diff --git a/1188.f4633e3d.async.js b/1188.f4633e3d.async.js
new file mode 100644
index 0000000000..a190b7360b
--- /dev/null
+++ b/1188.f4633e3d.async.js
@@ -0,0 +1,10 @@
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i=0;i<T.columns;i++)T.set(c,i,T.get(c,i)-u[i])}function ue(T,u){for(let c=0;c<T.rows;c++)for(let i=0;i<T.columns;i++)T.set(c,i,T.get(c,i)-u)}function he(T){const u=[];for(let c=0;c<T.rows;c++){let i=0;for(let l=0;l<T.columns;l++)i+=b(T.get(c,l),2)/(T.columns-1);u.push(Math.sqrt(i))}return u}function Ie(T,u){for(let c=0;c<T.rows;c++)for(let i=0;i<T.columns;i++)T.set(c,i,T.get(c,i)/u[c])}function pn(T){const u=[];for(let c=0;c<T.columns;c++){let i=0;for(let l=0;l<T.rows;l++)i+=b(T.get(l,c),2)/(T.rows-1);u.push(Math.sqrt(i))}return u}function De(T,u){for(let c=0;c<T.rows;c++)for(let i=0;i<T.columns;i++)T.set(c,i,T.get(c,i)/u[i])}function Me(T){const u=T.size-1;let c=0;for(let i=0;i<T.columns;i++)for(let l=0;l<T.rows;l++)c+=b(T.get(l,i),2)/u;return Math.sqrt(c)}function se(T,u){for(let c=0;c<T.rows;c++)for(let i=0;i<T.columns;i++)T.set(c,i,T.get(c,i)/u)}class Wt{static from1DArray(u,c,i){if(u*c!==i.length)throw new RangeError("data length does not match given dimensions");let m=new It(u,c);for(let B=0;B<u;B++)for(let U=0;U<c;U++)m.set(B,U,i[B*c+U]);return m}static rowVector(u){let c=new It(1,u.length);for(let i=0;i<u.length;i++)c.set(0,i,u[i]);return c}static columnVector(u){let c=new It(u.length,1);for(let i=0;i<u.length;i++)c.set(i,0,u[i]);return c}static zeros(u,c){return new It(u,c)}static ones(u,c){return new It(u,c).fill(1)}static rand(u,c,i={}){if(typeof i!="object")throw new TypeError("options must be an object");const{random:l=Math.random}=i;let m=new It(u,c);for(let B=0;B<u;B++)for(let U=0;U<c;U++)m.set(B,U,l());return m}static randInt(u,c,i={}){if(typeof i!="object")throw new TypeError("options must be an object");const{min:l=0,max:m=1e3,random:B=Math.random}=i;if(!Number.isInteger(l))throw new TypeError("min must be an integer");if(!Number.isInteger(m))throw new TypeError("max must be an integer");if(l>=m)throw new RangeError("min must be smaller than max");let U=m-l,V=new It(u,c);for(let G=0;G<u;G++)for(let rt=0;rt<c;rt++){let K=l+Math.round(B()*U);V.set(G,rt,K)}return V}static eye(u,c,i){c===void 0&&(c=u),i===void 0&&(i=1);let l=Math.min(u,c),m=this.zeros(u,c);for(let B=0;B<l;B++)m.set(B,B,i);return m}static diag(u,c,i){let l=u.length;c===void 0&&(c=l),i===void 0&&(i=c);let m=Math.min(l,c,i),B=this.zeros(c,i);for(let U=0;U<m;U++)B.set(U,U,u[U]);return B}static min(u,c){u=this.checkMatrix(u),c=this.checkMatrix(c);let i=u.rows,l=u.columns,m=new It(i,l);for(let B=0;B<i;B++)for(let U=0;U<l;U++)m.set(B,U,Math.min(u.get(B,U),c.get(B,U)));return m}static max(u,c){u=this.checkMatrix(u),c=this.checkMatrix(c);let i=u.rows,l=u.columns,m=new this(i,l);for(let B=0;B<i;B++)for(let U=0;U<l;U++)m.set(B,U,Math.max(u.get(B,U),c.get(B,U)));return m}static checkMatrix(u){return Wt.isMatrix(u)?u:new It(u)}static isMatrix(u){return u!=null&&u.klass==="Matrix"}get size(){return this.rows*this.columns}apply(u){if(typeof u!="function")throw new TypeError("callback must be a function");for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)u.call(this,c,i);return this}to1DArray(){let u=[];for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)u.push(this.get(c,i));return u}to2DArray(){let u=[];for(let c=0;c<this.rows;c++){u.push([]);for(let i=0;i<this.columns;i++)u[c].push(this.get(c,i))}return u}toJSON(){return this.to2DArray()}isRowVector(){return this.rows===1}isColumnVector(){return this.columns===1}isVector(){return this.rows===1||this.columns===1}isSquare(){return this.rows===this.columns}isEmpty(){return this.rows===0||this.columns===0}isSymmetric(){if(this.isSquare()){for(let u=0;u<this.rows;u++)for(let c=0;c<=u;c++)if(this.get(u,c)!==this.get(c,u))return!1;return!0}return!1}isDistance(){if(!this.isSymmetric())return!1;for(let u=0;u<this.rows;u++)if(this.get(u,u)!==0)return!1;return!0}isEchelonForm(){let u=0,c=0,i=-1,l=!0,m=!1;for(;u<this.rows&&l;){for(c=0,m=!1;c<this.columns&&m===!1;)this.get(u,c)===0?c++:this.get(u,c)===1&&c>i?(m=!0,i=c):(l=!1,m=!0);u++}return l}isReducedEchelonForm(){let u=0,c=0,i=-1,l=!0,m=!1;for(;u<this.rows&&l;){for(c=0,m=!1;c<this.columns&&m===!1;)this.get(u,c)===0?c++:this.get(u,c)===1&&c>i?(m=!0,i=c):(l=!1,m=!0);for(let B=c+1;B<this.rows;B++)this.get(u,B)!==0&&(l=!1);u++}return l}echelonForm(){let u=this.clone(),c=0,i=0;for(;c<u.rows&&i<u.columns;){let l=c;for(let m=c;m<u.rows;m++)u.get(m,i)>u.get(l,i)&&(l=m);if(u.get(l,i)===0)i++;else{u.swapRows(c,l);let m=u.get(c,i);for(let B=i;B<u.columns;B++)u.set(c,B,u.get(c,B)/m);for(let B=c+1;B<u.rows;B++){let U=u.get(B,i)/u.get(c,i);u.set(B,i,0);for(let V=i+1;V<u.columns;V++)u.set(B,V,u.get(B,V)-u.get(c,V)*U)}c++,i++}}return u}reducedEchelonForm(){let u=this.echelonForm(),c=u.columns,i=u.rows,l=i-1;for(;l>=0;)if(u.maxRow(l)===0)l--;else{let m=0,B=!1;for(;m<i&&B===!1;)u.get(l,m)===1?B=!0:m++;for(let U=0;U<l;U++){let V=u.get(U,m);for(let G=m;G<c;G++){let rt=u.get(U,G)-V*u.get(l,G);u.set(U,G,rt)}}l--}return u}set(){throw new Error("set method is unimplemented")}get(){throw new 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c=[];for(let i=0;i<this.rows;i++)c.push(this.get(i,u));return c}getColumnVector(u){return It.columnVector(this.getColumn(u))}setColumn(u,c){yt(this,u),c=Ot(this,c);for(let i=0;i<this.rows;i++)this.set(i,u,c[i]);return this}swapColumns(u,c){yt(this,u),yt(this,c);for(let i=0;i<this.rows;i++){let l=this.get(i,u);this.set(i,u,this.get(i,c)),this.set(i,c,l)}return this}addRowVector(u){u=Nt(this,u);for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)this.set(c,i,this.get(c,i)+u[i]);return this}subRowVector(u){u=Nt(this,u);for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)this.set(c,i,this.get(c,i)-u[i]);return this}mulRowVector(u){u=Nt(this,u);for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)this.set(c,i,this.get(c,i)*u[i]);return this}divRowVector(u){u=Nt(this,u);for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)this.set(c,i,this.get(c,i)/u[i]);return this}addColumnVector(u){u=Ot(this,u);for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)this.set(c,i,this.get(c,i)+u[c]);return this}subColumnVector(u){u=Ot(this,u);for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)this.set(c,i,this.get(c,i)-u[c]);return this}mulColumnVector(u){u=Ot(this,u);for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)this.set(c,i,this.get(c,i)*u[c]);return this}divColumnVector(u){u=Ot(this,u);for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)this.set(c,i,this.get(c,i)/u[c]);return this}mulRow(u,c){xt(this,u);for(let i=0;i<this.columns;i++)this.set(u,i,this.get(u,i)*c);return this}mulColumn(u,c){yt(this,u);for(let i=0;i<this.rows;i++)this.set(i,u,this.get(i,u)*c);return this}max(u){if(this.isEmpty())return NaN;switch(u){case"row":{const c=new Array(this.rows).fill(Number.NEGATIVE_INFINITY);for(let i=0;i<this.rows;i++)for(let l=0;l<this.columns;l++)this.get(i,l)>c[i]&&(c[i]=this.get(i,l));return c}case"column":{const c=new Array(this.columns).fill(Number.NEGATIVE_INFINITY);for(let i=0;i<this.rows;i++)for(let l=0;l<this.columns;l++)this.get(i,l)>c[l]&&(c[l]=this.get(i,l));return c}case void 0:{let c=this.get(0,0);for(let i=0;i<this.rows;i++)for(let l=0;l<this.columns;l++)this.get(i,l)>c&&(c=this.get(i,l));return c}default:throw new Error(`invalid option: ${u}`)}}maxIndex(){Ye(this);let u=this.get(0,0),c=[0,0];for(let i=0;i<this.rows;i++)for(let l=0;l<this.columns;l++)this.get(i,l)>u&&(u=this.get(i,l),c[0]=i,c[1]=l);return c}min(u){if(this.isEmpty())return NaN;switch(u){case"row":{const c=new Array(this.rows).fill(Number.POSITIVE_INFINITY);for(let i=0;i<this.rows;i++)for(let l=0;l<this.columns;l++)this.get(i,l)<c[i]&&(c[i]=this.get(i,l));return c}case"column":{const c=new Array(this.columns).fill(Number.POSITIVE_INFINITY);for(let i=0;i<this.rows;i++)for(let l=0;l<this.columns;l++)this.get(i,l)<c[l]&&(c[l]=this.get(i,l));return c}case void 0:{let c=this.get(0,0);for(let i=0;i<this.rows;i++)for(let l=0;l<this.columns;l++)this.get(i,l)<c&&(c=this.get(i,l));return c}default:throw new Error(`invalid option: ${u}`)}}minIndex(){Ye(this);let u=this.get(0,0),c=[0,0];for(let i=0;i<this.rows;i++)for(let l=0;l<this.columns;l++)this.get(i,l)<u&&(u=this.get(i,l),c[0]=i,c[1]=l);return c}maxRow(u){if(xt(this,u),this.isEmpty())return NaN;let c=this.get(u,0);for(let i=1;i<this.columns;i++)this.get(u,i)>c&&(c=this.get(u,i));return c}maxRowIndex(u){xt(this,u),Ye(this);let c=this.get(u,0),i=[u,0];for(let l=1;l<this.columns;l++)this.get(u,l)>c&&(c=this.get(u,l),i[1]=l);return i}minRow(u){if(xt(this,u),this.isEmpty())return NaN;let c=this.get(u,0);for(let i=1;i<this.columns;i++)this.get(u,i)<c&&(c=this.get(u,i));return c}minRowIndex(u){xt(this,u),Ye(this);let c=this.get(u,0),i=[u,0];for(let l=1;l<this.columns;l++)this.get(u,l)<c&&(c=this.get(u,l),i[1]=l);return i}maxColumn(u){if(yt(this,u),this.isEmpty())return NaN;let c=this.get(0,u);for(let i=1;i<this.rows;i++)this.get(i,u)>c&&(c=this.get(i,u));return c}maxColumnIndex(u){yt(this,u),Ye(this);let c=this.get(0,u),i=[0,u];for(let l=1;l<this.rows;l++)this.get(l,u)>c&&(c=this.get(l,u),i[0]=l);return i}minColumn(u){if(yt(this,u),this.isEmpty())return NaN;let c=this.get(0,u);for(let i=1;i<this.rows;i++)this.get(i,u)<c&&(c=this.get(i,u));return c}minColumnIndex(u){yt(this,u),Ye(this);let c=this.get(0,u),i=[0,u];for(let l=1;l<this.rows;l++)this.get(l,u)<c&&(c=this.get(l,u),i[0]=l);return i}diag(){let u=Math.min(this.rows,this.columns),c=[];for(let i=0;i<u;i++)c.push(this.get(i,i));return c}norm(u="frobenius"){switch(u){case"max":return this.max();case"frobenius":return Math.sqrt(this.dot(this));default:throw new RangeError(`unknown norm type: ${u}`)}}cumulativeSum(){let u=0;for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)u+=this.get(c,i),this.set(c,i,u);return this}dot(u){Wt.isMatrix(u)&&(u=u.to1DArray());let c=this.to1DArray();if(c.length!==u.length)throw new RangeError("vectors do not have the same size");let i=0;for(let l=0;l<c.length;l++)i+=c[l]*u[l];return i}mmul(u){u=It.checkMatrix(u);let c=this.rows,i=this.columns,l=u.columns,m=new It(c,l),B=new Float64Array(i);for(let U=0;U<l;U++){for(let V=0;V<i;V++)B[V]=u.get(V,U);for(let V=0;V<c;V++){let G=0;for(let rt=0;rt<i;rt++)G+=this.get(V,rt)*B[rt];m.set(V,U,G)}}return m}mpow(u){if(!this.isSquare())throw new RangeError("Matrix must be square");if(!Number.isInteger(u)||u<0)throw new RangeError("Exponent must be a non-negative integer");let c=It.eye(this.rows),i=this;for(let l=u;l>=1;l/=2)l&1&&(c=c.mmul(i)),i=i.mmul(i);return c}strassen2x2(u){u=It.checkMatrix(u);let c=new It(2,2);const i=this.get(0,0),l=u.get(0,0),m=this.get(0,1),B=u.get(0,1),U=this.get(1,0),V=u.get(1,0),G=this.get(1,1),rt=u.get(1,1),K=(i+G)*(l+rt),lt=(U+G)*l,Tt=i*(B-rt),ct=G*(V-l),pt=(i+m)*rt,Rt=(U-i)*(l+B),Z=(m-G)*(V+rt),St=K+ct-pt+Z,Ct=Tt+pt,Xt=lt+ct,Zt=K-lt+Tt+Rt;return c.set(0,0,St),c.set(0,1,Ct),c.set(1,0,Xt),c.set(1,1,Zt),c}strassen3x3(u){u=It.checkMatrix(u);let c=new It(3,3);const i=this.get(0,0),l=this.get(0,1),m=this.get(0,2),B=this.get(1,0),U=this.get(1,1),V=this.get(1,2),G=this.get(2,0),rt=this.get(2,1),K=this.get(2,2),lt=u.get(0,0),Tt=u.get(0,1),ct=u.get(0,2),pt=u.get(1,0),Rt=u.get(1,1),Z=u.get(1,2),St=u.get(2,0),Ct=u.get(2,1),Xt=u.get(2,2),Zt=(i+l+m-B-U-rt-K)*Rt,ge=(i-B)*(-Tt+Rt),Ut=U*(-lt+Tt+pt-Rt-Z-St+Xt),Yt=(-i+B+U)*(lt-Tt+Rt),ce=(B+U)*(-lt+Tt),tt=i*lt,wt=(-i+G+rt)*(lt-ct+Z),Lt=(-i+G)*(ct-Z),Mt=(G+rt)*(-lt+ct),we=(i+l+m-U-V-G-rt)*Z,ae=rt*(-lt+ct+pt-Rt-Z-St+Ct),fe=(-m+rt+K)*(Rt+St-Ct),pe=(m-K)*(Rt-Ct),Re=m*St,_e=(rt+K)*(-St+Ct),Se=(-m+U+V)*(Z+St-Xt),Je=(m-V)*(Z-Xt),Qe=(U+V)*(-St+Xt),te=l*pt,Le=V*Ct,Ue=B*ct,Ve=G*Tt,Oe=K*Xt,xr=tt+Re+te,Er=Zt+Yt+ce+tt+fe+Re+_e,Hn=tt+wt+Mt+we+Re+Se+Qe,br=ge+Ut+Yt+tt+Re+Se+Je,qn=ge+Yt+ce+tt+Le,Nr=Re+Se+Je+Qe+Ue,Mr=tt+wt+Lt+ae+fe+pe+Re,Sr=fe+pe+Re+_e+Ve,tr=tt+wt+Lt+Mt+Oe;return c.set(0,0,xr),c.set(0,1,Er),c.set(0,2,Hn),c.set(1,0,br),c.set(1,1,qn),c.set(1,2,Nr),c.set(2,0,Mr),c.set(2,1,Sr),c.set(2,2,tr),c}mmulStrassen(u){u=It.checkMatrix(u);let c=this.clone(),i=c.rows,l=c.columns,m=u.rows,B=u.columns;l!==m&&console.warn(`Multiplying ${i} x ${l} and ${m} x ${B} matrix: dimensions do not match.`);function U(K,lt,Tt){let ct=K.rows,pt=K.columns;if(ct===lt&&pt===Tt)return K;{let Rt=Wt.zeros(lt,Tt);return Rt=Rt.setSubMatrix(K,0,0),Rt}}let V=Math.max(i,m),G=Math.max(l,B);c=U(c,V,G),u=U(u,V,G);function rt(K,lt,Tt,ct){if(Tt<=512||ct<=512)return K.mmul(lt);Tt%2===1&&ct%2===1?(K=U(K,Tt+1,ct+1),lt=U(lt,Tt+1,ct+1)):Tt%2===1?(K=U(K,Tt+1,ct),lt=U(lt,Tt+1,ct)):ct%2===1&&(K=U(K,Tt,ct+1),lt=U(lt,Tt,ct+1));let pt=parseInt(K.rows/2,10),Rt=parseInt(K.columns/2,10),Z=K.subMatrix(0,pt-1,0,Rt-1),St=lt.subMatrix(0,pt-1,0,Rt-1),Ct=K.subMatrix(0,pt-1,Rt,K.columns-1),Xt=lt.subMatrix(0,pt-1,Rt,lt.columns-1),Zt=K.subMatrix(pt,K.rows-1,0,Rt-1),ge=lt.subMatrix(pt,lt.rows-1,0,Rt-1),Ut=K.subMatrix(pt,K.rows-1,Rt,K.columns-1),Yt=lt.subMatrix(pt,lt.rows-1,Rt,lt.columns-1),ce=rt(Wt.add(Z,Ut),Wt.add(St,Yt),pt,Rt),tt=rt(Wt.add(Zt,Ut),St,pt,Rt),wt=rt(Z,Wt.sub(Xt,Yt),pt,Rt),Lt=rt(Ut,Wt.sub(ge,St),pt,Rt),Mt=rt(Wt.add(Z,Ct),Yt,pt,Rt),we=rt(Wt.sub(Zt,Z),Wt.add(St,Xt),pt,Rt),ae=rt(Wt.sub(Ct,Ut),Wt.add(ge,Yt),pt,Rt),fe=Wt.add(ce,Lt);fe.sub(Mt),fe.add(ae);let pe=Wt.add(wt,Mt),Re=Wt.add(tt,Lt),_e=Wt.sub(ce,tt);_e.add(wt),_e.add(we);let Se=Wt.zeros(2*fe.rows,2*fe.columns);return Se=Se.setSubMatrix(fe,0,0),Se=Se.setSubMatrix(pe,fe.rows,0),Se=Se.setSubMatrix(Re,0,fe.columns),Se=Se.setSubMatrix(_e,fe.rows,fe.columns),Se.subMatrix(0,Tt-1,0,ct-1)}return rt(c,u,V,G)}scaleRows(u={}){if(typeof u!="object")throw new TypeError("options must be an object");const{min:c=0,max:i=1}=u;if(!Number.isFinite(c))throw new TypeError("min must be a number");if(!Number.isFinite(i))throw new TypeError("max must be a number");if(c>=i)throw new RangeError("min must be smaller than max");let l=new It(this.rows,this.columns);for(let m=0;m<this.rows;m++){const B=this.getRow(m);B.length>0&&nt(B,{min:c,max:i,output:B}),l.setRow(m,B)}return l}scaleColumns(u={}){if(typeof u!="object")throw new TypeError("options must be an object");const{min:c=0,max:i=1}=u;if(!Number.isFinite(c))throw new TypeError("min must be a number");if(!Number.isFinite(i))throw new TypeError("max must be a number");if(c>=i)throw new RangeError("min must be smaller than max");let l=new It(this.rows,this.columns);for(let m=0;m<this.columns;m++){const B=this.getColumn(m);B.length&&nt(B,{min:c,max:i,output:B}),l.setColumn(m,B)}return l}flipRows(){const u=Math.ceil(this.columns/2);for(let c=0;c<this.rows;c++)for(let i=0;i<u;i++){let l=this.get(c,i),m=this.get(c,this.columns-1-i);this.set(c,i,m),this.set(c,this.columns-1-i,l)}return this}flipColumns(){const u=Math.ceil(this.rows/2);for(let c=0;c<this.columns;c++)for(let i=0;i<u;i++){let l=this.get(i,c),m=this.get(this.rows-1-i,c);this.set(i,c,m),this.set(this.rows-1-i,c,l)}return this}kroneckerProduct(u){u=It.checkMatrix(u);let c=this.rows,i=this.columns,l=u.rows,m=u.columns,B=new It(c*l,i*m);for(let U=0;U<c;U++)for(let V=0;V<i;V++)for(let G=0;G<l;G++)for(let rt=0;rt<m;rt++)B.set(l*U+G,m*V+rt,this.get(U,V)*u.get(G,rt));return B}kroneckerSum(u){if(u=It.checkMatrix(u),!this.isSquare()||!u.isSquare())throw new Error("Kronecker Sum needs two Square Matrices");let c=this.rows,i=u.rows,l=this.kroneckerProduct(It.eye(i,i)),m=It.eye(c,c).kroneckerProduct(u);return l.add(m)}transpose(){let u=new It(this.columns,this.rows);for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)u.set(i,c,this.get(c,i));return u}sortRows(u=re){for(let c=0;c<this.rows;c++)this.setRow(c,this.getRow(c).sort(u));return this}sortColumns(u=re){for(let c=0;c<this.columns;c++)this.setColumn(c,this.getColumn(c).sort(u));return this}subMatrix(u,c,i,l){Ht(this,u,c,i,l);let m=new It(c-u+1,l-i+1);for(let B=u;B<=c;B++)for(let U=i;U<=l;U++)m.set(B-u,U-i,this.get(B,U));return m}subMatrixRow(u,c,i){if(c===void 0&&(c=0),i===void 0&&(i=this.columns-1),c>i||c<0||c>=this.columns||i<0||i>=this.columns)throw new RangeError("Argument out of range");let l=new It(u.length,i-c+1);for(let m=0;m<u.length;m++)for(let B=c;B<=i;B++){if(u[m]<0||u[m]>=this.rows)throw new RangeError(`Row index out of range: ${u[m]}`);l.set(m,B-c,this.get(u[m],B))}return l}subMatrixColumn(u,c,i){if(c===void 0&&(c=0),i===void 0&&(i=this.rows-1),c>i||c<0||c>=this.rows||i<0||i>=this.rows)throw new RangeError("Argument out of range");let l=new It(i-c+1,u.length);for(let m=0;m<u.length;m++)for(let B=c;B<=i;B++){if(u[m]<0||u[m]>=this.columns)throw new RangeError(`Column index out of range: ${u[m]}`);l.set(B-c,m,this.get(B,u[m]))}return l}setSubMatrix(u,c,i){if(u=It.checkMatrix(u),u.isEmpty())return this;let l=c+u.rows-1,m=i+u.columns-1;Ht(this,c,l,i,m);for(let B=0;B<u.rows;B++)for(let U=0;U<u.columns;U++)this.set(c+B,i+U,u.get(B,U));return this}selection(u,c){kt(this,u),Vt(this,c);let i=new It(u.length,c.length);for(let l=0;l<u.length;l++){let m=u[l];for(let B=0;B<c.length;B++){let U=c[B];i.set(l,B,this.get(m,U))}}return i}trace(){let u=Math.min(this.rows,this.columns),c=0;for(let i=0;i<u;i++)c+=this.get(i,i);return c}clone(){return this.constructor.copy(this,new It(this.rows,this.columns))}static copy(u,c){for(const[i,l,m]of u.entries())c.set(i,l,m);return c}sum(u){switch(u){case"row":return tn(this);case"column":return bn(this);case void 0:return Nn(this);default:throw new Error(`invalid option: ${u}`)}}product(u){switch(u){case"row":return an(this);case"column":return Ze(this);case void 0:return sn(this);default:throw new Error(`invalid option: ${u}`)}}mean(u){const c=this.sum(u);switch(u){case"row":{for(let i=0;i<this.rows;i++)c[i]/=this.columns;return c}case"column":{for(let i=0;i<this.columns;i++)c[i]/=this.rows;return c}case void 0:return c/this.size;default:throw new Error(`invalid option: ${u}`)}}variance(u,c={}){if(typeof u=="object"&&(c=u,u=void 0),typeof c!="object")throw new TypeError("options must be an object");const{unbiased:i=!0,mean:l=this.mean(u)}=c;if(typeof i!="boolean")throw new TypeError("unbiased must be a boolean");switch(u){case"row":{if(!ot.isAnyArray(l))throw new TypeError("mean must be an array");return gt(this,i,l)}case"column":{if(!ot.isAnyArray(l))throw new TypeError("mean must be an array");return vt(this,i,l)}case void 0:{if(typeof l!="number")throw new TypeError("mean must be a number");return At(this,i,l)}default:throw new Error(`invalid option: ${u}`)}}standardDeviation(u,c){typeof u=="object"&&(c=u,u=void 0);const i=this.variance(u,c);if(u===void 0)return Math.sqrt(i);for(let l=0;l<i.length;l++)i[l]=Math.sqrt(i[l]);return i}center(u,c={}){if(typeof u=="object"&&(c=u,u=void 0),typeof c!="object")throw new TypeError("options must be an object");const{center:i=this.mean(u)}=c;switch(u){case"row":{if(!ot.isAnyArray(i))throw new TypeError("center must be an array");return Ft(this,i),this}case"column":{if(!ot.isAnyArray(i))throw new TypeError("center must be an array");return qt(this,i),this}case void 0:{if(typeof i!="number")throw new TypeError("center must be a number");return ue(this,i),this}default:throw new Error(`invalid option: ${u}`)}}scale(u,c={}){if(typeof u=="object"&&(c=u,u=void 0),typeof c!="object")throw new TypeError("options must be an object");let i=c.scale;switch(u){case"row":{if(i===void 0)i=he(this);else if(!ot.isAnyArray(i))throw new TypeError("scale must be an array");return Ie(this,i),this}case"column":{if(i===void 0)i=pn(this);else if(!ot.isAnyArray(i))throw new TypeError("scale must be an array");return De(this,i),this}case void 0:{if(i===void 0)i=Me(this);else if(typeof i!="number")throw new TypeError("scale must be a number");return se(this,i),this}default:throw new Error(`invalid option: ${u}`)}}toString(u){return it(this,u)}[Symbol.iterator](){return this.entries()}*entries(){for(let u=0;u<this.rows;u++)for(let c=0;c<this.columns;c++)yield[u,c,this.get(u,c)]}*values(){for(let u=0;u<this.rows;u++)for(let c=0;c<this.columns;c++)yield this.get(u,c)}}Wt.prototype.klass="Matrix",typeof Symbol!="undefined"&&(Wt.prototype[Symbol.for("nodejs.util.inspect.custom")]=H);function re(T,u){return T-u}function en(T){return T.every(u=>typeof u=="number")}Wt.random=Wt.rand,Wt.randomInt=Wt.randInt,Wt.diagonal=Wt.diag,Wt.prototype.diagonal=Wt.prototype.diag,Wt.identity=Wt.eye,Wt.prototype.negate=Wt.prototype.neg,Wt.prototype.tensorProduct=Wt.prototype.kroneckerProduct;const on=class Zr extends Wt{constructor(u,c){if(super(),A(this,D),N(this,"data"),Zr.isMatrix(u))j(this,D,Y).call(this,u.rows,u.columns),Zr.copy(u,this);else if(Number.isInteger(u)&&u>=0)j(this,D,Y).call(this,u,c);else if(ot.isAnyArray(u)){const i=u;if(u=i.length,c=u?i[0].length:0,typeof c!="number")throw new TypeError("Data must be a 2D array with at least one element");this.data=[];for(let l=0;l<u;l++){if(i[l].length!==c)throw new RangeError("Inconsistent array dimensions");if(!en(i[l]))throw new TypeError("Input data contains non-numeric values");this.data.push(Float64Array.from(i[l]))}this.rows=u,this.columns=c}else throw new TypeError("First argument must be a positive number or an array")}set(u,c,i){return this.data[u][c]=i,this}get(u,c){return this.data[u][c]}removeRow(u){return xt(this,u),this.data.splice(u,1),this.rows-=1,this}addRow(u,c){return c===void 0&&(c=u,u=this.rows),xt(this,u,!0),c=Float64Array.from(Nt(this,c)),this.data.splice(u,0,c),this.rows+=1,this}removeColumn(u){yt(this,u);for(let c=0;c<this.rows;c++){const i=new Float64Array(this.columns-1);for(let l=0;l<u;l++)i[l]=this.data[c][l];for(let l=u+1;l<this.columns;l++)i[l-1]=this.data[c][l];this.data[c]=i}return this.columns-=1,this}addColumn(u,c){typeof c=="undefined"&&(c=u,u=this.columns),yt(this,u,!0),c=Ot(this,c);for(let i=0;i<this.rows;i++){const l=new Float64Array(this.columns+1);let m=0;for(;m<u;m++)l[m]=this.data[i][m];for(l[m++]=c[i];m<this.columns+1;m++)l[m]=this.data[i][m-1];this.data[i]=l}return this.columns+=1,this}};D=new WeakSet,Y=function(T,u){if(this.data=[],Number.isInteger(u)&&u>=0)for(let c=0;c<T;c++)this.data.push(new Float64Array(u));else throw new TypeError("nColumns must be a positive integer");this.rows=T,this.columns=u};let It=on;dt(Wt,It);const un=class Jr extends Wt{constructor(u){if(super(),A(this,_),It.isMatrix(u)){if(!u.isSymmetric())throw new TypeError("not symmetric data");I(this,_,It.copy(u,new It(u.rows,u.rows)))}else if(Number.isInteger(u)&&u>=0)I(this,_,new It(u,u));else if(I(this,_,new It(u)),!this.isSymmetric())throw new TypeError("not symmetric data")}get size(){return M(this,_).size}get rows(){return M(this,_).rows}get columns(){return M(this,_).columns}get diagonalSize(){return this.rows}static isSymmetricMatrix(u){return It.isMatrix(u)&&u.klassType==="SymmetricMatrix"}static zeros(u){return new this(u)}static ones(u){return new this(u).fill(1)}clone(){const u=new Jr(this.diagonalSize);for(const[c,i,l]of this.upperRightEntries())u.set(c,i,l);return u}toMatrix(){return new It(this)}get(u,c){return M(this,_).get(u,c)}set(u,c,i){return M(this,_).set(u,c,i),M(this,_).set(c,u,i),this}removeCross(u){return M(this,_).removeRow(u),M(this,_).removeColumn(u),this}addCross(u,c){c===void 0&&(c=u,u=this.diagonalSize);const i=c.slice();return i.splice(u,1),M(this,_).addRow(u,i),M(this,_).addColumn(u,c),this}applyMask(u){if(u.length!==this.diagonalSize)throw new RangeError("Mask size do not match with matrix size");const c=[];for(const[i,l]of u.entries())l||c.push(i);c.reverse();for(const i of c)this.removeCross(i);return this}toCompact(){const{diagonalSize:u}=this,c=new Array(u*(u+1)/2);for(let i=0,l=0,m=0;m<c.length;m++)c[m]=this.get(l,i),++i>=u&&(i=++l);return c}static fromCompact(u){const c=u.length,i=(Math.sqrt(8*c+1)-1)/2;if(!Number.isInteger(i))throw new TypeError(`This array is not a compact representation of a Symmetric Matrix, ${JSON.stringify(u)}`);const l=new Jr(i);for(let m=0,B=0,U=0;U<c;U++)l.set(m,B,u[U]),++m>=i&&(m=++B);return l}*upperRightEntries(){for(let u=0,c=0;u<this.diagonalSize;void 0){const i=this.get(u,c);yield[u,c,i],++c>=this.diagonalSize&&(c=++u)}}*upperRightValues(){for(let u=0,c=0;u<this.diagonalSize;void 0)yield this.get(u,c),++c>=this.diagonalSize&&(c=++u)}};_=new WeakMap;let Pe=un;Pe.prototype.klassType="SymmetricMatrix";class xe extends Pe{static isDistanceMatrix(u){return Pe.isSymmetricMatrix(u)&&u.klassSubType==="DistanceMatrix"}constructor(u){if(super(u),!this.isDistance())throw new TypeError("Provided arguments do no produce a distance matrix")}set(u,c,i){return u===c&&(i=0),super.set(u,c,i)}addCross(u,c){return c===void 0&&(c=u,u=this.diagonalSize),c=c.slice(),c[u]=0,super.addCross(u,c)}toSymmetricMatrix(){return new Pe(this)}clone(){const u=new xe(this.diagonalSize);for(const[c,i,l]of this.upperRightEntries())c!==i&&u.set(c,i,l);return u}toCompact(){const{diagonalSize:u}=this,c=(u-1)*u/2,i=new Array(c);for(let l=1,m=0,B=0;B<i.length;B++)i[B]=this.get(m,l),++l>=u&&(l=++m+1);return i}static fromCompact(u){const c=u.length;if(c===0)return new this(0);const i=(Math.sqrt(8*c+1)+1)/2;if(!Number.isInteger(i))throw new TypeError(`This array is not a compact representation of a DistanceMatrix, ${JSON.stringify(u)}`);const l=new this(i);for(let m=1,B=0,U=0;U<c;U++)l.set(m,B,u[U]),++m>=i&&(m=++B+1);return l}}xe.prototype.klassSubType="DistanceMatrix";class ke extends Wt{constructor(u,c,i){super(),this.matrix=u,this.rows=c,this.columns=i}}class vn extends ke{constructor(u,c){yt(u,c),super(u,u.rows,1),this.column=c}set(u,c,i){return this.matrix.set(u,this.column,i),this}get(u){return this.matrix.get(u,this.column)}}class Mn extends ke{constructor(u,c){Vt(u,c),super(u,u.rows,c.length),this.columnIndices=c}set(u,c,i){return this.matrix.set(u,this.columnIndices[c],i),this}get(u,c){return this.matrix.get(u,this.columnIndices[c])}}class In extends ke{constructor(u){super(u,u.rows,u.columns)}set(u,c,i){return this.matrix.set(u,this.columns-c-1,i),this}get(u,c){return this.matrix.get(u,this.columns-c-1)}}class nn extends ke{constructor(u){super(u,u.rows,u.columns)}set(u,c,i){return this.matrix.set(this.rows-u-1,c,i),this}get(u,c){return this.matrix.get(this.rows-u-1,c)}}class Sn extends ke{constructor(u,c){xt(u,c),super(u,1,u.columns),this.row=c}set(u,c,i){return this.matrix.set(this.row,c,i),this}get(u,c){return this.matrix.get(this.row,c)}}class Pn extends ke{constructor(u,c){kt(u,c),super(u,c.length,u.columns),this.rowIndices=c}set(u,c,i){return this.matrix.set(this.rowIndices[u],c,i),this}get(u,c){return this.matrix.get(this.rowIndices[u],c)}}class mn extends ke{constructor(u,c,i){kt(u,c),Vt(u,i),super(u,c.length,i.length),this.rowIndices=c,this.columnIndices=i}set(u,c,i){return this.matrix.set(this.rowIndices[u],this.columnIndices[c],i),this}get(u,c){return this.matrix.get(this.rowIndices[u],this.columnIndices[c])}}class Bn extends ke{constructor(u,c,i,l,m){Ht(u,c,i,l,m),super(u,i-c+1,m-l+1),this.startRow=c,this.startColumn=l}set(u,c,i){return this.matrix.set(this.startRow+u,this.startColumn+c,i),this}get(u,c){return this.matrix.get(this.startRow+u,this.startColumn+c)}}class Be extends ke{constructor(u){super(u,u.columns,u.rows)}set(u,c,i){return this.matrix.set(c,u,i),this}get(u,c){return this.matrix.get(c,u)}}class ze extends Wt{constructor(u,c={}){const{rows:i=1}=c;if(u.length%i!==0)throw new Error("the data length is not divisible by the number of rows");super(),this.rows=i,this.columns=u.length/i,this.data=u}set(u,c,i){let l=this._calculateIndex(u,c);return this.data[l]=i,this}get(u,c){let i=this._calculateIndex(u,c);return this.data[i]}_calculateIndex(u,c){return u*this.columns+c}}class Ae extends Wt{constructor(u){super(),this.data=u,this.rows=u.length,this.columns=u[0].length}set(u,c,i){return this.data[u][c]=i,this}get(u,c){return this.data[u][c]}}function fr(T,u){if(ot.isAnyArray(T))return T[0]&&ot.isAnyArray(T[0])?new Ae(T):new ze(T,u);throw new Error("the argument is not an array")}class _t{constructor(u){u=Ae.checkMatrix(u);let c=u.clone(),i=c.rows,l=c.columns,m=new Float64Array(i),B=1,U,V,G,rt,K,lt,Tt,ct,pt;for(U=0;U<i;U++)m[U]=U;for(ct=new Float64Array(i),V=0;V<l;V++){for(U=0;U<i;U++)ct[U]=c.get(U,V);for(U=0;U<i;U++){for(pt=Math.min(U,V),K=0,G=0;G<pt;G++)K+=c.get(U,G)*ct[G];ct[U]-=K,c.set(U,V,ct[U])}for(rt=V,U=V+1;U<i;U++)Math.abs(ct[U])>Math.abs(ct[rt])&&(rt=U);if(rt!==V){for(G=0;G<l;G++)lt=c.get(rt,G),c.set(rt,G,c.get(V,G)),c.set(V,G,lt);Tt=m[rt],m[rt]=m[V],m[V]=Tt,B=-B}if(V<i&&c.get(V,V)!==0)for(U=V+1;U<i;U++)c.set(U,V,c.get(U,V)/c.get(V,V))}this.LU=c,this.pivotVector=m,this.pivotSign=B}isSingular(){let u=this.LU,c=u.columns;for(let i=0;i<c;i++)if(u.get(i,i)===0)return!0;return!1}solve(u){u=It.checkMatrix(u);let c=this.LU;if(c.rows!==u.rows)throw new Error("Invalid matrix dimensions");if(this.isSingular())throw new Error("LU matrix is singular");let l=u.columns,m=u.subMatrixRow(this.pivotVector,0,l-1),B=c.columns,U,V,G;for(G=0;G<B;G++)for(U=G+1;U<B;U++)for(V=0;V<l;V++)m.set(U,V,m.get(U,V)-m.get(G,V)*c.get(U,G));for(G=B-1;G>=0;G--){for(V=0;V<l;V++)m.set(G,V,m.get(G,V)/c.get(G,G));for(U=0;U<G;U++)for(V=0;V<l;V++)m.set(U,V,m.get(U,V)-m.get(G,V)*c.get(U,G))}return m}get determinant(){let u=this.LU;if(!u.isSquare())throw new Error("Matrix must be square");let c=this.pivotSign,i=u.columns;for(let l=0;l<i;l++)c*=u.get(l,l);return c}get lowerTriangularMatrix(){let u=this.LU,c=u.rows,i=u.columns,l=new It(c,i);for(let m=0;m<c;m++)for(let B=0;B<i;B++)m>B?l.set(m,B,u.get(m,B)):m===B?l.set(m,B,1):l.set(m,B,0);return l}get upperTriangularMatrix(){let u=this.LU,c=u.rows,i=u.columns,l=new It(c,i);for(let m=0;m<c;m++)for(let B=0;B<i;B++)m<=B?l.set(m,B,u.get(m,B)):l.set(m,B,0);return l}get pivotPermutationVector(){return Array.from(this.pivotVector)}}function rn(T,u){let c=0;return Math.abs(T)>Math.abs(u)?(c=u/T,Math.abs(T)*Math.sqrt(1+c*c)):u!==0?(c=T/u,Math.abs(u)*Math.sqrt(1+c*c)):0}class Un{constructor(u){u=Ae.checkMatrix(u);let c=u.clone(),i=u.rows,l=u.columns,m=new Float64Array(l),B,U,V,G;for(V=0;V<l;V++){let rt=0;for(B=V;B<i;B++)rt=rn(rt,c.get(B,V));if(rt!==0){for(c.get(V,V)<0&&(rt=-rt),B=V;B<i;B++)c.set(B,V,c.get(B,V)/rt);for(c.set(V,V,c.get(V,V)+1),U=V+1;U<l;U++){for(G=0,B=V;B<i;B++)G+=c.get(B,V)*c.get(B,U);for(G=-G/c.get(V,V),B=V;B<i;B++)c.set(B,U,c.get(B,U)+G*c.get(B,V))}}m[V]=-rt}this.QR=c,this.Rdiag=m}solve(u){u=It.checkMatrix(u);let c=this.QR,i=c.rows;if(u.rows!==i)throw new Error("Matrix row dimensions must agree");if(!this.isFullRank())throw new Error("Matrix is rank deficient");let l=u.columns,m=u.clone(),B=c.columns,U,V,G,rt;for(G=0;G<B;G++)for(V=0;V<l;V++){for(rt=0,U=G;U<i;U++)rt+=c.get(U,G)*m.get(U,V);for(rt=-rt/c.get(G,G),U=G;U<i;U++)m.set(U,V,m.get(U,V)+rt*c.get(U,G))}for(G=B-1;G>=0;G--){for(V=0;V<l;V++)m.set(G,V,m.get(G,V)/this.Rdiag[G]);for(U=0;U<G;U++)for(V=0;V<l;V++)m.set(U,V,m.get(U,V)-m.get(G,V)*c.get(U,G))}return m.subMatrix(0,B-1,0,l-1)}isFullRank(){let u=this.QR.columns;for(let c=0;c<u;c++)if(this.Rdiag[c]===0)return!1;return!0}get upperTriangularMatrix(){let u=this.QR,c=u.columns,i=new It(c,c),l,m;for(l=0;l<c;l++)for(m=0;m<c;m++)l<m?i.set(l,m,u.get(l,m)):l===m?i.set(l,m,this.Rdiag[l]):i.set(l,m,0);return i}get orthogonalMatrix(){let u=this.QR,c=u.rows,i=u.columns,l=new It(c,i),m,B,U,V;for(U=i-1;U>=0;U--){for(m=0;m<c;m++)l.set(m,U,0);for(l.set(U,U,1),B=U;B<i;B++)if(u.get(U,U)!==0){for(V=0,m=U;m<c;m++)V+=u.get(m,U)*l.get(m,B);for(V=-V/u.get(U,U),m=U;m<c;m++)l.set(m,B,l.get(m,B)+V*u.get(m,U))}}return l}}class cn{constructor(u,c={}){if(u=Ae.checkMatrix(u),u.isEmpty())throw new Error("Matrix must be non-empty");let i=u.rows,l=u.columns;const{computeLeftSingularVectors:m=!0,computeRightSingularVectors:B=!0,autoTranspose:U=!1}=c;let V=!!m,G=!!B,rt=!1,K;if(i<l)if(!U)K=u.clone(),console.warn("Computing SVD on a matrix with more columns than rows. Consider enabling autoTranspose");else{K=u.transpose(),i=K.rows,l=K.columns,rt=!0;let tt=V;V=G,G=tt}else K=u.clone();let lt=Math.min(i,l),Tt=Math.min(i+1,l),ct=new Float64Array(Tt),pt=new It(i,lt),Rt=new It(l,l),Z=new Float64Array(l),St=new Float64Array(i),Ct=new Float64Array(Tt);for(let tt=0;tt<Tt;tt++)Ct[tt]=tt;let Xt=Math.min(i-1,l),Zt=Math.max(0,Math.min(l-2,i)),ge=Math.max(Xt,Zt);for(let tt=0;tt<ge;tt++){if(tt<Xt){ct[tt]=0;for(let wt=tt;wt<i;wt++)ct[tt]=rn(ct[tt],K.get(wt,tt));if(ct[tt]!==0){K.get(tt,tt)<0&&(ct[tt]=-ct[tt]);for(let wt=tt;wt<i;wt++)K.set(wt,tt,K.get(wt,tt)/ct[tt]);K.set(tt,tt,K.get(tt,tt)+1)}ct[tt]=-ct[tt]}for(let wt=tt+1;wt<l;wt++){if(tt<Xt&&ct[tt]!==0){let Lt=0;for(let Mt=tt;Mt<i;Mt++)Lt+=K.get(Mt,tt)*K.get(Mt,wt);Lt=-Lt/K.get(tt,tt);for(let Mt=tt;Mt<i;Mt++)K.set(Mt,wt,K.get(Mt,wt)+Lt*K.get(Mt,tt))}Z[wt]=K.get(tt,wt)}if(V&&tt<Xt)for(let wt=tt;wt<i;wt++)pt.set(wt,tt,K.get(wt,tt));if(tt<Zt){Z[tt]=0;for(let wt=tt+1;wt<l;wt++)Z[tt]=rn(Z[tt],Z[wt]);if(Z[tt]!==0){Z[tt+1]<0&&(Z[tt]=0-Z[tt]);for(let wt=tt+1;wt<l;wt++)Z[wt]/=Z[tt];Z[tt+1]+=1}if(Z[tt]=-Z[tt],tt+1<i&&Z[tt]!==0){for(let wt=tt+1;wt<i;wt++)St[wt]=0;for(let wt=tt+1;wt<i;wt++)for(let Lt=tt+1;Lt<l;Lt++)St[wt]+=Z[Lt]*K.get(wt,Lt);for(let wt=tt+1;wt<l;wt++){let Lt=-Z[wt]/Z[tt+1];for(let Mt=tt+1;Mt<i;Mt++)K.set(Mt,wt,K.get(Mt,wt)+Lt*St[Mt])}}if(G)for(let wt=tt+1;wt<l;wt++)Rt.set(wt,tt,Z[wt])}}let Ut=Math.min(l,i+1);if(Xt<l&&(ct[Xt]=K.get(Xt,Xt)),i<Ut&&(ct[Ut-1]=0),Zt+1<Ut&&(Z[Zt]=K.get(Zt,Ut-1)),Z[Ut-1]=0,V){for(let tt=Xt;tt<lt;tt++){for(let wt=0;wt<i;wt++)pt.set(wt,tt,0);pt.set(tt,tt,1)}for(let tt=Xt-1;tt>=0;tt--)if(ct[tt]!==0){for(let wt=tt+1;wt<lt;wt++){let Lt=0;for(let Mt=tt;Mt<i;Mt++)Lt+=pt.get(Mt,tt)*pt.get(Mt,wt);Lt=-Lt/pt.get(tt,tt);for(let Mt=tt;Mt<i;Mt++)pt.set(Mt,wt,pt.get(Mt,wt)+Lt*pt.get(Mt,tt))}for(let wt=tt;wt<i;wt++)pt.set(wt,tt,-pt.get(wt,tt));pt.set(tt,tt,1+pt.get(tt,tt));for(let wt=0;wt<tt-1;wt++)pt.set(wt,tt,0)}else{for(let wt=0;wt<i;wt++)pt.set(wt,tt,0);pt.set(tt,tt,1)}}if(G)for(let tt=l-1;tt>=0;tt--){if(tt<Zt&&Z[tt]!==0)for(let wt=tt+1;wt<l;wt++){let Lt=0;for(let Mt=tt+1;Mt<l;Mt++)Lt+=Rt.get(Mt,tt)*Rt.get(Mt,wt);Lt=-Lt/Rt.get(tt+1,tt);for(let Mt=tt+1;Mt<l;Mt++)Rt.set(Mt,wt,Rt.get(Mt,wt)+Lt*Rt.get(Mt,tt))}for(let wt=0;wt<l;wt++)Rt.set(wt,tt,0);Rt.set(tt,tt,1)}let Yt=Ut-1,ce=Number.EPSILON;for(;Ut>0;){let tt,wt;for(tt=Ut-2;tt>=-1&&tt!==-1;tt--){const Lt=Number.MIN_VALUE+ce*Math.abs(ct[tt]+Math.abs(ct[tt+1]));if(Math.abs(Z[tt])<=Lt||Number.isNaN(Z[tt])){Z[tt]=0;break}}if(tt===Ut-2)wt=4;else{let Lt;for(Lt=Ut-1;Lt>=tt&&Lt!==tt;Lt--){let Mt=(Lt!==Ut?Math.abs(Z[Lt]):0)+(Lt!==tt+1?Math.abs(Z[Lt-1]):0);if(Math.abs(ct[Lt])<=ce*Mt){ct[Lt]=0;break}}Lt===tt?wt=3:Lt===Ut-1?wt=1:(wt=2,tt=Lt)}switch(tt++,wt){case 1:{let Lt=Z[Ut-2];Z[Ut-2]=0;for(let Mt=Ut-2;Mt>=tt;Mt--){let we=rn(ct[Mt],Lt),ae=ct[Mt]/we,fe=Lt/we;if(ct[Mt]=we,Mt!==tt&&(Lt=-fe*Z[Mt-1],Z[Mt-1]=ae*Z[Mt-1]),G)for(let pe=0;pe<l;pe++)we=ae*Rt.get(pe,Mt)+fe*Rt.get(pe,Ut-1),Rt.set(pe,Ut-1,-fe*Rt.get(pe,Mt)+ae*Rt.get(pe,Ut-1)),Rt.set(pe,Mt,we)}break}case 2:{let Lt=Z[tt-1];Z[tt-1]=0;for(let Mt=tt;Mt<Ut;Mt++){let we=rn(ct[Mt],Lt),ae=ct[Mt]/we,fe=Lt/we;if(ct[Mt]=we,Lt=-fe*Z[Mt],Z[Mt]=ae*Z[Mt],V)for(let pe=0;pe<i;pe++)we=ae*pt.get(pe,Mt)+fe*pt.get(pe,tt-1),pt.set(pe,tt-1,-fe*pt.get(pe,Mt)+ae*pt.get(pe,tt-1)),pt.set(pe,Mt,we)}break}case 3:{const Lt=Math.max(Math.abs(ct[Ut-1]),Math.abs(ct[Ut-2]),Math.abs(Z[Ut-2]),Math.abs(ct[tt]),Math.abs(Z[tt])),Mt=ct[Ut-1]/Lt,we=ct[Ut-2]/Lt,ae=Z[Ut-2]/Lt,fe=ct[tt]/Lt,pe=Z[tt]/Lt,Re=((we+Mt)*(we-Mt)+ae*ae)/2,_e=Mt*ae*(Mt*ae);let Se=0;(Re!==0||_e!==0)&&(Re<0?Se=0-Math.sqrt(Re*Re+_e):Se=Math.sqrt(Re*Re+_e),Se=_e/(Re+Se));let Je=(fe+Mt)*(fe-Mt)+Se,Qe=fe*pe;for(let te=tt;te<Ut-1;te++){let Le=rn(Je,Qe);Le===0&&(Le=Number.MIN_VALUE);let Ue=Je/Le,Ve=Qe/Le;if(te!==tt&&(Z[te-1]=Le),Je=Ue*ct[te]+Ve*Z[te],Z[te]=Ue*Z[te]-Ve*ct[te],Qe=Ve*ct[te+1],ct[te+1]=Ue*ct[te+1],G)for(let Oe=0;Oe<l;Oe++)Le=Ue*Rt.get(Oe,te)+Ve*Rt.get(Oe,te+1),Rt.set(Oe,te+1,-Ve*Rt.get(Oe,te)+Ue*Rt.get(Oe,te+1)),Rt.set(Oe,te,Le);if(Le=rn(Je,Qe),Le===0&&(Le=Number.MIN_VALUE),Ue=Je/Le,Ve=Qe/Le,ct[te]=Le,Je=Ue*Z[te]+Ve*ct[te+1],ct[te+1]=-Ve*Z[te]+Ue*ct[te+1],Qe=Ve*Z[te+1],Z[te+1]=Ue*Z[te+1],V&&te<i-1)for(let Oe=0;Oe<i;Oe++)Le=Ue*pt.get(Oe,te)+Ve*pt.get(Oe,te+1),pt.set(Oe,te+1,-Ve*pt.get(Oe,te)+Ue*pt.get(Oe,te+1)),pt.set(Oe,te,Le)}Z[Ut-2]=Je;break}case 4:{if(ct[tt]<=0&&(ct[tt]=ct[tt]<0?-ct[tt]:0,G))for(let Lt=0;Lt<=Yt;Lt++)Rt.set(Lt,tt,-Rt.get(Lt,tt));for(;tt<Yt&&!(ct[tt]>=ct[tt+1]);){let Lt=ct[tt];if(ct[tt]=ct[tt+1],ct[tt+1]=Lt,G&&tt<l-1)for(let Mt=0;Mt<l;Mt++)Lt=Rt.get(Mt,tt+1),Rt.set(Mt,tt+1,Rt.get(Mt,tt)),Rt.set(Mt,tt,Lt);if(V&&tt<i-1)for(let Mt=0;Mt<i;Mt++)Lt=pt.get(Mt,tt+1),pt.set(Mt,tt+1,pt.get(Mt,tt)),pt.set(Mt,tt,Lt);tt++}Ut--;break}}}if(rt){let tt=Rt;Rt=pt,pt=tt}this.m=i,this.n=l,this.s=ct,this.U=pt,this.V=Rt}solve(u){let c=u,i=this.threshold,l=this.s.length,m=It.zeros(l,l);for(let lt=0;lt<l;lt++)Math.abs(this.s[lt])<=i?m.set(lt,lt,0):m.set(lt,lt,1/this.s[lt]);let B=this.U,U=this.rightSingularVectors,V=U.mmul(m),G=U.rows,rt=B.rows,K=It.zeros(G,rt);for(let lt=0;lt<G;lt++)for(let Tt=0;Tt<rt;Tt++){let ct=0;for(let pt=0;pt<l;pt++)ct+=V.get(lt,pt)*B.get(Tt,pt);K.set(lt,Tt,ct)}return K.mmul(c)}solveForDiagonal(u){return this.solve(It.diag(u))}inverse(){let u=this.V,c=this.threshold,i=u.rows,l=u.columns,m=new It(i,this.s.length);for(let rt=0;rt<i;rt++)for(let K=0;K<l;K++)Math.abs(this.s[K])>c&&m.set(rt,K,u.get(rt,K)/this.s[K]);let B=this.U,U=B.rows,V=B.columns,G=new It(i,U);for(let rt=0;rt<i;rt++)for(let K=0;K<U;K++){let lt=0;for(let Tt=0;Tt<V;Tt++)lt+=m.get(rt,Tt)*B.get(K,Tt);G.set(rt,K,lt)}return G}get condition(){return this.s[0]/this.s[Math.min(this.m,this.n)-1]}get norm2(){return this.s[0]}get rank(){let u=Math.max(this.m,this.n)*this.s[0]*Number.EPSILON,c=0,i=this.s;for(let l=0,m=i.length;l<m;l++)i[l]>u&&c++;return c}get diagonal(){return Array.from(this.s)}get threshold(){return Number.EPSILON/2*Math.max(this.m,this.n)*this.s[0]}get leftSingularVectors(){return this.U}get rightSingularVectors(){return this.V}get diagonalMatrix(){return It.diag(this.s)}}function lr(T,u=!1){return T=Ae.checkMatrix(T),u?new cn(T).inverse():Jn(T,It.eye(T.rows))}function Jn(T,u,c=!1){return T=Ae.checkMatrix(T),u=Ae.checkMatrix(u),c?new cn(T).solve(u):T.isSquare()?new _t(T).solve(u):new Un(T).solve(u)}function Rn(T){if(T=It.checkMatrix(T),T.isSquare()){if(T.columns===0)return 1;let u,c,i,l;if(T.columns===2)return u=T.get(0,0),c=T.get(0,1),i=T.get(1,0),l=T.get(1,1),u*l-c*i;if(T.columns===3){let m,B,U;return m=new mn(T,[1,2],[1,2]),B=new mn(T,[1,2],[0,2]),U=new mn(T,[1,2],[0,1]),u=T.get(0,0),c=T.get(0,1),i=T.get(0,2),u*Rn(m)-c*Rn(B)+i*Rn(U)}else return new _t(T).determinant}else throw Error("determinant can only be calculated for a square matrix")}function dr(T,u){let c=[];for(let i=0;i<T;i++)i!==u&&c.push(i);return c}function hr(T,u,c,i=1e-9,l=1e-9){if(T>l)return new Array(u.rows+1).fill(0);{let m=u.addRow(c,[0]);for(let B=0;B<m.rows;B++)Math.abs(m.get(B,0))<i&&m.set(B,0,0);return m.to1DArray()}}function Vn(T,u={}){const{thresholdValue:c=1e-9,thresholdError:i=1e-9}=u;T=It.checkMatrix(T);let l=T.rows,m=new It(l,l);for(let B=0;B<l;B++){let U=It.columnVector(T.getRow(B)),V=T.subMatrixRow(dr(l,B)).transpose(),rt=new cn(V).solve(U),K=It.sub(U,V.mmul(rt)).abs().max();m.setRow(B,hr(K,rt,B,c,i))}return m}function gr(T,u=Number.EPSILON){if(T=It.checkMatrix(T),T.isEmpty())return T.transpose();let c=new cn(T,{autoTranspose:!0}),i=c.leftSingularVectors,l=c.rightSingularVectors,m=c.diagonal;for(let B=0;B<m.length;B++)Math.abs(m[B])>u?m[B]=1/m[B]:m[B]=0;return l.mmul(It.diag(m).mmul(i.transpose()))}function Gn(T,u=T,c={}){T=new It(T);let i=!1;if(typeof u=="object"&&!It.isMatrix(u)&&!ot.isAnyArray(u)?(c=u,u=T,i=!0):u=new It(u),T.rows!==u.rows)throw new TypeError("Both matrices must have the same number of rows");const{center:l=!0}=c;l&&(T=T.center("column"),i||(u=u.center("column")));const m=T.transpose().mmul(u);for(let B=0;B<m.rows;B++)for(let U=0;U<m.columns;U++)m.set(B,U,m.get(B,U)*(1/(T.rows-1)));return m}function pr(T,u=T,c={}){T=new It(T);let i=!1;if(typeof u=="object"&&!It.isMatrix(u)&&!ot.isAnyArray(u)?(c=u,u=T,i=!0):u=new It(u),T.rows!==u.rows)throw new TypeError("Both matrices must have the same number of rows");const{center:l=!0,scale:m=!0}=c;l&&(T.center("column"),i||u.center("column")),m&&(T.scale("column"),i||u.scale("column"));const B=T.standardDeviation("column",{unbiased:!0}),U=i?B:u.standardDeviation("column",{unbiased:!0}),V=T.transpose().mmul(u);for(let G=0;G<V.rows;G++)for(let rt=0;rt<V.columns;rt++)V.set(G,rt,V.get(G,rt)*(1/(B[G]*U[rt]))*(1/(T.rows-1)));return V}class Qn{constructor(u,c={}){const{assumeSymmetric:i=!1}=c;if(u=Ae.checkMatrix(u),!u.isSquare())throw new Error("Matrix is not a square matrix");if(u.isEmpty())throw new Error("Matrix must be non-empty");let l=u.columns,m=new It(l,l),B=new Float64Array(l),U=new Float64Array(l),V=u,G,rt,K=!1;if(i?K=!0:K=u.isSymmetric(),K){for(G=0;G<l;G++)for(rt=0;rt<l;rt++)m.set(G,rt,V.get(G,rt));vr(l,U,B,m),mr(l,U,B,m)}else{let lt=new It(l,l),Tt=new Float64Array(l);for(rt=0;rt<l;rt++)for(G=0;G<l;G++)lt.set(G,rt,V.get(G,rt));yn(l,lt,Tt,m),yr(l,U,B,m,lt)}this.n=l,this.e=U,this.d=B,this.V=m}get realEigenvalues(){return Array.from(this.d)}get imaginaryEigenvalues(){return Array.from(this.e)}get eigenvectorMatrix(){return this.V}get diagonalMatrix(){let u=this.n,c=this.e,i=this.d,l=new It(u,u),m,B;for(m=0;m<u;m++){for(B=0;B<u;B++)l.set(m,B,0);l.set(m,m,i[m]),c[m]>0?l.set(m,m+1,c[m]):c[m]<0&&l.set(m,m-1,c[m])}return l}}function vr(T,u,c,i){let l,m,B,U,V,G,rt,K;for(V=0;V<T;V++)c[V]=i.get(T-1,V);for(U=T-1;U>0;U--){for(K=0,B=0,G=0;G<U;G++)K=K+Math.abs(c[G]);if(K===0)for(u[U]=c[U-1],V=0;V<U;V++)c[V]=i.get(U-1,V),i.set(U,V,0),i.set(V,U,0);else{for(G=0;G<U;G++)c[G]/=K,B+=c[G]*c[G];for(l=c[U-1],m=Math.sqrt(B),l>0&&(m=-m),u[U]=K*m,B=B-l*m,c[U-1]=l-m,V=0;V<U;V++)u[V]=0;for(V=0;V<U;V++){for(l=c[V],i.set(V,U,l),m=u[V]+i.get(V,V)*l,G=V+1;G<=U-1;G++)m+=i.get(G,V)*c[G],u[G]+=i.get(G,V)*l;u[V]=m}for(l=0,V=0;V<U;V++)u[V]/=B,l+=u[V]*c[V];for(rt=l/(B+B),V=0;V<U;V++)u[V]-=rt*c[V];for(V=0;V<U;V++){for(l=c[V],m=u[V],G=V;G<=U-1;G++)i.set(G,V,i.get(G,V)-(l*u[G]+m*c[G]));c[V]=i.get(U-1,V),i.set(U,V,0)}}c[U]=B}for(U=0;U<T-1;U++){if(i.set(T-1,U,i.get(U,U)),i.set(U,U,1),B=c[U+1],B!==0){for(G=0;G<=U;G++)c[G]=i.get(G,U+1)/B;for(V=0;V<=U;V++){for(m=0,G=0;G<=U;G++)m+=i.get(G,U+1)*i.get(G,V);for(G=0;G<=U;G++)i.set(G,V,i.get(G,V)-m*c[G])}}for(G=0;G<=U;G++)i.set(G,U+1,0)}for(V=0;V<T;V++)c[V]=i.get(T-1,V),i.set(T-1,V,0);i.set(T-1,T-1,1),u[0]=0}function mr(T,u,c,i){let l,m,B,U,V,G,rt,K,lt,Tt,ct,pt,Rt,Z,St,Ct;for(B=1;B<T;B++)u[B-1]=u[B];u[T-1]=0;let Xt=0,Zt=0,ge=Number.EPSILON;for(G=0;G<T;G++){for(Zt=Math.max(Zt,Math.abs(c[G])+Math.abs(u[G])),rt=G;rt<T&&!(Math.abs(u[rt])<=ge*Zt);)rt++;if(rt>G)do{for(l=c[G],K=(c[G+1]-l)/(2*u[G]),lt=rn(K,1),K<0&&(lt=-lt),c[G]=u[G]/(K+lt),c[G+1]=u[G]*(K+lt),Tt=c[G+1],m=l-c[G],B=G+2;B<T;B++)c[B]-=m;for(Xt=Xt+m,K=c[rt],ct=1,pt=ct,Rt=ct,Z=u[G+1],St=0,Ct=0,B=rt-1;B>=G;B--)for(Rt=pt,pt=ct,Ct=St,l=ct*u[B],m=ct*K,lt=rn(K,u[B]),u[B+1]=St*lt,St=u[B]/lt,ct=K/lt,K=ct*c[B]-St*l,c[B+1]=m+St*(ct*l+St*c[B]),V=0;V<T;V++)m=i.get(V,B+1),i.set(V,B+1,St*i.get(V,B)+ct*m),i.set(V,B,ct*i.get(V,B)-St*m);K=-St*Ct*Rt*Z*u[G]/Tt,u[G]=St*K,c[G]=ct*K}while(Math.abs(u[G])>ge*Zt);c[G]=c[G]+Xt,u[G]=0}for(B=0;B<T-1;B++){for(V=B,K=c[B],U=B+1;U<T;U++)c[U]<K&&(V=U,K=c[U]);if(V!==B)for(c[V]=c[B],c[B]=K,U=0;U<T;U++)K=i.get(U,B),i.set(U,B,i.get(U,V)),i.set(U,V,K)}}function yn(T,u,c,i){let l=0,m=T-1,B,U,V,G,rt,K,lt;for(K=l+1;K<=m-1;K++){for(lt=0,G=K;G<=m;G++)lt=lt+Math.abs(u.get(G,K-1));if(lt!==0){for(V=0,G=m;G>=K;G--)c[G]=u.get(G,K-1)/lt,V+=c[G]*c[G];for(U=Math.sqrt(V),c[K]>0&&(U=-U),V=V-c[K]*U,c[K]=c[K]-U,rt=K;rt<T;rt++){for(B=0,G=m;G>=K;G--)B+=c[G]*u.get(G,rt);for(B=B/V,G=K;G<=m;G++)u.set(G,rt,u.get(G,rt)-B*c[G])}for(G=0;G<=m;G++){for(B=0,rt=m;rt>=K;rt--)B+=c[rt]*u.get(G,rt);for(B=B/V,rt=K;rt<=m;rt++)u.set(G,rt,u.get(G,rt)-B*c[rt])}c[K]=lt*c[K],u.set(K,K-1,lt*U)}}for(G=0;G<T;G++)for(rt=0;rt<T;rt++)i.set(G,rt,G===rt?1:0);for(K=m-1;K>=l+1;K--)if(u.get(K,K-1)!==0){for(G=K+1;G<=m;G++)c[G]=u.get(G,K-1);for(rt=K;rt<=m;rt++){for(U=0,G=K;G<=m;G++)U+=c[G]*i.get(G,rt);for(U=U/c[K]/u.get(K,K-1),G=K;G<=m;G++)i.set(G,rt,i.get(G,rt)+U*c[G])}}}function yr(T,u,c,i,l){let m=T-1,B=0,U=T-1,V=Number.EPSILON,G=0,rt=0,K=0,lt=0,Tt=0,ct=0,pt=0,Rt=0,Z,St,Ct,Xt,Zt,ge,Ut,Yt,ce,tt,wt,Lt,Mt,we,ae;for(Z=0;Z<T;Z++)for((Z<B||Z>U)&&(c[Z]=l.get(Z,Z),u[Z]=0),St=Math.max(Z-1,0);St<T;St++)rt=rt+Math.abs(l.get(Z,St));for(;m>=B;){for(Xt=m;Xt>B&&(ct=Math.abs(l.get(Xt-1,Xt-1))+Math.abs(l.get(Xt,Xt)),ct===0&&(ct=rt),!(Math.abs(l.get(Xt,Xt-1))<V*ct));)Xt--;if(Xt===m)l.set(m,m,l.get(m,m)+G),c[m]=l.get(m,m),u[m]=0,m--,Rt=0;else if(Xt===m-1){if(Ut=l.get(m,m-1)*l.get(m-1,m),K=(l.get(m-1,m-1)-l.get(m,m))/2,lt=K*K+Ut,pt=Math.sqrt(Math.abs(lt)),l.set(m,m,l.get(m,m)+G),l.set(m-1,m-1,l.get(m-1,m-1)+G),Yt=l.get(m,m),lt>=0){for(pt=K>=0?K+pt:K-pt,c[m-1]=Yt+pt,c[m]=c[m-1],pt!==0&&(c[m]=Yt-Ut/pt),u[m-1]=0,u[m]=0,Yt=l.get(m,m-1),ct=Math.abs(Yt)+Math.abs(pt),K=Yt/ct,lt=pt/ct,Tt=Math.sqrt(K*K+lt*lt),K=K/Tt,lt=lt/Tt,St=m-1;St<T;St++)pt=l.get(m-1,St),l.set(m-1,St,lt*pt+K*l.get(m,St)),l.set(m,St,lt*l.get(m,St)-K*pt);for(Z=0;Z<=m;Z++)pt=l.get(Z,m-1),l.set(Z,m-1,lt*pt+K*l.get(Z,m)),l.set(Z,m,lt*l.get(Z,m)-K*pt);for(Z=B;Z<=U;Z++)pt=i.get(Z,m-1),i.set(Z,m-1,lt*pt+K*i.get(Z,m)),i.set(Z,m,lt*i.get(Z,m)-K*pt)}else c[m-1]=Yt+K,c[m]=Yt+K,u[m-1]=pt,u[m]=-pt;m=m-2,Rt=0}else{if(Yt=l.get(m,m),ce=0,Ut=0,Xt<m&&(ce=l.get(m-1,m-1),Ut=l.get(m,m-1)*l.get(m-1,m)),Rt===10){for(G+=Yt,Z=B;Z<=m;Z++)l.set(Z,Z,l.get(Z,Z)-Yt);ct=Math.abs(l.get(m,m-1))+Math.abs(l.get(m-1,m-2)),Yt=ce=.75*ct,Ut=-.4375*ct*ct}if(Rt===30&&(ct=(ce-Yt)/2,ct=ct*ct+Ut,ct>0)){for(ct=Math.sqrt(ct),ce<Yt&&(ct=-ct),ct=Yt-Ut/((ce-Yt)/2+ct),Z=B;Z<=m;Z++)l.set(Z,Z,l.get(Z,Z)-ct);G+=ct,Yt=ce=Ut=.964}for(Rt=Rt+1,Zt=m-2;Zt>=Xt&&(pt=l.get(Zt,Zt),Tt=Yt-pt,ct=ce-pt,K=(Tt*ct-Ut)/l.get(Zt+1,Zt)+l.get(Zt,Zt+1),lt=l.get(Zt+1,Zt+1)-pt-Tt-ct,Tt=l.get(Zt+2,Zt+1),ct=Math.abs(K)+Math.abs(lt)+Math.abs(Tt),K=K/ct,lt=lt/ct,Tt=Tt/ct,!(Zt===Xt||Math.abs(l.get(Zt,Zt-1))*(Math.abs(lt)+Math.abs(Tt))<V*(Math.abs(K)*(Math.abs(l.get(Zt-1,Zt-1))+Math.abs(pt)+Math.abs(l.get(Zt+1,Zt+1))))));)Zt--;for(Z=Zt+2;Z<=m;Z++)l.set(Z,Z-2,0),Z>Zt+2&&l.set(Z,Z-3,0);for(Ct=Zt;Ct<=m-1&&(we=Ct!==m-1,Ct!==Zt&&(K=l.get(Ct,Ct-1),lt=l.get(Ct+1,Ct-1),Tt=we?l.get(Ct+2,Ct-1):0,Yt=Math.abs(K)+Math.abs(lt)+Math.abs(Tt),Yt!==0&&(K=K/Yt,lt=lt/Yt,Tt=Tt/Yt)),Yt!==0);Ct++)if(ct=Math.sqrt(K*K+lt*lt+Tt*Tt),K<0&&(ct=-ct),ct!==0){for(Ct!==Zt?l.set(Ct,Ct-1,-ct*Yt):Xt!==Zt&&l.set(Ct,Ct-1,-l.get(Ct,Ct-1)),K=K+ct,Yt=K/ct,ce=lt/ct,pt=Tt/ct,lt=lt/K,Tt=Tt/K,St=Ct;St<T;St++)K=l.get(Ct,St)+lt*l.get(Ct+1,St),we&&(K=K+Tt*l.get(Ct+2,St),l.set(Ct+2,St,l.get(Ct+2,St)-K*pt)),l.set(Ct,St,l.get(Ct,St)-K*Yt),l.set(Ct+1,St,l.get(Ct+1,St)-K*ce);for(Z=0;Z<=Math.min(m,Ct+3);Z++)K=Yt*l.get(Z,Ct)+ce*l.get(Z,Ct+1),we&&(K=K+pt*l.get(Z,Ct+2),l.set(Z,Ct+2,l.get(Z,Ct+2)-K*Tt)),l.set(Z,Ct,l.get(Z,Ct)-K),l.set(Z,Ct+1,l.get(Z,Ct+1)-K*lt);for(Z=B;Z<=U;Z++)K=Yt*i.get(Z,Ct)+ce*i.get(Z,Ct+1),we&&(K=K+pt*i.get(Z,Ct+2),i.set(Z,Ct+2,i.get(Z,Ct+2)-K*Tt)),i.set(Z,Ct,i.get(Z,Ct)-K),i.set(Z,Ct+1,i.get(Z,Ct+1)-K*lt)}}}if(rt!==0){for(m=T-1;m>=0;m--)if(K=c[m],lt=u[m],lt===0)for(Xt=m,l.set(m,m,1),Z=m-1;Z>=0;Z--){for(Ut=l.get(Z,Z)-K,Tt=0,St=Xt;St<=m;St++)Tt=Tt+l.get(Z,St)*l.get(St,m);if(u[Z]<0)pt=Ut,ct=Tt;else if(Xt=Z,u[Z]===0?l.set(Z,m,Ut!==0?-Tt/Ut:-Tt/(V*rt)):(Yt=l.get(Z,Z+1),ce=l.get(Z+1,Z),lt=(c[Z]-K)*(c[Z]-K)+u[Z]*u[Z],ge=(Yt*ct-pt*Tt)/lt,l.set(Z,m,ge),l.set(Z+1,m,Math.abs(Yt)>Math.abs(pt)?(-Tt-Ut*ge)/Yt:(-ct-ce*ge)/pt)),ge=Math.abs(l.get(Z,m)),V*ge*ge>1)for(St=Z;St<=m;St++)l.set(St,m,l.get(St,m)/ge)}else if(lt<0)for(Xt=m-1,Math.abs(l.get(m,m-1))>Math.abs(l.get(m-1,m))?(l.set(m-1,m-1,lt/l.get(m,m-1)),l.set(m-1,m,-(l.get(m,m)-K)/l.get(m,m-1))):(ae=On(0,-l.get(m-1,m),l.get(m-1,m-1)-K,lt),l.set(m-1,m-1,ae[0]),l.set(m-1,m,ae[1])),l.set(m,m-1,0),l.set(m,m,1),Z=m-2;Z>=0;Z--){for(tt=0,wt=0,St=Xt;St<=m;St++)tt=tt+l.get(Z,St)*l.get(St,m-1),wt=wt+l.get(Z,St)*l.get(St,m);if(Ut=l.get(Z,Z)-K,u[Z]<0)pt=Ut,Tt=tt,ct=wt;else if(Xt=Z,u[Z]===0?(ae=On(-tt,-wt,Ut,lt),l.set(Z,m-1,ae[0]),l.set(Z,m,ae[1])):(Yt=l.get(Z,Z+1),ce=l.get(Z+1,Z),Lt=(c[Z]-K)*(c[Z]-K)+u[Z]*u[Z]-lt*lt,Mt=(c[Z]-K)*2*lt,Lt===0&&Mt===0&&(Lt=V*rt*(Math.abs(Ut)+Math.abs(lt)+Math.abs(Yt)+Math.abs(ce)+Math.abs(pt))),ae=On(Yt*Tt-pt*tt+lt*wt,Yt*ct-pt*wt-lt*tt,Lt,Mt),l.set(Z,m-1,ae[0]),l.set(Z,m,ae[1]),Math.abs(Yt)>Math.abs(pt)+Math.abs(lt)?(l.set(Z+1,m-1,(-tt-Ut*l.get(Z,m-1)+lt*l.get(Z,m))/Yt),l.set(Z+1,m,(-wt-Ut*l.get(Z,m)-lt*l.get(Z,m-1))/Yt)):(ae=On(-Tt-ce*l.get(Z,m-1),-ct-ce*l.get(Z,m),pt,lt),l.set(Z+1,m-1,ae[0]),l.set(Z+1,m,ae[1]))),ge=Math.max(Math.abs(l.get(Z,m-1)),Math.abs(l.get(Z,m))),V*ge*ge>1)for(St=Z;St<=m;St++)l.set(St,m-1,l.get(St,m-1)/ge),l.set(St,m,l.get(St,m)/ge)}for(Z=0;Z<T;Z++)if(Z<B||Z>U)for(St=Z;St<T;St++)i.set(Z,St,l.get(Z,St));for(St=T-1;St>=B;St--)for(Z=B;Z<=U;Z++){for(pt=0,Ct=B;Ct<=Math.min(St,U);Ct++)pt=pt+i.get(Z,Ct)*l.get(Ct,St);i.set(Z,St,pt)}}}function On(T,u,c,i){let l,m;return Math.abs(c)>Math.abs(i)?(l=i/c,m=c+l*i,[(T+l*u)/m,(u-l*T)/m]):(l=c/i,m=i+l*c,[(l*T+u)/m,(l*u-T)/m])}class Wn{constructor(u){if(u=Ae.checkMatrix(u),!u.isSymmetric())throw new Error("Matrix is not symmetric");let c=u,i=c.rows,l=new It(i,i),m=!0,B,U,V;for(U=0;U<i;U++){let G=0;for(V=0;V<U;V++){let rt=0;for(B=0;B<V;B++)rt+=l.get(V,B)*l.get(U,B);rt=(c.get(U,V)-rt)/l.get(V,V),l.set(U,V,rt),G=G+rt*rt}for(G=c.get(U,U)-G,m&&(m=G>0),l.set(U,U,Math.sqrt(Math.max(G,0))),V=U+1;V<i;V++)l.set(U,V,0)}this.L=l,this.positiveDefinite=m}isPositiveDefinite(){return this.positiveDefinite}solve(u){u=Ae.checkMatrix(u);let c=this.L,i=c.rows;if(u.rows!==i)throw new Error("Matrix dimensions do not match");if(this.isPositiveDefinite()===!1)throw new Error("Matrix is not positive definite");let l=u.columns,m=u.clone(),B,U,V;for(V=0;V<i;V++)for(U=0;U<l;U++){for(B=0;B<V;B++)m.set(V,U,m.get(V,U)-m.get(B,U)*c.get(V,B));m.set(V,U,m.get(V,U)/c.get(V,V))}for(V=i-1;V>=0;V--)for(U=0;U<l;U++){for(B=V+1;B<i;B++)m.set(V,U,m.get(V,U)-m.get(B,U)*c.get(B,V));m.set(V,U,m.get(V,U)/c.get(V,V))}return m}get lowerTriangularMatrix(){return this.L}}class wr{constructor(u,c={}){u=Ae.checkMatrix(u);let{Y:i}=c;const{scaleScores:l=!1,maxIterations:m=1e3,terminationCriteria:B=1e-10}=c;let U;if(i){if(ot.isAnyArray(i)&&typeof i[0]=="number"?i=It.columnVector(i):i=Ae.checkMatrix(i),i.rows!==u.rows)throw new Error("Y should have the same number of rows as X");U=i.getColumnVector(0)}else U=u.getColumnVector(0);let V=1,G,rt,K,lt;for(let Tt=0;Tt<m&&V>B;Tt++)K=u.transpose().mmul(U).div(U.transpose().mmul(U).get(0,0)),K=K.div(K.norm()),G=u.mmul(K).div(K.transpose().mmul(K).get(0,0)),Tt>0&&(V=G.clone().sub(lt).pow(2).sum()),lt=G.clone(),i?(rt=i.transpose().mmul(G).div(G.transpose().mmul(G).get(0,0)),rt=rt.div(rt.norm()),U=i.mmul(rt).div(rt.transpose().mmul(rt).get(0,0))):U=G;if(i){let Tt=u.transpose().mmul(G).div(G.transpose().mmul(G).get(0,0));Tt=Tt.div(Tt.norm());let ct=u.clone().sub(G.clone().mmul(Tt.transpose())),pt=U.transpose().mmul(G).div(G.transpose().mmul(G).get(0,0)),Rt=i.clone().sub(G.clone().mulS(pt.get(0,0)).mmul(rt.transpose()));this.t=G,this.p=Tt.transpose(),this.w=K.transpose(),this.q=rt,this.u=U,this.s=G.transpose().mmul(G),this.xResidual=ct,this.yResidual=Rt,this.betas=pt}else 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t=e.nodeFilter||sn,r=e.edgeFilter||sn;this.nodeFilter=t,this.edgeFilter=s=>{const{source:o,target:d}=this.graph.getEdgeDetail(s.id);return!t(o)||!t(d)?!1:r(s,o,d)},e.cache==="auto"?(this.cacheEnabled=!0,this.startAutoCache()):e.cache==="manual"?this.cacheEnabled=!0:this.cacheEnabled=!1}startAutoCache(){this.refreshCache(),this.graph.on("changed",this.handleGraphChanged)}stopAutoCache(){this.graph.off("changed",this.handleGraphChanged)}checkNodeExistence(e){this.getNode(e)}hasNode(e){if(!this.graph.hasNode(e))return!1;const t=this.graph.getNode(e);return this.nodeFilter(t)}areNeighbors(e,t){return this.checkNodeExistence(e),this.getNeighbors(t).some(r=>r.id===e)}getNode(e){const t=this.graph.getNode(e);if(!this.nodeFilter(t))throw new Error("Node not found for id: "+e);return t}getRelatedEdges(e,t){return this.checkNodeExistence(e),this.cacheEnabled?t==="in"?this.inEdgesMap.get(e):t==="out"?this.outEdgesMap.get(e):this.bothEdgesMap.get(e):this.graph.getRelatedEdges(e,t).filter(this.edgeFilter)}getDegree(e,t){return this.getRelatedEdges(e,t).length}getSuccessors(e){const r=this.getRelatedEdges(e,"out").map(s=>this.getNode(s.target));return Array.from(new Set(r))}getPredecessors(e){const r=this.getRelatedEdges(e,"in").map(s=>this.getNode(s.source));return Array.from(new Set(r))}getNeighbors(e){const t=this.getPredecessors(e),r=this.getSuccessors(e);return Array.from(new Set([...t,...r]))}hasEdge(e){if(!this.graph.hasEdge(e))return!1;const t=this.graph.getEdge(e);return this.edgeFilter(t)}getEdge(e){const t=this.graph.getEdge(e);if(!this.edgeFilter(t))throw new Error("Edge not found for id: "+e);return t}getEdgeDetail(e){const t=this.getEdge(e);return{edge:t,source:this.getNode(t.source),target:this.getNode(t.target)}}hasTreeStructure(e){return 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h&&(o=!0),!h}else if(d.type==="EdgeDataUpdated"||d.type==="EdgeUpdated")return d.id!==s.value.id;return!0}),o||r.push(s);break}case"NodeDataUpdated":case"EdgeDataUpdated":case"EdgeUpdated":{const o=r.findIndex(h=>h.type===s.type&&h.id===s.id&&(s.propertyName===void 0||h.propertyName===s.propertyName)),d=r[o];d?s.propertyName!==void 0?d.newValue=s.newValue:(r.splice(o,1),r.push(s)):r.push(s);break}case"TreeStructureDetached":{r=r.filter(o=>o.type==="TreeStructureAttached"||o.type==="TreeStructureChanged"?o.treeKey!==s.treeKey:!0),r.push(s);break}case"TreeStructureChanged":{const o=r.find(d=>d.type==="TreeStructureChanged"&&d.treeKey===s.treeKey&&d.nodeId===s.nodeId);o?o.newParentId=s.newParentId:r.push(s);break}default:r.push(s);break}}),r}checkNodeExistence(t){this.getNode(t)}hasNode(t){return this.nodeMap.has(t)}areNeighbors(t,r){return this.getNeighbors(r).some(s=>s.id===t)}getNode(t){const r=this.nodeMap.get(t);if(!r)throw new Error("Node not found for id: "+t);return r}getRelatedEdges(t,r){if(this.checkNodeExistence(t),r==="in"){const s=this.inEdgesMap.get(t);return Array.from(s)}else if(r==="out"){const s=this.outEdgesMap.get(t);return Array.from(s)}else{const s=this.bothEdgesMap.get(t);return Array.from(s)}}getDegree(t,r){return this.getRelatedEdges(t,r).length}getSuccessors(t){const s=this.getRelatedEdges(t,"out").map(o=>this.getNode(o.target));return Array.from(new Set(s))}getPredecessors(t){const s=this.getRelatedEdges(t,"in").map(o=>this.getNode(o.source));return Array.from(new Set(s))}getNeighbors(t){const r=this.getPredecessors(t),s=this.getSuccessors(t);return Array.from(new Set([...r,...s]))}doAddNode(t){if(this.hasNode(t.id))throw new Error("Node already exists: "+t.id);this.nodeMap.set(t.id,t),this.inEdgesMap.set(t.id,new Set),this.outEdgesMap.set(t.id,new Set),this.bothEdgesMap.set(t.id,new Set),this.treeIndices.forEach(r=>{r.childrenMap.set(t.id,new Set)}),this.changes.push({type:"NodeAdded",value:t})}addNodes(t){this.batch(()=>{for(const r of t)this.doAddNode(r)})}addNode(t){this.addNodes([t])}doRemoveNode(t){const r=this.getNode(t),s=this.bothEdgesMap.get(t);s==null||s.forEach(o=>this.doRemoveEdge(o.id)),this.nodeMap.delete(t),this.treeIndices.forEach(o=>{var h,p;(h=o.childrenMap.get(t))==null||h.forEach(g=>{o.parentMap.delete(g.id)});const d=o.parentMap.get(t);d&&((p=o.childrenMap.get(d.id))==null||p.delete(r)),o.parentMap.delete(t),o.childrenMap.delete(t)}),this.bothEdgesMap.delete(t),this.inEdgesMap.delete(t),this.outEdgesMap.delete(t),this.changes.push({type:"NodeRemoved",value:r})}removeNodes(t){this.batch(()=>{t.forEach(r=>this.doRemoveNode(r))})}removeNode(t){this.removeNodes([t])}updateNodeDataProperty(t,r,s){const o=this.getNode(t);this.batch(()=>{const 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ie=(W-bt)/C,de=($-Bt)/C,Jt=(X-Qt)/C;if($t&&(r[F].x-=$t*ie,r[F].y-=$t*de,r[F].z-=$t*Jt),Pt===0){const Te=zt(q);if(!Te)return;r[F].x-=Te*ie,r[F].y-=Te*de,r[F].z-=Te*Jt;return}if(Et===0||jt===0){const Te=Gt(q,h,p);if(!Te)return;r[F].x-=Te*ie,r[F].y-=Te*de,r[F].z-=Te*Jt;return}const oe=Kt(q);if(!oe)return;r[F].x-=oe*ie,r[F].y-=oe*de,r[F].z-=oe*Jt}})}updateVelocity(e,t,r,s){const{damping:o,maxSpeed:d,interval:h,dimensions:p}=s,g=e.getAllNodes();g!=null&&g.length&&g.forEach(y=>{const{id:O}=y;let L=(r[O].x+t[O].x*h)*o||.01,R=(r[O].y+t[O].y*h)*o||.01,k=p===3?(r[O].z+t[O].z*h)*o||.01:0;const F=Math.sqrt(L*L+R*R+k*k);if(F>d){const z=d/F;L=z*L,R=z*R,k=z*k}r[O]={x:L,y:R,z:k}})}updatePosition(e,t,r,s){const{distanceThresholdMode:o,interval:d,dimensions:h}=s,p=t.getAllNodes();if(!(p!=null&&p.length)){this.judgingDistance=0;return}let 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ea={gForce:!0,force2:!0,d3force:!0,fruchterman:!0,forceAtlas2:!0,force:!0,"graphin-force":!0},na={center:[0,0],comboPadding:10,treeKey:"combo"};class ra{constructor(e={}){this.options=e,this.id="comboCombined",this.options=Object.assign(Object.assign({},na),e)}execute(e,t){return A(this,void 0,void 0,function*(){return this.genericComboCombinedLayout(!1,e,t)})}assign(e,t){return A(this,void 0,void 0,function*(){yield this.genericComboCombinedLayout(!0,e,t)})}genericComboCombinedLayout(e,t,r){return A(this,void 0,void 0,function*(){const s=this.initVals(Object.assign(Object.assign({},this.options),r)),{center:o,treeKey:d,outerLayout:h}=s,p=t.getAllNodes().filter(J=>!J.data._isCombo),g=t.getAllNodes().filter(J=>J.data._isCombo),y=t.getAllEdges(),O=p==null?void 0:p.length;if(!O||O===1)return Tn(t,e,o);const L=[],R=new Map;p.forEach(J=>{R.set(J.id,J)});const k=new Map;g.forEach(J=>{k.set(J.id,J)});const F=new Map,z=this.getInnerGraphs(t,d,R,k,y,s,F);yield Promise.all(z);const C=new Map,W=[],$=new Map;let X=!0;t.getRoots(d).forEach(J=>{const mt=F.get(J.id),Et=k.get(J.id)||R.get(J.id),jt={id:J.id,data:Object.assign(Object.assign({},J.data),{x:mt.data.x||Et.data.x,y:mt.data.y||Et.data.y,fx:mt.data.fx||Et.data.fx,fy:mt.data.fy||Et.data.fy,mass:mt.data.mass||Et.data.mass,size:mt.data.size})};W.push(jt),C.set(J.id,!0),!isNaN(jt.data.x)&&jt.data.x!==0&&!isNaN(jt.data.y)&&jt.data.y!==0?X=!1:(jt.data.x=Math.random()*100,jt.data.y=Math.random()*100),zr(t,[J],Pt=>{Pt.id!==J.id&&$.set(Pt.id,J.id)},"TB",d)});const q=[];y.forEach(J=>{const mt=$.get(J.source)||J.source,Et=$.get(J.target)||J.target;mt!==Et&&C.has(mt)&&C.has(Et)&&q.push({id:J.id,source:mt,target:Et,data:{}})});let st;if(W!=null&&W.length){if(W.length===1)W[0].data.x=o[0],W[0].data.y=o[1];else{const J=new vt({nodes:W,edges:q}),mt=h||new Es;X&&ea[mt.id]&&(yield(W.length<100?new Ts:new Pr).assign(J));const Et=Object.assign({center:o,kg:5,preventOverlap:!0,animate:!1},mt.id==="force"?{gravity:1,factor:4,linkDistance:(jt,Pt,Dt)=>{const Gt=Math.max(...Pt.data.size)||32,zt=Math.max(...Dt.data.size)||32;return Gt/2+zt/2+200}}:{});st=yield Is(mt,J,Et)}F.forEach(J=>{var mt;const Et=st.nodes.find(Dt=>Dt.id===J.id);if(Et){const{x:Dt,y:Gt}=Et.data;J.data.visited=!0,J.data.x=Dt,J.data.y=Gt,L.push({id:J.id,data:{x:Dt,y:Gt}})}const{x:jt,y:Pt}=J.data;(mt=J.data.nodes)===null||mt===void 0||mt.forEach(Dt=>{L.push({id:Dt.id,data:{x:Dt.data.x+jt,y:Dt.data.y+Pt}})})}),F.forEach(({data:J})=>{const{x:mt,y:Et,visited:jt,nodes:Pt}=J;Pt==null||Pt.forEach(Dt=>{if(!jt){const Gt=L.find(zt=>zt.id===Dt.id);Gt.data.x+=mt||0,Gt.data.y+=Et||0}})})}return e&&L.forEach(J=>{t.mergeNodeData(J.id,{x:J.data.x,y:J.data.y})}),{nodes:L,edges:y}})}initVals(e){const t=Object.assign({},e),{nodeSize:r,spacing:s,comboPadding:o}=e;let d,h;if(_t(s)?h=()=>s:fn(s)?h=s:h=()=>0,t.spacing=h,!r)d=g=>{const y=h(g);return 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Ws{constructor(){super(...arguments),this.id="d3-force-3d",this.config={inputNodeAttrs:["x","y","z","vx","vy","vz","fx","fy","fz"],outputNodeAttrs:["x","y","z","vx","vy","vz"],simulationAttrs:["alpha","alphaMin","alphaDecay","alphaTarget","velocityDecay","randomSource","numDimensions"]},this.forceMap={link:Ga,manyBody:lu,center:du,collide:gu,radial:pu,x:vu,y:mu,z:yu},this.options={numDimensions:3,link:{id:e=>e.id},manyBody:{},center:{x:0,y:0,z:0}}}initSimulation(){return fu()}}var Hs=me(92546),xu=me.n(Hs);class or{constructor(e){this.id="dagre",this.options={},Object.assign(this.options,or.defaultOptions,e)}execute(e,t){return A(this,void 0,void 0,function*(){return this.genericDagreLayout(!1,e,Object.assign(Object.assign({},this.options),t))})}assign(e,t){return A(this,void 0,void 0,function*(){yield this.genericDagreLayout(!0,e,Object.assign(Object.assign({},this.options),t))})}genericDagreLayout(e,t,r){return A(this,void 0,void 0,function*(){const{nodeSize:s}=r,o=new Hs.graphlib.Graph;o.setGraph(r),o.setDefaultEdgeLabel(()=>({}));const d=t.getAllNodes(),h=t.getAllEdges();[...d,...h].some(({id:g})=>_t(g))&&console.error("Dagre layout only support string id, it will convert number to string."),t.getAllNodes().forEach(g=>{const{id:y}=g,O=Object.assign({},g.data);if(s!==void 0){const[L,R]=Yn(fn(s)?s(g):s);Object.assign(O,{width:L,height:R})}o.setNode(y.toString(),O)}),t.getAllEdges().forEach(({id:g,source:y,target:O})=>{o.setEdge(y.toString(),O.toString(),{id:g})}),xu().layout(o);const p={nodes:[],edges:[]};return o.nodes().forEach(g=>{const y=o.node(g);p.nodes.push({id:g,data:y}),e&&t.mergeNodeData(g,y)}),o.edges().forEach(g=>{const y=o.edge(g),{id:O}=y,L=f(y,["id"]),{v:R,w:k}=g;p.edges.push({id:O,source:R,target:k,data:L}),e&&t.mergeEdgeData(O,L)}),p})}}or.defaultOptions={};class $r{constructor(e){this.id=e.id||0,this.rx=e.rx,this.ry=e.ry,this.fx=0,this.fy=0,this.mass=e.mass,this.degree=e.degree,this.g=e.g||0}distanceTo(e){const t=this.rx-e.rx,r=this.ry-e.ry;return Math.hypot(t,r)}setPos(e,t){this.rx=e,this.ry=t}resetForce(){this.fx=0,this.fy=0}addForce(e){const t=e.rx-this.rx,r=e.ry-this.ry;let s=Math.hypot(t,r);s=s<1e-4?1e-4:s;const o=this.g*(this.degree+1)*(e.degree+1)/s;this.fx+=o*t/s,this.fy+=o*r/s}in(e){return e.contains(this.rx,this.ry)}add(e){const t=this.mass+e.mass,r=(this.rx*this.mass+e.rx*e.mass)/t,s=(this.ry*this.mass+e.ry*e.mass)/t,o=this.degree+e.degree,d={rx:r,ry:s,mass:t,degree:o};return new $r(d)}}class zn{constructor(e){this.xmid=e.xmid,this.ymid=e.ymid,this.length=e.length,this.massCenter=e.massCenter||[0,0],this.mass=e.mass||1}getLength(){return this.length}contains(e,t){const r=this.length/2;return e<=this.xmid+r&&e>=this.xmid-r&&t<=this.ymid+r&&t>=this.ymid-r}NW(){const e=this.xmid-this.length/4,t=this.ymid+this.length/4,r=this.length/2,s={xmid:e,ymid:t,length:r};return new zn(s)}NE(){const e=this.xmid+this.length/4,t=this.ymid+this.length/4,r=this.length/2,s={xmid:e,ymid:t,length:r};return new zn(s)}SW(){const e=this.xmid-this.length/4,t=this.ymid-this.length/4,r=this.length/2,s={xmid:e,ymid:t,length:r};return new zn(s)}SE(){const e=this.xmid+this.length/4,t=this.ymid-this.length/4,r=this.length/2,s={xmid:e,ymid:t,length:r};return new zn(s)}}class Fn{constructor(e){this.body=null,this.quad=null,this.NW=null,this.NE=null,this.SW=null,this.SE=null,this.theta=.5,e!=null&&(this.quad=e)}insert(e){if(this.body==null){this.body=e;return}this._isExternal()?(this.quad&&(this.NW=new Fn(this.quad.NW()),this.NE=new Fn(this.quad.NE()),this.SW=new Fn(this.quad.SW()),this.SE=new Fn(this.quad.SE())),this._putBody(this.body),this._putBody(e),this.body=this.body.add(e)):(this.body=this.body.add(e),this._putBody(e))}_putBody(e){this.quad&&(e.in(this.quad.NW())&&this.NW?this.NW.insert(e):e.in(this.quad.NE())&&this.NE?this.NE.insert(e):e.in(this.quad.SW())&&this.SW?this.SW.insert(e):e.in(this.quad.SE())&&this.SE&&this.SE.insert(e))}_isExternal(){return this.NW==null&&this.NE==null&&this.SW==null&&this.SE==null}updateForce(e){if(!(this.body==null||e===this.body))if(this._isExternal())e.addForce(this.body);else{const t=this.quad?this.quad.getLength():0,r=this.body.distanceTo(e);t/r<this.theta?e.addForce(this.body):(this.NW&&this.NW.updateForce(e),this.NE&&this.NE.updateForce(e),this.SW&&this.SW.updateForce(e),this.SE&&this.SE.updateForce(e))}}}const Eu={center:[0,0],width:300,height:300,kr:5,kg:1,mode:"normal",preventOverlap:!1,dissuadeHubs:!1,maxIteration:0,ks:.1,ksmax:10,tao:.1};class bu{constructor(e={}){this.options=e,this.id="forceAtlas2",this.options=Object.assign(Object.assign({},Eu),e)}execute(e,t){return A(this,void 0,void 0,function*(){return this.genericForceAtlas2Layout(!1,e,t)})}assign(e,t){return A(this,void 0,void 0,function*(){yield this.genericForceAtlas2Layout(!0,e,t)})}genericForceAtlas2Layout(e,t,r){return A(this,void 0,void 0,function*(){const s=t.getAllEdges(),o=t.getAllNodes(),d=this.formatOptions(r,o.length),{width:h,height:p,prune:g,maxIteration:y,nodeSize:O,center:L}=d;if(!(o!=null&&o.length)||o.length===1)return Tn(t,e,L);const R=o.map(C=>Ke(C,[h,p])),k=s.filter(C=>{const{source:W,target:$}=C;return W!==$}),F=new vt({nodes:R,edges:k}),z=this.getSizes(F,O);if(this.run(F,t,y,z,e,d),g){for(let W=0;W<k.length;W+=1){const{source:$,target:X}=k[W],q=F.getDegree($),st=F.getDegree($);if(q<=1){const ut=F.getNode(X);F.mergeNodeData($,{x:ut.data.x,y:ut.data.y})}else if(st<=1){const ut=F.getNode($);F.mergeNodeData(X,{x:ut.data.x,y:ut.data.y})}}const C=Object.assign(Object.assign({},d),{prune:!1,barnesHut:!1});this.run(F,t,100,z,e,C)}return{nodes:R,edges:s}})}getSizes(e,t){const r=e.getAllNodes(),s={};for(let o=0;o<r.length;o+=1){const d=r[o];s[d.id]=jr(t,void 0)(d)}return s}formatOptions(e={},t){const r=Object.assign(Object.assign({},this.options),e),{center:s,width:o,height:d,barnesHut:h,prune:p,maxIteration:g,kr:y,kg:O}=r;return r.width=!o&&typeof window!="undefined"?window.innerWidth:o,r.height=!d&&typeof window!="undefined"?window.innerHeight:d,r.center=s||[r.width/2,r.height/2],h===void 0&&t>250&&(r.barnesHut=!0),p===void 0&&t>100&&(r.prune=!0),g===0&&!p?(r.maxIteration=250,t<=200&&t>100?r.maxIteration=1e3:t>200&&(r.maxIteration=1200)):g===0&&p&&(r.maxIteration=100,t<=200&&t>100?r.maxIteration=500:t>200&&(r.maxIteration=950)),y||(r.kr=50,t>100&&t<=500?r.kr=20:t>500&&(r.kr=1)),O||(r.kg=20,t>100&&t<=500?r.kg=10:t>500&&(r.kg=1)),r}run(e,t,r,s,o,d){const{kr:h,barnesHut:p,onTick:g}=d,y=e.getAllNodes();let O=0,L=r;const R={},k={},F={};for(let z=0;z<y.length;z+=1){const{data:C,id:W}=y[z];if(R[W]=[0,0],p){const $={id:z,rx:C.x,ry:C.y,mass:1,g:h,degree:e.getDegree(W)};F[W]=new $r($)}}for(;L>0;)O=this.oneStep(e,{iter:L,preventOverlapIters:50,krPrime:100,sg:O,forces:R,preForces:k,bodies:F,sizes:s},d),L--,g==null||g({nodes:y,edges:t.getAllEdges()});return e}oneStep(e,t,r){const{iter:s,preventOverlapIters:o,krPrime:d,sg:h,preForces:p,bodies:g,sizes:y}=t;let{forces:O}=t;const{preventOverlap:L,barnesHut:R}=r,k=e.getAllNodes();for(let F=0;F<k.length;F+=1){const{id:z}=k[F];p[z]=[...O[z]],O[z]=[0,0]}return O=this.getAttrForces(e,s,o,y,O,r),R&&(L&&s>o||!L)?O=this.getOptRepGraForces(e,O,g,r):O=this.getRepGraForces(e,s,o,O,d,y,r),this.updatePos(e,O,p,h,r)}getAttrForces(e,t,r,s,o,d){const{preventOverlap:h,dissuadeHubs:p,mode:g,prune:y}=d,O=e.getAllEdges();for(let L=0;L<O.length;L+=1){const{source:R,target:k}=O[L],F=e.getNode(R),z=e.getNode(k),C=e.getDegree(R),W=e.getDegree(k);if(y&&(C<=1||W<=1))continue;const $=[z.data.x-F.data.x,z.data.y-F.data.y];let X=Math.hypot($[0],$[1]);X=X<1e-4?1e-4:X,$[0]=$[0]/X,$[1]=$[1]/X,h&&t<r&&(X=X-s[R]-s[k]);let q=X,st=q;g==="linlog"&&(q=Math.log(1+X),st=q),p&&(q=X/C,st=X/W),h&&t<r&&X<=0?(q=0,st=0):h&&t<r&&X>0&&(q=X,st=X),o[R][0]+=q*$[0],o[k][0]-=st*$[0],o[R][1]+=q*$[1],o[k][1]-=st*$[1]}return o}getOptRepGraForces(e,t,r,s){const{kg:o,center:d,prune:h}=s,p=e.getAllNodes(),g=p.length;let y=9e10,O=-9e10,L=9e10,R=-9e10;for(let W=0;W<g;W+=1){const{id:$,data:X}=p[W];h&&e.getDegree($)<=1||(r[$].setPos(X.x,X.y),X.x>=O&&(O=X.x),X.x<=y&&(y=X.x),X.y>=R&&(R=X.y),X.y<=L&&(L=X.y))}const k=Math.max(O-y,R-L),F={xmid:(O+y)/2,ymid:(R+L)/2,length:k,massCenter:d,mass:g},z=new zn(F),C=new Fn(z);for(let W=0;W<g;W+=1){const{id:$}=p[W];h&&e.getDegree($)<=1||r[$].in(z)&&C.insert(r[$])}for(let W=0;W<g;W+=1){const{id:$,data:X}=p[W],q=e.getDegree($);if(h&&q<=1)continue;r[$].resetForce(),C.updateForce(r[$]),t[$][0]-=r[$].fx,t[$][1]-=r[$].fy;const st=[X.x-d[0],X.y-d[1]];let ut=Math.hypot(st[0],st[1]);ut=ut<1e-4?1e-4:ut,st[0]=st[0]/ut,st[1]=st[1]/ut;const J=o*(q+1);t[$][0]-=J*st[0],t[$][1]-=J*st[1]}return t}getRepGraForces(e,t,r,s,o,d,h){const{preventOverlap:p,kr:g,kg:y,center:O,prune:L}=h,R=e.getAllNodes(),k=R.length;for(let F=0;F<k;F+=1){const z=R[F],C=e.getDegree(z.id);for(let q=F+1;q<k;q+=1){const st=R[q],ut=e.getDegree(st.id);if(L&&(C<=1||ut<=1))continue;const J=[st.data.x-z.data.x,st.data.y-z.data.y];let mt=Math.hypot(J[0],J[1]);mt=mt<1e-4?1e-4:mt,J[0]=J[0]/mt,J[1]=J[1]/mt,p&&t<r&&(mt=mt-d[z.id]-d[st.id]);let Et=g*(C+1)*(ut+1)/mt;p&&t<r&&mt<0?Et=o*(C+1)*(ut+1):p&&t<r&&mt===0?Et=0:p&&t<r&&mt>0&&(Et=g*(C+1)*(ut+1)/mt),s[z.id][0]-=Et*J[0],s[st.id][0]+=Et*J[0],s[z.id][1]-=Et*J[1],s[st.id][1]+=Et*J[1]}const W=[z.data.x-O[0],z.data.y-O[1]],$=Math.hypot(W[0],W[1]);W[0]=W[0]/$,W[1]=W[1]/$;const X=y*(C+1);s[z.id][0]-=X*W[0],s[z.id][1]-=X*W[1]}return s}updatePos(e,t,r,s,o){const{ks:d,tao:h,prune:p,ksmax:g}=o,y=e.getAllNodes(),O=y.length,L=[],R=[];let k=0,F=0,z=s;for(let W=0;W<O;W+=1){const{id:$}=y[W],X=e.getDegree($);if(p&&X<=1)continue;const q=[t[$][0]-r[$][0],t[$][1]-r[$][1]],st=Math.hypot(q[0],q[1]),ut=[t[$][0]+r[$][0],t[$][1]+r[$][1]],J=Math.hypot(ut[0],ut[1]);L[W]=st,R[W]=J/2,k+=(X+1)*L[W],F+=(X+1)*R[W]}const C=z;z=h*F/k,C!==0&&(z=z>1.5*C?1.5*C:z);for(let W=0;W<O;W+=1){const{id:$,data:X}=y[W],q=e.getDegree($);if(p&&q<=1||_t(X.fx)&&_t(X.fy))continue;let st=d*z/(1+z*Math.sqrt(L[W])),ut=Math.hypot(t[$][0],t[$][1]);ut=ut<1e-4?1e-4:ut;const J=g/ut;st=st>J?J:st;const mt=st*t[$][0],Et=st*t[$][1];e.mergeNodeData($,{x:X.x+mt,y:X.y+Et})}return z}}const Nu={maxIteration:1e3,gravity:10,speed:5,clustering:!1,clusterGravity:10,width:300,height:300,nodeClusterBy:"cluster"},Mu=800;class Su{constructor(e={}){this.options=e,this.id="fruchterman",this.timeInterval=0,this.running=!1,this.options=Object.assign(Object.assign({},Nu),e)}execute(e,t){return A(this,void 0,void 0,function*(){return this.genericFruchtermanLayout(!1,e,t)})}assign(e,t){return A(this,void 0,void 0,function*(){yield this.genericFruchtermanLayout(!0,e,t)})}stop(){this.timeInterval&&typeof window!="undefined"&&window.clearInterval(this.timeInterval),this.running=!1}tick(e=this.options.maxIteration||1){if(this.lastResult)return this.lastResult;for(let r=0;r<e;r++)this.runOneStep(this.lastGraph,this.lastClusterMap,this.lastOptions);const t={nodes:this.lastLayoutNodes,edges:this.lastLayoutEdges};return this.lastAssign&&t.nodes.forEach(r=>this.lastGraph.mergeNodeData(r.id,{x:r.data.x,y:r.data.y,z:this.options.dimensions===3?r.data.z:void 0})),t}genericFruchtermanLayout(e,t,r){return A(this,void 0,void 0,function*(){if(this.running)return;const s=this.formatOptions(r),{dimensions:o,width:d,height:h,center:p,clustering:g,nodeClusterBy:y,maxIteration:O,onTick:L}=s,R=t.getAllNodes(),k=t.getAllEdges();if(!(R!=null&&R.length)){const $={nodes:[],edges:k};return this.lastResult=$,$}if(R.length===1){e&&t.mergeNodeData(R[0].id,{x:p[0],y:p[1],z:o===3?p[2]:void 0});const $={nodes:[Object.assign(Object.assign({},R[0]),{data:Object.assign(Object.assign({},R[0].data),{x:p[0],y:p[1],z:o===3?p[2]:void 0})})],edges:k};return this.lastResult=$,$}const F=R.map($=>Ke($,[d,h])),z=new vt({nodes:F,edges:k}),C={};if(g&&F.forEach($=>{const X=$.data[y];C[X]||(C[X]={name:X,cx:0,cy:0,count:0})}),this.lastLayoutNodes=F,this.lastLayoutEdges=k,this.lastAssign=e,this.lastGraph=z,this.lastOptions=s,this.lastClusterMap=C,typeof window=="undefined")return;let W=0;return new Promise($=>{this.timeInterval=window.setInterval(()=>{if(!this.running){$({nodes:F,edges:k});return}this.runOneStep(z,C,s),e&&F.forEach(({id:X,data:q})=>t.mergeNodeData(X,{x:q.x,y:q.y,z:o===3?q.z:void 0})),L==null||L({nodes:F,edges:k}),W++,W>=O&&(window.clearInterval(this.timeInterval),$({nodes:F,edges:k}))},0),this.running=!0})})}formatOptions(e={}){const 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diff --git a/3339.259e8484.async.js b/3339.259e8484.async.js
deleted file mode 100644
index 41e635664e..0000000000
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+++ /dev/null
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K=l+Math.round(B()*U);V.set(G,rt,K)}return V}static eye(u,c,i){c===void 0&&(c=u),i===void 0&&(i=1);let l=Math.min(u,c),m=this.zeros(u,c);for(let B=0;B<l;B++)m.set(B,B,i);return m}static diag(u,c,i){let l=u.length;c===void 0&&(c=l),i===void 0&&(i=c);let m=Math.min(l,c,i),B=this.zeros(c,i);for(let U=0;U<m;U++)B.set(U,U,u[U]);return B}static min(u,c){u=this.checkMatrix(u),c=this.checkMatrix(c);let i=u.rows,l=u.columns,m=new It(i,l);for(let B=0;B<i;B++)for(let U=0;U<l;U++)m.set(B,U,Math.min(u.get(B,U),c.get(B,U)));return m}static max(u,c){u=this.checkMatrix(u),c=this.checkMatrix(c);let i=u.rows,l=u.columns,m=new this(i,l);for(let B=0;B<i;B++)for(let U=0;U<l;U++)m.set(B,U,Math.max(u.get(B,U),c.get(B,U)));return m}static checkMatrix(u){return Wt.isMatrix(u)?u:new It(u)}static isMatrix(u){return u!=null&&u.klass==="Matrix"}get size(){return this.rows*this.columns}apply(u){if(typeof u!="function")throw new TypeError("callback must be a function");for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)u.call(this,c,i);return this}to1DArray(){let u=[];for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)u.push(this.get(c,i));return u}to2DArray(){let u=[];for(let c=0;c<this.rows;c++){u.push([]);for(let i=0;i<this.columns;i++)u[c].push(this.get(c,i))}return u}toJSON(){return this.to2DArray()}isRowVector(){return this.rows===1}isColumnVector(){return this.columns===1}isVector(){return this.rows===1||this.columns===1}isSquare(){return this.rows===this.columns}isEmpty(){return this.rows===0||this.columns===0}isSymmetric(){if(this.isSquare()){for(let u=0;u<this.rows;u++)for(let c=0;c<=u;c++)if(this.get(u,c)!==this.get(c,u))return!1;return!0}return!1}isDistance(){if(!this.isSymmetric())return!1;for(let u=0;u<this.rows;u++)if(this.get(u,u)!==0)return!1;return!0}isEchelonForm(){let u=0,c=0,i=-1,l=!0,m=!1;for(;u<this.rows&&l;){for(c=0,m=!1;c<this.columns&&m===!1;)this.get(u,c)===0?c++:this.get(u,c)===1&&c>i?(m=!0,i=c):(l=!1,m=!0);u++}return l}isReducedEchelonForm(){let u=0,c=0,i=-1,l=!0,m=!1;for(;u<this.rows&&l;){for(c=0,m=!1;c<this.columns&&m===!1;)this.get(u,c)===0?c++:this.get(u,c)===1&&c>i?(m=!0,i=c):(l=!1,m=!0);for(let B=c+1;B<this.rows;B++)this.get(u,B)!==0&&(l=!1);u++}return l}echelonForm(){let u=this.clone(),c=0,i=0;for(;c<u.rows&&i<u.columns;){let l=c;for(let m=c;m<u.rows;m++)u.get(m,i)>u.get(l,i)&&(l=m);if(u.get(l,i)===0)i++;else{u.swapRows(c,l);let m=u.get(c,i);for(let B=i;B<u.columns;B++)u.set(c,B,u.get(c,B)/m);for(let B=c+1;B<u.rows;B++){let U=u.get(B,i)/u.get(c,i);u.set(B,i,0);for(let V=i+1;V<u.columns;V++)u.set(B,V,u.get(B,V)-u.get(c,V)*U)}c++,i++}}return u}reducedEchelonForm(){let u=this.echelonForm(),c=u.columns,i=u.rows,l=i-1;for(;l>=0;)if(u.maxRow(l)===0)l--;else{let m=0,B=!1;for(;m<i&&B===!1;)u.get(l,m)===1?B=!0:m++;for(let U=0;U<l;U++){let V=u.get(U,m);for(let G=m;G<c;G++){let rt=u.get(U,G)-V*u.get(l,G);u.set(U,G,rt)}}l--}return u}set(){throw new Error("set method is unimplemented")}get(){throw new Error("get method is unimplemented")}repeat(u={}){if(typeof u!="object")throw new TypeError("options must be an object");const{rows:c=1,columns:i=1}=u;if(!Number.isInteger(c)||c<=0)throw new TypeError("rows must be a positive integer");if(!Number.isInteger(i)||i<=0)throw new TypeError("columns must be a positive integer");let l=new It(this.rows*c,this.columns*i);for(let m=0;m<c;m++)for(let B=0;B<i;B++)l.setSubMatrix(this,this.rows*m,this.columns*B);return l}fill(u){for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)this.set(c,i,u);return this}neg(){return this.mulS(-1)}getRow(u){xt(this,u);let c=[];for(let i=0;i<this.columns;i++)c.push(this.get(u,i));return c}getRowVector(u){return It.rowVector(this.getRow(u))}setRow(u,c){xt(this,u),c=Nt(this,c);for(let i=0;i<this.columns;i++)this.set(u,i,c[i]);return this}swapRows(u,c){xt(this,u),xt(this,c);for(let i=0;i<this.columns;i++){let l=this.get(u,i);this.set(u,i,this.get(c,i)),this.set(c,i,l)}return this}getColumn(u){yt(this,u);let c=[];for(let i=0;i<this.rows;i++)c.push(this.get(i,u));return c}getColumnVector(u){return It.columnVector(this.getColumn(u))}setColumn(u,c){yt(this,u),c=Ot(this,c);for(let i=0;i<this.rows;i++)this.set(i,u,c[i]);return this}swapColumns(u,c){yt(this,u),yt(this,c);for(let i=0;i<this.rows;i++){let l=this.get(i,u);this.set(i,u,this.get(i,c)),this.set(i,c,l)}return this}addRowVector(u){u=Nt(this,u);for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)this.set(c,i,this.get(c,i)+u[i]);return this}subRowVector(u){u=Nt(this,u);for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)this.set(c,i,this.get(c,i)-u[i]);return this}mulRowVector(u){u=Nt(this,u);for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)this.set(c,i,this.get(c,i)*u[i]);return this}divRowVector(u){u=Nt(this,u);for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)this.set(c,i,this.get(c,i)/u[i]);return this}addColumnVector(u){u=Ot(this,u);for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)this.set(c,i,this.get(c,i)+u[c]);return this}subColumnVector(u){u=Ot(this,u);for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)this.set(c,i,this.get(c,i)-u[c]);return this}mulColumnVector(u){u=Ot(this,u);for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)this.set(c,i,this.get(c,i)*u[c]);return this}divColumnVector(u){u=Ot(this,u);for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)this.set(c,i,this.get(c,i)/u[c]);return this}mulRow(u,c){xt(this,u);for(let i=0;i<this.columns;i++)this.set(u,i,this.get(u,i)*c);return this}mulColumn(u,c){yt(this,u);for(let i=0;i<this.rows;i++)this.set(i,u,this.get(i,u)*c);return this}max(u){if(this.isEmpty())return NaN;switch(u){case"row":{const c=new Array(this.rows).fill(Number.NEGATIVE_INFINITY);for(let i=0;i<this.rows;i++)for(let l=0;l<this.columns;l++)this.get(i,l)>c[i]&&(c[i]=this.get(i,l));return c}case"column":{const c=new Array(this.columns).fill(Number.NEGATIVE_INFINITY);for(let i=0;i<this.rows;i++)for(let l=0;l<this.columns;l++)this.get(i,l)>c[l]&&(c[l]=this.get(i,l));return c}case void 0:{let c=this.get(0,0);for(let i=0;i<this.rows;i++)for(let l=0;l<this.columns;l++)this.get(i,l)>c&&(c=this.get(i,l));return c}default:throw new Error(`invalid option: ${u}`)}}maxIndex(){Ye(this);let u=this.get(0,0),c=[0,0];for(let i=0;i<this.rows;i++)for(let l=0;l<this.columns;l++)this.get(i,l)>u&&(u=this.get(i,l),c[0]=i,c[1]=l);return c}min(u){if(this.isEmpty())return NaN;switch(u){case"row":{const c=new Array(this.rows).fill(Number.POSITIVE_INFINITY);for(let i=0;i<this.rows;i++)for(let l=0;l<this.columns;l++)this.get(i,l)<c[i]&&(c[i]=this.get(i,l));return c}case"column":{const c=new Array(this.columns).fill(Number.POSITIVE_INFINITY);for(let i=0;i<this.rows;i++)for(let l=0;l<this.columns;l++)this.get(i,l)<c[l]&&(c[l]=this.get(i,l));return c}case void 0:{let c=this.get(0,0);for(let i=0;i<this.rows;i++)for(let l=0;l<this.columns;l++)this.get(i,l)<c&&(c=this.get(i,l));return c}default:throw new Error(`invalid option: ${u}`)}}minIndex(){Ye(this);let u=this.get(0,0),c=[0,0];for(let i=0;i<this.rows;i++)for(let l=0;l<this.columns;l++)this.get(i,l)<u&&(u=this.get(i,l),c[0]=i,c[1]=l);return c}maxRow(u){if(xt(this,u),this.isEmpty())return NaN;let c=this.get(u,0);for(let i=1;i<this.columns;i++)this.get(u,i)>c&&(c=this.get(u,i));return c}maxRowIndex(u){xt(this,u),Ye(this);let c=this.get(u,0),i=[u,0];for(let l=1;l<this.columns;l++)this.get(u,l)>c&&(c=this.get(u,l),i[1]=l);return i}minRow(u){if(xt(this,u),this.isEmpty())return NaN;let c=this.get(u,0);for(let i=1;i<this.columns;i++)this.get(u,i)<c&&(c=this.get(u,i));return c}minRowIndex(u){xt(this,u),Ye(this);let c=this.get(u,0),i=[u,0];for(let l=1;l<this.columns;l++)this.get(u,l)<c&&(c=this.get(u,l),i[1]=l);return i}maxColumn(u){if(yt(this,u),this.isEmpty())return NaN;let c=this.get(0,u);for(let i=1;i<this.rows;i++)this.get(i,u)>c&&(c=this.get(i,u));return c}maxColumnIndex(u){yt(this,u),Ye(this);let c=this.get(0,u),i=[0,u];for(let l=1;l<this.rows;l++)this.get(l,u)>c&&(c=this.get(l,u),i[0]=l);return i}minColumn(u){if(yt(this,u),this.isEmpty())return NaN;let c=this.get(0,u);for(let i=1;i<this.rows;i++)this.get(i,u)<c&&(c=this.get(i,u));return c}minColumnIndex(u){yt(this,u),Ye(this);let c=this.get(0,u),i=[0,u];for(let l=1;l<this.rows;l++)this.get(l,u)<c&&(c=this.get(l,u),i[0]=l);return i}diag(){let u=Math.min(this.rows,this.columns),c=[];for(let i=0;i<u;i++)c.push(this.get(i,i));return c}norm(u="frobenius"){switch(u){case"max":return this.max();case"frobenius":return Math.sqrt(this.dot(this));default:throw new RangeError(`unknown norm type: ${u}`)}}cumulativeSum(){let u=0;for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)u+=this.get(c,i),this.set(c,i,u);return this}dot(u){Wt.isMatrix(u)&&(u=u.to1DArray());let c=this.to1DArray();if(c.length!==u.length)throw new RangeError("vectors do not have the same size");let i=0;for(let l=0;l<c.length;l++)i+=c[l]*u[l];return i}mmul(u){u=It.checkMatrix(u);let c=this.rows,i=this.columns,l=u.columns,m=new It(c,l),B=new Float64Array(i);for(let U=0;U<l;U++){for(let V=0;V<i;V++)B[V]=u.get(V,U);for(let V=0;V<c;V++){let G=0;for(let rt=0;rt<i;rt++)G+=this.get(V,rt)*B[rt];m.set(V,U,G)}}return m}mpow(u){if(!this.isSquare())throw new RangeError("Matrix must be square");if(!Number.isInteger(u)||u<0)throw new RangeError("Exponent must be a non-negative integer");let c=It.eye(this.rows),i=this;for(let l=u;l>1;l/=2)l&1&&(c=c.mmul(i)),i=i.mmul(i);return c}strassen2x2(u){u=It.checkMatrix(u);let c=new It(2,2);const i=this.get(0,0),l=u.get(0,0),m=this.get(0,1),B=u.get(0,1),U=this.get(1,0),V=u.get(1,0),G=this.get(1,1),rt=u.get(1,1),K=(i+G)*(l+rt),lt=(U+G)*l,Tt=i*(B-rt),ct=G*(V-l),pt=(i+m)*rt,Rt=(U-i)*(l+B),Z=(m-G)*(V+rt),St=K+ct-pt+Z,Ct=Tt+pt,Xt=lt+ct,Zt=K-lt+Tt+Rt;return c.set(0,0,St),c.set(0,1,Ct),c.set(1,0,Xt),c.set(1,1,Zt),c}strassen3x3(u){u=It.checkMatrix(u);let c=new It(3,3);const i=this.get(0,0),l=this.get(0,1),m=this.get(0,2),B=this.get(1,0),U=this.get(1,1),V=this.get(1,2),G=this.get(2,0),rt=this.get(2,1),K=this.get(2,2),lt=u.get(0,0),Tt=u.get(0,1),ct=u.get(0,2),pt=u.get(1,0),Rt=u.get(1,1),Z=u.get(1,2),St=u.get(2,0),Ct=u.get(2,1),Xt=u.get(2,2),Zt=(i+l+m-B-U-rt-K)*Rt,ge=(i-B)*(-Tt+Rt),Ut=U*(-lt+Tt+pt-Rt-Z-St+Xt),Yt=(-i+B+U)*(lt-Tt+Rt),ce=(B+U)*(-lt+Tt),tt=i*lt,wt=(-i+G+rt)*(lt-ct+Z),Lt=(-i+G)*(ct-Z),Mt=(G+rt)*(-lt+ct),we=(i+l+m-U-V-G-rt)*Z,ae=rt*(-lt+ct+pt-Rt-Z-St+Ct),fe=(-m+rt+K)*(Rt+St-Ct),pe=(m-K)*(Rt-Ct),Re=m*St,_e=(rt+K)*(-St+Ct),Se=(-m+U+V)*(Z+St-Xt),Je=(m-V)*(Z-Xt),Qe=(U+V)*(-St+Xt),te=l*pt,Le=V*Ct,Ue=B*ct,Ve=G*Tt,Oe=K*Xt,xr=tt+Re+te,Er=Zt+Yt+ce+tt+fe+Re+_e,Hn=tt+wt+Mt+we+Re+Se+Qe,br=ge+Ut+Yt+tt+Re+Se+Je,qn=ge+Yt+ce+tt+Le,Nr=Re+Se+Je+Qe+Ue,Mr=tt+wt+Lt+ae+fe+pe+Re,Sr=fe+pe+Re+_e+Ve,tr=tt+wt+Lt+Mt+Oe;return c.set(0,0,xr),c.set(0,1,Er),c.set(0,2,Hn),c.set(1,0,br),c.set(1,1,qn),c.set(1,2,Nr),c.set(2,0,Mr),c.set(2,1,Sr),c.set(2,2,tr),c}mmulStrassen(u){u=It.checkMatrix(u);let c=this.clone(),i=c.rows,l=c.columns,m=u.rows,B=u.columns;l!==m&&console.warn(`Multiplying ${i} x ${l} and ${m} x ${B} matrix: dimensions do not match.`);function U(K,lt,Tt){let ct=K.rows,pt=K.columns;if(ct===lt&&pt===Tt)return K;{let Rt=Wt.zeros(lt,Tt);return Rt=Rt.setSubMatrix(K,0,0),Rt}}let V=Math.max(i,m),G=Math.max(l,B);c=U(c,V,G),u=U(u,V,G);function rt(K,lt,Tt,ct){if(Tt<=512||ct<=512)return K.mmul(lt);Tt%2===1&&ct%2===1?(K=U(K,Tt+1,ct+1),lt=U(lt,Tt+1,ct+1)):Tt%2===1?(K=U(K,Tt+1,ct),lt=U(lt,Tt+1,ct)):ct%2===1&&(K=U(K,Tt,ct+1),lt=U(lt,Tt,ct+1));let pt=parseInt(K.rows/2,10),Rt=parseInt(K.columns/2,10),Z=K.subMatrix(0,pt-1,0,Rt-1),St=lt.subMatrix(0,pt-1,0,Rt-1),Ct=K.subMatrix(0,pt-1,Rt,K.columns-1),Xt=lt.subMatrix(0,pt-1,Rt,lt.columns-1),Zt=K.subMatrix(pt,K.rows-1,0,Rt-1),ge=lt.subMatrix(pt,lt.rows-1,0,Rt-1),Ut=K.subMatrix(pt,K.rows-1,Rt,K.columns-1),Yt=lt.subMatrix(pt,lt.rows-1,Rt,lt.columns-1),ce=rt(Wt.add(Z,Ut),Wt.add(St,Yt),pt,Rt),tt=rt(Wt.add(Zt,Ut),St,pt,Rt),wt=rt(Z,Wt.sub(Xt,Yt),pt,Rt),Lt=rt(Ut,Wt.sub(ge,St),pt,Rt),Mt=rt(Wt.add(Z,Ct),Yt,pt,Rt),we=rt(Wt.sub(Zt,Z),Wt.add(St,Xt),pt,Rt),ae=rt(Wt.sub(Ct,Ut),Wt.add(ge,Yt),pt,Rt),fe=Wt.add(ce,Lt);fe.sub(Mt),fe.add(ae);let pe=Wt.add(wt,Mt),Re=Wt.add(tt,Lt),_e=Wt.sub(ce,tt);_e.add(wt),_e.add(we);let Se=Wt.zeros(2*fe.rows,2*fe.columns);return Se=Se.setSubMatrix(fe,0,0),Se=Se.setSubMatrix(pe,fe.rows,0),Se=Se.setSubMatrix(Re,0,fe.columns),Se=Se.setSubMatrix(_e,fe.rows,fe.columns),Se.subMatrix(0,Tt-1,0,ct-1)}return rt(c,u,V,G)}scaleRows(u={}){if(typeof u!="object")throw new TypeError("options must be an object");const{min:c=0,max:i=1}=u;if(!Number.isFinite(c))throw new TypeError("min must be a number");if(!Number.isFinite(i))throw new TypeError("max must be a number");if(c>=i)throw new RangeError("min must be smaller than max");let l=new It(this.rows,this.columns);for(let m=0;m<this.rows;m++){const B=this.getRow(m);B.length>0&&nt(B,{min:c,max:i,output:B}),l.setRow(m,B)}return l}scaleColumns(u={}){if(typeof u!="object")throw new TypeError("options must be an object");const{min:c=0,max:i=1}=u;if(!Number.isFinite(c))throw new TypeError("min must be a number");if(!Number.isFinite(i))throw new TypeError("max must be a number");if(c>=i)throw new RangeError("min must be smaller than max");let l=new It(this.rows,this.columns);for(let m=0;m<this.columns;m++){const B=this.getColumn(m);B.length&&nt(B,{min:c,max:i,output:B}),l.setColumn(m,B)}return l}flipRows(){const u=Math.ceil(this.columns/2);for(let c=0;c<this.rows;c++)for(let i=0;i<u;i++){let l=this.get(c,i),m=this.get(c,this.columns-1-i);this.set(c,i,m),this.set(c,this.columns-1-i,l)}return this}flipColumns(){const u=Math.ceil(this.rows/2);for(let c=0;c<this.columns;c++)for(let i=0;i<u;i++){let l=this.get(i,c),m=this.get(this.rows-1-i,c);this.set(i,c,m),this.set(this.rows-1-i,c,l)}return this}kroneckerProduct(u){u=It.checkMatrix(u);let c=this.rows,i=this.columns,l=u.rows,m=u.columns,B=new It(c*l,i*m);for(let U=0;U<c;U++)for(let V=0;V<i;V++)for(let G=0;G<l;G++)for(let rt=0;rt<m;rt++)B.set(l*U+G,m*V+rt,this.get(U,V)*u.get(G,rt));return B}kroneckerSum(u){if(u=It.checkMatrix(u),!this.isSquare()||!u.isSquare())throw new Error("Kronecker Sum needs two Square Matrices");let c=this.rows,i=u.rows,l=this.kroneckerProduct(It.eye(i,i)),m=It.eye(c,c).kroneckerProduct(u);return l.add(m)}transpose(){let u=new It(this.columns,this.rows);for(let c=0;c<this.rows;c++)for(let i=0;i<this.columns;i++)u.set(i,c,this.get(c,i));return u}sortRows(u=re){for(let c=0;c<this.rows;c++)this.setRow(c,this.getRow(c).sort(u));return this}sortColumns(u=re){for(let c=0;c<this.columns;c++)this.setColumn(c,this.getColumn(c).sort(u));return this}subMatrix(u,c,i,l){Ht(this,u,c,i,l);let m=new It(c-u+1,l-i+1);for(let B=u;B<=c;B++)for(let U=i;U<=l;U++)m.set(B-u,U-i,this.get(B,U));return m}subMatrixRow(u,c,i){if(c===void 0&&(c=0),i===void 0&&(i=this.columns-1),c>i||c<0||c>=this.columns||i<0||i>=this.columns)throw new RangeError("Argument out of range");let l=new It(u.length,i-c+1);for(let m=0;m<u.length;m++)for(let B=c;B<=i;B++){if(u[m]<0||u[m]>=this.rows)throw new RangeError(`Row index out of range: ${u[m]}`);l.set(m,B-c,this.get(u[m],B))}return l}subMatrixColumn(u,c,i){if(c===void 0&&(c=0),i===void 0&&(i=this.rows-1),c>i||c<0||c>=this.rows||i<0||i>=this.rows)throw new RangeError("Argument out of range");let l=new It(i-c+1,u.length);for(let m=0;m<u.length;m++)for(let B=c;B<=i;B++){if(u[m]<0||u[m]>=this.columns)throw new RangeError(`Column index out of range: ${u[m]}`);l.set(B-c,m,this.get(B,u[m]))}return l}setSubMatrix(u,c,i){if(u=It.checkMatrix(u),u.isEmpty())return this;let l=c+u.rows-1,m=i+u.columns-1;Ht(this,c,l,i,m);for(let B=0;B<u.rows;B++)for(let U=0;U<u.columns;U++)this.set(c+B,i+U,u.get(B,U));return this}selection(u,c){kt(this,u),Vt(this,c);let i=new It(u.length,c.length);for(let l=0;l<u.length;l++){let m=u[l];for(let B=0;B<c.length;B++){let U=c[B];i.set(l,B,this.get(m,U))}}return i}trace(){let u=Math.min(this.rows,this.columns),c=0;for(let i=0;i<u;i++)c+=this.get(i,i);return c}clone(){return this.constructor.copy(this,new It(this.rows,this.columns))}static copy(u,c){for(const[i,l,m]of u.entries())c.set(i,l,m);return c}sum(u){switch(u){case"row":return tn(this);case"column":return bn(this);case void 0:return Nn(this);default:throw new Error(`invalid option: ${u}`)}}product(u){switch(u){case"row":return an(this);case"column":return Ze(this);case void 0:return sn(this);default:throw new Error(`invalid option: ${u}`)}}mean(u){const c=this.sum(u);switch(u){case"row":{for(let i=0;i<this.rows;i++)c[i]/=this.columns;return c}case"column":{for(let i=0;i<this.columns;i++)c[i]/=this.rows;return c}case void 0:return c/this.size;default:throw new Error(`invalid option: ${u}`)}}variance(u,c={}){if(typeof u=="object"&&(c=u,u=void 0),typeof c!="object")throw new TypeError("options must be an object");const{unbiased:i=!0,mean:l=this.mean(u)}=c;if(typeof i!="boolean")throw new TypeError("unbiased must be a boolean");switch(u){case"row":{if(!ot.isAnyArray(l))throw new TypeError("mean must be an array");return gt(this,i,l)}case"column":{if(!ot.isAnyArray(l))throw new TypeError("mean must be an array");return vt(this,i,l)}case void 0:{if(typeof l!="number")throw new TypeError("mean must be a number");return At(this,i,l)}default:throw new Error(`invalid option: ${u}`)}}standardDeviation(u,c){typeof u=="object"&&(c=u,u=void 0);const i=this.variance(u,c);if(u===void 0)return Math.sqrt(i);for(let l=0;l<i.length;l++)i[l]=Math.sqrt(i[l]);return i}center(u,c={}){if(typeof u=="object"&&(c=u,u=void 0),typeof c!="object")throw new TypeError("options must be an object");const{center:i=this.mean(u)}=c;switch(u){case"row":{if(!ot.isAnyArray(i))throw new TypeError("center must be an array");return Ft(this,i),this}case"column":{if(!ot.isAnyArray(i))throw new TypeError("center must be an array");return qt(this,i),this}case void 0:{if(typeof i!="number")throw new TypeError("center must be a number");return ue(this,i),this}default:throw new Error(`invalid option: ${u}`)}}scale(u,c={}){if(typeof u=="object"&&(c=u,u=void 0),typeof c!="object")throw new TypeError("options must be an object");let i=c.scale;switch(u){case"row":{if(i===void 0)i=he(this);else if(!ot.isAnyArray(i))throw new TypeError("scale must be an array");return Ie(this,i),this}case"column":{if(i===void 0)i=pn(this);else if(!ot.isAnyArray(i))throw new TypeError("scale must be an array");return De(this,i),this}case void 0:{if(i===void 0)i=Me(this);else if(typeof i!="number")throw new TypeError("scale must be a number");return se(this,i),this}default:throw new Error(`invalid option: ${u}`)}}toString(u){return it(this,u)}[Symbol.iterator](){return this.entries()}*entries(){for(let u=0;u<this.rows;u++)for(let c=0;c<this.columns;c++)yield[u,c,this.get(u,c)]}*values(){for(let u=0;u<this.rows;u++)for(let c=0;c<this.columns;c++)yield this.get(u,c)}}Wt.prototype.klass="Matrix",typeof Symbol!="undefined"&&(Wt.prototype[Symbol.for("nodejs.util.inspect.custom")]=H);function re(T,u){return T-u}function en(T){return T.every(u=>typeof u=="number")}Wt.random=Wt.rand,Wt.randomInt=Wt.randInt,Wt.diagonal=Wt.diag,Wt.prototype.diagonal=Wt.prototype.diag,Wt.identity=Wt.eye,Wt.prototype.negate=Wt.prototype.neg,Wt.prototype.tensorProduct=Wt.prototype.kroneckerProduct;const on=class Zr extends Wt{constructor(u,c){if(super(),A(this,D),N(this,"data"),Zr.isMatrix(u))j(this,D,Y).call(this,u.rows,u.columns),Zr.copy(u,this);else if(Number.isInteger(u)&&u>=0)j(this,D,Y).call(this,u,c);else if(ot.isAnyArray(u)){const i=u;if(u=i.length,c=u?i[0].length:0,typeof c!="number")throw new TypeError("Data must be a 2D array with at least one element");this.data=[];for(let l=0;l<u;l++){if(i[l].length!==c)throw new RangeError("Inconsistent array dimensions");if(!en(i[l]))throw new TypeError("Input data contains non-numeric values");this.data.push(Float64Array.from(i[l]))}this.rows=u,this.columns=c}else throw new TypeError("First argument must be a positive number or an array")}set(u,c,i){return this.data[u][c]=i,this}get(u,c){return this.data[u][c]}removeRow(u){return xt(this,u),this.data.splice(u,1),this.rows-=1,this}addRow(u,c){return c===void 0&&(c=u,u=this.rows),xt(this,u,!0),c=Float64Array.from(Nt(this,c)),this.data.splice(u,0,c),this.rows+=1,this}removeColumn(u){yt(this,u);for(let c=0;c<this.rows;c++){const i=new Float64Array(this.columns-1);for(let l=0;l<u;l++)i[l]=this.data[c][l];for(let l=u+1;l<this.columns;l++)i[l-1]=this.data[c][l];this.data[c]=i}return this.columns-=1,this}addColumn(u,c){typeof c=="undefined"&&(c=u,u=this.columns),yt(this,u,!0),c=Ot(this,c);for(let i=0;i<this.rows;i++){const l=new Float64Array(this.columns+1);let m=0;for(;m<u;m++)l[m]=this.data[i][m];for(l[m++]=c[i];m<this.columns+1;m++)l[m]=this.data[i][m-1];this.data[i]=l}return this.columns+=1,this}};D=new WeakSet,Y=function(T,u){if(this.data=[],Number.isInteger(u)&&u>=0)for(let c=0;c<T;c++)this.data.push(new Float64Array(u));else throw new TypeError("nColumns must be a positive integer");this.rows=T,this.columns=u};let It=on;dt(Wt,It);const un=class Jr extends Wt{constructor(u){if(super(),A(this,_),It.isMatrix(u)){if(!u.isSymmetric())throw new TypeError("not symmetric data");I(this,_,It.copy(u,new It(u.rows,u.rows)))}else if(Number.isInteger(u)&&u>=0)I(this,_,new It(u,u));else if(I(this,_,new It(u)),!this.isSymmetric())throw new TypeError("not symmetric data")}get size(){return M(this,_).size}get rows(){return M(this,_).rows}get columns(){return M(this,_).columns}get diagonalSize(){return this.rows}static isSymmetricMatrix(u){return It.isMatrix(u)&&u.klassType==="SymmetricMatrix"}static zeros(u){return new this(u)}static ones(u){return new this(u).fill(1)}clone(){const u=new Jr(this.diagonalSize);for(const[c,i,l]of this.upperRightEntries())u.set(c,i,l);return u}toMatrix(){return new It(this)}get(u,c){return M(this,_).get(u,c)}set(u,c,i){return M(this,_).set(u,c,i),M(this,_).set(c,u,i),this}removeCross(u){return M(this,_).removeRow(u),M(this,_).removeColumn(u),this}addCross(u,c){c===void 0&&(c=u,u=this.diagonalSize);const i=c.slice();return i.splice(u,1),M(this,_).addRow(u,i),M(this,_).addColumn(u,c),this}applyMask(u){if(u.length!==this.diagonalSize)throw new RangeError("Mask size do not match with matrix size");const c=[];for(const[i,l]of u.entries())l||c.push(i);c.reverse();for(const i of c)this.removeCross(i);return this}toCompact(){const{diagonalSize:u}=this,c=new Array(u*(u+1)/2);for(let i=0,l=0,m=0;m<c.length;m++)c[m]=this.get(l,i),++i>=u&&(i=++l);return c}static fromCompact(u){const c=u.length,i=(Math.sqrt(8*c+1)-1)/2;if(!Number.isInteger(i))throw new TypeError(`This array is not a compact representation of a Symmetric Matrix, ${JSON.stringify(u)}`);const l=new Jr(i);for(let m=0,B=0,U=0;U<c;U++)l.set(m,B,u[U]),++m>=i&&(m=++B);return l}*upperRightEntries(){for(let u=0,c=0;u<this.diagonalSize;void 0){const i=this.get(u,c);yield[u,c,i],++c>=this.diagonalSize&&(c=++u)}}*upperRightValues(){for(let u=0,c=0;u<this.diagonalSize;void 0)yield this.get(u,c),++c>=this.diagonalSize&&(c=++u)}};_=new WeakMap;let Pe=un;Pe.prototype.klassType="SymmetricMatrix";class xe extends Pe{static isDistanceMatrix(u){return Pe.isSymmetricMatrix(u)&&u.klassSubType==="DistanceMatrix"}constructor(u){if(super(u),!this.isDistance())throw new TypeError("Provided arguments do no produce a distance matrix")}set(u,c,i){return u===c&&(i=0),super.set(u,c,i)}addCross(u,c){return c===void 0&&(c=u,u=this.diagonalSize),c=c.slice(),c[u]=0,super.addCross(u,c)}toSymmetricMatrix(){return new Pe(this)}clone(){const u=new xe(this.diagonalSize);for(const[c,i,l]of this.upperRightEntries())c!==i&&u.set(c,i,l);return u}toCompact(){const{diagonalSize:u}=this,c=(u-1)*u/2,i=new Array(c);for(let l=1,m=0,B=0;B<i.length;B++)i[B]=this.get(m,l),++l>=u&&(l=++m+1);return i}static fromCompact(u){const c=u.length;if(c===0)return new this(0);const i=(Math.sqrt(8*c+1)+1)/2;if(!Number.isInteger(i))throw new TypeError(`This array is not a compact representation of a DistanceMatrix, ${JSON.stringify(u)}`);const l=new this(i);for(let m=1,B=0,U=0;U<c;U++)l.set(m,B,u[U]),++m>=i&&(m=++B+1);return l}}xe.prototype.klassSubType="DistanceMatrix";class ke extends Wt{constructor(u,c,i){super(),this.matrix=u,this.rows=c,this.columns=i}}class vn extends ke{constructor(u,c){yt(u,c),super(u,u.rows,1),this.column=c}set(u,c,i){return this.matrix.set(u,this.column,i),this}get(u){return this.matrix.get(u,this.column)}}class Mn extends ke{constructor(u,c){Vt(u,c),super(u,u.rows,c.length),this.columnIndices=c}set(u,c,i){return this.matrix.set(u,this.columnIndices[c],i),this}get(u,c){return this.matrix.get(u,this.columnIndices[c])}}class In extends ke{constructor(u){super(u,u.rows,u.columns)}set(u,c,i){return this.matrix.set(u,this.columns-c-1,i),this}get(u,c){return this.matrix.get(u,this.columns-c-1)}}class nn extends ke{constructor(u){super(u,u.rows,u.columns)}set(u,c,i){return this.matrix.set(this.rows-u-1,c,i),this}get(u,c){return this.matrix.get(this.rows-u-1,c)}}class Sn extends ke{constructor(u,c){xt(u,c),super(u,1,u.columns),this.row=c}set(u,c,i){return this.matrix.set(this.row,c,i),this}get(u,c){return this.matrix.get(this.row,c)}}class Pn extends ke{constructor(u,c){kt(u,c),super(u,c.length,u.columns),this.rowIndices=c}set(u,c,i){return this.matrix.set(this.rowIndices[u],c,i),this}get(u,c){return this.matrix.get(this.rowIndices[u],c)}}class mn extends ke{constructor(u,c,i){kt(u,c),Vt(u,i),super(u,c.length,i.length),this.rowIndices=c,this.columnIndices=i}set(u,c,i){return this.matrix.set(this.rowIndices[u],this.columnIndices[c],i),this}get(u,c){return this.matrix.get(this.rowIndices[u],this.columnIndices[c])}}class Bn extends ke{constructor(u,c,i,l,m){Ht(u,c,i,l,m),super(u,i-c+1,m-l+1),this.startRow=c,this.startColumn=l}set(u,c,i){return this.matrix.set(this.startRow+u,this.startColumn+c,i),this}get(u,c){return this.matrix.get(this.startRow+u,this.startColumn+c)}}class Be extends ke{constructor(u){super(u,u.columns,u.rows)}set(u,c,i){return this.matrix.set(c,u,i),this}get(u,c){return this.matrix.get(c,u)}}class ze extends Wt{constructor(u,c={}){const{rows:i=1}=c;if(u.length%i!==0)throw new Error("the data length is not divisible by the number of rows");super(),this.rows=i,this.columns=u.length/i,this.data=u}set(u,c,i){let l=this._calculateIndex(u,c);return this.data[l]=i,this}get(u,c){let i=this._calculateIndex(u,c);return this.data[i]}_calculateIndex(u,c){return u*this.columns+c}}class Ae extends Wt{constructor(u){super(),this.data=u,this.rows=u.length,this.columns=u[0].length}set(u,c,i){return this.data[u][c]=i,this}get(u,c){return this.data[u][c]}}function fr(T,u){if(ot.isAnyArray(T))return T[0]&&ot.isAnyArray(T[0])?new Ae(T):new ze(T,u);throw new Error("the argument is not an array")}class _t{constructor(u){u=Ae.checkMatrix(u);let c=u.clone(),i=c.rows,l=c.columns,m=new Float64Array(i),B=1,U,V,G,rt,K,lt,Tt,ct,pt;for(U=0;U<i;U++)m[U]=U;for(ct=new Float64Array(i),V=0;V<l;V++){for(U=0;U<i;U++)ct[U]=c.get(U,V);for(U=0;U<i;U++){for(pt=Math.min(U,V),K=0,G=0;G<pt;G++)K+=c.get(U,G)*ct[G];ct[U]-=K,c.set(U,V,ct[U])}for(rt=V,U=V+1;U<i;U++)Math.abs(ct[U])>Math.abs(ct[rt])&&(rt=U);if(rt!==V){for(G=0;G<l;G++)lt=c.get(rt,G),c.set(rt,G,c.get(V,G)),c.set(V,G,lt);Tt=m[rt],m[rt]=m[V],m[V]=Tt,B=-B}if(V<i&&c.get(V,V)!==0)for(U=V+1;U<i;U++)c.set(U,V,c.get(U,V)/c.get(V,V))}this.LU=c,this.pivotVector=m,this.pivotSign=B}isSingular(){let u=this.LU,c=u.columns;for(let i=0;i<c;i++)if(u.get(i,i)===0)return!0;return!1}solve(u){u=It.checkMatrix(u);let c=this.LU;if(c.rows!==u.rows)throw new Error("Invalid matrix dimensions");if(this.isSingular())throw new Error("LU matrix is singular");let l=u.columns,m=u.subMatrixRow(this.pivotVector,0,l-1),B=c.columns,U,V,G;for(G=0;G<B;G++)for(U=G+1;U<B;U++)for(V=0;V<l;V++)m.set(U,V,m.get(U,V)-m.get(G,V)*c.get(U,G));for(G=B-1;G>=0;G--){for(V=0;V<l;V++)m.set(G,V,m.get(G,V)/c.get(G,G));for(U=0;U<G;U++)for(V=0;V<l;V++)m.set(U,V,m.get(U,V)-m.get(G,V)*c.get(U,G))}return m}get determinant(){let u=this.LU;if(!u.isSquare())throw new Error("Matrix must be square");let c=this.pivotSign,i=u.columns;for(let l=0;l<i;l++)c*=u.get(l,l);return c}get lowerTriangularMatrix(){let u=this.LU,c=u.rows,i=u.columns,l=new It(c,i);for(let m=0;m<c;m++)for(let B=0;B<i;B++)m>B?l.set(m,B,u.get(m,B)):m===B?l.set(m,B,1):l.set(m,B,0);return l}get upperTriangularMatrix(){let u=this.LU,c=u.rows,i=u.columns,l=new It(c,i);for(let m=0;m<c;m++)for(let B=0;B<i;B++)m<=B?l.set(m,B,u.get(m,B)):l.set(m,B,0);return l}get pivotPermutationVector(){return Array.from(this.pivotVector)}}function rn(T,u){let c=0;return Math.abs(T)>Math.abs(u)?(c=u/T,Math.abs(T)*Math.sqrt(1+c*c)):u!==0?(c=T/u,Math.abs(u)*Math.sqrt(1+c*c)):0}class Un{constructor(u){u=Ae.checkMatrix(u);let c=u.clone(),i=u.rows,l=u.columns,m=new Float64Array(l),B,U,V,G;for(V=0;V<l;V++){let rt=0;for(B=V;B<i;B++)rt=rn(rt,c.get(B,V));if(rt!==0){for(c.get(V,V)<0&&(rt=-rt),B=V;B<i;B++)c.set(B,V,c.get(B,V)/rt);for(c.set(V,V,c.get(V,V)+1),U=V+1;U<l;U++){for(G=0,B=V;B<i;B++)G+=c.get(B,V)*c.get(B,U);for(G=-G/c.get(V,V),B=V;B<i;B++)c.set(B,U,c.get(B,U)+G*c.get(B,V))}}m[V]=-rt}this.QR=c,this.Rdiag=m}solve(u){u=It.checkMatrix(u);let c=this.QR,i=c.rows;if(u.rows!==i)throw new Error("Matrix row dimensions must agree");if(!this.isFullRank())throw new Error("Matrix is rank deficient");let l=u.columns,m=u.clone(),B=c.columns,U,V,G,rt;for(G=0;G<B;G++)for(V=0;V<l;V++){for(rt=0,U=G;U<i;U++)rt+=c.get(U,G)*m.get(U,V);for(rt=-rt/c.get(G,G),U=G;U<i;U++)m.set(U,V,m.get(U,V)+rt*c.get(U,G))}for(G=B-1;G>=0;G--){for(V=0;V<l;V++)m.set(G,V,m.get(G,V)/this.Rdiag[G]);for(U=0;U<G;U++)for(V=0;V<l;V++)m.set(U,V,m.get(U,V)-m.get(G,V)*c.get(U,G))}return m.subMatrix(0,B-1,0,l-1)}isFullRank(){let u=this.QR.columns;for(let c=0;c<u;c++)if(this.Rdiag[c]===0)return!1;return!0}get upperTriangularMatrix(){let u=this.QR,c=u.columns,i=new It(c,c),l,m;for(l=0;l<c;l++)for(m=0;m<c;m++)l<m?i.set(l,m,u.get(l,m)):l===m?i.set(l,m,this.Rdiag[l]):i.set(l,m,0);return i}get orthogonalMatrix(){let u=this.QR,c=u.rows,i=u.columns,l=new It(c,i),m,B,U,V;for(U=i-1;U>=0;U--){for(m=0;m<c;m++)l.set(m,U,0);for(l.set(U,U,1),B=U;B<i;B++)if(u.get(U,U)!==0){for(V=0,m=U;m<c;m++)V+=u.get(m,U)*l.get(m,B);for(V=-V/u.get(U,U),m=U;m<c;m++)l.set(m,B,l.get(m,B)+V*u.get(m,U))}}return l}}class cn{constructor(u,c={}){if(u=Ae.checkMatrix(u),u.isEmpty())throw new Error("Matrix must be non-empty");let i=u.rows,l=u.columns;const{computeLeftSingularVectors:m=!0,computeRightSingularVectors:B=!0,autoTranspose:U=!1}=c;let V=!!m,G=!!B,rt=!1,K;if(i<l)if(!U)K=u.clone(),console.warn("Computing SVD on a matrix with more columns than rows. Consider enabling autoTranspose");else{K=u.transpose(),i=K.rows,l=K.columns,rt=!0;let tt=V;V=G,G=tt}else K=u.clone();let lt=Math.min(i,l),Tt=Math.min(i+1,l),ct=new Float64Array(Tt),pt=new It(i,lt),Rt=new It(l,l),Z=new Float64Array(l),St=new Float64Array(i),Ct=new Float64Array(Tt);for(let tt=0;tt<Tt;tt++)Ct[tt]=tt;let Xt=Math.min(i-1,l),Zt=Math.max(0,Math.min(l-2,i)),ge=Math.max(Xt,Zt);for(let tt=0;tt<ge;tt++){if(tt<Xt){ct[tt]=0;for(let wt=tt;wt<i;wt++)ct[tt]=rn(ct[tt],K.get(wt,tt));if(ct[tt]!==0){K.get(tt,tt)<0&&(ct[tt]=-ct[tt]);for(let wt=tt;wt<i;wt++)K.set(wt,tt,K.get(wt,tt)/ct[tt]);K.set(tt,tt,K.get(tt,tt)+1)}ct[tt]=-ct[tt]}for(let wt=tt+1;wt<l;wt++){if(tt<Xt&&ct[tt]!==0){let Lt=0;for(let Mt=tt;Mt<i;Mt++)Lt+=K.get(Mt,tt)*K.get(Mt,wt);Lt=-Lt/K.get(tt,tt);for(let Mt=tt;Mt<i;Mt++)K.set(Mt,wt,K.get(Mt,wt)+Lt*K.get(Mt,tt))}Z[wt]=K.get(tt,wt)}if(V&&tt<Xt)for(let wt=tt;wt<i;wt++)pt.set(wt,tt,K.get(wt,tt));if(tt<Zt){Z[tt]=0;for(let wt=tt+1;wt<l;wt++)Z[tt]=rn(Z[tt],Z[wt]);if(Z[tt]!==0){Z[tt+1]<0&&(Z[tt]=0-Z[tt]);for(let wt=tt+1;wt<l;wt++)Z[wt]/=Z[tt];Z[tt+1]+=1}if(Z[tt]=-Z[tt],tt+1<i&&Z[tt]!==0){for(let wt=tt+1;wt<i;wt++)St[wt]=0;for(let wt=tt+1;wt<i;wt++)for(let Lt=tt+1;Lt<l;Lt++)St[wt]+=Z[Lt]*K.get(wt,Lt);for(let wt=tt+1;wt<l;wt++){let Lt=-Z[wt]/Z[tt+1];for(let Mt=tt+1;Mt<i;Mt++)K.set(Mt,wt,K.get(Mt,wt)+Lt*St[Mt])}}if(G)for(let wt=tt+1;wt<l;wt++)Rt.set(wt,tt,Z[wt])}}let Ut=Math.min(l,i+1);if(Xt<l&&(ct[Xt]=K.get(Xt,Xt)),i<Ut&&(ct[Ut-1]=0),Zt+1<Ut&&(Z[Zt]=K.get(Zt,Ut-1)),Z[Ut-1]=0,V){for(let tt=Xt;tt<lt;tt++){for(let wt=0;wt<i;wt++)pt.set(wt,tt,0);pt.set(tt,tt,1)}for(let tt=Xt-1;tt>=0;tt--)if(ct[tt]!==0){for(let wt=tt+1;wt<lt;wt++){let Lt=0;for(let Mt=tt;Mt<i;Mt++)Lt+=pt.get(Mt,tt)*pt.get(Mt,wt);Lt=-Lt/pt.get(tt,tt);for(let Mt=tt;Mt<i;Mt++)pt.set(Mt,wt,pt.get(Mt,wt)+Lt*pt.get(Mt,tt))}for(let wt=tt;wt<i;wt++)pt.set(wt,tt,-pt.get(wt,tt));pt.set(tt,tt,1+pt.get(tt,tt));for(let wt=0;wt<tt-1;wt++)pt.set(wt,tt,0)}else{for(let wt=0;wt<i;wt++)pt.set(wt,tt,0);pt.set(tt,tt,1)}}if(G)for(let tt=l-1;tt>=0;tt--){if(tt<Zt&&Z[tt]!==0)for(let wt=tt+1;wt<l;wt++){let Lt=0;for(let Mt=tt+1;Mt<l;Mt++)Lt+=Rt.get(Mt,tt)*Rt.get(Mt,wt);Lt=-Lt/Rt.get(tt+1,tt);for(let Mt=tt+1;Mt<l;Mt++)Rt.set(Mt,wt,Rt.get(Mt,wt)+Lt*Rt.get(Mt,tt))}for(let wt=0;wt<l;wt++)Rt.set(wt,tt,0);Rt.set(tt,tt,1)}let Yt=Ut-1,ce=Number.EPSILON;for(;Ut>0;){let tt,wt;for(tt=Ut-2;tt>=-1&&tt!==-1;tt--){const Lt=Number.MIN_VALUE+ce*Math.abs(ct[tt]+Math.abs(ct[tt+1]));if(Math.abs(Z[tt])<=Lt||Number.isNaN(Z[tt])){Z[tt]=0;break}}if(tt===Ut-2)wt=4;else{let Lt;for(Lt=Ut-1;Lt>=tt&&Lt!==tt;Lt--){let Mt=(Lt!==Ut?Math.abs(Z[Lt]):0)+(Lt!==tt+1?Math.abs(Z[Lt-1]):0);if(Math.abs(ct[Lt])<=ce*Mt){ct[Lt]=0;break}}Lt===tt?wt=3:Lt===Ut-1?wt=1:(wt=2,tt=Lt)}switch(tt++,wt){case 1:{let Lt=Z[Ut-2];Z[Ut-2]=0;for(let Mt=Ut-2;Mt>=tt;Mt--){let we=rn(ct[Mt],Lt),ae=ct[Mt]/we,fe=Lt/we;if(ct[Mt]=we,Mt!==tt&&(Lt=-fe*Z[Mt-1],Z[Mt-1]=ae*Z[Mt-1]),G)for(let pe=0;pe<l;pe++)we=ae*Rt.get(pe,Mt)+fe*Rt.get(pe,Ut-1),Rt.set(pe,Ut-1,-fe*Rt.get(pe,Mt)+ae*Rt.get(pe,Ut-1)),Rt.set(pe,Mt,we)}break}case 2:{let Lt=Z[tt-1];Z[tt-1]=0;for(let Mt=tt;Mt<Ut;Mt++){let we=rn(ct[Mt],Lt),ae=ct[Mt]/we,fe=Lt/we;if(ct[Mt]=we,Lt=-fe*Z[Mt],Z[Mt]=ae*Z[Mt],V)for(let pe=0;pe<i;pe++)we=ae*pt.get(pe,Mt)+fe*pt.get(pe,tt-1),pt.set(pe,tt-1,-fe*pt.get(pe,Mt)+ae*pt.get(pe,tt-1)),pt.set(pe,Mt,we)}break}case 3:{const Lt=Math.max(Math.abs(ct[Ut-1]),Math.abs(ct[Ut-2]),Math.abs(Z[Ut-2]),Math.abs(ct[tt]),Math.abs(Z[tt])),Mt=ct[Ut-1]/Lt,we=ct[Ut-2]/Lt,ae=Z[Ut-2]/Lt,fe=ct[tt]/Lt,pe=Z[tt]/Lt,Re=((we+Mt)*(we-Mt)+ae*ae)/2,_e=Mt*ae*(Mt*ae);let Se=0;(Re!==0||_e!==0)&&(Re<0?Se=0-Math.sqrt(Re*Re+_e):Se=Math.sqrt(Re*Re+_e),Se=_e/(Re+Se));let Je=(fe+Mt)*(fe-Mt)+Se,Qe=fe*pe;for(let te=tt;te<Ut-1;te++){let Le=rn(Je,Qe);Le===0&&(Le=Number.MIN_VALUE);let Ue=Je/Le,Ve=Qe/Le;if(te!==tt&&(Z[te-1]=Le),Je=Ue*ct[te]+Ve*Z[te],Z[te]=Ue*Z[te]-Ve*ct[te],Qe=Ve*ct[te+1],ct[te+1]=Ue*ct[te+1],G)for(let Oe=0;Oe<l;Oe++)Le=Ue*Rt.get(Oe,te)+Ve*Rt.get(Oe,te+1),Rt.set(Oe,te+1,-Ve*Rt.get(Oe,te)+Ue*Rt.get(Oe,te+1)),Rt.set(Oe,te,Le);if(Le=rn(Je,Qe),Le===0&&(Le=Number.MIN_VALUE),Ue=Je/Le,Ve=Qe/Le,ct[te]=Le,Je=Ue*Z[te]+Ve*ct[te+1],ct[te+1]=-Ve*Z[te]+Ue*ct[te+1],Qe=Ve*Z[te+1],Z[te+1]=Ue*Z[te+1],V&&te<i-1)for(let Oe=0;Oe<i;Oe++)Le=Ue*pt.get(Oe,te)+Ve*pt.get(Oe,te+1),pt.set(Oe,te+1,-Ve*pt.get(Oe,te)+Ue*pt.get(Oe,te+1)),pt.set(Oe,te,Le)}Z[Ut-2]=Je;break}case 4:{if(ct[tt]<=0&&(ct[tt]=ct[tt]<0?-ct[tt]:0,G))for(let Lt=0;Lt<=Yt;Lt++)Rt.set(Lt,tt,-Rt.get(Lt,tt));for(;tt<Yt&&!(ct[tt]>=ct[tt+1]);){let Lt=ct[tt];if(ct[tt]=ct[tt+1],ct[tt+1]=Lt,G&&tt<l-1)for(let Mt=0;Mt<l;Mt++)Lt=Rt.get(Mt,tt+1),Rt.set(Mt,tt+1,Rt.get(Mt,tt)),Rt.set(Mt,tt,Lt);if(V&&tt<i-1)for(let Mt=0;Mt<i;Mt++)Lt=pt.get(Mt,tt+1),pt.set(Mt,tt+1,pt.get(Mt,tt)),pt.set(Mt,tt,Lt);tt++}Ut--;break}}}if(rt){let tt=Rt;Rt=pt,pt=tt}this.m=i,this.n=l,this.s=ct,this.U=pt,this.V=Rt}solve(u){let c=u,i=this.threshold,l=this.s.length,m=It.zeros(l,l);for(let lt=0;lt<l;lt++)Math.abs(this.s[lt])<=i?m.set(lt,lt,0):m.set(lt,lt,1/this.s[lt]);let B=this.U,U=this.rightSingularVectors,V=U.mmul(m),G=U.rows,rt=B.rows,K=It.zeros(G,rt);for(let lt=0;lt<G;lt++)for(let Tt=0;Tt<rt;Tt++){let ct=0;for(let pt=0;pt<l;pt++)ct+=V.get(lt,pt)*B.get(Tt,pt);K.set(lt,Tt,ct)}return K.mmul(c)}solveForDiagonal(u){return this.solve(It.diag(u))}inverse(){let u=this.V,c=this.threshold,i=u.rows,l=u.columns,m=new It(i,this.s.length);for(let rt=0;rt<i;rt++)for(let K=0;K<l;K++)Math.abs(this.s[K])>c&&m.set(rt,K,u.get(rt,K)/this.s[K]);let B=this.U,U=B.rows,V=B.columns,G=new It(i,U);for(let rt=0;rt<i;rt++)for(let K=0;K<U;K++){let lt=0;for(let Tt=0;Tt<V;Tt++)lt+=m.get(rt,Tt)*B.get(K,Tt);G.set(rt,K,lt)}return G}get condition(){return this.s[0]/this.s[Math.min(this.m,this.n)-1]}get norm2(){return this.s[0]}get rank(){let u=Math.max(this.m,this.n)*this.s[0]*Number.EPSILON,c=0,i=this.s;for(let l=0,m=i.length;l<m;l++)i[l]>u&&c++;return c}get diagonal(){return Array.from(this.s)}get threshold(){return Number.EPSILON/2*Math.max(this.m,this.n)*this.s[0]}get leftSingularVectors(){return this.U}get rightSingularVectors(){return this.V}get diagonalMatrix(){return It.diag(this.s)}}function lr(T,u=!1){return T=Ae.checkMatrix(T),u?new cn(T).inverse():Jn(T,It.eye(T.rows))}function Jn(T,u,c=!1){return T=Ae.checkMatrix(T),u=Ae.checkMatrix(u),c?new cn(T).solve(u):T.isSquare()?new _t(T).solve(u):new Un(T).solve(u)}function Rn(T){if(T=It.checkMatrix(T),T.isSquare()){if(T.columns===0)return 1;let u,c,i,l;if(T.columns===2)return u=T.get(0,0),c=T.get(0,1),i=T.get(1,0),l=T.get(1,1),u*l-c*i;if(T.columns===3){let m,B,U;return m=new mn(T,[1,2],[1,2]),B=new mn(T,[1,2],[0,2]),U=new mn(T,[1,2],[0,1]),u=T.get(0,0),c=T.get(0,1),i=T.get(0,2),u*Rn(m)-c*Rn(B)+i*Rn(U)}else return new _t(T).determinant}else throw Error("determinant can only be calculated for a square matrix")}function dr(T,u){let c=[];for(let i=0;i<T;i++)i!==u&&c.push(i);return c}function hr(T,u,c,i=1e-9,l=1e-9){if(T>l)return new Array(u.rows+1).fill(0);{let m=u.addRow(c,[0]);for(let B=0;B<m.rows;B++)Math.abs(m.get(B,0))<i&&m.set(B,0,0);return m.to1DArray()}}function Vn(T,u={}){const{thresholdValue:c=1e-9,thresholdError:i=1e-9}=u;T=It.checkMatrix(T);let l=T.rows,m=new It(l,l);for(let B=0;B<l;B++){let U=It.columnVector(T.getRow(B)),V=T.subMatrixRow(dr(l,B)).transpose(),rt=new cn(V).solve(U),K=It.sub(U,V.mmul(rt)).abs().max();m.setRow(B,hr(K,rt,B,c,i))}return m}function gr(T,u=Number.EPSILON){if(T=It.checkMatrix(T),T.isEmpty())return T.transpose();let c=new cn(T,{autoTranspose:!0}),i=c.leftSingularVectors,l=c.rightSingularVectors,m=c.diagonal;for(let B=0;B<m.length;B++)Math.abs(m[B])>u?m[B]=1/m[B]:m[B]=0;return l.mmul(It.diag(m).mmul(i.transpose()))}function Gn(T,u=T,c={}){T=new It(T);let i=!1;if(typeof u=="object"&&!It.isMatrix(u)&&!ot.isAnyArray(u)?(c=u,u=T,i=!0):u=new It(u),T.rows!==u.rows)throw new TypeError("Both matrices must have the same number of rows");const{center:l=!0}=c;l&&(T=T.center("column"),i||(u=u.center("column")));const m=T.transpose().mmul(u);for(let B=0;B<m.rows;B++)for(let U=0;U<m.columns;U++)m.set(B,U,m.get(B,U)*(1/(T.rows-1)));return m}function pr(T,u=T,c={}){T=new It(T);let i=!1;if(typeof u=="object"&&!It.isMatrix(u)&&!ot.isAnyArray(u)?(c=u,u=T,i=!0):u=new It(u),T.rows!==u.rows)throw new TypeError("Both matrices must have the same number of rows");const{center:l=!0,scale:m=!0}=c;l&&(T.center("column"),i||u.center("column")),m&&(T.scale("column"),i||u.scale("column"));const B=T.standardDeviation("column",{unbiased:!0}),U=i?B:u.standardDeviation("column",{unbiased:!0}),V=T.transpose().mmul(u);for(let G=0;G<V.rows;G++)for(let rt=0;rt<V.columns;rt++)V.set(G,rt,V.get(G,rt)*(1/(B[G]*U[rt]))*(1/(T.rows-1)));return V}class Qn{constructor(u,c={}){const{assumeSymmetric:i=!1}=c;if(u=Ae.checkMatrix(u),!u.isSquare())throw new Error("Matrix is not a square matrix");if(u.isEmpty())throw new Error("Matrix must be non-empty");let l=u.columns,m=new It(l,l),B=new Float64Array(l),U=new Float64Array(l),V=u,G,rt,K=!1;if(i?K=!0:K=u.isSymmetric(),K){for(G=0;G<l;G++)for(rt=0;rt<l;rt++)m.set(G,rt,V.get(G,rt));vr(l,U,B,m),mr(l,U,B,m)}else{let lt=new It(l,l),Tt=new Float64Array(l);for(rt=0;rt<l;rt++)for(G=0;G<l;G++)lt.set(G,rt,V.get(G,rt));yn(l,lt,Tt,m),yr(l,U,B,m,lt)}this.n=l,this.e=U,this.d=B,this.V=m}get realEigenvalues(){return Array.from(this.d)}get imaginaryEigenvalues(){return Array.from(this.e)}get eigenvectorMatrix(){return this.V}get diagonalMatrix(){let u=this.n,c=this.e,i=this.d,l=new It(u,u),m,B;for(m=0;m<u;m++){for(B=0;B<u;B++)l.set(m,B,0);l.set(m,m,i[m]),c[m]>0?l.set(m,m+1,c[m]):c[m]<0&&l.set(m,m-1,c[m])}return l}}function vr(T,u,c,i){let l,m,B,U,V,G,rt,K;for(V=0;V<T;V++)c[V]=i.get(T-1,V);for(U=T-1;U>0;U--){for(K=0,B=0,G=0;G<U;G++)K=K+Math.abs(c[G]);if(K===0)for(u[U]=c[U-1],V=0;V<U;V++)c[V]=i.get(U-1,V),i.set(U,V,0),i.set(V,U,0);else{for(G=0;G<U;G++)c[G]/=K,B+=c[G]*c[G];for(l=c[U-1],m=Math.sqrt(B),l>0&&(m=-m),u[U]=K*m,B=B-l*m,c[U-1]=l-m,V=0;V<U;V++)u[V]=0;for(V=0;V<U;V++){for(l=c[V],i.set(V,U,l),m=u[V]+i.get(V,V)*l,G=V+1;G<=U-1;G++)m+=i.get(G,V)*c[G],u[G]+=i.get(G,V)*l;u[V]=m}for(l=0,V=0;V<U;V++)u[V]/=B,l+=u[V]*c[V];for(rt=l/(B+B),V=0;V<U;V++)u[V]-=rt*c[V];for(V=0;V<U;V++){for(l=c[V],m=u[V],G=V;G<=U-1;G++)i.set(G,V,i.get(G,V)-(l*u[G]+m*c[G]));c[V]=i.get(U-1,V),i.set(U,V,0)}}c[U]=B}for(U=0;U<T-1;U++){if(i.set(T-1,U,i.get(U,U)),i.set(U,U,1),B=c[U+1],B!==0){for(G=0;G<=U;G++)c[G]=i.get(G,U+1)/B;for(V=0;V<=U;V++){for(m=0,G=0;G<=U;G++)m+=i.get(G,U+1)*i.get(G,V);for(G=0;G<=U;G++)i.set(G,V,i.get(G,V)-m*c[G])}}for(G=0;G<=U;G++)i.set(G,U+1,0)}for(V=0;V<T;V++)c[V]=i.get(T-1,V),i.set(T-1,V,0);i.set(T-1,T-1,1),u[0]=0}function mr(T,u,c,i){let l,m,B,U,V,G,rt,K,lt,Tt,ct,pt,Rt,Z,St,Ct;for(B=1;B<T;B++)u[B-1]=u[B];u[T-1]=0;let Xt=0,Zt=0,ge=Number.EPSILON;for(G=0;G<T;G++){for(Zt=Math.max(Zt,Math.abs(c[G])+Math.abs(u[G])),rt=G;rt<T&&!(Math.abs(u[rt])<=ge*Zt);)rt++;if(rt>G)do{for(l=c[G],K=(c[G+1]-l)/(2*u[G]),lt=rn(K,1),K<0&&(lt=-lt),c[G]=u[G]/(K+lt),c[G+1]=u[G]*(K+lt),Tt=c[G+1],m=l-c[G],B=G+2;B<T;B++)c[B]-=m;for(Xt=Xt+m,K=c[rt],ct=1,pt=ct,Rt=ct,Z=u[G+1],St=0,Ct=0,B=rt-1;B>=G;B--)for(Rt=pt,pt=ct,Ct=St,l=ct*u[B],m=ct*K,lt=rn(K,u[B]),u[B+1]=St*lt,St=u[B]/lt,ct=K/lt,K=ct*c[B]-St*l,c[B+1]=m+St*(ct*l+St*c[B]),V=0;V<T;V++)m=i.get(V,B+1),i.set(V,B+1,St*i.get(V,B)+ct*m),i.set(V,B,ct*i.get(V,B)-St*m);K=-St*Ct*Rt*Z*u[G]/Tt,u[G]=St*K,c[G]=ct*K}while(Math.abs(u[G])>ge*Zt);c[G]=c[G]+Xt,u[G]=0}for(B=0;B<T-1;B++){for(V=B,K=c[B],U=B+1;U<T;U++)c[U]<K&&(V=U,K=c[U]);if(V!==B)for(c[V]=c[B],c[B]=K,U=0;U<T;U++)K=i.get(U,B),i.set(U,B,i.get(U,V)),i.set(U,V,K)}}function yn(T,u,c,i){let l=0,m=T-1,B,U,V,G,rt,K,lt;for(K=l+1;K<=m-1;K++){for(lt=0,G=K;G<=m;G++)lt=lt+Math.abs(u.get(G,K-1));if(lt!==0){for(V=0,G=m;G>=K;G--)c[G]=u.get(G,K-1)/lt,V+=c[G]*c[G];for(U=Math.sqrt(V),c[K]>0&&(U=-U),V=V-c[K]*U,c[K]=c[K]-U,rt=K;rt<T;rt++){for(B=0,G=m;G>=K;G--)B+=c[G]*u.get(G,rt);for(B=B/V,G=K;G<=m;G++)u.set(G,rt,u.get(G,rt)-B*c[G])}for(G=0;G<=m;G++){for(B=0,rt=m;rt>=K;rt--)B+=c[rt]*u.get(G,rt);for(B=B/V,rt=K;rt<=m;rt++)u.set(G,rt,u.get(G,rt)-B*c[rt])}c[K]=lt*c[K],u.set(K,K-1,lt*U)}}for(G=0;G<T;G++)for(rt=0;rt<T;rt++)i.set(G,rt,G===rt?1:0);for(K=m-1;K>=l+1;K--)if(u.get(K,K-1)!==0){for(G=K+1;G<=m;G++)c[G]=u.get(G,K-1);for(rt=K;rt<=m;rt++){for(U=0,G=K;G<=m;G++)U+=c[G]*i.get(G,rt);for(U=U/c[K]/u.get(K,K-1),G=K;G<=m;G++)i.set(G,rt,i.get(G,rt)+U*c[G])}}}function yr(T,u,c,i,l){let m=T-1,B=0,U=T-1,V=Number.EPSILON,G=0,rt=0,K=0,lt=0,Tt=0,ct=0,pt=0,Rt=0,Z,St,Ct,Xt,Zt,ge,Ut,Yt,ce,tt,wt,Lt,Mt,we,ae;for(Z=0;Z<T;Z++)for((Z<B||Z>U)&&(c[Z]=l.get(Z,Z),u[Z]=0),St=Math.max(Z-1,0);St<T;St++)rt=rt+Math.abs(l.get(Z,St));for(;m>=B;){for(Xt=m;Xt>B&&(ct=Math.abs(l.get(Xt-1,Xt-1))+Math.abs(l.get(Xt,Xt)),ct===0&&(ct=rt),!(Math.abs(l.get(Xt,Xt-1))<V*ct));)Xt--;if(Xt===m)l.set(m,m,l.get(m,m)+G),c[m]=l.get(m,m),u[m]=0,m--,Rt=0;else if(Xt===m-1){if(Ut=l.get(m,m-1)*l.get(m-1,m),K=(l.get(m-1,m-1)-l.get(m,m))/2,lt=K*K+Ut,pt=Math.sqrt(Math.abs(lt)),l.set(m,m,l.get(m,m)+G),l.set(m-1,m-1,l.get(m-1,m-1)+G),Yt=l.get(m,m),lt>=0){for(pt=K>=0?K+pt:K-pt,c[m-1]=Yt+pt,c[m]=c[m-1],pt!==0&&(c[m]=Yt-Ut/pt),u[m-1]=0,u[m]=0,Yt=l.get(m,m-1),ct=Math.abs(Yt)+Math.abs(pt),K=Yt/ct,lt=pt/ct,Tt=Math.sqrt(K*K+lt*lt),K=K/Tt,lt=lt/Tt,St=m-1;St<T;St++)pt=l.get(m-1,St),l.set(m-1,St,lt*pt+K*l.get(m,St)),l.set(m,St,lt*l.get(m,St)-K*pt);for(Z=0;Z<=m;Z++)pt=l.get(Z,m-1),l.set(Z,m-1,lt*pt+K*l.get(Z,m)),l.set(Z,m,lt*l.get(Z,m)-K*pt);for(Z=B;Z<=U;Z++)pt=i.get(Z,m-1),i.set(Z,m-1,lt*pt+K*i.get(Z,m)),i.set(Z,m,lt*i.get(Z,m)-K*pt)}else c[m-1]=Yt+K,c[m]=Yt+K,u[m-1]=pt,u[m]=-pt;m=m-2,Rt=0}else{if(Yt=l.get(m,m),ce=0,Ut=0,Xt<m&&(ce=l.get(m-1,m-1),Ut=l.get(m,m-1)*l.get(m-1,m)),Rt===10){for(G+=Yt,Z=B;Z<=m;Z++)l.set(Z,Z,l.get(Z,Z)-Yt);ct=Math.abs(l.get(m,m-1))+Math.abs(l.get(m-1,m-2)),Yt=ce=.75*ct,Ut=-.4375*ct*ct}if(Rt===30&&(ct=(ce-Yt)/2,ct=ct*ct+Ut,ct>0)){for(ct=Math.sqrt(ct),ce<Yt&&(ct=-ct),ct=Yt-Ut/((ce-Yt)/2+ct),Z=B;Z<=m;Z++)l.set(Z,Z,l.get(Z,Z)-ct);G+=ct,Yt=ce=Ut=.964}for(Rt=Rt+1,Zt=m-2;Zt>=Xt&&(pt=l.get(Zt,Zt),Tt=Yt-pt,ct=ce-pt,K=(Tt*ct-Ut)/l.get(Zt+1,Zt)+l.get(Zt,Zt+1),lt=l.get(Zt+1,Zt+1)-pt-Tt-ct,Tt=l.get(Zt+2,Zt+1),ct=Math.abs(K)+Math.abs(lt)+Math.abs(Tt),K=K/ct,lt=lt/ct,Tt=Tt/ct,!(Zt===Xt||Math.abs(l.get(Zt,Zt-1))*(Math.abs(lt)+Math.abs(Tt))<V*(Math.abs(K)*(Math.abs(l.get(Zt-1,Zt-1))+Math.abs(pt)+Math.abs(l.get(Zt+1,Zt+1))))));)Zt--;for(Z=Zt+2;Z<=m;Z++)l.set(Z,Z-2,0),Z>Zt+2&&l.set(Z,Z-3,0);for(Ct=Zt;Ct<=m-1&&(we=Ct!==m-1,Ct!==Zt&&(K=l.get(Ct,Ct-1),lt=l.get(Ct+1,Ct-1),Tt=we?l.get(Ct+2,Ct-1):0,Yt=Math.abs(K)+Math.abs(lt)+Math.abs(Tt),Yt!==0&&(K=K/Yt,lt=lt/Yt,Tt=Tt/Yt)),Yt!==0);Ct++)if(ct=Math.sqrt(K*K+lt*lt+Tt*Tt),K<0&&(ct=-ct),ct!==0){for(Ct!==Zt?l.set(Ct,Ct-1,-ct*Yt):Xt!==Zt&&l.set(Ct,Ct-1,-l.get(Ct,Ct-1)),K=K+ct,Yt=K/ct,ce=lt/ct,pt=Tt/ct,lt=lt/K,Tt=Tt/K,St=Ct;St<T;St++)K=l.get(Ct,St)+lt*l.get(Ct+1,St),we&&(K=K+Tt*l.get(Ct+2,St),l.set(Ct+2,St,l.get(Ct+2,St)-K*pt)),l.set(Ct,St,l.get(Ct,St)-K*Yt),l.set(Ct+1,St,l.get(Ct+1,St)-K*ce);for(Z=0;Z<=Math.min(m,Ct+3);Z++)K=Yt*l.get(Z,Ct)+ce*l.get(Z,Ct+1),we&&(K=K+pt*l.get(Z,Ct+2),l.set(Z,Ct+2,l.get(Z,Ct+2)-K*Tt)),l.set(Z,Ct,l.get(Z,Ct)-K),l.set(Z,Ct+1,l.get(Z,Ct+1)-K*lt);for(Z=B;Z<=U;Z++)K=Yt*i.get(Z,Ct)+ce*i.get(Z,Ct+1),we&&(K=K+pt*i.get(Z,Ct+2),i.set(Z,Ct+2,i.get(Z,Ct+2)-K*Tt)),i.set(Z,Ct,i.get(Z,Ct)-K),i.set(Z,Ct+1,i.get(Z,Ct+1)-K*lt)}}}if(rt!==0){for(m=T-1;m>=0;m--)if(K=c[m],lt=u[m],lt===0)for(Xt=m,l.set(m,m,1),Z=m-1;Z>=0;Z--){for(Ut=l.get(Z,Z)-K,Tt=0,St=Xt;St<=m;St++)Tt=Tt+l.get(Z,St)*l.get(St,m);if(u[Z]<0)pt=Ut,ct=Tt;else if(Xt=Z,u[Z]===0?l.set(Z,m,Ut!==0?-Tt/Ut:-Tt/(V*rt)):(Yt=l.get(Z,Z+1),ce=l.get(Z+1,Z),lt=(c[Z]-K)*(c[Z]-K)+u[Z]*u[Z],ge=(Yt*ct-pt*Tt)/lt,l.set(Z,m,ge),l.set(Z+1,m,Math.abs(Yt)>Math.abs(pt)?(-Tt-Ut*ge)/Yt:(-ct-ce*ge)/pt)),ge=Math.abs(l.get(Z,m)),V*ge*ge>1)for(St=Z;St<=m;St++)l.set(St,m,l.get(St,m)/ge)}else if(lt<0)for(Xt=m-1,Math.abs(l.get(m,m-1))>Math.abs(l.get(m-1,m))?(l.set(m-1,m-1,lt/l.get(m,m-1)),l.set(m-1,m,-(l.get(m,m)-K)/l.get(m,m-1))):(ae=On(0,-l.get(m-1,m),l.get(m-1,m-1)-K,lt),l.set(m-1,m-1,ae[0]),l.set(m-1,m,ae[1])),l.set(m,m-1,0),l.set(m,m,1),Z=m-2;Z>=0;Z--){for(tt=0,wt=0,St=Xt;St<=m;St++)tt=tt+l.get(Z,St)*l.get(St,m-1),wt=wt+l.get(Z,St)*l.get(St,m);if(Ut=l.get(Z,Z)-K,u[Z]<0)pt=Ut,Tt=tt,ct=wt;else if(Xt=Z,u[Z]===0?(ae=On(-tt,-wt,Ut,lt),l.set(Z,m-1,ae[0]),l.set(Z,m,ae[1])):(Yt=l.get(Z,Z+1),ce=l.get(Z+1,Z),Lt=(c[Z]-K)*(c[Z]-K)+u[Z]*u[Z]-lt*lt,Mt=(c[Z]-K)*2*lt,Lt===0&&Mt===0&&(Lt=V*rt*(Math.abs(Ut)+Math.abs(lt)+Math.abs(Yt)+Math.abs(ce)+Math.abs(pt))),ae=On(Yt*Tt-pt*tt+lt*wt,Yt*ct-pt*wt-lt*tt,Lt,Mt),l.set(Z,m-1,ae[0]),l.set(Z,m,ae[1]),Math.abs(Yt)>Math.abs(pt)+Math.abs(lt)?(l.set(Z+1,m-1,(-tt-Ut*l.get(Z,m-1)+lt*l.get(Z,m))/Yt),l.set(Z+1,m,(-wt-Ut*l.get(Z,m)-lt*l.get(Z,m-1))/Yt)):(ae=On(-Tt-ce*l.get(Z,m-1),-ct-ce*l.get(Z,m),pt,lt),l.set(Z+1,m-1,ae[0]),l.set(Z+1,m,ae[1]))),ge=Math.max(Math.abs(l.get(Z,m-1)),Math.abs(l.get(Z,m))),V*ge*ge>1)for(St=Z;St<=m;St++)l.set(St,m-1,l.get(St,m-1)/ge),l.set(St,m,l.get(St,m)/ge)}for(Z=0;Z<T;Z++)if(Z<B||Z>U)for(St=Z;St<T;St++)i.set(Z,St,l.get(Z,St));for(St=T-1;St>=B;St--)for(Z=B;Z<=U;Z++){for(pt=0,Ct=B;Ct<=Math.min(St,U);Ct++)pt=pt+i.get(Z,Ct)*l.get(Ct,St);i.set(Z,St,pt)}}}function On(T,u,c,i){let l,m;return Math.abs(c)>Math.abs(i)?(l=i/c,m=c+l*i,[(T+l*u)/m,(u-l*T)/m]):(l=c/i,m=i+l*c,[(l*T+u)/m,(l*u-T)/m])}class Wn{constructor(u){if(u=Ae.checkMatrix(u),!u.isSymmetric())throw new Error("Matrix is not symmetric");let c=u,i=c.rows,l=new It(i,i),m=!0,B,U,V;for(U=0;U<i;U++){let G=0;for(V=0;V<U;V++){let rt=0;for(B=0;B<V;B++)rt+=l.get(V,B)*l.get(U,B);rt=(c.get(U,V)-rt)/l.get(V,V),l.set(U,V,rt),G=G+rt*rt}for(G=c.get(U,U)-G,m&&(m=G>0),l.set(U,U,Math.sqrt(Math.max(G,0))),V=U+1;V<i;V++)l.set(U,V,0)}this.L=l,this.positiveDefinite=m}isPositiveDefinite(){return this.positiveDefinite}solve(u){u=Ae.checkMatrix(u);let c=this.L,i=c.rows;if(u.rows!==i)throw new Error("Matrix dimensions do not match");if(this.isPositiveDefinite()===!1)throw new Error("Matrix is not positive definite");let l=u.columns,m=u.clone(),B,U,V;for(V=0;V<i;V++)for(U=0;U<l;U++){for(B=0;B<V;B++)m.set(V,U,m.get(V,U)-m.get(B,U)*c.get(V,B));m.set(V,U,m.get(V,U)/c.get(V,V))}for(V=i-1;V>=0;V--)for(U=0;U<l;U++){for(B=V+1;B<i;B++)m.set(V,U,m.get(V,U)-m.get(B,U)*c.get(B,V));m.set(V,U,m.get(V,U)/c.get(V,V))}return m}get lowerTriangularMatrix(){return this.L}}class wr{constructor(u,c={}){u=Ae.checkMatrix(u);let{Y:i}=c;const{scaleScores:l=!1,maxIterations:m=1e3,terminationCriteria:B=1e-10}=c;let U;if(i){if(ot.isAnyArray(i)&&typeof i[0]=="number"?i=It.columnVector(i):i=Ae.checkMatrix(i),i.rows!==u.rows)throw new Error("Y should have the same number of rows as X");U=i.getColumnVector(0)}else U=u.getColumnVector(0);let V=1,G,rt,K,lt;for(let Tt=0;Tt<m&&V>B;Tt++)K=u.transpose().mmul(U).div(U.transpose().mmul(U).get(0,0)),K=K.div(K.norm()),G=u.mmul(K).div(K.transpose().mmul(K).get(0,0)),Tt>0&&(V=G.clone().sub(lt).pow(2).sum()),lt=G.clone(),i?(rt=i.transpose().mmul(G).div(G.transpose().mmul(G).get(0,0)),rt=rt.div(rt.norm()),U=i.mmul(rt).div(rt.transpose().mmul(rt).get(0,0))):U=G;if(i){let Tt=u.transpose().mmul(G).div(G.transpose().mmul(G).get(0,0));Tt=Tt.div(Tt.norm());let ct=u.clone().sub(G.clone().mmul(Tt.transpose())),pt=U.transpose().mmul(G).div(G.transpose().mmul(G).get(0,0)),Rt=i.clone().sub(G.clone().mulS(pt.get(0,0)).mmul(rt.transpose()));this.t=G,this.p=Tt.transpose(),this.w=K.transpose(),this.q=rt,this.u=U,this.s=G.transpose().mmul(G),this.xResidual=ct,this.yResidual=Rt,this.betas=pt}else 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t=e.nodeFilter||sn,r=e.edgeFilter||sn;this.nodeFilter=t,this.edgeFilter=s=>{const{source:o,target:d}=this.graph.getEdgeDetail(s.id);return!t(o)||!t(d)?!1:r(s,o,d)},e.cache==="auto"?(this.cacheEnabled=!0,this.startAutoCache()):e.cache==="manual"?this.cacheEnabled=!0:this.cacheEnabled=!1}startAutoCache(){this.refreshCache(),this.graph.on("changed",this.handleGraphChanged)}stopAutoCache(){this.graph.off("changed",this.handleGraphChanged)}checkNodeExistence(e){this.getNode(e)}hasNode(e){if(!this.graph.hasNode(e))return!1;const t=this.graph.getNode(e);return this.nodeFilter(t)}areNeighbors(e,t){return this.checkNodeExistence(e),this.getNeighbors(t).some(r=>r.id===e)}getNode(e){const t=this.graph.getNode(e);if(!this.nodeFilter(t))throw new Error("Node not found for id: "+e);return t}getRelatedEdges(e,t){return this.checkNodeExistence(e),this.cacheEnabled?t==="in"?this.inEdgesMap.get(e):t==="out"?this.outEdgesMap.get(e):this.bothEdgesMap.get(e):this.graph.getRelatedEdges(e,t).filter(this.edgeFilter)}getDegree(e,t){return this.getRelatedEdges(e,t).length}getSuccessors(e){const r=this.getRelatedEdges(e,"out").map(s=>this.getNode(s.target));return Array.from(new Set(r))}getPredecessors(e){const r=this.getRelatedEdges(e,"in").map(s=>this.getNode(s.source));return Array.from(new Set(r))}getNeighbors(e){const t=this.getPredecessors(e),r=this.getSuccessors(e);return Array.from(new Set([...t,...r]))}hasEdge(e){if(!this.graph.hasEdge(e))return!1;const t=this.graph.getEdge(e);return this.edgeFilter(t)}getEdge(e){const t=this.graph.getEdge(e);if(!this.edgeFilter(t))throw new Error("Edge not found for id: "+e);return t}getEdgeDetail(e){const t=this.getEdge(e);return{edge:t,source:this.getNode(t.source),target:this.getNode(t.target)}}hasTreeStructure(e){return 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h&&(o=!0),!h}else if(d.type==="EdgeDataUpdated"||d.type==="EdgeUpdated")return d.id!==s.value.id;return!0}),o||r.push(s);break}case"NodeDataUpdated":case"EdgeDataUpdated":case"EdgeUpdated":{const o=r.findIndex(h=>h.type===s.type&&h.id===s.id&&(s.propertyName===void 0||h.propertyName===s.propertyName)),d=r[o];d?s.propertyName!==void 0?d.newValue=s.newValue:(r.splice(o,1),r.push(s)):r.push(s);break}case"TreeStructureDetached":{r=r.filter(o=>o.type==="TreeStructureAttached"||o.type==="TreeStructureChanged"?o.treeKey!==s.treeKey:!0),r.push(s);break}case"TreeStructureChanged":{const o=r.find(d=>d.type==="TreeStructureChanged"&&d.treeKey===s.treeKey&&d.nodeId===s.nodeId);o?o.newParentId=s.newParentId:r.push(s);break}default:r.push(s);break}}),r}checkNodeExistence(t){this.getNode(t)}hasNode(t){return this.nodeMap.has(t)}areNeighbors(t,r){return this.getNeighbors(r).some(s=>s.id===t)}getNode(t){const r=this.nodeMap.get(t);if(!r)throw new Error("Node not found for id: "+t);return r}getRelatedEdges(t,r){if(this.checkNodeExistence(t),r==="in"){const s=this.inEdgesMap.get(t);return Array.from(s)}else if(r==="out"){const s=this.outEdgesMap.get(t);return Array.from(s)}else{const s=this.bothEdgesMap.get(t);return Array.from(s)}}getDegree(t,r){return this.getRelatedEdges(t,r).length}getSuccessors(t){const s=this.getRelatedEdges(t,"out").map(o=>this.getNode(o.target));return Array.from(new Set(s))}getPredecessors(t){const s=this.getRelatedEdges(t,"in").map(o=>this.getNode(o.source));return Array.from(new Set(s))}getNeighbors(t){const r=this.getPredecessors(t),s=this.getSuccessors(t);return Array.from(new Set([...r,...s]))}doAddNode(t){if(this.hasNode(t.id))throw new Error("Node already exists: "+t.id);this.nodeMap.set(t.id,t),this.inEdgesMap.set(t.id,new Set),this.outEdgesMap.set(t.id,new Set),this.bothEdgesMap.set(t.id,new Set),this.treeIndices.forEach(r=>{r.childrenMap.set(t.id,new Set)}),this.changes.push({type:"NodeAdded",value:t})}addNodes(t){this.batch(()=>{for(const r of t)this.doAddNode(r)})}addNode(t){this.addNodes([t])}doRemoveNode(t){const r=this.getNode(t),s=this.bothEdgesMap.get(t);s==null||s.forEach(o=>this.doRemoveEdge(o.id)),this.nodeMap.delete(t),this.treeIndices.forEach(o=>{var h,p;(h=o.childrenMap.get(t))==null||h.forEach(g=>{o.parentMap.delete(g.id)});const d=o.parentMap.get(t);d&&((p=o.childrenMap.get(d.id))==null||p.delete(r)),o.parentMap.delete(t),o.childrenMap.delete(t)}),this.bothEdgesMap.delete(t),this.inEdgesMap.delete(t),this.outEdgesMap.delete(t),this.changes.push({type:"NodeRemoved",value:r})}removeNodes(t){this.batch(()=>{t.forEach(r=>this.doRemoveNode(r))})}removeNode(t){this.removeNodes([t])}updateNodeDataProperty(t,r,s){const o=this.getNode(t);this.batch(()=>{const 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ie=(W-bt)/C,de=($-Bt)/C,Jt=(X-Qt)/C;if($t&&(r[F].x-=$t*ie,r[F].y-=$t*de,r[F].z-=$t*Jt),Pt===0){const Te=zt(q);if(!Te)return;r[F].x-=Te*ie,r[F].y-=Te*de,r[F].z-=Te*Jt;return}if(Et===0||jt===0){const Te=Gt(q,h,p);if(!Te)return;r[F].x-=Te*ie,r[F].y-=Te*de,r[F].z-=Te*Jt;return}const oe=Kt(q);if(!oe)return;r[F].x-=oe*ie,r[F].y-=oe*de,r[F].z-=oe*Jt}})}updateVelocity(e,t,r,s){const{damping:o,maxSpeed:d,interval:h,dimensions:p}=s,g=e.getAllNodes();g!=null&&g.length&&g.forEach(y=>{const{id:O}=y;let L=(r[O].x+t[O].x*h)*o||.01,R=(r[O].y+t[O].y*h)*o||.01,k=p===3?(r[O].z+t[O].z*h)*o||.01:0;const F=Math.sqrt(L*L+R*R+k*k);if(F>d){const z=d/F;L=z*L,R=z*R,k=z*k}r[O]={x:L,y:R,z:k}})}updatePosition(e,t,r,s){const{distanceThresholdMode:o,interval:d,dimensions:h}=s,p=t.getAllNodes();if(!(p!=null&&p.length)){this.judgingDistance=0;return}let 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ea={gForce:!0,force2:!0,d3force:!0,fruchterman:!0,forceAtlas2:!0,force:!0,"graphin-force":!0},na={center:[0,0],comboPadding:10,treeKey:"combo"};class ra{constructor(e={}){this.options=e,this.id="comboCombined",this.options=Object.assign(Object.assign({},na),e)}execute(e,t){return A(this,void 0,void 0,function*(){return this.genericComboCombinedLayout(!1,e,t)})}assign(e,t){return A(this,void 0,void 0,function*(){yield this.genericComboCombinedLayout(!0,e,t)})}genericComboCombinedLayout(e,t,r){return A(this,void 0,void 0,function*(){const s=this.initVals(Object.assign(Object.assign({},this.options),r)),{center:o,treeKey:d,outerLayout:h}=s,p=t.getAllNodes().filter(J=>!J.data._isCombo),g=t.getAllNodes().filter(J=>J.data._isCombo),y=t.getAllEdges(),O=p==null?void 0:p.length;if(!O||O===1)return Tn(t,e,o);const L=[],R=new Map;p.forEach(J=>{R.set(J.id,J)});const k=new Map;g.forEach(J=>{k.set(J.id,J)});const F=new Map,z=this.getInnerGraphs(t,d,R,k,y,s,F);yield Promise.all(z);const C=new 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Et=Object.assign({center:o,kg:5,preventOverlap:!0,animate:!1},mt.id==="force"?{gravity:1,factor:4,linkDistance:(jt,Pt,Dt)=>{const Gt=Math.max(...Pt.data.size)||32,zt=Math.max(...Dt.data.size)||32;return Gt/2+zt/2+200}}:{});st=yield Is(mt,J,Et)}F.forEach(J=>{var mt;const Et=st.nodes.find(Dt=>Dt.id===J.id);if(Et){const{x:Dt,y:Gt}=Et.data;J.data.visited=!0,J.data.x=Dt,J.data.y=Gt,L.push({id:J.id,data:{x:Dt,y:Gt}})}const{x:jt,y:Pt}=J.data;(mt=J.data.nodes)===null||mt===void 0||mt.forEach(Dt=>{L.push({id:Dt.id,data:{x:Dt.data.x+jt,y:Dt.data.y+Pt}})})}),F.forEach(({data:J})=>{const{x:mt,y:Et,visited:jt,nodes:Pt}=J;Pt==null||Pt.forEach(Dt=>{if(!jt){const Gt=L.find(zt=>zt.id===Dt.id);Gt.data.x+=mt||0,Gt.data.y+=Et||0}})})}return e&&L.forEach(J=>{t.mergeNodeData(J.id,{x:J.data.x,y:J.data.y})}),{nodes:L,edges:y}})}initVals(e){const t=Object.assign({},e),{nodeSize:r,spacing:s,comboPadding:o}=e;let d,h;if(_t(s)?h=()=>s:fn(s)?h=s:h=()=>0,t.spacing=h,!r)d=g=>{const y=h(g);return 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Ws{constructor(){super(...arguments),this.id="d3-force-3d",this.config={inputNodeAttrs:["x","y","z","vx","vy","vz","fx","fy","fz"],outputNodeAttrs:["x","y","z","vx","vy","vz"],simulationAttrs:["alpha","alphaMin","alphaDecay","alphaTarget","velocityDecay","randomSource","numDimensions"]},this.forceMap={link:Ga,manyBody:lu,center:du,collide:gu,radial:pu,x:vu,y:mu,z:yu},this.options={numDimensions:3,link:{id:e=>e.id},manyBody:{},center:{x:0,y:0,z:0}}}initSimulation(){return fu()}}var Hs=me(92546),xu=me.n(Hs);class or{constructor(e){this.id="dagre",this.options={},Object.assign(this.options,or.defaultOptions,e)}execute(e,t){return A(this,void 0,void 0,function*(){return this.genericDagreLayout(!1,e,Object.assign(Object.assign({},this.options),t))})}assign(e,t){return A(this,void 0,void 0,function*(){yield this.genericDagreLayout(!0,e,Object.assign(Object.assign({},this.options),t))})}genericDagreLayout(e,t,r){return A(this,void 0,void 0,function*(){const{nodeSize:s}=r,o=new Hs.graphlib.Graph;o.setGraph(r),o.setDefaultEdgeLabel(()=>({}));const d=t.getAllNodes(),h=t.getAllEdges();[...d,...h].some(({id:g})=>_t(g))&&console.error("Dagre layout only support string id, it will convert number to string."),t.getAllNodes().forEach(g=>{const{id:y}=g,O=Object.assign({},g.data);if(s!==void 0){const[L,R]=Yn(fn(s)?s(g):s);Object.assign(O,{width:L,height:R})}o.setNode(y.toString(),O)}),t.getAllEdges().forEach(({id:g,source:y,target:O})=>{o.setEdge(y.toString(),O.toString(),{id:g})}),xu().layout(o);const p={nodes:[],edges:[]};return o.nodes().forEach(g=>{const y=o.node(g);p.nodes.push({id:g,data:y}),e&&t.mergeNodeData(g,y)}),o.edges().forEach(g=>{const y=o.edge(g),{id:O}=y,L=f(y,["id"]),{v:R,w:k}=g;p.edges.push({id:O,source:R,target:k,data:L}),e&&t.mergeEdgeData(O,L)}),p})}}or.defaultOptions={};class $r{constructor(e){this.id=e.id||0,this.rx=e.rx,this.ry=e.ry,this.fx=0,this.fy=0,this.mass=e.mass,this.degree=e.degree,this.g=e.g||0}distanceTo(e){const t=this.rx-e.rx,r=this.ry-e.ry;return Math.hypot(t,r)}setPos(e,t){this.rx=e,this.ry=t}resetForce(){this.fx=0,this.fy=0}addForce(e){const t=e.rx-this.rx,r=e.ry-this.ry;let s=Math.hypot(t,r);s=s<1e-4?1e-4:s;const o=this.g*(this.degree+1)*(e.degree+1)/s;this.fx+=o*t/s,this.fy+=o*r/s}in(e){return e.contains(this.rx,this.ry)}add(e){const t=this.mass+e.mass,r=(this.rx*this.mass+e.rx*e.mass)/t,s=(this.ry*this.mass+e.ry*e.mass)/t,o=this.degree+e.degree,d={rx:r,ry:s,mass:t,degree:o};return new $r(d)}}class zn{constructor(e){this.xmid=e.xmid,this.ymid=e.ymid,this.length=e.length,this.massCenter=e.massCenter||[0,0],this.mass=e.mass||1}getLength(){return this.length}contains(e,t){const r=this.length/2;return e<=this.xmid+r&&e>=this.xmid-r&&t<=this.ymid+r&&t>=this.ymid-r}NW(){const e=this.xmid-this.length/4,t=this.ymid+this.length/4,r=this.length/2,s={xmid:e,ymid:t,length:r};return new zn(s)}NE(){const e=this.xmid+this.length/4,t=this.ymid+this.length/4,r=this.length/2,s={xmid:e,ymid:t,length:r};return new zn(s)}SW(){const e=this.xmid-this.length/4,t=this.ymid-this.length/4,r=this.length/2,s={xmid:e,ymid:t,length:r};return new zn(s)}SE(){const e=this.xmid+this.length/4,t=this.ymid-this.length/4,r=this.length/2,s={xmid:e,ymid:t,length:r};return new zn(s)}}class Fn{constructor(e){this.body=null,this.quad=null,this.NW=null,this.NE=null,this.SW=null,this.SE=null,this.theta=.5,e!=null&&(this.quad=e)}insert(e){if(this.body==null){this.body=e;return}this._isExternal()?(this.quad&&(this.NW=new Fn(this.quad.NW()),this.NE=new Fn(this.quad.NE()),this.SW=new Fn(this.quad.SW()),this.SE=new Fn(this.quad.SE())),this._putBody(this.body),this._putBody(e),this.body=this.body.add(e)):(this.body=this.body.add(e),this._putBody(e))}_putBody(e){this.quad&&(e.in(this.quad.NW())&&this.NW?this.NW.insert(e):e.in(this.quad.NE())&&this.NE?this.NE.insert(e):e.in(this.quad.SW())&&this.SW?this.SW.insert(e):e.in(this.quad.SE())&&this.SE&&this.SE.insert(e))}_isExternal(){return this.NW==null&&this.NE==null&&this.SW==null&&this.SE==null}updateForce(e){if(!(this.body==null||e===this.body))if(this._isExternal())e.addForce(this.body);else{const t=this.quad?this.quad.getLength():0,r=this.body.distanceTo(e);t/r<this.theta?e.addForce(this.body):(this.NW&&this.NW.updateForce(e),this.NE&&this.NE.updateForce(e),this.SW&&this.SW.updateForce(e),this.SE&&this.SE.updateForce(e))}}}const Eu={center:[0,0],width:300,height:300,kr:5,kg:1,mode:"normal",preventOverlap:!1,dissuadeHubs:!1,maxIteration:0,ks:.1,ksmax:10,tao:.1};class bu{constructor(e={}){this.options=e,this.id="forceAtlas2",this.options=Object.assign(Object.assign({},Eu),e)}execute(e,t){return A(this,void 0,void 0,function*(){return this.genericForceAtlas2Layout(!1,e,t)})}assign(e,t){return A(this,void 0,void 0,function*(){yield this.genericForceAtlas2Layout(!0,e,t)})}genericForceAtlas2Layout(e,t,r){return A(this,void 0,void 0,function*(){const s=t.getAllEdges(),o=t.getAllNodes(),d=this.formatOptions(r,o.length),{width:h,height:p,prune:g,maxIteration:y,nodeSize:O,center:L}=d;if(!(o!=null&&o.length)||o.length===1)return Tn(t,e,L);const R=o.map(C=>Ke(C,[h,p])),k=s.filter(C=>{const{source:W,target:$}=C;return W!==$}),F=new vt({nodes:R,edges:k}),z=this.getSizes(F,O);if(this.run(F,t,y,z,e,d),g){for(let W=0;W<k.length;W+=1){const{source:$,target:X}=k[W],q=F.getDegree($),st=F.getDegree($);if(q<=1){const ut=F.getNode(X);F.mergeNodeData($,{x:ut.data.x,y:ut.data.y})}else if(st<=1){const ut=F.getNode($);F.mergeNodeData(X,{x:ut.data.x,y:ut.data.y})}}const C=Object.assign(Object.assign({},d),{prune:!1,barnesHut:!1});this.run(F,t,100,z,e,C)}return{nodes:R,edges:s}})}getSizes(e,t){const r=e.getAllNodes(),s={};for(let o=0;o<r.length;o+=1){const d=r[o];s[d.id]=jr(t,void 0)(d)}return s}formatOptions(e={},t){const r=Object.assign(Object.assign({},this.options),e),{center:s,width:o,height:d,barnesHut:h,prune:p,maxIteration:g,kr:y,kg:O}=r;return r.width=!o&&typeof window!="undefined"?window.innerWidth:o,r.height=!d&&typeof window!="undefined"?window.innerHeight:d,r.center=s||[r.width/2,r.height/2],h===void 0&&t>250&&(r.barnesHut=!0),p===void 0&&t>100&&(r.prune=!0),g===0&&!p?(r.maxIteration=250,t<=200&&t>100?r.maxIteration=1e3:t>200&&(r.maxIteration=1200)):g===0&&p&&(r.maxIteration=100,t<=200&&t>100?r.maxIteration=500:t>200&&(r.maxIteration=950)),y||(r.kr=50,t>100&&t<=500?r.kr=20:t>500&&(r.kr=1)),O||(r.kg=20,t>100&&t<=500?r.kg=10:t>500&&(r.kg=1)),r}run(e,t,r,s,o,d){const{kr:h,barnesHut:p,onTick:g}=d,y=e.getAllNodes();let O=0,L=r;const R={},k={},F={};for(let z=0;z<y.length;z+=1){const{data:C,id:W}=y[z];if(R[W]=[0,0],p){const $={id:z,rx:C.x,ry:C.y,mass:1,g:h,degree:e.getDegree(W)};F[W]=new $r($)}}for(;L>0;)O=this.oneStep(e,{iter:L,preventOverlapIters:50,krPrime:100,sg:O,forces:R,preForces:k,bodies:F,sizes:s},d),L--,g==null||g({nodes:y,edges:t.getAllEdges()});return e}oneStep(e,t,r){const{iter:s,preventOverlapIters:o,krPrime:d,sg:h,preForces:p,bodies:g,sizes:y}=t;let{forces:O}=t;const{preventOverlap:L,barnesHut:R}=r,k=e.getAllNodes();for(let F=0;F<k.length;F+=1){const{id:z}=k[F];p[z]=[...O[z]],O[z]=[0,0]}return O=this.getAttrForces(e,s,o,y,O,r),R&&(L&&s>o||!L)?O=this.getOptRepGraForces(e,O,g,r):O=this.getRepGraForces(e,s,o,O,d,y,r),this.updatePos(e,O,p,h,r)}getAttrForces(e,t,r,s,o,d){const{preventOverlap:h,dissuadeHubs:p,mode:g,prune:y}=d,O=e.getAllEdges();for(let L=0;L<O.length;L+=1){const{source:R,target:k}=O[L],F=e.getNode(R),z=e.getNode(k),C=e.getDegree(R),W=e.getDegree(k);if(y&&(C<=1||W<=1))continue;const $=[z.data.x-F.data.x,z.data.y-F.data.y];let X=Math.hypot($[0],$[1]);X=X<1e-4?1e-4:X,$[0]=$[0]/X,$[1]=$[1]/X,h&&t<r&&(X=X-s[R]-s[k]);let q=X,st=q;g==="linlog"&&(q=Math.log(1+X),st=q),p&&(q=X/C,st=X/W),h&&t<r&&X<=0?(q=0,st=0):h&&t<r&&X>0&&(q=X,st=X),o[R][0]+=q*$[0],o[k][0]-=st*$[0],o[R][1]+=q*$[1],o[k][1]-=st*$[1]}return o}getOptRepGraForces(e,t,r,s){const{kg:o,center:d,prune:h}=s,p=e.getAllNodes(),g=p.length;let y=9e10,O=-9e10,L=9e10,R=-9e10;for(let W=0;W<g;W+=1){const{id:$,data:X}=p[W];h&&e.getDegree($)<=1||(r[$].setPos(X.x,X.y),X.x>=O&&(O=X.x),X.x<=y&&(y=X.x),X.y>=R&&(R=X.y),X.y<=L&&(L=X.y))}const k=Math.max(O-y,R-L),F={xmid:(O+y)/2,ymid:(R+L)/2,length:k,massCenter:d,mass:g},z=new zn(F),C=new Fn(z);for(let W=0;W<g;W+=1){const{id:$}=p[W];h&&e.getDegree($)<=1||r[$].in(z)&&C.insert(r[$])}for(let W=0;W<g;W+=1){const{id:$,data:X}=p[W],q=e.getDegree($);if(h&&q<=1)continue;r[$].resetForce(),C.updateForce(r[$]),t[$][0]-=r[$].fx,t[$][1]-=r[$].fy;const st=[X.x-d[0],X.y-d[1]];let ut=Math.hypot(st[0],st[1]);ut=ut<1e-4?1e-4:ut,st[0]=st[0]/ut,st[1]=st[1]/ut;const J=o*(q+1);t[$][0]-=J*st[0],t[$][1]-=J*st[1]}return t}getRepGraForces(e,t,r,s,o,d,h){const{preventOverlap:p,kr:g,kg:y,center:O,prune:L}=h,R=e.getAllNodes(),k=R.length;for(let F=0;F<k;F+=1){const z=R[F],C=e.getDegree(z.id);for(let q=F+1;q<k;q+=1){const st=R[q],ut=e.getDegree(st.id);if(L&&(C<=1||ut<=1))continue;const J=[st.data.x-z.data.x,st.data.y-z.data.y];let mt=Math.hypot(J[0],J[1]);mt=mt<1e-4?1e-4:mt,J[0]=J[0]/mt,J[1]=J[1]/mt,p&&t<r&&(mt=mt-d[z.id]-d[st.id]);let Et=g*(C+1)*(ut+1)/mt;p&&t<r&&mt<0?Et=o*(C+1)*(ut+1):p&&t<r&&mt===0?Et=0:p&&t<r&&mt>0&&(Et=g*(C+1)*(ut+1)/mt),s[z.id][0]-=Et*J[0],s[st.id][0]+=Et*J[0],s[z.id][1]-=Et*J[1],s[st.id][1]+=Et*J[1]}const W=[z.data.x-O[0],z.data.y-O[1]],$=Math.hypot(W[0],W[1]);W[0]=W[0]/$,W[1]=W[1]/$;const X=y*(C+1);s[z.id][0]-=X*W[0],s[z.id][1]-=X*W[1]}return s}updatePos(e,t,r,s,o){const{ks:d,tao:h,prune:p,ksmax:g}=o,y=e.getAllNodes(),O=y.length,L=[],R=[];let k=0,F=0,z=s;for(let W=0;W<O;W+=1){const{id:$}=y[W],X=e.getDegree($);if(p&&X<=1)continue;const q=[t[$][0]-r[$][0],t[$][1]-r[$][1]],st=Math.hypot(q[0],q[1]),ut=[t[$][0]+r[$][0],t[$][1]+r[$][1]],J=Math.hypot(ut[0],ut[1]);L[W]=st,R[W]=J/2,k+=(X+1)*L[W],F+=(X+1)*R[W]}const C=z;z=h*F/k,C!==0&&(z=z>1.5*C?1.5*C:z);for(let W=0;W<O;W+=1){const{id:$,data:X}=y[W],q=e.getDegree($);if(p&&q<=1||_t(X.fx)&&_t(X.fy))continue;let st=d*z/(1+z*Math.sqrt(L[W])),ut=Math.hypot(t[$][0],t[$][1]);ut=ut<1e-4?1e-4:ut;const J=g/ut;st=st>J?J:st;const mt=st*t[$][0],Et=st*t[$][1];e.mergeNodeData($,{x:X.x+mt,y:X.y+Et})}return z}}const Nu={maxIteration:1e3,gravity:10,speed:5,clustering:!1,clusterGravity:10,width:300,height:300,nodeClusterBy:"cluster"},Mu=800;class Su{constructor(e={}){this.options=e,this.id="fruchterman",this.timeInterval=0,this.running=!1,this.options=Object.assign(Object.assign({},Nu),e)}execute(e,t){return A(this,void 0,void 0,function*(){return this.genericFruchtermanLayout(!1,e,t)})}assign(e,t){return A(this,void 0,void 0,function*(){yield this.genericFruchtermanLayout(!0,e,t)})}stop(){this.timeInterval&&typeof window!="undefined"&&window.clearInterval(this.timeInterval),this.running=!1}tick(e=this.options.maxIteration||1){if(this.lastResult)return this.lastResult;for(let r=0;r<e;r++)this.runOneStep(this.lastGraph,this.lastClusterMap,this.lastOptions);const t={nodes:this.lastLayoutNodes,edges:this.lastLayoutEdges};return this.lastAssign&&t.nodes.forEach(r=>this.lastGraph.mergeNodeData(r.id,{x:r.data.x,y:r.data.y,z:this.options.dimensions===3?r.data.z:void 0})),t}genericFruchtermanLayout(e,t,r){return A(this,void 0,void 0,function*(){if(this.running)return;const s=this.formatOptions(r),{dimensions:o,width:d,height:h,center:p,clustering:g,nodeClusterBy:y,maxIteration:O,onTick:L}=s,R=t.getAllNodes(),k=t.getAllEdges();if(!(R!=null&&R.length)){const $={nodes:[],edges:k};return this.lastResult=$,$}if(R.length===1){e&&t.mergeNodeData(R[0].id,{x:p[0],y:p[1],z:o===3?p[2]:void 0});const $={nodes:[Object.assign(Object.assign({},R[0]),{data:Object.assign(Object.assign({},R[0].data),{x:p[0],y:p[1],z:o===3?p[2]:void 0})})],edges:k};return this.lastResult=$,$}const F=R.map($=>Ke($,[d,h])),z=new vt({nodes:F,edges:k}),C={};if(g&&F.forEach($=>{const X=$.data[y];C[X]||(C[X]={name:X,cx:0,cy:0,count:0})}),this.lastLayoutNodes=F,this.lastLayoutEdges=k,this.lastAssign=e,this.lastGraph=z,this.lastOptions=s,this.lastClusterMap=C,typeof window=="undefined")return;let W=0;return new Promise($=>{this.timeInterval=window.setInterval(()=>{if(!this.running){$({nodes:F,edges:k});return}this.runOneStep(z,C,s),e&&F.forEach(({id:X,data:q})=>t.mergeNodeData(X,{x:q.x,y:q.y,z:o===3?q.z:void 0})),L==null||L({nodes:F,edges:k}),W++,W>=O&&(window.clearInterval(this.timeInterval),$({nodes:F,edges:k}))},0),this.running=!0})})}formatOptions(e={}){const 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diff --git a/4525.98b69bfb.async.js b/9122.ce5a422c.async.js
similarity index 97%
rename from 4525.98b69bfb.async.js
rename to 9122.ce5a422c.async.js
index 0f17c2effe..ec3f4a80a6 100644
--- a/4525.98b69bfb.async.js
+++ b/9122.ce5a422c.async.js
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i=t[0]*n[1]-t[1]*n[0],a=t[0]*n[2]-t[2]*n[0],s=t[0]*n[3]-t[3]*n[0],o=t[1]*n[2]-t[2]*n[1],l=t[1]*n[3]-t[3]*n[1],c=t[2]*n[3]-t[3]*n[2],h=e[0],p=e[1],C=e[2],k=e[3];return r[0]=p*c-C*l+k*o,r[1]=-(h*c)+C*s-k*a,r[2]=h*l-p*s+k*i,r[3]=-(h*o)+p*a-C*i,r}function Ee(r,e,t,n){var i=e[0],a=e[1],s=e[2],o=e[3];return r[0]=i+n*(t[0]-i),r[1]=a+n*(t[1]-a),r[2]=s+n*(t[2]-s),r[3]=o+n*(t[3]-o),r}function E(r,e){e=e||1;var t,n,i,a,s,o;do t=glMatrix.RANDOM()*2-1,n=glMatrix.RANDOM()*2-1,s=t*t+n*n;while(s>=1);do i=glMatrix.RANDOM()*2-1,a=glMatrix.RANDOM()*2-1,o=i*i+a*a;while(o>=1);var l=Math.sqrt((1-s)/o);return r[0]=e*t,r[1]=e*n,r[2]=e*i*l,r[3]=e*a*l,r}function B(r,e,t){var n=e[0],i=e[1],a=e[2],s=e[3];return r[0]=t[0]*n+t[4]*i+t[8]*a+t[12]*s,r[1]=t[1]*n+t[5]*i+t[9]*a+t[13]*s,r[2]=t[2]*n+t[6]*i+t[10]*a+t[14]*s,r[3]=t[3]*n+t[7]*i+t[11]*a+t[15]*s,r}function N(r,e,t){var n=e[0],i=e[1],a=e[2],s=t[0],o=t[1],l=t[2],c=t[3],h=c*n+o*a-l*i,p=c*i+l*n-s*a,C=c*a+s*i-o*n,k=-s*n-o*i-l*a;return r[0]=h*c+k*-s+p*-l-C*-o,r[1]=p*c+k*-o+C*-s-h*-l,r[2]=C*c+k*-l+h*-o-p*-s,r[3]=e[3],r}function V(r){return r[0]=0,r[1]=0,r[2]=0,r[3]=0,r}function q(r){return"vec4("+r[0]+", "+r[1]+", "+r[2]+", "+r[3]+")"}function ue(r,e){return r[0]===e[0]&&r[1]===e[1]&&r[2]===e[2]&&r[3]===e[3]}function ce(r,e){var t=r[0],n=r[1],i=r[2],a=r[3],s=e[0],o=e[1],l=e[2],c=e[3];return Math.abs(t-s)<=v*Math.max(1,Math.abs(t),Math.abs(s))&&Math.abs(n-o)<=v*Math.max(1,Math.abs(n),Math.abs(o))&&Math.abs(i-l)<=v*Math.max(1,Math.abs(i),Math.abs(l))&&Math.abs(a-c)<=v*Math.max(1,Math.abs(a),Math.abs(c))}var Oe=null,Se=null,Ue=null,je=null,it=null,at=null,et=null,st=function(){var r=Ye();return function(e,t,n,i,a,s){var o,l;for(t||(t=4),n||(n=0),i?l=Math.min(i*t+n,e.length):l=e.length,o=n;o<l;o+=t)r[0]=e[o],r[1]=e[o+1],r[2]=e[o+2],r[3]=e[o+3],a(r,r,s),e[o]=r[0],e[o+1]=r[1],e[o+2]=r[2],e[o+3]=r[3];return e}}();function Je(){var r=new M(16);return M!=Float32Array&&(r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[6]=0,r[7]=0,r[8]=0,r[9]=0,r[11]=0,r[12]=0,r[13]=0,r[14]=0),r[0]=1,r[5]=1,r[10]=1,r[15]=1,r}function ke(r){var e=new M(16);return e[0]=r[0],e[1]=r[1],e[2]=r[2],e[3]=r[3],e[4]=r[4],e[5]=r[5],e[6]=r[6],e[7]=r[7],e[8]=r[8],e[9]=r[9],e[10]=r[10],e[11]=r[11],e[12]=r[12],e[13]=r[13],e[14]=r[14],e[15]=r[15],e}function ft(r,e){return r[0]=e[0],r[1]=e[1],r[2]=e[2],r[3]=e[3],r[4]=e[4],r[5]=e[5],r[6]=e[6],r[7]=e[7],r[8]=e[8],r[9]=e[9],r[10]=e[10],r[11]=e[11],r[12]=e[12],r[13]=e[13],r[14]=e[14],r[15]=e[15],r}function yt(r,e,t,n,i,a,s,o,l,c,h,p,C,k,W,j){var K=new M(16);return K[0]=r,K[1]=e,K[2]=t,K[3]=n,K[4]=i,K[5]=a,K[6]=s,K[7]=o,K[8]=l,K[9]=c,K[10]=h,K[11]=p,K[12]=C,K[13]=k,K[14]=W,K[15]=j,K}function Pt(r,e,t,n,i,a,s,o,l,c,h,p,C,k,W,j,K){return r[0]=e,r[1]=t,r[2]=n,r[3]=i,r[4]=a,r[5]=s,r[6]=o,r[7]=l,r[8]=c,r[9]=h,r[10]=p,r[11]=C,r[12]=k,r[13]=W,r[14]=j,r[15]=K,r}function Ut(r){return r[0]=1,r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=1,r[6]=0,r[7]=0,r[8]=0,r[9]=0,r[10]=1,r[11]=0,r[12]=0,r[13]=0,r[14]=0,r[15]=1,r}function Qt(r,e){if(r===e){var t=e[1],n=e[2],i=e[3],a=e[6],s=e[7],o=e[11];r[1]=e[4],r[2]=e[8],r[3]=e[12],r[4]=t,r[6]=e[9],r[7]=e[13],r[8]=n,r[9]=a,r[11]=e[14],r[12]=i,r[13]=s,r[14]=o}else r[0]=e[0],r[1]=e[4],r[2]=e[8],r[3]=e[12],r[4]=e[1],r[5]=e[5],r[6]=e[9],r[7]=e[13],r[8]=e[2],r[9]=e[6],r[10]=e[10],r[11]=e[14],r[12]=e[3],r[13]=e[7],r[14]=e[11],r[15]=e[15];return r}function Ct(r,e){var t=e[0],n=e[1],i=e[2],a=e[3],s=e[4],o=e[5],l=e[6],c=e[7],h=e[8],p=e[9],C=e[10],k=e[11],W=e[12],j=e[13],K=e[14],Q=e[15],ee=t*o-n*s,re=t*l-i*s,ve=t*c-a*s,he=n*l-i*o,pe=n*c-a*o,ye=i*c-a*l,_e=h*j-p*W,De=h*K-C*W,Be=h*Q-k*W,ze=p*K-C*j,Xe=p*Q-k*j,$e=C*Q-k*K,ct=ee*$e-re*Xe+ve*ze+he*Be-pe*De+ye*_e;return ct?(ct=1/ct,r[0]=(o*$e-l*Xe+c*ze)*ct,r[1]=(i*Xe-n*$e-a*ze)*ct,r[2]=(j*ye-K*pe+Q*he)*ct,r[3]=(C*pe-p*ye-k*he)*ct,r[4]=(l*Be-s*$e-c*De)*ct,r[5]=(t*$e-i*Be+a*De)*ct,r[6]=(K*ve-W*ye-Q*re)*ct,r[7]=(h*ye-C*ve+k*re)*ct,r[8]=(s*Xe-o*Be+c*_e)*ct,r[9]=(n*Be-t*Xe-a*_e)*ct,r[10]=(W*pe-j*ve+Q*ee)*ct,r[11]=(p*ve-h*pe-k*ee)*ct,r[12]=(o*De-s*ze-l*_e)*ct,r[13]=(t*ze-n*De+i*_e)*ct,r[14]=(j*re-W*he-K*ee)*ct,r[15]=(h*he-p*re+C*ee)*ct,r):null}function It(r,e){var t=e[0],n=e[1],i=e[2],a=e[3],s=e[4],o=e[5],l=e[6],c=e[7],h=e[8],p=e[9],C=e[10],k=e[11],W=e[12],j=e[13],K=e[14],Q=e[15];return r[0]=o*(C*Q-k*K)-p*(l*Q-c*K)+j*(l*k-c*C),r[1]=-(n*(C*Q-k*K)-p*(i*Q-a*K)+j*(i*k-a*C)),r[2]=n*(l*Q-c*K)-o*(i*Q-a*K)+j*(i*c-a*l),r[3]=-(n*(l*k-c*C)-o*(i*k-a*C)+p*(i*c-a*l)),r[4]=-(s*(C*Q-k*K)-h*(l*Q-c*K)+W*(l*k-c*C)),r[5]=t*(C*Q-k*K)-h*(i*Q-a*K)+W*(i*k-a*C),r[6]=-(t*(l*Q-c*K)-s*(i*Q-a*K)+W*(i*c-a*l)),r[7]=t*(l*k-c*C)-s*(i*k-a*C)+h*(i*c-a*l),r[8]=s*(p*Q-k*j)-h*(o*Q-c*j)+W*(o*k-c*p),r[9]=-(t*(p*Q-k*j)-h*(n*Q-a*j)+W*(n*k-a*p)),r[10]=t*(o*Q-c*j)-s*(n*Q-a*j)+W*(n*c-a*o),r[11]=-(t*(o*k-c*p)-s*(n*k-a*p)+h*(n*c-a*o)),r[12]=-(s*(p*K-C*j)-h*(o*K-l*j)+W*(o*C-l*p)),r[13]=t*(p*K-C*j)-h*(n*K-i*j)+W*(n*C-i*p),r[14]=-(t*(o*K-l*j)-s*(n*K-i*j)+W*(n*l-i*o)),r[15]=t*(o*C-l*p)-s*(n*C-i*p)+h*(n*l-i*o),r}function Zt(r){var e=r[0],t=r[1],n=r[2],i=r[3],a=r[4],s=r[5],o=r[6],l=r[7],c=r[8],h=r[9],p=r[10],C=r[11],k=r[12],W=r[13],j=r[14],K=r[15],Q=e*s-t*a,ee=e*o-n*a,re=e*l-i*a,ve=t*o-n*s,he=t*l-i*s,pe=n*l-i*o,ye=c*W-h*k,_e=c*j-p*k,De=c*K-C*k,Be=h*j-p*W,ze=h*K-C*W,Xe=p*K-C*j;return Q*Xe-ee*ze+re*Be+ve*De-he*_e+pe*ye}function lt(r,e,t){var n=e[0],i=e[1],a=e[2],s=e[3],o=e[4],l=e[5],c=e[6],h=e[7],p=e[8],C=e[9],k=e[10],W=e[11],j=e[12],K=e[13],Q=e[14],ee=e[15],re=t[0],ve=t[1],he=t[2],pe=t[3];return r[0]=re*n+ve*o+he*p+pe*j,r[1]=re*i+ve*l+he*C+pe*K,r[2]=re*a+ve*c+he*k+pe*Q,r[3]=re*s+ve*h+he*W+pe*ee,re=t[4],ve=t[5],he=t[6],pe=t[7],r[4]=re*n+ve*o+he*p+pe*j,r[5]=re*i+ve*l+he*C+pe*K,r[6]=re*a+ve*c+he*k+pe*Q,r[7]=re*s+ve*h+he*W+pe*ee,re=t[8],ve=t[9],he=t[10],pe=t[11],r[8]=re*n+ve*o+he*p+pe*j,r[9]=re*i+ve*l+he*C+pe*K,r[10]=re*a+ve*c+he*k+pe*Q,r[11]=re*s+ve*h+he*W+pe*ee,re=t[12],ve=t[13],he=t[14],pe=t[15],r[12]=re*n+ve*o+he*p+pe*j,r[13]=re*i+ve*l+he*C+pe*K,r[14]=re*a+ve*c+he*k+pe*Q,r[15]=re*s+ve*h+he*W+pe*ee,r}function Mt(r,e,t){var n=t[0],i=t[1],a=t[2],s,o,l,c,h,p,C,k,W,j,K,Q;return e===r?(r[12]=e[0]*n+e[4]*i+e[8]*a+e[12],r[13]=e[1]*n+e[5]*i+e[9]*a+e[13],r[14]=e[2]*n+e[6]*i+e[10]*a+e[14],r[15]=e[3]*n+e[7]*i+e[11]*a+e[15]):(s=e[0],o=e[1],l=e[2],c=e[3],h=e[4],p=e[5],C=e[6],k=e[7],W=e[8],j=e[9],K=e[10],Q=e[11],r[0]=s,r[1]=o,r[2]=l,r[3]=c,r[4]=h,r[5]=p,r[6]=C,r[7]=k,r[8]=W,r[9]=j,r[10]=K,r[11]=Q,r[12]=s*n+h*i+W*a+e[12],r[13]=o*n+p*i+j*a+e[13],r[14]=l*n+C*i+K*a+e[14],r[15]=c*n+k*i+Q*a+e[15]),r}function Lt(r,e,t){var n=t[0],i=t[1],a=t[2];return r[0]=e[0]*n,r[1]=e[1]*n,r[2]=e[2]*n,r[3]=e[3]*n,r[4]=e[4]*i,r[5]=e[5]*i,r[6]=e[6]*i,r[7]=e[7]*i,r[8]=e[8]*a,r[9]=e[9]*a,r[10]=e[10]*a,r[11]=e[11]*a,r[12]=e[12],r[13]=e[13],r[14]=e[14],r[15]=e[15],r}function Nt(r,e,t,n){var i=n[0],a=n[1],s=n[2],o=Math.hypot(i,a,s),l,c,h,p,C,k,W,j,K,Q,ee,re,ve,he,pe,ye,_e,De,Be,ze,Xe,$e,ct,ut;return o<v?null:(o=1/o,i*=o,a*=o,s*=o,l=Math.sin(t),c=Math.cos(t),h=1-c,p=e[0],C=e[1],k=e[2],W=e[3],j=e[4],K=e[5],Q=e[6],ee=e[7],re=e[8],ve=e[9],he=e[10],pe=e[11],ye=i*i*h+c,_e=a*i*h+s*l,De=s*i*h-a*l,Be=i*a*h-s*l,ze=a*a*h+c,Xe=s*a*h+i*l,$e=i*s*h+a*l,ct=a*s*h-i*l,ut=s*s*h+c,r[0]=p*ye+j*_e+re*De,r[1]=C*ye+K*_e+ve*De,r[2]=k*ye+Q*_e+he*De,r[3]=W*ye+ee*_e+pe*De,r[4]=p*Be+j*ze+re*Xe,r[5]=C*Be+K*ze+ve*Xe,r[6]=k*Be+Q*ze+he*Xe,r[7]=W*Be+ee*ze+pe*Xe,r[8]=p*$e+j*ct+re*ut,r[9]=C*$e+K*ct+ve*ut,r[10]=k*$e+Q*ct+he*ut,r[11]=W*$e+ee*ct+pe*ut,e!==r&&(r[12]=e[12],r[13]=e[13],r[14]=e[14],r[15]=e[15]),r)}function Vt(r,e,t){var n=Math.sin(t),i=Math.cos(t),a=e[4],s=e[5],o=e[6],l=e[7],c=e[8],h=e[9],p=e[10],C=e[11];return e!==r&&(r[0]=e[0],r[1]=e[1],r[2]=e[2],r[3]=e[3],r[12]=e[12],r[13]=e[13],r[14]=e[14],r[15]=e[15]),r[4]=a*i+c*n,r[5]=s*i+h*n,r[6]=o*i+p*n,r[7]=l*i+C*n,r[8]=c*i-a*n,r[9]=h*i-s*n,r[10]=p*i-o*n,r[11]=C*i-l*n,r}function Kt(r,e,t){var n=Math.sin(t),i=Math.cos(t),a=e[0],s=e[1],o=e[2],l=e[3],c=e[8],h=e[9],p=e[10],C=e[11];return e!==r&&(r[4]=e[4],r[5]=e[5],r[6]=e[6],r[7]=e[7],r[12]=e[12],r[13]=e[13],r[14]=e[14],r[15]=e[15]),r[0]=a*i-c*n,r[1]=s*i-h*n,r[2]=o*i-p*n,r[3]=l*i-C*n,r[8]=a*n+c*i,r[9]=s*n+h*i,r[10]=o*n+p*i,r[11]=l*n+C*i,r}function qt(r,e,t){var n=Math.sin(t),i=Math.cos(t),a=e[0],s=e[1],o=e[2],l=e[3],c=e[4],h=e[5],p=e[6],C=e[7];return e!==r&&(r[8]=e[8],r[9]=e[9],r[10]=e[10],r[11]=e[11],r[12]=e[12],r[13]=e[13],r[14]=e[14],r[15]=e[15]),r[0]=a*i+c*n,r[1]=s*i+h*n,r[2]=o*i+p*n,r[3]=l*i+C*n,r[4]=c*i-a*n,r[5]=h*i-s*n,r[6]=p*i-o*n,r[7]=C*i-l*n,r}function ln(r,e){return r[0]=1,r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=1,r[6]=0,r[7]=0,r[8]=0,r[9]=0,r[10]=1,r[11]=0,r[12]=e[0],r[13]=e[1],r[14]=e[2],r[15]=1,r}function pn(r,e){return r[0]=e[0],r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=e[1],r[6]=0,r[7]=0,r[8]=0,r[9]=0,r[10]=e[2],r[11]=0,r[12]=0,r[13]=0,r[14]=0,r[15]=1,r}function mn(r,e,t){var n=t[0],i=t[1],a=t[2],s=Math.hypot(n,i,a),o,l,c;return s<v?null:(s=1/s,n*=s,i*=s,a*=s,o=Math.sin(e),l=Math.cos(e),c=1-l,r[0]=n*n*c+l,r[1]=i*n*c+a*o,r[2]=a*n*c-i*o,r[3]=0,r[4]=n*i*c-a*o,r[5]=i*i*c+l,r[6]=a*i*c+n*o,r[7]=0,r[8]=n*a*c+i*o,r[9]=i*a*c-n*o,r[10]=a*a*c+l,r[11]=0,r[12]=0,r[13]=0,r[14]=0,r[15]=1,r)}function yn(r,e){var t=Math.sin(e),n=Math.cos(e);return r[0]=1,r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=n,r[6]=t,r[7]=0,r[8]=0,r[9]=-t,r[10]=n,r[11]=0,r[12]=0,r[13]=0,r[14]=0,r[15]=1,r}function Zn(r,e){var t=Math.sin(e),n=Math.cos(e);return r[0]=n,r[1]=0,r[2]=-t,r[3]=0,r[4]=0,r[5]=1,r[6]=0,r[7]=0,r[8]=t,r[9]=0,r[10]=n,r[11]=0,r[12]=0,r[13]=0,r[14]=0,r[15]=1,r}function Nn(r,e){var t=Math.sin(e),n=Math.cos(e);return r[0]=n,r[1]=t,r[2]=0,r[3]=0,r[4]=-t,r[5]=n,r[6]=0,r[7]=0,r[8]=0,r[9]=0,r[10]=1,r[11]=0,r[12]=0,r[13]=0,r[14]=0,r[15]=1,r}function nn(r,e,t){var n=e[0],i=e[1],a=e[2],s=e[3],o=n+n,l=i+i,c=a+a,h=n*o,p=n*l,C=n*c,k=i*l,W=i*c,j=a*c,K=s*o,Q=s*l,ee=s*c;return r[0]=1-(k+j),r[1]=p+ee,r[2]=C-Q,r[3]=0,r[4]=p-ee,r[5]=1-(h+j),r[6]=W+K,r[7]=0,r[8]=C+Q,r[9]=W-K,r[10]=1-(h+k),r[11]=0,r[12]=t[0],r[13]=t[1],r[14]=t[2],r[15]=1,r}function Ln(r,e){var t=new M(3),n=-e[0],i=-e[1],a=-e[2],s=e[3],o=e[4],l=e[5],c=e[6],h=e[7],p=n*n+i*i+a*a+s*s;return p>0?(t[0]=(o*s+h*n+l*a-c*i)*2/p,t[1]=(l*s+h*i+c*n-o*a)*2/p,t[2]=(c*s+h*a+o*i-l*n)*2/p):(t[0]=(o*s+h*n+l*a-c*i)*2,t[1]=(l*s+h*i+c*n-o*a)*2,t[2]=(c*s+h*a+o*i-l*n)*2),nn(r,e,t),r}function Bn(r,e){return r[0]=e[12],r[1]=e[13],r[2]=e[14],r}function lr(r,e){var t=e[0],n=e[1],i=e[2],a=e[4],s=e[5],o=e[6],l=e[8],c=e[9],h=e[10];return r[0]=Math.hypot(t,n,i),r[1]=Math.hypot(a,s,o),r[2]=Math.hypot(l,c,h),r}function qn(r,e){var t=new M(3);lr(t,e);var n=1/t[0],i=1/t[1],a=1/t[2],s=e[0]*n,o=e[1]*i,l=e[2]*a,c=e[4]*n,h=e[5]*i,p=e[6]*a,C=e[8]*n,k=e[9]*i,W=e[10]*a,j=s+h+W,K=0;return j>0?(K=Math.sqrt(j+1)*2,r[3]=.25*K,r[0]=(p-k)/K,r[1]=(C-l)/K,r[2]=(o-c)/K):s>h&&s>W?(K=Math.sqrt(1+s-h-W)*2,r[3]=(p-k)/K,r[0]=.25*K,r[1]=(o+c)/K,r[2]=(C+l)/K):h>W?(K=Math.sqrt(1+h-s-W)*2,r[3]=(C-l)/K,r[0]=(o+c)/K,r[1]=.25*K,r[2]=(p+k)/K):(K=Math.sqrt(1+W-s-h)*2,r[3]=(o-c)/K,r[0]=(C+l)/K,r[1]=(p+k)/K,r[2]=.25*K),r}function Hr(r,e,t,n){var i=e[0],a=e[1],s=e[2],o=e[3],l=i+i,c=a+a,h=s+s,p=i*l,C=i*c,k=i*h,W=a*c,j=a*h,K=s*h,Q=o*l,ee=o*c,re=o*h,ve=n[0],he=n[1],pe=n[2];return r[0]=(1-(W+K))*ve,r[1]=(C+re)*ve,r[2]=(k-ee)*ve,r[3]=0,r[4]=(C-re)*he,r[5]=(1-(p+K))*he,r[6]=(j+Q)*he,r[7]=0,r[8]=(k+ee)*pe,r[9]=(j-Q)*pe,r[10]=(1-(p+W))*pe,r[11]=0,r[12]=t[0],r[13]=t[1],r[14]=t[2],r[15]=1,r}function hi(r,e,t,n,i){var a=e[0],s=e[1],o=e[2],l=e[3],c=a+a,h=s+s,p=o+o,C=a*c,k=a*h,W=a*p,j=s*h,K=s*p,Q=o*p,ee=l*c,re=l*h,ve=l*p,he=n[0],pe=n[1],ye=n[2],_e=i[0],De=i[1],Be=i[2],ze=(1-(j+Q))*he,Xe=(k+ve)*he,$e=(W-re)*he,ct=(k-ve)*pe,ut=(1-(C+Q))*pe,St=(K+ee)*pe,bt=(W+re)*ye,Et=(K-ee)*ye,xt=(1-(C+j))*ye;return r[0]=ze,r[1]=Xe,r[2]=$e,r[3]=0,r[4]=ct,r[5]=ut,r[6]=St,r[7]=0,r[8]=bt,r[9]=Et,r[10]=xt,r[11]=0,r[12]=t[0]+_e-(ze*_e+ct*De+bt*Be),r[13]=t[1]+De-(Xe*_e+ut*De+Et*Be),r[14]=t[2]+Be-($e*_e+St*De+xt*Be),r[15]=1,r}function cr(r,e){var t=e[0],n=e[1],i=e[2],a=e[3],s=t+t,o=n+n,l=i+i,c=t*s,h=n*s,p=n*o,C=i*s,k=i*o,W=i*l,j=a*s,K=a*o,Q=a*l;return r[0]=1-p-W,r[1]=h+Q,r[2]=C-K,r[3]=0,r[4]=h-Q,r[5]=1-c-W,r[6]=k+j,r[7]=0,r[8]=C+K,r[9]=k-j,r[10]=1-c-p,r[11]=0,r[12]=0,r[13]=0,r[14]=0,r[15]=1,r}function fi(r,e,t,n,i,a,s){var o=1/(t-e),l=1/(i-n),c=1/(a-s);return r[0]=a*2*o,r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=a*2*l,r[6]=0,r[7]=0,r[8]=(t+e)*o,r[9]=(i+n)*l,r[10]=(s+a)*c,r[11]=-1,r[12]=0,r[13]=0,r[14]=s*a*2*c,r[15]=0,r}function Hi(r,e,t,n,i){var a=1/Math.tan(e/2),s;return r[0]=a/t,r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=a,r[6]=0,r[7]=0,r[8]=0,r[9]=0,r[11]=-1,r[12]=0,r[13]=0,r[15]=0,i!=null&&i!==1/0?(s=1/(n-i),r[10]=(i+n)*s,r[14]=2*i*n*s):(r[10]=-1,r[14]=-2*n),r}var Kn=Hi;function Dn(r,e,t,n,i){var a=1/Math.tan(e/2),s;return r[0]=a/t,r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=a,r[6]=0,r[7]=0,r[8]=0,r[9]=0,r[11]=-1,r[12]=0,r[13]=0,r[15]=0,i!=null&&i!==1/0?(s=1/(n-i),r[10]=i*s,r[14]=i*n*s):(r[10]=-1,r[14]=-n),r}function Qn(r,e,t,n){var i=Math.tan(e.upDegrees*Math.PI/180),a=Math.tan(e.downDegrees*Math.PI/180),s=Math.tan(e.leftDegrees*Math.PI/180),o=Math.tan(e.rightDegrees*Math.PI/180),l=2/(s+o),c=2/(i+a);return r[0]=l,r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=c,r[6]=0,r[7]=0,r[8]=-((s-o)*l*.5),r[9]=(i-a)*c*.5,r[10]=n/(t-n),r[11]=-1,r[12]=0,r[13]=0,r[14]=n*t/(t-n),r[15]=0,r}function ur(r,e,t,n,i,a,s){var o=1/(e-t),l=1/(n-i),c=1/(a-s);return r[0]=-2*o,r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=-2*l,r[6]=0,r[7]=0,r[8]=0,r[9]=0,r[10]=2*c,r[11]=0,r[12]=(e+t)*o,r[13]=(i+n)*l,r[14]=(s+a)*c,r[15]=1,r}var fr=ur;function yr(r,e,t,n,i,a,s){var o=1/(e-t),l=1/(n-i),c=1/(a-s);return r[0]=-2*o,r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=-2*l,r[6]=0,r[7]=0,r[8]=0,r[9]=0,r[10]=c,r[11]=0,r[12]=(e+t)*o,r[13]=(i+n)*l,r[14]=a*c,r[15]=1,r}function er(r,e,t,n){var i,a,s,o,l,c,h,p,C,k,W=e[0],j=e[1],K=e[2],Q=n[0],ee=n[1],re=n[2],ve=t[0],he=t[1],pe=t[2];return Math.abs(W-ve)<v&&Math.abs(j-he)<v&&Math.abs(K-pe)<v?Ut(r):(h=W-ve,p=j-he,C=K-pe,k=1/Math.hypot(h,p,C),h*=k,p*=k,C*=k,i=ee*C-re*p,a=re*h-Q*C,s=Q*p-ee*h,k=Math.hypot(i,a,s),k?(k=1/k,i*=k,a*=k,s*=k):(i=0,a=0,s=0),o=p*s-C*a,l=C*i-h*s,c=h*a-p*i,k=Math.hypot(o,l,c),k?(k=1/k,o*=k,l*=k,c*=k):(o=0,l=0,c=0),r[0]=i,r[1]=o,r[2]=h,r[3]=0,r[4]=a,r[5]=l,r[6]=p,r[7]=0,r[8]=s,r[9]=c,r[10]=C,r[11]=0,r[12]=-(i*W+a*j+s*K),r[13]=-(o*W+l*j+c*K),r[14]=-(h*W+p*j+C*K),r[15]=1,r)}function Dr(r,e,t,n){var i=e[0],a=e[1],s=e[2],o=n[0],l=n[1],c=n[2],h=i-t[0],p=a-t[1],C=s-t[2],k=h*h+p*p+C*C;k>0&&(k=1/Math.sqrt(k),h*=k,p*=k,C*=k);var W=l*C-c*p,j=c*h-o*C,K=o*p-l*h;return k=W*W+j*j+K*K,k>0&&(k=1/Math.sqrt(k),W*=k,j*=k,K*=k),r[0]=W,r[1]=j,r[2]=K,r[3]=0,r[4]=p*K-C*j,r[5]=C*W-h*K,r[6]=h*j-p*W,r[7]=0,r[8]=h,r[9]=p,r[10]=C,r[11]=0,r[12]=i,r[13]=a,r[14]=s,r[15]=1,r}function qr(r){return"mat4("+r[0]+", "+r[1]+", "+r[2]+", "+r[3]+", "+r[4]+", "+r[5]+", "+r[6]+", "+r[7]+", "+r[8]+", "+r[9]+", "+r[10]+", "+r[11]+", "+r[12]+", "+r[13]+", "+r[14]+", "+r[15]+")"}function Zr(r){return Math.hypot(r[0],r[1],r[2],r[3],r[4],r[5],r[6],r[7],r[8],r[9],r[10],r[11],r[12],r[13],r[14],r[15])}function _i(r,e,t){return r[0]=e[0]+t[0],r[1]=e[1]+t[1],r[2]=e[2]+t[2],r[3]=e[3]+t[3],r[4]=e[4]+t[4],r[5]=e[5]+t[5],r[6]=e[6]+t[6],r[7]=e[7]+t[7],r[8]=e[8]+t[8],r[9]=e[9]+t[9],r[10]=e[10]+t[10],r[11]=e[11]+t[11],r[12]=e[12]+t[12],r[13]=e[13]+t[13],r[14]=e[14]+t[14],r[15]=e[15]+t[15],r}function _n(r,e,t){return r[0]=e[0]-t[0],r[1]=e[1]-t[1],r[2]=e[2]-t[2],r[3]=e[3]-t[3],r[4]=e[4]-t[4],r[5]=e[5]-t[5],r[6]=e[6]-t[6],r[7]=e[7]-t[7],r[8]=e[8]-t[8],r[9]=e[9]-t[9],r[10]=e[10]-t[10],r[11]=e[11]-t[11],r[12]=e[12]-t[12],r[13]=e[13]-t[13],r[14]=e[14]-t[14],r[15]=e[15]-t[15],r}function fn(r,e,t){return r[0]=e[0]*t,r[1]=e[1]*t,r[2]=e[2]*t,r[3]=e[3]*t,r[4]=e[4]*t,r[5]=e[5]*t,r[6]=e[6]*t,r[7]=e[7]*t,r[8]=e[8]*t,r[9]=e[9]*t,r[10]=e[10]*t,r[11]=e[11]*t,r[12]=e[12]*t,r[13]=e[13]*t,r[14]=e[14]*t,r[15]=e[15]*t,r}function kn(r,e,t,n){return r[0]=e[0]+t[0]*n,r[1]=e[1]+t[1]*n,r[2]=e[2]+t[2]*n,r[3]=e[3]+t[3]*n,r[4]=e[4]+t[4]*n,r[5]=e[5]+t[5]*n,r[6]=e[6]+t[6]*n,r[7]=e[7]+t[7]*n,r[8]=e[8]+t[8]*n,r[9]=e[9]+t[9]*n,r[10]=e[10]+t[10]*n,r[11]=e[11]+t[11]*n,r[12]=e[12]+t[12]*n,r[13]=e[13]+t[13]*n,r[14]=e[14]+t[14]*n,r[15]=e[15]+t[15]*n,r}function Wn(r,e){return r[0]===e[0]&&r[1]===e[1]&&r[2]===e[2]&&r[3]===e[3]&&r[4]===e[4]&&r[5]===e[5]&&r[6]===e[6]&&r[7]===e[7]&&r[8]===e[8]&&r[9]===e[9]&&r[10]===e[10]&&r[11]===e[11]&&r[12]===e[12]&&r[13]===e[13]&&r[14]===e[14]&&r[15]===e[15]}function Mr(r,e){var t=r[0],n=r[1],i=r[2],a=r[3],s=r[4],o=r[5],l=r[6],c=r[7],h=r[8],p=r[9],C=r[10],k=r[11],W=r[12],j=r[13],K=r[14],Q=r[15],ee=e[0],re=e[1],ve=e[2],he=e[3],pe=e[4],ye=e[5],_e=e[6],De=e[7],Be=e[8],ze=e[9],Xe=e[10],$e=e[11],ct=e[12],ut=e[13],St=e[14],bt=e[15];return Math.abs(t-ee)<=v*Math.max(1,Math.abs(t),Math.abs(ee))&&Math.abs(n-re)<=v*Math.max(1,Math.abs(n),Math.abs(re))&&Math.abs(i-ve)<=v*Math.max(1,Math.abs(i),Math.abs(ve))&&Math.abs(a-he)<=v*Math.max(1,Math.abs(a),Math.abs(he))&&Math.abs(s-pe)<=v*Math.max(1,Math.abs(s),Math.abs(pe))&&Math.abs(o-ye)<=v*Math.max(1,Math.abs(o),Math.abs(ye))&&Math.abs(l-_e)<=v*Math.max(1,Math.abs(l),Math.abs(_e))&&Math.abs(c-De)<=v*Math.max(1,Math.abs(c),Math.abs(De))&&Math.abs(h-Be)<=v*Math.max(1,Math.abs(h),Math.abs(Be))&&Math.abs(p-ze)<=v*Math.max(1,Math.abs(p),Math.abs(ze))&&Math.abs(C-Xe)<=v*Math.max(1,Math.abs(C),Math.abs(Xe))&&Math.abs(k-$e)<=v*Math.max(1,Math.abs(k),Math.abs($e))&&Math.abs(W-ct)<=v*Math.max(1,Math.abs(W),Math.abs(ct))&&Math.abs(j-ut)<=v*Math.max(1,Math.abs(j),Math.abs(ut))&&Math.abs(K-St)<=v*Math.max(1,Math.abs(K),Math.abs(St))&&Math.abs(Q-bt)<=v*Math.max(1,Math.abs(Q),Math.abs(bt))}var fa=lt,Si=_n;function Ti(){var r=new M(9);return M!=Float32Array&&(r[1]=0,r[2]=0,r[3]=0,r[5]=0,r[6]=0,r[7]=0),r[0]=1,r[4]=1,r[8]=1,r}function $i(r,e){return r[0]=e[0],r[1]=e[1],r[2]=e[2],r[3]=e[4],r[4]=e[5],r[5]=e[6],r[6]=e[8],r[7]=e[9],r[8]=e[10],r}function ji(r){var e=new glMatrix.ARRAY_TYPE(9);return e[0]=r[0],e[1]=r[1],e[2]=r[2],e[3]=r[3],e[4]=r[4],e[5]=r[5],e[6]=r[6],e[7]=r[7],e[8]=r[8],e}function Gi(r,e){return r[0]=e[0],r[1]=e[1],r[2]=e[2],r[3]=e[3],r[4]=e[4],r[5]=e[5],r[6]=e[6],r[7]=e[7],r[8]=e[8],r}function Fa(r,e,t,n,i,a,s,o,l){var c=new M(9);return c[0]=r,c[1]=e,c[2]=t,c[3]=n,c[4]=i,c[5]=a,c[6]=s,c[7]=o,c[8]=l,c}function ea(r,e,t,n,i,a,s,o,l,c){return r[0]=e,r[1]=t,r[2]=n,r[3]=i,r[4]=a,r[5]=s,r[6]=o,r[7]=l,r[8]=c,r}function $a(r){return r[0]=1,r[1]=0,r[2]=0,r[3]=0,r[4]=1,r[5]=0,r[6]=0,r[7]=0,r[8]=1,r}function io(r,e){if(r===e){var t=e[1],n=e[2],i=e[5];r[1]=e[3],r[2]=e[6],r[3]=t,r[5]=e[7],r[6]=n,r[7]=i}else r[0]=e[0],r[1]=e[3],r[2]=e[6],r[3]=e[1],r[4]=e[4],r[5]=e[7],r[6]=e[2],r[7]=e[5],r[8]=e[8];return r}function Bo(r,e){var t=e[0],n=e[1],i=e[2],a=e[3],s=e[4],o=e[5],l=e[6],c=e[7],h=e[8],p=h*s-o*c,C=-h*a+o*l,k=c*a-s*l,W=t*p+n*C+i*k;return W?(W=1/W,r[0]=p*W,r[1]=(-h*n+i*c)*W,r[2]=(o*n-i*s)*W,r[3]=C*W,r[4]=(h*t-i*l)*W,r[5]=(-o*t+i*a)*W,r[6]=k*W,r[7]=(-c*t+n*l)*W,r[8]=(s*t-n*a)*W,r):null}function Ml(r,e){var t=e[0],n=e[1],i=e[2],a=e[3],s=e[4],o=e[5],l=e[6],c=e[7],h=e[8];return r[0]=s*h-o*c,r[1]=i*c-n*h,r[2]=n*o-i*s,r[3]=o*l-a*h,r[4]=t*h-i*l,r[5]=i*a-t*o,r[6]=a*c-s*l,r[7]=n*l-t*c,r[8]=t*s-n*a,r}function ko(r){var e=r[0],t=r[1],n=r[2],i=r[3],a=r[4],s=r[5],o=r[6],l=r[7],c=r[8];return e*(c*a-s*l)+t*(-c*i+s*o)+n*(l*i-a*o)}function es(r,e,t){var n=e[0],i=e[1],a=e[2],s=e[3],o=e[4],l=e[5],c=e[6],h=e[7],p=e[8],C=t[0],k=t[1],W=t[2],j=t[3],K=t[4],Q=t[5],ee=t[6],re=t[7],ve=t[8];return r[0]=C*n+k*s+W*c,r[1]=C*i+k*o+W*h,r[2]=C*a+k*l+W*p,r[3]=j*n+K*s+Q*c,r[4]=j*i+K*o+Q*h,r[5]=j*a+K*l+Q*p,r[6]=ee*n+re*s+ve*c,r[7]=ee*i+re*o+ve*h,r[8]=ee*a+re*l+ve*p,r}function Sl(r,e,t){var n=e[0],i=e[1],a=e[2],s=e[3],o=e[4],l=e[5],c=e[6],h=e[7],p=e[8],C=t[0],k=t[1];return r[0]=n,r[1]=i,r[2]=a,r[3]=s,r[4]=o,r[5]=l,r[6]=C*n+k*s+c,r[7]=C*i+k*o+h,r[8]=C*a+k*l+p,r}function ts(r,e,t){var n=e[0],i=e[1],a=e[2],s=e[3],o=e[4],l=e[5],c=e[6],h=e[7],p=e[8],C=Math.sin(t),k=Math.cos(t);return r[0]=k*n+C*s,r[1]=k*i+C*o,r[2]=k*a+C*l,r[3]=k*s-C*n,r[4]=k*o-C*i,r[5]=k*l-C*a,r[6]=c,r[7]=h,r[8]=p,r}function Au(r,e,t){var n=t[0],i=t[1];return r[0]=n*e[0],r[1]=n*e[1],r[2]=n*e[2],r[3]=i*e[3],r[4]=i*e[4],r[5]=i*e[5],r[6]=e[6],r[7]=e[7],r[8]=e[8],r}function gc(r,e){return r[0]=1,r[1]=0,r[2]=0,r[3]=0,r[4]=1,r[5]=0,r[6]=e[0],r[7]=e[1],r[8]=1,r}function Tl(r,e){var t=Math.sin(e),n=Math.cos(e);return r[0]=n,r[1]=t,r[2]=0,r[3]=-t,r[4]=n,r[5]=0,r[6]=0,r[7]=0,r[8]=1,r}function zo(r,e){return r[0]=e[0],r[1]=0,r[2]=0,r[3]=0,r[4]=e[1],r[5]=0,r[6]=0,r[7]=0,r[8]=1,r}function pc(r,e){return r[0]=e[0],r[1]=e[1],r[2]=0,r[3]=e[2],r[4]=e[3],r[5]=0,r[6]=e[4],r[7]=e[5],r[8]=1,r}function Cu(r,e){var t=e[0],n=e[1],i=e[2],a=e[3],s=t+t,o=n+n,l=i+i,c=t*s,h=n*s,p=n*o,C=i*s,k=i*o,W=i*l,j=a*s,K=a*o,Q=a*l;return r[0]=1-p-W,r[3]=h-Q,r[6]=C+K,r[1]=h+Q,r[4]=1-c-W,r[7]=k-j,r[2]=C-K,r[5]=k+j,r[8]=1-c-p,r}function mc(r,e){var t=e[0],n=e[1],i=e[2],a=e[3],s=e[4],o=e[5],l=e[6],c=e[7],h=e[8],p=e[9],C=e[10],k=e[11],W=e[12],j=e[13],K=e[14],Q=e[15],ee=t*o-n*s,re=t*l-i*s,ve=t*c-a*s,he=n*l-i*o,pe=n*c-a*o,ye=i*c-a*l,_e=h*j-p*W,De=h*K-C*W,Be=h*Q-k*W,ze=p*K-C*j,Xe=p*Q-k*j,$e=C*Q-k*K,ct=ee*$e-re*Xe+ve*ze+he*Be-pe*De+ye*_e;return ct?(ct=1/ct,r[0]=(o*$e-l*Xe+c*ze)*ct,r[1]=(l*Be-s*$e-c*De)*ct,r[2]=(s*Xe-o*Be+c*_e)*ct,r[3]=(i*Xe-n*$e-a*ze)*ct,r[4]=(t*$e-i*Be+a*De)*ct,r[5]=(n*Be-t*Xe-a*_e)*ct,r[6]=(j*ye-K*pe+Q*he)*ct,r[7]=(K*ve-W*ye-Q*re)*ct,r[8]=(W*pe-j*ve+Q*ee)*ct,r):null}function yc(r,e,t){return r[0]=2/e,r[1]=0,r[2]=0,r[3]=0,r[4]=-2/t,r[5]=0,r[6]=-1,r[7]=1,r[8]=1,r}function Al(r){return"mat3("+r[0]+", "+r[1]+", "+r[2]+", "+r[3]+", "+r[4]+", "+r[5]+", "+r[6]+", "+r[7]+", "+r[8]+")"}function An(r){return Math.hypot(r[0],r[1],r[2],r[3],r[4],r[5],r[6],r[7],r[8])}function Xn(r,e,t){return r[0]=e[0]+t[0],r[1]=e[1]+t[1],r[2]=e[2]+t[2],r[3]=e[3]+t[3],r[4]=e[4]+t[4],r[5]=e[5]+t[5],r[6]=e[6]+t[6],r[7]=e[7]+t[7],r[8]=e[8]+t[8],r}function Fn(r,e,t){return r[0]=e[0]-t[0],r[1]=e[1]-t[1],r[2]=e[2]-t[2],r[3]=e[3]-t[3],r[4]=e[4]-t[4],r[5]=e[5]-t[5],r[6]=e[6]-t[6],r[7]=e[7]-t[7],r[8]=e[8]-t[8],r}function jn(r,e,t){return r[0]=e[0]*t,r[1]=e[1]*t,r[2]=e[2]*t,r[3]=e[3]*t,r[4]=e[4]*t,r[5]=e[5]*t,r[6]=e[6]*t,r[7]=e[7]*t,r[8]=e[8]*t,r}function Ir(r,e,t,n){return r[0]=e[0]+t[0]*n,r[1]=e[1]+t[1]*n,r[2]=e[2]+t[2]*n,r[3]=e[3]+t[3]*n,r[4]=e[4]+t[4]*n,r[5]=e[5]+t[5]*n,r[6]=e[6]+t[6]*n,r[7]=e[7]+t[7]*n,r[8]=e[8]+t[8]*n,r}function zr(r,e){return r[0]===e[0]&&r[1]===e[1]&&r[2]===e[2]&&r[3]===e[3]&&r[4]===e[4]&&r[5]===e[5]&&r[6]===e[6]&&r[7]===e[7]&&r[8]===e[8]}function _s(r,e){var t=r[0],n=r[1],i=r[2],a=r[3],s=r[4],o=r[5],l=r[6],c=r[7],h=r[8],p=e[0],C=e[1],k=e[2],W=e[3],j=e[4],K=e[5],Q=e[6],ee=e[7],re=e[8];return Math.abs(t-p)<=glMatrix.EPSILON*Math.max(1,Math.abs(t),Math.abs(p))&&Math.abs(n-C)<=glMatrix.EPSILON*Math.max(1,Math.abs(n),Math.abs(C))&&Math.abs(i-k)<=glMatrix.EPSILON*Math.max(1,Math.abs(i),Math.abs(k))&&Math.abs(a-W)<=glMatrix.EPSILON*Math.max(1,Math.abs(a),Math.abs(W))&&Math.abs(s-j)<=glMatrix.EPSILON*Math.max(1,Math.abs(s),Math.abs(j))&&Math.abs(o-K)<=glMatrix.EPSILON*Math.max(1,Math.abs(o),Math.abs(K))&&Math.abs(l-Q)<=glMatrix.EPSILON*Math.max(1,Math.abs(l),Math.abs(Q))&&Math.abs(c-ee)<=glMatrix.EPSILON*Math.max(1,Math.abs(c),Math.abs(ee))&&Math.abs(h-re)<=glMatrix.EPSILON*Math.max(1,Math.abs(h),Math.abs(re))}var ns=null,ks=null;function or(){var r=new M(4);return M!=Float32Array&&(r[0]=0,r[1]=0,r[2]=0),r[3]=1,r}function zs(r){return r[0]=0,r[1]=0,r[2]=0,r[3]=1,r}function wa(r,e,t){t=t*.5;var n=Math.sin(t);return r[0]=n*e[0],r[1]=n*e[1],r[2]=n*e[2],r[3]=Math.cos(t),r}function Ou(r,e){var t=Math.acos(e[3])*2,n=Math.sin(t/2);return n>glMatrix.EPSILON?(r[0]=e[0]/n,r[1]=e[1]/n,r[2]=e[2]/n):(r[0]=1,r[1]=0,r[2]=0),t}function Xd(r,e){var t=$n(r,e);return Math.acos(2*t*t-1)}function Vi(r,e,t){var n=e[0],i=e[1],a=e[2],s=e[3],o=t[0],l=t[1],c=t[2],h=t[3];return r[0]=n*h+s*o+i*c-a*l,r[1]=i*h+s*l+a*o-n*c,r[2]=a*h+s*c+n*l-i*o,r[3]=s*h-n*o-i*l-a*c,r}function Es(r,e,t){t*=.5;var n=e[0],i=e[1],a=e[2],s=e[3],o=Math.sin(t),l=Math.cos(t);return r[0]=n*l+s*o,r[1]=i*l+a*o,r[2]=a*l-i*o,r[3]=s*l-n*o,r}function S0(r,e,t){t*=.5;var n=e[0],i=e[1],a=e[2],s=e[3],o=Math.sin(t),l=Math.cos(t);return r[0]=n*l-a*o,r[1]=i*l+s*o,r[2]=a*l+n*o,r[3]=s*l-i*o,r}function Fo(r,e,t){t*=.5;var n=e[0],i=e[1],a=e[2],s=e[3],o=Math.sin(t),l=Math.cos(t);return r[0]=n*l+i*o,r[1]=i*l-n*o,r[2]=a*l+s*o,r[3]=s*l-a*o,r}function T0(r,e){var t=e[0],n=e[1],i=e[2];return r[0]=t,r[1]=n,r[2]=i,r[3]=Math.sqrt(Math.abs(1-t*t-n*n-i*i)),r}function Yd(r,e){var t=e[0],n=e[1],i=e[2],a=e[3],s=Math.sqrt(t*t+n*n+i*i),o=Math.exp(a),l=s>0?o*Math.sin(s)/s:0;return r[0]=t*l,r[1]=n*l,r[2]=i*l,r[3]=o*Math.cos(s),r}function Qd(r,e){var t=e[0],n=e[1],i=e[2],a=e[3],s=Math.sqrt(t*t+n*n+i*i),o=s>0?Math.atan2(s,a)/s:0;return r[0]=t*o,r[1]=n*o,r[2]=i*o,r[3]=.5*Math.log(t*t+n*n+i*i+a*a),r}function A0(r,e,t){return Qd(r,e),ar(r,r,t),Yd(r,r),r}function _c(r,e,t,n){var i=e[0],a=e[1],s=e[2],o=e[3],l=t[0],c=t[1],h=t[2],p=t[3],C,k,W,j,K;return k=i*l+a*c+s*h+o*p,k<0&&(k=-k,l=-l,c=-c,h=-h,p=-p),1-k>v?(C=Math.acos(k),W=Math.sin(C),j=Math.sin((1-n)*C)/W,K=Math.sin(n*C)/W):(j=1-n,K=n),r[0]=j*i+K*l,r[1]=j*a+K*c,r[2]=j*s+K*h,r[3]=j*o+K*p,r}function Jd(r){var e=glMatrix.RANDOM(),t=glMatrix.RANDOM(),n=glMatrix.RANDOM(),i=Math.sqrt(1-e),a=Math.sqrt(e);return r[0]=i*Math.sin(2*Math.PI*t),r[1]=i*Math.cos(2*Math.PI*t),r[2]=a*Math.sin(2*Math.PI*n),r[3]=a*Math.cos(2*Math.PI*n),r}function Ec(r,e){var t=e[0],n=e[1],i=e[2],a=e[3],s=t*t+n*n+i*i+a*a,o=s?1/s:0;return r[0]=-t*o,r[1]=-n*o,r[2]=-i*o,r[3]=a*o,r}function qd(r,e){return 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r[0]=1,r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=1,r[6]=0,r[7]=0,r[8]=0,r[9]=0,r[10]=1,r[11]=0,r[12]=0,r[13]=0,r[14]=0,r[15]=1,r}function Qt(r,e){if(r===e){var t=e[1],n=e[2],i=e[3],a=e[6],s=e[7],o=e[11];r[1]=e[4],r[2]=e[8],r[3]=e[12],r[4]=t,r[6]=e[9],r[7]=e[13],r[8]=n,r[9]=a,r[11]=e[14],r[12]=i,r[13]=s,r[14]=o}else r[0]=e[0],r[1]=e[4],r[2]=e[8],r[3]=e[12],r[4]=e[1],r[5]=e[5],r[6]=e[9],r[7]=e[13],r[8]=e[2],r[9]=e[6],r[10]=e[10],r[11]=e[14],r[12]=e[3],r[13]=e[7],r[14]=e[11],r[15]=e[15];return r}function Ct(r,e){var t=e[0],n=e[1],i=e[2],a=e[3],s=e[4],o=e[5],l=e[6],c=e[7],h=e[8],p=e[9],C=e[10],k=e[11],W=e[12],j=e[13],K=e[14],Q=e[15],ee=t*o-n*s,re=t*l-i*s,ve=t*c-a*s,he=n*l-i*o,pe=n*c-a*o,ye=i*c-a*l,_e=h*j-p*W,De=h*K-C*W,Be=h*Q-k*W,ze=p*K-C*j,Xe=p*Q-k*j,$e=C*Q-k*K,ct=ee*$e-re*Xe+ve*ze+he*Be-pe*De+ye*_e;return ct?(ct=1/ct,r[0]=(o*$e-l*Xe+c*ze)*ct,r[1]=(i*Xe-n*$e-a*ze)*ct,r[2]=(j*ye-K*pe+Q*he)*ct,r[3]=(C*pe-p*ye-k*he)*ct,r[4]=(l*Be-s*$e-c*De)*ct,r[5]=(t*$e-i*Be+a*De)*ct,r[6]=(K*ve-W*ye-Q*re)*ct,r[7]=(h*ye-C*ve+k*re)*ct,r[8]=(s*Xe-o*Be+c*_e)*ct,r[9]=(n*Be-t*Xe-a*_e)*ct,r[10]=(W*pe-j*ve+Q*ee)*ct,r[11]=(p*ve-h*pe-k*ee)*ct,r[12]=(o*De-s*ze-l*_e)*ct,r[13]=(t*ze-n*De+i*_e)*ct,r[14]=(j*re-W*he-K*ee)*ct,r[15]=(h*he-p*re+C*ee)*ct,r):null}function It(r,e){var t=e[0],n=e[1],i=e[2],a=e[3],s=e[4],o=e[5],l=e[6],c=e[7],h=e[8],p=e[9],C=e[10],k=e[11],W=e[12],j=e[13],K=e[14],Q=e[15];return r[0]=o*(C*Q-k*K)-p*(l*Q-c*K)+j*(l*k-c*C),r[1]=-(n*(C*Q-k*K)-p*(i*Q-a*K)+j*(i*k-a*C)),r[2]=n*(l*Q-c*K)-o*(i*Q-a*K)+j*(i*c-a*l),r[3]=-(n*(l*k-c*C)-o*(i*k-a*C)+p*(i*c-a*l)),r[4]=-(s*(C*Q-k*K)-h*(l*Q-c*K)+W*(l*k-c*C)),r[5]=t*(C*Q-k*K)-h*(i*Q-a*K)+W*(i*k-a*C),r[6]=-(t*(l*Q-c*K)-s*(i*Q-a*K)+W*(i*c-a*l)),r[7]=t*(l*k-c*C)-s*(i*k-a*C)+h*(i*c-a*l),r[8]=s*(p*Q-k*j)-h*(o*Q-c*j)+W*(o*k-c*p),r[9]=-(t*(p*Q-k*j)-h*(n*Q-a*j)+W*(n*k-a*p)),r[10]=t*(o*Q-c*j)-s*(n*Q-a*j)+W*(n*c-a*o),r[11]=-(t*(o*k-c*p)-s*(n*k-a*p)+h*(n*c-a*o)),r[12]=-(s*(p*K-C*j)-h*(o*K-l*j)+W*(o*C-l*p)),r[13]=t*(p*K-C*j)-h*(n*K-i*j)+W*(n*C-i*p),r[14]=-(t*(o*K-l*j)-s*(n*K-i*j)+W*(n*l-i*o)),r[15]=t*(o*C-l*p)-s*(n*C-i*p)+h*(n*l-i*o),r}function Zt(r){var e=r[0],t=r[1],n=r[2],i=r[3],a=r[4],s=r[5],o=r[6],l=r[7],c=r[8],h=r[9],p=r[10],C=r[11],k=r[12],W=r[13],j=r[14],K=r[15],Q=e*s-t*a,ee=e*o-n*a,re=e*l-i*a,ve=t*o-n*s,he=t*l-i*s,pe=n*l-i*o,ye=c*W-h*k,_e=c*j-p*k,De=c*K-C*k,Be=h*j-p*W,ze=h*K-C*W,Xe=p*K-C*j;return Q*Xe-ee*ze+re*Be+ve*De-he*_e+pe*ye}function lt(r,e,t){var n=e[0],i=e[1],a=e[2],s=e[3],o=e[4],l=e[5],c=e[6],h=e[7],p=e[8],C=e[9],k=e[10],W=e[11],j=e[12],K=e[13],Q=e[14],ee=e[15],re=t[0],ve=t[1],he=t[2],pe=t[3];return r[0]=re*n+ve*o+he*p+pe*j,r[1]=re*i+ve*l+he*C+pe*K,r[2]=re*a+ve*c+he*k+pe*Q,r[3]=re*s+ve*h+he*W+pe*ee,re=t[4],ve=t[5],he=t[6],pe=t[7],r[4]=re*n+ve*o+he*p+pe*j,r[5]=re*i+ve*l+he*C+pe*K,r[6]=re*a+ve*c+he*k+pe*Q,r[7]=re*s+ve*h+he*W+pe*ee,re=t[8],ve=t[9],he=t[10],pe=t[11],r[8]=re*n+ve*o+he*p+pe*j,r[9]=re*i+ve*l+he*C+pe*K,r[10]=re*a+ve*c+he*k+pe*Q,r[11]=re*s+ve*h+he*W+pe*ee,re=t[12],ve=t[13],he=t[14],pe=t[15],r[12]=re*n+ve*o+he*p+pe*j,r[13]=re*i+ve*l+he*C+pe*K,r[14]=re*a+ve*c+he*k+pe*Q,r[15]=re*s+ve*h+he*W+pe*ee,r}function Mt(r,e,t){var n=t[0],i=t[1],a=t[2],s,o,l,c,h,p,C,k,W,j,K,Q;return e===r?(r[12]=e[0]*n+e[4]*i+e[8]*a+e[12],r[13]=e[1]*n+e[5]*i+e[9]*a+e[13],r[14]=e[2]*n+e[6]*i+e[10]*a+e[14],r[15]=e[3]*n+e[7]*i+e[11]*a+e[15]):(s=e[0],o=e[1],l=e[2],c=e[3],h=e[4],p=e[5],C=e[6],k=e[7],W=e[8],j=e[9],K=e[10],Q=e[11],r[0]=s,r[1]=o,r[2]=l,r[3]=c,r[4]=h,r[5]=p,r[6]=C,r[7]=k,r[8]=W,r[9]=j,r[10]=K,r[11]=Q,r[12]=s*n+h*i+W*a+e[12],r[13]=o*n+p*i+j*a+e[13],r[14]=l*n+C*i+K*a+e[14],r[15]=c*n+k*i+Q*a+e[15]),r}function Lt(r,e,t){var n=t[0],i=t[1],a=t[2];return r[0]=e[0]*n,r[1]=e[1]*n,r[2]=e[2]*n,r[3]=e[3]*n,r[4]=e[4]*i,r[5]=e[5]*i,r[6]=e[6]*i,r[7]=e[7]*i,r[8]=e[8]*a,r[9]=e[9]*a,r[10]=e[10]*a,r[11]=e[11]*a,r[12]=e[12],r[13]=e[13],r[14]=e[14],r[15]=e[15],r}function Nt(r,e,t,n){var i=n[0],a=n[1],s=n[2],o=Math.hypot(i,a,s),l,c,h,p,C,k,W,j,K,Q,ee,re,ve,he,pe,ye,_e,De,Be,ze,Xe,$e,ct,ut;return o<v?null:(o=1/o,i*=o,a*=o,s*=o,l=Math.sin(t),c=Math.cos(t),h=1-c,p=e[0],C=e[1],k=e[2],W=e[3],j=e[4],K=e[5],Q=e[6],ee=e[7],re=e[8],ve=e[9],he=e[10],pe=e[11],ye=i*i*h+c,_e=a*i*h+s*l,De=s*i*h-a*l,Be=i*a*h-s*l,ze=a*a*h+c,Xe=s*a*h+i*l,$e=i*s*h+a*l,ct=a*s*h-i*l,ut=s*s*h+c,r[0]=p*ye+j*_e+re*De,r[1]=C*ye+K*_e+ve*De,r[2]=k*ye+Q*_e+he*De,r[3]=W*ye+ee*_e+pe*De,r[4]=p*Be+j*ze+re*Xe,r[5]=C*Be+K*ze+ve*Xe,r[6]=k*Be+Q*ze+he*Xe,r[7]=W*Be+ee*ze+pe*Xe,r[8]=p*$e+j*ct+re*ut,r[9]=C*$e+K*ct+ve*ut,r[10]=k*$e+Q*ct+he*ut,r[11]=W*$e+ee*ct+pe*ut,e!==r&&(r[12]=e[12],r[13]=e[13],r[14]=e[14],r[15]=e[15]),r)}function Vt(r,e,t){var n=Math.sin(t),i=Math.cos(t),a=e[4],s=e[5],o=e[6],l=e[7],c=e[8],h=e[9],p=e[10],C=e[11];return e!==r&&(r[0]=e[0],r[1]=e[1],r[2]=e[2],r[3]=e[3],r[12]=e[12],r[13]=e[13],r[14]=e[14],r[15]=e[15]),r[4]=a*i+c*n,r[5]=s*i+h*n,r[6]=o*i+p*n,r[7]=l*i+C*n,r[8]=c*i-a*n,r[9]=h*i-s*n,r[10]=p*i-o*n,r[11]=C*i-l*n,r}function Kt(r,e,t){var n=Math.sin(t),i=Math.cos(t),a=e[0],s=e[1],o=e[2],l=e[3],c=e[8],h=e[9],p=e[10],C=e[11];return e!==r&&(r[4]=e[4],r[5]=e[5],r[6]=e[6],r[7]=e[7],r[12]=e[12],r[13]=e[13],r[14]=e[14],r[15]=e[15]),r[0]=a*i-c*n,r[1]=s*i-h*n,r[2]=o*i-p*n,r[3]=l*i-C*n,r[8]=a*n+c*i,r[9]=s*n+h*i,r[10]=o*n+p*i,r[11]=l*n+C*i,r}function qt(r,e,t){var n=Math.sin(t),i=Math.cos(t),a=e[0],s=e[1],o=e[2],l=e[3],c=e[4],h=e[5],p=e[6],C=e[7];return e!==r&&(r[8]=e[8],r[9]=e[9],r[10]=e[10],r[11]=e[11],r[12]=e[12],r[13]=e[13],r[14]=e[14],r[15]=e[15]),r[0]=a*i+c*n,r[1]=s*i+h*n,r[2]=o*i+p*n,r[3]=l*i+C*n,r[4]=c*i-a*n,r[5]=h*i-s*n,r[6]=p*i-o*n,r[7]=C*i-l*n,r}function ln(r,e){return r[0]=1,r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=1,r[6]=0,r[7]=0,r[8]=0,r[9]=0,r[10]=1,r[11]=0,r[12]=e[0],r[13]=e[1],r[14]=e[2],r[15]=1,r}function pn(r,e){return r[0]=e[0],r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=e[1],r[6]=0,r[7]=0,r[8]=0,r[9]=0,r[10]=e[2],r[11]=0,r[12]=0,r[13]=0,r[14]=0,r[15]=1,r}function mn(r,e,t){var n=t[0],i=t[1],a=t[2],s=Math.hypot(n,i,a),o,l,c;return s<v?null:(s=1/s,n*=s,i*=s,a*=s,o=Math.sin(e),l=Math.cos(e),c=1-l,r[0]=n*n*c+l,r[1]=i*n*c+a*o,r[2]=a*n*c-i*o,r[3]=0,r[4]=n*i*c-a*o,r[5]=i*i*c+l,r[6]=a*i*c+n*o,r[7]=0,r[8]=n*a*c+i*o,r[9]=i*a*c-n*o,r[10]=a*a*c+l,r[11]=0,r[12]=0,r[13]=0,r[14]=0,r[15]=1,r)}function yn(r,e){var t=Math.sin(e),n=Math.cos(e);return r[0]=1,r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=n,r[6]=t,r[7]=0,r[8]=0,r[9]=-t,r[10]=n,r[11]=0,r[12]=0,r[13]=0,r[14]=0,r[15]=1,r}function Zn(r,e){var t=Math.sin(e),n=Math.cos(e);return r[0]=n,r[1]=0,r[2]=-t,r[3]=0,r[4]=0,r[5]=1,r[6]=0,r[7]=0,r[8]=t,r[9]=0,r[10]=n,r[11]=0,r[12]=0,r[13]=0,r[14]=0,r[15]=1,r}function Nn(r,e){var t=Math.sin(e),n=Math.cos(e);return r[0]=n,r[1]=t,r[2]=0,r[3]=0,r[4]=-t,r[5]=n,r[6]=0,r[7]=0,r[8]=0,r[9]=0,r[10]=1,r[11]=0,r[12]=0,r[13]=0,r[14]=0,r[15]=1,r}function nn(r,e,t){var n=e[0],i=e[1],a=e[2],s=e[3],o=n+n,l=i+i,c=a+a,h=n*o,p=n*l,C=n*c,k=i*l,W=i*c,j=a*c,K=s*o,Q=s*l,ee=s*c;return r[0]=1-(k+j),r[1]=p+ee,r[2]=C-Q,r[3]=0,r[4]=p-ee,r[5]=1-(h+j),r[6]=W+K,r[7]=0,r[8]=C+Q,r[9]=W-K,r[10]=1-(h+k),r[11]=0,r[12]=t[0],r[13]=t[1],r[14]=t[2],r[15]=1,r}function Ln(r,e){var t=new M(3),n=-e[0],i=-e[1],a=-e[2],s=e[3],o=e[4],l=e[5],c=e[6],h=e[7],p=n*n+i*i+a*a+s*s;return p>0?(t[0]=(o*s+h*n+l*a-c*i)*2/p,t[1]=(l*s+h*i+c*n-o*a)*2/p,t[2]=(c*s+h*a+o*i-l*n)*2/p):(t[0]=(o*s+h*n+l*a-c*i)*2,t[1]=(l*s+h*i+c*n-o*a)*2,t[2]=(c*s+h*a+o*i-l*n)*2),nn(r,e,t),r}function Bn(r,e){return r[0]=e[12],r[1]=e[13],r[2]=e[14],r}function lr(r,e){var t=e[0],n=e[1],i=e[2],a=e[4],s=e[5],o=e[6],l=e[8],c=e[9],h=e[10];return r[0]=Math.hypot(t,n,i),r[1]=Math.hypot(a,s,o),r[2]=Math.hypot(l,c,h),r}function qn(r,e){var t=new M(3);lr(t,e);var n=1/t[0],i=1/t[1],a=1/t[2],s=e[0]*n,o=e[1]*i,l=e[2]*a,c=e[4]*n,h=e[5]*i,p=e[6]*a,C=e[8]*n,k=e[9]*i,W=e[10]*a,j=s+h+W,K=0;return j>0?(K=Math.sqrt(j+1)*2,r[3]=.25*K,r[0]=(p-k)/K,r[1]=(C-l)/K,r[2]=(o-c)/K):s>h&&s>W?(K=Math.sqrt(1+s-h-W)*2,r[3]=(p-k)/K,r[0]=.25*K,r[1]=(o+c)/K,r[2]=(C+l)/K):h>W?(K=Math.sqrt(1+h-s-W)*2,r[3]=(C-l)/K,r[0]=(o+c)/K,r[1]=.25*K,r[2]=(p+k)/K):(K=Math.sqrt(1+W-s-h)*2,r[3]=(o-c)/K,r[0]=(C+l)/K,r[1]=(p+k)/K,r[2]=.25*K),r}function Hr(r,e,t,n){var i=e[0],a=e[1],s=e[2],o=e[3],l=i+i,c=a+a,h=s+s,p=i*l,C=i*c,k=i*h,W=a*c,j=a*h,K=s*h,Q=o*l,ee=o*c,re=o*h,ve=n[0],he=n[1],pe=n[2];return r[0]=(1-(W+K))*ve,r[1]=(C+re)*ve,r[2]=(k-ee)*ve,r[3]=0,r[4]=(C-re)*he,r[5]=(1-(p+K))*he,r[6]=(j+Q)*he,r[7]=0,r[8]=(k+ee)*pe,r[9]=(j-Q)*pe,r[10]=(1-(p+W))*pe,r[11]=0,r[12]=t[0],r[13]=t[1],r[14]=t[2],r[15]=1,r}function hi(r,e,t,n,i){var a=e[0],s=e[1],o=e[2],l=e[3],c=a+a,h=s+s,p=o+o,C=a*c,k=a*h,W=a*p,j=s*h,K=s*p,Q=o*p,ee=l*c,re=l*h,ve=l*p,he=n[0],pe=n[1],ye=n[2],_e=i[0],De=i[1],Be=i[2],ze=(1-(j+Q))*he,Xe=(k+ve)*he,$e=(W-re)*he,ct=(k-ve)*pe,ut=(1-(C+Q))*pe,St=(K+ee)*pe,bt=(W+re)*ye,Et=(K-ee)*ye,xt=(1-(C+j))*ye;return r[0]=ze,r[1]=Xe,r[2]=$e,r[3]=0,r[4]=ct,r[5]=ut,r[6]=St,r[7]=0,r[8]=bt,r[9]=Et,r[10]=xt,r[11]=0,r[12]=t[0]+_e-(ze*_e+ct*De+bt*Be),r[13]=t[1]+De-(Xe*_e+ut*De+Et*Be),r[14]=t[2]+Be-($e*_e+St*De+xt*Be),r[15]=1,r}function cr(r,e){var t=e[0],n=e[1],i=e[2],a=e[3],s=t+t,o=n+n,l=i+i,c=t*s,h=n*s,p=n*o,C=i*s,k=i*o,W=i*l,j=a*s,K=a*o,Q=a*l;return r[0]=1-p-W,r[1]=h+Q,r[2]=C-K,r[3]=0,r[4]=h-Q,r[5]=1-c-W,r[6]=k+j,r[7]=0,r[8]=C+K,r[9]=k-j,r[10]=1-c-p,r[11]=0,r[12]=0,r[13]=0,r[14]=0,r[15]=1,r}function fi(r,e,t,n,i,a,s){var o=1/(t-e),l=1/(i-n),c=1/(a-s);return r[0]=a*2*o,r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=a*2*l,r[6]=0,r[7]=0,r[8]=(t+e)*o,r[9]=(i+n)*l,r[10]=(s+a)*c,r[11]=-1,r[12]=0,r[13]=0,r[14]=s*a*2*c,r[15]=0,r}function Hi(r,e,t,n,i){var a=1/Math.tan(e/2),s;return r[0]=a/t,r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=a,r[6]=0,r[7]=0,r[8]=0,r[9]=0,r[11]=-1,r[12]=0,r[13]=0,r[15]=0,i!=null&&i!==1/0?(s=1/(n-i),r[10]=(i+n)*s,r[14]=2*i*n*s):(r[10]=-1,r[14]=-2*n),r}var Kn=Hi;function Dn(r,e,t,n,i){var a=1/Math.tan(e/2),s;return r[0]=a/t,r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=a,r[6]=0,r[7]=0,r[8]=0,r[9]=0,r[11]=-1,r[12]=0,r[13]=0,r[15]=0,i!=null&&i!==1/0?(s=1/(n-i),r[10]=i*s,r[14]=i*n*s):(r[10]=-1,r[14]=-n),r}function Qn(r,e,t,n){var i=Math.tan(e.upDegrees*Math.PI/180),a=Math.tan(e.downDegrees*Math.PI/180),s=Math.tan(e.leftDegrees*Math.PI/180),o=Math.tan(e.rightDegrees*Math.PI/180),l=2/(s+o),c=2/(i+a);return r[0]=l,r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=c,r[6]=0,r[7]=0,r[8]=-((s-o)*l*.5),r[9]=(i-a)*c*.5,r[10]=n/(t-n),r[11]=-1,r[12]=0,r[13]=0,r[14]=n*t/(t-n),r[15]=0,r}function ur(r,e,t,n,i,a,s){var o=1/(e-t),l=1/(n-i),c=1/(a-s);return r[0]=-2*o,r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=-2*l,r[6]=0,r[7]=0,r[8]=0,r[9]=0,r[10]=2*c,r[11]=0,r[12]=(e+t)*o,r[13]=(i+n)*l,r[14]=(s+a)*c,r[15]=1,r}var fr=ur;function yr(r,e,t,n,i,a,s){var o=1/(e-t),l=1/(n-i),c=1/(a-s);return r[0]=-2*o,r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=-2*l,r[6]=0,r[7]=0,r[8]=0,r[9]=0,r[10]=c,r[11]=0,r[12]=(e+t)*o,r[13]=(i+n)*l,r[14]=a*c,r[15]=1,r}function er(r,e,t,n){var i,a,s,o,l,c,h,p,C,k,W=e[0],j=e[1],K=e[2],Q=n[0],ee=n[1],re=n[2],ve=t[0],he=t[1],pe=t[2];return Math.abs(W-ve)<v&&Math.abs(j-he)<v&&Math.abs(K-pe)<v?Ut(r):(h=W-ve,p=j-he,C=K-pe,k=1/Math.hypot(h,p,C),h*=k,p*=k,C*=k,i=ee*C-re*p,a=re*h-Q*C,s=Q*p-ee*h,k=Math.hypot(i,a,s),k?(k=1/k,i*=k,a*=k,s*=k):(i=0,a=0,s=0),o=p*s-C*a,l=C*i-h*s,c=h*a-p*i,k=Math.hypot(o,l,c),k?(k=1/k,o*=k,l*=k,c*=k):(o=0,l=0,c=0),r[0]=i,r[1]=o,r[2]=h,r[3]=0,r[4]=a,r[5]=l,r[6]=p,r[7]=0,r[8]=s,r[9]=c,r[10]=C,r[11]=0,r[12]=-(i*W+a*j+s*K),r[13]=-(o*W+l*j+c*K),r[14]=-(h*W+p*j+C*K),r[15]=1,r)}function Dr(r,e,t,n){var i=e[0],a=e[1],s=e[2],o=n[0],l=n[1],c=n[2],h=i-t[0],p=a-t[1],C=s-t[2],k=h*h+p*p+C*C;k>0&&(k=1/Math.sqrt(k),h*=k,p*=k,C*=k);var W=l*C-c*p,j=c*h-o*C,K=o*p-l*h;return k=W*W+j*j+K*K,k>0&&(k=1/Math.sqrt(k),W*=k,j*=k,K*=k),r[0]=W,r[1]=j,r[2]=K,r[3]=0,r[4]=p*K-C*j,r[5]=C*W-h*K,r[6]=h*j-p*W,r[7]=0,r[8]=h,r[9]=p,r[10]=C,r[11]=0,r[12]=i,r[13]=a,r[14]=s,r[15]=1,r}function qr(r){return"mat4("+r[0]+", "+r[1]+", "+r[2]+", "+r[3]+", "+r[4]+", "+r[5]+", "+r[6]+", "+r[7]+", "+r[8]+", "+r[9]+", "+r[10]+", "+r[11]+", "+r[12]+", "+r[13]+", "+r[14]+", "+r[15]+")"}function Zr(r){return Math.hypot(r[0],r[1],r[2],r[3],r[4],r[5],r[6],r[7],r[8],r[9],r[10],r[11],r[12],r[13],r[14],r[15])}function _i(r,e,t){return r[0]=e[0]+t[0],r[1]=e[1]+t[1],r[2]=e[2]+t[2],r[3]=e[3]+t[3],r[4]=e[4]+t[4],r[5]=e[5]+t[5],r[6]=e[6]+t[6],r[7]=e[7]+t[7],r[8]=e[8]+t[8],r[9]=e[9]+t[9],r[10]=e[10]+t[10],r[11]=e[11]+t[11],r[12]=e[12]+t[12],r[13]=e[13]+t[13],r[14]=e[14]+t[14],r[15]=e[15]+t[15],r}function _n(r,e,t){return r[0]=e[0]-t[0],r[1]=e[1]-t[1],r[2]=e[2]-t[2],r[3]=e[3]-t[3],r[4]=e[4]-t[4],r[5]=e[5]-t[5],r[6]=e[6]-t[6],r[7]=e[7]-t[7],r[8]=e[8]-t[8],r[9]=e[9]-t[9],r[10]=e[10]-t[10],r[11]=e[11]-t[11],r[12]=e[12]-t[12],r[13]=e[13]-t[13],r[14]=e[14]-t[14],r[15]=e[15]-t[15],r}function fn(r,e,t){return r[0]=e[0]*t,r[1]=e[1]*t,r[2]=e[2]*t,r[3]=e[3]*t,r[4]=e[4]*t,r[5]=e[5]*t,r[6]=e[6]*t,r[7]=e[7]*t,r[8]=e[8]*t,r[9]=e[9]*t,r[10]=e[10]*t,r[11]=e[11]*t,r[12]=e[12]*t,r[13]=e[13]*t,r[14]=e[14]*t,r[15]=e[15]*t,r}function kn(r,e,t,n){return r[0]=e[0]+t[0]*n,r[1]=e[1]+t[1]*n,r[2]=e[2]+t[2]*n,r[3]=e[3]+t[3]*n,r[4]=e[4]+t[4]*n,r[5]=e[5]+t[5]*n,r[6]=e[6]+t[6]*n,r[7]=e[7]+t[7]*n,r[8]=e[8]+t[8]*n,r[9]=e[9]+t[9]*n,r[10]=e[10]+t[10]*n,r[11]=e[11]+t[11]*n,r[12]=e[12]+t[12]*n,r[13]=e[13]+t[13]*n,r[14]=e[14]+t[14]*n,r[15]=e[15]+t[15]*n,r}function Wn(r,e){return r[0]===e[0]&&r[1]===e[1]&&r[2]===e[2]&&r[3]===e[3]&&r[4]===e[4]&&r[5]===e[5]&&r[6]===e[6]&&r[7]===e[7]&&r[8]===e[8]&&r[9]===e[9]&&r[10]===e[10]&&r[11]===e[11]&&r[12]===e[12]&&r[13]===e[13]&&r[14]===e[14]&&r[15]===e[15]}function Mr(r,e){var t=r[0],n=r[1],i=r[2],a=r[3],s=r[4],o=r[5],l=r[6],c=r[7],h=r[8],p=r[9],C=r[10],k=r[11],W=r[12],j=r[13],K=r[14],Q=r[15],ee=e[0],re=e[1],ve=e[2],he=e[3],pe=e[4],ye=e[5],_e=e[6],De=e[7],Be=e[8],ze=e[9],Xe=e[10],$e=e[11],ct=e[12],ut=e[13],St=e[14],bt=e[15];return Math.abs(t-ee)<=v*Math.max(1,Math.abs(t),Math.abs(ee))&&Math.abs(n-re)<=v*Math.max(1,Math.abs(n),Math.abs(re))&&Math.abs(i-ve)<=v*Math.max(1,Math.abs(i),Math.abs(ve))&&Math.abs(a-he)<=v*Math.max(1,Math.abs(a),Math.abs(he))&&Math.abs(s-pe)<=v*Math.max(1,Math.abs(s),Math.abs(pe))&&Math.abs(o-ye)<=v*Math.max(1,Math.abs(o),Math.abs(ye))&&Math.abs(l-_e)<=v*Math.max(1,Math.abs(l),Math.abs(_e))&&Math.abs(c-De)<=v*Math.max(1,Math.abs(c),Math.abs(De))&&Math.abs(h-Be)<=v*Math.max(1,Math.abs(h),Math.abs(Be))&&Math.abs(p-ze)<=v*Math.max(1,Math.abs(p),Math.abs(ze))&&Math.abs(C-Xe)<=v*Math.max(1,Math.abs(C),Math.abs(Xe))&&Math.abs(k-$e)<=v*Math.max(1,Math.abs(k),Math.abs($e))&&Math.abs(W-ct)<=v*Math.max(1,Math.abs(W),Math.abs(ct))&&Math.abs(j-ut)<=v*Math.max(1,Math.abs(j),Math.abs(ut))&&Math.abs(K-St)<=v*Math.max(1,Math.abs(K),Math.abs(St))&&Math.abs(Q-bt)<=v*Math.max(1,Math.abs(Q),Math.abs(bt))}var fa=lt,Si=_n;function Ti(){var r=new M(9);return M!=Float32Array&&(r[1]=0,r[2]=0,r[3]=0,r[5]=0,r[6]=0,r[7]=0),r[0]=1,r[4]=1,r[8]=1,r}function $i(r,e){return r[0]=e[0],r[1]=e[1],r[2]=e[2],r[3]=e[4],r[4]=e[5],r[5]=e[6],r[6]=e[8],r[7]=e[9],r[8]=e[10],r}function ji(r){var e=new glMatrix.ARRAY_TYPE(9);return e[0]=r[0],e[1]=r[1],e[2]=r[2],e[3]=r[3],e[4]=r[4],e[5]=r[5],e[6]=r[6],e[7]=r[7],e[8]=r[8],e}function Gi(r,e){return r[0]=e[0],r[1]=e[1],r[2]=e[2],r[3]=e[3],r[4]=e[4],r[5]=e[5],r[6]=e[6],r[7]=e[7],r[8]=e[8],r}function Fa(r,e,t,n,i,a,s,o,l){var c=new M(9);return c[0]=r,c[1]=e,c[2]=t,c[3]=n,c[4]=i,c[5]=a,c[6]=s,c[7]=o,c[8]=l,c}function ea(r,e,t,n,i,a,s,o,l,c){return r[0]=e,r[1]=t,r[2]=n,r[3]=i,r[4]=a,r[5]=s,r[6]=o,r[7]=l,r[8]=c,r}function $a(r){return r[0]=1,r[1]=0,r[2]=0,r[3]=0,r[4]=1,r[5]=0,r[6]=0,r[7]=0,r[8]=1,r}function io(r,e){if(r===e){var t=e[1],n=e[2],i=e[5];r[1]=e[3],r[2]=e[6],r[3]=t,r[5]=e[7],r[6]=n,r[7]=i}else r[0]=e[0],r[1]=e[3],r[2]=e[6],r[3]=e[1],r[4]=e[4],r[5]=e[7],r[6]=e[2],r[7]=e[5],r[8]=e[8];return r}function Bo(r,e){var t=e[0],n=e[1],i=e[2],a=e[3],s=e[4],o=e[5],l=e[6],c=e[7],h=e[8],p=h*s-o*c,C=-h*a+o*l,k=c*a-s*l,W=t*p+n*C+i*k;return W?(W=1/W,r[0]=p*W,r[1]=(-h*n+i*c)*W,r[2]=(o*n-i*s)*W,r[3]=C*W,r[4]=(h*t-i*l)*W,r[5]=(-o*t+i*a)*W,r[6]=k*W,r[7]=(-c*t+n*l)*W,r[8]=(s*t-n*a)*W,r):null}function Ml(r,e){var t=e[0],n=e[1],i=e[2],a=e[3],s=e[4],o=e[5],l=e[6],c=e[7],h=e[8];return r[0]=s*h-o*c,r[1]=i*c-n*h,r[2]=n*o-i*s,r[3]=o*l-a*h,r[4]=t*h-i*l,r[5]=i*a-t*o,r[6]=a*c-s*l,r[7]=n*l-t*c,r[8]=t*s-n*a,r}function ko(r){var e=r[0],t=r[1],n=r[2],i=r[3],a=r[4],s=r[5],o=r[6],l=r[7],c=r[8];return e*(c*a-s*l)+t*(-c*i+s*o)+n*(l*i-a*o)}function es(r,e,t){var n=e[0],i=e[1],a=e[2],s=e[3],o=e[4],l=e[5],c=e[6],h=e[7],p=e[8],C=t[0],k=t[1],W=t[2],j=t[3],K=t[4],Q=t[5],ee=t[6],re=t[7],ve=t[8];return r[0]=C*n+k*s+W*c,r[1]=C*i+k*o+W*h,r[2]=C*a+k*l+W*p,r[3]=j*n+K*s+Q*c,r[4]=j*i+K*o+Q*h,r[5]=j*a+K*l+Q*p,r[6]=ee*n+re*s+ve*c,r[7]=ee*i+re*o+ve*h,r[8]=ee*a+re*l+ve*p,r}function Sl(r,e,t){var n=e[0],i=e[1],a=e[2],s=e[3],o=e[4],l=e[5],c=e[6],h=e[7],p=e[8],C=t[0],k=t[1];return r[0]=n,r[1]=i,r[2]=a,r[3]=s,r[4]=o,r[5]=l,r[6]=C*n+k*s+c,r[7]=C*i+k*o+h,r[8]=C*a+k*l+p,r}function ts(r,e,t){var n=e[0],i=e[1],a=e[2],s=e[3],o=e[4],l=e[5],c=e[6],h=e[7],p=e[8],C=Math.sin(t),k=Math.cos(t);return r[0]=k*n+C*s,r[1]=k*i+C*o,r[2]=k*a+C*l,r[3]=k*s-C*n,r[4]=k*o-C*i,r[5]=k*l-C*a,r[6]=c,r[7]=h,r[8]=p,r}function Au(r,e,t){var n=t[0],i=t[1];return r[0]=n*e[0],r[1]=n*e[1],r[2]=n*e[2],r[3]=i*e[3],r[4]=i*e[4],r[5]=i*e[5],r[6]=e[6],r[7]=e[7],r[8]=e[8],r}function gc(r,e){return r[0]=1,r[1]=0,r[2]=0,r[3]=0,r[4]=1,r[5]=0,r[6]=e[0],r[7]=e[1],r[8]=1,r}function Tl(r,e){var t=Math.sin(e),n=Math.cos(e);return r[0]=n,r[1]=t,r[2]=0,r[3]=-t,r[4]=n,r[5]=0,r[6]=0,r[7]=0,r[8]=1,r}function zo(r,e){return r[0]=e[0],r[1]=0,r[2]=0,r[3]=0,r[4]=e[1],r[5]=0,r[6]=0,r[7]=0,r[8]=1,r}function pc(r,e){return r[0]=e[0],r[1]=e[1],r[2]=0,r[3]=e[2],r[4]=e[3],r[5]=0,r[6]=e[4],r[7]=e[5],r[8]=1,r}function Cu(r,e){var t=e[0],n=e[1],i=e[2],a=e[3],s=t+t,o=n+n,l=i+i,c=t*s,h=n*s,p=n*o,C=i*s,k=i*o,W=i*l,j=a*s,K=a*o,Q=a*l;return r[0]=1-p-W,r[3]=h-Q,r[6]=C+K,r[1]=h+Q,r[4]=1-c-W,r[7]=k-j,r[2]=C-K,r[5]=k+j,r[8]=1-c-p,r}function mc(r,e){var t=e[0],n=e[1],i=e[2],a=e[3],s=e[4],o=e[5],l=e[6],c=e[7],h=e[8],p=e[9],C=e[10],k=e[11],W=e[12],j=e[13],K=e[14],Q=e[15],ee=t*o-n*s,re=t*l-i*s,ve=t*c-a*s,he=n*l-i*o,pe=n*c-a*o,ye=i*c-a*l,_e=h*j-p*W,De=h*K-C*W,Be=h*Q-k*W,ze=p*K-C*j,Xe=p*Q-k*j,$e=C*Q-k*K,ct=ee*$e-re*Xe+ve*ze+he*Be-pe*De+ye*_e;return ct?(ct=1/ct,r[0]=(o*$e-l*Xe+c*ze)*ct,r[1]=(l*Be-s*$e-c*De)*ct,r[2]=(s*Xe-o*Be+c*_e)*ct,r[3]=(i*Xe-n*$e-a*ze)*ct,r[4]=(t*$e-i*Be+a*De)*ct,r[5]=(n*Be-t*Xe-a*_e)*ct,r[6]=(j*ye-K*pe+Q*he)*ct,r[7]=(K*ve-W*ye-Q*re)*ct,r[8]=(W*pe-j*ve+Q*ee)*ct,r):null}function yc(r,e,t){return r[0]=2/e,r[1]=0,r[2]=0,r[3]=0,r[4]=-2/t,r[5]=0,r[6]=-1,r[7]=1,r[8]=1,r}function Al(r){return"mat3("+r[0]+", "+r[1]+", "+r[2]+", "+r[3]+", "+r[4]+", "+r[5]+", "+r[6]+", "+r[7]+", "+r[8]+")"}function An(r){return Math.hypot(r[0],r[1],r[2],r[3],r[4],r[5],r[6],r[7],r[8])}function Xn(r,e,t){return r[0]=e[0]+t[0],r[1]=e[1]+t[1],r[2]=e[2]+t[2],r[3]=e[3]+t[3],r[4]=e[4]+t[4],r[5]=e[5]+t[5],r[6]=e[6]+t[6],r[7]=e[7]+t[7],r[8]=e[8]+t[8],r}function Fn(r,e,t){return r[0]=e[0]-t[0],r[1]=e[1]-t[1],r[2]=e[2]-t[2],r[3]=e[3]-t[3],r[4]=e[4]-t[4],r[5]=e[5]-t[5],r[6]=e[6]-t[6],r[7]=e[7]-t[7],r[8]=e[8]-t[8],r}function jn(r,e,t){return r[0]=e[0]*t,r[1]=e[1]*t,r[2]=e[2]*t,r[3]=e[3]*t,r[4]=e[4]*t,r[5]=e[5]*t,r[6]=e[6]*t,r[7]=e[7]*t,r[8]=e[8]*t,r}function Ir(r,e,t,n){return r[0]=e[0]+t[0]*n,r[1]=e[1]+t[1]*n,r[2]=e[2]+t[2]*n,r[3]=e[3]+t[3]*n,r[4]=e[4]+t[4]*n,r[5]=e[5]+t[5]*n,r[6]=e[6]+t[6]*n,r[7]=e[7]+t[7]*n,r[8]=e[8]+t[8]*n,r}function zr(r,e){return r[0]===e[0]&&r[1]===e[1]&&r[2]===e[2]&&r[3]===e[3]&&r[4]===e[4]&&r[5]===e[5]&&r[6]===e[6]&&r[7]===e[7]&&r[8]===e[8]}function _s(r,e){var t=r[0],n=r[1],i=r[2],a=r[3],s=r[4],o=r[5],l=r[6],c=r[7],h=r[8],p=e[0],C=e[1],k=e[2],W=e[3],j=e[4],K=e[5],Q=e[6],ee=e[7],re=e[8];return 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c<Wu?c>-Wu?(t=Math.atan2(e[6]/o,e[10]/l),n=Math.atan2(e[1]/s,e[0]/s)):(n=0,t=-Math.atan2(e[4]/o,e[5]/o)):(n=0,t=Math.atan2(e[4]/o,e[5]/o)),r[0]=t,r[1]=c,r[2]=n,r}function dv(r,e){return e.length===16?Yw(r,e):Xw(r,e)}function Qw(r,e,t,n,i){var a=Math.cos(r),s=Math.sin(r);return Fa(n*a,i*s,0,-n*s,i*a,0,e,t,1)}function Jw(r,e,t,n,i,a,s){var o=arguments.length>7&&arguments[7]!==void 0?arguments[7]:!1,l=2*a,c=t-e,h=n-i,p=l/c,C=l/h,k=(t+e)/c,W=(n+i)/h,j,K,Q=s-a,ee=s*a;return o?(j=-s/Q,K=-ee/Q):(j=-(s+a)/Q,K=-2*ee/Q),r[0]=p,r[1]=0,r[2]=0,r[3]=0,r[4]=0,r[5]=C,r[6]=0,r[7]=0,r[8]=k,r[9]=W,r[10]=j,r[11]=-1,r[12]=0,r[13]=0,r[14]=K,r[15]=0,r}function lm(r){var e=r[0],t=r[1],n=r[3],i=r[4],a=Math.sqrt(e*e+t*t),s=Math.sqrt(n*n+i*i),o=e*i-t*n;if(o<0&&(e<i?a=-a:s=-s),a){var l=1/a;e*=l,t*=l}if(s){var c=1/s;n*=c,i*=c}var h=Math.atan2(t,e),p=ga(h);return[r[6],r[7],a,s,p]}var ws=Je(),rs=Je(),Mc=Ye(),Hn=[f(),f(),f()],cm=f();function qw(r,e,t,n,i,a){if(!$w(ws,r)||(ft(rs,ws),rs[3]=0,rs[7]=0,rs[11]=0,rs[15]=1,Math.abs(Zt(rs))<1e-8))return!1;var s=ws[3],o=ws[7],l=ws[11],c=ws[12],h=ws[13],p=ws[14],C=ws[15];if(s!==0||o!==0||l!==0){Mc[0]=s,Mc[1]=o,Mc[2]=l,Mc[3]=C;var k=Ct(rs,rs);if(!k)return!1;Qt(rs,rs),B(i,Mc,rs)}else i[0]=i[1]=i[2]=0,i[3]=1;if(e[0]=c,e[1]=h,e[2]=p,eM(Hn,ws),t[0]=D(Hn[0]),Ne(Hn[0],Hn[0]),n[0]=We(Hn[0],Hn[1]),vv(Hn[1],Hn[1],Hn[0],1,-n[0]),t[1]=D(Hn[1]),Ne(Hn[1],Hn[1]),n[0]/=t[1],n[1]=We(Hn[0],Hn[2]),vv(Hn[2],Hn[2],Hn[0],1,-n[1]),n[2]=We(Hn[1],Hn[2]),vv(Hn[2],Hn[2],Hn[1],1,-n[2]),t[2]=D(Hn[2]),Ne(Hn[2],Hn[2]),n[1]/=t[2],n[2]/=t[2],nt(cm,Hn[1],Hn[2]),We(Hn[0],cm)<0)for(var W=0;W<3;W++)t[W]*=-1,Hn[W][0]*=-1,Hn[W][1]*=-1,Hn[W][2]*=-1;return a[0]=.5*Math.sqrt(Math.max(1+Hn[0][0]-Hn[1][1]-Hn[2][2],0)),a[1]=.5*Math.sqrt(Math.max(1-Hn[0][0]+Hn[1][1]-Hn[2][2],0)),a[2]=.5*Math.sqrt(Math.max(1-Hn[0][0]-Hn[1][1]+Hn[2][2],0)),a[3]=.5*Math.sqrt(Math.max(1+Hn[0][0]+Hn[1][1]+Hn[2][2],0)),Hn[2][1]>Hn[1][2]&&(a[0]=-a[0]),Hn[0][2]>Hn[2][0]&&(a[1]=-a[1]),Hn[1][0]>Hn[0][1]&&(a[2]=-a[2]),!0}function $w(r,e){var t=e[15];if(t===0)return!1;for(var n=1/t,i=0;i<16;i++)r[i]=e[i]*n;return!0}function eM(r,e){r[0][0]=e[0],r[0][1]=e[1],r[0][2]=e[2],r[1][0]=e[4],r[1][1]=e[5],r[1][2]=e[6],r[2][0]=e[8],r[2][1]=e[9],r[2][2]=e[10]}function vv(r,e,t,n,i){r[0]=e[0]*n+t[0]*i,r[1]=e[1]*n+t[1]*i,r[2]=e[2]*n+t[2]*i}var Ar=function(r){return r[r.ORBITING=0]="ORBITING",r[r.EXPLORING=1]="EXPLORING",r[r.TRACKING=2]="TRACKING",r}({}),gv=function(r){return r[r.DEFAULT=0]="DEFAULT",r[r.ROTATIONAL=1]="ROTATIONAL",r[r.TRANSLATIONAL=2]="TRANSLATIONAL",r[r.CINEMATIC=3]="CINEMATIC",r}({}),Wa=function(r){return r[r.ORTHOGRAPHIC=0]="ORTHOGRAPHIC",r[r.PERSPECTIVE=1]="PERSPECTIVE",r}({}),um={UPDATED:"updated"},hm=2e-4,fm=function(){function r(){(0,b.Z)(this,r),this.clipSpaceNearZ=Uu.NEGATIVE_ONE,this.eventEmitter=new d,this.matrix=Je(),this.right=I(1,0,0),this.up=I(0,1,0),this.forward=I(0,0,1),this.position=I(0,0,1),this.focalPoint=I(0,0,0),this.distanceVector=I(0,0,-1),this.distance=1,this.azimuth=0,this.elevation=0,this.roll=0,this.relAzimuth=0,this.relElevation=0,this.relRoll=0,this.dollyingStep=0,this.maxDistance=1/0,this.minDistance=-1/0,this.zoom=1,this.rotateWorld=!1,this.fov=30,this.near=.1,this.far=1e3,this.aspect=1,this.projectionMatrix=Je(),this.projectionMatrixInverse=Je(),this.jitteredProjectionMatrix=void 0,this.enableUpdate=!0,this.type=Ar.EXPLORING,this.trackingMode=gv.DEFAULT,this.projectionMode=Wa.PERSPECTIVE,this.frustum=new Hw,this.orthoMatrix=Je()}return(0,z.Z)(r,[{key:"isOrtho",value:function(){return this.projectionMode===Wa.ORTHOGRAPHIC}},{key:"getProjectionMode",value:function(){return this.projectionMode}},{key:"getPerspective",value:function(){return this.jitteredProjectionMatrix||this.projectionMatrix}},{key:"getPerspectiveInverse",value:function(){return this.projectionMatrixInverse}},{key:"getFrustum",value:function(){return this.frustum}},{key:"getPosition",value:function(){return this.position}},{key:"getFocalPoint",value:function(){return this.focalPoint}},{key:"getDollyingStep",value:function(){return this.dollyingStep}},{key:"getNear",value:function(){return this.near}},{key:"getFar",value:function(){return this.far}},{key:"getZoom",value:function(){return this.zoom}},{key:"getOrthoMatrix",value:function(){return this.orthoMatrix}},{key:"getView",value:function(){return this.view}},{key:"setEnableUpdate",value:function(t){this.enableUpdate=t}},{key:"setType",value:function(t,n){return this.type=t,this.type===Ar.EXPLORING?this.setWorldRotation(!0):this.setWorldRotation(!1),this._getAngles(),this.type===Ar.TRACKING&&n!==void 0&&this.setTrackingMode(n),this}},{key:"setProjectionMode",value:function(t){return this.projectionMode=t,this}},{key:"setTrackingMode",value:function(t){if(this.type!==Ar.TRACKING)throw new Error("Impossible to set a tracking mode if the camera is not of tracking type");return this.trackingMode=t,this}},{key:"setWorldRotation",value:function(t){return this.rotateWorld=t,this._getAngles(),this}},{key:"getViewTransform",value:function(){return Ct(Je(),this.matrix)}},{key:"getWorldTransform",value:function(){return this.matrix}},{key:"jitterProjectionMatrix",value:function(t,n){var i=ln(Je(),[t,n,0]);this.jitteredProjectionMatrix=lt(Je(),i,this.projectionMatrix)}},{key:"clearJitterProjectionMatrix",value:function(){this.jitteredProjectionMatrix=void 0}},{key:"setMatrix",value:function(t){return this.matrix=t,this._update(),this}},{key:"setProjectionMatrix",value:function(t){this.projectionMatrix=t}},{key:"setFov",value:function(t){return this.setPerspective(this.near,this.far,t,this.aspect),this}},{key:"setAspect",value:function(t){return this.setPerspective(this.near,this.far,this.fov,t),this}},{key:"setNear",value:function(t){return this.projectionMode===Wa.PERSPECTIVE?this.setPerspective(t,this.far,this.fov,this.aspect):this.setOrthographic(this.left,this.rright,this.top,this.bottom,t,this.far),this}},{key:"setFar",value:function(t){return this.projectionMode===Wa.PERSPECTIVE?this.setPerspective(this.near,t,this.fov,this.aspect):this.setOrthographic(this.left,this.rright,this.top,this.bottom,this.near,t),this}},{key:"setViewOffset",value:function(t,n,i,a,s,o){return this.aspect=t/n,this.view===void 0&&(this.view={enabled:!0,fullWidth:1,fullHeight:1,offsetX:0,offsetY:0,width:1,height:1}),this.view.enabled=!0,this.view.fullWidth=t,this.view.fullHeight=n,this.view.offsetX=i,this.view.offsetY=a,this.view.width=s,this.view.height=o,this.projectionMode===Wa.PERSPECTIVE?this.setPerspective(this.near,this.far,this.fov,this.aspect):this.setOrthographic(this.left,this.rright,this.top,this.bottom,this.near,this.far),this}},{key:"clearViewOffset",value:function(){return this.view!==void 0&&(this.view.enabled=!1),this.projectionMode===Wa.PERSPECTIVE?this.setPerspective(this.near,this.far,this.fov,this.aspect):this.setOrthographic(this.left,this.rright,this.top,this.bottom,this.near,this.far),this}},{key:"setZoom",value:function(t){return this.zoom=t,this.projectionMode===Wa.ORTHOGRAPHIC?this.setOrthographic(this.left,this.rright,this.top,this.bottom,this.near,this.far):this.projectionMode===Wa.PERSPECTIVE&&this.setPerspective(this.near,this.far,this.fov,this.aspect),this}},{key:"setZoomByViewportPoint",value:function(t,n){var i=this.canvas.viewport2Canvas({x:n[0],y:n[1]}),a=i.x,s=i.y,o=this.roll;this.rotate(0,0,-o),this.setPosition(a,s),this.setFocalPoint(a,s),this.setZoom(t),this.rotate(0,0,o);var l=this.canvas.viewport2Canvas({x:n[0],y:n[1]}),c=l.x,h=l.y,p=I(c-a,h-s,0),C=We(p,this.right)/D(this.right),k=We(p,this.up)/D(this.up),W=this.getPosition(),j=(0,m.Z)(W,2),K=j[0],Q=j[1],ee=this.getFocalPoint(),re=(0,m.Z)(ee,2),ve=re[0],he=re[1];return this.setPosition(K-C,Q-k),this.setFocalPoint(ve-C,he-k),this}},{key:"setPerspective",value:function(t,n,i,a){var s;this.projectionMode=Wa.PERSPECTIVE,this.fov=i,this.near=t,this.far=n,this.aspect=a;var o=this.near*Math.tan(Tr(.5*this.fov))/this.zoom,l=2*o,c=this.aspect*l,h=-.5*c;if((s=this.view)!==null&&s!==void 0&&s.enabled){var p=this.view.fullWidth,C=this.view.fullHeight;h+=this.view.offsetX*c/p,o-=this.view.offsetY*l/C,c*=this.view.width/p,l*=this.view.height/C}return Jw(this.projectionMatrix,h,h+c,o-l,o,t,this.far,this.clipSpaceNearZ===Uu.ZERO),Ct(this.projectionMatrixInverse,this.projectionMatrix),this.triggerUpdate(),this}},{key:"setOrthographic",value:function(t,n,i,a,s,o){var l;this.projectionMode=Wa.ORTHOGRAPHIC,this.rright=n,this.left=t,this.top=i,this.bottom=a,this.near=s,this.far=o;var c=(this.rright-this.left)/(2*this.zoom),h=(this.top-this.bottom)/(2*this.zoom),p=(this.rright+this.left)/2,C=(this.top+this.bottom)/2,k=p-c,W=p+c,j=C+h,K=C-h;if((l=this.view)!==null&&l!==void 0&&l.enabled){var Q=(this.rright-this.left)/this.view.fullWidth/this.zoom,ee=(this.top-this.bottom)/this.view.fullHeight/this.zoom;k+=Q*this.view.offsetX,W=k+Q*this.view.width,j-=ee*this.view.offsetY,K=j-ee*this.view.height}return this.clipSpaceNearZ===Uu.NEGATIVE_ONE?fr(this.projectionMatrix,k,W,j,K,s,o):yr(this.projectionMatrix,k,W,j,K,s,o),Ct(this.projectionMatrixInverse,this.projectionMatrix),this._getOrthoMatrix(),this.triggerUpdate(),this}},{key:"setPosition",value:function(t){var n=arguments.length>1&&arguments[1]!==void 0?arguments[1]:this.position[1],i=arguments.length>2&&arguments[2]!==void 0?arguments[2]:this.position[2],a=na(t,n,i);return this._setPosition(a),this.setFocalPoint(this.focalPoint),this.triggerUpdate(),this}},{key:"setFocalPoint",value:function(t){var n=arguments.length>1&&arguments[1]!==void 0?arguments[1]:this.focalPoint[1],i=arguments.length>2&&arguments[2]!==void 0?arguments[2]:this.focalPoint[2],a=I(0,1,0);if(this.focalPoint=na(t,n,i),this.trackingMode===gv.CINEMATIC){var s=Y(f(),this.focalPoint,this.position);t=s[0],n=s[1],i=s[2];var o=D(s),l=ga(Math.asin(n/o)),c=90+ga(Math.atan2(i,t)),h=Je();Kt(h,h,Tr(c)),Vt(h,h,Tr(l)),a=Ke(f(),[0,1,0],h)}return Ct(this.matrix,er(Je(),this.position,this.focalPoint,a)),this._getAxes(),this._getDistance(),this._getAngles(),this.triggerUpdate(),this}},{key:"getDistance",value:function(){return this.distance}},{key:"getDistanceVector",value:function(){return this.distanceVector}},{key:"setDistance",value:function(t){if(this.distance===t||t<0)return this;this.distance=t,this.distance<hm&&(this.distance=hm),this.dollyingStep=this.distance/100;var n=f();t=this.distance;var i=this.forward,a=this.focalPoint;return n[0]=t*i[0]+a[0],n[1]=t*i[1]+a[1],n[2]=t*i[2]+a[2],this._setPosition(n),this.triggerUpdate(),this}},{key:"setMaxDistance",value:function(t){return this.maxDistance=t,this}},{key:"setMinDistance",value:function(t){return this.minDistance=t,this}},{key:"setAzimuth",value:function(t){return this.azimuth=Bl(t),this.computeMatrix(),this._getAxes(),this.type===Ar.ORBITING||this.type===Ar.EXPLORING?this._getPosition():this.type===Ar.TRACKING&&this._getFocalPoint(),this.triggerUpdate(),this}},{key:"getAzimuth",value:function(){return this.azimuth}},{key:"setElevation",value:function(t){return this.elevation=Bl(t),this.computeMatrix(),this._getAxes(),this.type===Ar.ORBITING||this.type===Ar.EXPLORING?this._getPosition():this.type===Ar.TRACKING&&this._getFocalPoint(),this.triggerUpdate(),this}},{key:"getElevation",value:function(){return this.elevation}},{key:"setRoll",value:function(t){return this.roll=Bl(t),this.computeMatrix(),this._getAxes(),this.type===Ar.ORBITING||this.type===Ar.EXPLORING?this._getPosition():this.type===Ar.TRACKING&&this._getFocalPoint(),this.triggerUpdate(),this}},{key:"getRoll",value:function(){return this.roll}},{key:"_update",value:function(){this._getAxes(),this._getPosition(),this._getDistance(),this._getAngles(),this._getOrthoMatrix(),this.triggerUpdate()}},{key:"computeMatrix",value:function(){var t=wa(or(),[0,0,1],Tr(this.roll));Ut(this.matrix);var n=wa(or(),[1,0,0],Tr((this.rotateWorld&&this.type!==Ar.TRACKING||this.type===Ar.TRACKING?1:-1)*this.elevation)),i=wa(or(),[0,1,0],Tr((this.rotateWorld&&this.type!==Ar.TRACKING||this.type===Ar.TRACKING?1:-1)*this.azimuth)),a=Vi(or(),i,n);a=Vi(or(),a,t);var s=cr(Je(),a);this.type===Ar.ORBITING||this.type===Ar.EXPLORING?(Mt(this.matrix,this.matrix,this.focalPoint),lt(this.matrix,this.matrix,s),Mt(this.matrix,this.matrix,[0,0,this.distance])):this.type===Ar.TRACKING&&(Mt(this.matrix,this.matrix,this.position),lt(this.matrix,this.matrix,s))}},{key:"_setPosition",value:function(t,n,i){this.position=na(t,n,i);var a=this.matrix;a[12]=this.position[0],a[13]=this.position[1],a[14]=this.position[2],a[15]=1,this._getOrthoMatrix()}},{key:"_getAxes",value:function(){U(this.right,na(B(Ye(),[1,0,0,0],this.matrix))),U(this.up,na(B(Ye(),[0,1,0,0],this.matrix))),U(this.forward,na(B(Ye(),[0,0,1,0],this.matrix))),Ne(this.right,this.right),Ne(this.up,this.up),Ne(this.forward,this.forward)}},{key:"_getAngles",value:function(){var t=this.distanceVector[0],n=this.distanceVector[1],i=this.distanceVector[2],a=D(this.distanceVector);if(a===0){this.elevation=0,this.azimuth=0;return}this.type===Ar.TRACKING?(this.elevation=ga(Math.asin(n/a)),this.azimuth=ga(Math.atan2(-t,-i))):this.rotateWorld?(this.elevation=ga(Math.asin(n/a)),this.azimuth=ga(Math.atan2(-t,-i))):(this.elevation=-ga(Math.asin(n/a)),this.azimuth=-ga(Math.atan2(-t,-i)))}},{key:"_getPosition",value:function(){U(this.position,na(B(Ye(),[0,0,0,1],this.matrix))),this._getDistance()}},{key:"_getFocalPoint",value:function(){rt(this.distanceVector,[0,0,-this.distance],$i(Ti(),this.matrix)),G(this.focalPoint,this.position,this.distanceVector),this._getDistance()}},{key:"_getDistance",value:function(){this.distanceVector=Y(f(),this.focalPoint,this.position),this.distance=D(this.distanceVector),this.dollyingStep=this.distance/100}},{key:"_getOrthoMatrix",value:function(){if(this.projectionMode===Wa.ORTHOGRAPHIC){var 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i=Tr(ma(r.d[0])),[Math.cos(i),0,-Math.sin(i),0,0,1,0,0,Math.sin(i),0,Math.cos(i),0,0,0,0,1];case"rotate":case"rotateZ":return i=Tr(ma(r.d[0])),[Math.cos(i),Math.sin(i),0,0,-Math.sin(i),Math.cos(i),0,0,0,0,1,0,0,0,0,1];case"rotate3d":e=r.d[0].value,t=r.d[1].value,n=r.d[2].value,i=Tr(ma(r.d[3]));var a=e*e+t*t+n*n;if(a===0)e=1,t=0,n=0;else if(a!==1){var s=Math.sqrt(a);e/=s,t/=s,n/=s}var o=Math.sin(i/2),l=o*Math.cos(i/2),c=o*o;return[1-2*(t*t+n*n)*c,2*(e*t*c+n*l),2*(e*n*c-t*l),0,2*(e*t*c-n*l),1-2*(e*e+n*n)*c,2*(t*n*c+e*l),0,2*(e*n*c+t*l),2*(t*n*c-e*l),1-2*(e*e+t*t)*c,0,0,0,0,1];case"scale":return[r.d[0].value,0,0,0,0,r.d[1].value,0,0,0,0,1,0,0,0,0,1];case"scaleX":return[r.d[0].value,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];case"scaleY":return[1,0,0,0,0,r.d[0].value,0,0,0,0,1,0,0,0,0,1];case"scaleZ":return[1,0,0,0,0,1,0,0,0,0,r.d[0].value,0,0,0,0,1];case"scale3d":return[r.d[0].value,0,0,0,0,r.d[1].value,0,0,0,0,r.d[2].value,0,0,0,0,1];case"skew":var h=Tr(ma(r.d[0])),p=Tr(ma(r.d[1]));return[1,Math.tan(p),0,0,Math.tan(h),1,0,0,0,0,1,0,0,0,0,1];case"skewX":return i=Tr(ma(r.d[0])),[1,0,0,0,Math.tan(i),1,0,0,0,0,1,0,0,0,0,1];case"skewY":return i=Tr(ma(r.d[0])),[1,Math.tan(i),0,0,0,1,0,0,0,0,1,0,0,0,0,1];case"translate":return e=Sa(r.d[0],0,null)||0,t=Sa(r.d[1],0,null)||0,[1,0,0,0,0,1,0,0,0,0,1,0,e,t,0,1];case"translateX":return e=Sa(r.d[0],0,null)||0,[1,0,0,0,0,1,0,0,0,0,1,0,e,0,0,1];case"translateY":return t=Sa(r.d[0],0,null)||0,[1,0,0,0,0,1,0,0,0,0,1,0,0,t,0,1];case"translateZ":return n=Sa(r.d[0],0,null)||0,[1,0,0,0,0,1,0,0,0,0,1,0,0,0,n,1];case"translate3d":return e=Sa(r.d[0],0,null)||0,t=Sa(r.d[1],0,null)||0,n=Sa(r.d[2],0,null)||0,[1,0,0,0,0,1,0,0,0,0,1,0,e,t,n,1];case"perspective":var C=Sa(r.d[0],0,null)||0,k=C?-1/C:0;return[1,0,0,0,0,1,0,0,0,0,1,k,0,0,0,1];case"matrix":return[r.d[0].value,r.d[1].value,0,0,r.d[2].value,r.d[3].value,0,0,0,0,1,0,r.d[4].value,r.d[5].value,0,1];case"matrix3d":return r.d.map(function(W){return W.value})}}function dS(r,e){return[r[0]*e[0]+r[4]*e[1]+r[8]*e[2]+r[12]*e[3],r[1]*e[0]+r[5]*e[1]+r[9]*e[2]+r[13]*e[3],r[2]*e[0]+r[6]*e[1]+r[10]*e[2]+r[14]*e[3],r[3]*e[0]+r[7]*e[1]+r[11]*e[2]+r[15]*e[3],r[0]*e[4]+r[4]*e[5]+r[8]*e[6]+r[12]*e[7],r[1]*e[4]+r[5]*e[5]+r[9]*e[6]+r[13]*e[7],r[2]*e[4]+r[6]*e[5]+r[10]*e[6]+r[14]*e[7],r[3]*e[4]+r[7]*e[5]+r[11]*e[6]+r[15]*e[7],r[0]*e[8]+r[4]*e[9]+r[8]*e[10]+r[12]*e[11],r[1]*e[8]+r[5]*e[9]+r[9]*e[10]+r[13]*e[11],r[2]*e[8]+r[6]*e[9]+r[10]*e[10]+r[14]*e[11],r[3]*e[8]+r[7]*e[9]+r[11]*e[10]+r[15]*e[11],r[0]*e[12]+r[4]*e[13]+r[8]*e[14]+r[12]*e[15],r[1]*e[12]+r[5]*e[13]+r[9]*e[14]+r[13]*e[15],r[2]*e[12]+r[6]*e[13]+r[10]*e[14]+r[14]*e[15],r[3]*e[12]+r[7]*e[13]+r[11]*e[14]+r[15]*e[15]]}function vS(r){return r.length===0?[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]:r.map(fS).reduce(dS)}function Zm(r){var e=[0,0,0],t=[1,1,1],n=[0,0,0],i=[0,0,0,1],a=[0,0,0,1];return qw(vS(r),e,t,n,i,a),[[e,t,n,a,i]]}var gS=function(){function r(n,i){for(var 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a=n.createPointerEvent(i);n.dispatchEvent(a),n.freeEvent(a)}},this.onPointerCancel=function(i){var a=n.createPointerEvent(i,void 0,void 0,n.context.config.alwaysTriggerPointerEventOnCanvas?n.rootTarget:void 0);n.dispatchEvent(a),n.freeEvent(a)},this.globalRuntime=e,this.context=t}return(0,z.Z)(r,[{key:"init",value:function(){this.rootTarget=this.context.renderingContext.root.parentNode,this.addEventMapping("pointerdown",this.onPointerDown),this.addEventMapping("pointerup",this.onPointerUp),this.addEventMapping("pointermove",this.onPointerMove),this.addEventMapping("pointerout",this.onPointerOut),this.addEventMapping("pointerleave",this.onPointerOut),this.addEventMapping("pointercancel",this.onPointerCancel),this.addEventMapping("pointerover",this.onPointerOver),this.addEventMapping("pointerupoutside",this.onPointerUpOutside),this.addEventMapping("wheel",this.onWheel),this.addEventMapping("click",this.onClick)}},{key:"destroy",value:function(){this.mappingTable={},this.mappingState={},this.eventPool.clear()}},{key:"getScale",value:function(){var t=this.context.contextService.getBoundingClientRect(),n=1,i=1,a=this.context.contextService.getDomElement();if(a&&t){var s=a.offsetWidth,o=a.offsetHeight;s&&o&&(n=t.width/s,i=t.height/o)}return{scaleX:n,scaleY:i,bbox:t}}},{key:"client2Viewport",value:function(t){var n=this.getScale(),i=n.scaleX,a=n.scaleY,s=n.bbox;return new Ri((t.x-((s==null?void 0:s.left)||0))/i,(t.y-((s==null?void 0:s.top)||0))/a)}},{key:"viewport2Client",value:function(t){var n=this.getScale(),i=n.scaleX,a=n.scaleY,s=n.bbox;return new Ri((t.x+((s==null?void 0:s.left)||0))*i,(t.y+((s==null?void 0:s.top)||0))*a)}},{key:"viewport2Canvas",value:function(t){var n=t.x,i=t.y,a=this.rootTarget.defaultView,s=a.getCamera(),o=this.context.config,l=o.width,c=o.height,h=s.getPerspectiveInverse(),p=s.getWorldTransform(),C=lt(this.tmpMatrix,p,h),k=F(this.tmpVec3,n/l*2-1,(1-i/c)*2-1,0);return Ke(k,k,C),new Ri(k[0],k[1])}},{key:"canvas2Viewport",value:function(t){var n=this.rootTarget.defaultView,i=n.getCamera(),a=i.getPerspective(),s=i.getViewTransform(),o=lt(this.tmpMatrix,a,s),l=F(this.tmpVec3,t.x,t.y,0);Ke(this.tmpVec3,this.tmpVec3,o);var c=this.context.config,h=c.width,p=c.height;return new Ri((l[0]+1)/2*h,(1-(l[1]+1)/2)*p)}},{key:"setPickHandler",value:function(t){this.pickHandler=t}},{key:"addEventMapping",value:function(t,n){this.mappingTable[t]||(this.mappingTable[t]=[]),this.mappingTable[t].push({fn:n,priority:0}),this.mappingTable[t].sort(function(i,a){return i.priority-a.priority})}},{key:"mapEvent",value:function(t){if(this.rootTarget){var n=this.mappingTable[t.type];if(n)for(var i=0,a=n.length;i<a;i++)n[i].fn(t);else console.warn("[EventService]: Event mapping not defined for ".concat(t.type))}}},{key:"dispatchEvent",value:function(t,n,i){if(!i)t.propagationStopped=!1,t.propagationImmediatelyStopped=!1,this.propagate(t,n);else{t.eventPhase=t.AT_TARGET;var a=this.rootTarget.defaultView||null;t.currentTarget=a,this.notifyListeners(t,n)}}},{key:"propagate",value:function(t,n){if(t.target){var i=t.composedPath();t.eventPhase=t.CAPTURING_PHASE;for(var a=i.length-1;a>=1;a--)if(t.currentTarget=i[a],this.notifyTarget(t,n),t.propagationStopped||t.propagationImmediatelyStopped)return;if(t.eventPhase=t.AT_TARGET,t.currentTarget=t.target,this.notifyTarget(t,n),!(t.propagationStopped||t.propagationImmediatelyStopped)){var s=i.indexOf(t.currentTarget);t.eventPhase=t.BUBBLING_PHASE;for(var o=s+1;o<i.length;o++)if(t.currentTarget=i[o],this.notifyTarget(t,n),t.propagationStopped||t.propagationImmediatelyStopped)return}}}},{key:"propagationPath",value:function(t){var n=[t],i=this.rootTarget.defaultView||null;if(i&&i===t)return n.unshift(i.document),n;for(var a=0;a<MT&&t!==this.rootTarget;a++)Kr.isNode(t)&&t.parentNode&&(n.push(t.parentNode),t=t.parentNode);return i&&n.push(i),n}},{key:"hitTest",value:function(t){var n=t.viewportX,i=t.viewportY,a=this.context.config,s=a.width,o=a.height,l=a.disableHitTesting;return n<0||i<0||n>s||i>o?null:!l&&this.pickHandler(t)||this.rootTarget||null}},{key:"isNativeEventFromCanvas",value:function(t,n){var i,a=n==null?void 0:n.target;if((i=a)!==null&&i!==void 0&&i.shadowRoot&&(a=n.composedPath()[0]),a){if(a===t)return!0;if(t&&t.contains)return t.contains(a)}return n!=null&&n.composedPath?n.composedPath().indexOf(t)>-1:!1}},{key:"getExistedHTML",value:function(t){if(t.nativeEvent.composedPath)for(var n=0,i=t.nativeEvent.composedPath();n<i.length;n++){var a=i[n],s=this.nativeHTMLMap.get(a);if(s)return s}return null}},{key:"pickTarget",value:function(t){return this.hitTest({clientX:t.clientX,clientY:t.clientY,viewportX:t.viewportX,viewportY:t.viewportY,x:t.canvasX,y:t.canvasY})}},{key:"createPointerEvent",value:function(t,n,i,a){var s=this.allocateEvent(nh);this.copyPointerData(t,s),this.copyMouseData(t,s),this.copyData(t,s),s.nativeEvent=t.nativeEvent,s.originalEvent=t;var o=this.getExistedHTML(s),l=this.context.contextService.getDomElement();return s.target=i!=null?i:o||this.isNativeEventFromCanvas(l,s.nativeEvent)&&this.pickTarget(s)||a,typeof n=="string"&&(s.type=n),s}},{key:"createWheelEvent",value:function(t){var n=this.allocateEvent(Fv);this.copyWheelData(t,n),this.copyMouseData(t,n),this.copyData(t,n),n.nativeEvent=t.nativeEvent,n.originalEvent=t;var i=this.getExistedHTML(n),a=this.context.contextService.getDomElement();return n.target=i||this.isNativeEventFromCanvas(a,n.nativeEvent)&&this.pickTarget(n),n}},{key:"trackingData",value:function(t){return this.mappingState.trackingData[t]||(this.mappingState.trackingData[t]={pressTargetsByButton:{},clicksByButton:{},overTarget:null}),this.mappingState.trackingData[t]}},{key:"cloneWheelEvent",value:function(t){var n=this.allocateEvent(Fv);return n.nativeEvent=t.nativeEvent,n.originalEvent=t.originalEvent,this.copyWheelData(t,n),this.copyMouseData(t,n),this.copyData(t,n),n.target=t.target,n.path=t.composedPath().slice(),n.type=t.type,n}},{key:"clonePointerEvent",value:function(t,n){var i=this.allocateEvent(nh);return i.nativeEvent=t.nativeEvent,i.originalEvent=t.originalEvent,this.copyPointerData(t,i),this.copyMouseData(t,i),this.copyData(t,i),i.target=t.target,i.path=t.composedPath().slice(),i.type=n!=null?n:i.type,i}},{key:"copyPointerData",value:function(t,n){n.pointerId=t.pointerId,n.width=t.width,n.height=t.height,n.isPrimary=t.isPrimary,n.pointerType=t.pointerType,n.pressure=t.pressure,n.tangentialPressure=t.tangentialPressure,n.tiltX=t.tiltX,n.tiltY=t.tiltY,n.twist=t.twist}},{key:"copyMouseData",value:function(t,n){n.altKey=t.altKey,n.button=t.button,n.buttons=t.buttons,n.ctrlKey=t.ctrlKey,n.metaKey=t.metaKey,n.shiftKey=t.shiftKey,n.client.copyFrom(t.client),n.movement.copyFrom(t.movement),n.canvas.copyFrom(t.canvas),n.screen.copyFrom(t.screen),n.global.copyFrom(t.global),n.offset.copyFrom(t.offset)}},{key:"copyWheelData",value:function(t,n){n.deltaMode=t.deltaMode,n.deltaX=t.deltaX,n.deltaY=t.deltaY,n.deltaZ=t.deltaZ}},{key:"copyData",value:function(t,n){n.isTrusted=t.isTrusted,n.timeStamp=Nv.now(),n.type=t.type,n.detail=t.detail,n.view=t.view,n.page.copyFrom(t.page),n.viewport.copyFrom(t.viewport)}},{key:"allocateEvent",value:function(t){this.eventPool.has(t)||this.eventPool.set(t,[]);var n=this.eventPool.get(t).pop()||new t(this);return n.eventPhase=n.NONE,n.currentTarget=null,n.path=[],n.target=null,n}},{key:"freeEvent",value:function(t){if(t.manager!==this)throw new Error("It is illegal to free an event not managed by this EventBoundary!");var n=t.constructor;this.eventPool.has(n)||this.eventPool.set(n,[]),this.eventPool.get(n).push(t)}},{key:"notifyTarget",value:function(t,n){n=n!=null?n:t.type;var i=t.eventPhase===t.CAPTURING_PHASE||t.eventPhase===t.AT_TARGET?"".concat(n,"capture"):n;this.notifyListeners(t,i),t.eventPhase===t.AT_TARGET&&this.notifyListeners(t,n)}},{key:"notifyListeners",value:function(t,n){var i=t.currentTarget.emitter,a=i._events[n];if(a)if("fn"in a)a.once&&i.removeListener(n,a.fn,void 0,!0),a.fn.call(t.currentTarget||a.context,t);else for(var s=0;s<a.length&&!t.propagationImmediatelyStopped;s++)a[s].once&&i.removeListener(n,a[s].fn,void 0,!0),a[s].fn.call(t.currentTarget||a[s].context,t)}},{key:"findMountedTarget",value:function(t){if(!t)return null;for(var n=t[t.length-1],i=t.length-2;i>=0;i--){var a=t[i];if(a===this.rootTarget||Kr.isNode(a)&&a.parentNode===n)n=t[i];else break}return n}},{key:"getCursor",value:function(t){for(var n=t;n;){var i=WS(n)&&n.getAttribute("cursor");if(i)return i;n=Kr.isNode(n)&&n.parentNode}}}])}(),Uv=function(){function r(){(0,b.Z)(this,r)}return(0,z.Z)(r,[{key:"getOrCreateCanvas",value:function(t,n){if(this.canvas)return this.canvas;if(t||jt.offscreenCanvas)this.canvas=t||jt.offscreenCanvas,this.context=this.canvas.getContext("2d",(0,H.Z)({willReadFrequently:!0},n));else try{this.canvas=new window.OffscreenCanvas(0,0),this.context=this.canvas.getContext("2d",(0,H.Z)({willReadFrequently:!0},n)),(!this.context||!this.context.measureText)&&(this.canvas=document.createElement("canvas"),this.context=this.canvas.getContext("2d"))}catch(i){this.canvas=document.createElement("canvas"),this.context=this.canvas.getContext("2d",(0,H.Z)({willReadFrequently:!0},n))}return this.canvas.width=10,this.canvas.height=10,this.canvas}},{key:"getOrCreateContext",value:function(t,n){return this.context?this.context:(this.getOrCreateCanvas(t,n),this.context)}}],[{key:"createCanvas",value:function(){try{return new window.OffscreenCanvas(0,0)}catch(t){}try{return document.createElement("canvas")}catch(t){}return null}}])}(),Ul=function(r){return r[r.CAMERA_CHANGED=0]="CAMERA_CHANGED",r[r.DISPLAY_OBJECT_CHANGED=1]="DISPLAY_OBJECT_CHANGED",r[r.NONE=2]="NONE",r}({}),TT=function(){function r(e,t){(0,b.Z)(this,r),this.inited=!1,this.stats={total:0,rendered:0},this.zIndexCounter=0,this.hooks={init:new ra,initAsync:new rT,dirtycheck:new kv,cull:new kv,beginFrame:new ra,beforeRender:new ra,render:new ra,afterRender:new ra,endFrame:new ra,destroy:new ra,pick:new iT,pickSync:new kv,pointerDown:new ra,pointerUp:new ra,pointerMove:new ra,pointerOut:new ra,pointerOver:new ra,pointerWheel:new ra,pointerCancel:new ra,click:new ra},this.globalRuntime=e,this.context=t}return(0,z.Z)(r,[{key:"init",value:function(t){var n=this,i=(0,H.Z)((0,H.Z)({},this.globalRuntime),this.context);this.context.renderingPlugins.forEach(function(a){a.apply(i,n.globalRuntime)}),this.hooks.init.call(),this.hooks.initAsync.getCallbacksNum()===0?(this.inited=!0,t()):this.hooks.initAsync.promise().then(function(){n.inited=!0,t()}).catch(function(a){})}},{key:"getStats",value:function(){return this.stats}},{key:"disableDirtyRectangleRendering",value:function(){var t=this.context.config.renderer,n=t.getConfig(),i=n.enableDirtyRectangleRendering;return!i||this.context.renderingContext.renderReasons.has(Ul.CAMERA_CHANGED)}},{key:"render",value:function(t,n,i){var a=this;this.stats.total=0,this.stats.rendered=0,this.zIndexCounter=0;var s=this.context.renderingContext;if(this.globalRuntime.sceneGraphService.syncHierarchy(s.root),this.globalRuntime.sceneGraphService.triggerPendingEvents(),s.renderReasons.size&&this.inited){s.dirtyRectangleRenderingDisabled=this.disableDirtyRectangleRendering();var o=s.renderReasons.size===1&&s.renderReasons.has(Ul.CAMERA_CHANGED),l=!t.disableRenderHooks||!(t.disableRenderHooks&&o);l&&this.renderDisplayObject(s.root,t,s),this.hooks.beginFrame.call(n),l&&s.renderListCurrentFrame.forEach(function(c){a.hooks.beforeRender.call(c),a.hooks.render.call(c),a.hooks.afterRender.call(c)}),this.hooks.endFrame.call(n),s.renderListCurrentFrame=[],s.renderReasons.clear(),i()}}},{key:"renderDisplayObject",value:function(t,n,i){var a=this,s=n.renderer.getConfig(),o=s.enableDirtyCheck,l=s.enableCulling;function c(W){var j=W.renderable,K=W.sortable,Q=o?j.dirty||i.dirtyRectangleRenderingDisabled?W:null:W;if(Q){var ee=l?a.hooks.cull.call(Q,a.context.camera):Q;ee&&(a.stats.rendered+=1,i.renderListCurrentFrame.push(ee))}j.dirty=!1,K.renderOrder=a.zIndexCounter,a.zIndexCounter+=1,a.stats.total+=1,K.dirty&&(a.sort(W,K),K.dirty=!1,K.dirtyChildren=[],K.dirtyReason=void 0)}for(var h=[t];h.length>0;){var p=h.pop();c(p);for(var C=p.sortable.sorted||p.childNodes,k=C.length-1;k>=0;k--)h.push(C[k])}}},{key:"sort",value:function(t,n){n.sorted&&n.dirtyReason!==Hu.Z_INDEX_CHANGED?n.dirtyChildren.forEach(function(i){var a=t.childNodes.indexOf(i);if(a===-1){var s=n.sorted.indexOf(i);s>=0&&n.sorted.splice(s,1)}else if(n.sorted.length===0)n.sorted.push(i);else{var o=HS(n.sorted,i);n.sorted.splice(o,0,i)}}):n.sorted=t.childNodes.slice().sort(Jm)}},{key:"destroy",value:function(){this.inited=!1,this.hooks.destroy.call(),this.globalRuntime.sceneGraphService.clearPendingEvents()}},{key:"dirtify",value:function(){this.context.renderingContext.renderReasons.add(Ul.DISPLAY_OBJECT_CHANGED)}}])}(),AT=/\[\s*(.*)=(.*)\s*\]/,CT=function(){function r(){(0,b.Z)(this,r)}return(0,z.Z)(r,[{key:"selectOne",value:function(t,n){var i=this;if(t.startsWith("."))return n.find(function(l){return((l==null?void 0:l.classList)||[]).indexOf(i.getIdOrClassname(t))>-1});if(t.startsWith("#"))return n.find(function(l){return l.id===i.getIdOrClassname(t)});if(t.startsWith("[")){var a=this.getAttribute(t),s=a.name,o=a.value;return s?n.find(function(l){return n!==l&&(s==="name"?l.name===o:i.attributeToString(l,s)===o)}):null}return n.find(function(l){return n!==l&&l.nodeName===t})}},{key:"selectAll",value:function(t,n){var i=this;if(t.startsWith("."))return n.findAll(function(l){return n!==l&&((l==null?void 0:l.classList)||[]).indexOf(i.getIdOrClassname(t))>-1});if(t.startsWith("#"))return n.findAll(function(l){return n!==l&&l.id===i.getIdOrClassname(t)});if(t.startsWith("[")){var a=this.getAttribute(t),s=a.name,o=a.value;return s?n.findAll(function(l){return n!==l&&(s==="name"?l.name===o:i.attributeToString(l,s)===o)}):[]}return n.findAll(function(l){return n!==l&&l.nodeName===t})}},{key:"is",value:function(t,n){if(t.startsWith("."))return n.className===this.getIdOrClassname(t);if(t.startsWith("#"))return n.id===this.getIdOrClassname(t);if(t.startsWith("[")){var i=this.getAttribute(t),a=i.name,s=i.value;return a==="name"?n.name===s:this.attributeToString(n,a)===s}return n.nodeName===t}},{key:"getIdOrClassname",value:function(t){return t.substring(1)}},{key:"getAttribute",value:function(t){var n=t.match(AT),i="",a="";return n&&n.length>2&&(i=n[1].replace(/"/g,""),a=n[2].replace(/"/g,"")),{name:i,value:a}}},{key:"attributeToString",value:function(t,n){if(!t.getAttribute)return"";var i=t.getAttribute(n);return Rn(i)?"":i.toString?i.toString():""}}])}(),tr=function(r){return r.ATTR_MODIFIED="DOMAttrModified",r.INSERTED="DOMNodeInserted",r.MOUNTED="DOMNodeInsertedIntoDocument",r.REMOVED="removed",r.UNMOUNTED="DOMNodeRemovedFromDocument",r.REPARENT="reparent",r.DESTROY="destroy",r.BOUNDS_CHANGED="bounds-changed",r.CULLED="culled",r}({}),Ts=function(r){function e(t,n,i,a,s,o,l,c){var h;return(0,b.Z)(this,e),h=_(this,e,[null]),h.relatedNode=n,h.prevValue=i,h.newValue=a,h.attrName=s,h.attrChange=o,h.prevParsedValue=l,h.newParsedValue=c,h.type=t,h}return(0,g.Z)(e,r),(0,z.Z)(e)}(th);Ts.ADDITION=2,Ts.MODIFICATION=1,Ts.REMOVAL=3;function uy(r){var e=r.renderable;e&&(e.renderBoundsDirty=!0,e.boundsDirty=!0)}var OT=new Ts(tr.REPARENT,null,"","","",0,"",""),PT=rv(),rh=f(),DT=I(1,1,1),LT=Je(),RT=rv(),co=f(),Wl=Je(),uo=or(),IT=f(),NT=or(),BT=f(),Lc=f(),Qo=f(),ih=Je(),hy=or(),fy=or(),ah=or(),Wv={affectChildren:!0},kT=function(){function r(e){(0,b.Z)(this,r),this.pendingEvents=new Map,this.boundsChangedEvent=new vi(tr.BOUNDS_CHANGED),this.displayObjectDependencyMap=new WeakMap,this.runtime=e}return(0,z.Z)(r,[{key:"matches",value:function(t,n){return this.runtime.sceneGraphSelector.is(t,n)}},{key:"querySelector",value:function(t,n){return this.runtime.sceneGraphSelector.selectOne(t,n)}},{key:"querySelectorAll",value:function(t,n){return this.runtime.sceneGraphSelector.selectAll(t,n)}},{key:"attach",value:function(t,n,i){var a,s=!1;t.parentNode&&(s=t.parentNode!==n,this.detach(t));var o=t.nodeName===Rt.FRAGMENT,l=eh(n);t.parentNode=n;var c=o?t.childNodes:[t];un(i)?c.forEach(function(k){n.childNodes.splice(i,0,k),k.parentNode=n}):c.forEach(function(k){n.childNodes.push(k),k.parentNode=n});var h=n,p=h.sortable;if((p!=null&&(a=p.sorted)!==null&&a!==void 0&&a.length||t.parsedStyle.zIndex)&&(p.dirtyChildren.indexOf(t)===-1&&p.dirtyChildren.push(t),p.dirty=!0,p.dirtyReason=Hu.ADDED),!l){if(o)this.dirtifyFragment(t);else{var C=t.transformable;C&&this.dirtifyWorld(t,C)}s&&t.dispatchEvent(OT)}}},{key:"detach",value:function(t){if(t.parentNode){var n,i,a=t.transformable,s=t.parentNode,o=s.sortable;(o!=null&&(n=o.sorted)!==null&&n!==void 0&&n.length||(i=t.style)!==null&&i!==void 0&&i.zIndex)&&(o.dirtyChildren.indexOf(t)===-1&&o.dirtyChildren.push(t),o.dirty=!0,o.dirtyReason=Hu.REMOVED);var l=t.parentNode.childNodes.indexOf(t);l>-1&&t.parentNode.childNodes.splice(l,1),a&&this.dirtifyWorld(t,a),t.parentNode=null}}},{key:"getOrigin",value:function(t){return t.getGeometryBounds(),t.transformable.origin}},{key:"setOrigin",value:function(t,n){var i=arguments.length>2&&arguments[2]!==void 0?arguments[2]:0,a=arguments.length>3&&arguments[3]!==void 0?arguments[3]:0;typeof n=="number"&&(n=[n,i,a]);var s=t.transformable;if(!(n[0]===s.origin[0]&&n[1]===s.origin[1]&&n[2]===s.origin[2])){var o=s.origin;o[0]=n[0],o[1]=n[1],o[2]=n[2]||0,this.dirtifyLocal(t,s)}}},{key:"rotate",value:function(t,n){var i=arguments.length>2&&arguments[2]!==void 0?arguments[2]:0,a=arguments.length>3&&arguments[3]!==void 0?arguments[3]:0;typeof n=="number"&&(n=I(n,i,a));var s=t.transformable;if(t.parentNode===null||!t.parentNode.transformable)this.rotateLocal(t,n);else{var o=uo;Cl(o,n[0],n[1],n[2]);var l=this.getRotation(t),c=this.getRotation(t.parentNode);Ol(ah,c),Ec(ah,ah),Vi(o,ah,o),Vi(s.localRotation,o,l),xs(s.localRotation,s.localRotation),this.dirtifyLocal(t,s)}}},{key:"rotateLocal",value:function(t,n){var i=arguments.length>2&&arguments[2]!==void 0?arguments[2]:0,a=arguments.length>3&&arguments[3]!==void 0?arguments[3]:0;typeof n=="number"&&(n=I(n,i,a));var s=t.transformable;Cl(fy,n[0],n[1],n[2]),Pl(s.localRotation,s.localRotation,fy),this.dirtifyLocal(t,s)}},{key:"setEulerAngles",value:function(t,n){var i=arguments.length>2&&arguments[2]!==void 0?arguments[2]:0,a=arguments.length>3&&arguments[3]!==void 0?arguments[3]:0;typeof n=="number"&&(n=I(n,i,a));var s=t.transformable;if(t.parentNode===null||!t.parentNode.transformable)this.setLocalEulerAngles(t,n);else{Cl(s.localRotation,n[0],n[1],n[2]);var o=this.getRotation(t.parentNode);Ol(hy,Ec(uo,o)),Pl(s.localRotation,s.localRotation,hy),this.dirtifyLocal(t,s)}}},{key:"setLocalEulerAngles",value:function(t,n){var i=arguments.length>2&&arguments[2]!==void 0?arguments[2]:0,a=arguments.length>3&&arguments[3]!==void 0?arguments[3]:0,s=arguments.length>4&&arguments[4]!==void 0?arguments[4]:!0;typeof n=="number"&&(n=I(n,i,a));var o=t.transformable;Cl(o.localRotation,n[0],n[1],n[2]),s&&this.dirtifyLocal(t,o)}},{key:"translateLocal",value:function(t,n){var i=arguments.length>2&&arguments[2]!==void 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Ei({id:"g-root",style:n}),t.documentElement.ownerDocument=t,t.documentElement.parentNode=t,t.childNodes=[t.documentElement],t}return(0,g.Z)(e,r),(0,z.Z)(e,[{key:"children",get:function(){return this.childNodes}},{key:"childElementCount",get:function(){return this.childNodes.length}},{key:"firstElementChild",get:function(){return this.firstChild}},{key:"lastElementChild",get:function(){return this.lastChild}},{key:"createElement",value:function(n,i){if(n==="svg")return this.documentElement;var a=this.defaultView.customElements.get(n);a||(console.warn("Unsupported tagName: ",n),a=n==="tspan"?el:Ei);var s=new a(i);return s.ownerDocument=this,s}},{key:"createElementNS",value:function(n,i,a){return this.createElement(i,a)}},{key:"cloneNode",value:function(n){throw new Error(Sr)}},{key:"destroy",value:function(){try{this.documentElement.destroyChildren(),this.timeline.destroy()}catch(n){}}},{key:"elementsFromBBox",value:function(n,i,a,s){var o=this.defaultView.context.rBushRoot,l=o.search({minX:n,minY:i,maxX:a,maxY:s}),c=[];return l.forEach(function(h){var p=h.displayObject,C=p.parsedStyle.pointerEvents,k=C===void 0?"auto":C,W=["auto","visiblepainted","visiblefill","visiblestroke","visible"].includes(k);(!W||W&&p.isVisible())&&!p.isCulled()&&p.isInteractive()&&c.push(p)}),c.sort(function(h,p){return p.sortable.renderOrder-h.sortable.renderOrder}),c}},{key:"elementFromPointSync",value:function(n,i){var a=this.defaultView.canvas2Viewport({x:n,y:i}),s=a.x,o=a.y,l=this.defaultView.getConfig(),c=l.width,h=l.height;if(s<0||o<0||s>c||o>h)return null;var p=this.defaultView.viewport2Client({x:s,y:o}),C=p.x,k=p.y,W=this.defaultView.getRenderingService().hooks.pickSync.call({topmost:!0,position:{x:n,y:i,viewportX:s,viewportY:o,clientX:C,clientY:k},picked:[]}),j=W.picked;return j&&j[0]||this.documentElement}},{key:"elementFromPoint",value:function(){var t=(0,so.Z)((0,Ki.Z)().mark(function i(a,s){var o,l,c,h,p,C,k,W,j,K,Q;return(0,Ki.Z)().wrap(function(re){for(;;)switch(re.prev=re.next){case 0:if(o=this.defaultView.canvas2Viewport({x:a,y:s}),l=o.x,c=o.y,h=this.defaultView.getConfig(),p=h.width,C=h.height,!(l<0||c<0||l>p||c>C)){re.next=4;break}return re.abrupt("return",null);case 4:return k=this.defaultView.viewport2Client({x:l,y:c}),W=k.x,j=k.y,re.next=7,this.defaultView.getRenderingService().hooks.pick.promise({topmost:!0,position:{x:a,y:s,viewportX:l,viewportY:c,clientX:W,clientY:j},picked:[]});case 7:return K=re.sent,Q=K.picked,re.abrupt("return",Q&&Q[0]||this.documentElement);case 10:case"end":return re.stop()}},i,this)}));function n(i,a){return t.apply(this,arguments)}return n}()},{key:"elementsFromPointSync",value:function(n,i){var a=this.defaultView.canvas2Viewport({x:n,y:i}),s=a.x,o=a.y,l=this.defaultView.getConfig(),c=l.width,h=l.height;if(s<0||o<0||s>c||o>h)return[];var p=this.defaultView.viewport2Client({x:s,y:o}),C=p.x,k=p.y,W=this.defaultView.getRenderingService().hooks.pickSync.call({topmost:!1,position:{x:n,y:i,viewportX:s,viewportY:o,clientX:C,clientY:k},picked:[]}),j=W.picked;return j[j.length-1]!==this.documentElement&&j.push(this.documentElement),j}},{key:"elementsFromPoint",value:function(){var t=(0,so.Z)((0,Ki.Z)().mark(function i(a,s){var o,l,c,h,p,C,k,W,j,K,Q;return(0,Ki.Z)().wrap(function(re){for(;;)switch(re.prev=re.next){case 0:if(o=this.defaultView.canvas2Viewport({x:a,y:s}),l=o.x,c=o.y,h=this.defaultView.getConfig(),p=h.width,C=h.height,!(l<0||c<0||l>p||c>C)){re.next=4;break}return re.abrupt("return",[]);case 4:return k=this.defaultView.viewport2Client({x:l,y:c}),W=k.x,j=k.y,re.next=7,this.defaultView.getRenderingService().hooks.pick.promise({topmost:!1,position:{x:a,y:s,viewportX:l,viewportY:c,clientX:W,clientY:j},picked:[]});case 7:return K=re.sent,Q=K.picked,Q[Q.length-1]!==this.documentElement&&Q.push(this.documentElement),re.abrupt("return",Q);case 11:case"end":return re.stop()}},i,this)}));function n(i,a){return t.apply(this,arguments)}return n}()},{key:"appendChild",value:function(n,i){throw new Error(Nl)}},{key:"insertBefore",value:function(n,i){throw new Error(Nl)}},{key:"removeChild",value:function(n,i){throw new Error(Nl)}},{key:"replaceChild",value:function(n,i,a){throw new Error(Nl)}},{key:"append",value:function(){throw new Error(Nl)}},{key:"prepend",value:function(){throw new Error(Nl)}},{key:"getElementById",value:function(n){return this.documentElement.getElementById(n)}},{key:"getElementsByName",value:function(n){return this.documentElement.getElementsByName(n)}},{key:"getElementsByTagName",value:function(n){return this.documentElement.getElementsByTagName(n)}},{key:"getElementsByClassName",value:function(n){return this.documentElement.getElementsByClassName(n)}},{key:"querySelector",value:function(n){return this.documentElement.querySelector(n)}},{key:"querySelectorAll",value:function(n){return this.documentElement.querySelectorAll(n)}},{key:"find",value:function(n){return this.documentElement.find(n)}},{key:"findAll",value:function(n){return this.documentElement.findAll(n)}}])}(Kr),my=function(){function r(e){(0,b.Z)(this,r),this.strategies=e}return(0,z.Z)(r,[{key:"apply",value:function(t){var n=t.camera,i=t.renderingService,a=t.renderingContext,s=this.strategies;i.hooks.cull.tap(r.tag,function(o){if(o){var l=o.cullable;return s.length===0?l.visible=a.unculledEntities.indexOf(o.entity)>-1:l.visible=s.every(function(c){return c.isVisible(n,o)}),!o.isCulled()&&o.isVisible()?o:(o.dispatchEvent(new vi(tr.CULLED)),null)}return o}),i.hooks.afterRender.tap(r.tag,function(o){o.cullable.visibilityPlaneMask=-1})}}])}();my.tag="Culling";var yy=function(){function r(){var e=this;(0,b.Z)(this,r),this.autoPreventDefault=!1,this.rootPointerEvent=new nh(null),this.rootWheelEvent=new Fv(null),this.onPointerMove=function(t){var n,i=(n=e.context.renderingContext.root)===null||n===void 0||(n=n.ownerDocument)===null||n===void 0?void 0:n.defaultView;if(!(i.supportsTouchEvents&&t.pointerType==="touch")){var a=e.normalizeToPointerEvent(t,i),s=Ho(a),o;try{for(s.s();!(o=s.n()).done;){var l=o.value,c=e.bootstrapEvent(e.rootPointerEvent,l,i,t);e.context.eventService.mapEvent(c)}}catch(h){s.e(h)}finally{s.f()}e.setCursor(e.context.eventService.cursor)}},this.onClick=function(t){var n,i=(n=e.context.renderingContext.root)===null||n===void 0||(n=n.ownerDocument)===null||n===void 0?void 0:n.defaultView,a=e.normalizeToPointerEvent(t,i),s=Ho(a),o;try{for(s.s();!(o=s.n()).done;){var l=o.value,c=e.bootstrapEvent(e.rootPointerEvent,l,i,t);e.context.eventService.mapEvent(c)}}catch(h){s.e(h)}finally{s.f()}e.setCursor(e.context.eventService.cursor)}}return(0,z.Z)(r,[{key:"apply",value:function(t){var n=this;this.context=t;var i=t.renderingService,a=this.context.renderingContext.root.ownerDocument.defaultView;this.context.eventService.setPickHandler(function(s){var o=n.context.renderingService.hooks.pickSync.call({position:s,picked:[],topmost:!0}),l=o.picked;return l[0]||null}),i.hooks.pointerWheel.tap(r.tag,function(s){var o=n.normalizeWheelEvent(s);n.context.eventService.mapEvent(o)}),i.hooks.pointerDown.tap(r.tag,function(s){if(!(a.supportsTouchEvents&&s.pointerType==="touch")){var o=n.normalizeToPointerEvent(s,a);if(n.autoPreventDefault&&o[0].isNormalized){var l=s.cancelable||!("cancelable"in s);l&&s.preventDefault()}var c=Ho(o),h;try{for(c.s();!(h=c.n()).done;){var p=h.value,C=n.bootstrapEvent(n.rootPointerEvent,p,a,s);n.context.eventService.mapEvent(C)}}catch(k){c.e(k)}finally{c.f()}n.setCursor(n.context.eventService.cursor)}}),i.hooks.pointerUp.tap(r.tag,function(s){if(!(a.supportsTouchEvents&&s.pointerType==="touch")){var o=n.context.contextService.getDomElement(),l=n.context.eventService.isNativeEventFromCanvas(o,s),c=l?"":"outside",h=n.normalizeToPointerEvent(s,a),p=Ho(h),C;try{for(p.s();!(C=p.n()).done;){var k=C.value,W=n.bootstrapEvent(n.rootPointerEvent,k,a,s);W.type+=c,n.context.eventService.mapEvent(W)}}catch(j){p.e(j)}finally{p.f()}n.setCursor(n.context.eventService.cursor)}}),i.hooks.pointerMove.tap(r.tag,this.onPointerMove),i.hooks.pointerOver.tap(r.tag,this.onPointerMove),i.hooks.pointerOut.tap(r.tag,this.onPointerMove),i.hooks.click.tap(r.tag,this.onClick),i.hooks.pointerCancel.tap(r.tag,function(s){var o=n.normalizeToPointerEvent(s,a),l=Ho(o),c;try{for(l.s();!(c=l.n()).done;){var h=c.value,p=n.bootstrapEvent(n.rootPointerEvent,h,a,s);n.context.eventService.mapEvent(p)}}catch(C){l.e(C)}finally{l.f()}n.setCursor(n.context.eventService.cursor)})}},{key:"bootstrapEvent",value:function(t,n,i,a){t.view=i,t.originalEvent=null,t.nativeEvent=a,t.pointerId=n.pointerId,t.width=n.width,t.height=n.height,t.isPrimary=n.isPrimary,t.pointerType=n.pointerType,t.pressure=n.pressure,t.tangentialPressure=n.tangentialPressure,t.tiltX=n.tiltX,t.tiltY=n.tiltY,t.twist=n.twist,this.transferMouseData(t,n);var s=this.context.eventService.client2Viewport({x:n.clientX,y:n.clientY}),o=s.x,l=s.y;t.viewport.x=o,t.viewport.y=l;var c=this.context.eventService.viewport2Canvas(t.viewport),h=c.x,p=c.y;return t.canvas.x=h,t.canvas.y=p,t.global.copyFrom(t.canvas),t.offset.copyFrom(t.canvas),t.isTrusted=a.isTrusted,t.type==="pointerleave"&&(t.type="pointerout"),t.type.startsWith("mouse")&&(t.type=t.type.replace("mouse","pointer")),t.type.startsWith("touch")&&(t.type=KS[t.type]||t.type),t}},{key:"normalizeWheelEvent",value:function(t){var n=this.rootWheelEvent;this.transferMouseData(n,t),n.deltaMode=t.deltaMode,n.deltaX=t.deltaX,n.deltaY=t.deltaY,n.deltaZ=t.deltaZ;var i=this.context.eventService.client2Viewport({x:t.clientX,y:t.clientY}),a=i.x,s=i.y;n.viewport.x=a,n.viewport.y=s;var o=this.context.eventService.viewport2Canvas(n.viewport),l=o.x,c=o.y;return n.canvas.x=l,n.canvas.y=c,n.global.copyFrom(n.canvas),n.offset.copyFrom(n.canvas),n.nativeEvent=t,n.type=t.type,n}},{key:"transferMouseData",value:function(t,n){t.isTrusted=n.isTrusted,t.srcElement=n.srcElement,t.timeStamp=Nv.now(),t.type=n.type,t.altKey=n.altKey,t.metaKey=n.metaKey,t.shiftKey=n.shiftKey,t.ctrlKey=n.ctrlKey,t.button=n.button,t.buttons=n.buttons,t.client.x=n.clientX,t.client.y=n.clientY,t.movement.x=n.movementX,t.movement.y=n.movementY,t.page.x=n.pageX,t.page.y=n.pageY,t.screen.x=n.screenX,t.screen.y=n.screenY,t.relatedTarget=null}},{key:"setCursor",value:function(t){this.context.contextService.applyCursorStyle(t||this.context.config.cursor||"default")}},{key:"normalizeToPointerEvent",value:function(t,n){var i=[];if(n.isTouchEvent(t))for(var a=0;a<t.changedTouches.length;a++){var s=t.changedTouches[a];Gn(s.button)&&(s.button=0),Gn(s.buttons)&&(s.buttons=1),Gn(s.isPrimary)&&(s.isPrimary=t.touches.length===1&&t.type==="touchstart"),Gn(s.width)&&(s.width=s.radiusX||1),Gn(s.height)&&(s.height=s.radiusY||1),Gn(s.tiltX)&&(s.tiltX=0),Gn(s.tiltY)&&(s.tiltY=0),Gn(s.pointerType)&&(s.pointerType="touch"),Gn(s.pointerId)&&(s.pointerId=s.identifier||0),Gn(s.pressure)&&(s.pressure=s.force||.5),Gn(s.twist)&&(s.twist=0),Gn(s.tangentialPressure)&&(s.tangentialPressure=0),s.isNormalized=!0,s.type=t.type,i.push(s)}else if(n.isMouseEvent(t)){var o=t;Gn(o.isPrimary)&&(o.isPrimary=!0),Gn(o.width)&&(o.width=1),Gn(o.height)&&(o.height=1),Gn(o.tiltX)&&(o.tiltX=0),Gn(o.tiltY)&&(o.tiltY=0),Gn(o.pointerType)&&(o.pointerType="mouse"),Gn(o.pointerId)&&(o.pointerId=ZS),Gn(o.pressure)&&(o.pressure=.5),Gn(o.twist)&&(o.twist=0),Gn(o.tangentialPressure)&&(o.tangentialPressure=0),o.isNormalized=!0,i.push(o)}else i.push(t);return i}}])}();yy.tag="Event";var uA=[Rt.CIRCLE,Rt.ELLIPSE,Rt.IMAGE,Rt.RECT,Rt.LINE,Rt.POLYLINE,Rt.POLYGON,Rt.TEXT,Rt.PATH,Rt.HTML],hA=function(){function r(){(0,b.Z)(this,r)}return(0,z.Z)(r,[{key:"isVisible",value:function(t,n){var i,a=n.cullable;if(!a.enable)return!0;var s=n.getRenderBounds();if(Nr.isEmpty(s))return!1;var o=t.getFrustum(),l=(i=n.parentNode)===null||i===void 0||(i=i.cullable)===null||i===void 0?void 0:i.visibilityPlaneMask;return a.visibilityPlaneMask=this.computeVisibilityWithPlaneMask(n,s,l||Rl.INDETERMINATE,o.planes),a.visible=a.visibilityPlaneMask!==Rl.OUTSIDE,a.visible}},{key:"computeVisibilityWithPlaneMask",value:function(t,n,i,a){if(i===Rl.OUTSIDE||i===Rl.INSIDE)return i;for(var s=Rl.INSIDE,o=uA.indexOf(t.nodeName)>-1,l=0,c=a.length;l<c;++l){var h=1<<l;if(i&h&&!(o&&(l===4||l===5))){var p=a[l],C=p.normal,k=p.distance;if(We(C,n.getPositiveFarPoint(a[l]))+k<0)return Rl.OUTSIDE;We(C,n.getNegativeFarPoint(a[l]))+k<0&&(s|=h)}}return s}}])}(),_y=function(){function r(){(0,b.Z)(this,r),this.syncTasks=new Map,this.isFirstTimeRendering=!0,this.syncing=!1,this.isFirstTimeRenderingFinished=!1}return(0,z.Z)(r,[{key:"apply",value:function(t){var n=this,i,a=t.renderingService,s=t.renderingContext,o=t.rBushRoot,l=s.root.ownerDocument.defaultView;this.rBush=o;var c=function(j){var K=j.target;K.renderable.dirty=!0,a.dirtify()},h=function(j){n.syncTasks.set(j.target,j.detail.affectChildren),a.dirtify()},p=function(j){var K=j.target;jt.enableSizeAttenuation&&jt.styleValueRegistry.updateSizeAttenuation(K,l.getCamera().getZoom())},C=function(j){var K=j.target,Q=K.rBushNode;Q.aabb&&n.rBush.remove(Q.aabb),n.syncTasks.delete(K),jt.sceneGraphService.dirtifyToRoot(K),a.dirtify()};a.hooks.init.tap(r.tag,function(){l.addEventListener(tr.MOUNTED,p),l.addEventListener(tr.UNMOUNTED,C),l.addEventListener(tr.ATTR_MODIFIED,c),l.addEventListener(tr.BOUNDS_CHANGED,h)}),a.hooks.destroy.tap(r.tag,function(){l.removeEventListener(tr.MOUNTED,p),l.removeEventListener(tr.UNMOUNTED,C),l.removeEventListener(tr.ATTR_MODIFIED,c),l.removeEventListener(tr.BOUNDS_CHANGED,h),n.syncTasks.clear()});var k=(i=jt.globalThis.requestIdleCallback)!==null&&i!==void 0?i:Bv.bind(jt.globalThis);a.hooks.endFrame.tap(r.tag,function(){n.isFirstTimeRendering?(n.isFirstTimeRendering=!1,n.syncing=!0,k(function(){n.syncRTree(!0),n.isFirstTimeRenderingFinished=!0})):n.syncRTree()})}},{key:"syncNode",value:function(t){var n=arguments.length>1&&arguments[1]!==void 0?arguments[1]:!1;if(t.isConnected){var i=t.rBushNode;i.aabb&&this.rBush.remove(i.aabb);var a=t.getRenderBounds();if(a){var s=t.renderable;n&&(s.dirtyRenderBounds||(s.dirtyRenderBounds=new Nr),s.dirtyRenderBounds.update(a.center,a.halfExtents));var o=a.getMin(),l=(0,m.Z)(o,2),c=l[0],h=l[1],p=a.getMax(),C=(0,m.Z)(p,2),k=C[0],W=C[1];i.aabb||(i.aabb={}),i.aabb.displayObject=t,i.aabb.minX=c,i.aabb.minY=h,i.aabb.maxX=k,i.aabb.maxY=W}if(i.aabb&&!isNaN(i.aabb.maxX)&&!isNaN(i.aabb.maxX)&&!isNaN(i.aabb.minX)&&!isNaN(i.aabb.minY))return i.aabb}}},{key:"syncRTree",value:function(){var t=this,n=arguments.length>0&&arguments[0]!==void 0?arguments[0]:!1;if(!(!n&&(this.syncing||this.syncTasks.size===0))){this.syncing=!0;var i=[],a=new Set,s=function(l){if(!a.has(l)&&l.renderable){var c=t.syncNode(l,n);c&&(i.push(c),a.add(l))}};this.syncTasks.forEach(function(o,l){o&&l.forEach(s);for(var c=l;c;)s(c),c=c.parentElement}),this.rBush.load(i),i.length=0,this.syncing=!1}}}])}();_y.tag="Prepare";function Qz(r){return!!r.document}var Aa=function(r){return r.READY="ready",r.BEFORE_RENDER="beforerender",r.RERENDER="rerender",r.AFTER_RENDER="afterrender",r.BEFORE_DESTROY="beforedestroy",r.AFTER_DESTROY="afterdestroy",r.RESIZE="resize",r.DIRTY_RECTANGLE="dirtyrectangle",r.RENDERER_CHANGED="rendererchanged",r}({}),Ey=500,fA=.1,dA=1e3,oh=new vi(tr.MOUNTED),lh=new vi(tr.UNMOUNTED),Vv=new vi(Aa.BEFORE_RENDER),xy=new vi(Aa.RERENDER),Zv=new vi(Aa.AFTER_RENDER),Kv=function(r){function e(t){var n;(0,b.Z)(this,e),n=_(this,e),n.Element=Fr,n.inited=!1,n.context={};var i=t.container,a=t.canvas,s=t.renderer,o=t.width,l=t.height,c=t.background,h=t.cursor,p=t.supportsMutipleCanvasesInOneContainer,C=t.cleanUpOnDestroy,k=C===void 0?!0:C,W=t.offscreenCanvas,j=t.devicePixelRatio,K=t.requestAnimationFrame,Q=t.cancelAnimationFrame,ee=t.createImage,re=t.supportsTouchEvents,ve=t.supportsPointerEvents,he=t.isTouchEvent,pe=t.isMouseEvent,ye=t.dblClickSpeed,_e=o,De=l,Be=j||Iv&&window.devicePixelRatio||1;return Be=Be>=1?Math.ceil(Be):1,a&&(_e=o||GS(a)||a.width/Be,De=l||VS(a)||a.height/Be),n.customElements=new cA,n.devicePixelRatio=Be,n.requestAnimationFrame=K!=null?K:Bv.bind(jt.globalThis),n.cancelAnimationFrame=Q!=null?Q:iy.bind(jt.globalThis),n.supportsTouchEvents=re!=null?re:"ontouchstart"in jt.globalThis,n.supportsPointerEvents=ve!=null?ve:!!jt.globalThis.PointerEvent,n.isTouchEvent=he!=null?he:function(ze){return n.supportsTouchEvents&&ze instanceof jt.globalThis.TouchEvent},n.isMouseEvent=pe!=null?pe:function(ze){return!jt.globalThis.MouseEvent||ze instanceof jt.globalThis.MouseEvent&&(!n.supportsPointerEvents||!(ze instanceof jt.globalThis.PointerEvent))},W&&(jt.offscreenCanvas=W),n.document=new py,n.document.defaultView=n,p||US(i,n,k),n.initRenderingContext((0,H.Z)((0,H.Z)({},t),{},{width:_e,height:De,background:c!=null?c:"transparent",cursor:h!=null?h:"default",cleanUpOnDestroy:k,devicePixelRatio:Be,requestAnimationFrame:n.requestAnimationFrame,cancelAnimationFrame:n.cancelAnimationFrame,supportsTouchEvents:n.supportsTouchEvents,supportsPointerEvents:n.supportsPointerEvents,isTouchEvent:n.isTouchEvent,isMouseEvent:n.isMouseEvent,dblClickSpeed:ye!=null?ye:200,createImage:ee!=null?ee:function(){return new window.Image}})),n.initDefaultCamera(_e,De,s.clipSpaceNearZ),n.initRenderer(s,!0),n}return(0,g.Z)(e,r),(0,z.Z)(e,[{key:"initRenderingContext",value:function(n){this.context.config=n,this.context.renderingContext={root:this.document.documentElement,renderListCurrentFrame:[],unculledEntities:[],renderReasons:new Set,force:!1,dirty:!1}}},{key:"initDefaultCamera",value:function(n,i,a){var s=this,o=new jt.CameraContribution;o.clipSpaceNearZ=a,o.setType(Ar.EXPLORING,gv.DEFAULT).setPosition(n/2,i/2,Ey).setFocalPoint(n/2,i/2,0).setOrthographic(n/-2,n/2,i/2,i/-2,fA,dA),o.canvas=this,o.eventEmitter.on(um.UPDATED,function(){s.context.renderingContext.renderReasons.add(Ul.CAMERA_CHANGED),jt.enableSizeAttenuation&&s.getConfig().renderer.getConfig().enableSizeAttenuation&&s.updateSizeAttenuation()}),this.context.camera=o}},{key:"updateSizeAttenuation",value:function(){var n=this.getCamera().getZoom();this.document.documentElement.forEach(function(i){jt.styleValueRegistry.updateSizeAttenuation(i,n)})}},{key:"getConfig",value:function(){return this.context.config}},{key:"getRoot",value:function(){return this.document.documentElement}},{key:"getCamera",value:function(){return this.context.camera}},{key:"getContextService",value:function(){return this.context.contextService}},{key:"getEventService",value:function(){return this.context.eventService}},{key:"getRenderingService",value:function(){return this.context.renderingService}},{key:"getRenderingContext",value:function(){return this.context.renderingContext}},{key:"getStats",value:function(){return this.getRenderingService().getStats()}},{key:"ready",get:function(){var n=this;return this.readyPromise||(this.readyPromise=new Promise(function(i){n.resolveReadyPromise=function(){i(n)}}),this.inited&&this.resolveReadyPromise()),this.readyPromise}},{key:"destroy",value:function(){var n=arguments.length>0&&arguments[0]!==void 0?arguments[0]:!0,i=arguments.length>1?arguments[1]:void 0;di.clearCache(),i||this.dispatchEvent(new vi(Aa.BEFORE_DESTROY)),this.frameId&&this.cancelAnimationFrame(this.frameId);var a=this.getRoot();n&&(this.unmountChildren(a),this.document.destroy(),this.getEventService().destroy()),this.getRenderingService().destroy(),this.getContextService().destroy(),this.context.rBushRoot&&this.context.rBushRoot.clear(),i||this.dispatchEvent(new vi(Aa.AFTER_DESTROY));var s=function(l){l.currentTarget=null,l.manager=null,l.target=null,l.relatedNode=null};s(oh),s(lh),s(Vv),s(xy),s(Zv),s(As),s(Hv),s(jv),s(gy)}},{key:"changeSize",value:function(n,i){this.resize(n,i)}},{key:"resize",value:function(n,i){var a=this.context.config;a.width=n,a.height=i,this.getContextService().resize(n,i);var s=this.context.camera,o=s.getProjectionMode();s.setPosition(n/2,i/2,Ey).setFocalPoint(n/2,i/2,0),o===Wa.ORTHOGRAPHIC?s.setOrthographic(n/-2,n/2,i/2,i/-2,s.getNear(),s.getFar()):s.setAspect(n/i),this.dispatchEvent(new vi(Aa.RESIZE,{width:n,height:i}))}},{key:"appendChild",value:function(n,i){return this.document.documentElement.appendChild(n,i)}},{key:"insertBefore",value:function(n,i){return this.document.documentElement.insertBefore(n,i)}},{key:"removeChild",value:function(n){return this.document.documentElement.removeChild(n)}},{key:"removeChildren",value:function(){this.document.documentElement.removeChildren()}},{key:"destroyChildren",value:function(){this.document.documentElement.destroyChildren()}},{key:"render",value:function(n){var i=this;n&&(Vv.detail=n,Zv.detail=n),this.dispatchEvent(Vv);var a=this.getRenderingService();a.render(this.getConfig(),n,function(){i.dispatchEvent(xy)}),this.dispatchEvent(Zv)}},{key:"run",value:function(){var n=this,i=function(s,o){n.render(o),n.frameId=n.requestAnimationFrame(i)};i()}},{key:"initRenderer",value:function(n){var i=this,a=arguments.length>1&&arguments[1]!==void 0?arguments[1]:!1;if(!n)throw new Error("Renderer is required.");this.inited=!1,this.readyPromise=void 0,this.context.rBushRoot=new kw,this.context.renderingPlugins=[],this.context.renderingPlugins.push(new yy,new _y,new my([new hA])),this.loadRendererContainerModule(n),this.context.contextService=new this.context.ContextService((0,H.Z)((0,H.Z)({},jt),this.context)),this.context.renderingService=new TT(jt,this.context),this.context.eventService=new ST(jt,this.context),this.context.eventService.init(),this.context.contextService.init?(this.context.contextService.init(),this.initRenderingService(n,a,!0)):this.context.contextService.initAsync().then(function(){i.initRenderingService(n,a)}).catch(function(s){console.error(s)})}},{key:"initRenderingService",value:function(n){var i=this,a=arguments.length>1&&arguments[1]!==void 0?arguments[1]:!1,s=arguments.length>2&&arguments[2]!==void 0?arguments[2]:!1;this.context.renderingService.init(function(){i.inited=!0,a?s?i.requestAnimationFrame(function(){i.dispatchEvent(new vi(Aa.READY))}):i.dispatchEvent(new vi(Aa.READY)):i.dispatchEvent(new vi(Aa.RENDERER_CHANGED)),i.readyPromise&&i.resolveReadyPromise(),a||i.getRoot().forEach(function(o){var l=o,c=l.renderable;c&&(c.renderBoundsDirty=!0,c.boundsDirty=!0,c.dirty=!0)}),i.mountChildren(i.getRoot()),n.getConfig().enableAutoRendering&&i.run()})}},{key:"loadRendererContainerModule",value:function(n){var i=this,a=n.getPlugins();a.forEach(function(s){s.context=i.context,s.init(jt)})}},{key:"setRenderer",value:function(n){var i=this.getConfig();if(i.renderer!==n){var a=i.renderer;i.renderer=n,this.destroy(!1,!0),(0,P.Z)((a==null?void 0:a.getPlugins())||[]).reverse().forEach(function(s){s.destroy(jt)}),this.initRenderer(n)}}},{key:"setCursor",value:function(n){var i=this.getConfig();i.cursor=n,this.getContextService().applyCursorStyle(n)}},{key:"unmountChildren",value:function(n){var i=this;n.childNodes.forEach(function(a){i.unmountChildren(a)}),this.inited&&(n.isMutationObserved?n.dispatchEvent(lh):(lh.target=n,this.dispatchEvent(lh,!0)),n!==this.document.documentElement&&(n.ownerDocument=null),n.isConnected=!1),n.isCustomElement&&n.disconnectedCallback&&n.disconnectedCallback()}},{key:"mountChildren",value:function(n){var i=this,a=arguments.length>1&&arguments[1]!==void 0?arguments[1]:eh(n);this.inited?n.isConnected||(n.ownerDocument=this.document,n.isConnected=!0,a||(n.isMutationObserved?n.dispatchEvent(oh):(oh.target=n,this.dispatchEvent(oh,!0)))):console.warn("[g]: You are trying to call `canvas.appendChild` before canvas' initialization finished. You can either await `canvas.ready` or listen to `CanvasEvent.READY` manually.","appended child: ",n.nodeName),n.childNodes.forEach(function(s){i.mountChildren(s,a)}),n.isCustomElement&&n.connectedCallback&&n.connectedCallback()}},{key:"mountFragment",value:function(n){this.mountChildren(n,!1)}},{key:"client2Viewport",value:function(n){return this.getEventService().client2Viewport(n)}},{key:"viewport2Client",value:function(n){return this.getEventService().viewport2Client(n)}},{key:"viewport2Canvas",value:function(n){return this.getEventService().viewport2Canvas(n)}},{key:"canvas2Viewport",value:function(n){return this.getEventService().canvas2Viewport(n)}},{key:"getPointByClient",value:function(n,i){return this.client2Viewport({x:n,y:i})}},{key:"getClientByPoint",value:function(n,i){return this.viewport2Client({x:n,y:i})}}])}(cy);var vA=function(r){function e(){var t;(0,b.Z)(this,e);for(var n=arguments.length,i=new Array(n),a=0;a<n;a++)i[a]=arguments[a];return t=_(this,e,[].concat(i)),t.landmarks=[],t}return(0,g.Z)(e,r),(0,z.Z)(e,[{key:"rotate",value:function(n,i,a){if(this.relElevation=Bl(i),this.relAzimuth=Bl(n),this.relRoll=Bl(a),this.elevation+=this.relElevation,this.azimuth+=this.relAzimuth,this.roll+=this.relRoll,this.type===Ar.EXPLORING){var s=wa(or(),[1,0,0],Tr((this.rotateWorld?1:-1)*this.relElevation)),o=wa(or(),[0,1,0],Tr((this.rotateWorld?1:-1)*this.relAzimuth)),l=wa(or(),[0,0,1],Tr(this.relRoll)),c=Vi(or(),o,s);c=Vi(or(),c,l);var h=cr(Je(),c);Mt(this.matrix,this.matrix,[0,0,-this.distance]),lt(this.matrix,this.matrix,h),Mt(this.matrix,this.matrix,[0,0,this.distance])}else{if(Math.abs(this.elevation)>90)return this;this.computeMatrix()}return this._getAxes(),this.type===Ar.ORBITING||this.type===Ar.EXPLORING?this._getPosition():this.type===Ar.TRACKING&&this._getFocalPoint(),this._update(),this}},{key:"pan",value:function(n,i){var a=na(n,i,0),s=y(this.position);return G(s,s,de(f(),this.right,a[0])),G(s,s,de(f(),this.up,a[1])),this._setPosition(s),this.triggerUpdate(),this}},{key:"dolly",value:function(n){var i=this.forward,a=y(this.position),s=n*this.dollyingStep,o=this.distance+n*this.dollyingStep;return s=Math.max(Math.min(o,this.maxDistance),this.minDistance)-this.distance,a[0]+=s*i[0],a[1]+=s*i[1],a[2]+=s*i[2],this._setPosition(a),this.type===Ar.ORBITING||this.type===Ar.EXPLORING?this._getDistance():this.type===Ar.TRACKING&&G(this.focalPoint,a,this.distanceVector),this.triggerUpdate(),this}},{key:"cancelLandmarkAnimation",value:function(){this.landmarkAnimationID!==void 0&&this.canvas.cancelAnimationFrame(this.landmarkAnimationID)}},{key:"createLandmark",value:function(n){var i,a,s,o,l=arguments.length>1&&arguments[1]!==void 0?arguments[1]:{},c=l.position,h=c===void 0?this.position:c,p=l.focalPoint,C=p===void 0?this.focalPoint:p,k=l.roll,W=l.zoom,j=new jt.CameraContribution;j.setType(this.type,void 0),j.setPosition(h[0],(i=h[1])!==null&&i!==void 0?i:this.position[1],(a=h[2])!==null&&a!==void 0?a:this.position[2]),j.setFocalPoint(C[0],(s=C[1])!==null&&s!==void 0?s:this.focalPoint[1],(o=C[2])!==null&&o!==void 0?o:this.focalPoint[2]),j.setRoll(k!=null?k:this.roll),j.setZoom(W!=null?W:this.zoom);var K={name:n,matrix:ke(j.getWorldTransform()),right:y(j.right),up:y(j.up),forward:y(j.forward),position:y(j.getPosition()),focalPoint:y(j.getFocalPoint()),distanceVector:y(j.getDistanceVector()),distance:j.getDistance(),dollyingStep:j.getDollyingStep(),azimuth:j.getAzimuth(),elevation:j.getElevation(),roll:j.getRoll(),relAzimuth:j.relAzimuth,relElevation:j.relElevation,relRoll:j.relRoll,zoom:j.getZoom()};return this.landmarks.push(K),K}},{key:"gotoLandmark",value:function(n){var i=this,a=arguments.length>1&&arguments[1]!==void 0?arguments[1]:{},s=dr(n)?this.landmarks.find(function(ze){return ze.name===n}):n;if(s){var o=un(a)?{duration:a}:a,l=o.easing,c=l===void 0?"linear":l,h=o.duration,p=h===void 0?100:h,C=o.easingFunction,k=C===void 0?void 0:C,W=o.onfinish,j=W===void 0?void 0:W,K=o.onframe,Q=K===void 0?void 0:K,ee=.01;this.cancelLandmarkAnimation();var re=s.position,ve=s.focalPoint,he=s.zoom,pe=s.roll,ye=k||jt.EasingFunction(c),_e,De=function(){i.setFocalPoint(ve),i.setPosition(re),i.setRoll(pe),i.setZoom(he),i.computeMatrix(),i.triggerUpdate(),j==null||j()};if(p===0)return De();var Be=function(Xe){_e===void 0&&(_e=Xe);var $e=Xe-_e;if($e>=p){De();return}var ct=ye($e/p),ut=f(),St=f(),bt=1,Et=0;qe(ut,i.focalPoint,ve,ct),qe(St,i.position,re,ct),Et=i.roll*(1-ct)+pe*ct,bt=i.zoom*(1-ct)+he*ct,i.setFocalPoint(ut),i.setPosition(St),i.setRoll(Et),i.setZoom(bt);var xt=tt(ut,ve)+tt(St,re);if(xt<=ee&&he===void 0&&pe===void 0)return De();i.computeMatrix(),i.triggerUpdate(),$e<p&&(Q==null||Q(ct),i.landmarkAnimationID=i.canvas.requestAnimationFrame(Be))};this.canvas.requestAnimationFrame(Be)}}}])}(fm);jt.CameraContribution=vA;var by=null,Jz=0,wy=new WeakMap,qz=null,$z=null,ch,Hs;function eF(r,e){return ch=new by(r,e)}function tF(r){return Hs||(Hs=by.copy(ch),Hs.oldValue=r,Hs)}function nF(){ch=Hs=void 0}function gA(r){return r===Hs||r===ch}function rF(r,e){return r===e?r:Hs&&gA(r)?Hs:null}function pA(r){r.nodes.forEach(function(e){var t=wy.get(e);t&&t.forEach(function(n){n.observer===r&&n.removeTransientObservers()})})}function iF(r,e){for(var t=r;t;t=t.parentNode){var n=wy.get(t);if(n)for(var i=0;i<n.length;i++){var a=n[i],s=a.options;if(!(t!==r&&!s.subtree)){var o=e(s);o&&a.enqueue(o)}}}}var Xv=!1,Yv=null;function aF(r){Yv.push(r),Xv||(Xv=!0,typeof runtime.globalThis!="undefined"?runtime.globalThis.setTimeout(Qv):Qv())}function Qv(){Xv=!1;var r=Yv;Yv=[],r.sort(function(t,n){return t.uid-n.uid});var e=!1;r.forEach(function(t){var n=t.takeRecords();pA(t),n.length&&(t.callback(n,t),e=!0)}),e&&Qv()}var Jv=function(r){function e(t,n,i,a){var s;return(0,b.Z)(this,e),s=_(this,e,[t]),s.currentTime=i,s.timelineTime=a,s.target=n,s.type="finish",s.bubbles=!1,s.currentTarget=n,s.defaultPrevented=!1,s.eventPhase=s.AT_TARGET,s.timeStamp=Date.now(),s.currentTime=i,s.timelineTime=a,s}return(0,g.Z)(e,r),(0,z.Z)(e)}(th),mA=0,yA=function(){function r(e,t){var n;(0,b.Z)(this,r),this.currentTimePending=!1,this._idle=!0,this._paused=!1,this._finishedFlag=!0,this._currentTime=0,this._playbackRate=1,this._inTimeline=!0,this.effect=e,e.animation=this,this.timeline=t,this.id="".concat(mA++),this._inEffect=!!this.effect.update(0),this._totalDuration=Number((n=this.effect)===null||n===void 0?void 0:n.getComputedTiming().endTime),this._holdTime=0,this._paused=!1,this.oldPlayState="idle",this.updatePromises()}return(0,z.Z)(r,[{key:"pending",get:function(){return this._startTime===null&&!this._paused&&this.playbackRate!==0||this.currentTimePending}},{key:"playState",get:function(){return this._idle?"idle":this._isFinished?"finished":this._paused?"paused":"running"}},{key:"ready",get:function(){var t=this;return this.readyPromise||(this.timeline.animationsWithPromises.indexOf(this)===-1&&this.timeline.animationsWithPromises.push(this),this.readyPromise=new Promise(function(n,i){t.resolveReadyPromise=function(){n(t)},t.rejectReadyPromise=function(){i(new Error)}}),this.pending||this.resolveReadyPromise()),this.readyPromise}},{key:"finished",get:function(){var t=this;return this.finishedPromise||(this.timeline.animationsWithPromises.indexOf(this)===-1&&this.timeline.animationsWithPromises.push(this),this.finishedPromise=new Promise(function(n,i){t.resolveFinishedPromise=function(){n(t)},t.rejectFinishedPromise=function(){i(new Error)}}),this.playState==="finished"&&this.resolveFinishedPromise()),this.finishedPromise}},{key:"currentTime",get:function(){return this.updatePromises(),this._idle||this.currentTimePending?null:this._currentTime},set:function(t){if(t=Number(t),!isNaN(t)){if(this.timeline.restart(),!this._paused&&this._startTime!==null){var n;this._startTime=Number((n=this.timeline)===null||n===void 0?void 0:n.currentTime)-t/this.playbackRate}this.currentTimePending=!1,this._currentTime!==t&&(this._idle&&(this._idle=!1,this._paused=!0),this.tickCurrentTime(t,!0),this.timeline.applyDirtiedAnimation(this))}}},{key:"startTime",get:function(){return this._startTime},set:function(t){if(t!==null){if(this.updatePromises(),t=Number(t),isNaN(t)||this._paused||this._idle)return;this._startTime=t,this.tickCurrentTime((Number(this.timeline.currentTime)-this._startTime)*this.playbackRate),this.timeline.applyDirtiedAnimation(this),this.updatePromises()}}},{key:"playbackRate",get:function(){return this._playbackRate},set:function(t){if(t!==this._playbackRate){this.updatePromises();var n=this.currentTime;this._playbackRate=t,this.startTime=null,this.playState!=="paused"&&this.playState!=="idle"&&(this._finishedFlag=!1,this._idle=!1,this.ensureAlive(),this.timeline.applyDirtiedAnimation(this)),n!==null&&(this.currentTime=n),this.updatePromises()}}},{key:"_isFinished",get:function(){return!this._idle&&(this._playbackRate>0&&Number(this._currentTime)>=this._totalDuration||this._playbackRate<0&&Number(this._currentTime)<=0)}},{key:"totalDuration",get:function(){return this._totalDuration}},{key:"_needsTick",get:function(){return this.pending||this.playState==="running"||!this._finishedFlag}},{key:"updatePromises",value:function(){var t=this.oldPlayState,n=this.pending?"pending":this.playState;return this.readyPromise&&n!==t&&(n==="idle"?(this.rejectReadyPromise(),this.readyPromise=void 0):t==="pending"?this.resolveReadyPromise():n==="pending"&&(this.readyPromise=void 0)),this.finishedPromise&&n!==t&&(n==="idle"?(this.rejectFinishedPromise(),this.finishedPromise=void 0):n==="finished"?this.resolveFinishedPromise():t==="finished"&&(this.finishedPromise=void 0)),this.oldPlayState=n,this.readyPromise||this.finishedPromise}},{key:"play",value:function(){this.updatePromises(),this._paused=!1,(this._isFinished||this._idle)&&(this.rewind(),this._startTime=null),this._finishedFlag=!1,this._idle=!1,this.ensureAlive(),this.timeline.applyDirtiedAnimation(this),this.timeline.animations.indexOf(this)===-1&&this.timeline.animations.push(this),this.updatePromises()}},{key:"pause",value:function(){this.updatePromises(),this.currentTime&&(this._holdTime=this.currentTime),!this._isFinished&&!this._paused&&!this._idle?this.currentTimePending=!0:this._idle&&(this.rewind(),this._idle=!1),this._startTime=null,this._paused=!0,this.updatePromises()}},{key:"finish",value:function(){this.updatePromises(),!this._idle&&(this.currentTime=this._playbackRate>0?this._totalDuration:0,this._startTime=this._totalDuration-this.currentTime,this.currentTimePending=!1,this.timeline.applyDirtiedAnimation(this),this.updatePromises())}},{key:"cancel",value:function(){var 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t=this.targetAnimations(),n=t.indexOf(this);n!==-1&&t.splice(n,1)}},{key:"tick",value:function(t,n){!this._idle&&!this._paused&&(this._startTime===null?n&&(this.startTime=t-this._currentTime/this.playbackRate):this._isFinished||this.tickCurrentTime((t-this._startTime)*this.playbackRate)),n&&(this.currentTimePending=!1,this.fireEvents(t))}},{key:"rewind",value:function(){if(this.playbackRate>=0)this.currentTime=0;else if(this._totalDuration<1/0)this.currentTime=this._totalDuration;else throw new Error("Unable to rewind negative playback rate animation with infinite duration")}},{key:"persist",value:function(){throw new Error(Sr)}},{key:"addEventListener",value:function(t,n,i){throw new Error(Sr)}},{key:"removeEventListener",value:function(t,n,i){throw new Error(Sr)}},{key:"dispatchEvent",value:function(t){throw new Error(Sr)}},{key:"commitStyles",value:function(){throw new Error(Sr)}},{key:"ensureAlive",value:function(){if(this.playbackRate<0&&this.currentTime===0){var 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Dt=xt.node,Ft=xt.clusterId;Dt&&(Dt.clusterId=Ft,Dt.clusterId&&ct[Dt.clusterId]&&(Dt.clusterId=ct[Dt.clusterId]))});var St=[],bt={};k.forEach(function(xt){var Dt=xt.source,Ft=xt.target,Xt=xt[n]||1,an=re[Dt].node.clusterId,dn=re[Ft].node.clusterId;if(!(!an||!dn)){var sn="".concat(an,"---").concat(dn);if(bt[sn])bt[sn].weight+=Xt,bt[sn].count++;else{var Tn={source:an,target:dn,weight:Xt,count:1};bt[sn]=Tn,St.push(Tn)}}});var Et=[];return Object.keys(Xe).forEach(function(xt){Et.push(Xe[xt])}),{clusters:Et,clusterEdges:St}},v1=SO,TO=function(e,t,n,i,a,s,o,l){return t===void 0&&(t=!1),n===void 0&&(n="weight"),i===void 0&&(i=1e-4),a===void 0&&(a=void 0),s===void 0&&(s=[]),o===void 0&&(o=["id"]),l===void 0&&(l=1),v1(e,t,n,i,!0,a,s,o,l)},AO=TO,CO=function(e,t){var n;t===void 0&&(t=1);for(var i=Vc(e),a=i.nodes,s=a===void 0?[]:a,o=i.edges,l=o===void 0?[]:o,c=function(){var C=cg({nodes:s,edges:l}),k=Object.keys(C);k.sort(function(K,Q){var ee,re;return((ee=C[K])===null||ee===void 0?void 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t,n=e,i=this.getLeft(e),a=this.getRight(e),s=this.list.length;i!==null&&i<s&&this.compareFn(this.list[n],this.list[i])>0?n=i:a!==null&&a<s&&this.compareFn(this.list[n],this.list[a])>0&&(n=a),e!==n&&(t=[this.list[n],this.list[e]],this.list[e]=t[0],this.list[n]=t[1],this.moveDown(n))},r}(),FO=zO,UO=function(e,t){var n=[],i=e.nodes,a=i===void 0?[]:i,s=e.edges,o=s===void 0?[]:s;if(a.length===0)return n;var l=a[0],c=new Set;c.add(l);var h=function(K,Q){return t?K.weight-Q.weight:0},p=new FO(h);for(Ph(l.id,o).forEach(function(j){p.insert(j)});!p.isEmpty();){var C=p.delMin(),k=C.source,W=C.target;c.has(k)&&c.has(W)||(n.push(C),c.has(k)||(c.add(k),Ph(k,o).forEach(function(j){p.insert(j)})),c.has(W)||(c.add(W),Ph(W,o).forEach(function(j){p.insert(j)})))}return n},m1=function(e,t){var n=[],i=e.nodes,a=i===void 0?[]:i,s=e.edges,o=s===void 0?[]:s;if(a.length===0)return n;var l=o.map(function(k){return k});t&&l.sort(function(k,W){return k.weight-W.weight});for(var c=new BO(a.map(function(k){return 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r(e,t){e===void 0&&(e=kh),t===void 0&&(t=Ds),this.id=e,this.label=t,this.edges=[],this.edgeMap={}}return r.prototype.addEdge=function(e){this.edges.push(e),this.edgeMap[e.id]=e},r}(),b1=function(){function r(e,t,n){e===void 0&&(e=kh),t===void 0&&(t=!0),n===void 0&&(n=!1),this.id=e,this.edgeIdAutoIncrease=t,this.edges=[],this.nodes=[],this.nodeMap={},this.edgeMap={},this.nodeLabelMap={},this.edgeLabelMap={},this.counter=0,this.directed=n}return r.prototype.getNodeNum=function(){return this.nodes.length},r.prototype.addNode=function(e,t){if(!this.nodeMap[e]){var n=new VO(e,t);this.nodes.push(n),this.nodeMap[e]=n,this.nodeLabelMap[t]||(this.nodeLabelMap[t]=[]),this.nodeLabelMap[t].push(e)}},r.prototype.addEdge=function(e,t,n,i){if((this.edgeIdAutoIncrease||e===void 0)&&(e=this.counter++),!(this.nodeMap[t]&&this.nodeMap[n]&&this.nodeMap[n].edgeMap[e])){var a=new 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t=e.edge;this.edges.push(t),this.nodesUsed[t.from]=1,this.nodesUsed[t.to]=1,this.edgesUsed[t.id]=1,e=e.preNode}this.edges=this.edges.reverse()}}return r.prototype.hasNode=function(e){return this.nodesUsed[e.id]===1},r.prototype.hasEdge=function(e){return this.edgesUsed[e.id]===1},r}(),ZO=function(){function r(e){var t=e.graphs,n=e.minSupport,i=n===void 0?2:n,a=e.minNodeNum,s=a===void 0?1:a,o=e.maxNodeNum,l=o===void 0?4:o,c=e.top,h=c===void 0?10:c,p=e.directed,C=p===void 0?!1:p,k=e.verbose,W=k===void 0?!1:k;this.graphs=t,this.dfsCode=new w1,this.support=0,this.frequentSize1Subgraphs=[],this.frequentSubgraphs=[],this.minSupport=i,this.top=h,this.directed=C,this.counter=0,this.maxNodeNum=l,this.minNodeNum=s,this.verbose=W,this.maxNodeNum<this.minNodeNum&&(this.maxNodeNum=this.minNodeNum),this.reportDF=[]}return r.prototype.findForwardRootEdges=function(e,t){var n=this,i=[],a=e.nodeMap;return t.edges.forEach(function(s){(n.directed||t.label<=a[s.to].label)&&i.push(s)}),i},r.prototype.findBackwardEdge=function(e,t,n,i){if(!this.directed&&t===n)return null;for(var a=e.nodeMap,s=a[n.to],o=s.edges,l=o.length,c=0;c<l;c++){var h=o[c];if(!(i.hasEdge(h)||h.to!==t.from)){if(this.directed){if(a[t.from].label<a[n.to].label||a[t.from].label===a[n.to].label&&t.label<=h.label)return h}else if(t.label<h.label||t.label===h.label&&a[t.to].label<=a[n.to].label)return h}}return null},r.prototype.findForwardPureEdges=function(e,t,n,i){for(var a=[],s=t.to,o=e.nodeMap[s].edges,l=o.length,c=0;c<l;c++){var h=o[c],p=e.nodeMap[h.to];n<=p.label&&!i.hasNode(p)&&a.push(h)}return a},r.prototype.findForwardRmpathEdges=function(e,t,n,i){for(var a=[],s=e.nodeMap,o=s[t.to].label,l=s[t.from],c=l.edges,h=c.length,p=0;p<h;p++){var C=c[p],k=s[C.to].label;t.to===C.to||n>k||i.hasNode(s[C.to])||(t.label<C.label||t.label===C.label&&o<=k)&&a.push(C)}return a},r.prototype.getSupport=function(e){var t={};return e.forEach(function(n){t[n.graphId]||(t[n.graphId]=!0)}),Object.keys(t).length},r.prototype.findMinLabel=function(e){var t=void 0;return Object.keys(e).forEach(function(n){var i=e[n],a=i.nodeLabel1,s=i.edgeLabel,o=i.nodeLabel2;if(!t){t={nodeLabel1:a,edgeLabel:s,nodeLabel2:o};return}(a<t.nodeLabel1||a===t.nodeLabel1&&s<t.edgeLabel||a===t.nodeLabel1&&s===t.edgeLabel&&o<t.nodeLabel2)&&(t={nodeLabel1:a,edgeLabel:s,nodeLabel2:o})}),t},r.prototype.isMin=function(){var e=this,t=this.dfsCode;if(this.verbose&&console.log("isMin checking",t),t.dfsEdgeList.length===1)return!0;var n=this.directed,i=t.toGraph(E1,n),a=i.nodeMap,s=new w1,o={};i.nodes.forEach(function(p){var C=e.findForwardRootEdges(i,p);C.forEach(function(k){var W=a[k.to],j="".concat(p.label,"-").concat(k.label,"-").concat(W.label);o[j]||(o[j]={projected:[],nodeLabel1:p.label,edgeLabel:k.label,nodeLabel2:W.label});var K={graphId:i.id,edge:k,preNode:null};o[j].projected.push(K)})});var l=this.findMinLabel(o);if(l){s.dfsEdgeList.push(new rl(0,1,l.nodeLabel1,l.edgeLabel,l.nodeLabel2));var c=function p(C){for(var k=s.buildRmpath(),W=s.dfsEdgeList[0].nodeEdgeNodeLabel.nodeLabel1,j=s.dfsEdgeList[k[0]].toNode,K={},Q=!1,ee=0,re=n?-1:0,ve=function(bt){if(Q)return"break";C.forEach(function(Et){var xt=new zh(Et),Dt=e.findBackwardEdge(i,xt.edges[k[bt]],xt.edges[k[0]],xt);Dt&&(K[Dt.label]||(K[Dt.label]={projected:[],edgeLabel:Dt.label}),K[Dt.label].projected.push({graphId:i.id,edge:K,preNode:Et}),ee=s.dfsEdgeList[k[bt]].fromNode,Q=!0)})},he=k.length-1;he>re;he--){var pe=ve(he);if(pe==="break")break}if(Q){var ye=e.findMinLabel(K);s.dfsEdgeList.push(new rl(j,ee,Ds,ye.edgeLabel,Ds));var _e=s.dfsEdgeList.length-1;return e.dfsCode.dfsEdgeList[_e]!==s.dfsEdgeList[_e]?!1:p(K[ye.edgeLabel].projected)}var De={};Q=!1;var Be=0;C.forEach(function(St){var bt=new zh(St),Et=e.findForwardPureEdges(i,bt.edges[k[0]],W,bt);Et.length>0&&(Q=!0,Be=j,Et.forEach(function(xt){var Dt="".concat(xt.label,"-").concat(a[xt.to].label);De[Dt]||(De[Dt]={projected:[],edgeLabel:xt.label,nodeLabel2:a[xt.to].label}),De[Dt].projected.push({graphId:i.id,edge:xt,preNode:St})}))});for(var ze=k.length,Xe=function(bt){if(Q)return"break";var Et=k[bt];C.forEach(function(xt){var Dt=new zh(xt),Ft=e.findForwardRmpathEdges(i,Dt.edges[Et],W,Dt);Ft.length>0&&(Q=!0,Be=s.dfsEdgeList[Et].fromNode,Ft.forEach(function(Xt){var an="".concat(Xt.label,"-").concat(a[Xt.to].label);De[an]||(De[an]={projected:[],edgeLabel:Xt.label,nodeLabel2:a[Xt.to].label}),De[an].projected.push({graphId:i.id,edge:Xt,preNode:xt})}))})},he=0;he<ze;he++){var $e=Xe(he);if($e==="break")break}if(!Q)return!0;var ct=e.findMinLabel(De);s.dfsEdgeList.push(new rl(Be,j+1,Ds,ct.edgeLabel,ct.nodeLabel2));var ut=s.dfsEdgeList.length-1;return t.dfsEdgeList[ut]!==s.dfsEdgeList[ut]?!1:p(De["".concat(ct.edgeLabel,"-").concat(ct.nodeLabel2)].projected)},h="".concat(l.nodeLabel1,"-").concat(l.edgeLabel,"-").concat(l.nodeLabel2);return c(o[h].projected)}},r.prototype.report=function(){if(!(this.dfsCode.getNodeNum()<this.minNodeNum)){this.counter++;var e=this.dfsCode.toGraph(this.counter,this.directed);this.frequentSubgraphs.push(Vc(e))}},r.prototype.subGraphMining=function(e){var t=this,n=this.getSupport(e);if(!(n<this.minSupport)&&this.isMin()){this.report();var i=this.dfsCode.getNodeNum(),a=this.dfsCode.buildRmpath(),s=this.dfsCode.dfsEdgeList[a[0]].toNode,o=this.dfsCode.dfsEdgeList[0].nodeEdgeNodeLabel.nodeLabel1,l={},c={};e.forEach(function(h){for(var p=t.graphs[h.graphId],C=p.nodeMap,k=new zh(h),W=a.length-1;W>=0;W--){var j=t.findBackwardEdge(p,k.edges[a[W]],k.edges[a[0]],k);if(j){var K="".concat(t.dfsCode.dfsEdgeList[a[W]].fromNode,"-").concat(j.label);c[K]||(c[K]={projected:[],toNodeId:t.dfsCode.dfsEdgeList[a[W]].fromNode,edgeLabel:j.label}),c[K].projected.push({graphId:h.graphId,edge:j,preNode:h})}}if(!(i>=t.maxNodeNum)){var Q=t.findForwardPureEdges(p,k.edges[a[0]],o,k);Q.forEach(function(re){var ve="".concat(s,"-").concat(re.label,"-").concat(C[re.to].label);l[ve]||(l[ve]={projected:[],fromNodeId:s,edgeLabel:re.label,nodeLabel2:C[re.to].label}),l[ve].projected.push({graphId:h.graphId,edge:re,preNode:h})});for(var ee=function(ve){var he=t.findForwardRmpathEdges(p,k.edges[a[ve]],o,k);he.forEach(function(pe){var ye="".concat(t.dfsCode.dfsEdgeList[a[ve]].fromNode,"-").concat(pe.label,"-").concat(C[pe.to].label);l[ye]||(l[ye]={projected:[],fromNodeId:t.dfsCode.dfsEdgeList[a[ve]].fromNode,edgeLabel:pe.label,nodeLabel2:C[pe.to].label}),l[ye].projected.push({graphId:h.graphId,edge:pe,preNode:h})})},W=0;W<a.length;W++)ee(W)}}),Object.keys(c).forEach(function(h){var p=c[h],C=p.toNodeId,k=p.edgeLabel;t.dfsCode.dfsEdgeList.push(new rl(s,C,"-1",k,"-1")),t.subGraphMining(c[h].projected),t.dfsCode.dfsEdgeList.pop()}),Object.keys(l).forEach(function(h){var p=l[h],C=p.fromNodeId,k=p.edgeLabel,W=p.nodeLabel2;t.dfsCode.dfsEdgeList.push(new rl(C,s+1,Ds,k,W)),t.subGraphMining(l[h].projected),t.dfsCode.dfsEdgeList.pop()})}},r.prototype.generate1EdgeFrequentSubGraphs=function(){var e=this.graphs,t=this.directed,n=this.minSupport,i=this.frequentSize1Subgraphs,a={},s={},o={},l={};return Object.keys(e).forEach(function(c){var h=e[c],p=h.nodeMap;h.nodes.forEach(function(C,k){var W=C.label,j="".concat(c,"-").concat(W);if(!o[j]){var K=a[W]||0;K++,a[W]=K}o[j]={graphKey:c,label:W},C.edges.forEach(function(Q){var ee=W,re=p[Q.to].label;if(!t&&ee>re){var ve=re;re=ee,ee=ve}var he=Q.label,pe="".concat(c,"-").concat(ee,"-").concat(he,"-").concat(re),ye="".concat(ee,"-").concat(he,"-").concat(re);if(!s[ye]){var _e=s[ye]||0;_e++,s[ye]=_e}l[pe]={graphId:c,nodeLabel1:ee,edgeLabel:he,nodeLabel2:re}})})}),Object.keys(a).forEach(function(c){var h=a[c];if(!(h<n)){var p={nodes:[],edges:[]};p.nodes.push({id:"0",label:c}),i.push(p)}}),i},r.prototype.run=function(){var e=this;if(this.frequentSize1Subgraphs=this.generate1EdgeFrequentSubGraphs(),!(this.maxNodeNum<2)){var t=this.graphs,n=this.directed,i={};Object.keys(t).forEach(function(a){var s=t[a],o=s.nodeMap;s.nodes.forEach(function(l){var c=e.findForwardRootEdges(s,l);c.forEach(function(h){var p=o[h.to],C="".concat(l.label,"-").concat(h.label,"-").concat(p.label);i[C]||(i[C]={projected:[],nodeLabel1:l.label,edgeLabel:h.label,nodeLabel2:p.label});var k={graphId:a,edge:h,preNode:null};i[C].projected.push(k)})})}),Object.keys(i).forEach(function(a){var s=i[a],o=s.projected,l=s.nodeLabel1,c=s.edgeLabel,h=s.nodeLabel2;e.dfsCode.dfsEdgeList.push(new rl(0,1,l,c,h)),e.subGraphMining(o),e.dfsCode.dfsEdgeList.pop()})}},r}(),KO=function(e,t,n,i){var a={};return Object.keys(e).forEach(function(s,o){var l=e[s],c=new b1(o,!0,t),h={};l.nodes.forEach(function(p,C){c.addNode(C,p[n]),h[p.id]=C}),l.edges.forEach(function(p,C){var k=h[p.source],W=h[p.target];c.addEdge(-1,k,W,p[i])}),c&&c.getNodeNum()&&(a[c.id]=c)}),a},XO=function(e,t,n){var i=[];return e.forEach(function(a){var s={nodes:[],edges:[]};a.nodes.forEach(function(o){var l;s.nodes.push((l={id:"".concat(o.id)},l[t]=o.label,l))}),a.edges.forEach(function(o){var l;s.edges.push((l={source:"".concat(o.from),target:"".concat(o.to)},l[n]=o.label,l))}),i.push(s)}),i},M1="cluster",YO=function(e){var t=e.graphs,n=e.directed,i=n===void 0?!1:n,a=e.nodeLabelProp,s=a===void 0?M1:a,o=e.edgeLabelProp,l=o===void 0?M1:o,c=KO(t,i,s,l),h=e.minSupport,p=e.maxNodeNum,C=e.minNodeNum,k=e.verbose,W=e.top,j={graphs:c,minSupport:h,maxNodeNum:p,minNodeNum:C,top:W,verbose:k,directed:i},K=new ZO(j);K.run();var Q=XO(K.frequentSubgraphs,s,l);return Q},QO=YO,S1=function(e,t,n,i){n===void 0&&(n="cluster"),i===void 0&&(i=2);var a=[],s=e.nodes;return t.forEach(function(o,l){a.push(T1(s,o,l,n,i))}),a},T1=function(e,t,n,i,a){var s=[n],o=[],l={};return t.forEach(function(c,h){if(c<=a&&n!==h){s.push(h),o.push(e[h]);var p=e[h][i];l[p]?(l[p].count++,l[p].dists.push(c)):l[p]={count:1,dists:[c]}}}),Object.keys(l).forEach(function(c){l[c].dists=l[c].dists.sort(function(h,p){return h-p})}),{nodeIdx:n,nodeId:e[n].id,nodeIdxs:s,neighbors:o,neighborNum:s.length-1,nodeLabelCountMap:l}},JO=function(e,t,n,i,a){var s=Math.ceil(n/t),o={},l=0;return i.forEach(function(c,h){for(var p=0,C=0,k=c.nodeIdxs,W=c.neighborNum-1;p<s;){for(var j=k[1+Math.floor(Math.random()*W)],K=0;(o["".concat(h,"-").concat(j)]||o["".concat(j,"-").concat(h)])&&(j=Math.floor(Math.random()*t),K++,!(K>2*t)););if(K<2*t&&(o["".concat(h,"-").concat(j)]={start:h,end:j,distance:a[h][j]},p++,l++,l>=n))return o;if(C++,C>2*t)break}if(p<s){var Q=s-p;s=(s+Q)/(t-h-1)}}),o},Fh=function(e,t,n,i){var a=n.nodes;return i||(i={}),Object.keys(e).forEach(function(s){var o,l;if(!(i&&i[s])){i[s]={nodes:[],edges:[]};var c=e[s],h=(o=t[c.start])===null||o===void 0?void 0:o.nodeIdxs,p=(l=t[c.end])===null||l===void 0?void 0:l.nodeIdxs;if(!(!h||!p)){var C=new Set(p),k=h.filter(function(ee){return C.has(ee)});if(!(!k||!k.length)){for(var W={},j=k.length,K=0;K<j;K++){var Q=a[k[K]];i[s].nodes.push(Q),W[Q.id]=!0}n.edges.forEach(function(ee){W[ee.source]&&W[ee.target]&&i[s].edges.push(ee)})}}}}),i},Uh=function(e,t,n,i){var a,s,o={};e.nodes.forEach(function(c){o[c.id]=c});var l=0;return!(!((a=t==null?void 0:t.edges)===null||a===void 0)&&a.length)||((s=t==null?void 0:t.nodes)===null||s===void 0?void 0:s.length)<2?0:(e.edges.forEach(function(c){var h=o[c.source][n],p=o[c.target][n],C=t==null?void 0:t.nodes[0][n],k=t==null?void 0:t.nodes[1][n],W=t==null?void 0:t.edges[0][i];c[i]===W&&(h===C&&p===k||h===k&&p===C)&&l++}),l)},qO=function(e,t,n){for(var i=1/0,a=0,s=function(c){var h=e[c],p=Object.keys(h).sort(function(ee,re){return 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c=n[s.source];c&&(c.degree++,c.outDegree++);var h=n[s.target];h&&(h.degree++,h.inDegree++)}),{edgeMap:i,edgeLabelMap:a}},O1=function(e,t,n){var i=t.length,a={};return t.forEach(function(s,o){for(var l=n?0:o+1,c=e[o].id,h=l;h<i;h++)if(o!==h){var p=e[h].id,C=s[h];a["".concat(c,"-").concat(p)]=C,n||(a["".concat(p,"-").concat(c)]=C)}}),a},$O=function(e,t,n,i,a,s,o,l,c,h,p){var C,k="".concat(t.id,"-").concat(n.id);if(h&&h[k])return h[k];var W=p?p[k]:void 0;if(!W){var j=(C={},C[k]={start:i[t.id].idx,end:i[n.id].idx,distance:a},C);p=Fh(j,s,e,p),W=p[k]}return Uh(W,o,l,c)},P1=function(e,t,n,i){var a,s,o,l=(a=e[t])===null||a===void 0?void 0:a.degree,c=(s=e[t])===null||s===void 0?void 0:s.inDegree,h=(o=e[t])===null||o===void 0?void 0:o.outDegree;return e[t]===void 0&&(l=1/0,c=1/0,h=1/0,i[t].forEach(function(p){var C=n[p.id].degree;l>C&&(l=C);var k=n[p.id].inDegree;c>k&&(c=k);var W=n[p.id].outDegree;h>W&&(h=W)}),e[t]={degree:l,inDegree:c,outDegree:h}),{minPatternNodeLabelDegree:l,minPatternNodeLabelInDegree:c,minPatternNodeLabelOutDegree:h}},eP=function(e,t,n,i,a,s,o){var l;if(n===void 0&&(n=!1),s===void 0&&(s="cluster"),o===void 0&&(o="cluster"),!(!e||!e.nodes)){var c=e.nodes.length;if(c){var h=mg(e,n),p=mg(t,n),C=O1(e.nodes,h,n),k=O1(t.nodes,p,n),W=A1(e.nodes,s),j=W.nodeMap,K=W.nodeLabelMap,Q=A1(t.nodes,s),ee=Q.nodeMap,re=Q.nodeLabelMap;C1(e.edges,o,j);var ve=C1(t.edges,o,ee).edgeLabelMap,he=[];p==null||p.forEach(function(nr){he=he.concat(nr)}),a||(a=Math.max.apply(Math,(0,we.ev)((0,we.ev)([],he,!1),[2],!1))),i||(i=a);var pe=S1(e,h,s,i),ye=S1(t,p,s,i),_e=Math.min(100,c*(c-1)/2),De=JO(i,c,_e,pe,h),Be=Fh(De,pe,e),ze=10,Xe=1,$e=1,ct=4,ut={graphs:Be,nodeLabelProp:s,edgeLabelProp:o,minSupport:Xe,minNodeNum:$e,maxNodeNum:ct,directed:n},St=QO(ut).slice(0,ze),bt=St.length,Et=[];St.forEach(function(nr,Er){Et[Er]={},Object.keys(Be).forEach(function(rr){var gr=Be[rr],wr=Uh(gr,nr,s,o);Et[Er][rr]=wr})});var xt=qO(Et,bt,St),Dt=xt.structure,Ft=xt.structureCountMap,Xt=t.nodes[0],an=[],dn=(l=t.nodes[0])===null||l===void 0?void 0:l[s],sn=-1/0;t.nodes.forEach(function(nr){var Er=nr[s],rr=K[Er];(rr==null?void 0:rr.length)>sn&&(sn=rr.length,an=rr,dn=Er,Xt=nr)});var Tn={},zn={},Vn={},ir={},hr={},Ji={};Object.keys(re).forEach(function(nr,Er){hr[nr]=[],n&&(Ji[nr]=[]);var rr=-1/0,gr=re[nr],wr={};gr.forEach(function(br){var mr=k["".concat(Xt.id,"-").concat(br.id)];if(mr&&hr[nr].push(mr),rr<mr&&(rr=mr),wr["".concat(Xt.id,"-").concat(br.id)]={start:0,end:ee[br.id].idx,distance:mr},n){var ni=k["".concat(br.id,"-").concat(Xt.id)];ni&&Ji[nr].push(ni)}}),hr[nr]=hr[nr].sort(function(br,mr){return br-mr}),n&&(Ji[nr]=Ji[nr].sort(function(br,mr){return br-mr})),zn=Fh(wr,ye,t,zn);var wn=[];if(Object.keys(wr).forEach(function(br){if(Vn[br]){wn.push(Vn[br]);return}var mr=zn[br];Vn[br]=Uh(mr,Dt,s,o),wn.push(Vn[br])}),wn=wn.sort(function(br,mr){return mr-br}),ir["".concat(Xt.id,"-").concat(nr)]=wn,nr!==dn)for(var pr=(an==null?void 0:an.length)||0,xr=function(mr){var ni=an[mr],ka=pe[j[ni.id].idx],ui=ka.nodeLabelCountMap[nr],bl=re[nr].length;if(!ui||ui.count<bl)return an.splice(mr,1),"continue";for(var dc=!1,ua=0;ua<bl;ua++)if(ui.dists[ua]>hr[nr][ua]){dc=!0;break}if(dc)return an.splice(mr,1),"continue";var qa={};ka.neighbors.forEach(function(ha){var ys=C["".concat(ni.id,"-").concat(ha.id)];qa["".concat(ni.id,"-").concat(ha.id)]={start:j[ni.id].idx,end:j[ha.id].idx,distance:ys}}),Be=Fh(qa,pe,e,Be);var Ns=[];Object.keys(qa).forEach(function(ha){if(Ft[ha]){Ns.push(Ft[ha]);return}var ys=Be[ha];Ft[ha]=Uh(ys,Dt,s,o),Ns.push(Ft[ha])}),Ns=Ns.sort(function(ha,ys){return ys-ha});for(var Io=!1,ua=0;ua<bl;ua++)if(Ns[ua]<wn[ua]){Io=!0;break}if(Io)return an.splice(mr,1),"continue"},yi=pr-1;yi>=0;yi--)xr(yi)});var _r=[];an==null||an.forEach(function(nr){for(var Er=j[nr.id].idx,rr=T1(e.nodes,h[Er],Er,s,a),gr=rr.neighbors,wr=gr.length,wn=!1,pr=wr-1;pr>=0;pr--){if(gr.length+1<t.nodes.length){wn=!0;return}var xr=gr[pr],yi=xr[s];if(!re[yi]||!re[yi].length){gr.splice(pr,1);continue}if(!hr[yi]||!hr[yi].length){gr.splice(pr,1);continue}var br="".concat(nr.id,"-").concat(xr.id),mr=C[br],ni=hr[yi].length-1,ka=hr[yi][ni];if(mr>ka){gr.splice(pr,1);continue}if(n){var ui="".concat(xr.id,"-").concat(nr.id),bl=C[ui];ni=Ji[yi].length-1;var dc=Ji[yi][ni];if(bl>dc){gr.splice(pr,1);continue}}var ua=Ft[br]?Ft[br]:$O(e,nr,xr,j,mr,pe,Dt,s,o,Ft,Be),qa="".concat(Xt.id,"-").concat(yi),Ns=ir[qa][ir[qa].length-1];if(ua<Ns){gr.splice(pr,1);continue}var Io=P1(Tn,yi,ee,re),ha=Io.minPatternNodeLabelDegree,ys=Io.minPatternNodeLabelInDegree,no=Io.minPatternNodeLabelOutDegree;if(j[xr.id].degree<ha){gr.splice(pr,1);continue}}wn||_r.push({nodes:[nr].concat(gr)})});var Ba=Ih(t,Xt.id,!1).length,qi={};n?(Object.keys(Ba).forEach(function(nr){var 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Bs=j[Wr].node[s];if(!qi[Bs]||!qi[Bs].length||ua[Wr]>qi[Bs][qi[Bs].length-1]){var za=wn[Wr].node[s];if(wr[za]--,wr[za]<re[za].length){ui=!0;return}var Mi=rr.nodes.indexOf(wn[Wr].node);rr.nodes.splice(Mi,1),wn[Wr]=void 0}}}),ui)return _r.splice(Er,1),"continue";for(var qa=!0,Ns=0;qa&&!ui;){qa=!1;var Io=n?wn[gr.id].degree<ee[Xt.id].degree||wn[gr.id].inDegree<ee[Xt.id].inDegree||wn[gr.id].outDegree<ee[Xt.id].outDegree:wn[gr.id].degree<ee[Xt.id].degree;if(Io){ui=!0;break}if(wr[gr[s]]<re[gr[s]].length){ui=!0;break}for(var ha=rr.nodes.length,ys=ha-1;ys>=0;ys--){var no=rr.nodes[ys],m2=wn[no.id].degree,C6=wn[no.id].inDegree,O6=wn[no.id].outDegree,P6=no[s],_0=P1(Tn,P6,ee,re),y2=_0.minPatternNodeLabelDegree,D6=_0.minPatternNodeLabelInDegree,L6=_0.minPatternNodeLabelOutDegree,R6=n?m2<y2||C6<D6||O6<L6:m2<y2;if(R6){if(wr[no[s]]--,wr[no[s]]<re[no[s]].length){ui=!0;break}rr.nodes.splice(ys,1),wn[no.id]=void 0,qa=!0}}if(ui||!qa&&Ns!==0)break;ka=pr.length;for(var Zd=ka-1;Zd>=0;Zd--){var ro=pr[Zd];if(!wn[ro.source]||!wn[ro.target]){pr.splice(Zd,1);var Kd=ro[o];if(xr[Kd]--,wn[ro.source]&&(wn[ro.source].degree--,wn[ro.source].outDegree--),wn[ro.target]&&(wn[ro.target].degree--,wn[ro.target].inDegree--),ve[Kd]&&xr[Kd]<ve[Kd].length){ui=!0;break}qa=!0}}Ns++}if(ui||ui||rr.nodes.length<t.nodes.length||pr.length<t.edges.length)return _r.splice(Er,1),"continue"},Di=Ro-1;Di>=0;Di--){var to=Ui(Di);if(to==="break")break}for(var Wi=_r.length,ba=function(Er){var rr=_r[Er],gr={};rr.edges.forEach(function(pr){var xr="".concat(pr.source,"-").concat(pr.target,"-").concat(pr.label);gr[xr]?gr[xr]++:gr[xr]=1});for(var wr=function(xr){var yi=_r[xr],br={};yi.edges.forEach(function(ni){var ka="".concat(ni.source,"-").concat(ni.target,"-").concat(ni.label);br[ka]?br[ka]++:br[ka]=1});var mr=!0;Object.keys(br).length!==Object.keys(gr).length?mr=!1:Object.keys(gr).forEach(function(ni){br[ni]!==gr[ni]&&(mr=!1)}),mr&&_r.splice(xr,1)},wn=Wi-1;wn>Er;wn--)wr(wn);Wi=_r.length},Di=0;Di<=Wi-1;Di++)ba(Di);return _r}}},tP=eP,nP=function(){function r(e){e===void 0&&(e=10),this.linkedList=new Yy,this.maxStep=e}return Object.defineProperty(r.prototype,"length",{get:function(){return this.linkedList.toArray().length},enumerable:!1,configurable:!0}),r.prototype.isEmpty=function(){return!this.linkedList.head},r.prototype.isMaxStack=function(){return this.toArray().length>=this.maxStep},r.prototype.peek=function(){return this.isEmpty()?null:this.linkedList.head.value},r.prototype.push=function(e){this.linkedList.prepend(e),this.length>this.maxStep&&this.linkedList.deleteTail()},r.prototype.pop=function(){var e=this.linkedList.deleteHead();return e?e.value:null},r.prototype.toArray=function(){return this.linkedList.toArray().map(function(e){return 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n=oi.callbacks[e].indexOf(t);n>-1&&oi.callbacks[e].splice(n,1),this.tryDestroy()}tryDestroy(){Object.values(oi.callbacks).every(e=>e.length===0)&&this.destroy()}}oi.isPinching=!1,oi.instance=null,oi.callbacks={pinchstart:[],pinchmove:[],pinchend:[]};const Z1=r=>r.map(e=>dr(e)?e.toLocaleLowerCase():e);class Zl{constructor(e){this.map=new Map,this.boundHandlePinch=()=>{},this.recordKey=new Set,this.onKeyDown=t=>{t!=null&&t.key&&(this.recordKey.add(t.key),this.trigger(t))},this.onKeyUp=t=>{t!=null&&t.key&&this.recordKey.delete(t.key)},this.onWheel=t=>{this.triggerExtendKey(kt.WHEEL,t)},this.onDrag=t=>{this.triggerExtendKey(kt.DRAG,t)},this.handlePinch=(t,n)=>{this.triggerExtendKey(kt.PINCH,Object.assign(Object.assign({},t),n))},this.onFocus=()=>{this.recordKey.clear()},this.emitter=e,this.bindEvents()}bind(e,t){e.length!==0&&(e.includes(kt.PINCH)&&!this.pinchHandler&&(this.boundHandlePinch=this.handlePinch.bind(this),this.pinchHandler=new oi(this.emitter,"pinchmove",this.boundHandlePinch)),this.map.set(e,t))}unbind(e,t){this.map.forEach((n,i)=>{si(i,e)&&(!t||t===n)&&this.map.delete(i)})}unbindAll(){this.map.clear()}match(e){const t=Z1(Array.from(this.recordKey)).sort(),n=Z1(e).sort();return si(t,n)}bindEvents(){var e;const{emitter:t}=this;t.on(kt.KEY_DOWN,this.onKeyDown),t.on(kt.KEY_UP,this.onKeyUp),t.on(kt.WHEEL,this.onWheel),t.on(kt.DRAG,this.onDrag),(e=globalThis.addEventListener)===null||e===void 0||e.call(globalThis,"focus",this.onFocus)}trigger(e){this.map.forEach((t,n)=>{this.match(n)&&t(e)})}triggerExtendKey(e,t){this.map.forEach((n,i)=>{i.includes(e)&&si(Array.from(this.recordKey),i.filter(a=>a!==e))&&n(t)})}destroy(){var e,t;this.unbindAll(),this.emitter.off(kt.KEY_DOWN,this.onKeyDown),this.emitter.off(kt.KEY_UP,this.onKeyUp),this.emitter.off(kt.WHEEL,this.onWheel),this.emitter.off(kt.DRAG,this.onDrag),(e=this.pinchHandler)===null||e===void 0||e.off("pinchmove",this.boundHandlePinch),(t=globalThis.removeEventListener)===null||t===void 0||t.call(globalThis,"blur",this.onFocus)}}class Xc extends Oa{constructor(e,t){super(e,ia({},Xc.defaultOptions,t)),this.shortcut=new Zl(e.graph),this.onPointerDown=this.onPointerDown.bind(this),this.onPointerMove=this.onPointerMove.bind(this),this.onPointerUp=this.onPointerUp.bind(this),this.clearStates=this.clearStates.bind(this),this.bindEvents()}onPointerDown(e){if(!this.validate(e)||!this.isKeydown()||this.startPoint)return;const{canvas:t,graph:n}=this.context,i=Object.assign({},this.options.style);this.options.style.lineWidth&&(i.lineWidth=+this.options.style.lineWidth/n.getZoom()),this.rectShape=new Ii({id:"g6-brush-select",style:i}),t.appendChild(this.rectShape),this.startPoint=[e.canvas.x,e.canvas.y]}onPointerMove(e){var t;if(!this.startPoint)return;const{immediately:n,mode:i}=this.options;this.endPoint=Zh(e),(t=this.rectShape)===null||t===void 0||t.attr({x:Math.min(this.endPoint[0],this.startPoint[0]),y:Math.min(this.endPoint[1],this.startPoint[1]),width:Math.abs(this.endPoint[0]-this.startPoint[0]),height:Math.abs(this.endPoint[1]-this.startPoint[1])}),n&&i==="default"&&this.updateElementsStates(V1(this.startPoint,this.endPoint))}onPointerUp(e){if(this.startPoint){if(!this.endPoint){this.clearBrush();return}this.endPoint=Zh(e),this.updateElementsStates(V1(this.startPoint,this.endPoint)),this.clearBrush()}}clearStates(){this.endPoint||this.clearElementsStates()}clearElementsStates(){const{graph:e}=this.context,t=Object.values(e.getData()).reduce((n,i)=>Object.assign({},n,i.reduce((a,s)=>(a[wt(s)]=[],a),{})),{});e.setElementState(t,this.options.animation)}updateElementsStates(e){const{graph:t}=this.context,{enableElements:n,state:i,mode:a,onSelect:s}=this.options,o=this.selector(t,e,n);let l={};switch(a){case"union":o.forEach(c=>{l[c]=[...t.getElementState(c),i]});break;case"diff":o.forEach(c=>{const h=t.getElementState(c);l[c]=h.includes(i)?h.filter(p=>p!==i):[...h,i]});break;case"intersect":o.forEach(c=>{const h=t.getElementState(c);l[c]=h.includes(i)?[i]:[]});break;case"default":default:o.forEach(c=>{l[c]=[i]});break}En(s)&&(l=s(l)),t.setElementState(l,this.options.animation)}selector(e,t,n){if(!n||n.length===0)return[];const i=[],a=e.getData();if(n.forEach(s=>{a[`${s}s`].forEach(o=>{const l=wt(o);e.getElementVisibility(l)!=="hidden"&&bP(e.getElementPosition(l),t)&&i.push(l)})}),n.includes("edge")){const s=a.edges;s==null||s.forEach(o=>{const{source:l,target:c}=o;i.includes(l)&&i.includes(c)&&i.push(wt(o))})}return i}clearBrush(){var e;(e=this.rectShape)===null||e===void 0||e.remove(),this.rectShape=void 0,this.startPoint=void 0,this.endPoint=void 0}isKeydown(){const{trigger:e}=this.options,t=Array.isArray(e)?e:[e];return this.shortcut.match(t.filter(n=>n!=="drag"))}validate(e){if(this.destroyed)return!1;const{enable:t}=this.options;return En(t)?t(e):!!t}bindEvents(){const{graph:e}=this.context;e.on(kt.POINTER_DOWN,this.onPointerDown),e.on(kt.POINTER_MOVE,this.onPointerMove),e.on(kt.POINTER_UP,this.onPointerUp),e.on(js.CLICK,this.clearStates)}unbindEvents(){const{graph:e}=this.context;e.off(kt.POINTER_DOWN,this.onPointerDown),e.off(kt.POINTER_MOVE,this.onPointerMove),e.off(kt.POINTER_UP,this.onPointerUp),e.off(js.CLICK,this.clearStates)}update(e){this.unbindEvents(),this.options=ia(this.options,e),this.bindEvents()}destroy(){this.unbindEvents(),super.destroy()}}Xc.defaultOptions={animation:!1,enable:!0,enableElements:["node","combo","edge"],immediately:!1,mode:"default",state:"selected",trigger:["shift"],style:{width:0,height:0,lineWidth:1,fill:"#1677FF",stroke:"#1677FF",fillOpacity:.1,zIndex:2,pointerEvents:"none"}};const Zh=r=>[r.canvas.x,r.canvas.y],Ys=.8,sl=["node","edge","combo"];function ol(r,e,t,n,i=0){n==="TB"&&e(r,i);const a=t(r);if(a)for(const s of a)ol(s,e,t,n,i+1);n==="BT"&&e(r,i)}function CP(r,e,t){const n=[[r,0]];for(;n.length;){const[i,a]=n.shift();e(i,a);const s=t(i);if(s)for(const o of s)n.push([o,a+1])}}function K1(r,e,t,n,i="both"){if(e==="combo"||e==="node")return Sg(r,t,n,i);const a=r.getEdgeData(t);if(!a)return[];const s=Sg(r,a.source,n-1,i),o=Sg(r,a.target,n-1,i);return Array.from(new Set([...s,...o,t]))}function Sg(r,e,t,n="both"){const i=new Set,a=new Set,s=new Set;return CP(e,(o,l)=>{l>t||(s.add(o),r.getRelatedEdgesData(o,n).forEach(c=>{const h=wt(c);!a.has(h)&&l<t&&(s.add(h),a.add(h))}))},o=>r.getRelatedEdgesData(o,n).map(l=>l.source===o?l.target:l.source).filter(l=>i.has(l)?!1:(i.add(l),!0))),Array.from(s)}function Tg(r){return r.states||[]}var Kh=function(r,e,t,n){function i(a){return a instanceof t?a:new t(function(s){s(a)})}return new(t||(t=Promise))(function(a,s){function o(h){try{c(n.next(h))}catch(p){s(p)}}function l(h){try{c(n.throw(h))}catch(p){s(p)}}function c(h){h.done?a(h.value):i(h.value).then(o,l)}c((n=n.apply(r,e||[])).next())})};class Xh extends Oa{constructor(e,t){super(e,Object.assign({},Xh.defaultOptions,t)),this.onClickSelect=n=>Kh(this,void 0,void 0,function*(){var i,a;this.validate(n)&&(yield this.updateState(n),(a=(i=this.options).onClick)===null||a===void 0||a.call(i,n))}),this.onClickCanvas=n=>Kh(this,void 0,void 0,function*(){var i,a;this.validate(n)&&(yield this.clearState(),(a=(i=this.options).onClick)===null||a===void 0||a.call(i,n))}),this.shortcut=new Zl(e.graph),this.bindEvents()}bindEvents(){const{graph:e}=this.context;this.unbindEvents(),sl.forEach(t=>{e.on(`${t}:${kt.CLICK}`,this.onClickSelect)}),e.on(js.CLICK,this.onClickCanvas)}get isMultipleSelect(){const{multiple:e,trigger:t}=this.options;return e&&this.shortcut.match(t)}getNeighborIds(e){const{target:t,targetType:n}=e,{graph:i}=this.context,{degree:a}=this.options;return K1(i,n,t.id,typeof a=="function"?a(e):a).filter(s=>s!==t.id)}updateState(e){return Kh(this,void 0,void 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Object.assign(h,this.getClearStates());yield o.setElementState(h,a)})}getDataStates(){const{graph:e}=this.context,{nodes:t,edges:n,combos:i}=e.getData(),a={};return[...t,...n,...i].forEach(s=>{a[wt(s)]=Tg(s)}),a}getClearStates(e=!1){const{graph:t}=this.context,{state:n,unselectedState:i,neighborState:a}=this.options,s=new Set([n,i,a]),{nodes:o,edges:l,combos:c}=t.getData(),h={};return[...o,...l,...c].forEach(p=>{const C=Tg(p),k=C.filter(W=>!s.has(W));(e||k.length!==C.length)&&(h[wt(p)]=k)}),h}clearState(){return Kh(this,void 0,void 0,function*(){const{graph:e}=this.context;yield e.setElementState(this.getClearStates(),this.options.animation)})}validate(e){if(this.destroyed)return!1;const{enable:t}=this.options;return En(t)?t(e):!!t}unbindEvents(){const{graph:e}=this.context;sl.forEach(t=>{e.off(`${t}:${kt.CLICK}`,this.onClickSelect)}),e.off(js.CLICK,this.onClickCanvas)}destroy(){this.unbindEvents(),super.destroy()}}Xh.defaultOptions={animation:!0,enable:!0,multiple:!1,trigger:["shift"],state:"selected",neighborState:"selected",unselectedState:void 0,degree:0};function xa(r){var e;return!!(!((e=r.style)===null||e===void 0)&&e.collapsed)}var aa=function(r,e,t){for(var n=0,i=dr(e)?e.split("."):e;r&&n<i.length;)r=r[i[n++]];return r===void 0||n<i.length?t:r},Yc=function(r,e,t){var n=r,i=dr(e)?e.split("."):e;return i.forEach(function(a,s){s<i.length-1?(ii(n[a])||(n[a]=un(i[s+1])?[]:{}),n=n[a]):n[a]=t}),r},OP=function(r){var e=Fy(r);return e.charAt(0).toLowerCase()+e.substring(1)},PP=OP;function Qc(r,e){if(!r.startsWith(e))return!1;const t=r[e.length];return t>="A"&&t<="Z"}function X1(r,e){return`${e}${Sh(r)}`}function Y1(r,e,t=!0){if(!e||!Qc(r,e))return r;const n=r.slice(e.length);return 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$1(r){const e=typeof r=="string"?Gs("palette",r):r;if(typeof e!="function")return e}function e_(r,e){let t=2*r;return typeof e=="string"?t=r*Number(e.replace("%",""))/100:typeof e=="number"&&(t=e),isNaN(t)&&(t=2*r),t}function t_(r,e,t=1,n=!1){const i=n?t:1,a=(r.max[0]-r.min[0])*i;return e_(a,e)}function NP(r,e,t=1){const n=Ur(r[0],r[1])*t;return e_(n,e)}var BP={}.toString,kP=function(r){return BP.call(r).replace(/^\[object /,"").replace(/]$/,"")},zP=kP,FP=Object.prototype,UP=function(r){var e=r&&r.constructor,t=typeof e=="function"&&e.prototype||FP;return r===t},WP=UP,HP=Object.prototype.hasOwnProperty;function jP(r){if(Rn(r))return!0;if(Fc(r))return!r.length;var e=zP(r);if(e==="Map"||e==="Set")return!r.size;if(WP(r))return!Object.keys(r).length;for(var t in r)if(HP.call(r,t))return!1;return!0}var Ls=jP;class Jc extends Gv{constructor(e){n_(e.style),super(e),this.shapeMap={},this.animateMap={},this.render(this.attributes,this),this.setVisibility(),this.bindEvents()}get parsedAttributes(){return this.attributes}upsert(e,t,n,i,a){var s,o,l,c,h,p,C,k;const W=this.shapeMap[e];if(n===!1){W&&((s=a==null?void 0:a.beforeDestroy)===null||s===void 0||s.call(a,W),i.removeChild(W),delete this.shapeMap[e],(o=a==null?void 0:a.afterDestroy)===null||o===void 0||o.call(a,W));return}const j=typeof t=="string"?Gs(Uc.SHAPE,t):t;if(!j)throw new Error(Vs(`Shape ${t} not found`));if(!W||W.destroyed||!(W instanceof j)){W&&((l=a==null?void 0:a.beforeDestroy)===null||l===void 0||l.call(a,W),W==null||W.destroy(),(c=a==null?void 0:a.afterDestroy)===null||c===void 0||c.call(a,W)),(h=a==null?void 0:a.beforeCreate)===null||h===void 0||h.call(a);const K=new j({className:e,style:n});return i.appendChild(K),this.shapeMap[e]=K,(p=a==null?void 0:a.afterCreate)===null||p===void 0||p.call(a,K),K}return(C=a==null?void 0:a.beforeUpdate)===null||C===void 0||C.call(a,W),Yg(W,n),(k=a==null?void 0:a.afterUpdate)===null||k===void 0||k.call(a,W),W}update(e={}){const t=Object.assign({},this.attributes,e);n_(t),VL(this,t),this.render(t,this),this.setVisibility()}bindEvents(){}getGraphicStyle(e){return LP(e)}get compositeShapes(){return[["badges","badge-"],["ports","port-"]]}animate(e,t){if(e.length===0)return null;const n=[];if(e[0].x!==void 0||e[0].y!==void 0||e[0].z!==void 0){const{x:a=0,y:s=0,z:o=0}=this.attributes;e.forEach(l=>{const{x:c=a,y:h=s,z:p=o}=l;Object.assign(l,{transform:p?[["translate3d",c,h,p]]:[["translate",c,h]]})})}const i=super.animate(e,t);if(i&&(Cg(this,i),n.push(i)),Array.isArray(e)&&e.length>0){const a=["transform","transformOrigin","x","y","z","zIndex"];if(Object.keys(e[0]).some(s=>!a.includes(s))){Object.entries(this.shapeMap).forEach(([o,l])=>{const c=`get${Sh(o)}Style`,h=this[c];if(En(h)){const p=e.map(k=>h.call(this,Object.assign(Object.assign({},this.attributes),k))),C=l.animate(sg(p),t);C&&(Cg(l,C),n.push(C))}});const s=(o,l)=>{if(!Ls(o)){const c=`get${Sh(l)}Style`,h=this[c];if(En(h)){const p=e.map(C=>h.call(this,Object.assign(Object.assign({},this.attributes),C)));Object.entries(p[0]).map(([C])=>{const k=p.map(j=>j[C]),W=o[C];if(W){const j=W.animate(sg(k),t);j&&(Cg(W,j),n.push(j))}})}}};this.compositeShapes.forEach(([o,l])=>{const c=Ag(this.shapeMap,l);s(c,o)})}}return ag(n)}getShape(e){return this.shapeMap[e]}setVisibility(){const{visibility:e}=this.attributes;il(this,e)}destroy(){this.shapeMap={},this.animateMap={},super.destroy()}}function Cg(r,e){e==null||e.finished.then(()=>{const t=r.activeAnimations.findIndex(n=>n===e);t>-1&&r.activeAnimations.splice(t,1)})}function n_(r){if(!r)return{};if("x"in r||"y"in r||"z"in r){const{x:e=0,y:t=0,z:n,transform:i}=r,a=Hy(e,t,n,i);a&&(r.transform=a)}return r}var GP=function(r,e){var t={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&e.indexOf(n)<0&&(t[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var 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s}render(e=this.parsedAttributes,t=this){this.upsert("text",el,this.getTextStyle(e),t),this.upsert("background",Ii,this.getBackgroundStyle(e),t)}getGeometryBounds(){return(this.getShape("background")||this.getShape("text")).getGeometryBounds()}}_o.defaultStyleProps={padding:0,fontSize:12,fontFamily:"system-ui, sans-serif",wordWrap:!0,maxLines:1,wordWrapWidth:128,textOverflow:"...",textBaseline:"middle",backgroundOpacity:.75,backgroundZIndex:-1,backgroundLineWidth:0};class Kl extends Jc{constructor(e){super(Ai({style:Kl.defaultStyleProps},e))}getBadgeStyle(e){return this.getGraphicStyle(e)}render(e=this.parsedAttributes,t=this){this.upsert("label",_o,this.getBadgeStyle(e),t)}getGeometryBounds(){const e=this.getShape("label");return(e.getShape("background")||e.getShape("text")).getGeometryBounds()}}Kl.defaultStyleProps={padding:[2,4,2,4],fontSize:10,wordWrap:!1,backgroundRadius:"50%",backgroundOpacity:1};function VP(r,e=!0){const t=[];return r.forEach((n,i)=>{t.push([i===0?"M":"L",...n])}),e&&t.push(["Z"]),t}const r_={M:["x","y"],m:["dx","dy"],H:["x"],h:["dx"],V:["y"],v:["dy"],L:["x","y"],l:["dx","dy"],Z:[],z:[],C:["x1","y1","x2","y2","x","y"],c:["dx1","dy1","dx2","dy2","dx","dy"],S:["x2","y2","x","y"],s:["dx2","dy2","dx","dy"],Q:["x1","y1","x","y"],q:["dx1","dy1","dx","dy"],T:["x","y"],t:["dx","dy"],A:["rx","ry","rotation","large-arc","sweep","x","y"],a:["rx","ry","rotation","large-arc","sweep","dx","dy"]};function ZP(r){const e=r.replace(/[\n\r]/g,"").replace(/-/g," -").replace(/(\d*\.)(\d+)(?=\.)/g,"$1$2 ").trim().split(/\s*,|\s+/),t=[];let n="",i={};for(;e.length>0;){let a=e.shift();a in r_?n=a:e.unshift(a),i={type:n},r_[n].forEach(l=>{a=e.shift(),i[l]=a}),n==="M"?n="L":n==="m"&&(n="l");const[s,...o]=Object.values(i);t.push([s,...o.map(Number)])}return t}function KP(r){const e=[];return(typeof r=="string"?ZP(r):r).forEach(n=>{const i=n[0];if(i==="Z"){e.push(e[0]);return}if(i!=="A")for(let 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W=Math.atan((C[0][1]-C[1][1])/(C[0][0]-C[1][0]));c.transform.push(["rotate",W/Math.PI*180]),c.textAlign="center",(e==="right"||e==="left")&&(W>0?c.textBaseline=e==="right"?"bottom":"top":c.textBaseline=e==="right"?"top":"bottom")}return c}var YP=function(r,e){var t={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&e.indexOf(n)<0&&(t[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var i=0,n=Object.getOwnPropertySymbols(r);i<n.length;i++)e.indexOf(n[i])<0&&Object.prototype.propertyIsEnumerable.call(r,n[i])&&(t[n[i]]=r[n[i]]);return t};class qc extends Jc{constructor(e){super(Ai({style:qc.defaultStyleProps},e))}getLabelStyle(e){if(!e.label||!e.d||e.d.length===0)return!1;const t=gi(this.getGraphicStyle(e),"label"),{maxWidth:n,offsetX:i,offsetY:a,autoRotate:s,placement:o,closeToPath:l}=t,c=YP(t,["maxWidth","offsetX","offsetY","autoRotate","placement","closeToPath"]),h=this.shapeMap.key,p=h==null?void 0:h.getRenderBounds();return Object.assign(XP(p,o,i,a,l,e.d,s),{wordWrapWidth:t_(p,n)},c)}getKeyStyle(e){return this.getGraphicStyle(e)}render(e,t){this.upsert("key",Ta,this.getKeyStyle(e),t),this.upsert("label",_o,this.getLabelStyle(e),t)}}qc.defaultStyleProps={label:!0,labelPlacement:"bottom",labelCloseToPath:!0,labelAutoRotate:!0,labelOffsetX:0,labelOffsetY:0};function QP(r){const e=[],t=n=>{n!=null&&n.children.length&&n.children.forEach(i=>{e.push(i),t(i)})};return t(r),e}function JP(r){const e=[];let t=r.parentNode;for(;t;)e.push(t),t=t.parentNode;return e}class Og extends Bc{constructor(e){super(e),this.onMounted=()=>{this.handleRadius()},this.onAttrModified=()=>{this.handleRadius()},Xl=this,this.isMutationObserved=!0,this.addEventListener(tr.MOUNTED,this.onMounted),this.addEventListener(tr.ATTR_MODIFIED,this.onAttrModified)}handleRadius(){const{radius:e,clipPath:t,width:n=0,height:i=0}=this.attributes;if(e&&n&&i){const[a,s]=this.getBounds().min,o={x:a,y:s,radius:e,width:n,height:i};if(t)Object.assign(this.parsedStyle.clipPath.style,o);else{const l=new Ii({style:o});this.style.clipPath=l}}else t&&(this.style.clipPath=null)}}const Pg=new WeakMap;let Xl=null;const Dg=r=>{if(Xl&&JP(Xl).includes(r)){const e=Pg.get(r);e?e.includes(Xl)||e.push(Xl):Pg.set(r,[Xl])}},Lg=r=>{const e=Pg.get(r);e&&e.forEach(t=>t.handleRadius())};class a_ extends Jc{constructor(e){super(e)}isImage(){const{src:e}=this.attributes;return!!e}getIconStyle(e=this.attributes){const{width:t=0,height:n=0}=e,i=this.getGraphicStyle(e);return this.isImage()?Object.assign({x:-t/2,y:-n/2},i):Object.assign({textBaseline:"middle",textAlign:"center"},i)}render(e=this.attributes,t=this){this.upsert("icon",this.isImage()?Og:el,this.getIconStyle(e),t)}}class s_ extends Jc{get context(){return this.config.context}get parsedAttributes(){return this.attributes}onframe(){}animate(e,t){const n=super.animate(e,t);return n&&(n.onframe=()=>this.onframe(),n.finished.then(()=>this.onframe())),n}}var Yh=function(r,e){var t={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&e.indexOf(n)<0&&(t[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var i=0,n=Object.getOwnPropertySymbols(r);i<n.length;i++)e.indexOf(n[i])<0&&Object.prototype.propertyIsEnumerable.call(r,n[i])&&(t[n[i]]=r[n[i]]);return t};class fs extends s_{constructor(e){super(Ai({style:fs.defaultStyleProps},e)),this.type="node"}getSize(e=this.attributes){const{size:t}=e;return Pa(t)}getKeyStyle(e){const t=this.getGraphicStyle(e);return Object.assign(Q1(t,["label","halo","icon","badge","port"]))}getLabelStyle(e){if(e.label===!1||!e.labelText)return!1;const t=gi(this.getGraphicStyle(e),"label"),{placement:n,maxWidth:i,offsetX:a,offsetY:s}=t,o=Yh(t,["placement","maxWidth","offsetX","offsetY"]),l=this.getShape("key").getLocalBounds();return Object.assign(F_(l,n,a,s),{wordWrapWidth:t_(l,i)},o)}getHaloStyle(e){if(e.halo===!1)return!1;const t=this.getKeyStyle(e),{fill:n}=t,i=Yh(t,["fill"]),a=gi(this.getGraphicStyle(e),"halo");return Object.assign(Object.assign(Object.assign({},i),{stroke:n}),a)}getIconStyle(e){if(e.icon===!1||!e.iconText&&!e.iconSrc)return!1;const t=gi(this.getGraphicStyle(e),"icon");return Object.assign(RP(e.size,t),t)}getBadgesStyle(e){var t;const n=Ag(this.shapeMap,"badge-"),i={};if(Object.keys(n).forEach(p=>{i[p]=!1}),e.badge===!1||!(!((t=e.badges)===null||t===void 0)&&t.length))return i;const{badges:a=[],badgePalette:s,opacity:o=1}=e,l=Yh(e,["badges","badgePalette","opacity"]),c=$1(s),h=gi(this.getGraphicStyle(l),"badge");return a.forEach((p,C)=>{i[C]=Object.assign(Object.assign({backgroundFill:c?c[C%(c==null?void 0:c.length)]:void 0,opacity:o},h),this.getBadgeStyle(p))}),i}getBadgeStyle(e){const t=this.getShape("key"),{placement:n="top",offsetX:i,offsetY:a}=e,s=Yh(e,["placement","offsetX","offsetY"]),o=F_(t.getLocalBounds(),n,i,a,!0);return Object.assign(Object.assign({},o),s)}getPortsStyle(e){var t;const n=this.getPorts(),i={};if(Object.keys(n).forEach(o=>{i[o]=!1}),e.port===!1||!(!((t=e.ports)===null||t===void 0)&&t.length))return i;const a=gi(this.getGraphicStyle(e),"port"),{ports:s=[]}=e;return s.forEach((o,l)=>{const c=o.key||l,h=Object.assign(Object.assign({},a),o);if(B_(h))i[c]=!1;else{const[p,C]=this.getPortXY(e,o);i[c]=Object.assign({transform:[["translate",p,C]]},h)}}),i}getPortXY(e,t){const{placement:n="left"}=t,i=this.getShape("key");return 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this.drawKeyShape(e,t)}render(e=this.parsedAttributes,t=this){this._drawKeyShape(e,t),this.getShape("key")&&(this.drawHaloShape(e,t),this.drawIconShape(e,t),this.drawBadgeShapes(e,t),this.drawLabelShape(e,t),this.drawPortShapes(e,t))}update(e){super.update(e),e&&("x"in e||"y"in e||"z"in e)&&Lg(this)}onframe(){this.drawBadgeShapes(this.parsedAttributes,this),this.drawLabelShape(this.parsedAttributes,this)}}fs.defaultStyleProps={x:0,y:0,size:32,droppable:!0,draggable:!0,port:!0,ports:[],portZIndex:2,portLinkToCenter:!1,badge:!0,badges:[],badgeZIndex:3,halo:!1,haloDroppable:!1,haloLineDash:0,haloLineWidth:12,haloStrokeOpacity:.25,haloPointerEvents:"none",haloZIndex:-1,icon:!0,iconZIndex:1,label:!0,labelIsBillboard:!0,labelMaxWidth:"200%",labelPlacement:"bottom",labelWordWrap:!1,labelZIndex:0};function qP(r,e){if(!r)return e.getLocalBounds();const t=r.canvas.getLayer(),n=e.cloneNode();il(n,"hidden"),t.appendChild(n);const i=n.getLocalBounds();return n.destroy(),i}class ll extends fs{constructor(e){super(Ai({style:ll.defaultStyleProps},e))}drawKeyShape(e,t){return this.upsert("key",Ws,this.getKeyStyle(e),t)}getKeyStyle(e){const t=super.getKeyStyle(e);return Object.assign(Object.assign({},t),{r:Math.min(...this.getSize(e))/2})}getIconStyle(e){const t=super.getIconStyle(e),{r:n}=this.getShape("key").attributes,i=n*2*Ys;return t?Object.assign({width:i,height:i},t):!1}getIntersectPoint(e,t=!1){const n=this.getShape("key").getBounds();return Vh(e,n,t)}}ll.defaultStyleProps={size:32};class Qh extends fs{constructor(e){super(e)}get parsedAttributes(){return this.attributes}drawKeyShape(e,t){return this.upsert("key",$o,this.getKeyStyle(e),t)}getKeyStyle(e){const t=super.getKeyStyle(e);return Object.assign(Object.assign({},t),{points:this.getPoints(e)})}getIntersectPoint(e,t=!1){var n,i;const{points:a}=this.getShape("key").attributes,s=[+(((n=this.attributes)===null||n===void 0?void 0:n.x)||0),+(((i=this.attributes)===null||i===void 0?void 0:i.y)||0)];return 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Q=K.img,ee=Q.width,re=Q.height;C.attributes.keepAspectRatio&&o(C,ee,re),C.renderable.dirty=!0,n.dirtify()}).catch(function(){}))};n.hooks.init.tap(r.tag,function(){s.addEventListener(tr.MOUNTED,l),s.addEventListener(tr.ATTR_MODIFIED,c)}),n.hooks.destroy.tap(r.tag,function(){s.removeEventListener(tr.MOUNTED,l),s.removeEventListener(tr.ATTR_MODIFIED,c)})}}])}();h_.tag="LoadImage";var ND=function(r){function e(){var t;(0,b.Z)(this,e);for(var n=arguments.length,i=new Array(n),a=0;a<n;a++)i[a]=arguments[a];return t=_(this,e,[].concat(i)),t.name="image-loader",t}return(0,g.Z)(e,r),(0,z.Z)(e,[{key:"init",value:function(n){this.context.imagePool=new kg(this.context,n),this.addRenderingPlugin(new h_)}},{key:"destroy",value:function(){this.removeAllRenderingPlugins()}}])}(oo);var li=RD("renderState"),f_=function(){function r(e){(0,b.Z)(this,r),this.removedRBushNodeAABBs=[],this.renderQueue=[],Object.defineProperty(this,li,{writable:!0,value:{restoreStack:[],prevObject:null,currentContext:new Map}}),this.clearFullScreenLastFrame=!1,this.clearFullScreen=!1,this.vpMatrix=Je(),this.dprMatrix=Je(),this.tmpMat4=Je(),this.vec3a=f(),this.vec3b=f(),this.vec3c=f(),this.vec3d=f(),this.canvasRendererPluginOptions=e}return(0,z.Z)(r,[{key:"apply",value:function(t,n){var i=this;this.context=t;var a=this.context,s=a.config,o=a.camera,l=a.renderingService,c=a.renderingContext,h=a.rBushRoot,p=a.pathGeneratorFactory,C=s.renderer.getConfig().enableRenderingOptimization;s.renderer.getConfig().enableDirtyCheck=!1,s.renderer.getConfig().enableDirtyRectangleRendering=!1,this.rBush=h,this.pathGeneratorFactory=p;var k=t.contextService,W=c.root.ownerDocument.defaultView,j=function(re){var ve=re.target,he=ve.rBushNode;he.aabb&&i.removedRBushNodeAABBs.push(he.aabb)},K=function(re){var ve=re.target,he=ve.rBushNode;he.aabb&&i.removedRBushNodeAABBs.push(he.aabb)};l.hooks.init.tap(r.tag,function(){W.addEventListener(tr.UNMOUNTED,j),W.addEventListener(tr.CULLED,K);var ee=k.getDPR(),re=s.width,ve=s.height,he=k.getContext();i.clearRect(he,0,0,re*ee,ve*ee,s.background)}),l.hooks.destroy.tap(r.tag,function(){W.removeEventListener(tr.UNMOUNTED,j),W.removeEventListener(tr.CULLED,K),i.renderQueue=[],i.removedRBushNodeAABBs=[],Rs(i,li)[li]={restoreStack:[],prevObject:null,currentContext:null}}),l.hooks.beginFrame.tap(r.tag,function(){var ee,re=k.getContext(),ve=k.getDPR(),he=s.width,pe=s.height,ye=i.canvasRendererPluginOptions,_e=ye.dirtyObjectNumThreshold,De=ye.dirtyObjectRatioThreshold,Be=l.getStats(),ze=Be.total,Xe=Be.rendered,$e=Xe/ze;i.clearFullScreen=i.clearFullScreenLastFrame||!((ee=W.context.renderingPlugins[1])!==null&&ee!==void 0&&ee.isFirstTimeRenderingFinished)||l.disableDirtyRectangleRendering()||Xe>_e&&$e>De,re&&(typeof re.resetTransform=="function"?re.resetTransform():re.setTransform(1,0,0,1,0,0),i.clearFullScreen&&i.clearRect(re,0,0,he*ve,pe*ve,s.background))});var Q=function(re,ve){for(var he=[re];he.length>0;){var pe=he.pop();pe.isVisible()&&!pe.isCulled()&&(C?i.renderDisplayObjectOptimized(pe,ve,i.context,Rs(i,li)[li],n):i.renderDisplayObject(pe,ve,i.context,Rs(i,li)[li],n));for(var ye=pe.sortable.sorted||pe.childNodes,_e=ye.length-1;_e>=0;_e--)he.push(ye[_e])}};l.hooks.endFrame.tap(r.tag,function(){if(c.root.childNodes.length===0){i.clearFullScreenLastFrame=!0;return}C=s.renderer.getConfig().enableRenderingOptimization,Rs(i,li)[li]={restoreStack:[],prevObject:null,currentContext:Rs(i,li)[li].currentContext},Rs(i,li)[li].currentContext.clear(),i.clearFullScreenLastFrame=!1;var ee=k.getContext(),re=k.getDPR();if(pn(i.dprMatrix,[re,re,1]),lt(i.vpMatrix,i.dprMatrix,o.getOrthoMatrix()),i.clearFullScreen)C?(ee.save(),Q(c.root,ee),ee.restore()):Q(c.root,ee),i.removedRBushNodeAABBs=[];else{var ve=i.safeMergeAABB.apply(i,[i.mergeDirtyAABBs(i.renderQueue)].concat((0,P.Z)(i.removedRBushNodeAABBs.map(function(sn){var Tn=sn.minX,zn=sn.minY,Vn=sn.maxX,ir=sn.maxY,hr=new Nr;return hr.setMinMax([Tn,zn,0],[Vn,ir,0]),hr}))));if(i.removedRBushNodeAABBs=[],Nr.isEmpty(ve)){i.renderQueue=[];return}var he=i.convertAABB2Rect(ve),pe=he.x,ye=he.y,_e=he.width,De=he.height,Be=Ke(i.vec3a,[pe,ye,0],i.vpMatrix),ze=Ke(i.vec3b,[pe+_e,ye,0],i.vpMatrix),Xe=Ke(i.vec3c,[pe,ye+De,0],i.vpMatrix),$e=Ke(i.vec3d,[pe+_e,ye+De,0],i.vpMatrix),ct=Math.min(Be[0],ze[0],$e[0],Xe[0]),ut=Math.min(Be[1],ze[1],$e[1],Xe[1]),St=Math.max(Be[0],ze[0],$e[0],Xe[0]),bt=Math.max(Be[1],ze[1],$e[1],Xe[1]),Et=Math.floor(ct),xt=Math.floor(ut),Dt=Math.ceil(St-ct),Ft=Math.ceil(bt-ut);ee.save(),i.clearRect(ee,Et,xt,Dt,Ft,s.background),ee.beginPath(),ee.rect(Et,xt,Dt,Ft),ee.clip(),ee.setTransform(i.vpMatrix[0],i.vpMatrix[1],i.vpMatrix[4],i.vpMatrix[5],i.vpMatrix[12],i.vpMatrix[13]);var Xt=s.renderer.getConfig(),an=Xt.enableDirtyRectangleRenderingDebug;an&&W.dispatchEvent(new vi(Aa.DIRTY_RECTANGLE,{dirtyRect:{x:Et,y:xt,width:Dt,height:Ft}}));var dn=i.searchDirtyObjects(ve);dn.sort(function(sn,Tn){return sn.sortable.renderOrder-Tn.sortable.renderOrder}).forEach(function(sn){sn&&sn.isVisible()&&!sn.isCulled()&&i.renderDisplayObject(sn,ee,i.context,Rs(i,li)[li],n)}),ee.restore(),i.renderQueue.forEach(function(sn){i.saveDirtyAABB(sn)}),i.renderQueue=[]}Rs(i,li)[li].restoreStack.forEach(function(){ee.restore()}),Rs(i,li)[li].restoreStack=[]}),l.hooks.render.tap(r.tag,function(ee){i.clearFullScreen||i.renderQueue.push(ee)})}},{key:"clearRect",value:function(t,n,i,a,s,o){t.clearRect(n,i,a,s),o&&(t.fillStyle=o,t.fillRect(n,i,a,s))}},{key:"renderDisplayObjectOptimized",value:function(t,n,i,a,s){var o=t.nodeName,l=!1,c=!1,h=this.context.styleRendererFactory[o],p=this.pathGeneratorFactory[o],C=t.parsedStyle.clipPath;if(C){l=!a.prevObject||!Wn(C.getWorldTransform(),a.prevObject.getWorldTransform()),l&&(this.applyWorldTransform(n,C),a.prevObject=null);var k=this.pathGeneratorFactory[C.nodeName];k&&(n.save(),c=!0,n.beginPath(),k(n,C.parsedStyle),n.closePath(),n.clip())}if(h){l=!a.prevObject||!Wn(t.getWorldTransform(),a.prevObject.getWorldTransform()),l&&this.applyWorldTransform(n,t);var W=!a.prevObject;if(!W){var j=a.prevObject.nodeName;o===Rt.TEXT?W=j!==Rt.TEXT:o===Rt.IMAGE?W=j!==Rt.IMAGE:W=j===Rt.TEXT||j===Rt.IMAGE}h.applyStyleToContext(n,t,W,a),a.prevObject=t}p&&(n.beginPath(),p(n,t.parsedStyle),o!==Rt.LINE&&o!==Rt.PATH&&o!==Rt.POLYLINE&&n.closePath()),h&&h.drawToContext(n,t,Rs(this,li)[li],this,s),c&&n.restore(),t.renderable.dirty=!1}},{key:"renderDisplayObject",value:function(t,n,i,a,s){var o=t.nodeName,l=a.restoreStack[a.restoreStack.length-1];l&&!(t.compareDocumentPosition(l)&Kr.DOCUMENT_POSITION_CONTAINS)&&(n.restore(),a.restoreStack.pop());var c=this.context.styleRendererFactory[o],h=this.pathGeneratorFactory[o],p=t.parsedStyle.clipPath;if(p){this.applyWorldTransform(n,p);var C=this.pathGeneratorFactory[p.nodeName];C&&(n.save(),a.restoreStack.push(t),n.beginPath(),C(n,p.parsedStyle),n.closePath(),n.clip())}c&&(this.applyWorldTransform(n,t),n.save(),this.applyAttributesToContext(n,t)),h&&(n.beginPath(),h(n,t.parsedStyle),o!==Rt.LINE&&o!==Rt.PATH&&o!==Rt.POLYLINE&&n.closePath()),c&&(c.render(n,t.parsedStyle,t,i,this,s),n.restore()),t.renderable.dirty=!1}},{key:"applyAttributesToContext",value:function(t,n){var i=n.parsedStyle,a=i.stroke,s=i.fill,o=i.opacity,l=i.lineDash,c=i.lineDashOffset;l&&t.setLineDash(l),Rn(c)||(t.lineDashOffset=c),Rn(o)||(t.globalAlpha*=o),!Rn(a)&&!Array.isArray(a)&&!a.isNone&&(t.strokeStyle=n.attributes.stroke),!Rn(s)&&!Array.isArray(s)&&!s.isNone&&(t.fillStyle=n.attributes.fill)}},{key:"convertAABB2Rect",value:function(t){var n=t.getMin(),i=t.getMax(),a=Math.floor(n[0]),s=Math.floor(n[1]),o=Math.ceil(i[0]),l=Math.ceil(i[1]),c=o-a,h=l-s;return{x:a,y:s,width:c,height:h}}},{key:"mergeDirtyAABBs",value:function(t){var n=new Nr;return t.forEach(function(i){var a=i.getRenderBounds();n.add(a);var s=i.renderable.dirtyRenderBounds;s&&n.add(s)}),n}},{key:"searchDirtyObjects",value:function(t){var n=t.getMin(),i=(0,m.Z)(n,2),a=i[0],s=i[1],o=t.getMax(),l=(0,m.Z)(o,2),c=l[0],h=l[1],p=this.rBush.search({minX:a,minY:s,maxX:c,maxY:h});return p.map(function(C){var k=C.displayObject;return k})}},{key:"saveDirtyAABB",value:function(t){var n=t.renderable;n.dirtyRenderBounds||(n.dirtyRenderBounds=new Nr);var i=t.getRenderBounds();i&&n.dirtyRenderBounds.update(i.center,i.halfExtents)}},{key:"applyWorldTransform",value:function(t,n,i){i?(ft(this.tmpMat4,n.getLocalTransform()),lt(this.tmpMat4,i,this.tmpMat4),lt(this.tmpMat4,this.vpMatrix,this.tmpMat4)):(ft(this.tmpMat4,n.getWorldTransform()),lt(this.tmpMat4,this.vpMatrix,this.tmpMat4)),t.setTransform(this.tmpMat4[0],this.tmpMat4[1],this.tmpMat4[4],this.tmpMat4[5],this.tmpMat4[12],this.tmpMat4[13])}},{key:"safeMergeAABB",value:function(){for(var t=new Nr,n=arguments.length,i=new Array(n),a=0;a<n;a++)i[a]=arguments[a];return i.forEach(function(s){t.add(s)}),t}}])}();f_.tag="CanvasRenderer";function rf(r,e,t,n,i,a,s){var o,l;if(r.image.nodeName==="rect"){var c=r.image.parsedStyle,h=c.width,p=c.height;l=n.contextService.getDPR();var C=n.config.offscreenCanvas;o=a.offscreenCanvasCreator.getOrCreateCanvas(C),o.width=h*l,o.height=p*l;var k=a.offscreenCanvasCreator.getOrCreateContext(C),W={restoreStack:[],prevObject:null,currentContext:new Map};r.image.forEach(function(K){i.renderDisplayObject(K,k,n,W,a)}),W.restoreStack.forEach(function(){k.restore()})}var j=s.getOrCreatePatternSync(e,r,t,o,l,e.getGeometryBounds().min,function(){e.renderable.dirty=!0,n.renderingService.dirtify()});return j}function af(r,e,t,n){var i;if(r.type===lo.LinearGradient||r.type===lo.RadialGradient){var a=e.getGeometryBounds(),s=a&&a.halfExtents[0]*2||1,o=a&&a.halfExtents[1]*2||1,l=a&&a.min||[0,0];i=n.getOrCreateGradient((0,H.Z)((0,H.Z)({type:r.type},r.value),{},{min:l,width:s,height:o}),t)}return i}var sf=["shadowBlur","shadowOffsetX","shadowOffsetY"],d_=["lineCap","lineJoin","miterLimit"],pi={globalAlpha:1,shadowBlur:0,shadowOffsetX:0,shadowOffsetY:0,shadowColor:"#000",filter:"none",globalCompositeOperation:"source-over",strokeStyle:"#000",strokeOpacity:1,lineWidth:1,lineDash:[],lineDashOffset:0,lineCap:"butt",lineJoin:"miter",miterLimit:10,fillStyle:"#000",fillOpacity:1},v_={};function Jr(r,e,t,n){var i=n.has(e)?n.get(e):pi[e];return i!==t&&(e==="lineDash"?r.setLineDash(t):r[e]=t,n.set(e,t)),i}var BD=function(){function r(e){(0,b.Z)(this,r),this.imagePool=e}return(0,z.Z)(r,[{key:"applyAttributesToContext",value:function(t,n){}},{key:"render",value:function(t,n,i,a,s,o){}},{key:"applyCommonStyleToContext",value:function(t,n,i,a){var s=i?v_:a.prevObject.parsedStyle,o=n.parsedStyle;(i||o.opacity!==s.opacity)&&Jr(t,"globalAlpha",Rn(o.opacity)?pi.globalAlpha:o.opacity,a.currentContext),(i||o.blend!==s.blend)&&Jr(t,"globalCompositeOperation",Rn(o.blend)?pi.globalCompositeOperation:o.blend,a.currentContext)}},{key:"applyStrokeFillStyleToContext",value:function(t,n,i,a){var s=i?v_:a.prevObject.parsedStyle,o=n.parsedStyle,l=o.lineWidth,c=l===void 0?pi.lineWidth:l,h=o.fill&&!o.fill.isNone,p=o.stroke&&!o.stroke.isNone&&c>0;if(p){if(i||n.attributes.stroke!==a.prevObject.attributes.stroke){var C=!Rn(o.stroke)&&!Array.isArray(o.stroke)&&!o.stroke.isNone?n.attributes.stroke:pi.strokeStyle;Jr(t,"strokeStyle",C,a.currentContext)}(i||o.lineWidth!==s.lineWidth)&&Jr(t,"lineWidth",Rn(o.lineWidth)?pi.lineWidth:o.lineWidth,a.currentContext),(i||o.lineDash!==s.lineDash)&&Jr(t,"lineDash",o.lineDash||pi.lineDash,a.currentContext),(i||o.lineDashOffset!==s.lineDashOffset)&&Jr(t,"lineDashOffset",Rn(o.lineDashOffset)?pi.lineDashOffset:o.lineDashOffset,a.currentContext);for(var k=0;k<d_.length;k++){var W=d_[k];(i||o[W]!==s[W])&&Jr(t,W,Rn(o[W])?pi[W]:o[W],a.currentContext)}}if(h&&(i||n.attributes.fill!==a.prevObject.attributes.fill)){var j=!Rn(o.fill)&&!Array.isArray(o.fill)&&!o.fill.isNone?n.attributes.fill:pi.fillStyle;Jr(t,"fillStyle",j,a.currentContext)}}},{key:"applyStyleToContext",value:function(t,n,i,a){var s=n.nodeName;this.applyCommonStyleToContext(t,n,i,a),s===Rt.IMAGE||this.applyStrokeFillStyleToContext(t,n,i,a)}},{key:"applyShadowAndFilterStyleToContext",value:function(t,n,i,a){var s=n.parsedStyle;if(i){Jr(t,"shadowColor",s.shadowColor.toString(),a.currentContext);for(var o=0;o<sf.length;o++){var l=sf[o];Jr(t,l,s[l]||pi[l],a.currentContext)}}s.filter&&s.filter.length&&Jr(t,"filter",n.attributes.filter,a.currentContext)}},{key:"clearShadowAndFilterStyleForContext",value:function(t,n,i,a){var s=arguments.length>4&&arguments[4]!==void 0?arguments[4]:!1;if(n){Jr(t,"shadowColor",pi.shadowColor,a.currentContext);for(var o=0;o<sf.length;o++){var l=sf[o];Jr(t,l,pi[l],a.currentContext)}}if(i)if(n&&s){var c=t.filter;!Rn(c)&&c.indexOf("drop-shadow")>-1&&Jr(t,"filter",c.replace(/drop-shadow\([^)]*\)/,"").trim()||pi.filter,a.currentContext)}else Jr(t,"filter",pi.filter,a.currentContext)}},{key:"fillToContext",value:function(t,n,i,a,s){var o=this,l=n.parsedStyle,c=l.fill,h=l.fillRule,p=null;if(Array.isArray(c)&&c.length>0)c.forEach(function(k){var W=Jr(t,"fillStyle",af(k,n,t,o.imagePool),i.currentContext);p=p!=null?p:W,h?t.fill(h):t.fill()});else{if(Ko(c)){var C=rf(c,n,t,n.ownerDocument.defaultView.context,a,s,this.imagePool);C&&(t.fillStyle=C,p=!0)}h?t.fill(h):t.fill()}p!==null&&Jr(t,"fillStyle",p,i.currentContext)}},{key:"strokeToContext",value:function(t,n,i,a,s){var o=this,l=n.parsedStyle.stroke,c=null;if(Array.isArray(l)&&l.length>0)l.forEach(function(C){var k=Jr(t,"strokeStyle",af(C,n,t,o.imagePool),i.currentContext);c=c!=null?c:k,t.stroke()});else{if(Ko(l)){var h=rf(l,n,t,n.ownerDocument.defaultView.context,a,s,this.imagePool);if(h){var p=Jr(t,"strokeStyle",h,i.currentContext);c=c!=null?c:p}}t.stroke()}c!==null&&Jr(t,"strokeStyle",c,i.currentContext)}},{key:"drawToContext",value:function(t,n,i,a,s){var o,l=n.nodeName,c=n.parsedStyle,h=c.opacity,p=h===void 0?pi.globalAlpha:h,C=c.fillOpacity,k=C===void 0?pi.fillOpacity:C,W=c.strokeOpacity,j=W===void 0?pi.strokeOpacity:W,K=c.lineWidth,Q=K===void 0?pi.lineWidth:K,ee=c.fill&&!c.fill.isNone,re=c.stroke&&!c.stroke.isNone&&Q>0;if(!(!ee&&!re)){var ve=!Rn(c.shadowColor)&&c.shadowBlur>0,he=c.shadowType==="inner",pe=((o=c.fill)===null||o===void 0?void 0:o.alpha)===0,ye=!!(c.filter&&c.filter.length),_e=ve&&re&&(l===Rt.PATH||l===Rt.LINE||l===Rt.POLYLINE||pe||he),De=null;if(ee){_e||this.applyShadowAndFilterStyleToContext(t,n,ve,i);var Be=p*k;De=Jr(t,"globalAlpha",Be,i.currentContext),this.fillToContext(t,n,i,a,s),_e||this.clearShadowAndFilterStyleForContext(t,ve,ye,i)}if(re){var ze=!1,Xe=p*j,$e=Jr(t,"globalAlpha",Xe,i.currentContext);if(De=ee?De:$e,_e&&(this.applyShadowAndFilterStyleToContext(t,n,ve,i),ze=!0,he)){var ct=t.globalCompositeOperation;t.globalCompositeOperation="source-atop",this.strokeToContext(t,n,i,a,s),t.globalCompositeOperation=ct,this.clearShadowAndFilterStyleForContext(t,ve,ye,i,!0)}this.strokeToContext(t,n,i,a,s),ze&&this.clearShadowAndFilterStyleForContext(t,ve,ye,i)}De!==null&&Jr(t,"globalAlpha",De,i.currentContext)}}}])}(),zg=function(r){function e(){return(0,b.Z)(this,e),_(this,e,arguments)}return(0,g.Z)(e,r),(0,z.Z)(e,[{key:"render",value:function(n,i,a,s,o,l){var c=i.fill,h=i.fillRule,p=i.opacity,C=p===void 0?1:p,k=i.fillOpacity,W=k===void 0?1:k,j=i.stroke,K=i.strokeOpacity,Q=K===void 0?1:K,ee=i.lineWidth,re=ee===void 0?1:ee,ve=i.lineCap,he=i.lineJoin,pe=i.shadowType,ye=i.shadowColor,_e=i.shadowBlur,De=i.filter,Be=i.miterLimit,ze=c&&!c.isNone,Xe=j&&!j.isNone&&re>0,$e=(c==null?void 0:c.alpha)===0,ct=!!(De&&De.length),ut=!Rn(ye)&&_e>0,St=a.nodeName,bt=pe==="inner",Et=Xe&&ut&&(St===Rt.PATH||St===Rt.LINE||St===Rt.POLYLINE||$e||bt);ze&&(n.globalAlpha=C*W,Et||of(a,n,ut),g_(n,a,c,h,s,o,l,this.imagePool),Et||this.clearShadowAndFilter(n,ct,ut)),Xe&&(n.globalAlpha=C*Q,n.lineWidth=re,Rn(Be)||(n.miterLimit=Be),Rn(ve)||(n.lineCap=ve),Rn(he)||(n.lineJoin=he),Et&&(bt&&(n.globalCompositeOperation="source-atop"),of(a,n,!0),bt&&(Fg(n,a,j,s,o,l,this.imagePool),n.globalCompositeOperation=pi.globalCompositeOperation,this.clearShadowAndFilter(n,ct,!0))),Fg(n,a,j,s,o,l,this.imagePool))}},{key:"clearShadowAndFilter",value:function(n,i,a){if(a&&(n.shadowColor="transparent",n.shadowBlur=0),i){var s=n.filter;!Rn(s)&&s.indexOf("drop-shadow")>-1&&(n.filter=s.replace(/drop-shadow\([^)]*\)/,"").trim()||"none")}}}])}(BD);function of(r,e,t){var 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ye=i.context.contextService.getDomElement();n.globalThis.navigator.msPointerEnabled?(ye.style.msContentZooming="none",ye.style.msTouchAction="none"):l.supportsPointerEvents&&(ye.style.touchAction="none"),l.supportsPointerEvents?Q(ye):re(ye),l.supportsTouchEvents&&ee(ye),o.useNativeClickEvent&&ye.addEventListener("click",K,!0),ye.addEventListener("wheel",j,{passive:!0,capture:!0})}),a.hooks.destroy.tap(r.tag,function(){var ye=i.context.contextService.getDomElement();n.globalThis.navigator.msPointerEnabled?(ye.style.msContentZooming="",ye.style.msTouchAction=""):l.supportsPointerEvents&&(ye.style.touchAction=""),l.supportsPointerEvents?ve(ye):pe(ye),l.supportsTouchEvents&&he(ye),o.useNativeClickEvent&&ye.removeEventListener("click",K,!0),ye.removeEventListener("wheel",j,!0)})}}])}();p_.tag="DOMInteraction";var HD=function(r){function e(){var t;(0,b.Z)(this,e);for(var n=arguments.length,i=new Array(n),a=0;a<n;a++)i[a]=arguments[a];return t=_(this,e,[].concat(i)),t.name="dom-interaction",t}return(0,g.Z)(e,r),(0,z.Z)(e,[{key:"init",value:function(){this.addRenderingPlugin(new p_)}},{key:"destroy",value:function(){this.removeAllRenderingPlugins()}}])}(oo);var jD="g-canvas-camera",m_=function(){function r(){(0,b.Z)(this,r),this.displayObjectHTMLElementMap=new WeakMap}return(0,z.Z)(r,[{key:"joinTransformMatrix",value:function(t){var n=arguments.length>1&&arguments[1]!==void 0?arguments[1]:[0,0,0];return"matrix(".concat([t[0],t[1],t[4],t[5],t[12]+n[0],t[13]+n[1]].join(","),")")}},{key:"apply",value:function(t,n){var i=this,a=t.camera,s=t.renderingContext,o=t.renderingService;this.context=t;var l=s.root.ownerDocument.defaultView,c=l.context.eventService.nativeHTMLMap,h=function(Q,ee){ee.style.transform=i.joinTransformMatrix(Q.getWorldTransform(),Q.getOrigin())},p=function(Q){var ee=Q.target;if(ee.nodeName===Rt.HTML){i.$camera||(i.$camera=i.createCamera(a));var 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Q=i.context.config,ee=Q.width,re=Q.height;i.$camera.parentElement.style.width="".concat(ee||0,"px"),i.$camera.parentElement.style.height="".concat(re||0,"px")}};o.hooks.init.tap(r.tag,function(){l.addEventListener(Aa.RESIZE,j),l.addEventListener(tr.MOUNTED,p),l.addEventListener(tr.UNMOUNTED,C),l.addEventListener(tr.ATTR_MODIFIED,k),l.addEventListener(tr.BOUNDS_CHANGED,W)}),o.hooks.endFrame.tap(r.tag,function(){i.$camera&&s.renderReasons.has(Ul.CAMERA_CHANGED)&&(i.$camera.style.transform=i.joinTransformMatrix(a.getOrthoMatrix()))}),o.hooks.destroy.tap(r.tag,function(){i.$camera&&i.$camera.remove(),l.removeEventListener(Aa.RESIZE,j),l.removeEventListener(tr.MOUNTED,p),l.removeEventListener(tr.UNMOUNTED,C),l.removeEventListener(tr.ATTR_MODIFIED,k),l.removeEventListener(tr.BOUNDS_CHANGED,W)})}},{key:"createCamera",value:function(t){var n=this.context.config,i=n.document,a=n.width,s=n.height,o=this.context.contextService.getDomElement(),l=o.parentNode;if(l){var 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l=n.parsedStyle.height;i.style.height=un(l)?"".concat(l,"px"):l.toString();break;case"zIndex":var c=n.parsedStyle.zIndex;i.style["z-index"]="".concat(c);break;case"visibility":var h=n.parsedStyle.visibility;i.style.visibility=h;break;case"pointerEvents":var p=n.parsedStyle.pointerEvents,C=p===void 0?"auto":p;i.style.pointerEvents=C;break;case"opacity":var k=n.parsedStyle.opacity;i.style.opacity="".concat(k);break;case"fill":var W=n.parsedStyle.fill,j="";Qu(W)?W.isNone?j="transparent":j=n.getAttribute("fill"):Array.isArray(W)?j=n.getAttribute("fill"):Ko(W),i.style.background=j;break;case"stroke":var K=n.parsedStyle.stroke,Q="";Qu(K)?K.isNone?Q="transparent":Q=n.getAttribute("stroke"):Array.isArray(K)?Q=n.getAttribute("stroke"):Ko(K),i.style["border-color"]=Q,i.style["border-style"]="solid";break;case"lineWidth":var ee=n.parsedStyle.lineWidth;i.style["border-width"]="".concat(ee||0,"px");break;case"lineDash":i.style["border-style"]="dashed";break;case"filter":var re=n.style.filter;i.style.filter=re;break;default:!Rn(n.style[t])&&n.style[t]!==""&&(i.style[t]=n.style[t])}}}])}();m_.tag="HTMLRendering";var GD=function(r){function e(){var t;(0,b.Z)(this,e);for(var n=arguments.length,i=new Array(n),a=0;a<n;a++)i[a]=arguments[a];return t=_(this,e,[].concat(i)),t.name="html-renderer",t}return(0,g.Z)(e,r),(0,z.Z)(e,[{key:"init",value:function(){this.addRenderingPlugin(new m_)}},{key:"destroy",value:function(){this.removeAllRenderingPlugins()}}])}(oo);var VD=function(){function r(e){(0,b.Z)(this,r),this.renderingContext=e.renderingContext,this.canvasConfig=e.config}return(0,z.Z)(r,[{key:"init",value:function(){var t=this.canvasConfig,n=t.container,i=t.canvas;if(i)this.$canvas=i,n&&i.parentElement!==n&&n.appendChild(i),this.$container=i.parentElement,this.canvasConfig.container=this.$container;else if(n&&(this.$container=dr(n)?document.getElementById(n):n,this.$container)){var a=document.createElement("canvas");this.$container.appendChild(a),this.$container.style.position||(this.$container.style.position="relative"),this.$canvas=a}this.context=this.$canvas.getContext("2d"),this.resize(this.canvasConfig.width,this.canvasConfig.height)}},{key:"getContext",value:function(){return this.context}},{key:"getDomElement",value:function(){return this.$canvas}},{key:"getDPR",value:function(){return this.dpr}},{key:"getBoundingClientRect",value:function(){if(this.$canvas.getBoundingClientRect)return this.$canvas.getBoundingClientRect()}},{key:"destroy",value:function(){this.$container&&this.$canvas&&this.$canvas.parentNode&&this.$container.removeChild(this.$canvas)}},{key:"resize",value:function(t,n){var i=this.canvasConfig.devicePixelRatio;this.dpr=i,this.$canvas&&(this.$canvas.width=this.dpr*t,this.$canvas.height=this.dpr*n,jS(this.$canvas,t,n)),this.renderingContext.renderReasons.add(Ul.CAMERA_CHANGED)}},{key:"applyCursorStyle",value:function(t){this.$container&&this.$container.style&&(this.$container.style.cursor=t)}},{key:"toDataURL",value:function(){var e=(0,so.Z)((0,Ki.Z)().mark(function n(){var i,a,s,o=arguments;return(0,Ki.Z)().wrap(function(c){for(;;)switch(c.prev=c.next){case 0:return i=o.length>0&&o[0]!==void 0?o[0]:{},a=i.type,s=i.encoderOptions,c.abrupt("return",this.context.canvas.toDataURL(a,s));case 3:case"end":return c.stop()}},n,this)}));function t(){return e.apply(this,arguments)}return t}()}])}(),ZD=function(r){function e(){var t;(0,b.Z)(this,e);for(var n=arguments.length,i=new Array(n),a=0;a<n;a++)i[a]=arguments[a];return t=_(this,e,[].concat(i)),t.name="canvas-context-register",t}return(0,g.Z)(e,r),(0,z.Z)(e,[{key:"init",value:function(){this.context.ContextService=VD}},{key:"destroy",value:function(){delete this.context.ContextService}}])}(oo),$c=function(r){function e(t){var n;return(0,b.Z)(this,e),n=_(this,e,[t]),n.registerPlugin(new ZD),n.registerPlugin(new ND),n.registerPlugin(new fD),n.registerPlugin(new WD),n.registerPlugin(new HD),n.registerPlugin(new DD),n.registerPlugin(new GD),n}return(0,g.Z)(e,r),(0,z.Z)(e)}(zw);function KD(r,e){if(r){var t;if(Ma(r))for(var n=0,i=r.length;n<i&&(t=e(r[n],n),t!==!1);n++);else if(ii(r)){for(var a in r)if(r.hasOwnProperty(a)&&(t=e(r[a],a),t===!1))break}}}var y_=KD,XD=Object.prototype.hasOwnProperty,ul=function(r,e){if(r===null||!Vl(r))return{};var t={};return y_(e,function(n){XD.call(r,n)&&(t[n]=r[n])}),t},YD=function(r,e){var t={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&e.indexOf(n)<0&&(t[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var i=0,n=Object.getOwnPropertySymbols(r);i<n.length;i++)e.indexOf(n[i])<0&&Object.prototype.propertyIsEnumerable.call(r,n[i])&&(t[n[i]]=r[n[i]]);return t};class lf extends fs{constructor(e){super(Object.assign(Object.assign({},e),{style:Object.assign({},lf.defaultStyleProps,e.style)})),this.rootPointerEvent=new nh(null),this.forwardEvents=t=>{const n=this.context.canvas,i=n.context.renderingContext.root.ownerDocument.defaultView;this.normalizeToPointerEvent(t,i).forEach(s=>{const o=this.bootstrapEvent(this.rootPointerEvent,s,i,t);Yc(n.context.eventService,"mappingTable.pointerupoutside",[]),n.context.eventService.mapEvent(o)})}}get eventService(){return this.context.canvas.context.eventService}get events(){return[kt.CLICK,kt.POINTER_DOWN,kt.POINTER_MOVE,kt.POINTER_UP,kt.POINTER_OVER,kt.POINTER_LEAVE]}getDomElement(){return this.getShape("key").getDomElement()}render(e=this.parsedAttributes,t=this){this.drawKeyShape(e,t),this.drawPortShapes(e,t)}getKeyStyle(e){const t=ul(e,["dx","dy","innerHTML","pointerEvents","cursor"]),{dx:n=0,dy:i=0}=t,a=YD(t,["dx","dy"]),[s,o]=this.getSize(e);return Object.assign(Object.assign({x:n,y:i},a),{width:s,height:o})}drawKeyShape(e,t){const n=this.getKeyStyle(e),{x:i,y:a,width:s=0,height:o=0}=n,l=this.upsert("key-container",Ii,{x:i,y:a,width:s,height:o,opacity:0},t);return this.upsert("key",Nc,n,l)}connectedCallback(){if(!(this.context.canvas.getRenderer("main")instanceof $c))return;const n=this.getDomElement();this.events.forEach(i=>{n.addEventListener(i,this.forwardEvents)})}attributeChangedCallback(e,t,n){e==="zIndex"&&t!==n&&(this.getDomElement().style.zIndex=n)}destroy(){const e=this.getDomElement();this.events.forEach(t=>{e.removeEventListener(t,this.forwardEvents)}),super.destroy()}normalizeToPointerEvent(e,t){const n=[];if(t.isTouchEvent(e))for(let i=0;i<e.changedTouches.length;i++){const a=e.changedTouches[i];Gn(a.button)&&(a.button=0),Gn(a.buttons)&&(a.buttons=1),Gn(a.isPrimary)&&(a.isPrimary=e.touches.length===1&&e.type==="touchstart"),Gn(a.width)&&(a.width=a.radiusX||1),Gn(a.height)&&(a.height=a.radiusY||1),Gn(a.tiltX)&&(a.tiltX=0),Gn(a.tiltY)&&(a.tiltY=0),Gn(a.pointerType)&&(a.pointerType="touch"),Gn(a.pointerId)&&(a.pointerId=a.identifier||0),Gn(a.pressure)&&(a.pressure=a.force||.5),Gn(a.twist)&&(a.twist=0),Gn(a.tangentialPressure)&&(a.tangentialPressure=0),a.isNormalized=!0,a.type=e.type,n.push(a)}else if(t.isMouseEvent(e)){const i=e;Gn(i.isPrimary)&&(i.isPrimary=!0),Gn(i.width)&&(i.width=1),Gn(i.height)&&(i.height=1),Gn(i.tiltX)&&(i.tiltX=0),Gn(i.tiltY)&&(i.tiltY=0),Gn(i.pointerType)&&(i.pointerType="mouse"),Gn(i.pointerId)&&(i.pointerId=1),Gn(i.pressure)&&(i.pressure=.5),Gn(i.twist)&&(i.twist=0),Gn(i.tangentialPressure)&&(i.tangentialPressure=0),i.isNormalized=!0,n.push(i)}else n.push(e);return n}transferMouseData(e,t){e.isTrusted=t.isTrusted,e.srcElement=t.srcElement,e.timeStamp=performance.now(),e.type=t.type,e.altKey=t.altKey,e.metaKey=t.metaKey,e.shiftKey=t.shiftKey,e.ctrlKey=t.ctrlKey,e.button=t.button,e.buttons=t.buttons,e.client.x=t.clientX,e.client.y=t.clientY,e.movement.x=t.movementX,e.movement.y=t.movementY,e.page.x=t.pageX,e.page.y=t.pageY,e.screen.x=t.screenX,e.screen.y=t.screenY,e.relatedTarget=null}bootstrapEvent(e,t,n,i){e.view=n,e.originalEvent=null,e.nativeEvent=i,e.pointerId=t.pointerId,e.width=t.width,e.height=t.height,e.isPrimary=t.isPrimary,e.pointerType=t.pointerType,e.pressure=t.pressure,e.tangentialPressure=t.tangentialPressure,e.tiltX=t.tiltX,e.tiltY=t.tiltY,e.twist=t.twist,this.transferMouseData(e,t);const{x:a,y:s}=this.getViewportXY(t);e.viewport.x=a,e.viewport.y=s;const[o,l]=this.context.canvas.getCanvasByViewport([a,s]);return e.canvas.x=o,e.canvas.y=l,e.global.copyFrom(e.canvas),e.offset.copyFrom(e.canvas),e.isTrusted=i.isTrusted,e.type==="pointerleave"&&(e.type="pointerout"),e}getViewportXY(e){let t,n;const{offsetX:i,offsetY:a,clientX:s,clientY:o}=e;if(!Rn(i)&&!Rn(a))t=i,n=a;else{const l=this.eventService.client2Viewport({x:s,y:o});t=l.x,n=l.y}return{x:t,y:n}}onframe(){super.onframe();const{opacity:e}=this.attributes;this.getDomElement().style.opacity=`${e}`}}lf.defaultStyleProps={size:[160,80],halo:!1,icon:!1,label:!1,pointerEvents:"auto"};var __=function(r,e){var t={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&e.indexOf(n)<0&&(t[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var i=0,n=Object.getOwnPropertySymbols(r);i<n.length;i++)e.indexOf(n[i])<0&&Object.prototype.propertyIsEnumerable.call(r,n[i])&&(t[n[i]]=r[n[i]]);return t};class cf extends fs{constructor(e){super(Ai({style:cf.defaultStyleProps},e))}getKeyStyle(e){const[t,n]=this.getSize(e),i=super.getKeyStyle(e),{fillOpacity:a,opacity:s=a}=i,o=__(i,["fillOpacity","opacity"]);return Object.assign(Object.assign({opacity:s},o),{width:t,height:n,x:-t/2,y:-n/2})}getHaloStyle(e){if(e.halo===!1)return!1;const t=this.getShape("key").attributes,{fill:n,stroke:i}=t,a=__(t,["fill","stroke"]),s=gi(this.getGraphicStyle(e),"halo"),o=Number(s.lineWidth),[l,c]=Jn(this.getSize(e),[o,o]);return Object.assign(Object.assign({},s),{width:l,height:c,fill:"transparent",x:-l/2,y:-c/2})}getIconStyle(e){const t=super.getIconStyle(e),[n,i]=this.getSize(e);return t?Object.assign({width:n*Ys,height:i*Ys},t):!1}drawKeyShape(e,t){const n=this.upsert("key",Og,this.getKeyStyle(e),t);return Dg(this),n}drawHaloShape(e,t){this.upsert("halo",Ii,this.getHaloStyle(e),t)}update(e){super.update(e),e&&("x"in e||"y"in e||"z"in e)&&Lg(this)}}cf.defaultStyleProps={size:32};class QD extends fs{constructor(e){super(e)}getKeyStyle(e){const[t,n]=this.getSize(e);return Object.assign(Object.assign({},super.getKeyStyle(e)),{width:t,height:n,x:-t/2,y:-n/2})}getIconStyle(e){const t=super.getIconStyle(e),{width:n,height:i}=this.getShape("key").attributes;return t?Object.assign({width:n*Ys,height:i*Ys},t):!1}drawKeyShape(e,t){return this.upsert("key",Ii,this.getKeyStyle(e),t)}}class JD extends Qh{constructor(e){super(e)}getInnerR(e){return e.innerR||this.getOuterR(e)*3/8}getOuterR(e){return Math.min(...this.getSize(e))/2}getPoints(e){return FL(this.getOuterR(e),this.getInnerR(e))}getIconStyle(e){const t=super.getIconStyle(e),n=this.getInnerR(e)*2*Ys;return t?Object.assign({width:n,height:n},t):!1}getPortXY(e,t){const{placement:n="top"}=t,i=this.getShape("key").getLocalBounds(),a=UL(this.getOuterR(e),this.getInnerR(e));return Zg(i,n,a,!1)}}class uf extends Qh{constructor(e){super(Ai({style:uf.defaultStyleProps},e))}getPoints(e){const{direction:t}=e,[n,i]=this.getSize(e);return WL(n,i,t)}getPortXY(e,t){const{direction:n}=e,{placement:i="top"}=t,a=this.getShape("key").getLocalBounds(),[s,o]=this.getSize(e),l=HL(s,o,n);return Zg(a,i,l,!1)}getIconStyle(e){const{icon:t,iconText:n,iconSrc:i,direction:a}=e;if(t===!1||Ls(n||i))return!1;const s=gi(this.getGraphicStyle(e),"icon"),o=this.getShape("key").getLocalBounds(),[l,c]=TC(o,a),h=AC(o,a)*2*Ys;return Object.assign({x:l,y:c,width:h,height:h},s)}}uf.defaultStyleProps={size:40,direction:"up"};var E_=function(r,e){var t={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&e.indexOf(n)<0&&(t[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var i=0,n=Object.getOwnPropertySymbols(r);i<n.length;i++)e.indexOf(n[i])<0&&Object.prototype.propertyIsEnumerable.call(r,n[i])&&(t[n[i]]=r[n[i]]);return t};class Yl extends fs{constructor(e){super(Ai({style:Yl.defaultStyleProps},e)),this.type="combo",this.updateComboPosition(this.parsedAttributes)}getKeySize(e){const{collapsed:t,childrenNode:n=[]}=e;return n.length===0?this.getEmptyKeySize(e):t?this.getCollapsedKeySize(e):this.getExpandedKeySize(e)}getEmptyKeySize(e){const{padding:t,collapsedSize:n}=e,[i,a,s,o]=os(t);return Jn(Pa(n),[o+a,i+s,0])}getCollapsedKeySize(e){return Pa(e.collapsedSize)}getExpandedKeySize(e){const t=this.getContentBBox(e);return[Os(t),Ps(t),0]}getContentBBox(e){const{childrenNode:t=[],padding:n}=e,i=t.map(s=>this.context.element.getElement(s)).filter(Boolean);if(i.length===0){const s=new Nr,{x:o=0,y:l=0,size:c}=e,[h,p]=Pa(c);return s.setMinMax([o-h/2,l-p/2,0],[o+h/2,l+p/2,0]),s}const a=Hc(i.map(s=>s.getBounds()));return n?go(a,n):a}drawCollapsedMarkerShape(e,t){const n=this.getCollapsedMarkerStyle(e);this.upsert("collapsed-marker",a_,n,t),Dg(this)}getCollapsedMarkerStyle(e){if(!e.collapsed||!e.collapsedMarker)return!1;const t=gi(this.getGraphicStyle(e),"collapsedMarker"),{type:n}=t,i=E_(t,["type"]),a=this.getShape("key"),[s,o]=Xs(a.getLocalBounds(),"center"),l=Object.assign(Object.assign({},i),{x:s,y:o});if(n){const c=this.getCollapsedMarkerText(n,e);Object.assign(l,{text:c})}return l}getCollapsedMarkerText(e,t){const{childrenData:n=[]}=t,{model:i}=this.context;return e==="descendant-count"?i.getDescendantsData(this.id).length.toString():e==="child-count"?n.length.toString():e==="node-count"?i.getDescendantsData(this.id).filter(a=>i.getElementType(wt(a))==="node").length.toString():En(e)?e(n):""}getComboPosition(e){const{x:t=0,y:n=0,collapsed:i,childrenData:a=[]}=e;if(a.length===0)return[+t,+n,0];if(i){const{model:s}=this.context,o=s.getDescendantsData(this.id).filter(l=>!s.isCombo(wt(l)));if(o.length>0&&o.some(_P)){const l=o.reduce((c,h)=>Jn(c,xi(h)),[0,0,0]);return us(l,o.length)}return[+t,+n,0]}return this.getContentBBox(e).center}getComboStyle(e){const[t,n]=this.getComboPosition(e);return{x:t,y:n,transform:[["translate",t,n]]}}updateComboPosition(e){const t=this.getComboStyle(e);Object.assign(this.style,t);const{x:n,y:i}=t;this.context.model.syncNodeLikeDatum({id:this.id,style:{x:n,y:i}}),Lg(this)}render(e,t=this){super.render(e,t),this.drawCollapsedMarkerShape(e,t)}update(e={}){super.update(e),this.updateComboPosition(this.parsedAttributes)}onframe(){super.onframe(),this.attributes.collapsed||this.updateComboPosition(this.parsedAttributes),this.drawKeyShape(this.parsedAttributes,this)}animate(e,t){const n=super.animate(this.attributes.collapsed?e:e.map(i=>{var{x:a,y:s,z:o,transform:l}=i,c=E_(i,["x","y","z","transform"]);return c}),t);return n&&new Proxy(n,{set:(i,a,s)=>(a==="currentTime"&&Promise.resolve().then(()=>this.onframe()),Reflect.set(i,a,s))})}}Yl.defaultStyleProps={childrenNode:[],droppable:!0,draggable:!0,collapsed:!1,collapsedSize:32,collapsedMarker:!0,collapsedMarkerZIndex:1,collapsedMarkerFontSize:12,collapsedMarkerTextAlign:"center",collapsedMarkerTextBaseline:"middle",collapsedMarkerType:"child-count"};class qD extends Yl{constructor(e){super(e)}drawKeyShape(e,t){return this.upsert("key",Ws,this.getKeyStyle(e),t)}getKeyStyle(e){const{collapsed:t}=e,n=super.getKeyStyle(e),[i]=this.getKeySize(e);return Object.assign(Object.assign(Object.assign({},n),t&&gi(n,"collapsed")),{r:i/2})}getCollapsedKeySize(e){const[t,n]=Pa(e.collapsedSize),i=Math.max(t,n)/2;return[i*2,i*2,0]}getExpandedKeySize(e){const t=this.getContentBBox(e),[n,i]=fo(t),a=Math.sqrt(Math.pow(n,2)+Math.pow(i,2))/2;return[a*2,a*2,0]}getIntersectPoint(e,t=!1){const n=this.getShape("key").getBounds();return Vh(e,n,t)}}class $D extends Yl{constructor(e){super(e)}drawKeyShape(e,t){return this.upsert("key",Ii,this.getKeyStyle(e),t)}getKeyStyle(e){const t=super.getKeyStyle(e),[n,i]=this.getKeySize(e);return Object.assign(Object.assign(Object.assign({},t),e.collapsed&&gi(t,"collapsed")),{width:n,height:i,x:-n/2,y:-i/2})}}var eL=function(r,e){if(!Fc(r))return r;for(var t=[],n=0;n<r.length;n++){var i=r[n];e(i,n)&&t.push(i)}return t},tL=eL,nL=function(r,e){return Fc(r)?r.indexOf(e)>-1:!1},rL=nL,iL=function(r,e){return e===void 0&&(e=[]),tL(r,function(t){return!rL(e,t)})},aL=iL;const sL={padding:10};function x_(r,e,t,n,i,a){const{padding:s}=Object.assign(sL,a),o=vo(t,s),l=vo(n,s),c=[r,...i,e];let h=null;const p=[];for(let C=0,k=c.length;C<k-1;C++){const W=C+1,j=c[C],K=c[W],Q=xP(j,K);let ee=null;if(C===0)if(W===k-1)if(o.intersects(l))ee=Wg(j,K,o,l);else if(!Ch(j,o)&&!Ch(K,l)){const re=nl(j,o),ve=nl(K,l);ee=w_(re,ve,sa(re,ve)),ee.points.unshift(re),ee.points.push(ve)}else Q||(ee=lL(j,K,o,l));else 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xo{constructor(e){super(Ai({style:hl.defaultStyleProps},e))}getKeyPath(e){const[t,n]=this.getEndpoints(e),{controlPoints:i,curvePosition:a,curveOffset:s}=e,o=this.getControlPoints(t,n,hL(a),uL(s),i);return A_(t,n,o)}getControlPoints(e,t,n,i,a){return(a==null?void 0:a.length)===2?a:[Hg(e,t,n[0],i[0]),Hg(e,t,n[1],i[1])]}}hl.defaultStyleProps={curvePosition:.5,curveOffset:20};class df extends hl{constructor(e){super(Ai({style:df.defaultStyleProps},e))}getControlPoints(e,t,n,i){const a=t[0]-e[0];return[[e[0]+a*n[0]+i[0],e[1]],[t[0]-a*n[1]+i[1],t[1]]]}}df.defaultStyleProps={curvePosition:[.5,.5],curveOffset:[0,0]};class vf extends hl{constructor(e){super(Ai({style:vf.defaultStyleProps},e))}get ref(){return this.context.model.getRootsData()[0]}getEndpoints(e){if(this.sourceNode.id===this.ref.id)return super.getEndpoints(e);const t=xi(this.ref),n=this.sourceNode.getIntersectPoint(t,!0),i=this.targetNode.getIntersectPoint(t);return[n,i]}toRadialCoordinate(e){const t=xi(this.ref),n=Ur(e,t),i=B1(Or(e,t));return[n,i]}getControlPoints(e,t,n,i){const[a,s]=this.toRadialCoordinate(e),[o]=this.toRadialCoordinate(t),l=o-a;return[[e[0]+(l*n[0]+i[0])*Math.cos(s),e[1]+(l*n[0]+i[0])*Math.sin(s)],[t[0]-(l*n[1]-i[0])*Math.cos(s),t[1]-(l*n[1]-i[0])*Math.sin(s)]]}}vf.defaultStyleProps={curvePosition:.5,curveOffset:20};class gf extends hl{constructor(e){super(Ai({style:gf.defaultStyleProps},e))}getControlPoints(e,t,n,i){const a=t[1]-e[1];return[[e[0],e[1]+a*n[0]+i[0]],[t[0],t[1]-a*n[1]+i[1]]]}}gf.defaultStyleProps={curvePosition:[.5,.5],curveOffset:[0,0]};class pf extends xo{constructor(e){super(Ai({style:pf.defaultStyleProps},e))}getKeyPath(e){const[t,n]=this.getEndpoints(e);return[["M",t[0],t[1]],["L",n[0],n[1]]]}}pf.defaultStyleProps={};const 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i=al(r.getCenter()),a=al(e.getCenter()),s=Object.assign(TL,n),{gridSize:o}=s,l=s.enableObstacleAvoidance?t:[r,e],c=CL(l,s),h=fl(i,o),p=fl(a,o),C=I_(i,r,s.startDirections,s),k=I_(a,e,s.endDirections,s);C.forEach(_e=>delete c[Qs(_e)]),k.forEach(_e=>delete c[Qs(_e)]);const W={},j={},K={},Q={},ee={},re=new LL;for(let _e=0;_e<C.length;_e++){const De=C[_e],Be=Qs(De);W[Be]=De,Q[Be]=0,ee[Be]=R_(De,k,s.distFunc),re.add({id:Be,value:ee[Be]})}const ve=k.map(_e=>Qs(_e));let he=s.maximumLoops,pe,ye=1/0;for(const[_e,De]of Object.entries(W))ee[_e]<=ye&&(ye=ee[_e],pe=De);for(;Object.keys(W).length>0&&he>0;){const _e=re.minId(!1);if(_e)pe=W[_e];else break;const De=Qs(pe);if(ve.includes(De))return PL(pe,K,h,a,C,p,o);delete W[De],re.remove(De),j[De]=!0;for(const Be of Object.values(s.directionMap)){const ze=Jn(pe,[Be.stepX,Be.stepY]),Xe=Qs(ze);if(j[Xe])continue;const $e=L_(pe,ze,K,h);if($e>s.maxAllowedDirectionChange||c[Xe])continue;W[Xe]||(W[Xe]=ze);const ct=s.penalties[$e],ut=s.distFunc(pe,ze)+(isNaN(ct)?o:ct),St=Q[De]+ut,bt=Q[Xe];bt&&St>=bt||(K[Xe]=pe,Q[Xe]=St,ee[Xe]=St+R_(ze,k,s.distFunc),re.add({id:Xe,value:ee[Xe]}))}he-=1}return[]}class LL{constructor(){this.arr=[],this.map={},this.arr=[],this.map={}}_innerAdd(e,t){let n=0,i=t-1;for(;i-n>1;){const a=Math.floor((n+i)/2);if(this.arr[a].value>e.value)i=a;else if(this.arr[a].value<e.value)n=a;else{this.arr.splice(a,0,e),this.map[e.id]=!0;return}}this.arr.splice(i,0,e),this.map[e.id]=!0}add(e){delete this.map[e.id];const t=this.arr.length;if(!t||this.arr[t-1].value<e.value){this.arr.push(e),this.map[e.id]=!0;return}this._innerAdd(e,t)}remove(e){this.map[e]&&delete this.map[e]}_clearAndGetMinId(){let e;for(let t=this.arr.length-1;t>=0;t--)this.map[this.arr[t].id]?e=this.arr[t].id:this.arr.splice(t,1);return e}_findFirstId(){for(;this.arr.length;){const e=this.arr.shift();if(this.map[e.id])return e.id}}minId(e){return e?this._clearAndGetMinId():this._findFirstId()}}class mf extends xo{constructor(e){super(Ai({style:mf.defaultStyleProps},e))}getControlPoints(e){const{router:t}=e,{sourceNode:n,targetNode:i}=this,[a,s]=this.getEndpoints(e,!1);let o=[];if(!t)o=e.controlPoints;else if(t.type==="shortest-path"){const l=this.context.element.getNodes();o=DL(n,i,l,t),o.length||(o=x_(a,s,n,i,e.controlPoints,{padding:t.offset}))}else t.type==="orth"&&(o=x_(a,s,n,i,e.controlPoints,t));return o}getPoints(e){const t=this.getControlPoints(e),[n,i]=this.getEndpoints(e,!0,t);return[n,...t,i]}getKeyPath(e){const t=this.getPoints(e);return jg(t,e.radius)}getLoopPath(e){const{sourcePort:t,targetPort:n,radius:i}=e,a=this.sourceNode,s=vo(a),o=Math.max(Os(s),Ps(s))/4,{placement:l,clockwise:c,dist:h=o}=gi(this.getGraphicStyle(e),"loop");return mL(a,i,l,c,h,t,n)}}mf.defaultStyleProps={radius:0,controlPoints:[],router:!1};class yf extends xo{constructor(e){super(Ai({style:yf.defaultStyleProps},e))}getKeyPath(e){const{curvePosition:t,curveOffset:n}=e,[i,a]=this.getEndpoints(e),s=e.controlPoint||Hg(i,a,t,n);return fL(i,a,s)}}yf.defaultStyleProps={curvePosition:.5,curveOffset:30};var RL=function(r,e){var t={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&e.indexOf(n)<0&&(t[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var i=0,n=Object.getOwnPropertySymbols(r);i<n.length;i++)e.indexOf(n[i])<0&&Object.prototype.propertyIsEnumerable.call(r,n[i])&&(t[n[i]]=r[n[i]]);return t};function tu(r){return r instanceof fs&&r.type==="node"}function N_(r){return r instanceof xo}function Vg(r){return r instanceof Yl}function IL(r){return tu(r)||N_(r)||Vg(r)}function NL(r,e){return!r||!e?!1:r===e}const BL={top:[.5,0],right:[1,.5],bottom:[.5,1],left:[0,.5],default:[.5,.5]};function Zg(r,e,t=BL,n=!0){const i=[.5,.5],a=dr(e)?aa(t,e.toLocaleLowerCase(),i):e;if(!n&&dr(e))return 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Xg(r,e){if(!r||!e)return[0,0,0];const t=Gl(e)?e:tu(e)?e.getCenter():e.getPosition();return r.getIntersectPoint(t)||r.getCenter()}function F_(r,e="bottom",t=0,n=0,i=!1){const a=e.split("-"),[s,o]=Xs(r,e),l=a.includes("left")?"right":a.includes("right")?"left":"center";let c=a.includes("top")?"bottom":a.includes("bottom")?"top":"middle";return i&&(c=c==="top"?"bottom":c==="bottom"?"top":c),{transform:[["translate",s+t,o+n]],textBaseline:c,textAlign:l}}function FL(r,e){return[[0,-r],[e*Math.cos(3*Math.PI/10),-e*Math.sin(3*Math.PI/10)],[r*Math.cos(Math.PI/10),-r*Math.sin(Math.PI/10)],[e*Math.cos(Math.PI/10),e*Math.sin(Math.PI/10)],[r*Math.cos(3*Math.PI/10),r*Math.sin(3*Math.PI/10)],[0,e],[-r*Math.cos(3*Math.PI/10),r*Math.sin(3*Math.PI/10)],[-e*Math.cos(Math.PI/10),e*Math.sin(Math.PI/10)],[-r*Math.cos(Math.PI/10),-r*Math.sin(Math.PI/10)],[-e*Math.cos(3*Math.PI/10),-e*Math.sin(3*Math.PI/10)]]}function UL(r,e){const t={};return t.top=[0,-r],t.left=[-r*Math.cos(Math.PI/10),-r*Math.sin(Math.PI/10)],t["left-bottom"]=[-r*Math.cos(3*Math.PI/10),r*Math.sin(3*Math.PI/10)],t.bottom=[0,e],t["right-bottom"]=[r*Math.cos(3*Math.PI/10),r*Math.sin(3*Math.PI/10)],t.right=t.default=[r*Math.cos(Math.PI/10),-r*Math.sin(Math.PI/10)],t}function WL(r,e,t){const n=e/2,i=r/2,a={up:[[-i,n],[i,n],[0,-n]],left:[[-i,0],[i,n],[i,-n]],right:[[-i,n],[-i,-n],[i,0]],down:[[-i,-n],[i,-n],[0,n]]};return a[t]||a.up}function HL(r,e,t){const n=e/2,i=r/2,a={};return t==="down"?(a.bottom=a.default=[0,n],a.right=[i,-n],a.left=[-i,-n]):t==="left"?(a.top=[i,-n],a.bottom=[i,n],a.left=a.default=[-i,0]):t==="right"?(a.top=[-i,-n],a.bottom=[-i,n],a.right=a.default=[i,0]):(a.left=[-i,n],a.top=a.default=[0,-n],a.right=[i,n]),a}function sU(r,e){return[[r/2,-e/2],[r/2,e/2],[-r/2,e/2],[-r/2,-e/2]]}function jL(r,e){return[[0,-e/2],[r/2,0],[0,e/2],[-r/2,0]]}function GL(r){return aa(r,["style","visibility"])!=="hidden"}function VL(r,e){const{zIndex:t,transform:n,transformOrigin:i,visibility:a,cursor:s,clipPath:o,component:l}=e,c=RL(e,["zIndex","transform","transformOrigin","visibility","cursor","clipPath","component"]);Object.assign(r.attributes,c),n&&r.setAttribute("transform",n),un(t)&&r.setAttribute("zIndex",t),i&&r.setAttribute("transformOrigin",i),a&&r.setAttribute("visibility",a),s&&r.setAttribute("cursor",s),o&&r.setAttribute("clipPath",o),l&&r.setAttribute("component",l)}function Yg(r,e){"update"in r?r.update(e):r.attr(e)}function ZL(r){return[[0,r],[r*Math.sqrt(3)/2,r/2],[r*Math.sqrt(3)/2,-r/2],[0,-r],[-r*Math.sqrt(3)/2,-r/2],[-r*Math.sqrt(3)/2,r/2]]}function KL(r){Yc(r,"__to_be_destroyed__",!0)}function _f(r){return aa(r,"__to_be_destroyed__",!1)}var XL=function(r,e,t,n){function i(a){return a instanceof t?a:new t(function(s){s(a)})}return new(t||(t=Promise))(function(a,s){function o(h){try{c(n.next(h))}catch(p){s(p)}}function l(h){try{c(n.throw(h))}catch(p){s(p)}}function c(h){h.done?a(h.value):i(h.value).then(o,l)}c((n=n.apply(r,e||[])).next())})};class Ef extends Oa{constructor(e,t){super(e,Object.assign({},Ef.defaultOptions,t)),this.onCollapseExpand=n=>XL(this,void 0,void 0,function*(){if(!this.validate(n))return;const{target:i}=n;if(!IL(i))return;const a=i.id,{model:s,graph:o}=this.context,l=s.getElementDataById(a);if(!l)return!1;const{onCollapse:c,onExpand:h,animation:p,align:C}=this.options;xa(l)?(yield o.expandElement(a,{animation:p,align:C}),h==null||h(a)):(yield o.collapseElement(a,{animation:p,align:C}),c==null||c(a))}),this.bindEvents()}update(e){this.unbindEvents(),super.update(e),this.bindEvents()}bindEvents(){const{graph:e}=this.context,{trigger:t}=this.options;e.on(`node:${t}`,this.onCollapseExpand),e.on(`combo:${t}`,this.onCollapseExpand)}unbindEvents(){const{graph:e}=this.context,{trigger:t}=this.options;e.off(`node:${t}`,this.onCollapseExpand),e.off(`combo:${t}`,this.onCollapseExpand)}validate(e){if(this.destroyed)return!1;const{enable:t}=this.options;return En(t)?t(e):!!t}destroy(){this.unbindEvents(),super.destroy()}}Ef.defaultOptions={enable:!0,animation:!0,trigger:kt.DBLCLICK,align:!0};var xf={},YL=function(r){return r=r||"g",xf[r]?xf[r]+=1:xf[r]=1,r+xf[r]},bf=function(r,e,t,n){function i(a){return a instanceof t?a:new t(function(s){s(a)})}return new(t||(t=Promise))(function(a,s){function o(h){try{c(n.next(h))}catch(p){s(p)}}function l(h){try{c(n.throw(h))}catch(p){s(p)}}function c(h){h.done?a(h.value):i(h.value).then(o,l)}c((n=n.apply(r,e||[])).next())})};const QL="g6-create-edge-assist-edge-id",wf="g6-create-edge-assist-node-id";class Mf extends Oa{constructor(e,t){super(e,Object.assign({},Mf.defaultOptions,t)),this.drop=n=>bf(this,void 0,void 0,function*(){const{targetType:i}=n;["combo","node"].includes(i)&&this.source?yield this.handleCreateEdge(n):yield this.cancelEdge()}),this.handleCreateEdge=n=>bf(this,void 0,void 0,function*(){var i,a,s;if(!this.validate(n))return;const{graph:o,canvas:l,batch:c,element:h}=this.context,{style:p}=this.options;if(this.source){this.createEdge(n),yield this.cancelEdge();return}c.startBatch(),l.setCursor("crosshair"),this.source=this.getSelectedNodeIDs([n.target.id])[0];const C=o.getElementData(this.source);o.addNodeData([{id:wf,style:{visibility:"hidden",ports:[{key:"port-1",placement:[.5,.5]}],x:(i=C.style)===null||i===void 0?void 0:i.x,y:(a=C.style)===null||a===void 0?void 0:a.y}}]),o.addEdgeData([{id:QL,source:this.source,target:wf,style:Object.assign({pointerEvents:"none"},p)}]),yield(s=h.draw({animation:!1}))===null||s===void 0?void 0:s.finished}),this.updateAssistEdge=n=>bf(this,void 0,void 0,function*(){var i;if(!this.source)return;const{model:a,element:s}=this.context;a.translateNodeTo(wf,[n.canvas.x,n.canvas.y]),yield(i=s.draw({animation:!1,silence:!0}))===null||i===void 0?void 0:i.finished}),this.createEdge=n=>{var i,a;const{graph:s}=this.context,{style:o,onFinish:l,onCreate:c}=this.options;if(((i=n.target)===null||i===void 0?void 0:i.id)===void 0||this.source===void 0)return;const p=(a=this.getSelectedNodeIDs([n.target.id]))===null||a===void 0?void 0:a[0],C=`${this.source}-${p}-${YL()}`,k=c({id:C,source:this.source,target:p,style:o});s.addEdgeData([k]),l(k)},this.cancelEdge=()=>bf(this,void 0,void 0,function*(){var n;if(!this.source)return;const{graph:i,element:a,batch:s}=this.context;i.removeNodeData([wf]),this.source=void 0,yield(n=a.draw({animation:!1}))===null||n===void 0?void 0:n.finished,s.endBatch()}),this.bindEvents()}update(e){super.update(e),this.bindEvents()}bindEvents(){const{graph:e}=this.context,{trigger:t}=this.options;this.unbindEvents(),t==="click"?(e.on(Za.CLICK,this.handleCreateEdge),e.on(tl.CLICK,this.handleCreateEdge),e.on(js.CLICK,this.cancelEdge),e.on(Th.CLICK,this.cancelEdge)):(e.on(Za.DRAG_START,this.handleCreateEdge),e.on(tl.DRAG_START,this.handleCreateEdge),e.on(kt.POINTER_UP,this.drop)),e.on(kt.POINTER_MOVE,this.updateAssistEdge)}getSelectedNodeIDs(e){return Array.from(new Set(this.context.graph.getElementDataByState("node",this.options.state).map(t=>t.id).concat(e)))}validate(e){if(this.destroyed)return!1;const{enable:t}=this.options;return En(t)?t(e):!!t}unbindEvents(){const{graph:e}=this.context;e.off(Za.CLICK,this.handleCreateEdge),e.off(tl.CLICK,this.handleCreateEdge),e.off(js.CLICK,this.cancelEdge),e.off(Th.CLICK,this.cancelEdge),e.off(Za.DRAG_START,this.handleCreateEdge),e.off(tl.DRAG_START,this.handleCreateEdge),e.off(kt.POINTER_UP,this.drop),e.off(kt.POINTER_MOVE,this.updateAssistEdge)}destroy(){this.unbindEvents(),super.destroy()}}Mf.defaultOptions={animation:!0,enable:!0,style:{},trigger:"drag",onCreate:r=>r,onFinish:()=>{}};function JL(r,e,t){var n;return function(){var i=this,a=arguments,s=function(){n=null,t||r.apply(i,a)},o=t&&!n;clearTimeout(n),n=setTimeout(s,e),o&&r.apply(i,a)}}var ru=JL,U_=function(r,e,t,n){function i(a){return a instanceof t?a:new t(function(s){s(a)})}return new(t||(t=Promise))(function(a,s){function o(h){try{c(n.next(h))}catch(p){s(p)}}function l(h){try{c(n.throw(h))}catch(p){s(p)}}function c(h){h.done?a(h.value):i(h.value).then(o,l)}c((n=n.apply(r,e||[])).next())})};class Sf extends Oa{constructor(e,t){super(e,Object.assign({},Sf.defaultOptions,t)),this.isDragging=!1,this.onDragStart=n=>{this.validate(n)&&(this.isDragging=!0,this.context.canvas.setCursor("grabbing"))},this.onDrag=n=>{var i,a,s,o;if(!this.isDragging||oi.isPinching)return;const l=(a=(i=n.movement)===null||i===void 0?void 0:i.x)!==null&&a!==void 0?a:n.dx,c=(o=(s=n.movement)===null||s===void 0?void 0:s.y)!==null&&o!==void 0?o:n.dy;l|c&&this.translate([l,c],!1)},this.onDragEnd=()=>{var n,i;this.isDragging=!1,this.context.canvas.setCursor(this.defaultCursor),(i=(n=this.options).onFinish)===null||i===void 0||i.call(n)},this.invokeOnFinish=ru(()=>{var n,i;(i=(n=this.options).onFinish)===null||i===void 0||i.call(n)},300),this.shortcut=new Zl(e.graph),this.bindEvents(),this.defaultCursor=this.context.canvas.getConfig().cursor||"default"}update(e){this.unbindEvents(),super.update(e),this.bindEvents()}bindEvents(){const{trigger:e}=this.options;if(ii(e)){const{up:t=[],down:n=[],left:i=[],right:a=[]}=e;this.shortcut.bind(t,s=>this.onTranslate([0,1],s)),this.shortcut.bind(n,s=>this.onTranslate([0,-1],s)),this.shortcut.bind(i,s=>this.onTranslate([1,0],s)),this.shortcut.bind(a,s=>this.onTranslate([-1,0],s))}else{const{graph:t}=this.context;t.on(kt.DRAG_START,this.onDragStart),t.on(kt.DRAG,this.onDrag),t.on(kt.DRAG_END,this.onDragEnd)}}onTranslate(e,t){return U_(this,void 0,void 0,function*(){if(!this.validate(t))return;const{sensitivity:n}=this.options,i=n*-1;yield this.translate(Zs(e,i),this.options.animation),this.invokeOnFinish()})}translate(e,t){return U_(this,void 0,void 0,function*(){e=this.clampByDirection(e),e=this.clampByRange(e),yield this.context.graph.translateBy(e,t)})}clampByDirection([e,t]){const{direction:n}=this.options;return n==="x"?t=0:n==="y"&&(e=0),[e,t]}clampByRange([e,t]){const{viewport:n,canvas:i}=this.context,[a,s]=i.getSize(),[o,l,c,h]=os(this.options.range),p=[s*o,a*l,s*c,a*h],C=go(lg(n.getCanvasCenter()),p),k=Or(n.getViewportCenter(),[e,t,0]);if(!ls(k,C)){const{min:[W,j],max:[K,Q]}=C;(k[0]<W&&e>0||k[0]>K&&e<0)&&(e=0),(k[1]<j&&t>0||k[1]>Q&&t<0)&&(t=0)}return[e,t]}validate(e){if(this.destroyed)return!1;const{enable:t}=this.options;return typeof t=="function"?t(e):!!t}unbindEvents(){this.shortcut.unbindAll();const{graph:e}=this.context;e.off(kt.DRAG_START,this.onDragStart),e.off(kt.DRAG,this.onDrag),e.off(kt.DRAG_END,this.onDragEnd)}destroy(){this.shortcut.destroy(),this.unbindEvents(),this.context.canvas.setCursor(this.defaultCursor),super.destroy()}}Sf.defaultOptions={enable:r=>"targetType"in r?r.targetType==="canvas":!0,sensitivity:10,direction:"both",range:1/0};var W_=function(r,e,t,n){function i(a){return a instanceof t?a:new t(function(s){s(a)})}return new(t||(t=Promise))(function(a,s){function o(h){try{c(n.next(h))}catch(p){s(p)}}function l(h){try{c(n.throw(h))}catch(p){s(p)}}function c(h){h.done?a(h.value):i(h.value).then(o,l)}c((n=n.apply(r,e||[])).next())})};class iu extends Oa{constructor(e,t){super(e,Object.assign({},iu.defaultOptions,t)),this.enable=!1,this.enableElements=["node","combo"],this.target=[],this.shadowOrigin=[0,0],this.hiddenEdges=[],this.isDragging=!1,this.onDrop=n=>W_(this,void 0,void 0,function*(){var i;if(this.options.dropEffect!=="link")return;const{model:a,element:s}=this.context,o=n.target.id;this.target.forEach(l=>{const c=a.getParentData(l,Lr);c&&wt(c)===o&&a.refreshComboData(o),a.setParent(l,o,Lr)}),yield(i=s==null?void 0:s.draw({animation:!0}))===null||i===void 0?void 0:i.finished}),this.setCursor=n=>{if(this.isDragging)return;const{type:i}=n,{canvas:a}=this.context,{cursor:s}=this.options;i===kt.POINTER_ENTER?a.setCursor((s==null?void 0:s.grab)||"grab"):a.setCursor((s==null?void 0:s.default)||"default")},this.onDragStart=this.onDragStart.bind(this),this.onDrag=this.onDrag.bind(this),this.onDragEnd=this.onDragEnd.bind(this),this.onDrop=this.onDrop.bind(this),this.bindEvents()}update(e){this.unbindEvents(),super.update(e),this.bindEvents()}bindEvents(){const{graph:e,canvas:t}=this.context,n=t.getLayer().getContextService().$canvas;n&&(n.addEventListener("blur",this.onDragEnd),n.addEventListener("contextmenu",this.onDragEnd)),this.enableElements.forEach(i=>{e.on(`${i}:${kt.DRAG_START}`,this.onDragStart),e.on(`${i}:${kt.DRAG}`,this.onDrag),e.on(`${i}:${kt.DRAG_END}`,this.onDragEnd),e.on(`${i}:${kt.POINTER_ENTER}`,this.setCursor),e.on(`${i}:${kt.POINTER_LEAVE}`,this.setCursor)}),["link"].includes(this.options.dropEffect)&&(e.on(tl.DROP,this.onDrop),e.on(js.DROP,this.onDrop))}getSelectedNodeIDs(e){return Array.from(new Set(this.context.graph.getElementDataByState("node",this.options.state).map(t=>t.id).concat(e)))}getDelta(e){const t=this.context.graph.getZoom();return us([e.dx,e.dy],t)}onDragStart(e){var t;if(this.enable=this.validate(e),!this.enable)return;const{batch:n,canvas:i,graph:a}=this.context;i.setCursor(((t=this.options.cursor)===null||t===void 0?void 0:t.grabbing)||"grabbing"),this.isDragging=!0,n.startBatch();const s=e.target.id;a.getElementState(s).includes(this.options.state)?this.target=this.getSelectedNodeIDs([s]):this.target=[s],this.hideEdge(),this.context.graph.frontElement(this.target),this.options.shadow&&this.createShadow(this.target)}onDrag(e){if(!this.enable)return;const t=this.getDelta(e);this.options.shadow?this.moveShadow(t):this.moveElement(this.target,t)}onDragEnd(){var e,t,n;if(this.enable=!1,this.options.shadow){if(!this.shadow)return;this.shadow.style.visibility="hidden";const{x:s=0,y:o=0}=this.shadow.attributes,[l,c]=Or([+s,+o],this.shadowOrigin);this.moveElement(this.target,[l,c])}this.showEdges(),(t=(e=this.options).onFinish)===null||t===void 0||t.call(e,this.target);const{batch:i,canvas:a}=this.context;i.endBatch(),a.setCursor(((n=this.options.cursor)===null||n===void 0?void 0:n.grab)||"grab"),this.isDragging=!1,this.target=[]}validate(e){if(this.destroyed)return!1;const{enable:t}=this.options;return En(t)?t(e):!!t}moveElement(e,t){return W_(this,void 0,void 0,function*(){const{graph:n,model:i}=this.context,{dropEffect:a}=this.options;a==="move"&&e.forEach(s=>i.refreshComboData(s)),n.translateElementBy(Object.fromEntries(e.map(s=>[s,t])),!1)})}moveShadow(e){if(!this.shadow)return;const{x:t=0,y:n=0}=this.shadow.attributes,[i,a]=e;this.shadow.attr({x:+t+i,y:+n+a})}createShadow(e){const t=gi(this.options,"shadow"),n=Hc(e.map(c=>this.context.element.getElement(c).getBounds())),[i,a]=n.min;this.shadowOrigin=[i,a];const[s,o]=fo(n),l={width:s,height:o,x:i,y:a};this.shadow?this.shadow.attr(Object.assign(Object.assign(Object.assign({},t),l),{visibility:"visible"})):(this.shadow=new Ii({style:Object.assign(Object.assign(Object.assign({$layer:"transient"},t),l),{pointerEvents:"none"})}),this.context.canvas.appendChild(this.shadow))}showEdges(){this.options.shadow||this.hiddenEdges.length===0||(this.context.graph.showElement(this.hiddenEdges),this.hiddenEdges=[])}hideEdge(){const{hideEdge:e,shadow:t}=this.options;if(e==="none"||t)return;const{graph:n}=this.context;e==="all"?this.hiddenEdges=n.getEdgeData().map(wt):this.hiddenEdges=Array.from(new Set(this.target.map(i=>n.getRelatedEdgesData(i,e).map(wt)).flat())),n.hideElement(this.hiddenEdges)}unbindEvents(){const{graph:e,canvas:t}=this.context,n=t.getLayer().getContextService().$canvas;n&&(n.removeEventListener("blur",this.onDragEnd),n.removeEventListener("contextmenu",this.onDragEnd)),this.enableElements.forEach(i=>{e.off(`${i}:${kt.DRAG_START}`,this.onDragStart),e.off(`${i}:${kt.DRAG}`,this.onDrag),e.off(`${i}:${kt.DRAG_END}`,this.onDragEnd),e.off(`${i}:${kt.POINTER_ENTER}`,this.setCursor),e.off(`${i}:${kt.POINTER_LEAVE}`,this.setCursor)}),e.off(`combo:${kt.DROP}`,this.onDrop),e.off(`canvas:${kt.DROP}`,this.onDrop)}destroy(){var e;this.unbindEvents(),(e=this.shadow)===null||e===void 0||e.destroy(),super.destroy()}}iu.defaultOptions={animation:!0,enable:r=>["node","combo"].includes(r.targetType),dropEffect:"move",state:"selected",hideEdge:"none",shadow:!1,shadowZIndex:100,shadowFill:"#F3F9FF",shadowFillOpacity:.5,shadowStroke:"#1890FF",shadowStrokeOpacity:.9,shadowLineDash:[5,5],cursor:{default:"default",grab:"grab",grabbing:"grabbing"}};var qL="*",$L=function(){function r(){this._events={}}return r.prototype.on=function(e,t,n){return this._events[e]||(this._events[e]=[]),this._events[e].push({callback:t,once:!!n}),this},r.prototype.once=function(e,t){return this.on(e,t,!0)},r.prototype.emit=function(e){for(var t=this,n=[],i=1;i<arguments.length;i++)n[i-1]=arguments[i];var a=this._events[e]||[],s=this._events[qL]||[],o=function(l){for(var c=l.length,h=0;h<c;h++)if(l[h]){var p=l[h],C=p.callback,k=p.once;k&&(l.splice(h,1),l.length===0&&delete t._events[e],c--,h--),C.apply(t,n)}};o(a),o(s)},r.prototype.off=function(e,t){if(!e)this._events={};else if(!t)delete this._events[e];else{for(var n=this._events[e]||[],i=n.length,a=0;a<i;a++)n[a].callback===t&&(n.splice(a,1),i--,a--);n.length===0&&delete this._events[e]}return this},r.prototype.getEvents=function(){return this._events},r}(),Tf=$L;function Qg(r,e,t,n){for(;r.length;){const i=r.shift();if(t(i))return!0;e.add(i.id),n(i.id).forEach(s=>{e.has(s.id)||(e.add(s.id),r.push(s))})}return!1}function Af(r,e,t,n){if(t(r))return!0;e.add(r.id);for(const a of n(r.id))if(!e.has(a.id)&&Af(a,e,t,n))return!0;return!1}const H_=()=>!0;class eR{constructor(e){Xr(this,"graph");Xr(this,"nodeFilter");Xr(this,"edgeFilter");Xr(this,"cacheEnabled");Xr(this,"inEdgesMap",new Map);Xr(this,"outEdgesMap",new Map);Xr(this,"bothEdgesMap",new Map);Xr(this,"allNodesMap",new Map);Xr(this,"allEdgesMap",new Map);Xr(this,"clearCache",()=>{this.inEdgesMap.clear(),this.outEdgesMap.clear(),this.bothEdgesMap.clear(),this.allNodesMap.clear(),this.allEdgesMap.clear()});Xr(this,"refreshCache",()=>{this.clearCache(),this.updateCache(this.graph.getAllNodes().map(e=>e.id))});Xr(this,"updateCache",e=>{const t=new Set;e.forEach(n=>{const i=this.bothEdgesMap.get(n);if(i&&i.forEach(a=>t.add(a.id)),!this.hasNode(n))this.inEdgesMap.delete(n),this.outEdgesMap.delete(n),this.bothEdgesMap.delete(n),this.allNodesMap.delete(n);else{const a=this.graph.getRelatedEdges(n,"in").filter(this.edgeFilter),s=this.graph.getRelatedEdges(n,"out").filter(this.edgeFilter),o=Array.from(new Set([...a,...s]));o.forEach(l=>t.add(l.id)),this.inEdgesMap.set(n,a),this.outEdgesMap.set(n,s),this.bothEdgesMap.set(n,o),this.allNodesMap.set(n,this.graph.getNode(n))}}),t.forEach(n=>{this.hasEdge(n)?this.allEdgesMap.set(n,this.graph.getEdge(n)):this.allEdgesMap.delete(n)})});Xr(this,"handleGraphChanged",e=>{const t=new Set;e.changes.forEach(n=>{switch(n.type){case"NodeAdded":t.add(n.value.id);break;case"NodeDataUpdated":t.add(n.id);break;case"EdgeAdded":t.add(n.value.source),t.add(n.value.target);break;case"EdgeUpdated":(n.propertyName==="source"||n.propertyName==="target")&&(t.add(n.oldValue),t.add(n.newValue));break;case"EdgeDataUpdated":if(e.graph.hasEdge(n.id)){const i=e.graph.getEdge(n.id);t.add(i.source),t.add(i.target)}break;case"EdgeRemoved":t.add(n.value.source),t.add(n.value.target);break;case"NodeRemoved":t.add(n.value.id);break;default:break}}),this.updateCache(t)});this.graph=e.graph;const t=e.nodeFilter||H_,n=e.edgeFilter||H_;this.nodeFilter=t,this.edgeFilter=i=>{const{source:a,target:s}=this.graph.getEdgeDetail(i.id);return!t(a)||!t(s)?!1:n(i,a,s)},e.cache==="auto"?(this.cacheEnabled=!0,this.startAutoCache()):e.cache==="manual"?this.cacheEnabled=!0:this.cacheEnabled=!1}startAutoCache(){this.refreshCache(),this.graph.on("changed",this.handleGraphChanged)}stopAutoCache(){this.graph.off("changed",this.handleGraphChanged)}checkNodeExistence(e){this.getNode(e)}hasNode(e){if(!this.graph.hasNode(e))return!1;const t=this.graph.getNode(e);return this.nodeFilter(t)}areNeighbors(e,t){return this.checkNodeExistence(e),this.getNeighbors(t).some(n=>n.id===e)}getNode(e){const t=this.graph.getNode(e);if(!this.nodeFilter(t))throw new Error("Node not found for id: "+e);return t}getRelatedEdges(e,t){return this.checkNodeExistence(e),this.cacheEnabled?t==="in"?this.inEdgesMap.get(e):t==="out"?this.outEdgesMap.get(e):this.bothEdgesMap.get(e):this.graph.getRelatedEdges(e,t).filter(this.edgeFilter)}getDegree(e,t){return this.getRelatedEdges(e,t).length}getSuccessors(e){const n=this.getRelatedEdges(e,"out").map(i=>this.getNode(i.target));return Array.from(new Set(n))}getPredecessors(e){const n=this.getRelatedEdges(e,"in").map(i=>this.getNode(i.source));return Array.from(new Set(n))}getNeighbors(e){const t=this.getPredecessors(e),n=this.getSuccessors(e);return Array.from(new Set([...t,...n]))}hasEdge(e){if(!this.graph.hasEdge(e))return!1;const t=this.graph.getEdge(e);return this.edgeFilter(t)}getEdge(e){const t=this.graph.getEdge(e);if(!this.edgeFilter(t))throw new Error("Edge not found for id: "+e);return t}getEdgeDetail(e){const t=this.getEdge(e);return{edge:t,source:this.getNode(t.source),target:this.getNode(t.target)}}hasTreeStructure(e){return this.graph.hasTreeStructure(e)}getRoots(e){return this.graph.getRoots(e).filter(this.nodeFilter)}getChildren(e,t){return this.checkNodeExistence(e),this.graph.getChildren(e,t).filter(this.nodeFilter)}getParent(e,t){this.checkNodeExistence(e);const n=this.graph.getParent(e,t);return!n||!this.nodeFilter(n)?null:n}getAllNodes(){return this.cacheEnabled?Array.from(this.allNodesMap.values()):this.graph.getAllNodes().filter(this.nodeFilter)}getAllEdges(){return this.cacheEnabled?Array.from(this.allEdgesMap.values()):this.graph.getAllEdges().filter(this.edgeFilter)}bfs(e,t,n="out"){const i={in:this.getPredecessors.bind(this),out:this.getSuccessors.bind(this),both:this.getNeighbors.bind(this)}[n];Qg([this.getNode(e)],new Set,t,i)}dfs(e,t,n="out"){const i={in:this.getPredecessors.bind(this),out:this.getSuccessors.bind(this),both:this.getNeighbors.bind(this)}[n];Af(this.getNode(e),new Set,t,i)}}class ci extends Tf{constructor(t){super();Xr(this,"nodeMap",new Map);Xr(this,"edgeMap",new Map);Xr(this,"inEdgesMap",new Map);Xr(this,"outEdgesMap",new Map);Xr(this,"bothEdgesMap",new Map);Xr(this,"treeIndices",new Map);Xr(this,"changes",[]);Xr(this,"batchCount",0);Xr(this,"onChanged",()=>{});Xr(this,"batch",t=>{this.batchCount+=1,t(),this.batchCount-=1,this.batchCount||this.commit()});t&&(t.nodes&&this.addNodes(t.nodes),t.edges&&this.addEdges(t.edges),t.tree&&this.addTree(t.tree),t.onChanged&&(this.onChanged=t.onChanged))}commit(){const t=this.changes;this.changes=[];const n={graph:this,changes:t};this.emit("changed",n),this.onChanged(n)}reduceChanges(t){let n=[];return t.forEach(i=>{switch(i.type){case"NodeRemoved":{let a=!1;n=n.filter(s=>{if(s.type==="NodeAdded"){const o=s.value.id===i.value.id;return o&&(a=!0),!o}else{if(s.type==="NodeDataUpdated")return s.id!==i.value.id;if(s.type==="TreeStructureChanged")return s.nodeId!==i.value.id}return!0}),a||n.push(i);break}case"EdgeRemoved":{let a=!1;n=n.filter(s=>{if(s.type==="EdgeAdded"){const o=s.value.id===i.value.id;return o&&(a=!0),!o}else if(s.type==="EdgeDataUpdated"||s.type==="EdgeUpdated")return s.id!==i.value.id;return!0}),a||n.push(i);break}case"NodeDataUpdated":case"EdgeDataUpdated":case"EdgeUpdated":{const a=n.findIndex(o=>o.type===i.type&&o.id===i.id&&(i.propertyName===void 0||o.propertyName===i.propertyName)),s=n[a];s?i.propertyName!==void 0?s.newValue=i.newValue:(n.splice(a,1),n.push(i)):n.push(i);break}case"TreeStructureDetached":{n=n.filter(a=>a.type==="TreeStructureAttached"||a.type==="TreeStructureChanged"?a.treeKey!==i.treeKey:!0),n.push(i);break}case"TreeStructureChanged":{const a=n.find(s=>s.type==="TreeStructureChanged"&&s.treeKey===i.treeKey&&s.nodeId===i.nodeId);a?a.newParentId=i.newParentId:n.push(i);break}default:n.push(i);break}}),n}checkNodeExistence(t){this.getNode(t)}hasNode(t){return this.nodeMap.has(t)}areNeighbors(t,n){return this.getNeighbors(n).some(i=>i.id===t)}getNode(t){const n=this.nodeMap.get(t);if(!n)throw new Error("Node not found for id: "+t);return n}getRelatedEdges(t,n){if(this.checkNodeExistence(t),n==="in"){const i=this.inEdgesMap.get(t);return Array.from(i)}else if(n==="out"){const i=this.outEdgesMap.get(t);return Array.from(i)}else{const i=this.bothEdgesMap.get(t);return Array.from(i)}}getDegree(t,n){return this.getRelatedEdges(t,n).length}getSuccessors(t){const i=this.getRelatedEdges(t,"out").map(a=>this.getNode(a.target));return Array.from(new Set(i))}getPredecessors(t){const i=this.getRelatedEdges(t,"in").map(a=>this.getNode(a.source));return Array.from(new Set(i))}getNeighbors(t){const n=this.getPredecessors(t),i=this.getSuccessors(t);return Array.from(new Set([...n,...i]))}doAddNode(t){if(this.hasNode(t.id))throw new Error("Node already exists: "+t.id);this.nodeMap.set(t.id,t),this.inEdgesMap.set(t.id,new Set),this.outEdgesMap.set(t.id,new Set),this.bothEdgesMap.set(t.id,new Set),this.treeIndices.forEach(n=>{n.childrenMap.set(t.id,new Set)}),this.changes.push({type:"NodeAdded",value:t})}addNodes(t){this.batch(()=>{for(const n of t)this.doAddNode(n)})}addNode(t){this.addNodes([t])}doRemoveNode(t){const n=this.getNode(t),i=this.bothEdgesMap.get(t);i==null||i.forEach(a=>this.doRemoveEdge(a.id)),this.nodeMap.delete(t),this.treeIndices.forEach(a=>{var o,l;(o=a.childrenMap.get(t))==null||o.forEach(c=>{a.parentMap.delete(c.id)});const s=a.parentMap.get(t);s&&((l=a.childrenMap.get(s.id))==null||l.delete(n)),a.parentMap.delete(t),a.childrenMap.delete(t)}),this.bothEdgesMap.delete(t),this.inEdgesMap.delete(t),this.outEdgesMap.delete(t),this.changes.push({type:"NodeRemoved",value:n})}removeNodes(t){this.batch(()=>{t.forEach(n=>this.doRemoveNode(n))})}removeNode(t){this.removeNodes([t])}updateNodeDataProperty(t,n,i){const a=this.getNode(t);this.batch(()=>{const s=a.data[n],o=i;a.data[n]=o,this.changes.push({type:"NodeDataUpdated",id:t,propertyName:n,oldValue:s,newValue:o})})}mergeNodeData(t,n){this.batch(()=>{Object.entries(n).forEach(([i,a])=>{this.updateNodeDataProperty(t,i,a)})})}updateNodeData(...t){const n=t[0],i=this.getNode(n);if(typeof t[1]=="string"){this.updateNodeDataProperty(n,t[1],t[2]);return}let a;if(typeof t[1]=="function"){const s=t[1];a=s(i.data)}else typeof t[1]=="object"&&(a=t[1]);this.batch(()=>{const s=i.data,o=a;i.data=a,this.changes.push({type:"NodeDataUpdated",id:n,oldValue:s,newValue:o})})}checkEdgeExistence(t){if(!this.hasEdge(t))throw new Error("Edge not found for id: "+t)}hasEdge(t){return this.edgeMap.has(t)}getEdge(t){return this.checkEdgeExistence(t),this.edgeMap.get(t)}getEdgeDetail(t){const n=this.getEdge(t);return{edge:n,source:this.getNode(n.source),target:this.getNode(n.target)}}doAddEdge(t){if(this.hasEdge(t.id))throw new Error("Edge already exists: "+t.id);this.checkNodeExistence(t.source),this.checkNodeExistence(t.target),this.edgeMap.set(t.id,t);const n=this.inEdgesMap.get(t.target),i=this.outEdgesMap.get(t.source),a=this.bothEdgesMap.get(t.source),s=this.bothEdgesMap.get(t.target);n.add(t),i.add(t),a.add(t),s.add(t),this.changes.push({type:"EdgeAdded",value:t})}addEdges(t){this.batch(()=>{for(const n of t)this.doAddEdge(n)})}addEdge(t){this.addEdges([t])}doRemoveEdge(t){const n=this.getEdge(t),i=this.outEdgesMap.get(n.source),a=this.inEdgesMap.get(n.target),s=this.bothEdgesMap.get(n.source),o=this.bothEdgesMap.get(n.target);i.delete(n),a.delete(n),s.delete(n),o.delete(n),this.edgeMap.delete(t),this.changes.push({type:"EdgeRemoved",value:n})}removeEdges(t){this.batch(()=>{t.forEach(n=>this.doRemoveEdge(n))})}removeEdge(t){this.removeEdges([t])}updateEdgeSource(t,n){const i=this.getEdge(t);this.checkNodeExistence(n);const a=i.source,s=n;this.outEdgesMap.get(a).delete(i),this.bothEdgesMap.get(a).delete(i),this.outEdgesMap.get(s).add(i),this.bothEdgesMap.get(s).add(i),i.source=n,this.batch(()=>{this.changes.push({type:"EdgeUpdated",id:t,propertyName:"source",oldValue:a,newValue:s})})}updateEdgeTarget(t,n){const i=this.getEdge(t);this.checkNodeExistence(n);const a=i.target,s=n;this.inEdgesMap.get(a).delete(i),this.bothEdgesMap.get(a).delete(i),this.inEdgesMap.get(s).add(i),this.bothEdgesMap.get(s).add(i),i.target=n,this.batch(()=>{this.changes.push({type:"EdgeUpdated",id:t,propertyName:"target",oldValue:a,newValue:s})})}updateEdgeDataProperty(t,n,i){const a=this.getEdge(t);this.batch(()=>{const s=a.data[n],o=i;a.data[n]=o,this.changes.push({type:"EdgeDataUpdated",id:t,propertyName:n,oldValue:s,newValue:o})})}updateEdgeData(...t){const n=t[0],i=this.getEdge(n);if(typeof t[1]=="string"){this.updateEdgeDataProperty(n,t[1],t[2]);return}let a;if(typeof t[1]=="function"){const s=t[1];a=s(i.data)}else typeof t[1]=="object"&&(a=t[1]);this.batch(()=>{const s=i.data,o=a;i.data=a,this.changes.push({type:"EdgeDataUpdated",id:n,oldValue:s,newValue:o})})}mergeEdgeData(t,n){this.batch(()=>{Object.entries(n).forEach(([i,a])=>{this.updateEdgeDataProperty(t,i,a)})})}checkTreeExistence(t){if(!this.hasTreeStructure(t))throw new Error("Tree structure not found for treeKey: "+t)}hasTreeStructure(t){return this.treeIndices.has(t)}attachTreeStructure(t){this.treeIndices.has(t)||(this.treeIndices.set(t,{parentMap:new Map,childrenMap:new Map}),this.batch(()=>{this.changes.push({type:"TreeStructureAttached",treeKey:t})}))}detachTreeStructure(t){this.checkTreeExistence(t),this.treeIndices.delete(t),this.batch(()=>{this.changes.push({type:"TreeStructureDetached",treeKey:t})})}addTree(t,n){this.batch(()=>{this.attachTreeStructure(n);const i=[],a=Array.isArray(t)?t:[t];for(;a.length;){const s=a.shift();i.push(s),s.children&&a.push(...s.children)}this.addNodes(i),i.forEach(s=>{var o;(o=s.children)==null||o.forEach(l=>{this.setParent(l.id,s.id,n)})})})}getRoots(t){return this.checkTreeExistence(t),this.getAllNodes().filter(n=>!this.getParent(n.id,t))}getChildren(t,n){this.checkNodeExistence(t),this.checkTreeExistence(n);const a=this.treeIndices.get(n).childrenMap.get(t);return Array.from(a||[])}getParent(t,n){return this.checkNodeExistence(t),this.checkTreeExistence(n),this.treeIndices.get(n).parentMap.get(t)||null}getAncestors(t,n){const i=[];let a=this.getNode(t),s;for(;s=this.getParent(a.id,n);)i.push(s),a=s;return i}setParent(t,n,i){var h,p;this.checkTreeExistence(i);const a=this.treeIndices.get(i);if(!a)return;const s=this.getNode(t),o=a.parentMap.get(t);if((o==null?void 0:o.id)===n)return;if(n==null){o&&((h=a.childrenMap.get(o.id))==null||h.delete(s)),a.parentMap.delete(t);return}const l=this.getNode(n);a.parentMap.set(t,l),o&&((p=a.childrenMap.get(o.id))==null||p.delete(s));let c=a.childrenMap.get(l.id);c||(c=new Set,a.childrenMap.set(l.id,c)),c.add(s),this.batch(()=>{this.changes.push({type:"TreeStructureChanged",treeKey:i,nodeId:t,oldParentId:o==null?void 0:o.id,newParentId:l.id})})}dfsTree(t,n,i){const a=s=>this.getChildren(s,i);return Af(this.getNode(t),new Set,n,a)}bfsTree(t,n,i){const a=s=>this.getChildren(s,i);return Qg([this.getNode(t)],new Set,n,a)}getAllNodes(){return Array.from(this.nodeMap.values())}getAllEdges(){return Array.from(this.edgeMap.values())}bfs(t,n,i="out"){const a={in:this.getPredecessors.bind(this),out:this.getSuccessors.bind(this),both:this.getNeighbors.bind(this)}[i];return Qg([this.getNode(t)],new Set,n,a)}dfs(t,n,i="out"){const a={in:this.getPredecessors.bind(this),out:this.getSuccessors.bind(this),both:this.getNeighbors.bind(this)}[i];return Af(this.getNode(t),new Set,n,a)}clone(){const t=this.getAllNodes().map(a=>b0(vc({},a),{data:vc({},a.data)})),n=this.getAllEdges().map(a=>b0(vc({},a),{data:vc({},a.data)})),i=new ci({nodes:t,edges:n});return this.treeIndices.forEach(({parentMap:a,childrenMap:s},o)=>{const l=new Map;a.forEach((h,p)=>{l.set(p,i.getNode(h.id))});const c=new Map;s.forEach((h,p)=>{c.set(p,new Set(Array.from(h).map(C=>i.getNode(C.id))))}),i.treeIndices.set(o,{parentMap:l,childrenMap:c})}),i}toJSON(){return JSON.stringify({nodes:this.getAllNodes(),edges:this.getAllEdges()})}createView(t){return new eR(vc({graph:this},t))}}class Cf{constructor(e,t){this.context=e,this.options=t||{}}}var tR=function(r,e,t,n){function i(a){return a instanceof t?a:new t(function(s){s(a)})}return new(t||(t=Promise))(function(a,s){function o(h){try{c(n.next(h))}catch(p){s(p)}}function l(h){try{c(n.throw(h))}catch(p){s(p)}}function c(h){h.done?a(h.value):i(h.value).then(o,l)}c((n=n.apply(r,e||[])).next())})},nR=function(r,e){var t={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&e.indexOf(n)<0&&(t[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var i=0,n=Object.getOwnPropertySymbols(r);i<n.length;i++)e.indexOf(n[i])<0&&Object.prototype.propertyIsEnumerable.call(r,n[i])&&(t[n[i]]=r[n[i]]);return t};function oU(r){const{type:e}=r;return!!(["comboCombined","comboForce"].includes(e)||e==="antv-dagre"&&r.sortByCombo)}function rR(r){const{type:e}=r;return["compact-box","mindmap","dendrogram","indented"].includes(e)}function lU(r){return isNumber(r.x)&&isNumber(r.y)}function iR(r){return!Array.isArray(r)&&(r==null?void 0:r.preLayout)}function Of(r){const{nodes:e,edges:t}=r,n={nodes:[],edges:[],combos:[]};return e.forEach(i=>{const a=i.data._isCombo?n.combos:n.nodes,{x:s,y:o,z:l=0}=i.data;a==null||a.push({id:i.id,style:{x:s,y:o,z:l}})}),t.forEach(i=>{const{id:a,source:s,target:o,data:{points:l=[],controlPoints:c=l.slice(1,l.length-1)}}=i;n.edges.push({id:a,source:s,target:o,style:Object.assign({},c!=null&&c.length?{controlPoints:c.map(Ni)}:{})})}),n}function aR(r,e){class t extends Cf{constructor(i,a){if(super(i,a),this.instance=new r({}),this.id=this.instance.id,"stop"in this.instance&&"tick"in this.instance){const s=this.instance;this.stop=s.stop.bind(s),this.tick=o=>{const l=s.tick(o);return Of(l)}}}execute(i,a){return tR(this,void 0,void 0,function*(){return Of(yield this.instance.execute(this.graphData2LayoutModel(i),this.transformOptions(ia({},this.options,a))))})}transformOptions(i){const{onTick:a}=i;return a&&(i.onTick=s=>a(Of(s))),i}graphData2LayoutModel(i){const{nodes:a=[],edges:s=[],combos:o=[]}=i,l=a.map(k=>{const W=wt(k),{data:j,style:K,combo:Q}=k,ee=nR(k,["data","style","combo"]),re={id:W,data:Object.assign(Object.assign(Object.assign(Object.assign(Object.assign({},j),{data:j}),Q?{parentId:Q}:{}),{style:K}),ee)};return K!=null&&K.x&&Object.assign(re.data,{x:K.x}),K!=null&&K.y&&Object.assign(re.data,{y:K.y}),K!=null&&K.z&&Object.assign(re.data,{z:K.z}),re}),c=new Map(l.map(k=>[k.id,k])),h=s.filter(k=>{const{source:W,target:j}=k;return c.has(W)&&c.has(j)}).map(k=>{const{source:W,target:j,data:K,style:Q}=k;return{id:wt(k),source:W,target:j,data:Object.assign({},K),style:Object.assign({},Q)}}),p=o.map(k=>({id:wt(k),data:Object.assign({_isCombo:!0},k.data),style:Object.assign({},k.style)})),C=new ci({nodes:[...l,...p],edges:h});return e.model.model.hasTreeStructure(Lr)&&(C.attachTreeStructure(Lr),l.forEach(k=>{const W=e.model.model.getParent(k.id,Lr);W&&C.hasNode(W.id)&&C.setParent(k.id,W.id,Lr)})),C}}return t}function Jg(r,e,...t){if(e in r)return r[e](...t);if("instance"in r){const n=r.instance;if(e in n)return n[e](...t)}return null}function j_(r,e){if(e in r)return r[e];if("instance"in r){const t=r.instance;if(e in t)return t[e]}return null}var sR=function(r,e,t,n){function i(a){return a instanceof t?a:new t(function(s){s(a)})}return new(t||(t=Promise))(function(a,s){function o(h){try{c(n.next(h))}catch(p){s(p)}}function l(h){try{c(n.throw(h))}catch(p){s(p)}}function c(h){h.done?a(h.value):i(h.value).then(o,l)}c((n=n.apply(r,e||[])).next())})};class oR extends iu{get forceLayoutInstance(){return this.context.layout.getLayoutInstance().find(e=>["d3-force","d3-force-3d"].includes(e==null?void 0:e.id))}validate(e){return this.context.layout?this.forceLayoutInstance?super.validate(e):(Ea.warn("DragElementForce only works with d3-force or d3-force-3d layout"),!1):!1}moveElement(e,t){return sR(this,void 0,void 0,function*(){const n=this.forceLayoutInstance;this.context.graph.getNodeData(e).forEach((i,a)=>{const{x:s=0,y:o=0}=i.style||{};n&&Jg(n,"setFixedPosition",e[a],[...Jn([+s,+o],t)])})})}onDragStart(e){if(this.enable=this.validate(e),!this.enable)return;this.target=this.getSelectedNodeIDs([e.target.id]),this.hideEdge(),this.context.graph.frontElement(this.target);const t=this.forceLayoutInstance;t&&j_(t,"simulation").alphaTarget(.3).restart(),this.context.graph.getNodeData(this.target).forEach(n=>{const{x:i=0,y:a=0}=n.style||{};t&&Jg(t,"setFixedPosition",wt(n),[+i,+a])})}onDrag(e){if(!this.enable)return;const t=this.getDelta(e);this.moveElement(this.target,t)}onDragEnd(){const e=this.forceLayoutInstance;e&&j_(e,"simulation").alphaTarget(0),!this.options.fixed&&this.context.graph.getNodeData(this.target).forEach(t=>{e&&Jg(e,"setFixedPosition",wt(t),[null,null,null])})}}var G_=function(r,e,t,n){function i(a){return a instanceof t?a:new t(function(s){s(a)})}return new(t||(t=Promise))(function(a,s){function o(h){try{c(n.next(h))}catch(p){s(p)}}function l(h){try{c(n.throw(h))}catch(p){s(p)}}function c(h){h.done?a(h.value):i(h.value).then(o,l)}c((n=n.apply(r,e||[])).next())})};class Pf extends Oa{constructor(e,t){super(e,Object.assign({},Pf.defaultOptions,t)),this.isZoomEvent=n=>!!(n.data&&"scale"in n.data),this.relatedEdgeToUpdate=new Set,this.zoom=this.context.graph.getZoom(),this.fixElementSize=n=>G_(this,void 0,void 0,function*(){if(!this.validate(n))return;const{graph:i}=this.context,{state:a,nodeFilter:s,edgeFilter:o,comboFilter:l}=this.options,c=(a?i.getElementDataByState("node",a):i.getNodeData()).filter(s),h=(a?i.getElementDataByState("edge",a):i.getEdgeData()).filter(o),p=(a?i.getElementDataByState("combo",a):i.getComboData()).filter(l),C=this.isZoomEvent(n)?this.zoom=Math.max(.01,Math.min(n.data.scale,10)):this.zoom,k=[...c,...p];k.length>0&&k.forEach(W=>this.fixNodeLike(W,C)),this.updateRelatedEdges(),h.length>0&&h.forEach(W=>this.fixEdge(W,C))}),this.cachedStyles=new Map,this.getOriginalFieldValue=(n,i,a)=>{var s;const o=this.cachedStyles.get(n)||[],l=((s=o.find(c=>c.shape===i))===null||s===void 0?void 0:s.style)||{};return a in l||(l[a]=i.attributes[a],this.cachedStyles.set(n,[...o.filter(c=>c.shape!==i),{shape:i,style:l}])),l[a]},this.scaleEntireElement=(n,i,a)=>{i.setLocalScale(1/a);const s=this.cachedStyles.get(n)||[];s.push({shape:i}),this.cachedStyles.set(n,s)},this.scaleSpecificShapes=(n,i,a)=>{const s=QP(n);(Array.isArray(a)?a:[a]).forEach(l=>{const{shape:c,fields:h}=l,p=typeof c=="function"?c(s):n.getShape(c);if(p){if(!h){this.scaleEntireElement(n.id,p,i);return}h.forEach(C=>{const k=this.getOriginalFieldValue(n.id,p,C);un(k)&&(p.style[C]=k/i)})}})},this.skipIfExceedViewport=n=>{const{viewport:i}=this.context;return!(i!=null&&i.isInViewport(n.getRenderBounds(),!1,30))},this.fixNodeLike=(n,i)=>{const a=wt(n),{element:s,model:o}=this.context,l=s.getElement(a);if(!l||this.skipIfExceedViewport(l))return;o.getRelatedEdgesData(a).forEach(p=>this.relatedEdgeToUpdate.add(wt(p)));const h=this.options[l.type];if(!h){this.scaleEntireElement(a,l,i);return}this.scaleSpecificShapes(l,i,h)},this.fixEdge=(n,i)=>{const a=wt(n),s=this.context.element.getElement(a);if(!s||this.skipIfExceedViewport(s))return;const o=this.options.edge;if(!o){s.style.transformOrigin="center",this.scaleEntireElement(a,s,i);return}this.scaleSpecificShapes(s,i,o)},this.updateRelatedEdges=()=>{const{element:n}=this.context;this.relatedEdgeToUpdate.size>0&&this.relatedEdgeToUpdate.forEach(i=>{const a=n.getElement(i);a==null||a.update({})}),this.relatedEdgeToUpdate.clear()},this.resetTransform=n=>G_(this,void 0,void 0,function*(){var i;!((i=n.data)===null||i===void 0)&&i.firstRender||(this.options.reset?this.restoreCachedStyles():this.fixElementSize({data:{scale:this.zoom}}))}),this.bindEvents()}restoreCachedStyles(){if(this.cachedStyles.size>0){this.cachedStyles.forEach(i=>{i.forEach(({shape:a,style:s})=>{if(Ls(s))a.setLocalScale(1);else{if(this.options.state)return;Object.entries(s).forEach(([o,l])=>a.style[o]=l)}})});const{graph:e,element:t}=this.context,n=Object.keys(Object.fromEntries(this.cachedStyles)).filter(i=>i&&e.getElementType(i)==="node");if(n.length>0){const i=new Set;n.forEach(a=>{e.getRelatedEdgesData(a).forEach(s=>i.add(wt(s)))}),i.forEach(a=>{const s=t==null?void 0:t.getElement(a);s==null||s.update({})})}}}bindEvents(){const{graph:e}=this.context;e.on($t.AFTER_DRAW,this.resetTransform),e.on($t.AFTER_TRANSFORM,this.fixElementSize)}unbindEvents(){const{graph:e}=this.context;e.off($t.AFTER_DRAW,this.resetTransform),e.off($t.AFTER_TRANSFORM,this.fixElementSize)}validate(e){if(this.destroyed)return!1;const{enable:t}=this.options;return En(t)?t(e):!!t}destroy(){this.unbindEvents(),super.destroy()}}Pf.defaultOptions={enable:r=>r.data.scale<1,nodeFilter:()=>!0,edgeFilter:()=>!0,comboFilter:()=>!0,edge:[{shape:"key",fields:["lineWidth"]},{shape:"halo",fields:["lineWidth"]},{shape:"label"}],reset:!1};var lR=function(r,e,t,n){function i(a){return a instanceof t?a:new t(function(s){s(a)})}return new(t||(t=Promise))(function(a,s){function o(h){try{c(n.next(h))}catch(p){s(p)}}function l(h){try{c(n.throw(h))}catch(p){s(p)}}function c(h){h.done?a(h.value):i(h.value).then(o,l)}c((n=n.apply(r,e||[])).next())})};class Df extends Oa{constructor(e,t){super(e,Object.assign({},Df.defaultOptions,t)),this.focus=n=>lR(this,void 0,void 0,function*(){if(!this.validate(n))return;const{graph:i}=this.context;yield i.focusElement(n.target.id,this.options.animation)}),this.bindEvents()}bindEvents(){const{graph:e}=this.context;this.unbindEvents(),sl.forEach(t=>{e.on(`${t}:${kt.CLICK}`,this.focus)})}validate(e){if(this.destroyed)return!1;const{enable:t}=this.options;return En(t)?t(e):!!t}unbindEvents(){const{graph:e}=this.context;sl.forEach(t=>{e.off(`${t}:${kt.CLICK}`,this.focus)})}destroy(){this.unbindEvents(),super.destroy()}}Df.defaultOptions={animation:{easing:"ease-in",duration:500},enable:!0};class Lf extends Oa{constructor(e,t){super(e,Object.assign({},Lf.defaultOptions,t)),this.isFrozen=!1,this.toggleFrozen=n=>{this.isFrozen=n.type==="dragstart"},this.hoverElement=n=>{if(!this.validate(n))return;const i=n.type===kt.POINTER_ENTER;this.updateElementsState(n,i);const{onHover:a,onHoverEnd:s}=this.options;i?a==null||a(n):s==null||s(n)},this.updateElementsState=(n,i)=>{if(!this.options.state&&!this.options.inactiveState)return;const{graph:a}=this.context,{state:s,animation:o,inactiveState:l}=this.options,c=this.getActiveIds(n),h={};if(s&&Object.assign(h,this.getElementsState(c,s,i)),l){const p=D1(a.getData(),!0).filter(C=>!c.includes(C));Object.assign(h,this.getElementsState(p,l,i))}a.setElementState(h,o)},this.getElementsState=(n,i,a)=>{const{graph:s}=this.context,o={};return n.forEach(l=>{const c=s.getElementState(l);a?o[l]=c.includes(i)?c:[...c,i]:o[l]=c.filter(h=>h!==i)}),o},this.bindEvents()}bindEvents(){const{graph:e}=this.context;this.unbindEvents(),sl.forEach(n=>{e.on(`${n}:${kt.POINTER_ENTER}`,this.hoverElement),e.on(`${n}:${kt.POINTER_LEAVE}`,this.hoverElement)});const t=this.context.canvas.document;t.addEventListener(`${kt.DRAG_START}`,this.toggleFrozen),t.addEventListener(`${kt.DRAG_END}`,this.toggleFrozen)}getActiveIds(e){const{graph:t}=this.context,{degree:n,direction:i}=this.options,a=e.target.id;return n?K1(t,e.targetType,a,typeof n=="function"?n(e):n,i):[a]}validate(e){if(this.destroyed||this.isFrozen||_f(e.target)||this.context.graph.isCollapsingExpanding)return!1;const{enable:t}=this.options;return En(t)?t(e):!!t}unbindEvents(){const{graph:e}=this.context;sl.forEach(n=>{e.off(`${n}:${kt.POINTER_ENTER}`,this.hoverElement),e.off(`${n}:${kt.POINTER_LEAVE}`,this.hoverElement)});const t=this.context.canvas.document;t.removeEventListener(`${kt.DRAG_START}`,this.toggleFrozen),t.removeEventListener(`${kt.DRAG_END}`,this.toggleFrozen)}destroy(){this.unbindEvents(),super.destroy()}}Lf.defaultOptions={animation:!1,enable:!0,degree:0,direction:"both",state:"active",inactiveState:void 0};class cR extends Xc{onPointerDown(e){if(!super.validate(e)||!super.isKeydown()||this.points)return;const{canvas:t}=this.context;this.pathShape=new Ta({id:"g6-lasso-select",style:this.options.style}),t.appendChild(this.pathShape),this.points=[Zh(e)]}onPointerMove(e){var t;if(!this.points)return;const{immediately:n,mode:i}=this.options;this.points.push(Zh(e)),(t=this.pathShape)===null||t===void 0||t.setAttribute("d",VP(this.points)),n&&i==="default"&&this.points.length>2&&super.updateElementsStates(this.points)}onPointerUp(){if(this.points){if(this.points.length<2){this.clearLasso();return}super.updateElementsStates(this.points),this.clearLasso()}}clearLasso(){var e;(e=this.pathShape)===null||e===void 0||e.remove(),this.pathShape=void 0,this.points=void 0}}class Rf extends Oa{constructor(e,t){super(e,Object.assign({},Rf.defaultOptions,t)),this.hiddenShapes=[],this.isVisible=!0,this.setElementsVisibility=(n,i,a)=>{n.filter(Boolean).forEach(s=>{i==="hidden"&&!s.isVisible()?this.hiddenShapes.push(s):i==="visible"&&this.hiddenShapes.includes(s)?this.hiddenShapes.splice(this.hiddenShapes.indexOf(s),1):il(s,i,a)})},this.filterShapes=(n,i)=>{if(En(i))return s=>!i(n,s);const a=i==null?void 0:i[n];return s=>s.className?!(a!=null&&a.includes(s.className)):!0},this.hideShapes=n=>{if(!this.validate(n)||!this.isVisible)return;const{element:i}=this.context,{shapes:a={}}=this.options;this.setElementsVisibility(i.getNodes(),"hidden",this.filterShapes("node",a)),this.setElementsVisibility(i.getEdges(),"hidden",this.filterShapes("edge",a)),this.setElementsVisibility(i.getCombos(),"hidden",this.filterShapes("combo",a)),this.isVisible=!1},this.showShapes=ru(n=>{if(!this.validate(n)||this.isVisible)return;const{element:i}=this.context;this.setElementsVisibility(i.getNodes(),"visible"),this.setElementsVisibility(i.getEdges(),"visible"),this.setElementsVisibility(i.getCombos(),"visible"),this.isVisible=!0},this.options.debounce),this.bindEvents()}bindEvents(){const{graph:e}=this.context;e.on($t.BEFORE_TRANSFORM,this.hideShapes),e.on($t.AFTER_TRANSFORM,this.showShapes)}unbindEvents(){const{graph:e}=this.context;e.off($t.BEFORE_TRANSFORM,this.hideShapes),e.off($t.AFTER_TRANSFORM,this.showShapes)}validate(e){if(this.destroyed)return!1;const{enable:t}=this.options;return 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0:re.length)===(ee==null?void 0:ee.length)||(k==null?void 0:k.length)===1?1:e.clusterNodeStrength(Q)},others:1,center:Q=>{const ee=t.getDegree(Q.id,"both");if(!ee)return{x:100,y:100,z:0};let re;if(ee===1){const{sameTypeLeaves:ve=[]}=C[Q.id]||{};ve.length===1?re=void 0:ve.length>1&&(re=zE(ve))}else re=void 0;return{x:re==null?void 0:re.x,y:re==null?void 0:re.y,z:re==null?void 0:re.z}}})),l&&c){C||(C=kE(t,c)),k||(k=Array.from(new Set(h.map(ee=>ee.data[c])))),k=k.filter(ee=>ee!==void 0);const Q={};k.forEach(ee=>{const re=h.filter(ve=>ve.data[c]===ee).map(ve=>t.getNode(ve.id));Q[ee]=zE(re)}),e.centripetalOptions=Object.assign(p,{single:ee=>e.clusterNodeStrength(ee),leaf:ee=>e.clusterNodeStrength(ee),others:ee=>e.clusterNodeStrength(ee),center:ee=>{const re=Q[ee.data[c]];return{x:re==null?void 0:re.x,y:re==null?void 0:re.y,z:re==null?void 0:re.z}}})}const{leaf:W,single:j,others:K}=e.centripetalOptions||{};W&&typeof W!="function"&&(e.centripetalOptions.leaf=()=>W),j&&typeof j!="function"&&(e.centripetalOptions.single=()=>j),K&&typeof K!="function"&&(e.centripetalOptions.others=()=>K)}runOneStep(e,t,n,i,a){const s={},o=e.getAllNodes(),l=e.getAllEdges();if(!(o!=null&&o.length))return;const{monitor:c}=a;if(this.calRepulsive(e,s,a),l&&this.calAttractive(e,s,a),this.calGravity(e,t,s,a),this.updateVelocity(e,s,i,a),c){const h=this.calTotalEnergy(s,o);c({energy:h,nodes:t.getAllNodes(),edges:t.getAllEdges(),iterations:n})}}calTotalEnergy(e,t){if(!(t!=null&&t.length))return 0;let n=0;return t.forEach((i,a)=>{const s=e[i.id].x,o=e[i.id].y,l=this.options.dimensions===3?e[i.id].z:0,c=s*s+o*o+l*l,{mass:h=1}=i.data;n+=h*c*.5}),n}calRepulsive(e,t,n){const{dimensions:i,factor:a,coulombDisScale:s}=n;zI(e,a,s*s,t,i)}calAttractive(e,t,n){const{dimensions:i,nodeSize:a}=n;e.getAllEdges().forEach((s,o)=>{const{source:l,target:c}=s,h=e.getNode(l),p=e.getNode(c);if(!h||!p)return;let C=p.data.x-h.data.x,k=p.data.y-h.data.y,W=i===3?p.data.z-h.data.z:0;!C&&!k&&(C=Math.random()*.01,k=Math.random()*.01,i===3&&!W&&(W=Math.random()*.01));const j=Math.sqrt(C*C+k*k+W*W);if(j<a(h)+a(p))return;const K=C/j,Q=k/j,ee=W/j,{linkDistance:re=200,edgeStrength:ve=200}=s.data||{},pe=(re-j)*ve,ye=h.data.mass||1,_e=p.data.mass||1,De=1/ye,Be=1/_e,ze=K*pe,Xe=Q*pe,$e=ee*pe;t[l].x-=ze*De,t[l].y-=Xe*De,t[l].z-=$e*De,t[c].x+=ze*Be,t[c].y+=Xe*Be,t[c].z+=$e*Be})}calGravity(e,t,n,i){const{getCenter:a}=i,s=e.getAllNodes(),o=t.getAllNodes(),l=t.getAllEdges(),{width:c,height:h,center:p,gravity:C,centripetalOptions:k}=i;s&&s.forEach(W=>{const{id:j,data:K}=W,{mass:Q,x:ee,y:re,z:ve}=K,he=t.getNode(j);let pe=0,ye=0,_e=0,De=C;const Be=e.getDegree(j,"in"),ze=e.getDegree(j,"out"),Xe=e.getDegree(j,"both"),$e=a==null?void 0:a(he,Xe);if($e){const[ct,ut,St]=$e;pe=ee-ct,ye=re-ut,De=St}else pe=ee-p[0],ye=re-p[1],_e=ve-p[2];if(De&&(n[j].x-=De*pe/Q,n[j].y-=De*ye/Q,n[j].z-=De*_e/Q),k){const{leaf:ct,single:ut,others:St,center:bt}=k,{x:Et,y:xt,z:Dt,centerStrength:Ft}=(bt==null?void 0:bt(he,o,l,c,h))||{x:0,y:0,z:0,centerStrength:0};if(!un(Et)||!un(xt))return;const Xt=(ee-Et)/Q,an=(re-xt)/Q,dn=(ve-Dt)/Q;if(Ft&&(n[j].x-=Ft*Xt,n[j].y-=Ft*an,n[j].z-=Ft*dn),Xe===0){const Tn=ut(he);if(!Tn)return;n[j].x-=Tn*Xt,n[j].y-=Tn*an,n[j].z-=Tn*dn;return}if(Be===0||ze===0){const Tn=ct(he,o,l);if(!Tn)return;n[j].x-=Tn*Xt,n[j].y-=Tn*an,n[j].z-=Tn*dn;return}const sn=St(he);if(!sn)return;n[j].x-=sn*Xt,n[j].y-=sn*an,n[j].z-=sn*dn}})}updateVelocity(e,t,n,i){const{damping:a,maxSpeed:s,interval:o,dimensions:l}=i,c=e.getAllNodes();c!=null&&c.length&&c.forEach(h=>{const{id:p}=h;let C=(n[p].x+t[p].x*o)*a||.01,k=(n[p].y+t[p].y*o)*a||.01,W=l===3?(n[p].z+t[p].z*o)*a||.01:0;const j=Math.sqrt(C*C+k*k+W*W);if(j>s){const K=s/j;C=K*C,k=K*k,W=K*W}n[p]={x:C,y:k,z:W}})}updatePosition(e,t,n,i){const{distanceThresholdMode:a,interval:s,dimensions:o}=i,l=t.getAllNodes();if(!(l!=null&&l.length)){this.judgingDistance=0;return}let c=0;a==="max"?this.judgingDistance=-1/0:a==="min"&&(this.judgingDistance=1/0),l.forEach(h=>{const{id:p}=h,C=e.getNode(p);if(un(C.data.fx)&&un(C.data.fy)){t.mergeNodeData(p,{x:C.data.fx,y:C.data.fy,z:o===3?C.data.fz:void 0});return}const k=n[p].x*s,W=n[p].y*s,j=o===3?n[p].z*s:0;t.mergeNodeData(p,{x:h.data.x+k,y:h.data.y+W,z:h.data.z+j});const K=Math.sqrt(k*k+W*W+j*j);switch(a){case"max":this.judgingDistance<K&&(this.judgingDistance=K);break;case"min":this.judgingDistance>K&&(this.judgingDistance=K);break;default:c=c+K;break}}),(!a||a==="mean")&&(this.judgingDistance=c/l.length)}}const kE=(r,e)=>{const t=r.getAllNodes();if(!(t!=null&&t.length))return{};const n={};return t.forEach((i,a)=>{r.getDegree(i.id,"both")===1&&(n[i.id]=jI(r,"leaf",i,e))}),n},jI=(r,e,t,n)=>{const i=r.getDegree(t.id,"in"),a=r.getDegree(t.id,"out");let s=t,o=[];i===0?(s=r.getSuccessors(t.id)[0],o=r.getNeighbors(s.id)):a===0&&(s=r.getPredecessors(t.id)[0],o=r.getNeighbors(s.id)),o=o.filter(c=>r.getDegree(c.id,"in")===0||r.getDegree(c.id,"out")===0);const l=GI(r,e,n,t,o);return{coreNode:s,siblingLeaves:o,sameTypeLeaves:l}},GI=(r,e,t,n,i)=>{const a=n.data[t]||"";let s=(i==null?void 0:i.filter(o=>o.data[t]===a))||[];return e==="leaf"&&(s=s.filter(o=>r.getDegree(o.id,"in")===0||r.getDegree(o.id,"out")===0)),s},zE=r=>{const e={x:0,y:0};r.forEach(n=>{const{x:i,y:a}=n.data;e.x+=i||0,e.y+=a||0});const t=r.length||1;return{x:e.x/t,y:e.y/t}},fp=(r,e)=>e.map(t=>{const{id:n,data:i}=t,a=r.getNode(n);return Object.assign(Object.assign({},a),{data:Object.assign(Object.assign({},a.data),{x:i.x,y:i.y,z:i.z})})});var sr=Z(39293);const fU=sr.XA,dU=sr.a_,vU=sr.yQ,gU=sr.Hs,pU=sr.Ec,mU=sr.dx,yU=sr.LU,_U=sr.Rm,Mo=sr.y3,EU=sr.qK,xU=sr.pb,bU=sr.j,wU=sr.sO,MU=sr.BZ,SU=sr.EK,TU=sr.Db,AU=sr.Fx,CU=sr.tU,OU=sr.Ym,PU=sr.rs,DU=sr.QR,LU=sr.TB,RU=sr.oH,FE=sr.Sc,IU=sr.BN,NU=sr.it,BU=sr.$r,kU=sr.QM,zU=sr.AV;var FU=(sr.y3,sr.y3);const UU=sr.GH,WU=sr.SO,HU=sr.uZ,jU=sr.yU,GU=sr.F1,VU=sr.re,UE=r=>{const e=[],t=r.length;for(let n=0;n<t;n+=1){e[n]=[];for(let i=0;i<t;i+=1)n===i?e[n][i]=0:r[n][i]===0||!r[n][i]?e[n][i]=1/0:e[n][i]=r[n][i]}for(let n=0;n<t;n+=1)for(let i=0;i<t;i+=1)for(let a=0;a<t;a+=1)e[i][a]>e[i][n]+e[n][a]&&(e[i][a]=e[i][n]+e[n][a]);return e},WE=(r,e)=>{const{nodes:t,edges:n}=r,i=[],a={};if(!t)throw new Error("invalid nodes data!");return t&&t.forEach((s,o)=>{a[s.id]=o;const l=[];i.push(l)}),n==null||n.forEach(s=>{const{source:o,target:l}=s,c=a[o],h=a[l];c===void 0||h===void 0||(i[c][h]=1,e||(i[h][c]=1))}),i},VI=(r,e)=>{const t=[];return r.forEach(n=>{const i=[];n.forEach(a=>{i.push(a*e)}),t.push(i)}),t},ZI=r=>{let e=1/0,t=1/0,n=-1/0,i=-1/0;return r.forEach(a=>{let s=a.data.size;Js(s)?s.length===1&&(s=[s[0],s[0]]):un(s)?s=[s,s]:(s===void 0||isNaN(s))&&(s=[30,30]);const o=[s[0]/2,s[1]/2],l=a.data.x-o[0],c=a.data.x+o[0],h=a.data.y-o[1],p=a.data.y+o[1];e>l&&(e=l),t>h&&(t=h),n<c&&(n=c),i<p&&(i=p)}),{minX:e,minY:t,maxX:n,maxY:i}},HE=(r,e)=>Math.sqrt((r.x-e.x)*(r.x-e.x)+(r.y-e.y)*(r.y-e.y)),dp=(r,e,t,n="TB",i,a={})=>{if(!(e!=null&&e.length))return;const{stopBranchFn:s,stopAllFn:o}=a;for(let l=0;l<e.length;l++){const c=e[l];if(r.hasNode(c.id)&&!(s!=null&&s(c))){if(o!=null&&o(c))return;n==="TB"&&t(c),dp(r,r.getChildren(c.id,i),t,n,i,a),n!=="TB"&&t(c)}}},KI={center:[0,0],linkDistance:50};class jE{constructor(e={}){this.options=e,this.id="mds",this.options=Object.assign(Object.assign({},KI),e)}execute(e,t){return(0,we.mG)(this,void 0,void 0,function*(){return this.genericMDSLayout(!1,e,t)})}assign(e,t){return(0,we.mG)(this,void 0,void 0,function*(){yield this.genericMDSLayout(!0,e,t)})}genericMDSLayout(e,t,n){return(0,we.mG)(this,void 0,void 0,function*(){const i=Object.assign(Object.assign({},this.options),n),{center:a=[0,0],linkDistance:s=50}=i,o=t.getAllNodes(),l=t.getAllEdges();if(!(o!=null&&o.length)||o.length===1)return vl(t,e,a);const c=WE({nodes:o,edges:l},!1),h=UE(c);XI(h);const p=VI(h,s),C=YI(p),k=[];return C.forEach((j,K)=>{const Q=La(o[K]);Q.data.x=j[0]+a[0],Q.data.y=j[1]+a[1],k.push(Q)}),e&&k.forEach(j=>t.mergeNodeData(j.id,{x:j.data.x,y:j.data.y})),{nodes:k,edges:l}})}}const XI=r=>{let e=-999999;r.forEach(t=>{t.forEach(n=>{n!==1/0&&e<n&&(e=n)})}),r.forEach((t,n)=>{t.forEach((i,a)=>{i===1/0&&(r[n][a]=e)})})},YI=r=>{const t=Mo.mul(Mo.pow(r,2),-.5),n=t.mean("row"),i=t.mean("column"),a=t.mean();t.add(a).subRowVector(n).subColumnVector(i);const s=new FE(t),o=Mo.sqrt(s.diagonalMatrix).diagonal();return s.leftSingularVectors.toJSON().map(l=>Mo.mul([l],[o]).toJSON()[0].splice(0,2))};function vp(r){return!!r.tick&&!!r.stop}const QI={gForce:!0,force2:!0,d3force:!0,fruchterman:!0,forceAtlas2:!0,force:!0,"graphin-force":!0},JI={center:[0,0],comboPadding:10,treeKey:"combo"};class qI{constructor(e={}){this.options=e,this.id="comboCombined",this.options=Object.assign(Object.assign({},JI),e)}execute(e,t){return(0,we.mG)(this,void 0,void 0,function*(){return this.genericComboCombinedLayout(!1,e,t)})}assign(e,t){return(0,we.mG)(this,void 0,void 0,function*(){yield this.genericComboCombinedLayout(!0,e,t)})}genericComboCombinedLayout(e,t,n){return(0,we.mG)(this,void 0,void 0,function*(){const i=this.initVals(Object.assign(Object.assign({},this.options),n)),{center:a,treeKey:s,outerLayout:o}=i,l=t.getAllNodes().filter(_e=>!_e.data._isCombo),c=t.getAllNodes().filter(_e=>_e.data._isCombo),h=t.getAllEdges(),p=l==null?void 0:l.length;if(!p||p===1)return vl(t,e,a);const C=[],k=new Map;l.forEach(_e=>{k.set(_e.id,_e)});const W=new Map;c.forEach(_e=>{W.set(_e.id,_e)});const j=new Map,K=this.getInnerGraphs(t,s,k,W,h,i,j);yield Promise.all(K);const Q=new Map,ee=[],re=new Map;let ve=!0;t.getRoots(s).forEach(_e=>{const De=j.get(_e.id),Be=W.get(_e.id)||k.get(_e.id),ze={id:_e.id,data:Object.assign(Object.assign({},_e.data),{x:De.data.x||Be.data.x,y:De.data.y||Be.data.y,fx:De.data.fx||Be.data.fx,fy:De.data.fy||Be.data.fy,mass:De.data.mass||Be.data.mass,size:De.data.size})};ee.push(ze),Q.set(_e.id,!0),!isNaN(ze.data.x)&&ze.data.x!==0&&!isNaN(ze.data.y)&&ze.data.y!==0?ve=!1:(ze.data.x=Math.random()*100,ze.data.y=Math.random()*100),dp(t,[_e],Xe=>{Xe.id!==_e.id&&re.set(Xe.id,_e.id)},"TB",s)});const he=[];h.forEach(_e=>{const De=re.get(_e.source)||_e.source,Be=re.get(_e.target)||_e.target;De!==Be&&Q.has(De)&&Q.has(Be)&&he.push({id:_e.id,source:De,target:Be,data:{}})});let pe;if(ee!=null&&ee.length){if(ee.length===1)ee[0].data.x=a[0],ee[0].data.y=a[1];else{const _e=new ci({nodes:ee,edges:he}),De=o||new BE;ve&&QI[De.id]&&(yield(ee.length<100?new jE:new lp).assign(_e));const Be=Object.assign({center:a,kg:5,preventOverlap:!0,animate:!1},De.id==="force"?{gravity:1,factor:4,linkDistance:(ze,Xe,$e)=>{const ct=Math.max(...Xe.data.size)||32,ut=Math.max(...$e.data.size)||32;return ct/2+ut/2+200}}:{});pe=yield GE(De,_e,Be)}j.forEach(_e=>{var De;const Be=pe.nodes.find($e=>$e.id===_e.id);if(Be){const{x:$e,y:ct}=Be.data;_e.data.visited=!0,_e.data.x=$e,_e.data.y=ct,C.push({id:_e.id,data:{x:$e,y:ct}})}const{x:ze,y:Xe}=_e.data;(De=_e.data.nodes)===null||De===void 0||De.forEach($e=>{C.push({id:$e.id,data:{x:$e.data.x+ze,y:$e.data.y+Xe}})})}),j.forEach(({data:_e})=>{const{x:De,y:Be,visited:ze,nodes:Xe}=_e;Xe==null||Xe.forEach($e=>{if(!ze){const ct=C.find(ut=>ut.id===$e.id);ct.data.x+=De||0,ct.data.y+=Be||0}})})}return e&&C.forEach(_e=>{t.mergeNodeData(_e.id,{x:_e.data.x,y:_e.data.y})}),{nodes:C,edges:h}})}initVals(e){const t=Object.assign({},e),{nodeSize:n,spacing:i,comboPadding:a}=e;let s,o;if(un(i)?o=()=>i:En(i)?o=i:o=()=>0,t.spacing=o,!n)s=c=>{const h=o(c);return 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s=["fx","fy","fz"][a];n[s]=i}})}getOptions(e){var t,n;const i=ia({},this.options,e);return i.collide&&((t=i.collide)===null||t===void 0?void 0:t.radius)===void 0&&(i.collide=i.collide||{},i.collide.radius=(n=i.nodeSize)!==null&&n!==void 0?n:10),i.iterations===void 0&&(i.link&&i.link.iterations===void 0&&(i.iterations=i.link.iterations),i.collide&&i.collide.iterations===void 0&&(i.iterations=i.collide.iterations)),this.context.options=i,i}genericLayout(e,t,n){var i;return(0,we.mG)(this,void 0,void 0,function*(){const a=this.getOptions(n),s=t.getAllNodes().map(({id:h,data:p})=>Object.assign(Object.assign({id:h},p),ul(p.data,this.config.inputNodeAttrs))),o=t.getAllEdges().map(h=>Object.assign({},h));Object.assign(this.context,{assign:e,nodes:s,edges:o,graph:t});const l=new Promise(h=>{this.resolver=h}),c=this.setSimulation(a);return c.nodes(s),(i=c.force("link"))===null||i===void 0||i.links(o),l})}getResult(){const{assign:e,nodes:t,edges:n,graph:i}=this.context,a=t.map(o=>({id:o.id,data:Object.assign(Object.assign({},o.data),ul(o,this.config.outputNodeAttrs))})),s=n.map(({id:o,source:l,target:c,data:h})=>({id:o,source:typeof l=="object"?l.id:l,target:typeof c=="object"?c.id:c,data:h}));return e&&a.forEach(o=>i.mergeNodeData(o.id,o.data)),{nodes:a,edges:s}}initSimulation(){return pN()}setSimulation(e){const t=this.simulation||this.options.forceSimulation||this.initSimulation();return this.simulation||(this.simulation=t.on("tick",()=>{var n;return(n=e.onTick)===null||n===void 0?void 0:n.call(e,this.getResult())}).on("end",()=>{var n;return(n=this.resolver)===null||n===void 0?void 0:n.call(this,this.getResult())})),ex(t,this.config.simulationAttrs.map(n=>[n,e[n]])),Object.entries(this.forceMap).forEach(([n,i])=>{const a=n;if(e[n]){let s=t.force(a);s||(s=i(),t.force(a,s)),ex(s,Object.entries(e[a]))}else t.force(a,null)}),t}}const ex=(r,e)=>e.reduce((t,[n,i])=>!t[n]||i===void 0?t:t[n].call(r,i),r);var tx=Z(92546),TN=Z.n(tx);class Hf{constructor(e){this.id="dagre",this.options={},Object.assign(this.options,Hf.defaultOptions,e)}execute(e,t){return(0,we.mG)(this,void 0,void 0,function*(){return this.genericDagreLayout(!1,e,Object.assign(Object.assign({},this.options),t))})}assign(e,t){return(0,we.mG)(this,void 0,void 0,function*(){yield this.genericDagreLayout(!0,e,Object.assign(Object.assign({},this.options),t))})}genericDagreLayout(e,t,n){return(0,we.mG)(this,void 0,void 0,function*(){const{nodeSize:i}=n,a=new tx.graphlib.Graph;a.setGraph(n),a.setDefaultEdgeLabel(()=>({}));const s=t.getAllNodes(),o=t.getAllEdges();[...s,...o].some(({id:c})=>un(c))&&console.error("Dagre layout only support string id, it will convert number to string."),t.getAllNodes().forEach(c=>{const{id:h}=c,p=Object.assign({},c.data);if(i!==void 0){const[C,k]=su(En(i)?i(c):i);Object.assign(p,{width:C,height:k})}a.setNode(h.toString(),p)}),t.getAllEdges().forEach(({id:c,source:h,target:p})=>{a.setEdge(h.toString(),p.toString(),{id:c})}),TN().layout(a);const l={nodes:[],edges:[]};return a.nodes().forEach(c=>{const h=a.node(c);l.nodes.push({id:c,data:h}),e&&t.mergeNodeData(c,h)}),a.edges().forEach(c=>{const h=a.edge(c),{id:p}=h,C=(0,we._T)(h,["id"]),{v:k,w:W}=c;l.edges.push({id:p,source:k,target:W,data:C}),e&&t.mergeEdgeData(p,C)}),l})}}Hf.defaultOptions={};class mp{constructor(e){this.id=e.id||0,this.rx=e.rx,this.ry=e.ry,this.fx=0,this.fy=0,this.mass=e.mass,this.degree=e.degree,this.g=e.g||0}distanceTo(e){const t=this.rx-e.rx,n=this.ry-e.ry;return Math.hypot(t,n)}setPos(e,t){this.rx=e,this.ry=t}resetForce(){this.fx=0,this.fy=0}addForce(e){const t=e.rx-this.rx,n=e.ry-this.ry;let i=Math.hypot(t,n);i=i<1e-4?1e-4:i;const a=this.g*(this.degree+1)*(e.degree+1)/i;this.fx+=a*t/i,this.fy+=a*n/i}in(e){return e.contains(this.rx,this.ry)}add(e){const t=this.mass+e.mass,n=(this.rx*this.mass+e.rx*e.mass)/t,i=(this.ry*this.mass+e.ry*e.mass)/t,a=this.degree+e.degree,s={rx:n,ry:i,mass:t,degree:a};return new mp(s)}}class ql{constructor(e){this.xmid=e.xmid,this.ymid=e.ymid,this.length=e.length,this.massCenter=e.massCenter||[0,0],this.mass=e.mass||1}getLength(){return this.length}contains(e,t){const n=this.length/2;return e<=this.xmid+n&&e>=this.xmid-n&&t<=this.ymid+n&&t>=this.ymid-n}NW(){const e=this.xmid-this.length/4,t=this.ymid+this.length/4,n=this.length/2,i={xmid:e,ymid:t,length:n};return new ql(i)}NE(){const e=this.xmid+this.length/4,t=this.ymid+this.length/4,n=this.length/2,i={xmid:e,ymid:t,length:n};return new ql(i)}SW(){const e=this.xmid-this.length/4,t=this.ymid-this.length/4,n=this.length/2,i={xmid:e,ymid:t,length:n};return new ql(i)}SE(){const e=this.xmid+this.length/4,t=this.ymid-this.length/4,n=this.length/2,i={xmid:e,ymid:t,length:n};return new ql(i)}}class $l{constructor(e){this.body=null,this.quad=null,this.NW=null,this.NE=null,this.SW=null,this.SE=null,this.theta=.5,e!=null&&(this.quad=e)}insert(e){if(this.body==null){this.body=e;return}this._isExternal()?(this.quad&&(this.NW=new $l(this.quad.NW()),this.NE=new $l(this.quad.NE()),this.SW=new $l(this.quad.SW()),this.SE=new $l(this.quad.SE())),this._putBody(this.body),this._putBody(e),this.body=this.body.add(e)):(this.body=this.body.add(e),this._putBody(e))}_putBody(e){this.quad&&(e.in(this.quad.NW())&&this.NW?this.NW.insert(e):e.in(this.quad.NE())&&this.NE?this.NE.insert(e):e.in(this.quad.SW())&&this.SW?this.SW.insert(e):e.in(this.quad.SE())&&this.SE&&this.SE.insert(e))}_isExternal(){return this.NW==null&&this.NE==null&&this.SW==null&&this.SE==null}updateForce(e){if(!(this.body==null||e===this.body))if(this._isExternal())e.addForce(this.body);else{const t=this.quad?this.quad.getLength():0,n=this.body.distanceTo(e);t/n<this.theta?e.addForce(this.body):(this.NW&&this.NW.updateForce(e),this.NE&&this.NE.updateForce(e),this.SW&&this.SW.updateForce(e),this.SE&&this.SE.updateForce(e))}}}const AN={center:[0,0],width:300,height:300,kr:5,kg:1,mode:"normal",preventOverlap:!1,dissuadeHubs:!1,maxIteration:0,ks:.1,ksmax:10,tao:.1};class CN{constructor(e={}){this.options=e,this.id="forceAtlas2",this.options=Object.assign(Object.assign({},AN),e)}execute(e,t){return(0,we.mG)(this,void 0,void 0,function*(){return this.genericForceAtlas2Layout(!1,e,t)})}assign(e,t){return(0,we.mG)(this,void 0,void 0,function*(){yield this.genericForceAtlas2Layout(!0,e,t)})}genericForceAtlas2Layout(e,t,n){return(0,we.mG)(this,void 0,void 0,function*(){const i=t.getAllEdges(),a=t.getAllNodes(),s=this.formatOptions(n,a.length),{width:o,height:l,prune:c,maxIteration:h,nodeSize:p,center:C}=s;if(!(a!=null&&a.length)||a.length===1)return vl(t,e,C);const k=a.map(Q=>La(Q,[o,l])),W=i.filter(Q=>{const{source:ee,target:re}=Q;return ee!==re}),j=new ci({nodes:k,edges:W}),K=this.getSizes(j,p);if(this.run(j,t,h,K,e,s),c){for(let ee=0;ee<W.length;ee+=1){const{source:re,target:ve}=W[ee],he=j.getDegree(re),pe=j.getDegree(re);if(he<=1){const ye=j.getNode(ve);j.mergeNodeData(re,{x:ye.data.x,y:ye.data.y})}else if(pe<=1){const ye=j.getNode(re);j.mergeNodeData(ve,{x:ye.data.x,y:ye.data.y})}}const Q=Object.assign(Object.assign({},s),{prune:!1,barnesHut:!1});this.run(j,t,100,K,e,Q)}return{nodes:k,edges:i}})}getSizes(e,t){const n=e.getAllNodes(),i={};for(let a=0;a<n.length;a+=1){const s=n[a];i[s.id]=sp(t,void 0)(s)}return i}formatOptions(e={},t){const n=Object.assign(Object.assign({},this.options),e),{center:i,width:a,height:s,barnesHut:o,prune:l,maxIteration:c,kr:h,kg:p}=n;return n.width=!a&&typeof window!="undefined"?window.innerWidth:a,n.height=!s&&typeof window!="undefined"?window.innerHeight:s,n.center=i||[n.width/2,n.height/2],o===void 0&&t>250&&(n.barnesHut=!0),l===void 0&&t>100&&(n.prune=!0),c===0&&!l?(n.maxIteration=250,t<=200&&t>100?n.maxIteration=1e3:t>200&&(n.maxIteration=1200)):c===0&&l&&(n.maxIteration=100,t<=200&&t>100?n.maxIteration=500:t>200&&(n.maxIteration=950)),h||(n.kr=50,t>100&&t<=500?n.kr=20:t>500&&(n.kr=1)),p||(n.kg=20,t>100&&t<=500?n.kg=10:t>500&&(n.kg=1)),n}run(e,t,n,i,a,s){const{kr:o,barnesHut:l,onTick:c}=s,h=e.getAllNodes();let p=0,C=n;const k={},W={},j={};for(let K=0;K<h.length;K+=1){const{data:Q,id:ee}=h[K];if(k[ee]=[0,0],l){const re={id:K,rx:Q.x,ry:Q.y,mass:1,g:o,degree:e.getDegree(ee)};j[ee]=new mp(re)}}for(;C>0;)p=this.oneStep(e,{iter:C,preventOverlapIters:50,krPrime:100,sg:p,forces:k,preForces:W,bodies:j,sizes:i},s),C--,c==null||c({nodes:h,edges:t.getAllEdges()});return e}oneStep(e,t,n){const{iter:i,preventOverlapIters:a,krPrime:s,sg:o,preForces:l,bodies:c,sizes:h}=t;let{forces:p}=t;const{preventOverlap:C,barnesHut:k}=n,W=e.getAllNodes();for(let j=0;j<W.length;j+=1){const{id:K}=W[j];l[K]=[...p[K]],p[K]=[0,0]}return p=this.getAttrForces(e,i,a,h,p,n),k&&(C&&i>a||!C)?p=this.getOptRepGraForces(e,p,c,n):p=this.getRepGraForces(e,i,a,p,s,h,n),this.updatePos(e,p,l,o,n)}getAttrForces(e,t,n,i,a,s){const{preventOverlap:o,dissuadeHubs:l,mode:c,prune:h}=s,p=e.getAllEdges();for(let C=0;C<p.length;C+=1){const{source:k,target:W}=p[C],j=e.getNode(k),K=e.getNode(W),Q=e.getDegree(k),ee=e.getDegree(W);if(h&&(Q<=1||ee<=1))continue;const re=[K.data.x-j.data.x,K.data.y-j.data.y];let ve=Math.hypot(re[0],re[1]);ve=ve<1e-4?1e-4:ve,re[0]=re[0]/ve,re[1]=re[1]/ve,o&&t<n&&(ve=ve-i[k]-i[W]);let he=ve,pe=he;c==="linlog"&&(he=Math.log(1+ve),pe=he),l&&(he=ve/Q,pe=ve/ee),o&&t<n&&ve<=0?(he=0,pe=0):o&&t<n&&ve>0&&(he=ve,pe=ve),a[k][0]+=he*re[0],a[W][0]-=pe*re[0],a[k][1]+=he*re[1],a[W][1]-=pe*re[1]}return a}getOptRepGraForces(e,t,n,i){const{kg:a,center:s,prune:o}=i,l=e.getAllNodes(),c=l.length;let h=9e10,p=-9e10,C=9e10,k=-9e10;for(let ee=0;ee<c;ee+=1){const{id:re,data:ve}=l[ee];o&&e.getDegree(re)<=1||(n[re].setPos(ve.x,ve.y),ve.x>=p&&(p=ve.x),ve.x<=h&&(h=ve.x),ve.y>=k&&(k=ve.y),ve.y<=C&&(C=ve.y))}const W=Math.max(p-h,k-C),j={xmid:(p+h)/2,ymid:(k+C)/2,length:W,massCenter:s,mass:c},K=new ql(j),Q=new $l(K);for(let ee=0;ee<c;ee+=1){const{id:re}=l[ee];o&&e.getDegree(re)<=1||n[re].in(K)&&Q.insert(n[re])}for(let ee=0;ee<c;ee+=1){const{id:re,data:ve}=l[ee],he=e.getDegree(re);if(o&&he<=1)continue;n[re].resetForce(),Q.updateForce(n[re]),t[re][0]-=n[re].fx,t[re][1]-=n[re].fy;const pe=[ve.x-s[0],ve.y-s[1]];let ye=Math.hypot(pe[0],pe[1]);ye=ye<1e-4?1e-4:ye,pe[0]=pe[0]/ye,pe[1]=pe[1]/ye;const _e=a*(he+1);t[re][0]-=_e*pe[0],t[re][1]-=_e*pe[1]}return t}getRepGraForces(e,t,n,i,a,s,o){const{preventOverlap:l,kr:c,kg:h,center:p,prune:C}=o,k=e.getAllNodes(),W=k.length;for(let j=0;j<W;j+=1){const K=k[j],Q=e.getDegree(K.id);for(let he=j+1;he<W;he+=1){const pe=k[he],ye=e.getDegree(pe.id);if(C&&(Q<=1||ye<=1))continue;const _e=[pe.data.x-K.data.x,pe.data.y-K.data.y];let De=Math.hypot(_e[0],_e[1]);De=De<1e-4?1e-4:De,_e[0]=_e[0]/De,_e[1]=_e[1]/De,l&&t<n&&(De=De-s[K.id]-s[pe.id]);let Be=c*(Q+1)*(ye+1)/De;l&&t<n&&De<0?Be=a*(Q+1)*(ye+1):l&&t<n&&De===0?Be=0:l&&t<n&&De>0&&(Be=c*(Q+1)*(ye+1)/De),i[K.id][0]-=Be*_e[0],i[pe.id][0]+=Be*_e[0],i[K.id][1]-=Be*_e[1],i[pe.id][1]+=Be*_e[1]}const ee=[K.data.x-p[0],K.data.y-p[1]],re=Math.hypot(ee[0],ee[1]);ee[0]=ee[0]/re,ee[1]=ee[1]/re;const ve=h*(Q+1);i[K.id][0]-=ve*ee[0],i[K.id][1]-=ve*ee[1]}return i}updatePos(e,t,n,i,a){const{ks:s,tao:o,prune:l,ksmax:c}=a,h=e.getAllNodes(),p=h.length,C=[],k=[];let W=0,j=0,K=i;for(let ee=0;ee<p;ee+=1){const{id:re}=h[ee],ve=e.getDegree(re);if(l&&ve<=1)continue;const he=[t[re][0]-n[re][0],t[re][1]-n[re][1]],pe=Math.hypot(he[0],he[1]),ye=[t[re][0]+n[re][0],t[re][1]+n[re][1]],_e=Math.hypot(ye[0],ye[1]);C[ee]=pe,k[ee]=_e/2,W+=(ve+1)*C[ee],j+=(ve+1)*k[ee]}const Q=K;K=o*j/W,Q!==0&&(K=K>1.5*Q?1.5*Q:K);for(let ee=0;ee<p;ee+=1){const{id:re,data:ve}=h[ee],he=e.getDegree(re);if(l&&he<=1||un(ve.fx)&&un(ve.fy))continue;let pe=s*K/(1+K*Math.sqrt(C[ee])),ye=Math.hypot(t[re][0],t[re][1]);ye=ye<1e-4?1e-4:ye;const _e=c/ye;pe=pe>_e?_e:pe;const De=pe*t[re][0],Be=pe*t[re][1];e.mergeNodeData(re,{x:ve.x+De,y:ve.y+Be})}return K}}const ON={maxIteration:1e3,gravity:10,speed:5,clustering:!1,clusterGravity:10,width:300,height:300,nodeClusterBy:"cluster"},PN=800;class DN{constructor(e={}){this.options=e,this.id="fruchterman",this.timeInterval=0,this.running=!1,this.options=Object.assign(Object.assign({},ON),e)}execute(e,t){return(0,we.mG)(this,void 0,void 0,function*(){return this.genericFruchtermanLayout(!1,e,t)})}assign(e,t){return(0,we.mG)(this,void 0,void 0,function*(){yield this.genericFruchtermanLayout(!0,e,t)})}stop(){this.timeInterval&&typeof window!="undefined"&&window.clearInterval(this.timeInterval),this.running=!1}tick(e=this.options.maxIteration||1){if(this.lastResult)return this.lastResult;for(let n=0;n<e;n++)this.runOneStep(this.lastGraph,this.lastClusterMap,this.lastOptions);const t={nodes:this.lastLayoutNodes,edges:this.lastLayoutEdges};return this.lastAssign&&t.nodes.forEach(n=>this.lastGraph.mergeNodeData(n.id,{x:n.data.x,y:n.data.y,z:this.options.dimensions===3?n.data.z:void 0})),t}genericFruchtermanLayout(e,t,n){return(0,we.mG)(this,void 0,void 0,function*(){if(this.running)return;const i=this.formatOptions(n),{dimensions:a,width:s,height:o,center:l,clustering:c,nodeClusterBy:h,maxIteration:p,onTick:C}=i,k=t.getAllNodes(),W=t.getAllEdges();if(!(k!=null&&k.length)){const re={nodes:[],edges:W};return this.lastResult=re,re}if(k.length===1){e&&t.mergeNodeData(k[0].id,{x:l[0],y:l[1],z:a===3?l[2]:void 0});const re={nodes:[Object.assign(Object.assign({},k[0]),{data:Object.assign(Object.assign({},k[0].data),{x:l[0],y:l[1],z:a===3?l[2]:void 0})})],edges:W};return this.lastResult=re,re}const j=k.map(re=>La(re,[s,o])),K=new ci({nodes:j,edges:W}),Q={};if(c&&j.forEach(re=>{const ve=re.data[h];Q[ve]||(Q[ve]={name:ve,cx:0,cy:0,count:0})}),this.lastLayoutNodes=j,this.lastLayoutEdges=W,this.lastAssign=e,this.lastGraph=K,this.lastOptions=i,this.lastClusterMap=Q,typeof window=="undefined")return;let ee=0;return new Promise(re=>{this.timeInterval=window.setInterval(()=>{if(!this.running){re({nodes:j,edges:W});return}this.runOneStep(K,Q,i),e&&j.forEach(({id:ve,data:he})=>t.mergeNodeData(ve,{x:he.x,y:he.y,z:a===3?he.z:void 0})),C==null||C({nodes:j,edges:W}),ee++,ee>=p&&(window.clearInterval(this.timeInterval),re({nodes:j,edges:W}))},0),this.running=!0})})}formatOptions(e={}){const t=Object.assign(Object.assign({},this.options),e),{clustering:n,nodeClusterBy:i}=t,{center:a,width:s,height:o}=t;return t.width=!s&&typeof window!="undefined"?window.innerWidth:s,t.height=!o&&typeof window!="undefined"?window.innerHeight:o,t.center=a||[t.width/2,t.height/2],t.clustering=n&&!!i,t}runOneStep(e,t,n){const{dimensions:i,height:a,width:s,gravity:o,center:l,speed:c,clustering:h,nodeClusterBy:p,clusterGravity:C}=n,k=a*s,W=Math.sqrt(k)/10,j=e.getAllNodes(),K=k/(j.length+1),Q=Math.sqrt(K),ee={};if(this.applyCalculate(e,ee,Q,K),h){for(const ve in t)t[ve].cx=0,t[ve].cy=0,t[ve].count=0;j.forEach(ve=>{const{data:he}=ve,pe=t[he[p]];un(he.x)&&(pe.cx+=he.x),un(he.y)&&(pe.cy+=he.y),pe.count++});for(const ve in t)t[ve].cx/=t[ve].count,t[ve].cy/=t[ve].count;const re=C||o;j.forEach((ve,he)=>{const{id:pe,data:ye}=ve;if(!un(ye.x)||!un(ye.y))return;const _e=t[ye[p]],De=Math.sqrt((ye.x-_e.cx)*(ye.x-_e.cx)+(ye.y-_e.cy)*(ye.y-_e.cy)),Be=Q*re;ee[pe].x-=Be*(ye.x-_e.cx)/De,ee[pe].y-=Be*(ye.y-_e.cy)/De})}j.forEach((re,ve)=>{const{id:he,data:pe}=re;if(!un(pe.x)||!un(pe.y))return;const ye=.01*Q*o;ee[he].x-=ye*(pe.x-l[0]),ee[he].y-=ye*(pe.y-l[1]),i===3&&(ee[he].z-=ye*(pe.z-l[2]))}),j.forEach((re,ve)=>{const{id:he,data:pe}=re;if(un(pe.fx)&&un(pe.fy)){pe.x=pe.fx,pe.y=pe.fy,i===3&&(pe.z=pe.fz);return}if(!un(pe.x)||!un(pe.y))return;const ye=Math.sqrt(ee[he].x*ee[he].x+ee[he].y*ee[he].y+(i===3?ee[he].z*ee[he].z:0));if(ye>0){const _e=Math.min(W*(c/PN),ye);e.mergeNodeData(he,{x:pe.x+ee[he].x/ye*_e,y:pe.y+ee[he].y/ye*_e,z:i===3?pe.z+ee[he].z/ye*_e:void 0})}})}applyCalculate(e,t,n,i){this.calRepulsive(e,t,i),this.calAttractive(e,t,n)}calRepulsive(e,t,n){const i=e.getAllNodes();i.forEach(({data:a,id:s},o)=>{t[s]={x:0,y:0,z:0},i.forEach(({data:l,id:c},h)=>{if(o<=h||!un(a.x)||!un(l.x)||!un(a.y)||!un(l.y))return;let p=a.x-l.x,C=a.y-l.y,k=this.options.dimensions===3?a.z-l.z:0,W=p*p+C*C+k*k;W===0&&(W=1,p=.01,C=.01,k=.01);const 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o.leftSingularVectors.toJSON().map(c=>Mo.mul([c],[l]).toJSON()[0].splice(0,r))}catch(n){const i=[];for(let a=0;a<e.length;a++){const s=Math.random()*t,o=Math.random()*t;i.push([s,o])}return i}},BN=800,kN={iterations:10,height:10,width:10,speed:100,gravity:10,k:5},zN=(r,e)=>{const t=Object.assign(Object.assign({},kN),e),{positions:n,iterations:i,width:a,k:s,speed:o=100,strictRadial:l,focusIdx:c,radii:h=[],nodeSizeFunc:p}=t,C=r.getAllNodes(),k=[],W=a/10;for(let j=0;j<i;j++)n.forEach((K,Q)=>{k[Q]={x:0,y:0}}),FN(C,n,k,s,h,p),UN(n,k,o,l,c,W,a,h);return n},FN=(r,e,t,n,i,a)=>{e.forEach((s,o)=>{t[o]={x:0,y:0},e.forEach((l,c)=>{if(o===c||i[o]!==i[c])return;let h=s.x-l.x,p=s.y-l.y,C=Math.sqrt(h*h+p*p);if(C===0){C=1;const k=o>c?1:-1;h=.01*k,p=.01*k}if(C<a(r[o])/2+a(r[c])/2){const k=n*n/C;t[o].x+=h/C*k,t[o].y+=p/C*k}})})},UN=(r,e,t,n,i,a,s,o)=>{const l=a||s/10;return n&&e.forEach((c,h)=>{const p=r[h].x-r[i].x,C=r[h].y-r[i].y,k=Math.sqrt(p*p+C*C);let W=C/k,j=-p/k;const K=Math.sqrt(c.x*c.x+c.y*c.y);let Q=Math.acos((W*c.x+j*c.y)/K);Q>Math.PI/2&&(Q-=Math.PI/2,W*=-1,j*=-1);const ee=Math.cos(Q)*K;c.x=W*ee,c.y=j*ee}),r.forEach((c,h)=>{if(h===i)return;const p=Math.sqrt(e[h].x*e[h].x+e[h].y*e[h].y);if(p>0&&h!==i){const C=Math.min(l*(t/BN),p);if(c.x+=e[h].x/p*C,c.y+=e[h].y/p*C,n){let k=c.x-r[i].x,W=c.y-r[i].y;const j=Math.sqrt(k*k+W*W);k=k/j*o[h],W=W/j*o[h],c.x=r[i].x+k,c.y=r[i].y+W}}}),r},WN={maxIteration:1e3,focusNode:null,unitRadius:null,linkDistance:50,preventOverlap:!1,strictRadial:!0,maxPreventOverlapIteration:200,sortStrength:10};class HN{constructor(e={}){this.options=e,this.id="radial",this.options=Object.assign(Object.assign({},WN),e)}execute(e,t){return(0,we.mG)(this,void 0,void 0,function*(){return this.genericRadialLayout(!1,e,t)})}assign(e,t){return(0,we.mG)(this,void 0,void 0,function*(){yield this.genericRadialLayout(!0,e,t)})}genericRadialLayout(e,t,n){return(0,we.mG)(this,void 0,void 0,function*(){const i=Object.assign(Object.assign({},this.options),n),{width:a,height:s,center:o,focusNode:l,unitRadius:c,nodeSize:h,nodeSpacing:p,strictRadial:C,preventOverlap:k,maxPreventOverlapIteration:W,sortBy:j,linkDistance:K=50,sortStrength:Q=10,maxIteration:ee=1e3}=i,re=t.getAllNodes(),ve=t.getAllEdges(),he=!a&&typeof window!="undefined"?window.innerWidth:a,pe=!s&&typeof window!="undefined"?window.innerHeight:s,ye=o||[he/2,pe/2];if(!(re!=null&&re.length)||re.length===1)return vl(t,e,ye);let _e=re[0];if(dr(l)){for(let zn=0;zn<re.length;zn++)if(re[zn].id===l){_e=re[zn];break}}else _e=l||re[0];const De=VN(re,_e.id),Be=WE({nodes:re,edges:ve},!1),ze=UE(Be),Xe=KN(ze,De);ZN(ze,De,Xe+1);const $e=ze[De];let ct=he-ye[0]>ye[0]?ye[0]:he-ye[0],ut=pe-ye[1]>ye[1]?ye[1]:pe-ye[1];ct===0&&(ct=he/2),ut===0&&(ut=pe/2);const St=Math.min(ct,ut),bt=Math.max(...$e),Et=[],xt=c||St/bt;$e.forEach((zn,Vn)=>{Et[Vn]=zn*xt});const Dt=jN(re,ze,K,Et,xt,j,Q),Ft=GN(Dt),Xt=NN(K,Dt,K);let an=Xt.map(([zn,Vn])=>({x:(isNaN(zn)?Math.random()*K:zn)-Xt[De][0],y:(isNaN(Vn)?Math.random()*K:Vn)-Xt[De][1]}));this.run(ee,an,Ft,Dt,Et,De);let dn;if(k){dn=sp(h,p);const zn={nodes:re,nodeSizeFunc:dn,positions:an,radii:Et,height:pe,width:he,strictRadial:!!C,focusIdx:De,iterations:W||200,k:an.length/4.5};an=zN(t,zn)}const sn=[];return an.forEach((zn,Vn)=>{const ir=La(re[Vn]);ir.data.x=zn.x+ye[0],ir.data.y=zn.y+ye[1],sn.push(ir)}),e&&sn.forEach(zn=>t.mergeNodeData(zn.id,{x:zn.data.x,y:zn.data.y})),{nodes:sn,edges:ve}})}run(e,t,n,i,a,s){for(let o=0;o<=e;o++){const l=o/e;this.oneIteration(l,t,a,i,n,s)}}oneIteration(e,t,n,i,a,s){const o=1-e;t.forEach((l,c)=>{const h=HE(l,{x:0,y:0}),p=h===0?0:1/h;if(c===s)return;let C=0,k=0,W=0;t.forEach((K,Q)=>{if(c===Q)return;const ee=HE(l,K),re=ee===0?0:1/ee,ve=i[Q][c];W+=a[c][Q],C+=a[c][Q]*(K.x+ve*(l.x-K.x)*re),k+=a[c][Q]*(K.y+ve*(l.y-K.y)*re)});const j=n[c]===0?0:1/n[c];W*=o,W+=e*j*j,C*=o,C+=e*j*l.x*p,l.x=C/W,k*=o,k+=e*j*l.y*p,l.y=k/W})}}const 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i*i}draw(e){e.ellipse(this.cx,this.cy,this.radius,this.radius,0,0,Math.PI*2)}}class pl{constructor(e,t=0,n=0,i=0,a=0,s=10,o=10,l=new Float32Array(Math.max(0,s*o)).fill(0)){this.pixelGroup=e,this.i=t,this.j=n,this.pixelX=i,this.pixelY=a,this.width=s,this.height=o,this.area=l}createSub(e,t){return new pl(this.pixelGroup,e.x,e.y,t.x,t.y,e.width,e.height)}static fromPixelRegion(e,t){return new pl(t,0,0,e.x,e.y,Math.ceil(e.width/t),Math.ceil(e.height/t))}copy(e,t){return new pl(this.pixelGroup,this.scaleX(t.x),this.scaleY(t.y),t.x,t.y,e.width,e.height,e.area)}boundX(e){return e<this.i?this.i:e>=this.width?this.width-1:e}boundY(e){return e<this.j?this.j:e>=this.height?this.height-1:e}scaleX(e){return this.boundX(Math.floor((e-this.pixelX)/this.pixelGroup))}scaleY(e){return this.boundY(Math.floor((e-this.pixelY)/this.pixelGroup))}scale(e){const 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0:i.data.rank,e=Math.max(e,t.data.maxRank||-1/0))}),e},z3=r=>{r.getAllNodes().forEach(e=>{e.data.dummy==="edge-proxy"&&(r.getEdge(e.data.e.id).data.labelRank=e.data.rank,r.removeNode(e.id))})},F3=(r,e)=>{let t,n=0,i,a=0;const{marginx:s=0,marginy:o=0}=e||{},l=c=>{if(!c.data)return;const h=c.data.x,p=c.data.y,C=c.data.width,k=c.data.height;!isNaN(h)&&!isNaN(C)&&(t===void 0&&(t=h-C/2),t=Math.min(t,h-C/2),n=Math.max(n,h+C/2)),!isNaN(p)&&!isNaN(k)&&(i===void 0&&(i=p-k/2),i=Math.min(i,p-k/2),a=Math.max(a,p+k/2))};return r.getAllNodes().forEach(c=>{l(c)}),r.getAllEdges().forEach(c=>{c!=null&&c.data.hasOwnProperty("x")&&l(c)}),t-=s,i-=o,r.getAllNodes().forEach(c=>{c.data.x-=t,c.data.y-=i}),r.getAllEdges().forEach(c=>{var h;(h=c.data.points)===null||h===void 0||h.forEach(p=>{p.x-=t,p.y-=i}),c.data.hasOwnProperty("x")&&(c.data.x-=t),c.data.hasOwnProperty("y")&&(c.data.y-=i)}),{width:n-t+s,height:a-i+o}},U3=r=>{r.getAllEdges().forEach(e=>{const t=r.getNode(e.source),n=r.getNode(e.target);let i,a;e.data.points?(i=e.data.points[0],a=e.data.points[e.data.points.length-1]):(e.data.points=[],i={x:n.data.x,y:n.data.y},a={x:t.data.x,y:t.data.y}),e.data.points.unshift(Q_(t.data,i)),e.data.points.push(Q_(n.data,a))})},W3=r=>{r.getAllEdges().forEach(e=>{if(e.data.hasOwnProperty("x"))switch((e.data.labelpos==="l"||e.data.labelpos==="r")&&(e.data.width-=e.data.labeloffset),e.data.labelpos){case"l":e.data.x-=e.data.width/2+e.data.labeloffset;break;case"r":e.data.x+=e.data.width/2+e.data.labeloffset;break}})},H3=r=>{r.getAllEdges().forEach(e=>{var t;e.data.reversed&&((t=e.data.points)===null||t===void 0||t.reverse())})},j3=r=>{r.getAllNodes().forEach(e=>{var t,n,i;if(!((t=r.getChildren(e.id))===null||t===void 0)&&t.length){const a=r.getNode(e.id),s=r.getNode(a.data.borderTop),o=r.getNode(a.data.borderBottom),l=r.getNode(a.data.borderLeft[((n=a.data.borderLeft)===null||n===void 0?void 0:n.length)-1]),c=r.getNode(a.data.borderRight[((i=a.data.borderRight)===null||i===void 0?void 0:i.length)-1]);a.data.width=Math.abs((c==null?void 0:c.data.x)-(l==null?void 0:l.data.x))||10,a.data.height=Math.abs((o==null?void 0:o.data.y)-(s==null?void 0:s.data.y))||10,a.data.x=((l==null?void 0:l.data.x)||0)+a.data.width/2,a.data.y=((s==null?void 0:s.data.y)||0)+a.data.height/2}}),r.getAllNodes().forEach(e=>{e.data.dummy==="border"&&r.removeNode(e.id)})},G3=r=>{r.getAllEdges().forEach(e=>{if(e.source===e.target){const t=r.getNode(e.source);t.data.selfEdges||(t.data.selfEdges=[]),t.data.selfEdges.push(e),r.removeEdge(e.id)}})},V3=r=>{const e=au(r);e==null||e.forEach(t=>{let n=0;t==null||t.forEach((i,a)=>{var s;const o=r.getNode(i);o.data.order=a+n,(s=o.data.selfEdges)===null||s===void 0||s.forEach(l=>{Ql(r,"selfedge",{width:l.data.width,height:l.data.height,rank:o.data.rank,order:a+ ++n,e:l},"_se")}),delete o.data.selfEdges})})},Z3=r=>{r.getAllNodes().forEach(e=>{const t=r.getNode(e.id);if(t.data.dummy==="selfedge"){const n=r.getNode(t.data.e.source),i=n.data.x+n.data.width/2,a=n.data.y,s=t.data.x-i,o=n.data.height/2;r.hasEdge(t.data.e.id)?r.updateEdgeData(t.data.e.id,t.data.e.data):r.addEdge({id:t.data.e.id,source:t.data.e.source,target:t.data.e.target,data:t.data.e.data}),r.removeNode(e.id),t.data.e.data.points=[{x:i+2*s/3,y:a-o},{x:i+5*s/6,y:a-o},{y:a,x:i+s},{x:i+5*s/6,y:a+o},{x:i+2*s/3,y:a+o}],t.data.e.data.x=t.data.x,t.data.e.data.y=t.data.y}})},CE=(r,e)=>{const t={};return e==null||e.forEach(n=>{r[n]!==void 0&&(t[n]=+r[n])}),t},OE=(r={})=>{const e={};return Object.keys(r).forEach(t=>{e[t.toLowerCase()]=r[t]}),e};function su(r){if(!r)return[0,0,0];if(un(r))return[r,r,r];if(r.length===0)return[0,0,0];const[e,t=e,n=e]=r;return[e,t,n]}function dl(r,e){let t;return En(e)?t=e:un(e)?t=()=>e:t=()=>r,t}function ap(r,e,t=!0){return!e&&e!==0?n=>{const{size:i}=n.data||{};return 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t.data=t.data||{},e&&(un(t.data.x)||(t.data.x=Math.random()*e[0]),un(t.data.y)||(t.data.y=Math.random()*e[1])),t},K3={rankdir:"TB",nodesep:50,ranksep:50,edgeLabelSpace:!0,ranker:"tight-tree",controlPoints:!1,radial:!1,focusNode:null};class X3{constructor(e={}){this.options=e,this.id="antv-dagre",this.options=Object.assign(Object.assign({},K3),e)}execute(e,t){return(0,we.mG)(this,void 0,void 0,function*(){return this.genericDagreLayout(!1,e,t)})}assign(e,t){return(0,we.mG)(this,void 0,void 0,function*(){yield this.genericDagreLayout(!0,e,t)})}genericDagreLayout(e,t,n){return(0,we.mG)(this,void 0,void 0,function*(){const i=Object.assign(Object.assign({},this.options),n),{nodeSize:a,align:s,rankdir:o="TB",ranksep:l,nodesep:c,ranksepFunc:h,nodesepFunc:p,edgeLabelSpace:C,ranker:k,nodeOrder:W,begin:j,controlPoints:K,radial:Q,sortByCombo:ee,preset:re}=i,ve=new ci({tree:[]}),he=dl(l||50,h),pe=dl(c||50,p);let ye=pe,_e=he;(o==="LR"||o==="RL")&&(ye=he,_e=pe);const 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e&&r.mergeNodeData(n[0].id,{x:t[0],y:t[1]}),{nodes:[Object.assign(Object.assign({},n[0]),{data:Object.assign(Object.assign({},n[0].data),{x:t[0],y:t[1]})})],edges:i}},Q3={radius:null,startRadius:null,endRadius:null,startAngle:0,endAngle:2*Math.PI,clockwise:!0,divisions:1,ordering:null,angleRatio:1};class J3{constructor(e={}){this.options=e,this.id="circular",this.options=Object.assign(Object.assign({},Q3),e)}execute(e,t){return(0,we.mG)(this,void 0,void 0,function*(){return this.genericCircularLayout(!1,e,t)})}assign(e,t){return(0,we.mG)(this,void 0,void 0,function*(){yield this.genericCircularLayout(!0,e,t)})}genericCircularLayout(e,t,n){return(0,we.mG)(this,void 0,void 0,function*(){const i=Object.assign(Object.assign({},this.options),n),{width:a,height:s,center:o,divisions:l,startAngle:c=0,endAngle:h=2*Math.PI,angleRatio:p,ordering:C,clockwise:k,nodeSpacing:W,nodeSize:j}=i,K=t.getAllNodes(),Q=t.getAllEdges(),[ee,re,ve]=$3(a,s,o),he=K==null?void 0:K.length;if(!he||he===1)return 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ve<o&&(Q===0&&(Q=So(t),ve+=Q*Q),ee===0&&(ee=So(t),ve+=ee*ee),ve<s&&(ve=Math.sqrt(s*ve)),e.vx+=Q*k.value*n/ve,e.vy+=ee*k.value*n/ve),!0;if(k.length||ve>=o)return;(k.data!==e||k.next)&&(Q===0&&(Q=So(t),ve+=Q*Q),ee===0&&(ee=So(t),ve+=ee*ee),ve<s&&(ve=Math.sqrt(s*ve)));do k.data!==e&&(re=a[k.data.index]*n/ve,e.vx+=Q*re,e.vy+=ee*re);while(k=k.next)}return c.initialize=function(k,W){r=k,t=W,h()},c.strength=function(k){return arguments.length?(i=typeof k=="function"?k:bi(+k),h(),c):i},c.distanceMin=function(k){return arguments.length?(s=k*k,c):Math.sqrt(s)},c.distanceMax=function(k){return arguments.length?(o=k*k,c):Math.sqrt(o)},c.theta=function(k){return arguments.length?(l=k*k,c):Math.sqrt(l)},c}function yN(r,e){var t,n=1;r==null&&(r=0),e==null&&(e=0);function i(){var a,s=t.length,o,l=0,c=0;for(a=0;a<s;++a)o=t[a],l+=o.x,c+=o.y;for(l=(l/s-r)*n,c=(c/s-e)*n,a=0;a<s;++a)o=t[a],o.x-=l,o.y-=c}return i.initialize=function(a){t=a},i.x=function(a){return 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ex=(r,e)=>e.reduce((t,[n,i])=>!t[n]||i===void 0?t:t[n].call(r,i),r);var tx=Z(92546),TN=Z.n(tx);class Hf{constructor(e){this.id="dagre",this.options={},Object.assign(this.options,Hf.defaultOptions,e)}execute(e,t){return(0,we.mG)(this,void 0,void 0,function*(){return this.genericDagreLayout(!1,e,Object.assign(Object.assign({},this.options),t))})}assign(e,t){return(0,we.mG)(this,void 0,void 0,function*(){yield this.genericDagreLayout(!0,e,Object.assign(Object.assign({},this.options),t))})}genericDagreLayout(e,t,n){return(0,we.mG)(this,void 0,void 0,function*(){const{nodeSize:i}=n,a=new tx.graphlib.Graph;a.setGraph(n),a.setDefaultEdgeLabel(()=>({}));const s=t.getAllNodes(),o=t.getAllEdges();[...s,...o].some(({id:c})=>un(c))&&console.error("Dagre layout only support string id, it will convert number to string."),t.getAllNodes().forEach(c=>{const{id:h}=c,p=Object.assign({},c.data);if(i!==void 0){const[C,k]=su(En(i)?i(c):i);Object.assign(p,{width:C,height:k})}a.setNode(h.toString(),p)}),t.getAllEdges().forEach(({id:c,source:h,target:p})=>{a.setEdge(h.toString(),p.toString(),{id:c})}),TN().layout(a);const l={nodes:[],edges:[]};return a.nodes().forEach(c=>{const h=a.node(c);l.nodes.push({id:c,data:h}),e&&t.mergeNodeData(c,h)}),a.edges().forEach(c=>{const h=a.edge(c),{id:p}=h,C=(0,we._T)(h,["id"]),{v:k,w:W}=c;l.edges.push({id:p,source:k,target:W,data:C}),e&&t.mergeEdgeData(p,C)}),l})}}Hf.defaultOptions={};class mp{constructor(e){this.id=e.id||0,this.rx=e.rx,this.ry=e.ry,this.fx=0,this.fy=0,this.mass=e.mass,this.degree=e.degree,this.g=e.g||0}distanceTo(e){const t=this.rx-e.rx,n=this.ry-e.ry;return Math.hypot(t,n)}setPos(e,t){this.rx=e,this.ry=t}resetForce(){this.fx=0,this.fy=0}addForce(e){const t=e.rx-this.rx,n=e.ry-this.ry;let i=Math.hypot(t,n);i=i<1e-4?1e-4:i;const a=this.g*(this.degree+1)*(e.degree+1)/i;this.fx+=a*t/i,this.fy+=a*n/i}in(e){return e.contains(this.rx,this.ry)}add(e){const t=this.mass+e.mass,n=(this.rx*this.mass+e.rx*e.mass)/t,i=(this.ry*this.mass+e.ry*e.mass)/t,a=this.degree+e.degree,s={rx:n,ry:i,mass:t,degree:a};return new mp(s)}}class ql{constructor(e){this.xmid=e.xmid,this.ymid=e.ymid,this.length=e.length,this.massCenter=e.massCenter||[0,0],this.mass=e.mass||1}getLength(){return this.length}contains(e,t){const n=this.length/2;return e<=this.xmid+n&&e>=this.xmid-n&&t<=this.ymid+n&&t>=this.ymid-n}NW(){const e=this.xmid-this.length/4,t=this.ymid+this.length/4,n=this.length/2,i={xmid:e,ymid:t,length:n};return new ql(i)}NE(){const e=this.xmid+this.length/4,t=this.ymid+this.length/4,n=this.length/2,i={xmid:e,ymid:t,length:n};return new ql(i)}SW(){const e=this.xmid-this.length/4,t=this.ymid-this.length/4,n=this.length/2,i={xmid:e,ymid:t,length:n};return new ql(i)}SE(){const e=this.xmid+this.length/4,t=this.ymid-this.length/4,n=this.length/2,i={xmid:e,ymid:t,length:n};return new ql(i)}}class $l{constructor(e){this.body=null,this.quad=null,this.NW=null,this.NE=null,this.SW=null,this.SE=null,this.theta=.5,e!=null&&(this.quad=e)}insert(e){if(this.body==null){this.body=e;return}this._isExternal()?(this.quad&&(this.NW=new $l(this.quad.NW()),this.NE=new $l(this.quad.NE()),this.SW=new $l(this.quad.SW()),this.SE=new $l(this.quad.SE())),this._putBody(this.body),this._putBody(e),this.body=this.body.add(e)):(this.body=this.body.add(e),this._putBody(e))}_putBody(e){this.quad&&(e.in(this.quad.NW())&&this.NW?this.NW.insert(e):e.in(this.quad.NE())&&this.NE?this.NE.insert(e):e.in(this.quad.SW())&&this.SW?this.SW.insert(e):e.in(this.quad.SE())&&this.SE&&this.SE.insert(e))}_isExternal(){return this.NW==null&&this.NE==null&&this.SW==null&&this.SE==null}updateForce(e){if(!(this.body==null||e===this.body))if(this._isExternal())e.addForce(this.body);else{const t=this.quad?this.quad.getLength():0,n=this.body.distanceTo(e);t/n<this.theta?e.addForce(this.body):(this.NW&&this.NW.updateForce(e),this.NE&&this.NE.updateForce(e),this.SW&&this.SW.updateForce(e),this.SE&&this.SE.updateForce(e))}}}const AN={center:[0,0],width:300,height:300,kr:5,kg:1,mode:"normal",preventOverlap:!1,dissuadeHubs:!1,maxIteration:0,ks:.1,ksmax:10,tao:.1};class CN{constructor(e={}){this.options=e,this.id="forceAtlas2",this.options=Object.assign(Object.assign({},AN),e)}execute(e,t){return(0,we.mG)(this,void 0,void 0,function*(){return this.genericForceAtlas2Layout(!1,e,t)})}assign(e,t){return(0,we.mG)(this,void 0,void 0,function*(){yield this.genericForceAtlas2Layout(!0,e,t)})}genericForceAtlas2Layout(e,t,n){return(0,we.mG)(this,void 0,void 0,function*(){const i=t.getAllEdges(),a=t.getAllNodes(),s=this.formatOptions(n,a.length),{width:o,height:l,prune:c,maxIteration:h,nodeSize:p,center:C}=s;if(!(a!=null&&a.length)||a.length===1)return vl(t,e,C);const k=a.map(Q=>La(Q,[o,l])),W=i.filter(Q=>{const{source:ee,target:re}=Q;return ee!==re}),j=new ci({nodes:k,edges:W}),K=this.getSizes(j,p);if(this.run(j,t,h,K,e,s),c){for(let ee=0;ee<W.length;ee+=1){const{source:re,target:ve}=W[ee],he=j.getDegree(re),pe=j.getDegree(re);if(he<=1){const ye=j.getNode(ve);j.mergeNodeData(re,{x:ye.data.x,y:ye.data.y})}else if(pe<=1){const ye=j.getNode(re);j.mergeNodeData(ve,{x:ye.data.x,y:ye.data.y})}}const Q=Object.assign(Object.assign({},s),{prune:!1,barnesHut:!1});this.run(j,t,100,K,e,Q)}return{nodes:k,edges:i}})}getSizes(e,t){const n=e.getAllNodes(),i={};for(let a=0;a<n.length;a+=1){const s=n[a];i[s.id]=sp(t,void 0)(s)}return i}formatOptions(e={},t){const n=Object.assign(Object.assign({},this.options),e),{center:i,width:a,height:s,barnesHut:o,prune:l,maxIteration:c,kr:h,kg:p}=n;return n.width=!a&&typeof window!="undefined"?window.innerWidth:a,n.height=!s&&typeof window!="undefined"?window.innerHeight:s,n.center=i||[n.width/2,n.height/2],o===void 0&&t>250&&(n.barnesHut=!0),l===void 0&&t>100&&(n.prune=!0),c===0&&!l?(n.maxIteration=250,t<=200&&t>100?n.maxIteration=1e3:t>200&&(n.maxIteration=1200)):c===0&&l&&(n.maxIteration=100,t<=200&&t>100?n.maxIteration=500:t>200&&(n.maxIteration=950)),h||(n.kr=50,t>100&&t<=500?n.kr=20:t>500&&(n.kr=1)),p||(n.kg=20,t>100&&t<=500?n.kg=10:t>500&&(n.kg=1)),n}run(e,t,n,i,a,s){const{kr:o,barnesHut:l,onTick:c}=s,h=e.getAllNodes();let p=0,C=n;const k={},W={},j={};for(let K=0;K<h.length;K+=1){const{data:Q,id:ee}=h[K];if(k[ee]=[0,0],l){const re={id:K,rx:Q.x,ry:Q.y,mass:1,g:o,degree:e.getDegree(ee)};j[ee]=new mp(re)}}for(;C>0;)p=this.oneStep(e,{iter:C,preventOverlapIters:50,krPrime:100,sg:p,forces:k,preForces:W,bodies:j,sizes:i},s),C--,c==null||c({nodes:h,edges:t.getAllEdges()});return e}oneStep(e,t,n){const{iter:i,preventOverlapIters:a,krPrime:s,sg:o,preForces:l,bodies:c,sizes:h}=t;let{forces:p}=t;const{preventOverlap:C,barnesHut:k}=n,W=e.getAllNodes();for(let j=0;j<W.length;j+=1){const{id:K}=W[j];l[K]=[...p[K]],p[K]=[0,0]}return p=this.getAttrForces(e,i,a,h,p,n),k&&(C&&i>a||!C)?p=this.getOptRepGraForces(e,p,c,n):p=this.getRepGraForces(e,i,a,p,s,h,n),this.updatePos(e,p,l,o,n)}getAttrForces(e,t,n,i,a,s){const{preventOverlap:o,dissuadeHubs:l,mode:c,prune:h}=s,p=e.getAllEdges();for(let C=0;C<p.length;C+=1){const{source:k,target:W}=p[C],j=e.getNode(k),K=e.getNode(W),Q=e.getDegree(k),ee=e.getDegree(W);if(h&&(Q<=1||ee<=1))continue;const re=[K.data.x-j.data.x,K.data.y-j.data.y];let ve=Math.hypot(re[0],re[1]);ve=ve<1e-4?1e-4:ve,re[0]=re[0]/ve,re[1]=re[1]/ve,o&&t<n&&(ve=ve-i[k]-i[W]);let he=ve,pe=he;c==="linlog"&&(he=Math.log(1+ve),pe=he),l&&(he=ve/Q,pe=ve/ee),o&&t<n&&ve<=0?(he=0,pe=0):o&&t<n&&ve>0&&(he=ve,pe=ve),a[k][0]+=he*re[0],a[W][0]-=pe*re[0],a[k][1]+=he*re[1],a[W][1]-=pe*re[1]}return a}getOptRepGraForces(e,t,n,i){const{kg:a,center:s,prune:o}=i,l=e.getAllNodes(),c=l.length;let h=9e10,p=-9e10,C=9e10,k=-9e10;for(let ee=0;ee<c;ee+=1){const{id:re,data:ve}=l[ee];o&&e.getDegree(re)<=1||(n[re].setPos(ve.x,ve.y),ve.x>=p&&(p=ve.x),ve.x<=h&&(h=ve.x),ve.y>=k&&(k=ve.y),ve.y<=C&&(C=ve.y))}const W=Math.max(p-h,k-C),j={xmid:(p+h)/2,ymid:(k+C)/2,length:W,massCenter:s,mass:c},K=new ql(j),Q=new $l(K);for(let ee=0;ee<c;ee+=1){const{id:re}=l[ee];o&&e.getDegree(re)<=1||n[re].in(K)&&Q.insert(n[re])}for(let ee=0;ee<c;ee+=1){const{id:re,data:ve}=l[ee],he=e.getDegree(re);if(o&&he<=1)continue;n[re].resetForce(),Q.updateForce(n[re]),t[re][0]-=n[re].fx,t[re][1]-=n[re].fy;const pe=[ve.x-s[0],ve.y-s[1]];let ye=Math.hypot(pe[0],pe[1]);ye=ye<1e-4?1e-4:ye,pe[0]=pe[0]/ye,pe[1]=pe[1]/ye;const _e=a*(he+1);t[re][0]-=_e*pe[0],t[re][1]-=_e*pe[1]}return t}getRepGraForces(e,t,n,i,a,s,o){const{preventOverlap:l,kr:c,kg:h,center:p,prune:C}=o,k=e.getAllNodes(),W=k.length;for(let j=0;j<W;j+=1){const K=k[j],Q=e.getDegree(K.id);for(let he=j+1;he<W;he+=1){const pe=k[he],ye=e.getDegree(pe.id);if(C&&(Q<=1||ye<=1))continue;const _e=[pe.data.x-K.data.x,pe.data.y-K.data.y];let De=Math.hypot(_e[0],_e[1]);De=De<1e-4?1e-4:De,_e[0]=_e[0]/De,_e[1]=_e[1]/De,l&&t<n&&(De=De-s[K.id]-s[pe.id]);let Be=c*(Q+1)*(ye+1)/De;l&&t<n&&De<0?Be=a*(Q+1)*(ye+1):l&&t<n&&De===0?Be=0:l&&t<n&&De>0&&(Be=c*(Q+1)*(ye+1)/De),i[K.id][0]-=Be*_e[0],i[pe.id][0]+=Be*_e[0],i[K.id][1]-=Be*_e[1],i[pe.id][1]+=Be*_e[1]}const ee=[K.data.x-p[0],K.data.y-p[1]],re=Math.hypot(ee[0],ee[1]);ee[0]=ee[0]/re,ee[1]=ee[1]/re;const ve=h*(Q+1);i[K.id][0]-=ve*ee[0],i[K.id][1]-=ve*ee[1]}return i}updatePos(e,t,n,i,a){const{ks:s,tao:o,prune:l,ksmax:c}=a,h=e.getAllNodes(),p=h.length,C=[],k=[];let W=0,j=0,K=i;for(let ee=0;ee<p;ee+=1){const{id:re}=h[ee],ve=e.getDegree(re);if(l&&ve<=1)continue;const he=[t[re][0]-n[re][0],t[re][1]-n[re][1]],pe=Math.hypot(he[0],he[1]),ye=[t[re][0]+n[re][0],t[re][1]+n[re][1]],_e=Math.hypot(ye[0],ye[1]);C[ee]=pe,k[ee]=_e/2,W+=(ve+1)*C[ee],j+=(ve+1)*k[ee]}const Q=K;K=o*j/W,Q!==0&&(K=K>1.5*Q?1.5*Q:K);for(let ee=0;ee<p;ee+=1){const{id:re,data:ve}=h[ee],he=e.getDegree(re);if(l&&he<=1||un(ve.fx)&&un(ve.fy))continue;let pe=s*K/(1+K*Math.sqrt(C[ee])),ye=Math.hypot(t[re][0],t[re][1]);ye=ye<1e-4?1e-4:ye;const _e=c/ye;pe=pe>_e?_e:pe;const De=pe*t[re][0],Be=pe*t[re][1];e.mergeNodeData(re,{x:ve.x+De,y:ve.y+Be})}return K}}const ON={maxIteration:1e3,gravity:10,speed:5,clustering:!1,clusterGravity:10,width:300,height:300,nodeClusterBy:"cluster"},PN=800;class DN{constructor(e={}){this.options=e,this.id="fruchterman",this.timeInterval=0,this.running=!1,this.options=Object.assign(Object.assign({},ON),e)}execute(e,t){return(0,we.mG)(this,void 0,void 0,function*(){return this.genericFruchtermanLayout(!1,e,t)})}assign(e,t){return(0,we.mG)(this,void 0,void 0,function*(){yield this.genericFruchtermanLayout(!0,e,t)})}stop(){this.timeInterval&&typeof window!="undefined"&&window.clearInterval(this.timeInterval),this.running=!1}tick(e=this.options.maxIteration||1){if(this.lastResult)return this.lastResult;for(let n=0;n<e;n++)this.runOneStep(this.lastGraph,this.lastClusterMap,this.lastOptions);const t={nodes:this.lastLayoutNodes,edges:this.lastLayoutEdges};return this.lastAssign&&t.nodes.forEach(n=>this.lastGraph.mergeNodeData(n.id,{x:n.data.x,y:n.data.y,z:this.options.dimensions===3?n.data.z:void 0})),t}genericFruchtermanLayout(e,t,n){return(0,we.mG)(this,void 0,void 0,function*(){if(this.running)return;const i=this.formatOptions(n),{dimensions:a,width:s,height:o,center:l,clustering:c,nodeClusterBy:h,maxIteration:p,onTick:C}=i,k=t.getAllNodes(),W=t.getAllEdges();if(!(k!=null&&k.length)){const re={nodes:[],edges:W};return this.lastResult=re,re}if(k.length===1){e&&t.mergeNodeData(k[0].id,{x:l[0],y:l[1],z:a===3?l[2]:void 0});const re={nodes:[Object.assign(Object.assign({},k[0]),{data:Object.assign(Object.assign({},k[0].data),{x:l[0],y:l[1],z:a===3?l[2]:void 0})})],edges:W};return this.lastResult=re,re}const j=k.map(re=>La(re,[s,o])),K=new ci({nodes:j,edges:W}),Q={};if(c&&j.forEach(re=>{const ve=re.data[h];Q[ve]||(Q[ve]={name:ve,cx:0,cy:0,count:0})}),this.lastLayoutNodes=j,this.lastLayoutEdges=W,this.lastAssign=e,this.lastGraph=K,this.lastOptions=i,this.lastClusterMap=Q,typeof window=="undefined")return;let ee=0;return new Promise(re=>{this.timeInterval=window.setInterval(()=>{if(!this.running){re({nodes:j,edges:W});return}this.runOneStep(K,Q,i),e&&j.forEach(({id:ve,data:he})=>t.mergeNodeData(ve,{x:he.x,y:he.y,z:a===3?he.z:void 0})),C==null||C({nodes:j,edges:W}),ee++,ee>=p&&(window.clearInterval(this.timeInterval),re({nodes:j,edges:W}))},0),this.running=!0})})}formatOptions(e={}){const t=Object.assign(Object.assign({},this.options),e),{clustering:n,nodeClusterBy:i}=t,{center:a,width:s,height:o}=t;return t.width=!s&&typeof window!="undefined"?window.innerWidth:s,t.height=!o&&typeof window!="undefined"?window.innerHeight:o,t.center=a||[t.width/2,t.height/2],t.clustering=n&&!!i,t}runOneStep(e,t,n){const{dimensions:i,height:a,width:s,gravity:o,center:l,speed:c,clustering:h,nodeClusterBy:p,clusterGravity:C}=n,k=a*s,W=Math.sqrt(k)/10,j=e.getAllNodes(),K=k/(j.length+1),Q=Math.sqrt(K),ee={};if(this.applyCalculate(e,ee,Q,K),h){for(const ve in t)t[ve].cx=0,t[ve].cy=0,t[ve].count=0;j.forEach(ve=>{const{data:he}=ve,pe=t[he[p]];un(he.x)&&(pe.cx+=he.x),un(he.y)&&(pe.cy+=he.y),pe.count++});for(const ve in t)t[ve].cx/=t[ve].count,t[ve].cy/=t[ve].count;const re=C||o;j.forEach((ve,he)=>{const{id:pe,data:ye}=ve;if(!un(ye.x)||!un(ye.y))return;const _e=t[ye[p]],De=Math.sqrt((ye.x-_e.cx)*(ye.x-_e.cx)+(ye.y-_e.cy)*(ye.y-_e.cy)),Be=Q*re;ee[pe].x-=Be*(ye.x-_e.cx)/De,ee[pe].y-=Be*(ye.y-_e.cy)/De})}j.forEach((re,ve)=>{const{id:he,data:pe}=re;if(!un(pe.x)||!un(pe.y))return;const ye=.01*Q*o;ee[he].x-=ye*(pe.x-l[0]),ee[he].y-=ye*(pe.y-l[1]),i===3&&(ee[he].z-=ye*(pe.z-l[2]))}),j.forEach((re,ve)=>{const{id:he,data:pe}=re;if(un(pe.fx)&&un(pe.fy)){pe.x=pe.fx,pe.y=pe.fy,i===3&&(pe.z=pe.fz);return}if(!un(pe.x)||!un(pe.y))return;const ye=Math.sqrt(ee[he].x*ee[he].x+ee[he].y*ee[he].y+(i===3?ee[he].z*ee[he].z:0));if(ye>0){const _e=Math.min(W*(c/PN),ye);e.mergeNodeData(he,{x:pe.x+ee[he].x/ye*_e,y:pe.y+ee[he].y/ye*_e,z:i===3?pe.z+ee[he].z/ye*_e:void 0})}})}applyCalculate(e,t,n,i){this.calRepulsive(e,t,i),this.calAttractive(e,t,n)}calRepulsive(e,t,n){const i=e.getAllNodes();i.forEach(({data:a,id:s},o)=>{t[s]={x:0,y:0,z:0},i.forEach(({data:l,id:c},h)=>{if(o<=h||!un(a.x)||!un(l.x)||!un(a.y)||!un(l.y))return;let p=a.x-l.x,C=a.y-l.y,k=this.options.dimensions===3?a.z-l.z:0,W=p*p+C*C+k*k;W===0&&(W=1,p=.01,C=.01,k=.01);const j=n/W,K=p*j,Q=C*j,ee=k*j;t[s].x+=K,t[s].y+=Q,t[c].x-=K,t[c].y-=Q,this.options.dimensions===3&&(t[s].z+=ee,t[c].z-=ee)})})}calAttractive(e,t,n){e.getAllEdges().forEach(a=>{const{source:s,target:o}=a;if(!s||!o||s===o)return;const{data:l}=e.getNode(s),{data:c}=e.getNode(o);if(!un(c.x)||!un(l.x)||!un(c.y)||!un(l.y))return;const h=c.x-l.x,p=c.y-l.y,C=this.options.dimensions===3?c.z-l.z:0,k=Math.sqrt(h*h+p*p+C*C)/n,W=h*k,j=p*k,K=C*k;t[s].x+=W,t[s].y+=j,t[o].x-=W,t[o].y-=j,this.options.dimensions===3&&(t[s].z+=K,t[o].z-=K)})}}const LN={begin:[0,0],preventOverlap:!0,preventOverlapPadding:10,condense:!1,rows:void 0,cols:void 0,position:void 0,sortBy:"degree",nodeSize:30,width:300,height:300};class RN{constructor(e={}){this.options=e,this.id="grid",this.options=Object.assign(Object.assign({},LN),e)}execute(e,t){return(0,we.mG)(this,void 0,void 0,function*(){return this.genericGridLayout(!1,e,t)})}assign(e,t){return(0,we.mG)(this,void 0,void 0,function*(){yield this.genericGridLayout(!0,e,t)})}genericGridLayout(e,t,n){return(0,we.mG)(this,void 0,void 0,function*(){const i=Object.assign(Object.assign({},this.options),n),{begin:a=[0,0],condense:s,preventOverlapPadding:o,preventOverlap:l,rows:c,cols:h,nodeSpacing:p,nodeSize:C,width:k,height:W,position:j}=i;let{sortBy:K}=i;const Q=t.getAllNodes(),ee=t.getAllEdges(),re=Q==null?void 0:Q.length;if(!re||re===1)return vl(t,e,a);const ve=Q.map(ut=>La(ut));K!=="id"&&(!dr(K)||ve[0].data[K]===void 0)&&(K="degree"),K==="degree"?ve.sort((ut,St)=>t.getDegree(St.id,"both")-t.getDegree(ut.id,"both")):K==="id"?ve.sort((ut,St)=>un(St.id)&&un(ut.id)?St.id-ut.id:`${ut.id}`.localeCompare(`${St.id}`)):ve.sort((ut,St)=>St.data[K]-ut.data[K]);const he=!k&&typeof window!="undefined"?window.innerWidth:k,pe=!W&&typeof window!="undefined"?window.innerHeight:W,ye=re,_e={rows:c,cols:h};if(c!=null&&h!=null)_e.rows=c,_e.cols=h;else if(c!=null&&h==null)_e.rows=c,_e.cols=Math.ceil(ye/_e.rows);else if(c==null&&h!=null)_e.cols=h,_e.rows=Math.ceil(ye/_e.cols);else{const ut=Math.sqrt(ye*pe/he);_e.rows=Math.round(ut),_e.cols=Math.round(he/pe*ut)}if(_e.rows=Math.max(_e.rows,1),_e.cols=Math.max(_e.cols,1),_e.cols*_e.rows>ye){const ut=jf(_e),St=Gf(_e);(ut-1)*St>=ye?jf(_e,ut-1):(St-1)*ut>=ye&&Gf(_e,St-1)}else for(;_e.cols*_e.rows<ye;){const ut=jf(_e),St=Gf(_e);(St+1)*ut>=ye?Gf(_e,St+1):jf(_e,ut+1)}let De=s?0:he/_e.cols,Be=s?0:pe/_e.rows;if(l||p){const ut=dl(10,p),St=ap(30,C,!1);ve.forEach(bt=>{(!bt.data.x||!bt.data.y)&&(bt.data.x=0,bt.data.y=0);const Et=t.getNode(bt.id),[xt,Dt]=su(St(Et)||30),Ft=ut!==void 0?ut(bt):o,Xt=xt+Ft,an=Dt+Ft;De=Math.max(De,Xt),Be=Math.max(Be,an)})}const ze={},Xe={row:0,col:0},$e={};for(let ut=0;ut<ve.length;ut++){const St=ve[ut];let bt;if(j&&(bt=j(t.getNode(St.id))),bt&&(bt.row!==void 0||bt.col!==void 0)){const Et={row:bt.row,col:bt.col};if(Et.col===void 0)for(Et.col=0;yp(ze,Et);)Et.col++;else if(Et.row===void 0)for(Et.row=0;yp(ze,Et);)Et.row++;$e[St.id]=Et,nx(ze,Et)}IN(St,a,De,Be,$e,_e,Xe,ze)}const ct={nodes:ve,edges:ee};return e&&ve.forEach(ut=>{t.mergeNodeData(ut.id,{x:ut.data.x,y:ut.data.y})}),ct})}}const jf=(r,e)=>{let t;const n=r.rows||5,i=r.cols||5;return e==null?t=Math.min(n,i):Math.min(n,i)===r.rows?r.rows=e:r.cols=e,t},Gf=(r,e)=>{let t;const n=r.rows||5,i=r.cols||5;return e==null?t=Math.max(n,i):Math.max(n,i)===r.rows?r.rows=e:r.cols=e,t},yp=(r,e)=>r[`c-${e.row}-${e.col}`]||!1,nx=(r,e)=>r[`c-${e.row}-${e.col}`]=!0,rx=(r,e)=>{const t=r.cols||5;e.col++,e.col>=t&&(e.col=0,e.row++)},IN=(r,e,t,n,i,a,s,o)=>{let l,c;const h=i[r.id];if(h)l=h.col*t+t/2+e[0],c=h.row*n+n/2+e[1];else{for(;yp(o,s);)rx(a,s);l=s.col*t+t/2+e[0],c=s.row*n+n/2+e[1],nx(o,s),rx(a,s)}r.data.x=l,r.data.y=c},NN=(r,e,t)=>{try{const n=Mo.mul(Mo.pow(e,2),-.5),i=n.mean("row"),a=n.mean("column"),s=n.mean();n.add(s).subRowVector(i).subColumnVector(a);const o=new FE(n),l=Mo.sqrt(o.diagonalMatrix).diagonal();return 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hx(Object.assign(sx(r),{distSquare:(n,i)=>Mp(r.x1,r.y1,r.x2,r.y2,n,i)}),e,t)}function hx(r,e,t){const n=cx(r,t),i=e.scale(n),a=e.createSub(i,n);return dB(a,e,t,(s,o)=>r.distSquare(s,o)),a}function dB(r,e,t,n){const i=t*t;for(let a=0;a<r.height;a++)for(let s=0;s<r.width;s++){const o=e.invertScaleX(r.i+s),l=e.invertScaleY(r.j+a),c=n(o,l);if(c===0){r.set(s,a,i);continue}if(c<i){const h=t-Math.sqrt(c);r.set(s,a,h*h)}}return r}function vB(r,e,t){const n=e.scale(r),i=e.addPadding(n,t),a=e.createSub(i,{x:r.x-t,y:r.y-t}),s=n.x-i.x,o=n.y-i.y,l=i.x2-n.x2,c=i.y2-n.y2,h=i.width-s-l,p=i.height-o-c,C=t*t;a.fillArea({x:s,y:o,width:h+1,height:p+1},C);const k=[0],W=Math.max(o,s,l,c);{const ee=e.invertScaleX(n.x+n.width/2);for(let re=1;re<W;re++){const ve=e.invertScaleY(n.y-re),he=r.distSquare(ee,ve);if(he<C){const pe=t-Math.sqrt(he);k.push(pe*pe)}else break}}const j=[],K=Math.max(s,l),Q=Math.max(o,l);for(let ee=1;ee<K;ee++){const re=e.invertScaleX(n.x-ee),ve=[];for(let he=1;he<Q;he++){const pe=e.invertScaleY(n.y-he),ye=r.distSquare(re,pe);if(ye<C){const _e=t-Math.sqrt(ye);ve.push(_e*_e)}else ve.push(0)}j.push(ve)}for(let ee=1;ee<Math.min(o,k.length);ee++){const re=k[ee];a.fillHorizontalLine(s,o-ee,h+1,re)}for(let ee=1;ee<Math.min(c,k.length);ee++){const re=k[ee];a.fillHorizontalLine(s,o+p+ee,h+1,re)}for(let ee=1;ee<Math.min(s,k.length);ee++){const re=k[ee];a.fillVerticalLine(s-ee,o,p+1,re)}for(let ee=1;ee<Math.min(c,k.length);ee++){const re=k[ee];a.fillVerticalLine(s+h+ee,o,p+1,re)}for(let ee=1;ee<s;ee++){const re=j[ee-1],ve=s-ee;for(let he=1;he<o;he++)a.set(ve,o-he,re[he-1]);for(let he=1;he<c;he++)a.set(ve,o+p+he,re[he-1])}for(let ee=1;ee<l;ee++){const re=j[ee-1],ve=s+h+ee;for(let he=1;he<o;he++)a.set(ve,o-he,re[he-1]);for(let he=1;he<c;he++)a.set(ve,o+p+he,re[he-1])}return a}function ZU(r,e,t,n){return{x:r,y:e,width:t,height:n}}function KU(r,e,t){return{cx:r,cy:e,radius:t}}function XU(r,e,t,n){return{x1:r,y1:e,x2:t,y2:n}}function Vr(r,e){return{x:r,y:e}}function gB(r,e,t,n){if(r.length===0)return[];const i=EB(r);return i.map((a,s)=>{const o=i.slice(0,s);return pB(e,a,o,t,n)}).flat()}function pB(r,e,t,n,i){const a=Vr(e.cx,e.cy),s=_B(a,t,r);if(s==null)return[];const o=new Ci(a.x,a.y,s.cx,s.cy),l=mB(o,r,n,i);return yB(l,r)}function mB(r,e,t,n){const i=[],a=[];a.push(r);let s=!0;for(let o=0;o<t&&s;o++)for(s=!1;!s&&a.length>0;){const l=a.pop(),c=fx(e,l),h=c?hB(l,c):null;if(!c||!h||h.count!==2){s||i.push(l);continue}let p=n,C=qf(c,p,h,!0),k=Ao(C,a)||Ao(C,i),W=Jf(C,e);for(;!k&&W&&p>=1;)p/=1.5,C=qf(c,p,h,!0),k=Ao(C,a)||Ao(C,i),W=Jf(C,e);if(C&&!k&&!W&&(a.push(new Ci(l.x1,l.y1,C.x,C.y)),a.push(new Ci(C.x,C.y,l.x2,l.y2)),s=!0),s)continue;p=n,C=qf(c,p,h,!1);let j=Ao(C,a)||Ao(C,i);for(W=Jf(C,e);!j&&W&&p>=1;)p/=1.5,C=qf(c,p,h,!1),j=Ao(C,a)||Ao(C,i),W=Jf(C,e);C&&!j&&(a.push(new Ci(l.x1,l.y1,C.x,C.y)),a.push(new Ci(C.x,C.y,l.x2,l.y2)),s=!0),s||i.push(l)}for(;a.length>0;)i.push(a.pop());return i}function yB(r,e){const t=[];for(;r.length>0;){const n=r.pop();if(r.length===0){t.push(n);break}const i=r.pop(),a=new Ci(n.x1,n.y1,i.x2,i.y2);fx(e,a)?(t.push(n),r.push(i)):r.push(a)}return t}function _B(r,e,t){let n=Number.POSITIVE_INFINITY;return e.reduce((i,a)=>{const s=To(r.x,r.y,a.cx,a.cy);if(s>n)return i;const o=new Ci(r.x,r.y,a.cx,a.cy),l=xB(t,o);return s*(l+1)*(l+1)<n&&(i=a,n=s*(l+1)*(l+1)),i},null)}function EB(r){if(r.length<2)return r;let e=0,t=0;return r.forEach(n=>{e+=n.cx,t+=n.cy}),e/=r.length,t/=r.length,r.map(n=>{const i=e-n.cx,a=t-n.cy,s=i*i+a*a;return[n,s]}).sort((n,i)=>n[1]-i[1]).map(n=>n[0])}function Jf(r,e){return e.some(t=>t.containsPt(r.x,r.y))}function Ao(r,e){return e.some(t=>!!(ax(t.x1,t.y1,r.x,r.y,.001)||ax(t.x2,t.y2,r.x,r.y,.001)))}function fx(r,e){let t=Number.POSITIVE_INFINITY,n=null;for(const i of r){if(!lx(i,e))continue;const a=uB(i,e);a>=0&&a<t&&(n=i,t=a)}return n}function xB(r,e){return r.reduce((t,n)=>lx(n,e)&&cB(n,e)?t+1:t,0)}function qf(r,e,t,n){const i=t.top,a=t.left,s=t.bottom,o=t.right;if(n){if(a.state===$r.POINT){if(i.state===$r.POINT)return Vr(r.x-e,r.y-e);if(s.state===$r.POINT)return Vr(r.x-e,r.y2+e);const C=r.width*r.height;return r.width*((a.y-r.y+(o.y-r.y))*.5)<C*.5?a.y>o.y?Vr(r.x-e,r.y-e):Vr(r.x2+e,r.y-e):a.y<o.y?Vr(r.x-e,r.y2+e):Vr(r.x2+e,r.y2+e)}if(o.state===$r.POINT){if(i.state===$r.POINT)return Vr(r.x2+e,r.y-e);if(s.state===$r.POINT)return Vr(r.x2+e,r.y2+e)}const h=r.height*r.width;return r.height*((i.x-r.x+(o.x-r.x))*.5)<h*.5?i.x>s.x?Vr(r.x-e,r.y-e):Vr(r.x-e,r.y2+e):i.x<s.x?Vr(r.x2+e,r.y-e):Vr(r.x2+e,r.y2+e)}if(a.state===$r.POINT){if(i.state===$r.POINT)return Vr(r.x2+e,r.y2+e);if(s.state===$r.POINT)return Vr(r.x2+e,r.y-e);const h=r.height*r.width;return r.width*((a.y-r.y+(o.y-r.y))*.5)<h*.5?a.y>o.y?Vr(r.x2+e,r.y2+e):Vr(r.x-e,r.y2+e):a.y<o.y?Vr(r.x2+e,r.y-e):Vr(r.x-e,r.y-e)}if(o.state===$r.POINT){if(i.state===$r.POINT)return Vr(r.x-e,r.y2+e);if(s.state===$r.POINT)return Vr(r.x-e,r.y-e)}const l=r.height*r.width;return r.height*((i.x-r.x+(o.x-r.x))*.5)<l*.5?i.x>s.x?Vr(r.x2+e,r.y2+e):Vr(r.x2+e,r.y-e):i.x<s.x?Vr(r.x-e,r.y2+e):Vr(r.x-e,r.y-e)}function bB(r,e,t,n){if(!(r.closed?t<r.length:t<r.length-1))return!1;const a=r.get(e),s=r.get(t+1);for(let o=e+1;o<=t;o++){const l=r.get(o);if(Mp(a.x,a.y,s.x,s.y,l.x,l.y)>n)return!1}return!0}function wB(r=0){return e=>{if(r<0||e.length<3)return e;const t=[];let n=0;const i=r*r;for(;n<e.length;){let a=n+1;for(;bB(e,n,a,i);)a++;t.push(e.get(n)),n=a}return new ml(t)}}function MB(r,e){switch(r){case-2:return(((-e+3)*e-3)*e+1)/6;case-1:return((3*e-6)*e*e+4)/6;case 0:return(((-3*e+3)*e+3)*e+1)/6;case 1:return e*e*e/6;default:throw new Error("unknown error")}}function SB(r=6){function a(s,o,l){let c=0,h=0;for(let p=-2;p<=1;p++){const C=s.get(o+p),k=MB(p,l);c+=k*C.x,h+=k*C.y}return{x:c,y:h}}return s=>{if(s.length<3)return s;const o=[],l=s.closed,c=s.length+3-1+(l?0:2);o.push(a(s,2-(l?0:2),0));for(let h=2-(l?0:2);h<c;h++)for(let p=1;p<=r;p++)o.push(a(s,h,p/r));return new ml(o)}}function TB(r=8){return e=>{let t=r,n=e.length;if(t>1)for(n=Math.floor(e.length/t);n<3&&t>1;)t-=1,n=Math.floor(e.length/t);const i=[];for(let a=0,s=0;s<n;s++,a+=t)i.push(e.get(a));return new ml(i)}}class ml{constructor(e=[],t=!0){this.points=e,this.closed=t}get(e){const t=e,n=this.points.length;return e<0?this.closed?this.get(e+n):this.points[0]:e>=n?this.closed?this.get(e-n):this.points[n-1]:this.points[t]}get length(){return this.points.length}toString(e=1/0){const t=this.points;if(t.length===0)return"";const n=typeof e=="function"?e:lB(e);let i="M";for(const a of t)i+=`${n(a.x)},${n(a.y)} L`;return i=i.slice(0,-1),this.closed&&(i+=" Z"),i}draw(e){const t=this.points;if(t.length!==0){e.beginPath(),e.moveTo(t[0].x,t[0].y);for(const n of t)e.lineTo(n.x,n.y);this.closed&&e.closePath()}}sample(e){return TB(e)(this)}simplify(e){return wB(e)(this)}bSplines(e){return SB(e)(this)}apply(e){return e(this)}containsElements(e){const t=fB(this.points);return t?e.every(n=>t.containsPt(n.cx,n.cy)&&this.withinArea(n.cx,n.cy)):!1}withinArea(e,t){if(this.length===0)return!1;let n=0;const i=this.points[0],a=new Ci(i.x,i.y,i.x,i.y);for(let s=1;s<this.points.length;s++){const o=this.points[s];a.x1=a.x2,a.y1=a.y2,a.x2=o.x,a.y2=o.y,a.cuts(e,t)&&n++}return a.x1=a.x2,a.y1=a.y2,a.x2=i.x,a.y2=i.y,a.cuts(e,t)&&n++,n%2===1}}class AB{constructor(e=0){this.count=0,this.arr=[],this.set=new Set,this.arr.length=e}add(e){this.set.add(`${e.x}x${e.y}`),this.arr[this.count++]=e}contains(e){return this.set.has(`${e.x}x${e.y}`)}isFirst(e){if(this.count===0)return!1;const t=this.arr[0];return t!=null&&t.x===e.x&&t.y===e.y}path(){return new ml(this.arr.slice(0,this.count))}clear(){this.set.clear(),this.count=0}get(e){return this.arr[e]}get length(){return this.count}}const hu=0,$f=1,ed=2,Tp=3;function CB(r,e){const t=(Math.floor(r.width)+Math.floor(r.height))*2,n=new AB(t);function i(l,c,h,p){const C=r.get(l,c);return Number.isNaN(C)?Number.NaN:C>e?h+p:h}function a(l,c){let h=hu;return h=i(l,c,h,1),h=i(l+1,c,h,2),h=i(l,c+1,h,4),h=i(l+1,c+1,h,8),Number.isNaN(h)?-1:h}let s=$f;function o(l,c){let h=l,p=c,C=r.invertScaleX(h),k=r.invertScaleY(p);for(let W=0;W<r.width*r.height;W++){const j={x:C,y:k};if(n.contains(j)){if(n.isFirst(j))return!0}else n.add(j);const K=a(h,p);switch(K){case-1:return!0;case 0:case 3:case 2:case 7:s=ed;break;case 12:case 14:case 4:s=Tp;break;case 6:s=s===hu?Tp:ed;break;case 1:case 13:case 5:s=hu;break;case 9:s=s===ed?hu:$f;break;case 10:case 8:case 11:s=$f;break;default:return console.warn("Marching squares invalid state: "+K),!0}switch(s){case hu:p--,k-=r.pixelGroup;break;case $f:p++,k+=r.pixelGroup;break;case Tp:h--,C-=r.pixelGroup;break;case ed:h++,C+=r.pixelGroup;break;default:return console.warn("Marching squares invalid state: "+K),!0}}return!0}for(let l=0;l<r.width;l++)for(let c=0;c<r.height;c++){if(r.get(l,c)<=e)continue;const h=a(l,c);if(!(h<0||h===15)&&o(l,c))return n.path()}return null}const td={maxRoutingIterations:100,maxMarchingIterations:20,pixelGroup:4,edgeR0:10,edgeR1:20,nodeR0:15,nodeR1:50,morphBuffer:10,threshold:1,memberInfluenceFactor:1,edgeInfluenceFactor:1,nonMemberInfluenceFactor:-.8,virtualEdges:!0};function fu(r){return r!=null&&typeof r.radius=="number"}function dx(r,e){if(fu(r)!==fu(e))return!1;if(fu(r)){const n=e;return r.cx===n.cx&&r.cy===n.cy&&r.radius===n.radius}const t=e;return r.x===t.x&&r.y===t.y&&r.width===t.width&&r.height===t.height}var ds;(function(r){r[r.MEMBERS=0]="MEMBERS",r[r.NON_MEMBERS=1]="NON_MEMBERS",r[r.EDGES=2]="EDGES"})(ds||(ds={}));class Ap{constructor(e={}){this.dirty=new Set,this.members=[],this.nonMembers=[],this.virtualEdges=[],this.edges=[],this.activeRegion=new Xi(0,0,0,0),this.potentialArea=new pl(1,0,0,0,0,0,0),this.o=Object.assign({},td,e)}pushMember(...e){if(e.length!==0){this.dirty.add(ds.MEMBERS);for(const t of e)this.members.push({raw:t,obj:fu(t)?Qf.from(t):Xi.from(t),area:null})}}removeMember(e){const t=this.members.findIndex(n=>dx(n.raw,e));return t<0?!1:(this.members.splice(t,1),this.dirty.add(ds.MEMBERS),!0)}removeNonMember(e){const t=this.nonMembers.findIndex(n=>dx(n.raw,e));return t<0?!1:(this.nonMembers.splice(t,1),this.dirty.add(ds.NON_MEMBERS),!0)}removeEdge(e){const t=this.edges.findIndex(n=>n.obj.equals(e));return t<0?!1:(this.edges.splice(t,1),this.dirty.add(ds.NON_MEMBERS),!0)}pushNonMember(...e){if(e.length!==0){this.dirty.add(ds.NON_MEMBERS);for(const t of e)this.nonMembers.push({raw:t,obj:fu(t)?Qf.from(t):Xi.from(t),area:null})}}pushEdge(...e){if(e.length!==0){this.dirty.add(ds.EDGES);for(const t of e)this.edges.push({raw:t,obj:Ci.from(t),area:null})}}update(){const e=this.dirty.has(ds.MEMBERS),t=this.dirty.has(ds.NON_MEMBERS);let n=this.dirty.has(ds.EDGES);this.dirty.clear();const i=this.members.map(c=>c.obj);if(this.o.virtualEdges&&(e||t)){const c=this.nonMembers.map(C=>C.obj),h=gB(i,c,this.o.maxRoutingIterations,this.o.morphBuffer),p=new Map(this.virtualEdges.map(C=>[C.obj.toString(),C.area]));this.virtualEdges=h.map(C=>{var k;return{raw:C,obj:C,area:(k=p.get(C.toString()))!==null&&k!==void 0?k:null}}),n=!0}let a=!1;if(e||n){const c=this.virtualEdges.concat(this.edges).map(k=>k.obj),h=PB(i,c),p=Math.max(this.o.edgeR1,this.o.nodeR1)+this.o.morphBuffer,C=Xi.from(cx(h,p));C.equals(this.activeRegion)||(a=!0,this.activeRegion=C)}if(a){const c=Math.ceil(this.activeRegion.width/this.o.pixelGroup),h=Math.ceil(this.activeRegion.height/this.o.pixelGroup);this.activeRegion.x!==this.potentialArea.pixelX||this.activeRegion.y!==this.potentialArea.pixelY?(this.potentialArea=pl.fromPixelRegion(this.activeRegion,this.o.pixelGroup),this.members.forEach(p=>p.area=null),this.nonMembers.forEach(p=>p.area=null),this.edges.forEach(p=>p.area=null),this.virtualEdges.forEach(p=>p.area=null)):(c!==this.potentialArea.width||h!==this.potentialArea.height)&&(this.potentialArea=pl.fromPixelRegion(this.activeRegion,this.o.pixelGroup))}const s=new Map,o=c=>{if(c.area){const h=`${c.obj.width}x${c.obj.height}x${c.obj instanceof Xi?"R":"C"}`;s.set(h,c.area)}},l=c=>{if(c.area)return;const h=`${c.obj.width}x${c.obj.height}x${c.obj instanceof Xi?"R":"C"}`;if(s.has(h)){const C=s.get(h);c.area=this.potentialArea.copy(C,{x:c.obj.x-this.o.nodeR1,y:c.obj.y-this.o.nodeR1});return}const p=c.obj instanceof Xi?vB(c.obj,this.potentialArea,this.o.nodeR1):hx(c.obj,this.potentialArea,this.o.nodeR1);c.area=p,s.set(h,p)};this.members.forEach(o),this.nonMembers.forEach(o),this.members.forEach(l),this.nonMembers.forEach(c=>{this.activeRegion.intersects(c.obj)?l(c):c.area=null}),this.edges.forEach(c=>{c.area||(c.area=ux(c.obj,this.potentialArea,this.o.edgeR1))}),this.virtualEdges.forEach(c=>{c.area||(c.area=ux(c.obj,this.potentialArea,this.o.edgeR1))})}drawMembers(e){for(const t of this.members)t.obj.draw(e)}drawNonMembers(e){for(const t of this.nonMembers)t.obj.draw(e)}drawEdges(e){for(const t of this.edges)t.obj.draw(e)}drawPotentialArea(e,t=!0){this.potentialArea.draw(e,t)}compute(){if(this.members.length===0)return new ml([]);this.dirty.size>0&&this.update();const{o:e,potentialArea:t}=this,n=this.members.map(o=>o.area),i=this.virtualEdges.concat(this.edges).map(o=>o.area),a=this.nonMembers.filter(o=>o.area!=null).map(o=>o.area),s=this.members.map(o=>o.obj);return OB(t,n,i,a,o=>o.containsElements(s),e)}}function OB(r,e,t,n,i,a={}){const s=Object.assign({},td,a);let o=s.threshold,l=s.memberInfluenceFactor,c=s.edgeInfluenceFactor,h=s.nonMemberInfluenceFactor;const p=(s.nodeR0-s.nodeR1)*(s.nodeR0-s.nodeR1),C=(s.edgeR0-s.edgeR1)*(s.edgeR0-s.edgeR1);for(let k=0;k<s.maxMarchingIterations;k++){if(r.clear(),l!==0){const j=l/p;for(const K of e)r.incArea(K,j)}if(c!==0){const j=c/C;for(const K of t)r.incArea(K,j)}if(h!==0){const j=h/p;for(const K of n)r.incArea(K,j)}const W=CB(r,o);if(W&&i(W))return W;if(o*=.95,k<=s.maxMarchingIterations*.5)l*=1.2,c*=1.2;else if(h!==0&&n.length>0)h*=.8;else break}return new ml([])}function PB(r,e){if(r.length===0)return new Xi(0,0,0,0);const t=Xi.from(r[0]);for(const n of r)t.add(n);for(const n of e)t.add(sx(n));return t}function YU(r,e=[],t=[],n={}){if(r.length===0)return new ml([]);const i=new Ap(n);return i.pushMember(...r),i.pushNonMember(...e),i.pushEdge(...t),i.compute()}var DB=function(r,e){var t={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&e.indexOf(n)<0&&(t[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var i=0,n=Object.getOwnPropertySymbols(r);i<n.length;i++)e.indexOf(n[i])<0&&Object.prototype.propertyIsEnumerable.call(r,n[i])&&(t[n[i]]=r[n[i]]);return t};class nd extends ki{constructor(e,t){super(e,ia({},nd.defaultOptions,t)),this.members=new Map,this.avoidMembers=new Map,this.bubbleSetOptions={},this.drawBubbleSets=()=>{const{style:n,bubbleSetOptions:i}=this.parseOptions();si(this.bubbleSetOptions,i)||this.init(),this.bubbleSetOptions=Object.assign({},i);const a=Object.assign(Object.assign({},n),{d:this.getPath()});this.shape?this.shape.update(a):(this.shape=new qc({style:a}),this.context.canvas.appendChild(this.shape))},this.updateBubbleSetsPath=n=>{if(!this.shape)return;const i=wt(n.data);[...this.options.members,...this.options.avoidMembers].includes(i)&&this.shape.update(Object.assign(Object.assign({},this.parseOptions().style),{d:this.getPath(i)}))},this.getPath=n=>{const{graph:i}=this.context,a=this.options.members,s=[...this.members.keys()],o=this.options.avoidMembers,l=[...this.avoidMembers.keys()];if(!n&&si(a,s)&&si(o,l))return this.path;const{enter:c=[],exit:h=[]}=po(s,a,K=>K),{enter:p=[],exit:C=[]}=po(l,o,K=>K);n&&(h.push(n),c.push(n));const k=(K,Q,ee)=>{K.forEach(re=>{const ve=ee?this.members:this.avoidMembers,he=ee?"pushMember":"pushNonMember",pe=ee?"removeMember":"removeNonMember";if(Q){let ye;i.getElementType(re)==="edge"?([ye]=RB(i,re),this.bubbleSets.pushEdge(ye)):([ye]=LB(i,re),this.bubbleSets[he](ye)),ve.set(re,ye)}else{const ye=ve.get(re);ye&&(i.getElementType(re)==="edge"?this.bubbleSets.removeEdge(ye):this.bubbleSets[pe](ye),ve.delete(re))}})};k(h,!1,!0),k(c,!0,!0),k(C,!1,!1),k(p,!0,!1);const j=this.bubbleSets.compute().sample(8).simplify(0).bSplines().simplify(0);return this.path=i_(j.points.map(Ni)),this.path},this.bindEvents(),this.bubbleSets=new Ap(this.options)}bindEvents(){this.context.graph.on($t.AFTER_RENDER,this.drawBubbleSets),this.context.graph.on($t.AFTER_ELEMENT_UPDATE,this.updateBubbleSetsPath)}init(){this.bubbleSets=new Ap(this.options),this.members=new Map,this.avoidMembers=new Map}parseOptions(){const e=this.options,{type:t,key:n,members:i,avoidMembers:a}=e,s=DB(e,["type","key","members","avoidMembers"]),o=Object.keys(s).reduce((l,c)=>(c in td?l.bubbleSetOptions[c]=s[c]:l.style[c]=s[c],l),{style:{},bubbleSetOptions:{}});return Object.assign({type:t,key:n,members:i,avoidMembers:a},o)}addMember(e){const t=Array.isArray(e)?e:[e];t.some(n=>this.options.avoidMembers.includes(n))&&(this.options.avoidMembers=this.options.avoidMembers.filter(n=>!t.includes(n))),this.options.members=[...new Set([...this.options.members,...t])],this.drawBubbleSets()}removeMember(e){const t=Array.isArray(e)?e:[e];this.options.members=this.options.members.filter(n=>!t.includes(n)),this.drawBubbleSets()}updateMember(e){this.options.members=En(e)?e(this.options.members):e,this.drawBubbleSets()}getMember(){return this.options.members}addAvoidMember(e){const t=Array.isArray(e)?e:[e];t.some(n=>this.options.members.includes(n))&&(this.options.members=this.options.members.filter(n=>!t.includes(n))),this.options.avoidMembers=[...new Set([...this.options.avoidMembers,...t])],this.drawBubbleSets()}removeAvoidMember(e){const t=Array.isArray(e)?e:[e];this.options.avoidMembers.some(n=>t.includes(n))&&(this.options.avoidMembers=this.options.avoidMembers.filter(n=>!t.includes(n)),this.drawBubbleSets())}updateAvoidMember(e){this.options.avoidMembers=Array.isArray(e)?e:[e],this.drawBubbleSets()}getAvoidMember(){return this.options.avoidMembers}destroy(){this.context.graph.off($t.AFTER_RENDER,this.drawBubbleSets),this.context.graph.off($t.AFTER_ELEMENT_UPDATE,this.updateBubbleSetsPath),this.shape.destroy(),super.destroy()}}nd.defaultOptions=Object.assign({members:[],avoidMembers:[],fill:"lightblue",fillOpacity:.2,stroke:"blue",strokeOpacity:.2},td);const LB=(r,e)=>(Array.isArray(e)?e:[e]).map(n=>{const i=r.getElementRenderBounds(n);return new Xi(i.min[0],i.min[1],Os(i),Ps(i))}),RB=(r,e)=>(Array.isArray(e)?e:[e]).map(n=>{const i=r.getEdgeData(n),a=r.getElementPosition(i.source),s=r.getElementPosition(i.target);return Ci.from({x1:a[0],y1:a[1],x2:s[0],y2:s[1]})});class QU extends null{constructor(e,t){super(e,t),this.setOptions=n=>{const i={cameraType:"setType",near:"setNear",far:"setFar",fov:"setFov",aspect:"setAspect",projectionMode:"setProjectionMode",distance:"setDistance",minDistance:"setMinDistance",maxDistance:"setMaxDistance",roll:"setRoll",elevation:"setElevation",azimuth:"setAzimuth"},a=(s,o)=>{switch(s){case"projectionMode":return o==="perspective"?1:0;case"cameraType":return{orbiting:0,exploring:1,tracking:2}[o];case"aspect":return typeof o=="number"?o:this.getCanvasAspect();default:return o}};Object.entries(i).forEach(([s,o])=>{const l=n[s];if(l!==void 0){const c=a(s,l);this.context.canvas.getCamera()[o](c)}})},this.bindEvents()}update(e){this.setOptions(e),super.update(e)}bindEvents(){this.context.graph.once(GraphEvent.BEFORE_DRAW,()=>this.setOptions(this.options))}getCanvasAspect(){const[e,t]=this.context.viewport.getCanvasSize();return e/t}}function IB(r){return`
     <ul class="g6-contextmenu-ul">
       ${r.map(e=>`<li  class="g6-contextmenu-li" value="${e.value}">${e.name}</li>`).join("")}
@@ -121,7 +121,7 @@ YYYY`):ca(t,"MM\u6708");case"year":return ca(t,"YYYY");default:return ca(t,"YYYY
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         </span>
         <span class="`).concat(o.VALUE,`" title="{value}">{value}</span>
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h0(x8(i.item,k))})},enumerable:!1,configurable:!0}),e.prototype.render=function(t,n){this.renderHTMLTooltipElement(),this.updatePosition()},e.prototype.destroy=function(){var t;(t=this.element)===null||t===void 0||t.remove(),r.prototype.destroy.call(this)},e.prototype.show=function(t,n){var i=this;if(t!==void 0&&n!==void 0){var a=this.element.style.visibility==="hidden",s=function(){i.attributes.x=t!=null?t:i.attributes.x,i.attributes.y=n!=null?n:i.attributes.y,i.updatePosition()};a?this.closeTransition(s):s()}this.element.style.visibility="visible"},e.prototype.hide=function(t,n){t===void 0&&(t=0),n===void 0&&(n=0);var i=this.attributes.enterable;i&&this.isCursorEntered(t,n)||(this.element.style.visibility="hidden")},e.prototype.initShape=function(){var t=this.attributes.template;this.element=h0(t.container),this.id&&this.element.setAttribute("id",this.id)},e.prototype.renderCustomContent=function(){if(!(this.prevCustomContentKey!==void 0&&this.prevCustomContentKey===this.attributes.contentKey)){this.prevCustomContentKey=this.attributes.contentKey;var t=this.attributes.content;t&&(typeof t=="string"?this.element.innerHTML=t:zb(this.element,t))}},e.prototype.renderHTMLTooltipElement=function(){var t,n,i=this.attributes,a=i.template,s=i.title,o=i.enterable,l=i.style,c=i.content,h=f0(a.prefixCls),p=this.element;if(this.element.style.pointerEvents=o?"auto":"none",c)this.renderCustomContent();else{s?(p.innerHTML=a.title,p.getElementsByClassName(h.TITLE)[0].innerHTML=s):(n=(t=p.getElementsByClassName(h.TITLE))===null||t===void 0?void 0:t[0])===null||n===void 0||n.remove();var C=this.HTMLTooltipItemsElements,k=document.createElement("ul");k.className=h.LIST,zb(k,C);var W=this.element.querySelector(".".concat(h.LIST));W?W.replaceWith(k):p.appendChild(k)}a5(p,l)},e.prototype.getRelativeOffsetFromCursor=function(t){var n=this.attributes,i=n.position,a=n.offset,s=t||i,o=s.split("-"),l={left:[-1,0],right:[1,0],top:[0,-1],bottom:[0,1]},c=this.elementSize,h=c.width,p=c.height,C=[-h/2,-p/2];return o.forEach(function(k){var W=(0,we.CR)(C,2),j=W[0],K=W[1],Q=(0,we.CR)(l[k],2),ee=Q[0],re=Q[1];C=[j+(h/2+a[0])*ee,K+(p/2+a[1])*re]}),C},e.prototype.setOffsetPosition=function(t){var n=(0,we.CR)(t,2),i=n[0],a=n[1],s=this.attributes,o=s.x,l=o===void 0?0:o,c=s.y,h=c===void 0?0:c,p=s.container,C=p.x,k=p.y;this.element.style.left="".concat(+l+C+i,"px"),this.element.style.top="".concat(+h+k+a,"px")},e.prototype.updatePosition=function(){var t=this.attributes.showDelay,n=t===void 0?60:t,i=Date.now();this.timestamp>0&&i-this.timestamp<n||(this.timestamp=i,this.setOffsetPosition(this.autoPosition(this.getRelativeOffsetFromCursor())))},e.prototype.autoPosition=function(t){var n=(0,we.CR)(t,2),i=n[0],a=n[1],s=this.attributes,o=s.x,l=s.y,c=s.bounding,h=s.position;if(!c)return[i,a];var p=this.element,C=p.offsetWidth,k=p.offsetHeight,W=(0,we.CR)([+o+i,+l+a],2),j=W[0],K=W[1],Q={left:"right",right:"left",top:"bottom",bottom:"top"},ee=c.x,re=c.y,ve=c.width,he=c.height,pe={left:j<ee,right:j+C>ee+ve,top:K<re,bottom:K+k>re+he},ye=[];h.split("-").forEach(function(De){pe[De]?ye.push(Q[De]):ye.push(De)});var _e=ye.join("-");return this.getRelativeOffsetFromCursor(_e)},e.prototype.isCursorEntered=function(t,n){if(this.element){var i=this.element.getBoundingClientRect(),a=i.x,s=i.y,o=i.width,l=i.height;return new Yi(a,s,o,l).isPointIn(t,n)}return!1},e.prototype.closeTransition=function(t){var n=this,i=this.element.style.transition;this.element.style.transition="none",t(),setTimeout(function(){n.element.style.transition=i},10)},e.tag="tooltip",e}(ti),Ub=function(r,e,t,n){function i(a){return a instanceof t?a:new t(function(s){s(a)})}return new(t||(t=Promise))(function(a,s){function o(h){try{c(n.next(h))}catch(p){s(p)}}function l(h){try{c(n.throw(h))}catch(p){s(p)}}function c(h){h.done?a(h.value):i(h.value).then(o,l)}c((n=n.apply(r,e||[])).next())})};class Pd extends ki{constructor(e,t){super(e,Object.assign({},Pd.defaultOptions,t)),this.currentTarget=null,this.tooltipElement=null,this.container=null,this.isEnable=(n,i)=>{const{enable:a}=this.options;return typeof a=="function"?a(n,i):a},this.onClick=n=>{const{target:{id:i}}=n;this.currentTarget===i?this.hide(n):this.show(n)},this.onPointerMove=n=>{const{target:i}=n;!this.currentTarget||i.id===this.currentTarget||this.show(n)},this.onPointerLeave=n=>{this.hide(n)},this.onCanvasMove=n=>{this.hide(n)},this.onPointerEnter=n=>{this.show(n)},this.showById=n=>Ub(this,void 0,void 0,function*(){const i={target:{id:n}};yield this.show(i)}),this.getElementData=(n,i)=>{const{model:a}=this.context;switch(i){case"node":return a.getNodeData([n]);case"edge":return a.getEdgeData([n]);case"combo":return a.getComboData([n]);default:return[]}},this.show=n=>Ub(this,void 0,void 0,function*(){var i,a;const{client:s,target:{id:o}}=n;if(_f(n.target))return;const l=this.context.graph.getElementType(o),{getContent:c,title:h}=this.options,p=this.getElementData(o,l);if(!this.tooltipElement||!this.isEnable(n,p))return;let C={};if(c){if(C.content=yield c(n,p),!C.content)return}else{const j=this.context.graph.getElementRenderStyle(o),K=l==="node"?j.fill:j.stroke;C={title:h||l,data:p.map(Q=>({name:"ID",value:Q.id||`${Q.source} -> ${Q.target}`,color:K}))}}this.currentTarget=o;let k,W;if(s)k=s.x,W=s.y;else{const j=aa(p,"0.style",{x:0,y:0});k=j.x,W=j.y}(a=(i=this.options).onOpenChange)===null||a===void 0||a.call(i,!0),this.tooltipElement.update(Object.assign(Object.assign(Object.assign({},this.tooltipStyleProps),{x:k,y:W,style:{".tooltip":{visibility:"visible"}}}),C))}),this.hide=n=>{var i,a,s,o,l;if(!n){(a=(i=this.options).onOpenChange)===null||a===void 0||a.call(i,!1),(s=this.tooltipElement)===null||s===void 0||s.hide(),this.currentTarget=null;return}if(!this.tooltipElement||!this.currentTarget)return;const{client:{x:c,y:h}}=n;(l=(o=this.options).onOpenChange)===null||l===void 0||l.call(o,!1),this.tooltipElement.hide(c,h),this.currentTarget=null},this.initTooltip=()=>{var n;const i=new w8({className:"tooltip",style:this.tooltipStyleProps});return(n=this.container)===null||n===void 0||n.appendChild(i.HTMLTooltipElement),i},this.render(),this.bindEvents()}getEvents(){return this.options.trigger==="click"?{"node:click":this.onClick,"edge:click":this.onClick,"combo:click":this.onClick,"canvas:click":this.onPointerLeave,contextmenu:this.onPointerLeave,drag:this.onPointerLeave}:{"node:pointerenter":this.onPointerEnter,"node:pointermove":this.onPointerMove,"canvas:pointermove":this.onCanvasMove,"edge:pointerenter":this.onPointerEnter,"edge:pointermove":this.onPointerMove,"combo:pointerenter":this.onPointerEnter,"combo:pointermove":this.onPointerMove,contextmenu:this.onPointerLeave,"node:drag":this.onPointerLeave}}update(e){var t;this.unbindEvents(),super.update(e),this.tooltipElement&&((t=this.container)===null||t===void 0||t.removeChild(this.tooltipElement.HTMLTooltipElement)),this.tooltipElement=this.initTooltip(),this.bindEvents()}render(){const{canvas:e}=this.context,t=e.getContainer();t&&(this.container=t,this.tooltipElement=this.initTooltip())}unbindEvents(){const{graph:e}=this.context,t=this.getEvents();Object.keys(t).forEach(n=>{e.off(n,t[n])})}bindEvents(){const{graph:e}=this.context,t=this.getEvents();Object.keys(t).forEach(n=>{e.on(n,t[n])})}get tooltipStyleProps(){const{canvas:e}=this.context,{center:t}=e.getBounds(),n=e.getContainer(),{top:i,left:a}=n.getBoundingClientRect(),{style:s,position:o,enterable:l,container:c={x:-a,y:-i},title:h,offset:p}=this.options,[C,k]=t,[W,j]=e.getSize();return{x:C,y:k,container:c,title:h,bounding:{x:0,y:0,width:W,height:j},position:o,enterable:l,offset:p,style:s}}destroy(){var e;this.unbindEvents(),this.tooltipElement&&((e=this.container)===null||e===void 0||e.removeChild(this.tooltipElement.HTMLTooltipElement)),super.destroy()}}Pd.defaultOptions={trigger:"hover",position:"top-right",enterable:!1,enable:!0,offset:[10,10],style:{".tooltip":{visibility:"hidden"}}};var Wb=function(r,e,t,n){function i(a){return a instanceof t?a:new t(function(s){s(a)})}return new(t||(t=Promise))(function(a,s){function o(h){try{c(n.next(h))}catch(p){s(p)}}function l(h){try{c(n.throw(h))}catch(p){s(p)}}function c(h){h.done?a(h.value):i(h.value).then(o,l)}c((n=n.apply(r,e||[])).next())})};let sc;function Hb(r,e){return sc||(sc=document.createElement("canvas")),sc.width=r,sc.height=e,sc.getContext("2d").clearRect(0,0,r,e),sc}function M8(r,e,t,n){return Wb(this,void 0,void 0,function*(){const i=Hb(r,e),a=i.getContext("2d"),{rotate:s,opacity:o,textFill:l,textFontSize:c,textFontFamily:h,textFontVariant:p,textFontWeight:C,textAlign:k,textBaseline:W}=n;return a.textAlign=k,a.textBaseline=W,a.translate(r/2,e/2),a.font=`${c}px ${h} ${p} 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ee=Q.length?dC(W,this.inferStyle(c,n),Q):null;return ee?((C=h==null?void 0:h.beforeAnimate)===null||C===void 0||C.call(h,ee),ee.finished.then(()=>{var re,ve;(re=h==null?void 0:h.afterAnimate)===null||re===void 0||re.call(h,ee),(ve=h==null?void 0:h.after)===null||ve===void 0||ve.call(h),this.animations.delete(ee)})):(k=h==null?void 0:h.after)===null||k===void 0||k.call(h),ee}).filter(Boolean);o.forEach(c=>this.animations.add(c));const l=ag(o);return l?((a=t==null?void 0:t.beforeAnimate)===null||a===void 0||a.call(t,l),l.finished.then(()=>{var c,h;(c=t==null?void 0:t.afterAnimate)===null||c===void 0||c.call(t,l),(h=t==null?void 0:t.after)===null||h===void 0||h.call(t),this.release()})):(s=t==null?void 0:t.after)===null||s===void 0||s.call(t),l}inferStyle(e,t){var n,i;const{element:a,elementType:s,stage:o,originalStyle:l,updatedStyle:c={}}=e;e.modifiedStyle||(e.modifiedStyle=Object.assign(Object.assign({},l),c));const{modifiedStyle:h}=e,p={},C={};if(o==="enter")Object.assign(p,{opacity:0});else if(o==="exit")Object.assign(C,{opacity:0});else if(o==="show")Object.assign(p,{opacity:0}),Object.assign(C,{opacity:(n=n2(a,"opacity"))!==null&&n!==void 0?n:Wc("opacity")});else if(o==="hide")Object.assign(p,{opacity:(i=n2(a,"opacity"))!==null&&i!==void 0?i:Wc("opacity")}),Object.assign(C,{opacity:0});else if(o==="collapse"){const{collapse:k}=t||{},{target:W,descendants:j,position:K}=k;if(s==="node"){if(j.includes(a.id)){const[Q,ee,re]=K;Object.assign(C,{x:Q,y:ee,z:re})}}else if(s==="combo"){if(a.id===W||j.includes(a.id)){const[Q,ee]=K;Object.assign(C,{x:Q,y:ee,childrenNode:l.childrenNode})}}else s==="edge"&&Object.assign(C,{sourceNode:h.sourceNode,targetNode:h.targetNode})}else if(o==="expand"){const{expand:k}=t||{},{target:W,descendants:j,position:K}=k;if(s==="node"){if(a.id===W||j.includes(a.id)){const[Q,ee,re]=K;Object.assign(p,{x:Q,y:ee,z:re})}}else if(s==="combo"){if(a.id===W||j.includes(a.id)){const[Q,ee,re]=K;Object.assign(p,{x:Q,y:ee,z:re,childrenNode:h.childrenNode})}}else s==="edge"&&Object.assign(p,{sourceNode:h.sourceNode,targetNode:h.targetNode})}return[Object.keys(p).length>0?Object.assign({},l,p):l,Object.keys(C).length>0?Object.assign({},h,C):h]}stop(){this.animations.forEach(e=>e.cancel())}clear(){this.tasks=[]}release(){var e,t;const{canvas:n}=this.context,i=(t=(e=n.document)===null||e===void 0?void 0:e.timeline)===null||t===void 0?void 0:t.animationsWithPromises;i&&(n.document.timeline.animationsWithPromises=i.filter(a=>a.playState!=="finished"))}destroy(){this.stop(),this.animations.clear(),this.tasks=[]}}class G8{constructor(e){this.batchCount=0,this.context=e}emit(e){const{graph:t}=this.context;t.emit(e.type,e)}startBatch(e=!0){this.batchCount++,this.batchCount===1&&this.emit(new mi($t.BATCH_START,{initiate:e}))}endBatch(){this.batchCount--,this.batchCount===0&&this.emit(new mi($t.BATCH_END))}get isBatching(){return this.batchCount>0}destroy(){this.context=null}}class V8 extends Eg{constructor(e){super(e),this.currentTarget=null,this.currentTargetType=null,this.category="behavior",this.forwardCanvasEvents=t=>{const{target:n}=t,i=U8(n);if(!i)return;const{graph:a,canvas:s}=this.context,{type:o,element:l}=i;if("destroyed"in l&&(_f(l)||l.destroyed))return;const{type:c,detail:h,button:p}=t,C=Object.assign(Object.assign({},t),{target:l,targetType:o,originalTarget:n});c===kt.POINTER_MOVE&&(this.currentTarget!==l&&(this.currentTarget&&a.emit(`${this.currentTargetType}:${kt.POINTER_LEAVE}`,Object.assign(Object.assign({},C),{type:kt.POINTER_LEAVE,target:this.currentTarget,targetType:this.currentTargetType})),l&&(Object.assign(C,{type:kt.POINTER_ENTER}),a.emit(`${o}:${kt.POINTER_ENTER}`,C))),this.currentTarget=l,this.currentTargetType=o),c===kt.CLICK&&p===2||(a.emit(`${o}:${c}`,C),a.emit(c,C)),c===kt.CLICK&&h===2&&(Object.assign(C,{type:kt.DBLCLICK}),a.emit(`${o}:${kt.DBLCLICK}`,C),a.emit(kt.DBLCLICK,C)),c===kt.POINTER_DOWN&&p===2&&(Object.assign(C,{type:kt.CONTEXT_MENU,preventDefault:()=>{var k;(k=s.getContainer())===null||k===void 0||k.addEventListener(kt.CONTEXT_MENU,W=>W.preventDefault(),{once:!0})}}),a.emit(`${o}:${kt.CONTEXT_MENU}`,C),a.emit(kt.CONTEXT_MENU,C))},this.forwardContainerEvents=t=>{this.context.graph.emit(t.type,t)},this.forwardEvents(),this.setBehaviors(this.context.options.behaviors||[])}setBehaviors(e){this.setExtensions(e)}forwardEvents(){const e=this.context.canvas.getContainer();e&&[Hl.KEY_DOWN,Hl.KEY_UP].forEach(n=>{e.addEventListener(n,this.forwardContainerEvents)});const t=this.context.canvas.document;t&&[kt.CLICK,kt.DBLCLICK,kt.POINTER_OVER,kt.POINTER_LEAVE,kt.POINTER_ENTER,kt.POINTER_MOVE,kt.POINTER_OUT,kt.POINTER_DOWN,kt.POINTER_UP,kt.CONTEXT_MENU,kt.DRAG_START,kt.DRAG,kt.DRAG_END,kt.DRAG_ENTER,kt.DRAG_OVER,kt.DRAG_LEAVE,kt.DROP,kt.WHEEL].forEach(n=>{t.addEventListener(n,this.forwardCanvasEvents)})}destroy(){const e=this.context.canvas.getContainer();e&&[Hl.KEY_DOWN,Hl.KEY_UP].forEach(t=>{e.removeEventListener(t,this.forwardContainerEvents)}),this.context.canvas.document.removeAllEventListeners(),super.destroy()}}function Z8(r,e){e===void 0&&(e=new Map);var t=[];if(Array.isArray(r))for(var n=0,i=r.length;n<i;n++){var a=r[n];e.has(a)||(t.push(a),e.set(a,!0))}return t}var Mu=function(r,e){var t={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&e.indexOf(n)<0&&(t[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var i=0,n=Object.getOwnPropertySymbols(r);i<n.length;i++)e.indexOf(n[i])<0&&Object.prototype.propertyIsEnumerable.call(r,n[i])&&(t[n[i]]=r[n[i]]);return t};function Lo(r,e){const{data:t,style:n}=r,i=Mu(r,["data","style"]),{data:a,style:s}=e,o=Mu(e,["data","style"]),l=Object.assign(Object.assign({},i),o);return(t||a)&&Object.assign(l,{data:Object.assign(Object.assign({},t),a)}),(n||s)&&Object.assign(l,{style:Object.assign(Object.assign({},n),s)}),l}function v0(r){const{data:e,style:t}=r,i=Mu(r,["data","style"]);return e&&(i.data=Object.assign({},e)),t&&(i.style=Object.assign({},t)),i}function PW(r){return!get(r,["nodes","length"])&&!get(r,["edges","length"])&&!get(r,["combos","length"])}function uc(r={},e={}){const{states:t=[],data:n={},style:i={},children:a=[]}=r,s=Mu(r,["states","data","style","children"]),{states:o=[],data:l={},style:c={},children:h=[]}=e,p=Mu(e,["states","data","style","children"]),C=(W,j)=>W.length!==j.length?!1:W.every((K,Q)=>K===j[Q]),k=(W,j)=>{const K=Object.keys(W),Q=Object.keys(j);return K.length!==Q.length?!1:K.every(ee=>W[ee]===j[ee])};return!(!k(s,p)||!C(a,h)||!C(t,o)||!k(n,l)||!k(i,c))}var K8=function(r,e){var t={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&e.indexOf(n)<0&&(t[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var i=0,n=Object.getOwnPropertySymbols(r);i<n.length;i++)e.indexOf(n[i])<0&&Object.prototype.propertyIsEnumerable.call(r,n[i])&&(t[n[i]]=r[n[i]]);return t};function g0(r){const{id:e=wt(r),style:t,data:n}=r,i=K8(r,["id","style","data"]),a=Object.assign(Object.assign({},r),{style:Object.assign({},t),data:Object.assign({},n)});return xC(r)?Object.assign({id:e,data:a},i):{id:e,data:a}}function Pi(r){return r.data}function X8(r){if(r.hasTreeStructure(Ca))return;r.attachTreeStructure(Ca);const e=r.getAllEdges();for(const t of e){const{source:n,target:i}=t;r.setParent(i,n,Ca)}}class Y8{constructor(){this.latestRemovedComboIds=new Set,this.comboIds=new Set,this.changes=[],this.batchCount=0,this.isTraceless=!1,this.enableUpdateNodeLikeHierarchy=!0,this.model=new ci}pushChange(e){if(this.isTraceless)return;const{type:t}=e;if(t===Gr.NodeUpdated||t===Gr.EdgeUpdated||t===Gr.ComboUpdated){const{value:n,original:i}=e;this.changes.push({value:v0(n),original:v0(i),type:t})}else this.changes.push({value:v0(e.value),type:t})}getChanges(){return this.changes}clearChanges(){this.changes=[]}batch(e){this.batchCount++,this.model.batch(e),this.batchCount--}isBatching(){return this.batchCount>0}silence(e){this.isTraceless=!0,e(),this.isTraceless=!1}isCombo(e){return this.comboIds.has(e)||this.latestRemovedComboIds.has(e)}getData(){return{nodes:this.getNodeData(),edges:this.getEdgeData(),combos:this.getComboData()}}getNodeData(e){return this.model.getAllNodes().reduce((t,n)=>{const i=Pi(n);return this.isCombo(wt(i))||(e===void 0||e.includes(wt(i)))&&t.push(i),t},[])}getEdgeDatum(e){return Pi(this.model.getEdge(e))}getEdgeData(e){return this.model.getAllEdges().reduce((t,n)=>{const i=Pi(n);return(e===void 0||e.includes(wt(i)))&&t.push(i),t},[])}getComboData(e){return this.model.getAllNodes().reduce((t,n)=>{const i=Pi(n);return this.isCombo(wt(i))&&(e===void 0||e.includes(wt(i)))&&t.push(i),t},[])}getRootsData(e=Ca){return this.model.getRoots(e).map(Pi)}getAncestorsData(e,t){const{model:n}=this;return!n.hasNode(e)||!n.hasTreeStructure(t)?[]:n.getAncestors(e,t).map(Pi)}getDescendantsData(e){const t=this.getElementDataById(e),n=[];return ol(t,i=>{i!==t&&n.push(i)},i=>this.getChildrenData(wt(i)),"TB"),n}getParentData(e,t){const{model:n}=this;if(!t){Ea.warn("The hierarchy structure key is not specified");return}if(!n.hasNode(e)||!n.hasTreeStructure(t))return;const i=n.getParent(e,t);return i?Pi(i):void 0}getChildrenData(e){const t=this.getElementType(e)==="node"?Ca:Lr,{model:n}=this;return!n.hasNode(e)||!n.hasTreeStructure(t)?[]:n.getChildren(e,t).map(Pi)}getElementsDataByType(e){return e==="node"?this.getNodeData():e==="edge"?this.getEdgeData():e==="combo"?this.getComboData():[]}getElementDataById(e){return this.getElementType(e)==="edge"?this.getEdgeDatum(e):this.getNodeLikeDatum(e)}getNodeLikeDatum(e){const t=this.model.getNode(e);return Pi(t)}getNodeLikeData(e){return this.model.getAllNodes().reduce((t,n)=>{const i=Pi(n);return e?e.includes(wt(i))&&t.push(i):t.push(i),t},[])}getElementDataByState(e,t){return this.getElementsDataByType(e).filter(i=>{var a;return(a=i.states)===null||a===void 0?void 0:a.includes(t)})}getElementState(e){var t;return((t=this.getElementDataById(e))===null||t===void 0?void 0:t.states)||[]}hasNode(e){return this.model.hasNode(e)&&!this.isCombo(e)}hasEdge(e){return this.model.hasEdge(e)}hasCombo(e){return this.model.hasNode(e)&&this.isCombo(e)}getRelatedEdgesData(e,t="both"){return this.model.getRelatedEdges(e,t).map(Pi)}getNeighborNodesData(e){return this.model.getNeighbors(e).map(Pi)}setData(e){const{nodes:t=[],edges:n=[],combos:i=[]}=e,{nodes:a,edges:s,combos:o}=this.getData(),l=po(a,t,p=>wt(p),uc),c=po(s,n,p=>wt(p),uc),h=po(o,i,p=>wt(p),uc);this.batch(()=>{const p={nodes:l.enter,edges:c.enter,combos:h.enter};this.addData(p),this.computeZIndex(p,"add",!0);const C={nodes:l.update,edges:c.update,combos:h.update};this.updateData(C),this.computeZIndex(C,"update",!0);const k={nodes:l.exit.map(wt),edges:c.exit.map(wt),combos:h.exit.map(wt)};this.removeData(k)})}addData(e){const{nodes:t,edges:n,combos:i}=e;this.batch(()=>{this.addComboData(i),this.addNodeData(t),this.addEdgeData(n)}),this.computeZIndex(e,"add")}addNodeData(e=[]){e.length&&(this.model.addNodes(e.map(t=>(this.pushChange({value:t,type:Gr.NodeAdded}),g0(t)))),this.updateNodeLikeHierarchy(e),this.computeZIndex({nodes:e},"add"))}addEdgeData(e=[]){e.length&&(this.model.addEdges(e.map(t=>(this.pushChange({value:t,type:Gr.EdgeAdded}),g0(t)))),this.computeZIndex({edges:e},"add"))}addComboData(e=[]){if(!e.length)return;const{model:t}=this;t.hasTreeStructure(Lr)||t.attachTreeStructure(Lr),t.addNodes(e.map(n=>(this.comboIds.add(wt(n)),this.pushChange({value:n,type:Gr.ComboAdded}),g0(n)))),this.updateNodeLikeHierarchy(e),this.computeZIndex({combos:e},"add")}addChildrenData(e,t){const n=this.getNodeLikeDatum(e),i=t.map(wt);this.addNodeData(t),this.updateNodeData([{id:e,children:[...n.children||[],...i]}]),this.addEdgeData(i.map(a=>({source:e,target:a})))}computeZIndex(e,t,n=!1){!n&&this.isBatching()||this.batch(()=>{const{nodes:i=[],edges:a=[],combos:s=[]}=e;s.forEach(o=>{var l,c,h;const p=wt(o);if(t==="add"&&un((l=o.style)===null||l===void 0?void 0:l.zIndex)||t==="update"&&!("combo"in o))return;const C=this.getParentData(p,Lr),k=C?((h=(c=C.style)===null||c===void 0?void 0:c.zIndex)!==null&&h!==void 0?h:0)+1:0;this.preventUpdateNodeLikeHierarchy(()=>{this.updateComboData([{id:p,style:{zIndex:k}}])})}),i.forEach(o=>{var l,c,h;const p=wt(o);if(t==="add"&&un((l=o.style)===null||l===void 0?void 0:l.zIndex)||t==="update"&&!("combo"in o)&&!("children"in o))return;let C=0;const k=this.getParentData(p,Lr);if(k)C=(((c=k.style)===null||c===void 0?void 0:c.zIndex)||0)+1;else{const W=this.getParentData(p,Ca);W&&(C=((h=W==null?void 0:W.style)===null||h===void 0?void 0:h.zIndex)||0)}this.preventUpdateNodeLikeHierarchy(()=>{this.updateNodeData([{id:p,style:{zIndex:C}}])})}),a.forEach(o=>{var l,c,h,p,C;if(un((l=o.style)===null||l===void 0?void 0:l.zIndex))return;let{id:k,source:W,target:j}=o;if(!k)k=wt(o);else{const ee=this.getEdgeDatum(k);W=ee.source,j=ee.target}if(!W||!j)return;const K=((h=(c=this.getNodeLikeDatum(W))===null||c===void 0?void 0:c.style)===null||h===void 0?void 0:h.zIndex)||0,Q=((C=(p=this.getNodeLikeDatum(j))===null||p===void 0?void 0:p.style)===null||C===void 0?void 0:C.zIndex)||0;this.updateEdgeData([{id:wt(o),style:{zIndex:Math.max(K,Q)-1}}])})})}getFrontZIndex(e){var t;const n=this.getElementType(e),i=this.getElementDataById(e),a=this.getData();if(Object.assign(a,{[`${n}s`]:a[`${n}s`].filter(s=>wt(s)!==e)}),n==="combo"&&!xa(i)){const s=new Set(this.getAncestorsData(e,Lr).map(wt));a.nodes=a.nodes.filter(o=>!s.has(wt(o))),a.combos=a.combos.filter(o=>!s.has(wt(o))),a.edges=a.edges.filter(({source:o,target:l})=>!s.has(o)&&!s.has(l))}return Math.max(((t=i.style)===null||t===void 0?void 0:t.zIndex)||0,0,...Object.values(a).flat().map(s=>{var o;return(((o=s==null?void 0:s.style)===null||o===void 0?void 0:o.zIndex)||0)+1}))}updateNodeLikeHierarchy(e){if(!this.enableUpdateNodeLikeHierarchy)return;const{model:t}=this;e.forEach(n=>{const i=wt(n),a=Wh(n);a!==void 0&&(t.hasTreeStructure(Lr)||t.attachTreeStructure(Lr),a===null&&this.refreshComboData(i),this.setParent(i,Wh(n),Lr));const s=n.children||[];if(s.length){t.hasTreeStructure(Ca)||t.attachTreeStructure(Ca);const o=s.filter(l=>t.hasNode(l));o.forEach(l=>this.setParent(l,i,Ca)),o.length!==s.length&&this.updateNodeData([{id:i,children:o}])}})}preventUpdateNodeLikeHierarchy(e){this.enableUpdateNodeLikeHierarchy=!1,e(),this.enableUpdateNodeLikeHierarchy=!0}updateData(e){const{nodes:t,edges:n,combos:i}=e;this.batch(()=>{this.updateNodeData(t),this.updateComboData(i),this.updateEdgeData(n)}),this.computeZIndex(e,"update")}updateNodeData(e=[]){if(!e.length)return;const{model:t}=this;this.batch(()=>{const n=[];e.forEach(i=>{const a=wt(i),s=Pi(t.getNode(a));if(uc(s,i))return;const o=Lo(s,i);this.pushChange({value:o,original:s,type:Gr.NodeUpdated}),t.mergeNodeData(a,o),n.push(o)}),this.updateNodeLikeHierarchy(n)}),this.computeZIndex({nodes:e},"update")}refreshData(){const{nodes:e,edges:t,combos:n}=this.getData();e.forEach(i=>{this.pushChange({value:i,original:i,type:Gr.NodeUpdated})}),t.forEach(i=>{this.pushChange({value:i,original:i,type:Gr.EdgeUpdated})}),n.forEach(i=>{this.pushChange({value:i,original:i,type:Gr.ComboUpdated})})}syncNodeLikeDatum(e){const{model:t}=this,n=wt(e);if(!t.hasNode(n))return;const i=Pi(t.getNode(n)),a=Lo(i,e);t.mergeNodeData(n,a)}syncEdgeDatum(e){const{model:t}=this,n=wt(e);if(!t.hasEdge(n))return;const i=Pi(t.getEdge(n)),a=Lo(i,e);t.mergeEdgeData(n,a)}updateEdgeData(e=[]){if(!e.length)return;const{model:t}=this;this.batch(()=>{e.forEach(n=>{const i=wt(n),a=Pi(t.getEdge(i));if(uc(a,n))return;n.source&&a.source!==n.source&&t.updateEdgeSource(i,n.source),n.target&&a.target!==n.target&&t.updateEdgeTarget(i,n.target);const s=Lo(a,n);this.pushChange({value:s,original:a,type:Gr.EdgeUpdated}),t.mergeEdgeData(i,s)})}),this.computeZIndex({edges:e},"update")}updateComboData(e=[]){if(!e.length)return;const{model:t}=this;t.batch(()=>{const n=[];e.forEach(i=>{const a=wt(i),s=Pi(t.getNode(a));if(uc(s,i))return;const o=Lo(s,i);this.pushChange({value:o,original:s,type:Gr.ComboUpdated}),t.mergeNodeData(a,o),n.push(o)}),this.updateNodeLikeHierarchy(n)}),this.computeZIndex({combos:e},"update")}setParent(e,t,n,i=!0){if(e===t)return;const a=this.getNodeLikeDatum(e),s=Wh(a);if(s!==t&&n===Lr){const o={id:e,combo:t};this.isCombo(e)?this.syncNodeLikeDatum(o):this.syncNodeLikeDatum(o)}this.model.setParent(e,t,n),i&&n===Lr&&Z8([s,t]).forEach(o=>{o!==void 0&&this.refreshComboData(o)})}refreshComboData(e){const t=this.getComboData([e])[0],n=this.getAncestorsData(e,Lr);t&&this.pushChange({value:t,original:t,type:Gr.ComboUpdated}),n.forEach(i=>{this.pushChange({value:i,original:i,type:Gr.ComboUpdated})})}getElementPosition(e){const t=this.getElementDataById(e);return xi(t)}translateNodeLikeBy(e,t){this.isCombo(e)?this.translateComboBy(e,t):this.translateNodeBy(e,t)}translateNodeLikeTo(e,t){this.isCombo(e)?this.translateComboTo(e,t):this.translateNodeTo(e,t)}translateNodeBy(e,t){const n=this.getElementPosition(e),i=Jn(n,[...t,0].slice(0,3));this.translateNodeTo(e,i)}translateNodeTo(e,t){const[n=0,i=0,a=0]=t;this.preventUpdateNodeLikeHierarchy(()=>{this.updateNodeData([{id:e,style:{x:n,y:i,z:a}}])})}translateComboBy(e,t){const[n=0,i=0,a=0]=t;if([n,i,a].some(isNaN)||[n,i,a].every(l=>l===0))return;const s=this.getComboData([e])[0];if(!s)return;const o=new Set;ol(s,l=>{const c=wt(l);if(o.has(c))return;o.add(c);const[h,p,C]=xi(l),k=Lo(l,{style:{x:h+n,y:p+i,z:C+a}});this.pushChange({value:k,original:l,type:this.isCombo(c)?Gr.ComboUpdated:Gr.NodeUpdated}),this.model.mergeNodeData(c,k)},l=>this.getChildrenData(wt(l)),"BT")}translateComboTo(e,t){var n;if(t.some(isNaN))return;const[i=0,a=0,s=0]=t,o=(n=this.getComboData([e]))===null||n===void 0?void 0:n[0];if(!o)return;const[l,c,h]=xi(o),p=i-l,C=a-c,k=s-h;ol(o,W=>{const j=wt(W),[K,Q,ee]=xi(W),re=Lo(W,{style:{x:K+p,y:Q+C,z:ee+k}});this.pushChange({value:re,original:W,type:this.isCombo(j)?Gr.ComboUpdated:Gr.NodeUpdated}),this.model.mergeNodeData(j,re)},W=>this.getChildrenData(wt(W)),"BT")}removeData(e){const{nodes:t,edges:n,combos:i}=e;this.batch(()=>{this.removeEdgeData(n),this.removeNodeData(t),this.removeComboData(i),this.latestRemovedComboIds=new Set(i)})}removeNodeData(e=[]){e.length&&this.batch(()=>{e.forEach(t=>{this.removeEdgeData(this.getRelatedEdgesData(t).map(wt)),this.pushChange({value:this.getNodeData([t])[0],type:Gr.NodeRemoved}),this.removeNodeLikeHierarchy(t)}),this.model.removeNodes(e)})}removeEdgeData(e=[]){e.length&&(e.forEach(t=>this.pushChange({value:this.getEdgeData([t])[0],type:Gr.EdgeRemoved})),this.model.removeEdges(e))}removeComboData(e=[]){e.length&&this.batch(()=>{e.forEach(t=>{this.pushChange({value:this.getComboData([t])[0],type:Gr.ComboRemoved}),this.removeNodeLikeHierarchy(t),this.comboIds.delete(t)}),this.model.removeNodes(e)})}removeNodeLikeHierarchy(e){if(this.model.hasTreeStructure(Lr)){const t=Wh(this.getNodeLikeDatum(e));this.setParent(e,void 0,Lr,!1),this.model.getChildren(e,Lr).forEach(n=>{const i=Pi(n),a=wt(i);this.setParent(wt(i),t,Lr,!1);const s=Lo(i,{id:wt(i),combo:t});this.pushChange({value:s,original:i,type:this.isCombo(a)?Gr.ComboUpdated:Gr.NodeUpdated}),this.model.mergeNodeData(wt(i),s)}),Rn(t)||this.refreshComboData(t)}}getElementType(e){if(this.model.hasNode(e))return this.isCombo(e)?"combo":"node";if(this.model.hasEdge(e))return"edge";throw new Error(Vs(`Unknown element type of id: ${e}`))}destroy(){const{model:e}=this,t=e.getAllNodes(),n=e.getAllEdges();e.removeEdges(n.map(i=>i.id)),e.removeNodes(t.map(i=>i.id)),this.context={}}}var Su=function(r,e,t,n){function i(a){return a instanceof t?a:new t(function(s){s(a)})}return new(t||(t=Promise))(function(a,s){function o(h){try{c(n.next(h))}catch(p){s(p)}}function l(h){try{c(n.throw(h))}catch(p){s(p)}}function c(h){h.done?a(h.value):i(h.value).then(o,l)}c((n=n.apply(r,e||[])).next())})};class Q8{constructor(e){this.elementMap={},this.shapeTypeMap={},this.paletteStyle={},this.defaultStyle={},this.stateStyle={},this.visibilityCache=new WeakMap,this.context=e}init(){this.initContainer()}initContainer(){if(!this.container||this.container.destroyed){const{canvas:e}=this.context;this.container=e.appendChild(new Ei({className:"elements"}))}}emit(e,t){t.silence||wi(this.context.graph,e)}forEachElementData(e){sl.forEach(t=>{const n=this.context.model.getElementsDataByType(t);e(t,n)})}getElementType(e,t){var n;const{options:i,graph:a}=this.context,s=((n=i[e])===null||n===void 0?void 0:n.type)||t.type;return s?typeof s=="string"?s:s.call(a,t):e==="edge"?"line":"circle"}getTheme(e){return Uy(this.context.options)[e]||{}}getThemeStyle(e){return this.getTheme(e).style||{}}getThemeStateStyle(e,t){const{state:n={}}=this.getTheme(e);return Object.assign({},...t.map(i=>n[i]||{}))}computePaletteStyle(){const{options:e}=this.context;this.paletteStyle={},this.forEachElementData((t,n)=>{var i,a;const s=Object.assign({},q1((i=this.getTheme(t))===null||i===void 0?void 0:i.palette),q1((a=e[t])===null||a===void 0?void 0:a.palette));s!=null&&s.field&&Object.assign(this.paletteStyle,IP(n,s))})}getPaletteStyle(e,t){const n=this.paletteStyle[t];return n?e==="edge"?{stroke:n}:{fill:n}:{}}computeElementDefaultStyle(e,t){var n;const{options:i}=this.context,a=((n=i[e])===null||n===void 0?void 0:n.style)||{};"transform"in a&&Array.isArray(a.transform)&&(a.transform=[...a.transform]),this.defaultStyle[wt(t.datum)]=J1(a,t)}computeElementsDefaultStyle(e){const{graph:t}=this.context;this.forEachElementData((n,i)=>{const a=i.length;for(let s=0;s<a;s++){const o=i[s];(e===void 0||e.includes(wt(o)))&&this.computeElementDefaultStyle(n,{datum:o,graph:t})}})}getDefaultStyle(e){return this.defaultStyle[e]||{}}getElementState(e){try{const{model:t}=this.context;return t.getElementState(e)}catch(t){return[]}}getElementStateStyle(e,t,n){var i,a;const{options:s}=this.context,o=((a=(i=s[e])===null||i===void 0?void 0:i.state)===null||a===void 0?void 0:a[t])||{};return J1(o,n)}computeElementStatesStyle(e,t,n){this.stateStyle[wt(n.datum)]=Object.assign({},...t.map(i=>this.getElementStateStyle(e,i,n)))}computeElementsStatesStyle(e){const{graph:t}=this.context;this.forEachElementData((n,i)=>{const a=i.length;for(let s=0;s<a;s++){const o=i[s];if(e===void 0||e.includes(wt(o))){const l=this.getElementState(wt(o));this.computeElementStatesStyle(n,l,{datum:o,graph:t})}}})}getStateStyle(e){return this.stateStyle[e]||{}}computeStyle(e,t){e&&["translate","zIndex"].includes(e)||(this.computePaletteStyle(),this.computeElementsDefaultStyle(t),this.computeElementsStatesStyle(t))}getElement(e){return this.elementMap[e]}getNodes(){return this.context.model.getNodeData().map(({id:e})=>this.elementMap[e])}getEdges(){return this.context.model.getEdgeData().map(e=>this.elementMap[wt(e)])}getCombos(){return this.context.model.getComboData().map(({id:e})=>this.elementMap[e])}getElementComputedStyle(e,t){const n=wt(t),i=this.getThemeStyle(e),a=this.getPaletteStyle(e,n),s=t.style||{},o=this.getDefaultStyle(n),l=this.getThemeStateStyle(e,this.getElementState(n)),c=this.getStateStyle(n),h=Object.assign({},i,a,s,o,l,c);if(e==="combo"){const p=this.context.model.getChildrenData(n),k=!!h.collapsed?[]:p.map(wt).filter(W=>this.getElement(W));Object.assign(h,{childrenNode:k,childrenData:p})}return h}getDrawData(e){this.init();const t=this.computeChangesAndDrawData(e);if(!t)return null;const{type:n="draw",stage:i=n}=e;return this.markDestroyElement(t.drawData),this.computeStyle(i),{type:n,stage:i,data:t}}draw(e={animation:!0}){const t=this.getDrawData(e);if(!t)return;const{data:{drawData:{add:n,update:i,remove:a}}}=t;return this.destroyElements(a,e),this.createElements(n,e),this.updateElements(i,e),this.setAnimationTask(e,t)}preLayoutDraw(){return Su(this,arguments,void 0,function*(e={animation:!0}){var t,n;const i=this.getDrawData(e);if(!i)return;const{data:{drawData:a}}=i;yield(n=(t=this.context.layout)===null||t===void 0?void 0:t.preLayout)===null||n===void 0?void 0:n.call(t,a);const{add:s,update:o,remove:l}=a;return this.destroyElements(l,e),this.createElements(s,e),this.updateElements(o,e),this.setAnimationTask(e,i)})}setAnimationTask(e,t){const{animation:n,silence:i}=e,{data:{dataChanges:a,drawData:s},stage:o,type:l}=t;return this.context.animation.animate(n,i?{}:{before:()=>this.emit(new mi($t.BEFORE_DRAW,{dataChanges:a,animation:n,stage:o,render:l==="render"}),e),beforeAnimate:c=>this.emit(new Ja($t.BEFORE_ANIMATE,_a.DRAW,c,s),e),afterAnimate:c=>this.emit(new Ja($t.AFTER_ANIMATE,_a.DRAW,c,s),e),after:()=>this.emit(new mi($t.AFTER_DRAW,{dataChanges:a,animation:n,stage:o,render:l==="render",firstRender:this.context.graph.rendered===!1}),e)})}computeChangesAndDrawData(e){const{model:t}=this.context,n=t.getChanges(),i=Cp(n);if(i.length===0)return null;const{NodeAdded:a=[],NodeUpdated:s=[],NodeRemoved:o=[],EdgeAdded:l=[],EdgeUpdated:c=[],EdgeRemoved:h=[],ComboAdded:p=[],ComboUpdated:C=[],ComboRemoved:k=[]}=Ah(i,Q=>Q.type),W=Q=>new Map(Q.map(ee=>{const re=ee.value;return[wt(re),re]})),j={add:{nodes:W(a),edges:W(l),combos:W(p)},update:{nodes:W(s),edges:W(c),combos:W(C)},remove:{nodes:W(o),edges:W(h),combos:W(k)}},K=this.transformData(j,e);return t.clearChanges(),{dataChanges:n,drawData:K}}transformData(e,t){const n=this.context.transform.getTransformInstance();return Object.values(n).reduce((i,a)=>a.beforeDraw(i,t),e)}createElement(e,t,n){var i;const a=wt(t);if(this.getElement(a))return;const o=this.getElementType(e,t),l=this.getElementComputedStyle(e,t),c=Gs(e,o);if(!c)return Ea.warn(`The element ${o} of ${e} is not registered.`);this.emit(new lc($t.BEFORE_ELEMENT_CREATE,e,t),n);const h=this.container.appendChild(new c({id:a,context:this.context,style:l}));this.shapeTypeMap[a]=o,this.elementMap[a]=h;const{stage:p="enter"}=n;(i=this.context.animation)===null||i===void 0||i.add({element:h,elementType:e,stage:p,originalStyle:Object.assign({},h.attributes),updatedStyle:l},{after:()=>{var C;this.emit(new lc($t.AFTER_ELEMENT_CREATE,e,t),n),(C=h.onCreate)===null||C===void 0||C.call(h)}})}createElements(e,t){const{nodes:n,edges:i,combos:a}=e;[["node",n],["combo",a],["edge",i]].forEach(([o,l])=>{l.forEach(c=>this.createElement(o,c,t))})}getUpdateStageStyle(e,t,n){const{stage:i="update"}=n;if(i==="translate")if(e==="node"||e==="combo"){const{style:{x:a=0,y:s=0,z:o=0}={}}=t;return{x:a,y:s,z:o}}else return{};return this.getElementComputedStyle(e,t)}updateElement(e,t,n){var i;const a=wt(t),{stage:s="update"}=n,o=this.getElement(a);if(!o)return()=>null;this.emit(new lc($t.BEFORE_ELEMENT_UPDATE,e,t),n);const l=this.getElementType(e,t),c=this.getUpdateStageStyle(e,t,n);this.shapeTypeMap[a]!==l&&(o.destroy(),delete this.shapeTypeMap[a],delete this.elementMap[a],this.createElement(e,t,{animation:!1,silence:!0}));const h=s!=="visibility"?s:c.visibility==="hidden"?"hide":"show";h==="hide"&&delete c.visibility,(i=this.context.animation)===null||i===void 0||i.add({element:o,elementType:e,stage:h,originalStyle:Object.assign({},o.attributes),updatedStyle:c},{before:()=>{const p=this.elementMap[a];s!=="collapse"&&Yg(p,c),s==="visibility"&&(H8(p,"opacity")||W8(p,"opacity"),this.visibilityCache.set(p,h==="show"?"visible":"hidden"),h==="show"&&il(p,"visible"))},after:()=>{var p;const C=this.elementMap[a];s==="collapse"&&Yg(C,c),h==="hide"&&il(C,this.visibilityCache.get(C)),this.emit(new lc($t.AFTER_ELEMENT_UPDATE,e,t),n),(p=C.onUpdate)===null||p===void 0||p.call(C)}})}updateElements(e,t){const{nodes:n,edges:i,combos:a}=e;[["node",n],["combo",a],["edge",i]].forEach(([o,l])=>{l.forEach(c=>this.updateElement(o,c,t))})}markDestroyElement(e){Object.values(e.remove).forEach(t=>{t.forEach(n=>{const i=wt(n),a=this.getElement(i);a&&KL(a)})})}destroyElement(e,t,n){var i;const{stage:a="exit"}=n,s=wt(t),o=this.elementMap[s];if(!o)return()=>null;this.emit(new lc($t.BEFORE_ELEMENT_DESTROY,e,t),n),(i=this.context.animation)===null||i===void 0||i.add({element:o,elementType:e,stage:a,originalStyle:Object.assign({},o.attributes),updatedStyle:{}},{after:()=>{var l;this.clearElement(s),o.destroy(),(l=o.onDestroy)===null||l===void 0||l.call(o),this.emit(new lc($t.AFTER_ELEMENT_DESTROY,e,t),n)}})}destroyElements(e,t){const{nodes:n,edges:i,combos:a}=e;[["combo",a],["edge",i],["node",n]].forEach(([o,l])=>{l.forEach(c=>this.destroyElement(o,c,t))})}clearElement(e){delete this.paletteStyle[e],delete this.defaultStyle[e],delete this.stateStyle[e],delete this.elementMap[e],delete this.shapeTypeMap[e]}alignLayoutResultToElement(e,t){var n,i;const a=(n=e.nodes)===null||n===void 0?void 0:n.find(s=>wt(s)===t);if(a){const s=xi(this.context.model.getNodeLikeDatum(t)),o=xi(a),l=Or(s,o);(i=e.nodes)===null||i===void 0||i.forEach(c=>{var h,p,C;!((h=c.style)===null||h===void 0)&&h.x&&(c.style.x+=l[0]),!((p=c.style)===null||p===void 0)&&p.y&&(c.style.y+=l[1]),!((C=c.style)===null||C===void 0)&&C.z&&(c.style.z+=l[2]||0)})}}collapseNode(e,t){return Su(this,void 0,void 0,function*(){var n;const{animation:i,align:a}=t,{model:s,layout:o}=this.context,l=this.computeChangesAndDrawData({stage:"collapse",animation:i});if(!l)return;this.markDestroyElement(l.drawData);const c=yield o.simulate();a&&this.alignLayoutResultToElement(c,e),s.updateData(c);const h=this.computeChangesAndDrawData({stage:"collapse",animation:i});if(!h)return;const{drawData:p}=h,{add:C,remove:k,update:W}=p;this.markDestroyElement(p);const j={animation:i,stage:"collapse",data:p};this.destroyElements(k,j),this.createElements(C,j),this.updateElements(W,j),yield(n=this.context.animation.animate(i,{beforeAnimate:K=>this.emit(new Ja($t.BEFORE_ANIMATE,_a.COLLAPSE,K,p),j),afterAnimate:K=>this.emit(new Ja($t.AFTER_ANIMATE,_a.COLLAPSE,K,p),j)},{collapse:{target:e,descendants:Array.from(k.nodes).map(([,K])=>wt(K)),position:xi(W.nodes.get(e))}}))===null||n===void 0?void 0:n.finished})}expandNode(e,t){return Su(this,void 0,void 0,function*(){var n;const{model:i,layout:a}=this.context,{animation:s,align:o}=t,l=xi(i.getNodeData([e])[0]),c=this.computeChangesAndDrawData({stage:"expand",animation:s});if(!c)return;const{drawData:{add:h}}=c;this.createElements(h,{animation:!1,stage:"expand",target:e}),this.context.animation.clear();const p=yield a.simulate();o&&this.alignLayoutResultToElement(p,e),i.updateData(p),this.computeStyle("expand");const C=this.computeChangesAndDrawData({stage:"collapse",animation:s});if(!C)return;const{drawData:k}=C,{update:W}=k,j={animation:s,stage:"expand",data:k};h.edges.forEach(K=>W.edges.set(wt(K),K)),h.nodes.forEach(K=>W.nodes.set(wt(K),K)),this.updateElements(W,j),yield(n=this.context.animation.animate(s,{beforeAnimate:K=>this.emit(new Ja($t.BEFORE_ANIMATE,_a.EXPAND,K,k),j),afterAnimate:K=>this.emit(new Ja($t.AFTER_ANIMATE,_a.EXPAND,K,k),j)},{expand:{target:e,descendants:Array.from(h.nodes).map(([,K])=>wt(K)),position:l}}))===null||n===void 0?void 0:n.finished})}collapseCombo(e,t){return Su(this,void 0,void 0,function*(){var n;const{model:i,element:a}=this.context;if(i.getAncestorsData(e,Lr).some(j=>xa(j)))return;const s=a.getElement(e),o=s.getComboPosition(Object.assign(Object.assign({},s.attributes),{collapsed:!0})),l=this.computeChangesAndDrawData({stage:"collapse",animation:t});if(!l)return;const{dataChanges:c,drawData:h}=l;this.markDestroyElement(h);const{update:p,remove:C}=h,k={animation:t,stage:"collapse",data:h};this.destroyElements(C,k),this.updateElements(p,k);const W=j=>Array.from(j).map(([,K])=>wt(K));yield(n=this.context.animation.animate(t,{before:()=>this.emit(new mi($t.BEFORE_DRAW,{dataChanges:c,animation:t}),k),beforeAnimate:j=>this.emit(new Ja($t.BEFORE_ANIMATE,_a.COLLAPSE,j,h),k),afterAnimate:j=>this.emit(new Ja($t.AFTER_ANIMATE,_a.COLLAPSE,j,h),k),after:()=>this.emit(new mi($t.AFTER_DRAW,{dataChanges:c,animation:t}),k)},{collapse:{target:e,descendants:[...W(C.nodes),...W(C.combos)],position:o}}))===null||n===void 0?void 0:n.finished})}expandCombo(e,t){return Su(this,void 0,void 0,function*(){var n;const{model:i}=this.context,a=xi(i.getComboData([e])[0]);this.computeStyle("expand");const s=this.computeChangesAndDrawData({stage:"expand",animation:t});if(!s)return;const{dataChanges:o,drawData:l}=s,{add:c,update:h}=l,p={animation:t,stage:"expand",data:l,target:e};this.createElements(c,p),this.updateElements(h,p);const C=k=>Array.from(k).map(([,W])=>wt(W));yield(n=this.context.animation.animate(t,{before:()=>this.emit(new mi($t.BEFORE_DRAW,{dataChanges:o,animation:t}),p),beforeAnimate:k=>this.emit(new Ja($t.BEFORE_ANIMATE,_a.EXPAND,k,l),p),afterAnimate:k=>this.emit(new Ja($t.AFTER_ANIMATE,_a.EXPAND,k,l),p),after:()=>this.emit(new mi($t.AFTER_DRAW,{dataChanges:o,animation:t}),p)},{expand:{target:e,descendants:[...C(c.nodes),...C(c.combos)],position:a}}))===null||n===void 0?void 0:n.finished})}clear(){this.container.destroy(),this.initContainer(),this.elementMap={},this.shapeTypeMap={},this.defaultStyle={},this.stateStyle={},this.paletteStyle={}}destroy(){this.clear(),this.container.destroy(),this.context={}}}const r2=Symbol("Comlink.proxy"),J8=Symbol("Comlink.endpoint"),i2=Symbol("Comlink.releaseProxy"),p0=Symbol("Comlink.finalizer"),Bd=Symbol("Comlink.thrown"),a2=r=>typeof r=="object"&&r!==null||typeof r=="function",q8={canHandle:r=>a2(r)&&r[r2],serialize(r){const{port1:e,port2:t}=new MessageChannel;return o2(r,e),[t,[t]]},deserialize(r){return r.start(),c2(r)}},$8={canHandle:r=>a2(r)&&Bd in r,serialize({value:r}){let e;return r instanceof Error?e={isError:!0,value:{message:r.message,name:r.name,stack:r.stack}}:e={isError:!1,value:r},[e,[]]},deserialize(r){throw r.isError?Object.assign(new Error(r.value.message),r.value):r.value}},s2=new Map([["proxy",q8],["throw",$8]]);function e6(r,e){for(const t of r)if(e===t||t==="*"||t instanceof 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DW(r,e=globalThis,t="*"){return{postMessage:(n,i)=>r.postMessage(n,t,i),addEventListener:e.addEventListener.bind(e),removeEventListener:e.removeEventListener.bind(e)}}function Ud(r){for(const[e,t]of s2)if(t.canHandle(r)){const[n,i]=t.serialize(r);return[{type:"HANDLER",name:e,value:n},i]}return[{type:"RAW",value:r},f2.get(r)||[]]}function xl(r){switch(r.type){case"HANDLER":return s2.get(r.name).deserialize(r.value);case"RAW":return r.value}}function hc(r,e,t,n){return new Promise(i=>{const a=o6();e.set(a,i),r.start&&r.start(),r.postMessage(Object.assign({id:a},t),n)})}function o6(){return new Array(4).fill(0).map(()=>Math.floor(Math.random()*Number.MAX_SAFE_INTEGER).toString(16)).join("-")}class l6 extends Tf{constructor(e,t,n){super(),this.graph=e,this.layout=t,this.options=n,this.spawnWorker()}spawnWorker(){this.proxy=c2(new Worker(new URL(Z.p+Z.u(3339),Z.b),{type:void 0})),this.running&&(this.running=!1,this.execute())}execute(){var e;return(0,we.mG)(this,void 0,void 0,function*(){if(this.running)return this;this.running=!0;const t=this.layout.options,{onTick:n}=t,i=(0,we._T)(t,["onTick"]),a={};Object.keys(i).forEach(c=>{En(i[c])||(a[c]=i[c])});const s={layout:{id:this.layout.id,options:a,iterations:(e=this.options)===null||e===void 0?void 0:e.iterations},nodes:this.graph.getAllNodes(),edges:this.graph.getAllEdges()},o=new Float32Array([0]),[l]=yield this.proxy.calculateLayout(s,[o]);return l})}stop(){return this.running=!1,this.proxy.stopLayout(),this}kill(){this.proxy[i2]()}isRunning(){return this.running}}var fc=function(r,e,t,n){function i(a){return a instanceof t?a:new t(function(s){s(a)})}return new(t||(t=Promise))(function(a,s){function o(h){try{c(n.next(h))}catch(p){s(p)}}function l(h){try{c(n.throw(h))}catch(p){s(p)}}function c(h){h.done?a(h.value):i(h.value).then(o,l)}c((n=n.apply(r,e||[])).next())})},c6=function(r,e){var t={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&e.indexOf(n)<0&&(t[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var i=0,n=Object.getOwnPropertySymbols(r);i<n.length;i++)e.indexOf(n[i])<0&&Object.prototype.propertyIsEnumerable.call(r,n[i])&&(t[n[i]]=r[n[i]]);return t};class u6{get presetOptions(){return{animation:!!Wy(this.context.options,!0)}}get options(){const{options:e}=this.context;return e.layout}constructor(e){this.instances=[],this.context=e}getLayoutInstance(){return this.instances}preLayout(e){return fc(this,void 0,void 0,function*(){var t,n,i,a;const{graph:s,model:o}=this.context,{add:l}=e;wi(s,new mi($t.BEFORE_LAYOUT,{type:"pre"}));const c=yield(t=this.context.layout)===null||t===void 0?void 0:t.simulate();(n=c==null?void 0:c.nodes)===null||n===void 0||n.forEach(h=>{const p=wt(h),C=l.nodes.get(p);o.syncNodeLikeDatum(h),C&&Object.assign(C.style,h.style)}),(i=c==null?void 0:c.edges)===null||i===void 0||i.forEach(h=>{const p=wt(h),C=l.edges.get(p);o.syncEdgeDatum(h),C&&Object.assign(C.style,h.style)}),(a=c==null?void 0:c.combos)===null||a===void 0||a.forEach(h=>{const p=wt(h),C=l.combos.get(p);o.syncNodeLikeDatum(h),C&&Object.assign(C.style,h.style)}),wi(s,new mi($t.AFTER_LAYOUT,{type:"pre"})),this.transformDataAfterLayout("pre",e)})}postLayout(){return fc(this,arguments,void 0,function*(e=this.options){if(!e)return;const t=Array.isArray(e)?e:[e],{graph:n}=this.context;wi(n,new mi($t.BEFORE_LAYOUT,{type:"post"}));for(const i of t){const a=t.indexOf(i),s=this.getLayoutData(i),o=Object.assign(Object.assign({},this.presetOptions),i);wi(n,new mi($t.BEFORE_STAGE_LAYOUT,{options:o,index:a}));const l=yield this.stepLayout(s,o,a);wi(n,new mi($t.AFTER_STAGE_LAYOUT,{options:o,index:a})),i.animation||this.updateElementPosition(l,!1)}wi(n,new mi($t.AFTER_LAYOUT,{type:"post"})),this.transformDataAfterLayout("post")})}transformDataAfterLayout(e,t){const n=this.context.transform.getTransformInstance();Object.values(n).forEach(i=>i.afterLayout(e,t))}simulate(){return fc(this,void 0,void 0,function*(){if(!this.options)return{};const e=Array.isArray(this.options)?this.options:[this.options];let t={};for(const n of e){const i=e.indexOf(n),a=this.getLayoutData(n);t=yield this.stepLayout(a,Object.assign(Object.assign(Object.assign({},this.presetOptions),n),{animation:!1}),i)}return t})}stepLayout(e,t,n){return fc(this,void 0,void 0,function*(){return rR(t)?yield this.treeLayout(e,t,n):yield this.graphLayout(e,t,n)})}graphLayout(e,t,n){return fc(this,void 0,void 0,function*(){const{animation:i,enableWorker:a,iterations:s=300}=t,o=this.initGraphLayout(t);if(!o)return{};if(this.instances[n]=o,this.instance=o,a){const c=o;return this.supervisor=new l6(c.graphData2LayoutModel(e),c.instance,{iterations:s}),Of(yield this.supervisor.execute())}if(vp(o))return i?yield o.execute(e,{onTick:c=>{this.updateElementPosition(c,!1)}}):(o.execute(e),o.stop(),o.tick(s));const l=yield o.execute(e);if(i){const c=this.updateElementPosition(l,i);yield c==null?void 0:c.finished}return l})}treeLayout(e,t,n){return fc(this,void 0,void 0,function*(){const{type:i,animation:a}=t,s=Gs("layout",i);if(!s)return{};const{nodes:o=[],edges:l=[]}=e,c=new ci({nodes:o.map(W=>({id:wt(W),data:W.data||{}})),edges:l.map(W=>({id:wt(W),source:W.source,target:W.target,data:W.data||{}}))});X8(c);const h={nodes:[],edges:[]},p={nodes:[],edges:[]};c.getRoots(Ca).forEach(W=>{ol(W,re=>{re.children=c.getSuccessors(re.id)},re=>c.getSuccessors(re.id),"TB");const j=s(W,t),{x:K,y:Q,z:ee=0}=j;ol(j,re=>{const{id:ve,x:he,y:pe,z:ye=0}=re;h.nodes.push({id:ve,style:{x:K,y:Q,z:ee}}),p.nodes.push({id:ve,style:{x:he,y:pe,z:ye}})},re=>re.children,"TB")});const k=this.inferTreeLayoutOffset(p);if(d2(p,k),a){d2(h,k),this.updateElementPosition(h,!1);const W=this.updateElementPosition(p,a);yield W==null?void 0:W.finished}return p})}inferTreeLayoutOffset(e){var t;let[n,i]=[1/0,-1/0],[a,s]=[1/0,-1/0];(t=e.nodes)===null||t===void 0||t.forEach(j=>{const{x:K=0,y:Q=0}=j.style||{};n=Math.min(n,K),i=Math.max(i,K),a=Math.min(a,Q),s=Math.max(s,Q)});const{canvas:o}=this.context,l=o.getSize(),[c,h]=o.getCanvasByViewport([0,0]),[p,C]=o.getCanvasByViewport(l);if(n>=c&&i<=p&&a>=h&&s<=C)return[0,0];const k=(c+p)/2,W=(h+C)/2;return[k-(n+i)/2,W-(a+s)/2]}stopLayout(){this.instance&&vp(this.instance)&&(this.instance.stop(),this.instance=void 0),this.supervisor&&(this.supervisor.stop(),this.supervisor=void 0),this.animationResult&&(this.animationResult.finish(),this.animationResult=void 0)}getLayoutData(e){const{nodeFilter:t=()=>!0,preLayout:n=!1,isLayoutInvisibleNodes:i=!1}=e,{nodes:a,edges:s,combos:o}=this.context.model.getData(),{element:l,model:c}=this.context,h=j=>l.getElement(j),p=n?j=>{var K;return!i&&(((K=j.style)===null||K===void 0?void 0:K.visibility)==="hidden"||c.getAncestorsData(j.id,Ca).some(xa)||c.getAncestorsData(j.id,Lr).some(xa))?!1:t(j)}:j=>{const K=wt(j),Q=h(K);return!Q||_f(Q)?!1:t(j)},C=a.filter(p),k=new Map(C.map(j=>[wt(j),j]));o.forEach(j=>k.set(wt(j),j));const W=s.filter(({source:j,target:K})=>k.has(j)&&k.has(K));return{nodes:C,edges:W,combos:o}}initGraphLayout(e){var t;const{element:n,viewport:i}=this.context,{type:a,enableWorker:s,animation:o,iterations:l}=e,c=c6(e,["type","enableWorker","animation","iterations"]),[h,p]=i.getCanvasSize(),C=[h/2,p/2],k=(t=e==null?void 0:e.nodeSize)!==null&&t!==void 0?t:ee=>{const re=n==null?void 0:n.getElement(ee.id);return re?re.attributes.size:n==null?void 0:n.getElementComputedStyle("node",ee).size},W=Gs("layout",a);if(!W)return Ea.warn(`The layout of ${a} is not registered.`);const j=Object.getPrototypeOf(W.prototype)===Cf.prototype?W:aR(W,this.context),K=new j(this.context),Q={nodeSize:k,width:h,height:p,center:C};switch(K.id){case"d3-force":case"d3-force-3d":Object.assign(Q,{center:{x:h/2,y:p/2,z:0}});break;default:break}return ia(K.options,Q,c),K}updateElementPosition(e,t){const{model:n,element:i}=this.context;return i?(n.updateData(e),i.draw({animation:t,silence:!0})):null}destroy(){var e;this.stopLayout(),this.context={},(e=this.supervisor)===null||e===void 0||e.kill(),this.supervisor=void 0,this.instance=void 0,this.instances=[],this.animationResult=void 0}}const d2=(r,e)=>{var t;const[n,i]=e;(t=r.nodes)===null||t===void 0||t.forEach(a=>{if(a.style){const{x:s=0,y:o=0}=a.style;a.style.x=s+n,a.style.y=o+i}else a.style={x:n,y:i}})};function h6(r){return[f6].reduce((t,n)=>n(t),r)}function f6(r){return!r.layout||Array.isArray(r.layout)||"preLayout"in r.layout||["antv-dagre","combo-combined","compact-box","circular","concentric","dagre","fishbone","grid","indented","mds","radial","random","snake","dendrogram","mindmap"].includes(r.layout.type)&&(r.layout.preLayout=!0),r}class d6 extends Eg{constructor(e){super(e),this.category="plugin",this.setPlugins(this.context.options.plugins||[])}setPlugins(e){this.setExtensions(e)}getPluginInstance(e){const t=this.extensionMap[e];if(t)return t;Ea.warn(`Cannot find the plugin ${e}, will try to find it by type.`);const n=this.extensions.find(i=>i.type===e);if(n)return this.extensionMap[n.key]}}const Wd=["update-related-edges","collapse-expand-node","collapse-expand-combo","get-edge-actual-ends","arrange-draw-order"];class v6 extends Eg{constructor(e){super(e),this.category="transform",this.setTransforms(this.context.options.transforms||[])}getTransforms(){}setTransforms(e){this.setExtensions([...Wd.slice(0,Wd.length-1),...e,Wd[Wd.length-1]])}getTransformInstance(e){return e?this.extensionMap[e]:this.extensionMap}}var Tu=function(r,e,t,n){function i(a){return a instanceof t?a:new t(function(s){s(a)})}return new(t||(t=Promise))(function(a,s){function o(h){try{c(n.next(h))}catch(p){s(p)}}function l(h){try{c(n.throw(h))}catch(p){s(p)}}function c(h){h.done?a(h.value):i(h.value).then(o,l)}c((n=n.apply(r,e||[])).next())})};class g6{get padding(){return os(this.context.options.padding)}get paddingOffset(){const[e,t,n,i]=this.padding,[a,s,o]=[(i-t)/2,(e-n)/2,0];return[a,s,o]}constructor(e){this.landmarkCounter=0,this.context=e;const[t,n]=this.paddingOffset,{zoom:i,rotation:a,x:s=t,y:o=n}=e.options;this.transform({mode:"absolute",scale:i,translate:[s,o],rotate:a},!1)}get camera(){const{canvas:e}=this.context;return new Proxy(e.getCamera(),{get:(t,n)=>{const a=Object.entries(e.getLayers()).filter(([o])=>!["main"].includes(o)).map(([,o])=>o.getCamera()),s=t[n];if(typeof s=="function")return(...o)=>{const l=s.apply(t,o);return a.forEach(c=>{c[n].apply(c,o)}),l}}})}createLandmark(e){return this.camera.createLandmark(`landmark-${this.landmarkCounter++}`,e)}getAnimation(e){const t=Wy(this.context.options,e);return t?ul(Object.assign({},t),["easing","duration"]):!1}getCanvasSize(){const{canvas:e}=this.context,{width:t=0,height:n=0}=e.getConfig();return[t,n]}getCanvasCenter(){const{canvas:e}=this.context,{width:t=0,height:n=0}=e.getConfig();return[t/2,n/2,0]}getViewportCenter(){const[e,t]=this.camera.getPosition();return[e,t,0]}getGraphCenter(){return this.context.graph.getViewportByCanvas(this.getCanvasCenter())}getZoom(){return this.camera.getZoom()}getRotation(){return this.camera.getRoll()}getTranslateOptions(e){const{camera:t}=this,{mode:n,translate:i=[]}=e,a=this.getZoom(),s=t.getPosition(),o=t.getFocalPoint(),[l,c]=this.getCanvasCenter(),[h=0,p=0,C=0]=i,k=us([-h,-p,-C],a);return n==="relative"?{position:Jn(s,k),focalPoint:Jn(o,k)}:{position:Jn([l,c,s[2]],k),focalPoint:Jn([l,c,o[2]],k)}}getRotateOptions(e){const{mode:t,rotate:n=0}=e;return{roll:t==="relative"?this.camera.getRoll()+n:n}}getZoomOptions(e){const{zoomRange:t}=this.context.options,n=this.camera.getZoom(),{mode:i,scale:a=1}=e;return Yr(i==="relative"?n*a:a,...t)}transform(e,t){return Tu(this,void 0,void 0,function*(){const{graph:n}=this.context,{translate:i,rotate:a,scale:s,origin:o}=e;this.cancelAnimation();const l=this.getAnimation(t);if(wi(n,new Id($t.BEFORE_TRANSFORM,e)),!a&&s&&!i&&o&&!l){this.camera.setZoomByViewportPoint(this.getZoomOptions(e),o),wi(n,new Id($t.AFTER_TRANSFORM,e));return}const c={};if(i&&Object.assign(c,this.getTranslateOptions(e)),un(a)&&Object.assign(c,this.getRotateOptions(e)),un(s)&&Object.assign(c,{zoom:this.getZoomOptions(e)}),l)return wi(n,new Ja($t.BEFORE_ANIMATE,_a.TRANSFORM,null,e)),new Promise(h=>{this.transformResolver=h,this.camera.gotoLandmark(this.createLandmark(c),Object.assign(Object.assign({},l),{onfinish:()=>{wi(n,new Ja($t.AFTER_ANIMATE,_a.TRANSFORM,null,e)),wi(n,new Id($t.AFTER_TRANSFORM,e)),this.transformResolver=void 0,h()}}))});this.camera.gotoLandmark(this.createLandmark(c),{duration:0}),wi(n,new Id($t.AFTER_TRANSFORM,e))})}fitView(e,t){return Tu(this,void 0,void 0,function*(){const[n,i,a,s]=this.padding,{when:o="always",direction:l="both"}=e||{},[c,h]=this.context.canvas.getSize(),p=c-s-i,C=h-n-a,k=this.context.canvas.getBounds(),W=this.getBBoxInViewport(k),[j,K]=fo(W),Q=l==="x"&&j>=p||l==="y"&&K>=C||l==="both"&&j>=p&&K>=C;if(o==="overflow"&&!Q)return yield this.fitCenter({animation:t});const ee=p/j,re=C/K,ve=l==="x"?ee:l==="y"?re:Math.min(ee,re),he=this.getAnimation(t);yield this.transform({mode:"relative",scale:ve,translate:Jn(Or(this.getCanvasCenter(),this.getBBoxInViewport(k).center),us(this.paddingOffset,ve))},he)})}fitCenter(e){return Tu(this,void 0,void 0,function*(){const t=this.context.canvas.getBounds();yield this.focus(t,e)})}focusElements(e){return Tu(this,arguments,void 0,function*(t,n={}){const{element:i}=this.context;if(!i)return;const a=o=>n.shapes?o.getShape(n.shapes).getRenderBounds():o.getRenderBounds(),s=Hc(t.map(o=>a(i.getElement(o))));yield this.focus(s,n)})}focus(e,t){return Tu(this,void 0,void 0,function*(){const n=this.context.graph.getViewportByCanvas(e.center),i=t.position||this.getCanvasCenter(),a=Or(i,n);yield this.transform({mode:"relative",translate:Jn(a,this.paddingOffset)},t.animation)})}getBBoxInViewport(e){const{min:t,max:n}=e,{graph:i}=this.context,[a,s]=i.getViewportByCanvas(t),[o,l]=i.getViewportByCanvas(n),c=new Nr;return c.setMinMax([a,s,0],[o,l,0]),c}isInViewport(e,t=!1,n=0){const{graph:i}=this.context,a=this.getCanvasSize(),[s,o]=i.getCanvasByViewport([0,0]),[l,c]=i.getCanvasByViewport(a);let h=new Nr;return h.setMinMax([s,o,0],[l,c,0]),n&&(h=go(h,n)),Gl(e)?ls(e,h):t?MC(e,h):h.intersects(e)}cancelAnimation(){var e,t;!((e=this.camera.landmarks)===null||e===void 0)&&e.length&&this.camera.cancelLandmarkAnimation(),(t=this.transformResolver)===null||t===void 0||t.call(this)}}var kr=function(r,e,t,n){function i(a){return a instanceof t?a:new t(function(s){s(a)})}return new(t||(t=Promise))(function(a,s){function o(h){try{c(n.next(h))}catch(p){s(p)}}function l(h){try{c(n.throw(h))}catch(p){s(p)}}function c(h){h.done?a(h.value):i(h.value).then(o,l)}c((n=n.apply(r,e||[])).next())})};class Hd extends Tf{constructor(e){var t;super(),this.options={},this.rendered=!1,this.destroyed=!1,this.context={model:new Y8},this.isCollapsingExpanding=!1,this.onResize=ru(()=>{this.resize()},300),this._setOptions(Object.assign({},Hd.defaultOptions,e),!0),this.context.graph=this,this.options.autoResize&&((t=globalThis.addEventListener)===null||t===void 0||t.call(globalThis,"resize",this.onResize))}getOptions(){return this.options}setOptions(e){this._setOptions(e,!1)}_setOptions(e,t){if(this.updateCanvas(e),Object.assign(this.options,h6(e)),t){const{data:C}=e;C&&this.addData(C);return}const{behaviors:n,combo:i,data:a,edge:s,layout:o,node:l,plugins:c,theme:h,transforms:p}=e;n&&this.setBehaviors(n),a&&this.setData(a),l&&this.setNode(l),s&&this.setEdge(s),i&&this.setCombo(i),o&&this.setLayout(o),h&&this.setTheme(h),c&&this.setPlugins(c),p&&this.setTransforms(p)}getSize(){return this.context.canvas?this.context.canvas.getSize():[this.options.width||0,this.options.height||0]}setSize(e,t){e&&(this.options.width=e),t&&(this.options.height=t),this.resize(e,t)}setZoomRange(e){this.options.zoomRange=e}getZoomRange(){return this.options.zoomRange}setNode(e){this.options.node=e,this.context.model.refreshData()}setEdge(e){this.options.edge=e,this.context.model.refreshData()}setCombo(e){this.options.combo=e,this.context.model.refreshData()}getTheme(){return this.options.theme}setTheme(e){this.options.theme=En(e)?e(this.getTheme()):e}setLayout(e){this.options.layout=En(e)?e(this.getLayout()):e}getLayout(){return this.options.layout}setBehaviors(e){var t;this.options.behaviors=En(e)?e(this.getBehaviors()):e,(t=this.context.behavior)===null||t===void 0||t.setBehaviors(this.options.behaviors)}updateBehavior(e){this.setBehaviors(t=>t.map(n=>typeof n=="object"&&n.key===e.key?Object.assign(Object.assign({},n),e):n))}getBehaviors(){return this.options.behaviors||[]}setPlugins(e){var t;this.options.plugins=En(e)?e(this.getPlugins()):e,(t=this.context.plugin)===null||t===void 0||t.setPlugins(this.options.plugins)}updatePlugin(e){this.setPlugins(t=>t.map(n=>typeof n=="object"&&n.key===e.key?Object.assign(Object.assign({},n),e):n))}getPlugins(){return this.options.plugins||[]}getPluginInstance(e){return this.context.plugin.getPluginInstance(e)}setTransforms(e){var t;this.options.transforms=En(e)?e(this.getTransforms()):e,(t=this.context.transform)===null||t===void 0||t.setTransforms(this.options.transforms)}updateTransform(e){this.setTransforms(t=>t.map(n=>typeof n=="object"&&n.key===e.key?Object.assign(Object.assign({},n),e):n)),this.context.model.refreshData()}getTransforms(){return this.options.transforms||[]}getData(){return this.context.model.getData()}getElementData(e){return Array.isArray(e)?e.map(t=>this.context.model.getElementDataById(t)):this.context.model.getElementDataById(e)}getNodeData(e){return e===void 0?this.context.model.getNodeData():Array.isArray(e)?this.context.model.getNodeData(e):this.context.model.getNodeLikeDatum(e)}getEdgeData(e){return e===void 0?this.context.model.getEdgeData():Array.isArray(e)?this.context.model.getEdgeData(e):this.context.model.getEdgeDatum(e)}getComboData(e){return e===void 0?this.context.model.getComboData():Array.isArray(e)?this.context.model.getComboData(e):this.context.model.getNodeLikeDatum(e)}setData(e){this.context.model.setData(En(e)?e(this.getData()):e)}addData(e){this.context.model.addData(En(e)?e(this.getData()):e)}addNodeData(e){this.context.model.addNodeData(En(e)?e(this.getNodeData()):e)}addEdgeData(e){this.context.model.addEdgeData(En(e)?e(this.getEdgeData()):e)}addComboData(e){this.context.model.addComboData(En(e)?e(this.getComboData()):e)}addChildrenData(e,t){this.context.model.addChildrenData(e,t)}updateData(e){this.context.model.updateData(En(e)?e(this.getData()):e)}updateNodeData(e){this.context.model.updateNodeData(En(e)?e(this.getNodeData()):e)}updateEdgeData(e){this.context.model.updateEdgeData(En(e)?e(this.getEdgeData()):e)}updateComboData(e){this.context.model.updateComboData(En(e)?e(this.getComboData()):e)}removeData(e){this.context.model.removeData(En(e)?e(this.getData()):e)}removeNodeData(e){this.context.model.removeNodeData(En(e)?e(this.getNodeData()):e)}removeEdgeData(e){this.context.model.removeEdgeData(En(e)?e(this.getEdgeData()):e)}removeComboData(e){this.context.model.removeComboData(En(e)?e(this.getComboData()):e)}getElementType(e){return this.context.model.getElementType(e)}getRelatedEdgesData(e,t="both"){return this.context.model.getRelatedEdgesData(e,t)}getNeighborNodesData(e){return this.context.model.getNeighborNodesData(e)}getAncestorsData(e,t){return this.context.model.getAncestorsData(e,t)}getParentData(e,t){return this.context.model.getParentData(e,t)}getChildrenData(e){return this.context.model.getChildrenData(e)}getDescendantsData(e){return this.context.model.getDescendantsData(e)}getElementDataByState(e,t){return this.context.model.getElementDataByState(e,t)}initCanvas(){return kr(this,void 0,void 0,function*(){var e;if(this.context.canvas)return yield this.context.canvas.ready;const{container:t="container",width:n,height:i,renderer:a,cursor:s,background:o,canvas:l,devicePixelRatio:c=(e=globalThis.devicePixelRatio)!==null&&e!==void 0?e:1}=this.options;if(t instanceof Jb)this.context.canvas=t,s&&t.setCursor(s),a&&t.setRenderer(a),yield t.ready;else{const h=dr(t)?document.getElementById(t):t,p=e2(h);this.emit($t.BEFORE_CANVAS_INIT,{container:h,width:n,height:i});const C=Object.assign(Object.assign({},l),{container:h,width:n||p[0],height:i||p[1],background:o,renderer:a,cursor:s,devicePixelRatio:c}),k=new Jb(C);this.context.canvas=k,yield k.ready,this.emit($t.AFTER_CANVAS_INIT,{canvas:k})}})}updateCanvas(e){var t,n;const{renderer:i,cursor:a,height:s,width:o}=e,l=this.context.canvas;l&&(i&&(this.emit($t.BEFORE_RENDERER_CHANGE,{renderer:this.options.renderer}),l.setRenderer(i),this.emit($t.AFTER_RENDERER_CHANGE,{renderer:i})),a&&l.setCursor(a),(un(o)||un(s))&&this.setSize((t=o!=null?o:this.options.width)!==null&&t!==void 0?t:0,(n=s!=null?s:this.options.height)!==null&&n!==void 0?n:0))}initRuntime(){this.context.options=this.options,this.context.batch||(this.context.batch=new G8(this.context)),this.context.plugin||(this.context.plugin=new d6(this.context)),this.context.viewport||(this.context.viewport=new g6(this.context)),this.context.transform||(this.context.transform=new v6(this.context)),this.context.element||(this.context.element=new Q8(this.context)),this.context.animation||(this.context.animation=new j8(this.context)),this.context.layout||(this.context.layout=new u6(this.context)),this.context.behavior||(this.context.behavior=new V8(this.context))}prepare(){return kr(this,void 0,void 0,function*(){if(yield Promise.resolve(),this.destroyed)throw new Error(Vs("The graph instance has been destroyed"));yield this.initCanvas(),this.initRuntime()})}render(){return kr(this,void 0,void 0,function*(){if(yield this.prepare(),wi(this,new mi($t.BEFORE_RENDER)),this.options.layout)if(!this.rendered&&iR(this.options.layout)){const e=yield this.context.element.preLayoutDraw({type:"render"});yield Promise.all([e==null?void 0:e.finished,this.autoFit()])}else{const e=this.context.element.draw({type:"render"});yield Promise.all([e==null?void 0:e.finished,this.context.layout.postLayout()]),yield this.autoFit()}else{const e=this.context.element.draw({type:"render"});yield Promise.all([e==null?void 0:e.finished,this.autoFit()])}this.rendered=!0,wi(this,new mi($t.AFTER_RENDER))})}draw(){return kr(this,void 0,void 0,function*(){var e;yield this.prepare(),yield(e=this.context.element.draw())===null||e===void 0?void 0:e.finished})}layout(e){return kr(this,void 0,void 0,function*(){yield this.context.layout.postLayout(e)})}stopLayout(){this.context.layout.stopLayout()}clear(){return kr(this,void 0,void 0,function*(){const{model:e,element:t}=this.context;e.setData({}),e.clearChanges(),t==null||t.clear()})}destroy(){var e;wi(this,new mi($t.BEFORE_DESTROY));const{layout:t,animation:n,element:i,model:a,canvas:s,behavior:o,plugin:l}=this.context;l==null||l.destroy(),o==null||o.destroy(),t==null||t.destroy(),n==null||n.destroy(),i==null||i.destroy(),a.destroy(),s==null||s.destroy(),this.options={},this.context={},this.off(),(e=globalThis.removeEventListener)===null||e===void 0||e.call(globalThis,"resize",this.onResize),this.destroyed=!0,wi(this,new mi($t.AFTER_DESTROY))}getCanvas(){return this.context.canvas}resize(e,t){var n;const i=e2((n=this.context.canvas)===null||n===void 0?void 0:n.getContainer()),a=[e||i[0],t||i[1]];if(!this.context.canvas)return;const s=this.context.canvas.getSize();si(a,s)||(wi(this,new mi($t.BEFORE_SIZE_CHANGE,{size:a})),this.context.canvas.resize(...a),wi(this,new mi($t.AFTER_SIZE_CHANGE,{size:a})))}fitView(e,t){return kr(this,void 0,void 0,function*(){var n;yield(n=this.context.viewport)===null||n===void 0?void 0:n.fitView(e,t)})}fitCenter(e){return kr(this,void 0,void 0,function*(){var t;yield(t=this.context.viewport)===null||t===void 0?void 0:t.fitCenter({animation:e})})}autoFit(){return kr(this,void 0,void 0,function*(){const{autoFit:e}=this.context.options;if(e)if(dr(e))e==="view"?yield this.fitView():e==="center"&&(yield this.fitCenter());else{const{type:t,animation:n}=e;t==="view"?yield this.fitView(e.options,n):t==="center"&&(yield this.fitCenter(n))}})}focusElement(e,t){return kr(this,void 0,void 0,function*(){var n;yield(n=this.context.viewport)===null||n===void 0?void 0:n.focusElements(Array.isArray(e)?e:[e],{animation:t})})}zoomBy(e,t,n){return kr(this,void 0,void 0,function*(){yield this.context.viewport.transform({mode:"relative",scale:e,origin:n},t)})}zoomTo(e,t,n){return kr(this,void 0,void 0,function*(){this.context.viewport.transform({mode:"absolute",scale:e,origin:n},t)})}getZoom(){return this.context.viewport.getZoom()}rotateBy(e,t,n){return kr(this,void 0,void 0,function*(){yield this.context.viewport.transform({mode:"relative",rotate:e,origin:n},t)})}rotateTo(e,t,n){return kr(this,void 0,void 0,function*(){yield this.context.viewport.transform({mode:"absolute",rotate:e,origin:n},t)})}getRotation(){return this.context.viewport.getRotation()}translateBy(e,t){return kr(this,void 0,void 0,function*(){yield this.context.viewport.transform({mode:"relative",translate:e},t)})}translateTo(e,t){return kr(this,void 0,void 0,function*(){yield this.context.viewport.transform({mode:"absolute",translate:e},t)})}getPosition(){return Or([0,0],this.getCanvasByViewport([0,0]))}translateElementBy(e,t){return kr(this,arguments,void 0,function*(n,i,a=!0){var s,o;const[l,c]=ii(n)?[n,(s=i)!==null&&s!==void 0?s:!0]:[{[n]:i},a];Object.entries(l).forEach(([h,p])=>this.context.model.translateNodeLikeBy(h,p)),yield(o=this.context.element.draw({animation:c,stage:"translate"}))===null||o===void 0?void 0:o.finished})}translateElementTo(e,t){return kr(this,arguments,void 0,function*(n,i,a=!0){var s,o;const[l,c]=ii(n)?[n,(s=i)!==null&&s!==void 0?s:!0]:[{[n]:i},a];Object.entries(l).forEach(([h,p])=>this.context.model.translateNodeLikeTo(h,p)),yield(o=this.context.element.draw({animation:c,stage:"translate"}))===null||o===void 0?void 0:o.finished})}getElementPosition(e){return this.context.model.getElementPosition(e)}getElementRenderStyle(e){return bp(this.context.element.getElement(e).attributes,["context"])}setElementVisibility(e,t){return kr(this,arguments,void 0,function*(n,i,a=!0){var s,o;const[l,c]=ii(n)?[n,(s=i)!==null&&s!==void 0?s:!0]:[{[n]:i},a],h={nodes:[],edges:[],combos:[]};Object.entries(l).forEach(([k,W])=>{const j=this.getElementType(k);h[`${j}s`].push({id:k,style:{visibility:W}})});const{model:p,element:C}=this.context;p.preventUpdateNodeLikeHierarchy(()=>{p.updateData(h)}),yield(o=C.draw({animation:c,stage:"visibility"}))===null||o===void 0?void 0:o.finished})}showElement(e,t){return kr(this,void 0,void 0,function*(){const n=Array.isArray(e)?e:[e];yield this.setElementVisibility(Object.fromEntries(n.map(i=>[i,"visible"])),t)})}hideElement(e,t){return kr(this,void 0,void 0,function*(){const n=Array.isArray(e)?e:[e];yield this.setElementVisibility(Object.fromEntries(n.map(i=>[i,"hidden"])),t)})}getElementVisibility(e){var t,n;const i=this.context.element.getElement(e);return(n=(t=i==null?void 0:i.style)===null||t===void 0?void 0:t.visibility)!==null&&n!==void 0?n:"visible"}setElementZIndex(e,t){return kr(this,void 0,void 0,function*(){var n;const i={nodes:[],edges:[],combos:[]},a=ii(e)?e:{[e]:t};Object.entries(a).forEach(([l,c])=>{const h=this.getElementType(l);i[`${h}s`].push({id:l,style:{zIndex:c}})});const{model:s,element:o}=this.context;s.preventUpdateNodeLikeHierarchy(()=>s.updateData(i)),yield(n=o.draw({animation:!1,stage:"zIndex"}))===null||n===void 0?void 0:n.finished})}frontElement(e){return kr(this,void 0,void 0,function*(){const t=Array.isArray(e)?e:[e],{model:n}=this.context,i={};t.map(a=>{const s=n.getFrontZIndex(a);if(n.getElementType(a)==="combo"){const l=n.getAncestorsData(a,Lr).at(-1)||this.getComboData(a),c=[l,...n.getDescendantsData(wt(l))],h=s-t2(l);c.forEach(C=>{i[wt(C)]=this.getElementZIndex(wt(C))+h});const{internal:p}=Gg(c.map(wt),C=>n.getRelatedEdgesData(C));p.forEach(C=>{const k=wt(C);i[k]=this.getElementZIndex(k)+h})}else i[a]=s}),yield this.setElementZIndex(i)})}getElementZIndex(e){return t2(this.context.model.getElementDataById(e))}setElementState(e,t){return kr(this,arguments,void 0,function*(n,i,a=!0){var s,o;const[l,c]=ii(n)?[n,(s=i)!==null&&s!==void 0?s:!0]:[{[n]:i},a],h=C=>C?Array.isArray(C)?C:[C]:[],p={nodes:[],edges:[],combos:[]};Object.entries(l).forEach(([C,k])=>{const W=this.getElementType(C);p[`${W}s`].push({id:C,states:h(k)})}),this.updateData(p),yield(o=this.context.element.draw({animation:c,stage:"state"}))===null||o===void 0?void 0:o.finished})}getElementState(e){return this.context.model.getElementState(e)}getElementRenderBounds(e){return this.context.element.getElement(e).getRenderBounds()}collapseElement(e){return kr(this,arguments,void 0,function*(t,n=!0){const{model:i,element:a}=this.context;if(xa(i.getNodeLikeData([t])[0])||this.isCollapsingExpanding)return;typeof n=="boolean"&&(n={animation:n,align:!0});const s=i.getElementType(t);yield this.frontElement(t),this.isCollapsingExpanding=!0,this.setElementCollapsibility(t,!0),s==="node"?yield a.collapseNode(t,n):s==="combo"&&(yield a.collapseCombo(t,!!n.animation)),this.isCollapsingExpanding=!1})}expandElement(e){return kr(this,arguments,void 0,function*(t,n=!0){const{model:i,element:a}=this.context;if(!xa(i.getNodeLikeData([t])[0])||this.isCollapsingExpanding)return;typeof n=="boolean"&&(n={animation:n,align:!0});const s=i.getElementType(t);this.isCollapsingExpanding=!0,this.setElementCollapsibility(t,!1),s==="node"?yield a.expandNode(t,n):s==="combo"&&(yield a.expandCombo(t,!!n.animation)),this.isCollapsingExpanding=!1})}setElementCollapsibility(e,t){const n=this.getElementType(e);n==="node"?this.updateNodeData([{id:e,style:{collapsed:t}}]):n==="combo"&&this.updateComboData([{id:e,style:{collapsed:t}}])}toDataURL(){return kr(this,arguments,void 0,function*(e={}){return this.context.canvas.toDataURL(e)})}getCanvasByViewport(e){return this.context.canvas.getCanvasByViewport(e)}getViewportByCanvas(e){return this.context.canvas.getViewportByCanvas(e)}getClientByCanvas(e){return this.context.canvas.getClientByCanvas(e)}getCanvasByClient(e){return this.context.canvas.getCanvasByClient(e)}getViewportCenter(){return this.context.viewport.getViewportCenter()}getCanvasCenter(){return this.context.viewport.getCanvasCenter()}on(e,t,n){return super.on(e,t,n)}once(e,t){return super.once(e,t)}off(e,t){return super.off(e,t)}}Hd.defaultOptions={autoResize:!1,theme:"light",rotation:0,zoom:1,zoomRange:[.01,10]};var p6=function(r,e){var t={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&e.indexOf(n)<0&&(t[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var i=0,n=Object.getOwnPropertySymbols(r);i<n.length;i++)e.indexOf(n[i])<0&&Object.prototype.propertyIsEnumerable.call(r,n[i])&&(t[n[i]]=r[n[i]]);return t};function m6(r,e){const{getNodeData:t=(o,l)=>{if(o.depth=l,!o.children)return o;const{children:c}=o,h=p6(o,["children"]);return Object.assign(Object.assign({},h),{children:c.map(p=>p.id)})},getEdgeData:n=(o,l)=>({source:o.id,target:l.id}),getChildren:i=o=>o.children||[]}=e||{},a=[],s=[];return ol(r,(o,l)=>{a.push(t(o,l));const c=i(o);for(const h of c)s.push(n(o,h))},o=>i(o),"TB"),{nodes:a,edges:s}}class y6 extends Do{beforeDraw(e){const{add:t,update:n}=e,{model:i}=this.context;return[...t.edges.entries(),...n.edges.entries()].forEach(([,a])=>{v2(i,a)}),e}}const v2=(r,e)=>{const{source:t,target:n}=e,i=r.getElementDataById(t),a=r.getElementDataById(n),s=O_(i,p=>r.getParentData(p,Lr)),o=O_(a,p=>r.getParentData(p,Lr)),l=wt(s),c=wt(o),h={sourceNode:l,targetNode:c};return e.style?Object.assign(e.style,h):e.style=h,e},_6=(r,e,t)=>{const[n,i]=e,[a,s]=t;if(i===n)return a;const o=(r-n)/(i-n);return a+o*(s-a)},E6=(r,e,t)=>{const[n,i]=e,[a,s]=t,o=Math.log(r-n+1)/Math.log(i-n+1);return a+o*(s-a)},x6=(r,e,t,n=2)=>{const[i,a]=e,[s,o]=t,l=Math.pow((r-i)/(a-i),n);return s+l*(o-s)},b6=(r,e,t)=>{const[n,i]=e,[a,s]=t,o=Math.sqrt((r-n)/(i-n));return a+o*(s-a)};class jd extends Do{constructor(e,t){super(e,ia({},jd.defaultOptions,t)),this.assignSizeByCentrality=(n,i,a,s,o,l)=>{const c=[i,a],h=[s[0],o[0]],p=[s[1],o[1]],C=[s[2],o[2]],k=(W,j)=>{if(typeof l=="function")return l(W,c,j);switch(l){case"linear":return _6(W,c,j);case"log":return E6(W,c,j);case"pow":return x6(W,c,j,2);case"sqrt":return b6(W,c,j);default:return j[0]}};return[k(n,h),k(n,p),k(n,C)]}}beforeDraw(e){const{model:t}=this.context,n=t.getNodeData(),i=Pa(this.options.maxSize),a=Pa(this.options.minSize),s=this.getCentralities(this.options.centrality),o=s.size>0?Math.max(...s.values()):0,l=s.size>0?Math.min(...s.values()):0;return n.forEach(c=>{var h;const p=this.assignSizeByCentrality(s.get(wt(c))||0,l,o,a,i,this.options.scale),C=(h=this.context.element)===null||h===void 0?void 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e=="string"?document.getElementById(e):e}getSize(){return[this.extends.config.width||0,this.extends.config.height||0]}appendChild(e,t){var n;const i=((n=e.style)===null||n===void 0?void 0:n.$layer)||"main";return this.getLayer(i).appendChild(e,t)}setRenderer(e){if(e===this.extends.renderer)return;const t=qb(e,this.config.enableMultiLayer?Qb:Yb);this.extends.renderers=t,Object.entries(t).forEach(([n,i])=>this.getLayer(n).setRenderer(i)),$b(this.getLayers())}getCanvasByViewport(e){return Ni(this.getLayer().viewport2Canvas(hs(e)))}getViewportByCanvas(e){return Ni(this.getLayer().canvas2Viewport(hs(e)))}getViewportByClient(e){return Ni(this.getLayer().client2Viewport(hs(e)))}getClientByViewport(e){return Ni(this.getLayer().viewport2Client(hs(e)))}getClientByCanvas(e){return this.getClientByViewport(this.getViewportByCanvas(e))}getCanvasByClient(e){const t=this.getLayer(),n=t.client2Viewport(hs(e));return Ni(t.viewport2Canvas(n))}toDataURL(){return Kb(this,arguments,void 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if(n==="overall"){const[Q,ee,re]=j.getPosition(),[ve,he,pe]=j.getFocalPoint();j.setPosition([Q+a,ee+s,re]),j.setFocalPoint([ve+a,he+s,pe])}const K=h.getContextService();return new Promise(Q=>{h.addEventListener(Aa.RERENDER,()=>Kb(this,void 0,void 0,function*(){yield new Promise(re=>setTimeout(re,300));const ee=yield K.toDataURL(i);Q(ee)}))})})}destroy(){Object.values(this.getLayers()).forEach(e=>{e.getCamera().cancelLandmarkAnimation(),e.destroy()})}}function qb(r,e){return Object.fromEntries(e.map(t=>{const n=(r==null?void 0:r(t))||new $c;return n instanceof $c&&n.setConfig({enableDirtyRectangleRendering:!1}),t==="main"?n.registerPlugin(new k8({isDocumentDraggable:!0,isDocumentDroppable:!0,dragstartDistanceThreshold:10,dragstartTimeThreshold:100})):n.unregisterPlugin(n.getPlugin("dom-interaction")),[t,n]}))}function $b(r){Object.entries(r).forEach(([e,t])=>{const n=t.getContextService().getDomElement();n!=null&&n.style&&(n.style.gridArea="1 / 1 / 2 / 2",n.style.outline="none",n.tabIndex=1,e!=="main"&&(n.style.pointerEvents="none")),n!=null&&n.parentElement&&(n.parentElement.style.display="grid")})}const oc=r=>r?parseInt(r):0;function F8(r){const e=getComputedStyle(r),t=r.clientWidth||oc(e.width),n=r.clientHeight||oc(e.height),i=oc(e.paddingLeft)+oc(e.paddingRight),a=oc(e.paddingTop)+oc(e.paddingBottom);return[t-i,n-a]}function e2(r){if(!r)return[0,0];let e=640,t=480;const[n,i]=F8(r);e=n||e,t=i||t;const a=1,s=1;return[Math.max(un(e)?e:a,a),Math.max(un(t)?t:s,s)]}class Rd{constructor(e){this.type=e}}class mi extends Rd{constructor(e,t){super(e),this.data=t}}class Ja extends Rd{constructor(e,t,n,i){super(e),this.animationType=t,this.animation=n,this.data=i}}class lc extends Rd{constructor(e,t,n){super(e),this.elementType=t,this.data=n}}class Id extends Rd{constructor(e,t){super(e),this.data=t}}function wi(r,e){r.emit(e.type,e)}function U8(r){if(!r)return null;if(r instanceof py)return{type:"canvas",element:r};let e=r;for(;e;){if(tu(e))return{type:"node",element:e};if(N_(e))return{type:"edge",element:e};if(Vg(e))return{type:"combo",element:e};e=e.parentElement}return null}function t2(r){var e;return((e=r==null?void 0:r.style)===null||e===void 0?void 0:e.zIndex)||0}const cc="cachedStyle",Nd=r=>`__${r}__`;function W8(r,e){const t=Array.isArray(e)?e:[e];aa(r,cc)||Yc(r,cc,{}),t.forEach(n=>{Yc(aa(r,cc),Nd(n),r.attributes[n])})}function n2(r,e){return aa(r,[cc,Nd(e)])}function H8(r,e){return Nd(e)in(aa(r,cc)||{})}function OW(r,e,t){set(r,[cc,Nd(e)],t)}class j8{constructor(e){this.tasks=[],this.animations=new Set,this.context=e}getTasks(){const e=[...this.tasks];return this.tasks=[],e}add(e,t){this.tasks.push([e,t])}animate(e,t,n){var i,a,s;(i=t==null?void 0:t.before)===null||i===void 0||i.call(t);const o=this.getTasks().map(([c,h])=>{var p,C,k;const{element:W,elementType:j,stage:K}=c,Q=hC(this.context.options,j,K,e);(p=h==null?void 0:h.before)===null||p===void 0||p.call(h);const ee=Q.length?dC(W,this.inferStyle(c,n),Q):null;return ee?((C=h==null?void 0:h.beforeAnimate)===null||C===void 0||C.call(h,ee),ee.finished.then(()=>{var re,ve;(re=h==null?void 0:h.afterAnimate)===null||re===void 0||re.call(h,ee),(ve=h==null?void 0:h.after)===null||ve===void 0||ve.call(h),this.animations.delete(ee)})):(k=h==null?void 0:h.after)===null||k===void 0||k.call(h),ee}).filter(Boolean);o.forEach(c=>this.animations.add(c));const l=ag(o);return l?((a=t==null?void 0:t.beforeAnimate)===null||a===void 0||a.call(t,l),l.finished.then(()=>{var c,h;(c=t==null?void 0:t.afterAnimate)===null||c===void 0||c.call(t,l),(h=t==null?void 0:t.after)===null||h===void 0||h.call(t),this.release()})):(s=t==null?void 0:t.after)===null||s===void 0||s.call(t),l}inferStyle(e,t){var n,i;const{element:a,elementType:s,stage:o,originalStyle:l,updatedStyle:c={}}=e;e.modifiedStyle||(e.modifiedStyle=Object.assign(Object.assign({},l),c));const{modifiedStyle:h}=e,p={},C={};if(o==="enter")Object.assign(p,{opacity:0});else if(o==="exit")Object.assign(C,{opacity:0});else if(o==="show")Object.assign(p,{opacity:0}),Object.assign(C,{opacity:(n=n2(a,"opacity"))!==null&&n!==void 0?n:Wc("opacity")});else if(o==="hide")Object.assign(p,{opacity:(i=n2(a,"opacity"))!==null&&i!==void 0?i:Wc("opacity")}),Object.assign(C,{opacity:0});else if(o==="collapse"){const{collapse:k}=t||{},{target:W,descendants:j,position:K}=k;if(s==="node"){if(j.includes(a.id)){const[Q,ee,re]=K;Object.assign(C,{x:Q,y:ee,z:re})}}else if(s==="combo"){if(a.id===W||j.includes(a.id)){const[Q,ee]=K;Object.assign(C,{x:Q,y:ee,childrenNode:l.childrenNode})}}else s==="edge"&&Object.assign(C,{sourceNode:h.sourceNode,targetNode:h.targetNode})}else if(o==="expand"){const{expand:k}=t||{},{target:W,descendants:j,position:K}=k;if(s==="node"){if(a.id===W||j.includes(a.id)){const[Q,ee,re]=K;Object.assign(p,{x:Q,y:ee,z:re})}}else if(s==="combo"){if(a.id===W||j.includes(a.id)){const[Q,ee,re]=K;Object.assign(p,{x:Q,y:ee,z:re,childrenNode:h.childrenNode})}}else s==="edge"&&Object.assign(p,{sourceNode:h.sourceNode,targetNode:h.targetNode})}return[Object.keys(p).length>0?Object.assign({},l,p):l,Object.keys(C).length>0?Object.assign({},h,C):h]}stop(){this.animations.forEach(e=>e.cancel())}clear(){this.tasks=[]}release(){var e,t;const{canvas:n}=this.context,i=(t=(e=n.document)===null||e===void 0?void 0:e.timeline)===null||t===void 0?void 0:t.animationsWithPromises;i&&(n.document.timeline.animationsWithPromises=i.filter(a=>a.playState!=="finished"))}destroy(){this.stop(),this.animations.clear(),this.tasks=[]}}class G8{constructor(e){this.batchCount=0,this.context=e}emit(e){const{graph:t}=this.context;t.emit(e.type,e)}startBatch(e=!0){this.batchCount++,this.batchCount===1&&this.emit(new mi($t.BATCH_START,{initiate:e}))}endBatch(){this.batchCount--,this.batchCount===0&&this.emit(new mi($t.BATCH_END))}get isBatching(){return this.batchCount>0}destroy(){this.context=null}}class V8 extends Eg{constructor(e){super(e),this.currentTarget=null,this.currentTargetType=null,this.category="behavior",this.forwardCanvasEvents=t=>{const{target:n}=t,i=U8(n);if(!i)return;const{graph:a,canvas:s}=this.context,{type:o,element:l}=i;if("destroyed"in l&&(_f(l)||l.destroyed))return;const{type:c,detail:h,button:p}=t,C=Object.assign(Object.assign({},t),{target:l,targetType:o,originalTarget:n});c===kt.POINTER_MOVE&&(this.currentTarget!==l&&(this.currentTarget&&a.emit(`${this.currentTargetType}:${kt.POINTER_LEAVE}`,Object.assign(Object.assign({},C),{type:kt.POINTER_LEAVE,target:this.currentTarget,targetType:this.currentTargetType})),l&&(Object.assign(C,{type:kt.POINTER_ENTER}),a.emit(`${o}:${kt.POINTER_ENTER}`,C))),this.currentTarget=l,this.currentTargetType=o),c===kt.CLICK&&p===2||(a.emit(`${o}:${c}`,C),a.emit(c,C)),c===kt.CLICK&&h===2&&(Object.assign(C,{type:kt.DBLCLICK}),a.emit(`${o}:${kt.DBLCLICK}`,C),a.emit(kt.DBLCLICK,C)),c===kt.POINTER_DOWN&&p===2&&(Object.assign(C,{type:kt.CONTEXT_MENU,preventDefault:()=>{var k;(k=s.getContainer())===null||k===void 0||k.addEventListener(kt.CONTEXT_MENU,W=>W.preventDefault(),{once:!0})}}),a.emit(`${o}:${kt.CONTEXT_MENU}`,C),a.emit(kt.CONTEXT_MENU,C))},this.forwardContainerEvents=t=>{this.context.graph.emit(t.type,t)},this.forwardEvents(),this.setBehaviors(this.context.options.behaviors||[])}setBehaviors(e){this.setExtensions(e)}forwardEvents(){const e=this.context.canvas.getContainer();e&&[Hl.KEY_DOWN,Hl.KEY_UP].forEach(n=>{e.addEventListener(n,this.forwardContainerEvents)});const t=this.context.canvas.document;t&&[kt.CLICK,kt.DBLCLICK,kt.POINTER_OVER,kt.POINTER_LEAVE,kt.POINTER_ENTER,kt.POINTER_MOVE,kt.POINTER_OUT,kt.POINTER_DOWN,kt.POINTER_UP,kt.CONTEXT_MENU,kt.DRAG_START,kt.DRAG,kt.DRAG_END,kt.DRAG_ENTER,kt.DRAG_OVER,kt.DRAG_LEAVE,kt.DROP,kt.WHEEL].forEach(n=>{t.addEventListener(n,this.forwardCanvasEvents)})}destroy(){const e=this.context.canvas.getContainer();e&&[Hl.KEY_DOWN,Hl.KEY_UP].forEach(t=>{e.removeEventListener(t,this.forwardContainerEvents)}),this.context.canvas.document.removeAllEventListeners(),super.destroy()}}function Z8(r,e){e===void 0&&(e=new Map);var t=[];if(Array.isArray(r))for(var n=0,i=r.length;n<i;n++){var a=r[n];e.has(a)||(t.push(a),e.set(a,!0))}return t}var Mu=function(r,e){var t={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&e.indexOf(n)<0&&(t[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var i=0,n=Object.getOwnPropertySymbols(r);i<n.length;i++)e.indexOf(n[i])<0&&Object.prototype.propertyIsEnumerable.call(r,n[i])&&(t[n[i]]=r[n[i]]);return t};function Lo(r,e){const{data:t,style:n}=r,i=Mu(r,["data","style"]),{data:a,style:s}=e,o=Mu(e,["data","style"]),l=Object.assign(Object.assign({},i),o);return(t||a)&&Object.assign(l,{data:Object.assign(Object.assign({},t),a)}),(n||s)&&Object.assign(l,{style:Object.assign(Object.assign({},n),s)}),l}function v0(r){const{data:e,style:t}=r,i=Mu(r,["data","style"]);return e&&(i.data=Object.assign({},e)),t&&(i.style=Object.assign({},t)),i}function PW(r){return!get(r,["nodes","length"])&&!get(r,["edges","length"])&&!get(r,["combos","length"])}function uc(r={},e={}){const{states:t=[],data:n={},style:i={},children:a=[]}=r,s=Mu(r,["states","data","style","children"]),{states:o=[],data:l={},style:c={},children:h=[]}=e,p=Mu(e,["states","data","style","children"]),C=(W,j)=>W.length!==j.length?!1:W.every((K,Q)=>K===j[Q]),k=(W,j)=>{const K=Object.keys(W),Q=Object.keys(j);return K.length!==Q.length?!1:K.every(ee=>W[ee]===j[ee])};return!(!k(s,p)||!C(a,h)||!C(t,o)||!k(n,l)||!k(i,c))}var K8=function(r,e){var t={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&e.indexOf(n)<0&&(t[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var i=0,n=Object.getOwnPropertySymbols(r);i<n.length;i++)e.indexOf(n[i])<0&&Object.prototype.propertyIsEnumerable.call(r,n[i])&&(t[n[i]]=r[n[i]]);return t};function g0(r){const{id:e=wt(r),style:t,data:n}=r,i=K8(r,["id","style","data"]),a=Object.assign(Object.assign({},r),{style:Object.assign({},t),data:Object.assign({},n)});return xC(r)?Object.assign({id:e,data:a},i):{id:e,data:a}}function Pi(r){return r.data}function X8(r){if(r.hasTreeStructure(Ca))return;r.attachTreeStructure(Ca);const e=r.getAllEdges();for(const t of e){const{source:n,target:i}=t;r.setParent(i,n,Ca)}}class Y8{constructor(){this.latestRemovedComboIds=new Set,this.comboIds=new Set,this.changes=[],this.batchCount=0,this.isTraceless=!1,this.enableUpdateNodeLikeHierarchy=!0,this.model=new ci}pushChange(e){if(this.isTraceless)return;const{type:t}=e;if(t===Gr.NodeUpdated||t===Gr.EdgeUpdated||t===Gr.ComboUpdated){const{value:n,original:i}=e;this.changes.push({value:v0(n),original:v0(i),type:t})}else this.changes.push({value:v0(e.value),type:t})}getChanges(){return this.changes}clearChanges(){this.changes=[]}batch(e){this.batchCount++,this.model.batch(e),this.batchCount--}isBatching(){return this.batchCount>0}silence(e){this.isTraceless=!0,e(),this.isTraceless=!1}isCombo(e){return this.comboIds.has(e)||this.latestRemovedComboIds.has(e)}getData(){return{nodes:this.getNodeData(),edges:this.getEdgeData(),combos:this.getComboData()}}getNodeData(e){return this.model.getAllNodes().reduce((t,n)=>{const i=Pi(n);return this.isCombo(wt(i))||(e===void 0||e.includes(wt(i)))&&t.push(i),t},[])}getEdgeDatum(e){return Pi(this.model.getEdge(e))}getEdgeData(e){return this.model.getAllEdges().reduce((t,n)=>{const i=Pi(n);return(e===void 0||e.includes(wt(i)))&&t.push(i),t},[])}getComboData(e){return this.model.getAllNodes().reduce((t,n)=>{const i=Pi(n);return this.isCombo(wt(i))&&(e===void 0||e.includes(wt(i)))&&t.push(i),t},[])}getRootsData(e=Ca){return this.model.getRoots(e).map(Pi)}getAncestorsData(e,t){const{model:n}=this;return!n.hasNode(e)||!n.hasTreeStructure(t)?[]:n.getAncestors(e,t).map(Pi)}getDescendantsData(e){const t=this.getElementDataById(e),n=[];return ol(t,i=>{i!==t&&n.push(i)},i=>this.getChildrenData(wt(i)),"TB"),n}getParentData(e,t){const{model:n}=this;if(!t){Ea.warn("The hierarchy structure key is not specified");return}if(!n.hasNode(e)||!n.hasTreeStructure(t))return;const i=n.getParent(e,t);return i?Pi(i):void 0}getChildrenData(e){const t=this.getElementType(e)==="node"?Ca:Lr,{model:n}=this;return!n.hasNode(e)||!n.hasTreeStructure(t)?[]:n.getChildren(e,t).map(Pi)}getElementsDataByType(e){return e==="node"?this.getNodeData():e==="edge"?this.getEdgeData():e==="combo"?this.getComboData():[]}getElementDataById(e){return this.getElementType(e)==="edge"?this.getEdgeDatum(e):this.getNodeLikeDatum(e)}getNodeLikeDatum(e){const t=this.model.getNode(e);return Pi(t)}getNodeLikeData(e){return this.model.getAllNodes().reduce((t,n)=>{const i=Pi(n);return e?e.includes(wt(i))&&t.push(i):t.push(i),t},[])}getElementDataByState(e,t){return this.getElementsDataByType(e).filter(i=>{var a;return(a=i.states)===null||a===void 0?void 0:a.includes(t)})}getElementState(e){var t;return((t=this.getElementDataById(e))===null||t===void 0?void 0:t.states)||[]}hasNode(e){return this.model.hasNode(e)&&!this.isCombo(e)}hasEdge(e){return this.model.hasEdge(e)}hasCombo(e){return this.model.hasNode(e)&&this.isCombo(e)}getRelatedEdgesData(e,t="both"){return this.model.getRelatedEdges(e,t).map(Pi)}getNeighborNodesData(e){return this.model.getNeighbors(e).map(Pi)}setData(e){const{nodes:t=[],edges:n=[],combos:i=[]}=e,{nodes:a,edges:s,combos:o}=this.getData(),l=po(a,t,p=>wt(p),uc),c=po(s,n,p=>wt(p),uc),h=po(o,i,p=>wt(p),uc);this.batch(()=>{const p={nodes:l.enter,edges:c.enter,combos:h.enter};this.addData(p),this.computeZIndex(p,"add",!0);const C={nodes:l.update,edges:c.update,combos:h.update};this.updateData(C),this.computeZIndex(C,"update",!0);const k={nodes:l.exit.map(wt),edges:c.exit.map(wt),combos:h.exit.map(wt)};this.removeData(k)})}addData(e){const{nodes:t,edges:n,combos:i}=e;this.batch(()=>{this.addComboData(i),this.addNodeData(t),this.addEdgeData(n)}),this.computeZIndex(e,"add")}addNodeData(e=[]){e.length&&(this.model.addNodes(e.map(t=>(this.pushChange({value:t,type:Gr.NodeAdded}),g0(t)))),this.updateNodeLikeHierarchy(e),this.computeZIndex({nodes:e},"add"))}addEdgeData(e=[]){e.length&&(this.model.addEdges(e.map(t=>(this.pushChange({value:t,type:Gr.EdgeAdded}),g0(t)))),this.computeZIndex({edges:e},"add"))}addComboData(e=[]){if(!e.length)return;const{model:t}=this;t.hasTreeStructure(Lr)||t.attachTreeStructure(Lr),t.addNodes(e.map(n=>(this.comboIds.add(wt(n)),this.pushChange({value:n,type:Gr.ComboAdded}),g0(n)))),this.updateNodeLikeHierarchy(e),this.computeZIndex({combos:e},"add")}addChildrenData(e,t){const n=this.getNodeLikeDatum(e),i=t.map(wt);this.addNodeData(t),this.updateNodeData([{id:e,children:[...n.children||[],...i]}]),this.addEdgeData(i.map(a=>({source:e,target:a})))}computeZIndex(e,t,n=!1){!n&&this.isBatching()||this.batch(()=>{const{nodes:i=[],edges:a=[],combos:s=[]}=e;s.forEach(o=>{var l,c,h;const p=wt(o);if(t==="add"&&un((l=o.style)===null||l===void 0?void 0:l.zIndex)||t==="update"&&!("combo"in o))return;const C=this.getParentData(p,Lr),k=C?((h=(c=C.style)===null||c===void 0?void 0:c.zIndex)!==null&&h!==void 0?h:0)+1:0;this.preventUpdateNodeLikeHierarchy(()=>{this.updateComboData([{id:p,style:{zIndex:k}}])})}),i.forEach(o=>{var l,c,h;const p=wt(o);if(t==="add"&&un((l=o.style)===null||l===void 0?void 0:l.zIndex)||t==="update"&&!("combo"in o)&&!("children"in o))return;let C=0;const k=this.getParentData(p,Lr);if(k)C=(((c=k.style)===null||c===void 0?void 0:c.zIndex)||0)+1;else{const W=this.getParentData(p,Ca);W&&(C=((h=W==null?void 0:W.style)===null||h===void 0?void 0:h.zIndex)||0)}this.preventUpdateNodeLikeHierarchy(()=>{this.updateNodeData([{id:p,style:{zIndex:C}}])})}),a.forEach(o=>{var l,c,h,p,C;if(un((l=o.style)===null||l===void 0?void 0:l.zIndex))return;let{id:k,source:W,target:j}=o;if(!k)k=wt(o);else{const ee=this.getEdgeDatum(k);W=ee.source,j=ee.target}if(!W||!j)return;const K=((h=(c=this.getNodeLikeDatum(W))===null||c===void 0?void 0:c.style)===null||h===void 0?void 0:h.zIndex)||0,Q=((C=(p=this.getNodeLikeDatum(j))===null||p===void 0?void 0:p.style)===null||C===void 0?void 0:C.zIndex)||0;this.updateEdgeData([{id:wt(o),style:{zIndex:Math.max(K,Q)-1}}])})})}getFrontZIndex(e){var t;const n=this.getElementType(e),i=this.getElementDataById(e),a=this.getData();if(Object.assign(a,{[`${n}s`]:a[`${n}s`].filter(s=>wt(s)!==e)}),n==="combo"&&!xa(i)){const s=new Set(this.getAncestorsData(e,Lr).map(wt));a.nodes=a.nodes.filter(o=>!s.has(wt(o))),a.combos=a.combos.filter(o=>!s.has(wt(o))),a.edges=a.edges.filter(({source:o,target:l})=>!s.has(o)&&!s.has(l))}return Math.max(((t=i.style)===null||t===void 0?void 0:t.zIndex)||0,0,...Object.values(a).flat().map(s=>{var o;return(((o=s==null?void 0:s.style)===null||o===void 0?void 0:o.zIndex)||0)+1}))}updateNodeLikeHierarchy(e){if(!this.enableUpdateNodeLikeHierarchy)return;const{model:t}=this;e.forEach(n=>{const i=wt(n),a=Wh(n);a!==void 0&&(t.hasTreeStructure(Lr)||t.attachTreeStructure(Lr),a===null&&this.refreshComboData(i),this.setParent(i,Wh(n),Lr));const s=n.children||[];if(s.length){t.hasTreeStructure(Ca)||t.attachTreeStructure(Ca);const o=s.filter(l=>t.hasNode(l));o.forEach(l=>this.setParent(l,i,Ca)),o.length!==s.length&&this.updateNodeData([{id:i,children:o}])}})}preventUpdateNodeLikeHierarchy(e){this.enableUpdateNodeLikeHierarchy=!1,e(),this.enableUpdateNodeLikeHierarchy=!0}updateData(e){const{nodes:t,edges:n,combos:i}=e;this.batch(()=>{this.updateNodeData(t),this.updateComboData(i),this.updateEdgeData(n)}),this.computeZIndex(e,"update")}updateNodeData(e=[]){if(!e.length)return;const{model:t}=this;this.batch(()=>{const n=[];e.forEach(i=>{const a=wt(i),s=Pi(t.getNode(a));if(uc(s,i))return;const o=Lo(s,i);this.pushChange({value:o,original:s,type:Gr.NodeUpdated}),t.mergeNodeData(a,o),n.push(o)}),this.updateNodeLikeHierarchy(n)}),this.computeZIndex({nodes:e},"update")}refreshData(){const{nodes:e,edges:t,combos:n}=this.getData();e.forEach(i=>{this.pushChange({value:i,original:i,type:Gr.NodeUpdated})}),t.forEach(i=>{this.pushChange({value:i,original:i,type:Gr.EdgeUpdated})}),n.forEach(i=>{this.pushChange({value:i,original:i,type:Gr.ComboUpdated})})}syncNodeLikeDatum(e){const{model:t}=this,n=wt(e);if(!t.hasNode(n))return;const i=Pi(t.getNode(n)),a=Lo(i,e);t.mergeNodeData(n,a)}syncEdgeDatum(e){const{model:t}=this,n=wt(e);if(!t.hasEdge(n))return;const i=Pi(t.getEdge(n)),a=Lo(i,e);t.mergeEdgeData(n,a)}updateEdgeData(e=[]){if(!e.length)return;const{model:t}=this;this.batch(()=>{e.forEach(n=>{const i=wt(n),a=Pi(t.getEdge(i));if(uc(a,n))return;n.source&&a.source!==n.source&&t.updateEdgeSource(i,n.source),n.target&&a.target!==n.target&&t.updateEdgeTarget(i,n.target);const s=Lo(a,n);this.pushChange({value:s,original:a,type:Gr.EdgeUpdated}),t.mergeEdgeData(i,s)})}),this.computeZIndex({edges:e},"update")}updateComboData(e=[]){if(!e.length)return;const{model:t}=this;t.batch(()=>{const n=[];e.forEach(i=>{const a=wt(i),s=Pi(t.getNode(a));if(uc(s,i))return;const o=Lo(s,i);this.pushChange({value:o,original:s,type:Gr.ComboUpdated}),t.mergeNodeData(a,o),n.push(o)}),this.updateNodeLikeHierarchy(n)}),this.computeZIndex({combos:e},"update")}setParent(e,t,n,i=!0){if(e===t)return;const a=this.getNodeLikeDatum(e),s=Wh(a);if(s!==t&&n===Lr){const o={id:e,combo:t};this.isCombo(e)?this.syncNodeLikeDatum(o):this.syncNodeLikeDatum(o)}this.model.setParent(e,t,n),i&&n===Lr&&Z8([s,t]).forEach(o=>{o!==void 0&&this.refreshComboData(o)})}refreshComboData(e){const t=this.getComboData([e])[0],n=this.getAncestorsData(e,Lr);t&&this.pushChange({value:t,original:t,type:Gr.ComboUpdated}),n.forEach(i=>{this.pushChange({value:i,original:i,type:Gr.ComboUpdated})})}getElementPosition(e){const t=this.getElementDataById(e);return xi(t)}translateNodeLikeBy(e,t){this.isCombo(e)?this.translateComboBy(e,t):this.translateNodeBy(e,t)}translateNodeLikeTo(e,t){this.isCombo(e)?this.translateComboTo(e,t):this.translateNodeTo(e,t)}translateNodeBy(e,t){const n=this.getElementPosition(e),i=Jn(n,[...t,0].slice(0,3));this.translateNodeTo(e,i)}translateNodeTo(e,t){const[n=0,i=0,a=0]=t;this.preventUpdateNodeLikeHierarchy(()=>{this.updateNodeData([{id:e,style:{x:n,y:i,z:a}}])})}translateComboBy(e,t){const[n=0,i=0,a=0]=t;if([n,i,a].some(isNaN)||[n,i,a].every(l=>l===0))return;const s=this.getComboData([e])[0];if(!s)return;const o=new Set;ol(s,l=>{const c=wt(l);if(o.has(c))return;o.add(c);const[h,p,C]=xi(l),k=Lo(l,{style:{x:h+n,y:p+i,z:C+a}});this.pushChange({value:k,original:l,type:this.isCombo(c)?Gr.ComboUpdated:Gr.NodeUpdated}),this.model.mergeNodeData(c,k)},l=>this.getChildrenData(wt(l)),"BT")}translateComboTo(e,t){var n;if(t.some(isNaN))return;const[i=0,a=0,s=0]=t,o=(n=this.getComboData([e]))===null||n===void 0?void 0:n[0];if(!o)return;const[l,c,h]=xi(o),p=i-l,C=a-c,k=s-h;ol(o,W=>{const j=wt(W),[K,Q,ee]=xi(W),re=Lo(W,{style:{x:K+p,y:Q+C,z:ee+k}});this.pushChange({value:re,original:W,type:this.isCombo(j)?Gr.ComboUpdated:Gr.NodeUpdated}),this.model.mergeNodeData(j,re)},W=>this.getChildrenData(wt(W)),"BT")}removeData(e){const{nodes:t,edges:n,combos:i}=e;this.batch(()=>{this.removeEdgeData(n),this.removeNodeData(t),this.removeComboData(i),this.latestRemovedComboIds=new Set(i)})}removeNodeData(e=[]){e.length&&this.batch(()=>{e.forEach(t=>{this.removeEdgeData(this.getRelatedEdgesData(t).map(wt)),this.pushChange({value:this.getNodeData([t])[0],type:Gr.NodeRemoved}),this.removeNodeLikeHierarchy(t)}),this.model.removeNodes(e)})}removeEdgeData(e=[]){e.length&&(e.forEach(t=>this.pushChange({value:this.getEdgeData([t])[0],type:Gr.EdgeRemoved})),this.model.removeEdges(e))}removeComboData(e=[]){e.length&&this.batch(()=>{e.forEach(t=>{this.pushChange({value:this.getComboData([t])[0],type:Gr.ComboRemoved}),this.removeNodeLikeHierarchy(t),this.comboIds.delete(t)}),this.model.removeNodes(e)})}removeNodeLikeHierarchy(e){if(this.model.hasTreeStructure(Lr)){const t=Wh(this.getNodeLikeDatum(e));this.setParent(e,void 0,Lr,!1),this.model.getChildren(e,Lr).forEach(n=>{const i=Pi(n),a=wt(i);this.setParent(wt(i),t,Lr,!1);const s=Lo(i,{id:wt(i),combo:t});this.pushChange({value:s,original:i,type:this.isCombo(a)?Gr.ComboUpdated:Gr.NodeUpdated}),this.model.mergeNodeData(wt(i),s)}),Rn(t)||this.refreshComboData(t)}}getElementType(e){if(this.model.hasNode(e))return this.isCombo(e)?"combo":"node";if(this.model.hasEdge(e))return"edge";throw new Error(Vs(`Unknown element type of id: ${e}`))}destroy(){const{model:e}=this,t=e.getAllNodes(),n=e.getAllEdges();e.removeEdges(n.map(i=>i.id)),e.removeNodes(t.map(i=>i.id)),this.context={}}}var Su=function(r,e,t,n){function i(a){return a instanceof t?a:new t(function(s){s(a)})}return new(t||(t=Promise))(function(a,s){function o(h){try{c(n.next(h))}catch(p){s(p)}}function l(h){try{c(n.throw(h))}catch(p){s(p)}}function c(h){h.done?a(h.value):i(h.value).then(o,l)}c((n=n.apply(r,e||[])).next())})};class Q8{constructor(e){this.elementMap={},this.shapeTypeMap={},this.paletteStyle={},this.defaultStyle={},this.stateStyle={},this.visibilityCache=new WeakMap,this.context=e}init(){this.initContainer()}initContainer(){if(!this.container||this.container.destroyed){const{canvas:e}=this.context;this.container=e.appendChild(new Ei({className:"elements"}))}}emit(e,t){t.silence||wi(this.context.graph,e)}forEachElementData(e){sl.forEach(t=>{const n=this.context.model.getElementsDataByType(t);e(t,n)})}getElementType(e,t){var n;const{options:i,graph:a}=this.context,s=((n=i[e])===null||n===void 0?void 0:n.type)||t.type;return s?typeof s=="string"?s:s.call(a,t):e==="edge"?"line":"circle"}getTheme(e){return Uy(this.context.options)[e]||{}}getThemeStyle(e){return this.getTheme(e).style||{}}getThemeStateStyle(e,t){const{state:n={}}=this.getTheme(e);return Object.assign({},...t.map(i=>n[i]||{}))}computePaletteStyle(){const{options:e}=this.context;this.paletteStyle={},this.forEachElementData((t,n)=>{var i,a;const s=Object.assign({},q1((i=this.getTheme(t))===null||i===void 0?void 0:i.palette),q1((a=e[t])===null||a===void 0?void 0:a.palette));s!=null&&s.field&&Object.assign(this.paletteStyle,IP(n,s))})}getPaletteStyle(e,t){const n=this.paletteStyle[t];return n?e==="edge"?{stroke:n}:{fill:n}:{}}computeElementDefaultStyle(e,t){var n;const{options:i}=this.context,a=((n=i[e])===null||n===void 0?void 0:n.style)||{};"transform"in a&&Array.isArray(a.transform)&&(a.transform=[...a.transform]),this.defaultStyle[wt(t.datum)]=J1(a,t)}computeElementsDefaultStyle(e){const{graph:t}=this.context;this.forEachElementData((n,i)=>{const a=i.length;for(let s=0;s<a;s++){const o=i[s];(e===void 0||e.includes(wt(o)))&&this.computeElementDefaultStyle(n,{datum:o,graph:t})}})}getDefaultStyle(e){return this.defaultStyle[e]||{}}getElementState(e){try{const{model:t}=this.context;return t.getElementState(e)}catch(t){return[]}}getElementStateStyle(e,t,n){var i,a;const{options:s}=this.context,o=((a=(i=s[e])===null||i===void 0?void 0:i.state)===null||a===void 0?void 0:a[t])||{};return J1(o,n)}computeElementStatesStyle(e,t,n){this.stateStyle[wt(n.datum)]=Object.assign({},...t.map(i=>this.getElementStateStyle(e,i,n)))}computeElementsStatesStyle(e){const{graph:t}=this.context;this.forEachElementData((n,i)=>{const a=i.length;for(let s=0;s<a;s++){const o=i[s];if(e===void 0||e.includes(wt(o))){const l=this.getElementState(wt(o));this.computeElementStatesStyle(n,l,{datum:o,graph:t})}}})}getStateStyle(e){return this.stateStyle[e]||{}}computeStyle(e,t){e&&["translate","zIndex"].includes(e)||(this.computePaletteStyle(),this.computeElementsDefaultStyle(t),this.computeElementsStatesStyle(t))}getElement(e){return this.elementMap[e]}getNodes(){return this.context.model.getNodeData().map(({id:e})=>this.elementMap[e])}getEdges(){return this.context.model.getEdgeData().map(e=>this.elementMap[wt(e)])}getCombos(){return this.context.model.getComboData().map(({id:e})=>this.elementMap[e])}getElementComputedStyle(e,t){const n=wt(t),i=this.getThemeStyle(e),a=this.getPaletteStyle(e,n),s=t.style||{},o=this.getDefaultStyle(n),l=this.getThemeStateStyle(e,this.getElementState(n)),c=this.getStateStyle(n),h=Object.assign({},i,a,s,o,l,c);if(e==="combo"){const p=this.context.model.getChildrenData(n),k=!!h.collapsed?[]:p.map(wt).filter(W=>this.getElement(W));Object.assign(h,{childrenNode:k,childrenData:p})}return h}getDrawData(e){this.init();const t=this.computeChangesAndDrawData(e);if(!t)return null;const{type:n="draw",stage:i=n}=e;return this.markDestroyElement(t.drawData),this.computeStyle(i),{type:n,stage:i,data:t}}draw(e={animation:!0}){const t=this.getDrawData(e);if(!t)return;const{data:{drawData:{add:n,update:i,remove:a}}}=t;return this.destroyElements(a,e),this.createElements(n,e),this.updateElements(i,e),this.setAnimationTask(e,t)}preLayoutDraw(){return Su(this,arguments,void 0,function*(e={animation:!0}){var t,n;const i=this.getDrawData(e);if(!i)return;const{data:{drawData:a}}=i;yield(n=(t=this.context.layout)===null||t===void 0?void 0:t.preLayout)===null||n===void 0?void 0:n.call(t,a);const{add:s,update:o,remove:l}=a;return this.destroyElements(l,e),this.createElements(s,e),this.updateElements(o,e),this.setAnimationTask(e,i)})}setAnimationTask(e,t){const{animation:n,silence:i}=e,{data:{dataChanges:a,drawData:s},stage:o,type:l}=t;return this.context.animation.animate(n,i?{}:{before:()=>this.emit(new mi($t.BEFORE_DRAW,{dataChanges:a,animation:n,stage:o,render:l==="render"}),e),beforeAnimate:c=>this.emit(new Ja($t.BEFORE_ANIMATE,_a.DRAW,c,s),e),afterAnimate:c=>this.emit(new Ja($t.AFTER_ANIMATE,_a.DRAW,c,s),e),after:()=>this.emit(new mi($t.AFTER_DRAW,{dataChanges:a,animation:n,stage:o,render:l==="render",firstRender:this.context.graph.rendered===!1}),e)})}computeChangesAndDrawData(e){const{model:t}=this.context,n=t.getChanges(),i=Cp(n);if(i.length===0)return null;const{NodeAdded:a=[],NodeUpdated:s=[],NodeRemoved:o=[],EdgeAdded:l=[],EdgeUpdated:c=[],EdgeRemoved:h=[],ComboAdded:p=[],ComboUpdated:C=[],ComboRemoved:k=[]}=Ah(i,Q=>Q.type),W=Q=>new Map(Q.map(ee=>{const re=ee.value;return[wt(re),re]})),j={add:{nodes:W(a),edges:W(l),combos:W(p)},update:{nodes:W(s),edges:W(c),combos:W(C)},remove:{nodes:W(o),edges:W(h),combos:W(k)}},K=this.transformData(j,e);return t.clearChanges(),{dataChanges:n,drawData:K}}transformData(e,t){const n=this.context.transform.getTransformInstance();return Object.values(n).reduce((i,a)=>a.beforeDraw(i,t),e)}createElement(e,t,n){var i;const a=wt(t);if(this.getElement(a))return;const o=this.getElementType(e,t),l=this.getElementComputedStyle(e,t),c=Gs(e,o);if(!c)return Ea.warn(`The element ${o} of ${e} is not registered.`);this.emit(new lc($t.BEFORE_ELEMENT_CREATE,e,t),n);const h=this.container.appendChild(new c({id:a,context:this.context,style:l}));this.shapeTypeMap[a]=o,this.elementMap[a]=h;const{stage:p="enter"}=n;(i=this.context.animation)===null||i===void 0||i.add({element:h,elementType:e,stage:p,originalStyle:Object.assign({},h.attributes),updatedStyle:l},{after:()=>{var C;this.emit(new lc($t.AFTER_ELEMENT_CREATE,e,t),n),(C=h.onCreate)===null||C===void 0||C.call(h)}})}createElements(e,t){const{nodes:n,edges:i,combos:a}=e;[["node",n],["combo",a],["edge",i]].forEach(([o,l])=>{l.forEach(c=>this.createElement(o,c,t))})}getUpdateStageStyle(e,t,n){const{stage:i="update"}=n;if(i==="translate")if(e==="node"||e==="combo"){const{style:{x:a=0,y:s=0,z:o=0}={}}=t;return{x:a,y:s,z:o}}else return{};return this.getElementComputedStyle(e,t)}updateElement(e,t,n){var i;const a=wt(t),{stage:s="update"}=n,o=this.getElement(a);if(!o)return()=>null;this.emit(new lc($t.BEFORE_ELEMENT_UPDATE,e,t),n);const l=this.getElementType(e,t),c=this.getUpdateStageStyle(e,t,n);this.shapeTypeMap[a]!==l&&(o.destroy(),delete this.shapeTypeMap[a],delete this.elementMap[a],this.createElement(e,t,{animation:!1,silence:!0}));const h=s!=="visibility"?s:c.visibility==="hidden"?"hide":"show";h==="hide"&&delete c.visibility,(i=this.context.animation)===null||i===void 0||i.add({element:o,elementType:e,stage:h,originalStyle:Object.assign({},o.attributes),updatedStyle:c},{before:()=>{const p=this.elementMap[a];s!=="collapse"&&Yg(p,c),s==="visibility"&&(H8(p,"opacity")||W8(p,"opacity"),this.visibilityCache.set(p,h==="show"?"visible":"hidden"),h==="show"&&il(p,"visible"))},after:()=>{var p;const C=this.elementMap[a];s==="collapse"&&Yg(C,c),h==="hide"&&il(C,this.visibilityCache.get(C)),this.emit(new lc($t.AFTER_ELEMENT_UPDATE,e,t),n),(p=C.onUpdate)===null||p===void 0||p.call(C)}})}updateElements(e,t){const{nodes:n,edges:i,combos:a}=e;[["node",n],["combo",a],["edge",i]].forEach(([o,l])=>{l.forEach(c=>this.updateElement(o,c,t))})}markDestroyElement(e){Object.values(e.remove).forEach(t=>{t.forEach(n=>{const i=wt(n),a=this.getElement(i);a&&KL(a)})})}destroyElement(e,t,n){var i;const{stage:a="exit"}=n,s=wt(t),o=this.elementMap[s];if(!o)return()=>null;this.emit(new lc($t.BEFORE_ELEMENT_DESTROY,e,t),n),(i=this.context.animation)===null||i===void 0||i.add({element:o,elementType:e,stage:a,originalStyle:Object.assign({},o.attributes),updatedStyle:{}},{after:()=>{var l;this.clearElement(s),o.destroy(),(l=o.onDestroy)===null||l===void 0||l.call(o),this.emit(new lc($t.AFTER_ELEMENT_DESTROY,e,t),n)}})}destroyElements(e,t){const{nodes:n,edges:i,combos:a}=e;[["combo",a],["edge",i],["node",n]].forEach(([o,l])=>{l.forEach(c=>this.destroyElement(o,c,t))})}clearElement(e){delete this.paletteStyle[e],delete this.defaultStyle[e],delete this.stateStyle[e],delete this.elementMap[e],delete this.shapeTypeMap[e]}alignLayoutResultToElement(e,t){var n,i;const a=(n=e.nodes)===null||n===void 0?void 0:n.find(s=>wt(s)===t);if(a){const s=xi(this.context.model.getNodeLikeDatum(t)),o=xi(a),l=Or(s,o);(i=e.nodes)===null||i===void 0||i.forEach(c=>{var h,p,C;!((h=c.style)===null||h===void 0)&&h.x&&(c.style.x+=l[0]),!((p=c.style)===null||p===void 0)&&p.y&&(c.style.y+=l[1]),!((C=c.style)===null||C===void 0)&&C.z&&(c.style.z+=l[2]||0)})}}collapseNode(e,t){return Su(this,void 0,void 0,function*(){var n;const{animation:i,align:a}=t,{model:s,layout:o}=this.context,l=this.computeChangesAndDrawData({stage:"collapse",animation:i});if(!l)return;this.markDestroyElement(l.drawData);const c=yield o.simulate();a&&this.alignLayoutResultToElement(c,e),s.updateData(c);const h=this.computeChangesAndDrawData({stage:"collapse",animation:i});if(!h)return;const{drawData:p}=h,{add:C,remove:k,update:W}=p;this.markDestroyElement(p);const j={animation:i,stage:"collapse",data:p};this.destroyElements(k,j),this.createElements(C,j),this.updateElements(W,j),yield(n=this.context.animation.animate(i,{beforeAnimate:K=>this.emit(new Ja($t.BEFORE_ANIMATE,_a.COLLAPSE,K,p),j),afterAnimate:K=>this.emit(new Ja($t.AFTER_ANIMATE,_a.COLLAPSE,K,p),j)},{collapse:{target:e,descendants:Array.from(k.nodes).map(([,K])=>wt(K)),position:xi(W.nodes.get(e))}}))===null||n===void 0?void 0:n.finished})}expandNode(e,t){return Su(this,void 0,void 0,function*(){var n;const{model:i,layout:a}=this.context,{animation:s,align:o}=t,l=xi(i.getNodeData([e])[0]),c=this.computeChangesAndDrawData({stage:"expand",animation:s});if(!c)return;const{drawData:{add:h}}=c;this.createElements(h,{animation:!1,stage:"expand",target:e}),this.context.animation.clear();const p=yield a.simulate();o&&this.alignLayoutResultToElement(p,e),i.updateData(p),this.computeStyle("expand");const C=this.computeChangesAndDrawData({stage:"collapse",animation:s});if(!C)return;const{drawData:k}=C,{update:W}=k,j={animation:s,stage:"expand",data:k};h.edges.forEach(K=>W.edges.set(wt(K),K)),h.nodes.forEach(K=>W.nodes.set(wt(K),K)),this.updateElements(W,j),yield(n=this.context.animation.animate(s,{beforeAnimate:K=>this.emit(new Ja($t.BEFORE_ANIMATE,_a.EXPAND,K,k),j),afterAnimate:K=>this.emit(new Ja($t.AFTER_ANIMATE,_a.EXPAND,K,k),j)},{expand:{target:e,descendants:Array.from(h.nodes).map(([,K])=>wt(K)),position:l}}))===null||n===void 0?void 0:n.finished})}collapseCombo(e,t){return Su(this,void 0,void 0,function*(){var n;const{model:i,element:a}=this.context;if(i.getAncestorsData(e,Lr).some(j=>xa(j)))return;const s=a.getElement(e),o=s.getComboPosition(Object.assign(Object.assign({},s.attributes),{collapsed:!0})),l=this.computeChangesAndDrawData({stage:"collapse",animation:t});if(!l)return;const{dataChanges:c,drawData:h}=l;this.markDestroyElement(h);const{update:p,remove:C}=h,k={animation:t,stage:"collapse",data:h};this.destroyElements(C,k),this.updateElements(p,k);const W=j=>Array.from(j).map(([,K])=>wt(K));yield(n=this.context.animation.animate(t,{before:()=>this.emit(new mi($t.BEFORE_DRAW,{dataChanges:c,animation:t}),k),beforeAnimate:j=>this.emit(new Ja($t.BEFORE_ANIMATE,_a.COLLAPSE,j,h),k),afterAnimate:j=>this.emit(new Ja($t.AFTER_ANIMATE,_a.COLLAPSE,j,h),k),after:()=>this.emit(new mi($t.AFTER_DRAW,{dataChanges:c,animation:t}),k)},{collapse:{target:e,descendants:[...W(C.nodes),...W(C.combos)],position:o}}))===null||n===void 0?void 0:n.finished})}expandCombo(e,t){return Su(this,void 0,void 0,function*(){var n;const{model:i}=this.context,a=xi(i.getComboData([e])[0]);this.computeStyle("expand");const s=this.computeChangesAndDrawData({stage:"expand",animation:t});if(!s)return;const{dataChanges:o,drawData:l}=s,{add:c,update:h}=l,p={animation:t,stage:"expand",data:l,target:e};this.createElements(c,p),this.updateElements(h,p);const C=k=>Array.from(k).map(([,W])=>wt(W));yield(n=this.context.animation.animate(t,{before:()=>this.emit(new mi($t.BEFORE_DRAW,{dataChanges:o,animation:t}),p),beforeAnimate:k=>this.emit(new Ja($t.BEFORE_ANIMATE,_a.EXPAND,k,l),p),afterAnimate:k=>this.emit(new Ja($t.AFTER_ANIMATE,_a.EXPAND,k,l),p),after:()=>this.emit(new mi($t.AFTER_DRAW,{dataChanges:o,animation:t}),p)},{expand:{target:e,descendants:[...C(c.nodes),...C(c.combos)],position:a}}))===null||n===void 0?void 0:n.finished})}clear(){this.container.destroy(),this.initContainer(),this.elementMap={},this.shapeTypeMap={},this.defaultStyle={},this.stateStyle={},this.paletteStyle={}}destroy(){this.clear(),this.container.destroy(),this.context={}}}const r2=Symbol("Comlink.proxy"),J8=Symbol("Comlink.endpoint"),i2=Symbol("Comlink.releaseProxy"),p0=Symbol("Comlink.finalizer"),Bd=Symbol("Comlink.thrown"),a2=r=>typeof r=="object"&&r!==null||typeof r=="function",q8={canHandle:r=>a2(r)&&r[r2],serialize(r){const{port1:e,port2:t}=new MessageChannel;return o2(r,e),[t,[t]]},deserialize(r){return r.start(),c2(r)}},$8={canHandle:r=>a2(r)&&Bd in r,serialize({value:r}){let e;return r instanceof Error?e={isError:!0,value:{message:r.message,name:r.name,stack:r.stack}}:e={isError:!1,value:r},[e,[]]},deserialize(r){throw r.isError?Object.assign(new Error(r.value.message),r.value):r.value}},s2=new Map([["proxy",q8],["throw",$8]]);function e6(r,e){for(const t of r)if(e===t||t==="*"||t instanceof RegExp&&t.test(e))return!0;return!1}function o2(r,e=globalThis,t=["*"]){e.addEventListener("message",function n(i){if(!i||!i.data)return;if(!e6(t,i.origin)){console.warn(`Invalid origin '${i.origin}' for comlink proxy`);return}const{id:a,type:s,path:o}=Object.assign({path:[]},i.data),l=(i.data.argumentList||[]).map(xl);let c;try{const h=o.slice(0,-1).reduce((C,k)=>C[k],r),p=o.reduce((C,k)=>C[k],r);switch(s){case"GET":c=p;break;case"SET":h[o.slice(-1)[0]]=xl(i.data.value),c=!0;break;case"APPLY":c=p.apply(h,l);break;case"CONSTRUCT":{const C=new p(...l);c=s6(C)}break;case"ENDPOINT":{const{port1:C,port2:k}=new MessageChannel;o2(r,k),c=a6(C,[C])}break;case"RELEASE":c=void 0;break;default:return}}catch(h){c={value:h,[Bd]:0}}Promise.resolve(c).catch(h=>({value:h,[Bd]:0})).then(h=>{const[p,C]=Ud(h);e.postMessage(Object.assign(Object.assign({},p),{id:a}),C),s==="RELEASE"&&(e.removeEventListener("message",n),l2(e),p0 in r&&typeof r[p0]=="function"&&r[p0]())}).catch(h=>{const[p,C]=Ud({value:new 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Proxy(n,{get(s,o){if(kd(i),o===i2)return()=>{r6(a),u2(r),e.clear(),i=!0};if(o==="then"){if(t.length===0)return{then:()=>a};const l=hc(r,e,{type:"GET",path:t.map(c=>c.toString())}).then(xl);return l.then.bind(l)}return m0(r,e,[...t,o])},set(s,o,l){kd(i);const[c,h]=Ud(l);return hc(r,e,{type:"SET",path:[...t,o].map(p=>p.toString()),value:c},h).then(xl)},apply(s,o,l){kd(i);const c=t[t.length-1];if(c===J8)return hc(r,e,{type:"ENDPOINT"}).then(xl);if(c==="bind")return m0(r,e,t.slice(0,-1));const[h,p]=h2(l);return hc(r,e,{type:"APPLY",path:t.map(C=>C.toString()),argumentList:h},p).then(xl)},construct(s,o){kd(i);const[l,c]=h2(o);return hc(r,e,{type:"CONSTRUCT",path:t.map(h=>h.toString()),argumentList:l},c).then(xl)}});return n6(a,r),a}function i6(r){return Array.prototype.concat.apply([],r)}function h2(r){const e=r.map(Ud);return[e.map(t=>t[0]),i6(e.map(t=>t[1]))]}const f2=new WeakMap;function a6(r,e){return f2.set(r,e),r}function s6(r){return Object.assign(r,{[r2]:!0})}function DW(r,e=globalThis,t="*"){return{postMessage:(n,i)=>r.postMessage(n,t,i),addEventListener:e.addEventListener.bind(e),removeEventListener:e.removeEventListener.bind(e)}}function Ud(r){for(const[e,t]of s2)if(t.canHandle(r)){const[n,i]=t.serialize(r);return[{type:"HANDLER",name:e,value:n},i]}return[{type:"RAW",value:r},f2.get(r)||[]]}function xl(r){switch(r.type){case"HANDLER":return s2.get(r.name).deserialize(r.value);case"RAW":return r.value}}function hc(r,e,t,n){return new Promise(i=>{const a=o6();e.set(a,i),r.start&&r.start(),r.postMessage(Object.assign({id:a},t),n)})}function o6(){return new Array(4).fill(0).map(()=>Math.floor(Math.random()*Number.MAX_SAFE_INTEGER).toString(16)).join("-")}class l6 extends Tf{constructor(e,t,n){super(),this.graph=e,this.layout=t,this.options=n,this.spawnWorker()}spawnWorker(){this.proxy=c2(new Worker(new URL(Z.p+Z.u(1188),Z.b),{type:void 0})),this.running&&(this.running=!1,this.execute())}execute(){var e;return(0,we.mG)(this,void 0,void 0,function*(){if(this.running)return this;this.running=!0;const t=this.layout.options,{onTick:n}=t,i=(0,we._T)(t,["onTick"]),a={};Object.keys(i).forEach(c=>{En(i[c])||(a[c]=i[c])});const s={layout:{id:this.layout.id,options:a,iterations:(e=this.options)===null||e===void 0?void 0:e.iterations},nodes:this.graph.getAllNodes(),edges:this.graph.getAllEdges()},o=new Float32Array([0]),[l]=yield this.proxy.calculateLayout(s,[o]);return l})}stop(){return this.running=!1,this.proxy.stopLayout(),this}kill(){this.proxy[i2]()}isRunning(){return this.running}}var fc=function(r,e,t,n){function i(a){return a instanceof t?a:new t(function(s){s(a)})}return new(t||(t=Promise))(function(a,s){function o(h){try{c(n.next(h))}catch(p){s(p)}}function l(h){try{c(n.throw(h))}catch(p){s(p)}}function c(h){h.done?a(h.value):i(h.value).then(o,l)}c((n=n.apply(r,e||[])).next())})},c6=function(r,e){var t={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&e.indexOf(n)<0&&(t[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var i=0,n=Object.getOwnPropertySymbols(r);i<n.length;i++)e.indexOf(n[i])<0&&Object.prototype.propertyIsEnumerable.call(r,n[i])&&(t[n[i]]=r[n[i]]);return t};class u6{get presetOptions(){return{animation:!!Wy(this.context.options,!0)}}get options(){const{options:e}=this.context;return e.layout}constructor(e){this.instances=[],this.context=e}getLayoutInstance(){return this.instances}preLayout(e){return fc(this,void 0,void 0,function*(){var t,n,i,a;const{graph:s,model:o}=this.context,{add:l}=e;wi(s,new mi($t.BEFORE_LAYOUT,{type:"pre"}));const c=yield(t=this.context.layout)===null||t===void 0?void 0:t.simulate();(n=c==null?void 0:c.nodes)===null||n===void 0||n.forEach(h=>{const p=wt(h),C=l.nodes.get(p);o.syncNodeLikeDatum(h),C&&Object.assign(C.style,h.style)}),(i=c==null?void 0:c.edges)===null||i===void 0||i.forEach(h=>{const p=wt(h),C=l.edges.get(p);o.syncEdgeDatum(h),C&&Object.assign(C.style,h.style)}),(a=c==null?void 0:c.combos)===null||a===void 0||a.forEach(h=>{const p=wt(h),C=l.combos.get(p);o.syncNodeLikeDatum(h),C&&Object.assign(C.style,h.style)}),wi(s,new mi($t.AFTER_LAYOUT,{type:"pre"})),this.transformDataAfterLayout("pre",e)})}postLayout(){return fc(this,arguments,void 0,function*(e=this.options){if(!e)return;const t=Array.isArray(e)?e:[e],{graph:n}=this.context;wi(n,new mi($t.BEFORE_LAYOUT,{type:"post"}));for(const i of t){const a=t.indexOf(i),s=this.getLayoutData(i),o=Object.assign(Object.assign({},this.presetOptions),i);wi(n,new mi($t.BEFORE_STAGE_LAYOUT,{options:o,index:a}));const l=yield this.stepLayout(s,o,a);wi(n,new mi($t.AFTER_STAGE_LAYOUT,{options:o,index:a})),i.animation||this.updateElementPosition(l,!1)}wi(n,new mi($t.AFTER_LAYOUT,{type:"post"})),this.transformDataAfterLayout("post")})}transformDataAfterLayout(e,t){const n=this.context.transform.getTransformInstance();Object.values(n).forEach(i=>i.afterLayout(e,t))}simulate(){return fc(this,void 0,void 0,function*(){if(!this.options)return{};const e=Array.isArray(this.options)?this.options:[this.options];let t={};for(const n of e){const i=e.indexOf(n),a=this.getLayoutData(n);t=yield this.stepLayout(a,Object.assign(Object.assign(Object.assign({},this.presetOptions),n),{animation:!1}),i)}return t})}stepLayout(e,t,n){return fc(this,void 0,void 0,function*(){return rR(t)?yield this.treeLayout(e,t,n):yield this.graphLayout(e,t,n)})}graphLayout(e,t,n){return fc(this,void 0,void 0,function*(){const{animation:i,enableWorker:a,iterations:s=300}=t,o=this.initGraphLayout(t);if(!o)return{};if(this.instances[n]=o,this.instance=o,a){const c=o;return this.supervisor=new l6(c.graphData2LayoutModel(e),c.instance,{iterations:s}),Of(yield this.supervisor.execute())}if(vp(o))return i?yield o.execute(e,{onTick:c=>{this.updateElementPosition(c,!1)}}):(o.execute(e),o.stop(),o.tick(s));const l=yield o.execute(e);if(i){const c=this.updateElementPosition(l,i);yield c==null?void 0:c.finished}return l})}treeLayout(e,t,n){return fc(this,void 0,void 0,function*(){const{type:i,animation:a}=t,s=Gs("layout",i);if(!s)return{};const{nodes:o=[],edges:l=[]}=e,c=new ci({nodes:o.map(W=>({id:wt(W),data:W.data||{}})),edges:l.map(W=>({id:wt(W),source:W.source,target:W.target,data:W.data||{}}))});X8(c);const h={nodes:[],edges:[]},p={nodes:[],edges:[]};c.getRoots(Ca).forEach(W=>{ol(W,re=>{re.children=c.getSuccessors(re.id)},re=>c.getSuccessors(re.id),"TB");const j=s(W,t),{x:K,y:Q,z:ee=0}=j;ol(j,re=>{const{id:ve,x:he,y:pe,z:ye=0}=re;h.nodes.push({id:ve,style:{x:K,y:Q,z:ee}}),p.nodes.push({id:ve,style:{x:he,y:pe,z:ye}})},re=>re.children,"TB")});const k=this.inferTreeLayoutOffset(p);if(d2(p,k),a){d2(h,k),this.updateElementPosition(h,!1);const W=this.updateElementPosition(p,a);yield W==null?void 0:W.finished}return p})}inferTreeLayoutOffset(e){var t;let[n,i]=[1/0,-1/0],[a,s]=[1/0,-1/0];(t=e.nodes)===null||t===void 0||t.forEach(j=>{const{x:K=0,y:Q=0}=j.style||{};n=Math.min(n,K),i=Math.max(i,K),a=Math.min(a,Q),s=Math.max(s,Q)});const{canvas:o}=this.context,l=o.getSize(),[c,h]=o.getCanvasByViewport([0,0]),[p,C]=o.getCanvasByViewport(l);if(n>=c&&i<=p&&a>=h&&s<=C)return[0,0];const k=(c+p)/2,W=(h+C)/2;return[k-(n+i)/2,W-(a+s)/2]}stopLayout(){this.instance&&vp(this.instance)&&(this.instance.stop(),this.instance=void 0),this.supervisor&&(this.supervisor.stop(),this.supervisor=void 0),this.animationResult&&(this.animationResult.finish(),this.animationResult=void 0)}getLayoutData(e){const{nodeFilter:t=()=>!0,preLayout:n=!1,isLayoutInvisibleNodes:i=!1}=e,{nodes:a,edges:s,combos:o}=this.context.model.getData(),{element:l,model:c}=this.context,h=j=>l.getElement(j),p=n?j=>{var K;return!i&&(((K=j.style)===null||K===void 0?void 0:K.visibility)==="hidden"||c.getAncestorsData(j.id,Ca).some(xa)||c.getAncestorsData(j.id,Lr).some(xa))?!1:t(j)}:j=>{const K=wt(j),Q=h(K);return!Q||_f(Q)?!1:t(j)},C=a.filter(p),k=new Map(C.map(j=>[wt(j),j]));o.forEach(j=>k.set(wt(j),j));const W=s.filter(({source:j,target:K})=>k.has(j)&&k.has(K));return{nodes:C,edges:W,combos:o}}initGraphLayout(e){var t;const{element:n,viewport:i}=this.context,{type:a,enableWorker:s,animation:o,iterations:l}=e,c=c6(e,["type","enableWorker","animation","iterations"]),[h,p]=i.getCanvasSize(),C=[h/2,p/2],k=(t=e==null?void 0:e.nodeSize)!==null&&t!==void 0?t:ee=>{const re=n==null?void 0:n.getElement(ee.id);return re?re.attributes.size:n==null?void 0:n.getElementComputedStyle("node",ee).size},W=Gs("layout",a);if(!W)return Ea.warn(`The layout of ${a} is not registered.`);const j=Object.getPrototypeOf(W.prototype)===Cf.prototype?W:aR(W,this.context),K=new j(this.context),Q={nodeSize:k,width:h,height:p,center:C};switch(K.id){case"d3-force":case"d3-force-3d":Object.assign(Q,{center:{x:h/2,y:p/2,z:0}});break;default:break}return ia(K.options,Q,c),K}updateElementPosition(e,t){const{model:n,element:i}=this.context;return i?(n.updateData(e),i.draw({animation:t,silence:!0})):null}destroy(){var e;this.stopLayout(),this.context={},(e=this.supervisor)===null||e===void 0||e.kill(),this.supervisor=void 0,this.instance=void 0,this.instances=[],this.animationResult=void 0}}const d2=(r,e)=>{var t;const[n,i]=e;(t=r.nodes)===null||t===void 0||t.forEach(a=>{if(a.style){const{x:s=0,y:o=0}=a.style;a.style.x=s+n,a.style.y=o+i}else a.style={x:n,y:i}})};function h6(r){return[f6].reduce((t,n)=>n(t),r)}function f6(r){return!r.layout||Array.isArray(r.layout)||"preLayout"in r.layout||["antv-dagre","combo-combined","compact-box","circular","concentric","dagre","fishbone","grid","indented","mds","radial","random","snake","dendrogram","mindmap"].includes(r.layout.type)&&(r.layout.preLayout=!0),r}class d6 extends Eg{constructor(e){super(e),this.category="plugin",this.setPlugins(this.context.options.plugins||[])}setPlugins(e){this.setExtensions(e)}getPluginInstance(e){const t=this.extensionMap[e];if(t)return t;Ea.warn(`Cannot find the plugin ${e}, will try to find it by type.`);const n=this.extensions.find(i=>i.type===e);if(n)return this.extensionMap[n.key]}}const Wd=["update-related-edges","collapse-expand-node","collapse-expand-combo","get-edge-actual-ends","arrange-draw-order"];class v6 extends Eg{constructor(e){super(e),this.category="transform",this.setTransforms(this.context.options.transforms||[])}getTransforms(){}setTransforms(e){this.setExtensions([...Wd.slice(0,Wd.length-1),...e,Wd[Wd.length-1]])}getTransformInstance(e){return e?this.extensionMap[e]:this.extensionMap}}var Tu=function(r,e,t,n){function i(a){return a instanceof t?a:new t(function(s){s(a)})}return new(t||(t=Promise))(function(a,s){function o(h){try{c(n.next(h))}catch(p){s(p)}}function l(h){try{c(n.throw(h))}catch(p){s(p)}}function c(h){h.done?a(h.value):i(h.value).then(o,l)}c((n=n.apply(r,e||[])).next())})};class g6{get padding(){return os(this.context.options.padding)}get paddingOffset(){const[e,t,n,i]=this.padding,[a,s,o]=[(i-t)/2,(e-n)/2,0];return[a,s,o]}constructor(e){this.landmarkCounter=0,this.context=e;const[t,n]=this.paddingOffset,{zoom:i,rotation:a,x:s=t,y:o=n}=e.options;this.transform({mode:"absolute",scale:i,translate:[s,o],rotate:a},!1)}get camera(){const{canvas:e}=this.context;return new Proxy(e.getCamera(),{get:(t,n)=>{const a=Object.entries(e.getLayers()).filter(([o])=>!["main"].includes(o)).map(([,o])=>o.getCamera()),s=t[n];if(typeof s=="function")return(...o)=>{const l=s.apply(t,o);return a.forEach(c=>{c[n].apply(c,o)}),l}}})}createLandmark(e){return this.camera.createLandmark(`landmark-${this.landmarkCounter++}`,e)}getAnimation(e){const t=Wy(this.context.options,e);return t?ul(Object.assign({},t),["easing","duration"]):!1}getCanvasSize(){const{canvas:e}=this.context,{width:t=0,height:n=0}=e.getConfig();return[t,n]}getCanvasCenter(){const{canvas:e}=this.context,{width:t=0,height:n=0}=e.getConfig();return[t/2,n/2,0]}getViewportCenter(){const[e,t]=this.camera.getPosition();return[e,t,0]}getGraphCenter(){return this.context.graph.getViewportByCanvas(this.getCanvasCenter())}getZoom(){return this.camera.getZoom()}getRotation(){return this.camera.getRoll()}getTranslateOptions(e){const{camera:t}=this,{mode:n,translate:i=[]}=e,a=this.getZoom(),s=t.getPosition(),o=t.getFocalPoint(),[l,c]=this.getCanvasCenter(),[h=0,p=0,C=0]=i,k=us([-h,-p,-C],a);return n==="relative"?{position:Jn(s,k),focalPoint:Jn(o,k)}:{position:Jn([l,c,s[2]],k),focalPoint:Jn([l,c,o[2]],k)}}getRotateOptions(e){const{mode:t,rotate:n=0}=e;return{roll:t==="relative"?this.camera.getRoll()+n:n}}getZoomOptions(e){const{zoomRange:t}=this.context.options,n=this.camera.getZoom(),{mode:i,scale:a=1}=e;return Yr(i==="relative"?n*a:a,...t)}transform(e,t){return Tu(this,void 0,void 0,function*(){const{graph:n}=this.context,{translate:i,rotate:a,scale:s,origin:o}=e;this.cancelAnimation();const l=this.getAnimation(t);if(wi(n,new Id($t.BEFORE_TRANSFORM,e)),!a&&s&&!i&&o&&!l){this.camera.setZoomByViewportPoint(this.getZoomOptions(e),o),wi(n,new Id($t.AFTER_TRANSFORM,e));return}const c={};if(i&&Object.assign(c,this.getTranslateOptions(e)),un(a)&&Object.assign(c,this.getRotateOptions(e)),un(s)&&Object.assign(c,{zoom:this.getZoomOptions(e)}),l)return wi(n,new Ja($t.BEFORE_ANIMATE,_a.TRANSFORM,null,e)),new Promise(h=>{this.transformResolver=h,this.camera.gotoLandmark(this.createLandmark(c),Object.assign(Object.assign({},l),{onfinish:()=>{wi(n,new Ja($t.AFTER_ANIMATE,_a.TRANSFORM,null,e)),wi(n,new Id($t.AFTER_TRANSFORM,e)),this.transformResolver=void 0,h()}}))});this.camera.gotoLandmark(this.createLandmark(c),{duration:0}),wi(n,new Id($t.AFTER_TRANSFORM,e))})}fitView(e,t){return Tu(this,void 0,void 0,function*(){const[n,i,a,s]=this.padding,{when:o="always",direction:l="both"}=e||{},[c,h]=this.context.canvas.getSize(),p=c-s-i,C=h-n-a,k=this.context.canvas.getBounds(),W=this.getBBoxInViewport(k),[j,K]=fo(W),Q=l==="x"&&j>=p||l==="y"&&K>=C||l==="both"&&j>=p&&K>=C;if(o==="overflow"&&!Q)return yield this.fitCenter({animation:t});const ee=p/j,re=C/K,ve=l==="x"?ee:l==="y"?re:Math.min(ee,re),he=this.getAnimation(t);yield this.transform({mode:"relative",scale:ve,translate:Jn(Or(this.getCanvasCenter(),this.getBBoxInViewport(k).center),us(this.paddingOffset,ve))},he)})}fitCenter(e){return Tu(this,void 0,void 0,function*(){const t=this.context.canvas.getBounds();yield this.focus(t,e)})}focusElements(e){return Tu(this,arguments,void 0,function*(t,n={}){const{element:i}=this.context;if(!i)return;const a=o=>n.shapes?o.getShape(n.shapes).getRenderBounds():o.getRenderBounds(),s=Hc(t.map(o=>a(i.getElement(o))));yield this.focus(s,n)})}focus(e,t){return Tu(this,void 0,void 0,function*(){const n=this.context.graph.getViewportByCanvas(e.center),i=t.position||this.getCanvasCenter(),a=Or(i,n);yield this.transform({mode:"relative",translate:Jn(a,this.paddingOffset)},t.animation)})}getBBoxInViewport(e){const{min:t,max:n}=e,{graph:i}=this.context,[a,s]=i.getViewportByCanvas(t),[o,l]=i.getViewportByCanvas(n),c=new Nr;return c.setMinMax([a,s,0],[o,l,0]),c}isInViewport(e,t=!1,n=0){const{graph:i}=this.context,a=this.getCanvasSize(),[s,o]=i.getCanvasByViewport([0,0]),[l,c]=i.getCanvasByViewport(a);let h=new Nr;return h.setMinMax([s,o,0],[l,c,0]),n&&(h=go(h,n)),Gl(e)?ls(e,h):t?MC(e,h):h.intersects(e)}cancelAnimation(){var e,t;!((e=this.camera.landmarks)===null||e===void 0)&&e.length&&this.camera.cancelLandmarkAnimation(),(t=this.transformResolver)===null||t===void 0||t.call(this)}}var kr=function(r,e,t,n){function i(a){return a instanceof t?a:new t(function(s){s(a)})}return new(t||(t=Promise))(function(a,s){function o(h){try{c(n.next(h))}catch(p){s(p)}}function l(h){try{c(n.throw(h))}catch(p){s(p)}}function c(h){h.done?a(h.value):i(h.value).then(o,l)}c((n=n.apply(r,e||[])).next())})};class Hd extends Tf{constructor(e){var t;super(),this.options={},this.rendered=!1,this.destroyed=!1,this.context={model:new Y8},this.isCollapsingExpanding=!1,this.onResize=ru(()=>{this.resize()},300),this._setOptions(Object.assign({},Hd.defaultOptions,e),!0),this.context.graph=this,this.options.autoResize&&((t=globalThis.addEventListener)===null||t===void 0||t.call(globalThis,"resize",this.onResize))}getOptions(){return this.options}setOptions(e){this._setOptions(e,!1)}_setOptions(e,t){if(this.updateCanvas(e),Object.assign(this.options,h6(e)),t){const{data:C}=e;C&&this.addData(C);return}const{behaviors:n,combo:i,data:a,edge:s,layout:o,node:l,plugins:c,theme:h,transforms:p}=e;n&&this.setBehaviors(n),a&&this.setData(a),l&&this.setNode(l),s&&this.setEdge(s),i&&this.setCombo(i),o&&this.setLayout(o),h&&this.setTheme(h),c&&this.setPlugins(c),p&&this.setTransforms(p)}getSize(){return this.context.canvas?this.context.canvas.getSize():[this.options.width||0,this.options.height||0]}setSize(e,t){e&&(this.options.width=e),t&&(this.options.height=t),this.resize(e,t)}setZoomRange(e){this.options.zoomRange=e}getZoomRange(){return this.options.zoomRange}setNode(e){this.options.node=e,this.context.model.refreshData()}setEdge(e){this.options.edge=e,this.context.model.refreshData()}setCombo(e){this.options.combo=e,this.context.model.refreshData()}getTheme(){return this.options.theme}setTheme(e){this.options.theme=En(e)?e(this.getTheme()):e}setLayout(e){this.options.layout=En(e)?e(this.getLayout()):e}getLayout(){return this.options.layout}setBehaviors(e){var t;this.options.behaviors=En(e)?e(this.getBehaviors()):e,(t=this.context.behavior)===null||t===void 0||t.setBehaviors(this.options.behaviors)}updateBehavior(e){this.setBehaviors(t=>t.map(n=>typeof n=="object"&&n.key===e.key?Object.assign(Object.assign({},n),e):n))}getBehaviors(){return this.options.behaviors||[]}setPlugins(e){var t;this.options.plugins=En(e)?e(this.getPlugins()):e,(t=this.context.plugin)===null||t===void 0||t.setPlugins(this.options.plugins)}updatePlugin(e){this.setPlugins(t=>t.map(n=>typeof n=="object"&&n.key===e.key?Object.assign(Object.assign({},n),e):n))}getPlugins(){return this.options.plugins||[]}getPluginInstance(e){return this.context.plugin.getPluginInstance(e)}setTransforms(e){var t;this.options.transforms=En(e)?e(this.getTransforms()):e,(t=this.context.transform)===null||t===void 0||t.setTransforms(this.options.transforms)}updateTransform(e){this.setTransforms(t=>t.map(n=>typeof n=="object"&&n.key===e.key?Object.assign(Object.assign({},n),e):n)),this.context.model.refreshData()}getTransforms(){return this.options.transforms||[]}getData(){return this.context.model.getData()}getElementData(e){return Array.isArray(e)?e.map(t=>this.context.model.getElementDataById(t)):this.context.model.getElementDataById(e)}getNodeData(e){return e===void 0?this.context.model.getNodeData():Array.isArray(e)?this.context.model.getNodeData(e):this.context.model.getNodeLikeDatum(e)}getEdgeData(e){return e===void 0?this.context.model.getEdgeData():Array.isArray(e)?this.context.model.getEdgeData(e):this.context.model.getEdgeDatum(e)}getComboData(e){return e===void 0?this.context.model.getComboData():Array.isArray(e)?this.context.model.getComboData(e):this.context.model.getNodeLikeDatum(e)}setData(e){this.context.model.setData(En(e)?e(this.getData()):e)}addData(e){this.context.model.addData(En(e)?e(this.getData()):e)}addNodeData(e){this.context.model.addNodeData(En(e)?e(this.getNodeData()):e)}addEdgeData(e){this.context.model.addEdgeData(En(e)?e(this.getEdgeData()):e)}addComboData(e){this.context.model.addComboData(En(e)?e(this.getComboData()):e)}addChildrenData(e,t){this.context.model.addChildrenData(e,t)}updateData(e){this.context.model.updateData(En(e)?e(this.getData()):e)}updateNodeData(e){this.context.model.updateNodeData(En(e)?e(this.getNodeData()):e)}updateEdgeData(e){this.context.model.updateEdgeData(En(e)?e(this.getEdgeData()):e)}updateComboData(e){this.context.model.updateComboData(En(e)?e(this.getComboData()):e)}removeData(e){this.context.model.removeData(En(e)?e(this.getData()):e)}removeNodeData(e){this.context.model.removeNodeData(En(e)?e(this.getNodeData()):e)}removeEdgeData(e){this.context.model.removeEdgeData(En(e)?e(this.getEdgeData()):e)}removeComboData(e){this.context.model.removeComboData(En(e)?e(this.getComboData()):e)}getElementType(e){return this.context.model.getElementType(e)}getRelatedEdgesData(e,t="both"){return this.context.model.getRelatedEdgesData(e,t)}getNeighborNodesData(e){return this.context.model.getNeighborNodesData(e)}getAncestorsData(e,t){return this.context.model.getAncestorsData(e,t)}getParentData(e,t){return this.context.model.getParentData(e,t)}getChildrenData(e){return this.context.model.getChildrenData(e)}getDescendantsData(e){return this.context.model.getDescendantsData(e)}getElementDataByState(e,t){return this.context.model.getElementDataByState(e,t)}initCanvas(){return kr(this,void 0,void 0,function*(){var e;if(this.context.canvas)return yield this.context.canvas.ready;const{container:t="container",width:n,height:i,renderer:a,cursor:s,background:o,canvas:l,devicePixelRatio:c=(e=globalThis.devicePixelRatio)!==null&&e!==void 0?e:1}=this.options;if(t instanceof Jb)this.context.canvas=t,s&&t.setCursor(s),a&&t.setRenderer(a),yield t.ready;else{const h=dr(t)?document.getElementById(t):t,p=e2(h);this.emit($t.BEFORE_CANVAS_INIT,{container:h,width:n,height:i});const C=Object.assign(Object.assign({},l),{container:h,width:n||p[0],height:i||p[1],background:o,renderer:a,cursor:s,devicePixelRatio:c}),k=new Jb(C);this.context.canvas=k,yield k.ready,this.emit($t.AFTER_CANVAS_INIT,{canvas:k})}})}updateCanvas(e){var t,n;const{renderer:i,cursor:a,height:s,width:o}=e,l=this.context.canvas;l&&(i&&(this.emit($t.BEFORE_RENDERER_CHANGE,{renderer:this.options.renderer}),l.setRenderer(i),this.emit($t.AFTER_RENDERER_CHANGE,{renderer:i})),a&&l.setCursor(a),(un(o)||un(s))&&this.setSize((t=o!=null?o:this.options.width)!==null&&t!==void 0?t:0,(n=s!=null?s:this.options.height)!==null&&n!==void 0?n:0))}initRuntime(){this.context.options=this.options,this.context.batch||(this.context.batch=new G8(this.context)),this.context.plugin||(this.context.plugin=new d6(this.context)),this.context.viewport||(this.context.viewport=new g6(this.context)),this.context.transform||(this.context.transform=new v6(this.context)),this.context.element||(this.context.element=new Q8(this.context)),this.context.animation||(this.context.animation=new j8(this.context)),this.context.layout||(this.context.layout=new u6(this.context)),this.context.behavior||(this.context.behavior=new V8(this.context))}prepare(){return kr(this,void 0,void 0,function*(){if(yield Promise.resolve(),this.destroyed)throw new Error(Vs("The graph instance has been destroyed"));yield this.initCanvas(),this.initRuntime()})}render(){return kr(this,void 0,void 0,function*(){if(yield this.prepare(),wi(this,new mi($t.BEFORE_RENDER)),this.options.layout)if(!this.rendered&&iR(this.options.layout)){const e=yield this.context.element.preLayoutDraw({type:"render"});yield Promise.all([e==null?void 0:e.finished,this.autoFit()])}else{const e=this.context.element.draw({type:"render"});yield Promise.all([e==null?void 0:e.finished,this.context.layout.postLayout()]),yield this.autoFit()}else{const e=this.context.element.draw({type:"render"});yield Promise.all([e==null?void 0:e.finished,this.autoFit()])}this.rendered=!0,wi(this,new mi($t.AFTER_RENDER))})}draw(){return kr(this,void 0,void 0,function*(){var e;yield this.prepare(),yield(e=this.context.element.draw())===null||e===void 0?void 0:e.finished})}layout(e){return kr(this,void 0,void 0,function*(){yield this.context.layout.postLayout(e)})}stopLayout(){this.context.layout.stopLayout()}clear(){return kr(this,void 0,void 0,function*(){const{model:e,element:t}=this.context;e.setData({}),e.clearChanges(),t==null||t.clear()})}destroy(){var e;wi(this,new mi($t.BEFORE_DESTROY));const{layout:t,animation:n,element:i,model:a,canvas:s,behavior:o,plugin:l}=this.context;l==null||l.destroy(),o==null||o.destroy(),t==null||t.destroy(),n==null||n.destroy(),i==null||i.destroy(),a.destroy(),s==null||s.destroy(),this.options={},this.context={},this.off(),(e=globalThis.removeEventListener)===null||e===void 0||e.call(globalThis,"resize",this.onResize),this.destroyed=!0,wi(this,new mi($t.AFTER_DESTROY))}getCanvas(){return this.context.canvas}resize(e,t){var n;const i=e2((n=this.context.canvas)===null||n===void 0?void 0:n.getContainer()),a=[e||i[0],t||i[1]];if(!this.context.canvas)return;const s=this.context.canvas.getSize();si(a,s)||(wi(this,new mi($t.BEFORE_SIZE_CHANGE,{size:a})),this.context.canvas.resize(...a),wi(this,new mi($t.AFTER_SIZE_CHANGE,{size:a})))}fitView(e,t){return kr(this,void 0,void 0,function*(){var n;yield(n=this.context.viewport)===null||n===void 0?void 0:n.fitView(e,t)})}fitCenter(e){return kr(this,void 0,void 0,function*(){var t;yield(t=this.context.viewport)===null||t===void 0?void 0:t.fitCenter({animation:e})})}autoFit(){return kr(this,void 0,void 0,function*(){const{autoFit:e}=this.context.options;if(e)if(dr(e))e==="view"?yield this.fitView():e==="center"&&(yield this.fitCenter());else{const{type:t,animation:n}=e;t==="view"?yield this.fitView(e.options,n):t==="center"&&(yield this.fitCenter(n))}})}focusElement(e,t){return kr(this,void 0,void 0,function*(){var n;yield(n=this.context.viewport)===null||n===void 0?void 0:n.focusElements(Array.isArray(e)?e:[e],{animation:t})})}zoomBy(e,t,n){return kr(this,void 0,void 0,function*(){yield this.context.viewport.transform({mode:"relative",scale:e,origin:n},t)})}zoomTo(e,t,n){return kr(this,void 0,void 0,function*(){this.context.viewport.transform({mode:"absolute",scale:e,origin:n},t)})}getZoom(){return this.context.viewport.getZoom()}rotateBy(e,t,n){return kr(this,void 0,void 0,function*(){yield this.context.viewport.transform({mode:"relative",rotate:e,origin:n},t)})}rotateTo(e,t,n){return kr(this,void 0,void 0,function*(){yield this.context.viewport.transform({mode:"absolute",rotate:e,origin:n},t)})}getRotation(){return this.context.viewport.getRotation()}translateBy(e,t){return kr(this,void 0,void 0,function*(){yield this.context.viewport.transform({mode:"relative",translate:e},t)})}translateTo(e,t){return kr(this,void 0,void 0,function*(){yield this.context.viewport.transform({mode:"absolute",translate:e},t)})}getPosition(){return Or([0,0],this.getCanvasByViewport([0,0]))}translateElementBy(e,t){return kr(this,arguments,void 0,function*(n,i,a=!0){var s,o;const[l,c]=ii(n)?[n,(s=i)!==null&&s!==void 0?s:!0]:[{[n]:i},a];Object.entries(l).forEach(([h,p])=>this.context.model.translateNodeLikeBy(h,p)),yield(o=this.context.element.draw({animation:c,stage:"translate"}))===null||o===void 0?void 0:o.finished})}translateElementTo(e,t){return kr(this,arguments,void 0,function*(n,i,a=!0){var s,o;const[l,c]=ii(n)?[n,(s=i)!==null&&s!==void 0?s:!0]:[{[n]:i},a];Object.entries(l).forEach(([h,p])=>this.context.model.translateNodeLikeTo(h,p)),yield(o=this.context.element.draw({animation:c,stage:"translate"}))===null||o===void 0?void 0:o.finished})}getElementPosition(e){return this.context.model.getElementPosition(e)}getElementRenderStyle(e){return bp(this.context.element.getElement(e).attributes,["context"])}setElementVisibility(e,t){return kr(this,arguments,void 0,function*(n,i,a=!0){var s,o;const[l,c]=ii(n)?[n,(s=i)!==null&&s!==void 0?s:!0]:[{[n]:i},a],h={nodes:[],edges:[],combos:[]};Object.entries(l).forEach(([k,W])=>{const j=this.getElementType(k);h[`${j}s`].push({id:k,style:{visibility:W}})});const{model:p,element:C}=this.context;p.preventUpdateNodeLikeHierarchy(()=>{p.updateData(h)}),yield(o=C.draw({animation:c,stage:"visibility"}))===null||o===void 0?void 0:o.finished})}showElement(e,t){return kr(this,void 0,void 0,function*(){const n=Array.isArray(e)?e:[e];yield this.setElementVisibility(Object.fromEntries(n.map(i=>[i,"visible"])),t)})}hideElement(e,t){return kr(this,void 0,void 0,function*(){const n=Array.isArray(e)?e:[e];yield this.setElementVisibility(Object.fromEntries(n.map(i=>[i,"hidden"])),t)})}getElementVisibility(e){var t,n;const i=this.context.element.getElement(e);return(n=(t=i==null?void 0:i.style)===null||t===void 0?void 0:t.visibility)!==null&&n!==void 0?n:"visible"}setElementZIndex(e,t){return kr(this,void 0,void 0,function*(){var n;const i={nodes:[],edges:[],combos:[]},a=ii(e)?e:{[e]:t};Object.entries(a).forEach(([l,c])=>{const h=this.getElementType(l);i[`${h}s`].push({id:l,style:{zIndex:c}})});const{model:s,element:o}=this.context;s.preventUpdateNodeLikeHierarchy(()=>s.updateData(i)),yield(n=o.draw({animation:!1,stage:"zIndex"}))===null||n===void 0?void 0:n.finished})}frontElement(e){return kr(this,void 0,void 0,function*(){const t=Array.isArray(e)?e:[e],{model:n}=this.context,i={};t.map(a=>{const s=n.getFrontZIndex(a);if(n.getElementType(a)==="combo"){const l=n.getAncestorsData(a,Lr).at(-1)||this.getComboData(a),c=[l,...n.getDescendantsData(wt(l))],h=s-t2(l);c.forEach(C=>{i[wt(C)]=this.getElementZIndex(wt(C))+h});const{internal:p}=Gg(c.map(wt),C=>n.getRelatedEdgesData(C));p.forEach(C=>{const k=wt(C);i[k]=this.getElementZIndex(k)+h})}else i[a]=s}),yield this.setElementZIndex(i)})}getElementZIndex(e){return t2(this.context.model.getElementDataById(e))}setElementState(e,t){return kr(this,arguments,void 0,function*(n,i,a=!0){var s,o;const[l,c]=ii(n)?[n,(s=i)!==null&&s!==void 0?s:!0]:[{[n]:i},a],h=C=>C?Array.isArray(C)?C:[C]:[],p={nodes:[],edges:[],combos:[]};Object.entries(l).forEach(([C,k])=>{const W=this.getElementType(C);p[`${W}s`].push({id:C,states:h(k)})}),this.updateData(p),yield(o=this.context.element.draw({animation:c,stage:"state"}))===null||o===void 0?void 0:o.finished})}getElementState(e){return this.context.model.getElementState(e)}getElementRenderBounds(e){return this.context.element.getElement(e).getRenderBounds()}collapseElement(e){return kr(this,arguments,void 0,function*(t,n=!0){const{model:i,element:a}=this.context;if(xa(i.getNodeLikeData([t])[0])||this.isCollapsingExpanding)return;typeof n=="boolean"&&(n={animation:n,align:!0});const s=i.getElementType(t);yield this.frontElement(t),this.isCollapsingExpanding=!0,this.setElementCollapsibility(t,!0),s==="node"?yield a.collapseNode(t,n):s==="combo"&&(yield a.collapseCombo(t,!!n.animation)),this.isCollapsingExpanding=!1})}expandElement(e){return kr(this,arguments,void 0,function*(t,n=!0){const{model:i,element:a}=this.context;if(!xa(i.getNodeLikeData([t])[0])||this.isCollapsingExpanding)return;typeof n=="boolean"&&(n={animation:n,align:!0});const s=i.getElementType(t);this.isCollapsingExpanding=!0,this.setElementCollapsibility(t,!1),s==="node"?yield a.expandNode(t,n):s==="combo"&&(yield a.expandCombo(t,!!n.animation)),this.isCollapsingExpanding=!1})}setElementCollapsibility(e,t){const n=this.getElementType(e);n==="node"?this.updateNodeData([{id:e,style:{collapsed:t}}]):n==="combo"&&this.updateComboData([{id:e,style:{collapsed:t}}])}toDataURL(){return kr(this,arguments,void 0,function*(e={}){return this.context.canvas.toDataURL(e)})}getCanvasByViewport(e){return this.context.canvas.getCanvasByViewport(e)}getViewportByCanvas(e){return this.context.canvas.getViewportByCanvas(e)}getClientByCanvas(e){return this.context.canvas.getClientByCanvas(e)}getCanvasByClient(e){return this.context.canvas.getCanvasByClient(e)}getViewportCenter(){return this.context.viewport.getViewportCenter()}getCanvasCenter(){return this.context.viewport.getCanvasCenter()}on(e,t,n){return super.on(e,t,n)}once(e,t){return super.once(e,t)}off(e,t){return super.off(e,t)}}Hd.defaultOptions={autoResize:!1,theme:"light",rotation:0,zoom:1,zoomRange:[.01,10]};var p6=function(r,e){var t={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&e.indexOf(n)<0&&(t[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var i=0,n=Object.getOwnPropertySymbols(r);i<n.length;i++)e.indexOf(n[i])<0&&Object.prototype.propertyIsEnumerable.call(r,n[i])&&(t[n[i]]=r[n[i]]);return t};function m6(r,e){const{getNodeData:t=(o,l)=>{if(o.depth=l,!o.children)return o;const{children:c}=o,h=p6(o,["children"]);return Object.assign(Object.assign({},h),{children:c.map(p=>p.id)})},getEdgeData:n=(o,l)=>({source:o.id,target:l.id}),getChildren:i=o=>o.children||[]}=e||{},a=[],s=[];return ol(r,(o,l)=>{a.push(t(o,l));const c=i(o);for(const h of c)s.push(n(o,h))},o=>i(o),"TB"),{nodes:a,edges:s}}class y6 extends Do{beforeDraw(e){const{add:t,update:n}=e,{model:i}=this.context;return[...t.edges.entries(),...n.edges.entries()].forEach(([,a])=>{v2(i,a)}),e}}const v2=(r,e)=>{const{source:t,target:n}=e,i=r.getElementDataById(t),a=r.getElementDataById(n),s=O_(i,p=>r.getParentData(p,Lr)),o=O_(a,p=>r.getParentData(p,Lr)),l=wt(s),c=wt(o),h={sourceNode:l,targetNode:c};return e.style?Object.assign(e.style,h):e.style=h,e},_6=(r,e,t)=>{const[n,i]=e,[a,s]=t;if(i===n)return a;const o=(r-n)/(i-n);return a+o*(s-a)},E6=(r,e,t)=>{const[n,i]=e,[a,s]=t,o=Math.log(r-n+1)/Math.log(i-n+1);return a+o*(s-a)},x6=(r,e,t,n=2)=>{const[i,a]=e,[s,o]=t,l=Math.pow((r-i)/(a-i),n);return 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x,this._requestAbort=!1,this._waitForTotalLength=!1,this._totalLengthReceived=!1,this._currentRequestURL=null,this._currentRedirectedURL=null,this._currentRequestRange=null,this._totalLength=null,this._contentLength=null,this._receivedLength=0,this._lastTimeLoaded=0}destroy(){this.isWorking()&&this.abort(),this._xhr&&(this._xhr.onreadystatechange=null,this._xhr.onprogress=null,this._xhr.onload=null,this._xhr.onerror=null,this._xhr=null),super.destroy()}get currentSpeed(){return this._speedSampler.lastSecondKBps}open(E,B){this._dataSource=E,this._range=B,this._status=L.kConnecting;let N=!1;this._dataSource.filesize!=null&&this._dataSource.filesize!==0&&(N=!0,this._totalLength=this._dataSource.filesize),!this._totalLengthReceived&&!N?(this._waitForTotalLength=!0,this._internalOpen(this._dataSource,{from:0,to:-1})):this._openSubRange()}_openSubRange(){let E=this._currentChunkSizeKB*1024,B=this._range.from+this._receivedLength,N=B+E;this._contentLength!=null&&N-this._range.from>=this._contentLength&&(N=this._range.from+this._contentLength-1),this._currentRequestRange={from:B,to:N},this._internalOpen(this._dataSource,this._currentRequestRange)}_internalOpen(E,B){this._lastTimeLoaded=0;let N=E.url;this._config.reuseRedirectedURL&&(this._currentRedirectedURL!=null?N=this._currentRedirectedURL:E.redirectedURL!=null&&(N=E.redirectedURL));let V=this._seekHandler.getConfig(N,B);this._currentRequestURL=V.url;let q=this._xhr=new XMLHttpRequest;if(q.open("GET",V.url,!0),q.responseType="arraybuffer",q.onreadystatechange=this._onReadyStateChange.bind(this),q.onprogress=this._onProgress.bind(this),q.onload=this._onLoad.bind(this),q.onerror=this._onXhrError.bind(this),E.withCredentials&&(q.withCredentials=!0),typeof V.headers=="object"){let ue=V.headers;for(let ce in ue)ue.hasOwnProperty(ce)&&q.setRequestHeader(ce,ue[ce])}if(typeof this._config.headers=="object"){let ue=this._config.headers;for(let ce in ue)ue.hasOwnProperty(ce)&&q.setRequestHeader(ce,ue[ce])}q.send()}abort(){this._requestAbort=!0,this._internalAbort(),this._status=L.kComplete}_internalAbort(){this._xhr&&(this._xhr.onreadystatechange=null,this._xhr.onprogress=null,this._xhr.onload=null,this._xhr.onerror=null,this._xhr.abort(),this._xhr=null)}_onReadyStateChange(E){let B=E.target;if(B.readyState===2){if(B.responseURL!=null){let N=this._seekHandler.removeURLParameters(B.responseURL);B.responseURL!==this._currentRequestURL&&N!==this._currentRedirectedURL&&(this._currentRedirectedURL=N,this._onURLRedirect&&this._onURLRedirect(N))}if(B.status>=200&&B.status<=299){if(this._waitForTotalLength)return;this._status=L.kBuffering}else if(this._status=L.kError,this._onError)this._onError(d.HTTP_STATUS_CODE_INVALID,{code:B.status,msg:B.statusText});else throw new O("RangeLoader: Http code invalid, "+B.status+" "+B.statusText)}}_onProgress(E){if(this._status===L.kError)return;if(this._contentLength===null){let N=!1;if(this._waitForTotalLength){this._waitForTotalLength=!1,this._totalLengthReceived=!0,N=!0;let V=E.total;this._internalAbort(),V!=null&V!==0&&(this._totalLength=V)}if(this._range.to===-1?this._contentLength=this._totalLength-this._range.from:this._contentLength=this._range.to-this._range.from+1,N){this._openSubRange();return}this._onContentLengthKnown&&this._onContentLengthKnown(this._contentLength)}let B=E.loaded-this._lastTimeLoaded;this._lastTimeLoaded=E.loaded,this._speedSampler.addBytes(B)}_normalizeSpeed(E){let B=this._chunkSizeKBList,N=B.length-1,V=0,q=0,ue=N;if(E<B[0])return B[0];for(;q<=ue;){if(V=q+Math.floor((ue-q)/2),V===N||E>=B[V]&&E<B[V+1])return B[V];B[V]<E?q=V+1:ue=V-1}}_onLoad(E){if(this._status===L.kError)return;if(this._waitForTotalLength){this._waitForTotalLength=!1;return}this._lastTimeLoaded=0;let B=this._speedSampler.lastSecondKBps;if(B===0&&(this._zeroSpeedChunkCount++,this._zeroSpeedChunkCount>=3&&(B=this._speedSampler.currentKBps)),B!==0){let ue=this._normalizeSpeed(B);this._currentSpeedNormalized!==ue&&(this._currentSpeedNormalized=ue,this._currentChunkSizeKB=ue)}let N=E.target.response,V=this._range.from+this._receivedLength;this._receivedLength+=N.byteLength;let q=!1;this._contentLength!=null&&this._receivedLength<this._contentLength?this._openSubRange():q=!0,this._onDataArrival&&this._onDataArrival(N,V,this._receivedLength),q&&(this._status=L.kComplete,this._onComplete&&this._onComplete(this._range.from,this._range.from+this._receivedLength-1))}_onXhrError(E){this._status=L.kError;let B=0,N=null;if(this._contentLength&&this._receivedLength>0&&this._receivedLength<this._contentLength?(B=d.EARLY_EOF,N={code:-1,msg:"RangeLoader meet Early-Eof"}):(B=d.EXCEPTION,N={code:-1,msg:E.constructor.name+" "+E.type}),this._onError)this._onError(B,N);else throw new O(N.msg)}}var U=I;class F extends v{static isSupported(){try{return typeof self.WebSocket!="undefined"}catch(E){return!1}}constructor(){super("websocket-loader"),this.TAG="WebSocketLoader",this._needStash=!0,this._ws=null,this._requestAbort=!1,this._receivedLength=0}destroy(){this._ws&&this.abort(),super.destroy()}open(E){try{let B=this._ws=new self.WebSocket(E.url);B.binaryType="arraybuffer",B.onopen=this._onWebSocketOpen.bind(this),B.onclose=this._onWebSocketClose.bind(this),B.onmessage=this._onWebSocketMessage.bind(this),B.onerror=this._onWebSocketError.bind(this),this._status=L.kConnecting}catch(B){this._status=L.kError;let N={code:B.code,msg:B.message};if(this._onError)this._onError(d.EXCEPTION,N);else throw new O(N.msg)}}abort(){let E=this._ws;E&&(E.readyState===0||E.readyState===1)&&(this._requestAbort=!0,E.close()),this._ws=null,this._status=L.kComplete}_onWebSocketOpen(E){this._status=L.kBuffering}_onWebSocketClose(E){if(this._requestAbort===!0){this._requestAbort=!1;return}this._status=L.kComplete,this._onComplete&&this._onComplete(0,this._receivedLength-1)}_onWebSocketMessage(E){if(E.data instanceof ArrayBuffer)this._dispatchArrayBuffer(E.data);else if(E.data instanceof Blob){let B=new FileReader;B.onload=()=>{this._dispatchArrayBuffer(B.result)},B.readAsArrayBuffer(E.data)}else{this._status=L.kError;let B={code:-1,msg:"Unsupported WebSocket message type: "+E.data.constructor.name};if(this._onError)this._onError(d.EXCEPTION,B);else throw new O(B.msg)}}_dispatchArrayBuffer(E){let B=E,N=this._receivedLength;this._receivedLength+=B.byteLength,this._onDataArrival&&this._onDataArrival(B,N,this._receivedLength)}_onWebSocketError(E){this._status=L.kError;let B={code:E.code,msg:E.message};if(this._onError)this._onError(d.EXCEPTION,B);else throw new O(B.msg)}}var G=F;class Y{constructor(E){this._zeroStart=E||!1}getConfig(E,B){let N={};if(B.from!==0||B.to!==-1){let V;B.to!==-1?V=`bytes=${B.from.toString()}-${B.to.toString()}`:V=`bytes=${B.from.toString()}-`,N.Range=V}else this._zeroStart&&(N.Range="bytes=0-");return{url:E,headers:N}}removeURLParameters(E){return E}}var te=Y;class ${constructor(E,B){this._startName=E,this._endName=B}getConfig(E,B){let N=E;if(B.from!==0||B.to!==-1){let V=!0;N.indexOf("?")===-1&&(N+="?",V=!1),V&&(N+="&"),N+=`${this._startName}=${B.from.toString()}`,B.to!==-1&&(N+=`&${this._endName}=${B.to.toString()}`)}return{url:N,headers:{}}}removeURLParameters(E){let B=E.split("?")[0],N,V=E.indexOf("?");V!==-1&&(N=E.substring(V+1));let q="";if(N!=null&&N.length>0){let ue=N.split("&");for(let ce=0;ce<ue.length;ce++){let Oe=ue[ce].split("="),Se=ce>0;Oe[0]!==this._startName&&Oe[0]!==this._endName&&(Se&&(q+="&"),q+=ue[ce])}}return q.length===0?B:B+"?"+q}}var oe=$;class ie{constructor(E,B,N){this.TAG="IOController",this._config=B,this._extraData=N,this._stashInitialSize=1024*384,B.stashInitialSize!=null&&B.stashInitialSize>0&&(this._stashInitialSize=B.stashInitialSize),this._stashUsed=0,this._stashSize=this._stashInitialSize,this._bufferSize=1024*1024*3,this._stashBuffer=new ArrayBuffer(this._bufferSize),this._stashByteStart=0,this._enableStash=!0,B.enableStashBuffer===!1&&(this._enableStash=!1),this._loader=null,this._loaderClass=null,this._seekHandler=null,this._dataSource=E,this._isWebSocketURL=/wss?:\/\/(.+?)/.test(E.url),this._refTotalLength=E.filesize?E.filesize:null,this._totalLength=this._refTotalLength,this._fullRequestFlag=!1,this._currentRange=null,this._redirectedURL=null,this._speedNormalized=0,this._speedSampler=new x,this._speedNormalizeList=[64,128,256,384,512,768,1024,1536,2048,3072,4096],this._isEarlyEofReconnecting=!1,this._paused=!1,this._resumeFrom=0,this._onDataArrival=null,this._onSeeked=null,this._onError=null,this._onComplete=null,this._onRedirect=null,this._onRecoveredEarlyEof=null,this._selectSeekHandler(),this._selectLoader(),this._createLoader()}destroy(){this._loader.isWorking()&&this._loader.abort(),this._loader.destroy(),this._loader=null,this._loaderClass=null,this._dataSource=null,this._stashBuffer=null,this._stashUsed=this._stashSize=this._bufferSize=this._stashByteStart=0,this._currentRange=null,this._speedSampler=null,this._isEarlyEofReconnecting=!1,this._onDataArrival=null,this._onSeeked=null,this._onError=null,this._onComplete=null,this._onRedirect=null,this._onRecoveredEarlyEof=null,this._extraData=null}isWorking(){return this._loader&&this._loader.isWorking()&&!this._paused}isPaused(){return this._paused}get status(){return this._loader.status}get extraData(){return this._extraData}set extraData(E){this._extraData=E}get onDataArrival(){return this._onDataArrival}set onDataArrival(E){this._onDataArrival=E}get onSeeked(){return this._onSeeked}set onSeeked(E){this._onSeeked=E}get onError(){return this._onError}set onError(E){this._onError=E}get onComplete(){return this._onComplete}set onComplete(E){this._onComplete=E}get onRedirect(){return this._onRedirect}set onRedirect(E){this._onRedirect=E}get onRecoveredEarlyEof(){return this._onRecoveredEarlyEof}set onRecoveredEarlyEof(E){this._onRecoveredEarlyEof=E}get currentURL(){return this._dataSource.url}get hasRedirect(){return this._redirectedURL!=null||this._dataSource.redirectedURL!=null}get currentRedirectedURL(){return this._redirectedURL||this._dataSource.redirectedURL}get currentSpeed(){return this._loaderClass===U?this._loader.currentSpeed:this._speedSampler.lastSecondKBps}get loaderType(){return this._loader.type}_selectSeekHandler(){let E=this._config;if(E.seekType==="range")this._seekHandler=new te(this._config.rangeLoadZeroStart);else if(E.seekType==="param"){let B=E.seekParamStart||"bstart",N=E.seekParamEnd||"bend";this._seekHandler=new oe(B,N)}else if(E.seekType==="custom"){if(typeof E.customSeekHandler!="function")throw new g("Custom seekType specified in config but invalid customSeekHandler!");this._seekHandler=new E.customSeekHandler}else throw new g(`Invalid seekType in config: ${E.seekType}`)}_selectLoader(){if(this._config.customLoader!=null)this._loaderClass=this._config.customLoader;else if(this._isWebSocketURL)this._loaderClass=G;else if(R.isSupported())this._loaderClass=R;else if(f.isSupported())this._loaderClass=f;else if(U.isSupported())this._loaderClass=U;else throw new O("Your browser doesn't support xhr with arraybuffer responseType!")}_createLoader(){this._loader=new this._loaderClass(this._seekHandler,this._config),this._loader.needStashBuffer===!1&&(this._enableStash=!1),this._loader.onContentLengthKnown=this._onContentLengthKnown.bind(this),this._loader.onURLRedirect=this._onURLRedirect.bind(this),this._loader.onDataArrival=this._onLoaderChunkArrival.bind(this),this._loader.onComplete=this._onLoaderComplete.bind(this),this._loader.onError=this._onLoaderError.bind(this)}open(E){this._currentRange={from:0,to:-1},E&&(this._currentRange.from=E),this._speedSampler.reset(),E||(this._fullRequestFlag=!0),this._loader.open(this._dataSource,Object.assign({},this._currentRange))}abort(){this._loader.abort(),this._paused&&(this._paused=!1,this._resumeFrom=0)}pause(){this.isWorking()&&(this._loader.abort(),this._stashUsed!==0?(this._resumeFrom=this._stashByteStart,this._currentRange.to=this._stashByteStart-1):this._resumeFrom=this._currentRange.to+1,this._stashUsed=0,this._stashByteStart=0,this._paused=!0)}resume(){if(this._paused){this._paused=!1;let E=this._resumeFrom;this._resumeFrom=0,this._internalSeek(E,!0)}}seek(E){this._paused=!1,this._stashUsed=0,this._stashByteStart=0,this._internalSeek(E,!0)}_internalSeek(E,B){this._loader.isWorking()&&this._loader.abort(),this._flushStashBuffer(B),this._loader.destroy(),this._loader=null;let N={from:E,to:-1};this._currentRange={from:N.from,to:-1},this._speedSampler.reset(),this._stashSize=this._stashInitialSize,this._createLoader(),this._loader.open(this._dataSource,N),this._onSeeked&&this._onSeeked()}updateUrl(E){if(!E||typeof E!="string"||E.length===0)throw new g("Url must be a non-empty string!");this._dataSource.url=E}_expandBuffer(E){let B=this._stashSize;for(;B+1024*1024*1<E;)B*=2;if(B+=1024*1024*1,B===this._bufferSize)return;let N=new ArrayBuffer(B);if(this._stashUsed>0){let V=new Uint8Array(this._stashBuffer,0,this._stashUsed);new Uint8Array(N,0,B).set(V,0)}this._stashBuffer=N,this._bufferSize=B}_normalizeSpeed(E){let B=this._speedNormalizeList,N=B.length-1,V=0,q=0,ue=N;if(E<B[0])return B[0];for(;q<=ue;){if(V=q+Math.floor((ue-q)/2),V===N||E>=B[V]&&E<B[V+1])return B[V];B[V]<E?q=V+1:ue=V-1}}_adjustStashSize(E){let B=0;this._config.isLive||E<512?B=E:E>=512&&E<=1024?B=Math.floor(E*1.5):B=E*2,B>8192&&(B=8192);let N=B*1024+1024*1024*1;this._bufferSize<N&&this._expandBuffer(N),this._stashSize=B*1024}_dispatchChunks(E,B){return this._currentRange.to=B+E.byteLength-1,this._onDataArrival(E,B)}_onURLRedirect(E){this._redirectedURL=E,this._onRedirect&&this._onRedirect(E)}_onContentLengthKnown(E){E&&this._fullRequestFlag&&(this._totalLength=E,this._fullRequestFlag=!1)}_onLoaderChunkArrival(E,B,N){if(!this._onDataArrival)throw new _("IOController: No existing consumer (onDataArrival) callback!");if(this._paused)return;this._isEarlyEofReconnecting&&(this._isEarlyEofReconnecting=!1,this._onRecoveredEarlyEof&&this._onRecoveredEarlyEof()),this._speedSampler.addBytes(E.byteLength);let V=this._speedSampler.lastSecondKBps;if(V!==0){let q=this._normalizeSpeed(V);this._speedNormalized!==q&&(this._speedNormalized=q,this._adjustStashSize(q))}if(this._enableStash)if(this._stashUsed===0&&this._stashByteStart===0&&(this._stashByteStart=B),this._stashUsed+E.byteLength<=this._stashSize)new Uint8Array(this._stashBuffer,0,this._stashSize).set(new Uint8Array(E),this._stashUsed),this._stashUsed+=E.byteLength;else{let q=new Uint8Array(this._stashBuffer,0,this._bufferSize);if(this._stashUsed>0){let ue=this._stashBuffer.slice(0,this._stashUsed),ce=this._dispatchChunks(ue,this._stashByteStart);if(ce<ue.byteLength){if(ce>0){let Oe=new Uint8Array(ue,ce);q.set(Oe,0),this._stashUsed=Oe.byteLength,this._stashByteStart+=ce}}else this._stashUsed=0,this._stashByteStart+=ce;this._stashUsed+E.byteLength>this._bufferSize&&(this._expandBuffer(this._stashUsed+E.byteLength),q=new Uint8Array(this._stashBuffer,0,this._bufferSize)),q.set(new Uint8Array(E),this._stashUsed),this._stashUsed+=E.byteLength}else{let ue=this._dispatchChunks(E,B);if(ue<E.byteLength){let ce=E.byteLength-ue;ce>this._bufferSize&&(this._expandBuffer(ce),q=new Uint8Array(this._stashBuffer,0,this._bufferSize)),q.set(new Uint8Array(E,ue),0),this._stashUsed+=ce,this._stashByteStart=B+ue}}}else if(this._stashUsed===0){let q=this._dispatchChunks(E,B);if(q<E.byteLength){let ue=E.byteLength-q;ue>this._bufferSize&&this._expandBuffer(ue),new Uint8Array(this._stashBuffer,0,this._bufferSize).set(new Uint8Array(E,q),0),this._stashUsed+=ue,this._stashByteStart=B+q}}else{this._stashUsed+E.byteLength>this._bufferSize&&this._expandBuffer(this._stashUsed+E.byteLength);let q=new Uint8Array(this._stashBuffer,0,this._bufferSize);q.set(new Uint8Array(E),this._stashUsed),this._stashUsed+=E.byteLength;let ue=this._dispatchChunks(this._stashBuffer.slice(0,this._stashUsed),this._stashByteStart);if(ue<this._stashUsed&&ue>0){let ce=new Uint8Array(this._stashBuffer,ue);q.set(ce,0)}this._stashUsed-=ue,this._stashByteStart+=ue}}_flushStashBuffer(E){if(this._stashUsed>0){let B=this._stashBuffer.slice(0,this._stashUsed),N=this._dispatchChunks(B,this._stashByteStart),V=B.byteLength-N;if(N<B.byteLength)if(E)P.w(this.TAG,`${V} bytes unconsumed data remain when flush buffer, dropped`);else{if(N>0){let q=new Uint8Array(this._stashBuffer,0,this._bufferSize),ue=new Uint8Array(B,N);q.set(ue,0),this._stashUsed=ue.byteLength,this._stashByteStart+=N}return 0}return this._stashUsed=0,this._stashByteStart=0,V}return 0}_onLoaderComplete(E,B){this._flushStashBuffer(!0),this._onComplete&&this._onComplete(this._extraData)}_onLoaderError(E,B){switch(P.e(this.TAG,`Loader error, code = ${B.code}, msg = ${B.msg}`),this._flushStashBuffer(!1),this._isEarlyEofReconnecting&&(this._isEarlyEofReconnecting=!1,E=d.UNRECOVERABLE_EARLY_EOF),E){case d.EARLY_EOF:{if(!this._config.isLive&&this._totalLength){let N=this._currentRange.to+1;N<this._totalLength&&(P.w(this.TAG,"Connection lost, trying reconnect..."),this._isEarlyEofReconnecting=!0,this._internalSeek(N,!1));return}E=d.UNRECOVERABLE_EARLY_EOF;break}case d.UNRECOVERABLE_EARLY_EOF:case d.CONNECTING_TIMEOUT:case d.HTTP_STATUS_CODE_INVALID:case d.EXCEPTION:break}if(this._onError)this._onError(E,B);else throw new O("IOException: "+B.msg)}}var ne=ie;const le={enableWorker:!1,enableStashBuffer:!0,stashInitialSize:void 0,isLive:!1,lazyLoad:!0,lazyLoadMaxDuration:3*60,lazyLoadRecoverDuration:30,deferLoadAfterSourceOpen:!0,autoCleanupMaxBackwardDuration:3*60,autoCleanupMinBackwardDuration:2*60,statisticsInfoReportInterval:600,fixAudioTimestampGap:!0,accurateSeek:!1,seekType:"range",seekParamStart:"bstart",seekParamEnd:"bend",rangeLoadZeroStart:!1,customSeekHandler:void 0,reuseRedirectedURL:!1,headers:void 0,customLoader:void 0};function ae(){return Object.assign({},le)}class de{static supportMSEH264Playback(){return window.MediaSource&&window.MediaSource.isTypeSupported('video/mp4; codecs="avc1.42E01E,mp4a.40.2"')}static supportNetworkStreamIO(){let E=new ne({},ae()),B=E.loaderType;return E.destroy(),B=="fetch-stream-loader"||B=="xhr-moz-chunked-loader"}static getNetworkLoaderTypeName(){let E=new ne({},ae()),B=E.loaderType;return E.destroy(),B}static supportNativeMediaPlayback(E){de.videoElement==null&&(de.videoElement=window.document.createElement("video"));let B=de.videoElement.canPlayType(E);return B==="probably"||B=="maybe"}static getFeatureList(){let E={mseFlvPlayback:!1,mseLiveFlvPlayback:!1,networkStreamIO:!1,networkLoaderName:"",nativeMP4H264Playback:!1,nativeWebmVP8Playback:!1,nativeWebmVP9Playback:!1};return E.mseFlvPlayback=de.supportMSEH264Playback(),E.networkStreamIO=de.supportNetworkStreamIO(),E.networkLoaderName=de.getNetworkLoaderTypeName(),E.mseLiveFlvPlayback=E.mseFlvPlayback&&E.networkStreamIO,E.nativeMP4H264Playback=de.supportNativeMediaPlayback('video/mp4; codecs="avc1.42001E, mp4a.40.2"'),E.nativeWebmVP8Playback=de.supportNativeMediaPlayback('video/webm; codecs="vp8.0, vorbis"'),E.nativeWebmVP9Playback=de.supportNativeMediaPlayback('video/webm; codecs="vp9"'),E}}var se=de,me={ERROR:"error",LOADING_COMPLETE:"loading_complete",RECOVERED_EARLY_EOF:"recovered_early_eof",MEDIA_INFO:"media_info",METADATA_ARRIVED:"metadata_arrived",SCRIPTDATA_ARRIVED:"scriptdata_arrived",STATISTICS_INFO:"statistics_info"};class ge{static get forceGlobalTag(){return P.FORCE_GLOBAL_TAG}static set forceGlobalTag(E){P.FORCE_GLOBAL_TAG=E,ge._notifyChange()}static get globalTag(){return P.GLOBAL_TAG}static set globalTag(E){P.GLOBAL_TAG=E,ge._notifyChange()}static get enableAll(){return P.ENABLE_VERBOSE&&P.ENABLE_DEBUG&&P.ENABLE_INFO&&P.ENABLE_WARN&&P.ENABLE_ERROR}static set enableAll(E){P.ENABLE_VERBOSE=E,P.ENABLE_DEBUG=E,P.ENABLE_INFO=E,P.ENABLE_WARN=E,P.ENABLE_ERROR=E,ge._notifyChange()}static get enableDebug(){return P.ENABLE_DEBUG}static set enableDebug(E){P.ENABLE_DEBUG=E,ge._notifyChange()}static get enableVerbose(){return P.ENABLE_VERBOSE}static set enableVerbose(E){P.ENABLE_VERBOSE=E,ge._notifyChange()}static get enableInfo(){return P.ENABLE_INFO}static set enableInfo(E){P.ENABLE_INFO=E,ge._notifyChange()}static get enableWarn(){return P.ENABLE_WARN}static set enableWarn(E){P.ENABLE_WARN=E,ge._notifyChange()}static get enableError(){return P.ENABLE_ERROR}static set enableError(E){P.ENABLE_ERROR=E,ge._notifyChange()}static getConfig(){return{globalTag:P.GLOBAL_TAG,forceGlobalTag:P.FORCE_GLOBAL_TAG,enableVerbose:P.ENABLE_VERBOSE,enableDebug:P.ENABLE_DEBUG,enableInfo:P.ENABLE_INFO,enableWarn:P.ENABLE_WARN,enableError:P.ENABLE_ERROR,enableCallback:P.ENABLE_CALLBACK}}static applyConfig(E){P.GLOBAL_TAG=E.globalTag,P.FORCE_GLOBAL_TAG=E.forceGlobalTag,P.ENABLE_VERBOSE=E.enableVerbose,P.ENABLE_DEBUG=E.enableDebug,P.ENABLE_INFO=E.enableInfo,P.ENABLE_WARN=E.enableWarn,P.ENABLE_ERROR=E.enableError,P.ENABLE_CALLBACK=E.enableCallback}static _notifyChange(){let E=ge.emitter;if(E.listenerCount("change")>0){let B=ge.getConfig();E.emit("change",B)}}static registerListener(E){ge.emitter.addListener("change",E)}static removeListener(E){ge.emitter.removeListener("change",E)}static addLogListener(E){P.emitter.addListener("log",E),P.emitter.listenerCount("log")>0&&(P.ENABLE_CALLBACK=!0,ge._notifyChange())}static removeLogListener(E){P.emitter.removeListener("log",E),P.emitter.listenerCount("log")===0&&(P.ENABLE_CALLBACK=!1,ge._notifyChange())}}ge.emitter=new(b());var xe=ge;class Me{constructor(){this.mimeType=null,this.duration=null,this.hasAudio=null,this.hasVideo=null,this.audioCodec=null,this.videoCodec=null,this.audioDataRate=null,this.videoDataRate=null,this.audioSampleRate=null,this.audioChannelCount=null,this.width=null,this.height=null,this.fps=null,this.profile=null,this.level=null,this.refFrames=null,this.chromaFormat=null,this.sarNum=null,this.sarDen=null,this.metadata=null,this.segments=null,this.segmentCount=null,this.hasKeyframesIndex=null,this.keyframesIndex=null}isComplete(){let E=this.hasAudio===!1||this.hasAudio===!0&&this.audioCodec!=null&&this.audioSampleRate!=null&&this.audioChannelCount!=null,B=this.hasVideo===!1||this.hasVideo===!0&&this.videoCodec!=null&&this.width!=null&&this.height!=null&&this.fps!=null&&this.profile!=null&&this.level!=null&&this.refFrames!=null&&this.chromaFormat!=null&&this.sarNum!=null&&this.sarDen!=null;return this.mimeType!=null&&this.duration!=null&&this.metadata!=null&&this.hasKeyframesIndex!=null&&E&&B}isSeekable(){return this.hasKeyframesIndex===!0}getNearestKeyframe(E){if(this.keyframesIndex==null)return null;let B=this.keyframesIndex,N=this._search(B.times,E);return{index:N,milliseconds:B.times[N],fileposition:B.filepositions[N]}}_search(E,B){let N=0,V=E.length-1,q=0,ue=0,ce=V;for(B<E[0]&&(N=0,ue=ce+1);ue<=ce;)if(q=ue+Math.floor((ce-ue)/2),q===V||B>=E[q]&&B<E[q+1]){N=q;break}else E[q]<B?ue=q+1:ce=q-1;return N}}var Ne=Me;function We(Ee,E,B){let N=Ee;if(E+B<N.length){for(;B--;)if((N[++E]&192)!==128)return!1;return!0}else return!1}function nt(Ee){let E=[],B=Ee,N=0,V=Ee.length;for(;N<V;){if(B[N]<128){E.push(String.fromCharCode(B[N])),++N;continue}else if(!(B[N]<192)){if(B[N]<224){if(We(B,N,1)){let q=(B[N]&31)<<6|B[N+1]&63;if(q>=128){E.push(String.fromCharCode(q&65535)),N+=2;continue}}}else if(B[N]<240){if(We(B,N,2)){let q=(B[N]&15)<<12|(B[N+1]&63)<<6|B[N+2]&63;if(q>=2048&&(q&63488)!==55296){E.push(String.fromCharCode(q&65535)),N+=3;continue}}}else if(B[N]<248&&We(B,N,3)){let q=(B[N]&7)<<18|(B[N+1]&63)<<12|(B[N+2]&63)<<6|B[N+3]&63;if(q>65536&&q<1114112){q-=65536,E.push(String.fromCharCode(q>>>10|55296)),E.push(String.fromCharCode(q&1023|56320)),N+=4;continue}}}E.push("\uFFFD"),++N}return E.join("")}var qe=nt;let ot=function(){let Ee=new ArrayBuffer(2);return new DataView(Ee).setInt16(0,256,!0),new Int16Array(Ee)[0]===256}();class mt{static parseScriptData(E,B,N){let V={};try{let q=mt.parseValue(E,B,N),ue=mt.parseValue(E,B+q.size,N-q.size);V[q.data]=ue.data}catch(q){P.e("AMF",q.toString())}return V}static parseObject(E,B,N){if(N<3)throw new _("Data not enough when parse ScriptDataObject");let V=mt.parseString(E,B,N),q=mt.parseValue(E,B+V.size,N-V.size),ue=q.objectEnd;return{data:{name:V.data,value:q.data},size:V.size+q.size,objectEnd:ue}}static parseVariable(E,B,N){return mt.parseObject(E,B,N)}static parseString(E,B,N){if(N<2)throw new _("Data not enough when parse String");let q=new DataView(E,B,N).getUint16(0,!ot),ue;return q>0?ue=qe(new Uint8Array(E,B+2,q)):ue="",{data:ue,size:2+q}}static parseLongString(E,B,N){if(N<4)throw new _("Data not enough when parse LongString");let q=new DataView(E,B,N).getUint32(0,!ot),ue;return q>0?ue=qe(new Uint8Array(E,B+4,q)):ue="",{data:ue,size:4+q}}static parseDate(E,B,N){if(N<10)throw new _("Data size invalid when parse Date");let V=new DataView(E,B,N),q=V.getFloat64(0,!ot),ue=V.getInt16(8,!ot);return q+=ue*60*1e3,{data:new Date(q),size:10}}static parseValue(E,B,N){if(N<1)throw new _("Data not enough when parse Value");let V=new DataView(E,B,N),q=1,ue=V.getUint8(0),ce,Oe=!1;try{switch(ue){case 0:ce=V.getFloat64(1,!ot),q+=8;break;case 1:{ce=!!V.getUint8(1),q+=1;break}case 2:{let Se=mt.parseString(E,B+1,N-1);ce=Se.data,q+=Se.size;break}case 3:{ce={};let Se=0;for((V.getUint32(N-4,!ot)&16777215)===9&&(Se=3);q<N-4;){let Ue=mt.parseObject(E,B+q,N-q-Se);if(Ue.objectEnd)break;ce[Ue.data.name]=Ue.data.value,q+=Ue.size}q<=N-3&&(V.getUint32(q-1,!ot)&16777215)===9&&(q+=3);break}case 8:{ce={},q+=4;let Se=0;for((V.getUint32(N-4,!ot)&16777215)===9&&(Se=3);q<N-8;){let Ue=mt.parseVariable(E,B+q,N-q-Se);if(Ue.objectEnd)break;ce[Ue.data.name]=Ue.data.value,q+=Ue.size}q<=N-3&&(V.getUint32(q-1,!ot)&16777215)===9&&(q+=3);break}case 9:ce=void 0,q=1,Oe=!0;break;case 10:{ce=[];let Se=V.getUint32(1,!ot);q+=4;for(let Ue=0;Ue<Se;Ue++){let je=mt.parseValue(E,B+q,N-q);ce.push(je.data),q+=je.size}break}case 11:{let Se=mt.parseDate(E,B+1,N-1);ce=Se.data,q+=Se.size;break}case 12:{let Se=mt.parseString(E,B+1,N-1);ce=Se.data,q+=Se.size;break}default:q=N,P.w("AMF","Unsupported AMF value type "+ue)}}catch(Se){P.e("AMF",Se.toString())}return{data:ce,size:q,objectEnd:Oe}}}var vt=mt;class Ke{constructor(E){this.TAG="ExpGolomb",this._buffer=E,this._buffer_index=0,this._total_bytes=E.byteLength,this._total_bits=E.byteLength*8,this._current_word=0,this._current_word_bits_left=0}destroy(){this._buffer=null}_fillCurrentWord(){let E=this._total_bytes-this._buffer_index;if(E<=0)throw new _("ExpGolomb: _fillCurrentWord() but no bytes available");let B=Math.min(4,E),N=new Uint8Array(4);N.set(this._buffer.subarray(this._buffer_index,this._buffer_index+B)),this._current_word=new DataView(N.buffer).getUint32(0,!1),this._buffer_index+=B,this._current_word_bits_left=B*8}readBits(E){if(E>32)throw new g("ExpGolomb: readBits() bits exceeded max 32bits!");if(E<=this._current_word_bits_left){let ue=this._current_word>>>32-E;return this._current_word<<=E,this._current_word_bits_left-=E,ue}let B=this._current_word_bits_left?this._current_word:0;B=B>>>32-this._current_word_bits_left;let N=E-this._current_word_bits_left;this._fillCurrentWord();let V=Math.min(N,this._current_word_bits_left),q=this._current_word>>>32-V;return this._current_word<<=V,this._current_word_bits_left-=V,B=B<<V|q,B}readBool(){return this.readBits(1)===1}readByte(){return this.readBits(8)}_skipLeadingZero(){let E;for(E=0;E<this._current_word_bits_left;E++)if(this._current_word&2147483648>>>E)return this._current_word<<=E,this._current_word_bits_left-=E,E;return this._fillCurrentWord(),E+this._skipLeadingZero()}readUEG(){let E=this._skipLeadingZero();return this.readBits(E+1)-1}readSEG(){let E=this.readUEG();return E&1?E+1>>>1:-1*(E>>>1)}}var rt=Ke;class Ze{static _ebsp2rbsp(E){let B=E,N=B.byteLength,V=new Uint8Array(N),q=0;for(let ue=0;ue<N;ue++)ue>=2&&B[ue]===3&&B[ue-1]===0&&B[ue-2]===0||(V[q]=B[ue],q++);return new Uint8Array(V.buffer,0,q)}static parseSPS(E){let B=Ze._ebsp2rbsp(E),N=new rt(B);N.readByte();let V=N.readByte();N.readByte();let q=N.readByte();N.readUEG();let ue=Ze.getProfileString(V),ce=Ze.getLevelString(q),Oe=1,Se=420,Ue=[0,420,422,444],je=8;if((V===100||V===110||V===122||V===244||V===44||V===83||V===86||V===118||V===128||V===138||V===144)&&(Oe=N.readUEG(),Oe===3&&N.readBits(1),Oe<=3&&(Se=Ue[Oe]),je=N.readUEG()+8,N.readUEG(),N.readBits(1),N.readBool())){let mn=Oe!==3?8:12;for(let yn=0;yn<mn;yn++)N.readBool()&&(yn<6?Ze._skipScalingList(N,16):Ze._skipScalingList(N,64))}N.readUEG();let it=N.readUEG();if(it===0)N.readUEG();else if(it===1){N.readBits(1),N.readSEG(),N.readSEG();let mn=N.readUEG();for(let yn=0;yn<mn;yn++)N.readSEG()}let at=N.readUEG();N.readBits(1);let et=N.readUEG(),st=N.readUEG(),Je=N.readBits(1);Je===0&&N.readBits(1),N.readBits(1);let ke=0,ft=0,yt=0,Pt=0;N.readBool()&&(ke=N.readUEG(),ft=N.readUEG(),yt=N.readUEG(),Pt=N.readUEG());let Qt=1,Ct=1,It=0,Zt=!0,lt=0,Mt=0;if(N.readBool()){if(N.readBool()){let mn=N.readByte(),yn=[1,12,10,16,40,24,20,32,80,18,15,64,160,4,3,2],Zn=[1,11,11,11,33,11,11,11,33,11,11,33,99,3,2,1];mn>0&&mn<16?(Qt=yn[mn-1],Ct=Zn[mn-1]):mn===255&&(Qt=N.readByte()<<8|N.readByte(),Ct=N.readByte()<<8|N.readByte())}if(N.readBool()&&N.readBool(),N.readBool()&&(N.readBits(4),N.readBool()&&N.readBits(24)),N.readBool()&&(N.readUEG(),N.readUEG()),N.readBool()){let mn=N.readBits(32),yn=N.readBits(32);Zt=N.readBool(),lt=yn,Mt=mn*2,It=lt/Mt}}let Nt=1;(Qt!==1||Ct!==1)&&(Nt=Qt/Ct);let Vt=0,Kt=0;if(Oe===0)Vt=1,Kt=2-Je;else{let mn=Oe===3?1:2,yn=Oe===1?2:1;Vt=mn,Kt=yn*(2-Je)}let qt=(et+1)*16,ln=(2-Je)*((st+1)*16);qt-=(ke+ft)*Vt,ln-=(yt+Pt)*Kt;let pn=Math.ceil(qt*Nt);return N.destroy(),N=null,{profile_string:ue,level_string:ce,bit_depth:je,ref_frames:at,chroma_format:Se,chroma_format_string:Ze.getChromaFormatString(Se),frame_rate:{fixed:Zt,fps:It,fps_den:Mt,fps_num:lt},sar_ratio:{width:Qt,height:Ct},codec_size:{width:qt,height:ln},present_size:{width:pn,height:ln}}}static _skipScalingList(E,B){let N=8,V=8,q=0;for(let ue=0;ue<B;ue++)V!==0&&(q=E.readSEG(),V=(N+q+256)%256),N=V===0?N:V}static getProfileString(E){switch(E){case 66:return"Baseline";case 77:return"Main";case 88:return"Extended";case 100:return"High";case 110:return"High10";case 122:return"High422";case 244:return"High444";default:return"Unknown"}}static getLevelString(E){return(E/10).toFixed(1)}static getChromaFormatString(E){switch(E){case 420:return"4:2:0";case 422:return"4:2:2";case 444:return"4:4:4";default:return"Unknown"}}}var Ve=Ze,He={OK:"OK",FORMAT_ERROR:"FormatError",FORMAT_UNSUPPORTED:"FormatUnsupported",CODEC_UNSUPPORTED:"CodecUnsupported"};function be(Ee){return Ee>>>8&255|(Ee&255)<<8}function Ie(Ee){return(Ee&4278190080)>>>24|(Ee&16711680)>>>8|(Ee&65280)<<8|(Ee&255)<<24}function Te(Ee,E){return Ee[E]<<24|Ee[E+1]<<16|Ee[E+2]<<8|Ee[E+3]}class Re{constructor(E,B){this.TAG="FLVDemuxer",this._config=B,this._onError=null,this._onMediaInfo=null,this._onMetaDataArrived=null,this._onScriptDataArrived=null,this._onTrackMetadata=null,this._onDataAvailable=null,this._dataOffset=E.dataOffset,this._firstParse=!0,this._dispatch=!1,this._hasAudio=E.hasAudioTrack,this._hasVideo=E.hasVideoTrack,this._hasAudioFlagOverrided=!1,this._hasVideoFlagOverrided=!1,this._audioInitialMetadataDispatched=!1,this._videoInitialMetadataDispatched=!1,this._mediaInfo=new Ne,this._mediaInfo.hasAudio=this._hasAudio,this._mediaInfo.hasVideo=this._hasVideo,this._metadata=null,this._audioMetadata=null,this._videoMetadata=null,this._naluLengthSize=4,this._timestampBase=0,this._timescale=1e3,this._duration=0,this._durationOverrided=!1,this._referenceFrameRate={fixed:!0,fps:23.976,fps_num:23976,fps_den:1e3},this._flvSoundRateTable=[5500,11025,22050,44100,48e3],this._mpegSamplingRates=[96e3,88200,64e3,48e3,44100,32e3,24e3,22050,16e3,12e3,11025,8e3,7350],this._mpegAudioV10SampleRateTable=[44100,48e3,32e3,0],this._mpegAudioV20SampleRateTable=[22050,24e3,16e3,0],this._mpegAudioV25SampleRateTable=[11025,12e3,8e3,0],this._mpegAudioL1BitRateTable=[0,32,64,96,128,160,192,224,256,288,320,352,384,416,448,-1],this._mpegAudioL2BitRateTable=[0,32,48,56,64,80,96,112,128,160,192,224,256,320,384,-1],this._mpegAudioL3BitRateTable=[0,32,40,48,56,64,80,96,112,128,160,192,224,256,320,-1],this._videoTrack={type:"video",id:1,sequenceNumber:0,samples:[],length:0},this._audioTrack={type:"audio",id:2,sequenceNumber:0,samples:[],length:0},this._littleEndian=function(){let N=new ArrayBuffer(2);return new DataView(N).setInt16(0,256,!0),new Int16Array(N)[0]===256}()}destroy(){this._mediaInfo=null,this._metadata=null,this._audioMetadata=null,this._videoMetadata=null,this._videoTrack=null,this._audioTrack=null,this._onError=null,this._onMediaInfo=null,this._onMetaDataArrived=null,this._onScriptDataArrived=null,this._onTrackMetadata=null,this._onDataAvailable=null}static probe(E){let B=new Uint8Array(E),N={match:!1};if(B[0]!==70||B[1]!==76||B[2]!==86||B[3]!==1)return N;let V=(B[4]&4)>>>2!==0,q=(B[4]&1)!==0,ue=Te(B,5);return ue<9?N:{match:!0,consumed:ue,dataOffset:ue,hasAudioTrack:V,hasVideoTrack:q}}bindDataSource(E){return E.onDataArrival=this.parseChunks.bind(this),this}get onTrackMetadata(){return this._onTrackMetadata}set onTrackMetadata(E){this._onTrackMetadata=E}get onMediaInfo(){return this._onMediaInfo}set onMediaInfo(E){this._onMediaInfo=E}get onMetaDataArrived(){return this._onMetaDataArrived}set onMetaDataArrived(E){this._onMetaDataArrived=E}get onScriptDataArrived(){return this._onScriptDataArrived}set onScriptDataArrived(E){this._onScriptDataArrived=E}get onError(){return this._onError}set onError(E){this._onError=E}get onDataAvailable(){return this._onDataAvailable}set onDataAvailable(E){this._onDataAvailable=E}get timestampBase(){return this._timestampBase}set timestampBase(E){this._timestampBase=E}get overridedDuration(){return this._duration}set overridedDuration(E){this._durationOverrided=!0,this._duration=E,this._mediaInfo.duration=E}set overridedHasAudio(E){this._hasAudioFlagOverrided=!0,this._hasAudio=E,this._mediaInfo.hasAudio=E}set overridedHasVideo(E){this._hasVideoFlagOverrided=!0,this._hasVideo=E,this._mediaInfo.hasVideo=E}resetMediaInfo(){this._mediaInfo=new Ne}_isInitialMetadataDispatched(){return this._hasAudio&&this._hasVideo?this._audioInitialMetadataDispatched&&this._videoInitialMetadataDispatched:this._hasAudio&&!this._hasVideo?this._audioInitialMetadataDispatched:!this._hasAudio&&this._hasVideo?this._videoInitialMetadataDispatched:!1}parseChunks(E,B){if(!this._onError||!this._onMediaInfo||!this._onTrackMetadata||!this._onDataAvailable)throw new _("Flv: onError & onMediaInfo & onTrackMetadata & onDataAvailable callback must be specified");let N=0,V=this._littleEndian;if(B===0)if(E.byteLength>13)N=Re.probe(E).dataOffset;else return 0;for(this._firstParse&&(this._firstParse=!1,B+N!==this._dataOffset&&P.w(this.TAG,"First time parsing but chunk byteStart invalid!"),new DataView(E,N).getUint32(0,!V)!==0&&P.w(this.TAG,"PrevTagSize0 !== 0 !!!"),N+=4);N<E.byteLength;){this._dispatch=!0;let q=new DataView(E,N);if(N+11+4>E.byteLength)break;let ue=q.getUint8(0),ce=q.getUint32(0,!V)&16777215;if(N+11+ce+4>E.byteLength)break;if(ue!==8&&ue!==9&&ue!==18){P.w(this.TAG,`Unsupported tag type ${ue}, skipped`),N+=11+ce+4;continue}let Oe=q.getUint8(4),Se=q.getUint8(5),Ue=q.getUint8(6),je=q.getUint8(7),it=Ue|Se<<8|Oe<<16|je<<24;(q.getUint32(7,!V)&16777215)!==0&&P.w(this.TAG,"Meet tag which has StreamID != 0!");let et=N+11;switch(ue){case 8:this._parseAudioData(E,et,ce,it);break;case 9:this._parseVideoData(E,et,ce,it,B+N);break;case 18:this._parseScriptData(E,et,ce);break}let st=q.getUint32(11+ce,!V);st!==11+ce&&P.w(this.TAG,`Invalid PrevTagSize ${st}`),N+=11+ce+4}return this._isInitialMetadataDispatched()&&this._dispatch&&(this._audioTrack.length||this._videoTrack.length)&&this._onDataAvailable(this._audioTrack,this._videoTrack),N}_parseScriptData(E,B,N){let V=vt.parseScriptData(E,B,N);if(V.hasOwnProperty("onMetaData")){if(V.onMetaData==null||typeof V.onMetaData!="object"){P.w(this.TAG,"Invalid onMetaData structure!");return}this._metadata&&P.w(this.TAG,"Found another onMetaData tag!"),this._metadata=V;let q=this._metadata.onMetaData;if(this._onMetaDataArrived&&this._onMetaDataArrived(Object.assign({},q)),typeof q.hasAudio=="boolean"&&this._hasAudioFlagOverrided===!1&&(this._hasAudio=q.hasAudio,this._mediaInfo.hasAudio=this._hasAudio),typeof q.hasVideo=="boolean"&&this._hasVideoFlagOverrided===!1&&(this._hasVideo=q.hasVideo,this._mediaInfo.hasVideo=this._hasVideo),typeof q.audiodatarate=="number"&&(this._mediaInfo.audioDataRate=q.audiodatarate),typeof q.videodatarate=="number"&&(this._mediaInfo.videoDataRate=q.videodatarate),typeof q.width=="number"&&(this._mediaInfo.width=q.width),typeof q.height=="number"&&(this._mediaInfo.height=q.height),typeof q.duration=="number"){if(!this._durationOverrided){let ue=Math.floor(q.duration*this._timescale);this._duration=ue,this._mediaInfo.duration=ue}}else this._mediaInfo.duration=0;if(typeof q.framerate=="number"){let ue=Math.floor(q.framerate*1e3);if(ue>0){let ce=ue/1e3;this._referenceFrameRate.fixed=!0,this._referenceFrameRate.fps=ce,this._referenceFrameRate.fps_num=ue,this._referenceFrameRate.fps_den=1e3,this._mediaInfo.fps=ce}}if(typeof q.keyframes=="object"){this._mediaInfo.hasKeyframesIndex=!0;let ue=q.keyframes;this._mediaInfo.keyframesIndex=this._parseKeyframesIndex(ue),q.keyframes=null}else this._mediaInfo.hasKeyframesIndex=!1;this._dispatch=!1,this._mediaInfo.metadata=q,P.v(this.TAG,"Parsed onMetaData"),this._mediaInfo.isComplete()&&this._onMediaInfo(this._mediaInfo)}Object.keys(V).length>0&&this._onScriptDataArrived&&this._onScriptDataArrived(Object.assign({},V))}_parseKeyframesIndex(E){let B=[],N=[];for(let V=1;V<E.times.length;V++){let q=this._timestampBase+Math.floor(E.times[V]*1e3);B.push(q),N.push(E.filepositions[V])}return{times:B,filepositions:N}}_parseAudioData(E,B,N,V){if(N<=1){P.w(this.TAG,"Flv: Invalid audio packet, missing SoundData payload!");return}if(this._hasAudioFlagOverrided===!0&&this._hasAudio===!1)return;let q=this._littleEndian,ce=new DataView(E,B,N).getUint8(0),Oe=ce>>>4;if(Oe!==2&&Oe!==10){this._onError(He.CODEC_UNSUPPORTED,"Flv: Unsupported audio codec idx: "+Oe);return}let Se=0,Ue=(ce&12)>>>2;if(Ue>=0&&Ue<=4)Se=this._flvSoundRateTable[Ue];else{this._onError(He.FORMAT_ERROR,"Flv: Invalid audio sample rate idx: "+Ue);return}let je=(ce&2)>>>1,it=ce&1,at=this._audioMetadata,et=this._audioTrack;if(at||(this._hasAudio===!1&&this._hasAudioFlagOverrided===!1&&(this._hasAudio=!0,this._mediaInfo.hasAudio=!0),at=this._audioMetadata={},at.type="audio",at.id=et.id,at.timescale=this._timescale,at.duration=this._duration,at.audioSampleRate=Se,at.channelCount=it===0?1:2),Oe===10){let st=this._parseAACAudioData(E,B+1,N-1);if(st==null)return;if(st.packetType===0){at.config&&P.w(this.TAG,"Found another AudioSpecificConfig!");let Je=st.data;at.audioSampleRate=Je.samplingRate,at.channelCount=Je.channelCount,at.codec=Je.codec,at.originalCodec=Je.originalCodec,at.config=Je.config,at.refSampleDuration=1024/at.audioSampleRate*at.timescale,P.v(this.TAG,"Parsed AudioSpecificConfig"),this._isInitialMetadataDispatched()?this._dispatch&&(this._audioTrack.length||this._videoTrack.length)&&this._onDataAvailable(this._audioTrack,this._videoTrack):this._audioInitialMetadataDispatched=!0,this._dispatch=!1,this._onTrackMetadata("audio",at);let ke=this._mediaInfo;ke.audioCodec=at.originalCodec,ke.audioSampleRate=at.audioSampleRate,ke.audioChannelCount=at.channelCount,ke.hasVideo?ke.videoCodec!=null&&(ke.mimeType='video/x-flv; codecs="'+ke.videoCodec+","+ke.audioCodec+'"'):ke.mimeType='video/x-flv; codecs="'+ke.audioCodec+'"',ke.isComplete()&&this._onMediaInfo(ke)}else if(st.packetType===1){let Je=this._timestampBase+V,ke={unit:st.data,length:st.data.byteLength,dts:Je,pts:Je};et.samples.push(ke),et.length+=st.data.length}else P.e(this.TAG,`Flv: Unsupported AAC data type ${st.packetType}`)}else if(Oe===2){if(!at.codec){let ft=this._parseMP3AudioData(E,B+1,N-1,!0);if(ft==null)return;at.audioSampleRate=ft.samplingRate,at.channelCount=ft.channelCount,at.codec=ft.codec,at.originalCodec=ft.originalCodec,at.refSampleDuration=1152/at.audioSampleRate*at.timescale,P.v(this.TAG,"Parsed MPEG Audio Frame Header"),this._audioInitialMetadataDispatched=!0,this._onTrackMetadata("audio",at);let yt=this._mediaInfo;yt.audioCodec=at.codec,yt.audioSampleRate=at.audioSampleRate,yt.audioChannelCount=at.channelCount,yt.audioDataRate=ft.bitRate,yt.hasVideo?yt.videoCodec!=null&&(yt.mimeType='video/x-flv; codecs="'+yt.videoCodec+","+yt.audioCodec+'"'):yt.mimeType='video/x-flv; codecs="'+yt.audioCodec+'"',yt.isComplete()&&this._onMediaInfo(yt)}let st=this._parseMP3AudioData(E,B+1,N-1,!1);if(st==null)return;let Je=this._timestampBase+V,ke={unit:st,length:st.byteLength,dts:Je,pts:Je};et.samples.push(ke),et.length+=st.length}}_parseAACAudioData(E,B,N){if(N<=1){P.w(this.TAG,"Flv: Invalid AAC packet, missing AACPacketType or/and Data!");return}let V={},q=new Uint8Array(E,B,N);return V.packetType=q[0],q[0]===0?V.data=this._parseAACAudioSpecificConfig(E,B+1,N-1):V.data=q.subarray(1),V}_parseAACAudioSpecificConfig(E,B,N){let V=new Uint8Array(E,B,N),q=null,ue=0,ce=0,Oe=null,Se=0,Ue=null;if(ue=ce=V[0]>>>3,Se=(V[0]&7)<<1|V[1]>>>7,Se<0||Se>=this._mpegSamplingRates.length){this._onError(He.FORMAT_ERROR,"Flv: AAC invalid sampling frequency index!");return}let je=this._mpegSamplingRates[Se],it=(V[1]&120)>>>3;if(it<0||it>=8){this._onError(He.FORMAT_ERROR,"Flv: AAC invalid channel configuration");return}ue===5&&(Ue=(V[1]&7)<<1|V[2]>>>7,Oe=(V[2]&124)>>>2);let at=self.navigator.userAgent.toLowerCase();return at.indexOf("firefox")!==-1?Se>=6?(ue=5,q=new Array(4),Ue=Se-3):(ue=2,q=new Array(2),Ue=Se):at.indexOf("android")!==-1?(ue=2,q=new Array(2),Ue=Se):(ue=5,Ue=Se,q=new Array(4),Se>=6?Ue=Se-3:it===1&&(ue=2,q=new Array(2),Ue=Se)),q[0]=ue<<3,q[0]|=(Se&15)>>>1,q[1]=(Se&15)<<7,q[1]|=(it&15)<<3,ue===5&&(q[1]|=(Ue&15)>>>1,q[2]=(Ue&1)<<7,q[2]|=8,q[3]=0),{config:q,samplingRate:je,channelCount:it,codec:"mp4a.40."+ue,originalCodec:"mp4a.40."+ce}}_parseMP3AudioData(E,B,N,V){if(N<4){P.w(this.TAG,"Flv: Invalid MP3 packet, header missing!");return}let q=this._littleEndian,ue=new Uint8Array(E,B,N),ce=null;if(V){if(ue[0]!==255)return;let Oe=ue[1]>>>3&3,Se=(ue[1]&6)>>1,Ue=(ue[2]&240)>>>4,je=(ue[2]&12)>>>2,at=(ue[3]>>>6&3)!==3?2:1,et=0,st=0,Je=34,ke="mp3";switch(Oe){case 0:et=this._mpegAudioV25SampleRateTable[je];break;case 2:et=this._mpegAudioV20SampleRateTable[je];break;case 3:et=this._mpegAudioV10SampleRateTable[je];break}switch(Se){case 1:Je=34,Ue<this._mpegAudioL3BitRateTable.length&&(st=this._mpegAudioL3BitRateTable[Ue]);break;case 2:Je=33,Ue<this._mpegAudioL2BitRateTable.length&&(st=this._mpegAudioL2BitRateTable[Ue]);break;case 3:Je=32,Ue<this._mpegAudioL1BitRateTable.length&&(st=this._mpegAudioL1BitRateTable[Ue]);break}ce={bitRate:st,samplingRate:et,channelCount:at,codec:ke,originalCodec:ke}}else ce=ue;return ce}_parseVideoData(E,B,N,V,q){if(N<=1){P.w(this.TAG,"Flv: Invalid video packet, missing VideoData payload!");return}if(this._hasVideoFlagOverrided===!0&&this._hasVideo===!1)return;let ue=new Uint8Array(E,B,N)[0],ce=(ue&240)>>>4,Oe=ue&15;if(Oe!==7){this._onError(He.CODEC_UNSUPPORTED,`Flv: Unsupported codec in video frame: ${Oe}`);return}this._parseAVCVideoPacket(E,B+1,N-1,V,q,ce)}_parseAVCVideoPacket(E,B,N,V,q,ue){if(N<4){P.w(this.TAG,"Flv: Invalid AVC packet, missing AVCPacketType or/and CompositionTime");return}let ce=this._littleEndian,Oe=new DataView(E,B,N),Se=Oe.getUint8(0),je=(Oe.getUint32(0,!ce)&16777215)<<8>>8;if(Se===0)this._parseAVCDecoderConfigurationRecord(E,B+4,N-4);else if(Se===1)this._parseAVCVideoData(E,B+4,N-4,V,q,ue,je);else if(Se!==2){this._onError(He.FORMAT_ERROR,`Flv: Invalid video packet type ${Se}`);return}}_parseAVCDecoderConfigurationRecord(E,B,N){if(N<7){P.w(this.TAG,"Flv: Invalid AVCDecoderConfigurationRecord, lack of data!");return}let V=this._videoMetadata,q=this._videoTrack,ue=this._littleEndian,ce=new DataView(E,B,N);V?typeof V.avcc!="undefined"&&P.w(this.TAG,"Found another AVCDecoderConfigurationRecord!"):(this._hasVideo===!1&&this._hasVideoFlagOverrided===!1&&(this._hasVideo=!0,this._mediaInfo.hasVideo=!0),V=this._videoMetadata={},V.type="video",V.id=q.id,V.timescale=this._timescale,V.duration=this._duration);let Oe=ce.getUint8(0),Se=ce.getUint8(1),Ue=ce.getUint8(2),je=ce.getUint8(3);if(Oe!==1||Se===0){this._onError(He.FORMAT_ERROR,"Flv: Invalid AVCDecoderConfigurationRecord");return}if(this._naluLengthSize=(ce.getUint8(4)&3)+1,this._naluLengthSize!==3&&this._naluLengthSize!==4){this._onError(He.FORMAT_ERROR,`Flv: Strange NaluLengthSizeMinusOne: ${this._naluLengthSize-1}`);return}let it=ce.getUint8(5)&31;if(it===0){this._onError(He.FORMAT_ERROR,"Flv: Invalid AVCDecoderConfigurationRecord: No SPS");return}else it>1&&P.w(this.TAG,`Flv: Strange AVCDecoderConfigurationRecord: SPS Count = ${it}`);let at=6;for(let st=0;st<it;st++){let Je=ce.getUint16(at,!ue);if(at+=2,Je===0)continue;let ke=new Uint8Array(E,B+at,Je);at+=Je;let ft=Ve.parseSPS(ke);if(st!==0)continue;V.codecWidth=ft.codec_size.width,V.codecHeight=ft.codec_size.height,V.presentWidth=ft.present_size.width,V.presentHeight=ft.present_size.height,V.profile=ft.profile_string,V.level=ft.level_string,V.bitDepth=ft.bit_depth,V.chromaFormat=ft.chroma_format,V.sarRatio=ft.sar_ratio,V.frameRate=ft.frame_rate,(ft.frame_rate.fixed===!1||ft.frame_rate.fps_num===0||ft.frame_rate.fps_den===0)&&(V.frameRate=this._referenceFrameRate);let yt=V.frameRate.fps_den,Pt=V.frameRate.fps_num;V.refSampleDuration=V.timescale*(yt/Pt);let Ut=ke.subarray(1,4),Qt="avc1.";for(let It=0;It<3;It++){let Zt=Ut[It].toString(16);Zt.length<2&&(Zt="0"+Zt),Qt+=Zt}V.codec=Qt;let Ct=this._mediaInfo;Ct.width=V.codecWidth,Ct.height=V.codecHeight,Ct.fps=V.frameRate.fps,Ct.profile=V.profile,Ct.level=V.level,Ct.refFrames=ft.ref_frames,Ct.chromaFormat=ft.chroma_format_string,Ct.sarNum=V.sarRatio.width,Ct.sarDen=V.sarRatio.height,Ct.videoCodec=Qt,Ct.hasAudio?Ct.audioCodec!=null&&(Ct.mimeType='video/x-flv; codecs="'+Ct.videoCodec+","+Ct.audioCodec+'"'):Ct.mimeType='video/x-flv; codecs="'+Ct.videoCodec+'"',Ct.isComplete()&&this._onMediaInfo(Ct)}let et=ce.getUint8(at);if(et===0){this._onError(He.FORMAT_ERROR,"Flv: Invalid AVCDecoderConfigurationRecord: No PPS");return}else et>1&&P.w(this.TAG,`Flv: Strange AVCDecoderConfigurationRecord: PPS Count = ${et}`);at++;for(let st=0;st<et;st++){let Je=ce.getUint16(at,!ue);at+=2,Je!==0&&(at+=Je)}V.avcc=new Uint8Array(N),V.avcc.set(new Uint8Array(E,B,N),0),P.v(this.TAG,"Parsed AVCDecoderConfigurationRecord"),this._isInitialMetadataDispatched()?this._dispatch&&(this._audioTrack.length||this._videoTrack.length)&&this._onDataAvailable(this._audioTrack,this._videoTrack):this._videoInitialMetadataDispatched=!0,this._dispatch=!1,this._onTrackMetadata("video",V)}_parseAVCVideoData(E,B,N,V,q,ue,ce){let Oe=this._littleEndian,Se=new DataView(E,B,N),Ue=[],je=0,it=0;const at=this._naluLengthSize;let et=this._timestampBase+V,st=ue===1;for(;it<N;){if(it+4>=N){P.w(this.TAG,`Malformed Nalu near timestamp ${et}, offset = ${it}, dataSize = ${N}`);break}let Je=Se.getUint32(it,!Oe);if(at===3&&(Je>>>=8),Je>N-at){P.w(this.TAG,`Malformed Nalus near timestamp ${et}, NaluSize > DataSize!`);return}let ke=Se.getUint8(it+at)&31;ke===5&&(st=!0);let ft=new Uint8Array(E,B+it,at+Je),yt={type:ke,data:ft};Ue.push(yt),je+=ft.byteLength,it+=at+Je}if(Ue.length){let Je=this._videoTrack,ke={units:Ue,length:je,isKeyframe:st,dts:et,cts:ce,pts:et+ce};st&&(ke.fileposition=q),Je.samples.push(ke),Je.length+=je}}}var Ge=Re;class Le{static init(){Le.types={avc1:[],avcC:[],btrt:[],dinf:[],dref:[],esds:[],ftyp:[],hdlr:[],mdat:[],mdhd:[],mdia:[],mfhd:[],minf:[],moof:[],moov:[],mp4a:[],mvex:[],mvhd:[],sdtp:[],stbl:[],stco:[],stsc:[],stsd:[],stsz:[],stts:[],tfdt:[],tfhd:[],traf:[],trak:[],trun:[],trex:[],tkhd:[],vmhd:[],smhd:[],".mp3":[]};for(let B in Le.types)Le.types.hasOwnProperty(B)&&(Le.types[B]=[B.charCodeAt(0),B.charCodeAt(1),B.charCodeAt(2),B.charCodeAt(3)]);let E=Le.constants={};E.FTYP=new Uint8Array([105,115,111,109,0,0,0,1,105,115,111,109,97,118,99,49]),E.STSD_PREFIX=new Uint8Array([0,0,0,0,0,0,0,1]),E.STTS=new Uint8Array([0,0,0,0,0,0,0,0]),E.STSC=E.STCO=E.STTS,E.STSZ=new Uint8Array([0,0,0,0,0,0,0,0,0,0,0,0]),E.HDLR_VIDEO=new Uint8Array([0,0,0,0,0,0,0,0,118,105,100,101,0,0,0,0,0,0,0,0,0,0,0,0,86,105,100,101,111,72,97,110,100,108,101,114,0]),E.HDLR_AUDIO=new Uint8Array([0,0,0,0,0,0,0,0,115,111,117,110,0,0,0,0,0,0,0,0,0,0,0,0,83,111,117,110,100,72,97,110,100,108,101,114,0]),E.DREF=new Uint8Array([0,0,0,0,0,0,0,1,0,0,0,12,117,114,108,32,0,0,0,1]),E.SMHD=new Uint8Array([0,0,0,0,0,0,0,0]),E.VMHD=new Uint8Array([0,0,0,1,0,0,0,0,0,0,0,0])}static box(E){let B=8,N=null,V=Array.prototype.slice.call(arguments,1),q=V.length;for(let ce=0;ce<q;ce++)B+=V[ce].byteLength;N=new Uint8Array(B),N[0]=B>>>24&255,N[1]=B>>>16&255,N[2]=B>>>8&255,N[3]=B&255,N.set(E,4);let ue=8;for(let ce=0;ce<q;ce++)N.set(V[ce],ue),ue+=V[ce].byteLength;return N}static generateInitSegment(E){let B=Le.box(Le.types.ftyp,Le.constants.FTYP),N=Le.moov(E),V=new Uint8Array(B.byteLength+N.byteLength);return V.set(B,0),V.set(N,B.byteLength),V}static moov(E){let B=Le.mvhd(E.timescale,E.duration),N=Le.trak(E),V=Le.mvex(E);return Le.box(Le.types.moov,B,N,V)}static mvhd(E,B){return Le.box(Le.types.mvhd,new Uint8Array([0,0,0,0,0,0,0,0,0,0,0,0,E>>>24&255,E>>>16&255,E>>>8&255,E&255,B>>>24&255,B>>>16&255,B>>>8&255,B&255,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,64,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,255,255,255,255]))}static trak(E){return Le.box(Le.types.trak,Le.tkhd(E),Le.mdia(E))}static tkhd(E){let B=E.id,N=E.duration,V=E.presentWidth,q=E.presentHeight;return Le.box(Le.types.tkhd,new Uint8Array([0,0,0,7,0,0,0,0,0,0,0,0,B>>>24&255,B>>>16&255,B>>>8&255,B&255,0,0,0,0,N>>>24&255,N>>>16&255,N>>>8&255,N&255,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,64,0,0,0,V>>>8&255,V&255,0,0,q>>>8&255,q&255,0,0]))}static mdia(E){return Le.box(Le.types.mdia,Le.mdhd(E),Le.hdlr(E),Le.minf(E))}static mdhd(E){let B=E.timescale,N=E.duration;return Le.box(Le.types.mdhd,new Uint8Array([0,0,0,0,0,0,0,0,0,0,0,0,B>>>24&255,B>>>16&255,B>>>8&255,B&255,N>>>24&255,N>>>16&255,N>>>8&255,N&255,85,196,0,0]))}static hdlr(E){let B=null;return E.type==="audio"?B=Le.constants.HDLR_AUDIO:B=Le.constants.HDLR_VIDEO,Le.box(Le.types.hdlr,B)}static minf(E){let B=null;return E.type==="audio"?B=Le.box(Le.types.smhd,Le.constants.SMHD):B=Le.box(Le.types.vmhd,Le.constants.VMHD),Le.box(Le.types.minf,B,Le.dinf(),Le.stbl(E))}static dinf(){return Le.box(Le.types.dinf,Le.box(Le.types.dref,Le.constants.DREF))}static stbl(E){return Le.box(Le.types.stbl,Le.stsd(E),Le.box(Le.types.stts,Le.constants.STTS),Le.box(Le.types.stsc,Le.constants.STSC),Le.box(Le.types.stsz,Le.constants.STSZ),Le.box(Le.types.stco,Le.constants.STCO))}static stsd(E){return E.type==="audio"?E.codec==="mp3"?Le.box(Le.types.stsd,Le.constants.STSD_PREFIX,Le.mp3(E)):Le.box(Le.types.stsd,Le.constants.STSD_PREFIX,Le.mp4a(E)):Le.box(Le.types.stsd,Le.constants.STSD_PREFIX,Le.avc1(E))}static mp3(E){let B=E.channelCount,N=E.audioSampleRate,V=new Uint8Array([0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,B,0,16,0,0,0,0,N>>>8&255,N&255,0,0]);return Le.box(Le.types[".mp3"],V)}static mp4a(E){let B=E.channelCount,N=E.audioSampleRate,V=new Uint8Array([0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,B,0,16,0,0,0,0,N>>>8&255,N&255,0,0]);return Le.box(Le.types.mp4a,V,Le.esds(E))}static esds(E){let B=E.config||[],N=B.length,V=new Uint8Array([0,0,0,0,3,23+N,0,1,0,4,15+N,64,21,0,0,0,0,0,0,0,0,0,0,0,5].concat([N]).concat(B).concat([6,1,2]));return Le.box(Le.types.esds,V)}static avc1(E){let B=E.avcc,N=E.codecWidth,V=E.codecHeight,q=new Uint8Array([0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,N>>>8&255,N&255,V>>>8&255,V&255,0,72,0,0,0,72,0,0,0,0,0,0,0,1,10,120,113,113,47,102,108,118,46,106,115,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,24,255,255]);return Le.box(Le.types.avc1,q,Le.box(Le.types.avcC,B))}static mvex(E){return Le.box(Le.types.mvex,Le.trex(E))}static trex(E){let B=E.id,N=new Uint8Array([0,0,0,0,B>>>24&255,B>>>16&255,B>>>8&255,B&255,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,1]);return Le.box(Le.types.trex,N)}static moof(E,B){return Le.box(Le.types.moof,Le.mfhd(E.sequenceNumber),Le.traf(E,B))}static mfhd(E){let B=new Uint8Array([0,0,0,0,E>>>24&255,E>>>16&255,E>>>8&255,E&255]);return Le.box(Le.types.mfhd,B)}static traf(E,B){let N=E.id,V=Le.box(Le.types.tfhd,new Uint8Array([0,0,0,0,N>>>24&255,N>>>16&255,N>>>8&255,N&255])),q=Le.box(Le.types.tfdt,new Uint8Array([0,0,0,0,B>>>24&255,B>>>16&255,B>>>8&255,B&255])),ue=Le.sdtp(E),ce=Le.trun(E,ue.byteLength+16+16+8+16+8+8);return Le.box(Le.types.traf,V,q,ce,ue)}static sdtp(E){let B=E.samples||[],N=B.length,V=new Uint8Array(4+N);for(let q=0;q<N;q++){let ue=B[q].flags;V[q+4]=ue.isLeading<<6|ue.dependsOn<<4|ue.isDependedOn<<2|ue.hasRedundancy}return Le.box(Le.types.sdtp,V)}static trun(E,B){let N=E.samples||[],V=N.length,q=12+16*V,ue=new Uint8Array(q);B+=8+q,ue.set([0,0,15,1,V>>>24&255,V>>>16&255,V>>>8&255,V&255,B>>>24&255,B>>>16&255,B>>>8&255,B&255],0);for(let ce=0;ce<V;ce++){let Oe=N[ce].duration,Se=N[ce].size,Ue=N[ce].flags,je=N[ce].cts;ue.set([Oe>>>24&255,Oe>>>16&255,Oe>>>8&255,Oe&255,Se>>>24&255,Se>>>16&255,Se>>>8&255,Se&255,Ue.isLeading<<2|Ue.dependsOn,Ue.isDependedOn<<6|Ue.hasRedundancy<<4|Ue.isNonSync,0,0,je>>>24&255,je>>>16&255,je>>>8&255,je&255],12+16*ce)}return Le.box(Le.types.trun,ue)}static mdat(E){return Le.box(Le.types.mdat,E)}}Le.init();var Fe=Le;class Qe{static getSilentFrame(E,B){if(E==="mp4a.40.2"){if(B===1)return new Uint8Array([0,200,0,128,35,128]);if(B===2)return new Uint8Array([33,0,73,144,2,25,0,35,128]);if(B===3)return new Uint8Array([0,200,0,128,32,132,1,38,64,8,100,0,142]);if(B===4)return new Uint8Array([0,200,0,128,32,132,1,38,64,8,100,0,128,44,128,8,2,56]);if(B===5)return new Uint8Array([0,200,0,128,32,132,1,38,64,8,100,0,130,48,4,153,0,33,144,2,56]);if(B===6)return new Uint8Array([0,200,0,128,32,132,1,38,64,8,100,0,130,48,4,153,0,33,144,2,0,178,0,32,8,224])}else{if(B===1)return new Uint8Array([1,64,34,128,163,78,230,128,186,8,0,0,0,28,6,241,193,10,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,94]);if(B===2)return new Uint8Array([1,64,34,128,163,94,230,128,186,8,0,0,0,0,149,0,6,241,161,10,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,94]);if(B===3)return new Uint8Array([1,64,34,128,163,94,230,128,186,8,0,0,0,0,149,0,6,241,161,10,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,90,94])}return null}}var tt=Qe;class dt{constructor(E,B,N,V,q){this.dts=E,this.pts=B,this.duration=N,this.originalDts=V,this.isSyncPoint=q,this.fileposition=null}}class pt{constructor(){this.beginDts=0,this.endDts=0,this.beginPts=0,this.endPts=0,this.originalBeginDts=0,this.originalEndDts=0,this.syncPoints=[],this.firstSample=null,this.lastSample=null}appendSyncPoint(E){E.isSyncPoint=!0,this.syncPoints.push(E)}}class Tt{constructor(){this._list=[]}clear(){this._list=[]}appendArray(E){let B=this._list;E.length!==0&&(B.length>0&&E[0].originalDts<B[B.length-1].originalDts&&this.clear(),Array.prototype.push.apply(B,E))}getLastSyncPointBeforeDts(E){if(this._list.length==0)return null;let B=this._list,N=0,V=B.length-1,q=0,ue=0,ce=V;for(E<B[0].dts&&(N=0,ue=ce+1);ue<=ce;)if(q=ue+Math.floor((ce-ue)/2),q===V||E>=B[q].dts&&E<B[q+1].dts){N=q;break}else B[q].dts<E?ue=q+1:ce=q-1;return this._list[N]}}class At{constructor(E){this._type=E,this._list=[],this._lastAppendLocation=-1}get type(){return this._type}get length(){return this._list.length}isEmpty(){return this._list.length===0}clear(){this._list=[],this._lastAppendLocation=-1}_searchNearestSegmentBefore(E){let B=this._list;if(B.length===0)return-2;let N=B.length-1,V=0,q=0,ue=N,ce=0;if(E<B[0].originalBeginDts)return ce=-1,ce;for(;q<=ue;)if(V=q+Math.floor((ue-q)/2),V===N||E>B[V].lastSample.originalDts&&E<B[V+1].originalBeginDts){ce=V;break}else B[V].originalBeginDts<E?q=V+1:ue=V-1;return ce}_searchNearestSegmentAfter(E){return this._searchNearestSegmentBefore(E)+1}append(E){let B=this._list,N=E,V=this._lastAppendLocation,q=0;V!==-1&&V<B.length&&N.originalBeginDts>=B[V].lastSample.originalDts&&(V===B.length-1||V<B.length-1&&N.originalBeginDts<B[V+1].originalBeginDts)?q=V+1:B.length>0&&(q=this._searchNearestSegmentBefore(N.originalBeginDts)+1),this._lastAppendLocation=q,this._list.splice(q,0,N)}getLastSegmentBefore(E){let B=this._searchNearestSegmentBefore(E);return B>=0?this._list[B]:null}getLastSampleBefore(E){let B=this.getLastSegmentBefore(E);return B!=null?B.lastSample:null}getLastSyncPointBefore(E){let B=this._searchNearestSegmentBefore(E),N=this._list[B].syncPoints;for(;N.length===0&&B>0;)B--,N=this._list[B].syncPoints;return N.length>0?N[N.length-1]:null}}class Ye{constructor(E){this.TAG="MP4Remuxer",this._config=E,this._isLive=E.isLive===!0,this._dtsBase=-1,this._dtsBaseInited=!1,this._audioDtsBase=1/0,this._videoDtsBase=1/0,this._audioNextDts=void 0,this._videoNextDts=void 0,this._audioStashedLastSample=null,this._videoStashedLastSample=null,this._audioMeta=null,this._videoMeta=null,this._audioSegmentInfoList=new At("audio"),this._videoSegmentInfoList=new At("video"),this._onInitSegment=null,this._onMediaSegment=null,this._forceFirstIDR=!!(S.chrome&&(S.version.major<50||S.version.major===50&&S.version.build<2661)),this._fillSilentAfterSeek=S.msedge||S.msie,this._mp3UseMpegAudio=!S.firefox,this._fillAudioTimestampGap=this._config.fixAudioTimestampGap}destroy(){this._dtsBase=-1,this._dtsBaseInited=!1,this._audioMeta=null,this._videoMeta=null,this._audioSegmentInfoList.clear(),this._audioSegmentInfoList=null,this._videoSegmentInfoList.clear(),this._videoSegmentInfoList=null,this._onInitSegment=null,this._onMediaSegment=null}bindDataSource(E){return E.onDataAvailable=this.remux.bind(this),E.onTrackMetadata=this._onTrackMetadataReceived.bind(this),this}get onInitSegment(){return this._onInitSegment}set onInitSegment(E){this._onInitSegment=E}get onMediaSegment(){return this._onMediaSegment}set onMediaSegment(E){this._onMediaSegment=E}insertDiscontinuity(){this._audioNextDts=this._videoNextDts=void 0}seek(E){this._audioStashedLastSample=null,this._videoStashedLastSample=null,this._videoSegmentInfoList.clear(),this._audioSegmentInfoList.clear()}remux(E,B){if(!this._onMediaSegment)throw new _("MP4Remuxer: onMediaSegment callback must be specificed!");this._dtsBaseInited||this._calculateDtsBase(E,B),this._remuxVideo(B),this._remuxAudio(E)}_onTrackMetadataReceived(E,B){let N=null,V="mp4",q=B.codec;if(E==="audio")this._audioMeta=B,B.codec==="mp3"&&this._mp3UseMpegAudio?(V="mpeg",q="",N=new Uint8Array):N=Fe.generateInitSegment(B);else if(E==="video")this._videoMeta=B,N=Fe.generateInitSegment(B);else return;if(!this._onInitSegment)throw new _("MP4Remuxer: onInitSegment callback must be specified!");this._onInitSegment(E,{type:E,data:N.buffer,codec:q,container:`${E}/${V}`,mediaDuration:B.duration})}_calculateDtsBase(E,B){this._dtsBaseInited||(E.samples&&E.samples.length&&(this._audioDtsBase=E.samples[0].dts),B.samples&&B.samples.length&&(this._videoDtsBase=B.samples[0].dts),this._dtsBase=Math.min(this._audioDtsBase,this._videoDtsBase),this._dtsBaseInited=!0)}flushStashedSamples(){let E=this._videoStashedLastSample,B=this._audioStashedLastSample,N={type:"video",id:1,sequenceNumber:0,samples:[],length:0};E!=null&&(N.samples.push(E),N.length=E.length);let V={type:"audio",id:2,sequenceNumber:0,samples:[],length:0};B!=null&&(V.samples.push(B),V.length=B.length),this._videoStashedLastSample=null,this._audioStashedLastSample=null,this._remuxVideo(N,!0),this._remuxAudio(V,!0)}_remuxAudio(E,B){if(this._audioMeta==null)return;let N=E,V=N.samples,q,ue=-1,ce=-1,Oe=-1,Se=this._audioMeta.refSampleDuration,Ue=this._audioMeta.codec==="mp3"&&this._mp3UseMpegAudio,je=this._dtsBaseInited&&this._audioNextDts===void 0,it=!1;if(!V||V.length===0||V.length===1&&!B)return;let at=0,et=null,st=0;Ue?(at=0,st=N.length):(at=8,st=8+N.length);let Je=null;if(V.length>1&&(Je=V.pop(),st-=Je.length),this._audioStashedLastSample!=null){let Ct=this._audioStashedLastSample;this._audioStashedLastSample=null,V.unshift(Ct),st+=Ct.length}Je!=null&&(this._audioStashedLastSample=Je);let ke=V[0].dts-this._dtsBase;if(this._audioNextDts)q=ke-this._audioNextDts;else if(this._audioSegmentInfoList.isEmpty())q=0,this._fillSilentAfterSeek&&!this._videoSegmentInfoList.isEmpty()&&this._audioMeta.originalCodec!=="mp3"&&(it=!0);else{let Ct=this._audioSegmentInfoList.getLastSampleBefore(ke);if(Ct!=null){let It=ke-(Ct.originalDts+Ct.duration);It<=3&&(It=0);let Zt=Ct.dts+Ct.duration+It;q=ke-Zt}else q=0}if(it){let Ct=ke-q,It=this._videoSegmentInfoList.getLastSegmentBefore(ke);if(It!=null&&It.beginDts<Ct){let Zt=tt.getSilentFrame(this._audioMeta.originalCodec,this._audioMeta.channelCount);if(Zt){let lt=It.beginDts,Mt=Ct-It.beginDts;P.v(this.TAG,`InsertPrefixSilentAudio: dts: ${lt}, duration: ${Mt}`),V.unshift({unit:Zt,dts:lt,pts:lt}),st+=Zt.byteLength}}else it=!1}let ft=[];for(let Ct=0;Ct<V.length;Ct++){let It=V[Ct],Zt=It.unit,lt=It.dts-this._dtsBase,Mt=lt-q;ue===-1&&(ue=Mt);let Lt=0;Ct!==V.length-1?Lt=V[Ct+1].dts-this._dtsBase-q-Mt:Je!=null?Lt=Je.dts-this._dtsBase-q-Mt:ft.length>=1?Lt=ft[ft.length-1].duration:Lt=Math.floor(Se);let Nt=!1,Vt=null;if(Lt>Se*1.5&&this._audioMeta.codec!=="mp3"&&this._fillAudioTimestampGap&&!S.safari){Nt=!0;let Kt=Math.abs(Lt-Se),qt=Math.ceil(Kt/Se),ln=Mt+Se;P.w(this.TAG,`Large audio timestamp gap detected, may cause AV sync to drift. Silent frames will be generated to avoid unsync.
-dts: ${Mt+Lt} ms, expected: ${Mt+Math.round(Se)} ms, delta: ${Math.round(Kt)} ms, generate: ${qt} frames`);let pn=tt.getSilentFrame(this._audioMeta.originalCodec,this._audioMeta.channelCount);pn==null&&(P.w(this.TAG,`Unable to generate silent frame for ${this._audioMeta.originalCodec} with ${this._audioMeta.channelCount} channels, repeat last frame`),pn=Zt),Vt=[];for(let yn=0;yn<qt;yn++){let Zn=Math.round(ln);if(Vt.length>0){let nn=Vt[Vt.length-1];nn.duration=Zn-nn.dts}let Nn={dts:Zn,pts:Zn,cts:0,unit:pn,size:pn.byteLength,duration:0,originalDts:lt,flags:{isLeading:0,dependsOn:1,isDependedOn:0,hasRedundancy:0}};Vt.push(Nn),st+=Nn.size,ln+=Se}let mn=Vt[Vt.length-1];mn.duration=Mt+Lt-mn.dts,Lt=Math.round(Se)}ft.push({dts:Mt,pts:Mt,cts:0,unit:It.unit,size:It.unit.byteLength,duration:Lt,originalDts:lt,flags:{isLeading:0,dependsOn:1,isDependedOn:0,hasRedundancy:0}}),Nt&&ft.push.apply(ft,Vt)}Ue?et=new Uint8Array(st):(et=new Uint8Array(st),et[0]=st>>>24&255,et[1]=st>>>16&255,et[2]=st>>>8&255,et[3]=st&255,et.set(Fe.types.mdat,4));for(let Ct=0;Ct<ft.length;Ct++){let It=ft[Ct].unit;et.set(It,at),at+=It.byteLength}let yt=ft[ft.length-1];ce=yt.dts+yt.duration,this._audioNextDts=ce;let Pt=new pt;Pt.beginDts=ue,Pt.endDts=ce,Pt.beginPts=ue,Pt.endPts=ce,Pt.originalBeginDts=ft[0].originalDts,Pt.originalEndDts=yt.originalDts+yt.duration,Pt.firstSample=new dt(ft[0].dts,ft[0].pts,ft[0].duration,ft[0].originalDts,!1),Pt.lastSample=new dt(yt.dts,yt.pts,yt.duration,yt.originalDts,!1),this._isLive||this._audioSegmentInfoList.append(Pt),N.samples=ft,N.sequenceNumber++;let Ut=null;Ue?Ut=new Uint8Array:Ut=Fe.moof(N,ue),N.samples=[],N.length=0;let Qt={type:"audio",data:this._mergeBoxes(Ut,et).buffer,sampleCount:ft.length,info:Pt};Ue&&je&&(Qt.timestampOffset=ue),this._onMediaSegment("audio",Qt)}_remuxVideo(E,B){if(this._videoMeta==null)return;let N=E,V=N.samples,q,ue=-1,ce=-1,Oe=-1,Se=-1;if(!V||V.length===0||V.length===1&&!B)return;let Ue=8,je=null,it=8+E.length,at=null;if(V.length>1&&(at=V.pop(),it-=at.length),this._videoStashedLastSample!=null){let yt=this._videoStashedLastSample;this._videoStashedLastSample=null,V.unshift(yt),it+=yt.length}at!=null&&(this._videoStashedLastSample=at);let et=V[0].dts-this._dtsBase;if(this._videoNextDts)q=et-this._videoNextDts;else if(this._videoSegmentInfoList.isEmpty())q=0;else{let yt=this._videoSegmentInfoList.getLastSampleBefore(et);if(yt!=null){let Pt=et-(yt.originalDts+yt.duration);Pt<=3&&(Pt=0);let Ut=yt.dts+yt.duration+Pt;q=et-Ut}else q=0}let st=new pt,Je=[];for(let yt=0;yt<V.length;yt++){let Pt=V[yt],Ut=Pt.dts-this._dtsBase,Qt=Pt.isKeyframe,Ct=Ut-q,It=Pt.cts,Zt=Ct+It;ue===-1&&(ue=Ct,Oe=Zt);let lt=0;if(yt!==V.length-1?lt=V[yt+1].dts-this._dtsBase-q-Ct:at!=null?lt=at.dts-this._dtsBase-q-Ct:Je.length>=1?lt=Je[Je.length-1].duration:lt=Math.floor(this._videoMeta.refSampleDuration),Qt){let Mt=new dt(Ct,Zt,lt,Pt.dts,!0);Mt.fileposition=Pt.fileposition,st.appendSyncPoint(Mt)}Je.push({dts:Ct,pts:Zt,cts:It,units:Pt.units,size:Pt.length,isKeyframe:Qt,duration:lt,originalDts:Ut,flags:{isLeading:0,dependsOn:Qt?2:1,isDependedOn:Qt?1:0,hasRedundancy:0,isNonSync:Qt?0:1}})}je=new Uint8Array(it),je[0]=it>>>24&255,je[1]=it>>>16&255,je[2]=it>>>8&255,je[3]=it&255,je.set(Fe.types.mdat,4);for(let yt=0;yt<Je.length;yt++){let Pt=Je[yt].units;for(;Pt.length;){let Qt=Pt.shift().data;je.set(Qt,Ue),Ue+=Qt.byteLength}}let ke=Je[Je.length-1];if(ce=ke.dts+ke.duration,Se=ke.pts+ke.duration,this._videoNextDts=ce,st.beginDts=ue,st.endDts=ce,st.beginPts=Oe,st.endPts=Se,st.originalBeginDts=Je[0].originalDts,st.originalEndDts=ke.originalDts+ke.duration,st.firstSample=new dt(Je[0].dts,Je[0].pts,Je[0].duration,Je[0].originalDts,Je[0].isKeyframe),st.lastSample=new dt(ke.dts,ke.pts,ke.duration,ke.originalDts,ke.isKeyframe),this._isLive||this._videoSegmentInfoList.append(st),N.samples=Je,N.sequenceNumber++,this._forceFirstIDR){let yt=Je[0].flags;yt.dependsOn=2,yt.isNonSync=0}let ft=Fe.moof(N,ue);N.samples=[],N.length=0,this._onMediaSegment("video",{type:"video",data:this._mergeBoxes(ft,je).buffer,sampleCount:Je.length,info:st})}_mergeBoxes(E,B){let N=new Uint8Array(E.byteLength+B.byteLength);return N.set(E,0),N.set(B,E.byteLength),N}}var ht=Ye,_t={IO_ERROR:"io_error",DEMUX_ERROR:"demux_error",INIT_SEGMENT:"init_segment",MEDIA_SEGMENT:"media_segment",LOADING_COMPLETE:"loading_complete",RECOVERED_EARLY_EOF:"recovered_early_eof",MEDIA_INFO:"media_info",METADATA_ARRIVED:"metadata_arrived",SCRIPTDATA_ARRIVED:"scriptdata_arrived",STATISTICS_INFO:"statistics_info",RECOMMEND_SEEKPOINT:"recommend_seekpoint"};class Ot{constructor(E,B){this.TAG="TransmuxingController",this._emitter=new(b()),this._config=B,E.segments||(E.segments=[{duration:E.duration,filesize:E.filesize,url:E.url}]),typeof E.cors!="boolean"&&(E.cors=!0),typeof E.withCredentials!="boolean"&&(E.withCredentials=!1),this._mediaDataSource=E,this._currentSegmentIndex=0;let N=0;this._mediaDataSource.segments.forEach(V=>{V.timestampBase=N,N+=V.duration,V.cors=E.cors,V.withCredentials=E.withCredentials,B.referrerPolicy&&(V.referrerPolicy=B.referrerPolicy)}),!isNaN(N)&&this._mediaDataSource.duration!==N&&(this._mediaDataSource.duration=N),this._mediaInfo=null,this._demuxer=null,this._remuxer=null,this._ioctl=null,this._pendingSeekTime=null,this._pendingResolveSeekPoint=null,this._statisticsReporter=null}destroy(){this._mediaInfo=null,this._mediaDataSource=null,this._statisticsReporter&&this._disableStatisticsReporter(),this._ioctl&&(this._ioctl.destroy(),this._ioctl=null),this._demuxer&&(this._demuxer.destroy(),this._demuxer=null),this._remuxer&&(this._remuxer.destroy(),this._remuxer=null),this._emitter.removeAllListeners(),this._emitter=null}on(E,B){this._emitter.addListener(E,B)}off(E,B){this._emitter.removeListener(E,B)}start(){this._loadSegment(0),this._enableStatisticsReporter()}_loadSegment(E,B){this._currentSegmentIndex=E;let N=this._mediaDataSource.segments[E],V=this._ioctl=new ne(N,this._config,E);V.onError=this._onIOException.bind(this),V.onSeeked=this._onIOSeeked.bind(this),V.onComplete=this._onIOComplete.bind(this),V.onRedirect=this._onIORedirect.bind(this),V.onRecoveredEarlyEof=this._onIORecoveredEarlyEof.bind(this),B?this._demuxer.bindDataSource(this._ioctl):V.onDataArrival=this._onInitChunkArrival.bind(this),V.open(B)}stop(){this._internalAbort(),this._disableStatisticsReporter()}_internalAbort(){this._ioctl&&(this._ioctl.destroy(),this._ioctl=null)}pause(){this._ioctl&&this._ioctl.isWorking()&&(this._ioctl.pause(),this._disableStatisticsReporter())}resume(){this._ioctl&&this._ioctl.isPaused()&&(this._ioctl.resume(),this._enableStatisticsReporter())}seek(E){if(this._mediaInfo==null||!this._mediaInfo.isSeekable())return;let B=this._searchSegmentIndexContains(E);if(B===this._currentSegmentIndex){let N=this._mediaInfo.segments[B];if(N==null)this._pendingSeekTime=E;else{let V=N.getNearestKeyframe(E);this._remuxer.seek(V.milliseconds),this._ioctl.seek(V.fileposition),this._pendingResolveSeekPoint=V.milliseconds}}else{let N=this._mediaInfo.segments[B];if(N==null)this._pendingSeekTime=E,this._internalAbort(),this._remuxer.seek(),this._remuxer.insertDiscontinuity(),this._loadSegment(B);else{let V=N.getNearestKeyframe(E);this._internalAbort(),this._remuxer.seek(E),this._remuxer.insertDiscontinuity(),this._demuxer.resetMediaInfo(),this._demuxer.timestampBase=this._mediaDataSource.segments[B].timestampBase,this._loadSegment(B,V.fileposition),this._pendingResolveSeekPoint=V.milliseconds,this._reportSegmentMediaInfo(B)}}this._enableStatisticsReporter()}_searchSegmentIndexContains(E){let B=this._mediaDataSource.segments,N=B.length-1;for(let V=0;V<B.length;V++)if(E<B[V].timestampBase){N=V-1;break}return N}_onInitChunkArrival(E,B){let N=null,V=0;if(B>0)this._demuxer.bindDataSource(this._ioctl),this._demuxer.timestampBase=this._mediaDataSource.segments[this._currentSegmentIndex].timestampBase,V=this._demuxer.parseChunks(E,B);else if((N=Ge.probe(E)).match){this._demuxer=new Ge(N,this._config),this._remuxer||(this._remuxer=new ht(this._config));let q=this._mediaDataSource;q.duration!=null&&!isNaN(q.duration)&&(this._demuxer.overridedDuration=q.duration),typeof q.hasAudio=="boolean"&&(this._demuxer.overridedHasAudio=q.hasAudio),typeof q.hasVideo=="boolean"&&(this._demuxer.overridedHasVideo=q.hasVideo),this._demuxer.timestampBase=q.segments[this._currentSegmentIndex].timestampBase,this._demuxer.onError=this._onDemuxException.bind(this),this._demuxer.onMediaInfo=this._onMediaInfo.bind(this),this._demuxer.onMetaDataArrived=this._onMetaDataArrived.bind(this),this._demuxer.onScriptDataArrived=this._onScriptDataArrived.bind(this),this._remuxer.bindDataSource(this._demuxer.bindDataSource(this._ioctl)),this._remuxer.onInitSegment=this._onRemuxerInitSegmentArrival.bind(this),this._remuxer.onMediaSegment=this._onRemuxerMediaSegmentArrival.bind(this),V=this._demuxer.parseChunks(E,B)}else N=null,P.e(this.TAG,"Non-FLV, Unsupported media type!"),Promise.resolve().then(()=>{this._internalAbort()}),this._emitter.emit(_t.DEMUX_ERROR,He.FORMAT_UNSUPPORTED,"Non-FLV, Unsupported media type"),V=0;return V}_onMediaInfo(E){this._mediaInfo==null&&(this._mediaInfo=Object.assign({},E),this._mediaInfo.keyframesIndex=null,this._mediaInfo.segments=[],this._mediaInfo.segmentCount=this._mediaDataSource.segments.length,Object.setPrototypeOf(this._mediaInfo,Ne.prototype));let B=Object.assign({},E);Object.setPrototypeOf(B,Ne.prototype),this._mediaInfo.segments[this._currentSegmentIndex]=B,this._reportSegmentMediaInfo(this._currentSegmentIndex),this._pendingSeekTime!=null&&Promise.resolve().then(()=>{let N=this._pendingSeekTime;this._pendingSeekTime=null,this.seek(N)})}_onMetaDataArrived(E){this._emitter.emit(_t.METADATA_ARRIVED,E)}_onScriptDataArrived(E){this._emitter.emit(_t.SCRIPTDATA_ARRIVED,E)}_onIOSeeked(){this._remuxer.insertDiscontinuity()}_onIOComplete(E){let N=E+1;N<this._mediaDataSource.segments.length?(this._internalAbort(),this._remuxer.flushStashedSamples(),this._loadSegment(N)):(this._remuxer.flushStashedSamples(),this._emitter.emit(_t.LOADING_COMPLETE),this._disableStatisticsReporter())}_onIORedirect(E){let B=this._ioctl.extraData;this._mediaDataSource.segments[B].redirectedURL=E}_onIORecoveredEarlyEof(){this._emitter.emit(_t.RECOVERED_EARLY_EOF)}_onIOException(E,B){P.e(this.TAG,`IOException: type = ${E}, code = ${B.code}, msg = ${B.msg}`),this._emitter.emit(_t.IO_ERROR,E,B),this._disableStatisticsReporter()}_onDemuxException(E,B){P.e(this.TAG,`DemuxException: type = ${E}, info = ${B}`),this._emitter.emit(_t.DEMUX_ERROR,E,B)}_onRemuxerInitSegmentArrival(E,B){this._emitter.emit(_t.INIT_SEGMENT,E,B)}_onRemuxerMediaSegmentArrival(E,B){if(this._pendingSeekTime==null&&(this._emitter.emit(_t.MEDIA_SEGMENT,E,B),this._pendingResolveSeekPoint!=null&&E==="video")){let N=B.info.syncPoints,V=this._pendingResolveSeekPoint;this._pendingResolveSeekPoint=null,S.safari&&N.length>0&&N[0].originalDts===V&&(V=N[0].pts),this._emitter.emit(_t.RECOMMEND_SEEKPOINT,V)}}_enableStatisticsReporter(){this._statisticsReporter==null&&(this._statisticsReporter=self.setInterval(this._reportStatisticsInfo.bind(this),this._config.statisticsInfoReportInterval))}_disableStatisticsReporter(){this._statisticsReporter&&(self.clearInterval(this._statisticsReporter),this._statisticsReporter=null)}_reportSegmentMediaInfo(E){let B=this._mediaInfo.segments[E],N=Object.assign({},B);N.duration=this._mediaInfo.duration,N.segmentCount=this._mediaInfo.segmentCount,delete N.segments,delete N.keyframesIndex,this._emitter.emit(_t.MEDIA_INFO,N)}_reportStatisticsInfo(){let E={};E.url=this._ioctl.currentURL,E.hasRedirect=this._ioctl.hasRedirect,E.hasRedirect&&(E.redirectedURL=this._ioctl.currentRedirectedURL),E.speed=this._ioctl.currentSpeed,E.loaderType=this._ioctl.loaderType,E.currentSegmentIndex=this._currentSegmentIndex,E.totalSegmentCount=this._mediaDataSource.segments.length,this._emitter.emit(_t.STATISTICS_INFO,E)}}var Wt=Ot,zt=function(Ee){let E="TransmuxingWorker",B=null,N=st.bind(this);J.install(),Ee.addEventListener("message",function(Je){switch(Je.data.cmd){case"init":B=new Wt(Je.data.param[0],Je.data.param[1]),B.on(_t.IO_ERROR,it.bind(this)),B.on(_t.DEMUX_ERROR,at.bind(this)),B.on(_t.INIT_SEGMENT,V.bind(this)),B.on(_t.MEDIA_SEGMENT,q.bind(this)),B.on(_t.LOADING_COMPLETE,ue.bind(this)),B.on(_t.RECOVERED_EARLY_EOF,ce.bind(this)),B.on(_t.MEDIA_INFO,Oe.bind(this)),B.on(_t.METADATA_ARRIVED,Se.bind(this)),B.on(_t.SCRIPTDATA_ARRIVED,Ue.bind(this)),B.on(_t.STATISTICS_INFO,je.bind(this)),B.on(_t.RECOMMEND_SEEKPOINT,et.bind(this));break;case"destroy":B&&(B.destroy(),B=null),Ee.postMessage({msg:"destroyed"});break;case"start":B.start();break;case"stop":B.stop();break;case"seek":B.seek(Je.data.param);break;case"pause":B.pause();break;case"resume":B.resume();break;case"logging_config":{let ke=Je.data.param;xe.applyConfig(ke),ke.enableCallback===!0?xe.addLogListener(N):xe.removeLogListener(N);break}}});function V(Je,ke){let ft={msg:_t.INIT_SEGMENT,data:{type:Je,data:ke}};Ee.postMessage(ft,[ke.data])}function q(Je,ke){let ft={msg:_t.MEDIA_SEGMENT,data:{type:Je,data:ke}};Ee.postMessage(ft,[ke.data])}function ue(){let Je={msg:_t.LOADING_COMPLETE};Ee.postMessage(Je)}function ce(){let Je={msg:_t.RECOVERED_EARLY_EOF};Ee.postMessage(Je)}function Oe(Je){let ke={msg:_t.MEDIA_INFO,data:Je};Ee.postMessage(ke)}function Se(Je){let ke={msg:_t.METADATA_ARRIVED,data:Je};Ee.postMessage(ke)}function Ue(Je){let ke={msg:_t.SCRIPTDATA_ARRIVED,data:Je};Ee.postMessage(ke)}function je(Je){let ke={msg:_t.STATISTICS_INFO,data:Je};Ee.postMessage(ke)}function it(Je,ke){Ee.postMessage({msg:_t.IO_ERROR,data:{type:Je,info:ke}})}function at(Je,ke){Ee.postMessage({msg:_t.DEMUX_ERROR,data:{type:Je,info:ke}})}function et(Je){Ee.postMessage({msg:_t.RECOMMEND_SEEKPOINT,data:Je})}function st(Je,ke){Ee.postMessage({msg:"logcat_callback",data:{type:Je,logcat:ke}})}};class en{constructor(E,B){if(this.TAG="Transmuxer",this._emitter=new(b()),B.enableWorker&&typeof Worker!="undefined")try{let N=Z(82059);this._worker=N(zt),this._workerDestroying=!1,this._worker.addEventListener("message",this._onWorkerMessage.bind(this)),this._worker.postMessage({cmd:"init",param:[E,B]}),this.e={onLoggingConfigChanged:this._onLoggingConfigChanged.bind(this)},xe.registerListener(this.e.onLoggingConfigChanged),this._worker.postMessage({cmd:"logging_config",param:xe.getConfig()})}catch(N){P.e(this.TAG,"Error while initialize transmuxing worker, fallback to inline transmuxing"),this._worker=null,this._controller=new Wt(E,B)}else this._controller=new Wt(E,B);if(this._controller){let N=this._controller;N.on(_t.IO_ERROR,this._onIOError.bind(this)),N.on(_t.DEMUX_ERROR,this._onDemuxError.bind(this)),N.on(_t.INIT_SEGMENT,this._onInitSegment.bind(this)),N.on(_t.MEDIA_SEGMENT,this._onMediaSegment.bind(this)),N.on(_t.LOADING_COMPLETE,this._onLoadingComplete.bind(this)),N.on(_t.RECOVERED_EARLY_EOF,this._onRecoveredEarlyEof.bind(this)),N.on(_t.MEDIA_INFO,this._onMediaInfo.bind(this)),N.on(_t.METADATA_ARRIVED,this._onMetaDataArrived.bind(this)),N.on(_t.SCRIPTDATA_ARRIVED,this._onScriptDataArrived.bind(this)),N.on(_t.STATISTICS_INFO,this._onStatisticsInfo.bind(this)),N.on(_t.RECOMMEND_SEEKPOINT,this._onRecommendSeekpoint.bind(this))}}destroy(){this._worker?this._workerDestroying||(this._workerDestroying=!0,this._worker.postMessage({cmd:"destroy"}),xe.removeListener(this.e.onLoggingConfigChanged),this.e=null):(this._controller.destroy(),this._controller=null),this._emitter.removeAllListeners(),this._emitter=null}on(E,B){this._emitter.addListener(E,B)}off(E,B){this._emitter.removeListener(E,B)}hasWorker(){return this._worker!=null}open(){this._worker?this._worker.postMessage({cmd:"start"}):this._controller.start()}close(){this._worker?this._worker.postMessage({cmd:"stop"}):this._controller.stop()}seek(E){this._worker?this._worker.postMessage({cmd:"seek",param:E}):this._controller.seek(E)}pause(){this._worker?this._worker.postMessage({cmd:"pause"}):this._controller.pause()}resume(){this._worker?this._worker.postMessage({cmd:"resume"}):this._controller.resume()}_onInitSegment(E,B){Promise.resolve().then(()=>{this._emitter.emit(_t.INIT_SEGMENT,E,B)})}_onMediaSegment(E,B){Promise.resolve().then(()=>{this._emitter.emit(_t.MEDIA_SEGMENT,E,B)})}_onLoadingComplete(){Promise.resolve().then(()=>{this._emitter.emit(_t.LOADING_COMPLETE)})}_onRecoveredEarlyEof(){Promise.resolve().then(()=>{this._emitter.emit(_t.RECOVERED_EARLY_EOF)})}_onMediaInfo(E){Promise.resolve().then(()=>{this._emitter.emit(_t.MEDIA_INFO,E)})}_onMetaDataArrived(E){Promise.resolve().then(()=>{this._emitter.emit(_t.METADATA_ARRIVED,E)})}_onScriptDataArrived(E){Promise.resolve().then(()=>{this._emitter.emit(_t.SCRIPTDATA_ARRIVED,E)})}_onStatisticsInfo(E){Promise.resolve().then(()=>{this._emitter.emit(_t.STATISTICS_INFO,E)})}_onIOError(E,B){Promise.resolve().then(()=>{this._emitter.emit(_t.IO_ERROR,E,B)})}_onDemuxError(E,B){Promise.resolve().then(()=>{this._emitter.emit(_t.DEMUX_ERROR,E,B)})}_onRecommendSeekpoint(E){Promise.resolve().then(()=>{this._emitter.emit(_t.RECOMMEND_SEEKPOINT,E)})}_onLoggingConfigChanged(E){this._worker&&this._worker.postMessage({cmd:"logging_config",param:E})}_onWorkerMessage(E){let B=E.data,N=B.data;if(B.msg==="destroyed"||this._workerDestroying){this._workerDestroying=!1,this._worker.terminate(),this._worker=null;return}switch(B.msg){case _t.INIT_SEGMENT:case _t.MEDIA_SEGMENT:this._emitter.emit(B.msg,N.type,N.data);break;case _t.LOADING_COMPLETE:case _t.RECOVERED_EARLY_EOF:this._emitter.emit(B.msg);break;case _t.MEDIA_INFO:Object.setPrototypeOf(N,Ne.prototype),this._emitter.emit(B.msg,N);break;case _t.METADATA_ARRIVED:case _t.SCRIPTDATA_ARRIVED:case _t.STATISTICS_INFO:this._emitter.emit(B.msg,N);break;case _t.IO_ERROR:case _t.DEMUX_ERROR:this._emitter.emit(B.msg,N.type,N.info);break;case _t.RECOMMEND_SEEKPOINT:this._emitter.emit(B.msg,N);break;case"logcat_callback":P.emitter.emit("log",N.type,N.logcat);break;default:break}}}var vn=en,cn={ERROR:"error",SOURCE_OPEN:"source_open",UPDATE_END:"update_end",BUFFER_FULL:"buffer_full"};class On{constructor(E){this.TAG="MSEController",this._config=E,this._emitter=new(b()),this._config.isLive&&this._config.autoCleanupSourceBuffer==null&&(this._config.autoCleanupSourceBuffer=!0),this.e={onSourceOpen:this._onSourceOpen.bind(this),onSourceEnded:this._onSourceEnded.bind(this),onSourceClose:this._onSourceClose.bind(this),onSourceBufferError:this._onSourceBufferError.bind(this),onSourceBufferUpdateEnd:this._onSourceBufferUpdateEnd.bind(this)},this._mediaSource=null,this._mediaSourceObjectURL=null,this._mediaElement=null,this._isBufferFull=!1,this._hasPendingEos=!1,this._requireSetMediaDuration=!1,this._pendingMediaDuration=0,this._pendingSourceBufferInit=[],this._mimeTypes={video:null,audio:null},this._sourceBuffers={video:null,audio:null},this._lastInitSegments={video:null,audio:null},this._pendingSegments={video:[],audio:[]},this._pendingRemoveRanges={video:[],audio:[]},this._idrList=new Tt}destroy(){(this._mediaElement||this._mediaSource)&&this.detachMediaElement(),this.e=null,this._emitter.removeAllListeners(),this._emitter=null}on(E,B){this._emitter.addListener(E,B)}off(E,B){this._emitter.removeListener(E,B)}attachMediaElement(E){if(this._mediaSource)throw new _("MediaSource has been attached to an HTMLMediaElement!");let B=this._mediaSource=new window.MediaSource;B.addEventListener("sourceopen",this.e.onSourceOpen),B.addEventListener("sourceended",this.e.onSourceEnded),B.addEventListener("sourceclose",this.e.onSourceClose),this._mediaElement=E,this._mediaSourceObjectURL=window.URL.createObjectURL(this._mediaSource),E.src=this._mediaSourceObjectURL}detachMediaElement(){if(this._mediaSource){let E=this._mediaSource;for(let B in this._sourceBuffers){let N=this._pendingSegments[B];N.splice(0,N.length),this._pendingSegments[B]=null,this._pendingRemoveRanges[B]=null,this._lastInitSegments[B]=null;let V=this._sourceBuffers[B];if(V){if(E.readyState!=="closed"){try{E.removeSourceBuffer(V)}catch(q){P.e(this.TAG,q.message)}V.removeEventListener("error",this.e.onSourceBufferError),V.removeEventListener("updateend",this.e.onSourceBufferUpdateEnd)}this._mimeTypes[B]=null,this._sourceBuffers[B]=null}}if(E.readyState==="open")try{E.endOfStream()}catch(B){P.e(this.TAG,B.message)}E.removeEventListener("sourceopen",this.e.onSourceOpen),E.removeEventListener("sourceended",this.e.onSourceEnded),E.removeEventListener("sourceclose",this.e.onSourceClose),this._pendingSourceBufferInit=[],this._isBufferFull=!1,this._idrList.clear(),this._mediaSource=null}this._mediaElement&&(this._mediaElement.src="",this._mediaElement.removeAttribute("src"),this._mediaElement=null),this._mediaSourceObjectURL&&(window.URL.revokeObjectURL(this._mediaSourceObjectURL),this._mediaSourceObjectURL=null)}appendInitSegment(E,B){if(!this._mediaSource||this._mediaSource.readyState!=="open"){this._pendingSourceBufferInit.push(E),this._pendingSegments[E.type].push(E);return}let N=E,V=`${N.container}`;N.codec&&N.codec.length>0&&(V+=`;codecs=${N.codec}`);let q=!1;if(P.v(this.TAG,"Received Initialization Segment, mimeType: "+V),this._lastInitSegments[N.type]=N,V!==this._mimeTypes[N.type]){if(this._mimeTypes[N.type])P.v(this.TAG,`Notice: ${N.type} mimeType changed, origin: ${this._mimeTypes[N.type]}, target: ${V}`);else{q=!0;try{let ue=this._sourceBuffers[N.type]=this._mediaSource.addSourceBuffer(V);ue.addEventListener("error",this.e.onSourceBufferError),ue.addEventListener("updateend",this.e.onSourceBufferUpdateEnd)}catch(ue){P.e(this.TAG,ue.message),this._emitter.emit(cn.ERROR,{code:ue.code,msg:ue.message});return}}this._mimeTypes[N.type]=V}B||this._pendingSegments[N.type].push(N),q||this._sourceBuffers[N.type]&&!this._sourceBuffers[N.type].updating&&this._doAppendSegments(),S.safari&&N.container==="audio/mpeg"&&N.mediaDuration>0&&(this._requireSetMediaDuration=!0,this._pendingMediaDuration=N.mediaDuration/1e3,this._updateMediaSourceDuration())}appendMediaSegment(E){let B=E;this._pendingSegments[B.type].push(B),this._config.autoCleanupSourceBuffer&&this._needCleanupSourceBuffer()&&this._doCleanupSourceBuffer();let N=this._sourceBuffers[B.type];N&&!N.updating&&!this._hasPendingRemoveRanges()&&this._doAppendSegments()}seek(E){for(let B in this._sourceBuffers){if(!this._sourceBuffers[B])continue;let N=this._sourceBuffers[B];if(this._mediaSource.readyState==="open")try{N.abort()}catch(q){P.e(this.TAG,q.message)}this._idrList.clear();let V=this._pendingSegments[B];if(V.splice(0,V.length),this._mediaSource.readyState!=="closed"){for(let q=0;q<N.buffered.length;q++){let ue=N.buffered.start(q),ce=N.buffered.end(q);this._pendingRemoveRanges[B].push({start:ue,end:ce})}if(N.updating||this._doRemoveRanges(),S.safari){let q=this._lastInitSegments[B];q&&(this._pendingSegments[B].push(q),N.updating||this._doAppendSegments())}}}}endOfStream(){let E=this._mediaSource,B=this._sourceBuffers;if(!E||E.readyState!=="open"){E&&E.readyState==="closed"&&this._hasPendingSegments()&&(this._hasPendingEos=!0);return}B.video&&B.video.updating||B.audio&&B.audio.updating?this._hasPendingEos=!0:(this._hasPendingEos=!1,E.endOfStream())}getNearestKeyframe(E){return this._idrList.getLastSyncPointBeforeDts(E)}_needCleanupSourceBuffer(){if(!this._config.autoCleanupSourceBuffer)return!1;let E=this._mediaElement.currentTime;for(let B in this._sourceBuffers){let N=this._sourceBuffers[B];if(N){let V=N.buffered;if(V.length>=1&&E-V.start(0)>=this._config.autoCleanupMaxBackwardDuration)return!0}}return!1}_doCleanupSourceBuffer(){let E=this._mediaElement.currentTime;for(let B in this._sourceBuffers){let N=this._sourceBuffers[B];if(N){let V=N.buffered,q=!1;for(let ue=0;ue<V.length;ue++){let ce=V.start(ue),Oe=V.end(ue);if(ce<=E&&E<Oe+3){if(E-ce>=this._config.autoCleanupMaxBackwardDuration){q=!0;let Se=E-this._config.autoCleanupMinBackwardDuration;this._pendingRemoveRanges[B].push({start:ce,end:Se})}}else Oe<E&&(q=!0,this._pendingRemoveRanges[B].push({start:ce,end:Oe}))}q&&!N.updating&&this._doRemoveRanges()}}}_updateMediaSourceDuration(){let E=this._sourceBuffers;if(this._mediaElement.readyState===0||this._mediaSource.readyState!=="open"||E.video&&E.video.updating||E.audio&&E.audio.updating)return;let B=this._mediaSource.duration,N=this._pendingMediaDuration;N>0&&(isNaN(B)||N>B)&&(P.v(this.TAG,`Update MediaSource duration from ${B} to ${N}`),this._mediaSource.duration=N),this._requireSetMediaDuration=!1,this._pendingMediaDuration=0}_doRemoveRanges(){for(let E in this._pendingRemoveRanges){if(!this._sourceBuffers[E]||this._sourceBuffers[E].updating)continue;let B=this._sourceBuffers[E],N=this._pendingRemoveRanges[E];for(;N.length&&!B.updating;){let V=N.shift();B.remove(V.start,V.end)}}}_doAppendSegments(){let E=this._pendingSegments;for(let B in E)if(!(!this._sourceBuffers[B]||this._sourceBuffers[B].updating)&&E[B].length>0){let N=E[B].shift();if(N.timestampOffset){let V=this._sourceBuffers[B].timestampOffset,q=N.timestampOffset/1e3;Math.abs(V-q)>.1&&(P.v(this.TAG,`Update MPEG audio timestampOffset from ${V} to ${q}`),this._sourceBuffers[B].timestampOffset=q),delete N.timestampOffset}if(!N.data||N.data.byteLength===0)continue;try{this._sourceBuffers[B].appendBuffer(N.data),this._isBufferFull=!1,B==="video"&&N.hasOwnProperty("info")&&this._idrList.appendArray(N.info.syncPoints)}catch(V){this._pendingSegments[B].unshift(N),V.code===22?(this._isBufferFull||this._emitter.emit(cn.BUFFER_FULL),this._isBufferFull=!0):(P.e(this.TAG,V.message),this._emitter.emit(cn.ERROR,{code:V.code,msg:V.message}))}}}_onSourceOpen(){if(P.v(this.TAG,"MediaSource onSourceOpen"),this._mediaSource.removeEventListener("sourceopen",this.e.onSourceOpen),this._pendingSourceBufferInit.length>0){let E=this._pendingSourceBufferInit;for(;E.length;){let B=E.shift();this.appendInitSegment(B,!0)}}this._hasPendingSegments()&&this._doAppendSegments(),this._emitter.emit(cn.SOURCE_OPEN)}_onSourceEnded(){P.v(this.TAG,"MediaSource onSourceEnded")}_onSourceClose(){P.v(this.TAG,"MediaSource onSourceClose"),this._mediaSource&&this.e!=null&&(this._mediaSource.removeEventListener("sourceopen",this.e.onSourceOpen),this._mediaSource.removeEventListener("sourceended",this.e.onSourceEnded),this._mediaSource.removeEventListener("sourceclose",this.e.onSourceClose))}_hasPendingSegments(){let E=this._pendingSegments;return E.video.length>0||E.audio.length>0}_hasPendingRemoveRanges(){let E=this._pendingRemoveRanges;return E.video.length>0||E.audio.length>0}_onSourceBufferUpdateEnd(){this._requireSetMediaDuration?this._updateMediaSourceDuration():this._hasPendingRemoveRanges()?this._doRemoveRanges():this._hasPendingSegments()?this._doAppendSegments():this._hasPendingEos&&this.endOfStream(),this._emitter.emit(cn.UPDATE_END)}_onSourceBufferError(E){P.e(this.TAG,`SourceBuffer Error: ${E}`)}}var Mn=On;const Yt={NETWORK_ERROR:"NetworkError",MEDIA_ERROR:"MediaError",OTHER_ERROR:"OtherError"},Jt={NETWORK_EXCEPTION:d.EXCEPTION,NETWORK_STATUS_CODE_INVALID:d.HTTP_STATUS_CODE_INVALID,NETWORK_TIMEOUT:d.CONNECTING_TIMEOUT,NETWORK_UNRECOVERABLE_EARLY_EOF:d.UNRECOVERABLE_EARLY_EOF,MEDIA_MSE_ERROR:"MediaMSEError",MEDIA_FORMAT_ERROR:He.FORMAT_ERROR,MEDIA_FORMAT_UNSUPPORTED:He.FORMAT_UNSUPPORTED,MEDIA_CODEC_UNSUPPORTED:He.CODEC_UNSUPPORTED};class Ht{constructor(E,B){if(this.TAG="FlvPlayer",this._type="FlvPlayer",this._emitter=new(b()),this._config=ae(),typeof B=="object"&&Object.assign(this._config,B),E.type.toLowerCase()!=="flv")throw new g("FlvPlayer requires an flv MediaDataSource input!");E.isLive===!0&&(this._config.isLive=!0),this.e={onvLoadedMetadata:this._onvLoadedMetadata.bind(this),onvSeeking:this._onvSeeking.bind(this),onvCanPlay:this._onvCanPlay.bind(this),onvStalled:this._onvStalled.bind(this),onvProgress:this._onvProgress.bind(this)},self.performance&&self.performance.now?this._now=self.performance.now.bind(self.performance):this._now=Date.now,this._pendingSeekTime=null,this._requestSetTime=!1,this._seekpointRecord=null,this._progressChecker=null,this._mediaDataSource=E,this._mediaElement=null,this._msectl=null,this._transmuxer=null,this._mseSourceOpened=!1,this._hasPendingLoad=!1,this._receivedCanPlay=!1,this._mediaInfo=null,this._statisticsInfo=null;let N=S.chrome&&(S.version.major<50||S.version.major===50&&S.version.build<2661);this._alwaysSeekKeyframe=!!(N||S.msedge||S.msie),this._alwaysSeekKeyframe&&(this._config.accurateSeek=!1)}destroy(){this._progressChecker!=null&&(window.clearInterval(this._progressChecker),this._progressChecker=null),this._transmuxer&&this.unload(),this._mediaElement&&this.detachMediaElement(),this.e=null,this._mediaDataSource=null,this._emitter.removeAllListeners(),this._emitter=null}on(E,B){E===me.MEDIA_INFO?this._mediaInfo!=null&&Promise.resolve().then(()=>{this._emitter.emit(me.MEDIA_INFO,this.mediaInfo)}):E===me.STATISTICS_INFO&&this._statisticsInfo!=null&&Promise.resolve().then(()=>{this._emitter.emit(me.STATISTICS_INFO,this.statisticsInfo)}),this._emitter.addListener(E,B)}off(E,B){this._emitter.removeListener(E,B)}attachMediaElement(E){if(this._mediaElement=E,E.addEventListener("loadedmetadata",this.e.onvLoadedMetadata),E.addEventListener("seeking",this.e.onvSeeking),E.addEventListener("canplay",this.e.onvCanPlay),E.addEventListener("stalled",this.e.onvStalled),E.addEventListener("progress",this.e.onvProgress),this._msectl=new Mn(this._config),this._msectl.on(cn.UPDATE_END,this._onmseUpdateEnd.bind(this)),this._msectl.on(cn.BUFFER_FULL,this._onmseBufferFull.bind(this)),this._msectl.on(cn.SOURCE_OPEN,()=>{this._mseSourceOpened=!0,this._hasPendingLoad&&(this._hasPendingLoad=!1,this.load())}),this._msectl.on(cn.ERROR,B=>{this._emitter.emit(me.ERROR,Yt.MEDIA_ERROR,Jt.MEDIA_MSE_ERROR,B)}),this._msectl.attachMediaElement(E),this._pendingSeekTime!=null)try{E.currentTime=this._pendingSeekTime,this._pendingSeekTime=null}catch(B){}}detachMediaElement(){this._mediaElement&&(this._msectl.detachMediaElement(),this._mediaElement.removeEventListener("loadedmetadata",this.e.onvLoadedMetadata),this._mediaElement.removeEventListener("seeking",this.e.onvSeeking),this._mediaElement.removeEventListener("canplay",this.e.onvCanPlay),this._mediaElement.removeEventListener("stalled",this.e.onvStalled),this._mediaElement.removeEventListener("progress",this.e.onvProgress),this._mediaElement=null),this._msectl&&(this._msectl.destroy(),this._msectl=null)}load(){if(!this._mediaElement)throw new _("HTMLMediaElement must be attached before load()!");if(this._transmuxer)throw new _("FlvPlayer.load() has been called, please call unload() first!");if(!this._hasPendingLoad){if(this._config.deferLoadAfterSourceOpen&&this._mseSourceOpened===!1){this._hasPendingLoad=!0;return}this._mediaElement.readyState>0&&(this._requestSetTime=!0,this._mediaElement.currentTime=0),this._transmuxer=new vn(this._mediaDataSource,this._config),this._transmuxer.on(_t.INIT_SEGMENT,(E,B)=>{this._msectl.appendInitSegment(B)}),this._transmuxer.on(_t.MEDIA_SEGMENT,(E,B)=>{if(this._msectl.appendMediaSegment(B),this._config.lazyLoad&&!this._config.isLive){let N=this._mediaElement.currentTime;B.info.endDts>=(N+this._config.lazyLoadMaxDuration)*1e3&&this._progressChecker==null&&(P.v(this.TAG,"Maximum buffering duration exceeded, suspend transmuxing task"),this._suspendTransmuxer())}}),this._transmuxer.on(_t.LOADING_COMPLETE,()=>{this._msectl.endOfStream(),this._emitter.emit(me.LOADING_COMPLETE)}),this._transmuxer.on(_t.RECOVERED_EARLY_EOF,()=>{this._emitter.emit(me.RECOVERED_EARLY_EOF)}),this._transmuxer.on(_t.IO_ERROR,(E,B)=>{this._emitter.emit(me.ERROR,Yt.NETWORK_ERROR,E,B)}),this._transmuxer.on(_t.DEMUX_ERROR,(E,B)=>{this._emitter.emit(me.ERROR,Yt.MEDIA_ERROR,E,{code:-1,msg:B})}),this._transmuxer.on(_t.MEDIA_INFO,E=>{this._mediaInfo=E,this._emitter.emit(me.MEDIA_INFO,Object.assign({},E))}),this._transmuxer.on(_t.METADATA_ARRIVED,E=>{this._emitter.emit(me.METADATA_ARRIVED,E)}),this._transmuxer.on(_t.SCRIPTDATA_ARRIVED,E=>{this._emitter.emit(me.SCRIPTDATA_ARRIVED,E)}),this._transmuxer.on(_t.STATISTICS_INFO,E=>{this._statisticsInfo=this._fillStatisticsInfo(E),this._emitter.emit(me.STATISTICS_INFO,Object.assign({},this._statisticsInfo))}),this._transmuxer.on(_t.RECOMMEND_SEEKPOINT,E=>{this._mediaElement&&!this._config.accurateSeek&&(this._requestSetTime=!0,this._mediaElement.currentTime=E/1e3)}),this._transmuxer.open()}}unload(){this._mediaElement&&this._mediaElement.pause(),this._msectl&&this._msectl.seek(0),this._transmuxer&&(this._transmuxer.close(),this._transmuxer.destroy(),this._transmuxer=null)}play(){return this._mediaElement.play()}pause(){this._mediaElement.pause()}get type(){return this._type}get buffered(){return this._mediaElement.buffered}get duration(){return this._mediaElement.duration}get volume(){return this._mediaElement.volume}set volume(E){this._mediaElement.volume=E}get muted(){return this._mediaElement.muted}set muted(E){this._mediaElement.muted=E}get currentTime(){return this._mediaElement?this._mediaElement.currentTime:0}set currentTime(E){this._mediaElement?this._internalSeek(E):this._pendingSeekTime=E}get mediaInfo(){return Object.assign({},this._mediaInfo)}get statisticsInfo(){return this._statisticsInfo==null&&(this._statisticsInfo={}),this._statisticsInfo=this._fillStatisticsInfo(this._statisticsInfo),Object.assign({},this._statisticsInfo)}_fillStatisticsInfo(E){if(E.playerType=this._type,!(this._mediaElement instanceof HTMLVideoElement))return E;let B=!0,N=0,V=0;if(this._mediaElement.getVideoPlaybackQuality){let q=this._mediaElement.getVideoPlaybackQuality();N=q.totalVideoFrames,V=q.droppedVideoFrames}else this._mediaElement.webkitDecodedFrameCount!=null?(N=this._mediaElement.webkitDecodedFrameCount,V=this._mediaElement.webkitDroppedFrameCount):B=!1;return B&&(E.decodedFrames=N,E.droppedFrames=V),E}_onmseUpdateEnd(){if(!this._config.lazyLoad||this._config.isLive)return;let E=this._mediaElement.buffered,B=this._mediaElement.currentTime,N=0,V=0;for(let q=0;q<E.length;q++){let ue=E.start(q),ce=E.end(q);if(ue<=B&&B<ce){N=ue,V=ce;break}}V>=B+this._config.lazyLoadMaxDuration&&this._progressChecker==null&&(P.v(this.TAG,"Maximum buffering duration exceeded, suspend transmuxing task"),this._suspendTransmuxer())}_onmseBufferFull(){P.v(this.TAG,"MSE SourceBuffer is full, suspend transmuxing task"),this._progressChecker==null&&this._suspendTransmuxer()}_suspendTransmuxer(){this._transmuxer&&(this._transmuxer.pause(),this._progressChecker==null&&(this._progressChecker=window.setInterval(this._checkProgressAndResume.bind(this),1e3)))}_checkProgressAndResume(){let E=this._mediaElement.currentTime,B=this._mediaElement.buffered,N=!1;for(let V=0;V<B.length;V++){let q=B.start(V),ue=B.end(V);if(E>=q&&E<ue){E>=ue-this._config.lazyLoadRecoverDuration&&(N=!0);break}}N&&(window.clearInterval(this._progressChecker),this._progressChecker=null,N&&(P.v(this.TAG,"Continue loading from paused position"),this._transmuxer.resume()))}_isTimepointBuffered(E){let B=this._mediaElement.buffered;for(let N=0;N<B.length;N++){let V=B.start(N),q=B.end(N);if(E>=V&&E<q)return!0}return!1}_internalSeek(E){let B=this._isTimepointBuffered(E),N=!1,V=0;if(E<1&&this._mediaElement.buffered.length>0){let q=this._mediaElement.buffered.start(0);(q<1&&E<q||S.safari)&&(N=!0,V=S.safari?.1:q)}if(N)this._requestSetTime=!0,this._mediaElement.currentTime=V;else if(B){if(!this._alwaysSeekKeyframe)this._requestSetTime=!0,this._mediaElement.currentTime=E;else{let q=this._msectl.getNearestKeyframe(Math.floor(E*1e3));this._requestSetTime=!0,q!=null?this._mediaElement.currentTime=q.dts/1e3:this._mediaElement.currentTime=E}this._progressChecker!=null&&this._checkProgressAndResume()}else this._progressChecker!=null&&(window.clearInterval(this._progressChecker),this._progressChecker=null),this._msectl.seek(E),this._transmuxer.seek(Math.floor(E*1e3)),this._config.accurateSeek&&(this._requestSetTime=!0,this._mediaElement.currentTime=E)}_checkAndApplyUnbufferedSeekpoint(){if(this._seekpointRecord)if(this._seekpointRecord.recordTime<=this._now()-100){let E=this._mediaElement.currentTime;this._seekpointRecord=null,this._isTimepointBuffered(E)||(this._progressChecker!=null&&(window.clearTimeout(this._progressChecker),this._progressChecker=null),this._msectl.seek(E),this._transmuxer.seek(Math.floor(E*1e3)),this._config.accurateSeek&&(this._requestSetTime=!0,this._mediaElement.currentTime=E))}else window.setTimeout(this._checkAndApplyUnbufferedSeekpoint.bind(this),50)}_checkAndResumeStuckPlayback(E){let B=this._mediaElement;if(E||!this._receivedCanPlay||B.readyState<2){let N=B.buffered;N.length>0&&B.currentTime<N.start(0)&&(P.w(this.TAG,`Playback seems stuck at ${B.currentTime}, seek to ${N.start(0)}`),this._requestSetTime=!0,this._mediaElement.currentTime=N.start(0),this._mediaElement.removeEventListener("progress",this.e.onvProgress))}else this._mediaElement.removeEventListener("progress",this.e.onvProgress)}_onvLoadedMetadata(E){this._pendingSeekTime!=null&&(this._mediaElement.currentTime=this._pendingSeekTime,this._pendingSeekTime=null)}_onvSeeking(E){let B=this._mediaElement.currentTime,N=this._mediaElement.buffered;if(this._requestSetTime){this._requestSetTime=!1;return}if(B<1&&N.length>0){let V=N.start(0);if(V<1&&B<V||S.safari){this._requestSetTime=!0,this._mediaElement.currentTime=S.safari?.1:V;return}}if(this._isTimepointBuffered(B)){if(this._alwaysSeekKeyframe){let V=this._msectl.getNearestKeyframe(Math.floor(B*1e3));V!=null&&(this._requestSetTime=!0,this._mediaElement.currentTime=V.dts/1e3)}this._progressChecker!=null&&this._checkProgressAndResume();return}this._seekpointRecord={seekPoint:B,recordTime:this._now()},window.setTimeout(this._checkAndApplyUnbufferedSeekpoint.bind(this),50)}_onvCanPlay(E){this._receivedCanPlay=!0,this._mediaElement.removeEventListener("canplay",this.e.onvCanPlay)}_onvStalled(E){this._checkAndResumeStuckPlayback(!0)}_onvProgress(E){this._checkAndResumeStuckPlayback()}}var bn=Ht;class Sn{constructor(E,B){if(this.TAG="NativePlayer",this._type="NativePlayer",this._emitter=new(b()),this._config=ae(),typeof B=="object"&&Object.assign(this._config,B),E.type.toLowerCase()==="flv")throw new g("NativePlayer does't support flv MediaDataSource input!");if(E.hasOwnProperty("segments"))throw new g(`NativePlayer(${E.type}) doesn't support multipart playback!`);this.e={onvLoadedMetadata:this._onvLoadedMetadata.bind(this)},this._pendingSeekTime=null,this._statisticsReporter=null,this._mediaDataSource=E,this._mediaElement=null}destroy(){this._mediaElement&&(this.unload(),this.detachMediaElement()),this.e=null,this._mediaDataSource=null,this._emitter.removeAllListeners(),this._emitter=null}on(E,B){E===me.MEDIA_INFO?this._mediaElement!=null&&this._mediaElement.readyState!==0&&Promise.resolve().then(()=>{this._emitter.emit(me.MEDIA_INFO,this.mediaInfo)}):E===me.STATISTICS_INFO&&this._mediaElement!=null&&this._mediaElement.readyState!==0&&Promise.resolve().then(()=>{this._emitter.emit(me.STATISTICS_INFO,this.statisticsInfo)}),this._emitter.addListener(E,B)}off(E,B){this._emitter.removeListener(E,B)}attachMediaElement(E){if(this._mediaElement=E,E.addEventListener("loadedmetadata",this.e.onvLoadedMetadata),this._pendingSeekTime!=null)try{E.currentTime=this._pendingSeekTime,this._pendingSeekTime=null}catch(B){}}detachMediaElement(){this._mediaElement&&(this._mediaElement.src="",this._mediaElement.removeAttribute("src"),this._mediaElement.removeEventListener("loadedmetadata",this.e.onvLoadedMetadata),this._mediaElement=null),this._statisticsReporter!=null&&(window.clearInterval(this._statisticsReporter),this._statisticsReporter=null)}load(){if(!this._mediaElement)throw new _("HTMLMediaElement must be attached before load()!");this._mediaElement.src=this._mediaDataSource.url,this._mediaElement.readyState>0&&(this._mediaElement.currentTime=0),this._mediaElement.preload="auto",this._mediaElement.load(),this._statisticsReporter=window.setInterval(this._reportStatisticsInfo.bind(this),this._config.statisticsInfoReportInterval)}unload(){this._mediaElement&&(this._mediaElement.src="",this._mediaElement.removeAttribute("src")),this._statisticsReporter!=null&&(window.clearInterval(this._statisticsReporter),this._statisticsReporter=null)}play(){return this._mediaElement.play()}pause(){this._mediaElement.pause()}get type(){return this._type}get buffered(){return this._mediaElement.buffered}get duration(){return this._mediaElement.duration}get volume(){return this._mediaElement.volume}set volume(E){this._mediaElement.volume=E}get muted(){return this._mediaElement.muted}set muted(E){this._mediaElement.muted=E}get currentTime(){return this._mediaElement?this._mediaElement.currentTime:0}set currentTime(E){this._mediaElement?this._mediaElement.currentTime=E:this._pendingSeekTime=E}get mediaInfo(){let B={mimeType:(this._mediaElement instanceof HTMLAudioElement?"audio/":"video/")+this._mediaDataSource.type};return this._mediaElement&&(B.duration=Math.floor(this._mediaElement.duration*1e3),this._mediaElement instanceof HTMLVideoElement&&(B.width=this._mediaElement.videoWidth,B.height=this._mediaElement.videoHeight)),B}get statisticsInfo(){let E={playerType:this._type,url:this._mediaDataSource.url};if(!(this._mediaElement instanceof HTMLVideoElement))return E;let B=!0,N=0,V=0;if(this._mediaElement.getVideoPlaybackQuality){let q=this._mediaElement.getVideoPlaybackQuality();N=q.totalVideoFrames,V=q.droppedVideoFrames}else this._mediaElement.webkitDecodedFrameCount!=null?(N=this._mediaElement.webkitDecodedFrameCount,V=this._mediaElement.webkitDroppedFrameCount):B=!1;return B&&(E.decodedFrames=N,E.droppedFrames=V),E}_onvLoadedMetadata(E){this._pendingSeekTime!=null&&(this._mediaElement.currentTime=this._pendingSeekTime,this._pendingSeekTime=null),this._emitter.emit(me.MEDIA_INFO,this.mediaInfo)}_reportStatisticsInfo(){this._emitter.emit(me.STATISTICS_INFO,this.statisticsInfo)}}var Pn=Sn;J.install();function hn(Ee,E){let B=Ee;if(B==null||typeof B!="object")throw new g("MediaDataSource must be an javascript object!");if(!B.hasOwnProperty("type"))throw new g("MediaDataSource must has type field to indicate video file type!");switch(B.type){case"flv":return new bn(B,E);default:return new Pn(B,E)}}function In(){return se.supportMSEH264Playback()}function Un(){return se.getFeatureList()}let Cn={};Cn.createPlayer=hn,Cn.isSupported=In,Cn.getFeatureList=Un,Cn.BaseLoader=v,Cn.LoaderStatus=L,Cn.LoaderErrors=d,Cn.Events=me,Cn.ErrorTypes=Yt,Cn.ErrorDetails=Jt,Cn.FlvPlayer=bn,Cn.NativePlayer=Pn,Cn.LoggingControl=xe,Object.defineProperty(Cn,"version",{enumerable:!0,get:function(){return"__VERSION__"}});var Bt=Cn},39293:function(Ae,Ce,Z){"use strict";var X,J=Object.defineProperty,H=Ee=>{throw TypeError(Ee)},b=Math.pow,z=(Ee,E,B)=>E in Ee?J(Ee,E,{enumerable:!0,configurable:!0,writable:!0,value:B}):Ee[E]=B,P=(Ee,E,B)=>z(Ee,typeof E!="symbol"?E+"":E,B),T=(Ee,E,B)=>E.has(Ee)||H("Cannot "+B),x=(Ee,E,B)=>(T(Ee,E,"read from private field"),B?B.call(Ee):E.get(Ee)),O=(Ee,E,B)=>E.has(Ee)?H("Cannot add the same private member more than once"):E instanceof WeakSet?E.add(Ee):E.set(Ee,B),_=(Ee,E,B,N)=>(T(Ee,E,"write to private field"),N?N.call(Ee,B):E.set(Ee,B),B),g=(Ee,E,B)=>(T(Ee,E,"access private method"),B),m,L,d;X={value:!0};var v=Z(34634),M=Z(34402);const w=" ".repeat(2),S=" ".repeat(4);function A(){return R(this)}function R(Ee,E={}){const{maxRows:B=15,maxColumns:N=10,maxNumSize:V=8,padMinus:q="auto"}=E;return`${Ee.constructor.name} {
+dts: ${Mt+Lt} ms, expected: ${Mt+Math.round(Se)} ms, delta: ${Math.round(Kt)} ms, generate: ${qt} frames`);let pn=tt.getSilentFrame(this._audioMeta.originalCodec,this._audioMeta.channelCount);pn==null&&(P.w(this.TAG,`Unable to generate silent frame for ${this._audioMeta.originalCodec} with ${this._audioMeta.channelCount} channels, repeat last frame`),pn=Zt),Vt=[];for(let yn=0;yn<qt;yn++){let Zn=Math.round(ln);if(Vt.length>0){let nn=Vt[Vt.length-1];nn.duration=Zn-nn.dts}let Nn={dts:Zn,pts:Zn,cts:0,unit:pn,size:pn.byteLength,duration:0,originalDts:lt,flags:{isLeading:0,dependsOn:1,isDependedOn:0,hasRedundancy:0}};Vt.push(Nn),st+=Nn.size,ln+=Se}let mn=Vt[Vt.length-1];mn.duration=Mt+Lt-mn.dts,Lt=Math.round(Se)}ft.push({dts:Mt,pts:Mt,cts:0,unit:It.unit,size:It.unit.byteLength,duration:Lt,originalDts:lt,flags:{isLeading:0,dependsOn:1,isDependedOn:0,hasRedundancy:0}}),Nt&&ft.push.apply(ft,Vt)}Ue?et=new Uint8Array(st):(et=new Uint8Array(st),et[0]=st>>>24&255,et[1]=st>>>16&255,et[2]=st>>>8&255,et[3]=st&255,et.set(Fe.types.mdat,4));for(let Ct=0;Ct<ft.length;Ct++){let It=ft[Ct].unit;et.set(It,at),at+=It.byteLength}let yt=ft[ft.length-1];ce=yt.dts+yt.duration,this._audioNextDts=ce;let Pt=new pt;Pt.beginDts=ue,Pt.endDts=ce,Pt.beginPts=ue,Pt.endPts=ce,Pt.originalBeginDts=ft[0].originalDts,Pt.originalEndDts=yt.originalDts+yt.duration,Pt.firstSample=new dt(ft[0].dts,ft[0].pts,ft[0].duration,ft[0].originalDts,!1),Pt.lastSample=new dt(yt.dts,yt.pts,yt.duration,yt.originalDts,!1),this._isLive||this._audioSegmentInfoList.append(Pt),N.samples=ft,N.sequenceNumber++;let Ut=null;Ue?Ut=new Uint8Array:Ut=Fe.moof(N,ue),N.samples=[],N.length=0;let Qt={type:"audio",data:this._mergeBoxes(Ut,et).buffer,sampleCount:ft.length,info:Pt};Ue&&je&&(Qt.timestampOffset=ue),this._onMediaSegment("audio",Qt)}_remuxVideo(E,B){if(this._videoMeta==null)return;let N=E,V=N.samples,q,ue=-1,ce=-1,Oe=-1,Se=-1;if(!V||V.length===0||V.length===1&&!B)return;let Ue=8,je=null,it=8+E.length,at=null;if(V.length>1&&(at=V.pop(),it-=at.length),this._videoStashedLastSample!=null){let yt=this._videoStashedLastSample;this._videoStashedLastSample=null,V.unshift(yt),it+=yt.length}at!=null&&(this._videoStashedLastSample=at);let et=V[0].dts-this._dtsBase;if(this._videoNextDts)q=et-this._videoNextDts;else if(this._videoSegmentInfoList.isEmpty())q=0;else{let yt=this._videoSegmentInfoList.getLastSampleBefore(et);if(yt!=null){let Pt=et-(yt.originalDts+yt.duration);Pt<=3&&(Pt=0);let Ut=yt.dts+yt.duration+Pt;q=et-Ut}else q=0}let st=new pt,Je=[];for(let yt=0;yt<V.length;yt++){let Pt=V[yt],Ut=Pt.dts-this._dtsBase,Qt=Pt.isKeyframe,Ct=Ut-q,It=Pt.cts,Zt=Ct+It;ue===-1&&(ue=Ct,Oe=Zt);let lt=0;if(yt!==V.length-1?lt=V[yt+1].dts-this._dtsBase-q-Ct:at!=null?lt=at.dts-this._dtsBase-q-Ct:Je.length>=1?lt=Je[Je.length-1].duration:lt=Math.floor(this._videoMeta.refSampleDuration),Qt){let Mt=new dt(Ct,Zt,lt,Pt.dts,!0);Mt.fileposition=Pt.fileposition,st.appendSyncPoint(Mt)}Je.push({dts:Ct,pts:Zt,cts:It,units:Pt.units,size:Pt.length,isKeyframe:Qt,duration:lt,originalDts:Ut,flags:{isLeading:0,dependsOn:Qt?2:1,isDependedOn:Qt?1:0,hasRedundancy:0,isNonSync:Qt?0:1}})}je=new Uint8Array(it),je[0]=it>>>24&255,je[1]=it>>>16&255,je[2]=it>>>8&255,je[3]=it&255,je.set(Fe.types.mdat,4);for(let yt=0;yt<Je.length;yt++){let Pt=Je[yt].units;for(;Pt.length;){let Qt=Pt.shift().data;je.set(Qt,Ue),Ue+=Qt.byteLength}}let ke=Je[Je.length-1];if(ce=ke.dts+ke.duration,Se=ke.pts+ke.duration,this._videoNextDts=ce,st.beginDts=ue,st.endDts=ce,st.beginPts=Oe,st.endPts=Se,st.originalBeginDts=Je[0].originalDts,st.originalEndDts=ke.originalDts+ke.duration,st.firstSample=new dt(Je[0].dts,Je[0].pts,Je[0].duration,Je[0].originalDts,Je[0].isKeyframe),st.lastSample=new dt(ke.dts,ke.pts,ke.duration,ke.originalDts,ke.isKeyframe),this._isLive||this._videoSegmentInfoList.append(st),N.samples=Je,N.sequenceNumber++,this._forceFirstIDR){let yt=Je[0].flags;yt.dependsOn=2,yt.isNonSync=0}let ft=Fe.moof(N,ue);N.samples=[],N.length=0,this._onMediaSegment("video",{type:"video",data:this._mergeBoxes(ft,je).buffer,sampleCount:Je.length,info:st})}_mergeBoxes(E,B){let N=new Uint8Array(E.byteLength+B.byteLength);return N.set(E,0),N.set(B,E.byteLength),N}}var ht=Ye,_t={IO_ERROR:"io_error",DEMUX_ERROR:"demux_error",INIT_SEGMENT:"init_segment",MEDIA_SEGMENT:"media_segment",LOADING_COMPLETE:"loading_complete",RECOVERED_EARLY_EOF:"recovered_early_eof",MEDIA_INFO:"media_info",METADATA_ARRIVED:"metadata_arrived",SCRIPTDATA_ARRIVED:"scriptdata_arrived",STATISTICS_INFO:"statistics_info",RECOMMEND_SEEKPOINT:"recommend_seekpoint"};class Ot{constructor(E,B){this.TAG="TransmuxingController",this._emitter=new(b()),this._config=B,E.segments||(E.segments=[{duration:E.duration,filesize:E.filesize,url:E.url}]),typeof E.cors!="boolean"&&(E.cors=!0),typeof E.withCredentials!="boolean"&&(E.withCredentials=!1),this._mediaDataSource=E,this._currentSegmentIndex=0;let N=0;this._mediaDataSource.segments.forEach(V=>{V.timestampBase=N,N+=V.duration,V.cors=E.cors,V.withCredentials=E.withCredentials,B.referrerPolicy&&(V.referrerPolicy=B.referrerPolicy)}),!isNaN(N)&&this._mediaDataSource.duration!==N&&(this._mediaDataSource.duration=N),this._mediaInfo=null,this._demuxer=null,this._remuxer=null,this._ioctl=null,this._pendingSeekTime=null,this._pendingResolveSeekPoint=null,this._statisticsReporter=null}destroy(){this._mediaInfo=null,this._mediaDataSource=null,this._statisticsReporter&&this._disableStatisticsReporter(),this._ioctl&&(this._ioctl.destroy(),this._ioctl=null),this._demuxer&&(this._demuxer.destroy(),this._demuxer=null),this._remuxer&&(this._remuxer.destroy(),this._remuxer=null),this._emitter.removeAllListeners(),this._emitter=null}on(E,B){this._emitter.addListener(E,B)}off(E,B){this._emitter.removeListener(E,B)}start(){this._loadSegment(0),this._enableStatisticsReporter()}_loadSegment(E,B){this._currentSegmentIndex=E;let N=this._mediaDataSource.segments[E],V=this._ioctl=new ne(N,this._config,E);V.onError=this._onIOException.bind(this),V.onSeeked=this._onIOSeeked.bind(this),V.onComplete=this._onIOComplete.bind(this),V.onRedirect=this._onIORedirect.bind(this),V.onRecoveredEarlyEof=this._onIORecoveredEarlyEof.bind(this),B?this._demuxer.bindDataSource(this._ioctl):V.onDataArrival=this._onInitChunkArrival.bind(this),V.open(B)}stop(){this._internalAbort(),this._disableStatisticsReporter()}_internalAbort(){this._ioctl&&(this._ioctl.destroy(),this._ioctl=null)}pause(){this._ioctl&&this._ioctl.isWorking()&&(this._ioctl.pause(),this._disableStatisticsReporter())}resume(){this._ioctl&&this._ioctl.isPaused()&&(this._ioctl.resume(),this._enableStatisticsReporter())}seek(E){if(this._mediaInfo==null||!this._mediaInfo.isSeekable())return;let B=this._searchSegmentIndexContains(E);if(B===this._currentSegmentIndex){let N=this._mediaInfo.segments[B];if(N==null)this._pendingSeekTime=E;else{let V=N.getNearestKeyframe(E);this._remuxer.seek(V.milliseconds),this._ioctl.seek(V.fileposition),this._pendingResolveSeekPoint=V.milliseconds}}else{let N=this._mediaInfo.segments[B];if(N==null)this._pendingSeekTime=E,this._internalAbort(),this._remuxer.seek(),this._remuxer.insertDiscontinuity(),this._loadSegment(B);else{let V=N.getNearestKeyframe(E);this._internalAbort(),this._remuxer.seek(E),this._remuxer.insertDiscontinuity(),this._demuxer.resetMediaInfo(),this._demuxer.timestampBase=this._mediaDataSource.segments[B].timestampBase,this._loadSegment(B,V.fileposition),this._pendingResolveSeekPoint=V.milliseconds,this._reportSegmentMediaInfo(B)}}this._enableStatisticsReporter()}_searchSegmentIndexContains(E){let B=this._mediaDataSource.segments,N=B.length-1;for(let V=0;V<B.length;V++)if(E<B[V].timestampBase){N=V-1;break}return N}_onInitChunkArrival(E,B){let N=null,V=0;if(B>0)this._demuxer.bindDataSource(this._ioctl),this._demuxer.timestampBase=this._mediaDataSource.segments[this._currentSegmentIndex].timestampBase,V=this._demuxer.parseChunks(E,B);else if((N=Ge.probe(E)).match){this._demuxer=new Ge(N,this._config),this._remuxer||(this._remuxer=new ht(this._config));let q=this._mediaDataSource;q.duration!=null&&!isNaN(q.duration)&&(this._demuxer.overridedDuration=q.duration),typeof q.hasAudio=="boolean"&&(this._demuxer.overridedHasAudio=q.hasAudio),typeof q.hasVideo=="boolean"&&(this._demuxer.overridedHasVideo=q.hasVideo),this._demuxer.timestampBase=q.segments[this._currentSegmentIndex].timestampBase,this._demuxer.onError=this._onDemuxException.bind(this),this._demuxer.onMediaInfo=this._onMediaInfo.bind(this),this._demuxer.onMetaDataArrived=this._onMetaDataArrived.bind(this),this._demuxer.onScriptDataArrived=this._onScriptDataArrived.bind(this),this._remuxer.bindDataSource(this._demuxer.bindDataSource(this._ioctl)),this._remuxer.onInitSegment=this._onRemuxerInitSegmentArrival.bind(this),this._remuxer.onMediaSegment=this._onRemuxerMediaSegmentArrival.bind(this),V=this._demuxer.parseChunks(E,B)}else N=null,P.e(this.TAG,"Non-FLV, Unsupported media type!"),Promise.resolve().then(()=>{this._internalAbort()}),this._emitter.emit(_t.DEMUX_ERROR,He.FORMAT_UNSUPPORTED,"Non-FLV, Unsupported media type"),V=0;return V}_onMediaInfo(E){this._mediaInfo==null&&(this._mediaInfo=Object.assign({},E),this._mediaInfo.keyframesIndex=null,this._mediaInfo.segments=[],this._mediaInfo.segmentCount=this._mediaDataSource.segments.length,Object.setPrototypeOf(this._mediaInfo,Ne.prototype));let B=Object.assign({},E);Object.setPrototypeOf(B,Ne.prototype),this._mediaInfo.segments[this._currentSegmentIndex]=B,this._reportSegmentMediaInfo(this._currentSegmentIndex),this._pendingSeekTime!=null&&Promise.resolve().then(()=>{let N=this._pendingSeekTime;this._pendingSeekTime=null,this.seek(N)})}_onMetaDataArrived(E){this._emitter.emit(_t.METADATA_ARRIVED,E)}_onScriptDataArrived(E){this._emitter.emit(_t.SCRIPTDATA_ARRIVED,E)}_onIOSeeked(){this._remuxer.insertDiscontinuity()}_onIOComplete(E){let N=E+1;N<this._mediaDataSource.segments.length?(this._internalAbort(),this._remuxer.flushStashedSamples(),this._loadSegment(N)):(this._remuxer.flushStashedSamples(),this._emitter.emit(_t.LOADING_COMPLETE),this._disableStatisticsReporter())}_onIORedirect(E){let B=this._ioctl.extraData;this._mediaDataSource.segments[B].redirectedURL=E}_onIORecoveredEarlyEof(){this._emitter.emit(_t.RECOVERED_EARLY_EOF)}_onIOException(E,B){P.e(this.TAG,`IOException: type = ${E}, code = ${B.code}, msg = ${B.msg}`),this._emitter.emit(_t.IO_ERROR,E,B),this._disableStatisticsReporter()}_onDemuxException(E,B){P.e(this.TAG,`DemuxException: type = ${E}, info = ${B}`),this._emitter.emit(_t.DEMUX_ERROR,E,B)}_onRemuxerInitSegmentArrival(E,B){this._emitter.emit(_t.INIT_SEGMENT,E,B)}_onRemuxerMediaSegmentArrival(E,B){if(this._pendingSeekTime==null&&(this._emitter.emit(_t.MEDIA_SEGMENT,E,B),this._pendingResolveSeekPoint!=null&&E==="video")){let N=B.info.syncPoints,V=this._pendingResolveSeekPoint;this._pendingResolveSeekPoint=null,S.safari&&N.length>0&&N[0].originalDts===V&&(V=N[0].pts),this._emitter.emit(_t.RECOMMEND_SEEKPOINT,V)}}_enableStatisticsReporter(){this._statisticsReporter==null&&(this._statisticsReporter=self.setInterval(this._reportStatisticsInfo.bind(this),this._config.statisticsInfoReportInterval))}_disableStatisticsReporter(){this._statisticsReporter&&(self.clearInterval(this._statisticsReporter),this._statisticsReporter=null)}_reportSegmentMediaInfo(E){let B=this._mediaInfo.segments[E],N=Object.assign({},B);N.duration=this._mediaInfo.duration,N.segmentCount=this._mediaInfo.segmentCount,delete N.segments,delete N.keyframesIndex,this._emitter.emit(_t.MEDIA_INFO,N)}_reportStatisticsInfo(){let E={};E.url=this._ioctl.currentURL,E.hasRedirect=this._ioctl.hasRedirect,E.hasRedirect&&(E.redirectedURL=this._ioctl.currentRedirectedURL),E.speed=this._ioctl.currentSpeed,E.loaderType=this._ioctl.loaderType,E.currentSegmentIndex=this._currentSegmentIndex,E.totalSegmentCount=this._mediaDataSource.segments.length,this._emitter.emit(_t.STATISTICS_INFO,E)}}var Wt=Ot,zt=function(Ee){let E="TransmuxingWorker",B=null,N=st.bind(this);J.install(),Ee.addEventListener("message",function(Je){switch(Je.data.cmd){case"init":B=new Wt(Je.data.param[0],Je.data.param[1]),B.on(_t.IO_ERROR,it.bind(this)),B.on(_t.DEMUX_ERROR,at.bind(this)),B.on(_t.INIT_SEGMENT,V.bind(this)),B.on(_t.MEDIA_SEGMENT,q.bind(this)),B.on(_t.LOADING_COMPLETE,ue.bind(this)),B.on(_t.RECOVERED_EARLY_EOF,ce.bind(this)),B.on(_t.MEDIA_INFO,Oe.bind(this)),B.on(_t.METADATA_ARRIVED,Se.bind(this)),B.on(_t.SCRIPTDATA_ARRIVED,Ue.bind(this)),B.on(_t.STATISTICS_INFO,je.bind(this)),B.on(_t.RECOMMEND_SEEKPOINT,et.bind(this));break;case"destroy":B&&(B.destroy(),B=null),Ee.postMessage({msg:"destroyed"});break;case"start":B.start();break;case"stop":B.stop();break;case"seek":B.seek(Je.data.param);break;case"pause":B.pause();break;case"resume":B.resume();break;case"logging_config":{let ke=Je.data.param;xe.applyConfig(ke),ke.enableCallback===!0?xe.addLogListener(N):xe.removeLogListener(N);break}}});function V(Je,ke){let ft={msg:_t.INIT_SEGMENT,data:{type:Je,data:ke}};Ee.postMessage(ft,[ke.data])}function q(Je,ke){let ft={msg:_t.MEDIA_SEGMENT,data:{type:Je,data:ke}};Ee.postMessage(ft,[ke.data])}function ue(){let Je={msg:_t.LOADING_COMPLETE};Ee.postMessage(Je)}function ce(){let Je={msg:_t.RECOVERED_EARLY_EOF};Ee.postMessage(Je)}function Oe(Je){let ke={msg:_t.MEDIA_INFO,data:Je};Ee.postMessage(ke)}function Se(Je){let ke={msg:_t.METADATA_ARRIVED,data:Je};Ee.postMessage(ke)}function Ue(Je){let ke={msg:_t.SCRIPTDATA_ARRIVED,data:Je};Ee.postMessage(ke)}function je(Je){let ke={msg:_t.STATISTICS_INFO,data:Je};Ee.postMessage(ke)}function it(Je,ke){Ee.postMessage({msg:_t.IO_ERROR,data:{type:Je,info:ke}})}function at(Je,ke){Ee.postMessage({msg:_t.DEMUX_ERROR,data:{type:Je,info:ke}})}function et(Je){Ee.postMessage({msg:_t.RECOMMEND_SEEKPOINT,data:Je})}function st(Je,ke){Ee.postMessage({msg:"logcat_callback",data:{type:Je,logcat:ke}})}};class en{constructor(E,B){if(this.TAG="Transmuxer",this._emitter=new(b()),B.enableWorker&&typeof Worker!="undefined")try{let N=Z(82059);this._worker=N(zt),this._workerDestroying=!1,this._worker.addEventListener("message",this._onWorkerMessage.bind(this)),this._worker.postMessage({cmd:"init",param:[E,B]}),this.e={onLoggingConfigChanged:this._onLoggingConfigChanged.bind(this)},xe.registerListener(this.e.onLoggingConfigChanged),this._worker.postMessage({cmd:"logging_config",param:xe.getConfig()})}catch(N){P.e(this.TAG,"Error while initialize transmuxing worker, fallback to inline transmuxing"),this._worker=null,this._controller=new Wt(E,B)}else this._controller=new Wt(E,B);if(this._controller){let N=this._controller;N.on(_t.IO_ERROR,this._onIOError.bind(this)),N.on(_t.DEMUX_ERROR,this._onDemuxError.bind(this)),N.on(_t.INIT_SEGMENT,this._onInitSegment.bind(this)),N.on(_t.MEDIA_SEGMENT,this._onMediaSegment.bind(this)),N.on(_t.LOADING_COMPLETE,this._onLoadingComplete.bind(this)),N.on(_t.RECOVERED_EARLY_EOF,this._onRecoveredEarlyEof.bind(this)),N.on(_t.MEDIA_INFO,this._onMediaInfo.bind(this)),N.on(_t.METADATA_ARRIVED,this._onMetaDataArrived.bind(this)),N.on(_t.SCRIPTDATA_ARRIVED,this._onScriptDataArrived.bind(this)),N.on(_t.STATISTICS_INFO,this._onStatisticsInfo.bind(this)),N.on(_t.RECOMMEND_SEEKPOINT,this._onRecommendSeekpoint.bind(this))}}destroy(){this._worker?this._workerDestroying||(this._workerDestroying=!0,this._worker.postMessage({cmd:"destroy"}),xe.removeListener(this.e.onLoggingConfigChanged),this.e=null):(this._controller.destroy(),this._controller=null),this._emitter.removeAllListeners(),this._emitter=null}on(E,B){this._emitter.addListener(E,B)}off(E,B){this._emitter.removeListener(E,B)}hasWorker(){return this._worker!=null}open(){this._worker?this._worker.postMessage({cmd:"start"}):this._controller.start()}close(){this._worker?this._worker.postMessage({cmd:"stop"}):this._controller.stop()}seek(E){this._worker?this._worker.postMessage({cmd:"seek",param:E}):this._controller.seek(E)}pause(){this._worker?this._worker.postMessage({cmd:"pause"}):this._controller.pause()}resume(){this._worker?this._worker.postMessage({cmd:"resume"}):this._controller.resume()}_onInitSegment(E,B){Promise.resolve().then(()=>{this._emitter.emit(_t.INIT_SEGMENT,E,B)})}_onMediaSegment(E,B){Promise.resolve().then(()=>{this._emitter.emit(_t.MEDIA_SEGMENT,E,B)})}_onLoadingComplete(){Promise.resolve().then(()=>{this._emitter.emit(_t.LOADING_COMPLETE)})}_onRecoveredEarlyEof(){Promise.resolve().then(()=>{this._emitter.emit(_t.RECOVERED_EARLY_EOF)})}_onMediaInfo(E){Promise.resolve().then(()=>{this._emitter.emit(_t.MEDIA_INFO,E)})}_onMetaDataArrived(E){Promise.resolve().then(()=>{this._emitter.emit(_t.METADATA_ARRIVED,E)})}_onScriptDataArrived(E){Promise.resolve().then(()=>{this._emitter.emit(_t.SCRIPTDATA_ARRIVED,E)})}_onStatisticsInfo(E){Promise.resolve().then(()=>{this._emitter.emit(_t.STATISTICS_INFO,E)})}_onIOError(E,B){Promise.resolve().then(()=>{this._emitter.emit(_t.IO_ERROR,E,B)})}_onDemuxError(E,B){Promise.resolve().then(()=>{this._emitter.emit(_t.DEMUX_ERROR,E,B)})}_onRecommendSeekpoint(E){Promise.resolve().then(()=>{this._emitter.emit(_t.RECOMMEND_SEEKPOINT,E)})}_onLoggingConfigChanged(E){this._worker&&this._worker.postMessage({cmd:"logging_config",param:E})}_onWorkerMessage(E){let B=E.data,N=B.data;if(B.msg==="destroyed"||this._workerDestroying){this._workerDestroying=!1,this._worker.terminate(),this._worker=null;return}switch(B.msg){case _t.INIT_SEGMENT:case _t.MEDIA_SEGMENT:this._emitter.emit(B.msg,N.type,N.data);break;case _t.LOADING_COMPLETE:case _t.RECOVERED_EARLY_EOF:this._emitter.emit(B.msg);break;case _t.MEDIA_INFO:Object.setPrototypeOf(N,Ne.prototype),this._emitter.emit(B.msg,N);break;case _t.METADATA_ARRIVED:case _t.SCRIPTDATA_ARRIVED:case _t.STATISTICS_INFO:this._emitter.emit(B.msg,N);break;case _t.IO_ERROR:case _t.DEMUX_ERROR:this._emitter.emit(B.msg,N.type,N.info);break;case _t.RECOMMEND_SEEKPOINT:this._emitter.emit(B.msg,N);break;case"logcat_callback":P.emitter.emit("log",N.type,N.logcat);break;default:break}}}var vn=en,cn={ERROR:"error",SOURCE_OPEN:"source_open",UPDATE_END:"update_end",BUFFER_FULL:"buffer_full"};class On{constructor(E){this.TAG="MSEController",this._config=E,this._emitter=new(b()),this._config.isLive&&this._config.autoCleanupSourceBuffer==null&&(this._config.autoCleanupSourceBuffer=!0),this.e={onSourceOpen:this._onSourceOpen.bind(this),onSourceEnded:this._onSourceEnded.bind(this),onSourceClose:this._onSourceClose.bind(this),onSourceBufferError:this._onSourceBufferError.bind(this),onSourceBufferUpdateEnd:this._onSourceBufferUpdateEnd.bind(this)},this._mediaSource=null,this._mediaSourceObjectURL=null,this._mediaElement=null,this._isBufferFull=!1,this._hasPendingEos=!1,this._requireSetMediaDuration=!1,this._pendingMediaDuration=0,this._pendingSourceBufferInit=[],this._mimeTypes={video:null,audio:null},this._sourceBuffers={video:null,audio:null},this._lastInitSegments={video:null,audio:null},this._pendingSegments={video:[],audio:[]},this._pendingRemoveRanges={video:[],audio:[]},this._idrList=new Tt}destroy(){(this._mediaElement||this._mediaSource)&&this.detachMediaElement(),this.e=null,this._emitter.removeAllListeners(),this._emitter=null}on(E,B){this._emitter.addListener(E,B)}off(E,B){this._emitter.removeListener(E,B)}attachMediaElement(E){if(this._mediaSource)throw new _("MediaSource has been attached to an HTMLMediaElement!");let B=this._mediaSource=new window.MediaSource;B.addEventListener("sourceopen",this.e.onSourceOpen),B.addEventListener("sourceended",this.e.onSourceEnded),B.addEventListener("sourceclose",this.e.onSourceClose),this._mediaElement=E,this._mediaSourceObjectURL=window.URL.createObjectURL(this._mediaSource),E.src=this._mediaSourceObjectURL}detachMediaElement(){if(this._mediaSource){let E=this._mediaSource;for(let B in this._sourceBuffers){let N=this._pendingSegments[B];N.splice(0,N.length),this._pendingSegments[B]=null,this._pendingRemoveRanges[B]=null,this._lastInitSegments[B]=null;let V=this._sourceBuffers[B];if(V){if(E.readyState!=="closed"){try{E.removeSourceBuffer(V)}catch(q){P.e(this.TAG,q.message)}V.removeEventListener("error",this.e.onSourceBufferError),V.removeEventListener("updateend",this.e.onSourceBufferUpdateEnd)}this._mimeTypes[B]=null,this._sourceBuffers[B]=null}}if(E.readyState==="open")try{E.endOfStream()}catch(B){P.e(this.TAG,B.message)}E.removeEventListener("sourceopen",this.e.onSourceOpen),E.removeEventListener("sourceended",this.e.onSourceEnded),E.removeEventListener("sourceclose",this.e.onSourceClose),this._pendingSourceBufferInit=[],this._isBufferFull=!1,this._idrList.clear(),this._mediaSource=null}this._mediaElement&&(this._mediaElement.src="",this._mediaElement.removeAttribute("src"),this._mediaElement=null),this._mediaSourceObjectURL&&(window.URL.revokeObjectURL(this._mediaSourceObjectURL),this._mediaSourceObjectURL=null)}appendInitSegment(E,B){if(!this._mediaSource||this._mediaSource.readyState!=="open"){this._pendingSourceBufferInit.push(E),this._pendingSegments[E.type].push(E);return}let N=E,V=`${N.container}`;N.codec&&N.codec.length>0&&(V+=`;codecs=${N.codec}`);let q=!1;if(P.v(this.TAG,"Received Initialization Segment, mimeType: "+V),this._lastInitSegments[N.type]=N,V!==this._mimeTypes[N.type]){if(this._mimeTypes[N.type])P.v(this.TAG,`Notice: ${N.type} mimeType changed, origin: ${this._mimeTypes[N.type]}, target: ${V}`);else{q=!0;try{let ue=this._sourceBuffers[N.type]=this._mediaSource.addSourceBuffer(V);ue.addEventListener("error",this.e.onSourceBufferError),ue.addEventListener("updateend",this.e.onSourceBufferUpdateEnd)}catch(ue){P.e(this.TAG,ue.message),this._emitter.emit(cn.ERROR,{code:ue.code,msg:ue.message});return}}this._mimeTypes[N.type]=V}B||this._pendingSegments[N.type].push(N),q||this._sourceBuffers[N.type]&&!this._sourceBuffers[N.type].updating&&this._doAppendSegments(),S.safari&&N.container==="audio/mpeg"&&N.mediaDuration>0&&(this._requireSetMediaDuration=!0,this._pendingMediaDuration=N.mediaDuration/1e3,this._updateMediaSourceDuration())}appendMediaSegment(E){let B=E;this._pendingSegments[B.type].push(B),this._config.autoCleanupSourceBuffer&&this._needCleanupSourceBuffer()&&this._doCleanupSourceBuffer();let N=this._sourceBuffers[B.type];N&&!N.updating&&!this._hasPendingRemoveRanges()&&this._doAppendSegments()}seek(E){for(let B in this._sourceBuffers){if(!this._sourceBuffers[B])continue;let N=this._sourceBuffers[B];if(this._mediaSource.readyState==="open")try{N.abort()}catch(q){P.e(this.TAG,q.message)}this._idrList.clear();let V=this._pendingSegments[B];if(V.splice(0,V.length),this._mediaSource.readyState!=="closed"){for(let q=0;q<N.buffered.length;q++){let ue=N.buffered.start(q),ce=N.buffered.end(q);this._pendingRemoveRanges[B].push({start:ue,end:ce})}if(N.updating||this._doRemoveRanges(),S.safari){let q=this._lastInitSegments[B];q&&(this._pendingSegments[B].push(q),N.updating||this._doAppendSegments())}}}}endOfStream(){let E=this._mediaSource,B=this._sourceBuffers;if(!E||E.readyState!=="open"){E&&E.readyState==="closed"&&this._hasPendingSegments()&&(this._hasPendingEos=!0);return}B.video&&B.video.updating||B.audio&&B.audio.updating?this._hasPendingEos=!0:(this._hasPendingEos=!1,E.endOfStream())}getNearestKeyframe(E){return this._idrList.getLastSyncPointBeforeDts(E)}_needCleanupSourceBuffer(){if(!this._config.autoCleanupSourceBuffer)return!1;let E=this._mediaElement.currentTime;for(let B in this._sourceBuffers){let N=this._sourceBuffers[B];if(N){let V=N.buffered;if(V.length>=1&&E-V.start(0)>=this._config.autoCleanupMaxBackwardDuration)return!0}}return!1}_doCleanupSourceBuffer(){let E=this._mediaElement.currentTime;for(let B in this._sourceBuffers){let N=this._sourceBuffers[B];if(N){let V=N.buffered,q=!1;for(let ue=0;ue<V.length;ue++){let ce=V.start(ue),Oe=V.end(ue);if(ce<=E&&E<Oe+3){if(E-ce>=this._config.autoCleanupMaxBackwardDuration){q=!0;let Se=E-this._config.autoCleanupMinBackwardDuration;this._pendingRemoveRanges[B].push({start:ce,end:Se})}}else Oe<E&&(q=!0,this._pendingRemoveRanges[B].push({start:ce,end:Oe}))}q&&!N.updating&&this._doRemoveRanges()}}}_updateMediaSourceDuration(){let E=this._sourceBuffers;if(this._mediaElement.readyState===0||this._mediaSource.readyState!=="open"||E.video&&E.video.updating||E.audio&&E.audio.updating)return;let B=this._mediaSource.duration,N=this._pendingMediaDuration;N>0&&(isNaN(B)||N>B)&&(P.v(this.TAG,`Update MediaSource duration from ${B} to ${N}`),this._mediaSource.duration=N),this._requireSetMediaDuration=!1,this._pendingMediaDuration=0}_doRemoveRanges(){for(let E in this._pendingRemoveRanges){if(!this._sourceBuffers[E]||this._sourceBuffers[E].updating)continue;let B=this._sourceBuffers[E],N=this._pendingRemoveRanges[E];for(;N.length&&!B.updating;){let V=N.shift();B.remove(V.start,V.end)}}}_doAppendSegments(){let E=this._pendingSegments;for(let B in E)if(!(!this._sourceBuffers[B]||this._sourceBuffers[B].updating)&&E[B].length>0){let N=E[B].shift();if(N.timestampOffset){let V=this._sourceBuffers[B].timestampOffset,q=N.timestampOffset/1e3;Math.abs(V-q)>.1&&(P.v(this.TAG,`Update MPEG audio timestampOffset from ${V} to ${q}`),this._sourceBuffers[B].timestampOffset=q),delete N.timestampOffset}if(!N.data||N.data.byteLength===0)continue;try{this._sourceBuffers[B].appendBuffer(N.data),this._isBufferFull=!1,B==="video"&&N.hasOwnProperty("info")&&this._idrList.appendArray(N.info.syncPoints)}catch(V){this._pendingSegments[B].unshift(N),V.code===22?(this._isBufferFull||this._emitter.emit(cn.BUFFER_FULL),this._isBufferFull=!0):(P.e(this.TAG,V.message),this._emitter.emit(cn.ERROR,{code:V.code,msg:V.message}))}}}_onSourceOpen(){if(P.v(this.TAG,"MediaSource onSourceOpen"),this._mediaSource.removeEventListener("sourceopen",this.e.onSourceOpen),this._pendingSourceBufferInit.length>0){let E=this._pendingSourceBufferInit;for(;E.length;){let B=E.shift();this.appendInitSegment(B,!0)}}this._hasPendingSegments()&&this._doAppendSegments(),this._emitter.emit(cn.SOURCE_OPEN)}_onSourceEnded(){P.v(this.TAG,"MediaSource onSourceEnded")}_onSourceClose(){P.v(this.TAG,"MediaSource onSourceClose"),this._mediaSource&&this.e!=null&&(this._mediaSource.removeEventListener("sourceopen",this.e.onSourceOpen),this._mediaSource.removeEventListener("sourceended",this.e.onSourceEnded),this._mediaSource.removeEventListener("sourceclose",this.e.onSourceClose))}_hasPendingSegments(){let E=this._pendingSegments;return E.video.length>0||E.audio.length>0}_hasPendingRemoveRanges(){let E=this._pendingRemoveRanges;return E.video.length>0||E.audio.length>0}_onSourceBufferUpdateEnd(){this._requireSetMediaDuration?this._updateMediaSourceDuration():this._hasPendingRemoveRanges()?this._doRemoveRanges():this._hasPendingSegments()?this._doAppendSegments():this._hasPendingEos&&this.endOfStream(),this._emitter.emit(cn.UPDATE_END)}_onSourceBufferError(E){P.e(this.TAG,`SourceBuffer Error: ${E}`)}}var Mn=On;const Yt={NETWORK_ERROR:"NetworkError",MEDIA_ERROR:"MediaError",OTHER_ERROR:"OtherError"},Jt={NETWORK_EXCEPTION:d.EXCEPTION,NETWORK_STATUS_CODE_INVALID:d.HTTP_STATUS_CODE_INVALID,NETWORK_TIMEOUT:d.CONNECTING_TIMEOUT,NETWORK_UNRECOVERABLE_EARLY_EOF:d.UNRECOVERABLE_EARLY_EOF,MEDIA_MSE_ERROR:"MediaMSEError",MEDIA_FORMAT_ERROR:He.FORMAT_ERROR,MEDIA_FORMAT_UNSUPPORTED:He.FORMAT_UNSUPPORTED,MEDIA_CODEC_UNSUPPORTED:He.CODEC_UNSUPPORTED};class Ht{constructor(E,B){if(this.TAG="FlvPlayer",this._type="FlvPlayer",this._emitter=new(b()),this._config=ae(),typeof B=="object"&&Object.assign(this._config,B),E.type.toLowerCase()!=="flv")throw new g("FlvPlayer requires an flv MediaDataSource input!");E.isLive===!0&&(this._config.isLive=!0),this.e={onvLoadedMetadata:this._onvLoadedMetadata.bind(this),onvSeeking:this._onvSeeking.bind(this),onvCanPlay:this._onvCanPlay.bind(this),onvStalled:this._onvStalled.bind(this),onvProgress:this._onvProgress.bind(this)},self.performance&&self.performance.now?this._now=self.performance.now.bind(self.performance):this._now=Date.now,this._pendingSeekTime=null,this._requestSetTime=!1,this._seekpointRecord=null,this._progressChecker=null,this._mediaDataSource=E,this._mediaElement=null,this._msectl=null,this._transmuxer=null,this._mseSourceOpened=!1,this._hasPendingLoad=!1,this._receivedCanPlay=!1,this._mediaInfo=null,this._statisticsInfo=null;let N=S.chrome&&(S.version.major<50||S.version.major===50&&S.version.build<2661);this._alwaysSeekKeyframe=!!(N||S.msedge||S.msie),this._alwaysSeekKeyframe&&(this._config.accurateSeek=!1)}destroy(){this._progressChecker!=null&&(window.clearInterval(this._progressChecker),this._progressChecker=null),this._transmuxer&&this.unload(),this._mediaElement&&this.detachMediaElement(),this.e=null,this._mediaDataSource=null,this._emitter.removeAllListeners(),this._emitter=null}on(E,B){E===me.MEDIA_INFO?this._mediaInfo!=null&&Promise.resolve().then(()=>{this._emitter.emit(me.MEDIA_INFO,this.mediaInfo)}):E===me.STATISTICS_INFO&&this._statisticsInfo!=null&&Promise.resolve().then(()=>{this._emitter.emit(me.STATISTICS_INFO,this.statisticsInfo)}),this._emitter.addListener(E,B)}off(E,B){this._emitter.removeListener(E,B)}attachMediaElement(E){if(this._mediaElement=E,E.addEventListener("loadedmetadata",this.e.onvLoadedMetadata),E.addEventListener("seeking",this.e.onvSeeking),E.addEventListener("canplay",this.e.onvCanPlay),E.addEventListener("stalled",this.e.onvStalled),E.addEventListener("progress",this.e.onvProgress),this._msectl=new Mn(this._config),this._msectl.on(cn.UPDATE_END,this._onmseUpdateEnd.bind(this)),this._msectl.on(cn.BUFFER_FULL,this._onmseBufferFull.bind(this)),this._msectl.on(cn.SOURCE_OPEN,()=>{this._mseSourceOpened=!0,this._hasPendingLoad&&(this._hasPendingLoad=!1,this.load())}),this._msectl.on(cn.ERROR,B=>{this._emitter.emit(me.ERROR,Yt.MEDIA_ERROR,Jt.MEDIA_MSE_ERROR,B)}),this._msectl.attachMediaElement(E),this._pendingSeekTime!=null)try{E.currentTime=this._pendingSeekTime,this._pendingSeekTime=null}catch(B){}}detachMediaElement(){this._mediaElement&&(this._msectl.detachMediaElement(),this._mediaElement.removeEventListener("loadedmetadata",this.e.onvLoadedMetadata),this._mediaElement.removeEventListener("seeking",this.e.onvSeeking),this._mediaElement.removeEventListener("canplay",this.e.onvCanPlay),this._mediaElement.removeEventListener("stalled",this.e.onvStalled),this._mediaElement.removeEventListener("progress",this.e.onvProgress),this._mediaElement=null),this._msectl&&(this._msectl.destroy(),this._msectl=null)}load(){if(!this._mediaElement)throw new _("HTMLMediaElement must be attached before load()!");if(this._transmuxer)throw new _("FlvPlayer.load() has been called, please call unload() first!");if(!this._hasPendingLoad){if(this._config.deferLoadAfterSourceOpen&&this._mseSourceOpened===!1){this._hasPendingLoad=!0;return}this._mediaElement.readyState>0&&(this._requestSetTime=!0,this._mediaElement.currentTime=0),this._transmuxer=new vn(this._mediaDataSource,this._config),this._transmuxer.on(_t.INIT_SEGMENT,(E,B)=>{this._msectl.appendInitSegment(B)}),this._transmuxer.on(_t.MEDIA_SEGMENT,(E,B)=>{if(this._msectl.appendMediaSegment(B),this._config.lazyLoad&&!this._config.isLive){let N=this._mediaElement.currentTime;B.info.endDts>=(N+this._config.lazyLoadMaxDuration)*1e3&&this._progressChecker==null&&(P.v(this.TAG,"Maximum buffering duration exceeded, suspend transmuxing task"),this._suspendTransmuxer())}}),this._transmuxer.on(_t.LOADING_COMPLETE,()=>{this._msectl.endOfStream(),this._emitter.emit(me.LOADING_COMPLETE)}),this._transmuxer.on(_t.RECOVERED_EARLY_EOF,()=>{this._emitter.emit(me.RECOVERED_EARLY_EOF)}),this._transmuxer.on(_t.IO_ERROR,(E,B)=>{this._emitter.emit(me.ERROR,Yt.NETWORK_ERROR,E,B)}),this._transmuxer.on(_t.DEMUX_ERROR,(E,B)=>{this._emitter.emit(me.ERROR,Yt.MEDIA_ERROR,E,{code:-1,msg:B})}),this._transmuxer.on(_t.MEDIA_INFO,E=>{this._mediaInfo=E,this._emitter.emit(me.MEDIA_INFO,Object.assign({},E))}),this._transmuxer.on(_t.METADATA_ARRIVED,E=>{this._emitter.emit(me.METADATA_ARRIVED,E)}),this._transmuxer.on(_t.SCRIPTDATA_ARRIVED,E=>{this._emitter.emit(me.SCRIPTDATA_ARRIVED,E)}),this._transmuxer.on(_t.STATISTICS_INFO,E=>{this._statisticsInfo=this._fillStatisticsInfo(E),this._emitter.emit(me.STATISTICS_INFO,Object.assign({},this._statisticsInfo))}),this._transmuxer.on(_t.RECOMMEND_SEEKPOINT,E=>{this._mediaElement&&!this._config.accurateSeek&&(this._requestSetTime=!0,this._mediaElement.currentTime=E/1e3)}),this._transmuxer.open()}}unload(){this._mediaElement&&this._mediaElement.pause(),this._msectl&&this._msectl.seek(0),this._transmuxer&&(this._transmuxer.close(),this._transmuxer.destroy(),this._transmuxer=null)}play(){return this._mediaElement.play()}pause(){this._mediaElement.pause()}get type(){return this._type}get buffered(){return this._mediaElement.buffered}get duration(){return this._mediaElement.duration}get volume(){return this._mediaElement.volume}set volume(E){this._mediaElement.volume=E}get muted(){return this._mediaElement.muted}set muted(E){this._mediaElement.muted=E}get currentTime(){return this._mediaElement?this._mediaElement.currentTime:0}set currentTime(E){this._mediaElement?this._internalSeek(E):this._pendingSeekTime=E}get mediaInfo(){return Object.assign({},this._mediaInfo)}get statisticsInfo(){return this._statisticsInfo==null&&(this._statisticsInfo={}),this._statisticsInfo=this._fillStatisticsInfo(this._statisticsInfo),Object.assign({},this._statisticsInfo)}_fillStatisticsInfo(E){if(E.playerType=this._type,!(this._mediaElement instanceof HTMLVideoElement))return E;let B=!0,N=0,V=0;if(this._mediaElement.getVideoPlaybackQuality){let q=this._mediaElement.getVideoPlaybackQuality();N=q.totalVideoFrames,V=q.droppedVideoFrames}else this._mediaElement.webkitDecodedFrameCount!=null?(N=this._mediaElement.webkitDecodedFrameCount,V=this._mediaElement.webkitDroppedFrameCount):B=!1;return B&&(E.decodedFrames=N,E.droppedFrames=V),E}_onmseUpdateEnd(){if(!this._config.lazyLoad||this._config.isLive)return;let E=this._mediaElement.buffered,B=this._mediaElement.currentTime,N=0,V=0;for(let q=0;q<E.length;q++){let ue=E.start(q),ce=E.end(q);if(ue<=B&&B<ce){N=ue,V=ce;break}}V>=B+this._config.lazyLoadMaxDuration&&this._progressChecker==null&&(P.v(this.TAG,"Maximum buffering duration exceeded, suspend transmuxing task"),this._suspendTransmuxer())}_onmseBufferFull(){P.v(this.TAG,"MSE SourceBuffer is full, suspend transmuxing task"),this._progressChecker==null&&this._suspendTransmuxer()}_suspendTransmuxer(){this._transmuxer&&(this._transmuxer.pause(),this._progressChecker==null&&(this._progressChecker=window.setInterval(this._checkProgressAndResume.bind(this),1e3)))}_checkProgressAndResume(){let E=this._mediaElement.currentTime,B=this._mediaElement.buffered,N=!1;for(let V=0;V<B.length;V++){let q=B.start(V),ue=B.end(V);if(E>=q&&E<ue){E>=ue-this._config.lazyLoadRecoverDuration&&(N=!0);break}}N&&(window.clearInterval(this._progressChecker),this._progressChecker=null,N&&(P.v(this.TAG,"Continue loading from paused position"),this._transmuxer.resume()))}_isTimepointBuffered(E){let B=this._mediaElement.buffered;for(let N=0;N<B.length;N++){let V=B.start(N),q=B.end(N);if(E>=V&&E<q)return!0}return!1}_internalSeek(E){let B=this._isTimepointBuffered(E),N=!1,V=0;if(E<1&&this._mediaElement.buffered.length>0){let q=this._mediaElement.buffered.start(0);(q<1&&E<q||S.safari)&&(N=!0,V=S.safari?.1:q)}if(N)this._requestSetTime=!0,this._mediaElement.currentTime=V;else if(B){if(!this._alwaysSeekKeyframe)this._requestSetTime=!0,this._mediaElement.currentTime=E;else{let q=this._msectl.getNearestKeyframe(Math.floor(E*1e3));this._requestSetTime=!0,q!=null?this._mediaElement.currentTime=q.dts/1e3:this._mediaElement.currentTime=E}this._progressChecker!=null&&this._checkProgressAndResume()}else this._progressChecker!=null&&(window.clearInterval(this._progressChecker),this._progressChecker=null),this._msectl.seek(E),this._transmuxer.seek(Math.floor(E*1e3)),this._config.accurateSeek&&(this._requestSetTime=!0,this._mediaElement.currentTime=E)}_checkAndApplyUnbufferedSeekpoint(){if(this._seekpointRecord)if(this._seekpointRecord.recordTime<=this._now()-100){let E=this._mediaElement.currentTime;this._seekpointRecord=null,this._isTimepointBuffered(E)||(this._progressChecker!=null&&(window.clearTimeout(this._progressChecker),this._progressChecker=null),this._msectl.seek(E),this._transmuxer.seek(Math.floor(E*1e3)),this._config.accurateSeek&&(this._requestSetTime=!0,this._mediaElement.currentTime=E))}else window.setTimeout(this._checkAndApplyUnbufferedSeekpoint.bind(this),50)}_checkAndResumeStuckPlayback(E){let B=this._mediaElement;if(E||!this._receivedCanPlay||B.readyState<2){let N=B.buffered;N.length>0&&B.currentTime<N.start(0)&&(P.w(this.TAG,`Playback seems stuck at ${B.currentTime}, seek to ${N.start(0)}`),this._requestSetTime=!0,this._mediaElement.currentTime=N.start(0),this._mediaElement.removeEventListener("progress",this.e.onvProgress))}else this._mediaElement.removeEventListener("progress",this.e.onvProgress)}_onvLoadedMetadata(E){this._pendingSeekTime!=null&&(this._mediaElement.currentTime=this._pendingSeekTime,this._pendingSeekTime=null)}_onvSeeking(E){let B=this._mediaElement.currentTime,N=this._mediaElement.buffered;if(this._requestSetTime){this._requestSetTime=!1;return}if(B<1&&N.length>0){let V=N.start(0);if(V<1&&B<V||S.safari){this._requestSetTime=!0,this._mediaElement.currentTime=S.safari?.1:V;return}}if(this._isTimepointBuffered(B)){if(this._alwaysSeekKeyframe){let V=this._msectl.getNearestKeyframe(Math.floor(B*1e3));V!=null&&(this._requestSetTime=!0,this._mediaElement.currentTime=V.dts/1e3)}this._progressChecker!=null&&this._checkProgressAndResume();return}this._seekpointRecord={seekPoint:B,recordTime:this._now()},window.setTimeout(this._checkAndApplyUnbufferedSeekpoint.bind(this),50)}_onvCanPlay(E){this._receivedCanPlay=!0,this._mediaElement.removeEventListener("canplay",this.e.onvCanPlay)}_onvStalled(E){this._checkAndResumeStuckPlayback(!0)}_onvProgress(E){this._checkAndResumeStuckPlayback()}}var bn=Ht;class Sn{constructor(E,B){if(this.TAG="NativePlayer",this._type="NativePlayer",this._emitter=new(b()),this._config=ae(),typeof B=="object"&&Object.assign(this._config,B),E.type.toLowerCase()==="flv")throw new g("NativePlayer does't support flv MediaDataSource input!");if(E.hasOwnProperty("segments"))throw new g(`NativePlayer(${E.type}) doesn't support multipart playback!`);this.e={onvLoadedMetadata:this._onvLoadedMetadata.bind(this)},this._pendingSeekTime=null,this._statisticsReporter=null,this._mediaDataSource=E,this._mediaElement=null}destroy(){this._mediaElement&&(this.unload(),this.detachMediaElement()),this.e=null,this._mediaDataSource=null,this._emitter.removeAllListeners(),this._emitter=null}on(E,B){E===me.MEDIA_INFO?this._mediaElement!=null&&this._mediaElement.readyState!==0&&Promise.resolve().then(()=>{this._emitter.emit(me.MEDIA_INFO,this.mediaInfo)}):E===me.STATISTICS_INFO&&this._mediaElement!=null&&this._mediaElement.readyState!==0&&Promise.resolve().then(()=>{this._emitter.emit(me.STATISTICS_INFO,this.statisticsInfo)}),this._emitter.addListener(E,B)}off(E,B){this._emitter.removeListener(E,B)}attachMediaElement(E){if(this._mediaElement=E,E.addEventListener("loadedmetadata",this.e.onvLoadedMetadata),this._pendingSeekTime!=null)try{E.currentTime=this._pendingSeekTime,this._pendingSeekTime=null}catch(B){}}detachMediaElement(){this._mediaElement&&(this._mediaElement.src="",this._mediaElement.removeAttribute("src"),this._mediaElement.removeEventListener("loadedmetadata",this.e.onvLoadedMetadata),this._mediaElement=null),this._statisticsReporter!=null&&(window.clearInterval(this._statisticsReporter),this._statisticsReporter=null)}load(){if(!this._mediaElement)throw new _("HTMLMediaElement must be attached before load()!");this._mediaElement.src=this._mediaDataSource.url,this._mediaElement.readyState>0&&(this._mediaElement.currentTime=0),this._mediaElement.preload="auto",this._mediaElement.load(),this._statisticsReporter=window.setInterval(this._reportStatisticsInfo.bind(this),this._config.statisticsInfoReportInterval)}unload(){this._mediaElement&&(this._mediaElement.src="",this._mediaElement.removeAttribute("src")),this._statisticsReporter!=null&&(window.clearInterval(this._statisticsReporter),this._statisticsReporter=null)}play(){return this._mediaElement.play()}pause(){this._mediaElement.pause()}get type(){return this._type}get buffered(){return this._mediaElement.buffered}get duration(){return this._mediaElement.duration}get volume(){return this._mediaElement.volume}set volume(E){this._mediaElement.volume=E}get muted(){return this._mediaElement.muted}set muted(E){this._mediaElement.muted=E}get currentTime(){return this._mediaElement?this._mediaElement.currentTime:0}set currentTime(E){this._mediaElement?this._mediaElement.currentTime=E:this._pendingSeekTime=E}get mediaInfo(){let B={mimeType:(this._mediaElement instanceof HTMLAudioElement?"audio/":"video/")+this._mediaDataSource.type};return this._mediaElement&&(B.duration=Math.floor(this._mediaElement.duration*1e3),this._mediaElement instanceof HTMLVideoElement&&(B.width=this._mediaElement.videoWidth,B.height=this._mediaElement.videoHeight)),B}get statisticsInfo(){let E={playerType:this._type,url:this._mediaDataSource.url};if(!(this._mediaElement instanceof HTMLVideoElement))return E;let B=!0,N=0,V=0;if(this._mediaElement.getVideoPlaybackQuality){let q=this._mediaElement.getVideoPlaybackQuality();N=q.totalVideoFrames,V=q.droppedVideoFrames}else this._mediaElement.webkitDecodedFrameCount!=null?(N=this._mediaElement.webkitDecodedFrameCount,V=this._mediaElement.webkitDroppedFrameCount):B=!1;return B&&(E.decodedFrames=N,E.droppedFrames=V),E}_onvLoadedMetadata(E){this._pendingSeekTime!=null&&(this._mediaElement.currentTime=this._pendingSeekTime,this._pendingSeekTime=null),this._emitter.emit(me.MEDIA_INFO,this.mediaInfo)}_reportStatisticsInfo(){this._emitter.emit(me.STATISTICS_INFO,this.statisticsInfo)}}var Pn=Sn;J.install();function hn(Ee,E){let B=Ee;if(B==null||typeof B!="object")throw new g("MediaDataSource must be an javascript object!");if(!B.hasOwnProperty("type"))throw new g("MediaDataSource must has type field to indicate video file type!");switch(B.type){case"flv":return new bn(B,E);default:return new Pn(B,E)}}function In(){return se.supportMSEH264Playback()}function Un(){return se.getFeatureList()}let 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N=="number"?this.subS(N):this.subM(N)},Ee.prototype.subS=function(N){for(let V=0;V<this.rows;V++)for(let q=0;q<this.columns;q++)this.set(V,q,this.get(V,q)-N);return this},Ee.prototype.subM=function(N){if(N=E.checkMatrix(N),this.rows!==N.rows||this.columns!==N.columns)throw new RangeError("Matrices dimensions must be equal");for(let V=0;V<this.rows;V++)for(let q=0;q<this.columns;q++)this.set(V,q,this.get(V,q)-N.get(V,q));return this},Ee.sub=function(N,V){return new E(N).sub(V)},Ee.prototype.subtract=Ee.prototype.sub,Ee.prototype.subtractS=Ee.prototype.subS,Ee.prototype.subtractM=Ee.prototype.subM,Ee.subtract=Ee.sub,Ee.prototype.mul=function(N){return typeof N=="number"?this.mulS(N):this.mulM(N)},Ee.prototype.mulS=function(N){for(let V=0;V<this.rows;V++)for(let q=0;q<this.columns;q++)this.set(V,q,this.get(V,q)*N);return this},Ee.prototype.mulM=function(N){if(N=E.checkMatrix(N),this.rows!==N.rows||this.columns!==N.columns)throw new RangeError("Matrices dimensions must be equal");for(let 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q}static randInt(E,B,N={}){if(typeof N!="object")throw new TypeError("options must be an object");const{min:V=0,max:q=1e3,random:ue=Math.random}=N;if(!Number.isInteger(V))throw new TypeError("min must be an integer");if(!Number.isInteger(q))throw new TypeError("max must be an integer");if(V>=q)throw new RangeError("min must be smaller than max");let ce=q-V,Oe=new be(E,B);for(let Se=0;Se<E;Se++)for(let Ue=0;Ue<B;Ue++){let je=V+Math.round(ue()*ce);Oe.set(Se,Ue,je)}return Oe}static eye(E,B,N){B===void 0&&(B=E),N===void 0&&(N=1);let V=Math.min(E,B),q=this.zeros(E,B);for(let ue=0;ue<V;ue++)q.set(ue,ue,N);return q}static diag(E,B,N){let V=E.length;B===void 0&&(B=V),N===void 0&&(N=B);let q=Math.min(V,B,N),ue=this.zeros(B,N);for(let ce=0;ce<q;ce++)ue.set(ce,ce,E[ce]);return ue}static min(E,B){E=this.checkMatrix(E),B=this.checkMatrix(B);let N=E.rows,V=E.columns,q=new be(N,V);for(let ue=0;ue<N;ue++)for(let ce=0;ce<V;ce++)q.set(ue,ce,Math.min(E.get(ue,ce),B.get(ue,ce)));return q}static max(E,B){E=this.checkMatrix(E),B=this.checkMatrix(B);let N=E.rows,V=E.columns,q=new this(N,V);for(let ue=0;ue<N;ue++)for(let ce=0;ce<V;ce++)q.set(ue,ce,Math.max(E.get(ue,ce),B.get(ue,ce)));return q}static checkMatrix(E){return Ze.isMatrix(E)?E:new be(E)}static isMatrix(E){return E!=null&&E.klass==="Matrix"}get size(){return this.rows*this.columns}apply(E){if(typeof E!="function")throw new TypeError("callback must be a function");for(let B=0;B<this.rows;B++)for(let N=0;N<this.columns;N++)E.call(this,B,N);return this}to1DArray(){let E=[];for(let B=0;B<this.rows;B++)for(let N=0;N<this.columns;N++)E.push(this.get(B,N));return E}to2DArray(){let E=[];for(let B=0;B<this.rows;B++){E.push([]);for(let N=0;N<this.columns;N++)E[B].push(this.get(B,N))}return E}toJSON(){return this.to2DArray()}isRowVector(){return this.rows===1}isColumnVector(){return this.columns===1}isVector(){return this.rows===1||this.columns===1}isSquare(){return this.rows===this.columns}isEmpty(){return this.rows===0||this.columns===0}isSymmetric(){if(this.isSquare()){for(let E=0;E<this.rows;E++)for(let B=0;B<=E;B++)if(this.get(E,B)!==this.get(B,E))return!1;return!0}return!1}isDistance(){if(!this.isSymmetric())return!1;for(let E=0;E<this.rows;E++)if(this.get(E,E)!==0)return!1;return!0}isEchelonForm(){let E=0,B=0,N=-1,V=!0,q=!1;for(;E<this.rows&&V;){for(B=0,q=!1;B<this.columns&&q===!1;)this.get(E,B)===0?B++:this.get(E,B)===1&&B>N?(q=!0,N=B):(V=!1,q=!0);E++}return V}isReducedEchelonForm(){let E=0,B=0,N=-1,V=!0,q=!1;for(;E<this.rows&&V;){for(B=0,q=!1;B<this.columns&&q===!1;)this.get(E,B)===0?B++:this.get(E,B)===1&&B>N?(q=!0,N=B):(V=!1,q=!0);for(let ue=B+1;ue<this.rows;ue++)this.get(E,ue)!==0&&(V=!1);E++}return V}echelonForm(){let E=this.clone(),B=0,N=0;for(;B<E.rows&&N<E.columns;){let V=B;for(let q=B;q<E.rows;q++)E.get(q,N)>E.get(V,N)&&(V=q);if(E.get(V,N)===0)N++;else{E.swapRows(B,V);let q=E.get(B,N);for(let ue=N;ue<E.columns;ue++)E.set(B,ue,E.get(B,ue)/q);for(let ue=B+1;ue<E.rows;ue++){let ce=E.get(ue,N)/E.get(B,N);E.set(ue,N,0);for(let Oe=N+1;Oe<E.columns;Oe++)E.set(ue,Oe,E.get(ue,Oe)-E.get(B,Oe)*ce)}B++,N++}}return E}reducedEchelonForm(){let E=this.echelonForm(),B=E.columns,N=E.rows,V=N-1;for(;V>=0;)if(E.maxRow(V)===0)V--;else{let q=0,ue=!1;for(;q<N&&ue===!1;)E.get(V,q)===1?ue=!0:q++;for(let ce=0;ce<V;ce++){let Oe=E.get(ce,q);for(let Se=q;Se<B;Se++){let Ue=E.get(ce,Se)-Oe*E.get(V,Se);E.set(ce,Se,Ue)}}V--}return E}set(){throw new Error("set method is unimplemented")}get(){throw new Error("get method is unimplemented")}repeat(E={}){if(typeof E!="object")throw new TypeError("options must be an object");const{rows:B=1,columns:N=1}=E;if(!Number.isInteger(B)||B<=0)throw new TypeError("rows must be a positive integer");if(!Number.isInteger(N)||N<=0)throw new TypeError("columns must be a positive integer");let V=new be(this.rows*B,this.columns*N);for(let q=0;q<B;q++)for(let ue=0;ue<N;ue++)V.setSubMatrix(this,this.rows*q,this.columns*ue);return V}fill(E){for(let B=0;B<this.rows;B++)for(let N=0;N<this.columns;N++)this.set(B,N,E);return this}neg(){return this.mulS(-1)}getRow(E){I(this,E);let B=[];for(let N=0;N<this.columns;N++)B.push(this.get(E,N));return B}getRowVector(E){return be.rowVector(this.getRow(E))}setRow(E,B){I(this,E),B=F(this,B);for(let N=0;N<this.columns;N++)this.set(E,N,B[N]);return this}swapRows(E,B){I(this,E),I(this,B);for(let N=0;N<this.columns;N++){let V=this.get(E,N);this.set(E,N,this.get(B,N)),this.set(B,N,V)}return this}getColumn(E){U(this,E);let B=[];for(let N=0;N<this.rows;N++)B.push(this.get(N,E));return B}getColumnVector(E){return be.columnVector(this.getColumn(E))}setColumn(E,B){U(this,E),B=G(this,B);for(let N=0;N<this.rows;N++)this.set(N,E,B[N]);return this}swapColumns(E,B){U(this,E),U(this,B);for(let N=0;N<this.rows;N++){let V=this.get(N,E);this.set(N,E,this.get(N,B)),this.set(N,B,V)}return this}addRowVector(E){E=F(this,E);for(let B=0;B<this.rows;B++)for(let N=0;N<this.columns;N++)this.set(B,N,this.get(B,N)+E[N]);return this}subRowVector(E){E=F(this,E);for(let B=0;B<this.rows;B++)for(let N=0;N<this.columns;N++)this.set(B,N,this.get(B,N)-E[N]);return this}mulRowVector(E){E=F(this,E);for(let B=0;B<this.rows;B++)for(let N=0;N<this.columns;N++)this.set(B,N,this.get(B,N)*E[N]);return this}divRowVector(E){E=F(this,E);for(let B=0;B<this.rows;B++)for(let N=0;N<this.columns;N++)this.set(B,N,this.get(B,N)/E[N]);return this}addColumnVector(E){E=G(this,E);for(let B=0;B<this.rows;B++)for(let N=0;N<this.columns;N++)this.set(B,N,this.get(B,N)+E[B]);return this}subColumnVector(E){E=G(this,E);for(let B=0;B<this.rows;B++)for(let N=0;N<this.columns;N++)this.set(B,N,this.get(B,N)-E[B]);return this}mulColumnVector(E){E=G(this,E);for(let B=0;B<this.rows;B++)for(let N=0;N<this.columns;N++)this.set(B,N,this.get(B,N)*E[B]);return this}divColumnVector(E){E=G(this,E);for(let B=0;B<this.rows;B++)for(let N=0;N<this.columns;N++)this.set(B,N,this.get(B,N)/E[B]);return this}mulRow(E,B){I(this,E);for(let N=0;N<this.columns;N++)this.set(E,N,this.get(E,N)*B);return this}mulColumn(E,B){U(this,E);for(let N=0;N<this.rows;N++)this.set(N,E,this.get(N,E)*B);return this}max(E){if(this.isEmpty())return NaN;switch(E){case"row":{const B=new Array(this.rows).fill(Number.NEGATIVE_INFINITY);for(let N=0;N<this.rows;N++)for(let V=0;V<this.columns;V++)this.get(N,V)>B[N]&&(B[N]=this.get(N,V));return B}case"column":{const B=new Array(this.columns).fill(Number.NEGATIVE_INFINITY);for(let N=0;N<this.rows;N++)for(let V=0;V<this.columns;V++)this.get(N,V)>B[V]&&(B[V]=this.get(N,V));return B}case void 0:{let B=this.get(0,0);for(let N=0;N<this.rows;N++)for(let V=0;V<this.columns;V++)this.get(N,V)>B&&(B=this.get(N,V));return B}default:throw new Error(`invalid option: ${E}`)}}maxIndex(){ne(this);let E=this.get(0,0),B=[0,0];for(let N=0;N<this.rows;N++)for(let V=0;V<this.columns;V++)this.get(N,V)>E&&(E=this.get(N,V),B[0]=N,B[1]=V);return B}min(E){if(this.isEmpty())return NaN;switch(E){case"row":{const B=new Array(this.rows).fill(Number.POSITIVE_INFINITY);for(let N=0;N<this.rows;N++)for(let V=0;V<this.columns;V++)this.get(N,V)<B[N]&&(B[N]=this.get(N,V));return B}case"column":{const B=new Array(this.columns).fill(Number.POSITIVE_INFINITY);for(let N=0;N<this.rows;N++)for(let V=0;V<this.columns;V++)this.get(N,V)<B[V]&&(B[V]=this.get(N,V));return B}case void 0:{let B=this.get(0,0);for(let N=0;N<this.rows;N++)for(let V=0;V<this.columns;V++)this.get(N,V)<B&&(B=this.get(N,V));return B}default:throw new Error(`invalid option: ${E}`)}}minIndex(){ne(this);let E=this.get(0,0),B=[0,0];for(let N=0;N<this.rows;N++)for(let V=0;V<this.columns;V++)this.get(N,V)<E&&(E=this.get(N,V),B[0]=N,B[1]=V);return B}maxRow(E){if(I(this,E),this.isEmpty())return NaN;let B=this.get(E,0);for(let N=1;N<this.columns;N++)this.get(E,N)>B&&(B=this.get(E,N));return B}maxRowIndex(E){I(this,E),ne(this);let B=this.get(E,0),N=[E,0];for(let V=1;V<this.columns;V++)this.get(E,V)>B&&(B=this.get(E,V),N[1]=V);return N}minRow(E){if(I(this,E),this.isEmpty())return NaN;let B=this.get(E,0);for(let N=1;N<this.columns;N++)this.get(E,N)<B&&(B=this.get(E,N));return B}minRowIndex(E){I(this,E),ne(this);let B=this.get(E,0),N=[E,0];for(let V=1;V<this.columns;V++)this.get(E,V)<B&&(B=this.get(E,V),N[1]=V);return N}maxColumn(E){if(U(this,E),this.isEmpty())return NaN;let B=this.get(0,E);for(let N=1;N<this.rows;N++)this.get(N,E)>B&&(B=this.get(N,E));return B}maxColumnIndex(E){U(this,E),ne(this);let B=this.get(0,E),N=[0,E];for(let V=1;V<this.rows;V++)this.get(V,E)>B&&(B=this.get(V,E),N[0]=V);return N}minColumn(E){if(U(this,E),this.isEmpty())return NaN;let B=this.get(0,E);for(let N=1;N<this.rows;N++)this.get(N,E)<B&&(B=this.get(N,E));return B}minColumnIndex(E){U(this,E),ne(this);let B=this.get(0,E),N=[0,E];for(let V=1;V<this.rows;V++)this.get(V,E)<B&&(B=this.get(V,E),N[0]=V);return N}diag(){let E=Math.min(this.rows,this.columns),B=[];for(let N=0;N<E;N++)B.push(this.get(N,N));return B}norm(E="frobenius"){switch(E){case"max":return this.max();case"frobenius":return Math.sqrt(this.dot(this));default:throw new RangeError(`unknown norm type: ${E}`)}}cumulativeSum(){let E=0;for(let B=0;B<this.rows;B++)for(let N=0;N<this.columns;N++)E+=this.get(B,N),this.set(B,N,E);return this}dot(E){Ze.isMatrix(E)&&(E=E.to1DArray());let B=this.to1DArray();if(B.length!==E.length)throw new RangeError("vectors do not have the same size");let N=0;for(let V=0;V<B.length;V++)N+=B[V]*E[V];return N}mmul(E){E=be.checkMatrix(E);let B=this.rows,N=this.columns,V=E.columns,q=new be(B,V),ue=new Float64Array(N);for(let ce=0;ce<V;ce++){for(let Oe=0;Oe<N;Oe++)ue[Oe]=E.get(Oe,ce);for(let Oe=0;Oe<B;Oe++){let Se=0;for(let Ue=0;Ue<N;Ue++)Se+=this.get(Oe,Ue)*ue[Ue];q.set(Oe,ce,Se)}}return q}mpow(E){if(!this.isSquare())throw new RangeError("Matrix must be square");if(!Number.isInteger(E)||E<0)throw new RangeError("Exponent must be a non-negative integer");let B=be.eye(this.rows),N=this;for(let V=E;V>1;V/=2)V&1&&(B=B.mmul(N)),N=N.mmul(N);return B}strassen2x2(E){E=be.checkMatrix(E);let B=new be(2,2);const N=this.get(0,0),V=E.get(0,0),q=this.get(0,1),ue=E.get(0,1),ce=this.get(1,0),Oe=E.get(1,0),Se=this.get(1,1),Ue=E.get(1,1),je=(N+Se)*(V+Ue),it=(ce+Se)*V,at=N*(ue-Ue),et=Se*(Oe-V),st=(N+q)*Ue,Je=(ce-N)*(V+ue),ke=(q-Se)*(Oe+Ue),ft=je+et-st+ke,yt=at+st,Pt=it+et,Ut=je-it+at+Je;return B.set(0,0,ft),B.set(0,1,yt),B.set(1,0,Pt),B.set(1,1,Ut),B}strassen3x3(E){E=be.checkMatrix(E);let B=new be(3,3);const N=this.get(0,0),V=this.get(0,1),q=this.get(0,2),ue=this.get(1,0),ce=this.get(1,1),Oe=this.get(1,2),Se=this.get(2,0),Ue=this.get(2,1),je=this.get(2,2),it=E.get(0,0),at=E.get(0,1),et=E.get(0,2),st=E.get(1,0),Je=E.get(1,1),ke=E.get(1,2),ft=E.get(2,0),yt=E.get(2,1),Pt=E.get(2,2),Ut=(N+V+q-ue-ce-Ue-je)*Je,Qt=(N-ue)*(-at+Je),Ct=ce*(-it+at+st-Je-ke-ft+Pt),It=(-N+ue+ce)*(it-at+Je),Zt=(ue+ce)*(-it+at),lt=N*it,Mt=(-N+Se+Ue)*(it-et+ke),Lt=(-N+Se)*(et-ke),Nt=(Se+Ue)*(-it+et),Vt=(N+V+q-ce-Oe-Se-Ue)*ke,Kt=Ue*(-it+et+st-Je-ke-ft+yt),qt=(-q+Ue+je)*(Je+ft-yt),ln=(q-je)*(Je-yt),pn=q*ft,mn=(Ue+je)*(-ft+yt),yn=(-q+ce+Oe)*(ke+ft-Pt),Zn=(q-Oe)*(ke-Pt),Nn=(ce+Oe)*(-ft+Pt),nn=V*st,Ln=Oe*yt,Bn=ue*et,lr=Se*at,qn=je*Pt,Hr=lt+pn+nn,hi=Ut+It+Zt+lt+qt+pn+mn,cr=lt+Mt+Nt+Vt+pn+yn+Nn,fi=Qt+Ct+It+lt+pn+yn+Zn,Hi=Qt+It+Zt+lt+Ln,Kn=pn+yn+Zn+Nn+Bn,Dn=lt+Mt+Lt+Kt+qt+ln+pn,Qn=qt+ln+pn+mn+lr,ur=lt+Mt+Lt+Nt+qn;return B.set(0,0,Hr),B.set(0,1,hi),B.set(0,2,cr),B.set(1,0,fi),B.set(1,1,Hi),B.set(1,2,Kn),B.set(2,0,Dn),B.set(2,1,Qn),B.set(2,2,ur),B}mmulStrassen(E){E=be.checkMatrix(E);let B=this.clone(),N=B.rows,V=B.columns,q=E.rows,ue=E.columns;V!==q&&console.warn(`Multiplying ${N} x ${V} and ${q} x ${ue} matrix: dimensions do not match.`);function ce(je,it,at){let et=je.rows,st=je.columns;if(et===it&&st===at)return je;{let Je=Ze.zeros(it,at);return Je=Je.setSubMatrix(je,0,0),Je}}let Oe=Math.max(N,q),Se=Math.max(V,ue);B=ce(B,Oe,Se),E=ce(E,Oe,Se);function Ue(je,it,at,et){if(at<=512||et<=512)return je.mmul(it);at%2===1&&et%2===1?(je=ce(je,at+1,et+1),it=ce(it,at+1,et+1)):at%2===1?(je=ce(je,at+1,et),it=ce(it,at+1,et)):et%2===1&&(je=ce(je,at,et+1),it=ce(it,at,et+1));let st=parseInt(je.rows/2,10),Je=parseInt(je.columns/2,10),ke=je.subMatrix(0,st-1,0,Je-1),ft=it.subMatrix(0,st-1,0,Je-1),yt=je.subMatrix(0,st-1,Je,je.columns-1),Pt=it.subMatrix(0,st-1,Je,it.columns-1),Ut=je.subMatrix(st,je.rows-1,0,Je-1),Qt=it.subMatrix(st,it.rows-1,0,Je-1),Ct=je.subMatrix(st,je.rows-1,Je,je.columns-1),It=it.subMatrix(st,it.rows-1,Je,it.columns-1),Zt=Ue(Ze.add(ke,Ct),Ze.add(ft,It),st,Je),lt=Ue(Ze.add(Ut,Ct),ft,st,Je),Mt=Ue(ke,Ze.sub(Pt,It),st,Je),Lt=Ue(Ct,Ze.sub(Qt,ft),st,Je),Nt=Ue(Ze.add(ke,yt),It,st,Je),Vt=Ue(Ze.sub(Ut,ke),Ze.add(ft,Pt),st,Je),Kt=Ue(Ze.sub(yt,Ct),Ze.add(Qt,It),st,Je),qt=Ze.add(Zt,Lt);qt.sub(Nt),qt.add(Kt);let ln=Ze.add(Mt,Nt),pn=Ze.add(lt,Lt),mn=Ze.sub(Zt,lt);mn.add(Mt),mn.add(Vt);let yn=Ze.zeros(2*qt.rows,2*qt.columns);return yn=yn.setSubMatrix(qt,0,0),yn=yn.setSubMatrix(ln,qt.rows,0),yn=yn.setSubMatrix(pn,0,qt.columns),yn=yn.setSubMatrix(mn,qt.rows,qt.columns),yn.subMatrix(0,at-1,0,et-1)}return Ue(B,E,Oe,Se)}scaleRows(E={}){if(typeof E!="object")throw new TypeError("options must be an object");const{min:B=0,max:N=1}=E;if(!Number.isFinite(B))throw new TypeError("min must be a number");if(!Number.isFinite(N))throw new TypeError("max must be a number");if(B>=N)throw new RangeError("min must be smaller than max");let V=new be(this.rows,this.columns);for(let q=0;q<this.rows;q++){const ue=this.getRow(q);ue.length>0&&M(ue,{min:B,max:N,output:ue}),V.setRow(q,ue)}return V}scaleColumns(E={}){if(typeof E!="object")throw new TypeError("options must be an object");const{min:B=0,max:N=1}=E;if(!Number.isFinite(B))throw new TypeError("min must be a number");if(!Number.isFinite(N))throw new TypeError("max must be a number");if(B>=N)throw new RangeError("min must be smaller than max");let V=new be(this.rows,this.columns);for(let q=0;q<this.columns;q++){const ue=this.getColumn(q);ue.length&&M(ue,{min:B,max:N,output:ue}),V.setColumn(q,ue)}return V}flipRows(){const E=Math.ceil(this.columns/2);for(let B=0;B<this.rows;B++)for(let N=0;N<E;N++){let V=this.get(B,N),q=this.get(B,this.columns-1-N);this.set(B,N,q),this.set(B,this.columns-1-N,V)}return this}flipColumns(){const E=Math.ceil(this.rows/2);for(let B=0;B<this.columns;B++)for(let N=0;N<E;N++){let V=this.get(N,B),q=this.get(this.rows-1-N,B);this.set(N,B,q),this.set(this.rows-1-N,B,V)}return this}kroneckerProduct(E){E=be.checkMatrix(E);let B=this.rows,N=this.columns,V=E.rows,q=E.columns,ue=new be(B*V,N*q);for(let ce=0;ce<B;ce++)for(let Oe=0;Oe<N;Oe++)for(let Se=0;Se<V;Se++)for(let Ue=0;Ue<q;Ue++)ue.set(V*ce+Se,q*Oe+Ue,this.get(ce,Oe)*E.get(Se,Ue));return ue}kroneckerSum(E){if(E=be.checkMatrix(E),!this.isSquare()||!E.isSquare())throw new Error("Kronecker Sum needs two Square Matrices");let B=this.rows,N=E.rows,V=this.kroneckerProduct(be.eye(N,N)),q=be.eye(B,B).kroneckerProduct(E);return V.add(q)}transpose(){let E=new be(this.columns,this.rows);for(let B=0;B<this.rows;B++)for(let N=0;N<this.columns;N++)E.set(N,B,this.get(B,N));return E}sortRows(E=Ve){for(let B=0;B<this.rows;B++)this.setRow(B,this.getRow(B).sort(E));return this}sortColumns(E=Ve){for(let B=0;B<this.columns;B++)this.setColumn(B,this.getColumn(B).sort(E));return this}subMatrix(E,B,N,V){$(this,E,B,N,V);let q=new be(B-E+1,V-N+1);for(let ue=E;ue<=B;ue++)for(let ce=N;ce<=V;ce++)q.set(ue-E,ce-N,this.get(ue,ce));return q}subMatrixRow(E,B,N){if(B===void 0&&(B=0),N===void 0&&(N=this.columns-1),B>N||B<0||B>=this.columns||N<0||N>=this.columns)throw new RangeError("Argument out of range");let V=new be(E.length,N-B+1);for(let q=0;q<E.length;q++)for(let ue=B;ue<=N;ue++){if(E[q]<0||E[q]>=this.rows)throw new RangeError(`Row index out of range: ${E[q]}`);V.set(q,ue-B,this.get(E[q],ue))}return V}subMatrixColumn(E,B,N){if(B===void 0&&(B=0),N===void 0&&(N=this.rows-1),B>N||B<0||B>=this.rows||N<0||N>=this.rows)throw new RangeError("Argument out of range");let V=new be(N-B+1,E.length);for(let q=0;q<E.length;q++)for(let ue=B;ue<=N;ue++){if(E[q]<0||E[q]>=this.columns)throw new RangeError(`Column index out of range: ${E[q]}`);V.set(ue-B,q,this.get(ue,E[q]))}return V}setSubMatrix(E,B,N){if(E=be.checkMatrix(E),E.isEmpty())return this;let V=B+E.rows-1,q=N+E.columns-1;$(this,B,V,N,q);for(let ue=0;ue<E.rows;ue++)for(let ce=0;ce<E.columns;ce++)this.set(B+ue,N+ce,E.get(ue,ce));return this}selection(E,B){Y(this,E),te(this,B);let N=new be(E.length,B.length);for(let V=0;V<E.length;V++){let q=E[V];for(let ue=0;ue<B.length;ue++){let ce=B[ue];N.set(V,ue,this.get(q,ce))}}return N}trace(){let E=Math.min(this.rows,this.columns),B=0;for(let N=0;N<E;N++)B+=this.get(N,N);return B}clone(){return this.constructor.copy(this,new be(this.rows,this.columns))}static copy(E,B){for(const[N,V,q]of E.entries())B.set(N,V,q);return B}sum(E){switch(E){case"row":return le(this);case"column":return ae(this);case void 0:return de(this);default:throw new Error(`invalid option: ${E}`)}}product(E){switch(E){case"row":return se(this);case"column":return fe(this);case void 0:return me(this);default:throw new Error(`invalid option: ${E}`)}}mean(E){const B=this.sum(E);switch(E){case"row":{for(let N=0;N<this.rows;N++)B[N]/=this.columns;return B}case"column":{for(let N=0;N<this.columns;N++)B[N]/=this.rows;return B}case void 0:return B/this.size;default:throw new Error(`invalid option: ${E}`)}}variance(E,B={}){if(typeof E=="object"&&(B=E,E=void 0),typeof B!="object")throw new TypeError("options must be an object");const{unbiased:N=!0,mean:V=this.mean(E)}=B;if(typeof N!="boolean")throw new TypeError("unbiased must be a boolean");switch(E){case"row":{if(!v.isAnyArray(V))throw new TypeError("mean must be an array");return ge(this,N,V)}case"column":{if(!v.isAnyArray(V))throw new TypeError("mean must be an array");return xe(this,N,V)}case void 0:{if(typeof V!="number")throw new TypeError("mean must be a number");return Me(this,N,V)}default:throw new Error(`invalid option: ${E}`)}}standardDeviation(E,B){typeof E=="object"&&(B=E,E=void 0);const N=this.variance(E,B);if(E===void 0)return Math.sqrt(N);for(let V=0;V<N.length;V++)N[V]=Math.sqrt(N[V]);return N}center(E,B={}){if(typeof E=="object"&&(B=E,E=void 0),typeof B!="object")throw new TypeError("options must be an object");const{center:N=this.mean(E)}=B;switch(E){case"row":{if(!v.isAnyArray(N))throw new TypeError("center must be an array");return Ne(this,N),this}case"column":{if(!v.isAnyArray(N))throw new TypeError("center must be an array");return We(this,N),this}case void 0:{if(typeof N!="number")throw new TypeError("center must be a number");return nt(this,N),this}default:throw new Error(`invalid option: ${E}`)}}scale(E,B={}){if(typeof E=="object"&&(B=E,E=void 0),typeof B!="object")throw new TypeError("options must be an object");let N=B.scale;switch(E){case"row":{if(N===void 0)N=qe(this);else if(!v.isAnyArray(N))throw new TypeError("scale must be an array");return ot(this,N),this}case"column":{if(N===void 0)N=mt(this);else if(!v.isAnyArray(N))throw new TypeError("scale must be an array");return vt(this,N),this}case void 0:{if(N===void 0)N=Ke(this);else if(typeof N!="number")throw new TypeError("scale must be a number");return rt(this,N),this}default:throw new Error(`invalid option: ${E}`)}}toString(E){return R(this,E)}[Symbol.iterator](){return this.entries()}*entries(){for(let E=0;E<this.rows;E++)for(let B=0;B<this.columns;B++)yield[E,B,this.get(E,B)]}*values(){for(let E=0;E<this.rows;E++)for(let B=0;B<this.columns;B++)yield this.get(E,B)}}Ze.prototype.klass="Matrix",typeof Symbol!="undefined"&&(Ze.prototype[Symbol.for("nodejs.util.inspect.custom")]=A);function Ve(Ee,E){return Ee-E}function Pe(Ee){return Ee.every(E=>typeof E=="number")}Ze.random=Ze.rand,Ze.randomInt=Ze.randInt,Ze.diagonal=Ze.diag,Ze.prototype.diagonal=Ze.prototype.diag,Ze.identity=Ze.eye,Ze.prototype.negate=Ze.prototype.neg,Ze.prototype.tensorProduct=Ze.prototype.kroneckerProduct;const He=class w0 extends Ze{constructor(E,B){if(super(),O(this,m),P(this,"data"),w0.isMatrix(E))g(this,m,L).call(this,E.rows,E.columns),w0.copy(E,this);else if(Number.isInteger(E)&&E>=0)g(this,m,L).call(this,E,B);else if(v.isAnyArray(E)){const N=E;if(E=N.length,B=E?N[0].length:0,typeof B!="number")throw new TypeError("Data must be a 2D array with at least one element");this.data=[];for(let V=0;V<E;V++){if(N[V].length!==B)throw new RangeError("Inconsistent array dimensions");if(!Pe(N[V]))throw new TypeError("Input data contains non-numeric values");this.data.push(Float64Array.from(N[V]))}this.rows=E,this.columns=B}else throw new TypeError("First argument must be a positive number or an array")}set(E,B,N){return this.data[E][B]=N,this}get(E,B){return this.data[E][B]}removeRow(E){return I(this,E),this.data.splice(E,1),this.rows-=1,this}addRow(E,B){return B===void 0&&(B=E,E=this.rows),I(this,E,!0),B=Float64Array.from(F(this,B)),this.data.splice(E,0,B),this.rows+=1,this}removeColumn(E){U(this,E);for(let B=0;B<this.rows;B++){const N=new Float64Array(this.columns-1);for(let V=0;V<E;V++)N[V]=this.data[B][V];for(let V=E+1;V<this.columns;V++)N[V-1]=this.data[B][V];this.data[B]=N}return this.columns-=1,this}addColumn(E,B){typeof B=="undefined"&&(B=E,E=this.columns),U(this,E,!0),B=G(this,B);for(let N=0;N<this.rows;N++){const V=new Float64Array(this.columns+1);let q=0;for(;q<E;q++)V[q]=this.data[N][q];for(V[q++]=B[N];q<this.columns+1;q++)V[q]=this.data[N][q-1];this.data[N]=V}return this.columns+=1,this}};m=new WeakSet,L=function(Ee,E){if(this.data=[],Number.isInteger(E)&&E>=0)for(let B=0;B<Ee;B++)this.data.push(new Float64Array(E));else throw new TypeError("nColumns must be a positive integer");this.rows=Ee,this.columns=E};let be=He;D(Ze,be);const Ie=class M0 extends Ze{constructor(E){if(super(),O(this,d),be.isMatrix(E)){if(!E.isSymmetric())throw new TypeError("not symmetric data");_(this,d,be.copy(E,new be(E.rows,E.rows)))}else if(Number.isInteger(E)&&E>=0)_(this,d,new be(E,E));else if(_(this,d,new be(E)),!this.isSymmetric())throw new TypeError("not symmetric data")}get size(){return x(this,d).size}get rows(){return x(this,d).rows}get columns(){return x(this,d).columns}get diagonalSize(){return this.rows}static isSymmetricMatrix(E){return be.isMatrix(E)&&E.klassType==="SymmetricMatrix"}static zeros(E){return new this(E)}static ones(E){return new this(E).fill(1)}clone(){const E=new M0(this.diagonalSize);for(const[B,N,V]of this.upperRightEntries())E.set(B,N,V);return E}toMatrix(){return new be(this)}get(E,B){return x(this,d).get(E,B)}set(E,B,N){return x(this,d).set(E,B,N),x(this,d).set(B,E,N),this}removeCross(E){return x(this,d).removeRow(E),x(this,d).removeColumn(E),this}addCross(E,B){B===void 0&&(B=E,E=this.diagonalSize);const N=B.slice();return N.splice(E,1),x(this,d).addRow(E,N),x(this,d).addColumn(E,B),this}applyMask(E){if(E.length!==this.diagonalSize)throw new RangeError("Mask size do not match with matrix size");const B=[];for(const[N,V]of E.entries())V||B.push(N);B.reverse();for(const N of B)this.removeCross(N);return this}toCompact(){const{diagonalSize:E}=this,B=new Array(E*(E+1)/2);for(let N=0,V=0,q=0;q<B.length;q++)B[q]=this.get(V,N),++N>=E&&(N=++V);return B}static fromCompact(E){const B=E.length,N=(Math.sqrt(8*B+1)-1)/2;if(!Number.isInteger(N))throw new TypeError(`This array is not a compact representation of a Symmetric Matrix, ${JSON.stringify(E)}`);const V=new M0(N);for(let q=0,ue=0,ce=0;ce<B;ce++)V.set(q,ue,E[ce]),++q>=N&&(q=++ue);return V}*upperRightEntries(){for(let E=0,B=0;E<this.diagonalSize;void 0){const N=this.get(E,B);yield[E,B,N],++B>=this.diagonalSize&&(B=++E)}}*upperRightValues(){for(let E=0,B=0;E<this.diagonalSize;void 0)yield this.get(E,B),++B>=this.diagonalSize&&(B=++E)}};d=new WeakMap;let Te=Ie;Te.prototype.klassType="SymmetricMatrix";class Re extends Te{static isDistanceMatrix(E){return Te.isSymmetricMatrix(E)&&E.klassSubType==="DistanceMatrix"}constructor(E){if(super(E),!this.isDistance())throw new TypeError("Provided arguments do no produce a distance matrix")}set(E,B,N){return E===B&&(N=0),super.set(E,B,N)}addCross(E,B){return B===void 0&&(B=E,E=this.diagonalSize),B=B.slice(),B[E]=0,super.addCross(E,B)}toSymmetricMatrix(){return new Te(this)}clone(){const E=new Re(this.diagonalSize);for(const[B,N,V]of this.upperRightEntries())B!==N&&E.set(B,N,V);return E}toCompact(){const{diagonalSize:E}=this,B=(E-1)*E/2,N=new Array(B);for(let V=1,q=0,ue=0;ue<N.length;ue++)N[ue]=this.get(q,V),++V>=E&&(V=++q+1);return N}static fromCompact(E){const B=E.length;if(B===0)return new this(0);const N=(Math.sqrt(8*B+1)+1)/2;if(!Number.isInteger(N))throw new TypeError(`This array is not a compact representation of a DistanceMatrix, ${JSON.stringify(E)}`);const V=new this(N);for(let q=1,ue=0,ce=0;ce<B;ce++)V.set(q,ue,E[ce]),++q>=N&&(q=++ue+1);return V}}Re.prototype.klassSubType="DistanceMatrix";class Ge extends Ze{constructor(E,B,N){super(),this.matrix=E,this.rows=B,this.columns=N}}class Le extends Ge{constructor(E,B){U(E,B),super(E,E.rows,1),this.column=B}set(E,B,N){return this.matrix.set(E,this.column,N),this}get(E){return this.matrix.get(E,this.column)}}class Fe extends Ge{constructor(E,B){te(E,B),super(E,E.rows,B.length),this.columnIndices=B}set(E,B,N){return this.matrix.set(E,this.columnIndices[B],N),this}get(E,B){return this.matrix.get(E,this.columnIndices[B])}}class Qe extends Ge{constructor(E){super(E,E.rows,E.columns)}set(E,B,N){return this.matrix.set(E,this.columns-B-1,N),this}get(E,B){return this.matrix.get(E,this.columns-B-1)}}class tt extends Ge{constructor(E){super(E,E.rows,E.columns)}set(E,B,N){return this.matrix.set(this.rows-E-1,B,N),this}get(E,B){return this.matrix.get(this.rows-E-1,B)}}class dt extends Ge{constructor(E,B){I(E,B),super(E,1,E.columns),this.row=B}set(E,B,N){return this.matrix.set(this.row,B,N),this}get(E,B){return this.matrix.get(this.row,B)}}class pt extends Ge{constructor(E,B){Y(E,B),super(E,B.length,E.columns),this.rowIndices=B}set(E,B,N){return this.matrix.set(this.rowIndices[E],B,N),this}get(E,B){return this.matrix.get(this.rowIndices[E],B)}}class Tt extends Ge{constructor(E,B,N){Y(E,B),te(E,N),super(E,B.length,N.length),this.rowIndices=B,this.columnIndices=N}set(E,B,N){return this.matrix.set(this.rowIndices[E],this.columnIndices[B],N),this}get(E,B){return this.matrix.get(this.rowIndices[E],this.columnIndices[B])}}class At extends Ge{constructor(E,B,N,V,q){$(E,B,N,V,q),super(E,N-B+1,q-V+1),this.startRow=B,this.startColumn=V}set(E,B,N){return this.matrix.set(this.startRow+E,this.startColumn+B,N),this}get(E,B){return this.matrix.get(this.startRow+E,this.startColumn+B)}}class Ye extends Ge{constructor(E){super(E,E.columns,E.rows)}set(E,B,N){return this.matrix.set(B,E,N),this}get(E,B){return this.matrix.get(B,E)}}class ht extends Ze{constructor(E,B={}){const{rows:N=1}=B;if(E.length%N!==0)throw new Error("the data length is not divisible by the number of rows");super(),this.rows=N,this.columns=E.length/N,this.data=E}set(E,B,N){let V=this._calculateIndex(E,B);return this.data[V]=N,this}get(E,B){let N=this._calculateIndex(E,B);return this.data[N]}_calculateIndex(E,B){return E*this.columns+B}}class gt extends Ze{constructor(E){super(),this.data=E,this.rows=E.length,this.columns=E[0].length}set(E,B,N){return this.data[E][B]=N,this}get(E,B){return this.data[E][B]}}function _t(Ee,E){if(v.isAnyArray(Ee))return Ee[0]&&v.isAnyArray(Ee[0])?new gt(Ee):new ht(Ee,E);throw new Error("the argument is not an array")}class Ot{constructor(E){E=gt.checkMatrix(E);let B=E.clone(),N=B.rows,V=B.columns,q=new Float64Array(N),ue=1,ce,Oe,Se,Ue,je,it,at,et,st;for(ce=0;ce<N;ce++)q[ce]=ce;for(et=new Float64Array(N),Oe=0;Oe<V;Oe++){for(ce=0;ce<N;ce++)et[ce]=B.get(ce,Oe);for(ce=0;ce<N;ce++){for(st=Math.min(ce,Oe),je=0,Se=0;Se<st;Se++)je+=B.get(ce,Se)*et[Se];et[ce]-=je,B.set(ce,Oe,et[ce])}for(Ue=Oe,ce=Oe+1;ce<N;ce++)Math.abs(et[ce])>Math.abs(et[Ue])&&(Ue=ce);if(Ue!==Oe){for(Se=0;Se<V;Se++)it=B.get(Ue,Se),B.set(Ue,Se,B.get(Oe,Se)),B.set(Oe,Se,it);at=q[Ue],q[Ue]=q[Oe],q[Oe]=at,ue=-ue}if(Oe<N&&B.get(Oe,Oe)!==0)for(ce=Oe+1;ce<N;ce++)B.set(ce,Oe,B.get(ce,Oe)/B.get(Oe,Oe))}this.LU=B,this.pivotVector=q,this.pivotSign=ue}isSingular(){let E=this.LU,B=E.columns;for(let N=0;N<B;N++)if(E.get(N,N)===0)return!0;return!1}solve(E){E=be.checkMatrix(E);let B=this.LU;if(B.rows!==E.rows)throw new Error("Invalid matrix dimensions");if(this.isSingular())throw new Error("LU matrix is singular");let V=E.columns,q=E.subMatrixRow(this.pivotVector,0,V-1),ue=B.columns,ce,Oe,Se;for(Se=0;Se<ue;Se++)for(ce=Se+1;ce<ue;ce++)for(Oe=0;Oe<V;Oe++)q.set(ce,Oe,q.get(ce,Oe)-q.get(Se,Oe)*B.get(ce,Se));for(Se=ue-1;Se>=0;Se--){for(Oe=0;Oe<V;Oe++)q.set(Se,Oe,q.get(Se,Oe)/B.get(Se,Se));for(ce=0;ce<Se;ce++)for(Oe=0;Oe<V;Oe++)q.set(ce,Oe,q.get(ce,Oe)-q.get(Se,Oe)*B.get(ce,Se))}return q}get determinant(){let E=this.LU;if(!E.isSquare())throw new Error("Matrix must be square");let B=this.pivotSign,N=E.columns;for(let V=0;V<N;V++)B*=E.get(V,V);return B}get lowerTriangularMatrix(){let E=this.LU,B=E.rows,N=E.columns,V=new be(B,N);for(let q=0;q<B;q++)for(let ue=0;ue<N;ue++)q>ue?V.set(q,ue,E.get(q,ue)):q===ue?V.set(q,ue,1):V.set(q,ue,0);return V}get upperTriangularMatrix(){let E=this.LU,B=E.rows,N=E.columns,V=new be(B,N);for(let q=0;q<B;q++)for(let ue=0;ue<N;ue++)q<=ue?V.set(q,ue,E.get(q,ue)):V.set(q,ue,0);return V}get pivotPermutationVector(){return Array.from(this.pivotVector)}}function Wt(Ee,E){let B=0;return Math.abs(Ee)>Math.abs(E)?(B=E/Ee,Math.abs(Ee)*Math.sqrt(1+B*B)):E!==0?(B=Ee/E,Math.abs(E)*Math.sqrt(1+B*B)):0}class Gt{constructor(E){E=gt.checkMatrix(E);let B=E.clone(),N=E.rows,V=E.columns,q=new Float64Array(V),ue,ce,Oe,Se;for(Oe=0;Oe<V;Oe++){let Ue=0;for(ue=Oe;ue<N;ue++)Ue=Wt(Ue,B.get(ue,Oe));if(Ue!==0){for(B.get(Oe,Oe)<0&&(Ue=-Ue),ue=Oe;ue<N;ue++)B.set(ue,Oe,B.get(ue,Oe)/Ue);for(B.set(Oe,Oe,B.get(Oe,Oe)+1),ce=Oe+1;ce<V;ce++){for(Se=0,ue=Oe;ue<N;ue++)Se+=B.get(ue,Oe)*B.get(ue,ce);for(Se=-Se/B.get(Oe,Oe),ue=Oe;ue<N;ue++)B.set(ue,ce,B.get(ue,ce)+Se*B.get(ue,Oe))}}q[Oe]=-Ue}this.QR=B,this.Rdiag=q}solve(E){E=be.checkMatrix(E);let B=this.QR,N=B.rows;if(E.rows!==N)throw new Error("Matrix row dimensions must agree");if(!this.isFullRank())throw new Error("Matrix is rank deficient");let V=E.columns,q=E.clone(),ue=B.columns,ce,Oe,Se,Ue;for(Se=0;Se<ue;Se++)for(Oe=0;Oe<V;Oe++){for(Ue=0,ce=Se;ce<N;ce++)Ue+=B.get(ce,Se)*q.get(ce,Oe);for(Ue=-Ue/B.get(Se,Se),ce=Se;ce<N;ce++)q.set(ce,Oe,q.get(ce,Oe)+Ue*B.get(ce,Se))}for(Se=ue-1;Se>=0;Se--){for(Oe=0;Oe<V;Oe++)q.set(Se,Oe,q.get(Se,Oe)/this.Rdiag[Se]);for(ce=0;ce<Se;ce++)for(Oe=0;Oe<V;Oe++)q.set(ce,Oe,q.get(ce,Oe)-q.get(Se,Oe)*B.get(ce,Se))}return q.subMatrix(0,ue-1,0,V-1)}isFullRank(){let E=this.QR.columns;for(let B=0;B<E;B++)if(this.Rdiag[B]===0)return!1;return!0}get upperTriangularMatrix(){let E=this.QR,B=E.columns,N=new be(B,B),V,q;for(V=0;V<B;V++)for(q=0;q<B;q++)V<q?N.set(V,q,E.get(V,q)):V===q?N.set(V,q,this.Rdiag[V]):N.set(V,q,0);return N}get orthogonalMatrix(){let E=this.QR,B=E.rows,N=E.columns,V=new be(B,N),q,ue,ce,Oe;for(ce=N-1;ce>=0;ce--){for(q=0;q<B;q++)V.set(q,ce,0);for(V.set(ce,ce,1),ue=ce;ue<N;ue++)if(E.get(ce,ce)!==0){for(Oe=0,q=ce;q<B;q++)Oe+=E.get(q,ce)*V.get(q,ue);for(Oe=-Oe/E.get(ce,ce),q=ce;q<B;q++)V.set(q,ue,V.get(q,ue)+Oe*E.get(q,ce))}}return V}}class zt{constructor(E,B={}){if(E=gt.checkMatrix(E),E.isEmpty())throw new Error("Matrix must be non-empty");let N=E.rows,V=E.columns;const{computeLeftSingularVectors:q=!0,computeRightSingularVectors:ue=!0,autoTranspose:ce=!1}=B;let Oe=!!q,Se=!!ue,Ue=!1,je;if(N<V)if(!ce)je=E.clone(),console.warn("Computing SVD on a matrix with more columns than rows. Consider enabling autoTranspose");else{je=E.transpose(),N=je.rows,V=je.columns,Ue=!0;let lt=Oe;Oe=Se,Se=lt}else je=E.clone();let it=Math.min(N,V),at=Math.min(N+1,V),et=new Float64Array(at),st=new be(N,it),Je=new be(V,V),ke=new Float64Array(V),ft=new Float64Array(N),yt=new Float64Array(at);for(let lt=0;lt<at;lt++)yt[lt]=lt;let Pt=Math.min(N-1,V),Ut=Math.max(0,Math.min(V-2,N)),Qt=Math.max(Pt,Ut);for(let lt=0;lt<Qt;lt++){if(lt<Pt){et[lt]=0;for(let Mt=lt;Mt<N;Mt++)et[lt]=Wt(et[lt],je.get(Mt,lt));if(et[lt]!==0){je.get(lt,lt)<0&&(et[lt]=-et[lt]);for(let Mt=lt;Mt<N;Mt++)je.set(Mt,lt,je.get(Mt,lt)/et[lt]);je.set(lt,lt,je.get(lt,lt)+1)}et[lt]=-et[lt]}for(let Mt=lt+1;Mt<V;Mt++){if(lt<Pt&&et[lt]!==0){let Lt=0;for(let Nt=lt;Nt<N;Nt++)Lt+=je.get(Nt,lt)*je.get(Nt,Mt);Lt=-Lt/je.get(lt,lt);for(let Nt=lt;Nt<N;Nt++)je.set(Nt,Mt,je.get(Nt,Mt)+Lt*je.get(Nt,lt))}ke[Mt]=je.get(lt,Mt)}if(Oe&&lt<Pt)for(let Mt=lt;Mt<N;Mt++)st.set(Mt,lt,je.get(Mt,lt));if(lt<Ut){ke[lt]=0;for(let Mt=lt+1;Mt<V;Mt++)ke[lt]=Wt(ke[lt],ke[Mt]);if(ke[lt]!==0){ke[lt+1]<0&&(ke[lt]=0-ke[lt]);for(let Mt=lt+1;Mt<V;Mt++)ke[Mt]/=ke[lt];ke[lt+1]+=1}if(ke[lt]=-ke[lt],lt+1<N&&ke[lt]!==0){for(let Mt=lt+1;Mt<N;Mt++)ft[Mt]=0;for(let Mt=lt+1;Mt<N;Mt++)for(let Lt=lt+1;Lt<V;Lt++)ft[Mt]+=ke[Lt]*je.get(Mt,Lt);for(let Mt=lt+1;Mt<V;Mt++){let Lt=-ke[Mt]/ke[lt+1];for(let Nt=lt+1;Nt<N;Nt++)je.set(Nt,Mt,je.get(Nt,Mt)+Lt*ft[Nt])}}if(Se)for(let Mt=lt+1;Mt<V;Mt++)Je.set(Mt,lt,ke[Mt])}}let Ct=Math.min(V,N+1);if(Pt<V&&(et[Pt]=je.get(Pt,Pt)),N<Ct&&(et[Ct-1]=0),Ut+1<Ct&&(ke[Ut]=je.get(Ut,Ct-1)),ke[Ct-1]=0,Oe){for(let lt=Pt;lt<it;lt++){for(let Mt=0;Mt<N;Mt++)st.set(Mt,lt,0);st.set(lt,lt,1)}for(let lt=Pt-1;lt>=0;lt--)if(et[lt]!==0){for(let Mt=lt+1;Mt<it;Mt++){let Lt=0;for(let Nt=lt;Nt<N;Nt++)Lt+=st.get(Nt,lt)*st.get(Nt,Mt);Lt=-Lt/st.get(lt,lt);for(let Nt=lt;Nt<N;Nt++)st.set(Nt,Mt,st.get(Nt,Mt)+Lt*st.get(Nt,lt))}for(let Mt=lt;Mt<N;Mt++)st.set(Mt,lt,-st.get(Mt,lt));st.set(lt,lt,1+st.get(lt,lt));for(let Mt=0;Mt<lt-1;Mt++)st.set(Mt,lt,0)}else{for(let Mt=0;Mt<N;Mt++)st.set(Mt,lt,0);st.set(lt,lt,1)}}if(Se)for(let lt=V-1;lt>=0;lt--){if(lt<Ut&&ke[lt]!==0)for(let Mt=lt+1;Mt<V;Mt++){let Lt=0;for(let Nt=lt+1;Nt<V;Nt++)Lt+=Je.get(Nt,lt)*Je.get(Nt,Mt);Lt=-Lt/Je.get(lt+1,lt);for(let Nt=lt+1;Nt<V;Nt++)Je.set(Nt,Mt,Je.get(Nt,Mt)+Lt*Je.get(Nt,lt))}for(let Mt=0;Mt<V;Mt++)Je.set(Mt,lt,0);Je.set(lt,lt,1)}let It=Ct-1,Zt=Number.EPSILON;for(;Ct>0;){let lt,Mt;for(lt=Ct-2;lt>=-1&&lt!==-1;lt--){const Lt=Number.MIN_VALUE+Zt*Math.abs(et[lt]+Math.abs(et[lt+1]));if(Math.abs(ke[lt])<=Lt||Number.isNaN(ke[lt])){ke[lt]=0;break}}if(lt===Ct-2)Mt=4;else{let Lt;for(Lt=Ct-1;Lt>=lt&&Lt!==lt;Lt--){let Nt=(Lt!==Ct?Math.abs(ke[Lt]):0)+(Lt!==lt+1?Math.abs(ke[Lt-1]):0);if(Math.abs(et[Lt])<=Zt*Nt){et[Lt]=0;break}}Lt===lt?Mt=3:Lt===Ct-1?Mt=1:(Mt=2,lt=Lt)}switch(lt++,Mt){case 1:{let Lt=ke[Ct-2];ke[Ct-2]=0;for(let Nt=Ct-2;Nt>=lt;Nt--){let Vt=Wt(et[Nt],Lt),Kt=et[Nt]/Vt,qt=Lt/Vt;if(et[Nt]=Vt,Nt!==lt&&(Lt=-qt*ke[Nt-1],ke[Nt-1]=Kt*ke[Nt-1]),Se)for(let ln=0;ln<V;ln++)Vt=Kt*Je.get(ln,Nt)+qt*Je.get(ln,Ct-1),Je.set(ln,Ct-1,-qt*Je.get(ln,Nt)+Kt*Je.get(ln,Ct-1)),Je.set(ln,Nt,Vt)}break}case 2:{let Lt=ke[lt-1];ke[lt-1]=0;for(let Nt=lt;Nt<Ct;Nt++){let Vt=Wt(et[Nt],Lt),Kt=et[Nt]/Vt,qt=Lt/Vt;if(et[Nt]=Vt,Lt=-qt*ke[Nt],ke[Nt]=Kt*ke[Nt],Oe)for(let ln=0;ln<N;ln++)Vt=Kt*st.get(ln,Nt)+qt*st.get(ln,lt-1),st.set(ln,lt-1,-qt*st.get(ln,Nt)+Kt*st.get(ln,lt-1)),st.set(ln,Nt,Vt)}break}case 3:{const Lt=Math.max(Math.abs(et[Ct-1]),Math.abs(et[Ct-2]),Math.abs(ke[Ct-2]),Math.abs(et[lt]),Math.abs(ke[lt])),Nt=et[Ct-1]/Lt,Vt=et[Ct-2]/Lt,Kt=ke[Ct-2]/Lt,qt=et[lt]/Lt,ln=ke[lt]/Lt,pn=((Vt+Nt)*(Vt-Nt)+Kt*Kt)/2,mn=Nt*Kt*(Nt*Kt);let yn=0;(pn!==0||mn!==0)&&(pn<0?yn=0-Math.sqrt(pn*pn+mn):yn=Math.sqrt(pn*pn+mn),yn=mn/(pn+yn));let Zn=(qt+Nt)*(qt-Nt)+yn,Nn=qt*ln;for(let nn=lt;nn<Ct-1;nn++){let Ln=Wt(Zn,Nn);Ln===0&&(Ln=Number.MIN_VALUE);let Bn=Zn/Ln,lr=Nn/Ln;if(nn!==lt&&(ke[nn-1]=Ln),Zn=Bn*et[nn]+lr*ke[nn],ke[nn]=Bn*ke[nn]-lr*et[nn],Nn=lr*et[nn+1],et[nn+1]=Bn*et[nn+1],Se)for(let qn=0;qn<V;qn++)Ln=Bn*Je.get(qn,nn)+lr*Je.get(qn,nn+1),Je.set(qn,nn+1,-lr*Je.get(qn,nn)+Bn*Je.get(qn,nn+1)),Je.set(qn,nn,Ln);if(Ln=Wt(Zn,Nn),Ln===0&&(Ln=Number.MIN_VALUE),Bn=Zn/Ln,lr=Nn/Ln,et[nn]=Ln,Zn=Bn*ke[nn]+lr*et[nn+1],et[nn+1]=-lr*ke[nn]+Bn*et[nn+1],Nn=lr*ke[nn+1],ke[nn+1]=Bn*ke[nn+1],Oe&&nn<N-1)for(let qn=0;qn<N;qn++)Ln=Bn*st.get(qn,nn)+lr*st.get(qn,nn+1),st.set(qn,nn+1,-lr*st.get(qn,nn)+Bn*st.get(qn,nn+1)),st.set(qn,nn,Ln)}ke[Ct-2]=Zn;break}case 4:{if(et[lt]<=0&&(et[lt]=et[lt]<0?-et[lt]:0,Se))for(let Lt=0;Lt<=It;Lt++)Je.set(Lt,lt,-Je.get(Lt,lt));for(;lt<It&&!(et[lt]>=et[lt+1]);){let Lt=et[lt];if(et[lt]=et[lt+1],et[lt+1]=Lt,Se&&lt<V-1)for(let Nt=0;Nt<V;Nt++)Lt=Je.get(Nt,lt+1),Je.set(Nt,lt+1,Je.get(Nt,lt)),Je.set(Nt,lt,Lt);if(Oe&&lt<N-1)for(let Nt=0;Nt<N;Nt++)Lt=st.get(Nt,lt+1),st.set(Nt,lt+1,st.get(Nt,lt)),st.set(Nt,lt,Lt);lt++}Ct--;break}}}if(Ue){let lt=Je;Je=st,st=lt}this.m=N,this.n=V,this.s=et,this.U=st,this.V=Je}solve(E){let B=E,N=this.threshold,V=this.s.length,q=be.zeros(V,V);for(let it=0;it<V;it++)Math.abs(this.s[it])<=N?q.set(it,it,0):q.set(it,it,1/this.s[it]);let ue=this.U,ce=this.rightSingularVectors,Oe=ce.mmul(q),Se=ce.rows,Ue=ue.rows,je=be.zeros(Se,Ue);for(let it=0;it<Se;it++)for(let at=0;at<Ue;at++){let et=0;for(let st=0;st<V;st++)et+=Oe.get(it,st)*ue.get(at,st);je.set(it,at,et)}return je.mmul(B)}solveForDiagonal(E){return this.solve(be.diag(E))}inverse(){let E=this.V,B=this.threshold,N=E.rows,V=E.columns,q=new be(N,this.s.length);for(let Ue=0;Ue<N;Ue++)for(let je=0;je<V;je++)Math.abs(this.s[je])>B&&q.set(Ue,je,E.get(Ue,je)/this.s[je]);let ue=this.U,ce=ue.rows,Oe=ue.columns,Se=new be(N,ce);for(let Ue=0;Ue<N;Ue++)for(let je=0;je<ce;je++){let it=0;for(let at=0;at<Oe;at++)it+=q.get(Ue,at)*ue.get(je,at);Se.set(Ue,je,it)}return Se}get condition(){return this.s[0]/this.s[Math.min(this.m,this.n)-1]}get norm2(){return this.s[0]}get rank(){let E=Math.max(this.m,this.n)*this.s[0]*Number.EPSILON,B=0,N=this.s;for(let V=0,q=N.length;V<q;V++)N[V]>E&&B++;return B}get diagonal(){return Array.from(this.s)}get threshold(){return Number.EPSILON/2*Math.max(this.m,this.n)*this.s[0]}get leftSingularVectors(){return this.U}get rightSingularVectors(){return this.V}get diagonalMatrix(){return be.diag(this.s)}}function en(Ee,E=!1){return Ee=gt.checkMatrix(Ee),E?new zt(Ee).inverse():vn(Ee,be.eye(Ee.rows))}function vn(Ee,E,B=!1){return Ee=gt.checkMatrix(Ee),E=gt.checkMatrix(E),B?new zt(Ee).solve(E):Ee.isSquare()?new Ot(Ee).solve(E):new Gt(Ee).solve(E)}function on(Ee){if(Ee=be.checkMatrix(Ee),Ee.isSquare()){if(Ee.columns===0)return 1;let E,B,N,V;if(Ee.columns===2)return E=Ee.get(0,0),B=Ee.get(0,1),N=Ee.get(1,0),V=Ee.get(1,1),E*V-B*N;if(Ee.columns===3){let q,ue,ce;return q=new Tt(Ee,[1,2],[1,2]),ue=new Tt(Ee,[1,2],[0,2]),ce=new Tt(Ee,[1,2],[0,1]),E=Ee.get(0,0),B=Ee.get(0,1),N=Ee.get(0,2),E*on(q)-B*on(ue)+N*on(ce)}else return new Ot(Ee).determinant}else throw Error("determinant can only be calculated for a square matrix")}function cn(Ee,E){let B=[];for(let N=0;N<Ee;N++)N!==E&&B.push(N);return B}function On(Ee,E,B,N=1e-9,V=1e-9){if(Ee>V)return new Array(E.rows+1).fill(0);{let q=E.addRow(B,[0]);for(let ue=0;ue<q.rows;ue++)Math.abs(q.get(ue,0))<N&&q.set(ue,0,0);return q.to1DArray()}}function Mn(Ee,E={}){const{thresholdValue:B=1e-9,thresholdError:N=1e-9}=E;Ee=be.checkMatrix(Ee);let V=Ee.rows,q=new be(V,V);for(let ue=0;ue<V;ue++){let ce=be.columnVector(Ee.getRow(ue)),Oe=Ee.subMatrixRow(cn(V,ue)).transpose(),Ue=new zt(Oe).solve(ce),je=be.sub(ce,Oe.mmul(Ue)).abs().max();q.setRow(ue,On(je,Ue,ue,B,N))}return q}function Yt(Ee,E=Number.EPSILON){if(Ee=be.checkMatrix(Ee),Ee.isEmpty())return Ee.transpose();let B=new zt(Ee,{autoTranspose:!0}),N=B.leftSingularVectors,V=B.rightSingularVectors,q=B.diagonal;for(let ue=0;ue<q.length;ue++)Math.abs(q[ue])>E?q[ue]=1/q[ue]:q[ue]=0;return V.mmul(be.diag(q).mmul(N.transpose()))}function Jt(Ee,E=Ee,B={}){Ee=new be(Ee);let N=!1;if(typeof E=="object"&&!be.isMatrix(E)&&!v.isAnyArray(E)?(B=E,E=Ee,N=!0):E=new be(E),Ee.rows!==E.rows)throw new TypeError("Both matrices must have the same number of rows");const{center:V=!0}=B;V&&(Ee=Ee.center("column"),N||(E=E.center("column")));const q=Ee.transpose().mmul(E);for(let ue=0;ue<q.rows;ue++)for(let ce=0;ce<q.columns;ce++)q.set(ue,ce,q.get(ue,ce)*(1/(Ee.rows-1)));return q}function Ht(Ee,E=Ee,B={}){Ee=new be(Ee);let N=!1;if(typeof E=="object"&&!be.isMatrix(E)&&!v.isAnyArray(E)?(B=E,E=Ee,N=!0):E=new be(E),Ee.rows!==E.rows)throw new TypeError("Both matrices must have the same number of rows");const{center:V=!0,scale:q=!0}=B;V&&(Ee.center("column"),N||E.center("column")),q&&(Ee.scale("column"),N||E.scale("column"));const ue=Ee.standardDeviation("column",{unbiased:!0}),ce=N?ue:E.standardDeviation("column",{unbiased:!0}),Oe=Ee.transpose().mmul(E);for(let Se=0;Se<Oe.rows;Se++)for(let Ue=0;Ue<Oe.columns;Ue++)Oe.set(Se,Ue,Oe.get(Se,Ue)*(1/(ue[Se]*ce[Ue]))*(1/(Ee.rows-1)));return Oe}class bn{constructor(E,B={}){const{assumeSymmetric:N=!1}=B;if(E=gt.checkMatrix(E),!E.isSquare())throw new Error("Matrix is not a square matrix");if(E.isEmpty())throw new Error("Matrix must be non-empty");let V=E.columns,q=new be(V,V),ue=new Float64Array(V),ce=new Float64Array(V),Oe=E,Se,Ue,je=!1;if(N?je=!0:je=E.isSymmetric(),je){for(Se=0;Se<V;Se++)for(Ue=0;Ue<V;Ue++)q.set(Se,Ue,Oe.get(Se,Ue));Sn(V,ce,ue,q),Pn(V,ce,ue,q)}else{let it=new be(V,V),at=new Float64Array(V);for(Ue=0;Ue<V;Ue++)for(Se=0;Se<V;Se++)it.set(Se,Ue,Oe.get(Se,Ue));hn(V,it,at,q),In(V,ce,ue,q,it)}this.n=V,this.e=ce,this.d=ue,this.V=q}get realEigenvalues(){return Array.from(this.d)}get imaginaryEigenvalues(){return Array.from(this.e)}get eigenvectorMatrix(){return this.V}get diagonalMatrix(){let E=this.n,B=this.e,N=this.d,V=new be(E,E),q,ue;for(q=0;q<E;q++){for(ue=0;ue<E;ue++)V.set(q,ue,0);V.set(q,q,N[q]),B[q]>0?V.set(q,q+1,B[q]):B[q]<0&&V.set(q,q-1,B[q])}return V}}function Sn(Ee,E,B,N){let V,q,ue,ce,Oe,Se,Ue,je;for(Oe=0;Oe<Ee;Oe++)B[Oe]=N.get(Ee-1,Oe);for(ce=Ee-1;ce>0;ce--){for(je=0,ue=0,Se=0;Se<ce;Se++)je=je+Math.abs(B[Se]);if(je===0)for(E[ce]=B[ce-1],Oe=0;Oe<ce;Oe++)B[Oe]=N.get(ce-1,Oe),N.set(ce,Oe,0),N.set(Oe,ce,0);else{for(Se=0;Se<ce;Se++)B[Se]/=je,ue+=B[Se]*B[Se];for(V=B[ce-1],q=Math.sqrt(ue),V>0&&(q=-q),E[ce]=je*q,ue=ue-V*q,B[ce-1]=V-q,Oe=0;Oe<ce;Oe++)E[Oe]=0;for(Oe=0;Oe<ce;Oe++){for(V=B[Oe],N.set(Oe,ce,V),q=E[Oe]+N.get(Oe,Oe)*V,Se=Oe+1;Se<=ce-1;Se++)q+=N.get(Se,Oe)*B[Se],E[Se]+=N.get(Se,Oe)*V;E[Oe]=q}for(V=0,Oe=0;Oe<ce;Oe++)E[Oe]/=ue,V+=E[Oe]*B[Oe];for(Ue=V/(ue+ue),Oe=0;Oe<ce;Oe++)E[Oe]-=Ue*B[Oe];for(Oe=0;Oe<ce;Oe++){for(V=B[Oe],q=E[Oe],Se=Oe;Se<=ce-1;Se++)N.set(Se,Oe,N.get(Se,Oe)-(V*E[Se]+q*B[Se]));B[Oe]=N.get(ce-1,Oe),N.set(ce,Oe,0)}}B[ce]=ue}for(ce=0;ce<Ee-1;ce++){if(N.set(Ee-1,ce,N.get(ce,ce)),N.set(ce,ce,1),ue=B[ce+1],ue!==0){for(Se=0;Se<=ce;Se++)B[Se]=N.get(Se,ce+1)/ue;for(Oe=0;Oe<=ce;Oe++){for(q=0,Se=0;Se<=ce;Se++)q+=N.get(Se,ce+1)*N.get(Se,Oe);for(Se=0;Se<=ce;Se++)N.set(Se,Oe,N.get(Se,Oe)-q*B[Se])}}for(Se=0;Se<=ce;Se++)N.set(Se,ce+1,0)}for(Oe=0;Oe<Ee;Oe++)B[Oe]=N.get(Ee-1,Oe),N.set(Ee-1,Oe,0);N.set(Ee-1,Ee-1,1),E[0]=0}function Pn(Ee,E,B,N){let V,q,ue,ce,Oe,Se,Ue,je,it,at,et,st,Je,ke,ft,yt;for(ue=1;ue<Ee;ue++)E[ue-1]=E[ue];E[Ee-1]=0;let Pt=0,Ut=0,Qt=Number.EPSILON;for(Se=0;Se<Ee;Se++){for(Ut=Math.max(Ut,Math.abs(B[Se])+Math.abs(E[Se])),Ue=Se;Ue<Ee&&!(Math.abs(E[Ue])<=Qt*Ut);)Ue++;if(Ue>Se)do{for(V=B[Se],je=(B[Se+1]-V)/(2*E[Se]),it=Wt(je,1),je<0&&(it=-it),B[Se]=E[Se]/(je+it),B[Se+1]=E[Se]*(je+it),at=B[Se+1],q=V-B[Se],ue=Se+2;ue<Ee;ue++)B[ue]-=q;for(Pt=Pt+q,je=B[Ue],et=1,st=et,Je=et,ke=E[Se+1],ft=0,yt=0,ue=Ue-1;ue>=Se;ue--)for(Je=st,st=et,yt=ft,V=et*E[ue],q=et*je,it=Wt(je,E[ue]),E[ue+1]=ft*it,ft=E[ue]/it,et=je/it,je=et*B[ue]-ft*V,B[ue+1]=q+ft*(et*V+ft*B[ue]),Oe=0;Oe<Ee;Oe++)q=N.get(Oe,ue+1),N.set(Oe,ue+1,ft*N.get(Oe,ue)+et*q),N.set(Oe,ue,et*N.get(Oe,ue)-ft*q);je=-ft*yt*Je*ke*E[Se]/at,E[Se]=ft*je,B[Se]=et*je}while(Math.abs(E[Se])>Qt*Ut);B[Se]=B[Se]+Pt,E[Se]=0}for(ue=0;ue<Ee-1;ue++){for(Oe=ue,je=B[ue],ce=ue+1;ce<Ee;ce++)B[ce]<je&&(Oe=ce,je=B[ce]);if(Oe!==ue)for(B[Oe]=B[ue],B[ue]=je,ce=0;ce<Ee;ce++)je=N.get(ce,ue),N.set(ce,ue,N.get(ce,Oe)),N.set(ce,Oe,je)}}function hn(Ee,E,B,N){let V=0,q=Ee-1,ue,ce,Oe,Se,Ue,je,it;for(je=V+1;je<=q-1;je++){for(it=0,Se=je;Se<=q;Se++)it=it+Math.abs(E.get(Se,je-1));if(it!==0){for(Oe=0,Se=q;Se>=je;Se--)B[Se]=E.get(Se,je-1)/it,Oe+=B[Se]*B[Se];for(ce=Math.sqrt(Oe),B[je]>0&&(ce=-ce),Oe=Oe-B[je]*ce,B[je]=B[je]-ce,Ue=je;Ue<Ee;Ue++){for(ue=0,Se=q;Se>=je;Se--)ue+=B[Se]*E.get(Se,Ue);for(ue=ue/Oe,Se=je;Se<=q;Se++)E.set(Se,Ue,E.get(Se,Ue)-ue*B[Se])}for(Se=0;Se<=q;Se++){for(ue=0,Ue=q;Ue>=je;Ue--)ue+=B[Ue]*E.get(Se,Ue);for(ue=ue/Oe,Ue=je;Ue<=q;Ue++)E.set(Se,Ue,E.get(Se,Ue)-ue*B[Ue])}B[je]=it*B[je],E.set(je,je-1,it*ce)}}for(Se=0;Se<Ee;Se++)for(Ue=0;Ue<Ee;Ue++)N.set(Se,Ue,Se===Ue?1:0);for(je=q-1;je>=V+1;je--)if(E.get(je,je-1)!==0){for(Se=je+1;Se<=q;Se++)B[Se]=E.get(Se,je-1);for(Ue=je;Ue<=q;Ue++){for(ce=0,Se=je;Se<=q;Se++)ce+=B[Se]*N.get(Se,Ue);for(ce=ce/B[je]/E.get(je,je-1),Se=je;Se<=q;Se++)N.set(Se,Ue,N.get(Se,Ue)+ce*B[Se])}}}function In(Ee,E,B,N,V){let q=Ee-1,ue=0,ce=Ee-1,Oe=Number.EPSILON,Se=0,Ue=0,je=0,it=0,at=0,et=0,st=0,Je=0,ke,ft,yt,Pt,Ut,Qt,Ct,It,Zt,lt,Mt,Lt,Nt,Vt,Kt;for(ke=0;ke<Ee;ke++)for((ke<ue||ke>ce)&&(B[ke]=V.get(ke,ke),E[ke]=0),ft=Math.max(ke-1,0);ft<Ee;ft++)Ue=Ue+Math.abs(V.get(ke,ft));for(;q>=ue;){for(Pt=q;Pt>ue&&(et=Math.abs(V.get(Pt-1,Pt-1))+Math.abs(V.get(Pt,Pt)),et===0&&(et=Ue),!(Math.abs(V.get(Pt,Pt-1))<Oe*et));)Pt--;if(Pt===q)V.set(q,q,V.get(q,q)+Se),B[q]=V.get(q,q),E[q]=0,q--,Je=0;else 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if(Pt=ke,E[ke]===0?V.set(ke,q,Ct!==0?-at/Ct:-at/(Oe*Ue)):(It=V.get(ke,ke+1),Zt=V.get(ke+1,ke),it=(B[ke]-je)*(B[ke]-je)+E[ke]*E[ke],Qt=(It*et-st*at)/it,V.set(ke,q,Qt),V.set(ke+1,q,Math.abs(It)>Math.abs(st)?(-at-Ct*Qt)/It:(-et-Zt*Qt)/st)),Qt=Math.abs(V.get(ke,q)),Oe*Qt*Qt>1)for(ft=ke;ft<=q;ft++)V.set(ft,q,V.get(ft,q)/Qt)}else if(it<0)for(Pt=q-1,Math.abs(V.get(q,q-1))>Math.abs(V.get(q-1,q))?(V.set(q-1,q-1,it/V.get(q,q-1)),V.set(q-1,q,-(V.get(q,q)-je)/V.get(q,q-1))):(Kt=Un(0,-V.get(q-1,q),V.get(q-1,q-1)-je,it),V.set(q-1,q-1,Kt[0]),V.set(q-1,q,Kt[1])),V.set(q,q-1,0),V.set(q,q,1),ke=q-2;ke>=0;ke--){for(lt=0,Mt=0,ft=Pt;ft<=q;ft++)lt=lt+V.get(ke,ft)*V.get(ft,q-1),Mt=Mt+V.get(ke,ft)*V.get(ft,q);if(Ct=V.get(ke,ke)-je,E[ke]<0)st=Ct,at=lt,et=Mt;else 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B.set(0,0,Hr),B.set(0,1,hi),B.set(0,2,cr),B.set(1,0,fi),B.set(1,1,Hi),B.set(1,2,Kn),B.set(2,0,Dn),B.set(2,1,Qn),B.set(2,2,ur),B}mmulStrassen(E){E=be.checkMatrix(E);let B=this.clone(),N=B.rows,V=B.columns,q=E.rows,ue=E.columns;V!==q&&console.warn(`Multiplying ${N} x ${V} and ${q} x ${ue} matrix: dimensions do not match.`);function ce(je,it,at){let et=je.rows,st=je.columns;if(et===it&&st===at)return je;{let Je=Ze.zeros(it,at);return Je=Je.setSubMatrix(je,0,0),Je}}let Oe=Math.max(N,q),Se=Math.max(V,ue);B=ce(B,Oe,Se),E=ce(E,Oe,Se);function Ue(je,it,at,et){if(at<=512||et<=512)return je.mmul(it);at%2===1&&et%2===1?(je=ce(je,at+1,et+1),it=ce(it,at+1,et+1)):at%2===1?(je=ce(je,at+1,et),it=ce(it,at+1,et)):et%2===1&&(je=ce(je,at,et+1),it=ce(it,at,et+1));let 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B=0;B<this.rows;B++)this.setRow(B,this.getRow(B).sort(E));return this}sortColumns(E=Ve){for(let B=0;B<this.columns;B++)this.setColumn(B,this.getColumn(B).sort(E));return this}subMatrix(E,B,N,V){$(this,E,B,N,V);let q=new be(B-E+1,V-N+1);for(let ue=E;ue<=B;ue++)for(let ce=N;ce<=V;ce++)q.set(ue-E,ce-N,this.get(ue,ce));return q}subMatrixRow(E,B,N){if(B===void 0&&(B=0),N===void 0&&(N=this.columns-1),B>N||B<0||B>=this.columns||N<0||N>=this.columns)throw new RangeError("Argument out of range");let V=new be(E.length,N-B+1);for(let q=0;q<E.length;q++)for(let ue=B;ue<=N;ue++){if(E[q]<0||E[q]>=this.rows)throw new RangeError(`Row index out of range: ${E[q]}`);V.set(q,ue-B,this.get(E[q],ue))}return V}subMatrixColumn(E,B,N){if(B===void 0&&(B=0),N===void 0&&(N=this.rows-1),B>N||B<0||B>=this.rows||N<0||N>=this.rows)throw new RangeError("Argument out of range");let V=new be(N-B+1,E.length);for(let q=0;q<E.length;q++)for(let ue=B;ue<=N;ue++){if(E[q]<0||E[q]>=this.columns)throw new RangeError(`Column 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Ze{constructor(E,B){if(super(),O(this,m),P(this,"data"),w0.isMatrix(E))g(this,m,L).call(this,E.rows,E.columns),w0.copy(E,this);else if(Number.isInteger(E)&&E>=0)g(this,m,L).call(this,E,B);else if(v.isAnyArray(E)){const N=E;if(E=N.length,B=E?N[0].length:0,typeof B!="number")throw new TypeError("Data must be a 2D array with at least one element");this.data=[];for(let V=0;V<E;V++){if(N[V].length!==B)throw new RangeError("Inconsistent array dimensions");if(!Pe(N[V]))throw new TypeError("Input data contains non-numeric values");this.data.push(Float64Array.from(N[V]))}this.rows=E,this.columns=B}else throw new TypeError("First argument must be a positive number or an array")}set(E,B,N){return this.data[E][B]=N,this}get(E,B){return this.data[E][B]}removeRow(E){return I(this,E),this.data.splice(E,1),this.rows-=1,this}addRow(E,B){return B===void 0&&(B=E,E=this.rows),I(this,E,!0),B=Float64Array.from(F(this,B)),this.data.splice(E,0,B),this.rows+=1,this}removeColumn(E){U(this,E);for(let B=0;B<this.rows;B++){const N=new Float64Array(this.columns-1);for(let V=0;V<E;V++)N[V]=this.data[B][V];for(let V=E+1;V<this.columns;V++)N[V-1]=this.data[B][V];this.data[B]=N}return this.columns-=1,this}addColumn(E,B){typeof B=="undefined"&&(B=E,E=this.columns),U(this,E,!0),B=G(this,B);for(let N=0;N<this.rows;N++){const V=new Float64Array(this.columns+1);let q=0;for(;q<E;q++)V[q]=this.data[N][q];for(V[q++]=B[N];q<this.columns+1;q++)V[q]=this.data[N][q-1];this.data[N]=V}return this.columns+=1,this}};m=new WeakSet,L=function(Ee,E){if(this.data=[],Number.isInteger(E)&&E>=0)for(let B=0;B<Ee;B++)this.data.push(new Float64Array(E));else throw new TypeError("nColumns must be a positive integer");this.rows=Ee,this.columns=E};let be=He;D(Ze,be);const Ie=class M0 extends Ze{constructor(E){if(super(),O(this,d),be.isMatrix(E)){if(!E.isSymmetric())throw new TypeError("not symmetric data");_(this,d,be.copy(E,new be(E.rows,E.rows)))}else if(Number.isInteger(E)&&E>=0)_(this,d,new be(E,E));else if(_(this,d,new be(E)),!this.isSymmetric())throw new TypeError("not symmetric data")}get size(){return x(this,d).size}get rows(){return x(this,d).rows}get columns(){return x(this,d).columns}get diagonalSize(){return this.rows}static isSymmetricMatrix(E){return be.isMatrix(E)&&E.klassType==="SymmetricMatrix"}static zeros(E){return new this(E)}static ones(E){return new this(E).fill(1)}clone(){const E=new M0(this.diagonalSize);for(const[B,N,V]of this.upperRightEntries())E.set(B,N,V);return E}toMatrix(){return new be(this)}get(E,B){return x(this,d).get(E,B)}set(E,B,N){return x(this,d).set(E,B,N),x(this,d).set(B,E,N),this}removeCross(E){return x(this,d).removeRow(E),x(this,d).removeColumn(E),this}addCross(E,B){B===void 0&&(B=E,E=this.diagonalSize);const N=B.slice();return N.splice(E,1),x(this,d).addRow(E,N),x(this,d).addColumn(E,B),this}applyMask(E){if(E.length!==this.diagonalSize)throw new RangeError("Mask size do not match with matrix size");const B=[];for(const[N,V]of E.entries())V||B.push(N);B.reverse();for(const N of B)this.removeCross(N);return this}toCompact(){const{diagonalSize:E}=this,B=new Array(E*(E+1)/2);for(let N=0,V=0,q=0;q<B.length;q++)B[q]=this.get(V,N),++N>=E&&(N=++V);return B}static fromCompact(E){const B=E.length,N=(Math.sqrt(8*B+1)-1)/2;if(!Number.isInteger(N))throw new TypeError(`This array is not a compact representation of a Symmetric Matrix, ${JSON.stringify(E)}`);const V=new M0(N);for(let q=0,ue=0,ce=0;ce<B;ce++)V.set(q,ue,E[ce]),++q>=N&&(q=++ue);return V}*upperRightEntries(){for(let E=0,B=0;E<this.diagonalSize;void 0){const N=this.get(E,B);yield[E,B,N],++B>=this.diagonalSize&&(B=++E)}}*upperRightValues(){for(let E=0,B=0;E<this.diagonalSize;void 0)yield this.get(E,B),++B>=this.diagonalSize&&(B=++E)}};d=new WeakMap;let Te=Ie;Te.prototype.klassType="SymmetricMatrix";class Re extends Te{static isDistanceMatrix(E){return Te.isSymmetricMatrix(E)&&E.klassSubType==="DistanceMatrix"}constructor(E){if(super(E),!this.isDistance())throw new TypeError("Provided arguments do no produce a distance matrix")}set(E,B,N){return E===B&&(N=0),super.set(E,B,N)}addCross(E,B){return B===void 0&&(B=E,E=this.diagonalSize),B=B.slice(),B[E]=0,super.addCross(E,B)}toSymmetricMatrix(){return new Te(this)}clone(){const E=new Re(this.diagonalSize);for(const[B,N,V]of this.upperRightEntries())B!==N&&E.set(B,N,V);return E}toCompact(){const{diagonalSize:E}=this,B=(E-1)*E/2,N=new Array(B);for(let V=1,q=0,ue=0;ue<N.length;ue++)N[ue]=this.get(q,V),++V>=E&&(V=++q+1);return N}static fromCompact(E){const B=E.length;if(B===0)return new this(0);const N=(Math.sqrt(8*B+1)+1)/2;if(!Number.isInteger(N))throw new TypeError(`This array is not a compact representation of a DistanceMatrix, ${JSON.stringify(E)}`);const V=new this(N);for(let q=1,ue=0,ce=0;ce<B;ce++)V.set(q,ue,E[ce]),++q>=N&&(q=++ue+1);return V}}Re.prototype.klassSubType="DistanceMatrix";class Ge extends Ze{constructor(E,B,N){super(),this.matrix=E,this.rows=B,this.columns=N}}class Le extends Ge{constructor(E,B){U(E,B),super(E,E.rows,1),this.column=B}set(E,B,N){return this.matrix.set(E,this.column,N),this}get(E){return this.matrix.get(E,this.column)}}class Fe extends Ge{constructor(E,B){te(E,B),super(E,E.rows,B.length),this.columnIndices=B}set(E,B,N){return this.matrix.set(E,this.columnIndices[B],N),this}get(E,B){return this.matrix.get(E,this.columnIndices[B])}}class Qe extends Ge{constructor(E){super(E,E.rows,E.columns)}set(E,B,N){return this.matrix.set(E,this.columns-B-1,N),this}get(E,B){return this.matrix.get(E,this.columns-B-1)}}class tt extends Ge{constructor(E){super(E,E.rows,E.columns)}set(E,B,N){return this.matrix.set(this.rows-E-1,B,N),this}get(E,B){return this.matrix.get(this.rows-E-1,B)}}class dt extends Ge{constructor(E,B){I(E,B),super(E,1,E.columns),this.row=B}set(E,B,N){return this.matrix.set(this.row,B,N),this}get(E,B){return this.matrix.get(this.row,B)}}class pt extends Ge{constructor(E,B){Y(E,B),super(E,B.length,E.columns),this.rowIndices=B}set(E,B,N){return this.matrix.set(this.rowIndices[E],B,N),this}get(E,B){return this.matrix.get(this.rowIndices[E],B)}}class Tt extends Ge{constructor(E,B,N){Y(E,B),te(E,N),super(E,B.length,N.length),this.rowIndices=B,this.columnIndices=N}set(E,B,N){return this.matrix.set(this.rowIndices[E],this.columnIndices[B],N),this}get(E,B){return this.matrix.get(this.rowIndices[E],this.columnIndices[B])}}class At extends Ge{constructor(E,B,N,V,q){$(E,B,N,V,q),super(E,N-B+1,q-V+1),this.startRow=B,this.startColumn=V}set(E,B,N){return this.matrix.set(this.startRow+E,this.startColumn+B,N),this}get(E,B){return this.matrix.get(this.startRow+E,this.startColumn+B)}}class Ye extends Ge{constructor(E){super(E,E.columns,E.rows)}set(E,B,N){return this.matrix.set(B,E,N),this}get(E,B){return this.matrix.get(B,E)}}class ht extends Ze{constructor(E,B={}){const{rows:N=1}=B;if(E.length%N!==0)throw new Error("the data length is not divisible by the number of rows");super(),this.rows=N,this.columns=E.length/N,this.data=E}set(E,B,N){let V=this._calculateIndex(E,B);return this.data[V]=N,this}get(E,B){let N=this._calculateIndex(E,B);return this.data[N]}_calculateIndex(E,B){return E*this.columns+B}}class gt extends Ze{constructor(E){super(),this.data=E,this.rows=E.length,this.columns=E[0].length}set(E,B,N){return this.data[E][B]=N,this}get(E,B){return this.data[E][B]}}function _t(Ee,E){if(v.isAnyArray(Ee))return Ee[0]&&v.isAnyArray(Ee[0])?new gt(Ee):new ht(Ee,E);throw new Error("the argument is not an array")}class Ot{constructor(E){E=gt.checkMatrix(E);let B=E.clone(),N=B.rows,V=B.columns,q=new Float64Array(N),ue=1,ce,Oe,Se,Ue,je,it,at,et,st;for(ce=0;ce<N;ce++)q[ce]=ce;for(et=new Float64Array(N),Oe=0;Oe<V;Oe++){for(ce=0;ce<N;ce++)et[ce]=B.get(ce,Oe);for(ce=0;ce<N;ce++){for(st=Math.min(ce,Oe),je=0,Se=0;Se<st;Se++)je+=B.get(ce,Se)*et[Se];et[ce]-=je,B.set(ce,Oe,et[ce])}for(Ue=Oe,ce=Oe+1;ce<N;ce++)Math.abs(et[ce])>Math.abs(et[Ue])&&(Ue=ce);if(Ue!==Oe){for(Se=0;Se<V;Se++)it=B.get(Ue,Se),B.set(Ue,Se,B.get(Oe,Se)),B.set(Oe,Se,it);at=q[Ue],q[Ue]=q[Oe],q[Oe]=at,ue=-ue}if(Oe<N&&B.get(Oe,Oe)!==0)for(ce=Oe+1;ce<N;ce++)B.set(ce,Oe,B.get(ce,Oe)/B.get(Oe,Oe))}this.LU=B,this.pivotVector=q,this.pivotSign=ue}isSingular(){let E=this.LU,B=E.columns;for(let N=0;N<B;N++)if(E.get(N,N)===0)return!0;return!1}solve(E){E=be.checkMatrix(E);let B=this.LU;if(B.rows!==E.rows)throw new Error("Invalid matrix dimensions");if(this.isSingular())throw new Error("LU matrix is singular");let V=E.columns,q=E.subMatrixRow(this.pivotVector,0,V-1),ue=B.columns,ce,Oe,Se;for(Se=0;Se<ue;Se++)for(ce=Se+1;ce<ue;ce++)for(Oe=0;Oe<V;Oe++)q.set(ce,Oe,q.get(ce,Oe)-q.get(Se,Oe)*B.get(ce,Se));for(Se=ue-1;Se>=0;Se--){for(Oe=0;Oe<V;Oe++)q.set(Se,Oe,q.get(Se,Oe)/B.get(Se,Se));for(ce=0;ce<Se;ce++)for(Oe=0;Oe<V;Oe++)q.set(ce,Oe,q.get(ce,Oe)-q.get(Se,Oe)*B.get(ce,Se))}return q}get determinant(){let E=this.LU;if(!E.isSquare())throw new Error("Matrix must be square");let B=this.pivotSign,N=E.columns;for(let V=0;V<N;V++)B*=E.get(V,V);return B}get lowerTriangularMatrix(){let E=this.LU,B=E.rows,N=E.columns,V=new be(B,N);for(let q=0;q<B;q++)for(let ue=0;ue<N;ue++)q>ue?V.set(q,ue,E.get(q,ue)):q===ue?V.set(q,ue,1):V.set(q,ue,0);return V}get upperTriangularMatrix(){let E=this.LU,B=E.rows,N=E.columns,V=new be(B,N);for(let q=0;q<B;q++)for(let ue=0;ue<N;ue++)q<=ue?V.set(q,ue,E.get(q,ue)):V.set(q,ue,0);return V}get pivotPermutationVector(){return Array.from(this.pivotVector)}}function Wt(Ee,E){let B=0;return Math.abs(Ee)>Math.abs(E)?(B=E/Ee,Math.abs(Ee)*Math.sqrt(1+B*B)):E!==0?(B=Ee/E,Math.abs(E)*Math.sqrt(1+B*B)):0}class Gt{constructor(E){E=gt.checkMatrix(E);let B=E.clone(),N=E.rows,V=E.columns,q=new Float64Array(V),ue,ce,Oe,Se;for(Oe=0;Oe<V;Oe++){let Ue=0;for(ue=Oe;ue<N;ue++)Ue=Wt(Ue,B.get(ue,Oe));if(Ue!==0){for(B.get(Oe,Oe)<0&&(Ue=-Ue),ue=Oe;ue<N;ue++)B.set(ue,Oe,B.get(ue,Oe)/Ue);for(B.set(Oe,Oe,B.get(Oe,Oe)+1),ce=Oe+1;ce<V;ce++){for(Se=0,ue=Oe;ue<N;ue++)Se+=B.get(ue,Oe)*B.get(ue,ce);for(Se=-Se/B.get(Oe,Oe),ue=Oe;ue<N;ue++)B.set(ue,ce,B.get(ue,ce)+Se*B.get(ue,Oe))}}q[Oe]=-Ue}this.QR=B,this.Rdiag=q}solve(E){E=be.checkMatrix(E);let B=this.QR,N=B.rows;if(E.rows!==N)throw new Error("Matrix row dimensions must agree");if(!this.isFullRank())throw new Error("Matrix is rank deficient");let V=E.columns,q=E.clone(),ue=B.columns,ce,Oe,Se,Ue;for(Se=0;Se<ue;Se++)for(Oe=0;Oe<V;Oe++){for(Ue=0,ce=Se;ce<N;ce++)Ue+=B.get(ce,Se)*q.get(ce,Oe);for(Ue=-Ue/B.get(Se,Se),ce=Se;ce<N;ce++)q.set(ce,Oe,q.get(ce,Oe)+Ue*B.get(ce,Se))}for(Se=ue-1;Se>=0;Se--){for(Oe=0;Oe<V;Oe++)q.set(Se,Oe,q.get(Se,Oe)/this.Rdiag[Se]);for(ce=0;ce<Se;ce++)for(Oe=0;Oe<V;Oe++)q.set(ce,Oe,q.get(ce,Oe)-q.get(Se,Oe)*B.get(ce,Se))}return q.subMatrix(0,ue-1,0,V-1)}isFullRank(){let E=this.QR.columns;for(let B=0;B<E;B++)if(this.Rdiag[B]===0)return!1;return!0}get upperTriangularMatrix(){let E=this.QR,B=E.columns,N=new be(B,B),V,q;for(V=0;V<B;V++)for(q=0;q<B;q++)V<q?N.set(V,q,E.get(V,q)):V===q?N.set(V,q,this.Rdiag[V]):N.set(V,q,0);return N}get orthogonalMatrix(){let E=this.QR,B=E.rows,N=E.columns,V=new be(B,N),q,ue,ce,Oe;for(ce=N-1;ce>=0;ce--){for(q=0;q<B;q++)V.set(q,ce,0);for(V.set(ce,ce,1),ue=ce;ue<N;ue++)if(E.get(ce,ce)!==0){for(Oe=0,q=ce;q<B;q++)Oe+=E.get(q,ce)*V.get(q,ue);for(Oe=-Oe/E.get(ce,ce),q=ce;q<B;q++)V.set(q,ue,V.get(q,ue)+Oe*E.get(q,ce))}}return V}}class zt{constructor(E,B={}){if(E=gt.checkMatrix(E),E.isEmpty())throw new Error("Matrix must be non-empty");let N=E.rows,V=E.columns;const{computeLeftSingularVectors:q=!0,computeRightSingularVectors:ue=!0,autoTranspose:ce=!1}=B;let Oe=!!q,Se=!!ue,Ue=!1,je;if(N<V)if(!ce)je=E.clone(),console.warn("Computing SVD on a matrix with more columns than rows. Consider enabling autoTranspose");else{je=E.transpose(),N=je.rows,V=je.columns,Ue=!0;let lt=Oe;Oe=Se,Se=lt}else je=E.clone();let it=Math.min(N,V),at=Math.min(N+1,V),et=new Float64Array(at),st=new be(N,it),Je=new be(V,V),ke=new Float64Array(V),ft=new Float64Array(N),yt=new Float64Array(at);for(let lt=0;lt<at;lt++)yt[lt]=lt;let Pt=Math.min(N-1,V),Ut=Math.max(0,Math.min(V-2,N)),Qt=Math.max(Pt,Ut);for(let lt=0;lt<Qt;lt++){if(lt<Pt){et[lt]=0;for(let Mt=lt;Mt<N;Mt++)et[lt]=Wt(et[lt],je.get(Mt,lt));if(et[lt]!==0){je.get(lt,lt)<0&&(et[lt]=-et[lt]);for(let Mt=lt;Mt<N;Mt++)je.set(Mt,lt,je.get(Mt,lt)/et[lt]);je.set(lt,lt,je.get(lt,lt)+1)}et[lt]=-et[lt]}for(let Mt=lt+1;Mt<V;Mt++){if(lt<Pt&&et[lt]!==0){let Lt=0;for(let Nt=lt;Nt<N;Nt++)Lt+=je.get(Nt,lt)*je.get(Nt,Mt);Lt=-Lt/je.get(lt,lt);for(let Nt=lt;Nt<N;Nt++)je.set(Nt,Mt,je.get(Nt,Mt)+Lt*je.get(Nt,lt))}ke[Mt]=je.get(lt,Mt)}if(Oe&&lt<Pt)for(let Mt=lt;Mt<N;Mt++)st.set(Mt,lt,je.get(Mt,lt));if(lt<Ut){ke[lt]=0;for(let Mt=lt+1;Mt<V;Mt++)ke[lt]=Wt(ke[lt],ke[Mt]);if(ke[lt]!==0){ke[lt+1]<0&&(ke[lt]=0-ke[lt]);for(let Mt=lt+1;Mt<V;Mt++)ke[Mt]/=ke[lt];ke[lt+1]+=1}if(ke[lt]=-ke[lt],lt+1<N&&ke[lt]!==0){for(let Mt=lt+1;Mt<N;Mt++)ft[Mt]=0;for(let Mt=lt+1;Mt<N;Mt++)for(let Lt=lt+1;Lt<V;Lt++)ft[Mt]+=ke[Lt]*je.get(Mt,Lt);for(let Mt=lt+1;Mt<V;Mt++){let Lt=-ke[Mt]/ke[lt+1];for(let Nt=lt+1;Nt<N;Nt++)je.set(Nt,Mt,je.get(Nt,Mt)+Lt*ft[Nt])}}if(Se)for(let Mt=lt+1;Mt<V;Mt++)Je.set(Mt,lt,ke[Mt])}}let Ct=Math.min(V,N+1);if(Pt<V&&(et[Pt]=je.get(Pt,Pt)),N<Ct&&(et[Ct-1]=0),Ut+1<Ct&&(ke[Ut]=je.get(Ut,Ct-1)),ke[Ct-1]=0,Oe){for(let lt=Pt;lt<it;lt++){for(let Mt=0;Mt<N;Mt++)st.set(Mt,lt,0);st.set(lt,lt,1)}for(let lt=Pt-1;lt>=0;lt--)if(et[lt]!==0){for(let Mt=lt+1;Mt<it;Mt++){let Lt=0;for(let Nt=lt;Nt<N;Nt++)Lt+=st.get(Nt,lt)*st.get(Nt,Mt);Lt=-Lt/st.get(lt,lt);for(let Nt=lt;Nt<N;Nt++)st.set(Nt,Mt,st.get(Nt,Mt)+Lt*st.get(Nt,lt))}for(let Mt=lt;Mt<N;Mt++)st.set(Mt,lt,-st.get(Mt,lt));st.set(lt,lt,1+st.get(lt,lt));for(let Mt=0;Mt<lt-1;Mt++)st.set(Mt,lt,0)}else{for(let Mt=0;Mt<N;Mt++)st.set(Mt,lt,0);st.set(lt,lt,1)}}if(Se)for(let lt=V-1;lt>=0;lt--){if(lt<Ut&&ke[lt]!==0)for(let Mt=lt+1;Mt<V;Mt++){let Lt=0;for(let Nt=lt+1;Nt<V;Nt++)Lt+=Je.get(Nt,lt)*Je.get(Nt,Mt);Lt=-Lt/Je.get(lt+1,lt);for(let Nt=lt+1;Nt<V;Nt++)Je.set(Nt,Mt,Je.get(Nt,Mt)+Lt*Je.get(Nt,lt))}for(let Mt=0;Mt<V;Mt++)Je.set(Mt,lt,0);Je.set(lt,lt,1)}let It=Ct-1,Zt=Number.EPSILON;for(;Ct>0;){let lt,Mt;for(lt=Ct-2;lt>=-1&&lt!==-1;lt--){const Lt=Number.MIN_VALUE+Zt*Math.abs(et[lt]+Math.abs(et[lt+1]));if(Math.abs(ke[lt])<=Lt||Number.isNaN(ke[lt])){ke[lt]=0;break}}if(lt===Ct-2)Mt=4;else{let Lt;for(Lt=Ct-1;Lt>=lt&&Lt!==lt;Lt--){let Nt=(Lt!==Ct?Math.abs(ke[Lt]):0)+(Lt!==lt+1?Math.abs(ke[Lt-1]):0);if(Math.abs(et[Lt])<=Zt*Nt){et[Lt]=0;break}}Lt===lt?Mt=3:Lt===Ct-1?Mt=1:(Mt=2,lt=Lt)}switch(lt++,Mt){case 1:{let Lt=ke[Ct-2];ke[Ct-2]=0;for(let Nt=Ct-2;Nt>=lt;Nt--){let Vt=Wt(et[Nt],Lt),Kt=et[Nt]/Vt,qt=Lt/Vt;if(et[Nt]=Vt,Nt!==lt&&(Lt=-qt*ke[Nt-1],ke[Nt-1]=Kt*ke[Nt-1]),Se)for(let ln=0;ln<V;ln++)Vt=Kt*Je.get(ln,Nt)+qt*Je.get(ln,Ct-1),Je.set(ln,Ct-1,-qt*Je.get(ln,Nt)+Kt*Je.get(ln,Ct-1)),Je.set(ln,Nt,Vt)}break}case 2:{let Lt=ke[lt-1];ke[lt-1]=0;for(let Nt=lt;Nt<Ct;Nt++){let Vt=Wt(et[Nt],Lt),Kt=et[Nt]/Vt,qt=Lt/Vt;if(et[Nt]=Vt,Lt=-qt*ke[Nt],ke[Nt]=Kt*ke[Nt],Oe)for(let ln=0;ln<N;ln++)Vt=Kt*st.get(ln,Nt)+qt*st.get(ln,lt-1),st.set(ln,lt-1,-qt*st.get(ln,Nt)+Kt*st.get(ln,lt-1)),st.set(ln,Nt,Vt)}break}case 3:{const Lt=Math.max(Math.abs(et[Ct-1]),Math.abs(et[Ct-2]),Math.abs(ke[Ct-2]),Math.abs(et[lt]),Math.abs(ke[lt])),Nt=et[Ct-1]/Lt,Vt=et[Ct-2]/Lt,Kt=ke[Ct-2]/Lt,qt=et[lt]/Lt,ln=ke[lt]/Lt,pn=((Vt+Nt)*(Vt-Nt)+Kt*Kt)/2,mn=Nt*Kt*(Nt*Kt);let yn=0;(pn!==0||mn!==0)&&(pn<0?yn=0-Math.sqrt(pn*pn+mn):yn=Math.sqrt(pn*pn+mn),yn=mn/(pn+yn));let Zn=(qt+Nt)*(qt-Nt)+yn,Nn=qt*ln;for(let nn=lt;nn<Ct-1;nn++){let Ln=Wt(Zn,Nn);Ln===0&&(Ln=Number.MIN_VALUE);let Bn=Zn/Ln,lr=Nn/Ln;if(nn!==lt&&(ke[nn-1]=Ln),Zn=Bn*et[nn]+lr*ke[nn],ke[nn]=Bn*ke[nn]-lr*et[nn],Nn=lr*et[nn+1],et[nn+1]=Bn*et[nn+1],Se)for(let qn=0;qn<V;qn++)Ln=Bn*Je.get(qn,nn)+lr*Je.get(qn,nn+1),Je.set(qn,nn+1,-lr*Je.get(qn,nn)+Bn*Je.get(qn,nn+1)),Je.set(qn,nn,Ln);if(Ln=Wt(Zn,Nn),Ln===0&&(Ln=Number.MIN_VALUE),Bn=Zn/Ln,lr=Nn/Ln,et[nn]=Ln,Zn=Bn*ke[nn]+lr*et[nn+1],et[nn+1]=-lr*ke[nn]+Bn*et[nn+1],Nn=lr*ke[nn+1],ke[nn+1]=Bn*ke[nn+1],Oe&&nn<N-1)for(let qn=0;qn<N;qn++)Ln=Bn*st.get(qn,nn)+lr*st.get(qn,nn+1),st.set(qn,nn+1,-lr*st.get(qn,nn)+Bn*st.get(qn,nn+1)),st.set(qn,nn,Ln)}ke[Ct-2]=Zn;break}case 4:{if(et[lt]<=0&&(et[lt]=et[lt]<0?-et[lt]:0,Se))for(let Lt=0;Lt<=It;Lt++)Je.set(Lt,lt,-Je.get(Lt,lt));for(;lt<It&&!(et[lt]>=et[lt+1]);){let Lt=et[lt];if(et[lt]=et[lt+1],et[lt+1]=Lt,Se&&lt<V-1)for(let Nt=0;Nt<V;Nt++)Lt=Je.get(Nt,lt+1),Je.set(Nt,lt+1,Je.get(Nt,lt)),Je.set(Nt,lt,Lt);if(Oe&&lt<N-1)for(let Nt=0;Nt<N;Nt++)Lt=st.get(Nt,lt+1),st.set(Nt,lt+1,st.get(Nt,lt)),st.set(Nt,lt,Lt);lt++}Ct--;break}}}if(Ue){let lt=Je;Je=st,st=lt}this.m=N,this.n=V,this.s=et,this.U=st,this.V=Je}solve(E){let B=E,N=this.threshold,V=this.s.length,q=be.zeros(V,V);for(let it=0;it<V;it++)Math.abs(this.s[it])<=N?q.set(it,it,0):q.set(it,it,1/this.s[it]);let ue=this.U,ce=this.rightSingularVectors,Oe=ce.mmul(q),Se=ce.rows,Ue=ue.rows,je=be.zeros(Se,Ue);for(let it=0;it<Se;it++)for(let at=0;at<Ue;at++){let et=0;for(let st=0;st<V;st++)et+=Oe.get(it,st)*ue.get(at,st);je.set(it,at,et)}return je.mmul(B)}solveForDiagonal(E){return this.solve(be.diag(E))}inverse(){let E=this.V,B=this.threshold,N=E.rows,V=E.columns,q=new be(N,this.s.length);for(let Ue=0;Ue<N;Ue++)for(let je=0;je<V;je++)Math.abs(this.s[je])>B&&q.set(Ue,je,E.get(Ue,je)/this.s[je]);let ue=this.U,ce=ue.rows,Oe=ue.columns,Se=new be(N,ce);for(let Ue=0;Ue<N;Ue++)for(let je=0;je<ce;je++){let it=0;for(let at=0;at<Oe;at++)it+=q.get(Ue,at)*ue.get(je,at);Se.set(Ue,je,it)}return Se}get condition(){return this.s[0]/this.s[Math.min(this.m,this.n)-1]}get norm2(){return this.s[0]}get rank(){let E=Math.max(this.m,this.n)*this.s[0]*Number.EPSILON,B=0,N=this.s;for(let V=0,q=N.length;V<q;V++)N[V]>E&&B++;return B}get diagonal(){return Array.from(this.s)}get threshold(){return Number.EPSILON/2*Math.max(this.m,this.n)*this.s[0]}get leftSingularVectors(){return this.U}get rightSingularVectors(){return this.V}get diagonalMatrix(){return be.diag(this.s)}}function en(Ee,E=!1){return Ee=gt.checkMatrix(Ee),E?new zt(Ee).inverse():vn(Ee,be.eye(Ee.rows))}function vn(Ee,E,B=!1){return Ee=gt.checkMatrix(Ee),E=gt.checkMatrix(E),B?new zt(Ee).solve(E):Ee.isSquare()?new Ot(Ee).solve(E):new Gt(Ee).solve(E)}function on(Ee){if(Ee=be.checkMatrix(Ee),Ee.isSquare()){if(Ee.columns===0)return 1;let E,B,N,V;if(Ee.columns===2)return E=Ee.get(0,0),B=Ee.get(0,1),N=Ee.get(1,0),V=Ee.get(1,1),E*V-B*N;if(Ee.columns===3){let q,ue,ce;return q=new Tt(Ee,[1,2],[1,2]),ue=new Tt(Ee,[1,2],[0,2]),ce=new Tt(Ee,[1,2],[0,1]),E=Ee.get(0,0),B=Ee.get(0,1),N=Ee.get(0,2),E*on(q)-B*on(ue)+N*on(ce)}else return new Ot(Ee).determinant}else throw Error("determinant can only be calculated for a square matrix")}function cn(Ee,E){let B=[];for(let N=0;N<Ee;N++)N!==E&&B.push(N);return B}function On(Ee,E,B,N=1e-9,V=1e-9){if(Ee>V)return new Array(E.rows+1).fill(0);{let q=E.addRow(B,[0]);for(let ue=0;ue<q.rows;ue++)Math.abs(q.get(ue,0))<N&&q.set(ue,0,0);return q.to1DArray()}}function Mn(Ee,E={}){const{thresholdValue:B=1e-9,thresholdError:N=1e-9}=E;Ee=be.checkMatrix(Ee);let V=Ee.rows,q=new be(V,V);for(let ue=0;ue<V;ue++){let ce=be.columnVector(Ee.getRow(ue)),Oe=Ee.subMatrixRow(cn(V,ue)).transpose(),Ue=new zt(Oe).solve(ce),je=be.sub(ce,Oe.mmul(Ue)).abs().max();q.setRow(ue,On(je,Ue,ue,B,N))}return q}function Yt(Ee,E=Number.EPSILON){if(Ee=be.checkMatrix(Ee),Ee.isEmpty())return Ee.transpose();let B=new zt(Ee,{autoTranspose:!0}),N=B.leftSingularVectors,V=B.rightSingularVectors,q=B.diagonal;for(let ue=0;ue<q.length;ue++)Math.abs(q[ue])>E?q[ue]=1/q[ue]:q[ue]=0;return V.mmul(be.diag(q).mmul(N.transpose()))}function Jt(Ee,E=Ee,B={}){Ee=new be(Ee);let N=!1;if(typeof E=="object"&&!be.isMatrix(E)&&!v.isAnyArray(E)?(B=E,E=Ee,N=!0):E=new be(E),Ee.rows!==E.rows)throw new TypeError("Both matrices must have the same number of rows");const{center:V=!0}=B;V&&(Ee=Ee.center("column"),N||(E=E.center("column")));const q=Ee.transpose().mmul(E);for(let ue=0;ue<q.rows;ue++)for(let ce=0;ce<q.columns;ce++)q.set(ue,ce,q.get(ue,ce)*(1/(Ee.rows-1)));return q}function Ht(Ee,E=Ee,B={}){Ee=new be(Ee);let N=!1;if(typeof E=="object"&&!be.isMatrix(E)&&!v.isAnyArray(E)?(B=E,E=Ee,N=!0):E=new be(E),Ee.rows!==E.rows)throw new TypeError("Both matrices must have the same number of rows");const{center:V=!0,scale:q=!0}=B;V&&(Ee.center("column"),N||E.center("column")),q&&(Ee.scale("column"),N||E.scale("column"));const ue=Ee.standardDeviation("column",{unbiased:!0}),ce=N?ue:E.standardDeviation("column",{unbiased:!0}),Oe=Ee.transpose().mmul(E);for(let Se=0;Se<Oe.rows;Se++)for(let Ue=0;Ue<Oe.columns;Ue++)Oe.set(Se,Ue,Oe.get(Se,Ue)*(1/(ue[Se]*ce[Ue]))*(1/(Ee.rows-1)));return Oe}class bn{constructor(E,B={}){const{assumeSymmetric:N=!1}=B;if(E=gt.checkMatrix(E),!E.isSquare())throw new Error("Matrix is not a square matrix");if(E.isEmpty())throw new Error("Matrix must be non-empty");let V=E.columns,q=new be(V,V),ue=new Float64Array(V),ce=new Float64Array(V),Oe=E,Se,Ue,je=!1;if(N?je=!0:je=E.isSymmetric(),je){for(Se=0;Se<V;Se++)for(Ue=0;Ue<V;Ue++)q.set(Se,Ue,Oe.get(Se,Ue));Sn(V,ce,ue,q),Pn(V,ce,ue,q)}else{let it=new be(V,V),at=new Float64Array(V);for(Ue=0;Ue<V;Ue++)for(Se=0;Se<V;Se++)it.set(Se,Ue,Oe.get(Se,Ue));hn(V,it,at,q),In(V,ce,ue,q,it)}this.n=V,this.e=ce,this.d=ue,this.V=q}get realEigenvalues(){return Array.from(this.d)}get imaginaryEigenvalues(){return Array.from(this.e)}get eigenvectorMatrix(){return this.V}get diagonalMatrix(){let E=this.n,B=this.e,N=this.d,V=new be(E,E),q,ue;for(q=0;q<E;q++){for(ue=0;ue<E;ue++)V.set(q,ue,0);V.set(q,q,N[q]),B[q]>0?V.set(q,q+1,B[q]):B[q]<0&&V.set(q,q-1,B[q])}return V}}function Sn(Ee,E,B,N){let V,q,ue,ce,Oe,Se,Ue,je;for(Oe=0;Oe<Ee;Oe++)B[Oe]=N.get(Ee-1,Oe);for(ce=Ee-1;ce>0;ce--){for(je=0,ue=0,Se=0;Se<ce;Se++)je=je+Math.abs(B[Se]);if(je===0)for(E[ce]=B[ce-1],Oe=0;Oe<ce;Oe++)B[Oe]=N.get(ce-1,Oe),N.set(ce,Oe,0),N.set(Oe,ce,0);else{for(Se=0;Se<ce;Se++)B[Se]/=je,ue+=B[Se]*B[Se];for(V=B[ce-1],q=Math.sqrt(ue),V>0&&(q=-q),E[ce]=je*q,ue=ue-V*q,B[ce-1]=V-q,Oe=0;Oe<ce;Oe++)E[Oe]=0;for(Oe=0;Oe<ce;Oe++){for(V=B[Oe],N.set(Oe,ce,V),q=E[Oe]+N.get(Oe,Oe)*V,Se=Oe+1;Se<=ce-1;Se++)q+=N.get(Se,Oe)*B[Se],E[Se]+=N.get(Se,Oe)*V;E[Oe]=q}for(V=0,Oe=0;Oe<ce;Oe++)E[Oe]/=ue,V+=E[Oe]*B[Oe];for(Ue=V/(ue+ue),Oe=0;Oe<ce;Oe++)E[Oe]-=Ue*B[Oe];for(Oe=0;Oe<ce;Oe++){for(V=B[Oe],q=E[Oe],Se=Oe;Se<=ce-1;Se++)N.set(Se,Oe,N.get(Se,Oe)-(V*E[Se]+q*B[Se]));B[Oe]=N.get(ce-1,Oe),N.set(ce,Oe,0)}}B[ce]=ue}for(ce=0;ce<Ee-1;ce++){if(N.set(Ee-1,ce,N.get(ce,ce)),N.set(ce,ce,1),ue=B[ce+1],ue!==0){for(Se=0;Se<=ce;Se++)B[Se]=N.get(Se,ce+1)/ue;for(Oe=0;Oe<=ce;Oe++){for(q=0,Se=0;Se<=ce;Se++)q+=N.get(Se,ce+1)*N.get(Se,Oe);for(Se=0;Se<=ce;Se++)N.set(Se,Oe,N.get(Se,Oe)-q*B[Se])}}for(Se=0;Se<=ce;Se++)N.set(Se,ce+1,0)}for(Oe=0;Oe<Ee;Oe++)B[Oe]=N.get(Ee-1,Oe),N.set(Ee-1,Oe,0);N.set(Ee-1,Ee-1,1),E[0]=0}function Pn(Ee,E,B,N){let V,q,ue,ce,Oe,Se,Ue,je,it,at,et,st,Je,ke,ft,yt;for(ue=1;ue<Ee;ue++)E[ue-1]=E[ue];E[Ee-1]=0;let Pt=0,Ut=0,Qt=Number.EPSILON;for(Se=0;Se<Ee;Se++){for(Ut=Math.max(Ut,Math.abs(B[Se])+Math.abs(E[Se])),Ue=Se;Ue<Ee&&!(Math.abs(E[Ue])<=Qt*Ut);)Ue++;if(Ue>Se)do{for(V=B[Se],je=(B[Se+1]-V)/(2*E[Se]),it=Wt(je,1),je<0&&(it=-it),B[Se]=E[Se]/(je+it),B[Se+1]=E[Se]*(je+it),at=B[Se+1],q=V-B[Se],ue=Se+2;ue<Ee;ue++)B[ue]-=q;for(Pt=Pt+q,je=B[Ue],et=1,st=et,Je=et,ke=E[Se+1],ft=0,yt=0,ue=Ue-1;ue>=Se;ue--)for(Je=st,st=et,yt=ft,V=et*E[ue],q=et*je,it=Wt(je,E[ue]),E[ue+1]=ft*it,ft=E[ue]/it,et=je/it,je=et*B[ue]-ft*V,B[ue+1]=q+ft*(et*V+ft*B[ue]),Oe=0;Oe<Ee;Oe++)q=N.get(Oe,ue+1),N.set(Oe,ue+1,ft*N.get(Oe,ue)+et*q),N.set(Oe,ue,et*N.get(Oe,ue)-ft*q);je=-ft*yt*Je*ke*E[Se]/at,E[Se]=ft*je,B[Se]=et*je}while(Math.abs(E[Se])>Qt*Ut);B[Se]=B[Se]+Pt,E[Se]=0}for(ue=0;ue<Ee-1;ue++){for(Oe=ue,je=B[ue],ce=ue+1;ce<Ee;ce++)B[ce]<je&&(Oe=ce,je=B[ce]);if(Oe!==ue)for(B[Oe]=B[ue],B[ue]=je,ce=0;ce<Ee;ce++)je=N.get(ce,ue),N.set(ce,ue,N.get(ce,Oe)),N.set(ce,Oe,je)}}function hn(Ee,E,B,N){let V=0,q=Ee-1,ue,ce,Oe,Se,Ue,je,it;for(je=V+1;je<=q-1;je++){for(it=0,Se=je;Se<=q;Se++)it=it+Math.abs(E.get(Se,je-1));if(it!==0){for(Oe=0,Se=q;Se>=je;Se--)B[Se]=E.get(Se,je-1)/it,Oe+=B[Se]*B[Se];for(ce=Math.sqrt(Oe),B[je]>0&&(ce=-ce),Oe=Oe-B[je]*ce,B[je]=B[je]-ce,Ue=je;Ue<Ee;Ue++){for(ue=0,Se=q;Se>=je;Se--)ue+=B[Se]*E.get(Se,Ue);for(ue=ue/Oe,Se=je;Se<=q;Se++)E.set(Se,Ue,E.get(Se,Ue)-ue*B[Se])}for(Se=0;Se<=q;Se++){for(ue=0,Ue=q;Ue>=je;Ue--)ue+=B[Ue]*E.get(Se,Ue);for(ue=ue/Oe,Ue=je;Ue<=q;Ue++)E.set(Se,Ue,E.get(Se,Ue)-ue*B[Ue])}B[je]=it*B[je],E.set(je,je-1,it*ce)}}for(Se=0;Se<Ee;Se++)for(Ue=0;Ue<Ee;Ue++)N.set(Se,Ue,Se===Ue?1:0);for(je=q-1;je>=V+1;je--)if(E.get(je,je-1)!==0){for(Se=je+1;Se<=q;Se++)B[Se]=E.get(Se,je-1);for(Ue=je;Ue<=q;Ue++){for(ce=0,Se=je;Se<=q;Se++)ce+=B[Se]*N.get(Se,Ue);for(ce=ce/B[je]/E.get(je,je-1),Se=je;Se<=q;Se++)N.set(Se,Ue,N.get(Se,Ue)+ce*B[Se])}}}function In(Ee,E,B,N,V){let q=Ee-1,ue=0,ce=Ee-1,Oe=Number.EPSILON,Se=0,Ue=0,je=0,it=0,at=0,et=0,st=0,Je=0,ke,ft,yt,Pt,Ut,Qt,Ct,It,Zt,lt,Mt,Lt,Nt,Vt,Kt;for(ke=0;ke<Ee;ke++)for((ke<ue||ke>ce)&&(B[ke]=V.get(ke,ke),E[ke]=0),ft=Math.max(ke-1,0);ft<Ee;ft++)Ue=Ue+Math.abs(V.get(ke,ft));for(;q>=ue;){for(Pt=q;Pt>ue&&(et=Math.abs(V.get(Pt-1,Pt-1))+Math.abs(V.get(Pt,Pt)),et===0&&(et=Ue),!(Math.abs(V.get(Pt,Pt-1))<Oe*et));)Pt--;if(Pt===q)V.set(q,q,V.get(q,q)+Se),B[q]=V.get(q,q),E[q]=0,q--,Je=0;else if(Pt===q-1){if(Ct=V.get(q,q-1)*V.get(q-1,q),je=(V.get(q-1,q-1)-V.get(q,q))/2,it=je*je+Ct,st=Math.sqrt(Math.abs(it)),V.set(q,q,V.get(q,q)+Se),V.set(q-1,q-1,V.get(q-1,q-1)+Se),It=V.get(q,q),it>=0){for(st=je>=0?je+st:je-st,B[q-1]=It+st,B[q]=B[q-1],st!==0&&(B[q]=It-Ct/st),E[q-1]=0,E[q]=0,It=V.get(q,q-1),et=Math.abs(It)+Math.abs(st),je=It/et,it=st/et,at=Math.sqrt(je*je+it*it),je=je/at,it=it/at,ft=q-1;ft<Ee;ft++)st=V.get(q-1,ft),V.set(q-1,ft,it*st+je*V.get(q,ft)),V.set(q,ft,it*V.get(q,ft)-je*st);for(ke=0;ke<=q;ke++)st=V.get(ke,q-1),V.set(ke,q-1,it*st+je*V.get(ke,q)),V.set(ke,q,it*V.get(ke,q)-je*st);for(ke=ue;ke<=ce;ke++)st=N.get(ke,q-1),N.set(ke,q-1,it*st+je*N.get(ke,q)),N.set(ke,q,it*N.get(ke,q)-je*st)}else 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V7qKHBNXM3gngPYHDbLrs4jLNerDddt/nkiAY2e5FlX7TiQDd4br3p2piXJHdBZVN80jg54iUEHS+mSuZfDdRMYf9z40ws+wTuwuG4Z8ntyG8z4mmgfmV4j5eQZvZKJxBhlX2flrO1agpMpa3woCTbOUNWdeWV7HSmEAqmp9HwA0y7LwxXlTc16oqvWfzMxnENG3oy5RCtwSZP7j8WV5O/cSZV4NgmT32AimJQTOA9E3ARhgvqK81PuH6N4iJM58mMAtTPRnVrzRAE9kostAJMTsoooS78PSX6ylw715N4JwCTMtJ1ZPMFONMjDGAF0qRYgY2BQOhefPnz5MYhlStiVKlCtrfJcD+EGkuihvDTWHSsXa/ma17wSDcAcRHQJGiAn3g3kdgGOJ6CQwgqFweJrgsOiDpgLDY1wKws3ihhZWwdLtDb6tY0cMO4HI/Ld9e6f47PoVLzxZMPWUQxwOPEFEEly31t+i5liBYEtuvruKgYdbEHj0hNKCmDLNXUP8ztrm8UGLbVc3sSgDkgIRLjjMH2YZ7sbDJ2Db26tbzlWkjpXv7vIpnuxklKWJcjKo6TEagf0MgXQkyvLFTR56zf6Sj9MYfFVFiffORNUpVikTjvkA54KMTy1YVT1ZoxOdO936CVEudBy4gpkv7m9Luu0/Tvi9JsodT4W4OjiLCt4C6NA+npdPGOpOgvHX2HmYsaCiNOfL8eaurPVdSaDfg/nR8lLvubH93ly1Z7JpmG8xUb4VtuYfOy2vUvhLZY3/XSIcHlbW7GPL8t7qPHdlrf9tAo5i5pMrSr0vyfuV1f7DycB7zLyiotQ7I3ZMLFFmUtduWfbSgqhrRmWN/ztE+KekyFN+nj73sNztr63YPcntdLwjj7UhxcfGPtC++bF/luHg18HkDIe5fP5070d718anTevqpsS6F9gPzFneKht/xVeXl3nv6KMeBnR4okTZxrym6UdtD04dcrgvqvGdaxA9DHBjMwfKhMAuXNU03WEYH4rRwGJ13LzS3NdljkWRgMD/Y4ZfIXTIvNL89YtW+QsNg2vFb15Z6ptzp+b+S/q2ude8BkBuRG6E4iwCGsvLvLcmCsriNf7TWOEZmyiDap2gU44syRYi36G9tSZ4mFLhBXNKPMWJzh3bTxPlZFDTY4YUgU93hnDAyI4udyELqN/dHhjdQb68bBP5HgOt4ciNSyjMaGhWGJ0XKYzmMAhm1ym4h3SfqbR4uhFlu/jCN6/+BxF9pzscGfzKqqaaL8YGC6UC7kKIjFF5BbudandXEepSarvhoIOMS444Qq4u7YMtFcuILe9xU4dvjLcHweXYr/6oyGGS0VXQobiprM7NpboFC6zo9bn4LBqGu9C/YdunsaQhYlE+cHkY/L3OOab7imEiRFkwWp2700pEd7Lvo4461xnPp7Kv8g7WeNt9gJxC+pL+7RZZGXgHUA8RjL/Eyi4W3OZWnhYvmKuy2ncVGXQHM/+potQrVsgOrT3HMfihihLv+RGi7HuPiA5jhSO6dL3ogignEsynwFfOLfHeFSuAEFlPVm41AeOVhcPnTs35oKradycMugLMt5eXeq/ZR+Zq3+/JIPHvtmVuw/hdsXQ2flI3vfOZqaz13UGgq5TCz+aW5fxmsHSfzDq9IcqLan1XGCAxGnQgypWrfN8ikx6UfPLBQMs0yYYhDx8ul3OlBDizxV+omOp9VeSrrGk6g8h4MpYoV67cdQA5XCuFKFtQZ8W6xdgp7AyyMVTgB+eWeC/ozT4Xr27+LTNfQ8BOgNbB4FvAZthtuquOmCT+yZG2pDbwLSZ13ZwpOVN7M3+0b9IftqaWmFJ3Cazs7ViFOoERuotGYC8CdQ3hdqK7u9lCvseEYsboPAdysww0BxkNfgtjhkUK1DQFFHKzI+zXkLtgqQuxJ1ITIqyAxoCFETkRouzNMuw/usVHIN2IsuSVzcmiNQDl9ahX5peZ1V/Y4q1sksMgs5QJ40jcPNn6aEv40xeT8bPtcd0uOixc6TvU6cBPABwBoAignUz4ALDuivpRRh4CrnkCxGVgvBMO43qnk64H8FXb0i15mAm3zC3xirXGbhJIk3tQ4aUEOpeB0gjR4veY1B/mluTZFhmx/JCJ/7TN8Y/6XQ33FA7Pv5YMQ8YUA1xLim8uL8v9j/RvI8rLwuDv90SU31zRVGY46WoEw1eJ72Ps1tss/7ciHLw5St7t63fwHV1ZlCN5qPmcCN8jJxMvauDArbEPFHJlTIRDpXKbTQCYzgZxIBSyvpPq1+XdnZu9FtNkTlfMGKUuY6Iv2tfnnVo4bM1tswbvs0iUKCvgL3NLci7r3CFqlWRwdX1ow6Hyuams8b1vE+UQH1ox3btsnzFJEuV4eZSravzvSEpHK4zDXn/yd8uO/+bVH8mtksXWafNK857bZ/2IP/wCAJ+IT7w55sgZhon3mXl107r6GfsQ5Rr/z4jwayi+vjfWzz5qLKnhEWu6c3m8YD7xwwZbLfOmDlvTTpQZdaFAcFo00LErorxw5Z6DHU7Hir4SZftBqta/hICj5fYgTOrz80vydiSy2feYna1rAuuJcIdiPkX89U0HzrMUzzCAzyxlHALiAhJXHOCH8nBYPsVzTCJzd+6jiXIyqOkxg47AJ9uCmDTaZa+7dmsQB49xYU9AIWwxRnpNmygL+R3bRpRj+0eF3dFkwdeiYMnjbisjr40cTyhw9s08M+hoDP6C6UaU28jkT+0ftD42sTqzn8+Ra9w+TtXt8MpVvuNh4EmSYBg77Sn8RHaAkjDCVlJ8SXmZ90HZ2xe+efUyEE23g50Yu0BCqvc226LD1gniExqxsnn/RaAvtc21ri1vtH0NyawuryjN/ZPdz527iggHgHklQC0gm7DLc2bkt4LRbDEfLcVQokTZUnzJvKm5i7rbXNUq3xdg0sshFZwoAVmxfSXDRTZlr6IwzymflvuxvLdolf+LZPLvOhPlyhqf5IQ9nRk/AtNyJh5lEv2aiT1Nn9R/KUpqKmubvg8Y5zHwosFqvGI8YiG8EVs+2pTOPs+Vtf6/E3BxPKwjZ4ZXM0uuWCaCnTPWvnFgsv9/hwL9H8AHxcuzLH6kFWXex7taoyeiXFXTdCbIeILB21uVKhOf4ihRDoV4lrg2dJ63K9eLRCzK8YhyZa1/KQFHynrhluD6LK9rLRGNsiw1r6tz2p5hg+FjhSmW4jFOJ30oxK1++QuzOmfqqKr2/QQG3Z4JRLmyxncfFB4Ti3CyRBkWn1A+1fuK6DXWohxUwWlyu7Vw2c5xTrd7VWfXC+kv2JtkF8aZSURjwfxIean3vES+Z8VKrKAeBCDEehQR/XHOFM+Pl6xtns0WroGBt4jxqQJ/h0DPMfjmLJdn6hEHkhQl6VXTRLlXcOnOQ4XAmi1BOM3IcY1alMWVYlSuaRNlIcC+VmUTYGmNzRbyPBGLcWF+xMq8p9my/2u1WZSHt1mUZV6ZR7f4CKQbUY7uxCZchJNhwAlWHzNTLTEsMuxCH5fHZsDoTv/M+HtFac6lA3VGXl3hG+N20XsEjBP/SlZ0YZCDK5xwTSeDxYWkEMxNlrIOF+tPVa3vw3Y/VebXWeFWNrCNCD8l0FkRObmyvMQ7b1G1/6eGgVtsTsx8+25f403eXK/HweZ9RDiVGT6wdXj9ipc+KZpxyscgKrFHS9o8qF9QmNaSw/gBEb7f9vpvK0q910VdL5hwC0LBN6EMR9DBlhFSluE2nSrADVGrlBR2Mcn4b6sVLOvsGrJwpW+sw4EPVIiPi6bo64ooV9Y2loPNl8hSR0UJtcgjqaiKRo5YwYzfVJTm2OVr26xg98t+RdaB0ttgz1tZ63t8r347rs6MZ1jhXiIUM3G+3IhID8l+oQgWSVYSRVmGwSdJloh4sivgorklOfd29X5PRHkvUeId3MxT5eFysC3KsUS50RH4ZCRly83SGFZqfkVZ7hud9/VmdeNs0zAXSwacVlaTnco8wHTgg0wgyhGSmlXbVR5l+dwUjhz+VtAKnSafyQ4+yiF/abTo0Zs1vnNMokfE9aI1iJLjD/FuXVjdcKDDcImLSwfXi0XVTV8zDONpCfJTYTVLqvtFiivRElsGy/pqtDx2JPe3cQ+3hr+t3ObnDDYeEZ9nZv5ORan3/u4+Wx+s4YIAB0RH4+wzTrTJm5ddOnMs2XnBVzK7Glc3/0wRXQvCP8oney5bXNv8DAiBOVM8EvDZq6aJcq/g0p2HCgGxIh9YELEor98WxMTRLtuCLA5AQpQb/JFiO8NzIi4UYlEuynfavscuB0FyVon1eU+zQiCk7HEFeQ4EwwyXSfC4k/4oDBUkg7puuhLl7kCqrG46FmQsiFdKuhMN+bC8xHt4T+mKklVKe5CUvUDHAEOxju4NuorkQt1LlPcG2Mja4k/scOYsI+AgsTarMGabJj8GolI7z/OyFw6PWsjeqN3zOQccb4t3UnTNqhpfjRBlSR/W4gt+7gtHjLD9/N5csXO86cyqsX/soP5RUZJ7cdSizCD59GxhgjxtypOqpCpzEvOd5WXex2T8GzVN8x1kPJ8oUX5zlf8Uw+TbYy3KlTW+fwLIqij1ittFh7ao1vcbYpoeDUSrqvadDcKfG3e3Tjzl6JGNyeol1cZV1jT9yi6q0LkxL2RWd5Fh/s1OZdaHFhtw1XmanoiyuMUYBu5hxqfhsH+akK0oURZXiHnTciQzQYc2UBbldh/lNleMePuqrG48lQxTLI7Vrz52+/Tjz7pmlh1ICP44XPfuoZ1vINLFoiwpBB2g46J+6Ax+lRU9KeDLQxSBxcXsm82tvoOzDOcIw5klN3Dfs2+jlDrFv2HL0txxBR52O65uu31QCnzCnqbGt/I93hPJNG0XLPnuaGkK/lO+K2RNJ5vLQHAB/CEzvQ37oY2+0ZaN5GVmvpWJQwTjfgbuFfeohbWNoxxs/E9cdAAEFFvfbPWF34h+/8QeGMmZvHhN8//AOD76OpHxizlTsve5PWRmk4hsC5kE9Fkq9D5MOqv8YM8+6QO7+8gkzQ60j3Ifvon00F4jIBblbFeEBO/0hTHSG7ESC0nOdhG27rFsP+OcNsIrRPnAUS6s3x5x0wiEGFt2h+FvVZg+zm1blaVPtpMwboRTvjV06waBTCTKbf5xEnF/ZI/KZ/y7vDTn6z32S7JDVY3vERCdIymYLAtHxRKK2B8fZn6zotQ7v6rW976k1GLw7gAHpsWmUqqq9d0P0AVSjpuAS0F8p+2rzbxLAl6Y2I6EJZC4dRxs/9gxnq4ozTmjssZXa6dsYrxVXpozO7odCRR0k7FSrkej1vV2izKrq3f7fa8FghZnu0xyOSUqANhTu6ilnZT3nShLUNhCeRYmYHlsMBtLHJB9dQsr+jBjpwMzzT/V79w1pa9FNZJU6YAMkyBHInpxn8kVn8OEa4moQ4aI3gohZ0ZZOLIrQitz9RzM13QPwbgI4OfLS7zi6hMTzNe1Rbey1v9Wm4/q3qwXtY3lBLNSXIBC9e/OiiWrPRUciVqUo0S5ssZ3GxFdG+9WaFFN080GGb9gxt0VpTk/iAbzycNiuH77jM7pDdOFKEcfHiW/eeTzzi5myA9nNI+wZNBeVVHi/UkkdzUd3U48wa0hDl3nNFxlDFxkvy69SW1XYeNvhoOvAUgiz5hYvLf4/0UD+iRLBkkVPJBL0slZKviq03A+pBjvM/CewaoRZH4rkv+b65pb/Fdku3JOIjLOAsEkhimfaQX152g2jdhzXLXafzMYkmNZBAox2Gk4HDNmT3Kv6Om8L17tX2U/SJJ52JzJWZ/01H8vHon27NRPE+UkgdPDkkJA3CzcjgibrakLorQoYl0Wv+MsJ2Fbo4UJo5y25ViaEOSJBRGrswT7SQCfWJY37gjZfsyBoLJdObY3hTFhlAtO7XnRrV4ylShX1fiXSuBPt5tnhMKWdVznACfbp9f0HswmxiqoxpA/vKorC0giB76qxv8sCF+OjSxvJ6krfGOynBCXiJESkFK/7PnZRTNPeTdKlIOBlukSiR7tLwUcxDIk6ZzAdCUI90SsOWiWmNZovwg9SUylAAAgAElEQVTB5GjWjJcqSr0/rqrxVdsWZWBpRUlO+w+nFB4gl3Ol+EIzcE9FSc4l7RZl5u91daUdu+/eWpTbsl5IMJ9t0ZMiF1O9peI3/RrAzxF1fLRli0NQ2B4NFhMrIQzz7t1Ne0qi5cgT0UOq9xEXnehZiNGjRUqdyUT3Rv3bk92HfesQ2nBkvODVKFEG4991y5//Rqz/buSBzqiSc6rYOn1uad6zIkdlrW+B+MdHz02sbG35yd+2/e1j0sPFktVXH7+9NLaASW+Jsp2hwel4FwRDBfmY2AqcYsl0svmuXDByWB0prgLtWS+YV9Ytf+HQdPZRTvYc9PO4XlVl7G7tJWsC81hczZgNgKokraAcsTklnuMSkXlxbXMNg0sI9O7sKdmziSgS4d9DS9qOpolyT9Dq9wcKAcmA0RJi2wosLhQSjCeE2eMi27WicxOCXdCWCm71lqCdMWOE14TDAIIWY9seC+NGRCzUunWNQIYSZVTV+B4GUYd8sLEI2FZZVleUl+W2p9GyfWpNXB4paU0T2wuQMDYw1CPhQPj3iZbGja4VY1EOcpiPjM0OUFndOAWGuVwC8OT6tKLE+4VokQaxKHcmylU1vtdA9HmxIDOrC2CYT9q+hMwvhuvf/XIgMG6fx8KlSx8JTTvjDIeke+uKKC/8sCHf6XFJJbLiZIhy1EeZQ62lndPSdemjHCk4InmU26++q2r8S5jUoxUluR1y/3Z1YhfV+o4jpvuaW5umnjhzrO23mCmtssb3RyL6Ucx+FLM6C6C/95UoK1bfm1ua+//iYdVOlCPuNZIZ4l+AWg2iiQRDHsomiGvOq4/dcWmU3MpDkgnjOXFxYuA/UPw0GyoApsMMMqTYzyRZL5YoS9GPfG9epX0Vr/j6EEKPv/GvP3wqc0Y/s4r5mrml3ts7y9ruEx2Tji7iikMPMOEzBXU9FK0iQ00y2PwZE2aBcXHUv73NJekdsSiv8tVM65x+sLIt6wUzflFRmtPnYOE0Ppe04L26bJcz15vlVMOUwcMMdoyAwcMNYCQrIx8Gew2W4GT2MsgrGSiYWK6cbO4pQacklflI7SKFernxsoAPXv/X7R/HPhxFMVq8unkpMx8JwsckGYGAOaaTDj5mYnaHAOF4mC5Z3fwTxXw7Eb1lMP39mJJsCQbssWmi3CNEuoNGQCOQqURZAkqcED9lqUjVqTHeA+GX5SU57Vfdb3zcWOFwmBIwZrssdNkYb6lmdVpvsmRU1vh/ToRfyXyd87NG0zPZPyxK3VRRlntj1EdZiDL7eUp0LTu9nJOk+pkk8X+7pan1pGyv+yMQDrRdLyyeGxsIFyt/1JWiK6L8wts783KHZ0ne1PHJEGUp4gDiV1Sodea8Q0Z+Frtuu1uHxcdHZesqj7L9MAHKLS/NOa2nT6StJ9N8yN/aND3TiPIr7+0aluV1/RmEUwHKBsvVuvo2Ed3bRTpEtjNh2CYF+/Z8729+pMJk279ZiOvj9eH1P+4uFeJe1ws8Q+A1UsqYgbF2iWzGRgb+UR9ef3vnOSLxAHQjyL7edxDzHhA+VcwLDKnyB5oL4JTYz1qkgInjVik5LXlyORw8QR6yKmuafg2ir8LCbRVTvQ91PgtVNb5/MWEGh/jrYiGOvi8PTwZDiPFhEuAoYSsEfAiF26JZG6SvncrQRf+W/dSHN5zWeS+LapoulQcVZjw/t9R7dU9nMV3fl3gHZThHmqYx2lSOMQwUwkChZJEBjNFMGCvZJsB2RUQhweKKkTSnjMWJWf26rYR1+8tL1rScqJRlF6Qhg37Piq8iwstzpuScmCjGzOxYvDrwMSSzD7i2fEpOQoV7kt6UtignqhrdTyOQ/ghkKlEWzUh6Mg88F8oPcpvf3XIm6xWrbudLsf6JVR83TWOT3pBUUz1pNBrw1lO/6PuSlB9O13tSlljcLwC+HiFazAaXkWncbmfDYN5lIXzEvNL8DW0WZfmSD7BlnRMysMpBhuR+/j2BZsq8FvO580q9j1bV+H4HougP+idQ/CtL0XIDYRcbjhkwMKO1qfXn67CueZq3dEVXRDlyRZ4rrhcHxhLlQueBHzGri7oreyyy2Fk9nFhJyjq1fOowCSCMNlpU67vFAF3LIT4saklvy6N8e0WJd3o70alummeQ8TJUeF6nOfaBOZOJcnSzEmCpXM4ch5JnK8NtGrRUHpA6EA7wdihczqSaScGIuqxYxGGEaI3lZPsKjlpD/vkzR27q6by2B/Mx/2FuqfcKORdZzuwiyyCDwi2bo5kS4sxDC5ftLJaMKCE2GiV1nPSrrPE9SkRnx6vc99LKPSM8hsO9ZeXz28QNQortYOpU8+Onngp3ZXWUojnbCwqMM6dPlwpUUX/cdpEkx7rHxfkcoIZ4D7Py0NjQ0sJdFbOR9Ixy+1KwfbtK51SDUUDsQDplTgB4CgwpKc0lxCSf87EEHiUkuL8IcHfnS27vAF4PppfDhvWXzhVPq2qbnwT4DBBZBH6QGd8xiK6ePcXTq+qIi9f4v88K9q0UkXPWnCmufVIWdpZTE+Wevhn0+xoBjQAymSjHkra2v+/z42rnLj776gUAnZLIcZAKZ2FSZYkmz7cJQ7X/SzD4YQLld15D5iOWPMq5/2mTRYL5Yq0hQnhiq+b8+ZXHfvdjIRK220S28wkQnRBPdgU+fm6J9/XKGv8GyaMsvqoVJd72+SM5lr1rJE0dM99fUer9TsQCPbFWEe6Hhfclae/e+S0iNlo+bq55Q8hGhyIpYetCpcJ15HBPJQPnE7Ofic5g4GvRIimLbFJMCxThK9Qa/iBapKSqtukWgC6E4htClnpNGSrkYNcIw6Fmw6La9oAiGW/QE/4W36RMsyh3pUP7ZoRMyXbSubSXnGUpDybnw22n3wJawajbheaZXVV97O58t1uUFf5aUZbzw0Q+Cz31qar1vcmgOWgNTamYkb9P+eGexuv3E0fA/szShMkw6Aix7jMwg4gnAVTQ6fsj8UkT7ynXGkGAWwBqJMZWcYUB82pxpQiHsMLX0ri6q5iCldvYu3t3YAeY3RKAKAV2wZhpgL46u8Tzf4mLAHy4nvP9oYBd1MRg/Gl2iefKnsZrotwTQvp9jYBGYH8hynE1LdfAhukQP+GsRI6D5CYOquD07spJdzVPpDIfXWJX5iN2MKgVzG8qZd0r+ZNlTAeizAiBpDhIpDHTRgXr/s4VyKTcszl29HkG8ddBKIhEv5P8aEmO1ZdamoLPNWTVBQrNA2+FIdeptCbW/1J+YMc6DryFgDFQeFWuvMWyVzjj5JsINKGrvTCwq7nVd32UqEpAIJyOn5OBz4ERYNB6hvWwWKMrq5tuVKB/SyETmUvkdRYW3Mz2tTz/paLE+3B0DSlqwTDOJdvv0SaA8qP5UYjUA58vzauVfjZxZOPipvX116d72epEztuilU1TDYchLjZ2RpM4+vg/Uup/MIxfgDnLF7amnDR92K5E5o/22eujzA+Ul3i/3ZuxXfW1q0EaLEVmtofrt8/snGGir/Pr8ZHPklE4ajaBTiXgOBBN6eKBqi9QBcBoYLDcEGwjoF4BW4ixBUQNCtYOttDApgowjCZuCfpaW6jplKNHNiWabjPW7QLAi0Q4jBljDNBRs0s8UtK9V61qtf8jkks34KAcp2firIm0u7sJNFHuFby6c6ohEAiyXalPUsRJkxLWn+0MoazI3e6NJ2ngioc77ewYuiWHwH5iUY4LTrR6V8LoMTaEwv5DeriK7va7+YYbbqCurpbbiPJ7dtYL5gZWNO21J363VSbrqn/nRYTgFhQU0Pz58yW/6D7W84T3mGRHkf/YY481Erm2Flk7Zx2ILitX7PL3ROZJUtS0GRab5zqe0NHS1BIMx8Bx9bsaJvU2dd7ePMr84NwS7wV9AagtS8bdIJoPpS4tL8v9e1/m02M7ImCXrZ809rtgurivaQNlZvmuAfCZBNyJfzoD1WBeD3BduMXaht0f+Qbqs7h4deBn4rcschDoPTvFJWOm02GWHDUpa3Vvdb94dfMbbeT+dBB+VT4l55eaKPcWRd0/bRCQMtZSNKQgprLe1j1hOEyycyzLXU9NfatNnHVLHoH9nSi/9tGOYldW1opEswoo4Ia5JTk3J494/JEdiHIXeZQHYk09Z2oj0Oba8udo9cQupWW8C+YqJrpYyvlKoYfe7mpRje8ag+i3YH60vNQbN1tMvHkjGTBIgjEPJdBsSWEoskgJ9d7KovvHR2DRB00FhockN3tcd6vu8JMbMSJeC+AjKH7fYiwPB1s/MRpWbB0oMtydPIvXNN8hwXs2USaSbCgPMvOXh03OPmM6yc1Y71rVav/LxLSLwd8gwkdzpuTM0kS5dxjq3mmEwPYmC7v9Fkwpby2p4kZFbh4/2RrElEIXdvkshCy2Lc26JY/A/k6UBbnKat+tZFCP5ZAlhVtzi+/0gfKN7USU9wQDLdNi8ygnr2U9Mp0RaMs1/X0QLiJQWRc+p1KSdBUYd5SX2dkien2bsHDlnoOdTsePFPNnXaVm6wm/ymr/xUR8GUC1YPWKYuO5uVNz6nsap9/vHQKVtb7rCHRrwqMYQRCvkvowitWiUMj60Njx4cahIMVdybx4TfO1rPi2tvfkvBSCaJ2Hso8+bDK154ZPdL9L1gRnsQr/HpC88Ly+vCTnZE2UE0VP90s7BKQQiThUSDGR3c0KrSFlk2Kp5CdlrtdtC2LSaJddylq35BHQRLmtPLQjR/zjyuMhyeBX0Br+RjT4LHnE44+0ifI3r5YCJKUS5NfKqjSaQWAg1tNzphcCTy75LHv0yLzpJsxSVjSeiC0Gf4IwVm1Z9WJtPFeW9NqllrY7BBZV+683DNzSXR+xGgMsmVIWMLCw2ldT3VWWj1RA+r0NXNjaGlgoxUJi5SHQT0CO1xLJXBEdV7Wdc9EQeA7Eb8052PMzIuI1a9g9eTK1xttr0k6bOj1cKhwfLUNjIFJhT3yUm1oUfC0KhfkONPgVmoMKza0Kk8dGqvjpljwCmihHsFu4bOc4Z5b7MYAqOqDJCDFhgT8Uvqi3AVJJaIUqa5ouA1OhIqyUFHBJzKGHaAQ0AhmKgOR6Nsj4W+ftMWCB8TbATyllvRANEE51GN5Z2zxeMeSJ721mLhZ5ifDCnCk5X1y8OnDBnCnZDySyh7fWBw5UIbWAQcvLp3jOiY5Zsqb5jNmTPU9popwIirpP2iFgKdhWY6eDELbYtiKLF4a099a32Nbk4TnanNxXxWqivBdBiSJ3FI46lWB8HuBcBtWEEXppfmn+e33FWY/XCGgENAJ9RWBRte9EwyC7OEek8TZW9BRx+JHyqcPEitxrt5u+ypTseGamxWsDPy6f7LnrnfU8NhgKnAfi4R547hK3iyVr/D+YPTmnx2qdVWsD82GpJ0HUiOHZh5YXkGTdsNtba5rPtBjHGMBmsVDPnuz6MFZebVFOVnt6XEohoBiQupi6DQwCmigPDK56Vo2ARkAj0N8I2GXhnaghkEuxusNqDd6TSEGZ/pajP+ZbsjpwNhGHj5nsebKr+RbX+m+cU5JzY3dricVYKTxGBBOgY+dMyV4Ur3/Vav+l5VNyOpRxT5paaNeL/jgCAzvHg60J3UYMrBADMPsBxgGY7/x80jP7goAlGRQzoHmzqN2CPpDb0UR5INHVc2sENAIagf5FoLK68VRLYfex0/Iq+3fmwZmNmc0lqwM/ZoNHzjnY83MisqtIxjZmNpasab4JhufPcw6mbXHJb63/RQAnwaC/lE/2XBavX2S+wE/mTPF0yAijifLg6HxIVjF2JK3eIZE30UW/7P4ynsl9NtHu+/TbsEv8lzODKB80ykTWICT00EQ56eOmB2oENAIaAY1ALxGQUtOk6NnZJZ7N8YauX89Zm0OBXwE40zCM42YfnCUp7fZpb69rnWGFrT8Py8/+4vTR5Is339La4MwQhU8on+K5PbZP0kxKW5R7qfUh6K6Jctega6Lc+8OoiXLvMdMjNAIaAY2ARiA5BBavaT6GGAe6Jmc/fQRRKN4si1c3383gr0MSYBF+4WLj5SNLsu1S6Mu2cI6vseXHBF6niHLKJ2ff250079Wxp9XX/Oc5U3Iu1EQ5Ob2l3agoUf6r96/4btZ3007+eAIbMGBKBd79tAVCwPqdUlQN0Bbl/fQQ6G1rBDQCGoEMR2DxusAEDvMPZZsO07jn6ElZazpvefFq/38B2s3M7VksAOwgggVQLgDJu/yR25t96RFFtKMnyBbXNj88p8RznibKPSGVIe9HifLfvX/HRVkXZ8iu9DZawsC6HZoo65OgEdAIaAQ0ApmPwJK1LQcrZd0N4O05kz03Rv2VJSPGktWBTSBewYwTu0aCqiRLRtZkz6yuLNNiRQ41B2YphcNBPB0wNs+ZnH2TJsqZf67sHWqinJmK1kQ5M/WairuaMWNGzs6dO2dIyWGl1KEApNTraCJyMLOTiJzMHCSidcy8log+AVAD4LW6uroerTepuGctk0ZAI5B6CAgpfmtt4HJmPtlJjis/d7CrdsnqwOUg/ApEFwP0lpNU0M63bJJJZGQbyhqlwjiUiS8B0f9MZN981MFoenttaJZi62QwHwLCViJUmYax7MiD3PIdtk/QoPZRTr3z0G8SaaLcb1Cm1ESaKKeUOjJOmGOPPdaxevXqU5j5fCL6EjMnU7FHfmzeJaIXmfm/9fX172ccUHpDGgGNwKAjsGRty0lsqT8AXACitcS4bXaJ5/+6E0QyaCxeG/gRGN8gIEigVxxk/OfIye6PE9mAJsqJoJSmfTRRTlPF9SC2JsqZqdeh3tW4ceMmM/P3lVJni9W4n+V53zCMP2VnZz+xdu3auKVi+3lNPZ1GQCOgEegzApoo9xnC1J1AE+XU1U1fJNNEuS/o6bGdESgsLDyAiG4QCzIgCfkHtG0jor/l5ub+vra2tr0y1oCuqCfXCGgENAJ9QEAT5T6Al+pDNVFOdQ0lJ58mysnhpkd1RKDNxeJKAEKSPYOMz1YAv7j44ov/edNNN+3jEzjIsujlNAIaAY1AXAQ0Uc7gw6GJcmYqVxPlzNTrYO7qgAMOmBoOhx9j5pmDuW4Xa60wTfOyTZs2vTnEcujlNQIaAY1AlwhoopzBB0MT5cxUribKmanXvuzqgAMOGB4Khb4H4KtEVMbMjQCey8rK+uX69evFetveCgsLLyKiPzJzdl/W7MexUibzrpycnOu1/3I/oqqn0ghoBPoFAU2U+wXG1JxEE+XU1EtfpdJEua8IZtb44uLiC5j5TmYe3sXOthiGMW/z5s2rDz/8cGd9ff3dzJyq1Yc+Ngzj3M2bN3+UWRrSu9EIaATSGQFNlNNZez3IrolyZipXE+XM1GtvdzV16lRvQ0PDfQDO6G4sEa0OBoPHulyuR5j5871dZzD7E1GQmX9QX1/fbanZwZRJr6UR0Ajs3whoopzB+tdEOTOVq4lyZuq1N7uaMGFCWSgU+g8zlyY4rhZASYJ9h7wbEf1pzpw5Vz711FOREpS6aQQ0AhqBIUJAE+UhAn4wltVEeTBQHvw1NFEefMxTacXi4uKvK6XuB+BNJbn6WxYietXlcp2xYcOG3f09t55PI6AR0AgkioAmyokilYb9NFFOQ6UlILImygmAlKFdiouLL1VK3Q0g6e/udIKGiJZlZ2ef8Mknn2xLJ7m1rBoBjUDmIJD0l21TC0ukcsLN6064q+7YTwhootxPQKbYNJoop5hCBkmc4uLiK5RSdw7ScimzDBHVEtHxmzdv3pQyQmlBNAIagf0GAU2UM1jVmihnpnI1Uc5MvXa3q8LCwp8C+M3+t/P2HW9wu93zN2zYsGE/xkBvXSOgERgCBDRRHgLQB2tJTZQHC+nBXUcT5cHFe6hXKy4uPk8p9dBQyzHU6xPRWrfbXd45L/RQy6XX1whoBDIbAU2UM1i/mihnpnI1Uc5MvXa1q+Li4mOYeSEza+c1ccwmWpaVlTVv3bp1e/afU6B3qhHQCAwlApooDyX6A7y2JsoDDPAQTa+J8hABP8jLFhUVjWfm9wCMHuSlU3o5IqryeDzH6yp+Ka0mLZxGIGMQ0EQ5Y1S570Y0Uc5M5WqinJl67byroqKil5n5C4nulogwcdw4TD3oIEw7+GAMz8vDg88+i+p16xKdIm36EdGDdXV1F6SNwFpQjYBGIG0R0EQ5bVXXs+CaKPeMUTr20EQ5HbXWO5mLioouZOaEqtPNP/JI/Pi882xy7MnK6rCQZVn44S234NmFC3snQBr0Ngzjqs2bN+93WUDSQDVaRI1ARiGgiXJGqbPjZjRRzkzlaqKcmXqN7mr8+PFF4XB4FYBh3e10WG4ubv7hD3HGCSd0C0g4HMb5P/sZFr7zTqYBZxHRSXV1da9m2sb0fjQCGoHUQUAT5dTRRb9Loolyv0OaEhNqopwSahgwIQoLC/8O4OLuFphQVISn7rwT48aMSUiOQEsLzrzqKry/Svh3RrUtHo9npi5IklE61ZvRCKQUApoop5Q6+lcYTZT7F89UmU0T5VTRRP/LceCBBx4YDAZXM7Mz3uwHjR9vk+TCUaN6JcD2Xbsw9/zzscfn69W4NOj8Yl1d3ReJqFdFsNJgX1pEjYBGIAUQ0EQ5BZQwUCKkAlG2f7lY0jrt3WVXrw0UBgMxr8WAmfQnp+8SaaLcdwxTdYaioqJ/MPN348k3Mj8fr957L8aMHJnUFh567jlcd9ddSY1N5UFE9MO6urq/prKMWjaNgEYgPRFI+udel7BOfYUPNlEOWcDGHUFkuwwUD3egwa+woykMEDAix8RIr9nla6mIZCDIWLtV9hL5iIwZ5oA3y8DaLUE4HYRgmHHwGBeMXn6C1m8PQYq/HzQ6rsGwRzg0Ue4RorTsMG7cuBFKqXpmdsXbwL0334xTKiqS3h8z49Qf/AAfVFcnPUeKDmwyDGOqLnOdotrRYmkE0hiBXv7M792pJsqpr/XBJsoNfktKAqA5qGyiLERTyKS06N+7ei0VkdwTUDYZLsg128VrDCi0hhgFeSZ2+iyYBiHfY7S/L+TaNIA9zQrDcgy0BBlhizHca8qzAhRHcBDr+qTRvSfZ0YU0UU7FE9N3mYqKin7AzH+JN9Ppxx2Hu3/+8z4v9PHatTjpkktgKdXnuVJpAiJ6rq6u7rRUkknLohHQCKQ/Apoop78O4+5gsImyCOJrURCSKUR5zZYgJo/dS5SFHApR7PxarFtGqqhje5OF3X4LpvhYMDBhlBNb9oQx3GPC4ya0hBjbGsM4YORey/CmXeEIuc4z7X2OG+GEUmwT5MJ8B7Y3Crm2nyUg1vcxeXtJeG/2rYlyb9BKn76FhYXvAjiiK4klR/Lbjz2G8WPH9suGvvvLX+KFysp+mSuVJjEM4/jNmze/lkoyaVk0AhqB9EZAE+X01l+30muinLxyW8NsW4FdDsLuZrEkK4QVeiTKYmEWF42auiBKi1zCsbGmPogphS58vKkVxSMixHrTrhCmj0uuKrEmysnrNVVHTpgwYWIwGIxbGeQLs2fjwVtu6Tfxl3z4Ib5+5ZX9Nl+qTERElXV1dXNTRR4th0ZAI5D+CGiinP46TFmLcjq7XoibhdMk20e5qUXZlvIct9Gt64VYlIfnmMhxE2rrgygpjFjT5e9ief5sZwij2lw5dvgs2+LsafOB7s0x1ES5N2ilR9/CwsKLANwTT9pHf/tbSGGR/myf/853ULN+fX9OmRJzmaZ57KZNm95MCWG0EBoBjUDaI6CJctqrMP4GhtqinM7BfJYC1m2LBO6Jn/HENp/i7oL5uiPKbgdh9DBHOzEWf2Zx5ZhY0PugPk2UM+9DW1RU9C9m/kZXO/NkZ6P2v/+Faez1h+8PBB5ZsADX3Jl5he2I6PG6urqz+wMjPYdGQCOgEdBEOYPPwFAQ5c5wpnt6OPEv7pzZQki07Ws8RE0T5SECfgCXLSwsrAfQpQPynFmz7LzJ/d2kCMnhZ56J3U1N/T31kM5HRM35+fljVq1alXEJo4cUWL24RmA/RUAT5QxWfCoQ5QyGd8i2ponykEE/IAsXFRWNYubt8Sb/0bnn4roLLxyQtW/8619xz9NPD8jcQzmpaZrnbdq06ZGhlEGvrRHQCGQGApooZ4Yeu9yFJsqZqVxNlDNLr+PGjTvWsqyF8XbV19zJ3aG1ftMmlJ93nh10mmHtqfr6+jMzbE96OxoBjcAQIKCJ8hCAPlhLaqI8WEgP7jqaKA8u3gO9WlFR0feZOW5Vuf/88Y84esaMARPj7GuuwRvvSma6zGlEtGPz5s2je1PWmpnN5iC+xMDpDBwNoBCMYZmDit6JRkAjIAgQIcCMOhBWEuHZHCeeJqK4PmiaKGfwudFEOTOVq4lyZum1uLj4FqXU9fF29fp996F04sQB2/TrS5fi3OuuG7D5h2pi0zRnbtq0aXki6/tCfBIr3AlGWSL9dR+NgEYgoxDYDgM3eZ24u6uHa02UM0rXHTfT30T51sCteL71eTjhtv9v73+z2v7tgkteZzfcFHnfxW640PH9yGuxf7Ii4xAZH/v+hHw3XMnV5chYzWqinFmqLSoq+iczfyfert5/6ikUjho1oJs+7bLL8O7KlQO6xmBPTkQ/qqur+3N36zIzNQfxSwZu4EjqdN00AhqB/RUBwr+9LnxLAoJjIUj6i0GXsE79k9TfRPl7vkvxYMtDcCMbWfAgC1lwsfxvtv2aW/5O8nrk75F+8l7M3+V1ioy3X+fI+9Ex9ryU3T5vyahsZDlSE+ughSEh8Zoop+Z5SFaqoqKi/zLzF+ONX/nMMxgxbGA9AJYuX46vXH55sltIyXFE9EBdXd23uxPO38o3KMaNKbkBLZRGQCMw6AgQ4fkcF75MRCq6eEYR5eWfttrlhaXlZZtoCSm7AERuViSXl5QlZgZGJ1k6eNA11scF+5soX+q7FA+1PIwioxhfdX0VDjhsK7D8b/S/DnbCQW3/Ziec5ISDXXaPSL/Ifx2Q1wLNY10AACAASURBVLoez8oBXytssp3KRHnjLoUxecagE3lNlPv4wUix4YWFhVIcI241ubcffxwH9FPp6u62ft511+G1pUtTDJ3kxSGij+rq6mbFm0HcLaDwgrYkJ4+xHqkRyEQEDMKNOW66KSOIshRtkMpp0fbJtiAmjY5UQ5MWCDHqG8I4aHSkqENNfRCTx7iGNAfuYB6q/ibKEYvywzjacQxez391wLbiC4fw8Y4m28qcykR5/U6FkAImjjDgHET3EE2UB+zoDcnEhYWFwk7jlt175d57MW3SpAGXrXrdOpxw0UWwVLshZcDXHMgFiChYWFjoff/990Od15HAPV8QK7RP8kBqQM+tEUhPBCTYz3Bhsodos+wgrS3K67eH2iubBcOM1VuC8LoNhBWjMN9plxKurmtFWZEbIQvYsD2IyWP3Eul4KuRQA0JbX2h/2zH8aBg58X+oUrX/PS2RirjjRpyO00dcEffEJiq/TZQDD+Eo5zFYmP9at5+AROeMThLbP6QU1mM6LFdpQkS5L2vJ+snqV4iyPIxJ1b2JI432wiQDLU+g/iU0NkXS7ublFiC78KQB/zYKW4AQ9N4208DRHhdljpmytwAk0L+oqGgZM8dNazHQWS9iRfztP/+JPz6SOemHiai0rq6utrMa/K18mmI8k4B6dBeNgEZgP0SACLd53fTTtCXKe5oVfK0Ku3wWRnhN26o8zGOiJcg2OZbKaeu3B3HwGJddJtjtMGw3jGyXgXxP/JJqV/qvwAOtD+CQ4HC8uOWE9qNx7Yh38ah3Xdyjkur9rxr+Fp7I/bTP8gdUAAZM5NNwbB65qXuiHPgMgdpb2vu4x58Lc2R5fLLeqf/mvK+g2TMXbsPd49OcK/QZxmy/tX3uhmFnw5cTf63+6q8Ut+eflSdOo62EX3/NHw+sMdtvgyvUps/sCfCU2J/lAW2aKA8cvEVFRR8wc1wXgX/+6lc4uTz+ee6rZOFwGJ/W1WHtp5+idsMGvFRVhZaWFpimiY/XrweLv1qaNiL6Ql1d3T7XX75Wvp8ZF6TptrTYGgGNwEAjQKjJdZOdBSctLcpChC3F+HRnCAeMdNoERb7LmwIR4ixlh9dtixDlcBtptiygtKh7a/KlvksgVthDgwWo2vbVdjVclr8I93ur46plf+lPIDtAbxjyUT/KvpFImPgmRZRz5sLJPd8AuEOfoXDnbe2y7Mw7G02eOXFlS/f+hTt/C7cmygP9NTlo8xcVFS1h5mPiLfizSy7BD846q1/ladizB+8sX27/WVZTg2C46+uCD2prodKYKBuG8e3Nmzc/0Bm8plauBqO0X0HVk2kENAIZhYDXjXwi2pOWRDmqiY07QpgwKuJ/LG3D9pBN/cOWuF44kOOOWI/FJUOux2P7dqXNV0Iv46PwRyhoCeLMjXstpm+MGYWP8/PiHoD9pf9/Wv+NZeEVONiYguUjPhpQolyX9xX4PBUYm5MNZ/xLAFsGo/UzuD/9Tbs8odHnIDwsvgWuv/rv8kd8lKXJB2lYtgG3Y+DlcX16K8xWbVHOlG/koqKi15j58/H2c+ZJJ+F3V1yBmvXrse7TT5Hr9aKwoAAlEyfaVt9EWzAUQtX77+PlykqIP3LUTmwQoWj0aEyeMAGTJkyw//7fN9/EQ889h5ZgMNHpU7KfYRi/2Lx586+7IMp7wIj/pZ6Su9FCaQQ0AoOJgItQ5nZTTVoT5a4AE2ty2w34YOK5X6ylg/k6qjnqo+wwCQcMH7zsFzqYL7M+boWFhc8DOCXerg4rLUXRqFHYsmNHhy7DvF4ce9RROP344zEyPz8uKLt278bT//sf3li6FL5AwO7ndjoxq6wMR86YgSNnzkSe19thvLhbXHzjjXh+0aJ0B/ue+vr6S/Yhyi1pbCZPd41o+TUCaYJANMYm44hymuCflmKKa8pDLY/gKMfRPQbz9WWD6ZT1Qqxy44cbPVq9+4JH57GaKPcnmkM/V2Fh4dMAvhZPkrEjR2LK+PEYM3IkZpSU2FbetRs34pPPPoPDNHHPzTdj1IgR3RLl7/785whbll3h78SKClQcfjhcru7dmlqDQZx51VXpXojkhfr6+n1yVPe2DsDQnxItgUZAIzDYCGiiPNiIZ8B6YlGWPMqF7XmUo7mRo7mU23Ik2/mTXZCcypG8yfvmUW7PuxyTgzmaY5ktsy2Pcmqnh9vmY4zKoUG/wdBEOQM+TDFbKCoqeoSZz+luV289+ijGjRnTwdVi4+bNWL9pk21V7tBaWyP/dLvbX35tyRIcPGECJhQX9wo88WU+9Yc/xLpN3Qfv9mrSwe28or6+fp+MIpooD64S9GoagXREQBPldNTaEMscrcwn1fPsinzUVo2vrTKf5D2Ovp7VVnHP3VbBL1qlT97Pprbxnar2tY+PVvpDFkpHeQa9oMcQw9zj8poo9whRWnUoLCy8G8D3uhO6esECiKtFQu3dd2BHNx/ZiUAnNHjfThvr6vC1H/8YddsjKQnTqRFRQ11d3T7mdk2U00mLWlaNwNAgkBFEWVLESf7kETl7A1rER3l7YxhjhjmwuSFs51SObcXDnXD0EBw2NCpJ/VVvDdyK51ufhxNu+/9cbX+cUsrathq77Gp6Lmr7N0f6Rfpn2e/bY7jtNXLDafdpe8+u4CclriPjpd+EfPeQlInurA1JMzjS6+hQWCRoMRp8ln3WpDUH2c68Ev23vCZp1aw2d8i6hrAdZEptDk8SYJpM00Q5GdRSd0xhYaEEm/2sOwlXPPMMRiZaxvqtJYAUDTlmtuQs7JeN123bhm9efTXWfBo/zWRfFnI6HAjFybzRl3kBcF1dnUlEHX4IkiHK8ml1OWAXrNJxMH3Uih6uERhABOQnV6ifZD2TGhrJtrQmylKBTyK1W8Nsp4nzuAw708VBoyNV93b5LYTCsHMtFw13YFtjGDkuAzlZBrKdyZGTZIHW49IXAXkI27gzBIdBaGpR8LgIpiFJ8oADCyLZVrY1WvaZawwoNAYs5HtMO4+35PYWUrwnoBBojaTGkBLqo3LN9pyMY/MjBLu3TRPl3iKW2v2Li4uvVEr9vjspP3jqKYwdNSqxjbyzFAiFgKOPARLIiuEPBNDa2gq3y4Wc7OzIGtGnuZiYtz1NTfjx736H/y1eHLFYR1u0b2LS2b2G5+XhjBNOwHFHH42SAw/E6JEj4W9uRv2OHXjs+eftjBvNLS29mDF+VyLKqaura47t0VuiLJ95j2svLP0imJ5EI6ARGHAEkq0BIIKlPVGWUtVCTlpDjII8E5/tDGFsvtNOji+lrYd5DKzbFqlcKrmVpUmBkmg56wHXjl4g7RGQc7S72bIJ72e7whiTZ8LlIHyyLYRJo532+ROOkJtl2Dm9R+c5IBkw1m6NlFKXstbyRLtpZ+QcylxSGMdOJecxMTwnOWufJsppf7Q6bKC4uPgCpdT93e1q6eOPY/zYsYlt/N13gWBrxPXCuTd9Zuzg+u3b8fwbb9h5lNuzaTCjuKAAR0yfji8dd5wdPNhVu/fppyEV/ITI2nS5F0RZgg9/csEFuOTMM21iHq9t3bEDX7/ySjtgsa+NiArq6uo6pAzpLVGWtI+DWaa+r3vW4zUCGoG9CARCUnuj94ikNVFe/lkr8rKMDhblxhZll6qWLzMhNSNyDGzdY9nJ8sXiLK05qOwiJLppBBJBQIiy3F5IWfRYi7I/qDCtOBIoJWXUhUiLW4WcPSHKTpPsB7jiEQ5sbbQgFfyk7WizKEfXHp5jIiuJGw5NlBPRXvr0KSoqOpWZn+tO4kUPPoiDDzig502Jy8Xbb0X6iUW5k+tFMBjEw88+iwULF0YKiTDbVmRPVhbEshzNm2wS4dT583HOl78McYvo3Lbs3Inf/OMfeOa112DJmuLjIPN1Q5pzPR7864477LR0HVqccStWr8bJl17aHwVPJtTX13fwGektURZrsna36Pn46R4agVREIBgGgkm4YKQ1UV6zNYiJBS7bH1TcL0blOrBpVwjifxx96g+EGFt2C3kh2y1DqIr8fdyI5K67U1H5WqaBRUCI8k6fBXGR2LwrhIJcB1xOwoa28uiyupwzcc2Q8+fNMmziK4R4YptrhrhvWAz7xkMsznsCFsYOc9jW6JFeM6kf30D9S2hsigRW5eUWILvwpIEFos3XWgh6b1v0i6a34/an/oWFhVIdp7K7Pb9y772YNmlSz7A0NwMffgB4coBZHatii5X2pr/+FZu2bIHTNG23h5PmzsXE8eNBRFDhsJ3d4n9VVXbOZWVZtlvEb668cu+6QoTlTxu53bx1K+5fsAAvvPkmJOivvdx1J8Kc5XLht1deiTNOPHHvXI2NwLp1QLM/YvkWi/n4jg8DEkT41rJlPe+7mx4ul2vqxo0bO5RW7S1R9u5NINInWfRgjYBGYPARSNb9Iq2J8spNrbYvaEtI2VfbYvGTJv7I8tQvREWMeKEww+0k28onvszShJzoNnQICGk008RNXIjy+u1B5GWb2NNs2T7uQoodJmyyK03ce8RfWfrlZpm2b/L2xr0uPuLDLD7yRfkO2wVIggL9LcoO+BNinUxrrr0VCGyMDM2eAE/JT5OZpldj+vpF06vF9rPOxcXFM5VS3Za6/O/dd+OwsjJs2b4dOxoaMGr4cIwtKNgXqY0bAEnlNno0MHlK+/uf1dfj+jvvxB6fDxPHjcMV55+PA2NTxdk+x/In8uFcv3EjxMUiy+3GL77XlpAjlvy2W6rbxhDh0/p6LF+9GuLW0dDUZFuqJVPH1EmTcMjkyXDGuoFYFiDZOeS/sU1kFtnb2h333487H3qoryfiiPr6+vdjJxkwouzzA34/4MkGcnO7lTvQWA8rFIDbWwCnO37fMFuob9kOMfeMdY+Cy+janaavIOnxGoFMRaCvv19JU5YB+6JJQFNiRZaMAb4WZQdLFQ+PkBYpYS2kZc2WCLlxOmD3kb/LNePuZoWJo5y9calLQBrdJRaBlhCjpr7VJo1Rq5P488rP6dotQTgdZGcqEReYVL/KFO4gD2JySyEZVKREdZTcisuFlESXMycPX+LWI4F+UaIsvsxyLsVlQzKvRKNwxZ95c0MIw7JNO7AvmaaJcjKope6YcePGHWxZ1pruJLzrmmvw9ocfdvDZnTR+PL57xhmYNnlyZKhU3Vv2UYR8zjwUiEkn98wrr+C+//zH9j++9sIL4Y7mWG5zv4h8KbaFikcD9aLvxQoWtSjLa/J3+0O818Lc4cu1O99lXxPQlaVYKgxOm96+4sPPPYdr77qrr8qbW19f38FiPyC/X/Vbgc11e2UdOwYYV9Sl7Ds2LkXAt81+j8jAyPGHIzt3Xx/0IIeweOcHCFiRwEYhyXNGHIZsM6uvmOjxGoH9BoH/z96bgMeVlmei79lqL5U2a5flRfK+yLbUbRrobmggbAkhMGSAS5JhwnJ7woRAINN3EgzNJHnSJCRz72TmAhPmyQoDZAIZ0u5utgvdNG1LsixvtNu7LKkkWWup9qpz/vt859SRquSSdGqVSvp/P360/ev7n6p6z3fe//22JFE2d5fI163JhPEkkN5EJEGP1M2FVP1niuAlVAb/XBLttYpOlim6XCkRzUq8iokoU9R0R70R9aDvHYqof56aBy9JzkCkstqVX0R1PXChdZH8QhQFnfTSYVHdbUVj+s2Y6XBBBHkhoiEU0xblF+R2EY4ZUguTaFPU2WkXFp+G5LImTpRzQWvj121vb29JJpOjizNdll25obYWHU1NuqyBJAwdzc244/cjGovp7j8fee978ZajR4GrLxtuF+SOsXdfxsKTyaRu7UaZ+fToiCmfSOmLjcqaceKF3jzN3y9GmvVGSxpkiihTR2T5grTXsf77NOK8EvxE5s8NAPF4Zg2XCzh2fPF3f/2d7+CJv/iLQjfxzX6//9n0TopOlAmnwSHDk8oshMPRw3RwIWP+sdA0Jm+/mPE7xeFF0+5H71vntdAdXAvezvh9h6sFB72pm6NCkeHtOQJbAIEtTZS3wP5W3BKJUJJet6VG0bXhE4EkOuoU3RqtxiXBZRdAdUiOsL2OP0LMZ4P5Yb58UNu4bXbt2uWLRCJzKxHlbpItyDJ++bHH8IFf+iXIigIivnQo75++/328fu9efPyBXqM5kWSSL6zmn2wenlskw5pB8FjqWDh9qlAxI8omcTejyWak2CSAQspYmL5SobHXONin1xu+Ayx3tfBVA4eWIsp//jd/gy/8j1UNQdbcWEmS3jYyMvJ0SYkyeUCfv3j/XA4fyMiQSBVIcjF1tz+jrqQ40LLnjfe1v7JwHbfDS/dQVKHZ0YBjvmUHItdEgVfgCGxdBDhR3rp7vyFXTiT4xkQcdV5JfwJMEVeSKJB0gRPl4mwZJ8rFwXGj9PLoo4/KV19+2fAQTJFQXdCQ+t7tcOC33v9+fOx977tvyldv30brzAw8kTDQ0gLsWuXAX3qkOj1SrKkGUdajyYYThqEdTv0ufVQ9giwY/swmcTYzcIhm5DQt8py2pvsmf+sWMJZJAtHeDmzvWKz6+Oc/j2//8IcFbZUoim8fHR39l5ISZer86jVgIbg0DEXHD+y9b+6amsD49R9BTaZSjQPw1u1CddPB++rOJOZxZnZo6ZAkgOPVB3WtMi8cAY6ANQQ4UbaGE69VJgTuk17MJeG0ifpnaiVLL8oEn6VhOFG2BFPFVCJTtdbmZmKmgk6OUwTZFDQQaf6Dj34Uv/krv2KsyYzomlHjCxeAwDxw4CBQU7OyRVu6HpmIMLWnqDJ9r/8tJb2gn+n39HO6DMOUW+gRZNEgy0SS6WeaE/1s9knfm1HlbFplkoiQ9GJ5Nr7jJwAz6QmAw7/8y5ieny9oL8tGlOnTmDTKdJiP1tDWCv2gTJaSiAUwP/Ey1EQUDm8DfNv2GDhmKeOxKdwOj+iH+dqdLWhzNBaEB2/MEdhqCHCivNV2fIOvdzlRpsNs82FN9xSutMN8GxVqTpQ36s7kNy8iym0tLTHGmGIS5XSSLIoiHn/ve/Gp3/iNpQFMHTAR09ERgKKzDodxEC6NaGbMKJ0oExGmPkxSTD/rpDmZiiwvI9A6QU8jxPQ9kWRJNsix+d8kyOnyi2xEeX4OuHQpEzCKJFNEOVW+++Mf48Of/Wx+oKa1KhtRLnimvAOOAEegFAhwolwKVHmfJUOAnu7qT295yRsBTpTzhm5DNmSMCe1tbWHGmIMO51EEmb7Sf52fCgLe+9a34vO/9VuZ86cTsubZsSuXAfIlJqLa2Ag4XQCR0dlZI9JcVWW0TXey0K1YNCOqm/6VpBjm79K1y6YWmUgwJSEhqcXi9+bvUmTamPjqWftu3wKmpow6ZAmX5qEcjkTwpg9/WPd1LkIp/WG+IkySd8ER4AiUBgFOlEuDK++VI7BhEeBEecNuTU4To0iy3uDUKaHtv//3gAC4SeVLEWS6l5REkiyRS4+AN5w8if/8H/6D0b/pLGH6HhPRJKJ7+zYwMb40B1MOcfgw4PZYIMqU51U1IsrJxJJW2Tzkp0eRU9pkWUlFlCkdpZJJmM0I8lpEeQW04okEfu2JJ/CTgQzr45ywTa8siuJjo6OjGULnorte5D073pAjwBEoNQKcKJcaYd4/R2CDIcCJ8gbbkDynk06Ut//VX02CsToix3o0Wc8kKhlEGdC9kr/21FMGeTW1yWZE2fyZiCnpYymKTLZrJMWgbHdmCup0f2TT8UInxilNMumGTflFgqLMqb8tJ8oUSSbtrSm7oEQii5rl1IG+RTKfpqm2gNO5K1fwiaeewit3Ugl1LLSxUKU8PsoWJsKrcAQ4AuVHgBPl8mPOR+QIrCsCnCivK/xFG3yRKH/jG2LHJz5xC0C7TMRYpAyQIpSU/IK+r/b58L0vf9lwoiCiSqSXortUzChvOonOpgvORpR1yUWKIBM51olz0vBjpsiyllySd+iaECLIopFymogyjU2kWZdgpAgzzckiUSabO3LuGLhyBd967jn0X75cNHzNjiRJOjkyMnImvWMeUS46zLxDjsCGRYAT5Q27NXxiHIHSIBDxP4PAwj298yrvNjib31yagdJ6LfSNpuQTrMABUkRZwDe+Iez8xCeIIe41STKRY7sk6dFlkzw/95WvwEVRYpOEmtIG8yAdYbCa7GGDEOUvfPWrZPmmTs3NRcPRqFNV1ZKeWpAk6ejIyMgFTpQr8EXCp8wRKAIChX5+VWQK6yLgxrvgCFQsAjwzX8VuXcbE04nyrk98oo8JwjE9kpyKKDtTRJmSjRCT/K9/8Ac4sGvXUgTZjNyaxHl5FHd5VHkDSC++9vTT+OQXvlDWDZQkac/IyEhGinAeUS7rFvDBOALrigAnyusKPx+cI1B+BDhRLj/mpRgxnSh3fvKTP9CAR0iXbBNF2CQJdlnWo8n0OyLQH3v/+/H21742047N1AYvJ83p0eX0yRNZXlgAPB5DvpHhelHaw3wvDg7ivZ/+NBLLvZNLAW5an5IktY2MjGRkNuFEucSg8+45AhsIAU6UN9Bm8KlwBMqBACfK5UC59GOkE+Wu3/3df9QYeweRYoooE1F2yrLueEGEmSQYv/DqV+N3PvCBJemFmeDDdLdIl2JkI8rRKECH5GamgQdPZiHKKZu4EtjDXR8exi8+/jjm6bBhmYvT6ay+efNmRtYSTpTLvAl8OI7AOiLAifI6gs+H5gisBwL8MN96oF78MZcR5a9qjP2aTZZ1omwXRTgVRY8o0+8oorytpgb/4w//0NAhm7pkkyTrB/rSkoK8/DJQ7TPq0cG8uTmAMtxRFJlcMB54sGwJR2YCAbztox/BnfGJ4oNoocfXvOY18je/+U3KfLhYOFG2AByvwhHYJAhworxJNpIvgyNgFQFOlK0itbHrpRPlvZ/61BeSmvY7FEmmqLJJlM2IMhFl4sF/+ZnPYHtzc2bKaFN+YUaU6euZM4a9W3oxk43Y7QClii5DCutoPI53//Zv49wrr6zLZgiCEBkbG3MtH5wT5XXZDj4oR2BdEOBEeV1g54NyBNYPAU6U1w/7Yo6cTpT3fepTT8Q17fO6Ppn+yzIcCmmUxUWtMkWS3/3GN+LfvOtdS0TZjC6bFnEmWe7vMyLJy4ky/Uz65CNHDas5KkSoKQMf2cGZZJps4ujv9Lv0oqfVFJYOFOoRbUphTVHulF0d/V0QwBjDh554Ak+fPVtM2HLta9zv9zdzopwrbLw+R2DzIMCJ8ubZS74SjoAlBDhRtgTThq+UQZQ//ekPxVT1vxFJNg/0mUSZosxmlr7qKi/+7qmnmCxKAmSSW6RSRptJRUziPNAPxGLZMaivB/buMw7yUaGEIumpqulTRf89y0x5nR6xpr/T+FTM1Nb0lQpFqhnDqaeewleeeWZd90EQhKtjY2P7OFFe123gg3ME1hUBTpTXFX4+OEeg/Ahwolx+zEsxYjpRPvh7v/eucDL5P3WXC9MeTjEO8dlEST/UZ3okf+zXfg3vfN3rjEiumVbaJKimRdylS0Ag4/za0hLIYq65Zekw3+JftFRUmaLMJommqHMq8pyKFC+SYdKC6BHmNBvk1Phf+dKXcOrrXy8FbLn2ecbv95/kRDlX2Hh9jsDmQYAT5c2zl3wlHAFLCHCibAmmDV8pPTPfoSeeeCQYj/9ATqWu1hOOpFwvKMospDTKRFl9Xi++8cUvak6nk/JdL0ke0n2Ub94EJsazY0D6ZEpcQsWMGuuey2QXl4oip/8tvZc0wm4cKtRPEBr90M+M4elvfAMf/vKXsUy0sV778Yzf738LJ8rrBT8flyOw/ghworz+e8BnwBEoKwKcKJcV7pIPxk6dEo/9wz8cmQmHB/UsfCnfZCLLFFHWU1kTUU7xUY0xvO3RR/HZxx/PdL+gmRJZpjLuB4gsLy9VVcDhIwaxTS/6z/Q/lYPKjCibhJm+picwMccx29DfEglc/eEP8JY//TNEdY3z+hdBEL42Njb2Pk6U138v+Aw4AuuFACfK64U8H5cjsE4IcKK8TsCXaFgiyif/6Z9axqan7xrkmAK1hpcy0VaTMJvDq5oGIst/9MlPsrc//DCx6MVorqkP1vXJ5wbunzFpk0mjnE6UTQKcLrcwWflyQm1GlM0IsknOyR/551fw3OB5/Mbf/30mqS4Rbha7/X/9fv//yYmyRbR4NY7AJkSAE+VNuKl8SRyB1RCI+J9BYOGeXqXKuw3O5jeXHLBC32hKPsEKHoCI8ut+/E3XjWtzC5JgRJENMwkJdFyOftbjxGawN6WYgCThK08+yR46csRokC6LoPoXLxhZ+MxiRpPTsVpOhM2/rfR78+/p0eXJSeDGdV3X/OKt23j3V7+6YXZDEIS/Hhsb+w1OlDfMlvCJcATKjkChn1+pt97c5819KHPHjLfgCBQDAZ6Zrxgobpw+GGPClz/yEfnJ7343bpJi0iSLjEHQZRcC6J9ZKJpM1msklLA7HPivv//7eLS39/4objgMXBgyDubZHcChQ0va5GzLN/XKOilf46PBTH99+xYwsZRI5Pb0NB7687/YOOACV/x+/8HNRJSDwQQmJ0PGFmXc0CztmWKTkEioS+cw19wRU3aTJr9ZbGPKclLWgPqVl63eaoMwMEGArMah3joPefs+JGw+CIuSn8U7sLROch+DGjMIkJGEdnMQUvNuJFx1EMjZZXHO6dd2ljFScv3M1SzHZyWcClnHGmOk7oXptZ/KLpTaf+NnekdwOBS0tHjW3O2tVoET5a2243y9Wx4BTpQ31yVARBnf/KbY9vGPxwRBkOhzmigJWcIRG6KPwOVEmRAgwkz/JVnGH3/84/jVNy97skBMKhQEAguG3EJRVgcumxwjm/SCeqF02FdfNiLWaaQ6nkxi52c/t+iTsRF2ShTF94yOjn4zfS6VHOg5d24cTqcCt0vWrwyjpBM3BkkSoWlaGo+mK4p048tvgNLbZe9rqU06kTPRXN6eCKnZz3LGKUDS4pgZeh61B3qg2qvpKk6rn+auPQ2QNQAAIABJREFUkvUKMvtbTlLvXwMR5dnzL6Gqcz+Yty7thiETp/uvT8Ip2zHU5WOkz/V+/DMxWz5KfnshCAzBQAxCSpIlSiLs9jTHGTDcvjWP17x2OyT9XYQXEwFOlPm1wBHYYghwory5Nlx3vzh1Smj7yldIJ+EyyPFizEiXXiySUSLHpmFbKqqsR5cZw3vf+lZ8/mMfg9N0tCgVTFNThtQimcw6wrE/eQoT6ZKPUs3Der9JQRD+sLq6+k+vXLkSpGaVTJQHB8exd28dXK41bnys41PWmv0DAzh+/Jiuwy9lOTc4iYMH62G3lXacUq4hve9oMILZBRU+rw3xRAJxAA017ozh+/v96O5uhCxvjjUXC1tOlIuFJO+HI1AhCPDDfBWyUTlMk8hya3PzNICaxXhcWqSWJBh63Cotwmt+rz8IT/2+a8cO/Pnv/R6O79+fw+gWq1Kmvxs3gOmpVRs89v/8F/w8TY5hsfdyVAsKgvCPAJ55/mfnvtbQ2Gh5TI/dctWSVySi3NlZC6/XVvKxSjFAX99ZHDt2DLJcWqI/MDCGAwe26dH3zVDmJoMIMRHNDQ7EI3FMLyTQ2ujNWFpf3yiOHWvmRHnZhnOivBleAXwNHIEcEOBEOQewKqRqiihPAqhffGiarhM2v0+XQqS+TyfKejRaEPChd78bn/7gB+EqVnR56p5BkleIIqfDfPLPvojh2dkNjbwoSnji90/h1//Nb1qaJyfKlmBas5KaBF782Tl0dx+BxyOvKYVfs8NVKuRDlIPzYdybjWBbnReKLCCWpAPTG4NoM02Df3IBbo8DWlyFw2WD00HO60uFE+XsFwQnyoW8knhbjkAFIsCJcgVu2hpTJp1ya2trjGna0qdyihwvP3q02FU2TXHaOE319fiDj34U73zssfwBI43znTuAReI7Ew7j0B/9cf7jlb5lSBCErz/9vR//2927Oy2PxomyZahWrEhnS4eGSEWUQDSioLU1DCZFUV/rgiKqUEUbqotISgcG/DhwoD6niPJCMIzrN+bQ0VyNwEIEDrcTTU2uwhdfrB4YEIsDdrtxTGD5fXBfnx/HjnHpxXK4OVEu1gXI++EIVAgCnChXyEblMM2WlpZ2xthwDk0sV33g8GGcevxxHNu3z3IbRCLA8B2A9Mg5lD/74Q/xZz/8UQ4tSl9VEISrAH7CGDstSdIzIyMjkUrXKFei9GJmBrh7Fzh61MiFk1QjiCTmsL2lBpKQhCooqKkqnsZlYGA8RZQzo66rXXHz8yH4J0Oo8tghaAyKIqO+YeO4SMzNASMjwP4DwPlzwImezNVwopx9dzlRLv37LB+BI1B2BKZCyzKnpc1A1YBgzDiZ7bGLkNY4t1HlEGAjQ94CSqFvNAUMvSWatra2vk3TtO+WcrG/+OijeOJDH8KOlpbsw5CNHLEZ0iDnSJCpw8t+P97x5a8gTFrm9SmTgiBcB3CNpgPgvMvlOn/9+nXDdDytcKJc/g2ihxJ3h4EjRw0VTzQShMMTg11R4HMr0GQBPk8qtXoRppdPRDkUTCAYBhilctcA2S7DkeEscf/EyEyGIrzlKESUCcMDh4DBAaCnN3NUTpSz70Khn195e4hU8htNOS5oPgZHoBAErowXLwVwe40Eb4Fv5IW+0RSCxVZo29ra+keapj1R6rWSfvno3r14/YMPYnd7O96yZw8cZMVFz8WJJKenrs5xMl958UW8PDGBuUgEC9EYgpKEUCyGWDyORDKpn9Sfnp+fFwRBYYzRSTRREAS60OmuT2WM6d+nfhcGEGSMkUsFHcIjRxD6mb5OCIIwLoriOGPML8vyuKqq4xQptjrlSv78qtTDfOlE+fp1QJE1tLQCqqpCTTA4PYpu40a+4cUo/f1jOHSoAY5lOt7V+v75zw3HQztdnSk3OuLMq5WFAPDAg6tblCdCISjuTIeKfNYYmDeUUESUs0WUz58dxqHjbfww3zJwC/38yvuKrOQ3mnwuUN6GI1BOBK7dy+blmd8Mmn0iPAUekC/0jSa/mW+dVs3NzRQBPVDuFZ/79KfQRBn7il2am4FduzN7FYSYsHdv8UKGBcy5kj+/NgtRtklJSGIQXo+MwEIcriob4nEGQVXhqfXoB9UK4czkNx2Pq1AU85FbNs9ouu+aX2TF9ya34w1vaEAuhhznz6tYWLgMl4sM20xKVQvAqbtBO+LzEG6cgdr1asRlV5qT9XLfavo5/X0/BoCMcAxXG0VxIRw6AIcT6O4GfvB9oLFpDPH4mD6urKoQXn4ZO9/wBnhXempUwGumkpsW+vnFiXIl7z6fO0egTAgU+kZTpmlW7DDNzc3bRVF8lDH2CGPsJAASFJfcDPXy//UEalxFPqzk8wEHDlJocPl+zAj79tVthE2qbKI8kbKH2xhuDFb3Mz2ifPMGEA6GUFUTh0MC5oNx2Gvd8MlAYDYIZnegraW6IKKsqszITrhYVsqmZ9ZhGBy0obpagjv1klgjmKz3TMkp9x+IIvN+k7Ruhhu6lojj5rmr6OzZD0o7v+zu0XRFXwphZ8w3ff4C5ubsuDcJHDwE9J0FjnaTlzlJnQT9adArfa9g/wP7oDg3xP2o1Uuj5PUK/fziRLnkW8QH4AhUPgKFvtFUPgLlXcGBAwc8s7OzxwRBOMIYoxTM9J/Ic0MxZ3Lrs6dgl60fdlpzbKfTEKFm61MQRoS9e9vX7KMMFSqbKFemj3KGRvk68booXJ4EnDIQDGpw+ySoJA0ORhATZLS012AxGFyGa4KGIA3w7IwRwaW5yJQ+Pj0gvWweRKRlCWhty3ZfaFQmNVP/uQk80GPdt3ul5c7PAcOmRvkc0LP8MF//BI51N0CW86Z2ZUK6vMMU+vmVN5qV/EZT3i3io3EEKh+BQt9oKh+BjbGCvXv3eoPB4C5BEHarqrodQJsgCEQ+WwE0McaISGdmIVh56trYf/p88aLWNhtw5AhgXzGaNSbs20fzXPdSyZ9fm0V6QfdULc3QiSiRSXoAocd8GRFV4/flLwyByXnYvC7MzkfhlBkcbhccBSQtocj2uXN+9PS0FOwbPTcL3BkGDh0GBvoMbXR66esbw7FjTVyjvOzCKfTzixPl8r8S+YgcAcsIBGNANGnlAWBml8VwukjvsdA3GssL5hULRqCtrc2pKEpDNBqtE0WxBkCtpmk1giBUM8a8oih6GWMeh6K4b3zmD/51wQNSB04XQNkAif2sVARhTti7l+az7qWyiTJJL2oqLjPf8sN8dKm0bojbpqXLMbQQxsiNBWzvqsVMIARJpUOoElo7atZ0F1rpojaI8hh6eloLJsrhEHDvHrB9B3DzOrDcCpwT5ey7UOjnFyfK6/6WzSfAEVgZAX+AYTac+8G+YjhdcKK8ua9M9tWvHgfTBgpeZW0tsGdvFv3lfT3HhX37CvRfKXi2egeVTZQrX3pBrhcbkSirSQ3zEyGILhmqpiEejSESB9q310CR8qNLOlEe8KOnN7eIspbUQFaggsAQUxkkCrOLIhx2CaFQApIkQBYEyPYl3TMnypwoF+cdkvfCEaggBCaDDPOR3CPKxXC64ES5gi6UPKbKvvrVd4Np38yjqdGEMge2txOLsNRFVAwAdux2djxw01KDElbiRLmE4K7QdSVElM2paxrTU8HTJa7LQPLjyHp3+RLlyEIEwXkNcAHJRAJepwPz4QTq6xyIRVTMLURgY4DT64TPZ8iduI8yJ8rlf2XzETkCHAEdgUIfXXEYNxYCbKzfpf30lVNiIPzpvGZWvw3o6FjdPHZZx0FpGpqozokCPuTd9fC38hq3SI04US4SkDl0oxPlu4aMfaNGlHNYjuWqBlEeQ09vbtKLZCSO+Zk4NIcARU1AcTvIbByKLIOC2/GEismxaXjqatBQZ9h0cKLMibLlC5NX5AhwBIqLACfKxcVzvXpjk5c8C4GZxyEIn3RcnRhV/HPHLM+Fwmo1NcD2DiCP5Ak6Udbzi1CETviS1yb9jtD+kOUkIZbnaaEiJ8oWQCpyFcpnc+M6cJiI8jWgugZoayvyIBuwO4Moj6OntzmnyHQ8HMd8MAmPW0A8CcSjKjRR1iPK01MBABIELQlms2FbrVM3o+PSC06UN+BLgE+JI7A1EOBEubL3md3o9wVZ5GMM7OMMqBMEqN6f3ogjoa5y+o6cnEWDHNfVATW12W3fLEKTTpR1sgzhsqAIv+rteA0lWylr4US5rHDrg0WjwKWLlB19EtXV9ThwUFzmPVz+OZVjRFXVcG7gGnp69+ZElPOZWzaiHF2IIhBNoqbWiWgwAY/PkZb0JJ9RrLfRKAkK3WCTjIVpYPSqF0VoySTEYtpSrjGlQj+/8lbeVPIbjfVt5jU5AhsDgaQGzK2hVaYXc50775f0qgst9I1mY6C49WbB7jxfE0gKHwe0fw+G6kUENO1u1eXZlKdxyo+L/mi3Q0/95XAYp63o6/2JQ/ICckGaAhMyD6YKYGpi+tYPErM3n2ZMuGaXcan2jZ8bzmuAHBpV8udXpdrDmdvT13cGJ04chyhWVsKUHC6vjKqUontgoB+9vQ8YpLGEZTlRVhMqhv0BPeKsCSJi98Ko3V6dk4MHHXCcuBeCrEio8SmYnY7CV+OCPe0Q4UpLmhu9A0dVHRKxMLRYAqLDBp08qxrs1XWwO8tztrfQz6+8d62S32hKeJ3yrjkCJUEgmgRuTqVnabp/GDLH39NQGvPRQt9oSgIK73RFBAJj/fWIhD/BmPBbALvPV1lQY8zL2vN+/88V+qQQQ1iiVMH3l+jYENTgvcU/CIKwwIAhAbjAwC5IkC8IDvViw+s+F8x13JXqV/Ln1+DgJLq6auDxVCbR7OvrQ3d3NxSlMuef6zVoEOUB9Pb2lp0oU+T25u0APFUyVEWGM5CEt82bk4MH9TEyE4RLE6BBhixrcHhccFFKxTVKYmEeUdKNEDkW3fDUOzB9axx1O1v1pC6lvnEwp1fo51feb5SV/Eaz1ubyv3MENhoCsSQwPLu6TZwkArvqOFHeaHtX7vmMPfvkCVfHg98WZOfKClDGUKUWninM2toYgvIMNNx/o5cMTSM2OrhmN4JAuSikOwLYC4xpL0qQX9r2ln0XBOE9q989rtBzJX9+Xei/gx2761BV41kTt41Yoa/vLLq7j20xotyH3t4HS04M+86O4kRPa8ZDoEQsidlAHDU1DkRDcbi8jpwiypqaxOhMCF5NQEKQoNgYfNUea/INTUV4PqgT68DYBOx1NVCjC0gkBHi2NUApUwZBTpQ34jsBnxNHYJMhUOgbzSaDY8MtZ/LpJ48lBfU9AsN7GNguyVULR9vxVefpTlRBElbMole0NcakIGJC+P7+NA2R4ZegxbP8zcLogiAlJNl+QxBtfUxTvws5+LTVqHOlEmU1FsPPv/UtaO4aJLYfBzSyjtTz2aX+p76Qp5n+O6b/E0UNhw83Q1HWjgJagL6gKn19l9DdvQ+KYj11+q1bk5iaikMUJYBRMIDWR4GDbLE+Y9160dP8mXVMTPQ/pNaw3HqTfqb+6e/Uf3obgltDba0bu3cvqZjWAsPQKN9GT++uRY0ySSKCoQTsDgUOh4R4TINiF62Rz1UGPPPSbQjiFCSCiVJwyzK83oPo6FD0rPKUopvUVckk4LWYv5OkEuOTIciihLptTiSTDHZb5nVE/VHJJjuOzs1h9tZNJEIhiDYbJEVBTWcXHFYnsBbAFv5e6OcXjyhbAJlX4QhsdQQKfaPZ6viVYv0Tzzx5VNXU9wgC3sMY61w+hqO1G5K7fsWhlYQEp1BXiqkt9qkhiZA8Y9KWjLHi07eQmL5RtPEFUWKyUjWv2HxXZUfdj91Vu78l7D3Ul22ASiXKxH4uv/A8Gtu3w9OU7YFBNgIo4OLFC+jq2onqausEr2gbs6wjsjDr7m6Eolh/+vXSS2exf/9B2PX06Ln4yqeR5vsWtNLfVm6TSKi4fHkKJ09aTymoqsC5c0BPz5IfczAUwvhsAo6YCptLRiAM7Nzl023fCilEyhOJeEYX/jE75gOCbst3bgBobgZCYWDPnvxGIrJ99gzw8MPGcQYqz5wG9u4Ddu68v0+mqlATCUwMDaG2sxOK2w2Z2HqJ9drpMyn08yvvbanYN5r8rg3eiiOwpREo9I1mS4NXxMWzS6dsE3fZBxjDJxmwf7WuRZsbzo4HASE7IRFUFV7WXMTZ3d9VWJpFUkjc9wctEUHk9s8AlnvWSasTFiWFgWnf16D9LwW272x783/0m20r+fPr3Pnz2NPVBU8OFn1DQ0Po6OioWKLc39+PI0eOwGazWd3+ktRLJjWQRry3t8ly/9mIcjQaxYIKyIEIJhdUuB0C6pur4ShRxL/vrGHLd+Uy0NgEhMNAV5flJWRUnJoCvv51oK0VeOObDKfIb3wdONEL7N69cp/j58+jrqtLJ8rlLoV+fnGiXO4d4+NxBCoQgULfaCpwyRtqyvde+BNvMhj6MJjwCcZYi9XJ2Rr2QqlOmVtkaeRRayEy64/ArY5L9eJCGFEp+/m76Nh5qMGpXLorqK6ucWY4KwjCt2VR+Lb9kVM/z6VDT3kO51ua0uDgOXR2dsGbw6ProaHzKaJcY2mMUlYiZ4bu7qacIsoDA2dx9OhRyPL6bkQioeH8+XH09lp+CepQDvQDJ3qWUI2GIxgej8LttMHnEhCIqGhq9ELMm5GtvmMUAe4+ZtjzFUqUKaL8P78GJFSgphp47A3Aiz8Fjp8AduxYeR4TFyii3AXFZSRHKWcp9PMr722p5Dvycm4QH4sjsBkQKPSNZjNgsB5r8D/9R9sEMf7bmsb+HcByf24u2eDa+RAEMTsZtmkOOLSqoi+NQdUP8BE7XV7U0BSio+eLPmYuHYqubZCbjkBpOgrR4Vuz6cYiypfQ2bkTXq8RmSP3gHA4AUES4XLIiMZUOJZZdw0NXUFHRyuqq1Nr1dskwUQBbqeMaFTVtbLlKLkS5bFR4MLF6+jc3YGOHYbWtoxP7TMgMYiyH729q0svQiFgfNzQCWsacPsWsGu3qRo3nBdbV+iCHrKs8BAo5+1JJICf/hTYvt2QRZAEpCktokzzm52NYm5uTL+OshXCWlGakEgY19tCAPjZi8bDIDpJ63EZUvn9B4DG9PPBLAiGCX2zJMYQv3wJTUe7UUUZPctcCv384kS5zBvGh+MIVCIChb7RVOKa13POkz861aRG8fuMsQ8CWD0pyBoTVWo7YKtf+TmrV62DwIpLksLSHJJCplbSYHUqIrdfAkkvNkYRINXs0Amz3HAQgpT90f7GIsoqOjulxcNYajKBG6MLIPWu22lHOBpFY0stbGmOAkNDKjo6RFRXGx/5pBu9MToPRRPhdCu6htRb64bHUXrLtlw0ysGgoavduQuYGKf10YGwKGrr3KjxiAgHNVTVlf5AqnmtWo0oX7gAXL2aOhYoAtPTAMnDyZKcSOW2euDY4SBEu4RgKK7jHo5pcLlkTE+F0bq9JquFmxqL6wfiyG6NknewZEw/YJgIRyHKCuy+qowDgXTI7qWXDHJMsojlRHlwkLqKYNu2ydTNRzZKSIdBt0HTjEhwYB544XmDKOtHH0WD2B8/bkSrl0oIwJQ+TyLKcxcvoP3IUfiItZe5FPr5xYlymTeMD8cRqEQECn2jqcQ1r8ecGTsljp9mH4GAP2YMa4c6rUxSFOHseBVEJTvfVpgdTrU4Q9F0EkIEEWkh68zo8B4d4tuQRbRBaTgApe1BSFWZj9Y3FlEGOjuXXAuYpmEiFEUNA+aCKgSFwe1zw53mTDA0BFAgb/EsH9PgD0RQK0uYmYmjtsEGUbJBka0fsMt3D/v6RtHdTQ4ca48VCAA3bwLd3cDwMBCJRhFPzKK1qQbxaARaQkbLDov2DflOOK2dQZQn0NtrXdt/+RLwwk+BgweA17zW6CwejWLkRgCCz4Zat4TphThqvQ7YHAri0Rh8Nd6sDhgLI+Ow1dUhEZiHINuRjC/AUVWF6Pg8ZJ8LztqarPmBSHpxtBuguRCZjUSA9nbg4kXjkGEuZXbW0CST9IKMSx5+xNA+k7RkNenF+aEhdHV1wc2lFyvDvZHeaHK5KHhdjgBHAOBEufRXweRzp7pVFV9ijD1Q7NFkbwPszUdW7NatVkNihR+U0iUX0gwY2XItK1o8gsidl/So8kYvkq8dtvaTkLcd0MNlG+nz6/wg0NkFeFI2ynpSibtB2CQBVdV2JBNAbZ1DNzkzywUiyjsAn6m80JK4OTwPRZDg9dkwH0igpbkKNiXv2JnlLc2VKN+4ARw7Bty+DQQDIXhqohAhw2UX9bU2tW5cokzE9Cc/MaKvdGz18CHgwZOAIiUxORKEzSlBZRpERUIsyVBXZYOqAe4VLrjI5AxgFxHyj8Pma4DNK0FQnFBnw1CqvVBWkM+cPQvd9cI8zBeNAM0tRtSbsM2lUHT8618zbtTe+Eajn29+w9Aor3aYb3BwUCfKHvPCzWXQAusW+vmV96uCa5QL3DnenCNQQQgU+kZTQUst+1Qnf3TKo0XxJGPs31NWjVJNwLm9d0U9rsgk0MG+7L601me0kssF9UC6ZNInV1IR7FWwtT2Aml29EOTyPeJfjlE8Bp1AkV704gVDipDON2SRMp8JehY0mywjuBCBpDhgS0WVL10C2tsAX5rKXW8jCIgnEvpj+1AwBqfLBmeJtcq5aJQpomwS5Vv0IIJp6NgpgmkMUqFeanlciJYjygwg+cVPnjcGoZsW09+lqRF481uW9i+papAlEUmNgbKrrlYiU/cgubyQJQnJWBJqIgJHbQ0iE/cgVflgd2UediTZMeFHEeSDBwGSWpAMIxI2brbOnAGam4DtOciGKaL87LMGSa5LuUt+59vGYcHV5MeDgwPo6trLifJqG7yR7sjzeH3wJhyBLY0AJ8ql2f6J0597pwrt/wZjK2fRK9LQksMHx/beFXuzMSccav7RudVcLihFNaWqrtRCshX3zlfB3XFSf+RdzkIRvP4+I0kE6UFJI+pyYzGpBGWCPrgnAMXJkIQAj1PB3IyK80N2yIqik2s6gEUHyCSSIGsA5e04tHceNqdxa2ZTFP3QmWBTUOMt/MnCavgURJQ1DdW+COwuG0IRFT6PqH+trnYWnKzDyp5a1Sjfuwf8fz8yDvIR9Q1HAFIc0PckWdi5A3jVQ1ZGLKxOLAY8/S9GFJv8k5drlOkG6uYN4O2/aFxb2QoR+fHxEJxOGXFKR80kVHnt+pMhh13EXCRJia2RUJOor135ZnJwcA5793rh90v6WIRBNBxHIJSAr9YJRFXITkW/rotdCv384hHlYu8I748jsAkRKPSNZhNCUtCSyA95fBj/mYF9tKCOcmxsbzoIuWplfaVL9UFmuRNBTUgiJJLkIsuEmIbIrRehJaM5znbjVRdtLnh2PgRXx4MrHvwr9qyJbFFkkAivSXzIXeChVxsjJRMJ3L05A0FS4KlRYLOJEJgAu8sFmwzE40ZCCNInv/Zhox86vHf31iwYSS9qbbrkQhJFONzOrIfIirmmfIkySS8SkSiYOIvW7fWIh2OYjzG4ZcDrc93n9FHMOZt9WSXKtF/mntENDkVyzYQjprnESsS02PMmz+TLlw2dNz2NMDXK5IJBN2AkmaCbrZWKpqm4dHUabY0ezAQWoEUk7Njpw/xEBIJPhJAku3JAFUQ0blvZI5kkQ5SUZOi8Md7xExru3JpFU0uVnt5+diSIuvZanXwXuxT6+cWJcrF3hPfHEdiECBT6RrMJIcl7SfeeO9WSVPGPjLGTeXeSZ0NBccC146GVk5BAgDtZo2tArReGkDwLFak8tssaxqeuIzFz23p3FVCTCLO36/VwbaeTUHl/jOa0UiK833sWuHXHGLG3F+jpNSKBaiwJLckQjMXh8jrAVA0Oh4JEEvjB94DrqQSIx48BJ1+Vcl9IaEgmVISjMTg8TkAji7jSRpNpwYVolBPhCAQpgJpGLwSNIaEmwDQBtbVe2CwcDswJ8CyVLUsv0trSjQ45d9BerVdZnnCENMpNzcD1a8Yhv9WKqibwynAAu1urMTI+BzUuoLXZi9C9MIQqESzO4PI4EInFUVvryfCCJskH3SjQzRlJUUjDTBFjsvhzOhnGR6dR21AFgakYuxlAy+46eDy5vPdYQ7TQz6+8X+Fco2xtg3gtjsBmQKDQN5rNgEEx1jD5zJOvVbXkNxmQ7jhajK4t96HU7YatLkuu2VQPEpPg1mqRPTx8/zARKYCEkD1azBJhhG/TAb7SZeCzvPASVFR8zfAdeNuqSV2KMSxFkp97FrgzbIjY6agkIbprp5HwgTICLy/kofv97wE3bma22d5uZFQjKcZ6FIMot0CxcHDwPo2ypqG+jjTVMCQXXgUxlcHrLj3BJ6ysRpTTcc2Wma+cuM/PA6+8YhzaI/cTXaMcAXbtAuiQH0WaHavI7zVVxex8HLXVDswvRKHIErnTgdxWPG4Z0YQGkS5ISYTTsURyR0aA0ZFU3wJhB8jSkkXewgLwQE8CgXASdXVOIK5CkKWieUinY1zo5xcnyuW8YvlYHIEKRaDQN5oKXXZRpz3+9Gc+xgT8GWMovVntKjOn5CPOna+CIK0ssVCYDU517fwmcTGMqJg9+x5NITo6CDU0XVQcN1pndCDO2XIU3n1vhGhLWVEUcZJEMIgk37oNkHtbel4IlRlazzf9QubjcyIyRJKvXQeWn3mjNnSw7y1vBdYjI3QuPsrLiTJFI9fBhndxN/MnyjH09NhLnijl+nU/ZmdH08ZRoKr7safLph/kNA/zmSmsyZXj2jXgHe8s/nMR0j77xwGvx7ixM8kmfU/XMM3hoTLotGnzCv38KhtRdtlQsvSMRXxP4l1xBDgCWRCgMxzxPFy9JBEnXTbhzFYGlb34Ref4fOBLjGkf2Cg4yL5W2Bv3rzodG3PAoa6ctS8pxBCR5rPk3jO6TS5MIua/sFGWXPJ50IE/38G3w9F8qKhjEemdJrMQwXiEffVloK2mZ/BEAAAgAElEQVQdcLtTpJkBdfXGI22z0OP+qZTBCLW59ooRSfTSdlK2OGpTZzwCL3fJV6NMrheSmJtDQ7HXlo/0QlVVDAwMorf3hO4yUsry0s9GcPBQbYZHtcNBN8SCLoFYjCibrhcvkZ+yBp9jDs4aHyKz8xAkAbGpWcg+H7zbUrYWeUyarkFyyKDrlwpJhMwkJfQzTauqePbtq86wYoiyXSbvwDzQ5k04AhyBdUcgkjDsqXItW50ok/VbMsqeBkMq1UCuCJaqvgBnx4MQ7atHQO3MBbt6fx1VSICy72VLUU0zZpqKyJ2fgSUq/wBfrjvgbDmsE+ZS2cnRYSiy9iKibLXQIS7yUa4qfrZyq1NYrLc1ifIAent7S06UCdvjx5uzWuelE2XTR/mVq2TrpmFh+B6cDVUITQfgqq9F7F4A9voqKAVkaiSCTP3HE0Y0mTIr1tQCis24wSN7Q0qcU45SMUSZgHLyqHI5rgk+BkegqAjk+yZDk9jKRNkgyTgNxl5T1A0pUmeSqxaOtuNr9ubQ3LBpS6yMUlOHxblVn9VuxgN8awKVVkFyVKH6yDthq9uVSzNLdenxeXpmPiuN7svMZ6VRierkepiPIslHjwLDd4wJ5eL5W+wlaBrD4OAYTpxozanr/v5+9OSaAi+nEYzK/f1j6O5ugpwlw2JGRDliSFgoEU1PL8PcrTF42hoQCwRgq/IhPDIJV1uTpeyJVqdJN3h79q6PNj7fzzDz8yvv5wC5HuYjMGkwsquhxyd5D2x1V3g9jgBHoCAE6PFsUjN8P/MtW5Uo33vhT7yJQOg0gJSJV74Ilrado7Ubkrt+zUGkaBxaKABG0Q4XeS2v/A7O4iGE9Qx892fnW3OgTVRBEER497we7l3FfZhQ+UTZIHNWUljTga++PkOHTXrXtrbyapQ1TYPfH0IkkjRs9VQNt27NobOzZoXXAL0udBVu6koWIcYDCF45i6rDDyEpuVLHMNNfP2Yb8+I3/0aP8LK9ztLr0zhGOhN6ud29G8DDD3esGVE2Ncp0LYWCQG93ELLDBi2RhOJyIboQgM3lgUhkLc9CNxViWgIVGqsrLaNknt3m1ayiiHJeK+SNOAIcgYpFYCsSZZ0kL4SfAWNlOqqS/+Uh2ty6BMPSUXMSHVowf42ODEANz+Y/qU3W0tl8GNVH3gGIxTnDOTh4HZ2drfB6rdtWDA3dQEdHI6qri3/YMNft6usbR3d3gyWiTJfcuJ98gF/Brt070damZHX4yHUOVuv7/eMYHp5Gc3O7Tn6TCQ03blLiDNLumoSYiKtJXtOJrQZGRouJENQ7P4e08yCSkiNFfc3jbcuJsEmwM46+pchw+pE4WkH6+HRfynRLwMbG7Jqc9IiySZQpAUkibiQkya0wjN8NorregZn5EDwOBZFwEr5at27TN3VvHoEQQ2uLD06nobml67arqw0eT/kzXHKinNvu8tocAY5AGRHYakR5+ulTVXEBz66HR3K+22pr2GvJ3owlY2tmpUsujCPmv5TvVDZtO7KRqz3+3hVTiOeycEoF3Nm5B16v9SyKQ0OD6OjYgepqioSub8lFo2zOdGDgLI4ePQq5zFkRR0ZGEI1G0EmicIrbakT4xnHiRNP6gpjH6MulF+3twMWLRiKUfMqcfwExp6A7rgfmw6jxuRGcjMDpsCEqJBFNiti5wwcxdYCRp7DOB2XehiPAEdj0CGwloqyTZLDnGPBgRW2sZINr50Mg27hsRYsFEZt8GSwWhK1xP2RvdgtopiURuf0zEKHm5X4EJIcXtQ/8BmQLUpfV8Dt3/jz2dHXBk8NpvvMXLmDHjh2o3gCn+fIhyqTxPXz4MOzZDKNLeLGNjo4iFAphz549+ijkejE0NI6enpYSjlqarrMd5rt61fBXzqdM3pqFs86BhXAMDpuEJPkkMwHzgTCiTMO2lhrUU6rrVBkcHEQXXbd0iq/MZf0iyjE2DYbaMq+XD8cR4AhUEAIKsMfhEK5V0JTzmipjp8TxZ/AvjLE359XBOjdSajtgqzeiZmahlNOJ6VtIzo+laS6ha5rt2/ZAsJHecqnE711DYjZ14mqd17NRh5fsbtT2/vqKNxs072g0CZXMjhfL0iN3AQzXz/4UzTs6sG2nxYOCjOHnL7yAmm0N8LZbbKPbeQlwOovvH1fpRPnsWUqYUuKIspZEdOwOHM3bAYmSqVjV+5OueSlDJunkXS5DopPVHu4M0NyU3wFJyuooUfIRTYMsiUiqDJJINnSUjQQQJBFymon34OA5dHXt2VpEORhjFxjD4Y36hsTnxRHgCKw/Ah47PIIghNZ/JqWdgf/0qacYY58q7Sgl7F0Q4dzxKpAXMGXTS8zcQSLgXyWjngDZ1wylZidEmxNaLITI8JlNm4GvmMgTxrW9vwbFd39U8t5kGFd+PoWqKvLQolFJq2oc6tKTnwkqcOlHqGptxs7XP2ZpWloigZf/6X+B2VyId/Tqh76WlLHph8/S9LICMDMTwYkTLaiuXjkxjaUJLKtUyUSZsLt4cQLJpAYh46Dd8gN55s1NNs2xua/L0TP6YAKgJIJgL78Ice+rELf5IOiZLVcbw9BJM5Ad41KCH0myI5HYjx07RNTW3p9w5NIlgBKDvP0XLR0/yGe7F9sMDt5CV1fzltMo/yWAxwtCjjfmCHAENi0CgoABj13IUwFXObBMPP2Z96vA31XOjLPPVHLVgHIDq0HKVGE1giXo0VEtGYEWma90CMo2f1Fx6DIMpao5Y8w7d+ahqQw7d62cFXFoYAC7du+Gt3rtzIlm55cGB9G2fTuqKcuIxXLp0hSamtyor7d+aNBK15VMlK2sr1h1zp8dRvcD2wvuLhgErlwxJBbkp92YSmG9cyfQ3wccP5GZ1bHgAVfogLTdXV118HiKc6g1l3mum/QimGCPMRXfz2WyvC5HgCOwdRAQBfxHt134o8284rFnnzwBNfk82cRv5nXytRUfAcnuRd1DH4LkWEpPNjwcQCKhYvfulQ/dnUtpPb05aD3PDw1hR0cHqnMh1xcn0dTsLQFR9qO7u9GS64WJ+kbRKBf/KsjeI0Wu6YaCtNAWjGbWnFbfWeDwEeDKZYMoU8KRpmbg+jXgaPeazYtS4dzgBPZ01W4tokzILcTYi2B4VVFQ5J1wBDgCmwcBAbMeG3YJgjC3eRaVuZKJ7/9ho5qI94Oxts26Rr6u0iKgeBtQd/LfLmbxGx6eQyIB7N69crR4cLAfnZ17S+56calkRJk0vs05EuUzOHy4ex0O891FKBTGHsqUUcZCRLm/z48TPU0ZXsT5TCG4ALxMGfi6jQQjekQ5DOzaDbz0kpHMJYdzoflMQW9z8dwwdu1phNtTXCmPlQmtW0SZJheOswc0hucZA6nNeeEIcAQ4AjoCooiPum3ClzYrHOzSKZt/mP1woycU2az4b6Z12et26ppl8rIeHp7XnRVWiygPDt5BZ2cjvF7Dj1ZTVUxMhiCKIrY1eJCMJCA75AyCNTQ0jI6OelRXGwcwKcX4xGQYdNirfpsL4VAMDpcdStrhK4Mok/Qih1zZFjamry/3iPLAwC0cPdoOWV46XKgmNURjGhxOSZerWElgkm16sRgwMWGQx5STmf61oREILswiHImjqyu704uF5eZVxSDKwzjR014QUY5GgX/5LvDQq4GmJoB8k+mr6aM8OgLcurUAh/OVNLkV6Z0pCZFJaNN11su9o0k7TWV5AhVz2YZWW0YCuPoTtJ84gbp9+/LCpJBG60qUaeKhOPugpuGvClkEb8sR4AhsKgS+4nUIH95UK1q2GP/Tp/4bA/voZl4jX1v5EPDsfAjefb8AQ3pBRHm1iHJmCmumqrg7Ewa5KscTAIvHUd1UA4djKava8hTWTNMwPLWAalFCKJIEU4CG+iooaamPSxdRXjszH5FXvz/F3QTg2ivAjh2AQmccGeCwaUAyAMVjg6IAwVkVrR3WfaVpZylyT1KEQACoqQVIvm0SZSKSU1N0oBFoawUOrWJbQIk+YuEkZJuEcDQJt0OkICIcChBLMMiiAMpy6nJZ1+ZSn319lPb6hH4DtFJRw2EkVQGKXURsIQRVjSIeiMPV0gSHy2Fk6xsGZueAw4fvP8yn3zQxDbFYPG0IIr2UJCSd/KYfTkxPhpJOkpcnRFnqko4ZTpw7g2379sNJpwrLXNadKNN6g3H2ATB8hbHFW5Ayw8CH4whwBDYCAoKAP3Xb8HuCIJihho0wraLOYeL0535BZeozRe2Ud7alERAEAbU9H8B4uB6JBMuZKI9MheAWBASCMcRDGpp31sLrWYq+LifKlDlj+F4AbkFEIinA6RIhO+xwO5baXLp4D03NnhJolNcmyvE4MD6+dElQJmVK9mHGNmUhgVh8ATt214IlVQTGo6husx75npsDCBMiwbs7V770nn8eiMeAtnZg7wrqC01TMXkniPpWD8bG5+CgaL4mIKYy2OyAIkoIxzS0NFdZvsYNotyHnp6e1YlyKIRoSEUyEYQa0+BpqEFkLgFvS1VGu+UaZTOibHlCRag4PnQedZ1dUMqh81g23w1BlGlOCzF2SGD4AgMq0ke0CNcB74IjsGUREARchIhPexRhUxNISioSE9glMFBOW144AkVDQLJ7EN3xASSYfVXpBRE8yn/hXDw+qmFiPAxBlNDQQFZ9GkRFBNICkZcuAh07gKVkfhomJkJkdovaGjvCoQR81ZmphdczokxE7pWrS9BGooDDbkR8iSzTOcbaqgVEmYhtNXZMT4TRtL0qIwa60saQC8TgIHDoEFBTA9y5bUSOjx1fakGknMhlQwOwYydwfhBwewzc7yuM4d5wEDWtbkxPLiApSnCKGoIJDW6HBIdNQSCcRFOjx9L8qH+DKJ9FT0/vqkQ5GQoiPBuBQMFqSmHtdiE0E0F1x7aMaZ49A3QfA+g6II3yehDliaEh1O3dC9mxhVJYr3gRxthhAfjlVHaqFsawdKS3aG8pvCOOAEdgPREQBITB4IeIi5KAf3bIeH4zR5FNrMdOn/oSGNvUspL1vK62+tjMswORlndmRJRJIjBy15AKENO6cwdoagTsKb4hSUBzQwKiLCAUjMLhsWNmMor5gBM2uxEhpsfv9fWAM5Ujhp7mtzTGQZLkYCwOl9uB+emI3rbaZxw5unRxIuV6kZlYptA9sqJRJskARZXNcm4AOHgIMBPzEWG2pU5G6b7QRKBTX1ebn+4mcdY4yEZ4UHn+x8DwXeD9/4fxM5Hks2eBbdvoUKXxO0MzbLS7z2FP0zB1LwyHS4bGBDjtAkIxDU5FREzVwChjnV2G22U9eYtBlIfQ03NkkShrqoZQOAGbTYHdLuq6bGgJqHriDxGaJkJSgHgkBnvKEYWumZ++YNwkkXRluUa50L200j4RjWDBP475mzfgaW6B7HKiuq0dQpre3Eo/hdTZMBHlQhbB23IEOAIcgY2OwPjpzz2mMZVbYm70jarw+cWa34od3UtZ0OdmDdcCyjlBpPjuXcDnM6LDROpEUUNj9SwUhwh7lQK7CIQjDly7LkGSBd1ejA5tEXeidtRGEBga66bhsAmQq2xQBAmKLICJMjxuQ0trRJRJelFsopyP68VVHDmySyeJZklEo4iGNcRVFdE409dqc9tQu4qrAsk5SJOcHhkmIkk3Ir/63iWS3LDNIMXpJRQCXnkl/5TPuVyWOjHvV3HihLRoDxcOhTEyFYVTFeGuUpCIMjS2rZ4OmrLxnXnJiCIT6S83UdZiEYSmZxGZm4Oo2CEgiUQkCnf9Njhq66E4yuMDwYlyLlcfr8sR4AhwBPJAYPJHpzxqFBcZYzvyaM6bcAQsI6DJXrQ+9nE9+cvyQgfMyMWAJANveauZKELF2K05neRKdgFOIopqEj6fodmdnQW++13A4wbe+jYzKqvBf2cWalKA7JbgJF0DVHiq3CA98BJRLoWP8toa5eXr7u8/i8OHjy7ZwzEN43dnkNRsaGxxIhpjcDkELCQ0VLtWth8jorh/f7psxYi40o3Eu/4VeRcbcotdK2T6vnABaG838C9lMYgycOLEUsa8RCKG+QSDEoghARGyKKG6wdpNDEkvyC/58qXySS+YmsDc6CScPo8ul4nMB+Csq0U8HIQgyEguzMO3fQck84IrIaCcKJcQXN41R4AjwBEgBPynT/0Xxti/42hwBMqBgLfzUXi6XpcxFLlAPHsaCIUNnW5LM/DIo0tSACJXsVgyJbfQIAoiJieBZ04DgQWjq8ZG4JFHDDJIhWkM8XgSih6p1TL0sCXTKPeP49ixRshpVnRrYdo3MICjRw7DRrYXqTI/FUIiIcBVJUFSZEzdW0BVjRveFdwlyCrt55ShLk2LTF29+FPg9m1g5y7DOo0y1q1UKPJMjhyrHQBcay1W/25mzTNNL2KhGO5OhOGwydhWZ8PsTAxNrdYOCJKU5EhawpFyaJS1WBRTw1PwNjgQi6lwOOwIz81B8Xgg2V2I3huDt3VX3rZ+VnGkepwo54IWr8sR4AhwBHJEwP/0k49ASP6IMctncXIcgVfnCGQiIEgKtj38scWsfRTxfOYZgA61UcDXdLN1OoA3vxlozZLyhmQGp582iHV6G7sNeNMvAB0dq6NeCumFlkzi8vPnsePoXoimyFpfTboV2bJ5MQ03+17E9sPdkJ1LUgNdl7zohMEQjcYgK8iwuEvviaQTt266cIhOUaUVIqQkqXjTmwwt72qFIvrkuXzwYGmuWMqYR2iQPIYObRK5JbkNFSLMEpIQZQlxIp4uGYlYUtdnh2Mqqrx2qGpSx2GpCBgddSESMezhBgaA5mYgHALKkUMlOjeDeDgO2eOAKCqQbWRjt4BEKApbVQ1c1blZ+uWLOifK+SLH23EEOAIcgTUQYOwb0vjpSxcZsJ+DxREoJwLujgdRdeCtegTzB98HFhagyyIoGkiH2ohAqZqhVX7sDUsH3WiOdIjrBz8AyAaNrJHDEePwm5xq43IBb3hjpgRh+dqs2sMlIjFMzyZRVevQE5e4PHa47Cl2t6zT2Pw8rn33OxB29SDuoNN06S6SRGDTE1oYjWUtAuGVn0HoOIK4k9wcqI1J/c0BqG2A/Leykm4ik7GYhHv39qOtVVm0maPf37wBqCrwr96z9u7euwfQ/wMH1q6baw1y37h8xYCA5kXa9Ooa4yAhoVLl1bC3Yx6eGjfmZyJo2O7F1N15KHYBMwsqdnbW4fy522BsOiVnoFYSvN796NhhgyIDIyNAVZVxUNI8zJjrPCuxPifKlbhrfM4cAY5ARSAw/vSpD2pgPKFSRezW5pokRZUbHv0ERJsrdQDPWB9ZldGjf9PqjYhUtpwUxqE9ow2lLt7eAVSn8pis1CYdQUvSC03D3Tvz2Nbkwb3xEGoanIgmGep9K1uAne/rw5ETxyGK2cl0tl1MRqM524qxpIZ7EyFIbhvcNgGBgITxCQlHjmaOoEsvbgHvS7lerHYVlZIomz7RdDM0PWU8QTh2DDhw0IgwR8JRDF+fRXNHDcRwDJpThv9uAHXb3JgNxLCrqx7nz43jxInmpeuBaRi9OwPZ7obHKSCwEEVVrUuP8tpcdsSCMf2reYBzc72CllbDifJm3Vm+Lo4AR2BdEWA/OuXwR3ENjGV5sL2uU+ODbxEEvJ2PwNP1+ozVElHu7DJcLKyW5UTZSjtL0gvGcPdOAN4qGyKBJGxVIhxOB9zOlUnw2b4+HOvuhkIp9UpYxu7OwldfhdDMAmRFAVMl3PE7dPJp3kDQ8C++aPgLHz9hHJ5L/9vy6V2/DpANcFsJ3xHo8CVJZmZmSUYCPPoosDeV9TkRjuuPFeZnI6ht9CIZius2cQuRJOoa3Dg3MIbuY02QFzMsMgwP34PD6UYoFEdLixdTUyEodgWIxDETjKO+oQr1teX3Ni7h1t/XNSfK5USbj8UR4AhsGQTGTn/md8DwxS2zYL7QDYeAqDjR8LpPQJCWDrFRsozOtIiylUnfl5nPQiNLRJkOSiWSuHp9GvWNPkgq01033M6V0y739Z1Bd/fxkhPluekwFsJJPRxb7bZB1Rj80279IGO6FzK5XoyNAkePAfPzQE/PymSZNL4ku1hK9mIByByqzM4ATz9tpJyms44U+Sf5NmmVH3oNIK4i5aZhyKNaPyiZIspM1XB3ZAZujwfB+ajuipLQGJyKBBkaokkBbq8NNas8Achh+hu2KifKG3Zr+MQ4AhyBSkUgpU2+wYA1jjxV6gr5vCsFAd+hX4SrvWdxuoODMXR2KvB6Vyajy9c2NBRDR4eC6mrrbawSZXOsREKFohiRZIqKkkxBJ3qphB2UuZhcNy5cuIXu7o60qKdRIRJRYXeIiCc03dkhElVBZhxJDbDbrMs00tc+NT6HYFJEa4MbGgMSSUnP+Hc8zfki3UeZDvXNzwEnegA6/LeUyRAg1xEi0vtS0d1iXz/k7/zd/21gR/KL9EQqlFuE5vzQQ6uPupwo06KDQSMK7XJKCAUTcHls0FRKUiIjHklCcciLloDFXtNG6Y8T5Y2yE3weHAGOwKZBYOyZz70LmvqtTbMgvpCKRUCpakb9qz+aRpTPo7OzE16vde3F0NAFdHRsR7UpUraAhiWN8rJ+iEzeuA6Qi1tjA+BIpdkm0jd1z0j2QQcM3/impcx61EU8GMLdsRA8PgcYNNhlCRFVgk1Soal08MybVYdtYRm6BZ6QFoq9csUgoaZzxQvPGwlH/vX7jN5u3DDSZ9M8f+kdABF8mvfQeeCBBzMPTVoZ32odOrRJRJymSqSerOz27U+R5pTrxX1ZAZd13tc3hmMZ0guro2/uepwob+795avjCHAE1gGBsdOnngdjr1mHofmQHIH7EKh/6MNQfK367wcHz6Gzswve9HDnGpgNDZ1HR8eOPIiy9cx8ly4ZhPLIYcCzguvX6KihByZ9NR2qM5cQDUZw5+48XNVueGwMsl1BJJJEjAnwiBrcPg9sivVo+FqX0OA56FZyhw4BwaDhJELRbirDw8A//7Px/ckHjQx9Fy8C3d1GZsNyFUo4QjKQXEpf3yiOHWvOjNbn0sEmrcuJ8ibdWL4sjgBHYH0QGP/ek4e1RPLC+ozOR+UI3I+Aq/04fIfeof/h/Pnz6OrqgptCnRbLhQtD2L6dIsrWU8rlElGmKC1Z0h09alitvfQzYP8BoLZ2aYL+MeD6DeDkSYNQU8SUDtCRVV0iEsfkVATVXjuimgq7Iuv9yKKq62jralOhaYvrXasaRZSvXDa0wKT3JpJsHuKjSPLlywahp7J3ryHFyOG+ZK3h1/x7tsx8azbKolG20mYr1OFEeSvsMl8jR4AjUDYE/KdPPcUY+1TZBuQDcQTWQIAO8zW+/nfBmIgr//K/4ahpgNB2CIwybiwW04eYvprf0x8FDA/fwIkTnfDlEBK1SpQpAQf585JjBBWK0P7tXxs+zV17jN+NjRl+xb0PLEkXqN3du7lHTYt5scxMA3eGjQQcJBMhskxWe4m4QfiJ/De3GGS6nIUT5eKizYlycfHkvXEEOAJbGAHGTonjz+AuY6xlC8PAl74BEfAdfBscLcdx5fT34ayvh9KaYqH6XM3sdulfDZJMhZKTNDd7MlJUr7VEK0SZCB3JGMjrl2zTqNAhuL//O+D1jxkEk0gy6X4fSCPJ5tgUVa7fBmyjPCLrWJJJIzW1WQgvWs/4+BQCgSj27CmhH1yWdTPG0N93FSd69uS0Z1yjnP0i4kR5HV9cfGiOAEdgcyEw8ezn3qiq6nOba1V8NZsBAcXbiPrXPI7B85PYs6cWbpdc0mVdujiBpuYq1NevLHuYnAQorXN6pjqTKFNKaKcLuPaKQZJt9vunS9kG6fBf97GSLiXvzkdHRxAKhbCnHPme02ZJRLmv7yx6eno5Uc5795YacqJcBBB5FxwBjgBHgBDwP3Pqr5jGPsjR4AhsRATqX/UhXLolo7OzFl7vkrdyKeZqxR6OdL6NTZm+xESUv/4PQOcew9mCbM0o5Xa2Qhnnzp0ztM2F5h/RyCpCENb0Gs4Fq9HR0RRRTo/e59JDfnUNotyHnp4eTpTzgzCjFSfKRQCRd8ER4AhwBMg72X/68jjA6jkaHIGNiICr7RhuJk+WiSjfQ1MzuV4sRZSj0SiSpFMgUYdAB/JsaG6xGamxU6oPIsrf/idg+3bgsTesTYDJ3YGs2gpN4nFneBrxCGXNq8L8dARN26sK3sL1JMqUwbCXE+WC95A64ES5KDDyTjgCHIGtjsDYs599GKr2462OA1//xkVAlG3w1/06dnc1lCmi7F0kysFgAgMDV1BVZR4gZBj3N8Pna9adK0x1dCwOnBsA3vwWYOfOtbEkokw2babGee0W2WvcHZtGcF7Dnj31WBgLwtfuTSm08+0RWE+i/PP+fuw7cSLHiDK3h8u225wo5/8a4C05AhwBjsAiAuOnT31RY+x3OCQcgY2MQMD3KFoOv7oMRDlTozw1Fcb4eASHDtUtwkMWats7gKq04G0kAvzt3wAPP2wkzFirFIcoM9wdnQVTGbxeB2KzSTTs8qFQ5+X1IsqUEWV8oB9N5J9HNhwWCz/Mlx0oTpQtXkC8GkeAI8ARWA0B/+nPXGcMuzlKHIGNjEDC1oiaB36zDER5MiW9cOlwTE9H4PcHcejQkkXF9WuGZKI1zRRC1yj/PVBdCzzyKGXVWxlNsl+jjHfkU2z6GOeLfSSiIRYTwVQNTICedGOtPkk7TTrqlcrI6CjC4TD2dHXlO6382jGG0YF+tBw/ASEnoswjytkA50Q5v8uQt+IIcAQ4AosITD5zqjOpsWscEo5AJSDgOv4R+BpL62BouF6QRtlIbJKNKBMppnTPx44voUa/+9rfAw++ClgIALtTCT2y4UpeypTgg5J6FFKIcJPcg1Jnr0WOzXGoDelFKC31SmV8ZAThcAi7yux6QfMZ7e9Da453EDyinH0nOVEu5NXF23IEOAIcAXK7OH3qccbYX5YCjKSqQiZjVl44Aulg0ZkAACAASURBVEVCwNZ6EnVH3lKk3rJ3c+li5mE+gyiHcOhQZoiYstiRD3JDg9GPbg/3t8Ab3gS0tgJnzgD79gE1NUYSj3Qt8kC/4cG81kG+mzcnMDU1DFE0fKGXl1hMgiwfwoMPKjlh8tyz06itu7noN53RWBDg8I/BIYrofOtbs9fJaTRrlYPjfsyPjiI2MwtnTQ1khwPb6LSjhTuAvj4/jh1r5Cmsl0HNibK1a4/X4ghwBDgCKyLgP33qO4yxXyoFRJFYHE57aa28SjFv3ufGRUBQ3Gh67HcBwbp+NdfVLE84YhDlBRw6lGLEqQ7DYYAIL8lpKas2EeW/+xvD8aKzC4hGgf4+St5BjhTAyVcZDYeGDIK8x4Lz2pkzo9i/vxp2e3bv6EhEwOA5G3bsNPjkYl5CZhwyzFbiceDePQ29vRRazlIEAdPD44iFk9h5ZFeu8OVRX0NoahJakm4oYlAcXrBEHNFIELIkw1mzDXbv6mnL+/q49CIb8Jwo53E58iYcAY4AR8BEgPV/SRmfHJ1mgLcUqARDUbiddggrRMNKMSbvs/wIkPetYCHqV6yZ1R5/L+yN+4rV3X39LE84shJRpoYzM8DFC8DhI0BtLeAfA6prDCJMXsnf/WdgeATwuIFfeRdw65ZBaI8csTb9/n4/jhxphM228o3B2ChDOKwhHktCYwIUmUFQFDhWaENZBb1eY74rldHREELhBPZ0kf9daUs8MI9wVIXLKYGeQkUXAnBU10NNJuBwOhHy++HbuXNVJw8eUc6+R5wol/ba5b1zBDgCmxyBieeefLWaTL5QqmUGgmE9oqwopc2kVqr5836tIaBqGqQcDl5Z63XlWo6Gvag58b5Cu1mx/eXLk2hsJI2yeZgvmoooZ883PT9nRInr6oEdO4zoslmuXwfODwLjE8C2ekPTbCWSbLbv7x/H4cMNsNtXJsrxUAgLcxqq6my4Nx2CpIiwKxKqa/K//x0dXUAoFMeePUtOH6UCPBkOYn58BrJd0s2nHU4F0bkFMEWCBBFqQkN1e+uqw/OIMifK/z973wEfV3Wl/533ps+oWS5y75LcsIxNsyWDQycdEhLSG5sN2WTTSO+bbMpu/pueJWXJpofdwBIIBAgxtmQDlunGmpFwARvbWFhtenn3/H/3jUYejUbSSJqRZqR7f/ZP0sy955773afR984793yFuj6VXYWAQmAGI3Di3i9/Hiz+pVAQ9PQF4bBb4VDpF4WCuCjsxhMJWC2TdzNEmo65Oz4BzZYksmNpLASOH+tBdCDrIJX7O5C0gGPH+swobnW1wzQ9UkQ5NbeMHh8+DLzcmXwlVVFC04FgIBlhlof3XnHpWLwFZEQ5SZSHy/VnnHz+DMJhDQuXeRCMJBAzEpAJT7Oqxy88kgtRTsQTpqCFqQoIQNMJuj644kbQH0Yoxqie5TIjwsM9eEiEg5B6LharBs1ihaZriAeDMBICtvLyYXO0U2iqw3yKKI/tN0v1VggoBBQCOSBw8p4vPcjgV+TQdVxdunoDsFl1eFxnFc7GZUgNKmoEovEE7JP81KBi7TVwLR2hbMMwiIVe7sQL7S/CtSiVe5uSC5EDkt/L86c1NWXQ9SSJPnMm1F8ebnCO8nCbIuspS+KcapIky4D7/v1ebNy4GlZr7gdc9+8/gQ0b5o1AlGGWhYuEDOgOhkW3wt8XMA/CuR1jO+CXvp4kUY6jtnb4/IxAlx+nzkShWzRUV7sQ8cdhd9tRUXn2XMKJ473QhIFYguAul0qGLuiW7AcTJ3KRq9QLRZQncv2osQoBhYBCYAgCfM/37SfpTA+Yk2GzPDeZtyqJskXXUDHKQZw8T63MTTICU3Fo01qxALO3vn/MKw2ePo1ITxeqa3PPcR4rUR7OqdbWR9HQcC6s1twJ7P79L2LDhpoRifKYQchhQC5EWd4NHH+hG3EhULOwGlo4hhgTyqrsAzN0nfYjEE2gym1FHIRZs0Y+lJeDa1m7KKKsiPJ4rx01TiGgEFAIZEXg5D1fvZiReKhQ8BiGQI8/aD5unVVRljyOr9q0RCAYloc2C3K/NSJec7Z/CBb3CKoeWUYHO08j0tWF6rqxEOXs5eHGupmtra1oaGgYI1EeLfVirF7k1v/FF/v6I8oj5yiHgxEIQ8DqciDWG0EUMrp89lqIxRKw2izJahycU6W33BzM6KVSLxRRHteFowYpBBQCCoHhEDj51y9+gQW+WiiEYgkD/kDINF9Z7p7Uw16FWpOymx2BQCg8Jek1npVNKKu9LOdtSUTCCJw8hVBPN2bX1kG3WqGPJE/Xbzl/EeV9aGjYNEaiPHrqRc4AjKFjLjnKYzBX8K4qoqyIcsEvMjWBQkAhMLMQOHHvlx4Ac+4sY4zwRGNxBEIRc1SZ2wnbJOewjtFd1X0CCPQGQqjwjP1g3QSmNIfqzgrMveRjo5thAZEw0NXhQyQYhiZzkTUd7jnVqFi0JJmZPELVjjNnRq56MboDyR6trYfQ0LAcVmvuNaBzyVHOdf6x9BsPUT59GkjEgQX9BSqkAuCjjyQPMe54xeBqIGPxJZe+KqKsiHIu14nqoxBQCCgEckKAd37JciqCbmb25DRgHJ1k3mooHDVHOh02uBxn8xbHYU4NKWIEZHUT+dRgKlr1Be+CbdbyEaeORwIInO6Ga1YVosEQLHYbREwgFgvCXVkJZg2OEfLoc6l6kcvaZdSzoWFeCRHlBGprq3JZmtlHlsHb1wpcfTWweHGSIN9/H7BhQ1LOO4fgfc5zZXZUEWVFlMd98aiBCgGFgEIgE4GT9371PObEvkIiEwxFEIkla3DJaLKMKqs2PRHo6vFjVuX4a/ZOBBXXonNRseG1o5oI9YXh8DgQDfYiGgVsFIEhLGDNgvLqkUU1kkQ5gPXrs9dRHnXy/g4y6tnQUDNGolzcOcrpa5fCK7t2A24XcN0bkvnID+8FrrgyV4TG36+19RQ2bZqrJKwzIFSCI+O/ptRIhcCMR+DIkSOOeDx+GTOvlmm0MwkQa/jFCyncdUUh12wIA7LyhWxkltzKrSQWiTi0eA/0aBfISEakVStuBCRRrqrwTKo6XwoRzerEvEtvBmj46yvScwaRYNwU4mCzVi/B0Cxwl7sQCYThqsqFKA+VsB7rrsiayJs21QyUnctl/FP7jmBtw2LzQNxkthMvBhAMRbF6de6CIweeAR7alfSyZh5wwQWA1wtcPsZPmnjAD6tnbDdeTzx6BBvOXWrWYVbtLAKKKKurQSGgEBgzAsxMHR0dH2fmzzNzxZgNqAGTggCxAVuvD7aeZyHJs2rFi8CZHj8qy1w53wzleyWzNr8F9rl1w5sVInnTJkOc8os+NjLV1xeFVMgrL08v63ZWoCQ5sSmn0V+LWf6cvEk8W+6Fcfx4H+bPl/WZ5fzy/dTXVP/U+GSJGKuIgtp2QVuxCRGnrOGcsplaauYcqeLN6SIq8nv5errtVO3o9K9n1yB79vZFEIsZmDPH1X/DK33tk+8M2LJay8GizhQdkSr1J08CR48mvzcYkOXTpUrhqlXpnktfngUgzy+kfJI3KklibEv4oXXshbHyfMRtMu1D9k/HaejabUYI8DVj+aWXo2zhyAp++b72it2eIsrFvkPKP4VAESLg9Xq/B+DDReiacikLAnqsG64Tf1NkuYivjjO9fpS7nFMmVe5csAGVG99QUITicQEhMolq5pSZ5Dn1fvL1xx8/aSr+WSyS+A3X96xNgkD41ItwzJ4HWG0Ajz5msEdj7Z8ky0QMeZgvHI5j1arqgSdDSborpfhSTa4jefMg70GePQDs2ZuktaQBdXVALJZUI+x/uNQ/UN74pimyJHX9kpgYCfhaD6J2Sz3IIm2PvgZiAd++g6g/vx5WdRZi0CWgiHJBPxaUcYXA9EPA5/N9lpm/Pv1WNr1XZAmfguvk36f3Ikt4dTKiXOZywGbLXUgjn8vVLDbMu/STgDY18+e6lv2tp9BQInm0kiiHQrExpV6kcpRlRLmxEVixEtjbAlxxVa4IJam4PJi3ZfN8U80w17Zv/0s4t2GOylHOAEwR5VyvINVPIaAQwNGjR+dHo9HDXCAlOgVxYRFwnXgAlkhnYSdR1seFgCTKLqcdTvtZ6eJxGZrAoKqGN8Ixf/0ELBR+6HiqXhTeq+wzJAVHZNWL4SWsM0c++STQ0pIkyRs3AkeOAG0HgVe+KvdVyMizvKHYvKVmTERZVb3IjrEiyrlfe6qnQmDGI+Dz+W5i5h/NeCBKFACr/wicnQ+XqPfT2G0GZOqFJMmSLE9Vc8yrR9W5N0zV9DnNO56qFzkZLkCnnCSsM+aVxLivL0mSX3oJePppYFYVsHlL7g4mifIJbN4iI8q5y3kqoqyIcu5XmeqpEFAIZEXA5/P9lJlvVPCUJgKyAkbZ838qTeenudcyoizTLmT6xVQ10i2Y94pPgixTR9ZHW3tpEeVTCAbDqK0duUb1aGse6/vy0GVr6zPYsmU9tDHkXrS2Po1Nm9bCYpnc6iBjXd9k91cR5clGXM2nEChhBHw+36+Z+W0lvIQZ77rn2F3Q4v4Zj0MxASBzSmV5OKvVgvIprpVdufFaOBdsLCZ4BvlSWkT5OILBEGpraycVzyRR3octW84bI1Heh02bzlVEOWO3FFGe1MtXTaYQKG0EvF7v1wB8rrRXMbO9d55+GNbAkZkNQpGtXj4q7+r1m6XhZIm4qWzFnn5RakQ5FAph9erJJcryOF9rayu2bNkCkqUzcmxyzKZNmxRRVkQ5xytGdVMIKASGINDR0fEawzDuVNCULgK2vg44Xm4t3QVMQ89TRJmIMKuiYIroOSFHutWsfkH61B0qHMnRUjrM19FxEsFQCGvXrCyo9HQmXpEI49FHn8S5526Ex62ZZefMCnGjtNbWR7Fp02ZFlBVRHu1SUe8rBBQCwyHw3HPPzU0kEi8phEoXAVlT2X383tJdwDT0PJV6IZdWPUUy1umwVm26Ho6adUWJdKlElH0+oLtbmPWURYKwcHEXDENHzVwPenojmDe/zBQVyXfz+4FnngGs1jiCASsWLPSDtTBmzy4H4gnAakF1ZfY8+P2tPWjYVAGvl1BVBUjdEWGIpEQLyX/amKpo5HttU2VPpV5MFfJqXoVAiSLg9Xp9ACb7WWKJolWMbjPKj/4PIBLF6NyM9CkVUZaLryr3jKlSQSEAc85fj8qGNxbC9IRtlgpRfvxxYM0awOkEHmsFquecRjSmY/WqKhw/2YWammrY9Pwz5dOngTMvA2vWAh3tUkExhFCkF0sXz0aZB/CHEqjwOLPuw2P7gY0NQPNuYOEiYOWyOF46GYTVrUEnDeGogYULZp4QqyLKE/61VQYUAjMLAZ/Pdyszv2tmrXp6rdZ98kHoYfVgoFh2VTCjuzdgulNR5oZljPLQ+V6HZrH3i48UX/WDUiHKTzwBrF4NOBzAE48xZi/oAhsEj8cOIRKYVV1eEKLc2QnI/2vXAu3tQNzog8Mdg40sZnTbU+5CZfnZqiaBACD6Bf6efALYcA4QjycJvr/bD81hRc1cB4QwEAxEUVY+tTn0+b7Wc7GniHIuKKk+CgGFwAACPp/vRmb+qYKkdBGwdz0Fe8+zpbuAaea5rFLQ1U+UyzxO2IqgPNeszW+BfW5d0SFdmkQZOGejAYuVEArGYXNaYbfmfshuLJuQTpR9XsDtNlCzgCAMRiIhYLXqsPbPLYl0dzdgtydTmGVmhrz0zJxmAKdfjGPpyj5Uz3cjHoqDScf8eYoo57ofuoYLXTZ6NP/PDXL1QPVTCCgEpgSBjo6OdYZhHJiSydWkeUHAEnoRrlO78mJLGZk4AiwYXX3JiLLH5YTdNvWRXNfCBlSc8/qJLy7PFkqRKEu1vZWL/LC5HIhEozBIx9zZ2dMfJgpXOlH2emHmGs+bl93qgQNAMJiMessmCZ2ZjywbA/4AcP75DIsl+Y58Ty9EYvVEF13g8SqiXGCAlXmFwHRDgJm19vb2bmYun25rmynr0UQUnqNKeKRY9js99cLlsMPpmPqKE5rNjXmX3pxbuYRJBLJUql6kp15Iorx+RQBstcPmAgIRRoW7MHs8hChXAvNqsm+QYQDdXYDoZ8dSmySVhiFHWK1Joj3TmyLKM/0KUOtXCIwDAZ/Pdy8zXzWOoWpIkSCghEeKZCMgyYlAd1/QdMhht8LtnDp1vnRUZl/0PlgrFxcPUABaW19EQ8P8gfSBonIuzZlMoly7OIC4riMUicBV5kR1RWH2eCxEORIBnnvuLDk+cQKoqUGysgUnUzJq686mYhQr1oX2SxHlQiOs7CsEpiECXq/3CwC+Og2XNmOWpIRHimerDSHQ00+U7TYrPFMoY52OimdlE8pqLyseoEyifAINDTUlRZSfeBw477xkWoPMR5f1slN5wPkGdyypF5lzy6oX525WxDgTF0WU832VKnvjQmDngd5VukV7hwYyb7MZYGJYDaa/XbzWfc9IRnc941+jWbQmOcbsp/V/ZWFlwHdxfdnfx+WUGjQsAj6f71Jm/puCqHQRsPZ1wKmER4piA9MjyvKwVbm7cAemhGAkDAMy3cMQMueUYdF1839ms5bNxezGDxYFRiknSpYonz85MA46zOcDnPY4LPYw5s0rhxGPobM7DLfVCne5E1br4GNm+1uBhk3JA32ZTf5xnamH0hRRnpxrV80yCgItbf5roWlDkiYF83e313s+OtzwXc8GN2kW/JmARVl+s5834uLqizeUtakNyC8CnZ2dZV1dXT0yXzm/lpW1yUJAj/XAfXzEe9DJcmXGzyPJa3f/YT5d11BZ5s4bJrJGs4AdCUNDJNqHRDyS1bbN5obL6YBOsUHvz73ko9CdlXnzZ6KGFFEeGcFsqRduZwBWlwt2K6G3N4JwMAQjrmPOggrY0shya6sXmzathsXSf9PEjNMnAqistqOzO4SKCjccNgt0vXAR8YleH4UYr4hyIVBVNseMQHNb36tJ0/885C6W+dtN9Z5PZTO4qy2wQSe6C4SlQ8fhBTLENY3rylQNrDHvRm4DfD7fE8zckFtv1av4EJDCI/8LiHjxuTbDPEpPvdCIUDVBGWv5eN+AA4ahIRTqhsjYY/no32r1wGKR9XETiEZ7zJQA2RzOSjhsAjolf65Yew1cSy8omh0pxRxlM/ViMiPKp4G16wCpDuiwReBwx1FZ6YIRiyMQMCBiEfRFDCxfOQfWNNGTbBLWfS/6EXOSWe0ifDoC3WqBe44bHs/UV2aZrItSEeXJQlrNMyICuw8GX6npuDtXotzyrH8d69pdRFieZUw3J4yrtq+v2KdgLxwCPp/vR8x8U+FmUJYLjYDrxIOwRJTwSKFxHs2+YQj0+JOH+WQbj4y1pLXxBCFhEMKRPpkMO2DPanPD7Z4Pl6cGLtdc2J1VIO0s0YmGu3Ds6IOIhLvMMbrFjjKXDVL3xD57JWad947RljBp75cSUa6t7VfmeyyZozwZTUaUX+5MKvO1y9QLRwLlVQIupwVGwkAsJmCzaZAaIza7BZa0cm+tra3YtGkTLGm5F6eO9MI1y4FQMAyHRUf3mQgqa8pRVXVWtGQy1jWVcyiiPJXoq7kHENh1MHiNruMvuRDl5qd7VpDNcg+IhlbDZ/aD6E2Nde57FbyFRaCjo+OthmH8prCzKOuFRMDR/TRs3aokdiExzsV2ekRZ9q8qd0MzSw+M3mRpr4SwIxTqg2Ek0yY0TYfLXQNP+WKUlS+C3Vk9qiEZdX7h0F8R8J9IkmXdhnK3DbrViprLPg1o1lFtTEaHUiHK+/cDixcnaxQ/+yywdetkoANICetjLySJshQcWbBw+DrKmR61tu7Dpk3nDiLKibiAxarBEGxGleNxKVqS27U5OSsu/CyKKBceYzVDDgjsbgtcqWn019GI8oNPvrzQ5nT8hUAbh5hlxMHizY1rym7PYUrVZYIIeL1eGc0/PEEzavgUImAJnYDr1ENT6IGaWiKQSZRzkbFOCKuppBYK9wAsyYsbZZVLUVa+BJ6yBaBxEFsWCTxvkuUXzY1xOMvgtgOzzns77LNXFcVmlUod5ReeB44cDSCRiGPJ4iqsrp0c+MJh4OCzUsb6FGbPnoc1awnuHFPeW1sPY9OmpWdzlCfH5aKfRRHlot+imeFgLkT5fm/nAhdcd4KwZQihBgwI3NS0xq2klSfxkvH5fKeYeRjdp0l0RE01LgTIiKLseSU8Mi7w8jjIMAz0+EMDFss9TlgzSg/IyhgJ1pEQGqLhEISIwemsRlnFMpRXLoXDNScvHrGI40j73QiFTpv2ytxOVNU2oby+OMqml8phPondyZPHEAyGsGrVZEuBM2S+8XlmYnTu0d/W1lPYtGkuLJbcx+TloityI4ooF/kGzRT3mr2Bq4hoSLoE9x/mu+8p/1yXQ5PVLbKeKhECn9u+xv2vMwWvYlmnz+f7EzNfWyz+KD/GjoDn2N3Q4n1jH6hG5A0BWa6tN40oL1t1FU6fegxRGS2WEWcjYRbNtNrKzGix27MA7rIFsNo8efMh3ZBhRHCo7XbEYn5YLFZUz1uEOds/VJC5xmq0VCLKcl3HX3wRoVAItatXj3WZE+ovD2a27t+PLZs355zCIyeUNyGbNtUoopyBviLKE7oc1eB8IdDiC14NYEitKmbx9S5EvlVNzrsB2p5tPsH879vrPTc3P91TFbVq2qFge9/7t2wxj/Lf6e0sc0QdTiMcizjDfTFj9pyKWDAavubC6kHMQPYrj2oVhs0avmxN+Zn7njrltsFaFYMtduXGMjO0cs89HXbb8nmeWG88nj5+98HgfAhRRcKINJ1TOSQVYffj/jmaHXMFg7stkWOvrZ/jT63jrv0nXHaPtVKPEGnyKDoAi07aSZw4VRNbWiF/jjlZ6BrIiGm6TSfNEMw71nvkCayzp3XytRFjtOPz+T7GzN8Z4zDVvYgQcHY+AqtfZdBM5ZZkEuX6DW+DxeoGCwPxuB+aZoWuO0Da0FrHhfI7Gj6DQ747zYoZUilw6VWfhuaYetX6px49jPWbl0JPlTArFAB5sHvq+HGEgkGsqJvkiDIznty3DxvPOw+UY667XO6+fS/i3HPnK6KsiHIern5lIu8IDHuYD5CpFLMJGCZqyb9srPO8R5LGZm/gu0S4gZl/1lRf9vl7HjlTXl5llwmYC4VBV0PjyzTgkwz6j6Z699fTF9Hc5v8yNPoIMf2+sd79gWZv8D0g/n8A9SVgXLGjrty729v3Wo20n4Jxf2O95+2SOJetmC/V6W4koiqpRMvMzYkEPrJjvefJnTuPOKwLZn8BoPcBNLd/vkNs8Feb1np+JX9uaQu8hQk/BEielBnQNDXY2K5r+neJsR7gCAgJqSgKkIOYj8RPdm7asWN59oKoed+d4Q12dHRcaBjGw5M4pZoqzwgo4ZE8AzoOc5mpF/Ub3g6LtXCiI7m62NdzBC8cvh+6FCNZcBWCjjX9Q9Pv0fv1js37dnmvn5KlSO8jX8uUrMh8TdZhkLbkV9lS45M2GQybEQK1tQCrtiDqmAOCkbaUbHIY6XOYunhpc2T6J/vKudPXkPIj03b6WjLnOOuS4+RT4GgYsWXngwdSIMY6R8q+tHvWx4ULZXk/DbGYgZMnU7GXpNqWXT4h8u0Fai9C1FYJGsA0ZSPzCiAwC0SjCWzduiQpYa3aAAJFF1Hez2zdDCSI+os4lvhmMTM9Bli2EE24WOl0wyZ9a0cgygYB2cMojD/FT55+W4ow7jwQaLBYqBXgzpNd3SvnVVe+Rof2B2a+r6nec9Vub+DfNKJPyCi1JNLp86feA0zi/e5mn/8mgvaj5Mck/6GpznNDi9d/PUj7I4PvbqrzvLq5LfgPpOEWMI6C+adCQ50GnBONJd546YbKQ7u9/q9qpH0BzF1g/iGTNpsI/yhtCgOv2b7W/ZeWtsA7odEvpQ0G7gMJ8yMqFjO+ZbVZ30rMS4joEgArwXyAmXZBQ2fixL6v79ixQz6PndLW0dFhF0L0MvPMqRU0pYjnf3IlPJJ/TMdqMTOiXLfhbebhvGJop0+04vSpxzFr0RrMvuC9aYQ3ncimPE0nkNmIcqpfJvlLJ6TpdgfPQWwgdOoEHHPmgSy2jIdq6TZThDCbP5lzZxL4bPNn8zt9dzJvDpJzJPp6IBJx2GbJ/PF0sj1xnFJCiqagjCx9Yrb+OYSByEsn4Jg3HzDLAOa2F1LsRoqJqDYYgaIhynvag7cw6J1gtpskmeGzWLTXXrDS0V6Km9ZyKLgFCbqNCMskWSaiEBN/r3G1+7NjXc90wybb+oerozw8Vrw77I+95vIts3rT+7T4ArcC9C4h+N2ahjcy6EoyEo2NayseafEGvg2im5nF15rqy74waNzAe3xrU73nPbu9/g9opP2YwZ0EquZEYis0mitFUZjxf0317tefJcLYLxLindvXlx1M2Xxgf1eFs8wuxU4WQIg3pCpxpHwA+J7GOs8rm32BtxPoV8z8P031nuuzrbfZG/g5Eb2Xmb/fVO/557FeP4Xu7/P5Wph5W6HnUfYLhYASHikUsrnazSTKtRveCpu1MPnHufo00I8Zh9v/DyyCWPm6fxnzcDVAIVDqCBQFUX7kMM9LxEOnMsEk4Cvb6txfLkWQ97aHfyJYmNHDVCMisXW100ZE6c+LRlzedMQmKxlsC76KNNyV014zWgOJxFVXra9IVsdPazt9ffUW1ltBHCamSgbf0VTveZPskgtRTkWU04jyd8D0RiI+aoB/LCPUYNzZWO9+3d+9fXVW0u8hYIXpAuNhZvzy5DN/+cWctddssFrpcWY+E2VRL/OeZZfmZ3svIIvlEWZub6r31O3yBt6qE/2GwT3E1CaDA0y8e3udZ+CGKkX+mfHjpnr3B3PCaBI7eb3ebwO4eRKnVFPlGQHXyQdhCSvhkTzDmrO5eMJAX+Bs1YvVa6+H3SGzuYqjxWN+HPHdgRVXfQQWT36qaxTHypQXCoHRESgYUT5wmj19vdFtMLuWfwAAIABJREFUgo3lxLQMwDIQdBB3g3GaoD/itNpbNi2nnkc6omsTIjFEapiIvret1vWR0ZdRfD1afKE/AjwkQui2uarkmnP1eDpik23tY4ooM3ujIn7VpWurns9mq8UX/D6AD4ERMgw0XrzO/YTsl5Z6MSSi3OwNfIuIPplJlAXzdzXmQ9C0H0iiSoQPgHFXY737tdLmTl/fbCvrHzD3mmi9fE0wfzIeT9xus1l9APujMdRftsE8fIeHnu1rslj03Qxua6rzrB0gyowAEV5ihhUk7muqK/uH1NqKnSj7fL7XMfMduV7Tql/xIaCER6Z2T+KGgb60qhcr66+FM0/l3vK1sjOnn4Jz6XK4lkySxFy+HFd2FAITRCDvRJmZ9b3tofeC8FVmjFxfleiOxlrXtfueCy2OGfzCkLVo+MZ4UhUmiElehu9pD/6CGfKQ2aBWWeuyrycy5ZP2Phe5ioXxT+kdGNTbWOt6a+q16YhNNoCbxxJRlsFb5sdZ0Ku2r3WfzLTXfDBwGen0AAOPNNW5LxognKn0CiG+0rSmbNCTiuGIsiTOJ8503zR/VtWTIFpKgJ2BO5rq3Nfu3LnTgjnnrZcH99KJuIws9x0+saN8xXw5ph5CfKhxTdkPZZ9mb+AXRPQeMP9GHgg8m3qB/zsYaLu+1l+td84JiuvXr09KbMlIeH86SbFGlI8cOVITjUaH7ENefpGUkUlBQAmPTArMw06SSBjoTYsoL699tVkCrthaIHoYnnNkgSLVFAIzB4G8EuU9h8NLOSH+Asa6nCDsJ8rMrO1tDz3JwIbUOJmmwBpd1rjKuTMnW0XW6eGO0PWCIQ+SDWTGE2jntjrXK1Ku7vEF/4GBWzJcf7mxzj3wbGs6YjM2osx9AGWtScSMvZFA9JohecoHA5dDp/sZeLSpzn1har6zEWUcIeI2ZrOKRPfBQNtb1nnqv57MX+ZfN9V73tHs83+QoP0QzL9trPe8rbktcANp9DvTVn/qRYvP/3VA+6wk5Az2aSCZp7uK+4l46rAfSzEU5tsJqADRFTLNQiToFTLSvbst8C5No1vB+HMqSp2Jz25f4Jca6J0M/LSpzv3+IrvUTXd8Pt9zzLyyGH1TPo2OgBIeGR2jQvbITL1YuvJqlFUsKeSU47IdDZ+CveHicY1VgxQCpYpAfolye/BuZrwyZzD6ibLsf4DZFjgcPt8wtAqNOSofTW+tcyV1NEu0PXo0vJxjtCrBsFo00XXBKmdren5yLkR5umKTuaXDRZRljWQCyyrDg6pUpMbL6O7JM11vvX7r4vBZQty3TSNdVpJ4qrHe/YbU6y1tgc9AMw/FCYDsAFtBOJ040bpFn3/eRwn0T8T8p8Y1no/Jsm0g+jqY75A/y+ixZcF5sqTbRjDtaqp33/SQ179Dh3YTEW8Hk4eBl8H8u8Spzq+kKnE0ewPvJsKHGFhODHk2+QnDEF+5ZF15s/Rrd5v/Ok3Tvgng3sY694ezXepm6Tqia0H4XVOdR/Ytuubz+eSBxLcXnWPKoZwR8By/G1pMCY/kDFgeO8bjBvqCZ3OUFy2/FJVVxSEZnb5Mecpe1FRBr1BinHncfmWqyBHIG1F+uD10rcE8Ni3UNKIsUww0GlQ/BVa388zGGgpKDPceY6ctFh5yimDLSpeZsiFzeQUbGzVd23/hSkdHJu77T7ArFo0tgRALWcB8pkWCAzosh9211rZUOkRLJ5c5+sKDTlHEEjAySfsjHaFFFm2wNmS6v490cLlFC1em+xGxcqJxifuELPOGw+H5MYG3CMHfSO9DQJfdQpvkazGbM7B1MXWNhk36+KdOsTsQiC3XBc83iGvMLAWIPgJ1VlQ4n1k/lwLFeE02t/W9WlaUyPSNBX+zaY3nMwN5x9mcZ/7tA7//t3d85StfMQtw3nbbbToWXSRrByGdQN924IDNGZllCTu6Ep4X7KQvLJN1c3DlxpqgfM9umWe3Hu6JXXPN6mgyrWKdA53BRFq9YrrtwAFZ7xjpqRGyXrPutDmAYFDaynTRtFXZYB5h37GpalB+unyv077K2m17KZESSck6Xo7dsUMeAp1ykZFsW9De3v6PQoifFOO1pXzKDQElPJIbToXoFY8n0BccuNfHgiXbMWt2qmZxIWYcv82EXcCyrDh9G/+q1EiFwPAI5IUoM7Nlb0f4KDMvzDLVyxpp/2zRuDlhd76sh+K1BhnrmMQ6COraVucyVb32tIeCzDyowjpp2tu3rXb+xiTKvtDrBfj2TPvbal3WvR3hXzKzmddLoBu21bn+kOonq0aIePhTTPhHZnZmg4KI/rCt1nVDvx8fZubvpfcjouPbal2L01/b0x6UB69SIhLmW0Tae7bVOm+V37e0h24Gs6wGMNCI6NC2WteqvR2xTULEHx/twiTg59vq3DeOho20s/8oz4/Ewp8E430AZ60rJNNZdI3Pv3CV+7HR5p7s94clyv0S1pL8zt949U8I2o3ZfJOH7rbXez5WrERysvGc7Pm8Xu85AJ6a7HkLOZ8USnS73bDZbJCCEMFgEInElJeuLtiSbX3PwfHyvoLZV4aHRyCWSMAfOEuU5y28AHPmNRQlZCwjWqtWyz94RemfckohkG8E8kKUkzWD0ZrNOYuOLbkQs9HI4HBEGdA+B4gBlTWd6LqLal0moZaElDmxZziCnPK31ImyjFBH2kNSHW3zaBeIZrGcs3Wl/ZnR+k32+8OlXnA/UZb+yKjvfOuy/ybQm7OSZYHPbV/j/tfJ9l3NZx6u1Hw+n4yWl00HPJxOJ+bPnw+r1XyAYDZmRm9vL06fPm1+P92aFuuB5/gQFfnptsyiXE9mRHlOzbmYt6CIq0vU1AAVFUWJpXJKIZBvBPJClPe0h4ZEYU1HiR5trHUNHKYayflxE2WCLDc3kCqhkf7qrbWOu83qGx2hfcw4dzTQSp0oD5PrnHXZNmgrz69zHh4Nk8l+f7SIcsofKQttmT/nV0T0xiw+Cob4UFNd2Y8n2381n3mg735mvrzUsZDkeOnSpUnZ3izN7/fjxIkTpb7MLP4r4ZGp2tRMojxrznosWFzEGj4OB7B06VTBpeZVCEwqArEEEMtZ/eKsa7qGC102etR89rK3PfRtwTxUcIC0WxprnYNEN4Zb3biJcoZB0vQrt6123L+nI3gTC5gSxEMbJYhwSh7mYtBsAv5nMlMvHvXFNsYp8QgYFoDNPNlBjSgifybg1m21rptGw6alI/QDCB5UZo6I9gH8gLTD0GYDYiUYDRara/2FK6jolAVyJcpyPXftP+GqLCv/I4FelQkdMxKCxNsuriv746T+JqnJJFH+MjN/qdShWLJkCWREeaR25swZvPzyy6W+1CH+u07+HZbwEO2nabfOYltQZupFxazVWLxsoEBSsbmb9EcSZUmYVVMITHMEwnHAME9Aja0NIsp7OoI/ZYEhuaNE+Nq2WvcgqeDhphmNDA6femFSSlnu67fEWgfrjr9uW0Wn97SHfpPKW06fkzT69Fw4v7t6NUXl61IYxd8TW3xRrb1N/pwtOp7vHOWUP7lWvRgNm5b20O1gfn36OjVon72o1vHtsagAju0SyG/vXFIv0mdsfrqniuyWOwFqyvSEGUGwcUPTmvLclP7yu5QZa62jo+MKwzDuK2UAZDR5xYqk0OJITaZePPfccxBiHJ+eoxmfwvftXU/D3nNgCj2YmVPH4gn40w7zeSqWYNnKIq9XLFMvZAqGagqBaYzAeNMuJCSDibIv9GsGvy0TK0nWttY5B1V1yDtRJjygOV2v3bqYzp6ESB6mexjMg9I+CHTntjrX60ba01Ikynvag7cwY0DJbWB9hG4CPUjA7fOtzjuWL09GqouxDafMl56jnOn3354JzLPb6P8IGJLew8zdBhlXXlJXkTV3vhgxKHWfDh06VJFIJLpkvnKprqWyshLz5uVW+krmKnd3d5fqUrP6bQmfhOtkSZauL+l9yCTKLk8NVtSa4p9F25g0YOVKQCvZX/eixVY5NvUIyFquCQHEx5FykfJ+EFFu8YV+CPAHhyyN6LuNta6P5rLk0aKmw0aULTivcaV7f+YcLb5gJ4DZ6a+TRh/fttr1/6YbUd77XPB1wsCIEsJE6CXWPry1zilrARdd2+3re50GfegaBP+HrGM8nMO7Dwbnkw4p5jE0F575DBjfYQ3m04Pp0oip99lA26+GKyc3lev0+XxPMbOsgFGSbe7cuaiqGlQdcth1hEIhHDt2rCTXOZzTSnhkarYzkyjbHZVYvfZNU+PMGGaNzpqLeHluvy9jMKu65oCATU8WHpGEbiJkLoepVJdxIjA4otwe/BozPpdpK/2Q3GjzjJcoN9a5h9SokeXq9rSH4kP8SSs3N5w/pRhRlmvZ0xH8Opg+PVo0j3Tt0m2rnH8fbT8m+/37vZ0LHMKxXdMgBMMgcIw0PWEIPn7xGs+IVTr+eqB3lstK24nJKgiaJkhjgk6AlcF2TVbJH6GJjPrd2bqmbMi+o9ljaIPm4zHWPiYzPf1sGxivJdfBEH5xYv+fduzYUXS1yrxer6ylnNO5hMm+xnKZbyxEWZaKO3ToUC5mS6qP+9jd0ONKeGQyNy0WS8AfOvtQVLc6sWbDOybThXHNJax2hBYuG9dYNWhiCCiiPDH8JmN0BlEOv4tZmPWDBzVCd2Wla0kuIhf5JMrShxZfUB5Ln5/uDxF9aluta1Bt40yXS5Uom2T5cHgpJfiNgiHTSy7IdlCQSB4QdL9nMi4SNcfMQ8Dn872dmYvyqUUuuzGW1IvpSpSdnY/C6p9+NwC57P9U9YnG4wgEz2bGkaZjXcP7psqdMc0bqlkC4Rj58OuYDKrOOSGgiHJOME1pp8FVL56LrBKGMUQNT3pIoB9X1Do/mlK+S/daKs6dv8plPrvMP1EONQPcOJi400ONta4dIyGXlSiD/NvqXOXp47KmduQoOJKyk+0wHxH6ttW6BxWoHA2bbOvZf4JnR/zhHwF8/eCbBdy3rdZ91ZRePaNMLsVFatZeuRkWbXM8Ev3zpQ2zB6TMzUN8Nuu1gkXPg3/49zukGl/LwcDl0GhJhI3/u2xN+ZlM881tfbVg7cKEwP071nsGHemXyngyMtt8MPAOIlDfkZN/kIp9vb7dkeuvv35IdtJDz/Y1WYjj8ajwZqjs0e6D/jcROBqLxfal+zzccs11bri60dD42R11pt8DkWip9uepsG0CcSJw+KX9Ui2wmPcs5VtHR8dKwzCeKwVfs/losVjMw3xSbGS0Nh1TL+Sabf7n4OhUwiOj7X8+34/GEwikHeaTttdsfA90/Wwd73zOl09bcU8ForPVob58YpqLLUWUc0FpavtYgVqHgzoG/prsaQ8eZEZWXUupSAeglYFTYC4jkMwdPo/BWmOd24z6jkYGh8tRzpZ6Ie21tAd/CcY7s8D0CyusP3A6rC+EdWiJUHwxyFg/oADYEX6PEOIXQ8bp9ObGVa4/SolrrSf8wUzpadk/V2W+s0Q59GYG/z5zLg10wdY618BfqtGwafGFP6sBx6HTXttK+/NbiMy0kz2+4JcZGFSui4j+vK3WVdynRABq9gZbibBZZIiI7HrGv0a3afJaeyFxct9Kk+T6AvcT6HJhYPP2te4hioe7fYF/1UCfSclhp/CWrxNwXheHr50F52MEWhZhY76dtJ+AaEksHL4uk/A2ewNPE9EGNvidTWs9A5HT+5465Xbby9pBWMCGcW3T2vIRc8alD7vaAhs0oseJ8FLcEFdpJOkZz5LEGSyWWcnaKit4JKKR+h0bq49P7a987rP7fL7TzDxEbj53C1Pbc+HChfB4sopbDnKss7MTXV1dU+tsAWZXwiMFAHUUk9FYAoG01AvZvXb9W2GzjX4dTr63g2eUh/qCi9WhvsneB0WUJxvxsc/nscNDRMGzRLkj/HYWYqyPXE8Viijv6Qi/jYX4dS5LI6KObbWuWtl376HwpSIh/pZ1HJkl5SxgzqpEMFai/PBzoW2GwS3Z5pLkiXTL5VJFbzSivMcXfJqBDUmyTszgHjDZAHZn2ibC17fVuj+fCy6T3afZG/gmAZsYFCWpMkhYAHkgD3iMCVI49f+xwGnSTBXIQyEOXewIOeLkpt8R6DIYfMUJcXTX9evXx3Z7/R/QoF3Zv4YFIPPGrJeAFma4ifkPgqhCI/oWs/hnkPZWgJezQe8mHXcCuDNxYt+bHnroIXHpmz55NWnCBZKS5dp3CLAz8GVm8ayZTxwzHhM2sE7WZ8HQo/H42ks3VI767LrZG/geEUmxnvaTiaMb5luW3UpEb5ES6iLOt8gbAoD7ouHI2lwi1JO9X8PN5/P57mDmEavLFIuv2fyQNZQXL148YlRZloc7cuQI4vEhRyGKeWk5+sYoO/q/IDEd15YjBJPcLRtRXll/HZyuQefRJ9mr3KeLzJqHRHll7gNUzwkjoIjyhCEsqAEiPOax0xaTl6VmkofI9raHb2fwWKKVBSPK0q89vtCDDB61ans6Ud53hGvisfALDB7zM6+xEuXHO3hOWISPM9iWnSxbN22rtT05FqI82s5bSL/iwlqHKURSbK3FG/g7iAZSYxjyUB8GbkqY8WOAX09E8+V7APvNi5DJDYKVGQFmfsP2NZ77mr2BnxPRe+X7DETBSJikluAyX2PcYkD8UQf9iYFfaESvB/NcZvwIGt5Lgr/AceO2xJkn/JYF5x8mYPFweMnoMhNe0jT6KxhxBu8FkEo4tBNBY+Y/NdWXfT9lY5e3Z7kGy2NEVAXmjz7w+3/7/mU33OwlotUs+C0COKBr9LQkyvFIdN1Dt3//xCWXXKJJ4i7TTYpt79L9aW9vv1kIMeJZgGL2X/pWXl5uSlgP106dOmXKWU/XpoRHJndno7E4AqHB1TuXrX4VPGULJ9eRcc5m2J0Iz18yztFq2HgQUER5PKhN3hiN8Dm3nf51EFGWP+w/wa5oIPxNBm4Ecy6SPYUlyh2RlSyM5sxDfZlQpRNlk2C3h77HzB8eAdJUnuugxKyxEmVzLl/omwz+VLa5iPJLlEmj72xb7frE5F0qY5upxRt4EMACgH4H4n8SzF8mom+wQa9gI9Kp2axLwdqfJbmUCnwy6i4JsLm/BJsZfRa4oXGt54Fmb/DHRPhHZn4vET7MAt8mwhcFic/Ew7FWzWavsujafhkdBiCJ55BioIbgKy9e47m/2Rv8T4CXEGEbQOUMPkhMHSC2MEMXLP5Fg/ZqKWYz7IoZdzbWuweirC2+wK0AvQuM5+PhWAOctMpC1kfkjQEzPw3AQUTyKYcA+Glm00crQH3ROF932QZP0akrptbu9Xql9m7WJyVjuyKmtrcky7IKRrqUtYwkS1U++X86N3v307B35yg8Qho0zW7WqmKRAJuR6BELzUxn6Ma1tkgsjmAGUV60/DJUVq0cl72pGBRctAJsGXN8aSpcnRZzKqJcxNtI6PbYsIKIeoYQ5ZTb+4/y/Ggs/Clmvp6I5mUrWWbmLTOkAMjH+8lpkJnNaF+qUVo5t7HmKKdsHDnCjpPx8PsF8HEwD4kKEpEsQ/iXxlrXa1Jj9h5jJ0KhTzPRzcw8cJxXpjWAsZOd/HZE8Q0IDKrfMx6ifIDZ1tce/gcBfIwIy5h5IEqfK1Fu6Qj+NxhXgzEkL5RAMSbeTUS3bF3lvF2ut1gvrxZv4D4mnA9QO4BziPlhgLYx8Z8ADjDTD5EwHJrV8qhMvYiL2GVxSsRccP0vCBexEDsSp/a3mHnLbcEfkoYPMvhvAO0AcwsRXcyMu5jwPBnG36FpkoheQkSDDzcye5n5jwkkfrljTdVRidcD+7sqHB6bF0RzwOKGBPEzfRx98bX1c/y3HThgm29Z9owktoL5uyTEbiaSZfiZSfs4Ebay4E80rfF8R9pq9gauAuguIlhSedPNvsC/E8j8XRitRY3YskvXVj0/Wr+pev/IkSOOaDQqw61Zn5RMlV/jmVdmjct8ZanYZxgGgsEgZLWL6d5GEx4hzQpX2So4PEtgtc8yH9WkmvyQFEYERjxg/k8YweTXWB+MRBDCGKQNNd2hzGl9kWgcwfDgiPL8JY2onr0up/HF0ClWUY1YVWmkihQDXhP1QRHliSJYuPGahn902+iWAS472lSypvHD7WEpdbUQGjmJtdPstL20dTFN+ikYkwBHowtZ8AKNoOnQOhMO2+FMVb+BD3xmS2t7ZElCw2IIDrPuPCrlsUdb83jf389sFYfCNUyak8nee8FyyLn0vR3h6NCbDf2VjXWOe9LnkuvTIuFq0jSXrL1r1+ydm5Yn72hKoTV7A/eC6HJiREFwyoNsJFMlGBGZMiHYeB0lEk+Qxf4cJ9MoThGbkeA5IOjxOG/esd7zpFxrszf4IyLclLnu/ki0BYJvNoD7dML/yCi2FOEhkJ3BLwK0gFl85lR3z8+v37rY/Kve7Au8nUC/YkYLgY8y0Q3M4kPb68t+0tLmvxaaJsl8X1zEN3Y+88CxZ599ls2KHN7gXknihRCXbF9TtmvnU2cWWRyOXQSYOsmSQHdR+KfV5JIS6gsZuB2MJ0BiCUG7EQx5o/MDMEkJOJmBHjlD4VskQS/mPfX5fA9zhjJmMfurfBuMAImYmaecrTncS1A+ewt0PZeHhkMtCJGAkegn0XG/+X1C/o/1QiRCM3IrotE4AhlEee6C8zC35tySwUNYrAgtGl3+vWQWVOSOKqJctBv0szIHDVJKHr2GUtGupbgd29MeawDEQkC8kpk/kOktafqqbasdox4YK+5VDvZO5igzUM2M/9A0+poQ4p+J6Acs6EZNx91s8OVIJA7DZvUlBYlYRlWZiOSTArswcF6q6kU/Uf6ATL0AQaoxfpgY3zWAD2sw84aOEaSCHOlgvpGJPgbwigQSV1jI8nMCbZQpFdvry76YJN6BvxHRpcziegJdB6I3Gcxvu7je89tmb+ApIjqHmX8BFncS6T9g8D4O8Qc1l3aUwdFgwljVh2OB+dZlfzEPHvY3eZBQCitppP0YzF3BKK+5cmPZ6d0H/Gs1q/asPIAYjBsrrlpfMek3lhO5dnw+33eYeVhFxYnYVmMnBwHPsbuhZQiPeKo2oKzKPDdckJZIBBENHkckdByxcNFmF+V97ZFYDMHQ4AqQ1XM3YP6irXmfq5AGwzVLYKiayoWEeMC2IsqTAvOYJiHCv7tt+FTmk3tFlMcEY+6d97QH/4sZ7846giiybbVTlh2ZgAp57r5MVk+Zo8xEtQx+kIDXQuC/iHAjg35DhA/IqCyT8YJOVnmDcMiIRV4hyB63WOhPMr0hvTzcbl/wBxrwQWb+ARHdCODnAN4nmG8h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diff --git a/p__knowledgegraph__Detail__components__Content__components__AbilityMap__Detail__index.8bc82d3e.async.js b/p__knowledgegraph__Detail__components__Content__components__AbilityMap__Detail__index.8e31dc24.async.js
similarity index 99%
rename from p__knowledgegraph__Detail__components__Content__components__AbilityMap__Detail__index.8bc82d3e.async.js
rename to p__knowledgegraph__Detail__components__Content__components__AbilityMap__Detail__index.8e31dc24.async.js
index 73ffdbf85e..119618c4f3 100644
--- a/p__knowledgegraph__Detail__components__Content__components__AbilityMap__Detail__index.8bc82d3e.async.js
+++ b/p__knowledgegraph__Detail__components__Content__components__AbilityMap__Detail__index.8e31dc24.async.js
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diff --git a/p__knowledgegraph__Detail__id.c6ef8129.async.js b/p__knowledgegraph__Detail__id.dd16dd62.async.js
similarity index 99%
rename from p__knowledgegraph__Detail__id.c6ef8129.async.js
rename to p__knowledgegraph__Detail__id.dd16dd62.async.js
index 218e7c0219..81814a9d5d 100644
--- a/p__knowledgegraph__Detail__id.c6ef8129.async.js
+++ b/p__knowledgegraph__Detail__id.dd16dd62.async.js
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",Ua="data:image/png;base64,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",Rs="data:image/png;base64,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",Jo="data:image/png;base64,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",Do="data:image/png;base64,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",Ca="data:image/png;base64,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in Pe?ja(Pe,ze,{enumerable:!0,configurable:!0,writable:!0,value:be}):Pe[ze]=be,ys=(Pe,ze)=>{for(var be in ze||(ze={}))Ma.call(ze,be)&&ba(Pe,be,ze[be]);if(Zn)for(var be of Zn(ze))Xa.call(ze,be)&&ba(Pe,be,ze[be]);return Pe};const Ja=()=>`shadow-${Math.random().toString(36).slice(2,9)}`;var Ba=({percentage:Pe,startAngle:ze=270,strokeColor:be="#42BECD",trackColor:bt="#e6e6e6",innerBackgroundColor:Kn="#fff",text:It="",textColor:li="#000",textSize:Zt="1rem",textPadding:kt="28rem",outerDiameter:yn,innerDiameter:Ui,maxTextLength:ji=6,onClick:yr,hoverEffect:Lr=!0,style:kr})=>{const[Vi,tr]=(0,ve.useState)(0),[br,hr]=(0,ve.useState)(0),[oo,ur]=(0,ve.useState)(!1),ar=Cr=>{var Or,ei;const jr=parseFloat(Cr),is=parseFloat((ei=(Or=document.documentElement)==null?void 0:Or.style)==null?void 0:ei.fontSize);return jr*is},Ao=()=>{tr(ar(yn)),hr(ar(Ui))};(0,ve.useEffect)(()=>(Ao(),window.addEventListener("resize",Ao),()=>window.removeEventListener("resize",Ao)),[yn,Ui]);const Mi=Vi/2,zn=br/2,Gi=(Vi-br)/2,Br=Mi-Gi,Hi=2*Math.PI*Br,Ni=Hi-Pe/100*Hi,Fo=`rotate(${ze} ${Mi} ${Mi})`,Bo=((Cr,Or)=>Or&&Cr.length>Or?Cr.slice(0,Or-1)+"...":Cr)(It,ji),Ro=()=>{Lr&&ur(!0)},bi=()=>{ur(!1)},Nr=ar("4rem");return ve.createElement("svg",{width:Vi,height:Vi,viewBox:`0 0 ${Vi} 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",Fs="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAUYAAACyCAYAAAA+o2ZLAAAAAXNSR0IArs4c6QAAIABJREFUeF7tnQl4VOW5x9/3O5MVEkBKlNWi7KiIGKwKWvfS2iu2FfXa61Izk5CQWRJUtKijoAKSzEwSIMnEuty6YavcVqv2WldEBQEBERAQhQAlyJIEkpDMnPf2BKxeciaZmcycOWfmzfP48DzmO+/yez/+fOd8GwL/MAEmwASYwP8jgMyDCWhJoPDBdYPa5NZJCDhaJhoJAMMR6RQgyCDEDCUWJGoEhEYiPAgAWwXiFgLalCSSl5c/NK5Wy3jZV2ISYGFMzLprlrXTSWK/vPYyv+y/AZAuJ4Lh3XGOCFuB8G1JSC/1E+PfcTpR7o49fpYJqBFgYeR+ERUC+XNXDva3YgEQ3QIEg6LiBKEWEJ+VkmnR4tkTd0XFBxtNSAIsjAlZ9uglne9cPUz2++8hwtsAKCl6nn5oGdsQ6WkhSfMXOyds08Yne4lnAiyM8VxdDXPLd27sKctHnUBgIwKThq7/7QoRfIDgEaKHc7Fz7JFYxMA+44MAC2N81DGmWUyf/elUArmCAAbGNJATzhFgN4KYsWTu+cv0EA/HYDwCLIzGq5luIi4s25rSWne4BIAKgg8Kqeno/pb6A980Hj1S19zUsK+lpelQa2tbs9/f2tQ+kSIlp4vkpDQpNb1Pcnrmqak9emal9ep7ekZ6j36pABRCn8VFyVm9i8utw48FHx+3ZAIAIXQyxsUEvifQPrnSgssA6LyuuSA1Hqo98s/daw/U7Vlf39rc4Ov6mY4tktMyTVkDzul12sDxfTP6DOoZnEjiGimVpvLkTDjEE/cZFsbErX3Ymec614wBv+/NrmebkQ7s23Jo28bX9zQ17o3oqC09o3/KsLFTBvQ9dWSfLgVSmb2WTNdUOc/7Iuyk+cGEIsDCmFDl7n6yec5VE8lPrwPBKZ1Zazi0q3H7xtdrDx/4qqn7XgNb6N33jPQzx04ZlNlncPvi8IA/CAdRwimVzuyV0YyHbccHARbG+KijJlmcGCl+0JkoHmuuP7bt81d31u3Z0KBJUCecZA04O3PYWdcOSUnrldKZOIJkmswjRy0rY0xfLIzGrJvmUbd/UzwGKzp7fW48VNu4buUz29taGvyaBwgASamZ0riJt56Z0WdQ4NEjQq2UAhfxN8dYVMg4PlkYjVOrmEV6YvZ5RWcTLXW16/ZvWvviLlmWKWaBAoAQAkePv3Fw1qBx/Tp5r16TnNX7Ip6tjmWl9O2bhVHf9dFFdLmzV1UEWpJDRLRj85u7vvny3f26CPZEEKeP+Gm/oaOuGYyIAfo4Lqqamz1DTzFzLPohwMKon1roMhJl8bYM8iuBgvtq0xs79SaK38WqiOMZo382JFDsAsT1vAhcl90u5kGxMMa8BPoNoH2bn+/o5kA7WpTX542rn9+p3wwAxk64eUig12plh4ww9RjF2wf1XMHYxMbCGBvuhvCa98DKhSRDsVqwykTLmuWLt8b6m2JXIJVvjudNyh8eaEIGBZRUPjxxZld2+PeJRYCFMbHqHXS2J07J2aR2IISyJGfV+4s2xWr2OegkTjRUZquzLykYrbaURzl4QkjSaD6VJ1Sq8d2ehTG+6xt2dtNnr6qRge5UM7Bx1bNbtV6nGHYiJx5U1jmOzb5F9ZBcAfjEkrnZOd31wc/HDwEWxvipZcQyObEPervaeYrKjpbV7y/6MmLONDQ04ZKCEeo7ZLBNSqUzeW2jhsXQuSsWRp0XKBbh5T6wah7IdE9H30hrl1dtjvQ2v8uumzchUJ7v/M+s1ZFioGwfHD8pd5Tq3mqB86sezp4VKV9sx9gEWBiNXb+IR6/c0bLXv+obtR0uB/Z9eXD9x3/YEWmnWgmjEvc5P/nd0L6njui4zxuhtr+UfTrfIRPp6hrTHgujMesWtagLHlhzhU/2vaU2WvzkbffGSJ+So/jRUhiVU3kuuNw+Vm3UaBKmKxc9fN4/ogaXDRuGAAujYUqlTaB5s1dVElDuyd4aD+1u/PT98qh8W9RSGJW8zr+kcERGn4Ed9lMjYFXl3Ow8bUizFz0TYGHUc3ViEFve/Su/VLvidOvnr35du335gWiEpLUwDjpzUt/hZ13745NzUa5mrZwzcUQ0cmSbxiLAwmisekU12sIH1w1q9R9TuYYU6cO/P7I+3JO3uwpaa2FUTgK/+Orfn6P2Op0spQwuf2hcbVcx8+/jmwALY3zXN6Ts8u5fdRMRPX/yQ01Hv23+5K2FUTv9WmthVPK74MqZY9J7/Cit46gRb66ck/1CSOC4cdwRYGGMu5KGn9D0+z99SCb5gZMt7N25um7z2peidqF9LIRx1PgbBvcfMiHr5FwFioeXzDn/wfAp8pPxQICFMR6qGKEccmevegGAbjzZ3LYvXv9m19b3vo2Qmw5mYiGMg4df+qNhY6ac3jEnfLFqbvZN0cqV7RqDAAujMeqkSZS5s1etVjuMdv3HT205sG9z1C6wj4Uw9j11VM9zfnL7SBVhXFM1NzvggnNNCsFOYk6AhTHmJdBPAHn3r9xBBB1maz/+R8mG5iP7W0ONtDPBC9VWV+1D3SHTI+PU5ImXO87u+I0Rvq6cM3FoV/749/FNgIUxvusbUnZ5s1d+SwB9T35o+ZuPfhbOSTp6FkblxJ1J19x3bgdhBDhQOXfij0ICx43jjgALY9yVNPyEcu9fdQyIkk+28N5fZ6+RZV/Id7noWRiFMOGlv5x7XgdaiK1Vc7ID3zQYPl5+0kAEWBgNVKxoh8rCCAAsjNHuZoawz8JoiDJpEyS/SgMgv0pr09l07oWFUecF0jK8QJMvK992bTjauI8nX7QsBvuKKQEWxpji15fzSC/X0fM3Rl6uo6++p7doWBj1VpEYxsMLvBX4vMA7hl1QN65ZGHVTitgHwlsCAXhLYOz7oR4iYGHUQxV0EgMfIqFMSvMhEjrpjjENg4Uxpvj15ZyPHQPgY8f01SdjFQ0LY6zI69RvQhxUO2xy3+Fjf8EH1eq0D+ohLBZGPVRBRzHw1QZ8tYGOumPMQmFhjBl6fTrmy7D4Mix99kxto2Jh1Ja37r3x9ako675IHGDUCbAwRh2x8RzkPrBqHsh0T8fIkdYur9p8+MBXTZHMSqvzGHv3PSN9/KTcUWp3vYDA+VUPZ8+KZF5sy7gEWBiNW7uoRZ4/d+VgfwtuB6Ckk500HNrVuPr9RRG9RlUrYZxwScGIzD6DO1ybCoBtUiqduXj2xKhd3xC1YrHhqBBgYYwKVuMbnT57VY0MdKdaJhtXPbu1bs+GBiNlmTXg7Myx2bcMV4sZEWoq50w0GykfjjW6BFgYo8vXsNbznauHyX7/JiIwnZzEseb6Y6veX7QpnMNrYwFEOZQ2+5KC0SlpvTqcs4gIPiFJoxc7J2yLRWzsU58EWBj1WRddRJX3wMqFJEOxWjCNh2ob1yxfvFWW5ZAPsNUyOSEEnjcpf3hGn0Eqr9AAKKCk8uGJM7WMiX3pnwALo/5rFLMI850be8q+o5sJYKBaEHW16/ZvXP38zpgFGITjsRNuHpI1aFw/1VdogN3C1GPUYufYqF30FUSI3ESHBFgYdVgUPYU0ffanU2WQXwkU01eb3tj5zZfv7tdTzN/FcvqIn/Y7Y/TPhgSKTYC4fsnc85fpMXaOKbYEWBhjy98Q3nNnr6oAoAK1YImIdmx+c5fexFERxaGjrhmMiAH6OC6qmps9wxAF4CA1J8DCqDly4zksLNua0lp3eIXandPfZaO8Vm9a++KuWH9zVL4pjh5/4+BAr8/H48U1yVm9Lyq3Dj9mvGpwxFoQYGHUgnIc+Ghf23gMVgDBoEDpKBMy61Y+sz1Ws9XK7PO4ibeeGWii5bgmQq2UAhfxmsU46JRRTIGFMYpw4810rnPNGPD7PgCCUwLlpizl2fb5qzu1XueorFMcdta1Q9SW5Pw7VoSDIJkmVznP+yLeasP5RJYAC2Nkeca9tTznqonkp9c7E0cFgrJDZvvG12sjvX3wZMDKNr8zx04ZpL6j5QetEQ6ihFMqndkr475InGC3CbAwdhth4hk4MXJ8s7PX6hPf8ujAvi2Htm18fU9T496Ifs9Lz+ifMmzslAF9Tx3ZR3Xv8w/LglALkukaHikmXl8NN2MWxnDJJfhzJ/ZTL+tsQuZ7REiNh2qP/HP32gN1e9bXtzY3+MLBl5yWacoacE6v0waO75vRZ1DPLgXx+EfFNVIqTeVviuEQT9xnWBgTt/bdzvzEbHVJoKU86g6Qmo7ub6k/8E3j0SN1zU0N+1pamg61trY1+/2tTe1HfknJ6SI5KU1KTe+TnJ55amqPnllpvfqenpHeo19qcGL4nWdclJzVu5hnn7td6oQzwMKYcCWPfMLKInACuSLQDpnIe+zcIgLsRhAzePG21uTjxx8LY/zUMqaZtG8flI86gcCmdvCEFsEpB0IAgkeIHk7e5qcF8fj1wcIYv7WNSWbKqTzkk2fJALeqnecYnaCwTQA8gyYxj0/JiQ7hRLPKwphoFdco3/bJmVYsAKJbup69DjMoZbYZ8VkpmRbx5EqYDPkxVQIsjNwxokpAuUNmv7z2Mr/svwGQLicC1cNigw0CEbYC4duSkF7qJ8a/43TyHS3BsuN2wRNgYQyeFbeMAIHCB9cNapNbJyHgaJloJAAMR6RTgCCDENvPTESiRkBoJMKDALBVIG4hoE1JInl5+UPjaiMQBptgAp0SYGHkDhJTAhZH+dkE8hwimNQuigjvA0qzvKUzInqvTEyTZOeGI8DCaLiSxU/AZkfZpQTya0DQ44dZIcK3KKTJ1SWFm+MnW87ESARYGI1UrTiKNf+uRae1tvnWA5Dq6dqAuPrqC/tfMG3aNH8cpc2pGIQAC6NBChVvYZodnheJaFpneQlAc7XbVhNvuXM++ifAwqj/GsVdhOYiz0Uk04ddJYYAXw/sPW6403lZWHuru7LPv2cCgQiwMHLf0JxAjsPzFhBdEYxjRLzR67ItDaYtt2ECkSLAwhgpkmwnKAI5RWU/AVn+KKjG7Qdu43Kv2zY52PbcjglEggALYyQoso2gCZgdnr8S0bUdH0A/AElqhpJMMG7JQvv6oJ1wQybQTQIsjN0EyI8HT8BirzhPBt9qtScQxYNAZCagjnfKCKypKbWZg/fELZlA9wiwMHaPHz8dAoFOvi0eTuslTm9pACuRPKeDScQWQalnVLtz94bgjpsygbAJsDCGjY4f/CGBwrKyFP/XUlYr+rIkglNlwCyUKUtGzEKgLAAYQkSXqo8WYa7XZb/fdp/71KPNsBMIkjuKI2xDgq2EeACADiKIAwjyQVkof+JBIcMBAdJBU6bv2/KHrA1cHSbQHQIsjN2hl2DP3n33ExkNbUdHy0Cjqf0/HIMAI4HgNALKDAcHItT3hJ5nuFw5yr5oMNvdTxLA7eHY+v4ZPIAIWwhgCyK2/2eSxJas9H7bnc5prd2zzU8nAgEWxkSocog5Ohw1pzRC01gAGo0AYwBgNBCMUf3+F6LtjiNBcXeNy/r4d//fUlw+SvbLnweaiOmeO/QD0g4E3AIEWwhhC5pMK6/K7reBd9h0j2y8Pc3CGG8VDSOfguKK033km+wnnAxEytKY0WGYCfkRBPhsYO8BF5w8ijM7ysqJ5BkhGwz3AYRGIPwYEZcLpA+lTNMni50FR8I1x88ZnwALo/FrGFIGRIR5M8tHyzJdQgCTAWgyEAwOyUhEGuP+pOSkyUsW5G852ZzFWZVO9S0riGhcRFyFbEQZWcJnAPQhAn4oQfKHla7pu0M2ww8YlgALo2FLF3zgOXeXDRJt8lQCvPL48V7UN/inI90SCRDeTkpKKlATxe+8Ka/zR+hIBSDcEKs7ZH6YOSLuAMDXBNKy/pnnvMfbFCPdL/Rlj4VRX/WIWDTT71480udr+xXIcD0BZUfMcABD7RdRAewHwDoiqEMBdaD8CVRHKOoA5DpA2IemtC+r5+fWBxuP07k0eV/Tt0N9vra+AHQKErb/Kbf/CacgQvufyv8jaP9df9VZ7WAdBtfuMAp8jWRcltxbeoNfu4ODZqRWLIxGqlYXseYUeyYIGX8lk3x9NL4TIoIMhDsAYRMCbSIUX6AQm5KSYFvFowUHEZFijXPp0qXSux/tH+oj/0gSNJIIRioz59Q+e06nRTo+BDwGCG8hwbK0dPqr51H7vkj7YHvaE2Bh1J55xDwe/164aLJf9v0aCacS0JBIGUfArYCwnhC+AMRNEsEX/TMztjidd7REyofWdgofLMtsOSKPFAQj/TKOQoQLgOAnBNQzErEo/3AQwEcC4M8g0v67uiT320jYZRvaE2Bh1J55tz0W3lvWr6WZbgMACwF163Kp48G0TzasR1CuFaAP0lNheaKMfJQR5lsr6sYR+C8moIsRUPmz47bEUKuG0AoEr0gCvZUl1rf1MJoONYVEbs/CaJDqK6PD3OKyn8oy5QLC9d36jobYggCrEPADBPogORNX8G6R7zuCsnypTfZfLB+/h+ZiRDqLCETYXQXhK0SsSZJMTy5+vOCfYdvhBzUjwMKoGerwHCmjw+YWuB2PH7AQ/ugQ4SsA8YokxF+ST5c/Kbdaj4UXUeI9lTdzSZbsa/0PQphKAFcAUWo4FNonqAheFQK9/TOtb/DVr+FQ1OYZFkZtOIfsxVLkuaz7o0NcL4TyOkcv87FdIZdA9YF856KebQ1t1xDh1H+Nun9BRH3CsoywCwifSEvDxeWPWfeHZYMfihoBFsaooQ3PsLnIfS0R3g9EE0O3gIQIHynftkyY9PISV/5XodvgJ4Il4HS+Y9rbsP5SuX3iS74unIXyCNgECF4Jkh/nReTBko9+OxbG6DPu0oPy/dBS7FHWHM4mgHO7fOCkBoiwBgCeSDIlvczfsEKlF7n2lpkVF5DfdycQ3hzyTDdCKwI8jSYxv/px6/bIRcWWwiHAwhgOtQg90z4j+tHeGwng90SkHNYQ9A8CHiGE50BAdU2JTfXw16CNccOIElBet32HfTfJCObQR/7oRwEvCMRHq0qsX0Q0MDYWNAEWxqBRRa6hpaoqCTe3/NYPdB8QDAvJMqIigtXJvUzP8Y6LkMjFpPH0me5zfH5hJpJ/CwC9gw+i/bPIMhLwCP/DFzy1SLVkYYwUySDsOJ0k9hwu+52MMBuITg/ikfYmPDoMlpR+2zkcS9OO0N7fAIKZjp9gFPwP4hsS4qyqUuu64B/ilt0hwMLYHXohPJtbXHGJ7Pd5QvqGiLBLACww9Up6ikeHIcDWedO8mZ6zfH64FwhuDPbcyfbtmABPSFLK7MqF0+t0nqLhw2NhjHIJLfe4h1ArPk5E04J21b4gWMwbmHna03zidNDUDNfQclfZmbKfZgHRrcEu2EfABkKcO6jXaR7uG9ErOQtjlNgeP1Ow+R4AuIsI0oJ0swWEeHRQ5tnP8bFWQRKLg2bKsXDQJt+FoLxmB9dXEHA7SmJmdUnhsjhAoLsUWBijUBKzw3MTAS0Idl0bIm4QKB7pnznjJd4NEYWCGMSkssPG5291IEF+sHfoIMLbJgkcvIA/skVmYYwgz/Z7k9FXBgQXB2NWWX9IgA97S61/4UMGgiGWGG3szid7Nx1uKJSBioKbyW4/BOSJtFSczbtoItNHWBgjwFE5TLW2fu9DQHBXMB/TEWHvv87xu7eq1PoMC2IEChCnJizFVT8iuWUOEZiD6VeAcBCEmFFTYn0+TpFolhYLYzdR5xWVjffJ9AwAndWVKeVQU0JwJfcyPcKzzF3R4t9/R0CZxfb7wUVEVwZJ5WWTKWU6z14HSUulGQtjmOyUfbK76zfcB0SzCSipKzMIsMyEycW8f7krUvz7QARyHWW/lIlKgjllCRG+RYT86lL7S0w0dAIsjKEzg9zisjF+ZZRINKGrxxFhI4Cwe13Wt7pqy79nAl0RUHZN0ZaWQiB6gAh6ddUeEZeiSC3g08S7IvX/f8/CGAIvZefK7sNlygfxuQSU0umjCAcFwINXXjhgCV/mHgJkbhoUgVC+P/5r5FgHgHlel+2VoIxzI2BhDLIT5DsWDWuFtqeCmXFGxFdSUzGXZwiDhMvNwiaQ6yg/Xwb56aAOIUF8LgN6FLpcOQfDdpggD7IwBlHo3OKyX/llWRHFjM6aI+IhgWStKrX/MQiz3IQJRIRAYVlZSssO+SEinNn17DXuQQE3eEttKyLiPE6NsDB2Uljl1bm2vuwRIJrVZf0R30hNEndWLCjc02VbbsAEokDg+HmQ/qeIaFSn/4ADtiFSUbXLXhGFMOLCJAtjgDIW3FvR91iz/3kAuqqLb4mNiKLYW2r1xkWP4CQMTcDpfDJ1d0PDHCAq6uoCLxT4LGamWqqduU2GTjoKwbMwqkBV1ib6ZfllAvhxF8zfNaWm3FE5b/rXUagNm2QCYRPInVlxoXx89DiicyO4PhlNv17sKtgWtrM4fJCF8aSi5hSV3QpEVZ3eBIfYIhDvqSopLOedK3H4tyJOUmo/AxL2PkIEdgDq7O/6YQnFrVUu61/jJPVup8HCeAKhsj4MtrS4ZJkKOn91xm8ESb+qds9Q7lnhHyagewK5RZ6fywR/7PxGQ+XEcHpkYC/bg3yQiXI4NP/A8VNNjr3c1VIcRHwrOVW6adFjMw4wNiZgJAI5M8uHgl/+MxCN7yxuBHizJ/b8z0Rf0pPwwpg3a8mP/S2tf+9qmxUizL/qwgG/58XaRpIDjvWHBNonZg7XLyGA27sgs0WkwNXV8+07E5VgQgujxVF+tkzyGwA0IGAHQGhEhDu8pfY/J2on4bzji4ClqCxXJlk5Hi85UGaIsFuS8GeVC22fx1f2wWWTsMKYZy+/2Af+V7s4725LcnLS9YsXFGwKDie3YgLGIJDnKJvoA/lPnR2mrGxYkEj8stJd+KExsopclAkpjOYi97VAsLSzY+SV03BSe4nbyh+yNkQON1tiAvohoOy3luWWF4Doik5Gjs0CxI2JNmOdcMJocXhuI6AaIjAFfn3Ged5S6328FEc/f4k5kugQWLp0qfS/H+1VLmtzBPaAfhRo8ZZa/xCdKPRnNaGE0Wz3zCSABYHXdCEJpOJql92lv1JxREwgegRyHGV3AdH8ztY7osD7vKW2x6IXhX4sJ4wwWhzuBXL71QPqP4jgEwh38AEQ+umcHIm2BJTNDUjyE529TSGip7rU6oj3t6mEEMYuRRGwCSTxG29J4evadkX2xgT0RcBcXD4F/PKf/nXLZXrAQQTAU9Uu2+/iWRzjXhgtds/9MtDDgb8nwkFJMl1btXDGR/rqohwNE4gNAeWUHtnnfw2A+gZ+wxIVXpe1MDYRRt9rXAuj2eGxEZG7k9fn3UKIq6tKrF9EHzV7YALGIWApLh9FfvlNAhoSeOSIj3ndtvuMk1XwkcatMJqLyn5HMtV08jE54Vf3B99NuGUiEshzLBnoo1ZlA0TAGzDjdUImLoUxt6j8Rpn8zwU6jw4RN6em4iV89UAi/nXnnEMhMH3W4j6+ljZl5Jgd6DmBUBhvh97GnTBa7GW/IKBXAl1pigBfS5gyqdI1fXcoHYTbMoFEJeBw1JzSSEffCzxyVJa5wR3VLtvT8cIoroTRUuS5TCb4W+CzFHFPEiZN5rud46X7ch5aEci/a9FpbW2+9wMftoJ+ALypxm39k1YxRdNP3AijudidDX58m4B6qgFTLiAXQlzKEy3R7E5sO54JWO5xD6Fj+EGgCRkEbANJXBcPy97iQhhn3F0+4Fib/1Mi6K8qioANJMHlNSW21fHccTk3JhBtAsevEfZ9AESnBRiANEsoLq4sta6NdizRtG94YVTOmKutb3gPiCYGEMUmlOia6hL78miCZNtMIFEI5M30nOXzwbuB1jki4M7UNDzfyJObhhdGs8PzDBH9l2qnRGgVIH5Z7bL+PVE6LefJBLQgkOsoP18m+R8ElBnA3/tidNqV1bm5bVrEE2kfhhbG44dC0OMBhvSyEOKGqhLry5GGxvaYABMAyHGUTUaiNwJvH8QlNW5bvhFZGVYYcx2en8lArwVcq5hAJ4EYseNxzPFBIMde9hsAWhpoIwUKoRxXZrg71w0pjOaiihEk+z4JdPo2Ir7gddlujo+ux1kwAX0TMDvcc4hgdqDPWSaSLjfaKeCGE0bLPVW95GPNiiiODPAKvaYnDJjkck1r1nd34uiYQHwQICK0ODzLCOA/1DPCfZCM59cssNYaJWNDCaPTSWL3Yc+rBDAlXgpglI7CcTKBzgjcffcTGYfajnxMRGMCjBw/HdSr12Sn844WI5A0lDDmONz3AcEjgYbsiHiZt9S2wgjgOUYmEG8ElDWObeBbSUR9VN/mAJ7yuu13GCFvwwijxV5xHoH/44B7oIW4M5HupDBC5+IYE4+AxVF2tUz0NwCS1LKXJPFrI6wUMYQwOhxL047A3jVENCrAaLGsxmW3JV435IyZgP4IWBzuYplgYYDPXftNpuSzKhdOr9Nf5N9HZAhhtBR5KmSZClSH54jvXHVh/6umTZvm1zNojo0JJBKBHIfnv4HotwFeqf/idduv0zMP3QujcgcF+f1/CyCKhygJzzHSbJeeOwPHxgQiRcDirEqnwy2fBTqNB4W4w1tqfSpS/iJtR9fCeOJC8A2BNqxLQrqpqrTwxUhDYXtMgAl0n0DuzIoL/T7/B2rfGxGwAVPo7Or59p3d9xR5C7oWRrPd/QoBTFX/roh/rHHZ1PdIR54TW2QCTCAMAhZH2SMyyar3wiDiO9Wl1iv0eNugboXx+J0t8hMBRPEbkZw6rnp+bn0YteJHmAAT0IiApaoqiTY1rySAcwN8DrN7XTaPRuEE7UaXwjjdsfgMH7WtUzt0FhFkIUyXVZXMeD/oLLkhE2ACMSNgcZSfTSSvIqCUk4NAhGZTUvL4JQvyt8QsQBXHuhRGs939t0C7WxBhvtdln6UniBwLE2ACnROw2D13y0DzA4waV3hdtov1xFB3wpjj8FwHRMtUAQJ8NrD3gAuczmmteoLIsTABJtA5gePbecveI6AZXCUsAAAFaklEQVRJqi0l8Z81Jdbn9cJRV8KonMa9u77hCyIa2gEQYoskcALf2aKXrsNxMIHQCHT2iQwQdmXAgJF6OfxFV8JoKfI4ZZkeVMWN8Psal/3R0ErBrZkAE9ATAYvDPUMmKFeLSQA+UO22zdFDvLoRxpyZ5UPBL3+hevUpwra0oeKscqv1mB6gcQxMgAmER2Dp0qXS/360Zx0RjO34VghHU5OkERULCveEZz1yT+lGGM129/8EOs8NJenn8XAlY+TKxpaYgHEJHD9oQn5T/c0Qn65x2W6PdXa6EMZOt/0B6H5fZayLyP6ZgNEImB2eV4noFx3jRpJQTKxyFX4ay5xiLoyFZWUpzTvkz4FgWMehNbaAJMbULCzcEUtI7JsJMIHIEph+9+KRvta2DWrHCCLgcq/bNjmyHkOzFnNhtBR5fi/LNFc9bHTWuG0PhZYSt2YCTMAIBCx2t0sGsKvFKgRMqy61vxSrPGIqjMcPiWj+Ggh6nAwAEXcM7JU5xihHoceqgOyXCRiVwPRZi/u0tbRtBaC+Hf7+A3yNo9NGxOpe6pgKo9nhnkcE96gVFoV0nbe08C9GLTrHzQSYQNcEcuyeAgCqUG0pxG01pdZnurYS+RYxE0ZltEj+lh2q+6EBXve67T+PfLpskQkwAT0RcDrfMe2uX79O/RIt/LzGbTs7FvHGTBgDjxaRBIpx1a7CDbEAwj6ZABPQloCluHyq7Pe/ovrmGKOlejERxoJ7K/q2Nvu/Vj89B//kddlu0LY07I0JMIFYEVDupTY7PJsC3BX/bo3bfpnWscVEGHMcnseASOWEHB4tat0B2B8T0AMBi92TIwN51WKRUMrWel2j5sLYxWjxz16X7Td6KBTHwASYgHYEjq9npq/VrjFBhJe8Lvs07aIB0FwYzXbPowR0b8ckkZJMdO6Shfb1WgJgX0yACeiDgMXhniUTPKaiDf4kTBqxxJX/lVaRaiqMymjxWItvBxBknJwgIvJoUauqsx8moEMCdueTvY/U1+8MoA+LvS6b6hXK0UhFU2EMfDEOjxajUVy2yQSMRsBs95QQUFHHgRM0o0gbUl2S+60WOWkmjMohtLX19buB4BSVxF6ucdt/rUXC7IMJMAH9EsgvWjS4TfZtV91DLcQsb6lV9XqESGekmTCa7Z7/IiCVVexIksDxVaXWdZFOju0xASZgPAJmu/tpArhV5XPbBq/Ldo4WGWkmjDl29woAuFAl2de8Ltu1WiTLPpgAE9A/gbyisvE+WV6jFqnJhGdXLrR9Hu0sNBHG6TPd57T5QHVEKEBcW+22vhbtRNk+E2ACxiFgdng2qm4TRJxX47KprGqJbG6aCGOO3bMYgKZ3CB3xm0G9rGc4nShHNi22xgSYgJEJ5Djc9wHBI2qa4S21DkVEimZ+URfGfOeinq31bXvUpuCBL7iKZm3ZNhMwLIG8WUt+7Gs5pnpAtZBgcnWJfXk0k4u6MFqKynJlWa7s8G0RsC09nQZ7HrXvi2aCbJsJMAFjEjA7PB8S0UUdo8clNW5bfjSzirowmu3utQRwbgdhRFzqddlujGZybJsJMAHjEjA73PlEsKijdsC3OCptQDQPscUcuzuq7+qByiIEXl5danvHuGXjyJkAE4gmgfYzW+XmvURgiqYfNduxEsYtNW77KK2TZX9MgAkYi0COw/MaEGl+aHVshFEIR02p1W2sEnG0TIAJaE3AbC+7hUD+o9Z+NRdGRGg2pSQPXDIv/5DWybI/JsAEjEVg5sxnetT7DtURULqWkWsujID4XI3LdouWSbIvJsAEjEvA7PC8TETXa5mB5sIoIU6pctne0DJJ9sUEmIBxCeQ6PHf4if6gZQb/B6A7xci7tb7JAAAAAElFTkSuQmCC",$r="data:image/png;base64,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",Xs="data:image/png;base64,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",ul="data:image/png;base64,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",Dd="data:image/png;base64,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",Zp="data:image/png;base64,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rqSA/QrX3Ec+hUCcZ+O6rA4R3RUofbhvGDd8be4/iYAYLFP6XdxTHQ754evsdP+httvdn2dLpl26Yq63fsfbL9hvk5+v0J8fI9D7xqt22hIgL506UlvG1W3VSUIjrM4nPZgeVvV72ilRqNsV1a6SJQuVBwTXXfhMQA5t2KC4AV5Jwd06dJx9dhjZ9SdvMbr1ffdLXL0AT0jxvCwWrZEaWKKY6L5RG22qspr3GxN8qB2euQL0mI+1kxmiVLd4pjo6/UgNu+nQbAGAKIO4v3jFWikRs+Un1e3e/+bXv/4cYW4B+g7+qzPnj0jTp5sbotDHybVGwG9P6LimKh7AWjh2Krzw7VTPrSA/kENcpqX4b8UZ4mu1c1/bSybt96q91Hj6V+jBpBly9r3X8w2m+zt3P+m83O4LvcAfUfhDGDPnhGzD1z3t3WZISXE9P6ynb3ZRaLU3h0ffTtrL1aCTtfDSjm0nW7iKJ3vsAQrJrRER16vDQBVACAKAFu1L/oiOrL/7fZXT1DKFe1530o3nYft3H9/Tqif4fmBPUBvC2a3VcnaM+Lmc68G1ImZiiybj5GoeyBO9ZXT7Zal7rTwyg+4F6TAJlEqQ/ja0OVW9bGboC2Hlig1Lo6Jbmd8HXpJ6MXqVy76Yz3FZLqg+NiLye3e/6bjmD6Y7XHo7Typ26jjAH0zB/SazitXo62q1Ei15rRs++HmzZuO5qfzY6JF8+7MQVE+fDrvbxhBBZqIujL0h04HoFIBIDri9Mb++nWpzagLbnn9vBX2BEp/SQlxKcl1fru//8Hmq8f96ZmRUfboo5++owvP24DCuqZ37aLw6ac/4R2NhAPg1ETbzi9WkSj9Lo6JbneiYn3Ei6oH+i/IcKsyAHQBgCiV4pgoQKkU2F4vRaL0u9cTWCopS3R0/fwc1Rldf5vXLwOo5WU1Xf+T+Hbvf7N5mopVinuA3i6UdlfPPv0Jb/5oH9AEYgJ2v6uFpQQnx0NLlP5UHBOl3y8tJVjohun3+Hho4/iIV8J9EUS+LREoCaj9/opjoiNLnCG1A6LULvJtL86QqANsv6+i/XD/w31uVX/tvEClYnmAPx0X90R9rayk2GjkL9eo+y/miuioQvM4OJ8wpVLEPQ69O6RusxUBeuGYCl31YcvDJn3Qwx51Oqqf9iIxFQHk/yCGnI4qxTmiIzsbaj9c//XqfxyAAN26+FS8ag0aGM8gqLc5rXm1IUvQ3Fw7PX36M5tqUnbU/x2svO1P8h0cw666tvYT3tIrwS0gt0R8FwCIUimOx2GlmSLjxEkL3S5ArSJNBqeD+vgDAUCGScIxDLUlSq2LY6L0e/j8GvpzhIehb5MkQ6Kj6m/d3/CU3OqNGINANuWNha/0GC8NPMtcT12rzPed8tfuP+95/fyMNwK7tJIiUXd2pYzjja4l6mYvu5HgHqB3hdNtN7L297ylV54fCejxcYClJRIl+o+vf0x/c4CeKOGgnYK1Uxy/5yGh2odKYQSQECgJuMVohvDk6sQAREeV4fZFX/nnZOv+N/Q5zNEHxqNUJjuLX18nDTUaJHYAHD+qHaCLuSA69H67n7iSom0Elij9Lo6JOkDfmEjw9Jk9Dr1tdO6i4rlzZ/zp8PqthIJb9oishMjCdV+mZrMJ4/tOeMqeLMTmXYzojW+SphI90ZSdpT/r1uv1DQMwaul1CZsaO3EwRtwD9B19wvbcGX+ldGkkABt13640MyRKgyiOiSKLsNNj69xErUlsUHrAt3xfGQJvg244CDxL4CFK/RXHRLd3k1vy6HXdbP96Ej2Vyu7KNzqDL2m14tt2J8ND+6Xzvxi8/+2Nd32txvHjvT1A72bmdtBmPaBv7euQd7l2vtNDVq+H2GoD1PqWk1a7BWOTb/OXklI519vR/8n4VmjxiuPcIBdAACmkjjqA94+J5mXz9htvkyGAsQBEqdCLQy9L8XKtv/5q+wCgIky2dPPF7pqBnM7mxvZyONv3kFs/P4VIQtQBfmUFGo2Go8PzRb8XlI7vu+93NrdG7uDZ3cmq2+Qwd3IIu+vb2jN+88rNQjG87U6IO3NRG+LQmfVLJwOLY+W74qkVr03gg1BpFree7mDfcWpwIlQ2p4lbb3tyblGxnoke7gH6dqdx8/YE6NbMVWdqqxnftliGREe1Ks4RRd5gyKrrAF0xYJZ61ciLjpQ6mUJisJ4VVqJyL3xxTJR+0983O0+rJ7KhF6soRIXWCkt0ZH+ZQs8XVtK1RzD4W1/fMM576T59pdVhwCp2/f23ll7Vtcra3ND9j5qf4fkbnC83v0mpuwfoO4tnuHDhl4OToXAcugUtqEHN0a3KKECTBTDTLEjxnr4tehiSBTwLX6jh8+uv6oMPGWRAlEpxTHRU2W39AEPkLEm5fbFdgTJ0nAVzrTSXX9PVysY1wcYxrPceHPbvW1JHevfcc2ZV6bPVHL+Z5+9ekePCLwftyKx6V6ybxHYboFoFIEqlOK5WAXmNxUnAnRW7//xLJc/Kbj1MogOj+xt+QlkG4Pvku5mfKY6Jjio7rb9dRPgAXKdZyV5q9XBggdrtApTLoK68pCplzw7ev+t62Ntq2Ltq6PpVOdXFPUBv96nsrp4lQJvULeuqZc+2uxKJuufVPyaaA3rtIcZJxFnW4KUJaQtA93oAIjoSpGKicLBbNyjfEzaTComOxGv/HNXZzd0M95+BQh+EJer6I7cg8vwecg+SkiGDOK3jq03EDEulvqm9lx/fmLmsyw7QAyAeBegtBl31D3b2AL2bJ7uDNtb+ctCezQG9k8L4JEfm8d6A2bpkpG3DdIh8elv9eeCBBAlEc7zlx0TfyEKyPGNxWvcuNHuxt+FlUukV6QB9m6U6fbCDuCdy3OY0bt784sW/FE6GJEuQu+eQ++Zw08K1s1IB5BM8bUYiGpPW+WuQZSyUtrO8P5SlyVsFnazvUUoAzwMgSqU4JjqKoxbctYivGea4w+eHx3+L66HPkDGdeq0XmqWJCCBe71yi00UJNrWrrq2Fu+o23VOLYawo0Tly5Ldv5blyR5/zTjvf1Sdypxe5E/XtxTNhR98YDUDiSiRuFNypOO5KTFRNlKcmWLwsEcKce41baefsVIh8wvW3Fd6UVCg8YYm6F8ITFqVCovS7OOa9ywFPb0YmmEq0dyC1Xh6AUJwnSr+LvoiOuv5w/dX5RIaBr5JIv9SMkwEOTfeVSPQrK6kD9MD9u7ZD8zPs7r0B70p0cA/QdwLGa306QEd9QO+A4yTZfsF55NIVhGHujwwgbUfvC9vJeINEBwESyMRWZLEpjrcb9oy6xWuz/+RRzBbzZHkUVWOFBL+2qP2phRiPL6bjb18Rtpybprfg0DSOUeOJAbHsZ7HXudKMxgacT/qGSSPmM0uA3mHZEM8go/YeoHc4iTutfvWrvxKNHWjfQkQYdshf6515FZFKAvSa+1GcAHhBFMTeofq2om43DHY9IivXf/u7MVk4DHArVwoG1qJBr76og8lFLY4s2ql3LmYmukXui9Eyi8IEfakSL3htBdNBGTq/Nw+bKdhRkenrAxS2mvvWEmsffPTTt3QH36r9G3n+rhU5rl79lWhMpRs9cmj2Sp6FnkRHhwrjFZEthH6wPzJJkmtBkgRA+PUgMfuKPAGbPwPBLSiNQJRKcaw0YvfVUuPm//eDO32IBH3DoiaIyQVVPrZgKqeW0ujYaN1v/3qYGAbQSspwY8W9n0XpixweX0pGArqYG6LbKOVAtfDgHqC3MVW7r2Kv/krUDW4B6GEGNMCwUznmcRkKCMNV/9DAKrssa5HxDuQvyE4XcQNCdzj3z+/3ey+e2v2drbW0POxab2JB84NLduKBhYQ9mGvOV8enETFOSqXry5gW4V79NzQMwUuuJZY49OYRZBuHOlS/rPYA/Xo8z037IED3dPcWHPXWQVSpHvNKoiGSAY4WWGFX2rxkvCP1XG+xU6l5TcqtX/v77+JycR8AWdcLkaM4Lizu9PfB89ubLstEalhjyUbTC0nw4Lysnu54ECdjwdWlFAcA3Ren1MpcGgXWbAwCG77e5kFnJR+aexx6e89o17Ws/ZWod1XSUgjACAtMoaNUimOiQ4WpuoflSZ6kEsNVV9EElpOJKING3p/bDmhoW6DVvwEIwa1SGok6+KsYBHigZAzjM7/1YW2sl4M5B/BWcCZnVmMA1ju1bj01hlVX9PjDz/DqsQuAfPV+invrtl7LQgfoobLVfFFGKHJ26meGaoe11oEDv7Xerr718N6UGtuSod6UkW1x0evXP1GqK397Mu9AX0zUvXav4vl+X/4lbUfg2V5aLXWgPFbw2g2XVwosz9vgt7MlQygAFEONmtw8EdGg3zpfryz82/f2X4nVuR0F6HwTHgsObgwsum22ij+Y/H1AtMZavDXQGXCQiTdx+j/2at9bxKOsDl2nV9ORgN7hA237YXMP0DuctJ1Wt9c/UYo163PU7bfOdMVHvU+k/pq/cwDaJnKylIa1htYaOYFLMOefbDLgfvpqvbTw5KNCLxy2WesQM2m9v6Pc6oUJvdaoCK3cnj/IqCEjUwa8FvBgxfL6rOKVJYbWGGOAWYK+sYTxNe5Ppu9Ecgvn2/f+3NeGu+TpbBIFxPuHyyYxXSPGFXmVFdzj0NsH2W5q2utnSrFZ7EcNbtHDQAxeZid8jDjHjKP1tSUHuMAXtgfjUQ8nJzONwjAhEIFLVHzf5d/+QNj8rz+HRo3WqOxm8NtoQ9sgaq9xLovu+QZikDpGbknuoX/aMms16c/RpGmI3Wvxvf/D5wv31KJ7ld5IHIcejrENpQUyxBB1nxwPwUrr6ChAi2B5D9DbeGi3U2VHgB64UKYnfKa5Z73AUFxJ1zCvbctBEEzUVlRpAo1lAJw22rQHr/z6T/ntcx+7nXHedlvmzSeVtz4ByEEbkj4Y0j9r8+gWNKlEoS/ae3/xi7q3kvkemhzYAQi8nIDj7OvLzvgzQKepV/ad/lSRiey2b+lOdnDXytA3bvxauaZNn0NviNO+5ZxlquYpU/M7WImUVysJG/kKNIINfalFGRmokCUqWPkvE2NX/sGnrbW3yKZ0Jx/L+r6tP3FW8YPfAsFAk0jNOBogyUhwRK2NN36hffgTzxmWaA9V4smVXoktZzqbT4NRi8IdDj3yYBn37QF6h9O2s+r2xq+VQfccoONEYBQqS9T1QiZtOi5M28VxIrDl31dvi/3jNgM/4NpoY2TkdWNUgqUmqHLOLGgBY6/+yi+xeOYndzaqO1QbWTeJ3vYPc6WJAY5oaONR+mlBKSgd/5N4+qfm2qoSoic4GVNUmqVj/sUbFTaXrs7FLeZnY96boaBer7aM+87sceg79HhdtwToWGeU42fLQg9s3pT8FO6fMFitpNqyssh6nm12uW5mZaH1kpqoKBx3/SngcODFv/K3UDYf3bLzN6iCKr/ldw36/YiCXDViwCKHNDP73/GvWe2hTk95wkA1TL1aOZF+KDyTRHpp5RCeXx5MBLVVIqcN573xpT1A3+EHTYBOTDzpLrNFZhdppoJr8t6DiJYFNu3VheylyYoiLUYeZGKswfFSR9fy/gDgwIu/8I/BpDvJyHtH71iVTvwrw+pz7iKFHhBJWW7beOzxf5H5DPMIL2Mp8qvbq5bisBQihKFI49Z0+M2ba5lzdjbUTrW8NDX1d/rhPztr+0bXvmtlaAfoWLn8jGEgbZJ6SDSfwLVPZsqrfCa+n/akgLK8clOwptRQDwaDpawAY9lkuaMrE6S28zm3U+c/9vvWkoHkO6OY8NAfKm/fxcHRkBIPee0yP/IXPieVzzwvT1VGIbqZjW0ZluM5fGC8Y8b2lXHx5j7zcrHv0Y5uKqz4i7gH6B3N2Y4rz839UqWqfcdRN0vjct0+ONnL6vun7UuvToQrCYh9/rIOHaDXQla1zWStnOjGhAbjXvJDDtDgtnn7TijaP/SkDPa/NjgWMsVkpXu/WT7yzq9L4DgcwitwrmtNYublg5MreuLQMfHMuZpI1PaX0H32IPYAfccxYOfOVJLeQpFB95bXu5B+74NVv7s0xr41H1hupZ0MmGj42bpwKW0zNVHummjSGIbAORx58S/+++8oQIeHnpRius+h++ZFsNgd/+CXyuXqq+BtDNDl6fWeL6RzST2v3/fIPrz0yiS7vLXo4By3EnIYd/Paa6eLE/f9ztYh9Xf8qW99gbtX5Jg7UwFTAHo9j05TjUHALdEX1fecqsLizQnz4lJIuS/seKCiug9SY8kLnI5WZl1I9Xi5idGkJrM2EKAf/3ffSYCW4eHPZXy/22yZ1NDGAjLmqfaxv/wfJ1hvLsdzDmopFXqesEnnYhwI5QD95+n3PjJduv7qpL7SKuaGaA6RLRYh7XQR9wC99dt0OzWIQ4Nt7qM+0gQgCHM6XC4nJw/2oFG7t/z8K75OFAEaS5VAZrDK1KQ1tpeUKj0ccyIM+XNMP//T//aOAZqFwA//AmBwAPSNfw+2/a0tp0IGhz+fif2OQxe+Hdbft9CZ/pmvTPC5OfAZ0j0NFpZe7xKgb9jD9QV59OQx/uxzVd6VxVwRdfM3kLyMfg8nMgOhFnBij0Nv+ZBup8L8i79erZZiB+jNSsfU/avZAyd8lsT7xeXZqg/Qy8YG3eEBhLa9JCrHMDEFYCiUhB196S/+6zsC6OAg+O/8I2DVfBtiaxTIpz8MZuGLm95HFp34svL3XwKDFlAb0kTL6n0Xuo0P/vk+/8ZNqbyhfcoziPhce6azr76MRw+XWXv5RHju2lbzNep8UIb5PUDvZuZ20MbO/3oVTAHoIZEjU0j+GWk/tdYCTldutPYdCjwtq17cLmOSlQTm4obUGDPGM76/0e0FByxyrjni/S/81P9jrX1dF4UY3QPe93wJWOnEujvV818A+ac/tOndq+jEl2NxaIZUdoXWrl3/wW9C9cTVhmheN7opoyjUKPNFbcxCMd/xSp3Mr1cD2ZlgF65NlmMXFplmgoJrLdGRAO7PHc2hOy9K8zjxyT0Zegf43HFVB2gr3bZPaQoQBDkd+ckMAOY6+8s31fiUwqjElDTlMO0EgdDc+gEiE61EVEAENQbWZBmaky//5D9+PTk0lh8E/3u+BBge2nCveuFLIL/xwc05dHjkj5R/8JIxyJlgqA3HpSO/+F88HsYc4mXfGpORX4fOslT7UdeWy8woXQ3SlYPVF24GiTVFMtUN89WfO5rDkfNZ9udx/H9v7vghvQkN7t5F4fyvV9MkOTAawqPTz3aUx2/oE9OpGT+WaVr6UUoNZiOuVjyWaiWjMvNAa63h+Isf/1dbApoFwA78FCAvg775+wBZbvcYLlh7BPzv/gJgMFopkz39Y2Dm/mBbgHaVjAHjN1YW9//CMwJ1ZkHGiS3XUy1qEkyMipV9K1sHSldeHuczW2s1tgBeUI7m9gB9h99Ox6ETmwN6QzrmYZads6AbcHzMsH2NtuI1lVqboGVWas40ZBLBRxaWfWQq9I2856XH/+mmgGYB+O/6KrD6d7kh2GwBsj/9UbDNr6+7c2y8G/zvfhLQ2+h9So5w6vm/Bvrqp7ecLRUe/SPp779EXnbGIkvC+6/O13/sqjZWeTxtK4sCLPO4Z3sRs14Qogx1Z7liry9Wwm66+hlzIofGwOeWqJs+y22KGomOnE/B9gC95RO6zQr2wi/XIPL6HHqLzljAZtWxfRqDklJkiEmSkoh7FD/Yk6WwnYlSYsK6NMGEoTARZu07Lj3+DzaTodnBj4P/8D9bd2Erm5B944Ngm3/q/s4mPgDeO/4DYJ4kdX1dWgw++/NgZv/ltmYiCe55KhZHZyjqABjD+cpfeKETvWXZszIue8lcyaZJ2c+6IYslMJ93dLVqKKCFUvvZ5YU6m9m1DLwizdzYPf9HkQ19W+N9syrdvSLH4i/X0oRt6WuRZRpb+Mh0G1lln+0tBmKll9hysJq1i1AtYqN6Y7Ubqn5QWvC0NuLhyx//1GaA5kf/Gnhv+dRGoMoVB2oMD4P38L8C5Bu9T61OQX7zo1uKGYOd9/wH/qQjpq+R8wYHa66NffxPRFBJyyJbnghu9LUXDNeSOhprVJxl3v5xaWrVirgyM2mXR3rMbdyBYP1tBRnexD1A39l31C7+zVqWdg7SVXzLbYYaidLv4phoW01Wl+Sxo5F/beYwm1/pZvUo9epRvgVEXiSFdOiJ8mIWHWCMWR+sPfTSz/yzTUUO/wAE7zsP6G2MArOyBcBLgKzIvbQ2F1Z1QT7zY2AW/9OOJog4tBTTlxi3xohKp73vF76WGOAlkXbGRXOWxCcB/aBd0EjHvr7WBpuapnjLwY70KvfguZd9b2P2m8H5GjWfUCrdxLEzexx6R09sh5UJ0NAH9GZNX8seujdAlRzyXrsOoG3P1qME6pFHtrZ+sWDsii5X46yyv4jUPn7hZ/7JVotCHHsP+N/9OUCxvTBCS9z7T38Y7MqG8L8t7z4Lj31Z+gcvuxcwOHKtOfbfvEzOdgFmnbFwYdaFsQyVwMy3fZGqTAp+Gb/rbWPmlZcm/aWdZ0CKqjf2AL3lI7q9CvbV36hDlDoOvTHf/loG/QvZW09NRM3rleRi0/e4bcpKycBYKFwQbIHozLZNqdpJCdB5OXbhZ//frQBN9XDs+/ug3ny7F5vOQfaNHwTbfnZXN67CY1/OvOkr1Lhbfef5uPI9N8lHMAhkuypWZj1kWCTzLbLzVcxC2+ep0z2/kL7tbePezcv72c0dq9+akt1oHPvflnc18De40d0rQ7/6G/VMKKfUJaBmUiNRB/D+MdHr8qGjBi3bZ1+6UikxnQO6FkH/80z1RYhmJfVrsaruM1JThJM99vLPblsPjWPvzTUZIxZ/1L+NZyD7xgfAdl/a9eMlQKfe9FXqYGXqY/9Ve5MJBYMjpp2pUvu6TixbyxOS5wzx9Wzb46mSpupfVPe/5bD3yrmG39n51hKS3cA9QO/62W2roV36jTqkOaA3K005VrqWHj5RE+25feFr88qOhamqlIRltsgmKoS1zSyqdjRxaA2Mczj2wsf/0XY4dHFtHH9fDmq+futE030Fsq9/ACBx0sKui4zu/c+Zd/CKxbA3t+/nv84YGmMsi4RpTwZLs0qRU9X6MoYzK11WETPx0WOcG3MyeuHVXQ0g8maxscehdzV3221kL/6PDWBBDugNe/qs3wOlhftK15PJI8AFTODiQmjBJAiMwvEEF84EHmNjbEGWjjD0hUXN77/w0393p6ZvNv7+XE3X1zmb1rOQfeOHALIb272tW9ZLwnu/osJj1+Lw1Mxy7X1Oq0HRjz7GK/vKrcs2ppQeBhUYDCUY5TFsJyJomtr+ahAvTNlLN8qRy3GW7w0zuEfMxglcv48Xg1k88tsbEtnc9k3dgQ7uXpGDAM3FYTcnJGpIjY7eojTteLSc1iaaWXmfAC0nw+68UACpF1QyKEVKQbln/SpHI5m25sSFj/3OTgHtLh0cAr7/x8GqFTCz/4YsLq/LY5PRPU+l3olXl8Z/8lvGG5MaDbeWC0SrygEsM5vpiKkWil683PaqbVOZ8oXsTbCl2clys+mZbC29dTFXREfN3/B51Nf3AP26PMZbd+I4dNQH9PAD2MBx8n6kjrxFNVafs+P3JtKvMs/aGsduJFpzaBTrqOokOQ9zLeG6U16qAAAgAElEQVSeV3/hd3cictzh24WkfPoPFyd+/ovS3xdbxii7NDLOANF0K2x5KeWNekdGB3qJMpx5ftVrz0zaG1cqYafrQxGa1R8lhWpJjrAasjU0+g3zCdf2AH2Hn7C9/DfGgKkjO7lMrMfL87j/iLJBRaVJTxlgynolwxnojHbGZKFgRvoC1b2v/Pz/tSsOvZMB7aBue/xHPtWc/OlvOvnIIGbWcKnBl4ZZH3WsEUXAdRZy2wIuIg7cr3jN6w11cdYTIxI27uDagN41PPy3dxWPuJPLvB51716RgwDNs6PbnYQ5c/SAZNW60DJm1ihreu4TnBkuDPNFW0bjbekdUBKdNeS7Z3/uk99JgF6of+Qf3Rz72PlUW89oKygtB3JrAmbajSC5VuJZypiS3FhNicwkiMAw7hn0vX3i2mVPrexcu7E6ucHMHqC3i7Rd1rMrf2MMOsmxvPnmm5TM26PTmSlVyzh7g3MwxlYDpTMUIGhdCFpnmPFKdTmrHNQuMBbxwct/6e+AMd8xUd8z9b/4L26UP/KC8KziViuPMy2YMQHTrQnRvmY5RbwLQK2xyJJa4t1OjLVaR1X2TfHrr0Sw0Af1+vmSSlN+GkvUzWb/mKibXmZm8ODfW9jlo3pDm929HPrqr4yDti49AXjMAjm2E3VO+wbJLZRol01WWurAsZq4cblhFjqxrpfaWC6tS5urNWSsXGmn5WkKkKX42WMz//3/zHR31dDyhj6VERe7NvnX/m5c/54ZhmgYaLBAcjTF1pj2ZNi+prVkw5sahTDrzNUpOz7Z1aX6IfvnL3tkUNpkvnL2wKwEg0TdUHy8ugfoO4wAe/XMOJj2PaMuI6UEz/OA6Kx94J6AJck4zNygUKuurpYN1ktuX6r+PleJUiChWm2a4IAxBgUT9vCV3/yrIrv5ljt8G9vu/srxv/erRoytU5kYC8xjuj2BzetiwG1EkTpSUAr2GytCZ0pxX8yaB06N4ZVXKrzZ22rj0OHznSy7Ur3vd+a3Pdg3seJdy6FbL/zmRNVPRgN6QAiZMfc/NM6WrntqrlWKmO3osXKMfmlt0zaAQIJZ1F49ltUDzpeDARy4+VsfKcXPf+BNfDarlzYsWrx09Hf/lyLTMyUBM8CAc4sBk+0GLF7XlAC4/4I6TQ0AVOzcsmBSkWfhxezUqXGcu1b3FjaavrfamDENL+N9f3sP0HcSDHbmNycg7bngPElhreSrj3k8XXFMdBbucQvHSX1xxuNgOqZajlmtpHVel0pgwXR0WOtB5QDliyPjRCmbLR+89r/+TwiKUuO9qaXT+IF/Pj/x088M+8kZgxgw3a4Hi9e1ZlgkyeHALB3vx6VFArRknF+Rp95+kF84F0HSD1S79S1tmE8TXMKTvzU6HOdNnZmNF79rOTQBWvZ6Jx2AhbFSMSQ6fIsJlMKZ5MT94/7cTJTNrWRsoiRZaZ19mnNlmllU79qSCxgwiqIMrZ2a/6ffV+v8l596M5+Z5JOvXDn6tz5llEAm8o1Ci2OrBRMsbe8PV2a0Fizf7GitNPy5RZtJM2MevE8ILSezVy+vc8rqVx2ev2Iuibr5Zd7FPUDfYRTYl351UrLMAXqrsmgmxzp2Ytqz3ZUGj1tSiwgGhU5rbEtG9Z6pbIiAGWt/8b6x1md/gunulikTthrHTs4j42m39MiXZsf+uz+2GI7ckJPsKxzSToN1r/EBGVorAM61QdtNVszBwwyVHrPXrpbF1tx51Bgzzi5WTvz9mzsZ/5tV9+7l0Nd/dVJ1k/to4m61dXDBr6RGlvFGeV5O7LcYRELFvZIXt0mFp50vkjBdHdS6MpqmEKzhhyFszMu9Zw6H8voEV/OT3PQ29xXd5dM04Eklxhelf2ChF771eiKm3c5TJA8XcjH9Lo6VBfRRtvd7rWspGCRRAzh9rTyvq8vjiiOvis5iWS8uVnh313powcVruAfoXT7VbTazF355SiE6QG/cV3A9xItfqa5ES3Jsqm2rUwAWQ5Z0Sly2BaRpApVqM6McA0P5WlyKcVqC5UuxUaU4R3RUGW4/XH+r88N9ru5yyBADkO3xYOGqMR5PjYg6Kmwo60e+UPGEWLwS6pVOxdNycK/wbU7xarVuql6rnP7U7XtY7fTCu6h/93JoArTRD2znnp2rKBok2tKVasdONBT4QddAxVjPY2hoxxxUVtRo0ynGGO05DApsf37I4EBGhr4zz5YXLeoWzlLr2zPg1oBGotRVcUyUfm88P7yNJ0GaW221ANBZJGw7kaLMGMX3Jkno6U7E0rRh5+cEy9Tg/W/9+o9gD4F5Fe/ZA/SWj/12KrSf/cV9YYg5oHew8Wtb1yq0KDSGM8OQG+sLSo3XUf5YRwWTxIQ5GsMESK6t8Rko8j1evytsMfK1zTU3vZetdt68RePii5BzdECLhknNuQLwlEJB7v0e10mNJzcjoWMElQVgJCXuYNbYGiwuCXTM+bZKhvqV8qlPz95WJ29Q47uXQ7/ya/tU1n4wn6etpOi1821Vq6QmqHDPN0WGaMo42oWg0ZTVg9Zapi2SIZlbcmuzlFUcLTC0gnapt8wwZgwnfzcOhmrQppmMceu2g3XJFCmF1iDYh7dCZmAM7VSViyjEmeky9FMpWuppRj1qbblGZMYK2sWNgWFA+wVxrrUwTAthjMey1pTfmbFWWQ58nUxUhZt9QG81P5ujTYC9gHuAvrOvpCVAy+5DO71KT9UqMZQqlqEtRGLO0PRMUGuaaBotkkUZrXViM2hrGRiO0mpODkEEb2uAGQTa5jXfWg2wry4kQse0tMz7JzFgjZ/n9R14HZJtvkXbqmiT82IaG+1JiIz86ig9o7Ee0v61ThyyaKlPbSkNaYhZezzozGhJ29GtLw224PTQO52j4foZ8gvlB//P67fbzxvR/q7l0J0//+v7A5GOBjQZTdxuVrnxZFAiiW29rHilbCj9UB9sWlsbY1DrZJU8z8eQiGCURUZbqmmLYAzS9mpWW9pazf2HVqNh9DeHR3K2AGK5Fjnt/Lo2x4aWosTPdc71+3nLSdtClyUen48p75W6pDMkeqBL0VB8AUjSd/u7gWBZe5K3rlGDAjCUWoleilJ2czkQanVBuBpyxplV2qCgORqeoBEfPIHiZdwD9J19H+2f//X9iqUuJ23hu0B0VKEHVzzANtQqmalUKWU4J0ckUoNpZWNbra1Iz0WRE1DcdsQDm2wTZ1zltP1zVCcv/V2pCOwD7RG5+22MIjHEUQdcTsk11vrP+14TUWjTT4d42qK5X+hPq0oUA3TsdnbzuG5PwNIM5wIpJ99gidTcki+UHLx/dx5XU6bnL3zf96OYP/IDKf5G56WEl0oP/9+7SsV7Z1Gwsfe7lkPbc790QCmdJ1neQelgtRLrasVpc/scihZQsSrVViCazlVv62Xe1V8EYOKK9BIQRyQJABhI4pVODqA/kRtcLg87Vt8XS4ohksyd6ygcl3VSOlq3kb11e4zT1sdOKHGbfLvrrY2okLlzNSJ9F0KbtSdEe0YTSIdKxc4tBaCL7AarZ7daQw9L3NLii3uA3gHIdlOVAJ1q6bzhhg0Pw/0VhgiiHahVtKlUNG1guYoyYzsqrLVNOefQqzIxQZtEWQGKUa5ozoxlnHglffBpf2JS95H/tOtqI6Y23NoA883lbwdcuiZJF5Zy3ljBSXSnhac1OaX3xxi6YPFNIGiTFB0I3Zrgy9c0qWwGr8bQVmB+yQflNlkp5mg78zU8aGnti6W3/8OZ3TynN7rNXcuhu09/YpoL9Vb3gCwjKRaJugkcYjHkiEQ7xBJ1gIZyLkP3gUvgjk1EgaXTjrtSwkYkJsq5BhQUW2itYARj6p44MQnMlKaZdGmWNixGZkCrfBtukhY0APJcHl6n8FhdFNL1GSUkI5mblnqoweYvCpDihPb0JlmcNm+jbQWcfK3QKo1GU9SYonvwMGtPYWvGIPHy/gK0z9IrYmHRRy0H73/UfBVzR3TUecHgBdwD9J19N+35T0ynsX2bu8oQiyYGp4HTdu8O4LSY4xwt0S7WKpktV0kN52zIBDAmTc9UG8u6fASAQrK4sEg6amRIsEdtrCFdhyF9miamysFqcoVySgqV801kpADpL9xo0VeoUQijffHBVaT8zk5koc3n6SXpixLUgdN4kATNGKnsLDJuOHLUSHpzx85pucu41SiVjpCSNbYuu/RRoi/DW2up/xrML/io5OD953e8lRpv/flA2HN7gL6zeIbun/3lg9xiDugdlAQbla6Nqo6bWWUJvIqXyl1bnmxnfNKByAXskbVQK7RacbCKWcqdT3yyL2KT5mFAJTc4hEKdt9mw6CqjzOxrbRmQNsWQiG0svVhMAfMMQ0EKCvcCIdqA6bjBs5ueTVoe9HpOBidlHwMom8VFEjl2MD0jqxo/OFd666dc1qbv9HL3ihwEaIC373SCu1itZKZUIbaeca8iWaWhUUSpZmE3sxUSHRBkxsFIkWv8co2E47hvYnHCdp69wAA5krJAA/d8brOaDx3GjeQq6QYqWeLQzej+amJpgeduHLdVjBHnSo9+2uXV+04vdy2g7Z/95YMpmofdBG+1bCeJ2CkhLCZYrfSgXEtZdSzDcMxycrxkIKX1Oyn4PlMxcWa321TfVEGTRIs/J6Hnlo6+LN3XMZPimZGsXDQoxIhc/CAxgowvhQEFi76dgWSjwxMKtEzT9XPjI4nlrp9+VcwlGC4ZD7gQrCxs7ORtkrNRJ17WXvBtt9PgKzmgB+5/JCD7c+PmiMqQRGK0//weoO/wq9z76s8fYpw/QpfRoIEDd5RKcUw0/wOt22iHWGO7plpZEgfuURhN2NxGjdwwiLX1pDQUI0u+EECs0Ir8AaPKDRW5vOtM1eRWAdaB2Lh0YtqS4qzvjEQ6Y+LoRIfxSvK0wzYZZkgGd2JzLsuQqOD02KTN4OheElf6L0qhv3ODMLSgZIJ7PAhAUnNaFJCoJABSoeZn96mblzlqPXj/br4G1hRbzZd7kVLxfPR9/+j2kvPdYTwU3d+9HPpbv3iolyVug5NhtV2mFQKLuGGWox8Io0MvsSi48Fhmo3rLVo+6mBS3ICTcok2lAplpA2QEIZY2IGLkRg1CE2kfSBvhPOWcRZB+O+aItMlJ7mVPqr5igomz04qSkR3b0dxCQos7JP8Px/RJS9c3oTuTNynrSNfsbCuW1HWD46HXltTXOh8XK5c9Mooi7VTozPZgwAfTLcH8qwKU9NBoa7RiqJSfKWVRa26VKcwwW6k9reDPRd+1B+g7+k72vvZXDnPQ79AghOS+Z7jnGfA8QonTIOTJDI1TRlhpPLAK0Ogmm5ju2drR3Ae5b4kjy6CySOl3CZikoiOeTP4clnESWpE0DM7Pw4HVLSlp78scuAV813lTFD8G1HaFSOI+6cYt+pzIUUi5uUhjOe05kadIchIOyRrk22FJvjdkf3efEIvaGM9jxuPUz5r4Qq3o3sblzecCkaSGCa7pRjgN3HcDM8TNSeuttSGBy7Mq4zpV5BI1/OCswueid/0Tty3zd3q5azj0E088wU+850Qw226XfF6OjiXPHB3LLr+VPs9gjRaG5F4yL2SKodFOjeWR27EmNmp8BJNZzZr8yNE2a9xL2jhKBE2qudxFCJnUgHGqaNG1aiMh4cE668naVJHCgzQcjqs6nk3rtdx65wzWhXPSLZaRuXElB7xzVOp3vXatwbfEyeA0gL5F0Qnlzr8j4GhpNyun+wZN7xo5MpE2kV4CfUBffTowKx2SrJ3S3NCHhYPU3NOQx1UKlmWUDEEx5jlrPFlPlTaCqUzoNAOdSWHNM3uAvs1X+ckLTwbR5HQEC2kFQhNq5KR6NaBQeZUgO3bjy5O13iunSWrULKparbIKNFucVMHEeFgoJHq+smEkuV/SGISWcV9ar5JAab+TigecIwguxtKztCi1AVIyEzKck1DfVkKmardpD6V4IebeBzNhiZKkF74dufcdiRd9B36nBnT99y2KuVyMRjtRppBpnYefk3Gd60fxWtDrll+JLu489SyGPrmxInLy9aNru1CywpKIiEYlESazAtPEKik90D0uu7Fnk1RiGCjwPF83u8A9TKBMG46qSHe6lIRKmsAnLxFSadI+ny1x+IUrlXdc8qKoF8/N95ovNZPHH398ZJzjbT72227+HcOhCcAsbJStwlrFY76SmmmmM4OYsK6XctZDXS7ZmPFYpW3/oYXnTzfUhYfKcnHF+LWwp0VVCC4BGNec+xrCQCMGBnlgme9TkiHDkdyAiHthBqJiyaM5Vz4Q4PoqXJJf6T/yJVKWzNFGEdIcX81dQglAJMGg17cE9n0uHMpzsG7qDz1gaCFrn6vb/xs5RDmZPXckze2GTtQBdBIKYV0w93UhQSg3eJN8Lml565g5B5NwNDExdVoOcMaUMVJ6CCmDLLUqUwJsxnUcuzdWaeObVodAnPBKVUsDVd5appQ7BO4kajx3Yf9PzkBXhSbQATEXZqTmJuhBr9t5/6n39+gVum00vg4dvGmAprXO5175eoVjWvdYqaSZYlpZWfFNT2rZ81JPy6DMM93zGQZph3GsmE4ta2bYDdjiI/Irx2rp8veTasGQ3GwZRU6BBuLKfghchBq9gPwdBJjMs1lb2F7HGkOZ3PwEKwc08+qaYlNIhnCGP+aUDS45vns8zt+N7G7O+87JnkXsym1ppQmehNRBLcZQ9EthPySNIDkokYzklqUO4049kjtdOxM+kkWRwCvQZp6J5yLoLDJELa2IFIuqGkXJAhcIWgmrY2azhFudWqW08C0piAx56wmmMz9tdRzn5uUafapWNP/a+cpHLosSCD/J4nJQZknF83WSlBAh1JKzUsPLuu20Ewndfuyex3YdkHu7mH5DAX3WnhX6RV2HUr0OWRxyI4wSuoeB381iK/eVhVqcX0QxXm0krVSjD4IjQ901dula3KqeqFlj5URV8NJ07/z0VPLSQ7R6J/2FNFFZe35ZoYisAUo/EXs6bvsmbnKTxIYJEUO5ZoQXMW2MANkjCPWgNCmVqFuGwgmmzneCOHDua5Tjur/w60cA9klfIzeCMfWxuepdOtDegXHkIrLP2/suq7nn0nqf/dVlZn9s5HEN5DXNnMNJ4rN40Ye0hUx4ErxIIBim445nOh2ax4SXKxLCuuZhhdL/Ca5TobIeGtn1DHFrZqzhvhHAaE3CQcZCd+JF7/grF8LHZpuxkRHrtMYqY3yumfjekUbsMw91O+Y+h8hjWDJWB9pwg0p3VdJe+dDbP+Qi19+ocscBffbsWaEP6DqvlMZsYgLQQO7ynTjVvTJXMvYPy+jkjOaX+dRykmBgQiszyQy3CqTh0IvbuhpGUVAeYwK9EFUqMWjds/TZfaWs+V7Jo7phUUkDL5GkyW3WikxnieukK6zKUDDegdqEZqUagpHcdJtc9mJPgJHOD4302GHUxdKE5lFdGx4RHyT9Wn99tx7PhDNOzkfk7ZHrqVcjUAql88aIq00lEFd9QMc83P86MJD4QQZ7TisK8sSTvTKmC55qrQTMZE7B4VJIc5byck2zoEYCVGh6S4FaXjHM48qKQHm1WgKlCcN4iQNKa9Keb9OOr9tNpqU0fuRLI0q0iugGB565WXr3n8lZKc3JYKLb1BxVppVtdaeiKT0fSy5XQMHJQB/sGkHcGzNVYYgRZClJRJ1qubr06MFHd76l3A7fhDsG6CcvPFnzbXVSM1UiEAswbSPqHdNZVE3RlB899VH19Ytfn1pJMpbqzAiJoeAq7ngRF0vLnXTsZDohmlOK2zF6dBptu9c27SP7q1k7bdcmOy+/o9q58m7iyuR84dl4MdCtBSHTxNo0C9GaJmtMZl5jkrZzZSpeKunlxcDKLEXuCZtJMEY7fyJkqKznxxCGhkWVFIN6ZkUFUAS2v7JzZpKcaVpGC8Y1c8eQ97QzJvaB7uJIXGxUUZ80JoXdchOBo8+unX81OSu5EFkSfyi3tYc6ZiZrh9BrBZB0hE0yppUiDQZpbehrxBlnCpTSGJVSVt+fYlAJTNaO9PINX7faBrmXYugbUar0WG0/8LAKRmUIqhuaXsvXK0vMkl7EF/PRva++NvHeBZQqNb632LoK8Ynji9hMxqdUN/fMarbjLkAtjvxFrExU3N+81POSSuLLNq+WojBK0sRyL1peiq8sP3768ddnr44hwL+ugCaRAi7BpGZ8nGUMrUw7ftlv1YJaJmdk9uijj0oCeiNsiFYLIGZprYwyM53QLqllI6qp2wuvwRuT2g8nQyky7fWWwyzsXdfXU6gd5mOxPG4tHhxLX7t3PLn8Nm7SpYpemuVZr8dQZuSszwXDFZw4IEV9n2XcE2lztgqL80zJTIlS5KlMaiO1VzgXUeQKqfdcLJQQEqwwPPSk9KME/IrifmSBR8oy3zAmnBmQNBf9ybSckdHQ6dZyEYV0L9xR97uQl53DKOlgnBWFrDqry0dCIvmiFn06nxJanhqjfKZTBBn7OusFKLsAaRLSitVm0r2Qww+VIUttFAieOseqVPthHE0d1EZ4ApJeJVu4wQz5q1DmYM5NEAWxLTcSf+wQMM/nWdpjQveibGW+JJeXm2L8uRcP/bfXlBE1JdNGAGEq0+pMdbzrrt2TrBZwWV7odQzXFaPnVesnHnvMpfI9Yy1736Wn/FjFfh3rYQZYy7I0FJ6JU0jnP3zfh3e9B/ko5v26APrsxbOhsWa/Ba/OMnqLzUqms5hSE3/4vg+ntAB86tJTtW5bYMCSqo38IOkkSmplogyXX5mA9N3NfWZ5DEqQdY9yo40Mgnk/zXrzp+bjx/Fxffbi2UYm7QMW9KRAETWSK9OHWt+Myqa9YE038Ujt1jd999jEZNtrHGbgeRxUr5Fcf0Vg6pIUZqxURtXtEZiL+rTHuzM09E3lxXFiNaeVP+1KpMgnGiNfIfe1ZYFBz9cWfTLQ0a6A5I5NSjharDnfZkvxrAU8B3g0QYDkFdrj2GoyzxjubOhKcQSF1kphZcbRpKhl5nGdMh0rWuCRZsHnRrkYl4FcSsV4B+8ntSKgEDNh8vtWNgiAcUarP2bi1ENmButLBlxjrdTzJo+kzBvnhrQkWvqmvejJ3mcn3/cPXyBNlMf2hSprj3EODWtYs/nAzStwHviJsRNi9vosTOyfsP5NXxHzGgbcE/YJfnjmsN/NfN+33Zr0sGpTa4U184898BhteXFbS+3B5ckOJZW8+levfjWKk/igNFgpo9fuyu4KKkybb2smDoRnz4pqtYpRFOFieXEibseipwwvRSXMOq12nE10YWYmI53m51743HG0/njgsbmW9prpc9d7ha7z81c/P45t7y3IsMFJo2FMdLD1zI0jybeOeKClNqSacnoK1IzzlnfoXoVelYRbD2S70bv2Mmf0aeSQYhBpRil0k2TV1cNSmKsLac39p/vHROm3g14R4mTok84ZfYwpypSg6WIFuEClkVMwABkVyfSSx3BTAhtauZFOmlRr5HgEhvBMLqlk5Wa+0eTJSvoUxmhJpVyyG5CZ06nTl2NwDMW9EnXjHbh/92AMspiVSxF2e5ySnQ05B2y8v7X7l1iKlsKpEwZLdbRpxhF1m9e+cq50z+cLMeHcuXP+Rb1U9oIeMbHAsOTiTjkt9XHZvxwyWSlHwjY0aiYxmP/Qye+jtL27BvauODS9qb71DzHLqjzgrXarvdLrjCePv/vdpK5ZHQxxVeazaqepGLfSkxnDUOPccracnU/PyzOPnVH01o5dGLvfKMGtTa9PxpPtwbf77NmzFTWlHgbBJ9yz0qbC0L768OJ/WIrS+XcOv4kKgqBdPnh/pplPmOAAKkwXL5X0cpMeLAHQisB3zvtWS49k6depOKDQNQonpv5vRsoDQ7pj4/RjoDn4wjq7JqnKCmDeahhFcAJRB+Ah56KiHd2bIpHBQ7RSqZBJJ6dSql1Om6+Qg9Y2CollK8HhtxoysyMzzdLRF+dLJ/74A/d94KUBfTP+wfWno0q3PW6V3S8zefVDb//QjlPuOjH1PIQ60mVPeeMJM2REuPHYA4/taguMbd3gwBzg2WfPHrJVO4EGu91ed7G8WI4fe2xN70hM5usXvzwVa+71ZI8iLQQBOUhhaa49l4bNcNXKRHU/+8IfnQoE05GJZt7z4Hs6gy8EyV/f8/yX38I9dhyk4oZRjBBWfMG/8L3Xf6+ijf7+4edDMvCyf/h+gywszjHQcaRWbgRmZcVxYUP7YqOgjQ0lcVLUxjNGWS51waXX9Xu7QXlbgeg2+neLQC4ExbDTEpSB0cwoRfbHW152G9dbDg6fzHg0xbROF8N7LyxUTryGIvqzD538vnWg/b2nf8873jg+xhN+LAuySx++78O7SoxOjG3q/FQEJaiAhklttQl19+p7Hvzx9lbTN3h+24CmxZynvGMBRcsbPheUgu67j7yb5OTVQiJGfDjmHHk9yixvZh6TqGRJWNWCVmd4Zfull790wmpbNmPmtQ8d+BCpdNZ9ar524claW3nvMhYjcg51HNpgdEPb//hzS//S66rOj20AtLEYB/v2dXjlUJGfwokN2mTCxs2S6S4J2+mR91EuKlCeL8bBCiaRJAHnlWRyvxDiabe5JdpOnsZWdZE53xPDyJAkGEV9OwdZElsIyERpvE6Lfnul5e0/3PPqx7hVvfnooWdb0ZEVMPLaD5z+oWeGrYLkZxM8FEyGLDwOCp6/Hd0zAbvy9UrZq3gN4Ytx8GBl/k/nr27X1L4tQH/5/JePCc+MJ4lZ8Jm//Nhn/nMPzpzZsLr+40t/PI069TqZYr41tisF00u95Weh0Tnz2GOEyDVx5NzZSgbZ6TIvnx/mzMWj+Oz5zx4LFD6SO5xzcqKw2pp6ibEv/qcnvnbzV9/13E9ahArlEBhMHKNQeB0+MS15ecI51ReO8bSwIq8ym3Z922v5JunRAoxAop1TsvNRQsYRleac8n3lbxGAcIEihhyhKF5Qry4AACAASURBVBS3DxqyT5JCbz2AirHkZu08e9Lg+Ea9hO5vZERy8nCufmMokILE3EvXTyzjbD/aWM+5fzvHLEqF4Kx8nlh1oN4RmkeNd14cOQVeUEWA+LXK933VeEJrzbt+xf/KKEvg2bNnRDb9riMqU5UfeduP/PmOBjCi8tNPP+3d8G9UyoG3n1IMhlC9+J4H37Mlt94U0E+ce8Ifh8pJTkp6a69Pxpfbjz76VzfInF989Yv1MR6UukkcKi6YbEmUkhTL4Zxoi+5jjz22IQzoPz37uQcygbp1rnXxVm/fl7712fu1L06ByrkzARoVi4zVy+Fy+T+/I/nUMcb1u0Y9kEx7QebXxxJRnlQGA/J5zsMBXQg3aZJpe7TMQ91DlSQBZj1m0ozRIoo4IYFxNddFzhlJRs7DV7mLWll1zidNdt/FuXg2ubEkl53FGp7JT49esA311z1TNzy3nRrpPwyjjTOLvzmrN/kiAXj9r8dWL9BOz6e81ljx9j/EUaU9f/LqtfLDL7v3DTCLW9lXfvw9o8WAJ65+NRpfbj4cZ+rZjzz6kdfDiIJfePYLJWAwLridkgCzP3TqhzZNGnlLQH/h2S+UmdD3i4C1PZXefM+DP75Ovh18AM6Iwv0IumTlLEO3OwcmiNLGSqMzCszU9vPf+vw7ueIvffDRD5IecuQn8nPf/Nxxxu3DayqqPDLFMBsZbWektM+8d+EfvxcRXD6NDZyPdMrMLyW8NpbZoE5+PWQY6ftf5pihkFLQGslfmpzhjUrB6swHmSLKjPYFh1QbEAQuyqgETl9MrsWrpdDK8bVFVxGmRYKLE3mKROXE5d11B2IUCay5UjgvedIN9zeX48iFo9A+yOTRcYv0ULfLEvvtY15tdMTEveT8ZC12X2t899c1RrQnAIV49bx69Me38tUgcaH6fPV0meP8e7cA3k6GS9y6V3+toW3jEDO2+b4HP3TxVu1HAvrsubMVy7IHrFULiyvducff/fg6WbnojLQdVebtN9JwySTq2Ng0ScCgr26ywzf+6ghdZNH2S8/9wbuWxia+9fiQHD440C8+/cW68eN3AyCZzPNnzSlWw31kAzC4WLGzL5+68YePcASnBdkAauK2yD2JQZRhqSZJnYfCzxNrDQa+Uv44+u3SFxnKeoDGaKC0BRT9DVpx8huxljzVCPxaGEonQF97ZUmvq5my1MRFB9wiIrwYH3FNx+VBIAHXyfOWM4Uu9oqTidoCCgNckFORtMyjb4MHmTNP+zYd+Ux2ApTBuoTYNJjcn0Bt2nDnepjcKL31zzpi0n3maTWOHlz72qkfffrMLTzrSJauPxjdZ7RIfviRH359AwLOnGFnf/ztNR2FRyExyQce/hH31RguGwD91a8+EaXV8ukM5M0my27eykTZN5b4pUSXlae5zixf6iTCEx5bvrG8/PEPf5wm4paLky+f+4N3xkutCz/6/T9LFqWR9WiCaqeit1ilTzCXrLBfyAhnLUewntIoA5lcf2T58we5XBgfCSTifqQi4UyQH7BiXimDoGIwiMi2a51jZhHk6mzNbkC5Oo24Y9/5mSgZoHO/aArqIyWgS91MOmXnXkoWcqus0zujzkWHtRjZfigXNSVP+ty90+mtgZPWm5LFIMk8zEXGcNrZKt9njn67eC7QnNuMq14nBNniptsjMYmMKMO57Qbna92eFutQwDAWjbFYVPZr65XJeVWD6M5WHni2JyZymZXiiKVUSgdP/8g7f+SWmfxJjo7HHnlr5InZx07fut5uXzqSep688GTVT/A4Z1nvsdM//sqmgCYtBZ9OTmkLrWp36tooa0/Rwdlv/vuGX6/VkyQBYs6pjDWmqLMgMfFrovX445vb6v/om//mPssD3nwxvrDZCvb3/+T3q+Uqf1haPUXXRovEAlPU0LOcdci/KZFG+R6vHVx57uh+9doRXy1nZH1zThfUhtb+ZP7of/5JO2BMIKzHeGa80HA/VOhFFrlvgFEYF4nH7mXPrXJ5KQ4oA4zh2iXoyh841eoHvzp2tt47qXDuz+lallDG0GVOcqGDzlCZ+1OvBR70r9t3hDIkkLvgKnrpKL+vin3dWymZ3hJQHEpfDCru9Vb3T39XtMYIK/WElScs8yKXDgqtjVlj5lLpoZe4CN3KhYLijZSU8ObFqFl/+VYiJI30q1efiLqL4TvEcvXpQVXubQB4JBN+8mtPVis1dlJyefMHHvjIuiSS6zj02Wd+/ySrcq+L7DUyWW8yEDx78WwAKyuhDi0HxYXxIi4XpWeyZveZ939s6VafpaJPsjJ2Fua/qwvm3E888hO0GeStuDl+6YV/N6669phgUZJC3C0ZvxsrnmmhVfxarCqPVDCdSaPSJFa9bnffgd5zp2vpwqHA9sg3uEcqOM5JM5urO4pjRx2D5GSC4aQOsySeAA/IZ5qSe2rLKThAME42PMMo5YtzaCsCX3OtWT+KL+/fgU7nK79RxQXI8oFMdQO+HvRAnAjdjxLM4wqAMjUppA3nrJLM6ozc3bhSJOOn1vQyj+J5RtwfXZ/+TvcqDYiUlyvGqzSkFRXLhF9cLPUqNxdL97zc8SZpreSKQYPMknSmLnmNxoub+TmT/Dz5bPig1sp88B0/+eJ2rX3UjqzKOwQ9fv7cE2M+lO/zuTo/qKteBTRpKkSvd59K0wsffPTxWy7U6MK0YJyqqslmmiFTxJ1RxxloJroaoNr7yKMfIfluK10onn32yUMZZIcAWs9/6O0/f0u/WTKw/Ogzfxi2286LSz02pAIsJuPpp3/PS5IDYauUhr40Ywd7L54qycV7fdOtM53GgSHf3zQj7QFxs77r0Pq5dLoLziRSVkaP0m8x8uNAJrhybse0VYsn3M4VKLiLesmz0JCUkCdv7Afp5okeaX1H+Qmcx5xjwRRM5lLskkOzk0ddvgNSgGhmjNaoDMnnyJSkzE2CkudZpQo9s6VFC1LgpKJkeKv3sm6hmudTZwr9UHlROcOwqtEr2TzMBjnSRqWQdsTY9Xbp2OUe1gZkcqfFoTyr/3973x4b13Xe+Z3Hfc3M5XBIDkWGeti0JcWULb8oWZYlS2wTO/Y6zSYLa7eLYFM32appGgP7R7F/lv8uFigW2XVTB+h2GyTZBV2g29prw3YQSY0t2xJpVVJEO5EtWxYtSqQ4nOE87uO8Vt8lqVDUDElRlC25voAggjz33HPP/Z3vfOd7/L5YifCU4t6HC1kt8Ps8eOz5dSB0eymOjzU6c80HLYL5C+81fZESko3DSBglgxh4NQxMDSTUzrnnwr11rGrYD6qjuR63ixPW0rfpXx2dxdslQB849n/vAgJFfSE7utC2gp2hahK3xE6riE28KjDRe1UzPp7W+XxeHzhwQPfXsVHXW4HoZbrNtK1RxOQp6HcXW0hLXcX9Fw8Qu3btsgMvsBVXdmt8ti0bfrTREVPrbFNt4xgVr6LQMjLECD0ulZhLz5kc1tDxMqN2JHbkaW5F0MhgkPye466fEJ4nMRuIWOSDxnzs5FA1Q/k4o+YkkhCNlwTd39N542i9QJMeAh21FI4Uo5iLmIh8VEOm7d5op8Mowtn3n9WXZ/mtp/XjpOiRpYjlRmClNLNTGrijKbEVUlUmZwFiBHPLMc9cmGL5c2W3q4BRJ3PnNUlcTMQ6KUht3odWDyPiGu7WCKzm9bTbKN5iM/Prvnu/nkTZLeXC7/TYd3bklAncqMItENIVSrpGEYcYxWOA0Se2/JtTjfrat+9vXJJvuksycupLd3wDg5umcydQ4to0vCPW7jvX4uVZykvMb/Piiz9wnI6uDqlNB2h+9o0tX/t4MXXlKp9DBk4MWPkxsKHZ4lNR4NxSHeki5sJaX0eriInabC2RL9rgds5AxiCVtEDESbx0krI6yxc3kzOYcMfN/K6O40RolZj1VFLyBFcB5uMmtuXEyYOnWXyH2QPsfDvx/PebdcwkagAwJgmzCLO5INRV1HIQuECYbQy1VJI3Ow1KY6gQ3C0l/2jz5JTTPhFSL8aaG5fz6zJMoEwywqk2ZSD0jJKps15wqNbX19+QSuz5wedTjg42YOw1ZfRU38Kq4xWfDRfD6ru99ZSbtjCAyCBrFeXVoCJCB2wxXg7CPX17LqlA8zvAnWHn0Rc6iRZtv3PfN1BKTwP6l7/6x7VEGc8VXacWOgheJZCW3BxVhYkonzNOvJpqisn2H6yUtK43CT3Dz/HsSGjRVpdHdoqqqfNel/q41YvCdqbjVkp1jsrQ56A9osIURS0BZfOsKU9rxSjSJqAugaY9ZFOc8R6qae9hwnIw46FMGErnXHgQTHJikwMieicNkejFTlJ20WSHgVqGG7C4STKvCdeEo9kOTT3coFkvObgij4gVaeIEkrJQMq8mmVutQaoa2Jmy4s3hbBUABPEVxDJo506OzgS3iikl4BzVcE7nM9XFpLK/Rq3htt0htZo0Kh59fNs3rzquGS1lrx3/f9l0s/KqRelK7qRIFHkxgK0iLHEnp8of8RMLGQ0GDg547Rl+TyZeO4jYTQCN6oZm1vh4T3V8GQr6koG7UEPcfrZ+5faMzbw2JeM8c1jZrZXP7Njx7YYOnRV58MVOpnX0IXYqPsUdXeZaUGa15omZmGIWUxYxoZsVRd8hUYaDyABEaWKMw8A4WgiHaGVxBtxgEe5k80duBfQBJSoyNdpCRyVPSGpQXUkscehaTGTKtCo+Tb6BSwMZwQwBS4kkgIVLBUxqyqU2REiWigy3oog4cQSe4Mghg/zYSTw3xVRhg+a7S6rDvElK/Df4kMTTbiIDrGAzPUaZMxFknODx9Y9jhF5DM2rrBugQQnQxcERs9Ggqny8uMymWDL4/0CSEc6chWmjJqoSICggSBCGaJi0SR5P0jVdPXVhIhUX1lzQX7jVAT6K6kwD6F8cG7ifKev/APxydWqr+u1JgqqeCeJ1rPBVH7ZLSZqNkaBH349de+sZkf38dZsPrNZCZfpOMi/37aRAcZ5XmDppNhzQsZ2kURDTfZpEomKAATVCrBaTJ9yGohUTYkmLt5JBxwoOIgJ3aQLnqIgTjL7AQwHQIacJhp9GSMA3I2SsBZaKsTBO4o5RlSMCgFPpeZtQVYzCebhq488Pn5k5KwtyRRGgbaZDYOgYBU5ozpNqdqMqg1uXeHS60M584MWCPVKCLU8hLJZQN7nlL8tLPH/q96nLVw+ms/5esLhJmi1WeBltnVCxTSmgrKc6hVBiJYPz3dn5rQdZTPFiuOg49TKqJHff9/tkE0PuO/12vjPTJ11/YU/40QFMPk5gFUx0567ku5LSmLdM6py4oW51/9O7/cEVk3nXG9XK6T+a2v7+fbHv0i/cwQm6VM1wIFO3NdTA4W5ho7p8SfXfetWD0J3odtUGemuQMSoEIBiaQxpriTBfB6FIMOoDWlujQ7Y+JRoBMHGdD/7tFxrwTHJ1WEgJqmXEZq4oXdNUWMxwsMmFk35G/z2Z8ukkaGsQiKmujy9WCiNIe0opwrqlO6yASX14CoDuOwEYjVXnX1t8/k0zWPx39P/dxTj98pefJ4nJX3HK++FLuSdJ+ShXXAZaSOmqJgKY4MZJzmIQiu9DXtwfNfYuZCJfyqOvW5uU3f3q/UeQWgkygydWoHP1S6ROne0FiXyRpnO0uUT8AaWIgAA1VAmSKAy8HStRq0hLQDvFwz7DsJ1dGSiaCbd8+Dv5os5K8XXHlMyyEYaAUR7VJT2WC8d2QpMNd40SRwcHnPYy+0ZNBkwTIADi+oLFHQooElBElUAprtHQ2Lk091ffUghwf6J3k+c2bLMPObbvra+cTQP/87YEeo6HCy/mz17jyrvFdG9+ehCfG3Y5IMdtyaMYC06SBphT6RCJZhbQs2AU11bfIBFy3AS7Q8Uuv/2QLAbM2UTmWeKE5MIE9mtUUA46pN7O0o4ZoBlom6oOikQYTGAZVYkQtJk6Q4jzUVijVx0VZeaxDNgIhSuHXX//HdEQqLcqCHNHMJRSJh+kUMVAqVqthM0DY1/cUmu1WRGigZWPd/fw2okwHGAjiUE0Jni45UI3LMuQsZhlmrKY4Emx1i3V80yLZ4YkOnR3dYkr8eF/fnso0oI//bBUVtCM8N/bu448/vZCHcImf4/o2S7IkLM+2tW9F5YrHHe0zwlORBNuymdQiDhwrXVSeKo+fgGCpweHXa9Qv7f/bB5lNViNl3vxnoG6cMCRIAGKBRj3XYM4BtuVaUkOEASKkNrFNaRQrFdkAYSx1zBwVa+pKVtLKtlH63yIX8gOgidRuzWaA8iwz0CS1SbJ6DEXZCFMqVpVarGLhpKMnH3wyWml6L7Rm9fbulSdODKSrABlNqC+kbjKKuagghUJWLUWLkalOBRHT/3r3H0wtMgby4ps/8dMOu/P8SfYWfucE0AMDA3bnRnWvJ9i7L9xAevRSAJak7nyYt+R7v3HcVRkaV2TKKEhrh6e0lLaVMMpQgVJMUV3RglRpR662iGt/KY9ecpuXD/z4VsJVFhPEMUZUG3RTY+aU0BL/l1QbV0rKXEVQ5oYVBb4tWU0rKWNT87h2q5ZG0La3p/XYWF7v3r0bPYt1aJtQdejncUu3AxVIK9A+5Sj1iIcBqbhLMIIS3apQHVQjqeJIE3F7zo82bdqDAawrIonnTw6CGbJtd4kYA8qicTIVjk+t6oxbJgoOyaasWqnmUYv7MlJIvFn80s5v1Y2mm9tvciB8W2+gDNTOe/7dTMz2TItfHv5ptwSVGk+5v7leJCBLRsA1NEz0wFuAB+8ct7XfyiyqLOoYVxrqsVh61LIsEwPTmMQERBDGIh3hoUkHaUJDxqzw+PFJuXfvlYkMyx0WWglKJWAjMAL5KHcJMEFQNuvWdZgg6DZDQ0OwYcOoGR/vMcPDw6a/vx/b1QVXYiF46b9boiltW5q4FmGeZjpFgXqgtWOQCTq5mUqiWUS5rDHDasBpWA0MhkeKIDgnHnvs+2KlpfD8OZqN1Ui8gv92c84Y3UIoZEEJT2Kuu+EFQ8TY6F3WFLwBdj6qOgBpierDIvNNXnvtrzPSs+/JmNpQb+/eJKHg0gn65MkXnY8nC5spNSO/eOH985+2+W654Jl/H07kE090sjjO8WLxnOV1+jQKFHV4k402ZMOlY5R2KOGWBGFpzaiVZMcgJ0ISu5TYfy1DhDYCmXaF7REBVUdWuVHNJJRV39KlqqszxYyurKuY7mDSlMsbDMCBZDi7d/ckwNy/f5gA7Ep+h/QOY2MHqef5pOLHVIecpVyfkmLAAWJOUjanRFtKUpsSYyklbeTwS2omJhwgBDkT0EevNCeCRiY2DoT4E7GsCLUUZmsFxbQEqEqA03Ihr99KzffcfhKpnGq7S2KmtGFnobbuwlh2jLZAweGa2tWi9IFazZSYtBCJm+l037ZvLqnAJ+5CzL9tswBV+t3eP0D3+Eyk4pwR7Bv8WRuQ6HYr0Cc+CYfG9ZjEpfaZEKh3T9Jy2WYANS4lZ7ytPbErpyRlNbA4IzWLUsfCuAIMCpbEWAgmwyQmHFKtDCU2xQTERDAgd8fcejuztYzQCow/IwAVmW47244l6gdGW+BfsU4tUp8iTy7VBMstYgEjwmQESuKiUg4IG3BBxVIp14ROVVOrSaEerbrbpDfiqauJp1nqfF1Fu9lwcjRZ0i9/vbuNcbdNa9XMNLCYkSmq4tHtv3YnhnD+vZyjKoFjhSql027Q1/vvF6UvwG+3am21WwFpCgtTv5p77rvMxokNO7uDLiFUZ9USx786I8av4mU+K03JwMAAzefzpL19nJ44McKy2TYapgW1uEOiAP8PCGc24bWQwIxDJeP7EEclygJO0BgVBZyk0kjchQ5EAMeVBqoAypMGs1w85RilxDTXRso1UC6DTLlGqtg4XpsWMjZeUNIVn+tM2dbTAWDDevdudCbWN719mh8A8XPrRridWDqtiH36gYsBQwjqRx7pcVRGuMSmHolIi4plNlnYhhStSJzesePb5eQstD9PFrOyGdNPDx5Zv8YY0wlBhIL3ssTZK4z2uE3EJLVORlFLNm2fuHuBsM5Pc/Ju8GeT/n5U5/rrDnNGP55Wc2/uK9FjKfXl9otpegjeJ5/saS4zuZrGplkqLRk1o7WCGkVz6syu6MQec6Oym2KgWhTVY31bn2qYBTN3ehDMb/7zurVRTDttJX69fft3CvOnr25OYZIrWDzXBYTnWRyf3L79O0iieLNP/s0NnRtw9AnA3t241iP61liRMUfKDzdvPhUMDXW6AH4qgjhLgbYJDS4xosiUOfPKKyNFPJ/NgnssG6nH1y9uKsb2+dXV9cyiTbGG97/0wLcQzFdgsi6gce7QZplOZ9q1Q7o4p2d33P/ByI24zd2A3/kzOSQE7+Hhde2ylC6hNJ55STI4+KwnrXSLRciqmGifgC5AlX24bds3p5JDIeRSNYhSIHXeUNEcBXL0kV1/fPJqJmlw8NlUbNyNaFPUFf1BX99TDTOcGgIaH5jkGLLjOWJ7aw3Ygmvv5JyXuZoxfd72Jp8BlJC3b4o3Cqk7wJiR2uTaU7P6LoL99dfXpF3XzsRcd+hQNmtDSkSGH+zc+SdF099Php7odIvK9dC23tf31JKSAFCF2fnIqk6X2WsjCgU7grPzdeYlqRxzG2GnX/nK7RlBahiAnwMpRnfsGP1cWt/kAF1o+EeGf7o+iGVt+z3fmpuAStDDFwRBC7WhK5TKNoH+8NVXR87MmngRK1//erc3HkQZG2CVUaSZg3j3oYe+e4kPD9sswSRM9u17Js1T7m0QS9fzUh+Vy3JyKWENC0rouS+N6S4AtWbHcToVNVRyffrAC6OFJQzuM/zpb95XO3r0x+lq1dX1dtx//vXfdokI7tBSFlv8zuPr56RgoaRev77qS2laIq260NRoYnj/4Yf3zmU0Is8PPutlypBynFz1anZ1dEIVCsVbKGWtkYkKRHjnx8fT5aWGLywZ0MmR3PTTt95qyShFcwLsdixpRwj96GY9NOIiPXDgdPwZXpTk6NEfp+pZqo4f/9mqUEabSco50rvxctvvtO4LWUX5LQRYFqT+zdatf3hm7vJNrGEx87WO85ryDiPE2K5d33unzhK/ZJdeaPljf0Gg1hDLaucAtThmo0qR8lKk8tx+rwrQszfiw8vlWppzp4VSjoxFInbMyM0ksX957C9zpkh6KhUx2Cgga9++ZzK+z6N6fH43imzGA1O5vCGuZ7+dVgHWbQ2NKDxwzx9dFhuBnuGKOL9Wx6bbSPFeb+/e9+e/04kTz2QqFTtvjL5FSlOedMnwfN8EGg9aW2lmItL08Yefvmoq3WTnd2qrLUraiOJhbFnnoFqrHDjwvdpyYvOXBejZF8eX8Tzfo1TmGFOthmtjgXWec33+RgYBjru5zd6hYz1y9mzbe/W2M1y0UWQeJKTlcKMtEwGfShnngQf+NMk4rncdPPgX3oMPTkX1LEQzkhAj0BoSGx49+pPVQlQLjdoMDv6v25hrWu6986nD9Z5/9OiP24UR9xClz9x//3+8TIImUpbrdh6TLypFJs+cyR2dPxfoYk6lbs1qHa6TUqakTA3Wk5qoiixVLcCQi1dffbbJ902XUpDVOq45jn8+jnX17Fn/UuWG5QiNawL07ANR7xkb+zjleZkMIapVKeMA0Kkoqp3r6/tPC5HILGfM13zPoSM/2hJXJaO07WgjsB4+/D+7pYzWnjnT+stGH+rNf/rLzQBUbnv4j4cbDeqNwz98KKy4Q/VAcOzYT3Ohqt6x9d4/Otjo/rd/9dd3Y93y++77dpLVPP9CXVgauUMLOLllyx9ekfKfSOkvr2qLbbZZCHN++/a9l1Hdohp56FBbTil7ozGaG1M6smPHf76CthafEwRRhnONi2tZVQ+QzTY/dq7dskgHcIaZwCUhvAtKBcH4eH5FwnxXBNCzk4xxyptC7hISe8aYHCGmSTOibaIKxWI49uijf/app0699daPNhCi11BKBnt799Yl1EGp5PudvyNlNLxt29MNg2XeeuuHj0YRPTbvQHQZ5oaGfvSEMeYX9SQsSm/P8h9RRL/YCCQI+khWdzb74cvrGzggDh36mw7Dwt64Zl7fufNPkkpi8y60F7cqpTdLqQvbt48fm79jvPnmD5qUYt1EUrJ913eP1Fs8MxaKhlGA9e4xAwPsYNdEKyFylTEkQylEAKwgpSkx1ha+8sqeaDmqRSMBsKKAnn3ItP++yfGinBM4YdpEcY44dgp1bUJgEonT+/q+94mnTg0OPpt1GN0aiPj4iy+OjzU6DB458sNbdAzdUzX3YKNDCZJaWrTwyAcfnXtpz57+hjX3hg791VcvTJZ/8eijf1aPGYocfvtHX6loc7ivd2/doBycy68+1v6QMHRi27b6OwFK2Tfe6NxAjVz70cfj+xuN5+DBv2ghytpMNZx+YNf3r6Ckff75Z1OdLli9X96Lu+qyr8Fnn7WiO3XOMiqvgfoK6zlpU6KUFRkT4UcfFcKF5mzZD54bPnotnSx0L0728HAPL5VGWK1GmzzPyTOtm/EeRWVRKXI+9Y5T7F3B+ONG4zl58gdOqeS4L7wwejEZuFFeXT/P5b7wu1ZsHX3uxdMNQT809MztWtPVW7Z8d/9C73/o0DNfnZysNQI0HHr9mS2U6LB3+/cbst7jQlSx6mvJy5caSWmUhIe7xu+LY8V29D39ZqMx4a4wYafJCgeeTduNedxOCGvnwDxCWBjK6ILWehygOfyNH6u9vXsx6PC6hlBcFwndaDLx4LBpE7CxsSpNpappIWQbB5pThNpEaWRjKCg+NTE6ehuyly45/+4qFuPs+zacVBzjHXeU2t65M3thoYTQt9/+q16t48ne3qevsA7MHc/hN//H1+xS8PO760toOHTomTU6Nl/ctuNPX230HkkY5u7sA4bz0zt2fP9so3Z4lpmYOJd9eHFrw5JMaQvNKy4Mra0cIbKdamjGgFhFoEIIGWclPRl4bDvSowAABHZJREFUfuz7scKUq+sN4rnj/EQBPffBKLmHhjoZxiO3Q42XQTUD0y0GmG/AYLhwoAgtShkW2tvXTi2WLHkVoF606VJO7GguQxVqsQPS4OB/WwtD3mijHQh3jcmzrH3rru9dZuedP8hpi9Jdainhldcj5ua1f/gvvmlxckzTVkJVFhmewMgAtF0wcVggPivn81yPjBRUX1//ZfV0Fp3wFWzwqQF6/qEF449npbeU5x2fp3xlm2YioYlQbROJbFmqKkAXKU0XPY9VFgPTCs7TsrtCVYAsvNsksdfXaUdazrjJyy//11Srx5tqwHKOVllFdYoltcF0jVlsUoVQ5M1euVy2NUrh++8fvciUfWPEZ98ogJ4/8clHngV4HF9gGYC0k3F8I6FJ6TiNZRqwciZwCJTQFZuxkqywKm93gpsB6MtB2krfg06NlKqmwQqapOZZxlWGGuIkBDXEREKQMidxyUTOFDRBEEVTxvc71alTP9d79jx3PVTCa37FGxXQV7zYrIoyNhYleXgAp7nvZ1xRZhkjI59yK60NcQhWUTXCaMUiznSNEV5RFqlCgQb+uo7wk1RdrvnrXGMHScyxN+zErU0uFyatQGa0YVjY0rMsYimVsDJJzlhNga5QQ8oR9SpekUXljK2nM8yH9YEDsGSK5Gsc8jXfftMAut6bIsj37wfa3t5Dx8aGqeM0ET0uuNvEHJAyFXOesplOCQkeWMTSMVDGkITfKCGMIBYNCdCQhjKMTBw2p3PhhBwTq4MWcaTSIW8gNeDS6/826bfKsQo8dVJ22QjXAeWCIB6zmau1dLDET1JsHBErAcsdxribMQFVlSJVpdxarVaNfZ/p30renB4e3nMx4/yT5xC8ZiTPdHBTA7rRJMwC3fc7yaxEd5xJki4rqm1uFWvCtV3qcJs4IIRHKLeV1vYsCJArmRnbSJCQ1AkkRimszQlEEvxnEUmwiA7higqtmKeUlKAZxW6kkQK069pGK9wp7EsWFcpiQhkyvqYgFgbZBajgLuXcUMxWsgxlERjOOWNGIJ0uHo4NZwwrx2IeLWXIWwdKI4W5wWrhybiMEagiMGoiiQsUWMiJFeqoFkOYE3Fr1SBog6DFtLc7+tQpBG5ClVCX12OlwPVp9POZBPRCE9nfD7Sn50mSz28iCHjPGyX26RYy4vkEQW9PTBG001KqeFrZjPLA0sRwF1weUmEh6GJCLW4UwxxtbRSjlFOUhsi1jNRdWHNWEk14YsqazvKevTDLO/nZ6KSeMVLhYggmIUxRonFBaGJsSalSMS4eQ6SjtQiRQloq0ewTWSuHird/QcLoKMStTSaKcgY5PiqVgunu7jQI2CefHL5IC9CY2+PTANsn8cx/cYC+ikm9mOjaT/78zwGee66H5PPIqYF8Gp3k1KlRsmkTwOnTLWQ9AIx4hZl5XAfO+OT0z6sXedKMQx153gFOT98StBjMTVq3rmBOnABAcJbL0+Qz+Pd/qSC9im/2W6KZq7np87afz8CNOgOfS+gb9ct8Pq5lzcD/B6kPVvCV/7fcAAAAAElFTkSuQmCC",cp="data:image/png;base64,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",ev="data:image/png;base64,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",tv=xe(37426),nv=xe(19150),iv=xe(55303),ay=xe(92691),pp=xe(99755),rv=xe(46016),ov="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAFgAAABYCAYAAABxlTA0AAAAAXNSR0IArs4c6QAAFR5JREFUeF7dXWtsHNd1PrO7s49ZLpcrLkmtxNeSej/s1pAdo4mRsrVjR4mbtIVS1HWNwEllw6mNtIXR9h+BokgNB4nhBEokOIoauYYjIzb8ku3EqRDH8Y/EDZpasinJevH9WGq55L5nd29x7p27M7M7szP7otguIYggZ+7c+8253/nOuedeCmDzc5S8L+6Xw/tEAPitGDv7kHBAtnlr05cdIb8MDUGwf0AOuvGh82Iifw0S048I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",Zp="data:image/png;base64,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rqSA/QrX3Ec+hUCcZ+O6rA4R3RUofbhvGDd8be4/iYAYLFP6XdxTHQ754evsdP+httvdn2dLpl26Yq63fsfbL9hvk5+v0J8fI9D7xqt22hIgL506UlvG1W3VSUIjrM4nPZgeVvV72ilRqNsV1a6SJQuVBwTXXfhMQA5t2KC4AV5Jwd06dJx9dhjZ9SdvMbr1ffdLXL0AT0jxvCwWrZEaWKKY6L5RG22qspr3GxN8qB2euQL0mI+1kxmiVLd4pjo6/UgNu+nQbAGAKIO4v3jFWikRs+Un1e3e/+bXv/4cYW4B+g7+qzPnj0jTp5sbotDHybVGwG9P6LimKh7AWjh2Krzw7VTPrSA/kENcpqX4b8UZ4mu1c1/bSybt96q91Hj6V+jBpBly9r3X8w2m+zt3P+m83O4LvcAfUfhDGDPnhGzD1z3t3WZISXE9P6ynb3ZRaLU3h0ffTtrL1aCTtfDSjm0nW7iKJ3vsAQrJrRER16vDQBVACAKAFu1L/oiOrL/7fZXT1DKFe1530o3nYft3H9/Tqif4fmBPUBvC2a3VcnaM+Lmc68G1ImZiiybj5GoeyBO9ZXT7Zal7rTwyg+4F6TAJlEqQ/ja0OVW9bGboC2Hlig1Lo6Jbmd8HXpJ6MXqVy76Yz3FZLqg+NiLye3e/6bjmD6Y7XHo7Typ26jjAH0zB/SazitXo62q1Ei15rRs++HmzZuO5qfzY6JF8+7MQVE+fDrvbxhBBZqIujL0h04HoFIBIDri9Mb++nWpzagLbnn9vBX2BEp/SQlxKcl1fru//8Hmq8f96ZmRUfboo5++owvP24DCuqZ37aLw6ac/4R2NhAPg1ETbzi9WkSj9Lo6JbneiYn3Ei6oH+i/IcKsyAHQBgCiV4pgoQKkU2F4vRaL0u9cTWCopS3R0/fwc1Rldf5vXLwOo5WU1Xf+T+Hbvf7N5mopVinuA3i6UdlfPPv0Jb/5oH9AEYgJ2v6uFpQQnx0NLlP5UHBOl3y8tJVjohun3+Hho4/iIV8J9EUS+LREoCaj9/opjoiNLnCG1A6LULvJtL86QqANsv6+i/XD/w31uVX/tvEClYnmAPx0X90R9rayk2GjkL9eo+y/miuioQvM4OJ8wpVLEPQ69O6RusxUBeuGYCl31YcvDJn3Qwx51Oqqf9iIxFQHk/yCGnI4qxTmiIzsbaj9c//XqfxyAAN26+FS8ag0aGM8gqLc5rXm1IUvQ3Fw7PX36M5tqUnbU/x2svO1P8h0cw666tvYT3tIrwS0gt0R8FwCIUimOx2GlmSLjxEkL3S5ArSJNBqeD+vgDAUCGScIxDLUlSq2LY6L0e/j8GvpzhIehb5MkQ6Kj6m/d3/CU3OqNGINANuWNha/0GC8NPMtcT12rzPed8tfuP+95/fyMNwK7tJIiUXd2pYzjja4l6mYvu5HgHqB3hdNtN7L297ylV54fCejxcYClJRIl+o+vf0x/c4CeKOGgnYK1Uxy/5yGh2odKYQSQECgJuMVohvDk6sQAREeV4fZFX/nnZOv+N/Q5zNEHxqNUJjuLX18nDTUaJHYAHD+qHaCLuSA69H67n7iSom0Elij9Lo6JOkDfmEjw9Jk9Dr1tdO6i4rlzZ/zp8PqthIJb9oishMjCdV+mZrMJ4/tOeMqeLMTmXYzojW+SphI90ZSdpT/r1uv1DQMwaul1CZsaO3EwRtwD9B19wvbcGX+ldGkkABt13640MyRKgyiOiSKLsNNj69xErUlsUHrAt3xfGQJvg244CDxL4CFK/RXHRLd3k1vy6HXdbP96Ej2Vyu7KNzqDL2m14tt2J8ND+6Xzvxi8/+2Nd32txvHjvT1A72bmdtBmPaBv7euQd7l2vtNDVq+H2GoD1PqWk1a7BWOTb/OXklI519vR/8n4VmjxiuPcIBdAACmkjjqA94+J5mXz9htvkyGAsQBEqdCLQy9L8XKtv/5q+wCgIky2dPPF7pqBnM7mxvZyONv3kFs/P4VIQtQBfmUFGo2Go8PzRb8XlI7vu+93NrdG7uDZ3cmq2+Qwd3IIu+vb2jN+88rNQjG87U6IO3NRG+LQmfVLJwOLY+W74qkVr03gg1BpFree7mDfcWpwIlQ2p4lbb3tyblGxnoke7gH6dqdx8/YE6NbMVWdqqxnftliGREe1Ks4RRd5gyKrrAF0xYJZ61ciLjpQ6mUJisJ4VVqJyL3xxTJR+0983O0+rJ7KhF6soRIXWCkt0ZH+ZQs8XVtK1RzD4W1/fMM576T59pdVhwCp2/f23ll7Vtcra3ND9j5qf4fkbnC83v0mpuwfoO4tnuHDhl4OToXAcugUtqEHN0a3KKECTBTDTLEjxnr4tehiSBTwLX6jh8+uv6oMPGWRAlEpxTHRU2W39AEPkLEm5fbFdgTJ0nAVzrTSXX9PVysY1wcYxrPceHPbvW1JHevfcc2ZV6bPVHL+Z5+9ekePCLwftyKx6V6ybxHYboFoFIEqlOK5WAXmNxUnAnRW7//xLJc/Kbj1MogOj+xt+QlkG4Pvku5mfKY6Jjio7rb9dRPgAXKdZyV5q9XBggdrtApTLoK68pCplzw7ev+t62Ntq2Ltq6PpVOdXFPUBv96nsrp4lQJvULeuqZc+2uxKJuufVPyaaA3rtIcZJxFnW4KUJaQtA93oAIjoSpGKicLBbNyjfEzaTComOxGv/HNXZzd0M95+BQh+EJer6I7cg8vwecg+SkiGDOK3jq03EDEulvqm9lx/fmLmsyw7QAyAeBegtBl31D3b2AL2bJ7uDNtb+ctCezQG9k8L4JEfm8d6A2bpkpG3DdIh8elv9eeCBBAlEc7zlx0TfyEKyPGNxWvcuNHuxt+FlUukV6QB9m6U6fbCDuCdy3OY0bt784sW/FE6GJEuQu+eQ++Zw08K1s1IB5BM8bUYiGpPW+WuQZSyUtrO8P5SlyVsFnazvUUoAzwMgSqU4JjqKoxbctYivGea4w+eHx3+L66HPkDGdeq0XmqWJCCBe71yi00UJNrWrrq2Fu+o23VOLYawo0Tly5Ldv5blyR5/zTjvf1Sdypxe5E/XtxTNhR98YDUDiSiRuFNypOO5KTFRNlKcmWLwsEcKce41baefsVIh8wvW3Fd6UVCg8YYm6F8ITFqVCovS7OOa9ywFPb0YmmEq0dyC1Xh6AUJwnSr+LvoiOuv5w/dX5RIaBr5JIv9SMkwEOTfeVSPQrK6kD9MD9u7ZD8zPs7r0B70p0cA/QdwLGa306QEd9QO+A4yTZfsF55NIVhGHujwwgbUfvC9vJeINEBwESyMRWZLEpjrcb9oy6xWuz/+RRzBbzZHkUVWOFBL+2qP2phRiPL6bjb18Rtpybprfg0DSOUeOJAbHsZ7HXudKMxgacT/qGSSPmM0uA3mHZEM8go/YeoHc4iTutfvWrvxKNHWjfQkQYdshf6515FZFKAvSa+1GcAHhBFMTeofq2om43DHY9IivXf/u7MVk4DHArVwoG1qJBr76og8lFLY4s2ql3LmYmukXui9Eyi8IEfakSL3htBdNBGTq/Nw+bKdhRkenrAxS2mvvWEmsffPTTt3QH36r9G3n+rhU5rl79lWhMpRs9cmj2Sp6FnkRHhwrjFZEthH6wPzJJkmtBkgRA+PUgMfuKPAGbPwPBLSiNQJRKcaw0YvfVUuPm//eDO32IBH3DoiaIyQVVPrZgKqeW0ujYaN1v/3qYGAbQSspwY8W9n0XpixweX0pGArqYG6LbKOVAtfDgHqC3MVW7r2Kv/krUDW4B6GEGNMCwUznmcRkKCMNV/9DAKrssa5HxDuQvyE4XcQNCdzj3z+/3ey+e2v2drbW0POxab2JB84NLduKBhYQ9mGvOV8enETFOSqXry5gW4V79NzQMwUuuJZY49OYRZBuHOlS/rPYA/Xo8z037IED3dPcWHPXWQVSpHvNKoiGSAY4WWGFX2rxkvCP1XG+xU6l5TcqtX/v77+JycR8AWdcLkaM4Lizu9PfB89ubLstEalhjyUbTC0nw4Lysnu54ECdjwdWlFAcA3Ren1MpcGgXWbAwCG77e5kFnJR+aexx6e89o17Ws/ZWod1XSUgjACAtMoaNUimOiQ4WpuoflSZ6kEsNVV9EElpOJKING3p/bDmhoW6DVvwEIwa1SGok6+KsYBHigZAzjM7/1YW2sl4M5B/BWcCZnVmMA1ju1bj01hlVX9PjDz/DqsQuAfPV+invrtl7LQgfoobLVfFFGKHJ26meGaoe11oEDv7Xerr718N6UGtuSod6UkW1x0evXP1GqK397Mu9AX0zUvXav4vl+X/4lbUfg2V5aLXWgPFbw2g2XVwosz9vgt7MlQygAFEONmtw8EdGg3zpfryz82/f2X4nVuR0F6HwTHgsObgwsum22ij+Y/H1AtMZavDXQGXCQiTdx+j/2at9bxKOsDl2nV9ORgN7hA237YXMP0DuctJ1Wt9c/UYo163PU7bfOdMVHvU+k/pq/cwDaJnKylIa1htYaOYFLMOefbDLgfvpqvbTw5KNCLxy2WesQM2m9v6Pc6oUJvdaoCK3cnj/IqCEjUwa8FvBgxfL6rOKVJYbWGGOAWYK+sYTxNe5Ppu9Ecgvn2/f+3NeGu+TpbBIFxPuHyyYxXSPGFXmVFdzj0NsH2W5q2utnSrFZ7EcNbtHDQAxeZid8jDjHjKP1tSUHuMAXtgfjUQ8nJzONwjAhEIFLVHzf5d/+QNj8rz+HRo3WqOxm8NtoQ9sgaq9xLovu+QZikDpGbknuoX/aMms16c/RpGmI3Wvxvf/D5wv31KJ7ld5IHIcejrENpQUyxBB1nxwPwUrr6ChAi2B5D9DbeGi3U2VHgB64UKYnfKa5Z73AUFxJ1zCvbctBEEzUVlRpAo1lAJw22rQHr/z6T/ntcx+7nXHedlvmzSeVtz4ByEEbkj4Y0j9r8+gWNKlEoS/ae3/xi7q3kvkemhzYAQi8nIDj7OvLzvgzQKepV/ad/lSRiey2b+lOdnDXytA3bvxauaZNn0NviNO+5ZxlquYpU/M7WImUVysJG/kKNIINfalFGRmokCUqWPkvE2NX/sGnrbW3yKZ0Jx/L+r6tP3FW8YPfAsFAk0jNOBogyUhwRK2NN36hffgTzxmWaA9V4smVXoktZzqbT4NRi8IdDj3yYBn37QF6h9O2s+r2xq+VQfccoONEYBQqS9T1QiZtOi5M28VxIrDl31dvi/3jNgM/4NpoY2TkdWNUgqUmqHLOLGgBY6/+yi+xeOYndzaqO1QbWTeJ3vYPc6WJAY5oaONR+mlBKSgd/5N4+qfm2qoSoic4GVNUmqVj/sUbFTaXrs7FLeZnY96boaBer7aM+87sceg79HhdtwToWGeU42fLQg9s3pT8FO6fMFitpNqyssh6nm12uW5mZaH1kpqoKBx3/SngcODFv/K3UDYf3bLzN6iCKr/ldw36/YiCXDViwCKHNDP73/GvWe2hTk95wkA1TL1aOZF+KDyTRHpp5RCeXx5MBLVVIqcN573xpT1A3+EHTYBOTDzpLrNFZhdppoJr8t6DiJYFNu3VheylyYoiLUYeZGKswfFSR9fy/gDgwIu/8I/BpDvJyHtH71iVTvwrw+pz7iKFHhBJWW7beOzxf5H5DPMIL2Mp8qvbq5bisBQihKFI49Z0+M2ba5lzdjbUTrW8NDX1d/rhPztr+0bXvmtlaAfoWLn8jGEgbZJ6SDSfwLVPZsqrfCa+n/akgLK8clOwptRQDwaDpawAY9lkuaMrE6S28zm3U+c/9vvWkoHkO6OY8NAfKm/fxcHRkBIPee0yP/IXPieVzzwvT1VGIbqZjW0ZluM5fGC8Y8b2lXHx5j7zcrHv0Y5uKqz4i7gH6B3N2Y4rz839UqWqfcdRN0vjct0+ONnL6vun7UuvToQrCYh9/rIOHaDXQla1zWStnOjGhAbjXvJDDtDgtnn7TijaP/SkDPa/NjgWMsVkpXu/WT7yzq9L4DgcwitwrmtNYublg5MreuLQMfHMuZpI1PaX0H32IPYAfccxYOfOVJLeQpFB95bXu5B+74NVv7s0xr41H1hupZ0MmGj42bpwKW0zNVHummjSGIbAORx58S/+++8oQIeHnpRius+h++ZFsNgd/+CXyuXqq+BtDNDl6fWeL6RzST2v3/fIPrz0yiS7vLXo4By3EnIYd/Paa6eLE/f9ztYh9Xf8qW99gbtX5Jg7UwFTAHo9j05TjUHALdEX1fecqsLizQnz4lJIuS/seKCiug9SY8kLnI5WZl1I9Xi5idGkJrM2EKAf/3ffSYCW4eHPZXy/22yZ1NDGAjLmqfaxv/wfJ1hvLsdzDmopFXqesEnnYhwI5QD95+n3PjJduv7qpL7SKuaGaA6RLRYh7XQR9wC99dt0OzWIQ4Nt7qM+0gQgCHM6XC4nJw/2oFG7t/z8K75OFAEaS5VAZrDK1KQ1tpeUKj0ccyIM+XNMP//T//aOAZqFwA//AmBwAPSNfw+2/a0tp0IGhz+fif2OQxe+Hdbft9CZ/pmvTPC5OfAZ0j0NFpZe7xKgb9jD9QV59OQx/uxzVd6VxVwRdfM3kLyMfg8nMgOhFnBij0Nv+ZBup8L8i79erZZiB+jNSsfU/avZAyd8lsT7xeXZqg/Qy8YG3eEBhLa9JCrHMDEFYCiUhB196S/+6zsC6OAg+O/8I2DVfBtiaxTIpz8MZuGLm95HFp34svL3XwKDFlAb0kTL6n0Xuo0P/vk+/8ZNqbyhfcoziPhce6azr76MRw+XWXv5RHju2lbzNep8UIb5PUDvZuZ20MbO/3oVTAHoIZEjU0j+GWk/tdYCTldutPYdCjwtq17cLmOSlQTm4obUGDPGM76/0e0FByxyrjni/S/81P9jrX1dF4UY3QPe93wJWOnEujvV818A+ac/tOndq+jEl2NxaIZUdoXWrl3/wW9C9cTVhmheN7opoyjUKPNFbcxCMd/xSp3Mr1cD2ZlgF65NlmMXFplmgoJrLdGRAO7PHc2hOy9K8zjxyT0Zegf43HFVB2gr3bZPaQoQBDkd+ckMAOY6+8s31fiUwqjElDTlMO0EgdDc+gEiE61EVEAENQbWZBmaky//5D9+PTk0lh8E/3u+BBge2nCveuFLIL/xwc05dHjkj5R/8JIxyJlgqA3HpSO/+F88HsYc4mXfGpORX4fOslT7UdeWy8woXQ3SlYPVF24GiTVFMtUN89WfO5rDkfNZ9udx/H9v7vghvQkN7t5F4fyvV9MkOTAawqPTz3aUx2/oE9OpGT+WaVr6UUoNZiOuVjyWaiWjMvNAa63h+Isf/1dbApoFwA78FCAvg775+wBZbvcYLlh7BPzv/gJgMFopkz39Y2Dm/mBbgHaVjAHjN1YW9//CMwJ1ZkHGiS3XUy1qEkyMipV9K1sHSldeHuczW2s1tgBeUI7m9gB9h99Ox6ETmwN6QzrmYZads6AbcHzMsH2NtuI1lVqboGVWas40ZBLBRxaWfWQq9I2856XH/+mmgGYB+O/6KrD6d7kh2GwBsj/9UbDNr6+7c2y8G/zvfhLQ2+h9So5w6vm/Bvrqp7ecLRUe/SPp779EXnbGIkvC+6/O13/sqjZWeTxtK4sCLPO4Z3sRs14Qogx1Z7liry9Wwm66+hlzIofGwOeWqJs+y22KGomOnE/B9gC95RO6zQr2wi/XIPL6HHqLzljAZtWxfRqDklJkiEmSkoh7FD/Yk6WwnYlSYsK6NMGEoTARZu07Lj3+DzaTodnBj4P/8D9bd2Erm5B944Ngm3/q/s4mPgDeO/4DYJ4kdX1dWgw++/NgZv/ltmYiCe55KhZHZyjqABjD+cpfeKETvWXZszIue8lcyaZJ2c+6IYslMJ93dLVqKKCFUvvZ5YU6m9m1DLwizdzYPf9HkQ19W+N9syrdvSLH4i/X0oRt6WuRZRpb+Mh0G1lln+0tBmKll9hysJq1i1AtYqN6Y7Ubqn5QWvC0NuLhyx//1GaA5kf/Gnhv+dRGoMoVB2oMD4P38L8C5Bu9T61OQX7zo1uKGYOd9/wH/qQjpq+R8wYHa66NffxPRFBJyyJbnghu9LUXDNeSOhprVJxl3v5xaWrVirgyM2mXR3rMbdyBYP1tBRnexD1A39l31C7+zVqWdg7SVXzLbYYaidLv4phoW01Wl+Sxo5F/beYwm1/pZvUo9epRvgVEXiSFdOiJ8mIWHWCMWR+sPfTSz/yzTUUO/wAE7zsP6G2MArOyBcBLgKzIvbQ2F1Z1QT7zY2AW/9OOJog4tBTTlxi3xohKp73vF76WGOAlkXbGRXOWxCcB/aBd0EjHvr7WBpuapnjLwY70KvfguZd9b2P2m8H5GjWfUCrdxLEzexx6R09sh5UJ0NAH9GZNX8seujdAlRzyXrsOoG3P1qME6pFHtrZ+sWDsii5X46yyv4jUPn7hZ/7JVotCHHsP+N/9OUCxvTBCS9z7T38Y7MqG8L8t7z4Lj31Z+gcvuxcwOHKtOfbfvEzOdgFmnbFwYdaFsQyVwMy3fZGqTAp+Gb/rbWPmlZcm/aWdZ0CKqjf2AL3lI7q9CvbV36hDlDoOvTHf/loG/QvZW09NRM3rleRi0/e4bcpKycBYKFwQbIHozLZNqdpJCdB5OXbhZ//frQBN9XDs+/ug3ny7F5vOQfaNHwTbfnZXN67CY1/OvOkr1Lhbfef5uPI9N8lHMAhkuypWZj1kWCTzLbLzVcxC2+ep0z2/kL7tbePezcv72c0dq9+akt1oHPvflnc18De40d0rQ7/6G/VMKKfUJaBmUiNRB/D+MdHr8qGjBi3bZ1+6UikxnQO6FkH/80z1RYhmJfVrsaruM1JThJM99vLPblsPjWPvzTUZIxZ/1L+NZyD7xgfAdl/a9eMlQKfe9FXqYGXqY/9Ve5MJBYMjpp2pUvu6TixbyxOS5wzx9Wzb46mSpupfVPe/5bD3yrmG39n51hKS3cA9QO/62W2roV36jTqkOaA3K005VrqWHj5RE+25feFr88qOhamqlIRltsgmKoS1zSyqdjRxaA2Mczj2wsf/0XY4dHFtHH9fDmq+futE030Fsq9/ACBx0sKui4zu/c+Zd/CKxbA3t+/nv84YGmMsi4RpTwZLs0qRU9X6MoYzK11WETPx0WOcG3MyeuHVXQ0g8maxscehdzV3221kL/6PDWBBDugNe/qs3wOlhftK15PJI8AFTODiQmjBJAiMwvEEF84EHmNjbEGWjjD0hUXN77/w0393p6ZvNv7+XE3X1zmb1rOQfeOHALIb272tW9ZLwnu/osJj1+Lw1Mxy7X1Oq0HRjz7GK/vKrcs2ppQeBhUYDCUY5TFsJyJomtr+ahAvTNlLN8qRy3GW7w0zuEfMxglcv48Xg1k88tsbEtnc9k3dgQ7uXpGDAM3FYTcnJGpIjY7eojTteLSc1iaaWXmfAC0nw+68UACpF1QyKEVKQbln/SpHI5m25sSFj/3OTgHtLh0cAr7/x8GqFTCz/4YsLq/LY5PRPU+l3olXl8Z/8lvGG5MaDbeWC0SrygEsM5vpiKkWil683PaqbVOZ8oXsTbCl2clys+mZbC29dTFXREfN3/B51Nf3AP26PMZbd+I4dNQH9PAD2MBx8n6kjrxFNVafs+P3JtKvMs/aGsduJFpzaBTrqOokOQ9zLeG6U16qAAAgAElEQVSeV3/hd3cictzh24WkfPoPFyd+/ovS3xdbxii7NDLOANF0K2x5KeWNekdGB3qJMpx5ftVrz0zaG1cqYafrQxGa1R8lhWpJjrAasjU0+g3zCdf2AH2Hn7C9/DfGgKkjO7lMrMfL87j/iLJBRaVJTxlgynolwxnojHbGZKFgRvoC1b2v/Pz/tSsOvZMB7aBue/xHPtWc/OlvOvnIIGbWcKnBl4ZZH3WsEUXAdRZy2wIuIg7cr3jN6w11cdYTIxI27uDagN41PPy3dxWPuJPLvB51716RgwDNs6PbnYQ5c/SAZNW60DJm1ihreu4TnBkuDPNFW0bjbekdUBKdNeS7Z3/uk99JgF6of+Qf3Rz72PlUW89oKygtB3JrAmbajSC5VuJZypiS3FhNicwkiMAw7hn0vX3i2mVPrexcu7E6ucHMHqC3i7Rd1rMrf2MMOsmxvPnmm5TM26PTmSlVyzh7g3MwxlYDpTMUIGhdCFpnmPFKdTmrHNQuMBbxwct/6e+AMd8xUd8z9b/4L26UP/KC8KziViuPMy2YMQHTrQnRvmY5RbwLQK2xyJJa4t1OjLVaR1X2TfHrr0Sw0Af1+vmSSlN+GkvUzWb/mKibXmZm8ODfW9jlo3pDm929HPrqr4yDti49AXjMAjm2E3VO+wbJLZRol01WWurAsZq4cblhFjqxrpfaWC6tS5urNWSsXGmn5WkKkKX42WMz//3/zHR31dDyhj6VERe7NvnX/m5c/54ZhmgYaLBAcjTF1pj2ZNi+prVkw5sahTDrzNUpOz7Z1aX6IfvnL3tkUNpkvnL2wKwEg0TdUHy8ugfoO4wAe/XMOJj2PaMuI6UEz/OA6Kx94J6AJck4zNygUKuurpYN1ktuX6r+PleJUiChWm2a4IAxBgUT9vCV3/yrIrv5ljt8G9vu/srxv/erRoytU5kYC8xjuj2BzetiwG1EkTpSUAr2GytCZ0pxX8yaB06N4ZVXKrzZ22rj0OHznSy7Ur3vd+a3Pdg3seJdy6FbL/zmRNVPRgN6QAiZMfc/NM6WrntqrlWKmO3osXKMfmlt0zaAQIJZ1F49ltUDzpeDARy4+VsfKcXPf+BNfDarlzYsWrx09Hf/lyLTMyUBM8CAc4sBk+0GLF7XlAC4/4I6TQ0AVOzcsmBSkWfhxezUqXGcu1b3FjaavrfamDENL+N9f3sP0HcSDHbmNycg7bngPElhreSrj3k8XXFMdBbucQvHSX1xxuNgOqZajlmtpHVel0pgwXR0WOtB5QDliyPjRCmbLR+89r/+TwiKUuO9qaXT+IF/Pj/x088M+8kZgxgw3a4Hi9e1ZlgkyeHALB3vx6VFArRknF+Rp95+kF84F0HSD1S79S1tmE8TXMKTvzU6HOdNnZmNF79rOTQBWvZ6Jx2AhbFSMSQ6fIsJlMKZ5MT94/7cTJTNrWRsoiRZaZ19mnNlmllU79qSCxgwiqIMrZ2a/6ffV+v8l596M5+Z5JOvXDn6tz5llEAm8o1Ci2OrBRMsbe8PV2a0Fizf7GitNPy5RZtJM2MevE8ILSezVy+vc8rqVx2ev2Iuibr5Zd7FPUDfYRTYl351UrLMAXqrsmgmxzp2Ytqz3ZUGj1tSiwgGhU5rbEtG9Z6pbIiAGWt/8b6x1md/gunulikTthrHTs4j42m39MiXZsf+uz+2GI7ckJPsKxzSToN1r/EBGVorAM61QdtNVszBwwyVHrPXrpbF1tx51Bgzzi5WTvz9mzsZ/5tV9+7l0Nd/dVJ1k/to4m61dXDBr6RGlvFGeV5O7LcYRELFvZIXt0mFp50vkjBdHdS6MpqmEKzhhyFszMu9Zw6H8voEV/OT3PQ29xXd5dM04Eklxhelf2ChF771eiKm3c5TJA8XcjH9Lo6VBfRRtvd7rWspGCRRAzh9rTyvq8vjiiOvis5iWS8uVnh313powcVruAfoXT7VbTazF355SiE6QG/cV3A9xItfqa5ES3Jsqm2rUwAWQ5Z0Sly2BaRpApVqM6McA0P5WlyKcVqC5UuxUaU4R3RUGW4/XH+r88N9ru5yyBADkO3xYOGqMR5PjYg6Kmwo60e+UPGEWLwS6pVOxdNycK/wbU7xarVuql6rnP7U7XtY7fTCu6h/93JoArTRD2znnp2rKBok2tKVasdONBT4QddAxVjPY2hoxxxUVtRo0ynGGO05DApsf37I4EBGhr4zz5YXLeoWzlLr2zPg1oBGotRVcUyUfm88P7yNJ0GaW221ANBZJGw7kaLMGMX3Jkno6U7E0rRh5+cEy9Tg/W/9+o9gD4F5Fe/ZA/SWj/12KrSf/cV9YYg5oHew8Wtb1yq0KDSGM8OQG+sLSo3XUf5YRwWTxIQ5GsMESK6t8Rko8j1evytsMfK1zTU3vZetdt68RePii5BzdECLhknNuQLwlEJB7v0e10mNJzcjoWMElQVgJCXuYNbYGiwuCXTM+bZKhvqV8qlPz95WJ29Q47uXQ7/ya/tU1n4wn6etpOi1821Vq6QmqHDPN0WGaMo42oWg0ZTVg9Zapi2SIZlbcmuzlFUcLTC0gnapt8wwZgwnfzcOhmrQppmMceu2g3XJFCmF1iDYh7dCZmAM7VSViyjEmeky9FMpWuppRj1qbblGZMYK2sWNgWFA+wVxrrUwTAthjMey1pTfmbFWWQ58nUxUhZt9QG81P5ujTYC9gHuAvrOvpCVAy+5DO71KT9UqMZQqlqEtRGLO0PRMUGuaaBotkkUZrXViM2hrGRiO0mpODkEEb2uAGQTa5jXfWg2wry4kQse0tMz7JzFgjZ/n9R14HZJtvkXbqmiT82IaG+1JiIz86ig9o7Ee0v61ThyyaKlPbSkNaYhZezzozGhJ29GtLw224PTQO52j4foZ8gvlB//P67fbzxvR/q7l0J0//+v7A5GOBjQZTdxuVrnxZFAiiW29rHilbCj9UB9sWlsbY1DrZJU8z8eQiGCURUZbqmmLYAzS9mpWW9pazf2HVqNh9DeHR3K2AGK5Fjnt/Lo2x4aWosTPdc71+3nLSdtClyUen48p75W6pDMkeqBL0VB8AUjSd/u7gWBZe5K3rlGDAjCUWoleilJ2czkQanVBuBpyxplV2qCgORqeoBEfPIHiZdwD9J19H+2f//X9iqUuJ23hu0B0VKEHVzzANtQqmalUKWU4J0ckUoNpZWNbra1Iz0WRE1DcdsQDm2wTZ1zltP1zVCcv/V2pCOwD7RG5+22MIjHEUQdcTsk11vrP+14TUWjTT4d42qK5X+hPq0oUA3TsdnbzuG5PwNIM5wIpJ99gidTcki+UHLx/dx5XU6bnL3zf96OYP/IDKf5G56WEl0oP/9+7SsV7Z1Gwsfe7lkPbc790QCmdJ1neQelgtRLrasVpc/scihZQsSrVViCazlVv62Xe1V8EYOKK9BIQRyQJABhI4pVODqA/kRtcLg87Vt8XS4ohksyd6ygcl3VSOlq3kb11e4zT1sdOKHGbfLvrrY2okLlzNSJ9F0KbtSdEe0YTSIdKxc4tBaCL7AarZ7daQw9L3NLii3uA3gHIdlOVAJ1q6bzhhg0Pw/0VhgiiHahVtKlUNG1guYoyYzsqrLVNOefQqzIxQZtEWQGKUa5ozoxlnHglffBpf2JS95H/tOtqI6Y23NoA883lbwdcuiZJF5Zy3ljBSXSnhac1OaX3xxi6YPFNIGiTFB0I3Zrgy9c0qWwGr8bQVmB+yQflNlkp5mg78zU8aGnti6W3/8OZ3TynN7rNXcuhu09/YpoL9Vb3gCwjKRaJugkcYjHkiEQ7xBJ1gIZyLkP3gUvgjk1EgaXTjrtSwkYkJsq5BhQUW2itYARj6p44MQnMlKaZdGmWNixGZkCrfBtukhY0APJcHl6n8FhdFNL1GSUkI5mblnqoweYvCpDihPb0JlmcNm+jbQWcfK3QKo1GU9SYonvwMGtPYWvGIPHy/gK0z9IrYmHRRy0H73/UfBVzR3TUecHgBdwD9J19N+35T0ynsX2bu8oQiyYGp4HTdu8O4LSY4xwt0S7WKpktV0kN52zIBDAmTc9UG8u6fASAQrK4sEg6amRIsEdtrCFdhyF9miamysFqcoVySgqV801kpADpL9xo0VeoUQijffHBVaT8zk5koc3n6SXpixLUgdN4kATNGKnsLDJuOHLUSHpzx85pucu41SiVjpCSNbYuu/RRoi/DW2up/xrML/io5OD953e8lRpv/flA2HN7gL6zeIbun/3lg9xiDugdlAQbla6Nqo6bWWUJvIqXyl1bnmxnfNKByAXskbVQK7RacbCKWcqdT3yyL2KT5mFAJTc4hEKdt9mw6CqjzOxrbRmQNsWQiG0svVhMAfMMQ0EKCvcCIdqA6bjBs5ueTVoe9HpOBidlHwMom8VFEjl2MD0jqxo/OFd666dc1qbv9HL3ihwEaIC373SCu1itZKZUIbaeca8iWaWhUUSpZmE3sxUSHRBkxsFIkWv8co2E47hvYnHCdp69wAA5krJAA/d8brOaDx3GjeQq6QYqWeLQzej+amJpgeduHLdVjBHnSo9+2uXV+04vdy2g7Z/95YMpmofdBG+1bCeJ2CkhLCZYrfSgXEtZdSzDcMxycrxkIKX1Oyn4PlMxcWa321TfVEGTRIs/J6Hnlo6+LN3XMZPimZGsXDQoxIhc/CAxgowvhQEFi76dgWSjwxMKtEzT9XPjI4nlrp9+VcwlGC4ZD7gQrCxs7ORtkrNRJ17WXvBtt9PgKzmgB+5/JCD7c+PmiMqQRGK0//weoO/wq9z76s8fYpw/QpfRoIEDd5RKcUw0/wOt22iHWGO7plpZEgfuURhN2NxGjdwwiLX1pDQUI0u+EECs0Ir8AaPKDRW5vOtM1eRWAdaB2Lh0YtqS4qzvjEQ6Y+LoRIfxSvK0wzYZZkgGd2JzLsuQqOD02KTN4OheElf6L0qhv3ODMLSgZIJ7PAhAUnNaFJCoJABSoeZn96mblzlqPXj/br4G1hRbzZd7kVLxfPR9/+j2kvPdYTwU3d+9HPpbv3iolyVug5NhtV2mFQKLuGGWox8Io0MvsSi48Fhmo3rLVo+6mBS3ICTcok2lAplpA2QEIZY2IGLkRg1CE2kfSBvhPOWcRZB+O+aItMlJ7mVPqr5igomz04qSkR3b0dxCQos7JP8Px/RJS9c3oTuTNynrSNfsbCuW1HWD46HXltTXOh8XK5c9Mooi7VTozPZgwAfTLcH8qwKU9NBoa7RiqJSfKWVRa26VKcwwW6k9reDPRd+1B+g7+k72vvZXDnPQ79AghOS+Z7jnGfA8QonTIOTJDI1TRlhpPLAK0Ogmm5ju2drR3Ae5b4kjy6CySOl3CZikoiOeTP4clnESWpE0DM7Pw4HVLSlp78scuAV813lTFD8G1HaFSOI+6cYt+pzIUUi5uUhjOe05kadIchIOyRrk22FJvjdkf3efEIvaGM9jxuPUz5r4Qq3o3sblzecCkaSGCa7pRjgN3HcDM8TNSeuttSGBy7Mq4zpV5BI1/OCswueid/0Tty3zd3q5azj0E088wU+850Qw226XfF6OjiXPHB3LLr+VPs9gjRaG5F4yL2SKodFOjeWR27EmNmp8BJNZzZr8yNE2a9xL2jhKBE2qudxFCJnUgHGqaNG1aiMh4cE668naVJHCgzQcjqs6nk3rtdx65wzWhXPSLZaRuXElB7xzVOp3vXatwbfEyeA0gL5F0Qnlzr8j4GhpNyun+wZN7xo5MpE2kV4CfUBffTowKx2SrJ3S3NCHhYPU3NOQx1UKlmWUDEEx5jlrPFlPlTaCqUzoNAOdSWHNM3uAvs1X+ckLTwbR5HQEC2kFQhNq5KR6NaBQeZUgO3bjy5O13iunSWrULKparbIKNFucVMHEeFgoJHq+smEkuV/SGISWcV9ar5JAab+TigecIwguxtKztCi1AVIyEzKck1DfVkKmardpD6V4IebeBzNhiZKkF74dufcdiRd9B36nBnT99y2KuVyMRjtRppBpnYefk3Gd60fxWtDrll+JLu489SyGPrmxInLy9aNru1CywpKIiEYlESazAtPEKik90D0uu7Fnk1RiGCjwPF83u8A9TKBMG46qSHe6lIRKmsAnLxFSadI+ny1x+IUrlXdc8qKoF8/N95ovNZPHH398ZJzjbT72227+HcOhCcAsbJStwlrFY76SmmmmM4OYsK6XctZDXS7ZmPFYpW3/oYXnTzfUhYfKcnHF+LWwp0VVCC4BGNec+xrCQCMGBnlgme9TkiHDkdyAiHthBqJiyaM5Vz4Q4PoqXJJf6T/yJVKWzNFGEdIcX81dQglAJMGg17cE9n0uHMpzsG7qDz1gaCFrn6vb/xs5RDmZPXckze2GTtQBdBIKYV0w93UhQSg3eJN8Lml565g5B5NwNDExdVoOcMaUMVJ6CCmDLLUqUwJsxnUcuzdWaeObVodAnPBKVUsDVd5appQ7BO4kajx3Yf9PzkBXhSbQATEXZqTmJuhBr9t5/6n39+gVum00vg4dvGmAprXO5175eoVjWvdYqaSZYlpZWfFNT2rZ81JPy6DMM93zGQZph3GsmE4ta2bYDdjiI/Irx2rp8veTasGQ3GwZRU6BBuLKfghchBq9gPwdBJjMs1lb2F7HGkOZ3PwEKwc08+qaYlNIhnCGP+aUDS45vns8zt+N7G7O+87JnkXsym1ppQmehNRBLcZQ9EthPySNIDkokYzklqUO4049kjtdOxM+kkWRwCvQZp6J5yLoLDJELa2IFIuqGkXJAhcIWgmrY2azhFudWqW08C0piAx56wmmMz9tdRzn5uUafapWNP/a+cpHLosSCD/J4nJQZknF83WSlBAh1JKzUsPLuu20Ewndfuyex3YdkHu7mH5DAX3WnhX6RV2HUr0OWRxyI4wSuoeB381iK/eVhVqcX0QxXm0krVSjD4IjQ901dula3KqeqFlj5URV8NJ07/z0VPLSQ7R6J/2FNFFZe35ZoYisAUo/EXs6bvsmbnKTxIYJEUO5ZoQXMW2MANkjCPWgNCmVqFuGwgmmzneCOHDua5Tjur/w60cA9klfIzeCMfWxuepdOtDegXHkIrLP2/suq7nn0nqf/dVlZn9s5HEN5DXNnMNJ4rN40Ye0hUx4ErxIIBim445nOh2ax4SXKxLCuuZhhdL/Ca5TobIeGtn1DHFrZqzhvhHAaE3CQcZCd+JF7/grF8LHZpuxkRHrtMYqY3yumfjekUbsMw91O+Y+h8hjWDJWB9pwg0p3VdJe+dDbP+Qi19+ocscBffbsWaEP6DqvlMZsYgLQQO7ynTjVvTJXMvYPy+jkjOaX+dRykmBgQiszyQy3CqTh0IvbuhpGUVAeYwK9EFUqMWjds/TZfaWs+V7Jo7phUUkDL5GkyW3WikxnieukK6zKUDDegdqEZqUagpHcdJtc9mJPgJHOD4302GHUxdKE5lFdGx4RHyT9Wn99tx7PhDNOzkfk7ZHrqVcjUAql88aIq00lEFd9QMc83P86MJD4QQZ7TisK8sSTvTKmC55qrQTMZE7B4VJIc5byck2zoEYCVGh6S4FaXjHM48qKQHm1WgKlCcN4iQNKa9Keb9OOr9tNpqU0fuRLI0q0iugGB565WXr3n8lZKc3JYKLb1BxVppVtdaeiKT0fSy5XQMHJQB/sGkHcGzNVYYgRZClJRJ1qubr06MFHd76l3A7fhDsG6CcvPFnzbXVSM1UiEAswbSPqHdNZVE3RlB899VH19Ytfn1pJMpbqzAiJoeAq7ngRF0vLnXTsZDohmlOK2zF6dBptu9c27SP7q1k7bdcmOy+/o9q58m7iyuR84dl4MdCtBSHTxNo0C9GaJmtMZl5jkrZzZSpeKunlxcDKLEXuCZtJMEY7fyJkqKznxxCGhkWVFIN6ZkUFUAS2v7JzZpKcaVpGC8Y1c8eQ97QzJvaB7uJIXGxUUZ80JoXdchOBo8+unX81OSu5EFkSfyi3tYc6ZiZrh9BrBZB0hE0yppUiDQZpbehrxBlnCpTSGJVSVt+fYlAJTNaO9PINX7faBrmXYugbUar0WG0/8LAKRmUIqhuaXsvXK0vMkl7EF/PRva++NvHeBZQqNb632LoK8Ynji9hMxqdUN/fMarbjLkAtjvxFrExU3N+81POSSuLLNq+WojBK0sRyL1peiq8sP3768ddnr44hwL+ugCaRAi7BpGZ8nGUMrUw7ftlv1YJaJmdk9uijj0oCeiNsiFYLIGZprYwyM53QLqllI6qp2wuvwRuT2g8nQyky7fWWwyzsXdfXU6gd5mOxPG4tHhxLX7t3PLn8Nm7SpYpemuVZr8dQZuSszwXDFZw4IEV9n2XcE2lztgqL80zJTIlS5KlMaiO1VzgXUeQKqfdcLJQQEqwwPPSk9KME/IrifmSBR8oy3zAmnBmQNBf9ybSckdHQ6dZyEYV0L9xR97uQl53DKOlgnBWFrDqry0dCIvmiFn06nxJanhqjfKZTBBn7OusFKLsAaRLSitVm0r2Qww+VIUttFAieOseqVPthHE0d1EZ4ApJeJVu4wQz5q1DmYM5NEAWxLTcSf+wQMM/nWdpjQveibGW+JJeXm2L8uRcP/bfXlBE1JdNGAGEq0+pMdbzrrt2TrBZwWV7odQzXFaPnVesnHnvMpfI9Yy1736Wn/FjFfh3rYQZYy7I0FJ6JU0jnP3zfh3e9B/ko5v26APrsxbOhsWa/Ba/OMnqLzUqms5hSE3/4vg+ntAB86tJTtW5bYMCSqo38IOkkSmplogyXX5mA9N3NfWZ5DEqQdY9yo40Mgnk/zXrzp+bjx/Fxffbi2UYm7QMW9KRAETWSK9OHWt+Myqa9YE038Ujt1jd999jEZNtrHGbgeRxUr5Fcf0Vg6pIUZqxURtXtEZiL+rTHuzM09E3lxXFiNaeVP+1KpMgnGiNfIfe1ZYFBz9cWfTLQ0a6A5I5NSjharDnfZkvxrAU8B3g0QYDkFdrj2GoyzxjubOhKcQSF1kphZcbRpKhl5nGdMh0rWuCRZsHnRrkYl4FcSsV4B+8ntSKgEDNh8vtWNgiAcUarP2bi1ENmButLBlxjrdTzJo+kzBvnhrQkWvqmvejJ3mcn3/cPXyBNlMf2hSprj3EODWtYs/nAzStwHviJsRNi9vosTOyfsP5NXxHzGgbcE/YJfnjmsN/NfN+33Zr0sGpTa4U184898BhteXFbS+3B5ckOJZW8+levfjWKk/igNFgpo9fuyu4KKkybb2smDoRnz4pqtYpRFOFieXEibseipwwvRSXMOq12nE10YWYmI53m51743HG0/njgsbmW9prpc9d7ha7z81c/P45t7y3IsMFJo2FMdLD1zI0jybeOeKClNqSacnoK1IzzlnfoXoVelYRbD2S70bv2Mmf0aeSQYhBpRil0k2TV1cNSmKsLac39p/vHROm3g14R4mTok84ZfYwpypSg6WIFuEClkVMwABkVyfSSx3BTAhtauZFOmlRr5HgEhvBMLqlk5Wa+0eTJSvoUxmhJpVyyG5CZ06nTl2NwDMW9EnXjHbh/92AMspiVSxF2e5ySnQ05B2y8v7X7l1iKlsKpEwZLdbRpxhF1m9e+cq50z+cLMeHcuXP+Rb1U9oIeMbHAsOTiTjkt9XHZvxwyWSlHwjY0aiYxmP/Qye+jtL27BvauODS9qb71DzHLqjzgrXarvdLrjCePv/vdpK5ZHQxxVeazaqepGLfSkxnDUOPccracnU/PyzOPnVH01o5dGLvfKMGtTa9PxpPtwbf77NmzFTWlHgbBJ9yz0qbC0L768OJ/WIrS+XcOv4kKgqBdPnh/pplPmOAAKkwXL5X0cpMeLAHQisB3zvtWS49k6depOKDQNQonpv5vRsoDQ7pj4/RjoDn4wjq7JqnKCmDeahhFcAJRB+Ah56KiHd2bIpHBQ7RSqZBJJ6dSql1Om6+Qg9Y2CollK8HhtxoysyMzzdLRF+dLJ/74A/d94KUBfTP+wfWno0q3PW6V3S8zefVDb//QjlPuOjH1PIQ60mVPeeMJM2REuPHYA4/taguMbd3gwBzg2WfPHrJVO4EGu91ed7G8WI4fe2xN70hM5usXvzwVa+71ZI8iLQQBOUhhaa49l4bNcNXKRHU/+8IfnQoE05GJZt7z4Hs6gy8EyV/f8/yX38I9dhyk4oZRjBBWfMG/8L3Xf6+ijf7+4edDMvCyf/h+gywszjHQcaRWbgRmZcVxYUP7YqOgjQ0lcVLUxjNGWS51waXX9Xu7QXlbgeg2+neLQC4ExbDTEpSB0cwoRfbHW152G9dbDg6fzHg0xbROF8N7LyxUTryGIvqzD538vnWg/b2nf8873jg+xhN+LAuySx++78O7SoxOjG3q/FQEJaiAhklttQl19+p7Hvzx9lbTN3h+24CmxZynvGMBRcsbPheUgu67j7yb5OTVQiJGfDjmHHk9yixvZh6TqGRJWNWCVmd4Zfull790wmpbNmPmtQ8d+BCpdNZ9ar524claW3nvMhYjcg51HNpgdEPb//hzS//S66rOj20AtLEYB/v2dXjlUJGfwokN2mTCxs2S6S4J2+mR91EuKlCeL8bBCiaRJAHnlWRyvxDiabe5JdpOnsZWdZE53xPDyJAkGEV9OwdZElsIyERpvE6Lfnul5e0/3PPqx7hVvfnooWdb0ZEVMPLaD5z+oWeGrYLkZxM8FEyGLDwOCp6/Hd0zAbvy9UrZq3gN4Ytx8GBl/k/nr27X1L4tQH/5/JePCc+MJ4lZ8Jm//Nhn/nMPzpzZsLr+40t/PI069TqZYr41tisF00u95Weh0Tnz2GOEyDVx5NzZSgbZ6TIvnx/mzMWj+Oz5zx4LFD6SO5xzcqKw2pp6ibEv/qcnvnbzV9/13E9ahArlEBhMHKNQeB0+MS15ecI51ReO8bSwIq8ym3Z922v5JunRAoxAop1TsvNRQsYRleac8n3lbxGAcIEihhyhKF5Qry4AACAASURBVBS3DxqyT5JCbz2AirHkZu08e9Lg+Ea9hO5vZERy8nCufmMokILE3EvXTyzjbD/aWM+5fzvHLEqF4Kx8nlh1oN4RmkeNd14cOQVeUEWA+LXK933VeEJrzbt+xf/KKEvg2bNnRDb9riMqU5UfeduP/PmOBjCi8tNPP+3d8G9UyoG3n1IMhlC9+J4H37Mlt94U0E+ce8Ifh8pJTkp6a69Pxpfbjz76VzfInF989Yv1MR6UukkcKi6YbEmUkhTL4Zxoi+5jjz22IQzoPz37uQcygbp1rnXxVm/fl7712fu1L06ByrkzARoVi4zVy+Fy+T+/I/nUMcb1u0Y9kEx7QebXxxJRnlQGA/J5zsMBXQg3aZJpe7TMQ91DlSQBZj1m0ozRIoo4IYFxNddFzhlJRs7DV7mLWll1zidNdt/FuXg2ubEkl53FGp7JT49esA311z1TNzy3nRrpPwyjjTOLvzmrN/kiAXj9r8dWL9BOz6e81ljx9j/EUaU9f/LqtfLDL7v3DTCLW9lXfvw9o8WAJ65+NRpfbj4cZ+rZjzz6kdfDiIJfePYLJWAwLridkgCzP3TqhzZNGnlLQH/h2S+UmdD3i4C1PZXefM+DP75Ovh18AM6Iwv0IumTlLEO3OwcmiNLGSqMzCszU9vPf+vw7ueIvffDRD5IecuQn8nPf/Nxxxu3DayqqPDLFMBsZbWektM+8d+EfvxcRXD6NDZyPdMrMLyW8NpbZoE5+PWQY6ftf5pihkFLQGslfmpzhjUrB6swHmSLKjPYFh1QbEAQuyqgETl9MrsWrpdDK8bVFVxGmRYKLE3mKROXE5d11B2IUCay5UjgvedIN9zeX48iFo9A+yOTRcYv0ULfLEvvtY15tdMTEveT8ZC12X2t899c1RrQnAIV49bx69Me38tUgcaH6fPV0meP8e7cA3k6GS9y6V3+toW3jEDO2+b4HP3TxVu1HAvrsubMVy7IHrFULiyvducff/fg6WbnojLQdVebtN9JwySTq2Ng0ScCgr26ywzf+6ghdZNH2S8/9wbuWxia+9fiQHD440C8+/cW68eN3AyCZzPNnzSlWw31kAzC4WLGzL5+68YePcASnBdkAauK2yD2JQZRhqSZJnYfCzxNrDQa+Uv44+u3SFxnKeoDGaKC0BRT9DVpx8huxljzVCPxaGEonQF97ZUmvq5my1MRFB9wiIrwYH3FNx+VBIAHXyfOWM4Uu9oqTidoCCgNckFORtMyjb4MHmTNP+zYd+Ux2ApTBuoTYNJjcn0Bt2nDnepjcKL31zzpi0n3maTWOHlz72qkfffrMLTzrSJauPxjdZ7RIfviRH359AwLOnGFnf/ztNR2FRyExyQce/hH31RguGwD91a8+EaXV8ukM5M0my27eykTZN5b4pUSXlae5zixf6iTCEx5bvrG8/PEPf5wm4paLky+f+4N3xkutCz/6/T9LFqWR9WiCaqeit1ilTzCXrLBfyAhnLUewntIoA5lcf2T58we5XBgfCSTifqQi4UyQH7BiXimDoGIwiMi2a51jZhHk6mzNbkC5Oo24Y9/5mSgZoHO/aArqIyWgS91MOmXnXkoWcqus0zujzkWHtRjZfigXNSVP+ty90+mtgZPWm5LFIMk8zEXGcNrZKt9njn67eC7QnNuMq14nBNniptsjMYmMKMO57Qbna92eFutQwDAWjbFYVPZr65XJeVWD6M5WHni2JyZymZXiiKVUSgdP/8g7f+SWmfxJjo7HHnlr5InZx07fut5uXzqSep688GTVT/A4Z1nvsdM//sqmgCYtBZ9OTmkLrWp36tooa0/Rwdlv/vuGX6/VkyQBYs6pjDWmqLMgMfFrovX445vb6v/om//mPssD3nwxvrDZCvb3/+T3q+Uqf1haPUXXRovEAlPU0LOcdci/KZFG+R6vHVx57uh+9doRXy1nZH1zThfUhtb+ZP7of/5JO2BMIKzHeGa80HA/VOhFFrlvgFEYF4nH7mXPrXJ5KQ4oA4zh2iXoyh841eoHvzp2tt47qXDuz+lallDG0GVOcqGDzlCZ+1OvBR70r9t3hDIkkLvgKnrpKL+vin3dWymZ3hJQHEpfDCru9Vb3T39XtMYIK/WElScs8yKXDgqtjVlj5lLpoZe4CN3KhYLijZSU8ObFqFl/+VYiJI30q1efiLqL4TvEcvXpQVXubQB4JBN+8mtPVis1dlJyefMHHvjIuiSS6zj02Wd+/ySrcq+L7DUyWW8yEDx78WwAKyuhDi0HxYXxIi4XpWeyZveZ939s6VafpaJPsjJ2Fua/qwvm3E888hO0GeStuDl+6YV/N6669phgUZJC3C0ZvxsrnmmhVfxarCqPVDCdSaPSJFa9bnffgd5zp2vpwqHA9sg3uEcqOM5JM5urO4pjRx2D5GSC4aQOsySeAA/IZ5qSe2rLKThAME42PMMo5YtzaCsCX3OtWT+KL+/fgU7nK79RxQXI8oFMdQO+HvRAnAjdjxLM4wqAMjUppA3nrJLM6ozc3bhSJOOn1vQyj+J5RtwfXZ/+TvcqDYiUlyvGqzSkFRXLhF9cLPUqNxdL97zc8SZpreSKQYPMknSmLnmNxoub+TmT/Dz5bPig1sp88B0/+eJ2rX3UjqzKOwQ9fv7cE2M+lO/zuTo/qKteBTRpKkSvd59K0wsffPTxWy7U6MK0YJyqqslmmiFTxJ1RxxloJroaoNr7yKMfIfluK10onn32yUMZZIcAWs9/6O0/f0u/WTKw/Ogzfxi2286LSz02pAIsJuPpp3/PS5IDYauUhr40Ywd7L54qycV7fdOtM53GgSHf3zQj7QFxs77r0Pq5dLoLziRSVkaP0m8x8uNAJrhybse0VYsn3M4VKLiLesmz0JCUkCdv7Afp5okeaX1H+Qmcx5xjwRRM5lLskkOzk0ddvgNSgGhmjNaoDMnnyJSkzE2CkudZpQo9s6VFC1LgpKJkeKv3sm6hmudTZwr9UHlROcOwqtEr2TzMBjnSRqWQdsTY9Xbp2OUe1gZkcqfFoTyr/3973x4b13Xe+Z3Hfc3M5XBIDkWGeti0JcWULb8oWZYlS2wTO/Y6zSYLa7eLYFM32appGgP7R7F/lv8uFigW2XVTB+h2GyTZBV2g29prw3YQSY0t2xJpVVJEO5EtWxYtSqQ4nOE87uO8Vt8lqVDUDElRlC25voAggjz33HPP/Z3vfOd7/L5YifCU4t6HC1kt8Ps8eOz5dSB0eymOjzU6c80HLYL5C+81fZESko3DSBglgxh4NQxMDSTUzrnnwr11rGrYD6qjuR63ixPW0rfpXx2dxdslQB849n/vAgJFfSE7utC2gp2hahK3xE6riE28KjDRe1UzPp7W+XxeHzhwQPfXsVHXW4HoZbrNtK1RxOQp6HcXW0hLXcX9Fw8Qu3btsgMvsBVXdmt8ti0bfrTREVPrbFNt4xgVr6LQMjLECD0ulZhLz5kc1tDxMqN2JHbkaW5F0MhgkPye466fEJ4nMRuIWOSDxnzs5FA1Q/k4o+YkkhCNlwTd39N542i9QJMeAh21FI4Uo5iLmIh8VEOm7d5op8Mowtn3n9WXZ/mtp/XjpOiRpYjlRmClNLNTGrijKbEVUlUmZwFiBHPLMc9cmGL5c2W3q4BRJ3PnNUlcTMQ6KUht3odWDyPiGu7WCKzm9bTbKN5iM/Prvnu/nkTZLeXC7/TYd3bklAncqMItENIVSrpGEYcYxWOA0Se2/JtTjfrat+9vXJJvuksycupLd3wDg5umcydQ4to0vCPW7jvX4uVZykvMb/Piiz9wnI6uDqlNB2h+9o0tX/t4MXXlKp9DBk4MWPkxsKHZ4lNR4NxSHeki5sJaX0eriInabC2RL9rgds5AxiCVtEDESbx0krI6yxc3kzOYcMfN/K6O40RolZj1VFLyBFcB5uMmtuXEyYOnWXyH2QPsfDvx/PebdcwkagAwJgmzCLO5INRV1HIQuECYbQy1VJI3Ow1KY6gQ3C0l/2jz5JTTPhFSL8aaG5fz6zJMoEwywqk2ZSD0jJKps15wqNbX19+QSuz5wedTjg42YOw1ZfRU38Kq4xWfDRfD6ru99ZSbtjCAyCBrFeXVoCJCB2wxXg7CPX17LqlA8zvAnWHn0Rc6iRZtv3PfN1BKTwP6l7/6x7VEGc8VXacWOgheJZCW3BxVhYkonzNOvJpqisn2H6yUtK43CT3Dz/HsSGjRVpdHdoqqqfNel/q41YvCdqbjVkp1jsrQ56A9osIURS0BZfOsKU9rxSjSJqAugaY9ZFOc8R6qae9hwnIw46FMGErnXHgQTHJikwMieicNkejFTlJ20WSHgVqGG7C4STKvCdeEo9kOTT3coFkvObgij4gVaeIEkrJQMq8mmVutQaoa2Jmy4s3hbBUABPEVxDJo506OzgS3iikl4BzVcE7nM9XFpLK/Rq3htt0htZo0Kh59fNs3rzquGS1lrx3/f9l0s/KqRelK7qRIFHkxgK0iLHEnp8of8RMLGQ0GDg547Rl+TyZeO4jYTQCN6oZm1vh4T3V8GQr6koG7UEPcfrZ+5faMzbw2JeM8c1jZrZXP7Njx7YYOnRV58MVOpnX0IXYqPsUdXeZaUGa15omZmGIWUxYxoZsVRd8hUYaDyABEaWKMw8A4WgiHaGVxBtxgEe5k80duBfQBJSoyNdpCRyVPSGpQXUkscehaTGTKtCo+Tb6BSwMZwQwBS4kkgIVLBUxqyqU2REiWigy3oog4cQSe4Mghg/zYSTw3xVRhg+a7S6rDvElK/Df4kMTTbiIDrGAzPUaZMxFknODx9Y9jhF5DM2rrBugQQnQxcERs9Ggqny8uMymWDL4/0CSEc6chWmjJqoSICggSBCGaJi0SR5P0jVdPXVhIhUX1lzQX7jVAT6K6kwD6F8cG7ifKev/APxydWqr+u1JgqqeCeJ1rPBVH7ZLSZqNkaBH349de+sZkf38dZsPrNZCZfpOMi/37aRAcZ5XmDppNhzQsZ2kURDTfZpEomKAATVCrBaTJ9yGohUTYkmLt5JBxwoOIgJ3aQLnqIgTjL7AQwHQIacJhp9GSMA3I2SsBZaKsTBO4o5RlSMCgFPpeZtQVYzCebhq488Pn5k5KwtyRRGgbaZDYOgYBU5ozpNqdqMqg1uXeHS60M584MWCPVKCLU8hLJZQN7nlL8tLPH/q96nLVw+ms/5esLhJmi1WeBltnVCxTSmgrKc6hVBiJYPz3dn5rQdZTPFiuOg49TKqJHff9/tkE0PuO/12vjPTJ11/YU/40QFMPk5gFUx0567ku5LSmLdM6py4oW51/9O7/cEVk3nXG9XK6T+a2v7+fbHv0i/cwQm6VM1wIFO3NdTA4W5ho7p8SfXfetWD0J3odtUGemuQMSoEIBiaQxpriTBfB6FIMOoDWlujQ7Y+JRoBMHGdD/7tFxrwTHJ1WEgJqmXEZq4oXdNUWMxwsMmFk35G/z2Z8ukkaGsQiKmujy9WCiNIe0opwrqlO6yASX14CoDuOwEYjVXnX1t8/k0zWPx39P/dxTj98pefJ4nJX3HK++FLuSdJ+ShXXAZaSOmqJgKY4MZJzmIQiu9DXtwfNfYuZCJfyqOvW5uU3f3q/UeQWgkygydWoHP1S6ROne0FiXyRpnO0uUT8AaWIgAA1VAmSKAy8HStRq0hLQDvFwz7DsJ1dGSiaCbd8+Dv5os5K8XXHlMyyEYaAUR7VJT2WC8d2QpMNd40SRwcHnPYy+0ZNBkwTIADi+oLFHQooElBElUAprtHQ2Lk091ffUghwf6J3k+c2bLMPObbvra+cTQP/87YEeo6HCy/mz17jyrvFdG9+ehCfG3Y5IMdtyaMYC06SBphT6RCJZhbQs2AU11bfIBFy3AS7Q8Uuv/2QLAbM2UTmWeKE5MIE9mtUUA46pN7O0o4ZoBlom6oOikQYTGAZVYkQtJk6Q4jzUVijVx0VZeaxDNgIhSuHXX//HdEQqLcqCHNHMJRSJh+kUMVAqVqthM0DY1/cUmu1WRGigZWPd/fw2okwHGAjiUE0Jni45UI3LMuQsZhlmrKY4Emx1i3V80yLZ4YkOnR3dYkr8eF/fnso0oI//bBUVtCM8N/bu448/vZCHcImf4/o2S7IkLM+2tW9F5YrHHe0zwlORBNuymdQiDhwrXVSeKo+fgGCpweHXa9Qv7f/bB5lNViNl3vxnoG6cMCRIAGKBRj3XYM4BtuVaUkOEASKkNrFNaRQrFdkAYSx1zBwVa+pKVtLKtlH63yIX8gOgidRuzWaA8iwz0CS1SbJ6DEXZCFMqVpVarGLhpKMnH3wyWml6L7Rm9fbulSdODKSrABlNqC+kbjKKuagghUJWLUWLkalOBRHT/3r3H0wtMgby4ps/8dMOu/P8SfYWfucE0AMDA3bnRnWvJ9i7L9xAevRSAJak7nyYt+R7v3HcVRkaV2TKKEhrh6e0lLaVMMpQgVJMUV3RglRpR662iGt/KY9ecpuXD/z4VsJVFhPEMUZUG3RTY+aU0BL/l1QbV0rKXEVQ5oYVBb4tWU0rKWNT87h2q5ZG0La3p/XYWF7v3r0bPYt1aJtQdejncUu3AxVIK9A+5Sj1iIcBqbhLMIIS3apQHVQjqeJIE3F7zo82bdqDAawrIonnTw6CGbJtd4kYA8qicTIVjk+t6oxbJgoOyaasWqnmUYv7MlJIvFn80s5v1Y2mm9tvciB8W2+gDNTOe/7dTMz2TItfHv5ptwSVGk+5v7leJCBLRsA1NEz0wFuAB+8ct7XfyiyqLOoYVxrqsVh61LIsEwPTmMQERBDGIh3hoUkHaUJDxqzw+PFJuXfvlYkMyx0WWglKJWAjMAL5KHcJMEFQNuvWdZgg6DZDQ0OwYcOoGR/vMcPDw6a/vx/b1QVXYiF46b9boiltW5q4FmGeZjpFgXqgtWOQCTq5mUqiWUS5rDHDasBpWA0MhkeKIDgnHnvs+2KlpfD8OZqN1Ui8gv92c84Y3UIoZEEJT2Kuu+EFQ8TY6F3WFLwBdj6qOgBpierDIvNNXnvtrzPSs+/JmNpQb+/eJKHg0gn65MkXnY8nC5spNSO/eOH985+2+W654Jl/H07kE090sjjO8WLxnOV1+jQKFHV4k402ZMOlY5R2KOGWBGFpzaiVZMcgJ0ISu5TYfy1DhDYCmXaF7REBVUdWuVHNJJRV39KlqqszxYyurKuY7mDSlMsbDMCBZDi7d/ckwNy/f5gA7Ep+h/QOY2MHqef5pOLHVIecpVyfkmLAAWJOUjanRFtKUpsSYyklbeTwS2omJhwgBDkT0EevNCeCRiY2DoT4E7GsCLUUZmsFxbQEqEqA03Ihr99KzffcfhKpnGq7S2KmtGFnobbuwlh2jLZAweGa2tWi9IFazZSYtBCJm+l037ZvLqnAJ+5CzL9tswBV+t3eP0D3+Eyk4pwR7Bv8WRuQ6HYr0Cc+CYfG9ZjEpfaZEKh3T9Jy2WYANS4lZ7ytPbErpyRlNbA4IzWLUsfCuAIMCpbEWAgmwyQmHFKtDCU2xQTERDAgd8fcejuztYzQCow/IwAVmW47244l6gdGW+BfsU4tUp8iTy7VBMstYgEjwmQESuKiUg4IG3BBxVIp14ROVVOrSaEerbrbpDfiqauJp1nqfF1Fu9lwcjRZ0i9/vbuNcbdNa9XMNLCYkSmq4tHtv3YnhnD+vZyjKoFjhSql027Q1/vvF6UvwG+3am21WwFpCgtTv5p77rvMxokNO7uDLiFUZ9USx786I8av4mU+K03JwMAAzefzpL19nJ44McKy2TYapgW1uEOiAP8PCGc24bWQwIxDJeP7EEclygJO0BgVBZyk0kjchQ5EAMeVBqoAypMGs1w85RilxDTXRso1UC6DTLlGqtg4XpsWMjZeUNIVn+tM2dbTAWDDevdudCbWN719mh8A8XPrRridWDqtiH36gYsBQwjqRx7pcVRGuMSmHolIi4plNlnYhhStSJzesePb5eQstD9PFrOyGdNPDx5Zv8YY0wlBhIL3ssTZK4z2uE3EJLVORlFLNm2fuHuBsM5Pc/Ju8GeT/n5U5/rrDnNGP55Wc2/uK9FjKfXl9otpegjeJ5/saS4zuZrGplkqLRk1o7WCGkVz6syu6MQec6Oym2KgWhTVY31bn2qYBTN3ehDMb/7zurVRTDttJX69fft3CvOnr25OYZIrWDzXBYTnWRyf3L79O0iieLNP/s0NnRtw9AnA3t241iP61liRMUfKDzdvPhUMDXW6AH4qgjhLgbYJDS4xosiUOfPKKyNFPJ/NgnssG6nH1y9uKsb2+dXV9cyiTbGG97/0wLcQzFdgsi6gce7QZplOZ9q1Q7o4p2d33P/ByI24zd2A3/kzOSQE7+Hhde2ylC6hNJ55STI4+KwnrXSLRciqmGifgC5AlX24bds3p5JDIeRSNYhSIHXeUNEcBXL0kV1/fPJqJmlw8NlUbNyNaFPUFf1BX99TDTOcGgIaH5jkGLLjOWJ7aw3Ygmvv5JyXuZoxfd72Jp8BlJC3b4o3Cqk7wJiR2uTaU7P6LoL99dfXpF3XzsRcd+hQNmtDSkSGH+zc+SdF099Php7odIvK9dC23tf31JKSAFCF2fnIqk6X2WsjCgU7grPzdeYlqRxzG2GnX/nK7RlBahiAnwMpRnfsGP1cWt/kAF1o+EeGf7o+iGVt+z3fmpuAStDDFwRBC7WhK5TKNoH+8NVXR87MmngRK1//erc3HkQZG2CVUaSZg3j3oYe+e4kPD9sswSRM9u17Js1T7m0QS9fzUh+Vy3JyKWENC0rouS+N6S4AtWbHcToVNVRyffrAC6OFJQzuM/zpb95XO3r0x+lq1dX1dtx//vXfdokI7tBSFlv8zuPr56RgoaRev77qS2laIq260NRoYnj/4Yf3zmU0Is8PPutlypBynFz1anZ1dEIVCsVbKGWtkYkKRHjnx8fT5aWGLywZ0MmR3PTTt95qyShFcwLsdixpRwj96GY9NOIiPXDgdPwZXpTk6NEfp+pZqo4f/9mqUEabSco50rvxctvvtO4LWUX5LQRYFqT+zdatf3hm7vJNrGEx87WO85ryDiPE2K5d33unzhK/ZJdeaPljf0Gg1hDLaucAtThmo0qR8lKk8tx+rwrQszfiw8vlWppzp4VSjoxFInbMyM0ksX957C9zpkh6KhUx2Cgga9++ZzK+z6N6fH43imzGA1O5vCGuZ7+dVgHWbQ2NKDxwzx9dFhuBnuGKOL9Wx6bbSPFeb+/e9+e/04kTz2QqFTtvjL5FSlOedMnwfN8EGg9aW2lmItL08Yefvmoq3WTnd2qrLUraiOJhbFnnoFqrHDjwvdpyYvOXBejZF8eX8Tzfo1TmGFOthmtjgXWec33+RgYBjru5zd6hYz1y9mzbe/W2M1y0UWQeJKTlcKMtEwGfShnngQf+NMk4rncdPPgX3oMPTkX1LEQzkhAj0BoSGx49+pPVQlQLjdoMDv6v25hrWu6986nD9Z5/9OiP24UR9xClz9x//3+8TIImUpbrdh6TLypFJs+cyR2dPxfoYk6lbs1qHa6TUqakTA3Wk5qoiixVLcCQi1dffbbJ902XUpDVOq45jn8+jnX17Fn/UuWG5QiNawL07ANR7xkb+zjleZkMIapVKeMA0Kkoqp3r6/tPC5HILGfM13zPoSM/2hJXJaO07WgjsB4+/D+7pYzWnjnT+stGH+rNf/rLzQBUbnv4j4cbDeqNwz98KKy4Q/VAcOzYT3Ohqt6x9d4/Otjo/rd/9dd3Y93y++77dpLVPP9CXVgauUMLOLllyx9ekfKfSOkvr2qLbbZZCHN++/a9l1Hdohp56FBbTil7ozGaG1M6smPHf76CthafEwRRhnONi2tZVQ+QzTY/dq7dskgHcIaZwCUhvAtKBcH4eH5FwnxXBNCzk4xxyptC7hISe8aYHCGmSTOibaIKxWI49uijf/app0699daPNhCi11BKBnt799Yl1EGp5PudvyNlNLxt29MNg2XeeuuHj0YRPTbvQHQZ5oaGfvSEMeYX9SQsSm/P8h9RRL/YCCQI+khWdzb74cvrGzggDh36mw7Dwt64Zl7fufNPkkpi8y60F7cqpTdLqQvbt48fm79jvPnmD5qUYt1EUrJ913eP1Fs8MxaKhlGA9e4xAwPsYNdEKyFylTEkQylEAKwgpSkx1ha+8sqeaDmqRSMBsKKAnn3ItP++yfGinBM4YdpEcY44dgp1bUJgEonT+/q+94mnTg0OPpt1GN0aiPj4iy+OjzU6DB458sNbdAzdUzX3YKNDCZJaWrTwyAcfnXtpz57+hjX3hg791VcvTJZ/8eijf1aPGYocfvtHX6loc7ivd2/doBycy68+1v6QMHRi27b6OwFK2Tfe6NxAjVz70cfj+xuN5+DBv2ghytpMNZx+YNf3r6Ckff75Z1OdLli9X96Lu+qyr8Fnn7WiO3XOMiqvgfoK6zlpU6KUFRkT4UcfFcKF5mzZD54bPnotnSx0L0728HAPL5VGWK1GmzzPyTOtm/EeRWVRKXI+9Y5T7F3B+ONG4zl58gdOqeS4L7wwejEZuFFeXT/P5b7wu1ZsHX3uxdMNQT809MztWtPVW7Z8d/9C73/o0DNfnZysNQI0HHr9mS2U6LB3+/cbst7jQlSx6mvJy5caSWmUhIe7xu+LY8V29D39ZqMx4a4wYafJCgeeTduNedxOCGvnwDxCWBjK6ILWehygOfyNH6u9vXsx6PC6hlBcFwndaDLx4LBpE7CxsSpNpappIWQbB5pThNpEaWRjKCg+NTE6ehuyly45/+4qFuPs+zacVBzjHXeU2t65M3thoYTQt9/+q16t48ne3qevsA7MHc/hN//H1+xS8PO760toOHTomTU6Nl/ctuNPX230HkkY5u7sA4bz0zt2fP9so3Z4lpmYOJd9eHFrw5JMaQvNKy4Mra0cIbKdamjGgFhFoEIIGWclPRl4bDvSowAABHZJREFUfuz7scKUq+sN4rnj/EQBPffBKLmHhjoZxiO3Q42XQTUD0y0GmG/AYLhwoAgtShkW2tvXTi2WLHkVoF606VJO7GguQxVqsQPS4OB/WwtD3mijHQh3jcmzrH3rru9dZuedP8hpi9Jdainhldcj5ua1f/gvvmlxckzTVkJVFhmewMgAtF0wcVggPivn81yPjBRUX1//ZfV0Fp3wFWzwqQF6/qEF449npbeU5x2fp3xlm2YioYlQbROJbFmqKkAXKU0XPY9VFgPTCs7TsrtCVYAsvNsksdfXaUdazrjJyy//11Srx5tqwHKOVllFdYoltcF0jVlsUoVQ5M1euVy2NUrh++8fvciUfWPEZ98ogJ4/8clHngV4HF9gGYC0k3F8I6FJ6TiNZRqwciZwCJTQFZuxkqywKm93gpsB6MtB2krfg06NlKqmwQqapOZZxlWGGuIkBDXEREKQMidxyUTOFDRBEEVTxvc71alTP9d79jx3PVTCa37FGxXQV7zYrIoyNhYleXgAp7nvZ1xRZhkjI59yK60NcQhWUTXCaMUiznSNEV5RFqlCgQb+uo7wk1RdrvnrXGMHScyxN+zErU0uFyatQGa0YVjY0rMsYimVsDJJzlhNga5QQ8oR9SpekUXljK2nM8yH9YEDsGSK5Gsc8jXfftMAut6bIsj37wfa3t5Dx8aGqeM0ET0uuNvEHJAyFXOesplOCQkeWMTSMVDGkITfKCGMIBYNCdCQhjKMTBw2p3PhhBwTq4MWcaTSIW8gNeDS6/826bfKsQo8dVJ22QjXAeWCIB6zmau1dLDET1JsHBErAcsdxribMQFVlSJVpdxarVaNfZ/p30renB4e3nMx4/yT5xC8ZiTPdHBTA7rRJMwC3fc7yaxEd5xJki4rqm1uFWvCtV3qcJs4IIRHKLeV1vYsCJArmRnbSJCQ1AkkRimszQlEEvxnEUmwiA7higqtmKeUlKAZxW6kkQK069pGK9wp7EsWFcpiQhkyvqYgFgbZBajgLuXcUMxWsgxlERjOOWNGIJ0uHo4NZwwrx2IeLWXIWwdKI4W5wWrhybiMEagiMGoiiQsUWMiJFeqoFkOYE3Fr1SBog6DFtLc7+tQpBG5ClVCX12OlwPVp9POZBPRCE9nfD7Sn50mSz28iCHjPGyX26RYy4vkEQW9PTBG001KqeFrZjPLA0sRwF1weUmEh6GJCLW4UwxxtbRSjlFOUhsi1jNRdWHNWEk14YsqazvKevTDLO/nZ6KSeMVLhYggmIUxRonFBaGJsSalSMS4eQ6SjtQiRQloq0ewTWSuHird/QcLoKMStTSaKcgY5PiqVgunu7jQI2CefHL5IC9CY2+PTANsn8cx/cYC+ikm9mOjaT/78zwGee66H5PPIqYF8Gp3k1KlRsmkTwOnTLWQ9AIx4hZl5XAfO+OT0z6sXedKMQx153gFOT98StBjMTVq3rmBOnABAcJbL0+Qz+Pd/qSC9im/2W6KZq7np87afz8CNOgOfS+gb9ct8Pq5lzcD/B6kPVvCV/7fcAAAAAElFTkSuQmCC",cp="data:image/png;base64,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",ev="data:image/png;base64,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",tv=xe(37426),nv=xe(19150),iv=xe(55303),ay=xe(92691),pp=xe(99755),rv=xe(46016),ov="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAFgAAABYCAYAAABxlTA0AAAAAXNSR0IArs4c6QAAFR5JREFUeF7dXWtsHNd1PrO7s49ZLpcrLkmtxNeSej/s1pAdo4mRsrVjR4mbtIVS1HWNwEllw6mNtIXR9h+BokgNB4nhBEokOIoauYYjIzb8ku3EqRDH8Y/EDZpasinJevH9WGq55L5nd29x7p27M7M7szP7otguIYggZ+7c+8253/nOuedeCmDzc5S8L+6Xw/tEAPitGDv7kHBAtnlr05cdIb8MDUGwf0AOuvGh82Iifw0S048I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",nn=xe.p+"static/newqrcode.a8740efb.png",tn=xe(32637),Gt=xe(59301),Mt=(vt,dt,rt)=>new 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diff --git a/p__tasks__index.62861477.async.js b/p__tasks__index.c7a485e4.async.js
similarity index 99%
rename from p__tasks__index.62861477.async.js
rename to p__tasks__index.c7a485e4.async.js
index b3a73538a1..6c8379b178 100644
--- a/p__tasks__index.62861477.async.js
+++ b/p__tasks__index.c7a485e4.async.js
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",rc="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAyAAAAMgCAMAAADsrvZaAAADAFBMVEUAAAD90UH/00P+0T7+0j/+0j7+0j/+0j//1ED90D78zz78zz/otjD6zz/ntzDfrCv7zz7vwDjfrizXqivery3zxjvKmyfVpSnery7YqCn6zj/vwTnktjP+4EvW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",rc="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAyAAAAMgCAMAAADsrvZaAAADAFBMVEUAAAD90UH/00P+0T7+0j/+0j7+0j/+0j//1ED90D78zz78zz/otjD6zz/ntzDfrCv7zz7vwDjfrizXqivery3zxjvKmyfVpSnery7YqCn6zj/vwTnktjP+4EvW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read"),an.reading=!0,an.sync=!0,an.length===0&&(an.needReadable=!0),this._read(an.highWaterMark),an.sync=!1,an.reading||(Sn=zn(mr,an))),(Fr=Sn>0?Jn(Sn,an):null)===null?(an.needReadable=!0,Sn=0):an.length-=Sn,an.length===0&&(an.ended||(an.needReadable=!0),mr!==Sn&&an.ended&&Or(this)),Fr!==null&&this.emit("data",Fr),Fr},Bn.prototype._read=function(Sn){this.emit("error",new Error("_read() is not implemented"))},Bn.prototype.pipe=function(Sn,an){var mr=this,Fr=this._readableState;switch(Fr.pipesCount){case 0:Fr.pipes=Sn;break;case 1:Fr.pipes=[Fr.pipes,Sn];break;default:Fr.pipes.push(Sn)}Fr.pipesCount+=1,St("pipe count=%d opts=%j",Fr.pipesCount,an);var jr=an&&an.end===!1||Sn===lt.stdout||Sn===lt.stderr?Vn:Pr;function Pr(){St("onend"),Sn.end()}Fr.endEmitted?Et.nextTick(jr):mr.once("end",jr),Sn.on("unpipe",function $n(Xr,si){St("onunpipe"),Xr===mr&&si&&si.hasUnpiped===!1&&(si.hasUnpiped=!0,St("cleanup"),Sn.removeListener("close",qn),Sn.removeListener("finish",lr),Sn.removeListener("drain",Qr),Sn.removeListener("error",Hn),Sn.removeListener("unpipe",$n),mr.removeListener("end",Pr),mr.removeListener("end",Vn),mr.removeListener("data",on),Dt=!0,!Fr.awaitDrain||Sn._writableState&&!Sn._writableState.needDrain||Qr())});var Qr=function($n){return function(){var Xr=$n._readableState;St("pipeOnDrain",Xr.awaitDrain),Xr.awaitDrain&&Xr.awaitDrain--,Xr.awaitDrain===0&&It($n,"data")&&(Xr.flowing=!0,hn($n))}}(mr);Sn.on("drain",Qr);var Dt=!1,Zt=!1;function on($n){St("ondata"),Zt=!1,Sn.write($n)!==!1||Zt||((Fr.pipesCount===1&&Fr.pipes===Sn||Fr.pipesCount>1&&Br(Fr.pipes,Sn)!==-1)&&!Dt&&(St("false write response, pause",mr._readableState.awaitDrain),mr._readableState.awaitDrain++,Zt=!0),mr.pause())}function Hn($n){St("onerror",$n),Vn(),Sn.removeListener("error",Hn),It(Sn,"error")===0&&Sn.emit("error",$n)}function qn(){Sn.removeListener("finish",lr),Vn()}function lr(){St("onfinish"),Sn.removeListener("close",qn),Vn()}function Vn(){St("unpipe"),mr.unpipe(Sn)}return mr.on("data",on),function($n,Xr,si){if(typeof $n.prependListener=="function")return $n.prependListener(Xr,si);$n._events&&$n._events[Xr]?Gt($n._events[Xr])?$n._events[Xr].unshift(si):$n._events[Xr]=[si,$n._events[Xr]]:$n.on(Xr,si)}(Sn,"error",Hn),Sn.once("close",qn),Sn.once("finish",lr),Sn.emit("pipe",mr),Fr.flowing||(St("pipe resume"),mr.resume()),Sn},Bn.prototype.unpipe=function(Sn){var an=this._readableState,mr={hasUnpiped:!1};if(an.pipesCount===0)return this;if(an.pipesCount===1)return Sn&&Sn!==an.pipes||(Sn||(Sn=an.pipes),an.pipes=null,an.pipesCount=0,an.flowing=!1,Sn&&Sn.emit("unpipe",this,mr)),this;if(!Sn){var Fr=an.pipes,jr=an.pipesCount;an.pipes=null,an.pipesCount=0,an.flowing=!1;for(var Pr=0;Pr<jr;Pr++)Fr[Pr].emit("unpipe",this,mr);return this}var Qr=Br(an.pipes,Sn);return Qr===-1||(an.pipes.splice(Qr,1),an.pipesCount-=1,an.pipesCount===1&&(an.pipes=an.pipes[0]),Sn.emit("unpipe",this,mr)),this},Bn.prototype.on=function(Sn,an){var mr=zt.prototype.on.call(this,Sn,an);if(Sn==="data")this._readableState.flowing!==!1&&this.resume();else if(Sn==="readable"){var Fr=this._readableState;Fr.endEmitted||Fr.readableListening||(Fr.readableListening=Fr.needReadable=!0,Fr.emittedReadable=!1,Fr.reading?Fr.length&&dn(this):Et.nextTick(In,this))}return mr},Bn.prototype.addListener=Bn.prototype.on,Bn.prototype.resume=function(){var Sn=this._readableState;return Sn.flowing||(St("resume"),Sn.flowing=!0,function(an,mr){mr.resumeScheduled||(mr.resumeScheduled=!0,Et.nextTick(Zn,an,mr))}(this,Sn)),this},Bn.prototype.pause=function(){return St("call pause flowing=%j",this._readableState.flowing),this._readableState.flowing!==!1&&(St("pause"),this._readableState.flowing=!1,this.emit("pause")),this},Bn.prototype.wrap=function(Sn){var an=this,mr=this._readableState,Fr=!1;for(var jr in Sn.on("end",function(){if(St("wrapped end"),mr.decoder&&!mr.ended){var Qr=mr.decoder.end();Qr&&Qr.length&&an.push(Qr)}an.push(null)}),Sn.on("data",function(Qr){St("wrapped data"),mr.decoder&&(Qr=mr.decoder.write(Qr)),mr.objectMode&&Qr==null||(mr.objectMode||Qr&&Qr.length)&&(an.push(Qr)||(Fr=!0,Sn.pause()))}),Sn)this[jr]===void 0&&typeof Sn[jr]=="function"&&(this[jr]=function(Qr){return function(){return Sn[Qr].apply(Sn,arguments)}}(jr));for(var Pr=0;Pr<Vt.length;Pr++)Sn.on(Vt[Pr],this.emit.bind(this,Vt[Pr]));return this._read=function(Qr){St("wrapped _read",Qr),Fr&&(Fr=!1,Sn.resume())},this},Object.defineProperty(Bn.prototype,"readableHighWaterMark",{enumerable:!1,get:function(){return this._readableState.highWaterMark}}),Bn._fromList=Jn}).call(this,be("_process"),yt.g!==void 0?yt.g:typeof self!="undefined"?self:typeof window!="undefined"?window:{})},{"./_stream_duplex":12,"./internal/streams/BufferList":17,"./internal/streams/destroy":18,"./internal/streams/stream":19,_process:10,"core-util-is":3,events:4,inherits:6,isarray:8,"process-nextick-args":9,"safe-buffer":20,"string_decoder/":21,util:2}],15:[function(be,Be,qe){Be.exports=Ft;var lt=be("./_stream_duplex"),dt=Object.create(be("core-util-is"));function Et(zt,wt){var xt=this._transformState;xt.transforming=!1;var kt=xt.writecb;if(!kt)return this.emit("error",new Error("write callback called multiple times"));xt.writechunk=null,xt.writecb=null,wt!=null&&this.push(wt),kt(zt);var Kt=this._readableState;Kt.reading=!1,(Kt.needReadable||Kt.length<Kt.highWaterMark)&&this._read(Kt.highWaterMark)}function Ft(zt){if(!(this instanceof Ft))return new Ft(zt);lt.call(this,zt),this._transformState={afterTransform:Et.bind(this),needTransform:!1,transforming:!1,writecb:null,writechunk:null,writeencoding:null},this._readableState.needReadable=!0,this._readableState.sync=!1,zt&&(typeof zt.transform=="function"&&(this._transform=zt.transform),typeof zt.flush=="function"&&(this._flush=zt.flush)),this.on("prefinish",Gt)}function Gt(){var zt=this;typeof this._flush=="function"?this._flush(function(wt,xt){It(zt,wt,xt)}):It(this,null,null)}function It(zt,wt,xt){if(wt)return zt.emit("error",wt);if(xt!=null&&zt.push(xt),zt._writableState.length)throw new Error("Calling transform done when ws.length != 0");if(zt._transformState.transforming)throw new Error("Calling transform done when still transforming");return zt.push(null)}dt.inherits=be("inherits"),dt.inherits(Ft,lt),Ft.prototype.push=function(zt,wt){return this._transformState.needTransform=!1,lt.prototype.push.call(this,zt,wt)},Ft.prototype._transform=function(zt,wt,xt){throw new Error("_transform() is not implemented")},Ft.prototype._write=function(zt,wt,xt){var kt=this._transformState;if(kt.writecb=xt,kt.writechunk=zt,kt.writeencoding=wt,!kt.transforming){var Kt=this._readableState;(kt.needTransform||Kt.needReadable||Kt.length<Kt.highWaterMark)&&this._read(Kt.highWaterMark)}},Ft.prototype._read=function(zt){var wt=this._transformState;wt.writechunk!==null&&wt.writecb&&!wt.transforming?(wt.transforming=!0,this._transform(wt.writechunk,wt.writeencoding,wt.afterTransform)):wt.needTransform=!0},Ft.prototype._destroy=function(zt,wt){var xt=this;lt.prototype._destroy.call(this,zt,function(kt){wt(kt),xt.emit("close")})}},{"./_stream_duplex":12,"core-util-is":3,inherits:6}],16:[function(be,Be,qe){(function(lt,dt,Et){var Ft=be("process-nextick-args");function Gt(bn){var Tn=this;this.next=null,this.entry=null,this.finish=function(){(function(gr,In,Zn){var hn=gr.entry;for(gr.entry=null;hn;){var Jn=hn.callback;In.pendingcb--,Jn(void 0),hn=hn.next}In.corkedRequestsFree?In.corkedRequestsFree.next=gr:In.corkedRequestsFree=gr})(Tn,bn)}}Be.exports=yn;var It,zt=!lt.browser&&["v0.10","v0.9."].indexOf(lt.version.slice(0,5))>-1?Et:Ft.nextTick;yn.WritableState=Vt;var wt=Object.create(be("core-util-is"));wt.inherits=be("inherits");var xt,kt={deprecate:be("util-deprecate")},Kt=be("./internal/streams/stream"),St=be("safe-buffer").Buffer,Rt=dt.Uint8Array||function(){},en=be("./internal/streams/destroy");function tn(){}function Vt(bn,Tn){It=It||be("./_stream_duplex"),bn=bn||{};var gr=Tn instanceof It;this.objectMode=!!bn.objectMode,gr&&(this.objectMode=this.objectMode||!!bn.writableObjectMode);var In=bn.highWaterMark,Zn=bn.writableHighWaterMark,hn=this.objectMode?16:16384;this.highWaterMark=In||In===0?In:gr&&(Zn||Zn===0)?Zn:hn,this.highWaterMark=Math.floor(this.highWaterMark),this.finalCalled=!1,this.needDrain=!1,this.ending=!1,this.ended=!1,this.finished=!1,this.destroyed=!1;var Jn=bn.decodeStrings===!1;this.decodeStrings=!Jn,this.defaultEncoding=bn.defaultEncoding||"utf8",this.length=0,this.writing=!1,this.corked=0,this.sync=!0,this.bufferProcessing=!1,this.onwrite=function(Or){(function(Sr,Br){var Sn=Sr._writableState,an=Sn.sync,mr=Sn.writecb;if(function(jr){jr.writing=!1,jr.writecb=null,jr.length-=jr.writelen,jr.writelen=0}(Sn),Br)(function(jr,Pr,Qr,Dt,Zt){--Pr.pendingcb,Qr?(Ft.nextTick(Zt,Dt),Ft.nextTick(dn,jr,Pr),jr._writableState.errorEmitted=!0,jr.emit("error",Dt)):(Zt(Dt),jr._writableState.errorEmitted=!0,jr.emit("error",Dt),dn(jr,Pr))})(Sr,Sn,an,Br,mr);else{var Fr=On(Sn);Fr||Sn.corked||Sn.bufferProcessing||!Sn.bufferedRequest||ir(Sr,Sn),an?zt(_n,Sr,Sn,Fr,mr):_n(Sr,Sn,Fr,mr)}})(Tn,Or)},this.writecb=null,this.writelen=0,this.bufferedRequest=null,this.lastBufferedRequest=null,this.pendingcb=0,this.prefinished=!1,this.errorEmitted=!1,this.bufferedRequestCount=0,this.corkedRequestsFree=new Gt(this)}function yn(bn){if(It=It||be("./_stream_duplex"),!(xt.call(yn,this)||this instanceof It))return new yn(bn);this._writableState=new Vt(bn,this),this.writable=!0,bn&&(typeof bn.write=="function"&&(this._write=bn.write),typeof bn.writev=="function"&&(this._writev=bn.writev),typeof bn.destroy=="function"&&(this._destroy=bn.destroy),typeof bn.final=="function"&&(this._final=bn.final)),Kt.call(this)}function Bn(bn,Tn,gr,In,Zn,hn,Jn){Tn.writelen=In,Tn.writecb=Jn,Tn.writing=!0,Tn.sync=!0,gr?bn._writev(Zn,Tn.onwrite):bn._write(Zn,hn,Tn.onwrite),Tn.sync=!1}function _n(bn,Tn,gr,In){gr||function(Zn,hn){hn.length===0&&hn.needDrain&&(hn.needDrain=!1,Zn.emit("drain"))}(bn,Tn),Tn.pendingcb--,In(),dn(bn,Tn)}function ir(bn,Tn){Tn.bufferProcessing=!0;var gr=Tn.bufferedRequest;if(bn._writev&&gr&&gr.next){var In=Tn.bufferedRequestCount,Zn=new Array(In),hn=Tn.corkedRequestsFree;hn.entry=gr;for(var Jn=0,Or=!0;gr;)Zn[Jn]=gr,gr.isBuf||(Or=!1),gr=gr.next,Jn+=1;Zn.allBuffers=Or,Bn(bn,Tn,!0,Tn.length,Zn,"",hn.finish),Tn.pendingcb++,Tn.lastBufferedRequest=null,hn.next?(Tn.corkedRequestsFree=hn.next,hn.next=null):Tn.corkedRequestsFree=new Gt(Tn),Tn.bufferedRequestCount=0}else{for(;gr;){var Sr=gr.chunk,Br=gr.encoding,Sn=gr.callback;if(Bn(bn,Tn,!1,Tn.objectMode?1:Sr.length,Sr,Br,Sn),gr=gr.next,Tn.bufferedRequestCount--,Tn.writing)break}gr===null&&(Tn.lastBufferedRequest=null)}Tn.bufferedRequest=gr,Tn.bufferProcessing=!1}function On(bn){return bn.ending&&bn.length===0&&bn.bufferedRequest===null&&!bn.finished&&!bn.writing}function zn(bn,Tn){bn._final(function(gr){Tn.pendingcb--,gr&&bn.emit("error",gr),Tn.prefinished=!0,bn.emit("prefinish"),dn(bn,Tn)})}function dn(bn,Tn){var gr=On(Tn);return gr&&(function(In,Zn){Zn.prefinished||Zn.finalCalled||(typeof In._final=="function"?(Zn.pendingcb++,Zn.finalCalled=!0,Ft.nextTick(zn,In,Zn)):(Zn.prefinished=!0,In.emit("prefinish")))}(bn,Tn),Tn.pendingcb===0&&(Tn.finished=!0,bn.emit("finish"))),gr}wt.inherits(yn,Kt),Vt.prototype.getBuffer=function(){for(var bn=this.bufferedRequest,Tn=[];bn;)Tn.push(bn),bn=bn.next;return Tn},function(){try{Object.defineProperty(Vt.prototype,"buffer",{get:kt.deprecate(function(){return this.getBuffer()},"_writableState.buffer is deprecated. Use _writableState.getBuffer instead.","DEP0003")})}catch(bn){}}(),typeof Symbol=="function"&&Symbol.hasInstance&&typeof Function.prototype[Symbol.hasInstance]=="function"?(xt=Function.prototype[Symbol.hasInstance],Object.defineProperty(yn,Symbol.hasInstance,{value:function(bn){return!!xt.call(this,bn)||this===yn&&bn&&bn._writableState instanceof Vt}})):xt=function(bn){return bn instanceof this},yn.prototype.pipe=function(){this.emit("error",new Error("Cannot pipe, not readable"))},yn.prototype.write=function(bn,Tn,gr){var In,Zn=this._writableState,hn=!1,Jn=!Zn.objectMode&&(In=bn,St.isBuffer(In)||In instanceof Rt);return Jn&&!St.isBuffer(bn)&&(bn=function(Or){return St.from(Or)}(bn)),typeof Tn=="function"&&(gr=Tn,Tn=null),Jn?Tn="buffer":Tn||(Tn=Zn.defaultEncoding),typeof gr!="function"&&(gr=tn),Zn.ended?function(Or,Sr){var Br=new Error("write after end");Or.emit("error",Br),Ft.nextTick(Sr,Br)}(this,gr):(Jn||function(Or,Sr,Br,Sn){var an=!0,mr=!1;return Br===null?mr=new TypeError("May not write null values to stream"):typeof Br=="string"||Br===void 0||Sr.objectMode||(mr=new TypeError("Invalid non-string/buffer chunk")),mr&&(Or.emit("error",mr),Ft.nextTick(Sn,mr),an=!1),an}(this,Zn,bn,gr))&&(Zn.pendingcb++,hn=function(Or,Sr,Br,Sn,an,mr){if(!Br){var Fr=function(Dt,Zt,on){return Dt.objectMode||Dt.decodeStrings===!1||typeof Zt!="string"||(Zt=St.from(Zt,on)),Zt}(Sr,Sn,an);Sn!==Fr&&(Br=!0,an="buffer",Sn=Fr)}var jr=Sr.objectMode?1:Sn.length;Sr.length+=jr;var Pr=Sr.length<Sr.highWaterMark;if(Pr||(Sr.needDrain=!0),Sr.writing||Sr.corked){var Qr=Sr.lastBufferedRequest;Sr.lastBufferedRequest={chunk:Sn,encoding:an,isBuf:Br,callback:mr,next:null},Qr?Qr.next=Sr.lastBufferedRequest:Sr.bufferedRequest=Sr.lastBufferedRequest,Sr.bufferedRequestCount+=1}else Bn(Or,Sr,!1,jr,Sn,an,mr);return Pr}(this,Zn,Jn,bn,Tn,gr)),hn},yn.prototype.cork=function(){this._writableState.corked++},yn.prototype.uncork=function(){var bn=this._writableState;bn.corked&&(bn.corked--,bn.writing||bn.corked||bn.finished||bn.bufferProcessing||!bn.bufferedRequest||ir(this,bn))},yn.prototype.setDefaultEncoding=function(bn){if(typeof bn=="string"&&(bn=bn.toLowerCase()),!(["hex","utf8","utf-8","ascii","binary","base64","ucs2","ucs-2","utf16le","utf-16le","raw"].indexOf((bn+"").toLowerCase())>-1))throw new TypeError("Unknown encoding: "+bn);return this._writableState.defaultEncoding=bn,this},Object.defineProperty(yn.prototype,"writableHighWaterMark",{enumerable:!1,get:function(){return this._writableState.highWaterMark}}),yn.prototype._write=function(bn,Tn,gr){gr(new Error("_write() is not implemented"))},yn.prototype._writev=null,yn.prototype.end=function(bn,Tn,gr){var In=this._writableState;typeof bn=="function"?(gr=bn,bn=null,Tn=null):typeof Tn=="function"&&(gr=Tn,Tn=null),bn!=null&&this.write(bn,Tn),In.corked&&(In.corked=1,this.uncork()),In.ending||In.finished||function(Zn,hn,Jn){hn.ending=!0,dn(Zn,hn),Jn&&(hn.finished?Ft.nextTick(Jn):Zn.once("finish",Jn)),hn.ended=!0,Zn.writable=!1}(this,In,gr)},Object.defineProperty(yn.prototype,"destroyed",{get:function(){return this._writableState!==void 0&&this._writableState.destroyed},set:function(bn){this._writableState&&(this._writableState.destroyed=bn)}}),yn.prototype.destroy=en.destroy,yn.prototype._undestroy=en.undestroy,yn.prototype._destroy=function(bn,Tn){this.end(),Tn(bn)}}).call(this,be("_process"),yt.g!==void 0?yt.g:typeof self!="undefined"?self:typeof window!="undefined"?window:{},be("timers").setImmediate)},{"./_stream_duplex":12,"./internal/streams/destroy":18,"./internal/streams/stream":19,_process:10,"core-util-is":3,inherits:6,"process-nextick-args":9,"safe-buffer":20,timers:27,"util-deprecate":28}],17:[function(be,Be,qe){var lt=be("safe-buffer").Buffer,dt=be("util");Be.exports=function(){function Et(){(function(Ft,Gt){if(!(Ft instanceof Gt))throw new TypeError("Cannot call a class as a function")})(this,Et),this.head=null,this.tail=null,this.length=0}return Et.prototype.push=function(Ft){var Gt={data:Ft,next:null};this.length>0?this.tail.next=Gt:this.head=Gt,this.tail=Gt,++this.length},Et.prototype.unshift=function(Ft){var Gt={data:Ft,next:this.head};this.length===0&&(this.tail=Gt),this.head=Gt,++this.length},Et.prototype.shift=function(){if(this.length!==0){var Ft=this.head.data;return this.length===1?this.head=this.tail=null:this.head=this.head.next,--this.length,Ft}},Et.prototype.clear=function(){this.head=this.tail=null,this.length=0},Et.prototype.join=function(Ft){if(this.length===0)return"";for(var Gt=this.head,It=""+Gt.data;Gt=Gt.next;)It+=Ft+Gt.data;return It},Et.prototype.concat=function(Ft){if(this.length===0)return lt.alloc(0);if(this.length===1)return this.head.data;for(var 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diff --git a/umi.76ab958a.js b/umi.ec93ef90.js
similarity index 99%
rename from umi.76ab958a.js
rename to umi.ec93ef90.js
index 26cf42e532..1046e6f2d3 100644
--- a/umi.76ab958a.js
+++ b/umi.ec93ef90.js
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