKTyVqrINP6UVf6t/4b9J32Vs/7ZL/58UUbki3Imj8DVqn/Z9P9+8Z/F+hODRntoB/O0vxPBH/yDPIS/VWaHjxCU2917r7sclGwRAgBuligWbKpMX35g7ZXE0aCRNAl5k9cMmJiQuiLKoz5zWF5tklQWcX9iU2T77f4Twh9GtdtzG5AlHjfBmeZKyL/UtcDxZ/cHAgfEH/qqC23axQNEG3vr5nEN8Ut0a1X0r/X/wfs/WXSdXHlMvjRpD/G7m1WTH+xDXhQe4tyXRaZK+gfUp7zuD98Zn44NlI8iOdOKQqkIMWKtJexn30CY0mM3GC/pwcxc7uVB4nRWrpL1J75F4mf3p3zHmClZw0zJCSVylZF/67+ZGD/QAV3KH+RuTT4jVhX9a/JXOvnD10nmYaRb1GvonnLb74z8kIcIH2HFS+qU45SyevGaewp6XepII8ZKcvZNK82wzMIhnnEp+UA8V2GZpquxeZfHvReLvH/R7bf7H1z+IMuDLRwtImfEcYaEsl0x+bf+P3j/U6+VDT8u62PZ9QTODlvDizfJg3OJ9W/Z8LPxm9hvLAUuVMF+Z+UHEt8kH6EuLqsTglTGyi2/OT6/1XJ/cKq6gdUlSmWQCIp2AJThnto1rfKYkZvnU8ip6s401pdOhVuu8Qfl9+SsfAKTwjUL+EHpb0B4t/giw25CMC35LXr82P2L1V+74Y9ZYp5dOIdadkhSZmn8USmb/t1N8yTpB7U/eEjdgNxwubWU9vtU8t/ruU8ee1P0y70hlG8uHYf53nW3u+Go32Y7YcHo9KTD0fEaDoUAb8mkxI2NYUdAu8SaR8tInP8tTWPZSZeHomvi6WNOBZ1v/KjTsEaxvmEHyLWP0Dxahr+hYU2z8jOFXxfTMVzO2sQM80BlNG/5LXr82P2L1V97wR+zcwMsvW7gU2EnoYOSfZxelykRUh2lOsv0l+lvlQXIzByMdmMa9ncv8qu69SD3bzfdU8EuUs5BuS6L89ShLNVJ6nH1Te4SLFGezStsvhUHQ8enQQGRlaaRI0FjYjYseT3Jy7s82Nk8l3sVWFVurKeGmaaCzfhxYStPZIaYheFZwg+yym+nnuTJ/BDmAWW5SPm1+xv+e5U/6Lo+zshZo/xCE0OEh7rM9BfRmH39xTbu136JHYedLKP93k3/wbaf9aq3uYvZ7rI5HXOlqdfKCnhzlHzkNgXWz8rxmhXFEyGYHbbEgbAxjmGJQz6J9/lyL990IO6urcKtvtQZj6p6TV+JnYY1jfEaVt/KJ5goHvQrjx86lcsNOB39Xsh7vxTyW/T4sfsXq78OiD/lF98BPoFhuR4+aOl4Nf01g/rLMwfVxdrXe7VftJMw5nOlst97lH/MSl8uPIWCXSJXuunC5Rvjy9ot97uKEY2czq4xTp4aATrDSupkCdUTO8aH+fMqj5lEHop4BBVrKNGQOgbEg9eh04GgceGACOPC39N4+lZ+SOoUD/ohXlmMmK4um5Yj/jzyYR1KYcCHjzLIrz4YEZsixo/df/iWfsXxb+CJlmdryrlc2TGmY49+Ni3H8SfVsPtv15UEJi/9iTE/wEzXSfwfVG38Q2d//r3/LfqeCFJJ/pRqZm55OW5CETyW2JCEhU6vQZYGGqbSI7PnNd8cxRNirIpQ8+hv6PW0ygPIedw/0oGgiim9P0gdndTXh5mX+SQvfBj22MonOM0ifuxuzMSd7PaxpAoFVib5LXr82P2L1V8TxJ+qdhUzdauU92Q0ex1n+s/0P+21lwoQIoiImy+D/d6v/Md999jlDyVfT1QZL9ov1aHB8090l+Jw1CVPypJZQxAc7MaIaPjY6eh9vGIgyoHEJ9lDh2s6pglpS0hdbuXx5mobNenwhhRUT8rk/gxDpQnJYxrrCCGWQc1ZGak3rulwEVn52cQPnbu1NXDrVBpRyeRXH4CKGj92/2T8zxT+DZxPFzk8u+Ahd4DD09E403+m/ynjI/Yvdh3Yzy42V3UrJv+L8z9zl2LkficZvcX/BX7lcM9ciVtYdno0FTtJGga+31KL+nnjB4OI0148kfPnbkkcSB7z83/e5Xk/np0j+/NgqKm0SNJ4nT6XIo7XQuw0HJwbxnxWHhDMIn7YJI4TxE9if5y84FA2+S16/Nj9Ez1XlP6aJv6DHnfFuDXKP2aie6b/0Nem/xNbGNg/2k+ykCLs92HkH7L9GPKWcjAoeVAoR1XOW3KXgdQspUqNhI4zbPRB1ugYTt6ZwoUSPCYgTNeAgORePsY0cTJdzKVeIXGeuEVQYMnLGeh1OpmJ82Ed1JKAAU5n5WcLP4jtJrqV31KV76iWUn4peEWOH7v/zONP+cce0ZOYpetmH3DZ/dSFdKb/Zkv/7dX+if2EHS3EflPwDqj/+n23ILyFv1EC54dRsTXhR2wxkB8j5M0zdpKytFYgRcRbiBpn53yYcUL2OCOn5C/H8qDkLflESTLrlpA3f38SOtaTjk+kBFpm33z9ZRYqSUvfyBXht/Ky9Fxl/NAA2RsnsxKUg5LKb9Hjx+5frP7KE3+c6cVP0632MEvH8WH6L7EJfMAnFuJDT5DQ0mZUWf8dpP5yyD4/genbXwX7z/FD3kL+wjYX7UpB5u69yz0SnTcnYBAhOHr8H3aqT1IizdHAQ39TcsdymphHeQxA+WQXb5sOPo8oPSVwTKdTsNUHeUs/mG7lPfn14NDj/xSXquDXcl2+5ACl1C27/BY9fuz+xeqvIvDHeO7i/0ncu2v6z/Q/yJDYb+p56PuFPO33hOR/jvwF5qlw501ncfVYXok7rcj9Dmugxg8bJPGyCIicP4KE8eE1w5qXeRim07g8yrcb+JQN+IbMJia3H5IPPGFxNZVpTCLI4TXDSlSsfPKEqjgJeasifqgz+nQdL/CcROdiBr7c8qtjpajxY/eHfOBBtI74Y8/BAAp9FWN9DcobECROdSJnskN9yfjw2vTnjNoPzMxhWrKdh/2epP4hfyGP8WJcmKfjqLAKtOfc74DxzGkHsiI8c4ZgN+DzWsmbxmscfXV5lpe9T1jj13uL7xWQhDFVTGDTKWOGmeDjGaRCGnFWXhS4YFI1/EjeIndiC5/iYv1VTssqv6wjx1To8hw/vK/dP0QfyzX+AZaxdZEfzGBvchabDz9K4ASVqo1/Vtr090T0N2zmPIy+vOBeFf1J/kIeI7Jb4J9CydyV74znMJ3xSD6dUoFRoZHE0WccPzaucfrhcX2SZTynaFku7/LYKzfHJQKQM/6TFzXoM0YA5cDmf0lN4tL6B3msfPXxw+wCvmaEb6r2MRFbEfnVMVbU+LH7JzrO8If+xriR8YNxZPrT7AeJHP7Pldn+j9Vf4DHkMwVyuWTCqKgKnLXlHgUm3hEiFxAzMnLGoVfTmTmtI9OUGDGdwOZZvjlwTRhwmVLl/XXGLSRmMiPHp0tf/3AWjmlh/a08O5BqfEjsKoTfBmq9yjXV0DCXWX6LHj92/9Hxn7f+KiP+HD9Ycub3XTdk20miD0x/1tR+cLIES1dNtZ8Qj9SVUX7JP1DfNvlMWtECAkKWCrive81KPL8x564CG2vpOio7inVRsiOb4NiT0HjSiZj50LxSZ5+mcXmUB5lbAgVO3l7RzRveFxIS1p9MLUiTPXRahg3QcJBHokls6Kx8ipGQYFI+xUyA2o6RRE8Zv6iF5wfs+YEB6mVldOT+tNQlk1+tD+uZhoM6MrrM4y+ts9V/JvsPBqDFF8vwwByZ/uNgxH/YgTLpP+kXjj/VxUEdJXoy+rfbb7hVHe9lsf9aH7YzDSsPATuZW3fvf/dKtCHpOf+RiaGc7ym36y26yzhwQ0BoRMSQ0AjiPz01lpx2lYL4o6RNrhVI+NMujwHFAwLbStrk/oFAp/cnqvgv9WcYeYTISYFkYPrgyICw8r7/S4wfZuD6MV5yQH/K2XFVkl+VuaLGj90/QcDwTx7aBY2M/sbxJfxyxAksefRNfwKh+tqPdov2lkJA214C+5+M3p35B+x8k7xG8+XtU1Ryd/K1hwiNltHqb69h33nsQI5zLl9ph2pYCB+LaZkwPMXyAGuegyu9f4iehumT4OF/Wn8fJ/VH2MoHM4/sO7oK4Ienic1u8jUHdm3u8le0/Nv9E12Ujt+c9U9d8Oc+Or4V3o3dlupM6lMNp/irzuBY1DB9078zYX9A+RdU5mlMNZz2fwnHHx5ELivqm62cacrdnddxD8P5cHNYaxbHTpJ1Z3SOhOE1EeZeChhQ+Rarv5YwC6VlwvAUy7fbroPP07T0mVLuz6UAvb9fFkjrD6WCk8+T+iNXM7n2uyB8/a18lfBb3+q7Tdmk6RWLyKz2P7cITFH+ipb/stwfMzZ8Y3gD2G9ghnwTLyJx36KEu5jn7+DQC7yFhB0sGH6biY88A7yBjpPNXLM5Bx+PhxinjS0skrebrgnjMIe4efTtPJbO5yCUfGibB6mYK4v+KQv++gA9bf3bwlYG6P81jKo5/F8w/Sn2pG72o4kld47BrcrIP/RH60fuIuio7+N/rq4AMocXVJt4g5ViqcYPYb4JCOUZ4XVWCdNeShzTuPwKWHAt5Ejj8yqPavLG8xAsbOVAfeiz/tD6otRYR+SgcYchkbDU3+dL689MVr5S+FHG+j35vuRWUfKXyk9B8p/r/RuuB8N9HE+4J9HcE4O2O9Hou5ObsTvhvu5OHjsWYWjl45aXoY0e547gQMnTQCyOYEP2adBbp6F+R1CJo5ANfrlGdIHopJLqr1z7b8L6G1+M2MSD/wA2YwGKFU0x/Vsn+4MHrAX0/xZn46qif8lvoKFyJ3OgF/m6V/5F/CBMmT5L70oCpOSMSkfj6WtaGCaJCvNpnmx8WCYMZ/PtpTyMykJK5rL3x+yaDq6wXnJPnxaGt93fypcWP99vsj9uJznZKT6UuTC8rf8rIP/TqD+/3AJFfU+v6+5utN2dmAk7Pt93d/1/10QneL8quP/61vi0ja47C++2H4WxORuHh56JB9Iz+EDH+qtshGHr/4Ppb8hLu9lyi8C5EepZvihh+tc/UGTt54zYH5CCTaxybYzjCTrGsuMqHHNhOJtvauW77u/f96boZ7x3Xi53MnfVW+Ln4Qn3XAWVM24gS+LSMCN4McZpnrzKQ3E0MMV7Gjud1dnT/TmVt8P8gZVP+vuU/VcG/PCiA99YRT1HJHFP/Vci+c0OocLqj43tqMsdMMa/wYC/4+Hr7jcrK1HyEkm2khW+XlmJW99fcPeD1JwDPXc/NOUcaI70242F4e8xrfL9qYsxG7qEF0iapdcfpv/HjuI9yV9G/5PEYWb8BHXxnsqXQP9iNeH2v7w2+tRYEKYUmSuZW74xvi/2qLxgt7Zoh5HlsffYN/txkyyPJ79FvFWzr091pPeHUPJEzAPX38oXgh+UBknGKt9ALlr+Knt/krem+xWeqH+JpdI7jr3eHZdNCfsZyDORN46W3+GOznfdOcDifBC7+4fkblwTU/1RAv1XNvnj2WOAZQl6ecctQil+pj8L0Z/TwB+6eAt9vjZuvGTj0vsXPH66ffeJY2+Mfput37SudxwQ07ghiJx8kJZGUo/3GBdOyQ97BXnxL5kV8+XGlWF9NX5S5bE7p4H177Yu/mL5JMZ0P/fFic97jgun9weR41MFntKl/ppXfStfSvx63Hgt/cZF/wLlT+YEK3R/wHUnZk1+2Rq4//WwrrsDM28cwTV3UQwiexdA4P9bMXPX+FHbnQMd8ABcPwDnbxzN6sJUfxSs/8oof9TFeNI6ianOJeDXHqdLU/xM/86M/cEY6WD/5DqX2NXOo/9Tmx+G0/4vePz4b85/hnXLw+U2M8f9JZsDt4zBl+xxAEHDU1/Mt1S470EbK/sf/PVu4WmXbzXcApZX5RMdNO661Kph1DsG2ZO9MWn9x+RjmpYJw1a+XPhB3vDCqnwAXOSxaPkr+/1hV7kx/XbozJ+edtL9/OaVaE9PzjpWzHfutSvx4okj7gLQ3gshdOcSE9WHZe//aevf3doPo72At5TlC0IqS+P0LNPGxZv+LZf+3amfNB5Evotv+a6pXBQtf7vdH/I5wJLeX+W1Dzi3mTmcJ/AIvhmIZUchcOwQJXIEhR+vD32mqdN4lsGsCc4XwOCccvlWU1ZHZXmVg56za1QIXDalpWeYPgke01Ef8ZlPlYTW38qXHz88ZHQhW6sqh0XLX5nvjyfOOyDnP+3Ou58ee320rnJu/v4R8ASYb759f/kd8UJnwz0EB6Q+BG/MnqO/VoT+K7P8qf7Hw8QaDhnmC3Ft07+1sD9tnniBF6dob0vNHyijkM8Ib+E/AuP4SzqWp+nLDMQ0b8DfvvL/iOfOfAA+3YUvPnCKlDyNpIyGk53CPErSQHzSmTumMZ6OeennVR51XMId2yRvdFQW9Dmtz2lcIXV8sxXXjOe1ztLpU6CSP6Zb+fLihw7d7G65dRmAJZE/HQdFyX/2/ni4uQcPLj9cOup+fPPrbAaOY3qa7rXvihfX73UX9nruEiiYM/LWf9n+L/P9oXcX4q6bM/2bTC7MuP3ZhGyulZ0/6PiBzuwd/6X74C3/b8TzMafqciFzr3hL/GgsWT5OCVvos3XhU6AaL8ZpPgVGr0N/KuVxAl4Hb7BmCZpehz7vTyWijml0jNN8nL1TYhfGh3mTUkkZK58ffjCUm5iDTWeXSiF/EIBC5d/fH4dk9yG3P8XT8A/ef310h8qo+fkicPUN8TmYjbgEeuQhDXzgaOr6z/e/3id3/XuA+3PJFQ/Mc6FONf07OsGgeIQ+Jblq9gt7YU5g5rof6mq2gy6MK4v89gbuax+8NvpmUsPp/Z06meOG3x/Ou5fDKCwquGFzNC7shDCd4TBPSPyyabzOpmfzZNPD39byOivHa7pQ+EPBz6bxOpuezZNND3/byueLH5Zn1jfxVQclTsQ/Kx+MC2Ukmx6mzUz5yB3Hiwzf31h3Pz62Em2xXeaKR2B5Je7ML7iHYhn24VgPOMoazaT8ZaAO23iq8Yflf87OLWSKm/72q0Zqa0J8NI4+XdY+MS7Mk00P03Irz+/3Ym8z7xfKBq+z8pHNk03PozwewtYu3nAfmvYLYVPfM/ejOWzsBZHjCc4gSRF9vl5OX8BHnALq4yRNZ7N8B0lcLuUj18KTaAuzEcmbQKgABDjZB4copA33xzGNbfKDhWmIkjxh/a18CfHDAMPBZ5uUqVLJH+UJchTKDxRQLvKPe/4SB7N+53+8Pvolx525ciHgifWtqNWty2+Oz2+33CMhv+eb/PqZbHzWrQkNjBdy5sPxY/q3hPrX2/8D2s82dCQ3OOFl8PLrb2xRWCQPwrj90TQ1ytTJHF4nvgSAp06JHJ78k++sIpHpNGCMw1OnkD0pEJA+/YFpl29G+C4j98LxhvA9QdPby943IXRB/SGQfANteGyJlS81fjxNHBp/i0qewlcm+ctb/vGENcC4+wkeXr79vusinAVnrgoIHHuTEO5f4qWJs9pb+DxijCVYHKabt/yUbfxsNdwGZuhgP+Wbrqa/PWlSmebebbVVovig/Kpov/CJvUVwi5Nlk7+dxh95EPpgqmRuqsusr/m/4zM3t9yLKUhKwiTsSRvDNKR+hlfyMI7Ejn7o8igPJcC3oo5kCRzroYNAwqg/X4RgmAOBx9nQMQ99K7+9/8qCHwbbJo6z3eCgY1+VSf4o46xTHvIvByNH7vtHznTfsRcaiHq1HV+YOHm3eyQE6FLoI6qlEZeH/sxTfncbv3hQWwC5lWOlCERZ9I/UxezHROwn3vI+iX7tlYU/7Cb/7bb7yLv/JLp7ZGBO8GKqZO7Vb4+fBMP0CDVOqlDo8/C/sBM0D9umBjYLzrTLt0nk8MatErQsOVOFQF8OL/QdofHaL1Y+Ibhlww8EpotZudWyyp/KzzTlH/Ldw2b6H957wn3rr+1cOIV8Zvzn49y60xfcoyDrF0O5y8qL6tZp608FcZryy7bsdfxik/wSdHFHH65VT5v+ng37RV3Wjd1JleuyyR/rxTrp+AOx+N573hB9Wes5aX9qZG55OW52HudegaNE5nRws/IjYYw0GFeJ47OkhpXkaV71p1ke+/pamKs5okSM99Kw+mGchJGAp4PkMTgI60ydllPfyg8xzRs/nEclm2ZHZAkdozJXtPzlcP8BjNpt+ArLN6FQZPMw+8DcbCKAB+klPC0/uh+5iyDz+FRk4uom/2j1ErbOtLM6mWhwLdb0d7XtF47ukdm5HPSnDKDDjB/o383+19wHjx3Dt6Wm4KZG5l55U3whliKv0DorCOrj6ShG4+T+GmYaz5FjvObLqzw+F3JEBj3PvcP9QwLGOui1+qi55JP6hWXCsFbeyheKH+SJH3lf5QhSuVKZYxdpuEj5U5mfhvxjM/hPFxvua3mdRE5MzZUDgRfgyzuLA/c4zAo8pK7yj3GdEjrT37CxFM0ZsV/U7dCZJ6epPwmX2g311WYIlMByr/fHl14+h73JP2G5STvK9lQc9ixcjIrLAcG8AU8xJwBUKPT5PUICo2FNYzzDLJNXebwB1eTMHIWc9xdBZwU4pU8fTqZKUS8dCMwnab4tLGPly4cfZKyHc37Wyix/KvMcGxqmzB1W/iG//wEj/qkPXBd91ogcEa2f+8Q10Qn2P5TVp/BE9R9l1L8q85OWfx0/HP80+qqj6Zv+ng37Rbst9ht9Oi35odaYlP0AIbp4WlpoKjNz/A7rRuReSrbKAQVGJMSNsw4cRDr7oESOnUBix3g2VMohnFd5ALwAJjen90ctEkJHP5l/E+IW1l/zSHtQZ3ni8/XXNPGtvKCp+Gj/K0bTxA/yw3/3hvKl91cZ43WYXoT8Tfr+ePTegEB+7X1/Gt3G9pgzBBSBV74tvghK/3I8nC6WRf9OWv51bIf2A/uhI+wjPILx3hQ973X8NPWP6f987GcPL7VBia+r/R7X/8ovyqD/p/W9Vp140rE+ER+Hvwj7lBk2oChAgtTxx8lw6TOOThmvdARHNZym5VGe90MHd+T+Mu2WEDPGiygCISEipAVwuplRgUtn7EjkrDwhErwkQEwKwo+ygw47wX4ts/xNVP4HGE6x+86Ro+7DRuREAu1PBgHKxdIZ7iN4M+LbSBpMVP4K0N97rT9eeeTYOAmdIFra9HciGLNgv2i/xeiUWP4op0Sc/saUZucmPjPHLz7cNufw+gNeDcfTjzQC1lQZcSJC+Avg+b0/ZdMj6ewULUMQNExyoG5C5QHAHARhfuT+sl7q60wSR0LCtoT3Rx55i8bHjaRbeYBTLH54Cj+JnuuXXf5Upkbk5wDy3xy4Ozc67l/w4fu7dIiYbwicCgGeUdfpuadCqd7nsPJXlfJQSy086B0hpTP9PbRpI/1XRfuFL/l09bOMB9CfI+2fcnlwjvWL1tyxSX8RQh9QTjXm95X2k6PuATzjh2RNDRV/gEaVx3nIj3mwmK5xYnQZDyef3MihPG8HQolZT9SPdaMQw+GVdkRk6o90rM0n9ffCzvprnJUvD36YUV3DVzl6ZZe/Scg/lFAXmzW/8p5r3CeNyMnwtT97RIDy8t43uE9RfjCN3dUDP/PSv5OQ//3aD6juXr/n1viwafp7duwXtnJ14h40P1zZ5Reb+xbIk/Y4TPecbeJkrnvSXcLPy8haaegjSs9d0dpxIEKRDGcHuR6GMnmVx+bwFkjkEANP4nhchcSGPivtz41hkI5EDkdeDOtv5YUEF4kf905AfraqIH+HlX8QuV9uHnEff/+10XexO3U4a52Ip/01BHZHAHJD+dk6zX0MG5t/laf+Paz8H6L8FmdHTH/Pjv3iPrlWx7WrIr/dDfkixO7jcx85hkRkH4V2ysqzjfC08zJ9whOiBoImgw5EiD7LZglcmI7lsdF8UyyPGbjTQdoaMqhx39BnPYWogaCNjWcGukw6znWS32GSlQfRzeCT4sIAXSb9MPhhQG+Cf6+PyNkU5Ufqn/n9POQXo6iPpaKv/OU10Q+kDvbHEJgQAq96a8zPDj0eirpVdv0tTT7E+MNbbYtcmQn1+2H0T/g7rJvp/3z1P/Q+Jl3diSrof8heDNn7q0me+QlTOjkH4b2ICkD+g9RwdkSB5V1o6ORujOfnlOAr8RvJx9+Ycnl8ULxJIpcureoSKqsEls9BrURD6sx4rT8JCPfKET3O3sFxICchK18EfhCsHpZW19kHVZC/g8o/lvPv2nLur43I6Wgzf5IIUK42Y/dJLJAcL7P+Puj4Eay8/ZEHv35igUx/V99+wRyDHyUPIdPmD4eVP8oh+dIkxy7pyIQc4HPuIpIyrF/LXjglaASWYb2WPD6OeQV4FNZ8eZRHZRc4gPnWo5I0fSpjHNN0gGu8XtPXOCtfPH74TiP3ZK6q8clDfkJZzUt+8fDw7Us23KeOXRvdM6FBaz9jCGxDgPL18HX3ScobE1XWy6S/tU6HsR9UG128KEX9QRfqdNP/FbV/eKGxQvr/YTK6EvE79N9kpuzQP+Pc1f9PfE5j0/2XXX8qmI1L8yIOsyoy0ZXG7RSYRPmBa7adOy29RUIG9nZ/Dnw/G2flPQIF49dvuZO9rsNxQ3twk5Af7gUN3ZTlF3tN1+Ku+/xfXh/9OrythQ2BaSPwqhvi86K2+13MCC/KvSo4fkYwGlP/RhtvuPaSTzmO5B13Yfq/9PYPn/s5gXnGrJZOenNM/3MSIFf+EdRsMOf+5/v/z+iOcaK237g92b+9/CiI3EOyHAdPT+nSYxoOGhLGjRsjaToqkIYnUB4Mdo5tSn8TFd/z/YNGWnnfvwXihxm5jYEnckHXiMim/RP29QTkR34885t7lp993h8zv3dstNwnjcgp6ubniQDljvKHo6Zul/vuU361rulYLGF56g88oG/sSX8EmdI2Faj/BF+7/4j93mbfAVLaVyWTP/ImHSOH9SdD5rBQiqnqC7I/hmn5sTN/2KguJC9MJ9h5lOcbtZhCx8Sc7OdL65fX/XnfIts/S/fH3rgelkY2pE05yU+u+PXdre95g/tbHCEhewF5b3OGQN4IUP7e+3+5vwPh+R7vPYv6C9P667BK/IZz6kL7lEYiMIvtnyX7hwOxO7Tzlei/yD1INpqFAnbAcJY/HehnXnWjO7cxwNly3nEfmTJhCj6vCazGw5cwr1lE0/Moj7dt20Xen7jY/Q/f/+jHPqbHV/OWnzz6D29Zd/sd97n3Xhd9BQMlnd3W8WG+IZA3ApRDyiPlEoaSb1OLXmc98tTf0xx/+O01THIN2B7eh20rm/2aZvvZXrpZaD/tPNtS+v6L3Tz5E+t6WDcRMocB/mAVAIKH/3jZI3GIx+dZvYAE8cyDJTIBm+G8yuNsOTkkuKj7Ky52/8P1P94EWuv1RNaSb/h6BQxcSy1/u/U/zui7t9Fyf/OBP4n+3Q8h8wyB0iBAucR5Xp/CHrqTRejv3cbPYcY/VuAGXX7yK7BTZbNf02w/ieJh8CtTebXzVeg/8qdJDHCVjQP/Fno/wuGlF/AH+GN8N5gCwYEuBA1hxuvAZz6mM41AMz/DjJ92eVSpgRnEZlH3532LbP+s3H8LR5BgfbyXt/xMGz+06a75TXfLu/8kuptyYs4QKCMClM/OuvsbPLHflaf+nvb4o/3BkVN96pcy2q882l9m+72f9mMXZBPy2WCZsvCPnepP/kQeddixfugfuOqt8f1RmWexIhQEDgL66rLXYTzDWiYMT6s8PzOGb1jKyw+sV3jPMDyt+yd3TP7a/RMc9tv/EPleb5DMCoR9Foar2H+Yabz9jLPcP978umhk306Ckv01BMqHwGvfFbdX73G/h72rskykY7mK44/ohvXHzM4RbHDgF4JG7Jn2gunvBAnFLItfiFMoD2F8WCYMh/kPg3+/4TZxysF6+Ht53p/32mv9sSz89x+4JvqV1u8gfkC7DlIcZWL3YAFLZ9dI6PwMFH2msUEM6wDQeE3LpTyr2vNEDmHec+T+HgmJ81CQ72kehtP6W/lC8APhibEMuVaI/ExRfrFH7meXbrq/NyLnB555lUCA8ooPhv895RevuiWrK2XV//scv9QzXHY1/e/tNySyavYPu6o7USvZzlM4/9hF/jCL+KDDDvpDzcytrMSNHy+5l2P6cPixeu438AROfDSCb5awohSGndIkHXnxbyrlcd8OvtvJz7cM64Gbeg7H2yfHx2XrGOTZVv8gzcpPHz/MyK1iZq6b9kMgW4L/FOVHfj8rGxO4PwzhD/HG6r9is4EYQ97HnCFQLQTi6NVvd08EAbp4WvqbeKTjXsfhBMaf2ib5/Yz+aDdlE/2S2oht90chTZPy/s9ONsbKZ+x/Dvjh816r4Cey2rEN/ynLj8hBcI9T3R9bhrYeuuo+tLIirxhQkvbtQlncd+GfnO7OwwBuC+vlQKDzT2j0Ga8/KrMpuJA4zeOv8yiPW3XYWOiBkRHIa/3PpHR0IrPklcgkbOWLww+jcZODsij5mYb8YjPHN/Ftvi8bkfODzLyKIhDFlGPKc1n1/0HGb3fgsH3ObbJTaAtM/xen/w+KP0hSsq2KpIr9SE5SAP/YTf7Io8inKGsHdWzfgR2+avtgFuahynzCoU/HimucXjMd68JC7pgmjfMzdpp3auVRPZwt19LPtuig1MbT1/9S3x2urTzRGSq1vPDr4TRvyM9GYfJDRTBB+cV+HGwzcl98/xuibyWI2l9DoPoIiDxH7kuYPR+oTmerVNdXcvzGbl30D9vhFR49JRdsn9oO1Yealr228kQrX/sh+x5xy0nq72nxF+VTCUr7/6vytu+Sy8txE2+GPpAF8fQiA5a+DmKNY7o2XsNMowPQQu4077TKt/DSAwcYHRusYYnw14wLB6FeM09YJgwzjU7zWvkEK8WIeNDpdTYsifizK344/6nXT7qNspS3/ExSfkHk+Gnvf3rfn0a3afvNNwRmBQHKdRPyDeLSJ4ljuyY5fvIe/56I8vw5caEu81G76y9ktPLF4Sf2P5DFstoPPOE/kLxK5Wq/PmXzQK7zdHceHr9w2DIGa3B7JWYaFQ6+MB/DGPDJYNfM+K1Jl8ebthG0iRwgyDVsdQzjCVLuH8YrsdCs9NOBqJGIs/L54IcO2sRyB7Y+jMpZXvIzUfnFYcDdLfcP/+Pa6OdsjzlDYBYRoHwPIOfQrt2Jjp/ATuQ5/ql/YJc2Qzth+j8f/T8J+yv2HzygCP6xL/nHQcedxx98qTWgJ/tTK4M192AwSVla5dMLK403MlJf2S9/lfH0+4hUAsdwHuVxblCbU6y8PzcgKoGTMF+2QDzPf6HP8+7UVwLHcoynb+XzxQ+gDzB7u16k/Ej/T0J+Ydg2mu7v3n/9ZD6qzHqZMwTKigDlvNvBJ8Ag9zMyftexr2lg9iOwhRWxn7T/5AFF8A+Oz33Jf5xsXTvIuD4QmeNbrHgyOT9knUrSWAklaQxrPPPyvzo2MJfyzs/K4cZhY5W4KWnTQcr6gdyheonTeF5rHFOsfEJ8p4ofv/KA/TfEuzD58UTuMPeHrPTjvvtHfOPyLrbFnCFQBwQo75jS+kfK/2HGD7Equjy3BGGVZ037zfR/DvofYE/K/kJ+8HLy0OXGP/ZpPzCB8QDyq2FN9x46UKEftN19IdgdEjUKOckbb4k9dJHGqR/G6x4KGRhB3mmVZ+e12q6F+0UUCs7AsT68v8YxTPLm4yWfxCE//TDeyqd4TB0/HEOyhSfhLeKvcpW3/Gj/H+b+ovR77l9sRo49aa5uCFDuG5B/PLkPqjh+2V86/uXt1j5mGs1+TF3/016r/oV/aPsdgQfo2OPvap8yPC3+ofXXe+1J/rF1jfxK67of/0Bkrj3v7q8zbryZMN5gCVWn4NLlTc9OGc+G0c+lPI4jYUcpu+fUGgWDfhqH+gsImP9J4zwqMMRC8sJ4Kz99/Kj4gfla4fKjy/OHkF8szf+r7ZHbj0qyvLOGgOyhwzjIXf9PYPyyL1JbBbsFg7DOt3JTm4B0sx8Eqdz2kzwA9rydK/84oPyRX1Hu9us8bdlnsb47X95U4MY4JWbwGUdP0uAJE2UeOu8zLs0z7fJcYtV1QO9zdk0Hn6ThQgYmI5EnTcOlzMRZefaeYEMvD/wGPbeBPkme5IuUH8iKyq36+5Tff7O3Vik15uqOgIyDpvvmPsfPYcffxMvjKzR9EjqxHbQNZj8qYz9h+DtVkL/+JvjVAZxwl/2Ue/5KvAhAzhDWBlYmxAw/gHOLY16I7fWR8vaIZtCb4BqzFZKX+TV50uU5q9Ph1Gq2hRx8NNKMx39NlilRXAh385Hy9pJm0Prj2spPDz9oyh6ehOWgziLlh919qPtH7gfvvTb6toqN+YZA3RF47+sxHlruB3nof2J9qPF7ivLY/rGBGYme2Y9q2U8cC9VqJJ/3mjr/OJT8td2Z5Fn8jf24LFXZtexZi+48MFxsaU0IHMkbiRgIjixJ8gd4zf98e0TDwtr8dR7lsaevhUP4IpI0JWpkagxj1ke21TNM8iZxYf19Gb69yjT+F9Zn5aeOHyBeV5kpUn4OJb+x+9l7/5v7KseCOUPAEBgiIOMicj8vu/3YbfwP+tBTZj8qZT/xbfaIvCAP/rGb/Owm/+RZw1Gzt9C+yRz4WLKe66fUWGmCw43eEvbXcnvkEeB4Qdan03C8nnJ5NKxDAibEjfcjawtb68NC5EDupP4cnPiflrHyueIHzbAJAt5NZaZA+aHIUEbTuuxRfiFnv37YmvsXeQyQH7E/hoAhMEQgijk+MLN1O+PKaj+kvqcY/9g314Ot2DL7kdjLqthPmHT5jvy0+cdu8rPb/VOeJT+0tz8hvdm1BKbfOKN1HgegDkIWCsP8QV5rvKYp2cvG67UazUmU9zyxzYGWHWxyvyBer5XAsSzLaLyVHx2sWVz0+rD4UbihHNcn0f9FyR+e+u5a+rH7p8N8LJl4mjMEZhkBjo8jt7nPwSYcZzvVRjBcpfEPg7vBIy7URrD+Zj9Kbz/liJJQ5sJwaeQPPEv4FoVqj45137P7o7/AK7Ot5Nw2TnSp0cyG+YNKzhgOwVJGmi0T/tZhy2O9t63kQu4fzrZ5pseJFiVt2bDc37+JYuUTnFI8p4QfZuQ2wKC5si2uSPlhBfZ7f5wjd6Kx4f7x5pujbtIC+2sIGAI7IcBx0lxzn8ED3MmsLfj/2Xu3btuWq76v5m2tfd/nIoE4IGFJYIRsbOw85DWP+QLHL25xkBBHIBsbsMAkL95+CjdLWL5y4otaiE1r6EskLc1J3NKCAy3B2AbThGQQQjpH57b3Wmve8v/1UX2smnPd5pxrjDHH2qvX3mtWjarqo2r06lX9P3pdBjTb9r8m9cem5euVf65z9I5Df6zqUuNfj/Un+GBd5vYhP2WZZdj4N0oHhre42NBtBea0k+cVpkthxDArdcoh7ErY46mcxeV8ujBrVxf0eqgDgBqdrAaP2dpG+cTb4ljS5Qhb3hwmLui7459kZqGND0fwvQ/yY+2/hfyOx2l2cJT+1y8+GdgzQB8uOBAcuJwD9Bf6Df2nT/qDWm+svzRu2fiVH9X1SuiP7vTHtvpbQOTA9QzNRriP8md4K8vVJt5WYE7PbOvljEjoR29PNUAjzq4dFcEk4jKIKgtqk15TXWzEsG+xgiNZAyfPMR3BKqx61ucHKWx5eZ6i/kHfDf+Eum3TQx/kp2z/TeV3tkz/pxTTt0y44ic4EBzYmAP0G/qP9bW18XfT/kef3Rc9O3MZv0J/ZH16M/TnBJzQR/xS6h/J1FbnzdEHNnI/9C+WdwTMXgSc6cgOA0h6ezGG+HVZEWcUQo7z69bp9WUKynOg5uX7NeCOdQ7k8ZOZ/bqsv+cPejh1ys+m+afPdWksr44iKfnv8uL89+vW5ad63Fperypfrw7/7l99dvDlTBZecCA4sCUH6D8CRb9zE/s/4xLjl8bFeVn/0B+rRhTnR9P6g/vupL+FE3qJX3LfMbkS3gJ3bdqdNgZzJ19LrwDaMGmq49WoFmXHNQVqQeuAPChcGEUcx0sQx3UX9Jwlg8DYSc+5fBqba3zqrylf++wY9aP+XBPmbDryBH13/NM3Vp71SX62lN+v/+pPp3+L7IQLDgQHdufAv/zZ9BvSH3+yZf+rZlTy+L1P/SMF8iz0x83Rn9Lz9nmvvuGXdfkHd23aqzYGc1oA/wrAzICcwBJMoGAHaxlJLkmnU5UWFCpDetv09tB8skPll28AxIPgKd+AXK4/wI04A3AKQ0N60HfDP8nU7ERHkZgAi//IzD7lZ8vyn42fpf9Nwm5WXpO9+AkOBAd24gD9iP6k8fdoX/pjy/6/ov+mg3SihX+z0B83Q39i9LG1dtnY1Af8cp78gbs27VCbgTkdSaKTkz/gbz7cHKULEOLViDDgzqxeUsooZ2NUjpNnrm167TkeUyXA2Xnl+5sTlaHTef0Je/3dbBv0ZzeKNM0/Dt7sk/xsI79ac/F/xIYH69bxExxohAP0p9lh+tf70h/b9P/z9N94pFkG6Z7QP/3Xv9I9Q611HPdd/0yEu2TmsJnDqzrZRmDur/wP6aWR5pgNOWLVEvIhjA8IIkxBWLa4xjegBLLK157P8uiiJXr1p4vLp2wv333PX9aTtPPqH/TN8U+iMdWq5anLxSb87438TdK/++LPDOzQU+odLjgQHGiGA7/2E4M/1iLa3z5v/O1N/79Af00X6UQKlcOEQ3+g+9f0fw/1p5051yP8chY/CXeBvzbpXRuBucUovY+bAd7c8fbhYXwaCgsXYSw4BvSUn3jicG3TawCwzQ/7Kn/fz3+TypdcPKukovrtg/xsyL83P/JO+s2y7hEODgQHmuPAn36afms0Tm+iL7rUHxv2f3vQi/SfjpM4Cv2zH/2/bfvJumqnXtCgfdY/jr+u6mG2CPCqTIJo38abEgKMoPLg7kOrTse3WgdmsizAG2m2EUGdsm365TSNJ4cqbk/l7/v5b1L5koWp5MfeYPsiPxvxT2/d+vzx//7kZ7SdJ1xwIDjQCgeePBks/vIXlv968DT917I22FRY2/pjo/6/if6TdY5ZB+lK061d6b/G6n+b9Cdm1JmOmdM5p33mn6buv00d7d9f1dk2ssxpbvl9pVXtvJuyVsBBHumAPf4IE982fTpMo32Wv+/nv0nla7A7c7jujaj/QfqNf/nXB28j0+GCA8GB9jhAP9OYYDvFu9AfTY4/jG9d678m60+r3pb6DycV6O4z/8Bfm/S0K8Hcq0+WD2TyvkuH4oYOmPza44oZWCuXdPsr3mY8L4LSNL2+z1GbTL2cLsvf9/PflPJlCp+p/WurnLdV3+uvnWp/9D//1OB3TbjjJzgQHGidA//qZwb/UedQ/lGpLxjTy2sqQVzPxo8p41zoH2GAjvT/ru0/Em7oofyYTLv8gL/AYVd1uCvB3P3H6X3c1G8E03RRf6lrpDsQp7cRcyVjSMO1TU/n1tZiM2vvo/x9P/9NKl+SY99gRS6odx/k50r+zdNs+iz9X9Q5XHAgONAdB+h32nk48xLpq33TP+eNH3ONc13pv/PKh19RfiU1l+EPfUpuDH7YJ37ZpP3AYdXTXPx7JZjTgs5q80O+x2KgjQ7VJ7MMwEloayBXKmYdQ7IkDR9SKoxrg16NNaZO+yrfBSHKr9oZfpzb/vO0mA3Tcd/k56r2kxz/1peeDN41AY6f4EBwoDMO0O/of23qj6v6Pw+7bfkyLhzPp1J3Hei/Nup/7vgtPrShv/dZ/5nW+oMfrI0Lw1Tfnl8g6/3U8TJ3JZjTO9G32YPpLi7Q7hPPn1+DgLVDxMCbgSvR8A20tukPdFAwD7mv8vf9/DelfAY42snr2xf58fqcJz/qRG/+2n939eJTnitccCA40DwH6H869uMN76fu9338YLzrQv85P84bv6L8q/HHTcAPJ4trgjnN0x5oC8MjgBkdB6BGGHROl0VQ8EHWLlASYMvrAM6RfJv0qoydL0dd9lH+vp//JpSvpgHmH/VRfi7inxTIcnSY/o0k2uQd+QoXHAgOdMwB9b8D9UNZURY3afzQoHGsscXq3Kb+u2j8Ir4L/XvTy78J+GEkHGZ47JKud6ll7vBxehlaBNGAmyM24qToHNR52EAfKlvO3wgIt0mvhaYjlTishbbj8u35Mi/28fw3pXxBuROXl7LOZbhv/NNOp3/3xZ8cfIs6hgsOBAf2xwH64eAg/Y7XwHUO1x7u2/ghRQiQO25T//X5+Xluq1+P8QP1Az9oOdmwb/Kzzj/HY1bnc34uBXPDp6emPZs+FQS3AkoorrA+v8I5c5aGZYywKW7yZdcWvR5gvM/yedYo//L2R2bU/kcuI/i1Kben/FPnfvY976T/z+U3/OBAcGC/HLD+yGHjN2D8cP0nNGNgri39F/qnGf0LjkBPdY1ftmm/Eo+d1xMvBXOaZH2fdRwoC6tcHc6dygSXdF3zllSn5zgruCX6gc6J2Wf5PGuUn9v8gvZX9FQLK08P2nVZ6IH8XNR+OvTzN3V4ab2LzmQ4foIDwYG9cYD+SL+s9UuPxw9jksY5nRGmzbj6dKGPeSR4+AbUv+/6/6Lx2/m/af3BEfvAL9vUX0Dz0h2tF4K5J09EuqymWWGMVg0ZSGORZckgi0co9ceZMiuCahytftqi1zkxI6uPyrcalx3lnPJlSr2w/kF/dfvtwj+9lZ601f5tyJ+WCLzxqz89+P1CfCIYHAgO9IAD9Ev6p1VFY30b/d/ujU4r3HXGr3L822X8pBpeftC3o7+HcxmF9oBftpTflw2XFXJZBi8Ec//pIL2oybORPSBAia85yOdMFgCbVUJ3su+hAaD0Z2nK44JHQW3Sa/fF0NbM5fJlJq2mezPwpHwDaEX9Lc8F9Q/65vmn9ueUqGkf5cfkg+8Jr8mvvpb9G6SFCw4EB/rHAfpnH/QPnNlI/1XjnxkRQv9cjB/2qn+H+qwXmqBD/LKx/Dh+keHKcNkFXfJCMMfHXb3DOHgzYKYb1fEKE8e1/5EXxV1fU3AGT03Tq50t4iYAAEAASURBVIwxYM3Lwr+sfAN2a/UP+nb5x5qRttof0Wpa/lTfP/i1zw6+wb3DBQeCA/3jgPXPQfoDatZ0/79Mf1xHf2m69Tj0j/SznOlpAnJ90r/6ju6orfbnma8jP04PLqs4d/b3QjCnGWTbyco3VZ35WN48DGBjyhWjhlld8r1J58/j2qQHuvEAXhZVWC9fmxPq+oP8y/pjsg76dvkn62k1xaq26Zv8rMuvRprFYKQ1OeGCA8GBXnNAffW3tElpvk/9sz5+wLB1/eP6T/VlI0ToH+lc+ITO7pv+la4aX9R+1LkP+kvcM1xGfdbdhWBO6xIee2ZZ+czxoGWYjoSzdXS68DR8B02ke3zj9PkTXraOQE/iK+zxy/I9nrgy7A8f9BKRFvinwZbpVRYAm2u8/fN9m5I/ceH3tSbnvXzb8IIDwYGecoB+OlJ/pXpN9X8fp9rQX0IwC9bOhf6pBApd0Df9qwrZlyDaaH+eugn9txyf4rKKk6e/zs/TGIVefXU50j6+h0TOXcJzDgdwFp0vzFOE+frJ0UbRFr0+wMwMtxVlD6FeYr5+yodSB1pxnmbR+cK8oG+cf+LrcVvt37T8sevs7rP02yvCEhfBgeBAbzlAfwUkmRLoWP/sMv4wHmaVUxke8oV5oX8a1z8I7lb6X4hCYEmTM6eub/prLFwGPjut4WnIZes0RqHJX9RXH3ReHEduQOWUdgSHrj0ek5vH+Q3EvPowYc/XBr0g9JgeIcuPmW29fKxsHofPA/pDrscHfav8W0w1xdpX+TGZLORXQvR7rz8ZPHU5Cj84EBzoNwfor/TbspZd6Z/18cPrcFn5jIfKt3C9FPqnVf1j2GBr/a91c45p2sQvu8gP9QGXgc9c3krfcU4Zlw7uVKY8vuJAgj+cZ7KK+EX2XYih8fQ26XVvM4l6NRzEyZSpo4gqR5iQg7gcXYM7v7Y8GQQGfTP8kzyctNn+ZdsRvpb8ae3N+P1hlVvnaVwHB/rOAeu36r/X6v96yK7obVw8h6mhvyojzL7173iRJl3gl3UR2Eb+HJ+t38Nxz0r8yTS9AIArCyDMQxo6FEjydI9joacvjsM06en4KPWm6QXQRnQAHsDedAjY3Kl1TIsrO0iZV+EBNGUcGyWCXjyADdnieR3+zfSR6T7Lj8snYqsp+9/94icGR/bw8RMcCA7cGA7Qb+m/XeufcvwgvGn5jIuhf/qrf9kE0QV+2VV+oNMR1C+c10HPBXOHWmSHkuMzVfjahVNPZXLtwIx0BJM4GIBAu2AT1yq9wBy7gyjfcBhrDhRwYEcc6dmv6881IMXTg755/onpCy1Onrfa/lm+rit/LJ6ejtO/1+3CBQeCAzeQA/Tf2UJjTpf6R3zaSf9hRWRsFH3or/7pbx0fMkSOWscvu8qP6AS16s2puqwdMnXGHZ+kFwBngDh8/Teghu+gjTCgzvPYmwn5cp5W6ceyyuWtzZSPJQkgh8Pjmj9PU9DS8T0vYUCd5wl6MUSuCf7NZumk1faXkDUmf+P05S/91OBZ9fTxGxwIDtw0DtB/R5Pq3LlO9M81xx/pHNvVGvqnf/p3LFyhUxhGfdZfkp/NLHM/9GR5R5PGh77rwUAamlOOjuKOsCwwBvbIw8Pzh6XDaHLmNugxhQI6SiDmAI4OYsDMwZ2hk6rWOcougr49/slUe+LC0kb704BNyd/w7fQfKumI3+BAcOCmcoB+3JX+gUfXGX9kSNBHLNobf0P/iblZ2RsvsNycRtXhi/CDwIXMRZbNjFi+fCxHWcJ12p8bXIde+OcQnFbV8PS3xDcWO34hPQaQaSGiTU06OMMvw+A7+3xXvpcp7RzXNr0eRoc1W2dQsHJuWVMD2WGEXn8Hd/hlOOjb4Z+2nGApnTn/S5kpw/uUH+ph5Q/TH3/xyeBbLkPhBweCAzeTA/RjGRf+GJ3Utv6pxw+V5dzaSv9pfMTuga5y+tBfFSf6oL/BF33XX8fCaS477p8BcyfzvJM1dwoy8sZTAjfieFjrNLLO4fOHQOOT7p2KcNP0fI+V8gFnoOt1oEaZLhSE85Rr3XEsPehb4Z/a+hj+ttn+3n7Xlb9JrJWDleGCA88FB6R+/n0X+gdmXVf/2ee9Qn/1Un+DL/quvyYZp5Ud9wyY00fRV+ZjeSimU72TuE98+TbCTUkjfqWANujz5ochtko5f8PJ4G6lfNIc8JGXPE4T9HCiWf7JvK3jlE5dL+WH6g3T2//0JwZ/fFrTCAUHggM3mQNf/JnB1+jX5TP0ePyZhv6pWqp3+lv4wmWot/KzhtOo7xkwp+lHM985aHPfn87BGvFY3Ign7MDO86/7TdGPxGjqACjjO1E8AGHvGA7W1n1/0FJwgr5Z/gkl88maGYLVVvs3JX/L6epho9Q5XHAgOHCzOeD9uu/jD+Ok9Kc2T4b+6pv+zvjCjEIuR03hl6b0l+O0src6xqni+HbCID1yYOYZeRDhJnPKwXKzamGgfI8H2GHBK9MI45qkdzDm4M0qozLsA6CacqU8TyOM4yE9H4DD4nLreHzQiyvX5J/ahhPOa9kgjGuy/RuRPx0NcO+l9OWqdvEbHAgOPC8coF+PhrVassfq3fijWmUdOw39U0le3/SvQFdGCD3UX8jPWF+BAK8VbgXM/eW/kx4qdViiUduxCnEm0nzyCmL1e5G+nkZc4/R8xktObzYG3Ajj7EF05hxhT7M4FuR7OolreYjCBb2YsMabbfm3bpVrpf0bkD8JyVdf//RgZTrYhCB+ggPBgRvNgdyvv8JD9HX8oW7oWFmk6jEo9I+Yck390yi9wFyf5UeyMwCvIUvuTIb84uBh3vwghekgzNNkD1665Q3fgZvHlenaatoePYgZC1JueLcm2cnIblkiLYO4uv6k5XTzg96Ar/OkCf7pJEwbnFptfzXodeVvOkr/yeUi/OBAcOD54sBBSr/PGOGzRjxdqZ+uO340Ra/1KLMmx1+/l31GMfSfGXFcskv9ton+VxsP+y4/jtf8GVfAnA57fYCgIviANRdafAhQ0k6I79t3Pc5p2qQfzItvsgLpSucgDtCWw7WvfP6t0Jok6Bvjn9p+xuRG3+VHD/zOr3128I1aBiIQHAgOPFcceF39W7ME7/ZRf5WMlj5d2LjpkaG/KiNMH/T3LE36Lj/gNRcd/BUwp7Vm9yyxWP/m1/j2dpMBkAE82SENwCnOfc9v6Xahnwxxr0vPbXzNnKFrak8HoE7uUybzqsS6ywsTDJ3n+ge9+NMg//R9xPpsOQd1zv6m2v+68gP9cBZWubpdIhAceE45IF12an1vSP80Mf64AcT1J+Omaa/QX5UeRx57oL918P0ATGPdo6fyU+O13IdXwJzi7tsDMFmcnQufX9e+HtAAHFY75bd8GdzVC+yUuUl6Mfi0vjR4fpPJoOQUnJzmIs8pqKsrr0DQN8o/rUCzrz70WX5o/md30ldKMYhwcCA48Pxx4Nmg6udN6p8VLjWl/xYaN6uX6tBfFR8GhZbfq/4Gb/RZfmR9vtgyJ9Rzn8rbBgIJq/kAO/7k/HrA5gPF1XlJzHnquBboNcWqmWwqor/cAVSnynGNq+pveSyN+JxWXwd9s/xjh/Oksr+12f7XlT8BzT+J77BaL4mf4MBzzQH6Of3d9FJP9Ne541e1bm7hOir0l+GPXuhvwxvITl/lZ5FnUnNPdgikS21zXaY7VNzWluEPKzOjgTfl8DVn7KQweuXJz2lAz0FeW/TjZbFejgqo9v4ABtQySLM40upEq22dt7oK+qb4p0FzxkDVdvtfW/60i7Vu+wgEB4IDzzUHtAPiP/OAfdFfF41fefysjRShv9RoPdDfmgq3kzP6Kj/LcbpruC33Yoc76bUn6a62S9s1a8t4AFfQS4E6e6vwjiEE5+nchzDAT8Y4c23RC6uNa6ucLgzAUaLCADewHM58T+eCtDKRp/T0TBD0u/OPLfZdtD9NZR1rB/mT1XkxeFoN7twnXHAgOPB8c2B8nL7K0N8X/QW3zxu/8vgZ+iuLo6lq189c7El/q0FGtFdf5UcvAYPXhNsy2yrwxsU7D9I9rGwOzIhDQeO70+aDlQcjnQf1h22dnknWomFVvjW0x3FJj7B4kiyCyMIFfQ1sm+KfXgLmgP3W2/8a8qcXjW/oY9xHhSREMDgQHHiOOUB/10tcvXN97/rrgvErj5+VMg79VevtvevvcT3xaL2kj/KjVXPVplXVsIY7irnvwAxAh5Wt9MVYA3autHk60vnzuA7oh1jY6kqD2vVXx5HAH3HySt8Fo86b04P+2vyDpTOAXAftT1sbaKT5tpG/O6OYYoVn4YIDt4kD02n6KuNET/TX+eOXxk+prWrdXOivFb3tenwv+ltr9B0H9VV+VL/73p8RHXMn83QPRcl0FBEoZxy+P5BFeGSOJ83ztkm/csZdrjUV5c8fAlShB9AjnMblvpGfihS5oDc2NME/ttZ30f4MyFZpfnKByN6m8rd4If1hTR+B4EBw4FZw4OAD6Q/7oL+uGr+0Yp11x6G/eqa/tWiuBnR1h9lB/1zV/tx7F/wEbvN6OQ7i+j51BDS5kiSSs3WIJ64OcyFHfH6u+rot+oW2CbNFw8AZKESOcPkAhLWbUnw7xW41jeLqcNCLG83wT+ZaHWReub7Kj76z99YXPxFTrN5O4QcHbgsH6Pf0/33rr6vKl0rCOhf6q2/6e5x0Qsn+8c9F8qOqnbXM+QF0DthKkEbHd0XtYb4tR16u8TO+qwFf0/QCiSOAGuUh9FjgAGdc42d8VgO2EuSRxzuKh4O+Gf6pXWZdtP915G+S0tdo93DBgeDA7eMA/f864wcca5ueHa2U4waH0F9w49TtTX8Ld1CLttt/V/zkuI061jKj72qauQ7LWg3SBJj8eh286W1n4Gn4/sUHj+Pm0Pj1denZuVGCN74EAbgjDp/FiZTpcYQBbH69Dt6C/vr8Q3j0MdZZF+1/LfmZpj9GHsIFB4IDt48DC/X/a40fMla0TY9lDh3m+opWCv11yo996W8dJzMCD7Xd/rviJ8dtyIuBuSdPlsPxVGvmBH6oOCjUfAWI43rET+Eo3NMIG2hrkX5cfv1B9UDwaWBD7N4JdO1vNuYr0fP4Akp/hKC/Pv/mepscq+27aP9d5W+uY1O++yR909s9/OBAcOB2cYD+PxyfLgfh6bvWX1eNX6hXxtPQX5VO743+lhGpD/jnIvk5mKe74Ddk2n5+7366O18DayySc9MfGee6IAsAjgQsZUQQz59b88hrjngPy782/TSNqCzgjF0P8u2zHywatYWj2TJXF0l8fVHlCfpm+Scpn3XW/hKmXeRP5tqvP3liyygLaYhgcCA4cFs4QP/XR8m/vsv44Ty6tv7aYPySgaFef4zyCv3l3N+j/s7TrF20/+nTKrQhfpoKh4HfoDUwNz6szpgz9KebmMVNko/w8wajKLPM4RNJPrfKWVTO2yr9AXsz5FRjrGxucbMo4kjiR5ksLcdhgYOOtKCHERUvmuBfBesreUBWWm1/FbCL/Knxv66qhQsOBAduMQcOD9LXdxk/utR/Mk/MQ3/1S3+PtQGiF/jnEv0HfqNr2+cqjk/SPX0qy9acSSGzyWAAWJOpU1jI8JuBN8KslTPrnPLo0sEe69dao2cKN9dlqQoNACIUbeVXYK0uX6CNeMvj9QfjQWMJQd8Y/9Tm8zzY1fzvm/xMBzHFSj8JFxy4zRx45zh98+5IU3h70F+86KIz0T+Xla/1WTObfgr91Sf9PbQlZPr++FXtR//ah/4Dv1E2OCeNB+kwbzAwoIZJEaEDoOFzjbNwFaytc1wirG3SL3R4H+UA5My6prBb54jPYM0AH6CNaVfyUn+jyURB3yz/JN02LdB2++8qf4L80y/9bHobGQkXHAgO3F4OMA5o598sq7JO9dfG49dImC/0V//0d8Yf+8I/V8kP+I2ebZY5AbEDpsjMGicrWF4cWvd8rrnwtwsP42P9Ih5E2ha9Fq8CimvrmofNV/mqnZ3wTUfQn+1slV87gTi7It1upBTCQV+13y78U1trva7Y2EH77yp/2pyhjQ+C9OGCA8GBW84Bvesvl9/UaPDtMAJdhd+r8Wuh5d+ql0AD+ql2ob/2q7/BHzQHbeP4oU/yo6n5A4TFLF4SnAOvHKDOEgBJch5fxhHGgVSxfhH2fG3QqyK1ZY6y3GFp8/IdnNm6OWUgjXweT9jjCOOCfnf+SapnXbV/1VqVvHkY/6ry1fZvlPkjHBwIDtxeDqyPB1eNH3DK9Rph8uO7a4Me6yH3d10V+qvCFyVPnP9d6W/HH120/y74STJyCua0Xs4uYJILr/vE6VgQc2UcEevXZVyZdl16PaCDzuJ9ZRWoWQX148LvPvHqIObKOCLWr8u4Mi3ojX2r/MIyl4F8lVr9epz7xF63/XelH8SRJGXTRDg4cKs5sD4elGOUM8bj3Cd+1/HH77kVvR8eXIytoX8qTpY6mZj16zKuTLsu/xx/lDJBWevXZVyZtlX7rxnHuOdV9I7fKpA0SgdCnStAiZu4qxcaKMJv7Gnut0nva+YoyxvGy3Xfp+L8uvRFX7ugr1mxEtiWf7KIFly1t9ZeyY8WrS7f/Z6wzK00clwEB24xBxgPJhfouTb11zb6c31cpblCf50K7Z70t+EkarEP/HOV/Ogg4FPLnFAs06wDF+jSL8M8DB+DxSfe0yy+RXrWNTjYcMTNtcdRPhsw/Lr0y7Dly8iXeE8L+u35p2/lMs1aA7i+yY/OPXz3S3/JdpXTvOGCA8GBW84BxoPZIL0DG7rUX14e/lX6Uyf62wkB5C11lOuq0H+Vzil5A6/a1P/gD9d1V7UfdfG8pYx5XBv04Dcrlx/NCR+WhaCYiXefsDviPG+Z7nFU2uPdd1r8Xeh9zhp6Gk33MBBBmDicx9HIHu9+laP6Dfpm+DfSVu2yfdts/7L9NpafRexiLfkW4eBAcED6Y5be8bGqj+OXNm3NXW+5X7Zb6K9m9Bc8Lfl7GX4o8cfG+kf3L+XL27ANetXvdDerbIhjvlnhhQPIMO1hUsy+ATRDl4p3U6ejTSpKXFv0h7o3jLe3E5XviwT9bYXylaVuHOLZzku+7BvAC3qB4Ab4N5mkxXRe7bqC97g2219yuL38pfRWVbP4DQ4EB4IDFQd0fMNbmlV4hauu9Nc24xdTqofjNJ9ONaSG/uqH/hZAmvrMo9qna/xzlfxoat5OJRm++mR5gBnRhFtTqP7WApADnOEDAGrBz/Hkt7lcpbljnVIb9Cq7nkIFtTmitvNXivLZ2ao6m9WOjkA+A37KUwO/oL82/9TuxuOu2n8n+RsEmPN+GX5wIDhQcUBnY77lRoe+jl/SW4vQX/3R3+CPfeKfq/Qf+A0cx8K+eicrQMnBm9/ABF7xXFtYQUAbXcPykuauJXoDmyrfD88DtFGkAbW18h28UV+30JnZLugb45+4L2521/7eftvI38HTmGaljcIFB4IDpxw4eKzDgzvWX9uOXzrAcxH6qz/62/HHNvqH9gMAdoifDoaPHuUz5kw9mzVuacKXQZLZ7+gLDtRy2CxgJU0ZhrYhesFNPu0x4H4G1Lx8OqSXuR4uys/VsPoEPcyTE1PMgroj/4Sk7XDLmv+Aa78X4YL/+5CfxTjNXn8yeFo9bPwGB4IDwYGKA69/evCU8aEr/bXL+Mf46voz9FeWXDFiX/ob/DGc5FlKqoP+XNd5e9Z/j2SUG85ndizJQLv/TCFjUrSKqs7mq+I+fVnGk88fymhaopdZfKBveNn0rU/h4ts3WGFqDitfVX+BvzIfdQz6hvknTnfV/tZ+6jjI3qbyJ3mNT3jlMTC84EBwYJUDjA99Hr80zhk0MD0W+qsX+hsL26b6p8y3i/7ahX5+TzhOAnOA6Dgg40aEAXAWJ5+uQFhyZQ7fAR7xbdJnwMu3WFfLzwDPQB31B8SxkzaDOwCcxcmn0kHfIP/YPp/BVdvt74K9jfxpAegzE9T4CQ4EB4IDaxwYzdPTPo9fWmC/CP3VL/2tJVu+7wF81hn+2VT/geOGynyAVQ7hRuYdsAGiPI45Y78pPmnEkZfrNunZFrxcs7ZZ+RncAd4AcQi/qrNa/xwX9Gq/zAv86/JPbymLrtqfNt1W/nT8QEyxwrhwwYHgwBkOHI/S016PXxpfTf+G/jKd3gf9bUu9JEld4x+EdxP9NxGOGy4n6cAAnH7wESIqTJibyDNQx3w1acTzRx5HTlwTxm+aXotVbZr1TPkIuhVclbtSvtJIQgioGkAv6Nfa7xr8k8BUa+Yu4v+e5UcvIe/R7uGCA8GB4MA6BybT9LQr/UXZGEXO6J9L9KesQPPQX/3S3/pyiJ1AT7vw1zf5WQjHjfWx2gk2Ld8pavpZP3Y+GwKXnadz6aDOAmvpTdNLqodaDlrXb6vyASxr9Qv6LdrvAv7pzB0Dy120/y7tNxuHZc75Fn5wIDiwyoG5xgfbmIAiy871W9P6a/3+XF+pP/2c1AvG3yvpXX8HfWP6f6oZwrotFTA56ZH8TGdpoqVkp5WkgkyZGpArhI46c8yHPUAOy7PNB8QTxrVB74j43PIFKq5VftBvzT/47TxnytbDbbU/MrWt/B29F2CO9ggXHAgOnOWAjw99Hb/Qv/oShC2HuXT8C/11Pf2zBf+wrNIWONd5fZIf7bYdDmUCHgLgqCiV82lNWweXgRrTlBzASxx5PMw0JvnbpFfZthnDy8S86WGmgVfKV5rVX/5K/QuaoL82/+xzM/C3i/a3zlPI3Cby92dSgDn4Fi44EBw4ywHGhz6PX+hb1e/0G62hv2qdvy/9nWYVTtpE/+T2q4FmF/gJHKdNgpVlDuGuPgoh4ZcNGlBkQEmCxTVgj2sP6+FqSxzdpS16HaBoBdXlK0AYcw2+leu+JehCfl1/dQSuSbL653DQ78Y/NpvAy67an87jMreJ/GnZwMmTJ+o+4YIDwYHgwDkcYHzQAqgTxrEV/eGHwvVA/6GfGO98bVbor/3q7yFnze0B/2yq/8BxQ22bqY/8MOFBeQqoIeR+I4v3azqA8tixHwDADOroM23QD8en1jcTbMoXQOOoCuuIGdTV5QPeFGf1z0Curj/XQX8t/onviy7b318sanmk/S6RP+06OqaNwwUHggPBgYs4oHFsZvqjZf217fhlOld1koll7kAu9Fel6/ep/7EGWduoaS7TP95+tb7KLwb1dUv0uv9An/RVNXkjAcBpA4mFdWnWF8ULF1UPwfI/XROvBaRVXoVr1xI99/dGpHArXz9W17pwBQBw1J8Mcubpx+qfQVzQX59/mIyRgzP8b6n9t5U/Wea0VjVccCA4EBy4mAPSKbz03atz9GT8cv3LOMvBZqG/+qH/7ViMPeCfjfXfURoNR0J0+gqEATUW9gGCECTiHGUiYKbEc5wBJYUtTvlbpedpVCDbuw2wybfyFW9xlO95vP7KQ5yBQE8L+kb4N5dlrtP2d9kERG4gf0yzSiTCBQeCA8GBCzkgnXXSif7acvxibKVeM+mr0F+Vzu+D/jdUvYH+8fbrGj+NDjWDqUXsZplDgFjQTiXwAXBMpa70BsWR5uZGwiPFOdhrhd6QQ66FwuUBeoTZZeKNzTUgDp84pmJX6h/01+afwFI1/S7GdtL+ZQNuJn8B5kqeRTg4EBw4wwFe+no6ftm4ylcgQn/1SH+DMzbTP/vBT9oAMUag/Q2F+jKF6teaShPc048CtkYO64ic0cgjXhsUBr5Vtw16wBoWOATbp1sBa1amanOm/Jyfetb1V76gb4Z/AstLmUY1FnbT/lvL32FY5pD9cMGB4MDFHBhN0rFORVie0R890X/oOnScjX+hv/avv8FJ0n1IVJf4Z1P9pxmz6mgSKkclsbiZhY5dG7nSZZqHAW0eRuA83Aa9hNoO60O4zeKmsq38bHWz8nPYOgD5vP6Kd5qgb4Z/8LvL9i9ly8OXlq/pE2Q3XHAgOBAcuIgD0hG2trZt/eVjFrrRw5eOX+TLBhJ0V+ivjE32rP9txi/jpE3aD7mjvb3Nt23/bekxtslgJdBbCBo3QcDNz+COMK622OV4r2ir9GrEqvTKQke4Bm0O6IqGJr2uv+J9XZ3F53sFfcUXHyjgkYc34l+X7a+yqBNuE/kbzm11Q0UQv8GB4EBw4BwOME50or+2HL+oauivjD/6pr9zW9ZGqwzuWsU/G8qPIO+IA4PtiI9aUWYgZ+avshMARwvHVtuSpgxbtrX86/fblJ7zXex+Zp87rcByfArU1sPn5T/9zkV1j3UaB33EB704sMZvvy7b+aKw8a+h9q9aS79r97tIfgaTAHM1zyIQHAgOnMsBxok+jl+Ma1SYtckrFV8bj0N/dav/19cvXqR/vP3W9dX6ddP0ApiyzHFycDbrIjx12HeDZokya1YWNCpCPpJ4i6hp2qDPQqy3qKUOUjEBN0Ge5fIBdQp7Wh3WgjlZm+oOEfTN8a/T9t9S/vSNurrNM2l4wYHgQHBghQM+TrSuv3Kpu+jP0F+nY/m+9beBr33gn03lp/wChM/TI9y+5sw2DeQHcPDGvd1IUuZtmx6Qlp/LjUSckrdc5nh8rss4AdWBW9qCvjn+7aP9N5W/dBCWOe8n4QcHggPnc4AjlrrUX5uOX2WdQn/1R3/v0n5d4ieWy40NhI0qBMwiPzvqQ/KPUNENUNwE3BrDG4Yrc9LtOke0QT+RBZCjegyUCbDxtlKjOuJ1zeGKOH3NInm4ttQpnvoHvdjQAP9mfs4cDJdru/23lb9xXhdZ1S5+gwPBgeDAWQ4c2tDVv/HL9a+OwTCwia4L/bV//Y0EgZW6xj+b6j+AI6fM2UQmFXVBosJeeQAawA5kir+ex6/botfhiZXFLVveHKy5Cbq+VnodztOrWOsAeGaxC3rj4zqP6usN+TfJU90uI223/7byp2/HciJNuOBAcCA4cCEHfJzo2/hFhRlbWTMX+qs/+lvNMtwH/tlU/830JS++zWpgDgGCEIeA+02qmErAPB3fO4HHtU0PeAOY4UoLnMeV6QAU4t06B02ZHvSnFsyt+Se+7qP9S/m6rPw7AeYQ93DBgeDAJRzwcaIr/bXp+EWVTf/qgKXQX5VRCZ7sXX8X+Ogy/VO3H/gjz24St3X7b0mvb5LrCxAqxyqgHwdxdp0BnYM2j8N3xxZdD2MObIPeLUeUU4a51gPU5YNIHcSR5uGSpgyTJ+i3559v54d/XbT/tvJ3lM8lpH7hggPBgeDAeRxgnOjj+OXgcjiprFKlzirDPFPor+31VykL2/Kv1EXcp0/yI/yzGB5obt4qhTVL4IwK45cV9XgEzcJ6EMIcVOf5WVzn+fD5c8Z5/C70mt5dwnQEGSuShWEkyJV5YsVbo2Tfr8uGCvrm+Gdt2WH7I0PbyI/eTszSDF244EBwIDhwHgcAc13oL8reZvxyfQqN1zv0V3P6y3hJm2yJH8aaGdwFvzTR/pvIjz6ruqgtc6XwcLbbiqBnqaqRqYDT+jk4bdFPS+ubyjVH+YUJk7gSvOn8oMEK0KuoTi17Qb8z/5ANgHtX7V/K1SbyJyQXYC7Le3jBgeDA+Rw4kOWrTCnHmT7oP31VbOiGCa8n1+ZCf+2sv3blHxtAN9E/3H8f8qPP0s3H82Waq/ADLQhdAuBMqBHzYhl5Ha9oCVma6a2hjKPybdGPVBeAmYM1NDXzz2Uc4M3OofF8ZKrfa4K+5NV1+YdAn+gbdV21v1rSLMA+2F4lf/N8Kjd04YIDwYHgwLkcOEmjRT7FoU39RdnlWHnV+OX6F2OFH2Tf5Ph93fH/ttLPdaQGuGPT9uscPw1lmTPhyYifMJXF4ftfGS+Eam80TH9aRn7apBcD3TRKUVoIaeW7oBPn5Zf5EDr/K+ODvhn+ddb+asdt5E8DM80eLjgQHAgOXMgB7co3PWIZ2tRfKmCb8cv1L1UK/VXxoA/624+86hz/bCg/JmMSGlszhxBxnpu7MlymuWCW6efFlenXocfiB70bCr1h/Zr6nhdXptMp/Pq8vOfFeX7uH/Sn/ONI3rI94U+b7c/9y/LOK6uME8gPMAfTwgUHggMXcuCENXM5tRw/nKAp/cX9thm/vHyO+vIDXUP/nOqf83T1eXFN6++pcAjmq/Nk5by4ruWHcxOHmsZcIGyanjJLG5XgGuc+cb5GrcxL2P/apKdhWIAor3pbKcNrceT1Tup+0DfHP94Yva297UuZ2Lf8HM3cTquKhgsOBAeCA+dwQGe4ac14N/prV/0Z+qtquD7obyF/wx+lruuT/MxGUstTITqUM28CXjmuAW8mhIZHNZOpdFjreT1MHo9rgx6wSVmar66mdwXkOEiYOJ16rGpXPnEIv/0pHvBnQpCng4P+lGfX4Z8MczC2loW229+n0zeVvzt30kRVDBccCA4EBy7kwEDjBHqrb+NXCRZCfwls90R/O7B2rINg9Ul+sA7qe15pjnIGvGkzhP25skawWGOGQqXiXOPcZ8qNtLbpaVCAmzPUfZvyUxrgBPDGOi7+arCius60xi/om+Ofpr0N9JsgdNT+28jfySzAnLVN/AQHggMXckA6y77i3IX+2mb8QgejTxln0XOhv/qhv9lg6bjH/a7wzybyM8Yyt5xU34AzywdzaPqDmIoC4Cxsc2u6Jl4OH/Anq1l1TAVhrDVt0M9UZi7fF93jm+WNzRhKszDWuly+oXnVHwBo4aBXo4kf4hvtdx3+cWhwp+2PzOX220T+JNQHPGO44EBwIDhwEQcOBmnSif7acvxirEPnah3YIPRXj/S3vsixif7x9usaP6HTtflP05gAN4QOpzAVMkG3iOrHBd+u1pRrm/Talm31sl0klIvL5Ts4ofwyTLrvOqkI8nXQV+y4Bv/E5wo0r8lMj+Qnplld6MMPDgQHzufAXNOshc4rw33Qf5oxqyegeIDQf1nvwIxr6C/Id6G3M+bW8EMpM2V4H/Kj2cj5cHgs9OuVLB4Uq5yQXm0V0XSrgT5jRgZ8zpQ26bEA1mCNcnFr5deHKZLmDQ0I9HzyDewFPRy6Fv+0WG5Y8zXzus329/bcVP60Aywsc1Urx29wIDhwAQdsnOjh+FWPd8w6hf461efMKu1Rf1vpF5TfB/035OxXlCSLQBEiA2+FANm8fQZ0hNf7hYO9Nuk5qM8EnI637nJdbYdE7phlB/COEfRiXEP8Yw2lN0MX7e9lbCp/y2mAOW+f8IMDwYHzOcCaOR9b2tRfXsam45frL9bNhf5S2zkeaUh/rUjDFvhhVug9v4e3bR/kBxw3nNrCucoKZ5XKNbWtuDysX2eTNODKt+mSZNfE6a9NekflfB+tdHZNnP7WklYjcmLQl9wTizLvNuWfds3wqbdqSl636qr9reN4eZeVr7UwT57Ue2VWHzauggPBgVvPARsfNE7AiN6NX7l1+OrDikIL/WWc2Zf+tr0DLi+X6Z/cfl3jpwE4TpsHODS42j2TFTUCbnUSGgagoUjNSqeHYCeHKfQc59eW3gb9KE/vZmReA3SEWxf1dRGuG1xx1gdyXp6pzh/0O/FvIvN/p+2vNttW/n7vfrpLW4cLDgQHggPrHGB88DGldf2lwr0sFLyX53F+va4/ldcsc6G/xMAe6G8dxmtGLG+vq9rPZE5goyv8ZJ9YFWpbIGRWuYw4tYvGptKI845A2C1vWoxp8R7XJv2Q3aw4NagJdhW0qDKuDNcfxHWCoG+Mf3pDGXbZ/lVDVwPipvI3nqZ7Thd+cCA4EBwoOXB3UL3sdaG/vFwvi+tNxk/G2VrhQRT6r2ZHrdYLnpT8aUP/j6Z5OdqG7UeT0eb4uG3b32mMeAP6QyxzB8s0dXMVqBNXVsLjiPeFfh6HcrVwNnd5fJP02txgS+Io3xvJrWs0qoVzhMfXre7pEMsFfeZD5RmbduGftvUb2O+i/V2mqPKm8pcO0538iOEFB4IDwYEVDujTTGa57+v4VY55tU7TE4T+qprRedKl/teGmcWm+qdJ/FPKwqXlC8cNtdByOstQ198Y3ALiPcDj0f51WIleUJv0TPnWZa6VXzfqWv3zpVf/tM5Bf8oLcWdX/mka27bNd9H+NOJF7X9R+dNZWOZq4Y9AcCA4sMKBQR4fLho/9q3/TvL46pW+aPzbdfz2+wZ9xQlfluV8Pg8/2NKzNfzQJ/kBxw1PRulE66AMMNkZYno+rySP6g9YPfbpbxnfJr06Vm2ZOy19tV7jtfq7kJK/rGfQn3Kg5Mu2/NNiy3qqlTu22f5lPU9rv9quZ8rPb95l/ggHB4IDwQE4oPVpd8tx5cz4UbCpzFdEr+iVxuk1vnpZm5S/7fjNvcv7Bv0q/jkPP2ideD1lus6/xtvfG3+tnYrolfajfHDccHSUTtgG7Q9AI1Nx94kH5HHeG/GEaz/HtUmvQ8MWdfmy0ln57lO+wmfKz9Y80lbq73TuB/1O/NOb7dDaoYP2X2m/TeUvwFzZ7yMcHAgOFBwAzPV5/GJ8Nf0b+qs3+luAd17jHtdDfdJ/43QyXt5N04HMh/NqAYExD9McACm/H5xa7bSjAzvZqDLdWV43SbZFbyBS1aHzaV6wKr9CnqvlUxGlW5J+rP7ViWin9Q/6Rvg3OJBk5IGm7fZXq56234byNxmn+8XYHcHgQHAgOFBz4FDjg7/o93H8Ynw1fRf6izY7Hf/3qL9tfhDc0zH+WXn+S/Tfcp6m44N76eTkPYEgGXYBZHx7EwTKTfRXV36uOMsDKtXn43Iem5PV87VGr3LS3UPtpFWvA6jx2Qx7q5Jv9VOklU+a8nCorc1ve/2hUx7ogr4x/o20rqNyEvA22987zzbyN12k8aufW9790k8NnuVahhccCA4EBxLjgvTEpCv9tcv4JQwnFZf1W+ivvevv8SQtn2k3K0Ys9FCX+GdT+QHHgTV1brAqKSBnldVRINnyZl3fdbaPA54H6x107tqkzx3P3lMMmOnTFRS+Ur4LvdJ81w91O1N/EakzB/01+KczbYZdtr/LGP6m8vfyPD1U9gBzJfMiHBy45RxgXDjCENCh/ipZvsn4NTnQp9HzCq3QXyX3NP7vQX/XwF9V2aT9yOPuTPspTVipcflTedPh658eTCU3ehGoHBWh8vwB0AbZzw9haVZZpZFOZdcftmn6GQCzakQ7sdvAmgrGEmflu5VOdSENyxx/pHNyM37QV/yy6QXxCMbtzL+hwFyH7V+8KGwsf8+WBuYqoY7f4EBwIDggDjAudK2/dhi/bHYp9Fc/9LfhjwqEbax/usRP4DdwnGFIHRI8k+0Q07M5Tp92AVSE8JwBu0EGepYnh20NFvnJ0xa9cOxcgj3KQK0qP4M2pSUOOc4LRqv669oBnNVfK7x0PQh6A7rX5h/TAJNJGmjqe8FrQNvtv4v8ac0klrlwwYHgQHCg5oB0wAMuutRf24xfjKUjrQ4P/VUZYNRUptv3qb/n2vzgeMgxTq/kZ2Qfmqi2OMymMtFJiBByNg6AKtl4wAMQZo2a72b1dIvPNORrk36EhY2dI7KyWfnZ8uZfqkDwPezpVn/FQ1PXP+gb45/WpfGNVpOZttu/bj/J4qbyp7rZoI1MhwsOBAeCA3BgMU+P0F1d6q9txi+9II/QWaG/qhm1PujvGn9soX+s/TrCT+A3ZNvOsxHKPC5BmyVIUVMhwli9XHEzQ+cOGsLka5l+7mBtpXwJfV1+AdqII/9K/XVNfNDDhcrRUQhZ+23JP94eO2z/reVPMn3/1V+vNjfnxw0vOBAcuMUcYDzQmVz1p/76OH7plH/TyaG/eqW/53vGP5fqP/Ab3doERyrdkB2gzeZdleCCvn5NHgg9vgy3RS+VvHDg4eWXoMzDpNXhDFTWr4O+aj/nC+3n4a34Z5+BhvpUFqB3udi3/GidQ3r01fS4qmH8BgeCA7edA4wHGhbM+TjFhYf7MH7xkkydXN/VY3PWZ6G/GtJfMDm7mscX4AfDH9lw5fx3meEWHt6X/Dh+q8CcPgXhD+bC7teaLzbw5tde8TLfRWFomqCXmVrLDirnjNcMau0uCpNBB0Su1D/oK7ZdxLMy/jL+abrCRaGasK9uuxImqon2z7c2zwu9SOZW4mfpxZI2wsGB4MDt5YBe8F7cZvyAU12PX+W4Svmhv/avv0v80Uf5kRX3BFmpTLrD6oKdq0TifIqyujq95pwV0vyhoPG8bdFLQS8GGZRh8SHsoMzKz2kr5a+BuKCv2rYp/mmXsIlAF+1fyuNW8jdML7j8hh8cCA7ccg5oPNhq/CjY5Tqubfqlj6uhv2osQjPsU38b/shGrbbb30XO5W39+rzypdlP18wdZcscBwZzExQ0C83tRnoS4rg2X3kI128sUumety16Ic+ZhHxAg1IG4fqNRaiOa+pq5SuP1T/HcQSH0QV9o/wbjiUWagsgXdvtv6v8jQeAOR0jHS44EBy45RxYDiaj9Nj0R8f6a9PxazBOw7HG1dBfUuk90t+GP/aIf66SH8dvZpnTh1lPzMKSQZyBosLiZkBO1z6HRt56ZMhgr016dktamXkOcKX8DNbq8iUEdf3z240BQeoc9NZsjfFPO6+QCYSt5r+EvuZ/fpvZl/wIxo0++fOxq7XuqxEIDtxSDjAOLKanswk1G/o0fumbrOiqevwM/WU4Y9/6u8YfkhXciv7sg/wIv1EvA3MTTspn0kx/ppRRwlxTeeJcKWfLnWLN+SJ3s8y0SC8rEKvmFibkWcCpQF0+KJ55V/1Z/cnDNeCNOO8U1D/oayB+Xf6JuyY/bbf/deRP6wFiqlUNFS44cJs5wDhg+iPrMnhRj396Ae2D/tOuxFHoLxkG+qS/BzrMA/wh11f5Mfym+pkyfjt/9siEW6AMJOpWOB7C4xE0D5Mu4TOw553C09qgZ0eJlc+ungzUOASYcF1+TuPcObfCKVTtDALUUf+gb4x/wwMNgZKBmv9YP3smP+qALyMD4YIDwYHbywHGgX3qL8bFq8qfYZKQngr9JTnNs2hIrOvsfehvWT4Wjmuuaj/P1wb+uUx+HL8ZmPvST6Yj7diww3VhHhgJYv6oIIceEsW1h32LLtGWX+DO09qgl3WGSb26jDPlq/FXyqcS+kMQPD7oT3nUBP98E4S1d8vtj5ztIn9q+xe1ACPWzRkD4yc4cPs4QP+X6nppl/GjS/03WiQZWbI+Df3VC/0tzTGr8cMe8Y/12nPK17r1JfiNdANzmnzks1xHDt5M0Us514Ksm2CJM+SpoMVrylIPeWqp427KR1ob9HOtePOzdwygcSiwgJqjdop38GblC9zVQI6Oka/JFvQCuA3wD9mytxDkA9di++8qf2r3yac+H0eUVA0Uv8GB28cB+j/r5fapv64av1iqouk8+/pD6C/N8PREf2OZQ69d1X7Wq/ag/2Ynwm0gIbkKzCmwGKdngDNQqOlm/fipx8ST2ePNr8BdbfFAANukX+o7oGYB0o/5amxbq0XF5CgfcEf9PR+AhTTi8T0+6MWMBvgnIDccDSu2tt3+tN+u8qd6xlQrDAwXHLiFHPD+v+v40YX+YycrY3Lor37pb3BHF+2/q/7UC8Az79Im31wI4DzTYSUvKjHNWO6XAZzBPQEkK4xo4vM1dNxA+e3cOeE77a1uh14G6BmQzK1t1IfyAWay2tm5c+oLQhd2LaRXpVN/Ogj5yRv0FeBtjH/LNNF3WmcmB/C/pfa/jvwNl+l9qtp/1F+44EBw4JZxQC/17+MoKywX+9JfV41fk0GahP7qn/4WsJktp/vHPxfJj29+oEvXlrn5ID1DISPs+PwBgszPwElRFs+NPY/yWx6AHHFt0YOQKd8AWQZmhLHO4dMRHKzh8+dvOb4bUlFBLx7Qfs6j6/JPjJ/Q7m23P22HMxnbVv4G6cGPf2F5WN0hfoMDwYHbwgH6vcDcA3/encYPjTdt0+v4DX2WVWNzNkyE/uqJ/sYy10H776o/T2bVejnkE9muHHOvkiBXzESO9RAIl95qasBm8fqhcBx5vCJ2rZ8yrUF6femkcgh6HVb5DuRIXU9TJ7H6r8QHfWP8kyV0fKyhzgWpr/Lz7Fl6v5r9q8hIuOBAcOB2cIB+P1vXa3r0Ukd1pL9Oyzyn/ENZ5miRFT0l3Rb6a7/6WzuL5z3BP+fKz+EkPUVucLVlTqcIP9OiNANvrpgtg4CcFLa9mZTxhDV9tYSGMB2ibXohkJVvtFK+bOf1FCthhJ8O4U5n1vClgnpK1uPJE/TX5x+jj3Zhjbpo/+vInwTnA9724QcHggO3gwP0+77or4vGL8ZPAEPor37pbwG5Bevu+yw/7x6dWuZqMHdwLDA3V8VVeUCZP4CtMVN8CdQIo7wtr9IYFhDUtulVHi9ZLH4waxxAjWleyieeMHGkO4AD3Ol8mJWOEvTN8k+fydFXaNpvf2TRytlB/gZ30uNXnywPkJVwwYHgwPPPgSe/vjzQlNLjYU/010XjF+Nn6K/+6W9t7rMTNPosP+A278k1mPvik3RsljYpTBL9AQgbuAO0oUmzc6scoM+mUuWbom2RfqrFiGX5DtoAbIQN6OXyHcCRnzSuDfEV9Q/6CvRel39TrfdARtpu/+vI32Cahg8epm93+Qk/OBAceL458OWvpG9nTXBf9NdF4xfjZ+iv/unvk1H1Afu+ys9UX6cAt3kvrsEcB3jMOZ5Eli0gk3YV2LdY/RrARjwPhk884MnDnub526CXQp4j9Cz4wgJn5ecwcQbaqL/CZpkr06h/zhP0zfJvskwHXbS/l+Eyt638DWYB5rzjhx8ceN45QH93fdQH/XXR+GXjZ+iv3ulv8Eaf5Uf7FXRYcHXGHH25AHO6mGqqFdAjE4sfBuvX9ukuEZgClQ+oIw/xhC0dsNciPQcHe/kANz57wie97K2GBDoE5Stsn0QhLV/bp7+K+gd9g/ybCFhj92y5/dV815O/YXohdrXCxXDBgeebA9bPD9ILro/6oL/gOGoKV+tPjZtLxs/QX73T3wIb1YcKhHH6KD86CLueYkWmVsDcaFklusChnHEmZ4QBbvn8Oc9j10oD2PkRIJ7WOD1z2OeVLxAHeJO1bnWjg+JwVn/CCgT9Ko+MHw3wT4PmQevt34D8aedtTLVar4if4MDzy4GnJ9rw1Df9dc74pXmkCUaI0F891N+yzNFDDD/0Af+syY/jNe/FK2BO0M6+8VUDHhGjoN0CR+ewry74TeX7NchV1i7bjNAWPev0dECx9v5kUCZfljdbC5ctdKvlKx2A5xa8bLmz/FbHoG+Mf4fjNGm7/ZuQP33+5Dtd+MMPDgQHnk8OSC+8gk7qk/46b/ySTjtAn4X+Ogc/7FF/Mws4OdBa+x7hnzPyk/Ga9+BVMHdSnVmi9WYDfwjPCPghjmttJjCfm1ucfEvP8W3Sq8KzunzhZrPGyT9TfgZxK/XPlrugz+3XIP/0QWJ1vcq12f6UULffbvJ3/4c+v3whVzW84EBw4DnjAP1beumeLRXKz9YX/UV1fPyy0x/0PVaMDKG/bJNitfkS/LFn/Q3O6Lv8pIzXvPuugLnjg/Qu4AzBwuJG2H0IsLwYeFsLl7t02qYXaJAKz3XJ4OwURlTgzuovix0CgeXOAN8ajT1L0FegvIZhu/MPORnpaxBtt38T8jeYp1eQoXDBgeDA88cB+rfrLfd5yj7or3L80inBY+oX+utUBtHVfdDfWOZoqz7LD3jtlHNra+Z+9afTU2l3O5jXhY7Mhp7k80ZRhv1GxPPQnkZ8W/Ra86T3mKou+DgrX6DNEqooIbhsfdK1x5OvDOesQU/7NcE/TbXWPM1WXK5dLvogP9RFsvHtT57YSSpe3fCDA8GB54AD9Gv6d1v6pxzLnF076788Xob+akj/eIPIv67+d6MRtyzbvAx7cTu3f77BLvRCaXPwmtcBf8UyJxYsxYT3ygx0Ci09qF0ZriMVWM/naevx16XXqa/OTy/CfBqvMDDVaevx5+Uh83o+v8F6fNA7Z1Z9+GTrP1ajz8jFddu/CXotrBx+9aX4IsRaU8VlcODGc4B+Tf/2B2la/zQx/njd9AJdH2K+rmc8z3p86B/nzKq/zidPXY/flH9Ms3KPvsqPnks47fRYEupaCz0XOJk438XMmcPVNJylVPP6Fl9YXTxvzmKex7nvaX7Nh97X4/wav86X6+FpxAsxL2b6q+M4emTN2XZ0xbnvyX69Un7QN8a/8VJfSNOkwWXtR1us8H+tjS29A/mbH8dGCO8X4QcHnhcODBfpO2/C+CNdNGa8dJ1U8t/j3Pc0v14ZP0N/Naa/nM9ssgRnuBx5vF+v8H9P+kt1WZlipY5nwNxkkt5lAbslZh90yrWftaIOY+nEueNBPV/b9FqbVYO5unwJdV0+BwfL2YF/8j3ez5o7t/5B3wj/xPjDttv/3PbbUv5Uxwc//LnlSy4/4QcHggM3mwP0Z51c8OCGjD+1VQ6uA9RcT7nect/jQ39V8nnu+N8g/2S9M3zhclTzP5tlzy1/S/2z3tO2xU/gtPV7nAFz6gxmmeMBKIA/1sPhQ1z6hH37Nw/uuz+Ib5N+oc96Ifz8IeCUheBzBInVMTes57H6K87T3A/65vknOThou/2t/SRj15U/yeuHuFe44EBw4OZzwPvzTRh/NE02Cf3TvP5BiuGr4Q/5hLfV/7NhmraJX6yO19Rf4LT1HnsGzL399qplzsGaEwLaXIkShlFeOcurShJPHH4b9JrNngLiAHB1+Wo0A3by/Y0G38FeXX/FeScK+ub5N57L2stBmC22f1PyJ9l4+TP/cPnAZSP84EBw4GZy4DNPlg/Gk/QSi8nb1j/XHX9m8zSaaDlK6J/m9Y9WkV1b/2v628xCbeGX68oP9OC09Z56Bsx96cngRAszj7GygU7N2qawdRD5XhGWBxL2PIA2A1byiW+TXjsyZnY2jxrOyhfrAW1WPjZSxWOl8zTyGsCT70Au6CteOI+a5B9grs32R9aakr9nz8I6tz4oxHVw4KZx4NmD9KGu9M91x5+DA218yLqojfE39N/19L9OzJj2WX/pMOMTcNp6Hz0D5sggxf6uMJE5BFdyZ8d3lOfJeZiHtjwZ3DnYa5VeyNkXIQLaACL4CLGDtbp80qi/0srzfDwc9M3zbzxKhzX/+yg/SDaAUE7n2Xx7fK+14kX8BgduIgfov/RjdE8n+gcm5fFjR/13GPqnkrS+6V9ZTRfSX/U34PuIf/TScsYqBzfPBXMCRO8aWCoscVxbRxERPpYRe0PhLkWYxYHWqZTfrSfka5p+OE8zQJy5DOgIW/mAOsrPAI98Vr7iIQHwkRb0xj1Du86LJvinI0oG2nE8arP9S5krw9vKHweJPp2lD2ZOhBccCA7cMA7Qf4cHeWlPR/qnHHPK8FXjj4wKY8bH0D/91L9MsXaBX0qZKcNXyU/GL5uDuWOdYcK0qvBO5QTWuHYzNpEOzsqwFSQQRb626U9kCjVQ5nVxoOblsyGCyuEUqNcnUEk5B3dleKX+QX8t/k3G6bDmfw/lZ0V+U/rOV399ubK7zIQkfoIDwYFec4B+q62HdhzJyvjdU/01YopVLvRPNYtW8mKl/fakf8EVXeCXFf0jzFIbyhy/XCK/88MtLHMHJ8osBcx8PqDMC+aaeBwIkj/PQxz5yO/5PK0Ven3Wqy5fDV+Xr7CVLyRh5evayhfY83jyrtQ/6Bvnn46POWy1/RuUv5GsiPf/KH03chEuOBAcuDkcoN/Sf6lxp/pnx/GHcZG6hv4p8EOf9O9E337POKev+mv47uqHHZAn3LnTrB96psxjzR0rg02pys9LBKAxZwAJ8CahJg8+CYSNTmlt0s9Gssx5+QJqdfmFhc6Qvq6pl/V2Atmt1D/oG+cf05cHOuG8r/Kz0v7I7En6zlg7570j/OBA/zlAf6Xf7kP/rI8ftf65RP+NNB5KSZrOXaEP/dO4/oG/u+j/mSxzXeCXlfbfAj/JWLY0fHZO9zwXzD2j7e+9AABAAElEQVR5MlhoYeezbIQzIOdh3cMO1HNw58qaykmgDTh5OU5DXg83RT9RWZpmnZdTrWxL97LxfZqPRvWwMlj9HdwFfcUz2q9x/g2qt9A22r8F+RscTcM6V/afCAcH+syB9xbpT0n/nM4qrI3/rnN6M/5oPAz901/9qw+3z0od2Dv5UWecawkc+Oy8fnkumCOjdnS8SycAoPFQtfKUxYV0lL/F5QQ8xdXWOfIQ1ya93nSmbnIDnGENolwHmMTROAA5B291Hv+Wa04I+ub5N9EBwryx9lV+1uVXayVe+aF/sbyDDIULDgQH+ssB+ulwmr7DFdM+9M/6+HGZ/tPBm0NZVQ5C/2Qd3UP9K5AwReIdP7SNX7aRH8urukmX6pus57sLwdxymt5yZAopD+iWN3zeiEj3uJV0gSri26bX/uGpI2nK97Ct29O1W+O8/p6Or7P0bIG/xwV9S/xbJgNHK/Ih/ut67/KzLr/IyfLN9FH8cMGB4EB/OUA/BTztU/+sjx9eF/TPuv7TERyHrmtC//RT/2qOysDcee3XF/2lndBvX9QrLwRzOkz1bT0UR3yYtYsb8JB+I0etvBk5wvTOJd/o2qYX4DTLnBnX9MNbDx1lIdRv4ex7ncv6Q2OdS4GgFzNa4p++BVFbukr+90F+bPBdk9/JPL3/tZ9bPnaZCT84EBzoFwfon5qv/Lbz+i9xXemfbcofaHd/Of6F/umf/p1r2VZf5YceiPycvJPeuqg3Xgjm/uXfTu9IwZtxy4W2RqdSgHQYUBwWFuLxMyO0z/TUYmeVUHrOW1n3mqNfaMGibevF0mZvPABO1dqAWn5qB23Usw4L6BmAER3xQd8O/zRoDfU2MW6p/VuRP+38+Z6LOkzEBweCA/vlwOJu+p6e6J/Nxh+Nf6OhJrFC//RW/4IjhA34GEGX+GUz+XH8pJoZLrug+10I5qTal5qHfMeAnBMLhNVOgM0AHKBO7ky+nPdMvN+gIXpbN6d7luDNTG1mbjsn3ssX4DMAB6gL+lb5pzaqrHM9lB+97ZyV31F6qG+2fsBFJfzgQHCgHxz4zC+oXy7SQwwGfdA/544fjHOF/qvHv6yTjJOhf3qlf0f63nst4WvttxLvF3uQv8FABjbhMq/Cun8xmFPOo1k26fFwqrz9cQfCigOoyTRpVjeiV+KUx9JyfFv0QtInBt4oR50FUMcnQrDOmZ/jzcZIPA6/zOudrIwL+sb4N5jooMyZtuQjN7geyc9F8js9Sh/RgaQuGVW94zc4EBzYGwfoj9NR+shNGD+oY9Z/Qxv/0DmhfyrZ6aP+Zb1ciWlO268C5ugs/nD4ZV7wEa6Ma4FemxAunGKl+EvB3MEoE/tD5Arj+YP5c2gzQn2gsA5GHPBgOsyxWmPXIr1b5qyf5M5iGlg//omquhNRb1fPZV5FB70zIbOoYf5pmmHVOpdlYt/yc1H5WnN58PA/x1EldJlwwYE+cID+SL+0uvR8/HD9Z+Ne1jVW79A/lSj1Tf9OZBTKMtUlfrlI/7j8lLIu08LuYO6Db6e3B4A0lWhgTXeWkc+uiSdOW0Yx/C1hgOVRXtKI482kbfrZLC1UlorOgKzoLKVlru5PBHKeMi7o2+Wf1qHZAuC+yc9l8qtlBt/1mSfLB9ah4ic4EBzYGwdeVT8cTdMHb9L4AbPY+IC+KXVN6J9KjEqe7FP/gh8E5Bb7wC+X6Z91/AQeu6wDXmqZ0+F0M2V4zxErN6LwbD5OjmAtTgCOazob1/ydZ5lrg15CMUUwDKPVEqJri1BCEcczOMiz5Jwn6Fvmn6ZZtUbxThvtb/dsQf70IjKcPU5/WlJf7+JGfsIFB4IDXXJgOXigfqheaHqlb/rnovFHg8Zd6c5h6J9VWemb/pXunwLk9oVfLpKfEj9JljgsuJzjXGWqri4Fc+R+dlRZ5+xB9cA8dGkaBLyVcV4x4kiT5cwsdW3Sq4hjx23UGWBm+E0/K4KT4z1vnUfxHqdg0GcewIgm+aeDqA9LWXEZKeP2IT+XlT+dpoef+kL6TuQiXHAgONA9B+h/WqD+yGeD+qZ/Lho/VM/DJsdPOI/Ocl0V+qtiSMkT51HNGwus8mydf+AHl6m+6Z8aP11yvhzPjLsSzB3cqw4PtunSisascxYUF/SfWVjzEWremrh25owVIE+b9HqImdZSqB0q8EFjeYNhncvtqdg1pwTSyGu0+AoEfTv80xcW9LKhT9rIamst0RP5uVJ+Z+nD8WUIa7H4CQ50ygH6nRTah9vUH1f2fz3xtuXriw+HjHehf/qtf8EN4Acwyr7wyybyd9V6OTrllWBO00xveWGck0OYh4YYoMY1Dt/+9ANj+MM5DdcebpoeCyAbIQyEZfAGOMNpas+2JHJdhkmjo0GDM1r8oK+BLXwpeVaGSduFf3c19dB0+1OXNuWPT/GM32K6NVxwIDjQJQcO3kzfS/9rU3/wPE2PHzbFqvuWY2YZpsxdxk/0lOu2oK/0tvESfmaewh/nUcnzMmw0IgA3gB+abv/G8Y9wGHW+zF0J5r74icHRcJBOeFg/wZowwKyscBl2xlCwHcInv236KUeUyHmD0bA4fQ3CrEBc65yWOky+ssHLsAmFUQd90/yT5XY8HqRJ3+TnKvnVkTcvfvLnl69ksQgvOBAcaJkD9Dcd/vUSxbStP67q/1uVr/FNAAGS0D+Fzu2j/uVos3VdRMNZ49F+HCKcr/eFf8Bf4DDqcZm7EsxBfKItsTwwf1zj82A8sIf9cGDiy3yWR6ZM4sr4pum189DAHAIDUKOeDuwwpRIu48kHaCOOsL5SYDRB3z7/9Jp9t+n270L+9Or3kdeeLO8hW+GCA8GB9jhg/Uz9rSv90eT4wfgGZ0L/VLNifda/C+EGdFGT7V/inCbk92R+tVUOedsIzB3qsDoeGAJ3ujZwZoxQGN8BG9OvhD0OGsJOm68bpddOp4X+ZtaBhNIcpOFTHiBtvXzPo7oZoOOaP8zXnoYf9A3zT2+uw1Eau4zAf5cV4vYhP5uULwEaLh6k75eQrMhSKVcRDg4EB67HAfrX9F76mM5oGzEecDf6Z3lXxoxejh+yyI3GaRL641Sn0m691L/gBeEGZGmT8X9f8nc4bBDMnUzT29apMkjjoXRtnYt4Vg9aen7aMo0oQ6d0ypbpNSVo1jkv34GYW+CYVPe4Mg+bHjye+pZpXAd95k+D/JMl9H7mdW/kh/rgvP3lmyIp5VcR93/459KHq5zxGxwIDjTNgc/8cvqwlOuD8/qfx5V9tC/6Bz5oCck9r5vrlNAfzeuPkse76m/wAvLUJ/lBhvzZqBvX4C/8q9xGlrl//rfSu8OJ9jTkhQVuOcE3J5+wX3sl/BpmWbhtep0XQ33qTkQvkrMdqoTzwji3vOGbk2+LSfN10FdC5Pxpg3+LWRrrCyPVae59kZ8sz1fJ7+Ru+q4f+vzyhSw94QUHggMNcYB+pWml7+J2neuPDfs/9WKM8PphpCBs49misspR/zbHT3SU3x9rQ+ivU35vqr/VZNX3WHP7eXteNf5f1P5t0AtwzsBfyNNVbiMwJyPpUtus3xzIHEmF5xkxAtKIA+QRJp50f6g6XbXwcJv0IO3x5FTIASFWP5XvYYR+kadOPQ6QR5j4slPU6UHfCv/0wex7fZKfbeR3vEgf06n0FRi9qpdFenAgOHAlB+hP9Kt96Y9t+j8P4zrN9Z82PdwN/XEKqvqsP9E7M3ay9gi/nCd/k4P0Bvjrys6jDBuCOeUcpDe0hmGAAOPocDBCIG/gnY8w6fyVcRWFGrllesqdz3Sas4AZnQpHnaqQHlbr5kjDke71L/OSHvTd8E/rFUZaS3FYyso+5Wcb+ZXMHDx+IX1MPaCWr0qy4jc4EBzYmgPqRw8fsh41HexLf2zT/9f1n9YAH0gZT0J/3BD9OUxTIaQFbd5n/aMNGm9u2pc2BnNvfSu9CXI0JKu7E/ZCPOxp+J5XmO/UOtYBPdY5ysfKhg+m83p5HPV261wZ9nxB3x3/tPPrfp/kB3mg/TeS30V6/N/+YvoINOGCA8GB3TlAP9LL9iPusHH/y8X1YfxgHKPeXn/XNaF/+ql/Zfc5zuJTY5my/TYa/zuQP3CX1/Mqf2Mw96Ung5P5QN9pLdxIqLZkAEmAN5xbxOZZwMs4y6CfNuiH+YgSL1/nxNSg0+O8fG1HPlP/bNCr6x/0LfNP3z/VvzsuR/uWn23Ln4zTK5/4wvL9LlPhBweCA9txgP5DP4Jq2/7n44b7e6Fn/GIckwv9ARdO9X9f9afWxZ20gT+alD/wFrir4ujVvxuDOW51eMT87akzoCaIWzqPs86V0wBRXOvg1RpYQeN5m6SfjdKcM+es/DylWpef18p5eSZoOc96XNCrrTrin054v8sUPG3gMrEv+dml/PEyfe9/84tL253rchR+cCA4cDUH6Df0H8+5S/9zWvyu6QEEjF9eB9cpoT+60x/Oe/xN+K+lPScCIguXlZLe4/qgf9bxVlnP88JbgTlNYZ41+TkULUGdx2XfGEPpHl/WxOMapF9MqiNK/DWpLt9fm8ryPa4EdR6X/aDPINz50jD/BLZHarHTw3hdJvYkP7Wcbli+PiUyujNLH3/tV5Ya18MFB4IDm3CA/nJnkD5O//GTEozuJvX/Ybpn41foj9Mmdz3RU/3JUqy6si5rDeKPbfWH1eWc8s/FW3XFzwa2AnOv/6309mh+2u18C6/dVkypT1HOFji7zpWs8xaVruO4QYP0qqHNh5slMHeyuqyi09VxlC/Bc8vhih/0cMe24lugJf7p6Js7OhzRrHMrcrQH+dml/OVhurN8mv7Mq79uyzSNVfETHAgOnM8B+smJ+ou+DnDHcjQ4/u/Sf3fRP8wmaJ1fVf/QHzdGf0rv+3m0pzOFPZO/kY4kAW+d33vOj90KzGmydDkfp285COLUZL8tcTJx2mcx8Im368PKqiNeVU6BtukxlZopVfXQN8eswfxlAdB2UfkaWAYAOXwqa9dB3wn/2AU2G6QHDMT7lp9dy9dOvIcvfzm+EJF7enjBgXM5wBceXvxq+rimVx96hj7pj037v7TEA/X5StdlvRH6o9/6U3jgRJsbzCTRV/yC/KmC3wJvef/YxN8OzHFHHVECE1C69jeqfJ3vZo6KmEImXWkzHcvnCrqO74BeBp1jAbolIME7GD6DBvUnbH/Kg18fT5LTyBf03fJPEny40Bb/Wk72KD8mJzuUrzWbL37676bvq3pD/AYHggPrHPiRX9aRPtoJTj9HR+D3TX9c2f/1PaPhNB2gI0J/3Bz9CS64CfgFnLXeb6663hrMfZdvlRV4YwYMsGZvMvjqlPwlpWGJ0xkpAxhHPlPQCtcWupbpfVcr5QPD6XBY2koLHfGAPbPEya/rr0zk460r6Lvlnw4NvdcH+bmm/L7vtV9YflQiFC44EBwoOGD9YpneRx/vs/64qv9PRjpSSc8V+uPm6E+UuuOCvstfjbOKvnNVsJ4mvSpjmf7Df3f5F0Z8W1Md0j6IgY+rPo5RL6rjbQuw5z5Z6CR0YgN1LdNPJunRUm9PWN3odDhAGkH81YuccOrZwcLQBX23/JN1613x/cjlxn2arEv58XLd37b8O3fTl//RXx18BbpwwYHbzoG/8nPLD90Zpw91Nf57v3Uf/jcxfmhV7J3xPD0I/SGG1so0h0+9Wm/2RX+y8UHfBH+77/LHkST/7G8O/q1YuZXb2jLH3SdDHSCcp6C45oA9QJuFFU+HoQM5uMPn2gEcfif0eSMEAodAOYDD145Xm4JV0LYzO9gjnnTyVzPrlR/03fFPHe7+5I7ObcoytTf5uWb5s2fpu3/oF5YfkASFCw7cag585h8uPwCQc6t7J+P/NfvveePPQOMS41PojxupP49vgvyBr3YZLHYCc4vj9KZ2tdqUKZ2SXT2av6wWyjOtSVgdCd/eilQzAF8Z3wW9UOWxrHPa+V4BNjogAA1f6x1sytXCnINHmpymgwdlPnurCHoDvCVf2uSfoe7j9GDf8tNE+QeH6Xv+yj9YvoxshQsO3EYOIP/HJ+mjXY//TfTfM/pL4xLjU5vjXznOhv6pbCpayrUs+bIt/2VJWoAHHJd0gT92lT/w1S7jxE5gji2z2mcxp7IwBQbhcw1o87D5usYSZ/nWatg2PfU64aRnlUvjrxVfgzoAHukIC0LjYfN1HfTd80+db6L1c3eQp33JT1Pye3icvu+1n1s+Xpe/uA4OPO8cQO6R/32M/031Xx9/pEAOZZU78DZDX5heCf3Re/25OEkzdIm3HX7b+GMX+VvMtj+SxJ9pJzDHltnpotptYQAOEKc/wFPpLC5HEGbm9TyG+j3aoFfr2ZlzdDw6JWCtrKMBOECc/upp1ZzB4opw0HfLP5nE7+mlwWR0X/LjsnKd8nkGydL3fza+EuHsDP8WcICvOyD3yP91+g+s2jc9m/wOtOkh9MfN1J86ruxoH/jDu/mm8qsXhjfAV063jb8bmFMJmpb8E3/bgkmENaVpDsDmcQA0HoR0w3pKIM3jIPC8bdDLZHmyONBXXmR5Y+EjJnIDZf5WpSiuSR9jgpOjw3pcOS0b9GJOl/w7SSPtQr7nsrIP+WlKfvVGP/7WMP1AWOisi8XPc84B5PyB5J2vOzwP/VfD3v05L5Zdjn/MJhXLgkL/7Kh/pP81jk9vgv7QJo1v7Do0nJl63PRGHPz4I59L/6V9igU0ZpwSMCPMJdcen33OFGJ9XZ1mGYt8BFug1/EiD/R3R39Lndg9mKmD0CnNeRhfzgFdnadID/r98E+7e97SruTpvuTH5biJ8pGhZ8/Sf/if/vvBNyuJi9/gwPPFgb+qNXKS8T+tRdXVJqY9j//X7b8yXEx0esPjGP/3M/6brpYe3pX/OnLsSH/vNjF+t4lfZI+b/48/k/7NoHPLnApcZhRp+Isf/QHUDMdZ5Ck4Y7gyRuRxi2TOnuPSsvKjvzboh+P0jHIMyBGQM8vbsiqfsAmMAB4gzrYuZ7Dn4I4sQZ+tm+JFl/wb66R1ZGdf8kPb45ooX7I1nIzTxz4Tu1wrpsbvc8UBdm8fTdPHDgBycv5yTriJ/pNtBqYzutAfh4easdH4Q/1j/N/P+A/vcbvy3/V/3+Vvdid9c1cgZ/wxLu34c3Ccvkmv8mlV61y6xre1cbnneTxxHga0sQ6hC3odXjwTWJsuBN403bUEuAHaZNIcECa+Bie6Jg9xvobOaYJ+P/yT+XioBrq/L/lxmW2yfC3k/Ogn/u7ygzt2vSALDvSOA5/6wvK7RpP00b6N/9fpvxrz7zP+uJ5wXRD648boz6np/4xTXBa6xB9e5lX64+7T3adYGQx2XjMH8T/+WX2nVR+EJUxF8cUzA2mgYAdqxOMsrgomTJ7kddcB/THI3svDZGsWuRxh4E1h4gB5ljcDvZom6PfGP7XHHVm0Duu26F5+Gpffw2H60Cc/v/yIP1P4wYGbygHkWIuiP9Tj8X/r/js61Oe6tIPV2yT0x83Tn8IVR95+e8Yfl8rfVNtHwVNe1138a4E5dl3ogLtvmIVNpeM7+nSfSsHE+m1NaIlwmbcL+pkaVW9TC96wzPImYOaWNrPQUf8yTpY5ewtTPJ3YaLDWBf3e+KeDnR/YoZ17kJ+25He0SB/45C8vv481qPSVcMGBm8QB5Bb5RY7LMb1v4/+2/Zdn0Xcg6+nVGP/zbNUN0n+aWVtoAvC4D/jjKvkbjTXLueNaOR8vrgfmdJeTefomVi5uSIX9xmbiyqYvOnYdnwNl3i7oKU+VsGNKqIIDNQt7/QFr7iS0ADecW+2qq+o36E95Vbdfy/xTOYPRSXpIC3QtP2XbN13+aJBefu3z6eOv/rodabheVFwHB3rJAeQVuUV+qWDZJ/s2/q8zsKxrPX4Vekrg9OFwUlmiYvw/HeudjzdB/2nq7Zh27gP+cL65vy5/4ChP29W/Npj74k+kt9j2W1fA5y5Z6e2dQ3E656UCSra7oMrtnaiaqM13aJFex1wc2Tq4DNIGXietn6tdTiOfdpdUdVac3tSqMHmD3ti1F/5p8l6Lq+9Sga7lxx66LfnVbrmHX0l/9rVfWVl9YEXGT3CgbxxATh//YfozGhUfdzV+Gw/a6n/OYOkfnQp8l0VCMf7fbP03mlUbH3mx6AP+uFB+hZ8MR7kM7uhfG8xhGhRIemOFWbkyPn1KZz9vfZy2Cw/sDU75u6Bnfd9QmyH8TWtJ+RmYrYC1XH9NfFVTXwJwjvFICvqqk++Lfzq36q7eDMddy08Wi3p9aNPlS8bup6c6i+5Xlve8rPCDA33jgMmn5NSmIfPLdxfjt/PBLS1N9z/ur/NGx3qdsv4X4//N1X/o+dkob2HsCf64SH7BT9edYjXZ9QKu5S/SN2SWrtf8YDGxzi0m4nNNx/N48hLmD6CH3xX9sU6ClsVwgFXJLEtY4KhLUX+uDdwpDZ9rgIvHB/1++afTn4f6ZuIDbYiwc2S6lB/kuU35lZzd0fvkD7z2S8v3XatPBnFwoAUOmFxKPtkYsI/xu83+Z2urRtUyjhj/pZtvsP5Dz4Mt+oY/zpNfreTf+aDgsovXAKyM3D68HHz6c+m/mLJ/VQy0TgEgygDJOr1u6oDO43kwynLlaHO1LdMbAJinl5daf+XWOAdnkl0HBwbczPKkKEAcSQ7oPD7oK77si38SlWOdyv52l/KDLHclv+qcf/RPfiJ9uYm3NuQ3XHBgZw5oo8OP/nL6bg2E39GV/Hs5XekPzdw80lh2oPJi/Nc453rupuk/m0UbpW9OpSBwXcnPTvhFu1j/+U+l/9sWdVXV3fn3+tOsVrS+1TpIbzCVCliCeTwYvpvEufawo2WUMDTko+N2QU8dToTaEVBACA1PGMElrF0ldg2wI171MiDHtYfdWhf0++WfmupQ8yF3u5QfiUH9tte2/KI4f+Tn08djHR1cD7cvDiB/P6KNDiez9B3UYZ/jd1vlj/XZQJ3McBDj/83Xf5LPoyPp7T7ij3X51SYbbXzY7Vus3Kt0DYE5LfYZVaZCR8P1GjmmwuQcqHmYfG6ZIwzjSeuEXhsh5irTLWuE/e2DMM7QPYFcfwd6nhb0/eDfQh+/1pEzk07lR0LQlfzOD9Oj0VH6c/FNV3peuK45gNwhfzqe6ZHNaqgCjOVdyb+Pv23qD8YPXycX438lYTdZ/8nIctRr/FH0n7vL6+9irVpMGMoD1/X//l8fvC00dkyHry1wQsfW8XVz4hyoESafDwolTRm2fKJ1q15T9BzQN9IXIRBYOi9vY251K8PEWR7lI+wd3eJFE/T94N+dcXokYG5LBrqQn67l91hTP4tJ+v4f/qXld8d5dOqM4VrnAHL22t9bfmhwmD6O/PVp/G6y/2n4H9r4ofEdpsb4f6oLb6T+k15Hv9OWbeGHpuRPEOIY3ERdm3CNgTkqszhJXwdwsWbOfWcocV5hCYmFnSnEk86107nfFr3WWj11UEb5suwMuAawEXbfBZo48uF8LUHQC+xKInH75B/rHw8X6TEy43LjflvywzN3Lb86KPGVz/y99AOvfm5pR7NQh3DBgaY58JOSrx/5JW1yWKTvfJ76j/NJ47aN5YwR6kiPGD/2OX5Rryi/Gf17PE1PbwL+oM3BS/hNuUbB3Hd9OH3dzZsSTnvT8Yq64sP3NNYcce1/5O2MHuvciQxuKt//KN/Nyz7tShzOgRu+p7FmzmnxyRf0cOF02rq6ap9/Mx0yI2B5vzP50YPtQ36n83TvUUo/8KlfXn678zb84EBTHECu3humP6c5m5XjcXo3fuuBr9v/JoP0gHHDx3B4GON3JUmu46qr9sfvJvSnTjmYj7NVzjGG17+P8gte8vo14dfWpiZuxj20df1j2hX0AkqVqS+YSLxb3ghPlMiHbj2Oa30Md8D3Wom3PPppm57DZ3Vm3H2sS1jbEGCfSqVT247XXH9/c6Ju5F+x3AV9b/i3PE7vnaT07CbI37XlXzt5Dw7S78lUX3/ZBPkMFxzYlgM//oXloT6X95ETWbihfd77j74je1cP+QAQEeP/86H/tK7znaOT6lusfZff+Un61uufHfzOtv30svyNg7kf/tzypfEgfZ+DOB8YMkargdx6vFfSgV0X9LzZDcfppfpwSFXCO7a/KVAvgJ0dW5LTS8Dn8eTDBX01MOyTf/Npepdv8VYtktdm5gt/keCSDu9ymZNNPnmx6EL+mij/ZJAW+pzSV17/yfS1pnZFOS/Cvw0c0Nq4z6cPaNnJB7Wnbtjl+NuE/O/Sf2ezdKgXqYfluO4tHeP3/sdvDCvb6g++1nE8S28cHsqucAPGb2GO//DPfmrwhstdE37jYE6iMPjUL6W/KBP2hI5WdtgVRaoEFCaML+P9oZzOfeLLfISboB9r2kqLfO87QPPyvaO7Tzwd3fMRRuDsSJMiPugrDjjf3O+af4OT9JZ2uEzblp99y6+XL7l8T9+P+L3XPz146jIYfnDgMg7YlxzeSx/VWHbfZ0Q8v/cb94lvY/x1+e2s/COdnnWQHsf4/XzpL5+RuRHyq6ngf/o30280fX5oo2vmKkYOlgcDbYRwrspn+pRLOmwZto6seEAZg4an2XQrBNl5fBv0KuJ4Ma12rfo6AZtu9cLlezxArgwbkFM6oA7Q4mlBr+nqPfNPbxGPxsNqCUyb8oPc7lN+vfyRlgsMj/VtV+1A5APoBfsjGBxY4QDygZzwpRHkpg/y28X4r0FpJMvNQ5jBWB7jd3VO6I3XX9LfatJjH+e7xA8+/m4jv+CjpoEcMt0CmEvp6TvpT3g4nL6jaUCOsMcRhuFcA/oAdeRzcOc++dqm1/qqhfr1MWfOeed2n/KJx8eVGhLA5lYn8gd9v/in9RMDmZ3rI0tovz7KX5PyP5uqW83SK4//IP2g1kC9n2cOFxwoOfAJyQXyoVHtO0Yad5uUPx+33afctsfvTeuvsUArajQe5O9tx/j9/Ogv9DffYXW5c79P8kddXP+Aj7hu2rUC5r74ZHA0Haa3tNvTgBCDBuCNN0AegHgYTkf3PP5gHuc+8W3T6+TvemoKUMb8u/uUz65VOr82S1j9SXcAR5g87pzOfeKDfj/8g/VCdI+ksYZ9lj+XHXyXe/eJ21r+l2mss8E+8qO/uPyzn/z5pVkiuE+428sB5AB5mEguhpKPPo2/Zau43LtP2tbyL/1S0tP/da7oQ80WmL6L8fv50l+l/vZ2d78J+bmu/JX0whBvg49KmW8q3MKauapqf/UfLF8+Pk7fixItK8sgshKnVysBn4GBOoeumeBMXsWfiWuIXgLxQKa3w7KuADZA3KVxGiHYQGGgrjTdiSjo+8E/TSOcqBHtcMa25Gff8ntZ+XqJ+ua9cfpK7Hote/LtCLNL9eksfVAL/l/miW+j/GOh12kEBzz/mTE5xu+brr+Op4v07mXjH+3ubt/yr0Ptf/cf/rWBPuHVvGvFMkc13/+N9KZg0LTeLog9XM6YToBr/gTgDNwB5HIe9y3veXHK2jS9tuUf1VtW84IvA2g57Gm1JY54/gTgDPD5nCt1C3q4wBfnls4L9/fBPwZyrQ0yC1Vf5c9s8OfJ+nlxMJd4/jboPyjy6bP05z/195cffvJkaUqNW4R7fjnw5NeXB5/6xeWHaXcDclmObpv80+8NyJVjMs0e4/dzob/Q233AD5uM35rinxkuamnYac0yR335/JB2DX3A6p4VD2GmWzXArJTNIIOFzvKe99MBvRZVvCALzpp9MFcmAzeumG5lTVZZTU1dLH09Rhlfh4PegC/82Bf/WFuhadd3+ip/Xci/5HuhRaJfHz1Mf6idr1nF11IagRvOAe1QnegYgVdOZunbNECdvqx3MH52Ib80z6b9V19MeTj22ZYYf/c+/vqi86bGf8n3VEdQvYVM9AE/XCX/80H62j/77ODL1LcNd9rZW7j7o2H6Oh3PLQj4MN2AHIOLqxL5K4zI+ahSl/Szk7x2Th0fcEb5CJ69xWXLG/EG5Bgc+MPJXwFyQd9L/mkB9OEBh0Tz0tBD+auESb8tyj9nK/KCtXwn/aDtfA1LXc32mxx4Ve1Iey6fpR+UNe4DtDPP0+X4WfOvRfndVH/QzwFyMX4/v/pr9jTra8lbH/DDVfIPHqrztBCwDt/CfetbfvoLy4/rMxsPmKu2KaHCAmcDjXKiXOmk6FecX3sDGeruiF7HWTzGLF9a2izM4ChAV8bbQKH6Au6Il+XHnF87wAt6WS17xD/J3ZHa5r0+yh8C1KX807cGB+kN/fuj15/EGXVVD745v689Wd5LL6XvGJ+kl47zzEaX8lPKax/Gb+rDZ7rEgzsx/laA/nnUP1jldEjwt/oof+f1P63VfPdXPjv4berblpOxol231Mdkl2OtW9DaUy1UNLs/StTmMjOISxngaaeVWcO4ZmDg2gYI8nVEP5yn9zQVNwGY6TtvFUADrGkjxEy1w5QJiDPGZRCnWtsUK/mNm5ku6PvJP32m7c7hIM31DawjwEyf5M/kp0v5p8BZennxQnrfj/3y8lvzo/S11392YFMXVpf46SUHXvu55eM0Tt+hcemR2i/Nxjp8HVnGdSk/Pes/WmDOJxrvxPj9fOsvHcH0rnYoVxsnJYMYfvos/+qTrVrl6PatW+aWy+Xgxz6XfnAxkrWLjg8KUk8zsEYN5M4L0ziWv8pyuuO1A3od6veIna280eTibRrVrvN0qw0WOfG8MG+FQd9v/qmd35vO0rO+yR8vOvuU/8koPdWLy5+89Ur6xpf+0sAXE3hXCH9PHOCw38d/mN6nzyW+f6ov1/ji3pDfaqEzQE7b1u+jImL8fX71jw75P1E7v31j5F8Lzf7xT6X/Z8CZFy26VtfMUW8eQIrpa1jjGHRqIGemrQzkFLY0JatDWhggZ3E5X5f0WlT5FCAGSCsXbdq1VJuBN0CdnIctTddap2FxQd9//ukN/j5/LnO0p4f3KX/I/V7LF1AYL9J3P/xq+gs/9o+WH4mz6pCM/Tn4/8nPLz9Ce9AuBuR6PH7uQ369L8f4ewv0j/Qz4zQOWfMxm2sP73X8VD3K8sE/bQM5nr11yxyF/FdPluPvfzH9+RN9TgU0bQ0gf66pS1+oSz6uWVt1UR6nc79Nen3e4aHkZeXcOQNuqqf71HndeZr7ZbrHuV+medjT3Pd4fI9zv0zzsKe57/H4Hud+meZhT3Pf4/E9zv0yzcOe5r7H43uc+2Wahz3NfY/H9zj3yzQPe5r7Ho/vce572kBr6GSJerdP8neejHuc+23K/3oZss8dPbuXvv7en6Q3vvREX74N1yoH2NDw/venl2bH6f16475LYd4m7nfZ/n0uX5bKByydoI7et90nzp3Hue/xpe9p7m+a5vmczn2Px/c498s0D3ua+x6P73Hul2ke9jT3PR7f49wv0zzsae57PL7HuV+medjT3Pd4fI9zv0zzsKe57/H4Oe74aJ7eASPcBPnnyxS/+2b6zf/liXYOtOw6AXM8AzuttB7tA7boXCjJQZxfA+JAsyweJL831Bk/T9W2TT8Y66sBSy0tXnfrUpavzVtPW6flej1P0Mucmdmyzpsu+TfTJ91kuu+L/J2R+/zi4/2lbfm/rPzBYXpHG5reHN5Nb8TxJucJ6W5xHCuyeJZe0k7Ml6Ys4teYeKYdOhr/zpTbI/ljvHD510kCD0YHeY3cPscPNfk4yrex/FLpX+dRvjZvPe2cG+lYpTcASN7+Ph72DT94/9Hysq+9/jcGf3DOozQe1RmY4yTyk4E+7KxdqTDeH9Z9fzKuATy1Ui0GL9JA5F3R8wkY1eXQ1vnlCuYlc17d8/1SKMuwcge9gPr5XDuNLXlWhtvn3zFrMfoifzDEBytX7F3K/ybla2fSW1oP8eY330vfCosdHNvOAeCGb6cXtcbrJTYz9Gn840n6LH+2tnlt9sS4X44ZZViJMf72evy15lsxeBTtp75xJIPQO13pfypzHfln06RwzG919eWdzsAcjHntF5Yf1cG8LzuDbDrVGwtfbh3E0bA2D16kd0U/PlB1puklncuV5rl838Bhb4eqr8Ur3QSQByCMI3+OD/qbwz+tbzhRm76jT7QtvP32JX83rnx943iCdXOS3vr7P57esY/cWWeIn5oD2hD2yV9ID2TVfHyoY5BOjtI9b2fy9Gn883r1Tf6nmmce30kPtQbmMMZfCc0t0T86DOMNxuWu9L/zdVf558in1//64Pfqvt9yoFMw99lfXN5/Okkf1w5CG7S8UdzqYM+aQZABPUW4Txr5QLtd0h/qFHFfj2F10M/KAOLgjURcrr+/AbpfJeoZFAh6McEHoB7yb3aYppoyeVsLwxb7lr+bWr6mCudH7Dibp7cX76V3X7/FZ9i9prPghve1rmuZHo8n6SFrhwFtN2H865v8wTcNsY+0Tm7iY62PrebH+Gtjq+sd951HN1X/qK8cac7u3a71/3Xk/51p+u1f/enBe877tv1OwRwP89ovLT/GuXPeEY1Z6oCgXwY3P5IBUyr5y3hoaEzydEV/747OCZ6nFzU1OKRMvsMqcFeX750D65vqbGlaUL/kg87Uv4wP+pvDP62fm0v5vj3Q+gyXy33I377lv6nyeaPm4Ez1n3feG6X3vveN9O6TJ+opz5nTt2+Hf/DBdD99Iz1U339wMEwPtLlm6GNW1+NXU+3Xh/qPBYJ1Bugj9cmxj/8x/lbGgVLPPG/6R0PEYj5Kb8qKvbgp/Yex7vXPDn6ny+Ft3S7SetknWhAoAMfHj7VhNNUfhzSFKQA00datqcCS+aoN8V6pPDDZZVf0Rydpri+TP5NJ7X7uMFY+oE5VrQ/hMiCn+uvNkc0bla+cxHv9g974cSP4p47BeuYX5if69t/INhL6i4XVvyv527f8N1W+wNxI59c91v0e3VM/+eMX0+KvfW55cjLWmXbP0rPFQXr6cJSedbW+xPvkdXzWAb8zT3eHJ+neoRbh6xTq+9+4nw5HmmCeaA6QXac65qju//sYv5pqP/i01/rP00TlP+IlH4bG+Ht79I8a/JnWMi/2Kn9byv99fYeVPtOl69wyx8P96N9b/tn5UoNgHuj8rY+pN49zJtB5aUSmVg2V69p8ASbP2zb9gXa2Cmm/yGe6sLi5dY43IOpZWuo8zutPfkAcU6tGF/Q3in+0o+TrHa3TOd6X/O1b/rssXy9DMy1y1gxtOp6eaP3i3XQ8eapDQo/S8b/42+m4i/Oa6r6r9W2f+Dv6nu+ddDi9lw5Gz3SQ+CAdaqr0QN35rpSMXt1MPmpLvY9Jfo8+jF9dtl8rzz8R3xeazZGL8fd26R/NkCylN988mWWr3B70/7b9R5bjo3/yNwb/r48BXfl7AXOf+MLy/fqW4J9COfKggDEfBBj8HKwZExzE5Ty+1sTzdUWvjRt3tRP3gerGblybRgWcUT5gzkFcOdh4/UvwF/Q3k38y8z/Vtvj39iV/3kdue/k6MmiuXjeVxWs+mqaZDqWcauyYzwQCtSN0MZ5K38uf3ElLWdWXB8fp/2/vXYIkSZLsMPX45q8q69Nd3fPZmcEKQYgAvPGAO04QXHCavoGyS650b89MN6YXM1wQF+ReiF3sYroxPd+W4ewI9zZ94olH7oEnXsgDSSEJEWB2trvrm1X5j38431M39bCI9KjKrMqMcI9QS8kwczXTCHN1NbXnar90dEfG9adS67cl2WhhNKALGwMgNmxmMTbibUC+dazKbY6a0sD5zDgoCGkugSmJ/VnX549ns1VPZMtsrNvPatrPl31+2ALpGHMxOlXS/2FLfvOX7yePtf9f4Ad8RosPX38q+5/vyldglPX3DchpTUjhGa42PIF3X3uQzOewgV4DQ2l5fORlSbgmfhj1DgzJBoBcQxUz+n0Dclqf8Ps5DfU3RWa+AkGCP+fPn18uKwqopPIDkN+iJwYe4hPUEfh8sfpnOr4s/S/L7+NYljraf6POo/agK5jXKCM0Jo69gSYAY/piOMTqFVUlDHemHXSA7ew8ZdIxZ5cedm5YroH8+jTBgIaZYI6s6qY+45LYn7LIf1H6RxDdxF57tLluPyfOgnXqPzA1A+9sEyDHxroo/bP2Rt/7ZfAHposMiW/UsCz4A1VdfODEZ8xFyg6e5QoIBM4vYciFmF0W0jiZOs9eID9WoenKFFj6ye+zx0CwvdOmgEmWhZ5k0vGT5PzVlB87Fgy539Il1uHZWroK+mtVXlb78d/PJODyj9p/gf3mhu1sZ2xvlJjbz/XsP6y/ncUEZW4/eHF8uKyFXUsBc2ygX+vII30ooRcMbZpZGjCspW/HROJGY1wDnRsP57QF8mO+TB8ovQvlmvw+3iAZuKoqDiin9eaYf0yHgUqdv7ryw5BPvY29B/FcsS4GYYH6x59bpv7777v8r1v/2K4wtHobfYOaVLef69l/9NnPor8tU///IvtHPENcw3LLCEsDc0CvQ8xbeWigjTdPQ2EPzwAb5wiRXiQcll00PyZD6l43rA8NjYE2XhOomfExwMZFE6QzfzY4f0Xlh+FWbviKxrO5aP2LdWgZ+u+/P5GAy/9q7S+8cZsYWr0Ja1lz+5m98K5j/8H+sp1ko2Bl6/8nrT8b8p2y/8AzxDVxmUWmlwbmeJP/z5E8bGHycnzD9vAMwNFgYhKkAro4TR6WnfXoXTd/lxOqUznj77OhhVFWXmqwxmcATgGbLeog+AtpFnb+assPXroduOduUueyp5/pJHW3rPprbYn1XUb78d+fvJy6/DP7TTno/nGpbLv9zF7+17n/YP+KvRkVF8R9fpwum/3CnN0R8Yz1A8uIlwrm/preuYY84kNi50dDzzQFYUa/CbRmeUxbMB5eW3pR/Fh6fAaX6jBucEwTqJlnzkBbA4MFlse0BZZz/vCsgyyqKD+AeR4pdIsrIBelf9Qh0/k47b9fDfsRP7M4vY7PD6MzDbYfbK7cqmL75/MzW+71f/X+j/0q+1e2Bfb7Zez/4zZraRz9+ZB4htfLCksFc7zph2/IQxzNMuZ5e3x4fEuzNGMNiNl5xXQDdqTFPHH6uvjpnaPCsW5DHg0BD53GAHRxmjQNiNngrQxjA3ZKc/5Kyw+b4UKFMWGb29dUQH/ZLpbZfvz3Xf6qf9hyhO2G7cdso9vPSV9Cmaxb/wEw12H/SixwXf33Vdsf4hfimPC0lhYtHcx9+lYyqm3IfTZuCpmgTRt66HD0gSLPOp9YUvZQDMEvkh/17A7GMjTPG2M2PoI2BWoBsGmDRJ6Bt7j+zHP+zHNZdfmxE8J72TaHi1qbWNBecv2lHi6z/fjvr6/8uVoVLz27bC9sNxyhqHr79/q/ev/H/rQ/kE4V+v8p+wX8QhxD2jLD7JSvpdTl3mN59Nsb8gYaRN0WPqAvlCY/Qgggz4ZhdY4SR11Jp0uWxdSzF9KL4Je+nGD/ql261/X36ZkLafpbcZZgHgLIs2FYLU/hk+78qyM/rMRr8SxfHFt3XBtAQ0Ioo/4uu/347y/Xfi1D/mjpzeZIbgLEAcO5/XP7P+n/RtggGAtgNCyi/74K/R9gA/OvAr8EM7/UKIhuqXXQH//nH6Vv9BP5Kr0FOSiDtA2smeeOD4B7e5FuQ1qx127R/JimuYNhgk2TIL1tfNNUUAePnDVWe3NT9BzoNqTAPAvOvzryw0kEXZzTy6PA1LOsMR90ifTX6mb6t+j247+f6caqy38Dp28Mu1gwVMfecW7/tF9w+58NKbP/4/AqFj2cVM7+pPLZL76bLH2IlfajFJ45VuT2gTz+4qbcAzDj/l30WaY4rkd3GyKAI3gDyENPP5nkzKEsAj8oQL59CfgJUBfGj475ZDSQFocO8LscNtXf55YlOGMS75+ZkAnq9FUUwwpMsyzX6xD4AcDl25c4/wrJb4zD13FiCE4mOEXcK6P+Lrv9+O8v134tQv7Q/xYWOWzjTFu1jm7/3P7H/R/6z/GY/Wg2xWqh/fcr6X8fXrlTWfixXSq7go/SeOZYtz/88/TeuCFfZZrDrdzDhUCOLlcGeuL4wJ+X1oIsu0B+CLGt+yPZjyOmZ46AjvjTRlv5JmaGbF7avsL5V0t+0NsuzgDLl9zP02V7/ovU37gu/vuZBFz+r25/Yf8SvJlv4zguPclhns2L6aZ/bv9Wy/7xucbPOU5jqPIInXrPnj3jKrS/tC9/+7PvJ6UYYqXMSgXm0jRN3vlQ/gvUihhOQwzmjBbHlm9xnMf0PLqVs3yLjW7xPPpsPvcbQ71xEuR0iMHcdE52ZfkWz5aZR7dylm+x0S2eR5/Nn1duHt35MwmYfCw2uVgc02GwxujgjjE3JJ9LZ/plsfFZPI8+mz+v3Dy682cSMPlYbHKxeB59Nn9euXn0Veev16UFQHYDQz8YoJgfrH1YPFtyHt3KWb7FRrd4Hn02f165eXTnzyRg8rHY5GLxPLrlwzXTgzE8mtdO5tGN3/ItNrrF8+iz+fPKzaOj3oOffyD/JzZIzEbZ7AuXGC99NWt87xTMjbHcJ41CZDCvHNNGY5ohFrSVszIWG93KK2P4uFJ+jPezs6byMlgcGzKjZSWyMpZvsZWx2Ojxdzp/JgHKyORjscnNYqOXQX7s2HC4O0+OuMlh+SvVv6AUpvcWL0z//fdVAiZ3i9dN/jjFgbNJbmIz+F14CqaAnLXJoCpqI619WmxlLDY6eYzm/JkEKA+Tj8UmI4uNTg6jZdyl6H/G8MqdsD7WTqzdWGx0ljEa0wy8tnyLrYzFRrfyjC28Ej9wSpmAHO+pVGCOFfp3/0L2U6B1PgS82SnqtQdjQ6xGj8uQl4FDs8yP8xbBjwmcY07g5NAqD4ZmI7IDoq0RYdWq3o/R4zJaeXw4/+rLr8nzJ7HiFc9/03TZnv+y9Nd/P5OAy//l7Sc6k02u5KZ+x7bN7V+mW27/p/u/LvpLnpxgtodxFdof8cknwClxvcuQLh2Yw25daaslDygczrlgzAfMmFCcwMzoSsvICvw4mZHblFi+xYvix0bCXRxFMsAcEa23xahHVn+4ZmjYjG71J40AD3Oq0hRz7SzfYudfPfnRa4HNJndwcsRtzLdsEtQtW3/995drPyorf+gvpplw899t6rXZLYvdfq2e/bK+i/HL9F9Y6d9Hp6jz5NinV8n+KT4p0fCqPQsFHXZRnjhN3v4L+XuYJKlbfhCUqQeDTx0ut/yaFSYNQY//QIc4lZdlTcovgB/HetTTntzGWEMuWxo19cZx7TA2oMuvWT/SEAjiWGYqL8ualHf+lZXfAPPocKTRcZegDv/h0WuU6/QC9Df/ragCOc1/v/T2J39WC3h+HFId8IUEC8Dcfrn9vmj/RVccdm3Y7w9lXLb++0XtZ9yXziffk/8X7pcpGx01t6Uly+eZU1Ek3K7jcwqWD5tvrLmEcK3DrYiZn28YzA6QZUPM9DL4h30Zjdo46gsWTt9MEdPjltcf1+puD/k0gswzsGex86+X/Dg0Bc/uHQy/btWxJ9ey9HfZ7cd/P7NjZX7+tFc4um4bU0vuYg6orlQ1u2Wx26/1sl/23C1+3vPvJXKKPWW5GKx0/feL7A9xSRmBnGIIfpQ1vPth+rt9TKQFLpue7UgCJ8UxzKZJs7yQXAY/h8+A3fUQCJ0zAvBGr5yG56VZwMohybcY54cQniczkxfLMNg1kpWU30jwAiinMIxdqvIy9JdiZPDfd/nH+ocX1A1s/LuNNpY5AmbbJZWm6u3P68+nqOGq7SdeAIbDujzL++iS9t92/7H9w+a1hz/9IPmPlle2uKSeuUxMcMV+3javVi7VIEIoAXbXxww1XKu1QYw0tn1QD52WAj0/HSIux8xr5ofH8LjWwj5zMcCwNH8fabyZpGr4jA4jYl47FmEZ51dJZB2EySnIZmXlV5daK5UbePZ3sHM+N9GOUJVeXbv+6q8ssf3470MCJZI/PHAt6iP1EjWruf1y+31Z+8v+kP2ite0y999WR8MPta6eH/y50kv6UWow9/H7Sa/byM4940kJCtQgSI0BzrCXUTYvLQJqMDoJ1sOnpijGs2j+QR3nmI/k1FYw8fctrTGAWz6vjm+CAajAzavzA62hGI/zr5/8oMd1gP2btkjCdLkK+r/s9ue/n73oms68rP2D/jWpfzBPN/GN2l+4/cpewt1+h/73gv1XV7DbAzxzlbRfm/KIeKSkOE6rVWowxxp+bV8eUAGwgVuCF1UNjGmsCdrUSIU0M9WIIybQY57xLIMf0zvPUAfdIBbgDFuLZYExwRrH51lHSzNXQRxi0LX+xuP86ys/Dtfj71Yb/+hIW1XR/2W3P//9l7d/CTZAx2KuXYyM7FL/3P6sr/0J/dIr9V/YUWKA4zk7/K6q2S/ij9eAQ1j3MofSg7m9vWS8LfI50TwdcDTQjOmBo2A1DeBmeQRxTDODMTo/BUXL4seCiBNMbB/xbZYvMKy/xqH+gZZYHvI1zeFX0qz+zu/ywx5ezc2m3BxjGwgoiZ42Qh03naduWbos+m/6u6z2579/OftHEEf9wscu9c3k5/bH7Y/1URpfov9i/4eVq0e0VVXrv6n/xB/EIah+qUO+fUapa4nKvftR+vewKe+mDqOi02J9qRzmebNrxrM0u9aOL4A7K295dn0d/BvZ0Ta71gio0PwdXpvnza4Zz9Ls2vlhDKLnt+7yw7YQQ3hNzriJJfWG+s0wq9N2vSz999/PnkuZ5U8Qh8npW/TCmb1hreM25vbH7c/L2F/0d4d4meuXWf+p60X2s5tI55ffTbAVSflD6T1zJsLtgXzGTgEoaBwLfYALXvOfw5Zxx2G8jJm/LH5VZCiFGkmeFBEqxushLnithjLFJMuQZ2XC5cSoOr/LLygFtjNpQDFuYuubu4OabFG/y6j/rO4y25//frH88ZKZDMYAcNAfyOgmXpSn1ltRbhZoj9x+QQhufy9lf/GC0DEgt6z+lzr8svbnDnAH+asQKuOZozD/8MP0G1gqfYtKwb3m6hiStIdkwuY1QR3zSGM5zvcgD/MYlsHP4S/83a5jUjuN4hjADZsi65CqATjWzUAd83jNchiz1/kKBvCc3+VXpD8wnGNs5dPFsokzziel/pRF/5fd/vz3J/YPky5rGELdgB3ZxIk12DJuEtz+oP8ItplScfv78v0P5smNekN5SjlWsf1hXPXgZx8kv2H9qxAq45mjMPcP5QscgTS2Doo0AjeCNNL4T6UhkGN6FryZ524Z/KjMGGthDrHLf2oGQusPw0EDqjSkaVgJ5Hh9DryFfOfPDIzLL+t4TH+4AXUbQ2U4NuVuHVtI9LARMWXENkGdX6b+++8vX/7YdLHZSuCBw/mpGE7dxn+NwMX0h3bF7Y/b36vof/hiiVGzo9jmxGk6WNR+h36a9oH/Zem/MaVrRLzBOlYlVArMfbqX9OFie0ThWgdlaRKoIKoUODGCgI7Ko8AunCDB9CzAWyQ/J4Kigz3jb9Jo0nhamjsD0wOnQA2Ajw3K3hBxX1qOtFmA5/xh+Mfll+sPdQTzVDa20HFjAtRraDOb+K8tW//99xdvfxptqevzx1DqFlZDQzX06C23P25/r7P/gZ510GsNytT/Xsb+oN08Jt5g/1qVwDZdqXDvsTy6f0fujAaAbwBweMtUAIe+HO8CUB+iPCA2DMcqANKbI4IDHTzYwHySXgY/6niatIHlBvCaoNIAnArgGKPGKWmsPFy8k/qHbbix4WJWfwIXDqM5v8vvBfrTgPcFk0y3cSTeNnSmj/bSTTelx7awDP1fdvtbl9/HxKYWNl3faGDVMzttPH+1GXr/bj/cfl5j/4EVoH0ce3XKrlZDifrfC7X/vgzunWROI7uFKsR6b1WoqNWRS4TTNs9HC0AueN3okTMaOyndjIsALtA53qQ0FgpBgeAS+DGX4JhL/RXIBa+bvSUpqIOxhSHGDU6/PSrNKo/Y+QGEXX6q9xfRn1YLTaAlN5s8UxNnazaxISx08jiPEQAAQABJREFUUfmtnbBNlL39WBNYVvst6+/Dk99ojmQHz/ju5qbcxI77LdMLvrW7/bAnl8VuP6/efmLoPsXZ5Mdl7n9NC+bZj/RGNbYisfuwuHJgjhX/5J3kMNnCcucMEE0d32U0roNGY9WOiorF62G4VnoAepZWgUS06+TH3LnRqAlAB8Wn8qs3jhUI4I00vNmI5oFMI8xrTFbW+zEe53f5mS6o/l5Qf9iJ1bkNRSK3MLfuTn0DnjuujF2Q/lubs7bK39Xgv5/Pbbyo/cHhz3U+P65IxSa/tzERaZPP1+2H289l9B99HNfF/u2i+mu2oCztn4seiC+CRapUVEkwRwnDI/M5lnhyAFIDhhF0gjcvMJyUrQQNkywNxJFOYKf5dP1GYdH8WBDRw2kVOn+O1YAxzoAd0pzIThomkWpsII50AjvNz++cJZ3f5fdy+gOPTQ1vqFs4g/AWPHa36bFTYAed4hxU6lYZ20++NJ0VRFh0+13m7/P5AIRv41ndwTwgrpDfwsKqxDpvtx9uP9kmFt1/wF6ccs/LKvS/Re0Xx9YNx1vZqB/lV7Wgxrpqlbb6fvtH6V3MDfkKr6lANOjsgBTtW6E47yJlFswPNH0LXpImDTABCRugGWW7hTzvImWc3+UXPLivoj9YRDEG0OsNBzhjGEfxcBX5hdrYgtuP3eOF6lbC9n+R+mNlXQ3Dp03YtxbsWwv2oj7XRnj79/Z/Be3f9JLxRfofOBywZaEcVK3/tfuk/cCih89+/J1k32hViyvrmaOgKXjsq3Vmhpw0AjleM20x0wwK9pBn84OYb//M0zIL5seGise4h5RAjr9PI52/WQcPHekMCvZAs3kwLGf/zu/yUx25Iv2hxw66tdXA8WGbGMLjS0cNq2LpFSpT+1l2+72u34eXoI52vk25U/58DlyhzI19vf1nbd1sH2O3f8uzf+y/4JE7ov2pWv9r7Rd7opxUGcip7edHlcN7P0zb2JjwP+eyYz4Y3osBM6Z5QgSGkHLPHWnzwrL42UGiircwcqrg2gwT6zmCi4S7DMcGa179WYZ5zp8ZNsrC5Xct+jPmijVstcPJCgMMw+qg/7LaD58zQ5V/X8HbWFrY9K0JYwBzkNkC199r0V/Vl9kPt5+X7z8I3mAEDngYfVXbH19O2w35/z5+H7P9KhwqPcxqcv/Dn6b38BjeZM9C5SKws7znxQR6DAR7DMvkx54jG9zoFcf5pngDv1D9aegZCPYY2KM6v8tv0frDlwd4lAc4r25Q6yrIG8UvVKqcBR9lan+s3qLaPzs9vsDhbN0mh0/rAG98Zt5+3X5VzX7j7NJjzNfsLrL9mCm5KvvR2JEHP3s30f1r7burGF8INJT+xjDT7Ns/kL87xr5KVlfzyBF1G7iztOVZ2aLYyhgPy1ja8or4jGZljOci/JiAvoNy2MB/4lHSLUwCuLO0va2z3LxgZYyH5SxtefN4SbcyxkOapS2PtHnByhgPy1na8ubxkm5ljIc0S1seafOClTEelrO05c3jJd3KGA9plrY80uYFK2M8LGdpy5vHS7qVMR7SLG15pM0LVsZ4WM7SljePl3QrYzykWdrySCsKACZpZyRDnEYxxHyvAbxNY6y0HMKDPmZbtLZRxGs0K3OZ9mO8jMvCr3Witw27SgLE1eFza2Ln8saLALfJ2GTO77G05el3z/mwMsbj/C4/0wXTjTmqo2QrYzxz9KczSOWk6HvK0v5eZD9w7GH3x38k/0FnqhfdSIVolZ4zl8sZU14HO9mBuHx4pJu3Tc8zCgUN1DFPH3IoazwsZull8KOzO8Xbuu46bd624HTTO7AOgHnayEL9mQ63qHSmnT+TiMvPNANe6/BScN36A33ksWL0d2+24G1GW7oFz91rWIn9WmMsu+1NbGCMIcU2zwWlRyrSX0svo/1RUi/7+7wPGyrFYafbm3XZxdYvd3GPr4X7vwH7s4WVp+qF8/Yb7T4QPX+zZW6/snZbVvvFfmrQz4CctZlXaT/Z3b58+3tZfsUNXDKzAmE1PHPhQXzn4/TLWFDwGpWLwM1iTBpO7VyOmE42K2NxEW2R/Dx2SYZyG424pgYf98Gh4zCiqh2y0VlXS1tcRHN+l1+Z9UfbHObfAfilQxx5N+pzS0V48eDZYx6GJEHKwrLaLzwQehwaKoaFvUjD08Y93vpYPUqApvVEW2VsbdFib3/e/src/viSZ7p6Ef3FvYyxK+Uznjdu/abF5Le0xYvsPy/z+/W6PPnRe0mlzl/l/c0LMfCfV6Yy9Nf25cEXOzhIuoHl+3zbM0AHUwuDm3sA1FuH1avc2JCdAx4qkXmer7Rl8WPDRdSHBxTvsv7ayBTZZWk+DH1oGMoaolWxIeJf68+yzFdaqL/zwwPg8uNcUtWlsuoP6tei8cecITTe7AWG2xxQf7k6iLAOp1WMCIxaYxxrXJdxD2lMXKbOj+EVky6umU8vWa2HNUPgA/ga40xjbecc+oFnsIY5PrpRdw82YaORATDw1LDhaQK7Qa8ivh08TQyN4hq/zxeqrC6hbvxVLPyAmw15qAPLsa6Ur7e/7Pm5/cp0YtXsD9roIf5HWMVavv4T7e+C/XefeIHtdVXCSnnm+FD+6z9Lb2xtyTcI1Aja+EZvJ0DYNcvZGz7TcVCgh05g2fzY32tzA3Po+EaHw9Ix+SgDcbxmYIdhnUdGyT4V6M2Ud36Xn+uPtx/aBrcfmZ10+/ly/UcXc+SA4Tpl7z9f1H+jf/3NL/84OY77zqqnV2POXPQU+IAwAv7MQBlX1emDJUAL5Qju6AVgzMCyTBvY4473y+aH4e1g8KbD+mlHTIDGCwSCMwI5xnodaLxkGeu4Mxee87v8wgsBlQXB9cfbj9sPt5+X7T/gH+kQyFWh/3xe/43NgQ9WDcjRrq+cZ4439c1fp/XXvpD/DICtRTCHuS0J5uLoEIiluT0AHzjpulVAlM8ZMAR0RjcefrelF8XfSuQmQFo7B3KsMyuCYOAtu8o+Fd/hgwDGQlxuXjouyy92fpPItJxdfq5/1rRiXTBtIc3bj9uPFbSfvWFNDhfd/115/z2Q4cOvyX/49C3dCcia7UrEK+eZ41Phg9oeyGemCOaR41waSxuQY3m+aRCc8Z/gjp48Km0Z+EfYxwcrh7T/4JtUUUdib1i8F+arJ4oXCHGH4/wuP9ef4naRUb39uP1w+znbf7D/6TfkqIr9J/tx6/NZ/8NU/nYVgRzt10p65sww/8FH6RsbY7k3632z/Ni7Fr9xEMRZmXl05i+KfwQlxIbCd/CT58C3gTWLrd4Wz6PP5s8rN4/u/JkETD4Wm1wsnkefzZ9Xbh7d+TMJmHwsNrlYPI8+mz+v3Dy682cSMPlYbHKxeB59Nn9euXl0588kYPKx2ORi8Tz6bP68cqCPe4k85bSkuF8k/6L6v6vqv7Gg6tEvvps8tHtftfgcOFilG/zFd+UR3ijOeE/mZYvvL/bOUWGYp2PtiAnieG30ZfKnOOQcRyc9w6TdHGSybnEDjD0ulsfY6DGNaQbnn8jH5ESZMFhs9JimBUIZy7fY+Cw2uvNPZOryyyRAHTH9sNj0xmKju/64/phOLKz9NIDX0O+w/1lm/8f7fdXfh0E/Ix4w2a1ivNJgDo7H9Mtvyt/iZAXM24ThHAUwFPyuCtTMBxuerpYBLc4zgLdMfuxzNer25FABXbDwGsXWnvfIa/zHeWYE8nkcgScuE27f+SkU/Meycfll2uH6E1qJKse0jnj7iXTE20/l7Qe8WGm/I0fsd8rQ/1G7Xrb/Zf9PHEA8YO10FeOVHma1B/buT9Lb2ODwK3Y9FRPMQVuxD12Kt5DLy2PB/Bj334CluJnfAzsWoA3ur8V9uXL6RRPO7/Jz/fH24/bD7Wfcf2COHBYB6pmrz+1KFtz/navLBX4fG/F//tNvJc/O8a4YYcU9c9nT4oOsDeWQVwRtFmuarx1QCAK5OI80Xk/RSsAPUNpJm3JK8MZ/GyslkNNr1FFjgLS8jNFmYud3+bn+oFGgrXj7cfvh9jPrGzGl52TYlW4Z+7+4P9b0C/pv9vvrAORgxdSUM1758Ph35Ivbv5VtbDvSwJFf3AF+4sWKPHNUEPXQ1QHwuECEyB9pC8xbOj/OxNts6O70G1qvyLNCg6QeOsB0jC1n62AjyM483Wx4+i0s90w4v8vP9QftxtuP2481tJ/oSjrYGPiMo1Wl7f8u2H/jxJfRs6/JF9Z3r3o8ATSrfqe4v+/9ebp9WJdvtAKan71lG2YloAveW8VyLG6eO6WXgH/UwTFDDdkF+GJtNGgnjBQBWRg91bkbaKC550HpJDAxE5w/A/guP9cfbz/Zm77JgbYhbxduP1bSfg4bMsC8tEPu1FX2/k875pn+a7b/3h3Jb/7i+8npTLGVvYx8Nit7j/mN8cE2h7IPz1pCCESF5b/BIXrc1OuGPCIkKgeBH8uYS1fpJeCvb0rawSaOXTRA86/S46ZeNxhbA3C2txwNMYlKxzmSTNBQK6YjEcH5XX6uP1E7AYDx9pPZCLcfkV6soP0kkOuJHGAOkroHyt7/vaj/Zj+/TkCO/fdaeeZ4w5Kmydt/Lr/bbGAhATVW0RziOB3IRmLMwKJTNLtgZpwuKltEi3nidFHZIhp4ADITPMRbaITN2Ntmb9QWg12zidtyml0wM05HZfKyRbSYJ04XlS2ixTxxuqhsES3midNFZYtoMU+cLipbRIt54nRR2SJazBOni8oW0WKeOF1UtogW88TporJFtJgnTheVLaLFPHG6qGwRLeaJ00Vli2gxT5wuKltEi3nidFHZIlrME6eLyhbRYp44XVS2iBbzxOmiskW0mCdOF5UtosU8cbqobBEt5onTRWWLaDFPnC4qW0SLeeJ0UdkiWswTp4vKFtFinjhdVLaIFngSADmcX3mA0Z58tee5vg7852hxnxWni8oW0WKeOF1UtogW80RpzJPrfvx9+Y/oGfP7AfvKh7XyzOnTxANub8hn2AhxbEAObyXpVBoFdSiWsakAEpZmfI4ngEKlL5CfnkR9oxplUG7cyhokPQoMIdKEpRlrOSK1ojRozq+icfllYnD9QaPx9jNpE24/YGdXwH5iD7kh+w8Dcovuv6hR5/pS0F62/9V+Hf37ugE5ynH9wBxu+uP3k96OyH0KgIrUGOIYLwI6hDwNcGY0xjyrNb5mubLwcwh4wM0d4Zur9bHAgYAOhsaAHWPMeUnja5Zj/UnLeXCdp53f5RdeDFx/vP24/Vg9+8n+gv0G+w/r26rY/+V1Rv/Ffp39O/u2dQtrCeb4kD/6IDnAmXNPDZSZQlCpLW0xPXFWzhSkRoAXypJmZY0Wx4vgZ4PEW8lBDOgMmNGjYOAtrz8BXgBypFlZo8Wx87v8XH+mp6TUvP24/aiw/awDyLG/YL9B+7/s/usqfp/9Oft13s86hrUFc3zYn3xXHvRGckbgxX8bajVFUBouxsFzp8OrXEgQaIzNY1cGfryPjOA2P0jaXFUeeeaCt46gjG/YmmeeueCxI3izYQPmMyiNsfOrt9Pl5/rj7cfth9rGCttP7CM3wkKnQ8woG5Wp/3qV/rfXlDP253w26xrWGsxxXL12Uz7DqQpDvhnYOD0VPPemheFWXuu0OCQM1DHmBeOy8PP4lVEfrnOep0eDE4ZLCUR0igcSBkoY84Ixy9o8OXZYRnP+DNRSHi6/ib6Yjrj+ePsxW+H2A+0DwdpGGe0vRm7GOHf8oDuUYRn7L8rvsv0v+294ytdynhzlZWH9VrPanUfxP8P+c1uJfJ0kA3R9IjdqO2LS9DrkW55mR+WQXRp+NIgGhoJvJQOp0cjauZp5GjQFKEQommDtkWQaQcsHes4Dep5GnmY7v8sv6An1xvWHUvD24/YDSlAy+4lRm3EDq1a7Z3gvRedV5v7L+tiL9L9nqfzNX63RfnJqYAo+HMwFoXz7v0/vDnfkDc4h4D50BuA0RhnS69h3jtjN0ronHa9JD6CuTPzYga6Jv1toxFykncJblxB7WXoEGi5F6QGUMS/F/Rto0zjicX6Xn+tP1pa8/bj9qIr9hE0ft7EvKXbQHVSl/2Kf+qL+t53Kww//KHnK57DuwcFcpAF/+IP0Kxhf3KWyG5lAjaDNToAgnWAP9OzYL1zHjSMux7LL5t+oS2sgchOArs5OmHUiWMO8Cey4l03qjjtnA34sx0Cgx04rpju/y8/1x9uP24/K2E/OoT5Cv0WXQ6X6r+f1n/26HP/i/eQz3pMHTJVyIUwk8OaR3IfrWZc1qxIFIGcl7LgQ9U+DSDe1AT/z0pHGUBb+LhowjO4B/sdmfNX9jzpyFMAAnnkZSGMgiGN5o5Pm/GFFYxCSy8/1x9tP9oJodsLtBy1lqeynLooDihtUsf+yfpUyjesPr0Tvq0/X59xV3v+LgnvmZiS0t5e2Ht6SvwMjnQNdezuIi0554HTyQaZsBu7ismXg5/1gp+9b45HUWTcCM+uIbG7HFC26AfPORSTnd/m5/gRPt7cfWAbMv3D7EdnUyFguy37WsGoVh3Tri3wMili1qvVfcf2hZ+M3viz/ae8tnfUUSXq9kzlgWW8xTO5+by/p93oB8Qc3W6xI5pUrBG3R8Kx+Y4n4sSBCGzYbOOuWA7nJrZ+nhddse+vWooHm/JOheBPhOZm4/FQ0rj+Rrnj7UZ0411ZAPUfz9vPS7aeGXQ3SmhzQ7q9C/6WC4Af6VPbPDuRyieQJB3O5KCaJX/5xcoy95fb1cOlAtj3nimjZTASMWXOvOoQ8DnvSkVYGfjbsYYqTInTDksmeYdmeG6h32IMuj6P62/5a8f0bzfn5hF1+ud6YHrn+5HNvra14+5kAW5OJ24+rtR+07zyiC30Y16tpKEP/w4rE+m91ukz/CSfKE/bP2V35ZywBH2aNpTGTfvvfp19rjGWbZAI0bh7M9BAeuAbm0zFtoYhmeYzLxI83taRZl9uYxB7efQHs0PGiM566p6n6c3PhcZZfVLaI5vwTCRDouPxcf6gRRW2liDbRnuxFwfXH9edF+oPFacM0zYZWp/RnBfqv/hgbA//z5LfxfXl6IgH3zE1kcS717H+Vz7td6RkQY2ygjWn+k4lxqz1ht3JxTCBo1wSCTPN/GfyYw5cCyD3DsAYWumYdhe0PZtehcyEAIchTIBJiBX1M89/KOz8lkYVITi4/1x9vP24/FmI/DcglTYzAwOFg/Q3jMvU/L9P/jYbSZ39sNtbj8xKY64k5X3Q9KW//PG0mh/KN5qbUrUHEHjpKxZSzH473teu4HMFe2fhZdyjALcyjaxGA2MbCSCcBkKh+ENARrNEzMEvnd1h556c0JvKgvHjt8nP98fbj9uM67SeGH7kt20HsbCh7/8O60j5afzmv/xwN4G3cld988g62wPcwVwIO5uaKZpKx95fpxm8fydepdARlVLoYnLGkATXlQj439InLmqLGtJgnTnNzlEXxc0Lpxkh20UraBGpaf8y04GQLdkAEaBYzz9Jx50S6GSqmyez807IyoOvym+hUrDNx2vXH24/bj4vbj/pY+tgM+KiJVZ5qfxfYf9jo0nX1X2dnkn7tnvzN3u8nXb03/5grAR9mnSuaSUZQpC8IxBi4SJUrhOzNYjYtKGdllYE8Ea1M/JyQetKXA3SgHdYVnWrKmXQEHXHgtdGYxXJatiDt/BNZmQxdfhOZuP54+3H7cTX2E/a7S/ud9jMgpytXo77G7E9Z+x/W7wX95xcO5OwpPj92z9zz5TOV++5P0ttwZ79B5ePeccy0tMVFNHrl6mF+nO05V0b+Zkt2Eiz4oKHl0KnF9CqZ1y6m816tjMVFNOd3+bn+5PNL83ZV1FaKaN5+vP0UtR9sPXI66MvJi/qUqvQ/5/rEujz86beSZ2wTHl4sAffMvVhGeQkqFsBcplwAaDmAI1gDuOO10bQBBRo9caao+ZeVkJ+GoTuWQ3qRQgeiHQ89KQRxed2ZAMDLAVwG9rSs0Zw/kxnl4fJz/fH24/bjquwn5jing4EcGZDjtJxV6H/i/hMnFz1zIDelMS+8mO6gX1jcC1ACPMO10ZQbVL4iiVjDsjy7rmNF62jGQ2dl4tjKG82uF8UP8NnGDuE3sNpVwT47IgVpmNBve0MZzeoYx7N5do0hAeefrABWmcZys7TJa/ba5ef64+1v2sNpbSSOV7n9wC6PsAfBkTRxPNeK9j8NeBw/9jNXY5W+UNo9cxcS03QhnuGKjRk7BFnMMc8bwRav2ciMZtcKyAzIEdShTFn5sfii18bmwjiGRifUmrct70gIysJQLO/PPE8EG7ye9UZZWecPHZHLz/XH249O5XD7cXH7yc2A8YL9DFZZgVxZ+49X6f+woKJ7189cZbO4dHDP3KVFljHs7aWNh7vyNcCXZvwVBHFEd1wnXhSYPydLi5eJn545KAi3LiFe08AEV5rNC1oQHxxmLQrO7/KboxqqLq4/EIO3H7cfM40EZ2rj8B454IrVqvQfRfb/uf0f9j1941B+iyM1Z+6+6JucNisB98zNSuSC11S4N74in43RuBSABT42NAK5mGZfGSsy07asOy5bJn68CY4HDbwJDjkrI3uDtFbGTpdzN4zOmIH5BHLaKStl8kGa82fycPm5/nj7cftBaxDbykL7CftLOxwDuSr0H5mlm3w+r/9jP4qtvz53IDeR12VTDuYuK7GoPA/7TTfkc/wroKuFOQyM7dw5bXSBTqBmZZjm3jz8OpaNy5WJfxN1H2fHw3RoaHCAswI4pvG2mA2rAtQpOAl5LDOOgF7ME6ed3+VH/aeuuP5M2pa3H7cfuf3EdB7aXyy8w+4j1es/4n5tXv3Zf7IfxTw5dRrQJni4vAQczF1eZlMc2JX6DK3soYI37u+DXDTEJAdqBHKg5yGkCdhY1kLZ+TEP4pj/9hrJDid+o1TjAwJpeMtKcqBGgBcXDGnnd/nFauH6k7UTbz9uP8x+0t5ilOdoFfoP6+fsXuL+j/0n+9G8jCdeSgL1l+JypikJ/G//85/0/tE/3Rt2+3ID5+OlmGuGoyLwz8NHAN4a8MAB+aS8xoqChIpMwBfTEsBqAsBS8w9lAFcc/1sYgq0JPCrYlw6vVZJo/empA3ijuy5Br8Q8AjncbxKXVc8DAF9Mc37I0eXn+uPtZ+3tB6wmhxwP0B/0Vqr/KOj/brTl4Q++nRzhnj28ogTil+NX/Kr1Zv+zd5LDd/8NtnG8Ia/nkgheOD0pIpY06MBuOlyZl4WDWWmBR+kl5B9gkioOcn7WTOUm6jhZ/IFxV61/fJ8hDbA3fa+gn7t/53f5sU24/uQmwWTh7WeN7EddBsNEjkYptiApof23fumc/X6J/gu7GzxmvzlReE+9igR0ztOrfIHzTkvg2z9K7+J96u4UFY2Smwjnw6pspLjmHIJZmjZg5E2FEvKPT+FZ25Ad1H9T68pOmBPpLI5vALQB8nLkF8rQcTlLc/4gR5ffRAKuP95+1sB+pDhSES/LJxy5mSg/UiW0/6/cfx3J/o//VbI/dZ9+8UoSAMD2cJUS+PF3kv0aPFcKygjaQrCVq6Tbma56fivLRDQ2kpy3xPy8H6zGO+4mcowh0nSEfbP0Vg3QEbDxPwRs5Jnlg2Zlm1YmouWA0PKcXyXg8nP9UUWI2oq3H0gk2AmzKVW0H7Sfp9gIeDSUYwVyoU/QfsDsH+ytJqO+oqr9x6ArTx3IhQd7hZGDuSsUpn0VVuU8HnVweD2AmS5sQIw5EOoFJZCzNFcosQxjzqszEMdrBXwV4G8MpIPxwae1Pu4lGFbMlcvAHYDdiCAOcT0cB0aja2mWYx7jOjccdn7tnFx+rj8KTrz9rLz9SLuYRg372R5Jt4r2/7L9F/vFT76XPLG+0uOrk4CDuauT5dQ3/ez7ySMstz4iSCOgU+AWedpYGFhNwR7eyJI6yhDA8Z/XWhQfVeDHm9Yoqcs+jpnpsRNKAcyIywjOCNII6BS4KZEZWUBfpcaa5c275/wuP9cfbz/rYD+w2K0/gN2k/ayy/b9o/8X+kP2i2X+Pr1YCPmfuauV57tve/jD90kZNdgjcGAjSmGZsjQDJqXRR2SJaGfkx/Lo9HMs274kGmYDN4lmagTjS4zR5GIzP4llazBOnnV/F5/KDGFz/Ju3I289EFrQpsc2I0wuxHzh/FCDujCCOzyW25UW2vogW88TporJFtJgnTheVLaLFPHG6qGx3LCeffJDc5716uB4JuGfueuSaf+snH8gDrNo5pYeNAI7BAJ0OweKayh+nma/DrogtVIUfOwuf4ozWQ/xnczzCDdBDRwPKYOBMh2BxTeMZp5mvw66ILTi/y8/1J2sN3n7O24yq2A89pxr2kXYytvlxusr2n33ZbP3Z/7EfNFvu8fVIwMHc9cg1+tYk/dF35P4okVN7YzGFN1DH2ILRzO1u1zxaq0L8PTTgp9hXr2cdD5Adtk3KgnlLLM86aeYajcOuNHx27fwuP9cfbz+UQFXtB4dVaRdhx3u062bbGVswWsXtv1j9WzjBgv0fZkZPvdzb/Xp8dRJwMHd1spz/TUmSvnkk9+tDTHKNAt/GrCFbIzagx5gLJTiHjnm2aCJiV29eWfkHYxmN6nIIA3bcAjDDasxzQ/owbPkpEgbazFAzJo8BOud3+cW6z7Trj7cfexEss/2g/WvgZR4r/w8wYjEyPV5l+6+OByzvu/tUvsCMaAdy9tCvMXYwd43Cjb8aBwiP7x3jHFe8qehiiJBpix7YsGM609ogonJMsnxcruz8AHVnOAjiGUCdOlbCMEPeuHmt/wR80dAs08oQ7p9lmHT+aTm5/Fx/vP1AB0pqPwBjsKZLnnUxrEr7VTX7zTozsN4WX6T/oUeO/R37Pf0C/7h2CfhxXtcu4skP/PVf/0n6T/7h3kl3WzZx7l4Db5MJdnfHUiac/oU5ZQN4othQSKMPnjSmx9iZl2Xxodt/MM3GVRX+UQMnftUwNRBHgGFvugbeINTjxjjl/fG+cSQYhqITgjjSeMOkMZ1CS1kWHykTzu/yU1Dv+uPtp8T2IxlJrwdvHGwfTGB17fdl+59hCiB3IPcdyE36/kWkzg19LeJH1/430jT5zo/kSwAxW/nSVnPDAcTpdiR8E+IYKukWM4l0z2gUpKWrwt+Sdn8gN+stGDeGeFyV17B6AHQK9piezScCHhoPy1va3HjO7/Jz/fH2Q0/+kuwHbRJe1g8xP6Y3a58rb79f0P9gw/yzjzFHLvGhVfZOCw1wcnhYuASg6D96D5NCT+WEv02spiGANnVph/Q5IBcVVUOB60rxJ9Ib9+XpxhinmQUARpurIRhfel3mGuKoqPNPxObygwRcf/TlxtvP8uxHvYe947qyPxfIBfulNju8gFfKfj+//ifs1xzIBSEtOHLP3IIFPvtzf/BR+gaGU28QkXGIlUOuBtK0rNGxtQmvuUqIe/rk30NLELxzVePH8MNWe0O2sUxXT3+opRhixlCrgTS9R3TQSh9l94xh2nQc0pav5a2c87v8zEtLBTG9cP1Rm+Ht53rsR62NOb4DOcFoS2dd7Lfa39D/9Gty/IvvJg+V5h9LkYB75pYi9smPsgEAoB0qEJsFaShGel6aDScEgjrz2jFdRf4ELnkYwGfNVAYxYNNbpJcFgfQshc9AUzpAnXli2EE5f0En5fJz/fH2c+32g/YLmw4/HfNoQwvBVq+y/Y76n0MHcvbglxc7mFue7PNf5lmueKM7IIGN31a2MqYXjt66GLAxrTtuh7Kxp65q/H0Yws5YnmHS7AmP8iIow/3mMb1w9NbFgM28C1Y29tQZzWLnd/m5/nj7uQ77McJ51F14pGi/sImm+oOrZn+tj7HO6LL1T1ryjP2X8Xu8PAlMhuuWVwf/5SCBd3+S3sbihzu8NICmHrhwnYM4euWiwLJslJHjrpL8OzWpYwXYDYC5lgE0GmHeKq9zEBdoJgLmEQA2jRDK89L5XX7UA9cfbz9XaT8AevpYZX+s+2muiP29bP+BPufpT7+VPGP78rB8CbhnbvnPIK8BGwaMxD6nwBG4EaBZJlZwatoAHem2gJU0NkReE9hVlf8EG2p2sArsGBsN88QLAjTeJwO9dozNIDM94AcCaQRyvGanzZg053f5QRU0uP54+6EivKr9oF0668tJH1uO0F7xO1fF/l6m/2A/5UCOT788wcFceZ6F1uSjD5IDADN1W8dvSrIxqagBuzi/h7MleG2GhaXj/Crxb2HDSWy2uQ+AZnhVJHK7WccckWQABMdrA3a8/zg/vnD+rGOP5ePyc/3x9vNC+9GjXcKA6hntS2xfV8n+2n1ZzHuN+w/0MY/YTyndP0ojAQdzpXkUk4pgDsIRvEoPsadaajtvW8PiNVaAajCkE9OYwWvjs7hq/Dp8gQOp+6fYdHMoYwMeCjrChXnmYhrvn9f8tzRj51dxZKDX5afCcP05rxOkePuZth+0P7WuHOIl8JB2aR3sr/UbFrP/YH/Efon9U6Y5/lkmCficuTI9jZm6fPCDdHPQlDc5dGpns7JxxWmy2Bmuxm75dj3LY/nWUMvOz/uo17F9SyqbMXAzwNYEOLE0y/I6DrM8lm88zu/yM12g3ph+mA65/kxkMisLk9fKyg+jBNgA+Nh0YdaWkl52+zlb55ex/xzxaQ7kwYd/lExW7JpQPC6FBBzMleIxzK/EN/fS1r3XcFrEQPToNTMcG3hVwnBrdqwX96ZD4By7/PQIXFtZi1nG0lXkx3l/TexOcrOLTUmsw53qXHB/xHHWsRhIs5j3b2nnpzQyWeWywLXLz/XH2w+OUuR2SU05ORtK32wm24ulq2g/X7b+kMPo0RO5/+le0ud3eCinBBzMlfO5TNXqm79O628+kC/hDatlxsQKcMQV0+U0WF5saJgRX1uZjCObClE1fmwDsNFqyHZ/JHUFH+FmioAas3KwgnE1K2P37/wALy4/lYDpRqwvzIivrUwQWQZ+w4XlxeWdv1ryw7HwIxz+fDocS9dGLlbNftp9UTdf1H/gbOze/lflwadvYZ8BD6WWgM+ZK/XjySrHhvTD9+RzLNM847wFUmlg+E8gRoBGmrnTu5hMZ+WYx2trwEavMj/2Des02rKP/1OuWI07T+tQKQ8GuzZvQ0bN6JoXypBuXr64rPNncollQllRLi6/DAhTDgyuP5P2lklkcl12/eHCqd4QByzW5WkXm/+anVxF+8lncxH7z/7mzSN45BzImTqXOnbPXKkfz/nK/Xc/Su8eDGTXcuzNSoGdrYgImcwbcNIqhmPnlZtH51dUgZ97053hODR0qO1zHQbugWCP25WYB04BiLmikD+PzvtnnvO7/Fx/Vr799LY25fikk201wrbPUAX7d132G0Orhz/+TrKfScI/qyAB98xV4SlFdfw3aGB4W3xC8MZAsMbJqfS+MSaNeUrjBYIZJaYHWEDBvFXh79RkmDRwgkRXnm3UROd0ELDxTdswm4Ey3j+3JdHtS0jkNcppWRRmTJrzu/xcf1a//XBeHPaNe0r7QSC3jvazqP+4uSX7DuTYE1QrOJir1vPS2nJp+GldHtTDRsLmeWNMg0TAZjQycCi2GfJI5z/LEOQxWFnGVeVv1qUPD90zdMKHnPdi3hTeH0EdNrnMT5BgHkFdwHO60TDTpLMTZ57zZ94Yl5/rz6q1nxraN7cZweSUp3iZ66+C/aMtf1X73UVHMdqSB3/2TnLIdu+hWhLwYdZqPa+p2r73w7SNM0jfGGGo0TLMMPGNK6bZW6c1eObF6bhs7MmbLRfzxOlS8aeYwtyUTcyt2xqPcTZpAGms47y01d9AHD12Mc28ds6fAd5ZWcayij2hs+Vcfi6/ora0CP2p1dCmh9LBOdinesJMeHm132ZMm1Z5+4f7uKz9r/MFONE95GYm68TS8XSZJeCeuTI/nRfUDR663u1n8kWrnx3yzOLqWQOQo1HidQy4zDuX04Nnj3TSGFaCH0vpu5jMXEtkH3tEda3zMO8c71NBBd7Q9Z4B9hgzqGcOQI75vI7Bh/PPABGXn+sP2gjbBdsKQ4nbT6c1Uk9cdlQggdyq2r9L2n/2H+xH2J9kT9E/qyiBvBFWsfJe50wCe3tp7dHrcm/clw2swkp0XNXGUFGEx38pfSady4/jsCiflwvXlp/TK8qPI3hq3HQYwG4DnroUb+jTes9xJLiT8rxwbfef00GI05av47jOP5GNyy9bPRMUJNaZOO36EyRwje0P7b7LTX/pieOvxbYsl/+K27/4nuM07x9eys69x/Jobw+TUzxUWgLTnVqlb8Ur/+5P0tt4S74VSwKbCKdowImugmBGMFxKJ/CzMAPgjLxK/E0MR6d92cEQ6gbnzcCQTe5/BoDY/Ws5eh44dsgQyjm/y8/1p7zthyAOjfsE7X3o9g/PyV7uI/vfa8vhT7+VPMsMm39WXQKTzqzqd+L1Vwm8/fN0C4DtNbjO63oiRATY7K3MYgI1tm3z2vELchoA4KryoxOuA/TeACBrDXHPsaeOIE1pAHBjDLfGeeZVsTgvG4HCnOb8Lj/Xn4W3H7Trbr8lJ7UzzDDBcGNs28zuWZzbushG5rQVtn99boy8IU8+eSc5o833sBoS8Dlzq/Ec87vQBroh95M25sAGI0UDxQL2cmYxjF0O5tXA0YsHmubjY1X5OUcEwy4HWM77FGBNtzNRgBa8dTgyTIfJDMgRoJGk9CiOPTPOD+Dr8lNvr+vP4tsPfrHHLZtgvw51DvEK269Xsd+YcjJAR3DfgRw0ZsVC3pmv2H2t/e1wHt3+HbmLLUi2CcoI1mgEzBPHawopNgz2xhqXZZlV58fwa3OAOXWDoTQJ4AjM2CHTQ8cwS7Nr5hnAI7Azj53zu/xcfxbTftp4GauncsL9JtfVftEO8SX8RfeP7ZtO7z6V/T2fH0eRrVxwMLdyj3T6ht7+03R3qy238ylxQG/cT0hBHD5gABIbWjBgp5koQwNhXr114L9BUDeWbWxA1yaSI0AzrxyBnQI3fEBmeRrATcvk+RR/6Mmd3+Xn+pO9NObt44raTxNnhjY35bQzgJnCi2lun9j+aMjW0H49z36f9eTZJ//S94+jeqxqcDC3qk82uq/f+8t0486ZvH6GeXQkB1unJSythiBYA4I9Bl4OmtjmZIChV1zE9FAk/65V4sf91jEMu9UcyCaBGeaYJPBOKoijXAJWYzJPk6YXiAj2GEiDFy91fpef6890uwhN5FLtB6v1U7xodTZTOTseZUdv0e7kQE6N0LSdWkf7FdtpLPYaHt+QJ7/6/cRMNk2ThxWUgM+ZW8GHOntLbMg3H8t92LpsHyEkaPfqAGo0dkyzpfNUiPhkCH4PAE3CcizAchpWnB+TqEcAZMeYUfgEHrrTVh0dB3ofBWwUABJMtwDUCNaYZudELwz/83Kg0XPHcs7v8sv1AgmmXX8u2H7Q/mp9OWmgPbJdwmaN3H5dyH73MKz6wIEcGtsaBPfMrcFDntximnz7R3IH1zsEaaTnb7VRmgCPeSzDtMWzNF6vA3/SwYkSG9JGZ7KFpa6cV5cSpPH+CeKsk7Y085mnQ7ChbBGNZYwnTheVLaLFPHG6qGwRLeaJ00Vli2gxT5wuKltEi3nidFHZIlrME6eLyhbRYp44XVS2iBbzxOmiskW0mCdOF5UtosU8cbqobBEt5onTRWWLaDFPnC4qW0SLeeK0lcXpNqMeTmuAkemlm9k+cWaL3H493363NuT4wz8QbDuCJQ8e1kIC7plbi8dsN5mkPEAZQ4j7aU/GBGrqnaNHDmm+7dIzx9JmNJk2QMe0BfXirQk/OxLMy+lii7l9eO2epTjPUb1wAGrqXaFHDmmCOpsjZUCO8mKegT+Tn/NnMnP5Zd5c159J+2H7SgZy0MXqVNiqDtufgTdrP+tkfy5jf2nXad8//IPkqQM505b1iB3MrcdznrrLn3w7OenclvvNZrYtB1Y56akRajRC2oZWzYgqyIMbjmXojlOe8K3rxI+NNnuDDt542/J0gI6GoEy3KIGLTUEb95xDGqvsdGjVQJyCvFCG+coT5Of8mcxcfhNdWjf9wTBqivldZ9qu0L6wtVJP7UwYQXD7k9nd59lf2ZIe7Trt+5TB94u1kIAPs67FY553k2ny7k/kFoDGTXrlbOLsZHIcifhnZghazi6ivHXlb25L0u/KJgS40euEcyJs3JVyAnDLx2GR5EESPERCQ5SndF4zOH8mB35GMuKly2+19CfZlAHsThftp3N8mo0KxPbG7Q+U/gL2Fyvxj/70W3Lg3jhaifUM7plbz+ce7jpJeZzL6bY85K7gDXrdYDjUdhCoxSFcDzkMi7SWwUcjXDN7HflxXNA4GenquqcQypPRppyZFy4Wn4ISEEbw5DGtp4MBtFlZAjx6pgjkNM+AnX1JuHZ+l1/V9YerUuH5Pxtuy/6oL/uh/aTraD9e1X5yg+TTJ/LwT/VYLp8fZ+ZyHWPdqmIdb9zveSKB/+N/+pPhP/mHeydnW9LEnIsmBr3ScSucBMF0HxSiNyA20tVzBBDH4UHLY3afQ4xEdWvK30uxdUJH+sOWnEI2Y3RONYC1WsqzXeltAyDDfKAEyykgSJRNMDs55BHAjXAdQF/KcgrqwGJlnN/lV2X9gfoPhljQMNiQo6Qv3RHai9sPtHkYz5exnzAZndsH8uijPcww9LD2EvBh1rVXgWkBfOvH6Q6W/9/ZBHmI+Sp8Wx4CWOgbJGkFaSvHb2I+Y5Y3ehGPlY3LGW2V+FtbUse+dVsAZm34lGoEwOqNw01aOl4sQRrvn2WMbuVIL0pbOctn7PwuP9OLIp0xXYn1xGhXqj/YVgRIo0dP3Bgb/BbZArMT/F23Hy+2n1zkAPT3zOfGUWM8mAQczJkkPM4lgKPAGl/syuubOBGhyPiyIOmclKygLwJ49iXGZ7HxxKBwnfi1w2roC3i7XZfWgMAOgI0Ou7izNfkZzWLSZ9PO7/Iro/7U65J2cAYoFk91znDcFhZzjKm/s7Zgndr/Vd0/vPm9e4/lCY7kmp2IwZ/wsMYScDC3xg//+beeJt/9UHaxemrXjC7Ld/BPADcbYnAXl4np5Inz4u+Iy8VlYvqq8N8A+MXbdRvz6zbaI2mNMNRKoGbgjFaanTRDTOd1nMdrC3G5uExMZ9k4z3gZx+XiMjGd5eI8XluIy8VlYjrLxnnGyzguF5eJ6SwX5/HaQlwuLhPTWTbOM17Gcbm4TExnuTiP1xbicnGZmM6ycZ7xMo7LxWViOsvFeby2EJeLy8R0lo3zjJdxXC4uE9NZLs7jdR7gej4D0NjsSJcrvote2lg2bts5LxJxO4/LxPR150/GcvTRB3LoixxizfG0ScDBnEnC40IJvPfDtI091l4b17OjwKyQGtwwj85oGs/QYsMcl3N+gGLIKjnDnLpE2nVsSwxj3Zperjm/89ROlZPqZmfLzNDmdb7Orwt2XH6vqD+Yz9nHopwupt73UnrgvP1nOwAEY3cV9m+bJ9I05MnH7yfZCT6xIfW0SyBIwFezuio8VwI0ILtHch9vyKeDBmZ9ITBW7xwWOxjNvqQT0fJyIdPK5vSo7Lry91s4Kgz71WEy+DP8Pz4byBEWUKjRBoCePhoM15RTTkdHzLTJjjGGc3NaXi4UsLI5PSpr3+H8Lr9zejKjP0E/j7AS9TE29n1K/VUgh3Le/ic2MbdzQX4vY/+wh+cp7a8DObNQHs+TgHvm5knG6eck8Ht/mW7snMid+jgfBVQw1xxi/twQoAJv5UzPMtKIaZkQx/l5nvNPyQ9euhq2gdlotaSdNCDvPubYAbjVCP2iYDQO0dKrN5vPonkZ53f5vYT+wF88xjF2ww48cG3zwAUd9PYbbNsV269RTYav7cjTPZyrHTV3T7oE5krAPXNzReMZsxLggc0ff0fu95s47BrAjACOoypq0BsAGcHskG75sbHXsjR6gcf558uPHrtxIqfq+RjLE4C1ZzWsCMT2LxwhVYBGAMdRVQVrXAUbhsxIJ81iAry8LEGf87v8gn7M059+W4bQtdNxE6edQP9wlt3TTeof9qOk/lj79vZ/9faPc+NoZx3IUdM8XFQCDuYuKikvpxJIkmyj4Xuvy0OcqzkcwRNnIG0DCQN2pDUJ8BDqAH7KHGgG4pjv/C+WH+bUjbGHXQ/zk45x+Ph+bwBwV5djeOwUvmmHTGCHhAE70rAJcSZ/dNwmf9IM2DHNxRfOD7mtufygKeP6hvTPWnKE9NMmABx07QTj/T3qn+kP26y33+wl7Krt1/aGDG5/SR589EFyQDtrMvfYJXARCUwN2VyEwcu4BCYSSJP3fig3cH0T5yomHEolcJs6Fix467QTIKjDNUGfki3NC9Cc//Lya+4AnHGjZwzHNvvSbiRSHwQPXbyYQkEcQR3yCPq0iKV5ARo9eNxWwvmDhhPlqqAyYEygvErywzy3IZ53v9+XHlagDjbRDr39Lt5+cbcAaNrRx+/Lsa9UDW3Po0tLwD1zlxaZM0wkkKSYmHuEjuDh+AwH0HN4FYaJYI2BkaXpsQvkPI8JAj8tg9j5Ly+/wQk8cuiQR6dyjKGwJ/0hvHY1OQa47sJzNyJwYyAQCUm9tjSBm5ZBTO8UjwszHpaxtPNXX37UB+pFDx5eHP2zjzOF9zvQG+pPA3rk7e/y7e9V7dcZ7CbtJ+2oAzk1Tf7xkhJwz9xLCs7ZzkuAp0fAS7RLLxxz6a2rA9yhs9ANhmMatoVP1EMXvHIEeubRw27xOsTg/K8uv6QjNRw/0Rpg0UoNmxVjyKypu/5zeBVoTb1wiAnczCOHcip/7jHGstg2JdEzYVHGaGPnL738RgBvWDjTa8IDh1XS/RrmYVqb8va3XPtD4Fxry6Gf4sBewcNVSMA9c1chRf8OlQAN0/5X5UEP5y4SwNmCCII0XmsHEmRFwBaGF3DeVUgD0ZHOcs5/NfJjB346lC7iE05ix9m6jzipHeDuBM44nQ9FwKZgDYiOQI5AjQDOhhgJ8nitAC48P5YzgOf8y5ffMMWCGcx543PtJ3Iw3JDH9LwBvB3z+bc3ZeztL5ufShVepv3BC1GHdtKBXDAmHl2JBNwzdyVi9C+ZlcDbP0+3ts5kFyCiYaCNZdih0JASrBHkWdrKkM60eRDs2r7f+a9efujom/0zeO6wBQrmzbUga25kXJ/1yvEZENARyBHcEeRZ2oCdefHMg2fX9vyc/9Xlx+FSPgqIf4Bp8gOc/zvsdTLobe3F2895rzZ1cJn2Ay+to7NDOfxkD1uFe3AJXLEEHMxdsUD96yYSSNM0ef9juYETJG5gNWZtFrixpBlXiyfc0ynLt87Kco1usdFnY8t3/smQN2VkcrHY5AYwVt/C0Cy2olCQlw7gXAVtHjgzkGb8s7HlO/9kyJoyMrlYPCs3gOQRlhsPBl0ZbbYQNzFUigPrrZw9N4uNPhtbvuv/xfT/KuUH+5ee9uXk538sR75KdVayfn1VEnAwd1WS9O+ZK4Fv/jqt33skt+DpyY91ne1U5jLPyXD+6U5pjpjmkl9GfgQE8ALVMQ+v0WxLk/PwsCKyXh9OH/U290ejjFlQF2VdKLlq/Jzfhv3FsFesDOByG+KIlSG8pSO+ABUJ5GWeX/w9zr+Y9sMh1Uf35ODTtxLdny9+Bp52CVylBBzMXaU0/bueKwGe8wpAdwsGjvPt5wa+yeIsQtVNThS2BRVzGWYynH/x8qMnb7MtNQ7XYuiv1sD1EGCPaQAvLJ68eODwLr5Pnz+HbwncLs6Nod8S8mMIe9QfyBhyGfawbxvqOOLwaKeXpeP7c/1dvP5etfyhv0P8H/gxXLFkPX2dEvAFENcpXf/uKQnQsP377yYP77blab0ddpIHWGOhBjwQ7MSYJpCzNK8ZmE9gp+kQM53TnH+p8mvVsYH0sfQx166DTux0PJRDxE+7OG+2M5RHgHNPerjGPK8jTNbnJP0O0j1sk8GD2ke1TWyjEjanBZ+uouXztTC74MLoNleP+QRxpC+KX+sEkMb64zf7GCrt8r46DTlD+lAXmoyw/Qfuf1iTx70xtgPB/TcHckw5cZ4bzjfVIVPX/9Vo/7RrmBt3QDvnQM5aqceLkEBjET/iv+ESiCWw905yhvl0nXf+TG7eel22sdeVel4UxIVhJfRwCTs48OVemVkPHYHcJgZueTg8g/PnMiNCKJP8eLzYMMEwLUDMgKuXCbj6iMPzSzAIlWI9TLK5hQ+cSwvgU2sA1CfHUseRZvT0JUkLnj8swABwVMCGzW5lZ0ek34MzDpoybofTLFAWi2j0ZAucmsGt9FMs60gBFnWVAGgK+gC8xti2Q483aOD80Q5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0:nr.style),tn),prefixCls:Tn,getPopupContainer:ut||zr,generateConfig:E,components:Es,direction:Zn,disabled:Ci,classNames:{popup:hr()(si,Ur,Yr,wt,Pn||Sn)},styles:{popup:Object.assign(Object.assign({},tt.popupStyle),{zIndex:_i})},allowClear:Ss,removeIcon:Li}))))})},F=L(),G=L(Xf,fy),Z=L(o0,l0),oe=L(lv,ym),Ae=L(bm,Yh),Ce=L(Em,u0);return{DatePicker:F,WeekPicker:G,MonthPicker:Z,YearPicker:oe,TimePicker:Ce,QuarterPicker:Ae}},dv=E=>{const{DatePicker:L,WeekPicker:F,MonthPicker:G,YearPicker:Z,TimePicker:oe,QuarterPicker:Ae}=my(E),Ce=h0(E),ke=L;return ke.WeekPicker=F,ke.MonthPicker=G,ke.YearPicker=Z,ke.RangePicker=Ce,ke.TimePicker=oe,ke.QuarterPicker=Ae,ke};const Gd=dv(Mt),m0=(0,Er.Z)(Gd,"popupAlign",void 0,"picker");Gd._InternalPanelDoNotUseOrYouWillBeFired=m0;const g0=(0,Er.Z)(Gd.RangePicker,"popupAlign",void 0,"picker");Gd._InternalRangePanelDoNotUseOrYouWillBeFired=g0,Gd.generatePicker=dv;var fv=Gd},91998:function(Re,bn,O){Re.exports=pe,Re.exports.simulator=O(72879);var y=O(82396);function pe(je,it){if(!je)throw new Error("Graph structure cannot be undefined");var un=it&&it.createSimulator||O(72879),Ye=un(it);if(Array.isArray(it))throw new Error("Physics settings is expected to be an object");var Ne=je.version>19?hn:qn;it&&typeof it.nodeMass=="function"&&(Ne=it.nodeMass);var Qt=new Map,gt={},Oe=0,st=Ye.settings.springTransform||Ge;oi(),Er();var Fe=!1,St={step:function(){if(Oe===0)return zt(!0),!0;var Ke=Ye.step();St.lastMove=Ke,St.fire("step");var Ct=Ke/Oe,Wn=Ct<=.01;return zt(Wn),Wn},getNodePosition:function(Ke){return dn(Ke).pos},setNodePosition:function(Ke){var Ct=dn(Ke);Ct.setPosition.apply(Ct,Array.prototype.slice.call(arguments,1))},getLinkPosition:function(Ke){var Ct=gt[Ke];if(Ct)return{from:Ct.from.pos,to:Ct.to.pos}},getGraphRect:function(){return Ye.getBBox()},forEachBody:Dt,pinNode:function(Ke,Ct){var Wn=dn(Ke.id);Wn.isPinned=!!Ct},isNodePinned:function(Ke){return dn(Ke.id).isPinned},dispose:function(){je.off("changed",ln),St.fire("disposed")},getBody:Mt,getSpring:It,getForceVectorLength:Kn,simulator:Ye,graph:je,lastMove:0};return y(St),St;function zt(Ke){Fe!==Ke&&(Fe=Ke,X(Ke))}function Dt(Ke){Qt.forEach(Ke)}function Kn(){var Ke=0,Ct=0;return Dt(function(Wn){Ke+=Math.abs(Wn.force.x),Ct+=Math.abs(Wn.force.y)}),Math.sqrt(Ke*Ke+Ct*Ct)}function It(Ke,Ct){var Wn;if(Ct===void 0)typeof Ke!="object"?Wn=Ke:Wn=Ke.id;else{var mr=je.hasLink(Ke,Ct);if(!mr)return;Wn=mr.id}return gt[Wn]}function Mt(Ke){return Qt.get(Ke)}function Er(){je.on("changed",ln)}function X(Ke){St.fire("stable",Ke)}function ln(Ke){for(var Ct=0;Ct<Ke.length;++Ct){var Wn=Ke[Ct];Wn.changeType==="add"?(Wn.node&&nn(Wn.node.id),Wn.link&&At(Wn.link)):Wn.changeType==="remove"&&(Wn.node&&jn(Wn.node),Wn.link&&Xt(Wn.link))}Oe=je.getNodesCount()}function oi(){Oe=0,je.forEachNode(function(Ke){nn(Ke.id),Oe+=1}),je.forEachLink(At)}function nn(Ke){var Ct=Qt.get(Ke);if(!Ct){var Wn=je.getNode(Ke);if(!Wn)throw new Error("initBody() was called with unknown node id");var mr=Wn.position;if(!mr){var Hr=sr(Wn);mr=Ye.getBestNewBodyPosition(Hr)}Ct=Ye.addBodyAt(mr),Ct.id=Ke,Qt.set(Ke,Ct),Hn(Ke),fn(Wn)&&(Ct.isPinned=!0)}}function jn(Ke){var Ct=Ke.id,Wn=Qt.get(Ct);Wn&&(Qt.delete(Ct),Ye.removeBody(Wn))}function At(Ke){Hn(Ke.fromId),Hn(Ke.toId);var Ct=Qt.get(Ke.fromId),Wn=Qt.get(Ke.toId),mr=Ye.addSpring(Ct,Wn,Ke.length);st(Ke,mr),gt[Ke.id]=mr}function Xt(Ke){var Ct=gt[Ke.id];if(Ct){var Wn=je.getNode(Ke.fromId),mr=je.getNode(Ke.toId);Wn&&Hn(Wn.id),mr&&Hn(mr.id),delete gt[Ke.id],Ye.removeSpring(Ct)}}function sr(Ke){var Ct=[];if(!Ke.links)return Ct;for(var Wn=Math.min(Ke.links.length,2),mr=0;mr<Wn;++mr){var Hr=Ke.links[mr],li=Hr.fromId!==Ke.id?Qt.get(Hr.fromId):Qt.get(Hr.toId);li&&li.pos&&Ct.push(li)}return Ct}function Hn(Ke){var Ct=Qt.get(Ke);if(Ct.mass=Ne(Ke),Number.isNaN(Ct.mass))throw new Error("Node mass should be a number")}function fn(Ke){return Ke&&(Ke.isPinned||Ke.data&&Ke.data.isPinned)}function dn(Ke){var Ct=Qt.get(Ke);return Ct||(nn(Ke),Ct=Qt.get(Ke)),Ct}function qn(Ke){var Ct=je.getLinks(Ke);return Ct?1+Ct.length/3:1}function hn(Ke){var Ct=je.getLinks(Ke);return Ct?1+Ct.size/3:1}}function Ge(){}},98786:function(Re,bn,O){const y=O(59321);Re.exports=function(Ge){return je;function je(it,un){let Ye=un&&un.indent||0,Ne=un&&un.join!==void 0?un.join:`
`,Qt=Array(Ye+1).join(" "),gt=[];for(let Oe=0;Oe<Ge;++Oe){let st=y(Oe),Fe=Oe===0?"":Qt;gt.push(Fe+it.replace(/{var}/g,st))}return gt.join(Ne)}}},41085:function(Re,bn,O){Re.exports=pe,Re.exports.generateFunctionBody=Ge;const y=O(98786);function pe(je){let it=Ge(je);return new Function("bodies","settings","random",it)}function Ge(je){let it=y(je);return`
  var boundingBox = {
    ${it("min_{var}: 0, max_{var}: 0,",{indent:4})}
  };

  return {
    box: boundingBox,

    update: updateBoundingBox,

    reset: resetBoundingBox,

    getBestNewPosition: function (neighbors) {
      var ${it("base_{var} = 0",{join:", "})};

      if (neighbors.length) {
        for (var i = 0; i < neighbors.length; ++i) {
          let neighborPos = neighbors[i].pos;
          ${it("base_{var} += neighborPos.{var};",{indent:10})}
        }

        ${it("base_{var} /= neighbors.length;",{indent:8})}
      } else {
        ${it("base_{var} = (boundingBox.min_{var} + boundingBox.max_{var}) / 2;",{indent:8})}
      }

      var springLength = settings.springLength;
      return {
        ${it("{var}: base_{var} + (random.nextDouble() - 0.5) * springLength,",{indent:8})}
      };
    }
  };

  function updateBoundingBox() {
    var i = bodies.length;
    if (i === 0) return; // No bodies - no borders.

    ${it("var max_{var} = -Infinity;",{indent:4})}
    ${it("var min_{var} = Infinity;",{indent:4})}

    while(i--) {
      // this is O(n), it could be done faster with quadtree, if we check the root node bounds
      var bodyPos = bodies[i].pos;
      ${it("if (bodyPos.{var} < min_{var}) min_{var} = bodyPos.{var};",{indent:6})}
      ${it("if (bodyPos.{var} > max_{var}) max_{var} = bodyPos.{var};",{indent:6})}
    }

    ${it("boundingBox.min_{var} = min_{var};",{indent:4})}
    ${it("boundingBox.max_{var} = max_{var};",{indent:4})}
  }

  function resetBoundingBox() {
    ${it("boundingBox.min_{var} = boundingBox.max_{var} = 0;",{indent:4})}
  }
`}},53623:function(Re,bn,O){const y=O(98786);Re.exports=pe,Re.exports.generateCreateBodyFunctionBody=Ge,Re.exports.getVectorCode=it,Re.exports.getBodyCode=je;function pe(un,Ye){let Ne=Ge(un,Ye),{Body:Qt}=new Function(Ne)();return Qt}function Ge(un,Ye){return`
${it(un,Ye)}
${je(un,Ye)}
return {Body: Body, Vector: Vector};
`}function je(un){let Ye=y(un),Ne=Ye("{var}",{join:", "});return`
function Body(${Ne}) {
  this.isPinned = false;
  this.pos = new Vector(${Ne});
  this.force = new Vector();
  this.velocity = new Vector();
  this.mass = 1;

  this.springCount = 0;
  this.springLength = 0;
}

Body.prototype.reset = function() {
  this.force.reset();
  this.springCount = 0;
  this.springLength = 0;
}

Body.prototype.setPosition = function (${Ne}) {
  ${Ye("this.pos.{var} = {var} || 0;",{indent:2})}
};`}function it(un,Ye){let Ne=y(un),Qt="";return Ye&&(Qt=`${Ne(`
   var v{var};
Object.defineProperty(this, '{var}', {
  set: function(v) { 
    if (!Number.isFinite(v)) throw new Error('Cannot set non-numbers to {var}');
    v{var} = v; 
  },
  get: function() { return v{var}; }
});`)}`),`function Vector(${Ne("{var}",{join:", "})}) {
  ${Qt}
    if (typeof arguments[0] === 'object') {
      // could be another vector
      let v = arguments[0];
      ${Ne('if (!Number.isFinite(v.{var})) throw new Error("Expected value is not a finite number at Vector constructor ({var})");',{indent:4})}
      ${Ne("this.{var} = v.{var};",{indent:4})}
    } else {
      ${Ne('this.{var} = typeof {var} === "number" ? {var} : 0;',{indent:4})}
    }
  }
  
  Vector.prototype.reset = function () {
    ${Ne("this.{var} = ",{join:""})}0;
  };`}},48812:function(Re,bn,O){const y=O(98786);Re.exports=pe,Re.exports.generateCreateDragForceFunctionBody=Ge;function pe(je){let it=Ge(je);return new Function("options",it)}function Ge(je){return`
  if (!Number.isFinite(options.dragCoefficient)) throw new Error('dragCoefficient is not a finite number');

  return {
    update: function(body) {
      ${y(je)("body.force.{var} -= options.dragCoefficient * body.velocity.{var};",{indent:6})}
    }
  };
`}},7584:function(Re,bn,O){const y=O(98786);Re.exports=pe,Re.exports.generateCreateSpringForceFunctionBody=Ge;function pe(je){let it=Ge(je);return new Function("options","random",it)}function Ge(je){let it=y(je);return`
  if (!Number.isFinite(options.springCoefficient)) throw new Error('Spring coefficient is not a number');
  if (!Number.isFinite(options.springLength)) throw new Error('Spring length is not a number');

  return {
    /**
     * Updates forces acting on a spring
     */
    update: function (spring) {
      var body1 = spring.from;
      var body2 = spring.to;
      var length = spring.length < 0 ? options.springLength : spring.length;
      ${it("var d{var} = body2.pos.{var} - body1.pos.{var};",{indent:6})}
      var r = Math.sqrt(${it("d{var} * d{var}",{join:" + "})});

      if (r === 0) {
        ${it("d{var} = (random.nextDouble() - 0.5) / 50;",{indent:8})}
        r = Math.sqrt(${it("d{var} * d{var}",{join:" + "})});
      }

      var d = r - length;
      var coefficient = ((spring.coefficient > 0) ? spring.coefficient : options.springCoefficient) * d / r;

      ${it("body1.force.{var} += coefficient * d{var}",{indent:6})};
      body1.springCount += 1;
      body1.springLength += r;

      ${it("body2.force.{var} -= coefficient * d{var}",{indent:6})};
      body2.springCount += 1;
      body2.springLength += r;
    }
  };
`}},26302:function(Re,bn,O){const y=O(98786);Re.exports=pe,Re.exports.generateIntegratorFunctionBody=Ge;function pe(je){let it=Ge(je);return new Function("bodies","timeStep","adaptiveTimeStepWeight",it)}function Ge(je){let it=y(je);return`
  var length = bodies.length;
  if (length === 0) return 0;

  ${it("var d{var} = 0, t{var} = 0;",{indent:2})}

  for (var i = 0; i < length; ++i) {
    var body = bodies[i];
    if (body.isPinned) continue;

    if (adaptiveTimeStepWeight && body.springCount) {
      timeStep = (adaptiveTimeStepWeight * body.springLength/body.springCount);
    }

    var coeff = timeStep / body.mass;

    ${it("body.velocity.{var} += coeff * body.force.{var};",{indent:4})}
    ${it("var v{var} = body.velocity.{var};",{indent:4})}
    var v = Math.sqrt(${it("v{var} * v{var}",{join:" + "})});

    if (v > 1) {
      // We normalize it so that we move within timeStep range. 
      // for the case when v <= 1 - we let velocity to fade out.
      ${it("body.velocity.{var} = v{var} / v;",{indent:6})}
    }

    ${it("d{var} = timeStep * body.velocity.{var};",{indent:4})}

    ${it("body.pos.{var} += d{var};",{indent:4})}

    ${it("t{var} += Math.abs(d{var});",{indent:4})}
  }

  return (${it("t{var} * t{var}",{join:" + "})})/length;
`}},24454:function(Re,bn,O){const y=O(98786),pe=O(59321);Re.exports=Ge,Re.exports.generateQuadTreeFunctionBody=je,Re.exports.getInsertStackCode=Qt,Re.exports.getQuadNodeCode=Ne,Re.exports.isSamePosition=it,Re.exports.getChildBodyCode=Ye,Re.exports.setChildBodyCode=un;function Ge(gt){let Oe=je(gt);return new Function(Oe)()}function je(gt){let Oe=y(gt),st=Math.pow(2,gt);return`
${Qt()}
${Ne(gt)}
${it(gt)}
${Ye(gt)}
${un(gt)}

function createQuadTree(options, random) {
  options = options || {};
  options.gravity = typeof options.gravity === 'number' ? options.gravity : -1;
  options.theta = typeof options.theta === 'number' ? options.theta : 0.8;

  var gravity = options.gravity;
  var updateQueue = [];
  var insertStack = new InsertStack();
  var theta = options.theta;

  var nodesCache = [];
  var currentInCache = 0;
  var root = newNode();

  return {
    insertBodies: insertBodies,

    /**
     * Gets root node if it is present
     */
    getRoot: function() {
      return root;
    },

    updateBodyForce: update,

    options: function(newOptions) {
      if (newOptions) {
        if (typeof newOptions.gravity === 'number') {
          gravity = newOptions.gravity;
        }
        if (typeof newOptions.theta === 'number') {
          theta = newOptions.theta;
        }

        return this;
      }

      return {
        gravity: gravity,
        theta: theta
      };
    }
  };

  function newNode() {
    // To avoid pressure on GC we reuse nodes.
    var node = nodesCache[currentInCache];
    if (node) {
${Dt("      node.")}
      node.body = null;
      node.mass = ${Oe("node.mass_{var} = ",{join:""})}0;
      ${Oe("node.min_{var} = node.max_{var} = ",{join:""})}0;
    } else {
      node = new QuadNode();
      nodesCache[currentInCache] = node;
    }

    ++currentInCache;
    return node;
  }

  function update(sourceBody) {
    var queue = updateQueue;
    var v;
    ${Oe("var d{var};",{indent:4})}
    var r; 
    ${Oe("var f{var} = 0;",{indent:4})}
    var queueLength = 1;
    var shiftIdx = 0;
    var pushIdx = 1;

    queue[0] = root;

    while (queueLength) {
      var node = queue[shiftIdx];
      var body = node.body;

      queueLength -= 1;
      shiftIdx += 1;
      var differentBody = (body !== sourceBody);
      if (body && differentBody) {
        // If the current node is a leaf node (and it is not source body),
        // calculate the force exerted by the current node on body, and add this
        // amount to body's net force.
        ${Oe("d{var} = body.pos.{var} - sourceBody.pos.{var};",{indent:8})}
        r = Math.sqrt(${Oe("d{var} * d{var}",{join:" + "})});

        if (r === 0) {
          // Poor man's protection against zero distance.
          ${Oe("d{var} = (random.nextDouble() - 0.5) / 50;",{indent:10})}
          r = Math.sqrt(${Oe("d{var} * d{var}",{join:" + "})});
        }

        // This is standard gravitation force calculation but we divide
        // by r^3 to save two operations when normalizing force vector.
        v = gravity * body.mass * sourceBody.mass / (r * r * r);
        ${Oe("f{var} += v * d{var};",{indent:8})}
      } else if (differentBody) {
        // Otherwise, calculate the ratio s / r,  where s is the width of the region
        // represented by the internal node, and r is the distance between the body
        // and the node's center-of-mass
        ${Oe("d{var} = node.mass_{var} / node.mass - sourceBody.pos.{var};",{indent:8})}
        r = Math.sqrt(${Oe("d{var} * d{var}",{join:" + "})});

        if (r === 0) {
          // Sorry about code duplication. I don't want to create many functions
          // right away. Just want to see performance first.
          ${Oe("d{var} = (random.nextDouble() - 0.5) / 50;",{indent:10})}
          r = Math.sqrt(${Oe("d{var} * d{var}",{join:" + "})});
        }
        // If s / r < \u03B8, treat this internal node as a single body, and calculate the
        // force it exerts on sourceBody, and add this amount to sourceBody's net force.
        if ((node.max_${pe(0)} - node.min_${pe(0)}) / r < theta) {
          // in the if statement above we consider node's width only
          // because the region was made into square during tree creation.
          // Thus there is no difference between using width or height.
          v = gravity * node.mass * sourceBody.mass / (r * r * r);
          ${Oe("f{var} += v * d{var};",{indent:10})}
        } else {
          // Otherwise, run the procedure recursively on each of the current node's children.

          // I intentionally unfolded this loop, to save several CPU cycles.
${zt()}
        }
      }
    }

    ${Oe("sourceBody.force.{var} += f{var};",{indent:4})}
  }

  function insertBodies(bodies) {
    ${Oe("var {var}min = Number.MAX_VALUE;",{indent:4})}
    ${Oe("var {var}max = Number.MIN_VALUE;",{indent:4})}
    var i = bodies.length;

    // To reduce quad tree depth we are looking for exact bounding box of all particles.
    while (i--) {
      var pos = bodies[i].pos;
      ${Oe("if (pos.{var} < {var}min) {var}min = pos.{var};",{indent:6})}
      ${Oe("if (pos.{var} > {var}max) {var}max = pos.{var};",{indent:6})}
    }

    // Makes the bounds square.
    var maxSideLength = -Infinity;
    ${Oe("if ({var}max - {var}min > maxSideLength) maxSideLength = {var}max - {var}min ;",{indent:4})}

    currentInCache = 0;
    root = newNode();
    ${Oe("root.min_{var} = {var}min;",{indent:4})}
    ${Oe("root.max_{var} = {var}min + maxSideLength;",{indent:4})}

    i = bodies.length - 1;
    if (i >= 0) {
      root.body = bodies[i];
    }
    while (i--) {
      insert(bodies[i], root);
    }
  }

  function insert(newBody) {
    insertStack.reset();
    insertStack.push(root, newBody);

    while (!insertStack.isEmpty()) {
      var stackItem = insertStack.pop();
      var node = stackItem.node;
      var body = stackItem.body;

      if (!node.body) {
        // This is internal node. Update the total mass of the node and center-of-mass.
        ${Oe("var {var} = body.pos.{var};",{indent:8})}
        node.mass += body.mass;
        ${Oe("node.mass_{var} += body.mass * {var};",{indent:8})}

        // Recursively insert the body in the appropriate quadrant.
        // But first find the appropriate quadrant.
        var quadIdx = 0; // Assume we are in the 0's quad.
        ${Oe("var min_{var} = node.min_{var};",{indent:8})}
        ${Oe("var max_{var} = (min_{var} + node.max_{var}) / 2;",{indent:8})}

${St(8)}

        var child = getChild(node, quadIdx);

        if (!child) {
          // The node is internal but this quadrant is not taken. Add
          // subnode to it.
          child = newNode();
          ${Oe("child.min_{var} = min_{var};",{indent:10})}
          ${Oe("child.max_{var} = max_{var};",{indent:10})}
          child.body = body;

          setChild(node, quadIdx, child);
        } else {
          // continue searching in this quadrant.
          insertStack.push(child, body);
        }
      } else {
        // We are trying to add to the leaf node.
        // We have to convert current leaf into internal node
        // and continue adding two nodes.
        var oldBody = node.body;
        node.body = null; // internal nodes do not cary bodies

        if (isSamePosition(oldBody.pos, body.pos)) {
          // Prevent infinite subdivision by bumping one node
          // anywhere in this quadrant
          var retriesCount = 3;
          do {
            var offset = random.nextDouble();
            ${Oe("var d{var} = (node.max_{var} - node.min_{var}) * offset;",{indent:12})}

            ${Oe("oldBody.pos.{var} = node.min_{var} + d{var};",{indent:12})}
            retriesCount -= 1;
            // Make sure we don't bump it out of the box. If we do, next iteration should fix it
          } while (retriesCount > 0 && isSamePosition(oldBody.pos, body.pos));

          if (retriesCount === 0 && isSamePosition(oldBody.pos, body.pos)) {
            // This is very bad, we ran out of precision.
            // if we do not return from the method we'll get into
            // infinite loop here. So we sacrifice correctness of layout, and keep the app running
            // Next layout iteration should get larger bounding box in the first step and fix this
            return;
          }
        }
        // Next iteration should subdivide node further.
        insertStack.push(node, oldBody);
        insertStack.push(node, body);
      }
    }
  }
}
return createQuadTree;

`;function St(Kn){let It=[],Mt=Array(Kn+1).join(" ");for(let Er=0;Er<gt;++Er)It.push(Mt+`if (${pe(Er)} > max_${pe(Er)}) {`),It.push(Mt+`  quadIdx = quadIdx + ${Math.pow(2,Er)};`),It.push(Mt+`  min_${pe(Er)} = max_${pe(Er)};`),It.push(Mt+`  max_${pe(Er)} = node.max_${pe(Er)};`),It.push(Mt+"}");return It.join(`
`)}function zt(){let Kn=Array(11).join(" "),It=[];for(let Mt=0;Mt<st;++Mt)It.push(Kn+`if (node.quad${Mt}) {`),It.push(Kn+`  queue[pushIdx] = node.quad${Mt};`),It.push(Kn+"  queueLength += 1;"),It.push(Kn+"  pushIdx += 1;"),It.push(Kn+"}");return It.join(`
`)}function Dt(Kn){let It=[];for(let Mt=0;Mt<st;++Mt)It.push(`${Kn}quad${Mt} = null;`);return It.join(`
`)}}function it(gt){let Oe=y(gt);return`
  function isSamePosition(point1, point2) {
    ${Oe("var d{var} = Math.abs(point1.{var} - point2.{var});",{indent:2})}
  
    return ${Oe("d{var} < 1e-8",{join:" && "})};
  }  
`}function un(gt){var Oe=Math.pow(2,gt);return`
function setChild(node, idx, child) {
  ${st()}
}`;function st(){let Fe=[];for(let St=0;St<Oe;++St){let zt=St===0?"  ":"  else ";Fe.push(`${zt}if (idx === ${St}) node.quad${St} = child;`)}return Fe.join(`
`)}}function Ye(gt){return`function getChild(node, idx) {
${Oe()}
  return null;
}`;function Oe(){let st=[],Fe=Math.pow(2,gt);for(let St=0;St<Fe;++St)st.push(`  if (idx === ${St}) return node.quad${St};`);return st.join(`
`)}}function Ne(gt){let Oe=y(gt),st=Math.pow(2,gt);var Fe=`
function QuadNode() {
  // body stored inside this node. In quad tree only leaf nodes (by construction)
  // contain bodies:
  this.body = null;

  // Child nodes are stored in quads. Each quad is presented by number:
  // 0 | 1
  // -----
  // 2 | 3
${St("  this.")}

  // Total mass of current node
  this.mass = 0;

  // Center of mass coordinates
  ${Oe("this.mass_{var} = 0;",{indent:2})}

  // bounding box coordinates
  ${Oe("this.min_{var} = 0;",{indent:2})}
  ${Oe("this.max_{var} = 0;",{indent:2})}
}
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/**
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function InsertStack () {
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    this.popIdx = 0;
}

InsertStack.prototype = {
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    },
    push: function (node, body) {
        var item = this.stack[this.popIdx];
        if (!item) {
            // we are trying to avoid memory pressure: create new element
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            this.stack[this.popIdx] = new InsertStackElement(node, body);
        } else {
            item.node = node;
            item.body = body;
        }
        ++this.popIdx;
    },
    pop: function () {
        if (this.popIdx > 0) {
            return this.stack[--this.popIdx];
        }
    },
    reset: function () {
        this.popIdx = 0;
    }
};

function InsertStackElement(node, body) {
    this.node = node; // QuadTree node
    this.body = body; // physical body which needs to be inserted to node
}
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The error may be correlated with this previous error:
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A=g.impact,b=g.viewport,M=g.destination,z=g.draggables,H=g.maxScrollChange,U=Kg(b,Na(b.scroll.current,H)),k=M.frame?Uh(M,Na(M.frame.scroll.current,H)):M,te=A.displaced,le=Ps({afterDragging:lm(te.all,z),destination:M,displacedBy:A.displacedBy,viewport:U.frame,last:te,forceShouldAnimate:!1}),ae=Ps({afterDragging:lm(te.all,z),destination:k,displacedBy:A.displacedBy,viewport:b.frame,last:te,forceShouldAnimate:!1}),ne={},ie={},me=[te,le,ae];te.all.forEach(function(_t){var on=um(_t,me);if(on){ie[_t]=on;return}ne[_t]=!0});var Xe=(0,Ge.Z)({},A,{displaced:{all:te.all,invisible:ne,visible:ie}});return Xe},cm=function(g,A){return Na(g.scroll.diff.displacement,A)},Vd=function(g){var A=g.pageBorderBoxCenter,b=g.draggable,M=g.viewport,z=cm(M,A),H=Po(z,b.page.borderBox.center);return Na(b.client.borderBox.center,H)},dm=function(g){var A=g.draggable,b=g.destination,M=g.newPageBorderBoxCenter,z=g.viewport,H=g.withDroppableDisplacement,U=g.onlyOnMainAxis,k=U===void 0?!1:U,te=Po(M,A.page.borderBox.center),le=gu(A.page.borderBox,te),ae={target:le,destination:b,withDroppableDisplacement:H,viewport:z};return k?Gg(ae):_c(ae)},ur=function(g){var A=g.isMovingForward,b=g.draggable,M=g.destination,z=g.draggables,H=g.previousImpact,U=g.viewport,k=g.previousPageBorderBoxCenter,te=g.previousClientSelection,le=g.afterCritical;if(!M.isEnabled)return null;var ae=Kc(M.descriptor.id,z),ne=Hu(b,M),ie=kg({isMovingForward:A,draggable:b,destination:M,insideDestination:ae,previousImpact:H})||$A({isMovingForward:A,isInHomeList:ne,draggable:b,draggables:z,destination:M,insideDestination:ae,previousImpact:H,viewport:U,afterCritical:le});if(!ie)return null;var me=Xh({impact:ie,draggable:b,droppable:M,draggables:z,afterCritical:le}),Xe=dm({draggable:b,destination:M,newPageBorderBoxCenter:me,viewport:U.frame,withDroppableDisplacement:!1,onlyOnMainAxis:!0});if(Xe){var _t=Vd({pageBorderBoxCenter:me,draggable:b,viewport:U});return{clientSelection:_t,impact:ie,scrollJumpRequest:null}}var on=Po(me,k),Gt=qg({impact:ie,viewport:U,destination:M,draggables:z,maxScrollChange:on});return{clientSelection:te,impact:Gt,scrollJumpRequest:on}},Mo=function(A){var b=A.subject.active;return b||Ot(!1),b},_g=function(g){var A=g.isMovingForward,b=g.pageBorderBoxCenter,M=g.source,z=g.droppables,H=g.viewport,U=M.subject.active;if(!U)return null;var k=M.axis,te=Zr(U[k.start],U[k.end]),le=Uf(z).filter(function(ne){return ne!==M}).filter(function(ne){return ne.isEnabled}).filter(function(ne){return!!ne.subject.active}).filter(function(ne){return qc(H.frame)(Mo(ne))}).filter(function(ne){var ie=Mo(ne);return A?U[k.crossAxisEnd]<ie[k.crossAxisEnd]:ie[k.crossAxisStart]<U[k.crossAxisStart]}).filter(function(ne){var ie=Mo(ne),me=Zr(ie[k.start],ie[k.end]);return te(ie[k.start])||te(ie[k.end])||me(U[k.start])||me(U[k.end])}).sort(function(ne,ie){var me=Mo(ne)[k.crossAxisStart],Xe=Mo(ie)[k.crossAxisStart];return A?me-Xe:Xe-me}).filter(function(ne,ie,me){return Mo(ne)[k.crossAxisStart]===Mo(me[0])[k.crossAxisStart]});if(!le.length)return null;if(le.length===1)return le[0];var ae=le.filter(function(ne){var ie=Zr(Mo(ne)[k.start],Mo(ne)[k.end]);return ie(b[k.line])});return ae.length===1?ae[0]:ae.length>1?ae.sort(function(ne,ie){return Mo(ne)[k.start]-Mo(ie)[k.start]})[0]:le.sort(function(ne,ie){var me=no(b,Yc(Mo(ne))),Xe=no(b,Yc(Mo(ie)));return me!==Xe?me-Xe:Mo(ne)[k.start]-Mo(ie)[k.start]})[0]},fm=function(A,b){var M=A.page.borderBox.center;return Ac(A.descriptor.id,b)?Po(M,b.displacedBy.point):M},hm=function(A,b){var M=A.page.borderBox;return Ac(A.descriptor.id,b)?gu(M,Zc(b.displacedBy.point)):M},$g=function(g){var A=g.pageBorderBoxCenter,b=g.viewport,M=g.destination,z=g.insideDestination,H=g.afterCritical,U=z.filter(function(k){return _c({target:hm(k,H),destination:M,viewport:b.frame,withDroppableDisplacement:!0})}).sort(function(k,te){var le=mu(A,om(M,fm(k,H))),ae=mu(A,om(M,fm(te,H)));return le<ae?-1:ae<le?1:k.descriptor.index-te.descriptor.index});return U[0]||null},jd=pi(function(A,b){var M=b[A.line];return{value:M,point:Ki(A.line,M)}}),pm=function(A,b,M){var z=A.axis;if(A.descriptor.mode==="virtual")return Ki(z.line,b[z.line]);var H=A.subject.page.contentBox[z.size],U=Kc(A.descriptor.id,M),k=U.reduce(function(ae,ne){return ae+ne.client.marginBox[z.size]},0),te=k+b[z.line],le=te-H;return le<=0?null:Ki(z.line,le)},qi=function(A,b){return(0,Ge.Z)({},A,{scroll:(0,Ge.Z)({},A.scroll,{max:b})})},mm=function(A,b,M){var z=A.frame;Hu(b,A)&&Ot(!1),A.subject.withPlaceholder&&Ot(!1);var H=jd(A.axis,b.displaceBy).point,U=pm(A,H,M),k={placeholderSize:H,increasedBy:U,oldFrameMaxScroll:A.frame?A.frame.scroll.max:null};if(!z){var te=Jc({page:A.subject.page,withPlaceholder:k,axis:A.axis,frame:A.frame});return(0,Ge.Z)({},A,{subject:te})}var le=U?Na(z.scroll.max,U):z.scroll.max,ae=qi(z,le),ne=Jc({page:A.subject.page,withPlaceholder:k,axis:A.axis,frame:ae});return(0,Ge.Z)({},A,{subject:ne,frame:ae})},Uu=function(A){var b=A.subject.withPlaceholder;b||Ot(!1);var M=A.frame;if(!M){var z=Jc({page:A.subject.page,axis:A.axis,frame:null,withPlaceholder:null});return(0,Ge.Z)({},A,{subject:z})}var H=b.oldFrameMaxScroll;H||Ot(!1);var U=qi(M,H),k=Jc({page:A.subject.page,axis:A.axis,frame:U,withPlaceholder:null});return(0,Ge.Z)({},A,{subject:k,frame:U})},gm=function(g){var A=g.previousPageBorderBoxCenter,b=g.moveRelativeTo,M=g.insideDestination,z=g.draggable,H=g.draggables,U=g.destination,k=g.viewport,te=g.afterCritical;if(!b){if(M.length)return null;var le={displaced:Ud,displacedBy:im,at:{type:"REORDER",destination:{droppableId:U.descriptor.id,index:0}}},ae=Xh({impact:le,draggable:z,droppable:U,draggables:H,afterCritical:te}),ne=Hu(z,U)?U:mm(U,z,H),ie=dm({draggable:z,destination:ne,newPageBorderBoxCenter:ae,viewport:k.frame,withDroppableDisplacement:!1,onlyOnMainAxis:!0});return ie?le:null}var me=A[U.axis.line]<=b.page.borderBox.center[U.axis.line],Xe=function(){var on=b.descriptor.index;return b.descriptor.id===z.descriptor.id||me?on:on+1}(),_t=jd(U.axis,z.displaceBy);return Vh({draggable:z,insideDestination:M,destination:U,viewport:k,displacedBy:_t,last:Ud,index:Xe})},ev=function(g){var A=g.isMovingForward,b=g.previousPageBorderBoxCenter,M=g.draggable,z=g.isOver,H=g.draggables,U=g.droppables,k=g.viewport,te=g.afterCritical,le=_g({isMovingForward:A,pageBorderBoxCenter:b,source:z,droppables:U,viewport:k});if(!le)return null;var ae=Kc(le.descriptor.id,H),ne=$g({pageBorderBoxCenter:b,viewport:k,destination:le,insideDestination:ae,afterCritical:te}),ie=gm({previousPageBorderBoxCenter:b,destination:le,draggable:M,draggables:H,moveRelativeTo:ne,insideDestination:ae,viewport:k,afterCritical:te});if(!ie)return null;var me=Xh({impact:ie,draggable:M,droppable:le,draggables:H,afterCritical:te}),Xe=Vd({pageBorderBoxCenter:me,draggable:M,viewport:k});return{clientSelection:Xe,impact:ie,scrollJumpRequest:null}},co=function(g){var A=g.at;return A?A.type==="REORDER"?A.destination.droppableId:A.combine.droppableId:null},r0=function(A,b){var M=co(A);return M?b[M]:null},tv=function(g){var A=g.state,b=g.type,M=r0(A.impact,A.dimensions.droppables),z=!!M,H=A.dimensions.droppables[A.critical.droppable.id],U=M||H,k=U.axis.direction,te=k==="vertical"&&(b==="MOVE_UP"||b==="MOVE_DOWN")||k==="horizontal"&&(b==="MOVE_LEFT"||b==="MOVE_RIGHT");if(te&&!z)return null;var le=b==="MOVE_DOWN"||b==="MOVE_RIGHT",ae=A.dimensions.draggables[A.critical.draggable.id],ne=A.current.page.borderBoxCenter,ie=A.dimensions,me=ie.draggables,Xe=ie.droppables;return te?ur({isMovingForward:le,previousPageBorderBoxCenter:ne,draggable:ae,destination:U,draggables:me,viewport:A.viewport,previousClientSelection:A.current.client.selection,previousImpact:A.impact,afterCritical:A.afterCritical}):ev({isMovingForward:le,previousPageBorderBoxCenter:ne,draggable:ae,isOver:U,draggables:me,droppables:Xe,viewport:A.viewport,afterCritical:A.afterCritical})};function ed(g){return g.phase==="DRAGGING"||g.phase==="COLLECTING"}function Gh(g){var A=Zr(g.top,g.bottom),b=Zr(g.left,g.right);return function(z){return A(z.y)&&b(z.x)}}function ko(g,A){return g.left<A.right&&g.right>A.left&&g.top<A.bottom&&g.bottom>A.top}function fs(g){var A=g.pageBorderBox,b=g.draggable,M=g.candidates,z=b.page.borderBox.center,H=M.map(function(U){var k=U.axis,te=Ki(U.axis.line,A.center[k.line],U.page.borderBox.center[k.crossAxisLine]);return{id:U.descriptor.id,distance:mu(z,te)}}).sort(function(U,k){return k.distance-U.distance});return H[0]?H[0].id:null}function ly(g){var A=g.pageBorderBox,b=g.draggable,M=g.droppables,z=Uf(M).filter(function(H){if(!H.isEnabled)return!1;var U=H.subject.active;if(!U||!ko(A,U))return!1;if(Gh(U)(A.center))return!0;var k=H.axis,te=U.center[k.crossAxisLine],le=A[k.crossAxisStart],ae=A[k.crossAxisEnd],ne=Zr(U[k.crossAxisStart],U[k.crossAxisEnd]),ie=ne(le),me=ne(ae);return!ie&&!me?!0:ie?le<te:ae>te});return z.length?z.length===1?z[0].descriptor.id:fs({pageBorderBox:A,draggable:b,candidates:z}):null}var vm=function(A,b){return Sa(gu(A,b))},Wh=function(g,A){var b=g.frame;return b?vm(A,b.scroll.diff.value):A};function nv(g){var A=g.displaced,b=g.id;return!!(A.visible[b]||A.invisible[b])}function rv(g){var A=g.draggable,b=g.closest,M=g.inHomeList;return b?M&&b.descriptor.index>A.descriptor.index?b.descriptor.index-1:b.descriptor.index:null}var uy=function(g){var A=g.pageBorderBoxWithDroppableScroll,b=g.draggable,M=g.destination,z=g.insideDestination,H=g.last,U=g.viewport,k=g.afterCritical,te=M.axis,le=jd(M.axis,b.displaceBy),ae=le.value,ne=A[te.start],ie=A[te.end],me=kh(b,z),Xe=vc(me,function(on){var Gt=on.descriptor.id,gn=on.page.borderBox.center[te.line],On=Ac(Gt,k),wr=nv({displaced:H,id:Gt});return On?wr?ie<=gn:ne<gn-ae:wr?ie<=gn+ae:ne<gn}),_t=rv({draggable:b,closest:Xe,inHomeList:Hu(b,M)});return Vh({draggable:b,insideDestination:z,destination:M,viewport:U,last:H,displacedBy:le,index:_t})},cy=4,i0=function(g){var A=g.draggable,b=g.pageBorderBoxWithDroppableScroll,M=g.previousImpact,z=g.destination,H=g.insideDestination,U=g.afterCritical;if(!z.isCombineEnabled)return null;var k=z.axis,te=jd(z.axis,A.displaceBy),le=te.value,ae=b[k.start],ne=b[k.end],ie=kh(A,H),me=vc(ie,function(_t){var on=_t.descriptor.id,Gt=_t.page.borderBox,gn=Gt[k.size],On=gn/cy,wr=Ac(on,U),Oi=nv({displaced:M.displaced,id:on});return wr?Oi?ne>Gt[k.start]+On&&ne<Gt[k.end]-On:ae>Gt[k.start]-le+On&&ae<Gt[k.end]-le-On:Oi?ne>Gt[k.start]+le+On&&ne<Gt[k.end]+le-On:ae>Gt[k.start]+On&&ae<Gt[k.end]-On});if(!me)return null;var Xe={displacedBy:te,displaced:M.displaced,at:{type:"COMBINE",combine:{draggableId:me.descriptor.id,droppableId:z.descriptor.id}}};return Xe},iv=function(g){var A=g.pageOffset,b=g.draggable,M=g.draggables,z=g.droppables,H=g.previousImpact,U=g.viewport,k=g.afterCritical,te=vm(b.page.borderBox,A),le=ly({pageBorderBox:te,draggable:b,droppables:z});if(!le)return ZA;var ae=z[le],ne=Kc(ae.descriptor.id,M),ie=Wh(ae,te);return i0({pageBorderBoxWithDroppableScroll:ie,draggable:b,previousImpact:H,destination:ae,insideDestination:ne,afterCritical:k})||uy({pageBorderBoxWithDroppableScroll:ie,draggable:b,destination:ae,insideDestination:ne,last:H.displaced,viewport:U,afterCritical:k})},Qh=function(g,A){var b;return(0,Ge.Z)({},g,(b={},b[A.descriptor.id]=A,b))},Zh=function(A){var b=A.previousImpact,M=A.impact,z=A.droppables,H=co(b),U=co(M);if(!H||H===U)return z;var k=z[H];if(!k.subject.withPlaceholder)return z;var te=Uu(k);return Qh(z,te)},dy=function(g){var A=g.draggable,b=g.draggables,M=g.droppables,z=g.previousImpact,H=g.impact,U=Zh({previousImpact:z,impact:H,droppables:M}),k=co(H);if(!k)return U;var te=M[k];if(Hu(A,te)||te.subject.withPlaceholder)return U;var le=mm(te,A,b);return Qh(U,le)},Xd=function(g){var A=g.state,b=g.clientSelection,M=g.dimensions,z=g.viewport,H=g.impact,U=g.scrollJumpRequest,k=z||A.viewport,te=M||A.dimensions,le=b||A.current.client.selection,ae=Po(le,A.initial.client.selection),ne={offset:ae,selection:le,borderBoxCenter:Na(A.initial.client.borderBoxCenter,ae)},ie={selection:Na(ne.selection,k.scroll.current),borderBoxCenter:Na(ne.borderBoxCenter,k.scroll.current),offset:Na(ne.offset,k.scroll.diff.value)},me={client:ne,page:ie};if(A.phase==="COLLECTING")return(0,Ge.Z)({phase:"COLLECTING"},A,{dimensions:te,viewport:k,current:me});var Xe=te.draggables[A.critical.draggable.id],_t=H||iv({pageOffset:ie.offset,draggable:Xe,draggables:te.draggables,droppables:te.droppables,previousImpact:A.impact,viewport:k,afterCritical:A.afterCritical}),on=dy({draggable:Xe,impact:_t,previousImpact:A.impact,draggables:te.draggables,droppables:te.droppables}),Gt=(0,Ge.Z)({},A,{current:me,dimensions:{draggables:te.draggables,droppables:on},impact:_t,viewport:k,scrollJumpRequest:U||null,forceShouldAnimate:U?!1:null});return Gt};function Am(g,A){return g.map(function(b){return A[b]})}var s0=function(g){var A=g.impact,b=g.viewport,M=g.draggables,z=g.destination,H=g.forceShouldAnimate,U=A.displaced,k=Am(U.all,M),te=Ps({afterDragging:k,destination:z,displacedBy:A.displacedBy,viewport:b.frame,forceShouldAnimate:H,last:U});return(0,Ge.Z)({},A,{displaced:te})},sv=function(g){var A=g.impact,b=g.draggable,M=g.droppable,z=g.draggables,H=g.viewport,U=g.afterCritical,k=Xh({impact:A,draggable:b,draggables:z,droppable:M,afterCritical:U});return Vd({pageBorderBoxCenter:k,draggable:b,viewport:H})},xm=function(g){var A=g.state,b=g.dimensions,M=g.viewport;A.movementMode!=="SNAP"&&Ot(!1);var z=A.impact,H=M||A.viewport,U=b||A.dimensions,k=U.draggables,te=U.droppables,le=k[A.critical.draggable.id],ae=co(z);ae||Ot(!1);var ne=te[ae],ie=s0({impact:z,viewport:H,destination:ne,draggables:k}),me=sv({impact:ie,draggable:le,droppable:ne,draggables:k,viewport:H,afterCritical:A.afterCritical});return Xd({impact:ie,clientSelection:me,state:A,dimensions:U,viewport:H})},av=function(g){return{index:g.index,droppableId:g.droppableId}},ov=function(g){var A=g.draggable,b=g.home,M=g.draggables,z=g.viewport,H=jd(b.axis,A.displaceBy),U=Kc(b.descriptor.id,M),k=U.indexOf(A);k===-1&&Ot(!1);var te=U.slice(k+1),le=te.reduce(function(me,Xe){return me[Xe.descriptor.id]=!0,me},{}),ae={inVirtualList:b.descriptor.mode==="virtual",displacedBy:H,effected:le},ne=Ps({afterDragging:te,destination:b,displacedBy:H,last:null,viewport:z.frame,forceShouldAnimate:!1}),ie={displaced:ne,displacedBy:H,at:{type:"REORDER",destination:av(A.descriptor)}};return{impact:ie,afterCritical:ae}},a0=function(g,A){return{draggables:g.draggables,droppables:Qh(g.droppables,A)}},td=function(A){},Xf=function(A){},fy=function(g){var A=g.draggable,b=g.offset,M=g.initialWindowScroll,z=Yi(A.client,b),H=as(z,M),U=(0,Ge.Z)({},A,{placeholder:(0,Ge.Z)({},A.placeholder,{client:z}),client:z,page:H});return U},o0=function(g){var A=g.frame;return A||Ot(!1),A},l0=function(g){var A=g.additions,b=g.updatedDroppables,M=g.viewport,z=M.scroll.diff.value;return A.map(function(H){var U=H.descriptor.droppableId,k=b[U],te=o0(k),le=te.scroll.diff.value,ae=Na(z,le),ne=fy({draggable:H,offset:ae,initialWindowScroll:M.scroll.initial});return ne})},lv=function(g){var A=g.state,b=g.published;td();var M=b.modified.map(function(On){var wr=A.dimensions.droppables[On.droppableId],Oi=Uh(wr,On.scroll);return Oi}),z=(0,Ge.Z)({},A.dimensions.droppables,{},Hg(M)),H=Hf(l0({additions:b.additions,updatedDroppables:z,viewport:A.viewport})),U=(0,Ge.Z)({},A.dimensions.draggables,{},H);b.removals.forEach(function(On){delete U[On]});var k={droppables:z,draggables:U},te=co(A.impact),le=te?k.droppables[te]:null,ae=k.draggables[A.critical.draggable.id],ne=k.droppables[A.critical.droppable.id],ie=ov({draggable:ae,home:ne,draggables:U,viewport:A.viewport}),me=ie.impact,Xe=ie.afterCritical,_t=le&&le.isCombineEnabled?A.impact:me,on=iv({pageOffset:A.current.page.offset,draggable:k.draggables[A.critical.draggable.id],draggables:k.draggables,droppables:k.droppables,previousImpact:_t,viewport:A.viewport,afterCritical:Xe});Xf();var Gt=(0,Ge.Z)({phase:"DRAGGING"},A,{phase:"DRAGGING",impact:on,onLiftImpact:me,dimensions:k,afterCritical:Xe,forceShouldAnimate:!1});if(A.phase==="COLLECTING")return Gt;var gn=(0,Ge.Z)({phase:"DROP_PENDING"},Gt,{phase:"DROP_PENDING",reason:A.reason,isWaiting:!1});return gn},ym=function(A){return A.movementMode==="SNAP"},bm=function(A,b,M){var z=a0(A.dimensions,b);return!ym(A)||M?Xd({state:A,dimensions:z}):xm({state:A,dimensions:z})};function Yh(g){return g.isDragging&&g.movementMode==="SNAP"?(0,Ge.Z)({phase:"DRAGGING"},g,{scrollJumpRequest:null}):g}var Em={phase:"IDLE",completed:null,shouldFlush:!1},u0=function(g,A){if(g===void 0&&(g=Em),A.type==="FLUSH")return(0,Ge.Z)({},Em,{shouldFlush:!0});if(A.type==="INITIAL_PUBLISH"){g.phase!=="IDLE"&&Ot(!1);var b=A.payload,M=b.critical,z=b.clientSelection,H=b.viewport,U=b.dimensions,k=b.movementMode,te=U.draggables[M.draggable.id],le=U.droppables[M.droppable.id],ae={selection:z,borderBoxCenter:te.client.borderBox.center,offset:Da},ne={client:ae,page:{selection:Na(ae.selection,H.scroll.initial),borderBoxCenter:Na(ae.selection,H.scroll.initial),offset:Na(ae.selection,H.scroll.diff.value)}},ie=Uf(U.droppables).every(function(of){return!of.isFixedOnPage}),me=ov({draggable:te,home:le,draggables:U.draggables,viewport:H}),Xe=me.impact,_t=me.afterCritical,on={phase:"DRAGGING",isDragging:!0,critical:M,movementMode:k,dimensions:U,initial:ne,current:ne,isWindowScrollAllowed:ie,impact:Xe,afterCritical:_t,onLiftImpact:Xe,viewport:H,scrollJumpRequest:null,forceShouldAnimate:null};return on}if(A.type==="COLLECTION_STARTING"){if(g.phase==="COLLECTING"||g.phase==="DROP_PENDING")return g;g.phase!=="DRAGGING"&&Ot(!1);var Gt=(0,Ge.Z)({phase:"COLLECTING"},g,{phase:"COLLECTING"});return 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function(b){b.type==="INITIAL_PUBLISH"&&g.dragging(),b.type==="DROP_ANIMATE"&&g.dropping(b.payload.completed.result.reason),(b.type==="FLUSH"||b.type==="DROP_COMPLETE")&&g.resting(),A(b)}}}},We={outOfTheWay:"cubic-bezier(0.2, 0, 0, 1)",drop:"cubic-bezier(.2,1,.1,1)"},Ee={opacity:{drop:0,combining:.7},scale:{drop:.75}},et={outOfTheWay:.2,minDropTime:.33,maxDropTime:.55},tt=et.outOfTheWay+"s "+We.outOfTheWay,pt={fluid:"opacity "+tt,snap:"transform "+tt+", opacity "+tt,drop:function(A){var b=A+"s "+We.drop;return"transform "+b+", opacity "+b},outOfTheWay:"transform "+tt,placeholder:"height "+tt+", width "+tt+", margin "+tt},ot=function(A){return pc(A,Da)?null:"translate("+A.x+"px, "+A.y+"px)"},xt={moveTo:ot,drop:function(A,b){var M=ot(A);return M?b?M+" scale("+Ee.scale.drop+")":M:null}},ut=et.minDropTime,Ze=et.maxDropTime,tn=Ze-ut,Ft=1500,wt=.6,an=function(g){var A=g.current,b=g.destination,M=g.reason,z=mu(A,b);if(z<=0)return ut;if(z>=Ft)return Ze;var 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k=H.phase==="DROP_PENDING"&&H.isWaiting;k&&Ot(!1),H.phase==="DRAGGING"||H.phase==="DROP_PENDING"||Ot(!1);var te=H.critical,le=H.dimensions,ae=le.draggables[H.critical.draggable.id],ne=Zt({reason:U,lastImpact:H.impact,afterCritical:H.afterCritical,onLiftImpact:H.onLiftImpact,home:H.dimensions.droppables[H.critical.droppable.id],viewport:H.viewport,draggables:H.dimensions.draggables}),ie=ne.impact,me=ne.didDropInsideDroppable,Xe=me?Hd(ie):null,_t=me?kf(ie):null,on={index:te.draggable.index,droppableId:te.droppable.id},Gt={draggableId:ae.descriptor.id,type:ae.descriptor.type,source:on,reason:U,mode:H.movementMode,destination:Xe,combine:_t},gn=Ht({impact:ie,draggable:ae,dimensions:le,viewport:H.viewport,afterCritical:H.afterCritical}),On={critical:H.critical,afterCritical:H.afterCritical,result:Gt,impact:ie},wr=!pc(H.current.client.offset,gn)||!!Gt.combine;if(!wr){b(L({completed:On}));return}var 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M&&z},nr=function(A,b){td(),b(),Xf()},Tn=function(A,b){return{draggableId:A.draggable.id,type:A.droppable.type,source:{droppableId:A.droppable.id,index:A.draggable.index},mode:b}},In=function(A,b,M,z){if(!A){M(z(b));return}var H=kn(M),U={announce:H};A(b,U),H.wasCalled()||M(z(b))},pn=function(g,A){var b=xn(),M=null,z=function(ie,me){M&&Ot(!1),nr("onBeforeCapture",function(){var Xe=g().onBeforeCapture;if(Xe){var _t={draggableId:ie,mode:me};Xe(_t)}})},H=function(ie,me){M&&Ot(!1),nr("onBeforeDragStart",function(){var Xe=g().onBeforeDragStart;Xe&&Xe(Tn(ie,me))})},U=function(ie,me){M&&Ot(!1);var Xe=Tn(ie,me);M={mode:me,lastCritical:ie,lastLocation:Xe.source,lastCombine:null},b.add(function(){nr("onDragStart",function(){return In(g().onDragStart,Xe,A,zd.onDragStart)})})},k=function(ie,me){var Xe=Hd(me),_t=kf(me);M||Ot(!1);var on=!zr(ie,M.lastCritical);on&&(M.lastCritical=ie);var Gt=!Fn(M.lastLocation,Xe);Gt&&(M.lastLocation=Xe);var gn=!Zn(M.lastCombine,_t);if(gn&&(M.lastCombine=_t),!(!on&&!Gt&&!gn)){var On=(0,Ge.Z)({},Tn(ie,M.mode),{combine:_t,destination:Xe});b.add(function(){nr("onDragUpdate",function(){return In(g().onDragUpdate,On,A,zd.onDragUpdate)})})}},te=function(){M||Ot(!1),b.flush()},le=function(ie){M||Ot(!1),M=null,nr("onDragEnd",function(){return In(g().onDragEnd,ie,A,zd.onDragEnd)})},ae=function(){if(M){var ie=(0,Ge.Z)({},Tn(M.lastCritical,M.mode),{combine:null,destination:null,reason:"CANCEL"});le(ie)}};return{beforeCapture:z,beforeStart:H,start:U,update:k,flush:te,drop:le,abort:ae}},Rn=function(g,A){var b=pn(g,A);return function(M){return function(z){return function(H){if(H.type==="BEFORE_INITIAL_CAPTURE"){b.beforeCapture(H.payload.draggableId,H.payload.movementMode);return}if(H.type==="INITIAL_PUBLISH"){var U=H.payload.critical;b.beforeStart(U,H.payload.movementMode),z(H),b.start(U,H.payload.movementMode);return}if(H.type==="DROP_COMPLETE"){var k=H.payload.completed.result;b.flush(),z(H),b.drop(k);return}if(z(H),H.type==="FLUSH"){b.abort();return}var te=M.getState();te.phase==="DRAGGING"&&b.update(te.critical,te.impact)}}}},Ln=function(g){return function(A){return function(b){if(b.type!=="DROP_ANIMATION_FINISHED"){A(b);return}var M=g.getState();M.phase!=="DROP_ANIMATING"&&Ot(!1),g.dispatch(L({completed:M.completed}))}}},jr=function(g){var A=null,b=null;function M(){b&&(cancelAnimationFrame(b),b=null),A&&(A(),A=null)}return function(z){return function(H){if((H.type==="FLUSH"||H.type==="DROP_COMPLETE"||H.type==="DROP_ANIMATION_FINISHED")&&M(),z(H),H.type==="DROP_ANIMATE"){var U={eventName:"scroll",options:{capture:!0,passive:!1,once:!0},fn:function(){var te=g.getState();te.phase==="DROP_ANIMATING"&&g.dispatch(Z())}};b=requestAnimationFrame(function(){b=null,A=Ia(window,[U])})}}}},Yr=function(g){return function(){return function(A){return function(b){(b.type==="DROP_COMPLETE"||b.type==="FLUSH"||b.type==="DROP_ANIMATE")&&g.stopPublishing(),A(b)}}}},qr=function(g){var A=!1;return function(){return function(b){return function(M){if(M.type==="INITIAL_PUBLISH"){A=!0,g.tryRecordFocus(M.payload.critical.draggable.id),b(M),g.tryRestoreFocusRecorded();return}if(b(M),!!A){if(M.type==="FLUSH"){A=!1,g.tryRestoreFocusRecorded();return}if(M.type==="DROP_COMPLETE"){A=!1;var z=M.payload.completed.result;z.combine&&g.tryShiftRecord(z.draggableId,z.combine.draggableId),g.tryRestoreFocusRecorded()}}}}}},si=function(A){return A.type==="DROP_COMPLETE"||A.type==="DROP_ANIMATE"||A.type==="FLUSH"},Ur=function(g){return function(A){return function(b){return function(M){if(si(M)){g.stop(),b(M);return}if(M.type==="INITIAL_PUBLISH"){b(M);var z=A.getState();z.phase!=="DRAGGING"&&Ot(!1),g.start(z);return}b(M),g.scroll(A.getState())}}}},ui=function(g){return function(A){return function(b){if(A(b),b.type==="PUBLISH_WHILE_DRAGGING"){var M=g.getState();M.phase==="DROP_PENDING"&&(M.isWaiting||g.dispatch(F({reason:M.reason})))}}}},bi=je.qC,Di=function(g){var A=g.dimensionMarshal,b=g.focusMarshal,M=g.styleMarshal,z=g.getResponders,H=g.announce,U=g.autoScroller;return(0,je.MT)(u0,bi((0,je.md)(ke(M),Yr(A),Ce(A),Qn,Ln,jr,ui,Ur(U),Dn,qr(b),Rn(z,H))))},Hi=function(){return{additions:{},removals:{},modified:{}}};function wi(g){var A=g.registry,b=g.callbacks,M=Hi(),z=null,H=function(){z||(b.collectionStarting(),z=requestAnimationFrame(function(){z=null,td();var ae=M,ne=ae.additions,ie=ae.removals,me=ae.modified,Xe=Object.keys(ne).map(function(Gt){return A.draggable.getById(Gt).getDimension(Da)}).sort(function(Gt,gn){return Gt.descriptor.index-gn.descriptor.index}),_t=Object.keys(me).map(function(Gt){var gn=A.droppable.getById(Gt),On=gn.callbacks.getScrollWhileDragging();return{droppableId:Gt,scroll:On}}),on={additions:Xe,removals:Object.keys(ie),modified:_t};M=Hi(),Xf(),b.publish(on)}))},U=function(ae){var 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t+//CHP0x6w3r4SturKcclfu9973trXkmXEkJn+4SHZeSBzC3CoFOOZlVEH6gwcvmFL3whyaPloXQZzfqFSdwlNBAzVO2iAIuU0HnnnZdWmVoNWmGoMWJ9k6nNWzCtnb4Bi8CKjJBF9d6tOq1fs1yWRp7M/fffP+GLNQ6avNbgwb877rijISzk+2v7JkPqQxU1vB7izipvvBkD+RUW5FnAJmVlvUcY6ieffDIbDmvjTw1gUYgB2bz99tsnbvVcv2x79PGyyy5rUKY8ds7X0L1kjuW8Urn3rGfEr1b5TsbNyovKQbNXv/rV1fkiJf23ZWoupZMcXHrppYnO0mceOHp67xUPi8Ztea0FmGg2Sw5QLU9Ly8MXPNmE3i0w8SA5AEspRXsqtwjAQptCrSiehx56KE1wxa4V7+xbmdaQbBkAy3PPPbcpZGZBpoyUDxvlxlgLWOAFfPnOd76TwIdyT6R8bU6NXN+UE2CxffKgxgJTO56aZMWhAIvGQr8YA4Dl6aefnqyiZEilpBQG0HgBLE888cTEg1GSRFgDWHCX04c3velNzaFDh9Lf+gw6W++KlQPGdfnllydDOvScKgUs8p625fog+7jivUGg/9Ds/PPPr/Iy1sx9lS0FLFafQWfmgfSZ8rm8wVYbew2waI7Jkwb/RbPSEPcsvKx9h/6xmNaizb/vQba+Dw9LLaUryy8CsKiLzz77bPOa17wmARb7HDx4MP2T70uUfuWQi4oDWLhJuebpy8MiwyhjRB+sR4U8CeK+/JQYIAALHpOS6+hlIM4999wEWGjDGw2fN6C+MVnf+ta3JuDp+3XaaaelHJW2PJVTTjmlwUiVPHgX4E+fjx2jDBBhMXaweO8LhhS6PPPMM5u6QL7Lf/3XfzUkX3qatfW1BrBQB3Ri7J/73Oc2VYkhYL6QE+LlhX+/5S1vmaz8FRby4+qDnniYfN5Prl4BV/rMfNdq24YQLahR8jl1oS8wJjwCiwoX9TEG1fGBD3yg4afkod/Iw1VXXdXceeedrfrM17WXAMvhw4cb9ICfG7/7u7+bZBO9tih9D1/k1ZPcvfKVr2y++93vTsJZkjfrNQsPS8ns6LHMIgCLDAIGWQmkQtx2aN6d2uOwO6taBg+LEr5yaN4CmK7B1HpYqI/Jmts6bXdxWVACr7S6sGE99c2HIeT+5TdGpybhdigPi5c9GxKyY/VgzCeQ+lDeNP7UABbmC8oUDws0kJfSyod1WcvrgiKWh0WhixqPVpd82e9LPSy5ZFk7DiVjyiCo3/KwKCTUlk9U0+e2sqUeFt4XLwiJAlgk0zbMIaDo5WwvnMMi+giYQgMlKUMzdMcyhITUBxsSErimz7nwvOVneFj6mHlT6lgEYKE7ahfAopCQjLAyxRHo0pVq32RSnkBNvX15WEQf/barDmtoSmkDYGFFWuJhUVsAFjwstKHPtI1XfbCJaJSzOSzeIMpbZA2PN7SltB7Sw2KBoAUsdjyMG5pAD8YtPpxxxhlpx0vbnMqNrwawCMALTFuvBG3KAEhubJKjjIKU7lCApdTDYoGsNQT8bY0a//ZhRNHMyuYQ48G7ct1115WKZSqHJ0shIcmS9QL5yvaKh4VxS3/Y8BjzSN6/KkIPVNiCple84hWTRVvOqyzZDMAyEDNy1S4KsKgvNuk2AMtJDokvMvD6ZjcBFm+0SsV+WQGLkm5Lx0G5GsCiem3SrQDTNMDCd0pstF6Xmn6Wlu0LsPidGN7DQojTAp1lASyis5XtACwjanjAIhp5mpXK2hDlLGBh0Yb3Kzwsp66sQOyb7z2Sjve84oJThqB9UZ2LBCy0zeFkxAmHUDhFBGgptAwhIX8OjQUxdmXfNc7thoSsJ8QeZEe7to/WHaoDoqbx1R4gVxP+GyIkpLHYVTseFnmlcu58S3fe45C5xx57rMorWAtYaIeQ0C233DI5v8Lz34cQMRTkCbDyLzm3p0uepn1fGhKyAFzgxHoM285gQp7QF6997Ws3hRFr5Kd0fDUhIeqE7ldcccUkXOfbyfVxr3hY2uwMsgnNkE0fai3lU1/lLH+QSUDxt771rezZMH6OqQ8REuqLGy31LBKw0CWFhDTh+S3FtUgBXgbA0hfrtwtYbD+svNh8iFxISKCqbzA6BGDxoSq/rdmPNSeveFgw2DVPLWChbiWEa1cFv30uh6U93/k8AYGEvudYLWCpoZVoTm4VCx17TtOiAYvmheis/ligm6M53993332TJGLRwxtEu1CAxujNn/3sZ6l4CQ/bctKm0V/G19O2jdZ8rjBaLlzdZmtsuLJWHoYsD43lYelaFARgGZITpu4ALHlCB2DJJ93m5EVJpiQbony6vBHbFe0hAIs1FMr90LZmvvPGcRGARaEFZBMPi00QbMtn0lEBMgpD82YIwOLDojmQN0TCZq2HhX7iLdD2cZsPhby0JTwDwAAUevx4JX/iP2E3ko4BLLRRsiAIwFKvdQKwjHZtXnlhhIQm0hMeltvSirk0gbZ+2jUprIHCKkm6Vf1tCq7Lw0ICnR6t8vs+sXgIwJJL9PRJtxYgLAKwiJ4CLAq7SXa8F8gmq/rERq32S4xdjcwNAViszPF37uC4ZfCwQCebj+E9xZIf6xHhMw4nQw9a0Gzf1dj0GVvtOYdG3rzwsNRIaHnZACwBWLZISwCWnQtYfJ4BK0sMoxI7ZWD7zpsYArDYA61kGGwOC4Ir74Q3RPr30CGhHGCxE0r8sIf56XsBFsub0tV5uYpvkhEtOYelpk5blj7nQkKz1jftvRoPiw8JSV7kHYF35Gz57fttISEBYvHL9jMAyxDc3lpnAJYALAFYDAVQYhxOt1M9LBqKVulf/OIXm7e//e2beDyE54i7hH7913+9N63V1kebJ5DbneXzDGYBLFxi+frXv75oLAJMv/Vbv9XcdNNNm1bk/MN6VCxv+By+cC+KfYbgDXcJsb27z8cDRO4e4y4h61UZwsNy9dVXN+973/uKhiLAwp1Nd99996bTkXMJmtYrBl+4t0aP9ahY74newVOKzHBQHXJZ4iWLkFARGzcVCsASgCUAyy4ELBoSK3uOsvcr4npVMf0NLkvDKPT1eJe6NQze2PjwhIACv2cBLBgbJU92jUchH4ALp+ly2q5OeM2BFVsffPGhuZJQQlef/PcY0ppLNkvrt56Gl73sZVtOky2tp6bcJz7xieaTn/xk0SsCGVxKyeWUVm5y4R0LTt74xjc2XOjIY3kiWfOhSOQgx89pHQ3AUsTGACyGArfcF4AlAMsuBCzWaNrTV1GsKN2+r4wfYleBvZOHPsubkTtDo8+QUK0a1Wra5gdh0LxRtCDSJtra7ea8Yw8lrO1LrrwPo/VRp62D/rLyZWdN3333fSUkxGGQJY9AhQ1XCiCK5vZgP9UJP9nxxG4U/4jHlueUoS3qtocxdvUxAEsXhbZ+Hx6WACwBWAKw1GsO90YAlpNHhFuwqBW6DfXYvBa+D8BSLn4BWD6fdv35cFtb+I3PY1vziGY1T02uVE292y0bHpYMBSPpdufmsGhnjc+FyG3L3O7kse8PAVhUv1/V5j5flIdFHisBD09ThRNs2GrevBnCw+K3LOe8BUPIXA1gEU9uvvnmiZHnM4Xq5BnJ9RMdyM4nPX68+re8fbMkS4eHpV4DhYclPCzhYdllHpZphsKfQ1GvMvJvDAFYrJHIJT367+XNkFHi9yw5LNuhid+lZXnRRfs2sLmd/vDuEIDFruiXNSSkPvodbJZHubmSCwlZkNmWM1WbfxSApV6yA7AEYAnAskMAC5P13nvvbT3+XQbb7nZQ7odWgDZHoi100WVYc2qmFrC07Sbxp8OWqrRFeVhkvPidy4ewIMoCKXtKqnij1Trl+roCYhbA0rYjpu0gOMrbO15KeTZLuVoPC23kttzndgmpP3zHEfC5m9HbclisHJSOKwBLKaVOlgvAEoAlAMsOASw5o4ACtcZNYMMnfLYBBA3dlp+mzNtUzHYuS2trr2bFuijAYulhD7pTf2zCsx2nDxHlVu0W4Aj42HKl6p77lGoOKLSG28tH23d7AbD4UJ6VT/9dCW+gGXcw1TxxNH8czY+8xEm3ZtZEDsty5bBIGepqdb8rhYOv2J0gUCI3d5sR96t+uz01d7ZJiUKtBSw5gGRvA/Z97OrDIgGLByIWVGjniICkaJ1LmvRgwPKF7/zOlC6a6PtawGI9dKpjGm/2iofFghKbBwON5BmsAdkBWEolODwsokAk3WZkJgDLcgEWhQo4yAo3tQ3leFe0FKk1MHymEISAAN8fPXo07VDxx8lLJGqSJmtCQrnQggw455jw+NNHu1TbIgGLTg3WllZPe8sjgRD7md0Oq5ADvDlw4MCms0MsoPFgZhp9SnNYcuE4S1f6A1+8Ud4rgAUaa77AHw86BVwETrtkNkJCXRTa+n2EhCIktEUqArAsF2CRIuRsiG9/+9tb+MWBVQcPHkzKVCvxrvMwdAGfVa4KaWBA+f60004runWWNi+77LJ0wVzJQzunn356c+TIkVTcrlbVB8ZSc33AogDLc889l4BFLiTAWJ599tk0VgHFLqChU1IFfvx70IzvLJjpovlZZ51VFBISQEWW6Le/yZjv287A2QshIXvGiuaXlTvodvjw4YlMd/FFNOsqZ7+PkFCEhJCHCAmZWRGAZbkAi4wEIaH7779/071AOgjLAhQfbrEXvGkFLy+GVowyjFo1CsjYRNBpirXGw2LPHRFg0apdHhbASo17fVGAxQI+9dcaektvjdWDSm2NtjzEkwEo0SOPjMJC/LuUN6UeFr9F13sQ6I/44vM39gJggR7QSN5Jy08f6rOh1bZ5Ex6WGqg2KhselvCwbJGaACzLBVhkyM4999yUpCfjJc+EX9174+2NnhQtxkcG1eco2NBSiVqpASwCULbfVuHTXu1t0osCLAJ69rcFfd7TVcMb3vW5EdPqbuNTKWCxISHfT/UFvuzlkJDoIE9YToYjJFSiMWYrE4AlAEsAFkMBFNCyXn4IYLnzzjs38UvK0a/kZUC53+bss89uXY3b1b3CMdyjU7urhEvpvvKVr1RpoUceeSQBE4EjHVdf41lRg4sGLISGfvSjH23hjc0D8h6LF7/4xc0pp5zSyhsAJQbSAlPRrIbQb3vb26ruEoL+XGZowdG0EN1eymER3QkPKZdMn3GfUi402MYrctL85ZddfI2QUISEkJEICZmZEh6W5fKwwBoMF+ESDKM3fHxvcwtsUiu3TnMOhbwWvMv3/pwPfU893NXCeRco5dI8ktxZFznlizFUkqnkTP2x5e1dO11KXB4j7+Xg30MfHKcdWnfccUc6TTWXUGw9SgIf9M3fcWNDZT7cI35BM26Tps5S3vz0pz9tnv/853eSUV4tcqLwytAHe5KvlzMLFvdCSMiHMi09nve856WTcclXsp6xTqJXFgjAEoAlAIubNAFYlguw2GRaQAs7FGSkARVtO2owjhjRQ4cOta78ZJCkjDFaN9xwQ/ORj3wkgaPSpxSwqD7qft3rXpdCXOqDVq07zcMC/QEsV1111STHQ56RttAW38MXAGXbqtwfLse/oRmX8pWCFehdClgE+B577LGG1b/NI5oGXveqh8WGVNk6/o1vfKPBazbkE4AlAEsAlgAsEwosY0jIhju85yG3orcr32mARcDA7lwBPHzoQx9KPzV5JLWAhbrZ9aTTRO12X+spKVX+iwwJMRYMyRVXXJHyO2yOUVs+Qxdg0Xs2B0ZHxkOzkqRO0a4GsPDOT37ykxRGtH33O4YsX/YaYFH41R4UiEeKhHiAy5BPAJYALAFYArAsNWCZVQGiWFnBk5OTW8XLsPr6FRKqabcWsFC3LpizIa62pNSuviwSsNC3WQzJtFypNt74S/m66FLrYaE8+UsYYB96zIUi5enbCyEhuxAQ2JfcEXokJFQSeivhWVuZWeQsbmuO25q3I3Od7y6DIXnooYdSP/3EnMVd3zngwgI2H6PwlUk+Ro3yXdak29IxW8UagOXMFBIZ+pnFkARgqefKou8SEkALwBFOpeUAACAASURBVFLPuz7eiF1CsUtoixxFDsty5bDMOtHDwzJ80q14E4DllSm3pmaXzCxyHYBl5C2oWYCFhyU8LLPMteJ3wsOSJ1V4WIpFKBUMwBKAJUJC/d7WHB6WOh3Ud+nwsISHJTwshgLLmHQ766QPwBKAJQBLAJbwsISHZVYbUvReeFjCw1IkKB2FArAEYAnAEoAlAEsAlj7sSWsdAVgCsPQhYAFYArAEYAnAEoAlAEsf9iQASyUVI4eljmABWAKwBGAJwBKAJQBLneWoLB0elvCwVIpMtngAlgAsAVgCsARgCcDShz1ZWg/LO97xjubRRx8ddIyzVH7xxRc3n/jEJ6pe1SFoNdsAZzmH5a677qo6yp77WqAzv0sfLsq75JJLSounctDs4x//eNXBcZ/61Kcafmoe+EJbNU8cHNe+fb5t0TLL3Lzpppsa7ropfZBJLkzkKZ03L3nJS5rPfOYzVduaOaDunnvuKe1WKscBhbfffnvVOznZ9Oeo2Ar57p3vfGe6zDJ3M3XuLKqDBw8273vf+xp+lz6zzOdZts/PAli4zLSWN6XjnrUcsnjOOee0ylkbT0WzmnbZPn/dddfVvDKXsrfcF7uE5kLoRTXSN2Dp8wTSWppwmqiOsvcKdujzL2r7WlI+AMvw5/2U8GHoMm1zZqcaktx4AF/Mz5pbztvm8zR+9A1Yhub9POsPwDJPapu2Fh0SWtCwB2k2AMsgZO2l0gAsAVg4BK3mWYaVbwCWGo7Nr2wAlvnRelNLAVj6I3wAlv5o2XdNAVgCsARg+V7VtAoPSzu5ArBUiVJ/hQOw9EfLACz90bLvmgKwBGAJwBKApS+9EoClL0pW1hOApZJgU4oHYOmPln3XFIAlAEsAlgAsfemVACx9UbKyngAslQQLwFK1O6M/6m6vpgAsAVgCsARg2Z4WOfl2AJa+KFlZTwCWSoIFYAnAsrKSpMArrTPPPLP56U9/2p9AtdQ0S27BLNvnBx/IAA3ELqE8UWOXUL/CFoClX3oW1xaApZhUnQUjJNRJooUVCA9LeFjCwxIelr4UUACWvihZWU8AlkqChYclPCzhYelv0vRcU3hYwsPSs0hlqwvAMg8qZ9oIwNIf4cPD0h8t+64pPCzhYQkPS3hY+tIrAVj6omRlPQFYKgnWUvy5555rbrzxxuYjH/lIc/z48ZTfsLa2lkqfOHEi+xYnxk7LLVjkSbevetWrmvvuu69ZXV2d9H19fT39m988+s4eH547BZfylKE836se6oBW0Iejw4d8SgCL+p5TRvrMjlljUb9f8IIXNI899tiE70ONp68cFsakH2TV8xWZ5vN9+/b1PhTNCeo/evRoc+DAgUkbx44da/bv37+lzS4544VFeVgYD2Oh78iI5j7/hn65edFm9OzAc+NZ1pNuGTdH81977bWb9EbvwrMkFTJf4DuyCp/4+4477miuuuqqJNOlzzIcUJjraxzNX8rBHVYOo4tSkocFZeVBSu6zZQUs9EuABVZYQ+4VrwUfTFoUtDU+YqWMod7nt5Q7ig56DWEY1X4JYLFiB4DCYOuxQM1/JhBD0i2AZchx0HZfgMXyxvKVv1G4KGKBzSHGhLzQDrTOGWYLaqyc0W8PcjSWRQEW2kdekH3dieTnikANY+E7fS9at4Ea//kyARb6Jt0G7a3x9TzbYWq9tbu5cekzzU3mDvqt5AnAUkKlcZk+PSzvec97GgzDXnrsqg9h5UcGWIbMeyZEn3kBFgzCH/3RHxV7MaZ5Gvzqz46FnQjvete7Jp4Uu+LNARatSKCZ5LDkniLkjLZqni7AYi/ekxL+X//rfyWa+Uv57JyxxkneCmuMuvr4/Oc/v+Hyt5pnHoAF3vzN3/zNZNdTCV8YwzXXXFMsZ9Dr8OHDzV/91V+l4Xu6SmYsbegHNPvDP/zDrJwtErCwcPn0pz/dfP/739/kUZGMtHlUGAveOR4PdnaChwU9p7H9zu/8TmNDb238qJH3ZSqbm/sWLMN7LnPNLVDbxhGApYLDfQKWimZ3ZVEZKh/20CrVD3pegAUFz0Tid+lD+fPOO28TkGAcbZ4i5AhlxQ23WklaAy7Q5g2fvFKl/aIcbdBWzdMFWORBoX8CnGxRxmsiQ6L2xE9oYecPK9+f+7mfq+lWAl65SyanVdInYKH/4qtvUzSrGRA0q5GzNprZEJU19PwtmknO6J/ka5GAhX5grOGPfRQe8npA4AT+v/zlL0+vaNw+9GjrWyYPiwVZ6js8yHkka+RomctKR2ju5PS6Xch2jSUASxeFzPcBWCqI1VJ0Gppm4uImPnLkyJa3lxWwIBMPPPBAc9FFF02MmTXoGAo/IfkeZX3rrbduiddLxmwuC6tRxv+hD32ouf7661MYhc9KniEAS07pPP74480LX/jCLV1iHHLr81s5Ck8++WS6kr7UFUzFywBY4AO0l5GEv/z96le/unn44YfT36W8KQUsCvc8/fTTicaSL9GzrT3KAaTuv//+1ryQnDdoyNuakW+FNC+99NKUxyCaIhu5+SKhQncwljbP9DJ7WCQvAl52USL+em9tyfxe9jIaL+P33nT63gZk2sYVgKWC430CFpugWdGFHV+UiXrw4MGkmKT4rTsbGqOYvBKeJ2BhFVey8lW/MVQAFoyvByc2mdiCNbwet99++2TCaiXC72effTYZdp9MecMNNzQf/vCHE6ArlR8lKtcITpeHhT7SPykbfgNARDMb1vMhH3mSnnjiiQRYrIu8q48AlgcffLCr2Kbv+/awwBvk1xv617zmNalvyjUq6eRPfvKTIjmjLmhKzs9LXvKSLVWffvrpSWYkj1bOoNl3v/vdTYaB7304xVY6JGBRO8jwlVde2dx5552bxgNteRgPjzxzGhtjecUrXjEZj03SXWbAMk0erKeScqVzu0TGFl1G+h593rY48Tlw0/ocgKWCo30Clopmd1VR67619NTf8h54wz9PwLLdkJBWDgAO7YKSIpK3AQ/LoUOHkuEAvFmlZY2hVuwobjwshIVkwEoEYygPizUk9BEPi3ILbKKdPCw+ERXvgsqXjIMyi/SwCJyJNwJa8haQeI3c1PCm1sPys5/9LHlYbDhBRl0G3YYY6CvgEw+g5EzlJaPz9rDQruRdHhatvG3frIdRIJdyjEUeFhvmahvPsoSEbI6eAKX1qOzWsJAWLNLnXj5tEnKJHgjAUkKlcZkALBXEaimam5h2tYdhyyHxZQQsmoQPPfTQphwWDd2DLxsqsoBFIEZGxYI6C1gIBzFha5TbUIBFBlsKqAuwaFUv2giwiPclkrUMgEXj9oAFI4ocMJ5cAmxufLWAhZAQeT8esFjQMQ2wqF9WvhYFWBgDc4CQkAUsubG0ARYLjAOwlMyg+Zfx8pUDLKUhVHofgKWCh30ClpyiqOjKji5qx+6VqIz3Ij0stSEhVtaEBORNgDnk4uhsDq26BTQYm5Ju9Z0NnbB1E4UuLwZl+B7vijwspQJA2KnvpFvatoCFf1vjq5Wv8jvoO7TA9ascBcoT3hBgKTHyCm+Ujp1yfYaEqE9bhK18MgaSruVhKe2fDaOVvKOkW++lRNYUjpSnTh4KC/KWBbBorAIskgFoqjAo49FYBFj4zdzUrredBFg8fy1QtzwrkYOdVEY8hVfSB+LnLOMIwFJBtT4BS0Wzu66odYX6FXab92AZPSxiDIZKbmoBDyVEynBoBchvgAgg4nOf+9yWc0jaZIxVCB4Wclg8mJsmIEN5WGybGJlHHnmkOeuss7acQ2NDQnZsO3WXUG6hgXG98MILE2Cp4U2ph0W0pvzZZ589NanXzifkDCD1rW99K3veTZuszSOHhbYvv/zytIutDax63YCcMRbCbzk+7IQcFhtK5W/0nTzKVi/uOqXvBqQQsTYUlM6bACyFkmHRPMRV7JrPMSS1K9/CZvdsMR9ygM4yvrmkzjblW7vddNZtzbTjFWxbuIPPASwkxJYqXgRh6G3NoqG8Bfzb70jynhUBMBJCfU6K5wnKSaGhnRYS0kTsS868V2raRJcyJ4cFGsutrnChPF4CxSrP98ilP4WZcnYOUV7J4dO8UtP6WGNIRMO3vOUtyQPWJmfqp10E4GE599xzU1fs4sZ6KK2c4cVCngHIpU9N6FFjYRyMR2Ox3taaEG5pH/dquRo5myeNlu6kW6+o7EmMABZ+7Cp6nsTajW3Z1YYmvACLPbuEsQsY5Ix/AJbyc1gUjmOLLoZBhsyeRGyNh+QO/rDrx56rIqNpeWKTJDEk8siUuohrDIn61ndIaBGARR4IAAs0E9iAtn5LLJ+pPH/bpFsLuqzOEACS/oJmJMTW6LMaQyI5u+yyy9IipE3O1L4HLPYcFrsyl6x5OcMjI8BSspKvkTONBZoxHv6dyzEqaXc36vG+x1QjZ323Pa2+pQMsvrN2hcLuDX54/DHz8yTabm1LmeQotze96U3Zo+n7MiR72cOi3RsXXHBBAixSvl6mcytGH97w+QWaG1rJA1he9KIXTZJUSxR6jSHZTYBF9AewEBKyuUFdvMnRrM1DKY8GxpctxzW6rMaQSM6uuOKKSUho2vlMyvHgPX9wXE7nWdlDzs4///wEWJCx0lyp0gMKNRZoxnjsQrZEpnerzh5qXDVyNlQfcvUuJWDx2+ikhAVYSibDPIm4k9vSJVlyraK0fAKp3Q4cgCXP7docFuhtAYv1osig+ZYwNrmQkFbIdgWvdzmDBONbM2f2KmARzTC+AiyWB20hh2khISUP2xwrgUl5pWpCGbWGhHYtYMnJme5nUh/RAZzDYq+asN5WAWxLG+QMwALtSp9aOaNdC1hKeFPalyi3mQK1cjYv+i0dYBFqz7m6lVugkxrnRaTd3E5udSLAkjOAAVi2B1ign/KyfBjN5uLY8yTsyhcPyxlnnJE6oTwX/vYJ1uqlkm6ZMzbeP02maw0Jde2GkJA8HdrWbGkk3ogvApUKS3DImrxl07YzCzhSRjRTHSV65rrrrmv46XqsnPmj+b2c5cCsDo6TnGm8Cht5PaBzWJ555pnJ5ZRdfazZjaZ8GbZn23uBfEg7vC1dVC/7vlTOymrrr9TSARZNDE16IXsElpNOtUMgl0fRH1n2Vk2elhdffHHryaABWLYHWHhbuST//u//PrkeQTkR0+Sa7z760Y9ObmwWL3x+geUROyO+9KUvFRsR+rdXAYvoiK75t3/7t007kWw+i6Wv3gFIfvKTn8xeSimJEfCUjgOwvvvd757kypRoHd4pvcxVcva1r31t04WRygcR0M3N6UsuuSR7YaTq1Jku2o2DJ+nLX/7y5ADHEv186qmnNrRT8qhdgNFXv/rVTfdlqf9tyfcl9UeZzRSokbN50m5HARYmiSaKXenMk2C7ta3SXTQBWPoDLH6Hlg2FWg+jNRIk3OIB4Mmdt6AcBX9VgQ1JdMnwXgcs8izKsCvp1p7XI2OvMhxmh5K3OSJtO73EO3sxZ6k+KwEC4q+VmxzQEHjWWLxc5LzcbYBFXkOFj0v7WVpO7dJHhdDseUueN10yHt9Pp0ApX+ZNx6UDLN4geiWeC1PMm2i7qT3dycLk94pZSsiONwDL9gAL9GMFr7wBKQbr2m4zIBhHcivIF/CP3eFh3xfApz34WZLLslcBi04CVfhMNLUAoA3YEw4iJ8kn0HLYHN4HzS+BFX4LsLTNqe3omRo5QwdoG7zVARqLwK8HMD7XMJcAvp0x2Hfpo+4zskCyizd9tR/1LAcFlhKwTEP8EtbSFclykHln9CKncLSyaYtda2Sxrbl8W7NoZsGDXTXa772c42GxZ134hE392xqZEpBiJXSvAhZLA9HMAkGfv2L/bQ81VD2Wp34eUS+A5ZZbbhn8Er4uObNGP7cgtH1X2Rxws96VIVfoNg/Ienx2hpaNXm6HAksHWBiMN5y5XUPbGXS8e5ICudWKV9xWMYeHJS89tbuEfC1+9Zqjc87D0uaZ8SGlGpkPwHKSWqKjFlFtYZKch8WDHXkvlGsxpIeljd85OevyWlt97AGC98LUyNl2y+Z4MyRQ2m5/4/3tU2ApAYtX1kO6GrdPwuk15BScXdEseoJN6x/9nBaisyOfl4eFw6lsPNsbEvtvrWJ10m3OpW1d9RrP0Cfd5uhqlW/bKhbjcM4556SQUM7waOyqn9/Tzt1ok9wALGWARXOD33hYOAjQJrTm+Ci+8XtZAIuVA+kjD1KsnrI6wXtvhtan1O93kvo5v90+LJu92Y49tN6o7dJlGd5fSsCyDITpqw9KdszFgZdtYpSMmTg/sWRvMOcBWLSK7bp11Bppe/mhPU+GsVKPErmtUpgHYGkzCNNWrPT3pS99aTrttsSDgpHRrdw1OygCsJTMhFHSs+a1DQnZhGform3L4rmMiJXNshaHK+XDOfbYfQuALSi2Cy/lZXUtgGYdgQWHasvX1eb9bWuzrbzNl6mtc9bxTXtPyfWivXSwpX+OL9Jx/JbOXvQCebv0CcCyXQpOed+vROz5DENN7KGGI68GypcbgUkmlIsbBcwtyihtfdbVD066Lb2tWXXJKHg62lt0VVY7NDixVxe/2dCW3S5P/6mDzxgnBxTecMMNxWOhTbw4Nbc1W/5PW9X6kB05LJzEyuN3SfBvJVHblXwXL/z3uw2w1N7WXEIvyzP+1i4hn1Mk8IzB0NxRgqsu5oRX9o6hae3Pw+BYcEBfBLRom7+ZJ21J4yW066OM9JHCbsi9DsEsrZ937Xsa9zxoXNrHNlBGX633RGNB/gSQfdL4rG0u03sBWAbmhnZmaDL5ydCVQzJw96qr1wT3Lw7pYZHX4Qc/+MFk66g8V+qHp6s8CgIsPuSiCa6bXO14hvawtCU3q0/0BXmRsZDiYQzccaPTRGUcrfdEfwuc0RZ16abaEobvNsBSe1tzCY2sPEFzC6btd/wtMCwvhr5fFg+L9fzwt1+N+xCMZEwARuC5TTeU0LOkjN/FpUUJ79o+ldRFGQvM/KLBtlVa3xDlRPucN9gnH2sMGpflW5tXaog+D1lnAJYBqWvdrLkVL9sdOTxpJzw5j4AmPZPhwgsvTKvM0tADHhZO0+R316PV1P33399cdNFFW4ofPHgweX1sPF1GnlMxb7755k3bSj0QUIW0A8+4YPPDH/7wppNku/p46NChYg8LfXv22WcnXirrifOK07vquUVYu4Rs6AtQwr+PHDmypavUqW3Nftttbly7DbAM6WGRbOItRDblpRNd/QV9Mq58rl1CNaHhoVf/uRCI7R9znZ+c3uJdbZEu9Rh1zSt9j67UtmZPA9pF7tEDfmHSVT/vMZZcndTFWAGci35yHnmfn8JYoLsWO7bP4s0yjGU7tAzAsh3qdbwrY+MFx07CnQpYrGJgUqOsASwCMV1k3Q5g8R4FaGgBi5QPvy1gUZ+0MrQuU40HnhESArCUgi/q7QuwWPCkM1TUT353ARbokFPadpXfxZsALF0UOrmil7xbwGJ56AGLZFOABTANv0qPaRgasORGngMsp5xyyqb5oX4BLBjbEIAFQ+y9CAKMyP2sgIWx2DCzbQMAtqxGvg2wCNh58Kl7rbqle3lLBGAZmDcYc+VI5JpSQtUiFNEsQ2c81pDrkC0Ay4MPPlh0MBnt1tzWbENC7BLyuRs2Cdcm0UJ3hYRUhzX+9j0mt+LygBV+asIoNduap23TR6nw5JQkfeTmZX9wnOeHTdKTQbXepy6+7zbAMlRIyCZx25NuLWBRiEV8wJDrIDlkE8CSWxF38ajP720+BLKUOxPIh8CUmOq9mqXAa5b+qy2BFJvM3BZyn9aODLryvnILmSHHU0ID8cbqLe+Rs94X5RjZ+/b07qLHUjLerjIBWLoo1MP3CjVoglGlFEMP1c+1Chlb76IcModFA8wdzsV3lq7euzAtT8CCRbsaGTqHReOxCljeFCVkUsbGoPmb72zSrQ/TIVO5kE+Np4h2A7DUT6k22bTyKU+K8taQTS4aXbanbY4LKPA750HJhZP6HFsuLKL6Z1n4CQy0jUV6us8xbKcu219PawtscsBkaN5sZ1w17wZgqaFWZdncJNKq7JFHHmne+MY3polvVziVTSykuPUGyRj+wz/8Q9pyW4riee/cc8/dEjtuGxA0Iu/jscceS0X8BPTuUdXzla98pbn66qtb6ZTzbP3+7/9+upSuxq1NG7TV9dgV7J133tm87GUvS8DEt5XzwrAyf/TRRzedQ+PDY2pfyv2pp55qXv/6109yWEo8LbsNsHCT8tAeTGT/s5/9bBf7NyV6confH//xH2dBZltFyNk0ee7sQEsBv+Uf3USSe45u3ttCldwg/oUvfCGFZbRTZda+5N6TR+fuu+9u3vnOd068vDkQ4xctufps2Eff27F+5jOfaX791399co1Gn2OprcvqAngCb9rAVI43jAPZHDopunZcs5QPwDIL1QrfsUbVZuLzumLe2u1SMskKmx2smCa0XKd20tx3333NeeedVwxYajppaUTb1rjnVoOiO78J1Vx++eVTk/GsK5h+XXvttekHt2rpQ67M5z//+aLiClt95zvfSd6MnBs+tyLyoR7R35YVPQRMCIe8+MUvnoCcEjnbbYCliCmVhbwhx8NIUnjbzhVvWPn3HXfckWSz61wh27UPfvCDzXXXXVfZ2+7itn/8TegVHZWTMesp0gIFzx86gN8KQXS3Wl5COoA5duWVV04WeWpLXqsS+bYARWOR90gHSRKqwwO2DJ5wO7/hiQ7PzOXzWHpoLIyD8SzDWMo5ni8ZgGW7FCx4H4HDkGi7IJOLHTKve93rUrLoTng0ETR57EqdiSHAMsRKVmEOxf+V30Ffctv1LDgEsKDgvELzngnroRFgqfGw1AAW+E2i39e//vUJyKM//rCunFzkVlC2nD9XgnwXvDjKjSmRtQAs3VTy8wHAcu+9924KT9pcEGsQqR15w/heccUVVR6WoQCLHTF95dRedFTbgy5TPhu0eOELX9h885vfTJdzDvUg24C8q666KrUtsAGda0Cf75/y8KQj+Pe//Mu/pPy3RecX+b4CWHSico7OWgyJN+gwxsF4ljV5uEZeArDUUGuGsjmXJdVMi3nP0MzcXvH5EPo3EwlDt0wPtMcoXHrppVkPS9tYWMFiGGqeWsBC3TmatclLV1/a3mMLNKvemicASw21Rvlo0Iyk87YQSu5zZBO5qXnmBVish8X3LxeGPPPMM5NOKzmmoGa8vqxo1jZ3a+tuq6cmib62ze2Utx6WHF/4zHvLluW8n+2MW+8GYOmDilPqCMAyMIE7aB+AJQDL0BIYgKVpArAMLWWj+gOwjCISV1546soKf9x875ENfl9xwSnz4cAubyUAy+IYHB6WJh0yFx6WYWUwAEsAlmEl7GTtAVgCsAwqawFYBiXv1MoDsARgmYf0BWAJwDIPOQsPS9NESGhgSQvAMjCBIySUKBA5LIuTswAsAVjmJX3hYQkPy6CyFoBlUPKGh2VMgQAsi5OzACwBWOYlfQFYArAMKmsBWAYlbwCWACyLE7BxywFYArDMSwgDsARgGVTWArAMSt4ALAFYFidgAVgm27hjl9B8xDAASwCWQSUtAMug5A3AEoBlcQIWgCUAy5ylLwDLDgIsnAp75MiRKhF53vOeV3UnDJX/7Gc/m3qUe1UHWgo//PDDkzshSuvjxNenn366tHgqx4mqp556atU7tJG7RI9K2g5a+trXvtZwZ8uQD22zkit9AItf/OIXm7e97W1b+q06NB77+/3vf39zzTXXlDaTys3r4Di2Kdc8lK890G+Wg+O4R+btb3/7pGs6Edn+9v3+x3/8x+aSSy7ZMpxpp/lyjwpzp+appVlN3ZoTsxwcB82QzZoHuayVzWnz2bct2r/hDW9ouIE697QdHIcOGPrguC996UvpLiE9JXKGzWg7UbxNn910003V+hndVHvSd41sMtYf/vCHk37ZedImQ/SHOVZyz5WtA5uB7Vi2Zyl3CUkIPbE++tGPNvzUPLMIHpfFtU3WmranleXiPxRWzdOXgvOT3PcBJYqhL5kQeneWyVozdsoCiFCKOSXbpijmBfLmAVjgB0fA1wLqGqUIbWcBLLPQ+fd+7/eau+66aws/LS+9rHJhJHOn5mE8tTSoqb8rh6WtrlloNoshmWU+18oYYxwarNDGb/zGb2wxvl36DJvxsY99rEqfzbLQrV20IZPYmpxseiDF2PmMazZkN0rBESDvHe94R41IJ1BcC4yrGpix8I4CLH/+539efWT6LEcsYxQEWHxIp8aIS8j47evB+OpysVLezXKUd9sx822gkM85yp62asdaOo5Zy7UZ0raxzNrOLO/NC7BwZwsXGg75zAJYavvTJWd9XgHBwXnLCFhqaTZreclmzjOybHO8a4xtx8xP02fXX399g+0Yeqy115PI+wk49Daira/YpmlXQFibI1rOYjfmcQVEF69z3wdgyVAlAEsAltrJFICljmIBWOrotZ3SAVgCsCzjnVWzyHQAlgAsmyjQZUhmEbK+3gkPy0a6FTc8LHWXbIaH5c3JYxoelnTrzGBPeFgGI+2k4gAsAVgCsPQwz8LDUkfELmAcIaE6ek4rHR6W8LCEh6W/+bSlprZ4ZOSw1F9HHzksAwqqqToASx2dA7DU0Ws7pQOwBGAJwLKdGdTxbgCWPIFmSZ4KwDKgoAZgmZm4AVhmJl31iwFYArAEYKmeNuUvBGAJwJKjQOSwRA5LbZ4AchQ5LJHDEruE3lxugJsm7cZlsbtsT+SwRA5L5LD0MCsjJFRHxPCw1NFrO6XDwxIelvCwbGcGRUgoHYIW57DUCVF4WMLDEh6WujlD6QAsAVgCsNTPm+I3FhkSOnbsWPPa1742gYn19fV02NDa2lrrUfWlg1Id7H5YXV1NJ5Z+61vfavbv319aRdqaWCN4tHnttdemH9rkYUw8/Ju/+c0Y+eFvTt+88sorU1t8b3dr6DCjffv2pXL6N2OAbrxP+bZj/YsHINrHkAAAIABJREFU2lKwT8Ai3qrPogVN039+Dhw4UNzlWg8LNIP/5513XqIZP8ePH0+yZk+wFA9E1xe/+MXNk08+mfol3thDpuAN9eh7/g1vqFdj7hpU7cFx1M8jWfZ9lszbdunzZZddNpEzfSdaSAdIXiWz9913X5o7kueusfD9PEJC9OmBBx7YcjT7NDljjNCuRs5KxmvLHD16tPnd3/3dyUGQfemz2n70VX43HRz3k5/8pDn//PMn81kybu2flX/mRpucib68yzvMd/19xx13JBlAFkqfCAmVUmp8Kmzu2OGhdwnBYJT9PAELBqX0iOVawELdf/ZnfzYXwIKB1zh2MmBBBug/kx4DXMqbGsBCnfBmXoBFvBkCsGjOML0ly0MClnvvvTeBvJ0OWLRIQN/UyFmFGk0GC0AUgGX5PCzwBsBywQUXzA2wIAulp/0GYKmYaYvwsEjxojy4YI1Lpngsg2W8SpmeK6/PdCeEVr8lCph7V2ruhABlv/vd725+//d/f0L9EgN89dVXN1/5ylc2ccx7aOwKn78fe+yxdMHYUGCFNvr0sFCfVi+iCb/hx1NPPZXu62Es3uPRJsbwJXcvji8vsEI73AmCHIiWdpXkP9N33AtD/+yT442t60c/+lHr5W+58bz85S8vuudKKzja56K0s846K3kL7PyQ505zSas//i2a+buD1Cf7ubxJ//AP/9C89KUvrQIsOZpVqKNsUesJYoyWZpoDyM40OWO+PP7441VyVtpvyxsuC7z77rsnHlRbRx/e49I+9VFumT0szGfkoOSBP+iY//7f/3tz+PDhTVe3CMzm9EKbnElX2bb1GXoJGRCvS+wXNoCfZXsi6dZxpA0sSQkphFDCSAme3LD+nba2SuouLYNXShnyCgPx7jRF1Xb/knU3+vZxVX7/+98v7dZM5foELFahexA3iyevdkD+YDS9b41cTrFwyq2/ZG6anHFfCSGRoZ82Q8K8yc0Zq2Bz80Dfiwbi0SxylqNZX/Swfc8ZjWlyVusxnbXPArTQUIDRhnRnrXcR7y0zYKmlB/MYnan5LFlqkyMBmNz3ahv+isfydPJdyYK4tv+LKB+AxVHdus0FNHDbyt1dAzJUVt4b6vAxySEFiVX8hz/84fRDu6x+bfuMS8ZEBpTJIMAipSYjqgmjXAv+LYP0qle9qnn44YdTfcqh6Fug+wYsUuDyAtBvPvvQhz7UcGGazQfpeyzeiHtDohW8coxEa4wvN8nKkIs3MuiSVQFsVnEc5y/Zs/zvY0zKZ3rTm97UHDp0KMkXnwlEKZZOW/pMOS02n0rfWxmzoE79v+iii5rvfve7VZ68IQCL1QMalxYE4o0HCuKx5IzcAvJ4hpKzaYsS5c3U5DX0IS/brWO3ABZkG48kIc4XvOAFad5Il8ruSP6tp166ytop6RI8dvAceco904DOdvkyr/cDsIwpjSB4hlrhkAEgZFTiUrNoWIpKCs2u6CWkpcCltG0pUQEWtePDIB6A0bdbbrmlQTHosX1DwTEhbBiCdy688MJkSLSiHEKA+wQs9I+xMA79aEUCYIFuNavQUr5Aq5whkawJgAA2BVpES/5N6M16WMQHJQqLN+IzgIVEXY2lpp8lPBT4QF6QG41DcuCTl63HxP/tFbMFLPxNXQAWVqWS75I+kivgvVIl700rY41Jbkya/9PkDMByxRVXVMlZbb/RV3YB4cHUkPO1tq8l5ZcZsHhPbdt4VA7PpwCLneNWJ+dAi/fOauGljQN2HqmscqVKaGxlt7T8vMoFYDGABSPRlgAHeuUhVl+j9KkTQeI9/1CPclisF2Ma80vblvDK+CKw9l0ZGptzImN68803N6yYvReA948cOdIcPHhwSxcxJFx7XmPka4W8b8DCWDDwWpFIUdxwww3JywLPS4FkqecCGmtXVY6XkhPJm1VkyAj5KKzIvFJBjqD9qaeeuomshITOOeecBM5KZYcKasbNah1DgtxYZQtNGIeXFw+SaU/yKiDiwRqfI8MA44ceemjT7rUuOXriiScGASzqs20/N7Y2ObvzzjsTYKmRs66x2u/pH7SXDrKGzgKXIfPOavpbUnaZAUvpnBGgOOOMMxp2veEBtfJuwbgWub5uL2fWOyM6qgxygAwgC6U6oBR8lfCszzIBWBw1BVokNHLJe9RawgQrVFZ4JJxqq6SuWcvYfAyL1jGaGDErmELqCgnlhNsjfnmlyC3YSSEhmyMhrwD8ALwQDiJL3ub8zEr/tvcEWiQL8u7Y1boFKzLqhDfOPPPMLdV6+ZQRevrpp1MOy1AhIdFIhiQ3f+iLxslvha3sWL3xb5sby5TDYkGWAKTdmi63vcJiXs7wsLC7bCg5y9Wr+ast6NqS3rd8D1XfMgOW2jH7HBa9Lz2kOW3nhuyIlzN4jT5H1iRvHnTkAHZtnxddPgBLCwekTKVk5FZVfL6EcXJjU4cMhoRoVgRbipBlJAht4DFQjNTGrn1oQgpOgCUn4EwKuxNE9JnFkJTQ0Jbp28PiJ7iMjhKVa/pXypdcnRa0yNtj3fj2ewALKzMeu+pSSEi8UX/YUTRL0m2tfGJIbr/99i27HdrOGfFg3ntYkE08D4xH84gyr3nNa5KHhafUMzBESEgA0nohc94VyrXJGUm3b3nLW2rErLqsBbLWq2JDw9uR3eoObfOFZQYspXNG8xbA8p3vfCfNT4WlkXm8rJJt72HxC0aRU7JnF9qSUb/wKWFB6VhK6uqzTAAWQ02LXiVAViBqGW8VgRUAlIVNThxCODQWv0vIKy2VY7yaJHaXUC6vx/cX48p5ArUn99YKcp+AJefJkBHEw0JIaChFLqWT83pYA0N/7AFQ/NsmkFre5MbDZxjrs88+e7CxCOQRQrz11lu3JPzZfvG3jbNL3hQOtWXl4rZzju85g4UcFtGwRIaGTrr1nhSBAZtw7OcM4wOwXH755YPzxvPAgt3SUGYJnedRZpkBS+n4JQt4StGZWlCIT8p5pL4csPc6QfNHi1QBIvvubvCuQI+lByyW6LNsN23bopsTrmmAxSPZEuFsW3HNA7Cof5Zm1qNiTz5lApUCFg/g5OLfiYAlBxSZ9IsELF6uSgGLfc+uthYNWKzSrQUsOYM/iydv0YDFypl4E4ClRINuLbMbAItGVbKtOQDLZhlYOsDi43VMbK1EMSQY4JqnBrCU1tuFVv0YEDq7m0MAobS9WcrlPCz+SH2LxNVH+u5DQnYVZschDwDfs615qHNYpPBz9y/Jy6A+lia+iUd2dexBXs0qfhYedb3j28eAs0tISbdtINrGtzHWlB9qLKrXGxJL16754sGWZNF79ygnwFIznlkBi7w8uVwC+tI1LuUlWcBi83cUEqoZS5fMtH3vFyV2Vc47ytWzYNd6+4bKs6kdTxdgsXpA/CEfDbvhwyuL8i5ZD4s9hwVaeH0m3uToVKvzamm9jOWXDrB4IlnDgpueHzG2hKBDABZrKCwY8Z9bRdW2mudz/ZSMp7SM3IOimSbCtLi/PDDQDBe/wGLXZIFHeFgEWEpzC0rHonKAIrYBWlAC7boMR1s71qBYd6zd1lzbxz7L54yEN765sVtDz71DL3rRi5KMCUT02UeBVu0SEm/ajHxp2xqXDcvxGbuEdM9XaV2lgEUGgDZzu/ZsX2TY/bzukkVrkBQSoo4h5gxjUN0+vOnDBvrellOZRRn2HH+7AIt9R+BQgGXZTvVldxC7hOwCpE2f5cCv5VnpQq10zixruaUELLmVFZ/J+NZMoCEAi8/i9mDAxuStQvPj6lJu2xUa6reAxdYnY6hzZSirSUHypD2HxcZG23ijkJBXjNsdg11hnHvuuZM8GWt8obe/gK+rXSUP+3p4T2G0ZVlVaixtHha+h+458KyQUM2c6aJdTo6sIbHGlz5D69L7cmzysK+HdvGwaFtz6ZhKAYvGZeel98DZfBDK6/BFhVTtjiD6z7hzxkYhIbY1l46jhi8q62XYH1JnvTuU1Vyyxt1+Pksf+nynC7D4vCjNZ3vat4z7UAdcdo1X7ZM8Lw+LwqVaAOjeH/hjDy1FVuBN7qLUrnZ3w/dLB1i8wbNuSYSOsFCNC/W2227bZHz7YJo3DFpt5Vx0VsHJ2NtYvleAXf3LeWpy70hJimZt7VhaqowFLG20tv3gPYWEanjTNVardPmbezRYXduVhbxTUlSlKw1N/FxdAizK8ynt5xDl7Eqev+2OlxLeYKx1zoNATUk/S+VMhlqGxLZheVPKF71vDT/9VV0CLDVgsnSXkJ0jkg8LWMQLSz/vpbN003e2vNVneFguvfTSiferT76IZtJV0jkCLNZ7oj55r5j0mWg/xGKkts4uwGJ5qL/trj/rza5tu4Q/JWVEe06sBrCQfGv7bT1u/G3njrU1pXOqpE87pczSARbvCrYT/FOf+lTzf/7P/6k6t+A973lPujSvryenyFGuv/Ebv9HqRpbSsO7gZ599tvmP//iPqh0CZJNffPHFRUNRW9CMH/94wGG///jHP57ascBMhkSxbv8+l2txqFmNISkaiImvk6TGhVzqi1U+1FWqgDwPvZHFK4cxGWIspWO2BscakmuuuWbL4XDeIFrDyjksXP5nk6y7+sDhc5dccklXsfS9aASQ4KJNr3htJSX8aeONPv/kJz/ZcBge/y71TECz3MGNfoCiG0ad8St3js9FvzYjwXZUf/mlHW9Ob9xzzz1JnmtCFdCZn5rn//7f/5t2l1lPsN9ZovrUZ8aPHHielQLZkv5xoF7JhaG2ri7AkgOTf//3f79FB/Y5jpKx2jLSocjk+973vgmdvT7L1cs7pXOztl87ofzSARaIZl2ymmS4yOSaVDJcCYFZwWB8+nz8JMaQsvLXgV5+9aKVsJ0kIGsUj851KVG+OuuidCx29SeaWpdpbsXYVXeuHh3ypdVo38hftPnBD36QaGbzC3zsv1QReR5aBX7dddelg+Nq5KyLbrN+L9kReAS0AkJ41D8LuGT87HhqDCL1AvC5ZqHkkSdCF/mpXRtqE/gqqY8yljee18wzkq9rwql4mAA5XY9d+WLgPdiyIMnndxCmYsu1f8Q/ymvl7Hfr1eSvIJv8dD3Wo8LhdFYHqk/UYUG59aTAf7/QKwGcXf2y36MDczSbVkcNYOnqS9/j6WpP30ufMY+hseaz5vS0ejQ37WKytN3dUG7pAIs3ojZnwq7yS4nvJ2vpe9PKEZemX+oPRgRFau8rsd4UrdBUJ/9GIZD3UQJU9F7bZM311Z84mvNG8JmAoFeo9NEn3Vre+FhxLk7fB62tAcMoaHWp/mqS157cyYFkuktIIEdjEmCZBdD1NeZcPdCYM1UIceQMozWoGpNCNpLZEnlrO+8m1yfRyN487EEGtFZMvos+vKu8lxwwZZ7RvxreMD9LAIv6RhIku7F84q3VRT6XS8ZXhkSufM0v78UT4FGeS+mJswDpEsBidQ1nveA1tLzvArSiM/XwHj9tl+p18bTtey3aat6vASxKuvVhPc3zvsdTOg4BJe75QpblMfQyIWBJf8U79J9fTOTyCkv7stPKLSVggYi5lbJWDT6uN43oQwAWv2pSLJLfPLkdBpr4cgeiEAAs+rwE7dcAFil0qyjtakqTQ+3K2Pl4qQCD5UeON0rMpXzfHhbxVyBPfbYA1n5WMgntalK00mfXXnttw89Q4yjpn5UXW94bXx+20r9t4rfAZImM0VYNYFE/ASwkkIonakvyXtq25r7kUbIm3rCrAqVd6kmjvlLAIpqx8ACw2L63yYK8XALT1ntiPRnqv8+dquVNDWDRnIQvAizTvG3Sq7yHfiJnTPqsBiCWyvcQgMXm3Xg70pZuUNrfvsuxg+/8889P4TqrvyR3FnQqp0sbD/YSSLF0X0rA4t1d3viWxPo0yEUBFgsE1BebdItCQFgFCEoUeg1gsUy2ffH98t95Q+ATB9t44xP0+p7c1AfNXv3qV0/NVSmho1dktq+M/wMf+ED6qTGKQ4zXGwn+TXjDhiusUdS4LI8sYC3tYy1goQ0Ay2WXXdbKm1K+dPHmgQceSICqhjelgEWgBMDy+OOPT8Il9N0CQNFRIR7eKwEsmuvWINXQhfdrAIvmLnwBsNBWbpeQ+rUbAIs3/F4PehBZOieGKMc8ZrOCDz/6tiR//M4BliHA5BDj7aPOpQMsDMrHp7eDJocALFrFCjhpe5q94yVnwLUVTcYXYa15ZgUsFqlbZStjNg0Ael70yZvSsUsJyShYpaMVo88p6KpbPLShMNW7k0JCMtxdQLSLHvb7GsAiZamQkPc+ygNREooSWJF3JeetmEdICMBC2E0yYsMhdhxWD0g2vRfTzjE7Dz3fSvlTA1hUJ3l8Aiy6dFPf2XljvUDQGePIY+dKaT9Lyg3hYVG703KcxMNFeVA1VxUS4rdAo9dn1h7yng7PtOOryecq4csyl1lKwOIBivew1AhaLWCRwvUKZZpBZAVHuMJfMteGfBGwBx98MB2CVbPC2i5g2a4gto3H5svI6Gy3rdz7VsFZ5Wp3c9TQM9cGCgPvCiGhmlV8zXhFR5tI7t/3AITvKf/zP//zzRNPPJHdvSFDb3lg505pH2sAi+q0OSzWgyAFvF2+0A58JiQ0lIdFYwGw5Fa90+Yz8/+1r33t5Dwg8aBt3PaSS+8lm8anWsBC+7kcFtuGbx9Q861vfSut/v0coD6FtWRkNdZaw1kLWOgLB1recsst6Xyb3OPnjT0nx/e9dD4MVQ4Zw8sOOJ42Pyxwt3OzZAOFv7R3KJ02FI18vUsHWKQUPAq2K5saotfuErJARUJkV0055dIGWCC2EqZ0QJsY0LarYBrjASycK7Ooh7HbHUFSVDX8sH0vNWLiPQqO23qVBEhdJHSypdTuTimhD23zLvxRrF8GXx6Wknr6KKNVOHJmFYzkR656/m3DG3aFn5NVyvtcpZL+ohQB1CWPlOadd97ZvPWtb53cCo5Bpm3dVFzqYZERVFK0ZEu8scmgJf3zNCt5pxSwWAMt42t5pWRPm/A8S06P7XMtYOFdFm133HHH5PwqZMUmqavPkkN++6RbC0LFC7tw9LkjJXTezi4hhbskH/4WefHG6utZ9VTJWGYpQ7Itc40b1TV/pZd8krron/OwqG27APL0maV/y/jO0gEWKWk7GXIgoVT4ajwstk6P1NWf3BbENsAihSXDQf0yjg8//PAkebDUcC+DhyW3ytS4FF7pW9ClDAF5PofFe75KaSklbXmklYwAS+2KsWbcfveb3rVyJ8MgbxLf2RwWH36wHpach6aUNjUeFilGn8OiPjMuS+MSGok3dq6JN9rWzFhKPa2lOSzqWy1goS8YXzwStl/eaFj66+/aLec1gEXyK8ACvXK7+9RnARboD2DVjjw7D+SlEO3tAs/ytkQ/13hYJOvSgTYfUDJm9Y/6bPWV/Yx3SvpYIq+1ZaTPACra1iy6Uhcy4QG+bKAFLL7/bbpZNrVtM0ht/xdZfukAC0TXdjSPjjWhBABKCFcDWHw81xoRuXC1ndm23QZY7M4Z9dkCFuWw2HFNG9MyARZNFikBeCZDM5QisFtHraJktUj7pQZZykpK0BsPQkKAFj4fYpJTr7aMi/d+5S2Db40ef3MvELsLpNgkT7zPD6ssD7ytl6WERjWARfKqi/ykNPWbeVO6ZVd1TQMsGFJtay7lzVCAxRpNZBMw7XMLLHCzvBZfa0NmNYBFsoGXGQ9LKWChHMnNAix2nPJueo+xBct2zNP0WQ1g0S4ZeZlnASx6x3vvS+xIn2UEGsld4RwazmEpBSzTvJ8WsFgvmPQNNBxKN/dJn2l1LR1gsXvn1XFrFPn+tNNOKzZOZMiXHhxHO6effnrDCYwyahJuq2D8HRTTQkK4KhHQgwcPbuID3gJi3px4W4r2mayHDh2al2xk2zl8+HCiUe6BLoy15FRR3i8xnpQTD/BKXXTRRdkzPXK7OKYRSrzGmMIj+/zpn/5p82d/9mdTT5SdlQmMmfbaaCR5kLz4VTpnhKDoZNSVyC1Dklv5Uhd8K5UzlCIGq+TR3MQgXnnlla28KeW1yiFjzzzzzBYZ+fa3v508GW05DLk+DwFYtLCS3NkQrz3jhP6gr5CzNuCGLBDWLHlqAAv1IU+E6gjZ2UfyJXkTINBcIyeH1bwMqW56FzBWOfELeaQuxprziOfGVhsSgk7owM997nObqqMPyIqOlZDOKPXAldC97zLQ78c//nEKcfszgmSDrIdR8x2AQ35RDnwwx+ET4dTcg4yV6ua+x9tXfUsHWBgYgAGitwlcza6hGg/LNPeshMAbN/rblXRrEa6EUOENJYx6F2COwcvgYWHioHhtzohWVKUrq1mEFxpiRAEs0Ir2bQ5HzvNV0o7cyNbjQcItHhaB55J6assoTGK9O96z6FdD9BEPSy4hFDmCJm2GT27mEuBQ62Gh3ywKACyMi7livYazXjInIwlt1X88LOxeoZ3Sg7+GACyW34wV40sCpQ8Zy3jL0PO91Wt2ZV0iQ6WAxXrx5GGhL5KxafMFWt9///3ZKwC6FiXW49c1nhoPi2SBpFvy+MR/AXWdGK42rQfYeiuhiwf1Xf3s+3vJCJ4VAAgLEAsM7XyR3Gg+2W3N6pcdD/SQLlM7Gv8yA7hSGi8lYJEyZxDWKM1iEGsAixUAH/KQos8Bi2mAxbqB7cojt0W3i2nLAFi0orYhGY1raHcj+Qs2T4D27OQsMcZWodkwjA1lzGNbs3Xf2ratu9qHdvh37mh+64WxrmDGWmsQeacWsNCGLvLjbxuD5+9awKLVpNUDkrF5bWvu2iWkeSAA0jafNRbpAS+jpd4IyW0pYBHvqV860M5TG/62fbJ0tgfHabx2HDaHSuPs0mH2+xrAon7ZSzYt7bxesuOXHJWGEGvGMEtZ0Tu3rdnKvh2D3rFz03q3NM/t4jGnY2bp7zK9s3SARUSW4rYKGKU4y6V0pYZMQs8Fa3K7yxjY/vj6SgCLnSy8z1a2v/mbv8lePd8mIEMDgi7BlLKywFFKg0u8SFa0K5hp9eEJ4JLFUle4Ba+ayPz2Rr1rDPZ7C7rs56zi+Cldwde0SVnJlL3ITzJllZDGZ+XtL//yLydhRNVj6SEQJoNE6OT973//oHKmtrwL29KldA5qzJIr/94f/MEfpMTjmtXiEB4Wq6f4G4Dzt3/7t1tuErcyannM+DDYXMwnHVciRzWAhfoAi5/+9KdTW9Nk3xo3yv3hH/5hQ/hR886DGq8X8bp+4hOfmIQES/gNzXin9EGHklfzrne9a9Mrvm/6Up8D2JjPmhuL1qOar4SxkBmlIKjfbXrJ6ztPtzbdAcjRxaQ186aUL/Mst3SAJRfu0WdcE86E9ac1TiMYByaByrsemK3VOpOCfAmt4O27ubDRtBwWa+QlcLTDj7Y7yu3X1Ud71kVX2b6/F0jxHiatsnSUN9+X5BdoS1/pHS+0j3eFczi8EZhFAeXkTEqb71D0Q8R7aYO6oRFyxso8Z7BEV5+MS58IS1olnQv3CCAT18cw2PMoumSjZuVLXbTFHLv11lsnvPHKs6tNa2QU8rPviDfawl4DJocALLZvms8KG1svmRZBtrw+03z2h7lNo1UtYIFe9Mt6V3zfJT92IYKM0S87t3LhHhvewDBihBWmKeV5aTkbls95pqxutt4fS7OadILSfs1SDnlWLlturoiu3ivUNjfteNUffSavlI6kmKW/y/LO0gEWEcYyTEr+xhtvbD7ykY9UrcpLAYvaZYK/7nWvSwfByZWo+GnbqqFkW7OUgt2xoSSoUoO7SMBiBdbSg77z72984xsJUJS6XWsBC+0LsNhVgpS/NRI1k0uxfBlAfyt46Xhq2qQsyuqXfumXiuUst+rKKW2BeRkfvBHccl0DvmYFLBzoZeVb3rac0S6hF7xgPBq7PWsjB2ra6hwasFiwZcG0BwYC81ockah81VVXbUn67guwyDj7Awo9XT0wbBuDLadcGC3I8BgjzySSDvEIjCALACnlEiqXrS2hGXlclqs2crbNA8McqLDhOOwSB45676pskxa/2rUJffAu/cu//EtrMu4Q/BqqzqUELN49qcHLw1JDjFrAQt1a+fK3R7850DLNwzKtr23jbHtnGQCLN5L6d+2BXrMAlrbcilo61sjPkGWRM8CBpek0d/C0vvj39O8zzzyz864SX28tYOH9mlt0h6Rpru55AZa2cbXJ5yzzudbDMgStc+OZZT4P0TdfJ/NAxxSULgzn0a9Z27B5fLmxepsFrxad+zjrWHPvBWDJUGVegKWWkbMouNo2usoHYOmiUPn3AVjKabWdkgFYtkO9re8GYOmXnjW1BWAZbf+/8sJTV1b44+Z7j2zw+4oLTqmhY69l94qHpZZoAVhemY4M9094WE4mH3uPYHhYNl9nUDLnSk+6LalLK97c6n6W+RwellKqj8qFhyU8LHUSM0PpACx5os2i4GYg/9RXwsPSH0XDw9IfLafVFB6WfukcHpZ+6VlTW3hYwsOyRV4iJNQ+hQKw1KiX6WUDsPRHywAs86Flm8cocljmQ/8ALAFYArBUzLUALBXE6igagKU/WgZgmQ8tA7DMj865lgKwBGAJwFIxBwOwVBArAEvaZbfo3RkREupPZgOw9EvL2toCsARgCcBSMWsCsFQQKwBLAJbx0QiRdNvfvKmpKZJuI+m2Rl5mKhtJt3myRdJt7BJqm1BxDku7qgkPy0xquPWlSLrtl541tYWHJTws4WGpmDHhYakgVnhYwsMSHpb+JswMNYWHJTwsM4hNP69wAmfuHI5ptX/qU59Kx5/XPFdfffXk4q+u91ht2Iv82o7v9/W85CUvaT772c92Vb/p+1k8LO95z3safuyjFVKbJ4vxf/WrX910X43e7wuwcGz4l770pXSnUunz5JNPTi5LUz/8b1/XxRdfnC5ZzLnk28aPzPAz9HP33XdPjhjXUfP+DhF7RTz9vemmmxruB2o7gdmOkzKHDx8SEY61AAAgAElEQVTedCldyZiQ57vuuquk6KQMZ5dA62mPlx0uvnvDG96Qvecmd5w/x42/973vbR555JEqufnCF75QVF60YyyPP/74pmsm7PHojLGPvBx21txzzz1VdCZRmxOfh3yQm3e+853Nj370oy06wPNQ/Th48GDDBaj8Ln0effTR5h3veEdp8VQOGfMXJnbps9tvv73hxPOhH/Q5er30efrpp9P4+e2fHJ35DNlEP9fIYMncLO3zosst5Um3fRJFV6vX1Jk7Zt4bCFsfl8udd9552SPQ21z1r3jFK6rB1yyA5brrrksXRvqnzVjz+aWXXppuxc6Br74ASw0/VFZHxrf1ITfpOZb6tttuqwIss1wBUTMe9d/fiWQvb9MdRh6wIGscBscDf3Q5ov5N3VbmuOPl53/+56vuq6kZS21ZCzDhC/yxn2kckk8LDAAsv/iLv9g8+OCDRQBklr7xzrwAS23/5lUe2nNvV9vi0M4/8QeZZH5Cu9JnHldAMJbrr7++YU6XLiZL++/LzXo9yc9+9rPJfBYQaesrgBX57wMwzzrORb4XgCVD/QAsAVhyIK+PiYqiAYzoxmZW7gIlHsDk2gOwyCjYy+10CZwupdO7rOLJ4bCXEvYxjto6ZOSsIvb3fOmyUV0SyFgYl1XO9obrvg2QaKQbri14srypHftOKx+AZTaOBWCZjW41bwVgCcCyiQLhYWnSamwowCJin3rqqSmUKE8CBtGGx2TguZmWMvp57LHHGm5g9g/Gnfe5ldl6zwAslNdt1jXKoe+yjIlxMibGjquem2R1Y60FBbrJ3Hs2tfLvG6xoZctvXWdg6aj+9E2TZawvAMtsXAnAMhvdat4KwBKAJQCLk4GhAQteA3kTbNMHDhxouF5exhjDzr/1YNCfeOKJ5owzzkgfKYSkMBC/lWvBb35+/OMfN69+9asTQFjko9AVfaKfjO2f//mfE2Bh3DyALh7K8mPzWPj72WefbX75l3855aRRdii3OICF/A3An/gkWgtUDdX2InmktgOwzMaFACyz0a3mrQAsAVgCsMwZsHhjjPFTeEddsf/GgMjQA1gUElI98g7YeuSRofzLXvayieEdwjNRonB8SAgAcPPNN6cclly+jjxO+o5+A95+6Zd+KeVWiCYlbdeWAbCQdLtv376JZ0t1CKgEYEl35E5AY+SwNEkuaxKidZ1B5LCUz9AALAFYArDMGbCoObwM8o7IA8JnPPKssMoHvMijAAAhJ8UaC77HwFNXLoflRS96UfJiUK5mV1a5GikvaRNsb7311uRhsY+AiPJ8fA7L+eef3/zgBz9IIIdQUt8P7WN8SVa2ISFP177bXab6wsMyGzcCsMxGt5q3ArAEYAnAMmfAgtEGQPgwjd0l5Ff0GBG+B7Bo66gAD2Vt6ELhIN5h9fZrv/ZrqTqFWmoURF9l/e4l6v30pz/d/Oqv/mpqwoID/i0Pk03Epczll1/e/PCHP0zv4AHp+4En/PzXf/1Xoin94DfAUf20YLHv9pehvgAss3EhAMtsdKt5KwBLAJYALAsALBgF5XXIWGOA5QEBlLz73e9u/sf/+B/NOeeckwwm35FAq1wVDCvlFC7icz4DDNmQxVNPPVWjEwYpqz4KXDF2Eo8BYfyIBgpl8T1jsV4o3uXMiqHCWvJq0Z/TTz99EyCi/9rZtZvDQQJlsa25fhoEYKmnWe0bAVgCsARgmTNgoTkZaWug+fuv/uqv0uFYGOqXvvSlzctf/vKJ4eQdjKoNk8jzonr8mSYCCGqvVkH0Vd4aeQte5K3wOTwq43cJ6XN7/kxffRStoDEAUcCQNgGTucPs+mx7WeoKD8tsnAjAMhvdat4KwDInwKKVixQ3yVm1BwAty8FxGouMDb8ZC2dkDPnshIPj7KFa02hhAQt/c5Ag4OSv//qvE2Cxu1EUmgDEkLchwGITUy3w8YBAp+gO5Zko4XkOsNjPcoDFJxULUGh7dN/jEUCBxnh/1J4Ai22vxsviw12WXtO+K6HrEGVKAIvXZySCs3tL+VUl/VqWg+P8nC2dw36MtYBFB46SfOvp2SbbcXDcEt4lVCLspWVqT7rFGNx3333J+Eop+e2V/hApjoxn6yi/cw/1KIlQypaTcb/+9a9PYuMl46kFLLR57bXXph/1Wedx+J0qap/vyROgrbazOxS6sKEMxgINtKujZDy1ZQBFF1xwwaZ+aaVteaV6+Qz+Hzp0aC4n3dKeQIXAnAUV/tRaymAYX/ziFzf/83/+z+aP/uiPJueoUNbSmbI+AXUZjV0tT5epvJ0b6pf18NidSVbOvRfIv6OkaMmCEqQpBzhSfsyy0AI6kNw87UoTZFOJ4Mg9ocpvfOMbSZZLn3kCFk67bdNnzFnlKtF3e7xALq+sbXw1gAXec6YSu96U4M1nomtbGwFYArBskg0EBsCi7Wk5F7tWXkoktNvTBEh0SqeSBtWIVtbnnntu2gZHudJkyFrAwlgEWGRAvXIVsldOBf8WyMsBLb/LRBOasTAmrUZLlVZpOfonwCKeqM9eEdmVOdtmdY8IfRd//IrG9mOWc1gsIETh2R0s/jwVtQV//vf//t/NNddck4yW8jkEvrzXQX22gCxAS6kElZfLARcfDmqjuzxdtOYXCZJbPle+jIzlkEC/ZOQ2D4ry9kRh+it9ZkGbQDS/OR0YAELuT6k+GxKw2LnDIZDMafFE/G1LcmeMOhuoZidaKWCRDiUfCzujvCyrx/xWf/EwAMsuByxcsFV7aBYXUvGefdpW8AIvXMimg69yLkZ/8BSTmjteah4OzfIXf3W9zyV+f/d3f5eKWTe2Nfr6Tp9x2Bg0k4H37knF8wUY+M1Yhla65HT4CyNt7oZ30/MdHoyzzz4727c2ozMLYBEfBJa0jViA1QJfedu4lI+7cdhGK9rJkFGPDRsJrHgaU15bobtkIb6fTgF/8WSutOa493aprF2giH8CO14+uWCSSwb19B3iquW3+kc/2CUlY50Lkcj7Z73NnPdTEyqD3mxRr3nsAsS+1zaXaYOdciwq7RwUrdt4A1/gTw1PCOnW6EDq1o436THphjaaBGDZ5YClZjIIfOAO1eFUfmL649NVv53U3gNg/23LaZKVToq2ydo2Ribjhz70oXT5l00c1EpDyteOwQIb3z+5LK1S9mOTYa2le0l5wmgPPPDAJBlSgEmrKassLU29MrOKOadgtwNYVJ/fAWT7A4jiZts/+ZM/mRwCJ2+dDRtBEwzHM888k055BQSxK8iu4lFw3otXQssos5UC4hFzHn5Ab37wfp122mnpM3vvU877mgMslvcCtLyLx/Qtb3nL5FTfZeCJ5HeaPtMY7LyyC4chdUApYBHN9duOywJE+z1l5GmCL/DHemv74o/XP57WCh3m7EIAlgAsm+SQFetFF100ASxaKatQzuvgvScSQIEEBDDnWqScnfxdE6IWsDCWD3/4w+mHvjAW63a0x5trclg3qY21SyGhvHMeKxlcq9S7xlPzPfWSI/Od73wn0Qw+WEClFW9OiXoFq74O4WFhTAIRUtyKS9MP/sYb9dWvfjW50S1Q0eoMHiEv/Nx7773p7BVAC+XxxvC9fvgMMFMKemtovtfKiheSe0AKAJEwxwte8ILkyZJHQUZH80nvesAiGYA/fGdz2e64446ULyZ5XhS9rcGU/CrvRgsY239kuE0HCKi35Ytsd4xdgMV6TqRfpbvEOz9X7MGL+vuyyy5r4I/CYdvtt33fzvPcvEXHMvcDsGyl+q7fJVSjyOUeBLCQcCaj6IVNK3pNhLY2FDqx8W+7omelffjw4VR9bqXv2cVkJYG05FGbAiz2jhq9L3BSApwUl1bOjfqsVQljoQ1+rJu4pK9dZUQbcmQALPbANL1r8w58vkFb/X0CFhtz9gbA0hvvHcm1733vezfdoKywDvTFff3Nb34zJePhZiehkd0XGFDakQeAeiMk1CU95d9rPsMD6MrcJL+AnyNHjqSE0pe85CVbkmTtKl2GXYaf39QDf33o7s4772ze+ta3JsDZ95wpH/Xo0EEbfpxFn/EO4K5Gn9HHWmDTBVi6xm11A31mIQAg9foXvuBhqUknKOWh+gC94L31uIgmkcOS5+SuByxdApz7HrcbCWF2deGPTM+5/K2QaVXPZ0qyyxkyW09XX2s9LNRnwxvWhe13s1h3qAy5VoO2j0oo9ZPMA5iusczyPQlqhOr8g3GxRlwKwRoSJQ3yLp9rTDmguJ2QkPpm83x06BttvvGNb2z+6Z/+KSlJHsCvDiSjX1/+8peTEuWwOMAK9IZXSsidhW7xTh0FrOeOv+EPOwABLsga4BwvmRIzfe3WCPO+BQNasfMZK3gS3IcIO9SNeJQgLMAmPdGmz/gcD8B29VltHynfBVjswkXXKVg94AGL1Ymaj4wPvsCfrpySWcYgYOPBmvriL0G1bURIaJeHhGo9LAgHHhYAC+9iUBAghF+GzhpEO8klWHaC6DMBAmvYZTxLhZ7JettttxUV12SQh0VjsSt5G09X/7zXwdJPxt2Ohc7YlUUNvYsGYuoHsOBhkUeI9+VhyHlYPKjy4KRPD4vls/VcSQnR1ic/+cmkcP/bf/tvk1WtZIByd999d5IxwAz5OvBKRtHWY+md20lUStcot5kCVobkKVF4CDmTt0XeBM4eyYEWzQF5LnR2jgCA5I4V/KWXXroU4TwLWNp0gJ0/bTqgdv7Xlu8CLJajXg9bnkoPS3+orHS83SlZ2scSL7ntn8pb4CI+eFuifwdgCcAykSEJTi1gaRMuuwKxqyg+z3kougzIPABLbsJbY2xBmz5fVsCSUw5+fH15WGw9HrAoUZPt1fDQruT4G7nj+Pz//M//TDuayJdgBa+zWKx8if76LABL16wp/34aYKEW3Pd4vwAgLGC4VBK3fg4Ii6/yRngPGXwEsJArUWoQy0dSXzLn6fX9sjrLe4Xa8kO6elI79hrAosWA7YMPz+cAC+NU0m1X/7t0zLT32wALfWyzDwFYdjlgqRE4i2IVErKhHSkhOxEQLNz/NneDz+xuD+9d0fs5l+q0/m43JGQ9Kja51o6HVb31JtmxUM4rKutSrVU+tbyxISG7elK4x7t3lQBpt5da70yfHhZdxKedV9CR9gUo+PfnPve55rd/+7c3HUhIGeL+99xzT9oxRI6LwkVe4XZ5jGrpGeWnUyAnH/AT0IJ+IJ/lrLPO2pSLZOe0vK+5ra7UA2C54oorqvM4+uab10M6N0ggZCh9Nss4SgGLTaRljvGjOZrzgNu+oMvhCyGhIXWa11dqa1qIMABLAJaJrEpB6dAkGQy/c0bAxRqQNm+KXMr2jAe5JmsnbA1g0VjIx+CHf/uTU5chdl5CA9GZ4+tJhhYAZEzWzU5dpW5Za4z4W94M/hbNagCl+Mw7frs431199dXNH/zBH6RQD49WdpQl1EAC5m/+5m82Z5xxRuJTMhbrY+qsNM3GyuhvPlqdfLzeNBsk5Rgqbqw2DWXH5XnvxPi9tfUTzdrGetOsrjTHV6hrrVlpVpr9qnj8zqQ+W+9K0xxPDa83q+lnI7V7eGV/6o+aXGOXVJo4pk/0f/wRv+lPAr8nuzn593pzotlojjcrzeqonnEp3qPVE2OijKpfb7iveQ2iqIG11WZjhXJNc3w87tNKhKyijBKjOWCSc3QAmBaU2K3PAi2SD+kU5KT2IMiKLm4pKqDuz5qxxzSU1N9XPSVt5crIy6xcIH7bnJDc374eedKsp9svbuRhqdEBs47JLqiowy8mbb3TAIs8M9KBu9H7Gkm3TspgOse/K7nTKpykItdlRUbG0XpPVJU+t0g+lw2PYRJ4KUHyNYBF2685h4UfCW+tgpp1Evb5nowBgOX+++/ftBU8t3qdpW3RBz7p7BrvXSqtl/fscd/wFqBlLzKkLgwfBw5y1gq5EK95zWtSQqfaXVsdmexk5BLA2PwAHBLGEDhIv8eAxRQ9MQYiqxvrzQqABfCxMoIdfJUAC/hDgAUgYREG3wN8Vik2AisCLM+t7NsCWDaBlcmkGI9jDCLsSATAGOF6s5HaGEGp8cDTXwCREdg5idEoNwYsokMqehKwUHZ0K1B/D/xk9whnAhHCY2u5+Gb1AcbTe1rtqnpowMLckCx5/WJDOCW6J4mACWVP02ezLsimcUjzHB14yy23THSA7RPv58CI6rXhIN+WBSz8retJZtUBXWMRqPCLmzSDxwnQSaQ3LPIfnUCcu4POlsst2mQPbPi+vxkxv5oCsDhaw3jO+1DSrUfYuVivBGtaHJd6vUejZCuh7V4NYNHEtYDF59GUKqr5iWO+JdGVkJAAiwWSbaGdrn7b96TMLGCxCrCrLil0706X8maXCSGfif0ehw1ZpSNrF154YQI0SopOACoDWDDnqa30f4DDGFxMaj5p/ieKegxEACsr4/ePrQA5RqBAgEXAhhZWN8aeHKGk1abhe9q3gOVEghbjZ2X0XuOUbOqtPD7CVwZpaSyj2kcjXAVMJbeKOr/S4DzajKNG409tJmbJ1bOS/uRVAM4pJcyrLIOh0Smt8JVt55rjdqFiT7+Wl0VyNzRg8d5dGUObI5Ezim2ksIawD31WQ3KNxQIW7yX1utrzQ3PU5yrpPTsmAZZaHVAypq5Qm6ezrbMUsHidaENkJX1c1jIBWAxnxGS7rdmfr4FBUQhBRlMuPJ/H4CfQdkMyNYBFE80CFiuEOyUcZPtMOAUD770q01ZO0yaed6FSloktmuVWkdPqg6YkYZLjIOWoFTc3sxLukYFgDNTPhXGs1Mltweht2kq6dtLDInuM98E+I9/DBA80yaq3WpyTvomj48DSBLCMQygqQS20vmLCUiPAQlsj0JKgxLppjw8SeNjqC9rSpRRDsuVGf1MrsGqN/il2pJfHAx2Fh0bPJsCmzo9DaAIsB7q07+ZFbFfpcT9Hl9dxqB/n5HBGiwyercADFn03r5CQn+f+cr2akIcMqQDZdvVZEaFNIcYiwOJ1QC78oW3NPtwjr5eOHvBeB74nh2XaBbC1fc+Vt7xRaMvKi3SFfXcaYLFAx9NjVh3Zxzj7rGPXA5YaLwJMZSIgFA8//PAkH6IrjOInvZ3YdpUjYKMdA9ruKODTxVgm6+23395VLH2vyerPFPF9q6FPUcMVhUrblnLCA+HPYRHILK3Lds/yzU520azr5tRpQ/WeOACLPCx2Bc5JtnhYyF/RBYgn+6KMlZNAwxrrTWOZgJZRmGfymHBRCvmMQ0tgAQGdtbH5P54CMiPMMQEsegkwl7wyo2cClEgU0QeT3waIyNuysqlX43fGrRlvyyhDZi3lpqQklC0NnhzaJNSlLpwkU+qgQkiprmnPDICF+gGm3FLOHVeEK3OPvRvKhi9mBSw5d3/b0BSS8gng1ph16TZfN+2rXrsbTuc6Wa9xF9lrvldbb3rTmyaXmfK+nUu1RtnqDk/XWc5hKeWNAJKOzLAy0hW6L81hUT0CQLm7n6bRv3QsNTzso+yuByxve9vbmi9+8YtFtNJqmEvpMI7WrTaNgZxM+oY3vCFdssXjXY45o4qC+9rXvja5YLBEQBA64uWlD/0AFHFKp++DlOcshr60/WnloBXnkYhmJXUyft0GK2Vl3bklNMy1ozr0m/wE6FajzG+66aZ0KJx9UBbwgPwUwIpXrnz30EMPNT/60Y+aX/mVX9l0EuooJERiCdDBwgjTwsrIu2FzT6znge9sjgseB9UkKMT3I8Ayyh7Rw98jJ8gY5aS8kAxgsV6Q1VF+zMlnlI+SQjsCLBYcpC/0jMASISZSaQlTreTAkOo3+SyKBCWQZaocErCkka2vN//2b/+WDvh71atedZJ2Y5CGPOmkVK2gbThglpAQN3u///3vL5kuqX+09/a3v71Bp+mxQL3G02pBuF+kId/oM+mnvnMlNBaAC/lCyhHTgjAHVuRB/djHPtZ89KMf3UQzTwOvT9i5xxys0QGMn9O4ux7lk5Bs//rXvz6dbO15I/p5L28bYLHj9+EgeI8MTEvm9X2ukbOu8fb5/a4HLDoAqIRomrz2mnC/u0dH08vg8xuBI7/CCp6EIxdH5h3CG+RjJKOSW32WdHhKGXvKowTYtjNr3sc2uzV5PUeztrptmEShFAu0apSubcN7QbR6VN5JjYfl1ltvTe5qhQXlPdNqVJ/Tvs2XIRmXxNvf+q3f2pTjlBTWBhZ7EmcZgZdkkMdhGBnv8YaiLakc48EqOXd9g2DOSsrtGAGWEShh59AoGTfjapCHhZyblbVxSMiEYsZJvCNBHjU4wjAn3R3Km5lgDdfMCHCN4BLeFUBL2v2TASwbK2NYldJiViY7oEYen1ESrnCXAMuaRXRjmmyZc7VelvFg2N1lAYufVx6wqF34Owtg+eAHP9hcd911RdNQc4R8DM4AssbPzqmiygzdJNP2PcJihDblRRxCp/mEWp+XoXlLv2zIyO6UlD5OcnriRPaYBo2PMVBPLjE2RzNrN6bRVHxBB5IvyRUc9pl1l1AusZbPtH2+1JNPX2rkrEZ+tls2AIuh4HYBi7wFCEYpYBliYjOkACzdU2MIwKKdGQAWraoVahSvBViQE5Q8gEXns2z2zp202CObPnaRtAAW7e61W5+T8h7vJtqYClg2TgIWG8aZABZ2Fo0SbCc/CZOcOOk9cYDlZDRHPpBxKGkqYMGTs5aAxz6fwwLQGoMqukXwa+QbUhjrxCiUNK5fO6tWM3k9fQEWVq8c8icPiwcseDcTxBxvv9XKeR6AJZFiYyPteJkXYCEPa6jHzg0LOMRLD1jEi2UDLKIPYeJ5ApaanLwALENJcUe9NR4WIXPyCnC9aSIoVCTFoyaVzIVrDw8LvzWRct2yMV/qx8OiRL2hgItF1T7Ja0EsSc3WeFhsP60LWLSrmYh+zPKUCVSIXrWhMgwC8XVWNDb5GuCIC9sebmdzCNiiCGAhh8Xz52hzfLQLJvkSxtt8U8xnc6KrdsRY4y2rPQIXZIawm2ZUk5JRJzksGxsjD0sy9IShxhafkNMYhKSzTdjWOt6VMwk1rcoLNPKjjEJS+G5OBpg2mhPjasbvOyaMMMhoTKOxjMoR3lkxO46Sx8Qk6ooKI8CCt2ij2SfHDp4Y4bvxiS5beD8BN1MSlccvbXE+ra6kuct1CuSwMP9zXktOx5VeEWiRHhnaw6IVtwCLXUj1MfetJ4DTmQHf3CYuT2UfbXhdK1r6um24Vd9p0YbxBbS0eS7swkU5OLPolFIPi7z2LHABLOwgFM26QlClB8dZL648LNNsk6dnAJY+pbeirhrAorimFzxrYHL5KRyrjsLid1K649hx0ocbG5PcBZ0iy+cSvIqhbLuoNcI2b2PbFc9QwayAJddvayhKgUZf9Wjo3PFESAjlJ3Ai3ksZWdnRychsjX388cdTDpQPGx1ZBWjwn5Jgx1t9N+WB4PnYnJsy6tN4F884VJKAy0baLDzKFRnvNB59DpjZOOmq4PWxG0VRKEBEMhb2jBZaSYDFvDAGHgIv2qg8whEjUDGqaTQW9csCAkVwOPdFW7HpH58zVrW2f2MljWmd3Jnxw1kzAmuTw/Y6PSxjuhbI8aSfqyspz4kTitkhRO6C37kC/3Ubr8CKyszLw8KQuK8IQE1/tO1+Qq/V1eKTdr1H0p6KDWAhvGm37heQc+Yibbtg7ByTHhZg0YJAXi47P9UR6ZJSPWIHUApY9A46kNQAAAt9QjZsAi7lZslh4T27Q0p3VtUQOwBLDbV6LFsDWNRsTvByCF7lce0hePz2j3VXJkU7Vvwk3eZuHu5x6L1XlVtB0oi/j6PEWzQrYOl9UD1VaO8JokpyF6SE+M2/Sb618sDfKHkOjsPDwmPl7NnkmTgZhtEpskePjmIlB/avNSdOjL0aOg13ZQQqVmXYZctBDGb/M8Z2dObLSnPs+Ilm/9pak2w9QMbssBE2Un1ryRtjDlOZJJo06f2VlX2bnDS0mTw6G6MzagUi8KGMoJgA0+i3wk3slj5mwMnJnUzpjfSz78RGs2avweBm9BXk8blmdY38g9XmxPETTbMvnTQzOeUFI7Bvdd/JttLAoVmCY5OyVjTG/q3NOcVN09x1113piH4WIDIwMoj8G6+rBSvyEFrA4hNYp4lkrSFpCwn1JPYj/q2spK3deIyHDAmV9NnraXTTjTfe2Nxwww0TMGDr8flvfiFTA1xqAQv2gkNK2Rrv2/F2I8nn6moKPX7zm9/clKDfppd5B+Bic1hKaEiZWjkrrXe75SKHJUPBZQYsNRNou8Lh32cSaWVj+6HQTE17ABaUvE1Urnl/2cqy3RwPi42ji0Y+h0UrVQEWJd0mo2p2mBwdH+2WPuPgQYz06kpz4vjYwO7DIG80K2M0ARgAbLC5aLJZZx3PyQh2bKxuTDYdbaxj7Edpt8fJuSLJlxXdOCK0sTZOmRkjlrWUM6JdOKNj+XlObJCrMzL0K6kDSgwefU99gJUmHZk/ChNNQNA4zLWaPCWj8vL44BQ5OvYc0e6+cbDp2MlSzQGiWMfWm4bOpbGP5HN1ZUQTurJ+4nja3bS6NgqHJY8PScaTfJyNZj39e7XZMIfUedAtGCO5E4D50pe+lEJCbYAFr6uAKyvoeQMW+isPi/qu0FDi34kTxUn/Mow2KVV1AlRm8bD0rc98nhhz7/rrr09nK2nXUG7x6b3Ps+gXwrt42ksfdB8AxC50c2E7C6KUSpAL79ukW42H3+FhKeXIEpTbbR6Wvid4DYuYOPKm+Iz9mnoou5sBC6sabbvkbxQJB8qJZoqTdwGWExhxjPbGerPBlRAbq83+favN+jgZFYfAsePr6TP7bDpWH7BzYhQmWV/bGJ3ztr7R7Fvbl1wz6WuaSUmhTYNDIuEhsldJch2Dn30roxNxR8BiDDs2aP+5Zm1tXzL4gIBNx/KPmz6+frRZO7B/ssd6tIGZf47OjLGAha9Smsq+pnnOhn/Ge4+OjoNKAIZT6OvR4yLj1GQAACAASURBVM3agbUEUKj16HNHm1MOHBh3dL3Z2DjRHD0BjUZ9HPVem7ZHh+AlQLm61hw7MT5ld3Wl2Tcua+lqt33rtJudAFh0pogMn0JDjI35XOIRTXQbbyZAfvHQKf+L7zgUkfOEakNCfeszjcWGjBQSop/W0IsePtRlPWQ1/ZsFsABA7NEO4o0uoPV9thfA2h2slNPORHsWzjxDj7U2YJby4WHJUG2ZPSyzMLmvd2x8169kUHxaQZa0t9tCQocOHZrksAjYaWWNYiGXAdCiHAbR0m5rllFIxhxXyeETTbN/zd52mEIqzx3F99I0a9ysvX6sWcMYJy/Mye3GMqjJ7o69F+ywwcvRpFDKmjn2fqNZx8Mw3h6tzTknk1nBDyvNgYRTxqm9E5eI2Te0gZfi5KYhGz9Zb/CNjDJb+G+EHEZej1HDo3pW1kd5NrhznttHGGm05Xr/2Et0FG8KuTgbK83+o6vN6v7V5gTYK4GnpjkNoIVT6QRn4Bxv9h040CTAxL06m8I9o1OEaVUr7yaFhDY/o5NkRsZ6JPPjhOBxsRrAInlQTpOSbocICdFfJYALsMgzsgncroySh0ueXJhC8sz5KwAWnZNkjX5J3X2XsUmn1sPiQ0CEaQW+7PxTf3z5af0sDQkJaGizBgcQil9qz24712fQv83DYsNC+lugTXJWc0xDhIT6lsjC+sLDUkiowmIcqIRSyj3yJnBia9ejhLPdEhJS0i3jRgHqYksZA5tQK8XY5WFpjloqjl0d+0dnj4yeEXjYdDR/whR4FsZGaOx5GF0eiPHdaPYBCrDu8oicONY0B05pmhPHm4bwztpqs378WLNBDkhySqykXJHm+LFmbXXfKA8lRWGSu6Y5diz5aJp9+0eH4CdMhLfi+Oh+5XQV4WjLzwjwjHNGJkk1CQiANMYXFgFe0qBONM3q+K5pxapS6IqwE+6gVVBbc3zsDWI4a0dVP22dwIXQNKefalDUyJDjFVLCDvQaGbh9k3LQzx7fspF2Lk0CbZN9R12AhdWzDQlp2/u8Vr4A5be+9a3pNnD7AJ55+L4UXEAjDDzeQ10/oTrxrHz7299uzjnnnGKPTQ4gdOmNru/9Qory9vZ1u1OIcetcrSS35jJb6bAa+rBLqiQkRDvQ8tFHH023fXsdeNppp6XDPgWk7RUI1M8iJ83+8UW84h88gTfwyD7wHhnQjrUuGvJ9AJYSKg1QZrcBlgFIVFxlUuIbIxe6YvE2NGQnfVelu9XDYsM9GEZl/aMAa0NC6Wj6EV5Iz8gRIb/HerNB/sHGiWYf4GS8+h8lsYy2I6fdQOOftD9nfZQweyrG+uixkxmwgIHnnmsaknnXAAE0iJviaLNx+mlNgweHzykHYBl3i4Po1lbWm2MnTqRcmNW1/akI4CYl0NIeIOjwUyMwtH4cJDMGLMqwHee9jPYfjQ/HU4iLM14of3LDdAJZKU8GwLLSNKccaDZOP4WTwpoVGv3p4TEtAC6MZ63ZOO2UZgUwpQMaiaklwDJ+xt6pUVrwiOApJdjc5ZS+SXhrNPq1RKOm6QIsyDlzBaODbMwTsNhtzayybQ6aht61jdbPY3mH+NyGXdjOPOS25i590vY9fdTt69ZDLF2lKwX0vg0TqUwpjWo9LIDZ888/PwEW6VYfnvJ9locltyPN7iiyR2jAe7a2i/8ltAzAUkKlAcoEYOmPqJo89rRfn8tSGg/fzYAl2baxS15n9bDqqQYs9uA08klWSRDFM4JhX///7H0HnF1Vuf069bbpk5nJTCoE0ish9CJSRR8oNuwVn/UJ+myAoEAQsCDo89lQsYHPigIKCSBICWmEnp6QXqbPraf+f2ufu4fj9SZz72RuGPnfg+PN3Dlnn3322WXt71vf+uA7FhRGvIR1UwhWaCXJE1ypncIfkafZCwi5EVWD4hA8EJR4cHMZ7N24CXZvUoADkcVZBYyohqajj4BZVwuVO3JBqqXabV7dRYATD45Luw3Dk/RBwCKyPfP7XBZ927agf98+eJk0FNeG5tLNQ+uJAlou+EOXVIDMyIOR3BYnD1YCwCKikwVRWMRBCQuLUhND89QjYdbEYTsO9q1ZK9xBIhya2CsSQevcOTDiMSgEIALssCEkCnwZER4MsAhvWJmAhX1AAhYujK8EYOE9SbotBCylLsIHmj3kgigXTgIW7vzpGgqDmpGbfYZXUiFgKSyF45KbigO5xQ6mOltYVrmAhS4hkm4LAUuYCF1Yr4MBFgm2JMlfliNJt+U8SxWwDK+/HfJVrybAwg4oxekOuWHKLEAOnLB1JVwESXelmpZ5HQdpYR6NMqs0qk6/8847ceKJJw7WKaynwHYJkxHDrP+Dcli4QIY0VnzPhuvkYOqaACpuOgM3Z0HzCEdUsSArRjSwkAyKtxB56MJY43kafF8TUvwk0SKbISEGAzt34Jff/ja6n98AP5mBb7vwNKBjzjSc/cF3Y+yMqYhOaAcUE67wkwSAQSXR1rOFRYeAhc6fAKxB1Em1LDidXXj0j3/Ek3ffjfSunYg6NuKOA81zhWotgYCjKMgyGlrR4OUjjnQPiDlukDZA8eHmheB4rg9aeTS4vg69rRn/8ZmPo/XISejp6cavrroRzp5OgdmMiI76ujpc/IMfoqGtTfBZFLorBYE5754SeIXIhmAmH2YlsEyBmJwgP7+sqZcPqjqohSUMWKSFhZ+FHJZyOvJwFhLmUwvnEhJPp5IkHURVlcOhkWO8UB9E5hIqh3TL9iknl1g57RRe6GUuobD6OMuSzyDdt3Ju47V0yxRaMYa6P9u4lFxCspwDzYG8b3gjKAEI68Ucd8xZJDdF4blERMjl32u4rqwX+0A5x3D6WTnlD/fcKum2SMuNVtLtcJQxh9sxCq8L+3fDf5OEMLYZBxMHV6Dv8f/XccYZZ4hdrCQ20gUkd7HcRXHSaG5uHgR1pZBuU8KC8TL2ELCDLhXbRnLffqx7+BGsefARTG3rwJj6RjTXN6D1iKOAcR1AQy0Q0QGTpF2aOxR4ZhS+EQ3CnplZ0LFEWf3bXsIPPv5f8F/YggQpH7SiRHUYk9pxzn9/DK3zZgLjO4BIAg65Jox59shz8WDSRSXCigNLCQOSRPnCJeTA7e3DE9//AZ79819g79iJhG2jxrJhugQs/AFsTUVOVeBotAYF5F/D9VBjezCFn96HrXqCshIEOAfZkbK+AXV8K95w5aVomTIZXbv24s7Lr4fZTcVpF6qhiCzKJ9x2G+ra2qDRt0/AwjaUyEpEYgVuND8ffsWIKbq+hBUmHxUVnPay8q900x3MJcR3zJBV6RLiwni4AQu5ELQiSFdDoQW0UIDtYKM2HDYrz5PAgOXyXuz3pVpZSdKV4eAjPVuEybISLMq8TvJexSwO8rtiytVD1ZHPwmca6ggTasMWnrA7qhAQskxex2cJ56eSwKvYs4TL431kmoih6se/VwFLKa1UgXNeTRaWVxKwhF9NmATGQcHfn3/+eWHeLHdXUoFX/ooUKQFLmK0vllddF4vm6tWr/ymTbSmAJT2o9RZYA0zHCXgamRz6duzEij/chaV3/B9qXAVRX4Wp6DCiUSiMRmquh1lXg4Zx7WiZfoSwMChNzVAbWzBh/HjETJEGURBpk1u34NeXfh7a0xsRy9iIOD4sHdAnj8NrrvscWo6ZDbS0wIuYsBGD6msiSkfQOEQMdKCDQlKv4LoIs4kjeDJuMoXV3/kenvvz3fC270CdZaPeJmCxA10WBbBUBVlTg6uqsGlNgY+I56E+54roIJ88Gc2FLVACAQtl5DRkFQ3a5HE4/bMfQdMRE9C9dx/u/uq3YeztEa4z1VQxbvw4TP6f7yFWXy84Kb4aJLMTxhTuRqlD45Ge40HVNWi6hlg8jkRtPQyCG3Fivkvlw8zFb/nvRjNgkTtu6cKVY5PWPwmchjtYpLxBgPv8f5I7KNUlVEnAIl5RnrMUtrYUsyaxLQgQwiTXe++9V6TaKCSwHqy9SgUssm4sW4KP8IYwbGEp5LAc6LlkvSTBW1p45eZR9oFSXYFVwDLckXGI11UByyE2YMHlhZYW+fuGDRuE2m+pu6uRrdUrX5rsZ2ETrdwVcSILA5ZSXULURBPrYh4MqB6XbBdqOo3eLS9h1e2/xvI7/4D6jIWI68OgvgitAroGNWpCj5iINtQjNrYF0fpa9I9phT15Mi547/tgRPORXK6D5PYtuOOyz0B77jlE01lEbQ+2aiBy5BE45StXYMwx84G2Nvi6DlflXYKDBGDDUaCKhYFaMQ4UoQkThE7D8uAOJPHE//wIz939F1g7diJm20jQqeO4gk8rtF50IKu6cDS6fuia0RFRIOoScx1o5Lv4OWjCmKOKDEsZTUdftAbuuLF4/Wc/gZbxHejcsgX33XAzEt19AiwRkI1tqUfdhW+CGo0L+OcqOhzPh2NKa4kPg5xj24MbiSPW2IhJc+ejcdFCqLGIiJQaTJJNF5XgB5UOWGj2l6D+QBaWclwy5Swk4fDWMIiQro9DGTWFZRQKSpYyD1QasJTyfHL+kqRX+fuSJUuETEE5G7ByAQvLDmeCDs8LB+LUDPVMhfNz2JpTqX42VJ1G8u9Vl1CR1qy6hA7cxQo7vfy9VMLZSHbe0VTWwQALgdyqVauEuJY8SrGwyCghER0kNFIo1W9DSw6gb8MmrPr+bdjw+3vQks4iQXE0j0DDFsohqlS3ZZi1rgkvzra2NqTmzMEXv/9joLY+IMgQsOzcjDs+8ymoL6xGNJUWgMXX44gcMR0nXfllNM8/BugYJ9wmBBfkkzgMZ4aHuMvoF0YfufCsHFS6oEReIpYNOH1JPP7TX+H5++5DdtcuGDZF9RQojg/NonqvwCewtJywori+QUk4xAi60ilEMinodg7RzABMy0FUV5BTNaR0E91t45BtbcVFn/wYWlpbsPfZZ/DAt76FMQNJKNkclJyF5jodLoGNtMwoJpg/OUcqC3yhiptQFKQtIGPWo37CZBz39rej+R1vBWImPEMVbSewFS0TQiTvZavLUBaWQsAitYrCYc2vhoVkOGNxtACWYhaYwlQbpTxfOYCllPJeyXPKAcaHs55VwFIFLGX1typgKd5cFQEseY024goRh6OQVOdSPANd6zfg4Vv/Fy/+6V6M93zEPBeG64AOFdV3oHuBSgqtIXSzED/sP3ISrEWL8KlvfBuINwQPIlxCG/CrSz8Ofe0ziKRSiNC0Y8QRmTIdJ0vA0t4RRAhJwKJQ0o30V/4nYpAEmArCofMKdHTnWDb2rHwKXc89B7e7G5rjQjdVKBSvc3zBd2GIsK04cDVPeJJcVxWqulHXxf7nn0Ny906kN22E29+HRDwKL14DZUwLOl73ejhjWnHUCYuEe2r744/h4ZtvxZj+fpheYJmJGEA/76VHBS/FhQbbU5Dxs1CYb4hVtWx4ZgJ9kQTaps/CWz7/ReCMU5msCa5KmMjUBVpAw5UpBEp0CVUBy4GnlypgKWvqPawnVwHLYW3ul29WdQmNbMNXAcvhAyw+w39JAJX5gMQi6QJ9Pdi7cSP+etvtePGBB9GYs4XrhIt0xM/BcIGIiMSh5cMTXBFGCWXmzYZ++ul49+cuB2J1gV/DtjCwdSN++amPILr+BURp1XBc2HocsWlzcfKVV6B5/gKgdWwgNEdVWSFAF5BhScINxOGC2B0RgUO3USAPG4jb9fcL1Vk4OSiuBdBtJHguwq+UF4ILsgQJ8ivDroWkr4M9d92NvStX4tm7/4x4NgvLMBBtb0fTrFk4bfH18OvqoEU1dG7ehIdvvgW9f30QY7NZRA0dmq4ileqHaxBaMUIq0G9xPRe65sM0NcFboRhiOl6PzngNWhccg3fc+HVgymT4ZgSe74LhzpoSEMnzWl0w8kFEVQvL8OeXKmAZfttV+soqYKl0Cx+g/CpgGdmGrwKWwwhYhAson9Anr5kS8EMc2MkkurZsQZr6Jtu3I9fTjWxPFzpf4nf74SVT8C0HXs5CJpeBZeWQOOUktJ5/Hs566zvhG/GgbNvGwJYN+Pl/fhiJLWsRy+Zguh4sPYL4rPmBS2jefGBMSwAshL5bXhcFPiwiGIbGwhcBSUGYkBmI8HsUGbRg5LKw9u2CP9AvABKtNIKW4gYJEzWhveKIvNQeo5lIw1ENaM0t2HTXn7F7+XK8eNddaDEi6Od92jvQPGcuzl58PdDcDOQGsGPNU/jD5Veibdte1KXSsF0bOYKliIZ0hGGivCEDf3TEFB9mLgPVD+rN/+81Y/CnTsPYRcfhdV++Cmiog8uIFwHrfJG/SdXIfwnefxWwHPq8UgUsh96GlSqhClgq1bJDlFsFLCPb8FXAcvgAiyvopQFgoWrs4PZeSNi6QI46Klnkdu1Errcbqe4u7N+6Bcnd++GkUvAsC146h3RyAOlMBvWLFqD19FOx4Iwz4SmxgCzr2BjYuAG3X/IB1G7ZgHguJ7gwWTOGmtnzcdKXr0LTvHlAU3MAWATpRCrP+rBpVxGAJUh7FAAWI6CxELA4Fox0P3aufBLW7t1QclmR3ZAWGOrCvAxYXBh011CITvdRV9eI5mMXYeM992L3ihXY8Je/oFkz0Of5MDvGYczcuThn8Q1AcxPc3duwfeVK/P7qr+CIviyitJh4DnKGivYpk9FfFxeAhfmWWH3yfTIvbYGXIaiz4Ks6Os0o6k84Ee3HH49TL/00EIsKwCJzPDNDtqqbQR5JxipVLSyHPLFUAcshN2HFCqgCloo17cELrgKWkW34KmA5fIAli5ywggRpePIJCwVWIAWU5A+RnjiQ06evgvL3OWqrUKsl/0PA0tcn3B5KfQL6mAbUj5+EnK/B5HJMC8uGdbj9fe9F7fZNiFuWCCUeMBNoPGYRTrrySjTNnQM0NAQCazxkPiDhoqK5pEibcGEXVqEc8NJL+OON12PfqlUwBlLQPUcUYfsGfKFtogv1W01VkVYd5KIaps6dizOuvhI7H34Y+1atxJa/3gNtIIUBNYJ4x0S0zJ2Hc278BlATR8/Sv2HXiifxyC9+hbEZT6jp5hIxGBPG4qKP/ye6x08MVPl9B0oujehAH5b/+Gfo3foSMl09Qj+my4xgxsUXY9wJJ2DaGy8EohH45NoIoTxGPLmAGROPxINNzqPqEhr+/FIFLMNvu0pfWQUslW7hA5RfBSwj2/BVwHL4AItwaQQJbAQfJEI+C7f4QvjMD7b5rg3XzgaWAIbcUvBM2BHoZhFs3XwMLoGBDVAwzjCR8VXQ4aFS6fbFF/HT97wbjbu2I2ZZ0KhAGkmg8YQTAw7LnNlAXV1e1j4PWCSZg/6dUMLmANDIxMxBPiLvhedw/403oWvFChi9fcIdQ7+PpZCuS4E2E4rtipDldFSBVWegffo0vPbaa7D1kYexd/VKbLv/XsQdG2m1FtFxE9E0Zx7Ouu56caOV370Fe1etQu+zz6LW9jDgeohOmYQxx83H6Zd/Eeg4Ki8CZwPZAaBzH5Z88lIk122E090Ly3aQrG/CiZ/4CDqOW4QxVCyuiYloq8F0h2x3PSroRDzKUboNhzVXo4ReHj9VwDKyc/NIllYFLCPZmmWUVQUsZTRWCadWAcvhAyx2IFAbwgMe/GwmIOLaObhdXSJXDq0Bg9kORSJEnUl0AvCikSyaBy6qDWhMQqggbeqI2i7UTBYDzz6Ln7z/A2jp3I2oIOsCfYlatBx/Eo7/8uWC4IpEjcAhYgEPkYAp9iYX73xQ0+AiT+6H5mTgrHsR9y2+Dt3LlsHs6oWZywmAZTMhpNB1MUWWZc3T0Gv6SNbpmDx7Ls666ivoXLUce1etwNrf/wY18NCjJmCOn4jm+fNx3o03Anv2YMni67B/zRoYe/fD0A30RSKY+JpTcPTrz8b4150Lp3aisN6I/EXpfmD9i/jdJy+Du20nIpkssrYDq60DZ/33pWhbdCy0ubMBM0+0kbK9AqWQhJsHLNUooRJmi4OfUgUsh9yEFSugClgq1rQHL7gKWEa24auA5fABFuF+yCdiFtIfBCNORqjIDuzZg+eXPoBkZzdqaxJIxOMi/0nDmDGI1TZAj9dCNSJQonGo8ZpAkp4KaTqtHj5ysShMiqul0xhY8zR++sEPoq2nU2idcI0eqG1Ay8kn47jLv4jGmTOAWDwALEIj7uWkOgQsMjO0ACwi948apDLiv60ksHkT7rv2K+h6YhmM7l5EmP/I0GDF4/B0E54ehWIxDFtD0lSQqTEwYepMnPmlK7D/iSewb9VyrLvrN4g7LvoitTDGjUfD3Ll4/ddvwsC6tfj74uvR89zzqE2mYGs60s1NmHHBGzDrogtRs2AOnGgrNI8EX08QdJOPP4o/f/YLUPbsQ9z2kHF9+BMn4swvfA6tC48BptIiIx4g4Ovw06cMnTEojCgTP1ddQsOfX6qAZfhtV+krq4Cl0i18gPIvvvhiLFu2rKy7M+8L8+KEj3DOjMLCmMDrlFNOwcDAwAGzfhZe097eDibMK+fgc/B5yjmYjKyB/IMROMLqlYWS0cXa7GC35PXbt28vub1GoPoVLUL2s2JKt8MVjiM+ofdHYAL+CACTBdJJ7HphLX5/07ew99nn0R6Po6mhQeQq6pg6BY1tHTDr6qFFYtBr6qGPaYNSVw+/JgLUmIjHEnAScWiWBSWVwsCKFfjJJZdgXH8PdJv8EgXphmZ0nH4aFnz+s2iYPh2I0kVSAFioDScSHwZeIDqqSG5VVRH3A5Vcm2w/tG3bcN81V6Pr8Sdg9NLCYkOLm0B7O5BIwI8kAJcxQipypg47HkHL+Mk4+aOfwO6/PyQAy6a7/wDTyorwY619HOrmzMJ/fOMm7F65Ao/fcBOS69aj3nbRzzoefTTmve0tmPvWi0QOJNeoh0ZzlefBt/qx864/4aGrF0Pr6kbc85Ehh+boKTjj8i+hZcH8IG+SyOAYSuTE7NueAU1meS7BwkI12HXr1omcUjJTs3QJsZ+sWbMGl1122WC/LEXd9P3vfz8+8IEPVLQvH67Cd+zYIebNcg7mKho7dmw5lxzw3APNZ/z+5ptvxoIFC8q6D5+Fz1TqwfswWWIpqsClljlS51166aXgz2g7XvXCca90gx8I6Byu3cXVV18tElkVHoU5bw53O1FQa9KkSSJr86vpGEnAEmRYzruFuEBy4UMOSPZj9zPP4Z5rvobcixsQH0hCZy4cxYfFvIS6Iqwrqm7AiNYgUt8IM56ANXUqjAULccH73wMvokOlNkpfH/of/gdu++jHMMHOQrMdEd3TV9uIYy5+B46+5INIHHkEEAsAiwQtYr32XTi8r/AJicxE1I4VIctc65mxGdk0sGk9Hlp8A7qWPQGtp1ukLvTranDKxz+CMTOmA60tQDwR5CWSuiyRGqC5Het+91vsW7kM25bcjZiTQVKJQe8Yj/q5c/D6ry/GjuXLsOKmb2Fg/QbUOA52KAoWvvMdOOLc89Bx6imCe+MJi48r+D5Obxf+ceNN2P27P0PtHRApAvriEdQdtxCvufxytMyeDdTUAVo+NFuosJDLokP3tUBfhk9LRAbg8ccfFwuoTEsRlqznRubYY48FM3KHJdhlf6f0OxVVyxmLHMtf/epXX01DpqxnkW02UvPZgdp+OJb5sh4EEBncuQ4UZrgupz+Ue89/9/OrgKXCb7AKWIo3cBWwULlWEYvZrl27cPLJJ4uGCveXnCvSAglOCL0SAfk2B3R2Ys/Tz+LexTch/czzaHEdRDwXmu/BNlzhsaGSrMiYrKpwdHJZNOSOPRHGa8/B2z/yQbhRExozLff1I/nQI/j1Zz6DMSnqpDhwfAXZlg6c9pEPoeOtb4Y5YXzgUlK47DPBUaBrS5sKgVLgJ5LBQjqIg4LoZw/IpIVL6B/Xfw37Hn8CfncXNN9BfHwHjvvQ+9E4czowaSJgRAQvBy7F3UjE1UBstvLOX2PvM6vQuepRxD0HdrQBSksraqdNwxu+cS12PfUUHrnxG+hbvwkJTUd/exve+bUbUTd7NlSq87ImMQfIZEUIt9XTjTs++kn4T6xCjPmXDAN7oipmvPkiHPPhD6NuylGwEwloQWam/H8ELBoMApZ8omfShKqApcKTZ5Hiq4Dl8Lf5aLpjFbBU+G1UAUsVsAzbJcRFXxBDGBnEzH9sS0cQTfc89wLu+dZ30bn8KbSRturZwmLi6g4MzxUZl0meJchxaHVhWPRZ56PmjW/HmRe/FTA8gDot+zrRc/c9+P1116IxlRTAyNF0JFvG4qIvfgH1Z54Jta0ViJHEq8Hliq2oIhSYxZtCkC0fzSRifVW4TIgoAUs2BWzejAeuWYzOZcug9fZCt22RUbpl3lwYTc1wa2pgCXKxApVaKUKjhWWo2Ln2WeS69kLv3QPddeCa9YiO7UD9rJk4/cZrsY/hzLf8AF2bt4rMujPe/hYc84EPwGwbCyRqIbT5kRTpDJBMI7dpG2775GWIbXwJZt58tTOh4aKrr8CE818Hc2w7rEgUJkyReoCRQoG0nA6K80vAQjxVBSwVnjyrgOXwN/Aov2MVsFT4BVUBSxWwDBewBHl58mJsErAQwezZh31r1+H+H/0M+5avRoNrw3AswLHgIgvVdgRBVfe4+HtwVB++5yH++jeh8a3vxgkXvB7QKDxnwd29G3t/+zvcc/O30JBOi6gkRzPQPaYN7118LeInnQSlqSkALELpleaTgFQjAItQUpO6MIFryHEDwMJ7g4Bl0yYsuXYxup5cDqO3H4ZlC/l9s7UViEZhaQYchZmmyX3xoPA6kmRVDX2du+HnUqjzMlA8Fzm9FvH2cWiaPQsnf+0a7Fm2DA9/78fo3r4TNY1NOPVTHxPAQ2NyR5MRVCbg9gEZC05PH7qXP43bv/wVNO3ugUaAp/jYVx/Bh279BppPPAFqYxMsMwJz0MJCwBJYWAigqoClwhPmEMVXLSyvbPu/0nevApYKv4EqYKkCluECFtfLQSNZQnA7SAINInIwWwiw+AAAIABJREFU0I/+Hbvx7P0PoXvtBvi9PfAyabi5NAZSPfCSfTDTOWgMW3YcWJ4L33cw9oI3Y8Jb34UZJ58QRAtZNrJbt+KlH/wIy37xS9RaGXiqipxhYH9zCz72gx8gIjgdNSIRoAAsFKcjYGHmZgIWEm18Jx9NQ5SiIOf70BU14LBkUsD6DVjytZvQ+eQK6L29SNhMesjzFDiKAosPRbeSiOEOAJCiisQBcK0MNLggX5jZinpcA/Fx4zFm3lycfu0V2PTEk3jgx79Eti+JWYsW4fSPfwz6jKmAYYi2cgmC7F7RCft27sXq3/4Zj//fnzHeVqDQYqN4yLY14EPfuxnmhA74EQIoE6bUsFGDXEysjeKrVQ5LhefLoYqvApahWujV/fcqYKnw+60ClipgKRWwsK/I/kIiq4Nc3g0RuITIeXENCthT/80FktmAo9HbIxRvfSuL7EA3kl3dGNi9B6meXuzbvgPbtm1DZ2cX5px/Pha88SK0kZMS1YWs/8Da9Xjma9/A5iX3owYubE1BmlomEyfgo7f/ApHJk4UVBLopXqTLdMoaExQSsHgwLYIXGf7riszQOZFqUIHu+yKPkEdr0E3fxN7HnoTKMGxyRwgImP2Zz0SyjanCJomXQngekw0qiOoqdAIYurXIP9FN7PV0NE2fhkknnYBTPv9prHzkMWx4fCXq4nV4/UVvA2ZPD3IECAJPPtKHZBhXQW4ggz0btiOSshDp7IcqrFYK/DFx1M+YBr+xHr5hwFVUmHmjkfBPibLySRqlYF5e6rZKuq3wBFpQfBWwHN72Hm13qwKWCr+RKmCpApbhApaMMwBDD/LZ0MXCCJycQA1BbiHV8WCQlcvYZ7pqfBe+68Bnhmbbhee6cOkKyVrwmCOosR5mYxO0qEF/jYgQ6n76OTz+5WvQu2o1EgaQVYAsc+gsWoR33PwtIdJG14qv6UE+IxJuhShM4K3SrEBUl4s6MwsRsNhKYB2hEcdkssMtW/C7627AjieehNbbh5iiiPBpxVVF9DDzIStRYgofmm6I6KZcKsXMQjANZn72kc5YQKIOSvs4HHXCcZh+2qmY8IazsX/3XmhpG4YRRW1rB1DDaKNcYPXxrCDfEjk2FNLTTLhmjai44ijCxcR283Ufak0MrsZUAUy+qPwzYCEgE6xnEoLzynH5MKEqYKnwBFoFLIe3gUf53aqApcIvqApYqoBlOICF1hTLScPIK9UKp4SwutA1wQgg8lN84UURi6hYSLkS0yKRX1ilOApdSq4H39Dgm1qgTEvAsn8/Op96Go9ecS2sdethqg5SKpBNxNH2uvNw7hVXQG9tF4DF042AxCvzCSmB8r9vBwE9wgrh5USQj8MwYp8/BFU5KHu6sOy3/4eutS8CySQMVYFquzDEOYoQm/MNRifxBgZUxYDn2TD0IKmi5/rI2YBZ2ygAVNuMGWibNRM10ychncnCJCFWNaAaUQHrkju2ofOlTejZsQWalYHqKvBiCcRb2jDp+JOg19RBIYAhoZbAhjmGDB0uOSoiN7MaWIBYGtuJHCDhqpJC/YHIHY8qYKnwBFoFLIe3gUf53aqApcIvqApYqoDlYIBl8+bNIqyZolNhlxABi+faQjU2WESDjHsBlyJQRKGSrIgeEopy+UOYYvLJfQSikPmEyGP14GtesNT6Ntxt27Fv1VN45Oqvwdy5S4RMpzTAbqjD3A99CPM/+AGgoRm+UKPN8zoIWOTteK4MvRZ1IXrhIs88RnlFXFpSsjl0r1+LbPd+eLmswFMEWxFPz1uPPNh+RtTPc0z4ngFdV2BEHOEeEoYQV0ck0YDImHYYLc0wmhvhRgFHVaCrRhBhREyRSmP3sifwwsNLsX7Zo4haGRiuDq++Hi3TpuO1H/8ojHET87oydMExJYAjODMiYlmAPR0aPxldleewBFoswSESUjIHUhWwVHj2/Nfiqy6hw97ko+qGVcBS4ddRBSxVwDJcwCIyBQsXT6DP4oiMzVzAGUrswyBQkemDBUahWhuxQhByHKAHDZrgiyh5awGjcFy42QFkXliH3StX4x833oz67n5AsZA1VCitLTjrii+i5dzz4NXUwaerRDWFsj+Xa7poRMoiTUVOCzxCBE+ql4NCrotGgTUfvhNEOQktXGq8ENDwC4OVJdrJk4nFc1iAoMnEIZAI3TlKKp9IiQkWo4G/KlETcGgUH1nTh6cpUOhGIueFIGMgja1/vQdr7r0Lzz20BDW5NGJKDG7zGLTPn4cLv3wl1ClHIk0SsbCTKDBJ+6X7TGjAqFAVPVAf1ege8oSrSritQv8FTKKqhaXC0+e/FF8FLIe7xUfX/aqA5RDeR1hK+2DyyjyP8ty6rouFh2qYFAybPXs2cjnBSqjIQV2Kyy+/XPzw3qyjVNzk74XHwdIPyN0/PykvzmcQS2I+8x2fg98XK7fYw/3/LBwn25JtF7awsJ3+6R2k+9C/cTPMfd2IElBYOUClDkp+r88FmhYPAgNGxZAI6iQFl0X4ikTuIaEeJxIhCsMLo28oQ9vbhe41a9C1eQvWPrEcyNrw6J4xIog3jcFZ73oHtCMmAnXxoCzbCcoSGaFpfcjfGwZc3xZaL+n6GBrnzADGtARJFymH358Btu6AtWk91FQfNDjImEEaRdM2hLtGdfIuLD6XR7MGURBRWjL4ZGCx60KNBMRfySPxDBUp1nf+fGi8Z7wOyDl48ee/xLYH7sPeJx9DTbIf/VoCxoSJGLvwWJx55dXAERPgM9N1/hAGKs+Cq5Kfw9srVLsRR+Ag8mHQGsR6Ss8QPUoADpZLiKk6jjnmGEF65riT751jhPPBaaedJpRuyzkqrXQr57HCua2UtAHlPMdwzuV8xja79957B+czzkP8KXXeKXZfvhuORf6IjYHj4Pzzz8cjjzwCyyJJqzJHU1MTNm7ciMbGxsEbSKXkwvm11LWmMjUdPaVWAcsw3wU7FAe3HOC2bQ8OIlkkJyUOgrBcO7/j75zEjjzySPF3ljXSE4KcFCnNf9VVV4ny5YAUEzFdDl4gqx5eQPm3g4Ea+dyDk72igM9OsCKfgf8e6vj/GbAEa26gdHsgl5BKkNDfiT9++1YMPL8W2LEXTcQfdgY+I1v4/sjb0HRhqQi4oMx3k6GBAxpBCS0CQtMt+LfNAGESShUXUTsLtb8XXjKF7L5uGPxej8HyVViajvjEcXBrEnB0WmsCHRczb7khbmEOIYU3yvhwIzpypgKroxHv/sLnEJk6DQoBiwO4KRvP3XEnNi5dCmvfbui+jZzuCg6r4RpQPRUqo6JpFxKBPQRWRqDw62fgqzY8xRc6LYzeoUVEBD6LkGUdekc7Tnnv+4S7Rx83Hsi4eOaHP8TOhx5A56onUZ9KozcWgzpuEtqOOQZnX34FMHEyLF0X2EsYUgQmcmiMEk0lyh4ELIGRhyq3ik0QmKey5LHTUIBl0aJF4h3LMcX3zrHJMXLqqaeKxZdqu6UelQIs4XmAdSE44Lge6Xmp1OcsPE9ukmhhefDBB8XcFZ5zRARdPmdTqfeQ58uxyOvknP3a174WDz/8sJgf+V0lDgKWTZs2DUrzF6b1kPcMp3vgd3wv5fSZStT9lSrzVQ9YmGCsEvlqwjthDhzmDGFirrCl5WCAZd++fSKRobRQSER9sI7A5+DzlHJwUuQkyWRp73vf+wYXyGI7qDD44L9p+WF+i2K7lgMBllWrViGbzQ4Co6HqmMlkcMstt4Cfr4ZD9rNycwkdELBwJe3bjds+/yV0P/Uc/G070eISTOag5sOKbS6l1Blh/h3fFYkHSSJV6UERBgQClpf1Q0gqFSG7cBDxbcR8F5rjQs1kEVFVmEYCOUqneEA6ZsLVDVh0QTHrsu8hQsua6wriL/VTmORQzQC5qI5MRIU7qQ2X3fwNRGbOgmKYwhrhDFhY9r8/xDN/ugvWzu2IeBYsPcgIbbhaAFjIExYcEaIBIgEDukrHFgOkrQCw6Cps7qRFKLQq7p9TdJiTJuCCSz+DcfPmQZ84EUhZWPGd72LPI39H79NPoTGbRXc8Cn3CRLQtOAZnXn4lMH4icpoRJJRU8h4qRljR0EMLy8u0H9E1g4gnVUQWDVpYSgAs6XQaH/7wh7F79+7BRU+CeY6tiRMn4p3vfKdYfEoFBrTIPPTQQyM+ZArnhdWrVyOZTJZcr+FUiPPlCSecMOSlcmPINpo3bx6+/e1vD4KT8Dw8UoCF74iJ/55++unBjd2QlSzzBD5TLBbDpz/96cF1o5gVpfA7ttnChQurgGVqNLAz378+K/ZqZx+dt3mW+SJG2+mVTGIlB3ldXZ1IYlVDgS165/Muk/CuRe4IJDDhtRKslNpmRPx8nlKPg4ETWcdipl9OitzJyAkgDFLkcxTWYfLkyaINSj0OlPir1OtH23mynx0KYAmDVmFx6NuC337mixh4ei2UHfsQ700joniIRqJiUU26Odiej7hJNdcAVAjThO8gy7BmeoC4MDM3D8mxHsXcaMHIwdayiOqUYvNh2g50uoMUapDoIsqHcm2UWAn6B90iCnTNE5YWWU9Di0C3dSSp3RJRYU8Zh4/e+nVg2tQgmSEtOp1JrLrtdqz7/Z/gbNuGOEOOVUvkPdI8Nc8XphqvK/giZJTAM8Wz6LDgiDAkQDUMZF0LhhqBp+iwFQ0DigF7XBvefOVVGHfMAqCjA+jqx/2Lr0HPihWwN2/EGNvB7qiG2qOOwthjj8Upl18OtLfBUiJBaibPR5TWKJmxMa/bG2RD4sFwbXJ08qRe2fHyRsSDWVjYdnKzJLM0JxIJsZHg2KLL4XWve90/uWqH6te0sNBqWqlDWhs4nmXmYbnxKmVTVU69mPx069at5VwizpUWaTm/yjlpOFmPpbtezsdyrit3bi77IShk2NcHtnNvb++gtV4+S6FVRz4bQS7bLAzOCi0ww6nLv8s1r3oLSyUBi3zJ0rTX0NDwL++dkxM7FE2sxY6wFWaoTlMuYJGDTnb2cMeWrqnCnR0n1qVLlwrAUjgByMlM+nxZX1n/KVOmYPv27QKEFctMW/hsVcDyry6hsGuQjg9153P47ZXXov/5jcDuTsT6MoiTPOt6sOEiozhIJGKwM9lAIw2K2HlZroOcS4uBCkOPBiouLlDjaqhxVHiqg4yShodcYDmhfcMD+m0fWjQBLRJDP/36DGXOh00zzNhT8oG/dGflF/uIUotshKDFx8DYOvzXrd+EccwxQDTOEBu4vWksv+1nWPuHP8Hbtg0J24LqW4LLIsjAtKswhFt1hCXFo5qsy9SDpN96UF1LcEh0XUPWtuB5tK7osDUT6ZoGJFtbccEVX8C4BfNgtLUBfUn83yc/jfSLz0Lfv1cAll2mi9Z589F+3LFYeNllQHMTEKmF66uCs0xXF/8XhC4HR6B8k48YH/zu5V4saUSlABaOI1pU+MN5QI6rcscz715pwCLH9FFHHTUsMDHUHBb+ezmA5WDWE85L5NBFKXBYxiGvK7SMh4so12pT6u15766uLkydOhU9PT1ik8sfOS/zs3BuZr8hgZ+8l+GAs1LrNprPe9UDFumLHMmXELaWsFNx8SXqpaWFv0sSmOx8Ye5IuBNykNEsWOrBCe6MM84o6XQOwgMRelkfDm6arMXknLf2SFRPkzMBi9x9hF1DdOHE4/F/qcP06dOFPzYMZg5WUbYZ3SGFqdVLerhReBLfC9/PoVpYBk3ctGr0b8Ovvnwddj79Avq37UEk66JGJ+GZeXd8eIYP17ERVVWx+NPNovm6iCZySfAOBFfgWa4AM43pHBozObiOBYN4gmHTBAOGgSTBQGMjUnQHuQzUiQi+i0JhNd8TSQ9dnbwBBarQWWEUkIe0pQPxKBxThzauBZfdsBiJWfNEaLPv+vAtF0t+8GM8+6c/ILedLiHhUAoyUHusFW03GlyN0Ti0sgTRThHbRYPlIZ7LiaSHUddGIhFHLusId07GjGC3HgemTMHZl34S4+fMQn1HO9DTi5+9972wNq5HrL8PtbaFvoiKmaeejLbjF2HiRz4E1NcDRq1INUD/mWU7MEwmOwy4CrJuNK3k5VgGP2UIOWvNYyjA0t3dPWjyZ9+QxHR+SsAS5mIM1bXJR+PPSB6Szxbm5HFhJM9Ozg2SNDyS9yVgYfBBKQfrQZczD4K+QqtCmMNSymIu57Zw24e5fJJsy3myVHddKc/Bc6SliqRsAhYCF3lvWYZ0HUrAJOdm2WZyneH5PLeUZy61fqP5vFc9YJELyUi+BHaWsLuHlhUOPLn4FgIa3ruQ8MrvOAnI6J1S6lfOjkx2eNmxwwupnDjlJCQnKmkOJamNgEUOLjmowwBGDhA5oI4++mjRBqWajSXIe7UAlpF2CQk3TGofnrn3fvTv2o9Mbwq65cFgGC93X7QGmApcKwuTYbgkrAoFVxo2dHh6Pj+PABaBKm5s6zboGzdh0+b1ZO4JgCCk6U0DA6qKOWefBaV5DCy6c0wTrsNQ3kDnhfwOV3WCdD8yrw4JgD7DmBURWaM21uGkN70J5tgO2kaEy4XquBv//jD2rnkKbncnNIY20/Xjk1tD20Y+kaJQyqVAGxm4LnTbQyxtwV2/Gbk9e9C5eQNiqgKLz1lbLwTt6k55LZT2DhzxhrNQN74dsVgU2LAJt33ow3B3bkOdlUHCcZDRFByxcAGaZ89A+4Wvh0XA0tCGaHMrIo1NcIlKCAQFvThwBuluoCWTj+QORPKCcCIxLkSOpxIAC3fP3DzIKBR+csxznHA8n3322WUtiHQHVcIlFA4i4DhnQIB08VaKeFqOhUXOPXKBLnRlD8eVE3YtsdxCPkylwIC8T39/v2hngloBlGk9LYjClGuNnFfpQuJGLwx8SglyKGV9+Xc451UPWCrlEgoDFoalsRNJl1Ch64WdToY0FyLh8EQxVIcpB7CwLDkxyvoUEmblIA0DFj7XAw88MOgSktdK4COfW37KcG0OJLkjKwW0VF1CgUuIII/CcSeffHKBcByg5PqAvgEihUC3hIq19EUwnw8XTmZcpn6JYIsy5Jbhx9Q5MQMlWy63FJZzXXhdvcj94zH0P/QQVi5fAXsgBZfUFl1DriYBbVw7LvzspUgcOQVoag6sDza1UBjKTB4sy7cDmXvWhcxeRgJx4RYh7p4oS2ttE/cnCCD9Raja93QD/T1ANi0ySg+q8YImfC78MqqMJ/PvdqBIN2Ch+/6l2P/MM3h26RLolgXP1BBpbUfj1Bk46fJrgLp64Mh2IG4C6RSsv/8dv/zc54HOvajzXMT47FBRP2Ec4mNbUTt7GgYaG2FOPAptc+ehbeZsIB5HbjDKmWRfJnXUA8AiI8gJWESbBlYYTQkie4aysBQCFmlh4WaB4/ncc88tKwqlUi6h8DzEf9MlJK0fMpJxqPmp3L+XA1iK8TSki5r3HW7kjLwuDFbCz1EJfkgYsEgOiwQsct4OW7Rk+3O+4Pm0ZEurmNwMl9v2/67nv+oBSyUsLLKTSDOeJN2GLSxyQS/GHwmb/8ox5ZXjEirskIVWFIIZDlb5vRwArJsk3UoUHyag0VRKk2zhDocm5HJJt2Gr1L/rAJL1Hq5LKAxYCnd5cFJ58bdgnfQZEh+hqJr4JS+2pgMWF9HA/SNicgVfKg8ueF5/H3qXLcPOP92N3ffcj1R/ClGoSPoKMoYGe/xYHPv2izD93e+B0dRApBuACKFcm0/8R9OKEH7TAN0IkiEqvHcmyOQscgQwakkVQnOO5wf4Ch6ingM3GQAWReha5EGPT3coY4uFtn/QlIYLX6c6LrkrJvb84Y/Yu3Il1tzzF9QzhJ4KuK1tqJ8xG2fceAvQ2ATUsi4+/GQfdt/+czzyP9+B39WFmGNDyaSRMGqQdG1k4aHXUJGpb0Bi+hwce+GFOOYNFwATOpAWIc2BhC9bMmYbLwOWfN5DWn6COHHWtnTAIvkr0nQv+QpyAxK2vg41DugOGmkLi3SnSPcP6xAm0VcSsJTqEgqPjfAiHXbjhAHMUO0Y3qwVbhrDG65y5udS7innVH6SdDtt2jRBuuU9+SNd+dJqEt5s8hpJug2XczgIwqU+W6XPe9UDlkpYWKTpTqLi5uZmrF27FiTfFrOgSDNf4YJULnovx8Ii68jOzM5PcFLskPWVAISkzfvuu08INBWaGg80IbBs+mLLYfxXLSz/amH5l/fj5+DZPnxq3GhGoD9iOzB1LcAHcIQbQyQU5qLPcF+HeEOFSyDhO9BogVmzBj//+jegPf8i6nfsFcut6xuwGLFSV4vowvm44PproZG0SrtMzkF6fyf8XAaKZwnQoeoq1GgcZksbEK+Bb8RguR4iRmDBCVZ6unc0ZGxfhF7rIvrGh9fTiU0PPQh7104YrA8zTTPcGqbI6yyyNotM1UBWdUGs0NbSgvHHLsL2pUuwe9UqvPinPyHm5OBETETaOtAwfTbO/cZ3gNYWuMRnrgN0d+KJr1yNl/7yF6jJfkRdFybzLYH8lMAA5eoqBjQde804jr/gjTjp7W+FdvxC5BIRuMwZJACLipiV10bJg5VALDhwZwXgKiDRH8zCIhelMHdFjkd+ljOeZd+ohIWlcFxzPM+cOVPs5EeavxHu4+VYWAoX6MI6D5ccW3idLFeClkqCgbAWVXhDKS3jsu3lJ+tCF9KLL754SEJ5lQYVlSx/VAKWwoV8uJ2RDTccwFIISAqBRuHvBCrr168XgKWSx3AmOAmqDjTxFAIWDpb7779/SMAiSWAyPJoDiS6hcNscrC0qBVgOBgKL7aTCRMOR6GdyNyp5P/xdSvPLsPcwn+igFhbGAlFUUGiPkKCqQHU9QXgV23/hbxEB0CLwmEHBju0hSp0WWmeyabi7tmHpdddhx+pVqO3sRsNAWmQl7lV1OGNa0Hj00Tjhwx9CyxmvBeK1yHb3oGfrdjzwqzugJQeg21mR0djhXWoTOOsd70L91KnQx7YHwm2KVALNK6qpOnIWQ/aDH4Yvp7dsxgPf+w72P7Uaet8AIi6JwjocyxUAwaDFhhYSDxjQdeTiCUyedjRO+dRHsO3RR7B79WpsvPdeRKw0XFVDpGM8GucswLnf/K4g0DKpI91Xzo6t+NtnP4uB5ctgpLOIuh6iDNduboGbzcLLWfAyGSiROPpitWiYPg3tJx6HhZ//DPymGmQFj0YRiRQjlO4VceHBj+XQcEWCEMEZLUkBYClMfhheSNnfuChxTEmgIq0tPE9aTMuxYFQCsITdvrL+4fFcuMsfqTmuXMBSyn2HAhqF88NIrjWl1C98jgQs5LKE581wf5D/llY4thnpB5LbIoFceB47kHur3PqNxvNHJWApRM/hTlXuyxgOYJGoOnwvORDCSFi+0EIOi+x8I21OHC5gOVjHC3Nxgk3yP3NYCgFImGzLv0nAwrBmuoTCvtVXArDIvlPMGlToxqpEPyucONg+BCwrV65EbW2taJJSAYtHmEAuiAi7DeJpmDQwkLUNAAtF1EiNDZRuA9eRQbdLug/pPTuxacnfsOL734PZ24OadA6xnINsPIruWAxtxx+HsfPnY8F73welrQPwDdj9KfS8tAN3fvVq2Nt3ImqloTHPju/Aicdw2tvfjgmnnIoxxx4LLxaFKngdQfyvWO41U+TkCfLukATsILdhHe694QbsW74cOkmo2cAlJUV4NZWCdLTkKOgzY0glGjBp1nScc82XsH3FYwFgufteRLMpoe5rdoxDw5z5OO9b3w1cQsxCnUoi88IzuPu/Pwdv/VoYmRwMEnehofHkE2Enk7B6+5DatlN4djKxBNDWhsSs6Tj3xuuASW2wTB2eSO6oIeoFwncCsGiAxWzRZt4VJ15iaYCFi5HUYJGf0qXK8cwoxlJBPs+rBGAJjxnOc6wnXUKUKQgviCNtbakEYAnP2YcyBxTOFZVYvA8EWAo3zNJCz88JEyYIS/aB1kTpIitce0Z6LapEe5RS5qgDLAcDJPyb3CWXaqobLmAJL8yFO6DC34tZC8p195Tysg4HYGE9whyWYgherIt5N4AELCTpSQtLKVLWlbKwyHYsRmaWg1mChvBnuP0PpZ9J8384vQEBy/LlywdJ2WFAezALiyOgyMtpDrh2BlL7eYzAUGCq14rsiEF25AhhQl8/Mjs2Y/+6F/HE7T9F+sllqLdzMC2KtflI10SRmtiBBW95i1B/bT3jTECPQcjc2j5Sezvxp6sux87ly1GfTiPCd+3ZsCJRjDv+eEz7jzfgqPNfBzTWw48wP1YesDCsmtwWrvLCf+UDJMpuXI/7b/g6ulYsh9HbDSPVD931oZgMK6b6LuDmUlA1Db1mLQYSjRg/fSrOXXwFdq5+ErufWoW1f7wLiWwGvh6B0T4O9XPm4rybbwVaWgOc1tON3uWP429fvhLm9h3QMjloloeYpuOoD70PfjqN1N692MG8SQM52EYETmMjIkcegfMWfxn6glnwauICsNgugU48YNzmAQs5wIYekIuDo3i25kILCwGLjAySLlapxSIBSykkddk/KwFYwmOGdaEVqFA4rpT5qdxzKgFYwnU4EFG3cI0ptpjLOSzM6yn3+YY6vxTAIsuQbiIJWA5kDZZzXLE1a6j6/Dv8fVQClnAHCr+Y8MsotXFLBSy8pySihsN4w/5DuXgX3rtYEqtS61fOeZUALIX357MvWbJERAkVA4XFJgG+I4Y1E/mXugurBGDhvcOh4qyr3J3w+7BeQeHua6T6mZzgpKAeSXQEc4899tighaV0wDJIRRXBOkKMNdCAEz+WyjBc0j8VqLYLxXZhUD5+3z4svfVm7HpqNVLr12Kiy7xBffA0HZZhoCtu4MRPfARHvvXNiE2YAERr4SgR6CSSZrLwenuwa+nfcOc116B5fxdqbAcJitXpOjJjmjDrjRdgzjvfBhx5BFIt44NIIuq5sDYecxUxookV9IBcBnhpK+5bfB26li2D3teDGpEM1EZGVcH0PI7qQyUvRwP6tDgGIvXomH40LrqHxgPbAAAgAElEQVTmCuxdsxJ7Vq/Gut/8AfWMWjJjUDvGIjFnDs6+9Vagtk5ETVl79mDPfffgr9cvxphUEhp5NC4Q0Q0suPVGNCVq0blhI/76zVtQn3UQ06LoV3zk6mtx/Kf+E0d/+P1Q6+uEdo3g5miJgHQruczCEfQyYNFKBCyFLiFJqiRo+cc//iEsLK80YCm2+BFkS07aUDy4cuaw8LmVACxyoyDHeliYU84Nsg6F4FLOFeF5vtSN8XDaoBTAIsXkZPnhNpPzG+sto1B5XtjNH16/hhtJNZxnq9Q1ow6wyM4iO4ocTGxsOXBkJyylUcqNEpIdhPeS7Plwpwm7hOQ55CbQHSJN/uWw/kt5BnlO2IRcznUHO1eaH+VgZdtKC0vYty3LCLszwuVKEzKfvVSlW06II63DUo7pM2yFkf2MdZdWknL7GaXW2VdYBhcmuUtj2zA3ixQJDIe4H5TDImU/8h4g4WNh8E4+OZ8FytcDEUZ70ZqRdeCs24K//+hHeOmxR2F37UdNNoVaK4sofPSaJpI1tZhyxik44XP/hcjkSVDiCbhGDJ4SEUkA6cJRcllkt67D/33mM4g+vwGx/gHUpLJQNB37dA1jjluAI958AY54x9vRP2YCVArM5YOTfdtDhMJyAlURsGSBrVvx4NduwL7HH4PS1YWoQvCjIj5hHNREAjlThxExYLs2UloMdrwO4ydOwsmXvA+7H30Ue1auwobf/wm1NkROIbWjHbXzZuOc73wbaKgHevvRu249Vv7wB9i19D7UpFNCtM5TNIwZ04IFv/g+auvq0bl2Pe5ffAO07XvR4PqwGCVl6nBmTcXFP/4hjPZWEWHlayYULSosREFeIR+KTr3dQKlFJEPMW76G4rBIFVOS2WXSQ7mYyg2ITFRaypiulA6LBNFyES8W9VfO2CrlWSQfo5RzSz2n3DqG+TlyDgwnsi1nDij33qUAFvncYQ5LsciqYm698OayEhb/Ut/JSJ436gBL4SIZRos/+9nP8POf/3www3EpDcGkdAwbK+WQwOTOO+/E2LFjxSXhjnCgMqjAyER+Ulm2lGtKqU/hORzgTGY40kcYtPDft99+u9hdFfpSw4S2sFmV369YsWIw+WEpVhZO0kx8dihp4Qvbodh958+fj5tvvvlfkjKOdD/jeyEwkQfDv2X4Kj9PPPHEQYtVqRyWwZTBYcCie3A9aot4QtE26tOy4gCdvcht2YYnfvhTbH/kUZjpLDRGhuVSYrG17Bz8I6cgvmABznjvO1B//LHwEwmht6KoJhyHQm70gDBrsge3dxee/8lPsOU3v4f10jbU9CZRY0TQqXjItDah6aRFOO8zl8Kafwp8hjcz67HIPcTFPO85Id/GzgHr1mMpOSzLnoTf0yMsFZHWFix81zvRcPQUuC1joJCHIoAYa6AhEo2hbuJEbPvdH7HvyZXYcs99qHFcpHQV+oR21M2fjbO++TWgJgFs2YY9q9fgrzfdBHPPdujZHBQzAi2RQOuECVh4x08RS9Sgd9MWLPve97HjwYfRnEzDs11h4Um2jcEbv3oVGk87DfqYMQAl3plXyWFG9jzH1jBg5/MKBYAlCMM+GGBJpVK45JJLsHfv3kEQLzc87KsEBeHEpKWMa/axcD8r5ZrhnLNs2bKiStmljO1S78cFm4kMR/oorCPbmOOT34ctJuE5IAw2eN5ll10mkh+WQ4jmutGWj7Qr5ZlKASzh9Y9lUnlXJow8EH2i8Pk5B4YTRpZSt9F6zr8NYGEDfvWrXxWkM8mbKKVRyxlgErBwsSY4kEfYdBjuJNJFRYllns/spjwkKi/n3qU8i0ytXsq55Z4jybIcoNKNFrY2yWcJW2J4D3lOMTfaUHUod0cyVHnh9yX/zTZjqoGDTVY8N1yX4fSzsDowyyKIlYClWAoG2acOamGRWe3/ycJCAizzjDCLsguTbpLeASQ3bkbXmmex4kc/QXrrNtQrmrCYWFYOuYgmLAc1xx6L5te8Bie95U3AuFb4RiRI6+zrQfBLkNmHQc9Augd7l96Pld/5X/S/uB613X2o0wz0Kx564ibis6bhnI/9JxL/8e7AKsGLVQ8Kw+j5b35Bq4+TBdauw5Kv3Yh9Ty4HevuEbyvWMQ6nfvwjGDNzBpSxbUJp1mestlDAzV+rqNhwx++wf/VT2PXwY4h5Pvp1RQCWhgWzcTYBi6kju+pZ7F6xCku++z+oTfVAsW340Si0unocNXcuZv74fxGJRJHasQNrf/NbPPHzn6O1pw+6w9xFQF9dHKf950cw8W1vQZQZnxMJ+J4KjzmT8oLBim7mAUtgTcoHPR8UsJC/ctxxxwkBNu7aZR+U8wb7Jq2ZldzFlzpmis114WtHei5j2bRKMxqpEke4vtIqVSpgYX3Cc2CpLju+5/C6MdRzlQNYCt9P+PnCVn85l4X/Hu5nhVIVQ9VxtP191AEWueAXNiwH9bXXXit+Su1Aw2lsLtgbNmwQu5/wInawcDmafclTkBLLw7lvKdfIjlfKucM9h89JuXCaq4uRZwt3HGHOhoyCOJDmy3DrVOp1kofEekt3jwQs4QEvIyHC/m359+H2szBRWbqX+ElLCwELXV+yD0lwx/oeFLBQQVaClXzUsGCvSERg2fB7uuGsXo1n71+CZ5c+CGP7djR4isjhwzBnK2pij2Fg6qKFmHz+GzDunPMQnzwhWHFVHb5HeX8XuqaJcj0m63Qd6FSc3bEdS75yHfavegrG9t2oy7rwDA19JkOF63Hk8Sdg4de/L8TmmNvI9SzotE7kSbgiTplh0evXYen1N2H/shVQenuhKT7UhmYc99aL0HTEZKiNDVAMQ4AH6rcwHFrJ5ODv7cTKe5egc9MW5LZuQ9TU0K160MeNRcP8OXj9974lODeb7/g99q5cg/VLHkLcGhBunHTEgNLchDe86z1o/sLnA5dZfy8yzz6NWz7xcYzv7EEtRYEVFXscG2NOOQUnf/6/0TxnNtA0Bo7N5I+aAGCBLUVFji4zLfi9VMBy7LHHinccdpPSPcTfqXVEVenRsoiwf0rSbSGni/VlvUfyIGAZaWuRtNjKZ+EYK3SjhQMGivF3+J2cA8tZawo3ukO1VSmARZbBtmddwnOLpCTwU1ImJBiW17FvcQ4kL7GSfJyhnnWk/j4qAUv44cI+RglYJKgZqUYIv1y+cGbD5EAKc1iK1Ul+FxYAkt+VY0os9TkqAViKRdMUEpWLhT4XLr7lDOxSn/dQzpNWOC4KBBOFpNvCsg+1nxUDLLwHy5UWlkLr3FCAJccC/CBxoc5wlcHQZRfI5uDv24u+5Svw0G0/xsCmDfA796JN9eBlcsgpGizdQLquAZgxC2/69H+hbtYcqBMmBuYPUxXWFx6mGQuyFYsK+0JrRMkmgVQf1v/2d4L0uvlvDyK6pwcRRYOaiMKviQF1dZh16y2YsHA+ojWMqmHsL10nquC1CPcSAcu6zbhv8fXY/9gT0Lt7kYCCrOfCb2qEZ5pgQDPDj8l5yfquIBPXGDHUOR5yXT3wbQsRQxFuo06SjDva0DRnFs658VqgqxsPLr4F+9Y8B2XPHtQxkaPqIRWPQp04Hu/5+k1Q5pxIZCLAk71jK/5w5ZegPLEckWQapu0gpevoa2nFaV/4AtqPX4SaObMDQT6COBFGHri4XMrx50V5ZezWwVxCtLAsXLhQuFclYCHZVibW43geDYBFzgF8/aVu0g5lbMprKwFYwvWS1l8ZWVVIug2fKxd6OW9LwFLOWlMJwFI495a6voQt3xKwSOv4SLy7V6qMUQdYCslBElHy+2uuuUa4hSp1SG4Bd0QS+Rci8LB7SNajmIUlzP8YqfpWArAUW7gLLSyF/t1iv1fCZDycdpMTjhzoErDI9xjegYR3HIfaz2SGa9k2Mu0Bn4ETJX3PhRPkUIAlEOb3BGARP1w7bQd+Mon0/i5sfXw5nvzlL+Csex412SRqHRtmOglV8WFH43CZxHDiJBz3uS+gZdFxUBqb4ccT0DQfnkPl40B2X9E1ZHM2jEhEJCsMQJIFpNLIPP8cdtLdctO30ZrMQktZ8Bi1TOtDbQL+pz+K09/8RrSMaweYcNHQkBOAhXqxgGpn4a3fgCXX3YCeJ5Yj2tMHUwAlBVndgJOX9I9YHiJQkdGAjOojqulI5GwoliMk8/0IwNzi/aaO2ITxGDN3Ds669svY8sjjWPPDXyO16SXE+pJCqC4V0dA8awbaTzwe8z7xMaD9qCAHkmvDS3Zj2x2/xPKbb4HW04246yOn6thbV4+p7303Oo4/DtPOPRdIxOD5nmiPQI2fJB1TEJ55UMSXx1CAhS4hmcVcXKdpYpfMdy+tf6OBEFls4xLur5WoYyUAixzT4Q2IBCzhMR5e+AVOD0UU8t+M3qKVuZyjEoCF9w9vfsP8Nznnhp9Z1rdYPyu2dpXzfKPh3FEHWAobNUyMIlg53IAl3PHFtMUJXjDxXj7oCqI0PT+L7aJ55kgs6IcDsHBQn3POOf/kEvp3AizhAc12p7Vo6dKl//TeipHVDrWfFQIWGW3Eex0MsFC1kskPTznlFNGhwq7HfvhCVJ7aKRoVbqkM29Uj3B9dm7Zg0+PLsPWxJ1CTTSOm+EzeDMu1kNNV1Bw1GXUTxmPSSSdh2jsuhi8E1gyhmEsFfV8kLBQdWkj/ZywbumkKwq3i+zCYNTmVAbq70PniWjz47f/B/uVPoT7nQfdc6MwqG4lg6+nH4c2XfBATZkyD0sHEhypyIqWQItIHqLYFb90G/OX6G9G1YjUiff2IJTMwycdVGXejwM9nqaVVhu4cGjRMRUWUIrqOB1dRkDM1DKg++uI6Wo46ApPnz8VJ73sXlvzwJ9j3j1Xwuvth5GykHRduWwOmnnk6Zp5/FlrOPAO5mvFC/E5xHWjZFLLLl+EPX7oK9o7diGRyUHwVvbE4osfNR8fCBTj7kkuAcS0iiFlkwRYDWKW/6uX3owc2lkLAEl7YaWFZtGiRUCaVFhbZP6WpnhaW0bCQFAKWQoAyVB2HA2gqAVjCJFXZ1hKwyGco5H/I+VlyXDgHnnnmmaMGsIQ3v8UASyExNwxywsB4qHc4GgDJUHUYdYBFdp5ihExJhhzqoQ7172GkLF9y2O8ZfvH8d1dXF2bMmCE+C4FJMUJU+BnLATKVACyFizctA+eddx4YoltKePKhtvVIXx8e3HJRYG6kYtFIBxrAw+ln0iVU2F/4O9uUIc3FwGwYsIStP+RO9DGaxndhuC50Wlb6M0g+vxbP/+Ev2L92Pfa/sBbaQJbeHaEfQmtFKmIiXRvDxFNPwPg5M3Hs+efCmDwOrsFQY/XlVDiqDpfWFK7FugbLc6GqmrCK8DAppJJMC4nX5M5dWHPHb7Dktl+g1VNQ43pIOC4MRcPq8U142yUfwhEL5iO+YC4QNWGpQVJNIc3vWHDWbsbvvv517F21BpFkCon+tLielSEOYKROzlRgKyoMj8kSXWiehqijw3NU4WJKmwYGdAV99TqOnD0NMxfMwZSZM/Dbb3wL7q5uaPkE1r2eDXPaFMy/8DzMu/BcxI+ajD6tHREB/FwYqTSwdTt+/YWr0L9xK/yefsRcIBcxkGxKYOycWXjbFz8PY+aR8Bj2pOpQSExmdYlcWG/RQAGfYyjAUozDwuvCgGWkx8BwypNWHzlfFdMtkuUWzs0SlJNnUWwzcKD6VAKwFN6LdZUJI4vVu9g6w/FKKzPnwHLm50pZWEp9n4XARc6FlVg3Sq3TSJ/3qgcsxTpksUYMJlhVdFAmMpQcFk4s5CBIdcpipKdCDos04YUXz0KzXjFUPNTLrUSUkKyjJKKyDmEOSyW4OAea+IZ6/lL/LuvMdxkerIW7yFEPWHwLcUWHTutANoeBzZtw5y3fReeLG4BkCjWui1pCDIrGMacQLSURA3NOPQXz3nwh6iZPAsY0wfUtqLE45eWCJqRyrSZYt+JXuj4IePLwRXynCxeKIxZot7cXex59Anf98MfAvk6omSwitot4JIp1rU2YOGsmJs+aide882KgNiFcQ1zwPM+FqfhIr9+Iu773v9j33PMw0hnEUxlEGWLKaCeGMpNeogUicrrig2keswNZRL0IopEa+JouROZ6FRd1U8dj/qkn4uiZM/DXX/8KL72wFrGkBV2YZhRkIibmnPMaTDnntZh46vHCRZXUG5kEGhoFtnwH2LcfS2/+Lva/uA7JXXugWTYcI4I9qov6iRNw7gfeg+lnnAY3EYWiMs+RBjtnIUKQInlENFOVAFiOOeYYYUHjHBLmioT7Zvj7ofp4qfPZUOUc7O+FlghpPeG9JfFTkkBlfYZTr1casLANDpR9vlz9LpZViSihct5jFbCU01ojeO5ILiTDqVYxpByWWheTvEeNhsA9RA4Lc+nwk0d4kQ9HzoQBjKzXgUhVxepdKaQsd/ay3meddZYwhxa6w4bTlq/ENWHASPBFs7ucbOU7Y71Gsp+NtIWFz5B2XRiaCo0St66FTFcP9mzcAN3mAu3CoCXCcWGaUXZI+K4LR1URP3IKIs1NUExTLLaIGsj5iqCYaIoiEiq6ti+SDgrrQT4OxhMWF/Zpto0LlaQZhk2z3HQKe559BqZtw/Ac6NQo8RXsjdUhVt+IWF0DGidMguW60BihwzxHnotsKou44qNz8wbYPd1QrZzI2MykhHQ/Be+BOID5kBR4mke0BE3VAUuB49JlpIps1X4sAjURQbSlGdH6WvRvXA+nPwk1kxMZqzWF50RhtHdAb2mGzugl04CfU2BZWcGcjURUKL6DzMb1cHv74aWzUB0XjusKK46SSKCmYxxqJ02Eq9C6EmRFCurowWU6bGFgKZ5LqNAlJDkscr7ghkcKxRXyq16JsSLnMjlmWM+wsGH478UshGEXZrlKqq80YAlzWuRiL6Oh5KatnA1b1cJS+R78qrewlBPKJRc1Zl5mWLMMG5OLm/wML4i8hhYWWmTos5YLYliLJbwwhncitNpQr4NHKTsUGVUwkt1Cgijpv2XZcnchrU7SHVaOebSUOpbzbkopT06uYWXisA6LfA/yHY12wMLl3MpRgE4VRNlMcgCKbwlSLGGGSZcFXTky/JlcELowItG8u0eFSq0V3RBAQlxEKwYpvLRwiNAgIeUq+BnCeiDpWeJPvkhKKE7wPTjpJAwhLBeIyzGCxtJqg0zSmgYzGoPHHEG09jDYSOQ9Ysi0CpeAgSJyrsPsR1DIWmWo8aDGTN7UotrwNRcKAYHLrNNSuU0XInceGbB5Q5HqWECOBN4ggkpx/EBIjnmCFBWOokCjii6TLBP00QWlU8fGCoi/IkcSnwPwHReeHhG5hIQgX0MzHLaNQCq+IBGTaSvHgJ7nsQ3lElqwYIEQjqOFpZDHcuqpp4pwU6oilzq2SpknSh0rxc4rNibCIIzPUIyTJedGghapPzRUPV5pwMJn5fxLQnzYOsF/Sx4fLTClzlN07460DstQbRj+e9XCUk5rjeC5I7mQlNrZJGjgvdetWzcIWMLfDxewFOtUYpdWBSwj2GuCoqRrS4Ksf2fAwkU4k81B0wlYVORyaXAdp2gcl3HB++S/mZlPLKAqoOsChASWgACwiEXY8+GJ7M6MzGWYNKOOCgBL+G3ko6g9l/quFKR3BUjR1ECaXizkjg/fiMMVoTMKNOEmUURAjvCcUFclDy4oSAffEVYXWl8EI3dQZ0YN6s/6wCbygG/ogKeJ3ESC6EIri6LBp0tHRHS40FgGAYtIuEh058CLxUU4suP6cLwgNJlJlgWmoVaMasP2M8inaBSsWmZvJviiJD+tPLblwIzX8vH+CbD4+dAgmYaAtywVsHDh40IfdrdIwMJ5oNSj0oClWD2KARaCrLDFWNYrrPA81DONFsDCZ5HrhHw/ErCEo/2Gep4qYBmqhQ797696C0u5TUTfLAGL5LBIQR5ZTjGRJ0YH0SVULAUAzascDFJ7obA+Ui+klB1WpVxC4TpxoZcuoVLqVG77Hs7z2e7hKKHCe48kMK6ES8hzAh87CbiqRldNYCWgPAgBg+1awtggTPguXTAeVAIWRRNpfMRB1V0SZAlc4MMG3R85mJoBU6i7UJlWhe8GKrXyICGX9xTp/ijVL+5FS0PAhCHmEHUwCH0CdEM3U8TQQWMKjT9akNCYuQnzBhzWwIOmE/SQDyEqKOoQABZiFoYxO0L+xPUJgkxxLu9JA43gukqrDA1Mdg6qoYnrXYdt4gl3jVCoJaayAZ3YjUBPI1fGR9ZLwVC84DlYH5v10+AwXhsaNJ0KwMGzC9XdPG5xmTggLyRH0FcKYJFRQtKCKcms/J0uISokH0wf5HCMF9ZFunakVbVYlJCsC8+R+XbkdUFXC3iApR6jAbCwzjKij/+WlnFGCYVzg5XyTFWXUCmtdGjnVAFLkfYbKkpIXiIXdLqCiknzhyeBsMx9MAG+PEmU+gorDVjkAn4gaf5/JwAjd3+FstRhvs5oByyUQhHZDUNR9K5HC0SgSGrZNuKx6GBfIgeFgJsLPL0tlJZ3SHzV/x975wFvWVHk/5rIRIRhyMElhyEMIJJBkbyu6yr+JRhwd3XV/ajAGhcByShKEN11FREMiKIgQckgOSlBiQOI5BwkDUzi//n2m9+zpjnnnu777n3vvqHPfO7nvrmnT5/u6uqqX1dVV4+zOfMDXPsO7wMikGsFpxA5XkAlI2zWHA4YHdWXeXW+pwhDynzc03fWELhizjx7HUAzepS9NvKV+e6nETYacDFnpI3moMD53ha0PgYQ2tZ3nMC8EFaDYmPDTfBCkbMFN9L8E5E5GoB2cmTAiHl9mWVDuha6zoad2XNsLrE7ExexufPm2KvzZoWt0WPGjgvWI44ZoE/BIDK//X0AaJ69QjbeRUYaMGhUoMU8mzNrjo0hx8p8nxng5aWZs2ycAz4CXz5mIxWwoJgBnvH8EW/W8WGqXOh0OZ+zSEBEMkvzp2rhltuPXgAsfrOBp2OcPDOFxgWwpFBpYGUWesDCgVQ6LKqJVEw4Jutee+1lTz755BsEjBc43l/I75THT+3LVFlPlJZ9ueWWs6uuuqo/iVTKyuTmm2+2ffbZp6kb2fdj3ycWI/pSZxXKfkHFA4suumjoP9+dvCRQFaeCuX2JJZYI7rf46nnAMsdsLrlFZs60l15+2Z597hmbjTYe2XeIG7yED56/x4wZHWIhpi4xxcZPmGCj5wfUhngSkp+xKp4z22bOfMX++tcHQhzKaquvahM4rXnOHBs9GuU/37U0gvQnWHJGB89PcD+FHRVzbWzI34/P5/Xgk5o19m/28isz7Zlnn7Nbbr3NnnjiaVtpxZVstVVWs39468o2ZuSoEOzb/0yokAQt8+NDcCGNHBlOVg6ABVfPvNkhNT5tCtAjuIpIMjOnzw9G++bMsYcf+au9/NortvTyS9vEiRP7MvbOB2H0OcQqz51no8bhJpt/vNEIdgq9HvoTYliEmkYv0pebBsvMGKwtfe6s8Gadmt3/R9iXHNipySXEwXMPP/zwAikC4DusYozXkksu2R+kn7IgYP53QwZoW7PkEHmBaHeVC6pKDnJSPfOZ7fvizaZ5PdSAJeD0+Zsn1Fb6i9wjRYV2dqUenbDCCitkHbOQk5q/iZYxsNT/GatuL3RT2tapMgs9YPEp01OIxsRdffXVw8FcfjXurSXeD606FfnvJ7PfAaRAXQkELDKcWSTFmuKb1nH0Kf3ILeP90ZqgigPJrSulPGfrQGO+O33FQKTqvBDeORwAy7w5c+2+e++1P//5Nrv08svstTkENY4Mga24cILLiODSUaMC+Hv/v/yzTd9wQxs1clSfiX7UqPmAxezVmTPt8Ucfs29961s2ZuwY+/SnP22rrrZq0Mp9Npc+MMGunDnz5vTt1Jmfsz9kfOUc5ZDmti8Qdc6ceXb7gzfalddcZQ88+LDde+8D9uJLL9vib1nc3rrSP9hGG25k79h2W1t6yhJ91g6lue83mfSNfNgFRF6YEAiM5WeOzZtF/MnYECcTLk6E5vkRnFk0x557/jn74Uk/sCeefsLe8773hrO8lltuhWBVwqqDFQnLDUHAr4+eH5RLNfwJQCPIGIAWfGcjQ9xNaKRcQaPZTTTfuBXaHtTb3002iYCF1PwPPvjgAvErWtVrzvN/71ppNR+UBK3Tcybe8s+mAywGXvH5hY3feECZxRZbLBxpwnxOdQ0NNWDxixvJA/rl5V5qX9oZjwJY8qlWAEtEMwEWJqvAh4CHJq8HL3o8XnXE/0ehyFdKfQiE2267LayyUq9uAhb1TRNXbfJAJrWdKeW6CViq+lDVpuEAWMAQV15xhZ177tn27e98x16byyF0fUBiNhaCvo3IQUksMXWqHfutb9huu32gPwHcaA6sm79l56UXX7a777orrLjGTxhnv/7VGbbFVlva6EVG2+tz2J3TFwvCh/iYESPGBBdReHzWXFtkLOf99OlsgNTzzzxvvzj3ZPvhKT+y+/5yv7340qthN82c2XNtypQlgmVz3333s8023sQmLDJ6vqWC+vtTwPThIawrI4m7mWcjidEJATEAlTEhcV24yBsT0MbscAbSAw89YHt9aC+774H77JBDDw2ZgjdYfwObM3den0to1CgbiYUIT1Kf4aTPUjTidZsza7aNCX6qPuCFKWXeq6/ZSE6dDtmC2SreF4ATvHHBtTQ/cGb+VmwF6DRZWIhh8S4hv02WMcPyx0o+9eoWYPHvZ14Qk0dekbqLBZqP/ZgyZYrdcccdwWKUeg01YEGO01dZvflbC0pZl3MColP7rXIFsORSzKwAlgqaEXDLqsgrvthtkkrqqq1mPLvSSiv1r2BS6+o2YEltRyfKdRuwpLSx5wHL/Lwol112qZ155pn23f/9no0ZOzakrw8wJYCJ123U6FE2b+48W3yxxe3444+xf/rHXWxsiGWZf7AzlobZs23mK6/ajHvvs03evolNHD/Rfnveb22rrbYMW4+DFXN4rTMAACAASURBVGqRMcGFQsI3EA8Wjr4wWdwrCPYxfUBontkzTz9rl156mf3Xf33K/vbc88GSM/ktb7GJEybZE089Hd6FW2qddabZGWf8ypYKro++bcGLLDLGZs0iXgaghWtrtM187dWgvIlF6XvfPBs1t89yFLqLJYQAyZFgmNfswYcetD332sse+uv9dsghX7OtttzK1pu23vw525fuf97IEfbqrFk2iXqJlyH/zJxZ4cykMLfDP9xf7Djq6zvXmDEjbebM2TZuHGCvT6nR6b44tL48LKOw/pjZtddea8suu2z/2WM+WPXFF18Mhx/GpzV73sxdEAwWYFlllVVq5VPV7iCse7kW06EGLCkyoptlCmDJp24BLAWw5HNNB54ogKUvrqQuNX/YWcaJxrPn2LXXXWfnn3+eff3rX7fttt/e9tvv87baqqv1xUVguZvdl+skxOssvphNmjzBxuDSCAnPXrfnnn7K3jJpsr3y6hy7a8a9tunmW9gKKyxjp/7057bp299u80ZgPRltr816tS/ny2h2/mDkeD18wm6ZsG15bPg/773lllts///+b7vx8sttvfXXt403fpv956c/bRMnLWq33HyLnX7GGXb2OecEgLX/Vw+w9+32L7b88sv2Bdvi1ho9KgTPzglAaqYt9pbFwzbr2RhxQsoTdi+xM6jPwjJ6kTH24gsv2ZxwEuEIe+KJx+0jWFjuutuOPupIY4vw2mutE8DUK6+9arNxs4wwGz9pUjiRuW+3z4iQL4bOvTZnlo3AtTZqVNj2/drsWX1bwQGANtImjhvft/26b6N2CBYOgb/zQ4PZGF4Ay9/zRxXAki8UC2DJp1kBLAWw5HNNB54ogKUZsLzMeT6vz7Mrr7jSfnv2Ofad40+wd++8ix15xFE2bZ1pYedNiDkJRwj2/ZsbMtSSnmSmPfjgQ/arX/3K/nLfvbbE1MVtrXU2sMlvWcJ2/+Du9pbFJtmvTj/dttxii2A1eeSRh+3Un/80bFtedrnl7IMf/H82ZtRoe/Dhh+z+v95vl176e1tpxX+w3T6wW9iddPHFl4QYmJGvzA1AasuttrK1113HRo0YbS++9KJdcNFFdvZZZ9tjTz9hH//4J2yb7d5hU6dOmZ9F93W77ppr7ZprrrYnH3/cnnv6GVts0qK2xWab2/TN3m4rrbZqKDcXMDNrlj351FNhi+nV11wTdiatsdrqttQSS9h3v32CPXDvX+yoww61rbbcwlZffU0bNXqM/eqsM+zOu++yBx9+OOwM2nidafYv//zPRqB7QCujRtpDjz5q19xwvd3y5z/btA3Ws1deecVuv+32AEo22XBj2+29//L3WKFg9WGH099dcKNHFAtLAHPzE+gVwJIvFAtgyadZASwFsORzTQeeKIClGbC8ZHOCpePyy39v5551ln3vO/9ru7xrB/vaQQfbOmutHcDK6BCs2rc/GOWBJYJQj7vuvtP+/Oc/20kn/cgefexhW3zxt9g6625oSy+zkh1+xGG26OQJdvqvfmVbAVhGmN11xx32tYMPCCBotVVXsYMPPsTGLTLW7rjzrmBN+eFJP7L11l3PvnrAAfbCiy/YOWefY1/4whdtxSnL2w9/dJJttvlmNnHypACaQEC33nqrXXvd9fb4k0/aTrvuZGuuvbZNmjwxWGiee/ppO/WnP7XLL/u9PfXkE/bS8y/YhHGL2Jabb2k77LqrvW2LzWzK1CVCro/Hn37SZtxzj/30xz+x6268wSaMn2CrrrKKLbvkUnbZxZfYk488Zl8/7LDQj1VWW90eeuRh+5//+1+74+477eHHHrXXZs+26WuubXt/9KO29lpr2T+s+FazMaPttjvusDPPPssuuvxS23DTt9tzzzxjd/z5dhs/bpy9e5ddbN/P7jMfsPTlsglOoQUAS9/hh8Ul1LfnvgCWfKFYAEs+zQpgKYAln2s68EQBLNWARaQFfLwcLCdmV1x5uZ1zzln2/e/8j2220ab28Y99zFb+h5UDWJkUXD2vhHiWcePH2SqrrRICRw8+9GC76uqr7A833hgCISdMGG9z5uL6mGPPPvOsTZmymJ166qkhMPb1ubMDwPjQnnvY7DmzbNq0te0Xp51ukydNsBtuuNEuv/wKO/Tgw2zLrTe3H//kJ3b3XXfbj0/5if34Jz+1d22xnR197Ddt2rrr2uxZs23s+LEBsLBbJ8Szjhphs+bOC5YO3FOvvPyy/ebMM+zggw6y5595zsaMHm2LTppgL7/wYtiQvOOu/2jv/cAH7P27vc/m2Ov2u4vOtyuuuNyO+eY3bez4Cbbi8svbqy/PtJf+9oLNnTXbRsydZ8d+81u21VZb2wpvfasdcMD+dtIpPwoxLJMmTwrbp595/Anb7O1vt2223Mq+9pWv2siJE+33l15iJ//0p/brs39jy660oj14/73hbKQVV1jBPrznXnbAgQeGocAVRF+gr790rnUBLAWwtCsOC2DJp1wBLAWw5HNNB54ogKUZsMjCcuXlV9hvzzrHvnPccTZ50mRbcurUEAD68ssvhziM0WPG2vhJE23Ft65kxxx/rM18eaZ9fr/97E+3/skmjB9v3zjqKFt6yaXs+quutUsvuMiuue5aW2T8Inbu+efZVltvHbZG33LrLfaRj3zEXnvtVVtnnbXt9F/+0iZMnBjcUQR7H3HEkbbV5pvZT37ykwBifnDiD0KW1n9+3wfsC1/6oq215po2ZpGxfUGsNrtvU01I+DbK5r4+x8aMGGUv/O0Fm3H3Pfbv/7a3PXD/X23XXXe19ddfzzbb5G12wcUX2+k//6W99tosW3+99e1XZ54Z3DCf+PQn7eprrrannn/aPvjB3e0D73+/PfPUU3brLX+y478JPSbaN75xtG280UZhq/deH/mwzXx1pu20y062yz/ubBPfsqjtt+8X7MmHH7X11p5m//Otb9vqq69tN15/rZ140g/sxz/7ic0dO9Le99732YYbTLcVll/epq21tm20ySbzdzD17S9iy7cy7gZXyPw5UABLASztisMCWPIpVwBLASz5XNOBJwpg6QMs7CB59NFHbcsttwxU1Xb4kOhtvmK84vLf2zlnnWXHH3ucTZo4ySZNmmSjx4wOwbFYENiGO2nRybbKaqvaMccdazded4Mdeeih9tijj4Wg2lN/9rOwK2jG7XfY1b//vX3xC1+28YtOsF+feaZtseWWNmvOHLvplpsDYGG30Lrrrms//elPQ06Na66+OgCWww873LbeZhs76Yc/tD/84UY78cQT7cKLLrL37/FB+++v7G9rrLGmjSADLwnm5r7WlzyMlLbs+QnpS14P7bn5pltt749+xJZdehk78sgjbOONN7IllphiL738ou237352+SWX29hRY+17J37fVnjrCvbxT37C/vDHP9riUxcPcSwrLLO8vfDC32zGXXfZx/b+t5Cw8dvHn2Brr72O3XvfvfbZfT9jq6y+in1or73sA8ThjFvEDjn8SDvzF7+2xSZOtgM//2V7/7+83/508y32fz/8vp38s1Ns1PhF7Mprr7ZVlls+ZLcdM2qMjRnLoZEcc9C3zbtvbxCRyH1gZX4aluISKjEsbUvDAljySVcASwEs+VzTgScKYGkGLH0JZV+3q6+6yn7323PtW0cfbWuvsaZt+45t+/JdjCThGnlMRtioMWNssSmL2ft2+4Cdecav7bhvHWcv/O1vtsvOO9uJP/iBjRk5xh595CG76Y832gfe///sLYsvZr88/XTbfMstQv6Tm2+91fbYfY/g/thg/fUDYFl08mS7WoDl8CNtm222thN/eJLdfPNNAbj87ne/tX9833vtawd9LcTUAFiwrMx9ffb8RGucJzSq75yiESPt7rtn2JVXXm2f/cxnbf31N7Djjv2WTZ++QThO4PUR8+yggw6ys848y5576nk79LDDbM01VrPPf+m/QgDt6musbuedf74tOXVJe+WVl+0v9/3F9tjjQ/bIww/bN446Ouyauv322+yrB+5vSy+7tG2+xWb2trdvYiNHj7RzLrzYbrjyGpsy+S22z3982j7x8U/aH2/6g/3gRyfZz375c3vLkovbTTfdbMtNmdJ3oGJIudJ34GII8OGMGfH8/DOaOCuJq1hYioWlXXFYAEs+5QpgKYAln2s68EQBLM2AhWX9vLlz7bprr7XzzzvPjv7GUbb9dtvbFz//haDAcVPMsXk2dvy4cA4QwGPqUkvZ9/7ve/a9737PXnv1VfvAbrvZccceGzLG/u3F5+z2O2+zbbZ5hy2x5FT7xS9+YVtsvkVwdtzyp1tst/d/MOQq2XD6dPvZz061iePH2zVXX2OXX3G5HXHkkbbV1lvZD086yW67/TY75eST7de//rW9Y4ft7agjjrT11l03HHgYzhsaafbySy8FlxWuq3Hjxtn4CRPt5ptvtQsvvMj++7+/attsu7Udc8yxtu5664YTnIl1OeHbJ9hpp/3S7pvxF9t3n31svWlr28GHHWIPPPhX22STje1HJ59iyyy7jL362iy7//4HbM899rQHH3jIDj/kkHAMwJ9uucWOOPLwEEczdcmpNmWJKSGe56Hnnrbnn3zSll1iKfvYHh+x/fbZz669/no76Scn2+lnnWnLrbyiXX81gGZyOOCRYws4KTqYi8h+O9IBlvm8r4iWAlgKYGlXHBbAkk+5AlgKYMnnmg48UQBLAmCZ7xP6/SWX2tlnnGEnfv/79o+77mIHfe1gW2vatL6ji/G3zE8pj6+CBGz/+7//a9854bshv8n7/+V9dsJxx4dYl7+99LzdcdfttuUWW9viS04JW54BLLPnzLVbb7nV9tp9z2AhIYbkpz/BwjLJfn/55XbFFVfat775LVt/w+l2+umn2cOPPmo/P+2Xdvwxx9hKq/6D/fDEH9qmm2xiE8ct0medmDfXbrjuOrv4ggvsvvvusw9/9GO2wYbT7bHHn7Srrr7GPvmf/2nbbvsO+8Y3vm7rrbeuLUKm3dfNjjnmGPvlaafbX+673z7+7x+3rbfYzA446AC79957bNq0dUKcy8RJEwNgeeCBB23vvfe22/98hx33rWNt1ZVXsRtvvMG+ccThNmrsaFt6uWVs6lJL2quzXrOZYyzE0Cw9ZartsOU77D8+/Um76ppr7KQfnWSnn/krW2Oj9e388863pSZNslE0ZNYcGzV6HBnl5h87PTIAn+AW0tlK84NYCmApgKVdcVgASz7lehKw1HWDFNYc9pZz4e9PPbxK9XL6cspBZEF+vf66UX799dc3GDD1IkYh9+A/4gteeuml1FeEcl/+8pfDx1/+LKSqM4ze/e53B1dAKg2yGjS/cC8Alm7wmWir80j4P9tzORTOx6eoXKsYFh0BwVice+659o1vfMPe80/vsSOOPMKmTSMPy7yQxI006ToXhXeRFfeII46wxx57zN7+9reHZ7n/l7/cZ9ddd53tvffHwtkvlCN2hrbeeOON9m//9m8hTfyaa64ZLCzElpx11lkhhuV73/uebb75Fvbzn58a5tP5559v//7v/x6exZWzzTbbhLq4x3zADXXCCSfYs889Z//xH/9hn/jEJ0JEDu/56Ec/YmuttVYAKGSCXXzxxQONPvvZz9pvf/vb0IZjjz02lPnUpz5lHPq51FJL2U033WSkgKf+GTPuCfUQ/3PkkUeGNj/4wIP22c991kiHv+eee9r73ve+EEtz94wZNnnSJJswYUJ4nnl3/fXX2/e///1gZdpg+nS78IILQmyQrpSzvSgbp+b32ZMZH9qn9O/QhrGiTdTPuDLXcrLdtpPptp353EoGLkyZbuuyXUMzDnPs5oUMvPLKKyvPU6tqF7899NBDtsEGG1TK5qqs6jxTDj/s5igOw7qff/75cDYQ3712oUwQcvFVN1H5fbvttgtK6s0KWAYyhp0ELAIhHOD5m9/8xv7nf/4nbEN+73vfa8svv3wABzp0k7/JdEtsC7t+vvSlL9ndd98djoAA6FAeAfy73/0ugBCU9tlnnx3O4AF0sK35wx/+cOBhTp3FSsM5VwTX/uEPfwi5WN7xjneE/0+dOtVuv/32AFQALgALANQee+wR3k9beRfPAIxOOumk0G5ACefNcBo67iISzwFY1lhjjQAgADgciUGbAVOAi3/9138NQp3yhxxyiO200072+OOP2x//+Ec79NBDg7I/+uijgxCnzIc+9KEAPHbbbbcAWFAKRx11VHgGGgDK1ltvPbvhhhtCu84444zw7IUXXhhOfPZXCmhpAiwo/pAfZ/To8AlnHI0cGT46aqPbgIVx411VQKOdOf5mACyi2UBkQdOzdYu2OtlMfZxxx7EJVeNWAEsTxcv9QIECWPIZoZctLPm9+fsT3QAsl112WVDgWDlQ7ihYgABKj4BVrCwoQqw43MPah1UNEMLvKHHOxwJAsKr/05/+ZJMnT+63sNB6Tg6n3COPPBIU/uc+97lQHwBnxowZYTeTAMvSSy9tDz/8sJ1yyin23e9+NwARztPZeeedA2A555xzQnmyx9IWgAEghHIcRfCZz3wmWFre9a53BcsIp6Nj+QH88E6sQj/4wQ+CReSLX/xiULYkwWPVyzvYGQTwOf300wOo+uY3v2lve9vbAiAAdHEfaw/thU6cTv3EE0+E9xx++OE2ffr08L6TTz450IA2XnTRRQWwJDJ+ASyJhGooVgBLPh2HlUsov3uD80QBLPl0LoAlIYZlvssRhY015Dvf+U4AKDplFqr7vwEaH/vYx+yrX/2qffvb3w7ghA9lsIpgVcEKgxUDRY61ZNNNNw0gAXfmJz/5yWBN4T5ggWcAOrhhATlbbLGF/fjHP7Ylllgi/IbL6fOf/3xQ/nKHAkpoI0ACMEKdWFQAE7QDiwPBurisABEoP94fDl8cNSpYj3bffXd75zvfGZ4h1wt9wEWEBQW+0Ym61MdzuIQ233zzAJqol4R4gDjqpR1PPfVUSMsPEKIs5S655JIAuLA2YXE577zzKl1CTVaWYmEZ3jEsddaMYmHJl+mD8UQBLB2gcgEs+UQsgKUZsKCQAQZ33nlncIGcdtppQenHbgsUM+VQ5LhCcKNwUjDPAXJw32D5wDpBfAexIwhqlDc5VwAZgAPAChYVrA3Ut84669iOO+4YYkoAGVh3cAMRcyKwhKvlRz/6kd1222121113BXcUQAcQgAVl++23D5aLvpOO5wYgQR8uuOCCABjwyfM776ftO+ywQ3gvO4toA/coQ8I62gWAwI1E/QT08gGk8X/A1bPPPmuHHXZYsMDQNsoDVoihwW2Fu4s6OSmY2B4AERaXAw44ILyT8gIp/u86Di+ApQCWfOnX90SxsORTrgCWfJq94YkCWPKJWABLGmBBwaNgAQ1PP/10sJBgweCSVQLwISADeCH2g+cAD1g+sGrwDBYWwANKHXAD8FBdAApcOFgx+PA3VhieoX7q4VlcST6InXvPPfeczZw5MzzD/1H8WDaw0vA8gEiBprQbIECbeI5+yRqC5UYBxLxH/aKf1I1Fhos6qZsAdNqCZUlWHZ5hPgLYeAYa0G7cWLRJAbDUSRuoQ8G4styojf67AJa/U6C4hPLlXdUTBbDk07EAlnyaFcDSAZoVwNIMWFCuKFat+BWropW/zNk+AE+But6VASjwAZ8CN96CwHu8q4VnAB7+AhzQBgWN6h7Pqq3UHbLczg8u5bsKsMjSoucUNCw3jwKKvUWJNnHpnnZIqR3evC9rDt+AGT70V+0T4JN1h/97wKI6i0vojZO9AJYOCMBiYWmLiAWwtEW2BR8qFpZ8IhbA0gxYoKoUtrcMiNooWO7HLgysHVgTdB/AwP/9xW8ofoEWwIAsEJTjfTwPKOAC8HB58BP7/z1ooW5ZYuJ3eYDB37TBgzHqUXukHLmv+B3ff29lEjAS+PB0qXqnLDi009MxFaxQrriEiksoX/r1PVEsLPmUK4Aln2ZveKIAlnwiFsDSDFjiHCsCEHKvSJlL4cuawH3lgYndNwIIfCunkSwpAhZ6Xu9BsastssSoDPXjdhGokZVCVhe5eCijXU2ycug5WT/0f/ojV5UHTAro9dxGH3CT6b3e6iTQ5V1mshJ5utCe3FxNakMBLAWw5Eu/AljapVkBLO1Szj1XAEs+EQtgaQYssnQIZHiLhqwZsnz4EfAKWqBDFoQ6F4fAgNxLlFMwrs/v4J/XDiWv7GXxUHu8C0buKll+vAuGuBnib/xvWFkALvymvsdBxx6c8U7awnNyG8V08S6gqjbmcnIBLAWw5PKMyhcLSz7lCmCJaMYqjxVbLMy0YkVgx75uAAvJfAgi7KULoc3uBz4+PoE2eqXhFQn9ZGcIW2ml5KTEfKzEQPuZA1i8tcCvslsp7YG2L/f52HWjttF27qGMY+UJL5GvhO3BbBmWW4RyVYo1blPsksltc1V7mn4byDtaPeuBzUCBhAdd3aQZdZOaf5lllgk7lBhPH3PE/wlWBlTK9YbbTZYxTp9m55YsSym0zc10S928Q4kgq1yLKe+Ny2jXl/pFADe70sKhnIkXO7WgW8rl3wc9kQOSY951GdfFvQMPPDB86sC6rIYaF/4PzRgfvSeljTlleBe76aAZtBMdY8Af10niuFVXXfUNuwVVTvpJfEj/yULNrjxZLXPa2WtlC2BxI8JklkIUc0uQDkfAwsQmJ8fCAlikEDTxehmwwDcKIIXFAMHeUsFvAiykbyfRmQJaucezVdaTXhMgb/b2NAEWFjOyEjHePk6o24BF8mwwAQtKWLzdxBu5gEUAHSU8WICFOdnJhZpoAy+wK24wAYuAc9O49PL9hR6wsG1RYKPVQPgAPHz62lURWxe8j17mdlZROksoVkpDOfisSshYyhktHoE3tYnEXQjibl5YWEhGxnfKhQJntaidIrF1QRaOqp0eKfV3ugw8J74DrMBTAloCI9yXhWXrrbcOTaiKPel020p9aRTw7qcqCyVjxTwhzwsW1viCR9mK7uWJAnyRLyTE+6d/+qd+a2eKYtxnn31s3333beyA5Bnt5h28K3afUYksF40Vzi/r3Y16nm+2ljOf+a6yQlfVT4JC5GbqxTyivT6A3FvTZCFRfbrnz1PzFowqa4Z+0/lLVTRLbW9dOblQW9HMywHfTk+zKouR5yHdZzFEzqGqGLCB9mWwn1/oAUs7GQsxu731rW9dYCzEQAIp/qbfqcDvdabHwR5c3nfwwQeHjwIQJYRbCSrOruHArF676lZkUgK0N0Xod6NfEkLeEufbw0pb4MyDLVZYgBbO9Mk9DLMb/Xgz1xm7kqq2f3v+YvV98cUXB1mx9tprB9L5uU9ZWVhk8leAsf6fC7BxCTGfcy69g3cqwFhB0Tn1+LI6w8oHO8fxRe3W3eq5uoP8vFvHAxb1Wa6wqroZR4EsucFzx6XdvioOzLuE6iyrflEdL9h0rw4sdtJ93G5fO/FcASzzqchAawcB2TM5+4RB9ofLeQTvt0FWBRH2AoOAqMn6yYf2skLxQkUuCE0WuVgEWCTUpIyHCogJBHB+DStZ0VtCSDtJOjEhOlUHq0BZWaAb59sAWDyfwVtkiIXfSC2POd1b8NrdudKpPrzZ6mkV+xLTgnmE9ZZMucQUkGmXy88vxpq4Nn7DyqI4pnhcm+IW/LtzAEurRYni9HLiZ2iHgpll6Yzpwv3YCtMJPpIcJh4DmstKKderdqPpXd6lL/kmcOABnLbP17UxZ2xS+9lkRaVNciF7IOL74QGV51u5oUUvgehUq1dqH4aq3EIPWDiThICzlEvKhMPeWDV5q4SYzMdP+MnhAYr+HqrVPu3i3XwEWLQC8atGlfNAhL9Jge4tLH4VlULH1DKpAEiCBksE6eEFHDU+CsIbSpDohYaAlMYAeuAaIHOsBIgAL2AFMy8H83GasK4qS14qXUu5zlFA4xqvvJlPHBnAcQSAaPhSgMW7hZ955pl+l5APvtXOp5Tgat8bTqzOsbDocEzVof60YxkRT9K/Kksi78oNUk2VkbybD3IJ+aS5rznGosVvlvAyOHbTezAji5OnD/fj/EOd46i+mmifcgvFcksBswIZnkaSfX7xrP4odYBo5RfVvDOX1zrd507Ut9ADlu222y4ZsGg3B0IIC4u/4pwVrYivQN3UydiJgYzrUBsEWBAkcXviFRiMj1AlopyVTKw0O92fVMAiRXDvvfeGA/Xii9TrJEtTn7tBz6Y6PRCsEjCcUrziiiv2p56XAOG8G1LOswJfbbXV+mleAm6bKD449zWWskbKOsL/b7755qB0OJ+IsZUiEl9zD8ACUPWKhnKyCDAvGfvUuQVg4ZNywZMcO4Aik1IUn0qZyaqcUp8OsPTzzIMB+sE85Eqd2zluJAAJgOXCCy9coLn0jWMYkAO6mmQBz0iBqw0CP8g9WZ5yxiaFhqIN70Sn+PpFMx8308rKqnYLfEJ7xqhuN1CTNSm1/UNZbqEHLDkxLHI1EMOCEIIhlF3Tm+qFfLXylxnUI/fB8oE2MQ+rMczImigSXPSLSRlbV+iTXEKxEE0VQk1tyr3vXUJsg1TMSgwMpDBy6+9EedokvvBmdn6D1p/+9KfDh9W4ytEvFBbn3lx//fXBLYRyK66gToxI+3V4xaVa/CqYOcKYMU847Zoxi48xYGwpI2DKfSmnGIw2KVffkxyXkOSZf17ASUot1yICb/KR7IhlhCxHqQAsdZS8Swi6V8UNxmOktngAKdDFewVMAELeQurblDM2qX2JgUbMY9A2PkrCH4kRg8+4n/6+7smak9rGXi230AOWHJeQBgnXg7ewwPCa2FXo1ZsfqaMbTJ7LQDIrYmE5/PDD+7fYet91bGGRgBNgifvRaSGUC4AUdOvN2bSJPsmClFtnLl3rysfgybuteIbV33nnnWfaDeTrYaV13XXXhXwMK6+8cigrUNOp9pV6minglZZAC+PgeQplQpI73EF8b7jhhv27VnhGvAk/Er/CHMPKoXqq5EcOrLmeoAAAIABJREFUz+a6hLwFRP3zQMa7Fpoo5OuKwVC7buNcmaKgW1mIvDvEAw/JrirXSQwQ4rq81SdnbJroF9/346F7sXU+fr/XNR74SEcxDlrQxbyb275eLL/QA5YcCwsDxCDfc889QXFUBTapjPcz8kwcnOXR/lAMvN4f7xKKhZbKeTOk3yXUjaCzdumB5Qu3iSwuqidH6Lb77qbn/C6hqpUt99lRgsClvV4wsfpB+d1www3BtcBpy5wuXK7BpUC8yo53nmByx2pCGgPA8/Tp08NYif+8FVaWM1b0/qMy4pfcxU2OhUWyKgZi/K525LhkVJ/4V//nO160dWPkeC+uauZRbKWK3y9F78eQMvTXWzDr5HadFaST/aoDJ3Gb1Aeve3wfWlnCfYDvUOukTtCuAJaIijFgiQdZ/+91wKJueZeQV6TereJdFDw3HACLX+11YiIMtI4UwHLMMccEwLLBBhssAFgkuEjzzipx8uTJAbjw98KQnXKgtB2s52Ml5ZUdf2MxISaFeAnAy9ve9rb+8ZF1hW/ACh/KKWkc3yjZAljaH80YsFQp4Fagc2EHLFXWoAJY2ue3IXkyx8KilRIuIaWMrjrC3pt+qzqVu2rqBmG8hYVVmfoWK1atjtQnH8OifniTady3wbDASAixmwbLl9oqy1Y7K0bRw09yLwBzTdV+DKssPigsaE++lXPOOac/5kFCVO8mlgVrCxYWPmTDlB86zvUil16JeenMDIp3hogH4HFZVQiQJuEX8UYAEB9bQCtwGWGF0TELgE4BFZnrq4LZU10PuRaWzlCmrxa/SIgXDINl5QTws60ZGsa097KplQwWMJXLxM/11HHoJF1VV5UlLLU9VbIr9dlu9KVbdRYLi6OsgmfZjeLPBqlTCDBJFXip+71bg1hXLxPz0EMPDR+1SZOizm2BcMbCguk13gYXr178e2Vx8uChU/3VKkHbf+OV70DeI6ElU3FMp9y6fX0xiIHm5OwgW+lHP/rR/lOGvf+f50k2dsstt4Q8H8suu2wALQrGxfoikLmwBNLl0ngwykN7LCR8Y1nBBUSMETEr2p4et0PxLYwL/MQHcOMBC2M9XAGL76/kh2SjgHe3xkbv0bZmvT+O04jBiG9PHYiJF2TdkGGtZLTAoHcVt0tHr3u8u8+HN7Rbdy88VwBLNAoMrGJYPEL15uL4FFtZGbz5bagHN7aw0J7Yd6sgNQkbTdzLLrtsgTwssfuLuuK+xoFr3eg/li/ylcQxLFXgK+X9slx4IKbf6E87eSUkfPT+2FJDneT4ufHGG/sz38JnsuSx9VC05O877rgjrNi180gHpVEGOjCGMT1S+l7KvJECsrDAA9Bb207JQMyY8S0Xj2K+PPhgrDnIUit/wKUSrcntOtwBSwzIJSNFD+2q7AZP8g4BlngRWWXp1ZxirjA2WpCqbdpaHltZtQjluxuLAm/J01z3csNbS3LmabygFHgRACup+XOoOURlc1xCUlbkzPCniMZKJ7aqiMEGI1Ar1VWhNiqGRYJVbfQTWHXq2wMWb+r1bhQPWHxQWM5kSzVZqs1YWNgW3GkTrl/ZxO33q5ROsTAZTznj6Ytf/GJ/jg6EieKKJLx4NwoQxalD2Nhx4q1A8QqzU218M9bjV+fwtJQgWYtxz7Et2R+G5w+T49mnnnqqfzch9xhnARYBFc3DOldkE90VRN9Urtv3Y2uAnzdeUTa1I1UGSPbIJRS7pPSeeJEpme4BQWyF8YutJlnf1J+U+/79vnwsh1Lqip/3FpbB6EtuGwdavlhY5lMQZkG4IJCuuuqqkIeFSxMxRq8xoxAkmTr52h00FBeJxlIumT9PPvlkO+WUUxbYFdAEen7+85/bZpttVunuUr0esKBs8e3LFJ5ifqQMNE4pq3ehvIkB8cLJC8p2/egeiFEf8QovvPBCVy0XvJPTeqdNmxZcDdBQSo02yKqllaRvY2ztK4G5KTMivYx3HcDTsmQxBlheRH/lXuE+1jB2seECAuAwbgq0Ve4SWVlikJkD8o877jg7/vjj0zvT4ZJqq3fJ8ApowKnjOcdkAOokZ5uaqXgt8t6cdtpp/cW9XK5z+eBiZU77y9O8CkAAUBnHFPnU1Pa6+9DskUceWeA4B/WhXVkmenigBp8utdRSXe1LuzTIfa4AlohimhhaCcXunipG4owYhJUOr+sWk3PEAHllUi6ZaA866KCQOG6g1p8YucfgDIsUuSn03qY2imappzVTnyazXxFpfJpAWFV7YuuRysgqpaDKpr403a9bDaLQPv/5z9sXvvCFkHsF905VRmXRnn7TJrmH/K6TpjaU+80UiJUfT3hwEQML/g/Q5NgF4lxwAfEbYynrC2NaZV1p18LSDp839zyvhAfPehJAgNuMgHH4NMUySXncvCkX9cmlIzeNj2WrAiuSE3VWKQ+6YrrWxfGltLWpjBZgxEdBAw+mRFvpkNTxlnVGPOufU+6aeANJUzt78X4BLPNHhQHXmTSaGN60KQZSbANMp/sE4QFYvPKt8qkOlAEALLi4Ui5NRgEWnvF+ZfqobJXer+4BAH/H+Q6q+sVvxJZAg9QJBq0IZEwBLFU+33YFvqedBz76nb4oUDlF6Oo5L2CaaOBjbljFLbfccnbAAQfYXnvt1R9nJMsKK3e5FTSG3n/PGPozVFJ4o5RppkActyUlrIUMY4y1E0sc46ExYNHiFyxapVPGg59O8G9zLzpfwi9cfO3PPvtsyJEEcEu9UNbIjNQrXnR5wEIdtE1l/ByJc1FpfBRrFM9zntV5at1afNJeaAXNoJ2/vHxIpQ3lZFXx8oe++EDlnPp6sWwBLG5UPLqVQNGk8Ewdl8MMjPLlm6tb20xzAIvagSL86le/2i9E1S8pa3Xf+0/1mxhfK8vYP6xJQl0AFmgQA6M6ps8BLK1WvnVm4NzJJiBGfQAWMorS39Tgwdji1ARaUHCADQAhSo2DD5dZZplg7idPi8CiFATf8JVcR3Iv5LgTcmnyZivv+Ux9hx9Ee9EaKwKWAWJUpPR0hgu/aWzkMmLctCjw883Ps267k7sxln7xgvJlBxwAzgOHVu/NASwahzr5WjV2ap+2gst6XmXxjC3qAiwa+07STzIFWgmwiGdS5U1Te9RXD1i60ZemdnT6fgEsFRQV80r51iFelRuugCVePVQpfynM2O/uY1i6DVj8EHl/cxXIameC0EcBhKEALLJ20Q4BFtqBQOeICAXjMl5SkBJw7fS3PFNNAa/0BE5kWYHusnax3VkWVQERxgiAojNg+D8B0nLjxfNnuFpYPOWUa4a+DCfAUjX6Qw1YxEc5MUCt5rHc2QWwDDNpl7NLyK9+YsTu/y9FKSGE7xrrgnJkCOB02pyYY2GRFci7hLz1I96RUrfCE4iJTcExYGH3jiwsKSySY2Gpqs9bMNRXyqWuVL1lwgMW/pYJ2deb0qe61XP8rPedc493SsDIBUeZT37yk7bvvvuGoFy1Ebrl9hcFm3NRP5aCnEuBpznPKDi17pmqVTMZZpusV3F9AIfcC3CCFQxaoEQefvjh4AKizYod4r7+D1DRDi7eRRkAjFb5CwNgicfDAxYCW4ljw2ognm6ieY6FJa4rdk37+DbKehksC0uVXPZuJllU+dZOyW5YMEVHaAXNoF0MWHwIQhMdfX9VVvKEvuASoj/d6EtK2zpZplhYBkhNGILEXnfeeWf4js2NVQqUScKEQ8jlMFEOYFG3PGDRu2IF7RW9F0Iy7crFVddW3BRrrLFGlj96oIBlgMMWHveZMn3f/HEGnXhPSh1VfOJdERKsCB6COvm/tkJ7RQJfSXhTJwr+U5/6VL+bMkXZT5061Y466qiUZveXmTFjhh199NH975Y/HcWv3BzejUXbcVeutdZaYS54+lOOZxSALGFOua985SshPb4AdEojv/3tbwcw4S9P75j21A1v8LvOAeJZ1UF7BFZkUeE3ARa1Nz5xV6CF+r1C6vTCxvfTW009jf2Cg/JxzI6XAwIgWqjJauTrU9BtvBun1fgMBLDU1RuDKvjsiCOOCAfAxidT1y1IGDdcQiTPTF0ApfBhXAagIpdQyrxs9Q7aqUVoDN4UdNtOG3vtmQJY2hwRH+AUK1+P/iWMday5JkA7EyFnl5ACh4lf2X///YOAlOuBLivhmO+HzKJVK1uRSUGesYWDlPm5FhbiAFKCbtscopaPMamhh7Ziix70ixgWBJxWXJ1+f6pw8ruUaAsr9t/85jcGoFDbtM1WgIYy+pv3IBTf8573LGCVaeoPsTS/+MUvmoqF+2ojmXn/67/+q1/RCwRLGXtQIuACwFl//fUXOJlaQERgQfXwTV8//OEPh9w0qTTkuXPPPbc/vkydqgMsEvzwBdYTXVhPeT/0VQAtfdORC7K6KLGcB2cCbFUANLa8JBE9o5Cfy+pzHYhRtX5hw29eAapfAFHoo3GFz9Zcc81gYfHxJk2AhZxXnbzURy+D/XEGsXtfySE9P9D/OHlmShtzZbpAHokhNU58t3P6PP1Sn+FFuS9lYbngggv6Y7G60ZeUOjtRpgCWNqnoFT27hFC+Stnt3ShUX2WZkMLJCdDNsbCofQceeKDxkWD0QV0eoGjV59sau4PUFz3H/zVJMG2S2E1lmsg61BYWWY/UTr8zjIBbBd36YOumPnX6vheuUuCco6Lt84qv0DhJaHnFgzDcbrvtArBQ+aZ2chzA2Wef3VSsf6xp20033RQsOTGQVSWejgIFJ5xwgm200Ub9AEBjwjeKJA5A5Pf3vve9wTWTAyZRPgqIbwVYvKVDAF/zRsDEW0+oS24tKXK+ZVkRQKHvus8zVSv7XGWXMjgxqPPv1XiI73UvRQ6oXj1LWwAsuIUVdJsCKLthYfH8JhnIXMZqqr55N5Dkle8TfKcDYD24S6F5Shm9n7kJDdje7OWRd9en0FE85flX7xBgueSSSyrzaqW0t5fKFMDS5mh4wEKMwX333RdiDbhiwOKFpIQXjJSbKjkHsOidcQyLJqhPOa1Vrfok4eUDUT1Y8UJN9cjCwrMpSn6oAQv9kUslNskPhUuoFRtKaULXm2++OazyvdDVOCHo2MHilR/CcMsttwyKVUnQmliebdbnn39+U7H+uBpWhH/84x/D+UiipV/NVwld2vr973/fNtlkk/6t8x5QUac/pkAKf6eddgpJCr21sKmhnILtz2CSgI/BixQwdBKN+U1WJFxx2jUIPemXYn28ZUaxLwJe9IM6PDjwoFLzqakfufe9rPHvk+zhN1l/BI6r3D1eafO33Nm+Pb3iEooBC+0FsGA1jV0lAgYeyCm1hSwsssTm0r5VeQFxAAsLvRiwxNae1HfLSiz3nuZdcQmlUrAHyrUTdNvUbK12ZfpkxevzsPgJjhkZBqoLYvTCrOm9ABZWyymXgAMuIT5a9flnYwtKky+dCUAAJ4I7vtZee+0A2rTttqmNABbMwUPlEqpSEvyGskK4HXbYYf15DZr6kns/VuB1q6iqxHW33357v7WA8VMyKOguZSr+5JuVL1mL4bPUiy3WZOFtuqSk4fHrrrsuuGu4/K4m+B6BrHNbNGco8+Mf/9jIXKotmFIO1AvwUkyI+gOd4H9cjxLKTW3kPtYfAZaq8lIQimkSMPFAUK4P+qO+qK8ejMglxD3xk2LVNM5+3jEuPlg3pT+pZURHwJWUsua4FifqY6s6vaIXeFZ5LXaIKyKODSWsvje1E+sCMqOTlwfK6qsPohevaSygPTItnoPnnXdeCFZlvHOsHKl9gaZPPvlkiOGK437gP+K3NJ9T6qTfsUVS84Z+XHjhhf2ALbW+lHKDXaZYWDpAcVxBTLwpU6YsUBuMLkEhxRKbxptAgq8w18KCoBRg4T0oNY/eveCtmuhSLr6NlJNgp22aVORgUKbblK15vWBh8e3Uapg+A1b4xEF6HWCVAVXBOHAYonc9SimilBhvFIZiLLiHiZ70/xrDFOFLunSsEikX44/QB7AQK1MHCKreS5wMYKpqRUmdBAzH/IpFhnTmqZY82gPIkxutFWDxweWMvY9h0dlAUtACV96i5C0oUuz8Fif/i9vg4y1SaJ5aplW9ypasA1C9C0HWFj/vJctkBRP9ldGXbc0AFrL+pl7ddAmpDdBAeZViHpRslhzkvsA2LpSqE+tT+9aqnIAFQB7LtM9dU7VISX1nDKQZY8aQfgBYFoYjPApgSeUGV85PaJheeVgkFCVkJdy0mvemR/3tBXJTU3IBC3XjEuLD5Vd2VSsrCSVNqDi+hvuqw/eRv4dbDAv08LuEvFXMZ8ZsGpN27sdj3gpExH5prFLwmXhLgcOKrdDYaSxZPTI2OTEsnIuFVSLlQrGzCr322mtt1113fUO2Te86lRIX75955pm2xRZbLLDy8/3i/fo/fyNwSarHFmPqTQHGPHfvvfe2BCyU0ZjoG7r6uCberfdRRucECRSoPXKxUKfmj4A/v3m3q39vCq3bLSMwIjkkV5HaUwegxJeeXwVYxE/iT6wE2qKb2s5uAxbNgThxnAfvkuW+r/ytGBbVkdqnlHJ6F0AFGvit4NBabRL/p9RJGT/HZUmivvjAyNT6erFcASxtjEoMWFgNcmBgHNgnkFAlGFi9YQ7PEVrsxNhnn32SW8zE4Owhf/6QJosmogceqpidG1hA6gBL1e977LFH2L2R2h+dWJyb7yO58wkF/arSA0j813xywGTC6ypp48FKFXDxbUA5Mv5aFUspeoWkfmh8Wd3vvvvu/ULQW/jq2sxBaSeeeGJjlwQmUNJYMb70pS/1WxTVl1aAhcBe4ms8WJSQlnL1/ArfffzjHw8xLPQzNoHXNfjUU0+tdGP68vEC4vrrr19g/OmHVqyUlRtIFkZkwMYbb7xAsLCfJ95aqbFByd96661ZO7gaB8UVUJ80nz1gaRXsT59uvPHGSjei+Mcrfd6DNYyDGbUVPaWdxPzlyLOUOlXGzyVcjxwCS5u9m0X0qHKlHHvssTZ9+vSsscFa6K1yTe0FqOy5557BZeovP2ea6qh6TjJY8xMrzsc+9rFk1xbPAz4BU712FcAywBFhsipAUFV5QONXiNwXM5LBlLiXusDPATYrPK54DEyiMuFK0MSuKd3nOa0u+Ds2K/vVmSYGglx+eu4r+VmrPrQTpNcJmsR1aNXvrU/kB+GT0o922uRX3P75GLBIkKo893VYGn/rfmw98Su0Kv5sp811z/ButUPbMb0VrgpUSJESJ8Dp2+IprS4FRrwVUAHDLAr4W/Omnb7EdBYolJsHfpZ7N+YPlY0DG2UtoG6v1FWnb6foI4vpQNwAdf2nnbK+6SC/qrZofqs/kg8oLKUp8PxUJeP4DasflixyUaVe1M97unH5NgtcVsVxqZxfuMHHsqblWPKQ56lKHj6BzxS8LVkqWtRZuVNoJUAsPicebfvtt0+2SPIOrFKyzKe8c7DKFMDSJqUldPW4XwlXCUQJDwllUC+r0m4eXCf/rSLkBZj4FlPHK24mKP5bzIhxnwS+/LY7CbgmP31M5qEGLAKOEhReyQiwtFqFtsk2A36M+JWq0129IuFvKUWdAJ27aku1LsETopMAhnfVxPNE9PZm9yaiCJxJscv91fRcO/d5FwGk5KIRHflNZz9V1UkfUbzEsdXRDdowJooj4P8okl122SUrIDq3TyjE3/3ud2E+QzfaFyeFi+ukv8SkxScp180ZnsdaAmCJ4/hatbebgMUDAC+PPT9KFgus+UWb5LJifVLongpYPBjRYk98k7tzVO3yCy5ZjsS/AOMddtgh2SJZAEvKaHepTDd2CeU01SN3P4lkYcmpq52y2qJbBbDqXBDk+ogBS9O7BYCayun+UAMWrzjVJtGoait4ar+6WQ4aoxDY+ZN6VQGG1Ge7WY52tcNn3WyT502AYc6cYWVNfFEVYKmbG7kxae323VtMVYfmfl17yalSd5JyrPSpEwtL6unrakO3AUu79KoDO031pQKWpnravV83pu3wWbGwtDsKA3yuAJaDg3kvR/gOhiIpgCWfsdsBLPlvGZwnCmAxa0eRtDM6BbC0Q7X8ZwpgyadZ7hPFJZRLsczybxYLSyZZgltD8Ri5z3aqfB2IW5gsLJ2iVafrKYClAJZetrC0w+8FsLRDtbxnCmDJo1d26QJYqklWAEs2K4W4o1yXUP5bBueJAlgKYCmApbNzrbiEOkvPIamtuISKS6iO8YqFZUimZHhpASwFsBTA0tn5VwBLZ+k5JLUVwFIASwEsQzL1Wr60AJYCWApg6ey8LICls/QcktoKYCmApQCWIZl6BbDMp0DZJVTNCgWwdHZeFsDSWXoOSW0FsBTAUgDLkEy9AlgKYGnJAwWwdHZeFsDSWXoOSW0FsBTAUgDLkEy9AlgKYCmAZRCnXgEsg0jsbr2qAJYCWApg6dbsar/eEsNSYliKhaX9+VP1ZAEsnaVncm11Pl8SIPHJvVLTjOfWO5DyVVlmB1JfK6Uc3/NnTdRluqyqL07V73fZcIgZ2UFTr7KtOZVSfy/3ZtrWXCcDOGAvJ9Mv1Pvyl79s48aNSyY4x0wcddRRyeUpyGGhdQf5DXUMy9577518xk3VHPeEqOuLlymphBtquRyn7Pft5rDEuky/df3LzcPCQZF1B0ZWZajmN/jsc5/7XG1GZdoW07WdBIUl020qF7tzbuJHlGY+o6oFDvLLea5TZetQ72CtLuqSoLUSPNttt13IwlmXur/qbI7cyVoASz6HFcDSd4qsDuVLpSAAB0E/VNdQA5bcfqPwOGag7mDCqv60M591YGRu+zpZvm5s2rHMtysDObWZy+uKugUtY9LqCIgCWDrJHYl11TFRASyJBHTFCmCpp1nJw5LPT516osklVCcDCmDp1Ai0nhcFsLwjLNpyrgJYcqjVXtmezHRbAEt7g1n1VAEsBbB0jps6V1MBLIMXw5I7asXCYlYsLF8zdEevXQWwdHlEikuomsDtmJA7PVTFwtJpiqbXVwBLASzFJdR3nlpxCaXLjQJY0mnVVskCWApgaYtxKh4qMSwlhqVTvNSqnmJhKRaWEnSbMdOKSyiDWA1Fi0uouIQ6x02dq6lYWIqFpVhYioUlV6IUC0suxTLLFwtLsbBkskxt8WJhKRaWTvFSsbD0UaDsEqrmhGJhyZhpxcKSQaxiYWmbWCWGpW3SDfjBYmEpFpZiYSkWllxBUiwsuRTLLF8sLMXCkskyxcLSYuVbtjV3iptau0rLtuayrbnsEkqca1UZCPmNPCyHHHJIZUKzuqrJjLvtttsmvrnaTFhn8UmptACWzgGWkSNH2rx581LInlSmWFiSyJRcyNNT2TbrEmD1uoUlnvOdkAEQ0tOFPB8kaayjUTLhWxRsZ870atCt5j596tS1MLqEOsFnxSWUyWFz584NT4waNSpM6Dlz5tgRRxxhRx55pJE6O/XKASy8k/fNmjUrfPPhmj17to0ePboyHXKrdjDBmPx8+FsTjf6QZGj11Vc39TO1PznlaP8BBxwQPnq3n/RqE+3hQxnas+OOO4akSWq/n9T62wMHnrvnnnts5ZVXTqZR7rZm3jFmzJj+sfd0pZ9qT47wL4Alh5uqy0J7eAZaMj7MHc1bfmPeSoB6Zc14XnjhhWExofHjN8+Lfs5QB/9nzjB3coBraqZbL3Pox9ixY/s7jQygf+1e1E2bqYM+8v8rrrjCdtlll36atVt3q+c4koC+xPNeso3f4znDONx7771hPvurTp5R5rnnnrPVVlvNnn322eRu5LqExFsaF98e8WAVmKlaAIufBOgkT/T7DjvsEGRgjnzOTRwHraAZtNOlOaC54vmc37Aw3nfffbVylvJ80Feez3bdddcsvVkASyIbCzT44vpNmW4ZDAnCpmpzAAt1cb7DIoss0l9tfC5DVfua2sB9KXpNHtKLI3xT+5HyjrgMdBJgkdKos/j4Z5uSJvlVmyaYAEvq6icHsEi4QnuEFYIrVn45Ckx9LYClHa564zNSIBqXWAEK1MRPNs3NGCjzPHPm/vvv7wpgkbKiHyj6qtW3BzUp1ItBl1eUOuMFEAMg6uQFb0N35Av10w4pdS1O1Ba+tTAUYPTKt6oPsTxjPqN8n3nmmeRu5AAW+uEXkPCc5zPfJ9+AePHZqi+S03xvv/32XQUstFeAhTwsMVD3ffDy1tPM82IrvSk+y9GbBbAks3FfQQ2GR8APPvhgOEckVjStqp4+fXrWOSIw9J577mmPP/74AtXSDt6bg7gFEqray0GB++67b1fNwbwXpXDppZeGvnjwpTZVWSQ4LC1eXWkya8LHQO7YY4/NOpRu/Pjx4RAvvpsuveuxxx6zPfbY4w00KxaWJgp29z5zg3l2zDHHLPAieMsriJhnOGAO8BFflKtyZVDffvvtFw7ZzLGkbbXVVv3KLoUSKJD3vOc9byjqLUAp9ai/ei4G1Sj5W2+9NVSV2h/mJp+US3McOXPLLbcs8I7YwuL7xr1NNtmk/8BI3zZvqfXjCcDjPX6x19RGLAsc/pdyCSDBZ8iaqoWk+kB9shbzfcopp4RPDLJa8dm//uu/BmtG6rjwTvrirSVN/YJmHJiJDPTg2FuO4jqgL2Oj8Yvv+zmneuCzP/3pT1l6k74Djnrt6smgW9C0THSadGLQ+P+dJKiEK8pawChG5ELCqe8V0KEev9KEITC7plokUt/ny/HOQw89NMT9yEzoTcOezhKa9E8rX4/6Va9WOqpHK7NVV101mOpTJziH0UHjlEPp9K6HHnqo3+0Ut03vTX2/AJwvL96qy13Tzhh08hnaOmXKlCxg2Mn3V9UlYIFr57LLLut3Lfp5orms3/R/WfL8ffEhq0EWB5of+ps5w9yJFVYn+ik+e/HFF23xxRfvF/B+9Z7LZ97VQBulRNRe7udYB3NWvpJd73znO4P7Se/3Mkf98YuqeIEVAxaBAckz7kMvXBV8p145B8Cm8llMV57DMs9HvOXbJz7TOInPLr744uCuzJHXyLowAAAgAElEQVTPuQHh0IrgZgFwjZesJZ7HY2tSvPikT0OlN1PHuxPlehKwEKOCya9KKAlB1iHMdolCvWIUlC/WHN4PE8DU8vXmKETaIsDC37RZpl+Y++677x6QX7ypr7zrsMMOCx/aD029cKRvap+EFDQQYOFv+itaix5eoIk2a665Zph8qcI3B7DIqgVgwews4SVF4q1eOeMTC+YCWJo46o33Nf7bbLONXXLJJQsAY6/opSy1koSnBFj4W7TXPJMPXgoDXuZv5gwLik7Pf9onPgKwLLHEEv18JrCv+ZBDJb/Q8qt+1SF5llpnKmDx8gz3BoBF81cWSQ9W1E4vX/280vjQB1kyJM8EWGbMmGFTp05N7UpYsNSdCB1X4vkMMOHjNLQY5JlYZ9A2LdqqrOPiMwEW8Zniq7ifeuUAFt4Hj0EzgItcdp628eLcL9I0T7yOQW8yJlVt7pbeTKVNp8r1HGDxAEGdFPLkHp8JEyYkr+RzV2IzZ860tdZaKwAWf8l1wf1U1K3VU7yKh6kQugjfVua/gQyyaCbAwkSMlXkcW0B7YfYLLrjAUEAebMUWDS9wqRvAIpCXAhoALACcFAuL6Ai91llnnTeQZeLEica4pIIlvworFpaBcFnfs5ipWY3CN/5CQTAukyZNWuB3KdOddtopKFIPBBhrKXb/EL8TiwEPrLTSSv2WnJTW58gAeOjJJ5+0ZZdd9g1V0w/64y0/Te+nPuQVc6QuTgX6pW4kwPqXut2Ufr/88sshsPfKK6+slWd1fRDdvEUlBlhS9FK+kydP7reON9EGwMLiMOWCjrhQ4LPzzz//Dfz0yiuvGHJAcspbKbyFxcu8qtgq8RmABRkYW9hbtZW+0KemS3SFVgAWaCc6ep0nMJLSBulNb9mUbuE3+Ev0aWof93PmTEp9nSrTc4CFjhEohXCKESb36hTnQAniVySACVbzvF+o3A9gikJWe5gUTHiElV/R5wScDaRvClQWE2qFqx0dvl8CBt4lFCuNut0SOasL6mzXwsLY0HbtutCKxLsOUulVLCyplKov51e+uISkKJrmCLSXhcXHHmiOVwVXcy93J0ZOD72FhVVvlSVC9TX1T+WqVvyyEGqBkBNwm2ph4f0CVriEACyyiMSxHgIhsp7ItaA+qr3USR184gDrnPks2uRYWNRmuR4lh6QPJLt8bI6ewSUut7jvC+2o47OmgPAqvuqUDIx3pXrAIvkt17z6Tb98gLHKeX6NLZ45c6NXyvYcYNEk8ZMFYvnVcw76yymrQYbxvLWA32Vm02ROGUAvGHheDEWbACysFgUkctqZ8m7RSxYWATJtzZQ7yJtJNZk1WeOJov9LWAjQUTcWFq0uUiwdCDgCLlMsLF7AAVgETiSs5IdOVSJemRQLSwo31ZcR6EORwDfeYghttUvF1yA+8oBFPCMLC//X7hnqkduIOaNgwBxLZ0ovxQsE3RJXEPMZ7aE/sTJoVbdkB/1Rv/0qOAbNTe3MsbCoLsWw6F2ip0CNf6fkkO+j5ILkGfe04NG4MI+xFvAdWwvq+oS8WGWVVZq6vMB9AZbYMh0vpLzsAuSxcPO8RaXqlxZA3iojC4vKpTSSvqRYWMRXnmYCi1qsaz542ktXiE+rFtFDoTdTaNOpMj0JWIQaPbMMBmARUX3QrVeK3C+Apc9aJAuYzPmDBVhiASeF0G58QQEsnRElPuhWCmu4ARZRgl0VCrrlN8mATgIWvSsXZLcDWEhOx9ZW/05ZIqriOuLFU68BFu16lALnuw6wQF+sKwq69RaW4QhY/GLLz1wBTPGqQNFg6s3OSJLWtfQcYBHq90F1dYPRDQLxrnZyPVS1RYJblgg/WYbCJeRN0T7CXysPCS9vDo3393tfqRcYnTKHthpT3AFrrLFGZSyAXxmm8kVxCaVSqnU56Ii//6KLLmoZRM7c8gGSPt+PjyegPv4vKyBvl+DtpktIvSTR3JJLLtn1HEl+AZQKXHJcQgJbJEFjTteBE29x0Rh5cObnueLaNDYal267hNSGVnxWZfminYcffnj4yPXmAZn4TLJa/RkKl5Da7909vk+y0ilQWG314FOyXGOvvqbEwXRGGnS3lp4ELN3tcnPtcglp0P2E9SY3oVkpPq80Y3MydXjXBe/AJZJjXm5u+d9LqF4FnFVZIuI21rmEYjN/lftqMACLfN51QCOHPh48Uh9jox0CBx54YHJgY847W5WNzbx+peT/xlXBLhYp8dgn36n2pNbjXULEsPB/KbOYv7xS4F7sEvIuHglj74rlPoHa3coPoTHAJYSFhf/LVK8Ej1Ur11a0imVDrEhSgYrekQtYeM5vH6/is9Sx9i4hnvGgBnq14+JN3SUUux7VZvhEgMtbE7xVSC6h2L3ig1JVn97TTcAi+bnooou+IbWDFohxX6rGyLuNJA+8Oy5ebKaOcy+XK4ClYnSaAEs8cVVFkzATYKE8bieyw0ooVoGAgTAOzEqdbOnjw/+bYj20yvXbmuPto3UAa7gBFk/beEVPdmBAi195DmQs6p6tE7BxeW+ZALC89NJLoUjVirkb7WxVp/Lw4BJiuylzIAYs8fMSpH5bc11f/OqRusnDAmDpxtioDQAWLCwKWlWfBkJbD9ZEMymZnHqHErDE7fTyRHlYUMJ+ld+qbzlBt9QD3eAz4kska1tZEMRnAix1u4I8aBwMwCKakFMJHeBz1/D+KmtIHLMj4BsDYP5fpUukD/yiIIfveqVsASxtABbPEGKwmEni3wVMxHgCLGKwTgMWKUMPWGKrgtrkV108Fwfd+vsLE2DxlhrRBqEGWAG0iD6dnqwSSOIF8UBM23gFSBtjC0tsbep0W5vqkwD0gKXKIuf7KrrGFhZvoVS//CKAsQGwsK2Zq9PCV3OGGBYBFg802qW1n9sxT3leaKI193sBsPixEc1QviSOE2BJkWc5gEXjID7zY+FBi/72bYwtLFV8JtoPBmDR+5nL0MxnbvZ9kVzQAtm30c+nmG/UBz8GAt8p45LCh0NVpgCWNgCLHlGEvHyOWqHBYNpC6AWeZzgBlk4LXd8dmNoDFn9PClqHsck/Snsx7fsTrj06X5gAS7xtVas4AZZuTG7o58938QLWr5r4PU7sx32EGwrV8+BQW1rgJfiFGJbYIieF7NMDiOfjM6tkeVCcS9wvVvSsSLGwdGNsRFPSqwuwVM2ZXGEdW2Rpu2hAH3POEhpqwKK2+7HhNwALYBL+TL1yAIvklXaj8Q7fBm21ppxkrmgswOLnjJ6PQehgABa1izwsyvYtK6pkkPJm0R4dvOstrT7ORXIjBih+LpYYllSuHIblmlxCHqHHyDwWcHGci+4r6LbJfN4u+RQc6/OwCLGLwb3Fxb9HgKXKwrCwABb1vWoslZpfQiFlDHIVqASIj0/xPuc6OmM+xmXB5V1KKW3sRhm5BQiGxDKnK8Uqx3Zbdq9AO/XFA/xYmVA3QbcrrrjiAsG7Tf1KHRspQFxuseL1K3YPLJve7ecadWiM9a4qN0WrOocSsHjgFY+Ngm5JTibQ0ESbnG3N1AnN/PZ5ybOm8VUcn+ezOrk9EMCi3aVN/RZgIREhNAC46BrIAtZbNsVnir2Kj7poamMTTZue79b9YmGpoGwTYPHMzsDCcCRmwhwaXxLcsQKCgZZbbrmOm7X9+2FglBu7HvR+r0iqTIc8v8wyy9QeYrawABb66S0sUhysdhlPxrIO0FVNxtNOO8023XTTxnkK/RRPxKF8Dz/88ALPeEER+9YpSH4gr9xzlWdjA9soAO3I1rrUUkstQDPxV8x7esUTTzwRTkeX4tHvik/xAI6/SfLFO7SlPhWwcfCbVwpNXeRdjIunvwBmFYhqqi/un8pfd911tvvuu4cVtBRLU11DCVjUD4EHzRlowtgsvfTS/RY2T7u6PlGeeZNyif4c4sghi1Ls3jJRVw8WSWRgFZ910sICz6SMo4AFWYg5zJVvtaOJp1dYYYWga+pci5IHXo7AZ7wnBxxzKCOH0/baVQBLxYg0AZZ44OMtfTCdhK4HCGIm/aZgPr4HgqyrmCpO1ayVq1cK/Ba7HWIlsbAG3caCygtfTfYm4eHpnrOrQFYVts9jMfDv8TEb8RlWaqMPRB1qgeIDL6tcbD42SPzvXT7QWltL1Rc/NvGWTQ+CUvuOskpJUOitHn61Gs+Z1PeqXFVdvAvrEluOxQ8p9Q4lYImtkV4OestYSj8ok5PaQaAXmuFK5PKySa410dK7TySPq4BhJwFLar8l/1lMQgMAFe3wbsLYDSQZod2l/l3eaufrocxg8llq/wdSrgCWAQAWTeB4e1oBLM0sOZC8DXVCpvmtfy9RB1i0CtMqMrXOHMBCnfBIASx9O9lSAYuUVMqq2o9brwOWHGDcq4BFY5MTT1UAS/uAxVu6UwFLt/ksVVYOpFwBLG0AFj0iX618kTrkLbZKSEHFLoZOW1WqGMGv3vz7q95dFZjlY3DqXEi8d7hta9aKsGp1K4uX3DcpEywHsCiI2QOWVubautVrO6valL60W0bzQf2rihmg7ipXmx8PgcYqAaukWVo9prQ1FbD4uqpiajoxX6VcqB9rAScp0/dURT/UgKWV9VFjkwoocwCLZGhslfLW6phfWvGZ6hsKC4v4jOBuTp+Xy57f5eqJ+6KAdOK3sMrGQbfxPJAsF59hycuZM+3wWcpcHGiZAljaACw+YBOGV7S3/OTxfTGiBPFAB63d5+OYiBiMVNUbg5iFNYalnRWip1cOYBENFaTH/2NztXcNiW/iWJCcGJt2eSbnuSpAqzZ7V05crkpIxwAux/8et7kdwKI6quZMzjyO54t31aJ8CTyOlWYrmrejSDqVOE799tbHgbgncwBL7BISzTxI9oBSbjhP/yo+GwrAEruEFESvMAJtQRYfSAZzny39ciPHMsL3X3wmwMLxDDlXO3yWU3+7ZXsSsPg4Cil7L/A6sdJpRTBvLYh98EK+YjraxfHgd911V9japxVIuwPSqec0UWmv/Ltx3bEw5n6cFlrxBn4c4nrYgkfKfCZS6tWOSyg1Nb9WI+qfstiqbTkKIrU/OYBFdTbxmR+f1Hb4cvRTfe9Gn2MgFdO5nTa3esZv/83pz0AAS6v2SLFozktJeLDDPb8T0CtQH4+RSqt2FEknAUtqO1PK5QAWyZ8rrrgixP1UnXCdwxOed+O2wmds0WfnWzflOXyJheXZZ59dIMA7bo8H655mPuZKsttbh9X2weKzlDEfaJmeBCxCxzFTefPfQDte9bzeu+qqq4btZv59Xnnob30rB4EyFtZZIbrR5ro6/WpcoMO3y9PYK3JvUZEFJo7Ij11eTBwm3mAAFt4Tm89pnx8T/V+/+YBar0w6OR45gMXzmaeZ7wdty/E5e/eQF9y+7wMFQFX0anpXu1Ygb6WUsoqDPFP70y3AEgfT+pWwp5XmEb/5uYQiede73rXAtu4mnnyzAxa50epkQCpPSLdUuS3hM7I2s4W624CFw1y1gymWV+IFLxdkYYl5yv9fliTNm8Hisybe7cT9ngMs3jLgJ7gX3t1gIt4rAbTWWmsF5ctvTAy2bHLst0x2XjDxW1XQbbetQLmD78EHfyt5mX4Xk3sFVEVn6MAWxtg6k5qDQO3GwtLO2SO8x7eLdsQHtXkApknLMzGQyaVhq/KcIOuT7bUCkjl8ltJG8SX903lIMahOqacTZQSc9H5v4UmtX2OqvmgMc5SRf1e3AEsMfjV3JKu8dZb5JlnCN31Bkey0005ZMSztnNbcyxYWZEDO5d1o4gu+c5Lv+ffpuVimxMkzU9qYq5fYHYTFhLPB/HxFvipxXAxaqlxClPGBt/AaOmuw+SyFRgMt03OAhQ6hFJVrocpaURUcOlBC+Oe9qV5CiPZwyRTplR+WFQ5lU7Kpbrcvta8S+Npu6pG6jyOIwYzuKV+Id4PFdQn4aCt41Yqlqr05LiGtpshzwHsYC37zgWWy+gh4akuw92V3E7DkWFhEjxQ+SxnrGGT6FRb9b1eYp7ybMvEBhd56p/mbAzZi3uQdUv70RW7O1PZ1A7CI96rcPR6wSGbAn/EiZrBM9b0MWFKtslLIopkHGpI5uXFOKu/logB2q/PUUvmurpzkGQkKASx8S27pmRj8aE54C4uvn/te3vt7g8VnA6VLyvM9B1h8sJA64IUDgz1+/PiWPr+UjleV0XvWXHPNsPoXQvVlfS4MysNoKF8mHpYWrzBzEXe77a567rXXXqtN/ka7Sdg1YcKE8KgHLK3aQLmZM2f2P+fLYpXiXAwJ8Ka+QDNAXkp+DAmkGTNm2Nprr/2GqukH/WnlQvEWlm4AyksuuSTJwkLjPZ9BA/FRzGepSl6gBGHL+FRdrLi0ym8am5z73voYP4ciGDdunL3yyivJeYbUZ+Y4famiAXOQvsLjKVc3AEur98YWlhioyMKJItlxxx37LX8pfcHCwtEROVcvA5ZUCwvzlzkOzXbeeecFus89+AU+y7n0XBWfnX/++WE+w7+p8zBH3sMjTz31lKFr/FEbtL9Knkl+YWG+8847QyoA/74qmTbYfJZD+3bL9hxggcggRVlYpFCFMKVcq7YOt0sE/xxCXYBFpmmvCKu2H+rgL1lYqqxCnWhbTh2ik+jHt48nkOledYr5PeNLkXqBG1tjtJpmiy5ZWLlStmi2Y2Ghft7jTe+x1cS7JDyv+DZ5i0QOTVuVzbWwiM8U8S/Lgd6RQsN47NT3WHiJDqmCN4cmno88D1WNQ2q9etZb63zsR667qxuARQuTuK3xXOG+H0ueU7I9AkgBLCnZUUW7N2sMi7bKa1uz6NopPhNPSZ4QdAtg4fdO6xrxA7uDiJfkW/wU77qiPZpXlMHCokWOeEJlhprPUuf3QMr1HGChM7iElOmvCrXGu4gGQoD4WYSHdry0C1g62Z6B1OVdOTFg0U6aXMAiQaGJLcDCxHvooYeS/fHtABZcQrwnBiwSZvRlOAGWXD6r4wUPwLzLTuVjc/NAeKrqWSnpKsCisckBS+qP+iLeFfj2YDylL70IWJg32vFSAEvzKHqXkAKVxVsevLTLZzFgkcW0G7rGu4SwmMSAxQOPGLAoD0tVmSrAMph81jyKAy/Rk4DFr9L9bgGATKoZeCCkaXXGS5XbAeXLeSU+cVw33A65fWISQq+YZlJgXtH4iY5JEmURryziVYBvz/rrr99vYUlpJzTjTIwUl5Dqw8LCe+LLKzZZt/imfwBfub6k8FLal1uGM1E233zzrMfgM4E8KWmv9HMq01hW8acEYk59OWVpM2PAwXf+khk7Bs6t6lb/Ne9jBaQAxRzF1A3A4vtA//gQixCPI+XUfw+m+fvaa68NZwnlXF/+8peNT87Vqy4hrAXIzZzrqquusne/+921MiCHL8SfVdbMc88915ifORchAVUL7Lo6cAUhz2KXUKtYOwALNKi6fOyY7g8mn+XQqt2yPQdYqhCtfjvqqKPs61//ev8hTjnMmUIgCV7Mjssvv/wCwid28+jdYlB8qN6NlfK+bpaRW000kyCN2+3boHt+ssbjEU8K6gVI4l9WzE+KCZVJuvXWW79hslbRRPWxEuU9vM+bSb2ri+f9+TYIHfrD1arvAx0LFA8KKOWSoGSFLT7TczGfpdRX1S/9pvNKfKBySp2pZbRDa8stt7Rzzjmn/5BNPz5eeDbV26ovPLvBBhuEgwnhiapcHFX1dwuw+LnhwXRq3zks89RTT81yORBTQdxQztWrgAU6VR0YG/fNA19ozgJMMsBbRlrFsNXRyy+IJSPYpQONFSid6p4FfAHCUi7a2moB7uOgfH0scFoBKc97+nuw+Cyl3wMt03OARR0Sk8h1gbI64ogj7Mgjj+yqlYX33XPPPWE3il/t+hWs96fnCOOBDlbu80wIaMYH+nl/bN0kpG8yh/rVgszwqiOeUAgRgEIKWKEf2tIXry7q+khbECSyFmm1SjtiC4sfE4Q1ORXiwMdcWjaVl1JoKqf7OXyWWiflBFQ1XiSlAhTBC926AC0k2TrvvPP6XbkCr9pB1M676Ys/BA4enjZtWvDhpyoR3tstwKI+QWvyNuGujJVmvDPPzxtiJIiVSJ0z7dCQZ3oVsOT2h/nPJV72lgjJgJxFrLeweHnCO+J3pbSVeDR2/TRd4l3aH8dr6v++Dlnr6RtByriS/cLRW5VjCy3vGCw+a+p3J+73LGDxE1uuiMMOO8z45Ph8c4nEALPbBcDiBVIVcvWTI8cUmNumdsszMQ499NBAsziAtm41Qj+UUyTuk5RgLIRpn9/emdLedgALQkljH1tYNBbxmDBZ6U+3xycXsIjPEHB1vNVOm7XqFx04r2SppZbKUvAp4+fLMC7Q+cILLwzAkHaL3waijL0FQzJAcT85q+nBAiwkAYsVZtUcgnb8Ds1YHAwWmJaVVe/nO0fB5/JFp8vHAam+P63cKHXt8CAltorF70rpSypg8bottmBXeRg8IOEdJM9sGjdvqRwsPkuh0UDL9CRgqTOLH3zwwUaUfLevKsbrpjuhm/0RzfzklsCqYvpWgKWT7cwFLO28W0qhFwEL/ekkn9XxJ3TW7rV2aJj6DEKRnVLx1Y6LS4q0CrDlHrJJXUMJWKrmmuZiHc1SaZ5abmGxsKT2d6jKpQKWgbSPd1QB4yoQOth8NpB+pT5bAEsFpTqpSFIHolvlCmDpTQtLASytOb4O6BTAki8pCmDJp1k7TxTA0g7V8p4pgKUAlgUoUCwseRNIpXNdQgWwFMBSLCztzbVefaoAlu6PTAEsBbAUwNKBeVYAS3EJtTLVx7FV/L8Alg5MvB6qogCW7g9GASwFsBTA0oF5VgBLASwFsHRgIg3jKgpg6f7gFcBSAEsBLB2YZwWwFMBSAEsHJtIwrqIAlu4PXgEsBbAUwNKBeVYASwEsBbB0YCIN4yoKYOn+4BXAUgBLASwdmGcFsBTAUgBLBybSMK6iAJbuD14BLAWwFMDSgXlWAEsBLAWwdGAiDeMqCmDp/uANK8By3HHHGZ9uXxwutcIKKyzwmuGaOA56HX/88f19idM4VyWP4yA/zp/IybTK+S456dI5xG6PPfYwvlMv6uc9qRftpx/0JyeBGQcy5iZbawewVPFZU984q6RqXIY6cdxmm20W6OyvqpTh/v4yyyxTey5O3XhVHUzaRDPOkpo8eXJTsf770Df1TBgeUmr+XMBSRbOmRsKXOQeGUl+v5mEhm2wsZ5v6P1j3H3/88ewjYHLnM3zGYYY5crYkjnstsMCOa4wbMYI/Lpzx6ut877B63gFbg8VI5T1DS4FOJfRC6HL+So7wpbzOeKraJppLmbrsvwcddFB2RuV2AEs77eVsoCowNdSApZ2+1B0BkVtXU3nolXpmFXXBk2THja863m8CLE3ty7lPpm/4M+fqVcDCsRQo4KG86sZ0MOZznQxstbgqgKUAlqGcL8Pu3QWwVA/ZYAg4AFYBLPlTpgCWdxgn0PfaWUIFsFQv2gpgqZ/jPekSyhdJ5YnBokABLAWwdILXBiujMm0tgKUAljqeLRaWTszmwaujAJbBo/VC8aYCWApg6QQjF8DSHhWLS6g9uhXA8saDSTtLycGprQCWwaHzQvOWAlgKYOkEMxfA0h4VC2Bpj24FsBTA0lnOKbUNCwoUwFIASycYtQCW9qhYAEt7dCuApQCWznJOqW1YUKAAlgJYOsGoBbC0R8UCWNqjWwEsBbB0lnNKbcOCAgWwFMDSCUYtgKU9KhbA0h7dCmApgKWznFNqGxYUKIClAJZOMGoBLO1RsQCW9uhWAEsBLJ3lnFLbsKBAASwFsHSCUQtgaY+KBbC0R7cCWApg6SznzK9t3rx5IdU1aZu5+P/IkSPD33PmzAnp3xdZpGTh7QbxU44fGCrAwnvvueceW3fddQMfqB3wCf9v5xqqTLe0GT4eO3Zs+NaRBmPGjOnvW1V/mAfPPPNMz2W6pR9cs2bNCt+0k/HRPNac9n2izMUXX2zbbrtt//yO+zx79mwbPXp0f+py6udd1EudkhFNYz+UeVjgMfoqGuhv0Ykxf+21vuydKdebFbAwRxhvxh6+EM/xO7SFjvE1EHnW7USQ8MXUqVPtjjvusClTpgQe50Pf4r5IB9Kf+++/39ZYY43QZ6X011wTT8FjyETuQ7NtttnGzjvvvH6apfBZr5bpyW3NfjAgnAZSk98Dml4l7HBqlxjeA0Paj7KoEgJVZ1+QMp/U+alXTmp+KfSHHnrIOK/FKwCBDimvnPOMhgqwQCMELsJJlwCYhKxAjVf+lCVlvI4zkBDn96FKzS8lorlJnzxdvYKOlffvf//7AFi4vFAWGPHgWP2jft6ZClaoeygBSwzgRBvNLcm6VL59swIW6Kj5ItrFmXv9fPAL3SZQUyXPuglYxLucbwUAWXTRRfsBi3ie9ot3vEzV8SSxnI3nGfVIdjDHOAYDOlTJ9FSZ3QvlhhVgQWE9+OCD/cIt59CoXiB2r7YhVnZYMVCK3QQskyZNCofl8d10afI++eSTtvvuuwdlpRXrcAYsG220kY0bN64fbIgOWm3Fqyjuc5CfaNYtwIIFk4P5mi61E/7hrJ7bbrstKJVUwMLBnNOnT1+g/+JFgWeBMdW58cYb24QJExYKwMIcW2+99RYA4E0033vvvY1PzrWwnCUEb4nP/FwRj8TWX+kHDhjkU2eFGSrAMn78+CADJ06cGLrj21G3AHnuuefecABw1XO+vg022CA8g9WlAJacmZNQtpW59+CDD84+lC7hlaXIfApIKWjlK4Uoxan7nbCwtEt0FFmsEIebS0h9rzqOXitt9VNlJYw9SPE07KSFpZ0zXjirBsUYXx5cSojKQur7KlCqMvS/yupQRbMmXhpKC0tsVfJtZeXLXOv2tbAAFuiUymee12SV8vKM+7JADDZg8WBL89bzgOaMgJi/Vzc3pTfFbzFP1bnyu817na6/5ywsXjCLqVBIMNchhxwSPqDEdpVUpwm4sF5XOBUAACAASURBVNXHZFFsQdVE7lQMSw7dmtw9WCmIb/BKL6X+oXAJya8M//7lL3+xlVZaKVgYxNP0NTZ1qy8yc6ufMvvWlec5VqRVpzu3ok8OYKEftPmKK66wd73rXWGeyn9Ou1ASssR4JeJjUARMxG8S4tBE9yTEoRmrZZ5PXS0ONWDROAmE0W5+I7bgkksu6frKd2EALJ7Ptttuu34+g6biuSqehm8OOOAAO/DAAxewYMQLgfjZbrqE9C6/KJFbXjF5mgsCILoP7wPaPZiXNZKyzAu5fvy8qgMyKXKyl8r0HGCBOK+88kowlXuzML8ffvjhdthhh9mrr75aG6jXS8QdDm2R9cSvaC+77LIQW8Ak8X7PTltY4vGto5cUNa4KAhTjuA4pBJ5PjQXwyjNe8Rx00EHZlrxcAQd/33333QGw+GvmzJnhv5iLubx1qxU/ddrCgm895YInmI+sfHfeeecFHmGc6CfzudUlYeoFLG4fnotXoNCMOKZUsMJ7hxKwaCxRuD5mid+33npru+CCC8JYV620q2jWjht8YQAs0IJFCXy24447LkAaaAK/vPzyy/2/KwaMH5jPfCTPtChoJc9y53PKXFGZOEg9fhZ+QM5VWR1XXnllu/POO8MiIeYFZAfzosr1xTuoc7hvWOk5wCKE6JlKprxDDz3U+BTrSs70aF1WFhOhc74J0PLBkD7AsZMWlhzh6y0Tsc9WAEYKPpU6Q2FhoW1aFd577739Fhb1Qbyt3TFV7jgfkKfx6DRgYRWXctEWPiiS7bffPghSb1XR/9U+gcs4PicOGkToateRaMYz0IwA75wV41ACFvol65DirkQTLCxYM/l/KnhPGZO4zMIAWEQ7+EyWPK/QFcTuY6DEY1hXACySDynyrJuAxb9fc4W2aS7LshiDWHge6ydzoEp2yhPh3eYq5y2V7fBQrzzTc4Clys+orV6KYfHCrVcIOZzbIZO9LBmYqQEsAjFVAZBxf3N3CeXQS++PVxya5LGwSq17KACLB16AAiwsdbtiPIj0q8HYTeIBWyzIuu0S0nxVbAFAQ4G3ar92EsmsLfeXdwFV7XLw4yglD82Gk0soBnCMtbavA1iIYamLS0rl46ZyCwNg8S4h+uMtKOq/n8/iJ74BLHIJ+d1DHiTUgbwm2rZ7n7YyD5gr3mJcZ/XR78gL5kCVRc7PJy+7KQv96iwv7fZhKJ7rOcACEVhZQVzPgPwNYOFTrs5SwAMWmLtqu6neOFQWFt6vCemBiwSTn6yp1BkKwOLbJsDirVxyG8D/PpBOY1RH/05bWFJdQuoPgOWd73znArkhvFCOxySe2x6w0BdAKHJA4yoBPNyCbuk3Y6mttZ5PWRTgfs25qlbWTc8vDIDF8xn9id3CMb+In+AlvxW8VwCLHzPNbX7zgNaDEvVXgCXuB88K/Mii5+tt4pHhcr/nAEudQGYwcAcRw5Lq7x0ugzCU7YwVPcIVvzqrv6pcF50ELLn99quPeDLnBtwKAPl6VP9gxLDwrhkzZhg+6bqcIjGttS1RbfaBq50GLKkuIa1SCbrdYYcd3hCn4elMnyV4fdCs3GBNoJMVKckDMYvnKO6hdAnFoFg8T18ALBdddFFWX3LnDOUXFsACj8NnuB7rwgKq5Nn+++9vfHLSNHTTJeTb2JQskvHz1iQfEO8trXVy2buY68q0w1ND9UzPARYJwFggQexiYWmfTWITapVJldpRKK0ykA4lYEnpvbe4eCWu2Am5JWIXhKLzZUKWzzvlnV4ppJSXEmPHi+IxYreAb6fqjGnvV1lDCVhonywsmr9qc53CFpCpKi9rioQ136LPfffdFwBLzpUKWCRzSORFgj5/xa5qzRXFSZAfirH0fFXlyvS7wQAsuF+7faUAllZuCT93Yvkcz7GcvuTsRhPvw2fsEhJYV2yLxkPv19zgOcWwqB9VMWBxu7sJWPy7YhAfAxTv2qL9VRaWKmuLlxl+ruWMTy+WHTaABeKVPCx5LOSRfCpg4RkF3VatYgtgqR6DHAEnJY7bRdaCFMASv7nXAAs0qHOzpXKuzNhSKn5LO8IbkNfLgMXPs1aAhXvKQJpKm3bLLWyABdcjckiuD4EmH2unucF3r+dhUYyX5/k4R5HKaFuzn/utAEu7PNOrzxXA0qsjM8B2aZcVzFzlLol9wHrdcAcs6kdV/2JfsSexFA3PKW+DhGLKUOQAFgkfv+OlVeBllbVFK9149RuDzG4H3Yo2CrodKGCJaR0DFmgGYMkZm1QLi97N2S5kVfYKUFafeDcP48ZvsrDU7fBQ3Z7PACxYM3P6ksKLddYCPzZ+MeODtmNXK3XVyY/YJZnrls2xsGg3DXyG69FbvHybq+a0AEtVpte6BVjOfM4dE78lucq1VTUe8BX09XlY6lzJue0ZTuULYBlOo5XZ1lhpx8K0ylw/nAELbVcftergN4Rbla84XqFBXn7DhAxoyYmTyBVwjA3xGHIjaGi9uVqH/3FP/fAr+Hh7psp5NhmugKXKZdntGBaBEc54kUvIuxxoE2MikEh5PVN1xov6UMdnAiw5fJYpAkLxFAsL5eiL+hhbivR7bAFT23lW8wyapeRDygEsAk4esHhayHXiz2iSu055WFQ+JfYjdz63My6x+5D/x/Fcoqvq9zQTb8KPOXmJ2mlrrzyz0AOWbguDXhnIuB1idAQNH3ZcxMquSqgMJmDpxtj41ZZfRcbKXCvmuAzlFHSrrZQpY4yZGmHadPE+xcvEO178ai83QK4XYlg67RKqAtR+W3PqChOLCcCt6RL44KwmAIu3GMSWlbguAAsB1OIr3ZdSquIzpebP4bN25kwTYPF1topJ8X3wYIy+yuKRAlSqlG/T2MTbmlU+thRVWXl84rh4HDtpYUkdG7UBWvlDUL3MjumoxSeApWoHX52VqYmudfdT+9Ju/e0+t9ADFg4Ky/V5t0vMXnyOqHo+PkGRb2fM6IMFWMi4uO+++3Y082LVJEPBnXLKKaHLMZiRQvTBeAhidkjxiYViq/E9+eSTQ36ElEsC67Of/Wx/2vxYcNYJoC996Ushe2wMwBYWwKJ+xS4YuR8+85nPhIM5cwVqqkCPQVIVaKoaYwARB8xVtauOz5BLH/7wh7P4DPChpI4pvEaZJsDi61H7P/e5zyUd6aDyZFk9/vjjQzZVuTCb2pdjYZG1BGDIXIuvVvwgmlWBk04Cln322af/JPWmvtNeMkSfcMIJ/Rl6U3ga3uc9Xp6Jv1Keb2qX7rfDZ6l1D6TcQg9YlGZ+IEQajs8qpX4cqNy0IhkswMLEQ8Hz3ckrnrQ+P0i8+vKmeq0YcR3JpK37Ke1LVYiqS++jvVUrqzpFyWmt7GLh8qvFhQmw0LeqFbzPteHN6U3j8+yzzybxmfjjpZdeCsraW3BaWQ5i60lssajjM9qNiymHz2L3RlPfcwAL7RbfKSDc1x9bX3w/AWwAENLj18XNxW3NASw8692lPqhWMUC5Vkkp/SpF345LqIpmVePj+QwaeOuf6K+5LZrHi62qhWYKL6SWaYfPUuseSLmFHrD4JGgDIdRwfBamrjvOoCpGgD4OJmBhtdRJwEJ/FQSpCR+f7iqA4GMT+E1uGtFAK/xOjzv1KsMl79RqVAJI7aZ9SjimMjwLYPE0kyl+YQIsHqwJNPhdE6kreI0d7p0UPhMNX3jhhX7rAuMhhaYYDbVPyeBUpipWKgae8cGtOcCL/vgkaKm82WRhqZIF3l0pAKJDG2WR9O8HFK622mqBP1OvHMCieC7NS4ErvUtgRTEg9Ikykgf83e2g29ykhvAlNIN2HoBUjUe8kPL9gofic6pSx6CuXDt8NtB3pjxfAEsKlYZhGbmAACyccC2TepOPeTgDFj9MmtC4wxDYVQHHUibxakXBlAJA3Rp+gRMvWKt88N4Kg5AjxoJrYQ26lTKqooWUJv1v4uVcwKLyKN0ll1yyX4kIIFWBC8UWxCtgAV8p0iqQJaCcw2ftKJImwKJ+i+9R7CjfFVZY4Q18Fs8x8SA0W3XVVQ2wR39SdgzlABb/Xm9p8WMTz9Oq7b5+HDR2nbKwpAIW8S20gmbQzs9x348q/uJ+LtDNlWHt8FnuO9opXwBLO1QbRs8AVnALMXljpV3F9MMdsHhTMX0RYPEuGK3S4t0bfmUTr4y7MeQSlN6U7S0l8WqSvsWARf1dmCwsAmMekPjx436OC65dC0ts6REIFi8oriJ2lXgrmfoS7zZS33L5rB1F0gRYfGCw3JMKbvbKUfzqLU4CLNCYHW8o4dTxaRewiP5VbpLYUtkEYurcSO24hFIBi9qEK4hAbQCLB4uiOd9enlWB4G6Bl3b4rBsyMq6zAJYKKtcx8WAMSKffUQBLn4XFC+UUwNLpcaiqLxewwJeYj30My3AGLL7/MX1is3gMLnPGZ7AAi3gsBbDISpADvOhzO4okB7BobryZAQtjkrrrz/NhO4BllVVWCXO6AJa0GV0Ai6OTgIoC4eItcFo5VJkQ08g9+KUUdBuv5OpWdr1sYfHK2Y9BXdI1xlOpvKsUQ2xu9TTJXfl2Y2TjNuDHfuyxx4xtujEPDgcLi8zechkod0TqWUI6CdqvNFPongpY/MqXoNumORPHIPn2NbXR9z2H17oBWGIa0h4dG1FF36oFnYJuU7aPq86BWlhSxr6dMsh/ktNhnc0BlLmABb5cffXV7ZlnnnnDe1qB+bo+dVKetcNn7dA695kCWGooJkblG0aID5HKJXSnyueCpV4GLLm7hKrMva0sDK0Ai5QE31pVMkZVO286NXbt1OOFEP3xytf76IcDYPH9j8Ghd0/SFyl/v1siR3n4d3ULsOgdsaXMW1jUFx+g6+MocnmiHUXSZGEZSsCSeyp4Lr1alWfcyE/F7rNY3rfjEkrdJeSBsXejaUGcciBi1ZgJSHZCnpVdQhmcVueSaecsodxdQqBrGEZCJQ7MGm7uol4GLKm7hHyQndjIK2iEDmNWZXVoZWFBUKFIFKAcK8RuB7alTAkPWPib1Rirf67hBFh8P7RTxit6T2sPJj1I1c4pbTtPoR9lugFY1F6lTPfxLB6w+L5IIXn3pHaMpfZlYQMsqbmLUumTU06y3Mt0WWsBLFhY/O7BprpTLSyKX2L7vLaC0wbFSGmDBO9LDSynbCflWTt81kSfTtwvFpb5VPQMI+HKLQlVbRsTmOkE8dup481qYWF8sHJ5+osWUhbQM7aQ1AEWykmZePDD3wgp7nd6q2DueKstcqHQXuUU0W/avtnrFpY6cKI5pmBP0Ug5V7wVQ9ZOWcWqzmGponE3AIt4p8oMLx6UsvGKRP31QMxbcJt4pB1FUiws1VT1Fha/EOL37bffPriTU3PK8HyOhYXxZ/GBS+jFF1/sXyDzbm9hSbUqtpJn1JkLjIuFpWkmuvtDYWHhnSgohItWQl64sIrnIkNrKhNldDm56JsRsMjE6c23dTEc8VbfOsCi+ANPeCkh7vEhE2VVHFPyYA2woFZaAidUp8RxsgAOF8DSihTQ3QMW/k82X7KmVm2P1fhoTjaRuRuApe6d6gv3BVjoC38DsKpkRwzOWvWnAJam0c67zxxHpnvXI2O44447BsCis6NSas0BLPD1U089ZWuttdYCO6t4N+2Bt1O2hqtdreQZfQMEkY04VZ4BWDhTrdeuYmGJRsRvP9QKVwmHYvNurw1mVXsWBpeQBL8HI76vCB2EfjwZGb9WLiEEgxRJFe3qkusN1bjTnqeffroyZXqvW1g0NppDVWZvD0Lpj9wtsqxoISGwljoO3QAs8YpWssKb8GOrkkBZbAXMUUwLG2DpBZcQ8l3jKbfMdtttNyguIXYJ+dw1ckF53knl807Ks3b4LLWdAylXAEtEvTrrjs+0mWvlGMgADfTZhQGweBoIUHp3UN1JpU2AhXolqHzwbq5CHOgYpTwvRT/c87B4K5afU15pxxYXT592BHk3AAtt8m4h/vYxCGqz+uIXQnF/ciy27SiSXnYJDTVg8cDZj0s7QbepMSx6T93OKn9UQw5vSJ55YKznc0Ax9bTDZylybKBlCmCZT0HFsKD8dt99d3viiSfCHc8w7QjLgQ6Qf3769OnhgLWcq1cBC5Ny8803XyBba12/tCJdaqml7LTTTlsg3bYAZpUVphVgqUpEpt84MPOjH/1of1DrUALU2HKy6aabBpNxnUss/h2hqCDdVL5pZ7upjkCQEvcK2/dBAaf8Bi/D01VCOba2qL499tjDnnzyyQV27jX1q1uAxeeGWWaZZQJvxjJD/FklO2699dZwkF2crr9Vf9pRJL0KWODjzTbbrGn4unKf8ZCrOeZVfr/tttvCGT85cWz0hT41XZJn1P2HP/yh/8BID4BzAUZV0kv9xhw79thjs+QZu5d68dDgAlgiwMIgY6ZjB4sY2gthv5uhiTE7fV/H0efU26uAJacPcgWtuOKKIT+ErCHeRdcpwELd8t/Wrb5y2j7QsgoolsLzZ6r4unvdJURbY2uD38EXW7gUzOotafzN3HzooYdCXUMZdEt/PGDxIM/vaqvadq8xlbsyZyfKwgRYBjo3Bvq8X7TE80dW2xzAktoeyTMfciBgK/dnpwAL9aA3Lr300v7jWVLb2YvlCmCJRoVgp2nTpoWIb5lx45T2QzWQb1bAImVHRD0rH8ZDYAWg0gmXkLY2I0z2339/+8pXvpK0WhosXqgDJHr/cAAsnlYAkosvvjgI0//f3rX9WjZ83U2Q7nbLr9FuTYLWLpHmjbjFtZHwjCf+BN4kLnF/bf8BXvAHSEto5BOiecKD0K7poIlbomkdt9+XsT9jf+PMrrVX1dpr7b1PnbGSk3PO3rXWqjlqVs1Rc86qakoEVHIG+UBQ0DdBWkuWew7lYdGZOWakn376aaMs3IeFq9zwP5bN3nLLLeMEy9zLhCUXqfxyPGSUJAH5cEy2HSqPDeMX3oPEco5vnCD3ERJCX8Hz8Kyrr756tHPnzqUaz/JbZ2VJE5YEchh89u7dO/4mGoLSmGLXhkndt5YJC/BoClU05R215bA0hS/gYYFhWE3XaiMswB6zPuh0KuTW1Kbom/B+llzzICzQTRCpElniSeI5Mpmw5KC0NsvEsCPHty52Y1kRNGExYVmBwDwNSWmnMGFpRsyEpRkbE5ZrxqvllKBPy8fDd/PYmr+0/7v8dARMWBakIU2zq3nsdAuR7WGZz8y3VL1MWExY7GF5eJxjVXIta9JtiQwu246ACUs7RoOUMGFJw9rFtVdD0i3RMGExYTFhMWEZxOhU8FATlgU1ogmLCUsKARMWExYTFhOWBZmlpX+tCcuCmsiExYTFhKWs8zmHxTksTQg4JFTWl1ZraROWBbWcCYsJiwlLWeczYTFhMWEp6zO1lTZhWVCLmrCYsJiwlHU+ExYTFhOWsj5TW2kTlgW1qAmLCYsJS1nnM2ExYTFhKesztZU2YVlQi5qwmLCYsJR1PhMWExYTlrI+U1tpE5YFtagJy/ISliaV+Oqrr4q2S8eR6ldeeeX4aPXcC9tMb968Obf4uBy2vv7222+T9/S50y0OzNy9e3dR3d58881D5Jm2BT++u/jii0f79+9PHhiYevmxxx47evHFF4vq1QXnnMMPYyVwYGDqsDjdLVbPWMHnzz///OjUU08tkufWW28dY5Z7TcOsaWyCjt1+++0rNmfT9+m5V3xGl8NMcZDl8ccfnyvKuFxp0i3uQT/jmTc5L4NMOOOpZCdwvAN9oORCH0Nfa+q7Jc9C2abn4CDLRR3MWCpDW3n0MfS1Gi7vdJtoRW8c17xxXF9K33S0el/Pz3lOn4Slr+Po2wjLxo0bR9i5NV6p2RXKHHfcccnyOfiUlOlCWKY9v6ltvvzyy+JTZGHkoW+5FwhBCuNpR0DguAAczJgy2E2ydNlXKVcGLdeFsHR5T+k9Q50KXlKPprbRgzlLnueywyJgwmLCsgKBtq35+1JHE5bRKGV8TVj+T8NMWPrqad08LP29vflJJizzQLmud5iwmLCYsPyLAI1kl8MP7WH5n3HoYWhXvT0s5QbIHpZmzOxhKdenRd5hwmLCYsJiwjLzGOSQkENCpUpkD0spYi5vwmLCYsJiwjLzSGjCYsJSqkQmLKWIubwJiwmLCYsJy8wjoQmLCUupEpmwlCLm8iYsJiwmLCYsM4+EJiwmLKVKZMJSipjLm7CYsJiwmLDMPBKasJiwlCqRCUspYi5vwmLCYsJiwjLzSGjCYsJSqkQmLKWIubwJiwlLlYQl7pYKIZu2riYA81zWjF1EP/nkkxE2KWS9/vnnn9Hhhx8+rg7/xm98j5+///57tGnTptHPP/88LsP66mZleC7K8Z7//Oc/o3379o2OPPLIwUa7P//8c/TGG2+Mbr755vG7UR/IwTrri3UZaVMb6a6wkJ8XnknMiFOOUCUbx+HdJ5xwwhgzYMk6/vXXX6Mjjjgi+TrIi+XWW7ZsGbdbvBa5cRza5qabbhqBUKKe+KGO5GA3ZBkTlm7oTturCfqHH+oq9BYX/kffLNm9uFvthr3LhMWEpXrCAgF1l1Lt8Grs50lYMIDs2bNnboQF71OC0NewAvwwKJYSllgXbZNphAWYnXXWWRNilyNHLmEhycNuwrMQllxiPPROt2wbE5ZmLVlt+7DE8SpK1kRYQPBJVnP6zLKWMWExYVkYYdm2bVvRluk5nYhGh7NJdOA//vhjfKZQ7sy3y8ZxOK8m91wU1BEDCIz86aefvoJING3/zrqnMIsGkt4X/MbW/Ng2HjNtzK5yPBOoQ84ZTyhHT9Bbb701Agap2XvqM5xvctRRR008MZSvaUCmYYGn4IwzzsiSg8/ETD5na37OSo8++ugxZqmZrNaPbYW67d27d4S2Ydvi3ZjRsi1SxHhIwkKyAs8a2gXtQ+JOXFIerpw+1leZM888c/TBBx8UPW5eocdl3Jof+oTJwcGDBw9pS9VFBZTeTvS1devWFWG9jIVNWExYFkJY8NIcIzJLp0FnjYaUhIahlr48LL/++mvR4Y+QC4c/4sA4JVkaHkrJjgE+dfgdQxEpQgLSUuJdofEtwR6D6YEDB8bviWEsPIczPA1J4FDGK664YhLaUuJFIhTrTcxK6laqZ3gnMIuXyhCNPur722+/TcJxSg4WGRIC3qyXyoP6si3aSHIJ1iVlm3Ce9oy1RljYDxjmxSGzIMZKhKlfmBiwXRVD9JnSA1BL2nGeZU1YTFgWRliGVnR0XsyUbrjhhqJD6bp4WEplwUxp69at49wHGAzMhDX/AQMU80D4bHyGQ/mOOeaYyetIUDTXggOXGtUczwrLw7uA3JqcqykfgiQMXgt4uOKF73ft2jWClyEVV6d3gvdRJmD2xRdfJHNFcuqbU0Zxp6cOn9Fo8Bkku5qvE++dRoyH9LCwjtGAUQ7m5yyKrOS0Q6rMWiMsEQPmSsX+Efs681XQvtCz1157zTksXZWu7b6mTvTII4+MHn744bbbV3zfxbXn05qHP625qBELC1N/8Bvtf/3116+Ykairvy8PS0kVGUo577zzJsYXBiSGG/DM6GH44YcfVnhY1CPD2Rg9ATqINXksUvUGYUGeSM4VQyDqTeB3jKurJwnPfvXVV8eDKeurHhZiwd/AByQPmJHk5dQPZRTXafeQOJFkKDFB3UjOmsJC6lnie1UXtT1oSKCfQ10kvVHHlcRoYvFQ9ejzuWuRsKg+om+ec845Ey+m6jfCPuxr7O9o+6uvvno8OUA/K5m49NlufT3LHpYEkiYs8yEsuYakRNkZkmDHxAB37bXXTnILSBamGZIuHpYSWTiYwPh+/vnnSTdu9FxALngrkAyKlT80/sQGOSow6OvXr0/ChRwe3J+zSgCD4tlnn50FO2RhbByeFOCuniKuWOCgyxk+8Hr99dfHhAWXDrCMu2sF8BlkBGYIWcUwy7TKan2mlcOAjyvlEcLnGzZsGOcP8HlNLvj4jkWEhIAX5ECuUOpiHgTarkR3s5SioFBJqBKPXWuEBW2Dfk1iqZMJ9mV6W6CfKBv196qrrhq9/PLLzmEp0MuiovawpOHq4kKmV6pp0EwNrnAf4l2lg0lRIw9YWI0fQ0LRIOL1TZh0ISxdxAExxgCkdeHyYxhn4q9eFISEUvkV6p0gacNzQRDwrJJlzSUhoUhQVBbUA+/lAEqSxbZgSIjP0NlfU50Vsy6Yt91DYoj3a84KdUVxZr31My4fJeladEgIcjCZmHXS8dUhocNWEDa2cxfPfJtudf2e/QX3w7tID4tugZAi8Jz00G5MW5rftW7zvs8elgTi9rDMh7AMMbNDx9X9Bjgjo/HGO4cICeXKQg8P6nn++edPwhuoM2bDMO4oox4WNfQgLMcee+xYa9XA434MbMyFiWSnZGApCQmRoPD59D5ondXYK5lSo6AxdzwD8sMrBK8H2xSfAzN4WHA1xfGjrLltkyLvlI/YYtCnkSdhadInPm8RHpZUe1P3UW/dn6MrPiU61VS2dFK01jwswE0JCycTwE0JC9oQfQV9Qvdhwr1dJrp9tO0QzzBhMWFZgQA6wmr2sOiMEZ0VA9z27dsnA7QKuygPC+uIPBEun+VsPg5CzG0hEQBh4SohNfJqHPk33oMymGGXzKRLPCxKWFJhtpQHBvegTnBTI75O17YafuZfRKNPzEpCQrkDZ/SU0KiniIe+n7kBKK9Jt4tc1ow6sz1owJTgKkkpJQ25eA5Rbi0SFu3PSDhHWFR1M+X94z3oWyAs8GaupnZu0h0TlhbCoh2ffw/REXOe2YUpr7WQ0GogLGxrDW/QsGviJz0t9MrgvibCkhqMVjth0dVONLZDhoTaCEsT2V2NhEWN4GoyZEpYdDzuSmCjseczlykklEtYUjbEhCXHss5YZlE5LDrzRayQM0Fls00zxhlFzrrdhOX/YYozRP4fcwewOds111wzSQZNhSriDHroHBbqGY0vB00NA2n+hM6Wvv/++3HS7ZBXqYclpy4qD/sQjQJdGBdsgAAAFktJREFU3pocS4JCLwXJC5KBmfeT895ZysSk2pgIncphiZ4XvF9XaNHbAR1gfy7xfs0iz7R74wqnWFZXqqiM8yI7xIhJ9PgfXjquikF91YOkuUNKRHX81r+Z1EovGb3MQ+Gdem4qtBjHM4RDMW6k5FA58Xy2Uxe7MU+5S95lD4ugxcHk3HPPHS83jbkEJcAOUbaL4tXmYUnlSOhARdwZUiBh0WTISFDmTVhoxKBnDAlpfoEaubjCRT0sWq5PfRuCsGj9aPhBWBASYtgqJQPl5wBNzFA2N4clFxtd4hvDQTSI0ajE/I/UhCYm75I0oz+/8sorC19qGskI8VLsUwQmyprqh7nYt5Xj2AzCcuONN07y1FDHphycVFsQe/YdvpehPI4bTAinDWirX9fvS8Yz1B0bTYKwNI1nqEfU0S52o6s8Q99nwhIQhgIpYVGFjko+dOPE53dRvBoIiyYIpmaCmjvBAYeDpybdAk8mq+lMd96EJXpY8H5doog66uoa1g9lVquHhStVOCOGjLqsmQRE2ycuwUaboW+W7sNS2k/j7FWTVOMsFu3EhGcSMRo//uZyb95LorVMHhaObWifeFAe9BV9kCvN1CMUPZtcXZWzfL60XZiTRsKi97PNop6plwz1R/1S5Fk/wzNAWECmh/AgpcYzjk0kHPSOxPEsNZmg3tnDUqpRPZVfVEiIxhDLxuKgqIrbxOh7Er/xMWuVsHCAJwmhfqRc05HQxCS9ZQgJMUSgISHOwjnjiuEI1vvHH3+cJN0OMZhC+YbwsDB5mJ4kJSxsT53p0xWunQHfo29ylVD0Ps3a/xRPtAeNBT4nweU7OAZoO8UQkYa12H74Ta8A+7OuAplVhlnuVy+f1gmf4/9UcrR6CEh6SDpnqUu8l7qB/oyNIGPbs+2IOTFW71ZqbyO2RyQ/3NQwpYezyjXLeKarhKiDqdAkCZCGHmet9zLcbw/Lv62AhqVrGmcv4MwGbXR2CDWS827ASy+9dPTCCy8UvbYGDwsFxuzom2++OWRHWHXzRnB27949uvPOOydn3Oj3sS35f5cclm+//XZyKFlbA9FAo17ffffdZBan7m3KpOQd3+NMEN2av+1dXb5Hne64444ut069JxL9559/fnTZZZeN21PJKP9PTVzQN6EDJBR9VpLGDeMA2lM9I1yRpSt/8G7KhFk5D7JsmtCoIUdbXnLJJaMdO3asWLbaJg9OnsbP0BfGv6aQGwmMhoDwN+QfwrMCWbl52jvvvJPUzWkTSpwlhVAqx3NiR7KSGtMxzmK8Zbvn4L158+bJnjc55fHsr7/++pCNFumZSz0D7YKN4FJEyx6WHNQHKLMoDwtE4cxCZxuqtIvyrmgnK4G8BsLCgROdNZ5xw8FGZ1YRK43p8jsNI2l5fN6FsGA3Xcz+ci4aW3jxcGKtzpT0fq0jjTiMFQ5axEUPQN86idONsQNvn1epN4j9UJNuuZlcymD2UVfO2oFvJAVNeka9Qzsi763t0rwQev90NVTb/dBN/AxxqfeLy8f1PTEXR/UOS+0x+8dJ1yg3RD5LzGeiZwH1oAcvpWcYA/GTMvIxjAd9w34m0DU+N9eTh/ZH32m7qNPQs3iS+LTxjIRr2niGMvq9PSxtrdHD94sgLHgn47QxESoqQQ8izu0RNRAWgoUBATkMceanLlHG32nw6M5H/JqbfkWC0gdhwUqkEsKC+oGwcIBTwwxdxIDJreJZP9xz0kknjX766adB9Qd14iq5vl4E7OlhYJvQyMSkW+3/igvqksph6quOfA5m48A5Jt5qSCGGFxQzespIrHjGCw0JvRAkLKnk0CaZcJZa34Ql5UUAYaEOoH6oM3dfThn+jRs3jj799NPBVrBxx171ikSvCvWKhp2kCZhhHOQVtw7A55p0y/+pb7n6pf05556ff/55tGXLlkP6c9N4xv6D9moaz0xYcpDvucwiCAsbOnZGKs8QM4aeYUs+rgbCQqOF3AUSljjARNKhs0EOYPqbhk9nibOEhEoIC+qBQXPPnj1jj5GGG5Usa6iE8mHmDxc3rxJjl6tvQxAWnfXFnA1+F/t9arasIZm++ySf/csvv4wJS8xhSeFH7wg8LDBYKW8s5dLQAzDgpoZNoZfU+4YgLHwPCRZkgl4yLM78nejJU9JGwoJjIzT0latzbeVUN9TTQq+QhhTZz9kWJCzTclhiOEVDW7ntk0tYVM9IWJSMKBbqcaGsOo7x75j/xc/tYWnTrB6+XxRhYdXVBWjC0kODzviIEsKihlw7ODswB6ZlJyxNerdaCYuqQCrJVMMRSj6j6syLsJx44omT8DDaIrXMmcQT8qQIi44nmpOEz1cbYUl1YV1aOzRhifqD/3VSkiKvJYQlyjdvwsIwWpOexQmYkhb1OuFzh4RmNDilty+asGh9Y7ywqW6lMs6rfA0eFrYBPCxwVdPzoC5gHbAiGZk2S1mEh4X1iTMynZ2njHoqJJRKGJxVt4bwsLSFcqK88f+S5MdZ5YcHCwYYdYDhgm5xOWzUMxoSEhatd8y5gK6pIWzaZn5a/YfwsKTy9uBhwZ4fJFfqwWCfUcICIg195sGcpTlLXdos1Xf5mRJ+eljiJIDtqx6U6IUpqVeuh4V1hCcPOCMEGQlLajwjGWnKc4leIpbrsrq0RO55lvUqoXmiPed3oWM89thjo8cff/yQ/QfI0KObF0q+rGcJYUDYunVroyzs0LqEFp9hYNX9F6YZedz70EMPjR588MGiPRhKQ0Kolw5wJMIxl0UHfshw2mmnjbC0OdVuGs7UwauU1JQSluii1zp3JRrxPuLTRnz66GIwIJs2bWrVM74LOgMi/eGHH644FZt15u6pJDfEJ+4RlFP3EsKi78c7Uyt4VO80lKNHILQZcdxHD8tQK5hYT/zWPWHi5JLYqv5oDkubLDlt0FQml7DwfhBj9DUQl5RnpKQuTX0cYx83KJwHiSypc5ey1ROWuDlVF5BW8z2aIa8MPRpxyjhPwhKNbhvOPEVYOx6ekUpAIyFTmdWtivuaTjcdcpUQjQLe/9FHH01yWDCQxtOJObiqIdGQkCbnxZklsYyx/TaM8X3pKiFtxzgTj0Y65/1KTuJMU9s151ldysCQ4PiDNj3T/CEleUo6aThhZPE3TuTGb8gIwnLTTTdNTqPOqessq4QYdtMQFzdaYz+h9zJ6WJScQS+x5JthLnyHE8TRP3kwZ44ss5ShLKwDV5DpM+k5ih4WHetmqUO8N3eV0BCEBc/kSe3MOWKbgrDADpZcy0puTFhKWnEVleWgT8ISl05ysF2khyWXsMSQUPSgxMRTDro6CCtR4GBHTIgVPRQkLKmwTJMKlCxr5mDwySefjMkB68aVNPwecnHwoeHHTJZ7Sihh4cDNFSpxUI7u4mmqXEJYiF18H9tMV2vldh/cm7qPz+TvvgdVPhczXhCWaXpGHaPHh5ihTkpY6H2izvH8GxIW7NpKPc3Bp5SwxHAP9SSuvuK72Z5NhIW6Sr1kG5Cw4LcSmRyZcsvEEJu+J+XJoyxrgbDE8Q2YcvwgYYl9dRruffet3DZuK1c9YVnGUzfbGqWP77nCgYSF21LrDJgKre+bp4clV04Oroipw/Wu26HTkKtcGNj0YDS6S9XDkjLg9GjQKOC9OgOdVt9ZQ0J8tm7bjc80BIK/kQyK5ZAckDiIo+4681UyyIGdRrMN95KQkK5OUEyJeWp5dtv78T1m8PCARXKiMqQSLXOe3VSGerZ///4xYZmmZ+xflB8GHst6lTyzfsCAuTD67qFDQngXlwOTFLEPtBkrJSypiQU/Y5gJmxkiJILfzMeYpS1S98Yt7XNlUcKisuROmHLlWGRIiJMv9kHoJT3POGIAHhbm7OTKs4zlqicsazUkBMU9cODA6Iknnhg9+eSTK3QPHX39+vWj33777RCdnCdhyR0w6Pn4+OOPRxdeeOEhdcZmVb///vsh23VHIsYBjkYe92FAh3HU6/777x898MADo3Xr1mX32euuuy57HxaVB6cPo15xRsOZcczZgCGFB0C9Mhys1COk5AFtDV3AlTNzAmH57LPPsmTH84A9LoQ7oleK4QfUMefduF8JJw0tPRoHDx4ck0glM1kVzSjEdsEut9i1NV6qZyjLpFOU043joicgEivIAuPLZc05hpd1AZlGjlXbhXdAr9EmqYttBt3QC/eBjF1wwQXjzQMjyQXuMIRx7EAoCCHOk08+Oaud2+ofv9dwafwOdYR+o31SsmAMxE/ch6lvwgu8cjaOYx37zGHBMzds2DCWMY5n2Bn3pZdeGuNTMuaWttE8yldPWNaqhwWKiwH10UcfHf/QcLCTNu2tME/CkqvgnPliXwicJaPhLMpFYxi9Ceigqf0X2HFJFuhNwedIuIVhIIY59Sz1sGDQBwHjPiw8NI7vSiVIoo7wsDAkpPVCWzMPJlVfDX+1yVPiYZmWVAvDjcGzhPiRoMBAwdimSA5DRimM2mSb9j31DDuQnnDCCRM948yUITvWkc9CHYEZPCypOtEzQELEXAOcJL59+/Zkcm9TPUuSbvEMhgjVI0K9pheM5VT3uA+LzthJxFAO+sbt8vE/Vgchh2MeO92SRClRB6YaMiTRRxndh4UyU4dm0Zd47yI9LOpFpuccbQQ54WHB2Ugl41mfuPT5LBOWPtFcomcxXhmXNXMAWoYclly4OBBhWTMNvIYK1A1PuTkjh7zqvlcjoyEivY85LCUx31LCgnppkh49E225Bamt+dULQ6MYQ2S5WKNcCWHR59I4xtBbl5msPosGlV6lEllKylKn4MECzmrQ+W4abeJMo8llzSmd0VVC6oGChwW5T7mzXshSSli0Pqrj6gWKcuI9ukqI33MyQNn12SAsSLodclmz9nmVhfqhnkqtm64SUllLdCOn7KIJS9N4tmyngudg2VSmesLy1FNPjQ8ZW2sXO+YzzzwzevbZZw8ZFJtm3PPysMAwv/32240HrGl7kWTt27dvfJBhHOA1oZhEhYYBhmfbtm2Tx+lAFkNELHTXXXeN8FNiaO+5557Re++9l61mqMe99947zpVQedTzw4dpnW+77bZJeCdFxIgF647fl19++fgdOSEZvBN1gjw5F/UMIQHgTPx1FpzznFQZyqeE5d133x2vphrC8BAf5LAA52l6poQF5RAKee655yb1UqyV5KjxB2F9+umns9sFONx9993jn5yL9X///fdX7I5MPPE9E4ujbmDcZK6Uvot6pd4WfI/cFchPwpJTv5IylAVhFMijF75LhUNZBl720lUyJXVjWRyYeMopp2Tf2mdIiISaWLAS+JyHbJb0GRDWkvBWttAzFqyesMyIz6q9XV22qWRM9UpEcjCPfVjYWXWb+Saw6WaHAUMMnUsqUV4JCu/XDa100yT1RExbVaBLUIdSALwDxwzAa0QDkmoTnTWhHMIkkF+NaYp8ajIkQkg6y2+TiUfYt5XD98QabmcYhhSu08JG8R0ccGNohc9gMihDgTl1zC1TqmeqbxqOSxl1eidoWCEnMNu1a1d2YneuHOwX3K8E3j+En0iyIgGJ5APfp7wFumKNz1CvB/KLmsJ4JXVPlWXyMOSAPE19JSVLqVdq1rrm3t8nYcE7o2cTbYNQGS7i17STbqzzsmJmwpKrXauwHPd8oJJqJ1+0h6WEsLAzovNhdo1LDUD0sLCpUAaDG4xCk7eEe2JwNRBzSZj30neeBOuG94KwwDCoV0UNgA6+nAErUUnNmEhUiQ+WQSP3pyn5MqXWJYQF94NEwvju3LlzbHw1ZDALfsyRoJz4/6KLLhong+YOvKXdFnoCeWB82/Qs4p9qI02oVcKAz7mh1ywYtckHcnvLLbeME3wZZlNCrzKqHuKcKySE44qJ1DSANIa4j6vBUqSmrY653+MdICyQhwm0wFHJK9uAbYPvkECPvLTofcx971Dl+iQs0cOiY33U6Rx5TFhyUPq3TJP7mvkYBY9a00VTA2gbIPMKCZUSFg6s0U0/TR7IAqMAj1FuOKQNnz6/Z56AGr4ubUZs8FsJD/6Hiz6VpDtNjlLCgmc1bf9dEorSOjXdp7kVfbaFPqvEdZ5ThxSxgXzz2jKd+VW5eoZyIIXAetmupuMMmtoMn2NVFfLSlm0M6JOwtLVTqU6bsLQhKt+bsBSA1XPRZSYspaKasJiwlOrMEOVNWPpD1YSlPyynPcmEpQBnE5YCsHouasLSM6BTHmcPSzM4i/Sw9K0BJiz9IWrC0h+WJiw9YWnC0hOQHR5jwtIBtI63mLCYsCBReejLISGHhEp1zB6WAsRMWArA6rmoCUvPgNrD0il3wB6W/vTQhMWEpVSbTFgKEDNhKQCr56ImLD0DasJiwnLYYSuWoTNE5KTb8r7mkFA5Zl3uMGEpQM2EpQCsnouasPQMqAmLCYsJS2+dyoSlNyinPsiEpQBnE5YCsHouasLSM6AmLCYsJiy9dSoTlt6gNGHpC0oTlr6QLH+OCUs5Zl3vcNJtM3LOYemqVYfe5xwW57CUapM9LAWImbAUgNVzUROWngG1h8UeFntYeutU9rD0BqU9LENDCWWdxzLAoeVY9ufjcLWhD77CFvs7duyYbLU/FCaQI/ewuKHq0PRcHDCXc5bSLPXClvz33Xdf0SNQJ9St5JoXzvPArETuWcrOCzMcgIrdi0suHH6JAy2X7YIckKfkgocJCc7Lds1rDOwi97JitpRnCXUB2PcYASNgBIyAETAC9SJgwlJv21oyI2AEjIARMALVIGDCUk1TWhAjYASMgBEwAvUiYMJSb9taMiNgBIyAETAC1SBgwlJNU1oQI2AEjIARMAL1ImDCUm/bWjIjYASMgBEwAtUgYMJSTVNaECNgBIyAETAC9SJgwlJv21oyI2AEjIARMALVIGDCUk1TWhAjYASMgBEwAvUiYMJSb9taMiNgBIyAETAC1SBgwlJNU1oQI2AEjIARMAL1ImDCUm/bWjIjYASMgBEwAtUgYMJSTVNaECNgBIyAETAC9SJgwlJv21oyI2AEjIARMALVIGDCUk1TWhAjYASMgBEwAvUiYMJSb9taMiNgBIyAETAC1SBgwlJNU1oQI2AEjIARMAL1ImDCUm/bWjIjYASMgBEwAtUgYMJSTVNaECNgBIyAETAC9SJgwlJv21oyI2AEjIARMALVIGDCUk1TWhAjYASMgBEwAvUiYMJSb9taMiNgBIyAETAC1SBgwlJNU1oQI2AEjIARMAL1ImDCUm/bWjIjYASMgBEwAtUgYMJSTVNaECNgBIyAETAC9SJgwlJv21oyI2AEjIARMALVIGDCUk1TWhAjYASMgBEwAvUiYMJSb9taMiNgBIyAETAC1SBgwlJNU1oQI2AEjIARMAL1ImDCUm/bWjIjYASMgBEwAtUgYMJSTVNaECNgBIyAETAC9SJgwlJv21oyI2AEjIARMALVIGDCUk1TWhAjYASMgBEwAvUiYMJSb9taMiNgBIyAETAC1SBgwlJNU1oQI2AEjIARMAL1ImDCUm/bWjIjYASMgBEwAtUgYMJSTVNaECNgBIyAETAC9SLQSFjqFdmSGQEjYASMgBEwAqsVge1b1x12GCr/8p6D/12tQrjeRsAIGAEjYASMQN0ITAhL3WJaOiNgBIyAETACRmC1I/C/+Ryxj68oilIAAAAASUVORK5CYII="},11051:function(Re){"use strict";Re.exports="data:image/png;base64,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"},30711:function(Re){"use strict";Re.exports="data:image/png;base64,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"},64690:function(Re){"use strict";Re.exports="data:image/png;base64,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"},40517:function(Re){"use strict";Re.exports="data:image/png;base64,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"},89006:function(Re){"use strict";Re.exports="data:image/png;base64,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"},57581:function(Re){"use strict";Re.exports="data:image/png;base64,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"},12175:function(Re,bn,O){"use strict";Re.exports=O.p+"static/bg.d81594a7.png"},47444:function(Re){"use strict";Re.exports="data:image/png;base64,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"},425:function(Re,bn,O){"use 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strict";Re.exports="data:image/png;base64,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"},11862:function(Re){"use strict";Re.exports="data:image/png;base64,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"},93148:function(Re,bn,O){"use 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"},50356:function(Re){"use strict";Re.exports="data:image/png;base64,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"},40362:function(Re){"use strict";Re.exports="data:image/png;base64,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"},74732:function(Re){"use strict";Re.exports="data:image/png;base64,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"},87017:function(Re){"use strict";Re.exports="data:image/png;base64,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"},49747:function(Re){"use strict";Re.exports="data:image/png;base64,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"},7875:function(Re){"use strict";Re.exports="data:image/png;base64,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"},14813:function(Re){"use strict";Re.exports="data:image/png;base64,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"},79989:function(Re){"use strict";Re.exports="data:image/png;base64,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"},73486:function(Re){"use strict";Re.exports="data:image/png;base64,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"},23280:function(Re){"use strict";Re.exports="data:image/png;base64,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"},30019:function(Re,bn,O){"use 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"},37618:function(Re){"use strict";Re.exports="data:image/png;base64,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"},14760:function(Re){"use strict";Re.exports="data:image/png;base64,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"},87620:function(Re){"use strict";Re.exports="data:image/png;base64,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"},31537:function(Re){"use strict";Re.exports="data:image/png;base64,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"},46058:function(Re){"use strict";Re.exports="data:image/png;base64,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"},71190:function(Re){"use strict";Re.exports="data:image/png;base64,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"},51889:function(Re){"use strict";Re.exports="data:image/png;base64,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"},95754:function(Re){"use strict";Re.exports="data:image/png;base64,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"},9490:function(Re){"use strict";Re.exports="data:image/png;base64,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"},82670:function(Re){"use strict";Re.exports="data:image/png;base64,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"},61834:function(Re){"use strict";Re.exports="data:image/png;base64,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"},8451:function(Re){"use strict";Re.exports="data:image/png;base64,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"},71463:function(Re){"use strict";Re.exports="data:image/png;base64,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"},73099:function(Re){"use strict";Re.exports="data:image/png;base64,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"},39633:function(Re){"use strict";Re.exports="data:image/png;base64,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"},31434:function(Re){"use strict";Re.exports="data:image/png;base64,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"},16065:function(Re){"use strict";Re.exports="data:image/png;base64,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"},69035:function(Re){"use strict";Re.exports="data:image/png;base64,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"},40181:function(Re){"use strict";Re.exports="data:image/png;base64,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"},17149:function(Re){"use strict";Re.exports="data:image/png;base64,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"},64813:function(Re){"use strict";Re.exports="data:image/png;base64,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"},362:function(Re){"use strict";Re.exports="data:image/png;base64,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"},16033:function(Re){"use strict";Re.exports="data:image/png;base64,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"},26358:function(Re){"use strict";Re.exports="data:image/png;base64,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"},16122:function(Re){"use strict";Re.exports="data:image/png;base64,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"},82396:function(Re){"use strict";function bn(pe){y(pe);const Ge=O(pe);return pe.on=Ge.on,pe.off=Ge.off,pe.fire=Ge.fire,pe}function O(pe){let Ge=Object.create(null);return{on:function(je,it,un){if(typeof it!="function")throw new Error("callback is expected to be a function");let Ye=Ge[je];return Ye||(Ye=Ge[je]=[]),Ye.push({callback:it,ctx:un}),pe},off:function(je,it){if(typeof je>"u")return Ge=Object.create(null),pe;if(Ge[je])if(typeof it!="function")delete Ge[je];else{const un=Ge[je];for(let Ye=0;Ye<un.length;++Ye)un[Ye].callback===it&&un.splice(Ye,1)}return pe},fire:function(je){const it=Ge[je];if(!it)return pe;let un;arguments.length>1&&(un=Array.prototype.slice.call(arguments,1));for(let Ye=0;Ye<it.length;++Ye){const Ne=it[Ye];Ne.callback.apply(Ne.ctx,un)}return pe}}}function y(pe){if(!pe)throw new Error("Eventify cannot use falsy object as events subject");const Ge=["on","fire","off"];for(let je=0;je<Ge.length;++je)if(pe.hasOwnProperty(Ge[je]))throw new Error("Subject cannot be eventified, since it already has property '"+Ge[je]+"'")}Re.exports=bn},84255:function(Re,bn,O){"use strict";O.d(bn,{Z:function(){return pe}});var y=O(29658);function pe(Ge,je){Ge.prototype=Object.create(je.prototype),Ge.prototype.constructor=Ge,(0,y.Z)(Ge,je)}}}]);
}());