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diff --git a/PaperFigures.ipynb b/PaperFigures.ipynb
index 353616d..c141aa3 100755
--- a/PaperFigures.ipynb
+++ b/PaperFigures.ipynb
@@ -1,1255 +1,1446 @@
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this.clone().ineg()},a.prototype.ineg=function(){return this.isZero()||(this.negative^=1),this},a.prototype.iuor=function(t){for(;this.length<t.length;)this.words[this.length++]=0;for(var e=0;e<t.length;e++)this.words[e]=this.words[e]|t.words[e];return this.strip()},a.prototype.ior=function(t){return n(0==(this.negative|t.negative)),this.iuor(t)},a.prototype.or=function(t){return this.length>t.length?this.clone().ior(t):t.clone().ior(this)},a.prototype.uor=function(t){return this.length>t.length?this.clone().iuor(t):t.clone().iuor(this)},a.prototype.iuand=function(t){var e;e=this.length>t.length?t:this;for(var r=0;r<e.length;r++)this.words[r]=this.words[r]&t.words[r];return this.length=e.length,this.strip()},a.prototype.iand=function(t){return n(0==(this.negative|t.negative)),this.iuand(t)},a.prototype.and=function(t){return this.length>t.length?this.clone().iand(t):t.clone().iand(this)},a.prototype.uand=function(t){return this.length>t.length?this.clone().iuand(t):t.clone().iuand(this)},a.prototype.iuxor=function(t){var e,r;this.length>t.length?(e=this,r=t):(e=t,r=this);for(var n=0;n<r.length;n++)this.words[n]=e.words[n]^r.words[n];if(this!==e)for(;n<e.length;n++)this.words[n]=e.words[n];return this.length=e.length,this.strip()},a.prototype.ixor=function(t){return n(0==(this.negative|t.negative)),this.iuxor(t)},a.prototype.xor=function(t){return this.length>t.length?this.clone().ixor(t):t.clone().ixor(this)},a.prototype.uxor=function(t){return this.length>t.length?this.clone().iuxor(t):t.clone().iuxor(this)},a.prototype.inotn=function(t){n(\"number\"==typeof t&&t>=0);var e=0|Math.ceil(t/26),r=t%26;this._expand(e),r>0&&e--;for(var i=0;i<e;i++)this.words[i]=67108863&~this.words[i];return r>0&&(this.words[i]=~this.words[i]&67108863>>26-r),this.strip()},a.prototype.notn=function(t){return this.clone().inotn(t)},a.prototype.setn=function(t,e){n(\"number\"==typeof t&&t>=0);var r=t/26|0,i=t%26;return this._expand(r+1),this.words[r]=e?this.words[r]|1<<i:this.words[r]&~(1<<i),this.strip()},a.prototype.iadd=function(t){var e,r,n;if(0!==this.negative&&0===t.negative)return this.negative=0,e=this.isub(t),this.negative^=1,this._normSign();if(0===this.negative&&0!==t.negative)return t.negative=0,e=this.isub(t),t.negative=1,e._normSign();this.length>t.length?(r=this,n=t):(r=t,n=this);for(var i=0,a=0;a<n.length;a++)e=(0|r.words[a])+(0|n.words[a])+i,this.words[a]=67108863&e,i=e>>>26;for(;0!==i&&a<r.length;a++)e=(0|r.words[a])+i,this.words[a]=67108863&e,i=e>>>26;if(this.length=r.length,0!==i)this.words[this.length]=i,this.length++;else if(r!==this)for(;a<r.length;a++)this.words[a]=r.words[a];return this},a.prototype.add=function(t){var e;return 0!==t.negative&&0===this.negative?(t.negative=0,e=this.sub(t),t.negative^=1,e):0===t.negative&&0!==this.negative?(this.negative=0,e=t.sub(this),this.negative=1,e):this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},a.prototype.isub=function(t){if(0!==t.negative){t.negative=0;var e=this.iadd(t);return t.negative=1,e._normSign()}if(0!==this.negative)return this.negative=0,this.iadd(t),this.negative=1,this._normSign();var r,n,i=this.cmp(t);if(0===i)return this.negative=0,this.length=1,this.words[0]=0,this;i>0?(r=this,n=t):(r=t,n=this);for(var a=0,o=0;o<n.length;o++)a=(e=(0|r.words[o])-(0|n.words[o])+a)>>26,this.words[o]=67108863&e;for(;0!==a&&o<r.length;o++)a=(e=(0|r.words[o])+a)>>26,this.words[o]=67108863&e;if(0===a&&o<r.length&&r!==this)for(;o<r.length;o++)this.words[o]=r.words[o];return this.length=Math.max(this.length,o),r!==this&&(this.negative=1),this.strip()},a.prototype.sub=function(t){return this.clone().isub(t)};var p=function(t,e,r){var n,i,a,o=t.words,s=e.words,l=r.words,c=0,u=0|o[0],f=8191&u,h=u>>>13,p=0|o[1],d=8191&p,g=p>>>13,v=0|o[2],m=8191&v,y=v>>>13,x=0|o[3],b=8191&x,_=x>>>13,w=0|o[4],k=8191&w,T=w>>>13,A=0|o[5],M=8191&A,S=A>>>13,E=0|o[6],C=8191&E,L=E>>>13,z=0|o[7],O=8191&z,I=z>>>13,D=0|o[8],P=8191&D,R=D>>>13,F=0|o[9],B=8191&F,N=F>>>13,j=0|s[0],V=8191&j,U=j>>>13,H=0|s[1],q=8191&H,G=H>>>13,Y=0|s[2],W=8191&Y,X=Y>>>13,Z=0|s[3],$=8191&Z,J=Z>>>13,K=0|s[4],Q=8191&K,tt=K>>>13,et=0|s[5],rt=8191&et,nt=et>>>13,it=0|s[6],at=8191&it,ot=it>>>13,st=0|s[7],lt=8191&st,ct=st>>>13,ut=0|s[8],ft=8191&ut,ht=ut>>>13,pt=0|s[9],dt=8191&pt,gt=pt>>>13;r.negative=t.negative^e.negative,r.length=19;var vt=(c+(n=Math.imul(f,V))|0)+((8191&(i=(i=Math.imul(f,U))+Math.imul(h,V)|0))<<13)|0;c=((a=Math.imul(h,U))+(i>>>13)|0)+(vt>>>26)|0,vt&=67108863,n=Math.imul(d,V),i=(i=Math.imul(d,U))+Math.imul(g,V)|0,a=Math.imul(g,U);var mt=(c+(n=n+Math.imul(f,q)|0)|0)+((8191&(i=(i=i+Math.imul(f,G)|0)+Math.imul(h,q)|0))<<13)|0;c=((a=a+Math.imul(h,G)|0)+(i>>>13)|0)+(mt>>>26)|0,mt&=67108863,n=Math.imul(m,V),i=(i=Math.imul(m,U))+Math.imul(y,V)|0,a=Math.imul(y,U),n=n+Math.imul(d,q)|0,i=(i=i+Math.imul(d,G)|0)+Math.imul(g,q)|0,a=a+Math.imul(g,G)|0;var yt=(c+(n=n+Math.imul(f,W)|0)|0)+((8191&(i=(i=i+Math.imul(f,X)|0)+Math.imul(h,W)|0))<<13)|0;c=((a=a+Math.imul(h,X)|0)+(i>>>13)|0)+(yt>>>26)|0,yt&=67108863,n=Math.imul(b,V),i=(i=Math.imul(b,U))+Math.imul(_,V)|0,a=Math.imul(_,U),n=n+Math.imul(m,q)|0,i=(i=i+Math.imul(m,G)|0)+Math.imul(y,q)|0,a=a+Math.imul(y,G)|0,n=n+Math.imul(d,W)|0,i=(i=i+Math.imul(d,X)|0)+Math.imul(g,W)|0,a=a+Math.imul(g,X)|0;var xt=(c+(n=n+Math.imul(f,$)|0)|0)+((8191&(i=(i=i+Math.imul(f,J)|0)+Math.imul(h,$)|0))<<13)|0;c=((a=a+Math.imul(h,J)|0)+(i>>>13)|0)+(xt>>>26)|0,xt&=67108863,n=Math.imul(k,V),i=(i=Math.imul(k,U))+Math.imul(T,V)|0,a=Math.imul(T,U),n=n+Math.imul(b,q)|0,i=(i=i+Math.imul(b,G)|0)+Math.imul(_,q)|0,a=a+Math.imul(_,G)|0,n=n+Math.imul(m,W)|0,i=(i=i+Math.imul(m,X)|0)+Math.imul(y,W)|0,a=a+Math.imul(y,X)|0,n=n+Math.imul(d,$)|0,i=(i=i+Math.imul(d,J)|0)+Math.imul(g,$)|0,a=a+Math.imul(g,J)|0;var bt=(c+(n=n+Math.imul(f,Q)|0)|0)+((8191&(i=(i=i+Math.imul(f,tt)|0)+Math.imul(h,Q)|0))<<13)|0;c=((a=a+Math.imul(h,tt)|0)+(i>>>13)|0)+(bt>>>26)|0,bt&=67108863,n=Math.imul(M,V),i=(i=Math.imul(M,U))+Math.imul(S,V)|0,a=Math.imul(S,U),n=n+Math.imul(k,q)|0,i=(i=i+Math.imul(k,G)|0)+Math.imul(T,q)|0,a=a+Math.imul(T,G)|0,n=n+Math.imul(b,W)|0,i=(i=i+Math.imul(b,X)|0)+Math.imul(_,W)|0,a=a+Math.imul(_,X)|0,n=n+Math.imul(m,$)|0,i=(i=i+Math.imul(m,J)|0)+Math.imul(y,$)|0,a=a+Math.imul(y,J)|0,n=n+Math.imul(d,Q)|0,i=(i=i+Math.imul(d,tt)|0)+Math.imul(g,Q)|0,a=a+Math.imul(g,tt)|0;var _t=(c+(n=n+Math.imul(f,rt)|0)|0)+((8191&(i=(i=i+Math.imul(f,nt)|0)+Math.imul(h,rt)|0))<<13)|0;c=((a=a+Math.imul(h,nt)|0)+(i>>>13)|0)+(_t>>>26)|0,_t&=67108863,n=Math.imul(C,V),i=(i=Math.imul(C,U))+Math.imul(L,V)|0,a=Math.imul(L,U),n=n+Math.imul(M,q)|0,i=(i=i+Math.imul(M,G)|0)+Math.imul(S,q)|0,a=a+Math.imul(S,G)|0,n=n+Math.imul(k,W)|0,i=(i=i+Math.imul(k,X)|0)+Math.imul(T,W)|0,a=a+Math.imul(T,X)|0,n=n+Math.imul(b,$)|0,i=(i=i+Math.imul(b,J)|0)+Math.imul(_,$)|0,a=a+Math.imul(_,J)|0,n=n+Math.imul(m,Q)|0,i=(i=i+Math.imul(m,tt)|0)+Math.imul(y,Q)|0,a=a+Math.imul(y,tt)|0,n=n+Math.imul(d,rt)|0,i=(i=i+Math.imul(d,nt)|0)+Math.imul(g,rt)|0,a=a+Math.imul(g,nt)|0;var wt=(c+(n=n+Math.imul(f,at)|0)|0)+((8191&(i=(i=i+Math.imul(f,ot)|0)+Math.imul(h,at)|0))<<13)|0;c=((a=a+Math.imul(h,ot)|0)+(i>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(O,V),i=(i=Math.imul(O,U))+Math.imul(I,V)|0,a=Math.imul(I,U),n=n+Math.imul(C,q)|0,i=(i=i+Math.imul(C,G)|0)+Math.imul(L,q)|0,a=a+Math.imul(L,G)|0,n=n+Math.imul(M,W)|0,i=(i=i+Math.imul(M,X)|0)+Math.imul(S,W)|0,a=a+Math.imul(S,X)|0,n=n+Math.imul(k,$)|0,i=(i=i+Math.imul(k,J)|0)+Math.imul(T,$)|0,a=a+Math.imul(T,J)|0,n=n+Math.imul(b,Q)|0,i=(i=i+Math.imul(b,tt)|0)+Math.imul(_,Q)|0,a=a+Math.imul(_,tt)|0,n=n+Math.imul(m,rt)|0,i=(i=i+Math.imul(m,nt)|0)+Math.imul(y,rt)|0,a=a+Math.imul(y,nt)|0,n=n+Math.imul(d,at)|0,i=(i=i+Math.imul(d,ot)|0)+Math.imul(g,at)|0,a=a+Math.imul(g,ot)|0;var kt=(c+(n=n+Math.imul(f,lt)|0)|0)+((8191&(i=(i=i+Math.imul(f,ct)|0)+Math.imul(h,lt)|0))<<13)|0;c=((a=a+Math.imul(h,ct)|0)+(i>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(P,V),i=(i=Math.imul(P,U))+Math.imul(R,V)|0,a=Math.imul(R,U),n=n+Math.imul(O,q)|0,i=(i=i+Math.imul(O,G)|0)+Math.imul(I,q)|0,a=a+Math.imul(I,G)|0,n=n+Math.imul(C,W)|0,i=(i=i+Math.imul(C,X)|0)+Math.imul(L,W)|0,a=a+Math.imul(L,X)|0,n=n+Math.imul(M,$)|0,i=(i=i+Math.imul(M,J)|0)+Math.imul(S,$)|0,a=a+Math.imul(S,J)|0,n=n+Math.imul(k,Q)|0,i=(i=i+Math.imul(k,tt)|0)+Math.imul(T,Q)|0,a=a+Math.imul(T,tt)|0,n=n+Math.imul(b,rt)|0,i=(i=i+Math.imul(b,nt)|0)+Math.imul(_,rt)|0,a=a+Math.imul(_,nt)|0,n=n+Math.imul(m,at)|0,i=(i=i+Math.imul(m,ot)|0)+Math.imul(y,at)|0,a=a+Math.imul(y,ot)|0,n=n+Math.imul(d,lt)|0,i=(i=i+Math.imul(d,ct)|0)+Math.imul(g,lt)|0,a=a+Math.imul(g,ct)|0;var Tt=(c+(n=n+Math.imul(f,ft)|0)|0)+((8191&(i=(i=i+Math.imul(f,ht)|0)+Math.imul(h,ft)|0))<<13)|0;c=((a=a+Math.imul(h,ht)|0)+(i>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(B,V),i=(i=Math.imul(B,U))+Math.imul(N,V)|0,a=Math.imul(N,U),n=n+Math.imul(P,q)|0,i=(i=i+Math.imul(P,G)|0)+Math.imul(R,q)|0,a=a+Math.imul(R,G)|0,n=n+Math.imul(O,W)|0,i=(i=i+Math.imul(O,X)|0)+Math.imul(I,W)|0,a=a+Math.imul(I,X)|0,n=n+Math.imul(C,$)|0,i=(i=i+Math.imul(C,J)|0)+Math.imul(L,$)|0,a=a+Math.imul(L,J)|0,n=n+Math.imul(M,Q)|0,i=(i=i+Math.imul(M,tt)|0)+Math.imul(S,Q)|0,a=a+Math.imul(S,tt)|0,n=n+Math.imul(k,rt)|0,i=(i=i+Math.imul(k,nt)|0)+Math.imul(T,rt)|0,a=a+Math.imul(T,nt)|0,n=n+Math.imul(b,at)|0,i=(i=i+Math.imul(b,ot)|0)+Math.imul(_,at)|0,a=a+Math.imul(_,ot)|0,n=n+Math.imul(m,lt)|0,i=(i=i+Math.imul(m,ct)|0)+Math.imul(y,lt)|0,a=a+Math.imul(y,ct)|0,n=n+Math.imul(d,ft)|0,i=(i=i+Math.imul(d,ht)|0)+Math.imul(g,ft)|0,a=a+Math.imul(g,ht)|0;var At=(c+(n=n+Math.imul(f,dt)|0)|0)+((8191&(i=(i=i+Math.imul(f,gt)|0)+Math.imul(h,dt)|0))<<13)|0;c=((a=a+Math.imul(h,gt)|0)+(i>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(B,q),i=(i=Math.imul(B,G))+Math.imul(N,q)|0,a=Math.imul(N,G),n=n+Math.imul(P,W)|0,i=(i=i+Math.imul(P,X)|0)+Math.imul(R,W)|0,a=a+Math.imul(R,X)|0,n=n+Math.imul(O,$)|0,i=(i=i+Math.imul(O,J)|0)+Math.imul(I,$)|0,a=a+Math.imul(I,J)|0,n=n+Math.imul(C,Q)|0,i=(i=i+Math.imul(C,tt)|0)+Math.imul(L,Q)|0,a=a+Math.imul(L,tt)|0,n=n+Math.imul(M,rt)|0,i=(i=i+Math.imul(M,nt)|0)+Math.imul(S,rt)|0,a=a+Math.imul(S,nt)|0,n=n+Math.imul(k,at)|0,i=(i=i+Math.imul(k,ot)|0)+Math.imul(T,at)|0,a=a+Math.imul(T,ot)|0,n=n+Math.imul(b,lt)|0,i=(i=i+Math.imul(b,ct)|0)+Math.imul(_,lt)|0,a=a+Math.imul(_,ct)|0,n=n+Math.imul(m,ft)|0,i=(i=i+Math.imul(m,ht)|0)+Math.imul(y,ft)|0,a=a+Math.imul(y,ht)|0;var Mt=(c+(n=n+Math.imul(d,dt)|0)|0)+((8191&(i=(i=i+Math.imul(d,gt)|0)+Math.imul(g,dt)|0))<<13)|0;c=((a=a+Math.imul(g,gt)|0)+(i>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(B,W),i=(i=Math.imul(B,X))+Math.imul(N,W)|0,a=Math.imul(N,X),n=n+Math.imul(P,$)|0,i=(i=i+Math.imul(P,J)|0)+Math.imul(R,$)|0,a=a+Math.imul(R,J)|0,n=n+Math.imul(O,Q)|0,i=(i=i+Math.imul(O,tt)|0)+Math.imul(I,Q)|0,a=a+Math.imul(I,tt)|0,n=n+Math.imul(C,rt)|0,i=(i=i+Math.imul(C,nt)|0)+Math.imul(L,rt)|0,a=a+Math.imul(L,nt)|0,n=n+Math.imul(M,at)|0,i=(i=i+Math.imul(M,ot)|0)+Math.imul(S,at)|0,a=a+Math.imul(S,ot)|0,n=n+Math.imul(k,lt)|0,i=(i=i+Math.imul(k,ct)|0)+Math.imul(T,lt)|0,a=a+Math.imul(T,ct)|0,n=n+Math.imul(b,ft)|0,i=(i=i+Math.imul(b,ht)|0)+Math.imul(_,ft)|0,a=a+Math.imul(_,ht)|0;var St=(c+(n=n+Math.imul(m,dt)|0)|0)+((8191&(i=(i=i+Math.imul(m,gt)|0)+Math.imul(y,dt)|0))<<13)|0;c=((a=a+Math.imul(y,gt)|0)+(i>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(B,$),i=(i=Math.imul(B,J))+Math.imul(N,$)|0,a=Math.imul(N,J),n=n+Math.imul(P,Q)|0,i=(i=i+Math.imul(P,tt)|0)+Math.imul(R,Q)|0,a=a+Math.imul(R,tt)|0,n=n+Math.imul(O,rt)|0,i=(i=i+Math.imul(O,nt)|0)+Math.imul(I,rt)|0,a=a+Math.imul(I,nt)|0,n=n+Math.imul(C,at)|0,i=(i=i+Math.imul(C,ot)|0)+Math.imul(L,at)|0,a=a+Math.imul(L,ot)|0,n=n+Math.imul(M,lt)|0,i=(i=i+Math.imul(M,ct)|0)+Math.imul(S,lt)|0,a=a+Math.imul(S,ct)|0,n=n+Math.imul(k,ft)|0,i=(i=i+Math.imul(k,ht)|0)+Math.imul(T,ft)|0,a=a+Math.imul(T,ht)|0;var Et=(c+(n=n+Math.imul(b,dt)|0)|0)+((8191&(i=(i=i+Math.imul(b,gt)|0)+Math.imul(_,dt)|0))<<13)|0;c=((a=a+Math.imul(_,gt)|0)+(i>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(B,Q),i=(i=Math.imul(B,tt))+Math.imul(N,Q)|0,a=Math.imul(N,tt),n=n+Math.imul(P,rt)|0,i=(i=i+Math.imul(P,nt)|0)+Math.imul(R,rt)|0,a=a+Math.imul(R,nt)|0,n=n+Math.imul(O,at)|0,i=(i=i+Math.imul(O,ot)|0)+Math.imul(I,at)|0,a=a+Math.imul(I,ot)|0,n=n+Math.imul(C,lt)|0,i=(i=i+Math.imul(C,ct)|0)+Math.imul(L,lt)|0,a=a+Math.imul(L,ct)|0,n=n+Math.imul(M,ft)|0,i=(i=i+Math.imul(M,ht)|0)+Math.imul(S,ft)|0,a=a+Math.imul(S,ht)|0;var Ct=(c+(n=n+Math.imul(k,dt)|0)|0)+((8191&(i=(i=i+Math.imul(k,gt)|0)+Math.imul(T,dt)|0))<<13)|0;c=((a=a+Math.imul(T,gt)|0)+(i>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(B,rt),i=(i=Math.imul(B,nt))+Math.imul(N,rt)|0,a=Math.imul(N,nt),n=n+Math.imul(P,at)|0,i=(i=i+Math.imul(P,ot)|0)+Math.imul(R,at)|0,a=a+Math.imul(R,ot)|0,n=n+Math.imul(O,lt)|0,i=(i=i+Math.imul(O,ct)|0)+Math.imul(I,lt)|0,a=a+Math.imul(I,ct)|0,n=n+Math.imul(C,ft)|0,i=(i=i+Math.imul(C,ht)|0)+Math.imul(L,ft)|0,a=a+Math.imul(L,ht)|0;var Lt=(c+(n=n+Math.imul(M,dt)|0)|0)+((8191&(i=(i=i+Math.imul(M,gt)|0)+Math.imul(S,dt)|0))<<13)|0;c=((a=a+Math.imul(S,gt)|0)+(i>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(B,at),i=(i=Math.imul(B,ot))+Math.imul(N,at)|0,a=Math.imul(N,ot),n=n+Math.imul(P,lt)|0,i=(i=i+Math.imul(P,ct)|0)+Math.imul(R,lt)|0,a=a+Math.imul(R,ct)|0,n=n+Math.imul(O,ft)|0,i=(i=i+Math.imul(O,ht)|0)+Math.imul(I,ft)|0,a=a+Math.imul(I,ht)|0;var zt=(c+(n=n+Math.imul(C,dt)|0)|0)+((8191&(i=(i=i+Math.imul(C,gt)|0)+Math.imul(L,dt)|0))<<13)|0;c=((a=a+Math.imul(L,gt)|0)+(i>>>13)|0)+(zt>>>26)|0,zt&=67108863,n=Math.imul(B,lt),i=(i=Math.imul(B,ct))+Math.imul(N,lt)|0,a=Math.imul(N,ct),n=n+Math.imul(P,ft)|0,i=(i=i+Math.imul(P,ht)|0)+Math.imul(R,ft)|0,a=a+Math.imul(R,ht)|0;var Ot=(c+(n=n+Math.imul(O,dt)|0)|0)+((8191&(i=(i=i+Math.imul(O,gt)|0)+Math.imul(I,dt)|0))<<13)|0;c=((a=a+Math.imul(I,gt)|0)+(i>>>13)|0)+(Ot>>>26)|0,Ot&=67108863,n=Math.imul(B,ft),i=(i=Math.imul(B,ht))+Math.imul(N,ft)|0,a=Math.imul(N,ht);var It=(c+(n=n+Math.imul(P,dt)|0)|0)+((8191&(i=(i=i+Math.imul(P,gt)|0)+Math.imul(R,dt)|0))<<13)|0;c=((a=a+Math.imul(R,gt)|0)+(i>>>13)|0)+(It>>>26)|0,It&=67108863;var Dt=(c+(n=Math.imul(B,dt))|0)+((8191&(i=(i=Math.imul(B,gt))+Math.imul(N,dt)|0))<<13)|0;return c=((a=Math.imul(N,gt))+(i>>>13)|0)+(Dt>>>26)|0,Dt&=67108863,l[0]=vt,l[1]=mt,l[2]=yt,l[3]=xt,l[4]=bt,l[5]=_t,l[6]=wt,l[7]=kt,l[8]=Tt,l[9]=At,l[10]=Mt,l[11]=St,l[12]=Et,l[13]=Ct,l[14]=Lt,l[15]=zt,l[16]=Ot,l[17]=It,l[18]=Dt,0!==c&&(l[19]=c,r.length++),r};function d(t,e,r){return(new g).mulp(t,e,r)}function g(t,e){this.x=t,this.y=e}Math.imul||(p=h),a.prototype.mulTo=function(t,e){var r=this.length+t.length;return 10===this.length&&10===t.length?p(this,t,e):r<63?h(this,t,e):r<1024?function(t,e,r){r.negative=e.negative^t.negative,r.length=t.length+e.length;for(var n=0,i=0,a=0;a<r.length-1;a++){var o=i;i=0;for(var s=67108863&n,l=Math.min(a,e.length-1),c=Math.max(0,a-t.length+1);c<=l;c++){var u=a-c,f=(0|t.words[u])*(0|e.words[c]),h=67108863&f;s=67108863&(h=h+s|0),i+=(o=(o=o+(f/67108864|0)|0)+(h>>>26)|0)>>>26,o&=67108863}r.words[a]=s,n=o,o=i}return 0!==n?r.words[a]=n:r.length--,r.strip()}(this,t,e):d(this,t,e)},g.prototype.makeRBT=function(t){for(var e=new Array(t),r=a.prototype._countBits(t)-1,n=0;n<t;n++)e[n]=this.revBin(n,r,t);return e},g.prototype.revBin=function(t,e,r){if(0===t||t===r-1)return t;for(var n=0,i=0;i<e;i++)n|=(1&t)<<e-i-1,t>>=1;return n},g.prototype.permute=function(t,e,r,n,i,a){for(var o=0;o<a;o++)n[o]=e[t[o]],i[o]=r[t[o]]},g.prototype.transform=function(t,e,r,n,i,a){this.permute(a,t,e,r,n,i);for(var o=1;o<i;o<<=1)for(var s=o<<1,l=Math.cos(2*Math.PI/s),c=Math.sin(2*Math.PI/s),u=0;u<i;u+=s)for(var f=l,h=c,p=0;p<o;p++){var d=r[u+p],g=n[u+p],v=r[u+p+o],m=n[u+p+o],y=f*v-h*m;m=f*m+h*v,v=y,r[u+p]=d+v,n[u+p]=g+m,r[u+p+o]=d-v,n[u+p+o]=g-m,p!==s&&(y=l*f-c*h,h=l*h+c*f,f=y)}},g.prototype.guessLen13b=function(t,e){var r=1|Math.max(e,t),n=1&r,i=0;for(r=r/2|0;r;r>>>=1)i++;return 1<<i+1+n},g.prototype.conjugate=function(t,e,r){if(!(r<=1))for(var n=0;n<r/2;n++){var i=t[n];t[n]=t[r-n-1],t[r-n-1]=i,i=e[n],e[n]=-e[r-n-1],e[r-n-1]=-i}},g.prototype.normalize13b=function(t,e){for(var r=0,n=0;n<e/2;n++){var i=8192*Math.round(t[2*n+1]/e)+Math.round(t[2*n]/e)+r;t[n]=67108863&i,r=i<67108864?0:i/67108864|0}return t},g.prototype.convert13b=function(t,e,r,i){for(var a=0,o=0;o<e;o++)a+=0|t[o],r[2*o]=8191&a,a>>>=13,r[2*o+1]=8191&a,a>>>=13;for(o=2*e;o<i;++o)r[o]=0;n(0===a),n(0==(-8192&a))},g.prototype.stub=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=0;return e},g.prototype.mulp=function(t,e,r){var n=2*this.guessLen13b(t.length,e.length),i=this.makeRBT(n),a=this.stub(n),o=new Array(n),s=new Array(n),l=new Array(n),c=new Array(n),u=new Array(n),f=new Array(n),h=r.words;h.length=n,this.convert13b(t.words,t.length,o,n),this.convert13b(e.words,e.length,c,n),this.transform(o,a,s,l,n,i),this.transform(c,a,u,f,n,i);for(var p=0;p<n;p++){var d=s[p]*u[p]-l[p]*f[p];l[p]=s[p]*f[p]+l[p]*u[p],s[p]=d}return this.conjugate(s,l,n),this.transform(s,l,h,a,n,i),this.conjugate(h,a,n),this.normalize13b(h,n),r.negative=t.negative^e.negative,r.length=t.length+e.length,r.strip()},a.prototype.mul=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},a.prototype.mulf=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),d(this,t,e)},a.prototype.imul=function(t){return this.clone().mulTo(t,this)},a.prototype.imuln=function(t){n(\"number\"==typeof t),n(t<67108864);for(var e=0,r=0;r<this.length;r++){var i=(0|this.words[r])*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[r]=67108863&a}return 0!==e&&(this.words[r]=e,this.length++),this},a.prototype.muln=function(t){return this.clone().imuln(t)},a.prototype.sqr=function(){return this.mul(this)},a.prototype.isqr=function(){return this.imul(this.clone())},a.prototype.pow=function(t){var e=function(t){for(var e=new Array(t.bitLength()),r=0;r<e.length;r++){var n=r/26|0,i=r%26;e[r]=(t.words[n]&1<<i)>>>i}return e}(t);if(0===e.length)return new a(1);for(var r=this,n=0;n<e.length&&0===e[n];n++,r=r.sqr());if(++n<e.length)for(var i=r.sqr();n<e.length;n++,i=i.sqr())0!==e[n]&&(r=r.mul(i));return r},a.prototype.iushln=function(t){n(\"number\"==typeof t&&t>=0);var e,r=t%26,i=(t-r)/26,a=67108863>>>26-r<<26-r;if(0!==r){var o=0;for(e=0;e<this.length;e++){var s=this.words[e]&a,l=(0|this.words[e])-s<<r;this.words[e]=l|o,o=s>>>26-r}o&&(this.words[e]=o,this.length++)}if(0!==i){for(e=this.length-1;e>=0;e--)this.words[e+i]=this.words[e];for(e=0;e<i;e++)this.words[e]=0;this.length+=i}return this.strip()},a.prototype.ishln=function(t){return n(0===this.negative),this.iushln(t)},a.prototype.iushrn=function(t,e,r){var i;n(\"number\"==typeof t&&t>=0),i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<<a,l=r;if(i-=o,i=Math.max(0,i),l){for(var c=0;c<o;c++)l.words[c]=this.words[c];l.length=o}if(0===o);else if(this.length>o)for(this.length-=o,c=0;c<this.length;c++)this.words[c]=this.words[c+o];else this.words[0]=0,this.length=1;var u=0;for(c=this.length-1;c>=0&&(0!==u||c>=i);c--){var f=0|this.words[c];this.words[c]=u<<26-a|f>>>a,u=f&s}return l&&0!==u&&(l.words[l.length++]=u),0===this.length&&(this.words[0]=0,this.length=1),this.strip()},a.prototype.ishrn=function(t,e,r){return n(0===this.negative),this.iushrn(t,e,r)},a.prototype.shln=function(t){return this.clone().ishln(t)},a.prototype.ushln=function(t){return this.clone().iushln(t)},a.prototype.shrn=function(t){return this.clone().ishrn(t)},a.prototype.ushrn=function(t){return this.clone().iushrn(t)},a.prototype.testn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26,i=1<<e;return!(this.length<=r)&&!!(this.words[r]&i)},a.prototype.imaskn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26;if(n(0===this.negative,\"imaskn works only with positive numbers\"),this.length<=r)return this;if(0!==e&&r++,this.length=Math.min(r,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},a.prototype.maskn=function(t){return this.clone().imaskn(t)},a.prototype.iaddn=function(t){return n(\"number\"==typeof t),n(t<67108864),t<0?this.isubn(-t):0!==this.negative?1===this.length&&(0|this.words[0])<t?(this.words[0]=t-(0|this.words[0]),this.negative=0,this):(this.negative=0,this.isubn(t),this.negative=1,this):this._iaddn(t)},a.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},a.prototype.isubn=function(t){if(n(\"number\"==typeof t),n(t<67108864),t<0)return this.iaddn(-t);if(0!==this.negative)return this.negative=0,this.iaddn(t),this.negative=1,this;if(this.words[0]-=t,1===this.length&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},a.prototype.addn=function(t){return this.clone().iaddn(t)},a.prototype.subn=function(t){return this.clone().isubn(t)},a.prototype.iabs=function(){return this.negative=0,this},a.prototype.abs=function(){return this.clone().iabs()},a.prototype._ishlnsubmul=function(t,e,r){var i,a,o=t.length+r;this._expand(o);var s=0;for(i=0;i<t.length;i++){a=(0|this.words[i+r])+s;var l=(0|t.words[i])*e;s=((a-=67108863&l)>>26)-(l/67108864|0),this.words[i+r]=67108863&a}for(;i<this.length-r;i++)s=(a=(0|this.words[i+r])+s)>>26,this.words[i+r]=67108863&a;if(0===s)return this.strip();for(n(-1===s),s=0,i=0;i<this.length;i++)s=(a=-(0|this.words[i])+s)>>26,this.words[i]=67108863&a;return this.negative=1,this.strip()},a.prototype._wordDiv=function(t,e){var r=(this.length,t.length),n=this.clone(),i=t,o=0|i.words[i.length-1];0!==(r=26-this._countBits(o))&&(i=i.ushln(r),n.iushln(r),o=0|i.words[i.length-1]);var s,l=n.length-i.length;if(\"mod\"!==e){(s=new a(null)).length=l+1,s.words=new Array(s.length);for(var c=0;c<s.length;c++)s.words[c]=0}var u=n.clone()._ishlnsubmul(i,1,l);0===u.negative&&(n=u,s&&(s.words[l]=1));for(var f=l-1;f>=0;f--){var h=67108864*(0|n.words[i.length+f])+(0|n.words[i.length+f-1]);for(h=Math.min(h/o|0,67108863),n._ishlnsubmul(i,h,f);0!==n.negative;)h--,n.negative=0,n._ishlnsubmul(i,1,f),n.isZero()||(n.negative^=1);s&&(s.words[f]=h)}return s&&s.strip(),n.strip(),\"div\"!==e&&0!==r&&n.iushrn(r),{div:s||null,mod:n}},a.prototype.divmod=function(t,e,r){return n(!t.isZero()),this.isZero()?{div:new a(0),mod:new a(0)}:0!==this.negative&&0===t.negative?(s=this.neg().divmod(t,e),\"mod\"!==e&&(i=s.div.neg()),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.iadd(t)),{div:i,mod:o}):0===this.negative&&0!==t.negative?(s=this.divmod(t.neg(),e),\"mod\"!==e&&(i=s.div.neg()),{div:i,mod:s.mod}):0!=(this.negative&t.negative)?(s=this.neg().divmod(t.neg(),e),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.isub(t)),{div:s.div,mod:o}):t.length>this.length||this.cmp(t)<0?{div:new a(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new a(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new a(this.modn(t.words[0]))}:this._wordDiv(t,e);var i,o,s},a.prototype.div=function(t){return this.divmod(t,\"div\",!1).div},a.prototype.mod=function(t){return this.divmod(t,\"mod\",!1).mod},a.prototype.umod=function(t){return this.divmod(t,\"mod\",!0).mod},a.prototype.divRound=function(t){var e=this.divmod(t);if(e.mod.isZero())return e.div;var r=0!==e.div.negative?e.mod.isub(t):e.mod,n=t.ushrn(1),i=t.andln(1),a=r.cmp(n);return a<0||1===i&&0===a?e.div:0!==e.div.negative?e.div.isubn(1):e.div.iaddn(1)},a.prototype.modn=function(t){n(t<=67108863);for(var e=(1<<26)%t,r=0,i=this.length-1;i>=0;i--)r=(e*r+(0|this.words[i]))%t;return r},a.prototype.idivn=function(t){n(t<=67108863);for(var e=0,r=this.length-1;r>=0;r--){var i=(0|this.words[r])+67108864*e;this.words[r]=i/t|0,e=i%t}return this.strip()},a.prototype.divn=function(t){return this.clone().idivn(t)},a.prototype.egcd=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i=new a(1),o=new a(0),s=new a(0),l=new a(1),c=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++c;for(var u=r.clone(),f=e.clone();!e.isZero();){for(var h=0,p=1;0==(e.words[0]&p)&&h<26;++h,p<<=1);if(h>0)for(e.iushrn(h);h-- >0;)(i.isOdd()||o.isOdd())&&(i.iadd(u),o.isub(f)),i.iushrn(1),o.iushrn(1);for(var d=0,g=1;0==(r.words[0]&g)&&d<26;++d,g<<=1);if(d>0)for(r.iushrn(d);d-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(u),l.isub(f)),s.iushrn(1),l.iushrn(1);e.cmp(r)>=0?(e.isub(r),i.isub(s),o.isub(l)):(r.isub(e),s.isub(i),l.isub(o))}return{a:s,b:l,gcd:r.iushln(c)}},a.prototype._invmp=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i,o=new a(1),s=new a(0),l=r.clone();e.cmpn(1)>0&&r.cmpn(1)>0;){for(var 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0!==(z=q?l.sweepBipartite(t,e,B,N,X,Z,R,K,Y,W):l.sweepBipartite(t,e,R,K,Y,W,B,N,X,Z)))return z}else T(O++,P+1,R,K,B,N,q,-1/0,1/0),T(O++,P+1,B,N,R,K,1^q,-1/0,1/0);if(K<F){var Q=c(t,P,B,N,X,Z),tt=X[I*Q+P],et=g(t,P,Q,N,X,Z,tt);if(et<N&&T(O++,P,K,F,et,N,(4|q)+(G?16:0),tt,H),B<Q&&T(O++,P,K,F,B,Q,(2|q)+(G?16:0),U,tt),Q+1===et){if(void 0!==(z=G?M(t,P,e,K,F,Y,W,Q,X,Z[Q]):A(t,P,e,q,K,F,Y,W,Q,X,Z[Q])))return z}else if(Q<et){var rt;if(G){if(rt=y(t,P,K,F,Y,W,tt),K<rt){var nt=g(t,P,K,rt,Y,W,tt);if(P===t-2){if(K<nt&&void 0!==(z=l.sweepComplete(t,e,K,nt,Y,W,Q,et,X,Z)))return z;if(nt<rt&&void 0!==(z=l.sweepBipartite(t,e,nt,rt,Y,W,Q,et,X,Z)))return z}else K<nt&&T(O++,P+1,K,nt,Q,et,16,-1/0,1/0),nt<rt&&(T(O++,P+1,nt,rt,Q,et,0,-1/0,1/0),T(O++,P+1,Q,et,nt,rt,1,-1/0,1/0))}}else rt=q?x(t,P,K,F,Y,W,tt):y(t,P,K,F,Y,W,tt),K<rt&&(P===t-2?z=q?l.sweepBipartite(t,e,Q,et,X,Z,K,rt,Y,W):l.sweepBipartite(t,e,K,rt,Y,W,Q,et,X,Z):(T(O++,P+1,K,rt,Q,et,q,-1/0,1/0),T(O++,P+1,Q,et,K,rt,1^q,-1/0,1/0)))}}}}};var n=t(\"typedarray-pool\"),i=t(\"bit-twiddle\"),a=t(\"./brute\"),o=a.partial,s=a.full,l=t(\"./sweep\"),c=t(\"./median\"),u=t(\"./partition\"),f=128,h=1<<22,p=1<<22,d=u(\"!(lo>=p0)&&!(p1>=hi)\",[\"p0\",\"p1\"]),g=u(\"lo===p0\",[\"p0\"]),v=u(\"lo<p0\",[\"p0\"]),m=u(\"hi<=p0\",[\"p0\"]),y=u(\"lo<=p0&&p0<=hi\",[\"p0\"]),x=u(\"lo<p0&&p0<=hi\",[\"p0\"]),b=6,_=2,w=n.mallocInt32(1024),k=n.mallocDouble(1024);function T(t,e,r,n,i,a,o,s,l){var c=b*t;w[c]=e,w[c+1]=r,w[c+2]=n,w[c+3]=i,w[c+4]=a,w[c+5]=o;var u=_*t;k[u]=s,k[u+1]=l}function A(t,e,r,n,i,a,o,s,l,c,u){var f=2*t,h=l*f,p=c[h+e];t:for(var d=i,g=i*f;d<a;++d,g+=f){var v=o[g+e],m=o[g+e+t];if(!(p<v||m<p)&&(!n||p!==v)){for(var y,x=s[d],b=e+1;b<t;++b){v=o[g+b],m=o[g+b+t];var _=c[h+b],w=c[h+b+t];if(m<_||w<v)continue t}if(void 0!==(y=n?r(u,x):r(x,u)))return y}}}function M(t,e,r,n,i,a,o,s,l,c){var u=2*t,f=s*u,h=l[f+e];t:for(var p=n,d=n*u;p<i;++p,d+=u){var g=o[p];if(g!==c){var v=a[d+e],m=a[d+e+t];if(!(h<v||m<h)){for(var y=e+1;y<t;++y){v=a[d+y],m=a[d+y+t];var x=l[f+y],b=l[f+y+t];if(m<x||b<v)continue t}var _=r(g,c);if(void 0!==_)return _}}}}},{\"./brute\":90,\"./median\":92,\"./partition\":93,\"./sweep\":95,\"bit-twiddle\":85,\"typedarray-pool\":532}],92:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,o,s,l){if(o<=r+1)return r;var c=r,u=o,f=o+r>>>1,h=2*t,p=f,d=s[h*f+e];for(;c<u;){if(u-c<i){a(t,e,c,u,s,l),d=s[h*f+e];break}var g=u-c,v=Math.random()*g+c|0,m=s[h*v+e],y=Math.random()*g+c|0,x=s[h*y+e],b=Math.random()*g+c|0,_=s[h*b+e];m<=x?_>=x?(p=y,d=x):m>=_?(p=v,d=m):(p=b,d=_):x>=_?(p=y,d=x):_>=m?(p=v,d=m):(p=b,d=_);for(var w=h*(u-1),k=h*p,T=0;T<h;++T,++w,++k){var A=s[w];s[w]=s[k],s[k]=A}var M=l[u-1];l[u-1]=l[p],l[p]=M,p=n(t,e,c,u-1,s,l,d);for(var w=h*(u-1),k=h*p,T=0;T<h;++T,++w,++k){var A=s[w];s[w]=s[k],s[k]=A}var M=l[u-1];if(l[u-1]=l[p],l[p]=M,f<p){for(u=p-1;c<u&&s[h*(u-1)+e]===d;)u-=1;u+=1}else{if(!(p<f))break;for(c=p+1;c<u&&s[h*c+e]===d;)c+=1}}return n(t,e,r,f,s,l,s[h*f+e])};var n=t(\"./partition\")(\"lo<p0\",[\"p0\"]),i=8;function a(t,e,r,n,i,a){for(var o=2*t,s=o*(r+1)+e,l=r+1;l<n;++l,s+=o)for(var c=i[s],u=l,f=o*(l-1);u>r&&i[f+e]>c;--u,f-=o){for(var h=f,p=f+o,d=0;d<o;++d,++h,++p){var g=i[h];i[h]=i[p],i[p]=g}var v=a[u];a[u]=a[u-1],a[u-1]=v}}},{\"./partition\":93}],93:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=\"abcdef\".split(\"\").concat(e),i=[];t.indexOf(\"lo\")>=0&&i.push(\"lo=e[k+n]\");t.indexOf(\"hi\")>=0&&i.push(\"hi=e[k+o]\");return r.push(n.replace(\"_\",i.join()).replace(\"$\",t)),Function.apply(void 0,r)};var n=\"for(var j=2*a,k=j*c,l=k,m=c,n=b,o=a+b,p=c;d>p;++p,k+=j){var _;if($)if(m===p)m+=1,l+=j;else{for(var s=0;j>s;++s){var t=e[k+s];e[k+s]=e[l],e[l++]=t}var u=f[p];f[p]=f[m],f[m++]=u}}return m\"},{}],94:[function(t,e,r){\"use strict\";e.exports=function(t,e){e<=4*n?i(0,e-1,t):function t(e,r,f){var 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r=8*e;p.length<r&&(n.free(p),p=n.mallocDouble(r))},sweepBipartite:function(t,e,r,n,i,f,h,v,m,y){for(var x=0,b=2*t,_=t-1,w=b-1,k=r;k<n;++k){var T=f[k],A=b*k;p[x++]=i[A+_],p[x++]=-(T+1),p[x++]=i[A+w],p[x++]=T}for(var k=h;k<v;++k){var T=y[k]+o,M=b*k;p[x++]=m[M+_],p[x++]=-T,p[x++]=m[M+w],p[x++]=T}var S=x>>>1;a(p,S);for(var E=0,C=0,k=0;k<S;++k){var L=0|p[2*k+1];if(L>=o)d(c,u,C--,L=L-o|0);else if(L>=0)d(s,l,E--,L);else if(L<=-o){L=-L-o|0;for(var z=0;z<E;++z){var O=e(s[z],L);if(void 0!==O)return O}g(c,u,C++,L)}else{L=-L-1|0;for(var z=0;z<C;++z){var O=e(L,c[z]);if(void 0!==O)return O}g(s,l,E++,L)}}},sweepComplete:function(t,e,r,n,i,o,v,m,y,x){for(var b=0,_=2*t,w=t-1,k=_-1,T=r;T<n;++T){var A=o[T]+1<<1,M=_*T;p[b++]=i[M+w],p[b++]=-A,p[b++]=i[M+k],p[b++]=A}for(var T=v;T<m;++T){var A=x[T]+1<<1,S=_*T;p[b++]=y[S+w],p[b++]=1|-A,p[b++]=y[S+k],p[b++]=1|A}var E=b>>>1;a(p,E);for(var C=0,L=0,z=0,T=0;T<E;++T){var O=0|p[2*T+1],I=1&O;if(T<E-1&&O>>1==p[2*T+3]>>1&&(I=2,T+=1),O<0){for(var D=-(O>>1)-1,P=0;P<z;++P){var R=e(f[P],D);if(void 0!==R)return R}if(0!==I)for(var P=0;P<C;++P){var R=e(s[P],D);if(void 0!==R)return R}if(1!==I)for(var P=0;P<L;++P){var R=e(c[P],D);if(void 0!==R)return R}0===I?g(s,l,C++,D):1===I?g(c,u,L++,D):2===I&&g(f,h,z++,D)}else{var D=(O>>1)-1;0===I?d(s,l,C--,D):1===I?d(c,u,L--,D):2===I&&d(f,h,z--,D)}}},scanBipartite:function(t,e,r,n,i,c,u,f,h,v,m,y){var x=0,b=2*t,_=e,w=e+t,k=1,T=1;n?T=o:k=o;for(var A=i;A<c;++A){var M=A+k,S=b*A;p[x++]=u[S+_],p[x++]=-M,p[x++]=u[S+w],p[x++]=M}for(var A=h;A<v;++A){var M=A+T,E=b*A;p[x++]=m[E+_],p[x++]=-M}var C=x>>>1;a(p,C);for(var L=0,A=0;A<C;++A){var z=0|p[2*A+1];if(z<0){var M=-z,O=!1;if(M>=o?(O=!n,M-=o):(O=!!n,M-=1),O)g(s,l,L++,M);else{var I=y[M],D=b*M,P=m[D+e+1],R=m[D+e+1+t];t:for(var F=0;F<L;++F){var B=s[F],N=b*B;if(!(R<u[N+e+1]||u[N+e+1+t]<P)){for(var j=e+2;j<t;++j)if(m[D+j+t]<u[N+j]||u[N+j+t]<m[D+j])continue t;var V,U=f[B];if(void 0!==(V=n?r(I,U):r(U,I)))return V}}}}else d(s,l,L--,z-k)}},scanComplete:function(t,e,r,n,i,l,c,u,f,h,d){for(var g=0,v=2*t,m=e,y=e+t,x=n;x<i;++x){var b=x+o,_=v*x;p[g++]=l[_+m],p[g++]=-b,p[g++]=l[_+y],p[g++]=b}for(var x=u;x<f;++x){var b=x+1,w=v*x;p[g++]=h[w+m],p[g++]=-b}var k=g>>>1;a(p,k);for(var T=0,x=0;x<k;++x){var A=0|p[2*x+1];if(A<0){var b=-A;if(b>=o)s[T++]=b-o;else{var M=d[b-=1],S=v*b,E=h[S+e+1],C=h[S+e+1+t];t:for(var L=0;L<T;++L){var z=s[L],O=c[z];if(O===M)break;var I=v*z;if(!(C<l[I+e+1]||l[I+e+1+t]<E)){for(var D=e+2;D<t;++D)if(h[S+D+t]<l[I+D]||l[I+D+t]<h[S+D])continue t;var P=r(O,M);if(void 0!==P)return P}}}}else{for(var b=A-o,L=T-1;L>=0;--L)if(s[L]===b){for(var D=L+1;D<T;++D)s[D-1]=s[D];break}--T}}}};var n=t(\"typedarray-pool\"),i=t(\"bit-twiddle\"),a=t(\"./sort\"),o=1<<28,s=n.mallocInt32(1024),l=n.mallocInt32(1024),c=n.mallocInt32(1024),u=n.mallocInt32(1024),f=n.mallocInt32(1024),h=n.mallocInt32(1024),p=n.mallocDouble(8192);function d(t,e,r,n){var i=e[n],a=t[r-1];t[i]=a,e[a]=i}function 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c=(a=r.right=o(a)).right=o(a.right),r.right=a.left,a.left=r,a.right=c,a._color=r._color,e._color=i,r._color=i,c._color=i,l(r),l(a),u>1&&((f=t[u-2]).left===r?f.left=a:f.right=a),void(t[u-1]=a);if(a.left&&a.left._color===n)return c=(a=r.right=o(a)).left=o(a.left),r.right=c.left,a.left=c.right,c.left=r,c.right=a,c._color=r._color,r._color=i,a._color=i,e._color=i,l(r),l(a),l(c),u>1&&((f=t[u-2]).left===r?f.left=c:f.right=c),void(t[u-1]=c);if(a._color===i){if(r._color===n)return r._color=i,void(r.right=s(n,a));r.right=s(n,a);continue}a=o(a),r.right=a.left,a.left=r,a._color=r._color,r._color=n,l(r),l(a),u>1&&((f=t[u-2]).left===r?f.left=a:f.right=a),t[u-1]=a,t[u]=r,u+1<t.length?t[u+1]=e:t.push(e),u+=2}else{if((a=r.left).left&&a.left._color===n)return c=(a=r.left=o(a)).left=o(a.left),r.left=a.right,a.right=r,a.left=c,a._color=r._color,e._color=i,r._color=i,c._color=i,l(r),l(a),u>1&&((f=t[u-2]).right===r?f.right=a:f.left=a),void(t[u-1]=a);if(a.right&&a.right._color===n)return c=(a=r.left=o(a)).right=o(a.right),r.left=c.right,a.right=c.left,c.right=r,c.left=a,c._color=r._color,r._color=i,a._color=i,e._color=i,l(r),l(a),l(c),u>1&&((f=t[u-2]).right===r?f.right=c:f.left=c),void(t[u-1]=c);if(a._color===i){if(r._color===n)return r._color=i,void(r.left=s(n,a));r.left=s(n,a);continue}var f;a=o(a),r.left=a.right,a.right=r,a._color=r._color,r._color=n,l(r),l(a),u>1&&((f=t[u-2]).right===r?f.right=a:f.left=a),t[u-1]=a,t[u]=r,u+1<t.length?t[u+1]=e:t.push(e),u+=2}}}(e),g.left===r?g.left=null:g.right=null,new c(this.tree._compare,e[0])},Object.defineProperty(h,\"key\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].key},enumerable:!0}),Object.defineProperty(h,\"value\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].value},enumerable:!0}),Object.defineProperty(h,\"index\",{get:function(){var t=0,e=this._stack;if(0===e.length){var r=this.tree.root;return 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c(this.tree._compare,r[0])},h.prev=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.left)for(e=e.left;e;)t.push(e),e=e.right;else for(t.pop();t.length>0&&t[t.length-1].left===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(h,\"hasPrev\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].left)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].right===t[e])return!0;return!1}})},{}],230:[function(t,e,r){var n=[.9999999999998099,676.5203681218851,-1259.1392167224028,771.3234287776531,-176.6150291621406,12.507343278686905,-.13857109526572012,9984369578019572e-21,1.5056327351493116e-7],i=607/128,a=[.9999999999999971,57.15623566586292,-59.59796035547549,14.136097974741746,-.4919138160976202,3399464998481189e-20,4652362892704858e-20,-9837447530487956e-20,.0001580887032249125,-.00021026444172410488,.00021743961811521265,-.0001643181065367639,8441822398385275e-20,-26190838401581408e-21,36899182659531625e-22];function o(t){if(t<0)return 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r.update(e),r};var n=t(\"./lib/text.js\"),i=t(\"./lib/lines.js\"),a=t(\"./lib/background.js\"),o=t(\"./lib/cube.js\"),s=t(\"./lib/ticks.js\"),l=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]);function c(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function u(t){this.gl=t,this.pixelRatio=1,this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.autoTicks=!0,this.tickSpacing=[1,1,1],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickAlign=[\"auto\",\"auto\",\"auto\"],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[10,10,10],this.lastCubeProps={cubeEdges:[0,0,0],axis:[0,0,0]},this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=\"sans-serif\",this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelAlign=[\"auto\",\"auto\",\"auto\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[10,10,10],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[0,0,0],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!1,!1,!1],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._firstInit=!0,this._text=null,this._lines=null,this._background=a(t)}var f=u.prototype;function h(){this.primalOffset=[0,0,0],this.primalMinor=[0,0,0],this.mirrorOffset=[0,0,0],this.mirrorMinor=[0,0,0]}f.update=function(t){function e(e,r,n){if(n in t){var i,a=t[n],o=this[n];(e?Array.isArray(a)&&Array.isArray(a[0]):Array.isArray(a))?this[n]=i=[r(a[0]),r(a[1]),r(a[2])]:this[n]=i=[r(a),r(a),r(a)];for(var s=0;s<3;++s)if(i[s]!==o[s])return!0}return!1}t=t||{};var r,a=e.bind(this,!1,Number),o=e.bind(this,!1,Boolean),l=e.bind(this,!1,String),c=e.bind(this,!0,function(t){if(Array.isArray(t)){if(3===t.length)return[+t[0],+t[1],+t[2],1];if(4===t.length)return[+t[0],+t[1],+t[2],+t[3]]}return[0,0,0,1]}),u=!1,f=!1;if(\"bounds\"in t)for(var h=t.bounds,p=0;p<2;++p)for(var d=0;d<3;++d)h[p][d]!==this.bounds[p][d]&&(f=!0),this.bounds[p][d]=h[p][d];if(\"ticks\"in t){r=t.ticks,u=!0,this.autoTicks=!1;for(p=0;p<3;++p)this.tickSpacing[p]=0}else a(\"tickSpacing\")&&(this.autoTicks=!0,f=!0);if(this._firstInit&&(\"ticks\"in t||\"tickSpacing\"in t||(this.autoTicks=!0),f=!0,u=!0,this._firstInit=!1),f&&this.autoTicks&&(r=s.create(this.bounds,this.tickSpacing),u=!0),u){for(p=0;p<3;++p)r[p].sort(function(t,e){return t.x-e.x});s.equal(r,this.ticks)?u=!1:this.ticks=r}o(\"tickEnable\"),l(\"tickFont\")&&(u=!0),a(\"tickSize\"),a(\"tickAngle\"),a(\"tickPad\"),c(\"tickColor\");var g=l(\"labels\");l(\"labelFont\")&&(g=!0),o(\"labelEnable\"),a(\"labelSize\"),a(\"labelPad\"),c(\"labelColor\"),o(\"lineEnable\"),o(\"lineMirror\"),a(\"lineWidth\"),c(\"lineColor\"),o(\"lineTickEnable\"),o(\"lineTickMirror\"),a(\"lineTickLength\"),a(\"lineTickWidth\"),c(\"lineTickColor\"),o(\"gridEnable\"),a(\"gridWidth\"),c(\"gridColor\"),o(\"zeroEnable\"),c(\"zeroLineColor\"),a(\"zeroLineWidth\"),o(\"backgroundEnable\"),c(\"backgroundColor\"),this._text?this._text&&(g||u)&&this._text.update(this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont):this._text=n(this.gl,this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont),this._lines&&u&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=i(this.gl,this.bounds,this.ticks))};var p=[new h,new h,new h];function d(t,e,r,n,i){for(var a=t.primalOffset,o=t.primalMinor,s=t.mirrorOffset,l=t.mirrorMinor,c=n[e],u=0;u<3;++u)if(e!==u){var f=a,h=s,p=o,d=l;c&1<<u&&(f=s,h=a,p=l,d=o),f[u]=r[0][u],h[u]=r[1][u],i[u]>0?(p[u]=-1,d[u]=0):(p[u]=0,d[u]=1)}}var g=[0,0,0],v={model:l,view:l,projection:l,_ortho:!1};f.isOpaque=function(){return!0},f.isTransparent=function(){return!1},f.drawTransparent=function(t){};var m=[0,0,0],y=[0,0,0],x=[0,0,0];f.draw=function(t){t=t||v;for(var e=this.gl,r=t.model||l,n=t.view||l,i=t.projection||l,a=this.bounds,s=t._ortho||!1,u=o(r,n,i,a,s),f=u.cubeEdges,h=u.axis,b=n[12],_=n[13],w=n[14],k=n[15],T=(s?2:1)*this.pixelRatio*(i[3]*b+i[7]*_+i[11]*w+i[15]*k)/e.drawingBufferHeight,A=0;A<3;++A)this.lastCubeProps.cubeEdges[A]=f[A],this.lastCubeProps.axis[A]=h[A];var M=p;for(A=0;A<3;++A)d(p[A],A,this.bounds,f,h);e=this.gl;var S,E=g;for(A=0;A<3;++A)this.backgroundEnable[A]?E[A]=h[A]:E[A]=0;this._background.draw(r,n,i,a,E,this.backgroundColor),this._lines.bind(r,n,i,this);for(A=0;A<3;++A){var C=[0,0,0];h[A]>0?C[A]=a[1][A]:C[A]=a[0][A];for(var L=0;L<2;++L){var z=(A+1+L)%3,O=(A+1+(1^L))%3;this.gridEnable[z]&&this._lines.drawGrid(z,O,this.bounds,C,this.gridColor[z],this.gridWidth[z]*this.pixelRatio)}for(L=0;L<2;++L){z=(A+1+L)%3,O=(A+1+(1^L))%3;this.zeroEnable[O]&&Math.min(a[0][O],a[1][O])<=0&&Math.max(a[0][O],a[1][O])>=0&&this._lines.drawZero(z,O,this.bounds,C,this.zeroLineColor[O],this.zeroLineWidth[O]*this.pixelRatio)}}for(A=0;A<3;++A){this.lineEnable[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].primalOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio),this.lineMirror[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].mirrorOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio);var I=c(m,M[A].primalMinor),D=c(y,M[A].mirrorMinor),P=this.lineTickLength;for(L=0;L<3;++L){var R=T/r[5*L];I[L]*=P[L]*R,D[L]*=P[L]*R}this.lineTickEnable[A]&&this._lines.drawAxisTicks(A,M[A].primalOffset,I,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio),this.lineTickMirror[A]&&this._lines.drawAxisTicks(A,M[A].mirrorOffset,D,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio)}this._lines.unbind(),this._text.bind(r,n,i,this.pixelRatio);var F,B;function N(t){(B=[0,0,0])[t]=1}function j(t,e,r){var n=(t+1)%3,i=(t+2)%3,a=e[n],o=e[i],s=r[n],l=r[i];a>0&&l>0?N(n):a>0&&l<0?N(n):a<0&&l>0?N(n):a<0&&l<0?N(n):o>0&&s>0?N(i):o>0&&s<0?N(i):o<0&&s>0?N(i):o<0&&s<0&&N(i)}for(A=0;A<3;++A){var V=M[A].primalMinor,U=M[A].mirrorMinor,H=c(x,M[A].primalOffset);for(L=0;L<3;++L)this.lineTickEnable[A]&&(H[L]+=T*V[L]*Math.max(this.lineTickLength[L],0)/r[5*L]);var q=[0,0,0];if(q[A]=1,this.tickEnable[A]){-3600===this.tickAngle[A]?(this.tickAngle[A]=0,this.tickAlign[A]=\"auto\"):this.tickAlign[A]=-1,F=1,\"auto\"===(S=[this.tickAlign[A],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),B=[0,0,0],j(A,V,U);for(L=0;L<3;++L)H[L]+=T*V[L]*this.tickPad[L]/r[5*L];this._text.drawTicks(A,this.tickSize[A],this.tickAngle[A],H,this.tickColor[A],q,B,S)}if(this.labelEnable[A]){F=0,B=[0,0,0],this.labels[A].length>4&&(N(A),F=1),\"auto\"===(S=[this.labelAlign[A],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]);for(L=0;L<3;++L)H[L]+=T*V[L]*this.labelPad[L]/r[5*L];H[A]+=.5*(a[0][A]+a[1][A]),this._text.drawLabel(A,this.labelSize[A],this.labelAngle[A],H,this.labelColor[A],[0,0,0],B,S)}}this._text.unbind()},f.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},{\"./lib/background.js\":233,\"./lib/cube.js\":234,\"./lib/lines.js\":235,\"./lib/text.js\":237,\"./lib/ticks.js\":238}],233:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=[],r=[],s=0,l=0;l<3;++l)for(var c=(l+1)%3,u=(l+2)%3,f=[0,0,0],h=[0,0,0],p=-1;p<=1;p+=2){r.push(s,s+2,s+1,s+1,s+2,s+3),f[l]=p,h[l]=p;for(var d=-1;d<=1;d+=2){f[c]=d;for(var g=-1;g<=1;g+=2)f[u]=g,e.push(f[0],f[1],f[2],h[0],h[1],h[2]),s+=1}var v=c;c=u,u=v}var m=n(t,new Float32Array(e)),y=n(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),x=i(t,[{buffer:m,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:m,type:t.FLOAT,size:3,offset:12,stride:24}],y),b=a(t);return b.attributes.position.location=0,b.attributes.normal.location=1,new o(t,m,x,b)};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders\").bg;function o(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}var s=o.prototype;s.draw=function(t,e,r,n,i,a){for(var o=!1,s=0;s<3;++s)o=o||i[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:i,colors:a},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),this.vao.unbind(),l.disable(l.POLYGON_OFFSET_FILL)}},s.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders\":236,\"gl-buffer\":240,\"gl-vao\":322}],234:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,a,p){i(s,e,t),i(s,r,s);for(var y=0,x=0;x<2;++x){u[2]=a[x][2];for(var b=0;b<2;++b){u[1]=a[b][1];for(var _=0;_<2;++_)u[0]=a[_][0],h(l[y],u,s),y+=1}}for(var w=-1,x=0;x<8;++x){for(var k=l[x][3],T=0;T<3;++T)c[x][T]=l[x][T]/k;p&&(c[x][2]*=-1),k<0&&(w<0?w=x:c[x][2]<c[w][2]&&(w=x))}if(w<0){w=0;for(var A=0;A<3;++A){for(var M=(A+2)%3,S=(A+1)%3,E=-1,C=-1,L=0;L<2;++L){var z=L<<A,O=z+(L<<M)+(1-L<<S),I=z+(1-L<<M)+(L<<S);o(c[z],c[O],c[I],f)<0||(L?E=1:C=1)}if(E<0||C<0)C>E&&(w|=1<<A);else{for(var L=0;L<2;++L){var z=L<<A,O=z+(L<<M)+(1-L<<S),I=z+(1-L<<M)+(L<<S),D=d([l[z],l[O],l[I],l[z+(1<<M)+(1<<S)]]);L?E=D:C=D}C>E&&(w|=1<<A)}}}for(var P=7^w,R=-1,x=0;x<8;++x)x!==w&&x!==P&&(R<0?R=x:c[R][1]>c[x][1]&&(R=x));for(var F=-1,x=0;x<3;++x){var B=R^1<<x;if(B!==w&&B!==P){F<0&&(F=B);var S=c[B];S[0]<c[F][0]&&(F=B)}}for(var N=-1,x=0;x<3;++x){var B=R^1<<x;if(B!==w&&B!==P&&B!==F){N<0&&(N=B);var S=c[B];S[0]>c[N][0]&&(N=B)}}var j=g;j[0]=j[1]=j[2]=0,j[n.log2(F^R)]=R&F,j[n.log2(R^N)]=R&N;var V=7^N;V===w||V===P?(V=7^F,j[n.log2(N^V)]=V&N):j[n.log2(F^V)]=V&F;for(var U=v,H=w,A=0;A<3;++A)U[A]=H&1<<A?-1:1;return m};var n=t(\"bit-twiddle\"),i=t(\"gl-mat4/multiply\"),a=t(\"split-polygon\"),o=t(\"robust-orientation\"),s=new Array(16),l=new Array(8),c=new Array(8),u=new Array(3),f=[0,0,0];function h(t,e,r){for(var n=0;n<4;++n){t[n]=r[12+n];for(var i=0;i<3;++i)t[n]+=e[i]*r[4*i+n]}}!function(){for(var t=0;t<8;++t)l[t]=[1,1,1,1],c[t]=[1,1,1]}();var p=[[0,0,1,0,0],[0,0,-1,1,0],[0,-1,0,1,0],[0,1,0,1,0],[-1,0,0,1,0],[1,0,0,1,0]];function d(t){for(var e=0;e<p.length;++e)if((t=a.positive(t,p[e])).length<3)return 0;var r=t[0],n=r[0]/r[3],i=r[1]/r[3],o=0;for(e=1;e+1<t.length;++e){var s=t[e],l=t[e+1],c=s[0]/s[3]-n,u=s[1]/s[3]-i,f=l[0]/l[3]-n,h=l[1]/l[3]-i;o+=Math.abs(c*h-u*f)}return o}var g=[1,1,1],v=[0,0,0],m={cubeEdges:g,axis:v}},{\"bit-twiddle\":85,\"gl-mat4/multiply\":266,\"robust-orientation\":497,\"split-polygon\":514}],235:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){var o=[],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[0,0,0];o.push(0,0,1,0,1,1,0,0,-1,0,0,-1,0,1,1,0,1,-1);for(var f=0;f<3;++f){for(var h=o.length/3|0,d=0;d<r[f].length;++d){var g=+r[f][d].x;o.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}var v=o.length/3|0;s[f]=h,l[f]=v-h;for(var h=o.length/3|0,m=0;m<r[f].length;++m){var g=+r[f][m].x;o.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}var v=o.length/3|0;c[f]=h,u[f]=v-h}var y=n(t,new Float32Array(o)),x=i(t,[{buffer:y,type:t.FLOAT,size:3,stride:0,offset:0}]),b=a(t);return b.attributes.position.location=0,new p(t,y,x,b,l,s,u,c)};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders\").line,o=[0,0,0],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[1,1];function f(t){return t[0]=t[1]=t[2]=0,t}function h(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function p(t,e,r,n,i,a,o,s){this.gl=t,this.vertBuffer=e,this.vao=r,this.shader=n,this.tickCount=i,this.tickOffset=a,this.gridCount=o,this.gridOffset=s}var d=p.prototype;d.bind=function(t,e,r){this.shader.bind(),this.shader.uniforms.model=t,this.shader.uniforms.view=e,this.shader.uniforms.projection=r,u[0]=this.gl.drawingBufferWidth,u[1]=this.gl.drawingBufferHeight,this.shader.uniforms.screenShape=u,this.vao.bind()},d.unbind=function(){this.vao.unbind()},d.drawAxisLine=function(t,e,r,n,i){var a=f(s);this.shader.uniforms.majorAxis=s,a[t]=e[1][t]-e[0][t],this.shader.uniforms.minorAxis=a;var o,u=h(c,r);u[t]+=e[0][t],this.shader.uniforms.offset=u,this.shader.uniforms.lineWidth=i,this.shader.uniforms.color=n,(o=f(l))[(t+2)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6),(o=f(l))[(t+1)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6)},d.drawAxisTicks=function(t,e,r,n,i){if(this.tickCount[t]){var a=f(o);a[t]=1,this.shader.uniforms.majorAxis=a,this.shader.uniforms.offset=e,this.shader.uniforms.minorAxis=r,this.shader.uniforms.color=n,this.shader.uniforms.lineWidth=i;var s=f(l);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}},d.drawGrid=function(t,e,r,n,i,a){if(this.gridCount[t]){var u=f(s);u[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=u;var p=h(c,n);p[e]+=r[0][e],this.shader.uniforms.offset=p;var d=f(o);d[t]=1,this.shader.uniforms.majorAxis=d;var g=f(l);g[t]=1,this.shader.uniforms.screenAxis=g,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])}},d.drawZero=function(t,e,r,n,i,a){var o=f(s);this.shader.uniforms.majorAxis=o,o[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=o;var u=h(c,n);u[t]+=r[0][t],this.shader.uniforms.offset=u;var p=f(l);p[e]=1,this.shader.uniforms.screenAxis=p,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,6)},d.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},{\"./shaders\":236,\"gl-buffer\":240,\"gl-vao\":322}],236:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, majorAxis, minorAxis, screenAxis;\\nuniform float lineWidth;\\nuniform vec2 screenShape;\\n\\nvec3 project(vec3 p) {\\n vec4 pp = projection * view * model * vec4(p, 1.0);\\n return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nvoid main() {\\n vec3 major = position.x * majorAxis;\\n vec3 minor = position.y * minorAxis;\\n\\n vec3 vPosition = major + minor + offset;\\n vec3 pPosition = project(vPosition);\\n vec3 offset = project(vPosition + screenAxis * position.z);\\n\\n vec2 screen = normalize((offset - pPosition).xy * screenShape) / screenShape;\\n\\n gl_Position = vec4(pPosition + vec3(0.5 * screen * lineWidth, 0), 1.0);\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n gl_FragColor = color;\\n}\"]);r.line=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"}])};var s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, axis, alignDir, alignOpt;\\nuniform float scale, angle, pixelScale;\\nuniform vec2 resolution;\\n\\nvec3 project(vec3 p) {\\n vec4 pp = projection * view * model * vec4(p, 1.0);\\n return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nfloat computeViewAngle(vec3 a, vec3 b) {\\n vec3 A = project(a);\\n vec3 B = project(b);\\n\\n return atan(\\n (B.y - A.y) * resolution.y,\\n (B.x - A.x) * resolution.x\\n );\\n}\\n\\nconst float PI = 3.141592;\\nconst float TWO_PI = 2.0 * PI;\\nconst float HALF_PI = 0.5 * PI;\\nconst float ONE_AND_HALF_PI = 1.5 * PI;\\n\\nint option = int(floor(alignOpt.x + 0.001));\\nfloat hv_ratio = alignOpt.y;\\nbool enableAlign = (alignOpt.z != 0.0);\\n\\nfloat mod_angle(float a) {\\n return mod(a, PI);\\n}\\n\\nfloat positive_angle(float a) {\\n return mod_angle((a < 0.0) ?\\n a + TWO_PI :\\n a\\n );\\n}\\n\\nfloat look_upwards(float a) {\\n float b = positive_angle(a);\\n return ((b > HALF_PI) && (b <= ONE_AND_HALF_PI)) ?\\n b - PI :\\n b;\\n}\\n\\nfloat look_horizontal_or_vertical(float a, float ratio) {\\n // ratio controls the ratio between being horizontal to (vertical + horizontal)\\n // if ratio is set to 0.5 then it is 50%, 50%.\\n // when using a higher ratio e.g. 0.75 the result would\\n // likely be more horizontal than vertical.\\n\\n float b = positive_angle(a);\\n\\n return\\n (b < ( ratio) * HALF_PI) ? 0.0 :\\n (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI :\\n (b < (2.0 + ratio) * HALF_PI) ? 0.0 :\\n (b < (4.0 - ratio) * HALF_PI) ? HALF_PI :\\n 0.0;\\n}\\n\\nfloat roundTo(float a, float b) {\\n return float(b * floor((a + 0.5 * b) / b));\\n}\\n\\nfloat look_round_n_directions(float a, int n) {\\n float b = positive_angle(a);\\n float div = TWO_PI / float(n);\\n float c = roundTo(b, div);\\n return look_upwards(c);\\n}\\n\\nfloat applyAlignOption(float rawAngle, float delta) {\\n return\\n (option > 2) ? look_round_n_directions(rawAngle + delta, option) : // option 3-n: round to n directions\\n (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical\\n (option == 1) ? rawAngle + delta : // use free angle, and flip to align with one direction of the axis\\n (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards\\n (option ==-1) ? 0.0 : // useful for backward compatibility, all texts remains horizontal\\n rawAngle; // otherwise return back raw input angle\\n}\\n\\nbool isAxisTitle = (axis.x == 0.0) &&\\n (axis.y == 0.0) &&\\n (axis.z == 0.0);\\n\\nvoid main() {\\n //Compute world offset\\n float axisDistance = position.z;\\n vec3 dataPosition = axisDistance * axis + offset;\\n\\n float beta = angle; // i.e. user defined attributes for each tick\\n\\n float axisAngle;\\n float clipAngle;\\n float flip;\\n\\n if (enableAlign) {\\n axisAngle = (isAxisTitle) ? HALF_PI :\\n computeViewAngle(dataPosition, dataPosition + axis);\\n clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir);\\n\\n axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0;\\n clipAngle += (sin(clipAngle) < 0.0) ? PI : 0.0;\\n\\n flip = (dot(vec2(cos(axisAngle), sin(axisAngle)),\\n vec2(sin(clipAngle),-cos(clipAngle))) > 0.0) ? 1.0 : 0.0;\\n\\n beta += applyAlignOption(clipAngle, flip * PI);\\n }\\n\\n //Compute plane offset\\n vec2 planeCoord = position.xy * pixelScale;\\n\\n mat2 planeXform = scale * mat2(\\n cos(beta), sin(beta),\\n -sin(beta), cos(beta)\\n );\\n\\n vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\\n\\n //Compute clip position\\n vec3 clipPosition = project(dataPosition);\\n\\n //Apply text offset in clip coordinates\\n clipPosition += vec3(viewOffset, 0.0);\\n\\n //Done\\n gl_Position = vec4(clipPosition, 1.0);\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n gl_FragColor = color;\\n}\"]);r.text=function(t){return i(t,s,l,null,[{name:\"position\",type:\"vec3\"}])};var c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 enable;\\nuniform vec3 bounds[2];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n\\n vec3 signAxis = sign(bounds[1] - bounds[0]);\\n\\n vec3 realNormal = signAxis * normal;\\n\\n if(dot(realNormal, enable) > 0.0) {\\n vec3 minRange = min(bounds[0], bounds[1]);\\n vec3 maxRange = max(bounds[0], bounds[1]);\\n vec3 nPosition = mix(minRange, maxRange, 0.5 * (position + 1.0));\\n gl_Position = projection * view * model * vec4(nPosition, 1.0);\\n } else {\\n gl_Position = vec4(0,0,0,0);\\n }\\n\\n colorChannel = abs(realNormal);\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 colors[3];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n gl_FragColor = colorChannel.x * colors[0] +\\n colorChannel.y * colors[1] +\\n colorChannel.z * colors[2];\\n}\"]);r.bg=function(t){return i(t,c,u,null,[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}])}},{\"gl-shader\":300,glslify:404}],237:[function(t,e,r){(function(r){\"use strict\";e.exports=function(t,e,r,a,s,l){var u=n(t),f=i(t,[{buffer:u,size:3}]),h=o(t);h.attributes.position.location=0;var p=new c(t,h,u,f);return p.update(e,r,a,s,l),p};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"vectorize-text\"),o=t(\"./shaders\").text,s=window||r.global||{},l=s.__TEXT_CACHE||{};s.__TEXT_CACHE={};function c(t,e,r,n){this.gl=t,this.shader=e,this.buffer=r,this.vao=n,this.tickOffset=this.tickCount=this.labelOffset=this.labelCount=null}var u=c.prototype,f=[0,0];u.bind=function(t,e,r,n){this.vao.bind(),this.shader.bind();var i=this.shader.uniforms;i.model=t,i.view=e,i.projection=r,i.pixelScale=n,f[0]=this.gl.drawingBufferWidth,f[1]=this.gl.drawingBufferHeight,this.shader.uniforms.resolution=f},u.unbind=function(){this.vao.unbind()},u.update=function(t,e,r,n,i){var o=[];function s(t,e,r,n,i,s){var c=l[r];c||(c=l[r]={});var u=c[e];u||(u=c[e]=function(t,e){try{return a(t,e)}catch(e){return console.warn('error vectorizing text:\"'+t+'\" 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strict\";function n(t,e){var r=t+\"\",n=r.indexOf(\".\"),i=0;n>=0&&(i=r.length-n-1);var a=Math.pow(10,i),o=Math.round(t*e*a),s=o+\"\";if(s.indexOf(\"e\")>=0)return s;var l=o/a,c=o%a;o<0?(l=0|-Math.ceil(l),c=0|-c):(l=0|Math.floor(l),c|=0);var u=\"\"+l;if(o<0&&(u=\"-\"+u),i){for(var f=\"\"+c;f.length<i;)f=\"0\"+f;return u+\".\"+f}return u}r.create=function(t,e){for(var r=[],i=0;i<3;++i){for(var a=[],o=(t[0][i],t[1][i],0);o*e[i]<=t[1][i];++o)a.push({x:o*e[i],text:n(e[i],o)});for(var o=-1;o*e[i]>=t[0][i];--o)a.push({x:o*e[i],text:n(e[i],o)});r.push(a)}return r},r.equal=function(t,e){for(var r=0;r<3;++r){if(t[r].length!==e[r].length)return!1;for(var n=0;n<t[r].length;++n){var i=t[r][n],a=e[r][n];if(i.x!==a.x||i.text!==a.text||i.font!==a.font||i.fontColor!==a.fontColor||i.fontSize!==a.fontSize||i.dx!==a.dx||i.dy!==a.dy)return!1}}return!0}},{}],239:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,l,f){var h=e.model||c,p=e.view||c,m=e.projection||c,y=e._ortho||!1,x=t.bounds,b=(f=f||a(h,p,m,x,y)).axis;o(u,p,h),o(u,m,u);for(var _=g,w=0;w<3;++w)_[w].lo=1/0,_[w].hi=-1/0,_[w].pixelsPerDataUnit=1/0;var k=n(s(u,u));s(u,u);for(var T=0;T<3;++T){var A=(T+1)%3,M=(T+2)%3,S=v;t:for(var w=0;w<2;++w){var E=[];if(b[T]<0!=!!w){S[T]=x[w][T];for(var C=0;C<2;++C){S[A]=x[C^w][A];for(var L=0;L<2;++L)S[M]=x[L^C^w][M],E.push(S.slice())}for(var z=y?5:4,C=z;C===z;++C){if(0===E.length)continue t;E=i.positive(E,k[C])}for(var C=0;C<E.length;++C)for(var M=E[C],O=d(v,u,M,r,l),L=0;L<3;++L)_[L].lo=Math.min(_[L].lo,M[L]),_[L].hi=Math.max(_[L].hi,M[L]),L!==T&&(_[L].pixelsPerDataUnit=Math.min(_[L].pixelsPerDataUnit,Math.abs(O[L])))}}}return _};var n=t(\"extract-frustum-planes\"),i=t(\"split-polygon\"),a=t(\"./lib/cube.js\"),o=t(\"gl-mat4/multiply\"),s=t(\"gl-mat4/transpose\"),l=t(\"gl-vec4/transformMat4\"),c=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]),u=new Float32Array(16);function f(t,e,r){this.lo=t,this.hi=e,this.pixelsPerDataUnit=r}var h=[0,0,0,1],p=[0,0,0,1];function d(t,e,r,n,i){for(var a=0;a<3;++a){for(var o=h,s=p,c=0;c<3;++c)s[c]=o[c]=r[c];s[3]=o[3]=1,s[a]+=1,l(s,s,e),s[3]<0&&(t[a]=1/0),o[a]-=1,l(o,o,e),o[3]<0&&(t[a]=1/0);var u=(o[0]/o[3]-s[0]/s[3])*n,f=(o[1]/o[3]-s[1]/s[3])*i;t[a]=.25*Math.sqrt(u*u+f*f)}return t}var g=[new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0)],v=[0,0,0]},{\"./lib/cube.js\":234,\"extract-frustum-planes\":223,\"gl-mat4/multiply\":266,\"gl-mat4/transpose\":275,\"gl-vec4/transformMat4\":393,\"split-polygon\":514}],240:[function(t,e,r){\"use strict\";var n=t(\"typedarray-pool\"),i=t(\"ndarray-ops\"),a=t(\"ndarray\"),o=[\"uint8\",\"uint8_clamped\",\"uint16\",\"uint32\",\"int8\",\"int16\",\"int32\",\"float32\"];function s(t,e,r,n,i){this.gl=t,this.type=e,this.handle=r,this.length=n,this.usage=i}var l=s.prototype;function c(t,e,r,n,i,a){var o=i.length*i.BYTES_PER_ELEMENT;if(a<0)return t.bufferData(e,i,n),o;if(o+a>r)throw new Error(\"gl-buffer: If resizing buffer, must not specify offset\");return t.bufferSubData(e,a,i),r}function u(t,e){for(var r=n.malloc(t.length,e),i=t.length,a=0;a<i;++a)r[a]=t[a];return r}l.bind=function(){this.gl.bindBuffer(this.type,this.handle)},l.unbind=function(){this.gl.bindBuffer(this.type,null)},l.dispose=function(){this.gl.deleteBuffer(this.handle)},l.update=function(t,e){if(\"number\"!=typeof e&&(e=-1),this.bind(),\"object\"==typeof t&&\"undefined\"!=typeof t.shape){var r=t.dtype;if(o.indexOf(r)<0&&(r=\"float32\"),this.type===this.gl.ELEMENT_ARRAY_BUFFER)r=gl.getExtension(\"OES_element_index_uint\")&&\"uint16\"!==r?\"uint32\":\"uint16\";if(r===t.dtype&&function(t,e){for(var r=1,n=e.length-1;n>=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}(t.shape,t.stride))0===t.offset&&t.data.length===t.shape[0]?this.length=c(this.gl,this.type,this.length,this.usage,t.data,e):this.length=c(this.gl,this.type,this.length,this.usage,t.data.subarray(t.offset,t.shape[0]),e);else{var s=n.malloc(t.size,r),l=a(s,t.shape);i.assign(l,t),this.length=c(this.gl,this.type,this.length,this.usage,e<0?s:s.subarray(0,t.size),e),n.free(s)}}else if(Array.isArray(t)){var f;f=this.type===this.gl.ELEMENT_ARRAY_BUFFER?u(t,\"uint16\"):u(t,\"float32\"),this.length=c(this.gl,this.type,this.length,this.usage,e<0?f:f.subarray(0,t.length),e),n.free(f)}else if(\"object\"==typeof t&&\"number\"==typeof t.length)this.length=c(this.gl,this.type,this.length,this.usage,t,e);else{if(\"number\"!=typeof t&&void 0!==t)throw new Error(\"gl-buffer: Invalid data type\");if(e>=0)throw new Error(\"gl-buffer: Cannot specify offset when resizing buffer\");(t|=0)<=0&&(t=1),this.gl.bufferData(this.type,0|t,this.usage),this.length=t}},e.exports=function(t,e,r,n){if(r=r||t.ARRAY_BUFFER,n=n||t.DYNAMIC_DRAW,r!==t.ARRAY_BUFFER&&r!==t.ELEMENT_ARRAY_BUFFER)throw new Error(\"gl-buffer: Invalid type for webgl buffer, must be either gl.ARRAY_BUFFER or gl.ELEMENT_ARRAY_BUFFER\");if(n!==t.DYNAMIC_DRAW&&n!==t.STATIC_DRAW&&n!==t.STREAM_DRAW)throw new Error(\"gl-buffer: Invalid usage for buffer, must be either gl.DYNAMIC_DRAW, gl.STATIC_DRAW or gl.STREAM_DRAW\");var i=t.createBuffer(),a=new s(t,r,i,0,n);return a.update(e),a}},{ndarray:445,\"ndarray-ops\":439,\"typedarray-pool\":532}],241:[function(t,e,r){\"use strict\";var n=t(\"gl-vec3\"),i=function(t,e){for(var r=0;r<t.length;r++)if(t[r]>=e)return r-1;return r},a=n.create(),o=n.create(),s=function(t,e,r){return t<e?e:t>r?r:t},l=function(t,e,r,l){var c=t[0],u=t[1],f=t[2],h=r[0].length,p=r[1].length,d=r[2].length,g=i(r[0],c),v=i(r[1],u),m=i(r[2],f),y=g+1,x=v+1,b=m+1;if(l&&(g=s(g,0,h-1),y=s(y,0,h-1),v=s(v,0,p-1),x=s(x,0,p-1),m=s(m,0,d-1),b=s(b,0,d-1)),g<0||v<0||m<0||y>=h||x>=p||b>=d)return n.create();var _=(c-r[0][g])/(r[0][y]-r[0][g]),w=(u-r[1][v])/(r[1][x]-r[1][v]),k=(f-r[2][m])/(r[2][b]-r[2][m]);(_<0||_>1||isNaN(_))&&(_=0),(w<0||w>1||isNaN(w))&&(w=0),(k<0||k>1||isNaN(k))&&(k=0);var T=m*h*p,A=b*h*p,M=v*h,S=x*h,E=g,C=y,L=e[M+T+E],z=e[M+T+C],O=e[S+T+E],I=e[S+T+C],D=e[M+A+E],P=e[M+A+C],R=e[S+A+E],F=e[S+A+C],B=n.create();return n.lerp(B,L,z,_),n.lerp(a,O,I,_),n.lerp(B,B,a,w),n.lerp(a,D,P,_),n.lerp(o,R,F,_),n.lerp(a,a,o,w),n.lerp(B,B,a,k),B};e.exports=function(t,e){var r;r=t.positions?t.positions:function(t){for(var e=t[0],r=t[1],n=t[2],i=[],a=0;a<n.length;a++)for(var o=0;o<r.length;o++)for(var s=0;s<e.length;s++)i.push([n[a],r[o],e[s]]);return i}(t.meshgrid);var i=t.meshgrid,a=t.vectors,o={positions:[],vertexIntensity:[],vertexIntensityBounds:t.vertexIntensityBounds,vertexNormals:[],vectors:[],cells:[],coneOffset:t.coneOffset,colormap:t.colormap};if(0===t.positions.length)return e&&(e[0]=[0,0,0],e[1]=[0,0,0]),o;for(var s=0,c=1/0,u=-1/0,f=1/0,h=-1/0,p=1/0,d=-1/0,g=null,v=null,m=[],y=1/0,x=0;x<r.length;x++){var b,_=r[x];c=Math.min(_[0],c),u=Math.max(_[0],u),f=Math.min(_[1],f),h=Math.max(_[1],h),p=Math.min(_[2],p),d=Math.max(_[2],d),b=i?l(_,a,i,!0):a[x],n.length(b)>s&&(s=n.length(b)),x&&(y=Math.min(y,2*n.distance(g,_)/(n.length(v)+n.length(b)))),g=_,v=b,m.push(b)}var w=[c,f,p],k=[u,h,d];e&&(e[0]=w,e[1]=k),0===s&&(s=1);var T=1/s;isFinite(y)&&!isNaN(y)||(y=1),o.vectorScale=y;var A=function(t,e,r){var i=n.create();return void 0!==t&&n.set(i,t,e,r),i}(0,1,0),M=t.coneSize||.5;t.absoluteConeSize&&(M=t.absoluteConeSize*T),o.coneScale=M;x=0;for(var S=0;x<r.length;x++)for(var E=(_=r[x])[0],C=_[1],L=_[2],z=m[x],O=n.length(z)*T,I=0;I<8;I++){o.positions.push([E,C,L,S++]),o.positions.push([E,C,L,S++]),o.positions.push([E,C,L,S++]),o.positions.push([E,C,L,S++]),o.positions.push([E,C,L,S++]),o.positions.push([E,C,L,S++]),o.vectors.push(z),o.vectors.push(z),o.vectors.push(z),o.vectors.push(z),o.vectors.push(z),o.vectors.push(z),o.vertexIntensity.push(O,O,O),o.vertexIntensity.push(O,O,O),o.vertexNormals.push(A,A,A),o.vertexNormals.push(A,A,A);var D=o.positions.length;o.cells.push([D-6,D-5,D-4],[D-3,D-2,D-1])}return o},e.exports.createConeMesh=t(\"./lib/conemesh\")},{\"./lib/conemesh\":242,\"gl-vec3\":341}],242:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"normals\"),l=t(\"gl-mat4/multiply\"),c=t(\"gl-mat4/invert\"),u=t(\"ndarray\"),f=t(\"colormap\"),h=t(\"simplicial-complex-contour\"),p=t(\"typedarray-pool\"),d=t(\"./shaders\"),g=d.meshShader,v=d.pickShader,m=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function y(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,v,y,x,b,_,w,k,T){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.pickShader=n,this.trianglePositions=i,this.triangleVectors=a,this.triangleColors=s,this.triangleNormals=c,this.triangleUVs=l,this.triangleIds=o,this.triangleVAO=u,this.triangleCount=0,this.lineWidth=1,this.edgePositions=f,this.edgeColors=p,this.edgeUVs=d,this.edgeIds=h,this.edgeVAO=g,this.edgeCount=0,this.pointPositions=v,this.pointColors=x,this.pointUVs=b,this.pointSizes=_,this.pointIds=y,this.pointVAO=w,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=k,this.contourVAO=T,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.coneScale=2,this.vectorScale=1,this.coneOffset=.25,this._model=m,this._view=m,this._projection=m,this._resolution=[1,1]}var x=y.prototype;function b(t){var e=n(t,v.vertex,v.fragment,null,v.attributes);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.vector.location=5,e}x.isOpaque=function(){return this.opacity>=1},x.isTransparent=function(){return this.opacity<1},x.pickSlots=1,x.setPickBase=function(t){this.pickId=t},x.highlight=function(t){if(t&&this.contourEnable){for(var e=h(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=p.mallocFloat32(6*a),s=0,l=0;l<a;++l)for(var c=r[l],u=0;u<2;++u){var f=c[0];2===c.length&&(f=c[u]);for(var d=n[f][0],g=n[f][1],v=i[f],m=1-v,y=this.positions[d],x=this.positions[g],b=0;b<3;++b)o[s++]=v*y[b]+m*x[b]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),p.free(o)}else this.contourCount=0},x.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),\"opacity\"in t&&(this.opacity=t.opacity),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),void 0!==t.vectorScale&&(this.vectorScale=t.vectorScale),void 0!==t.coneScale&&(this.coneScale=t.coneScale),void 0!==t.coneOffset&&(this.coneOffset=t.coneOffset),t.texture?(this.texture.dispose(),this.texture=o(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t){for(var e=f({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var i=e[n],a=0;a<3;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return u(r,[256,256,4],[4,0,1])}(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions,i=t.vectors;if(n&&r&&i){var a=[],l=[],c=[],h=[],p=[],d=[],g=[],v=[],m=[],y=[],x=[],b=[],_=[],w=[],k=[];this.cells=r,this.positions=n;var T=t.vertexNormals,A=t.cellNormals,M=void 0===t.vertexNormalsEpsilon?1e-6:t.vertexNormalsEpsilon,S=void 0===t.faceNormalsEpsilon?1e-6:t.faceNormalsEpsilon;t.useFacetNormals&&!A&&(A=s.faceNormals(r,n,S)),A||T||(T=s.vertexNormals(r,n,M));var E=t.vertexColors,C=t.cellColors,L=t.meshColor||[1,1,1,1],z=t.vertexUVs,O=t.vertexIntensity,I=t.cellUVs,D=t.cellIntensity,P=1/0,R=-1/0;if(!z&&!I)if(O)if(t.vertexIntensityBounds)P=+t.vertexIntensityBounds[0],R=+t.vertexIntensityBounds[1];else for(var F=0;F<O.length;++F){var B=O[F];P=Math.min(P,B),R=Math.max(R,B)}else if(D)for(F=0;F<D.length;++F){B=D[F];P=Math.min(P,B),R=Math.max(R,B)}else for(F=0;F<n.length;++F){B=n[F][2];P=Math.min(P,B),R=Math.max(R,B)}this.intensity=O||(D?function(t,e,r){for(var n=new Array(e),i=0;i<e;++i)n[i]=0;var a=t.length;for(i=0;i<a;++i)for(var o=t[i],s=0;s<o.length;++s)n[o[s]]=r[i];return n}(r,n.length,D):function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n));var N=t.pointSizes,j=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(F=0;F<n.length;++F)for(var V=n[F],U=0;U<3;++U)!isNaN(V[U])&&isFinite(V[U])&&(this.bounds[0][U]=Math.min(this.bounds[0][U],V[U]),this.bounds[1][U]=Math.max(this.bounds[1][U],V[U]));var H=0,q=0,G=0;t:for(F=0;F<r.length;++F){var Y=r[F];switch(Y.length){case 1:for(V=n[X=Y[0]],U=0;U<3;++U)if(isNaN(V[U])||!isFinite(V[U]))continue t;x.push(V[0],V[1],V[2],V[3]),3===(Z=E?E[X]:C?C[F]:L).length?b.push(Z[0],Z[1],Z[2],1):b.push(Z[0],Z[1],Z[2],Z[3]),$=z?z[X]:O?[(O[X]-P)/(R-P),0]:I?I[F]:D?[(D[F]-P)/(R-P),0]:[(V[2]-P)/(R-P),0],_.push($[0],$[1]),N?w.push(N[X]):w.push(j),k.push(F),G+=1;break;case 2:for(U=0;U<2;++U){V=n[X=Y[U]];for(var W=0;W<3;++W)if(isNaN(V[W])||!isFinite(V[W]))continue t}for(U=0;U<2;++U){V=n[X=Y[U]];g.push(V[0],V[1],V[2]),3===(Z=E?E[X]:C?C[F]:L).length?v.push(Z[0],Z[1],Z[2],1):v.push(Z[0],Z[1],Z[2],Z[3]),$=z?z[X]:O?[(O[X]-P)/(R-P),0]:I?I[F]:D?[(D[F]-P)/(R-P),0]:[(V[2]-P)/(R-P),0],m.push($[0],$[1]),y.push(F)}q+=1;break;case 3:for(U=0;U<3;++U)for(V=n[X=Y[U]],W=0;W<3;++W)if(isNaN(V[W])||!isFinite(V[W]))continue t;for(U=0;U<3;++U){var X;V=n[X=Y[2-U]];a.push(V[0],V[1],V[2],V[3]);var Z,$,J,K=i[X];l.push(K[0],K[1],K[2]),3===(Z=E?E[X]:C?C[F]:L).length?c.push(Z[0],Z[1],Z[2],1):c.push(Z[0],Z[1],Z[2],Z[3]),$=z?z[X]:O?[(O[X]-P)/(R-P),0]:I?I[F]:D?[(D[F]-P)/(R-P),0]:[(V[2]-P)/(R-P),0],p.push($[0],$[1]),J=T?T[X]:A[F],h.push(J[0],J[1],J[2]),d.push(F)}H+=1}}this.pointCount=G,this.edgeCount=q,this.triangleCount=H,this.pointPositions.update(x),this.pointColors.update(b),this.pointUVs.update(_),this.pointSizes.update(w),this.pointIds.update(new Uint32Array(k)),this.edgePositions.update(g),this.edgeColors.update(v),this.edgeUVs.update(m),this.edgeIds.update(new Uint32Array(y)),this.trianglePositions.update(a),this.triangleVectors.update(l),this.triangleColors.update(c),this.triangleUVs.update(p),this.triangleNormals.update(h),this.triangleIds.update(new Uint32Array(d))}},x.drawTransparent=x.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||m,n=t.view||m,i=t.projection||m,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,inverseModel:m.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,contourColor:this.contourColor,texture:0};s.inverseModel=c(s.inverseModel,s.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);l(u,s.view,s.model),l(u,s.projection,u),c(u,u);for(o=0;o<3;++o)s.eyePosition[o]=u[12+o]/u[15];var f=u[15];for(o=0;o<3;++o)f+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var h=u[12+o],p=0;p<3;++p)h+=u[4*p+o]*this.lightPosition[p];s.lightPosition[o]=h/f}if(this.triangleCount>0){var d=this.triShader;d.bind(),d.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}},x.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||m,n=t.view||m,i=t.projection||m,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},l=this.pickShader;l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind())},x.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions[r[1]].slice(0,3);return{index:Math.floor(r[1]/48),position:n,dataCoordinate:n}},x.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose()},e.exports=function(t,e){1===arguments.length&&(t=(e=t).gl);var r=e.triShader||function(t){var e=n(t,g.vertex,g.fragment,null,g.attributes);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.vector.location=5,e}(t),s=b(t),l=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));l.generateMipmap(),l.minFilter=t.LINEAR_MIPMAP_LINEAR,l.magFilter=t.LINEAR;var c=i(t),f=i(t),h=i(t),p=i(t),d=i(t),v=i(t),m=a(t,[{buffer:c,type:t.FLOAT,size:4},{buffer:v,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:h,type:t.FLOAT,size:4},{buffer:p,type:t.FLOAT,size:2},{buffer:d,type:t.FLOAT,size:3},{buffer:f,type:t.FLOAT,size:3}]),x=i(t),_=i(t),w=i(t),k=i(t),T=a(t,[{buffer:x,type:t.FLOAT,size:3},{buffer:k,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:_,type:t.FLOAT,size:4},{buffer:w,type:t.FLOAT,size:2}]),A=i(t),M=i(t),S=i(t),E=i(t),C=i(t),L=a(t,[{buffer:A,type:t.FLOAT,size:3},{buffer:C,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:M,type:t.FLOAT,size:4},{buffer:S,type:t.FLOAT,size:2},{buffer:E,type:t.FLOAT,size:1}]),z=i(t),O=new y(t,l,r,s,c,f,v,h,p,d,m,x,k,_,w,T,A,C,M,S,E,L,z,a(t,[{buffer:z,type:t.FLOAT,size:3}]));return O.update(e),O}},{\"./shaders\":243,colormap:119,\"gl-buffer\":240,\"gl-mat4/invert\":264,\"gl-mat4/multiply\":266,\"gl-shader\":300,\"gl-texture2d\":317,\"gl-vao\":322,ndarray:445,normals:448,\"simplicial-complex-contour\":505,\"typedarray-pool\":532}],243:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n // Return up-vector for only-z vector.\\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\\n // Assign z = 0, x = -b, y = a:\\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n return normalize(vec3(-v.y, v.x, 0.0));\\n } else {\\n return normalize(vec3(0.0, v.z, -v.y));\\n }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n// segment + 0 top vertex\\n// segment + 1 perimeter vertex a+1\\n// segment + 2 perimeter vertex a\\n// segment + 3 center base vertex\\n// segment + 4 perimeter vertex a\\n// segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n const float segmentCount = 8.0;\\n\\n float index = rawIndex - floor(rawIndex /\\n (segmentCount * 6.0)) *\\n (segmentCount * 6.0);\\n\\n float segment = floor(0.001 + index/6.0);\\n float segmentIndex = index - (segment*6.0);\\n\\n normal = -normalize(d);\\n\\n if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n return mix(vec3(0.0), -d, coneOffset);\\n }\\n\\n float nextAngle = (\\n (segmentIndex > 0.99 && segmentIndex < 1.01) ||\\n (segmentIndex > 4.99 && segmentIndex < 5.01)\\n ) ? 1.0 : 0.0;\\n float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n vec3 v2 = v1 - d;\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d)*0.25;\\n vec3 y = v * sin(angle) * length(d)*0.25;\\n vec3 v3 = v2 + x + y;\\n if (segmentIndex < 3.0) {\\n vec3 tx = u * sin(angle);\\n vec3 ty = v * -cos(angle);\\n vec3 tangent = tx + ty;\\n normal = normalize(cross(v3 - v1, tangent));\\n }\\n\\n if (segmentIndex == 0.0) {\\n return mix(d, vec3(0.0), coneOffset);\\n }\\n return v3;\\n}\\n\\nattribute vec3 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\nuniform float vectorScale;\\nuniform float coneScale;\\n\\nuniform float coneOffset;\\n\\nuniform mat4 model\\n , view\\n , projection\\n , inverseModel;\\nuniform vec3 eyePosition\\n , lightPosition;\\n\\nvarying vec3 f_normal\\n , f_lightDirection\\n , f_eyeDirection\\n , f_data\\n , f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n // Scale the vector magnitude to stay constant with\\n // model & view changes.\\n vec3 normal;\\n vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\\n vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * conePosition;\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\\n f_normal = normalize((vec4(normal,0.0) * inverseModel).xyz);\\n\\n // vec4 m_position = model * vec4(conePosition, 1.0);\\n vec4 t_position = view * conePosition;\\n gl_Position = projection * t_position;\\n\\n f_color = color;\\n f_data = conePosition.xyz;\\n f_position = position.xyz;\\n f_uv = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness,\\n float fresnel) {\\n\\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n //Half angle vector\\n vec3 H = normalize(lightDirection + viewDirection);\\n\\n //Geometric term\\n float NdotH = max(dot(surfaceNormal, H), 0.0);\\n float VdotH = max(dot(viewDirection, H), 0.000001);\\n float LdotH = max(dot(lightDirection, H), 0.000001);\\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n float G = min(1.0, min(G1, G2));\\n \\n //Distribution term\\n float D = beckmannDistribution(NdotH, roughness);\\n\\n //Fresnel term\\n float F = pow(1.0 - VdotN, fresnel);\\n\\n //Multiply terms and done\\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n , fresnel\\n , kambient\\n , kdiffuse\\n , kspecular\\n , opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n , f_lightDirection\\n , f_eyeDirection\\n , f_data\\n , f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n vec3 N = normalize(f_normal);\\n vec3 L = normalize(f_lightDirection);\\n vec3 V = normalize(f_eyeDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\\n\\n gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n // Return up-vector for only-z vector.\\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\\n // Assign z = 0, x = -b, y = a:\\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n return normalize(vec3(-v.y, v.x, 0.0));\\n } else {\\n return normalize(vec3(0.0, v.z, -v.y));\\n }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n// segment + 0 top vertex\\n// segment + 1 perimeter vertex a+1\\n// segment + 2 perimeter vertex a\\n// segment + 3 center base vertex\\n// segment + 4 perimeter vertex a\\n// segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n const float segmentCount = 8.0;\\n\\n float index = rawIndex - floor(rawIndex /\\n (segmentCount * 6.0)) *\\n (segmentCount * 6.0);\\n\\n float segment = floor(0.001 + index/6.0);\\n float segmentIndex = index - (segment*6.0);\\n\\n normal = -normalize(d);\\n\\n if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n return mix(vec3(0.0), -d, coneOffset);\\n }\\n\\n float nextAngle = (\\n (segmentIndex > 0.99 && segmentIndex < 1.01) ||\\n (segmentIndex > 4.99 && segmentIndex < 5.01)\\n ) ? 1.0 : 0.0;\\n float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n vec3 v2 = v1 - d;\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d)*0.25;\\n vec3 y = v * sin(angle) * length(d)*0.25;\\n vec3 v3 = v2 + x + y;\\n if (segmentIndex < 3.0) {\\n vec3 tx = u * sin(angle);\\n vec3 ty = v * -cos(angle);\\n vec3 tangent = tx + ty;\\n normal = normalize(cross(v3 - v1, tangent));\\n }\\n\\n if (segmentIndex == 0.0) {\\n return mix(d, vec3(0.0), coneOffset);\\n }\\n return v3;\\n}\\n\\nattribute vec3 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nuniform float vectorScale;\\nuniform float coneScale;\\nuniform float coneOffset;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n vec3 normal;\\n vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\\n vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n gl_Position = projection * view * conePosition;\\n f_id = id;\\n f_position = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n gl_FragColor = vec4(pickId, 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4466:\"NUM_COMPRESSED_TEXTURE_FORMATS\",34467:\"COMPRESSED_TEXTURE_FORMATS\",34660:\"BUFFER_SIZE\",34661:\"BUFFER_USAGE\",34816:\"STENCIL_BACK_FUNC\",34817:\"STENCIL_BACK_FAIL\",34818:\"STENCIL_BACK_PASS_DEPTH_FAIL\",34819:\"STENCIL_BACK_PASS_DEPTH_PASS\",34877:\"BLEND_EQUATION_ALPHA\",34921:\"MAX_VERTEX_ATTRIBS\",34922:\"VERTEX_ATTRIB_ARRAY_NORMALIZED\",34930:\"MAX_TEXTURE_IMAGE_UNITS\",34962:\"ARRAY_BUFFER\",34963:\"ELEMENT_ARRAY_BUFFER\",34964:\"ARRAY_BUFFER_BINDING\",34965:\"ELEMENT_ARRAY_BUFFER_BINDING\",34975:\"VERTEX_ATTRIB_ARRAY_BUFFER_BINDING\",35040:\"STREAM_DRAW\",35044:\"STATIC_DRAW\",35048:\"DYNAMIC_DRAW\",35632:\"FRAGMENT_SHADER\",35633:\"VERTEX_SHADER\",35660:\"MAX_VERTEX_TEXTURE_IMAGE_UNITS\",35661:\"MAX_COMBINED_TEXTURE_IMAGE_UNITS\",35663:\"SHADER_TYPE\",35664:\"FLOAT_VEC2\",35665:\"FLOAT_VEC3\",35666:\"FLOAT_VEC4\",35667:\"INT_VEC2\",35668:\"INT_VEC3\",35669:\"INT_VEC4\",35670:\"BOOL\",35671:\"BOOL_VEC2\",35672:\"BOOL_VEC3\",35673:\"BOOL_VEC4\",35674:\"FLOAT_MAT2\",35675:\"FLOAT_MAT3\",35676:\"FLOAT_MAT4\",35678:\"SAMPLER_2D\",35680:\"SAMPLER_CUBE\",35712:\"DELETE_STATUS\",35713:\"COMPILE_STATUS\",35714:\"LINK_STATUS\",35715:\"VALIDATE_STATUS\",35716:\"INFO_LOG_LENGTH\",35717:\"ATTACHED_SHADERS\",35718:\"ACTIVE_UNIFORMS\",35719:\"ACTIVE_UNIFORM_MAX_LENGTH\",35720:\"SHADER_SOURCE_LENGTH\",35721:\"ACTIVE_ATTRIBUTES\",35722:\"ACTIVE_ATTRIBUTE_MAX_LENGTH\",35724:\"SHADING_LANGUAGE_VERSION\",35725:\"CURRENT_PROGRAM\",36003:\"STENCIL_BACK_REF\",36004:\"STENCIL_BACK_VALUE_MASK\",36005:\"STENCIL_BACK_WRITEMASK\",36006:\"FRAMEBUFFER_BINDING\",36007:\"RENDERBUFFER_BINDING\",36048:\"FRAMEBUFFER_ATTACHMENT_OBJECT_TYPE\",36049:\"FRAMEBUFFER_ATTACHMENT_OBJECT_NAME\",36050:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_LEVEL\",36051:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_CUBE_MAP_FACE\",36053:\"FRAMEBUFFER_COMPLETE\",36054:\"FRAMEBUFFER_INCOMPLETE_ATTACHMENT\",36055:\"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT\",36057:\"FRAMEBUFFER_INCOMPLETE_DIMENSIONS\",36061:\"FRAMEBUFFER_UNSUPPORTED\",36064:\"COLOR_ATTACHMENT0\",36096:\"DEPTH_ATTACHMENT\",36128:\"STENCIL_ATTACHMENT\",36160:\"FRAMEBUFFER\",36161:\"RENDERBUFFER\",36162:\"RENDERBUFFER_WIDTH\",36163:\"RENDERBUFFER_HEIGHT\",36164:\"RENDERBUFFER_INTERNAL_FORMAT\",36168:\"STENCIL_INDEX8\",36176:\"RENDERBUFFER_RED_SIZE\",36177:\"RENDERBUFFER_GREEN_SIZE\",36178:\"RENDERBUFFER_BLUE_SIZE\",36179:\"RENDERBUFFER_ALPHA_SIZE\",36180:\"RENDERBUFFER_DEPTH_SIZE\",36181:\"RENDERBUFFER_STENCIL_SIZE\",36194:\"RGB565\",36336:\"LOW_FLOAT\",36337:\"MEDIUM_FLOAT\",36338:\"HIGH_FLOAT\",36339:\"LOW_INT\",36340:\"MEDIUM_INT\",36341:\"HIGH_INT\",36346:\"SHADER_COMPILER\",36347:\"MAX_VERTEX_UNIFORM_VECTORS\",36348:\"MAX_VARYING_VECTORS\",36349:\"MAX_FRAGMENT_UNIFORM_VECTORS\",37440:\"UNPACK_FLIP_Y_WEBGL\",37441:\"UNPACK_PREMULTIPLY_ALPHA_WEBGL\",37442:\"CONTEXT_LOST_WEBGL\",37443:\"UNPACK_COLORSPACE_CONVERSION_WEBGL\",37444:\"BROWSER_DEFAULT_WEBGL\"}},{}],245:[function(t,e,r){var 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outOfRange(clipBounds[0], clipBounds[1], fragPosition) ||\\n fragColor.a * opacity == 0.\\n ) discard;\\n\\n gl_FragColor = opacity * fragColor;\\n}\"]);e.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"offset\",type:\"vec3\"}])}},{\"gl-shader\":300,glslify:404}],248:[function(t,e,r){\"use strict\";var n=t(\"gl-texture2d\");e.exports=function(t,e,r,n){i||(i=t.FRAMEBUFFER_UNSUPPORTED,a=t.FRAMEBUFFER_INCOMPLETE_ATTACHMENT,o=t.FRAMEBUFFER_INCOMPLETE_DIMENSIONS,s=t.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT);var c=t.getExtension(\"WEBGL_draw_buffers\");!l&&c&&function(t,e){var r=t.getParameter(e.MAX_COLOR_ATTACHMENTS_WEBGL);l=new Array(r+1);for(var n=0;n<=r;++n){for(var i=new Array(r),a=0;a<n;++a)i[a]=t.COLOR_ATTACHMENT0+a;for(var a=n;a<r;++a)i[a]=t.NONE;l[n]=i}}(t,c);Array.isArray(e)&&(n=r,r=0|e[1],e=0|e[0]);if(\"number\"!=typeof e)throw new Error(\"gl-fbo: Missing shape parameter\");var 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u(t,e){t.bindFramebuffer(t.FRAMEBUFFER,e[0]),t.bindRenderbuffer(t.RENDERBUFFER,e[1]),t.bindTexture(t.TEXTURE_2D,e[2])}function f(t){switch(t){case i:throw new Error(\"gl-fbo: Framebuffer unsupported\");case a:throw new Error(\"gl-fbo: Framebuffer incomplete attachment\");case o:throw new Error(\"gl-fbo: Framebuffer incomplete dimensions\");case s:throw new Error(\"gl-fbo: Framebuffer incomplete missing attachment\");default:throw new Error(\"gl-fbo: Framebuffer failed for unspecified reason\")}}function h(t,e,r,i,a,o){if(!i)return null;var s=n(t,e,r,a,i);return s.magFilter=t.NEAREST,s.minFilter=t.NEAREST,s.mipSamples=1,s.bind(),t.framebufferTexture2D(t.FRAMEBUFFER,o,t.TEXTURE_2D,s.handle,0),s}function p(t,e,r,n,i){var a=t.createRenderbuffer();return t.bindRenderbuffer(t.RENDERBUFFER,a),t.renderbufferStorage(t.RENDERBUFFER,n,e,r),t.framebufferRenderbuffer(t.FRAMEBUFFER,i,t.RENDERBUFFER,a),a}function d(t,e,r,n,i,a,o,s){this.gl=t,this._shape=[0|e,0|r],this._destroyed=!1,this._ext=s,this.color=new Array(i);for(var d=0;d<i;++d)this.color[d]=null;this._color_rb=null,this.depth=null,this._depth_rb=null,this._colorType=n,this._useDepth=a,this._useStencil=o;var g=this,v=[0|e,0|r];Object.defineProperties(v,{0:{get:function(){return g._shape[0]},set:function(t){return g.width=t}},1:{get:function(){return g._shape[1]},set:function(t){return g.height=t}}}),this._shapeVector=v,function(t){var e=c(t.gl),r=t.gl,n=t.handle=r.createFramebuffer(),i=t._shape[0],a=t._shape[1],o=t.color.length,s=t._ext,d=t._useStencil,g=t._useDepth,v=t._colorType;r.bindFramebuffer(r.FRAMEBUFFER,n);for(var m=0;m<o;++m)t.color[m]=h(r,i,a,v,r.RGBA,r.COLOR_ATTACHMENT0+m);0===o?(t._color_rb=p(r,i,a,r.RGBA4,r.COLOR_ATTACHMENT0),s&&s.drawBuffersWEBGL(l[0])):o>1&&s.drawBuffersWEBGL(l[o]);var y=r.getExtension(\"WEBGL_depth_texture\");y?d?t.depth=h(r,i,a,y.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):g&&(t.depth=h(r,i,a,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):g&&d?t._depth_rb=p(r,i,a,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):g?t._depth_rb=p(r,i,a,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):d&&(t._depth_rb=p(r,i,a,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var x=r.checkFramebufferStatus(r.FRAMEBUFFER);if(x!==r.FRAMEBUFFER_COMPLETE){for(t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null),m=0;m<t.color.length;++m)t.color[m].dispose(),t.color[m]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),u(r,e),f(x)}u(r,e)}(this)}var g=d.prototype;function v(t,e,r){if(t._destroyed)throw new Error(\"gl-fbo: Can't resize destroyed FBO\");if(t._shape[0]!==e||t._shape[1]!==r){var n=t.gl,i=n.getParameter(n.MAX_RENDERBUFFER_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var a=c(n),o=0;o<t.color.length;++o)t.color[o].shape=t._shape;t._color_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._color_rb),n.renderbufferStorage(n.RENDERBUFFER,n.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&n.renderbufferStorage(n.RENDERBUFFER,n.STENCIL_INDEX,t._shape[0],t._shape[1])),n.bindFramebuffer(n.FRAMEBUFFER,t.handle);var s=n.checkFramebufferStatus(n.FRAMEBUFFER);s!==n.FRAMEBUFFER_COMPLETE&&(t.dispose(),u(n,a),f(s)),u(n,a)}}Object.defineProperties(g,{shape:{get:function(){return this._destroyed?[0,0]:this._shapeVector},set:function(t){if(Array.isArray(t)||(t=[0|t,0|t]),2!==t.length)throw new Error(\"gl-fbo: Shape vector must be length 2\");var e=0|t[0],r=0|t[1];return v(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return v(this,t|=0,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t|=0,v(this,this._shape[0],t),t},enumerable:!1}}),g.bind=function(){if(!this._destroyed){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,this.handle),t.viewport(0,0,this._shape[0],this._shape[1])}},g.dispose=function(){if(!this._destroyed){this._destroyed=!0;var t=this.gl;t.deleteFramebuffer(this.handle),this.handle=null,this.depth&&(this.depth.dispose(),this.depth=null),this._depth_rb&&(t.deleteRenderbuffer(this._depth_rb),this._depth_rb=null);for(var e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},{\"gl-texture2d\":317}],249:[function(t,e,r){var n=t(\"sprintf-js\").sprintf,i=t(\"gl-constants/lookup\"),a=t(\"glsl-shader-name\"),o=t(\"add-line-numbers\");e.exports=function(t,e,r){\"use strict\";var s=a(e)||\"of unknown name (see npm glsl-shader-name)\",l=\"unknown type\";void 0!==r&&(l=r===i.FRAGMENT_SHADER?\"fragment\":\"vertex\");for(var c=n(\"Error compiling %s shader %s:\\n\",l,s),u=n(\"%s%s\",c,t),f=t.split(\"\\n\"),h={},p=0;p<f.length;p++){var d=f[p];if(\"\"!==d&&\"\\0\"!==d){var g=parseInt(d.split(\":\")[2]);if(isNaN(g))throw new Error(n(\"Could not parse error: %s\",d));h[g]=d}}for(var v=o(e).split(\"\\n\"),p=0;p<v.length;p++)if(h[p+3]||h[p+2]||h[p+1]){var m=v[p];if(c+=m+\"\\n\",h[p+1]){var y=h[p+1];y=y.substr(y.split(\":\",3).join(\":\").length+1).trim(),c+=n(\"^^^ %s\\n\\n\",y)}}return{long:c.trim(),short:u.trim()}}},{\"add-line-numbers\":54,\"gl-constants/lookup\":245,\"glsl-shader-name\":396,\"sprintf-js\":515}],250:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=t.gl,n=o(r,l.vertex,l.fragment),i=o(r,l.pickVertex,l.pickFragment),a=s(r),u=s(r),f=s(r),h=s(r),p=new c(t,n,i,a,u,f,h);return p.update(e),t.addObject(p),p};var n=t(\"binary-search-bounds\"),i=t(\"iota-array\"),a=t(\"typedarray-pool\"),o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"./lib/shaders\");function c(t,e,r,n,i,a,o){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.weightBuffer=i,this.colorBuffer=a,this.idBuffer=o,this.xData=[],this.yData=[],this.shape=[0,0],this.bounds=[1/0,1/0,-1/0,-1/0],this.pickOffset=0}var u,f=c.prototype,h=[0,0,1,0,0,1,1,0,1,1,0,1];f.draw=(u=[1,0,0,0,1,0,0,0,1],function(){var t=this.plot,e=this.shader,r=this.bounds,n=this.numVertices;if(!(n<=0)){var i=t.gl,a=t.dataBox,o=r[2]-r[0],s=r[3]-r[1],l=a[2]-a[0],c=a[3]-a[1];u[0]=2*o/l,u[4]=2*s/c,u[6]=2*(r[0]-a[0])/l-1,u[7]=2*(r[1]-a[1])/c-1,e.bind();var f=e.uniforms;f.viewTransform=u,f.shape=this.shape;var h=e.attributes;this.positionBuffer.bind(),h.position.pointer(),this.weightBuffer.bind(),h.weight.pointer(i.UNSIGNED_BYTE,!1),this.colorBuffer.bind(),h.color.pointer(i.UNSIGNED_BYTE,!0),i.drawArrays(i.TRIANGLES,0,n)}}),f.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=this.plot,i=this.pickShader,a=this.bounds,o=this.numVertices;if(!(o<=0)){var s=n.gl,l=n.dataBox,c=a[2]-a[0],u=a[3]-a[1],f=l[2]-l[0],h=l[3]-l[1];t[0]=2*c/f,t[4]=2*u/h,t[6]=2*(a[0]-l[0])/f-1,t[7]=2*(a[1]-l[1])/h-1;for(var p=0;p<4;++p)e[p]=r>>8*p&255;this.pickOffset=r,i.bind();var d=i.uniforms;d.viewTransform=t,d.pickOffset=e,d.shape=this.shape;var g=i.attributes;return this.positionBuffer.bind(),g.position.pointer(),this.weightBuffer.bind(),g.weight.pointer(s.UNSIGNED_BYTE,!1),this.idBuffer.bind(),g.pickId.pointer(s.UNSIGNED_BYTE,!1),s.drawArrays(s.TRIANGLES,0,o),r+this.shape[0]*this.shape[1]}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.shape[0]*this.shape[1];if(r<n||r>=n+i)return null;var a=r-n,o=this.xData,s=this.yData;return{object:this,pointId:a,dataCoord:[o[a%this.shape[0]],s[a/this.shape[0]|0]]}},f.update=function(t){var e=(t=t||{}).shape||[0,0],r=t.x||i(e[0]),o=t.y||i(e[1]),s=t.z||new Float32Array(e[0]*e[1]);this.xData=r,this.yData=o;var l=t.colorLevels||[0],c=t.colorValues||[0,0,0,1],u=l.length,f=this.bounds,p=f[0]=r[0],d=f[1]=o[0],g=1/((f[2]=r[r.length-1])-p),v=1/((f[3]=o[o.length-1])-d),m=e[0],y=e[1];this.shape=[m,y];var x=(m-1)*(y-1)*(h.length>>>1);this.numVertices=x;for(var b=a.mallocUint8(4*x),_=a.mallocFloat32(2*x),w=a.mallocUint8(2*x),k=a.mallocUint32(x),T=0,A=0;A<y-1;++A)for(var M=v*(o[A]-d),S=v*(o[A+1]-d),E=0;E<m-1;++E)for(var C=g*(r[E]-p),L=g*(r[E+1]-p),z=0;z<h.length;z+=2){var O,I,D,P,R=h[z],F=h[z+1],B=s[(A+F)*m+(E+R)],N=n.le(l,B);if(N<0)O=c[0],I=c[1],D=c[2],P=c[3];else if(N===u-1)O=c[4*u-4],I=c[4*u-3],D=c[4*u-2],P=c[4*u-1];else{var j=(B-l[N])/(l[N+1]-l[N]),V=1-j,U=4*N,H=4*(N+1);O=V*c[U]+j*c[H],I=V*c[U+1]+j*c[H+1],D=V*c[U+2]+j*c[H+2],P=V*c[U+3]+j*c[H+3]}b[4*T]=255*O,b[4*T+1]=255*I,b[4*T+2]=255*D,b[4*T+3]=255*P,_[2*T]=.5*C+.5*L,_[2*T+1]=.5*M+.5*S,w[2*T]=R,w[2*T+1]=F,k[T]=A*m+E,T+=1}this.positionBuffer.update(_),this.weightBuffer.update(w),this.colorBuffer.update(b),this.idBuffer.update(k),a.free(_),a.free(b),a.free(w),a.free(k)},f.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.weightBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},{\"./lib/shaders\":251,\"binary-search-bounds\":252,\"gl-buffer\":240,\"gl-shader\":300,\"iota-array\":411,\"typedarray-pool\":532}],251:[function(t,e,r){\"use strict\";var n=t(\"glslify\");e.exports={fragment:n([\"precision lowp float;\\n#define GLSLIFY 1\\nvarying vec4 fragColor;\\nvoid main() {\\n gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\\n}\\n\"]),vertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 color;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n fragColor = color;\\n gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"]),pickFragment:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nuniform vec2 shape;\\nuniform vec4 pickOffset;\\n\\nvoid main() {\\n vec2 d = step(.5, vWeight);\\n vec4 id = fragId + pickOffset;\\n id.x += d.x + d.y*shape.x;\\n\\n id.y += floor(id.x / 256.0);\\n id.x -= floor(id.x / 256.0) * 256.0;\\n\\n id.z += floor(id.y / 256.0);\\n id.y -= floor(id.y / 256.0) * 256.0;\\n\\n id.w += floor(id.z / 256.0);\\n id.z -= floor(id.z / 256.0) * 256.0;\\n\\n gl_FragColor = id/255.;\\n}\\n\"]),pickVertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nvoid main() {\\n vWeight = weight;\\n\\n fragId = pickId;\\n\\n vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"])}},{glslify:404}],252:[function(t,e,r){arguments[4][104][0].apply(r,arguments)},{dup:104}],253:[function(t,e,r){var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, nextPosition;\\nattribute float arcLength, lineWidth;\\nattribute vec4 color;\\n\\nuniform vec2 screenShape;\\nuniform float pixelRatio;\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 fragColor;\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\n\\nvec4 project(vec3 p) {\\n return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n vec4 startPoint = project(position);\\n vec4 endPoint = project(nextPosition);\\n\\n vec2 A = startPoint.xy / startPoint.w;\\n vec2 B = endPoint.xy / endPoint.w;\\n\\n float clipAngle = atan(\\n (B.y - A.y) * screenShape.y,\\n (B.x - A.x) * screenShape.x\\n );\\n\\n vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(\\n sin(clipAngle),\\n -cos(clipAngle)\\n ) / screenShape;\\n\\n gl_Position = vec4(startPoint.xy + startPoint.w * offset, startPoint.zw);\\n\\n worldPosition = position;\\n pixelArcLength = arcLength;\\n fragColor = color;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float dashScale;\\nuniform float opacity;\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n if (\\n outOfRange(clipBounds[0], clipBounds[1], worldPosition) ||\\n fragColor.a * opacity == 0.\\n ) discard;\\n\\n float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n if(dashWeight < 0.5) {\\n discard;\\n }\\n gl_FragColor = fragColor * opacity;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\n#define FLOAT_MAX 1.70141184e38\\n#define FLOAT_MIN 1.17549435e-38\\n\\nlowp vec4 encode_float_1540259130(highp float v) {\\n highp float av = abs(v);\\n\\n //Handle special cases\\n if(av < FLOAT_MIN) {\\n return vec4(0.0, 0.0, 0.0, 0.0);\\n } else if(v > FLOAT_MAX) {\\n return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n } else if(v < -FLOAT_MAX) {\\n return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n }\\n\\n highp vec4 c = vec4(0,0,0,0);\\n\\n //Compute exponent and mantissa\\n highp float e = floor(log2(av));\\n highp float m = av * pow(2.0, -e) - 1.0;\\n \\n //Unpack mantissa\\n c[1] = floor(128.0 * m);\\n m -= c[1] / 128.0;\\n c[2] = floor(32768.0 * m);\\n m -= c[2] / 32768.0;\\n c[3] = floor(8388608.0 * m);\\n \\n //Unpack exponent\\n highp float ebias = e + 127.0;\\n c[0] = floor(ebias / 2.0);\\n ebias -= c[0] * 2.0;\\n c[1] += floor(ebias) * 128.0; \\n\\n //Unpack sign bit\\n c[0] += 128.0 * step(0.0, -v);\\n\\n //Scale back to range\\n return c / 255.0;\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard;\\n\\n gl_FragColor = vec4(pickId/255.0, encode_float_1540259130(pixelArcLength).xyz);\\n}\"]),l=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];r.createShader=function(t){return i(t,a,o,null,l)},r.createPickShader=function(t){return i(t,a,s,null,l)}},{\"gl-shader\":300,glslify:404}],254:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl||t.scene&&t.scene.gl,r=u(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var o=f(e);o.attributes.position.location=0,o.attributes.nextPosition.location=1,o.attributes.arcLength.location=2,o.attributes.lineWidth.location=3,o.attributes.color.location=4;for(var s=n(e),c=i(e,[{buffer:s,size:3,offset:0,stride:48},{buffer:s,size:3,offset:12,stride:48},{buffer:s,size:1,offset:24,stride:48},{buffer:s,size:1,offset:28,stride:48},{buffer:s,size:4,offset:32,stride:48}]),h=l(new Array(1024),[256,1,4]),p=0;p<1024;++p)h.data[p]=255;var d=a(e,h);d.wrap=e.REPEAT;var g=new v(e,r,o,s,c,d);return g.update(t),g};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"gl-texture2d\"),o=t(\"glsl-read-float\"),s=t(\"binary-search-bounds\"),l=t(\"ndarray\"),c=t(\"./lib/shaders\"),u=c.createShader,f=c.createPickShader,h=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function p(t,e){for(var r=0,n=0;n<3;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function d(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;r<3;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function g(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function v(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.hasAlpha=!1,this.dirty=!0,this.pixelRatio=1}var m=v.prototype;m.isTransparent=function(){return this.hasAlpha},m.isOpaque=function(){return!this.hasAlpha},m.pickSlots=1,m.setPickBase=function(t){this.pickId=t},m.drawTransparent=m.draw=function(t){if(this.vertexCount){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||h,view:t.view||h,projection:t.projection||h,clipBounds:d(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},m.drawPick=function(t){if(this.vertexCount){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||h,view:t.view||h,projection:t.projection||h,pickId:this.pickId,clipBounds:d(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},m.update=function(t){var e,r;this.dirty=!0;var n=!!t.connectGaps;\"dashScale\"in t&&(this.dashScale=t.dashScale),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var i=[],a=[],o=[],c=0,u=0,f=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],h=t.position||t.positions;if(h){var d=t.color||t.colors||[0,0,0,1],g=t.lineWidth||1,v=!1;t:for(e=1;e<h.length;++e){var m,y,x,b=h[e-1],_=h[e];for(a.push(c),o.push(b.slice()),r=0;r<3;++r){if(isNaN(b[r])||isNaN(_[r])||!isFinite(b[r])||!isFinite(_[r])){if(!n&&i.length>0){for(var w=0;w<24;++w)i.push(i[i.length-12]);u+=2,v=!0}continue t}f[0][r]=Math.min(f[0][r],b[r],_[r]),f[1][r]=Math.max(f[1][r],b[r],_[r])}Array.isArray(d[0])?(m=d.length>e-1?d[e-1]:d.length>0?d[d.length-1]:[0,0,0,1],y=d.length>e?d[e]:d.length>0?d[d.length-1]:[0,0,0,1]):m=y=d,3===m.length&&(m=[m[0],m[1],m[2],1]),3===y.length&&(y=[y[0],y[1],y[2],1]),!this.hasAlpha&&m[3]<1&&(this.hasAlpha=!0),x=Array.isArray(g)?g.length>e-1?g[e-1]:g.length>0?g[g.length-1]:[0,0,0,1]:g;var k=c;if(c+=p(b,_),v){for(r=0;r<2;++r)i.push(b[0],b[1],b[2],_[0],_[1],_[2],k,x,m[0],m[1],m[2],m[3]);u+=2,v=!1}i.push(b[0],b[1],b[2],_[0],_[1],_[2],k,x,m[0],m[1],m[2],m[3],b[0],b[1],b[2],_[0],_[1],_[2],k,-x,m[0],m[1],m[2],m[3],_[0],_[1],_[2],b[0],b[1],b[2],c,-x,y[0],y[1],y[2],y[3],_[0],_[1],_[2],b[0],b[1],b[2],c,x,y[0],y[1],y[2],y[3]),u+=4}}if(this.buffer.update(i),a.push(c),o.push(h[h.length-1].slice()),this.bounds=f,this.vertexCount=u,this.points=o,this.arcLength=a,\"dashes\"in t){var T=t.dashes.slice();for(T.unshift(0),e=1;e<T.length;++e)T[e]=T[e-1]+T[e];var A=l(new Array(1024),[256,1,4]);for(e=0;e<256;++e){for(r=0;r<4;++r)A.set(e,0,r,0);1&s.le(T,T[T.length-1]*e/255)?A.set(e,0,0,0):A.set(e,0,0,255)}this.texture.setPixels(A)}},m.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()},m.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=o(t.value[0],t.value[1],t.value[2],0),r=s.le(this.arcLength,e);if(r<0)return null;if(r===this.arcLength.length-1)return new g(this.arcLength[this.arcLength.length-1],this.points[this.points.length-1].slice(),r);for(var n=this.points[r],i=this.points[Math.min(r+1,this.points.length-1)],a=(e-this.arcLength[r])/(this.arcLength[r+1]-this.arcLength[r]),l=1-a,c=[0,0,0],u=0;u<3;++u)c[u]=l*n[u]+a*i[u];var f=Math.min(a<.5?r:r+1,this.points.length-1);return new g(e,c,f,this.points[f])}},{\"./lib/shaders\":253,\"binary-search-bounds\":255,\"gl-buffer\":240,\"gl-texture2d\":317,\"gl-vao\":322,\"glsl-read-float\":395,ndarray:445}],255:[function(t,e,r){arguments[4][104][0].apply(r,arguments)},{dup:104}],256:[function(t,e,r){e.exports=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=r*a-i*n;return o?(o=1/o,t[0]=a*o,t[1]=-n*o,t[2]=-i*o,t[3]=r*o,t):null}},{}],257:[function(t,e,r){e.exports=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],c=e[7],u=e[8],f=u*o-s*c,h=-u*a+s*l,p=c*a-o*l,d=r*f+n*h+i*p;return 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r=e[0],n=e[1],i=e[2],a=e[3],o=r+r,s=n+n,l=i+i,c=r*o,u=n*o,f=n*s,h=i*o,p=i*s,d=i*l,g=a*o,v=a*s,m=a*l;return t[0]=1-f-d,t[1]=u+m,t[2]=h-v,t[3]=0,t[4]=u-m,t[5]=1-c-d,t[6]=p+g,t[7]=0,t[8]=h+v,t[9]=p-g,t[10]=1-c-f,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],262:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=n+n,l=i+i,c=a+a,u=n*s,f=n*l,h=n*c,p=i*l,d=i*c,g=a*c,v=o*s,m=o*l,y=o*c;return t[0]=1-(p+g),t[1]=f+y,t[2]=h-m,t[3]=0,t[4]=f-y,t[5]=1-(u+g),t[6]=d+v,t[7]=0,t[8]=h+m,t[9]=d-v,t[10]=1-(u+p),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t}},{}],263:[function(t,e,r){e.exports=function(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],264:[function(t,e,r){e.exports=function(t,e){var 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n(t);f=g-_,h=v-w,p=m-k,d=1/Math.sqrt(f*f+h*h+p*p),a=x*(p*=d)-b*(h*=d),o=b*(f*=d)-y*p,s=y*h-x*f,(d=Math.sqrt(a*a+o*o+s*s))?(a*=d=1/d,o*=d,s*=d):(a=0,o=0,s=0);l=h*s-p*o,c=p*a-f*s,u=f*o-h*a,(d=Math.sqrt(l*l+c*c+u*u))?(l*=d=1/d,c*=d,u*=d):(l=0,c=0,u=0);return t[0]=a,t[1]=l,t[2]=f,t[3]=0,t[4]=o,t[5]=c,t[6]=h,t[7]=0,t[8]=s,t[9]=u,t[10]=p,t[11]=0,t[12]=-(a*g+o*v+s*m),t[13]=-(l*g+c*v+u*m),t[14]=-(f*g+h*v+p*m),t[15]=1,t}},{\"./identity\":263}],266:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],f=e[8],h=e[9],p=e[10],d=e[11],g=e[12],v=e[13],m=e[14],y=e[15],x=r[0],b=r[1],_=r[2],w=r[3];return t[0]=x*n+b*s+_*f+w*g,t[1]=x*i+b*l+_*h+w*v,t[2]=x*a+b*c+_*p+w*m,t[3]=x*o+b*u+_*d+w*y,x=r[4],b=r[5],_=r[6],w=r[7],t[4]=x*n+b*s+_*f+w*g,t[5]=x*i+b*l+_*h+w*v,t[6]=x*a+b*c+_*p+w*m,t[7]=x*o+b*u+_*d+w*y,x=r[8],b=r[9],_=r[10],w=r[11],t[8]=x*n+b*s+_*f+w*g,t[9]=x*i+b*l+_*h+w*v,t[10]=x*a+b*c+_*p+w*m,t[11]=x*o+b*u+_*d+w*y,x=r[12],b=r[13],_=r[14],w=r[15],t[12]=x*n+b*s+_*f+w*g,t[13]=x*i+b*l+_*h+w*v,t[14]=x*a+b*c+_*p+w*m,t[15]=x*o+b*u+_*d+w*y,t}},{}],267:[function(t,e,r){e.exports=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),c=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*c,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*c,t[15]=1,t}},{}],268:[function(t,e,r){e.exports=function(t,e,r,n,i){var a=1/Math.tan(e/2),o=1/(n-i);return t[0]=a/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=a,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(i+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*i*n*o,t[15]=0,t}},{}],269:[function(t,e,r){e.exports=function(t,e,r,n){var i,a,o,s,l,c,u,f,h,p,d,g,v,m,y,x,b,_,w,k,T,A,M,S,E=n[0],C=n[1],L=n[2],z=Math.sqrt(E*E+C*C+L*L);if(Math.abs(z)<1e-6)return null;E*=z=1/z,C*=z,L*=z,i=Math.sin(r),a=Math.cos(r),o=1-a,s=e[0],l=e[1],c=e[2],u=e[3],f=e[4],h=e[5],p=e[6],d=e[7],g=e[8],v=e[9],m=e[10],y=e[11],x=E*E*o+a,b=C*E*o+L*i,_=L*E*o-C*i,w=E*C*o-L*i,k=C*C*o+a,T=L*C*o+E*i,A=E*L*o+C*i,M=C*L*o-E*i,S=L*L*o+a,t[0]=s*x+f*b+g*_,t[1]=l*x+h*b+v*_,t[2]=c*x+p*b+m*_,t[3]=u*x+d*b+y*_,t[4]=s*w+f*k+g*T,t[5]=l*w+h*k+v*T,t[6]=c*w+p*k+m*T,t[7]=u*w+d*k+y*T,t[8]=s*A+f*M+g*S,t[9]=l*A+h*M+v*S,t[10]=c*A+p*M+m*S,t[11]=u*A+d*M+y*S,e!==t&&(t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t}},{}],270:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[4],o=e[5],s=e[6],l=e[7],c=e[8],u=e[9],f=e[10],h=e[11];e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[4]=a*i+c*n,t[5]=o*i+u*n,t[6]=s*i+f*n,t[7]=l*i+h*n,t[8]=c*i-a*n,t[9]=u*i-o*n,t[10]=f*i-s*n,t[11]=h*i-l*n,t}},{}],271:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],c=e[8],u=e[9],f=e[10],h=e[11];e!==t&&(t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[0]=a*i-c*n,t[1]=o*i-u*n,t[2]=s*i-f*n,t[3]=l*i-h*n,t[8]=a*n+c*i,t[9]=o*n+u*i,t[10]=s*n+f*i,t[11]=l*n+h*i,t}},{}],272:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],c=e[4],u=e[5],f=e[6],h=e[7];e!==t&&(t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[0]=a*i+c*n,t[1]=o*i+u*n,t[2]=s*i+f*n,t[3]=l*i+h*n,t[4]=c*i-a*n,t[5]=u*i-o*n,t[6]=f*i-s*n,t[7]=h*i-l*n,t}},{}],273:[function(t,e,r){e.exports=function(t,e,r){var n=r[0],i=r[1],a=r[2];return t[0]=e[0]*n,t[1]=e[1]*n,t[2]=e[2]*n,t[3]=e[3]*n,t[4]=e[4]*i,t[5]=e[5]*i,t[6]=e[6]*i,t[7]=e[7]*i,t[8]=e[8]*a,t[9]=e[9]*a,t[10]=e[10]*a,t[11]=e[11]*a,t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t}},{}],274:[function(t,e,r){e.exports=function(t,e,r){var n,i,a,o,s,l,c,u,f,h,p,d,g=r[0],v=r[1],m=r[2];e===t?(t[12]=e[0]*g+e[4]*v+e[8]*m+e[12],t[13]=e[1]*g+e[5]*v+e[9]*m+e[13],t[14]=e[2]*g+e[6]*v+e[10]*m+e[14],t[15]=e[3]*g+e[7]*v+e[11]*m+e[15]):(n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],f=e[8],h=e[9],p=e[10],d=e[11],t[0]=n,t[1]=i,t[2]=a,t[3]=o,t[4]=s,t[5]=l,t[6]=c,t[7]=u,t[8]=f,t[9]=h,t[10]=p,t[11]=d,t[12]=n*g+s*v+f*m+e[12],t[13]=i*g+l*v+h*m+e[13],t[14]=a*g+c*v+p*m+e[14],t[15]=o*g+u*v+d*m+e[15]);return t}},{}],275:[function(t,e,r){e.exports=function(t,e){if(t===e){var r=e[1],n=e[2],i=e[3],a=e[6],o=e[7],s=e[11];t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=r,t[6]=e[9],t[7]=e[13],t[8]=n,t[9]=a,t[11]=e[14],t[12]=i,t[13]=o,t[14]=s}else t[0]=e[0],t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=e[1],t[5]=e[5],t[6]=e[9],t[7]=e[13],t[8]=e[2],t[9]=e[6],t[10]=e[10],t[11]=e[14],t[12]=e[3],t[13]=e[7],t[14]=e[11],t[15]=e[15];return t}},{}],276:[function(t,e,r){\"use strict\";e.exports=function(t,e){switch(e.length){case 0:break;case 1:t[0]=1/e[0];break;case 4:n(t,e);break;case 9:i(t,e);break;case 16:a(t,e);break;default:throw new Error(\"currently supports matrices up to 4x4\")}return t};var n=t(\"gl-mat2/invert\"),i=t(\"gl-mat3/invert\"),a=t(\"gl-mat4/invert\")},{\"gl-mat2/invert\":256,\"gl-mat3/invert\":257,\"gl-mat4/invert\":264}],277:[function(t,e,r){\"use strict\";var n=t(\"barycentric\"),i=t(\"polytope-closest-point/lib/closest_point_2d.js\");function a(t,e){for(var r=[0,0,0,0],n=0;n<4;++n)for(var i=0;i<4;++i)r[i]+=t[4*n+i]*e[n];return r}function o(t,e,r,n,i){for(var o=a(n,a(r,a(e,[t[0],t[1],t[2],1]))),s=0;s<3;++s)o[s]/=o[3];return[.5*i[0]*(1+o[0]),.5*i[1]*(1-o[1])]}e.exports=function(t,e,r,a,s,l){if(1===t.length)return[0,t[0].slice()];for(var c=new Array(t.length),u=0;u<t.length;++u)c[u]=o(t[u],r,a,s,l);for(var f=0,h=1/0,u=0;u<c.length;++u){for(var p=0,d=0;d<2;++d)p+=Math.pow(c[u][d]-e[d],2);p<h&&(h=p,f=u)}for(var g=function(t,e){if(2===t.length){for(var r=0,a=0,o=0;o<2;++o)r+=Math.pow(e[o]-t[0][o],2),a+=Math.pow(e[o]-t[1][o],2);return r=Math.sqrt(r),a=Math.sqrt(a),r+a<1e-6?[1,0]:[a/(r+a),r/(a+r)]}if(3===t.length){var s=[0,0];return i(t[0],t[1],t[2],e,s),n(t,s)}return[]}(c,e),v=0,u=0;u<3;++u){if(g[u]<-.001||g[u]>1.0001)return null;v+=g[u]}if(Math.abs(v-1)>.001)return null;return[f,function(t,e){for(var r=[0,0,0],n=0;n<t.length;++n)for(var i=t[n],a=e[n],o=0;o<3;++o)r[o]+=a*i[o];return r}(t,g),g]}},{barycentric:66,\"polytope-closest-point/lib/closest_point_2d.js\":476}],278:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n , view\\n , projection\\n , inverseModel;\\nuniform vec3 eyePosition\\n , lightPosition;\\n\\nvarying vec3 f_normal\\n , f_lightDirection\\n , f_eyeDirection\\n , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvec4 project(vec3 p) {\\n return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n gl_Position = project(position);\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * vec4(position , 1.0);\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n f_color = color;\\n f_data = position;\\n f_uv = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness,\\n float fresnel) {\\n\\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n //Half angle vector\\n vec3 H = normalize(lightDirection + viewDirection);\\n\\n //Geometric term\\n float NdotH = max(dot(surfaceNormal, H), 0.0);\\n float VdotH = max(dot(viewDirection, H), 0.000001);\\n float LdotH = max(dot(lightDirection, H), 0.000001);\\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n float G = min(1.0, min(G1, G2));\\n \\n //Distribution term\\n float D = beckmannDistribution(NdotH, roughness);\\n\\n //Fresnel term\\n float F = pow(1.0 - VdotN, fresnel);\\n\\n //Multiply terms and done\\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n , fresnel\\n , kambient\\n , kdiffuse\\n , kspecular;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n , f_lightDirection\\n , f_eyeDirection\\n , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (f_color.a == 0.0 ||\\n outOfRange(clipBounds[0], clipBounds[1], f_data)\\n ) discard;\\n\\n vec3 N = normalize(f_normal);\\n vec3 L = normalize(f_lightDirection);\\n vec3 V = normalize(f_eyeDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\\n\\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\\n\\n gl_FragColor = litColor * f_color.a;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n f_color = color;\\n f_data = position;\\n f_uv = uv;\\n}\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard;\\n\\n gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0);\\n } else {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n }\\n gl_PointSize = pointSize;\\n f_color = color;\\n f_uv = uv;\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5);\\n if(dot(pointR, pointR) > 0.25) {\\n discard;\\n }\\n gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n f_id = id;\\n f_position = position;\\n}\"]),f=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]),h=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute float pointSize;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0.0, 0.0, 0.0, 0.0);\\n } else {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n gl_PointSize = pointSize;\\n }\\n f_id = id;\\n f_position = position;\\n}\"]),p=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n}\"]),d=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n gl_FragColor = vec4(contourColor, 1.0);\\n}\\n\"]);r.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.wireShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.pointShader={vertex:l,fragment:c,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},r.pickShader={vertex:u,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},r.pointPickShader={vertex:h,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},r.contourShader={vertex:p,fragment:d,attributes:[{name:\"position\",type:\"vec3\"}]}},{glslify:404}],279:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"normals\"),l=t(\"gl-mat4/multiply\"),c=t(\"gl-mat4/invert\"),u=t(\"ndarray\"),f=t(\"colormap\"),h=t(\"simplicial-complex-contour\"),p=t(\"typedarray-pool\"),d=t(\"./lib/shaders\"),g=t(\"./lib/closest-point\"),v=d.meshShader,m=d.wireShader,y=d.pointShader,x=d.pickShader,b=d.pointPickShader,_=d.contourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function k(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,v,m,y,x,b,_,k,T,A,M,S){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=u,this.triangleNormals=h,this.triangleUVs=f,this.triangleIds=c,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=v,this.edgeUVs=m,this.edgeIds=g,this.edgeVAO=y,this.edgeCount=0,this.pointPositions=x,this.pointColors=_,this.pointUVs=k,this.pointSizes=T,this.pointIds=b,this.pointVAO=A,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=M,this.contourVAO=S,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=w,this._view=w,this._projection=w,this._resolution=[1,1]}var T=k.prototype;function A(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}function M(t){var e=n(t,y.vertex,y.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function S(t){var e=n(t,x.vertex,x.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e}function E(t){var e=n(t,b.vertex,b.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function C(t){var e=n(t,_.vertex,_.fragment);return e.attributes.position.location=0,e}T.isOpaque=function(){return!this.hasAlpha},T.isTransparent=function(){return this.hasAlpha},T.pickSlots=1,T.setPickBase=function(t){this.pickId=t},T.highlight=function(t){if(t&&this.contourEnable){for(var e=h(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=p.mallocFloat32(6*a),s=0,l=0;l<a;++l)for(var c=r[l],u=0;u<2;++u){var f=c[0];2===c.length&&(f=c[u]);for(var d=n[f][0],g=n[f][1],v=i[f],m=1-v,y=this.positions[d],x=this.positions[g],b=0;b<3;++b)o[s++]=v*y[b]+m*x[b]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),p.free(o)}else this.contourCount=0},T.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=t.opacity,this.opacity<1&&(this.hasAlpha=!0)),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale,this.hasAlpha=!0),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),t.texture?(this.texture.dispose(),this.texture=o(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t,e){for(var r=f({colormap:t,nshades:256,format:\"rgba\"}),n=new Uint8Array(1024),i=0;i<256;++i){for(var a=r[i],o=0;o<3;++o)n[4*i+o]=a[o];n[4*i+3]=e?255*A(i/255,e):255*a[3]}return u(n,[256,256,4],[4,0,1])}(t.colormap,this.opacityscale)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var i=[],a=[],l=[],c=[],h=[],p=[],d=[],g=[],v=[],m=[],y=[],x=[],b=[],_=[];this.cells=r,this.positions=n;var w=t.vertexNormals,k=t.cellNormals,T=void 0===t.vertexNormalsEpsilon?1e-6:t.vertexNormalsEpsilon,M=void 0===t.faceNormalsEpsilon?1e-6:t.faceNormalsEpsilon;t.useFacetNormals&&!k&&(k=s.faceNormals(r,n,M)),k||w||(w=s.vertexNormals(r,n,T));var S=t.vertexColors,E=t.cellColors,C=t.meshColor||[1,1,1,1],L=t.vertexUVs,z=t.vertexIntensity,O=t.cellUVs,I=t.cellIntensity,D=1/0,P=-1/0;if(!L&&!O)if(z)if(t.vertexIntensityBounds)D=+t.vertexIntensityBounds[0],P=+t.vertexIntensityBounds[1];else for(var R=0;R<z.length;++R){var F=z[R];D=Math.min(D,F),P=Math.max(P,F)}else if(I)for(R=0;R<I.length;++R){F=I[R];D=Math.min(D,F),P=Math.max(P,F)}else for(R=0;R<n.length;++R){F=n[R][2];D=Math.min(D,F),P=Math.max(P,F)}this.intensity=z||(I?function(t,e,r){for(var n=new Array(e),i=0;i<e;++i)n[i]=0;var a=t.length;for(i=0;i<a;++i)for(var o=t[i],s=0;s<o.length;++s)n[o[s]]=r[i];return n}(r,n.length,I):function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n));var B=t.pointSizes,N=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(R=0;R<n.length;++R)for(var j=n[R],V=0;V<3;++V)!isNaN(j[V])&&isFinite(j[V])&&(this.bounds[0][V]=Math.min(this.bounds[0][V],j[V]),this.bounds[1][V]=Math.max(this.bounds[1][V],j[V]));var U=0,H=0,q=0;t:for(R=0;R<r.length;++R){var G=r[R];switch(G.length){case 1:for(j=n[W=G[0]],V=0;V<3;++V)if(isNaN(j[V])||!isFinite(j[V]))continue t;m.push(j[0],j[1],j[2]),X=S?S[W]:E?E[R]:C,this.opacityscale&&z?a.push(X[0],X[1],X[2],this.opacity*A((z[W]-D)/(P-D),this.opacityscale)):3===X.length?y.push(X[0],X[1],X[2],this.opacity):(y.push(X[0],X[1],X[2],X[3]*this.opacity),!this.hasAlpha&&X[3]<1&&(this.hasAlpha=!0)),Z=L?L[W]:z?[(z[W]-D)/(P-D),0]:O?O[R]:I?[(I[R]-D)/(P-D),0]:[(j[2]-D)/(P-D),0],x.push(Z[0],Z[1]),B?b.push(B[W]):b.push(N),_.push(R),q+=1;break;case 2:for(V=0;V<2;++V){j=n[W=G[V]];for(var Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t}for(V=0;V<2;++V){j=n[W=G[V]];p.push(j[0],j[1],j[2]),X=S?S[W]:E?E[R]:C,this.opacityscale&&z?a.push(X[0],X[1],X[2],this.opacity*A((z[W]-D)/(P-D),this.opacityscale)):3===X.length?d.push(X[0],X[1],X[2],this.opacity):(d.push(X[0],X[1],X[2],X[3]*this.opacity),!this.hasAlpha&&X[3]<1&&(this.hasAlpha=!0)),Z=L?L[W]:z?[(z[W]-D)/(P-D),0]:O?O[R]:I?[(I[R]-D)/(P-D),0]:[(j[2]-D)/(P-D),0],g.push(Z[0],Z[1]),v.push(R)}H+=1;break;case 3:for(V=0;V<3;++V)for(j=n[W=G[V]],Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t;for(V=0;V<3;++V){var W,X,Z,$;j=n[W=G[2-V]];i.push(j[0],j[1],j[2]),X=S?S[W]:E?E[R]:C,this.opacityscale&&z?a.push(X[0],X[1],X[2],this.opacity*A((z[W]-D)/(P-D),this.opacityscale)):3===X.length?a.push(X[0],X[1],X[2],this.opacity):(a.push(X[0],X[1],X[2],X[3]*this.opacity),!this.hasAlpha&&X[3]<1&&(this.hasAlpha=!0)),Z=L?L[W]:z?[(z[W]-D)/(P-D),0]:O?O[R]:I?[(I[R]-D)/(P-D),0]:[(j[2]-D)/(P-D),0],c.push(Z[0],Z[1]),$=w?w[W]:k[R],l.push($[0],$[1],$[2]),h.push(R)}U+=1}}this.pointCount=q,this.edgeCount=H,this.triangleCount=U,this.pointPositions.update(m),this.pointColors.update(y),this.pointUVs.update(x),this.pointSizes.update(b),this.pointIds.update(new Uint32Array(_)),this.edgePositions.update(p),this.edgeColors.update(d),this.edgeUVs.update(g),this.edgeIds.update(new Uint32Array(v)),this.trianglePositions.update(i),this.triangleColors.update(a),this.triangleUVs.update(c),this.triangleNormals.update(l),this.triangleIds.update(new Uint32Array(h))}},T.drawTransparent=T.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,inverseModel:w.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],contourColor:this.contourColor,texture:0};s.inverseModel=c(s.inverseModel,s.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);l(u,s.view,s.model),l(u,s.projection,u),c(u,u);for(o=0;o<3;++o)s.eyePosition[o]=u[12+o]/u[15];var f,h=u[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var p=u[12+o],d=0;d<3;++d)p+=u[4*d+o]*this.lightPosition[d];s.lightPosition[o]=p/h}this.triangleCount>0&&((f=this.triShader).bind(),f.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind());this.edgeCount>0&&this.lineWidth>0&&((f=this.lineShader).bind(),f.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind());this.pointCount>0&&((f=this.pointShader).bind(),f.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind());this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0&&((f=this.contourShader).bind(),f.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind())},T.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s,l={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255};((s=this.pickShader).bind(),s.uniforms=l,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0)&&((s=this.pointPickShader).bind(),s.uniforms=l,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind())},T.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;a<r.length;++a)i[a]=n[r[a]];var o=g(i,[t.coord[0],this._resolution[1]-t.coord[1]],this._model,this._view,this._projection,this._resolution);if(!o)return null;var s=o[2],l=0;for(a=0;a<r.length;++a)l+=s[a]*this.intensity[r[a]];return{position:o[1],index:r[o[0]],cell:r,cellId:e,intensity:l,dataCoordinate:this.positions[r[o[0]]]}},T.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},e.exports=function(t,e){if(1===arguments.length&&(t=(e=t).gl),!(t.getExtension(\"OES_standard_derivatives\")||t.getExtension(\"MOZ_OES_standard_derivatives\")||t.getExtension(\"WEBKIT_OES_standard_derivatives\")))throw new Error(\"derivatives not supported\");var r=function(t){var e=n(t,v.vertex,v.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}(t),s=function(t){var e=n(t,m.vertex,m.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}(t),l=M(t),c=S(t),f=E(t),h=C(t),p=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));p.generateMipmap(),p.minFilter=t.LINEAR_MIPMAP_LINEAR,p.magFilter=t.LINEAR;var d=i(t),g=i(t),y=i(t),x=i(t),b=i(t),_=a(t,[{buffer:d,type:t.FLOAT,size:3},{buffer:b,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:g,type:t.FLOAT,size:4},{buffer:y,type:t.FLOAT,size:2},{buffer:x,type:t.FLOAT,size:3}]),w=i(t),T=i(t),A=i(t),L=i(t),z=a(t,[{buffer:w,type:t.FLOAT,size:3},{buffer:L,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:T,type:t.FLOAT,size:4},{buffer:A,type:t.FLOAT,size:2}]),O=i(t),I=i(t),D=i(t),P=i(t),R=i(t),F=a(t,[{buffer:O,type:t.FLOAT,size:3},{buffer:R,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:I,type:t.FLOAT,size:4},{buffer:D,type:t.FLOAT,size:2},{buffer:P,type:t.FLOAT,size:1}]),B=i(t),N=new k(t,p,r,s,l,c,f,h,d,b,g,y,x,_,w,L,T,A,z,O,R,I,D,P,F,B,a(t,[{buffer:B,type:t.FLOAT,size:3}]));return N.update(e),N}},{\"./lib/closest-point\":277,\"./lib/shaders\":278,colormap:119,\"gl-buffer\":240,\"gl-mat4/invert\":264,\"gl-mat4/multiply\":266,\"gl-shader\":300,\"gl-texture2d\":317,\"gl-vao\":322,ndarray:445,normals:448,\"simplicial-complex-contour\":505,\"typedarray-pool\":532}],280:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[0,0,0,1,1,0,1,1]),s=i(e,a.boxVert,a.lineFrag);return new o(t,r,s)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"./shaders\");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawBox=(s=[0,0],l=[0,0],function(t,e,r,n,i){var a=this.plot,o=this.shader,c=a.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,o.uniforms.lo=s,o.uniforms.hi=l,o.uniforms.color=i,c.drawArrays(c.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":283,\"gl-buffer\":240,\"gl-shader\":300}],281:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e),a=i(e,o.gridVert,o.gridFrag),l=i(e,o.tickVert,o.gridFrag);return new s(t,r,a,l)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"binary-search-bounds\"),o=t(\"./shaders\");function s(t,e,r,n){this.plot=t,this.vbo=e,this.shader=r,this.tickShader=n,this.ticks=[[],[]]}function l(t,e){return t-e}var c,u,f,h,p,d=s.prototype;d.draw=(c=[0,0],u=[0,0],f=[0,0],function(){for(var t=this.plot,e=this.vbo,r=this.shader,n=this.ticks,i=t.gl,a=t._tickBounds,o=t.dataBox,s=t.viewBox,l=t.gridLineWidth,h=t.gridLineColor,p=t.gridLineEnable,d=t.pixelRatio,g=0;g<2;++g){var v=a[g],m=a[g+2]-v,y=.5*(o[g+2]+o[g]),x=o[g+2]-o[g];u[g]=2*m/x,c[g]=2*(v-y)/x}r.bind(),e.bind(),r.attributes.dataCoord.pointer(),r.uniforms.dataShift=c,r.uniforms.dataScale=u;var b=0;for(g=0;g<2;++g){f[0]=f[1]=0,f[g]=1,r.uniforms.dataAxis=f,r.uniforms.lineWidth=l[g]/(s[g+2]-s[g])*d,r.uniforms.color=h[g];var _=6*n[g].length;p[g]&&_&&i.drawArrays(i.TRIANGLES,b,_),b+=_}}),d.drawTickMarks=function(){var t=[0,0],e=[0,0],r=[1,0],n=[0,1],i=[0,0],o=[0,0];return function(){for(var s=this.plot,c=this.vbo,u=this.tickShader,f=this.ticks,h=s.gl,p=s._tickBounds,d=s.dataBox,g=s.viewBox,v=s.pixelRatio,m=s.screenBox,y=m[2]-m[0],x=m[3]-m[1],b=g[2]-g[0],_=g[3]-g[1],w=0;w<2;++w){var k=p[w],T=p[w+2]-k,A=.5*(d[w+2]+d[w]),M=d[w+2]-d[w];e[w]=2*T/M,t[w]=2*(k-A)/M}e[0]*=b/y,t[0]*=b/y,e[1]*=_/x,t[1]*=_/x,u.bind(),c.bind(),u.attributes.dataCoord.pointer();var S=u.uniforms;S.dataShift=t,S.dataScale=e;var E=s.tickMarkLength,C=s.tickMarkWidth,L=s.tickMarkColor,z=6*f[0].length,O=Math.min(a.ge(f[0],(d[0]-p[0])/(p[2]-p[0]),l),f[0].length),I=Math.min(a.gt(f[0],(d[2]-p[0])/(p[2]-p[0]),l),f[0].length),D=0+6*O,P=6*Math.max(0,I-O),R=Math.min(a.ge(f[1],(d[1]-p[1])/(p[3]-p[1]),l),f[1].length),F=Math.min(a.gt(f[1],(d[3]-p[1])/(p[3]-p[1]),l),f[1].length),B=z+6*R,N=6*Math.max(0,F-R);i[0]=2*(g[0]-E[1])/y-1,i[1]=(g[3]+g[1])/x-1,o[0]=E[1]*v/y,o[1]=C[1]*v/x,N&&(S.color=L[1],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(g[2]+g[0])/y-1,i[1]=2*(g[1]-E[0])/x-1,o[0]=C[0]*v/y,o[1]=E[0]*v/x,P&&(S.color=L[0],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,D,P)),i[0]=2*(g[2]+E[3])/y-1,i[1]=(g[3]+g[1])/x-1,o[0]=E[3]*v/y,o[1]=C[3]*v/x,N&&(S.color=L[3],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(g[2]+g[0])/y-1,i[1]=2*(g[3]+E[2])/x-1,o[0]=C[2]*v/y,o[1]=E[2]*v/x,P&&(S.color=L[2],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,D,P))}}(),d.update=(h=[1,1,-1,-1,1,-1],p=[1,-1,1,1,-1,-1],function(t){for(var e=t.ticks,r=t.bounds,n=new Float32Array(18*(e[0].length+e[1].length)),i=(this.plot.zeroLineEnable,0),a=[[],[]],o=0;o<2;++o)for(var s=a[o],l=e[o],c=r[o],u=r[o+2],f=0;f<l.length;++f){var d=(l[f].x-c)/(u-c);s.push(d);for(var g=0;g<6;++g)n[i++]=d,n[i++]=h[g],n[i++]=p[g]}this.ticks=a,this.vbo.update(n)}),d.dispose=function(){this.vbo.dispose(),this.shader.dispose(),this.tickShader.dispose()}},{\"./shaders\":283,\"binary-search-bounds\":285,\"gl-buffer\":240,\"gl-shader\":300}],282:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[-1,-1,-1,1,1,-1,1,1]),s=i(e,a.lineVert,a.lineFrag);return new o(t,r,s)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"./shaders\");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawLine=(s=[0,0],l=[0,0],function(t,e,r,n,i,a){var o=this.plot,c=this.shader,u=o.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,c.uniforms.start=s,c.uniforms.end=l,c.uniforms.width=i*o.pixelRatio,c.uniforms.color=a,u.drawArrays(u.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":283,\"gl-buffer\":240,\"gl-shader\":300}],283:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=n([\"precision lowp float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n gl_FragColor = vec4(color.xyz * color.w, color.w);\\n}\\n\"]);e.exports={lineVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 start, end;\\nuniform float width;\\n\\nvec2 perp(vec2 v) {\\n return vec2(v.y, -v.x);\\n}\\n\\nvec2 screen(vec2 v) {\\n return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n vec2 delta = normalize(perp(start - end));\\n vec2 offset = mix(start, end, 0.5 * (coord.y+1.0));\\n gl_Position = vec4(screen(offset + 0.5 * width * delta * coord.x), 0, 1);\\n}\\n\"]),lineFrag:i,textVert:n([\"#define GLSLIFY 1\\nattribute vec3 textCoordinate;\\n\\nuniform vec2 dataScale, dataShift, dataAxis, screenOffset, textScale;\\nuniform float angle;\\n\\nvoid main() {\\n float dataOffset = textCoordinate.z;\\n vec2 glyphOffset = textCoordinate.xy;\\n mat2 glyphMatrix = mat2(cos(angle), sin(angle), -sin(angle), cos(angle));\\n vec2 screenCoordinate = dataAxis * (dataScale * dataOffset + dataShift) +\\n glyphMatrix * glyphOffset * textScale + screenOffset;\\n gl_Position = vec4(screenCoordinate, 0, 1);\\n}\\n\"]),textFrag:i,gridVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale;\\nuniform float lineWidth;\\n\\nvoid main() {\\n vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n pos += 10.0 * dataCoord.y * vec2(dataAxis.y, -dataAxis.x) + dataCoord.z * lineWidth;\\n gl_Position = vec4(pos, 0, 1);\\n}\\n\"]),gridFrag:i,boxVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 lo, hi;\\n\\nvec2 screen(vec2 v) {\\n return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n gl_Position = vec4(screen(mix(lo, hi, coord)), 0, 1);\\n}\\n\"]),tickVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale, screenOffset, tickScale;\\n\\nvoid main() {\\n vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n gl_Position = vec4(pos + tickScale*dataCoord.yz + screenOffset, 0, 1);\\n}\\n\"])}},{glslify:404}],284:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e),a=i(e,s.textVert,s.textFrag);return new l(t,r,a)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"text-cache\"),o=t(\"binary-search-bounds\"),s=t(\"./shaders\");function l(t,e,r){this.plot=t,this.vbo=e,this.shader=r,this.tickOffset=[[],[]],this.tickX=[[],[]],this.labelOffset=[0,0],this.labelCount=[0,0]}var c,u,f,h,p,d,g=l.prototype;g.drawTicks=(c=[0,0],u=[0,0],f=[0,0],function(t){var e=this.plot,r=this.shader,n=this.tickX[t],i=this.tickOffset[t],a=e.gl,s=e.viewBox,l=e.dataBox,h=e.screenBox,p=e.pixelRatio,d=e.tickEnable,g=e.tickPad,v=e.tickColor,m=e.tickAngle,y=e.labelEnable,x=e.labelPad,b=e.labelColor,_=e.labelAngle,w=this.labelOffset[t],k=this.labelCount[t],T=o.lt(n,l[t]),A=o.le(n,l[t+2]);c[0]=c[1]=0,c[t]=1,u[t]=(s[2+t]+s[t])/(h[2+t]-h[t])-1;var M=2/h[2+(1^t)]-h[1^t];u[1^t]=M*s[1^t]-1,d[t]&&(u[1^t]-=M*p*g[t],T<A&&i[A]>i[T]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=v[t],r.uniforms.angle=m[t],a.drawArrays(a.TRIANGLES,i[T],i[A]-i[T]))),y[t]&&k&&(u[1^t]-=M*p*x[t],r.uniforms.dataAxis=f,r.uniforms.screenOffset=u,r.uniforms.color=b[t],r.uniforms.angle=_[t],a.drawArrays(a.TRIANGLES,w,k)),u[1^t]=M*s[2+(1^t)]-1,d[t+2]&&(u[1^t]+=M*p*g[t+2],T<A&&i[A]>i[T]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=v[t+2],r.uniforms.angle=m[t+2],a.drawArrays(a.TRIANGLES,i[T],i[A]-i[T]))),y[t+2]&&k&&(u[1^t]+=M*p*x[t+2],r.uniforms.dataAxis=f,r.uniforms.screenOffset=u,r.uniforms.color=b[t+2],r.uniforms.angle=_[t+2],a.drawArrays(a.TRIANGLES,w,k))}),g.drawTitle=function(){var t=[0,0],e=[0,0];return function(){var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,c=r.pixelRatio;if(this.titleCount){for(var u=0;u<2;++u)e[u]=2*(o[u]*c-a[u])/(a[2+u]-a[u])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}}(),g.bind=(h=[0,0],p=[0,0],d=[0,0],function(){var t=this.plot,e=this.shader,r=t._tickBounds,n=t.dataBox,i=t.screenBox,a=t.viewBox;e.bind();for(var o=0;o<2;++o){var s=r[o],l=r[o+2]-s,c=.5*(n[o+2]+n[o]),u=n[o+2]-n[o],f=a[o],g=a[o+2]-f,v=i[o],m=i[o+2]-v;p[o]=2*l/u*g/m,h[o]=2*(s-c)/u*g/m}d[1]=2*t.pixelRatio/(i[3]-i[1]),d[0]=d[1]*(i[3]-i[1])/(i[2]-i[0]),e.uniforms.dataScale=p,e.uniforms.dataShift=h,e.uniforms.textScale=d,this.vbo.bind(),e.attributes.textCoordinate.pointer()}),g.update=function(t){var e,r,n,i,o,s=[],l=t.ticks,c=t.bounds;for(o=0;o<2;++o){var u=[Math.floor(s.length/3)],f=[-1/0],h=l[o];for(e=0;e<h.length;++e){var p=h[e],d=p.x,g=p.text,v=p.font||\"sans-serif\";i=p.fontSize||12;for(var m=1/(c[o+2]-c[o]),y=c[o],x=g.split(\"\\n\"),b=0;b<x.length;b++)for(n=a(v,x[b]).data,r=0;r<n.length;r+=2)s.push(n[r]*i,-n[r+1]*i-b*i*1.2,(d-y)*m);u.push(Math.floor(s.length/3)),f.push(d)}this.tickOffset[o]=u,this.tickX[o]=f}for(o=0;o<2;++o){for(this.labelOffset[o]=Math.floor(s.length/3),n=a(t.labelFont[o],t.labels[o],{textAlign:\"center\"}).data,i=t.labelSize[o],e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.labelCount[o]=Math.floor(s.length/3)-this.labelOffset[o]}for(this.titleOffset=Math.floor(s.length/3),n=a(t.titleFont,t.title).data,i=t.titleSize,e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.titleCount=Math.floor(s.length/3)-this.titleOffset,this.vbo.update(s)},g.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":283,\"binary-search-bounds\":285,\"gl-buffer\":240,\"gl-shader\":300,\"text-cache\":523}],285:[function(t,e,r){arguments[4][104][0].apply(r,arguments)},{dup:104}],286:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[e.drawingBufferWidth,e.drawingBufferHeight]),c=new l(e,r);return c.grid=i(c),c.text=a(c),c.line=o(c),c.box=s(c),c.update(t),c};var n=t(\"gl-select-static\"),i=t(\"./lib/grid\"),a=t(\"./lib/text\"),o=t(\"./lib/line\"),s=t(\"./lib/box\");function l(t,e){this.gl=t,this.pickBuffer=e,this.screenBox=[0,0,t.drawingBufferWidth,t.drawingBufferHeight],this.viewBox=[0,0,0,0],this.dataBox=[-10,-10,10,10],this.gridLineEnable=[!0,!0],this.gridLineWidth=[1,1],this.gridLineColor=[[0,0,0,1],[0,0,0,1]],this.pixelRatio=1,this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickEnable=[!0,!0,!0,!0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[15,15,15,15],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelEnable=[!0,!0,!0,!0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.titleCenter=[0,0],this.titleEnable=!0,this.titleAngle=0,this.titleColor=[0,0,0,1],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[4,4],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderLineEnable=[!0,!0,!0,!0],this.borderLineWidth=[2,2,2,2],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.grid=null,this.text=null,this.line=null,this.box=null,this.objects=[],this.overlays=[],this._tickBounds=[1/0,1/0,-1/0,-1/0],this.static=!1,this.dirty=!1,this.pickDirty=!1,this.pickDelay=120,this.pickRadius=10,this._pickTimeout=null,this._drawPick=this.drawPick.bind(this),this._depthCounter=0}var c=l.prototype;function u(t){for(var e=t.slice(),r=0;r<e.length;++r)e[r]=e[r].slice();return e}function f(t,e){return t.x-e.x}c.setDirty=function(){this.dirty=this.pickDirty=!0},c.setOverlayDirty=function(){this.dirty=!0},c.nextDepthValue=function(){return this._depthCounter++/65536},c.draw=function(){var t=this.gl,e=this.screenBox,r=this.viewBox,n=this.dataBox,i=this.pixelRatio,a=this.grid,o=this.line,s=this.text,l=this.objects;if(this._depthCounter=0,this.pickDirty&&(this._pickTimeout&&clearTimeout(this._pickTimeout),this.pickDirty=!1,this._pickTimeout=setTimeout(this._drawPick,this.pickDelay)),this.dirty){if(this.dirty=!1,t.bindFramebuffer(t.FRAMEBUFFER,null),t.enable(t.SCISSOR_TEST),t.disable(t.DEPTH_TEST),t.depthFunc(t.LESS),t.depthMask(!1),t.enable(t.BLEND),t.blendEquation(t.FUNC_ADD,t.FUNC_ADD),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),this.borderColor){t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var c=this.borderColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT)}t.scissor(r[0],r[1],r[2]-r[0],r[3]-r[1]),t.viewport(r[0],r[1],r[2]-r[0],r[3]-r[1]);var u=this.backgroundColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[3]),t.clear(t.COLOR_BUFFER_BIT),a.draw();var f=this.zeroLineEnable,h=this.zeroLineColor,p=this.zeroLineWidth;if(f[0]||f[1]){o.bind();for(var d=0;d<2;++d)if(f[d]&&n[d]<=0&&n[d+2]>=0){var g=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(g,e[1],g,e[3],p[d],h[d]):o.drawLine(e[0],g,e[2],g,p[d],h[d])}}for(d=0;d<l.length;++d)l[d].draw();t.viewport(e[0],e[1],e[2]-e[0],e[3]-e[1]),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]),this.grid.drawTickMarks(),o.bind();var v=this.borderLineEnable,m=this.borderLineWidth,y=this.borderLineColor;for(v[1]&&o.drawLine(r[0],r[1]-.5*m[1]*i,r[0],r[3]+.5*m[3]*i,m[1],y[1]),v[0]&&o.drawLine(r[0]-.5*m[0]*i,r[1],r[2]+.5*m[2]*i,r[1],m[0],y[0]),v[3]&&o.drawLine(r[2],r[1]-.5*m[1]*i,r[2],r[3]+.5*m[3]*i,m[3],y[3]),v[2]&&o.drawLine(r[0]-.5*m[0]*i,r[3],r[2]+.5*m[2]*i,r[3],m[2],y[2]),s.bind(),d=0;d<2;++d)s.drawTicks(d);this.titleEnable&&s.drawTitle();var x=this.overlays;for(d=0;d<x.length;++d)x[d].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}},c.drawPick=function(){if(!this.static){var t=this.pickBuffer;this.gl;this._pickTimeout=null,t.begin();for(var e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}},c.pick=function(t,e){if(!this.static){var r=this.pixelRatio,n=this.pickPixelRatio,i=this.viewBox,a=0|Math.round((t-i[0]/r)*n),o=0|Math.round((e-i[1]/r)*n),s=this.pickBuffer.query(a,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),c=this.objects,u=0;u<c.length;++u){var f=c[u].pick(a,o,l);if(f)return f}return null}},c.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},c.setDataBox=function(t){var e=this.dataBox;(e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3])&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},c.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},c.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]);this.screenBox;this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,i=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/i,10,10/i]),this.borderColor=!1!==t.borderColor&&(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=u(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=u(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=u(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!(\"titleEnable\"in t&&!t.titleEnable),this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=u(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=u(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=u(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var a=t.ticks||[[],[]],o=this._tickBounds;o[0]=o[1]=1/0,o[2]=o[3]=-1/0;for(var s=0;s<2;++s){var l=a[s].slice(0);0!==l.length&&(l.sort(f),o[s]=Math.min(o[s],l[0].x),o[s+2]=Math.max(o[s+2],l[l.length-1].x))}this.grid.update({bounds:o,ticks:a}),this.text.update({bounds:o,ticks:a,labels:t.labels||[\"x\",\"y\"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||[\"sans-serif\",\"sans-serif\"],title:t.title||\"\",titleSize:t.titleSize||18,titleFont:t.titleFont||\"sans-serif\"}),this.static=!!t.static,this.setDirty()},c.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();this.objects.length=0;for(t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},c.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},c.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},c.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},c.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},{\"./lib/box\":280,\"./lib/grid\":281,\"./lib/line\":282,\"./lib/text\":284,\"gl-select-static\":299}],287:[function(t,e,r){\"use strict\";e.exports=function(t,e){t=t||document.body,e=e||{};var r=[.01,1/0];\"distanceLimits\"in e&&(r[0]=e.distanceLimits[0],r[1]=e.distanceLimits[1]);\"zoomMin\"in e&&(r[0]=e.zoomMin);\"zoomMax\"in e&&(r[1]=e.zoomMax);var c=i({center:e.center||[0,0,0],up:e.up||[0,1,0],eye:e.eye||[0,0,10],mode:e.mode||\"orbit\",distanceLimits:r}),u=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],f=0,h=t.clientWidth,p=t.clientHeight,d={keyBindingMode:\"rotate\",enableWheel:!0,view:c,element:t,delay:e.delay||16,rotateSpeed:e.rotateSpeed||1,zoomSpeed:e.zoomSpeed||1,translateSpeed:e.translateSpeed||1,flipX:!!e.flipX,flipY:!!e.flipY,modes:c.modes,_ortho:e._ortho||e.projection&&\"orthographic\"===e.projection.type||!1,tick:function(){var e=n(),r=this.delay,i=e-2*r;c.idle(e-r),c.recalcMatrix(i),c.flush(e-(100+2*r));for(var a=!0,o=c.computedMatrix,s=0;s<16;++s)a=a&&u[s]===o[s],u[s]=o[s];var l=t.clientWidth===h&&t.clientHeight===p;return h=t.clientWidth,p=t.clientHeight,a?!l:(f=Math.exp(c.computedRadius[0]),!0)},lookAt:function(t,e,r){c.lookAt(c.lastT(),t,e,r)},rotate:function(t,e,r){c.rotate(c.lastT(),t,e,r)},pan:function(t,e,r){c.pan(c.lastT(),t,e,r)},translate:function(t,e,r){c.translate(c.lastT(),t,e,r)}};return Object.defineProperties(d,{matrix:{get:function(){return c.computedMatrix},set:function(t){return c.setMatrix(c.lastT(),t),c.computedMatrix},enumerable:!0},mode:{get:function(){return c.getMode()},set:function(t){var e=c.computedUp.slice(),r=c.computedEye.slice(),i=c.computedCenter.slice();if(c.setMode(t),\"turntable\"===t){var a=n();c._active.lookAt(a,r,i,e),c._active.lookAt(a+500,r,i,[0,0,1]),c._active.flush(a)}return c.getMode()},enumerable:!0},center:{get:function(){return c.computedCenter},set:function(t){return c.lookAt(c.lastT(),null,t),c.computedCenter},enumerable:!0},eye:{get:function(){return c.computedEye},set:function(t){return c.lookAt(c.lastT(),t),c.computedEye},enumerable:!0},up:{get:function(){return c.computedUp},set:function(t){return c.lookAt(c.lastT(),null,null,t),c.computedUp},enumerable:!0},distance:{get:function(){return f},set:function(t){return c.setDistance(c.lastT(),t),t},enumerable:!0},distanceLimits:{get:function(){return c.getDistanceLimits(r)},set:function(t){return c.setDistanceLimits(t),t},enumerable:!0}}),t.addEventListener(\"contextmenu\",function(t){return t.preventDefault(),!1}),d._lastX=-1,d._lastY=-1,d._lastMods={shift:!1,control:!1,alt:!1,meta:!1},d.enableMouseListeners=function(){function e(e,r,i,a){var o=d.keyBindingMode;if(!1!==o){var s=\"rotate\"===o,l=\"pan\"===o,u=\"zoom\"===o,h=!!a.control,p=!!a.alt,g=!!a.shift,v=!!(1&e),m=!!(2&e),y=!!(4&e),x=1/t.clientHeight,b=x*(r-d._lastX),_=x*(i-d._lastY),w=d.flipX?1:-1,k=d.flipY?1:-1,T=Math.PI*d.rotateSpeed,A=n();if(-1!==d._lastX&&-1!==d._lastY&&((s&&v&&!h&&!p&&!g||v&&!h&&!p&&g)&&c.rotate(A,w*T*b,-k*T*_,0),(l&&v&&!h&&!p&&!g||m||v&&h&&!p&&!g)&&c.pan(A,-d.translateSpeed*b*f,d.translateSpeed*_*f,0),u&&v&&!h&&!p&&!g||y||v&&!h&&p&&!g)){var M=-d.zoomSpeed*_/window.innerHeight*(A-c.lastT())*100;c.pan(A,0,0,f*(Math.exp(M)-1))}return d._lastX=r,d._lastY=i,d._lastMods=a,!0}}d.mouseListener=a(t,e),t.addEventListener(\"touchstart\",function(r){var n=s(r.changedTouches[0],t);e(0,n[0],n[1],d._lastMods),e(1,n[0],n[1],d._lastMods),r.preventDefault()},!!l&&{passive:!1}),t.addEventListener(\"touchmove\",function(r){var n=s(r.changedTouches[0],t);e(1,n[0],n[1],d._lastMods),r.preventDefault()},!!l&&{passive:!1}),t.addEventListener(\"touchend\",function(t){e(0,d._lastX,d._lastY,d._lastMods),t.preventDefault()},!!l&&{passive:!1}),d.wheelListener=o(t,function(t,e){if(!1!==d.keyBindingMode&&d.enableWheel){var r=d.flipX?1:-1,i=d.flipY?1:-1,a=n();if(Math.abs(t)>Math.abs(e))c.rotate(a,0,0,-t*r*Math.PI*d.rotateSpeed/window.innerWidth);else if(!d._ortho){var o=-d.zoomSpeed*i*e/window.innerHeight*(a-c.lastT())/20;c.pan(a,0,0,f*(Math.exp(o)-1))}}},!0)},d.enableMouseListeners(),d};var n=t(\"right-now\"),i=t(\"3d-view\"),a=t(\"mouse-change\"),o=t(\"mouse-wheel\"),s=t(\"mouse-event-offset\"),l=t(\"has-passive-events\")},{\"3d-view\":50,\"has-passive-events\":406,\"mouse-change\":430,\"mouse-event-offset\":431,\"mouse-wheel\":433,\"right-now\":491}],288:[function(t,e,r){var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision mediump float;\\n#define GLSLIFY 1\\nattribute vec2 position;\\nvarying vec2 uv;\\nvoid main() {\\n uv = position;\\n gl_Position = vec4(position, 0, 1);\\n}\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D accumBuffer;\\nvarying vec2 uv;\\n\\nvoid main() {\\n vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\\n gl_FragColor = min(vec4(1,1,1,1), accum);\\n}\"]);e.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec2\"}])}},{\"gl-shader\":300,glslify:404}],289:[function(t,e,r){\"use strict\";var n=t(\"./camera.js\"),i=t(\"gl-axes3d\"),a=t(\"gl-axes3d/properties\"),o=t(\"gl-spikes3d\"),s=t(\"gl-select-static\"),l=t(\"gl-fbo\"),c=t(\"a-big-triangle\"),u=t(\"mouse-change\"),f=t(\"mouse-wheel\"),h=t(\"gl-mat4/perspective\"),p=t(\"gl-mat4/ortho\"),d=t(\"./lib/shader\"),g=t(\"is-mobile\")({tablet:!0});function v(){this.mouse=[-1,-1],this.screen=null,this.distance=1/0,this.index=null,this.dataCoordinate=null,this.dataPosition=null,this.object=null,this.data=null}function m(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){var r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}if(e>0){r=Math.round(Math.pow(10,e));return Math.ceil(t/r)*r}return Math.ceil(t)}function y(t){return\"boolean\"!=typeof t||t}e.exports={createScene:function(t){(t=t||{}).camera=t.camera||{};var e=t.canvas;if(!e)if(e=document.createElement(\"canvas\"),t.container){var r=t.container;r.appendChild(e)}else document.body.appendChild(e);var x=t.gl;x||(x=function(t,e){var r=null;try{(r=t.getContext(\"webgl\",e))||(r=t.getContext(\"experimental-webgl\",e))}catch(t){return null}return r}(e,t.glOptions||{premultipliedAlpha:!0,antialias:!0,preserveDrawingBuffer:g}));if(!x)throw new Error(\"webgl not supported\");var b=t.bounds||[[-10,-10,-10],[10,10,10]],_=new v,w=l(x,[x.drawingBufferWidth,x.drawingBufferHeight],{preferFloat:!g}),k=d(x),T=t.cameraObject&&!0===t.cameraObject._ortho||t.camera.projection&&\"orthographic\"===t.camera.projection.type||!1,A={eye:t.camera.eye||[2,0,0],center:t.camera.center||[0,0,0],up:t.camera.up||[0,1,0],zoomMin:t.camera.zoomMax||.1,zoomMax:t.camera.zoomMin||100,mode:t.camera.mode||\"turntable\",_ortho:T},M=t.axes||{},S=i(x,M);S.enable=!M.disable;var E=t.spikes||{},C=o(x,E),L=[],z=[],O=[],I=[],D=!0,P=!0,R=new Array(16),F=new Array(16),B={view:null,projection:R,model:F,_ortho:!1},P=!0,N=[x.drawingBufferWidth,x.drawingBufferHeight],j=t.cameraObject||n(e,A),V={gl:x,contextLost:!1,pixelRatio:t.pixelRatio||1,canvas:e,selection:_,camera:j,axes:S,axesPixels:null,spikes:C,bounds:b,objects:L,shape:N,aspect:t.aspectRatio||[1,1,1],pickRadius:t.pickRadius||10,zNear:t.zNear||.01,zFar:t.zFar||1e3,fovy:t.fovy||Math.PI/4,clearColor:t.clearColor||[0,0,0,0],autoResize:y(t.autoResize),autoBounds:y(t.autoBounds),autoScale:!!t.autoScale,autoCenter:y(t.autoCenter),clipToBounds:y(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:B,oncontextloss:null,mouseListener:null,_stopped:!1},U=[x.drawingBufferWidth/V.pixelRatio|0,x.drawingBufferHeight/V.pixelRatio|0];function H(){if(!V._stopped&&V.autoResize){var t=e.parentNode,r=1,n=1;t&&t!==document.body?(r=t.clientWidth,n=t.clientHeight):(r=window.innerWidth,n=window.innerHeight);var i=0|Math.ceil(r*V.pixelRatio),a=0|Math.ceil(n*V.pixelRatio);if(i!==e.width||a!==e.height){e.width=i,e.height=a;var o=e.style;o.position=o.position||\"absolute\",o.left=\"0px\",o.top=\"0px\",o.width=r+\"px\",o.height=n+\"px\",D=!0}}}V.autoResize&&H();function q(){for(var t=L.length,e=I.length,r=0;r<e;++r)O[r]=0;t:for(var r=0;r<t;++r){var n=L[r],i=n.pickSlots;if(i){for(var a=0;a<e;++a)if(O[a]+i<255){z[r]=a,n.setPickBase(O[a]+1),O[a]+=i;continue t}var o=s(x,N);z[r]=e,I.push(o),O.push(i),n.setPickBase(1),e+=1}else z[r]=-1}for(;e>0&&0===O[e-1];)O.pop(),I.pop().dispose()}function G(){if(V.contextLost)return!0;x.isContextLost()&&(V.contextLost=!0,V.mouseListener.enabled=!1,V.selection.object=null,V.oncontextloss&&V.oncontextloss())}window.addEventListener(\"resize\",H),V.update=function(t){V._stopped||(t=t||{},D=!0,P=!0)},V.add=function(t){V._stopped||(t.axes=S,L.push(t),z.push(-1),D=!0,P=!0,q())},V.remove=function(t){if(!V._stopped){var e=L.indexOf(t);e<0||(L.splice(e,1),z.pop(),D=!0,P=!0,q())}},V.dispose=function(){if(!V._stopped&&(V._stopped=!0,window.removeEventListener(\"resize\",H),e.removeEventListener(\"webglcontextlost\",G),V.mouseListener.enabled=!1,!V.contextLost)){S.dispose(),C.dispose();for(var t=0;t<L.length;++t)L[t].dispose();w.dispose();for(var t=0;t<I.length;++t)I[t].dispose();k.dispose(),x=null,S=null,C=null,L=[]}},V.wheelListener=f(e,function(t,e){if(!1!==j.keyBindingMode&&j.enableWheel&&j._ortho){var r=t>e?1.1:1/1.1;V.aspect[0]*=r,V.aspect[1]*=r,V.aspect[2]*=r,V.redraw()}},!0),V._mouseRotating=!1,V._prevButtons=0,V.enableMouseListeners=function(){V.mouseListener=u(e,function(t,e,r){if(!V._stopped){var n=I.length,i=L.length,a=_.object;_.distance=1/0,_.mouse[0]=e,_.mouse[1]=r,_.object=null,_.screen=null,_.dataCoordinate=_.dataPosition=null;var o=!1;if(t&&V._prevButtons)V._mouseRotating=!0;else{V._mouseRotating&&(P=!0),V._mouseRotating=!1;for(var s=0;s<n;++s){var l=I[s].query(e,U[1]-r-1,V.pickRadius);if(l){if(l.distance>_.distance)continue;for(var c=0;c<i;++c){var u=L[c];if(z[c]===s){var f=u.pick(l);f&&(_.buttons=t,_.screen=l.coord,_.distance=l.distance,_.object=u,_.index=f.distance,_.dataPosition=f.position,_.dataCoordinate=f.dataCoordinate,_.data=f,o=!0)}}}}}a&&a!==_.object&&(a.highlight&&a.highlight(null),D=!0),_.object&&(_.object.highlight&&_.object.highlight(_.data),D=!0),(o=o||_.object!==a)&&V.onselect&&V.onselect(_),1&t&&!(1&V._prevButtons)&&V.onclick&&V.onclick(_),V._prevButtons=t}})},e.addEventListener(\"webglcontextlost\",G);var Y=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],W=[Y[0].slice(),Y[1].slice()];function X(){if(!G()){H();var t=V.camera.tick();B.view=V.camera.matrix,D=D||t,P=P||t,S.pixelRatio=V.pixelRatio,C.pixelRatio=V.pixelRatio;var e=L.length,r=Y[0],n=Y[1];r[0]=r[1]=r[2]=1/0,n[0]=n[1]=n[2]=-1/0;for(var i=0;i<e;++i){var o=L[i];o.pixelRatio=V.pixelRatio,o.axes=V.axes,D=D||!!o.dirty,P=P||!!o.dirty;var s=o.bounds;if(s)for(var l=s[0],u=s[1],f=0;f<3;++f)r[f]=Math.min(r[f],l[f]),n[f]=Math.max(n[f],u[f])}var d=V.bounds;if(V.autoBounds)for(var f=0;f<3;++f){if(n[f]<r[f])r[f]=-1,n[f]=1;else{r[f]===n[f]&&(r[f]-=1,n[f]+=1);var g=.05*(n[f]-r[f]);r[f]=r[f]-g,n[f]=n[f]+g}d[0][f]=r[f],d[1][f]=n[f]}for(var v=!1,f=0;f<3;++f)v=v||W[0][f]!==d[0][f]||W[1][f]!==d[1][f],W[0][f]=d[0][f],W[1][f]=d[1][f];if(P=P||v,D=D||v){if(v){for(var y=[0,0,0],i=0;i<3;++i)y[i]=m((d[1][i]-d[0][i])/10);S.autoTicks?S.update({bounds:d,tickSpacing:y}):S.update({bounds:d})}var b=x.drawingBufferWidth,A=x.drawingBufferHeight;N[0]=b,N[1]=A,U[0]=0|Math.max(b/V.pixelRatio,1),U[1]=0|Math.max(A/V.pixelRatio,1),T?(p(R,-b/A,b/A,-1,1,V.zNear,V.zFar),B._ortho=!0):(h(R,V.fovy,b/A,V.zNear,V.zFar),B._ortho=!1);for(var i=0;i<16;++i)F[i]=0;F[15]=1;for(var M=0,i=0;i<3;++i)M=Math.max(M,d[1][i]-d[0][i]);for(var i=0;i<3;++i)V.autoScale?F[5*i]=V.aspect[i]/(d[1][i]-d[0][i]):F[5*i]=1/M,V.autoCenter&&(F[12+i]=.5*-F[5*i]*(d[0][i]+d[1][i]));for(var i=0;i<e;++i){var o=L[i];o.axesBounds=d,V.clipToBounds&&(o.clipBounds=d)}_.object&&(V.snapToData?C.position=_.dataCoordinate:C.position=_.dataPosition,C.bounds=d),P&&(P=!1,function(){if(G())return;x.colorMask(!0,!0,!0,!0),x.depthMask(!0),x.disable(x.BLEND),x.enable(x.DEPTH_TEST);for(var t=L.length,e=I.length,r=0;r<e;++r){var n=I[r];n.shape=U,n.begin();for(var i=0;i<t;++i)if(z[i]===r){var a=L[i];a.drawPick&&(a.pixelRatio=1,a.drawPick(B))}n.end()}}()),V.axesPixels=a(V.axes,B,b,A),V.onrender&&V.onrender(),x.bindFramebuffer(x.FRAMEBUFFER,null),x.viewport(0,0,b,A);var E=V.clearColor;x.clearColor(E[0],E[1],E[2],E[3]),x.clear(x.COLOR_BUFFER_BIT|x.DEPTH_BUFFER_BIT),x.depthMask(!0),x.colorMask(!0,!0,!0,!0),x.enable(x.DEPTH_TEST),x.depthFunc(x.LEQUAL),x.disable(x.BLEND),x.disable(x.CULL_FACE);var O=!1;S.enable&&(O=O||S.isTransparent(),S.draw(B)),C.axes=S,_.object&&C.draw(B),x.disable(x.CULL_FACE);for(var i=0;i<e;++i){var o=L[i];o.axes=S,o.pixelRatio=V.pixelRatio,o.isOpaque&&o.isOpaque()&&o.draw(B),o.isTransparent&&o.isTransparent()&&(O=!0)}if(O){w.shape=N,w.bind(),x.clear(x.DEPTH_BUFFER_BIT),x.colorMask(!1,!1,!1,!1),x.depthMask(!0),x.depthFunc(x.LESS),S.enable&&S.isTransparent()&&S.drawTransparent(B);for(var i=0;i<e;++i){var o=L[i];o.isOpaque&&o.isOpaque()&&o.draw(B)}x.enable(x.BLEND),x.blendEquation(x.FUNC_ADD),x.blendFunc(x.ONE,x.ONE_MINUS_SRC_ALPHA),x.colorMask(!0,!0,!0,!0),x.depthMask(!1),x.clearColor(0,0,0,0),x.clear(x.COLOR_BUFFER_BIT),S.isTransparent()&&S.drawTransparent(B);for(var i=0;i<e;++i){var o=L[i];o.isTransparent&&o.isTransparent()&&o.drawTransparent(B)}x.bindFramebuffer(x.FRAMEBUFFER,null),x.blendFunc(x.ONE,x.ONE_MINUS_SRC_ALPHA),x.disable(x.DEPTH_TEST),k.bind(),w.color[0].bind(0),k.uniforms.accumBuffer=0,c(x),x.disable(x.BLEND)}D=!1;for(var i=0;i<e;++i)L[i].dirty=!1}}}return V.enableMouseListeners(),function t(){V._stopped||V.contextLost||(X(),requestAnimationFrame(t))}(),V.redraw=function(){V._stopped||(D=!0,X())},V},createCamera:n}},{\"./camera.js\":287,\"./lib/shader\":288,\"a-big-triangle\":52,\"gl-axes3d\":232,\"gl-axes3d/properties\":239,\"gl-fbo\":248,\"gl-mat4/ortho\":267,\"gl-mat4/perspective\":268,\"gl-select-static\":299,\"gl-spikes3d\":309,\"is-mobile\":415,\"mouse-change\":430,\"mouse-wheel\":433}],290:[function(t,e,r){var n=t(\"glslify\");r.pointVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform float pointCloud;\\n\\nhighp float rand(vec2 co) {\\n highp float a = 12.9898;\\n highp float b = 78.233;\\n highp float c = 43758.5453;\\n highp float d = dot(co.xy, vec2(a, b));\\n highp float e = mod(d, 3.14);\\n return fract(sin(e) * c);\\n}\\n\\nvoid main() {\\n vec3 hgPosition = matrix * vec3(position, 1);\\n gl_Position = vec4(hgPosition.xy, 0, hgPosition.z);\\n // if we don't jitter the point size a bit, overall point cloud\\n // saturation 'jumps' on zooming, which is disturbing and confusing\\n gl_PointSize = pointSize * ((19.5 + rand(position)) / 20.0);\\n if(pointCloud != 0.0) { // pointCloud is truthy\\n // get the same square surface as circle would be\\n gl_PointSize *= 0.886;\\n }\\n}\"]),r.pointFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\nuniform float pointCloud;\\n\\nvoid main() {\\n float radius;\\n vec4 baseColor;\\n if(pointCloud != 0.0) { // pointCloud is truthy\\n if(centerFraction == 1.0) {\\n gl_FragColor = color;\\n } else {\\n gl_FragColor = mix(borderColor, color, centerFraction);\\n }\\n } else {\\n radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n if(radius > 1.0) {\\n discard;\\n }\\n baseColor = mix(borderColor, color, step(radius, centerFraction));\\n gl_FragColor = vec4(baseColor.rgb * baseColor.a, baseColor.a);\\n }\\n}\\n\"]),r.pickVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n vec3 hgPosition = matrix * vec3(position, 1);\\n gl_Position = vec4(hgPosition.xy, 0, hgPosition.z);\\n gl_PointSize = pointSize;\\n\\n vec4 id = pickId + pickOffset;\\n id.y += floor(id.x / 256.0);\\n id.x -= floor(id.x / 256.0) * 256.0;\\n\\n id.z += floor(id.y / 256.0);\\n id.y -= floor(id.y / 256.0) * 256.0;\\n\\n id.w += floor(id.z / 256.0);\\n id.z -= floor(id.z / 256.0) * 256.0;\\n\\n fragId = id;\\n}\\n\"]),r.pickFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n float radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n if(radius > 1.0) {\\n discard;\\n }\\n gl_FragColor = fragId / 255.0;\\n}\\n\"])},{glslify:404}],291:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"typedarray-pool\"),o=t(\"./lib/shader\");function s(t,e,r,n,i){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.shader=n,this.pickShader=i,this.sizeMin=.5,this.sizeMinCap=2,this.sizeMax=20,this.areaRatio=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.blend=!1,this.pickOffset=0,this.points=null}e.exports=function(t,e){var r=t.gl,a=i(r),l=i(r),c=n(r,o.pointVertex,o.pointFragment),u=n(r,o.pickVertex,o.pickFragment),f=new s(t,a,l,c,u);return f.update(e),t.addObject(f),f};var l,c,u=s.prototype;u.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},u.update=function(t){var e;function r(e,r){return e in t?t[e]:r}t=t||{},this.sizeMin=r(\"sizeMin\",.5),this.sizeMax=r(\"sizeMax\",20),this.color=r(\"color\",[1,0,0,1]).slice(),this.areaRatio=r(\"areaRatio\",1),this.borderColor=r(\"borderColor\",[0,0,0,1]).slice(),this.blend=r(\"blend\",!1);var n=t.positions.length>>>1,i=t.positions instanceof Float32Array,o=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,s=t.positions,l=i?s:a.mallocFloat32(s.length),c=o?t.idToIndex:a.mallocInt32(n);if(i||l.set(s),!o)for(l.set(s),e=0;e<n;e++)c[e]=e;this.points=s,this.offsetBuffer.update(l),this.pickBuffer.update(c),i||a.free(l),o||a.free(c),this.pointCount=n,this.pickOffset=0},u.unifiedDraw=(l=[1,0,0,0,1,0,0,0,1],c=[0,0,0,0],function(t){var e=void 0!==t,r=e?this.pickShader:this.shader,n=this.plot.gl,i=this.plot.dataBox;if(0===this.pointCount)return t;var a=i[2]-i[0],o=i[3]-i[1],s=function(t,e){var r,n=0,i=t.length>>>1;for(r=0;r<i;r++){var a=t[2*r],o=t[2*r+1];a>=e[0]&&a<=e[2]&&o>=e[1]&&o<=e[3]&&n++}return n}(this.points,i),u=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(s,.33333)));l[0]=2/a,l[4]=2/o,l[6]=-2*i[0]/a-1,l[7]=-2*i[1]/o-1,this.offsetBuffer.bind(),r.bind(),r.attributes.position.pointer(),r.uniforms.matrix=l,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointCloud=u<5,r.uniforms.pointSize=u,r.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),e&&(c[0]=255&t,c[1]=t>>8&255,c[2]=t>>16&255,c[3]=t>>24&255,this.pickBuffer.bind(),r.attributes.pickId.pointer(n.UNSIGNED_BYTE),r.uniforms.pickOffset=c,this.pickOffset=t);var f=n.getParameter(n.BLEND),h=n.getParameter(n.DITHER);return f&&!this.blend&&n.disable(n.BLEND),h&&n.disable(n.DITHER),n.drawArrays(n.POINTS,0,this.pointCount),f&&!this.blend&&n.enable(n.BLEND),h&&n.enable(n.DITHER),t+this.pointCount}),u.draw=u.unifiedDraw,u.drawPick=u.unifiedDraw,u.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(r<n||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},{\"./lib/shader\":290,\"gl-buffer\":240,\"gl-shader\":300,\"typedarray-pool\":532}],292:[function(t,e,r){e.exports=function(t,e,r,n){var i,a,o,s,l,c=e[0],u=e[1],f=e[2],h=e[3],p=r[0],d=r[1],g=r[2],v=r[3];(a=c*p+u*d+f*g+h*v)<0&&(a=-a,p=-p,d=-d,g=-g,v=-v);1-a>1e-6?(i=Math.acos(a),o=Math.sin(i),s=Math.sin((1-n)*i)/o,l=Math.sin(n*i)/o):(s=1-n,l=n);return t[0]=s*c+l*p,t[1]=s*u+l*d,t[2]=s*f+l*g,t[3]=s*h+l*v,t}},{}],293:[function(t,e,r){\"use strict\";e.exports=function(t){return t||0===t?t.toString():\"\"}},{}],294:[function(t,e,r){\"use strict\";var n=t(\"vectorize-text\");e.exports=function(t,e,r){var a=i[e];a||(a=i[e]={});if(t in a)return a[t];var o={textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e,lineSpacing:1.25,styletags:{breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},triangles:!0},s=n(t,o);o.triangles=!1;var l,c,u=n(t,o);if(r&&1!==r){for(l=0;l<s.positions.length;++l)for(c=0;c<s.positions[l].length;++c)s.positions[l][c]/=r;for(l=0;l<u.positions.length;++l)for(c=0;c<u.positions[l].length;++c)u.positions[l][c]/=r}var f=[[1/0,1/0],[-1/0,-1/0]],h=u.positions.length;for(l=0;l<h;++l){var p=u.positions[l];for(c=0;c<2;++c)f[0][c]=Math.min(f[0][c],p[c]),f[1][c]=Math.max(f[1][c],p[c])}return a[t]=[s,u,f]};var i={}},{\"vectorize-text\":537}],295:[function(t,e,r){var n=t(\"gl-shader\"),i=t(\"glslify\"),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0,0,0,0);\\n } else {\\n float scale = 1.0;\\n if(distance(highlightId, id) < 0.0001) {\\n scale = highlightScale;\\n }\\n\\n vec4 worldPosition = model * vec4(position, 1);\\n vec4 viewPosition = view * worldPosition;\\n viewPosition = viewPosition / viewPosition.w;\\n vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n\\n gl_Position = clipPosition;\\n interpColor = color;\\n pickId = id;\\n dataCoordinate = position;\\n }\\n}\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0,0,0,0);\\n } else {\\n float scale = pixelRatio;\\n if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n scale *= highlightScale;\\n }\\n\\n vec4 worldPosition = model * vec4(position, 1.0);\\n vec4 viewPosition = view * worldPosition;\\n vec4 clipPosition = projection * viewPosition;\\n clipPosition /= clipPosition.w;\\n\\n gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n interpColor = color;\\n pickId = id;\\n dataCoordinate = position;\\n }\\n}\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0,0,0,0);\\n } else {\\n float lscale = pixelRatio * scale;\\n if(distance(highlightId, id) < 0.0001) {\\n lscale *= highlightScale;\\n }\\n\\n vec4 clipCenter = projection * view * model * vec4(position, 1);\\n vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n gl_Position = clipPosition;\\n interpColor = color;\\n pickId = id;\\n dataCoordinate = dataPosition;\\n }\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (\\n outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) ||\\n interpColor.a * opacity == 0.\\n ) discard;\\n gl_FragColor = interpColor * opacity;\\n}\\n\"]),c=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard;\\n\\n gl_FragColor = vec4(pickGroup, pickId.bgr);\\n}\"]),u=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],f={vertex:a,fragment:l,attributes:u},h={vertex:o,fragment:l,attributes:u},p={vertex:s,fragment:l,attributes:u},d={vertex:a,fragment:c,attributes:u},g={vertex:o,fragment:c,attributes:u},v={vertex:s,fragment:c,attributes:u};function m(t,e){var r=n(t,e),i=r.attributes;return i.position.location=0,i.color.location=1,i.glyph.location=2,i.id.location=3,r}r.createPerspective=function(t){return m(t,f)},r.createOrtho=function(t){return m(t,h)},r.createProject=function(t){return m(t,p)},r.createPickPerspective=function(t){return m(t,d)},r.createPickOrtho=function(t){return m(t,g)},r.createPickProject=function(t){return m(t,v)}},{\"gl-shader\":300,glslify:404}],296:[function(t,e,r){\"use strict\";var n=t(\"is-string-blank\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"typedarray-pool\"),s=t(\"gl-mat4/multiply\"),l=t(\"./lib/shaders\"),c=t(\"./lib/glyphs\"),u=t(\"./lib/get-simple-string\"),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function p(t,e,r,n){return h(n,n),h(n,n),h(n,n)}function d(t,e){this.index=t,this.dataCoordinate=this.position=e}function g(t){return!0===t?1:t>1?1:t}function v(t,e,r,n,i,a,o,s,l,c,u,f){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=a,this.glyphBuffer=o,this.idBuffer=s,this.vao=l,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.hasAlpha=!1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.projectHasAlpha=!1,this.pickId=0,this.pickPerspectiveShader=c,this.pickOrthoShader=u,this.pickProjectShader=f,this.points=[],this._selectResult=new d(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.dirty=!0}e.exports=function(t){var e=t.gl,r=l.createPerspective(e),n=l.createOrtho(e),o=l.createProject(e),s=l.createPickPerspective(e),c=l.createPickOrtho(e),u=l.createPickProject(e),f=i(e),h=i(e),p=i(e),d=i(e),g=a(e,[{buffer:f,size:3,type:e.FLOAT},{buffer:h,size:4,type:e.FLOAT},{buffer:p,size:2,type:e.FLOAT},{buffer:d,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),m=new v(e,r,n,o,f,h,p,d,g,s,c,u);return m.update(t),m};var m=v.prototype;m.pickSlots=1,m.setPickBase=function(t){this.pickId=t},m.isTransparent=function(){if(this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&this.projectHasAlpha)return!0;return!1},m.isOpaque=function(){if(!this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&!this.projectHasAlpha)return!0;return!1};var y=[0,0],x=[0,0,0],b=[0,0,0],_=[0,0,0,1],w=[0,0,0,1],k=f.slice(),T=[0,0,0],A=[[0,0,0],[0,0,0]];function M(t){return t[0]=t[1]=t[2]=0,t}function S(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function E(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}function C(t,e,r,n){var i,a=e.axesProject,o=e.gl,l=t.uniforms,c=r.model||f,u=r.view||f,h=r.projection||f,d=e.axesBounds,g=function(t){for(var e=A,r=0;r<2;++r)for(var n=0;n<3;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}(e.clipBounds);i=e.axes&&e.axes.lastCubeProps?e.axes.lastCubeProps.axis:[1,1,1],y[0]=2/o.drawingBufferWidth,y[1]=2/o.drawingBufferHeight,t.bind(),l.view=u,l.projection=h,l.screenSize=y,l.highlightId=e.highlightId,l.highlightScale=e.highlightScale,l.clipBounds=g,l.pickGroup=e.pickId/255,l.pixelRatio=n;for(var v=0;v<3;++v)if(a[v]){l.scale=e.projectScale[v],l.opacity=e.projectOpacity[v];for(var m=k,C=0;C<16;++C)m[C]=0;for(C=0;C<4;++C)m[5*C]=1;m[5*v]=0,i[v]<0?m[12+v]=d[0][v]:m[12+v]=d[1][v],s(m,c,m),l.model=m;var L=(v+1)%3,z=(v+2)%3,O=M(x),I=M(b);O[L]=1,I[z]=1;var D=p(0,0,0,S(_,O)),P=p(0,0,0,S(w,I));if(Math.abs(D[1])>Math.abs(P[1])){var R=D;D=P,P=R,R=O,O=I,I=R;var F=L;L=z,z=F}D[0]<0&&(O[L]=-1),P[1]>0&&(I[z]=-1);var B=0,N=0;for(C=0;C<4;++C)B+=Math.pow(c[4*L+C],2),N+=Math.pow(c[4*z+C],2);O[L]/=Math.sqrt(B),I[z]/=Math.sqrt(N),l.axes[0]=O,l.axes[1]=I,l.fragClipBounds[0]=E(T,g[0],v,-1e8),l.fragClipBounds[1]=E(T,g[1],v,1e8),e.vao.bind(),e.vao.draw(o.TRIANGLES,e.vertexCount),e.lineWidth>0&&(o.lineWidth(e.lineWidth*n),e.vao.draw(o.LINES,e.lineVertexCount,e.vertexCount)),e.vao.unbind()}}var L=[[-1e8,-1e8,-1e8],[1e8,1e8,1e8]];function z(t,e,r,n,i,a,o){var s=r.gl;if((a===r.projectHasAlpha||o)&&C(e,r,n,i),a===r.hasAlpha||o){t.bind();var l=t.uniforms;l.model=n.model||f,l.view=n.view||f,l.projection=n.projection||f,y[0]=2/s.drawingBufferWidth,y[1]=2/s.drawingBufferHeight,l.screenSize=y,l.highlightId=r.highlightId,l.highlightScale=r.highlightScale,l.fragClipBounds=L,l.clipBounds=r.axes.bounds,l.opacity=r.opacity,l.pickGroup=r.pickId/255,l.pixelRatio=i,r.vao.bind(),r.vao.draw(s.TRIANGLES,r.vertexCount),r.lineWidth>0&&(s.lineWidth(r.lineWidth*i),r.vao.draw(s.LINES,r.lineVertexCount,r.vertexCount)),r.vao.unbind()}}function O(t,e,r,i){var a;a=Array.isArray(t)?e<t.length?t[e]:void 0:t,a=u(a);var o=!0;n(a)&&(a=\"\\u25bc\",o=!1);var s=c(a,r,i);return{mesh:s[0],lines:s[1],bounds:s[2],visible:o}}m.draw=function(t){z(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!1,!1)},m.drawTransparent=function(t){z(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!0,!1)},m.drawPick=function(t){z(this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader,this.pickProjectShader,this,t,1,!0,!0)},m.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||e<0)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;i<3;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},m.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},m.update=function(t){if(\"perspective\"in(t=t||{})&&(this.useOrtho=!t.perspective),\"orthographic\"in t&&(this.useOrtho=!!t.orthographic),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"project\"in t)if(Array.isArray(t.project))this.axesProject=t.project;else{var e=!!t.project;this.axesProject=[e,e,e]}if(\"projectScale\"in t)if(Array.isArray(t.projectScale))this.projectScale=t.projectScale.slice();else{var r=+t.projectScale;this.projectScale=[r,r,r]}if(this.projectHasAlpha=!1,\"projectOpacity\"in t){if(Array.isArray(t.projectOpacity))this.projectOpacity=t.projectOpacity.slice();else{r=+t.projectOpacity;this.projectOpacity=[r,r,r]}for(var n=0;n<3;++n)this.projectOpacity[n]=g(this.projectOpacity[n]),this.projectOpacity[n]<1&&(this.projectHasAlpha=!0)}this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=g(t.opacity),this.opacity<1&&(this.hasAlpha=!0)),this.dirty=!0;var i,a,s=t.position,l=t.font||\"normal\",c=t.alignment||[0,0];if(2===c.length)i=c[0],a=c[1];else{i=[],a=[];for(n=0;n<c.length;++n)i[n]=c[n][0],a[n]=c[n][1]}var u=[1/0,1/0,1/0],f=[-1/0,-1/0,-1/0],h=t.glyph,p=t.color,d=t.size,v=t.angle,m=t.lineColor,y=-1,x=0,b=0,_=0;if(s.length){_=s.length;t:for(n=0;n<_;++n){for(var w=s[n],k=0;k<3;++k)if(isNaN(w[k])||!isFinite(w[k]))continue t;var T=(N=O(h,n,l,this.pixelRatio)).mesh,A=N.lines,M=N.bounds;x+=3*T.cells.length,b+=2*A.edges.length}}var S=x+b,E=o.mallocFloat(3*S),C=o.mallocFloat(4*S),L=o.mallocFloat(2*S),z=o.mallocUint32(S);if(S>0){var I=0,D=x,P=[0,0,0,1],R=[0,0,0,1],F=Array.isArray(p)&&Array.isArray(p[0]),B=Array.isArray(m)&&Array.isArray(m[0]);t:for(n=0;n<_;++n){y+=1;for(w=s[n],k=0;k<3;++k){if(isNaN(w[k])||!isFinite(w[k]))continue t;f[k]=Math.max(f[k],w[k]),u[k]=Math.min(u[k],w[k])}T=(N=O(h,n,l,this.pixelRatio)).mesh,A=N.lines,M=N.bounds;var N,j=N.visible;if(j)if(Array.isArray(p)){if(3===(V=F?n<p.length?p[n]:[0,0,0,0]:p).length){for(k=0;k<3;++k)P[k]=V[k];P[3]=1}else if(4===V.length){for(k=0;k<4;++k)P[k]=V[k];!this.hasAlpha&&V[3]<1&&(this.hasAlpha=!0)}}else P[0]=P[1]=P[2]=0,P[3]=1;else P=[1,1,1,0];if(j)if(Array.isArray(m)){var V;if(3===(V=B?n<m.length?m[n]:[0,0,0,0]:m).length){for(k=0;k<3;++k)R[k]=V[k];R[k]=1}else if(4===V.length){for(k=0;k<4;++k)R[k]=V[k];!this.hasAlpha&&V[3]<1&&(this.hasAlpha=!0)}}else R[0]=R[1]=R[2]=0,R[3]=1;else R=[1,1,1,0];var U=.5;j?Array.isArray(d)?U=n<d.length?+d[n]:12:d?U=+d:this.useOrtho&&(U=12):U=0;var H=0;Array.isArray(v)?H=n<v.length?+v[n]:0:v&&(H=+v);var q=Math.cos(H),G=Math.sin(H);for(w=s[n],k=0;k<3;++k)f[k]=Math.max(f[k],w[k]),u[k]=Math.min(u[k],w[k]);var Y=i,W=a;Y=0;Array.isArray(i)?Y=n<i.length?i[n]:0:i&&(Y=i);W=0;Array.isArray(a)?W=n<a.length?a[n]:0:a&&(W=a);var X=[Y*=Y>0?1-M[0][0]:Y<0?1+M[1][0]:1,W*=W>0?1-M[0][1]:W<0?1+M[1][1]:1],Z=T.cells||[],$=T.positions||[];for(k=0;k<Z.length;++k)for(var J=Z[k],K=0;K<3;++K){for(var Q=0;Q<3;++Q)E[3*I+Q]=w[Q];for(Q=0;Q<4;++Q)C[4*I+Q]=P[Q];z[I]=y;var tt=$[J[K]];L[2*I]=U*(q*tt[0]-G*tt[1]+X[0]),L[2*I+1]=U*(G*tt[0]+q*tt[1]+X[1]),I+=1}for(Z=A.edges,$=A.positions,k=0;k<Z.length;++k)for(J=Z[k],K=0;K<2;++K){for(Q=0;Q<3;++Q)E[3*D+Q]=w[Q];for(Q=0;Q<4;++Q)C[4*D+Q]=R[Q];z[D]=y;tt=$[J[K]];L[2*D]=U*(q*tt[0]-G*tt[1]+X[0]),L[2*D+1]=U*(G*tt[0]+q*tt[1]+X[1]),D+=1}}}this.bounds=[u,f],this.points=s,this.pointCount=s.length,this.vertexCount=x,this.lineVertexCount=b,this.pointBuffer.update(E),this.colorBuffer.update(C),this.glyphBuffer.update(L),this.idBuffer.update(z),o.free(E),o.free(C),o.free(L),o.free(z)},m.dispose=function(){this.shader.dispose(),this.orthoShader.dispose(),this.pickPerspectiveShader.dispose(),this.pickOrthoShader.dispose(),this.vao.dispose(),this.pointBuffer.dispose(),this.colorBuffer.dispose(),this.glyphBuffer.dispose(),this.idBuffer.dispose()}},{\"./lib/get-simple-string\":293,\"./lib/glyphs\":294,\"./lib/shaders\":295,\"gl-buffer\":240,\"gl-mat4/multiply\":266,\"gl-vao\":322,\"is-string-blank\":418,\"typedarray-pool\":532}],297:[function(t,e,r){\"use strict\";var n=t(\"glslify\");r.boxVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 vertex;\\n\\nuniform vec2 cornerA, cornerB;\\n\\nvoid main() {\\n gl_Position = vec4(mix(cornerA, cornerB, vertex), 0, 1);\\n}\\n\"]),r.boxFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n gl_FragColor = color;\\n}\\n\"])},{glslify:404}],298:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"./lib/shaders\");function o(t,e,r){this.plot=t,this.boxBuffer=e,this.boxShader=r,this.enabled=!0,this.selectBox=[1/0,1/0,-1/0,-1/0],this.borderColor=[0,0,0,1],this.innerFill=!1,this.innerColor=[0,0,0,.25],this.outerFill=!0,this.outerColor=[0,0,0,.5],this.borderWidth=10}e.exports=function(t,e){var r=t.gl,s=i(r,[0,0,0,1,1,0,1,1]),l=n(r,a.boxVertex,a.boxFragment),c=new o(t,s,l);return c.update(e),t.addOverlay(c),c};var s=o.prototype;s.draw=function(){if(this.enabled){var t=this.plot,e=this.selectBox,r=this.borderWidth,n=(this.innerFill,this.innerColor),i=(this.outerFill,this.outerColor),a=this.borderColor,o=t.box,s=t.screenBox,l=t.dataBox,c=t.viewBox,u=t.pixelRatio,f=(e[0]-l[0])*(c[2]-c[0])/(l[2]-l[0])+c[0],h=(e[1]-l[1])*(c[3]-c[1])/(l[3]-l[1])+c[1],p=(e[2]-l[0])*(c[2]-c[0])/(l[2]-l[0])+c[0],d=(e[3]-l[1])*(c[3]-c[1])/(l[3]-l[1])+c[1];if(f=Math.max(f,c[0]),h=Math.max(h,c[1]),p=Math.min(p,c[2]),d=Math.min(d,c[3]),!(p<f||d<h)){o.bind();var g=s[2]-s[0],v=s[3]-s[1];if(this.outerFill&&(o.drawBox(0,0,g,h,i),o.drawBox(0,h,f,d,i),o.drawBox(0,d,g,v,i),o.drawBox(p,h,g,d,i)),this.innerFill&&o.drawBox(f,h,p,d,n),r>0){var m=r*u;o.drawBox(f-m,h-m,p+m,h+m,a),o.drawBox(f-m,d-m,p+m,d+m,a),o.drawBox(f-m,h-m,f+m,d+m,a),o.drawBox(p-m,h-m,p+m,d+m,a)}}}},s.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},s.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},{\"./lib/shaders\":297,\"gl-buffer\":240,\"gl-shader\":300}],299:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=n(t,e),a=i.mallocUint8(e[0]*e[1]*4);return new c(t,r,a)};var n=t(\"gl-fbo\"),i=t(\"typedarray-pool\"),a=t(\"ndarray\"),o=t(\"bit-twiddle\").nextPow2,s=t(\"cwise/lib/wrapper\")({args:[\"array\",{offset:[0,0,1],array:0},{offset:[0,0,2],array:0},{offset:[0,0,3],array:0},\"scalar\",\"scalar\",\"index\"],pre:{body:\"{this_closestD2=1e8,this_closestX=-1,this_closestY=-1}\",args:[],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[]},body:{body:\"{if(_inline_16_arg0_<255||_inline_16_arg1_<255||_inline_16_arg2_<255||_inline_16_arg3_<255){var _inline_16_l=_inline_16_arg4_-_inline_16_arg6_[0],_inline_16_a=_inline_16_arg5_-_inline_16_arg6_[1],_inline_16_f=_inline_16_l*_inline_16_l+_inline_16_a*_inline_16_a;_inline_16_f<this_closestD2&&(this_closestD2=_inline_16_f,this_closestX=_inline_16_arg6_[0],this_closestY=_inline_16_arg6_[1])}}\",args:[{name:\"_inline_16_arg0_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_16_arg1_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_16_arg2_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_16_arg3_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_16_arg4_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_16_arg5_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_16_arg6_\",lvalue:!1,rvalue:!0,count:4}],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[\"_inline_16_a\",\"_inline_16_f\",\"_inline_16_l\"]},post:{body:\"{return[this_closestX,this_closestY,this_closestD2]}\",args:[],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[]},debug:!1,funcName:\"cwise\",blockSize:64});function l(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function c(t,e,r){this.gl=t,this.fbo=e,this.buffer=r,this._readTimeout=null;var n=this;this._readCallback=function(){n.gl&&(e.bind(),t.readPixels(0,0,e.shape[0],e.shape[1],t.RGBA,t.UNSIGNED_BYTE,n.buffer),n._readTimeout=null)}}var u=c.prototype;Object.defineProperty(u,\"shape\",{get:function(){return this.gl?this.fbo.shape.slice():[0,0]},set:function(t){if(this.gl){this.fbo.shape=t;var e=this.fbo.shape[0],r=this.fbo.shape[1];if(r*e*4>this.buffer.length){i.free(this.buffer);for(var n=this.buffer=i.mallocUint8(o(r*e*4)),a=0;a<r*e*4;++a)n[a]=255}return t}}}),u.begin=function(){var t=this.gl;this.shape;t&&(this.fbo.bind(),t.clearColor(1,1,1,1),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT))},u.end=function(){var t=this.gl;t&&(t.bindFramebuffer(t.FRAMEBUFFER,null),this._readTimeout||clearTimeout(this._readTimeout),this._readTimeout=setTimeout(this._readCallback,1))},u.query=function(t,e,r){if(!this.gl)return null;var n=this.fbo.shape.slice();t|=0,e|=0,\"number\"!=typeof r&&(r=1);var i=0|Math.min(Math.max(t-r,0),n[0]),o=0|Math.min(Math.max(t+r,0),n[0]),c=0|Math.min(Math.max(e-r,0),n[1]),u=0|Math.min(Math.max(e+r,0),n[1]);if(o<=i||u<=c)return null;var f=[o-i,u-c],h=a(this.buffer,[f[0],f[1],4],[4,4*n[0],1],4*(i+n[0]*c)),p=s(h.hi(f[0],f[1],1),r,r),d=p[0],g=p[1];return d<0||Math.pow(this.radius,2)<p[2]?null:new l(d+i|0,g+c|0,h.get(d,g,0),[h.get(d,g,1),h.get(d,g,2),h.get(d,g,3)],Math.sqrt(p[2]))},u.dispose=function(){this.gl&&(this.fbo.dispose(),i.free(this.buffer),this.gl=null,this._readTimeout&&clearTimeout(this._readTimeout))}},{\"bit-twiddle\":85,\"cwise/lib/wrapper\":142,\"gl-fbo\":248,ndarray:445,\"typedarray-pool\":532}],300:[function(t,e,r){\"use strict\";var n=t(\"./lib/create-uniforms\"),i=t(\"./lib/create-attributes\"),a=t(\"./lib/reflect\"),o=t(\"./lib/shader-cache\"),s=t(\"./lib/runtime-reflect\"),l=t(\"./lib/GLError\");function 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l=s.prototype,c=[0,0,0],u=[0,0,0],f=[0,0];l.isTransparent=function(){return!1},l.drawTransparent=function(t){},l.draw=function(t){var e=this.gl,r=this.vao,n=this.shader;r.bind(),n.bind();var i,a=t.model||o,s=t.view||o,l=t.projection||o;this.axes&&(i=this.axes.lastCubeProps.axis);for(var h=c,p=u,d=0;d<3;++d)i&&i[d]<0?(h[d]=this.bounds[0][d],p[d]=this.bounds[1][d]):(h[d]=this.bounds[1][d],p[d]=this.bounds[0][d]);f[0]=e.drawingBufferWidth,f[1]=e.drawingBufferHeight,n.uniforms.model=a,n.uniforms.view=s,n.uniforms.projection=l,n.uniforms.coordinates=[this.position,h,p],n.uniforms.colors=this.colors,n.uniforms.screenShape=f;for(d=0;d<3;++d)n.uniforms.lineWidth=this.lineWidth[d]*this.pixelRatio,this.enabled[d]&&(r.draw(e.TRIANGLES,6,6*d),this.drawSides[d]&&r.draw(e.TRIANGLES,12,18+12*d));r.unbind()},l.update=function(t){t&&(\"bounds\"in t&&(this.bounds=t.bounds),\"position\"in t&&(this.position=t.position),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"colors\"in t&&(this.colors=t.colors),\"enabled\"in t&&(this.enabled=t.enabled),\"drawSides\"in t&&(this.drawSides=t.drawSides))},l.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders/index\":308,\"gl-buffer\":240,\"gl-vao\":322}],310:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n // Return up-vector for only-z vector.\\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\\n // Assign z = 0, x = -b, y = a:\\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n return normalize(vec3(-v.y, v.x, 0.0));\\n } else {\\n return normalize(vec3(0.0, v.z, -v.y));\\n }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n float segmentCount = 8.0;\\n\\n float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d);\\n vec3 y = v * sin(angle) * length(d);\\n vec3 v3 = x + y;\\n\\n normal = normalize(v3);\\n\\n return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\nuniform float vectorScale;\\nuniform float tubeScale;\\n\\nuniform mat4 model\\n , view\\n , projection\\n , inverseModel;\\nuniform vec3 eyePosition\\n , lightPosition;\\n\\nvarying vec3 f_normal\\n , f_lightDirection\\n , f_eyeDirection\\n , f_data\\n , f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n // Scale the vector magnitude to stay constant with\\n // model & view changes.\\n vec3 normal;\\n vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * tubePosition;\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\\n f_normal = normalize((vec4(normal,0.0) * inverseModel).xyz);\\n\\n // vec4 m_position = model * vec4(tubePosition, 1.0);\\n vec4 t_position = view * tubePosition;\\n gl_Position = projection * t_position;\\n\\n f_color = color;\\n f_data = tubePosition.xyz;\\n f_position = position.xyz;\\n f_uv = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness,\\n float fresnel) {\\n\\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n //Half angle vector\\n vec3 H = normalize(lightDirection + viewDirection);\\n\\n //Geometric term\\n float NdotH = max(dot(surfaceNormal, H), 0.0);\\n float VdotH = max(dot(viewDirection, H), 0.000001);\\n float LdotH = max(dot(lightDirection, H), 0.000001);\\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n float G = min(1.0, min(G1, G2));\\n \\n //Distribution term\\n float D = beckmannDistribution(NdotH, roughness);\\n\\n //Fresnel term\\n float F = pow(1.0 - VdotN, fresnel);\\n\\n //Multiply terms and done\\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n , fresnel\\n , kambient\\n , kdiffuse\\n , kspecular\\n , opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n , f_lightDirection\\n , f_eyeDirection\\n , f_data\\n , f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n vec3 N = normalize(f_normal);\\n vec3 L = normalize(f_lightDirection);\\n vec3 V = normalize(f_eyeDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\\n\\n gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n // Return up-vector for only-z vector.\\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\\n // Assign z = 0, x = -b, y = a:\\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n return normalize(vec3(-v.y, v.x, 0.0));\\n } else {\\n return normalize(vec3(0.0, v.z, -v.y));\\n }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n float segmentCount = 8.0;\\n\\n float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d);\\n vec3 y = v * sin(angle) * length(d);\\n vec3 v3 = x + y;\\n\\n normal = normalize(v3);\\n\\n return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float tubeScale;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n vec3 normal;\\n vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n gl_Position = projection * view * tubePosition;\\n f_id = id;\\n f_position = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);r.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec4\"}]},r.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec4\"}]}},{glslify:404}],311:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"normals\"),l=t(\"gl-mat4/multiply\"),c=t(\"gl-mat4/invert\"),u=t(\"ndarray\"),f=t(\"colormap\"),h=t(\"simplicial-complex-contour\"),p=t(\"typedarray-pool\"),d=t(\"./shaders\"),g=d.meshShader,v=d.pickShader,m=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function y(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,v,y,x,b,_,w,k,T){this.gl=t,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.pickShader=n,this.trianglePositions=i,this.triangleVectors=a,this.triangleColors=s,this.triangleNormals=c,this.triangleUVs=l,this.triangleIds=o,this.triangleVAO=u,this.triangleCount=0,this.lineWidth=1,this.edgePositions=f,this.edgeColors=p,this.edgeUVs=d,this.edgeIds=h,this.edgeVAO=g,this.edgeCount=0,this.pointPositions=v,this.pointColors=x,this.pointUVs=b,this.pointSizes=_,this.pointIds=y,this.pointVAO=w,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=k,this.contourVAO=T,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!1,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.tubeScale=1,this._model=m,this._view=m,this._projection=m,this._resolution=[1,1],this.pixelRatio=1}var x=y.prototype;function b(t){var e=n(t,v.vertex,v.fragment,null,v.attributes);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.vector.location=5,e}x.isOpaque=function(){return this.opacity>=1},x.isTransparent=function(){return this.opacity<1},x.pickSlots=1,x.setPickBase=function(t){this.pickId=t},x.highlight=function(t){if(t&&this.contourEnable){for(var e=h(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=p.mallocFloat32(6*a),s=0,l=0;l<a;++l)for(var c=r[l],u=0;u<2;++u){var f=c[0];2===c.length&&(f=c[u]);for(var d=n[f][0],g=n[f][1],v=i[f],m=1-v,y=this.positions[d],x=this.positions[g],b=0;b<3;++b)o[s++]=v*y[b]+m*x[b]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),p.free(o)}else this.contourCount=0},x.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),\"opacity\"in t&&(this.opacity=t.opacity),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),t.texture?(this.texture.dispose(),this.texture=o(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t){for(var e=f({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var i=e[n],a=0;a<3;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return u(r,[256,256,4],[4,0,1])}(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions,i=t.vectors;if(n&&r&&i){void 0!==t.tubeScale&&(this.tubeScale=t.tubeScale);var a=[],l=[],c=[],h=[],p=[],d=[],g=[],v=[],m=[],y=[],x=[],b=[],_=[],w=[],k=[];this.cells=r,this.positions=n,this.vectors=i;var T=t.vertexNormals,A=t.cellNormals,M=void 0===t.vertexNormalsEpsilon?1e-6:t.vertexNormalsEpsilon,S=void 0===t.faceNormalsEpsilon?1e-6:t.faceNormalsEpsilon;t.useFacetNormals&&!A&&(A=s.faceNormals(r,n,S)),A||T||(T=s.vertexNormals(r,n,M));var E=t.vertexColors,C=t.cellColors,L=t.meshColor||[1,1,1,1],z=t.vertexUVs,O=t.vertexIntensity,I=t.cellUVs,D=t.cellIntensity,P=1/0,R=-1/0;if(!z&&!I)if(O)if(t.vertexIntensityBounds)P=+t.vertexIntensityBounds[0],R=+t.vertexIntensityBounds[1];else for(var F=0;F<O.length;++F){var B=O[F];P=Math.min(P,B),R=Math.max(R,B)}else if(D)for(F=0;F<D.length;++F){B=D[F];P=Math.min(P,B),R=Math.max(R,B)}else for(F=0;F<n.length;++F){B=n[F][2];P=Math.min(P,B),R=Math.max(R,B)}this.intensity=O||(D?function(t,e,r){for(var n=new Array(e),i=0;i<e;++i)n[i]=0;var a=t.length;for(i=0;i<a;++i)for(var o=t[i],s=0;s<o.length;++s)n[o[s]]=r[i];return n}(r,n.length,D):function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n));var N=t.pointSizes,j=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(F=0;F<n.length;++F)for(var V=n[F],U=0;U<3;++U)!isNaN(V[U])&&isFinite(V[U])&&(this.bounds[0][U]=Math.min(this.bounds[0][U],V[U]),this.bounds[1][U]=Math.max(this.bounds[1][U],V[U]));var H=0,q=0,G=0;t:for(F=0;F<r.length;++F){var Y=r[F];switch(Y.length){case 1:for(V=n[X=Y[0]],U=0;U<3;++U)if(isNaN(V[U])||!isFinite(V[U]))continue t;x.push(V[0],V[1],V[2],V[3]),3===(Z=E?E[X]:C?C[F]:L).length?b.push(Z[0],Z[1],Z[2],1):b.push(Z[0],Z[1],Z[2],Z[3]),$=z?z[X]:O?[(O[X]-P)/(R-P),0]:I?I[F]:D?[(D[F]-P)/(R-P),0]:[(V[2]-P)/(R-P),0],_.push($[0],$[1]),N?w.push(N[X]):w.push(j),k.push(F),G+=1;break;case 2:for(U=0;U<2;++U){V=n[X=Y[U]];for(var W=0;W<3;++W)if(isNaN(V[W])||!isFinite(V[W]))continue t}for(U=0;U<2;++U){V=n[X=Y[U]];g.push(V[0],V[1],V[2]),3===(Z=E?E[X]:C?C[F]:L).length?v.push(Z[0],Z[1],Z[2],1):v.push(Z[0],Z[1],Z[2],Z[3]),$=z?z[X]:O?[(O[X]-P)/(R-P),0]:I?I[F]:D?[(D[F]-P)/(R-P),0]:[(V[2]-P)/(R-P),0],m.push($[0],$[1]),y.push(F)}q+=1;break;case 3:for(U=0;U<3;++U)for(V=n[X=Y[U]],W=0;W<3;++W)if(isNaN(V[W])||!isFinite(V[W]))continue t;for(U=0;U<3;++U){var X;V=n[X=Y[2-U]];a.push(V[0],V[1],V[2],V[3]);var Z,$,J,K=i[X];l.push(K[0],K[1],K[2],K[3]),3===(Z=E?E[X]:C?C[F]:L).length?c.push(Z[0],Z[1],Z[2],1):c.push(Z[0],Z[1],Z[2],Z[3]),$=z?z[X]:O?[(O[X]-P)/(R-P),0]:I?I[F]:D?[(D[F]-P)/(R-P),0]:[(V[2]-P)/(R-P),0],p.push($[0],$[1]),J=T?T[X]:A[F],h.push(J[0],J[1],J[2]),d.push(F)}H+=1}}this.pointCount=G,this.edgeCount=q,this.triangleCount=H,this.pointPositions.update(x),this.pointColors.update(b),this.pointUVs.update(_),this.pointSizes.update(w),this.pointIds.update(new Uint32Array(k)),this.edgePositions.update(g),this.edgeColors.update(v),this.edgeUVs.update(m),this.edgeIds.update(new Uint32Array(y)),this.trianglePositions.update(a),this.triangleVectors.update(l),this.triangleColors.update(c),this.triangleUVs.update(p),this.triangleNormals.update(h),this.triangleIds.update(new Uint32Array(d))}},x.drawTransparent=x.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||m,n=t.view||m,i=t.projection||m,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,inverseModel:m.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,tubeScale:this.tubeScale,contourColor:this.contourColor,texture:0};s.inverseModel=c(s.inverseModel,s.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);l(u,s.view,s.model),l(u,s.projection,u),c(u,u);for(o=0;o<3;++o)s.eyePosition[o]=u[12+o]/u[15];var f=u[15];for(o=0;o<3;++o)f+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var h=u[12+o],p=0;p<3;++p)h+=u[4*p+o]*this.lightPosition[p];s.lightPosition[o]=h/f}if(this.triangleCount>0){var d=this.triShader;d.bind(),d.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}},x.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||m,n=t.view||m,i=t.projection||m,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,tubeScale:this.tubeScale,pickId:this.pickId/255},l=this.pickShader;l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind())},x.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions[r[1]].slice(0,3);return{index:e,position:n,intensity:this.intensity[r[1]],velocity:this.vectors[r[1]].slice(0,3),divergence:this.vectors[r[1]][3],dataCoordinate:n}},x.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose()},e.exports=function(t,e){1===arguments.length&&(t=(e=t).gl);var r=e.triShader||function(t){var e=n(t,g.vertex,g.fragment,null,g.attributes);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.vector.location=5,e}(t),s=b(t),l=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));l.generateMipmap(),l.minFilter=t.LINEAR_MIPMAP_LINEAR,l.magFilter=t.LINEAR;var c=i(t),f=i(t),h=i(t),p=i(t),d=i(t),v=i(t),m=a(t,[{buffer:c,type:t.FLOAT,size:4},{buffer:v,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:h,type:t.FLOAT,size:4},{buffer:p,type:t.FLOAT,size:2},{buffer:d,type:t.FLOAT,size:3},{buffer:f,type:t.FLOAT,size:4}]),x=i(t),_=i(t),w=i(t),k=i(t),T=a(t,[{buffer:x,type:t.FLOAT,size:3},{buffer:k,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:_,type:t.FLOAT,size:4},{buffer:w,type:t.FLOAT,size:2}]),A=i(t),M=i(t),S=i(t),E=i(t),C=i(t),L=a(t,[{buffer:A,type:t.FLOAT,size:3},{buffer:C,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:M,type:t.FLOAT,size:4},{buffer:S,type:t.FLOAT,size:2},{buffer:E,type:t.FLOAT,size:1}]),z=i(t),O=new y(t,l,r,s,c,f,v,h,p,d,m,x,k,_,w,T,A,C,M,S,E,L,z,a(t,[{buffer:z,type:t.FLOAT,size:3}]));return O.update(e),O}},{\"./shaders\":310,colormap:119,\"gl-buffer\":240,\"gl-mat4/invert\":264,\"gl-mat4/multiply\":266,\"gl-shader\":300,\"gl-texture2d\":317,\"gl-vao\":322,ndarray:445,normals:448,\"simplicial-complex-contour\":505,\"typedarray-pool\":532}],312:[function(t,e,r){\"use strict\";var n=t(\"gl-vec3\"),i=t(\"gl-vec4\"),a=function(t,e,r,a){for(var o=0,s=0;s<t.length;s++)for(var l=t[s].velocities,c=0;c<l.length;c++){var u=n.length(l[c]);u>o&&(o=u)}var f=t.map(function(t){return function(t,e,r,a){var o,s,l,c=t.points,u=t.velocities,f=t.divergences;n.set(n.create(),0,1,0),n.create(),n.create();n.create();for(var h=[],p=[],d=[],g=[],v=[],m=[],y=0,x=0,b=i.create(),_=i.create(),w=0;w<c.length;w++){o=c[w],s=u[w],l=f[w],0===e&&(l=.05*r),x=n.length(s)/a,b=i.create(),n.copy(b,s),b[3]=l;for(var k=0;k<8;k++)v[k]=[o[0],o[1],o[2],k];if(g.length>0)for(k=0;k<8;k++){var T=(k+1)%8;h.push(g[k],v[k],v[T],v[T],g[T],g[k]),d.push(_,b,b,b,_,_),m.push(y,x,x,x,y,y),p.push([h.length-6,h.length-5,h.length-4],[h.length-3,h.length-2,h.length-1])}var A=g;g=v,v=A,A=_,_=b,b=A,A=y,y=x,x=A}return{positions:h,cells:p,vectors:d,vertexIntensity:m}}(t,r,a,o)}),h=[],p=[],d=[],g=[];for(s=0;s<f.length;s++){var v=f[s],m=h.length;h=h.concat(v.positions),d=d.concat(v.vectors),g=g.concat(v.vertexIntensity);for(c=0;c<v.cells.length;c++){var y=v.cells[c],x=[];p.push(x);for(var b=0;b<y.length;b++)x.push(y[b]+m)}}return{positions:h,cells:p,vectors:d,vertexIntensity:g,colormap:e}},o=function(t,e){var r=n.create(),i=1e-4;n.add(r,t,[i,0,0]);var a=this.getVelocity(r);n.subtract(a,a,e),n.scale(a,a,1e4),n.add(r,t,[0,i,0]);var o=this.getVelocity(r);n.subtract(o,o,e),n.scale(o,o,1e4),n.add(r,t,[0,0,i]);var s=this.getVelocity(r);return n.subtract(s,s,e),n.scale(s,s,1e4),n.add(r,a,o),n.add(r,r,s),r},s=function(t){return h(t,this.vectors,this.meshgrid,this.clampBorders)},l=function(t,e){for(var r=0;r<t.length;r++){var n=t[r];if(n===e)return r;if(n>e)return r-1}return r},c=n.create(),u=n.create(),f=function(t,e,r){return t<e?e:t>r?r:t},h=function(t,e,r,i){var a=t[0],o=t[1],s=t[2],h=r[0].length,p=r[1].length,d=r[2].length,g=l(r[0],a),v=l(r[1],o),m=l(r[2],s),y=g+1,x=v+1,b=m+1;if(r[0][g]===a&&(y=g),r[1][v]===o&&(x=v),r[2][m]===s&&(b=m),i&&(g=f(g,0,h-1),y=f(y,0,h-1),v=f(v,0,p-1),x=f(x,0,p-1),m=f(m,0,d-1),b=f(b,0,d-1)),g<0||v<0||m<0||y>=h||x>=p||b>=d)return n.create();var _=(a-r[0][g])/(r[0][y]-r[0][g]),w=(o-r[1][v])/(r[1][x]-r[1][v]),k=(s-r[2][m])/(r[2][b]-r[2][m]);(_<0||_>1||isNaN(_))&&(_=0),(w<0||w>1||isNaN(w))&&(w=0),(k<0||k>1||isNaN(k))&&(k=0);var T=m*h*p,A=b*h*p,M=v*h,S=x*h,E=g,C=y,L=e[M+T+E],z=e[M+T+C],O=e[S+T+E],I=e[S+T+C],D=e[M+A+E],P=e[M+A+C],R=e[S+A+E],F=e[S+A+C],B=n.create();return n.lerp(B,L,z,_),n.lerp(c,O,I,_),n.lerp(B,B,c,w),n.lerp(c,D,P,_),n.lerp(u,R,F,_),n.lerp(c,c,u,w),n.lerp(B,B,c,k),B},p=function(t){var e=1/0;t.sort(function(t,e){return t-e});for(var r=1;r<t.length;r++){var n=Math.abs(t[r]-t[r-1]);n<e&&(e=n)}return e};e.exports=function(t,e){var r=t.startingPositions,i=t.maxLength||1e3,l=t.tubeSize||1,c=t.absoluteTubeSize;t.getDivergence||(t.getDivergence=o),t.getVelocity||(t.getVelocity=s),void 0===t.clampBorders&&(t.clampBorders=!0);var u=[],f=e[0][0],h=e[0][1],d=e[0][2],g=e[1][0],v=e[1][1],m=e[1][2],y=function(t,e){var r=e[0],n=e[1],i=e[2];return r>=f&&r<=g&&n>=h&&n<=v&&i>=d&&i<=m},x=10*n.distance(e[0],e[1])/i,b=x*x,_=1,w=0;n.create();r.length>=2&&(_=function(t){for(var e=[],r=[],n=[],i={},a={},o={},s=0;s<t.length;s++){var l=t[s],c=l[0],u=l[1],f=l[2];i[c]||(e.push(c),i[c]=!0),a[u]||(r.push(u),a[u]=!0),o[f]||(n.push(f),o[f]=!0)}var h=p(e),d=p(r),g=p(n),v=Math.min(h,d,g);return isFinite(v)?v:1}(r));for(var k=0;k<r.length;k++){var T=n.create();n.copy(T,r[k]);var A=[T],M=[],S=t.getVelocity(T),E=T;M.push(S);var C=[],L=t.getDivergence(T,S);(D=n.length(L))>w&&!isNaN(D)&&isFinite(D)&&(w=D),C.push(D),u.push({points:A,velocities:M,divergences:C});for(var z=0;z<100*i&&A.length<i&&y(0,T);){z++;var O=n.clone(S),I=n.squaredLength(O);if(0===I)break;if(I>b&&n.scale(O,O,x/Math.sqrt(I)),n.add(O,O,T),S=t.getVelocity(O),n.squaredDistance(E,O)-b>-1e-4*b){A.push(O),E=O,M.push(S);L=t.getDivergence(O,S);(D=n.length(L))>w&&!isNaN(D)&&isFinite(D)&&(w=D),C.push(D)}T=O}}for(k=0;k<C.length;k++){var D=C[k];!isNaN(D)&&isFinite(D)||(C[k]=w)}var P=a(u,t.colormap,w,_);return c?P.tubeScale=c:(0===w&&(w=1),P.tubeScale=.5*l*_/w),P},e.exports.createTubeMesh=t(\"./lib/tubemesh\")},{\"./lib/tubemesh\":311,\"gl-vec3\":341,\"gl-vec4\":377}],313:[function(t,e,r){var n=t(\"gl-shader\"),i=t(\"glslify\"),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute vec3 f;\\nattribute vec3 normal;\\n\\nuniform vec3 objectOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 lightPosition, eyePosition;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n vec3 localCoordinate = vec3(uv.zw, f.x);\\n worldCoordinate = objectOffset + localCoordinate;\\n vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n vec4 clipPosition = projection * view * worldPosition;\\n gl_Position = clipPosition;\\n kill = f.y;\\n value = f.z;\\n planeCoordinate = uv.xy;\\n\\n vColor = texture2D(colormap, vec2(value, value));\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * worldPosition;\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n lightDirection = lightPosition - cameraCoordinate.xyz;\\n eyeDirection = eyePosition - cameraCoordinate.xyz;\\n surfaceNormal = normalize((vec4(normal,0) * inverseModel).xyz);\\n}\\n\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat beckmannSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness) {\\n return beckmannDistribution(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform float vertexColor;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n if ((kill > 0.0) ||\\n (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard;\\n\\n vec3 N = normalize(surfaceNormal);\\n vec3 V = normalize(eyeDirection);\\n vec3 L = normalize(lightDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = max(beckmannSpecular(L, V, N, roughness), 0.);\\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n //decide how to interpolate color \\u2014 in vertex or in fragment\\n vec4 surfaceColor =\\n step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) +\\n step(.5, vertexColor) * vColor;\\n\\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\\n\\n gl_FragColor = mix(litColor, contourColor, contourTint) * opacity;\\n}\\n\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute float f;\\n\\nuniform vec3 objectOffset;\\nuniform mat3 permutation;\\nuniform mat4 model, view, projection;\\nuniform float height, zOffset;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n vec3 dataCoordinate = permutation * vec3(uv.xy, height);\\n worldCoordinate = objectOffset + dataCoordinate;\\n vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n\\n vec4 clipPosition = projection * view * worldPosition;\\n clipPosition.z += zOffset;\\n\\n gl_Position = clipPosition;\\n value = f + objectOffset.z;\\n kill = -1.0;\\n planeCoordinate = uv.zw;\\n\\n vColor = texture2D(colormap, vec2(value, value));\\n\\n //Don't do lighting for contours\\n surfaceNormal = vec3(1,0,0);\\n eyeDirection = vec3(0,1,0);\\n lightDirection = vec3(0,0,1);\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n float vh = 255.0 * v;\\n float upper = floor(vh);\\n float lower = fract(vh);\\n return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n if ((kill > 0.0) ||\\n (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard;\\n\\n vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\\n\"]);r.createShader=function(t){var e=n(t,a,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createPickShader=function(t){var e=n(t,a,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createContourShader=function(t){var e=n(t,s,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e},r.createPickContourShader=function(t){var e=n(t,s,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},{\"gl-shader\":300,glslify:404}],314:[function(t,e,r){arguments[4][104][0].apply(r,arguments)},{dup:104}],315:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=y(e),n=b(e),s=x(e),l=_(e),c=i(e),u=a(e,[{buffer:c,size:4,stride:w,offset:0},{buffer:c,size:3,stride:w,offset:16},{buffer:c,size:3,stride:w,offset:28}]),f=i(e),h=a(e,[{buffer:f,size:4,stride:20,offset:0},{buffer:f,size:1,stride:20,offset:16}]),p=i(e),d=a(e,[{buffer:p,size:2,type:e.FLOAT}]),g=o(e,1,S,e.RGBA,e.UNSIGNED_BYTE);g.minFilter=e.LINEAR,g.magFilter=e.LINEAR;var v=new E(e,[0,0],[[0,0,0],[0,0,0]],r,n,c,u,g,s,l,f,h,p,d,[0,0,0]),m={levels:[[],[],[]]};for(var k in t)m[k]=t[k];return m.colormap=m.colormap||\"jet\",v.update(m),v};var n=t(\"bit-twiddle\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"typedarray-pool\"),l=t(\"colormap\"),c=t(\"ndarray-ops\"),u=t(\"ndarray-pack\"),f=t(\"ndarray\"),h=t(\"surface-nets\"),p=t(\"gl-mat4/multiply\"),d=t(\"gl-mat4/invert\"),g=t(\"binary-search-bounds\"),v=t(\"ndarray-gradient\"),m=t(\"./lib/shaders\"),y=m.createShader,x=m.createContourShader,b=m.createPickShader,_=m.createPickContourShader,w=40,k=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],T=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],A=[[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]];function M(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}!function(){for(var t=0;t<3;++t){var e=A[t],r=(t+2)%3;e[(t+1)%3+0]=1,e[r+3]=1,e[t+6]=1}}();var S=256;function E(t,e,r,n,i,a,o,l,c,u,h,p,d,g,v){this.gl=t,this.shape=e,this.bounds=r,this.objectOffset=v,this.intensityBounds=[],this._shader=n,this._pickShader=i,this._coordinateBuffer=a,this._vao=o,this._colorMap=l,this._contourShader=c,this._contourPickShader=u,this._contourBuffer=h,this._contourVAO=p,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new M([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=g,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.snapToData=!1,this.pixelRatio=1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}var C=E.prototype;C.isTransparent=function(){return this.opacity<1},C.isOpaque=function(){if(this.opacity>=1)return!0;for(var t=0;t<3;++t)if(this._contourCounts[t].length>0||this._dynamicCounts[t]>0)return!0;return!1},C.pickSlots=1,C.setPickBase=function(t){this.pickId=t};var L=[0,0,0],z={showSurface:!1,showContour:!1,projections:[k.slice(),k.slice(),k.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function O(t,e){var r,n,i,a=e.axes&&e.axes.lastCubeProps.axis||L,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=z.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(a[r]>0)][r],p(l,t.model,l);var c=z.clipBounds[r];for(i=0;i<2;++i)for(n=0;n<3;++n)c[i][n]=t.clipBounds[i][n];c[0][r]=-1e8,c[1][r]=1e8}return z.showSurface=o,z.showContour=s,z}var I={model:k,view:k,projection:k,inverseModel:k.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},D=k.slice(),P=[1,0,0,0,1,0,0,0,1];function R(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=I;n.model=t.model||k,n.view=t.view||k,n.projection=t.projection||k,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.objectOffset=this.objectOffset,n.contourColor=this.contourColor[0],n.inverseModel=d(n.inverseModel,n.model);for(var i=0;i<2;++i)for(var a=n.clipBounds[i],o=0;o<3;++o)a[o]=Math.min(Math.max(this.clipBounds[i][o],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=P,n.vertexColor=this.vertexColor;var s=D;for(p(s,n.view,n.model),p(s,n.projection,s),d(s,s),i=0;i<3;++i)n.eyePosition[i]=s[12+i]/s[15];var l=s[15];for(i=0;i<3;++i)l+=this.lightPosition[i]*s[4*i+3];for(i=0;i<3;++i){var c=s[12+i];for(o=0;o<3;++o)c+=s[4*o+i]*this.lightPosition[o];n.lightPosition[i]=c/l}var u=O(n,this);if(u.showSurface&&e===this.opacity<1){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),i=0;i<3;++i)this.surfaceProject[i]&&this.vertexCount&&(this._shader.uniforms.model=u.projections[i],this._shader.uniforms.clipBounds=u.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(u.showContour&&!e){var f=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,f.bind(),f.uniforms=n;var h=this._contourVAO;for(h.bind(),i=0;i<3;++i)for(f.uniforms.permutation=A[i],r.lineWidth(this.contourWidth[i]*this.pixelRatio),o=0;o<this.contourLevels[i].length;++o)o===this.highlightLevel[i]?(f.uniforms.contourColor=this.highlightColor[i],f.uniforms.contourTint=this.highlightTint[i]):0!==o&&o-1!==this.highlightLevel[i]||(f.uniforms.contourColor=this.contourColor[i],f.uniforms.contourTint=this.contourTint[i]),this._contourCounts[i][o]&&(f.uniforms.height=this.contourLevels[i][o],h.draw(r.LINES,this._contourCounts[i][o],this._contourOffsets[i][o]));for(i=0;i<3;++i)for(f.uniforms.model=u.projections[i],f.uniforms.clipBounds=u.clipBounds[i],o=0;o<3;++o)if(this.contourProject[i][o]){f.uniforms.permutation=A[o],r.lineWidth(this.contourWidth[o]*this.pixelRatio);for(var g=0;g<this.contourLevels[o].length;++g)g===this.highlightLevel[o]?(f.uniforms.contourColor=this.highlightColor[o],f.uniforms.contourTint=this.highlightTint[o]):0!==g&&g-1!==this.highlightLevel[o]||(f.uniforms.contourColor=this.contourColor[o],f.uniforms.contourTint=this.contourTint[o]),this._contourCounts[o][g]&&(f.uniforms.height=this.contourLevels[o][g],h.draw(r.LINES,this._contourCounts[o][g],this._contourOffsets[o][g]))}for(h.unbind(),(h=this._dynamicVAO).bind(),i=0;i<3;++i)if(0!==this._dynamicCounts[i])for(f.uniforms.model=n.model,f.uniforms.clipBounds=n.clipBounds,f.uniforms.permutation=A[i],r.lineWidth(this.dynamicWidth[i]*this.pixelRatio),f.uniforms.contourColor=this.dynamicColor[i],f.uniforms.contourTint=this.dynamicTint[i],f.uniforms.height=this.dynamicLevel[i],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]),o=0;o<3;++o)this.contourProject[o][i]&&(f.uniforms.model=u.projections[o],f.uniforms.clipBounds=u.clipBounds[o],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]));h.unbind()}}C.draw=function(t){return R.call(this,t,!1)},C.drawTransparent=function(t){return R.call(this,t,!0)};var F={model:k,view:k,projection:k,inverseModel:k,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,objectOffset:[0,0,0],permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};function B(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function N(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function j(t){if(Array.isArray(t)){if(Array.isArray(t))return[N(t[0]),N(t[1]),N(t[2])];var e=N(t);return[e.slice(),e.slice(),e.slice()]}}C.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=F;r.model=t.model||k,r.view=t.view||k,r.projection=t.projection||k,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.objectOffset=this.objectOffset,r.permutation=P;for(var n=0;n<2;++n)for(var i=r.clipBounds[n],a=0;a<3;++a)i[a]=Math.min(Math.max(this.clipBounds[n][a],-1e8),1e8);var o=O(r,this);if(o.showSurface){for(this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount),n=0;n<3;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=o.projections[n],this._pickShader.uniforms.clipBounds=o.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(o.showContour){var s=this._contourPickShader;s.bind(),s.uniforms=r;var l=this._contourVAO;for(l.bind(),a=0;a<3;++a)for(e.lineWidth(this.contourWidth[a]*this.pixelRatio),s.uniforms.permutation=A[a],n=0;n<this.contourLevels[a].length;++n)this._contourCounts[a][n]&&(s.uniforms.height=this.contourLevels[a][n],l.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n]));for(n=0;n<3;++n)for(s.uniforms.model=o.projections[n],s.uniforms.clipBounds=o.clipBounds[n],a=0;a<3;++a)if(this.contourProject[n][a]){s.uniforms.permutation=A[a],e.lineWidth(this.contourWidth[a]*this.pixelRatio);for(var c=0;c<this.contourLevels[a].length;++c)this._contourCounts[a][c]&&(s.uniforms.height=this.contourLevels[a][c],l.draw(e.LINES,this._contourCounts[a][c],this._contourOffsets[a][c]))}l.unbind()}},C.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var c=r.position;c[0]=c[1]=c[2]=0;for(var u=0;u<2;++u)for(var f=u?a:1-a,h=0;h<2;++h)for(var p=i+u,d=s+h,v=f*(h?l:1-l),m=0;m<3;++m)c[m]+=this._field[m].get(p,d)*v;for(var y=this._pickResult.level,x=0;x<3;++x)if(y[x]=g.le(this.contourLevels[x],c[x]),y[x]<0)this.contourLevels[x].length>0&&(y[x]=0);else if(y[x]<this.contourLevels[x].length-1){var b=this.contourLevels[x][y[x]],_=this.contourLevels[x][y[x]+1];Math.abs(b-c[x])>Math.abs(_-c[x])&&(y[x]+=1)}for(r.index[0]=a<.5?i:i+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],m=0;m<3;++m)r.dataCoordinate[m]=this._field[m].get(r.index[0],r.index[1]);return r},C.padField=function(t,e){var r=e.shape.slice(),n=t.shape.slice();c.assign(t.lo(1,1).hi(r[0],r[1]),e),c.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),c.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),c.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),c.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))},C.update=function(t){t=t||{},this.objectOffset=t.objectOffset||this.objectOffset,this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=B(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=B(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=B(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=j(t.contourColor)),\"contourProject\"in t&&(this.contourProject=B(t.contourProject,function(t){return B(t,Boolean)})),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=j(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=B(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=B(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\"colorBounds\"in t&&(this.colorBounds=t.colorBounds),\"vertexColor\"in t&&(this.vertexColor=t.vertexColor?1:0);var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var i=(e.shape[0]+2)*(e.shape[1]+2);i>this._field[2].data.length&&(s.freeFloat(this._field[2].data),this._field[2].data=s.mallocFloat(n.nextPow2(i))),this._field[2]=f(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),this.padField(this._field[2],e),this.shape=e.shape.slice();for(var a=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(s.freeFloat(this._field[o].data),this._field[o].data=s.mallocFloat(this._field[2].size)),this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2]);if(t.coords){var p=t.coords;if(!Array.isArray(p)||3!==p.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(o=0;o<2;++o){var d=p[o];for(b=0;b<2;++b)if(d.shape[b]!==a[b])throw new Error(\"gl-surface: coords have incorrect shape\");this.padField(this._field[o],d)}}else if(t.ticks){var g=t.ticks;if(!Array.isArray(g)||2!==g.length)throw new Error(\"gl-surface: invalid ticks\");for(o=0;o<2;++o){var m=g[o];if((Array.isArray(m)||m.length)&&(m=f(m)),m.shape[0]!==a[o])throw new Error(\"gl-surface: invalid tick length\");var y=f(m.data,a);y.stride[o]=m.stride[0],y.stride[1^o]=0,this.padField(this._field[o],y)}}else{for(o=0;o<2;++o){var x=[0,0];x[o]=1,this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2],x,0)}this._field[0].set(0,0,0);for(var b=0;b<a[0];++b)this._field[0].set(b+1,0,b);for(this._field[0].set(a[0]+1,0,a[0]-1),this._field[1].set(0,0,0),b=0;b<a[1];++b)this._field[1].set(0,b+1,b);this._field[1].set(0,a[1]+1,a[1]-1)}var _=this._field,w=f(s.mallocFloat(3*_[2].size*2),[3,a[0]+2,a[1]+2,2]);for(o=0;o<3;++o)v(w.pick(o),_[o],\"mirror\");var k=f(s.mallocFloat(3*_[2].size),[a[0]+2,a[1]+2,3]);for(o=0;o<a[0]+2;++o)for(b=0;b<a[1]+2;++b){var A=w.get(0,o,b,0),M=w.get(0,o,b,1),E=w.get(1,o,b,0),C=w.get(1,o,b,1),L=w.get(2,o,b,0),z=w.get(2,o,b,1),O=E*z-C*L,I=L*M-z*A,D=A*C-M*E,P=Math.sqrt(O*O+I*I+D*D);P<1e-8?(P=Math.max(Math.abs(O),Math.abs(I),Math.abs(D)))<1e-8?(D=1,I=O=0,P=1):P=1/P:P=1/Math.sqrt(P),k.set(o,b,0,O*P),k.set(o,b,1,I*P),k.set(o,b,2,D*P)}s.free(w.data);var R=[1/0,1/0,1/0],F=[-1/0,-1/0,-1/0],N=1/0,V=-1/0,U=(a[0]-1)*(a[1]-1)*6,H=s.mallocFloat(n.nextPow2(10*U)),q=0,G=0;for(o=0;o<a[0]-1;++o)t:for(b=0;b<a[1]-1;++b){for(var Y=0;Y<2;++Y)for(var W=0;W<2;++W)for(var X=0;X<3;++X){var Z=this._field[X].get(1+o+Y,1+b+W);if(isNaN(Z)||!isFinite(Z))continue t}for(X=0;X<6;++X){var $=o+T[X][0],J=b+T[X][1],K=this._field[0].get($+1,J+1),Q=this._field[1].get($+1,J+1);Z=this._field[2].get($+1,J+1),O=k.get($+1,J+1,0),I=k.get($+1,J+1,1),D=k.get($+1,J+1,2),t.intensity&&(tt=t.intensity.get($,J));var tt=t.intensity?t.intensity.get($,J):Z+this.objectOffset[2];H[q++]=$,H[q++]=J,H[q++]=K,H[q++]=Q,H[q++]=Z,H[q++]=0,H[q++]=tt,H[q++]=O,H[q++]=I,H[q++]=D,R[0]=Math.min(R[0],K+this.objectOffset[0]),R[1]=Math.min(R[1],Q+this.objectOffset[1]),R[2]=Math.min(R[2],Z+this.objectOffset[2]),N=Math.min(N,tt),F[0]=Math.max(F[0],K+this.objectOffset[0]),F[1]=Math.max(F[1],Q+this.objectOffset[1]),F[2]=Math.max(F[2],Z+this.objectOffset[2]),V=Math.max(V,tt),G+=1}}for(t.intensityBounds&&(N=+t.intensityBounds[0],V=+t.intensityBounds[1]),o=6;o<q;o+=10)H[o]=(H[o]-N)/(V-N);this._vertexCount=G,this._coordinateBuffer.update(H.subarray(0,q)),s.freeFloat(H),s.free(k.data),this.bounds=[R,F],this.intensity=t.intensity||this._field[2],this.intensityBounds[0]===N&&this.intensityBounds[1]===V||(r=!0),this.intensityBounds=[N,V]}if(\"levels\"in t){var et=t.levels;for(et=Array.isArray(et[0])?et.slice():[[],[],et],o=0;o<3;++o)et[o]=et[o].slice(),et[o].sort(function(t,e){return t-e});for(o=0;o<3;++o)for(b=0;b<et[o].length;++b)et[o][b]-=this.objectOffset[o];t:for(o=0;o<3;++o){if(et[o].length!==this.contourLevels[o].length){r=!0;break}for(b=0;b<et[o].length;++b)if(et[o][b]!==this.contourLevels[o][b]){r=!0;break t}}this.contourLevels=et}if(r){_=this._field,a=this.shape;for(var rt=[],nt=0;nt<3;++nt){var it=this.contourLevels[nt],at=[],ot=[],st=[0,0,0];for(o=0;o<it.length;++o){var lt=h(this._field[nt],it[o]);at.push(rt.length/5|0),G=0;t:for(b=0;b<lt.cells.length;++b){var ct=lt.cells[b];for(X=0;X<2;++X){var ut=lt.positions[ct[X]],ft=ut[0],ht=0|Math.floor(ft),pt=ft-ht,dt=ut[1],gt=0|Math.floor(dt),vt=dt-gt,mt=!1;e:for(var yt=0;yt<3;++yt){st[yt]=0;var xt=(nt+yt+1)%3;for(Y=0;Y<2;++Y){var bt=Y?pt:1-pt;for($=0|Math.min(Math.max(ht+Y,0),a[0]),W=0;W<2;++W){var _t=W?vt:1-vt;if(J=0|Math.min(Math.max(gt+W,0),a[1]),Z=yt<2?this._field[xt].get($,J):(this.intensity.get($,J)-this.intensityBounds[0])/(this.intensityBounds[1]-this.intensityBounds[0]),!isFinite(Z)||isNaN(Z)){mt=!0;break e}var wt=bt*_t;st[yt]+=wt*Z}}}if(mt){if(X>0){for(var kt=0;kt<5;++kt)rt.pop();G-=1}continue t}rt.push(st[0],st[1],ut[0],ut[1],st[2]),G+=1}}ot.push(G)}this._contourOffsets[nt]=at,this._contourCounts[nt]=ot}var Tt=s.mallocFloat(rt.length);for(o=0;o<rt.length;++o)Tt[o]=rt[o];this._contourBuffer.update(Tt),s.freeFloat(Tt)}t.colormap&&this._colorMap.setPixels(function(t){var e=u([l({colormap:t,nshades:S,format:\"rgba\"}).map(function(t){return[t[0],t[1],t[2],255*t[3]]})]);return c.divseq(e,255),e}(t.colormap))},C.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;t<3;++t)s.freeFloat(this._field[t].data)},C.highlight=function(t){var e,r;if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;for(r=this.snapToData?t.dataCoordinate:t.position,e=0;e<3;++e)r[e]-=this.objectOffset[e];if(this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=s.mallocFloat(12*i[0]*i[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var l=(o+1)%3,c=(o+2)%3,u=this._field[o],f=this._field[l],p=this._field[c],d=h(u,r[o]),g=d.cells,v=d.positions;for(this._dynamicOffsets[o]=n,e=0;e<g.length;++e)for(var m=g[e],y=0;y<2;++y){var x=v[m[y]],b=+x[0],_=0|b,w=0|Math.min(_+1,i[0]),k=b-_,T=1-k,A=+x[1],M=0|A,S=0|Math.min(M+1,i[1]),E=A-M,C=1-E,L=T*C,z=T*E,O=k*C,I=k*E,D=L*f.get(_,M)+z*f.get(_,S)+O*f.get(w,M)+I*f.get(w,S),P=L*p.get(_,M)+z*p.get(_,S)+O*p.get(w,M)+I*p.get(w,S);if(isNaN(D)||isNaN(P)){y&&(n-=1);break}a[2*n+0]=D,a[2*n+1]=P,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(a.subarray(0,2*n)),s.freeFloat(a)}}},{\"./lib/shaders\":313,\"binary-search-bounds\":314,\"bit-twiddle\":85,colormap:119,\"gl-buffer\":240,\"gl-mat4/invert\":264,\"gl-mat4/multiply\":266,\"gl-texture2d\":317,\"gl-vao\":322,ndarray:445,\"ndarray-gradient\":436,\"ndarray-ops\":439,\"ndarray-pack\":440,\"surface-nets\":518,\"typedarray-pool\":532}],316:[function(t,e,r){\"use strict\";var n=t(\"css-font\"),i=t(\"pick-by-alias\"),a=t(\"regl\"),o=t(\"gl-util/context\"),s=t(\"es6-weak-map\"),l=t(\"color-normalize\"),c=t(\"font-atlas\"),u=t(\"typedarray-pool\"),f=t(\"parse-rect\"),h=t(\"is-plain-obj\"),p=t(\"parse-unit\"),d=t(\"to-px\"),g=t(\"detect-kerning\"),v=t(\"object-assign\"),m=t(\"font-measure\"),y=t(\"flatten-vertex-data\"),x=t(\"bit-twiddle\").nextPow2,b=new s,_=!1;if(document.body){var w=document.body.appendChild(document.createElement(\"div\"));w.style.font=\"italic small-caps bold condensed 16px/2 cursive\",getComputedStyle(w).fontStretch&&(_=!0),document.body.removeChild(w)}var k=function(t){!function(t){return\"function\"==typeof t&&t._gl&&t.prop&&t.texture&&t.buffer}(t)?this.gl=o(t):(t={regl:t},this.gl=t.regl._gl),this.shader=b.get(this.gl),this.shader?this.regl=this.shader.regl:this.regl=t.regl||a({gl:this.gl}),this.charBuffer=this.regl.buffer({type:\"uint8\",usage:\"stream\"}),this.sizeBuffer=this.regl.buffer({type:\"float\",usage:\"stream\"}),this.shader||(this.shader=this.createShader(),b.set(this.gl,this.shader)),this.batch=[],this.fontSize=[],this.font=[],this.fontAtlas=[],this.draw=this.shader.draw.bind(this),this.render=function(){this.regl._refresh(),this.draw(this.batch)},this.canvas=this.gl.canvas,this.update(h(t)?t:{})};k.prototype.createShader=function(){var t=this.regl,e=t({blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},stencil:{enable:!1},depth:{enable:!1},count:t.prop(\"count\"),offset:t.prop(\"offset\"),attributes:{charOffset:{offset:4,stride:8,buffer:t.this(\"sizeBuffer\")},width:{offset:0,stride:8,buffer:t.this(\"sizeBuffer\")},char:t.this(\"charBuffer\"),position:t.this(\"position\")},uniforms:{atlasSize:function(t,e){return[e.atlas.width,e.atlas.height]},atlasDim:function(t,e){return[e.atlas.cols,e.atlas.rows]},atlas:function(t,e){return e.atlas.texture},charStep:function(t,e){return e.atlas.step},em:function(t,e){return e.atlas.em},color:t.prop(\"color\"),opacity:t.prop(\"opacity\"),viewport:t.this(\"viewportArray\"),scale:t.this(\"scale\"),align:t.prop(\"align\"),baseline:t.prop(\"baseline\"),translate:t.this(\"translate\"),positionOffset:t.prop(\"positionOffset\")},primitive:\"points\",viewport:t.this(\"viewport\"),vert:\"\\n\\t\\t\\tprecision highp float;\\n\\t\\t\\tattribute float width, charOffset, char;\\n\\t\\t\\tattribute vec2 position;\\n\\t\\t\\tuniform float fontSize, charStep, em, align, baseline;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tuniform vec4 color;\\n\\t\\t\\tuniform vec2 atlasSize, atlasDim, scale, translate, positionOffset;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\t\"+(k.normalViewport?\"\":\"vec2 positionOffset = vec2(positionOffset.x,- positionOffset.y);\")+\"\\n\\n\\t\\t\\t\\tvec2 offset = floor(em * (vec2(align + charOffset, baseline)\\n\\t\\t\\t\\t\\t+ positionOffset))\\n\\t\\t\\t\\t\\t/ (viewport.zw * scale.xy);\\n\\n\\t\\t\\t\\tvec2 position = (position + translate) * scale;\\n\\t\\t\\t\\tposition += offset * scale;\\n\\n\\t\\t\\t\\t\"+(k.normalViewport?\"position.y = 1. - position.y;\":\"\")+\"\\n\\n\\t\\t\\t\\tcharCoord = position * viewport.zw + viewport.xy;\\n\\n\\t\\t\\t\\tgl_Position = vec4(position * 2. - 1., 0, 1);\\n\\n\\t\\t\\t\\tgl_PointSize = charStep;\\n\\n\\t\\t\\t\\tcharId.x = mod(char, atlasDim.x);\\n\\t\\t\\t\\tcharId.y = floor(char / atlasDim.x);\\n\\n\\t\\t\\t\\tcharWidth = width * em;\\n\\n\\t\\t\\t\\tfontColor = color / 255.;\\n\\t\\t\\t}\",frag:\"\\n\\t\\t\\tprecision highp float;\\n\\t\\t\\tuniform sampler2D atlas;\\n\\t\\t\\tuniform float fontSize, charStep, opacity;\\n\\t\\t\\tuniform vec2 atlasSize;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\n\\t\\t\\tfloat lightness(vec4 color) {\\n\\t\\t\\t\\treturn color.r * 0.299 + color.g * 0.587 + color.b * 0.114;\\n\\t\\t\\t}\\n\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\tvec2 uv = gl_FragCoord.xy - charCoord + charStep * .5;\\n\\t\\t\\t\\tfloat halfCharStep = floor(charStep * .5 + .5);\\n\\n\\t\\t\\t\\t// invert y and shift by 1px (FF expecially needs that)\\n\\t\\t\\t\\tuv.y = charStep - uv.y;\\n\\n\\t\\t\\t\\t// ignore points outside of character bounding box\\n\\t\\t\\t\\tfloat halfCharWidth = ceil(charWidth * .5);\\n\\t\\t\\t\\tif (floor(uv.x) > halfCharStep + halfCharWidth ||\\n\\t\\t\\t\\t\\tfloor(uv.x) < halfCharStep - halfCharWidth) return;\\n\\n\\t\\t\\t\\tuv += charId * charStep;\\n\\t\\t\\t\\tuv = uv / atlasSize;\\n\\n\\t\\t\\t\\tvec4 color = fontColor;\\n\\t\\t\\t\\tvec4 mask = texture2D(atlas, uv);\\n\\n\\t\\t\\t\\tfloat maskY = lightness(mask);\\n\\t\\t\\t\\t// float colorY = lightness(color);\\n\\t\\t\\t\\tcolor.a *= maskY;\\n\\t\\t\\t\\tcolor.a *= opacity;\\n\\n\\t\\t\\t\\t// color.a += .1;\\n\\n\\t\\t\\t\\t// antialiasing, see yiq color space y-channel formula\\n\\t\\t\\t\\t// color.rgb += (1. - color.rgb) * (1. - mask.rgb);\\n\\n\\t\\t\\t\\tgl_FragColor = color;\\n\\t\\t\\t}\"});return{regl:t,draw:e,atlas:{}}},k.prototype.update=function(t){var e=this;if(\"string\"==typeof t)t={text:t};else if(!t)return;null!=(t=i(t,{position:\"position positions coord coords coordinates\",font:\"font fontFace fontface typeface cssFont css-font family fontFamily\",fontSize:\"fontSize fontsize size font-size\",text:\"text texts chars characters value values symbols\",align:\"align alignment textAlign textbaseline\",baseline:\"baseline textBaseline textbaseline\",direction:\"dir direction textDirection\",color:\"color colour fill fill-color fillColor textColor textcolor\",kerning:\"kerning kern\",range:\"range dataBox\",viewport:\"vp viewport viewBox viewbox viewPort\",opacity:\"opacity alpha transparency visible visibility opaque\",offset:\"offset positionOffset padding shift indent indentation\"},!0)).opacity&&(Array.isArray(t.opacity)?this.opacity=t.opacity.map(function(t){return parseFloat(t)}):this.opacity=parseFloat(t.opacity)),null!=t.viewport&&(this.viewport=f(t.viewport),k.normalViewport&&(this.viewport.y=this.canvas.height-this.viewport.y-this.viewport.height),this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null==this.viewport&&(this.viewport={x:0,y:0,width:this.gl.drawingBufferWidth,height:this.gl.drawingBufferHeight},this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null!=t.kerning&&(this.kerning=t.kerning),null!=t.offset&&(\"number\"==typeof t.offset&&(t.offset=[t.offset,0]),this.positionOffset=y(t.offset)),t.direction&&(this.direction=t.direction),t.range&&(this.range=t.range,this.scale=[1/(t.range[2]-t.range[0]),1/(t.range[3]-t.range[1])],this.translate=[-t.range[0],-t.range[1]]),t.scale&&(this.scale=t.scale),t.translate&&(this.translate=t.translate),this.scale||(this.scale=[1/this.viewport.width,1/this.viewport.height]),this.translate||(this.translate=[0,0]),this.font.length||t.font||(t.font=k.baseFontSize+\"px sans-serif\");var r,a=!1,o=!1;if(t.font&&(Array.isArray(t.font)?t.font:[t.font]).forEach(function(t,r){if(\"string\"==typeof t)try{t=n.parse(t)}catch(e){t=n.parse(k.baseFontSize+\"px \"+t)}else t=n.parse(n.stringify(t));var i=n.stringify({size:k.baseFontSize,family:t.family,stretch:_?t.stretch:void 0,variant:t.variant,weight:t.weight,style:t.style}),s=p(t.size),l=Math.round(s[0]*d(s[1]));if(l!==e.fontSize[r]&&(o=!0,e.fontSize[r]=l),!(e.font[r]&&i==e.font[r].baseString||(a=!0,e.font[r]=k.fonts[i],e.font[r]))){var c=t.family.join(\", \"),u=[t.style];t.style!=t.variant&&u.push(t.variant),t.variant!=t.weight&&u.push(t.weight),_&&t.weight!=t.stretch&&u.push(t.stretch),e.font[r]={baseString:i,family:c,weight:t.weight,stretch:t.stretch,style:t.style,variant:t.variant,width:{},kerning:{},metrics:m(c,{origin:\"top\",fontSize:k.baseFontSize,fontStyle:u.join(\" \")})},k.fonts[i]=e.font[r]}}),(a||o)&&this.font.forEach(function(r,i){var a=n.stringify({size:e.fontSize[i],family:r.family,stretch:_?r.stretch:void 0,variant:r.variant,weight:r.weight,style:r.style});if(e.fontAtlas[i]=e.shader.atlas[a],!e.fontAtlas[i]){var o=r.metrics;e.shader.atlas[a]=e.fontAtlas[i]={fontString:a,step:2*Math.ceil(e.fontSize[i]*o.bottom*.5),em:e.fontSize[i],cols:0,rows:0,height:0,width:0,chars:[],ids:{},texture:e.regl.texture()}}null==t.text&&(t.text=e.text)}),\"string\"==typeof t.text&&t.position&&t.position.length>2){for(var s=Array(.5*t.position.length),h=0;h<s.length;h++)s[h]=t.text;t.text=s}if(null!=t.text||a){if(this.textOffsets=[0],Array.isArray(t.text)){this.count=t.text[0].length,this.counts=[this.count];for(var b=1;b<t.text.length;b++)e.textOffsets[b]=e.textOffsets[b-1]+t.text[b-1].length,e.count+=t.text[b].length,e.counts.push(t.text[b].length);this.text=t.text.join(\"\")}else this.text=t.text,this.count=this.text.length,this.counts=[this.count];r=[],this.font.forEach(function(t,n){k.atlasContext.font=t.baseString;for(var i=e.fontAtlas[n],a=0;a<e.text.length;a++){var o=e.text.charAt(a);if(null==i.ids[o]&&(i.ids[o]=i.chars.length,i.chars.push(o),r.push(o)),null==t.width[o]&&(t.width[o]=k.atlasContext.measureText(o).width/k.baseFontSize,e.kerning)){var s=[];for(var l in t.width)s.push(l+o,o+l);v(t.kerning,g(t.family,{pairs:s}))}}})}if(t.position)if(t.position.length>2){for(var w=!t.position[0].length,T=u.mallocFloat(2*this.count),A=0,M=0;A<this.counts.length;A++){var S=e.counts[A];if(w)for(var E=0;E<S;E++)T[M++]=t.position[2*A],T[M++]=t.position[2*A+1];else for(var C=0;C<S;C++)T[M++]=t.position[A][0],T[M++]=t.position[A][1]}this.position.call?this.position({type:\"float\",data:T}):this.position=this.regl.buffer({type:\"float\",data:T}),u.freeFloat(T)}else this.position.destroy&&this.position.destroy(),this.position={constant:t.position};if(t.text||a){var L=u.mallocUint8(this.count),z=u.mallocFloat(2*this.count);this.textWidth=[];for(var O=0,I=0;O<this.counts.length;O++){for(var D=e.counts[O],P=e.font[O]||e.font[0],R=e.fontAtlas[O]||e.fontAtlas[0],F=0;F<D;F++){var B=e.text.charAt(I),N=e.text.charAt(I-1);if(L[I]=R.ids[B],z[2*I]=P.width[B],F){var j=z[2*I-2],V=z[2*I],U=z[2*I-1]+.5*j+.5*V;if(e.kerning){var H=P.kerning[N+B];H&&(U+=.001*H)}z[2*I+1]=U}else z[2*I+1]=.5*z[2*I];I++}e.textWidth.push(z.length?.5*z[2*I-2]+z[2*I-1]:0)}t.align||(t.align=this.align),this.charBuffer({data:L,type:\"uint8\",usage:\"stream\"}),this.sizeBuffer({data:z,type:\"float\",usage:\"stream\"}),u.freeUint8(L),u.freeFloat(z),r.length&&this.font.forEach(function(t,r){var n=e.fontAtlas[r],i=n.step,a=Math.floor(k.maxAtlasSize/i),o=Math.min(a,n.chars.length),s=Math.ceil(n.chars.length/o),l=x(o*i),u=x(s*i);n.width=l,n.height=u,n.rows=s,n.cols=o,n.em&&n.texture({data:c({canvas:k.atlasCanvas,font:n.fontString,chars:n.chars,shape:[l,u],step:[i,i]})})})}if(t.align&&(this.align=t.align,this.alignOffset=this.textWidth.map(function(t,r){var n=Array.isArray(e.align)?e.align.length>1?e.align[r]:e.align[0]:e.align;if(\"number\"==typeof n)return n;switch(n){case\"right\":case\"end\":return-t;case\"center\":case\"centre\":case\"middle\":return.5*-t}return 0})),null==this.baseline&&null==t.baseline&&(t.baseline=0),null!=t.baseline&&(this.baseline=t.baseline,Array.isArray(this.baseline)||(this.baseline=[this.baseline]),this.baselineOffset=this.baseline.map(function(t,r){var n=(e.font[r]||e.font[0]).metrics,i=0;return i+=.5*n.bottom,i+=\"number\"==typeof t?t-n.baseline:-n[t],k.normalViewport||(i*=-1),i})),null!=t.color)if(t.color||(t.color=\"transparent\"),\"string\"!=typeof t.color&&isNaN(t.color)){var q;if(\"number\"==typeof t.color[0]&&t.color.length>this.counts.length){var G=t.color.length;q=u.mallocUint8(G);for(var Y=(t.color.subarray||t.color.slice).bind(t.color),W=0;W<G;W+=4)q.set(l(Y(W,W+4),\"uint8\"),W)}else{var X=t.color.length;q=u.mallocUint8(4*X);for(var Z=0;Z<X;Z++)q.set(l(t.color[Z]||0,\"uint8\"),4*Z)}this.color=q}else this.color=l(t.color,\"uint8\");if(t.position||t.text||t.color||t.baseline||t.align||t.font||t.offset||t.opacity)if(this.color.length>4||this.baselineOffset.length>1||this.align&&this.align.length>1||this.fontAtlas.length>1||this.positionOffset.length>2){var $=Math.max(.5*this.position.length||0,.25*this.color.length||0,this.baselineOffset.length||0,this.alignOffset.length||0,this.font.length||0,this.opacity.length||0,.5*this.positionOffset.length||0);this.batch=Array($);for(var J=0;J<this.batch.length;J++)e.batch[J]={count:e.counts.length>1?e.counts[J]:e.counts[0],offset:e.textOffsets.length>1?e.textOffsets[J]:e.textOffsets[0],color:e.color?e.color.length<=4?e.color:e.color.subarray(4*J,4*J+4):[0,0,0,255],opacity:Array.isArray(e.opacity)?e.opacity[J]:e.opacity,baseline:null!=e.baselineOffset[J]?e.baselineOffset[J]:e.baselineOffset[0],align:e.align?null!=e.alignOffset[J]?e.alignOffset[J]:e.alignOffset[0]:0,atlas:e.fontAtlas[J]||e.fontAtlas[0],positionOffset:e.positionOffset.length>2?e.positionOffset.subarray(2*J,2*J+2):e.positionOffset}}else this.count?this.batch=[{count:this.count,offset:0,color:this.color||[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[0]:this.opacity,baseline:this.baselineOffset[0],align:this.alignOffset?this.alignOffset[0]:0,atlas:this.fontAtlas[0],positionOffset:this.positionOffset}]:this.batch=[]},k.prototype.destroy=function(){},k.prototype.kerning=!0,k.prototype.position={constant:new Float32Array(2)},k.prototype.translate=null,k.prototype.scale=null,k.prototype.font=null,k.prototype.text=\"\",k.prototype.positionOffset=[0,0],k.prototype.opacity=1,k.prototype.color=new Uint8Array([0,0,0,255]),k.prototype.alignOffset=[0,0],k.normalViewport=!1,k.maxAtlasSize=1024,k.atlasCanvas=document.createElement(\"canvas\"),k.atlasContext=k.atlasCanvas.getContext(\"2d\",{alpha:!1}),k.baseFontSize=64,k.fonts={},e.exports=k},{\"bit-twiddle\":85,\"color-normalize\":113,\"css-font\":132,\"detect-kerning\":160,\"es6-weak-map\":219,\"flatten-vertex-data\":226,\"font-atlas\":227,\"font-measure\":228,\"gl-util/context\":318,\"is-plain-obj\":417,\"object-assign\":449,\"parse-rect\":454,\"parse-unit\":456,\"pick-by-alias\":460,regl:489,\"to-px\":526,\"typedarray-pool\":532}],317:[function(t,e,r){\"use strict\";var n=t(\"ndarray\"),i=t(\"ndarray-ops\"),a=t(\"typedarray-pool\");e.exports=function(t){if(arguments.length<=1)throw new Error(\"gl-texture2d: Missing arguments for texture2d 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Error(\"gl-texture2d: Invalid arguments for texture2d constructor\")};var o=null,s=null,l=null;function c(t){return\"undefined\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\"undefined\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\"undefined\"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement||\"undefined\"!=typeof ImageData&&t instanceof ImageData}var u=function(t,e){i.muls(t,e,255)};function f(t,e,r){var n=t.gl,i=n.getParameter(n.MAX_TEXTURE_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-texture2d: Invalid texture size\");return t._shape=[e,r],t.bind(),n.texImage2D(n.TEXTURE_2D,0,t.format,e,r,0,t.format,t.type,null),t._mipLevels=[0],t}function h(t,e,r,n,i,a){this.gl=t,this.handle=e,this.format=i,this.type=a,this._shape=[r,n],this._mipLevels=[0],this._magFilter=t.NEAREST,this._minFilter=t.NEAREST,this._wrapS=t.CLAMP_TO_EDGE,this._wrapT=t.CLAMP_TO_EDGE,this._anisoSamples=1;var o=this,s=[this._wrapS,this._wrapT];Object.defineProperties(s,[{get:function(){return o._wrapS},set:function(t){return o.wrapS=t}},{get:function(){return o._wrapT},set:function(t){return o.wrapT=t}}]),this._wrapVector=s;var l=[this._shape[0],this._shape[1]];Object.defineProperties(l,[{get:function(){return o._shape[0]},set:function(t){return o.width=t}},{get:function(){return o._shape[1]},set:function(t){return o.height=t}}]),this._shapeVector=l}var p=h.prototype;function d(t,e){return 3===t.length?1===e[2]&&e[1]===t[0]*t[2]&&e[0]===t[2]:1===e[0]&&e[1]===t[0]}function g(t){var e=t.createTexture();return t.bindTexture(t.TEXTURE_2D,e),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),e}function v(t,e,r,n,i){var a=t.getParameter(t.MAX_TEXTURE_SIZE);if(e<0||e>a||r<0||r>a)throw new Error(\"gl-texture2d: Invalid texture shape\");if(i===t.FLOAT&&!t.getExtension(\"OES_texture_float\"))throw new Error(\"gl-texture2d: Floating point textures not supported on this platform\");var o=g(t);return t.texImage2D(t.TEXTURE_2D,0,n,e,r,0,n,i,null),new h(t,o,e,r,n,i)}Object.defineProperties(p,{minFilter:{get:function(){return this._minFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&o.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),s.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,t),this._minFilter=t}},magFilter:{get:function(){return this._magFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&o.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),s.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,t),this._magFilter=t}},mipSamples:{get:function(){return this._anisoSamples},set:function(t){var e=this._anisoSamples;if(this._anisoSamples=0|Math.max(t,1),e!==this._anisoSamples){var r=this.gl.getExtension(\"EXT_texture_filter_anisotropic\");r&&this.gl.texParameterf(this.gl.TEXTURE_2D,r.TEXTURE_MAX_ANISOTROPY_EXT,this._anisoSamples)}return this._anisoSamples}},wrapS:{get:function(){return this._wrapS},set:function(t){if(this.bind(),l.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_S,t),this._wrapS=t}},wrapT:{get:function(){return this._wrapT},set:function(t){if(this.bind(),l.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_T,t),this._wrapT=t}},wrap:{get:function(){return this._wrapVector},set:function(t){if(Array.isArray(t)||(t=[t,t]),2!==t.length)throw new Error(\"gl-texture2d: Must specify wrap mode for rows and columns\");for(var e=0;e<2;++e)if(l.indexOf(t[e])<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);this._wrapS=t[0],this._wrapT=t[1];var r=this.gl;return this.bind(),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_S,this._wrapS),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_T,this._wrapT),t}},shape:{get:function(){return this._shapeVector},set:function(t){if(Array.isArray(t)){if(2!==t.length)throw new Error(\"gl-texture2d: Invalid texture shape\")}else t=[0|t,0|t];return f(this,0|t[0],0|t[1]),[0|t[0],0|t[1]]}},width:{get:function(){return this._shape[0]},set:function(t){return f(this,t|=0,this._shape[1]),t}},height:{get:function(){return this._shape[1]},set:function(t){return t|=0,f(this,this._shape[0],t),t}}}),p.bind=function(t){var e=this.gl;return void 0!==t&&e.activeTexture(e.TEXTURE0+(0|t)),e.bindTexture(e.TEXTURE_2D,this.handle),void 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y=f.size,x=c.indexOf(o)<0;x&&c.push(o);if(g===l&&m)0===f.offset&&f.data.length===y?x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,f.data):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,f.data):x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,f.data.subarray(f.offset,f.offset+y)):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,f.data.subarray(f.offset,f.offset+y));else{var b;b=l===t.FLOAT?a.mallocFloat32(y):a.mallocUint8(y);var _=n(b,p,[p[2],p[2]*p[0],1]);g===t.FLOAT&&l===t.UNSIGNED_BYTE?u(_,f):i.assign(_,f),x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,b.subarray(0,y)):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,b.subarray(0,y)),l===t.FLOAT?a.freeFloat32(b):a.freeUint8(b)}}(s,e,r,o,this.format,this.type,this._mipLevels,t)}}},{ndarray:445,\"ndarray-ops\":439,\"typedarray-pool\":532}],318:[function(t,e,r){\"use strict\";var n=t(\"pick-by-alias\");function i(t){if(t.container)if(t.container==document.body)document.body.style.width||(t.canvas.width=t.width||t.pixelRatio*window.innerWidth),document.body.style.height||(t.canvas.height=t.height||t.pixelRatio*window.innerHeight);else{var e=t.container.getBoundingClientRect();t.canvas.width=t.width||e.right-e.left,t.canvas.height=t.height||e.bottom-e.top}}function a(t){return\"function\"==typeof t.getContext&&\"width\"in t&&\"height\"in t}e.exports=function(t){var e;if(t?\"string\"==typeof t&&(t={container:t}):t={},a(t)?t={container:t}:t=\"string\"==typeof(e=t).nodeName&&\"function\"==typeof e.appendChild&&\"function\"==typeof e.getBoundingClientRect?{container:t}:function(t){return\"function\"==typeof t.drawArrays||\"function\"==typeof t.drawElements}(t)?{gl:t}:n(t,{container:\"container target element el canvas holder parent parentNode wrapper use ref root node\",gl:\"gl context webgl glContext\",attrs:\"attributes attrs contextAttributes\",pixelRatio:\"pixelRatio pxRatio px ratio pxratio 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3:t.vertexAttrib3f(this.location,this.a,this.b,this.c);break;case 4:t.vertexAttrib4f(this.location,this.a,this.b,this.c,this.d)}},a.prototype.bind=function(){this._ext.bindVertexArrayOES(this.handle);for(var t=0;t<this._attribs.length;++t)this._attribs[t].bind(this.gl)},a.prototype.unbind=function(){this._ext.bindVertexArrayOES(null)},a.prototype.dispose=function(){this._ext.deleteVertexArrayOES(this.handle)},a.prototype.update=function(t,e,r){if(this.bind(),n(this.gl,e,t),this.unbind(),this._attribs.length=0,t)for(var a=0;a<t.length;++a){var o=t[a];\"number\"==typeof o?this._attribs.push(new i(a,1,o)):Array.isArray(o)&&this._attribs.push(new i(a,o.length,o[0],o[1],o[2],o[3]))}this._useElements=!!e,this._elementsType=r||this.gl.UNSIGNED_SHORT},a.prototype.draw=function(t,e,r){r=r||0;var n=this.gl;this._useElements?n.drawElements(t,e,this._elementsType,r):n.drawArrays(t,r,e)},e.exports=function(t,e){return new 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ft={\"to-number\":U,\"to-color\":G},ht=function(t,e){this.type=t,this.args=e};ht.parse=function(t,e){if(t.length<2)return e.error(\"Expected at least one argument.\");for(var r=t[0],n=ft[r],i=[],a=1;a<t.length;a++){var o=e.parse(t[a],a,W);if(!o)return null;i.push(o)}return new ht(n,i)},ht.prototype.evaluate=function(t){if(\"color\"===this.type.kind){for(var e,r,n=0,i=this.args;n<i.length;n+=1)if(r=null,\"string\"==typeof(e=i[n].evaluate(t))){var a=t.parseColor(e);if(a)return a}else if(Array.isArray(e)&&!(r=e.length<3||e.length>4?\"Invalid rbga value \"+JSON.stringify(e)+\": expected an array containing either three or four numeric values.\":nt(e[0],e[1],e[2],e[3])))return new tt(e[0]/255,e[1]/255,e[2]/255,e[3]);throw new ot(r||\"Could not parse color from value '\"+(\"string\"==typeof e?e:JSON.stringify(e))+\"'\")}for(var o=null,s=0,l=this.args;s<l.length;s+=1)if(null!==(o=l[s].evaluate(t))){var c=Number(o);if(!isNaN(c))return c}throw new ot(\"Could not convert \"+JSON.stringify(o)+\" 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e=0,r=this.outputs;e<r.length;e+=1)t(r[e])},_t.prototype.possibleOutputs=function(){return(t=[]).concat.apply(t,this.outputs.map(function(t){return t.possibleOutputs()}));var t},_t.prototype.serialize=function(){for(var t=[\"step\",this.input.serialize()],e=0;e<this.labels.length;e++)e>0&&t.push(this.labels[e]),t.push(this.outputs[e].serialize());return t};var kt=Object.freeze({number:wt,color:function(t,e,r){return new tt(wt(t.r,e.r,r),wt(t.g,e.g,r),wt(t.b,e.b,r),wt(t.a,e.a,r))},array:function(t,e,r){return t.map(function(t,n){return wt(t,e[n],r)})}}),Tt=function(t,e,r,n){this.type=t,this.interpolation=e,this.input=r,this.labels=[],this.outputs=[];for(var i=0,a=n;i<a.length;i+=1){var o=a[i],s=o[0],l=o[1];this.labels.push(s),this.outputs.push(l)}};function At(t,e,r,n){var i=n-r,a=t-r;return 0===i?0:1===e?a/i:(Math.pow(e,a)-1)/(Math.pow(e,i)-1)}Tt.interpolationFactor=function(t,e,r,n){var i=0;if(\"exponential\"===t.name)i=At(e,t.base,r,n);else if(\"linear\"===t.name)i=At(e,1,r,n);else 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this._styleExpression.evaluateWithoutErrorHandling(t,e)},ke.prototype.evaluate=function(t,e){return this._styleExpression.evaluate(t,e)};var Te=function(t,e,r){this.kind=t,this.zoomStops=r.labels,this._styleExpression=e,r instanceof Tt&&(this._interpolationType=r.interpolation)};function Ae(t,e){if(\"error\"===(t=we(t,e)).result)return t;var r=t.value.expression,n=vt(r);if(!n&&!e[\"property-function\"])return Yt([new N(\"\",\"property expressions not supported\")]);var i=mt(r,[\"zoom\"]);if(!i&&!1===e[\"zoom-function\"])return Yt([new N(\"\",\"zoom expressions not supported\")]);var a=function t(e){var r=null;if(e instanceof St)r=t(e.result);else if(e instanceof Mt)for(var n=0,i=e.args;n<i.length;n+=1){var a=i[n];if(r=t(a))break}else(e instanceof _t||e instanceof Tt)&&e.input instanceof gt&&\"zoom\"===e.input.name&&(r=e);return r instanceof N?r:(e.eachChild(function(e){var n=t(e);n instanceof N?r=n:!r&&n?r=new N(\"\",'\"zoom\" expression may only be used as input to a top-level 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n,i,a,o=\"color\"===r.type,s=e.stops&&\"object\"==typeof e.stops[0][0],l=s||void 0!==e.property,c=s||!l,u=e.type||(\"interpolated\"===r.function?\"exponential\":\"interval\");if(o&&((e=R({},e)).stops&&(e.stops=e.stops.map(function(t){return[t[0],tt.parse(t[1])]})),e.default?e.default=tt.parse(e.default):e.default=tt.parse(r.default)),e.colorSpace&&\"rgb\"!==e.colorSpace&&!ue[e.colorSpace])throw new Error(\"Unknown color space: \"+e.colorSpace);if(\"exponential\"===u)n=me;else if(\"interval\"===u)n=ve;else if(\"categorical\"===u){n=ge,i=Object.create(null);for(var f=0,h=e.stops;f<h.length;f+=1){var p=h[f];i[p[0]]=p[1]}a=typeof e.stops[0][0]}else{if(\"identity\"!==u)throw new Error('Unknown function type \"'+u+'\"');n=ye}if(s){for(var d={},g=[],v=0;v<e.stops.length;v++){var m=e.stops[v],y=m[0].zoom;void 0===d[y]&&(d[y]={zoom:y,type:e.type,property:e.property,default:e.default,stops:[]},g.push(y)),d[y].stops.push([m[0].value,m[1]])}for(var x=[],b=0,_=g;b<_.length;b+=1){var w=_[b];x.push([d[w].zoom,t(d[w],r)])}return{kind:\"composite\",interpolationFactor:Tt.interpolationFactor.bind(void 0,{name:\"linear\"}),zoomStops:x.map(function(t){return t[0]}),evaluate:function(t,n){var i=t.zoom;return me({stops:x,base:e.base},r,i).evaluate(i,n)}}}return c?{kind:\"camera\",interpolationFactor:\"exponential\"===u?Tt.interpolationFactor.bind(void 0,{name:\"exponential\",base:void 0!==e.base?e.base:1}):function(){return 0},zoomStops:e.stops.map(function(t){return t[0]}),evaluate:function(t){var o=t.zoom;return n(e,r,o,i,a)}}:{kind:\"source\",evaluate:function(t,o){var s=o&&o.properties?o.properties[e.property]:void 0;return void 0===s?de(e.default,r.default):n(e,r,s,i,a)}}}(this._parameters,this._specification))};function Se(t,e){if(he(t))return new Me(t,e);if(_e(t)){var r=Ae(t,e);if(\"error\"===r.result)throw new Error(r.value.map(function(t){return t.key+\": \"+t.message}).join(\", \"));return r.value}var n=t;return\"string\"==typeof 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D(t.key,t.value,\"exponential functions not supported\")),t.styleSpec.$version>=8&&(l&&!t.valueSpec[\"property-function\"]?u.push(new D(t.key,t.value,\"property functions not supported\")):s&&!t.valueSpec[\"zoom-function\"]&&\"heatmap-color\"!==t.objectKey&&\"line-gradient\"!==t.objectKey&&u.push(new D(t.key,t.value,\"zoom functions not supported\"))),\"categorical\"!==a&&!c||void 0!==t.value.property||u.push(new D(t.key,t.value,'\"property\" property is required')),u;function f(t){var e=[],a=t.value,s=t.key;if(\"array\"!==fe(a))return[new D(s,a,\"array expected, \"+fe(a)+\" found\")];if(2!==a.length)return[new D(s,a,\"array length 2 expected, length \"+a.length+\" found\")];if(c){if(\"object\"!==fe(a[0]))return[new D(s,a,\"object expected, \"+fe(a[0])+\" found\")];if(void 0===a[0].zoom)return[new D(s,a,\"object stop key must have zoom\")];if(void 0===a[0].value)return[new D(s,a,\"object stop key must have value\")];if(n&&n>F(a[0].zoom))return[new D(s,a[0].zoom,\"stop zoom values must 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Me(t._parameters,t._specification)},Me.serialize=function(t){return{_parameters:t._parameters,_specification:t._specification}};var Pe={type:\"boolean\",default:!1,function:!0,\"property-function\":!0,\"zoom-function\":!0};function Re(t){if(!t)return function(){return!0};De(t)||(t=Be(t));var e=we(t,Pe);if(\"error\"===e.result)throw new Error(e.value.map(function(t){return t.key+\": \"+t.message}).join(\", \"));return function(t,r){return e.value.evaluate(t,r)}}function Fe(t,e){return t<e?-1:t>e?1:0}function Be(t){if(!t)return!0;var e,r=t[0];return t.length<=1?\"any\"!==r:\"==\"===r?Ne(t[1],t[2],\"==\"):\"!=\"===r?Ue(Ne(t[1],t[2],\"==\")):\"<\"===r||\">\"===r||\"<=\"===r||\">=\"===r?Ne(t[1],t[2],r):\"any\"===r?(e=t.slice(1),[\"any\"].concat(e.map(Be))):\"all\"===r?[\"all\"].concat(t.slice(1).map(Be)):\"none\"===r?[\"all\"].concat(t.slice(1).map(Be).map(Ue)):\"in\"===r?je(t[1],t.slice(2)):\"!in\"===r?Ue(je(t[1],t.slice(2))):\"has\"===r?Ve(t[1]):\"!has\"!==r||Ue(Ve(t[1]))}function 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l=1;l<r.length;l++)o=o.concat(t({key:n+\"[\"+l+\"]\",value:r[l],style:e.style,styleSpec:e.styleSpec}));break;case\"has\":case\"!has\":i=fe(r[1]),2!==r.length?o.push(new D(n,r,'filter array for \"'+r[0]+'\" operator must have 2 elements')):\"string\"!==i&&o.push(new D(n+\"[1]\",r[1],\"string expected, \"+i+\" found\"))}return o}(t)}function qe(t,e){var r=t.key,n=t.style,i=t.styleSpec,a=t.value,o=t.objectKey,s=i[e+\"_\"+t.layerType];if(!s)return[];var l=o.match(/^(.*)-transition$/);if(\"paint\"===e&&l&&s[l[1]]&&s[l[1]].transition)return Ke({key:r,value:a,valueSpec:i.transition,style:n,styleSpec:i});var c,u=t.valueSpec||s[o];if(!u)return[new D(r,a,'unknown property \"'+o+'\"')];if(\"string\"===fe(a)&&u[\"property-function\"]&&!u.tokens&&(c=/^{([^}]+)}$/.exec(a)))return[new D(r,a,'\"'+o+'\" does not support interpolation syntax\\nUse an identity property function instead: `{ \"type\": \"identity\", \"property\": '+JSON.stringify(c[1])+\" }`.\")];var f=[];return\"symbol\"===t.layerType&&(\"text-field\"===o&&n&&!n.glyphs&&f.push(new D(r,a,'use of \"text-field\" requires a style \"glyphs\" property')),\"text-font\"===o&&he(B(a))&&\"identity\"===F(a.type)&&f.push(new D(r,a,'\"text-font\" does not support identity functions'))),f.concat(Ke({key:t.key,value:a,valueSpec:u,style:n,styleSpec:i,expressionContext:\"property\",propertyKey:o}))}function Ge(t){return qe(t,\"paint\")}function Ye(t){return qe(t,\"layout\")}function We(t){var e=[],r=t.value,n=t.key,i=t.style,a=t.styleSpec;r.type||r.ref||e.push(new D(n,r,'either \"type\" or \"ref\" is required'));var o,s=F(r.type),l=F(r.ref);if(r.id)for(var c=F(r.id),u=0;u<t.arrayIndex;u++){var f=i.layers[u];F(f.id)===c&&e.push(new D(n,r.id,'duplicate layer id \"'+r.id+'\", previously used at line '+f.id.__line__))}if(\"ref\"in r)[\"type\",\"source\",\"source-layer\",\"filter\",\"layout\"].forEach(function(t){t in r&&e.push(new D(n,r[t],'\"'+t+'\" is prohibited for ref 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n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i)}return t},Rr.prototype.possiblyEvaluate=function(t){for(var e=new Br(this._properties),r=0,n=Object.keys(this._values);r<n.length;r+=1){var i=n[r];e._values[i]=this._values[i].possiblyEvaluate(t)}return e};var Fr=function(t,e,r){this.property=t,this.value=e,this.globals=r};Fr.prototype.isConstant=function(){return\"constant\"===this.value.kind},Fr.prototype.constantOr=function(t){return\"constant\"===this.value.kind?this.value.value:t},Fr.prototype.evaluate=function(t){return this.property.evaluate(this.value,this.globals,t)};var Br=function(t){this._properties=t,this._values=Object.create(t.defaultPossiblyEvaluatedValues)};Br.prototype.get=function(t){return this._values[t]};var Nr=function(t){this.specification=t};Nr.prototype.possiblyEvaluate=function(t,e){return t.expression.evaluate(e)},Nr.prototype.interpolate=function(t,e,r){var n=kt[this.specification.type];return n?n(t,e,r):t};var jr=function(t){this.specification=t};jr.prototype.possiblyEvaluate=function(t,e){return\"constant\"===t.expression.kind||\"camera\"===t.expression.kind?new Fr(this,{kind:\"constant\",value:t.expression.evaluate(e)},e):new Fr(this,t.expression,e)},jr.prototype.interpolate=function(t,e,r){if(\"constant\"!==t.value.kind||\"constant\"!==e.value.kind)return t;if(void 0===t.value.value||void 0===e.value.value)return new Fr(this,{kind:\"constant\",value:void 0},t.globals);var n=kt[this.specification.type];return n?new Fr(this,{kind:\"constant\",value:n(t.value.value,e.value.value,r)},t.globals):t},jr.prototype.evaluate=function(t,e,r){return\"constant\"===t.kind?t.value:t.evaluate(e,r)};var Vr=function(t){this.specification=t};Vr.prototype.possiblyEvaluate=function(t,e){if(void 0!==t.value){if(\"constant\"===t.expression.kind){var r=t.expression.evaluate(e);return this._calculate(r,r,r,e)}return this._calculate(t.expression.evaluate(new Lr(Math.floor(e.zoom-1),e)),t.expression.evaluate(new Lr(Math.floor(e.zoom),e)),t.expression.evaluate(new Lr(Math.floor(e.zoom+1),e)),e)}},Vr.prototype._calculate=function(t,e,r,n){var i=n.zoom,a=i-Math.floor(i),o=n.crossFadingFactor();return i>n.zoomHistory.lastIntegerZoom?{from:t,to:e,fromScale:2,toScale:1,t:a+(1-a)*o}:{from:r,to:e,fromScale:.5,toScale:1,t:1-(1-o)*a}},Vr.prototype.interpolate=function(t){return t};var Ur=function(t){this.specification=t};Ur.prototype.possiblyEvaluate=function(t,e){return!!t.expression.evaluate(e)},Ur.prototype.interpolate=function(){return!1};var Hr=function(t){for(var e in this.properties=t,this.defaultPropertyValues={},this.defaultTransitionablePropertyValues={},this.defaultTransitioningPropertyValues={},this.defaultPossiblyEvaluatedValues={},t){var r=t[e],n=this.defaultPropertyValues[e]=new zr(r,void 0),i=this.defaultTransitionablePropertyValues[e]=new Or(r);this.defaultTransitioningPropertyValues[e]=i.untransitioned(),this.defaultPossiblyEvaluatedValues[e]=n.possiblyEvaluate({})}};pr(\"DataDrivenProperty\",jr),pr(\"DataConstantProperty\",Nr),pr(\"CrossFadedProperty\",Vr),pr(\"ColorRampProperty\",Ur);var qr=function(t){function e(e,r){for(var n in t.call(this),this.id=e.id,this.metadata=e.metadata,this.type=e.type,this.minzoom=e.minzoom,this.maxzoom=e.maxzoom,this.visibility=\"visible\",\"background\"!==e.type&&(this.source=e.source,this.sourceLayer=e[\"source-layer\"],this.filter=e.filter),this._featureFilter=function(){return!0},r.layout&&(this._unevaluatedLayout=new Rr(r.layout)),this._transitionablePaint=new Ir(r.paint),e.paint)this.setPaintProperty(n,e.paint[n],{validate:!1});for(var i in e.layout)this.setLayoutProperty(i,e.layout[i],{validate:!1});this._transitioningPaint=this._transitionablePaint.untransitioned()}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getLayoutProperty=function(t){return\"visibility\"===t?this.visibility:this._unevaluatedLayout.getValue(t)},e.prototype.setLayoutProperty=function(t,e,r){if(null!=e){var n=\"layers.\"+this.id+\".layout.\"+t;if(this._validate(or,n,t,e,r))return}\"visibility\"!==t?this._unevaluatedLayout.setValue(t,e):this.visibility=\"none\"===e?e:\"visible\"},e.prototype.getPaintProperty=function(t){return v(t,\"-transition\")?this._transitionablePaint.getTransition(t.slice(0,-\"-transition\".length)):this._transitionablePaint.getValue(t)},e.prototype.setPaintProperty=function(t,e,r){if(null!=e){var n=\"layers.\"+this.id+\".paint.\"+t;if(this._validate(ar,n,t,e,r))return}v(t,\"-transition\")?this._transitionablePaint.setTransition(t.slice(0,-\"-transition\".length),e||void 0):this._transitionablePaint.setValue(t,e)},e.prototype.isHidden=function(t){return!!(this.minzoom&&t<this.minzoom)||!!(this.maxzoom&&t>=this.maxzoom)||\"none\"===this.visibility},e.prototype.updateTransitions=function(t){this._transitioningPaint=this._transitionablePaint.transitioned(t,this._transitioningPaint)},e.prototype.hasTransition=function(){return this._transitioningPaint.hasTransition()},e.prototype.recalculate=function(t){this._unevaluatedLayout&&(this.layout=this._unevaluatedLayout.possiblyEvaluate(t)),this.paint=this._transitioningPaint.possiblyEvaluate(t)},e.prototype.serialize=function(){var t={id:this.id,type:this.type,source:this.source,\"source-layer\":this.sourceLayer,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom,filter:this.filter,layout:this._unevaluatedLayout&&this._unevaluatedLayout.serialize(),paint:this._transitionablePaint&&this._transitionablePaint.serialize()};return\"none\"===this.visibility&&(t.layout=t.layout||{},t.layout.visibility=\"none\"),y(t,function(t,e){return!(void 0===t||\"layout\"===e&&!Object.keys(t).length||\"paint\"===e&&!Object.keys(t).length)})},e.prototype._validate=function(t,e,r,n,i){return(!i||!1!==i.validate)&&sr(this,t.call(nr,{key:e,layerType:this.type,objectKey:r,value:n,styleSpec:I,style:{glyphs:!0,sprite:!0}}))},e.prototype.hasOffscreenPass=function(){return!1},e.prototype.resize=function(){},e}(O),Gr={Int8:Int8Array,Uint8:Uint8Array,Int16:Int16Array,Uint16:Uint16Array,Int32:Int32Array,Uint32:Uint32Array,Float32:Float32Array},Yr=function(t,e){this._structArray=t,this._pos1=e*this.size,this._pos2=this._pos1/2,this._pos4=this._pos1/4,this._pos8=this._pos1/8},Wr=function(){this.isTransferred=!1,this.capacity=-1,this.resize(0)};function Xr(t,e){void 0===e&&(e=1);var r=0,n=0;return{members:t.map(function(t){var i,a=(i=t.type,Gr[i].BYTES_PER_ELEMENT),o=r=Zr(r,Math.max(e,a)),s=t.components||1;return n=Math.max(n,a),r+=a*s,{name:t.name,type:t.type,components:s,offset:o}}),size:Zr(r,Math.max(n,e)),alignment:e}}function Zr(t,e){return Math.ceil(t/e)*e}Wr.serialize=function(t,e){return t._trim(),e&&(t.isTransferred=!0,e.push(t.arrayBuffer)),{length:t.length,arrayBuffer:t.arrayBuffer}},Wr.deserialize=function(t){var e=Object.create(this.prototype);return e.arrayBuffer=t.arrayBuffer,e.length=t.length,e.capacity=t.arrayBuffer.byteLength/e.bytesPerElement,e._refreshViews(),e},Wr.prototype._trim=function(){this.length!==this.capacity&&(this.capacity=this.length,this.arrayBuffer=this.arrayBuffer.slice(0,this.length*this.bytesPerElement),this._refreshViews())},Wr.prototype.clear=function(){this.length=0},Wr.prototype.resize=function(t){this.reserve(t),this.length=t},Wr.prototype.reserve=function(t){if(t>this.capacity){this.capacity=Math.max(t,Math.floor(5*this.capacity),128),this.arrayBuffer=new ArrayBuffer(this.capacity*this.bytesPerElement);var e=this.uint8;this._refreshViews(),e&&this.uint8.set(e)}},Wr.prototype._refreshViews=function(){throw new Error(\"_refreshViews() must be implemented by each concrete StructArray layout\")};var $r=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;this.resize(r+1);var n=2*r;return this.int16[n+0]=t,this.int16[n+1]=e,r},e}(Wr);$r.prototype.bytesPerElement=4,pr(\"StructArrayLayout2i4\",$r);var Jr=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;this.resize(i+1);var a=4*i;return this.int16[a+0]=t,this.int16[a+1]=e,this.int16[a+2]=r,this.int16[a+3]=n,i},e}(Wr);Jr.prototype.bytesPerElement=8,pr(\"StructArrayLayout4i8\",Jr);var Kr=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;this.resize(o+1);var s=6*o;return this.int16[s+0]=t,this.int16[s+1]=e,this.int16[s+2]=r,this.int16[s+3]=n,this.int16[s+4]=i,this.int16[s+5]=a,o},e}(Wr);Kr.prototype.bytesPerElement=12,pr(\"StructArrayLayout2i4i12\",Kr);var Qr=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s){var l=this.length;this.resize(l+1);var c=6*l,u=12*l;return this.int16[c+0]=t,this.int16[c+1]=e,this.int16[c+2]=r,this.int16[c+3]=n,this.uint8[u+8]=i,this.uint8[u+9]=a,this.uint8[u+10]=o,this.uint8[u+11]=s,l},e}(Wr);Qr.prototype.bytesPerElement=12,pr(\"StructArrayLayout4i4ub12\",Qr);var tn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s){var l=this.length;this.resize(l+1);var c=8*l;return this.int16[c+0]=t,this.int16[c+1]=e,this.int16[c+2]=r,this.int16[c+3]=n,this.uint16[c+4]=i,this.uint16[c+5]=a,this.uint16[c+6]=o,this.uint16[c+7]=s,l},e}(Wr);tn.prototype.bytesPerElement=16,pr(\"StructArrayLayout4i4ui16\",tn);var en=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;this.resize(n+1);var i=3*n;return this.float32[i+0]=t,this.float32[i+1]=e,this.float32[i+2]=r,n},e}(Wr);en.prototype.bytesPerElement=12,pr(\"StructArrayLayout3f12\",en);var rn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;this.resize(e+1);var r=1*e;return this.uint32[r+0]=t,e},e}(Wr);rn.prototype.bytesPerElement=4,pr(\"StructArrayLayout1ul4\",rn);var nn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u){var f=this.length;this.resize(f+1);var h=12*f,p=6*f;return this.int16[h+0]=t,this.int16[h+1]=e,this.int16[h+2]=r,this.int16[h+3]=n,this.int16[h+4]=i,this.int16[h+5]=a,this.uint32[p+3]=o,this.uint16[h+8]=s,this.uint16[h+9]=l,this.int16[h+10]=c,this.int16[h+11]=u,f},e}(Wr);nn.prototype.bytesPerElement=24,pr(\"StructArrayLayout6i1ul2ui2i24\",nn);var an=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;this.resize(o+1);var s=6*o;return this.int16[s+0]=t,this.int16[s+1]=e,this.int16[s+2]=r,this.int16[s+3]=n,this.int16[s+4]=i,this.int16[s+5]=a,o},e}(Wr);an.prototype.bytesPerElement=12,pr(\"StructArrayLayout2i2i2i12\",an);var on=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;this.resize(r+1);var n=4*r;return this.uint8[n+0]=t,this.uint8[n+1]=e,r},e}(Wr);on.prototype.bytesPerElement=4,pr(\"StructArrayLayout2ub4\",on);var sn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p){var d=this.length;this.resize(d+1);var g=20*d,v=10*d,m=40*d;return this.int16[g+0]=t,this.int16[g+1]=e,this.uint16[g+2]=r,this.uint16[g+3]=n,this.uint32[v+2]=i,this.uint32[v+3]=a,this.uint32[v+4]=o,this.uint16[g+10]=s,this.uint16[g+11]=l,this.uint16[g+12]=c,this.float32[v+7]=u,this.float32[v+8]=f,this.uint8[m+36]=h,this.uint8[m+37]=p,d},e}(Wr);sn.prototype.bytesPerElement=40,pr(\"StructArrayLayout2i2ui3ul3ui2f2ub40\",sn);var ln=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;this.resize(e+1);var r=1*e;return this.float32[r+0]=t,e},e}(Wr);ln.prototype.bytesPerElement=4,pr(\"StructArrayLayout1f4\",ln);var cn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;this.resize(n+1);var i=3*n;return this.int16[i+0]=t,this.int16[i+1]=e,this.int16[i+2]=r,n},e}(Wr);cn.prototype.bytesPerElement=6,pr(\"StructArrayLayout3i6\",cn);var un=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;this.resize(n+1);var i=2*n,a=4*n;return this.uint32[i+0]=t,this.uint16[a+2]=e,this.uint16[a+3]=r,n},e}(Wr);un.prototype.bytesPerElement=8,pr(\"StructArrayLayout1ul2ui8\",un);var fn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;this.resize(n+1);var i=3*n;return this.uint16[i+0]=t,this.uint16[i+1]=e,this.uint16[i+2]=r,n},e}(Wr);fn.prototype.bytesPerElement=6,pr(\"StructArrayLayout3ui6\",fn);var hn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;this.resize(r+1);var n=2*r;return this.uint16[n+0]=t,this.uint16[n+1]=e,r},e}(Wr);hn.prototype.bytesPerElement=4,pr(\"StructArrayLayout2ui4\",hn);var pn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;this.resize(r+1);var n=2*r;return this.float32[n+0]=t,this.float32[n+1]=e,r},e}(Wr);pn.prototype.bytesPerElement=8,pr(\"StructArrayLayout2f8\",pn);var dn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;this.resize(i+1);var a=4*i;return this.float32[a+0]=t,this.float32[a+1]=e,this.float32[a+2]=r,this.float32[a+3]=n,i},e}(Wr);dn.prototype.bytesPerElement=16,pr(\"StructArrayLayout4f16\",dn);var gn=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorPointX:{configurable:!0},anchorPointY:{configurable:!0},x1:{configurable:!0},y1:{configurable:!0},x2:{configurable:!0},y2:{configurable:!0},featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0},radius:{configurable:!0},signedDistanceFromAnchor:{configurable:!0},anchorPoint:{configurable:!0}};return r.anchorPointX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorPointX.set=function(t){this._structArray.int16[this._pos2+0]=t},r.anchorPointY.get=function(){return this._structArray.int16[this._pos2+1]},r.anchorPointY.set=function(t){this._structArray.int16[this._pos2+1]=t},r.x1.get=function(){return this._structArray.int16[this._pos2+2]},r.x1.set=function(t){this._structArray.int16[this._pos2+2]=t},r.y1.get=function(){return this._structArray.int16[this._pos2+3]},r.y1.set=function(t){this._structArray.int16[this._pos2+3]=t},r.x2.get=function(){return this._structArray.int16[this._pos2+4]},r.x2.set=function(t){this._structArray.int16[this._pos2+4]=t},r.y2.get=function(){return this._structArray.int16[this._pos2+5]},r.y2.set=function(t){this._structArray.int16[this._pos2+5]=t},r.featureIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.featureIndex.set=function(t){this._structArray.uint32[this._pos4+3]=t},r.sourceLayerIndex.get=function(){return this._structArray.uint16[this._pos2+8]},r.sourceLayerIndex.set=function(t){this._structArray.uint16[this._pos2+8]=t},r.bucketIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.bucketIndex.set=function(t){this._structArray.uint16[this._pos2+9]=t},r.radius.get=function(){return this._structArray.int16[this._pos2+10]},r.radius.set=function(t){this._structArray.int16[this._pos2+10]=t},r.signedDistanceFromAnchor.get=function(){return this._structArray.int16[this._pos2+11]},r.signedDistanceFromAnchor.set=function(t){this._structArray.int16[this._pos2+11]=t},r.anchorPoint.get=function(){return new l(this.anchorPointX,this.anchorPointY)},Object.defineProperties(e.prototype,r),e}(Yr);gn.prototype.size=24;var vn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new gn(this,t)},e}(nn);pr(\"CollisionBoxArray\",vn);var mn=function(t){function 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Nn=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map(function(t){return t.id}),this.index=t.index,this.layoutVertexArray=new $r,this.indexArray=new fn,this.segments=new Mn,this.programConfigurations=new In(An,t.layers,t.zoom)};function jn(t,e,r){for(var n=0;n<t.length;n++){var i=t[n];if(Zn(i,e))return!0;if(Yn(e,i,r))return!0}return!1}function Vn(t,e){if(1===t.length&&1===t[0].length)return Xn(e,t[0][0]);for(var r=0;r<e.length;r++)for(var n=e[r],i=0;i<n.length;i++)if(Xn(t,n[i]))return!0;for(var a=0;a<t.length;a++){for(var o=t[a],s=0;s<o.length;s++)if(Xn(e,o[s]))return!0;for(var l=0;l<e.length;l++)if(qn(o,e[l]))return!0}return!1}function Un(t,e,r){for(var n=0;n<e.length;n++)for(var i=e[n],a=0;a<t.length;a++){var o=t[a];if(o.length>=3)for(var s=0;s<i.length;s++)if(Zn(o,i[s]))return!0;if(Hn(o,i,r))return!0}return!1}function Hn(t,e,r){if(t.length>1){if(qn(t,e))return!0;for(var n=0;n<e.length;n++)if(Yn(e[n],t,r))return!0}for(var 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n=e.paint.get(t).value;return\"constant\"===n.kind?n.value:r.programConfigurations.get(e.id).binders[t].statistics.max}function Jn(t){return Math.sqrt(t[0]*t[0]+t[1]*t[1])}function Kn(t,e,r,n,i){if(!e[0]&&!e[1])return t;var a=l.convert(e);\"viewport\"===r&&a._rotate(-n);for(var o=[],s=0;s<t.length;s++){for(var c=t[s],u=[],f=0;f<c.length;f++)u.push(c[f].sub(a._mult(i)));o.push(u)}return o}Nn.prototype.populate=function(t,e){for(var r=0,n=t;r<n.length;r+=1){var i=n[r],a=i.feature,o=i.index,s=i.sourceLayerIndex;if(this.layers[0]._featureFilter(new Lr(this.zoom),a)){var l=Fn(a);this.addFeature(a,l),e.featureIndex.insert(a,l,o,s,this.index)}}},Nn.prototype.isEmpty=function(){return 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r=t.readVarint()+t.pos;t.pos<r;){var n=e._keys[t.readVarint()],i=e._values[t.readVarint()];e.properties[n]=i}}(r,e):3==t?e.type=r.readVarint():4==t&&(e._geometry=r.pos)}function ua(t){for(var e,r,n=0,i=0,a=t.length,o=a-1;i<a;o=i++)e=t[i],n+=((r=t[o]).x-e.x)*(e.y+r.y);return n}la.types=[\"Unknown\",\"Point\",\"LineString\",\"Polygon\"],la.prototype.loadGeometry=function(){var t=this._pbf;t.pos=this._geometry;for(var e,r=t.readVarint()+t.pos,n=1,i=0,a=0,o=0,s=[];t.pos<r;){if(i<=0){var c=t.readVarint();n=7&c,i=c>>3}if(i--,1===n||2===n)a+=t.readSVarint(),o+=t.readSVarint(),1===n&&(e&&s.push(e),e=[]),e.push(new l(a,o));else{if(7!==n)throw new Error(\"unknown command \"+n);e&&e.push(e[0].clone())}}return e&&s.push(e),s},la.prototype.bbox=function(){var t=this._pbf;t.pos=this._geometry;for(var e=t.readVarint()+t.pos,r=1,n=0,i=0,a=0,o=1/0,s=-1/0,l=1/0,c=-1/0;t.pos<e;){if(n<=0){var u=t.readVarint();r=7&u,n=u>>3}if(n--,1===r||2===r)(i+=t.readSVarint())<o&&(o=i),i>s&&(s=i),(a+=t.readSVarint())<l&&(l=a),a>c&&(c=a);else if(7!==r)throw new Error(\"unknown command \"+r)}return[o,l,s,c]},la.prototype.toGeoJSON=function(t,e,r){var n,i,a=this.extent*Math.pow(2,r),o=this.extent*t,s=this.extent*e,l=this.loadGeometry(),c=la.types[this.type];function u(t){for(var e=0;e<t.length;e++){var r=t[e],n=180-360*(r.y+s)/a;t[e]=[360*(r.x+o)/a-180,360/Math.PI*Math.atan(Math.exp(n*Math.PI/180))-90]}}switch(this.type){case 1:var f=[];for(n=0;n<l.length;n++)f[n]=l[n][0];u(l=f);break;case 2:for(n=0;n<l.length;n++)u(l[n]);break;case 3:for(l=function(t){var e=t.length;if(e<=1)return[t];for(var r,n,i=[],a=0;a<e;a++){var o=ua(t[a]);0!==o&&(void 0===n&&(n=o<0),n===o<0?(r&&i.push(r),r=[t[a]]):r.push(t[a]))}return r&&i.push(r),i}(l),n=0;n<l.length;n++)for(i=0;i<l[n].length;i++)u(l[n][i])}1===l.length?l=l[0]:c=\"Multi\"+c;var h={type:\"Feature\",geometry:{type:c,coordinates:l},properties:this.properties};return\"id\"in this&&(h.id=this.id),h};var fa=ha;function ha(t,e){this.version=1,this.name=null,this.extent=4096,this.length=0,this._pbf=t,this._keys=[],this._values=[],this._features=[],t.readFields(pa,this,e),this.length=this._features.length}function pa(t,e,r){15===t?e.version=r.readVarint():1===t?e.name=r.readString():5===t?e.extent=r.readVarint():2===t?e._features.push(r.pos):3===t?e._keys.push(r.readString()):4===t&&e._values.push(function(t){for(var e=null,r=t.readVarint()+t.pos;t.pos<r;){var n=t.readVarint()>>3;e=1===n?t.readString():2===n?t.readFloat():3===n?t.readDouble():4===n?t.readVarint64():5===n?t.readVarint():6===n?t.readSVarint():7===n?t.readBoolean():null}return e}(r))}function da(t,e,r){if(3===t){var n=new fa(r,r.readVarint()+r.pos);n.length&&(e[n.name]=n)}}ha.prototype.feature=function(t){if(t<0||t>=this._features.length)throw new Error(\"feature index out of 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i=n[r],a=i.feature,o=i.index,s=i.sourceLayerIndex;if(this.layers[0]._featureFilter(new Lr(this.zoom),a)){var l=Fn(a);this.addFeature(a,l),e.featureIndex.insert(a,l,o,s,this.index)}}},wa.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},wa.prototype.upload=function(t){this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,oa),this.indexBuffer=t.createIndexBuffer(this.indexArray),this.programConfigurations.upload(t)},wa.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},wa.prototype.addFeature=function(t,e){for(var r=this.layers[0].layout,n=r.get(\"line-join\").evaluate(t),i=r.get(\"line-cap\"),a=r.get(\"line-miter-limit\"),o=r.get(\"line-round-limit\"),s=0,l=e;s<l.length;s+=1){var c=l[s];this.addLine(c,t,n,i,a,o)}},wa.prototype.addLine=function(t,e,r,n,i,a){var o=null;e.properties&&e.properties.hasOwnProperty(\"mapbox_clip_start\")&&e.properties.hasOwnProperty(\"mapbox_clip_end\")&&(o={start:e.properties.mapbox_clip_start,end:e.properties.mapbox_clip_end,tileTotal:void 0});for(var s=\"Polygon\"===va[e.type],l=t.length;l>=2&&t[l-1].equals(t[l-2]);)l--;for(var c=0;c<l-1&&t[c].equals(t[c+1]);)c++;if(!(l<(s?3:2))){o&&(o.tileTotal=function(t,e,r){for(var n,i,a=0,o=c;o<r-1;o++)n=t[o],i=t[o+1],a+=n.dist(i);return a}(t,0,l)),\"bevel\"===r&&(i=1.05);var u=Pn/(512*this.overscaling)*15,f=t[c],h=this.segments.prepareSegment(10*l,this.layoutVertexArray,this.indexArray);this.distance=0;var p,d,g,v=n,m=s?\"butt\":n,y=!0,x=void 0,b=void 0,_=void 0,w=void 0;this.e1=this.e2=this.e3=-1,s&&(p=t[l-2],w=f.sub(p)._unit()._perp());for(var k=c;k<l;k++)if(!(b=s&&k===l-1?t[c+1]:t[k+1])||!t[k].equals(b)){w&&(_=w),p&&(x=p),p=t[k],w=b?b.sub(p)._unit()._perp():_;var T=(_=_||w).add(w);0===T.x&&0===T.y||T._unit();var A=T.x*w.x+T.y*w.y,M=0!==A?1/A:1/0,S=A<ya&&x&&b;if(S&&k>c){var E=p.dist(x);if(E>2*u){var C=p.sub(p.sub(x)._mult(u/E)._round());this.distance+=C.dist(x),this.addCurrentVertex(C,this.distance,_.mult(1),0,0,!1,h,o),x=C}}var L=x&&b,z=L?r:b?v:m;if(L&&\"round\"===z&&(M<a?z=\"miter\":M<=2&&(z=\"fakeround\")),\"miter\"===z&&M>i&&(z=\"bevel\"),\"bevel\"===z&&(M>2&&(z=\"flipbevel\"),M<i&&(z=\"miter\")),x&&(this.distance+=p.dist(x)),\"miter\"===z)T._mult(M),this.addCurrentVertex(p,this.distance,T,0,0,!1,h,o);else if(\"flipbevel\"===z){if(M>100)T=w.clone().mult(-1);else{var O=_.x*w.y-_.y*w.x>0?-1:1,I=M*_.add(w).mag()/_.sub(w).mag();T._perp()._mult(I*O)}this.addCurrentVertex(p,this.distance,T,0,0,!1,h,o),this.addCurrentVertex(p,this.distance,T.mult(-1),0,0,!1,h,o)}else if(\"bevel\"===z||\"fakeround\"===z){var D=_.x*w.y-_.y*w.x>0,P=-Math.sqrt(M*M-1);if(D?(g=0,d=P):(d=0,g=P),y||this.addCurrentVertex(p,this.distance,_,d,g,!1,h,o),\"fakeround\"===z){for(var R=Math.floor(8*(.5-(A-.5))),F=void 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V=p.add(b.sub(p)._mult(u/j)._round());this.distance+=V.dist(p),this.addCurrentVertex(V,this.distance,w.mult(1),0,0,!1,h,o),p=V}}y=!1}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,e)}},wa.prototype.addCurrentVertex=function(t,e,r,n,i,a,o,s){var l,c=this.layoutVertexArray,u=this.indexArray;s&&(e=ka(e,s)),l=r.clone(),n&&l._sub(r.perp()._mult(n)),_a(c,t,l,a,!1,n,e),this.e3=o.vertexLength++,this.e1>=0&&this.e2>=0&&(u.emplaceBack(this.e1,this.e2,this.e3),o.primitiveLength++),this.e1=this.e2,this.e2=this.e3,l=r.mult(-1),i&&l._sub(r.perp()._mult(i)),_a(c,t,l,a,!0,-i,e),this.e3=o.vertexLength++,this.e1>=0&&this.e2>=0&&(u.emplaceBack(this.e1,this.e2,this.e3),o.primitiveLength++),this.e1=this.e2,this.e2=this.e3,e>ba/2&&!s&&(this.distance=0,this.addCurrentVertex(t,this.distance,r,n,i,a,o))},wa.prototype.addPieSliceVertex=function(t,e,r,n,i,a){r=r.mult(n?-1:1);var 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e(e,r,n,i){t.call(this,e,r),this.angle=n,void 0!==i&&(this.segment=i)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.clone=function(){return new e(this.x,this.y,this.angle,this.segment)},e}(l);function Fa(t,e){var r=e.expression;if(\"constant\"===r.kind)return{functionType:\"constant\",layoutSize:r.evaluate(new Lr(t+1))};if(\"source\"===r.kind)return{functionType:\"source\"};for(var n=r.zoomStops,i=0;i<n.length&&n[i]<=t;)i++;for(var a=i=Math.max(0,i-1);a<n.length&&n[a]<t+1;)a++;a=Math.min(n.length-1,a);var o={min:n[i],max:n[a]};return\"composite\"===r.kind?{functionType:\"composite\",zoomRange:o,propertyValue:e.value}:{functionType:\"camera\",layoutSize:r.evaluate(new Lr(t+1)),zoomRange:o,sizeRange:{min:r.evaluate(new Lr(o.min)),max:r.evaluate(new Lr(o.max))},propertyValue:e.value}}pr(\"Anchor\",Ra);var Ba=ga.VectorTileFeature.types,Na=[{name:\"a_fade_opacity\",components:1,type:\"Uint8\",offset:0}];function ja(t,e,r,n,i,a,o,s){t.emplaceBack(e,r,Math.round(32*n),Math.round(32*i),a,o,s?s[0]:0,s?s[1]:0)}function Va(t,e,r){t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r)}var Ua=function(t){this.layoutVertexArray=new tn,this.indexArray=new fn,this.programConfigurations=t,this.segments=new Mn,this.dynamicLayoutVertexArray=new en,this.opacityVertexArray=new rn,this.placedSymbolArray=new yn};Ua.prototype.upload=function(t,e){this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,Ca.members),this.indexBuffer=t.createIndexBuffer(this.indexArray,e),this.programConfigurations.upload(t),this.dynamicLayoutVertexBuffer=t.createVertexBuffer(this.dynamicLayoutVertexArray,La.members,!0),this.opacityVertexBuffer=t.createVertexBuffer(this.opacityVertexArray,Na,!0),this.opacityVertexBuffer.itemSize=1},Ua.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.dynamicLayoutVertexBuffer.destroy(),this.opacityVertexBuffer.destroy())},pr(\"SymbolBuffers\",Ua);var Ha=function(t,e,r){this.layoutVertexArray=new t,this.layoutAttributes=e,this.indexArray=new r,this.segments=new Mn,this.collisionVertexArray=new on};Ha.prototype.upload=function(t){this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,this.layoutAttributes),this.indexBuffer=t.createIndexBuffer(this.indexArray),this.collisionVertexBuffer=t.createVertexBuffer(this.collisionVertexArray,za.members,!0)},Ha.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.segments.destroy(),this.collisionVertexBuffer.destroy())},pr(\"CollisionBuffers\",Ha);var qa=function(t){this.collisionBoxArray=t.collisionBoxArray,this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map(function(t){return t.id}),this.index=t.index,this.pixelRatio=t.pixelRatio,this.sourceLayerIndex=t.sourceLayerIndex;var e=this.layers[0]._unevaluatedLayout._values;this.textSizeData=Fa(this.zoom,e[\"text-size\"]),this.iconSizeData=Fa(this.zoom,e[\"icon-size\"]);var r=this.layers[0].layout;this.sortFeaturesByY=r.get(\"text-allow-overlap\")||r.get(\"icon-allow-overlap\")||r.get(\"text-ignore-placement\")||r.get(\"icon-ignore-placement\")};qa.prototype.createArrays=function(){this.text=new Ua(new In(Ca.members,this.layers,this.zoom,function(t){return/^text/.test(t)})),this.icon=new Ua(new In(Ca.members,this.layers,this.zoom,function(t){return/^icon/.test(t)})),this.collisionBox=new Ha(an,Oa.members,hn),this.collisionCircle=new Ha(an,Ia.members,fn),this.glyphOffsetArray=new bn,this.lineVertexArray=new wn},qa.prototype.populate=function(t,e){var r=this.layers[0],n=r.layout,i=n.get(\"text-font\"),a=n.get(\"text-field\"),o=n.get(\"icon-image\"),s=(\"constant\"!==a.value.kind||a.value.value.length>0)&&(\"constant\"!==i.value.kind||i.value.value.length>0),l=\"constant\"!==o.value.kind||o.value.value&&o.value.value.length>0;if(this.features=[],s||l){for(var c=e.iconDependencies,u=e.glyphDependencies,f=new Lr(this.zoom),h=0,p=t;h<p.length;h+=1){var d=p[h],g=d.feature,v=d.index,m=d.sourceLayerIndex;if(r._featureFilter(f,g)){var y=void 0;s&&(y=Da(y=r.getValueAndResolveTokens(\"text-field\",g),r,g));var x=void 0;if(l&&(x=r.getValueAndResolveTokens(\"icon-image\",g)),y||x){var b={text:y,icon:x,index:v,sourceLayerIndex:m,geometry:Fn(g),properties:g.properties,type:Ba[g.type]};if(void 0!==g.id&&(b.id=g.id),this.features.push(b),x&&(c[x]=!0),y)for(var _=i.evaluate(g).join(\",\"),w=u[_]=u[_]||{},k=\"map\"===n.get(\"text-rotation-alignment\")&&\"line\"===n.get(\"symbol-placement\"),T=xr(y),A=0;A<y.length;A++)if(w[y.charCodeAt(A)]=!0,k&&T){var M=Pa[y.charAt(A)];M&&(w[M.charCodeAt(0)]=!0)}}}}\"line\"===n.get(\"symbol-placement\")&&(this.features=function(t){var e={},r={},n=[],i=0;function a(e){n.push(t[e]),i++}function o(t,e,i){var a=r[t];return delete r[t],r[e]=a,n[a].geometry[0].pop(),n[a].geometry[0]=n[a].geometry[0].concat(i[0]),a}function s(t,r,i){var a=e[r];return delete e[r],e[t]=a,n[a].geometry[0].shift(),n[a].geometry[0]=i[0].concat(n[a].geometry[0]),a}function l(t,e,r){var n=r?e[0][e[0].length-1]:e[0][0];return t+\":\"+n.x+\":\"+n.y}for(var c=0;c<t.length;c++){var u=t[c],f=u.geometry,h=u.text;if(h){var p=l(h,f),d=l(h,f,!0);if(p in r&&d in e&&r[p]!==e[d]){var g=s(p,d,f),v=o(p,d,n[g].geometry);delete e[p],delete r[d],r[l(h,n[v].geometry,!0)]=v,n[g].geometry=null}else p in r?o(p,d,f):d in e?s(p,d,f):(a(c),e[p]=i-1,r[d]=i-1)}else a(c)}return n.filter(function(t){return t.geometry})}(this.features))}},qa.prototype.isEmpty=function(){return 0===this.symbolInstances.length},qa.prototype.upload=function(t){this.text.upload(t,this.sortFeaturesByY),this.icon.upload(t,this.sortFeaturesByY),this.collisionBox.upload(t),this.collisionCircle.upload(t)},qa.prototype.destroy=function(){this.text.destroy(),this.icon.destroy(),this.collisionBox.destroy(),this.collisionCircle.destroy()},qa.prototype.addToLineVertexArray=function(t,e){var r=this.lineVertexArray.length;if(void 0!==t.segment){for(var n=t.dist(e[t.segment+1]),i=t.dist(e[t.segment]),a={},o=t.segment+1;o<e.length;o++)a[o]={x:e[o].x,y:e[o].y,tileUnitDistanceFromAnchor:n},o<e.length-1&&(n+=e[o+1].dist(e[o]));for(var s=t.segment||0;s>=0;s--)a[s]={x:e[s].x,y:e[s].y,tileUnitDistanceFromAnchor:i},s>0&&(i+=e[s-1].dist(e[s]));for(var l=0;l<e.length;l++){var c=a[l];this.lineVertexArray.emplaceBack(c.x,c.y,c.tileUnitDistanceFromAnchor)}}return{lineStartIndex:r,lineLength:this.lineVertexArray.length-r}},qa.prototype.addSymbols=function(t,e,r,n,i,a,o,s,l,c){for(var u=t.indexArray,f=t.layoutVertexArray,h=t.dynamicLayoutVertexArray,p=t.segments.prepareSegment(4*e.length,t.layoutVertexArray,t.indexArray),d=this.glyphOffsetArray.length,g=p.vertexLength,v=0,m=e;v<m.length;v+=1){var y=m[v],x=y.tl,b=y.tr,_=y.bl,w=y.br,k=y.tex,T=p.vertexLength,A=y.glyphOffset[1];ja(f,s.x,s.y,x.x,A+x.y,k.x,k.y,r),ja(f,s.x,s.y,b.x,A+b.y,k.x+k.w,k.y,r),ja(f,s.x,s.y,_.x,A+_.y,k.x,k.y+k.h,r),ja(f,s.x,s.y,w.x,A+w.y,k.x+k.w,k.y+k.h,r),Va(h,s,0),u.emplaceBack(T,T+1,T+2),u.emplaceBack(T+1,T+2,T+3),p.vertexLength+=4,p.primitiveLength+=2,this.glyphOffsetArray.emplaceBack(y.glyphOffset[0])}t.placedSymbolArray.emplaceBack(s.x,s.y,d,this.glyphOffsetArray.length-d,g,l,c,s.segment,r?r[0]:0,r?r[1]:0,n[0],n[1],o,!1),t.programConfigurations.populatePaintArrays(t.layoutVertexArray.length,a)},qa.prototype._addCollisionDebugVertex=function(t,e,r,n,i){return e.emplaceBack(0,0),t.emplaceBack(r.x,r.y,n.x,n.y,Math.round(i.x),Math.round(i.y))},qa.prototype.addCollisionDebugVertices=function(t,e,r,n,i,a,o,s){var c=i.segments.prepareSegment(4,i.layoutVertexArray,i.indexArray),u=c.vertexLength,f=i.layoutVertexArray,h=i.collisionVertexArray;if(this._addCollisionDebugVertex(f,h,a,o.anchor,new l(t,e)),this._addCollisionDebugVertex(f,h,a,o.anchor,new l(r,e)),this._addCollisionDebugVertex(f,h,a,o.anchor,new l(r,n)),this._addCollisionDebugVertex(f,h,a,o.anchor,new l(t,n)),c.vertexLength+=4,s){var p=i.indexArray;p.emplaceBack(u,u+1,u+2),p.emplaceBack(u,u+2,u+3),c.primitiveLength+=2}else{var d=i.indexArray;d.emplaceBack(u,u+1),d.emplaceBack(u+1,u+2),d.emplaceBack(u+2,u+3),d.emplaceBack(u+3,u),c.primitiveLength+=4}},qa.prototype.generateCollisionDebugBuffers=function(){for(var t=0,e=this.symbolInstances;t<e.length;t+=1){var r=e[t];r.textCollisionFeature={boxStartIndex:r.textBoxStartIndex,boxEndIndex:r.textBoxEndIndex},r.iconCollisionFeature={boxStartIndex:r.iconBoxStartIndex,boxEndIndex:r.iconBoxEndIndex};for(var n=0;n<2;n++){var i=r[0===n?\"textCollisionFeature\":\"iconCollisionFeature\"];if(i)for(var a=i.boxStartIndex;a<i.boxEndIndex;a++){var o=this.collisionBoxArray.get(a),s=o.x1,l=o.y1,c=o.x2,u=o.y2,f=o.radius>0;this.addCollisionDebugVertices(s,l,c,u,f?this.collisionCircle:this.collisionBox,o.anchorPoint,r,f)}}}},qa.prototype.deserializeCollisionBoxes=function(t,e,r,n,i){for(var a={},o=e;o<r;o++){var s=t.get(o);if(0===s.radius){a.textBox={x1:s.x1,y1:s.y1,x2:s.x2,y2:s.y2,anchorPointX:s.anchorPointX,anchorPointY:s.anchorPointY},a.textFeatureIndex=s.featureIndex;break}a.textCircles||(a.textCircles=[],a.textFeatureIndex=s.featureIndex),a.textCircles.push(s.anchorPointX,s.anchorPointY,s.radius,s.signedDistanceFromAnchor,1)}for(var l=n;l<i;l++){var c=t.get(l);if(0===c.radius){a.iconBox={x1:c.x1,y1:c.y1,x2:c.x2,y2:c.y2,anchorPointX:c.anchorPointX,anchorPointY:c.anchorPointY},a.iconFeatureIndex=c.featureIndex;break}}return a},qa.prototype.hasTextData=function(){return this.text.segments.get().length>0},qa.prototype.hasIconData=function(){return this.icon.segments.get().length>0},qa.prototype.hasCollisionBoxData=function(){return this.collisionBox.segments.get().length>0},qa.prototype.hasCollisionCircleData=function(){return this.collisionCircle.segments.get().length>0},qa.prototype.sortFeatures=function(t){var e=this;if(this.sortFeaturesByY&&this.sortedAngle!==t&&(this.sortedAngle=t,!(this.text.segments.get().length>1||this.icon.segments.get().length>1))){for(var r=[],n=0;n<this.symbolInstances.length;n++)r.push(n);var i=Math.sin(t),a=Math.cos(t);r.sort(function(t,r){var n=e.symbolInstances[t],o=e.symbolInstances[r];return(i*n.anchor.x+a*n.anchor.y|0)-(i*o.anchor.x+a*o.anchor.y|0)||o.featureIndex-n.featureIndex}),this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var o=0,s=r;o<s.length;o+=1){var l=s[o],c=e.symbolInstances[l];e.featureSortOrder.push(c.featureIndex);for(var u=0,f=c.placedTextSymbolIndices;u<f.length;u+=1)for(var h=f[u],p=e.text.placedSymbolArray.get(h),d=p.vertexStartIndex+4*p.numGlyphs,g=p.vertexStartIndex;g<d;g+=4)e.text.indexArray.emplaceBack(g,g+1,g+2),e.text.indexArray.emplaceBack(g+1,g+2,g+3);var v=e.icon.placedSymbolArray.get(l);if(v.numGlyphs){var m=v.vertexStartIndex;e.icon.indexArray.emplaceBack(m,m+1,m+2),e.icon.indexArray.emplaceBack(m+1,m+2,m+3)}}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},pr(\"SymbolBucket\",qa,{omit:[\"layers\",\"collisionBoxArray\",\"features\",\"compareText\"],shallow:[\"symbolInstances\"]}),qa.MAX_GLYPHS=65535,qa.addDynamicAttributes=Va;var Ga=new Hr({\"symbol-placement\":new Nr(I.layout_symbol[\"symbol-placement\"]),\"symbol-spacing\":new Nr(I.layout_symbol[\"symbol-spacing\"]),\"symbol-avoid-edges\":new Nr(I.layout_symbol[\"symbol-avoid-edges\"]),\"icon-allow-overlap\":new Nr(I.layout_symbol[\"icon-allow-overlap\"]),\"icon-ignore-placement\":new Nr(I.layout_symbol[\"icon-ignore-placement\"]),\"icon-optional\":new Nr(I.layout_symbol[\"icon-optional\"]),\"icon-rotation-alignment\":new Nr(I.layout_symbol[\"icon-rotation-alignment\"]),\"icon-size\":new jr(I.layout_symbol[\"icon-size\"]),\"icon-text-fit\":new Nr(I.layout_symbol[\"icon-text-fit\"]),\"icon-text-fit-padding\":new Nr(I.layout_symbol[\"icon-text-fit-padding\"]),\"icon-image\":new jr(I.layout_symbol[\"icon-image\"]),\"icon-rotate\":new jr(I.layout_symbol[\"icon-rotate\"]),\"icon-padding\":new Nr(I.layout_symbol[\"icon-padding\"]),\"icon-keep-upright\":new Nr(I.layout_symbol[\"icon-keep-upright\"]),\"icon-offset\":new jr(I.layout_symbol[\"icon-offset\"]),\"icon-anchor\":new jr(I.layout_symbol[\"icon-anchor\"]),\"icon-pitch-alignment\":new Nr(I.layout_symbol[\"icon-pitch-alignment\"]),\"text-pitch-alignment\":new Nr(I.layout_symbol[\"text-pitch-alignment\"]),\"text-rotation-alignment\":new Nr(I.layout_symbol[\"text-rotation-alignment\"]),\"text-field\":new jr(I.layout_symbol[\"text-field\"]),\"text-font\":new jr(I.layout_symbol[\"text-font\"]),\"text-size\":new jr(I.layout_symbol[\"text-size\"]),\"text-max-width\":new jr(I.layout_symbol[\"text-max-width\"]),\"text-line-height\":new Nr(I.layout_symbol[\"text-line-height\"]),\"text-letter-spacing\":new jr(I.layout_symbol[\"text-letter-spacing\"]),\"text-justify\":new jr(I.layout_symbol[\"text-justify\"]),\"text-anchor\":new jr(I.layout_symbol[\"text-anchor\"]),\"text-max-angle\":new Nr(I.layout_symbol[\"text-max-angle\"]),\"text-rotate\":new jr(I.layout_symbol[\"text-rotate\"]),\"text-padding\":new Nr(I.layout_symbol[\"text-padding\"]),\"text-keep-upright\":new Nr(I.layout_symbol[\"text-keep-upright\"]),\"text-transform\":new jr(I.layout_symbol[\"text-transform\"]),\"text-offset\":new jr(I.layout_symbol[\"text-offset\"]),\"text-allow-overlap\":new Nr(I.layout_symbol[\"text-allow-overlap\"]),\"text-ignore-placement\":new Nr(I.layout_symbol[\"text-ignore-placement\"]),\"text-optional\":new Nr(I.layout_symbol[\"text-optional\"])}),Ya={paint:new Hr({\"icon-opacity\":new jr(I.paint_symbol[\"icon-opacity\"]),\"icon-color\":new jr(I.paint_symbol[\"icon-color\"]),\"icon-halo-color\":new jr(I.paint_symbol[\"icon-halo-color\"]),\"icon-halo-width\":new jr(I.paint_symbol[\"icon-halo-width\"]),\"icon-halo-blur\":new jr(I.paint_symbol[\"icon-halo-blur\"]),\"icon-translate\":new Nr(I.paint_symbol[\"icon-translate\"]),\"icon-translate-anchor\":new Nr(I.paint_symbol[\"icon-translate-anchor\"]),\"text-opacity\":new jr(I.paint_symbol[\"text-opacity\"]),\"text-color\":new jr(I.paint_symbol[\"text-color\"]),\"text-halo-color\":new jr(I.paint_symbol[\"text-halo-color\"]),\"text-halo-width\":new jr(I.paint_symbol[\"text-halo-width\"]),\"text-halo-blur\":new jr(I.paint_symbol[\"text-halo-blur\"]),\"text-translate\":new Nr(I.paint_symbol[\"text-translate\"]),\"text-translate-anchor\":new Nr(I.paint_symbol[\"text-translate-anchor\"])}),layout:Ga},Wa=function(t){function e(e){t.call(this,e,Ya)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.recalculate=function(e){t.prototype.recalculate.call(this,e),\"auto\"===this.layout.get(\"icon-rotation-alignment\")&&(\"line\"===this.layout.get(\"symbol-placement\")?this.layout._values[\"icon-rotation-alignment\"]=\"map\":this.layout._values[\"icon-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-rotation-alignment\")&&(\"line\"===this.layout.get(\"symbol-placement\")?this.layout._values[\"text-rotation-alignment\"]=\"map\":this.layout._values[\"text-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-pitch-alignment\")&&(this.layout._values[\"text-pitch-alignment\"]=this.layout.get(\"text-rotation-alignment\")),\"auto\"===this.layout.get(\"icon-pitch-alignment\")&&(this.layout._values[\"icon-pitch-alignment\"]=this.layout.get(\"icon-rotation-alignment\"))},e.prototype.getValueAndResolveTokens=function(t,e){var r,n=this.layout.get(t).evaluate(e),i=this._unevaluatedLayout._values[t];return i.isDataDriven()||_e(i.value)?n:(r=e.properties,n.replace(/{([^{}]+)}/g,function(t,e){return e in r?String(r[e]):\"\"}))},e.prototype.createBucket=function(t){return new qa(t)},e.prototype.queryRadius=function(){return 0},e.prototype.queryIntersectsFeature=function(){return!1},e}(qr),Xa={paint:new Hr({\"background-color\":new Nr(I.paint_background[\"background-color\"]),\"background-pattern\":new Vr(I.paint_background[\"background-pattern\"]),\"background-opacity\":new Nr(I.paint_background[\"background-opacity\"])})},Za=function(t){function e(e){t.call(this,e,Xa)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(qr),$a={paint:new Hr({\"raster-opacity\":new Nr(I.paint_raster[\"raster-opacity\"]),\"raster-hue-rotate\":new Nr(I.paint_raster[\"raster-hue-rotate\"]),\"raster-brightness-min\":new Nr(I.paint_raster[\"raster-brightness-min\"]),\"raster-brightness-max\":new Nr(I.paint_raster[\"raster-brightness-max\"]),\"raster-saturation\":new Nr(I.paint_raster[\"raster-saturation\"]),\"raster-contrast\":new Nr(I.paint_raster[\"raster-contrast\"]),\"raster-fade-duration\":new Nr(I.paint_raster[\"raster-fade-duration\"])})},Ja={circle:ni,heatmap:pi,hillshade:gi,fill:Ji,\"fill-extrusion\":aa,line:Sa,symbol:Wa,background:Za,raster:function(t){function e(e){t.call(this,e,$a)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(qr)},Ka=i(function(t,e){t.exports=function(){function t(t,e,r){r=r||{},this.w=t||64,this.h=e||64,this.autoResize=!!r.autoResize,this.shelves=[],this.freebins=[],this.stats={},this.bins={},this.maxId=0}function e(t,e,r){this.x=0,this.y=t,this.w=this.free=e,this.h=r}return t.prototype.pack=function(t,e){t=[].concat(t),e=e||{};for(var r,n,i,a,o=[],s=0;s<t.length;s++)if(r=t[s].w||t[s].width,n=t[s].h||t[s].height,i=t[s].id,r&&n){if(!(a=this.packOne(r,n,i)))continue;e.inPlace&&(t[s].x=a.x,t[s].y=a.y,t[s].id=a.id),o.push(a)}return this.shrink(),o},t.prototype.packOne=function(t,r,n){var i,a,o,s,l,c,u,f,h={freebin:-1,shelf:-1,waste:1/0},p=0;if(\"string\"==typeof n||\"number\"==typeof n){if(i=this.getBin(n))return this.ref(i),i;\"number\"==typeof n&&(this.maxId=Math.max(n,this.maxId))}else n=++this.maxId;for(s=0;s<this.freebins.length;s++){if(r===(i=this.freebins[s]).maxh&&t===i.maxw)return this.allocFreebin(s,t,r,n);r>i.maxh||t>i.maxw||r<=i.maxh&&t<=i.maxw&&(o=i.maxw*i.maxh-t*r)<h.waste&&(h.waste=o,h.freebin=s)}for(s=0;s<this.shelves.length;s++)if(p+=(a=this.shelves[s]).h,!(t>a.free)){if(r===a.h)return 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e=t.h;this.stats[e]=1+(0|this.stats[e])}return t.refcount},t.prototype.unref=function(t){return 0===t.refcount?0:(0==--t.refcount&&(this.stats[t.h]--,delete this.bins[t.id],this.freebins.push(t)),t.refcount)},t.prototype.clear=function(){this.shelves=[],this.freebins=[],this.stats={},this.bins={},this.maxId=0},t.prototype.resize=function(t,e){this.w=t,this.h=e;for(var r=0;r<this.shelves.length;r++)this.shelves[r].resize(t);return!0},e.prototype.alloc=function(t,e,r){if(t>this.free||e>this.h)return null;var n=this.x;return this.x+=t,this.free-=t,new function(t,e,r,n,i,a,o){this.id=t,this.x=e,this.y=r,this.w=n,this.h=i,this.maxw=a||n,this.maxh=o||i,this.refcount=0}(r,n,this.y,t,e,t,this.h)},e.prototype.resize=function(t){return this.free+=t-this.w,this.w=t,!0},t}()}),Qa=function(t,e){var r=e.pixelRatio;this.paddedRect=t,this.pixelRatio=r},to={tl:{configurable:!0},br:{configurable:!0},displaySize:{configurable:!0}};to.tl.get=function(){return[this.paddedRect.x+1,this.paddedRect.y+1]},to.br.get=function(){return[this.paddedRect.x+this.paddedRect.w-1,this.paddedRect.y+this.paddedRect.h-1]},to.displaySize.get=function(){return[(this.paddedRect.w-2)/this.pixelRatio,(this.paddedRect.h-2)/this.pixelRatio]},Object.defineProperties(Qa.prototype,to);var eo=function(t){var e=new ui({width:0,height:0}),r={},n=new Ka(0,0,{autoResize:!0});for(var i in t){var a=t[i],o=n.packOne(a.data.width+2,a.data.height+2);e.resize({width:n.w,height:n.h}),ui.copy(a.data,e,{x:0,y:0},{x:o.x+1,y:o.y+1},a.data),r[i]=new Qa(o,a)}n.shrink(),e.resize({width:n.w,height:n.h}),this.image=e,this.positions=r};pr(\"ImagePosition\",Qa),pr(\"ImageAtlas\",eo);var ro=function(t,e,r,n,i){var 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n=this.pos-r;n>=128&&lo(r,n,this),this.pos=r-1,this.writeVarint(n),this.pos+=n},writeMessage:function(t,e,r){this.writeTag(t,ao.Bytes),this.writeRawMessage(e,r)},writePackedVarint:function(t,e){this.writeMessage(t,co,e)},writePackedSVarint:function(t,e){this.writeMessage(t,uo,e)},writePackedBoolean:function(t,e){this.writeMessage(t,po,e)},writePackedFloat:function(t,e){this.writeMessage(t,fo,e)},writePackedDouble:function(t,e){this.writeMessage(t,ho,e)},writePackedFixed32:function(t,e){this.writeMessage(t,go,e)},writePackedSFixed32:function(t,e){this.writeMessage(t,vo,e)},writePackedFixed64:function(t,e){this.writeMessage(t,mo,e)},writePackedSFixed64:function(t,e){this.writeMessage(t,yo,e)},writeBytesField:function(t,e){this.writeTag(t,ao.Bytes),this.writeBytes(e)},writeFixed32Field:function(t,e){this.writeTag(t,ao.Fixed32),this.writeFixed32(e)},writeSFixed32Field:function(t,e){this.writeTag(t,ao.Fixed32),this.writeSFixed32(e)},writeFixed64Field:function(t,e){this.writeTag(t,ao.Fixed64),this.writeFixed64(e)},writeSFixed64Field:function(t,e){this.writeTag(t,ao.Fixed64),this.writeSFixed64(e)},writeVarintField:function(t,e){this.writeTag(t,ao.Varint),this.writeVarint(e)},writeSVarintField:function(t,e){this.writeTag(t,ao.Varint),this.writeSVarint(e)},writeStringField:function(t,e){this.writeTag(t,ao.Bytes),this.writeString(e)},writeFloatField:function(t,e){this.writeTag(t,ao.Fixed32),this.writeFloat(e)},writeDoubleField:function(t,e){this.writeTag(t,ao.Fixed64),this.writeDouble(e)},writeBooleanField:function(t,e){this.writeVarintField(t,Boolean(e))}};var wo=3;function ko(t,e,r){1===t&&r.readMessage(To,e)}function To(t,e,r){if(3===t){var n=r.readMessage(Ao,{}),i=n.id,a=n.bitmap,o=n.width,s=n.height,l=n.left,c=n.top,u=n.advance;e.push({id:i,bitmap:new ci({width:o+2*wo,height:s+2*wo},a),metrics:{width:o,height:s,left:l,top:c,advance:u}})}}function Ao(t,e,r){1===t?e.id=r.readVarint():2===t?e.bitmap=r.readBytes():3===t?e.width=r.readVarint():4===t?e.height=r.readVarint():5===t?e.left=r.readSVarint():6===t?e.top=r.readSVarint():7===t&&(e.advance=r.readVarint())}var Mo=wo,So=function(t,e,r){this.target=t,this.parent=e,this.mapId=r,this.callbacks={},this.callbackID=0,g([\"receive\"],this),this.target.addEventListener(\"message\",this.receive,!1)};So.prototype.send=function(t,e,r,n){var i=r?this.mapId+\":\"+this.callbackID++:null;r&&(this.callbacks[i]=r);var a=[];this.target.postMessage({targetMapId:n,sourceMapId:this.mapId,type:t,id:String(i),data:gr(e,a)},a)},So.prototype.receive=function(t){var e,r=this,n=t.data,i=n.id;if(!n.targetMapId||this.mapId===n.targetMapId){var a=function(t,e){var n=[];r.target.postMessage({sourceMapId:r.mapId,type:\"<response>\",id:String(i),error:t?gr(t):null,data:gr(e,n)},n)};if(\"<response>\"===n.type)e=this.callbacks[n.id],delete this.callbacks[n.id],e&&n.error?e(vr(n.error)):e&&e(null,vr(n.data));else if(void 0!==n.id&&this.parent[n.type])this.parent[n.type](n.sourceMapId,vr(n.data),a);else if(void 0!==n.id&&this.parent.getWorkerSource){var o=n.type.split(\".\");this.parent.getWorkerSource(n.sourceMapId,o[0],o[1])[o[2]](vr(n.data),a)}else this.parent[n.type](vr(n.data))}},So.prototype.remove=function(){this.target.removeEventListener(\"message\",this.receive,!1)};var Eo=n(i(function(t,e){!function(t){function e(t,e,n){var i=r(256*t,256*(e=Math.pow(2,n)-e-1),n),a=r(256*(t+1),256*(e+1),n);return i[0]+\",\"+i[1]+\",\"+a[0]+\",\"+a[1]}function r(t,e,r){var n=2*Math.PI*6378137/256/Math.pow(2,r);return[t*n-2*Math.PI*6378137/2,e*n-2*Math.PI*6378137/2]}t.getURL=function(t,r,n,i,a,o){return o=o||{},t+\"?\"+[\"bbox=\"+e(n,i,a),\"format=\"+(o.format||\"image/png\"),\"service=\"+(o.service||\"WMS\"),\"version=\"+(o.version||\"1.1.1\"),\"request=\"+(o.request||\"GetMap\"),\"srs=\"+(o.srs||\"EPSG:3857\"),\"width=\"+(o.width||256),\"height=\"+(o.height||256),\"layers=\"+r].join(\"&\")},t.getTileBBox=e,t.getMercCoords=r,Object.defineProperty(t,\"__esModule\",{value:!0})}(e)})),Co=function(t,e,r){this.z=t,this.x=e,this.y=r,this.key=Oo(0,t,e,r)};Co.prototype.equals=function(t){return this.z===t.z&&this.x===t.x&&this.y===t.y},Co.prototype.url=function(t,e){var r=Eo.getTileBBox(this.x,this.y,this.z),n=function(t,e,r){for(var n,i=\"\",a=t;a>0;a--)i+=(e&(n=1<<a-1)?1:0)+(r&n?2:0);return i}(this.z,this.x,this.y);return t[(this.x+this.y)%t.length].replace(\"{prefix}\",(this.x%16).toString(16)+(this.y%16).toString(16)).replace(\"{z}\",String(this.z)).replace(\"{x}\",String(this.x)).replace(\"{y}\",String(\"tms\"===e?Math.pow(2,this.z)-this.y-1:this.y)).replace(\"{quadkey}\",n).replace(\"{bbox-epsg-3857}\",r)};var Lo=function(t,e){this.wrap=t,this.canonical=e,this.key=Oo(t,e.z,e.x,e.y)},zo=function(t,e,r,n,i){this.overscaledZ=t,this.wrap=e,this.canonical=new Co(r,+n,+i),this.key=Oo(e,t,n,i)};function Oo(t,e,r,n){(t*=2)<0&&(t=-1*t-1);var i=1<<e;return 32*(i*i*t+i*n+r)+e}zo.prototype.equals=function(t){return this.overscaledZ===t.overscaledZ&&this.wrap===t.wrap&&this.canonical.equals(t.canonical)},zo.prototype.scaledTo=function(t){var e=this.canonical.z-t;return t>this.canonical.z?new zo(t,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new zo(t,this.wrap,t,this.canonical.x>>e,this.canonical.y>>e)},zo.prototype.isChildOf=function(t){var e=this.canonical.z-t.canonical.z;return 0===t.overscaledZ||t.overscaledZ<this.overscaledZ&&t.canonical.x===this.canonical.x>>e&&t.canonical.y===this.canonical.y>>e},zo.prototype.children=function(t){if(this.overscaledZ>=t)return[new zo(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var e=this.canonical.z+1,r=2*this.canonical.x,n=2*this.canonical.y;return[new zo(e,this.wrap,e,r,n),new zo(e,this.wrap,e,r+1,n),new zo(e,this.wrap,e,r,n+1),new zo(e,this.wrap,e,r+1,n+1)]},zo.prototype.isLessThan=function(t){return this.wrap<t.wrap||!(this.wrap>t.wrap)&&(this.overscaledZ<t.overscaledZ||!(this.overscaledZ>t.overscaledZ)&&(this.canonical.x<t.canonical.x||!(this.canonical.x>t.canonical.x)&&this.canonical.y<t.canonical.y))},zo.prototype.wrapped=function(){return new zo(this.overscaledZ,0,this.canonical.z,this.canonical.x,this.canonical.y)},zo.prototype.unwrapTo=function(t){return new zo(this.overscaledZ,t,this.canonical.z,this.canonical.x,this.canonical.y)},zo.prototype.overscaleFactor=function(){return Math.pow(2,this.overscaledZ-this.canonical.z)},zo.prototype.toUnwrapped=function(){return new Lo(this.wrap,this.canonical)},zo.prototype.toString=function(){return this.overscaledZ+\"/\"+this.canonical.x+\"/\"+this.canonical.y},zo.prototype.toCoordinate=function(){return new s(this.canonical.x+Math.pow(2,this.wrap),this.canonical.y,this.canonical.z)},pr(\"CanonicalTileID\",Co),pr(\"OverscaledTileID\",zo,{omit:[\"posMatrix\"]});var Io=function(t,e,r){if(t<=0)throw new RangeError(\"Level must have positive dimension\");this.dim=t,this.border=e,this.stride=this.dim+2*this.border,this.data=r||new Int32Array((this.dim+2*this.border)*(this.dim+2*this.border))};Io.prototype.set=function(t,e,r){this.data[this._idx(t,e)]=r+65536},Io.prototype.get=function(t,e){return this.data[this._idx(t,e)]-65536},Io.prototype._idx=function(t,e){if(t<-this.border||t>=this.dim+this.border||e<-this.border||e>=this.dim+this.border)throw new RangeError(\"out of range source coordinates for DEM data\");return(e+this.border)*this.stride+(t+this.border)},pr(\"Level\",Io);var Do=function(t,e,r){this.uid=t,this.scale=e||1,this.level=r||new Io(256,512),this.loaded=!!r};Do.prototype.loadFromImage=function(t,e){if(t.height!==t.width)throw new RangeError(\"DEM tiles must be square\");if(e&&\"mapbox\"!==e&&\"terrarium\"!==e)return _('\"'+e+'\" is not a valid encoding type. 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Uint8Array(this.level.data.buffer))},Do.prototype.backfillBorder=function(t,e,r){var n=this.level,i=t.level;if(n.dim!==i.dim)throw new Error(\"level mismatch (dem dimension)\");var a=e*n.dim,o=e*n.dim+n.dim,s=r*n.dim,l=r*n.dim+n.dim;switch(e){case-1:a=o-1;break;case 1:o=a+1}switch(r){case-1:s=l-1;break;case 1:l=s+1}for(var c=h(a,-n.border,n.dim+n.border),u=h(o,-n.border,n.dim+n.border),f=h(s,-n.border,n.dim+n.border),p=h(l,-n.border,n.dim+n.border),d=-e*n.dim,g=-r*n.dim,v=f;v<p;v++)for(var m=c;m<u;m++)n.set(m,v,i.get(m+d,v+g))},pr(\"DEMData\",Do);var Po=function(t){this._stringToNumber={},this._numberToString=[];for(var e=0;e<t.length;e++){var r=t[e];this._stringToNumber[r]=e,this._numberToString[e]=r}};Po.prototype.encode=function(t){return this._stringToNumber[t]},Po.prototype.decode=function(t){return this._numberToString[t]};var Ro=function(t,e,r,n){this.type=\"Feature\",this._vectorTileFeature=t,t._z=e,t._x=r,t._y=n,this.properties=t.properties,null!=t.id&&(this.id=t.id)},Fo={geometry:{configurable:!0}};Fo.geometry.get=function(){return void 0===this._geometry&&(this._geometry=this._vectorTileFeature.toGeoJSON(this._vectorTileFeature._x,this._vectorTileFeature._y,this._vectorTileFeature._z).geometry),this._geometry},Fo.geometry.set=function(t){this._geometry=t},Ro.prototype.toJSON=function(){var t={geometry:this.geometry};for(var e in this)\"_geometry\"!==e&&\"_vectorTileFeature\"!==e&&(t[e]=this[e]);return t},Object.defineProperties(Ro.prototype,Fo);var Bo=function(t,e,r){this.tileID=t,this.x=t.canonical.x,this.y=t.canonical.y,this.z=t.canonical.z,this.grid=e||new lr(Pn,16,0),this.featureIndexArray=r||new Tn};function No(t,e){return e-t}Bo.prototype.insert=function(t,e,r,n,i){var a=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(r,n,i);for(var o=0;o<e.length;o++){for(var s=e[o],l=[1/0,1/0,-1/0,-1/0],c=0;c<s.length;c++){var u=s[c];l[0]=Math.min(l[0],u.x),l[1]=Math.min(l[1],u.y),l[2]=Math.max(l[2],u.x),l[3]=Math.max(l[3],u.y)}l[0]<Pn&&l[1]<Pn&&l[2]>=0&&l[3]>=0&&this.grid.insert(a,l[0],l[1],l[2],l[3])}},Bo.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new ga.VectorTile(new io(this.rawTileData)).layers,this.sourceLayerCoder=new Po(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"])),this.vtLayers},Bo.prototype.query=function(t,e){var r=this;this.loadVTLayers();for(var n=t.params||{},i=Pn/t.tileSize/t.scale,a=Re(n.filter),o=t.queryGeometry,s=t.queryPadding*i,l=1/0,c=1/0,u=-1/0,f=-1/0,h=0;h<o.length;h++)for(var p=o[h],d=0;d<p.length;d++){var g=p[d];l=Math.min(l,g.x),c=Math.min(c,g.y),u=Math.max(u,g.x),f=Math.max(f,g.y)}var v=this.grid.query(l-s,c-s,u+s,f+s);v.sort(No);for(var m,y={},x=function(s){var l=v[s];if(l!==m){m=l;var 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m=v-d,y=g-p,x=h.get(\"text-size\").evaluate(o)/24,b=a.left*x,_=a.right*x,w=a.top*x,k=_-b,T=a.bottom*x-w,A=h.get(\"icon-text-fit-padding\")[0],M=h.get(\"icon-text-fit-padding\")[1],S=h.get(\"icon-text-fit-padding\")[2],E=h.get(\"icon-text-fit-padding\")[3],C=\"width\"===h.get(\"icon-text-fit\")?.5*(T-y):0,L=\"height\"===h.get(\"icon-text-fit\")?.5*(k-m):0,z=\"width\"===h.get(\"icon-text-fit\")||\"both\"===h.get(\"icon-text-fit\")?k:m,O=\"height\"===h.get(\"icon-text-fit\")||\"both\"===h.get(\"icon-text-fit\")?T:y;s=new t.default$1(b+L-E,w+C-A),l=new t.default$1(b+L+M+z,w+C-A),c=new t.default$1(b+L+M+z,w+C+S+O),u=new t.default$1(b+L-E,w+C+S+O)}else s=new t.default$1(d,p),l=new t.default$1(v,p),c=new t.default$1(v,g),u=new t.default$1(d,g);var I=n.layout.get(\"icon-rotate\").evaluate(o)*Math.PI/180;if(I){var D=Math.sin(I),P=Math.cos(I),R=[P,-D,D,P];s._matMult(R),l._matMult(R),u._matMult(R),c._matMult(R)}return[{tl:s,tr:l,bl:u,br:c,tex:f.paddedRect,writingMode:void 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r}function Dt(t,e){var r=[];r.size=t.size,void 0!==t.start&&(r.start=t.start,r.end=t.end);for(var n=0;n<t.length;n+=3)r.push(t[n]+e,t[n+1],t[n+2]);return r}function Pt(t,e){if(t.transformed)return t;var r,n,i,a=1<<t.z,o=t.x,s=t.y;for(r=0;r<t.features.length;r++){var l=t.features[r],c=l.geometry,u=l.type;if(l.geometry=[],1===u)for(n=0;n<c.length;n+=2)l.geometry.push(Rt(c[n],c[n+1],e,a,o,s));else for(n=0;n<c.length;n++){var f=[];for(i=0;i<c[n].length;i+=2)f.push(Rt(c[n][i],c[n][i+1],e,a,o,s));l.geometry.push(f)}}return t.transformed=!0,t}function Rt(t,e,r,n,i,a){return[Math.round(r*(t*n-i)),Math.round(r*(e*n-a))]}function Ft(t,e,r,n,i){for(var a=e===i.maxZoom?0:i.tolerance/((1<<e)*i.extent),o={features:[],numPoints:0,numSimplified:0,numFeatures:0,source:null,x:r,y:n,z:e,transformed:!1,minX:2,minY:1,maxX:-1,maxY:0},s=0;s<t.length;s++){o.numFeatures++,Bt(o,t[s],a,i);var l=t[s].minX,c=t[s].minY,u=t[s].maxX,f=t[s].maxY;l<o.minX&&(o.minX=l),c<o.minY&&(o.minY=c),u>o.maxX&&(o.maxX=u),f>o.maxY&&(o.maxY=f)}return o}function Bt(t,e,r,n){var i=e.geometry,a=e.type,o=[];if(\"Point\"===a||\"MultiPoint\"===a)for(var s=0;s<i.length;s+=3)o.push(i[s]),o.push(i[s+1]),t.numPoints++,t.numSimplified++;else if(\"LineString\"===a)Nt(o,i,t,r,!1,!1);else if(\"MultiLineString\"===a||\"Polygon\"===a)for(s=0;s<i.length;s++)Nt(o,i[s],t,r,\"Polygon\"===a,0===s);else if(\"MultiPolygon\"===a)for(var l=0;l<i.length;l++){var c=i[l];for(s=0;s<c.length;s++)Nt(o,c[s],t,r,!0,0===s)}if(o.length){var u=e.tags||null;if(\"LineString\"===a&&n.lineMetrics){for(var f in u={},e.tags)u[f]=e.tags[f];u.mapbox_clip_start=i.start/i.size,u.mapbox_clip_end=i.end/i.size}var h={geometry:o,type:\"Polygon\"===a||\"MultiPolygon\"===a?3:\"LineString\"===a||\"MultiLineString\"===a?2:1,tags:u};null!==e.id&&(h.id=e.id),t.features.push(h)}}function Nt(t,e,r,n,i,a){var o=n*n;if(n>0&&e.size<(i?o:n))r.numPoints+=e.length/3;else{for(var s=[],l=0;l<e.length;l+=3)(0===n||e[l+2]>o)&&(r.numSimplified++,s.push(e[l]),s.push(e[l+1])),r.numPoints++;i&&function(t,e){for(var r=0,n=0,i=t.length,a=i-2;n<i;a=n,n+=2)r+=(t[n]-t[a])*(t[n+1]+t[a+1]);if(r>0===e)for(n=0,i=t.length;n<i/2;n+=2){var o=t[n],s=t[n+1];t[n]=t[i-2-n],t[n+1]=t[i-1-n],t[i-2-n]=o,t[i-1-n]=s}}(s,a),t.push(s)}}function jt(t,e){var r=(e=this.options=function(t,e){for(var r in e)t[r]=e[r];return t}(Object.create(this.options),e)).debug;if(r&&console.time(\"preprocess data\"),e.maxZoom<0||e.maxZoom>24)throw new Error(\"maxZoom should be in the 0-24 range\");var n=function(t,e){var r=[];if(\"FeatureCollection\"===t.type)for(var n=0;n<t.features.length;n++)xt(r,t.features[n],e);else\"Feature\"===t.type?xt(r,t,e):xt(r,{geometry:t},e);return r}(t,e);this.tiles={},this.tileCoords=[],r&&(console.timeEnd(\"preprocess data\"),console.log(\"index: maxZoom: %d, maxPoints: %d\",e.indexMaxZoom,e.indexMaxPoints),console.time(\"generate tiles\"),this.stats={},this.total=0),(n=function(t,e){var r=e.buffer/e.extent,n=t,i=At(t,1,-1-r,r,0,-1,2,e),a=At(t,1,1-r,2+r,0,-1,2,e);return(i||a)&&(n=At(t,1,-r,1+r,0,-1,2,e)||[],i&&(n=It(i,1).concat(n)),a&&(n=n.concat(It(a,-1)))),n}(n,e)).length&&this.splitTile(n,0,0,0),r&&(n.length&&console.log(\"features: %d, points: %d\",this.tiles[0].numFeatures,this.tiles[0].numPoints),console.timeEnd(\"generate tiles\"),console.log(\"tiles generated:\",this.total,JSON.stringify(this.stats)))}function Vt(t,e,r){return 32*((1<<t)*r+e)+t}function Ut(t,e){var r=t.tileID.canonical;if(!this._geoJSONIndex)return e(null,null);var n=this._geoJSONIndex.getTile(r.z,r.x,r.y);if(!n)return e(null,null);var i=new R(n.features),a=V(i);0===a.byteOffset&&a.byteLength===a.buffer.byteLength||(a=new Uint8Array(a)),e(null,{vectorTile:i,rawData:a.buffer})}ot.prototype={options:{minZoom:0,maxZoom:16,radius:40,extent:512,nodeSize:64,log:!1,reduce:null,initial:function(){return{}},map:function(t){return t}},load:function(t){var e=this.options.log;e&&console.time(\"total time\");var r=\"prepare \"+t.length+\" points\";e&&console.time(r),this.points=t;var n=t.map(lt);e&&console.timeEnd(r);for(var i=this.options.maxZoom;i>=this.options.minZoom;i--){var a=+Date.now();this.trees[i+1]=rt(n,dt,gt,this.options.nodeSize,Float32Array),n=this._cluster(n,i),e&&console.log(\"z%d: %d clusters in %dms\",i,n.length,+Date.now()-a)}return this.trees[this.options.minZoom]=rt(n,dt,gt,this.options.nodeSize,Float32Array),e&&console.timeEnd(\"total time\"),this},getClusters:function(t,e){for(var r=this.trees[this._limitZoom(e)],n=r.range(ft(t[0]),ht(t[3]),ft(t[2]),ht(t[1])),i=[],a=0;a<n.length;a++){var o=r.points[n[a]];i.push(o.numPoints?ct(o):this.points[o.id])}return i},getChildren:function(t,e){for(var r=this.trees[e+1].points[t],n=this.options.radius/(this.options.extent*Math.pow(2,e)),i=this.trees[e+1].within(r.x,r.y,n),a=[],o=0;o<i.length;o++){var s=this.trees[e+1].points[i[o]];s.parentId===t&&a.push(s.numPoints?ct(s):this.points[s.id])}return a},getLeaves:function(t,e,r,n){r=r||10,n=n||0;var i=[];return this._appendLeaves(i,t,e,r,n,0),i},getTile:function(t,e,r){var n=this.trees[this._limitZoom(t)],i=Math.pow(2,t),a=this.options.extent,o=this.options.radius/a,s=(r-o)/i,l=(r+1+o)/i,c={features:[]};return this._addTileFeatures(n.range((e-o)/i,s,(e+1+o)/i,l),n.points,e,r,i,c),0===e&&this._addTileFeatures(n.range(1-o/i,s,1,l),n.points,i,r,i,c),e===i-1&&this._addTileFeatures(n.range(0,s,o/i,l),n.points,-1,r,i,c),c.features.length?c:null},getClusterExpansionZoom:function(t,e){for(;e<this.options.maxZoom;){var r=this.getChildren(t,e);if(e++,1!==r.length)break;t=r[0].properties.cluster_id}return e},_appendLeaves:function(t,e,r,n,i,a){for(var o=this.getChildren(e,r),s=0;s<o.length;s++){var l=o[s].properties;if(l.cluster?a+l.point_count<=i?a+=l.point_count:a=this._appendLeaves(t,l.cluster_id,r+1,n,i,a):a<i?a++:t.push(o[s]),t.length===n)break}return a},_addTileFeatures:function(t,e,r,n,i,a){for(var o=0;o<t.length;o++){var s=e[t[o]];a.features.push({type:1,geometry:[[Math.round(this.options.extent*(s.x*i-r)),Math.round(this.options.extent*(s.y*i-n))]],tags:s.numPoints?ut(s):this.points[s.id].properties})}},_limitZoom:function(t){return Math.max(this.options.minZoom,Math.min(t,this.options.maxZoom+1))},_cluster:function(t,e){for(var r=[],n=this.options.radius/(this.options.extent*Math.pow(2,e)),i=0;i<t.length;i++){var a=t[i];if(!(a.zoom<=e)){a.zoom=e;var o=this.trees[e+1],s=o.within(a.x,a.y,n),l=a.numPoints||1,c=a.x*l,u=a.y*l,f=null;this.options.reduce&&(f=this.options.initial(),this._accumulate(f,a));for(var h=0;h<s.length;h++){var p=o.points[s[h]];if(e<p.zoom){var d=p.numPoints||1;p.zoom=e,c+=p.x*d,u+=p.y*d,l+=d,p.parentId=i,this.options.reduce&&this._accumulate(f,p)}}1===l?r.push(a):(a.parentId=i,r.push(st(c/l,u/l,l,i,f)))}}return r},_accumulate:function(t,e){var r=e.numPoints?e.properties:this.options.map(this.points[e.id].properties);this.options.reduce(t,r)}},jt.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,debug:0},jt.prototype.splitTile=function(t,e,r,n,i,a,o){for(var s=[t,e,r,n],l=this.options,c=l.debug;s.length;){n=s.pop(),r=s.pop(),e=s.pop(),t=s.pop();var u=1<<e,f=Vt(e,r,n),h=this.tiles[f];if(!h&&(c>1&&console.time(\"creation\"),h=this.tiles[f]=Ft(t,e,r,n,l),this.tileCoords.push({z:e,x:r,y:n}),c)){c>1&&(console.log(\"tile z%d-%d-%d (features: %d, points: %d, simplified: %d)\",e,r,n,h.numFeatures,h.numPoints,h.numSimplified),console.timeEnd(\"creation\"));var p=\"z\"+e;this.stats[p]=(this.stats[p]||0)+1,this.total++}if(h.source=t,i){if(e===l.maxZoom||e===i)continue;var d=1<<i-e;if(r!==Math.floor(a/d)||n!==Math.floor(o/d))continue}else if(e===l.indexMaxZoom||h.numPoints<=l.indexMaxPoints)continue;if(h.source=null,0!==t.length){c>1&&console.time(\"clipping\");var g,v,m,y,x,b,_=.5*l.buffer/l.extent,w=.5-_,k=.5+_,T=1+_;g=v=m=y=null,x=At(t,u,r-_,r+k,0,h.minX,h.maxX,l),b=At(t,u,r+w,r+T,0,h.minX,h.maxX,l),t=null,x&&(g=At(x,u,n-_,n+k,1,h.minY,h.maxY,l),v=At(x,u,n+w,n+T,1,h.minY,h.maxY,l),x=null),b&&(m=At(b,u,n-_,n+k,1,h.minY,h.maxY,l),y=At(b,u,n+w,n+T,1,h.minY,h.maxY,l),b=null),c>1&&console.timeEnd(\"clipping\"),s.push(g||[],e+1,2*r,2*n),s.push(v||[],e+1,2*r,2*n+1),s.push(m||[],e+1,2*r+1,2*n),s.push(y||[],e+1,2*r+1,2*n+1)}}},jt.prototype.getTile=function(t,e,r){var n=this.options,i=n.extent,a=n.debug;if(t<0||t>24)return null;var o=1<<t,s=Vt(t,e=(e%o+o)%o,r);if(this.tiles[s])return Pt(this.tiles[s],i);a>1&&console.log(\"drilling down to z%d-%d-%d\",t,e,r);for(var l,c=t,u=e,f=r;!l&&c>0;)c--,u=Math.floor(u/2),f=Math.floor(f/2),l=this.tiles[Vt(c,u,f)];return l&&l.source?(a>1&&console.log(\"found parent tile z%d-%d-%d\",c,u,f),a>1&&console.time(\"drilling down\"),this.splitTile(l.source,c,u,f,t,e,r),a>1&&console.timeEnd(\"drilling down\"),this.tiles[s]?Pt(this.tiles[s],i):null):null};var Ht=function(e){function r(t,r,n){e.call(this,t,r,Ut),n&&(this.loadGeoJSON=n)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadData=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),this._pendingCallback=e,this._pendingLoadDataParams=t,this._state&&\"Idle\"!==this._state?this._state=\"NeedsLoadData\":(this._state=\"Coalescing\",this._loadData())},r.prototype._loadData=function(){var t=this;if(this._pendingCallback&&this._pendingLoadDataParams){var e=this._pendingCallback,r=this._pendingLoadDataParams;delete this._pendingCallback,delete this._pendingLoadDataParams,this.loadGeoJSON(r,function(n,i){if(n||!i)return e(n);if(\"object\"!=typeof i)return e(new Error(\"Input data is not a valid GeoJSON object.\"));!function t(e,r){switch(e&&e.type||null){case\"FeatureCollection\":return e.features=e.features.map(z(t,r)),e;case\"Feature\":return e.geometry=t(e.geometry,r),e;case\"Polygon\":case\"MultiPolygon\":return function(t,e){return\"Polygon\"===t.type?t.coordinates=O(t.coordinates,e):\"MultiPolygon\"===t.type&&(t.coordinates=t.coordinates.map(z(O,e))),t}(e,r);default:return e}}(i,!0);try{t._geoJSONIndex=r.cluster?function(t){return new ot(t)}(r.superclusterOptions).load(i.features):new jt(i,r.geojsonVtOptions)}catch(n){return e(n)}t.loaded={};var a={};if(r.request&&r.request.collectResourceTiming){var o=w(r.request.url);o&&(a.resourceTiming={},a.resourceTiming[r.source]=JSON.parse(JSON.stringify(o)))}e(null,a)})}},r.prototype.coalesce=function(){\"Coalescing\"===this._state?this._state=\"Idle\":\"NeedsLoadData\"===this._state&&(this._state=\"Coalescing\",this._loadData())},r.prototype.reloadTile=function(t,r){var n=this.loaded,i=t.uid;return n&&n[i]?e.prototype.reloadTile.call(this,t,r):this.loadTile(t,r)},r.prototype.loadGeoJSON=function(e,r){if(e.request)t.getJSON(e.request,r);else{if(\"string\"!=typeof e.data)return r(new Error(\"Input data is not a valid GeoJSON object.\"));try{return r(null,JSON.parse(e.data))}catch(t){return r(new Error(\"Input data is not a valid GeoJSON object.\"))}}},r.prototype.removeSource=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),e()},r}(T),qt=function(e){var r=this;this.self=e,this.actor=new t.default$7(e,this),this.layerIndexes={},this.workerSourceTypes={vector:T,geojson:Ht},this.workerSources={},this.demWorkerSources={},this.self.registerWorkerSource=function(t,e){if(r.workerSourceTypes[t])throw new Error('Worker source with name \"'+t+'\" already registered.');r.workerSourceTypes[t]=e},this.self.registerRTLTextPlugin=function(e){if(t.plugin.isLoaded())throw new Error(\"RTL text plugin already 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qt.prototype.setLayers=function(t,e,r){this.getLayerIndex(t).replace(e),r()},qt.prototype.updateLayers=function(t,e,r){this.getLayerIndex(t).update(e.layers,e.removedIds),r()},qt.prototype.loadTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).loadTile(e,r)},qt.prototype.loadDEMTile=function(t,e,r){this.getDEMWorkerSource(t,e.source).loadTile(e,r)},qt.prototype.reloadTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).reloadTile(e,r)},qt.prototype.abortTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).abortTile(e,r)},qt.prototype.removeTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).removeTile(e,r)},qt.prototype.removeDEMTile=function(t,e){this.getDEMWorkerSource(t,e.source).removeTile(e)},qt.prototype.removeSource=function(t,e,r){if(this.workerSources[t]&&this.workerSources[t][e.type]&&this.workerSources[t][e.type][e.source]){var n=this.workerSources[t][e.type][e.source];delete this.workerSources[t][e.type][e.source],void 0!==n.removeSource?n.removeSource(e,r):r()}},qt.prototype.loadWorkerSource=function(t,e,r){try{this.self.importScripts(e.url),r()}catch(t){r(t.toString())}},qt.prototype.loadRTLTextPlugin=function(e,r,n){try{t.plugin.isLoaded()||(this.self.importScripts(r),n(t.plugin.isLoaded()?null:new Error(\"RTL Text Plugin failed to import scripts from \"+r)))}catch(t){n(t.toString())}},qt.prototype.getLayerIndex=function(t){var e=this.layerIndexes[t];return e||(e=this.layerIndexes[t]=new n),e},qt.prototype.getWorkerSource=function(t,e,r){var n=this;if(this.workerSources[t]||(this.workerSources[t]={}),this.workerSources[t][e]||(this.workerSources[t][e]={}),!this.workerSources[t][e][r]){var i={send:function(e,r,i){n.actor.send(e,r,i,t)}};this.workerSources[t][e][r]=new this.workerSourceTypes[e](i,this.getLayerIndex(t))}return this.workerSources[t][e][r]},qt.prototype.getDEMWorkerSource=function(t,e){return this.demWorkerSources[t]||(this.demWorkerSources[t]={}),this.demWorkerSources[t][e]||(this.demWorkerSources[t][e]=new A),this.demWorkerSources[t][e]},\"undefined\"!=typeof WorkerGlobalScope&&\"undefined\"!=typeof self&&self instanceof WorkerGlobalScope&&new qt(self),qt}),i(0,function(t){var e=t.createCommonjsModule(function(t){function e(t){return!!(\"undefined\"!=typeof window&&\"undefined\"!=typeof document&&Array.prototype&&Array.prototype.every&&Array.prototype.filter&&Array.prototype.forEach&&Array.prototype.indexOf&&Array.prototype.lastIndexOf&&Array.prototype.map&&Array.prototype.some&&Array.prototype.reduce&&Array.prototype.reduceRight&&Array.isArray&&Function.prototype&&Function.prototype.bind&&Object.keys&&Object.create&&Object.getPrototypeOf&&Object.getOwnPropertyNames&&Object.isSealed&&Object.isFrozen&&Object.isExtensible&&Object.getOwnPropertyDescriptor&&Object.defineProperty&&Object.defineProperties&&Object.seal&&Object.freeze&&Object.preventExtensions&&\"JSON\"in 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r={};e.webGLContextAttributes={antialias:!1,alpha:!0,stencil:!0,depth:!0}}),r=t.default.performance&&t.default.performance.now?t.default.performance.now.bind(t.default.performance):Date.now.bind(Date),n=t.default.requestAnimationFrame||t.default.mozRequestAnimationFrame||t.default.webkitRequestAnimationFrame||t.default.msRequestAnimationFrame,i=t.default.cancelAnimationFrame||t.default.mozCancelAnimationFrame||t.default.webkitCancelAnimationFrame||t.default.msCancelAnimationFrame,a={now:r,frame:function(t){return n(t)},cancelFrame:function(t){return i(t)},getImageData:function(e){var r=t.default.document.createElement(\"canvas\"),n=r.getContext(\"2d\");if(!n)throw new Error(\"failed to create canvas 2d context\");return r.width=e.width,r.height=e.height,n.drawImage(e,0,0,e.width,e.height),n.getImageData(0,0,e.width,e.height)},hardwareConcurrency:t.default.navigator.hardwareConcurrency||4,get devicePixelRatio(){return 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t.protocol+\"://\"+t.authority+t.path+e}var S=t.default.HTMLImageElement,E=t.default.HTMLCanvasElement,C=t.default.HTMLVideoElement,L=t.default.ImageData,z=function(t,e,r,n){this.context=t,this.format=r,this.texture=t.gl.createTexture(),this.update(e,n)};z.prototype.update=function(t,e){var r=t.width,n=t.height,i=!this.size||this.size[0]!==r||this.size[1]!==n,a=this.context,o=a.gl;this.useMipmap=Boolean(e&&e.useMipmap),o.bindTexture(o.TEXTURE_2D,this.texture),i?(this.size=[r,n],a.pixelStoreUnpack.set(1),this.format!==o.RGBA||e&&!1===e.premultiply||a.pixelStoreUnpackPremultiplyAlpha.set(!0),t instanceof S||t instanceof E||t instanceof C||t instanceof L?o.texImage2D(o.TEXTURE_2D,0,this.format,this.format,o.UNSIGNED_BYTE,t):o.texImage2D(o.TEXTURE_2D,0,this.format,r,n,0,this.format,o.UNSIGNED_BYTE,t.data)):t instanceof S||t instanceof E||t instanceof C||t instanceof L?o.texSubImage2D(o.TEXTURE_2D,0,0,0,o.RGBA,o.UNSIGNED_BYTE,t):o.texSubImage2D(o.TEXTURE_2D,0,0,0,r,n,o.RGBA,o.UNSIGNED_BYTE,t.data),this.useMipmap&&this.isSizePowerOfTwo()&&o.generateMipmap(o.TEXTURE_2D)},z.prototype.bind=function(t,e,r){var n=this.context.gl;n.bindTexture(n.TEXTURE_2D,this.texture),r!==n.LINEAR_MIPMAP_NEAREST||this.isSizePowerOfTwo()||(r=n.LINEAR),t!==this.filter&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,t),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,r||t),this.filter=t),e!==this.wrap&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,e),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,e),this.wrap=e)},z.prototype.isSizePowerOfTwo=function(){return this.size[0]===this.size[1]&&Math.log(this.size[0])/Math.LN2%1==0},z.prototype.destroy=function(){this.context.gl.deleteTexture(this.texture),this.texture=null};var O=function(){this.images={},this.loaded=!1,this.requestors=[],this.shelfPack=new t.default$2(64,64,{autoResize:!0}),this.patterns={},this.atlasImage=new t.RGBAImage({width:64,height:64}),this.dirty=!0};O.prototype.isLoaded=function(){return this.loaded},O.prototype.setLoaded=function(t){if(this.loaded!==t&&(this.loaded=t,t)){for(var e=0,r=this.requestors;e<r.length;e+=1){var n=r[e],i=n.ids,a=n.callback;this._notify(i,a)}this.requestors=[]}},O.prototype.getImage=function(t){return this.images[t]},O.prototype.addImage=function(t,e){this.images[t]=e},O.prototype.removeImage=function(t){delete this.images[t];var e=this.patterns[t];e&&(this.shelfPack.unref(e.bin),delete this.patterns[t])},O.prototype.getImages=function(t,e){var r=!0;if(!this.isLoaded())for(var n=0,i=t;n<i.length;n+=1){var a=i[n];this.images[a]||(r=!1)}this.isLoaded()||r?this._notify(t,e):this.requestors.push({ids:t,callback:e})},O.prototype._notify=function(t,e){for(var r={},n=0,i=t;n<i.length;n+=1){var a=i[n],o=this.images[a];o&&(r[a]={data:o.data.clone(),pixelRatio:o.pixelRatio,sdf:o.sdf})}e(null,r)},O.prototype.getPixelSize=function(){return{width:this.shelfPack.w,height:this.shelfPack.h}},O.prototype.getPattern=function(e){var r=this.patterns[e];if(r)return r.position;var n=this.getImage(e);if(!n)return null;var i=n.data.width+2,a=n.data.height+2,o=this.shelfPack.packOne(i,a);if(!o)return null;this.atlasImage.resize(this.getPixelSize());var s=n.data,l=this.atlasImage,c=o.x+1,u=o.y+1,f=s.width,h=s.height;t.RGBAImage.copy(s,l,{x:0,y:0},{x:c,y:u},{width:f,height:h}),t.RGBAImage.copy(s,l,{x:0,y:h-1},{x:c,y:u-1},{width:f,height:1}),t.RGBAImage.copy(s,l,{x:0,y:0},{x:c,y:u+h},{width:f,height:1}),t.RGBAImage.copy(s,l,{x:f-1,y:0},{x:c-1,y:u},{width:1,height:h}),t.RGBAImage.copy(s,l,{x:0,y:0},{x:c+f,y:u},{width:1,height:h}),this.dirty=!0;var p=new t.ImagePosition(o,n);return this.patterns[e]={bin:o,position:p},p},O.prototype.bind=function(t){var e=t.gl;this.atlasTexture?this.dirty&&(this.atlasTexture.update(this.atlasImage),this.dirty=!1):this.atlasTexture=new z(t,this.atlasImage,e.RGBA),this.atlasTexture.bind(e.LINEAR,e.CLAMP_TO_EDGE)};var I=P,D=1e20;function P(t,e,r,n,i,a){this.fontSize=t||24,this.buffer=void 0===e?3:e,this.cutoff=n||.25,this.fontFamily=i||\"sans-serif\",this.fontWeight=a||\"normal\",this.radius=r||8;var o=this.size=this.fontSize+2*this.buffer;this.canvas=document.createElement(\"canvas\"),this.canvas.width=this.canvas.height=o,this.ctx=this.canvas.getContext(\"2d\"),this.ctx.font=this.fontWeight+\" \"+this.fontSize+\"px \"+this.fontFamily,this.ctx.textBaseline=\"middle\",this.ctx.fillStyle=\"black\",this.gridOuter=new Float64Array(o*o),this.gridInner=new Float64Array(o*o),this.f=new Float64Array(o),this.d=new Float64Array(o),this.z=new Float64Array(o+1),this.v=new Int16Array(o),this.middle=Math.round(o/2*(navigator.userAgent.indexOf(\"Gecko/\")>=0?1.2:1))}function R(t,e,r,n,i,a,o){for(var s=0;s<e;s++){for(var l=0;l<r;l++)n[l]=t[l*e+s];for(F(n,i,a,o,r),l=0;l<r;l++)t[l*e+s]=i[l]}for(l=0;l<r;l++){for(s=0;s<e;s++)n[s]=t[l*e+s];for(F(n,i,a,o,e),s=0;s<e;s++)t[l*e+s]=Math.sqrt(i[s])}}function F(t,e,r,n,i){r[0]=0,n[0]=-D,n[1]=+D;for(var a=1,o=0;a<i;a++){for(var s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);s<=n[o];)o--,s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);r[++o]=a,n[o]=s,n[o+1]=+D}for(a=0,o=0;a<i;a++){for(;n[o+1]<a;)o++;e[a]=(a-r[o])*(a-r[o])+t[r[o]]}}P.prototype.draw=function(t){this.ctx.clearRect(0,0,this.size,this.size),this.ctx.fillText(t,this.buffer,this.middle);for(var e=this.ctx.getImageData(0,0,this.size,this.size),r=new Uint8ClampedArray(this.size*this.size),n=0;n<this.size*this.size;n++){var i=e.data[4*n+3]/255;this.gridOuter[n]=1===i?0:0===i?D:Math.pow(Math.max(0,.5-i),2),this.gridInner[n]=1===i?D:0===i?0:Math.pow(Math.max(0,i-.5),2)}for(R(this.gridOuter,this.size,this.size,this.f,this.d,this.v,this.z),R(this.gridInner,this.size,this.size,this.f,this.d,this.v,this.z),n=0;n<this.size*this.size;n++){var a=this.gridOuter[n]-this.gridInner[n];r[n]=Math.max(0,Math.min(255,Math.round(255-255*(a/this.radius+this.cutoff))))}return r};var B=function(t,e){this.requestTransform=t,this.localIdeographFontFamily=e,this.entries={}};B.prototype.setURL=function(t){this.url=t},B.prototype.getGlyphs=function(e,r){var n=this,i=[];for(var a in e)for(var o=0,s=e[a];o<s.length;o+=1){var l=s[o];i.push({stack:a,id:l})}t.asyncAll(i,function(t,e){var r=t.stack,i=t.id,a=n.entries[r];a||(a=n.entries[r]={glyphs:{},requests:{}});var o=a.glyphs[i];if(void 0===o)if(o=n._tinySDF(a,r,i))e(null,{stack:r,id:i,glyph:o});else{var s=Math.floor(i/256);if(256*s>65535)e(new Error(\"glyphs > 65535 not supported\"));else{var l=a.requests[s];l||(l=a.requests[s]=[],B.loadGlyphRange(r,s,n.url,n.requestTransform,function(t,e){if(e)for(var r in e)a.glyphs[+r]=e[+r];for(var n=0,i=l;n<i.length;n+=1)(0,i[n])(t,e);delete a.requests[s]})),l.push(function(t,n){t?e(t):n&&e(null,{stack:r,id:i,glyph:n[i]||null})})}}else e(null,{stack:r,id:i,glyph:o})},function(t,e){if(t)r(t);else if(e){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i],s=o.stack,l=o.id,c=o.glyph;(n[s]||(n[s]={}))[l]=c&&{id:c.id,bitmap:c.bitmap.clone(),metrics:c.metrics}}r(null,n)}})},B.prototype._tinySDF=function(e,r,n){var i=this.localIdeographFontFamily;if(i&&(t.default$4[\"CJK Unified Ideographs\"](n)||t.default$4[\"Hangul Syllables\"](n))){var a=e.tinySDF;if(!a){var o=\"400\";/bold/i.test(r)?o=\"900\":/medium/i.test(r)?o=\"500\":/light/i.test(r)&&(o=\"200\"),a=e.tinySDF=new B.TinySDF(24,3,8,.25,i,o)}return{id:n,bitmap:new t.AlphaImage({width:30,height:30},a.draw(String.fromCharCode(n))),metrics:{width:24,height:24,left:0,top:-8,advance:24}}}},B.loadGlyphRange=function(e,r,n,i,a){var o=256*r,s=o+255,l=i(function(t,e){if(!x(t))return t;var r=A(t);return r.path=\"/fonts/v1\"+r.path,y(r,e)}(n).replace(\"{fontstack}\",e).replace(\"{range}\",o+\"-\"+s),t.ResourceType.Glyphs);t.getArrayBuffer(l,function(e,r){if(e)a(e);else if(r){for(var n={},i=0,o=t.default$3(r.data);i<o.length;i+=1){var s=o[i];n[s.id]=s}a(null,n)}})},B.TinySDF=I;var N=function(){this.specification=t.default$5.light.position};N.prototype.possiblyEvaluate=function(e,r){return t.sphericalToCartesian(e.expression.evaluate(r))},N.prototype.interpolate=function(e,r,n){return{x:t.number(e.x,r.x,n),y:t.number(e.y,r.y,n),z:t.number(e.z,r.z,n)}};var j=new t.Properties({anchor:new t.DataConstantProperty(t.default$5.light.anchor),position:new N,color:new t.DataConstantProperty(t.default$5.light.color),intensity:new t.DataConstantProperty(t.default$5.light.intensity)}),V=function(e){function r(r){e.call(this),this._transitionable=new t.Transitionable(j),this.setLight(r),this._transitioning=this._transitionable.untransitioned()}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getLight=function(){return this._transitionable.serialize()},r.prototype.setLight=function(e){if(!this._validate(t.validateLight,e))for(var r in e){var n=e[r];t.endsWith(r,\"-transition\")?this._transitionable.setTransition(r.slice(0,-\"-transition\".length),n):this._transitionable.setValue(r,n)}},r.prototype.updateTransitions=function(t){this._transitioning=this._transitionable.transitioned(t,this._transitioning)},r.prototype.hasTransition=function(){return this._transitioning.hasTransition()},r.prototype.recalculate=function(t){this.properties=this._transitioning.possiblyEvaluate(t)},r.prototype._validate=function(e,r){return t.emitValidationErrors(this,e.call(t.validateStyle,t.extend({value:r,style:{glyphs:!0,sprite:!0},styleSpec:t.default$5})))},r}(t.Evented),U=function(t,e){this.width=t,this.height=e,this.nextRow=0,this.bytes=4,this.data=new Uint8Array(this.width*this.height*this.bytes),this.positions={}};U.prototype.getDash=function(t,e){var r=t.join(\",\")+String(e);return this.positions[r]||(this.positions[r]=this.addDash(t,e)),this.positions[r]},U.prototype.addDash=function(e,r){var n=r?7:0,i=2*n+1;if(this.nextRow+i>this.height)return t.warnOnce(\"LineAtlas out of space\"),null;for(var a=0,o=0;o<e.length;o++)a+=e[o];for(var s=this.width/a,l=s/2,c=e.length%2==1,u=-n;u<=n;u++)for(var f=this.nextRow+n+u,h=this.width*f,p=c?-e[e.length-1]:0,d=e[0],g=1,v=0;v<this.width;v++){for(;d<v/s;)p=d,d+=e[g],c&&g===e.length-1&&(d+=e[0]),g++;var m=Math.abs(v-p*s),y=Math.abs(v-d*s),x=Math.min(m,y),b=g%2==1,_=void 0;if(r){var w=n?u/n*(l+1):0;if(b){var k=l-Math.abs(w);_=Math.sqrt(x*x+k*k)}else _=l-Math.sqrt(x*x+w*w)}else _=(b?1:-1)*x;this.data[3+4*(h+v)]=Math.max(0,Math.min(255,_+128))}var T={y:(this.nextRow+n+.5)/this.height,height:2*n/this.height,width:a};return this.nextRow+=i,this.dirty=!0,T},U.prototype.bind=function(t){var e=t.gl;this.texture?(e.bindTexture(e.TEXTURE_2D,this.texture),this.dirty&&(this.dirty=!1,e.texSubImage2D(e.TEXTURE_2D,0,0,0,this.width,this.height,e.RGBA,e.UNSIGNED_BYTE,this.data))):(this.texture=e.createTexture(),e.bindTexture(e.TEXTURE_2D,this.texture),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_S,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_T,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,e.LINEAR),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,e.LINEAR),e.texImage2D(e.TEXTURE_2D,0,e.RGBA,this.width,this.height,0,e.RGBA,e.UNSIGNED_BYTE,this.data))};var H=function e(r,n){this.workerPool=r,this.actors=[],this.currentActor=0,this.id=t.uniqueId();for(var i=this.workerPool.acquire(this.id),a=0;a<i.length;a++){var o=i[a],s=new e.Actor(o,n,this.id);s.name=\"Worker \"+a,this.actors.push(s)}};function q(e,r,n){var i=function(e,r){if(e)return n(e);if(r){var i=t.pick(r,[\"tiles\",\"minzoom\",\"maxzoom\",\"attribution\",\"mapbox_logo\",\"bounds\"]);r.vector_layers&&(i.vectorLayers=r.vector_layers,i.vectorLayerIds=i.vectorLayers.map(function(t){return t.id})),n(null,i)}};e.url?t.getJSON(r(b(e.url),t.ResourceType.Source),i):a.frame(function(){return i(null,e)})}H.prototype.broadcast=function(e,r,n){n=n||function(){},t.asyncAll(this.actors,function(t,n){t.send(e,r,n)},n)},H.prototype.send=function(t,e,r,n){return(\"number\"!=typeof n||isNaN(n))&&(n=this.currentActor=(this.currentActor+1)%this.actors.length),this.actors[n].send(t,e,r),n},H.prototype.remove=function(){this.actors.forEach(function(t){t.remove()}),this.actors=[],this.workerPool.release(this.id)},H.Actor=t.default$7;var G=function(t,e){if(isNaN(t)||isNaN(e))throw new Error(\"Invalid LngLat object: (\"+t+\", \"+e+\")\");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error(\"Invalid LngLat latitude value: must be between -90 and 90\")};G.prototype.wrap=function(){return new G(t.wrap(this.lng,-180,180),this.lat)},G.prototype.toArray=function(){return[this.lng,this.lat]},G.prototype.toString=function(){return\"LngLat(\"+this.lng+\", \"+this.lat+\")\"},G.prototype.toBounds=function(t){var e=360*t/40075017,r=e/Math.cos(Math.PI/180*this.lat);return new Y(new G(this.lng-r,this.lat-e),new G(this.lng+r,this.lat+e))},G.convert=function(t){if(t instanceof G)return t;if(Array.isArray(t)&&(2===t.length||3===t.length))return new G(Number(t[0]),Number(t[1]));if(!Array.isArray(t)&&\"object\"==typeof t&&null!==t)return new G(Number(t.lng),Number(t.lat));throw new Error(\"`LngLatLike` argument must be specified as a LngLat instance, an object {lng: <lng>, lat: <lat>}, or an array of [<lng>, <lat>]\")};var Y=function(t,e){t&&(e?this.setSouthWest(t).setNorthEast(e):4===t.length?this.setSouthWest([t[0],t[1]]).setNorthEast([t[2],t[3]]):this.setSouthWest(t[0]).setNorthEast(t[1]))};Y.prototype.setNorthEast=function(t){return this._ne=t instanceof G?new G(t.lng,t.lat):G.convert(t),this},Y.prototype.setSouthWest=function(t){return this._sw=t instanceof G?new G(t.lng,t.lat):G.convert(t),this},Y.prototype.extend=function(t){var e,r,n=this._sw,i=this._ne;if(t instanceof G)e=t,r=t;else{if(!(t instanceof Y))return Array.isArray(t)?t.every(Array.isArray)?this.extend(Y.convert(t)):this.extend(G.convert(t)):this;if(e=t._sw,r=t._ne,!e||!r)return this}return n||i?(n.lng=Math.min(e.lng,n.lng),n.lat=Math.min(e.lat,n.lat),i.lng=Math.max(r.lng,i.lng),i.lat=Math.max(r.lat,i.lat)):(this._sw=new G(e.lng,e.lat),this._ne=new G(r.lng,r.lat)),this},Y.prototype.getCenter=function(){return new G((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},Y.prototype.getSouthWest=function(){return this._sw},Y.prototype.getNorthEast=function(){return this._ne},Y.prototype.getNorthWest=function(){return new G(this.getWest(),this.getNorth())},Y.prototype.getSouthEast=function(){return new G(this.getEast(),this.getSouth())},Y.prototype.getWest=function(){return this._sw.lng},Y.prototype.getSouth=function(){return this._sw.lat},Y.prototype.getEast=function(){return this._ne.lng},Y.prototype.getNorth=function(){return this._ne.lat},Y.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},Y.prototype.toString=function(){return\"LngLatBounds(\"+this._sw.toString()+\", \"+this._ne.toString()+\")\"},Y.prototype.isEmpty=function(){return!(this._sw&&this._ne)},Y.convert=function(t){return!t||t instanceof Y?t:new Y(t)};var W=function(t,e,r){this.bounds=Y.convert(this.validateBounds(t)),this.minzoom=e||0,this.maxzoom=r||24};W.prototype.validateBounds=function(t){return Array.isArray(t)&&4===t.length?[Math.max(-180,t[0]),Math.max(-90,t[1]),Math.min(180,t[2]),Math.min(90,t[3])]:[-180,-90,180,90]},W.prototype.contains=function(t){var e=Math.floor(this.lngX(this.bounds.getWest(),t.z)),r=Math.floor(this.latY(this.bounds.getNorth(),t.z)),n=Math.ceil(this.lngX(this.bounds.getEast(),t.z)),i=Math.ceil(this.latY(this.bounds.getSouth(),t.z));return t.x>=e&&t.x<n&&t.y>=r&&t.y<i},W.prototype.lngX=function(t,e){return(t+180)*(Math.pow(2,e)/360)},W.prototype.latY=function(e,r){var n=t.clamp(Math.sin(Math.PI/180*e),-.9999,.9999),i=Math.pow(2,r)/(2*Math.PI);return Math.pow(2,r-1)+.5*Math.log((1+n)/(1-n))*-i};var X=function(e){function r(r,n,i,a){if(e.call(this),this.id=r,this.dispatcher=i,this.type=\"vector\",this.minzoom=0,this.maxzoom=22,this.scheme=\"xyz\",this.tileSize=512,this.reparseOverscaled=!0,this.isTileClipped=!0,t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\"])),this._options=t.extend({type:\"vector\"},n),this._collectResourceTiming=n.collectResourceTiming,512!==this.tileSize)throw new Error(\"vector tile sources must have a tileSize of 512\");this.setEventedParent(a)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),q(this._options,this.map._transformRequest,function(r,n){r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new W(n.bounds,e.minzoom,e.maxzoom)),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))})},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.loadTile=function(e,r){var n=k(e.tileID.canonical.url(this.tiles,this.scheme),this.url),i={request:this.map._transformRequest(n,t.ResourceType.Tile),uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,tileSize:this.tileSize*e.tileID.overscaleFactor(),type:this.type,source:this.id,pixelRatio:a.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes};function o(t,n){return e.aborted?r(null):t?r(t):(n&&n.resourceTiming&&(e.resourceTiming=n.resourceTiming),this.map._refreshExpiredTiles&&e.setExpiryData(n),e.loadVectorData(n,this.map.painter),r(null),void(e.reloadCallback&&(this.loadTile(e,e.reloadCallback),e.reloadCallback=null)))}i.request.collectResourceTiming=this._collectResourceTiming,void 0===e.workerID||\"expired\"===e.state?e.workerID=this.dispatcher.send(\"loadTile\",i,o.bind(this)):\"loading\"===e.state?e.reloadCallback=r:this.dispatcher.send(\"reloadTile\",i,o.bind(this),e.workerID)},r.prototype.abortTile=function(t){this.dispatcher.send(\"abortTile\",{uid:t.uid,type:this.type,source:this.id},void 0,t.workerID)},r.prototype.unloadTile=function(t){t.unloadVectorData(),this.dispatcher.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id},void 0,t.workerID)},r.prototype.hasTransition=function(){return!1},r}(t.Evented),Z=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.dispatcher=i,this.setEventedParent(a),this.type=\"raster\",this.minzoom=0,this.maxzoom=22,this.roundZoom=!0,this.scheme=\"xyz\",this.tileSize=512,this._loaded=!1,this._options=t.extend({},n),t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\"]))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),q(this._options,this.map._transformRequest,function(r,n){r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new W(n.bounds,e.minzoom,e.maxzoom)),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))})},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.loadTile=function(e,r){var n=this,i=k(e.tileID.canonical.url(this.tiles,this.scheme),this.url,this.tileSize);e.request=t.getImage(this.map._transformRequest(i,t.ResourceType.Tile),function(t,i){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(t)e.state=\"errored\",r(t);else if(i){n.map._refreshExpiredTiles&&e.setExpiryData(i),delete i.cacheControl,delete i.expires;var a=n.map.painter.context,o=a.gl;e.texture=n.map.painter.getTileTexture(i.width),e.texture?e.texture.update(i,{useMipmap:!0}):(e.texture=new z(a,i,o.RGBA,{useMipmap:!0}),e.texture.bind(o.LINEAR,o.CLAMP_TO_EDGE,o.LINEAR_MIPMAP_NEAREST),a.extTextureFilterAnisotropic&&o.texParameterf(o.TEXTURE_2D,a.extTextureFilterAnisotropic.TEXTURE_MAX_ANISOTROPY_EXT,a.extTextureFilterAnisotropicMax)),e.state=\"loaded\",r(null)}})},r.prototype.abortTile=function(t,e){t.request&&(t.request.abort(),delete t.request),e()},r.prototype.unloadTile=function(t,e){t.texture&&this.map.painter.saveTileTexture(t.texture),e()},r.prototype.hasTransition=function(){return!1},r}(t.Evented),$=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),this.type=\"raster-dem\",this.maxzoom=22,this._options=t.extend({},n),this.encoding=n.encoding||\"mapbox\"}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.serialize=function(){return{type:\"raster-dem\",url:this.url,tileSize:this.tileSize,tiles:this.tiles,bounds:this.bounds,encoding:this.encoding}},r.prototype.loadTile=function(e,r){var n=k(e.tileID.canonical.url(this.tiles,this.scheme),this.url,this.tileSize);e.request=t.getImage(this.map._transformRequest(n,t.ResourceType.Tile),function(t,n){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(t)e.state=\"errored\",r(t);else if(n){this.map._refreshExpiredTiles&&e.setExpiryData(n),delete n.cacheControl,delete n.expires;var i=a.getImageData(n),o={uid:e.uid,coord:e.tileID,source:this.id,rawImageData:i,encoding:this.encoding};e.workerID&&\"expired\"!==e.state||(e.workerID=this.dispatcher.send(\"loadDEMTile\",o,function(t,n){t&&(e.state=\"errored\",r(t)),n&&(e.dem=n,e.needsHillshadePrepare=!0,e.state=\"loaded\",r(null))}.bind(this)))}}.bind(this)),e.neighboringTiles=this._getNeighboringTiles(e.tileID)},r.prototype._getNeighboringTiles=function(e){var r=e.canonical,n=Math.pow(2,r.z),i=(r.x-1+n)%n,a=0===r.x?e.wrap-1:e.wrap,o=(r.x+1+n)%n,s=r.x+1===n?e.wrap+1:e.wrap,l={};return l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y).key]={backfilled:!1},r.y>0&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y-1).key]={backfilled:!1}),r.y+1<n&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y+1).key]={backfilled:!1}),l},r.prototype.unloadTile=function(t){t.demTexture&&this.map.painter.saveTileTexture(t.demTexture),t.fbo&&(t.fbo.destroy(),delete t.fbo),t.dem&&delete t.dem,delete t.neighboringTiles,t.state=\"unloaded\",this.dispatcher.send(\"removeDEMTile\",{uid:t.uid,source:this.id},void 0,t.workerID)},r}(Z),J=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.type=\"geojson\",this.minzoom=0,this.maxzoom=18,this.tileSize=512,this.isTileClipped=!0,this.reparseOverscaled=!0,this._removed=!1,this.dispatcher=i,this.setEventedParent(a),this._data=n.data,this._options=t.extend({},n),this._collectResourceTiming=n.collectResourceTiming,this._resourceTiming=[],void 0!==n.maxzoom&&(this.maxzoom=n.maxzoom),n.type&&(this.type=n.type);var o=t.default$8/this.tileSize;this.workerOptions=t.extend({source:this.id,cluster:n.cluster||!1,geojsonVtOptions:{buffer:(void 0!==n.buffer?n.buffer:128)*o,tolerance:(void 0!==n.tolerance?n.tolerance:.375)*o,extent:t.default$8,maxZoom:this.maxzoom,lineMetrics:n.lineMetrics||!1},superclusterOptions:{maxZoom:void 0!==n.clusterMaxZoom?Math.min(n.clusterMaxZoom,this.maxzoom-1):this.maxzoom-1,extent:t.default$8,radius:(n.clusterRadius||50)*o,log:!1}},n.workerOptions)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData(function(r){if(r)e.fire(new t.ErrorEvent(r));else{var n={dataType:\"source\",sourceDataType:\"metadata\"};e._collectResourceTiming&&e._resourceTiming&&e._resourceTiming.length>0&&(n.resourceTiming=e._resourceTiming,e._resourceTiming=[]),e.fire(new t.Event(\"data\",n))}})},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setData=function(e){var r=this;return this._data=e,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData(function(e){if(e)return r.fire(new t.ErrorEvent(e));var n={dataType:\"source\",sourceDataType:\"content\"};r._collectResourceTiming&&r._resourceTiming&&r._resourceTiming.length>0&&(n.resourceTiming=r._resourceTiming,r._resourceTiming=[]),r.fire(new t.Event(\"data\",n))}),this},r.prototype._updateWorkerData=function(e){var r,n,i=this,a=t.extend({},this.workerOptions),o=this._data;\"string\"==typeof o?(a.request=this.map._transformRequest((r=o,(n=t.default.document.createElement(\"a\")).href=r,n.href),t.ResourceType.Source),a.request.collectResourceTiming=this._collectResourceTiming):a.data=JSON.stringify(o),this.workerID=this.dispatcher.send(this.type+\".\"+a.source+\".loadData\",a,function(t,r){i._removed||r&&r.abandoned||(i._loaded=!0,r&&r.resourceTiming&&r.resourceTiming[i.id]&&(i._resourceTiming=r.resourceTiming[i.id].slice(0)),i.dispatcher.send(i.type+\".\"+a.source+\".coalesce\",null,null,i.workerID),e(t))},this.workerID)},r.prototype.loadTile=function(t,e){var r=this,n=void 0===t.workerID?\"loadTile\":\"reloadTile\",i={type:this.type,uid:t.uid,tileID:t.tileID,zoom:t.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:a.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes};t.workerID=this.dispatcher.send(n,i,function(i,a){return t.unloadVectorData(),t.aborted?e(null):i?e(i):(t.loadVectorData(a,r.map.painter,\"reloadTile\"===n),e(null))},this.workerID)},r.prototype.abortTile=function(t){t.aborted=!0},r.prototype.unloadTile=function(t){t.unloadVectorData(),this.dispatcher.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id},null,t.workerID)},r.prototype.onRemove=function(){this._removed=!0,this.dispatcher.send(\"removeSource\",{type:this.type,source:this.id},null,this.workerID)},r.prototype.serialize=function(){return t.extend({},this._options,{type:this.type,data:this._data})},r.prototype.hasTransition=function(){return!1},r}(t.Evented),K=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]),Q=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};Q.prototype.bind=function(t,e,r,n,i,a,o,s){this.context=t;for(var l=this.boundPaintVertexBuffers.length!==n.length,c=0;!l&&c<n.length;c++)this.boundPaintVertexBuffers[c]!==n[c]&&(l=!0);var u=!this.vao||this.boundProgram!==e||this.boundLayoutVertexBuffer!==r||l||this.boundIndexBuffer!==i||this.boundVertexOffset!==a||this.boundDynamicVertexBuffer!==o||this.boundDynamicVertexBuffer2!==s;!t.extVertexArrayObject||u?this.freshBind(e,r,n,i,a,o,s):(t.bindVertexArrayOES.set(this.vao),o&&o.bind(),i&&i.dynamicDraw&&i.bind(),s&&s.bind())},Q.prototype.freshBind=function(t,e,r,n,i,a,o){var s,l=t.numAttributes,c=this.context,u=c.gl;if(c.extVertexArrayObject)this.vao&&this.destroy(),this.vao=c.extVertexArrayObject.createVertexArrayOES(),c.bindVertexArrayOES.set(this.vao),s=0,this.boundProgram=t,this.boundLayoutVertexBuffer=e,this.boundPaintVertexBuffers=r,this.boundIndexBuffer=n,this.boundVertexOffset=i,this.boundDynamicVertexBuffer=a,this.boundDynamicVertexBuffer2=o;else{s=c.currentNumAttributes||0;for(var f=l;f<s;f++)u.disableVertexAttribArray(f)}e.enableAttributes(u,t);for(var h=0,p=r;h<p.length;h+=1)p[h].enableAttributes(u,t);a&&a.enableAttributes(u,t),o&&o.enableAttributes(u,t),e.bind(),e.setVertexAttribPointers(u,t,i);for(var d=0,g=r;d<g.length;d+=1){var v=g[d];v.bind(),v.setVertexAttribPointers(u,t,i)}a&&(a.bind(),a.setVertexAttribPointers(u,t,i)),n&&n.bind(),o&&(o.bind(),o.setVertexAttribPointers(u,t,i)),c.currentNumAttributes=l},Q.prototype.destroy=function(){this.vao&&(this.context.extVertexArrayObject.deleteVertexArrayOES(this.vao),this.vao=null)};var tt=function(e){function r(t,r,n,i){e.call(this),this.id=t,this.dispatcher=n,this.coordinates=r.coordinates,this.type=\"image\",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this.setEventedParent(i),this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this.url=this.options.url,t.getImage(this.map._transformRequest(this.url,t.ResourceType.Image),function(r,n){r?e.fire(new t.ErrorEvent(r)):n&&(e.image=a.getImageData(n),e._finishLoading())})},r.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setCoordinates=function(e){this.coordinates=e;var r=this.map,n=e.map(function(t){return r.transform.locationCoordinate(G.convert(t)).zoomTo(0)}),i=this.centerCoord=t.getCoordinatesCenter(n);i.column=Math.floor(i.column),i.row=Math.floor(i.row),this.tileID=new t.CanonicalTileID(i.zoom,i.column,i.row),this.minzoom=this.maxzoom=i.zoom;var a=n.map(function(e){var r=e.zoomTo(i.zoom);return new t.default$1(Math.round((r.column-i.column)*t.default$8),Math.round((r.row-i.row)*t.default$8))});return this._boundsArray=new t.RasterBoundsArray,this._boundsArray.emplaceBack(a[0].x,a[0].y,0,0),this._boundsArray.emplaceBack(a[1].x,a[1].y,t.default$8,0),this._boundsArray.emplaceBack(a[3].x,a[3].y,0,t.default$8),this._boundsArray.emplaceBack(a[2].x,a[2].y,t.default$8,t.default$8),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})),this},r.prototype.prepare=function(){if(0!==Object.keys(this.tiles).length&&this.image){var t=this.map.painter.context,e=t.gl;for(var r in this.boundsBuffer||(this.boundsBuffer=t.createVertexBuffer(this._boundsArray,K.members)),this.boundsVAO||(this.boundsVAO=new Q),this.texture||(this.texture=new z(t,this.image,e.RGBA),this.texture.bind(e.LINEAR,e.CLAMP_TO_EDGE)),this.tiles){var n=this.tiles[r];\"loaded\"!==n.state&&(n.state=\"loaded\",n.texture=this.texture)}}},r.prototype.loadTile=function(t,e){this.tileID&&this.tileID.equals(t.tileID.canonical)?(this.tiles[String(t.tileID.wrap)]=t,t.buckets={},e(null)):(t.state=\"errored\",e(null))},r.prototype.serialize=function(){return{type:\"image\",url:this.options.url,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return!1},r}(t.Evented),et=function(e){function r(t,r,n,i){e.call(this,t,r,n,i),this.roundZoom=!0,this.type=\"video\",this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this,r=this.options;this.urls=[];for(var n=0,i=r.urls;n<i.length;n+=1){var a=i[n];e.urls.push(e.map._transformRequest(a,t.ResourceType.Source).url)}t.getVideo(this.urls,function(r,n){r?e.fire(new t.ErrorEvent(r)):n&&(e.video=n,e.video.loop=!0,e.video.addEventListener(\"playing\",function(){e.map._rerender()}),e.map&&e.video.play(),e._finishLoading())})},r.prototype.getVideo=function(){return this.video},r.prototype.onAdd=function(t){this.map||(this.map=t,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},r.prototype.prepare=function(){if(!(0===Object.keys(this.tiles).length||this.video.readyState<2)){var t=this.map.painter.context,e=t.gl;for(var r in this.boundsBuffer||(this.boundsBuffer=t.createVertexBuffer(this._boundsArray,K.members)),this.boundsVAO||(this.boundsVAO=new Q),this.texture?this.video.paused||(this.texture.bind(e.LINEAR,e.CLAMP_TO_EDGE),e.texSubImage2D(e.TEXTURE_2D,0,0,0,e.RGBA,e.UNSIGNED_BYTE,this.video)):(this.texture=new z(t,this.video,e.RGBA),this.texture.bind(e.LINEAR,e.CLAMP_TO_EDGE)),this.tiles){var n=this.tiles[r];\"loaded\"!==n.state&&(n.state=\"loaded\",n.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this.video&&!this.video.paused},r}(tt),rt=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),n.coordinates?Array.isArray(n.coordinates)&&4===n.coordinates.length&&!n.coordinates.some(function(t){return!Array.isArray(t)||2!==t.length||t.some(function(t){return\"number\"!=typeof t})})||this.fire(new t.ErrorEvent(new t.default$9(\"sources.\"+r,null,'\"coordinates\" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new t.ErrorEvent(new t.default$9(\"sources.\"+r,null,'missing required property \"coordinates\"'))),n.animate&&\"boolean\"!=typeof n.animate&&this.fire(new t.ErrorEvent(new t.default$9(\"sources.\"+r,null,'optional \"animate\" property must be a boolean value'))),n.canvas?\"string\"==typeof n.canvas||n.canvas instanceof t.default.HTMLCanvasElement||this.fire(new t.ErrorEvent(new t.default$9(\"sources.\"+r,null,'\"canvas\" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new t.ErrorEvent(new t.default$9(\"sources.\"+r,null,'missing required property \"canvas\"'))),this.options=n,this.animate=void 0===n.animate||n.animate}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){this.canvas||(this.canvas=this.options.canvas instanceof t.default.HTMLCanvasElement?this.options.canvas:t.default.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new t.ErrorEvent(new Error(\"Canvas dimensions cannot be less than or equal to zero.\"))):(this.play=function(){this._playing=!0,this.map._rerender()},this.pause=function(){this._playing=!1},this._finishLoading())},r.prototype.getCanvas=function(){return this.canvas},r.prototype.onAdd=function(t){this.map=t,this.load(),this.canvas&&this.animate&&this.play()},r.prototype.onRemove=function(){this.pause()},r.prototype.prepare=function(){var t=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,t=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,t=!0),!this._hasInvalidDimensions()&&0!==Object.keys(this.tiles).length){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,K.members)),this.boundsVAO||(this.boundsVAO=new Q),this.texture?t?this.texture.update(this.canvas):this._playing&&(this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE),r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,this.canvas)):(this.texture=new z(e,this.canvas,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"canvas\",coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this._playing},r.prototype._hasInvalidDimensions=function(){for(var t=0,e=[this.canvas.width,this.canvas.height];t<e.length;t+=1){var r=e[t];if(isNaN(r)||r<=0)return!0}return!1},r}(tt),nt={vector:X,raster:Z,\"raster-dem\":$,geojson:J,video:et,image:tt,canvas:rt},it=function(e,r,n,i){var a=new nt[r.type](e,r,n,i);if(a.id!==e)throw new Error(\"Expected Source id to be \"+e+\" instead of \"+a.id);return t.bindAll([\"load\",\"abort\",\"unload\",\"serialize\",\"prepare\"],a),a};function at(t,e,r,n,i){var a=i.maxPitchScaleFactor(),o=t.tilesIn(r,a);o.sort(ot);for(var s=[],l=0,c=o;l<c.length;l+=1){var u=c[l];s.push({wrappedTileID:u.tileID.wrapped().key,queryResults:u.tile.queryRenderedFeatures(e,u.queryGeometry,u.scale,n,i,a,t.transform.calculatePosMatrix(u.tileID.toUnwrapped()))})}return function(t){for(var e={},r={},n=0,i=t;n<i.length;n+=1){var a=i[n],o=a.queryResults,s=a.wrappedTileID,l=r[s]=r[s]||{};for(var c in o)for(var u=o[c],f=l[c]=l[c]||{},h=e[c]=e[c]||[],p=0,d=u;p<d.length;p+=1){var g=d[p];f[g.featureIndex]||(f[g.featureIndex]=!0,h.push(g.feature))}}return e}(s)}function ot(t,e){var r=t.tileID,n=e.tileID;return r.overscaledZ-n.overscaledZ||r.canonical.y-n.canonical.y||r.wrap-n.wrap||r.canonical.x-n.canonical.x}var st=function(e,r){this.tileID=e,this.uid=t.uniqueId(),this.uses=0,this.tileSize=r,this.buckets={},this.expirationTime=null,this.queryPadding=0,this.expiredRequestCount=0,this.state=\"loading\"};st.prototype.registerFadeDuration=function(t){var e=t+this.timeAdded;e<a.now()||this.fadeEndTime&&e<this.fadeEndTime||(this.fadeEndTime=e)},st.prototype.wasRequested=function(){return\"errored\"===this.state||\"loaded\"===this.state||\"reloading\"===this.state},st.prototype.loadVectorData=function(e,r,n){if(this.hasData()&&this.unloadVectorData(),this.state=\"loaded\",e){if(e.featureIndex&&(this.latestFeatureIndex=e.featureIndex,e.rawTileData?(this.latestRawTileData=e.rawTileData,this.latestFeatureIndex.rawTileData=e.rawTileData):this.latestRawTileData&&(this.latestFeatureIndex.rawTileData=this.latestRawTileData)),this.collisionBoxArray=e.collisionBoxArray,this.buckets=function(t,e){var r={};if(!e)return r;for(var n=0,i=t;n<i.length;n+=1){var a=i[n],o=a.layerIds.map(function(t){return e.getLayer(t)}).filter(Boolean);if(0!==o.length){a.layers=o;for(var s=0,l=o;s<l.length;s+=1)r[l[s].id]=a}}return r}(e.buckets,r.style),n)for(var i in this.buckets){var a=this.buckets[i];a instanceof t.default$14&&(a.justReloaded=!0)}for(var o in this.queryPadding=0,this.buckets){var s=this.buckets[o];this.queryPadding=Math.max(this.queryPadding,r.style.getLayer(s.layerIds[0]).queryRadius(s))}e.iconAtlasImage&&(this.iconAtlasImage=e.iconAtlasImage),e.glyphAtlasImage&&(this.glyphAtlasImage=e.glyphAtlasImage)}else this.collisionBoxArray=new t.CollisionBoxArray},st.prototype.unloadVectorData=function(){for(var t in this.buckets)this.buckets[t].destroy();this.buckets={},this.iconAtlasTexture&&this.iconAtlasTexture.destroy(),this.glyphAtlasTexture&&this.glyphAtlasTexture.destroy(),this.latestFeatureIndex=null,this.state=\"unloaded\"},st.prototype.unloadDEMData=function(){this.dem=null,this.neighboringTiles=null,this.state=\"unloaded\"},st.prototype.getBucket=function(t){return this.buckets[t.id]},st.prototype.upload=function(t){for(var e in this.buckets){var r=this.buckets[e];r.uploaded||(r.upload(t),r.uploaded=!0)}var n=t.gl;this.iconAtlasImage&&(this.iconAtlasTexture=new z(t,this.iconAtlasImage,n.RGBA),this.iconAtlasImage=null),this.glyphAtlasImage&&(this.glyphAtlasTexture=new z(t,this.glyphAtlasImage,n.ALPHA),this.glyphAtlasImage=null)},st.prototype.queryRenderedFeatures=function(t,e,r,n,i,a,o){return this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData?this.latestFeatureIndex.query({queryGeometry:e,scale:r,tileSize:this.tileSize,posMatrix:o,transform:i,params:n,queryPadding:this.queryPadding*a},t):{}},st.prototype.querySourceFeatures=function(e,r){if(this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData){var n=this.latestFeatureIndex.loadVTLayers(),i=r?r.sourceLayer:\"\",a=n._geojsonTileLayer||n[i];if(a)for(var o=t.default$13(r&&r.filter),s={z:this.tileID.overscaledZ,x:this.tileID.canonical.x,y:this.tileID.canonical.y},l=0;l<a.length;l++){var c=a.feature(l);if(o(new t.default$16(this.tileID.overscaledZ),c)){var u=new t.default$12(c,s.z,s.x,s.y);u.tile=s,e.push(u)}}}},st.prototype.clearMask=function(){this.segments&&(this.segments.destroy(),delete this.segments),this.maskedBoundsBuffer&&(this.maskedBoundsBuffer.destroy(),delete this.maskedBoundsBuffer),this.maskedIndexBuffer&&(this.maskedIndexBuffer.destroy(),delete this.maskedIndexBuffer)},st.prototype.setMask=function(e,r){if(!t.default$10(this.mask,e)&&(this.mask=e,this.clearMask(),!t.default$10(e,{0:!0}))){var n=new t.RasterBoundsArray,i=new t.TriangleIndexArray;this.segments=new t.default$15,this.segments.prepareSegment(0,n,i);for(var a=Object.keys(e),o=0;o<a.length;o++){var s=e[a[o]],l=t.default$8>>s.z,c=new t.default$1(s.x*l,s.y*l),u=new t.default$1(c.x+l,c.y+l),f=this.segments.prepareSegment(4,n,i);n.emplaceBack(c.x,c.y,c.x,c.y),n.emplaceBack(u.x,c.y,u.x,c.y),n.emplaceBack(c.x,u.y,c.x,u.y),n.emplaceBack(u.x,u.y,u.x,u.y);var h=f.vertexLength;i.emplaceBack(h,h+1,h+2),i.emplaceBack(h+1,h+2,h+3),f.vertexLength+=4,f.primitiveLength+=2}this.maskedBoundsBuffer=r.createVertexBuffer(n,K.members),this.maskedIndexBuffer=r.createIndexBuffer(i)}},st.prototype.hasData=function(){return\"loaded\"===this.state||\"reloading\"===this.state||\"expired\"===this.state},st.prototype.setExpiryData=function(e){var r=this.expirationTime;if(e.cacheControl){var n=t.parseCacheControl(e.cacheControl);n[\"max-age\"]&&(this.expirationTime=Date.now()+1e3*n[\"max-age\"])}else e.expires&&(this.expirationTime=new Date(e.expires).getTime());if(this.expirationTime){var i=Date.now(),a=!1;if(this.expirationTime>i)a=!1;else if(r)if(this.expirationTime<r)a=!0;else{var o=this.expirationTime-r;o?this.expirationTime=i+Math.max(o,3e4):a=!0}else a=!0;a?(this.expiredRequestCount++,this.state=\"expired\"):this.expiredRequestCount=0}},st.prototype.getExpiryTimeout=function(){if(this.expirationTime)return this.expiredRequestCount?1e3*(1<<Math.min(this.expiredRequestCount-1,31)):Math.min(this.expirationTime-(new Date).getTime(),Math.pow(2,31)-1)};var lt=function(t,e){this.max=t,this.onRemove=e,this.reset()};lt.prototype.reset=function(){for(var t in this.data)for(var e=0,r=this.data[t];e<r.length;e+=1){var n=r[e];n.timeout&&clearTimeout(n.timeout),this.onRemove(n.value)}return this.data={},this.order=[],this},lt.prototype.add=function(t,e,r){var n=this,i=t.wrapped().key;void 0===this.data[i]&&(this.data[i]=[]);var a={value:e,timeout:void 0};if(void 0!==r&&(a.timeout=setTimeout(function(){n.remove(t,a)},r)),this.data[i].push(a),this.order.push(i),this.order.length>this.max){var o=this._getAndRemoveByKey(this.order[0]);o&&this.onRemove(o)}return this},lt.prototype.has=function(t){return t.wrapped().key in this.data},lt.prototype.getAndRemove=function(t){return this.has(t)?this._getAndRemoveByKey(t.wrapped().key):null},lt.prototype._getAndRemoveByKey=function(t){var e=this.data[t].shift();return e.timeout&&clearTimeout(e.timeout),0===this.data[t].length&&delete this.data[t],this.order.splice(this.order.indexOf(t),1),e.value},lt.prototype.get=function(t){return this.has(t)?this.data[t.wrapped().key][0].value:null},lt.prototype.remove=function(t,e){if(!this.has(t))return this;var r=t.wrapped().key,n=void 0===e?0:this.data[r].indexOf(e),i=this.data[r][n];return this.data[r].splice(n,1),i.timeout&&clearTimeout(i.timeout),0===this.data[r].length&&delete this.data[r],this.onRemove(i.value),this.order.splice(this.order.indexOf(r),1),this},lt.prototype.setMaxSize=function(t){for(this.max=t;this.order.length>this.max;){var e=this._getAndRemoveByKey(this.order[0]);e&&this.onRemove(e)}return this};var ct=function(t,e,r){this.context=t;var n=t.gl;this.buffer=n.createBuffer(),this.dynamicDraw=Boolean(r),this.unbindVAO(),t.bindElementBuffer.set(this.buffer),n.bufferData(n.ELEMENT_ARRAY_BUFFER,e.arrayBuffer,this.dynamicDraw?n.DYNAMIC_DRAW:n.STATIC_DRAW),this.dynamicDraw||delete e.arrayBuffer};ct.prototype.unbindVAO=function(){this.context.extVertexArrayObject&&this.context.bindVertexArrayOES.set(null)},ct.prototype.bind=function(){this.context.bindElementBuffer.set(this.buffer)},ct.prototype.updateData=function(t){var e=this.context.gl;this.unbindVAO(),this.bind(),e.bufferSubData(e.ELEMENT_ARRAY_BUFFER,0,t.arrayBuffer)},ct.prototype.destroy=function(){var t=this.context.gl;this.buffer&&(t.deleteBuffer(this.buffer),delete this.buffer)};var ut={Int8:\"BYTE\",Uint8:\"UNSIGNED_BYTE\",Int16:\"SHORT\",Uint16:\"UNSIGNED_SHORT\",Int32:\"INT\",Uint32:\"UNSIGNED_INT\",Float32:\"FLOAT\"},ft=function(t,e,r,n){this.length=e.length,this.attributes=r,this.itemSize=e.bytesPerElement,this.dynamicDraw=n,this.context=t;var i=t.gl;this.buffer=i.createBuffer(),t.bindVertexBuffer.set(this.buffer),i.bufferData(i.ARRAY_BUFFER,e.arrayBuffer,this.dynamicDraw?i.DYNAMIC_DRAW:i.STATIC_DRAW),this.dynamicDraw||delete e.arrayBuffer};ft.prototype.bind=function(){this.context.bindVertexBuffer.set(this.buffer)},ft.prototype.updateData=function(t){var e=this.context.gl;this.bind(),e.bufferSubData(e.ARRAY_BUFFER,0,t.arrayBuffer)},ft.prototype.enableAttributes=function(t,e){for(var r=0;r<this.attributes.length;r++){var n=this.attributes[r],i=e.attributes[n.name];void 0!==i&&t.enableVertexAttribArray(i)}},ft.prototype.setVertexAttribPointers=function(t,e,r){for(var n=0;n<this.attributes.length;n++){var i=this.attributes[n],a=e.attributes[i.name];void 0!==a&&t.vertexAttribPointer(a,i.components,t[ut[i.type]],!1,this.itemSize,i.offset+this.itemSize*(r||0))}},ft.prototype.destroy=function(){var t=this.context.gl;this.buffer&&(t.deleteBuffer(this.buffer),delete this.buffer)};var ht=function(e){this.context=e,this.current=t.default$6.transparent};ht.prototype.get=function(){return this.current},ht.prototype.set=function(t){var e=this.current;t.r===e.r&&t.g===e.g&&t.b===e.b&&t.a===e.a||(this.context.gl.clearColor(t.r,t.g,t.b,t.a),this.current=t)};var pt=function(t){this.context=t,this.current=1};pt.prototype.get=function(){return this.current},pt.prototype.set=function(t){this.current!==t&&(this.context.gl.clearDepth(t),this.current=t)};var dt=function(t){this.context=t,this.current=0};dt.prototype.get=function(){return this.current},dt.prototype.set=function(t){this.current!==t&&(this.context.gl.clearStencil(t),this.current=t)};var gt=function(t){this.context=t,this.current=[!0,!0,!0,!0]};gt.prototype.get=function(){return this.current},gt.prototype.set=function(t){var e=this.current;t[0]===e[0]&&t[1]===e[1]&&t[2]===e[2]&&t[3]===e[3]||(this.context.gl.colorMask(t[0],t[1],t[2],t[3]),this.current=t)};var vt=function(t){this.context=t,this.current=!0};vt.prototype.get=function(){return this.current},vt.prototype.set=function(t){this.current!==t&&(this.context.gl.depthMask(t),this.current=t)};var mt=function(t){this.context=t,this.current=255};mt.prototype.get=function(){return this.current},mt.prototype.set=function(t){this.current!==t&&(this.context.gl.stencilMask(t),this.current=t)};var yt=function(t){this.context=t,this.current={func:t.gl.ALWAYS,ref:0,mask:255}};yt.prototype.get=function(){return this.current},yt.prototype.set=function(t){var e=this.current;t.func===e.func&&t.ref===e.ref&&t.mask===e.mask||(this.context.gl.stencilFunc(t.func,t.ref,t.mask),this.current=t)};var xt=function(t){this.context=t;var e=this.context.gl;this.current=[e.KEEP,e.KEEP,e.KEEP]};xt.prototype.get=function(){return this.current},xt.prototype.set=function(t){var e=this.current;t[0]===e[0]&&t[1]===e[1]&&t[2]===e[2]||(this.context.gl.stencilOp(t[0],t[1],t[2]),this.current=t)};var bt=function(t){this.context=t,this.current=!1};bt.prototype.get=function(){return this.current},bt.prototype.set=function(t){if(this.current!==t){var e=this.context.gl;t?e.enable(e.STENCIL_TEST):e.disable(e.STENCIL_TEST),this.current=t}};var _t=function(t){this.context=t,this.current=[0,1]};_t.prototype.get=function(){return this.current},_t.prototype.set=function(t){var e=this.current;t[0]===e[0]&&t[1]===e[1]||(this.context.gl.depthRange(t[0],t[1]),this.current=t)};var wt=function(t){this.context=t,this.current=!1};wt.prototype.get=function(){return this.current},wt.prototype.set=function(t){if(this.current!==t){var e=this.context.gl;t?e.enable(e.DEPTH_TEST):e.disable(e.DEPTH_TEST),this.current=t}};var kt=function(t){this.context=t,this.current=t.gl.LESS};kt.prototype.get=function(){return this.current},kt.prototype.set=function(t){this.current!==t&&(this.context.gl.depthFunc(t),this.current=t)};var Tt=function(t){this.context=t,this.current=!1};Tt.prototype.get=function(){return this.current},Tt.prototype.set=function(t){if(this.current!==t){var e=this.context.gl;t?e.enable(e.BLEND):e.disable(e.BLEND),this.current=t}};var At=function(t){this.context=t;var e=this.context.gl;this.current=[e.ONE,e.ZERO]};At.prototype.get=function(){return this.current},At.prototype.set=function(t){var e=this.current;t[0]===e[0]&&t[1]===e[1]||(this.context.gl.blendFunc(t[0],t[1]),this.current=t)};var Mt=function(e){this.context=e,this.current=t.default$6.transparent};Mt.prototype.get=function(){return this.current},Mt.prototype.set=function(t){var e=this.current;t.r===e.r&&t.g===e.g&&t.b===e.b&&t.a===e.a||(this.context.gl.blendColor(t.r,t.g,t.b,t.a),this.current=t)};var St=function(t){this.context=t,this.current=null};St.prototype.get=function(){return this.current},St.prototype.set=function(t){this.current!==t&&(this.context.gl.useProgram(t),this.current=t)};var Et=function(t){this.context=t,this.current=1};Et.prototype.get=function(){return this.current},Et.prototype.set=function(e){var r=this.context.lineWidthRange,n=t.clamp(e,r[0],r[1]);this.current!==n&&(this.context.gl.lineWidth(n),this.current=e)};var Ct=function(t){this.context=t,this.current=t.gl.TEXTURE0};Ct.prototype.get=function(){return this.current},Ct.prototype.set=function(t){this.current!==t&&(this.context.gl.activeTexture(t),this.current=t)};var Lt=function(t){this.context=t;var e=this.context.gl;this.current=[0,0,e.drawingBufferWidth,e.drawingBufferHeight]};Lt.prototype.get=function(){return this.current},Lt.prototype.set=function(t){var e=this.current;t[0]===e[0]&&t[1]===e[1]&&t[2]===e[2]&&t[3]===e[3]||(this.context.gl.viewport(t[0],t[1],t[2],t[3]),this.current=t)};var zt=function(t){this.context=t,this.current=null};zt.prototype.get=function(){return this.current},zt.prototype.set=function(t){if(this.current!==t){var e=this.context.gl;e.bindFramebuffer(e.FRAMEBUFFER,t),this.current=t}};var Ot=function(t){this.context=t,this.current=null};Ot.prototype.get=function(){return this.current},Ot.prototype.set=function(t){if(this.current!==t){var e=this.context.gl;e.bindRenderbuffer(e.RENDERBUFFER,t),this.current=t}};var It=function(t){this.context=t,this.current=null};It.prototype.get=function(){return this.current},It.prototype.set=function(t){if(this.current!==t){var e=this.context.gl;e.bindTexture(e.TEXTURE_2D,t),this.current=t}};var Dt=function(t){this.context=t,this.current=null};Dt.prototype.get=function(){return this.current},Dt.prototype.set=function(t){if(this.current!==t){var e=this.context.gl;e.bindBuffer(e.ARRAY_BUFFER,t),this.current=t}};var Pt=function(t){this.context=t,this.current=null};Pt.prototype.get=function(){return this.current},Pt.prototype.set=function(t){var e=this.context.gl;e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,t),this.current=t};var Rt=function(t){this.context=t,this.current=null};Rt.prototype.get=function(){return this.current},Rt.prototype.set=function(t){this.current!==t&&this.context.extVertexArrayObject&&(this.context.extVertexArrayObject.bindVertexArrayOES(t),this.current=t)};var Ft=function(t){this.context=t,this.current=4};Ft.prototype.get=function(){return this.current},Ft.prototype.set=function(t){if(this.current!==t){var e=this.context.gl;e.pixelStorei(e.UNPACK_ALIGNMENT,t),this.current=t}};var Bt=function(t){this.context=t,this.current=!1};Bt.prototype.get=function(){return this.current},Bt.prototype.set=function(t){if(this.current!==t){var e=this.context.gl;e.pixelStorei(e.UNPACK_PREMULTIPLY_ALPHA_WEBGL,t),this.current=t}};var Nt=function(t,e){this.context=t,this.current=null,this.parent=e};Nt.prototype.get=function(){return this.current};var jt=function(t){function e(e,r){t.call(this,e,r),this.dirty=!1}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){if(this.dirty||this.current!==t){var e=this.context.gl;this.context.bindFramebuffer.set(this.parent),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0),this.current=t,this.dirty=!1}},e.prototype.setDirty=function(){this.dirty=!0},e}(Nt),Vt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){if(this.current!==t){var e=this.context.gl;this.context.bindFramebuffer.set(this.parent),e.framebufferRenderbuffer(e.FRAMEBUFFER,e.DEPTH_ATTACHMENT,e.RENDERBUFFER,t),this.current=t}},e}(Nt),Ut=function(t,e,r){this.context=t,this.width=e,this.height=r;var n=t.gl,i=this.framebuffer=n.createFramebuffer();this.colorAttachment=new jt(t,i),this.depthAttachment=new Vt(t,i)};Ut.prototype.destroy=function(){var t=this.context.gl,e=this.colorAttachment.get();e&&t.deleteTexture(e);var r=this.depthAttachment.get();r&&t.deleteRenderbuffer(r),t.deleteFramebuffer(this.framebuffer)};var Ht=function(t,e,r){this.func=t,this.mask=e,this.range=r};Ht.ReadOnly=!1,Ht.ReadWrite=!0,Ht.disabled=new Ht(519,Ht.ReadOnly,[0,1]);var qt=function(t,e,r,n,i,a){this.test=t,this.ref=e,this.mask=r,this.fail=n,this.depthFail=i,this.pass=a};qt.disabled=new qt({func:519,mask:0},0,0,7680,7680,7680);var Gt=function(t,e,r){this.blendFunction=t,this.blendColor=e,this.mask=r};Gt.disabled=new Gt(Gt.Replace=[1,0],t.default$6.transparent,[!1,!1,!1,!1]),Gt.unblended=new Gt(Gt.Replace,t.default$6.transparent,[!0,!0,!0,!0]),Gt.alphaBlended=new Gt([1,771],t.default$6.transparent,[!0,!0,!0,!0]);var Yt=function(t){this.gl=t,this.extVertexArrayObject=this.gl.getExtension(\"OES_vertex_array_object\"),this.lineWidthRange=t.getParameter(t.ALIASED_LINE_WIDTH_RANGE),this.clearColor=new ht(this),this.clearDepth=new pt(this),this.clearStencil=new dt(this),this.colorMask=new gt(this),this.depthMask=new vt(this),this.stencilMask=new mt(this),this.stencilFunc=new yt(this),this.stencilOp=new xt(this),this.stencilTest=new bt(this),this.depthRange=new _t(this),this.depthTest=new wt(this),this.depthFunc=new kt(this),this.blend=new Tt(this),this.blendFunc=new At(this),this.blendColor=new Mt(this),this.program=new St(this),this.lineWidth=new Et(this),this.activeTexture=new Ct(this),this.viewport=new Lt(this),this.bindFramebuffer=new zt(this),this.bindRenderbuffer=new Ot(this),this.bindTexture=new It(this),this.bindVertexBuffer=new Dt(this),this.bindElementBuffer=new Pt(this),this.bindVertexArrayOES=this.extVertexArrayObject&&new Rt(this),this.pixelStoreUnpack=new Ft(this),this.pixelStoreUnpackPremultiplyAlpha=new Bt(this),this.extTextureFilterAnisotropic=t.getExtension(\"EXT_texture_filter_anisotropic\")||t.getExtension(\"MOZ_EXT_texture_filter_anisotropic\")||t.getExtension(\"WEBKIT_EXT_texture_filter_anisotropic\"),this.extTextureFilterAnisotropic&&(this.extTextureFilterAnisotropicMax=t.getParameter(this.extTextureFilterAnisotropic.MAX_TEXTURE_MAX_ANISOTROPY_EXT)),this.extTextureHalfFloat=t.getExtension(\"OES_texture_half_float\"),this.extTextureHalfFloat&&t.getExtension(\"OES_texture_half_float_linear\")};Yt.prototype.createIndexBuffer=function(t,e){return new ct(this,t,e)},Yt.prototype.createVertexBuffer=function(t,e,r){return new ft(this,t,e,r)},Yt.prototype.createRenderbuffer=function(t,e,r){var n=this.gl,i=n.createRenderbuffer();return this.bindRenderbuffer.set(i),n.renderbufferStorage(n.RENDERBUFFER,t,e,r),this.bindRenderbuffer.set(null),i},Yt.prototype.createFramebuffer=function(t,e){return new Ut(this,t,e)},Yt.prototype.clear=function(t){var e=t.color,r=t.depth,n=this.gl,i=0;e&&(i|=n.COLOR_BUFFER_BIT,this.clearColor.set(e),this.colorMask.set([!0,!0,!0,!0])),void 0!==r&&(i|=n.DEPTH_BUFFER_BIT,this.clearDepth.set(r),this.depthMask.set(!0)),n.clear(i)},Yt.prototype.setDepthMode=function(t){t.func!==this.gl.ALWAYS||t.mask?(this.depthTest.set(!0),this.depthFunc.set(t.func),this.depthMask.set(t.mask),this.depthRange.set(t.range)):this.depthTest.set(!1)},Yt.prototype.setStencilMode=function(t){t.test.func!==this.gl.ALWAYS||t.mask?(this.stencilTest.set(!0),this.stencilMask.set(t.mask),this.stencilOp.set([t.fail,t.depthFail,t.pass]),this.stencilFunc.set({func:t.test.func,ref:t.ref,mask:t.test.mask})):this.stencilTest.set(!1)},Yt.prototype.setColorMode=function(e){t.default$10(e.blendFunction,Gt.Replace)?this.blend.set(!1):(this.blend.set(!0),this.blendFunc.set(e.blendFunction),this.blendColor.set(e.blendColor)),this.colorMask.set(e.mask)};var Wt=function(e){function r(t,r,n){var i=this;e.call(this),this.id=t,this.dispatcher=n,this.on(\"data\",function(t){\"source\"===t.dataType&&\"metadata\"===t.sourceDataType&&(i._sourceLoaded=!0),i._sourceLoaded&&!i._paused&&\"source\"===t.dataType&&\"content\"===t.sourceDataType&&(i.reload(),i.transform&&i.update(i.transform))}),this.on(\"error\",function(){i._sourceErrored=!0}),this._source=it(t,r,n,this),this._tiles={},this._cache=new lt(0,this._unloadTile.bind(this)),this._timers={},this._cacheTimers={},this._maxTileCacheSize=null,this._isIdRenderable=this._isIdRenderable.bind(this),this._coveredTiles={}}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.onAdd=function(t){this.map=t,this._maxTileCacheSize=t?t._maxTileCacheSize:null,this._source&&this._source.onAdd&&this._source.onAdd(t)},r.prototype.onRemove=function(t){this._source&&this._source.onRemove&&this._source.onRemove(t)},r.prototype.loaded=function(){if(this._sourceErrored)return!0;if(!this._sourceLoaded)return!1;for(var t in this._tiles){var e=this._tiles[t];if(\"loaded\"!==e.state&&\"errored\"!==e.state)return!1}return!0},r.prototype.getSource=function(){return this._source},r.prototype.pause=function(){this._paused=!0},r.prototype.resume=function(){if(this._paused){var t=this._shouldReloadOnResume;this._paused=!1,this._shouldReloadOnResume=!1,t&&this.reload(),this.transform&&this.update(this.transform)}},r.prototype._loadTile=function(t,e){return this._source.loadTile(t,e)},r.prototype._unloadTile=function(t){if(this._source.unloadTile)return this._source.unloadTile(t,function(){})},r.prototype._abortTile=function(t){if(this._source.abortTile)return this._source.abortTile(t,function(){})},r.prototype.serialize=function(){return this._source.serialize()},r.prototype.prepare=function(t){for(var e in this._source.prepare&&this._source.prepare(),this._tiles)this._tiles[e].upload(t)},r.prototype.getIds=function(){var e=this;return Object.keys(this._tiles).map(Number).sort(function(r,n){var i=e._tiles[r].tileID,a=e._tiles[n].tileID,o=new t.default$1(i.canonical.x,i.canonical.y).rotate(e.transform.angle),s=new t.default$1(a.canonical.x,a.canonical.y).rotate(e.transform.angle);return i.overscaledZ-a.overscaledZ||s.y-o.y||s.x-o.x})},r.prototype.getRenderableIds=function(){return this.getIds().filter(this._isIdRenderable)},r.prototype.hasRenderableParent=function(t){var e=this.findLoadedParent(t,0,{});return!!e&&this._isIdRenderable(e.tileID.key)},r.prototype._isIdRenderable=function(t){return this._tiles[t]&&this._tiles[t].hasData()&&!this._coveredTiles[t]},r.prototype.reload=function(){if(this._paused)this._shouldReloadOnResume=!0;else for(var t in this._cache.reset(),this._tiles)this._reloadTile(t,\"reloading\")},r.prototype._reloadTile=function(t,e){var r=this._tiles[t];r&&(\"loading\"!==r.state&&(r.state=e),this._loadTile(r,this._tileLoaded.bind(this,r,t,e)))},r.prototype._tileLoaded=function(e,r,n,i){if(i)return e.state=\"errored\",void(404!==i.status?this._source.fire(new t.ErrorEvent(i,{tile:e})):this.update(this.transform));e.timeAdded=a.now(),\"expired\"===n&&(e.refreshedUponExpiration=!0),this._setTileReloadTimer(r,e),\"raster-dem\"===this.getSource().type&&e.dem&&this._backfillDEM(e),this._source.fire(new t.Event(\"data\",{dataType:\"source\",tile:e,coord:e.tileID})),this.map&&(this.map.painter.tileExtentVAO.vao=null)},r.prototype._backfillDEM=function(t){for(var e=this.getRenderableIds(),r=0;r<e.length;r++){var n=e[r];if(t.neighboringTiles&&t.neighboringTiles[n]){var i=this.getTileByID(n);a(t,i),a(i,t)}}function a(t,e){t.needsHillshadePrepare=!0;var r=e.tileID.canonical.x-t.tileID.canonical.x,n=e.tileID.canonical.y-t.tileID.canonical.y,i=Math.pow(2,t.tileID.canonical.z),a=e.tileID.key;0===r&&0===n||Math.abs(n)>1||(Math.abs(r)>1&&(1===Math.abs(r+i)?r+=i:1===Math.abs(r-i)&&(r-=i)),e.dem&&t.dem&&(t.dem.backfillBorder(e.dem,r,n),t.neighboringTiles&&t.neighboringTiles[a]&&(t.neighboringTiles[a].backfilled=!0)))}},r.prototype.getTile=function(t){return this.getTileByID(t.key)},r.prototype.getTileByID=function(t){return this._tiles[t]},r.prototype.getZoom=function(t){return t.zoom+t.scaleZoom(t.tileSize/this._source.tileSize)},r.prototype._findLoadedChildren=function(t,e,r){var n=!1;for(var i in this._tiles){var a=this._tiles[i];if(!(r[i]||!a.hasData()||a.tileID.overscaledZ<=t.overscaledZ||a.tileID.overscaledZ>e)){var o=Math.pow(2,a.tileID.canonical.z-t.canonical.z);if(Math.floor(a.tileID.canonical.x/o)===t.canonical.x&&Math.floor(a.tileID.canonical.y/o)===t.canonical.y)for(r[i]=a.tileID,n=!0;a&&a.tileID.overscaledZ-1>t.overscaledZ;){var s=a.tileID.scaledTo(a.tileID.overscaledZ-1);if(!s)break;(a=this._tiles[s.key])&&a.hasData()&&(delete r[i],r[s.key]=s)}}}return n},r.prototype.findLoadedParent=function(t,e,r){for(var n=t.overscaledZ-1;n>=e;n--){var i=t.scaledTo(n);if(!i)return;var a=String(i.key),o=this._tiles[a];if(o&&o.hasData())return r[a]=i,o;if(this._cache.has(i))return r[a]=i,this._cache.get(i)}},r.prototype.updateCacheSize=function(t){var e=(Math.ceil(t.width/this._source.tileSize)+1)*(Math.ceil(t.height/this._source.tileSize)+1),r=Math.floor(5*e),n=\"number\"==typeof this._maxTileCacheSize?Math.min(this._maxTileCacheSize,r):r;this._cache.setMaxSize(n)},r.prototype.handleWrapJump=function(t){var e=(t-(void 0===this._prevLng?t:this._prevLng))/360,r=Math.round(e);if(this._prevLng=t,r){var n={};for(var i in this._tiles){var a=this._tiles[i];a.tileID=a.tileID.unwrapTo(a.tileID.wrap+r),n[a.tileID.key]=a}for(var o in this._tiles=n,this._timers)clearTimeout(this._timers[o]),delete this._timers[o];for(var s in this._tiles){var l=this._tiles[s];this._setTileReloadTimer(s,l)}}},r.prototype.update=function(e){var n=this;if(this.transform=e,this._sourceLoaded&&!this._paused){var i;this.updateCacheSize(e),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used?this._source.tileID?i=e.getVisibleUnwrappedCoordinates(this._source.tileID).map(function(e){return new t.OverscaledTileID(e.canonical.z,e.wrap,e.canonical.z,e.canonical.x,e.canonical.y)}):(i=e.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(i=i.filter(function(t){return n._source.hasTile(t)}))):i=[];var o,s=(this._source.roundZoom?Math.round:Math.floor)(this.getZoom(e)),l=Math.max(s-r.maxOverzooming,this._source.minzoom),c=Math.max(s+r.maxUnderzooming,this._source.minzoom),u=this._updateRetainedTiles(i,s),f={};if(Zt(this._source.type))for(var h=Object.keys(u),p=0;p<h.length;p++){var d=h[p],g=u[d],v=n._tiles[d];if(v&&(void 0===v.fadeEndTime||v.fadeEndTime>=a.now())){n._findLoadedChildren(g,c,u)&&(u[d]=g);var m=n.findLoadedParent(g,l,f);m&&n._addTile(m.tileID)}}for(o in f)u[o]||(n._coveredTiles[o]=!0);for(o in f)u[o]=f[o];for(var y=t.keysDifference(this._tiles,u),x=0;x<y.length;x++)n._removeTile(y[x])}},r.prototype._updateRetainedTiles=function(t,e){for(var n={},i={},a=Math.max(e-r.maxOverzooming,this._source.minzoom),o=Math.max(e+r.maxUnderzooming,this._source.minzoom),s=0;s<t.length;s++){var l=t[s],c=this._addTile(l),u=!1;if(c.hasData())n[l.key]=l;else{u=c.wasRequested(),n[l.key]=l;var f=!0;if(e+1>this._source.maxzoom){var h=l.children(this._source.maxzoom)[0],p=this.getTile(h);p&&p.hasData()?n[h.key]=h:f=!1}else{this._findLoadedChildren(l,o,n);for(var d=l.children(this._source.maxzoom),g=0;g<d.length;g++)if(!n[d[g].key]){f=!1;break}}if(!f)for(var v=l.overscaledZ-1;v>=a;--v){var m=l.scaledTo(v);if(i[m.key])break;if(i[m.key]=!0,!(c=this.getTile(m))&&u&&(c=this._addTile(m)),c&&(n[m.key]=m,u=c.wasRequested(),c.hasData()))break}}}return n},r.prototype._addTile=function(e){var r=this._tiles[e.key];if(r)return r;(r=this._cache.getAndRemove(e))&&(this._setTileReloadTimer(e.key,r),r.tileID=e);var n=Boolean(r);return n||(r=new st(e,this._source.tileSize*e.overscaleFactor()),this._loadTile(r,this._tileLoaded.bind(this,r,e.key,r.state))),r?(r.uses++,this._tiles[e.key]=r,n||this._source.fire(new t.Event(\"dataloading\",{tile:r,coord:r.tileID,dataType:\"source\"})),r):null},r.prototype._setTileReloadTimer=function(t,e){var r=this;t in this._timers&&(clearTimeout(this._timers[t]),delete this._timers[t]);var n=e.getExpiryTimeout();n&&(this._timers[t]=setTimeout(function(){r._reloadTile(t,\"expired\"),delete r._timers[t]},n))},r.prototype._removeTile=function(t){var e=this._tiles[t];e&&(e.uses--,delete this._tiles[t],this._timers[t]&&(clearTimeout(this._timers[t]),delete this._timers[t]),e.uses>0||(e.hasData()?this._cache.add(e.tileID,e,e.getExpiryTimeout()):(e.aborted=!0,this._abortTile(e),this._unloadTile(e))))},r.prototype.clearTiles=function(){for(var t in this._shouldReloadOnResume=!1,this._paused=!1,this._tiles)this._removeTile(t);this._cache.reset()},r.prototype.tilesIn=function(e,r){for(var n=[],i=this.getIds(),a=1/0,o=1/0,s=-1/0,l=-1/0,c=e[0].zoom,u=0;u<e.length;u++){var f=e[u];a=Math.min(a,f.column),o=Math.min(o,f.row),s=Math.max(s,f.column),l=Math.max(l,f.row)}for(var h=0;h<i.length;h++){var p=this._tiles[i[h]],d=p.tileID,g=Math.pow(2,this.transform.zoom-p.tileID.overscaledZ),v=r*p.queryPadding*t.default$8/p.tileSize/g,m=[Xt(d,new t.default$17(a,o,c)),Xt(d,new t.default$17(s,l,c))];if(m[0].x-v<t.default$8&&m[0].y-v<t.default$8&&m[1].x+v>=0&&m[1].y+v>=0){for(var y=[],x=0;x<e.length;x++)y.push(Xt(d,e[x]));n.push({tile:p,tileID:d,queryGeometry:[y],scale:g})}}return n},r.prototype.getVisibleCoordinates=function(){for(var t=this,e=this.getRenderableIds().map(function(e){return t._tiles[e].tileID}),r=0,n=e;r<n.length;r+=1){var i=n[r];i.posMatrix=t.transform.calculatePosMatrix(i.toUnwrapped())}return e},r.prototype.hasTransition=function(){if(this._source.hasTransition())return!0;if(Zt(this._source.type))for(var t in this._tiles){var e=this._tiles[t];if(void 0!==e.fadeEndTime&&e.fadeEndTime>=a.now())return!0}return!1},r}(t.Evented);function Xt(e,r){var n=r.zoomTo(e.canonical.z);return new t.default$1((n.column-(e.canonical.x+e.wrap*Math.pow(2,e.canonical.z)))*t.default$8,(n.row-e.canonical.y)*t.default$8)}function Zt(t){return\"raster\"===t||\"image\"===t||\"video\"===t}function $t(){return new t.default.Worker(En.workerUrl)}Wt.maxOverzooming=10,Wt.maxUnderzooming=3;var Jt,Kt=function(){this.active={}};function Qt(e,r){var n={};for(var i in e)\"ref\"!==i&&(n[i]=e[i]);return t.default$18.forEach(function(t){t in r&&(n[t]=r[t])}),n}function te(t){t=t.slice();for(var e=Object.create(null),r=0;r<t.length;r++)e[t[r].id]=t[r];for(var n=0;n<t.length;n++)\"ref\"in t[n]&&(t[n]=Qt(t[n],e[t[n].ref]));return t}Kt.prototype.acquire=function(t){if(!this.workers){var e=En.workerCount;for(this.workers=[];this.workers.length<e;)this.workers.push(new $t)}return this.active[t]=!0,this.workers.slice()},Kt.prototype.release=function(t){delete this.active[t],0===Object.keys(this.active).length&&(this.workers.forEach(function(t){t.terminate()}),this.workers=null)};var ee={setStyle:\"setStyle\",addLayer:\"addLayer\",removeLayer:\"removeLayer\",setPaintProperty:\"setPaintProperty\",setLayoutProperty:\"setLayoutProperty\",setFilter:\"setFilter\",addSource:\"addSource\",removeSource:\"removeSource\",setGeoJSONSourceData:\"setGeoJSONSourceData\",setLayerZoomRange:\"setLayerZoomRange\",setLayerProperty:\"setLayerProperty\",setCenter:\"setCenter\",setZoom:\"setZoom\",setBearing:\"setBearing\",setPitch:\"setPitch\",setSprite:\"setSprite\",setGlyphs:\"setGlyphs\",setTransition:\"setTransition\",setLight:\"setLight\"};function re(t,e,r){r.push({command:ee.addSource,args:[t,e[t]]})}function ne(t,e,r){e.push({command:ee.removeSource,args:[t]}),r[t]=!0}function ie(t,e,r,n){ne(t,r,n),re(t,e,r)}function ae(e,r,n){var i;for(i in e[n])if(e[n].hasOwnProperty(i)&&\"data\"!==i&&!t.default$10(e[n][i],r[n][i]))return!1;for(i in r[n])if(r[n].hasOwnProperty(i)&&\"data\"!==i&&!t.default$10(e[n][i],r[n][i]))return!1;return!0}function oe(e,r,n,i,a,o){var s;for(s in r=r||{},e=e||{})e.hasOwnProperty(s)&&(t.default$10(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}));for(s in r)r.hasOwnProperty(s)&&!e.hasOwnProperty(s)&&(t.default$10(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}))}function se(t){return t.id}function le(t,e){return t[e.id]=e,t}var ce=function(t,e,r){var n=this.boxCells=[],i=this.circleCells=[];this.xCellCount=Math.ceil(t/r),this.yCellCount=Math.ceil(e/r);for(var a=0;a<this.xCellCount*this.yCellCount;a++)n.push([]),i.push([]);this.circleKeys=[],this.boxKeys=[],this.bboxes=[],this.circles=[],this.width=t,this.height=e,this.xScale=this.xCellCount/t,this.yScale=this.yCellCount/e,this.boxUid=0,this.circleUid=0};ce.prototype.keysLength=function(){return this.boxKeys.length+this.circleKeys.length},ce.prototype.insert=function(t,e,r,n,i){this._forEachCell(e,r,n,i,this._insertBoxCell,this.boxUid++),this.boxKeys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(i)},ce.prototype.insertCircle=function(t,e,r,n){this._forEachCell(e-n,r-n,e+n,r+n,this._insertCircleCell,this.circleUid++),this.circleKeys.push(t),this.circles.push(e),this.circles.push(r),this.circles.push(n)},ce.prototype._insertBoxCell=function(t,e,r,n,i,a){this.boxCells[i].push(a)},ce.prototype._insertCircleCell=function(t,e,r,n,i,a){this.circleCells[i].push(a)},ce.prototype._query=function(t,e,r,n,i){if(r<0||t>this.width||n<0||e>this.height)return!i&&[];var a=[];if(t<=0&&e<=0&&this.width<=r&&this.height<=n){if(i)return!0;for(var o=0;o<this.boxKeys.length;o++)a.push({key:this.boxKeys[o],x1:this.bboxes[4*o],y1:this.bboxes[4*o+1],x2:this.bboxes[4*o+2],y2:this.bboxes[4*o+3]});for(var s=0;s<this.circleKeys.length;s++){var l=this.circles[3*s],c=this.circles[3*s+1],u=this.circles[3*s+2];a.push({key:this.circleKeys[s],x1:l-u,y1:c-u,x2:l+u,y2:c+u})}}else{var f={hitTest:i,seenUids:{box:{},circle:{}}};this._forEachCell(t,e,r,n,this._queryCell,a,f)}return i?a.length>0:a},ce.prototype._queryCircle=function(t,e,r,n){var i=t-r,a=t+r,o=e-r,s=e+r;if(a<0||i>this.width||s<0||o>this.height)return!n&&[];var l=[],c={hitTest:n,circle:{x:t,y:e,radius:r},seenUids:{box:{},circle:{}}};return this._forEachCell(i,o,a,s,this._queryCellCircle,l,c),n?l.length>0:l},ce.prototype.query=function(t,e,r,n){return this._query(t,e,r,n,!1)},ce.prototype.hitTest=function(t,e,r,n){return this._query(t,e,r,n,!0)},ce.prototype.hitTestCircle=function(t,e,r){return this._queryCircle(t,e,r,!0)},ce.prototype._queryCell=function(t,e,r,n,i,a,o){var s=o.seenUids,l=this.boxCells[i];if(null!==l)for(var c=this.bboxes,u=0,f=l;u<f.length;u+=1){var h=f[u];if(!s.box[h]){s.box[h]=!0;var p=4*h;if(t<=c[p+2]&&e<=c[p+3]&&r>=c[p+0]&&n>=c[p+1]){if(o.hitTest)return a.push(!0),!0;a.push({key:this.boxKeys[h],x1:c[p],y1:c[p+1],x2:c[p+2],y2:c[p+3]})}}}var d=this.circleCells[i];if(null!==d)for(var g=this.circles,v=0,m=d;v<m.length;v+=1){var y=m[v];if(!s.circle[y]){s.circle[y]=!0;var x=3*y;if(this._circleAndRectCollide(g[x],g[x+1],g[x+2],t,e,r,n)){if(o.hitTest)return a.push(!0),!0;var b=g[x],_=g[x+1],w=g[x+2];a.push({key:this.circleKeys[y],x1:b-w,y1:_-w,x2:b+w,y2:_+w})}}}},ce.prototype._queryCellCircle=function(t,e,r,n,i,a,o){var s=o.circle,l=o.seenUids,c=this.boxCells[i];if(null!==c)for(var u=this.bboxes,f=0,h=c;f<h.length;f+=1){var p=h[f];if(!l.box[p]){l.box[p]=!0;var d=4*p;if(this._circleAndRectCollide(s.x,s.y,s.radius,u[d+0],u[d+1],u[d+2],u[d+3]))return a.push(!0),!0}}var g=this.circleCells[i];if(null!==g)for(var v=this.circles,m=0,y=g;m<y.length;m+=1){var x=y[m];if(!l.circle[x]){l.circle[x]=!0;var b=3*x;if(this._circlesCollide(v[b],v[b+1],v[b+2],s.x,s.y,s.radius))return a.push(!0),!0}}},ce.prototype._forEachCell=function(t,e,r,n,i,a,o){for(var s=this._convertToXCellCoord(t),l=this._convertToYCellCoord(e),c=this._convertToXCellCoord(r),u=this._convertToYCellCoord(n),f=s;f<=c;f++)for(var h=l;h<=u;h++){var p=this.xCellCount*h+f;if(i.call(this,t,e,r,n,p,a,o))return}},ce.prototype._convertToXCellCoord=function(t){return Math.max(0,Math.min(this.xCellCount-1,Math.floor(t*this.xScale)))},ce.prototype._convertToYCellCoord=function(t){return Math.max(0,Math.min(this.yCellCount-1,Math.floor(t*this.yScale)))},ce.prototype._circlesCollide=function(t,e,r,n,i,a){var o=n-t,s=i-e,l=r+a;return l*l>o*o+s*s},ce.prototype._circleAndRectCollide=function(t,e,r,n,i,a,o){var s=(a-n)/2,l=Math.abs(t-(n+s));if(l>s+r)return!1;var c=(o-i)/2,u=Math.abs(e-(i+c));if(u>c+r)return!1;if(l<=s||u<=c)return!0;var f=l-s,h=u-c;return f*f+h*h<=r*r};var ue=t.default$19.layout;function fe(e,r,n,i,a){var o=t.mat4.identity(new Float32Array(16));return r?(t.mat4.identity(o),t.mat4.scale(o,o,[1/a,1/a,1]),n||t.mat4.rotateZ(o,o,i.angle)):(t.mat4.scale(o,o,[i.width/2,-i.height/2,1]),t.mat4.translate(o,o,[1,-1,0]),t.mat4.multiply(o,o,e)),o}function he(e,r,n,i,a){var o=t.mat4.identity(new Float32Array(16));return r?(t.mat4.multiply(o,o,e),t.mat4.scale(o,o,[a,a,1]),n||t.mat4.rotateZ(o,o,-i.angle)):(t.mat4.scale(o,o,[1,-1,1]),t.mat4.translate(o,o,[-1,-1,0]),t.mat4.scale(o,o,[2/i.width,2/i.height,1])),o}function pe(e,r){var n=[e.x,e.y,0,1];ke(n,n,r);var i=n[3];return{point:new t.default$1(n[0]/i,n[1]/i),signedDistanceFromCamera:i}}function de(t,e){var r=t[0]/t[3],n=t[1]/t[3];return r>=-e[0]&&r<=e[0]&&n>=-e[1]&&n<=e[1]}function ge(e,r,n,i,a,o,s,l){var c=i?e.textSizeData:e.iconSizeData,u=t.evaluateSizeForZoom(c,n.transform.zoom,ue.properties[i?\"text-size\":\"icon-size\"]),f=[256/n.width*2+1,256/n.height*2+1],h=i?e.text.dynamicLayoutVertexArray:e.icon.dynamicLayoutVertexArray;h.clear();for(var p=e.lineVertexArray,d=i?e.text.placedSymbolArray:e.icon.placedSymbolArray,g=n.transform.width/n.transform.height,v=!1,m=0;m<d.length;m++){var y=d.get(m);if(y.hidden||y.writingMode===t.WritingMode.vertical&&!v)we(y.numGlyphs,h);else{v=!1;var x=[y.anchorX,y.anchorY,0,1];if(t.vec4.transformMat4(x,x,r),de(x,f)){var b=.5+x[3]/n.transform.cameraToCenterDistance*.5,_=t.evaluateSizeForFeature(c,u,y),w=s?_*b:_/b,k=new t.default$1(y.anchorX,y.anchorY),T=pe(k,a).point,A={},M=ye(y,w,!1,l,r,a,o,e.glyphOffsetArray,p,h,T,k,A,g);v=M.useVertical,(M.notEnoughRoom||v||M.needsFlipping&&ye(y,w,!0,l,r,a,o,e.glyphOffsetArray,p,h,T,k,A,g).notEnoughRoom)&&we(y.numGlyphs,h)}else we(y.numGlyphs,h)}}i?e.text.dynamicLayoutVertexBuffer.updateData(h):e.icon.dynamicLayoutVertexBuffer.updateData(h)}function ve(t,e,r,n,i,a,o,s,l,c,u,f){var h=s.glyphStartIndex+s.numGlyphs,p=s.lineStartIndex,d=s.lineStartIndex+s.lineLength,g=e.getoffsetX(s.glyphStartIndex),v=e.getoffsetX(h-1),m=be(t*g,r,n,i,a,o,s.segment,p,d,l,c,u,f);if(!m)return null;var y=be(t*v,r,n,i,a,o,s.segment,p,d,l,c,u,f);return y?{first:m,last:y}:null}function me(e,r,n,i){return e===t.WritingMode.horizontal&&Math.abs(n.y-r.y)>Math.abs(n.x-r.x)*i?{useVertical:!0}:(e===t.WritingMode.vertical?r.y<n.y:r.x>n.x)?{needsFlipping:!0}:null}function ye(e,r,n,i,a,o,s,l,c,u,f,h,p,d){var g,v=r/24,m=e.lineOffsetX*r,y=e.lineOffsetY*r;if(e.numGlyphs>1){var x=e.glyphStartIndex+e.numGlyphs,b=e.lineStartIndex,_=e.lineStartIndex+e.lineLength,w=ve(v,l,m,y,n,f,h,e,c,o,p,!1);if(!w)return{notEnoughRoom:!0};var k=pe(w.first.point,s).point,T=pe(w.last.point,s).point;if(i&&!n){var A=me(e.writingMode,k,T,d);if(A)return A}g=[w.first];for(var M=e.glyphStartIndex+1;M<x-1;M++)g.push(be(v*l.getoffsetX(M),m,y,n,f,h,e.segment,b,_,c,o,p,!1));g.push(w.last)}else{if(i&&!n){var S=pe(h,a).point,E=e.lineStartIndex+e.segment+1,C=new t.default$1(c.getx(E),c.gety(E)),L=pe(C,a),z=L.signedDistanceFromCamera>0?L.point:xe(h,C,S,1,a),O=me(e.writingMode,S,z,d);if(O)return O}var I=be(v*l.getoffsetX(e.glyphStartIndex),m,y,n,f,h,e.segment,e.lineStartIndex,e.lineStartIndex+e.lineLength,c,o,p,!1);if(!I)return{notEnoughRoom:!0};g=[I]}for(var D=0,P=g;D<P.length;D+=1){var R=P[D];t.addDynamicAttributes(u,R.point,R.angle)}return{}}function xe(t,e,r,n,i){var a=pe(t.add(t.sub(e)._unit()),i).point,o=r.sub(a);return r.add(o._mult(n/o.mag()))}function be(e,r,n,i,a,o,s,l,c,u,f,h,p){var d=i?e-r:e+r,g=d>0?1:-1,v=0;i&&(g*=-1,v=Math.PI),g<0&&(v+=Math.PI);for(var m=g>0?l+s:l+s+1,y=m,x=a,b=a,_=0,w=0,k=Math.abs(d);_+w<=k;){if((m+=g)<l||m>=c)return null;if(b=x,void 0===(x=h[m])){var T=new t.default$1(u.getx(m),u.gety(m)),A=pe(T,f);if(A.signedDistanceFromCamera>0)x=h[m]=A.point;else{var M=m-g;x=xe(0===_?o:new t.default$1(u.getx(M),u.gety(M)),T,b,k-_+1,f)}}_+=w,w=b.dist(x)}var S=(k-_)/w,E=x.sub(b),C=E.mult(S)._add(b);return C._add(E._unit()._perp()._mult(n*g)),{point:C,angle:v+Math.atan2(x.y-b.y,x.x-b.x),tileDistance:p?{prevTileDistance:m-g===y?0:u.gettileUnitDistanceFromAnchor(m-g),lastSegmentViewportDistance:k-_}:null}}var _e=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function we(t,e){for(var r=0;r<t;r++){var n=e.length;e.resize(n+4),e.float32.set(_e,3*n)}}function ke(t,e,r){var n=e[0],i=e[1];return t[0]=r[0]*n+r[4]*i+r[12],t[1]=r[1]*n+r[5]*i+r[13],t[3]=r[3]*n+r[7]*i+r[15],t}t.default$20.mat4;var Te=function(t,e,r){void 0===e&&(e=new ce(t.width+200,t.height+200,25)),void 0===r&&(r=new ce(t.width+200,t.height+200,25)),this.transform=t,this.grid=e,this.ignoredGrid=r,this.pitchfactor=Math.cos(t._pitch)*t.cameraToCenterDistance,this.screenRightBoundary=t.width+100,this.screenBottomBoundary=t.height+100};function Ae(t,e,r){t[e+4]=r?1:0}function Me(e,r,n){return r*(t.default$8/(e.tileSize*Math.pow(2,n-e.tileID.overscaledZ)))}Te.prototype.placeCollisionBox=function(t,e,r,n){var i=this.projectAndGetPerspectiveRatio(n,t.anchorPointX,t.anchorPointY),a=r*i.perspectiveRatio,o=t.x1*a+i.point.x,s=t.y1*a+i.point.y,l=t.x2*a+i.point.x,c=t.y2*a+i.point.y;return!e&&this.grid.hitTest(o,s,l,c)?{box:[],offscreen:!1}:{box:[o,s,l,c],offscreen:this.isOffscreen(o,s,l,c)}},Te.prototype.approximateTileDistance=function(t,e,r,n,i){var a=i?1:n/this.pitchfactor,o=t.lastSegmentViewportDistance*r;return t.prevTileDistance+o+(a-1)*o*Math.abs(Math.sin(e))},Te.prototype.placeCollisionCircles=function(e,r,n,i,a,o,s,l,c,u,f,h,p){var d=[],g=this.projectAnchor(u,o.anchorX,o.anchorY),v=c/24,m=o.lineOffsetX*c,y=o.lineOffsetY*c,x=new t.default$1(o.anchorX,o.anchorY),b=ve(v,l,m,y,!1,pe(x,f).point,x,o,s,f,{},!0),_=!1,w=!0,k=g.perspectiveRatio*i,T=1/(i*n),A=0,M=0;b&&(A=this.approximateTileDistance(b.first.tileDistance,b.first.angle,T,g.cameraDistance,p),M=this.approximateTileDistance(b.last.tileDistance,b.last.angle,T,g.cameraDistance,p));for(var S=0;S<e.length;S+=5){var E=e[S],C=e[S+1],L=e[S+2],z=e[S+3];if(!b||z<-A||z>M)Ae(e,S,!1);else{var O=this.projectPoint(u,E,C),I=L*k;if(d.length>0){var D=O.x-d[d.length-4],P=O.y-d[d.length-3];if(I*I*2>D*D+P*P&&S+8<e.length){var R=e[S+8];if(R>-A&&R<M){Ae(e,S,!1);continue}}}var F=S/5;if(d.push(O.x,O.y,I,F),Ae(e,S,!0),w=w&&this.isOffscreen(O.x-I,O.y-I,O.x+I,O.y+I),!r&&this.grid.hitTestCircle(O.x,O.y,I)){if(!h)return{circles:[],offscreen:!1};_=!0}}}return{circles:_?[]:d,offscreen:w}},Te.prototype.queryRenderedSymbols=function(e){if(0===e.length||0===this.grid.keysLength()&&0===this.ignoredGrid.keysLength())return{};for(var r=[],n=1/0,i=1/0,a=-1/0,o=-1/0,s=0,l=e;s<l.length;s+=1){var c=l[s],u=new t.default$1(c.x+100,c.y+100);n=Math.min(n,u.x),i=Math.min(i,u.y),a=Math.max(a,u.x),o=Math.max(o,u.y),r.push(u)}for(var f={},h={},p=0,d=this.grid.query(n,i,a,o).concat(this.ignoredGrid.query(n,i,a,o));p<d.length;p+=1){var g=d[p],v=g.key;if(void 0===f[v.bucketInstanceId]&&(f[v.bucketInstanceId]={}),!f[v.bucketInstanceId][v.featureIndex]){var m=[new t.default$1(g.x1,g.y1),new t.default$1(g.x2,g.y1),new t.default$1(g.x2,g.y2),new t.default$1(g.x1,g.y2)];t.polygonIntersectsPolygon(r,m)&&(f[v.bucketInstanceId][v.featureIndex]=!0,void 0===h[v.bucketInstanceId]&&(h[v.bucketInstanceId]=[]),h[v.bucketInstanceId].push(v.featureIndex))}}return h},Te.prototype.insertCollisionBox=function(t,e,r,n){var i={bucketInstanceId:r,featureIndex:n};(e?this.ignoredGrid:this.grid).insert(i,t[0],t[1],t[2],t[3])},Te.prototype.insertCollisionCircles=function(t,e,r,n){for(var i=e?this.ignoredGrid:this.grid,a={bucketInstanceId:r,featureIndex:n},o=0;o<t.length;o+=4)i.insertCircle(a,t[o],t[o+1],t[o+2])},Te.prototype.projectAnchor=function(t,e,r){var n=[e,r,0,1];return ke(n,n,t),{perspectiveRatio:.5+this.transform.cameraToCenterDistance/n[3]*.5,cameraDistance:n[3]}},Te.prototype.projectPoint=function(e,r,n){var i=[r,n,0,1];return ke(i,i,e),new t.default$1((i[0]/i[3]+1)/2*this.transform.width+100,(-i[1]/i[3]+1)/2*this.transform.height+100)},Te.prototype.projectAndGetPerspectiveRatio=function(e,r,n){var i=[r,n,0,1];return ke(i,i,e),{point:new t.default$1((i[0]/i[3]+1)/2*this.transform.width+100,(-i[1]/i[3]+1)/2*this.transform.height+100),perspectiveRatio:.5+this.transform.cameraToCenterDistance/i[3]*.5}},Te.prototype.isOffscreen=function(t,e,r,n){return r<100||t>=this.screenRightBoundary||n<100||e>this.screenBottomBoundary};var Se=t.default$19.layout,Ee=function(t,e,r,n){this.opacity=t?Math.max(0,Math.min(1,t.opacity+(t.placed?e:-e))):n&&r?1:0,this.placed=r};Ee.prototype.isHidden=function(){return 0===this.opacity&&!this.placed};var Ce=function(t,e,r,n,i){this.text=new Ee(t?t.text:null,e,r,i),this.icon=new Ee(t?t.icon:null,e,n,i)};Ce.prototype.isHidden=function(){return this.text.isHidden()&&this.icon.isHidden()};var Le=function(t,e,r){this.text=t,this.icon=e,this.skipFade=r},ze=function(t,e){this.transform=t.clone(),this.collisionIndex=new Te(this.transform),this.placements={},this.opacities={},this.stale=!1,this.fadeDuration=e,this.retainedQueryData={}};function Oe(t,e,r){t.emplaceBack(e?1:0,r?1:0),t.emplaceBack(e?1:0,r?1:0),t.emplaceBack(e?1:0,r?1:0),t.emplaceBack(e?1:0,r?1:0)}ze.prototype.placeLayerTile=function(e,r,n,i){var a=r.getBucket(e),o=r.latestFeatureIndex;if(a&&o&&e.id===a.layerIds[0]){var s=r.collisionBoxArray,l=a.layers[0].layout,c=Math.pow(2,this.transform.zoom-r.tileID.overscaledZ),u=r.tileSize/t.default$8,f=this.transform.calculatePosMatrix(r.tileID.toUnwrapped()),h=fe(f,\"map\"===l.get(\"text-pitch-alignment\"),\"map\"===l.get(\"text-rotation-alignment\"),this.transform,Me(r,1,this.transform.zoom)),p=fe(f,\"map\"===l.get(\"icon-pitch-alignment\"),\"map\"===l.get(\"icon-rotation-alignment\"),this.transform,Me(r,1,this.transform.zoom));this.retainedQueryData[a.bucketInstanceId]=new function(t,e,r,n,i){this.bucketInstanceId=t,this.featureIndex=e,this.sourceLayerIndex=r,this.bucketIndex=n,this.tileID=i}(a.bucketInstanceId,o,a.sourceLayerIndex,a.index,r.tileID),this.placeLayerBucket(a,f,h,p,c,u,n,i,s)}},ze.prototype.placeLayerBucket=function(e,r,n,i,a,o,s,l,c){for(var u=e.layers[0].layout,f=t.evaluateSizeForZoom(e.textSizeData,this.transform.zoom,Se.properties[\"text-size\"]),h=!e.hasTextData()||u.get(\"text-optional\"),p=!e.hasIconData()||u.get(\"icon-optional\"),d=0,g=e.symbolInstances;d<g.length;d+=1){var v=g[d];if(!l[v.crossTileID]){var m=void 0!==v.feature.text,y=void 0!==v.feature.icon,x=!0,b=null,_=null,w=null,k=0,T=0;v.collisionArrays||(v.collisionArrays=e.deserializeCollisionBoxes(c,v.textBoxStartIndex,v.textBoxEndIndex,v.iconBoxStartIndex,v.iconBoxEndIndex)),v.collisionArrays.textFeatureIndex&&(k=v.collisionArrays.textFeatureIndex),v.collisionArrays.textBox&&(m=(b=this.collisionIndex.placeCollisionBox(v.collisionArrays.textBox,u.get(\"text-allow-overlap\"),o,r)).box.length>0,x=x&&b.offscreen);var A=v.collisionArrays.textCircles;if(A){var M=e.text.placedSymbolArray.get(v.placedTextSymbolIndices[0]),S=t.evaluateSizeForFeature(e.textSizeData,f,M);_=this.collisionIndex.placeCollisionCircles(A,u.get(\"text-allow-overlap\"),a,o,v.key,M,e.lineVertexArray,e.glyphOffsetArray,S,r,n,s,\"map\"===u.get(\"text-pitch-alignment\")),m=u.get(\"text-allow-overlap\")||_.circles.length>0,x=x&&_.offscreen}v.collisionArrays.iconFeatureIndex&&(T=v.collisionArrays.iconFeatureIndex),v.collisionArrays.iconBox&&(y=(w=this.collisionIndex.placeCollisionBox(v.collisionArrays.iconBox,u.get(\"icon-allow-overlap\"),o,r)).box.length>0,x=x&&w.offscreen),h||p?p?h||(y=y&&m):m=y&&m:y=m=y&&m,m&&b&&this.collisionIndex.insertCollisionBox(b.box,u.get(\"text-ignore-placement\"),e.bucketInstanceId,k),y&&w&&this.collisionIndex.insertCollisionBox(w.box,u.get(\"icon-ignore-placement\"),e.bucketInstanceId,T),m&&_&&this.collisionIndex.insertCollisionCircles(_.circles,u.get(\"text-ignore-placement\"),e.bucketInstanceId,k),this.placements[v.crossTileID]=new Le(m,y,x||e.justReloaded),l[v.crossTileID]=!0}}e.justReloaded=!1},ze.prototype.commit=function(t,e){this.commitTime=e;var r=!1,n=t&&0!==this.fadeDuration?(this.commitTime-t.commitTime)/this.fadeDuration:1,i=t?t.opacities:{};for(var a in this.placements){var o=this.placements[a],s=i[a];s?(this.opacities[a]=new Ce(s,n,o.text,o.icon),r=r||o.text!==s.text.placed||o.icon!==s.icon.placed):(this.opacities[a]=new Ce(null,n,o.text,o.icon,o.skipFade),r=r||o.text||o.icon)}for(var l in i){var c=i[l];if(!this.opacities[l]){var u=new Ce(c,n,!1,!1);u.isHidden()||(this.opacities[l]=u,r=r||c.text.placed||c.icon.placed)}}r?this.lastPlacementChangeTime=e:\"number\"!=typeof this.lastPlacementChangeTime&&(this.lastPlacementChangeTime=t?t.lastPlacementChangeTime:e)},ze.prototype.updateLayerOpacities=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1){var a=i[n],o=a.getBucket(t);o&&a.latestFeatureIndex&&t.id===o.layerIds[0]&&this.updateBucketOpacities(o,r,a.collisionBoxArray)}},ze.prototype.updateBucketOpacities=function(t,e,r){t.hasTextData()&&t.text.opacityVertexArray.clear(),t.hasIconData()&&t.icon.opacityVertexArray.clear(),t.hasCollisionBoxData()&&t.collisionBox.collisionVertexArray.clear(),t.hasCollisionCircleData()&&t.collisionCircle.collisionVertexArray.clear();for(var n=t.layers[0].layout,i=new Ce(null,0,!1,!1,!0),a=new Ce(null,0,n.get(\"text-allow-overlap\"),n.get(\"icon-allow-overlap\"),!0),o=0;o<t.symbolInstances.length;o++){var s=t.symbolInstances[o],l=e[s.crossTileID],c=this.opacities[s.crossTileID];l?c=i:c||(c=a,this.opacities[s.crossTileID]=c),e[s.crossTileID]=!0;var u=s.numGlyphVertices>0||s.numVerticalGlyphVertices>0,f=s.numIconVertices>0;if(u){for(var h=je(c.text),p=(s.numGlyphVertices+s.numVerticalGlyphVertices)/4,d=0;d<p;d++)t.text.opacityVertexArray.emplaceBack(h);for(var g=0,v=s.placedTextSymbolIndices;g<v.length;g+=1){var m=v[g];t.text.placedSymbolArray.get(m).hidden=c.text.isHidden()}}if(f){for(var y=je(c.icon),x=0;x<s.numIconVertices/4;x++)t.icon.opacityVertexArray.emplaceBack(y);t.icon.placedSymbolArray.get(o).hidden=c.icon.isHidden()}s.collisionArrays||(s.collisionArrays=t.deserializeCollisionBoxes(r,s.textBoxStartIndex,s.textBoxEndIndex,s.iconBoxStartIndex,s.iconBoxEndIndex));var b=s.collisionArrays;if(b){b.textBox&&t.hasCollisionBoxData()&&Oe(t.collisionBox.collisionVertexArray,c.text.placed,!1),b.iconBox&&t.hasCollisionBoxData()&&Oe(t.collisionBox.collisionVertexArray,c.icon.placed,!1);var _=b.textCircles;if(_&&t.hasCollisionCircleData())for(var w=0;w<_.length;w+=5){var k=l||0===_[w+4];Oe(t.collisionCircle.collisionVertexArray,c.text.placed,k)}}}t.sortFeatures(this.transform.angle),this.retainedQueryData[t.bucketInstanceId]&&(this.retainedQueryData[t.bucketInstanceId].featureSortOrder=t.featureSortOrder),t.hasTextData()&&t.text.opacityVertexBuffer&&t.text.opacityVertexBuffer.updateData(t.text.opacityVertexArray),t.hasIconData()&&t.icon.opacityVertexBuffer&&t.icon.opacityVertexBuffer.updateData(t.icon.opacityVertexArray),t.hasCollisionBoxData()&&t.collisionBox.collisionVertexBuffer&&t.collisionBox.collisionVertexBuffer.updateData(t.collisionBox.collisionVertexArray),t.hasCollisionCircleData()&&t.collisionCircle.collisionVertexBuffer&&t.collisionCircle.collisionVertexBuffer.updateData(t.collisionCircle.collisionVertexArray)},ze.prototype.symbolFadeChange=function(t){return 0===this.fadeDuration?1:(t-this.commitTime)/this.fadeDuration},ze.prototype.hasTransitions=function(t){return this.stale||t-this.lastPlacementChangeTime<this.fadeDuration},ze.prototype.stillRecent=function(t){return\"undefined\"!==this.commitTime&&this.commitTime+this.fadeDuration>t},ze.prototype.setStale=function(){this.stale=!0};var Ie=Math.pow(2,25),De=Math.pow(2,24),Pe=Math.pow(2,17),Re=Math.pow(2,16),Fe=Math.pow(2,9),Be=Math.pow(2,8),Ne=Math.pow(2,1);function je(t){if(0===t.opacity&&!t.placed)return 0;if(1===t.opacity&&t.placed)return 4294967295;var e=t.placed?1:0,r=Math.floor(127*t.opacity);return r*Ie+e*De+r*Pe+e*Re+r*Fe+e*Be+r*Ne+e}var Ve=function(){this._currentTileIndex=0,this._seenCrossTileIDs={}};Ve.prototype.continuePlacement=function(t,e,r,n,i){for(;this._currentTileIndex<t.length;){var a=t[this._currentTileIndex];if(e.placeLayerTile(n,a,r,this._seenCrossTileIDs),this._currentTileIndex++,i())return!0}};var Ue=function(t,e,r,n,i){this.placement=new ze(t,i),this._currentPlacementIndex=e.length-1,this._forceFullPlacement=r,this._showCollisionBoxes=n,this._done=!1};Ue.prototype.isDone=function(){return this._done},Ue.prototype.continuePlacement=function(t,e,r){for(var n=this,i=a.now(),o=function(){var t=a.now()-i;return!n._forceFullPlacement&&t>2};this._currentPlacementIndex>=0;){var s=e[t[n._currentPlacementIndex]],l=n.placement.collisionIndex.transform.zoom;if(\"symbol\"===s.type&&(!s.minzoom||s.minzoom<=l)&&(!s.maxzoom||s.maxzoom>l)){if(n._inProgressLayer||(n._inProgressLayer=new Ve),n._inProgressLayer.continuePlacement(r[s.source],n.placement,n._showCollisionBoxes,s,o))return;delete n._inProgressLayer}n._currentPlacementIndex--}this._done=!0},Ue.prototype.commit=function(t,e){return this.placement.commit(t,e),this.placement};var He=512/t.default$8/2,qe=function(t,e,r){this.tileID=t,this.indexedSymbolInstances={},this.bucketInstanceId=r;for(var n=0,i=e;n<i.length;n+=1){var a=i[n],o=a.key;this.indexedSymbolInstances[o]||(this.indexedSymbolInstances[o]=[]),this.indexedSymbolInstances[o].push({crossTileID:a.crossTileID,coord:this.getScaledCoordinates(a,t)})}};qe.prototype.getScaledCoordinates=function(e,r){var n=r.canonical.z-this.tileID.canonical.z,i=He/Math.pow(2,n),a=e.anchor;return{x:Math.floor((r.canonical.x*t.default$8+a.x)*i),y:Math.floor((r.canonical.y*t.default$8+a.y)*i)}},qe.prototype.findMatches=function(t,e,r){for(var n=this.tileID.canonical.z<e.canonical.z?1:Math.pow(2,this.tileID.canonical.z-e.canonical.z),i=0,a=t;i<a.length;i+=1){var o=a[i];if(!o.crossTileID){var s=this.indexedSymbolInstances[o.key];if(s)for(var l=this.getScaledCoordinates(o,e),c=0,u=s;c<u.length;c+=1){var f=u[c];if(Math.abs(f.coord.x-l.x)<=n&&Math.abs(f.coord.y-l.y)<=n&&!r[f.crossTileID]){r[f.crossTileID]=!0,o.crossTileID=f.crossTileID;break}}}}};var Ge=function(){this.maxCrossTileID=0};Ge.prototype.generate=function(){return++this.maxCrossTileID};var Ye=function(){this.indexes={},this.usedCrossTileIDs={},this.lng=0};Ye.prototype.handleWrapJump=function(t){var e=Math.round((t-this.lng)/360);if(0!==e)for(var r in this.indexes){var n=this.indexes[r],i={};for(var a in n){var o=n[a];o.tileID=o.tileID.unwrapTo(o.tileID.wrap+e),i[o.tileID.key]=o}this.indexes[r]=i}this.lng=t},Ye.prototype.addBucket=function(t,e,r){if(this.indexes[t.overscaledZ]&&this.indexes[t.overscaledZ][t.key]){if(this.indexes[t.overscaledZ][t.key].bucketInstanceId===e.bucketInstanceId)return!1;this.removeBucketCrossTileIDs(t.overscaledZ,this.indexes[t.overscaledZ][t.key])}for(var n=0,i=e.symbolInstances;n<i.length;n+=1)i[n].crossTileID=0;this.usedCrossTileIDs[t.overscaledZ]||(this.usedCrossTileIDs[t.overscaledZ]={});var a=this.usedCrossTileIDs[t.overscaledZ];for(var o in this.indexes){var s=this.indexes[o];if(Number(o)>t.overscaledZ)for(var l in s){var c=s[l];c.tileID.isChildOf(t)&&c.findMatches(e.symbolInstances,t,a)}else{var u=s[t.scaledTo(Number(o)).key];u&&u.findMatches(e.symbolInstances,t,a)}}for(var f=0,h=e.symbolInstances;f<h.length;f+=1){var p=h[f];p.crossTileID||(p.crossTileID=r.generate(),a[p.crossTileID]=!0)}return void 0===this.indexes[t.overscaledZ]&&(this.indexes[t.overscaledZ]={}),this.indexes[t.overscaledZ][t.key]=new qe(t,e.symbolInstances,e.bucketInstanceId),!0},Ye.prototype.removeBucketCrossTileIDs=function(t,e){for(var r in e.indexedSymbolInstances)for(var n=0,i=e.indexedSymbolInstances[r];n<i.length;n+=1){var a=i[n];delete this.usedCrossTileIDs[t][a.crossTileID]}},Ye.prototype.removeStaleBuckets=function(t){var e=!1;for(var r in this.indexes){var n=this.indexes[r];for(var i in n)t[n[i].bucketInstanceId]||(this.removeBucketCrossTileIDs(r,n[i]),delete n[i],e=!0)}return e};var We=function(){this.layerIndexes={},this.crossTileIDs=new Ge,this.maxBucketInstanceId=0,this.bucketsInCurrentPlacement={}};We.prototype.addLayer=function(t,e,r){var n=this.layerIndexes[t.id];void 0===n&&(n=this.layerIndexes[t.id]=new Ye);var i=!1,a={};n.handleWrapJump(r);for(var o=0,s=e;o<s.length;o+=1){var l=s[o],c=l.getBucket(t);c&&t.id===c.layerIds[0]&&(c.bucketInstanceId||(c.bucketInstanceId=++this.maxBucketInstanceId),n.addBucket(l.tileID,c,this.crossTileIDs)&&(i=!0),a[c.bucketInstanceId]=!0)}return n.removeStaleBuckets(a)&&(i=!0),i},We.prototype.pruneUnusedLayers=function(t){var e={};for(var r in t.forEach(function(t){e[t]=!0}),this.layerIndexes)e[r]||delete this.layerIndexes[r]};var Xe=function(e,r){return t.emitValidationErrors(e,r&&r.filter(function(t){return\"source.canvas\"!==t.identifier}))},Ze=t.pick(ee,[\"addLayer\",\"removeLayer\",\"setPaintProperty\",\"setLayoutProperty\",\"setFilter\",\"addSource\",\"removeSource\",\"setLayerZoomRange\",\"setLight\",\"setTransition\",\"setGeoJSONSourceData\"]),$e=t.pick(ee,[\"setCenter\",\"setZoom\",\"setBearing\",\"setPitch\"]),Je=function(e){function r(n,i){var a=this;void 0===i&&(i={}),e.call(this),this.map=n,this.dispatcher=new H((Jt||(Jt=new Kt),Jt),this),this.imageManager=new O,this.glyphManager=new B(n._transformRequest,i.localIdeographFontFamily),this.lineAtlas=new U(256,512),this.crossTileSymbolIndex=new We,this._layers={},this._order=[],this.sourceCaches={},this.zoomHistory=new t.default$23,this._loaded=!1,this._resetUpdates();var o=this;this._rtlTextPluginCallback=r.registerForPluginAvailability(function(t){for(var e in o.dispatcher.broadcast(\"loadRTLTextPlugin\",t.pluginURL,t.completionCallback),o.sourceCaches)o.sourceCaches[e].reload()}),this.on(\"data\",function(t){if(\"source\"===t.dataType&&\"metadata\"===t.sourceDataType){var e=a.sourceCaches[t.sourceId];if(e){var r=e.getSource();if(r&&r.vectorLayerIds)for(var n in a._layers){var i=a._layers[n];i.source===r.id&&a._validateLayer(i)}}}})}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadURL=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"}));var i=\"boolean\"==typeof r.validate?r.validate:!x(e);e=function(t,e){if(!x(t))return t;var r=A(t);return r.path=\"/styles/v1\"+r.path,y(r,e)}(e,r.accessToken);var a=this.map._transformRequest(e,t.ResourceType.Style);t.getJSON(a,function(e,r){e?n.fire(new t.ErrorEvent(e)):r&&n._load(r,i)})},r.prototype.loadJSON=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),a.frame(function(){n._load(e,!1!==r.validate)})},r.prototype._load=function(e,r){var n=this;if(!r||!Xe(this,t.validateStyle(e))){for(var i in this._loaded=!0,this.stylesheet=e,e.sources)n.addSource(i,e.sources[i],{validate:!1});e.sprite?function(e,r,n){var i,o,s,l=a.devicePixelRatio>1?\"@2x\":\"\";function c(){if(s)n(s);else if(i&&o){var e=a.getImageData(o),r={};for(var l in i){var c=i[l],u=c.width,f=c.height,h=c.x,p=c.y,d=c.sdf,g=c.pixelRatio,v=new t.RGBAImage({width:u,height:f});t.RGBAImage.copy(e,v,{x:h,y:p},{x:0,y:0},{width:u,height:f}),r[l]={data:v,pixelRatio:g,sdf:d}}n(null,r)}}t.getJSON(r(_(e,l,\".json\"),t.ResourceType.SpriteJSON),function(t,e){s||(s=t,i=e,c())}),t.getImage(r(_(e,l,\".png\"),t.ResourceType.SpriteImage),function(t,e){s||(s=t,o=e,c())})}(e.sprite,this.map._transformRequest,function(e,r){if(e)n.fire(new t.ErrorEvent(e));else if(r)for(var i in r)n.imageManager.addImage(i,r[i]);n.imageManager.setLoaded(!0),n.fire(new t.Event(\"data\",{dataType:\"style\"}))}):this.imageManager.setLoaded(!0),this.glyphManager.setURL(e.glyphs);var o=te(this.stylesheet.layers);this._order=o.map(function(t){return t.id}),this._layers={};for(var s=0,l=o;s<l.length;s+=1){var c=l[s];(c=t.default$22(c)).setEventedParent(n,{layer:{id:c.id}}),n._layers[c.id]=c}this.dispatcher.broadcast(\"setLayers\",this._serializeLayers(this._order)),this.light=new V(this.stylesheet.light),this.fire(new t.Event(\"data\",{dataType:\"style\"})),this.fire(new t.Event(\"style.load\"))}},r.prototype._validateLayer=function(e){var r=this.sourceCaches[e.source];if(r){var n=e.sourceLayer;if(n){var i=r.getSource();(\"geojson\"===i.type||i.vectorLayerIds&&-1===i.vectorLayerIds.indexOf(n))&&this.fire(new t.ErrorEvent(new Error('Source layer \"'+n+'\" does not exist on source \"'+i.id+'\" as specified by style layer \"'+e.id+'\"')))}}},r.prototype.loaded=function(){if(!this._loaded)return!1;if(Object.keys(this._updatedSources).length)return!1;for(var t in this.sourceCaches)if(!this.sourceCaches[t].loaded())return!1;return!!this.imageManager.isLoaded()},r.prototype._serializeLayers=function(t){var e=this;return t.map(function(t){return e._layers[t].serialize()})},r.prototype.hasTransitions=function(){if(this.light&&this.light.hasTransition())return!0;for(var t in this.sourceCaches)if(this.sourceCaches[t].hasTransition())return!0;for(var e in this._layers)if(this._layers[e].hasTransition())return!0;return!1},r.prototype._checkLoaded=function(){if(!this._loaded)throw new Error(\"Style is not done loading\")},r.prototype.update=function(e){if(this._loaded){if(this._changed){var r=Object.keys(this._updatedLayers),n=Object.keys(this._removedLayers);for(var i in(r.length||n.length)&&this._updateWorkerLayers(r,n),this._updatedSources){var a=this._updatedSources[i];\"reload\"===a?this._reloadSource(i):\"clear\"===a&&this._clearSource(i)}for(var o in this._updatedPaintProps)this._layers[o].updateTransitions(e);this.light.updateTransitions(e),this._resetUpdates(),this.fire(new t.Event(\"data\",{dataType:\"style\"}))}for(var s in this.sourceCaches)this.sourceCaches[s].used=!1;for(var l=0,c=this._order;l<c.length;l+=1){var u=c[l],f=this._layers[u];f.recalculate(e),!f.isHidden(e.zoom)&&f.source&&(this.sourceCaches[f.source].used=!0)}this.light.recalculate(e),this.z=e.zoom}},r.prototype._updateWorkerLayers=function(t,e){this.dispatcher.broadcast(\"updateLayers\",{layers:this._serializeLayers(t),removedIds:e})},r.prototype._resetUpdates=function(){this._changed=!1,this._updatedLayers={},this._removedLayers={},this._updatedSources={},this._updatedPaintProps={}},r.prototype.setState=function(e){var r=this;if(this._checkLoaded(),Xe(this,t.validateStyle(e)))return!1;(e=t.clone(e)).layers=te(e.layers);var n=function(e,r){if(!e)return[{command:ee.setStyle,args:[r]}];var n=[];try{if(!t.default$10(e.version,r.version))return[{command:ee.setStyle,args:[r]}];t.default$10(e.center,r.center)||n.push({command:ee.setCenter,args:[r.center]}),t.default$10(e.zoom,r.zoom)||n.push({command:ee.setZoom,args:[r.zoom]}),t.default$10(e.bearing,r.bearing)||n.push({command:ee.setBearing,args:[r.bearing]}),t.default$10(e.pitch,r.pitch)||n.push({command:ee.setPitch,args:[r.pitch]}),t.default$10(e.sprite,r.sprite)||n.push({command:ee.setSprite,args:[r.sprite]}),t.default$10(e.glyphs,r.glyphs)||n.push({command:ee.setGlyphs,args:[r.glyphs]}),t.default$10(e.transition,r.transition)||n.push({command:ee.setTransition,args:[r.transition]}),t.default$10(e.light,r.light)||n.push({command:ee.setLight,args:[r.light]});var i={},a=[];!function(e,r,n,i){var a;for(a in r=r||{},e=e||{})e.hasOwnProperty(a)&&(r.hasOwnProperty(a)||ne(a,n,i));for(a in r)r.hasOwnProperty(a)&&(e.hasOwnProperty(a)?t.default$10(e[a],r[a])||(\"geojson\"===e[a].type&&\"geojson\"===r[a].type&&ae(e,r,a)?n.push({command:ee.setGeoJSONSourceData,args:[a,r[a].data]}):ie(a,r,n,i)):re(a,r,n))}(e.sources,r.sources,a,i);var o=[];e.layers&&e.layers.forEach(function(t){i[t.source]?n.push({command:ee.removeLayer,args:[t.id]}):o.push(t)}),n=n.concat(a),function(e,r,n){r=r||[];var i,a,o,s,l,c,u,f=(e=e||[]).map(se),h=r.map(se),p=e.reduce(le,{}),d=r.reduce(le,{}),g=f.slice(),v=Object.create(null);for(i=0,a=0;i<f.length;i++)o=f[i],d.hasOwnProperty(o)?a++:(n.push({command:ee.removeLayer,args:[o]}),g.splice(g.indexOf(o,a),1));for(i=0,a=0;i<h.length;i++)o=h[h.length-1-i],g[g.length-1-i]!==o&&(p.hasOwnProperty(o)?(n.push({command:ee.removeLayer,args:[o]}),g.splice(g.lastIndexOf(o,g.length-a),1)):a++,c=g[g.length-i],n.push({command:ee.addLayer,args:[d[o],c]}),g.splice(g.length-i,0,o),v[o]=!0);for(i=0;i<h.length;i++)if(s=p[o=h[i]],l=d[o],!v[o]&&!t.default$10(s,l))if(t.default$10(s.source,l.source)&&t.default$10(s[\"source-layer\"],l[\"source-layer\"])&&t.default$10(s.type,l.type)){for(u in oe(s.layout,l.layout,n,o,null,ee.setLayoutProperty),oe(s.paint,l.paint,n,o,null,ee.setPaintProperty),t.default$10(s.filter,l.filter)||n.push({command:ee.setFilter,args:[o,l.filter]}),t.default$10(s.minzoom,l.minzoom)&&t.default$10(s.maxzoom,l.maxzoom)||n.push({command:ee.setLayerZoomRange,args:[o,l.minzoom,l.maxzoom]}),s)s.hasOwnProperty(u)&&\"layout\"!==u&&\"paint\"!==u&&\"filter\"!==u&&\"metadata\"!==u&&\"minzoom\"!==u&&\"maxzoom\"!==u&&(0===u.indexOf(\"paint.\")?oe(s[u],l[u],n,o,u.slice(6),ee.setPaintProperty):t.default$10(s[u],l[u])||n.push({command:ee.setLayerProperty,args:[o,u,l[u]]}));for(u in l)l.hasOwnProperty(u)&&!s.hasOwnProperty(u)&&\"layout\"!==u&&\"paint\"!==u&&\"filter\"!==u&&\"metadata\"!==u&&\"minzoom\"!==u&&\"maxzoom\"!==u&&(0===u.indexOf(\"paint.\")?oe(s[u],l[u],n,o,u.slice(6),ee.setPaintProperty):t.default$10(s[u],l[u])||n.push({command:ee.setLayerProperty,args:[o,u,l[u]]}))}else n.push({command:ee.removeLayer,args:[o]}),c=g[g.lastIndexOf(o)+1],n.push({command:ee.addLayer,args:[l,c]})}(o,r.layers,n)}catch(t){console.warn(\"Unable to compute style diff:\",t),n=[{command:ee.setStyle,args:[r]}]}return n}(this.serialize(),e).filter(function(t){return!(t.command in $e)});if(0===n.length)return!1;var i=n.filter(function(t){return!(t.command in Ze)});if(i.length>0)throw new Error(\"Unimplemented: \"+i.map(function(t){return t.command}).join(\", \")+\".\");return n.forEach(function(t){\"setTransition\"!==t.command&&r[t.command].apply(r,t.args)}),this.stylesheet=e,!0},r.prototype.addImage=function(e,r){if(this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"An image with this name already exists.\")));this.imageManager.addImage(e,r),this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.getImage=function(t){return this.imageManager.getImage(t)},r.prototype.removeImage=function(e){if(!this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"No image with this name exists.\")));this.imageManager.removeImage(e),this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.addSource=function(e,r,n){var i=this;if(this._checkLoaded(),void 0!==this.sourceCaches[e])throw new Error(\"There is already a source with this ID\");if(!r.type)throw new Error(\"The type property must be defined, but the only the following properties were given: \"+Object.keys(r).join(\", \")+\".\");if(!([\"vector\",\"raster\",\"geojson\",\"video\",\"image\"].indexOf(r.type)>=0&&this._validate(t.validateStyle.source,\"sources.\"+e,r,null,n))){this.map&&this.map._collectResourceTiming&&(r.collectResourceTiming=!0);var a=this.sourceCaches[e]=new Wt(e,r,this.dispatcher);a.style=this,a.setEventedParent(this,function(){return{isSourceLoaded:i.loaded(),source:a.serialize(),sourceId:e}}),a.onAdd(this.map),this._changed=!0}},r.prototype.removeSource=function(e){if(this._checkLoaded(),void 0===this.sourceCaches[e])throw new Error(\"There is no source with this ID\");for(var r in this._layers)if(this._layers[r].source===e)return this.fire(new t.ErrorEvent(new Error('Source \"'+e+'\" cannot be removed while layer \"'+r+'\" is using it.')));var n=this.sourceCaches[e];delete this.sourceCaches[e],delete this._updatedSources[e],n.fire(new t.Event(\"data\",{sourceDataType:\"metadata\",dataType:\"source\",sourceId:e})),n.setEventedParent(null),n.clearTiles(),n.onRemove&&n.onRemove(this.map),this._changed=!0},r.prototype.setGeoJSONSourceData=function(t,e){this._checkLoaded(),this.sourceCaches[t].getSource().setData(e),this._changed=!0},r.prototype.getSource=function(t){return this.sourceCaches[t]&&this.sourceCaches[t].getSource()},r.prototype.addLayer=function(e,r,n){this._checkLoaded();var i=e.id;if(this.getLayer(i))this.fire(new t.ErrorEvent(new Error('Layer with id \"'+i+'\" already exists on this map')));else if(\"object\"==typeof e.source&&(this.addSource(i,e.source),e=t.clone(e),e=t.extend(e,{source:i})),!this._validate(t.validateStyle.layer,\"layers.\"+i,e,{arrayIndex:-1},n)){var a=t.default$22(e);this._validateLayer(a),a.setEventedParent(this,{layer:{id:i}});var o=r?this._order.indexOf(r):this._order.length;if(r&&-1===o)this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.')));else{if(this._order.splice(o,0,i),this._layerOrderChanged=!0,this._layers[i]=a,this._removedLayers[i]&&a.source){var s=this._removedLayers[i];delete this._removedLayers[i],s.type!==a.type?this._updatedSources[a.source]=\"clear\":(this._updatedSources[a.source]=\"reload\",this.sourceCaches[a.source].pause())}this._updateLayer(a)}}},r.prototype.moveLayer=function(e,r){if(this._checkLoaded(),this._changed=!0,this._layers[e]){if(e!==r){var n=this._order.indexOf(e);this._order.splice(n,1);var i=r?this._order.indexOf(r):this._order.length;r&&-1===i?this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.'))):(this._order.splice(i,0,e),this._layerOrderChanged=!0)}}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be moved.\")))},r.prototype.removeLayer=function(e){this._checkLoaded();var r=this._layers[e];if(r){r.setEventedParent(null);var n=this._order.indexOf(e);this._order.splice(n,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[e]=r,delete this._layers[e],delete this._updatedLayers[e],delete this._updatedPaintProps[e]}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be removed.\")))},r.prototype.getLayer=function(t){return this._layers[t]},r.prototype.setLayerZoomRange=function(e,r,n){this._checkLoaded();var i=this.getLayer(e);i?i.minzoom===r&&i.maxzoom===n||(null!=r&&(i.minzoom=r),null!=n&&(i.maxzoom=n),this._updateLayer(i)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot have zoom extent.\")))},r.prototype.setFilter=function(e,r){this._checkLoaded();var n=this.getLayer(e);if(n){if(!t.default$10(n.filter,r))return null==r?(n.filter=void 0,void this._updateLayer(n)):void(this._validate(t.validateStyle.filter,\"layers.\"+n.id+\".filter\",r)||(n.filter=t.clone(r),this._updateLayer(n)))}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be filtered.\")))},r.prototype.getFilter=function(e){return t.clone(this.getLayer(e).filter)},r.prototype.setLayoutProperty=function(e,r,n){this._checkLoaded();var i=this.getLayer(e);i?t.default$10(i.getLayoutProperty(r),n)||(i.setLayoutProperty(r,n),this._updateLayer(i)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getLayoutProperty=function(t,e){return this.getLayer(t).getLayoutProperty(e)},r.prototype.setPaintProperty=function(e,r,n){this._checkLoaded();var i=this.getLayer(e);if(i){if(!t.default$10(i.getPaintProperty(r),n)){var a=i._transitionablePaint._values[r].value.isDataDriven();i.setPaintProperty(r,n),(i._transitionablePaint._values[r].value.isDataDriven()||a)&&this._updateLayer(i),this._changed=!0,this._updatedPaintProps[e]=!0}}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getPaintProperty=function(t,e){return this.getLayer(t).getPaintProperty(e)},r.prototype.getTransition=function(){return t.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},r.prototype.serialize=function(){var e=this;return t.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:t.mapObject(this.sourceCaches,function(t){return t.serialize()}),layers:this._order.map(function(t){return e._layers[t].serialize()})},function(t){return void 0!==t})},r.prototype._updateLayer=function(t){this._updatedLayers[t.id]=!0,t.source&&!this._updatedSources[t.source]&&(this._updatedSources[t.source]=\"reload\",this.sourceCaches[t.source].pause()),this._changed=!0},r.prototype._flattenRenderedFeatures=function(t){for(var e=[],r=this._order.length-1;r>=0;r--)for(var n=this._order[r],i=0,a=t;i<a.length;i+=1){var o=a[i][n];if(o)for(var s=0,l=o;s<l.length;s+=1){var c=l[s];e.push(c)}}return e},r.prototype.queryRenderedFeatures=function(e,r,n){r&&r.filter&&this._validate(t.validateStyle.filter,\"queryRenderedFeatures.filter\",r.filter);var i={};if(r&&r.layers){if(!Array.isArray(r.layers))return this.fire(new t.ErrorEvent(new Error(\"parameters.layers must be an Array.\"))),[];for(var a=0,o=r.layers;a<o.length;a+=1){var s=o[a],l=this._layers[s];if(!l)return this.fire(new t.ErrorEvent(new Error(\"The layer '\"+s+\"' does not exist in the map's style and cannot be queried for features.\"))),[];i[l.source]=!0}}var c=[];for(var u in this.sourceCaches)r.layers&&!i[u]||c.push(at(this.sourceCaches[u],this._layers,e.worldCoordinate,r,n));return this.placement&&c.push(function(t,e,r,n,i){for(var a={},o=n.queryRenderedSymbols(e),s=[],l=0,c=Object.keys(o).map(Number);l<c.length;l+=1){var u=c[l];s.push(i[u])}s.sort(ot);for(var f=function(){var e=p[h],n=e.featureIndex.lookupSymbolFeatures(o[e.bucketInstanceId],e.bucketIndex,e.sourceLayerIndex,r.filter,r.layers,t);for(var i in n){var s=a[i]=a[i]||[],l=n[i];l.sort(function(t,r){var n=e.featureSortOrder;if(n){var i=n.indexOf(t.featureIndex);return n.indexOf(r.featureIndex)-i}return r.featureIndex-t.featureIndex});for(var c=0,u=l;c<u.length;c+=1){var f=u[c];s.push(f.feature)}}},h=0,p=s;h<p.length;h+=1)f();return a}(this._layers,e.viewport,r,this.placement.collisionIndex,this.placement.retainedQueryData)),this._flattenRenderedFeatures(c)},r.prototype.querySourceFeatures=function(e,r){r&&r.filter&&this._validate(t.validateStyle.filter,\"querySourceFeatures.filter\",r.filter);var n=this.sourceCaches[e];return n?function(t,e){for(var r=t.getRenderableIds().map(function(e){return t.getTileByID(e)}),n=[],i={},a=0;a<r.length;a++){var o=r[a],s=o.tileID.canonical.key;i[s]||(i[s]=!0,o.querySourceFeatures(n,e))}return n}(n,r):[]},r.prototype.addSourceType=function(t,e,n){return r.getSourceType(t)?n(new Error('A source type called \"'+t+'\" already exists.')):(r.setSourceType(t,e),e.workerSourceURL?void this.dispatcher.broadcast(\"loadWorkerSource\",{name:t,url:e.workerSourceURL},n):n(null,null))},r.prototype.getLight=function(){return this.light.getLight()},r.prototype.setLight=function(e){this._checkLoaded();var r=this.light.getLight(),n=!1;for(var i in e)if(!t.default$10(e[i],r[i])){n=!0;break}if(n){var o={now:a.now(),transition:t.extend({duration:300,delay:0},this.stylesheet.transition)};this.light.setLight(e),this.light.updateTransitions(o)}},r.prototype._validate=function(e,r,n,i,a){return(!a||!1!==a.validate)&&Xe(this,e.call(t.validateStyle,t.extend({key:r,style:this.serialize(),value:n,styleSpec:t.default$5},i)))},r.prototype._remove=function(){for(var e in t.evented.off(\"pluginAvailable\",this._rtlTextPluginCallback),this.sourceCaches)this.sourceCaches[e].clearTiles();this.dispatcher.remove()},r.prototype._clearSource=function(t){this.sourceCaches[t].clearTiles()},r.prototype._reloadSource=function(t){this.sourceCaches[t].resume(),this.sourceCaches[t].reload()},r.prototype._updateSources=function(t){for(var e in this.sourceCaches)this.sourceCaches[e].update(t)},r.prototype._generateCollisionBoxes=function(){for(var t in this.sourceCaches)this._reloadSource(t)},r.prototype._updatePlacement=function(t,e,r){for(var n=!1,i=!1,o={},s=0,l=this._order;s<l.length;s+=1){var c=l[s],u=this._layers[c];if(\"symbol\"===u.type){if(!o[u.source]){var f=this.sourceCaches[u.source];o[u.source]=f.getRenderableIds().map(function(t){return f.getTileByID(t)}).sort(function(t,e){return e.tileID.overscaledZ-t.tileID.overscaledZ||(t.tileID.isLessThan(e.tileID)?-1:1)})}var h=this.crossTileSymbolIndex.addLayer(u,o[u.source],t.center.lng);n=n||h}}this.crossTileSymbolIndex.pruneUnusedLayers(this._order);var p=this._layerOrderChanged;if((p||!this.pauseablePlacement||this.pauseablePlacement.isDone()&&!this.placement.stillRecent(a.now()))&&(this.pauseablePlacement=new Ue(t,this._order,p,e,r),this._layerOrderChanged=!1),this.pauseablePlacement.isDone()?this.placement.setStale():(this.pauseablePlacement.continuePlacement(this._order,this._layers,o),this.pauseablePlacement.isDone()&&(this.placement=this.pauseablePlacement.commit(this.placement,a.now()),i=!0),n&&this.pauseablePlacement.placement.setStale()),i||n)for(var d=0,g=this._order;d<g.length;d+=1){var v=g[d],m=this._layers[v];\"symbol\"===m.type&&this.placement.updateLayerOpacities(m,o[m.source])}return!this.pauseablePlacement.isDone()||this.placement.hasTransitions(a.now())},r.prototype.getImages=function(t,e,r){this.imageManager.getImages(e.icons,r)},r.prototype.getGlyphs=function(t,e,r){this.glyphManager.getGlyphs(e.stacks,r)},r}(t.Evented);Je.getSourceType=function(t){return nt[t]},Je.setSourceType=function(t,e){nt[t]=e},Je.registerForPluginAvailability=t.registerForPluginAvailability;var Ke=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2}]),Qe={prelude:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n\\n#if !defined(highp)\\n#define highp\\n#endif\\n\\n#endif\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n\\n#if !defined(highp)\\n#define highp\\n#endif\\n\\n#endif\\n\\n// Unpack a pair of values that have been packed into a single float.\\n// The packed values are assumed to be 8-bit unsigned integers, and are\\n// packed like so:\\n// packedValue = floor(input[0]) * 256 + input[1],\\nvec2 unpack_float(const float packedValue) {\\n int packedIntValue = int(packedValue);\\n int v0 = packedIntValue / 256;\\n return vec2(v0, packedIntValue - v0 * 256);\\n}\\n\\nvec2 unpack_opacity(const float packedOpacity) {\\n int intOpacity = int(packedOpacity) / 2;\\n return vec2(float(intOpacity) / 127.0, mod(packedOpacity, 2.0));\\n}\\n\\n// To minimize the number of attributes needed, we encode a 4-component\\n// color into a pair of floats (i.e. a vec2) as follows:\\n// [ floor(color.r * 255) * 256 + color.g * 255,\\n// floor(color.b * 255) * 256 + color.g * 255 ]\\nvec4 decode_color(const vec2 encodedColor) {\\n return vec4(\\n unpack_float(encodedColor[0]) / 255.0,\\n unpack_float(encodedColor[1]) / 255.0\\n );\\n}\\n\\n// Unpack a pair of paint values and interpolate between them.\\nfloat unpack_mix_vec2(const vec2 packedValue, const float t) {\\n return mix(packedValue[0], packedValue[1], t);\\n}\\n\\n// Unpack a pair of paint values and interpolate between them.\\nvec4 unpack_mix_vec4(const vec4 packedColors, const float t) {\\n vec4 minColor = decode_color(vec2(packedColors[0], packedColors[1]));\\n vec4 maxColor = decode_color(vec2(packedColors[2], packedColors[3]));\\n return mix(minColor, maxColor, t);\\n}\\n\\n// The offset depends on how many pixels are between the world origin and the edge of the tile:\\n// vec2 offset = mod(pixel_coord, size)\\n//\\n// At high zoom levels there are a ton of pixels between the world origin and the edge of the tile.\\n// The glsl spec only guarantees 16 bits of precision for highp floats. We need more than that.\\n//\\n// The pixel_coord is passed in as two 16 bit values:\\n// pixel_coord_upper = floor(pixel_coord / 2^16)\\n// pixel_coord_lower = mod(pixel_coord, 2^16)\\n//\\n// The offset is calculated in a series of steps that should preserve this precision:\\nvec2 get_pattern_pos(const vec2 pixel_coord_upper, const vec2 pixel_coord_lower,\\n const vec2 pattern_size, const float tile_units_to_pixels, const vec2 pos) {\\n\\n vec2 offset = mod(mod(mod(pixel_coord_upper, pattern_size) * 256.0, pattern_size) * 256.0 + pixel_coord_lower, pattern_size);\\n return (tile_units_to_pixels * pos + offset) / pattern_size;\\n}\\n\"},background:{fragmentSource:\"uniform vec4 u_color;\\nuniform float u_opacity;\\n\\nvoid main() {\\n gl_FragColor = u_color * u_opacity;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"attribute vec2 a_pos;\\n\\nuniform mat4 u_matrix;\\n\\nvoid main() {\\n gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n}\\n\"},backgroundPattern:{fragmentSource:\"uniform vec2 u_pattern_tl_a;\\nuniform vec2 u_pattern_br_a;\\nuniform vec2 u_pattern_tl_b;\\nuniform vec2 u_pattern_br_b;\\nuniform vec2 u_texsize;\\nuniform float u_mix;\\nuniform float u_opacity;\\n\\nuniform sampler2D u_image;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\n\\nvoid main() {\\n vec2 imagecoord = mod(v_pos_a, 1.0);\\n vec2 pos = mix(u_pattern_tl_a / u_texsize, u_pattern_br_a / u_texsize, imagecoord);\\n vec4 color1 = texture2D(u_image, pos);\\n\\n vec2 imagecoord_b = mod(v_pos_b, 1.0);\\n vec2 pos2 = mix(u_pattern_tl_b / u_texsize, u_pattern_br_b / u_texsize, imagecoord_b);\\n vec4 color2 = texture2D(u_image, pos2);\\n\\n gl_FragColor = mix(color1, color2, u_mix) * u_opacity;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"uniform mat4 u_matrix;\\nuniform vec2 u_pattern_size_a;\\nuniform vec2 u_pattern_size_b;\\nuniform vec2 u_pixel_coord_upper;\\nuniform vec2 u_pixel_coord_lower;\\nuniform float u_scale_a;\\nuniform float u_scale_b;\\nuniform float u_tile_units_to_pixels;\\n\\nattribute vec2 a_pos;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\n\\nvoid main() {\\n gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n\\n v_pos_a = get_pattern_pos(u_pixel_coord_upper, u_pixel_coord_lower, u_scale_a * u_pattern_size_a, u_tile_units_to_pixels, a_pos);\\n v_pos_b = get_pattern_pos(u_pixel_coord_upper, u_pixel_coord_lower, u_scale_b * u_pattern_size_b, u_tile_units_to_pixels, a_pos);\\n}\\n\"},circle:{fragmentSource:\"#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\n\\nvarying vec3 v_data;\\n\\nvoid main() {\\n #pragma mapbox: initialize highp vec4 color\\n #pragma mapbox: initialize mediump float radius\\n #pragma mapbox: initialize lowp float blur\\n #pragma mapbox: initialize lowp float opacity\\n #pragma mapbox: initialize highp vec4 stroke_color\\n #pragma mapbox: initialize mediump float stroke_width\\n #pragma mapbox: initialize lowp float stroke_opacity\\n\\n vec2 extrude = v_data.xy;\\n float extrude_length = length(extrude);\\n\\n lowp float antialiasblur = v_data.z;\\n float antialiased_blur = -max(blur, antialiasblur);\\n\\n float opacity_t = smoothstep(0.0, antialiased_blur, extrude_length - 1.0);\\n\\n float color_t = stroke_width < 0.01 ? 0.0 : smoothstep(\\n antialiased_blur,\\n 0.0,\\n extrude_length - radius / (radius + stroke_width)\\n );\\n\\n gl_FragColor = opacity_t * mix(color * opacity, stroke_color * stroke_opacity, color_t);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"uniform mat4 u_matrix;\\nuniform bool u_scale_with_map;\\nuniform bool u_pitch_with_map;\\nuniform vec2 u_extrude_scale;\\nuniform highp float u_camera_to_center_distance;\\n\\nattribute vec2 a_pos;\\n\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\n\\nvarying vec3 v_data;\\n\\nvoid main(void) {\\n #pragma mapbox: initialize highp vec4 color\\n #pragma mapbox: initialize mediump float radius\\n #pragma mapbox: initialize lowp float blur\\n #pragma mapbox: initialize lowp float opacity\\n #pragma mapbox: initialize highp vec4 stroke_color\\n #pragma mapbox: initialize mediump float stroke_width\\n #pragma mapbox: initialize lowp float stroke_opacity\\n\\n // unencode the extrusion vector that we snuck into the a_pos vector\\n vec2 extrude = vec2(mod(a_pos, 2.0) * 2.0 - 1.0);\\n\\n // multiply a_pos by 0.5, since we had it * 2 in order to sneak\\n // in extrusion data\\n vec2 circle_center = floor(a_pos * 0.5);\\n if (u_pitch_with_map) {\\n vec2 corner_position = circle_center;\\n if (u_scale_with_map) {\\n corner_position += extrude * (radius + stroke_width) * u_extrude_scale;\\n } else {\\n // Pitching the circle with the map effectively scales it with the map\\n // To counteract the effect for pitch-scale: viewport, we rescale the\\n // whole circle based on the pitch scaling effect at its central point\\n vec4 projected_center = u_matrix * vec4(circle_center, 0, 1);\\n corner_position += extrude * (radius + stroke_width) * u_extrude_scale * (projected_center.w / u_camera_to_center_distance);\\n }\\n\\n gl_Position = u_matrix * vec4(corner_position, 0, 1);\\n } else {\\n gl_Position = u_matrix * vec4(circle_center, 0, 1);\\n\\n if (u_scale_with_map) {\\n gl_Position.xy += extrude * (radius + stroke_width) * u_extrude_scale * u_camera_to_center_distance;\\n } else {\\n gl_Position.xy += extrude * (radius + stroke_width) * u_extrude_scale * gl_Position.w;\\n }\\n }\\n\\n // This is a minimum blur distance that serves as a faux-antialiasing for\\n // the circle. since blur is a ratio of the circle's size and the intent is\\n // to keep the blur at roughly 1px, the two are inversely related.\\n lowp float antialiasblur = 1.0 / DEVICE_PIXEL_RATIO / (radius + stroke_width);\\n\\n v_data = vec3(extrude.x, extrude.y, antialiasblur);\\n}\\n\"},clippingMask:{fragmentSource:\"void main() {\\n gl_FragColor = vec4(1.0);\\n}\\n\",vertexSource:\"attribute vec2 a_pos;\\n\\nuniform mat4 u_matrix;\\n\\nvoid main() {\\n gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n}\\n\"},heatmap:{fragmentSource:\"#pragma mapbox: define highp float weight\\n\\nuniform highp float u_intensity;\\nvarying vec2 v_extrude;\\n\\n// Gaussian kernel coefficient: 1 / sqrt(2 * PI)\\n#define GAUSS_COEF 0.3989422804014327\\n\\nvoid main() {\\n #pragma mapbox: initialize highp float weight\\n\\n // Kernel density estimation with a Gaussian kernel of size 5x5\\n float d = -0.5 * 3.0 * 3.0 * dot(v_extrude, v_extrude);\\n float val = weight * u_intensity * GAUSS_COEF * exp(d);\\n\\n gl_FragColor = vec4(val, 1.0, 1.0, 1.0);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#pragma mapbox: define highp float weight\\n#pragma mapbox: define mediump float radius\\n\\nuniform mat4 u_matrix;\\nuniform float u_extrude_scale;\\nuniform float u_opacity;\\nuniform float u_intensity;\\n\\nattribute vec2 a_pos;\\n\\nvarying vec2 v_extrude;\\n\\n// Effective \\\"0\\\" in the kernel density texture to adjust the kernel size to;\\n// this empirically chosen number minimizes artifacts on overlapping kernels\\n// for typical heatmap cases (assuming clustered source)\\nconst highp float ZERO = 1.0 / 255.0 / 16.0;\\n\\n// Gaussian kernel coefficient: 1 / sqrt(2 * PI)\\n#define GAUSS_COEF 0.3989422804014327\\n\\nvoid main(void) {\\n #pragma mapbox: initialize highp float weight\\n #pragma mapbox: initialize mediump float radius\\n\\n // unencode the extrusion vector that we snuck into the a_pos vector\\n vec2 unscaled_extrude = vec2(mod(a_pos, 2.0) * 2.0 - 1.0);\\n\\n // This 'extrude' comes in ranging from [-1, -1], to [1, 1]. We'll use\\n // it to produce the vertices of a square mesh framing the point feature\\n // we're adding to the kernel density texture. We'll also pass it as\\n // a varying, so that the fragment shader can determine the distance of\\n // each fragment from the point feature.\\n // Before we do so, we need to scale it up sufficiently so that the\\n // kernel falls effectively to zero at the edge of the mesh.\\n // That is, we want to know S such that\\n // weight * u_intensity * GAUSS_COEF * exp(-0.5 * 3.0^2 * S^2) == ZERO\\n // Which solves to:\\n // S = sqrt(-2.0 * log(ZERO / (weight * u_intensity * GAUSS_COEF))) / 3.0\\n float S = sqrt(-2.0 * log(ZERO / weight / u_intensity / GAUSS_COEF)) / 3.0;\\n\\n // Pass the varying in units of radius\\n v_extrude = S * unscaled_extrude;\\n\\n // Scale by radius and the zoom-based scale factor to produce actual\\n // mesh position\\n vec2 extrude = v_extrude * radius * u_extrude_scale;\\n\\n // multiply a_pos by 0.5, since we had it * 2 in order to sneak\\n // in extrusion data\\n vec4 pos = vec4(floor(a_pos * 0.5) + extrude, 0, 1);\\n\\n gl_Position = u_matrix * pos;\\n}\\n\"},heatmapTexture:{fragmentSource:\"uniform sampler2D u_image;\\nuniform sampler2D u_color_ramp;\\nuniform float u_opacity;\\nvarying vec2 v_pos;\\n\\nvoid main() {\\n float t = texture2D(u_image, v_pos).r;\\n vec4 color = texture2D(u_color_ramp, vec2(t, 0.5));\\n gl_FragColor = color * u_opacity;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(0.0);\\n#endif\\n}\\n\",vertexSource:\"uniform mat4 u_matrix;\\nuniform vec2 u_world;\\nattribute vec2 a_pos;\\nvarying vec2 v_pos;\\n\\nvoid main() {\\n gl_Position = u_matrix * vec4(a_pos * u_world, 0, 1);\\n\\n v_pos.x = a_pos.x;\\n v_pos.y = 1.0 - a_pos.y;\\n}\\n\"},collisionBox:{fragmentSource:\"\\nvarying float v_placed;\\nvarying float v_notUsed;\\n\\nvoid main() {\\n\\n float alpha = 0.5;\\n\\n // Red = collision, hide label\\n gl_FragColor = vec4(1.0, 0.0, 0.0, 1.0) * alpha;\\n\\n // Blue = no collision, label is showing\\n if (v_placed > 0.5) {\\n gl_FragColor = vec4(0.0, 0.0, 1.0, 0.5) * alpha;\\n }\\n\\n if (v_notUsed > 0.5) {\\n // This box not used, fade it out\\n gl_FragColor *= .1;\\n }\\n}\",vertexSource:\"attribute vec2 a_pos;\\nattribute vec2 a_anchor_pos;\\nattribute vec2 a_extrude;\\nattribute vec2 a_placed;\\n\\nuniform mat4 u_matrix;\\nuniform vec2 u_extrude_scale;\\nuniform float u_camera_to_center_distance;\\n\\nvarying float v_placed;\\nvarying float v_notUsed;\\n\\nvoid main() {\\n vec4 projectedPoint = u_matrix * vec4(a_anchor_pos, 0, 1);\\n highp float camera_to_anchor_distance = projectedPoint.w;\\n highp float collision_perspective_ratio = clamp(\\n 0.5 + 0.5 * (u_camera_to_center_distance / camera_to_anchor_distance),\\n 0.0, // Prevents oversized near-field boxes in pitched/overzoomed tiles\\n 4.0);\\n\\n gl_Position = u_matrix * vec4(a_pos, 0.0, 1.0);\\n gl_Position.xy += a_extrude * u_extrude_scale * gl_Position.w * collision_perspective_ratio;\\n\\n v_placed = a_placed.x;\\n v_notUsed = a_placed.y;\\n}\\n\"},collisionCircle:{fragmentSource:\"uniform float u_overscale_factor;\\n\\nvarying float v_placed;\\nvarying float v_notUsed;\\nvarying float v_radius;\\nvarying vec2 v_extrude;\\nvarying vec2 v_extrude_scale;\\n\\nvoid main() {\\n float alpha = 0.5;\\n\\n // Red = collision, hide label\\n vec4 color = vec4(1.0, 0.0, 0.0, 1.0) * alpha;\\n\\n // Blue = no collision, label is showing\\n if (v_placed > 0.5) {\\n color = vec4(0.0, 0.0, 1.0, 0.5) * alpha;\\n }\\n\\n if (v_notUsed > 0.5) {\\n // This box not used, fade it out\\n color *= .2;\\n }\\n\\n float extrude_scale_length = length(v_extrude_scale);\\n float extrude_length = length(v_extrude) * extrude_scale_length;\\n float stroke_width = 15.0 * extrude_scale_length / u_overscale_factor;\\n float radius = v_radius * extrude_scale_length;\\n\\n float distance_to_edge = abs(extrude_length - radius);\\n float opacity_t = smoothstep(-stroke_width, 0.0, -distance_to_edge);\\n\\n gl_FragColor = opacity_t * color;\\n}\\n\",vertexSource:\"attribute vec2 a_pos;\\nattribute vec2 a_anchor_pos;\\nattribute vec2 a_extrude;\\nattribute vec2 a_placed;\\n\\nuniform mat4 u_matrix;\\nuniform vec2 u_extrude_scale;\\nuniform float u_camera_to_center_distance;\\n\\nvarying float v_placed;\\nvarying float v_notUsed;\\nvarying float v_radius;\\n\\nvarying vec2 v_extrude;\\nvarying vec2 v_extrude_scale;\\n\\nvoid main() {\\n vec4 projectedPoint = u_matrix * vec4(a_anchor_pos, 0, 1);\\n highp float camera_to_anchor_distance = projectedPoint.w;\\n highp float collision_perspective_ratio = clamp(\\n 0.5 + 0.5 * (u_camera_to_center_distance / camera_to_anchor_distance),\\n 0.0, // Prevents oversized near-field circles in pitched/overzoomed tiles\\n 4.0);\\n\\n gl_Position = u_matrix * vec4(a_pos, 0.0, 1.0);\\n\\n highp float padding_factor = 1.2; // Pad the vertices slightly to make room for anti-alias blur\\n gl_Position.xy += a_extrude * u_extrude_scale * padding_factor * gl_Position.w * collision_perspective_ratio;\\n\\n v_placed = a_placed.x;\\n v_notUsed = a_placed.y;\\n v_radius = abs(a_extrude.y); // We don't pitch the circles, so both units of the extrusion vector are equal in magnitude to the radius\\n\\n v_extrude = a_extrude * padding_factor;\\n v_extrude_scale = u_extrude_scale * u_camera_to_center_distance * collision_perspective_ratio;\\n}\\n\"},debug:{fragmentSource:\"uniform highp vec4 u_color;\\n\\nvoid main() {\\n gl_FragColor = u_color;\\n}\\n\",vertexSource:\"attribute vec2 a_pos;\\n\\nuniform mat4 u_matrix;\\n\\nvoid main() {\\n gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n}\\n\"},fill:{fragmentSource:\"#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\n\\nvoid main() {\\n #pragma mapbox: initialize highp vec4 color\\n #pragma mapbox: initialize lowp float opacity\\n\\n gl_FragColor = color * opacity;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"attribute vec2 a_pos;\\n\\nuniform mat4 u_matrix;\\n\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\n\\nvoid main() {\\n #pragma mapbox: initialize highp vec4 color\\n #pragma mapbox: initialize lowp float opacity\\n\\n gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n}\\n\"},fillOutline:{fragmentSource:\"#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\n\\nvarying vec2 v_pos;\\n\\nvoid main() {\\n #pragma mapbox: initialize highp vec4 outline_color\\n #pragma mapbox: initialize lowp float opacity\\n\\n float dist = length(v_pos - gl_FragCoord.xy);\\n float alpha = 1.0 - smoothstep(0.0, 1.0, dist);\\n gl_FragColor = outline_color * (alpha * opacity);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"attribute vec2 a_pos;\\n\\nuniform mat4 u_matrix;\\nuniform vec2 u_world;\\n\\nvarying vec2 v_pos;\\n\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\n\\nvoid main() {\\n #pragma mapbox: initialize highp vec4 outline_color\\n #pragma mapbox: initialize lowp float opacity\\n\\n gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n v_pos = (gl_Position.xy / gl_Position.w + 1.0) / 2.0 * u_world;\\n}\\n\"},fillOutlinePattern:{fragmentSource:\"uniform vec2 u_pattern_tl_a;\\nuniform vec2 u_pattern_br_a;\\nuniform vec2 u_pattern_tl_b;\\nuniform vec2 u_pattern_br_b;\\nuniform vec2 u_texsize;\\nuniform float u_mix;\\n\\nuniform sampler2D u_image;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\nvarying vec2 v_pos;\\n\\n#pragma mapbox: define lowp float opacity\\n\\nvoid main() {\\n #pragma mapbox: initialize lowp float opacity\\n\\n vec2 imagecoord = mod(v_pos_a, 1.0);\\n vec2 pos = mix(u_pattern_tl_a / u_texsize, u_pattern_br_a / u_texsize, imagecoord);\\n vec4 color1 = texture2D(u_image, pos);\\n\\n vec2 imagecoord_b = mod(v_pos_b, 1.0);\\n vec2 pos2 = mix(u_pattern_tl_b / u_texsize, u_pattern_br_b / u_texsize, imagecoord_b);\\n vec4 color2 = texture2D(u_image, pos2);\\n\\n // find distance to outline for alpha interpolation\\n\\n float dist = length(v_pos - gl_FragCoord.xy);\\n float alpha = 1.0 - smoothstep(0.0, 1.0, dist);\\n\\n\\n gl_FragColor = mix(color1, color2, u_mix) * alpha * opacity;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"uniform mat4 u_matrix;\\nuniform vec2 u_world;\\nuniform vec2 u_pattern_size_a;\\nuniform vec2 u_pattern_size_b;\\nuniform vec2 u_pixel_coord_upper;\\nuniform vec2 u_pixel_coord_lower;\\nuniform float u_scale_a;\\nuniform float u_scale_b;\\nuniform float u_tile_units_to_pixels;\\n\\nattribute vec2 a_pos;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\nvarying vec2 v_pos;\\n\\n#pragma mapbox: define lowp float opacity\\n\\nvoid main() {\\n #pragma mapbox: initialize lowp float opacity\\n\\n gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n\\n v_pos_a = get_pattern_pos(u_pixel_coord_upper, u_pixel_coord_lower, u_scale_a * u_pattern_size_a, u_tile_units_to_pixels, a_pos);\\n v_pos_b = get_pattern_pos(u_pixel_coord_upper, u_pixel_coord_lower, u_scale_b * u_pattern_size_b, u_tile_units_to_pixels, a_pos);\\n\\n v_pos = (gl_Position.xy / gl_Position.w + 1.0) / 2.0 * u_world;\\n}\\n\"},fillPattern:{fragmentSource:\"uniform vec2 u_pattern_tl_a;\\nuniform vec2 u_pattern_br_a;\\nuniform vec2 u_pattern_tl_b;\\nuniform vec2 u_pattern_br_b;\\nuniform vec2 u_texsize;\\nuniform float u_mix;\\n\\nuniform sampler2D u_image;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\n\\n#pragma mapbox: define lowp float opacity\\n\\nvoid main() {\\n #pragma mapbox: initialize lowp float opacity\\n\\n vec2 imagecoord = mod(v_pos_a, 1.0);\\n vec2 pos = mix(u_pattern_tl_a / u_texsize, u_pattern_br_a / u_texsize, imagecoord);\\n vec4 color1 = texture2D(u_image, pos);\\n\\n vec2 imagecoord_b = mod(v_pos_b, 1.0);\\n vec2 pos2 = mix(u_pattern_tl_b / u_texsize, u_pattern_br_b / u_texsize, imagecoord_b);\\n vec4 color2 = texture2D(u_image, pos2);\\n\\n gl_FragColor = mix(color1, color2, u_mix) * opacity;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"uniform mat4 u_matrix;\\nuniform vec2 u_pattern_size_a;\\nuniform vec2 u_pattern_size_b;\\nuniform vec2 u_pixel_coord_upper;\\nuniform vec2 u_pixel_coord_lower;\\nuniform float u_scale_a;\\nuniform float u_scale_b;\\nuniform float u_tile_units_to_pixels;\\n\\nattribute vec2 a_pos;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\n\\n#pragma mapbox: define lowp float opacity\\n\\nvoid main() {\\n #pragma mapbox: initialize lowp float opacity\\n\\n gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n\\n v_pos_a = get_pattern_pos(u_pixel_coord_upper, u_pixel_coord_lower, u_scale_a * u_pattern_size_a, u_tile_units_to_pixels, a_pos);\\n v_pos_b = get_pattern_pos(u_pixel_coord_upper, u_pixel_coord_lower, u_scale_b * u_pattern_size_b, u_tile_units_to_pixels, a_pos);\\n}\\n\"},fillExtrusion:{fragmentSource:\"varying vec4 v_color;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define highp vec4 color\\n\\nvoid main() {\\n #pragma mapbox: initialize lowp float base\\n #pragma mapbox: initialize lowp float height\\n #pragma mapbox: initialize highp vec4 color\\n\\n gl_FragColor = v_color;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"uniform mat4 u_matrix;\\nuniform vec3 u_lightcolor;\\nuniform lowp vec3 u_lightpos;\\nuniform lowp float u_lightintensity;\\n\\nattribute vec2 a_pos;\\nattribute vec4 a_normal_ed;\\n\\nvarying vec4 v_color;\\n\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n\\n#pragma mapbox: define highp vec4 color\\n\\nvoid main() {\\n #pragma mapbox: initialize lowp float base\\n #pragma mapbox: initialize lowp float height\\n #pragma mapbox: initialize highp vec4 color\\n\\n vec3 normal = a_normal_ed.xyz;\\n\\n base = max(0.0, base);\\n height = max(0.0, height);\\n\\n float t = mod(normal.x, 2.0);\\n\\n gl_Position = u_matrix * vec4(a_pos, t > 0.0 ? height : base, 1);\\n\\n // Relative luminance (how dark/bright is the surface color?)\\n float colorvalue = color.r * 0.2126 + color.g * 0.7152 + color.b * 0.0722;\\n\\n v_color = vec4(0.0, 0.0, 0.0, 1.0);\\n\\n // Add slight ambient lighting so no extrusions are totally black\\n vec4 ambientlight = vec4(0.03, 0.03, 0.03, 1.0);\\n color += ambientlight;\\n\\n // Calculate cos(theta), where theta is the angle between surface normal and diffuse light ray\\n float directional = clamp(dot(normal / 16384.0, u_lightpos), 0.0, 1.0);\\n\\n // Adjust directional so that\\n // the range of values for highlight/shading is narrower\\n // with lower light intensity\\n // and with lighter/brighter surface colors\\n directional = mix((1.0 - u_lightintensity), max((1.0 - colorvalue + u_lightintensity), 1.0), directional);\\n\\n // Add gradient along z axis of side surfaces\\n if (normal.y != 0.0) {\\n directional *= clamp((t + base) * pow(height / 150.0, 0.5), mix(0.7, 0.98, 1.0 - u_lightintensity), 1.0);\\n }\\n\\n // Assign final color based on surface + ambient light color, diffuse light directional, and light color\\n // with lower bounds adjusted to hue of light\\n // so that shading is tinted with the complementary (opposite) color to the light color\\n v_color.r += clamp(color.r * directional * u_lightcolor.r, mix(0.0, 0.3, 1.0 - u_lightcolor.r), 1.0);\\n v_color.g += clamp(color.g * directional * u_lightcolor.g, mix(0.0, 0.3, 1.0 - u_lightcolor.g), 1.0);\\n v_color.b += clamp(color.b * directional * u_lightcolor.b, mix(0.0, 0.3, 1.0 - u_lightcolor.b), 1.0);\\n}\\n\"},fillExtrusionPattern:{fragmentSource:\"uniform vec2 u_pattern_tl_a;\\nuniform vec2 u_pattern_br_a;\\nuniform vec2 u_pattern_tl_b;\\nuniform vec2 u_pattern_br_b;\\nuniform vec2 u_texsize;\\nuniform float u_mix;\\n\\nuniform sampler2D u_image;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\nvarying vec4 v_lighting;\\n\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n\\nvoid main() {\\n #pragma mapbox: initialize lowp float base\\n #pragma mapbox: initialize lowp float height\\n\\n vec2 imagecoord = mod(v_pos_a, 1.0);\\n vec2 pos = mix(u_pattern_tl_a / u_texsize, u_pattern_br_a / u_texsize, imagecoord);\\n vec4 color1 = texture2D(u_image, pos);\\n\\n vec2 imagecoord_b = mod(v_pos_b, 1.0);\\n vec2 pos2 = mix(u_pattern_tl_b / u_texsize, u_pattern_br_b / u_texsize, imagecoord_b);\\n vec4 color2 = texture2D(u_image, pos2);\\n\\n vec4 mixedColor = mix(color1, color2, u_mix);\\n\\n gl_FragColor = mixedColor * v_lighting;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"uniform mat4 u_matrix;\\nuniform vec2 u_pattern_size_a;\\nuniform vec2 u_pattern_size_b;\\nuniform vec2 u_pixel_coord_upper;\\nuniform vec2 u_pixel_coord_lower;\\nuniform float u_scale_a;\\nuniform float u_scale_b;\\nuniform float u_tile_units_to_pixels;\\nuniform float u_height_factor;\\n\\nuniform vec3 u_lightcolor;\\nuniform lowp vec3 u_lightpos;\\nuniform lowp float u_lightintensity;\\n\\nattribute vec2 a_pos;\\nattribute vec4 a_normal_ed;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\nvarying vec4 v_lighting;\\nvarying float v_directional;\\n\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n\\nvoid main() {\\n #pragma mapbox: initialize lowp float base\\n #pragma mapbox: initialize lowp float height\\n\\n vec3 normal = a_normal_ed.xyz;\\n float edgedistance = a_normal_ed.w;\\n\\n base = max(0.0, base);\\n height = max(0.0, height);\\n\\n float t = mod(normal.x, 2.0);\\n float z = t > 0.0 ? height : base;\\n\\n gl_Position = u_matrix * vec4(a_pos, z, 1);\\n\\n vec2 pos = normal.x == 1.0 && normal.y == 0.0 && normal.z == 16384.0\\n ? a_pos // extrusion top\\n : vec2(edgedistance, z * u_height_factor); // extrusion side\\n\\n v_pos_a = get_pattern_pos(u_pixel_coord_upper, u_pixel_coord_lower, u_scale_a * u_pattern_size_a, u_tile_units_to_pixels, pos);\\n v_pos_b = get_pattern_pos(u_pixel_coord_upper, u_pixel_coord_lower, u_scale_b * u_pattern_size_b, u_tile_units_to_pixels, pos);\\n\\n v_lighting = vec4(0.0, 0.0, 0.0, 1.0);\\n float directional = clamp(dot(normal / 16383.0, u_lightpos), 0.0, 1.0);\\n directional = mix((1.0 - u_lightintensity), max((0.5 + u_lightintensity), 1.0), directional);\\n\\n if (normal.y != 0.0) {\\n directional *= clamp((t + base) * pow(height / 150.0, 0.5), mix(0.7, 0.98, 1.0 - u_lightintensity), 1.0);\\n }\\n\\n v_lighting.rgb += clamp(directional * u_lightcolor, mix(vec3(0.0), vec3(0.3), 1.0 - u_lightcolor), vec3(1.0));\\n}\\n\"},extrusionTexture:{fragmentSource:\"uniform sampler2D u_image;\\nuniform float u_opacity;\\nvarying vec2 v_pos;\\n\\nvoid main() {\\n gl_FragColor = texture2D(u_image, v_pos) * u_opacity;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(0.0);\\n#endif\\n}\\n\",vertexSource:\"uniform mat4 u_matrix;\\nuniform vec2 u_world;\\nattribute vec2 a_pos;\\nvarying vec2 v_pos;\\n\\nvoid main() {\\n gl_Position = u_matrix * vec4(a_pos * u_world, 0, 1);\\n\\n v_pos.x = a_pos.x;\\n v_pos.y = 1.0 - a_pos.y;\\n}\\n\"},hillshadePrepare:{fragmentSource:\"#ifdef GL_ES\\nprecision highp float;\\n#endif\\n\\nuniform sampler2D u_image;\\nvarying vec2 v_pos;\\nuniform vec2 u_dimension;\\nuniform float u_zoom;\\nuniform float u_maxzoom;\\n\\nfloat getElevation(vec2 coord, float bias) {\\n // Convert encoded elevation value to meters\\n vec4 data = texture2D(u_image, coord) * 255.0;\\n return (data.r + data.g * 256.0 + data.b * 256.0 * 256.0) / 4.0;\\n}\\n\\nvoid main() {\\n vec2 epsilon = 1.0 / u_dimension;\\n\\n // queried pixels:\\n // +-----------+\\n // | | | |\\n // | a | b | c |\\n // | | | |\\n // +-----------+\\n // | | | |\\n // | d | e | f |\\n // | | | |\\n // +-----------+\\n // | | | |\\n // | g | h | i |\\n // | | | |\\n // +-----------+\\n\\n float a = getElevation(v_pos + vec2(-epsilon.x, -epsilon.y), 0.0);\\n float b = getElevation(v_pos + vec2(0, -epsilon.y), 0.0);\\n float c = getElevation(v_pos + vec2(epsilon.x, -epsilon.y), 0.0);\\n float d = getElevation(v_pos + vec2(-epsilon.x, 0), 0.0);\\n float e = getElevation(v_pos, 0.0);\\n float f = getElevation(v_pos + vec2(epsilon.x, 0), 0.0);\\n float g = getElevation(v_pos + vec2(-epsilon.x, epsilon.y), 0.0);\\n float h = getElevation(v_pos + vec2(0, epsilon.y), 0.0);\\n float i = getElevation(v_pos + vec2(epsilon.x, epsilon.y), 0.0);\\n\\n // here we divide the x and y slopes by 8 * pixel size\\n // where pixel size (aka meters/pixel) is:\\n // circumference of the world / (pixels per tile * number of tiles)\\n // which is equivalent to: 8 * 40075016.6855785 / (512 * pow(2, u_zoom))\\n // which can be reduced to: pow(2, 19.25619978527 - u_zoom)\\n // we want to vertically exaggerate the hillshading though, because otherwise\\n // it is barely noticeable at low zooms. to do this, we multiply this by some\\n // scale factor pow(2, (u_zoom - u_maxzoom) * a) where a is an arbitrary value\\n // Here we use a=0.3 which works out to the expression below. see \\n // nickidlugash's awesome breakdown for more info\\n // https://github.com/mapbox/mapbox-gl-js/pull/5286#discussion_r148419556\\n float exaggeration = u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;\\n\\n vec2 deriv = vec2(\\n (c + f + f + i) - (a + d + d + g),\\n (g + h + h + i) - (a + b + b + c)\\n ) / pow(2.0, (u_zoom - u_maxzoom) * exaggeration + 19.2562 - u_zoom);\\n\\n gl_FragColor = clamp(vec4(\\n deriv.x / 2.0 + 0.5,\\n deriv.y / 2.0 + 0.5,\\n 1.0,\\n 1.0), 0.0, 1.0);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"uniform mat4 u_matrix;\\n\\nattribute vec2 a_pos;\\nattribute vec2 a_texture_pos;\\n\\nvarying vec2 v_pos;\\n\\nvoid main() {\\n gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n v_pos = (a_texture_pos / 8192.0) / 2.0 + 0.25;\\n}\\n\"},hillshade:{fragmentSource:\"uniform sampler2D u_image;\\nvarying vec2 v_pos;\\n\\nuniform vec2 u_latrange;\\nuniform vec2 u_light;\\nuniform vec4 u_shadow;\\nuniform vec4 u_highlight;\\nuniform vec4 u_accent;\\n\\n#define PI 3.141592653589793\\n\\nvoid main() {\\n vec4 pixel = texture2D(u_image, v_pos);\\n\\n vec2 deriv = ((pixel.rg * 2.0) - 1.0);\\n\\n // We divide the slope by a scale factor based on the cosin of the pixel's approximate latitude\\n // to account for mercator projection distortion. see #4807 for details\\n float scaleFactor = cos(radians((u_latrange[0] - u_latrange[1]) * (1.0 - v_pos.y) + u_latrange[1]));\\n // We also multiply the slope by an arbitrary z-factor of 1.25\\n float slope = atan(1.25 * length(deriv) / scaleFactor);\\n float aspect = deriv.x != 0.0 ? atan(deriv.y, -deriv.x) : PI / 2.0 * (deriv.y > 0.0 ? 1.0 : -1.0);\\n\\n float intensity = u_light.x;\\n // We add PI to make this property match the global light object, which adds PI/2 to the light's azimuthal\\n // position property to account for 0deg corresponding to north/the top of the viewport in the style spec\\n // and the original shader was written to accept (-illuminationDirection - 90) as the azimuthal.\\n float azimuth = u_light.y + PI;\\n\\n // We scale the slope exponentially based on intensity, using a calculation similar to\\n // the exponential interpolation function in the style spec:\\n // https://github.com/mapbox/mapbox-gl-js/blob/master/src/style-spec/expression/definitions/interpolate.js#L217-L228\\n // so that higher intensity values create more opaque hillshading.\\n float base = 1.875 - intensity * 1.75;\\n float maxValue = 0.5 * PI;\\n float scaledSlope = intensity != 0.5 ? ((pow(base, slope) - 1.0) / (pow(base, maxValue) - 1.0)) * maxValue : slope;\\n\\n // The accent color is calculated with the cosine of the slope while the shade color is calculated with the sine\\n // so that the accent color's rate of change eases in while the shade color's eases out.\\n float accent = cos(scaledSlope);\\n // We multiply both the accent and shade color by a clamped intensity value\\n // so that intensities >= 0.5 do not additionally affect the color values\\n // while intensity values < 0.5 make the overall color more transparent.\\n vec4 accent_color = (1.0 - accent) * u_accent * clamp(intensity * 2.0, 0.0, 1.0);\\n float shade = abs(mod((aspect + azimuth) / PI + 0.5, 2.0) - 1.0);\\n vec4 shade_color = mix(u_shadow, u_highlight, shade) * sin(scaledSlope) * clamp(intensity * 2.0, 0.0, 1.0);\\n gl_FragColor = accent_color * (1.0 - shade_color.a) + shade_color;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"uniform mat4 u_matrix;\\n\\nattribute vec2 a_pos;\\nattribute vec2 a_texture_pos;\\n\\nvarying vec2 v_pos;\\n\\nvoid main() {\\n gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n v_pos = a_texture_pos / 8192.0;\\n}\\n\"},line:{fragmentSource:\"#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n\\nvarying vec2 v_width2;\\nvarying vec2 v_normal;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n #pragma mapbox: initialize highp vec4 color\\n #pragma mapbox: initialize lowp float blur\\n #pragma mapbox: initialize lowp float opacity\\n\\n // Calculate the distance of the pixel from the line in pixels.\\n float dist = length(v_normal) * v_width2.s;\\n\\n // Calculate the antialiasing fade factor. This is either when fading in\\n // the line in case of an offset line (v_width2.t) or when fading out\\n // (v_width2.s)\\n float blur2 = (blur + 1.0 / DEVICE_PIXEL_RATIO) * v_gamma_scale;\\n float alpha = clamp(min(dist - (v_width2.t - blur2), v_width2.s - dist) / blur2, 0.0, 1.0);\\n\\n gl_FragColor = color * (alpha * opacity);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"\\n\\n// the distance over which the line edge fades out.\\n// Retina devices need a smaller distance to avoid aliasing.\\n#define ANTIALIASING 1.0 / DEVICE_PIXEL_RATIO / 2.0\\n\\n// floor(127 / 2) == 63.0\\n// the maximum allowed miter limit is 2.0 at the moment. the extrude normal is\\n// stored in a byte (-128..127). we scale regular normals up to length 63, but\\n// there are also \\\"special\\\" normals that have a bigger length (of up to 126 in\\n// this case).\\n// #define scale 63.0\\n#define scale 0.015873016\\n\\nattribute vec4 a_pos_normal;\\nattribute vec4 a_data;\\n\\nuniform mat4 u_matrix;\\nuniform mediump float u_ratio;\\nuniform vec2 u_gl_units_to_pixels;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_width2;\\nvarying float v_gamma_scale;\\nvarying highp float v_linesofar;\\n\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\n\\nvoid main() {\\n #pragma mapbox: initialize highp vec4 color\\n #pragma mapbox: initialize lowp float blur\\n #pragma mapbox: initialize lowp float opacity\\n #pragma mapbox: initialize mediump float gapwidth\\n #pragma mapbox: initialize lowp float offset\\n #pragma mapbox: initialize mediump float width\\n\\n vec2 a_extrude = a_data.xy - 128.0;\\n float a_direction = mod(a_data.z, 4.0) - 1.0;\\n\\n v_linesofar = (floor(a_data.z / 4.0) + a_data.w * 64.0) * 2.0;\\n\\n vec2 pos = a_pos_normal.xy;\\n\\n // x is 1 if it's a round cap, 0 otherwise\\n // y is 1 if the normal points up, and -1 if it points down\\n mediump vec2 normal = a_pos_normal.zw;\\n v_normal = normal;\\n\\n // these transformations used to be applied in the JS and native code bases.\\n // moved them into the shader for clarity and simplicity.\\n gapwidth = gapwidth / 2.0;\\n float halfwidth = width / 2.0;\\n offset = -1.0 * offset;\\n\\n float inset = gapwidth + (gapwidth > 0.0 ? ANTIALIASING : 0.0);\\n float outset = gapwidth + halfwidth * (gapwidth > 0.0 ? 2.0 : 1.0) + ANTIALIASING;\\n\\n // Scale the extrusion vector down to a normal and then up by the line width\\n // of this vertex.\\n mediump vec2 dist = outset * a_extrude * scale;\\n\\n // Calculate the offset when drawing a line that is to the side of the actual line.\\n // We do this by creating a vector that points towards the extrude, but rotate\\n // it when we're drawing round end points (a_direction = -1 or 1) since their\\n // extrude vector points in another direction.\\n mediump float u = 0.5 * a_direction;\\n mediump float t = 1.0 - abs(u);\\n mediump vec2 offset2 = offset * a_extrude * scale * normal.y * mat2(t, -u, u, t);\\n\\n vec4 projected_extrude = u_matrix * vec4(dist / u_ratio, 0.0, 0.0);\\n gl_Position = u_matrix * vec4(pos + offset2 / u_ratio, 0.0, 1.0) + projected_extrude;\\n\\n // calculate how much the perspective view squishes or stretches the extrude\\n float extrude_length_without_perspective = length(dist);\\n float extrude_length_with_perspective = length(projected_extrude.xy / gl_Position.w * u_gl_units_to_pixels);\\n v_gamma_scale = extrude_length_without_perspective / extrude_length_with_perspective;\\n\\n v_width2 = vec2(outset, inset);\\n}\\n\"},lineGradient:{fragmentSource:\"\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n\\nuniform sampler2D u_image;\\n\\nvarying vec2 v_width2;\\nvarying vec2 v_normal;\\nvarying float v_gamma_scale;\\nvarying highp float v_lineprogress;\\n\\nvoid main() {\\n #pragma mapbox: initialize lowp float blur\\n #pragma mapbox: initialize lowp float opacity\\n\\n // Calculate the distance of the pixel from the line in pixels.\\n float dist = length(v_normal) * v_width2.s;\\n\\n // Calculate the antialiasing fade factor. This is either when fading in\\n // the line in case of an offset line (v_width2.t) or when fading out\\n // (v_width2.s)\\n float blur2 = (blur + 1.0 / DEVICE_PIXEL_RATIO) * v_gamma_scale;\\n float alpha = clamp(min(dist - (v_width2.t - blur2), v_width2.s - dist) / blur2, 0.0, 1.0);\\n\\n // For gradient lines, v_lineprogress is the ratio along the entire line,\\n // scaled to [0, 2^15), and the gradient ramp is stored in a texture.\\n vec4 color = texture2D(u_image, vec2(v_lineprogress, 0.5));\\n\\n gl_FragColor = color * (alpha * opacity);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"\\n// the attribute conveying progress along a line is scaled to [0, 2^15)\\n#define MAX_LINE_DISTANCE 32767.0\\n\\n// the distance over which the line edge fades out.\\n// Retina devices need a smaller distance to avoid aliasing.\\n#define ANTIALIASING 1.0 / DEVICE_PIXEL_RATIO / 2.0\\n\\n// floor(127 / 2) == 63.0\\n// the maximum allowed miter limit is 2.0 at the moment. the extrude normal is\\n// stored in a byte (-128..127). we scale regular normals up to length 63, but\\n// there are also \\\"special\\\" normals that have a bigger length (of up to 126 in\\n// this case).\\n// #define scale 63.0\\n#define scale 0.015873016\\n\\nattribute vec4 a_pos_normal;\\nattribute vec4 a_data;\\n\\nuniform mat4 u_matrix;\\nuniform mediump float u_ratio;\\nuniform vec2 u_gl_units_to_pixels;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_width2;\\nvarying float v_gamma_scale;\\nvarying highp float v_lineprogress;\\n\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\n\\nvoid main() {\\n #pragma mapbox: initialize lowp float blur\\n #pragma mapbox: initialize lowp float opacity\\n #pragma mapbox: initialize mediump float gapwidth\\n #pragma mapbox: initialize lowp float offset\\n #pragma mapbox: initialize mediump float width\\n\\n vec2 a_extrude = a_data.xy - 128.0;\\n float a_direction = mod(a_data.z, 4.0) - 1.0;\\n\\n v_lineprogress = (floor(a_data.z / 4.0) + a_data.w * 64.0) * 2.0 / MAX_LINE_DISTANCE;\\n\\n vec2 pos = a_pos_normal.xy;\\n\\n // x is 1 if it's a round cap, 0 otherwise\\n // y is 1 if the normal points up, and -1 if it points down\\n mediump vec2 normal = a_pos_normal.zw;\\n v_normal = normal;\\n\\n // these transformations used to be applied in the JS and native code bases.\\n // moved them into the shader for clarity and simplicity.\\n gapwidth = gapwidth / 2.0;\\n float halfwidth = width / 2.0;\\n offset = -1.0 * offset;\\n\\n float inset = gapwidth + (gapwidth > 0.0 ? ANTIALIASING : 0.0);\\n float outset = gapwidth + halfwidth * (gapwidth > 0.0 ? 2.0 : 1.0) + ANTIALIASING;\\n\\n // Scale the extrusion vector down to a normal and then up by the line width\\n // of this vertex.\\n mediump vec2 dist = outset * a_extrude * scale;\\n\\n // Calculate the offset when drawing a line that is to the side of the actual line.\\n // We do this by creating a vector that points towards the extrude, but rotate\\n // it when we're drawing round end points (a_direction = -1 or 1) since their\\n // extrude vector points in another direction.\\n mediump float u = 0.5 * a_direction;\\n mediump float t = 1.0 - abs(u);\\n mediump vec2 offset2 = offset * a_extrude * scale * normal.y * mat2(t, -u, u, t);\\n\\n vec4 projected_extrude = u_matrix * vec4(dist / u_ratio, 0.0, 0.0);\\n gl_Position = u_matrix * vec4(pos + offset2 / u_ratio, 0.0, 1.0) + projected_extrude;\\n\\n // calculate how much the perspective view squishes or stretches the extrude\\n float extrude_length_without_perspective = length(dist);\\n float extrude_length_with_perspective = length(projected_extrude.xy / gl_Position.w * u_gl_units_to_pixels);\\n v_gamma_scale = extrude_length_without_perspective / extrude_length_with_perspective;\\n\\n v_width2 = vec2(outset, inset);\\n}\\n\"},linePattern:{fragmentSource:\"uniform vec2 u_pattern_size_a;\\nuniform vec2 u_pattern_size_b;\\nuniform vec2 u_pattern_tl_a;\\nuniform vec2 u_pattern_br_a;\\nuniform vec2 u_pattern_tl_b;\\nuniform vec2 u_pattern_br_b;\\nuniform vec2 u_texsize;\\nuniform float u_fade;\\n\\nuniform sampler2D u_image;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_width2;\\nvarying float v_linesofar;\\nvarying float v_gamma_scale;\\n\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n\\nvoid main() {\\n #pragma mapbox: initialize lowp float blur\\n #pragma mapbox: initialize lowp float opacity\\n\\n // Calculate the distance of the pixel from the line in pixels.\\n float dist = length(v_normal) * v_width2.s;\\n\\n // Calculate the antialiasing fade factor. This is either when fading in\\n // the line in case of an offset line (v_width2.t) or when fading out\\n // (v_width2.s)\\n float blur2 = (blur + 1.0 / DEVICE_PIXEL_RATIO) * v_gamma_scale;\\n float alpha = clamp(min(dist - (v_width2.t - blur2), v_width2.s - dist) / blur2, 0.0, 1.0);\\n\\n float x_a = mod(v_linesofar / u_pattern_size_a.x, 1.0);\\n float x_b = mod(v_linesofar / u_pattern_size_b.x, 1.0);\\n\\n // v_normal.y is 0 at the midpoint of the line, -1 at the lower edge, 1 at the upper edge\\n // we clamp the line width outset to be between 0 and half the pattern height plus padding (2.0)\\n // to ensure we don't sample outside the designated symbol on the sprite sheet.\\n // 0.5 is added to shift the component to be bounded between 0 and 1 for interpolation of\\n // the texture coordinate\\n float y_a = 0.5 + (v_normal.y * clamp(v_width2.s, 0.0, (u_pattern_size_a.y + 2.0) / 2.0) / u_pattern_size_a.y);\\n float y_b = 0.5 + (v_normal.y * clamp(v_width2.s, 0.0, (u_pattern_size_b.y + 2.0) / 2.0) / u_pattern_size_b.y);\\n vec2 pos_a = mix(u_pattern_tl_a / u_texsize, u_pattern_br_a / u_texsize, vec2(x_a, y_a));\\n vec2 pos_b = mix(u_pattern_tl_b / u_texsize, u_pattern_br_b / u_texsize, vec2(x_b, y_b));\\n\\n vec4 color = mix(texture2D(u_image, pos_a), texture2D(u_image, pos_b), u_fade);\\n\\n gl_FragColor = color * alpha * opacity;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"// floor(127 / 2) == 63.0\\n// the maximum allowed miter limit is 2.0 at the moment. the extrude normal is\\n// stored in a byte (-128..127). we scale regular normals up to length 63, but\\n// there are also \\\"special\\\" normals that have a bigger length (of up to 126 in\\n// this case).\\n// #define scale 63.0\\n#define scale 0.015873016\\n\\n// We scale the distance before adding it to the buffers so that we can store\\n// long distances for long segments. Use this value to unscale the distance.\\n#define LINE_DISTANCE_SCALE 2.0\\n\\n// the distance over which the line edge fades out.\\n// Retina devices need a smaller distance to avoid aliasing.\\n#define ANTIALIASING 1.0 / DEVICE_PIXEL_RATIO / 2.0\\n\\nattribute vec4 a_pos_normal;\\nattribute vec4 a_data;\\n\\nuniform mat4 u_matrix;\\nuniform mediump float u_ratio;\\nuniform vec2 u_gl_units_to_pixels;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_width2;\\nvarying float v_linesofar;\\nvarying float v_gamma_scale;\\n\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define mediump float width\\n\\nvoid main() {\\n #pragma mapbox: initialize lowp float blur\\n #pragma mapbox: initialize lowp float opacity\\n #pragma mapbox: initialize lowp float offset\\n #pragma mapbox: initialize mediump float gapwidth\\n #pragma mapbox: initialize mediump float width\\n\\n vec2 a_extrude = a_data.xy - 128.0;\\n float a_direction = mod(a_data.z, 4.0) - 1.0;\\n float a_linesofar = (floor(a_data.z / 4.0) + a_data.w * 64.0) * LINE_DISTANCE_SCALE;\\n\\n vec2 pos = a_pos_normal.xy;\\n\\n // x is 1 if it's a round cap, 0 otherwise\\n // y is 1 if the normal points up, and -1 if it points down\\n mediump vec2 normal = a_pos_normal.zw;\\n v_normal = normal;\\n\\n // these transformations used to be applied in the JS and native code bases.\\n // moved them into the shader for clarity and simplicity.\\n gapwidth = gapwidth / 2.0;\\n float halfwidth = width / 2.0;\\n offset = -1.0 * offset;\\n\\n float inset = gapwidth + (gapwidth > 0.0 ? ANTIALIASING : 0.0);\\n float outset = gapwidth + halfwidth * (gapwidth > 0.0 ? 2.0 : 1.0) + ANTIALIASING;\\n\\n // Scale the extrusion vector down to a normal and then up by the line width\\n // of this vertex.\\n mediump vec2 dist = outset * a_extrude * scale;\\n\\n // Calculate the offset when drawing a line that is to the side of the actual line.\\n // We do this by creating a vector that points towards the extrude, but rotate\\n // it when we're drawing round end points (a_direction = -1 or 1) since their\\n // extrude vector points in another direction.\\n mediump float u = 0.5 * a_direction;\\n mediump float t = 1.0 - abs(u);\\n mediump vec2 offset2 = offset * a_extrude * scale * normal.y * mat2(t, -u, u, t);\\n\\n vec4 projected_extrude = u_matrix * vec4(dist / u_ratio, 0.0, 0.0);\\n gl_Position = u_matrix * vec4(pos + offset2 / u_ratio, 0.0, 1.0) + projected_extrude;\\n\\n // calculate how much the perspective view squishes or stretches the extrude\\n float extrude_length_without_perspective = length(dist);\\n float extrude_length_with_perspective = length(projected_extrude.xy / gl_Position.w * u_gl_units_to_pixels);\\n v_gamma_scale = extrude_length_without_perspective / extrude_length_with_perspective;\\n\\n v_linesofar = a_linesofar;\\n v_width2 = vec2(outset, inset);\\n}\\n\"},lineSDF:{fragmentSource:\"\\nuniform sampler2D u_image;\\nuniform float u_sdfgamma;\\nuniform float u_mix;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_width2;\\nvarying vec2 v_tex_a;\\nvarying vec2 v_tex_b;\\nvarying float v_gamma_scale;\\n\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\n\\nvoid main() {\\n #pragma mapbox: initialize highp vec4 color\\n #pragma mapbox: initialize lowp float blur\\n #pragma mapbox: initialize lowp float opacity\\n #pragma mapbox: initialize mediump float width\\n #pragma mapbox: initialize lowp float floorwidth\\n\\n // Calculate the distance of the pixel from the line in pixels.\\n float dist = length(v_normal) * v_width2.s;\\n\\n // Calculate the antialiasing fade factor. This is either when fading in\\n // the line in case of an offset line (v_width2.t) or when fading out\\n // (v_width2.s)\\n float blur2 = (blur + 1.0 / DEVICE_PIXEL_RATIO) * v_gamma_scale;\\n float alpha = clamp(min(dist - (v_width2.t - blur2), v_width2.s - dist) / blur2, 0.0, 1.0);\\n\\n float sdfdist_a = texture2D(u_image, v_tex_a).a;\\n float sdfdist_b = texture2D(u_image, v_tex_b).a;\\n float sdfdist = mix(sdfdist_a, sdfdist_b, u_mix);\\n alpha *= smoothstep(0.5 - u_sdfgamma / floorwidth, 0.5 + u_sdfgamma / floorwidth, sdfdist);\\n\\n gl_FragColor = color * (alpha * opacity);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"// floor(127 / 2) == 63.0\\n// the maximum allowed miter limit is 2.0 at the moment. the extrude normal is\\n// stored in a byte (-128..127). we scale regular normals up to length 63, but\\n// there are also \\\"special\\\" normals that have a bigger length (of up to 126 in\\n// this case).\\n// #define scale 63.0\\n#define scale 0.015873016\\n\\n// We scale the distance before adding it to the buffers so that we can store\\n// long distances for long segments. Use this value to unscale the distance.\\n#define LINE_DISTANCE_SCALE 2.0\\n\\n// the distance over which the line edge fades out.\\n// Retina devices need a smaller distance to avoid aliasing.\\n#define ANTIALIASING 1.0 / DEVICE_PIXEL_RATIO / 2.0\\n\\nattribute vec4 a_pos_normal;\\nattribute vec4 a_data;\\n\\nuniform mat4 u_matrix;\\nuniform mediump float u_ratio;\\nuniform vec2 u_patternscale_a;\\nuniform float u_tex_y_a;\\nuniform vec2 u_patternscale_b;\\nuniform float u_tex_y_b;\\nuniform vec2 u_gl_units_to_pixels;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_width2;\\nvarying vec2 v_tex_a;\\nvarying vec2 v_tex_b;\\nvarying float v_gamma_scale;\\n\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\n\\nvoid main() {\\n #pragma mapbox: initialize highp vec4 color\\n #pragma mapbox: initialize lowp float blur\\n #pragma mapbox: initialize lowp float opacity\\n #pragma mapbox: initialize mediump float gapwidth\\n #pragma mapbox: initialize lowp float offset\\n #pragma mapbox: initialize mediump float width\\n #pragma mapbox: initialize lowp float floorwidth\\n\\n vec2 a_extrude = a_data.xy - 128.0;\\n float a_direction = mod(a_data.z, 4.0) - 1.0;\\n float a_linesofar = (floor(a_data.z / 4.0) + a_data.w * 64.0) * LINE_DISTANCE_SCALE;\\n\\n vec2 pos = a_pos_normal.xy;\\n\\n // x is 1 if it's a round cap, 0 otherwise\\n // y is 1 if the normal points up, and -1 if it points down\\n mediump vec2 normal = a_pos_normal.zw;\\n v_normal = normal;\\n\\n // these transformations used to be applied in the JS and native code bases.\\n // moved them into the shader for clarity and simplicity.\\n gapwidth = gapwidth / 2.0;\\n float halfwidth = width / 2.0;\\n offset = -1.0 * offset;\\n\\n float inset = gapwidth + (gapwidth > 0.0 ? ANTIALIASING : 0.0);\\n float outset = gapwidth + halfwidth * (gapwidth > 0.0 ? 2.0 : 1.0) + ANTIALIASING;\\n\\n // Scale the extrusion vector down to a normal and then up by the line width\\n // of this vertex.\\n mediump vec2 dist =outset * a_extrude * scale;\\n\\n // Calculate the offset when drawing a line that is to the side of the actual line.\\n // We do this by creating a vector that points towards the extrude, but rotate\\n // it when we're drawing round end points (a_direction = -1 or 1) since their\\n // extrude vector points in another direction.\\n mediump float u = 0.5 * a_direction;\\n mediump float t = 1.0 - abs(u);\\n mediump vec2 offset2 = offset * a_extrude * scale * normal.y * mat2(t, -u, u, t);\\n\\n vec4 projected_extrude = u_matrix * vec4(dist / u_ratio, 0.0, 0.0);\\n gl_Position = u_matrix * vec4(pos + offset2 / u_ratio, 0.0, 1.0) + projected_extrude;\\n\\n // calculate how much the perspective view squishes or stretches the extrude\\n float extrude_length_without_perspective = length(dist);\\n float extrude_length_with_perspective = length(projected_extrude.xy / gl_Position.w * u_gl_units_to_pixels);\\n v_gamma_scale = extrude_length_without_perspective / extrude_length_with_perspective;\\n\\n v_tex_a = vec2(a_linesofar * u_patternscale_a.x / floorwidth, normal.y * u_patternscale_a.y + u_tex_y_a);\\n v_tex_b = vec2(a_linesofar * u_patternscale_b.x / floorwidth, normal.y * u_patternscale_b.y + u_tex_y_b);\\n\\n v_width2 = vec2(outset, inset);\\n}\\n\"},raster:{fragmentSource:\"uniform float u_fade_t;\\nuniform float u_opacity;\\nuniform sampler2D u_image0;\\nuniform sampler2D u_image1;\\nvarying vec2 v_pos0;\\nvarying vec2 v_pos1;\\n\\nuniform float u_brightness_low;\\nuniform float u_brightness_high;\\n\\nuniform float u_saturation_factor;\\nuniform float u_contrast_factor;\\nuniform vec3 u_spin_weights;\\n\\nvoid main() {\\n\\n // read and cross-fade colors from the main and parent tiles\\n vec4 color0 = texture2D(u_image0, v_pos0);\\n vec4 color1 = texture2D(u_image1, v_pos1);\\n if (color0.a > 0.0) {\\n color0.rgb = color0.rgb / color0.a;\\n }\\n if (color1.a > 0.0) {\\n color1.rgb = color1.rgb / color1.a;\\n }\\n vec4 color = mix(color0, color1, u_fade_t);\\n color.a *= u_opacity;\\n vec3 rgb = color.rgb;\\n\\n // spin\\n rgb = vec3(\\n dot(rgb, u_spin_weights.xyz),\\n dot(rgb, u_spin_weights.zxy),\\n dot(rgb, u_spin_weights.yzx));\\n\\n // saturation\\n float average = (color.r + color.g + color.b) / 3.0;\\n rgb += (average - rgb) * u_saturation_factor;\\n\\n // contrast\\n rgb = (rgb - 0.5) * u_contrast_factor + 0.5;\\n\\n // brightness\\n vec3 u_high_vec = vec3(u_brightness_low, u_brightness_low, u_brightness_low);\\n vec3 u_low_vec = vec3(u_brightness_high, u_brightness_high, u_brightness_high);\\n\\n gl_FragColor = vec4(mix(u_high_vec, u_low_vec, rgb) * color.a, color.a);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"uniform mat4 u_matrix;\\nuniform vec2 u_tl_parent;\\nuniform float u_scale_parent;\\nuniform float u_buffer_scale;\\n\\nattribute vec2 a_pos;\\nattribute vec2 a_texture_pos;\\n\\nvarying vec2 v_pos0;\\nvarying vec2 v_pos1;\\n\\nvoid main() {\\n gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n // We are using Int16 for texture position coordinates to give us enough precision for\\n // fractional coordinates. We use 8192 to scale the texture coordinates in the buffer\\n // as an arbitrarily high number to preserve adequate precision when rendering.\\n // This is also the same value as the EXTENT we are using for our tile buffer pos coordinates,\\n // so math for modifying either is consistent.\\n v_pos0 = (((a_texture_pos / 8192.0) - 0.5) / u_buffer_scale ) + 0.5;\\n v_pos1 = (v_pos0 * u_scale_parent) + u_tl_parent;\\n}\\n\"},symbolIcon:{fragmentSource:\"uniform sampler2D u_texture;\\n\\n#pragma mapbox: define lowp float opacity\\n\\nvarying vec2 v_tex;\\nvarying float v_fade_opacity;\\n\\nvoid main() {\\n #pragma mapbox: initialize lowp float opacity\\n\\n lowp float alpha = opacity * v_fade_opacity;\\n gl_FragColor = texture2D(u_texture, v_tex) * alpha;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"const float PI = 3.141592653589793;\\n\\nattribute vec4 a_pos_offset;\\nattribute vec4 a_data;\\nattribute vec3 a_projected_pos;\\nattribute float a_fade_opacity;\\n\\nuniform bool u_is_size_zoom_constant;\\nuniform bool u_is_size_feature_constant;\\nuniform highp float u_size_t; // used to interpolate between zoom stops when size is a composite function\\nuniform highp float u_size; // used when size is both zoom and feature constant\\nuniform highp float u_camera_to_center_distance;\\nuniform highp float u_pitch;\\nuniform bool u_rotate_symbol;\\nuniform highp float u_aspect_ratio;\\nuniform float u_fade_change;\\n\\n#pragma mapbox: define lowp float opacity\\n\\nuniform mat4 u_matrix;\\nuniform mat4 u_label_plane_matrix;\\nuniform mat4 u_gl_coord_matrix;\\n\\nuniform bool u_is_text;\\nuniform bool u_pitch_with_map;\\n\\nuniform vec2 u_texsize;\\n\\nvarying vec2 v_tex;\\nvarying float v_fade_opacity;\\n\\nvoid main() {\\n #pragma mapbox: initialize lowp float opacity\\n\\n vec2 a_pos = a_pos_offset.xy;\\n vec2 a_offset = a_pos_offset.zw;\\n\\n vec2 a_tex = a_data.xy;\\n vec2 a_size = a_data.zw;\\n\\n highp float segment_angle = -a_projected_pos[2];\\n\\n float size;\\n if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {\\n size = mix(a_size[0], a_size[1], u_size_t) / 10.0;\\n } else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {\\n size = a_size[0] / 10.0;\\n } else if (!u_is_size_zoom_constant && u_is_size_feature_constant) {\\n size = u_size;\\n } else {\\n size = u_size;\\n }\\n\\n vec4 projectedPoint = u_matrix * vec4(a_pos, 0, 1);\\n highp float camera_to_anchor_distance = projectedPoint.w;\\n // See comments in symbol_sdf.vertex\\n highp float distance_ratio = u_pitch_with_map ?\\n camera_to_anchor_distance / u_camera_to_center_distance :\\n u_camera_to_center_distance / camera_to_anchor_distance;\\n highp float perspective_ratio = clamp(\\n 0.5 + 0.5 * distance_ratio,\\n 0.0, // Prevents oversized near-field symbols in pitched/overzoomed tiles\\n 4.0);\\n\\n size *= perspective_ratio;\\n\\n float fontScale = u_is_text ? size / 24.0 : size;\\n\\n highp float symbol_rotation = 0.0;\\n if (u_rotate_symbol) {\\n // See comments in symbol_sdf.vertex\\n vec4 offsetProjectedPoint = u_matrix * vec4(a_pos + vec2(1, 0), 0, 1);\\n\\n vec2 a = projectedPoint.xy / projectedPoint.w;\\n vec2 b = offsetProjectedPoint.xy / offsetProjectedPoint.w;\\n\\n symbol_rotation = atan((b.y - a.y) / u_aspect_ratio, b.x - a.x);\\n }\\n\\n highp float angle_sin = sin(segment_angle + symbol_rotation);\\n highp float angle_cos = cos(segment_angle + symbol_rotation);\\n mat2 rotation_matrix = mat2(angle_cos, -1.0 * angle_sin, angle_sin, angle_cos);\\n\\n vec4 projected_pos = u_label_plane_matrix * vec4(a_projected_pos.xy, 0.0, 1.0);\\n gl_Position = u_gl_coord_matrix * vec4(projected_pos.xy / projected_pos.w + rotation_matrix * (a_offset / 32.0 * fontScale), 0.0, 1.0);\\n\\n v_tex = a_tex / u_texsize;\\n vec2 fade_opacity = unpack_opacity(a_fade_opacity);\\n float fade_change = fade_opacity[1] > 0.5 ? u_fade_change : -u_fade_change;\\n v_fade_opacity = max(0.0, min(1.0, fade_opacity[0] + fade_change));\\n}\\n\"},symbolSDF:{fragmentSource:\"#define SDF_PX 8.0\\n#define EDGE_GAMMA 0.105/DEVICE_PIXEL_RATIO\\n\\nuniform bool u_is_halo;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\n\\nuniform sampler2D u_texture;\\nuniform highp float u_gamma_scale;\\nuniform bool u_is_text;\\n\\nvarying vec2 v_data0;\\nvarying vec3 v_data1;\\n\\nvoid main() {\\n #pragma mapbox: initialize highp vec4 fill_color\\n #pragma mapbox: initialize highp vec4 halo_color\\n #pragma mapbox: initialize lowp float opacity\\n #pragma mapbox: initialize lowp float halo_width\\n #pragma mapbox: initialize lowp float halo_blur\\n\\n vec2 tex = v_data0.xy;\\n float gamma_scale = v_data1.x;\\n float size = v_data1.y;\\n float fade_opacity = v_data1[2];\\n\\n float fontScale = u_is_text ? size / 24.0 : size;\\n\\n lowp vec4 color = fill_color;\\n highp float gamma = EDGE_GAMMA / (fontScale * u_gamma_scale);\\n lowp float buff = (256.0 - 64.0) / 256.0;\\n if (u_is_halo) {\\n color = halo_color;\\n gamma = (halo_blur * 1.19 / SDF_PX + EDGE_GAMMA) / (fontScale * u_gamma_scale);\\n buff = (6.0 - halo_width / fontScale) / SDF_PX;\\n }\\n\\n lowp float dist = texture2D(u_texture, tex).a;\\n highp float gamma_scaled = gamma * gamma_scale;\\n highp float alpha = smoothstep(buff - gamma_scaled, buff + gamma_scaled, dist);\\n\\n gl_FragColor = color * (alpha * opacity * fade_opacity);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"const float PI = 3.141592653589793;\\n\\nattribute vec4 a_pos_offset;\\nattribute vec4 a_data;\\nattribute vec3 a_projected_pos;\\nattribute float a_fade_opacity;\\n\\n// contents of a_size vary based on the type of property value\\n// used for {text,icon}-size.\\n// For constants, a_size is disabled.\\n// For source functions, we bind only one value per vertex: the value of {text,icon}-size evaluated for the current feature.\\n// For composite functions:\\n// [ text-size(lowerZoomStop, feature),\\n// text-size(upperZoomStop, feature) ]\\nuniform bool u_is_size_zoom_constant;\\nuniform bool u_is_size_feature_constant;\\nuniform highp float u_size_t; // used to interpolate between zoom stops when size is a composite function\\nuniform highp float u_size; // used when size is both zoom and feature constant\\n\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\n\\nuniform mat4 u_matrix;\\nuniform mat4 u_label_plane_matrix;\\nuniform mat4 u_gl_coord_matrix;\\n\\nuniform bool u_is_text;\\nuniform bool u_pitch_with_map;\\nuniform highp float u_pitch;\\nuniform bool u_rotate_symbol;\\nuniform highp float u_aspect_ratio;\\nuniform highp float u_camera_to_center_distance;\\nuniform float u_fade_change;\\n\\nuniform vec2 u_texsize;\\n\\nvarying vec2 v_data0;\\nvarying vec3 v_data1;\\n\\nvoid main() {\\n #pragma mapbox: initialize highp vec4 fill_color\\n #pragma mapbox: initialize highp vec4 halo_color\\n #pragma mapbox: initialize lowp float opacity\\n #pragma mapbox: initialize lowp float halo_width\\n #pragma mapbox: initialize lowp float halo_blur\\n\\n vec2 a_pos = a_pos_offset.xy;\\n vec2 a_offset = a_pos_offset.zw;\\n\\n vec2 a_tex = a_data.xy;\\n vec2 a_size = a_data.zw;\\n\\n highp float segment_angle = -a_projected_pos[2];\\n float size;\\n\\n if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {\\n size = mix(a_size[0], a_size[1], u_size_t) / 10.0;\\n } else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {\\n size = a_size[0] / 10.0;\\n } else if (!u_is_size_zoom_constant && u_is_size_feature_constant) {\\n size = u_size;\\n } else {\\n size = u_size;\\n }\\n\\n vec4 projectedPoint = u_matrix * vec4(a_pos, 0, 1);\\n highp float camera_to_anchor_distance = projectedPoint.w;\\n // If the label is pitched with the map, layout is done in pitched space,\\n // which makes labels in the distance smaller relative to viewport space.\\n // We counteract part of that effect by multiplying by the perspective ratio.\\n // If the label isn't pitched with the map, we do layout in viewport space,\\n // which makes labels in the distance larger relative to the features around\\n // them. We counteract part of that effect by dividing by the perspective ratio.\\n highp float distance_ratio = u_pitch_with_map ?\\n camera_to_anchor_distance / u_camera_to_center_distance :\\n u_camera_to_center_distance / camera_to_anchor_distance;\\n highp float perspective_ratio = clamp(\\n 0.5 + 0.5 * distance_ratio,\\n 0.0, // Prevents oversized near-field symbols in pitched/overzoomed tiles\\n 4.0);\\n\\n size *= perspective_ratio;\\n\\n float fontScale = u_is_text ? size / 24.0 : size;\\n\\n highp float symbol_rotation = 0.0;\\n if (u_rotate_symbol) {\\n // Point labels with 'rotation-alignment: map' are horizontal with respect to tile units\\n // To figure out that angle in projected space, we draw a short horizontal line in tile\\n // space, project it, and measure its angle in projected space.\\n vec4 offsetProjectedPoint = u_matrix * vec4(a_pos + vec2(1, 0), 0, 1);\\n\\n vec2 a = projectedPoint.xy / projectedPoint.w;\\n vec2 b = offsetProjectedPoint.xy / offsetProjectedPoint.w;\\n\\n symbol_rotation = atan((b.y - a.y) / u_aspect_ratio, b.x - a.x);\\n }\\n\\n highp float angle_sin = sin(segment_angle + symbol_rotation);\\n highp float angle_cos = cos(segment_angle + symbol_rotation);\\n mat2 rotation_matrix = mat2(angle_cos, -1.0 * angle_sin, angle_sin, angle_cos);\\n\\n vec4 projected_pos = u_label_plane_matrix * vec4(a_projected_pos.xy, 0.0, 1.0);\\n gl_Position = u_gl_coord_matrix * vec4(projected_pos.xy / projected_pos.w + rotation_matrix * (a_offset / 32.0 * fontScale), 0.0, 1.0);\\n float gamma_scale = gl_Position.w;\\n\\n vec2 tex = a_tex / u_texsize;\\n vec2 fade_opacity = unpack_opacity(a_fade_opacity);\\n float fade_change = fade_opacity[1] > 0.5 ? u_fade_change : -u_fade_change;\\n float interpolated_fade_opacity = max(0.0, min(1.0, fade_opacity[0] + fade_change));\\n\\n v_data0 = vec2(tex.x, tex.y);\\n v_data1 = vec3(gamma_scale, size, interpolated_fade_opacity);\\n}\\n\"}},tr=/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,er=function(t){var e=Qe[t],r={};e.fragmentSource=e.fragmentSource.replace(tr,function(t,e,n,i,a){return r[a]=!0,\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nvarying \"+n+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+n+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"\\n#ifdef HAS_UNIFORM_u_\"+a+\"\\n \"+n+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"}),e.vertexSource=e.vertexSource.replace(tr,function(t,e,n,i,a){var o=\"float\"===i?\"vec2\":\"vec4\";return r[a]?\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float a_\"+a+\"_t;\\nattribute \"+n+\" \"+o+\" a_\"+a+\";\\nvarying \"+n+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+n+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n \"+a+\" = unpack_mix_\"+o+\"(a_\"+a+\", a_\"+a+\"_t);\\n#else\\n \"+n+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float a_\"+a+\"_t;\\nattribute \"+n+\" \"+o+\" a_\"+a+\";\\n#else\\nuniform \"+n+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n \"+n+\" \"+i+\" \"+a+\" = unpack_mix_\"+o+\"(a_\"+a+\", a_\"+a+\"_t);\\n#else\\n \"+n+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"})};for(var rr in Qe)er(rr);var nr=Qe,ir=function(t,e,r,n){var i=t.gl;this.program=i.createProgram();var o=r.defines().concat(\"#define DEVICE_PIXEL_RATIO \"+a.devicePixelRatio.toFixed(1));n&&o.push(\"#define OVERDRAW_INSPECTOR;\");var s=o.concat(nr.prelude.fragmentSource,e.fragmentSource).join(\"\\n\"),l=o.concat(nr.prelude.vertexSource,e.vertexSource).join(\"\\n\"),c=i.createShader(i.FRAGMENT_SHADER);i.shaderSource(c,s),i.compileShader(c),i.attachShader(this.program,c);var u=i.createShader(i.VERTEX_SHADER);i.shaderSource(u,l),i.compileShader(u),i.attachShader(this.program,u);for(var f=r.layoutAttributes||[],h=0;h<f.length;h++)i.bindAttribLocation(this.program,h,f[h].name);i.linkProgram(this.program),this.numAttributes=i.getProgramParameter(this.program,i.ACTIVE_ATTRIBUTES),this.attributes={},this.uniforms={};for(var p=0;p<this.numAttributes;p++){var d=i.getActiveAttrib(this.program,p);d&&(this.attributes[d.name]=i.getAttribLocation(this.program,d.name))}for(var g=i.getProgramParameter(this.program,i.ACTIVE_UNIFORMS),v=0;v<g;v++){var m=i.getActiveUniform(this.program,v);m&&(this.uniforms[m.name]=i.getUniformLocation(this.program,m.name))}};function ar(e,r,n,i,a){for(var o=0;o<n.length;o++){var s=n[o];if(i.isLessThan(s.tileID))break;if(r.key===s.tileID.key)return;if(s.tileID.isChildOf(r)){for(var l=r.children(1/0),c=0;c<l.length;c++)ar(e,l[c],n.slice(o),i,a);return}}var u=r.overscaledZ-e.overscaledZ,f=new t.CanonicalTileID(u,r.canonical.x-(e.canonical.x<<u),r.canonical.y-(e.canonical.y<<u));a[f.key]=a[f.key]||f}function or(t,e,r,n,i){var a=t.context,o=a.gl,s=i?t.useProgram(\"collisionCircle\"):t.useProgram(\"collisionBox\");a.setDepthMode(Ht.disabled),a.setStencilMode(qt.disabled),a.setColorMode(t.colorModeForRenderPass());for(var l=0;l<n.length;l++){var c=n[l],u=e.getTile(c),f=u.getBucket(r);if(f){var h=i?f.collisionCircle:f.collisionBox;if(h){o.uniformMatrix4fv(s.uniforms.u_matrix,!1,c.posMatrix),i||a.lineWidth.set(1),o.uniform1f(s.uniforms.u_camera_to_center_distance,t.transform.cameraToCenterDistance);var p=Me(u,1,t.transform.zoom),d=Math.pow(2,t.transform.zoom-u.tileID.overscaledZ);o.uniform1f(s.uniforms.u_pixels_to_tile_units,p),o.uniform2f(s.uniforms.u_extrude_scale,t.transform.pixelsToGLUnits[0]/(p*d),t.transform.pixelsToGLUnits[1]/(p*d)),o.uniform1f(s.uniforms.u_overscale_factor,u.tileID.overscaleFactor()),s.draw(a,i?o.TRIANGLES:o.LINES,r.id,h.layoutVertexBuffer,h.indexBuffer,h.segments,null,h.collisionVertexBuffer,null)}}}}ir.prototype.draw=function(t,e,r,n,i,a,o,s,l){for(var c,u=t.gl,f=(c={},c[u.LINES]=2,c[u.TRIANGLES]=3,c)[e],h=0,p=a.get();h<p.length;h+=1){var d=p[h],g=d.vaos||(d.vaos={});(g[r]||(g[r]=new Q)).bind(t,this,n,o?o.getPaintVertexBuffers():[],i,d.vertexOffset,s,l),u.drawElements(e,d.primitiveLength*f,u.UNSIGNED_SHORT,d.primitiveOffset*f*2)}};var sr=t.mat4.identity(new Float32Array(16)),lr=t.default$19.layout;function cr(t,e,r,n,i,a,o,s,l,c){var u,f=t.context,h=f.gl,p=t.transform,d=\"map\"===s,g=\"map\"===l,v=d&&\"line\"===r.layout.get(\"symbol-placement\"),m=d&&!g&&!v,y=g;f.setDepthMode(y?t.depthModeForSublayer(0,Ht.ReadOnly):Ht.disabled);for(var x=0,b=n;x<b.length;x+=1){var _=b[x],w=e.getTile(_),k=w.getBucket(r);if(k){var T=i?k.text:k.icon;if(T&&T.segments.get().length){var A=T.programConfigurations.get(r.id),M=i||k.sdfIcons,S=i?k.textSizeData:k.iconSizeData;if(u||(u=t.useProgram(M?\"symbolSDF\":\"symbolIcon\",A),A.setUniforms(t.context,u,r.paint,{zoom:t.transform.zoom}),ur(u,t,r,i,m,g,S)),f.activeTexture.set(h.TEXTURE0),h.uniform1i(u.uniforms.u_texture,0),i)w.glyphAtlasTexture.bind(h.LINEAR,h.CLAMP_TO_EDGE),h.uniform2fv(u.uniforms.u_texsize,w.glyphAtlasTexture.size);else{var E=1!==r.layout.get(\"icon-size\").constantOr(0)||k.iconsNeedLinear,C=g||0!==p.pitch;w.iconAtlasTexture.bind(M||t.options.rotating||t.options.zooming||E||C?h.LINEAR:h.NEAREST,h.CLAMP_TO_EDGE),h.uniform2fv(u.uniforms.u_texsize,w.iconAtlasTexture.size)}h.uniformMatrix4fv(u.uniforms.u_matrix,!1,t.translatePosMatrix(_.posMatrix,w,a,o));var L=Me(w,1,t.transform.zoom),z=fe(_.posMatrix,g,d,t.transform,L),O=he(_.posMatrix,g,d,t.transform,L);h.uniformMatrix4fv(u.uniforms.u_gl_coord_matrix,!1,t.translatePosMatrix(O,w,a,o,!0)),v?(h.uniformMatrix4fv(u.uniforms.u_label_plane_matrix,!1,sr),ge(k,_.posMatrix,t,i,z,O,g,c)):h.uniformMatrix4fv(u.uniforms.u_label_plane_matrix,!1,z),h.uniform1f(u.uniforms.u_fade_change,t.options.fadeDuration?t.symbolFadeChange:1),fr(u,A,t,r,w,T,i,M,g)}}}}function ur(e,r,n,i,a,o,s){var l=r.context.gl,c=r.transform;l.uniform1i(e.uniforms.u_pitch_with_map,o?1:0),l.uniform1f(e.uniforms.u_is_text,i?1:0),l.uniform1f(e.uniforms.u_pitch,c.pitch/360*2*Math.PI);var u=\"constant\"===s.functionType||\"source\"===s.functionType,f=\"constant\"===s.functionType||\"camera\"===s.functionType;l.uniform1i(e.uniforms.u_is_size_zoom_constant,u?1:0),l.uniform1i(e.uniforms.u_is_size_feature_constant,f?1:0),l.uniform1f(e.uniforms.u_camera_to_center_distance,c.cameraToCenterDistance);var h=t.evaluateSizeForZoom(s,c.zoom,lr.properties[i?\"text-size\":\"icon-size\"]);void 0!==h.uSizeT&&l.uniform1f(e.uniforms.u_size_t,h.uSizeT),void 0!==h.uSize&&l.uniform1f(e.uniforms.u_size,h.uSize),l.uniform1f(e.uniforms.u_aspect_ratio,c.width/c.height),l.uniform1i(e.uniforms.u_rotate_symbol,a?1:0)}function fr(t,e,r,n,i,a,o,s,l){var c=r.context,u=c.gl,f=r.transform;if(s){var h=0!==n.paint.get(o?\"text-halo-width\":\"icon-halo-width\").constantOr(1),p=l?Math.cos(f._pitch)*f.cameraToCenterDistance:1;u.uniform1f(t.uniforms.u_gamma_scale,p),h&&(u.uniform1f(t.uniforms.u_is_halo,1),hr(a,n,c,t)),u.uniform1f(t.uniforms.u_is_halo,0)}hr(a,n,c,t)}function hr(t,e,r,n){n.draw(r,r.gl.TRIANGLES,e.id,t.layoutVertexBuffer,t.indexBuffer,t.segments,t.programConfigurations.get(e.id),t.dynamicLayoutVertexBuffer,t.opacityVertexBuffer)}function pr(t,e,r,n,i,o,s,l,c){var u,f,h,p,d=e.context,g=d.gl,v=i.paint.get(\"line-dasharray\"),m=i.paint.get(\"line-pattern\");if(l||c){var y=1/Me(r,1,e.transform.tileZoom);if(v){u=e.lineAtlas.getDash(v.from,\"round\"===i.layout.get(\"line-cap\")),f=e.lineAtlas.getDash(v.to,\"round\"===i.layout.get(\"line-cap\"));var x=u.width*v.fromScale,b=f.width*v.toScale;g.uniform2f(t.uniforms.u_patternscale_a,y/x,-u.height/2),g.uniform2f(t.uniforms.u_patternscale_b,y/b,-f.height/2),g.uniform1f(t.uniforms.u_sdfgamma,e.lineAtlas.width/(256*Math.min(x,b)*a.devicePixelRatio)/2)}else if(m){if(h=e.imageManager.getPattern(m.from),p=e.imageManager.getPattern(m.to),!h||!p)return;g.uniform2f(t.uniforms.u_pattern_size_a,h.displaySize[0]*m.fromScale/y,h.displaySize[1]),g.uniform2f(t.uniforms.u_pattern_size_b,p.displaySize[0]*m.toScale/y,p.displaySize[1]);var _=e.imageManager.getPixelSize(),w=_.width,k=_.height;g.uniform2fv(t.uniforms.u_texsize,[w,k])}g.uniform2f(t.uniforms.u_gl_units_to_pixels,1/e.transform.pixelsToGLUnits[0],1/e.transform.pixelsToGLUnits[1])}l&&(v?(g.uniform1i(t.uniforms.u_image,0),d.activeTexture.set(g.TEXTURE0),e.lineAtlas.bind(d),g.uniform1f(t.uniforms.u_tex_y_a,u.y),g.uniform1f(t.uniforms.u_tex_y_b,f.y),g.uniform1f(t.uniforms.u_mix,v.t)):m&&(g.uniform1i(t.uniforms.u_image,0),d.activeTexture.set(g.TEXTURE0),e.imageManager.bind(d),g.uniform2fv(t.uniforms.u_pattern_tl_a,h.tl),g.uniform2fv(t.uniforms.u_pattern_br_a,h.br),g.uniform2fv(t.uniforms.u_pattern_tl_b,p.tl),g.uniform2fv(t.uniforms.u_pattern_br_b,p.br),g.uniform1f(t.uniforms.u_fade,m.t))),d.setStencilMode(e.stencilModeForClipping(o));var T=e.translatePosMatrix(o.posMatrix,r,i.paint.get(\"line-translate\"),i.paint.get(\"line-translate-anchor\"));if(g.uniformMatrix4fv(t.uniforms.u_matrix,!1,T),g.uniform1f(t.uniforms.u_ratio,1/Me(r,1,e.transform.zoom)),i.paint.get(\"line-gradient\")){d.activeTexture.set(g.TEXTURE0);var A=i.gradientTexture;if(!i.gradient)return;A||(A=i.gradientTexture=new z(d,i.gradient,g.RGBA)),A.bind(g.LINEAR,g.CLAMP_TO_EDGE),g.uniform1i(t.uniforms.u_image,0)}t.draw(d,g.TRIANGLES,i.id,n.layoutVertexBuffer,n.indexBuffer,n.segments,s)}var dr=function(t,e){if(!t)return!1;var r=e.imageManager.getPattern(t.from),n=e.imageManager.getPattern(t.to);return!r||!n},gr=function(t,e,r){var n=e.context,i=n.gl,a=e.imageManager.getPattern(t.from),o=e.imageManager.getPattern(t.to);i.uniform1i(r.uniforms.u_image,0),i.uniform2fv(r.uniforms.u_pattern_tl_a,a.tl),i.uniform2fv(r.uniforms.u_pattern_br_a,a.br),i.uniform2fv(r.uniforms.u_pattern_tl_b,o.tl),i.uniform2fv(r.uniforms.u_pattern_br_b,o.br);var s=e.imageManager.getPixelSize(),l=s.width,c=s.height;i.uniform2fv(r.uniforms.u_texsize,[l,c]),i.uniform1f(r.uniforms.u_mix,t.t),i.uniform2fv(r.uniforms.u_pattern_size_a,a.displaySize),i.uniform2fv(r.uniforms.u_pattern_size_b,o.displaySize),i.uniform1f(r.uniforms.u_scale_a,t.fromScale),i.uniform1f(r.uniforms.u_scale_b,t.toScale),n.activeTexture.set(i.TEXTURE0),e.imageManager.bind(e.context)},vr=function(t,e,r){var n=e.context.gl;n.uniform1f(r.uniforms.u_tile_units_to_pixels,1/Me(t,1,e.transform.tileZoom));var i=Math.pow(2,t.tileID.overscaledZ),a=t.tileSize*Math.pow(2,e.transform.tileZoom)/i,o=a*(t.tileID.canonical.x+t.tileID.wrap*i),s=a*t.tileID.canonical.y;n.uniform2f(r.uniforms.u_pixel_coord_upper,o>>16,s>>16),n.uniform2f(r.uniforms.u_pixel_coord_lower,65535&o,65535&s)};function mr(t,e,r,n,i){if(!dr(r.paint.get(\"fill-pattern\"),t))for(var a=!0,o=0,s=n;o<s.length;o+=1){var l=s[o],c=e.getTile(l),u=c.getBucket(r);u&&(t.context.setStencilMode(t.stencilModeForClipping(l)),i(t,e,r,c,l,u,a),a=!1)}}function yr(t,e,r,n,i,a,o){var s=t.context.gl,l=a.programConfigurations.get(r.id);br(\"fill\",r.paint.get(\"fill-pattern\"),t,l,r,n,i,o).draw(t.context,s.TRIANGLES,r.id,a.layoutVertexBuffer,a.indexBuffer,a.segments,l)}function xr(t,e,r,n,i,a,o){var s=t.context.gl,l=a.programConfigurations.get(r.id),c=br(\"fillOutline\",r.getPaintProperty(\"fill-outline-color\")?null:r.paint.get(\"fill-pattern\"),t,l,r,n,i,o);s.uniform2f(c.uniforms.u_world,s.drawingBufferWidth,s.drawingBufferHeight),c.draw(t.context,s.LINES,r.id,a.layoutVertexBuffer,a.indexBuffer2,a.segments2,l)}function br(t,e,r,n,i,a,o,s){var l,c=r.context.program.get();return e?(l=r.useProgram(t+\"Pattern\",n),(s||l.program!==c)&&(n.setUniforms(r.context,l,i.paint,{zoom:r.transform.zoom}),gr(e,r,l)),vr(a,r,l)):(l=r.useProgram(t,n),(s||l.program!==c)&&n.setUniforms(r.context,l,i.paint,{zoom:r.transform.zoom})),r.context.gl.uniformMatrix4fv(l.uniforms.u_matrix,!1,r.translatePosMatrix(o.posMatrix,a,i.paint.get(\"fill-translate\"),i.paint.get(\"fill-translate-anchor\"))),l}var _r=t.default$20.mat3,wr=t.default$20.mat4,kr=t.default$20.vec3;function Tr(t,e,r,n,i,a,o){var s=t.context,l=s.gl,c=r.paint.get(\"fill-extrusion-pattern\"),u=t.context.program.get(),f=a.programConfigurations.get(r.id),h=t.useProgram(c?\"fillExtrusionPattern\":\"fillExtrusion\",f);if((o||h.program!==u)&&f.setUniforms(s,h,r.paint,{zoom:t.transform.zoom}),c){if(dr(c,t))return;gr(c,t,h),vr(n,t,h),l.uniform1f(h.uniforms.u_height_factor,-Math.pow(2,i.overscaledZ)/n.tileSize/8)}t.context.gl.uniformMatrix4fv(h.uniforms.u_matrix,!1,t.translatePosMatrix(i.posMatrix,n,r.paint.get(\"fill-extrusion-translate\"),r.paint.get(\"fill-extrusion-translate-anchor\"))),function(t,e){var r=e.context.gl,n=e.style.light,i=n.properties.get(\"position\"),a=[i.x,i.y,i.z],o=_r.create();\"viewport\"===n.properties.get(\"anchor\")&&_r.fromRotation(o,-e.transform.angle),kr.transformMat3(a,a,o);var s=n.properties.get(\"color\");r.uniform3fv(t.uniforms.u_lightpos,a),r.uniform1f(t.uniforms.u_lightintensity,n.properties.get(\"intensity\")),r.uniform3f(t.uniforms.u_lightcolor,s.r,s.g,s.b)}(h,t),h.draw(s,l.TRIANGLES,r.id,a.layoutVertexBuffer,a.indexBuffer,a.segments,f)}function Ar(e,r,n){var i=e.context,a=i.gl,o=r.fbo;if(o){var s=e.useProgram(\"hillshade\"),l=e.transform.calculatePosMatrix(r.tileID.toUnwrapped(),!0);!function(t,e,r){var n=r.paint.get(\"hillshade-illumination-direction\")*(Math.PI/180);\"viewport\"===r.paint.get(\"hillshade-illumination-anchor\")&&(n-=e.transform.angle),e.context.gl.uniform2f(t.uniforms.u_light,r.paint.get(\"hillshade-exaggeration\"),n)}(s,e,n);var c=function(e,r){var n=r.toCoordinate(),i=new t.default$17(n.column,n.row+1,n.zoom);return[e.transform.coordinateLocation(n).lat,e.transform.coordinateLocation(i).lat]}(e,r.tileID);i.activeTexture.set(a.TEXTURE0),a.bindTexture(a.TEXTURE_2D,o.colorAttachment.get()),a.uniformMatrix4fv(s.uniforms.u_matrix,!1,l),a.uniform2fv(s.uniforms.u_latrange,c),a.uniform1i(s.uniforms.u_image,0);var u=n.paint.get(\"hillshade-shadow-color\");a.uniform4f(s.uniforms.u_shadow,u.r,u.g,u.b,u.a);var f=n.paint.get(\"hillshade-highlight-color\");a.uniform4f(s.uniforms.u_highlight,f.r,f.g,f.b,f.a);var h=n.paint.get(\"hillshade-accent-color\");if(a.uniform4f(s.uniforms.u_accent,h.r,h.g,h.b,h.a),r.maskedBoundsBuffer&&r.maskedIndexBuffer&&r.segments)s.draw(i,a.TRIANGLES,n.id,r.maskedBoundsBuffer,r.maskedIndexBuffer,r.segments);else{var p=e.rasterBoundsBuffer;e.rasterBoundsVAO.bind(i,s,p,[]),a.drawArrays(a.TRIANGLE_STRIP,0,p.length)}}}function Mr(e,r,n){var i=e.context,a=i.gl;if(r.dem&&r.dem.level){var o=r.dem.level.dim,s=r.dem.getPixels();if(i.activeTexture.set(a.TEXTURE1),i.pixelStoreUnpackPremultiplyAlpha.set(!1),r.demTexture=r.demTexture||e.getTileTexture(r.tileSize),r.demTexture){var l=r.demTexture;l.update(s,{premultiply:!1}),l.bind(a.NEAREST,a.CLAMP_TO_EDGE)}else r.demTexture=new z(i,s,a.RGBA,{premultiply:!1}),r.demTexture.bind(a.NEAREST,a.CLAMP_TO_EDGE);i.activeTexture.set(a.TEXTURE0);var c=r.fbo;if(!c){var u=new z(i,{width:o,height:o,data:null},a.RGBA);u.bind(a.LINEAR,a.CLAMP_TO_EDGE),(c=r.fbo=i.createFramebuffer(o,o)).colorAttachment.set(u.texture)}i.bindFramebuffer.set(c.framebuffer),i.viewport.set([0,0,o,o]);var f=t.mat4.create();t.mat4.ortho(f,0,t.default$8,-t.default$8,0,0,1),t.mat4.translate(f,f,[0,-t.default$8,0]);var h=e.useProgram(\"hillshadePrepare\");a.uniformMatrix4fv(h.uniforms.u_matrix,!1,f),a.uniform1f(h.uniforms.u_zoom,r.tileID.overscaledZ),a.uniform2fv(h.uniforms.u_dimension,[2*o,2*o]),a.uniform1i(h.uniforms.u_image,1),a.uniform1f(h.uniforms.u_maxzoom,n);var p=e.rasterBoundsBuffer;e.rasterBoundsVAO.bind(i,h,p,[]),a.drawArrays(a.TRIANGLE_STRIP,0,p.length),r.needsHillshadePrepare=!1}}function Sr(e,r,n,i,o){var s=i.paint.get(\"raster-fade-duration\");if(s>0){var l=a.now(),c=(l-e.timeAdded)/s,u=r?(l-r.timeAdded)/s:-1,f=n.getSource(),h=o.coveringZoomLevel({tileSize:f.tileSize,roundZoom:f.roundZoom}),p=!r||Math.abs(r.tileID.overscaledZ-h)>Math.abs(e.tileID.overscaledZ-h),d=p&&e.refreshedUponExpiration?1:t.clamp(p?c:1-u,0,1);return e.refreshedUponExpiration&&c>=1&&(e.refreshedUponExpiration=!1),r?{opacity:1,mix:1-d}:{opacity:d,mix:0}}return{opacity:1,mix:0}}function Er(e,r,n){var i=e.context,o=i.gl;i.lineWidth.set(1*a.devicePixelRatio);var 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a=n.createTexture();n.bindTexture(n.TEXTURE_2D,a),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,n.LINEAR),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,n.LINEAR),i=r.heatmapFbo=t.createFramebuffer(e.width/4,e.height/4),function t(e,r,n,i){var a=e.gl;a.texImage2D(a.TEXTURE_2D,0,a.RGBA,r.width/4,r.height/4,0,a.RGBA,e.extTextureHalfFloat?e.extTextureHalfFloat.HALF_FLOAT_OES:a.UNSIGNED_BYTE,null),i.colorAttachment.set(n),e.extTextureHalfFloat&&a.checkFramebufferStatus(a.FRAMEBUFFER)!==a.FRAMEBUFFER_COMPLETE&&(e.extTextureHalfFloat=null,i.colorAttachment.setDirty(),t(e,r,n,i))}(t,e,a,i)}}(a,e,n),a.clear({color:t.default$6.transparent}),a.setColorMode(new Gt([o.ONE,o.ONE],t.default$6.transparent,[!0,!0,!0,!0]));for(var s=!0,l=0;l<i.length;l++){var c=i[l];if(!r.hasRenderableParent(c)){var u=r.getTile(c),f=u.getBucket(n);if(f){var h=e.context.program.get(),p=f.programConfigurations.get(n.id),d=e.useProgram(\"heatmap\",p),g=e.transform.zoom;(s||d.program!==h)&&(p.setUniforms(e.context,d,n.paint,{zoom:g}),s=!1),o.uniform1f(d.uniforms.u_extrude_scale,Me(u,1,g)),o.uniform1f(d.uniforms.u_intensity,n.paint.get(\"heatmap-intensity\")),o.uniformMatrix4fv(d.uniforms.u_matrix,!1,c.posMatrix),d.draw(a,o.TRIANGLES,n.id,f.layoutVertexBuffer,f.indexBuffer,f.segments,p)}}}a.viewport.set([0,0,e.width,e.height])}else\"translucent\"===e.renderPass&&(e.context.setColorMode(e.colorModeForRenderPass()),function(e,r){var n=e.context,i=n.gl,a=r.heatmapFbo;if(a){n.activeTexture.set(i.TEXTURE0),i.bindTexture(i.TEXTURE_2D,a.colorAttachment.get()),n.activeTexture.set(i.TEXTURE1);var o=r.colorRampTexture;o||(o=r.colorRampTexture=new z(n,r.colorRamp,i.RGBA)),o.bind(i.LINEAR,i.CLAMP_TO_EDGE),n.setDepthMode(Ht.disabled);var s=e.useProgram(\"heatmapTexture\"),l=r.paint.get(\"heatmap-opacity\");i.uniform1f(s.uniforms.u_opacity,l),i.uniform1i(s.uniforms.u_image,0),i.uniform1i(s.uniforms.u_color_ramp,1);var c=t.mat4.create();t.mat4.ortho(c,0,e.width,e.height,0,0,1),i.uniformMatrix4fv(s.uniforms.u_matrix,!1,c),i.uniform2f(s.uniforms.u_world,i.drawingBufferWidth,i.drawingBufferHeight),e.viewportVAO.bind(e.context,s,e.viewportBuffer,[]),i.drawArrays(i.TRIANGLE_STRIP,0,4)}}(e,n))},line:function(t,e,r,n){if(\"translucent\"===t.renderPass&&0!==r.paint.get(\"line-opacity\").constantOr(1)){var i=t.context;i.setDepthMode(t.depthModeForSublayer(0,Ht.ReadOnly)),i.setColorMode(t.colorModeForRenderPass());for(var a,o=r.paint.get(\"line-dasharray\")?\"lineSDF\":r.paint.get(\"line-pattern\")?\"linePattern\":r.paint.get(\"line-gradient\")?\"lineGradient\":\"line\",s=!0,l=0,c=n;l<c.length;l+=1){var u=c[l],f=e.getTile(u),h=f.getBucket(r);if(h){var p=h.programConfigurations.get(r.id),d=t.context.program.get(),g=t.useProgram(o,p),v=s||g.program!==d,m=a!==f.tileID.overscaledZ;v&&p.setUniforms(t.context,g,r.paint,{zoom:t.transform.zoom}),pr(g,t,f,h,r,u,p,v,m),a=f.tileID.overscaledZ,s=!1}}}},fill:function(e,r,n,i){var a=n.paint.get(\"fill-color\"),o=n.paint.get(\"fill-opacity\");if(0!==o.constantOr(1)){var s=e.context;s.setColorMode(e.colorModeForRenderPass());var l=n.paint.get(\"fill-pattern\")||1!==a.constantOr(t.default$6.transparent).a||1!==o.constantOr(0)?\"translucent\":\"opaque\";e.renderPass===l&&(s.setDepthMode(e.depthModeForSublayer(1,\"opaque\"===e.renderPass?Ht.ReadWrite:Ht.ReadOnly)),mr(e,r,n,i,yr)),\"translucent\"===e.renderPass&&n.paint.get(\"fill-antialias\")&&(s.lineWidth.set(2),s.setDepthMode(e.depthModeForSublayer(n.getPaintProperty(\"fill-outline-color\")?2:0,Ht.ReadOnly)),mr(e,r,n,i,xr))}},\"fill-extrusion\":function(e,r,n,i){if(0!==n.paint.get(\"fill-extrusion-opacity\"))if(\"offscreen\"===e.renderPass){!function(e,r){var n=e.context,i=n.gl,a=r.viewportFrame;if(e.depthRboNeedsClear&&e.setupOffscreenDepthRenderbuffer(),!a){var o=new z(n,{width:e.width,height:e.height,data:null},i.RGBA);o.bind(i.LINEAR,i.CLAMP_TO_EDGE),(a=r.viewportFrame=n.createFramebuffer(e.width,e.height)).colorAttachment.set(o.texture)}n.bindFramebuffer.set(a.framebuffer),a.depthAttachment.set(e.depthRbo),e.depthRboNeedsClear&&(n.clear({depth:1}),e.depthRboNeedsClear=!1),n.clear({color:t.default$6.transparent}),n.setStencilMode(qt.disabled),n.setDepthMode(new Ht(i.LEQUAL,Ht.ReadWrite,[0,1])),n.setColorMode(e.colorModeForRenderPass())}(e,n);for(var a=!0,o=0,s=i;o<s.length;o+=1){var l=s[o],c=r.getTile(l),u=c.getBucket(n);u&&(Tr(e,0,n,c,l,u,a),a=!1)}}else\"translucent\"===e.renderPass&&function(t,e){var r=e.viewportFrame;if(r){var n=t.context,i=n.gl,a=t.useProgram(\"extrusionTexture\");n.setStencilMode(qt.disabled),n.setDepthMode(Ht.disabled),n.setColorMode(t.colorModeForRenderPass()),n.activeTexture.set(i.TEXTURE0),i.bindTexture(i.TEXTURE_2D,r.colorAttachment.get()),i.uniform1f(a.uniforms.u_opacity,e.paint.get(\"fill-extrusion-opacity\")),i.uniform1i(a.uniforms.u_image,0);var o=wr.create();wr.ortho(o,0,t.width,t.height,0,0,1),i.uniformMatrix4fv(a.uniforms.u_matrix,!1,o),i.uniform2f(a.uniforms.u_world,i.drawingBufferWidth,i.drawingBufferHeight),t.viewportVAO.bind(n,a,t.viewportBuffer,[]),i.drawArrays(i.TRIANGLE_STRIP,0,4)}}(e,n)},hillshade:function(t,e,r,n){if(\"offscreen\"===t.renderPass||\"translucent\"===t.renderPass){var i=t.context,a=e.getSource().maxzoom;i.setDepthMode(t.depthModeForSublayer(0,Ht.ReadOnly)),i.setStencilMode(qt.disabled),i.setColorMode(t.colorModeForRenderPass());for(var o=0,s=n;o<s.length;o+=1){var l=s[o],c=e.getTile(l);c.needsHillshadePrepare&&\"offscreen\"===t.renderPass?Mr(t,c,a):\"translucent\"===t.renderPass&&Ar(t,c,r)}i.viewport.set([0,0,t.width,t.height])}},raster:function(t,e,r,n){if(\"translucent\"===t.renderPass&&0!==r.paint.get(\"raster-opacity\")){var i,a,o=t.context,s=o.gl,l=e.getSource(),c=t.useProgram(\"raster\");o.setStencilMode(qt.disabled),o.setColorMode(t.colorModeForRenderPass()),s.uniform1f(c.uniforms.u_brightness_low,r.paint.get(\"raster-brightness-min\")),s.uniform1f(c.uniforms.u_brightness_high,r.paint.get(\"raster-brightness-max\")),s.uniform1f(c.uniforms.u_saturation_factor,(i=r.paint.get(\"raster-saturation\"))>0?1-1/(1.001-i):-i),s.uniform1f(c.uniforms.u_contrast_factor,(a=r.paint.get(\"raster-contrast\"))>0?1/(1-a):1+a),s.uniform3fv(c.uniforms.u_spin_weights,function(t){t*=Math.PI/180;var e=Math.sin(t),r=Math.cos(t);return[(2*r+1)/3,(-Math.sqrt(3)*e-r+1)/3,(Math.sqrt(3)*e-r+1)/3]}(r.paint.get(\"raster-hue-rotate\"))),s.uniform1f(c.uniforms.u_buffer_scale,1),s.uniform1i(c.uniforms.u_image0,0),s.uniform1i(c.uniforms.u_image1,1);for(var u=n.length&&n[0].overscaledZ,f=0,h=n;f<h.length;f+=1){var p=h[f];o.setDepthMode(t.depthModeForSublayer(p.overscaledZ-u,1===r.paint.get(\"raster-opacity\")?Ht.ReadWrite:Ht.ReadOnly,s.LESS));var d=e.getTile(p),g=t.transform.calculatePosMatrix(p.toUnwrapped(),!0);d.registerFadeDuration(r.paint.get(\"raster-fade-duration\")),s.uniformMatrix4fv(c.uniforms.u_matrix,!1,g);var v=e.findLoadedParent(p,0,{}),m=Sr(d,v,e,r,t.transform),y=void 0,x=void 0;if(o.activeTexture.set(s.TEXTURE0),d.texture.bind(s.LINEAR,s.CLAMP_TO_EDGE,s.LINEAR_MIPMAP_NEAREST),o.activeTexture.set(s.TEXTURE1),v?(v.texture.bind(s.LINEAR,s.CLAMP_TO_EDGE,s.LINEAR_MIPMAP_NEAREST),y=Math.pow(2,v.tileID.overscaledZ-d.tileID.overscaledZ),x=[d.tileID.canonical.x*y%1,d.tileID.canonical.y*y%1]):d.texture.bind(s.LINEAR,s.CLAMP_TO_EDGE,s.LINEAR_MIPMAP_NEAREST),s.uniform2fv(c.uniforms.u_tl_parent,x||[0,0]),s.uniform1f(c.uniforms.u_scale_parent,y||1),s.uniform1f(c.uniforms.u_fade_t,m.mix),s.uniform1f(c.uniforms.u_opacity,m.opacity*r.paint.get(\"raster-opacity\")),l instanceof tt){var b=l.boundsBuffer;l.boundsVAO.bind(o,c,b,[]),s.drawArrays(s.TRIANGLE_STRIP,0,b.length)}else if(d.maskedBoundsBuffer&&d.maskedIndexBuffer&&d.segments)c.draw(o,s.TRIANGLES,r.id,d.maskedBoundsBuffer,d.maskedIndexBuffer,d.segments);else{var _=t.rasterBoundsBuffer;t.rasterBoundsVAO.bind(o,c,_,[]),s.drawArrays(s.TRIANGLE_STRIP,0,_.length)}}}},background:function(t,e,r){var n=r.paint.get(\"background-color\"),i=r.paint.get(\"background-opacity\");if(0!==i){var a=t.context,o=a.gl,s=t.transform,l=s.tileSize,c=r.paint.get(\"background-pattern\"),u=c||1!==n.a||1!==i?\"translucent\":\"opaque\";if(t.renderPass===u){var f;if(a.setStencilMode(qt.disabled),a.setDepthMode(t.depthModeForSublayer(0,\"opaque\"===u?Ht.ReadWrite:Ht.ReadOnly)),a.setColorMode(t.colorModeForRenderPass()),c){if(dr(c,t))return;f=t.useProgram(\"backgroundPattern\"),gr(c,t,f),t.tileExtentPatternVAO.bind(a,f,t.tileExtentBuffer,[])}else f=t.useProgram(\"background\"),o.uniform4fv(f.uniforms.u_color,[n.r,n.g,n.b,n.a]),t.tileExtentVAO.bind(a,f,t.tileExtentBuffer,[]);o.uniform1f(f.uniforms.u_opacity,i);for(var h=0,p=s.coveringTiles({tileSize:l});h<p.length;h+=1){var d=p[h];c&&vr({tileID:d,tileSize:l},t,f),o.uniformMatrix4fv(f.uniforms.u_matrix,!1,t.transform.calculatePosMatrix(d.toUnwrapped())),o.drawArrays(o.TRIANGLE_STRIP,0,t.tileExtentBuffer.length)}}}},debug:function(t,e,r){for(var n=0;n<r.length;n++)Er(t,e,r[n])}},zr=function(e,r){this.context=new Yt(e),this.transform=r,this._tileTextures={},this.setup(),this.numSublayers=Wt.maxUnderzooming+Wt.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.depthRboNeedsClear=!0,this.emptyProgramConfiguration=new t.default$24,this.crossTileSymbolIndex=new We};function Or(t,e){if(t.row>e.row){var r=t;t=e,e=r}return{x0:t.column,y0:t.row,x1:e.column,y1:e.row,dx:e.column-t.column,dy:e.row-t.row}}function Ir(t,e,r,n,i){var a=Math.max(r,Math.floor(e.y0)),o=Math.min(n,Math.ceil(e.y1));if(t.x0===e.x0&&t.y0===e.y0?t.x0+e.dy/t.dy*t.dx<e.x1:t.x1-e.dy/t.dy*t.dx<e.x0){var s=t;t=e,e=s}for(var l=t.dx/t.dy,c=e.dx/e.dy,u=t.dx>0,f=e.dx<0,h=a;h<o;h++){var p=l*Math.max(0,Math.min(t.dy,h+u-t.y0))+t.x0,d=c*Math.max(0,Math.min(e.dy,h+f-e.y0))+e.x0;i(Math.floor(d),Math.ceil(p),h)}}function Dr(t,e,r,n,i,a){var o,s=Or(t,e),l=Or(e,r),c=Or(r,t);s.dy>l.dy&&(o=s,s=l,l=o),s.dy>c.dy&&(o=s,s=c,c=o),l.dy>c.dy&&(o=l,l=c,c=o),s.dy&&Ir(c,s,n,i,a),l.dy&&Ir(c,l,n,i,a)}zr.prototype.resize=function(t,e){var r=this.context.gl;if(this.width=t*a.devicePixelRatio,this.height=e*a.devicePixelRatio,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(var n=0,i=this.style._order;n<i.length;n+=1){var o=i[n];this.style._layers[o].resize()}this.depthRbo&&(r.deleteRenderbuffer(this.depthRbo),this.depthRbo=null)},zr.prototype.setup=function(){var e=this.context,r=new t.PosArray;r.emplaceBack(0,0),r.emplaceBack(t.default$8,0),r.emplaceBack(0,t.default$8),r.emplaceBack(t.default$8,t.default$8),this.tileExtentBuffer=e.createVertexBuffer(r,Ke.members),this.tileExtentVAO=new Q,this.tileExtentPatternVAO=new Q;var n=new t.PosArray;n.emplaceBack(0,0),n.emplaceBack(t.default$8,0),n.emplaceBack(t.default$8,t.default$8),n.emplaceBack(0,t.default$8),n.emplaceBack(0,0),this.debugBuffer=e.createVertexBuffer(n,Ke.members),this.debugVAO=new Q;var i=new t.RasterBoundsArray;i.emplaceBack(0,0,0,0),i.emplaceBack(t.default$8,0,t.default$8,0),i.emplaceBack(0,t.default$8,0,t.default$8),i.emplaceBack(t.default$8,t.default$8,t.default$8,t.default$8),this.rasterBoundsBuffer=e.createVertexBuffer(i,K.members),this.rasterBoundsVAO=new Q;var a=new t.PosArray;a.emplaceBack(0,0),a.emplaceBack(1,0),a.emplaceBack(0,1),a.emplaceBack(1,1),this.viewportBuffer=e.createVertexBuffer(a,Ke.members),this.viewportVAO=new Q},zr.prototype.clearStencil=function(){var e=this.context,r=e.gl;e.setColorMode(Gt.disabled),e.setDepthMode(Ht.disabled),e.setStencilMode(new qt({func:r.ALWAYS,mask:0},0,255,r.ZERO,r.ZERO,r.ZERO));var n=t.mat4.create();t.mat4.ortho(n,0,this.width,this.height,0,0,1),t.mat4.scale(n,n,[r.drawingBufferWidth,r.drawingBufferHeight,0]);var i=this.useProgram(\"clippingMask\");r.uniformMatrix4fv(i.uniforms.u_matrix,!1,n),this.viewportVAO.bind(e,i,this.viewportBuffer,[]),r.drawArrays(r.TRIANGLE_STRIP,0,4)},zr.prototype._renderTileClippingMasks=function(t){var e=this.context,r=e.gl;e.setColorMode(Gt.disabled),e.setDepthMode(Ht.disabled);var n=1;this._tileClippingMaskIDs={};for(var i=0,a=t;i<a.length;i+=1){var o=a[i],s=this._tileClippingMaskIDs[o.key]=n++;e.setStencilMode(new qt({func:r.ALWAYS,mask:0},s,255,r.KEEP,r.KEEP,r.REPLACE));var l=this.useProgram(\"clippingMask\");r.uniformMatrix4fv(l.uniforms.u_matrix,!1,o.posMatrix),this.tileExtentVAO.bind(this.context,l,this.tileExtentBuffer,[]),r.drawArrays(r.TRIANGLE_STRIP,0,this.tileExtentBuffer.length)}},zr.prototype.stencilModeForClipping=function(t){var e=this.context.gl;return new qt({func:e.EQUAL,mask:255},this._tileClippingMaskIDs[t.key],0,e.KEEP,e.KEEP,e.REPLACE)},zr.prototype.colorModeForRenderPass=function(){var e=this.context.gl;return this._showOverdrawInspector?new Gt([e.CONSTANT_COLOR,e.ONE],new t.default$6(1/8,1/8,1/8,0),[!0,!0,!0,!0]):\"opaque\"===this.renderPass?Gt.unblended:Gt.alphaBlended},zr.prototype.depthModeForSublayer=function(t,e,r){var n=1-((1+this.currentLayer)*this.numSublayers+t)*this.depthEpsilon,i=n-1+this.depthRange;return new Ht(r||this.context.gl.LEQUAL,e,[i,n])},zr.prototype.render=function(e,r){var n=this;for(var i in this.style=e,this.options=r,this.lineAtlas=e.lineAtlas,this.imageManager=e.imageManager,this.glyphManager=e.glyphManager,this.symbolFadeChange=e.placement.symbolFadeChange(a.now()),e.sourceCaches){var o=n.style.sourceCaches[i];o.used&&o.prepare(n.context)}var s=this.style._order,l=t.filterObject(this.style.sourceCaches,function(t){return\"raster\"===t.getSource().type||\"raster-dem\"===t.getSource().type}),c=function(e){var r=l[e];!function(e,r){for(var n=e.sort(function(t,e){return t.tileID.isLessThan(e.tileID)?-1:e.tileID.isLessThan(t.tileID)?1:0}),i=0;i<n.length;i++){var a={},o=n[i],s=n.slice(i+1);ar(o.tileID.wrapped(),o.tileID,s,new t.OverscaledTileID(0,o.tileID.wrap+1,0,0,0),a),o.setMask(a,r)}}(r.getVisibleCoordinates().map(function(t){return r.getTile(t)}),n.context)};for(var u in l)c(u);this.renderPass=\"offscreen\";var f,h=[];this.depthRboNeedsClear=!0;for(var p=0;p<s.length;p++){var d=n.style._layers[s[p]];d.hasOffscreenPass()&&!d.isHidden(n.transform.zoom)&&(d.source!==(f&&f.id)&&(h=[],(f=n.style.sourceCaches[d.source])&&(h=f.getVisibleCoordinates()).reverse()),h.length&&n.renderLayer(n,f,d,h))}this.context.bindFramebuffer.set(null),this.context.clear({color:r.showOverdrawInspector?t.default$6.black:t.default$6.transparent,depth:1}),this._showOverdrawInspector=r.showOverdrawInspector,this.depthRange=(e._order.length+2)*this.numSublayers*this.depthEpsilon,this.renderPass=\"opaque\";var g,v=[];for(this.currentLayer=s.length-1,this.currentLayer;this.currentLayer>=0;this.currentLayer--){var m=n.style._layers[s[n.currentLayer]];m.source!==(g&&g.id)&&(v=[],(g=n.style.sourceCaches[m.source])&&(n.clearStencil(),v=g.getVisibleCoordinates(),g.getSource().isTileClipped&&n._renderTileClippingMasks(v))),n.renderLayer(n,g,m,v)}this.renderPass=\"translucent\";var y,x=[];for(this.currentLayer=0,this.currentLayer;this.currentLayer<s.length;this.currentLayer++){var b=n.style._layers[s[n.currentLayer]];b.source!==(y&&y.id)&&(x=[],(y=n.style.sourceCaches[b.source])&&(n.clearStencil(),x=y.getVisibleCoordinates(),y.getSource().isTileClipped&&n._renderTileClippingMasks(x)),x.reverse()),n.renderLayer(n,y,b,x)}if(this.options.showTileBoundaries){var _=this.style.sourceCaches[Object.keys(this.style.sourceCaches)[0]];_&&Lr.debug(this,_,_.getVisibleCoordinates())}},zr.prototype.setupOffscreenDepthRenderbuffer=function(){var t=this.context;this.depthRbo||(this.depthRbo=t.createRenderbuffer(t.gl.DEPTH_COMPONENT16,this.width,this.height))},zr.prototype.renderLayer=function(t,e,r,n){r.isHidden(this.transform.zoom)||(\"background\"===r.type||n.length)&&(this.id=r.id,Lr[r.type](t,e,r,n))},zr.prototype.translatePosMatrix=function(e,r,n,i,a){if(!n[0]&&!n[1])return e;var o=a?\"map\"===i?this.transform.angle:0:\"viewport\"===i?-this.transform.angle:0;if(o){var s=Math.sin(o),l=Math.cos(o);n=[n[0]*l-n[1]*s,n[0]*s+n[1]*l]}var c=[a?n[0]:Me(r,n[0],this.transform.zoom),a?n[1]:Me(r,n[1],this.transform.zoom),0],u=new Float32Array(16);return t.mat4.translate(u,e,c),u},zr.prototype.saveTileTexture=function(t){var e=this._tileTextures[t.size[0]];e?e.push(t):this._tileTextures[t.size[0]]=[t]},zr.prototype.getTileTexture=function(t){var e=this._tileTextures[t];return e&&e.length>0?e.pop():null},zr.prototype._createProgramCached=function(t,e){this.cache=this.cache||{};var r=\"\"+t+(e.cacheKey||\"\")+(this._showOverdrawInspector?\"/overdraw\":\"\");return this.cache[r]||(this.cache[r]=new ir(this.context,nr[t],e,this._showOverdrawInspector)),this.cache[r]},zr.prototype.useProgram=function(t,e){var r=this._createProgramCached(t,e||this.emptyProgramConfiguration);return this.context.program.set(r.program),r};var Pr=t.default$20.vec4,Rr=t.default$20.mat4,Fr=t.default$20.mat2,Br=function(t,e,r){this.tileSize=512,this._renderWorldCopies=void 0===r||r,this._minZoom=t||0,this._maxZoom=e||22,this.latRange=[-85.05113,85.05113],this.width=0,this.height=0,this._center=new G(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._posMatrixCache={},this._alignedPosMatrixCache={}},Nr={minZoom:{configurable:!0},maxZoom:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerPoint:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},unmodified:{configurable:!0},x:{configurable:!0},y:{configurable:!0},point:{configurable:!0}};Br.prototype.clone=function(){var t=new Br(this._minZoom,this._maxZoom,this._renderWorldCopies);return t.tileSize=this.tileSize,t.latRange=this.latRange,t.width=this.width,t.height=this.height,t._center=this._center,t.zoom=this.zoom,t.angle=this.angle,t._fov=this._fov,t._pitch=this._pitch,t._unmodified=this._unmodified,t._calcMatrices(),t},Nr.minZoom.get=function(){return this._minZoom},Nr.minZoom.set=function(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},Nr.maxZoom.get=function(){return this._maxZoom},Nr.maxZoom.set=function(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},Nr.renderWorldCopies.get=function(){return this._renderWorldCopies},Nr.renderWorldCopies.set=function(t){void 0===t?t=!0:null===t&&(t=!1),this._renderWorldCopies=t},Nr.worldSize.get=function(){return this.tileSize*this.scale},Nr.centerPoint.get=function(){return this.size._div(2)},Nr.size.get=function(){return new t.default$1(this.width,this.height)},Nr.bearing.get=function(){return-this.angle/Math.PI*180},Nr.bearing.set=function(e){var r=-t.wrap(e,-180,180)*Math.PI/180;this.angle!==r&&(this._unmodified=!1,this.angle=r,this._calcMatrices(),this.rotationMatrix=Fr.create(),Fr.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},Nr.pitch.get=function(){return this._pitch/Math.PI*180},Nr.pitch.set=function(e){var r=t.clamp(e,0,60)/180*Math.PI;this._pitch!==r&&(this._unmodified=!1,this._pitch=r,this._calcMatrices())},Nr.fov.get=function(){return this._fov/Math.PI*180},Nr.fov.set=function(t){t=Math.max(.01,Math.min(60,t)),this._fov!==t&&(this._unmodified=!1,this._fov=t/180*Math.PI,this._calcMatrices())},Nr.zoom.get=function(){return this._zoom},Nr.zoom.set=function(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._constrain(),this._calcMatrices())},Nr.center.get=function(){return this._center},Nr.center.set=function(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._constrain(),this._calcMatrices())},Br.prototype.coveringZoomLevel=function(t){return(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize))},Br.prototype.getVisibleUnwrappedCoordinates=function(e){var r=this.pointCoordinate(new t.default$1(0,0),0),n=this.pointCoordinate(new t.default$1(this.width,0),0),i=Math.floor(r.column),a=Math.floor(n.column),o=[new t.UnwrappedTileID(0,e)];if(this._renderWorldCopies)for(var s=i;s<=a;s++)0!==s&&o.push(new t.UnwrappedTileID(s,e));return o},Br.prototype.coveringTiles=function(e){var r=this.coveringZoomLevel(e),n=r;if(void 0!==e.minzoom&&r<e.minzoom)return[];void 0!==e.maxzoom&&r>e.maxzoom&&(r=e.maxzoom);var i=this.pointCoordinate(this.centerPoint,r),a=new t.default$1(i.column-.5,i.row-.5);return function(e,r,n,i){void 0===i&&(i=!0);var a=1<<e,o={};function s(r,s,l){var c,u,f,h;if(l>=0&&l<=a)for(c=r;c<s;c++)u=Math.floor(c/a),f=(c%a+a)%a,0!==u&&!0!==i||(h=new t.OverscaledTileID(n,u,e,f,l),o[h.key]=h)}return Dr(r[0],r[1],r[2],0,a,s),Dr(r[2],r[3],r[0],0,a,s),Object.keys(o).map(function(t){return o[t]})}(r,[this.pointCoordinate(new t.default$1(0,0),r),this.pointCoordinate(new t.default$1(this.width,0),r),this.pointCoordinate(new t.default$1(this.width,this.height),r),this.pointCoordinate(new t.default$1(0,this.height),r)],e.reparseOverscaled?n:r,this._renderWorldCopies).sort(function(t,e){return a.dist(t.canonical)-a.dist(e.canonical)})},Br.prototype.resize=function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._constrain(),this._calcMatrices()},Nr.unmodified.get=function(){return this._unmodified},Br.prototype.zoomScale=function(t){return Math.pow(2,t)},Br.prototype.scaleZoom=function(t){return Math.log(t)/Math.LN2},Br.prototype.project=function(e){return new t.default$1(this.lngX(e.lng),this.latY(e.lat))},Br.prototype.unproject=function(t){return new G(this.xLng(t.x),this.yLat(t.y))},Nr.x.get=function(){return this.lngX(this.center.lng)},Nr.y.get=function(){return this.latY(this.center.lat)},Nr.point.get=function(){return new t.default$1(this.x,this.y)},Br.prototype.lngX=function(t){return(180+t)*this.worldSize/360},Br.prototype.latY=function(t){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))*this.worldSize/360},Br.prototype.xLng=function(t){return 360*t/this.worldSize-180},Br.prototype.yLat=function(t){var e=180-360*t/this.worldSize;return 360/Math.PI*Math.atan(Math.exp(e*Math.PI/180))-90},Br.prototype.setLocationAtPoint=function(t,e){var r=this.pointCoordinate(e)._sub(this.pointCoordinate(this.centerPoint));this.center=this.coordinateLocation(this.locationCoordinate(t)._sub(r)),this._renderWorldCopies&&(this.center=this.center.wrap())},Br.prototype.locationPoint=function(t){return this.coordinatePoint(this.locationCoordinate(t))},Br.prototype.pointLocation=function(t){return this.coordinateLocation(this.pointCoordinate(t))},Br.prototype.locationCoordinate=function(e){return new t.default$17(this.lngX(e.lng)/this.tileSize,this.latY(e.lat)/this.tileSize,this.zoom).zoomTo(this.tileZoom)},Br.prototype.coordinateLocation=function(t){var e=t.zoomTo(this.zoom);return new G(this.xLng(e.column*this.tileSize),this.yLat(e.row*this.tileSize))},Br.prototype.pointCoordinate=function(e,r){void 0===r&&(r=this.tileZoom);var n=[e.x,e.y,0,1],i=[e.x,e.y,1,1];Pr.transformMat4(n,n,this.pixelMatrixInverse),Pr.transformMat4(i,i,this.pixelMatrixInverse);var a=n[3],o=i[3],s=n[0]/a,l=i[0]/o,c=n[1]/a,u=i[1]/o,f=n[2]/a,h=i[2]/o,p=f===h?0:(0-f)/(h-f);return new t.default$17(t.number(s,l,p)/this.tileSize,t.number(c,u,p)/this.tileSize,this.zoom)._zoomTo(r)},Br.prototype.coordinatePoint=function(e){var r=e.zoomTo(this.zoom),n=[r.column*this.tileSize,r.row*this.tileSize,0,1];return Pr.transformMat4(n,n,this.pixelMatrix),new t.default$1(n[0]/n[3],n[1]/n[3])},Br.prototype.calculatePosMatrix=function(e,r){void 0===r&&(r=!1);var n=e.key,i=r?this._alignedPosMatrixCache:this._posMatrixCache;if(i[n])return i[n];var a=e.canonical,o=this.worldSize/this.zoomScale(a.z),s=a.x+Math.pow(2,a.z)*e.wrap,l=Rr.identity(new Float64Array(16));return Rr.translate(l,l,[s*o,a.y*o,0]),Rr.scale(l,l,[o/t.default$8,o/t.default$8,1]),Rr.multiply(l,r?this.alignedProjMatrix:this.projMatrix,l),i[n]=new Float32Array(l),i[n]},Br.prototype._constrain=function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var e,r,n,i,a=-90,o=90,s=-180,l=180,c=this.size,u=this._unmodified;if(this.latRange){var f=this.latRange;a=this.latY(f[1]),e=(o=this.latY(f[0]))-a<c.y?c.y/(o-a):0}if(this.lngRange){var h=this.lngRange;s=this.lngX(h[0]),r=(l=this.lngX(h[1]))-s<c.x?c.x/(l-s):0}var p=Math.max(r||0,e||0);if(p)return this.center=this.unproject(new t.default$1(r?(l+s)/2:this.x,e?(o+a)/2:this.y)),this.zoom+=this.scaleZoom(p),this._unmodified=u,void(this._constraining=!1);if(this.latRange){var d=this.y,g=c.y/2;d-g<a&&(i=a+g),d+g>o&&(i=o-g)}if(this.lngRange){var v=this.x,m=c.x/2;v-m<s&&(n=s+m),v+m>l&&(n=l-m)}void 0===n&&void 0===i||(this.center=this.unproject(new t.default$1(void 0!==n?n:this.x,void 0!==i?i:this.y))),this._unmodified=u,this._constraining=!1}},Br.prototype._calcMatrices=function(){if(this.height){this.cameraToCenterDistance=.5/Math.tan(this._fov/2)*this.height;var t=this._fov/2,e=Math.PI/2+this._pitch,r=Math.sin(t)*this.cameraToCenterDistance/Math.sin(Math.PI-e-t),n=this.x,i=this.y,a=1.01*(Math.cos(Math.PI/2-this._pitch)*r+this.cameraToCenterDistance),o=new Float64Array(16);Rr.perspective(o,this._fov,this.width/this.height,1,a),Rr.scale(o,o,[1,-1,1]),Rr.translate(o,o,[0,0,-this.cameraToCenterDistance]),Rr.rotateX(o,o,this._pitch),Rr.rotateZ(o,o,this.angle),Rr.translate(o,o,[-n,-i,0]);var s=this.worldSize/(2*Math.PI*6378137*Math.abs(Math.cos(this.center.lat*(Math.PI/180))));Rr.scale(o,o,[1,1,s,1]),this.projMatrix=o;var l=this.width%2/2,c=this.height%2/2,u=Math.cos(this.angle),f=Math.sin(this.angle),h=n-Math.round(n)+u*l+f*c,p=i-Math.round(i)+u*c+f*l,d=new Float64Array(o);if(Rr.translate(d,d,[h>.5?h-1:h,p>.5?p-1:p,0]),this.alignedProjMatrix=d,o=Rr.create(),Rr.scale(o,o,[this.width/2,-this.height/2,1]),Rr.translate(o,o,[1,-1,0]),this.pixelMatrix=Rr.multiply(new Float64Array(16),o,this.projMatrix),!(o=Rr.invert(new Float64Array(16),this.pixelMatrix)))throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=o,this._posMatrixCache={},this._alignedPosMatrixCache={}}},Br.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var e=this.pointCoordinate(new t.default$1(0,0)).zoomTo(this.zoom),r=[e.column*this.tileSize,e.row*this.tileSize,0,1];return Pr.transformMat4(r,r,this.pixelMatrix)[3]/this.cameraToCenterDistance},Object.defineProperties(Br.prototype,Nr);var jr=function(){var e,r,n,i;t.bindAll([\"_onHashChange\",\"_updateHash\"],this),this._updateHash=(e=this._updateHashUnthrottled.bind(this),300,r=!1,n=0,i=function(){n=0,r&&(e(),n=setTimeout(i,300),r=!1)},function(){return r=!0,n||i(),n})};jr.prototype.addTo=function(e){return this._map=e,t.default.addEventListener(\"hashchange\",this._onHashChange,!1),this._map.on(\"moveend\",this._updateHash),this},jr.prototype.remove=function(){return t.default.removeEventListener(\"hashchange\",this._onHashChange,!1),this._map.off(\"moveend\",this._updateHash),clearTimeout(this._updateHash()),delete this._map,this},jr.prototype.getHashString=function(t){var e=this._map.getCenter(),r=Math.round(100*this._map.getZoom())/100,n=Math.ceil((r*Math.LN2+Math.log(512/360/.5))/Math.LN10),i=Math.pow(10,n),a=Math.round(e.lng*i)/i,o=Math.round(e.lat*i)/i,s=this._map.getBearing(),l=this._map.getPitch(),c=\"\";return c+=t?\"#/\"+a+\"/\"+o+\"/\"+r:\"#\"+r+\"/\"+o+\"/\"+a,(s||l)&&(c+=\"/\"+Math.round(10*s)/10),l&&(c+=\"/\"+Math.round(l)),c},jr.prototype._onHashChange=function(){var e=t.default.location.hash.replace(\"#\",\"\").split(\"/\");return e.length>=3&&(this._map.jumpTo({center:[+e[2],+e[1]],zoom:+e[0],bearing:+(e[3]||0),pitch:+(e[4]||0)}),!0)},jr.prototype._updateHashUnthrottled=function(){var e=this.getHashString();t.default.history.replaceState(t.default.history.state,\"\",e)};var Vr=function(e){function r(r,n,i,a){void 0===a&&(a={});var o=s.mousePos(n.getCanvasContainer(),i),l=n.unproject(o);e.call(this,r,t.extend({point:o,lngLat:l,originalEvent:i},a)),this._defaultPrevented=!1,this.target=n}e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r;var n={defaultPrevented:{configurable:!0}};return r.prototype.preventDefault=function(){this._defaultPrevented=!0},n.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(r.prototype,n),r}(t.Event),Ur=function(e){function r(r,n,i){var a=s.touchPos(n.getCanvasContainer(),i),o=a.map(function(t){return n.unproject(t)}),l=a.reduce(function(t,e,r,n){return t.add(e.div(n.length))},new t.default$1(0,0)),c=n.unproject(l);e.call(this,r,{points:a,point:l,lngLats:o,lngLat:c,originalEvent:i}),this._defaultPrevented=!1}e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r;var n={defaultPrevented:{configurable:!0}};return r.prototype.preventDefault=function(){this._defaultPrevented=!0},n.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(r.prototype,n),r}(t.Event),Hr=function(t){function e(e,r,n){t.call(this,e,{originalEvent:n}),this._defaultPrevented=!1}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={defaultPrevented:{configurable:!0}};return e.prototype.preventDefault=function(){this._defaultPrevented=!0},r.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(e.prototype,r),e}(t.Event),qr=function(e){this._map=e,this._el=e.getCanvasContainer(),this._delta=0,t.bindAll([\"_onWheel\",\"_onTimeout\",\"_onScrollFrame\",\"_onScrollFinished\"],this)};qr.prototype.isEnabled=function(){return!!this._enabled},qr.prototype.isActive=function(){return!!this._active},qr.prototype.enable=function(t){this.isEnabled()||(this._enabled=!0,this._aroundCenter=t&&\"center\"===t.around)},qr.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},qr.prototype.onWheel=function(e){if(this.isEnabled()){var r=e.deltaMode===t.default.WheelEvent.DOM_DELTA_LINE?40*e.deltaY:e.deltaY,n=a.now(),i=n-(this._lastWheelEventTime||0);this._lastWheelEventTime=n,0!==r&&r%4.000244140625==0?this._type=\"wheel\":0!==r&&Math.abs(r)<4?this._type=\"trackpad\":i>400?(this._type=null,this._lastValue=r,this._timeout=setTimeout(this._onTimeout,40,e)):this._type||(this._type=Math.abs(i*r)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,r+=this._lastValue)),e.shiftKey&&r&&(r/=4),this._type&&(this._lastWheelEvent=e,this._delta-=r,this.isActive()||this._start(e)),e.preventDefault()}},qr.prototype._onTimeout=function(t){this._type=\"wheel\",this._delta-=this._lastValue,this.isActive()||this._start(t)},qr.prototype._start=function(e){if(this._delta){this._frameId&&(this._map._cancelRenderFrame(this._frameId),this._frameId=null),this._active=!0,this._map.fire(new t.Event(\"movestart\",{originalEvent:e})),this._map.fire(new t.Event(\"zoomstart\",{originalEvent:e})),this._finishTimeout&&clearTimeout(this._finishTimeout);var r=s.mousePos(this._el,e);this._around=G.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(r)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=this._map._requestRenderFrame(this._onScrollFrame))}},qr.prototype._onScrollFrame=function(){var e=this;if(this._frameId=null,this.isActive()){var r=this._map.transform;if(0!==this._delta){var n=\"wheel\"===this._type&&Math.abs(this._delta)>4.000244140625?1/450:.01,i=2/(1+Math.exp(-Math.abs(this._delta*n)));this._delta<0&&0!==i&&(i=1/i);var o=\"number\"==typeof this._targetZoom?r.zoomScale(this._targetZoom):r.scale;this._targetZoom=Math.min(r.maxZoom,Math.max(r.minZoom,r.scaleZoom(o*i))),\"wheel\"===this._type&&(this._startZoom=r.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var s=!1;if(\"wheel\"===this._type){var l=Math.min((a.now()-this._lastWheelEventTime)/200,1),c=this._easing(l);r.zoom=t.number(this._startZoom,this._targetZoom,c),l<1?this._frameId||(this._frameId=this._map._requestRenderFrame(this._onScrollFrame)):s=!0}else r.zoom=this._targetZoom,s=!0;r.setLocationAtPoint(this._around,this._aroundPoint),this._map.fire(new t.Event(\"move\",{originalEvent:this._lastWheelEvent})),this._map.fire(new t.Event(\"zoom\",{originalEvent:this._lastWheelEvent})),s&&(this._active=!1,this._finishTimeout=setTimeout(function(){e._map.fire(new t.Event(\"zoomend\",{originalEvent:e._lastWheelEvent})),e._map.fire(new t.Event(\"moveend\",{originalEvent:e._lastWheelEvent})),delete e._targetZoom},200))}},qr.prototype._smoothOutEasing=function(e){var r=t.ease;if(this._prevEase){var n=this._prevEase,i=(a.now()-n.start)/n.duration,o=n.easing(i+.01)-n.easing(i),s=.27/Math.sqrt(o*o+1e-4)*.01,l=Math.sqrt(.0729-s*s);r=t.bezier(s,l,.25,1)}return this._prevEase={start:a.now(),duration:e,easing:r},r};var Gr=function(e){this._map=e,this._el=e.getCanvasContainer(),this._container=e.getContainer(),t.bindAll([\"_onMouseMove\",\"_onMouseUp\",\"_onKeyDown\"],this)};Gr.prototype.isEnabled=function(){return!!this._enabled},Gr.prototype.isActive=function(){return!!this._active},Gr.prototype.enable=function(){this.isEnabled()||(this._enabled=!0)},Gr.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},Gr.prototype.onMouseDown=function(e){this.isEnabled()&&e.shiftKey&&0===e.button&&(t.default.document.addEventListener(\"mousemove\",this._onMouseMove,!1),t.default.document.addEventListener(\"keydown\",this._onKeyDown,!1),t.default.document.addEventListener(\"mouseup\",this._onMouseUp,!1),s.disableDrag(),this._startPos=s.mousePos(this._el,e),this._active=!0)},Gr.prototype._onMouseMove=function(t){var e=this._startPos,r=s.mousePos(this._el,t);this._box||(this._box=s.create(\"div\",\"mapboxgl-boxzoom\",this._container),this._container.classList.add(\"mapboxgl-crosshair\"),this._fireEvent(\"boxzoomstart\",t));var n=Math.min(e.x,r.x),i=Math.max(e.x,r.x),a=Math.min(e.y,r.y),o=Math.max(e.y,r.y);s.setTransform(this._box,\"translate(\"+n+\"px,\"+a+\"px)\"),this._box.style.width=i-n+\"px\",this._box.style.height=o-a+\"px\"},Gr.prototype._onMouseUp=function(e){if(0===e.button){var r=this._startPos,n=s.mousePos(this._el,e),i=(new Y).extend(this._map.unproject(r)).extend(this._map.unproject(n));this._finish(),s.suppressClick(),r.x===n.x&&r.y===n.y?this._fireEvent(\"boxzoomcancel\",e):this._map.fitBounds(i,{linear:!0}).fire(new t.Event(\"boxzoomend\",{originalEvent:e,boxZoomBounds:i}))}},Gr.prototype._onKeyDown=function(t){27===t.keyCode&&(this._finish(),this._fireEvent(\"boxzoomcancel\",t))},Gr.prototype._finish=function(){this._active=!1,t.default.document.removeEventListener(\"mousemove\",this._onMouseMove,!1),t.default.document.removeEventListener(\"keydown\",this._onKeyDown,!1),t.default.document.removeEventListener(\"mouseup\",this._onMouseUp,!1),this._container.classList.remove(\"mapboxgl-crosshair\"),this._box&&(s.remove(this._box),this._box=null),s.enableDrag()},Gr.prototype._fireEvent=function(e,r){return this._map.fire(new t.Event(e,{originalEvent:r}))};var Yr=t.bezier(0,0,.25,1),Wr=function(e,r){this._map=e,this._el=r.element||e.getCanvasContainer(),this._state=\"disabled\",this._button=r.button||\"right\",this._bearingSnap=r.bearingSnap||0,this._pitchWithRotate=!1!==r.pitchWithRotate,t.bindAll([\"_onMouseMove\",\"_onMouseUp\",\"_onBlur\",\"_onDragFrame\"],this)};Wr.prototype.isEnabled=function(){return\"disabled\"!==this._state},Wr.prototype.isActive=function(){return\"active\"===this._state},Wr.prototype.enable=function(){this.isEnabled()||(this._state=\"enabled\")},Wr.prototype.disable=function(){if(this.isEnabled())switch(this._state){case\"active\":this._state=\"disabled\",this._unbind(),this._deactivate(),this._fireEvent(\"rotateend\"),this._pitchWithRotate&&this._fireEvent(\"pitchend\"),this._fireEvent(\"moveend\");break;case\"pending\":this._state=\"disabled\",this._unbind();break;default:this._state=\"disabled\"}},Wr.prototype.onMouseDown=function(e){if(\"enabled\"===this._state){if(\"right\"===this._button){if(this._eventButton=s.mouseButton(e),this._eventButton!==(e.ctrlKey?0:2))return}else{if(e.ctrlKey||0!==s.mouseButton(e))return;this._eventButton=0}s.disableDrag(),t.default.document.addEventListener(\"mousemove\",this._onMouseMove,{capture:!0}),t.default.document.addEventListener(\"mouseup\",this._onMouseUp),t.default.addEventListener(\"blur\",this._onBlur),this._state=\"pending\",this._inertia=[[a.now(),this._map.getBearing()]],this._previousPos=s.mousePos(this._el,e),this._center=this._map.transform.centerPoint,e.preventDefault()}},Wr.prototype._onMouseMove=function(t){this._lastMoveEvent=t,this._pos=s.mousePos(this._el,t),\"pending\"===this._state&&(this._state=\"active\",this._fireEvent(\"rotatestart\",t),this._fireEvent(\"movestart\",t),this._pitchWithRotate&&this._fireEvent(\"pitchstart\",t)),this._frameId||(this._frameId=this._map._requestRenderFrame(this._onDragFrame))},Wr.prototype._onDragFrame=function(){this._frameId=null;var t=this._lastMoveEvent;if(t){var e=this._map.transform,r=this._previousPos,n=this._pos,i=.8*(r.x-n.x),o=-.5*(r.y-n.y),s=e.bearing-i,l=e.pitch-o,c=this._inertia,u=c[c.length-1];this._drainInertiaBuffer(),c.push([a.now(),this._map._normalizeBearing(s,u[1])]),e.bearing=s,this._pitchWithRotate&&(this._fireEvent(\"pitch\",t),e.pitch=l),this._fireEvent(\"rotate\",t),this._fireEvent(\"move\",t),delete this._lastMoveEvent,this._previousPos=this._pos}},Wr.prototype._onMouseUp=function(t){if(s.mouseButton(t)===this._eventButton)switch(this._state){case\"active\":this._state=\"enabled\",s.suppressClick(),this._unbind(),this._deactivate(),this._inertialRotate(t);break;case\"pending\":this._state=\"enabled\",this._unbind()}},Wr.prototype._onBlur=function(t){switch(this._state){case\"active\":this._state=\"enabled\",this._unbind(),this._deactivate(),this._fireEvent(\"rotateend\",t),this._pitchWithRotate&&this._fireEvent(\"pitchend\",t),this._fireEvent(\"moveend\",t);break;case\"pending\":this._state=\"enabled\",this._unbind()}},Wr.prototype._unbind=function(){t.default.document.removeEventListener(\"mousemove\",this._onMouseMove,{capture:!0}),t.default.document.removeEventListener(\"mouseup\",this._onMouseUp),t.default.removeEventListener(\"blur\",this._onBlur),s.enableDrag()},Wr.prototype._deactivate=function(){this._frameId&&(this._map._cancelRenderFrame(this._frameId),this._frameId=null),delete this._lastMoveEvent,delete this._previousPos},Wr.prototype._inertialRotate=function(t){var e=this;this._fireEvent(\"rotateend\",t),this._drainInertiaBuffer();var r=this._map,n=r.getBearing(),i=this._inertia,a=function(){Math.abs(n)<e._bearingSnap?r.resetNorth({noMoveStart:!0},{originalEvent:t}):e._fireEvent(\"moveend\",t),e._pitchWithRotate&&e._fireEvent(\"pitchend\",t)};if(i.length<2)a();else{var o=i[0],s=i[i.length-1],l=i[i.length-2],c=r._normalizeBearing(n,l[1]),u=s[1]-o[1],f=u<0?-1:1,h=(s[0]-o[0])/1e3;if(0!==u&&0!==h){var p=Math.abs(u*(.25/h));p>180&&(p=180);var d=p/180;c+=f*p*(d/2),Math.abs(r._normalizeBearing(c,0))<this._bearingSnap&&(c=r._normalizeBearing(0,c)),r.rotateTo(c,{duration:1e3*d,easing:Yr,noMoveStart:!0},{originalEvent:t})}else a()}},Wr.prototype._fireEvent=function(e,r){return this._map.fire(new t.Event(e,r?{originalEvent:r}:{}))},Wr.prototype._drainInertiaBuffer=function(){for(var t=this._inertia,e=a.now();t.length>0&&e-t[0][0]>160;)t.shift()};var Xr=t.bezier(0,0,.3,1),Zr=function(e){this._map=e,this._el=e.getCanvasContainer(),this._state=\"disabled\",t.bindAll([\"_onMove\",\"_onMouseUp\",\"_onTouchEnd\",\"_onBlur\",\"_onDragFrame\"],this)};Zr.prototype.isEnabled=function(){return\"disabled\"!==this._state},Zr.prototype.isActive=function(){return\"active\"===this._state},Zr.prototype.enable=function(){this.isEnabled()||(this._el.classList.add(\"mapboxgl-touch-drag-pan\"),this._state=\"enabled\")},Zr.prototype.disable=function(){if(this.isEnabled())switch(this._el.classList.remove(\"mapboxgl-touch-drag-pan\"),this._state){case\"active\":this._state=\"disabled\",this._unbind(),this._deactivate(),this._fireEvent(\"dragend\"),this._fireEvent(\"moveend\");break;case\"pending\":this._state=\"disabled\",this._unbind();break;default:this._state=\"disabled\"}},Zr.prototype.onMouseDown=function(e){\"enabled\"===this._state&&(e.ctrlKey||0!==s.mouseButton(e)||(s.addEventListener(t.default.document,\"mousemove\",this._onMove,{capture:!0}),s.addEventListener(t.default.document,\"mouseup\",this._onMouseUp),this._start(e)))},Zr.prototype.onTouchStart=function(e){\"enabled\"===this._state&&(e.touches.length>1||(s.addEventListener(t.default.document,\"touchmove\",this._onMove,{capture:!0,passive:!1}),s.addEventListener(t.default.document,\"touchend\",this._onTouchEnd),this._start(e)))},Zr.prototype._start=function(e){t.default.addEventListener(\"blur\",this._onBlur),this._state=\"pending\",this._previousPos=s.mousePos(this._el,e),this._inertia=[[a.now(),this._previousPos]]},Zr.prototype._onMove=function(t){this._lastMoveEvent=t,t.preventDefault(),this._pos=s.mousePos(this._el,t),this._drainInertiaBuffer(),this._inertia.push([a.now(),this._pos]),\"pending\"===this._state&&(this._state=\"active\",this._fireEvent(\"dragstart\",t),this._fireEvent(\"movestart\",t)),this._frameId||(this._frameId=this._map._requestRenderFrame(this._onDragFrame))},Zr.prototype._onDragFrame=function(){this._frameId=null;var t=this._lastMoveEvent;if(t){var e=this._map.transform;e.setLocationAtPoint(e.pointLocation(this._previousPos),this._pos),this._fireEvent(\"drag\",t),this._fireEvent(\"move\",t),this._previousPos=this._pos,delete this._lastMoveEvent}},Zr.prototype._onMouseUp=function(t){if(0===s.mouseButton(t))switch(this._state){case\"active\":this._state=\"enabled\",s.suppressClick(),this._unbind(),this._deactivate(),this._inertialPan(t);break;case\"pending\":this._state=\"enabled\",this._unbind()}},Zr.prototype._onTouchEnd=function(t){switch(this._state){case\"active\":this._state=\"enabled\",this._unbind(),this._deactivate(),this._inertialPan(t);break;case\"pending\":this._state=\"enabled\",this._unbind()}},Zr.prototype._onBlur=function(t){switch(this._state){case\"active\":this._state=\"enabled\",this._unbind(),this._deactivate(),this._fireEvent(\"dragend\",t),this._fireEvent(\"moveend\",t);break;case\"pending\":this._state=\"enabled\",this._unbind()}},Zr.prototype._unbind=function(){s.removeEventListener(t.default.document,\"touchmove\",this._onMove,{capture:!0,passive:!1}),s.removeEventListener(t.default.document,\"touchend\",this._onTouchEnd),s.removeEventListener(t.default.document,\"mousemove\",this._onMove,{capture:!0}),s.removeEventListener(t.default.document,\"mouseup\",this._onMouseUp),s.removeEventListener(t.default,\"blur\",this._onBlur)},Zr.prototype._deactivate=function(){this._frameId&&(this._map._cancelRenderFrame(this._frameId),this._frameId=null),delete this._lastMoveEvent,delete this._previousPos,delete this._pos},Zr.prototype._inertialPan=function(t){this._fireEvent(\"dragend\",t),this._drainInertiaBuffer();var e=this._inertia;if(e.length<2)this._fireEvent(\"moveend\",t);else{var r=e[e.length-1],n=e[0],i=r[1].sub(n[1]),a=(r[0]-n[0])/1e3;if(0===a||r[1].equals(n[1]))this._fireEvent(\"moveend\",t);else{var o=i.mult(.3/a),s=o.mag();s>1400&&(s=1400,o._unit()._mult(s));var l=s/750,c=o.mult(-l/2);this._map.panBy(c,{duration:1e3*l,easing:Xr,noMoveStart:!0},{originalEvent:t})}}},Zr.prototype._fireEvent=function(e,r){return this._map.fire(new t.Event(e,r?{originalEvent:r}:{}))},Zr.prototype._drainInertiaBuffer=function(){for(var t=this._inertia,e=a.now();t.length>0&&e-t[0][0]>160;)t.shift()};var $r=function(e){this._map=e,this._el=e.getCanvasContainer(),t.bindAll([\"_onKeyDown\"],this)};function Jr(t){return t*(2-t)}$r.prototype.isEnabled=function(){return!!this._enabled},$r.prototype.enable=function(){this.isEnabled()||(this._el.addEventListener(\"keydown\",this._onKeyDown,!1),this._enabled=!0)},$r.prototype.disable=function(){this.isEnabled()&&(this._el.removeEventListener(\"keydown\",this._onKeyDown),this._enabled=!1)},$r.prototype._onKeyDown=function(t){if(!(t.altKey||t.ctrlKey||t.metaKey)){var e=0,r=0,n=0,i=0,a=0;switch(t.keyCode){case 61:case 107:case 171:case 187:e=1;break;case 189:case 109:case 173:e=-1;break;case 37:t.shiftKey?r=-1:(t.preventDefault(),i=-1);break;case 39:t.shiftKey?r=1:(t.preventDefault(),i=1);break;case 38:t.shiftKey?n=1:(t.preventDefault(),a=-1);break;case 40:t.shiftKey?n=-1:(a=1,t.preventDefault());break;default:return}var o=this._map,s=o.getZoom(),l={duration:300,delayEndEvents:500,easing:Jr,zoom:e?Math.round(s)+e*(t.shiftKey?2:1):s,bearing:o.getBearing()+15*r,pitch:o.getPitch()+10*n,offset:[100*-i,100*-a],center:o.getCenter()};o.easeTo(l,{originalEvent:t})}};var Kr=function(e){this._map=e,t.bindAll([\"_onDblClick\",\"_onZoomEnd\"],this)};Kr.prototype.isEnabled=function(){return!!this._enabled},Kr.prototype.isActive=function(){return!!this._active},Kr.prototype.enable=function(){this.isEnabled()||(this._enabled=!0)},Kr.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},Kr.prototype.onTouchStart=function(t){var e=this;this.isEnabled()&&(t.points.length>1||(this._tapped?(clearTimeout(this._tapped),this._tapped=null,this._zoom(t)):this._tapped=setTimeout(function(){e._tapped=null},300)))},Kr.prototype.onDblClick=function(t){this.isEnabled()&&(t.originalEvent.preventDefault(),this._zoom(t))},Kr.prototype._zoom=function(t){this._active=!0,this._map.on(\"zoomend\",this._onZoomEnd),this._map.zoomTo(this._map.getZoom()+(t.originalEvent.shiftKey?-1:1),{around:t.lngLat},t)},Kr.prototype._onZoomEnd=function(){this._active=!1,this._map.off(\"zoomend\",this._onZoomEnd)};var Qr=t.bezier(0,0,.15,1),tn=function(e){this._map=e,this._el=e.getCanvasContainer(),t.bindAll([\"_onMove\",\"_onEnd\",\"_onTouchFrame\"],this)};tn.prototype.isEnabled=function(){return!!this._enabled},tn.prototype.enable=function(t){this.isEnabled()||(this._el.classList.add(\"mapboxgl-touch-zoom-rotate\"),this._enabled=!0,this._aroundCenter=!!t&&\"center\"===t.around)},tn.prototype.disable=function(){this.isEnabled()&&(this._el.classList.remove(\"mapboxgl-touch-zoom-rotate\"),this._enabled=!1)},tn.prototype.disableRotation=function(){this._rotationDisabled=!0},tn.prototype.enableRotation=function(){this._rotationDisabled=!1},tn.prototype.onStart=function(e){if(this.isEnabled()&&2===e.touches.length){var r=s.mousePos(this._el,e.touches[0]),n=s.mousePos(this._el,e.touches[1]);this._startVec=r.sub(n),this._gestureIntent=void 0,this._inertia=[],s.addEventListener(t.default.document,\"touchmove\",this._onMove,{passive:!1}),s.addEventListener(t.default.document,\"touchend\",this._onEnd)}},tn.prototype._getTouchEventData=function(t){var e=s.mousePos(this._el,t.touches[0]),r=s.mousePos(this._el,t.touches[1]),n=e.sub(r);return{vec:n,center:e.add(r).div(2),scale:n.mag()/this._startVec.mag(),bearing:this._rotationDisabled?0:180*n.angleWith(this._startVec)/Math.PI}},tn.prototype._onMove=function(e){if(2===e.touches.length){var r=this._getTouchEventData(e),n=r.vec,i=r.scale,a=r.bearing;if(!this._gestureIntent){var o=Math.abs(1-i)>.15;Math.abs(a)>10?this._gestureIntent=\"rotate\":o&&(this._gestureIntent=\"zoom\"),this._gestureIntent&&(this._map.fire(new t.Event(this._gestureIntent+\"start\",{originalEvent:e})),this._map.fire(new t.Event(\"movestart\",{originalEvent:e})),this._startVec=n)}this._lastTouchEvent=e,this._frameId||(this._frameId=this._map._requestRenderFrame(this._onTouchFrame)),e.preventDefault()}},tn.prototype._onTouchFrame=function(){this._frameId=null;var e=this._gestureIntent;if(e){var r=this._map.transform;this._startScale||(this._startScale=r.scale,this._startBearing=r.bearing);var n=this._getTouchEventData(this._lastTouchEvent),i=n.center,o=n.bearing,s=n.scale,l=r.pointLocation(i),c=r.locationPoint(l);\"rotate\"===e&&(r.bearing=this._startBearing+o),r.zoom=r.scaleZoom(this._startScale*s),r.setLocationAtPoint(l,c),this._map.fire(new t.Event(e,{originalEvent:this._lastTouchEvent})),this._map.fire(new t.Event(\"move\",{originalEvent:this._lastTouchEvent})),this._drainInertiaBuffer(),this._inertia.push([a.now(),s,i])}},tn.prototype._onEnd=function(e){s.removeEventListener(t.default.document,\"touchmove\",this._onMove,{passive:!1}),s.removeEventListener(t.default.document,\"touchend\",this._onEnd);var r=this._gestureIntent,n=this._startScale;if(this._frameId&&(this._map._cancelRenderFrame(this._frameId),this._frameId=null),delete this._gestureIntent,delete this._startScale,delete this._startBearing,delete this._lastTouchEvent,r){this._map.fire(new t.Event(r+\"end\",{originalEvent:e})),this._drainInertiaBuffer();var i=this._inertia,a=this._map;if(i.length<2)a.snapToNorth({},{originalEvent:e});else{var o=i[i.length-1],l=i[0],c=a.transform.scaleZoom(n*o[1]),u=a.transform.scaleZoom(n*l[1]),f=c-u,h=(o[0]-l[0])/1e3,p=o[2];if(0!==h&&c!==u){var d=.15*f/h;Math.abs(d)>2.5&&(d=d>0?2.5:-2.5);var g=1e3*Math.abs(d/(12*.15)),v=c+d*g/2e3;v<0&&(v=0),a.easeTo({zoom:v,duration:g,easing:Qr,around:this._aroundCenter?a.getCenter():a.unproject(p),noMoveStart:!0},{originalEvent:e})}else a.snapToNorth({},{originalEvent:e})}}},tn.prototype._drainInertiaBuffer=function(){for(var t=this._inertia,e=a.now();t.length>2&&e-t[0][0]>160;)t.shift()};var en={scrollZoom:qr,boxZoom:Gr,dragRotate:Wr,dragPan:Zr,keyboard:$r,doubleClickZoom:Kr,touchZoomRotate:tn},rn=function(e){function r(r,n){e.call(this),this._moving=!1,this._zooming=!1,this.transform=r,this._bearingSnap=n.bearingSnap,t.bindAll([\"_renderFrameCallback\"],this)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getCenter=function(){return this.transform.center},r.prototype.setCenter=function(t,e){return this.jumpTo({center:t},e)},r.prototype.panBy=function(e,r,n){return e=t.default$1.convert(e).mult(-1),this.panTo(this.transform.center,t.extend({offset:e},r),n)},r.prototype.panTo=function(e,r,n){return this.easeTo(t.extend({center:e},r),n)},r.prototype.getZoom=function(){return this.transform.zoom},r.prototype.setZoom=function(t,e){return this.jumpTo({zoom:t},e),this},r.prototype.zoomTo=function(e,r,n){return this.easeTo(t.extend({zoom:e},r),n)},r.prototype.zoomIn=function(t,e){return this.zoomTo(this.getZoom()+1,t,e),this},r.prototype.zoomOut=function(t,e){return this.zoomTo(this.getZoom()-1,t,e),this},r.prototype.getBearing=function(){return this.transform.bearing},r.prototype.setBearing=function(t,e){return this.jumpTo({bearing:t},e),this},r.prototype.rotateTo=function(e,r,n){return this.easeTo(t.extend({bearing:e},r),n)},r.prototype.resetNorth=function(e,r){return this.rotateTo(0,t.extend({duration:1e3},e),r),this},r.prototype.snapToNorth=function(t,e){return Math.abs(this.getBearing())<this._bearingSnap?this.resetNorth(t,e):this},r.prototype.getPitch=function(){return this.transform.pitch},r.prototype.setPitch=function(t,e){return this.jumpTo({pitch:t},e),this},r.prototype.fitBounds=function(e,r,n){if(\"number\"==typeof(r=t.extend({padding:{top:0,bottom:0,right:0,left:0},offset:[0,0],maxZoom:this.transform.maxZoom},r)).padding){var i=r.padding;r.padding={top:i,bottom:i,right:i,left:i}}if(!t.default$10(Object.keys(r.padding).sort(function(t,e){return t<e?-1:t>e?1:0}),[\"bottom\",\"left\",\"right\",\"top\"]))return t.warnOnce(\"options.padding must be a positive number, or an Object with keys 'bottom', 'left', 'right', 'top'\"),this;e=Y.convert(e);var a=[(r.padding.left-r.padding.right)/2,(r.padding.top-r.padding.bottom)/2],o=Math.min(r.padding.right,r.padding.left),s=Math.min(r.padding.top,r.padding.bottom);r.offset=[r.offset[0]+a[0],r.offset[1]+a[1]];var l=t.default$1.convert(r.offset),c=this.transform,u=c.project(e.getNorthWest()),f=c.project(e.getSouthEast()),h=f.sub(u),p=(c.width-2*o-2*Math.abs(l.x))/h.x,d=(c.height-2*s-2*Math.abs(l.y))/h.y;return d<0||p<0?(t.warnOnce(\"Map cannot fit within canvas with the given bounds, padding, and/or offset.\"),this):(r.center=c.unproject(u.add(f).div(2)),r.zoom=Math.min(c.scaleZoom(c.scale*Math.min(p,d)),r.maxZoom),r.bearing=0,r.linear?this.easeTo(r,n):this.flyTo(r,n))},r.prototype.jumpTo=function(e,r){this.stop();var n=this.transform,i=!1,a=!1,o=!1;return\"zoom\"in e&&n.zoom!==+e.zoom&&(i=!0,n.zoom=+e.zoom),void 0!==e.center&&(n.center=G.convert(e.center)),\"bearing\"in e&&n.bearing!==+e.bearing&&(a=!0,n.bearing=+e.bearing),\"pitch\"in e&&n.pitch!==+e.pitch&&(o=!0,n.pitch=+e.pitch),this.fire(new t.Event(\"movestart\",r)).fire(new t.Event(\"move\",r)),i&&this.fire(new t.Event(\"zoomstart\",r)).fire(new t.Event(\"zoom\",r)).fire(new t.Event(\"zoomend\",r)),a&&this.fire(new t.Event(\"rotatestart\",r)).fire(new t.Event(\"rotate\",r)).fire(new t.Event(\"rotateend\",r)),o&&this.fire(new t.Event(\"pitchstart\",r)).fire(new t.Event(\"pitch\",r)).fire(new t.Event(\"pitchend\",r)),this.fire(new t.Event(\"moveend\",r))},r.prototype.easeTo=function(e,r){var n=this;this.stop(),!1===(e=t.extend({offset:[0,0],duration:500,easing:t.ease},e)).animate&&(e.duration=0);var i=this.transform,a=this.getZoom(),o=this.getBearing(),s=this.getPitch(),l=\"zoom\"in e?+e.zoom:a,c=\"bearing\"in e?this._normalizeBearing(e.bearing,o):o,u=\"pitch\"in e?+e.pitch:s,f=i.centerPoint.add(t.default$1.convert(e.offset)),h=i.pointLocation(f),p=G.convert(e.center||h);this._normalizeCenter(p);var d,g,v=i.project(h),m=i.project(p).sub(v),y=i.zoomScale(l-a);return e.around&&(d=G.convert(e.around),g=i.locationPoint(d)),this._zooming=l!==a,this._rotating=o!==c,this._pitching=u!==s,this._prepareEase(r,e.noMoveStart),clearTimeout(this._easeEndTimeoutID),this._ease(function(e){if(n._zooming&&(i.zoom=t.number(a,l,e)),n._rotating&&(i.bearing=t.number(o,c,e)),n._pitching&&(i.pitch=t.number(s,u,e)),d)i.setLocationAtPoint(d,g);else{var h=i.zoomScale(i.zoom-a),p=l>a?Math.min(2,y):Math.max(.5,y),x=Math.pow(p,1-e),b=i.unproject(v.add(m.mult(e*x)).mult(h));i.setLocationAtPoint(i.renderWorldCopies?b.wrap():b,f)}n._fireMoveEvents(r)},function(){e.delayEndEvents?n._easeEndTimeoutID=setTimeout(function(){return n._afterEase(r)},e.delayEndEvents):n._afterEase(r)},e),this},r.prototype._prepareEase=function(e,r){this._moving=!0,r||this.fire(new t.Event(\"movestart\",e)),this._zooming&&this.fire(new t.Event(\"zoomstart\",e)),this._rotating&&this.fire(new t.Event(\"rotatestart\",e)),this._pitching&&this.fire(new t.Event(\"pitchstart\",e))},r.prototype._fireMoveEvents=function(e){this.fire(new t.Event(\"move\",e)),this._zooming&&this.fire(new t.Event(\"zoom\",e)),this._rotating&&this.fire(new t.Event(\"rotate\",e)),this._pitching&&this.fire(new t.Event(\"pitch\",e))},r.prototype._afterEase=function(e){var r=this._zooming,n=this._rotating,i=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,r&&this.fire(new t.Event(\"zoomend\",e)),n&&this.fire(new t.Event(\"rotateend\",e)),i&&this.fire(new t.Event(\"pitchend\",e)),this.fire(new t.Event(\"moveend\",e))},r.prototype.flyTo=function(e,r){var n=this;this.stop(),e=t.extend({offset:[0,0],speed:1.2,curve:1.42,easing:t.ease},e);var i=this.transform,a=this.getZoom(),o=this.getBearing(),s=this.getPitch(),l=\"zoom\"in e?t.clamp(+e.zoom,i.minZoom,i.maxZoom):a,c=\"bearing\"in e?this._normalizeBearing(e.bearing,o):o,u=\"pitch\"in e?+e.pitch:s,f=i.zoomScale(l-a),h=i.centerPoint.add(t.default$1.convert(e.offset)),p=i.pointLocation(h),d=G.convert(e.center||p);this._normalizeCenter(d);var g=i.project(p),v=i.project(d).sub(g),m=e.curve,y=Math.max(i.width,i.height),x=y/f,b=v.mag();if(\"minZoom\"in e){var _=t.clamp(Math.min(e.minZoom,a,l),i.minZoom,i.maxZoom),w=y/i.zoomScale(_-a);m=Math.sqrt(w/b*2)}var k=m*m;function T(t){var e=(x*x-y*y+(t?-1:1)*k*k*b*b)/(2*(t?x:y)*k*b);return Math.log(Math.sqrt(e*e+1)-e)}function A(t){return(Math.exp(t)-Math.exp(-t))/2}function M(t){return(Math.exp(t)+Math.exp(-t))/2}var S=T(0),E=function(t){return M(S)/M(S+m*t)},C=function(t){return y*((M(S)*(A(e=S+m*t)/M(e))-A(S))/k)/b;var e},L=(T(1)-S)/m;if(Math.abs(b)<1e-6||!isFinite(L)){if(Math.abs(y-x)<1e-6)return this.easeTo(e,r);var z=x<y?-1:1;L=Math.abs(Math.log(x/y))/m,C=function(){return 0},E=function(t){return Math.exp(z*m*t)}}if(\"duration\"in e)e.duration=+e.duration;else{var O=\"screenSpeed\"in e?+e.screenSpeed/m:+e.speed;e.duration=1e3*L/O}return e.maxDuration&&e.duration>e.maxDuration&&(e.duration=0),this._zooming=!0,this._rotating=o!==c,this._pitching=u!==s,this._prepareEase(r,!1),this._ease(function(e){var l=e*L,f=1/E(l);i.zoom=a+i.scaleZoom(f),n._rotating&&(i.bearing=t.number(o,c,e)),n._pitching&&(i.pitch=t.number(s,u,e));var p=i.unproject(g.add(v.mult(C(l))).mult(f));i.setLocationAtPoint(i.renderWorldCopies?p.wrap():p,h),n._fireMoveEvents(r)},function(){return n._afterEase(r)},e),this},r.prototype.isEasing=function(){return!!this._easeFrameId},r.prototype.stop=function(){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var t=this._onEaseEnd;delete this._onEaseEnd,t.call(this)}return this},r.prototype._ease=function(t,e,r){!1===r.animate||0===r.duration?(t(1),e()):(this._easeStart=a.now(),this._easeOptions=r,this._onEaseFrame=t,this._onEaseEnd=e,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},r.prototype._renderFrameCallback=function(){var t=Math.min((a.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(t)),t<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},r.prototype._normalizeBearing=function(e,r){e=t.wrap(e,-180,180);var n=Math.abs(e-r);return Math.abs(e-360-r)<n&&(e-=360),Math.abs(e+360-r)<n&&(e+=360),e},r.prototype._normalizeCenter=function(t){var e=this.transform;if(e.renderWorldCopies&&!e.lngRange){var r=t.lng-e.center.lng;t.lng+=r>180?-360:r<-180?360:0}},r}(t.Evented),nn=function(e){void 0===e&&(e={}),this.options=e,t.bindAll([\"_updateEditLink\",\"_updateData\",\"_updateCompact\"],this)};nn.prototype.getDefaultPosition=function(){return\"bottom-right\"},nn.prototype.onAdd=function(t){var e=this.options&&this.options.compact;return this._map=t,this._container=s.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-attrib\"),e&&this._container.classList.add(\"mapboxgl-compact\"),this._updateAttributions(),this._updateEditLink(),this._map.on(\"sourcedata\",this._updateData),this._map.on(\"moveend\",this._updateEditLink),void 0===e&&(this._map.on(\"resize\",this._updateCompact),this._updateCompact()),this._container},nn.prototype.onRemove=function(){s.remove(this._container),this._map.off(\"sourcedata\",this._updateData),this._map.off(\"moveend\",this._updateEditLink),this._map.off(\"resize\",this._updateCompact),this._map=void 0},nn.prototype._updateEditLink=function(){var t=this._editLink;t||(t=this._editLink=this._container.querySelector(\".mapbox-improve-map\"));var e=[{key:\"owner\",value:this.styleOwner},{key:\"id\",value:this.styleId},{key:\"access_token\",value:v.ACCESS_TOKEN}];if(t){var r=e.reduce(function(t,r,n){return r.value&&(t+=r.key+\"=\"+r.value+(n<e.length-1?\"&\":\"\")),t},\"?\");t.href=\"https://www.mapbox.com/feedback/\"+r+(this._map._hash?this._map._hash.getHashString(!0):\"\")}},nn.prototype._updateData=function(t){t&&\"metadata\"===t.sourceDataType&&(this._updateAttributions(),this._updateEditLink())},nn.prototype._updateAttributions=function(){if(this._map.style){var t=[];if(this._map.style.stylesheet){var e=this._map.style.stylesheet;this.styleOwner=e.owner,this.styleId=e.id}var r=this._map.style.sourceCaches;for(var n in r){var i=r[n].getSource();i.attribution&&t.indexOf(i.attribution)<0&&t.push(i.attribution)}t.sort(function(t,e){return t.length-e.length}),(t=t.filter(function(e,r){for(var n=r+1;n<t.length;n++)if(t[n].indexOf(e)>=0)return!1;return!0})).length?(this._container.innerHTML=t.join(\" | \"),this._container.classList.remove(\"mapboxgl-attrib-empty\")):this._container.classList.add(\"mapboxgl-attrib-empty\"),this._editLink=null}},nn.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add(\"mapboxgl-compact\"):this._container.classList.remove(\"mapboxgl-compact\")};var an=function(){t.bindAll([\"_updateLogo\"],this)};an.prototype.onAdd=function(t){this._map=t,this._container=s.create(\"div\",\"mapboxgl-ctrl\");var e=s.create(\"a\",\"mapboxgl-ctrl-logo\");return e.target=\"_blank\",e.href=\"https://www.mapbox.com/\",e.setAttribute(\"aria-label\",\"Mapbox logo\"),this._container.appendChild(e),this._container.style.display=\"none\",this._map.on(\"sourcedata\",this._updateLogo),this._updateLogo(),this._container},an.prototype.onRemove=function(){s.remove(this._container),this._map.off(\"sourcedata\",this._updateLogo)},an.prototype.getDefaultPosition=function(){return\"bottom-left\"},an.prototype._updateLogo=function(t){t&&\"metadata\"!==t.sourceDataType||(this._container.style.display=this._logoRequired()?\"block\":\"none\")},an.prototype._logoRequired=function(){if(this._map.style){var t=this._map.style.sourceCaches;for(var e in t)if(t[e].getSource().mapbox_logo)return!0;return!1}};var on=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};on.prototype.add=function(t){var e=++this._id;return this._queue.push({callback:t,id:e,cancelled:!1}),e},on.prototype.remove=function(t){for(var e=this._currentlyRunning,r=0,n=e?this._queue.concat(e):this._queue;r<n.length;r+=1){var i=n[r];if(i.id===t)return void(i.cancelled=!0)}},on.prototype.run=function(){var t=this._currentlyRunning=this._queue;this._queue=[];for(var e=0,r=t;e<r.length;e+=1){var n=r[e];if(!n.cancelled&&(n.callback(),this._cleared))break}this._cleared=!1,this._currentlyRunning=!1},on.prototype.clear=function(){this._currentlyRunning&&(this._cleared=!0),this._queue=[]};var sn=t.default.HTMLImageElement,ln=t.default.HTMLElement,cn={center:[0,0],zoom:0,bearing:0,pitch:0,minZoom:0,maxZoom:22,interactive:!0,scrollZoom:!0,boxZoom:!0,dragRotate:!0,dragPan:!0,keyboard:!0,doubleClickZoom:!0,touchZoomRotate:!0,bearingSnap:7,hash:!1,attributionControl:!0,failIfMajorPerformanceCaveat:!1,preserveDrawingBuffer:!1,trackResize:!0,renderWorldCopies:!0,refreshExpiredTiles:!0,maxTileCacheSize:null,transformRequest:null,fadeDuration:300},un=function(r){function n(e){if(null!=(e=t.extend({},cn,e)).minZoom&&null!=e.maxZoom&&e.minZoom>e.maxZoom)throw new Error(\"maxZoom must be greater than minZoom\");var n=new Br(e.minZoom,e.maxZoom,e.renderWorldCopies);r.call(this,n,e),this._interactive=e.interactive,this._maxTileCacheSize=e.maxTileCacheSize,this._failIfMajorPerformanceCaveat=e.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=e.preserveDrawingBuffer,this._trackResize=e.trackResize,this._bearingSnap=e.bearingSnap,this._refreshExpiredTiles=e.refreshExpiredTiles,this._fadeDuration=e.fadeDuration,this._crossFadingFactor=1,this._collectResourceTiming=e.collectResourceTiming,this._renderTaskQueue=new on;var i=e.transformRequest;if(this._transformRequest=i?function(t,e){return i(t,e)||{url:t}}:function(t){return{url:t}},\"string\"==typeof e.container){var a=t.default.document.getElementById(e.container);if(!a)throw new Error(\"Container '\"+e.container+\"' not found.\");this._container=a}else{if(!(e.container instanceof ln))throw new Error(\"Invalid type: 'container' must be a String or HTMLElement.\");this._container=e.container}e.maxBounds&&this.setMaxBounds(e.maxBounds),t.bindAll([\"_onWindowOnline\",\"_onWindowResize\",\"_contextLost\",\"_contextRestored\",\"_update\",\"_render\",\"_onData\",\"_onDataLoading\"],this),this._setupContainer(),this._setupPainter(),this.on(\"move\",this._update.bind(this,!1)),this.on(\"zoom\",this._update.bind(this,!0)),void 0!==t.default&&(t.default.addEventListener(\"online\",this._onWindowOnline,!1),t.default.addEventListener(\"resize\",this._onWindowResize,!1)),function(t,e){var r=t.getCanvasContainer(),n=null,i=!1;for(var a in en)t[a]=new en[a](t,e),e.interactive&&e[a]&&t[a].enable(e[a]);s.addEventListener(r,\"mouseout\",function(e){t.fire(new Vr(\"mouseout\",t,e))}),s.addEventListener(r,\"mousedown\",function(r){i=!0;var n=new Vr(\"mousedown\",t,r);t.fire(n),n.defaultPrevented||(e.interactive&&!t.doubleClickZoom.isActive()&&t.stop(),t.boxZoom.onMouseDown(r),t.boxZoom.isActive()||t.dragPan.isActive()||t.dragRotate.onMouseDown(r),t.boxZoom.isActive()||t.dragRotate.isActive()||t.dragPan.onMouseDown(r))}),s.addEventListener(r,\"mouseup\",function(e){var r=t.dragRotate.isActive();n&&!r&&t.fire(new Vr(\"contextmenu\",t,n)),n=null,i=!1,t.fire(new Vr(\"mouseup\",t,e))}),s.addEventListener(r,\"mousemove\",function(e){if(!t.dragPan.isActive()&&!t.dragRotate.isActive()){for(var n=e.toElement||e.target;n&&n!==r;)n=n.parentNode;n===r&&t.fire(new Vr(\"mousemove\",t,e))}}),s.addEventListener(r,\"mouseover\",function(e){for(var n=e.toElement||e.target;n&&n!==r;)n=n.parentNode;n===r&&t.fire(new Vr(\"mouseover\",t,e))}),s.addEventListener(r,\"touchstart\",function(r){var n=new Ur(\"touchstart\",t,r);t.fire(n),n.defaultPrevented||(e.interactive&&t.stop(),t.boxZoom.isActive()||t.dragRotate.isActive()||t.dragPan.onTouchStart(r),t.touchZoomRotate.onStart(r),t.doubleClickZoom.onTouchStart(n))},{passive:!1}),s.addEventListener(r,\"touchmove\",function(e){t.fire(new Ur(\"touchmove\",t,e))},{passive:!1}),s.addEventListener(r,\"touchend\",function(e){t.fire(new Ur(\"touchend\",t,e))}),s.addEventListener(r,\"touchcancel\",function(e){t.fire(new Ur(\"touchcancel\",t,e))}),s.addEventListener(r,\"click\",function(e){t.fire(new Vr(\"click\",t,e))}),s.addEventListener(r,\"dblclick\",function(e){var r=new Vr(\"dblclick\",t,e);t.fire(r),r.defaultPrevented||t.doubleClickZoom.onDblClick(r)}),s.addEventListener(r,\"contextmenu\",function(e){var r=t.dragRotate.isActive();i||r?i&&(n=e):t.fire(new Vr(\"contextmenu\",t,e)),e.preventDefault()}),s.addEventListener(r,\"wheel\",function(e){var r=new Hr(\"wheel\",t,e);t.fire(r),r.defaultPrevented||t.scrollZoom.onWheel(e)},{passive:!1})}(this,e),this._hash=e.hash&&(new jr).addTo(this),this._hash&&this._hash._onHashChange()||this.jumpTo({center:e.center,zoom:e.zoom,bearing:e.bearing,pitch:e.pitch}),this.resize(),e.style&&this.setStyle(e.style,{localIdeographFontFamily:e.localIdeographFontFamily}),e.attributionControl&&this.addControl(new nn),this.addControl(new an,e.logoPosition),this.on(\"style.load\",function(){this.transform.unmodified&&this.jumpTo(this.style.stylesheet)}),this.on(\"data\",this._onData),this.on(\"dataloading\",this._onDataLoading)}r&&(n.__proto__=r),n.prototype=Object.create(r&&r.prototype),n.prototype.constructor=n;var i={showTileBoundaries:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0}};return n.prototype.addControl=function(t,e){void 0===e&&t.getDefaultPosition&&(e=t.getDefaultPosition()),void 0===e&&(e=\"top-right\");var r=t.onAdd(this),n=this._controlPositions[e];return-1!==e.indexOf(\"bottom\")?n.insertBefore(r,n.firstChild):n.appendChild(r),this},n.prototype.removeControl=function(t){return t.onRemove(this),this},n.prototype.resize=function(e){var r=this._containerDimensions(),n=r[0],i=r[1];return this._resizeCanvas(n,i),this.transform.resize(n,i),this.painter.resize(n,i),this.fire(new t.Event(\"movestart\",e)).fire(new t.Event(\"move\",e)).fire(new t.Event(\"resize\",e)).fire(new t.Event(\"moveend\",e))},n.prototype.getBounds=function(){var e=new Y(this.transform.pointLocation(new t.default$1(0,this.transform.height)),this.transform.pointLocation(new t.default$1(this.transform.width,0)));return(this.transform.angle||this.transform.pitch)&&(e.extend(this.transform.pointLocation(new t.default$1(this.transform.size.x,0))),e.extend(this.transform.pointLocation(new t.default$1(0,this.transform.size.y)))),e},n.prototype.getMaxBounds=function(){return this.transform.latRange&&2===this.transform.latRange.length&&this.transform.lngRange&&2===this.transform.lngRange.length?new Y([this.transform.lngRange[0],this.transform.latRange[0]],[this.transform.lngRange[1],this.transform.latRange[1]]):null},n.prototype.setMaxBounds=function(t){if(t){var e=Y.convert(t);this.transform.lngRange=[e.getWest(),e.getEast()],this.transform.latRange=[e.getSouth(),e.getNorth()],this.transform._constrain(),this._update()}else null==t&&(this.transform.lngRange=null,this.transform.latRange=null,this._update());return this},n.prototype.setMinZoom=function(t){if((t=null==t?0:t)>=0&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()<t&&this.setZoom(t),this;throw new Error(\"minZoom must be between 0 and the current maxZoom, inclusive\")},n.prototype.getMinZoom=function(){return this.transform.minZoom},n.prototype.setMaxZoom=function(t){if((t=null==t?22:t)>=this.transform.minZoom)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error(\"maxZoom must be greater than the current minZoom\")},n.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},n.prototype.setRenderWorldCopies=function(t){return this.transform.renderWorldCopies=t,this._update(),this},n.prototype.getMaxZoom=function(){return this.transform.maxZoom},n.prototype.project=function(t){return this.transform.locationPoint(G.convert(t))},n.prototype.unproject=function(e){return this.transform.pointLocation(t.default$1.convert(e))},n.prototype.isMoving=function(){return this._moving||this.dragPan.isActive()||this.dragRotate.isActive()||this.scrollZoom.isActive()},n.prototype.isZooming=function(){return this._zooming||this.scrollZoom.isActive()},n.prototype.isRotating=function(){return this._rotating||this.dragRotate.isActive()},n.prototype.on=function(t,e,n){var i,a=this;if(void 0===n)return r.prototype.on.call(this,t,e);var o=function(){if(\"mouseenter\"===t||\"mouseover\"===t){var r=!1;return{layer:e,listener:n,delegates:{mousemove:function(i){var o=a.getLayer(e)?a.queryRenderedFeatures(i.point,{layers:[e]}):[];o.length?r||(r=!0,n.call(a,new Vr(t,a,i.originalEvent,{features:o}))):r=!1},mouseout:function(){r=!1}}}}if(\"mouseleave\"===t||\"mouseout\"===t){var o=!1;return{layer:e,listener:n,delegates:{mousemove:function(r){(a.getLayer(e)?a.queryRenderedFeatures(r.point,{layers:[e]}):[]).length?o=!0:o&&(o=!1,n.call(a,new Vr(t,a,r.originalEvent)))},mouseout:function(e){o&&(o=!1,n.call(a,new Vr(t,a,e.originalEvent)))}}}}return{layer:e,listener:n,delegates:(i={},i[t]=function(t){var r=a.getLayer(e)?a.queryRenderedFeatures(t.point,{layers:[e]}):[];r.length&&(t.features=r,n.call(a,t),delete t.features)},i)}}();for(var s in this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[t]=this._delegatedListeners[t]||[],this._delegatedListeners[t].push(o),o.delegates)a.on(s,o.delegates[s]);return this},n.prototype.off=function(t,e,n){if(void 0===n)return r.prototype.off.call(this,t,e);if(this._delegatedListeners&&this._delegatedListeners[t])for(var i=this._delegatedListeners[t],a=0;a<i.length;a++){var o=i[a];if(o.layer===e&&o.listener===n){for(var s in o.delegates)this.off(s,o.delegates[s]);return i.splice(a,1),this}}return this},n.prototype.queryRenderedFeatures=function(e,r){var n;return 2===arguments.length?(e=arguments[0],r=arguments[1]):1===arguments.length&&((n=arguments[0])instanceof t.default$1||Array.isArray(n))?(e=arguments[0],r={}):1===arguments.length?(e=void 0,r=arguments[0]):(e=void 0,r={}),this.style?this.style.queryRenderedFeatures(this._makeQueryGeometry(e),r,this.transform):[]},n.prototype._makeQueryGeometry=function(e){var r,n=this;if(void 0===e&&(e=[t.default$1.convert([0,0]),t.default$1.convert([this.transform.width,this.transform.height])]),e instanceof t.default$1||\"number\"==typeof e[0])r=[t.default$1.convert(e)];else{var i=[t.default$1.convert(e[0]),t.default$1.convert(e[1])];r=[i[0],new t.default$1(i[1].x,i[0].y),i[1],new t.default$1(i[0].x,i[1].y),i[0]]}return{viewport:r,worldCoordinate:r.map(function(t){return n.transform.pointCoordinate(t)})}},n.prototype.querySourceFeatures=function(t,e){return this.style.querySourceFeatures(t,e)},n.prototype.setStyle=function(e,r){if((!r||!1!==r.diff&&!r.localIdeographFontFamily)&&this.style&&e&&\"object\"==typeof e)try{return this.style.setState(e)&&this._update(!0),this}catch(e){t.warnOnce(\"Unable to perform style diff: \"+(e.message||e.error||e)+\". Rebuilding the style from scratch.\")}return this.style&&(this.style.setEventedParent(null),this.style._remove()),e?(this.style=new Je(this,r||{}),this.style.setEventedParent(this,{style:this.style}),\"string\"==typeof e?this.style.loadURL(e):this.style.loadJSON(e),this):(delete this.style,this)},n.prototype.getStyle=function(){if(this.style)return this.style.serialize()},n.prototype.isStyleLoaded=function(){return this.style?this.style.loaded():t.warnOnce(\"There is no style added to the map.\")},n.prototype.addSource=function(t,e){return this.style.addSource(t,e),this._update(!0),this},n.prototype.isSourceLoaded=function(e){var r=this.style&&this.style.sourceCaches[e];if(void 0!==r)return r.loaded();this.fire(new t.ErrorEvent(new Error(\"There is no source with ID '\"+e+\"'\")))},n.prototype.areTilesLoaded=function(){var t=this.style&&this.style.sourceCaches;for(var e in t){var r=t[e]._tiles;for(var n in r){var i=r[n];if(\"loaded\"!==i.state&&\"errored\"!==i.state)return!1}}return!0},n.prototype.addSourceType=function(t,e,r){return this.style.addSourceType(t,e,r)},n.prototype.removeSource=function(t){return this.style.removeSource(t),this._update(!0),this},n.prototype.getSource=function(t){return this.style.getSource(t)},n.prototype.addImage=function(e,r,n){void 0===n&&(n={});var i=n.pixelRatio;void 0===i&&(i=1);var o=n.sdf;if(void 0===o&&(o=!1),r instanceof sn){var s=a.getImageData(r),l=s.width,c=s.height,u=s.data;this.style.addImage(e,{data:new t.RGBAImage({width:l,height:c},u),pixelRatio:i,sdf:o})}else{if(void 0===r.width||void 0===r.height)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));var f=r.width,h=r.height,p=r.data;this.style.addImage(e,{data:new t.RGBAImage({width:f,height:h},p.slice(0)),pixelRatio:i,sdf:o})}},n.prototype.hasImage=function(e){return e?!!this.style.getImage(e):(this.fire(new t.ErrorEvent(new Error(\"Missing required image id\"))),!1)},n.prototype.removeImage=function(t){this.style.removeImage(t)},n.prototype.loadImage=function(e,r){t.getImage(this._transformRequest(e,t.ResourceType.Image),r)},n.prototype.addLayer=function(t,e){return this.style.addLayer(t,e),this._update(!0),this},n.prototype.moveLayer=function(t,e){return this.style.moveLayer(t,e),this._update(!0),this},n.prototype.removeLayer=function(t){return this.style.removeLayer(t),this._update(!0),this},n.prototype.getLayer=function(t){return this.style.getLayer(t)},n.prototype.setFilter=function(t,e){return this.style.setFilter(t,e),this._update(!0),this},n.prototype.setLayerZoomRange=function(t,e,r){return this.style.setLayerZoomRange(t,e,r),this._update(!0),this},n.prototype.getFilter=function(t){return this.style.getFilter(t)},n.prototype.setPaintProperty=function(t,e,r){return this.style.setPaintProperty(t,e,r),this._update(!0),this},n.prototype.getPaintProperty=function(t,e){return this.style.getPaintProperty(t,e)},n.prototype.setLayoutProperty=function(t,e,r){return this.style.setLayoutProperty(t,e,r),this._update(!0),this},n.prototype.getLayoutProperty=function(t,e){return this.style.getLayoutProperty(t,e)},n.prototype.setLight=function(t){return this.style.setLight(t),this._update(!0),this},n.prototype.getLight=function(){return this.style.getLight()},n.prototype.getContainer=function(){return this._container},n.prototype.getCanvasContainer=function(){return this._canvasContainer},n.prototype.getCanvas=function(){return this._canvas},n.prototype._containerDimensions=function(){var t=0,e=0;return this._container&&(t=this._container.offsetWidth||400,e=this._container.offsetHeight||300),[t,e]},n.prototype._setupContainer=function(){var t=this._container;t.classList.add(\"mapboxgl-map\"),(this._missingCSSContainer=s.create(\"div\",\"mapboxgl-missing-css\",t)).innerHTML=\"Missing Mapbox GL JS CSS\";var e=this._canvasContainer=s.create(\"div\",\"mapboxgl-canvas-container\",t);this._interactive&&e.classList.add(\"mapboxgl-interactive\"),this._canvas=s.create(\"canvas\",\"mapboxgl-canvas\",e),this._canvas.style.position=\"absolute\",this._canvas.addEventListener(\"webglcontextlost\",this._contextLost,!1),this._canvas.addEventListener(\"webglcontextrestored\",this._contextRestored,!1),this._canvas.setAttribute(\"tabindex\",\"0\"),this._canvas.setAttribute(\"aria-label\",\"Map\");var r=this._containerDimensions();this._resizeCanvas(r[0],r[1]);var n=this._controlContainer=s.create(\"div\",\"mapboxgl-control-container\",t),i=this._controlPositions={};[\"top-left\",\"top-right\",\"bottom-left\",\"bottom-right\"].forEach(function(t){i[t]=s.create(\"div\",\"mapboxgl-ctrl-\"+t,n)})},n.prototype._resizeCanvas=function(e,r){var n=t.default.devicePixelRatio||1;this._canvas.width=n*e,this._canvas.height=n*r,this._canvas.style.width=e+\"px\",this._canvas.style.height=r+\"px\"},n.prototype._setupPainter=function(){var r=t.extend({failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer},e.webGLContextAttributes),n=this._canvas.getContext(\"webgl\",r)||this._canvas.getContext(\"experimental-webgl\",r);n?this.painter=new zr(n,this.transform):this.fire(new t.ErrorEvent(new Error(\"Failed to initialize WebGL\")))},n.prototype._contextLost=function(e){e.preventDefault(),this._frameId&&(a.cancelFrame(this._frameId),this._frameId=null),this.fire(new t.Event(\"webglcontextlost\",{originalEvent:e}))},n.prototype._contextRestored=function(e){this._setupPainter(),this.resize(),this._update(),this.fire(new t.Event(\"webglcontextrestored\",{originalEvent:e}))},n.prototype.loaded=function(){return!this._styleDirty&&!this._sourcesDirty&&!(!this.style||!this.style.loaded())},n.prototype._update=function(t){this.style&&(this._styleDirty=this._styleDirty||t,this._sourcesDirty=!0,this._rerender())},n.prototype._requestRenderFrame=function(t){return this._update(),this._renderTaskQueue.add(t)},n.prototype._cancelRenderFrame=function(t){this._renderTaskQueue.remove(t)},n.prototype._render=function(){this._renderTaskQueue.run();var e=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;var r=this.transform.zoom,n=a.now();this.style.zoomHistory.update(r,n);var i=new t.default$16(r,{now:n,fadeDuration:this._fadeDuration,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),o=i.crossFadingFactor();1===o&&o===this._crossFadingFactor||(e=!0,this._crossFadingFactor=o),this.style.update(i)}return this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,this._fadeDuration),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),fadeDuration:this._fadeDuration}),this.fire(new t.Event(\"render\")),this.loaded()&&!this._loaded&&(this._loaded=!0,this.fire(new t.Event(\"load\"))),this.style&&(this.style.hasTransitions()||e)&&(this._styleDirty=!0),(this._sourcesDirty||this._repaint||this._styleDirty||this._placementDirty)&&this._rerender(),this},n.prototype.remove=function(){this._hash&&this._hash.remove(),a.cancelFrame(this._frameId),this._renderTaskQueue.clear(),this._frameId=null,this.setStyle(null),void 0!==t.default&&(t.default.removeEventListener(\"resize\",this._onWindowResize,!1),t.default.removeEventListener(\"online\",this._onWindowOnline,!1));var e=this.painter.context.gl.getExtension(\"WEBGL_lose_context\");e&&e.loseContext(),fn(this._canvasContainer),fn(this._controlContainer),fn(this._missingCSSContainer),this._container.classList.remove(\"mapboxgl-map\"),this.fire(new t.Event(\"remove\"))},n.prototype._rerender=function(){var t=this;this.style&&!this._frameId&&(this._frameId=a.frame(function(){t._frameId=null,t._render()}))},n.prototype._onWindowOnline=function(){this._update()},n.prototype._onWindowResize=function(){this._trackResize&&this.stop().resize()._update()},i.showTileBoundaries.get=function(){return!!this._showTileBoundaries},i.showTileBoundaries.set=function(t){this._showTileBoundaries!==t&&(this._showTileBoundaries=t,this._update())},i.showCollisionBoxes.get=function(){return!!this._showCollisionBoxes},i.showCollisionBoxes.set=function(t){this._showCollisionBoxes!==t&&(this._showCollisionBoxes=t,t?this.style._generateCollisionBoxes():this._update())},i.showOverdrawInspector.get=function(){return!!this._showOverdrawInspector},i.showOverdrawInspector.set=function(t){this._showOverdrawInspector!==t&&(this._showOverdrawInspector=t,this._update())},i.repaint.get=function(){return!!this._repaint},i.repaint.set=function(t){this._repaint=t,this._update()},i.vertices.get=function(){return!!this._vertices},i.vertices.set=function(t){this._vertices=t,this._update()},n.prototype._onData=function(e){this._update(\"style\"===e.dataType),this.fire(new t.Event(e.dataType+\"data\",e))},n.prototype._onDataLoading=function(e){this.fire(new t.Event(e.dataType+\"dataloading\",e))},Object.defineProperties(n.prototype,i),n}(rn);function fn(t){t.parentNode&&t.parentNode.removeChild(t)}var hn={showCompass:!0,showZoom:!0},pn=function(e){var r=this;this.options=t.extend({},hn,e),this._container=s.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._container.addEventListener(\"contextmenu\",function(t){return t.preventDefault()}),this.options.showZoom&&(this._zoomInButton=this._createButton(\"mapboxgl-ctrl-icon mapboxgl-ctrl-zoom-in\",\"Zoom In\",function(){return r._map.zoomIn()}),this._zoomOutButton=this._createButton(\"mapboxgl-ctrl-icon mapboxgl-ctrl-zoom-out\",\"Zoom Out\",function(){return r._map.zoomOut()})),this.options.showCompass&&(t.bindAll([\"_rotateCompassArrow\"],this),this._compass=this._createButton(\"mapboxgl-ctrl-icon mapboxgl-ctrl-compass\",\"Reset North\",function(){return r._map.resetNorth()}),this._compassArrow=s.create(\"span\",\"mapboxgl-ctrl-compass-arrow\",this._compass))};function dn(t,e,r){if(t=new G(t.lng,t.lat),e){var n=new G(t.lng-360,t.lat),i=new G(t.lng+360,t.lat),a=r.locationPoint(t).distSqr(e);r.locationPoint(n).distSqr(e)<a?t=n:r.locationPoint(i).distSqr(e)<a&&(t=i)}for(;Math.abs(t.lng-r.center.lng)>180;){var o=r.locationPoint(t);if(o.x>=0&&o.y>=0&&o.x<=r.width&&o.y<=r.height)break;t.lng>r.center.lng?t.lng-=360:t.lng+=360}return t}pn.prototype._rotateCompassArrow=function(){var t=\"rotate(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\";this._compassArrow.style.transform=t},pn.prototype.onAdd=function(t){return this._map=t,this.options.showCompass&&(this._map.on(\"rotate\",this._rotateCompassArrow),this._rotateCompassArrow(),this._handler=new Wr(t,{button:\"left\",element:this._compass}),this._handler.enable()),this._container},pn.prototype.onRemove=function(){s.remove(this._container),this.options.showCompass&&(this._map.off(\"rotate\",this._rotateCompassArrow),this._handler.disable(),delete this._handler),delete this._map},pn.prototype._createButton=function(t,e,r){var n=s.create(\"button\",t,this._container);return n.type=\"button\",n.setAttribute(\"aria-label\",e),n.addEventListener(\"click\",r),n};var gn={center:\"translate(-50%,-50%)\",top:\"translate(-50%,0)\",\"top-left\":\"translate(0,0)\",\"top-right\":\"translate(-100%,0)\",bottom:\"translate(-50%,-100%)\",\"bottom-left\":\"translate(0,-100%)\",\"bottom-right\":\"translate(-100%,-100%)\",left:\"translate(0,-50%)\",right:\"translate(-100%,-50%)\"};function vn(t,e,r){var n=t.classList;for(var i in gn)n.remove(\"mapboxgl-\"+r+\"-anchor-\"+i);n.add(\"mapboxgl-\"+r+\"-anchor-\"+e)}var mn=function(e){if((arguments[0]instanceof t.default.HTMLElement||2===arguments.length)&&(e=t.extend({element:e},arguments[1])),t.bindAll([\"_update\",\"_onMapClick\"],this),this._anchor=e&&e.anchor||\"center\",this._color=e&&e.color||\"#3FB1CE\",e&&e.element)this._element=e.element,this._offset=t.default$1.convert(e&&e.offset||[0,0]);else{this._defaultMarker=!0,this._element=s.create(\"div\");var r=s.createNS(\"http://www.w3.org/2000/svg\",\"svg\");r.setAttributeNS(null,\"height\",\"41px\"),r.setAttributeNS(null,\"width\",\"27px\"),r.setAttributeNS(null,\"viewBox\",\"0 0 27 41\");var n=s.createNS(\"http://www.w3.org/2000/svg\",\"g\");n.setAttributeNS(null,\"stroke\",\"none\"),n.setAttributeNS(null,\"stroke-width\",\"1\"),n.setAttributeNS(null,\"fill\",\"none\"),n.setAttributeNS(null,\"fill-rule\",\"evenodd\");var i=s.createNS(\"http://www.w3.org/2000/svg\",\"g\");i.setAttributeNS(null,\"fill-rule\",\"nonzero\");var a=s.createNS(\"http://www.w3.org/2000/svg\",\"g\");a.setAttributeNS(null,\"transform\",\"translate(3.0, 29.0)\"),a.setAttributeNS(null,\"fill\",\"#000000\");for(var o=0,l=[{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"9.5\",ry:\"4.77275007\"},{rx:\"8.5\",ry:\"4.29549936\"},{rx:\"7.5\",ry:\"3.81822308\"},{rx:\"6.5\",ry:\"3.34094679\"},{rx:\"5.5\",ry:\"2.86367051\"},{rx:\"4.5\",ry:\"2.38636864\"}];o<l.length;o+=1){var c=l[o],u=s.createNS(\"http://www.w3.org/2000/svg\",\"ellipse\");u.setAttributeNS(null,\"opacity\",\"0.04\"),u.setAttributeNS(null,\"cx\",\"10.5\"),u.setAttributeNS(null,\"cy\",\"5.80029008\"),u.setAttributeNS(null,\"rx\",c.rx),u.setAttributeNS(null,\"ry\",c.ry),a.appendChild(u)}var f=s.createNS(\"http://www.w3.org/2000/svg\",\"g\");f.setAttributeNS(null,\"fill\",this._color);var h=s.createNS(\"http://www.w3.org/2000/svg\",\"path\");h.setAttributeNS(null,\"d\",\"M27,13.5 C27,19.074644 20.250001,27.000002 14.75,34.500002 C14.016665,35.500004 12.983335,35.500004 12.25,34.500002 C6.7499993,27.000002 0,19.222562 0,13.5 C0,6.0441559 6.0441559,0 13.5,0 C20.955844,0 27,6.0441559 27,13.5 Z\"),f.appendChild(h);var p=s.createNS(\"http://www.w3.org/2000/svg\",\"g\");p.setAttributeNS(null,\"opacity\",\"0.25\"),p.setAttributeNS(null,\"fill\",\"#000000\");var d=s.createNS(\"http://www.w3.org/2000/svg\",\"path\");d.setAttributeNS(null,\"d\",\"M13.5,0 C6.0441559,0 0,6.0441559 0,13.5 C0,19.222562 6.7499993,27 12.25,34.5 C13,35.522727 14.016664,35.500004 14.75,34.5 C20.250001,27 27,19.074644 27,13.5 C27,6.0441559 20.955844,0 13.5,0 Z M13.5,1 C20.415404,1 26,6.584596 26,13.5 C26,15.898657 24.495584,19.181431 22.220703,22.738281 C19.945823,26.295132 16.705119,30.142167 13.943359,33.908203 C13.743445,34.180814 13.612715,34.322738 13.5,34.441406 C13.387285,34.322738 13.256555,34.180814 13.056641,33.908203 C10.284481,30.127985 7.4148684,26.314159 5.015625,22.773438 C2.6163816,19.232715 1,15.953538 1,13.5 C1,6.584596 6.584596,1 13.5,1 Z\"),p.appendChild(d);var g=s.createNS(\"http://www.w3.org/2000/svg\",\"g\");g.setAttributeNS(null,\"transform\",\"translate(6.0, 7.0)\"),g.setAttributeNS(null,\"fill\",\"#FFFFFF\");var v=s.createNS(\"http://www.w3.org/2000/svg\",\"g\");v.setAttributeNS(null,\"transform\",\"translate(8.0, 8.0)\");var m=s.createNS(\"http://www.w3.org/2000/svg\",\"circle\");m.setAttributeNS(null,\"fill\",\"#000000\"),m.setAttributeNS(null,\"opacity\",\"0.25\"),m.setAttributeNS(null,\"cx\",\"5.5\"),m.setAttributeNS(null,\"cy\",\"5.5\"),m.setAttributeNS(null,\"r\",\"5.4999962\");var y=s.createNS(\"http://www.w3.org/2000/svg\",\"circle\");y.setAttributeNS(null,\"fill\",\"#FFFFFF\"),y.setAttributeNS(null,\"cx\",\"5.5\"),y.setAttributeNS(null,\"cy\",\"5.5\"),y.setAttributeNS(null,\"r\",\"5.4999962\"),v.appendChild(m),v.appendChild(y),i.appendChild(a),i.appendChild(f),i.appendChild(p),i.appendChild(g),i.appendChild(v),r.appendChild(i),this._element.appendChild(r),this._offset=t.default$1.convert(e&&e.offset||[0,-14])}this._element.classList.add(\"mapboxgl-marker\"),this._popup=null};mn.prototype.addTo=function(t){return this.remove(),this._map=t,t.getCanvasContainer().appendChild(this._element),t.on(\"move\",this._update),t.on(\"moveend\",this._update),this._update(),this._map.on(\"click\",this._onMapClick),this},mn.prototype.remove=function(){return this._map&&(this._map.off(\"click\",this._onMapClick),this._map.off(\"move\",this._update),this._map.off(\"moveend\",this._update),delete this._map),s.remove(this._element),this._popup&&this._popup.remove(),this},mn.prototype.getLngLat=function(){return this._lngLat},mn.prototype.setLngLat=function(t){return this._lngLat=G.convert(t),this._pos=null,this._popup&&this._popup.setLngLat(this._lngLat),this._update(),this},mn.prototype.getElement=function(){return this._element},mn.prototype.setPopup=function(t){if(this._popup&&(this._popup.remove(),this._popup=null),t){if(!(\"offset\"in t.options)){var e=Math.sqrt(Math.pow(13.5,2)/2);t.options.offset=this._defaultMarker?{top:[0,0],\"top-left\":[0,0],\"top-right\":[0,0],bottom:[0,-38.1],\"bottom-left\":[e,-1*(24.6+e)],\"bottom-right\":[-e,-1*(24.6+e)],left:[13.5,-24.6],right:[-13.5,-24.6]}:this._offset}this._popup=t,this._lngLat&&this._popup.setLngLat(this._lngLat)}return this},mn.prototype._onMapClick=function(t){var e=t.originalEvent.target,r=this._element;this._popup&&(e===r||r.contains(e))&&this.togglePopup()},mn.prototype.getPopup=function(){return this._popup},mn.prototype.togglePopup=function(){var t=this._popup;return t?(t.isOpen()?t.remove():t.addTo(this._map),this):this},mn.prototype._update=function(t){this._map&&(this._map.transform.renderWorldCopies&&(this._lngLat=dn(this._lngLat,this._pos,this._map.transform)),this._pos=this._map.project(this._lngLat)._add(this._offset),t&&\"moveend\"!==t.type||(this._pos=this._pos.round()),s.setTransform(this._element,gn[this._anchor]+\" translate(\"+this._pos.x+\"px, \"+this._pos.y+\"px)\"),vn(this._element,this._anchor,\"marker\"))},mn.prototype.getOffset=function(){return this._offset},mn.prototype.setOffset=function(e){return this._offset=t.default$1.convert(e),this._update(),this};var yn,xn={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showUserLocation:!0},bn=function(e){function r(r){e.call(this),this.options=t.extend({},xn,r),t.bindAll([\"_onSuccess\",\"_onError\",\"_finish\",\"_setupUI\",\"_updateCamera\",\"_updateMarker\"],this)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.onAdd=function(e){var r;return this._map=e,this._container=s.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),r=this._setupUI,void 0!==yn?r(yn):void 0!==t.default.navigator.permissions?t.default.navigator.permissions.query({name:\"geolocation\"}).then(function(t){yn=\"denied\"!==t.state,r(yn)}):(yn=!!t.default.navigator.geolocation,r(yn)),this._container},r.prototype.onRemove=function(){void 0!==this._geolocationWatchID&&(t.default.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker.remove(),s.remove(this._container),this._map=void 0},r.prototype._onSuccess=function(e){if(this.options.trackUserLocation)switch(this._lastKnownPosition=e,this._watchState){case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"BACKGROUND\":case\"BACKGROUND_ERROR\":this._watchState=\"BACKGROUND\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\")}this.options.showUserLocation&&\"OFF\"!==this._watchState&&this._updateMarker(e),this.options.trackUserLocation&&\"ACTIVE_LOCK\"!==this._watchState||this._updateCamera(e),this.options.showUserLocation&&this._dotElement.classList.remove(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"geolocate\",e)),this._finish()},r.prototype._updateCamera=function(t){var e=new G(t.coords.longitude,t.coords.latitude),r=t.coords.accuracy;this._map.fitBounds(e.toBounds(r),this.options.fitBoundsOptions,{geolocateSource:!0})},r.prototype._updateMarker=function(t){t?this._userLocationDotMarker.setLngLat([t.coords.longitude,t.coords.latitude]).addTo(this._map):this._userLocationDotMarker.remove()},r.prototype._onError=function(e){if(this.options.trackUserLocation)if(1===e.code)this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),void 0!==this._geolocationWatchID&&this._clearWatch();else switch(this._watchState){case\"WAITING_ACTIVE\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"ACTIVE_LOCK\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\");break;case\"BACKGROUND\":this._watchState=\"BACKGROUND_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\")}\"OFF\"!==this._watchState&&this.options.showUserLocation&&this._dotElement.classList.add(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"error\",e)),this._finish()},r.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},r.prototype._setupUI=function(e){var r=this;!1!==e&&(this._container.addEventListener(\"contextmenu\",function(t){return t.preventDefault()}),this._geolocateButton=s.create(\"button\",\"mapboxgl-ctrl-icon mapboxgl-ctrl-geolocate\",this._container),this._geolocateButton.type=\"button\",this._geolocateButton.setAttribute(\"aria-label\",\"Geolocate\"),this.options.trackUserLocation&&(this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this._watchState=\"OFF\"),this.options.showUserLocation&&(this._dotElement=s.create(\"div\",\"mapboxgl-user-location-dot\"),this._userLocationDotMarker=new mn(this._dotElement),this.options.trackUserLocation&&(this._watchState=\"OFF\")),this._geolocateButton.addEventListener(\"click\",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on(\"movestart\",function(e){e.geolocateSource||\"ACTIVE_LOCK\"!==r._watchState||(r._watchState=\"BACKGROUND\",r._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\"),r._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),r.fire(new t.Event(\"trackuserlocationend\")))}))},r.prototype.trigger=function(){if(!this._setup)return t.warnOnce(\"Geolocate control triggered before added to a map\"),!1;if(this.options.trackUserLocation){switch(this._watchState){case\"OFF\":this._watchState=\"WAITING_ACTIVE\",this.fire(new t.Event(\"trackuserlocationstart\"));break;case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":case\"BACKGROUND_ERROR\":this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this.fire(new t.Event(\"trackuserlocationend\"));break;case\"BACKGROUND\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new t.Event(\"trackuserlocationstart\"))}switch(this._watchState){case\"WAITING_ACTIVE\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_LOCK\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"BACKGROUND\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\");break;case\"BACKGROUND_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\")}\"OFF\"===this._watchState&&void 0!==this._geolocationWatchID?this._clearWatch():void 0===this._geolocationWatchID&&(this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"true\"),this._geolocationWatchID=t.default.navigator.geolocation.watchPosition(this._onSuccess,this._onError,this.options.positionOptions))}else t.default.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},r.prototype._clearWatch=function(){t.default.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this.options.showUserLocation&&this._updateMarker(null)},r}(t.Evented),_n={maxWidth:100,unit:\"metric\"},wn=function(e){this.options=t.extend({},_n,e),t.bindAll([\"_onMove\",\"setUnit\"],this)};function kn(t,e,r){var n,i,a,o,s,l,c=r&&r.maxWidth||100,u=t._container.clientHeight/2,f=(n=t.unproject([0,u]),i=t.unproject([c,u]),a=Math.PI/180,o=n.lat*a,s=i.lat*a,l=Math.sin(o)*Math.sin(s)+Math.cos(o)*Math.cos(s)*Math.cos((i.lng-n.lng)*a),6371e3*Math.acos(Math.min(l,1)));if(r&&\"imperial\"===r.unit){var h=3.2808*f;h>5280?Tn(e,c,h/5280,\"mi\"):Tn(e,c,h,\"ft\")}else r&&\"nautical\"===r.unit?Tn(e,c,f/1852,\"nm\"):Tn(e,c,f,\"m\")}function Tn(t,e,r,n){var i,a,o,s=(i=r,(a=Math.pow(10,(\"\"+Math.floor(i)).length-1))*(o=(o=i/a)>=10?10:o>=5?5:o>=3?3:o>=2?2:1)),l=s/r;\"m\"===n&&s>=1e3&&(s/=1e3,n=\"km\"),t.style.width=e*l+\"px\",t.innerHTML=s+n}wn.prototype.getDefaultPosition=function(){return\"bottom-left\"},wn.prototype._onMove=function(){kn(this._map,this._container,this.options)},wn.prototype.onAdd=function(t){return this._map=t,this._container=s.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-scale\",t.getContainer()),this._map.on(\"move\",this._onMove),this._onMove(),this._container},wn.prototype.onRemove=function(){s.remove(this._container),this._map.off(\"move\",this._onMove),this._map=void 0},wn.prototype.setUnit=function(t){this.options.unit=t,kn(this._map,this._container,this.options)};var An=function(){this._fullscreen=!1,t.bindAll([\"_onClickFullscreen\",\"_changeIcon\"],this),\"onfullscreenchange\"in t.default.document?this._fullscreenchange=\"fullscreenchange\":\"onmozfullscreenchange\"in t.default.document?this._fullscreenchange=\"mozfullscreenchange\":\"onwebkitfullscreenchange\"in t.default.document?this._fullscreenchange=\"webkitfullscreenchange\":\"onmsfullscreenchange\"in t.default.document&&(this._fullscreenchange=\"MSFullscreenChange\"),this._className=\"mapboxgl-ctrl\"};An.prototype.onAdd=function(e){return this._map=e,this._mapContainer=this._map.getContainer(),this._container=s.create(\"div\",this._className+\" mapboxgl-ctrl-group\"),this._checkFullscreenSupport()?this._setupUI():(this._container.style.display=\"none\",t.warnOnce(\"This device does not support fullscreen mode.\")),this._container},An.prototype.onRemove=function(){s.remove(this._container),this._map=null,t.default.document.removeEventListener(this._fullscreenchange,this._changeIcon)},An.prototype._checkFullscreenSupport=function(){return!!(t.default.document.fullscreenEnabled||t.default.document.mozFullScreenEnabled||t.default.document.msFullscreenEnabled||t.default.document.webkitFullscreenEnabled)},An.prototype._setupUI=function(){var e=this._fullscreenButton=s.create(\"button\",this._className+\"-icon \"+this._className+\"-fullscreen\",this._container);e.setAttribute(\"aria-label\",\"Toggle fullscreen\"),e.type=\"button\",this._fullscreenButton.addEventListener(\"click\",this._onClickFullscreen),t.default.document.addEventListener(this._fullscreenchange,this._changeIcon)},An.prototype._isFullscreen=function(){return this._fullscreen},An.prototype._changeIcon=function(){(t.default.document.fullscreenElement||t.default.document.mozFullScreenElement||t.default.document.webkitFullscreenElement||t.default.document.msFullscreenElement)===this._mapContainer!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle(this._className+\"-shrink\"),this._fullscreenButton.classList.toggle(this._className+\"-fullscreen\"))},An.prototype._onClickFullscreen=function(){this._isFullscreen()?t.default.document.exitFullscreen?t.default.document.exitFullscreen():t.default.document.mozCancelFullScreen?t.default.document.mozCancelFullScreen():t.default.document.msExitFullscreen?t.default.document.msExitFullscreen():t.default.document.webkitCancelFullScreen&&t.default.document.webkitCancelFullScreen():this._mapContainer.requestFullscreen?this._mapContainer.requestFullscreen():this._mapContainer.mozRequestFullScreen?this._mapContainer.mozRequestFullScreen():this._mapContainer.msRequestFullscreen?this._mapContainer.msRequestFullscreen():this._mapContainer.webkitRequestFullscreen&&this._mapContainer.webkitRequestFullscreen()};var Mn={closeButton:!0,closeOnClick:!0},Sn=function(e){function r(r){e.call(this),this.options=t.extend(Object.create(Mn),r),t.bindAll([\"_update\",\"_onClickClose\"],this)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.addTo=function(e){return this._map=e,this._map.on(\"move\",this._update),this.options.closeOnClick&&this._map.on(\"click\",this._onClickClose),this._update(),this.fire(new t.Event(\"open\")),this},r.prototype.isOpen=function(){return!!this._map},r.prototype.remove=function(){return this._content&&s.remove(this._content),this._container&&(s.remove(this._container),delete this._container),this._map&&(this._map.off(\"move\",this._update),this._map.off(\"click\",this._onClickClose),delete this._map),this.fire(new t.Event(\"close\")),this},r.prototype.getLngLat=function(){return this._lngLat},r.prototype.setLngLat=function(t){return this._lngLat=G.convert(t),this._pos=null,this._update(),this},r.prototype.setText=function(e){return this.setDOMContent(t.default.document.createTextNode(e))},r.prototype.setHTML=function(e){var r,n=t.default.document.createDocumentFragment(),i=t.default.document.createElement(\"body\");for(i.innerHTML=e;r=i.firstChild;)n.appendChild(r);return this.setDOMContent(n)},r.prototype.setDOMContent=function(t){return this._createContent(),this._content.appendChild(t),this._update(),this},r.prototype._createContent=function(){this._content&&s.remove(this._content),this._content=s.create(\"div\",\"mapboxgl-popup-content\",this._container),this.options.closeButton&&(this._closeButton=s.create(\"button\",\"mapboxgl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.setAttribute(\"aria-label\",\"Close popup\"),this._closeButton.innerHTML=\"&#215;\",this._closeButton.addEventListener(\"click\",this._onClickClose))},r.prototype._update=function(){if(this._map&&this._lngLat&&this._content){this._container||(this._container=s.create(\"div\",\"mapboxgl-popup\",this._map.getContainer()),this._tip=s.create(\"div\",\"mapboxgl-popup-tip\",this._container),this._container.appendChild(this._content)),this._map.transform.renderWorldCopies&&(this._lngLat=dn(this._lngLat,this._pos,this._map.transform));var e=this._pos=this._map.project(this._lngLat),r=this.options.anchor,n=function e(r){if(r){if(\"number\"==typeof r){var n=Math.round(Math.sqrt(.5*Math.pow(r,2)));return{center:new t.default$1(0,0),top:new t.default$1(0,r),\"top-left\":new t.default$1(n,n),\"top-right\":new t.default$1(-n,n),bottom:new t.default$1(0,-r),\"bottom-left\":new t.default$1(n,-n),\"bottom-right\":new t.default$1(-n,-n),left:new t.default$1(r,0),right:new t.default$1(-r,0)}}if(r instanceof t.default$1||Array.isArray(r)){var i=t.default$1.convert(r);return{center:i,top:i,\"top-left\":i,\"top-right\":i,bottom:i,\"bottom-left\":i,\"bottom-right\":i,left:i,right:i}}return{center:t.default$1.convert(r.center||[0,0]),top:t.default$1.convert(r.top||[0,0]),\"top-left\":t.default$1.convert(r[\"top-left\"]||[0,0]),\"top-right\":t.default$1.convert(r[\"top-right\"]||[0,0]),bottom:t.default$1.convert(r.bottom||[0,0]),\"bottom-left\":t.default$1.convert(r[\"bottom-left\"]||[0,0]),\"bottom-right\":t.default$1.convert(r[\"bottom-right\"]||[0,0]),left:t.default$1.convert(r.left||[0,0]),right:t.default$1.convert(r.right||[0,0])}}return e(new t.default$1(0,0))}(this.options.offset);if(!r){var i,a=this._container.offsetWidth,o=this._container.offsetHeight;i=e.y+n.bottom.y<o?[\"top\"]:e.y>this._map.transform.height-o?[\"bottom\"]:[],e.x<a/2?i.push(\"left\"):e.x>this._map.transform.width-a/2&&i.push(\"right\"),r=0===i.length?\"bottom\":i.join(\"-\")}var l=e.add(n[r]).round();s.setTransform(this._container,gn[r]+\" translate(\"+l.x+\"px,\"+l.y+\"px)\"),vn(this._container,r,\"popup\")}},r.prototype._onClickClose=function(){this.remove()},r}(t.Evented),En={version:\"0.45.0\",supported:e,workerCount:Math.max(Math.floor(a.hardwareConcurrency/2),1),setRTLTextPlugin:t.setRTLTextPlugin,Map:un,NavigationControl:pn,GeolocateControl:bn,AttributionControl:nn,ScaleControl:wn,FullscreenControl:An,Popup:Sn,Marker:mn,Style:Je,LngLat:G,LngLatBounds:Y,Point:t.default$1,Evented:t.Evented,config:v,get accessToken(){return v.ACCESS_TOKEN},set accessToken(t){v.ACCESS_TOKEN=t},workerUrl:\"\"};return En}),n})}).call(this,\"undefined\"!=typeof global?global:\"undefined\"!=typeof self?self:\"undefined\"!=typeof window?window:{})},{}],422:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=1<<t+1,r=new Array(e),n=0;n<e;++n)r[n]=a(t,n);return r};var n=t(\"convex-hull\");function i(t,e,r){for(var n=new Array(t),i=0;i<t;++i)n[i]=0,i===e&&(n[i]+=.5),i===r&&(n[i]+=.5);return n}function a(t,e){if(0===e||e===(1<<t+1)-1)return[];for(var r=[],a=[],o=0;o<=t;++o)if(e&1<<o){r.push(i(t,o-1,o-1)),a.push(null);for(var s=0;s<=t;++s)~e&1<<s&&(r.push(i(t,o-1,s-1)),a.push([o,s]))}var l=n(r),c=[];t:for(o=0;o<l.length;++o){var u=l[o],f=[];for(s=0;s<u.length;++s){if(!a[u[s]])continue t;f.push(a[u[s]].slice())}c.push(f)}return c}},{\"convex-hull\":123}],423:[function(t,e,r){var n=t(\"./normalize\"),i=t(\"gl-mat4/create\"),a=t(\"gl-mat4/clone\"),o=t(\"gl-mat4/determinant\"),s=t(\"gl-mat4/invert\"),l=t(\"gl-mat4/transpose\"),c={length:t(\"gl-vec3/length\"),normalize:t(\"gl-vec3/normalize\"),dot:t(\"gl-vec3/dot\"),cross:t(\"gl-vec3/cross\")},u=i(),f=i(),h=[0,0,0,0],p=[[0,0,0],[0,0,0],[0,0,0]],d=[0,0,0];function g(t,e,r,n,i){t[0]=e[0]*n+r[0]*i,t[1]=e[1]*n+r[1]*i,t[2]=e[2]*n+r[2]*i}e.exports=function(t,e,r,i,v,m){if(e||(e=[0,0,0]),r||(r=[0,0,0]),i||(i=[0,0,0]),v||(v=[0,0,0,1]),m||(m=[0,0,0,1]),!n(u,t))return!1;if(a(f,u),f[3]=0,f[7]=0,f[11]=0,f[15]=1,Math.abs(o(f)<1e-8))return!1;var y,x,b,_,w,k,T,A=u[3],M=u[7],S=u[11],E=u[12],C=u[13],L=u[14],z=u[15];if(0!==A||0!==M||0!==S){if(h[0]=A,h[1]=M,h[2]=S,h[3]=z,!s(f,f))return!1;l(f,f),y=v,b=f,_=(x=h)[0],w=x[1],k=x[2],T=x[3],y[0]=b[0]*_+b[4]*w+b[8]*k+b[12]*T,y[1]=b[1]*_+b[5]*w+b[9]*k+b[13]*T,y[2]=b[2]*_+b[6]*w+b[10]*k+b[14]*T,y[3]=b[3]*_+b[7]*w+b[11]*k+b[15]*T}else v[0]=v[1]=v[2]=0,v[3]=1;if(e[0]=E,e[1]=C,e[2]=L,function(t,e){t[0][0]=e[0],t[0][1]=e[1],t[0][2]=e[2],t[1][0]=e[4],t[1][1]=e[5],t[1][2]=e[6],t[2][0]=e[8],t[2][1]=e[9],t[2][2]=e[10]}(p,u),r[0]=c.length(p[0]),c.normalize(p[0],p[0]),i[0]=c.dot(p[0],p[1]),g(p[1],p[1],p[0],1,-i[0]),r[1]=c.length(p[1]),c.normalize(p[1],p[1]),i[0]/=r[1],i[1]=c.dot(p[0],p[2]),g(p[2],p[2],p[0],1,-i[1]),i[2]=c.dot(p[1],p[2]),g(p[2],p[2],p[1],1,-i[2]),r[2]=c.length(p[2]),c.normalize(p[2],p[2]),i[1]/=r[2],i[2]/=r[2],c.cross(d,p[1],p[2]),c.dot(p[0],d)<0)for(var O=0;O<3;O++)r[O]*=-1,p[O][0]*=-1,p[O][1]*=-1,p[O][2]*=-1;return 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MIN_DIFF : scale.y;\\n\\n vec2 scaleRatio = adjustedScale * viewport.zw;\\n\\tvec2 normalWidth = thickness / scaleRatio;\\n\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineBot = 1. - lineTop;\\n\\n\\tfragColor = (lineStart * aColor + lineEnd * bColor) / 255.;\\n\\n\\tif (isNaN(aCoord.x) || isNaN(aCoord.y) || isNaN(bCoord.x) || isNaN(bCoord.y)) return;\\n\\n\\tif (aCoord == prevCoord) prevCoord = aCoord + normalize(bCoord - aCoord);\\n\\tif (bCoord == nextCoord) nextCoord = bCoord - normalize(bCoord - aCoord);\\n\\n\\tvec2 prevDiff = aCoord - prevCoord;\\n\\tvec2 currDiff = bCoord - aCoord;\\n\\tvec2 nextDiff = nextCoord - bCoord;\\n\\n\\tvec2 prevTangent = normalize(prevDiff * scaleRatio);\\n\\tvec2 currTangent = normalize(currDiff * scaleRatio);\\n\\tvec2 nextTangent = normalize(nextDiff * scaleRatio);\\n\\n\\tvec2 prevNormal = vec2(-prevTangent.y, prevTangent.x);\\n\\tvec2 currNormal = vec2(-currTangent.y, currTangent.x);\\n\\tvec2 nextNormal = vec2(-nextTangent.y, nextTangent.x);\\n\\n\\tvec2 startJoinDirection = normalize(prevTangent - currTangent);\\n\\tvec2 endJoinDirection = normalize(currTangent - nextTangent);\\n\\n\\t// collapsed/unidirectional segment cases\\n\\t// FIXME: there should be more elegant solution\\n\\tvec2 prevTanDiff = abs(prevTangent - currTangent);\\n\\tvec2 nextTanDiff = abs(nextTangent - currTangent);\\n\\tif (max(prevTanDiff.x, prevTanDiff.y) < MIN_DIFF) {\\n\\t\\tstartJoinDirection = currNormal;\\n\\t}\\n\\tif (max(nextTanDiff.x, nextTanDiff.y) < MIN_DIFF) {\\n\\t\\tendJoinDirection = currNormal;\\n\\t}\\n\\tif (aCoord == bCoord) {\\n\\t\\tendJoinDirection = startJoinDirection;\\n\\t\\tcurrNormal = prevNormal;\\n\\t\\tcurrTangent = prevTangent;\\n\\t}\\n\\n\\ttangent = currTangent;\\n\\n\\t//calculate join shifts relative to normals\\n\\tfloat startJoinShift = dot(currNormal, startJoinDirection);\\n\\tfloat endJoinShift = dot(currNormal, endJoinDirection);\\n\\n\\tfloat startMiterRatio = abs(1. / startJoinShift);\\n\\tfloat endMiterRatio = abs(1. / endJoinShift);\\n\\n\\tvec2 startJoin = startJoinDirection * startMiterRatio;\\n\\tvec2 endJoin = endJoinDirection * endMiterRatio;\\n\\n\\tvec2 startTopJoin, startBotJoin, endTopJoin, endBotJoin;\\n\\tstartTopJoin = sign(startJoinShift) * startJoin * .5;\\n\\tstartBotJoin = -startTopJoin;\\n\\n\\tendTopJoin = sign(endJoinShift) * endJoin * .5;\\n\\tendBotJoin = -endTopJoin;\\n\\n\\tvec2 aTopCoord = aCoord + normalWidth * startTopJoin;\\n\\tvec2 bTopCoord = bCoord + normalWidth * endTopJoin;\\n\\tvec2 aBotCoord = aCoord + normalWidth * startBotJoin;\\n\\tvec2 bBotCoord = bCoord + normalWidth * endBotJoin;\\n\\n\\t//miter anti-clipping\\n\\tfloat baClipping = distToLine(bCoord, aCoord, aBotCoord) / dot(normalize(normalWidth * endBotJoin), normalize(normalWidth.yx * vec2(-startBotJoin.y, startBotJoin.x)));\\n\\tfloat abClipping = distToLine(aCoord, bCoord, bTopCoord) / dot(normalize(normalWidth * startBotJoin), normalize(normalWidth.yx * vec2(-endBotJoin.y, endBotJoin.x)));\\n\\n\\t//prevent close to reverse direction switch\\n\\tbool prevReverse = dot(currTangent, prevTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, prevNormal)) * min(length(prevDiff), length(currDiff)) < length(normalWidth * currNormal);\\n\\tbool nextReverse = dot(currTangent, nextTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, nextNormal)) * min(length(nextDiff), length(currDiff)) < length(normalWidth * currNormal);\\n\\n\\tif (prevReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * startJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / startMiterRatio, 1.);\\n\\t\\taBotCoord = aCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\taTopCoord = aCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!nextReverse && baClipping > 0. && baClipping < length(normalWidth * endBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\tbTopCoord -= normalWidth * endTopJoin;\\n\\t\\tbTopCoord += normalize(endTopJoin * normalWidth) * baClipping;\\n\\t}\\n\\n\\tif (nextReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * endJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / endMiterRatio, 1.);\\n\\t\\tbBotCoord = bCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\tbTopCoord = bCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!prevReverse && abClipping > 0. && abClipping < length(normalWidth * startBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\taBotCoord -= normalWidth * startBotJoin;\\n\\t\\taBotCoord += normalize(startBotJoin * normalWidth) * abClipping;\\n\\t}\\n\\n\\tvec2 aTopPosition = (aTopCoord) * adjustedScale + translate;\\n\\tvec2 aBotPosition = (aBotCoord) * adjustedScale + translate;\\n\\n\\tvec2 bTopPosition = (bTopCoord) * adjustedScale + translate;\\n\\tvec2 bBotPosition = (bBotCoord) * adjustedScale + translate;\\n\\n\\t//position is normalized 0..1 coord on the screen\\n\\tvec2 position = (aTopPosition * lineTop + aBotPosition * lineBot) * lineStart + (bTopPosition * lineTop + bBotPosition * lineBot) * lineEnd;\\n\\n\\tstartCoord = aCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\tendCoord = bCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tenableStartMiter = step(dot(currTangent, prevTangent), .5);\\n\\tenableEndMiter = step(dot(currTangent, nextTangent), .5);\\n\\n\\t//bevel miter cutoffs\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x) / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n\\n\\t//round miter cutoffs\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * abs(dot(startJoinDirection, currNormal)) * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * abs(dot(endJoinDirection, currNormal)) * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x) / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D dashPattern;\\nuniform float dashSize, pixelRatio, thickness, opacity, id, miterMode;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nvoid main() {\\n\\tfloat alpha = 1., distToStart, distToEnd;\\n\\tfloat cutoff = thickness * .5;\\n\\n\\t//bevel miter\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToStart + 1., 0.), 1.);\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToEnd + 1., 0.), 1.);\\n\\t\\t}\\n\\t}\\n\\n\\t// round miter\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - startCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - endCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashSize) * .5 + .25;\\n\\tfloat dash = texture2D(dashPattern, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1},bColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:4,divisor:1},prevCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:0,divisor:1},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},nextCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:24,divisor:1}}},n))}catch(t){e=i}return{fill:t({primitive:\"triangle\",elements:function(t,e){return e.triangles},offset:0,vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position, positionFract;\\n\\nuniform vec4 color;\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float pixelRatio, id;\\nuniform vec4 viewport;\\nuniform float opacity;\\n\\nvarying vec4 fragColor;\\n\\nconst float MAX_LINES = 256.;\\n\\nvoid main() {\\n\\tfloat depth = (MAX_LINES - 4. - id) / (MAX_LINES);\\n\\n\\tvec2 position = position * scale + translate\\n + positionFract * scale + translateFract\\n + position * scaleFract\\n + positionFract * scaleFract;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n\\tfragColor.a *= opacity;\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n\\tgl_FragColor = fragColor;\\n}\\n\"]),uniforms:{scale:t.prop(\"scale\"),color:t.prop(\"fill\"),scaleFract:t.prop(\"scaleFract\"),translateFract:t.prop(\"translateFract\"),translate:t.prop(\"translate\"),opacity:t.prop(\"opacity\"),pixelRatio:t.context(\"pixelRatio\"),id:t.prop(\"id\"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]}},attributes:{position:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8},positionFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:8}},blend:n.blend,depth:{enable:!1},scissor:n.scissor,stencil:n.stencil,viewport:n.viewport}),rect:i,miter:e}},v.defaults={dashes:null,join:\"miter\",miterLimit:1,thickness:10,cap:\"square\",color:\"black\",opacity:1,overlay:!1,viewport:null,range:null,close:!1,fill:null},v.prototype.render=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];e.length&&(t=this).update.apply(t,e),this.draw()},v.prototype.draw=function(){for(var t=this,e=[],r=arguments.length;r--;)e[r]=arguments[r];return(e.length?e:this.passes).forEach(function(e,r){var n;if(e&&Array.isArray(e))return(n=t).draw.apply(n,e);\"number\"==typeof e&&(e=t.passes[e]),e&&e.count>1&&e.opacity&&(t.regl._refresh(),e.fill&&e.triangles&&e.triangles.length>2&&t.shaders.fill(e),e.thickness&&(e.scale[0]*e.viewport.width>v.precisionThreshold||e.scale[1]*e.viewport.height>v.precisionThreshold?t.shaders.rect(e):\"rect\"===e.join||!e.join&&(e.thickness<=2||e.count>=v.maxPoints)?t.shaders.rect(e):t.shaders.miter(e)))}),this},v.prototype.update=function(t){var e=this;if(t){null!=t.length?\"number\"==typeof t[0]&&(t=[{positions:t}]):Array.isArray(t)||(t=[t]);var r=this.regl,o=this.gl;if(t.forEach(function(t,f){var d=e.passes[f];if(void 0!==t)if(null!==t){if(\"number\"==typeof t[0]&&(t={positions:t}),t=s(t,{positions:\"positions points data coords\",thickness:\"thickness lineWidth lineWidths line-width linewidth width stroke-width strokewidth strokeWidth\",join:\"lineJoin linejoin join type mode\",miterLimit:\"miterlimit miterLimit\",dashes:\"dash dashes dasharray dash-array dashArray\",color:\"color colour stroke colors colours stroke-color strokeColor\",fill:\"fill fill-color fillColor\",opacity:\"alpha opacity\",overlay:\"overlay crease overlap intersect\",close:\"closed close closed-path closePath\",range:\"range dataBox\",viewport:\"viewport viewBox\",hole:\"holes hole hollow\"}),d||(e.passes[f]=d={id:f,scale:null,scaleFract:null,translate:null,translateFract:null,count:0,hole:[],depth:0,dashLength:1,dashTexture:r.texture({channels:1,data:new Uint8Array([255]),width:1,height:1,mag:\"linear\",min:\"linear\"}),colorBuffer:r.buffer({usage:\"dynamic\",type:\"uint8\",data:new Uint8Array}),positionBuffer:r.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array}),positionFractBuffer:r.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array})},t=a({},v.defaults,t)),null!=t.thickness&&(d.thickness=parseFloat(t.thickness)),null!=t.opacity&&(d.opacity=parseFloat(t.opacity)),null!=t.miterLimit&&(d.miterLimit=parseFloat(t.miterLimit)),null!=t.overlay&&(d.overlay=!!t.overlay,f<v.maxLines&&(d.depth=2*(v.maxLines-1-f%v.maxLines)/v.maxLines-1)),null!=t.join&&(d.join=t.join),null!=t.hole&&(d.hole=t.hole),null!=t.fill&&(d.fill=t.fill?n(t.fill,\"uint8\"):null),null!=t.viewport&&(d.viewport=g(t.viewport)),d.viewport||(d.viewport=g([o.drawingBufferWidth,o.drawingBufferHeight])),null!=t.close&&(d.close=t.close),null===t.positions&&(t.positions=[]),t.positions){var m,y;if(t.positions.x&&t.positions.y){var x=t.positions.x,b=t.positions.y;y=d.count=Math.max(x.length,b.length),m=new Float64Array(2*y);for(var _=0;_<y;_++)m[2*_]=x[_],m[2*_+1]=b[_]}else m=l(t.positions,\"float64\"),y=d.count=Math.floor(m.length/2);var w=d.bounds=i(m,2);if(d.fill){for(var k=[],T={},A=0,M=0,S=0,E=d.count;M<E;M++){var C=m[2*M],L=m[2*M+1];isNaN(C)||isNaN(L)||null==C||null==L?(C=m[2*A],L=m[2*A+1],T[M]=A):A=M,k[S++]=C,k[S++]=L}for(var z=c(k,d.hole||[]),O=0,I=z.length;O<I;O++)null!=T[z[O]]&&(z[O]=T[z[O]]);d.triangles=z}var D=new Float64Array(m);u(D,2,w);var P=new Float64Array(2*y+6);d.close?m[0]===m[2*y-2]&&m[1]===m[2*y-1]?(P[0]=D[2*y-4],P[1]=D[2*y-3]):(P[0]=D[2*y-2],P[1]=D[2*y-1]):(P[0]=D[0],P[1]=D[1]),P.set(D,2),d.close?m[0]===m[2*y-2]&&m[1]===m[2*y-1]?(P[2*y+2]=D[2],P[2*y+3]=D[3],d.count-=1):(P[2*y+2]=D[0],P[2*y+3]=D[1],P[2*y+4]=D[2],P[2*y+5]=D[3]):(P[2*y+2]=D[2*y-2],P[2*y+3]=D[2*y-1],P[2*y+4]=D[2*y-2],P[2*y+5]=D[2*y-1]),d.positionBuffer(h(P)),d.positionFractBuffer(p(P))}if(t.range?d.range=t.range:d.range||(d.range=d.bounds),(t.range||t.positions)&&d.count){var R=d.bounds,F=R[2]-R[0],B=R[3]-R[1],N=d.range[2]-d.range[0],j=d.range[3]-d.range[1];d.scale=[F/N,B/j],d.translate=[-d.range[0]/N+R[0]/N||0,-d.range[1]/j+R[1]/j||0],d.scaleFract=p(d.scale),d.translateFract=p(d.translate)}if(t.dashes){var V,U=0;if(!t.dashes||t.dashes.length<2)U=1,V=new Uint8Array([255,255,255,255,255,255,255,255]);else{U=0;for(var H=0;H<t.dashes.length;++H)U+=t.dashes[H];V=new Uint8Array(U*v.dashMult);for(var q=0,G=255,Y=0;Y<2;Y++)for(var W=0;W<t.dashes.length;++W){for(var X=0,Z=t.dashes[W]*v.dashMult*.5;X<Z;++X)V[q++]=G;G^=255}}d.dashLength=U,d.dashTexture({channels:1,data:V,width:V.length,height:1,mag:\"linear\",min:\"linear\"},0,0)}if(t.color){var $=d.count,J=t.color;J||(J=\"transparent\");var K=new Uint8Array(4*$+4);if(Array.isArray(J)&&\"number\"!=typeof J[0]){for(var Q=0;Q<$;Q++){var tt=n(J[Q],\"uint8\");K.set(tt,4*Q)}K.set(n(J[0],\"uint8\"),4*$)}else for(var et=n(J,\"uint8\"),rt=0;rt<$+1;rt++)K.set(et,4*rt);d.colorBuffer({usage:\"dynamic\",type:\"uint8\",data:K})}}else e.passes[f]=null}),t.length<this.passes.length){for(var f=t.length;f<this.passes.length;f++){var d=e.passes[f];d&&(d.colorBuffer.destroy(),d.positionBuffer.destroy(),d.dashTexture.destroy())}this.passes.length=t.length}for(var m=[],y=0;y<this.passes.length;y++)null!==e.passes[y]&&m.push(e.passes[y]);return this.passes=m,this}},v.prototype.destroy=function(){return this.passes.forEach(function(t){t.colorBuffer.destroy(),t.positionBuffer.destroy(),t.dashTexture.destroy()}),this.passes.length=0,this}},{\"array-bounds\":58,\"array-normalize\":59,\"color-normalize\":113,earcut:165,\"es6-weak-map\":219,\"flatten-vertex-data\":226,glslify:404,\"object-assign\":449,\"parse-rect\":454,\"pick-by-alias\":460,\"to-float32\":525}],487:[function(t,e,r){\"use strict\";function n(t,e){return function(t){if(Array.isArray(t))return t}(t)||function(t,e){var r=[],n=!0,i=!1,a=void 0;try{for(var o,s=t[Symbol.iterator]();!(n=(o=s.next()).done)&&(r.push(o.value),!e||r.length!==e);n=!0);}catch(t){i=!0,a=t}finally{try{n||null==s.return||s.return()}finally{if(i)throw a}}return r}(t,e)||function(){throw new TypeError(\"Invalid attempt to destructure non-iterable instance\")}()}function i(t){return function(t){if(Array.isArray(t)){for(var e=0,r=new Array(t.length);e<t.length;e++)r[e]=t[e];return r}}(t)||function(t){if(Symbol.iterator in Object(t)||\"[object Arguments]\"===Object.prototype.toString.call(t))return Array.from(t)}(t)||function(){throw new TypeError(\"Invalid attempt to spread non-iterable instance\")}()}var a=t(\"color-normalize\"),o=t(\"array-bounds\"),s=t(\"color-id\"),l=t(\"point-cluster\"),c=t(\"object-assign\"),u=t(\"glslify\"),f=t(\"pick-by-alias\"),h=t(\"update-diff\"),p=t(\"flatten-vertex-data\"),d=t(\"is-iexplorer\"),g=t(\"to-float32\"),v=t(\"parse-rect\"),m=y;function y(t,e){var r=this;if(!(this instanceof y))return new y(t,e);\"function\"==typeof t?(e||(e={}),e.regl=t):(e=t,t=null),e&&e.length&&(e.positions=e);var n,i=(t=e.regl)._gl,a=[];this.tooManyColors=d,n=t.texture({data:new Uint8Array(1020),width:255,height:1,type:\"uint8\",format:\"rgba\",wrapS:\"clamp\",wrapT:\"clamp\",mag:\"nearest\",min:\"nearest\"}),c(this,{regl:t,gl:i,groups:[],markerCache:[null],markerTextures:[null],palette:a,paletteIds:{},paletteTexture:n,maxColors:255,maxSize:100,canvas:i.canvas}),this.update(e);var o={uniforms:{pixelRatio:t.context(\"pixelRatio\"),palette:n,paletteSize:function(t,e){return[r.tooManyColors?0:255,n.height]},scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translate:t.prop(\"translate\"),translateFract:t.prop(\"translateFract\"),opacity:t.prop(\"opacity\"),marker:t.prop(\"markerTexture\")},attributes:{x:function(t,e){return e.xAttr||{buffer:e.positionBuffer,stride:8,offset:0}},y:function(t,e){return e.yAttr||{buffer:e.positionBuffer,stride:8,offset:4}},xFract:function(t,e){return e.xAttr?{constant:[0,0]}:{buffer:e.positionFractBuffer,stride:8,offset:0}},yFract:function(t,e){return e.yAttr?{constant:[0,0]}:{buffer:e.positionFractBuffer,stride:8,offset:4}},size:function(t,e){return e.size.length?{buffer:e.sizeBuffer,stride:2,offset:0}:{constant:[Math.round(255*e.size/r.maxSize)]}},borderSize:function(t,e){return e.borderSize.length?{buffer:e.sizeBuffer,stride:2,offset:1}:{constant:[Math.round(255*e.borderSize/r.maxSize)]}},colorId:function(t,e){return e.color.length?{buffer:e.colorBuffer,stride:r.tooManyColors?8:4,offset:0}:{constant:r.tooManyColors?a.slice(4*e.color,4*e.color+4):[e.color]}},borderColorId:function(t,e){return e.borderColor.length?{buffer:e.colorBuffer,stride:r.tooManyColors?8:4,offset:r.tooManyColors?4:2}:{constant:r.tooManyColors?a.slice(4*e.borderColor,4*e.borderColor+4):[e.borderColor]}},isActive:function(t,e){return!0===e.activation?{constant:[1]}:e.activation?e.activation:{constant:[0]}}},blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},scissor:{enable:!0,box:t.prop(\"viewport\")},viewport:t.prop(\"viewport\"),stencil:{enable:!1},depth:{enable:!1},elements:t.prop(\"elements\"),count:t.prop(\"count\"),offset:t.prop(\"offset\"),primitive:\"points\"},s=c({},o);s.frag=u([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragWidth, fragBorderColorLevel, fragColorLevel;\\n\\nuniform sampler2D marker;\\nuniform float pixelRatio, opacity;\\n\\nfloat smoothStep(float x, float y) {\\n return 1.0 / (1.0 + exp(50.0*(x - y)));\\n}\\n\\nvoid main() {\\n float dist = texture2D(marker, gl_PointCoord).r, delta = fragWidth;\\n\\n // max-distance alpha\\n if (dist < 0.003) discard;\\n\\n // null-border case\\n if (fragBorderColorLevel == fragColorLevel || fragBorderColor.a == 0.) {\\n float colorAmt = smoothstep(.5 - delta, .5 + delta, dist);\\n gl_FragColor = vec4(fragColor.rgb, colorAmt * fragColor.a * opacity);\\n }\\n else {\\n float borderColorAmt = smoothstep(fragBorderColorLevel - delta, fragBorderColorLevel + delta, dist);\\n float colorAmt = smoothstep(fragColorLevel - delta, fragColorLevel + delta, dist);\\n\\n vec4 color = fragBorderColor;\\n color.a *= borderColorAmt;\\n color = mix(color, fragColor, colorAmt);\\n color.a *= opacity;\\n\\n gl_FragColor = color;\\n }\\n\\n}\\n\"]),s.vert=u([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute float x, y, xFract, yFract;\\nattribute float size, borderSize;\\nattribute vec4 colorId, borderColorId;\\nattribute float isActive;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract, paletteSize;\\nuniform float pixelRatio;\\nuniform sampler2D palette;\\n\\nconst float maxSize = 100.;\\nconst float borderLevel = .5;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragPointSize, fragBorderRadius, fragWidth, fragBorderColorLevel, fragColorLevel;\\n\\nbool isDirect = (paletteSize.x < 1.);\\n\\nvec4 getColor(vec4 id) {\\n return isDirect ? id / 255. : texture2D(palette,\\n vec2(\\n (id.x + .5) / paletteSize.x,\\n (id.y + .5) / paletteSize.y\\n )\\n );\\n}\\n\\nvoid main() {\\n if (isActive == 0.) return;\\n\\n vec2 position = vec2(x, y);\\n vec2 positionFract = vec2(xFract, yFract);\\n\\n vec4 color = getColor(colorId);\\n vec4 borderColor = getColor(borderColorId);\\n\\n float size = size * maxSize / 255.;\\n float borderSize = borderSize * maxSize / 255.;\\n\\n gl_PointSize = 2. * size * pixelRatio;\\n fragPointSize = size * pixelRatio;\\n\\n vec2 pos = (position + translate) * scale\\n + (positionFract + translateFract) * scale\\n + (position + translate) * scaleFract\\n + (positionFract + translateFract) * scaleFract;\\n\\n gl_Position = vec4(pos * 2. - 1., 0, 1);\\n\\n fragColor = color;\\n fragBorderColor = borderColor;\\n fragWidth = 1. / gl_PointSize;\\n\\n fragBorderColorLevel = clamp(borderLevel - borderLevel * borderSize / size, 0., 1.);\\n fragColorLevel = clamp(borderLevel + (1. - borderLevel) * borderSize / size, 0., 1.);\\n}\"]),this.drawMarker=t(s);var l=c({},o);l.frag=u([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor, fragBorderColor;\\n\\nuniform float opacity;\\nvarying float fragBorderRadius, fragWidth;\\n\\nfloat smoothStep(float edge0, float edge1, float x) {\\n\\tfloat t;\\n\\tt = clamp((x - edge0) / (edge1 - edge0), 0.0, 1.0);\\n\\treturn t * t * (3.0 - 2.0 * t);\\n}\\n\\nvoid main() {\\n\\tfloat radius, alpha = 1.0, delta = fragWidth;\\n\\n\\tradius = length(2.0 * gl_PointCoord.xy - 1.0);\\n\\n\\tif (radius > 1.0 + delta) {\\n\\t\\tdiscard;\\n\\t}\\n\\n\\talpha -= smoothstep(1.0 - delta, 1.0 + delta, radius);\\n\\n\\tfloat borderRadius = fragBorderRadius;\\n\\tfloat ratio = smoothstep(borderRadius - delta, borderRadius + delta, radius);\\n\\tvec4 color = mix(fragColor, fragBorderColor, ratio);\\n\\tcolor.a *= alpha * opacity;\\n\\tgl_FragColor = color;\\n}\\n\"]),l.vert=u([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute float x, y, xFract, yFract;\\nattribute float size, borderSize;\\nattribute vec4 colorId, borderColorId;\\nattribute float isActive;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float pixelRatio;\\nuniform sampler2D palette;\\nuniform vec2 paletteSize;\\n\\nconst float maxSize = 100.;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragBorderRadius, fragWidth;\\n\\nbool isDirect = (paletteSize.x < 1.);\\n\\nvec4 getColor(vec4 id) {\\n return isDirect ? id / 255. : texture2D(palette,\\n vec2(\\n (id.x + .5) / paletteSize.x,\\n (id.y + .5) / paletteSize.y\\n )\\n );\\n}\\n\\nvoid main() {\\n // ignore inactive points\\n if (isActive == 0.) return;\\n\\n vec2 position = vec2(x, y);\\n vec2 positionFract = vec2(xFract, yFract);\\n\\n vec4 color = getColor(colorId);\\n vec4 borderColor = getColor(borderColorId);\\n\\n float size = size * maxSize / 255.;\\n float borderSize = borderSize * maxSize / 255.;\\n\\n gl_PointSize = (size + borderSize) * pixelRatio;\\n\\n vec2 pos = (position + translate) * scale\\n + (positionFract + translateFract) * scale\\n + (position + translate) * scaleFract\\n + (positionFract + translateFract) * scaleFract;\\n\\n gl_Position = vec4(pos * 2. - 1., 0, 1);\\n\\n fragBorderRadius = 1. - 2. * borderSize / (size + borderSize);\\n fragColor = color;\\n fragBorderColor = borderColor.a == 0. || borderSize == 0. ? vec4(color.rgb, 0.) : borderColor;\\n fragWidth = 1. / gl_PointSize;\\n}\\n\"]),d&&(l.frag=l.frag.replace(\"smoothstep\",\"smoothStep\"),s.frag=s.frag.replace(\"smoothstep\",\"smoothStep\")),this.drawCircle=t(l)}y.defaults={color:\"black\",borderColor:\"transparent\",borderSize:0,size:12,opacity:1,marker:void 0,viewport:null,range:null,pixelSize:null,count:0,offset:0,bounds:null,positions:[],snap:1e4},y.prototype.render=function(){return arguments.length&&this.update.apply(this,arguments),this.draw(),this},y.prototype.draw=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];var i=this.groups;if(1===r.length&&Array.isArray(r[0])&&(null===r[0][0]||Array.isArray(r[0][0]))&&(r=r[0]),this.regl._refresh(),r.length)for(var a=0;a<r.length;a++)this.drawItem(a,r[a]);else i.forEach(function(e,r){t.drawItem(r)});return this},y.prototype.drawItem=function(t,e){var r=this.groups,n=r[t];if(\"number\"==typeof e&&(t=e,n=r[e],e=null),n&&n.count&&n.opacity){n.activation[0]&&this.drawCircle(this.getMarkerDrawOptions(0,n,e));for(var a=[],o=1;o<n.activation.length;o++)n.activation[o]&&(!0===n.activation[o]||n.activation[o].data.length)&&a.push.apply(a,i(this.getMarkerDrawOptions(o,n,e)));a.length&&this.drawMarker(a)}},y.prototype.getMarkerDrawOptions=function(t,e,r){var i=e.range,a=e.tree,o=e.viewport,s=e.activation,l=e.selectionBuffer,u=e.count;this.regl;if(!a)return r?[c({},e,{markerTexture:this.markerTextures[t],activation:s[t],count:r.length,elements:r,offset:0})]:[c({},e,{markerTexture:this.markerTextures[t],activation:s[t],offset:0})];var f=[],h=a.range(i,{lod:!0,px:[(i[2]-i[0])/o.width,(i[3]-i[1])/o.height]});if(r){for(var p=s[t].data,d=new Uint8Array(u),g=0;g<r.length;g++){var v=r[g];d[v]=p?p[v]:1}l.subdata(d)}for(var m=h.length;m--;){var y=n(h[m],2),x=y[0],b=y[1];f.push(c({},e,{markerTexture:this.markerTextures[t],activation:r?l:s[t],offset:x,count:b-x}))}return f},y.prototype.update=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];if(r.length){1===r.length&&Array.isArray(r[0])&&(r=r[0]);var i=this.groups,a=this.gl,s=this.regl,u=this.maxSize,d=this.maxColors,m=this.palette;this.groups=i=r.map(function(e,r){var n=i[r];if(void 0===e)return n;null===e?e={positions:null}:\"function\"==typeof e?e={ondraw:e}:\"number\"==typeof e[0]&&(e={positions:e}),null===(e=f(e,{positions:\"positions data points\",snap:\"snap cluster lod tree\",size:\"sizes size radius\",borderSize:\"borderSizes borderSize border-size bordersize borderWidth borderWidths border-width borderwidth stroke-width strokeWidth strokewidth outline\",color:\"colors color fill fill-color fillColor\",borderColor:\"borderColors borderColor stroke stroke-color strokeColor\",marker:\"markers marker shape\",range:\"range dataBox databox\",viewport:\"viewport viewPort viewBox viewbox\",opacity:\"opacity alpha transparency\",bounds:\"bound bounds boundaries limits\",tooManyColors:\"tooManyColors palette paletteMode optimizePalette enablePalette\"})).positions&&(e.positions=[]),null!=e.tooManyColors&&(t.tooManyColors=e.tooManyColors),n||(i[r]=n={id:r,scale:null,translate:null,scaleFract:null,translateFract:null,activation:[],selectionBuffer:s.buffer({data:new Uint8Array(0),usage:\"stream\",type:\"uint8\"}),sizeBuffer:s.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"uint8\"}),colorBuffer:s.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"uint8\"}),positionBuffer:s.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"float\"}),positionFractBuffer:s.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"float\"})},e=c({},y.defaults,e)),!e.positions||\"marker\"in e||(e.marker=n.marker,delete n.marker),!e.marker||\"positions\"in e||(e.positions=n.positions,delete n.positions);var x=0,b=0;if(h(n,e,[{snap:!0,size:function(t,e){return null==t&&(t=y.defaults.size),x+=t&&t.length?1:0,t},borderSize:function(t,e){return null==t&&(t=y.defaults.borderSize),x+=t&&t.length?1:0,t},opacity:parseFloat,color:function(e,r){return null==e&&(e=y.defaults.color),e=t.updateColor(e),b++,e},borderColor:function(e,r){return null==e&&(e=y.defaults.borderColor),e=t.updateColor(e),b++,e},bounds:function(t,e,r){return\"range\"in r||(r.range=null),t},positions:function(t,e,r){var n=e.snap,i=e.positionBuffer,a=e.positionFractBuffer,c=e.selectionBuffer;if(t.x||t.y)return t.x.length?e.xAttr={buffer:s.buffer(t.x),offset:0,stride:4,count:t.x.length}:e.xAttr={buffer:t.x.buffer,offset:4*t.x.offset||0,stride:4*(t.x.stride||1),count:t.x.count},t.y.length?e.yAttr={buffer:s.buffer(t.y),offset:0,stride:4,count:t.y.length}:e.yAttr={buffer:t.y.buffer,offset:4*t.y.offset||0,stride:4*(t.y.stride||1),count:t.y.count},e.count=Math.max(e.xAttr.count,e.yAttr.count),t;t=p(t,\"float64\");var u=e.count=Math.floor(t.length/2),f=e.bounds=u?o(t,2):null;if(r.range||e.range||(delete e.range,r.range=f),r.marker||e.marker||(delete e.marker,r.marker=null),n&&(!0===n||u>n)?e.tree=l(t,{bounds:f}):n&&n.length&&(e.tree=n),e.tree){var h={primitive:\"points\",usage:\"static\",data:e.tree,type:\"uint32\"};e.elements?e.elements(h):e.elements=s.elements(h)}return i({data:g.float(t),usage:\"dynamic\"}),a({data:g.fract(t),usage:\"dynamic\"}),c({data:new Uint8Array(u),type:\"uint8\",usage:\"stream\"}),t}},{marker:function(e,r,n){var i=r.activation;if(i.forEach(function(t){return t&&t.destroy&&t.destroy()}),i.length=0,e&&\"number\"!=typeof e[0]){for(var a=[],o=0,l=Math.min(e.length,r.count);o<l;o++){var c=t.addMarker(e[o]);a[c]||(a[c]=new Uint8Array(r.count)),a[c][o]=1}for(var u=0;u<a.length;u++)if(a[u]){var f={data:a[u],type:\"uint8\",usage:\"static\"};i[u]?i[u](f):i[u]=s.buffer(f),i[u].data=a[u]}}else{i[t.addMarker(e)]=!0}return e},range:function(t,e,r){var n=e.bounds;if(n)return t||(t=n),e.scale=[1/(t[2]-t[0]),1/(t[3]-t[1])],e.translate=[-t[0],-t[1]],e.scaleFract=g.fract(e.scale),e.translateFract=g.fract(e.translate),t},viewport:function(t){return v(t||[a.drawingBufferWidth,a.drawingBufferHeight])}}]),x){var _=n,w=_.count,k=_.size,T=_.borderSize,A=_.sizeBuffer,M=new Uint8Array(2*w);if(k.length||T.length)for(var S=0;S<w;S++)M[2*S]=Math.round(255*(null==k[S]?k:k[S])/u),M[2*S+1]=Math.round(255*(null==T[S]?T:T[S])/u);A({data:M,usage:\"dynamic\"})}if(b){var E,C=n,L=C.count,z=C.color,O=C.borderColor,I=C.colorBuffer;if(t.tooManyColors){if(z.length||O.length){E=new Uint8Array(8*L);for(var D=0;D<L;D++){var P=z[D];E[8*D]=m[4*P],E[8*D+1]=m[4*P+1],E[8*D+2]=m[4*P+2],E[8*D+3]=m[4*P+3];var R=O[D];E[8*D+4]=m[4*R],E[8*D+5]=m[4*R+1],E[8*D+6]=m[4*R+2],E[8*D+7]=m[4*R+3]}}}else if(z.length||O.length){E=new Uint8Array(4*L+2);for(var F=0;F<L;F++)null!=z[F]&&(E[4*F]=z[F]%d,E[4*F+1]=Math.floor(z[F]/d)),null!=O[F]&&(E[4*F+2]=O[F]%d,E[4*F+3]=Math.floor(O[F]/d))}I({data:E||new Uint8Array(0),type:\"uint8\",usage:\"dynamic\"})}return n})}},y.prototype.addMarker=function(t){var e,r=this.markerTextures,n=this.regl,i=this.markerCache,a=null==t?0:i.indexOf(t);if(a>=0)return a;if(t instanceof Uint8Array||t instanceof Uint8ClampedArray)e=t;else{e=new Uint8Array(t.length);for(var o=0,s=t.length;o<s;o++)e[o]=255*t[o]}var l=Math.floor(Math.sqrt(e.length));return a=r.length,i.push(t),r.push(n.texture({channels:1,data:e,radius:l,mag:\"linear\",min:\"linear\"})),a},y.prototype.updateColor=function(t){var e=this.paletteIds,r=this.palette,n=this.maxColors;Array.isArray(t)||(t=[t]);var i=[];if(\"number\"==typeof t[0]){var o=[];if(Array.isArray(t))for(var l=0;l<t.length;l+=4)o.push(t.slice(l,l+4));else for(var c=0;c<t.length;c+=4)o.push(t.subarray(c,c+4));t=o}for(var u=0;u<t.length;u++){var f=t[u];f=a(f,\"uint8\");var h=s(f,!1);if(null==e[h]){var p=r.length;e[h]=Math.floor(p/4),r[p]=f[0],r[p+1]=f[1],r[p+2]=f[2],r[p+3]=f[3]}i[u]=e[h]}return!this.tooManyColors&&r.length>4*n&&(this.tooManyColors=!0),this.updatePalette(r),1===i.length?i[0]:i},y.prototype.updatePalette=function(t){if(!this.tooManyColors){var e=this.maxColors,r=this.paletteTexture,n=Math.ceil(.25*t.length/e);if(n>1)for(var i=.25*(t=t.slice()).length%e;i<n*e;i++)t.push(0,0,0,0);r.height<n&&r.resize(e,n),r.subimage({width:Math.min(.25*t.length,e),height:n,data:t},0,0)}},y.prototype.destroy=function(){return this.groups.forEach(function(t){t.sizeBuffer.destroy(),t.positionBuffer.destroy(),t.positionFractBuffer.destroy(),t.colorBuffer.destroy(),t.activation.forEach(function(t){return t&&t.destroy&&t.destroy()}),t.selectionBuffer.destroy(),t.elements&&t.elements.destroy()}),this.groups.length=0,this.paletteTexture.destroy(),this.markerTextures.forEach(function(t){return t&&t.destroy&&t.destroy()}),this};var x=t(\"object-assign\");e.exports=function(t,e){var r=new m(t,e),n=r.render.bind(r);return x(n,{render:n,update:r.update.bind(r),draw:r.draw.bind(r),destroy:r.destroy.bind(r),regl:r.regl,gl:r.gl,canvas:r.gl.canvas,groups:r.groups,markers:r.markerCache,palette:r.palette}),n}},{\"array-bounds\":58,\"color-id\":111,\"color-normalize\":113,\"flatten-vertex-data\":226,glslify:404,\"is-iexplorer\":414,\"object-assign\":449,\"parse-rect\":454,\"pick-by-alias\":460,\"point-cluster\":464,\"to-float32\":525,\"update-diff\":536}],488:[function(t,e,r){\"use strict\";var n=t(\"regl-scatter2d\"),i=t(\"pick-by-alias\"),a=t(\"array-bounds\"),o=t(\"raf\"),s=t(\"array-range\"),l=t(\"parse-rect\"),c=t(\"flatten-vertex-data\");function u(t,e){if(!(this instanceof u))return new u(t,e);this.traces=[],this.passes={},this.regl=t,this.scatter=n(t),this.canvas=this.scatter.canvas}function f(t,e,r){return(null!=t.id?t.id:t)<<16|(255&e)<<8|255&r}function h(t,e,r){var n,i,a,o,s=t[e],l=t[r];return s.length>2?(s[0],s[2],n=s[1],i=s[3]):s.length?(n=s[0],i=s[1]):(s.x,n=s.y,s.x+s.width,i=s.y+s.height),l.length>2?(a=l[0],o=l[2],l[1],l[3]):l.length?(a=l[0],o=l[1]):(a=l.x,l.y,o=l.x+l.width,l.y+l.height),[a,n,o,i]}function p(t){if(\"number\"==typeof t)return[t,t,t,t];if(2===t.length)return[t[0],t[1],t[0],t[1]];var e=l(t);return[e.x,e.y,e.x+e.width,e.y+e.height]}e.exports=u,u.prototype.render=function(){for(var t,e=this,r=[],n=arguments.length;n--;)r[n]=arguments[n];return r.length&&(t=this).update.apply(t,r),this.regl.attributes.preserveDrawingBuffer?this.draw():(this.dirty?null==this.planned&&(this.planned=o(function(){e.draw(),e.dirty=!0,e.planned=null})):(this.draw(),this.dirty=!0,o(function(){e.dirty=!1})),this)},u.prototype.update=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=0;n<e.length;n++)this.updateItem(n,e[n]);this.traces=this.traces.filter(Boolean);for(var i=[],a=0,o=0;o<this.traces.length;o++){for(var s=this.traces[o],l=this.traces[o].passes,c=0;c<l.length;c++)i.push(this.passes[l[c]]);s.passOffset=a,a+=s.passes.length}return(t=this.scatter).update.apply(t,i),this}},u.prototype.updateItem=function(t,e){var r=this.regl;if(null===e)return this.traces[t]=null,this;if(!e)return this;var n,o=i(e,{data:\"data items columns rows values dimensions samples x\",snap:\"snap cluster\",size:\"sizes size radius\",color:\"colors color fill fill-color fillColor\",opacity:\"opacity alpha transparency 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return(t=e.year()+(e.year()<0?1:0))%4==3||t%4==-1},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear),13},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(13===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return(t=i.year())<0&&t++,i.day()+30*(i.month()-1)+365*(t-1)+Math.floor(t/4)+this.jdEpoch-1},fromJD:function(t){var e=Math.floor(t)+.5-this.jdEpoch,r=Math.floor((e-Math.floor((e+366)/1461))/365)+1;r<=0&&r--,e=Math.floor(t)+.5-this.newDate(r,1,1).toJD();var n=Math.floor(e/30)+1,i=e-30*(n-1)+1;return 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this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),13},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),400},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/8)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]},daysInWeek:function(){return 8},dayOfWeek:function(t,e,r){return(this._validate(t,e,r,n.local.invalidDate).day()+1)%8},weekDay:function(t,e,r){var n=this.dayOfWeek(t,e,r);return n>=2&&n<=6},extraInfo:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return{century:o[Math.floor((i.year()-1)/100)+1]||\"\"}},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year()+(i.year()<0?1:0),e=i.month(),(r=i.day())+(e>1?16:0)+(e>2?32*(e-2):0)+400*(t-1)+this.jdEpoch-1},fromJD:function(t){t=Math.floor(t+.5)-Math.floor(this.jdEpoch)-1;var e=Math.floor(t/400)+1;t-=400*(e-1),t+=t>15?16:0;var r=Math.floor(t/32)+1,n=t-32*(r-1)+1;return this.newDate(e<=0?e-1:e,r,n)}});var o={20:\"Fruitbat\",21:\"Anchovy\"};n.calendars.discworld=a},{\"../main\":558,\"object-assign\":449}],547:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return this._leapYear(e.year())},_leapYear:function(t){return o(7*(t=t<0?t+1:t)+1,19)<7},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),this._leapYear(t.year?t.year():t)?13:12},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){return t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year(),this.toJD(-1===t?1:t+1,7,1)-this.toJD(t,7,1)},daysInMonth:function(t,e){return t.year&&(e=t.month(),t=t.year()),this._validate(t,e,this.minDay,n.local.invalidMonth),12===e&&this.leapYear(t)?30:8===e&&5===o(this.daysInYear(t),10)?30:9===e&&3===o(this.daysInYear(t),10)?29:this.daysPerMonth[e-1]},weekDay:function(t,e,r){return 6!==this.dayOfWeek(t,e,r)},extraInfo:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return{yearType:(this.leapYear(i)?\"embolismic\":\"common\")+\" \"+[\"deficient\",\"regular\",\"complete\"][this.daysInYear(i)%10-3]}},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t<=0?t+1:t,o=this.jdEpoch+this._delay1(a)+this._delay2(a)+r+1;if(e<7){for(var s=7;s<=this.monthsInYear(t);s++)o+=this.daysInMonth(t,s);for(s=1;s<e;s++)o+=this.daysInMonth(t,s)}else for(s=7;s<e;s++)o+=this.daysInMonth(t,s);return o},_delay1:function(t){var e=Math.floor((235*t-234)/19),r=12084+13753*e,n=29*e+Math.floor(r/25920);return o(3*(n+1),7)<3&&n++,n},_delay2:function(t){var e=this._delay1(t-1),r=this._delay1(t);return this._delay1(t+1)-r==356?2:r-e==382?1:0},fromJD:function(t){t=Math.floor(t)+.5;for(var e=Math.floor(98496*(t-this.jdEpoch)/35975351)-1;t>=this.toJD(-1===e?1:e+1,7,1);)e++;for(var r=t<this.toJD(e,1,1)?7:1;t>this.toJD(e,r,this.daysInMonth(e,r));)r++;var n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),n.calendars.hebrew=a},{\"../main\":558,\"object-assign\":449}],549:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Islamic\",jdEpoch:1948439.5,daysPerMonth:[30,29,30,29,30,29,30,29,30,29,30,29],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Islamic\",epochs:[\"BH\",\"AH\"],monthNames:[\"Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' al-thani\",\"Jumada al-awwal\",\"Jumada al-thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-ahad\",\"Yawm al-ithnayn\",\"Yawm ath-thulaathaa'\",\"Yawm al-arbi'aa'\",\"Yawm al-kham\\u012bs\",\"Yawm al-jum'a\",\"Yawm as-sabt\"],dayNamesShort:[\"Aha\",\"Ith\",\"Thu\",\"Arb\",\"Kha\",\"Jum\",\"Sab\"],dayNamesMin:[\"Ah\",\"It\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!1}},leapYear:function(t){return(11*this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year()+14)%30<11},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){return this.leapYear(t)?355:354},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year(),e=i.month(),t=t<=0?t+1:t,(r=i.day())+Math.ceil(29.5*(e-1))+354*(t-1)+Math.floor((3+11*t)/30)+this.jdEpoch-1},fromJD:function(t){t=Math.floor(t)+.5;var e=Math.floor((30*(t-this.jdEpoch)+10646)/10631);e=e<=0?e-1:e;var r=Math.min(12,Math.ceil((t-29-this.toJD(e,1,1))/29.5)+1),n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),n.calendars.islamic=a},{\"../main\":558,\"object-assign\":449}],550:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Julian\",jdEpoch:1721423.5,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Julian\",epochs:[\"BC\",\"AD\"],monthNames:[\"January\",\"February\",\"March\",\"April\",\"May\",\"June\",\"July\",\"August\",\"September\",\"October\",\"November\",\"December\"],monthNamesShort:[\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"],dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"mm/dd/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return(t=e.year()<0?e.year()+1:e.year())%4==0},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(4-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year(),e=i.month(),r=i.day(),t<0&&t++,e<=2&&(t--,e+=12),Math.floor(365.25*(t+4716))+Math.floor(30.6001*(e+1))+r-1524.5},fromJD:function(t){var e=Math.floor(t+.5)+1524,r=Math.floor((e-122.1)/365.25),n=Math.floor(365.25*r),i=Math.floor((e-n)/30.6001),a=i-Math.floor(i<14?1:13),o=r-Math.floor(a>2?4716:4715),s=e-n-Math.floor(30.6001*i);return o<=0&&o--,this.newDate(o,a,s)}}),n.calendars.julian=a},{\"../main\":558,\"object-assign\":449}],551:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}function o(t,e){return t-e*Math.floor(t/e)}function s(t,e){return o(t-1,e)+1}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Mayan\",jdEpoch:584282.5,hasYearZero:!0,minMonth:0,firstMonth:0,minDay:0,regionalOptions:{\"\":{name:\"Mayan\",epochs:[\"\",\"\"],monthNames:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\"],monthNamesShort:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\"],dayNames:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],dayNamesShort:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],dayNamesMin:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],digits:null,dateFormat:\"YYYY.m.d\",firstDay:0,isRTL:!1,haabMonths:[\"Pop\",\"Uo\",\"Zip\",\"Zotz\",\"Tzec\",\"Xul\",\"Yaxkin\",\"Mol\",\"Chen\",\"Yax\",\"Zac\",\"Ceh\",\"Mac\",\"Kankin\",\"Muan\",\"Pax\",\"Kayab\",\"Cumku\",\"Uayeb\"],tzolkinMonths:[\"Imix\",\"Ik\",\"Akbal\",\"Kan\",\"Chicchan\",\"Cimi\",\"Manik\",\"Lamat\",\"Muluc\",\"Oc\",\"Chuen\",\"Eb\",\"Ben\",\"Ix\",\"Men\",\"Cib\",\"Caban\",\"Etznab\",\"Cauac\",\"Ahau\"]}},leapYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),!1},formatYear:function(t){t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year();var e=Math.floor(t/400);return t%=400,t+=t<0?400:0,e+\".\"+Math.floor(t/20)+\".\"+t%20},forYear:function(t){if((t=t.split(\".\")).length<3)throw\"Invalid Mayan year\";for(var e=0,r=0;r<t.length;r++){var n=parseInt(t[r],10);if(Math.abs(n)>19||r>0&&n<0)throw\"Invalid Mayan year\";e=20*e+n}return e},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),18},weekOfYear:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),0},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),360},daysInMonth:function(t,e){return this._validate(t,e,this.minDay,n.local.invalidMonth),20},daysInWeek:function(){return 5},dayOfWeek:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate).day()},weekDay:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),!0},extraInfo:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate).toJD(),a=this._toHaab(i),o=this._toTzolkin(i);return{haabMonthName:this.local.haabMonths[a[0]-1],haabMonth:a[0],haabDay:a[1],tzolkinDayName:this.local.tzolkinMonths[o[0]-1],tzolkinDay:o[0],tzolkinTrecena:o[1]}},_toHaab:function(t){var e=o((t-=this.jdEpoch)+8+340,365);return[Math.floor(e/20)+1,o(e,20)]},_toTzolkin:function(t){return[s((t-=this.jdEpoch)+20,20),s(t+4,13)]},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return i.day()+20*i.month()+360*i.year()+this.jdEpoch},fromJD:function(t){t=Math.floor(t)+.5-this.jdEpoch;var e=Math.floor(t/360);t%=360,t+=t<0?360:0;var r=Math.floor(t/20),n=t%20;return this.newDate(e,r,n)}}),n.calendars.mayan=a},{\"../main\":558,\"object-assign\":449}],552:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar;var o=n.instance(\"gregorian\");i(a.prototype,{name:\"Nanakshahi\",jdEpoch:2257673.5,daysPerMonth:[31,31,31,31,31,30,30,30,30,30,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Nanakshahi\",epochs:[\"BN\",\"AN\"],monthNames:[\"Chet\",\"Vaisakh\",\"Jeth\",\"Harh\",\"Sawan\",\"Bhadon\",\"Assu\",\"Katak\",\"Maghar\",\"Poh\",\"Magh\",\"Phagun\"],monthNamesShort:[\"Che\",\"Vai\",\"Jet\",\"Har\",\"Saw\",\"Bha\",\"Ass\",\"Kat\",\"Mgr\",\"Poh\",\"Mgh\",\"Pha\"],dayNames:[\"Somvaar\",\"Mangalvar\",\"Budhvaar\",\"Veervaar\",\"Shukarvaar\",\"Sanicharvaar\",\"Etvaar\"],dayNamesShort:[\"Som\",\"Mangal\",\"Budh\",\"Veer\",\"Shukar\",\"Sanichar\",\"Et\"],dayNamesMin:[\"So\",\"Ma\",\"Bu\",\"Ve\",\"Sh\",\"Sa\",\"Et\"],digits:null,dateFormat:\"dd-mm-yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear);return o.leapYear(e.year()+(e.year()<1?1:0)+1469)},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(1-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidMonth);(t=i.year())<0&&t++;for(var a=i.day(),s=1;s<i.month();s++)a+=this.daysPerMonth[s-1];return a+o.toJD(t+1468,3,13)},fromJD:function(t){t=Math.floor(t+.5);for(var e=Math.floor((t-(this.jdEpoch-1))/366);t>=this.toJD(e+1,1,1);)e++;for(var r=t-Math.floor(this.toJD(e,1,1)+.5)+1,n=1;r>this.daysInMonth(e,n);)r-=this.daysInMonth(e,n),n++;return this.newDate(e,n,r)}}),n.calendars.nanakshahi=a},{\"../main\":558,\"object-assign\":449}],553:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Nepali\",jdEpoch:1700709.5,daysPerMonth:[31,31,32,32,31,30,30,29,30,29,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,daysPerYear:365,regionalOptions:{\"\":{name:\"Nepali\",epochs:[\"BBS\",\"ABS\"],monthNames:[\"Baisakh\",\"Jestha\",\"Ashadh\",\"Shrawan\",\"Bhadra\",\"Ashwin\",\"Kartik\",\"Mangsir\",\"Paush\",\"Mangh\",\"Falgun\",\"Chaitra\"],monthNamesShort:[\"Bai\",\"Je\",\"As\",\"Shra\",\"Bha\",\"Ash\",\"Kar\",\"Mang\",\"Pau\",\"Ma\",\"Fal\",\"Chai\"],dayNames:[\"Aaitabaar\",\"Sombaar\",\"Manglbaar\",\"Budhabaar\",\"Bihibaar\",\"Shukrabaar\",\"Shanibaar\"],dayNamesShort:[\"Aaita\",\"Som\",\"Mangl\",\"Budha\",\"Bihi\",\"Shukra\",\"Shani\"],dayNamesMin:[\"Aai\",\"So\",\"Man\",\"Bu\",\"Bi\",\"Shu\",\"Sha\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:1,isRTL:!1}},leapYear:function(t){return this.daysInYear(t)!==this.daysPerYear},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){if(t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year(),\"undefined\"==typeof this.NEPALI_CALENDAR_DATA[t])return this.daysPerYear;for(var e=0,r=this.minMonth;r<=12;r++)e+=this.NEPALI_CALENDAR_DATA[t][r];return e},daysInMonth:function(t,e){return t.year&&(e=t.month(),t=t.year()),this._validate(t,e,this.minDay,n.local.invalidMonth),\"undefined\"==typeof this.NEPALI_CALENDAR_DATA[t]?this.daysPerMonth[e-1]:this.NEPALI_CALENDAR_DATA[t][e]},weekDay:function(t,e,r){return 6!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=n.instance(),o=0,s=e,l=t;this._createMissingCalendarData(t);var c=t-(s>9||9===s&&r>=this.NEPALI_CALENDAR_DATA[l][0]?56:57);for(9!==e&&(o=r,s--);9!==s;)s<=0&&(s=12,l--),o+=this.NEPALI_CALENDAR_DATA[l][s],s--;return 9===e?(o+=r-this.NEPALI_CALENDAR_DATA[l][0])<0&&(o+=a.daysInYear(c)):o+=this.NEPALI_CALENDAR_DATA[l][9]-this.NEPALI_CALENDAR_DATA[l][0],a.newDate(c,1,1).add(o,\"d\").toJD()},fromJD:function(t){var e=n.instance().fromJD(t),r=e.year(),i=e.dayOfYear(),a=r+56;this._createMissingCalendarData(a);for(var o=9,s=this.NEPALI_CALENDAR_DATA[a][0],l=this.NEPALI_CALENDAR_DATA[a][o]-s+1;i>l;)++o>12&&(o=1,a++),l+=this.NEPALI_CALENDAR_DATA[a][o];var c=this.NEPALI_CALENDAR_DATA[a][o]-(l-i);return this.newDate(a,o,c)},_createMissingCalendarData:function(t){var e=this.daysPerMonth.slice(0);e.unshift(17);for(var r=t-1;r<t+2;r++)\"undefined\"==typeof 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 682*((e.year()-(e.year()>0?474:473))%2820+474+38)%2816<682},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-(n.dayOfWeek()+1)%7,\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t-(t>=0?474:473),s=474+o(a,2820);return r+(e<=7?31*(e-1):30*(e-1)+6)+Math.floor((682*s-110)/2816)+365*(s-1)+1029983*Math.floor(a/2820)+this.jdEpoch-1},fromJD:function(t){var e=(t=Math.floor(t)+.5)-this.toJD(475,1,1),r=Math.floor(e/1029983),n=o(e,1029983),i=2820;if(1029982!==n){var a=Math.floor(n/366),s=o(n,366);i=Math.floor((2134*a+2816*s+2815)/1028522)+a+1}var l=i+2820*r+474;l=l<=0?l-1:l;var 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i=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(i.year());return a.weekOfYear(t,i.month(),i.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=this._t2gYear(i.year());return a.toJD(t,i.month(),i.day())},fromJD:function(t){var e=a.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)},_g2tYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)}}),n.calendars.taiwan=o},{\"../main\":558,\"object-assign\":449}],556:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\"),a=n.instance();function 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n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"UmmAlQura\",hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Umm al-Qura\",epochs:[\"BH\",\"AH\"],monthNames:[\"Al-Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' Al-Thani\",\"Jumada Al-Awwal\",\"Jumada Al-Thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-Ahad\",\"Yawm al-Ithnain\",\"Yawm al-Thal\\u0101th\\u0101\\u2019\",\"Yawm al-Arba\\u2018\\u0101\\u2019\",\"Yawm al-Kham\\u012bs\",\"Yawm al-Jum\\u2018a\",\"Yawm al-Sabt\"],dayNamesMin:[\"Ah\",\"Ith\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!0}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 355===this.daysInYear(e.year())},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){for(var e=0,r=1;r<=12;r++)e+=this.daysInMonth(t,r);return e},daysInMonth:function(t,e){for(var r=this._validate(t,e,this.minDay,n.local.invalidMonth).toJD()-24e5+.5,i=0,a=0;a<o.length;a++){if(o[a]>r)return o[i]-o[i-1];i++}return 30},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate),a=12*(i.year()-1)+i.month()-15292;return i.day()+o[a-1]-1+24e5-.5},fromJD:function(t){for(var e=t-24e5+.5,r=0,n=0;n<o.length&&!(o[n]>e);n++)r++;var i=r+15292,a=Math.floor((i-1)/12),s=a+1,l=i-12*a,c=e-o[r-1]+1;return this.newDate(s,l,c)},isValid:function(t,e,r){var i=n.baseCalendar.prototype.isValid.apply(this,arguments);return i&&(i=(t=null!=t.year?t.year:t)>=1276&&t<=1500),i},_validate:function(t,e,r,i){var a=n.baseCalendar.prototype._validate.apply(this,arguments);if(a.year<1276||a.year>1500)throw i.replace(/\\{0\\}/,this.local.name);return a}}),n.calendars.ummalqura=a;var 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n=t(\"object-assign\");function i(){this.regionalOptions=[],this.regionalOptions[\"\"]={invalidCalendar:\"Calendar {0} not found\",invalidDate:\"Invalid {0} date\",invalidMonth:\"Invalid {0} month\",invalidYear:\"Invalid {0} year\",differentCalendars:\"Cannot mix {0} and {1} dates\"},this.local=this.regionalOptions[\"\"],this.calendars={},this._localCals={}}function a(t,e,r,n){if(this._calendar=t,this._year=e,this._month=r,this._day=n,0===this._calendar._validateLevel&&!this._calendar.isValid(this._year,this._month,this._day))throw(c.local.invalidDate||c.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name)}function o(t,e){return\"000000\".substring(0,e-(t=\"\"+t).length)+t}function s(){this.shortYearCutoff=\"+10\"}function l(t){this.local=this.regionalOptions[t]||this.regionalOptions[\"\"]}n(i.prototype,{instance:function(t,e){t=(t||\"gregorian\").toLowerCase(),e=e||\"\";var r=this._localCals[t+\"-\"+e];if(!r&&this.calendars[t]&&(r=new this.calendars[t](e),this._localCals[t+\"-\"+e]=r),!r)throw(this.local.invalidCalendar||this.regionalOptions[\"\"].invalidCalendar).replace(/\\{0\\}/,t);return r},newDate:function(t,e,r,n,i){return(n=(null!=t&&t.year?t.calendar():\"string\"==typeof n?this.instance(n,i):n)||this.instance()).newDate(t,e,r)},substituteDigits:function(t){return function(e){return(e+\"\").replace(/[0-9]/g,function(e){return t[e]})}},substituteChineseDigits:function(t,e){return function(r){for(var n=\"\",i=0;r>0;){var a=r%10;n=(0===a?\"\":t[a]+e[i])+n,i++,r=Math.floor(r/10)}return 0===n.indexOf(t[1]+e[1])&&(n=n.substr(1)),n||t[0]}}}),n(a.prototype,{newDate:function(t,e,r){return this._calendar.newDate(null==t?this:t,e,r)},year:function(t){return 0===arguments.length?this._year:this.set(t,\"y\")},month:function(t){return 0===arguments.length?this._month:this.set(t,\"m\")},day:function(t){return 0===arguments.length?this._day:this.set(t,\"d\")},date:function(t,e,r){if(!this._calendar.isValid(t,e,r))throw(c.local.invalidDate||c.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name);return this._year=t,this._month=e,this._day=r,this},leapYear:function(){return this._calendar.leapYear(this)},epoch:function(){return this._calendar.epoch(this)},formatYear:function(){return this._calendar.formatYear(this)},monthOfYear:function(){return this._calendar.monthOfYear(this)},weekOfYear:function(){return this._calendar.weekOfYear(this)},daysInYear:function(){return this._calendar.daysInYear(this)},dayOfYear:function(){return this._calendar.dayOfYear(this)},daysInMonth:function(){return this._calendar.daysInMonth(this)},dayOfWeek:function(){return this._calendar.dayOfWeek(this)},weekDay:function(){return this._calendar.weekDay(this)},extraInfo:function(){return this._calendar.extraInfo(this)},add:function(t,e){return this._calendar.add(this,t,e)},set:function(t,e){return this._calendar.set(this,t,e)},compareTo:function(t){if(this._calendar.name!==t._calendar.name)throw(c.local.differentCalendars||c.regionalOptions[\"\"].differentCalendars).replace(/\\{0\\}/,this._calendar.local.name).replace(/\\{1\\}/,t._calendar.local.name);var e=this._year!==t._year?this._year-t._year:this._month!==t._month?this.monthOfYear()-t.monthOfYear():this._day-t._day;return 0===e?0:e<0?-1:1},calendar:function(){return this._calendar},toJD:function(){return this._calendar.toJD(this)},fromJD:function(t){return this._calendar.fromJD(t)},toJSDate:function(){return this._calendar.toJSDate(this)},fromJSDate:function(t){return this._calendar.fromJSDate(t)},toString:function(){return(this.year()<0?\"-\":\"\")+o(Math.abs(this.year()),4)+\"-\"+o(this.month(),2)+\"-\"+o(this.day(),2)}}),n(s.prototype,{_validateLevel:0,newDate:function(t,e,r){return null==t?this.today():(t.year&&(this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),r=t.day(),e=t.month(),t=t.year()),new a(this,t,e,r))},today:function(){return this.fromJSDate(new Date)},epoch:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear).year()<0?this.local.epochs[0]:this.local.epochs[1]},formatYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear);return(e.year()<0?\"-\":\"\")+o(Math.abs(e.year()),4)},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear),12},monthOfYear:function(t,e){var r=this._validate(t,e,this.minDay,c.local.invalidMonth||c.regionalOptions[\"\"].invalidMonth);return(r.month()+this.monthsInYear(r)-this.firstMonth)%this.monthsInYear(r)+this.minMonth},fromMonthOfYear:function(t,e){var r=(e+this.firstMonth-2*this.minMonth)%this.monthsInYear(t)+this.minMonth;return this._validate(t,r,this.minDay,c.local.invalidMonth||c.regionalOptions[\"\"].invalidMonth),r},daysInYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear);return this.leapYear(e)?366:365},dayOfYear:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);return n.toJD()-this.newDate(n.year(),this.fromMonthOfYear(n.year(),this.minMonth),this.minDay).toJD()+1},daysInWeek:function(){return 7},dayOfWeek:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);return(Math.floor(this.toJD(n))+2)%this.daysInWeek()},extraInfo:function(t,e,r){return this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),{}},add:function(t,e,r){return this._validate(t,this.minMonth,this.minDay,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),this._correctAdd(t,this._add(t,e,r),e,r)},_add:function(t,e,r){if(this._validateLevel++,\"d\"===r||\"w\"===r){var n=t.toJD()+e*(\"w\"===r?this.daysInWeek():1),i=t.calendar().fromJD(n);return this._validateLevel--,[i.year(),i.month(),i.day()]}try{var a=t.year()+(\"y\"===r?e:0),o=t.monthOfYear()+(\"m\"===r?e:0);i=t.day();\"y\"===r?(t.month()!==this.fromMonthOfYear(a,o)&&(o=this.newDate(a,t.month(),this.minDay).monthOfYear()),o=Math.min(o,this.monthsInYear(a)),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o)))):\"m\"===r&&(!function(t){for(;o<t.minMonth;)a--,o+=t.monthsInYear(a);for(var e=t.monthsInYear(a);o>e-1+t.minMonth;)a++,o-=e,e=t.monthsInYear(a)}(this),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o))));var s=[a,this.fromMonthOfYear(a,o),i];return this._validateLevel--,s}catch(t){throw 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f=d.width;a=\"M\"+(r.x-f)+\",\"+r.yh+\"h\"+2*f+\"m-\"+f+\",0V\"+r.ys,r.noYS||(a+=\"m-\"+f+\",0h\"+2*f),!o.size()?o=e.append(\"path\").style(\"vector-effect\",\"non-scaling-stroke\").classed(\"yerror\",!0):u&&(o=o.transition().duration(s.duration).ease(s.easing)),o.attr(\"d\",a)}else o.remove();var h=e.select(\"path.xerror\");if(p.visible&&i(r.y)&&i(r.xh)&&i(r.xs)){var v=(p.copy_ystyle?d:p).width;a=\"M\"+r.xh+\",\"+(r.y-v)+\"v\"+2*v+\"m0,-\"+v+\"H\"+r.xs,r.noXS||(a+=\"m0,-\"+v+\"v\"+2*v),!h.size()?h=e.append(\"path\").style(\"vector-effect\",\"non-scaling-stroke\").classed(\"xerror\",!0):u&&(h=h.transition().duration(s.duration).ease(s.easing)),h.attr(\"d\",a)}else h.remove()}})}})}},{\"../../traces/scatter/subtypes\":1098,\"../drawing\":601,d3:157,\"fast-isnumeric\":224}],609:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../color\");e.exports=function(t){t.each(function(t){var e=t[0].trace,r=e.error_y||{},a=e.error_x||{},o=n.select(this);o.selectAll(\"path.yerror\").style(\"stroke-width\",r.thickness+\"px\").call(i.stroke,r.color),a.copy_ystyle&&(a=r),o.selectAll(\"path.xerror\").style(\"stroke-width\",a.thickness+\"px\").call(i.stroke,a.color)})}},{\"../color\":580,d3:157}],610:[function(t,e,r){\"use strict\";var n=t(\"../../plots/font_attributes\"),i=t(\"./layout_attributes\").hoverlabel,a=t(\"../../lib/extend\").extendFlat;e.exports={hoverlabel:{bgcolor:a({},i.bgcolor,{arrayOk:!0}),bordercolor:a({},i.bordercolor,{arrayOk:!0}),font:n({arrayOk:!0,editType:\"none\"}),align:a({},i.align,{arrayOk:!0}),namelength:a({},i.namelength,{arrayOk:!0}),editType:\"none\"}}},{\"../../lib/extend\":693,\"../../plots/font_attributes\":777,\"./layout_attributes\":620}],611:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../registry\");function a(t,e,r,i){i=i||n.identity,Array.isArray(t)&&(e[0][r]=i(t))}e.exports=function(t){var 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r,n=null,i=1/0,a=0;a<t.length;a++)(r=t[a].spikeDistance)<i&&r<=e&&(n=t[a],i=r);return n}function vt(t){return t?{xa:t.xa,ya:t.ya,x:void 0!==t.xSpike?t.xSpike:(t.x0+t.x1)/2,y:void 0!==t.ySpike?t.ySpike:(t.y0+t.y1)/2,distance:t.distance,spikeDistance:t.spikeDistance,curveNumber:t.trace.index,color:t.color,pointNumber:t.index}:null}var mt={fullLayout:u,container:u._hoverlayer,outerContainer:u._paperdiv,event:e},yt=t._spikepoints,xt={vLinePoint:K.vLinePoint,hLinePoint:K.hLinePoint};if(t._spikepoints=xt,y&&0!==Z&&0!==$.length){var bt=$.filter(function(t){return t.ya.showspikes}),_t=gt(bt,Z);K.hLinePoint=vt(_t);var wt=$.filter(function(t){return t.xa.showspikes}),kt=gt(wt,Z);K.vLinePoint=vt(kt)}if(0===$.length){var Tt=h.unhoverRaw(t,e);return!y||null===K.hLinePoint&&null===K.vLinePoint||C(yt)&&E(K,mt),Tt}y&&C(yt)&&E(K,mt);$.sort(function(t,e){return t.distance-e.distance});var At=t._hoverdata,Mt=[];for(F=0;F<$.length;F++){var 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i=t.map(function(t){return{color:t.color||f.defaultLine,x0:t.x0||t.x||0,x1:t.x1||t.x||0,y0:t.y0||t.y||0,y1:t.y1||t.y||0,xLabel:t.xLabel,yLabel:t.yLabel,zLabel:t.zLabel,text:t.text,name:t.name,idealAlign:t.idealAlign,borderColor:t.borderColor,fontFamily:t.fontFamily,fontSize:t.fontSize,fontColor:t.fontColor,nameLength:t.nameLength,textAlign:t.textAlign,trace:t.trace||{index:0,hoverinfo:\"\"},xa:{_offset:0},ya:{_offset:0},index:0,hovertemplate:t.hovertemplate||!1,eventData:t.eventData||!1,hovertemplateLabels:t.hovertemplateLabels||!1}}),a=n.select(e.container),o=e.outerContainer?n.select(e.outerContainer):a,s={hovermode:\"closest\",rotateLabels:!1,bgColor:e.bgColor||f.background,container:a,outerContainer:o},l=A(i,s,e.gd),c=0,u=0;return l.sort(function(t,e){return t.y0-e.y0}).each(function(t,r){var n=t.y0-t.by/2;t.offset=n-5<c?c-n+5:0,c=n+t.by+t.offset,r===e.anchorIndex&&(u=t.offset)}).each(function(t){t.offset-=u}),M(l,s.rotateLabels),r?l:l.node()};var 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n=t(\"./constants\"),i=t(\"../../plots/font_attributes\")({editType:\"none\"});i.family.dflt=n.HOVERFONT,i.size.dflt=n.HOVERFONTSIZE,e.exports={clickmode:{valType:\"flaglist\",flags:[\"event\",\"select\"],dflt:\"event\",editType:\"plot\",extras:[\"none\"]},dragmode:{valType:\"enumerated\",values:[\"zoom\",\"pan\",\"select\",\"lasso\",\"orbit\",\"turntable\",!1],dflt:\"zoom\",editType:\"modebar\"},hovermode:{valType:\"enumerated\",values:[\"x\",\"y\",\"closest\",!1],editType:\"modebar\"},hoverdistance:{valType:\"integer\",min:-1,dflt:20,editType:\"none\"},spikedistance:{valType:\"integer\",min:-1,dflt:20,editType:\"none\"},hoverlabel:{bgcolor:{valType:\"color\",editType:\"none\"},bordercolor:{valType:\"color\",editType:\"none\"},font:i,align:{valType:\"enumerated\",values:[\"left\",\"right\",\"auto\"],dflt:\"auto\",editType:\"none\"},namelength:{valType:\"integer\",min:-1,dflt:15,editType:\"none\"},editType:\"none\"},selectdirection:{valType:\"enumerated\",values:[\"h\",\"v\",\"d\",\"any\"],dflt:\"any\",editType:\"none\"}}},{\"../../plots/font_attributes\":777,\"./constants\":613}],621:[function(t,e,r){\"use 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e._shapeUpperLayer.selectAll(\"path\").remove(),e._shapeLowerLayer.selectAll(\"path\").remove(),e._plots){var n=e._plots[r].shapelayer;n&&n.selectAll(\"path\").remove()}for(var i=0;i<e.shapes.length;i++)e.shapes[i].visible&&p(t,i)},drawOne:p}},{\"../../lib\":703,\"../../lib/setcursor\":723,\"../../plot_api/plot_template\":741,\"../../plots/cartesian/axes\":751,\"../../registry\":831,\"../color\":580,\"../dragelement\":598,\"../drawing\":601,\"./constants\":658,\"./helpers\":661}],661:[function(t,e,r){\"use strict\";var n=t(\"./constants\"),i=t(\"../../lib\");r.rangeToShapePosition=function(t){return\"log\"===t.type?t.r2d:function(t){return t}},r.shapePositionToRange=function(t){return\"log\"===t.type?t.d2r:function(t){return t}},r.decodeDate=function(t){return function(e){return e.replace&&(e=e.replace(\"_\",\" \")),t(e)}},r.encodeDate=function(t){return function(e){return t(e).replace(\" \",\"_\")}},r.extractPathCoords=function(t,e){var r=[];return t.match(n.segmentRE).forEach(function(t){var a=e[t.charAt(0)].drawn;if(void 0!==a){var o=t.substr(1).match(n.paramRE);!o||o.length<a||r.push(i.cleanNumber(o[a]))}}),r},r.getDataToPixel=function(t,e,n){var i,a=t._fullLayout._size;if(e){var o=r.shapePositionToRange(e);i=function(t){return e._offset+e.r2p(o(t,!0))},\"date\"===e.type&&(i=r.decodeDate(i))}else i=n?function(t){return a.t+a.h*(1-t)}:function(t){return a.l+a.w*t};return i},r.getPixelToData=function(t,e,n){var i,a=t._fullLayout._size;if(e){var o=r.rangeToShapePosition(e);i=function(t){return o(e.p2r(t-e._offset))}}else i=n?function(t){return 1-(t-a.t)/a.h}:function(t){return(t-a.l)/a.w};return i},r.roundPositionForSharpStrokeRendering=function(t,e){var r=1===Math.round(e%2),n=Math.round(t);return r?n+.5:n}},{\"../../lib\":703,\"./constants\":658}],662:[function(t,e,r){\"use strict\";var n=t(\"./draw\");e.exports={moduleType:\"component\",name:\"shapes\",layoutAttributes:t(\"./attributes\"),supplyLayoutDefaults:t(\"./defaults\"),includeBasePlot:t(\"../../plots/cartesian/include_components\")(\"shapes\"),calcAutorange:t(\"./calc_autorange\"),draw:n.draw,drawOne:n.drawOne}},{\"../../plots/cartesian/include_components\":761,\"./attributes\":656,\"./calc_autorange\":657,\"./defaults\":659,\"./draw\":660}],663:[function(t,e,r){\"use strict\";var n=t(\"../../plots/font_attributes\"),i=t(\"../../plots/pad_attributes\"),a=t(\"../../lib/extend\").extendDeepAll,o=t(\"../../plot_api/edit_types\").overrideAll,s=t(\"../../plots/animation_attributes\"),l=t(\"../../plot_api/plot_template\").templatedArray,c=t(\"./constants\"),u=l(\"step\",{visible:{valType:\"boolean\",dflt:!0},method:{valType:\"enumerated\",values:[\"restyle\",\"relayout\",\"animate\",\"update\",\"skip\"],dflt:\"restyle\"},args:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},label:{valType:\"string\"},value:{valType:\"string\"},execute:{valType:\"boolean\",dflt:!0}});e.exports=o(l(\"slider\",{visible:{valType:\"boolean\",dflt:!0},active:{valType:\"number\",min:0,dflt:0},steps:u,lenmode:{valType:\"enumerated\",values:[\"fraction\",\"pixels\"],dflt:\"fraction\"},len:{valType:\"number\",min:0,dflt:1},x:{valType:\"number\",min:-2,max:3,dflt:0},pad:a(i({editType:\"arraydraw\"}),{},{t:{dflt:20}}),xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"left\"},y:{valType:\"number\",min:-2,max:3,dflt:0},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"top\"},transition:{duration:{valType:\"number\",min:0,dflt:150},easing:{valType:\"enumerated\",values:s.transition.easing.values,dflt:\"cubic-in-out\"}},currentvalue:{visible:{valType:\"boolean\",dflt:!0},xanchor:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],dflt:\"left\"},offset:{valType:\"number\",dflt:10},prefix:{valType:\"string\"},suffix:{valType:\"string\"},font:n({})},font:n({}),activebgcolor:{valType:\"color\",dflt:c.gripBgActiveColor},bgcolor:{valType:\"color\",dflt:c.railBgColor},bordercolor:{valType:\"color\",dflt:c.railBorderColor},borderwidth:{valType:\"number\",min:0,dflt:c.railBorderWidth},ticklen:{valType:\"number\",min:0,dflt:c.tickLength},tickcolor:{valType:\"color\",dflt:c.tickColor},tickwidth:{valType:\"number\",min:0,dflt:1},minorticklen:{valType:\"number\",min:0,dflt:c.minorTickLength}}),\"arraydraw\",\"from-root\")},{\"../../lib/extend\":693,\"../../plot_api/edit_types\":734,\"../../plot_api/plot_template\":741,\"../../plots/animation_attributes\":746,\"../../plots/font_attributes\":777,\"../../plots/pad_attributes\":811,\"./constants\":664}],664:[function(t,e,r){\"use strict\";e.exports={name:\"sliders\",containerClassName:\"slider-container\",groupClassName:\"slider-group\",inputAreaClass:\"slider-input-area\",railRectClass:\"slider-rail-rect\",railTouchRectClass:\"slider-rail-touch-rect\",gripRectClass:\"slider-grip-rect\",tickRectClass:\"slider-tick-rect\",inputProxyClass:\"slider-input-proxy\",labelsClass:\"slider-labels\",labelGroupClass:\"slider-label-group\",labelClass:\"slider-label\",currentValueClass:\"slider-current-value\",railHeight:5,menuIndexAttrName:\"slider-active-index\",autoMarginIdRoot:\"slider-\",minWidth:30,minHeight:30,textPadX:40,arrowOffsetX:4,railRadius:2,railWidth:5,railBorder:4,railBorderWidth:1,railBorderColor:\"#bec8d9\",railBgColor:\"#f8fafc\",railInset:8,stepInset:10,gripRadius:10,gripWidth:20,gripHeight:20,gripBorder:20,gripBorderWidth:1,gripBorderColor:\"#bec8d9\",gripBgColor:\"#f6f8fa\",gripBgActiveColor:\"#dbdde0\",labelPadding:8,labelOffset:0,tickWidth:1,tickColor:\"#333\",tickOffset:25,tickLength:7,minorTickOffset:25,minorTickColor:\"#333\",minorTickLength:4,currentValuePadding:8,currentValueInset:0}},{}],665:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../plots/array_container_defaults\"),a=t(\"./attributes\"),o=t(\"./constants\").name,s=a.steps;function l(t,e,r){function o(r,i){return n.coerce(t,e,a,r,i)}for(var s=i(t,e,{name:\"steps\",handleItemDefaults:c}),l=0,u=0;u<s.length;u++)s[u].visible&&l++;if(l<2?e.visible=!1:o(\"visible\")){e._stepCount=l;var f=e._visibleSteps=n.filterVisible(s);(s[o(\"active\")]||{}).visible||(e.active=f[0]._index),o(\"x\"),o(\"y\"),n.noneOrAll(t,e,[\"x\",\"y\"]),o(\"xanchor\"),o(\"yanchor\"),o(\"len\"),o(\"lenmode\"),o(\"pad.t\"),o(\"pad.r\"),o(\"pad.b\"),o(\"pad.l\"),n.coerceFont(o,\"font\",r.font),o(\"currentvalue.visible\")&&(o(\"currentvalue.xanchor\"),o(\"currentvalue.prefix\"),o(\"currentvalue.suffix\"),o(\"currentvalue.offset\"),n.coerceFont(o,\"currentvalue.font\",e.font)),o(\"transition.duration\"),o(\"transition.easing\"),o(\"bgcolor\"),o(\"activebgcolor\"),o(\"bordercolor\"),o(\"borderwidth\"),o(\"ticklen\"),o(\"tickwidth\"),o(\"tickcolor\"),o(\"minorticklen\")}}function c(t,e){function r(r,i){return n.coerce(t,e,s,r,i)}if(\"skip\"===t.method||Array.isArray(t.args)?r(\"visible\"):e.visible=!1){r(\"method\"),r(\"args\");var i=r(\"label\",\"step-\"+e._index);r(\"value\",i),r(\"execute\")}}e.exports=function(t,e){i(t,e,{name:o,handleItemDefaults:l})}},{\"../../lib\":703,\"../../plots/array_container_defaults\":747,\"./attributes\":663,\"./constants\":664}],666:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../plots/plots\"),a=t(\"../color\"),o=t(\"../drawing\"),s=t(\"../../lib\"),l=t(\"../../lib/svg_text_utils\"),c=t(\"../../plot_api/plot_template\").arrayEditor,u=t(\"./constants\"),f=t(\"../../constants/alignment\"),h=f.LINE_SPACING,p=f.FROM_TL,d=f.FROM_BR;function g(t){return u.autoMarginIdRoot+t._index}function v(t){return t._index}function m(t,e){var r=o.tester.selectAll(\"g.\"+u.labelGroupClass).data(e._visibleSteps);r.enter().append(\"g\").classed(u.labelGroupClass,!0);var a=0,c=0;r.each(function(t){var r=b(n.select(this),{step:t},e).node();if(r){var i=o.bBox(r);c=Math.max(c,i.height),a=Math.max(a,i.width)}}),r.remove();var f=e._dims={};f.inputAreaWidth=Math.max(u.railWidth,u.gripHeight);var h=t._fullLayout._size;f.lx=h.l+h.w*e.x,f.ly=h.t+h.h*(1-e.y),\"fraction\"===e.lenmode?f.outerLength=Math.round(h.w*e.len):f.outerLength=e.len,f.inputAreaStart=0,f.inputAreaLength=Math.round(f.outerLength-e.pad.l-e.pad.r);var v=(f.inputAreaLength-2*u.stepInset)/(e._stepCount-1),m=a+u.labelPadding;if(f.labelStride=Math.max(1,Math.ceil(m/v)),f.labelHeight=c,f.currentValueMaxWidth=0,f.currentValueHeight=0,f.currentValueTotalHeight=0,f.currentValueMaxLines=1,e.currentvalue.visible){var x=o.tester.append(\"g\");r.each(function(t){var r=y(x,e,t.label),n=r.node()&&o.bBox(r.node())||{width:0,height:0},i=l.lineCount(r);f.currentValueMaxWidth=Math.max(f.currentValueMaxWidth,Math.ceil(n.width)),f.currentValueHeight=Math.max(f.currentValueHeight,Math.ceil(n.height)),f.currentValueMaxLines=Math.max(f.currentValueMaxLines,i)}),f.currentValueTotalHeight=f.currentValueHeight+e.currentvalue.offset,x.remove()}f.height=f.currentValueTotalHeight+u.tickOffset+e.ticklen+u.labelOffset+f.labelHeight+e.pad.t+e.pad.b;var _=\"left\";s.isRightAnchor(e)&&(f.lx-=f.outerLength,_=\"right\"),s.isCenterAnchor(e)&&(f.lx-=f.outerLength/2,_=\"center\");var w=\"top\";s.isBottomAnchor(e)&&(f.ly-=f.height,w=\"bottom\"),s.isMiddleAnchor(e)&&(f.ly-=f.height/2,w=\"middle\"),f.outerLength=Math.ceil(f.outerLength),f.height=Math.ceil(f.height),f.lx=Math.round(f.lx),f.ly=Math.round(f.ly);var k={y:e.y,b:f.height*d[w],t:f.height*p[w]};\"fraction\"===e.lenmode?(k.l=0,k.xl=e.x-e.len*p[_],k.r=0,k.xr=e.x+e.len*d[_]):(k.x=e.x,k.l=f.outerLength*p[_],k.r=f.outerLength*d[_]),i.autoMargin(t,g(e),k)}function y(t,e,r){if(e.currentvalue.visible){var n,i,a=e._dims;switch(e.currentvalue.xanchor){case\"right\":n=a.inputAreaLength-u.currentValueInset-a.currentValueMaxWidth,i=\"left\";break;case\"center\":n=.5*a.inputAreaLength,i=\"middle\";break;default:n=u.currentValueInset,i=\"left\"}var c=s.ensureSingle(t,\"text\",u.labelClass,function(t){t.classed(\"user-select-none\",!0).attr({\"text-anchor\":i,\"data-notex\":1})}),f=e.currentvalue.prefix?e.currentvalue.prefix:\"\";if(\"string\"==typeof r)f+=r;else{var p=e.steps[e.active].label,d=e._gd._fullLayout._meta;d&&(p=s.templateString(p,d)),f+=p}e.currentvalue.suffix&&(f+=e.currentvalue.suffix),c.call(o.font,e.currentvalue.font).text(f).call(l.convertToTspans,e._gd);var g=l.lineCount(c),v=(a.currentValueMaxLines+1-g)*e.currentvalue.font.size*h;return l.positionText(c,n,v),c}}function x(t,e,r){s.ensureSingle(t,\"rect\",u.gripRectClass,function(n){n.call(T,e,t,r).style(\"pointer-events\",\"all\")}).attr({width:u.gripWidth,height:u.gripHeight,rx:u.gripRadius,ry:u.gripRadius}).call(a.stroke,r.bordercolor).call(a.fill,r.bgcolor).style(\"stroke-width\",r.borderwidth+\"px\")}function b(t,e,r){var n=s.ensureSingle(t,\"text\",u.labelClass,function(t){t.classed(\"user-select-none\",!0).attr({\"text-anchor\":\"middle\",\"data-notex\":1})}),i=e.step.label,a=r._gd._fullLayout._meta;return a&&(i=s.templateString(i,a)),n.call(o.font,r.font).text(i).call(l.convertToTspans,r._gd),n}function _(t,e){var r=s.ensureSingle(t,\"g\",u.labelsClass),i=e._dims,a=r.selectAll(\"g.\"+u.labelGroupClass).data(i.labelSteps);a.enter().append(\"g\").classed(u.labelGroupClass,!0),a.exit().remove(),a.each(function(t){var 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t.dtick){var c=t.dtick;throw t.dtick=1,\"ax.dtick error: \"+String(c)}},A.tickIncrement=function(t,e,r,a){var o=r?-1:1;if(i(e))return t+o*e;var l=e.charAt(0),c=o*Number(e.substr(1));if(\"M\"===l)return s.incrementMonth(t,c,a);if(\"L\"===l)return Math.log(Math.pow(10,t)+c)/Math.LN10;if(\"D\"===l){var u=\"D2\"===e?F:R,f=t+.01*o,h=s.roundUp(s.mod(f,1),u,r);return Math.floor(f)+Math.log(n.round(Math.pow(10,h),1))/Math.LN10}throw\"unrecognized dtick \"+String(e)},A.tickFirst=function(t){var e=t.r2l||Number,r=s.simpleMap(t.range,e),a=r[1]<r[0],o=a?Math.floor:Math.ceil,l=1.0001*r[0]-1e-4*r[1],c=t.dtick,u=e(t.tick0);if(i(c)){var f=o((l-u)/c)*c+u;return\"category\"!==t.type&&\"multicategory\"!==t.type||(f=s.constrain(f,0,t._categories.length-1)),f}var h=c.charAt(0),p=Number(c.substr(1));if(\"M\"===h){for(var d,g,v,m=0,y=u;m<10;){if(((d=A.tickIncrement(y,c,a,t.calendar))-l)*(y-l)<=0)return 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c._constraintShrinkable,x=Math.max(x,u),\"domain\"===c.constrain&&(k=!0);if(!(y>l*x)||k)for(r=0;r<m.length;r++)if(u=_[n=m[r]],f=(c=w[n]).constrain,u!==b||\"domain\"===f)if(p=u/b,\"range\"===f)a(c,p);else{var T=c._inputDomain,A=(c.domain[1]-c.domain[0])/(T[1]-T[0]),M=(c.r2l(c.range[1])-c.r2l(c.range[0]))/(c.r2l(c._inputRange[1])-c.r2l(c._inputRange[0]));if((p/=A)*M<1){c.domain=c._input.domain=T.slice(),a(c,p);continue}if(M<1&&(c.range=c._input.range=c._inputRange.slice(),p*=M),c.autorange){var S=c.r2l(c.range[0]),E=c.r2l(c.range[1]),C=(S+E)/2,L=C,z=C,O=Math.abs(E-C),I=C-O*p*1.0001,D=C+O*p*1.0001,P=o(c);h(c,p);var R,F,B=Math.abs(c._m),N=s(t,c),j=N.min,V=N.max;for(F=0;F<j.length;F++)(R=j[F].val-P(j[F])/B)>I&&R<L&&(L=R);for(F=0;F<V.length;F++)(R=V[F].val+P(V[F])/B)<D&&R>z&&(z=R);p/=(z-L)/(2*O),L=c.l2r(L),z=c.l2r(z),c.range=c._input.range=S<E?[L,z]:[z,L]}h(c,p)}}},r.clean=function(t,e){if(e._inputDomain){for(var 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n=t(\"d3\"),i=t(\"tinycolor2\"),a=t(\"has-passive-events\"),o=t(\"../../registry\"),s=t(\"../../lib\"),l=t(\"../../lib/svg_text_utils\"),c=t(\"../../components/color\"),u=t(\"../../components/drawing\"),f=t(\"../../components/fx\"),h=t(\"./axes\"),p=t(\"../../lib/setcursor\"),d=t(\"../../components/dragelement\"),g=t(\"../../constants/alignment\").FROM_TL,v=t(\"../../lib/clear_gl_canvases\"),m=t(\"../../plot_api/subroutines\").redrawReglTraces,y=t(\"../plots\"),x=t(\"./axis_ids\").getFromId,b=t(\"./select\").prepSelect,_=t(\"./select\").clearSelect,w=t(\"./select\").selectOnClick,k=t(\"./scale_zoom\"),T=t(\"./constants\"),A=T.MINDRAG,M=T.MINZOOM,S=!0;function E(t,e,r,n){var i=s.ensureSingle(t.draglayer,e,r,function(e){e.classed(\"drag\",!0).style({fill:\"transparent\",\"stroke-width\":0}).attr(\"data-subplot\",t.id)});return i.call(p,n),i.node()}function C(t,e,r,i,a,o,s){var l=E(t,\"rect\",e,r);return n.select(l).call(u.setRect,i,a,o,s),l}function L(t,e){for(var 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n,o,s=a.nestedProperty(t,e).get();if(o=(o=\"date\"===t.type?a.dfltRange(t.calendar):\"y\"===f?g.DFLTRANGEY:r.dfltRange||g.DFLTRANGEX).slice(),s&&2===s.length)for(\"date\"!==t.type||t.autorange||(s[0]=a.cleanDate(s[0],p,t.calendar),s[1]=a.cleanDate(s[1],p,t.calendar)),n=0;n<2;n++)if(\"date\"===t.type){if(!a.isDateTime(s[n],t.calendar)){t[e]=o;break}if(t.r2l(s[0])===t.r2l(s[1])){var l=a.constrain(t.r2l(s[0]),a.MIN_MS+1e3,a.MAX_MS-1e3);s[0]=t.l2r(l-1e3),s[1]=t.l2r(l+1e3);break}}else{if(!i(s[n])){if(!i(s[1-n])){t[e]=o;break}s[n]=s[1-n]*(n?10:.1)}if(s[n]<-h?s[n]=-h:s[n]>h&&(s[n]=h),s[0]===s[1]){var c=Math.max(1,Math.abs(1e-6*s[0]));s[0]-=c,s[1]+=c}}else a.nestedProperty(t,e).set(o)},t.setScale=function(r){var n=e._size;if(t.overlaying){var i=v.getFromId({_fullLayout:e},t.overlaying);t.domain=i.domain}var a=r&&t._r?\"_r\":\"range\",o=t.calendar;t.cleanRange(a);var s=t.r2l(t[a][0],o),l=t.r2l(t[a][1],o);if(\"y\"===f?(t._offset=n.t+(1-t.domain[1])*n.h,t._length=n.h*(t.domain[1]-t.domain[0]),t._m=t._length/(s-l),t._b=-t._m*l):(t._offset=n.l+t.domain[0]*n.w,t._length=n.w*(t.domain[1]-t.domain[0]),t._m=t._length/(l-s),t._b=-t._m*s),!isFinite(t._m)||!isFinite(t._b)||t._length<0)throw e._replotting=!1,new Error(\"Something went wrong with axis scaling\")},t.makeCalcdata=function(e,r){var n,i,o,s,l=t.type,c=\"date\"===l&&e[r+\"calendar\"];if(r in e){if(n=e[r],s=e._length||a.minRowLength(n),a.isTypedArray(n)&&(\"linear\"===l||\"log\"===l)){if(s===n.length)return n;if(n.subarray)return n.subarray(0,s)}if(\"multicategory\"===l)return function(t,e){for(var r=new Array(e),n=0;n<e;n++){var i=(t[0]||[])[n],a=(t[1]||[])[n];r[n]=T([i,a])}return r}(n,s);for(i=new Array(s),o=0;o<s;o++)i[o]=t.d2c(n[o],0,c)}else{var u=r+\"0\"in e?t.d2c(e[r+\"0\"],0,c):0,f=e[\"d\"+r]?Number(e[\"d\"+r]):1;for(n=e[{x:\"y\",y:\"x\"}[r]],s=e._length||n.length,i=new 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f=0;f<t.length;f++)a=t[f],\"gl2d\"===e&&n.traceIs(a,\"gl2d\")?a[l[0]]===o&&a[l[1]]===s&&c.push(a):a[l]===r&&c.push(a);return c}},{\"../registry\":831,\"./cartesian/constants\":757}],787:[function(t,e,r){\"use strict\";var n=t(\"mouse-change\"),i=t(\"mouse-wheel\"),a=t(\"mouse-event-offset\"),o=t(\"../cartesian/constants\"),s=t(\"has-passive-events\");function l(t,e){this.element=t,this.plot=e,this.mouseListener=null,this.wheelListener=null,this.lastInputTime=Date.now(),this.lastPos=[0,0],this.boxEnabled=!1,this.boxInited=!1,this.boxStart=[0,0],this.boxEnd=[0,0],this.dragStart=[0,0]}e.exports=function(t){var e=t.mouseContainer,r=t.glplot,c=new l(e,r);function u(){t.xaxis.autorange=!1,t.yaxis.autorange=!1}function f(e,n,i){var a,s,l=t.calcDataBox(),f=r.viewBox,h=c.lastPos[0],p=c.lastPos[1],d=o.MINDRAG*r.pixelRatio,g=o.MINZOOM*r.pixelRatio;function v(e,r,n){var i=Math.min(r,n),a=Math.max(r,n);i!==a?(l[e]=i,l[e+2]=a,c.dataBox=l,t.setRanges(l)):(t.selectBox.selectBox=[0,0,1,1],t.glplot.setDirty())}switch(n*=r.pixelRatio,i*=r.pixelRatio,i=f[3]-f[1]-i,t.fullLayout.dragmode){case\"zoom\":if(e){var m=n/(f[2]-f[0])*(l[2]-l[0])+l[0],y=i/(f[3]-f[1])*(l[3]-l[1])+l[1];c.boxInited||(c.boxStart[0]=m,c.boxStart[1]=y,c.dragStart[0]=n,c.dragStart[1]=i),c.boxEnd[0]=m,c.boxEnd[1]=y,c.boxInited=!0,c.boxEnabled||c.boxStart[0]===c.boxEnd[0]&&c.boxStart[1]===c.boxEnd[1]||(c.boxEnabled=!0);var x=Math.abs(c.dragStart[0]-n)<g,b=Math.abs(c.dragStart[1]-i)<g;if(!function(){for(var e=t.graphDiv._fullLayout._axisConstraintGroups,r=t.xaxis._id,n=t.yaxis._id,i=0;i<e.length;i++)if(-1!==e[i][r]){if(-1!==e[i][n])return!0;break}return!1}()||x&&b)x&&(c.boxEnd[0]=c.boxStart[0]),b&&(c.boxEnd[1]=c.boxStart[1]);else{a=c.boxEnd[0]-c.boxStart[0],s=c.boxEnd[1]-c.boxStart[1];var _=(l[3]-l[1])/(l[2]-l[0]);Math.abs(a*_)>Math.abs(s)?(c.boxEnd[1]=c.boxStart[1]+Math.abs(a)*_*(s>=0?1:-1),c.boxEnd[1]<l[1]?(c.boxEnd[1]=l[1],c.boxEnd[0]=c.boxStart[0]+(l[1]-c.boxStart[1])/Math.abs(_)):c.boxEnd[1]>l[3]&&(c.boxEnd[1]=l[3],c.boxEnd[0]=c.boxStart[0]+(l[3]-c.boxStart[1])/Math.abs(_))):(c.boxEnd[0]=c.boxStart[0]+Math.abs(s)/_*(a>=0?1:-1),c.boxEnd[0]<l[0]?(c.boxEnd[0]=l[0],c.boxEnd[1]=c.boxStart[1]+(l[0]-c.boxStart[0])*Math.abs(_)):c.boxEnd[0]>l[2]&&(c.boxEnd[0]=l[2],c.boxEnd[1]=c.boxStart[1]+(l[2]-c.boxStart[0])*Math.abs(_)))}}else c.boxEnabled?(a=c.boxStart[0]!==c.boxEnd[0],s=c.boxStart[1]!==c.boxEnd[1],a||s?(a&&(v(0,c.boxStart[0],c.boxEnd[0]),t.xaxis.autorange=!1),s&&(v(1,c.boxStart[1],c.boxEnd[1]),t.yaxis.autorange=!1),t.relayoutCallback()):t.glplot.setDirty(),c.boxEnabled=!1,c.boxInited=!1):c.boxInited&&(c.boxInited=!1);break;case\"pan\":c.boxEnabled=!1,c.boxInited=!1,e?(c.panning||(c.dragStart[0]=n,c.dragStart[1]=i),Math.abs(c.dragStart[0]-n)<d&&(n=c.dragStart[0]),Math.abs(c.dragStart[1]-i)<d&&(i=c.dragStart[1]),a=(h-n)*(l[2]-l[0])/(r.viewBox[2]-r.viewBox[0]),s=(p-i)*(l[3]-l[1])/(r.viewBox[3]-r.viewBox[1]),l[0]+=a,l[2]+=a,l[1]+=s,l[3]+=s,t.setRanges(l),c.panning=!0,c.lastInputTime=Date.now(),u(),t.cameraChanged(),t.handleAnnotations()):c.panning&&(c.panning=!1,t.relayoutCallback())}c.lastPos[0]=n,c.lastPos[1]=i}return c.mouseListener=n(e,f),e.addEventListener(\"touchstart\",function(t){var r=a(t.changedTouches[0],e);f(0,r[0],r[1]),f(1,r[0],r[1]),t.preventDefault()},!!s&&{passive:!1}),e.addEventListener(\"touchmove\",function(t){t.preventDefault();var r=a(t.changedTouches[0],e);f(1,r[0],r[1]),t.preventDefault()},!!s&&{passive:!1}),e.addEventListener(\"touchend\",function(t){f(0,c.lastPos[0],c.lastPos[1]),t.preventDefault()},!!s&&{passive:!1}),c.wheelListener=i(e,function(e,n){if(!t.scrollZoom)return!1;var i=t.calcDataBox(),a=r.viewBox,o=c.lastPos[0],s=c.lastPos[1],l=Math.exp(5*n/(a[3]-a[1])),f=o/(a[2]-a[0])*(i[2]-i[0])+i[0],h=s/(a[3]-a[1])*(i[3]-i[1])+i[1];return i[0]=(i[0]-f)*l+f,i[2]=(i[2]-f)*l+f,i[1]=(i[1]-h)*l+h,i[3]=(i[3]-h)*l+h,t.setRanges(i),c.lastInputTime=Date.now(),u(),t.cameraChanged(),t.handleAnnotations(),t.relayoutCallback(),!0},!0),c}},{\"../cartesian/constants\":757,\"has-passive-events\":406,\"mouse-change\":430,\"mouse-event-offset\":431,\"mouse-wheel\":433}],788:[function(t,e,r){\"use strict\";var n=t(\"../cartesian/axes\"),i=t(\"../../lib/str2rgbarray\");function a(t){this.scene=t,this.gl=t.gl,this.pixelRatio=t.pixelRatio,this.screenBox=[0,0,1,1],this.viewBox=[0,0,1,1],this.dataBox=[-1,-1,1,1],this.borderLineEnable=[!1,!1,!1,!1],this.borderLineWidth=[1,1,1,1],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.ticks=[[],[]],this.tickEnable=[!0,!0,!1,!1],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labels=[\"x\",\"y\"],this.labelEnable=[!0,!0,!1,!1],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelPad=[15,15,15,15],this.labelSize=[12,12],this.labelFont=[\"sans-serif\",\"sans-serif\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.title=\"\",this.titleEnable=!0,this.titleCenter=[0,0,0,0],this.titleAngle=0,this.titleColor=[0,0,0,1],this.titleFont=\"sans-serif\",this.titleSize=18,this.gridLineEnable=[!0,!0],this.gridLineColor=[[0,0,0,.5],[0,0,0,.5]],this.gridLineWidth=[1,1],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[1,1],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.static=this.scene.staticPlot}var o=a.prototype,s=[\"xaxis\",\"yaxis\"];o.merge=function(t){var e,r,n,a,o,l,c,u,f,h,p;for(this.titleEnable=!1,this.backgroundColor=i(t.plot_bgcolor),h=0;h<2;++h){var d=(e=s[h]).charAt(0);for(n=(r=t[this.scene[e]._name]).title.text===this.scene.fullLayout._dfltTitle[d]?\"\":r.title.text,p=0;p<=2;p+=2)this.labelEnable[h+p]=!1,this.labels[h+p]=n,this.labelColor[h+p]=i(r.title.font.color),this.labelFont[h+p]=r.title.font.family,this.labelSize[h+p]=r.title.font.size,this.labelPad[h+p]=this.getLabelPad(e,r),this.tickEnable[h+p]=!1,this.tickColor[h+p]=i((r.tickfont||{}).color),this.tickAngle[h+p]=\"auto\"===r.tickangle?0:Math.PI*-r.tickangle/180,this.tickPad[h+p]=this.getTickPad(r),this.tickMarkLength[h+p]=0,this.tickMarkWidth[h+p]=r.tickwidth||0,this.tickMarkColor[h+p]=i(r.tickcolor),this.borderLineEnable[h+p]=!1,this.borderLineColor[h+p]=i(r.linecolor),this.borderLineWidth[h+p]=r.linewidth||0;c=this.hasSharedAxis(r),o=this.hasAxisInDfltPos(e,r)&&!c,l=this.hasAxisInAltrPos(e,r)&&!c,a=r.mirror||!1,u=c?-1!==String(a).indexOf(\"all\"):!!a,f=c?\"allticks\"===a:-1!==String(a).indexOf(\"ticks\"),o?this.labelEnable[h]=!0:l&&(this.labelEnable[h+2]=!0),o?this.tickEnable[h]=r.showticklabels:l&&(this.tickEnable[h+2]=r.showticklabels),(o||u)&&(this.borderLineEnable[h]=r.showline),(l||u)&&(this.borderLineEnable[h+2]=r.showline),(o||f)&&(this.tickMarkLength[h]=this.getTickMarkLength(r)),(l||f)&&(this.tickMarkLength[h+2]=this.getTickMarkLength(r)),this.gridLineEnable[h]=r.showgrid,this.gridLineColor[h]=i(r.gridcolor),this.gridLineWidth[h]=r.gridwidth,this.zeroLineEnable[h]=r.zeroline,this.zeroLineColor[h]=i(r.zerolinecolor),this.zeroLineWidth[h]=r.zerolinewidth}},o.hasSharedAxis=function(t){var 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n=t(\"../../plot_api/edit_types\").overrideAll,i=t(\"./scene2d\"),a=t(\"../layout_attributes\"),o=t(\"../../constants/xmlns_namespaces\"),s=t(\"../cartesian/constants\"),l=t(\"../cartesian\"),c=t(\"../../components/fx/layout_attributes\"),u=t(\"../get_data\").getSubplotData;r.name=\"gl2d\",r.attr=[\"xaxis\",\"yaxis\"],r.idRoot=[\"x\",\"y\"],r.idRegex=s.idRegex,r.attrRegex=s.attrRegex,r.attributes=t(\"../cartesian/attributes\"),r.supplyLayoutDefaults=function(t,e,r){e._has(\"cartesian\")||l.supplyLayoutDefaults(t,e,r)},r.layoutAttrOverrides=n(l.layoutAttributes,\"plot\",\"from-root\"),r.baseLayoutAttrOverrides=n({plot_bgcolor:a.plot_bgcolor,hoverlabel:c.hoverlabel},\"plot\",\"nested\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl2d,a=0;a<n.length;a++){var o=n[a],s=e._plots[o],l=u(r,\"gl2d\",o),c=s._scene2d;void 0===c&&(c=new i({id:o,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),s._scene2d=c),c.plot(l,t.calcdata,e,t.layout)}},r.clean=function(t,e,r,n){for(var i=n._subplots.gl2d||[],a=0;a<i.length;a++){var o=i[a],s=n._plots[o];if(s._scene2d)0===u(t,\"gl2d\",o).length&&(s._scene2d.destroy(),delete n._plots[o])}l.clean.apply(this,arguments)},r.drawFramework=function(t){t._context.staticPlot||l.drawFramework(t)},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){var i=e._plots[r[n]]._scene2d,a=i.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":a,x:0,y:0,width:\"100%\",height:\"100%\",preserveAspectRatio:\"none\"}),i.destroy()}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){e._plots[r[n]]._scene2d.updateFx(e.dragmode)}}},{\"../../components/fx/layout_attributes\":620,\"../../constants/xmlns_namespaces\":681,\"../../plot_api/edit_types\":734,\"../cartesian\":762,\"../cartesian/attributes\":749,\"../cartesian/constants\":757,\"../get_data\":786,\"../layout_attributes\":803,\"./scene2d\":790}],790:[function(t,e,r){\"use strict\";var n,i,a=t(\"../../registry\"),o=t(\"../../plots/cartesian/axes\"),s=t(\"../../components/fx\"),l=t(\"gl-plot2d\"),c=t(\"gl-spikes2d\"),u=t(\"gl-select-box\"),f=t(\"webgl-context\"),h=t(\"./convert\"),p=t(\"./camera\"),d=t(\"../../lib/show_no_webgl_msg\"),g=t(\"../cartesian/constraints\"),v=g.enforce,m=g.clean,y=t(\"../cartesian/autorange\").doAutoRange,x=[\"xaxis\",\"yaxis\"],b=t(\"../cartesian/constants\").SUBPLOT_PATTERN;function _(t,e){this.container=t.container,this.graphDiv=t.graphDiv,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.scrollZoom=this.graphDiv._context._scrollZoom.cartesian,this.fullData=null,this.updateRefs(e),this.makeFramework(),this.stopped||(this.glplotOptions=h(this),this.glplotOptions.merge(e),this.glplot=l(this.glplotOptions),this.camera=p(this),this.traces={},this.spikes=c(this.glplot),this.selectBox=u(this.glplot,{innerFill:!1,outerFill:!0}),this.lastButtonState=0,this.pickResult=null,this.isMouseOver=!0,this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw())}e.exports=_;var w=_.prototype;w.makeFramework=function(){if(this.staticPlot){if(!(i||(n=document.createElement(\"canvas\"),i=f({canvas:n,preserveDrawingBuffer:!1,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"Error creating static canvas/context for image server\");this.canvas=n,this.gl=i}else{var t=this.container.querySelector(\".gl-canvas-focus\"),e=f({canvas:t,preserveDrawingBuffer:!0,premultipliedAlpha:!0});if(!e)return d(this),void(this.stopped=!0);this.canvas=t,this.gl=e}var r=this.canvas;r.style.width=\"100%\",r.style.height=\"100%\",r.style.position=\"absolute\",r.style.top=\"0px\",r.style.left=\"0px\",r.style[\"pointer-events\"]=\"none\",this.updateSize(r),r.className+=\" user-select-none\";var a=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");a.style.position=\"absolute\",a.style.top=a.style.left=\"0px\",a.style.width=a.style.height=\"100%\",a.style[\"z-index\"]=20,a.style[\"pointer-events\"]=\"none\";var o=this.mouseContainer=document.createElement(\"div\");o.style.position=\"absolute\",o.style[\"pointer-events\"]=\"auto\",this.pickCanvas=this.container.querySelector(\".gl-canvas-pick\");var s=this.container;s.appendChild(a),s.appendChild(o);var l=this;o.addEventListener(\"mouseout\",function(){l.isMouseOver=!1,l.unhover()}),o.addEventListener(\"mouseover\",function(){l.isMouseOver=!0})},w.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(n),this.updateSize(this.canvas);var e=this.glplot.gl,r=e.drawingBufferWidth,i=e.drawingBufferHeight;e.clearColor(1,1,1,0),e.clear(e.COLOR_BUFFER_BIT|e.DEPTH_BUFFER_BIT),this.glplot.setDirty(),this.glplot.draw(),e.bindFramebuffer(e.FRAMEBUFFER,null);var a=new Uint8Array(r*i*4);e.readPixels(0,0,r,i,e.RGBA,e.UNSIGNED_BYTE,a);for(var o=0,s=i-1;o<s;++o,--s)for(var l=0;l<r;++l)for(var c=0;c<4;++c){var u=a[4*(r*o+l)+c];a[4*(r*o+l)+c]=a[4*(r*s+l)+c],a[4*(r*s+l)+c]=u}var f=document.createElement(\"canvas\");f.width=r,f.height=i;var h,p=f.getContext(\"2d\"),d=p.createImageData(r,i);switch(d.data.set(a),p.putImageData(d,0,0),t){case\"jpeg\":h=f.toDataURL(\"image/jpeg\");break;case\"webp\":h=f.toDataURL(\"image/webp\");break;default:h=f.toDataURL(\"image/png\")}return this.staticPlot&&this.container.removeChild(n),h},w.updateSize=function(t){t||(t=this.canvas);var e=this.pixelRatio,r=this.fullLayout,n=r.width,i=r.height,a=0|Math.ceil(e*n),o=0|Math.ceil(e*i);return t.width===a&&t.height===o||(t.width=a,t.height=o),t},w.computeTickMarks=function(){this.xaxis.setScale(),this.yaxis.setScale();for(var t=[o.calcTicks(this.xaxis),o.calcTicks(this.yaxis)],e=0;e<2;++e)for(var r=0;r<t[e].length;++r)t[e][r].text=t[e][r].text+\"\";return t},w.updateRefs=function(t){this.fullLayout=t;var e=this.id.match(b),r=\"xaxis\"+e[1],n=\"yaxis\"+e[2];this.xaxis=this.fullLayout[r],this.yaxis=this.fullLayout[n]},w.relayoutCallback=function(){var t=this.graphDiv,e=this.xaxis,r=this.yaxis,n=t.layout,i={},o=i[e._name+\".range\"]=e.range.slice(),s=i[r._name+\".range\"]=r.range.slice();i[e._name+\".autorange\"]=e.autorange,i[r._name+\".autorange\"]=r.autorange,a.call(\"_storeDirectGUIEdit\",t.layout,t._fullLayout._preGUI,i);var l=n[e._name];l.range=o,l.autorange=e.autorange;var c=n[r._name];c.range=s,c.autorange=r.autorange,i.lastInputTime=this.camera.lastInputTime,t.emit(\"plotly_relayout\",i)},w.cameraChanged=function(){var t=this.camera;this.glplot.setDataBox(this.calcDataBox());var e=this.computeTickMarks();(function(t,e){for(var r=0;r<2;++r){var n=t[r],i=e[r];if(n.length!==i.length)return!0;for(var a=0;a<n.length;++a)if(n[a].x!==i[a].x)return!0}return!1})(e,this.glplotOptions.ticks)&&(this.glplotOptions.ticks=e,this.glplotOptions.dataBox=t.dataBox,this.glplot.update(this.glplotOptions),this.handleAnnotations())},w.handleAnnotations=function(){for(var t=this.graphDiv,e=this.fullLayout.annotations,r=0;r<e.length;r++){var n=e[r];n.xref===this.xaxis._id&&n.yref===this.yaxis._id&&a.getComponentMethod(\"annotations\",\"drawOne\")(t,r)}},w.destroy=function(){if(this.glplot){var t=this.traces;t&&Object.keys(t).map(function(e){t[e].dispose(),delete t[e]}),this.glplot.dispose(),this.container.removeChild(this.svgContainer),this.container.removeChild(this.mouseContainer),this.fullData=null,this.glplot=null,this.stopped=!0,this.camera.mouseListener.enabled=!1,this.mouseContainer.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=null}},w.plot=function(t,e,r){var n=this.glplot;this.updateRefs(r),this.xaxis.clearCalc(),this.yaxis.clearCalc(),this.updateTraces(t,e),this.updateFx(r.dragmode);var i=r.width,a=r.height;this.updateSize(this.canvas);var o=this.glplotOptions;o.merge(r),o.screenBox=[0,0,i,a];var s={_fullLayout:{_axisConstraintGroups:this.graphDiv._fullLayout._axisConstraintGroups,xaxis:this.xaxis,yaxis:this.yaxis}};m(s,this.xaxis),m(s,this.yaxis);var l,c,u=r._size,f=this.xaxis.domain,h=this.yaxis.domain;for(o.viewBox=[u.l+f[0]*u.w,u.b+h[0]*u.h,i-u.r-(1-f[1])*u.w,a-u.t-(1-h[1])*u.h],this.mouseContainer.style.width=u.w*(f[1]-f[0])+\"px\",this.mouseContainer.style.height=u.h*(h[1]-h[0])+\"px\",this.mouseContainer.height=u.h*(h[1]-h[0]),this.mouseContainer.style.left=u.l+f[0]*u.w+\"px\",this.mouseContainer.style.top=u.t+(1-h[1])*u.h+\"px\",c=0;c<2;++c)(l=this[x[c]])._length=o.viewBox[c+2]-o.viewBox[c],y(this.graphDiv,l),l.setScale();v(s),o.ticks=this.computeTickMarks(),o.dataBox=this.calcDataBox(),o.merge(r),n.update(o),this.glplot.draw()},w.calcDataBox=function(){var t=this.xaxis,e=this.yaxis,r=t.range,n=e.range,i=t.r2l,a=e.r2l;return[i(r[0]),a(n[0]),i(r[1]),a(n[1])]},w.setRanges=function(t){var e=this.xaxis,r=this.yaxis,n=e.l2r,i=r.l2r;e.range=[n(t[0]),n(t[2])],r.range=[i(t[1]),i(t[3])]},w.updateTraces=function(t,e){var r,n,i,a=Object.keys(this.traces);this.fullData=t;t:for(r=0;r<a.length;r++){var o=a[r],s=this.traces[o];for(n=0;n<t.length;n++)if((i=t[n]).uid===o&&i.type===s.type)continue t;s.dispose(),delete this.traces[o]}for(r=0;r<t.length;r++){i=t[r];var l=e[r],c=this.traces[i.uid];c?c.update(i,l):(c=i._module.plot(this,i,l),this.traces[i.uid]=c)}this.glplot.objects.sort(function(t,e){return t._trace.index-e._trace.index})},w.updateFx=function(t){\"lasso\"===t||\"select\"===t?(this.pickCanvas.style[\"pointer-events\"]=\"none\",this.mouseContainer.style[\"pointer-events\"]=\"none\"):(this.pickCanvas.style[\"pointer-events\"]=\"auto\",this.mouseContainer.style[\"pointer-events\"]=\"auto\"),this.mouseContainer.style.cursor=\"pan\"===t?\"move\":\"zoom\"===t?\"crosshair\":null},w.emitPointAction=function(t,e){for(var r,n=t.trace.uid,i=t.pointIndex,a=0;a<this.fullData.length;a++)this.fullData[a].uid===n&&(r=this.fullData[a]);var o={x:t.traceCoord[0],y:t.traceCoord[1],curveNumber:r.index,pointNumber:i,data:r._input,fullData:this.fullData,xaxis:this.xaxis,yaxis:this.yaxis};s.appendArrayPointValue(o,r,i),this.graphDiv.emit(e,{points:[o]})},w.draw=function(){if(!this.stopped){requestAnimationFrame(this.redraw);var t=this.glplot,e=this.camera,r=e.mouseListener,n=1===this.lastButtonState&&0===r.buttons,i=this.fullLayout;this.lastButtonState=r.buttons,this.cameraChanged();var a,o=r.x*t.pixelRatio,l=this.canvas.height-t.pixelRatio*r.y;if(e.boxEnabled&&\"zoom\"===i.dragmode){this.selectBox.enabled=!0;for(var c=this.selectBox.selectBox=[Math.min(e.boxStart[0],e.boxEnd[0]),Math.min(e.boxStart[1],e.boxEnd[1]),Math.max(e.boxStart[0],e.boxEnd[0]),Math.max(e.boxStart[1],e.boxEnd[1])],u=0;u<2;u++)e.boxStart[u]===e.boxEnd[u]&&(c[u]=t.dataBox[u],c[u+2]=t.dataBox[u+2]);t.setDirty()}else if(!e.panning&&this.isMouseOver){this.selectBox.enabled=!1;var f=i._size,h=this.xaxis.domain,p=this.yaxis.domain,d=(a=t.pick(o/t.pixelRatio+f.l+h[0]*f.w,l/t.pixelRatio-(f.t+(1-p[1])*f.h)))&&a.object._trace.handlePick(a);if(d&&n&&this.emitPointAction(d,\"plotly_click\"),a&&\"skip\"!==a.object._trace.hoverinfo&&i.hovermode&&d&&(!this.lastPickResult||this.lastPickResult.traceUid!==d.trace.uid||this.lastPickResult.dataCoord[0]!==d.dataCoord[0]||this.lastPickResult.dataCoord[1]!==d.dataCoord[1])){var g=d;this.lastPickResult={traceUid:d.trace?d.trace.uid:null,dataCoord:d.dataCoord.slice()},this.spikes.update({center:a.dataCoord}),g.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(a.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(a.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio],this.emitPointAction(d,\"plotly_hover\");var v=this.fullData[g.trace.index]||{},m=g.pointIndex,y=s.castHoverinfo(v,i,m);if(y&&\"all\"!==y){var x=y.split(\"+\");-1===x.indexOf(\"x\")&&(g.traceCoord[0]=void 0),-1===x.indexOf(\"y\")&&(g.traceCoord[1]=void 0),-1===x.indexOf(\"z\")&&(g.traceCoord[2]=void 0),-1===x.indexOf(\"text\")&&(g.textLabel=void 0),-1===x.indexOf(\"name\")&&(g.name=void 0)}s.loneHover({x:g.screenCoord[0],y:g.screenCoord[1],xLabel:this.hoverFormatter(\"xaxis\",g.traceCoord[0]),yLabel:this.hoverFormatter(\"yaxis\",g.traceCoord[1]),zLabel:g.traceCoord[2],text:g.textLabel,name:g.name,color:s.castHoverOption(v,m,\"bgcolor\")||g.color,borderColor:s.castHoverOption(v,m,\"bordercolor\"),fontFamily:s.castHoverOption(v,m,\"font.family\"),fontSize:s.castHoverOption(v,m,\"font.size\"),fontColor:s.castHoverOption(v,m,\"font.color\"),nameLength:s.castHoverOption(v,m,\"namelength\"),textAlign:s.castHoverOption(v,m,\"align\")},{container:this.svgContainer,gd:this.graphDiv})}}a||this.unhover(),t.draw()}},w.unhover=function(){this.lastPickResult&&(this.spikes.update({}),this.lastPickResult=null,this.graphDiv.emit(\"plotly_unhover\"),s.loneUnhover(this.svgContainer))},w.hoverFormatter=function(t,e){if(void 0!==e){var r=this[t];return o.tickText(r,r.c2l(e),\"hover\").text}}},{\"../../components/fx\":619,\"../../lib/show_no_webgl_msg\":724,\"../../plots/cartesian/axes\":751,\"../../registry\":831,\"../cartesian/autorange\":750,\"../cartesian/constants\":757,\"../cartesian/constraints\":758,\"./camera\":787,\"./convert\":788,\"gl-plot2d\":286,\"gl-select-box\":298,\"gl-spikes2d\":307,\"webgl-context\":543}],791:[function(t,e,r){\"use strict\";var n=t(\"../../plot_api/edit_types\").overrideAll,i=t(\"../../components/fx/layout_attributes\"),a=t(\"./scene\"),o=t(\"../get_data\").getSubplotData,s=t(\"../../lib\"),l=t(\"../../constants/xmlns_namespaces\");r.name=\"gl3d\",r.attr=\"scene\",r.idRoot=\"scene\",r.idRegex=r.attrRegex=s.counterRegex(\"scene\"),r.attributes=t(\"./layout/attributes\"),r.layoutAttributes=t(\"./layout/layout_attributes\"),r.baseLayoutAttrOverrides=n({hoverlabel:i.hoverlabel},\"plot\",\"nested\"),r.supplyLayoutDefaults=t(\"./layout/defaults\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl3d,i=0;i<n.length;i++){var s=n[i],l=o(r,\"gl3d\",s),c=e[s],u=c.camera,f=c._scene;f||(f=new a({id:s,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio,camera:u},e),c._scene=f),f.viewInitial||(f.viewInitial={up:{x:u.up.x,y:u.up.y,z:u.up.z},eye:{x:u.eye.x,y:u.eye.y,z:u.eye.z},center:{x:u.center.x,y:u.center.y,z:u.center.z}}),f.plot(l,e,t.layout)}},r.clean=function(t,e,r,n){for(var i=n._subplots.gl3d||[],a=0;a<i.length;a++){var o=i[a];!e[o]&&n[o]._scene&&(n[o]._scene.destroy(),n._infolayer&&n._infolayer.selectAll(\".annotation-\"+o).remove())}},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=e._size,i=0;i<r.length;i++){var a=e[r[i]],o=a.domain,s=a._scene,c=s.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:l.svg,\"xlink:href\":c,x:n.l+n.w*o.x[0],y:n.t+n.h*(1-o.y[1]),width:n.w*(o.x[1]-o.x[0]),height:n.h*(o.y[1]-o.y[0]),preserveAspectRatio:\"none\"}),s.destroy()}},r.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),\"scene\"+e}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=0;n<r.length;n++){e[r[n]]._scene.updateFx(e.dragmode,e.hovermode)}}},{\"../../components/fx/layout_attributes\":620,\"../../constants/xmlns_namespaces\":681,\"../../lib\":703,\"../../plot_api/edit_types\":734,\"../get_data\":786,\"./layout/attributes\":792,\"./layout/defaults\":796,\"./layout/layout_attributes\":797,\"./scene\":801}],792:[function(t,e,r){\"use strict\";e.exports={scene:{valType:\"subplotid\",dflt:\"scene\",editType:\"calc+clearAxisTypes\"}}},{}],793:[function(t,e,r){\"use strict\";var n=t(\"../../../components/color\"),i=t(\"../../cartesian/layout_attributes\"),a=t(\"../../../lib/extend\").extendFlat,o=t(\"../../../plot_api/edit_types\").overrideAll;e.exports=o({visible:i.visible,showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:n.defaultLine},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},color:i.color,categoryorder:i.categoryorder,categoryarray:i.categoryarray,title:i.title,type:a({},i.type,{values:[\"-\",\"linear\",\"log\",\"date\",\"category\"]}),autorange:i.autorange,rangemode:i.rangemode,range:a({},i.range,{items:[{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}},{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}}],anim:!1}),tickmode:i.tickmode,nticks:i.nticks,tick0:i.tick0,dtick:i.dtick,tickvals:i.tickvals,ticktext:i.ticktext,ticks:i.ticks,mirror:i.mirror,ticklen:i.ticklen,tickwidth:i.tickwidth,tickcolor:i.tickcolor,showticklabels:i.showticklabels,tickfont:i.tickfont,tickangle:i.tickangle,tickprefix:i.tickprefix,showtickprefix:i.showtickprefix,ticksuffix:i.ticksuffix,showticksuffix:i.showticksuffix,showexponent:i.showexponent,exponentformat:i.exponentformat,separatethousands:i.separatethousands,tickformat:i.tickformat,tickformatstops:i.tickformatstops,hoverformat:i.hoverformat,showline:i.showline,linecolor:i.linecolor,linewidth:i.linewidth,showgrid:i.showgrid,gridcolor:a({},i.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:i.gridwidth,zeroline:i.zeroline,zerolinecolor:i.zerolinecolor,zerolinewidth:i.zerolinewidth,_deprecated:{title:i._deprecated.title,titlefont:i._deprecated.titlefont}},\"plot\",\"from-root\")},{\"../../../components/color\":580,\"../../../lib/extend\":693,\"../../../plot_api/edit_types\":734,\"../../cartesian/layout_attributes\":763}],794:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\").mix,i=t(\"../../../lib\"),a=t(\"../../../plot_api/plot_template\"),o=t(\"./axis_attributes\"),s=t(\"../../cartesian/type_defaults\"),l=t(\"../../cartesian/axis_defaults\"),c=[\"xaxis\",\"yaxis\",\"zaxis\"];e.exports=function(t,e,r){var u,f;function h(t,e){return i.coerce(u,f,o,t,e)}for(var p=0;p<c.length;p++){var d=c[p];u=t[d]||{},(f=a.newContainer(e,d))._id=d[0]+r.scene,f._name=d,s(u,f,h,r),l(u,f,h,{font:r.font,letter:d[0],data:r.data,showGrid:!0,noTickson:!0,bgColor:r.bgColor,calendar:r.calendar},r.fullLayout),h(\"gridcolor\",n(f.color,r.bgColor,13600/187).toRgbString()),h(\"title.text\",d[0]),f.setScale=i.noop,h(\"showspikes\")&&(h(\"spikesides\"),h(\"spikethickness\"),h(\"spikecolor\",f.color)),h(\"showaxeslabels\"),h(\"showbackground\")&&h(\"backgroundcolor\")}}},{\"../../../lib\":703,\"../../../plot_api/plot_template\":741,\"../../cartesian/axis_defaults\":753,\"../../cartesian/type_defaults\":774,\"./axis_attributes\":793,tinycolor2:524}],795:[function(t,e,r){\"use strict\";var n=t(\"../../../lib/str2rgbarray\"),i=t(\"../../../lib\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"];function o(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open Sans\"],this.labelSize=[20,20,20],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=this.tickPad.slice(),this._defaultLabelPad=this.labelPad.slice(),this._defaultLineTickLength=this.lineTickLength.slice()}o.prototype.merge=function(t,e){for(var r=0;r<3;++r){var o=e[a[r]];o.visible?(this.labels[r]=t._meta?i.templateString(o.title.text,t._meta):o.title.text,\"font\"in o.title&&(o.title.font.color&&(this.labelColor[r]=n(o.title.font.color)),o.title.font.family&&(this.labelFont[r]=o.title.font.family),o.title.font.size&&(this.labelSize[r]=o.title.font.size)),\"showline\"in o&&(this.lineEnable[r]=o.showline),\"linecolor\"in o&&(this.lineColor[r]=n(o.linecolor)),\"linewidth\"in o&&(this.lineWidth[r]=o.linewidth),\"showgrid\"in o&&(this.gridEnable[r]=o.showgrid),\"gridcolor\"in o&&(this.gridColor[r]=n(o.gridcolor)),\"gridwidth\"in o&&(this.gridWidth[r]=o.gridwidth),\"log\"===o.type?this.zeroEnable[r]=!1:\"zeroline\"in o&&(this.zeroEnable[r]=o.zeroline),\"zerolinecolor\"in o&&(this.zeroLineColor[r]=n(o.zerolinecolor)),\"zerolinewidth\"in o&&(this.zeroLineWidth[r]=o.zerolinewidth),\"ticks\"in o&&o.ticks?this.lineTickEnable[r]=!0:this.lineTickEnable[r]=!1,\"ticklen\"in o&&(this.lineTickLength[r]=this._defaultLineTickLength[r]=o.ticklen),\"tickcolor\"in o&&(this.lineTickColor[r]=n(o.tickcolor)),\"tickwidth\"in o&&(this.lineTickWidth[r]=o.tickwidth),\"tickangle\"in o&&(this.tickAngle[r]=\"auto\"===o.tickangle?-3600:Math.PI*-o.tickangle/180),\"showticklabels\"in o&&(this.tickEnable[r]=o.showticklabels),\"tickfont\"in o&&(o.tickfont.color&&(this.tickColor[r]=n(o.tickfont.color)),o.tickfont.family&&(this.tickFont[r]=o.tickfont.family),o.tickfont.size&&(this.tickSize[r]=o.tickfont.size)),\"mirror\"in o?-1!==[\"ticks\",\"all\",\"allticks\"].indexOf(o.mirror)?(this.lineTickMirror[r]=!0,this.lineMirror[r]=!0):!0===o.mirror?(this.lineTickMirror[r]=!1,this.lineMirror[r]=!0):(this.lineTickMirror[r]=!1,this.lineMirror[r]=!1):this.lineMirror[r]=!1,\"showbackground\"in o&&!1!==o.showbackground?(this.backgroundEnable[r]=!0,this.backgroundColor[r]=n(o.backgroundcolor)):this.backgroundEnable[r]=!1):(this.tickEnable[r]=!1,this.labelEnable[r]=!1,this.lineEnable[r]=!1,this.lineTickEnable[r]=!1,this.gridEnable[r]=!1,this.zeroEnable[r]=!1,this.backgroundEnable[r]=!1)}},e.exports=function(t,e){var r=new o;return r.merge(t,e),r}},{\"../../../lib\":703,\"../../../lib/str2rgbarray\":726}],796:[function(t,e,r){\"use strict\";var n=t(\"../../../lib\"),i=t(\"../../../components/color\"),a=t(\"../../../registry\"),o=t(\"../../subplot_defaults\"),s=t(\"./axis_defaults\"),l=t(\"./layout_attributes\"),c=t(\"../../get_data\").getSubplotData,u=\"gl3d\";function f(t,e,r,n){for(var o=r(\"bgcolor\"),l=i.combine(o,n.paper_bgcolor),f=[\"up\",\"center\",\"eye\"],h=0;h<f.length;h++)r(\"camera.\"+f[h]+\".x\"),r(\"camera.\"+f[h]+\".y\"),r(\"camera.\"+f[h]+\".z\");r(\"camera.projection.type\");var p=!!r(\"aspectratio.x\")&&!!r(\"aspectratio.y\")&&!!r(\"aspectratio.z\"),d=r(\"aspectmode\",p?\"manual\":\"auto\");p||(t.aspectratio=e.aspectratio={x:1,y:1,z:1},\"manual\"===d&&(e.aspectmode=\"auto\"),t.aspectmode=e.aspectmode);var g=c(n.fullData,u,n.id);s(t,e,{font:n.font,scene:n.id,data:g,bgColor:l,calendar:n.calendar,fullLayout:n.fullLayout}),a.getComponentMethod(\"annotations3d\",\"handleDefaults\")(t,e,n);var v=n.getDfltFromLayout(\"dragmode\");if(!1!==v&&!v)if(v=\"orbit\",t.camera&&t.camera.up){var m=t.camera.up.x,y=t.camera.up.y,x=t.camera.up.z;0!==x&&(m&&y&&x?x/Math.sqrt(m*m+y*y+x*x)>.999&&(v=\"turntable\"):v=\"turntable\")}else v=\"turntable\";r(\"dragmode\",v),r(\"hovermode\",n.getDfltFromLayout(\"hovermode\"))}e.exports=function(t,e,r){var i=e._basePlotModules.length>1;o(t,e,r,{type:u,attributes:l,handleDefaults:f,fullLayout:e,font:e.font,fullData:r,getDfltFromLayout:function(e){if(!i)return n.validate(t[e],l[e])?t[e]:void 0},paper_bgcolor:e.paper_bgcolor,calendar:e.calendar})}},{\"../../../components/color\":580,\"../../../lib\":703,\"../../../registry\":831,\"../../get_data\":786,\"../../subplot_defaults\":826,\"./axis_defaults\":794,\"./layout_attributes\":797}],797:[function(t,e,r){\"use strict\";var n=t(\"./axis_attributes\"),i=t(\"../../domain\").attributes,a=t(\"../../../lib/extend\").extendFlat,o=t(\"../../../lib\").counterRegex;function s(t,e,r){return{x:{valType:\"number\",dflt:t,editType:\"camera\"},y:{valType:\"number\",dflt:e,editType:\"camera\"},z:{valType:\"number\",dflt:r,editType:\"camera\"},editType:\"camera\"}}e.exports={_arrayAttrRegexps:[o(\"scene\",\".annotations\",!0)],bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"plot\"},camera:{up:a(s(0,0,1),{}),center:a(s(0,0,0),{}),eye:a(s(1.25,1.25,1.25),{}),projection:{type:{valType:\"enumerated\",values:[\"perspective\",\"orthographic\"],dflt:\"perspective\",editType:\"calc\"},editType:\"calc\"},editType:\"camera\"},domain:i({name:\"scene\",editType:\"plot\"}),aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\",editType:\"plot\",impliedEdits:{\"aspectratio.x\":void 0,\"aspectratio.y\":void 0,\"aspectratio.z\":void 0}},aspectratio:{x:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},y:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},z:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},editType:\"plot\",impliedEdits:{aspectmode:\"manual\"}},xaxis:n,yaxis:n,zaxis:n,dragmode:{valType:\"enumerated\",values:[\"orbit\",\"turntable\",\"zoom\",\"pan\",!1],editType:\"plot\"},hovermode:{valType:\"enumerated\",values:[\"closest\",!1],dflt:\"closest\",editType:\"modebar\"},uirevision:{valType:\"any\",editType:\"none\"},editType:\"plot\",_deprecated:{cameraposition:{valType:\"info_array\",editType:\"camera\"}}}},{\"../../../lib\":703,\"../../../lib/extend\":693,\"../../domain\":776,\"./axis_attributes\":793}],798:[function(t,e,r){\"use strict\";var n=t(\"../../../lib/str2rgbarray\"),i=[\"xaxis\",\"yaxis\",\"zaxis\"];function a(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}a.prototype.merge=function(t){for(var e=0;e<3;++e){var r=t[i[e]];r.visible?(this.enabled[e]=r.showspikes,this.colors[e]=n(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness):(this.enabled[e]=!1,this.drawSides[e]=!1)}},e.exports=function(t){var e=new a;return e.merge(t),e}},{\"../../../lib/str2rgbarray\":726}],799:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,s=t.fullSceneLayout,l=[[],[],[]],c=0;c<3;++c){var u=s[a[c]];if(u._length=(r[c].hi-r[c].lo)*r[c].pixelsPerDataUnit/t.dataScale[c],Math.abs(u._length)===1/0||isNaN(u._length))l[c]=[];else{u._input_range=u.range.slice(),u.range[0]=r[c].lo/t.dataScale[c],u.range[1]=r[c].hi/t.dataScale[c],u._m=1/(t.dataScale[c]*r[c].pixelsPerDataUnit),u.range[0]===u.range[1]&&(u.range[0]-=1,u.range[1]+=1);var f=u.tickmode;if(\"auto\"===u.tickmode){u.tickmode=\"linear\";var h=u.nticks||i.constrain(u._length/40,4,9);n.autoTicks(u,Math.abs(u.range[1]-u.range[0])/h)}for(var p=n.calcTicks(u),d=0;d<p.length;++d)p[d].x=p[d].x*t.dataScale[c],\"date\"===u.type&&(p[d].text=p[d].text.replace(/\\<br\\>/g,\" \"));l[c]=p,u.tickmode=f}}e.ticks=l;for(var c=0;c<3;++c){o[c]=.5*(t.glplot.bounds[0][c]+t.glplot.bounds[1][c]);for(var d=0;d<2;++d)e.bounds[d][c]=t.glplot.bounds[d][c]}t.contourLevels=function(t){for(var e=new Array(3),r=0;r<3;++r){for(var n=t[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;e[r]=i}return e}(l)};var n=t(\"../../cartesian/axes\"),i=t(\"../../../lib\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"],o=[0,0,0]},{\"../../../lib\":703,\"../../cartesian/axes\":751}],800:[function(t,e,r){\"use strict\";function n(t,e){var r,n,i=[0,0,0,0];for(r=0;r<4;++r)for(n=0;n<4;++n)i[n]+=t[4*r+n]*e[r];return i}e.exports=function(t,e){return n(t.projection,n(t.view,n(t.model,[e[0],e[1],e[2],1])))}},{}],801:[function(t,e,r){\"use strict\";var n,i,a=t(\"gl-plot3d\").createCamera,o=t(\"gl-plot3d\").createScene,s=t(\"webgl-context\"),l=t(\"has-passive-events\"),c=t(\"../../registry\"),u=t(\"../../lib\"),f=t(\"../../plots/cartesian/axes\"),h=t(\"../../components/fx\"),p=t(\"../../lib/str2rgbarray\"),d=t(\"../../lib/show_no_webgl_msg\"),g=t(\"./project\"),v=t(\"./layout/convert\"),m=t(\"./layout/spikes\"),y=t(\"./layout/tick_marks\");function x(t,e,r,a){if(t.initializeGLCamera(),!function(t,e,r,a,l){var c={canvas:a,gl:l,container:t.container,axes:t.axesOptions,spikes:t.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1,cameraObject:e,pixelRatio:r};if(t.staticMode){if(!(i||(n=document.createElement(\"canvas\"),i=s({canvas:n,preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"error creating static canvas/context for image server\");c.pixelRatio=t.pixelRatio,c.gl=i,c.canvas=n}try{t.glplot=o(c)}catch(t){return!1}return!0}(t,t.camera,e,r,a))return d(t);var c=t.graphDiv,p=function(t){if(!1!==t.fullSceneLayout.dragmode){var e={};e[t.id+\".camera\"]=T(t.camera),t.saveCamera(c.layout),t.graphDiv.emit(\"plotly_relayout\",e)}};return t.glplot.canvas.addEventListener(\"mouseup\",function(){p(t)}),t.glplot.canvas.addEventListener(\"wheel\",function(){c._context._scrollZoom.gl3d&&p(t)},!!l&&{passive:!1}),t.glplot.canvas.addEventListener(\"mousemove\",function(){if(!1!==t.fullSceneLayout.dragmode&&0!==t.camera.mouseListener.buttons){var e={};e[t.id+\".camera\"]=T(t.camera),t.graphDiv.emit(\"plotly_relayouting\",e)}}),t.staticMode||t.glplot.canvas.addEventListener(\"webglcontextlost\",function(e){c&&c.emit&&c.emit(\"plotly_webglcontextlost\",{event:e,layer:t.id})},!1),t.glplot.camera=t.camera,t.glplot.oncontextloss=function(){t.recoverContext()},t.glplot.onrender=function(t){var e,r=t.graphDiv,n=t.svgContainer,i=t.container.getBoundingClientRect(),a=i.width,o=i.height;n.setAttributeNS(null,\"viewBox\",\"0 0 \"+a+\" \"+o),n.setAttributeNS(null,\"width\",a),n.setAttributeNS(null,\"height\",o),y(t),t.glplot.axes.update(t.axesOptions);for(var s,l=Object.keys(t.traces),c=null,p=t.glplot.selection,d=0;d<l.length;++d)\"skip\"!==(e=t.traces[l[d]]).data.hoverinfo&&e.handlePick(p)&&(c=e),e.setContourLevels&&e.setContourLevels();function v(e,r){var n=t.fullSceneLayout[e];return f.tickText(n,n.d2l(r),\"hover\").text}if(null!==c){var m=g(t.glplot.cameraParams,p.dataCoordinate);e=c.data;var x,b=r._fullData[e.index],_=p.index,w={xLabel:v(\"xaxis\",p.traceCoordinate[0]),yLabel:v(\"yaxis\",p.traceCoordinate[1]),zLabel:v(\"zaxis\",p.traceCoordinate[2])},k=h.castHoverinfo(b,t.fullLayout,_),T=(k||\"\").split(\"+\"),A=k&&\"all\"===k;b.hovertemplate||A||(-1===T.indexOf(\"x\")&&(w.xLabel=void 0),-1===T.indexOf(\"y\")&&(w.yLabel=void 0),-1===T.indexOf(\"z\")&&(w.zLabel=void 0),-1===T.indexOf(\"text\")&&(p.textLabel=void 0),-1===T.indexOf(\"name\")&&(c.name=void 0));var M=[];\"cone\"===e.type||\"streamtube\"===e.type?(w.uLabel=v(\"xaxis\",p.traceCoordinate[3]),(A||-1!==T.indexOf(\"u\"))&&M.push(\"u: \"+w.uLabel),w.vLabel=v(\"yaxis\",p.traceCoordinate[4]),(A||-1!==T.indexOf(\"v\"))&&M.push(\"v: \"+w.vLabel),w.wLabel=v(\"zaxis\",p.traceCoordinate[5]),(A||-1!==T.indexOf(\"w\"))&&M.push(\"w: \"+w.wLabel),w.normLabel=p.traceCoordinate[6].toPrecision(3),(A||-1!==T.indexOf(\"norm\"))&&M.push(\"norm: \"+w.normLabel),\"streamtube\"===e.type&&(w.divergenceLabel=p.traceCoordinate[7].toPrecision(3),(A||-1!==T.indexOf(\"divergence\"))&&M.push(\"divergence: \"+w.divergenceLabel)),p.textLabel&&M.push(p.textLabel),x=M.join(\"<br>\")):\"isosurface\"===e.type||\"volume\"===e.type?(w.valueLabel=f.tickText(t.mockAxis,t.mockAxis.d2l(p.traceCoordinate[3]),\"hover\").text,M.push(\"value: \"+w.valueLabel),p.textLabel&&M.push(p.textLabel),x=M.join(\"<br>\")):x=p.textLabel;var S={x:p.traceCoordinate[0],y:p.traceCoordinate[1],z:p.traceCoordinate[2],data:b._input,fullData:b,curveNumber:b.index,pointNumber:_};h.appendArrayPointValue(S,b,_),e._module.eventData&&(S=b._module.eventData(S,p,b,{},_));var E={points:[S]};t.fullSceneLayout.hovermode&&h.loneHover({trace:b,x:(.5+.5*m[0]/m[3])*a,y:(.5-.5*m[1]/m[3])*o,xLabel:w.xLabel,yLabel:w.yLabel,zLabel:w.zLabel,text:x,name:c.name,color:h.castHoverOption(b,_,\"bgcolor\")||c.color,borderColor:h.castHoverOption(b,_,\"bordercolor\"),fontFamily:h.castHoverOption(b,_,\"font.family\"),fontSize:h.castHoverOption(b,_,\"font.size\"),fontColor:h.castHoverOption(b,_,\"font.color\"),nameLength:h.castHoverOption(b,_,\"namelength\"),textAlign:h.castHoverOption(b,_,\"align\"),hovertemplate:u.castOption(b,_,\"hovertemplate\"),hovertemplateLabels:u.extendFlat({},S,w),eventData:[S]},{container:n,gd:r}),p.buttons&&p.distance<5?r.emit(\"plotly_click\",E):r.emit(\"plotly_hover\",E),s=E}else h.loneUnhover(n),r.emit(\"plotly_unhover\",s);t.drawAnnotations(t)}.bind(null,t),t.traces={},t.make4thDimension(),!0}function b(t,e){var r=document.createElement(\"div\"),n=t.container;this.graphDiv=t.graphDiv;var i=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");i.style.position=\"absolute\",i.style.top=i.style.left=\"0px\",i.style.width=i.style.height=\"100%\",i.style[\"z-index\"]=20,i.style[\"pointer-events\"]=\"none\",r.appendChild(i),this.svgContainer=i,r.id=t.id,r.style.position=\"absolute\",r.style.top=r.style.left=\"0px\",r.style.width=r.style.height=\"100%\",n.appendChild(r),this.fullLayout=e,this.id=t.id||\"scene\",this.fullSceneLayout=e[this.id],this.plotArgs=[[],{},{}],this.axesOptions=v(e,e[this.id]),this.spikeOptions=m(e[this.id]),this.container=r,this.staticMode=!!t.staticPlot,this.pixelRatio=this.pixelRatio||t.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],this.convertAnnotations=c.getComponentMethod(\"annotations3d\",\"convert\"),this.drawAnnotations=c.getComponentMethod(\"annotations3d\",\"draw\"),x(this,this.pixelRatio)}var _=b.prototype;_.initializeGLCamera=function(){var t=this.fullSceneLayout.camera,e=\"orthographic\"===t.projection.type;this.camera=a(this.container,{center:[t.center.x,t.center.y,t.center.z],eye:[t.eye.x,t.eye.y,t.eye.z],up:[t.up.x,t.up.y,t.up.z],_ortho:e,zoomMin:.01,zoomMax:100,mode:\"orbit\"})},_.recoverContext=function(){var t=this,e=this.glplot.gl,r=this.glplot.canvas,n=this.glplot.camera,i=this.glplot.pixelRatio;this.glplot.dispose(),requestAnimationFrame(function a(){e.isContextLost()?requestAnimationFrame(a):x(t,n,i,r)?t.plot.apply(t,t.plotArgs):u.error(\"Catastrophic and unrecoverable WebGL error. Context lost.\")})};var w=[\"xaxis\",\"yaxis\",\"zaxis\"];function k(t,e,r){for(var n=t.fullSceneLayout,i=0;i<3;i++){var a=w[i],o=a.charAt(0),s=n[a],l=e[o],c=e[o+\"calendar\"],f=e[\"_\"+o+\"length\"];if(u.isArrayOrTypedArray(l))for(var h,p=0;p<(f||l.length);p++)if(u.isArrayOrTypedArray(l[p]))for(var d=0;d<l[p].length;++d)h=s.d2l(l[p][d],0,c),!isNaN(h)&&isFinite(h)&&(r[0][i]=Math.min(r[0][i],h),r[1][i]=Math.max(r[1][i],h));else h=s.d2l(l[p],0,c),!isNaN(h)&&isFinite(h)&&(r[0][i]=Math.min(r[0][i],h),r[1][i]=Math.max(r[1][i],h));else r[0][i]=Math.min(r[0][i],0),r[1][i]=Math.max(r[1][i],f-1)}}function T(t){return{up:{x:t.up[0],y:t.up[1],z:t.up[2]},center:{x:t.center[0],y:t.center[1],z:t.center[2]},eye:{x:t.eye[0],y:t.eye[1],z:t.eye[2]},projection:{type:!0===t._ortho?\"orthographic\":\"perspective\"}}}_.plot=function(t,e,r){if(this.plotArgs=[t,e,r],!this.glplot.contextLost){var n,i,a,o,s,l,c=e[this.id],u=r[this.id];c.bgcolor?this.glplot.clearColor=p(c.bgcolor):this.glplot.clearColor=[0,0,0,0],this.glplot.snapToData=!0,this.fullLayout=e,this.fullSceneLayout=c,this.glplotLayout=c,this.axesOptions.merge(e,c),this.spikeOptions.merge(c),this.setCamera(c.camera),this.updateFx(c.dragmode,c.hovermode),this.camera.enableWheel=this.graphDiv._context._scrollZoom.gl3d,this.glplot.update({}),this.setConvert(s),t?Array.isArray(t)||(t=[t]):t=[];var f=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(a=0;a<t.length;++a)!0===(n=t[a]).visible&&0!==n._length&&k(this,n,f);!function(t,e){for(var r=t.fullSceneLayout,n=r.annotations||[],i=0;i<3;i++)for(var a=w[i],o=a.charAt(0),s=r[a],l=0;l<n.length;l++){var c=n[l];if(c.visible){var u=s.r2l(c[o]);!isNaN(u)&&isFinite(u)&&(e[0][i]=Math.min(e[0][i],u),e[1][i]=Math.max(e[1][i],u))}}}(this,f);var h=[1,1,1];for(o=0;o<3;++o)f[1][o]===f[0][o]?h[o]=1:h[o]=1/(f[1][o]-f[0][o]);for(this.dataScale=h,this.convertAnnotations(this),a=0;a<t.length;++a)!0===(n=t[a]).visible&&0!==n._length&&((i=this.traces[n.uid])?i.data.type===n.type?i.update(n):(i.dispose(),i=n._module.plot(this,n),this.traces[n.uid]=i):(i=n._module.plot(this,n),this.traces[n.uid]=i),i.name=n.name);var d=Object.keys(this.traces);t:for(a=0;a<d.length;++a){for(o=0;o<t.length;++o)if(t[o].uid===d[a]&&!0===t[o].visible&&0!==t[o]._length)continue t;(i=this.traces[d[a]]).dispose(),delete this.traces[d[a]]}this.glplot.objects.sort(function(t,e){return t._trace.data.index-e._trace.data.index});var g=[[0,0,0],[0,0,0]],v=[],m={};for(a=0;a<3;++a){if((l=(s=c[w[a]]).type)in m?(m[l].acc*=h[a],m[l].count+=1):m[l]={acc:h[a],count:1},s.autorange){g[0][a]=1/0,g[1][a]=-1/0;var y=this.glplot.objects,x=this.fullSceneLayout.annotations||[],b=s._name.charAt(0);for(o=0;o<y.length;o++){var _=y[o],T=_.bounds,A=_._trace.data._pad||0;\"ErrorBars\"===_.constructor.name&&s._lowerLogErrorBound?g[0][a]=Math.min(g[0][a],s._lowerLogErrorBound):g[0][a]=Math.min(g[0][a],T[0][a]/h[a]-A),g[1][a]=Math.max(g[1][a],T[1][a]/h[a]+A)}for(o=0;o<x.length;o++){var M=x[o];if(M.visible){var S=s.r2l(M[b]);g[0][a]=Math.min(g[0][a],S),g[1][a]=Math.max(g[1][a],S)}}if(\"rangemode\"in s&&\"tozero\"===s.rangemode&&(g[0][a]=Math.min(g[0][a],0),g[1][a]=Math.max(g[1][a],0)),g[0][a]>g[1][a])g[0][a]=-1,g[1][a]=1;else{var E=g[1][a]-g[0][a];g[0][a]-=E/32,g[1][a]+=E/32}if(\"reversed\"===s.autorange){var C=g[0][a];g[0][a]=g[1][a],g[1][a]=C}}else{var L=s.range;g[0][a]=s.r2l(L[0]),g[1][a]=s.r2l(L[1])}g[0][a]===g[1][a]&&(g[0][a]-=1,g[1][a]+=1),v[a]=g[1][a]-g[0][a],this.glplot.bounds[0][a]=g[0][a]*h[a],this.glplot.bounds[1][a]=g[1][a]*h[a]}var z=[1,1,1];for(a=0;a<3;++a){var O=m[l=(s=c[w[a]]).type];z[a]=Math.pow(O.acc,1/O.count)/h[a]}var I;if(\"auto\"===c.aspectmode)I=Math.max.apply(null,z)/Math.min.apply(null,z)<=4?z:[1,1,1];else if(\"cube\"===c.aspectmode)I=[1,1,1];else if(\"data\"===c.aspectmode)I=z;else{if(\"manual\"!==c.aspectmode)throw new Error(\"scene.js aspectRatio was not one of the enumerated types\");var D=c.aspectratio;I=[D.x,D.y,D.z]}c.aspectratio.x=u.aspectratio.x=I[0],c.aspectratio.y=u.aspectratio.y=I[1],c.aspectratio.z=u.aspectratio.z=I[2],this.glplot.aspect=I;var P=c.domain||null,R=e._size||null;if(P&&R){var F=this.container.style;F.position=\"absolute\",F.left=R.l+P.x[0]*R.w+\"px\",F.top=R.t+(1-P.y[1])*R.h+\"px\",F.width=R.w*(P.x[1]-P.x[0])+\"px\",F.height=R.h*(P.y[1]-P.y[0])+\"px\"}this.glplot.redraw()}},_.destroy=function(){this.glplot&&(this.camera.mouseListener.enabled=!1,this.container.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=this.glplot.camera=null,this.glplot.dispose(),this.container.parentNode.removeChild(this.container),this.glplot=null)},_.getCamera=function(){return this.glplot.camera.view.recalcMatrix(this.camera.view.lastT()),T(this.glplot.camera)},_.setCamera=function(t){var e;this.glplot.camera.lookAt.apply(this,[[(e=t).eye.x,e.eye.y,e.eye.z],[e.center.x,e.center.y,e.center.z],[e.up.x,e.up.y,e.up.z]]);var r=\"orthographic\"===t.projection.type;if(r!==this.glplot.camera._ortho){this.glplot.redraw();var n=this.glplot.pixelRatio,i=this.glplot.clearColor;this.glplot.gl.clearColor(i[0],i[1],i[2],i[3]),this.glplot.gl.clear(this.glplot.gl.DEPTH_BUFFER_BIT|this.glplot.gl.COLOR_BUFFER_BIT),this.glplot.dispose(),x(this,n),this.glplot.camera._ortho=r}},_.saveCamera=function(t){var e=this.fullLayout,r=this.getCamera(),n=u.nestedProperty(t,this.id+\".camera\"),i=n.get(),a=!1;function o(t,e,r,n){var i=[\"up\",\"center\",\"eye\"],a=[\"x\",\"y\",\"z\"];return e[i[r]]&&t[i[r]][a[n]]===e[i[r]][a[n]]}if(void 0===i)a=!0;else{for(var s=0;s<3;s++)for(var l=0;l<3;l++)if(!o(r,i,s,l)){a=!0;break}(!i.projection||r.projection&&r.projection.type!==i.projection.type)&&(a=!0)}if(a){var f={};f[this.id+\".camera\"]=i,c.call(\"_storeDirectGUIEdit\",t,e._preGUI,f),n.set(r),u.nestedProperty(e,this.id+\".camera\").set(r)}return a},_.updateFx=function(t,e){var r=this.camera;if(r)if(\"orbit\"===t)r.mode=\"orbit\",r.keyBindingMode=\"rotate\";else 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strict\";e.exports={requiredVersion:\"0.45.0\",styleUrlPrefix:\"mapbox://styles/mapbox/\",styleUrlSuffix:\"v9\",controlContainerClassName:\"mapboxgl-control-container\",wrongVersionErrorMsg:[\"Your custom plotly.js bundle is not using the correct mapbox-gl version\",\"Please install mapbox-gl@0.45.0.\"].join(\"\\n\"),noAccessTokenErrorMsg:[\"Missing Mapbox access token.\",\"Mapbox trace type require a Mapbox access token to be registered.\",\"For example:\",\" Plotly.plot(gd, data, layout, { mapboxAccessToken: 'my-access-token' });\",\"More info here: https://www.mapbox.com/help/define-access-token/\"].join(\"\\n\"),mapOnErrorMsg:\"Mapbox error.\",styleRules:{map:\"overflow:hidden;position:relative;\",\"missing-css\":\"display:none\"}}},{}],805:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e){var r=t.split(\" \"),i=r[0],a=r[1],o=n.isArrayOrTypedArray(e)?n.mean(e):e,s=.5+o/100,l=1.5+o/100,c=[\"\",\"\"],u=[0,0];switch(i){case\"top\":c[0]=\"top\",u[1]=-l;break;case\"bottom\":c[0]=\"bottom\",u[1]=l}switch(a){case\"left\":c[1]=\"right\",u[0]=-s;break;case\"right\":c[1]=\"left\",u[0]=s}return{anchor:c[0]&&c[1]?c.join(\"-\"):c[0]?c[0]:c[1]?c[1]:\"center\",offset:u}}},{\"../../lib\":703}],806:[function(t,e,r){\"use strict\";var n=t(\"mapbox-gl\"),i=t(\"../../lib\"),a=t(\"../../plots/get_data\").getSubplotCalcData,o=t(\"../../constants/xmlns_namespaces\"),s=t(\"./mapbox\"),l=t(\"./constants\");for(var c in l.styleRules)i.addStyleRule(\".mapboxgl-\"+c,l.styleRules[c]);r.name=\"mapbox\",r.attr=\"subplot\",r.idRoot=\"mapbox\",r.idRegex=r.attrRegex=i.counterRegex(\"mapbox\"),r.attributes={subplot:{valType:\"subplotid\",dflt:\"mapbox\",editType:\"calc\"}},r.layoutAttributes=t(\"./layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout_defaults\"),r.plot=function(t){var e=t._fullLayout,r=t.calcdata,o=e._subplots.mapbox;if(n.version!==l.requiredVersion)throw new Error(l.wrongVersionErrorMsg);var c=function(t,e){var r=t._fullLayout;if(\"\"===t._context.mapboxAccessToken)return\"\";for(var n=0;n<e.length;n++){var i=r[e[n]];if(i.accesstoken)return i.accesstoken}throw new Error(l.noAccessTokenErrorMsg)}(t,o);n.accessToken=c;for(var u=0;u<o.length;u++){var f=o[u],h=a(r,\"mapbox\",f),p=e[f],d=p._subplot;d||(d=s({gd:t,container:e._glcontainer.node(),id:f,fullLayout:e,staticPlot:t._context.staticPlot}),e[f]._subplot=d),d.viewInitial||(d.viewInitial={center:i.extendFlat({},p.center),zoom:p.zoom,bearing:p.bearing,pitch:p.pitch}),d.plot(h,e,t._promises)}},r.clean=function(t,e,r,n){for(var i=n._subplots.mapbox||[],a=0;a<i.length;a++){var o=i[a];!e[o]&&n[o]._subplot&&n[o]._subplot.destroy()}},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.mapbox,n=e._size,i=0;i<r.length;i++){var a=e[r[i]],s=a.domain,l=a._subplot,c=l.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":c,x:n.l+n.w*s.x[0],y:n.t+n.h*(1-s.y[1]),width:n.w*(s.x[1]-s.x[0]),height:n.h*(s.y[1]-s.y[0]),preserveAspectRatio:\"none\"}),l.destroy()}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.mapbox,n=0;n<r.length;n++){e[r[n]]._subplot.updateFx(e)}}},{\"../../constants/xmlns_namespaces\":681,\"../../lib\":703,\"../../plots/get_data\":786,\"./constants\":804,\"./layout_attributes\":808,\"./layout_defaults\":809,\"./mapbox\":810,\"mapbox-gl\":421}],807:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./convert_text_opts\");function a(t,e){this.mapbox=t,this.map=t.map,this.uid=t.uid+\"-layer\"+e,this.idSource=this.uid+\"-source\",this.idLayer=this.uid+\"-layer\",this.sourceType=null,this.source=null,this.layerType=null,this.below=null,this.visible=!1}var o=a.prototype;function s(t){var e=t.source;return t.visible&&(n.isPlainObject(e)||\"string\"==typeof e&&e.length>0)}function l(t){var e={},r={};switch(t.type){case\"circle\":n.extendFlat(r,{\"circle-radius\":t.circle.radius,\"circle-color\":t.color,\"circle-opacity\":t.opacity});break;case\"line\":n.extendFlat(r,{\"line-width\":t.line.width,\"line-color\":t.color,\"line-opacity\":t.opacity,\"line-dasharray\":t.line.dash});break;case\"fill\":n.extendFlat(r,{\"fill-color\":t.color,\"fill-outline-color\":t.fill.outlinecolor,\"fill-opacity\":t.opacity});break;case\"symbol\":var a=t.symbol,o=i(a.textposition,a.iconsize);n.extendFlat(e,{\"icon-image\":a.icon+\"-15\",\"icon-size\":a.iconsize/10,\"text-field\":a.text,\"text-size\":a.textfont.size,\"text-anchor\":o.anchor,\"text-offset\":o.offset,\"symbol-placement\":a.placement}),n.extendFlat(r,{\"icon-color\":t.color,\"text-color\":a.textfont.color,\"text-opacity\":t.opacity})}return{layout:e,paint:r}}o.update=function(t){this.visible?this.needsNewSource(t)?(this.removeLayer(),this.updateSource(t),this.updateLayer(t)):this.needsNewLayer(t)?this.updateLayer(t):this.updateStyle(t):(this.updateSource(t),this.updateLayer(t)),this.visible=s(t)},o.needsNewSource=function(t){return this.sourceType!==t.sourcetype||this.source!==t.source||this.layerType!==t.type},o.needsNewLayer=function(t){return this.layerType!==t.type||this.below!==t.below},o.updateSource=function(t){var e=this.map;if(e.getSource(this.idSource)&&e.removeSource(this.idSource),this.sourceType=t.sourcetype,this.source=t.source,s(t)){var r=function(t){var e,r=t.sourcetype,n=t.source,i={type:r};\"geojson\"===r?e=\"data\":\"vector\"===r&&(e=\"string\"==typeof n?\"url\":\"tiles\");return i[e]=n,i}(t);e.addSource(this.idSource,r)}},o.updateLayer=function(t){var e=this.map,r=l(t);this.removeLayer(),this.layerType=t.type,s(t)&&e.addLayer({id:this.idLayer,source:this.idSource,\"source-layer\":t.sourcelayer||\"\",type:t.type,minzoom:t.minzoom,maxzoom:t.maxzoom,layout:r.layout,paint:r.paint},t.below)},o.updateStyle=function(t){if(s(t)){var e=l(t);this.mapbox.setOptions(this.idLayer,\"setLayoutProperty\",e.layout),this.mapbox.setOptions(this.idLayer,\"setPaintProperty\",e.paint)}},o.removeLayer=function(){var t=this.map;t.getLayer(this.idLayer)&&t.removeLayer(this.idLayer)},o.dispose=function(){var t=this.map;t.removeLayer(this.idLayer),t.removeSource(this.idSource)},e.exports=function(t,e,r){var n=new a(t,e);return n.update(r),n}},{\"../../lib\":703,\"./convert_text_opts\":805}],808:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/color\").defaultLine,a=t(\"../domain\").attributes,o=t(\"../font_attributes\"),s=t(\"../../traces/scatter/attributes\").textposition,l=t(\"../../plot_api/edit_types\").overrideAll,c=t(\"../../plot_api/plot_template\").templatedArray,u=o({});u.family.dflt=\"Open Sans Regular, Arial Unicode MS 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a=r(\"type\");r(\"below\"),r(\"color\"),r(\"opacity\"),r(\"minzoom\"),r(\"maxzoom\"),\"circle\"===a&&r(\"circle.radius\"),\"line\"===a&&(r(\"line.width\"),r(\"line.dash\")),\"fill\"===a&&r(\"fill.outlinecolor\"),\"symbol\"===a&&(r(\"symbol.icon\"),r(\"symbol.iconsize\"),r(\"symbol.text\"),n.coerceFont(r,\"symbol.textfont\"),r(\"symbol.textposition\"),r(\"symbol.placement\"))}}e.exports=function(t,e,r){i(t,e,r,{type:\"mapbox\",attributes:o,handleDefaults:s,partition:\"y\",accessToken:e._mapboxAccessToken})}},{\"../../lib\":703,\"../array_container_defaults\":747,\"../subplot_defaults\":826,\"./layout_attributes\":808}],810:[function(t,e,r){\"use strict\";var n=t(\"mapbox-gl\"),i=t(\"../../components/fx\"),a=t(\"../../lib\"),o=t(\"../../registry\"),s=t(\"../../components/dragelement\"),l=t(\"../cartesian/select\").prepSelect,c=t(\"../cartesian/select\").selectOnClick,u=t(\"./constants\"),f=t(\"./layout_attributes\"),h=t(\"./layers\");function p(t){this.id=t.id,this.gd=t.gd,this.container=t.container,this.isStatic=t.staticPlot;var e=t.fullLayout;this.uid=e._uid+\"-\"+this.id,this.div=null,this.xaxis=null,this.yaxis=null,this.createFramework(e),this.map=null,this.accessToken=null,this.styleObj=null,this.traceHash={},this.layerList=[]}var d=p.prototype;function g(t){var e=f.style.values,r=f.style.dflt,n={};return a.isPlainObject(t)?(n.id=t.id,n.style=t):\"string\"==typeof t?(n.id=t,n.style=-1!==e.indexOf(t)?v(t):t):(n.id=r,n.style=v(r)),n.transition={duration:0,delay:0},n}function v(t){return u.styleUrlPrefix+t+\"-\"+u.styleUrlSuffix}function m(t){return[t.lon,t.lat]}e.exports=function(t){return new p(t)},d.plot=function(t,e,r){var n,i=this,a=e[i.id];i.map&&a.accesstoken!==i.accessToken&&(i.map.remove(),i.map=null,i.styleObj=null,i.traceHash=[],i.layerList={}),n=i.map?new Promise(function(r,n){i.updateMap(t,e,r,n)}):new Promise(function(r,n){i.createMap(t,e,r,n)}),r.push(n)},d.createMap=function(t,e,r,a){var 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s=i({},t.layout);if([[s,[\"plot_bgcolor\"],[\"backgroundColor\"]],[s,[\"showlegend\"],[\"showLegend\"]],[s,[\"radialaxis\"],[\"radialAxis\"]],[s,[\"angularaxis\"],[\"angularAxis\"]],[s.angularaxis,[\"showline\"],[\"gridLinesVisible\"]],[s.angularaxis,[\"showticklabels\"],[\"labelsVisible\"]],[s.angularaxis,[\"nticks\"],[\"ticksCount\"]],[s.angularaxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.angularaxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.angularaxis,[\"range\"],[\"domain\"]],[s.angularaxis,[\"endpadding\"],[\"endPadding\"]],[s.radialaxis,[\"showline\"],[\"gridLinesVisible\"]],[s.radialaxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.radialaxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.radialaxis,[\"range\"],[\"domain\"]],[s.angularAxis,[\"showline\"],[\"gridLinesVisible\"]],[s.angularAxis,[\"showticklabels\"],[\"labelsVisible\"]],[s.angularAxis,[\"nticks\"],[\"ticksCount\"]],[s.angularAxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.angularAxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.angularAxis,[\"range\"],[\"domain\"]],[s.angularAxis,[\"endpadding\"],[\"endPadding\"]],[s.radialAxis,[\"showline\"],[\"gridLinesVisible\"]],[s.radialAxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.radialAxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.radialAxis,[\"range\"],[\"domain\"]],[s.font,[\"outlinecolor\"],[\"outlineColor\"]],[s.legend,[\"traceorder\"],[\"reverseOrder\"]],[s,[\"labeloffset\"],[\"labelOffset\"]],[s,[\"defaultcolorrange\"],[\"defaultColorRange\"]]].forEach(function(t,r){o.util.translator.apply(null,t.concat(e))}),e?(\"undefined\"!=typeof 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n=t(\"d3\"),i=t(\"tinycolor2\"),a=t(\"../../registry\"),o=t(\"../../lib\"),s=t(\"../../components/color\"),l=t(\"../../components/drawing\"),c=t(\"../plots\"),u=t(\"../../plots/cartesian/axes\"),f=t(\"../cartesian/set_convert\"),h=t(\"./set_convert\"),p=t(\"../cartesian/autorange\").doAutoRange,d=t(\"../cartesian/dragbox\"),g=t(\"../../components/dragelement\"),v=t(\"../../components/fx\"),m=t(\"../../components/titles\"),y=t(\"../cartesian/select\").prepSelect,x=t(\"../cartesian/select\").selectOnClick,b=t(\"../cartesian/select\").clearSelect,_=t(\"../../lib/setcursor\"),w=t(\"../../lib/clear_gl_canvases\"),k=t(\"../../plot_api/subroutines\").redrawReglTraces,T=t(\"../../constants/alignment\").MID_SHIFT,A=t(\"./constants\"),M=t(\"./helpers\"),S=o._,E=o.mod,C=o.deg2rad,L=o.rad2deg;function z(t,e){this.id=e,this.gd=t,this._hasClipOnAxisFalse=null,this.vangles=null,this.radialAxisAngle=null,this.traceHash={},this.layers={},this.clipPaths={},this.clipIds={},this.viewInitial={};var r=t._fullLayout,n=\"clip\"+r._uid+e;this.clipIds.forTraces=n+\"-for-traces\",this.clipPaths.forTraces=r._clips.append(\"clipPath\").attr(\"id\",this.clipIds.forTraces),this.clipPaths.forTraces.append(\"path\"),this.framework=r._polarlayer.append(\"g\").attr(\"class\",e),this.radialTickLayout=null,this.angularTickLayout=null}var O=z.prototype;function I(t){var e=t.ticks+String(t.ticklen)+String(t.showticklabels);return\"side\"in t&&(e+=t.side),e}function D(t,e){return e[o.findIndexOfMin(e,function(e){return o.angleDist(t,e)})]}function P(t,e,r){return e?(t.attr(\"display\",null),t.attr(r)):t&&t.attr(\"display\",\"none\"),t}function R(t,e){return\"translate(\"+t+\",\"+e+\")\"}function F(t){return\"rotate(\"+t+\")\"}e.exports=function(t,e){return new z(t,e)},O.plot=function(t,e){var r=e[this.id];this._hasClipOnAxisFalse=!1;for(var 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e,r,n,i,a=t[0],o=t[1]-a,s=E(a,360),l=s+o,c=Math.cos(C(s)),u=Math.sin(C(s)),f=Math.cos(C(l)),h=Math.sin(C(l));i=s<=90&&l>=90||s>90&&l>=450?1:u<=0&&h<=0?0:Math.max(u,h);e=s<=180&&l>=180||s>180&&l>=540?-1:c>=0&&f>=0?0:Math.min(c,f);r=s<=270&&l>=270||s>270&&l>=630?-1:u>=0&&h>=0?0:Math.min(u,h);n=l>=360?1:c<=0&&f<=0?0:Math.max(c,f);return[e,r,n,i]}(h),x=y[2]-y[0],b=y[3]-y[1],_=f/u,w=Math.abs(b/x);_>w?(p=u,m=(f-(d=u*w))/n.h/2,g=[o[0],o[1]],v=[c[0]+m,c[1]-m]):(d=f,m=(u-(p=f/w))/n.w/2,g=[o[0]+m,o[1]-m],v=[c[0],c[1]]),this.xLength2=p,this.yLength2=d,this.xDomain2=g,this.yDomain2=v;var k=this.xOffset2=n.l+n.w*g[0],T=this.yOffset2=n.t+n.h*(1-v[1]),A=this.radius=p/x,M=this.innerRadius=e.hole*A,S=this.cx=k-A*y[0],L=this.cy=T+A*y[3],z=this.cxx=S-k,O=this.cyy=L-T;this.radialAxis=this.mockAxis(t,e,i,{_id:\"x\",side:{counterclockwise:\"top\",clockwise:\"bottom\"}[i.side],domain:[M/n.w,A/n.w]}),this.angularAxis=this.mockAxis(t,e,a,{side:\"right\",domain:[0,Math.PI],autorange:!1}),this.doAutoRange(t,e),this.updateAngularAxis(t,e),this.updateRadialAxis(t,e),this.updateRadialAxisTitle(t,e),this.xaxis=this.mockCartesianAxis(t,e,{_id:\"x\",domain:g}),this.yaxis=this.mockCartesianAxis(t,e,{_id:\"y\",domain:v});var I=this.pathSubplot();this.clipPaths.forTraces.select(\"path\").attr(\"d\",I).attr(\"transform\",R(z,O)),r.frontplot.attr(\"transform\",R(k,T)).call(l.setClipUrl,this._hasClipOnAxisFalse?null:this.clipIds.forTraces,this.gd),r.bg.attr(\"d\",I).attr(\"transform\",R(S,L)).call(s.fill,e.bgcolor)},O.mockAxis=function(t,e,r,n){var i=o.extendFlat({anchor:\"free\",position:0},r,n);return h(i,e,t),i},O.mockCartesianAxis=function(t,e,r){var n=this,i=r._id,a=o.extendFlat({type:\"linear\"},r);f(a,t);var s={x:[0,2],y:[1,3]};return a.setRange=function(){var t=n.sectorBBox,r=s[i],o=n.radialAxis._rl,l=(o[1]-o[0])/(1-e.hole);a.range=[t[r[0]]*l,t[r[1]]*l]},a.isPtWithinRange=\"x\"===i?function(t){return n.isPtInside(t)}:function(){return!0},a.setRange(),a.setScale(),a},O.doAutoRange=function(t,e){var r=this.gd,n=this.radialAxis,i=e.radialaxis;n.setScale(),p(r,n);var a=n.range;i.range=a.slice(),i._input.range=a.slice(),n._rl=[n.r2l(a[0],null,\"gregorian\"),n.r2l(a[1],null,\"gregorian\")]},O.updateRadialAxis=function(t,e){var r=this,n=r.gd,i=r.layers,a=r.radius,l=r.innerRadius,c=r.cx,f=r.cy,h=e.radialaxis,p=E(e.sector[0],360),d=r.radialAxis,g=l<a;r.fillViewInitialKey(\"radialaxis.angle\",h.angle),r.fillViewInitialKey(\"radialaxis.range\",d.range.slice()),d.setGeometry(),\"auto\"===d.tickangle&&p>90&&p<=270&&(d.tickangle=180);var v=function(t){return\"translate(\"+(d.l2p(t.x)+l)+\",0)\"},m=I(h);if(r.radialTickLayout!==m&&(i[\"radial-axis\"].selectAll(\".xtick\").remove(),r.radialTickLayout=m),g){d.setScale();var y=u.calcTicks(d),x=u.clipEnds(d,y),b=u.getTickSigns(d)[2];u.drawTicks(n,d,{vals:y,layer:i[\"radial-axis\"],path:u.makeTickPath(d,0,b),transFn:v,crisp:!1}),u.drawGrid(n,d,{vals:x,layer:i[\"radial-grid\"],path:function(t){return r.pathArc(d.r2p(t.x)+l)},transFn:o.noop,crisp:!1}),u.drawLabels(n,d,{vals:y,layer:i[\"radial-axis\"],transFn:v,labelFns:u.makeLabelFns(d,0)})}var 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r=this,n=r.gd,i=r.layers,a=r.radius,l=r.innerRadius,c=r.cx,f=r.cy,h=e.angularaxis,p=r.angularAxis;r.fillViewInitialKey(\"angularaxis.rotation\",h.rotation),p.setGeometry(),p.setScale();var d=function(t){return p.t2g(t.x)};\"linear\"===p.type&&\"radians\"===p.thetaunit&&(p.tick0=L(p.tick0),p.dtick=L(p.dtick));var g=function(t){return R(c+a*Math.cos(t),f-a*Math.sin(t))},v=u.makeLabelFns(p,0).labelStandoff,m={xFn:function(t){var e=d(t);return Math.cos(e)*v},yFn:function(t){var e=d(t),r=Math.sin(e)>0?.2:1;return-Math.sin(e)*(v+t.fontSize*r)+Math.abs(Math.cos(e))*(t.fontSize*T)},anchorFn:function(t){var e=d(t),r=Math.cos(e);return Math.abs(r)<.1?\"middle\":r>0?\"start\":\"end\"},heightFn:function(t,e,r){var n=d(t);return-.5*(1+Math.sin(n))*r}},y=I(h);r.angularTickLayout!==y&&(i[\"angular-axis\"].selectAll(\".\"+p._id+\"tick\").remove(),r.angularTickLayout=y);var x,b=u.calcTicks(p);if(\"linear\"===e.gridshape?(x=b.map(d),o.angleDelta(x[0],x[1])<0&&(x=x.slice().reverse())):x=null,r.vangles=x,\"category\"===p.type&&(b=b.filter(function(t){return o.isAngleInsideSector(d(t),r.sectorInRad)})),p.visible){var _=\"inside\"===p.ticks?-1:1,w=(p.linewidth||1)/2;u.drawTicks(n,p,{vals:b,layer:i[\"angular-axis\"],path:\"M\"+_*w+\",0h\"+_*p.ticklen,transFn:function(t){var e=d(t);return g(e)+F(-L(e))},crisp:!1}),u.drawGrid(n,p,{vals:b,layer:i[\"angular-grid\"],path:function(t){var e=d(t),r=Math.cos(e),n=Math.sin(e);return\"M\"+[c+l*r,f-l*n]+\"L\"+[c+a*r,f-a*n]},transFn:o.noop,crisp:!1}),u.drawLabels(n,p,{vals:b,layer:i[\"angular-axis\"],repositionOnUpdate:!0,transFn:function(t){return g(d(t))},labelFns:m})}P(i[\"angular-line\"].select(\"path\"),h.showline,{d:r.pathSubplot(),transform:R(c,f)}).attr(\"stroke-width\",h.linewidth).call(s.stroke,h.linecolor)},O.updateFx=function(t,e){this.gd._context.staticPlot||(this.updateAngularDrag(t),this.updateRadialDrag(t,e,0),this.updateRadialDrag(t,e,1),this.updateMainDrag(t))},O.updateMainDrag=function(t){var e=this,r=e.gd,o=e.layers,s=t._zoomlayer,l=A.MINZOOM,c=A.OFFEDGE,u=e.radius,f=e.innerRadius,h=e.cx,p=e.cy,m=e.cxx,_=e.cyy,w=e.sectorInRad,k=e.vangles,T=e.radialAxis,S=M.clampTiny,E=M.findXYatLength,C=M.findEnclosingVertexAngles,L=A.cornerHalfWidth,z=A.cornerLen/2,O=d.makeDragger(o,\"path\",\"maindrag\",\"crosshair\");n.select(O).attr(\"d\",e.pathSubplot()).attr(\"transform\",R(h,p));var I,D,P,F,B,N,j,V,U,H={element:O,gd:r,subplot:e.id,plotinfo:{id:e.id,xaxis:e.xaxis,yaxis:e.yaxis},xaxes:[e.xaxis],yaxes:[e.yaxis]};function q(t,e){return Math.sqrt(t*t+e*e)}function G(t,e){return q(t-m,e-_)}function Y(t,e){return Math.atan2(_-e,t-m)}function W(t,e){return[t*Math.cos(e),t*Math.sin(-e)]}function X(t,r){if(0===t)return e.pathSector(2*L);var n=z/t,i=r-n,a=r+n,o=Math.max(0,Math.min(t,u)),s=o-L,l=o+L;return\"M\"+W(s,i)+\"A\"+[s,s]+\" 0,0,0 \"+W(s,a)+\"L\"+W(l,a)+\"A\"+[l,l]+\" 0,0,1 \"+W(l,i)+\"Z\"}function Z(t,r,n){if(0===t)return e.pathSector(2*L);var i,a,o=W(t,r),s=W(t,n),l=S((o[0]+s[0])/2),c=S((o[1]+s[1])/2);if(l&&c){var u=c/l,f=-1/u,h=E(L,u,l,c);i=E(z,f,h[0][0],h[0][1]),a=E(z,f,h[1][0],h[1][1])}else{var p,d;c?(p=z,d=L):(p=L,d=z),i=[[l-p,c-d],[l+p,c-d]],a=[[l-p,c+d],[l+p,c+d]]}return\"M\"+i.join(\"L\")+\"L\"+a.reverse().join(\"L\")+\"Z\"}function $(t,e){return e=Math.max(Math.min(e,u),f),t<c?t=0:u-t<c?t=u:e<c?e=0:u-e<c&&(e=u),Math.abs(e-t)>l?(t<e?(P=t,F=e):(P=e,F=t),!0):(P=null,F=null,!1)}function J(t,e){t=t||B,e=e||\"M0,0Z\",V.attr(\"d\",t),U.attr(\"d\",e),d.transitionZoombox(V,U,N,j),N=!0;var n={};rt(n),r.emit(\"plotly_relayouting\",n)}function K(t,r){var n,i,a=I+t,o=D+r,s=G(I,D),l=Math.min(G(a,o),u),c=Y(I,D);$(s,l)&&(n=B+e.pathSector(F),P&&(n+=e.pathSector(P)),i=X(P,c)+X(F,c)),J(n,i)}function Q(t,e,r,n){var i=M.findIntersectionXY(r,n,r,[t-m,_-e]);return q(i[0],i[1])}function tt(t,r){var n,i,a=I+t,o=D+r,s=Y(I,D),l=Y(a,o),c=C(s,k),f=C(l,k);$(Q(I,D,c[0],c[1]),Math.min(Q(a,o,f[0],f[1]),u))&&(n=B+e.pathSector(F),P&&(n+=e.pathSector(P)),i=[Z(P,c[0],c[1]),Z(F,c[0],c[1])].join(\" \")),J(n,i)}function et(){if(d.removeZoombox(r),null!==P&&null!==F){var t={};rt(t),d.showDoubleClickNotifier(r),a.call(\"_guiRelayout\",r,t)}}function rt(t){var r=T._rl,n=(r[1]-r[0])/(1-f/u)/u,i=[r[0]+(P-f)*n,r[0]+(F-f)*n];t[e.id+\".radialaxis.range\"]=i}function nt(t,n){var i=r._fullLayout.clickmode;if(d.removeZoombox(r),2===t){var o={};for(var s in e.viewInitial)o[e.id+\".\"+s]=e.viewInitial[s];r.emit(\"plotly_doubleclick\",null),a.call(\"_guiRelayout\",r,o)}i.indexOf(\"select\")>-1&&1===t&&x(n,r,[e.xaxis],[e.yaxis],e.id,H),i.indexOf(\"event\")>-1&&v.click(r,n,e.id)}H.prepFn=function(t,n,a){var o=r._fullLayout.dragmode,l=O.getBoundingClientRect();if(I=n-l.left,D=a-l.top,k){var c=M.findPolygonOffset(u,w[0],w[1],k);I+=m+c[0],D+=_+c[1]}switch(o){case\"zoom\":H.moveFn=k?tt:K,H.clickFn=nt,H.doneFn=et,function(){P=null,F=null,B=e.pathSubplot(),N=!1;var t=r._fullLayout[e.id];j=i(t.bgcolor).getLuminance(),(V=d.makeZoombox(s,j,h,p,B)).attr(\"fill-rule\",\"evenodd\"),U=d.makeCorners(s,h,p),b(r)}();break;case\"select\":case\"lasso\":y(t,n,a,H,o)}},O.onmousemove=function(t){v.hover(r,t,e.id),r._fullLayout._lasthover=O,r._fullLayout._hoversubplot=e.id},O.onmouseout=function(t){r._dragging||g.unhover(r,t)},g.init(H)},O.updateRadialDrag=function(t,e,r){var i=this,s=i.gd,l=i.layers,c=i.radius,u=i.innerRadius,f=i.cx,h=i.cy,p=i.radialAxis,v=A.radialDragBoxSize,m=v/2;if(p.visible){var y,x,_,T=C(i.radialAxisAngle),M=p._rl,S=M[0],E=M[1],z=M[r],O=.75*(M[1]-M[0])/(1-e.hole)/c;r?(y=f+(c+m)*Math.cos(T),x=h-(c+m)*Math.sin(T),_=\"radialdrag\"):(y=f+(u-m)*Math.cos(T),x=h-(u-m)*Math.sin(T),_=\"radialdrag-inner\");var I,B,N,j=d.makeRectDragger(l,_,\"crosshair\",-m,-m,v,v),V={element:j,gd:s};P(n.select(j),p.visible&&u<c,{transform:R(y,x)}),V.prepFn=function(){I=null,B=null,N=null,V.moveFn=U,V.doneFn=H,b(s)},V.clampFn=function(t,e){return Math.sqrt(t*t+e*e)<A.MINDRAG&&(t=0,e=0),[t,e]},g.init(V)}function U(t,e){if(I)I(t,e);else{var n=[t,-e],a=[Math.cos(T),Math.sin(T)],l=Math.abs(o.dot(n,a)/Math.sqrt(o.dot(n,n)));isNaN(l)||(I=l<.5?q:G)}var c={};!function(t){null!==B?t[i.id+\".radialaxis.angle\"]=B:null!==N&&(t[i.id+\".radialaxis.range[\"+r+\"]\"]=N)}(c),s.emit(\"plotly_relayouting\",c)}function 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n=t(\"../../components/color/attributes\"),i=t(\"../domain\").attributes,a=t(\"../cartesian/layout_attributes\"),o=t(\"../../plot_api/edit_types\").overrideAll,s=t(\"../../lib/extend\").extendFlat,l={title:a.title,color:a.color,tickmode:a.tickmode,nticks:s({},a.nticks,{dflt:6,min:1}),tick0:a.tick0,dtick:a.dtick,tickvals:a.tickvals,ticktext:a.ticktext,ticks:a.ticks,ticklen:a.ticklen,tickwidth:a.tickwidth,tickcolor:a.tickcolor,showticklabels:a.showticklabels,showtickprefix:a.showtickprefix,tickprefix:a.tickprefix,showticksuffix:a.showticksuffix,ticksuffix:a.ticksuffix,showexponent:a.showexponent,exponentformat:a.exponentformat,separatethousands:a.separatethousands,tickfont:a.tickfont,tickangle:a.tickangle,tickformat:a.tickformat,tickformatstops:a.tickformatstops,hoverformat:a.hoverformat,showline:s({},a.showline,{dflt:!0}),linecolor:a.linecolor,linewidth:a.linewidth,showgrid:s({},a.showgrid,{dflt:!0}),gridcolor:a.gridcolor,gridwidth:a.gridwidth,layer:a.layer,min:{valType:\"number\",dflt:0,min:0},_deprecated:{title:a._deprecated.title,titlefont:a._deprecated.titlefont}},c=e.exports=o({domain:i({name:\"ternary\"}),bgcolor:{valType:\"color\",dflt:n.background},sum:{valType:\"number\",dflt:1,min:0},aaxis:l,baxis:l,caxis:l},\"plot\",\"from-root\");c.uirevision={valType:\"any\",editType:\"none\"},c.aaxis.uirevision=c.baxis.uirevision=c.caxis.uirevision={valType:\"any\",editType:\"none\"}},{\"../../components/color/attributes\":579,\"../../lib/extend\":693,\"../../plot_api/edit_types\":734,\"../cartesian/layout_attributes\":763,\"../domain\":776}],829:[function(t,e,r){\"use 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n=t(\"d3\"),i=t(\"tinycolor2\"),a=t(\"../../registry\"),o=t(\"../../lib\"),s=o._,l=t(\"../../components/color\"),c=t(\"../../components/drawing\"),u=t(\"../cartesian/set_convert\"),f=t(\"../../lib/extend\").extendFlat,h=t(\"../plots\"),p=t(\"../cartesian/axes\"),d=t(\"../../components/dragelement\"),g=t(\"../../components/fx\"),v=t(\"../../components/titles\"),m=t(\"../cartesian/select\").prepSelect,y=t(\"../cartesian/select\").selectOnClick,x=t(\"../cartesian/select\").clearSelect,b=t(\"../cartesian/constants\");function _(t,e){this.id=t.id,this.graphDiv=t.graphDiv,this.init(e),this.makeFramework(e),this.aTickLayout=null,this.bTickLayout=null,this.cTickLayout=null}e.exports=_;var w=_.prototype;w.init=function(t){this.container=t._ternarylayer,this.defs=t._defs,this.layoutId=t._uid,this.traceHash={},this.layers={}},w.plot=function(t,e){var r=e[this.id],n=e._size;this._hasClipOnAxisFalse=!1;for(var i=0;i<t.length;i++){if(!1===t[i][0].trace.cliponaxis){this._hasClipOnAxisFalse=!0;break}}this.updateLayers(r),this.adjustLayout(r,n),h.generalUpdatePerTraceModule(this.graphDiv,this,t,r),this.layers.plotbg.select(\"path\").call(l.fill,r.bgcolor)},w.makeFramework=function(t){var e=this.graphDiv,r=t[this.id],n=this.clipId=\"clip\"+this.layoutId+this.id,i=this.clipIdRelative=\"clip-relative\"+this.layoutId+this.id;this.clipDef=o.ensureSingleById(t._clips,\"clipPath\",n,function(t){t.append(\"path\").attr(\"d\",\"M0,0Z\")}),this.clipDefRelative=o.ensureSingleById(t._clips,\"clipPath\",i,function(t){t.append(\"path\").attr(\"d\",\"M0,0Z\")}),this.plotContainer=o.ensureSingle(this.container,\"g\",this.id),this.updateLayers(r),c.setClipUrl(this.layers.backplot,n,e),c.setClipUrl(this.layers.grids,n,e)},w.updateLayers=function(t){var e=this.layers,r=[\"draglayer\",\"plotbg\",\"backplot\",\"grids\"];\"below traces\"===t.aaxis.layer&&r.push(\"aaxis\",\"aline\"),\"below 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p={mode:i.barmode,norm:i.barnorm,gap:i.bargap,groupgap:i.bargroupgap};u(t,r,n,c,p),u(t,n,r,l,p)},setGroupPositions:u}},{\"../../constants/numerical\":680,\"../../lib\":703,\"../../plots/cartesian/axes\":751,\"../../plots/cartesian/axis_ids\":754,\"../../registry\":831,\"./sieve.js\":853,\"fast-isnumeric\":224}],845:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/color\"),a=t(\"../../registry\"),o=t(\"../scatter/xy_defaults\"),s=t(\"./style_defaults\"),l=t(\"../../plots/cartesian/axis_ids\").getAxisGroup,c=t(\"./attributes\"),u=n.coerceFont;function f(t,e,r,n){var i=e.orientation,a=e[{v:\"x\",h:\"y\"}[i]+\"axis\"],o=l(r,a)+i,s=r._alignmentOpts||{},c=n(\"alignmentgroup\"),u=s[o];u||(u=s[o]={});var f=u[c];f?f.traces.push(e):f=u[c]={traces:[e],alignmentIndex:Object.keys(u).length,offsetGroups:{}};var h=n(\"offsetgroup\"),p=f.offsetGroups,d=p[h];h&&(d||(d=p[h]={offsetIndex:Object.keys(p).length}),e._offsetIndex=d.offsetIndex)}function h(t,e,r,i,a,o){var 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C=\"stack\"===y.mode||\"relative\"===y.mode,L=n[i],z=!C||L._outmost;if(E&&\"none\"!==_&&(!L.isBlank&&s!==c&&p!==m||\"auto\"!==_&&\"inside\"!==_)){var O=T.font,I=f.getBarColor(n[i],M),D=f.getInsideTextFont(M,i,O,I),P=f.getOutsideTextFont(M,i,O),R=r.datum();S?\"log\"===w.type&&R.s0<=0&&(s=w.range[0]<w.range[1]?0:w._length):\"log\"===k.type&&R.s0<=0&&(p=k.range[0]<k.range[1]?k._length:0);var F,B,N,j,V,U,H=Math.abs(c-s)-2*v,q=Math.abs(m-p)-2*v;if(\"outside\"===_&&(z||L.hasB||(_=\"inside\")),\"auto\"===_)if(z){_=\"inside\",F=A(r,E,D),B=l.bBox(F.node()),N=B.width,j=B.height;var G=N>0&&j>0,Y=N<=H&&j<=q,W=N<=q&&j<=H,X=S?H>=N*(q/j):q>=j*(H/N);G&&(Y||W||X)?_=\"inside\":(_=\"outside\",F.remove(),F=null)}else 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y=f[\"violin\"===t?\"_numViolins\":\"_numBoxes\"],x=\"group\"===f[t+\"mode\"]&&y>1,b=1-f[t+\"gap\"],_=1-f[t+\"groupgap\"];for(s=0;s<r.length;s++){var w,k,T,A,M,S,E=(c=u[r[s]])[0].trace,C=c[0].t,L=E.width,z=E.side;if(L)w=k=A=L/2,T=0;else if(w=m,x){var O=a(f,o._id)+E.orientation,I=(f._alignmentOpts[O]||{})[E.alignmentgroup]||{},D=Object.keys(I.offsetGroups||{}).length,P=D||y;k=w*b*_/P,T=2*w*(((D?E._offsetIndex:C.num)+.5)/P-.5)*b,A=w*b/P}else k=w*b*_,T=0,A=w;C.dPos=w,C.bPos=T,C.bdPos=k,C.wHover=A;var R,F,B,N,j,V,U=T+k,H=Boolean(L);if(\"positive\"===z?(M=w*(L?1:.5),R=U,S=R=T):\"negative\"===z?(M=R=T,S=w*(L?1:.5),F=U):(M=S=w,R=F=U),(E.boxpoints||E.points)&&g>0){var q=E.pointpos,G=E.jitter,Y=E.marker.size/2,W=0;q+G>=0&&((W=U*(q+G))>M?(H=!0,j=Y,B=W):W>R&&(j=Y,B=M)),W<=M&&(B=M);var X=0;q-G<=0&&((X=-U*(q-G))>S?(H=!0,V=Y,N=X):X>F&&(V=Y,N=S)),X<=S&&(N=S)}else B=M,N=S;var Z=new 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u=r(\"hoveron\");\"all\"!==u&&-1===u.indexOf(\"points\")||r(\"hovertemplate\"),n.coerceSelectionMarkerOpacity(e,r)}e.exports={supplyDefaults:function(t,e,r,i){function o(r,i){return n.coerce(t,e,s,r,i)}l(t,e,o,i),!1!==e.visible&&(o(\"line.color\",(t.marker||{}).color||r),o(\"line.width\"),o(\"fillcolor\",a.addOpacity(e.line.color,.5)),o(\"whiskerwidth\"),o(\"boxmean\"),o(\"width\"),o(\"notched\",void 0!==t.notchwidth)&&o(\"notchwidth\"),c(t,e,o,{prefix:\"box\"}))},crossTraceDefaults:function(t,e){var r,i;function a(t){return n.coerce(i._input,i,s,t)}for(var l=0;l<t.length;l++){var c=(i=t[l]).type;\"box\"!==c&&\"violin\"!==c||(r=i._input,\"group\"===e[c+\"mode\"]&&o(r,i,e,a))}},handleSampleDefaults:l,handlePointsDefaults:c}},{\"../../components/color\":580,\"../../lib\":703,\"../../registry\":831,\"../bar/defaults\":845,\"./attributes\":864}],868:[function(t,e,r){\"use strict\";e.exports=function(t,e){return e.hoverOnBox&&(t.hoverOnBox=e.hoverOnBox),\"xVal\"in e&&(t.x=e.xVal),\"yVal\"in e&&(t.y=e.yVal),e.xa&&(t.xaxis=e.xa),e.ya&&(t.yaxis=e.ya),t}},{}],869:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\"),i=t(\"../../lib\"),a=t(\"../../components/fx\"),o=t(\"../../components/color\"),s=i.fillText;function l(t,e,r,s){var l,c,u,f,h,p,d,g,v,m,y,x,b,_,w=t.cd,k=t.xa,T=t.ya,A=w[0].trace,M=w[0].t,S=\"violin\"===A.type,E=[],C=M.bdPos,L=M.wHover,z=function(t){return t.pos+M.bPos-p};S&&\"both\"!==A.side?(\"positive\"===A.side&&(v=function(t){var e=z(t);return a.inbox(e,e+L,m)},x=C,b=0),\"negative\"===A.side&&(v=function(t){var e=z(t);return a.inbox(e-L,e,m)},x=0,b=C)):(v=function(t){var e=z(t);return a.inbox(e-L,e+L,m)},x=b=C),_=S?function(t){return a.inbox(t.span[0]-h,t.span[1]-h,m)}:function(t){return a.inbox(t.min-h,t.max-h,m)},\"h\"===A.orientation?(h=e,p=r,d=_,g=v,l=\"y\",u=T,c=\"x\",f=k):(h=r,p=e,d=v,g=_,l=\"x\",u=k,c=\"y\",f=T);var O=Math.min(1,C/Math.abs(u.r2c(u.range[1])-u.r2c(u.range[0])));function 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0,G.hovertemplate=!1,E.push(G)}}return E}function c(t,e,r){for(var n,o,l,c=t.cd,u=t.xa,f=t.ya,h=c[0].trace,p=u.c2p(e),d=f.c2p(r),g=a.quadrature(function(t){var e=Math.max(3,t.mrc||0);return Math.max(Math.abs(u.c2p(t.x)-p)-e,1-3/e)},function(t){var e=Math.max(3,t.mrc||0);return Math.max(Math.abs(f.c2p(t.y)-d)-e,1-3/e)}),v=!1,m=0;m<c.length;m++){o=c[m];for(var y=0;y<(o.pts||[]).length;y++){var x=g(l=o.pts[y]);x<=t.distance&&(t.distance=x,v=[m,y])}}if(!v)return!1;l=(o=c[v[0]]).pts[v[1]];var b,_=u.c2p(l.x,!0),w=f.c2p(l.y,!0),k=l.mrc||1;return n=i.extendFlat({},t,{index:l.i,color:(h.marker||{}).color,name:h.name,x0:_-k,x1:_+k,y0:w-k,y1:w+k,spikeDistance:t.distance,hovertemplate:h.hovertemplate}),\"h\"===h.orientation?(b=f,n.xLabelVal=l.x,n.yLabelVal=o.pos):(b=u,n.xLabelVal=o.pos,n.yLabelVal=l.y),n[b._id.charAt(0)+\"Spike\"]=b.c2p(o.pos,!0),s(l,h,n),n}e.exports={hoverPoints:function(t,e,r,n){var i,a=t.cd[0].trace.hoveron,o=[];return-1!==a.indexOf(\"boxes\")&&(o=o.concat(l(t,e,r,n))),-1!==a.indexOf(\"points\")&&(i=c(t,e,r)),\"closest\"===n?i?[i]:o:i?(o.push(i),o):o},hoverOnBoxes:l,hoverOnPoints:c}},{\"../../components/color\":580,\"../../components/fx\":619,\"../../lib\":703,\"../../plots/cartesian/axes\":751}],870:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),layoutAttributes:t(\"./layout_attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,crossTraceDefaults:t(\"./defaults\").crossTraceDefaults,supplyLayoutDefaults:t(\"./layout_defaults\").supplyLayoutDefaults,calc:t(\"./calc\"),crossTraceCalc:t(\"./cross_trace_calc\").crossTraceCalc,plot:t(\"./plot\").plot,style:t(\"./style\").style,styleOnSelect:t(\"./style\").styleOnSelect,hoverPoints:t(\"./hover\").hoverPoints,eventData:t(\"./event_data\"),selectPoints:t(\"./select\"),moduleType:\"trace\",name:\"box\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"cartesian\",\"svg\",\"symbols\",\"oriented\",\"box-violin\",\"showLegend\",\"boxLayout\",\"zoomScale\"],meta:{}}},{\"../../plots/cartesian\":762,\"./attributes\":864,\"./calc\":865,\"./cross_trace_calc\":866,\"./defaults\":867,\"./event_data\":868,\"./hover\":869,\"./layout_attributes\":871,\"./layout_defaults\":872,\"./plot\":873,\"./select\":874,\"./style\":875}],871:[function(t,e,r){\"use strict\";e.exports={boxmode:{valType:\"enumerated\",values:[\"group\",\"overlay\"],dflt:\"overlay\",editType:\"calc\"},boxgap:{valType:\"number\",min:0,max:1,dflt:.3,editType:\"calc\"},boxgroupgap:{valType:\"number\",min:0,max:1,dflt:.3,editType:\"calc\"}}},{}],872:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"./layout_attributes\");function o(t,e,r,i,a){for(var o=a+\"Layout\",s=!1,l=0;l<r.length;l++){var c=r[l];if(n.traceIs(c,o)){s=!0;break}}s&&(i(a+\"mode\"),i(a+\"gap\"),i(a+\"groupgap\"))}e.exports={supplyLayoutDefaults:function(t,e,r){o(0,0,r,function(r,n){return i.coerce(t,e,a,r,n)},\"box\")},_supply:o}},{\"../../lib\":703,\"../../registry\":831,\"./layout_attributes\":871}],873:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../lib\"),a=t(\"../../components/drawing\"),o=5,s=.01;function l(t,e,r,a){var o,s,l=e.pos,c=e.val,u=a.bPos,f=a.wdPos||0,h=a.bPosPxOffset||0,p=r.whiskerwidth||0,d=r.notched||!1,g=d?1-2*r.notchwidth:1;Array.isArray(a.bdPos)?(o=a.bdPos[0],s=a.bdPos[1]):(o=a.bdPos,s=a.bdPos);var v=t.selectAll(\"path.box\").data(\"violin\"!==r.type||r.box.visible?i.identity:[]);v.enter().append(\"path\").style(\"vector-effect\",\"non-scaling-stroke\").attr(\"class\",\"box\"),v.exit().remove(),v.each(function(t){if(t.empty)return\"M0,0Z\";var e=t.pos,a=l.c2p(e+u,!0)+h,v=l.c2p(e+u-o,!0)+h,m=l.c2p(e+u+s,!0)+h,y=l.c2p(e+u-f,!0)+h,x=l.c2p(e+u+f,!0)+h,b=l.c2p(e+u-o*g,!0)+h,_=l.c2p(e+u+s*g,!0)+h,w=c.c2p(t.q1,!0),k=c.c2p(t.q3,!0),T=i.constrain(c.c2p(t.med,!0),Math.min(w,k)+1,Math.max(w,k)-1),A=void 0===t.lf||!1===r.boxpoints,M=c.c2p(A?t.min:t.lf,!0),S=c.c2p(A?t.max:t.uf,!0),E=c.c2p(t.ln,!0),C=c.c2p(t.un,!0);\"h\"===r.orientation?n.select(this).attr(\"d\",\"M\"+T+\",\"+b+\"V\"+_+\"M\"+w+\",\"+v+\"V\"+m+(d?\"H\"+E+\"L\"+T+\",\"+_+\"L\"+C+\",\"+m:\"\")+\"H\"+k+\"V\"+v+(d?\"H\"+C+\"L\"+T+\",\"+b+\"L\"+E+\",\"+v:\"\")+\"ZM\"+w+\",\"+a+\"H\"+M+\"M\"+k+\",\"+a+\"H\"+S+(0===p?\"\":\"M\"+M+\",\"+y+\"V\"+x+\"M\"+S+\",\"+y+\"V\"+x)):n.select(this).attr(\"d\",\"M\"+b+\",\"+T+\"H\"+_+\"M\"+v+\",\"+w+\"H\"+m+(d?\"V\"+E+\"L\"+_+\",\"+T+\"L\"+m+\",\"+C:\"\")+\"V\"+k+\"H\"+v+(d?\"V\"+C+\"L\"+b+\",\"+T+\"L\"+v+\",\"+E:\"\")+\"ZM\"+a+\",\"+w+\"V\"+M+\"M\"+a+\",\"+k+\"V\"+S+(0===p?\"\":\"M\"+y+\",\"+M+\"H\"+x+\"M\"+y+\",\"+S+\"H\"+x))})}function c(t,e,r,n){var l=e.x,c=e.y,u=n.bdPos,f=n.bPos,h=r.boxpoints||r.points;i.seedPseudoRandom();var p=t.selectAll(\"g.points\").data(h?function(t){return t.forEach(function(t){t.t=n,t.trace=r}),t}:[]);p.enter().append(\"g\").attr(\"class\",\"points\"),p.exit().remove();var d=p.selectAll(\"path\").data(function(t){var e,n,a=t.pts2,l=Math.max((t.max-t.min)/10,t.q3-t.q1),c=1e-9*l,p=l*s,d=[],g=0;if(r.jitter){if(0===l)for(g=1,d=new Array(a.length),e=0;e<a.length;e++)d[e]=1;else for(e=0;e<a.length;e++){var v=Math.max(0,e-o),m=a[v].v,y=Math.min(a.length-1,e+o),x=a[y].v;\"all\"!==h&&(a[e].v<t.lf?x=Math.min(x,t.lf):m=Math.max(m,t.uf));var b=Math.sqrt(p*(y-v)/(x-m+c))||0;b=i.constrain(Math.abs(b),0,1),d.push(b),g=Math.max(b,g)}n=2*r.jitter/(g||1)}for(e=0;e<a.length;e++){var _=a[e],w=_.v,k=r.jitter?n*d[e]*(i.pseudoRandom()-.5):0,T=t.pos+f+u*(r.pointpos+k);\"h\"===r.orientation?(_.y=T,_.x=w):(_.x=T,_.y=w),\"suspectedoutliers\"===h&&w<t.uo&&w>t.lo&&(_.so=!0)}return a});d.enter().append(\"path\").classed(\"point\",!0),d.exit().remove(),d.call(a.translatePoints,l,c)}function u(t,e,r,a){var 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n=t(\"../../lib\"),i=t(\"../heatmap/xyz_defaults\"),a=t(\"./attributes\"),o=t(\"../contour/constraint_defaults\"),s=t(\"../contour/contours_defaults\"),l=t(\"../contour/style_defaults\");e.exports=function(t,e,r,c){function u(r,i){return n.coerce(t,e,a,r,i)}if(u(\"carpet\"),t.a&&t.b){if(!i(t,e,u,c,\"a\",\"b\"))return void(e.visible=!1);u(\"text\"),\"constraint\"===u(\"contours.type\")?o(t,e,u,c,r,{hasHover:!1}):(s(t,e,u,function(r){return n.coerce2(t,e,a,r)}),l(t,e,u,c,{hasHover:!1}))}else e._defaultColor=r,e._length=null}},{\"../../lib\":703,\"../contour/constraint_defaults\":926,\"../contour/contours_defaults\":928,\"../contour/style_defaults\":942,\"../heatmap/xyz_defaults\":986,\"./attributes\":943}],946:[function(t,e,r){\"use 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n=t(\"../pie/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../plots/domain\").attributes,o=t(\"../../components/fx/hovertemplate_attributes\"),s=t(\"../../lib/extend\").extendFlat;e.exports={labels:n.labels,label0:n.label0,dlabel:n.dlabel,values:n.values,marker:{colors:n.marker.colors,line:{color:s({},n.marker.line.color,{dflt:null}),width:s({},n.marker.line.width,{dflt:1}),editType:\"calc\"},editType:\"calc\"},text:n.text,hovertext:n.hovertext,scalegroup:s({},n.scalegroup,{}),textinfo:s({},n.textinfo,{flags:[\"label\",\"text\",\"value\",\"percent\"]}),hoverinfo:s({},i.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:o({},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),textposition:s({},n.textposition,{values:[\"inside\",\"none\"],dflt:\"inside\"}),textfont:n.textfont,insidetextfont:n.insidetextfont,title:{text:n.title.text,font:n.title.font,position:s({},n.title.position,{values:[\"top left\",\"top center\",\"top 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n=t(\"../../lib\"),i=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\"),r(\"funnelareacolorway\",e.colorway),r(\"extendfunnelareacolors\")}},{\"../../lib\":703,\"./layout_attributes\":968}],970:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../components/drawing\"),a=t(\"../../lib\"),o=t(\"../../lib/svg_text_utils\"),s=t(\"../bar/plot\").getTransformToMoveInsideBar,l=t(\"../pie/helpers\"),c=t(\"../pie/plot\"),u=c.attachFxHandlers,f=c.determineInsideTextFont,h=c.layoutAreas,p=c.prerenderTitles,d=c.positionTitleOutside;function g(t,e){return\"l\"+(e[0]-t[0])+\",\"+(e[1]-t[1])}e.exports=function(t,e){var r=t._fullLayout;p(e,t),h(e,r._size),a.makeTraceGroups(r._funnelarealayer,e,\"trace\").each(function(e){var c=n.select(this),h=e[0],p=h.trace;!function(t){if(!t.length)return;var e=t[0],r=e.trace,n=r.aspectratio,i=r.baseratio;i>.999&&(i=.999);var a,o=Math.pow(i,2),s=e.vTotal,l=s,c=s*o/(1-o)/s;function u(){var t,e={x:t=Math.sqrt(c),y:-t};return[e.x,e.y]}var f,h,p=[];for(p.push(u()),f=t.length-1;f>-1;f--)if(!(h=t[f]).hidden){var d=h.v/l;c+=d,p.push(u())}var g=1/0,v=-1/0;for(f=0;f<p.length;f++)a=p[f],g=Math.min(g,a[1]),v=Math.max(v,a[1]);for(f=0;f<p.length;f++)p[f][1]-=(v+g)/2;var m=p[p.length-1][0],y=e.r,x=(v-g)/2,b=y/m,_=y/x*n;for(e.r=_*x,f=0;f<p.length;f++)p[f][0]*=b,p[f][1]*=_;var w=[-(a=p[0])[0],a[1]],k=[a[0],a[1]],T=0;for(f=t.length-1;f>-1;f--)if(!(h=t[f]).hidden){var A=p[T+=1][0],M=p[T][1];h.TL=[-A,M],h.TR=[A,M],h.BL=w,h.BR=k,h.pxmid=(S=h.TR,E=h.BR,[.5*(S[0]+E[0]),.5*(S[1]+E[1])]),w=h.TL,k=h.TR}var S,E}(e),c.each(function(){var c=n.select(this).selectAll(\"g.slice\").data(e);c.enter().append(\"g\").classed(\"slice\",!0),c.exit().remove(),c.each(function(r){if(r.hidden)n.select(this).selectAll(\"path,g\").remove();else{r.pointNumber=r.i,r.curveNumber=p.index;var c=h.cx,d=h.cy,v=n.select(this),m=v.selectAll(\"path.surface\").data([r]);m.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":\"all\"}),v.call(u,t,e);var y=\"M\"+(c+r.TR[0])+\",\"+(d+r.TR[1])+g(r.TR,r.BR)+g(r.BR,r.BL)+g(r.BL,r.TL)+\"Z\";m.attr(\"d\",y);var x=l.castOption(p.textposition,r.pts),b=v.selectAll(\"g.slicetext\").data(r.text&&\"none\"!==x?[0]:[]);b.enter().append(\"g\").classed(\"slicetext\",!0),b.exit().remove(),b.each(function(){var e=a.ensureSingle(n.select(this),\"text\",\"\",function(t){t.attr(\"data-notex\",1)});e.text(r.text).attr({class:\"slicetext\",transform:\"\",\"text-anchor\":\"middle\"}).call(i.font,f(p,r,t._fullLayout.font)).call(o.convertToTspans,t);var l,u,h,g=i.bBox(e.node()),v=Math.min(r.BL[1],r.BR[1]),m=Math.max(r.TL[1],r.TR[1]);u=Math.max(r.TL[0],r.BL[0]),h=Math.min(r.TR[0],r.BR[0]),l=s(u,h,v,m,g,{isHorizontal:!0,constrained:!0,angle:0,anchor:\"middle\"}),e.attr(\"transform\",\"translate(\"+c+\",\"+d+\")\"+l)})}});var v=n.select(this).selectAll(\"g.titletext\").data(p.title.text?[0]:[]);v.enter().append(\"g\").classed(\"titletext\",!0),v.exit().remove(),v.each(function(){var e=a.ensureSingle(n.select(this),\"text\",\"\",function(t){t.attr(\"data-notex\",1)}),s=p.title.text;p._meta&&(s=a.templateString(s,p._meta)),e.text(s).attr({class:\"titletext\",transform:\"\",\"text-anchor\":\"middle\"}).call(i.font,p.title.font).call(o.convertToTspans,t);var l=d(h,r._size);e.attr(\"transform\",\"translate(\"+l.x+\",\"+l.y+\")\"+(l.scale<1?\"scale(\"+l.scale+\")\":\"\")+\"translate(\"+l.tx+\",\"+l.ty+\")\")})})})}},{\"../../components/drawing\":601,\"../../lib\":703,\"../../lib/svg_text_utils\":727,\"../bar/plot\":851,\"../pie/helpers\":1054,\"../pie/plot\":1058,d3:157}],971:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../pie/style_one\");e.exports=function(t){t._fullLayout._funnelarealayer.selectAll(\".trace\").each(function(t){var e=t[0].trace,r=n.select(this);r.style({opacity:e.opacity}),r.selectAll(\"path.surface\").each(function(t){n.select(this).call(i,t,e)})})}},{\"../pie/style_one\":1060,d3:157}],972:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),i=t(\"../../components/fx/hovertemplate_attributes\"),a=t(\"../../components/colorscale/attributes\"),o=t(\"../../lib/extend\").extendFlat;e.exports=o({z:{valType:\"data_array\",editType:\"calc\"},x:o({},n.x,{impliedEdits:{xtype:\"array\"}}),x0:o({},n.x0,{impliedEdits:{xtype:\"scaled\"}}),dx:o({},n.dx,{impliedEdits:{xtype:\"scaled\"}}),y:o({},n.y,{impliedEdits:{ytype:\"array\"}}),y0:o({},n.y0,{impliedEdits:{ytype:\"scaled\"}}),dy:o({},n.dy,{impliedEdits:{ytype:\"scaled\"}}),text:{valType:\"data_array\",editType:\"calc\"},hovertext:{valType:\"data_array\",editType:\"calc\"},transpose:{valType:\"boolean\",dflt:!1,editType:\"calc\"},xtype:{valType:\"enumerated\",values:[\"array\",\"scaled\"],editType:\"calc+clearAxisTypes\"},ytype:{valType:\"enumerated\",values:[\"array\",\"scaled\"],editType:\"calc+clearAxisTypes\"},zsmooth:{valType:\"enumerated\",values:[\"fast\",\"best\",!1],dflt:!1,editType:\"calc\"},connectgaps:{valType:\"boolean\",dflt:!1,editType:\"calc\"},xgap:{valType:\"number\",dflt:0,min:0,editType:\"plot\"},ygap:{valType:\"number\",dflt:0,min:0,editType:\"plot\"},zhoverformat:{valType:\"string\",dflt:\"\",editType:\"none\"},hovertemplate:i()},{transforms:void 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n=t(\"../../lib/extend\").extendFlat,i=t(\"../../plots/attributes\"),a=t(\"../../plots/font_attributes\"),o=t(\"../../components/colorscale/attributes\"),s=t(\"../../components/fx/hovertemplate_attributes\"),l=t(\"../../plots/domain\").attributes,c=n({editType:\"calc\"},o(\"line\",{editTypeOverride:\"calc\"}),{shape:{valType:\"enumerated\",values:[\"linear\",\"hspline\"],dflt:\"linear\",editType:\"plot\"},hovertemplate:s({editType:\"plot\",arrayOk:!1},{keys:[\"count\",\"probability\"]})});e.exports={domain:l({name:\"parcats\",trace:!0,editType:\"calc\"}),hoverinfo:n({},i.hoverinfo,{flags:[\"count\",\"probability\"],editType:\"plot\",arrayOk:!1}),hoveron:{valType:\"enumerated\",values:[\"category\",\"color\",\"dimension\"],dflt:\"category\",editType:\"plot\"},hovertemplate:s({editType:\"plot\",arrayOk:!1},{keys:[\"count\",\"probability\",\"category\",\"categorycount\",\"colorcount\",\"bandcolorcount\"]}),arrangement:{valType:\"enumerated\",values:[\"perpendicular\",\"freeform\",\"fixed\"],dflt:\"perpendicular\",editType:\"plot\"},bundlecolors:{valType:\"boolean\",dflt:!0,editType:\"plot\"},sortpaths:{valType:\"enumerated\",values:[\"forward\",\"backward\"],dflt:\"forward\",editType:\"plot\"},labelfont:a({editType:\"calc\"}),tickfont:a({editType:\"calc\"}),dimensions:{_isLinkedToArray:\"dimension\",label:{valType:\"string\",editType:\"calc\"},categoryorder:{valType:\"enumerated\",values:[\"trace\",\"category 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s=o[0];i(t,s,r,a)}},r.clean=function(t,e,r,n){var i=n._has&&n._has(\"parcats\"),a=e._has&&e._has(\"parcats\");i&&!a&&n._paperdiv.selectAll(\".parcats\").remove()}},{\"../../plots/get_data\":786,\"./plot\":1037}],1033:[function(t,e,r){\"use strict\";var n=t(\"../../lib/gup\").wrap,i=t(\"../../components/colorscale/helpers\").hasColorscale,a=t(\"../../components/colorscale/calc\"),o=t(\"../../lib/filter_unique.js\"),s=t(\"../../components/drawing\"),l=t(\"../../lib\");function c(t,e,r){t.valueInds.push(e),t.count+=r}function u(t,e,r){t.valueInds.push(e),t.count+=r}e.exports=function(t,e){var r=l.filterVisible(e.dimensions);if(0===r.length)return[];var f,h,p,d=r.map(function(t){var e;return\"trace\"===t.categoryorder?e=null:\"array\"===t.categoryorder?e=t.categoryarray:(e=o(t.values).sort(),\"category descending\"===t.categoryorder&&(e=e.reverse())),function(t,e){e=null==e?[]:e.map(function(t){return t});var r={},n={},i=[];e.forEach(function(t,e){r[t]=0,n[t]=e});for(var a=0;a<t.length;a++){var o,s=t[a];void 0===r[s]?(r[s]=1,o=e.push(s)-1,n[s]=o):(r[s]++,o=n[s]),i.push(o)}var l=e.map(function(t){return r[t]});return{uniqueValues:e,uniqueCounts:l,inds:i}}(t.values,e)});f=l.isArrayOrTypedArray(e.counts)?e.counts:[e.counts],function(t){var e;if(function(t){for(var e=new Array(t.length),r=0;r<t.length;r++){if(t[r]<0||t[r]>=t.length)return!1;if(void 0!==e[t[r]])return!1;e[t[r]]=!0}return!0}(t.map(function(t){return t.displayindex})))for(e=0;e<t.length;e++)t[e]._displayindex=t[e].displayindex;else for(e=0;e<t.length;e++)t[e]._displayindex=e}(r),r.forEach(function(t,e){!function(t,e){t._categoryarray=e.uniqueValues,null===t.ticktext||void 0===t.ticktext?t._ticktext=[]:t._ticktext=t.ticktext.slice();for(var r=t._ticktext.length;r<e.uniqueValues.length;r++)t._ticktext.push(e.uniqueValues[r])}(t,d[e])});var g,v=e.line;v?(i(e,\"line\")&&a(t,e,{vals:e.line.color,containerStr:\"line\",cLetter:\"c\"}),g=s.tryColorscale(v)):g=l.identity;var m,y,x,b,_=r[0].values.length,w={},k=d.map(function(t){return t.inds});for(p=0,m=0;m<_;m++){var T=[];for(y=0;y<k.length;y++)T.push(k[y][m]);h=f[m%f.length],p+=h;var A=(x=m,b=void 0,b=l.isArrayOrTypedArray(v.color)?v.color[x%v.color.length]:v.color,{color:g(b),rawColor:b}),M=T+\"-\"+A.rawColor;void 0===w[M]&&(w[M]={categoryInds:T,color:A.color,rawColor:A.rawColor,valueInds:[],count:0}),u(w[M],m,h)}var S,E=r.map(function(t,e){return r=e,n=t._index,i=t._displayindex,a=t.label,{dimensionInd:r,containerInd:n,displayInd:i,dimensionLabel:a,count:p,categories:[],dragX:null};var r,n,i,a});for(m=0;m<_;m++)for(h=f[m%f.length],y=0;y<E.length;y++){var C=E[y].containerInd,L=d[y].inds[m],z=E[y].categories;if(void 0===z[L]){var O=e.dimensions[C]._categoryarray[L],I=e.dimensions[C]._ticktext[L];z[L]={dimensionInd:y,categoryInd:S=L,categoryValue:O,displayInd:S,categoryLabel:I,valueInds:[],count:0,dragY:null}}c(z[L],m,h)}return n(function(t,e,r){var n=t.map(function(t){return t.categories.length}).reduce(function(t,e){return Math.max(t,e)});return{dimensions:t,paths:e,trace:void 0,maxCats:n,count:r}}(E,w,p))}},{\"../../components/colorscale/calc\":588,\"../../components/colorscale/helpers\":591,\"../../components/drawing\":601,\"../../lib\":703,\"../../lib/filter_unique.js\":694,\"../../lib/gup\":701}],1034:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/colorscale/helpers\").hasColorscale,a=t(\"../../components/colorscale/defaults\"),o=t(\"../../plots/domain\").defaults,s=t(\"../../plots/array_container_defaults\"),l=t(\"./attributes\"),c=t(\"../parcoords/merge_length\");function u(t,e){function r(r,i){return n.coerce(t,e,l.dimensions,r,i)}var i=r(\"values\"),a=r(\"visible\");if(i&&i.length||(a=e.visible=!1),a){r(\"label\"),r(\"displayindex\",e._index);var o,s=t.categoryarray,c=Array.isArray(s)&&s.length>0;c&&(o=\"array\");var u=r(\"categoryorder\",o);\"array\"===u?(r(\"categoryarray\"),r(\"ticktext\")):(delete t.categoryarray,delete t.ticktext),c||\"array\"!==u||(e.categoryorder=\"trace\")}}e.exports=function(t,e,r,f){function h(r,i){return n.coerce(t,e,l,r,i)}var p=s(t,e,{name:\"dimensions\",handleItemDefaults:u}),d=function(t,e,r,o,s){s(\"line.shape\"),s(\"line.hovertemplate\");var l=s(\"line.color\",o.colorway[0]);if(i(t,\"line\")&&n.isArrayOrTypedArray(l)){if(l.length)return s(\"line.colorscale\"),a(t,e,o,s,{prefix:\"line.\",cLetter:\"c\"}),l.length;e.line.color=r}return 1/0}(t,e,r,f,h);o(e,f,h),Array.isArray(p)&&p.length||(e.visible=!1),c(e,p,\"values\",d),h(\"hoveron\"),h(\"hovertemplate\"),h(\"arrangement\"),h(\"bundlecolors\"),h(\"sortpaths\"),h(\"counts\");var g={family:f.font.family,size:Math.round(f.font.size),color:f.font.color};n.coerceFont(h,\"labelfont\",g);var v={family:f.font.family,size:Math.round(f.font.size/1.2),color:f.font.color};n.coerceFont(h,\"tickfont\",v)}},{\"../../components/colorscale/defaults\":590,\"../../components/colorscale/helpers\":591,\"../../lib\":703,\"../../plots/array_container_defaults\":747,\"../../plots/domain\":776,\"../parcoords/merge_length\":1046,\"./attributes\":1031}],1035:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\"),plot:t(\"./plot\"),colorbar:{container:\"line\",min:\"cmin\",max:\"cmax\"},moduleType:\"trace\",name:\"parcats\",basePlotModule:t(\"./base_plot\"),categories:[\"noOpacity\"],meta:{}}},{\"./attributes\":1031,\"./base_plot\":1032,\"./calc\":1033,\"./defaults\":1034,\"./plot\":1037}],1036:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../plot_api/plot_api\"),a=t(\"../../components/fx\"),o=t(\"../../lib\"),s=t(\"../../components/drawing\"),l=t(\"tinycolor2\"),c=t(\"../../lib/svg_text_utils\");function u(t,e,r,i){var a=t.map(function(t,e,r){var n,i=r[0],a=e.margin||{l:80,r:80,t:100,b:80},o=i.trace,s=o.domain,l=e.width,c=e.height,u=Math.floor(l*(s.x[1]-s.x[0])),f=Math.floor(c*(s.y[1]-s.y[0])),h=s.x[0]*l+a.l,p=e.height-s.y[1]*e.height+a.t,d=o.line.shape;n=\"all\"===o.hoverinfo?[\"count\",\"probability\"]:(o.hoverinfo||\"\").split(\"+\");var g={trace:o,key:o.uid,model:i,x:h,y:p,width:u,height:f,hoveron:o.hoveron,hoverinfoItems:n,arrangement:o.arrangement,bundlecolors:o.bundlecolors,sortpaths:o.sortpaths,labelfont:o.labelfont,categorylabelfont:o.tickfont,pathShape:d,dragDimension:null,margin:a,paths:[],dimensions:[],graphDiv:t,traceSelection:null,pathSelection:null,dimensionSelection:null};i.dimensions&&(R(g),P(g));return g}.bind(0,e,r)),l=i.selectAll(\"g.parcatslayer\").data([null]);l.enter().append(\"g\").attr(\"class\",\"parcatslayer\").style(\"pointer-events\",\"all\");var u=l.selectAll(\"g.trace.parcats\").data(a,f),v=u.enter().append(\"g\").attr(\"class\",\"trace 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t.categories},f),A=T.enter().append(\"g\").attr(\"class\",\"category\");T.attr(\"transform\",function(t){return\"translate(0, \"+t.y+\")\"}),A.append(\"rect\").attr(\"class\",\"catrect\").attr(\"pointer-events\",\"none\"),T.select(\"rect.catrect\").attr(\"fill\",\"none\").attr(\"width\",function(t){return t.width}).attr(\"height\",function(t){return t.height}),b(A);var z=T.selectAll(\"rect.bandrect\").data(function(t){return t.bands},f);z.each(function(){o.raiseToTop(this)}),z.attr(\"fill\",function(t){return t.color});var O=z.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"stroke-opacity\",0).attr(\"fill\",function(t){return t.color}).attr(\"fill-opacity\",0);z.attr(\"fill\",function(t){return t.color}).attr(\"width\",function(t){return t.width}).attr(\"height\",function(t){return t.height}).attr(\"y\",function(t){return t.y}).attr(\"cursor\",function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"perpendicular\"===t.parcatsViewModel.arrangement?\"ns-resize\":\"move\"}),_(O),z.exit().remove(),A.append(\"text\").attr(\"class\",\"catlabel\").attr(\"pointer-events\",\"none\");var I=e._fullLayout.paper_bgcolor;T.select(\"text.catlabel\").attr(\"text-anchor\",function(t){return h(t)?\"start\":\"end\"}).attr(\"alignment-baseline\",\"middle\").style(\"text-shadow\",I+\" -1px 1px 2px, \"+I+\" 1px 1px 2px, \"+I+\" 1px -1px 2px, \"+I+\" -1px -1px 2px\").style(\"fill\",\"rgb(0, 0, 0)\").attr(\"x\",function(t){return h(t)?t.width+5:-5}).attr(\"y\",function(t){return t.height/2}).text(function(t){return t.model.categoryLabel}).each(function(t){s.font(n.select(this),t.parcatsViewModel.categorylabelfont),c.convertToTspans(n.select(this),e)}),A.append(\"text\").attr(\"class\",\"dimlabel\"),T.select(\"text.dimlabel\").attr(\"text-anchor\",\"middle\").attr(\"alignment-baseline\",\"baseline\").attr(\"cursor\",function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"ew-resize\"}).attr(\"x\",function(t){return t.width/2}).attr(\"y\",-5).text(function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null}).each(function(t){s.font(n.select(this),t.parcatsViewModel.labelfont)}),T.selectAll(\"rect.bandrect\").on(\"mouseover\",M).on(\"mouseout\",S),T.exit().remove(),k.call(n.behavior.drag().origin(function(t){return{x:t.x,y:0}}).on(\"dragstart\",E).on(\"drag\",C).on(\"dragend\",L)),u.each(function(t){t.traceSelection=n.select(this),t.pathSelection=n.select(this).selectAll(\"g.paths\").selectAll(\"path.path\"),t.dimensionSelection=n.select(this).selectAll(\"g.dimensions\").selectAll(\"g.dimension\")}),u.exit().remove()}function f(t){return t.key}function h(t){var e=t.parcatsViewModel.dimensions.length,r=t.parcatsViewModel.dimensions[e-1].model.dimensionInd;return t.model.dimensionInd===r}function p(t,e){return t.model.rawColor>e.model.rawColor?1:t.model.rawColor<e.model.rawColor?-1:0}function d(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){o.raiseToTop(this),x(n.select(this));var e=v(t);if(t.parcatsViewModel.graphDiv.emit(\"plotly_hover\",{points:e,event:n.event}),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\")){var r,i,s,c=n.mouse(this)[0],u=t.parcatsViewModel.graphDiv,f=t.parcatsViewModel.trace,h=u._fullLayout,p=h._paperdiv.node().getBoundingClientRect(),d=t.parcatsViewModel.graphDiv.getBoundingClientRect();for(s=0;s<t.leftXs.length-1;s++)if(t.leftXs[s]+t.dimWidths[s]-2<=c&&c<=t.leftXs[s+1]+2){var g=t.parcatsViewModel.dimensions[s],m=t.parcatsViewModel.dimensions[s+1];r=(g.x+g.width+m.x)/2,i=(t.topYs[s]+t.topYs[s+1]+t.height)/2;break}var y=t.parcatsViewModel.x+r,b=t.parcatsViewModel.y+i,_=l.mostReadable(t.model.color,[\"black\",\"white\"]),w=t.model.count,k=w/t.parcatsViewModel.model.count,T={countLabel:w,probabilityLabel:k.toFixed(3)},A=[];-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&A.push([\"Count:\",T.countLabel].join(\" \")),-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&A.push([\"P:\",T.probabilityLabel].join(\" \"));var M=A.join(\"<br>\"),S=n.mouse(u)[0];a.loneHover({trace:f,x:y-p.left+d.left,y:b-p.top+d.top,text:M,color:t.model.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:10,fontColor:_,idealAlign:S<y?\"right\":\"left\",hovertemplate:(f.line||{}).hovertemplate,hovertemplateLabels:T,eventData:[{data:f._input,fullData:f,count:w,probability:k}]},{container:h._hoverlayer.node(),outerContainer:h._paper.node(),gd:u})}}}function g(t){if(!t.parcatsViewModel.dragDimension&&(y(n.select(this)),a.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()),t.parcatsViewModel.pathSelection.sort(p),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\"))){var e=v(t);t.parcatsViewModel.graphDiv.emit(\"plotly_unhover\",{points:e,event:n.event})}}function v(t){for(var e=[],r=z(t.parcatsViewModel),n=0;n<t.model.valueInds.length;n++){var i=t.model.valueInds[n];e.push({curveNumber:r,pointNumber:i})}return e}function m(t){if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){var e=v(t);t.parcatsViewModel.graphDiv.emit(\"plotly_click\",{points:e,event:n.event})}}function y(t){t.attr(\"fill\",function(t){return t.model.color}).attr(\"fill-opacity\",.6).attr(\"stroke\",\"lightgray\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1)}function x(t){t.attr(\"fill-opacity\",.8).attr(\"stroke\",function(t){return l.mostReadable(t.model.color,[\"black\",\"white\"])}).attr(\"stroke-width\",.3)}function b(t){t.select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",1).attr(\"stroke-opacity\",1)}function _(t){t.attr(\"stroke\",\"black\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1).attr(\"fill-opacity\",1)}function w(t){var e=t.parcatsViewModel.pathSelection,r=t.categoryViewModel.model.dimensionInd,n=t.categoryViewModel.model.categoryInd;return e.filter(function(e){return e.model.categoryInds[r]===n&&e.model.color===t.color})}function k(t,e,r){var i=n.select(t).datum().parcatsViewModel.graphDiv,a=n.select(t.parentNode).selectAll(\"rect.bandrect\"),o=[];a.each(function(t){w(t).each(function(t){Array.prototype.push.apply(o,v(t))})}),i.emit(e,{points:o,event:r})}function T(t,e,r){var i=n.select(t).datum(),a=i.parcatsViewModel.graphDiv,o=w(i),s=[];o.each(function(t){Array.prototype.push.apply(s,v(t))}),a.emit(e,{points:s,event:r})}function A(t,e){var r,i,a=n.select(e.parentNode).select(\"rect.catrect\"),o=a.node().getBoundingClientRect(),s=a.datum(),l=s.parcatsViewModel,c=l.model.dimensions[s.model.dimensionInd],u=l.trace,f=o.top+o.height/2;l.dimensions.length>1&&c.displayInd===l.dimensions.length-1?(r=o.left,i=\"left\"):(r=o.left+o.width,i=\"right\");var h=s.model.count,p=s.model.categoryLabel,d=h/s.parcatsViewModel.model.count,g={countLabel:h,categoryLabel:p,probabilityLabel:d.toFixed(3)},v=[];-1!==s.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&v.push([\"Count:\",g.countLabel].join(\" \")),-1!==s.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&v.push([\"P(\"+g.categoryLabel+\"):\",g.probabilityLabel].join(\" \"));var m=v.join(\"<br>\");return{trace:u,x:r-t.left,y:f-t.top,text:m,color:\"lightgray\",borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", 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e=w(t);x(e),e.each(function(){o.raiseToTop(this)})}),n.select(t.parentNode).select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",2.5)}(this),k(this,\"plotly_hover\",n.event)),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\"))\"category\"===c?e=A(s,this):\"color\"===c?e=function(t,e){var r,i,a=e.getBoundingClientRect(),o=n.select(e).datum(),s=o.categoryViewModel,c=s.parcatsViewModel,u=c.model.dimensions[s.model.dimensionInd],f=c.trace,h=a.y+a.height/2;c.dimensions.length>1&&u.displayInd===c.dimensions.length-1?(r=a.left,i=\"left\"):(r=a.left+a.width,i=\"right\");var p=s.model.categoryLabel,d=o.parcatsViewModel.model.count,g=0;o.categoryViewModel.bands.forEach(function(t){t.color===o.color&&(g+=t.count)});var v=s.model.count,m=0;c.pathSelection.each(function(t){t.model.color===o.color&&(m+=t.model.count)});var y=g/d,x=g/m,b=g/v,_={countLabel:d,categoryLabel:p,probabilityLabel:y.toFixed(3)},w=[];-1!==s.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&w.push([\"Count:\",_.countLabel].join(\" \")),-1!==s.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&(w.push(\"P(color \\u2229 \"+p+\"): \"+_.probabilityLabel),w.push(\"P(\"+p+\" | color): \"+x.toFixed(3)),w.push(\"P(color | \"+p+\"): \"+b.toFixed(3)));var k=w.join(\"<br>\"),T=l.mostReadable(o.color,[\"black\",\"white\"]);return{trace:f,x:r-t.left,y:h-t.top,text:k,color:o.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontColor:T,fontSize:10,idealAlign:i,hovertemplate:f.hovertemplate,hovertemplateLabels:_,eventData:[{data:f._input,fullData:f,category:p,count:d,probability:y,categorycount:v,colorcount:m,bandcolorcount:g}]}}(s,this):\"dimension\"===c&&(e=function(t,e){var r=[];return n.select(e.parentNode.parentNode).selectAll(\"g.category\").select(\"rect.catrect\").each(function(){r.push(A(t,this))}),r}(s,this)),e&&a.loneHover(e,{container:i._hoverlayer.node(),outerContainer:i._paper.node(),gd:r})}}function S(t){var e=t.parcatsViewModel;if(!e.dragDimension&&(y(e.pathSelection),b(e.dimensionSelection.selectAll(\"g.category\")),_(e.dimensionSelection.selectAll(\"g.category\").selectAll(\"rect.bandrect\")),a.loneUnhover(e.graphDiv._fullLayout._hoverlayer.node()),e.pathSelection.sort(p),-1===e.hoverinfoItems.indexOf(\"skip\"))){\"color\"===t.parcatsViewModel.hoveron?T(this,\"plotly_unhover\",n.event):k(this,\"plotly_unhover\",n.event)}}function E(t){\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragDimensionDisplayInd=t.model.displayInd,t.initialDragDimensionDisplayInds=t.parcatsViewModel.model.dimensions.map(function(t){return t.displayInd}),t.dragHasMoved=!1,t.dragCategoryDisplayInd=null,n.select(this).selectAll(\"g.category\").select(\"rect.catrect\").each(function(e){var r=n.mouse(this)[0],i=n.mouse(this)[1];-2<=r&&r<=e.width+2&&-2<=i&&i<=e.height+2&&(t.dragCategoryDisplayInd=e.model.displayInd,t.initialDragCategoryDisplayInds=t.model.categories.map(function(t){return t.displayInd}),e.model.dragY=e.y,o.raiseToTop(this.parentNode),n.select(this.parentNode).selectAll(\"rect.bandrect\").each(function(e){e.y<i&&i<=e.y+e.height&&(t.potentialClickBand=this)}))}),t.parcatsViewModel.dragDimension=t,a.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()))}function C(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragHasMoved=!0,null!==t.dragDimensionDisplayInd)){var e=t.dragDimensionDisplayInd,r=e-1,i=e+1,a=t.parcatsViewModel.dimensions[e];if(null!==t.dragCategoryDisplayInd){var o=a.categories[t.dragCategoryDisplayInd];o.model.dragY+=n.event.dy;var s=o.model.dragY,l=o.model.displayInd,c=a.categories,u=c[l-1],f=c[l+1];void 0!==u&&s<u.y+u.height/2&&(o.model.displayInd=u.model.displayInd,u.model.displayInd=l),void 0!==f&&s+o.height>f.y+f.height/2&&(o.model.displayInd=f.model.displayInd,f.model.displayInd=l),t.dragCategoryDisplayInd=o.model.displayInd}if(null===t.dragCategoryDisplayInd||\"freeform\"===t.parcatsViewModel.arrangement){a.model.dragX=n.event.x;var h=t.parcatsViewModel.dimensions[r],p=t.parcatsViewModel.dimensions[i];void 0!==h&&a.model.dragX<h.x+h.width&&(a.model.displayInd=h.model.displayInd,h.model.displayInd=e),void 0!==p&&a.model.dragX+a.width>p.x&&(a.model.displayInd=p.model.displayInd,p.model.displayInd=t.dragDimensionDisplayInd),t.dragDimensionDisplayInd=a.model.displayInd}R(t.parcatsViewModel),P(t.parcatsViewModel),I(t.parcatsViewModel),O(t.parcatsViewModel)}}function L(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&null!==t.dragDimensionDisplayInd){n.select(this).selectAll(\"text\").attr(\"font-weight\",\"normal\");var e={},r=z(t.parcatsViewModel),a=t.parcatsViewModel.model.dimensions.map(function(t){return t.displayInd}),o=t.initialDragDimensionDisplayInds.some(function(t,e){return t!==a[e]});o&&a.forEach(function(r,n){var i=t.parcatsViewModel.model.dimensions[n].containerInd;e[\"dimensions[\"+i+\"].displayindex\"]=r});var s=!1;if(null!==t.dragCategoryDisplayInd){var l=t.model.categories.map(function(t){return t.displayInd});if(s=t.initialDragCategoryDisplayInds.some(function(t,e){return t!==l[e]})){var c=t.model.categories.slice().sort(function(t,e){return t.displayInd-e.displayInd}),u=c.map(function(t){return t.categoryValue}),f=c.map(function(t){return t.categoryLabel});e[\"dimensions[\"+t.model.containerInd+\"].categoryarray\"]=[u],e[\"dimensions[\"+t.model.containerInd+\"].ticktext\"]=[f],e[\"dimensions[\"+t.model.containerInd+\"].categoryorder\"]=\"array\"}}if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")&&!t.dragHasMoved&&t.potentialClickBand&&(\"color\"===t.parcatsViewModel.hoveron?T(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent):k(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent)),t.model.dragX=null,null!==t.dragCategoryDisplayInd)t.parcatsViewModel.dimensions[t.dragDimensionDisplayInd].categories[t.dragCategoryDisplayInd].model.dragY=null,t.dragCategoryDisplayInd=null;t.dragDimensionDisplayInd=null,t.parcatsViewModel.dragDimension=null,t.dragHasMoved=null,t.potentialClickBand=null,R(t.parcatsViewModel),P(t.parcatsViewModel),n.transition().duration(300).ease(\"cubic-in-out\").each(function(){I(t.parcatsViewModel,!0),O(t.parcatsViewModel,!0)}).each(\"end\",function(){(o||s)&&i.restyle(t.parcatsViewModel.graphDiv,e,[r])})}}function z(t){for(var e,r=t.graphDiv._fullData,n=0;n<r.length;n++)if(t.key===r[n].uid){e=n;break}return e}function O(t,e){var r;void 0===e&&(e=!1),t.pathSelection.data(function(t){return t.paths},f),(r=t.pathSelection,e?r.transition():r).attr(\"d\",function(t){return t.svgD})}function I(t,e){function r(t){return e?t.transition():t}void 0===e&&(e=!1),t.dimensionSelection.data(function(t){return t.dimensions},f);var i=t.dimensionSelection.selectAll(\"g.category\").data(function(t){return t.categories},f);r(t.dimensionSelection).attr(\"transform\",function(t){return\"translate(\"+t.x+\", 0)\"}),r(i).attr(\"transform\",function(t){return\"translate(0, \"+t.y+\")\"}),i.select(\".dimlabel\").text(function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null}),i.select(\".catlabel\").attr(\"text-anchor\",function(t){return h(t)?\"start\":\"end\"}).attr(\"x\",function(t){return h(t)?t.width+5:-5}).each(function(t){var e,r;h(t)?(e=t.width+5,r=\"start\"):(e=-5,r=\"end\"),n.select(this).selectAll(\"tspan\").attr(\"x\",e).attr(\"text-anchor\",r)});var a=i.selectAll(\"rect.bandrect\").data(function(t){return t.bands},f),s=a.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"cursor\",\"move\").attr(\"stroke-opacity\",0).attr(\"fill\",function(t){return t.color}).attr(\"fill-opacity\",0);a.attr(\"fill\",function(t){return t.color}).attr(\"width\",function(t){return t.width}).attr(\"height\",function(t){return t.height}).attr(\"y\",function(t){return t.y}),_(s),a.each(function(){o.raiseToTop(this)}),a.exit().remove()}function D(t,e,r,i,a){var o,s,l=[],c=[];for(s=0;s<r.length-1;s++)o=n.interpolateNumber(r[s]+t[s],t[s+1]),l.push(o(a)),c.push(o(1-a));var u=\"M \"+t[0]+\",\"+e[0];for(u+=\"l\"+r[0]+\",0 \",s=1;s<r.length;s++)u+=\"C\"+l[s-1]+\",\"+e[s-1]+\" \"+c[s-1]+\",\"+e[s]+\" \"+t[s]+\",\"+e[s],u+=\"l\"+r[s]+\",0 \";for(u+=\"l0,\"+i+\" \",u+=\"l -\"+r[r.length-1]+\",0 \",s=r.length-2;s>=0;s--)u+=\"C\"+c[s]+\",\"+(e[s+1]+i)+\" \"+l[s]+\",\"+(e[s]+i)+\" \"+(t[s]+r[s])+\",\"+(e[s]+i),u+=\"l-\"+r[s]+\",0 \";return u+=\"Z\"}function P(t){var e=t.dimensions,r=t.model,n=e.map(function(t){return t.categories.map(function(t){return t.y})}),i=t.model.dimensions.map(function(t){return t.categories.map(function(t){return t.displayInd})}),a=t.model.dimensions.map(function(t){return t.displayInd}),o=t.dimensions.map(function(t){return t.model.dimensionInd}),s=e.map(function(t){return t.x}),l=e.map(function(t){return t.width}),c=[];for(var u in r.paths)r.paths.hasOwnProperty(u)&&c.push(r.paths[u]);function f(t){var e=t.categoryInds.map(function(t,e){return i[e][t]});return o.map(function(t){return e[t]})}c.sort(function(e,r){var n=f(e),i=f(r);return\"backward\"===t.sortpaths&&(n.reverse(),i.reverse()),n.push(e.valueInds[0]),i.push(r.valueInds[0]),t.bundlecolors&&(n.unshift(e.rawColor),i.unshift(r.rawColor)),n<i?-1:n>i?1:0});for(var h=new Array(c.length),p=e[0].model.count,d=e[0].categories.map(function(t){return t.height}).reduce(function(t,e){return t+e}),g=0;g<c.length;g++){var v,m=c[g];v=p>0?d*(m.count/p):0;for(var y,x=new Array(n.length),b=0;b<m.categoryInds.length;b++){var _=m.categoryInds[b],w=i[b][_],k=a[b];x[k]=n[k][w],n[k][w]+=v;var T=t.dimensions[k].categories[w],A=T.bands.length,M=T.bands[A-1];if(void 0===M||m.rawColor!==M.rawColor){var S=void 0===M?0:M.y+M.height;T.bands.push({key:S,color:m.color,rawColor:m.rawColor,height:v,width:T.width,count:m.count,y:S,categoryViewModel:T,parcatsViewModel:t})}else{var E=T.bands[A-1];E.height+=v,E.count+=m.count}}y=\"hspline\"===t.pathShape?D(s,x,l,v,.5):D(s,x,l,v,0),h[g]={key:m.valueInds[0],model:m,height:v,leftXs:s,topYs:x,dimWidths:l,svgD:y,parcatsViewModel:t}}t.paths=h}function R(t){var e=t.model.dimensions.map(function(t){return{displayInd:t.displayInd,dimensionInd:t.dimensionInd}});e.sort(function(t,e){return t.displayInd-e.displayInd});var r=[];for(var n in e){var i=e[n].dimensionInd,a=t.model.dimensions[i];r.push(F(t,a))}t.dimensions=r}function F(t,e){var r,n=t.model.dimensions.length,i=e.displayInd;r=40+(n>1?(t.width-80-16)/(n-1):0)*i;var a,o,s,l,c,u=[],f=t.model.maxCats,h=e.categories.length,p=e.count,d=t.height-8*(f-1),g=8*(f-h)/2,v=e.categories.map(function(t){return{displayInd:t.displayInd,categoryInd:t.categoryInd}});for(v.sort(function(t,e){return t.displayInd-e.displayInd}),c=0;c<h;c++)l=v[c].categoryInd,o=e.categories[l],a=p>0?o.count/p*d:0,s={key:o.valueInds[0],model:o,width:16,height:a,y:null!==o.dragY?o.dragY:g,bands:[],parcatsViewModel:t},g=g+a+8,u.push(s);return{key:e.dimensionInd,x:null!==e.dragX?e.dragX:r,y:0,width:16,model:e,categories:u,parcatsViewModel:t,dragCategoryDisplayInd:null,dragDimensionDisplayInd:null,initialDragDimensionDisplayInds:null,initialDragCategoryDisplayInds:null,dragHasMoved:null,potentialClickBand:null}}e.exports=function(t,e,r,n){u(r,t,n,e)}},{\"../../components/drawing\":601,\"../../components/fx\":619,\"../../lib\":703,\"../../lib/svg_text_utils\":727,\"../../plot_api/plot_api\":738,d3:157,tinycolor2:524}],1037:[function(t,e,r){\"use strict\";var n=t(\"./parcats\");e.exports=function(t,e,r,i){var a=t._fullLayout,o=a._paper,s=a._size;n(t,o,e,{width:s.w,height:s.h,margin:{t:s.t,r:s.r,b:s.b,l:s.l}},r,i)}},{\"./parcats\":1036}],1038:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/cartesian/layout_attributes\"),a=t(\"../../plots/font_attributes\"),o=t(\"../../plots/domain\").attributes,s=t(\"../../lib/extend\").extendFlat,l=t(\"../../plot_api/plot_template\").templatedArray;e.exports={domain:o({name:\"parcoords\",trace:!0,editType:\"calc\"}),labelfont:a({editType:\"calc\"}),tickfont:a({editType:\"calc\"}),rangefont:a({editType:\"calc\"}),dimensions:l(\"dimension\",{label:{valType:\"string\",editType:\"calc\"},tickvals:s({},i.tickvals,{editType:\"calc\"}),ticktext:s({},i.ticktext,{editType:\"calc\"}),tickformat:{valType:\"string\",dflt:\"3s\",editType:\"calc\"},visible:{valType:\"boolean\",dflt:!0,editType:\"calc\"},range:{valType:\"info_array\",items:[{valType:\"number\",editType:\"calc\"},{valType:\"number\",editType:\"calc\"}],editType:\"calc\"},constraintrange:{valType:\"info_array\",freeLength:!0,dimensions:\"1-2\",items:[{valType:\"number\",editType:\"calc\"},{valType:\"number\",editType:\"calc\"}],editType:\"calc\"},multiselect:{valType:\"boolean\",dflt:!0,editType:\"calc\"},values:{valType:\"data_array\",editType:\"calc\"},editType:\"calc\"}),line:s({editType:\"calc\"},n(\"line\",{colorscaleDflt:\"Viridis\",autoColorDflt:!1,editTypeOverride:\"calc\"}))}},{\"../../components/colorscale/attributes\":587,\"../../lib/extend\":693,\"../../plot_api/plot_template\":741,\"../../plots/cartesian/layout_attributes\":763,\"../../plots/domain\":776,\"../../plots/font_attributes\":777}],1039:[function(t,e,r){\"use strict\";var n=t(\"./constants\"),i=t(\"d3\"),a=t(\"../../lib/gup\").keyFun,o=t(\"../../lib/gup\").repeat,s=t(\"../../lib\").sorterAsc,l=n.bar.snapRatio;function c(t,e){return t*(1-l)+e*l}var u=n.bar.snapClose;function f(t,e){return t*(1-u)+e*u}function h(t,e,r,n){if(function(t,e){for(var r=0;r<e.length;r++)if(t>=e[r][0]&&t<=e[r][1])return!0;return!1}(r,n))return r;var i=t?-1:1,a=0,o=e.length-1;if(i<0){var s=a;a=o,o=s}for(var l=e[a],u=l,h=a;i*h<i*o;h+=i){var p=h+i,d=e[p];if(i*r<i*f(l,d))return c(l,u);if(i*r<i*d||p===o)return c(d,l);u=l,l=d}}function p(t){t.attr(\"x\",-n.bar.captureWidth/2).attr(\"width\",n.bar.captureWidth)}function d(t){t.attr(\"visibility\",\"visible\").style(\"visibility\",\"visible\").attr(\"fill\",\"yellow\").attr(\"opacity\",0)}function g(t){if(!t.brush.filterSpecified)return\"0,\"+t.height;for(var e,r,n,i=v(t.brush.filter.getConsolidated(),t.height),a=[0],o=i.length?i[0][0]:null,s=0;s<i.length;s++)r=(e=i[s])[1]-e[0],a.push(o),a.push(r),(n=s+1)<i.length&&(o=i[n][0]-e[1]);return a.push(t.height),a}function v(t,e){return t.map(function(t){return t.map(function(t){return t*e}).sort(s)})}function m(){i.select(document.body).style(\"cursor\",null)}function y(t){t.attr(\"stroke-dasharray\",g)}function x(t,e){var r=i.select(t).selectAll(\".highlight, .highlight-shadow\");y(e?r.transition().duration(n.bar.snapDuration).each(\"end\",e):r)}function b(t,e){var r,i=t.brush,a=NaN,o={};if(i.filterSpecified){var s=t.height,l=i.filter.getConsolidated(),c=v(l,s),u=NaN,f=NaN,h=NaN;for(r=0;r<=c.length;r++){var p=c[r];if(p&&p[0]<=e&&e<=p[1]){u=r;break}if(f=r?r-1:NaN,p&&p[0]>e){h=r;break}}if(a=u,isNaN(a)&&(a=isNaN(f)||isNaN(h)?isNaN(f)?h:f:e-c[f][1]<c[h][0]-e?f:h),!isNaN(a)){var d=c[a],g=function(t,e){var r=n.bar.handleHeight;if(!(e>t[1]+r||e<t[0]-r))return e>=.9*t[1]+.1*t[0]?\"n\":e<=.9*t[0]+.1*t[1]?\"s\":\"ns\"}(d,e);g&&(o.interval=l[a],o.intervalPix=d,o.region=g)}}if(t.ordinal&&!o.region){var m=t.unitTickvals,y=t.unitToPaddedPx.invert(e);for(r=0;r<m.length;r++){var x=[.25*m[Math.max(r-1,0)]+.75*m[r],.25*m[Math.min(r+1,m.length-1)]+.75*m[r]];if(y>=x[0]&&y<=x[1]){o.clickableOrdinalRange=x;break}}}return o}function _(t){t.on(\"mousemove\",function(t){if(i.event.preventDefault(),!t.parent.inBrushDrag){var e=b(t,t.height-i.mouse(this)[1]-2*n.verticalPadding),r=\"crosshair\";e.clickableOrdinalRange?r=\"pointer\":e.region&&(r=e.region+\"-resize\"),i.select(document.body).style(\"cursor\",r)}}).on(\"mouseleave\",function(t){t.parent.inBrushDrag||m()}).call(i.behavior.drag().on(\"dragstart\",function(t){i.event.sourceEvent.stopPropagation();var e=t.height-i.mouse(this)[1]-2*n.verticalPadding,r=t.unitToPaddedPx.invert(e),a=t.brush,o=b(t,e),s=o.interval,l=a.svgBrush;if(l.wasDragged=!1,l.grabbingBar=\"ns\"===o.region,l.grabbingBar){var c=s.map(t.unitToPaddedPx);l.grabPoint=e-c[0]-n.verticalPadding,l.barLength=c[1]-c[0]}l.clickableOrdinalRange=o.clickableOrdinalRange,l.stayingIntervals=t.multiselect&&a.filterSpecified?a.filter.getConsolidated():[],s&&(l.stayingIntervals=l.stayingIntervals.filter(function(t){return t[0]!==s[0]&&t[1]!==s[1]})),l.startExtent=o.region?s[\"s\"===o.region?1:0]:r,t.parent.inBrushDrag=!0,l.brushStartCallback()}).on(\"drag\",function(t){i.event.sourceEvent.stopPropagation();var e=t.height-i.mouse(this)[1]-2*n.verticalPadding,r=t.brush.svgBrush;r.wasDragged=!0,r.grabbingBar?r.newExtent=[e-r.grabPoint,e+r.barLength-r.grabPoint].map(t.unitToPaddedPx.invert):r.newExtent=[r.startExtent,t.unitToPaddedPx.invert(e)].sort(s);var a=Math.max(0,-r.newExtent[0]),o=Math.max(0,r.newExtent[1]-1);r.newExtent[0]+=a,r.newExtent[1]-=o,r.grabbingBar&&(r.newExtent[1]+=a,r.newExtent[0]-=o),t.brush.filterSpecified=!0,r.extent=r.stayingIntervals.concat([r.newExtent]),r.brushCallback(t),x(this.parentNode)}).on(\"dragend\",function(t){i.event.sourceEvent.stopPropagation();var e=t.brush,r=e.filter,n=e.svgBrush,a=n.grabbingBar;if(n.grabbingBar=!1,n.grabLocation=void 0,t.parent.inBrushDrag=!1,m(),!n.wasDragged)return n.wasDragged=void 0,n.clickableOrdinalRange?e.filterSpecified&&t.multiselect?n.extent.push(n.clickableOrdinalRange):(n.extent=[n.clickableOrdinalRange],e.filterSpecified=!0):a?(n.extent=n.stayingIntervals,0===n.extent.length&&k(e)):k(e),n.brushCallback(t),x(this.parentNode),void n.brushEndCallback(e.filterSpecified?r.getConsolidated():[]);var o=function(){r.set(r.getConsolidated())};if(t.ordinal){var s=t.unitTickvals;s[s.length-1]<s[0]&&s.reverse(),n.newExtent=[h(0,s,n.newExtent[0],n.stayingIntervals),h(1,s,n.newExtent[1],n.stayingIntervals)];var l=n.newExtent[1]>n.newExtent[0];n.extent=n.stayingIntervals.concat(l?[n.newExtent]:[]),n.extent.length||k(e),n.brushCallback(t),l?x(this.parentNode,o):(o(),x(this.parentNode))}else o();n.brushEndCallback(e.filterSpecified?r.getConsolidated():[])}))}function w(t,e){return t[0]-e[0]}function k(t){t.filterSpecified=!1,t.svgBrush.extent=[[0,1]]}function T(t){for(var e,r=t.slice(),n=[],i=r.shift();i;){for(e=i.slice();(i=r.shift())&&i[0]<=e[1];)e[1]=Math.max(e[1],i[1]);n.push(e)}return n}e.exports={makeBrush:function(t,e,r,n,i,a){var o,l=function(){var t,e,r=[];return{set:function(n){r=n.map(function(t){return t.slice().sort(s)}).sort(w),t=T(r),e=r.reduce(function(t,e){return[Math.min(t[0],e[0]),Math.max(t[1],e[1])]},[1/0,-1/0])},get:function(){return r.slice()},getConsolidated:function(){return t},getBounds:function(){return e}}}();return l.set(r),{filter:l,filterSpecified:e,svgBrush:{extent:[],brushStartCallback:n,brushCallback:(o=i,function(t){var e=t.brush,r=function(t){return t.svgBrush.extent.map(function(t){return t.slice()})}(e).slice();e.filter.set(r),o()}),brushEndCallback:a}}},ensureAxisBrush:function(t){var e=t.selectAll(\".\"+n.cn.axisBrush).data(o,a);e.enter().append(\"g\").classed(n.cn.axisBrush,!0),function(t){var e=t.selectAll(\".background\").data(o);e.enter().append(\"rect\").classed(\"background\",!0).call(p).call(d).style(\"pointer-events\",\"auto\").attr(\"transform\",\"translate(0 \"+n.verticalPadding+\")\"),e.call(_).attr(\"height\",function(t){return t.height-n.verticalPadding});var r=t.selectAll(\".highlight-shadow\").data(o);r.enter().append(\"line\").classed(\"highlight-shadow\",!0).attr(\"x\",-n.bar.width/2).attr(\"stroke-width\",n.bar.width+n.bar.strokeWidth).attr(\"stroke\",n.bar.strokeColor).attr(\"opacity\",n.bar.strokeOpacity).attr(\"stroke-linecap\",\"butt\"),r.attr(\"y1\",function(t){return t.height}).call(y);var i=t.selectAll(\".highlight\").data(o);i.enter().append(\"line\").classed(\"highlight\",!0).attr(\"x\",-n.bar.width/2).attr(\"stroke-width\",n.bar.width-n.bar.strokeWidth).attr(\"stroke\",n.bar.fillColor).attr(\"opacity\",n.bar.fillOpacity).attr(\"stroke-linecap\",\"butt\"),i.attr(\"y1\",function(t){return t.height}).call(y)}(e)},cleanRanges:function(t,e){if(Array.isArray(t[0])?(t=t.map(function(t){return t.sort(s)}),t=e.multiselect?T(t.sort(w)):[t[0]]):t=[t.sort(s)],e.tickvals){var r=e.tickvals.slice().sort(s);if(!(t=t.map(function(t){var e=[h(0,r,t[0],[]),h(1,r,t[1],[])];if(e[1]>e[0])return e}).filter(function(t){return t})).length)return}return t.length>1?t:t[0]}}},{\"../../lib\":703,\"../../lib/gup\":701,\"./constants\":1042,d3:157}],1040:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../plots/get_data\").getModuleCalcData,a=t(\"./plot\"),o=t(\"../../constants/xmlns_namespaces\");r.name=\"parcoords\",r.plot=function(t){var e=i(t.calcdata,\"parcoords\")[0];e.length&&a(t,e)},r.clean=function(t,e,r,n){var i=n._has&&n._has(\"parcoords\"),a=e._has&&e._has(\"parcoords\");i&&!a&&(n._paperdiv.selectAll(\".parcoords\").remove(),n._glimages.selectAll(\"*\").remove())},r.toSVG=function(t){var e=t._fullLayout._glimages,r=n.select(t).selectAll(\".svg-container\");r.filter(function(t,e){return e===r.size()-1}).selectAll(\".gl-canvas-context, .gl-canvas-focus\").each(function(){var t=this.toDataURL(\"image/png\");e.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":t,preserveAspectRatio:\"none\",x:0,y:0,width:this.width,height:this.height})}),window.setTimeout(function(){n.selectAll(\"#filterBarPattern\").attr(\"id\",\"filterBarPattern\")},60)}},{\"../../constants/xmlns_namespaces\":681,\"../../plots/get_data\":786,\"./plot\":1048,d3:157}],1041:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale\"),i=t(\"../../lib\"),a=t(\"../../lib/gup\").wrap;function o(t){return i.isTypedArray(t)?Array.prototype.slice.call(t):t}e.exports=function(t,e){for(var r=0;r<e.dimensions.length;r++)e.dimensions[r].values=o(e.dimensions[r].values);var i,s;return e.line.color=o(e.line.color),n.hasColorscale(e,\"line\")&&Array.isArray(e.line.color)?(i=e.line.color,s=n.extractOpts(e.line).colorscale,n.calc(t,e,{vals:i,containerStr:\"line\",cLetter:\"c\"})):(i=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=.5;return e}(e._length),s=[[0,e.line.color],[1,e.line.color]]),a({lineColor:i,cscale:s})}},{\"../../components/colorscale\":592,\"../../lib\":703,\"../../lib/gup\":701}],1042:[function(t,e,r){\"use strict\";e.exports={maxDimensionCount:60,overdrag:45,verticalPadding:2,tickDistance:50,canvasPixelRatio:1,blockLineCount:5e3,layers:[\"contextLineLayer\",\"focusLineLayer\",\"pickLineLayer\"],axisTitleOffset:28,axisExtentOffset:10,bar:{width:4,captureWidth:10,fillColor:\"magenta\",fillOpacity:1,snapDuration:150,snapRatio:.25,snapClose:.01,strokeColor:\"white\",strokeOpacity:1,strokeWidth:1,handleHeight:8,handleOpacity:1,handleOverlap:0},cn:{axisExtentText:\"axis-extent-text\",parcoordsLineLayers:\"parcoords-line-layers\",parcoordsLineLayer:\"parcoords-lines\",parcoords:\"parcoords\",parcoordsControlView:\"parcoords-control-view\",yAxis:\"y-axis\",axisOverlays:\"axis-overlays\",axis:\"axis\",axisHeading:\"axis-heading\",axisTitle:\"axis-title\",axisExtent:\"axis-extent\",axisExtentTop:\"axis-extent-top\",axisExtentTopText:\"axis-extent-top-text\",axisExtentBottom:\"axis-extent-bottom\",axisExtentBottomText:\"axis-extent-bottom-text\",axisBrush:\"axis-brush\"},id:{filterBarPattern:\"filter-bar-pattern\"}}},{}],1043:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/colorscale/helpers\").hasColorscale,a=t(\"../../components/colorscale/defaults\"),o=t(\"../../plots/domain\").defaults,s=t(\"../../plots/array_container_defaults\"),l=t(\"./attributes\"),c=t(\"./axisbrush\"),u=t(\"./constants\").maxDimensionCount,f=t(\"./merge_length\");function h(t,e){function r(r,i){return n.coerce(t,e,l.dimensions,r,i)}var i=r(\"values\"),a=r(\"visible\");if(i&&i.length||(a=e.visible=!1),a){r(\"label\"),r(\"tickvals\"),r(\"ticktext\"),r(\"tickformat\"),r(\"range\"),r(\"multiselect\");var o=r(\"constraintrange\");o&&(e.constraintrange=c.cleanRanges(o,e))}}e.exports=function(t,e,r,c){function p(r,i){return n.coerce(t,e,l,r,i)}var d=t.dimensions;Array.isArray(d)&&d.length>u&&(n.log(\"parcoords traces support up to \"+u+\" dimensions at the moment\"),d.splice(u));var g=s(t,e,{name:\"dimensions\",handleItemDefaults:h}),v=function(t,e,r,o,s){var l=s(\"line.color\",r);if(i(t,\"line\")&&n.isArrayOrTypedArray(l)){if(l.length)return s(\"line.colorscale\"),a(t,e,o,s,{prefix:\"line.\",cLetter:\"c\"}),l.length;e.line.color=r}return 1/0}(t,e,r,c,p);o(e,c,p),Array.isArray(g)&&g.length||(e.visible=!1),f(e,g,\"values\",v);var m={family:c.font.family,size:Math.round(c.font.size/1.2),color:c.font.color};n.coerceFont(p,\"labelfont\",m),n.coerceFont(p,\"tickfont\",m),n.coerceFont(p,\"rangefont\",m)}},{\"../../components/colorscale/defaults\":590,\"../../components/colorscale/helpers\":591,\"../../lib\":703,\"../../plots/array_container_defaults\":747,\"../../plots/domain\":776,\"./attributes\":1038,\"./axisbrush\":1039,\"./constants\":1042,\"./merge_length\":1046}],1044:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\"),plot:t(\"./plot\"),colorbar:{container:\"line\",min:\"cmin\",max:\"cmax\"},moduleType:\"trace\",name:\"parcoords\",basePlotModule:t(\"./base_plot\"),categories:[\"gl\",\"regl\",\"noOpacity\",\"noHover\"],meta:{}}},{\"./attributes\":1038,\"./base_plot\":1040,\"./calc\":1041,\"./defaults\":1043,\"./plot\":1048}],1045:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 p0, p1, p2, p3,\\n p4, p5, p6, p7,\\n p8, p9, pa, pb,\\n pc, pd, pe;\\n\\nattribute vec4 pf;\\n\\nuniform mat4 dim1A, dim2A, dim1B, dim2B, dim1C, dim2C, dim1D, dim2D,\\n loA, hiA, loB, hiB, loC, hiC, loD, hiD;\\n\\nuniform vec2 resolution,\\n viewBoxPosition,\\n viewBoxSize;\\n\\nuniform sampler2D palette;\\nuniform sampler2D mask;\\nuniform float maskHeight;\\n\\nuniform vec2 colorClamp;\\n\\nvarying vec4 fragColor;\\n\\nvec4 unit_1 = vec4(1, 1, 1, 1);\\n\\nfloat val(mat4 p, mat4 v) {\\n return dot(matrixCompMult(p, v) * unit_1, unit_1);\\n}\\n\\nfloat axisY(\\n float x,\\n mat4 d[4],\\n mat4 dim1A, mat4 dim2A, mat4 dim1B, mat4 dim2B, mat4 dim1C, mat4 dim2C, mat4 dim1D, mat4 dim2D\\n ) {\\n\\n float y1 = val(d[0], dim1A) + val(d[1], dim1B) + val(d[2], dim1C) + val(d[3], dim1D);\\n float y2 = val(d[0], dim2A) + val(d[1], dim2B) + val(d[2], dim2C) + val(d[3], dim2D);\\n return y1 * (1.0 - x) + y2 * x;\\n}\\n\\nconst int bitsPerByte = 8;\\n\\nint mod2(int a) {\\n return a - 2 * (a / 2);\\n}\\n\\nint mod8(int a) {\\n return a - 8 * (a / 8);\\n}\\n\\nvec4 zero = vec4(0, 0, 0, 0);\\nvec4 unit_0 = vec4(1, 1, 1, 1);\\nvec2 xyProjection = vec2(1, 1);\\n\\nmat4 mclamp(mat4 m, mat4 lo, mat4 hi) {\\n return mat4(clamp(m[0], lo[0], hi[0]),\\n clamp(m[1], lo[1], hi[1]),\\n clamp(m[2], lo[2], hi[2]),\\n clamp(m[3], lo[3], hi[3]));\\n}\\n\\nbool mshow(mat4 p, mat4 lo, mat4 hi) {\\n return mclamp(p, lo, hi) == p;\\n}\\n\\nbool withinBoundingBox(\\n mat4 d[4],\\n mat4 loA, mat4 hiA, mat4 loB, mat4 hiB, mat4 loC, mat4 hiC, mat4 loD, mat4 hiD\\n ) {\\n\\n return mshow(d[0], loA, hiA) &&\\n mshow(d[1], loB, hiB) &&\\n mshow(d[2], loC, hiC) &&\\n mshow(d[3], loD, hiD);\\n}\\n\\nbool withinRasterMask(mat4 d[4], sampler2D mask, float height) {\\n bool result = true;\\n int bitInByteStepper;\\n float valY, valueY, scaleX;\\n int hit, bitmask, valX;\\n for(int i = 0; i < 4; i++) {\\n for(int j = 0; j < 4; j++) {\\n for(int k = 0; k < 4; k++) {\\n bitInByteStepper = mod8(j * 4 + k);\\n valX = i * 2 + j / 2;\\n valY = d[i][j][k];\\n valueY = valY * (height - 1.0) + 0.5;\\n scaleX = (float(valX) + 0.5) / 8.0;\\n hit = int(texture2D(mask, vec2(scaleX, (valueY + 0.5) / height))[3] * 255.0) / int(pow(2.0, float(bitInByteStepper)));\\n result = result && mod2(hit) == 1;\\n }\\n }\\n }\\n return result;\\n}\\n\\nvec4 position(\\n float depth,\\n vec2 resolution, vec2 viewBoxPosition, vec2 viewBoxSize,\\n mat4 dims[4],\\n float signum,\\n mat4 dim1A, mat4 dim2A, mat4 dim1B, mat4 dim2B, mat4 dim1C, mat4 dim2C, mat4 dim1D, mat4 dim2D,\\n mat4 loA, mat4 hiA, mat4 loB, mat4 hiB, mat4 loC, mat4 hiC, mat4 loD, mat4 hiD,\\n sampler2D mask, float maskHeight\\n ) {\\n\\n float x = 0.5 * signum + 0.5;\\n float y = axisY(x, dims, dim1A, dim2A, dim1B, dim2B, dim1C, dim2C, dim1D, dim2D);\\n\\n float show = float(\\n withinBoundingBox(dims, loA, hiA, loB, hiB, loC, hiC, loD, hiD)\\n && withinRasterMask(dims, mask, maskHeight)\\n );\\n\\n vec2 viewBoxXY = viewBoxPosition + viewBoxSize * vec2(x, y);\\n float depthOrHide = depth + 2.0 * (1.0 - show);\\n\\n return vec4(\\n xyProjection * (2.0 * viewBoxXY / resolution - 1.0),\\n depthOrHide,\\n 1.0\\n );\\n}\\n\\nvoid main() {\\n\\n float prominence = abs(pf[3]);\\n\\n mat4 p[4];\\n p[0] = mat4(p0, p1, p2, p3);\\n p[1] = mat4(p4, p5, p6, p7);\\n p[2] = mat4(p8, p9, pa, pb);\\n p[3] = mat4(pc, pd, pe, abs(pf));\\n\\n gl_Position = position(\\n 1.0 - prominence,\\n resolution, viewBoxPosition, viewBoxSize,\\n p,\\n sign(pf[3]),\\n dim1A, dim2A, dim1B, dim2B, dim1C, dim2C, dim1D, dim2D,\\n loA, hiA, loB, hiB, loC, hiC, loD, hiD,\\n mask, maskHeight\\n );\\n\\n float clampedColorIndex = clamp((prominence - colorClamp[0]) / (colorClamp[1] - colorClamp[0]), 0.0, 1.0);\\n fragColor = texture2D(palette, vec2((clampedColorIndex * 255.0 + 0.5) / 256.0, 0.5));\\n}\\n\"]),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 p0, p1, p2, p3,\\n p4, p5, p6, p7,\\n p8, p9, pa, pb,\\n pc, pd, pe;\\n\\nattribute vec4 pf;\\n\\nuniform mat4 dim1A, dim2A, dim1B, dim2B, dim1C, dim2C, dim1D, dim2D;\\n\\nuniform vec2 resolution,\\n viewBoxPosition,\\n viewBoxSize;\\n\\nuniform sampler2D palette;\\n\\nuniform vec2 colorClamp;\\n\\nvarying vec4 fragColor;\\n\\nvec2 xyProjection = vec2(1, 1);\\n\\nvec4 unit = vec4(1, 1, 1, 1);\\n\\nfloat val(mat4 p, mat4 v) {\\n return dot(matrixCompMult(p, v) * unit, unit);\\n}\\n\\nfloat axisY(\\n float x,\\n mat4 d[4],\\n mat4 dim1A, mat4 dim2A, mat4 dim1B, mat4 dim2B, mat4 dim1C, mat4 dim2C, mat4 dim1D, mat4 dim2D\\n ) {\\n\\n float y1 = val(d[0], dim1A) + val(d[1], dim1B) + val(d[2], dim1C) + val(d[3], dim1D);\\n float y2 = val(d[0], dim2A) + val(d[1], dim2B) + val(d[2], dim2C) + val(d[3], dim2D);\\n return y1 * (1.0 - x) + y2 * x;\\n}\\n\\nvec4 position(\\n float depth,\\n vec2 resolution, vec2 viewBoxPosition, vec2 viewBoxSize,\\n mat4 dims[4],\\n float signum,\\n mat4 dim1A, mat4 dim2A, mat4 dim1B, mat4 dim2B, mat4 dim1C, mat4 dim2C, mat4 dim1D, mat4 dim2D\\n ) {\\n\\n float x = 0.5 * signum + 0.5;\\n float y = axisY(x, dims, dim1A, dim2A, dim1B, dim2B, dim1C, dim2C, dim1D, dim2D);\\n\\n vec2 viewBoxXY = viewBoxPosition + viewBoxSize * vec2(x, y);\\n\\n return vec4(\\n xyProjection * (2.0 * viewBoxXY / resolution - 1.0),\\n depth,\\n 1.0\\n );\\n}\\n\\nvoid main() {\\n\\n float prominence = abs(pf[3]);\\n\\n mat4 p[4];\\n p[0] = mat4(p0, p1, p2, p3);\\n p[1] = mat4(p4, p5, p6, p7);\\n p[2] = mat4(p8, p9, pa, pb);\\n p[3] = mat4(pc, pd, pe, abs(pf));\\n\\n gl_Position = position(\\n 1.0 - prominence,\\n resolution, viewBoxPosition, viewBoxSize,\\n p,\\n sign(pf[3]),\\n dim1A, dim2A, dim1B, dim2B, dim1C, dim2C, dim1D, dim2D\\n );\\n\\n float clampedColorIndex = clamp((prominence - colorClamp[0]) / (colorClamp[1] - colorClamp[0]), 0.0, 1.0);\\n fragColor = texture2D(palette, vec2((clampedColorIndex * 255.0 + 0.5) / 256.0, 0.5));\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 p0, p1, p2, p3,\\n p4, p5, p6, p7,\\n p8, p9, pa, pb,\\n pc, pd, pe;\\n\\nattribute vec4 pf;\\n\\nuniform mat4 dim1A, dim2A, dim1B, dim2B, dim1C, dim2C, dim1D, dim2D,\\n loA, hiA, loB, hiB, loC, hiC, loD, hiD;\\n\\nuniform vec2 resolution,\\n viewBoxPosition,\\n viewBoxSize;\\n\\nuniform sampler2D mask;\\nuniform float maskHeight;\\n\\nuniform vec2 colorClamp;\\n\\nvarying vec4 fragColor;\\n\\nvec4 unit_1 = vec4(1, 1, 1, 1);\\n\\nfloat val(mat4 p, mat4 v) {\\n return dot(matrixCompMult(p, v) * unit_1, unit_1);\\n}\\n\\nfloat axisY(\\n float x,\\n mat4 d[4],\\n mat4 dim1A, mat4 dim2A, mat4 dim1B, mat4 dim2B, mat4 dim1C, mat4 dim2C, mat4 dim1D, mat4 dim2D\\n ) {\\n\\n float y1 = val(d[0], dim1A) + val(d[1], dim1B) + val(d[2], dim1C) + val(d[3], dim1D);\\n float y2 = val(d[0], dim2A) + val(d[1], dim2B) + val(d[2], dim2C) + val(d[3], dim2D);\\n return y1 * (1.0 - x) + y2 * x;\\n}\\n\\nconst int bitsPerByte = 8;\\n\\nint mod2(int a) {\\n return a - 2 * (a / 2);\\n}\\n\\nint mod8(int a) {\\n return a - 8 * (a / 8);\\n}\\n\\nvec4 zero = vec4(0, 0, 0, 0);\\nvec4 unit_0 = vec4(1, 1, 1, 1);\\nvec2 xyProjection = vec2(1, 1);\\n\\nmat4 mclamp(mat4 m, mat4 lo, mat4 hi) {\\n return mat4(clamp(m[0], lo[0], hi[0]),\\n clamp(m[1], lo[1], hi[1]),\\n clamp(m[2], lo[2], hi[2]),\\n clamp(m[3], lo[3], hi[3]));\\n}\\n\\nbool mshow(mat4 p, mat4 lo, mat4 hi) {\\n return mclamp(p, lo, hi) == p;\\n}\\n\\nbool withinBoundingBox(\\n mat4 d[4],\\n mat4 loA, mat4 hiA, mat4 loB, mat4 hiB, mat4 loC, mat4 hiC, mat4 loD, mat4 hiD\\n ) {\\n\\n return mshow(d[0], loA, hiA) &&\\n mshow(d[1], loB, hiB) &&\\n mshow(d[2], loC, hiC) &&\\n mshow(d[3], loD, hiD);\\n}\\n\\nbool withinRasterMask(mat4 d[4], sampler2D mask, float height) {\\n bool result = true;\\n int bitInByteStepper;\\n float valY, valueY, scaleX;\\n int hit, bitmask, valX;\\n for(int i = 0; i < 4; i++) {\\n for(int j = 0; j < 4; j++) {\\n for(int k = 0; k < 4; k++) {\\n bitInByteStepper = mod8(j * 4 + k);\\n valX = i * 2 + j / 2;\\n valY = d[i][j][k];\\n valueY = valY * (height - 1.0) + 0.5;\\n scaleX = (float(valX) + 0.5) / 8.0;\\n hit = int(texture2D(mask, vec2(scaleX, (valueY + 0.5) / height))[3] * 255.0) / int(pow(2.0, float(bitInByteStepper)));\\n result = result && mod2(hit) == 1;\\n }\\n }\\n }\\n return result;\\n}\\n\\nvec4 position(\\n float depth,\\n vec2 resolution, vec2 viewBoxPosition, vec2 viewBoxSize,\\n mat4 dims[4],\\n float signum,\\n mat4 dim1A, mat4 dim2A, mat4 dim1B, mat4 dim2B, mat4 dim1C, mat4 dim2C, mat4 dim1D, mat4 dim2D,\\n mat4 loA, mat4 hiA, mat4 loB, mat4 hiB, mat4 loC, mat4 hiC, mat4 loD, mat4 hiD,\\n sampler2D mask, float maskHeight\\n ) {\\n\\n float x = 0.5 * signum + 0.5;\\n float y = axisY(x, dims, dim1A, dim2A, dim1B, dim2B, dim1C, dim2C, dim1D, dim2D);\\n\\n float show = float(\\n withinBoundingBox(dims, loA, hiA, loB, hiB, loC, hiC, loD, hiD)\\n && withinRasterMask(dims, mask, maskHeight)\\n );\\n\\n vec2 viewBoxXY = viewBoxPosition + viewBoxSize * vec2(x, y);\\n float depthOrHide = depth + 2.0 * (1.0 - show);\\n\\n return vec4(\\n xyProjection * (2.0 * viewBoxXY / resolution - 1.0),\\n depthOrHide,\\n 1.0\\n );\\n}\\n\\nvoid main() {\\n\\n float prominence = abs(pf[3]);\\n\\n mat4 p[4];\\n p[0] = mat4(p0, p1, p2, p3);\\n p[1] = mat4(p4, p5, p6, p7);\\n p[2] = mat4(p8, p9, pa, pb);\\n p[3] = mat4(pc, pd, pe, abs(pf));\\n\\n gl_Position = position(\\n 1.0 - prominence,\\n resolution, viewBoxPosition, viewBoxSize,\\n p,\\n sign(pf[3]),\\n dim1A, dim2A, dim1B, dim2B, dim1C, dim2C, dim1D, dim2D,\\n loA, hiA, loB, hiB, loC, hiC, loD, hiD,\\n mask, maskHeight\\n );\\n\\n fragColor = vec4(pf.rgb, 1.0);\\n}\\n\"]),s=n([\"precision lowp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n gl_FragColor = fragColor;\\n}\\n\"]),l=t(\"../../lib\"),c=1e-6,u=1e-7,f=2048,h=64,p=2,d=4,g=8,v=h/g,m=[119,119,119],y=new Uint8Array(4),x=new Uint8Array(4),b={shape:[256,1],format:\"rgba\",type:\"uint8\",mag:\"nearest\",min:\"nearest\"};function _(t,e,r,n,i){var a=t._gl;a.enable(a.SCISSOR_TEST),a.scissor(e,r,n,i),t.clear({color:[0,0,0,0],depth:1})}function w(t,e,r,n,i,a){var o=a.key;r.drawCompleted||(!function(t){t.read({x:0,y:0,width:1,height:1,data:y})}(t),r.drawCompleted=!0),function s(l){var c;c=Math.min(n,i-l*n),a.offset=p*l*n,a.count=p*c,0===l&&(window.cancelAnimationFrame(r.currentRafs[o]),delete 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O(t){r=t.model,n=t.viewModel,p=n.dimensions.slice(),d=p[0]?p[0].values.length:0;var e=r.lines,i=M?e.color.map(function(t,r){return r/e.color.length}):e.color,a=Math.max(1/255,Math.pow(1/i.length,1/3)),o=function(t,e,r){for(var n,i=e.length,a=[],o=0;o<t;o++)for(var s=0;s<h;s++)a.push(s<i?e[s].paddedUnitValues[o]:s===h-1?(n=r[o],Math.max(c,Math.min(1-c,n))):s>=h-4?k(o,h-2-s):.5);return a}(d,p,i);!function(t,e,r){for(var n=0;n<16;n++)t[\"p\"+n.toString(16)](T(e,r,n))}(C,d,o),L=S.texture(l.extendFlat({data:function(t,e,r){for(var n=[],i=0;i<256;i++){var a=t(i/255);n.push((e?m:a).concat(r))}return n}(r.unitToColor,A,Math.round(255*(A?a:1)))},b))}var I=[0,1];var D=[];function P(t,e,n,i,a,o,s,c,u,f,h){var p,d,g,v,m=[t,e],y=[0,1].map(function(){return[0,1,2,3].map(function(){return new Float32Array(16)})});for(p=0;p<2;p++)for(v=m[p],d=0;d<4;d++)for(g=0;g<16;g++)y[p][d][g]=g+16*d===v?1:0;var x=r.lines.canvasOverdrag,b=r.domain,_=r.canvasWidth,w=r.canvasHeight;return l.extendFlat({key:s,resolution:[_,w],viewBoxPosition:[n+x,i],viewBoxSize:[a,o],i:t,ii:e,dim1A:y[0][0],dim1B:y[0][1],dim1C:y[0][2],dim1D:y[0][3],dim2A:y[1][0],dim2B:y[1][1],dim2C:y[1][2],dim2D:y[1][3],colorClamp:I,scissorX:(c===u?0:n+x)+(r.pad.l-x)+r.layoutWidth*b.x[0],scissorWidth:(c===f?_-n+x:a+.5)+(c===u?n+x:0),scissorY:i+r.pad.b+r.layoutHeight*b.y[0],scissorHeight:o,viewportX:r.pad.l-x+r.layoutWidth*b.x[0],viewportY:r.pad.b+r.layoutHeight*b.y[0],viewportWidth:_,viewportHeight:w},h)}return{setColorDomain:function(t){I[0]=t[0],I[1]=t[1]},render:function(t,e,n){var i,a,o,s=t.length,l=1/0,c=-1/0;for(i=0;i<s;i++)t[i].dim2.canvasX>c&&(c=t[i].dim2.canvasX,o=i),t[i].dim1.canvasX<l&&(l=t[i].dim1.canvasX,a=i);0===s&&_(S,0,0,r.canvasWidth,r.canvasHeight);var h=A?{}:function(){var t,e,r,n=[0,1].map(function(){return[0,1,2,3].map(function(){return new Float32Array(16)})});for(t=0;t<2;t++)for(e=0;e<4;e++)for(r=0;r<16;r++){var i,a=r+16*e;i=a<p.length?p[a].brush.filter.getBounds()[t]:t,n[t][e][r]=i+(2*t-1)*u}function o(t,e){var r=f-1;return[Math.max(0,Math.floor(e[0]*r)),Math.min(r,Math.ceil(e[1]*r))]}for(var s=Array.apply(null,new Array(f*v)).map(function(){return 255}),l=0;l<p.length;l++){var c=l%g,h=(l-c)/g,d=Math.pow(2,c),m=p[l],x=m.brush.filter.get();if(!(x.length<2))for(var b=o(0,x[0])[1],_=1;_<x.length;_++){for(var w=o(0,x[_]),k=b+1;k<w[0];k++)s[k*v+h]&=~d;b=Math.max(b,w[1])}}var T={shape:[v,f],format:\"alpha\",type:\"uint8\",mag:\"nearest\",min:\"nearest\",data:s};return y?y(T):y=S.texture(T),{maskTexture:y,maskHeight:f,loA:n[0][0],loB:n[0][1],loC:n[0][2],loD:n[0][3],hiA:n[1][0],hiB:n[1][1],hiC:n[1][2],hiD:n[1][3]}}();for(i=0;i<s;i++){var m=t[i],x=m.dim1,b=x.crossfilterDimensionIndex,k=m.canvasX,T=m.canvasY,M=m.dim2.crossfilterDimensionIndex,C=m.panelSizeX,L=m.panelSizeY,O=k+C;if(e||!D[b]||D[b][0]!==k||D[b][1]!==O){D[b]=[k,O];var 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g(t){return!(\"visible\"in t)||t.visible}function v(t){var e=t.range?t.range[0]:a.aggNums(Math.min,null,t.values,t._length),r=t.range?t.range[1]:a.aggNums(Math.max,null,t.values,t._length);return!isNaN(e)&&isFinite(e)||(e=0),!isNaN(r)&&isFinite(r)||(r=0),e===r&&(0===e?(e-=1,r+=1):(e*=.9,r*=1.1)),[e,r]}function m(t){return t.dimensions.some(function(t){return t.brush.filterSpecified})}function y(t,e,r){var o=f(e),l=o.trace,c=o.lineColor,u=l.line,p=s.extractOpts(u),d=p.reversescale?s.flipScale(o.cscale):o.cscale,m=l.domain,y=l.dimensions,x=t.width,b=l.labelfont,_=l.tickfont,w=l.rangefont,k=a.extendDeepNoArrays({},u,{color:c.map(n.scale.linear().domain(v({values:c,range:[p.min,p.max],_length:l._length}))),blockLineCount:h.blockLineCount,canvasOverdrag:h.overdrag*h.canvasPixelRatio}),T=Math.floor(x*(m.x[1]-m.x[0])),A=Math.floor(t.height*(m.y[1]-m.y[0])),M=t.margin||{l:80,r:80,t:100,b:80},S=T,E=A;return{key:r,colCount:y.filter(g).length,dimensions:y,tickDistance:h.tickDistance,unitToColor:function(t){var e=t.map(function(t){return t[0]}),r=t.map(function(t){var e=i(t[1]);return n.rgb(\"rgb(\"+e[0]+\",\"+e[1]+\",\"+e[2]+\")\")}),a=\"rgb\".split(\"\").map(function(t){return n.scale.linear().clamp(!0).domain(e).range(r.map((i=t,function(t){return t[i]})));var i});return function(t){return a.map(function(e){return e(t)})}}(d),lines:k,labelFont:b,tickFont:_,rangeFont:w,layoutWidth:x,layoutHeight:t.height,domain:m,translateX:m.x[0]*x,translateY:t.height-m.y[1]*t.height,pad:M,canvasWidth:S*h.canvasPixelRatio+2*k.canvasOverdrag,canvasHeight:E*h.canvasPixelRatio,width:S,height:E,canvasPixelRatio:h.canvasPixelRatio}}function x(t,e,r){var i=r.width,o=r.height,s=r.dimensions,l=r.canvasPixelRatio,c=function(t){return i*t/Math.max(1,r.colCount-1)},u=h.verticalPadding/o,f=function(t,e){return n.scale.linear().range([e,t-e])}(o,h.verticalPadding),d={key:r.key,xScale:c,model:r,inBrushDrag:!1},y={};return d.dimensions=s.filter(g).map(function(i,s){var g=function(t,e){return n.scale.linear().domain(v(t)).range([e,1-e])}(i,u),x=y[i.label];y[i.label]=(x||0)+1;var b=i.label+(x?\"__\"+x:\"\"),_=i.constraintrange,w=_&&_.length;w&&!Array.isArray(_[0])&&(_=[_]);var k=w?_.map(function(t){return t.map(g)}):[[0,1]],T=i.values;T.length>i._length&&(T=T.slice(0,i._length));var A,M=i.tickvals;function S(t,e){return{val:t,text:A[e]}}function E(t,e){return t.val-e.val}if(Array.isArray(M)&&M.length){A=i.ticktext,Array.isArray(A)&&A.length?A.length>M.length?A=A.slice(0,M.length):M.length>A.length&&(M=M.slice(0,A.length)):A=M.map(n.format(i.tickformat));for(var C=1;C<M.length;C++)if(M[C]<M[C-1]){for(var L=M.map(S).sort(E),z=0;z<M.length;z++)M[z]=L[z].val,A[z]=L[z].text;break}}else M=void 0;return{key:b,label:i.label,tickFormat:i.tickformat,tickvals:M,ticktext:A,ordinal:!!M,multiselect:i.multiselect,xIndex:s,crossfilterDimensionIndex:s,visibleIndex:i._index,height:o,values:T,paddedUnitValues:T.map(g),unitTickvals:M&&M.map(g),xScale:c,x:c(s),canvasX:c(s)*l,unitToPaddedPx:f,domainScale:function(t,e,r,i,a){var o,s,l=v(r);return i?n.scale.ordinal().domain(i.map((o=n.format(r.tickformat),s=a,s?function(t,e){var r=s[e];return null==r?o(t):r}:o))).range(i.map(function(r){var n=(r-l[0])/(l[1]-l[0]);return t-e+n*(2*e-t)})):n.scale.linear().domain(l).range([t-e,e])}(o,h.verticalPadding,i,M,A),ordinalScale:function(t){if(t.tickvals){var e=v(t);return n.scale.ordinal().domain(t.tickvals).range(t.tickvals.map(function(t){return(t-e[0])/(e[1]-e[0])}))}}(i),parent:d,model:r,brush:p.makeBrush(t,w,k,function(){t.linePickActive(!1)},function(){var e=d;e.focusLayer&&e.focusLayer.render(e.panels,!0);var r=m(e);!t.contextShown()&&r?(e.contextLayer&&e.contextLayer.render(e.panels,!0),t.contextShown(!0)):t.contextShown()&&!r&&(e.contextLayer&&e.contextLayer.render(e.panels,!0,!0),t.contextShown(!1))},function(r){var n=d;if(n.focusLayer.render(n.panels,!0),n.pickLayer&&n.pickLayer.render(n.panels,!0),t.linePickActive(!0),e&&e.filterChanged){var o=g.invert,s=r.map(function(t){return t.map(o).sort(a.sorterAsc)}).sort(function(t,e){return t[0]-e[0]});e.filterChanged(n.key,i._index,s)}})}}),d}function b(t){t.classed(h.cn.axisExtentText,!0).attr(\"text-anchor\",\"middle\").style(\"cursor\",\"default\").style(\"user-select\",\"none\")}e.exports=function(t,e,r,i,s,l){var g,v,_=(g=!0,v=!1,{linePickActive:function(t){return arguments.length?g=!!t:g},contextShown:function(t){return arguments.length?v=!!t:v}}),w=i.filter(function(t){return f(t).trace.visible}).map(y.bind(0,s)).map(x.bind(0,_,l));r.each(function(t,e){return a.extendFlat(t,w[e])});var k=r.selectAll(\".gl-canvas\").each(function(t){t.viewModel=w[0],t.model=t.viewModel?t.viewModel.model:null}),T=null;k.filter(function(t){return t.pick}).style(\"pointer-events\",\"auto\").on(\"mousemove\",function(t){if(_.linePickActive()&&t.lineLayer&&l&&l.hover){var e=n.event,r=this.width,i=this.height,a=n.mouse(this),o=a[0],s=a[1];if(o<0||s<0||o>=r||s>=i)return;var c=t.lineLayer.readPixel(o,i-1-s),u=0!==c[3],f=u?c[2]+256*(c[1]+256*c[0]):null,h={x:o,y:s,clientX:e.clientX,clientY:e.clientY,dataIndex:t.model.key,curveNumber:f};f!==T&&(u?l.hover(h):l.unhover&&l.unhover(h),T=f)}}),k.style(\"opacity\",function(t){return t.pick?.01:1}),e.style(\"background\",\"rgba(255, 255, 255, 0)\");var A=e.selectAll(\".\"+h.cn.parcoords).data(w,c);A.exit().remove(),A.enter().append(\"g\").classed(h.cn.parcoords,!0).style(\"shape-rendering\",\"crispEdges\").style(\"pointer-events\",\"none\"),A.attr(\"transform\",function(t){return\"translate(\"+t.model.translateX+\",\"+t.model.translateY+\")\"});var M=A.selectAll(\".\"+h.cn.parcoordsControlView).data(u,c);M.enter().append(\"g\").classed(h.cn.parcoordsControlView,!0),M.attr(\"transform\",function(t){return\"translate(\"+t.model.pad.l+\",\"+t.model.pad.t+\")\"});var S=M.selectAll(\".\"+h.cn.yAxis).data(function(t){return t.dimensions},c);function E(t,e){for(var r=e.panels||(e.panels=[]),n=t.data(),i=n.length-1,a=0;a<i;a++){var o=r[a]||(r[a]={}),s=n[a],l=n[a+1];o.dim1=s,o.dim2=l,o.canvasX=s.canvasX,o.panelSizeX=l.canvasX-s.canvasX,o.panelSizeY=e.model.canvasHeight,o.y=0,o.canvasY=0}}S.enter().append(\"g\").classed(h.cn.yAxis,!0),M.each(function(t){E(S,t)}),k.each(function(t){if(t.viewModel){!t.lineLayer||l?t.lineLayer=d(this,t):t.lineLayer.update(t),(t.key||0===t.key)&&(t.viewModel[t.key]=t.lineLayer);var e=!t.context||l;t.lineLayer.render(t.viewModel.panels,e)}}),S.attr(\"transform\",function(t){return\"translate(\"+t.xScale(t.xIndex)+\", 0)\"}),S.call(n.behavior.drag().origin(function(t){return t}).on(\"drag\",function(t){var e=t.parent;_.linePickActive(!1),t.x=Math.max(-h.overdrag,Math.min(t.model.width+h.overdrag,n.event.x)),t.canvasX=t.x*t.model.canvasPixelRatio,S.sort(function(t,e){return t.x-e.x}).each(function(e,r){e.xIndex=r,e.x=t===e?e.x:e.xScale(e.xIndex),e.canvasX=e.x*e.model.canvasPixelRatio}),E(S,e),S.filter(function(e){return 0!==Math.abs(t.xIndex-e.xIndex)}).attr(\"transform\",function(t){return\"translate(\"+t.xScale(t.xIndex)+\", 0)\"}),n.select(this).attr(\"transform\",\"translate(\"+t.x+\", 0)\"),S.each(function(r,n,i){i===t.parent.key&&(e.dimensions[n]=r)}),e.contextLayer&&e.contextLayer.render(e.panels,!1,!m(e)),e.focusLayer.render&&e.focusLayer.render(e.panels)}).on(\"dragend\",function(t){var e=t.parent;t.x=t.xScale(t.xIndex),t.canvasX=t.x*t.model.canvasPixelRatio,E(S,e),n.select(this).attr(\"transform\",function(t){return\"translate(\"+t.x+\", 0)\"}),e.contextLayer&&e.contextLayer.render(e.panels,!1,!m(e)),e.focusLayer&&e.focusLayer.render(e.panels),e.pickLayer&&e.pickLayer.render(e.panels,!0),_.linePickActive(!0),l&&l.axesMoved&&l.axesMoved(e.key,e.dimensions.map(function(t){return t.crossfilterDimensionIndex}))})),S.exit().remove();var C=S.selectAll(\".\"+h.cn.axisOverlays).data(u,c);C.enter().append(\"g\").classed(h.cn.axisOverlays,!0),C.selectAll(\".\"+h.cn.axis).remove();var L=C.selectAll(\".\"+h.cn.axis).data(u,c);L.enter().append(\"g\").classed(h.cn.axis,!0),L.each(function(t){var e=t.model.height/t.model.tickDistance,r=t.domainScale,i=r.domain();n.select(this).call(n.svg.axis().orient(\"left\").tickSize(4).outerTickSize(2).ticks(e,t.tickFormat).tickValues(t.ordinal?i:null).tickFormat(t.ordinal?function(t){return t}:null).scale(r)),o.font(L.selectAll(\"text\"),t.model.tickFont)}),L.selectAll(\".domain, .tick>line\").attr(\"fill\",\"none\").attr(\"stroke\",\"black\").attr(\"stroke-opacity\",.25).attr(\"stroke-width\",\"1px\"),L.selectAll(\"text\").style(\"text-shadow\",\"1px 1px 1px #fff, -1px -1px 1px #fff, 1px -1px 1px #fff, -1px 1px 1px #fff\").style(\"cursor\",\"default\").style(\"user-select\",\"none\");var z=C.selectAll(\".\"+h.cn.axisHeading).data(u,c);z.enter().append(\"g\").classed(h.cn.axisHeading,!0);var O=z.selectAll(\".\"+h.cn.axisTitle).data(u,c);O.enter().append(\"text\").classed(h.cn.axisTitle,!0).attr(\"text-anchor\",\"middle\").style(\"cursor\",\"ew-resize\").style(\"user-select\",\"none\").style(\"pointer-events\",\"auto\"),O.attr(\"transform\",\"translate(0,\"+-h.axisTitleOffset+\")\").text(function(t){return t.label}).each(function(t){o.font(n.select(this),t.model.labelFont)});var I=C.selectAll(\".\"+h.cn.axisExtent).data(u,c);I.enter().append(\"g\").classed(h.cn.axisExtent,!0);var D=I.selectAll(\".\"+h.cn.axisExtentTop).data(u,c);D.enter().append(\"g\").classed(h.cn.axisExtentTop,!0),D.attr(\"transform\",\"translate(0,\"+-h.axisExtentOffset+\")\");var P=D.selectAll(\".\"+h.cn.axisExtentTopText).data(u,c);function R(t,e){if(t.ordinal)return\"\";var r=t.domainScale.domain();return n.format(t.tickFormat)(r[e?r.length-1:0])}P.enter().append(\"text\").classed(h.cn.axisExtentTopText,!0).call(b),P.text(function(t){return R(t,!0)}).each(function(t){o.font(n.select(this),t.model.rangeFont)});var F=I.selectAll(\".\"+h.cn.axisExtentBottom).data(u,c);F.enter().append(\"g\").classed(h.cn.axisExtentBottom,!0),F.attr(\"transform\",function(t){return\"translate(0,\"+(t.model.height+h.axisExtentOffset)+\")\"});var B=F.selectAll(\".\"+h.cn.axisExtentBottomText).data(u,c);B.enter().append(\"text\").classed(h.cn.axisExtentBottomText,!0).attr(\"dy\",\"0.75em\").call(b),B.text(function(t){return R(t)}).each(function(t){o.font(n.select(this),t.model.rangeFont)}),p.ensureAxisBrush(C)}},{\"../../components/colorscale\":592,\"../../components/drawing\":601,\"../../lib\":703,\"../../lib/gup\":701,\"./axisbrush\":1039,\"./constants\":1042,\"./lines\":1045,\"color-rgba\":115,d3:157}],1048:[function(t,e,r){\"use strict\";var n=t(\"./parcoords\"),i=t(\"../../lib/prepare_regl\");e.exports=function(t,e){var r=t._fullLayout,a=r._toppaper,o=r._paperdiv,s=r._glcontainer;if(i(t)){var l={},c={},u={},f={},h=r._size;e.forEach(function(e,r){var n=e[0].trace;u[r]=n.index;var i=f[r]=n._fullInput.index;l[r]=t.data[i].dimensions,c[r]=t.data[i].dimensions.slice()});n(o,a,s,e,{width:h.w,height:h.h,margin:{t:h.t,r:h.r,b:h.b,l:h.l}},{filterChanged:function(e,n,i){var a=c[e][n],o=i.map(function(t){return t.slice()}),s=\"dimensions[\"+n+\"].constraintrange\",l=r._tracePreGUI[t._fullData[u[e]]._fullInput.uid];if(void 0===l[s]){var h=a.constraintrange;l[s]=h||null}var p=t._fullData[u[e]].dimensions[n];o.length?(1===o.length&&(o=o[0]),a.constraintrange=o,p.constraintrange=o.slice(),o=[o]):(delete a.constraintrange,delete p.constraintrange,o=null);var d={};d[s]=o,t.emit(\"plotly_restyle\",[d,[f[e]]])},hover:function(e){t.emit(\"plotly_hover\",e)},unhover:function(e){t.emit(\"plotly_unhover\",e)},axesMoved:function(e,r){function n(t){return!(\"visible\"in t)||t.visible}function i(t,e,r){var n=e.indexOf(r),i=t.indexOf(n);return-1===i&&(i+=e.length),i}var a=function(t){return function(e,n){return i(r,t,e)-i(r,t,n)}}(c[e].filter(n));l[e].sort(a),c[e].filter(function(t){return!n(t)}).sort(function(t){return c[e].indexOf(t)}).forEach(function(t){l[e].splice(l[e].indexOf(t),1),l[e].splice(c[e].indexOf(t),0,t)}),t.emit(\"plotly_restyle\",[{dimensions:[l[e]]},[f[e]]])}})}}},{\"../../lib/prepare_regl\":716,\"./parcoords\":1047}],1049:[function(t,e,r){\"use strict\";var n=t(\"../../plots/attributes\"),i=t(\"../../plots/domain\").attributes,a=t(\"../../plots/font_attributes\"),o=t(\"../../components/color/attributes\"),s=t(\"../../components/fx/hovertemplate_attributes\"),l=t(\"../../lib/extend\").extendFlat,c=a({editType:\"plot\",arrayOk:!0,colorEditType:\"plot\"});e.exports={labels:{valType:\"data_array\",editType:\"calc\"},label0:{valType:\"number\",dflt:0,editType:\"calc\"},dlabel:{valType:\"number\",dflt:1,editType:\"calc\"},values:{valType:\"data_array\",editType:\"calc\"},marker:{colors:{valType:\"data_array\",editType:\"calc\"},line:{color:{valType:\"color\",dflt:o.defaultLine,arrayOk:!0,editType:\"style\"},width:{valType:\"number\",min:0,dflt:0,arrayOk:!0,editType:\"style\"},editType:\"calc\"},editType:\"calc\"},text:{valType:\"data_array\",editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"style\"},scalegroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"value\",\"percent\"],extras:[\"none\"],editType:\"calc\"},hoverinfo:l({},n.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:s({},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),textposition:{valType:\"enumerated\",values:[\"inside\",\"outside\",\"auto\",\"none\"],dflt:\"auto\",arrayOk:!0,editType:\"plot\"},textfont:l({},c,{}),insidetextfont:l({},c,{}),outsidetextfont:l({},c,{}),title:{text:{valType:\"string\",dflt:\"\",editType:\"plot\"},font:l({},c,{}),position:{valType:\"enumerated\",values:[\"top 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f(t,e){var r,n=JSON.stringify(t),i=e[n];if(!i){for(i=t.slice(),r=0;r<t.length;r++)i.push(a(t[r]).lighten(20).toHexString());for(r=0;r<t.length;r++)i.push(a(t[r]).darken(20).toHexString());e[n]=i}return i}e.exports={calc:function(t,e){var r,a,o=[],c=t._fullLayout,f=c.hiddenlabels||[],h=e.labels,p=e.marker.colors||[],d=e.values,g=i(d)&&d.length;if(e.dlabel)for(h=new Array(d.length),r=0;r<d.length;r++)h[r]=String(e.label0+r*e.dlabel);var v={},m=u(c[\"_\"+e.type+\"colormap\"]),y=(g?d:h).length,x=0,b=!1;for(r=0;r<y;r++){var _,w,k;if(g){if(_=d[r],!n(_))continue;if((_=+_)<0)continue}else _=1;void 0!==(w=h[r])&&\"\"!==w||(w=r);var T=v[w=String(w)];void 0===T?(v[w]=o.length,(k=-1!==f.indexOf(w))||(x+=_),o.push({v:_,label:w,color:m(p[r],w),i:r,pts:[r],hidden:k})):(b=!0,(a=o[T]).v+=_,a.pts.push(r),a.hidden||(x+=_),!1===a.color&&p[r]&&(a.color=m(p[r],w)))}(\"funnelarea\"===e.type?b:e.sort)&&o.sort(function(t,e){return e.v-t.v}),o[0]&&(o[0].vTotal=x);var A=e.textinfo;if(A&&\"none\"!==A){var M,S=A.split(\"+\"),E=function(t){return-1!==S.indexOf(t)},C=E(\"label\"),L=E(\"text\"),z=E(\"value\"),O=E(\"percent\"),I=c.separators;for(r=0;r<o.length;r++){if(a=o[r],M=C?[a.label]:[],L){var D=s.getFirstFilled(e.text,a.pts);l(D)&&M.push(D)}z&&M.push(s.formatPieValue(a.v,I)),O&&M.push(s.formatPiePercent(a.v/x,I)),a.text=M.join(\"<br>\")}}return o},crossTraceCalc:function(t,e){var r=(e||{}).type;r||(r=\"pie\");var n=t._fullLayout,i=t.calcdata,a=n[r+\"colorway\"],o=n[\"_\"+r+\"colormap\"];n[\"extend\"+r+\"colors\"]&&(a=f(a,c));for(var s=0,l=0;l<i.length;l++){var u=i[l];if(u[0].trace.type===r)for(var h=0;h<u.length;h++){var p=u[h];!1===p.color&&(o[p.label]?p.color=o[p.label]:(o[p.label]=p.color=a[s%a.length],s++))}}},makePullColorFn:u,generateExtendedColors:f}},{\"../../components/color\":580,\"../../lib\":703,\"./helpers\":1054,\"fast-isnumeric\":224,tinycolor2:524}],1052:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./attributes\"),a=t(\"../../plots/domain\").defaults,o=t(\"../bar/defaults\").handleText;e.exports=function(t,e,r,s){function l(r,a){return n.coerce(t,e,i,r,a)}var c,u=l(\"values\"),f=n.isArrayOrTypedArray(u),h=l(\"labels\");if(Array.isArray(h)?(c=h.length,f&&(c=Math.min(c,u.length))):f&&(c=u.length,l(\"label0\"),l(\"dlabel\")),c){e._length=c,l(\"marker.line.width\")&&l(\"marker.line.color\"),l(\"marker.colors\"),l(\"scalegroup\");var p=l(\"text\"),d=l(\"textinfo\",Array.isArray(p)?\"text+percent\":\"percent\");if(l(\"hovertext\"),l(\"hovertemplate\"),d&&\"none\"!==d){var g=l(\"textposition\");o(t,e,s,l,g,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1})}a(e,s,l);var v=l(\"hole\");if(l(\"title.text\")){var m=l(\"title.position\",v?\"middle center\":\"top center\");v||\"middle center\"!==m||(e.title.position=\"top 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r=t.toPrecision(10);return-1!==r.lastIndexOf(\".\")&&(r=r.replace(/[.]?0+$/,\"\")),n.numSeparate(r,e)},r.getFirstFilled=function(t,e){if(Array.isArray(t))for(var r=0;r<e.length;r++){var n=t[e[r]];if(n||0===n)return n}},r.castOption=function(t,e){return Array.isArray(t)?r.getFirstFilled(t,e):t||void 0}},{\"../../lib\":703}],1055:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),supplyLayoutDefaults:t(\"./layout_defaults\"),layoutAttributes:t(\"./layout_attributes\"),calc:t(\"./calc\").calc,crossTraceCalc:t(\"./calc\").crossTraceCalc,plot:t(\"./plot\").plot,style:t(\"./style\"),styleOne:t(\"./style_one\"),moduleType:\"trace\",name:\"pie\",basePlotModule:t(\"./base_plot\"),categories:[\"pie-like\",\"pie\",\"showLegend\"],meta:{}}},{\"./attributes\":1049,\"./base_plot\":1050,\"./calc\":1051,\"./defaults\":1052,\"./layout_attributes\":1056,\"./layout_defaults\":1057,\"./plot\":1058,\"./style\":1059,\"./style_one\":1060}],1056:[function(t,e,r){\"use strict\";e.exports={hiddenlabels:{valType:\"data_array\",editType:\"calc\"},piecolorway:{valType:\"colorlist\",editType:\"calc\"},extendpiecolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},{}],1057:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\"),r(\"piecolorway\",e.colorway),r(\"extendpiecolors\")}},{\"../../lib\":703,\"./layout_attributes\":1056}],1058:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../components/fx\"),a=t(\"../../components/color\"),o=t(\"../../components/drawing\"),s=t(\"../../lib\"),l=t(\"../../lib/svg_text_utils\"),c=t(\"./helpers\"),u=t(\"./event_data\");function f(t,e,r){var a=r[0],o=a.trace,l=a.cx,f=a.cy;\"_hasHoverLabel\"in o||(o._hasHoverLabel=!1),\"_hasHoverEvent\"in o||(o._hasHoverEvent=!1),t.on(\"mouseover\",function(t){var r=e._fullLayout,h=e._fullData[o.index];if(!e._dragging&&!1!==r.hovermode){var p=h.hoverinfo;if(Array.isArray(p)&&(p=i.castHoverinfo({hoverinfo:[c.castOption(p,t.pts)],_module:o._module},r,0)),\"all\"===p&&(p=\"label+text+value+percent+name\"),h.hovertemplate||\"none\"!==p&&\"skip\"!==p&&p){var d=t.rInscribed||0,g=l+t.pxmid[0]*(1-d),v=f+t.pxmid[1]*(1-d),m=r.separators,y=[];if(p&&-1!==p.indexOf(\"label\")&&y.push(t.label),t.text=c.castOption(h.hovertext||h.text,t.pts),p&&-1!==p.indexOf(\"text\")){var x=t.text;s.isValidTextValue(x)&&y.push(x)}t.value=t.v,t.valueLabel=c.formatPieValue(t.v,m),p&&-1!==p.indexOf(\"value\")&&y.push(t.valueLabel),t.percent=t.v/a.vTotal,t.percentLabel=c.formatPiePercent(t.percent,m),p&&-1!==p.indexOf(\"percent\")&&y.push(t.percentLabel);var b=h.hoverlabel,_=b.font;i.loneHover({trace:o,x0:g-d*a.r,x1:g+d*a.r,y:v,text:y.join(\"<br>\"),name:h.hovertemplate||-1!==p.indexOf(\"name\")?h.name:void 0,idealAlign:t.pxmid[0]<0?\"left\":\"right\",color:c.castOption(b.bgcolor,t.pts)||t.color,borderColor:c.castOption(b.bordercolor,t.pts),fontFamily:c.castOption(_.family,t.pts),fontSize:c.castOption(_.size,t.pts),fontColor:c.castOption(_.color,t.pts),nameLength:c.castOption(b.namelength,t.pts),textAlign:c.castOption(b.align,t.pts),hovertemplate:c.castOption(h.hovertemplate,t.pts),hovertemplateLabels:t,eventData:[u(t,h)]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:e}),o._hasHoverLabel=!0}o._hasHoverEvent=!0,e.emit(\"plotly_hover\",{points:[u(t,h)],event:n.event})}}),t.on(\"mouseout\",function(t){var r=e._fullLayout,a=e._fullData[o.index],s=n.select(this).datum();o._hasHoverEvent&&(t.originalEvent=n.event,e.emit(\"plotly_unhover\",{points:[u(s,a)],event:n.event}),o._hasHoverEvent=!1),o._hasHoverLabel&&(i.loneUnhover(r._hoverlayer.node()),o._hasHoverLabel=!1)}),t.on(\"click\",function(t){var r=e._fullLayout,a=e._fullData[o.index];e._dragging||!1===r.hovermode||(e._hoverdata=[u(t,a)],i.click(e,n.event))})}function h(t,e,r){var n=c.castOption(t.insidetextfont.color,e.pts);!n&&t._input.textfont&&(n=c.castOption(t._input.textfont.color,e.pts));var i=c.castOption(t.insidetextfont.family,e.pts)||c.castOption(t.textfont.family,e.pts)||r.family,o=c.castOption(t.insidetextfont.size,e.pts)||c.castOption(t.textfont.size,e.pts)||r.size;return{color:n||a.contrast(e.color),family:i,size:o}}function p(t,e){for(var r,n,i=0;i<t.length;i++)if((n=(r=t[i][0]).trace).title.text){var a=n.title.text;n._meta&&(a=s.templateString(a,n._meta));var c=o.tester.append(\"text\").attr(\"data-notex\",1).text(a).call(o.font,n.title.font).call(l.convertToTspans,e),u=o.bBox(c.node(),!0);r.titleBox={width:u.width,height:u.height},c.remove()}}function d(t,e,r){var n=Math.sqrt(t.width*t.width+t.height*t.height),i=t.width/t.height,a=e.halfangle,o=e.ring,s=e.rInscribed,l=r.r||e.rpx1,c={scale:s*l*2/n,rCenter:1-s,rotate:0};if(c.scale>=1)return c;var u=i+1/(2*Math.tan(a)),f=l*Math.min(1/(Math.sqrt(u*u+.5)+u),o/(Math.sqrt(i*i+o/2)+i)),h={scale:2*f/t.height,rCenter:Math.cos(f/l)-f*i/l,rotate:(180/Math.PI*e.midangle+720)%180-90},p=1/i,d=p+1/(2*Math.tan(a)),g=l*Math.min(1/(Math.sqrt(d*d+.5)+d),o/(Math.sqrt(p*p+o/2)+p)),v={scale:2*g/t.width,rCenter:Math.cos(g/l)-g/i/l,rotate:(180/Math.PI*e.midangle+810)%180-90},m=v.scale>h.scale?v:h;return c.scale<1&&m.scale>c.scale?m:c}function g(t,e){return t.v!==e.vTotal||e.trace.hole?Math.min(1/(1+1/Math.sin(t.halfangle)),t.ring/2):1}function v(t,e){var r=e.pxmid[0],n=e.pxmid[1],i=t.width/2,a=t.height/2;return r<0&&(i*=-1),n<0&&(a*=-1),{scale:1,rCenter:1,rotate:0,x:i+Math.abs(a)*(i>0?1:-1)/2,y:a/(1+r*r/(n*n)),outside:!0}}function m(t,e){var r,n,i,a=t.trace,o={x:t.cx,y:t.cy},s={tx:0,ty:0};s.ty+=a.title.font.size,i=x(a),-1!==a.title.position.indexOf(\"top\")?(o.y-=(1+i)*t.r,s.ty-=t.titleBox.height):-1!==a.title.position.indexOf(\"bottom\")&&(o.y+=(1+i)*t.r);var l,c,u=(l=t.r,c=t.trace.aspectratio,l/(void 0===c?1:c)),f=e.w*(a.domain.x[1]-a.domain.x[0])/2;return-1!==a.title.position.indexOf(\"left\")?(f+=u,o.x-=(1+i)*u,s.tx+=t.titleBox.width/2):-1!==a.title.position.indexOf(\"center\")?f*=2:-1!==a.title.position.indexOf(\"right\")&&(f+=u,o.x+=(1+i)*u,s.tx-=t.titleBox.width/2),r=f/t.titleBox.width,n=y(t,e)/t.titleBox.height,{x:o.x,y:o.y,scale:Math.min(r,n),tx:s.tx,ty:s.ty}}function y(t,e){var r=t.trace,n=e.h*(r.domain.y[1]-r.domain.y[0]);return Math.min(t.titleBox.height,n/2)}function x(t){var e,r=t.pull;if(!r)return 0;if(Array.isArray(r))for(r=0,e=0;e<t.pull.length;e++)t.pull[e]>r&&(r=t.pull[e]);return r}function b(t,e){for(var r=[],n=0;n<t.length;n++){var i=t[n][0],a=i.trace,o=a.domain,s=e.w*(o.x[1]-o.x[0]),l=e.h*(o.y[1]-o.y[0]);a.title.text&&\"middle center\"!==a.title.position&&(l-=y(i,e));var c=s/2,u=l/2;\"funnelarea\"!==a.type||a.scalegroup||(u/=a.aspectratio),i.r=Math.min(c,u)/(1+x(a)),i.cx=e.l+e.w*(a.domain.x[1]+a.domain.x[0])/2,i.cy=e.t+e.h*(1-a.domain.y[0])-l/2,a.title.text&&-1!==a.title.position.indexOf(\"bottom\")&&(i.cy-=y(i,e)),a.scalegroup&&-1===r.indexOf(a.scalegroup)&&r.push(a.scalegroup)}!function(t,e){for(var r,n,i,a=0;a<e.length;a++){var o=1/0,s=e[a];for(n=0;n<t.length;n++)if(r=t[n][0],(i=r.trace).scalegroup===s){var l;if(\"pie\"===i.type)l=r.r*r.r;else if(\"funnelarea\"===i.type){var c,u;i.aspectratio>1?(c=r.r,u=c/i.aspectratio):(u=r.r,c=u*i.aspectratio),c*=(1+i.baseratio)/2,l=c*u}o=Math.min(o,l/r.vTotal)}for(n=0;n<t.length;n++)if(r=t[n][0],(i=r.trace).scalegroup===s){var f=o*r.vTotal;\"funnelarea\"===i.type&&(f/=(1+i.baseratio)/2,f/=i.aspectratio),r.r=Math.sqrt(f)}}}(t,r)}e.exports={plot:function(t,e){var r=t._fullLayout;p(e,t),b(e,r._size);var i=s.makeTraceGroups(r._pielayer,e,\"trace\").each(function(e){var i=n.select(this),u=e[0],p=u.trace;!function(t){var e,r,n,i=t[0],a=i.trace,o=a.rotation*Math.PI/180,s=2*Math.PI/i.vTotal,l=\"px0\",c=\"px1\";if(\"counterclockwise\"===a.direction){for(e=0;e<t.length&&t[e].hidden;e++);if(e===t.length)return;o+=s*t[e].v,s*=-1,l=\"px1\",c=\"px0\"}function u(t){return[i.r*Math.sin(t),-i.r*Math.cos(t)]}for(n=u(o),e=0;e<t.length;e++)(r=t[e]).hidden||(r[l]=n,o+=s*r.v/2,r.pxmid=u(o),r.midangle=o,o+=s*r.v/2,n=u(o),r[c]=n,r.largeArc=r.v>i.vTotal/2?1:0,r.halfangle=Math.PI*Math.min(r.v/i.vTotal,.5),r.ring=1-a.hole,r.rInscribed=g(r,i))}(e),i.attr(\"stroke-linejoin\",\"round\"),i.each(function(){var i=n.select(this).selectAll(\"g.slice\").data(e);i.enter().append(\"g\").classed(\"slice\",!0),i.exit().remove();var g=[[[],[]],[[],[]]],y=!1;i.each(function(r){if(r.hidden)n.select(this).selectAll(\"path,g\").remove();else{r.pointNumber=r.i,r.curveNumber=p.index,g[r.pxmid[1]<0?0:1][r.pxmid[0]<0?0:1].push(r);var i=u.cx,a=u.cy,m=n.select(this),x=m.selectAll(\"path.surface\").data([r]);if(x.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":\"all\"}),m.call(f,t,e),p.pull){var b=+c.castOption(p.pull,r.pts)||0;b>0&&(i+=b*r.pxmid[0],a+=b*r.pxmid[1])}r.cxFinal=i,r.cyFinal=a;var _=p.hole;if(r.v===u.vTotal){var w=\"M\"+(i+r.px0[0])+\",\"+(a+r.px0[1])+S(r.px0,r.pxmid,!0,1)+S(r.pxmid,r.px0,!0,1)+\"Z\";_?x.attr(\"d\",\"M\"+(i+_*r.px0[0])+\",\"+(a+_*r.px0[1])+S(r.px0,r.pxmid,!1,_)+S(r.pxmid,r.px0,!1,_)+\"Z\"+w):x.attr(\"d\",w)}else{var k=S(r.px0,r.px1,!0,1);if(_){var T=1-_;x.attr(\"d\",\"M\"+(i+_*r.px1[0])+\",\"+(a+_*r.px1[1])+S(r.px1,r.px0,!1,_)+\"l\"+T*r.px0[0]+\",\"+T*r.px0[1]+k+\"Z\")}else x.attr(\"d\",\"M\"+i+\",\"+a+\"l\"+r.px0[0]+\",\"+r.px0[1]+k+\"Z\")}var A=c.castOption(p.textposition,r.pts),M=m.selectAll(\"g.slicetext\").data(r.text&&\"none\"!==A?[0]:[]);M.enter().append(\"g\").classed(\"slicetext\",!0),M.exit().remove(),M.each(function(){var e=s.ensureSingle(n.select(this),\"text\",\"\",function(t){t.attr(\"data-notex\",1)});e.text(r.text).attr({class:\"slicetext\",transform:\"\",\"text-anchor\":\"middle\"}).call(o.font,\"outside\"===A?function(t,e,r){var n=c.castOption(t.outsidetextfont.color,e.pts)||c.castOption(t.textfont.color,e.pts)||r.color,i=c.castOption(t.outsidetextfont.family,e.pts)||c.castOption(t.textfont.family,e.pts)||r.family,a=c.castOption(t.outsidetextfont.size,e.pts)||c.castOption(t.textfont.size,e.pts)||r.size;return{color:n,family:i,size:a}}(p,r,t._fullLayout.font):h(p,r,t._fullLayout.font)).call(l.convertToTspans,t);var f,g=o.bBox(e.node());\"outside\"===A?f=v(g,r):(f=d(g,r,u),\"auto\"===A&&f.scale<1&&(e.call(o.font,p.outsidetextfont),p.outsidetextfont.family===p.insidetextfont.family&&p.outsidetextfont.size===p.insidetextfont.size||(g=o.bBox(e.node())),f=v(g,r)));var m=i+r.pxmid[0]*f.rCenter+(f.x||0),x=a+r.pxmid[1]*f.rCenter+(f.y||0);f.outside&&(r.yLabelMin=x-g.height/2,r.yLabelMid=x,r.yLabelMax=x+g.height/2,r.labelExtraX=0,r.labelExtraY=0,y=!0),e.attr(\"transform\",\"translate(\"+m+\",\"+x+\")\"+(f.scale<1?\"scale(\"+f.scale+\")\":\"\")+(f.rotate?\"rotate(\"+f.rotate+\")\":\"\")+\"translate(\"+-(g.left+g.right)/2+\",\"+-(g.top+g.bottom)/2+\")\")})}function S(t,e,n,i){var a=i*(e[0]-t[0]),o=i*(e[1]-t[1]);return\"a\"+i*u.r+\",\"+i*u.r+\" 0 \"+r.largeArc+(n?\" 1 \":\" 0 \")+a+\",\"+o}});var x=n.select(this).selectAll(\"g.titletext\").data(p.title.text?[0]:[]);x.enter().append(\"g\").classed(\"titletext\",!0),x.exit().remove(),x.each(function(){var e,i=s.ensureSingle(n.select(this),\"text\",\"\",function(t){t.attr(\"data-notex\",1)}),a=p.title.text;p._meta&&(a=s.templateString(a,p._meta)),i.text(a).attr({class:\"titletext\",transform:\"\",\"text-anchor\":\"middle\"}).call(o.font,p.title.font).call(l.convertToTspans,t),e=\"middle center\"===p.title.position?function(t){var e=Math.sqrt(t.titleBox.width*t.titleBox.width+t.titleBox.height*t.titleBox.height);return{x:t.cx,y:t.cy,scale:t.trace.hole*t.r*2/e,tx:0,ty:-t.titleBox.height/2+t.trace.title.font.size}}(u):m(u,r._size),i.attr(\"transform\",\"translate(\"+e.x+\",\"+e.y+\")\"+(e.scale<1?\"scale(\"+e.scale+\")\":\"\")+\"translate(\"+e.tx+\",\"+e.ty+\")\")}),y&&function(t,e){var r,n,i,a,o,s,l,u,f,h,p,d,g;function v(t,e){return t.pxmid[1]-e.pxmid[1]}function m(t,e){return e.pxmid[1]-t.pxmid[1]}function y(t,r){r||(r={});var i,u,f,p,d,g,v=r.labelExtraY+(n?r.yLabelMax:r.yLabelMin),m=n?t.yLabelMin:t.yLabelMax,y=n?t.yLabelMax:t.yLabelMin,x=t.cyFinal+o(t.px0[1],t.px1[1]),b=v-m;if(b*l>0&&(t.labelExtraY=b),Array.isArray(e.pull))for(u=0;u<h.length;u++)(f=h[u])===t||(c.castOption(e.pull,t.pts)||0)>=(c.castOption(e.pull,f.pts)||0)||((t.pxmid[1]-f.pxmid[1])*l>0?(p=f.cyFinal+o(f.px0[1],f.px1[1]),(b=p-m-t.labelExtraY)*l>0&&(t.labelExtraY+=b)):(y+t.labelExtraY-x)*l>0&&(i=3*s*Math.abs(u-h.indexOf(t)),d=f.cxFinal+a(f.px0[0],f.px1[0]),(g=d+i-(t.cxFinal+t.pxmid[0])-t.labelExtraX)*s>0&&(t.labelExtraX+=g)))}for(n=0;n<2;n++)for(i=n?v:m,o=n?Math.max:Math.min,l=n?1:-1,r=0;r<2;r++){for(a=r?Math.max:Math.min,s=r?1:-1,(u=t[n][r]).sort(i),f=t[1-n][r],h=f.concat(u),d=[],p=0;p<u.length;p++)void 0!==u[p].yLabelMid&&d.push(u[p]);for(g=!1,p=0;n&&p<f.length;p++)if(void 0!==f[p].yLabelMid){g=f[p];break}for(p=0;p<d.length;p++){var x=p&&d[p-1];g&&!p&&(x=g),y(d[p],x)}}}(g,p),function(t,e){t.each(function(t){var r=n.select(this);if(t.labelExtraX||t.labelExtraY){var i=r.select(\"g.slicetext text\");i.attr(\"transform\",\"translate(\"+t.labelExtraX+\",\"+t.labelExtraY+\")\"+i.attr(\"transform\"));var o=t.cxFinal+t.pxmid[0],l=t.cyFinal+t.pxmid[1],c=\"M\"+o+\",\"+l,u=(t.yLabelMax-t.yLabelMin)*(t.pxmid[0]<0?-1:1)/4;if(t.labelExtraX){var f=t.labelExtraX*t.pxmid[1]/t.pxmid[0],h=t.yLabelMid+t.labelExtraY-(t.cyFinal+t.pxmid[1]);Math.abs(f)>Math.abs(h)?c+=\"l\"+h*t.pxmid[0]/t.pxmid[1]+\",\"+h+\"H\"+(o+t.labelExtraX+u):c+=\"l\"+t.labelExtraX+\",\"+f+\"v\"+(h-f)+\"h\"+u}else c+=\"V\"+(t.yLabelMid+t.labelExtraY)+\"h\"+u;s.ensureSingle(r,\"path\",\"textline\").call(a.stroke,e.outsidetextfont.color).attr({\"stroke-width\":Math.min(2,e.outsidetextfont.size/8),d:c,fill:\"none\"})}else r.select(\"path.textline\").remove()})}(i,p)})});setTimeout(function(){i.selectAll(\"tspan\").each(function(){var t=n.select(this);t.attr(\"dy\")&&t.attr(\"dy\",t.attr(\"dy\"))})},0)},transformInsideText:d,determineInsideTextFont:h,positionTitleOutside:m,prerenderTitles:p,layoutAreas:b,attachFxHandlers:f}},{\"../../components/color\":580,\"../../components/drawing\":601,\"../../components/fx\":619,\"../../lib\":703,\"../../lib/svg_text_utils\":727,\"./event_data\":1053,\"./helpers\":1054,d3:157}],1059:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"./style_one\");e.exports=function(t){t._fullLayout._pielayer.selectAll(\".trace\").each(function(t){var e=t[0].trace,r=n.select(this);r.style({opacity:e.opacity}),r.selectAll(\"path.surface\").each(function(t){n.select(this).call(i,t,e)})})}},{\"./style_one\":1060,d3:157}],1060:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\"),i=t(\"./helpers\").castOption;e.exports=function(t,e,r){var a=r.marker.line,o=i(a.color,e.pts)||n.defaultLine,s=i(a.width,e.pts)||0;t.style(\"stroke-width\",s).call(n.fill,e.color).call(n.stroke,o)}},{\"../../components/color\":580,\"./helpers\":1054}],1061:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\");e.exports={x:n.x,y:n.y,xy:{valType:\"data_array\",editType:\"calc\"},indices:{valType:\"data_array\",editType:\"calc\"},xbounds:{valType:\"data_array\",editType:\"calc\"},ybounds:{valType:\"data_array\",editType:\"calc\"},text:n.text,marker:{color:{valType:\"color\",arrayOk:!1,editType:\"calc\"},opacity:{valType:\"number\",min:0,max:1,dflt:1,arrayOk:!1,editType:\"calc\"},blend:{valType:\"boolean\",dflt:null,editType:\"calc\"},sizemin:{valType:\"number\",min:.1,max:2,dflt:.5,editType:\"calc\"},sizemax:{valType:\"number\",min:.1,dflt:20,editType:\"calc\"},border:{color:{valType:\"color\",arrayOk:!1,editType:\"calc\"},arearatio:{valType:\"number\",min:0,max:1,dflt:0,editType:\"calc\"},editType:\"calc\"},editType:\"calc\"},transforms:void 0}},{\"../scatter/attributes\":1075}],1062:[function(t,e,r){\"use strict\";var n=t(\"gl-pointcloud2d\"),i=t(\"../../lib/str2rgbarray\"),a=t(\"../../plots/cartesian/autorange\").findExtremes,o=t(\"../scatter/get_trace_color\");function s(t,e){this.scene=t,this.uid=e,this.type=\"pointcloud\",this.pickXData=[],this.pickYData=[],this.xData=[],this.yData=[],this.textLabels=[],this.color=\"rgb(0, 0, 0)\",this.name=\"\",this.hoverinfo=\"all\",this.idToIndex=new Int32Array(0),this.bounds=[0,0,0,0],this.pointcloudOptions={positions:new Float32Array(0),idToIndex:this.idToIndex,sizemin:.5,sizemax:12,color:[0,0,0,1],areaRatio:1,borderColor:[0,0,0,1]},this.pointcloud=n(t.glplot,this.pointcloudOptions),this.pointcloud._trace=this}var l=s.prototype;l.handlePick=function(t){var e=this.idToIndex[t.pointId];return{trace:this,dataCoord:t.dataCoord,traceCoord:this.pickXYData?[this.pickXYData[2*e],this.pickXYData[2*e+1]]:[this.pickXData[e],this.pickYData[e]],textLabel:Array.isArray(this.textLabels)?this.textLabels[e]:this.textLabels,color:this.color,name:this.name,pointIndex:e,hoverinfo:this.hoverinfo}},l.update=function(t){this.index=t.index,this.textLabels=t.text,this.name=t.name,this.hoverinfo=t.hoverinfo,this.bounds=[1/0,1/0,-1/0,-1/0],this.updateFast(t),this.color=o(t,{})},l.updateFast=function(t){var e,r,n,o,s,l,c=this.xData=this.pickXData=t.x,u=this.yData=this.pickYData=t.y,f=this.pickXYData=t.xy,h=t.xbounds&&t.ybounds,p=t.indices,d=this.bounds;if(f){if(n=f,e=f.length>>>1,h)d[0]=t.xbounds[0],d[2]=t.xbounds[1],d[1]=t.ybounds[0],d[3]=t.ybounds[1];else for(l=0;l<e;l++)o=n[2*l],s=n[2*l+1],o<d[0]&&(d[0]=o),o>d[2]&&(d[2]=o),s<d[1]&&(d[1]=s),s>d[3]&&(d[3]=s);if(p)r=p;else for(r=new Int32Array(e),l=0;l<e;l++)r[l]=l}else for(e=c.length,n=new Float32Array(2*e),r=new Int32Array(e),l=0;l<e;l++)o=c[l],s=u[l],r[l]=l,n[2*l]=o,n[2*l+1]=s,o<d[0]&&(d[0]=o),o>d[2]&&(d[2]=o),s<d[1]&&(d[1]=s),s>d[3]&&(d[3]=s);this.idToIndex=r,this.pointcloudOptions.idToIndex=r,this.pointcloudOptions.positions=n;var g=i(t.marker.color),v=i(t.marker.border.color),m=t.opacity*t.marker.opacity;g[3]*=m,this.pointcloudOptions.color=g;var y=t.marker.blend;if(null===y){y=c.length<100||u.length<100}this.pointcloudOptions.blend=y,v[3]*=m,this.pointcloudOptions.borderColor=v;var x=t.marker.sizemin,b=Math.max(t.marker.sizemax,t.marker.sizemin);this.pointcloudOptions.sizeMin=x,this.pointcloudOptions.sizeMax=b,this.pointcloudOptions.areaRatio=t.marker.border.arearatio,this.pointcloud.update(this.pointcloudOptions);var _=this.scene.xaxis,w=this.scene.yaxis,k=b/2||.5;t._extremes[_._id]=a(_,[d[0],d[2]],{ppad:k}),t._extremes[w._id]=a(w,[d[1],d[3]],{ppad:k})},l.dispose=function(){this.pointcloud.dispose()},e.exports=function(t,e){var r=new s(t,e.uid);return 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n=\"bgsankey-\"+e.trace.uid+\"-\"+r;f.ensureSingle(t._fullLayout._draggers,\"rect\",n),t._fullData[r]._bgRect=i.select(\".\"+n),t._fullData[r]._bgRect.style(\"pointer-events\",\"all\").attr(\"width\",e.width).attr(\"height\",e.height).attr(\"x\",e.translateX).attr(\"y\",e.translateY).classed(\"bgsankey\",!0).style({fill:\"transparent\",\"stroke-width\":0})}),_.transition().ease(n.ease).duration(n.duration).attr(\"transform\",T);var I=_.selectAll(\".\"+n.cn.sankeyLinks).data(d,p);I.enter().append(\"g\").classed(n.cn.sankeyLinks,!0).style(\"fill\",\"none\");var D=I.selectAll(\".\"+n.cn.sankeyLink).data(function(t){return t.graph.links.filter(function(t){return t.value}).map(function(t,e,r){var n=a(e.color),i=e.source.label+\"|\"+e.target.label+\"__\"+r;return e.trace=t.trace,e.curveNumber=t.trace.index,{circular:t.circular,key:i,traceId:t.key,pointNumber:e.pointNumber,link:e,tinyColorHue:o.tinyRGB(n),tinyColorAlpha:n.getAlpha(),linkPath:y,linkLineColor:t.linkLineColor,linkLineWidth:t.linkLineWidth,valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,parent:t,interactionState:t.interactionState,flow:e.flow}}.bind(null,t))},p);D.enter().append(\"path\").classed(n.cn.sankeyLink,!0).call(z,_,h.linkEvents),D.style(\"stroke\",function(t){return k(t)?o.tinyRGB(a(t.linkLineColor)):t.tinyColorHue}).style(\"stroke-opacity\",function(t){return k(t)?o.opacity(t.linkLineColor):t.tinyColorAlpha}).style(\"fill\",function(t){return t.tinyColorHue}).style(\"fill-opacity\",function(t){return t.tinyColorAlpha}).style(\"stroke-width\",function(t){return k(t)?t.linkLineWidth:1}).attr(\"d\",y()),D.style(\"opacity\",function(){return t._context.staticPlot||v||m?1:0}).transition().ease(n.ease).duration(n.duration).style(\"opacity\",1),D.exit().transition().ease(n.ease).duration(n.duration).style(\"opacity\",0).remove();var P=_.selectAll(\".\"+n.cn.sankeyNodeSet).data(d,p);P.enter().append(\"g\").classed(n.cn.sankeyNodeSet,!0),P.style(\"cursor\",function(t){switch(t.arrangement){case\"fixed\":return\"default\";case\"perpendicular\":return\"ns-resize\";default:return\"move\"}});var R=P.selectAll(\".\"+n.cn.sankeyNode).data(function(t){var e=t.graph.nodes;return function(t){var e,r=[];for(e=0;e<t.length;e++)t[e].originalX=(t[e].x0+t[e].x1)/2,t[e].originalY=(t[e].y0+t[e].y1)/2,-1===r.indexOf(t[e].originalX)&&r.push(t[e].originalX);for(r.sort(function(t,e){return t-e}),e=0;e<t.length;e++)t[e].originalLayerIndex=r.indexOf(t[e].originalX),t[e].originalLayer=t[e].originalLayerIndex/(r.length-1)}(e),e.map(function(t,e){var r=a(e.color),i=n.nodePadAcross,s=t.nodePad/2;e.dx=e.x1-e.x0,e.dy=e.y1-e.y0;var l=e.dx,c=Math.max(.5,e.dy),u=\"node_\"+e.pointNumber;return e.group&&(u=f.randstr()),e.trace=t.trace,e.curveNumber=t.trace.index,{index:e.pointNumber,key:u,partOfGroup:e.partOfGroup||!1,group:e.group,traceId:t.key,trace:t.trace,node:e,nodePad:t.nodePad,nodeLineColor:t.nodeLineColor,nodeLineWidth:t.nodeLineWidth,textFont:t.textFont,size:t.horizontal?t.height:t.width,visibleWidth:Math.ceil(l),visibleHeight:c,zoneX:-i,zoneY:-s,zoneWidth:l+2*i,zoneHeight:c+2*s,labelY:t.horizontal?e.dy/2+1:e.dx/2+1,left:1===e.originalLayer,sizeAcross:t.width,forceLayouts:t.forceLayouts,horizontal:t.horizontal,darkBackground:r.getBrightness()<=128,tinyColorHue:o.tinyRGB(r),tinyColorAlpha:r.getAlpha(),valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,graph:t.graph,arrangement:t.arrangement,uniqueNodeLabelPathId:[t.guid,t.key,u].join(\"_\"),interactionState:t.interactionState,figure:t}}.bind(null,t))},p);R.enter().append(\"g\").classed(n.cn.sankeyNode,!0).call(x).style(\"opacity\",function(e){return!t._context.staticPlot&&!v||e.partOfGroup?0:1}),R.call(z,_,h.nodeEvents).call(O,D,h,t),R.transition().ease(n.ease).duration(n.duration).call(x).style(\"opacity\",function(t){return t.partOfGroup?0:1}),R.exit().transition().ease(n.ease).duration(n.duration).style(\"opacity\",0).remove();var F=R.selectAll(\".\"+n.cn.nodeRect).data(d);F.enter().append(\"rect\").classed(n.cn.nodeRect,!0).call(w),F.style(\"stroke-width\",function(t){return t.nodeLineWidth}).style(\"stroke\",function(t){return o.tinyRGB(a(t.nodeLineColor))}).style(\"stroke-opacity\",function(t){return o.opacity(t.nodeLineColor)}).style(\"fill\",function(t){return t.tinyColorHue}).style(\"fill-opacity\",function(t){return t.tinyColorAlpha}),F.transition().ease(n.ease).duration(n.duration).call(w);var B=R.selectAll(\".\"+n.cn.nodeCapture).data(d);B.enter().append(\"rect\").classed(n.cn.nodeCapture,!0).style(\"fill-opacity\",0),B.attr(\"x\",function(t){return t.zoneX}).attr(\"y\",function(t){return t.zoneY}).attr(\"width\",function(t){return t.zoneWidth}).attr(\"height\",function(t){return t.zoneHeight});var 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c=e._length,u=t._fullLayout,f=r._id,h=n._id,p=u._firstScatter[d(e)]===e.uid,v=(g(e,u,r,n)||{}).orientation,m=e.fill;r._minDtick=0,n._minDtick=0;var y={padded:!0},x={padded:!0};l&&(y.ppad=x.ppad=l);var b=c<2||i[0]!==i[c-1]||o[0]!==o[c-1];b&&(\"tozerox\"===m||\"tonextx\"===m&&(p||\"h\"===v))?y.tozero=!0:(e.error_y||{}).visible||\"tonexty\"!==m&&\"tozeroy\"!==m&&(s.hasMarkers(e)||s.hasText(e))||(y.padded=!1,y.ppad=0),b&&(\"tozeroy\"===m||\"tonexty\"===m&&(p||\"v\"===v))?x.tozero=!0:\"tonextx\"!==m&&\"tozerox\"!==m||(x.padded=!1),f&&(e._extremes[f]=a.findExtremes(r,i,y)),h&&(e._extremes[h]=a.findExtremes(n,o,x))}function h(t,e){if(s.hasMarkers(t)){var r,n=t.marker,o=1.6*(t.marker.sizeref||1);if(r=\"area\"===t.marker.sizemode?function(t){return Math.max(Math.sqrt((t||0)/o),3)}:function(t){return Math.max((t||0)/o,3)},i.isArrayOrTypedArray(n.size)){var l={type:\"linear\"};a.setConvert(l);for(var c=l.makeCalcdata(t.marker,\"size\"),u=new Array(e),f=0;f<e;f++)u[f]=r(c[f]);return u}return 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n=t(\"gl-line3d\"),i=t(\"gl-scatter3d\"),a=t(\"gl-error3d\"),o=t(\"gl-mesh3d\"),s=t(\"delaunay-triangulate\"),l=t(\"../../lib\"),c=t(\"../../lib/str2rgbarray\"),u=t(\"../../lib/gl_format_color\").formatColor,f=t(\"../scatter/make_bubble_size_func\"),h=t(\"../../constants/gl3d_dashes\"),p=t(\"../../constants/gl3d_markers\"),d=t(\"./calc_errors\");function g(t,e){this.scene=t,this.uid=e,this.linePlot=null,this.scatterPlot=null,this.errorBars=null,this.textMarkers=null,this.delaunayMesh=null,this.color=null,this.mode=\"\",this.dataPoints=[],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.textLabels=null,this.data=null}var v=g.prototype;function m(t){return null==t?0:t.indexOf(\"left\")>-1?-1:t.indexOf(\"right\")>-1?1:0}function y(t){return null==t?0:t.indexOf(\"top\")>-1?-1:t.indexOf(\"bottom\")>-1?1:0}function x(t,e){return e(4*t)}function b(t){return p[t]}function _(t,e,r,n,i){var a=null;if(l.isArrayOrTypedArray(t)){a=[];for(var o=0;o<e;o++)void 0===t[o]?a[o]=n:a[o]=r(t[o],i)}else 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d=t.opacity;if(t.marker&&t.marker.opacity&&(d*=t.marker.opacity),r={gl:this.scene.glplot.gl,position:p.position,color:p.scatterColor,size:p.scatterSize,glyph:p.scatterMarker,opacity:d,orthographic:!0,lineWidth:p.scatterLineWidth,lineColor:p.scatterLineColor,project:p.project,projectScale:p.projectScale,projectOpacity:p.projectOpacity},-1!==this.mode.indexOf(\"markers\")?this.scatterPlot?this.scatterPlot.update(r):(this.scatterPlot=i(r),this.scatterPlot._trace=this,this.scatterPlot.highlightScale=1,this.scene.glplot.add(this.scatterPlot)):this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose(),this.scatterPlot=null),c={gl:this.scene.glplot.gl,position:p.position,glyph:p.text,color:p.textColor,size:p.textSize,angle:p.textAngle,alignment:p.textOffset,font:p.textFont,orthographic:!0,lineWidth:0,project:!1,opacity:t.opacity},this.textLabels=t.hovertext||t.text,-1!==this.mode.indexOf(\"text\")?this.textMarkers?this.textMarkers.update(c):(this.textMarkers=i(c),this.textMarkers._trace=this,this.textMarkers.highlightScale=1,this.scene.glplot.add(this.textMarkers)):this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose(),this.textMarkers=null),l={gl:this.scene.glplot.gl,position:p.position,color:p.errorColor,error:p.errorBounds,lineWidth:p.errorLineWidth,capSize:p.errorCapSize,opacity:t.opacity},this.errorBars?p.errorBounds?this.errorBars.update(l):(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose(),this.errorBars=null):p.errorBounds&&(this.errorBars=a(l),this.errorBars._trace=this,this.scene.glplot.add(this.errorBars)),p.delaunayAxis>=0){var 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n=t(\"../../lib\"),i=t(\"../scatter/constants\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/line_shape_defaults\"),c=t(\"../scatter/text_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),f=t(\"./attributes\");e.exports=function(t,e,r,h){function p(r,i){return n.coerce(t,e,f,r,i)}p(\"carpet\"),e.xaxis=\"x\",e.yaxis=\"y\";var d=p(\"a\"),g=p(\"b\"),v=Math.min(d.length,g.length);if(v){e._length=v,p(\"text\"),p(\"hovertext\"),p(\"mode\",v<i.PTS_LINESONLY?\"lines+markers\":\"lines\"),a.hasLines(e)&&(s(t,e,r,h,p),l(t,e,p),p(\"connectgaps\")),a.hasMarkers(e)&&o(t,e,r,h,p,{gradient:!0}),a.hasText(e)&&c(t,e,h,p);var m=[];(a.hasMarkers(e)||a.hasText(e))&&(p(\"marker.maxdisplayed\"),m.push(\"points\")),p(\"fill\"),\"none\"!==e.fill&&(u(t,e,r,p),a.hasLines(e)||l(t,e,p)),\"tonext\"!==e.fill&&\"toself\"!==e.fill||m.push(\"fills\"),\"fills\"!==p(\"hoveron\",m.join(\"+\")||\"points\")&&p(\"hovertemplate\"),n.coerceSelectionMarkerOpacity(e,p)}else e.visible=!1}},{\"../../lib\":703,\"../scatter/constants\":1079,\"../scatter/fillcolor_defaults\":1083,\"../scatter/line_defaults\":1087,\"../scatter/line_shape_defaults\":1089,\"../scatter/marker_defaults\":1093,\"../scatter/subtypes\":1098,\"../scatter/text_defaults\":1099,\"./attributes\":1107}],1110:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,i){var a=n[i];return t.a=a.a,t.b=a.b,t.y=a.y,t}},{}],1111:[function(t,e,r){\"use strict\";var n=t(\"../scatter/hover\"),i=t(\"../../lib\").fillText;e.exports=function(t,e,r,a){var o=n(t,e,r,a);if(o&&!1!==o[0].index){var s=o[0];if(void 0===s.index){var l=1-s.y0/t.ya._length,c=t.xa._length,u=c*l/2,f=c-u;return s.x0=Math.max(Math.min(s.x0,f),u),s.x1=Math.max(Math.min(s.x1,f),u),o}var h=s.cd[s.index];s.a=h.a,s.b=h.b,s.xLabelVal=void 0,s.yLabelVal=void 0;var p=s.trace,d=p._carpet,g=d.ab2ij([h.a,h.b]),v=Math.floor(g[0]),m=g[0]-v,y=Math.floor(g[1]),x=g[1]-y,b=d.evalxy([],v,y,m,x);s.yLabel=b[1].toFixed(3),delete s.text;var _=[];if(!p.hovertemplate){var w=(h.hi||p.hoverinfo).split(\"+\");-1!==w.indexOf(\"all\")&&(w=[\"a\",\"b\",\"text\"]),-1!==w.indexOf(\"a\")&&k(d.aaxis,h.a),-1!==w.indexOf(\"b\")&&k(d.baxis,h.b),_.push(\"y: \"+s.yLabel),-1!==w.indexOf(\"text\")&&i(h,p,_),s.extraText=_.join(\"<br>\")}return o}function k(t,e){var r;r=t.labelprefix&&t.labelprefix.length>0?t.labelprefix.replace(/ = $/,\"\"):t._hovertitle,_.push(r+\": \"+e.toFixed(3)+t.labelsuffix)}}},{\"../../lib\":703,\"../scatter/hover\":1085}],1112:[function(t,e,r){\"use 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s,l,c,u=r[0][0].carpet,f={xaxis:i.getFromId(t,u.xaxis||\"x\"),yaxis:i.getFromId(t,u.yaxis||\"y\"),plot:e.plot};for(n(t,f,r,o),s=0;s<r.length;s++)l=r[s][0].trace,c=o.selectAll(\"g.trace\"+l.uid+\" .js-line\"),a.setClipUrl(c,r[s][0].carpet._clipPathId,t)}},{\"../../components/drawing\":601,\"../../plots/cartesian/axes\":751,\"../scatter/plot\":1094}],1114:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx/hovertemplate_attributes\"),i=t(\"../scatter/attributes\"),a=t(\"../../plots/attributes\"),o=t(\"../../components/colorscale/attributes\"),s=t(\"../../components/drawing/attributes\").dash,l=t(\"../../lib/extend\").extendFlat,c=t(\"../../plot_api/edit_types\").overrideAll,u=i.marker,f=i.line,h=u.line;e.exports=c({lon:{valType:\"data_array\"},lat:{valType:\"data_array\"},locations:{valType:\"data_array\"},locationmode:{valType:\"enumerated\",values:[\"ISO-3\",\"USA-states\",\"country names\"],dflt:\"ISO-3\"},mode:l({},i.mode,{dflt:\"markers\"}),text:l({},i.text,{}),hovertext:l({},i.hovertext,{}),textfont:i.textfont,textposition:i.textposition,line:{color:f.color,width:f.width,dash:s},connectgaps:i.connectgaps,marker:l({symbol:u.symbol,opacity:u.opacity,size:u.size,sizeref:u.sizeref,sizemin:u.sizemin,sizemode:u.sizemode,colorbar:u.colorbar,line:l({width:h.width},o(\"marker.line\")),gradient:u.gradient},o(\"marker\")),fill:{valType:\"enumerated\",values:[\"none\",\"toself\"],dflt:\"none\"},fillcolor:i.fillcolor,selected:i.selected,unselected:i.unselected,hoverinfo:l({},a.hoverinfo,{flags:[\"lon\",\"lat\",\"location\",\"text\",\"name\"]}),hovertemplate:n()},\"calc\",\"nested\")},{\"../../components/colorscale/attributes\":587,\"../../components/drawing/attributes\":600,\"../../components/fx/hovertemplate_attributes\":618,\"../../lib/extend\":693,\"../../plot_api/edit_types\":734,\"../../plots/attributes\":748,\"../scatter/attributes\":1075}],1115:[function(t,e,r){\"use 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n=t(\"../../lib\"),i=t(\"../scatter/subtypes\"),a=t(\"../scatter/marker_defaults\"),o=t(\"../scatter/line_defaults\"),s=t(\"../scatter/text_defaults\"),l=t(\"../scatter/fillcolor_defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,u){function f(r,i){return n.coerce(t,e,c,r,i)}!function(t,e,r){var n,i,a=0,o=r(\"locations\");if(o)return r(\"locationmode\"),a=o.length;return n=r(\"lon\")||[],i=r(\"lat\")||[],a=Math.min(n.length,i.length),e._length=a,a}(0,e,f)?e.visible=!1:(f(\"text\"),f(\"hovertext\"),f(\"hovertemplate\"),f(\"mode\"),i.hasLines(e)&&(o(t,e,r,u,f),f(\"connectgaps\")),i.hasMarkers(e)&&a(t,e,r,u,f,{gradient:!0}),i.hasText(e)&&s(t,e,u,f),f(\"fill\"),\"none\"!==e.fill&&l(t,e,r,f),n.coerceSelectionMarkerOpacity(e,f))}},{\"../../lib\":703,\"../scatter/fillcolor_defaults\":1083,\"../scatter/line_defaults\":1087,\"../scatter/marker_defaults\":1093,\"../scatter/subtypes\":1098,\"../scatter/text_defaults\":1099,\"./attributes\":1114}],1117:[function(t,e,r){\"use 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a=e.hi||t.hoverinfo,o=\"all\"===a?l.hoverinfo.flags:a.split(\"+\"),c=-1!==o.indexOf(\"location\")&&Array.isArray(t.locations),u=-1!==o.indexOf(\"lon\"),f=-1!==o.indexOf(\"lat\"),h=-1!==o.indexOf(\"text\"),p=[];function d(t){return i.tickText(r,r.c2l(t),\"hover\").text+\"\\xb0\"}c?p.push(e.loc):u&&f?p.push(\"(\"+d(e.lonlat[0])+\", \"+d(e.lonlat[1])+\")\"):u?p.push(n.lon+d(e.lonlat[0])):f&&p.push(n.lat+d(e.lonlat[1]));h&&s(e,t,p);return p.join(\"<br>\")}(u,v,p.mockAxis,c[0].t.labels),t.hovertemplate=u.hovertemplate,[t]}}},{\"../../components/fx\":619,\"../../constants/numerical\":680,\"../../lib\":703,\"../../plots/cartesian/axes\":751,\"../scatter/get_trace_color\":1084,\"./attributes\":1114}],1119:[function(t,e,r){\"use 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n=t(\"d3\"),i=t(\"../../lib\"),a=t(\"../../constants/numerical\").BADNUM,o=t(\"../../lib/topojson_utils\").getTopojsonFeatures,s=t(\"../../lib/geo_location_utils\").locationToFeature,l=t(\"../../lib/geojson_utils\"),c=t(\"../scatter/subtypes\"),u=t(\"./style\");function f(t,e){var r=t[0].trace;if(Array.isArray(r.locations))for(var n=o(r,e),i=r.locationmode,l=0;l<t.length;l++){var c=t[l],u=s(i,c.loc,n);c.lonlat=u?u.properties.ct:[a,a]}}e.exports=function(t,e,r){for(var o=0;o<r.length;o++)f(r[o],e.topojson);function s(t,e){t.lonlat[0]===a&&n.select(e).remove()}var h=e.layers.frontplot.select(\".scatterlayer\"),p=i.makeTraceGroups(h,r,\"trace scattergeo\");p.selectAll(\"*\").remove(),p.each(function(e){var r=e[0].node3=n.select(this),a=e[0].trace;if(c.hasLines(a)||\"none\"!==a.fill){var 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n=t(\"regl-scatter2d\"),i=t(\"regl-line2d\"),a=t(\"regl-error2d\"),o=t(\"point-cluster\"),s=t(\"gl-text\"),l=t(\"../../registry\"),c=t(\"../../lib\"),u=t(\"../../lib/prepare_regl\"),f=t(\"../../plots/cartesian/axis_ids\"),h=t(\"../../plots/cartesian/autorange\").findExtremes,p=t(\"../../components/color\"),d=t(\"../scatter/subtypes\"),g=t(\"../scatter/calc\"),v=g.calcMarkerSize,m=g.calcAxisExpansion,y=g.setFirstScatter,x=t(\"../scatter/colorscale_calc\"),b=t(\"../scatter/link_traces\"),_=t(\"../scatter/get_trace_color\"),w=c.fillText,k=t(\"./convert\"),T=t(\"../../constants/numerical\").BADNUM,A=t(\"./constants\").TOO_MANY_POINTS,M=t(\"../../constants/interactions\").DESELECTDIM;function S(t,e,r){var n=t._extremes[e._id],i=h(e,r._bnds,{padded:!0});n.min=n.min.concat(i.min),n.max=n.max.concat(i.max)}function E(t,e){var 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l[f].length||a.draw(f);o[f]&&r.textOptions[f]&&o[f].render()}s&&s.draw(l),r.dirty=!1},r.destroy=function(){r.fill2d&&r.fill2d.destroy&&r.fill2d.destroy(),r.scatter2d&&r.scatter2d.destroy&&r.scatter2d.destroy(),r.error2d&&r.error2d.destroy&&r.error2d.destroy(),r.line2d&&r.line2d.destroy&&r.line2d.destroy(),r.select2d&&r.select2d.destroy&&r.select2d.destroy(),r.glText&&r.glText.forEach(function(t){t.destroy&&t.destroy()}),r.lineOptions=null,r.fillOptions=null,r.markerOptions=null,r.markerSelectedOptions=null,r.markerUnselectedOptions=null,r.errorXOptions=null,r.errorYOptions=null,r.textOptions=null,r.textSelectedOptions=null,r.textUnselectedOptions=null,r.selectBatch=null,r.unselectBatch=null,e._scene=null}),r.dirty||c.extendFlat(r,n),r}function C(t,e,r,n){var i=t.xa,a=t.ya,o=t.distance,s=t.dxy,u=t.index,f={pointNumber:u,x:e[u],y:r[u]};f.tx=Array.isArray(n.text)?n.text[u]:n.text,f.htx=Array.isArray(n.hovertext)?n.hovertext[u]:n.hovertext,f.data=Array.isArray(n.customdata)?n.customdata[u]:n.customdata,f.tp=Array.isArray(n.textposition)?n.textposition[u]:n.textposition;var h=n.textfont;h&&(f.ts=Array.isArray(h.size)?h.size[u]:h.size,f.tc=Array.isArray(h.color)?h.color[u]:h.color,f.tf=Array.isArray(h.family)?h.family[u]:h.family);var p=n.marker;p&&(f.ms=c.isArrayOrTypedArray(p.size)?p.size[u]:p.size,f.mo=c.isArrayOrTypedArray(p.opacity)?p.opacity[u]:p.opacity,f.mx=Array.isArray(p.symbol)?p.symbol[u]:p.symbol,f.mc=c.isArrayOrTypedArray(p.color)?p.color[u]:p.color);var d=p&&p.line;d&&(f.mlc=Array.isArray(d.color)?d.color[u]:d.color,f.mlw=c.isArrayOrTypedArray(d.width)?d.width[u]:d.width);var g=p&&p.gradient;g&&\"none\"!==g.type&&(f.mgt=Array.isArray(g.type)?g.type[u]:g.type,f.mgc=Array.isArray(g.color)?g.color[u]:g.color);var v=i.c2p(f.x,!0),m=a.c2p(f.y,!0),y=f.mrc||1,x=n.hoverlabel;x&&(f.hbg=Array.isArray(x.bgcolor)?x.bgcolor[u]:x.bgcolor,f.hbc=Array.isArray(x.bordercolor)?x.bordercolor[u]:x.bordercolor,f.hts=Array.isArray(x.font.size)?x.font.size[u]:x.font.size,f.htc=Array.isArray(x.font.color)?x.font.color[u]:x.font.color,f.htf=Array.isArray(x.font.family)?x.font.family[u]:x.font.family,f.hnl=Array.isArray(x.namelength)?x.namelength[u]:x.namelength);var b=n.hoverinfo;b&&(f.hi=Array.isArray(b)?b[u]:b);var k=n.hovertemplate;k&&(f.ht=Array.isArray(k)?k[u]:k);var T={};return T[t.index]=f,c.extendFlat(t,{color:_(n,f),x0:v-y,x1:v+y,xLabelVal:f.x,y0:m-y,y1:m+y,yLabelVal:f.y,cd:T,distance:o,spikeDistance:s,hovertemplate:f.ht}),f.htx?t.text=f.htx:f.tx?t.text=f.tx:n.text&&(t.text=n.text),w(f,n,t),l.getComponentMethod(\"errorbars\",\"hoverInfo\")(f,n,t),t}function L(t){var e,r,n=t[0],i=n.trace,a=n.t,o=a._scene,s=a.index,l=o.selectBatch[s],u=o.unselectBatch[s],f=o.textOptions[s],h=o.textSelectedOptions[s]||{},d=o.textUnselectedOptions[s]||{},g=c.extendFlat({},f);if(l.length||u.length){var v=h.color,m=d.color,y=f.color,x=Array.isArray(y);for(g.color=new Array(i._length),e=0;e<l.length;e++)r=l[e],g.color[r]=v||(x?y[r]:y);for(e=0;e<u.length;e++){r=u[e];var b=x?y[r]:y;g.color[r]=m||(v?b:p.addOpacity(b,M))}}o.glText[s].update(g)}e.exports={moduleType:\"trace\",name:\"scattergl\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"gl\",\"regl\",\"cartesian\",\"symbols\",\"errorBarsOK\",\"showLegend\",\"scatter-like\"],attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),crossTraceDefaults:t(\"../scatter/cross_trace_defaults\"),colorbar:t(\"../scatter/marker_colorbar\"),calc:function(t,e){var r,n,i,a=t._fullLayout,s=f.getFromId(t,e.xaxis),l=f.getFromId(t,e.yaxis),u=a._plots[e.xaxis+e.yaxis],h=e._length,p=h>=A,d=2*h,g={},b=s.makeCalcdata(e,\"x\"),_=l.makeCalcdata(e,\"y\"),w=new Array(d);for(r=0;r<h;r++)n=b[r],i=_[r],w[2*r]=n===T?NaN:n,w[2*r+1]=i===T?NaN:i;if(\"log\"===s.type)for(r=0;r<d;r+=2)w[r]=s.c2l(w[r]);if(\"log\"===l.type)for(r=1;r<d;r+=2)w[r]=l.c2l(w[r]);if(p&&\"log\"!==s.type&&\"log\"!==l.type)g.tree=o(w);else{var M=g.ids=new Array(h);for(r=0;r<h;r++)M[r]=r}x(t,e);var C,L=function(t,e,r,n,i,a){var o=k.style(t,r);if(o.marker&&(o.marker.positions=n),o.line&&n.length>1&&c.extendFlat(o.line,k.linePositions(t,r,n)),o.errorX||o.errorY){var s=k.errorBarPositions(t,r,n,i,a);o.errorX&&c.extendFlat(o.errorX,s.x),o.errorY&&c.extendFlat(o.errorY,s.y)}return o.text&&(c.extendFlat(o.text,{positions:n},k.textPosition(t,r,o.text,o.marker)),c.extendFlat(o.textSel,{positions:n},k.textPosition(t,r,o.text,o.markerSel)),c.extendFlat(o.textUnsel,{positions:n},k.textPosition(t,r,o.text,o.markerUnsel))),o}(t,0,e,w,b,_),z=E(0,u);return y(a,e),p?L.marker&&(C=2*(L.marker.sizeAvg||Math.max(L.marker.size,3))):C=v(e,h),m(t,e,s,l,b,_,C),L.errorX&&S(e,s,L.errorX),L.errorY&&S(e,l,L.errorY),L.fill&&!z.fill2d&&(z.fill2d=!0),L.marker&&!z.scatter2d&&(z.scatter2d=!0),L.line&&!z.line2d&&(z.line2d=!0),!L.errorX&&!L.errorY||z.error2d||(z.error2d=!0),L.text&&!z.glText&&(z.glText=!0),L.marker&&(L.marker.snap=g.tree||A),z.lineOptions.push(L.line),z.errorXOptions.push(L.errorX),z.errorYOptions.push(L.errorY),z.fillOptions.push(L.fill),z.markerOptions.push(L.marker),z.markerSelectedOptions.push(L.markerSel),z.markerUnselectedOptions.push(L.markerUnsel),z.textOptions.push(L.text),z.textSelectedOptions.push(L.textSel),z.textUnselectedOptions.push(L.textUnsel),z.selectBatch.push([]),z.unselectBatch.push([]),g._scene=z,g.index=z.count,g.x=b,g.y=_,g.positions=w,z.count++,[{x:!1,y:!1,t:g,trace:e}]},plot:function(t,e,r){if(r.length){var o,l,f=t._fullLayout,h=e._scene,p=e.xaxis,g=e.yaxis;if(h)if(u(t,[\"ANGLE_instanced_arrays\",\"OES_element_index_uint\"])){var v=h.count,m=f._glcanvas.data()[0].regl;if(b(t,e,r),h.dirty){if(!0===h.error2d&&(h.error2d=a(m)),!0===h.line2d&&(h.line2d=i(m)),!0===h.scatter2d&&(h.scatter2d=n(m)),!0===h.fill2d&&(h.fill2d=i(m)),!0===h.glText)for(h.glText=new Array(v),o=0;o<v;o++)h.glText[o]=new s(m);if(h.glText){if(v>h.glText.length){var y=v-h.glText.length;for(o=0;o<y;o++)h.glText.push(new s(m))}else if(v<h.glText.length){var x=h.glText.length-v;h.glText.splice(v,x).forEach(function(t){t.destroy()})}for(o=0;o<v;o++)h.glText[o].update(h.textOptions[o])}if(h.line2d&&(h.line2d.update(h.lineOptions),h.lineOptions=h.lineOptions.map(function(t){if(t&&t.positions){for(var e=t.positions,r=0;r<e.length&&(isNaN(e[r])||isNaN(e[r+1]));)r+=2;for(var n=e.length-2;n>r&&(isNaN(e[n])||isNaN(e[n+1]));)n-=2;t.positions=e.slice(r,n+2)}return t}),h.line2d.update(h.lineOptions)),h.error2d){var _=(h.errorXOptions||[]).concat(h.errorYOptions||[]);h.error2d.update(_)}h.scatter2d&&h.scatter2d.update(h.markerOptions),h.fillOrder=c.repeat(null,v),h.fill2d&&(h.fillOptions=h.fillOptions.map(function(t,e){var n=r[e];if(t&&n&&n[0]&&n[0].trace){var i,a,o=n[0],s=o.trace,l=o.t,c=h.lineOptions[e],u=[];s._ownfill&&u.push(e),s._nexttrace&&u.push(e+1),u.length&&(h.fillOrder[e]=u);var f,p,d=[],g=c&&c.positions||l.positions;if(\"tozeroy\"===s.fill){for(f=0;f<g.length&&isNaN(g[f+1]);)f+=2;for(p=g.length-2;p>f&&isNaN(g[p+1]);)p-=2;0!==g[f+1]&&(d=[g[f],0]),d=d.concat(g.slice(f,p+2)),0!==g[p+1]&&(d=d.concat([g[p],0]))}else if(\"tozerox\"===s.fill){for(f=0;f<g.length&&isNaN(g[f]);)f+=2;for(p=g.length-2;p>f&&isNaN(g[p]);)p-=2;0!==g[f]&&(d=[0,g[f+1]]),d=d.concat(g.slice(f,p+2)),0!==g[p]&&(d=d.concat([0,g[p+1]]))}else if(\"toself\"===s.fill||\"tonext\"===s.fill){for(d=[],i=0,a=0;a<g.length;a+=2)(isNaN(g[a])||isNaN(g[a+1]))&&((d=d.concat(g.slice(i,a))).push(g[i],g[i+1]),i=a+2);d=d.concat(g.slice(i)),i&&d.push(g[i],g[i+1])}else{var v=s._nexttrace;if(v){var m=h.lineOptions[e+1];if(m){var y=m.positions;if(\"tonexty\"===s.fill){for(d=g.slice(),e=Math.floor(y.length/2);e--;){var x=y[2*e],b=y[2*e+1];isNaN(x)||isNaN(b)||d.push(x,b)}t.fill=v.fillcolor}}}}if(s._prevtrace&&\"tonext\"===s._prevtrace.fill){var _=h.lineOptions[e-1].positions,w=d.length/2,k=[i=w];for(a=0;a<_.length;a+=2)(isNaN(_[a])||isNaN(_[a+1]))&&(k.push(a/2+w+1),i=a+2);d=d.concat(_),t.hole=k}return t.fillmode=s.fill,t.opacity=s.opacity,t.positions=d,t}}),h.fill2d.update(h.fillOptions))}var w=f.dragmode,k=\"lasso\"===w||\"select\"===w,T=f.clickmode.indexOf(\"select\")>-1;for(o=0;o<v;o++){var A=r[o][0],M=A.trace,S=A.t,E=S.index,C=M._length,z=S.x,O=S.y;if(M.selectedpoints||k||T){if(k||(k=!0),M.selectedpoints){var I=h.selectBatch[E]=c.selIndices2selPoints(M),D={};for(l=0;l<I.length;l++)D[I[l]]=1;var P=[];for(l=0;l<C;l++)D[l]||P.push(l);h.unselectBatch[E]=P}var R=S.xpx=new Array(C),F=S.ypx=new Array(C);for(l=0;l<C;l++)R[l]=p.c2p(z[l]),F[l]=g.c2p(O[l])}else S.xpx=S.ypx=null}if(k){if(h.select2d||(h.select2d=n(f._glcanvas.data()[1].regl)),h.scatter2d){var B=new Array(v);for(o=0;o<v;o++)B[o]=h.selectBatch[o].length||h.unselectBatch[o].length?h.markerUnselectedOptions[o]:{};h.scatter2d.update(B)}h.select2d&&(h.select2d.update(h.markerOptions),h.select2d.update(h.markerSelectedOptions)),h.glText&&r.forEach(function(t){var e=((t||[])[0]||{}).trace||{};d.hasText(e)&&L(t)})}else h.scatter2d&&h.scatter2d.update(h.markerOptions);var N={viewport:function(t,e,r){var n=t._size,i=t.width,a=t.height;return[n.l+e.domain[0]*n.w,n.b+r.domain[0]*n.h,i-n.r-(1-e.domain[1])*n.w,a-n.t-(1-r.domain[1])*n.h]}(f,p,g),range:[(p._rl||p.range)[0],(g._rl||g.range)[0],(p._rl||p.range)[1],(g._rl||g.range)[1]]},j=c.repeat(N,h.count);h.fill2d&&h.fill2d.update(j),h.line2d&&h.line2d.update(j),h.error2d&&h.error2d.update(j.concat(j)),h.scatter2d&&h.scatter2d.update(j),h.select2d&&h.select2d.update(j),h.glText&&h.glText.forEach(function(t){t.update(N)})}else h.init()}},hoverPoints:function(t,e,r,n){var i,a,o,s,l,c,u,f,h,p=t.cd,d=p[0].t,g=p[0].trace,v=t.xa,m=t.ya,y=d.x,x=d.y,b=v.c2p(e),_=m.c2p(r),w=t.distance;if(d.tree){var k=v.p2c(b-w),T=v.p2c(b+w),A=m.p2c(_-w),M=m.p2c(_+w);i=\"x\"===n?d.tree.range(Math.min(k,T),Math.min(m._rl[0],m._rl[1]),Math.max(k,T),Math.max(m._rl[0],m._rl[1])):d.tree.range(Math.min(k,T),Math.min(A,M),Math.max(k,T),Math.max(A,M))}else{if(!d.ids)return[t];i=d.ids}var S=w;if(\"x\"===n)for(l=0;l<i.length;l++)o=y[i[l]],(c=Math.abs(v.c2p(o)-b))<S&&(S=c,u=m.c2p(x[i[l]])-_,h=Math.sqrt(c*c+u*u),a=i[l]);else for(l=i.length-1;l>-1;l--)o=y[i[l]],s=x[i[l]],c=v.c2p(o)-b,u=m.c2p(s)-_,(f=Math.sqrt(c*c+u*u))<S&&(S=h=f,a=i[l]);return t.index=a,t.distance=S,t.dxy=h,void 0===a?[t]:(C(t,y,x,g),[t])},selectPoints:function(t,e){var r=t.cd,n=[],i=r[0].trace,a=r[0].t,o=i._length,s=a.x,l=a.y,c=a._scene,u=a.index;if(!c)return n;var f=d.hasText(i),h=d.hasMarkers(i),p=!h&&!f;if(!0!==i.visible||p)return n;var g=[],v=[];if(!1!==e&&!e.degenerate)for(var m=0;m<o;m++)e.contains([a.xpx[m],a.ypx[m]],!1,m,t)?(g.push(m),n.push({pointNumber:m,x:s[m],y:l[m]})):v.push(m);if(h){var y=c.scatter2d;if(g.length||v.length){if(!c.selectBatch[u].length&&!c.unselectBatch[u].length){var x=new Array(c.count);x[u]=c.markerUnselectedOptions[u],y.update.apply(y,x)}}else{var b=new Array(c.count);b[u]=c.markerOptions[u],y.update.apply(y,b)}}return c.selectBatch[u]=g,c.unselectBatch[u]=v,f&&L(r),n},sceneUpdate:E,calcHover:C,meta:{}}},{\"../../components/color\":580,\"../../constants/interactions\":679,\"../../constants/numerical\":680,\"../../lib\":703,\"../../lib/prepare_regl\":716,\"../../plots/cartesian\":762,\"../../plots/cartesian/autorange\":750,\"../../plots/cartesian/axis_ids\":754,\"../../registry\":831,\"../scatter/calc\":1076,\"../scatter/colorscale_calc\":1078,\"../scatter/cross_trace_defaults\":1081,\"../scatter/get_trace_color\":1084,\"../scatter/link_traces\":1090,\"../scatter/marker_colorbar\":1092,\"../scatter/subtypes\":1098,\"./attributes\":1123,\"./constants\":1124,\"./convert\":1125,\"./defaults\":1126,\"gl-text\":316,\"point-cluster\":464,\"regl-error2d\":485,\"regl-line2d\":486,\"regl-scatter2d\":487}],1128:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx/hovertemplate_attributes\"),i=t(\"../scattergeo/attributes\"),a=t(\"../scatter/attributes\"),o=t(\"../../plots/mapbox/layout_attributes\"),s=t(\"../../plots/attributes\"),l=t(\"../../components/colorscale/attributes\"),c=t(\"../../lib/extend\").extendFlat,u=t(\"../../plot_api/edit_types\").overrideAll,f=i.line,h=i.marker;e.exports=u({lon:i.lon,lat:i.lat,mode:c({},a.mode,{dflt:\"markers\"}),text:c({},a.text,{}),hovertext:c({},a.hovertext,{}),line:{color:f.color,width:f.width},connectgaps:a.connectgaps,marker:c({symbol:{valType:\"string\",dflt:\"circle\",arrayOk:!0},opacity:h.opacity,size:h.size,sizeref:h.sizeref,sizemin:h.sizemin,sizemode:h.sizemode},l(\"marker\")),fill:i.fill,fillcolor:a.fillcolor,textfont:o.layers.symbol.textfont,textposition:o.layers.symbol.textposition,selected:{marker:a.selected.marker},unselected:{marker:a.unselected.marker},hoverinfo:c({},s.hoverinfo,{flags:[\"lon\",\"lat\",\"text\",\"name\"]}),hovertemplate:n()},\"calc\",\"nested\")},{\"../../components/colorscale/attributes\":587,\"../../components/fx/hovertemplate_attributes\":618,\"../../lib/extend\":693,\"../../plot_api/edit_types\":734,\"../../plots/attributes\":748,\"../../plots/mapbox/layout_attributes\":808,\"../scatter/attributes\":1075,\"../scattergeo/attributes\":1114}],1129:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib\"),a=t(\"../../constants/numerical\").BADNUM,o=t(\"../../lib/geojson_utils\"),s=t(\"../../components/colorscale\"),l=t(\"../../components/drawing\"),c=t(\"../scatter/make_bubble_size_func\"),u=t(\"../scatter/subtypes\"),f=t(\"../../plots/mapbox/convert_text_opts\");function h(){return{geojson:o.makeBlank(),layout:{visibility:\"none\"},paint:{}}}function p(t){return i.isArrayOrTypedArray(t)?function(t){return t}:t?function(){return t}:d}function d(){return\"\"}function g(t){return t[0]===a}e.exports=function(t){var e,r=t[0].trace,a=!0===r.visible&&0!==r._length,v=\"none\"!==r.fill,m=u.hasLines(r),y=u.hasMarkers(r),x=u.hasText(r),b=y&&\"circle\"===r.marker.symbol,_=y&&\"circle\"!==r.marker.symbol,w=h(),k=h(),T=h(),A=h(),M={fill:w,line:k,circle:T,symbol:A};if(!a)return M;if((v||m)&&(e=o.calcTraceToLineCoords(t)),v&&(w.geojson=o.makePolygon(e),w.layout.visibility=\"visible\",i.extendFlat(w.paint,{\"fill-color\":r.fillcolor})),m&&(k.geojson=o.makeLine(e),k.layout.visibility=\"visible\",i.extendFlat(k.paint,{\"line-width\":r.line.width,\"line-color\":r.line.color,\"line-opacity\":r.opacity})),b){var S=function(t){var e,r,a,o,u=t[0].trace,f=u.marker,h=u.selectedpoints,p=i.isArrayOrTypedArray(f.color),d=i.isArrayOrTypedArray(f.size),v=i.isArrayOrTypedArray(f.opacity);function m(t){return u.opacity*t}p&&(r=s.hasColorscale(u,\"marker\")?s.makeColorScaleFuncFromTrace(f):i.identity);d&&(a=c(u));v&&(o=function(t){var e=n(t)?+i.constrain(t,0,1):0;return m(e)});var y,x=[];for(e=0;e<t.length;e++){var b=t[e],_=b.lonlat;if(!g(_)){var w={};r&&(w.mcc=b.mcc=r(b.mc)),a&&(w.mrc=b.mrc=a(b.ms)),o&&(w.mo=o(b.mo)),h&&(w.selected=b.selected||0),x.push({type:\"Feature\",geometry:{type:\"Point\",coordinates:_},properties:w})}}if(h)for(y=l.makeSelectedPointStyleFns(u),e=0;e<x.length;e++){var k=x[e].properties;y.selectedOpacityFn&&(k.mo=m(y.selectedOpacityFn(k))),y.selectedColorFn&&(k.mcc=y.selectedColorFn(k)),y.selectedSizeFn&&(k.mrc=y.selectedSizeFn(k))}return{geojson:{type:\"FeatureCollection\",features:x},mcc:p||y&&y.selectedColorFn?{type:\"identity\",property:\"mcc\"}:f.color,mrc:d||y&&y.selectedSizeFn?{type:\"identity\",property:\"mrc\"}:(T=f.size,T/2),mo:v||y&&y.selectedOpacityFn?{type:\"identity\",property:\"mo\"}:m(f.opacity)};var T}(t);T.geojson=S.geojson,T.layout.visibility=\"visible\",i.extendFlat(T.paint,{\"circle-color\":S.mcc,\"circle-radius\":S.mrc,\"circle-opacity\":S.mo})}if((_||x)&&(A.geojson=function(t){for(var e=t[0].trace,r=(e.marker||{}).symbol,n=e.text,i=\"circle\"!==r?p(r):d,a=u.hasText(e)?p(n):d,o=[],s=0;s<t.length;s++){var l=t[s];g(l.lonlat)||o.push({type:\"Feature\",geometry:{type:\"Point\",coordinates:l.lonlat},properties:{symbol:i(l.mx),text:a(l.tx)}})}return{type:\"FeatureCollection\",features:o}}(t),i.extendFlat(A.layout,{visibility:\"visible\",\"icon-image\":\"{symbol}-15\",\"text-field\":\"{text}\"}),_&&(i.extendFlat(A.layout,{\"icon-size\":r.marker.size/10}),i.extendFlat(A.paint,{\"icon-opacity\":r.opacity*r.marker.opacity,\"icon-color\":r.marker.color})),x)){var E=(r.marker||{}).size,C=f(r.textposition,E);i.extendFlat(A.layout,{\"text-size\":r.textfont.size,\"text-anchor\":C.anchor,\"text-offset\":C.offset}),i.extendFlat(A.paint,{\"text-color\":r.textfont.color,\"text-opacity\":r.opacity})}return 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n=i.modHalf(e[0],360),a=e[1],o=h.project([n,a]),l=o.x-u.c2p([d,a]),c=o.y-f.c2p([n,r]),p=Math.max(3,t.mrc||0);return Math.max(Math.sqrt(l*l+c*c)-p,1-3/p)},t),!1!==t.index){var g=l[t.index],v=g.lonlat,m=[i.modHalf(v[0],360)+p,v[1]],y=u.c2p(m),x=f.c2p(m),b=g.mrc||1;return t.x0=y-b,t.x1=y+b,t.y0=x-b,t.y1=x+b,t.color=a(c,g),t.extraText=function(t,e,r){if(t.hovertemplate)return;var n=(e.hi||t.hoverinfo).split(\"+\"),i=-1!==n.indexOf(\"all\"),a=-1!==n.indexOf(\"lon\"),s=-1!==n.indexOf(\"lat\"),l=e.lonlat,c=[];function u(t){return t+\"\\xb0\"}i||a&&s?c.push(\"(\"+u(l[0])+\", \"+u(l[1])+\")\"):a?c.push(r.lon+u(l[0])):s&&c.push(r.lat+u(l[1]));(i||-1!==n.indexOf(\"text\"))&&o(e,t,c);return c.join(\"<br>\")}(c,g,l[0].t.labels),t.hovertemplate=c.hovertemplate,[t]}}},{\"../../components/fx\":619,\"../../constants/numerical\":680,\"../../lib\":703,\"../scatter/get_trace_color\":1084}],1133:[function(t,e,r){\"use 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a=this.order[i],o=r[a];e.setOptions(this.layerIds[a],\"setLayoutProperty\",o.layout),\"visible\"===o.layout.visibility&&(this.setSourceData(a,o),e.setOptions(this.layerIds[a],\"setPaintProperty\",o.paint))}t[0].trace._glTrace=this},a.dispose=function(){for(var t=this.subplot.map,e=0;e<this.order.length;e++){var r=this.order[e];t.removeLayer(this.layerIds[r]),t.removeSource(this.sourceIds[r])}},e.exports=function(t,e){for(var r=new i(t,e[0].trace.uid),a=n(e),o=0;o<r.order.length;o++){var s=r.order[o],l=a[s];r.addSource(s,l),r.addLayer(s,l)}return e[0].trace._glTrace=r,r}},{\"./convert\":1129}],1135:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../scatter/subtypes\"),a=t(\"../../constants/numerical\").BADNUM;e.exports=function(t,e){var r,o=t.cd,s=t.xaxis,l=t.yaxis,c=[],u=o[0].trace;if(!i.hasMarkers(u))return[];if(!1===e)for(r=0;r<o.length;r++)o[r].selected=0;else for(r=0;r<o.length;r++){var f=o[r],h=f.lonlat;if(h[0]!==a){var p=[n.modHalf(h[0],360),h[1]],d=[s.c2p(p),l.c2p(p)];e.contains(d,null,r,t)?(c.push({pointNumber:r,lon:h[0],lat:h[1]}),f.selected=1):f.selected=0}}return c}},{\"../../constants/numerical\":680,\"../../lib\":703,\"../scatter/subtypes\":1098}],1136:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx/hovertemplate_attributes\"),i=t(\"../../lib/extend\").extendFlat,a=t(\"../scatter/attributes\"),o=t(\"../../plots/attributes\"),s=a.line;e.exports={mode:a.mode,r:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},theta:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},r0:{valType:\"any\",dflt:0,editType:\"calc+clearAxisTypes\"},dr:{valType:\"number\",dflt:1,editType:\"calc\"},theta0:{valType:\"any\",dflt:0,editType:\"calc+clearAxisTypes\"},dtheta:{valType:\"number\",editType:\"calc\"},thetaunit:{valType:\"enumerated\",values:[\"radians\",\"degrees\",\"gradians\"],dflt:\"degrees\",editType:\"calc+clearAxisTypes\"},text:a.text,hovertext:a.hovertext,line:{color:s.color,width:s.width,dash:s.dash,shape:i({},s.shape,{values:[\"linear\",\"spline\"]}),smoothing:s.smoothing,editType:\"calc\"},connectgaps:a.connectgaps,marker:a.marker,cliponaxis:i({},a.cliponaxis,{dflt:!1}),textposition:a.textposition,textfont:a.textfont,fill:i({},a.fill,{values:[\"none\",\"toself\",\"tonext\"],dflt:\"none\"}),fillcolor:a.fillcolor,hoverinfo:i({},o.hoverinfo,{flags:[\"r\",\"theta\",\"text\",\"name\"]}),hoveron:a.hoveron,hovertemplate:n(),selected:a.selected,unselected:a.unselected}},{\"../../components/fx/hovertemplate_attributes\":618,\"../../lib/extend\":693,\"../../plots/attributes\":748,\"../scatter/attributes\":1075}],1137:[function(t,e,r){\"use 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n=t(\"../../lib\"),i=t(\"../scatter/subtypes\"),a=t(\"../scatter/marker_defaults\"),o=t(\"../scatter/line_defaults\"),s=t(\"../scatter/line_shape_defaults\"),l=t(\"../scatter/text_defaults\"),c=t(\"../scatter/fillcolor_defaults\"),u=t(\"../scatter/constants\").PTS_LINESONLY,f=t(\"./attributes\");function h(t,e,r,n){var i,a=n(\"r\"),o=n(\"theta\");if(a)o?i=Math.min(a.length,o.length):(i=a.length,n(\"theta0\"),n(\"dtheta\"));else{if(!o)return 0;i=e.theta.length,n(\"r0\"),n(\"dr\")}return e._length=i,i}e.exports={handleRThetaDefaults:h,supplyDefaults:function(t,e,r,p){function d(r,i){return n.coerce(t,e,f,r,i)}var g=h(0,e,0,d);if(g){d(\"thetaunit\"),d(\"mode\",g<u?\"lines+markers\":\"lines\"),d(\"text\"),d(\"hovertext\"),\"fills\"!==e.hoveron&&d(\"hovertemplate\"),i.hasLines(e)&&(o(t,e,r,p,d),s(t,e,d),d(\"connectgaps\")),i.hasMarkers(e)&&a(t,e,r,p,d,{gradient:!0}),i.hasText(e)&&l(t,e,p,d);var v=[];(i.hasMarkers(e)||i.hasText(e))&&(d(\"cliponaxis\"),d(\"marker.maxdisplayed\"),v.push(\"points\")),d(\"fill\"),\"none\"!==e.fill&&(c(t,e,r,d),i.hasLines(e)||s(t,e,d)),\"tonext\"!==e.fill&&\"toself\"!==e.fill||v.push(\"fills\"),d(\"hoveron\",v.join(\"+\")||\"points\"),n.coerceSelectionMarkerOpacity(e,d)}else e.visible=!1}}},{\"../../lib\":703,\"../scatter/constants\":1079,\"../scatter/fillcolor_defaults\":1083,\"../scatter/line_defaults\":1087,\"../scatter/line_shape_defaults\":1089,\"../scatter/marker_defaults\":1093,\"../scatter/subtypes\":1098,\"../scatter/text_defaults\":1099,\"./attributes\":1136}],1139:[function(t,e,r){\"use strict\";var n=t(\"../scatter/hover\"),i=t(\"../../plots/cartesian/axes\"),a=t(\"../../lib\");function o(t,e,r,n){var o=r.radialAxis,s=r.angularAxis;o._hovertitle=\"r\",s._hovertitle=\"\\u03b8\";var l=t.hi||e.hoverinfo,c=[];function u(t,e){c.push(t._hovertitle+\": \"+i.tickText(t,e,\"hover\").text)}if(!e.hovertemplate){var f=l.split(\"+\");if(-1!==f.indexOf(\"all\")&&(f=[\"r\",\"theta\",\"text\"]),-1!==f.indexOf(\"r\")&&u(o,o.c2l(t.r)),-1!==f.indexOf(\"theta\")){var h=t.theta;u(s,\"degrees\"===s.thetaunit?a.rad2deg(h):h)}-1!==f.indexOf(\"text\")&&n.text&&(c.push(n.text),delete n.text),n.extraText=c.join(\"<br>\")}}e.exports={hoverPoints:function(t,e,r,i){var a=n(t,e,r,i);if(a&&!1!==a[0].index){var s=a[0];if(void 0===s.index)return a;var l=t.subplot,c=s.cd[s.index],u=s.trace;if(l.isPtInside(c))return s.xLabelVal=void 0,s.yLabelVal=void 0,o(c,u,l,s),s.hovertemplate=u.hovertemplate,a}},makeHoverPointText:o}},{\"../../lib\":703,\"../../plots/cartesian/axes\":751,\"../scatter/hover\":1085}],1140:[function(t,e,r){\"use strict\";e.exports={moduleType:\"trace\",name:\"scatterpolar\",basePlotModule:t(\"../../plots/polar\"),categories:[\"polar\",\"symbols\",\"showLegend\",\"scatter-like\"],attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,colorbar:t(\"../scatter/marker_colorbar\"),calc:t(\"./calc\"),plot:t(\"./plot\"),style:t(\"../scatter/style\").style,hoverPoints:t(\"./hover\").hoverPoints,selectPoints:t(\"../scatter/select\"),meta:{}}},{\"../../plots/polar\":815,\"../scatter/marker_colorbar\":1092,\"../scatter/select\":1095,\"../scatter/style\":1097,\"./attributes\":1136,\"./calc\":1137,\"./defaults\":1138,\"./hover\":1139,\"./plot\":1141}],1141:[function(t,e,r){\"use strict\";var n=t(\"../scatter/plot\"),i=t(\"../../constants/numerical\").BADNUM;e.exports=function(t,e,r){for(var a=e.layers.frontplot.select(\"g.scatterlayer\"),o={xaxis:e.xaxis,yaxis:e.yaxis,plot:e.framework,layerClipId:e._hasClipOnAxisFalse?e.clipIds.forTraces:null},s=e.radialAxis,l=e.angularAxis,c=0;c<r.length;c++)for(var u=r[c],f=0;f<u.length;f++){var h=u[f],p=h.r;if(p===i)h.x=h.y=i;else{var d=s.c2g(p),g=l.c2g(h.theta);h.x=d*Math.cos(g),h.y=d*Math.sin(g)}}n(t,o,r,a)}},{\"../../constants/numerical\":680,\"../scatter/plot\":1094}],1142:[function(t,e,r){\"use strict\";var n=t(\"../scatterpolar/attributes\"),i=t(\"../scattergl/attributes\");e.exports={mode:n.mode,r:n.r,theta:n.theta,r0:n.r0,dr:n.dr,theta0:n.theta0,dtheta:n.dtheta,thetaunit:n.thetaunit,text:n.text,hovertext:n.hovertext,hovertemplate:n.hovertemplate,line:i.line,connectgaps:i.connectgaps,marker:i.marker,fill:i.fill,fillcolor:i.fillcolor,textposition:i.textposition,textfont:i.textfont,hoverinfo:n.hoverinfo,selected:n.selected,unselected:n.unselected}},{\"../scattergl/attributes\":1123,\"../scatterpolar/attributes\":1136}],1143:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../scatter/subtypes\"),a=t(\"../scatterpolar/defaults\").handleRThetaDefaults,o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),c=t(\"../scatter/fillcolor_defaults\"),u=t(\"../scatter/constants\").PTS_LINESONLY,f=t(\"./attributes\");e.exports=function(t,e,r,h){function p(r,i){return n.coerce(t,e,f,r,i)}var d=a(t,e,h,p);d?(p(\"thetaunit\"),p(\"mode\",d<u?\"lines+markers\":\"lines\"),p(\"text\"),p(\"hovertext\"),\"fills\"!==e.hoveron&&p(\"hovertemplate\"),i.hasLines(e)&&(s(t,e,r,h,p),p(\"connectgaps\")),i.hasMarkers(e)&&o(t,e,r,h,p),i.hasText(e)&&l(t,e,h,p),p(\"fill\"),\"none\"!==e.fill&&c(t,e,r,p),n.coerceSelectionMarkerOpacity(e,p)):e.visible=!1}},{\"../../lib\":703,\"../scatter/constants\":1079,\"../scatter/fillcolor_defaults\":1083,\"../scatter/line_defaults\":1087,\"../scatter/marker_defaults\":1093,\"../scatter/subtypes\":1098,\"../scatter/text_defaults\":1099,\"../scatterpolar/defaults\":1138,\"./attributes\":1142}],1144:[function(t,e,r){\"use strict\";var n=t(\"point-cluster\"),i=t(\"fast-isnumeric\"),a=t(\"../scattergl\"),o=t(\"../scatter/colorscale_calc\"),s=t(\"../scatter/calc\").calcMarkerSize,l=t(\"../scattergl/convert\"),c=t(\"../../lib\"),u=t(\"../../plots/cartesian/axes\"),f=t(\"../scatterpolar/hover\").makeHoverPointText,h=t(\"../scattergl/constants\").TOO_MANY_POINTS;e.exports={moduleType:\"trace\",name:\"scatterpolargl\",basePlotModule:t(\"../../plots/polar\"),categories:[\"gl\",\"regl\",\"polar\",\"symbols\",\"showLegend\",\"scatter-like\"],attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),colorbar:t(\"../scatter/marker_colorbar\"),calc:function(t,e){var r=t._fullLayout,n=e.subplot,i=r[n].radialaxis,a=r[n].angularaxis,c=i.makeCalcdata(e,\"r\"),f=a.makeCalcdata(e,\"theta\"),p=e._length,d={};p<c.length&&(c=c.slice(0,p)),p<f.length&&(f=f.slice(0,p)),d.r=c,d.theta=f,o(t,e);var g,v=d.opts=l.style(t,e);return 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p(t,e,r){this.scene=t,this.uid=r,this.surface=e,this.data=null,this.showContour=[!1,!1,!1],this.contourStart=[null,null,null],this.contourEnd=[null,null,null],this.contourSize=[0,0,0],this.minValues=[1/0,1/0,1/0],this.maxValues=[-1/0,-1/0,-1/0],this.dataScaleX=1,this.dataScaleY=1,this.refineData=!0,this.objectOffset=[0,0,0]}var d=p.prototype;d.getXat=function(t,e,r,n){var i=s(this.data.x)?s(this.data.x[0])?this.data.x[e][t]:this.data.x[t]:t;return void 0===r?i:n.d2l(i,0,r)},d.getYat=function(t,e,r,n){var i=s(this.data.y)?s(this.data.y[0])?this.data.y[e][t]:this.data.y[e]:e;return void 0===r?i:n.d2l(i,0,r)},d.getZat=function(t,e,r,n){var i=this.data.z[e][t];return null===i&&this.data.connectgaps&&this.data._interpolatedZ&&(i=this.data._interpolatedZ[e][t]),void 0===r?i:n.d2l(i,0,r)},d.handlePick=function(t){if(t.object===this.surface){var e=(t.data.index[0]-1)/this.dataScaleX-1,r=(t.data.index[1]-1)/this.dataScaleY-1,n=Math.max(Math.min(Math.round(e),this.data.z[0].length-1),0),i=Math.max(Math.min(Math.round(r),this.data._ylength-1),0);t.index=[n,i],t.traceCoordinate=[this.getXat(n,i),this.getYat(n,i),this.getZat(n,i)],t.dataCoordinate=[this.getXat(n,i,this.data.xcalendar,this.scene.fullSceneLayout.xaxis),this.getYat(n,i,this.data.ycalendar,this.scene.fullSceneLayout.yaxis),this.getZat(n,i,this.data.zcalendar,this.scene.fullSceneLayout.zaxis)];for(var a=0;a<3;a++){var o=t.dataCoordinate[a];null!=o&&(t.dataCoordinate[a]*=this.scene.dataScale[a])}var s=this.data.hovertext||this.data.text;return Array.isArray(s)&&s[i]&&void 0!==s[i][n]?t.textLabel=s[i][n]:t.textLabel=s||\"\",t.data.dataCoordinate=t.dataCoordinate.slice(),this.surface.highlight(t.data),this.scene.glplot.spikes.position=t.dataCoordinate,!0}};var 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v(t,e){if(t<e)return 0;for(var r=0;0===Math.floor(t%e);)t/=e,r++;return r}function m(t){for(var e=[],r=0;r<g.length;r++){var n=g[r];e.push(v(t,n))}return e}function y(t){for(var e=m(t),r=t,n=0;n<g.length;n++)if(e[n]>0){r=g[n];break}return r}function x(t,e){if(!(t<1||e<1)){for(var r=m(t),n=m(e),i=1,a=0;a<g.length;a++)i*=Math.pow(g[a],Math.max(r[a],n[a]));return i}}d.calcXnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getXat(e-1,0),i=this.getXat(e,0);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r},d.calcYnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getYat(0,e-1),i=this.getYat(0,e);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r};var b=[1,2,4,6,12,24,36,48,60,120,180,240,360,720,840,1260],_=b[9],w=b[13];function k(t,e){for(var r=!1,n=0;n<t.length;n++)if(e===t[n]){r=!0;break}!1===r&&t.push(e)}d.estimateScale=function(t,e){for(var r=1+function(t){if(0!==t.length){for(var e=1,r=0;r<t.length;r++)e=x(e,t[r]);return e}}(0===e?this.calcXnums(t):this.calcYnums(t));r<_;)r*=2;for(;r>w;)r--,r/=y(r),++r<_&&(r=w);var n=Math.round(r/t);return n>1?n:1},d.refineCoords=function(t){for(var e=this.dataScaleX,r=this.dataScaleY,n=t[0].shape[0],o=t[0].shape[1],s=0|Math.floor(t[0].shape[0]*e+1),l=0|Math.floor(t[0].shape[1]*r+1),c=1+n+1,u=1+o+1,f=i(new Float32Array(c*u),[c,u]),h=0;h<t.length;++h){this.surface.padField(f,t[h]);var p=i(new Float32Array(s*l),[s,l]);a(p,f,[e,0,0,0,r,0,0,0,1]),t[h]=p}},d.setContourLevels=function(){var t,e,r,n=[[],[],[]],i=[!1,!1,!1],a=!1;for(t=0;t<3;++t)if(this.showContour[t]&&(a=!0,this.contourSize[t]>0&&null!==this.contourStart[t]&&null!==this.contourEnd[t]&&this.contourEnd[t]>this.contourStart[t]))for(i[t]=!0,e=this.contourStart[t];e<this.contourEnd[t];e+=this.contourSize[t])r=e*this.scene.dataScale[t],k(n[t],r);if(a){var o=[[],[],[]];for(t=0;t<3;++t)this.showContour[t]&&(o[t]=i[t]?n[t]:this.scene.contourLevels[t]);this.surface.update({levels:o})}},d.update=function(t){var e,r,n,a,s=this.scene,p=s.fullSceneLayout,d=this.surface,g=t.opacity,v=l(t,g),m=s.dataScale,y=t.z[0].length,x=t._ylength,b=s.contourLevels;this.data=t;var _=[];for(e=0;e<3;e++)for(_[e]=[],r=0;r<y;r++)_[e][r]=[];for(r=0;r<y;r++)for(n=0;n<x;n++)_[0][r][n]=this.getXat(r,n,t.xcalendar,p.xaxis),_[1][r][n]=this.getYat(r,n,t.ycalendar,p.yaxis),_[2][r][n]=this.getZat(r,n,t.zcalendar,p.zaxis);if(t.connectgaps)for(t._emptypoints=h(_[2]),f(_[2],t._emptypoints),t._interpolatedZ=[],r=0;r<y;r++)for(t._interpolatedZ[r]=[],n=0;n<x;n++)t._interpolatedZ[r][n]=_[2][r][n];for(e=0;e<3;e++)for(r=0;r<y;r++)for(n=0;n<x;n++)null==(a=_[e][r][n])?_[e][r][n]=NaN:a=_[e][r][n]*=m[e];for(e=0;e<3;e++)for(r=0;r<y;r++)for(n=0;n<x;n++)null!=(a=_[e][r][n])&&(this.minValues[e]>a&&(this.minValues[e]=a),this.maxValues[e]<a&&(this.maxValues[e]=a));for(e=0;e<3;e++)this.objectOffset[e]=.5*(this.minValues[e]+this.maxValues[e]);for(e=0;e<3;e++)for(r=0;r<y;r++)for(n=0;n<x;n++)null!=(a=_[e][r][n])&&(_[e][r][n]-=this.objectOffset[e]);var k=[i(new Float32Array(y*x),[y,x]),i(new Float32Array(y*x),[y,x]),i(new Float32Array(y*x),[y,x])];o(k[0],function(t,e){return _[0][t][e]}),o(k[1],function(t,e){return _[1][t][e]}),o(k[2],function(t,e){return _[2][t][e]}),_=[];var T={colormap:v,levels:[[],[],[]],showContour:[!0,!0,!0],showSurface:!t.hidesurface,contourProject:[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],contourWidth:[1,1,1],contourColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],contourTint:[1,1,1],dynamicColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],dynamicWidth:[1,1,1],dynamicTint:[1,1,1],opacity:t.opacity},A=u(t);if(T.intensityBounds=[A.min,A.max],t.surfacecolor){var M=i(new Float32Array(y*x),[y,x]);o(M,function(e,r){return t.surfacecolor[r][e]}),k.push(M)}else T.intensityBounds[0]*=m[2],T.intensityBounds[1]*=m[2];(w<k[0].shape[0]||w<k[0].shape[1])&&(this.refineData=!1),!0===this.refineData&&(this.dataScaleX=this.estimateScale(k[0].shape[0],0),this.dataScaleY=this.estimateScale(k[0].shape[1],1),1===this.dataScaleX&&1===this.dataScaleY||this.refineCoords(k)),t.surfacecolor&&(T.intensity=k.pop());var S=[!0,!0,!0],E=[\"x\",\"y\",\"z\"];for(e=0;e<3;++e){var C=t.contours[E[e]];S[e]=C.highlight,T.showContour[e]=C.show||C.highlight,T.showContour[e]&&(T.contourProject[e]=[C.project.x,C.project.y,C.project.z],C.show?(this.showContour[e]=!0,T.levels[e]=b[e],d.highlightColor[e]=T.contourColor[e]=c(C.color),C.usecolormap?d.highlightTint[e]=T.contourTint[e]=0:d.highlightTint[e]=T.contourTint[e]=1,T.contourWidth[e]=C.width,this.contourStart[e]=C.start,this.contourEnd[e]=C.end,this.contourSize[e]=C.size):(this.showContour[e]=!1,this.contourStart[e]=null,this.contourEnd[e]=null,this.contourSize[e]=0),C.highlight&&(T.dynamicColor[e]=c(C.highlightcolor),T.dynamicWidth[e]=C.highlightwidth))}(function(t){var e=t[0].rgb,r=t[t.length-1].rgb;return e[0]===r[0]&&e[1]===r[1]&&e[2]===r[2]&&e[3]===r[3]})(v)&&(T.vertexColor=!0),T.objectOffset=this.objectOffset,T.coords=k,d.update(T),d.visible=t.visible,d.enableDynamic=S,d.enableHighlight=S,d.snapToData=!0,\"lighting\"in t&&(d.ambientLight=t.lighting.ambient,d.diffuseLight=t.lighting.diffuse,d.specularLight=t.lighting.specular,d.roughness=t.lighting.roughness,d.fresnel=t.lighting.fresnel),\"lightposition\"in t&&(d.lightPosition=[t.lightposition.x,t.lightposition.y,t.lightposition.z]),g&&g<1&&(d.supportsTransparency=!0)},d.dispose=function(){this.scene.glplot.remove(this.surface),this.surface.dispose()},e.exports=function(t,e){var r=t.glplot.gl,i=n({gl:r}),a=new p(t,i,e.uid);return i._trace=a,a.update(e),t.glplot.add(i),a}},{\"../../components/colorscale\":592,\"../../lib\":703,\"../../lib/gl_format_color\":700,\"../../lib/str2rgbarray\":726,\"../heatmap/find_empties\":978,\"../heatmap/interp2d\":981,\"gl-surface3d\":315,ndarray:445,\"ndarray-fill\":435,\"ndarray-homography\":437}],1174:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"../../components/colorscale/defaults\"),o=t(\"./attributes\");function s(t,e,r){e in t&&!(r in 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m=\"contours.\"+v[c],y=f(m+\".show\"),x=f(m+\".highlight\");if(y||x)for(u=0;u<3;++u)f(m+\".project.\"+v[u]);y&&(f(m+\".color\"),f(m+\".width\"),f(m+\".usecolormap\")),x&&(f(m+\".highlightcolor\"),f(m+\".highlightwidth\")),f(m+\".start\"),f(m+\".end\"),f(m+\".size\")}g||(s(t,\"zmin\",\"cmin\"),s(t,\"zmax\",\"cmax\"),s(t,\"zauto\",\"cauto\")),a(t,e,l,f,{prefix:\"\",cLetter:\"c\"}),e._length=null}}},{\"../../components/colorscale/defaults\":590,\"../../lib\":703,\"../../registry\":831,\"./attributes\":1171}],1175:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),colorbar:{min:\"cmin\",max:\"cmax\"},calc:t(\"./calc\"),plot:t(\"./convert\"),moduleType:\"trace\",name:\"surface\",basePlotModule:t(\"../../plots/gl3d\"),categories:[\"gl3d\",\"2dMap\",\"noOpacity\"],meta:{}}},{\"../../plots/gl3d\":791,\"./attributes\":1171,\"./calc\":1172,\"./convert\":1173,\"./defaults\":1174}],1176:[function(t,e,r){\"use strict\";var n=t(\"../../components/annotations/attributes\"),i=t(\"../../lib/extend\").extendFlat,a=t(\"../../plot_api/edit_types\").overrideAll,o=t(\"../../plots/font_attributes\"),s=t(\"../../plots/domain\").attributes;(e.exports=a({domain:s({name:\"table\",trace:!0}),columnwidth:{valType:\"number\",arrayOk:!0,dflt:null},columnorder:{valType:\"data_array\"},header:{values:{valType:\"data_array\",dflt:[]},format:{valType:\"data_array\",dflt:[]},prefix:{valType:\"string\",arrayOk:!0,dflt:null},suffix:{valType:\"string\",arrayOk:!0,dflt:null},height:{valType:\"number\",dflt:28},align:i({},n.align,{arrayOk:!0}),line:{width:{valType:\"number\",arrayOk:!0,dflt:1},color:{valType:\"color\",arrayOk:!0,dflt:\"grey\"}},fill:{color:{valType:\"color\",arrayOk:!0,dflt:\"white\"}},font:i({},o({arrayOk:!0}))},cells:{values:{valType:\"data_array\",dflt:[]},format:{valType:\"data_array\",dflt:[]},prefix:{valType:\"string\",arrayOk:!0,dflt:null},suffix:{valType:\"string\",arrayOk:!0,dflt:null},height:{valType:\"number\",dflt:20},align:i({},n.align,{arrayOk:!0}),line:{width:{valType:\"number\",arrayOk:!0,dflt:1},color:{valType:\"color\",arrayOk:!0,dflt:\"grey\"}},fill:{color:{valType:\"color\",arrayOk:!0,dflt:\"white\"}},font:i({},o({arrayOk:!0}))}},\"calc\",\"from-root\")).transforms=void 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\",cn:{table:\"table\",tableControlView:\"table-control-view\",scrollBackground:\"scroll-background\",yColumn:\"y-column\",columnBlock:\"column-block\",scrollAreaClip:\"scroll-area-clip\",scrollAreaClipRect:\"scroll-area-clip-rect\",columnBoundary:\"column-boundary\",columnBoundaryClippath:\"column-boundary-clippath\",columnBoundaryRect:\"column-boundary-rect\",columnCells:\"column-cells\",columnCell:\"column-cell\",cellRect:\"cell-rect\",cellText:\"cell-text\",cellTextHolder:\"cell-text-holder\",scrollbarKit:\"scrollbar-kit\",scrollbar:\"scrollbar\",scrollbarSlider:\"scrollbar-slider\",scrollbarGlyph:\"scrollbar-glyph\",scrollbarCaptureZone:\"scrollbar-capture-zone\"}}},{}],1180:[function(t,e,r){\"use strict\";var n=t(\"./constants\"),i=t(\"../../lib/extend\").extendFlat,a=t(\"fast-isnumeric\");function o(t){if(Array.isArray(t)){for(var e=0,r=0;r<t.length;r++)e=Math.max(e,o(t[r]));return e}return t}function s(t,e){return t+e}function l(t){var e,r=t.slice(),n=1/0,i=0;for(e=0;e<r.length;e++)Array.isArray(r[e])||(r[e]=[r[e]]),n=Math.min(n,r[e].length),i=Math.max(i,r[e].length);if(n!==i)for(e=0;e<r.length;e++){var a=i-r[e].length;a&&(r[e]=r[e].concat(c(a)))}return r}function c(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=\"\";return e}function u(t){return t.calcdata.columns.reduce(function(e,r){return r.xIndex<t.xIndex?e+r.columnWidth:e},0)}function f(t,e){return Object.keys(t).map(function(r){return i({},t[r],{auxiliaryBlocks:e})})}function h(t,e){for(var r,n={},i=0,a=0,o={firstRowIndex:null,lastRowIndex:null,rows:[]},s=0,l=0,c=0;c<t.length;c++)r=t[c],o.rows.push({rowIndex:c,rowHeight:r}),((a+=r)>=e||c===t.length-1)&&(n[i]=o,o.key=l++,o.firstRowIndex=s,o.lastRowIndex=c,o={firstRowIndex:null,lastRowIndex:null,rows:[]},i+=a,s=c+1,a=0);return n}e.exports=function(t,e){var r=l(e.cells.values),p=function(t){return t.slice(e.header.values.length,t.length)},d=l(e.header.values);d.length&&!d[0].length&&(d[0]=[\"\"],d=l(d));var 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C=Math.max(o(e.header.line.width),o(e.cells.line.width)),L={key:e.uid+t._context.staticPlot,translateX:v.x[0]*t._fullLayout._size.w,translateY:t._fullLayout._size.h*(1-v.y[1]),size:t._fullLayout._size,width:m,maxLineWidth:C,height:y,columnOrder:M,groupHeight:y,rowBlocks:T,headerRowBlocks:k,scrollY:0,cells:i({},e.cells,{values:r}),headerCells:i({},e.header,{values:g}),gdColumns:g.map(function(t){return t[0]}),gdColumnsOriginalOrder:g.map(function(t){return t[0]}),prevPages:[0,0],scrollbarState:{scrollbarScrollInProgress:!1},columns:g.map(function(t,e){var r=A[t];return A[t]=(r||0)+1,{key:t+\"__\"+A[t],label:t,specIndex:e,xIndex:M[e],xScale:u,x:void 0,calcdata:void 0,columnWidth:S[e]}})};return L.columns.forEach(function(t){t.calcdata=L,t.x=u(t)}),L}},{\"../../lib/extend\":693,\"./constants\":1179,\"fast-isnumeric\":224}],1181:[function(t,e,r){\"use strict\";var n=t(\"../../lib/extend\").extendFlat;r.splitToPanels=function(t){var 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n=t(\"./constants\"),i=t(\"d3\"),a=t(\"../../lib/gup\"),o=t(\"../../components/drawing\"),s=t(\"../../lib/svg_text_utils\"),l=t(\"../../lib\").raiseToTop,c=t(\"../../lib\").cancelTransition,u=t(\"./data_preparation_helper\"),f=t(\"./data_split_helpers\"),h=t(\"../../components/color\");function p(t){return Math.ceil(t.calcdata.maxLineWidth/2)}function d(t,e){return\"clip\"+t._fullLayout._uid+\"_scrollAreaBottomClip_\"+e.key}function g(t,e){return\"clip\"+t._fullLayout._uid+\"_columnBoundaryClippath_\"+e.calcdata.key+\"_\"+e.specIndex}function v(t){return[].concat.apply([],t.map(function(t){return t})).map(function(t){return t.__data__})}function m(t,e,r){var o=t.selectAll(\".\"+n.cn.scrollbarKit).data(a.repeat,a.keyFun);o.enter().append(\"g\").classed(n.cn.scrollbarKit,!0).style(\"shape-rendering\",\"geometricPrecision\"),o.each(function(t){var e=t.scrollbarState;e.totalHeight=function(t){var e=t.rowBlocks;return 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n=t(\"../box/attributes\"),i=t(\"../../lib/extend\").extendFlat;e.exports={y:n.y,x:n.x,x0:n.x0,y0:n.y0,name:i({},n.name,{}),orientation:i({},n.orientation,{}),bandwidth:{valType:\"number\",min:0,editType:\"calc\"},scalegroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},scalemode:{valType:\"enumerated\",values:[\"width\",\"count\"],dflt:\"width\",editType:\"calc\"},spanmode:{valType:\"enumerated\",values:[\"soft\",\"hard\",\"manual\"],dflt:\"soft\",editType:\"calc\"},span:{valType:\"info_array\",items:[{valType:\"any\",editType:\"calc\"},{valType:\"any\",editType:\"calc\"}],editType:\"calc\"},line:{color:{valType:\"color\",editType:\"style\"},width:{valType:\"number\",min:0,dflt:2,editType:\"style\"},editType:\"plot\"},fillcolor:n.fillcolor,points:i({},n.boxpoints,{}),jitter:i({},n.jitter,{}),pointpos:i({},n.pointpos,{}),width:i({},n.width,{}),marker:n.marker,text:n.text,hovertext:n.hovertext,hovertemplate:n.hovertemplate,box:{visible:{valType:\"boolean\",dflt:!1,editType:\"plot\"},width:{valType:\"number\",min:0,max:1,dflt:.25,editType:\"plot\"},fillcolor:{valType:\"color\",editType:\"style\"},line:{color:{valType:\"color\",editType:\"style\"},width:{valType:\"number\",min:0,editType:\"style\"},editType:\"style\"},editType:\"plot\"},meanline:{visible:{valType:\"boolean\",dflt:!1,editType:\"plot\"},color:{valType:\"color\",editType:\"style\"},width:{valType:\"number\",min:0,editType:\"style\"},editType:\"plot\"},side:{valType:\"enumerated\",values:[\"both\",\"positive\",\"negative\"],dflt:\"both\",editType:\"calc\"},offsetgroup:n.offsetgroup,alignmentgroup:n.alignmentgroup,selected:n.selected,unselected:n.unselected,hoveron:{valType:\"flaglist\",flags:[\"violins\",\"points\",\"kde\"],dflt:\"violins+points+kde\",extras:[\"all\"],editType:\"style\"}}},{\"../../lib/extend\":693,\"../box/attributes\":864}],1186:[function(t,e,r){\"use 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u=c.cd,f=u[0].trace,h=\"h\"===f.orientation?t.xa:t.ya,p=u[c.index],d=p.isSum?p.b+p.s:p.rawS;if(!p.isSum){if(d>0)c.extraText=g(d)+\" \"+o;else{if(!(d<0))return;c.extraText=\"(\"+g(-d)+\") \"+s}c.extraText+=\"<br>Initial: \"+g(p.b+p.s-d)}return c.color=function(t,e){var r=t[e.dir].marker,n=r.color,a=r.line.color,o=r.line.width;if(i(n))return n;if(i(a)&&o)return a}(f,p),[c]}function g(t){return n(h,t)}}},{\"../../components/color\":580,\"../../plots/cartesian/axes\":751,\"../bar/hover\":847}],1205:[function(t,e,r){\"use 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" });\n",
" require(['plotly'], function(Plotly) {\n",
" window._Plotly = Plotly;\n",
" });\n",
" }\n",
" </script>\n",
" "
]
},
"metadata": {},
"output_type": "display_data"
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "[nltk_data] Downloading package averaged_perceptron_tagger to\n",
- "[nltk_data] /home/j562r/nltk_data...\n",
- "[nltk_data] Package averaged_perceptron_tagger is already up-to-\n",
- "[nltk_data] date!\n",
- "[nltk_data] Downloading package wordnet to /home/j562r/nltk_data...\n",
- "[nltk_data] Package wordnet is already up-to-date!\n"
- ]
}
],
"source": [
"import numpy as np\n",
"from scipy.spatial.distance import cdist\n",
"from scipy.spatial import distance\n",
"from scipy.stats import pearsonr\n",
"from sklearn.preprocessing import MinMaxScaler, StandardScaler\n",
"import gensim\n",
"import os\n",
"import re\n",
"import seaborn as sns\n",
"import pandas as pd\n",
"pd.set_option('display.max_colwidth', -1)\n",
"from sklearn.manifold import TSNE\n",
"from sklearn.cluster import KMeans\n",
"import plotly\n",
"from plotly.subplots import make_subplots\n",
"import plotly.graph_objects as go\n",
"plotly.offline.init_notebook_mode()\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib\n",
"import colorsys\n",
"import sys\n",
"import json\n",
"sys.path.append('..')\n",
- "from mtc.mtc_config import NLP_MODELS_PATH, NLP_RAW_DATA, NLP_EXPERIMENT_PATH\n",
"from pathlib import Path"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
+ "source": [
+ "NLP_RAW_DATA = os.environ.get('NLP_RAW_DATA')\n",
+ "NLP_EXPERIMENT_PATH = os.environ.get('NLP_EXPERIMENT_PATH')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
"source": [
"# If problems with the fonts occur (e.g. it cannot find the serif family), run\n",
"# sudo apt-get install msttcorefonts -qq\n",
"# rm ~/.cache/matplotlib/fontlist-v*.json\n",
"# Source: https://stackoverflow.com/a/42841531\n",
"plt.rcParams['font.family'] = 'serif'\n",
"plt.rcParams['font.serif'] = ['Times New Roman']\n",
"plt.rcParams['font.cursive'] = ['Times New Roman']\n",
"plt.rcParams['mathtext.fontset'] = 'custom'\n",
"plt.rcParams['mathtext.rm'] = 'Times New Roman'\n",
"plt.rcParams['mathtext.it'] = 'Times New Roman:italic'\n",
"plt.rcParams['mathtext.bf'] = 'Times New Roman:bold'\n",
"plt.rcParams['font.size'] = 18"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load the Data"
]
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# Pure data\n",
"raw_train_path = NLP_RAW_DATA + '/n2c2/clinicalSTS2019.train.txt'\n",
"raw_test_path = NLP_RAW_DATA + '/n2c2/clinicalSTS2019.test.txt'\n",
"raw_test_path_labels = NLP_RAW_DATA + '/n2c2/clinicalSTS2019.test.gs.sim.txt'\n",
"df_train = pd.read_csv(raw_train_path, sep='\\t', header=None, names=['a', 'b','Label'])\n",
"\n",
"df_test = pd.read_csv(raw_test_path, sep='\\t', header=None, names=['a', 'b'])\n",
"df_test['Label'] = pd.read_csv(raw_test_path_labels, sep='\\t', header=None, names=['Label'])['Label']\n",
"\n",
"\n",
"# Results:\n",
"SET_DIR = NLP_EXPERIMENT_PATH + '/submission_generation/03_12_2020_20_18_37_original_data/bert_base/'\n",
"TSNE_DIR = SET_DIR + '1_example_run_step1/preprocessed_data_2020-03-15_21-49-55/'\n",
"vectors = np.load(TSNE_DIR + 'tsne_vectors.npy')\n",
"projections = np.load(TSNE_DIR + 'tsne_projections.npy')\n",
"#df_se = pd.read_pickle(os.path.join(NETWORK_SHARE + SET_DIR + '1_example_run_step1/preprocessed_data_2020-03-15_21-49-55/sentence_embeddings.pickle'))\n",
"\n",
"test_train_labels = 2 * (1642 * ['Training set'] + 412 * ['Test set']) \n",
"train_idx_bool = np.array([t == 'Training set' for t in test_train_labels])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The statistics show the absolute difference between the ground truth and the bert scores. Opaque points perform badly with bert."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Sentence lengths test-train"
]
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"def number_of_words(row):\n",
" all_length = []\n",
" number_of_words = (row['a'] + ' ' + row['b']).split()\n",
" all_length.append(number_of_words)\n",
" return len(number_of_words)\n",
"df_test['Number of Words'] = df_test.apply(lambda row: number_of_words(row), axis=1)\n",
"df_train['Number of Words'] = df_train.apply(lambda row: number_of_words(row), axis=1)"
]
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
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9fYB45tPXgHpDoxEzxnwaeAdP7EwKYLdKnnbjOrU6d84FLi3/rFbWjcbCDyvjHTTGQvgbfZejbzGE+If7syVJY41tj5Fn26NLZYfBqylufYTBzfjXrSWVx/NapDc6ksjM21qk31Ou126R1tDqPP0HRWcJwDrArPLxHhS39r2yuZ1TtnVeRl9bZ5tKkf/spMvMi9vE0p/DKDpCb87MJ53Lmdm4QovyuHt2cIxByczL6esM+tfGuF1RDIa+CfDDsiPxnDLPvhGxWZlnXYqhJ1rO6hfFxBGvL/9sef4DP6Lvc9f8eWy8zn9sdGY2lb868K7yzwv7Kf8v/WxvdBifEMU4af+chCIzv5KZl/azX0+yk0oaXhtWHs9rSss2+32e4v746cB3gFsi4l3Rz0Cbg9DuWJ3k689F5XoKbQYKHGYtYy5/JXpa+eeiVnlKl5frrSJincr2gaYSbvzqOagGcfkr1POGEM8Uil9mxpTyF+yvZ+bd5SCUH6WI+bWVbJ00MBvnziaVbY3BMp+dmdNaLGuUy1DOteH+bEnSWGPbY+TZ9hgG5T/+L6FvsP9XM7IzKw70+g50hV3jSpxOOkMvqjxutHUa7Zwv99POmVpp6/yksn+3n5l9yvVgzgkobiUcSSeX65kUV/1BcVXVWWUHH8B3y3VQXD0FxZX4NzZfwVSxO8XQEtDPcy2vYmxcmdb8PAd6nfegGKsV+r+6sr8yzqQYC2si8HHgroj4dAxiAqJeZCeVNLyeW3n8q8HuVP6qtQtwIsWAe1tRDMJ4S0S8bFgjHF7VX/0GagiMtOrsN+0a2PMrj0fy18P1KH61grERT8fKGUy+CFxBcUXT8zLzPQPsNpDGuVM9bxoVf0czGbWyCn+2JGmwbHvUx7bHEJVXLL2Svg6i/4qI17fZZVXV6jwd9nbOIDWON1bOie/RdyvrIRExCXgdfZ1XUIwZ1XgNG7cFHgKc0qbcoX4eh/o8t6w8HtItxOWVqS+kmE10EcW58FHgLxHxgSHGMe7ZSSUNk4jYE2hMGzufITQUATLzgcw8gmLMgpMoKrRNgJ9GxKuGMdTh1LjN61H6LkmvyyOVx1v1m6vvV8mlFLPnjJTqtLiDiQeKX7THlCim2v4TxTggzy7Ha+h2bA/oO3furmxrvGbPp42h3t6xin62JGlAtj1sezRZJdoemfk7nji+5HcoBhwfT6pDITTaOo33Z592bZmIWG2Yb4NsnKdj4pwob21t3C73MorOp0epXH1WjhHVuK1v24g4mOJKph+0KXqon8ehPs/qezJtiPuSmcsz8zMUnV2fpIh3LeALEXFc2517jJ1U0vD5WOXxcUP5Rz4ivtEYpDAzb8/Mw4DnUM5eAXxqWCMdPpuX64vK+9kbGuNYDPQdM5wV8E0UU21DMYV2fxrjClzcFPOwKgdnbNx//rw2jY1GPNeXg3zWLiLeHxGNyvdHFBX9pzJzOBvWjXPnF5VtjdfrrRHR7haOkwZ7kFX4syVJg2Hbo49tj1Wo7ZGZ36eYQRhgDYrxL/tTx3vbrcZ5+iDFbH/Q995sDLyxzb5vopgZc7hcWa5nRMQz+snTOCdW0jfA/Ug6qVxPphjA/tQWg6F/t/L4qxSfn/n0b27l8WA+jxe1ydPKvMrjZw1lx4j4j4jYBorbXjPz4xS32l5WZvlgOeaWsJNKGhYR8V5g//LP8ym+SIdifWBOdUNmXknf4HzNvwY0vsTrHlfnheX6i03bGw22DZu2ExGbV/5co0WZjcbbkJ5beRlt4xeX3SOiv5lYti/X3xpK+R1qVK7r03fPfbN28VR/ZRuVhlc5VsYemflQRMygb4D0dgPodlKXvJBirIevVLY1ZtGZAZzRatafiHgTT/ylbCBD/WxJ0irBtodtj36MhbZHDGbfzDyW9rdvNfT73tLXGQSt39u6NM7T/61MQvAb+iY3OD4innT1WDnO2XuB3w1jLNXOnubBwhsa58S5/XRcNs6L4WqPng08UD5emyfe6gdAOQHDFZU8bc+VzJxH39Wkr6r84Npse4rvs+/2k96fP9B39ebrBsjbfKVc8MTxXMnMe4ADKb5/JgKbDTGecctOKql/A1Z05eW4H6avoXQ+cFA/v5JV/+Fu1Qg6vsVgpY3LUK9u2t4YVHD7iFgvIiZHxInlPd3Qd4nx9AEuFx4opoa1mjdExB7Ay4HjM/PXTcmNX4qeFhEHlfknlGMOVDsldijTqt9Fjec2p0zbPiI+PsiYjwbuo6gIvtT83CNiU4ppgc/JzJ827duYOWeg+9MHO10yFFPK3lA+/lxEPOGcKmf2eBXF+3tCi/2rv6jMGMJxq1avPG57Tpfvw9fpq+Afpm/MgA+XnVZExDMjovr6bRgR60fEG1oU2+rcOZBiHJT/yMxbK0k/BP5YPt4PuCYi3hoRu0TEnIj4MsVnrfnX/eoxWr0/Q/lsSVKdbHv0se3R+vgDGQttj2kUs9oNxlspOm/aaby3e0fE3gDl+fdO4L8q+Zrf2+rr1uqz9c9b8irncav0oZ6n04APUnRqfL6xPTOXUNzmBcXr85uI+EJEPC8iZkXE2yk6p75VDvDdKs4hTxZQzjDZ6JB5Z0Rs2yJb40fA/sYcbXT4dHpONMf0GHB6+ecVbWYEPalcLwbOGkTR76EYL2ptWlwNGhHPo5gl+n8y8/qm5Mbr3PI1zsxllTJ3Ld+vZo1298QWP7Z+OCK2btp2P8VtwI/QNwuoMtPFxaVpoWg0PETRs50UM6VMK9MC2AA4lOIf6qQYX+A/gAn9lBcUlVKjvO8AEyvpPy23XwI8q9y2AcWtUA9TjAVULe+1lbIepvgl4t/KtJnAtZX0d1ePVSljIsWvFo18xwBRSZ9WKecB4HCKijiAl1J8qf53dZ/KvtMpZm5plH1v+Xr+unxts7L8Etinsu95lbT5FPfxbzSYmMs8u5SxJcV96xuX259J0SC7EFi3aZ91KWb6SIpfVvZpSn8OxbS0WeabNoRzaTOK6WiT4rLibcvtW5Z//xHYtMV+UygGlmw8118M5biVck6rlHECsFqLPGsAsyn+0VkJrF9JO6Oy/1Lgr+X7uU95XjS23wRsUu6zNcWsJ1m+f6+jaIBPoGgELQL+vc3rdXPTOdJYlgD7t/hsfbqS51Rg9U4/Wy4uLi51Ldj2ANse1fRVsu1RPue7KK6WPoAW7Y5+3rtbgHn9pG9H0dZoxPVXin/qzwC2rWxfCZwL7EhxMUa1ffAtnnj+TwK+XUk/pOlcnF6+d430f2mK6ZTKMT9fOV92oLjt7BfA9H4+l19rOh+ry7dbfC9cWEn/PLBGB98vk8vXJiluW5tTxrIO8D8U3ydz+on3yKbXfrth+s7bvSzzyDZ5ppXv/feGUO7LKNqMjder8T06p4z/28Ckpn22oe8zvKIso9X3TFTOmxXAf1J0iE2gmH3w7spr9QmKNvDqwIfLbbdTXAG7GkUn6v9SfP7fMhyv6XhZag/AxWUsLcBe5ZdZf/8kL6X4tW0+xWDS36S4p3xqmzKn88SKtbEsA3Yu8/y0KW1xWYF8G9i8RZkBfJai8XUH8LZy+8f7iXs5ZeVZ5tuZvoZP8/ObXsk3AXgNxS8X91L8MnEHRQNsjwFey2dRNAyXlM/l6EaFUJZzOk0NsjJtc4oreRaX6x2HEnOZdwbwhfJ9fLQ8/q+Ag2lqzANHlZVDc7n3l+m3tUhbCbxvCOfVVIpxQ64tn9c9wO8pKv0pLfJ/snzPWh33IeAZAxxvHeDFwGfKfZrPhUVlOQ+V8VTTf9mirO9QNPwfoPglbr3K+fYIRefW5k37Taa4pPx8iobPoxS/EH1rEPGvTfFPwI3l+7uQYmysHZvyTaD1Z2s58IpOPlsuLi4uo71g28O2x/hoe+zMk9sUWb7u7xpEvNsAc9ukz6Ho/HmU4oexo8pzcguKtsiJwC6V8/+xfs7J15TLin7e180oxkhq9f78oSmm51C0a24rjzefonPqIFp0cDTt+wrgYorP9hKKcaMOa8pzaD9xrACe08F3TZRlNm47fKA8Pz4NbNgi//7l693q872I8jugy++/q2jRmdeU53SaOgkHUe7W5Tkxr3xf/wKcA7y4Rd7T+nmOf29T/sHA5eV7t4jis/5W4J3l63oWRWf9M8vX/cM8+XNxbxmTP5g2LVG+yJIkSZIkSVJtHJNKkiRJkiRJtbOTSpIkSZIkSbWzk0qSJEmSJEm1s5NKkiRJkiRJtbOTSpIkSZIkSbWbWHcAY9WMGTNyiy22qDsMaeSseKxYT5xcbxw95rEVjwMweaK/EUhjwVVXXbUwM2fWHYf62AbrwBiq063nJEkDadf+spOqH1tssQVz586tOwxp5Hz3JcX6sPPqjaPHHPSN3wNwxhGza45EEkBE3Fl3DHoi22AdGEN1uvWcJGkg7dpf/sQhSZIkSZKk2tlJJUmSJEmSpNrZSSVJkiRJkqTa2UklSZIkSZKk2jlwutSr9v5A3RH0pKOev03dIUiSxpsxVKdbz0mSumEnldSrtt637gh60l7bzKg7BEnSeDOG6nTrOUlSN7zdT+pV915bLBpV189fxPXzF9UdhiRpPBlDdbr1nCSpG15JJfWq8z9SrA87r944esyx59wAwBlHzK45EknSuDGG6nTrOUlSN7ySSpIkSZIkSbWzk0qSJEmSJEm1s5NKkiRJkiRJtbOTSpIkSZIkSbVz4HSpV+338boj6EkfetF2dYcgSRpvxlCdbj0nSeqGnVRSr9psj7oj6EmzNp9edwiSpPFmDNXp1nOSpG54u5/Uq+66vFg0qq668wGuuvOBusOQJI0nY6hOt56TJHXDK6mkXnXxscX6sPPqjaPHfP78mwE444jZNUciSRo3xlCdbj0nSerGmOykioh1gWOBvYEA/gx8IDPvHUIZLwU+CGwELAVWAN8FTsjMx4c9aI2oay79BSsfub/uMFqasNZ67LzXC+sOQ5Ik9ahHFj1ArlzOLeef1jafbRZJ0lg35jqpImI94CJgLjArM1dExHHAFRGxV2beOYgyjgSOBw7NzNPKbc8ALgSeDRw8Yk9AI2LlI/cza8ayusNo6aqFY7PzTJIk9YZcuZy1V398wLaSbRZJ0lg3Fsek+iawCXBUZq4otx1NcUXVyRER7XaOiLWBLwCnNzqoADLzRuCzwBsj4jkjErkkSZIkSZI6MqY6qSJib+DlwLmZubixPTOXA2cD+wAHDFDMDsCawMIWabeV6427j1aSJEmSJEnDZazd7ndQub6qRdrlwJHAocD/tSljfrl+XUR8MjP/XknbDlgC/LbbQKVV3os+U3cEPenjL9u+7hAkSePM3VscyPbTltcdBmA9J0nqzljrpHpRuZ7XIu32cr1nuwIy866IOA94CfDDiHhFZj4SEdOAdwFHZqY35Esb7lR3BD1ph43WqTsESdI48+jUTWGdsTF2p/WcJKkbY+Z2v3Ksqc3LP+9pkWVRud44IqYMUNxhwA3A84HLImInirGu3pmZJw9HvNIq77ZfFYtG1aW3LuTSW1vdjSxJUmfWXnQTLLi57jAA6zlJUnfG0pVU04EJ5eNHWqQvrjyeBjzaX0GZuaAc3+onwN7An4CvARe3CyAiDgcOB9hss80GHbi0SvrNfxfrrfetN44e85Vf3grAXtvMqDkSSdJ4seFffw6rPw4zt6s7FOs5SVJXxsyVVMAalcetrleudqg9Nojy1qW4muoFwL3AO4BzImLN/nbIzBMzc7fM3G3mzJmDOIQkSZIkSZKGw1jqpHqo8nhyi/Sp5Xol8GC7giJiR+AC4JOZeTGwB0WH1QHAWeWthZIkSZIkSRojxkwnVWYupm8sqlaXMTWuGb4rM7O/ciJiNeB04OLMnF+WfTfF+FS3Af8CvG644pYkSZIkSVL3xkwnVemScv20FmlblesLByjjecAOwDXVjZl5H3Bw+efLOw1QkiRJkiRJw28sDZwO8D3gDcBs4DtNabuV67MGKGNauV67OSEz/xARfwee0k2Q0rjwsi/XHUFPOu7Vz6w7BEnSOHPnVm9gx3VbDek6+qznJEndGFNXUmXmBcBvgVdExD/HpSofvxK4rMxDREyIiFMi4tyIqHZI/YFi5r/9m8uPiGkUnVgDXY0ljX8ztikWjRgNSXIAACAASURBVKqtZ67F1jPXqjsMSdI48tiU9WGt9esOA7CekyR1Z0x1UpUOpRgc/bgoTAK+CiwF3ljJtwvF7XsvodIhVd7W9yFg34g4NiImAETEdOAUik6wb4zGE5HGtJt/XiwaVRfdcB8X3XBf3WFIksaRdR68Fu67ru4wAOs5SVJ3xtrtfmTmHRExG/gCcC1Fh9VvgF0zc0El6w3AXIoroy5tKuOEiLgLeD9wV0QsLMs5E/jvzBwb10NLdbrshGK93QH1xtFjvvnb2wF4wfZj4xdvSdKqb/35F8OCx2H9HesOxXpOktSVMddJBZCZ84DXDpBnCbB7m/SfAT8b3sgkSZIkSZI0Esbi7X6SJEmSJEnqMXZSSZIkjVMRsW5EfCUi/hQR10bEaRGx4RDLWCMiPlnuf3U5ac12g9x3ZkQcHRHnRcQJEfGWzp6JJEnqBXZSSZIkjUMRsR5wCTAVmJWZOwF3AldExOaDLGMqcB7FEAuzM3MXiuEUroiIXQbY9+3ALRST37wqM9+Vmd/p+AlJkqRxb0yOSSVpFLzaSS7r8KWDdq47BEm945vAJhSdSyvKbUcDbwJOjoh9MzMHKOM4YB9gy8xcDJCZJ0bEvwGnR8SzMnNpdYeICOBrFDM2vywzLxq+p6RW7njaoew0fXndYQDWc5Kk7nglldSr1tmkWDSqNpo2hY2mTak7DEnjXETsDbwcOLfRuQSQmcuBsyk6ntpO7xoRWwFHApdl5t1NyWcC2wKtbt/7HHAE8DY7qEbH8snTYcq6dYcBWM9JkrpjJ5XUq677cbFoVJ3zp/mc86f5dYchafw7qFxf1SLt8nJ96ABlvIbiqvtBlxERBwAfBC7IzFMHF6q6te7CuTD/j3WHAVjPSZK64+1+Uq+6shwWZMfX1BtHjzn1D3cC8LJnbVRzJJLGuReV63kt0m4v13sOQxm7RsSUzHw0IiYCXy63HzfIODUMZt73W3jgcdho17pDsZ6TJHXFK6kkSZLGkXJMqMbA6Pe0yLKoXG8cEe3uy9pyEGVMBLYoHz+f4hbA+cBaEfHtiLg0Im6KiK9HxAaDfQ6SJKk32UklSZI0vkwHJpSPH2mRvrjyeFqbcmYOsYxXl+slwOoU41LtC5xSPr4yIjZuczxJktTj7KSSJEkaX9aoPF7WIr063MNjgyhnsGU8vVx/NTPPzswVmbk8Mz8NXEQx0+CXWh0oIg6PiLkRMXfBggVtQpIkSeOZnVSSJEnjy0OVx5NbpE8t1yuBBwdRTrsyABaW68btfH9rkf/Ecv3yiJjUnJiZJ2bmbpm528yZM5uTJUlSj3DgdKlXve57dUfQk7528Ky6Q5A0zmXm4oi4B9iY4pa9G5uyzCjXd2Vmtinq5jJvq16jRhlLgfvKx0vK9YoW+eeW68nlvk7/Noxu2/Zt7PzUVhe8jT7rOUlSN7ySSupVU59aLBpV06dOYvrUJ11EIEnD7ZJy/bQWaVuV6wuHoYxLMrNxu99N5XqTFvnvLdeP88QrvTQMVq6+Fkxaq+4wAOs5SVJ37KSSetXVpxWLRtWP5t7Nj+beXXcYksa/xuWys1uk7VauzxqgjFOBHEIZPy3Xe7fI37ga6w+ZuaRFurrw1Pt/D3dfXncYgPWcJKk7dlJJveqa7xeLRtWZV/2VM6/6a91hSBrnMvMC4LfAKyLin2NKlY9fCVxW5iEiJkTEKRFxbkSsXSnjRoqOqjkRsX7TIQ4CbgdOrmw7E7gWeElEbNaU/4Xl+rjun52aPXXBH+DuK+oOA7CekyR1x04qSZKk8elQisHRj4vCJOCrFONIvbGSbxfgYOAlwP5NZbwbuA34SkSsXpbzCWAz4KDMXNrImJmPAwdS3M53RkRMB4iInYFPA1/IzPNG4HlKkqRxwoHTJUmSxqHMvCMiZgNfoLjCaSXwG2DXzFxQyXoDxcDm04BLm8p4KCL2Aj4LXAMsL8vaOTPntTjmreUxPwdcFxH3AY8C78vM04f5KY5r11z6C1Y+cv+g8m726GLWXn3KCEckSdLIs5NKkiRpnCo7kl47QJ4lwO5t0hcCbx3CMW+juKJKXVj5yP3MmjG4GfsWPL5yhKORJGl0eLufJEmSJEmSaueVVFKveuOP6o6gJ5102LPrDkGSNM5cOun5vGqPXeoOA7CekyR1x04qqVdNWrPuCHrSlEkT6g5BkjTOrIyJMGFS3WEA1nOSpO54u5/Uq674ZrFoVJ3y+3mc8vt5NUchSRpPtlpxM8y7dOCMo8B6TpLUDTuppF51/U+LRaPq3Gvv5dxr7607DEnSOLLpyjth/tV1hwFYz0mSumMnlSRJkiRJkmpnJ5UkSZIkSZJqZyeVJEmSJEmSamcnlSRJkiRJkmo3se4AJNXksPPqjqAnnXHE7LpDkCSNM5dM/hcOfO6susMArOckSd3xSipJkiRJkiTVzk4qqVf97vhi0ag68Te3ceJvbqs7DEnSOLLt8uvhtl/WHQZgPSdJ6o6dVFKvuuWCYtGouvjG+7n4xvvrDkOSNI5s+Pg9cN/1dYcBWM9JkrpjJ5UkSZIkSZJqZyeVJEmSJEmSamcnlSRJkiRJkmo3se4AJNVk9TXqjqAnrbH6hLpDkCSNMyuZABNWrzsMwHpOktQdO6mkXnXwj+uOoCed/JZn1x2CJGmcuXTyfhy4x6y6wwCs5yRJ3fF2P0mSJEmSJNXOTiqpV13y+WLRqDr+4ls5/uJb6w5DkjSOPGP5tXDLBXWHAVjPSZK6YyeV1Ktuv6RYNKp+95eF/O4vC+sOQ5I0jqz3+N9g4S11hwFYz0mSumMnlSRJkiRJkmpnJ5UkSZIkSZJqZyeVJEmSJEmSajex7gAk1WTNdeuOoCetu+akukOQJI0zjzEZJk2tOwzAek6S1B07qaReddCpdUfQk75+yKy6Q5AkjTN/mLwPB+42NuoX6zlJUje83U+SJEmSJEm1s5NK6lUXHVMsGlWfO/8mPnf+TXWHIUkaR3Zc/ke48Zy6wwCs5yRJ3fF2P6lX3X1l3RH0pD/e+WDdIUiSxpmnPr4QHlxadxiA9ZwkqTteSSVJkiRJkqTa2UklSZIkSZKk2tlJJUmSJEmSpNo5JpXUq56yUd0R9KQN11mj7hAkSePMklgTpkyrOwzAek6S1B07qaRe9Zpv1h1BT/ryv+5SdwiSpHHmykl7sfkus+oOA7CekyR1x9v9JEmSJEmSVDs7qaRe9fMPF4tG1SfOuZ5PnHN93WFIksaRZy27Eq7/Sd1hANZzkqTueLuf1Kv+9ue6I+hJN8z/R90hSJLGmWn5ICxaXncYgPWcJKk7XkklSZIkSZKk2tlJJUmSJEmSpNrZSSVJkiRJkqTa2Ukl9aqnbl0sGlVbzZzKVjOn1h2GpB4REetGxFci4k8RcW1EnBYRGw6xjDUi4pPl/ldHxLkRsd0A+xwZEdliOaC7Z6RWHo61Ya316g4DsJ6TJHXHgdOlXvXy4+uOoCd95tU71R2CpB4REesBFwFzgVmZuSIijgOuiIi9MvPOQZQxFfgZsByYnZmLI+Lwsow5mXl1i31WBz4IrGxKuj4zf97l01ILf5w0m612mlV3GID1nCSpO15JJUmSND59E9gEOCozV5TbjgYCODkiYhBlHAfsA7wtMxcDZOaJwE3A6RGxRot9DgHOy8yJTcuzun1CkiRpfLOTSupVP3t3sWhUfeQn1/KRn1xbdxiSxrmI2Bt4OXBuo3MJIDOXA2dTdDy1vfUuIrYCjgQuy8y7m5LPBLYF3tK0zwTg/cDnu30OGrxdl/0erj2j7jAA6zlJUnfspJJ61d9vKxaNqtsXLOb2BYsHzihJ3TmoXF/VIu3ycn3oAGW8hmJoiKGUcRCwFXB8RLynvOVQI2ztfBgeub/uMADrOUlSd4atkyoidoiIL0TEcRHxtOEqV5IkqZcMU5vqReV6Xou028v1nsNQxq4RMQWgvH3wI8AawCuALwN3RsSx5RVWkiRJbQ154PSI+GP5cDlwcWZ+NCL2BH4BTKYY5+DIiHh2Zt4yfKFKkiSNHyPVpio7izYv/7ynRZZF5XrjiJiSmY/2U9SWgyhjIrAFcCOwJsUYVk8F9gBeDEwHPgbsFhEvr4yNJUmS9CSdXEm1M3Af8KqyMTUB+BbFr2YnA88Cvgh8atiilCRJGn9Gqk01HWhcufRIi/TqvVjT2pQzcyhlZObizPxBZp6QmYcAWwMnlHkOAD7e34Ei4vCImBsRcxcsWNAmJEmSNJ4N+Uoq4FHg9Zn5UPn3vwLbAVdmZmPwzD9HxJXDEaCkEbLBM+uOoCdtv9FT6g5B0tgxUm2q6ox7y1qkV9t/jw2inI7KKJ/XURGxEDgGeG9EfCozn1ReOWPgiQC77bZbtolJLTwU6zJznbEx/Jf1nCSpG510Ut3SaEyVl5P/B5AUYxBUrd9lbJJG0gGfrTuCnnT0y3aoOwRJY8dItakeqjye3CJ9arleCTw4QDkzBigDYOEA8RwLvIriyrDtgWsGyK8h+tOk3dlmh1l1hwFYz0mSutPJ7X5LI2Ld8vHbgR0ppib+ZSNDRMwBNu4+PEmSpHFrRNpUmbmYvnGkZrbIMqNc35WZ7a5aunkQZSyluGWxXTwJfLv8s5MfSCVJUo/opJPqK8AfIuJn5ePHgHc3EiPihcAPhic8SSPmx28rFo2q955+Ne89/eq6w5A0Noxkm+qSct1qdsCtyvWFw1DGJZnZ7pbBhr9QDBB/6yDyaoh2X3YpXH1K3WEA1nOSpO4M+deszPx+RDwMvBH4MXB8Zl4NEBH/A2wLzB3WKCUNv3/MrzuCnnTvoqV1hyBpjBjhNtX3gDcAs4HvNKXtVq7PGqCMUyluPZzdIm2wZTRsCJyZmYsGzKkhWzOXwKOd/PY8/KznJEnd6OiS68w8Bzinxfb3A0TEGplpDSVJktTGSLWpMvOCiPgt8IqIeFfjaqeImAy8kuK2wgvKbROAk4B1KQZyf7gs48aIOBV4fUSsn5nV2/oOAm6nmIWwrYhYHXgtcPhQn4ckSeotQ/7JJSKe1JBq4Y0RsWsH8TSOsW5EfCUi/hQR10bEaRGxYRflzYyIoyPivIg4ISLeMvBekiRJI2cU2lSHUgyOflwUJgFfpRhH6o2VfLsABwMvAfZvKuPdwG3AVyJi9bKcTwCbAQdVO9Ai4ksRsTAi/r08FhExA/gc8OHMvLvD5yFJknpEJ9cFbzBQhsz8NvCeDsomItajGANhKjArM3cC7gSuiIjNOyjv7cAtFA2yV2XmuzKz+bJ3SZKk0TaibarMvIPiVr3NgGuBK4DFwK6ZOa+S9QaK2wr/AlzaVMZDwF7APyhm5bsa2BLYOTObb0X8GUWb7VPArRHxbeBfgf/KzD918hwkSVJvGfB2v4jYCdi5sml6RBwCRJsydwJeTfEL3lB9E9gEmJ2ZK8ptRwNvAk6OiH0HmImmEXcAXytjeFlmXtRBLNL4tenudUfQk3bdfN2BM0kal2poU1F2Rr12gDxLgH4rhcxcCLx1EMf6FTBriCFqGPx9tRnMXHfAPs9RYT0nSerGYMakuhXYEziGvumGTxpgnxhEnifvFLE38HLglHL6ZAAyc3lEnA0cCRwA/N8givsccARwiB1UUgsvOKbuCHrSf7zo6XWHIKk+o9amUm+5bvVdefozxkb/oPWcJKkbA3ZSZeajwNci4v+AsykaVd9ss8syisvFz+wgnoPK9VUt0i6n6KQ6lAE6qSLiAOCDwAWZeWoHcUiSJA2rUW5TSZIkrXIGPbtfZt4ZES8EvpuZnxiheF5Urue1SLu9XO/ZroCImAh8ufzzuOEJSxqHzji4WB9kP+5oevspRR/81w8ZG794Sxp9o9SmUg95zmOXwNw/wW71zw1kPSdJ6saQBk7PzAXAYYPJWw5YPmjlGFKNgdHvaZFlUbneOCKmtCnq+cC2wHxgrYj4dkRcGhE3RcTXI2Js3LAv1W3Jg8WiUfXgkmU8uGRZ3WFIqtlItqnUeybzGCxbPHDGUWA9J0nqxpBn9ysbVW2VM/R9aohFTwcmlI8faZFerXmntSnn1eV6CbA6xbhU+wKnlI+vjIiNW+0YEYdHxNyImLtgwYBPU5IkqWMj2KaSJElaJQ36dr+GiFgNeCfwGoqpkyc1ZZkArE/RQTQUa1Qet/r5pRrrY23KaYzW+NXMPLuy/dMRMQd4AfAl4HXNO2bmicCJALvtttuAMwhKkiR1agTbVJIkSaukIXdSAV8EjqL/6ZIbhtrJ81Dl8eQW6VPL9Uqg3T1Kjdv5/tYi7USKTqqXR8SkzPRaZEmSVJeRalNJkiStkjrppDoUmAt8ArgNWNoiz9OBs4ZSaGYujoh7gI2BmcCNTVkaUzXflZntGmtLyvWKFmlzy/Xksrz5Q4lRGle22qfuCHrSnk+bMXAmSb1iRNpU6j33r7YBM2dsVHcYgPWcJKk7nXRSLQfek5l/aJPnzoi4qIOyLwHeADwN+E1T2lbl+sIByrgJ2AXYpEXaveX6cZ545ZbUe/b5UN0R9KR377dN3SFIGjtGsk2lHnLj6juxw7ZjYzY96zlJUjeGPHA68BNg7UHke1cHZX+vXM9ukbZbuR7o18Sfluu9W6TNLNd/yMwlLdIlSZJGy0i2qSRJklY5nXRSfYziaqeBXDDUgjPzAuC3wCsi4p/jUpWPXwlcVuYhIiZExCkRcW5EVBt4ZwLXAi+JiM2aDvHCcn3cUGOTxp1TX1MsGlWHfucKDv3OFXWHIWlsGLE2lXrLXo9dDJd/ve4wAOs5SVJ3Ornd7wBgUUR8HbisRfpqwE7Ath3GdGhZ7nER8QGKGW2+SjFOwxsr+XYBDi4f70/ROUVmPh4RBwK/A86IiJdk5gMRsTPwaeALmXleh7FJ48fyVkOfaKQtXb6y7hAkjR0j3aZSj5jASli5vO4wAOs5SVJ3OumkOhrYgmImmrf1kyfocCaazLwjImYDX6C4ImolxfhUu2bmgkrWGygGG50GXNpUxq1lGZ8DrouI+4BHgfdl5umdxCVJkjTMRrRNJUmStKrppJPqx8CeFLflPUYxCHnVJIqrnPbvNKjMnAe8doA8S4Dd26TfBhzYaQySJEkjbMTbVJIkSauSTjqpfgT8NDNbXZb+TxFxW2chSZIk9QTbVJIkSRVD7qTKzCsjYma7PBHxLIpfBiWNVdv6w3wd9nvGenWHIGmMsE2l4XLvahszc/1N6g4DsJ6TJHWnkyupaBobqpUTgH06KVvSKNnz3XVH0JMO33vrukOQNIbYptJwuGX1Hdhp61l1hwFYz0mSujPkTqqI+E6b5AnAlsBzKWbe+16HcUmSJI1rtqkkSZKeqJMrqd48yHwfwwaVNHZ99yXF+rDz6o2jxxz0jd8DcMYRs2uORNIY8OZB5rNNpbb2eexCuOwyeO5RdYdiPSdJ6konnVSPA0cCN/dT3tHA54GHu4hLkiRpvLNNJUmSVNFJJ9XVmXlif4kRkcBngf06jkqSJGn8s00lSZJUsdpQd8jM3QdI/yWwCfDFToOSJEka72xTSZIkPdGQO6kGEhFTgKnAgcNdtiRJUq+wTSVJknpNJ7P7valN8nSKhtTawD2dBiVpFOzwyroj6Ekv3WnDukOQNEbYptJwuXvC5szcaLO6wwCs5yRJ3elkTKqTgGyTHuX6Ex2ULWm0PPttdUfQkw6ZvUXdIUgaO07CNpWGwe0Tt2PXLWbVHQZgPSdJ6k4nnVQAfwSu58kNq2XA34D/y8zLuwlM0ghbtqRYT1qz3jh6zKPLVgIwZdKEmiORNEbYplLXJuQKWLkMJkyqOxTrOUlSVzrppPob8JzMXDncwUgaRae9tlgfdl69cfSYN3/3CgDOOGJ2zZFIGgNsU2lY7LXsl3D5FfDco+oOxXpOktSVTgZOf7+NKUmSpK7ZppIkSaoY8pVUmfkDgIgI4KXA84A1gXnA2Zl563AGKEmSNB7ZppIkSXqijsakiohtgR8BOzY2UYyl8LmI+BHwrsxcODwhSpIkjU+2qSRJkvoMuZMqItYDfgVsCDwI/B64C3gMmAnsCVwcEc/NzMXDGKskSdK4YZtKkiTpiTq5kupjwFTg7cBJmbmsmlhesv4l4P3AsV1HKGlk7PyGuiPoSQfO2qTuECSNHbapNCzmTdiamZtuXncYgPWcJKk7nXRSvRR4WWb+tlViZmZEvA+4FBtU0ti1yxvrjqAnvXa3TesOQdLYYZtKw+LOiVuz+6az6g4DsJ6TJHWnk9n9Hu6vMdWQmQlM6SwkSaNi8d+LRaPqgcXLeGDxsoEzSuoFtqk0LCblUlj2SN1hANZzkqTudNJJNWANGBF7UIyvIGms+uGbikWj6h2nXsU7Tr2q7jAkjQ22qTQsZi/7Dcz9bt1hANZzkqTudNJJdUVEfKBVQkRMiIjXA+dQDAQqSZKk1mxTSZIkVXQyJtVngasi4iDgYmABsC6wGbA/MANYAhwzTDFKkiSNR7apJEmSKobcSZWZf4uIFwKnAR8CskyKcn0vcFBm3jI8IUqSJI0/tqkkSZKeqJMrqcjMGyJiFsWsNC8FNgUWAZcAp2Tm2Bi5UZIkaQyzTSVJktSno04qgMx8HPhZuUha1ez+lroj6EkHP2fzukOQNMaMZJsqItYFjgX2prhC68/ABzLz3iGUsQbwn8ArgJXAPcD7M/PmQe7/sTKGLTNz3pCegAbltgnbMnOLLesOA7CekyR1Z8BOqohYjWJ8hOnAU4EbM3NRP3kPyswzhjdESSNix9fUHUFPetmzNqo7BEk1Ge02VUSsB1wEzAVmZeaKiDiOYsD2vTLzzkGUMZWi82w5MDszF0fE4WUZczLz6gH2nw18vJvnoYH9deIWsNGudYcBWM9JkrrTdna/iGg0Su4HfgRsAyxts8t1EfGViJg0fCFKGhGL/losGlXzH3qU+Q89WncYkkZZTW2qbwKbAEdl5opy29EUV1SdHBHR7559jgP2Ad6WmYsBMvNE4Cbg9PIqq5YiYh3gu8B9nT8FDcaUxxfDow/WHQZgPSdJ6k7bTirgIIpBPD8H7JqZp2TmY/1lzszrgf+hmK1G0lj2kyOKRaPqfWdcw/vOuKbuMCSNvlFtU0XE3sDLgXMbnUtlucuBsyk6ng4YoIytgCOByzLz7qbkM4FtgXb3jn8D+BrwlyE/AQ3Js5f/Dq4+te4wAOs5SVJ3Buqk2hf4fmZ+tBwvYUDlWAPXlZd3S5IkafTbVAeV66tapF1erg8doIzXUAwNMeQyIuItwJqZ+b8DHEOSJOmfBuqkOoTOxhE4vdxXkiRJo9+melG5ntci7fZyvecwlLFrREypJkTEtsCHgMMGjFKSJKlioE6qDTqZhSUzlwAbdxSRJEnS+DNqbapyrKnGFGv3tMjSGKx94+YOpiaN6eLalTER2KJy7EnAqRRjWP19sDFLkiTBwJ1Ua3VRtlN7SJIkFUazTTUdmFA+fqRF+uLK42ltypnZQRmfpRgH67cDBVkVEYdHxNyImLtgwYKh7CpJksaRiQOkP7WTQsspljfpZF9Jo+S576o7gp70tudtVXcIkuoxmm2q6ox7y1qkV9t//Q7eXilnUGVExIuAnYEXDCLGJyhnDDwRYLfddsuh7t/rbpn4DGZu/bS6wwCs5yRJ3Rmok+qvEfG8of4aBrwEGBvz4Epqbbu2kzpphLxg+/XrDkFSPUazTfVQ5fHkFulTy/XKAcp+CJgxQBkACyNifeC/gX8Z7MDwGj73TtgU1t+x7jAA6zlJUncGut3vHOC4iFh9sAVGxBrA0cCvuglM0ghbeGuxaFTdtuARblvQ6s4ZSePcqLWpMnMxfeNIzWyRZUa5visz2121dPMgylgK3Ae8DdgBuCcisroA+5R57yi3zRnkU9EgrfX4InjkvrrDAKznJEndGaiT6kTg6cBPI2LA8RAiYl3ghxSXep/UdXSSRs457y0WjaqP/uTPfPQnf647DEmjb7TbVJeU61b3gDXux7pwGMq4JDMfo7jq6uZ+lkfLvLeXfy8ZKHgNzazll8O1P6w7DMB6TpLUnbadVJm5CHgTxRTEN0fEiRHxqojYOiLWiYgJEbF+RDw3Ij4N3ERxWfq3MvPKkQ9fkiRp7KuhTfW9cj27Rdpu5fqsAco4FcjBlJGZJ2Tm01stwBVl3v3KbVe0KE+SJGnAManIzJ9HxJHA/wL/Vi79CeCngCMyS5IkVYxmmyozL4iI3wKviIh3lVc7ERGTgVcCl2XmBeW2CRRXa60LvD4zHy7LuDEiTgVeHxHrZ2b1frKDKK6MOrmT+CRJkloZ6HY/ADLzG8BzgSspGk2tloeADwAHZuaKEYlWkiRpFTbKbapDKQZHPy4Kk4CvUowj9cZKvl2Agymu3Nq/qYx3A7cBX4mI1ctyPgFsBhyUmUu7iE+SJOkJBrySqiEz/wg8JyJ2Ap4PbA1MAhZSNLQuyMxH2xQhSZLU80arTZWZd0TEbOALwLUUHVa/AXbNzAWVrDcAc4FpwKVNZTwUEXsBnwWuAZaXZe2cmfO6jVGSJKlq0J1UDZl5LUXjRNKqbO8P1B1BTzrq+dvUHYKkMWI02lRlR9JrB8izBNi9TfpC4K1dxDCn0301ODdOfCYztxkb9Yv1nCSpG0PupJI0Tmy9b90R9KS9tpkxcCZJkobg/gkbwszt6g4DsJ6TJHVnUGNSSRqH7r22WDSqrp+/iOvnL6o7DEnSOLLO4w/Aor/WHQZgPSdJ6o6dVFKvOv8jxaJRdew5N3DsOTfUHYYkaRzZeflcuP6susMArOckSd2xk0qSJEmSJEm1s5NKkiRJkiRJtRuRTqqIWC8iNhuJsiVJknqFbSpJktRLRupKqqnAa0aobEmSpF5hm0qSJPWMif0lRMSF7dLbmAQ8A/g98KUO45I00vb7eN0R9KQPvWhsTBEuafTYplLDNZf+gpWP3D+ovPNuvo5ZM7YdVN7rJu7Mvk9/ejehDRvrOUlSN9o127VtVgAAIABJREFUmP4BvLqftARigLL37igiSaNjsz3qjqAnzdp8et0hSBp9tqkEwMpH7mfWjGWDynvHnx4edLl/n7AeTN+y07CGlfWcJKkb7TqpvghsD7wFWACsKLcfABwDfBz4NfBYi33fBVw6XEFKGgF3XV6s7awaVVfd+QAwtEb8xZdezsJ/LB2pkLoy4ylrsN9enkPSAGxTaUQ9deX98MAdY6KjqpN6TpKkhn47qTLzsog4PTP/UN0eEW8B/iUzr+1v34j4CHA8cPawRSppeF18bLE+7Lx64+gxnz//ZgDOOGL2oPdZ+I+lrHxq/f94tLLw73fUHYI05tmm0kjbccU1cNNf4LlH1R1KR/WcJEkNbQdOz8xjW+3TrjFV7rcC2KqbwCRJksYL21SSJEkD62R2v6kRsU67DBGxM/C8zkKSJEnqCbapJEmSKjqZaeZc4McRcWBmPtScGBG7AGcBN3QbnCRJ0jhmm0rDYumyZfxj8aPcfN0tbfPdsGgKs140SkFJkv4/e3ceJ1lZHnr89zDMMMywDLOxg8OuuLCKCAKKBlHcoyCgiAsao8YYozEmbjcSo7lJbmK8XkhUFFRcccGI0SiIKDgoILsyMywzMMwMzDALsz/3j3Nam6a6u/ZTXfX7fj71OdV13nrr6TqfrvP0U+95XzWhmSLVR4DrgLsj4jsUidN6YBbwDOBEilVq3tWuICVJkvqQOZXaIjNh0mS2Tp89Zrs1Sx9XC5Ukqac0XKTKzNURcQJwEXAmxdLJQwLYCrwnM7/RnhAldcTz/77qCAbSB170pKpDkNQjzKnULj9ccxBHH3xY1WEAnuckSa1pZiQVmbkMeEGZWL0cOAjYAtwCXJSZt7UvREkdsftTq45gIB26x5jTz0gaMOZUaocHt+zIuu13qzoMwPOcJKk1TRWphmTmVcBVbYpFUjfd9eNiu/+zq41jwFz92+UAHH/g2JdkSBos5lRqxb6TH2KnNQt4ZIfqF4L0PCdJakVTRaqImAf8LbB3Zj6vfOxw4Gzgq5n5i/aFKKkjrvrHYmuRqqv+7X9+C5i8SyqYU6kdjpu2kBnLHuqJIpXnOUlSKxouUkXE/sAvKCb1vG/o8cz8dUQsAr4bET/OzL9pW5SSJEl9xpxKkiTpsZoZSfVRYDpwGfDE4Tsy8+GIeCNwS0Qszsz/24YYJUmS+pE5lSRJ0jDbNPGck4EXZebLgcetY1tO8PkI8PYWY5MkSepn5lSSJEnDNFOkWpqZPyrv58idEbEDxbeC81oJTJIkqc+ZU0mSJA3TzOV+i8fZ/w5gEsPmVpDUg170L1VHMJDOf/lTqg5BUu8wp1JbfH/NIRzzxCOqDgPwPCdJak0zRar/iYiXZOa3Ru6IiLcCH6H4NvDLrQYnqYNmH1h1BANp/zk7VB2CpN5hTqW2eGjLdNZv1xur6XmekyS1opki1T8Dl0fEc4A5EfFmYH/gNOBgIIAbgb9rW5SS2u+O/yq2B59abRwD5oe3LgXguU/ateJIJPUAcyq1xQFTljFj9R2s3PHgqkPxPCdJaknDRarM3BgRpwEfBGYCw1ebeRS4CHhvZq5tT4iSOuKaTxZbi1RddeFPFwAm75LMqdQ+T9/+HmYsX9UTRSrPc5KkVjQzkorM3AD8dUS8n+KbvpnAGuD2zNzYxvgkSZL6ljmVJEnSHzRcpIqIF2fmtwEyM4Hbh+2bFhG7Df2cmfe0JUpJkqQ+Y04lSZL0WNs08ZzLIuLzETG9xr7pwNHAJ4EFzQYVEbtExL9FxI0RcVNEXBIRuzfbX9nn30ZERsQTWulHkiSpTTqeU0mSJE0kzRSpAM4Cro+Iw4Y/mJnLMvPrwMuAFc10HBFzgSspkrMjM/OpwN3AdRGxb5N9Hgt8oJnnSpIkdVDHcipJkqSJppk5qe4C7gNOBH4eEe/NzH8d3iAzt0REs8PSLwT2Ao7NzM3lYx8EXgtcFBHPLofE1yUidgY+CywF9mwyJqn/vPz/VR3BQPrn0w8bv5GkQdHpnEoD4jurD+WZhx5VdRiA5zlJUmuaGUn1MPAc4EMURa5/johvR8TMEe02NdpxRJwAvBj47vCVbDJzE/AtiiSu0aXI/h/Fajm/azQeqa/tvFdxU1ftMWN79pixfdVhSOoNHcupNFhWb53Kxsk7Vx0G4HlOktSapi73y8JHgJMovgE8DbihLDK14vRye32NfdeW23Pq7SwiXg9My8z/02JcUv+5+evFTV31nRuX8J0bl1QdhqQe0cGcSgPkkClLmbnqlqrDADzPSZJa0+ycVABk5s+ApwHfoLhE70cR8cGICCCa6PL55XZRjX1Dk4YeV09HEXEQ8B7g3CbikPrfLz9T3NRVF//ibi7+xd1VhyGpx3Qgp9IAOWL7+9j1oflVhwF4npMktaaZItW04T9k5srM/GPgrcBGignKfwLs0kinZRI2NDH64hpNVpXbPSNizDHEETEFuBh4U2Y62agkSepFHcmpJEmSJqpmilQHRsSJIx/MzE8DTwduBZ4FHNhgvzOBSeX9NTX2rx12f8Y4fX2MYl6rnzYYgyRJUrd0KqeSJEmakJopUn0JeF1EfCIiHvP8zLwFOIpisvJGh6ZPHXZ/Y439w1ci3DBaJxHxfOAw4O8afH0i4ryImB8R85ctW9bo0yVJkhrRqZxKkiRpQtp2/CaPlZmvG2f/BuBPIuLSBrteOez+djX2Ty+3WyhWw3mciNgV+EfgjzJza4OvT2ZeAFwAcNRRR2Wjz5ckSapXB3MqSZKkCanhIlUDnkYxj0JdMnNtRCwG9gTmALeNaDK73N6TmaMVkN4EHAosLqa4qmlhue/ZmVl3fFLfedXnq45gIP3fs4+sOgRJE09DOdVwEbEL8BHgBIoRWb8B3p2Z9zfQx1Tg/cBLKL4sXAz8RWbeMUr7M4F3AwdTzCn6NeCvM7PWdA5qg28+8hSOf/IxVYcBeJ6TJLVm1Mv9ImLb8SYoH+O5TwE+3MRTryy3B9TYt1+5/cEYz18J3DHK7dGyzYLy53VNxCf1j+mzipu6aub0KcycPqXqMCR1UUU5FRExlyK3mg4cmZlPBe4GrouIfcd88h/6mA5cDhwNHJuZhwPfLvs4vEb7vwK+QPGF4zbA7sDbKQpV6pBHcwqbt502fsMu8DwnSWrFWHNSXQvcFRGPOeNFxJqI2DLWDbgB2LGJeIaGdhxbY99R5faboz05Mz+ZmYfUugHXlc1OLh+7brR+pIHw60uKm7rqq/Pv5avz7606DEndVUVOBXAhsBfw9szcXD72QYoRVRfFGMPOhzkfOJFixeS18PvpEW4HvlyOshr6fZ4MnAIcmJl7AzsD/7vcfUpEPKPJ30PjeMp2S5j98A1VhwF4npMktWasItVMiqRo8ojHv06R3Ix3a1hmXgH8FHhJRPx+Xqry/kuBa8o2RMSkiPhCRHw3IppN3qTBdcMXi5u66mvX38fXrr+v6jAkdVfXc6qIOAF4McVqx79fITkzNwHfoig8nTpOH/sBb6XIv0ZWHb4GHAS8fthjhwCnZeaC8rU2An8J3FLu36OZ30Xje8rU+5mz8saqwwA8z0mSWjNWkerpwKGZuWrE458BvgHMArbNzG2G3yjmuTqG5i+nO4divoPzozAF+BSwHjhrWLvDgbOBF1J8aydJktSLqsipTi+319fYd225PWecPl5RxlBXH5n5teEFsfKxpChSrQeuHuf1JEnSgBt14vTMXDbK41dGxLzMrLnCXrmq3i8j4tPNBJSZCyPiWOATwE0UBaurgCNGxHQrMB+YgUmPJEnqURXlVM8vt4tq7FtQbo9rQx9HRMT2mflojTZDDqWYOP3BcV5PkiQNuKZW98vMz9XR5i+b6bt87iLgleO0WUcxiWe9fZ7UbDySJEmd0Imcqpxramhi9MU1mgyN6NpznALTvDr62BZ4Ao9flXkolj8FvpeZ/zxe3JIkSWNd7teSiOiN2RslSZImsCZyqpnApPL+mhr7h1+SN2OMfuY000e5muEzIuKLwCeBcyPi9YwhIs6LiPkRMX/ZspoDzyRJ0gAYdSRVOeFmMyZRzBd1aJPPl9QNZ3216ggG0ufOfXrVIUjqsgpyqqnD7m+ssX94/rehjn4a7WMXYD9gKfAQMBv4z4jYnJmfp4ZyxcALAI466qgcIybV8JVVh3HiU2stjt19nuckSa0Y63K/LwG7dSsQSV02Zdr4bdR220+ZNH4jSf2m2znVymH3t6uxf3q53QLUnA9rWD+zx+kDYPnwHeUcXF8EvhgRH6L4/U8FPgrULFKpNZuZxNZtRi4eWQ3Pc5KkVoxVpPpP4K+B3wCPAFvr7HMScCAwt7XQJHXUdRcW26e/qdo4BswXfr4IgNcc+4Qqw5DUXV3NqTJzbUQsBvakuGRv5HxRs8vtPeXqe6O5o2w7p8a+oT7WU4yYGi2WVRHxGuBeYK+ImJWZK+r4NdSAw6fex9yHfsmDM+uerrVjPM9JkloxVpHqQmBuZr6l0U4jYjrw26ajktR5t1xWbC1SddV3b7ofMHmXBkwVOdWVwJnAARSrJA+3X7n9QR19HFf2MdJQH1dm5liXDJKZKyLiSorVAmtdOqga7n1gKb+8+c662h4waTGzVq3viSKV5zlJUitGnTg9M+8FPttMp5m5Fji72aAkSZL6RUU51dBldbUmKjqq3H5znD4uBrLFPoZsAK7PzNV1th94GzZtYev02XXdxhwPJ0nSBDLm6n6ZeW0znUbEG4AfNxWRJElSn+l2TpWZVwA/BV4SEb+fU6q8/1LgmrINETEpIr4QEd+NiB2H9XEbRaHqpIjYdcRLnA4sAC6q43fYBXgm8LeN/h6SJGmwjFmkasEC4EMd6luSJGlQtJJTnUMxOfr5UZgCfIpiHqmzhrU7nGK01guBU0b08Q7gLuDfImJy2c+HgX2A0zNz/VDDiPiPiLgqIs6IiEnlY3MpJlH/28z8ryZ/D0mSNCDGmpOqpogIioTl2cAOPL7QNQnYn2LZ4g+2GmA/uuHq/2bLmgerDqOmSTvM5bDjn1d1GJIk9b1O51SZuTAijgU+AdxEUbC6CjiiXIFvyK3AfGAGcPWIPlZGxPHAx4AbgE1lX4dl5qIRL7mQotB1CfCJiJgP3A38WWbWN7mSJEkaaA0XqYD3AX9XR7tfNdH3QNiy5kGOnN2b84Zev7w3i2fqgHMvrzqCgXTpm2tN7SJpQHU8pyoLSa8cp806YNQZtzNzOfDGOl7ro8BHGwxRbfDv9xzEGUefVnUYgOc5SVJrmrnc7zUUk3EeS7Hay5UUK7zMK29PAv4beEabYpQkSepH5lSSJEnDNFOkmgqcm5nXZuYC4EfAAZl5d3m7nWKll3PaGaikNvvZvxY3ddUFV93FBVfdVXUYknqDOZXa4qSZS9lt+TVVhwF4npMktaaZItWSzMcsdPtZ4K9GtLkOeGvTUUnqvDuvKG7qqh/d9iA/us3LaiUB5lRqk0N3WMUuq39bdRiA5zlJUmuaKVKtiYiPRMSzImJmZi4GHoyI8yNim4iYTDEJ6EHtDVWSJKmvmFNJkiQN08zE6R8F/gd4P/Ab4LDy/o3An5R9TqNYJUaSJEm1mVNJkiQN03CRKjOvioiXAG+mSKyGljj+Y4olh3cG7ir3S5IkqQZzKnXbfUse4NLvXVlX29k7TeXk44/pcESSJD1WMyOpyMzLgctHPPaDiNgdmFEuVSypl02eWnUEA2nq5ElVhyCph5hTqR02bd2GrduMn9av37SVLbPm1dXn8hULm4rF85wkqRVNFalGk5mbgeUAEXFFZp7Szv4ltdHZX686goF00eufXnUIkiYAcyo14oL7DuCMY06rOgzA85wkqTVNF6kiYh6wKzBlxK5tgKcBz2khLkmSpIFgTiVJklRouEgVEfsBXwEOb384krrmyo8X2xPfU20cA+Zff1QsEf6Okw+sOBJJVTOnUrs8b9b97PHgVSyZe0LVoXiekyS1pJmRVJ+hSKZuA1YAW0fsD+AAYPfWQpPUUQvKiVMtUnXVz35XTC9j8i4Jcyq1yUHTV7Pz2oUsofoilec5SVIrmilSHQE8IzN/OVqDiJgOLGo2KEmSpAFgTiVJkjTMNk0857qxkimAzFwLfKC5kCRJkgaCOZUkSdIwzRSpri+/1RvP0ib6liRJGhTmVJIkScM0U6T6J+DPx2oQEZOATzYVkaTumLZLcVNX7TJtCrtMG7mAl6QBZU6ltli7ZVs2T9q+6jAAz3OSpNY0MyfVCuCJEfFVYHWN/dsAT6JYSllSrzr94qojGEiffs2RVYcgqXeYU6ktPrd4P854xmlVhwF4npMktaaZItU/AK+uo1020bckSdKgMKeSJEkappki1dnAT4ALKOZIqLVc8tOB81uKTFJn/fBDxfa5H6owiMHzD9+/HYD3Pv+QiiOR1APMqdQWL5yzmL2X/oh7dz256lA8z0mSWtJMkWotcEpmbhqjzU8i4nXNhSSpK+4dc0Epdciv7n646hAk9Q5zKrXFE7Zfyw7r7qs6DMDznCSpNc1MnP79cZKpIU9uom9JkqRBYU4lSZI0TDNFqq9FxHF1tPuvJvqWJEkaFOZUkiRJwzRzud/vgLdExEMUw9RHmgQ8FTihlcAkSZL6nDmVJEnSMM0UqW4GpgPvbXMskrpppz2qjmAg7b7z1KpDaKtbbr+TS6sOoobZO03l5OOPqToMaTzmVGqLlZsmM2PyTlWHAfTfeU6S1F3NFKl+ARwG3AVs4PHLIm8LHAjMaS00SR31igurjmAg/csZh1cdQlut3rCFLbPmVR3G4yxfsbDqEKR6mFOpLS65fx5nPPO0qsMA+u88J0nqrmaKVFcCL8vMWsPSAYiIHYHfNh2VJElS/zOnkiRJGqaZidN/DLw2InYerUFmrgbe2HRUkjrvv/6quKmrPvydW/jwd26pOgxJvcGcSm3x0rn3ss/9V1QdBuB5TpLUmmZGUl0IHAIcDLxztEaZ+d1mg5LUBQ/8puoIBtKtSx6pOgRJvcOcSm2x59RHmb7+garDADzPSZJa08xIqh3L7XfGahQRzRTAJEmSBoU5lSRJ0jDNFKneAjwI/Hycdg7TkCRJGp05lSRJ0jDNfDN3M0VSdVFEfAIYObZ4MvAC4KAWY5MkSepn5lSSJEnDNFOkugbYvbz/8jbGIqmbZu1fdQQDab8506sOQVLvMKdSWyzbuB07bTer6jAAz3OSpNY0U6T6J+AfgUXAfcCWEfsDmAfs1VJkkjrrxf9adQQD6e9f/tSqQ5DUO8yp1BZfeWBfzjjutKrDADzPSZJa00yR6tPAGzLz0NEaRMQ04J6mo5IkSep/5lSSJEnDNDxxemauA95VR5t3NBuUpC749juKm7rqfd+4ifd946aqw5DUA8yp1C6v2u1u5i35btVhAJ7nJEmtaWpJ48y8AiAiZgLPAKYBizJz/rA2X2xLhJI6Y8VdVUcwkBYsW1t1CANhyR3zuX6b+6oOo6ZJO8zlsOOfV3UY6hHmVGqHOVM2MHXDiqrDADzPSZJa01SRKiK2Bz4BvJFi5ZmhxxcD52fmp9sTniRJjXtw0e1s3WV51WHUdPOq7S1S6ffMqSRJkv6g4SJVREwBrgCOLx9aQzHZ5wZgDvCpiHhWZp7VtiglSWrA+k1b2Tp9dtVh1LRm6cqqQ1CPMKeSJEl6rIbnpALeSZFMfRl4OrBzZj4pMw/PzL2AA4E9I+K1bYxTkiSp35hTSZIkDdPM5X5nA+/MzJrr12fmXRHxMuDrwOdbCU5SB+32lKojGEhP2mOnqkOQ1DvMqdQWi9dvz/Spu1UdBuB5TpLUmmaKVNNHS6aGZObD5RwLknrVqR+rOoKB9MEXjbrSvKTB0/GcKiJ2AT4CnAAE8Bvg3Zl5fwN9TAXeD7wE2AIsBv4iM++o0XZb4D3A64B9gYeA/wI+kJm9uZpBH7jswb0541mnVB0G4HlOktSaZi73Wzxeg4jYDZjXRN+SJEmDoqM5VUTMBa4EpgNHZuZTgbuB6yJi3zr7mA5cDhwNHJuZhwPfLvs4fETbAL4BfBTYBXgU2A04F/hVRBzUzO8hSZIGRzNFqvsj4sTRdkbE3sBlwM1NRyWp877+puKmrnrnl3/NO7/866rDkNQbOp1TXQjsBbw9MzeXj32QYkTVRWVRaTznAycCb8rMtQCZeQFwO/DlcpTVkDMoRk8dlZlzKApVLwUeppgI3pUKO+Ss3Rey/33frDoMwPOcJKk1zVzu9wngvyPiP4AfAcsokpB9gBcBLyj7fUG7gpTUAY8sqTqCnvOjq69l+SPrO/oaNy1cB8Cl37uy7ufcfOfveOKxDk6V+lDHcqqIOAF4MfCFoeISQGZuiohvAW8FTgW+N0Yf+5XtrsnMe0fs/hrwceD1wKfKx04DnpuZy8rXSuBbEfE24BLgpIjYKTMfafT30dhmTN7ElE298bbev6qz51FJUn9ruEiVmfMj4i0U3869a8TuALYCf5mZV7QhPknqmuWPrGfLrM4Wg3LyAoCGXmfNo7d1KhxJFepwTnV6ub2+xr5rKYpP5zBGkQp4BUWuOFoflH0MFan+fahANcJXgc8Bk8ubJElSTc1c7kdmXgo8Gfg/wF3ARopv/75KMV/BP7UtQkmSpD7VwZzq+eV2UY19C8rtcW3o44ihid0z85panWTmJopL/hZn5opxXlOSJA2wMYtUEfHt0fZl5j2Z+a7MPCgzt8/M3TLz9Mz8ZfvDlCRJmri6mVOVc00NTYxea3L2VeV2z3FWDhwa8jlWH9sCTxgnnlnAbIrRVJIkSaMa73K/Z0XEDpm5pivRSOqevY+uOoKBtM/MaVWHIKka3cypZgKTyvu1Xm/tsPszKFbhq2VOA32M5VXACuB/j9YgIs4DzgPYZ599xulOIy16dDrTpu1VdRgAHLHvLlWHIEmawMYrUu0M/Doifgk0Ogvi+sx8a3NhSeq4536o6ggG0imH7lZ1CJKq0c2caviKextr7B+e/22oo5+m+4iIacB7gbdk5sOjtStXDLwA4KijjsoxYlINly/bkx1POLnqMAB47/MPqToESdIEVs/E6dcAV1M7QRnuTOC55f3lFEsOS5IkqdCtnGrlsPvb1dg/vdxuoZgraqx+Zo/TBxQxjuZjwJcy8xtjtJEkSQLGL1ItzsxzxmpQznvwDxTJVAC3Aqdl5qK2RCipMy49u9iefnG1cQyYS669G4Czjtl3nJaS+kzXcqrMXBsRi4E9KS7ZG7lE6Oxye09mjjVq6Y6y7Zwa+4b6WA8srfXkiDgD2AX4szpDV5Net+cC9r7nK/x2n1dVHQpv+UKxGOSnX3NkxZFIkiai8YpUF461MyJ2AL4EvIAimboCOD0zH2lPeJI6Zt1YX56rU9Zt3FJ1CJKq0e2c6kqKEVkHAFeN2Ldfuf1BHX0cV/Yx0lAfV2bm4y73i4iTgJcDZ45TCFMbTJ+0mW23jDa12B+sW7GE5fMvq6vPLRs3wQtObDiWh9eNN1BQkqTRjVmkysyPjLYvIvYDvg08kSKZ+iTwzszc2tYIJUnqI/cteYBLv3dl1WE8zuydpnLy8cdUHUbfqiCn+jxFkepY4DMj9h1Vbr85Th8XA+8r+xhp1D4i4ljgHcCrM3PziH1TgQ0WrqoxLdZzzNxNdbWdv2Dl+I0kSWqzeuakepyIeA7wFYoh3FspEql/b2dgkiT1o/WbtrJl1ryqw3ic5SsWVh3CQOpUTpWZV0TET4GXRMTbhkY7RcR2FHNcXZOZV5SPTQI+V8bw6sxcXfZxW0RcDLw6InbNzOGX9Z0OLAAuGvH7PJOisHX6yBFWEfEE4J8pRlhJkiQ9zjaNPiEi3gZ8n2J549UUcyVYoJIkSWpAF3KqcygmRz8/ClOAT1HMI3XWsHaHA2cDLwROGdHHO4C7gH+LiMllPx8G9qEoRP1+pcKIOIXiEsKnAL+KiNvL2x0RcS9FUetWR1FJkqTR1D2SqvyW7VPAGymGoi8EXpSZt3YoNkmdtF/j80yodfvPmT5+I0l9rVs5VWYuLC+9+wRwE0XB6irgiMxcNqzprcB8YAbF6oPD+1gZEcdTrNJ3A7Cp7Ouw4RO6l22+A0zmsSv/jeRqHR1w59od2W7f3hihedwBs8dvJEnSKOoqUkXELODrwLMokqlrgJdm5lhLDkvqZSe+p+oIBtJzDtm16hAkVajbOVVZSHrlOG3WAUePsX85RUFtrD6uBqY0EaLa4L9X7M6suSe0tc9G5s8bPqfdO04+sK1xSJIGy7hFqoh4CvAtYF+KZOoS4A2ZOebSHRFxfWa69qwkSRLmVJpYGpk/zzntJEntMuacVBHxUuBnFMlUAn+bma+pI5maSe3liiX1iotfUdzUVZ+7ZiGfu8ZkXho05lTqpPP2+h0H331J1WEAcM5nruOcz1xXdRiSpAlqvJFUXy+3AawCTo6Ik8d5zmTgEGCHFmOT1Emb1o/fRm23aYvzBUsDypxKHTN5m61ss3Vz1WEAsH7TlqpDkCRNYOMVqQJYBrwZeLjOPqcCzwb+soW4JEmS+ok5lSRJ0jjqmTj9zMz8UYP9XhERr2omIEmSpD5lTiVJkjSGMeekAu5rIpka8vdNPk+SJKnfmFNJkiSNY7yRVG9ttuPMvLDZ50bELsBHgBMohsf/Bnh3Zt5f5/O3Bd4DvI5igtKHgP8CPpCZ9zUbl9RXDjql6ggG0iG77Vh1CJKqUUlOpcFwy5qdmTzvwKrDAODkJ86tOgRJ0gQ2ZpEqM7/brUCGRMRc4IfAfODIzNwcEecD10XE8Zl59zjPD+AbwIuA5cCjwG7AucBpZR93dvSXkCaC495RdQQD6VkHzqk6BEkVqCKn0uD4yUO7stvsZ1YdBgDnnbB/1SFIkiaw8S73q8KFwF7A2zNzaJmSD1KMqLqoLEKN5QyK0VNHZeYcYBfgpRSTlM4BPt2RqCVJkiRJktS0eiZO75qIOAElXttcAAAgAElEQVR4MfCFzFw79HhmboqIb1EMlT8V+N4Y3ZwGPDczl5XPTeBbEfE24BLgpIjYKTMf6dTvMZHddfvNFG9Tb1l0x80cOfugqsPoL599YbE99/Jq4xgwF/50AQBvetZ+FUciSeoXf7rPncxdeBG3zTunkte/5fY7ubS8//9uXAfAm582rWbb2TtN5eTjj+lSZJKkiaanilTA6eX2+hr7rqUoUp3D2EWqfx8qUI3wVeBzwOTyphq22bCaI2dvrDqMx1l44+qqQ5AkSVINqzdsYcuseQDk5OLLmKGfR1q+YmHX4pIkTTy9VqR6frldVGPfgnJ73FgdZOY1ozy+KSIeBjZl5oqmI5QkSZIkSVLb9cycVOVcU/uWPy6u0WRVud0zIrZvov9ZwGyK0VSSJEmSJEnqIT1TpAJmApPK+2tq7F877P6MJvp/FbAC+N9NPFeSJEmSJEkd1EuX+00ddr/WpEjDY93QSMcRMQ14L/CWzHx4jHbnAecB7LPPPo28hDTxHPrSqiMYSE/Zc+eqQ5Ak9ZkbHtmFI/d/UtVhAJ7nJEmt6aUi1cph97ersX96ud0CjFpoGsXHgC9l5jfGapSZFwAXABx11FHZ4GtIE8vT31R1BAPpGfvNqjoESVKf+dnKOew98+iqwwA8z0mSWtMzl/tl5lr+MBfVnBpNZpfbezKz7gJSRJwB7AL8dWsRSn1m47ripq7auHkrGzdvrToMSVIfmRxb2WbrpqrDADzPSZJa0zNFqtKV5faAGvv2K7c/qLeziDgJeDlwbiOFLWkgXPLK4qauuujni7jo54sqjkKS1E/O2/t3HHz3F6sOA/A8J0lqTa8VqT5fbo+tse+ocvvNejqKiGOBdwCvyczNI/ZNLVcTlCRJkiRJUg/oqSJVZl4B/BR4SUT8fl6q8v5LgWvKNkTEpIj4QkR8NyJ2HN5PRDyT4vK+szNzw4h9TwC+1NFfRJIkSZIkSQ3ppYnTh5wDXAOcHxHvBiYDnwLWA2cNa3c4cHZ5/xTgawARcQrwdWA58KthA6YCmAbsCfx9lZf/3XzHXWx94NGqXn5M9z6wtOoQarr3gaX88uY7qw6jpltXbc+Rz686CkmSJEmSJraeK1Jl5sLyUr1PADdRrOZ3FXBEZi4b1vRWYD4wA7gaICKOB75DUdiazugu7kDodVuzfhNb95g9fsMKbNh0R9Uh1LRh0xa2Tu/N92zN0pXjN5IkSZIkSWPquSIVQGYuAsac0Tkz1wFHj3jsamBK5yKT+shhZ1YdwUA6Yp9dqg5BktRnrls1i2MOeFrVYQCe5yRJrenJIpWkLjj8rPHbqO2O3NfkXZLUXr9cNYv9dzms6jAAz3OSpNb01MTpkrpo7Yripq5au2EzazdsHr+hJEl1mj5pM9tuXld1GIDnOUlSayxSSYPqK68tbuqqL153D1+87p6qw5Ak9ZHX7bmAA+/9atVhAJ7nJEmtsUglSZIkSZKkylmkkiRJkiRJUuUsUkmSJEmSJKlyFqkkSZIkSZJUuW2rDkCa6JYvXsD137+k6jAeZ9IOczns+OeN3uDo13cvGP3eMfNmVh2CJKnP/Ozh2TzzoCOrDgPwPCdJao1FKqlF2219lCNnb6w6jMe5fvmDYzd48iu6E4ge46l7zag6BElSn7lh9UwO2fnQqsMAPM9JklpjkUoaVKvuK7Y771VtHANm5bqioDlj2pSKI5Ek9YsZ225kyqZVbJy8c9WhjHueu+X2O7m0jn5m7zSVk48/po2RSZImAotU0qD6xpuL7bmXVxvHgPnq9UVx8E3P2q/iSCRJ/eKsPRYx977LuG3eOVWHMu55bvWGLWyZNW/cfpavWNjWuCRJE4MTp0uSJEmSJKlyjqSSJEmSuuDmO+5i6wOP1tV2xcpVHY5GkqTeY5FKkiRJ6oI16zexdY/ZdbXdvHlrh6ORJKn3eLmfJEmSJEmSKudIKmlQPfNtVUcwkI4/oL5v0CVJqtdPHprLsw45uuowAM9zkqTWWKSSBtXBp1YdwUB64u47VR2CVFO9y8JXwaXomxcRuwAfAU4AAvgN8O7MvL+BPqYC7wdeAmwBFgN/kZl3jPGcKcDrgPcCJ2fmoiZ/BdXhljUzeMqOB1cdBuB5TpLUGotU0qBa/ttiO/vAauMYMMtWbwBgzo7bVRyJ9Fj1LgtfBZeib05EzAV+CMwHjszMzRFxPnBdRByfmXfX0cd04NvAJuDYzFwbEeeVfZyUmb8e0T6ANwNvAo5o86+kUcyZsp6pG5azfrvqRzF5npMktcIildSiFQ+v5Jc331l1GI9z66rtOfL5YzT4zjuL7bmXdyUeFS67YTEAb3rWfhVHImkAXAjsRVFc2lw+9kHgtcBFEfHszMxx+jgfOBGYl5lrATLzgoh4A/DliHhaZq4fapyZGRFfAD4DLAJ2b+tvpJpetds9zF1yObfNO6fqUDzPSZJaYpFKatHmLcnW6dV/cznSmqUrqw5BklSRiDgBeDHwhaHiEkBmboqIbwFvBU4FvjdGH/uV7a7JzHtH7P4a8HHg9cCnhu8Yer2IWIhFKkmS1ABX95MkSeo/p5fb62vsu7bcjjfs5hUUX2g228emcfqXJEl6DItUkiRJ/Wfogu9FNfYtKLfHtaGPIyJi+4YikyRJGoVFKkmSpD5STl6+b/nj4hpNVpXbPccpMA3NpD9WH9sCT2g0RkmSpFqck0oaVCe8u+oIBtKzD55bdQiS+t9MYFJ5f02N/WuH3Z8BPDpKP3Ma6KMl5YqB5wHss88+rXY3cP57+W6c9MRnVB0G4HlOktQai1TSoNr/2VVHMJAOmLtD1SFI6n9Th93fWGP/8PxvQx39tNJHXTLzAuACgKOOOmq8FQc1wp3rduKIHXpjNT3Pc5KkVlikkgbV/TcV292fWm0cA2bJymLAwh4znMJFUscMX951uxr7p5fbLcDD4/Qze5w+AJY3FJ3abo/t1jHt0QdYt/1ubetz3YolLJ9/WX1tFy8AXgB4npMktcYilTSovv++Ynvu5dXGMWAu/839ALzpWb3xjbek/pOZayNiMbAnxSV7t41oMrvc3pOZY41auqNsO6fGvqE+1gNLWwhXbfCyXe9j7gNXcNu88RZsrN+0WM8xc+tboHHhLat/f9/znCSpFU6cLkmS1H+uLLcH1Ng3VD34QRv6uDIzW77cT5IkCRxJJUk9b93i21k+v9aUMNUbfomH6tPIJTTd5LHsO58HzgSOBT4zYt9R5fab4/RxMfC+so+R6u1D6rgfXX0tyx9ZX1fb2TtN5eTjj+lwRJKkZlmkkqQeN23r6rovuei24Zd4qD6NXELTTR7L/pKZV0TET4GXRMTbhkY7RcR2wEuBazLzivKxScDngF2AV2fm6rKP2yLiYuDVEbFrZg6/rO90YAFw0RhhDI3YnzRGG6llyx9Zz5ZZ8+pru2Jhh6ORJLXCIpUkSVJ/Oge4Bjg/It4NTAY+RTGP1FnD2h0OnF3ePwX42rB97wCeDvxbRJwFbAY+BOwDPDczaw5fiYjtgX3LHw8F7mrD76MBcsvtd3JpnW1vvvN3PPHY+opUkqTeZpFKGlQnf6DqCAbSHz1p16pDkDQgMnNhRBwLfAK4iWI1v6uAIzJz2bCmtwLzgRnA1SP6WBkRxwMfA24ANpV9HZaZi2q9bkR8HjiVP0yu/rWIuBN4Xmbe36ZfT8NcvmwPnnvocVWHAbTvPLd6w5a6R0eteXTk2gCSpInKIpU0qPZxPoYq7Dtr+viNJKlNykLSK8dpsw44eoz9y4E3NvCar623rdpj0aM7sGba3lWHAXiekyS1xiKV1KeWL17A9d+/ZNT901cXV16s3XH/boX0e5N2mMthxz+v66/bC+5esRYwiZcktc8Ttl/DDuvu7YlClec5SVIrLFJJfWq7rY9y5OwxVoS7s1xdbN7buxPQMNcvf7Drr9krfnBrMe/wm5613zgtJUmqzwvnLGHu0v/htnnnVB2K5zlJUku2Gb+JJEmSJEmS1FkWqSRJkiRJklQ5i1SSJEmSJEmqnEUqSZIkSZIkVc6J06VBdejLqo5gIL3wKbtXHYIkqc98c+lePP/JJ1QdBuB5TpLUGotU0qDaea+qIxhIe8zYvuoQJEl9ZsmGaazbfreqwwA8z0mSWmORSupTKx5eyS9vvnPU/Ts9ei8Aj2y/d7dC+r1bV23Pkc/v+sv2hN89uAaAA+buUHEkkqR+cdC0R9hpzQIe2WG/qkPxPCdJaolFKj3GeIWNqqxYuarqECaczVuSrdNnj7p/9wcvB2Dl7MO7FdLvrVm6suuv2St+fMeDgMm7JKl9njf7AeYu+2lPFKk8z0mSWmGRSo8xXmGjKps3b606BEk1rFuxhOXzL6s6jMfZ8PAS4ElVhzGh9OqxBNiycRO84MSqw5AkSVKHWaSSJDVtWqznmLmbqg7jcRbm+qpDmHB69VgCzF8wuKMvJUmSBsk2VQcgSZIkSZIkWaSSJEmSJElS5bzcTxpQC/d4YdUhDKSXHrZn1SFIkvrMVx7Yhxc+9aSqwwA8z0mSWmORShpQ67frvQnyq7bkjvlMmnJjR18jyu3yBp7jJOCSpLEs2zi1Z87rc3bcruoQJEkTmEUqaUDNWH0HACt3PLjiSHrHlI0rOWqvGR19jetXFktyHzljTd3PcRJwSdJYDt1hJTNW39ET5/Tb7n8EgCfuvlPFkUiSJiKLVNKA2n35LwCLVN323aUzgcaKVJIkjeWkmQ8yd/kveuKcfvXvirHCFqkkSc1w4nRJkiRJkiRVziKVJEmSJEmSKmeRSpIkSZIkSZWzSCVJkiRJkqTKOXG6NKDu2uulVYcwkP503pKqQ5Ak9ZlLljyBFx92cmWvv27FEpbPvwyA506eBMDy+TfVbrt4AfCCboUmSZpgLFJJA2rj5J2rDmEgzZ6yueoQJEl9ZuXmKZWe16fFeo6Zu6n8adOYbRfesrrzAY3hltvv5NI6287eaSonH39MR+ORJD2WRSppQM1cdQsAD+18aMWRDJZrHtoRgGfOrDZJlyT1j8N2fIiZq27piXN6r5/nVm/YwpZZ8+pqu3zFwg5HI0kaySKVNKB2fWg+YJGq2/572S5A7ybvkqSJ57hdljP3ofk9cU7vp/NcvaOuHHElSe1jkUqSJEmSRqh31JUjriSpfVzdT5IkSZIkSZWzSCVJkiRJkqTKWaSSJEmSJElS5ZyTShpQv937lVWHMJD+fP/FVYcgSeozn1u8Hy87/I+qDgPwPCdJao1FKmlAbd52WtUhDKSdtt1SdQiSpD6zdsu2PXNe9zw3th9dfS3LH1lfV9t77lnIPvuMP3G7qwtK6icWqaQBNfvhGwBYvsthFUcyWH6yfGcATpq9quJIJEn94uidVzD74Rt64pzueW5syx9ZX9eKgQBLbryNPQ93dUFJg8UilTSg5qy8EbBI1W1XrjB5lyS119N3XsGclTf2xDl9vPPcuhVLWD7/snH7Wbd4AfCCdoYmSZoALFJJkiRJ6oppsZ5j5m4at93CW1Z3IZr2uOX2O7m0zrY33/k7nnhsfSOpqtbIpYleciipXSxSSeq6+5Y8wKXfu7LqMB7nvvuXctR+M6oOQ5IkTSCrN2yp+xK+NY/e1uFo2qeRSxO95FBSu1ikktR16zdtrTvp6ab1G53sVZKkXlDvZYHgpYGNjORyxJOkXmeRSpIkSVJPqfeyQJhYlwZ2QiMjuRzxJKnXWaSSBtQd+55ZdQgD6a8OvLfqECRJfeaCew/glUeeWnUYQDXnOUddSVL/6MkiVUTsAnwEOAEI4DfAuzPz/gb6mAq8H3gJsAVYDPxFZt7R/oiliWfrNpOrDmEgbbdNVh2CpAFSRU5lDtZ9m3KbnjmvV3Gec9TVxOFk7JLG03NFqoiYC/wQmA8cmZmbI+J84LqIOD4z766jj+nAt4FNwLGZuTYiziv7OCkzf93J30GaCOY+9EsAHpx5dMWRDJYrHiwmZj9l7sqKI5HU76rIqczBqnHcjGXMfeiXPXFO9zw3mOqdF6tY3fB5dfV55c+uqLSgZUFNqkbPFamAC4G9KBKbzeVjHwReC1wUEc/OzPG+ojkfOBGYl5lrATLzgoh4A/DliHhaZtb3iSP1qVmrbgUsUnXbLx7eCTB5l9QVVeRU5mAVOGynh5m16taeOKd7nuttjUyyXhSU6pvrqt55sRpZ3bDqubZc3VCqRk8VqSLiBODFwBeGEhuAzNwUEd8C3gqcCnxvjD72K9tdk5kjL4r/GvBx4PXAp9ocviRJUk+oIqcyB5N6XyOFn0YKSoPOFRal9tmm6gBGOL3cXl9j37Xl9pxx+ngFRfGtlT4kSZImsipyKnMwSQNpqPhXz63eSwilQdVTI6mA55fbRTX2LSi3x7WhjyMiYvvMfLSh6CRJkiaGKnIqczD1PFcC7E+NjGS6556F7LPP+KPJGrncsRH1xtrIiKtOzZ9Vb7+ODuuMQZ0XrWeKVBERwL7lj4trNFlVbvccJ7kZ+iQZq49tgScAjmGVJEl9pcKcyhxMPc+VAPtTI5cxLrnxNvY8vL3zZzWi3lgbmeeqU/Nn1dvvRJqTayIVfgZ1XrQYf77M7oiIWcDy8scnZubtI/bvB9xV/rjHaEsnR8RqYAfg1Mz8/oh921AshQzwzMz8+Yj95wHnlT8eDHRqqeTZ/OF3VXf4nneX73d3+X53l+9393XyPd83M+d0qO9KVJVTmYOpzTxWE4vHa+LwWE0c/XysRs2/emYkFTB12P2NNfYPj3VDHf003EdmXgBcMEbfbRER8zPzqE6/jv7A97y7fL+7y/e7u3y/u8/3vGFV5VTmYGobj9XE4vGaODxWE8egHqtemjh9+Dq129XYP73cbgEerqOfsfqA/q1ISpKkwVZVTmUOJkmSWtIzRapyeeShOQxqDfuaXW7vybGvURwaHj5WH+uBpQ0HKUmS1OMqzKnMwSRJUkt6pkhVurLcHlBj337l9gdt6OPKzBxreHundXw4ux7H97y7fL+7y/e7u3y/u8/3vHFV5FTmYGonj9XE4vGaODxWE8dAHqteK1J9vtweW2Pf0LWY3xynj4uBbLGPjirnXVAX+Z53l+93d/l+d5fvd/f5njelipzKHExt47GaWDxeE4fHauIY1GPVM6v7DYmIq4BDgL2HvmmLiO2A+4A7M/O48rFJwOeAXYBXZ+bqYX18Hng1sFdmLh32+E0UcyIcmpn1rTspSZI0AVWRU5mDSZKkVvTaSCqAcygm8jw/ClOAT1HMYXDWsHaHA2cDLwROGdHHOyiWVv63iJhc9vNhYB/gdJMjSZI0AKrIqczBJElS03quSJWZCymGie8D3ARcB6wFjsjMRcOa3grMB34HXD2ij5XA8cAjwA3Ar4F5wGGZOb/Dv4IkSVLlqsipzMEkSVIreu5yv34WEbsAHwFOAAL4DfDuzLy/0sD6WETsAPwJ8BeZuVvV8fSriJgOfAh4FbA7cD/FvCMfzsyxljdXk8rLc94KvIViQuKlwEXA/8rMzVXGNigi4j+B12dmVB1Lv4qIjwN/OeLhBJ6cmbdWEJImKHOw3lPv37fHrrvqzZ0jYi/g74GnAJOAq4C/zsxV7Wiv+jTyv05EfAV45YiH1wH7ZOaKEW09Xm3S6P9JjX7m9eNnZM+NpOpXETGXYtWb6cCRmflU4G7guojYt9Lg+lBETI2Iv6D4BvfjwK4Vh9S3ImJ74CfAu4EpwCaKb+3/DLg2ImotRa7WfRL4J2AHiuRhX+AD5ePqsIh4FfD6quPoZxExk6IIu2XE7bsWqNQIc7DeU+/ft8euexrJnSPiIODnwMLMPAw4DNgJ+GlEzGi1vcbX6P86EXEI8DIe/zf3mRoFKo9XmzT6f1Kjn3n9+hnpSKouiYhvAc+imLx0bfnYZGAhxfD6Z6cHo20iYhtgO2AaRbV6sqMdOiMi3gf8EfDmzLyzHOFzLkWxZDvgs5npP/NtFBGnAm8A/jQzl0bEjsCngTMpvoXecyJ/e9LrypP+/wAzgRl+tnRGRHwEeCQz/7HqWDSxmYP1nnr/vj123VNv7ly2mw9sDzxp6P2PiFnAPcDXM/O1zbZXfRr9X6dc1OLbmfm1Ovr1eLVJo/8nNfqZ16+fkY6k6oKIOAF4McW3Q2uHHs/MTcC3gBOBUysKry9l5tbMfLT8ZmBZ1fH0uWcAL8jMOwEyc0tm/gfFsFOAl1QWWf+aRTEB8VKAciWuNwAPUQzz3b3C2PpamVxcArwLcMh7h0TEThRF109XHYsmNnOw3lPv37fHrrsayJ3Pplhs4avD//ktn/cT4DURcWgL7VWHRv7XiYh5FKOhvlFH1x6v9qr7/6RGP/P6+TPSIlV3nF5ur6+x79pye06XYhlEm6oOoF9FRAAfy8xHa+z+Yrmd0sWQBkJmXpyZW0Y8tp7iG5MHgFsqCWwwfBD4VWZ+q+pA+tzbgNnAZyLijRGxc9UBacIyB+s99f59e+yqM1buXM9xGT7SptH2atx4/+u8D5gLXBQRry4vQRuNx6tNmvg/qdHPvL79jLRI1R3PL7eLauxbUG6P604oUvtk4eej7F5abm/sVjyDrFxafn+KSwA3VB1PPyq/sXoBj5/oV20UEdOAdwI7U0zweiGwKCLeXmlgmqjMwXpIg3/fHrseU+Yazy5/XFSjyWOOS6Pt1X7lBOjnUMxZdTZFceSuiDi9RluPVxs18X9So595ffsZaZGqw8oK6tCkZYtrNBm6XGTPcara0kRzSLn9XJVBDJC/Az6QmfUM5VaDypVTPg2caRGw46YDf17evg6sBWYA/xoRF1QZmCYWc7CeVNfft8euZ+1GMVcRjH1cDmyyvdpvW+BNwHuAy4GNFNNCfDki3j+ircerex7zf1Kjn3n9/hlpkarzZlKsvAWwpsb+tcPuu1qC+skZwO3ARVUH0q8iYruIeE5EfJ9idM97I+K0quPqU/9BMWT7zqoD6XeZuSwzL8nMf8nMP6ZIhr9S7n5TRLgQg+plDtZjGvj79tj1puErkY11XIaOSaPt1WaZuSgzP5+Zn8jM04AnUyz+AvB3EXHysOYer+4Z+X9So595ff0ZaZGq86YOu7+xxv5th93323n1hYjYjWIi79eVk/epM3YD9qJYbWUtxZK234yI51QaVZ+JiDcDazPz81XHMojKlSrPAD5bPvSeCsPRxGIO1uPG+Pv22PWmeo/L0DFptL06LDN/SzGZ9g/Kh4ZPYeDx6oJR/k9q9DOvrz8jLVJ13sph97ersX96ud0CPNz5cKSu+DTwN5l57bgt1bTMvLv8duw8im+jr6c4KX242sj6R0Q8CfgT4K1VxzLIyhWG3k6xMMDBETHhvhVUJczBJoBR/r49dr2p3uOyvMn26oLM3Ai8HlhPsfrcEI9Xd9T6P6nRz7y+/oy0SNVh5XKQQ9eJzqnRZHa5vWf4Mp/SRBURfwXcnJkuHd9F5bfRQ6utHFZlLH3mXcDTgNURkcNvlHMBDHvsCRXG2ffK8+nQajjbjtVWAnOwiWTk37fHrmf9juKfXhj7uCxqsr26JDMXA9/jsedTj1eHjfZ/UqOfef3+GWmRqjuuLLcH1Ni3X7n9QY190oQSEWcCe2Xm31QdyyDKzFsprm+vNexXzVkG3DHKbXPZZuhnL23tvN8BSzPTb3FVL3OwiWPk37fHrseUC4cMjf4Y97g02l5d9zvglqEfPF6dVcf/SY1+5vXtZ6RFqu4Ymsfk2Br7jiq33+xSLFJHRMRLgZMphuyP3Det+xENrA3Aj6sOol9k5vsy85BaN8pvsIY9Vmt1FbXX7sBnqg5CE4o52MQx8u/bY9ebxjsuCVzWQnt1z+7Af454zOPVAXX+n9ToZ17ffkbGBBz9NSFFxFUUS03uPbR8eURsB9wH3JmZx1UZXz+LiHuAvSmGj28Zr70aFxEvB14KnDvyPY6IpwLvzszX1nyy2iYi5gE3Acdn5o1Vx9PvImIRsG9mRtWxDIKI2An4BvCyzFxddTyaOMzBet9of98eu2qMlTuX7//NwLrMfNqwx3cF7gW+mplnNdtejWvmf52I2Bu4ADht+HM8Xu3XyP9JjX7m9etnpCOpuuccimt8z4/CFOBTFBPW+YfeIRExmz9ck3tolbH0q4h4HcXy0ccCt0TE7eXtjohYAtwI/LTKGPtJREyKiO9GxPcj4tSIiPLx/Si+UTnLApUmsoj4RkQsjohzImKb8rF9gfOB11ugUhPMwXpEE3/fHrsuGy93Lv8RPhPYLyL+rHzODhQrNN4OvK2V9mrMeMcrIn5V5uQvGvbYk4H3AmeOLJp4vNqrif+TGv3M68vPSEdSdVE5qe4nKKqdW4CrgP+VmcsqDKtvRcQPKYY67lw+9Cjw2+HfCqg1EXE68CVgrJEkG4DdMnPlGG3UgIj4d+BVwExgAfBr4C7gk15y1j2OpOqMiHgV8CGK+RQWAf8DzAe+MGypZqkh5mC9oZm/b49d9zSSO0fE04B/AHYrH/oO8A+ZuWaUvhtqr/HVc7wi4m3AnwN7AbdSzGN0DcWIqFELAR6v1jX7f1Kjn3n9+BlpkUqSJEmSJEmV83I/SZIkSZIkVc4ilSRJkiRJkipnkUqSJEmSJEmVs0glSZIkSZKkylmkkiRJkiRJUuUsUkmSJEmSJKlyFqkkSZIkSZJUOYtUkiRJkiRJqpxFKkkDLyLmRcS/RMQjHeh7x4h4S0TcEBEfanf/kiRJ44nCqRHxg4j4bNXxtENEHBwR/x4Rv46IhyLiqxGxX9VxdUJEbBsRr46I6yLib6qOR+oki1SSelpEvC0iFkZEjrjdGxHvb0P/rwL+E/gzYMeWA35s33OBD5e3p7Wzb0mS1D0R8aIy9xjKQ7ZGxMvHaP/BiLhvWPtVEfHdbsY8LJYA/g/waeB5QFQRRztFxJHAl4C/yszDgYuBPwZ+HBHbDGs3o0YeuSkivlLuf2tErB6x/+GI+PiI13E3qLsAACAASURBVPvnEe0ejIjtu/S7zqA4dp8Eju7Ga0pVskglqadl5iczcx7wj8MefkVm7p2ZH21D/18BngusbbWvGn0/mJnvokiiJEnSBJWZ38nMvYE/ApZTFHo+HxE1v4TKzA8DewNfABYA+2Tmad2Kd0QsmZnvAN5Txet3yAXAtZm5uvz5L4DLgPuAHGqUmSvLPPLvhz333Mx8Vbn/U8A84M5h+w/NzMe8V5n5/9u78/iYrv4P4J+TTPZJZF+ECCGCWOOHqqWqtiqtaqtUaa2l9WiLojytWmJpaVGl1FK01FJUqaX29rHVniCkkiD7Htkzk/P7486NEUkEIQmf9+uV103uemYm994z33vO93wEoDYAHYD5UkpXKWVWGb+mIhlewxAA3zyO4xGVNwapiKiy2GeY5kgpfy3LHUsp8wGklOU+CynzboRERET0+Ekp9wIYZvjTBsA2IYRLMetKAH8BOCmlTH1MRSxJYnkXoCwIIeoCaAYgWZ0npcyTUvaSUj5reN8Lm47b9TF74wVSygQAE41mWRRz6HwA2QD++6Blf0jx5XRcoseKQSoiqiyyC03Lmu4R7RdQKjVERET0ZEiG8nBLAqgBYLMQwqyYdXPx6Oou9+tR1nUeJz/DNK+0G0gpMwH8Yvjz9SJW+Q1AnOH3HsXs5mUA24xabz1uT8rnR1QiBqmIiIiIiIjuzzkAnxt+bwvgu3Isy9NGbQlVVIupkvxomLYVQtQwXiCl1AHYaPizXzHb9wPw030ek4juE4NURPTEEkKYCyE+FkL8I4Q4KYSIFkIcEEJ0uMd23YUQ54QQWYZtuxWzXoAQYp0Q4ogQIlEIEWRIwFnpE5ISERFRyaSU03A7aDFECPGfktY3JN9OM0q+7W2YX08IEW40/x3DfD8hxGQhxF5D0m5vIURHIcRiQzLwOCHEPCGEmRDCXQgxRwixz7DuISGETwllMRdCzDbsI1UI8ZMQwqOI9UwMoxT/YRhFL0UIscOQuNx4vReEEPsNCeNdhRC7DfsdcK/3UQhhJ4SYLoQ4ajjGTSHEj4XLL4ToL4T4B8AUw6xhhnraP0KI9vc6jpTybwBXoeQTe7uIVbwN05ZCCN9Cx/YEUA/A3mJeQwshxCZDnfCaEOK8EGKcEMK80HpaIcRYIUSUEKKauJ2QP8j4/RfKyIXrhRAhhjrpTgB1ijl2VyHEX0KIU0bJ3RPu9X4QVVQMUhHRk2wNgFkABkop/w/KiCh+AH43VDbuIoToB2ATADsAZgACDOv3KbReLwCfARglpWwLpWJzFcAiMLElERHR02IwgP8Zfp8nhHihuBUNybf9AOQUmn9JSukNYH2hTSKg1CmaANACeA9ArpRyhGE/wQA+gtJCaBiAaVLKjlAGhGmL2y2DCjMBsAXAEAB6KHWefgCOCiGc1ZUMD91+BmAK4EXDKHodALQA8LcQ4hkhRBUhxG8AdhuWmRqO+6xhv0OLez8Mx3AHcAJK66h2hmN0BdARwFkhRBuj92mtlLI5lFGTAWCplLK54edQSccxstowvSNIZcgr1hrARcOs/oW26wdgo6HFVeHX0A/AHgDfGuqEPlA+kzkA9gohrA3rdQdwEsCXADyg1DF/AFANQAMoSflheM2noXz+9aSUjaF0VRxXxLH/D8BKAP2llAEA3MHWXlTJMUhFRE8kQyXrDQCRUspgAJBS3gSwDYA1gJbFbPosgKqGkWBqATgO5Vr5nRDCxmjfKwEMNSTbhCE/wRTDPkYJIWo9itdFREREFYeUMgfAKwDCoARoNgghapewfhSA2GIWhxRaN0tKmQ7gX8OsNVLKI0bHXWqYbyGlnKrmSpJSHgdwCUDTYlpTdYESfHKRUnoAeBVAJpT8WsYjJw8DYCOlXKQmI5dSngGwFkpy8ZlSylQpZU+j7d6E8hCvDoC5uF03Ks4yKAGqj6WUeYZjBEEJ/mkBbBRCVLnHPu7HaijdBH2FEMZ1wTeh1BGXGf7uX6hl/FtQXvcdDPW9pVACZgcN5ZdSyrlQHnq2g/LAFFLKHQD8AdxQjwGlrtkVwAIoSfgdDdudklKONwzuAynljwA2F/F63gQQK6UMN6yXAWA4gKRSvh9EFQ6DVET0pEoBcBhKIkxjalJMbVEbSSnfl1ImG36/DqAvlCeejlCeTALK0zcrAL8JIY6pP1CehkUCiAJQvwxfCxEREVVQUsp4KMm20wA4QKkf2JW0yX0eQm15lVFovhrsKiqRtzqSn1sRy/6QUv5kFADZgttBpteMgjMjoQS6jhWq73SBUt+parTPCMP0gJTykJQyWko5Vkq5D8UQQjQE8BKAw1LKXONlUsrdUFo1uQN4p7h93C9D3e6A4U/jrohvQwlg/QwlQXlNKA8uIYRoAMBaSnmiiF1+CGWUxz+LWDbPMB0uhHAwHF8P5b0DgDlSygwp5W4p5WgpZYphf264nT/L2MEi5gkAjYUQU4Qheb8hUFWmI2ETPU4MUhHRE0lKqZNStpdSjgYAIUR7IcQKKEEnoJTXPyllGJQm7ACg5idoBSBFStmq0M//SSmrGX5+L8vXQ0RERBWXodV2Hyjd5+oBWCeEKKvvWsUFtUoaPVhdZl7COsYWG6aOAJwNXdQaAvipiPpOfUNdxzhvk94wjS7l8QCgp2EaX8zyg4Zp2/vYZ2msMkz7GHJz+QJwBXBQShkHYJdhudol8C0U34VOHQmwqNdwAkoLNXPc2YK/pPeqt2EaXMSynCLmLYUSpPwcQIgQYoQQwkpKOaGY8hJVeAxSEdETTQjRSwhxGkpT/Kl4sH76oYX+VitwJT0lJSIioqeIlHIXlBxRAPAigNnlWJz7YmhFbtxFzAFKK51ik6+XgepGxyrKdcPUuoyPuxlKYMcJQHcowai1apdG3M5b9YYQwhLKA87i6o/FvgZDq6kow5+lfQ1qcvTs0qwspbwMoDmAP6C0/voOwBUhRM8SNySqwBikIqInjhDCViiWQKlovCel/Ejtr/8A1CSZ6vbpUK6fLxVzfLuSRtQhIiKiJ5OUciGUQVQAYCyUhNuVhQ5KHSfRMAWAjmri78KEEM0e8niphqlXMcvVlkPhD3mcO0gpM6HkfQKULn9v4XZgClBSRSRDyZU1E0rOp8IPLFVl/RrUFnBOpVwfUsorUsoXobT03w8lEfuWkpL4E1VkDFIR0ZNoPJSWU8OhJBktKofA/fADkIXb+QZOG6bTiknm+TFKboJPRERET67RuJ0qoFMRy9X8S46F5psWmj42hpxJLgB+l1LmSylTAVyDEqiZWsT6FlBGG3wY6oh8LYQQrkUsdzFMtz7kcYqi5nx6GUCMlPKKusCQlP4Xw5+jUUTCdCPqa+hRzHIXKC3CzpSyXGo3v1alWVkIMcvwWUBKedwwumMglO/5JY6sSFRRMUhFRJWFSaFpkYQQz0Bpnq6OrFM4F4OlYWpqWF+gBEIIDyhDAgeqCdWhVGxyoIzIclAI0cKwrrkQYhSA/zPkslKVW6WTiIiIypwlALPiFhq6efWBkvi7KDGG6duGlt8aIcR7UEYlBpRuW8Y0hmnheoRahymqblTSsqK8A+WB3BSjeerogWOEEAsMoxtDCFEdSpe5/UUcr9j3pQi7AJw3bFNUQKUdlLxOhZOSq3U5i/s4VmGHoYzIKHBnKyqVOk+P2wGronwJJWdYD8P7UkAIURdKrqtAo66EQMnv1QrDdJg6qnQRjOu29lBaghmba5jqQFQJMUhFRJWF+jRNK4TwLGoFIUQXKMMH/wrgqGF2fyHEQCFEKyHEAtx+0tVSCPE+lFZSgDIaoPpEysbwuyuUStgaGA3JbBgZZgSU1lJNABwXQqRBGXXnv7j7yWKTQlMiIiKqvJ4D4CeEKLZLlqEl0ksAEopYvMMw/RBKwCoBQDMA6wzzJwghNhnSF9jidp6ihoX283+GaX0hhBrIgqEeoz6sa2S0/i0oQZeuQogXjdbvCqUVem8pZYjR+nMB7DX8PgpArBAiBUrLoHQp5Xqjdf0N0+fVlj33YhhdsA+UpOOThRAFrZGEEB8DqAHgbXUUQsN8ASXfFwC0VUe0u1+GoNFqKA8d7wpCSSmPArgCYI9h9Mbi9nMUwEQoAaeNQgh3QzmdoIz6/BNuB/vUz8bb8Ge3Ina5GMr/hxeULnsuhu1cAfQ3rNNaCOFlFMRaIIR41Wgfr0BprbcIRJWQuDOoS0RUsQghakCpuE0D0MAwOxnKUMfq6CjmUIZBdgIQJqWsZdj2Yyj5IMyhBK3+C8AOwHYoFawP1aGRDTf64VAqSzUB/AslcLXUMDRzUWXrYNhnC0NZ/gTwiZTyX8PyKgBO4nblEoZyvyKlPPvAbwoRERE9dkKIYVACEt6GWekAQqWUTUvY5lkogZb3jOZpAHwDJWF3OoBvAcyCMkJbBwBTpJQHDEGbH6C0xgGUwMNhAF0BBAGoi9utcmIBfGBYdypu5zTKB7BfStnJcOz6UAJOXaA0WAiHUueZIaW8VkT5zQGMAfAulKBRNICVhvV1QggtlK5stY02iwcwUkq5qfD+inmPqgL4AkrwKQ1K/esogNlSylij9V4G8D0AN6PNYwHclFI2L82xCh23JoBZUso+xSyfBOCalHJdUcsLrdsdSp2zAZRuktkAVkkpVxmtMwDA17jdzVNCCYQ1MLS+U9czgxI0HAylpdQ+KJ9RKpTPbp/hZxOUllzDDZvGQanfJgD4TEp58p5vAlEFxCAVERERERERERGVO3b3IyIiIiIiIiKicscgFRERERERERERlTsGqYiIiIiIiIiIqNwxSEVEREREREREROWOQSoiIiIiIiIiIip3DFIREREREREREVG5Y5CKiIiIiIiIiIjKHYNURERERERERERU7hikIiIiIiIiIiKicscgFRERERERERERlTsGqYiIiIiIiIiIqNwxSEVEREREREREROWOQSoiIiIiIiIiIip3DFIREREREREREVG5Y5CKiIiIiIiIiIjKHYNURERERERERERU7hikIiIiIiIiIiKicscgFRERERERERERlTsGqYiIiIiIiIiIqNwxSEVEREREREREROWOQSoiIiIiIiIiIip3DFIREREREREREVG5Y5CKiIiIiIiIiIjKHYNURERERERERERU7hikIiIiIiIiIiKicscgFRERERERERERlTsGqYiIiIiIiIiIqNwxSEVEREREREREROWOQSoiIiIiIiIiIip3DFIREREREREREVG5Y5CKiIiIiIiIiIjKHYNURERERERERERU7hikIiIiIiIiIiKicscgFRERERERERERlTsGqYiIiIiIiIiIqNwxSEVEREREREREROWOQSoiIiIiIiIiIip3mvIuAD09Tp06ZQ6gr5mZ2YsAGkkprcq7TERERERERETGhBBZAM7n5eXtBLAuICAgt7zL9LQQUsryLgM9BU6dOuWg0WhW2dnZNXR0dMy1sbHJNDU1zRdClHfRiIiIiIiIiAAAUkro9XqTjIwM66SkJPO0tLQLOp1uYEBAQEp5l+1pwO5+9FiYmJgMcHR0bOjt7Z1UpUqVdI1GwwAVERERERERVShCCGg0mvwqVaqke3t7Jzk4ODQyMTEZUN7lelowSEWPhampaX9nZ+d0BqaIiIiIiIioMhBCwMXF5Zapqenb5V2WpwWDVPRYSCmdLS0t2Y+XiIiIiIiIKg1LS8tcKaVzeZfjacEgFT0ugq2oiIiIiIiIqDIxfI/ll9nHhEEqIiIiIiIiIiIqdwxSERERERERERFRuWOQioiIiIiIiIiIyp2mvAtARFQRfffdd45jx46tMXr06OiZM2fGPMy+3nrrLa/ffvvN8aeffvq3Z8+et8qqjERE9Ohs23PQNi4ty6y8y/GgXO2s8l7u/NwTd885deqUZefOnev6+/tnHDp0KPRh9lWW93oqP0f3brXNT4uptOeqiZ173jOdXnnizlWiB8UgFVEF9eGHH1ZdtWqVa2pqqikAaDQaeenSpQu1a9fOu9e2er0ePj4+/hERERYAYGdnp2/Xrl3q9u3bwx51uR/GsmXLHIYNG1bLysoqv1q1ajnm5uYSAIKDg60BwMfHJ9vS0jJfp9OJyMhI8/T0dNPXX389YcOGDRFlXZaYmBizrKwsk8jISPOH3VdUVJR5enq6aUJCQoW55ur1esyZM8dl7dq1ztnZ2SaWlpb55ubmskOHDmktW7bMWLt2rWNF/3+h8sPrU/lenx7G4sWLHZcuXeqakpJiam1tnW9iYoK2bdumtW/fPn3ZsmXOf/7557/lXcaKIi4ty0y6+lbaXgdxcVfK7Ev7jRs3NF5eXo1NTU2ll5dXjrW1dT4AhIWFWWZmZpq4u7vnOjk56aSUiI+PN4uPjzerVq1azo0bN4LKqgyqlJQU09TUVE1UVJTFw+6rLO/1ZWnz5s12c+fOdYuKirKwsbHRSynRokWL9E6dOqWtWrXKedOmTWFVqlTJL+9yVhT5aTFmz7rnVtpz9e+YsguwVaRz9WHs27fPZsaMGR6hoaGWWq1Wr9frRbNmzTK6du2a+scff1QZP358bNOmTbPLu5z0aFTak5noSffNN99ExcbGnmvfvn0qAOh0OhEYGOhemm3XrFljr34BrFu3blZkZOS5iv4FEADS0tJMn3nmmVuRkZHnrly5cjEoKOhSUFDQJXX56tWrrwUFBV26fPnyxYSEhHNDhgyJTU9PN30UZZk6dWpsaGjo+VWrVl1/2H3t2bMnNDw8/PygQYOSy6JsD0uv16Nbt24+3377rfvSpUvD//333+Dg4OBLGzZsuHb9+nXzN998s3ZYWJjlwxwjPz8f+/btsymrMlPFwutT+V6fVCdPnrRMSkoqdV3u7bff9po4caLX9OnTb4aFhQUHBwdf2rVr19W8vDzRt2/f2mfPntU+bJn27t3L8/4JlJKSYuri4pJ35syZ4GvXrgWr//8NGjTIBIARI0bEBgUFXQoODr4UFxd3fvny5deys7MfyfeMjh07Zly/fv3cuXPnLj7svsryXl9WpkyZ4ta3b9/a7777bkJ4eHhQcHDwpb/++iukatWqeYMGDfL5888/7R/2GDxPn1wV6VxVpaWlmZw4ccKqtOt///33jl26dKnbsWPHtPDw8KCLFy9eOnXq1KWmTZtmfvDBB96//PKL88OWiedAxcYgFVEFZmFhIbt27ZpqYqKcquvWrXOOjo6+Z2ucefPmuavbBAQEpGu1WvloS1o2bt26ZTp//vzrDg4O93w6aGFhIZcsWXLTzs5O/6jK4+Pjk6e+jw/DzMwMNWrUuGcLk8fl22+/ddq7d6/9V199df3ZZ5/NUufXqVMnd9OmTeH9+/ePf9hjbNy4scqOHTuqPOx+qOLi9al4j+P6BACTJk3yTE5OLlUgbMuWLXZr1651+fTTTyO7d++ers739PTULVu27Ob48eMjH7Y8x48ft1q+fPlDf3mgiic1NdX0ww8/jG7YsGFOadYfNGhQcocOHVIfVXmqVq2qs7a2LpNrR1nd68vChQsXLKZPn+75zjvvxA0dOrTgwZajo2N+YGBgzOLFix86oB8dHa2ZMWOGx8PuhyqminauAsCCBQuc//nnn1IFqWJjY03HjBlTo2vXrimTJk2KU89NrVYrP/nkk/hNmzaFPuz5mpWVJSZOnFjtoXZCj1TFuCITUbGsra3z27Ztm2ppaZmfnZ1tMnv2bNeS1t++fbvt1atXrdq2bZsKKF+WHk9JH17Lli0zAgICSt1019TUFAMHDkx8lGV6Ev3+++/2AFCtWrUiA2dfffVVpIWFxQN3I0hISDAdP3589QfdnioPXp+K96ivT2vXrrW/nxYVW7durQIAVatWLfK8//zzz2NdXFweOJielZUlhg8fXkPKSvOR0n1wdXXV9e7d+76+yA4aNIj35/u0devWKnq9Xnh4eBR5Lg4aNCi5YcOGGQ9zjCFDhnhlZmY+0laeVH4q2rl6+fJl87lz55Y6KPrHH3/YZmRkmLi5uRV5DnTp0iX9hRdeSHmYMo0aNcozLi6u0uYwexowSEVUCTg5Oelef/31RABYuXKla2pqarHn7pw5c9xff/31RCcnJ93jK2HZ6NatW/r9Ph3p1q1b+r3XImN6vV4AwH//+9+qOTk5ovByNzc3fbNmzR6oEpyWlmby8ssv11K7c9GTj9enkrd5FGXZv3+/zfDhw2veT0BIPe9nz57tkZycfNcLsbS0lG3atEl7kPLk5OSIPn36eJ87d47dJ55Qvr6+uXXr1s29n226du3K+/N9Us/TZcuWuYaHhxf5Jbpjx44PdJ4CypfznTt3Ojzo9lTxVaRz9caNG5qePXvWTklJKXVOVp1OJwBg48aNTmfOnCky9UTnzp0fuOXXrFmzXJYvX+72oNvT48EgFVElMWnSpBhTU1OZlpZmOm/ePJei1jl69KjV0aNHbSdNmnTPEWq2bdtm27lzZ5+mTZv62draNmnYsGG9ZcuW3VVxWbNmjX1AQEDdpk2b+rm5uTXy8/OrP2fOnDuOf/LkScuPP/64ap06dRqMGTPGIzU11WTEiBGebm5ujWxsbJr27NmzZlpa2iO93uTk5Iivv/7a2dvb2//333+3PXDggLWPj08DDw+PhkePHrUCgMjISM3AgQOr+/v71/P19a3v6uraqHv37rWuXLlyR8LUpKQkk3nz5jk3a9bM77XXXvNW51+8eNF88uTJbg0bNqz32muveefk5IhPP/3UvXr16v5WVlZN27VrV+fGjRt33IivXr1qPm7cOI/q1av7L1iwwEmdf+DAAevhw4dXq1atWsMFCxY4RUZGavr161fDwcGhsa2tbZN33323el7e3Q+RkpKSTIYOHVrNx8enQa1atRqYmpoGCCEChBABvr6+9Rs2bFjv9OnTJeaTev7559MA4NChQ1UCAgL81PfH2LJly24Wte2KFSscOnToULthw4b1bG1tm7Ro0aLu1q1bbQGlJUXfvn29w8PDLQFg7dq1zv7+/vX8/f3r6XSVLiZB94HXp9I5fPiw9UsvvVQrICCgrr29fRNfX9+7ypufn48pU6a4+fv716tTp04DMzOzZkKIgK5du9YCgN27d2vHjh1b0FLxxRdfrOPv719vzJgxJT6p7tSpUxoABAUFWTdt2rT+rl277so/Vdx5v2XLFrtOnToVfB6NGjXyW7lyZcHnMXDgQK/z58/bAMCePXvs1fM+IiKCT6oJALB161bbVq1a+Y4ZM8YjMjJS06ZNmzq2trZNvv32WycAyM7OFur/vb+/fz0XF5dGLVu29N2+fbut8X7y8vKwbt26Kl26dPHx9vb2V+fHx8ebLliwwOm5556rrc5fuXKlg7+/fz1LS8tmfn5+9QvnSSzLez2gnLszZ850qVevXn1fX9/6FhYWzdT7s6enZ0N/f/96ixcvdizpferSpUsaAERHR5s3b968/qpVq+5qLfn1119HFZU0/ciRI9Y9evSoqV5f6tSp02DWrFku+fnKqmPGjPHYvXt3FUAZ8EF9rw8cOGBdUpno6RMeHm729ttve7Vq1crXzc2tUdWqVRsOHz68WuF75aZNm+wCAgLqNmjQoJ6NjU1TIUSAg4NDYwC4fv26pn///t5qgCowMNDT39+/3vPPP1+7pGN37tz5lpmZmbx165Zpu3bt/ObNm+es/g+rxowZk1BU0vTz589bvPbaa94tWrSo6+jo2Njb29t/woQJ7mp9Wh0wCABiY2PN1XNg3bp1TE9RwTBIRVRJ1K1bN7d79+7JALB48WK37Ozsu1rABAYGunfv3j35Xk9QAgMDXdauXeu0adOmsDNnzly+fPlykEajkcOGDav1xRdfFHTXmT17tsuAAQN8+vXrl3jmzJnLYWFhFxwdHfPGjx/vtXr1ansASE9PF7GxsWZBQUFWoaGhluHh4RYDBw6s0bp164z169eHtmjR4tb27dsdP/roI8+yfk9Uhw8ftm7evLnfxx9/XCMiIsLixo0bZv379/cJDw+3jImJMV+/fr1DamqqyTPPPON35MgRuyNHjoRcuXLl4tKlS8N27tzp0LNnz4IbZlJSkskXX3zh/s0337ifOXPGxrilQmhoqEVERIRFUFCQdVJSkqZfv341vLy8cn/66adrPXr0SDpy5IjdoEGDaqjrHz9+3Gru3Lmu3377rfvNmzcLWhZFRkZq8vLyxIkTJ7SRkZHmp0+fth41alS13r17J2/YsCHU29s7Z9WqVa6zZs26o+uU+hr2799f5fDhwyHXrl0L3rlzZ4hGo5EAMHz48LgLFy5catasWYldksaNGxffokWLW4BSUW3btm39N998s0ZYWFiJXyiHDx9e7fTp09a7du3698KFC5eOHz9+MS4uzuzVV1/1XbVqlb2VlZXcsWPHtfHjx0cBQP/+/RPUhJ0aTYUZ2JAeAV6f7m3lypUO06ZN8/jhhx8iTp06FXLt2rXz1apVyx0/frzX0KFDC3JjTJs2zfX333+3P3r0aMjVq1eDg4ODg+rWrVuQO65Lly7pp0+fvuzn55cJADt37rwaFBR0ae7cudElHX/gwIEp6mcUERFh0a1bt7ovvvhirfPnz5fY6nHq1Kmu69evd9i8eXPYmTNnLgcHBwcJITBo0KBaM2bMcAWA9evXR3zzzTcRANC5c+cU9byvSLn4qHwkJiaaPv/887V79+7te/z4cVu9Xi9eeeUVn9OnT2vT09NNV65c6QwAvXv3rjljxgzPVatWhQUFBV06duzYpWvXrlm+8cYbtY3vTYGBga4LFixw27Nnj31eXl7Bdeb8+fOWgPLwJScnR4wcOdIzLCzMfMmSJRGTJ0++GRISYtW3b1+f9PR0AZTtvV7Vp08f7ylTplRfsmRJ+JUrVy6GhIRc8PLyygGU/HtBQUGXRowYkVTS+/XMM89kffDBBzGG907z7rvv+rRq1cr30KFDJQaSVq9ebT9lyhSPpUuX3jh16lRIWFjYN6kPtwAAH7hJREFUeW9v7+yJEyd6DR48uDoAzJ07N3r79u2hANCgQYNM9Tzt0KFD5j0+RnqKnDt3zqJXr14+H330UdyxY8euREZGnn/rrbcSli5d6ta2bVtftQX+oUOHrEeMGOH9888/hwUHB1+Kjo4+17Nnz4L/by8vL92hQ4dC33zzzQQA+PTTTyODgoIu7d+/P7Sk43t5eemmTZt2AwDS09NNx4wZU6NRo0b1tm3bZlvSdrt379YOHz68xqxZsyJPnDgREhkZeb5169a3Zs+e7fnSSy/5AMAnn3wSf+bMmUsA4ObmlqueA3379n2kObno/jFIRRXKy9/+Vbfwz3cHQ10AICNHZ1LU8pV/hzkBQFxatqao5etPXHcAgIjEDLOilm87G1kFAC5GpVkUtXxPcIwtAJyKSLYqavmRq/E2AKBOH6VJkybFCCEQHx9v9t133zkZL7t8+bL5H3/84fDpp5+W2Erhn3/+sfzqq6+qrl27NsLOzi4fUBLnjhkzJgYAZs2a5ak+KVm+fLkLAPTo0SMNAKytreU777yTAAD79++3BZREhi+99NIttfl5QkKCZuPGjWFvv/12SocOHTK//PLLmwCwc+fOhx6Npjjt2rXLvHDhwqWAgIB0AFixYoXL//73v8sHDhy41L9///iRI0cmbNmyxe7GjRsWzZo1y1ATH7/yyiu3vL29s0NCQqxiY2NNASU56fz586MGDRp0V/Lwnj173urRo0cKoAxbvWLFiuvvvfdeUrt27TKXLFlyw9TUFAcPHqySlZUlAKBly5ZZS5YsufnMM8/cMt6Pp6enrnPnzhmtWrW6BQA5OTkmv/76a3jv3r3TOnXqlDFp0qQoANi2bdsdLUdmzJjhduXKFasRI0bEenp66gDlC2vv3r0TAeDQoUMl3sBVFhYWct++fVf79u0bL4SAXq/HL7/84lyvXr2GI0eO9CyqK9DmzZvtDhw4YPftt99GqnmE6tevnzt48OA4KSUmTZr05OegWtqh7l0/RwythnLSTYpcfnyJcp7eitEUufzUj8pnnHTNrMjlFzYqT/diLlgUufzy78pnfuO4VZHL/z2gXJfU6SPE61Pxbty4ofnPf/5TY82aNeHu7u56QLnWfPHFF1EAsGLFCrerV6+aA8CGDRucGjVqlGlra5sPKF03Fi5cGFEW5di6deu1UaNGRZuamkoA+OOPPxyaNWvWoF+/fl5RUVF3RZKPHz9utWDBAg/jz8PLy0v30UcfxQDKk/HMzMy7ApJEKicnJ/3+/ftDR40aFQ0AW7dudZwyZUrkpUuXgoYOHRr72WefRUVHR2t27tzp4Orqmte8efNsQElm3qlTp5Ts7GyTw4cPF1y/Pv/88zj1vDXWsWPHjEGDBiUBQFpammb48OEJU6dOjW3Tpk3m5MmT4xo0aJAZHx9vtn//fi1Qtvd6QPmCvGnTJqfOnTsnt2/fPhMAvL298yZMmBAFAMeOHSvV/RkAFi5cGBkYGHjdysoqHwCOHz9u+9xzz9Xr2rVrrYsXL5oXXj86Olrz/vvve69evTrCw8NDBwAODg75U6dOjQKAH3/80bWo7YiK8tZbb9UaM2ZMjPrAU6PRYPbs2dFarVZ//vx5m+XLlzsAwNq1ax2dnJx06oMnOzu7/DVr1kRUqVLloQcMGT9+fPyyZcuu2dvb6wDlgeorr7zi27p16zrHjx+/q/V/VlaWGDBgQK158+bdqF27dh4AWFlZyXnz5t0ElBa+u3fvfujRa+nx4aNtokqkRYsWWe3bt089ePBglQULFriPHj06wdRUyX0ZGBjo3qZNm7SWLVtmlbSPRYsWueTm5pq0aNGirvH83NxcE1dX1zwACA4OtnjmmWey2rdvn6bVavONn4a7u7vrACAjI+OOpJtqou2AgIBMM7PbDXLq16+fAwAJCQmPvNtHtWrVck+dOoUhQ4bE16hRI69GjRp57dq1uw4o3QFr1qyZ/cILL9yRy8HJyUkXHh6OtLQ0Uzc3t4Iba3E3WUtLSwkA9erVyzJubu/o6Jhvb2+vS0xM1MTGxmq8vb0L3rPiRvhSgz3PPPPMHbkA6tatW+R7duzYMS0A1KxZ846WKG3atEn/5ZdfnJOSkkp9TddqtfLnn3++Pnjw4MSPP/64+vnz521ycnLE4sWL3Tdv3uy0du3afzt16lSQl+q7775ziY+PN2vcuLGf8X6ysrJMXF1d83Q6nYiJiTFVv4DT04fXp+ItXbrUKScnx6RLly51jOfr9Xqhvq5z585Z1qlTJ1dKifXr1zs/99xztwYMGJACAJ06dcrYsmVLqUZqKolGo8GCBQuiBgwYkPThhx9W//vvv+30er1Yt26dy44dOxyXLFkSZvxE+dtvv3XJzs42ad68+R3nfeHP4//+7/9KnVCenk41atTIBYDWrVvfUkeXXLp06U1A6cLXvHnzdH9//zta9Li6uuoAZWRN4/kODg5F3mesrKwkANjb2+saN258x/ni7e2dExwcbB0VFXXHuV5W9/rDhw9rAcDLy+uO+/MLL7yQDgD3k5MHACZOnBj/xhtvpHz00UfVfv/9d0cpJXbv3u3QrFkz+2nTpl0fN25cgrru0qVLHXNyckxefPHFO7pRFbq+WNWvX/++8hTR0+fQoUPWwcHB1jNmzKj65Zdfuhsvs7W11VtbW+dfvXrVEgCklAgJCbH6+OOPq86cOTPawsJC2tnZ5b/44ovJRe/9/gwZMiT5pZdeShs3bpznunXrnPV6vTh69Kjds88+W//DDz+M+uqrrwpaD69bt84+Li7O7L333rurhaN6DgQFBVl26dKFefIqCQapqELZ9kGbkOKW2Vho8kta7mpnqStpeQ0nm7ySltevapdT0vKAGg5ZJS1vW8floUZbKa0JEybEHDx4sEpERITFypUrHYYMGZIcHR2t2bhxo9OWLVuu3mv7U6dO2dSqVSvr3Llzl++1rnF+knPnzll8//33zn/99ZctoOReMFZcQmF1iGg1EeKjpLYO8PT0vKuLSaNGjXKuXbsWDChPXNasWWP/66+/OoSGhloBd78edV+FlZQ4Wf0iXDgZ+f3uy9raOh8AjLsyAErFGwCio6PvqGS7u7vnAUBxowGVpGPHjhnnzp27vGLFCocpU6Z43rhxwyIuLs7s5Zdf9j1+/PhFdQjjs2fPalu3bn1rx44d1+73GE+MYQeKPf9hoc0vcbmtu67E5Y618kpc7t4wp8Tl1VtmlbjcpwOvT0V4XNenEydOaO3t7XWleV2jRo2KHTlyZM2BAwf6zJ8/P33s2LExffr0Sf3uu+8iy6o8zZs3z/7rr7+ubtmyxW7ixInVQkJCrNLS0kzffvttHxcXl5AXXnghAwBOnz5t4+vrm3X69Ol7lpuoJOp9UL1fGTMzM8PJkycLrl87duzQrlq1yvnEiRNa4O7zWe3iXsQxij2+en/Ozc19qPuz8b6M7/WOjo46ACg8YphaH1G/KN8PHx+fvN9++y3syJEjsWPHjq124sQJ25ycHPHJJ5/UsLOzyx8+fHgSoFxfbG1t9aW5vhCV5K+//tICwIYNG/5V63/Fef/99xPWr1/v8vXXX3ts2LDBadSoUTHvv/9+Qlneq9zd3fVr1qy5Pnbs2NixY8dW+/PPP+31ej3mzp1b1crKKn/atGmxAHD06FEbADh+/HiIGmCmyo3d/YgqmS5duqQ3a9YsHQDmzZvnDgCzZ8929fPzyyrN6BypqamaGzdulHrktaNHj1q1b9++9pgxY6q9+uqrKYGBgWV283nccnJyxOTJk90aN25cLyYmxuynn36K8PX1LbFlR0Xy7rvvJgK3uzKpQkNDLQDg9ddfLzHXRUkGDRqUHBISEjx48OBYQGkhNWXKlIJEzKmpqaYcsY/uhdenoqWkpJgmJSWZlSZB+4gRI5I2b9581cfHJ/v06dPafv361W7atKnfvQZEeBC9evVKCwoKujhx4sRIExMT6PV68dlnnxXk50pJSdFcv36d5z09FqtXr7avX79+vV9//dVh+vTpUb17937ge9rj1q9fvxStVqs/duyY1njQk0uXLlkAQI8ePR74tbRt2zbz+PHjVxYuXBiutsCeOnWqpxq8S05ONk1JSdEkJSXxex09lKSkJFMACAkJued1v2nTptn/+9//LrZr1y41MjLSfMKECV61a9du+NNPP5V5EvLGjRvn7N2799/169eH2tra6gHg66+/rnrr1i0TAEhOTtYAt883qvx4MSOqhMaOHRsDAJcuXbJetWqV/apVq1zHjh1bYtJclbW1dX5KSopm7969ReaouXr1qnlMTIwpACxcuNCpXbt29bp165b6559//qs+Xa+MEhMTTZs3b+73yy+/OB84cODKZ599Fufk5FSpuqb16tUrbc6cORF79uxxWLt2rT2g5PpZtGiRW69evRLfeOONUg1LPXz48GpFjRxoZWUlf/jhh5tq4suzZ88W/I9YW1vnX7582To0NLTIblH//POPpXF+Dnp68fp0Nxsbm3y9Xo8NGzYUWXlPSEgwvXz5ckHOmFdffTUtJCQkeNmyZde8vLxyzp8/b9OxY8e6ReWNKq0JEya4F7W9RqNBYGBgzPDhw2MAQB2lz1BufWJioqa40b+uXLlirubzI3oY/fr18xoxYkTNRYsWRSxfvvzGvQZYqGg8PDx0mzdvvqrT6cTo0aM98/LykJaWZjJu3LhqtWvXzg4MDCzVNXDp0qUOhUchVH3wwQeJgYGB1wEgKirKPDo6WgMo15f8/Hxs2LChyNx6SUlJJsHBwfzyTvek1WrzAWDr1q3F5mn866+/Cu4HjRo1yjl06FDovn37Lrdq1epWbGys2YABA2qroz4/iN27d2uNR4811qdPn9QVK1ZcA4CMjAyTc+fOWQLKvQoANm/eXOQ9Ni8vDydOnLgrlxVVXAxSEVVCffr0Sa1Tp04WAIwYMaKms7NzXmlHpmjYsGEGAHzyySfVixqBa8qUKe42NjYyMjJS8/HHH9fw8vLKmTBhwl2JRSubsWPHVg0KCrIeP358lJp0vDKytrbO9/b2zp4/f76bn59f/bfeeqvm+++/H7tx48bw0u7j1q1bJjt37iy2AvHmm28mAXfm6mjQoEGmXq/HqFGjqhfuepGfn49Zs2a5q/lA6OnG69PdGjdunAkA06dP9yyqtcPUqVPd1K5K6khcpqamGDJkSHJwcHBwq1atbqWkpGjWrFlTZMW9NPLz80VxFXgA6N+/fxIA2NnZFVwf1RxBY8eOrV64GzMATJkyxUNN8E70oFavXm2/bt06l169eiVW5pHmtFptvp2dnf7y5ctWDRo0qN+6deu69erVyzp69OhldcCW0vjtt9+KPU8HDx6cBCjdFNV7dJMmTTIBYMaMGVUTExPvChpPnz7dvbhujUTGmjdvngkAGzdudD569OhdQZ2tW7faqoGhkSNHeqoPJ59//vmMo0ePXvnggw9i8vPzsWzZMpeHKceOHTuKPQdee+21NK1WqwcAZ2dnHQA0a9YsEwAWLVrk/u+//971MHXhwoXOaisxqhwYpCKq4LKzs00K5yYyMTHBhx9+GKMuHz16dEzh/AnZ2dkmwN15jYYPH54ghMDZs2dtOnToUOfMmTOWAJCammoyatQoTyklbG1t80NDQ811Op0ovL36xVGv1wvgdq4INc9D4QCGMZ3u/mND6nDRwN25ngpTh5AuXGYACAsLszAup0r9W6fTCeOyF359hde/x+u84xgPui91O9Vvv/1mO3r06Jo7d+68evLkyZDLly9fPHXqVMiECRPiS8rFUZQpU6Z4Ftfy6cKFC1YA0KdPn0R1njoC0q5duxx69uxZS21RFRMTY9qnTx9vX1/fgsTJ5ubmap6f+yoTVT68PpXu+jR8+PAEMzMzGRERYdG2bdu6hw8ftgaU/HhTp051DQ4OtqpTp04uABw5csT23LlzBa0etFqtfO+99+KAO3PxmJmZ3Xc+rblz53okJCQUebE4e/asFQAYd7F677334gHg9OnT2g4dOtRWy5WammoycuRIT41GI9W8Xmo3pMeRf5AqDvWcK3xvLayk+/PVq1ctilpW3Pms/o8VPp/V9Us6zwvfV8vqXh8dHa156aWXfMeNGxe9f//+0CtXrlwMCgq6tGjRokhnZ+f7arX9448/uoaEhBQ5Gt8///xjBQBdunRJ0Wq1EgCGDRuWaG5uLm/evGnRpk2bumrLx+zsbDFjxgzX06dPW/v5+eUCt89Tvb5SNSSnMlCac/XFF1+85e3tnZ2bmyu6d+/uu2rVKnudTof8/Hxs2rTJbvz48dX79u2bAijd2L///ntH4+0nT54cA9yZ682oTljqe8P27dsd//e//xXZ8ik0NNQsPT3dtGnTphnq//WAAQOSq1Spok9JSdE899xzdbdt22abn58PnU6HxYsXO/7444/OnTp1SgeUHHhq9/bSlocePwapiCqw/Px8HDlyRBscHGyt9rtWDR06NKlq1aq57u7uucOGDbsj10FSUpLJhQsXrAHgzJkzNsbBiI4dO2Z89NFHBUMiN2vWrIGtrW0TR0fHptu3b3dYtGjRTQBo1KhRtq2trf7GjRsW7733XrW//vrLetKkSe4zZ870AIArV65Yrlu3rsrq1avtAeDs2bPWABAUFHTHTcX4y9axY8eK7DJSkh07dtipvx88eLDY1j96vR5Xr161KryNqkWLFhmAMmT61q1bbX/99Ve77t2714qKijIHgJ07d9p+8MEHBblYTp8+bQ0AV69etTKuzJ0+fdpKnW/cZS46OlqTmpqqAW5XIgGlifGlS5esgLvfGzUYdP78+Tvel6CgIEsASExM1Ny4caOge87+/ftt9Xo96tev39Db29u/Zs2aDXx8fBr4+fnVb9mype+4ceM8Cv+fFOfs2bM2rVq1qrtnz547uhWsXLnS4euvv/bo3r178tixYwtaqAwdOjS5d+/eiQCwY8cOhzp16jSys7Nr4uHh0eTatWsWU6dOjVHXrVu3brbhdVgDwIoVKxyuX7/OgTqeMLw+lf765Ofnlztz5szrQghcvHjRun379vW0Wm1TW1vbpvPnz/dYvnz5dXXdvLw80atXr9rqMNs6nQ7bt2+3d3NzyxswYEDBqEk1a9bMAZTrjU6nw6xZs+755DoiIsKiZcuWfps2bbIzvq5t27bNdtKkSdVbtmx5a+bMmVHq/M6dO2f85z//iQaAo0eP2jVp0sRf/Tz++OMP+4ULFxYkr/f19c0RQuDy5ctW+fn52LZtm+2pU6fKPI8WVRzXr1/XhIWFWQLK6LMlBT7Uc+/IkSO2hR+QtGnTJgMAtm7d6rRw4UKnffv22bzzzjvV9+zZYw8AJ06csJk5c6bL2bNnLQHg+PHj1gCQmJhoZtyFVW35kZSUZGZ8z8nPz8e1a9csAWWUO+Njl9W9/uTJk1bJycmakSNH1qxevXrB/dnX17d+06ZN/QYMGOB15cqVIgNPhaWmppq2bdvW7/vvv3c0blH6999/Ww0ePLimj49P9rJlywquGXXq1MmdM2dOhImJCS5fvmz1/PPP19NqtU21Wm3TuXPnevzwww8R6rqenp55Wq1WHxYWZpmZmSlOnz5t+TBds6hyKO25ampqitWrV4dptVp9cnKy5t133/XRarXNbGxsmr755pu1Z8yYcdPR0bEgcvvpp596/fjjjwVdA9etW2dvZmYmR40aFafOq127dg4AnD9/3goA5s6d65yZmVligCg3N1d069at7pdffulsnMvxwoULFq+++qqPm5tb3po1a8LU+Q4ODvnff/99mJmZmbx586bFK6+84qvVaptaW1s3GzNmTI0lS5ZEGD/MrV69ek5cXJxZdHS05vr165oVK1Y8cCtlejSE+mSD6FE6d+5ceOPGjRPuvSapxowZ47FmzRqX+Ph4MwCws7PTN27cOOPw4cMFI2QFBga66PV68d///rfgZtCuXbs6Z86csUlPTy+4Gtvb2+vatGmTtn379oIL+ooVKxzmz5/vFhISYm1lZaXv2LFj6vz5828ad4XbunWr7dixY72io6PN69Spk/Xhhx/GdOvW7VazZs3q5+bmitGjR8dMnjw5rlatWg3Umx8AeHp65q5ateraihUrnLZt2+aUmZlpAgBWVlb5gwcPjlu4cOE9kxsfOXLE+p133qkZERFhaXwzrVGjRs7kyZMjhwwZUvBl7ffff7d99913axoPI+/p6Zm7b9++EDWvRWZmphg4cGCNXbt22Wu1Wn2HDh1SZ8+eHbV06VKnr776qmpAQED6Dz/8EFGtWrW8Ro0a1Td+PR4eHrl79+69MmzYMK9jx47ZqU9WXV1d82bPnn09ODjYatmyZW6pqammgPLUqHv37knDhg1LeOedd2rFxsaaAYAQAk2aNMnYsmXLv88++6xfZGRkQYW1Ro0aObt3774yYsQIr7///ttOfdJlZ2ennzhxYuSECRPiExISTNu3b++bkZFhmpqaapqRkWFa+Mlz69at0/7+++8SR1EbNmxYtY4dO94KDw83P3jwoG14eLiliYmJTE5O1ri7u+e988478R988EFi4dYv+fn5+Oqrr1yWL1/uEh4ebmlnZ6fr0aNH8tdffx1pPEQ3AIwaNcrzhx9+cG3Tpk3ayJEj43v16lWqfFlUOfD6VPrrk7GtW7faBgYGVr1w4YK1RqORzz77bNq8efNuGg8NX7NmzQbh4eGWQghUrVo1187OTufv7585Z86cKHW4ewCIjIzUdOnSpU5UVJR5r169kqZPnx7t4eFRbHOwCRMmuNetWzcnNTXV5MCBA3ZXr161NDExQXJyssbBwUHXp0+fxAkTJsSZmd2ddm7ZsmUOCxYscL969aqVlZWVvlOnTinffPNNZNWqVe843owZM1xnzpzp2ahRo/ShQ4cmvPvuu2UyFHl5WbbpD0fp6ltpH+iKuCv5Q1/r9kiSj/v5+dWPiIiwUFtFAoCLi0te7969ExcvXlxwDqWmppo0atSovnECfgcHB93cuXOvG/9/TJkyxe27775zy8vLE02bNs2YPn16ZGpqqukbb7xR28PDI/fLL7+88fLLL9/q0aNHzT179jio90h7e3vdnDlzrgcHB1stXbrULSsrywQAtFqt/u23345/7rnnbo0ePbpGTExMwf22Zs2a2WfPnr3UpEmTemVxr//111/D8/Pz0bdv3xqHDx+2y8vLM8nIyDDJzc01MW6J5eTkpAsODg5yc3MrNpq3dOlSh7i4ODNnZ2fdwYMHbdWHPWlpaaYWFhayR48eyZ9//nlM4XsuAGzfvt12xowZHufPn7cxNTWVrVu3vjVv3rybDRo0uGOUtjVr1tj/5z//qVGtWrXcAQMGxI8bN67S18//3rzE8Vn33Ep7rv4dY57/bO/3yvVcNRYUFGQxceLEqkeOHKmSnZ1tUr9+/cwvvvgiskePHrfUdfr16+e1bt06F0AZ3dLDwyPX0dFRN23atMj27dsXdNvV6/V47bXXvHft2uXQtWvX5DFjxsS1adOm2G69u3fv1u7cudOuSZMmWQcOHLA9c+aMjZQSar2hc+fOKV988UVMUfe7I0eOWH/22WdVT548aavX6xEQEJA+Z86cm61bt84qfIwBAwbUsrW11fft2zfh888/j9Vo7v0s9dy5c86NGzf2vueK9NAYpKLHgkEqoof3888/V1m3bp2j8Zd5QKkAJCcnm+7atct26NChNcPDw8+XVAkmIqJ727bnoG1cWlaRg0VUBq52Vnkvd37u1r3XpId18eJF8/79+9c6ePDgFTs7u4IAUn5+PjIyMkzOnDljOXDgwJpffPFF5IABA1LKs6xPoqN7t9rmp8VU2nPVxM4975lOr/BcreAYpHp82P2CiKgSuHjxovnQoUNr7d2793LhZaampnB2dtb3798/ZcGCBZnGFWQiInowDPBQaeTk5IhXX321dr9+/RIK339NTExga2ub365du8zOnTunurq6MlnjI8AAD9GTpdI2iyQiepp88803rpmZmSbq8MBFCQ4OtujQoUMqR9kjIiJ6PH799Ve7kJAQK2tr62Lvz9nZ2SIjI8Okc+fO6Y+zbERElRGDVERElcCrr76aYmlpmf/aa6/5/P7777aFRxz6448/tNu3b7ebOXNmTDG7ICIiojLWrl27jOrVq+dMmzat2qJFixwLJ4UOCgqymDFjhuvcuXMjC+d6JCKiuzEnFT0WzElF9PBCQkLMZ8+e7Xbo0CG7lJQUjYeHR667u3uut7d3Tr9+/ZKff/75jPIuIxER0dMmOTnZ5KuvvnLdvn27/Y0bNyxcXFzy3N3d86pXr57TsWPHWwMHDkw2Hl2MiCof5qR6fBikoseCQSoiIiIiIiKqjBikenzY5pSIiIiIiIiIiModg1RERERERERERFTuGKQiIiIiIiIiIqJyxyAVERERERERERGVOwap6LFhkn4iIiIiIiKqTPg99vFikIoeCyFEuk6n49i7REREREREVGnodDqNECK9vMvxtGCQih4LKeWRtLQ0bXmXg4iIiIiIiKi00tLStFLKI+VdjqcFg1T0WOh0uo3x8fFCp9Pxf46IiIiIiIgqPJ1OZxIfHw+dTrexvMvytGDAgB6XA1lZWT+EhobaJSYm2ufl5WnYt5eIiIiIiIgqEikl8vLyNImJifahoaF2WVlZPwA4UN7leloIBgrocTl16pQA0EGj0bwuhGgrpWT3PyIiIiIiIqpQhBDpUsojhhZUBwICAhg4eUwYpCIiIiIiIiIionLH7n5ERERERERERFTuGKQiIiIiIiIiIqJyxyAVERERERERERGVOwapiIiIiIiIiIio3DFIRURERERERERE5e7/AX6z2zE5OsuFAAAAAElFTkSuQmCC\n",
+ "image/png": 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\n",
"text/plain": [
"<Figure size 1440x504 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.rcParams['font.size'] = 24\n",
"\n",
"fig, axes = plt.subplots(1, 2, figsize=(20, 7))\n",
"# sns.scatterplot(x=\"pca_x\", y=\"pca_y\", hue=\"label_name\", palette=sns.color_palette(\"hls\", df_dataset['labels'].nunique()),\n",
"# data=df_dataset, legend=\"brief\", alpha=0.8, ax=axes[0])\n",
"# sns.scatterplot(x=\"pca_x\", y=\"pca_y\", hue=\"pred_name\", palette=sns.color_palette(\"hls\", df_dataset['labels'].nunique()),\n",
"# data=df_dataset, legend=\"brief\", alpha=0.8, ax=axes[1])\n",
"\n",
"\n",
"hist_kws = {'edgecolor': \"k\", 'linewidth': 0.5}\n",
"sns.distplot(df_train['Label'], bins=12, kde=False, norm_hist=True, label='Training Set', ax=axes[0], color='#1f77b4', hist_kws=hist_kws)\n",
"sns.distplot(df_test['Label'], bins=12, kde=False, norm_hist=True, label='Test Set', ax=axes[0], color='#ff7f0e', hist_kws=hist_kws)\n",
"\n",
"axes[0].set_ylabel('Normalized Counts')\n",
"\n",
"axes[0].axvline(df_train['Label'].mean(), label='Mean Training Set', color='#1f77b4', linestyle='--')\n",
"#axes[0].axvline(df_train['Label'].mean()-np.std(df_train['Label']), label='Variance', color='r', linestyle=':')\n",
"#axes[0].axvline(df_train['Label'].mean()+np.std(df_train['Label']), color='r', linestyle=':')\n",
"axes[0].axvline(df_test['Label'].mean(), label='Mean Test Set', color='#ff7f0e', linestyle='--')\n",
"#axes[0].axvline(df_test['Label'].mean()-np.std(df_test['Label']), label='Variance', color='b', linestyle=':')\n",
"#axes[0].axvline(df_test['Label'].mean()+np.std(df_test['Label']), color='b', linestyle=':')\n",
"#axes[0].legend()\n",
"axes[0].set_title('Distribution of Labels')\n",
"\n",
"sns.distplot(df_train['Number of Words'], bins=range(0, 220, 5), kde=False, norm_hist=True, label='Training Set', ax=axes[1], color='#1f77b4', hist_kws=hist_kws)\n",
"sns.distplot(df_test['Number of Words'], bins=range(0, 220, 5), kde=False, norm_hist=True, label='Test Set', ax=axes[1], color='#ff7f0e', hist_kws=hist_kws)\n",
"axes[1].axvline(df_train['Number of Words'].mean(), label='Mean Training Set', color='#1f77b4', linestyle='--')\n",
"#axes[1].axvline(df_train['Number of words'].mean()-np.std(df_train['Number of words']), label='Variance', color='r', linestyle=':')\n",
"#axes[1].axvline(df_train['Number of words'].mean()+np.std(df_train['Number of words']), color='r', linestyle=':')\n",
"axes[1].axvline(df_test['Number of Words'].mean(), label='Mean Test Set', color='#ff7f0e', linestyle='--')\n",
"#axes[1].axvline(df_test['Number of words'].mean()-np.std(df_test['Number of words']), label='Variance', color='b', linestyle=':')\n",
"#axes[1].axvline(df_test['Number of words'].mean()+np.std(df_test['Number of words']), color='b', linestyle=':')\n",
"#axes[1].legend(loc='upper center', bbox_to_anchor=(0.5, -0.05), ncol=4)\n",
"#ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.05)\n",
"# fancybox=True, shadow=True, ncol=5)\n",
"\n",
"axes[1].set_ylabel('Normalized Counts')\n",
"axes[1].set_title('Distribution of Number of Words')\n",
"#f.title('distriution of labels and number of words in the training and test set.') \n",
"\n",
"handles, labels = axes[0].get_legend_handles_labels()\n",
"lgd = axes[1].legend(handles, labels, loc='upper center', bbox_to_anchor=(-0.1, -0.2), ncol=4)\n",
"#fig.savefig(f\"dataset_imbalance.png\")\n",
"fig.savefig('dataset_imbalance.png', bbox_extra_artists=(lgd,), bbox_inches='tight')\n"
]
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['#1f77b4', '#ff7f0e']"
]
},
- "execution_count": 6,
+ "execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pal = sns.color_palette(n_colors=2)\n",
"pal.as_hex()"
]
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(2.787484774665043, 1.7645631067961165)"
]
},
- "execution_count": 7,
+ "execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_train['Label'].mean(), df_test['Label'].mean()"
]
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(41.942143727162, 25.74271844660194)"
]
},
- "execution_count": 8,
+ "execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_train['Number of Words'].mean(), df_test['Number of Words'].mean()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Sentence embeddings"
]
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": 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\n",
"text/plain": [
"<Figure size 864x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"df_embeddings = pd.DataFrame({'$t$-SNE Projection 1': projections[:, 0], '$t$-SNE Projection 2': projections[:, 1], 'label': test_train_labels })\n",
"fig, ax = plt.subplots(figsize=(12, 10))\n",
"sns.scatterplot(x=\"$t$-SNE Projection 1\", y=\"$t$-SNE Projection 2\", hue=r'label', palette=sns.color_palette(n_colors=2),\n",
" data=df_embeddings.sort_values('label', ascending=False), legend=\"brief\", alpha=0.8, sizes=(20, 200)).set_title('Sentence Clustering: Training and Test set')\n",
"handles, labels = ax.get_legend_handles_labels()\n",
"#ax.legend(handles=handles[1:], labels=labels[1:], prop={'size': 15})\n",
"#lgd = ax.legend(handles, labels, loc='upper center', bbox_to_anchor=(0.5, -0.2), ncol=3)\n",
"lgd = ax.legend(handles, labels, loc='center left', bbox_to_anchor=(1, 0.5))\n",
"#fig.savefig('clusterplot.png', bbox_extra_artists=(lgd,), bbox_inches='tight')"
]
},
{
"cell_type": "code",
- "execution_count": 21,
+ "execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": 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\n",
"text/plain": [
"<Figure size 720x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.rcParams['font.size'] = 24\n",
"fig, ax = plt.subplots(1, 1, figsize=(10, 10))\n",
"\n",
"ax.scatter(projections[:, 0][train_idx_bool], projections[:, 1][train_idx_bool], c='#1f77b4', label='Training Set')\n",
"ax.scatter(projections[:, 0][~train_idx_bool], projections[:, 1][~train_idx_bool], c='#ff7f0e', label='Test Set')\n",
"\n",
"ax.set_title('Sentence Clustering: Training and Test Set')\n",
"ax.set_xlabel('$t$-SNE Projection 1')\n",
"ax.set_ylabel('$t$-SNE Projection 2')\n",
"leg = ax.legend(framealpha=0.9, bbox_to_anchor=(1, 0.75))\n",
"\n",
"# Remove opacity from legend marker points\n",
"for lh in leg.legendHandles:\n",
" lh.set_alpha(1)\n",
"\n",
"fig.savefig('clusterplot.png', bbox_inches='tight')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Clustering"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Clustering only for train embeddings"
]
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"train_bert_scores = pd.read_csv(SET_DIR + '2_evaluate_bert_test/train_scores.csv', header=None)[0].tolist()\n",
"train_labelsx2 = np.array(df_train['Label'].tolist() + df_train['Label'].tolist())\n",
"train_bert_scoresx2 = np.array(train_bert_scores + train_bert_scores)\n",
"train_projections = projections[train_idx_bool]"
]
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "(0.8499682968488111, 0.0)"
+ "(0.849968296848811, 0.0)"
]
},
- "execution_count": 12,
+ "execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pearsonr(df_train['Label'].tolist(), train_bert_scores)"
]
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"k = 10\n",
"kmeans = KMeans(n_clusters=k, random_state=1337).fit( vectors[train_idx_bool])"
]
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"df_train_embeddings= pd.DataFrame({'$t$-SNE Projection 1': train_projections[:, 0], '$t$-SNE Projection 2': train_projections[:, 1], 'label': kmeans.labels_, 'label_mu_sigma': kmeans.labels_, 'Bert scoers': train_bert_scoresx2, r'$\\bf{Score}$ $\\bf{Difference}$': abs(train_labelsx2-train_bert_scoresx2)})"
]
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"cluster_labels = {}\n",
"for label in kmeans.labels_:\n",
" scores_label = train_labelsx2[kmeans.labels_ == label]\n",
" bscores_label = train_bert_scoresx2[kmeans.labels_ == label]\n",
" score_diff = np.abs(scores_label - bscores_label)\n",
" \n",
" cluster_labels.update({label: 'Cluster {} (μ={:.2f}, σ={:.2f})'.format(label, np.mean(score_diff), np.std(score_diff))})\n",
"\n",
"df_train_embeddings[r'$\\bf{Sentence}$ $\\bf{Cluster}$'] = [cluster_labels[label] for label in df_train_embeddings['label']]"
]
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": 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\n",
"text/plain": [
"<Figure size 864x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots(figsize=(12, 10))\n",
"sns.scatterplot(x=\"$t$-SNE Projection 1\", y=\"$t$-SNE Projection 2\", hue=r'$\\bf{Sentence}$ $\\bf{Cluster}$', size=r'$\\bf{Score}$ $\\bf{Difference}$', palette=sns.color_palette(\"hls\", df_train_embeddings['label'].nunique()),\n",
" data=df_train_embeddings.sort_values('label', ascending=True), legend=\"brief\", alpha=0.8, sizes=(20, 200)).set_title('Sentence Clustering')\n",
"handles, labels = ax.get_legend_handles_labels()\n",
"#ax.legend(handles=handles[1:], labels=labels[1:], prop={'size': 15})\n",
"#lgd = ax.legend(handles, labels, loc='upper center', bbox_to_anchor=(0.5, -0.2), ncol=3)\n",
"lgd = ax.legend(handles, labels, loc='center left', bbox_to_anchor=(1, 0.5))\n",
"fig.savefig('clusterplot.png', bbox_extra_artists=(lgd,), bbox_inches='tight')"
]
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": 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\n",
"text/plain": [
"<Figure size 720x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.rcParams['font.size'] = 24\n",
"fig, ax = plt.subplots(1, 1, figsize=(10, 10))\n",
"\n",
"# Cluster colors\n",
"np.random.seed(1337)\n",
"cluster_colors = []\n",
"cluster_bg_colors = []\n",
"cluster_colors_values = []\n",
"\n",
"for label in np.unique(kmeans.labels_):\n",
" # Genertate a random distinct colour for the current cluster (as HLS)\n",
" # Hue: equally distributed\n",
" # Luminance: randomly generated without using extreme values\n",
" # Saturation: randomly generated in the upper area (more saturated colours)\n",
" color = [label / (k - 1), np.random.randint(20, 80) / 100, np.random.randint(50, 90) / 100]\n",
" color = colorsys.hls_to_rgb(*color)\n",
" \n",
" # Use the gray value of the colour to decide whether a white or black background should be used\n",
" # Conversion formula: https://en.wikipedia.org/wiki/Grayscale#Converting_color_to_grayscale\n",
" gray_value = 0.2126*color[0] + 0.7152*color[1] + 0.0722*color[2]\n",
" if gray_value < 0.5:\n",
" cluster_bg_colors.append('rgba(255, 255, 255, 0.9)')\n",
" else:\n",
" cluster_bg_colors.append('rgba(0, 0, 0, 0.9)')\n",
" \n",
" # Convert the colour to a valid HTML specification\n",
" color = [int(round(v * 255)) for v in color]\n",
" cluster_colors_values.append(color)\n",
" cluster_colors.append('rgb(' + ', '.join([str(c) for c in color]) + ')')\n",
"\n",
"score_diffs = np.abs(scores_label - bscores_label)\n",
"score_diffs_min = np.min(score_diffs)\n",
"score_diffs_max = np.max(score_diffs)\n",
"\n",
+ "score_diff_cluster = []\n",
+ "\n",
"for label, color in zip(np.unique(kmeans.labels_), cluster_colors_values):\n",
" data_label = train_projections[kmeans.labels_ == label, :]\n",
" scores_label = train_labelsx2[kmeans.labels_ == label]\n",
" bscores_label = train_bert_scoresx2[kmeans.labels_ == label]\n",
" \n",
" # Normalized difference between BERT and the ground truth\n",
" score_diff = np.abs(scores_label - bscores_label)\n",
+ " score_diff_cluster.append(score_diff)\n",
" opacity = (score_diff - score_diffs_min) / (score_diffs_max - score_diffs_min)\n",
" opacity = np.clip(opacity, 0, 1)\n",
" \n",
" # Array with colors for each point in each row\n",
" colors = np.zeros((data_label.shape[0], 4))\n",
" colors[:, :3] = np.array(color) / 255\n",
" colors[:, 3] = opacity\n",
" \n",
" label = f'Cluster {label} (μ={np.mean(score_diff):.2f}, σ={np.std(score_diff):.2f})'\n",
" ax.scatter(data_label[:, 0], data_label[:, 1], c=colors, label=label)\n",
"\n",
"ax.set_title('Sentence Clustering')\n",
"ax.set_xlabel('$t$-SNE Projection 1')\n",
"ax.set_ylabel('$t$-SNE Projection 2')\n",
"leg = ax.legend(framealpha=0.9, bbox_to_anchor=(1, 0.75))\n",
"\n",
"# Remove opacity from legend marker points\n",
"for lh in leg.legendHandles:\n",
" lh.set_alpha(1)\n",
"\n",
"fig.savefig('clusterplot_bert_difference.png', bbox_inches='tight')"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": 97,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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K4TE91dGbldpwk5syszbGvRb3B6JhPvsG321xj/CFLOnpf0dENN7D0KmIOKiH56v9nnaVM7x07crOhZf+FmXm5RRD5Q4vd01j6fniO5SZsyimgAT4QkdvKMvk/9vdaVNanpisS8uX9SJiuy7qzC8fF7H0DCKXlo+voklCGhEjgPNr9TLzceB3ZfFOdb2gjdanSOq/30F5U+XNr7VxwHtGxH5NYhoOnE4PF37prigWgTqXJcM1jq7dBFdBrUevs57p+l6/ZvVqi9W8Fjing17CL7EkSeyu61hy0+ypEfHmxgpRLAT1WYrpHysr73v43/LLrSNi/ybnmkAxveLPymPuAe4ti4+KiJ2aHDMe+CZLvxbqPxEhixmLPsOS+yg6+0SoI2M62F/7lOD8un21n9cI4OcRsWrjQeVN4Ks13A/SK1nMxLQvxXjwlYAzu/uJSEQcQs9nkKl9WtJs6Mpadc9HNJR9IOoWWsvMxZn5DZZct8afT61zoNkbm9ox21DMbNTM/6PJDcLS8s5kXVr+nNtFL16tt+qUzJxRt/9EipvToOid+mlEbBsRb4yIPSg+op6XmTfUHXMoRfI/mmIu9qVEscLoa4DvZOZtDcW1IQidrRJ4NEt67b4XEZdExLvKXtOdKeYun5uZN3XYwrIxjey6FkTEWOCnLOl9/R+afI+l0XXHddRDWhu/3NGbmvo6HdU7gyU9prsCN0Wx2uVG5c/qBxTTNn6n4bhOr3WZ3NVW9FwZuC4iTopiNdNNI+JTFEn6OQ1JZf0sL53dkzC64etjKYaLAJxerhq5ZUS8OSIOpJjT/rrMrB86VZsGdDhwWUScFRHbRMTGEbEbxVzf12bmI3XHvK0sq/9ea/OxAzS+JrtjmSEtEbEhxZSRtwI/qDvXjcDl5ZcbArdHxCHlNX1rRBxHMS3qMQ1Ndud3o1OZ+TuKTxkWl7FdUt5I3qGIOJRigaaLG/aPrfuyWRu1qSa3rN0gGsVKrAey9KderyvLarnFNIo3l41qP/fGn0/tTcHWZTvrR0Tt+K/XlR8REVdGxPvL342dolgFdQOK3+na91U/DMrVSrX8yjaY7N3Nza3rjeImq9oCH3MpZsJ4LUVv7dDyeW0hoQuAoU3a2IZiho5sst1M3Uqkdce8szxfAqcAq5T730oxa8qFlAvV1B2zNksWknlpirsOvq/dWLKoT+N2C7ByD6/TlnXH/41iVpvaQjpDKWYr+TzFHOEJ3Eknq0BSLFR0VV2bezap8x6KTzKyvL6bN6kziiLRq7XzB2BCk3pvqIutcXuShkWDgB3qzv0o5SJITdoN4LsdtJsUiXpjvH+oK/9EQ/k0iun5kmJF01c0lH+8k5/rr2lYZKs85vBO4vst5YJMddcpKe6ZOJiiR3wIRW/7QuDiHrxmptWdZz7wOWBsWfZfFGPh7wemNTl2IsUnWM1ifpFlVwTt9u9GN2PflmLF26T4fTyc4jW+Ulm+CrAzxb0su3XQxr51MV8DjGkoX7e8zrU6D1P8TfhJea7a/kUUb17WZ8nfq0UUixZNLF+Db6eYXepP9T/P8jy/rmvr0fI8Uxu+147+fj1AuVJu3eu9/vv6G+UKzG5uy9s24AG4ubl1byv/+f0MWBN4H8XY3NspErj5FAneZdStbtlBO+tQfJT/GMVNc3eV/+CXSZ7qjlmLItF7gGLO8fvLf6zvblL3+x38M53XSfsbUtw090QZ0z8p3oyM6c61Kdv4OEWP8zMdnb9MEv5DkVydRPFGpMNEieKmuIVN2ppZlr+qbLfZ+Z4FvlrW+3IH7Syi+LTjtQ3nnULxkf6/yuvxGMVKmWs11Lu/g3P/uovv6SqKXsr5FG/S9myo8x6KRLOx3ecoVrW9uknZYopPc+rbeUP5mn2yfN3cCnyKutVum8S3JfArijm6n6dIsg5l2RVC38Cy1/IpiplSduvsHE3OOa2unY9RvAGdWb5e/kHRq7vMG6u640dQDCH6a3mNZlG8uXhrQ70e/250M/6VKFZAvZhiONHs8nXzb4p7SQ7tKH6WrF7beC0/3VBva4r7WJ6jGIZ1MEVCPI0icT8L2Ljh71Xj62NWeY0+TblCbJO/M3+k+J36I03eeFK82TmbIpFfUH6P3wYm19UZSsdvFE/vzbV2cxuILTITSZIGq4iYxpJVat+emdcMWDCS1MAx65IkSVKbMlmXJEmS2pTJuiRpsKufQcgVMiW1FZN1SdKgVU7vt2vdrl26mKZSkvqVN5hKkgaliPgw8COWzHteswjYNzPP7f+oJGlpJusdmDx5ck6bNm2gw5AkSdIK7pZbbnkyM5dZBRmW7U1Qadq0aUyfPn2gw5AkSdIKLiL+3VGZY9YlSZKkNmWyLkmSJLUpk3VJkiSpTZmsS5IkSW3KZF2SJElqUybrkiRJUpsyWZckSZLalMm6JEmS1KZM1iVJkqQ2ZbIuSZIktSmTdUmSJKlNmaxLkiRJbcpkXZIkSWpTJuuSJElSmzJZlyRJktrUsIEOQJLqRUSftp+Zfdq+JEmtZLIuqa30NJmOCBNwSdIKy2EwkiRJUpsyWZckSZLalMm6JEmS1KZM1iVJkqQ2ZbIuSZIktSmTdUmSJKlNmaxLkiRJbcpkXZIkSWpTJuuSJElSmzJZlyRJktqUybokSZLUpkzWJUmSpDZlsi5JkiS1KZN1SZIkqU2ZrEuSJEltymRdkiRJalMm65IkSVKbMlmXJEmS2pTJuiRJktSmTNYlSZKkNmWyLkmSJLUpk3VJkiSpTZmsS5IkSW3KZF2SJElqUybrkiRJUpsyWZckSZLalMm6JEmS1KZM1iVJkqQ2ZbIuSZIktSmTdUmSJKlNmaxLkiRJbartkvWIGBMRJ0XEvyNiQfl4SkRM7GE7IyPiqxFxR0TcFhFXRMSr+ypuSZIkqdXaKlmPiFHANcDngBHAQmBN4DPATRGxajfbGQP8GtgU2CIzNwYuB/4SERv3QeiSJElSy7VVsg4cAswFXp2ZqwHjgX2AF4BXAd/oZjv/A2wF7JuZ8wAy8yzgHuDiiBjZ6sAlSZKkVmu3ZH1zYIfM/AdAZi7KzHOA48ry93bVQESsAxwA3JCZDzUU/wxYD9irdSFLkiRJfaNtkvWICOCEzHyuSfFF5eOIbjT1QWAYcEuTspvKx917HqEkSZLUv9omWc/CjR0UP1E+3t6NprYvHx9sUvav8nETh8JIkiSp3bVNst6F15SP53ej7trl4yNNymaXj8Pq6kmSJEltaXlJ1j9KcXPoBd2oW5sxZm6Tsnl1zyc0FkbEvhExPSKmz5w5s+dRSpIkSS3U9sl6RLwc+CSwR2Yu7MYhteEtC5qUDat7/kJjYWaelZmbZuamq67arVkiJUmSpD7T9sk68D3gS5l5U5c1C7PKx5WalI2pe/5kr6KSJEmS+lhbJ+sRcTjw98w8sweH3Vs+Nusan1w+Ps+Sm1YlSZKkttS2yXpEfBxYIzOP6uGh15aP6zYpW6dWJzOXGQYjSZIktZO2TNYj4n3ANsDBTcpGd3H4D4EEtmhStmn5eGmvApQkSZL6Qdsl6xHxAYqFjfbNzGwo25BiDDsRMSwiLoyIKyJiXK1OZt5NkbBvHREva2j+IxRzrXdnVhlJkiRpQFVO1iNiy4jYt+7rDSJiq3Il0qpt7gFcAmwO3BkR95TbvRHxKMWiSH8qq78B2BXYEXhnQ1OfBu4HTouI4VH4CrAm8JHMfL5qjJIkSVJ/6XGyXvZoXwr8EagfT34nMA24MSI2qtDuR4BzgaEU481fXbetB6xGMd3iT8tD7gKmA/cBf65vKzNnAW8F5gB/BW6jWATpDZk5vaexSZIkSQNhWNdVlnE48N7GnZm5GLggIl4A/hwRb83M27vbaGb+BPhJD+rPB97USfmTwN7dbU+SJElqN1WGwXwCOINiBdBHmpRfAgwHTuhFXJIkSdKgV6VnfTxwSGa+GBHZWJiZiyPiRYphKJIkSZIqqtKzfndmvthRYUT8NzAa6LCOJEmSpK5VSdb/FRGrl8+XmvklItYAzqKY5/zaxgMlSZIkdV+VZP3rwA8iYmMgI2JERKwfEYdTzLwyjWLWli+3LkxJkiRp8OnxmPXMvC8ijqJYBXRN4Lm64gCeBHbtyUwwkiRJkpZV5QZTMvPGiHgVxYJEmwOTgLnArcClmTmvdSFKkiRJg1OlZB0gMxcCvyw3SZIkSS1WZcw6ETEpIt4fESPq9q0fEZ+MiAmtC0+SJEkavHqcrJczvtwB/AzYo7Y/M++iuMH02ojYvlUBSpIkSYNVlZ7144CpwLMUY9Rfkpm3AIcCv4oIF0WSJEmSeqFKsv524F3AxMyc3liYmVcBs4Gv9DI2SZIkaVCrcoPpU5n5v13UWUgxS4wkSZKkiqr0rC+ov7G0UURsA7wMcPpGSZIkqReqJOs/A86JiNGNBRHxfuDHQAKX9TI2SZIkaVCrMgzmNOBK4P6IuAr4D7AasAXwKopVTP8NfKlVQUqSJEmDUY+T9cxcWE7N+P+AvYDh9cXAr4D9M3NGa0KUJEmSqouISsdlZosj6blKK5hm5nPA/hFxBMWNpJMoZoC5JTMfb2F8kiRJUq90lHRHRFsk5J2plKzXZOYs4HfNyiLiq5l5dG/alyRJkgazKjeYdioKGwOfaXXbkiRJ0mDS4571iBgFfA34IPBylh6zLkmSJKlFqgyDORvYpRv12nsAkCRJktTmqgyDeS9wBfB6YFRmDmncgNfiokiSJElSr1TpWZ8FHJeZd3VUITPvjYgfVQ9LkiRJUpWe9R8BU7tR7/wKbUuSJEkqVUnWvwp8MCK6OtaedUmSJKkXqgyDORRYBFweEX9pUj4E2BBYuzeBSZIkSYNdlWT9w8D6QAA7dFLP2WAkSZKkXqiSrP+Mouf8D8ALwOKG8hHAxsB+vQtNkiRJGtyqJuvXZOa1nVWKiK0rRSRJkiQJqJCsZ+adETGyG/XWrxaSJEmSJKg2GwzARhFxdUTcXdsRERtHxJkR8eEWxSZJkiQNaj1O1iNiE+CPwNbAmNr+zLwNOBjYLSJ+2I2pHSVJkiR1okpCfRwwFzgFmFNfkJkLgAOAXYAjex2dJEmSNIhVSdbfAmybmYcCzzYWZuZDwGxgr17GJkmSJA1qVWaDeSAzby+fLzOXekSsAowDurwJVZIkSVLHqvSsP95F+dFlu/+u0LYkSZKkUpVk/bKI2L9xZ0SMjIgTgU9T9Lif19vgJEmSpMGsyjCYs4CLImJ7YI2I+DrwSuAdwISyzh+Ab7UmREmSJGlwqrIoUgIfi4j9gLWALwBRFv+LIpn/VmYualmUkiRJ0iDU42Q9IgKYlplnAmdGxChgIjA3M+d0frQkSZKk7qoyZv1S4L6I+BJAZj6XmY+aqEuSJEmtVSVZ37J8nNHKQCRJkiQtrUqy/i2KlUvP6axSRFxYKSJJkiRJQIVkPTOPBw4HToiIpgsfRcT6wM69jE2SJEka1KrcYPp3YDQwHvhkRDSOVR8OrMaSGWIkSZIkVVBlnvWrgIPrvp7UQb2s0LYkSZKkUpUx6ycBM4G1gWGZOaRxAzYCXmhloJI0GETEgG2SpPZTZVGkhyPixMz8dyd1/hYRZ/UutBVfq/45FutUSVoR9Ob3OSL8eyBJK5gqPetk5rciYlpE7FDbFxHrRMRadXUOaUWAK7LM7HLrTj1JkiStmCol6xFxMnAf8N263TOBPSLiVxExtRXBSZIkSYNZj5P1iNgf+Ex57EvjODLz2cz8CvB74NaIWLtlUUqSJEmDUJWe9QOAS4E3AI81Kf8exQwx3+hFXJIkSdKgV2XqxtWAzTNzXkQsaizMzIUR8Rywba+jkyRJkgaxKj3rd2XmvI4KI+JNwDhgaOWoJEmSJFVK1h+OiInl86XmHoyIccCZFAsi/aWXsUmSJEmDWpVk/ZvAuRExmXKV0ogYGxEfBW6lGMu+GPhqy6KUJEmSBqEOx6xHxBjgDODRzDyitj8zb42IHwD/BEZFxGPAZJbMDvMCsH9mXtunkUuSJEkruM5uMP0ysBvwN+CI+oLMvDQirivLN6eY/WUuRc/6BZn5UN+EK0mSJA0enSXrHwVuAj5cvzMiRmfm/Mx8CjilrwKLiLHA/sChmblaxTZOBD7fsJcTPFgAACAASURBVDuB12fmXb0MUZIkSepTXY1Zf3uTXvJrutNwRHy361pNjxsZEYcBtwEnAi+v2M4k4FPAoobtChN1SZIkLQ86S9avzsznm+yPJvua2aZCPAALKMbKbw4srNgGwCHAcZk5rGF7Ty/alCRJkvpNZ8NgfhQRF1GsVvoMReKcwNiIeBsdJ+0rAe8A1q0SUGYuBp4DnouImcDUnrYREeOBXYCNqsQgSZIktYMOk/XM/ENETAPOA0Y1FF/TdyEtpWrP+kEUM9ScFxG/B36ambNbF5YkSZLU9zrrWSczz46Iy4H3Aa8GJgI7AVd0cthIiiEsa7YqyJ6IiNHAZ4GVgQ+V20kRcUxmnjYQMUmSJElV9Hie9Yi4OTP37KzRciXTR1sWZc+MoRivvirwVmB7YAJwakRskJn7DlBckqQeiOjuLVKtlZkDcl5JaqazG0xr86zv0LD/T101mpnPAif3Iq7KMnNmZv4oM0/JzJ2BVwGXlMX7RMReAxGXJKlnMrPy1pvjJamddJas1+ZZ36lh/1HdaTgzj6kaVCtl5mMU38t55a4vdFQ3IvaNiOkRMX3mzJn9Ep8kSZLUkbabZ70vZNFVcjDwOPDqiJjQQb2zMnPTzNx01VVX7dcYJUmSpEbtOM96n8jMecBF5Zed3lgrSZIktYO2m2e9j90HPJGZTw50IJIkqXVadUOy9y2o3bT7POutthpw7kAHIUmSWqs7SXZEmIxrudPu86wPAYiIoZm5qL6gXKX0Iope/z0ayxuV9f8LeH8L4pIkSZL6XJdjtzPzCeDM2tf9Nc96REymWIUU4HXAHQ1VtgN2LJ9/G5heHvcLYDPgSODCzFwcEWsBnwf2KqeVlCRJktpeV7PBNNPn86xHxJUU48trw2/+LyIak/XrgfuBm4E76/ZfDMymeINxV0ScQTGG/rOZ+Z+qMUmSJEn9LRy71dymm26a06dPH+gwHF8ndcHfkSW8Fkt4LdSMrws1apfXRETckpmbNiur0rPe3ZNe1HUtSZIkSR3pcMx6RLwGGJ+Zf2nYv2UXbQ4BXg98sPfhSZIkSYNXZzeYXgNMjIipmflU3f4fAy/v06gkSZIkdZqs3wq8AmicPeWHwOeAv1PcyNk4ZeJQ4FXAlBbFKEmSJA1KnS2KtEMHRecBK2XmIR0dGxFjgX/2MjZJkiRpUOvxDaaZeQ/wiy7qzAU+UzUoSZIkSRVng8nM67pR55IqbUuSJEkqdLmCab2I2Bj4GPAmiptMF1CsVHo98KPMfKDlEUqSJEmDVLeS9YiYQrEi6Hvqd5ePrwe2A46JiO8Bn8vMBS2NUpIkLSUiuq7UA+2wMIykZXWZrEfEGsB1wFosSdAfAh4HkmLWl2llWwcCb4iI/zZhlySp73Q3uW6XFRolVdOdMesXUSTjs4AvAWtk5lqZuVlmbp6Z6wAvAw4FngDeApzSR/FKkiRJg0anyXpEvAN4K8Wc6htn5tcz89HGepk5MzNPATYCbgL2joh1+iJgSZIkabDoqmf9fcDTwLsy8z9dNZaZM4GdgEeAXXsfniRJkjR4dZWsvxE4MTMf6W6Dmfk0cAywVW8CkyRJkga7rpL1NYGLK7T7c+AVFY6TJEmSVOoqWR/eneEvjTJzPjC/WkiSJEmSoOtkfVG/RCFJkiRpGV0l66tERI9WOa2zWsXjJEmSJNH1okjDgX0j4uEetjsGmFwtJEmSJEnQjRVMgdP6PApJkiRJy+hOsr4QmEH3x68Po+hVH1E1KEmSJEldJ+t/ArbLzBd60mhEjAb+t3JUkiRJkrq8wfSKnibq8NLUjZdWC0mSJEkSdJ2sn92Ltr/fi2MlSZKkQa/TZD0zZ1VtODNnVz1WkiRJUtc965IkSZIGiMm6JEmS1KZM1iVJkqQ2ZbIuSZIktSmTdUmSJKlNVUrWI2JCRBwTEefV7ds4Io6MiGmtCk6SJEkazLpawXQZETEFuAFYG3iktj8zb4uIZ4FLI+KMzOzNHO2SJEnSoNfjZB04niJRvx0YV1+QmfdFxH7AjRHxTGb+rAUxSpIkSYNSlWEwOwKfyMxNgCcbCzPzL8A84IhexiZJkiQNalWS9fmZ+aPyeTYWRsRKwErA+r0JTJIkSRrsqiTr/+qifHdgOPB0hbYlSZIklaok69MjYotmBRGxI3AyRY/7Zb0JTJIkSRrsqtxgegLw24j4GTA+IrYD1gXeA2wLBPAf4Msti1KSJEkahHqcrGfmnIh4L3Aq8BrgtxQJes3vgH0zc2ZrQpQkSZIGpyo962Tmk8AuEXEw8CZgEjAXuDUzH25hfJIkSdKgVWVRpMOB/YHDynnUf9fyqCRJkiRVusH0CGANYIMWxyJJkiSpTpVhML8F3gl8s7NKEXFQZn6nUlSSVhi33347O31wJ15c9GKftB+jgtXWXq3l7e61x14c/+XjW96uJEk9USVZ3xP4PsVKphc3qxARY4DjAJN1aZC75557eP7lzzP202P7pP21WKvlbc6/dT5/uuFPLW9XkqSeqpKsnwY8DxwfEbsDjzWUDwc2B1buZWySVhDDRg9jxBojBjqMblvwnwUDHYIkSUC1ZH0S8F6K6RrX7qReVopIkiRJElAtWf86sAPwKYrFjxY1lAfFzacn9y40SZIkaXCrsijSzRFxSWae30m1ayJi1+phSZIkSaoydSOZ+Ylu1NmsStuSJEmSCpVWMAWIiLWATwNvA0YDDwKXAj/OzPktiU6SJEkaxCol6xHxAeACiiQ9yt3rU4xl/1JEfCwzb2pNiJIkSdLg1ONkPSI2pphfPSgWSLqG4kbTF4BVga2AyyNi88x8oHWhSpIkSYNLlZ71LwF3Ax/NzLublJ8TER8GDgf2601wkiRJ0mBW5QbTLYAdO0jUAcjMSyiGxUiSJEmqqEqy/nBmPtyNei+v0LYkSZKkUpVkfUFEjOqsQkTsXbFtSZIkSaUqCfXlwIURMaGxICI2iogzge8Bv+htcJIkSdJgVuUG01OAa4HHI+KvwExgIrAmsHpZ537gqy2JUJIkSRqkepysZ+bCiHgHcCKwDzCiocoVwD6ZOacF8UmSJEmDVqVFkTLzOeDgiDgWeCfwCmA2cG1ns8RIkiRJ6r5KyXpNZj4FXNSiWJYSEWOB/YFDM3O1CsdPBI4DtqRYwOlvwOcy87GWBipJkiT1kUoztkTE2yLi2xExtW7f+hFxYkRs3ZuAImJkRBwG3EYx1KbHU0BGxBSKcfVjgDdm5obAv4G/RMRavYlPkiRJ6i89TtYjYnPgKuAg4P21/Zl5F0VP9lci4vhexLQAOAPYHFhYsY2zgTWAgzPzxXLflyl62C+IiOhFfJIkSVK/qNKzfiwwH/gN8Mv6gsycC3wSOCIiPlkloMxcnJnPlUNsZvb0+IjYEngPcEVmzqtrdyFwGbAV8K4qsUmSJEn9qUqy/hpgvcx8d2Y+0liYmfcBjwCH9DY4qvWsf6R8vKVJ2U3l4+7VwpEkSZL6T5UbTGdk5oyOCiNiKDAOWLVyVL2zffn4YJOyf5WPb+mfUCRJkqTqqvSsz46IzmZn2R8YT9G73q/Ksei1G0ibnX92+bh6RIzqn6gkSZKkaqok66cDv46IN9bvjIg1IuLbwMlAAue1IL6emgQMLZ/PbVI+r+75hMbCiNg3IqZHxPSZM3s8XF6SJElqqSormP4yIt4C3BwRjwL/AVajmH1lCMWMK/8LnNDKQLtpZN3zBU3K67/fFxoLM/Ms4CyATTfdNFsbmiRJktQzleZZz8zPAx8DHgc2oxh6MhT4B3AYsGPdlIn9aVbd85WalI8pHxcBz/R9OJIkSVJ1lVcwzcyfAD8px35PBOaUUzcOmMycFxGPAKtT3OB6d0OVyeXjfzLTnnNJkqQVwPXXX88111xT6djjj+/58kDvec972GCDDSqdr6cqJ+s1mfkc8FwLYmmVa4FdgHWB6xrK1ikff9+vEUmSJKnPfOmwwxh+//2stlKzgRUd+/hqq3Hvd7/bo2Punz+fe//2N35w8cU9Oq6qXifrETEROBh4M8XQkgszcyCT4R9QJOtbAOc2lG1aPl7arxFJkiSp72Sy4+TJbLryyn1+ql/PnMkj/ThAo9NkPSK+RzHDChQzvPynHK9eK18PuJriBlMobi7dJSJOyszDWxDfkPI8QzNzUUNs44GLKN4g7FErz8z/jYg/Ae+NiIMy84Wy/krA+4AbMvN/WxCbJEmS1Ke6usH0V8DOFDdrfrkhUR9O0UM9lSJJv56ih/1s4LCI2LE3gUXEZJaMMX9dkyrbATsCuwIbN5TtTnET6f9EYQRwBvA88PHexCVJkiT1l66GwawP/CYz39uk7LPAayl63H+cmbvWCiLiDuAzwK+rBBURV1IMWaktXPR/EXFfZm5YV+164H7gaeDO+uMz84GI2AI4CbiDInG/DtgkM51AXZIkScuFrpL1d1GsSLqUiJgAHFF++QTwqYYq3wO+UDWozPzvbtR5jOIm0o7KHwQ+VDUGSZIkaaB1NQxmfGbe22T/EcDKFL3qxzRO2ZiZi4GnWhOiJEmSNDh1lawPb9wREdMoxqYncA/w/Q6OdR5zSZIkqRe6XMG0TM7rnQmMLJ8f1mxxoYjYEHist8FJkiRJg1lXyfpPgZ9FxGsjYmI5leO2FL3mv8jM33Vw3P8AV7UwTkmSJGnQ6SpZPxFYCPwdeBLYp9x/V93zl0TEOhFxCcWNqX9vYZySJEnSoNPpbDCZuSAitgEOB94NDAWuBL6SmXPq60bEycCrKeZc/z3F/OxX9kXQkiRJ0mDQ1dSNZOZzwJfLrbN6n21VUJIkSZK6kaxL/SkiKh3X5D5nSZKk5Z7JutpKZ0l3RJiUS5KkQaXLqRslSZIkDQyTdUmSJKlNmaxLkiRJbcpkXZIkSWpTJuuSJElSm6qUrEfEZhFxdUTcXbdv44g4MyI+3LrwJEmS1BsR0a1N7anHyXpEbAL8EdgaGFPbn5m3AQcDu0XEDyPCXntJkqQBlplLbc32OTVy+6qSUB8HzAVOAebUF2TmAuAAYBfgyF5HJ0mSJA1iVZL1twDbZuahwLONhZn5EDAb2KuXsUmSJEmDWpUVTB/IzNvL58t8ZhIRqwDjgJG9CUySJEka7Kok6493UX40RY/9vyu0LalU9WYfxx1KkrTiqDIM5rKI2L9xZ0SMjIgTgU9T9Lif19vgpMGs2c0/Xd0cZKIuSdKKpUrP+lnARRGxPbBGRHwdeCXwDmBCWecPwLdaE6IkSZI0OPU4Wc+i6+5jEbEfsBbwBaD2ef2/KJL5b2XmopZFKUnLiccff5xnnnlmwM5/9913d12phYYPH866667br+eUpMGkSs86AJl5JnBmRIwCJgJzM3NOF4dJUq898qFHmPfovGX2j5k6htV/uvoARLTEq179aoavPJaBWF9k2ISxvHX7/+7Xc86d8RTXXP1Htthii349ryQNFj1O1iPirMzct/Z1Zj4HPNdQ50DgN5n5QO9DlKSlzXt0XtPx+e2wAt+8uXN57bcPIIb0/7pwq/X7GeGpb1/KnDn200hSX6ny3+QNXVXIzNOBL1ZoW5IkSVKpy571iFiLYmx6zbiIeBtLxqk3a3ND4CPAp3odoSRJkjRIdWcYzAJgR+BgYKVy3zXdOO7KijFJkiRJohvJemY+BnwxIi4BfkmRsP+6k0MWAPcBZ7YkwuXUbbfdxpVXtub9ykknnVT52OHDh7PffvsxatSolsQiSVJ/O/ILR3H66d/pdTvDGM7KYyZ0XbEDu+++J6eecXKv45B6ots3mGbmLRGxFXB2Zu7ZhzGtEI75/OeZdeONvGL48F61s/Po0dx2/PGVj79u4ULWXXdddtppp17FIbWTMVPHNL2ZdMzUMQMQjaS+dsdf/8Y7R36K9Uf+V+8aqp6nc98Lt3LHbX/q3fmlCno0G0xm/isiuhyHHhEbZebt1cNaAWTyrhEj2HLkyN6108se8Yd7+WZBakcDPT2juiczOe5rX+Nf/+r/icFi6DB233Ovfjvf2DFj+MYJX2fs2LH9ds7BZqUYxeih4wfw/KMH7Nwa3KosivTPblT7TkRslZmLK8QkSVoBZCbHHnMMq2zav3O/A0zaeGt+/feH+u18L9x/G7vt+nE233zzfjunpMGhyjzr53ZSPBRYG/gvYFfgBxXjkiStACKC8etuNNBh9Llnn7h/oEOQtIKqsoLpHt2sdzQm65IkSWojH7nrLh599tll9k8dN46frL/+AETUuSrJ+mLgAODeDtr7MnAisOxVkDToTJgwgfn3zGf0zNEMW7XKn5z+lYuTBTcsYPLEyQMdiiSpDzz67LNtuwp2M1X+c96WmWd1VBgRCZwAvKNyVJJWGNtttx2f3//znHjAiazyzVUYsdaIgQ6pQ7kweebrz7DmnDU554pzBjocSZIY0tMDMvNNXZRfDawB/L+qQUlacUQERx1xFKd87RRmfnomz/39uYEOqanF8xbz9BefZuPhG/Pnq/7MpEmTBjokSZJ6nqx3JSJGAWOAnVvdtqTl11577sUlF1zCM0c+w9wb5g50OEt58ZkXeeqQp9jx9Tvym0t/4yJikqS2UWU2mE90UjyJIkkfBzxSNShJK6YddtiBK399Je989ztZvM9ixu84cHMm1yx4eAFPf/5pDvzEgRx/3PFtO2ZRg8f8+fO55557Wtrmrbfe2us21l57bSZOnNiCaCT1RJUx6+cDy47KX6L2n+4rFdqWtILbbLPNuOlPN7HVtlsx+5nZjP/4+AFLkJ+/93mePvxpTjj2BA7c/8ABiUFq9MUvHsnFF/+cceNWaUl7kyZNY+ede7dA1HPPPcvGG7+e3/zmspbEJA2kqePGNf2/M3XcuAGIpmtVp2a4FbiTZZP2BcDjwG8y86beBCZpxfXqV7+aW//vVrbabitmPzWblQ9emRjSvwn7vJvnMeurs/jBWT/gAx/4QL+eW+rM3Lnz2HLLw9h88z0GOpSX/OMff+Tee08f6DCklmjH6Rk7UyVZfxzYPDMXtToYSYPH1KlTufnPN7PdTtvxwFceYMKXJjBkRMtvo2nq2SufZe6pc/n1z3/NVltt1S/nlCSpiir/GQ8zUZfUChMmTOC6K6/jzWPfzDNfeIZF8/r+T8ucS+aw8MyFXP/H603UJUltr8rUjT/uTr2I+GvPw5E02IwcOZLLf3Y5793kvTz16ad48akX++Q8mcms781ipd+uxPQbprPBBhv0yXkkSWqlDofBRMSWFdscCmwMvK7i8ZIGmaFDh3LOd89hwR4L+N3Xf8ekb7Z+jvNnr3yWBb9ZwJ333Mnkya5OKklaPnQ2Zv0iYLX+CkTS4HbZZZfxy1//krlPzeXJtzzZZ+c56LMHceG5FzJ8+PA+O4ckSa3SWbJ+LnAk8DdgDrC4m20OBV4FTOldaJIGi++e+V2+cMwXmHTiJKa+ZmqfnWfxc4u56tir2O7d23HFz69gzJgxfXYuSVL/iSFDeH5xd1PV3nlh0SJiSP9MiACdJ+tnA1My81M9bTQixgD/rByVpEEhMzn62KM59bxTmXzaZEasMaJPzzdk1BAmHj+RO0+6ky223oKrf3u1Q2IkaQWwy557cvpRR/GWCRP6dO2OFxYv5mezZ3P2Hnv02Tkadfi2IDMfAs6r0mhmzgN2rRqUpBXfokWL2Gu/vTjjp2ew6hmr9nmiXhPDggmHT+CJ9Z9gky024cEHH+yX80qS+s4n996bIVOm8PunnurT81wyYwYbbbYZ73znO/v0PPU67cPvzcJGmXl11WMlrdief/55dvrATvzq9l+xyrdXYdikquuzVRMRTNhvAgvfvZBN/2tT7rjjjn49vySptYYMGcIZ55zDWTNmMH9R30wDPOOFF7jkySf59hln9En7Hak84CYi1oqIb0XEXyLi7xFxRUR8MiJGtzJASSuWWbNm8bZ3vI3pz09n4jcmMmRM/437azR+5/GM2H8Eb93mrVxzzTUDFockqfc233xz3rnDDvxgxow+af/MmTM54KCDWGeddfqk/Y5U6s6KiA8AFwCjgdrAoPWBHYAvRcTHetMrL2nF9Mgjj7DVdlvx7IbPMvHAicSQvhtX2F3j3jGOoROGstPOO3Hed8/jQx/60ECH1CMPfv5M5s1Y9mPfMVNWYdpJ+w1ARJI0cL5x8sm8br312GHCBNYcNapl7f51zhzuXLCAXxx9dMva7K4ed2lFxMbAxcBI4LfAF4CPAu8H9gWuBy6PiLVbGKek5dzdd9/NG7d4I/PePo+VD1q5LRL1mtFvHM0q31yFvQ7ai9NOP22gw+mReTOeIjOX2Zol8JK0oltttdU44qijOH3GDDKzJW2+mMlpM2bwrdNOG5BZxKp8/vwl4G5gw8zcKTO/mZmXZOZlmXlOZu4GHAwc3tJIJS23brzxRrbYaguG7D6E8buM79M79asaud5IJn9nMkedeBRfPPKLLfsjL0nqX5/57GeZOWIEN8ya1ZL2fvXkk0x55Sv58Ic/3JL2eqpKsr4FsGNm3t1Rhcy8hGJYjKRB7o477mC7d2/H2C+OZdy7xg10OJ0asfoIJp8xmbMvP5sjjjlioMORJFUwYsQITj3zTE6fMYMXejn3+uyFCzn/iSc4/eyzB6yjqUqy/nBmPtyNei+v0LakFczdd9/N2E3GMmaL5WMBomEThzFq91Hc8JcbBjoUSVJF22+/PRu+6U38dObMXrVz7owZfGSXXdhwww1bFFnPVUnWF0REpyP2I2Lvim1L0sBrv1E6kqQeOvV73+MnM2cy44UXKh3/z3nzuO7ZZ/naCSe0OLKeqTIbzOXAhRGxd2YuNRgoIjYCDgA+CZzcgvgkSZ0YM2WVph/NjpmyygBEM7Ce+N15zJ/19DL7R0+YxMu233MAIpI0kNZZZx32P/BAzvzRjzh6jTV6dGyWN5V+9etfZ9KkSX0UYfdUSdZPAa4FHo+IvwIzgYnAmsDqZZ37ga+2JEJJUoecnnGJ+bOebnpjcDve0Cypf+zzqU/xzW99i98/8kil43fdbbcWR9RzPU7WM3NhRLwDOBHYB2hcI/wKYJ/MnFM1qIiYCBwHbEnxgfTfgM9l5mM9bOcA4PQmRTtk5m+rxtfXPjJnDo/On7/M/qmjR/OT8eMHICJJkpZPJz21C0/OXzZ9mDx6NT6/ykUDEJH601ePPpoPTp3KgVOn9vjYYx96iJO+8Q2+8tWB7X+uNK48M5/LzIMpetJ3BY6gGP7yusx8T2Y+UTWgiJhC0XM/BnhjZm4I/Bv4S0Ss1YN2hlPMAb+oYbujnRN1gEfnz286b3KzBF6SJHXsyfmPNf2f2iyB14rl5ptv5orLL2f3KVMqHb//lCmcevLJPPjgg60NrId6dRNoZj6VmRdl5jcy83udTefYA2cDawAHZ+aL5b4vU/SwXxDd/zxzN+CKzBzWsG3UghglSZLUphYvXswBe+/N3quuythhVUZ9w8tWWomdJ0/mswce2OLoeqbKCqbj67e6/Z+MiJsj4saIqDRrfERsCbyHIsmeV9ufmQuBy4CtgHd1o52hwGEUQ3UkSZI0iFxwwQW88NhjbD95cq/a+eiUKdx8/fVcddVVLYqs56r0rM8CngH+DHwKICL2Ac4C3gisB/woIrat0PZHysdbmpTdVD7u3s121gFOjYjPlENrJEkrsNETJhERy2yjJwzsTA6S+tfs2bM5/LDDOHjKFIb08gbzlYYM4YApUzhon31YuHBhiyLsmWqfC8A3MvNIgIhYGahNQLlXZp4fEVsDxwJ/6GG725ePDzYp+1f5+JbOGiiHyRwJjATeW24nRMSJwHGZuaiHMUmSlgNOzygJ4CtHH81mo0fz2rFjW9Le2yZO5PJ//5vTTzuNQw49tCVt9kSVnvVngKPqvj6AYurGSzLzfIDMvAYY3ZNGyyS7dgNps/l1ZpePq3exKNNo4HjgYOCHwNMUifsxwK8iouoblH4zdfTopr1DU0f36JJKkjToTR69WtP/qZNHrzbQoakP3H333Vxw7rns/bKXtazNiOCgl72Mrx57LDNmzGhZu91VJXG9LzMXA0TEGOAQillWjqlVKBPvV/aw3UnA0PL53Cbl8+qeTwCea9ZIOdb9x+WX34mICRRzvh9EMd79mPpY29FPxo8Hp2iUJKnXPr/KRTD41ggblDKTg/fbj11XXZVJw4e3tO1po0ax7YQJHH7YYZx74YUtbbsrVXrW50TEJhExBPg2sCpwUWb+s67OpygS6p4YWfd8QZPy+jcW3V43NjNnldNMHlvuOiQiGueGByAi9o2I6RExfebMmd09hSRJkgbYZZddxoN33sn7V121T9r//+3dd3gU1frA8e+bQiB0CCiggKgI2EBQQAELCmLBjliuSLErP8tVsberXlGs1wIqCnZUxKsIiFgRRcF2UeyCqKiA0klIeX9/nFmzLptk+0yS9/M8++xm5syZMyezM+/OnHPm1JYteXnaND788MO05F+RRIL1y4FZwEpgBLAM+CeAiLQWkRuBexLId3XY57wo8+t776W4pjjxuh74DGgIdImWQFUnqGoPVe3RIk3/aGOMMcYYk1qbNm3i/LPP5tyWLcnJSmpk8go1yMlhZMuWnD1qFGVlZWlZRzRxb42qfgh0xQXt5wBdVTV0Gfp4XBvxS3EPJIon3w2Ut1WPFimHxt75UaM9T7rq/BV4yPsz8O3WjTHGGGNMbMaNHUsHoEfjxmldz6CCAgp/+YXHMtgUJqGgVVV/Bh6IMv2OJMvzFnAisAPwdsS8Dt77q0nk/y1QDHxTVUJjjDGmuho7dndWrvxxi+kFBW255JJPfSiRyZQLRp/Pd998W2maXLIZPOiwStN06tKZseNuTWXR0uq1GTM4PAP9/bJEOKRhQ+bMmMGwYbGMJp68hK8weyOyHIgbVx3ccIuvqeqaCheq2mRcsN4bmBgxr4f3/kIS+bcCnkuyjMYYY0ygrVz5I9FuQsf+wnigaQAAIABJREFUEHBTXd15z130y9sZ9+D36HrndWbNG0srnF9GGXe99mq1CtZRJTtD+3eWCMTfyCNhCQXrInIccB9uBJdwm0TkRlW9OZF8VXWWiLwDHCEi56pqkbe+POBIYJ6qzvKm5QCP4IaNPEFV11VR5lzgOOD0RMpmjDHGGFMdtM/ZKqkfZiVaygel1gghKOJusy4iB+OGRmyOG7XlJeAO4FZgDnCViNyfRJmG4TqR3iROHdwPg0LgpLB0XYGTgUOBgWHlu0NEVorIhaFRX0SkALgFGKOqy5IomzHGVKpuvbr8MW0uRctX+V2UtCpZv4k/5nzE+qXLybdnQBhjTNokcmX9BlyQ/z5woqouCZ8pIq2A50RksKr+N97MVfUHEemNC/4/wwXubwN7hHVkBfgCWIAbInJu2PT/Av2AfwH/JyKvAR8DV6rqxnjLY4wx8fhw/gdMePghJo97jJzmjcjdsyONenUmp0H1D2jLSkpZ/+m3bJ7/NWu/+J4BAwdyxmNP0qdPH7+LZowxNVYiwfrOQAkwRFV/ipypqstF5ChcE5W4g3UvjyW4JiuVpdkI7Bll+htA90TWa4wxydp555256/Y7GDf2Vl577TXGT3yIWWMepFGX7aiz10406LoDWTnZVWcUEKrKpu+Xs+n9xaz9YDGdu3ThrNP+j2OPPZbGaR51wZhwRRr1WYgZXL9d7zP+SCRY/wZoEC1QD1HV370nhxqzhZ9//pl58+YltOyzzz4bc9qGDRsycOBA61BlfJGTk8PBBx/MwQcfzNq1a3nuuee4/+EH+WLyqzTaqzP1enemXofWgd0/N69aw7r3vqDw/S+pn1OHM08dwbDxT9O+fXu/i1YrrFv3W1LLFxS0jbpvFRS09aU8yTrngjM58biTaZa9NR3qds34+pcWfcH0wv/w0D/HZ3zdxiQSrF8OPCsijSsaVUVE8oHtkyqZqbEuvfj/+OqTt9h2q/pVJw7Tf48mPHXfxTGnn7PgN+a9v4Cdd9453iJmzDPPPM1HHy+MeznJgkvHxF4XOTm5XPzPS2jSxH5D+6FRo0aMGDGCESNGsGTJEiZNnsyDj07kz+Ii6vbqRMPeO1OnwP+r1KWbili74CtKPviajT/+xpAhx3HalJvo2bNnYH9U1ESjR5/N4YcfRVHRHwwceB25uXWrXihCqoZnLCsr5a237mD+/Ad5+unHU5JnIgYNGsRzL07h2COP50i9iM71emds3d8WLmTKxpt44pnJHHrooRlbrzEhcQfrqjpdREbi2oSfV0Gyq4AfkimYqblKS0o4+/AChuzfMq3r6XXeJkpLS9O6jmRddMloOh24mvpN4guEDj+/Dl8W3x1z+oVTs+m+Rw+OPvroeItoUqx9+/Zcc/XVXH3VVcyfP58HH5nIlBseJ3/bluTttyuNenTKeJkKf/qdDTMXsvrjr+nTty9nXn0Thx12GHl50R4mbdKtW7du/O9/H3PqqaMYP34AQ4Y8RMuWHateMMXWrFnO88+fQdOm8OmnC9lmm20yXoZw/fv3Z+Zr0zlkwGEU6Vl0zT8g7ev8fNNcXiq8kxenT2XfffdN+/qMiabCYF1E1gANKltYRM6uZPZFiRbKmNqk34l1KNg2PY9GDln+uT20N2hEhJ49e6KqbC4q4onHHqf11s34/J6pvpWpe8+9OGPESAvUA6Bp06ZMm/Yc48dPYMyYQxk48Fq6dz8xY3c4Fi+exbRpoznvvLO5+uoryc4ORj+Lnj178ubc1zlwvwFs3riRvfIrf7BPMj7a+CqvlTzEq2/MpEePHlUvYEyaVHYGfwQYDWwAVuM6lcZqNVCrG3bl5uXxs89XdTer8ltxMbm5ub6Wwxjzd0uWLOHRSZN48NGJbCwtpm6vTuxw61nUKWhMk5P7+1Km0k1F/LrwK8654QqGjxrJcUOO47ThI+nVq1dSAWJ+/fqs++QNctvsSF5BmxrXnGbz2lUULfuK9at+T3mHWxHhzDPPoE+ffTjmmOP5/vs3Ofzw26hXL31NpkpKipg16zq+/vplXnzxOfr27Zu2dSVq11135d3577B/3wMp3LiefvlDU76O9za+wPs8x9vz3qRLly4pz9+YeFQWrN8J7AocqNEeg2Yqdf3YsfTv25eCwkIOqht/e8NkbVblmqIiOu+9NwcckP5bhcaYyq1Zs+avTqaLFy92nUxPOYAmHVoFIoDNrpdHkz67QZ/d2LxqDTPe+4IXjj+G/OxcTjt1BMNOOYXtttsurjyzsrL44vPPeeyxx5jw8ET++OR1clvvSL22ncht2DRNW5J+pYUb2fDjV+hv36GFGzj55JMY+dj9dO7cOS3r22WXXfj44w8ZPfoC7rtvf4477kHatk39oGcrVnzLlCmj2GWX9ixa9AnNmkU+9zA4dthhB95f8C779TmAwnUbOKjeiJR8j1SVtzY9yed5c5g3d27c+7wx6VDhvXdv+MQHEg3URaT6HolTYJdddmHOO+/wADC7sDCj6w4F6i323ptnX3zRrqwb45OSkhJmzJjBkccdw9bbtOGKB+/i9z23od24s2h+Un/ytw/maDB1mjem+WG9aX3DqdQddgDj581glz260n3vXjz00EOsWRN1bIGo2rZtyxVXXMGS777l9VkzGNK3G+vmvcCad55n7TefUFpUPYbDKyspZv2PX7L+g+msmD2Z/bYv4KmJE1jx26/cfeed7L777mldf35+Pg89NJ57772VJ544gbfeuouysrKU5b9w4dNMmDCIiy8+jZdeeiHQgXpImzZteO/Dd1nRchEvbbybMk2uPlSVWZsm8H2Td3l/wbsWqJvAqLQhq6rGPk7elj4G2iexfLUXCtgP7NsXLSxkQAausG9W5eqiIrbaZx+efuEFC9SN8cGnn37KQ49M5PEnn3APRtqrI+1uOa3aPRhJRKjXoTX1OrSm6fH7seLTb7nyobs574LzGTBwAGeMGMWAAQPIyam6T4SI0L17d7p3785dd97B7NmzmfDQw8yaNYkGrdqRtfUO5LfugGQHp3+FqlL4+0+U/PING376hq7d9uCsay/nqKOOokGDSrt0pc0xxxxDjx496NVrb6CMffe9IOk8P/nkeV566Z/MnfsO3bp1S76QGVRQUMA7779Fz+69mPfn8/TJr/QRLZX6YNPL/JA/n4UfLKgWP1ZM7ZGWo6KInAZsm468q5tddtmFOXPnckCfPmhhIQPTGLAXeVfULVA3xj979dmbr779hvxenSm46FjyWjX3u0gpkZWTTaPuO0H3nWiyfiMfzl/MvIvOpXTVOj5873223z720Xpzc3M55JBDOOSQQ1i7di3PP/889094kEWvvEH9bTuS23pH8lr4175985pVFP70FZt/+pqWBQWcftpITj7pJFq3bu1LecKtWbOGCy+8hNzcpkyffj3Tp1+fsrxHj76QZ555IhDbGY9nnpnC78tX8eWG+3hp1X3JZbYKJj/6GOdf+H+pKZwxKZDSYF1E+gGXAQNSmW91t/POO/P63Ln079sX0hSwF3lX1Fv16cNTU6daoG6MTxa8N5/OD16MVKOnlMYrp0E+zfp3h/7dWXXHVL799tu4gvVwjRo1Yvjw4QwfPpxly5bx2GOPcefd97C+uITGvQdntG27qrL67WcpXL2K004/jZHD709785Z4zJ8/n2OPPYH27ftz5pmzyc2tl7K8y8pKefPN29lttz149NGHOOyw9I2ykkq3jh3HbTfcwciG4yholvzQkn+W/Mot117K6tWruea6qwPZTK0qLZoVsGrTOgqyGyWcx6qytbQsSO/wyiZ2SQfrIpILnAj8HxA6qglgnVLDhAL2A/r0SXnAXqTKVUVFtLZA3ZhgyKp+J/iEpWhb165dy+zZs3nhvy+xfv166m+7Ez9Nn5iSvOPVsFkB01+ZQZvWrSkoKKBNmza+lCOkrKyMW24Zy9ixtzN48O3sskvqA+msrGwOOOBittuuDyNGnMGQIbMZN25sYIfwVFWuuOxKJt33JCMb3k6TnNQElk1ztmZUwzt45O4x/PnHn9x5zx3VLmC/5vpruf3ym+lblliwrqoszl3OdTf+K8UlM4lKOFgXka2As4EzgBa4AB1cW/VvgMQbjtVQXbp0+Stg18JCDk5BwB4K1Nv07ctTU6fG1HbUGGOCoLi4mFdffZXxDz3Ma6++SoNW7ZCtd2CrQ0Yi2Tk07LqfL+VSVTau+InbHnma666/gd27duOs00dx9NFHZ7yt+q+//srQoSfzyy8bOeusOTRtmt4Wpttt15tzznmLadNG06NHL55//hk6dsz8A5kqU1ZWxjlnnseMKXMY2fAOGmSn9snMDbObMbzBOB5/4gpWrx7BxEkPBWac+ViMGjWKf117A79vWE3LBOrm19I/0cY5nHLKKWkonUlE3E9iEZEeIvIYsBS4Egj9nH0Z6Kuq3VV1KLAkZaWsQUIB+0MivJbkKDElqlxZWGiBujGm2lBVFixYwFlnn0NBy60YduZ5vPfTOloMHEaDPQdRf9sdfe9kKiLUa7ktDbseQMtBI/hOG3PRdf+m5VZbc8xxQ5g1axYlJfE8eiQxM2fOZNddu5GX150RI/6b9kA9JD+/KSecMJmOHU+mZ899mDRpUkbWG4uSkhJOHnoKc559l+ENbkt5oB6Sn9WQYfVv4cPpizjmiOMoKipKy3rSIS8vjxtu/heLc5f/bfqLJR8yaf2cLV4vlnz4VxpVZXGd5dw09maLKQIkpv+EiGQBx+KauvQKTQbWAJOAfVV1cMRiB6WqkDVNhw4d6NypE9e99x7XpSC/R446qsZ+qbqM+Jgfl6/bYnrbVg35YmL1GrXAmNps6dKlTH7sMR58eCJr1q0nt01HGu1zVODHW8/KyaVB252g7U7kF27krR++4s2RZ6CFGzjppBMZOXw4u+++e0qbSmzevJkxYy7nscee5phjHmL77fdJWd6xEhF69RpJu3a9uOKKkcycOZsJE+6nYcOGGS9LSGFhIcceOYQlH6zglPr/pk5WekdYy8uqx0kNbuTZeTdyyIDD+O8r06hfv35a15kqw4YN47qrr+XXP/9k6xz3HVtduJZoo3GLyF/Pq/+5dBV1CuoxdGjqHzRlEldphCcizYDTcc1d2lDe1GURcC/wuKpuEJF5kcuq6vcpLmuNUFhYyOCDDyZn8WLe2GorcpI8wP9QUsI/zzuP7Oxs/lEDb1n9uHxdxQcXY0zgTZkyhbHjbueLL75wI73s0JNmzYM5vnxVsuvm02jHbrBjNzavXcVTbyxg0uNPUtCsKWeeNoqLLrooJc0lrrjiKmbOXMg557xN/fr+DiHYqtXOnHXW67z44gUMGzaSqVOn+FKO9evXc+jAw1n/ZRYn1r+eHMlM36xcqcPx9a9m2qLbOKDvgcx6fQZNmqTnan4q5ebmctMtN3PluZewVWmTmL5vobbqd912b7Vq9lMbVNUMZhpwE7ANUAJMwV1F301Vx6vqhnQXsCYpLCxk8MCB6KefckVeXtKBOsB2OTmMq1ePf559NpMDdKvSGGPKysoYOnQoy+psxVaDRtBw9/2oW+DfkIypVKdRcxrt3JvmB53CprZ7cMPNt7Bw4cKU5L1y5R907nyE74F6SJ06+ey++1BWrvzDtzKMPvt8Ni7O47j8yzMWqIdkSzZH5V9M9pKWnD78zIyuOxknnngi2Y3r8ktpbP+3ZaUrabhVE44++ug0l8zEq9JgXVX7AfsB/wWKgQ24pi8mToWFhRw+YAD62WcpC9RD2nsB+8XnnGMBuzEmcOpv43879HRx7du3oW7Dxil9oqj5u99/XUGnrN5kiT9XfLMki87Z+/D7ryt8WX8isrOz+fdtt7C4zvKod6jDuavqvzB23K1kZcXdndGkWZX/EVV9W1WPBHbDBetzReQtETnGa8tuqhAK1OV//0t5oB4SHrBPevTRlOdvjDHGmOrl2GOPpUGLRvxcuqrSdD+WrqDFNltz+OGHZ6hkJh4xX+rw2qCPFpGrcO3YbwduF5H7gTqR6UWkk6p+mbKSVlObNm1i8IAByKJFXJ6mQD2kfU4Ot9erx4Xnnouqcurw4Wlbl8m8a/uXsOKnTVtMb7FNPa6dUzOvWhpjjElOWVkZcwo/JS8vL2oTtLy8PN4s/B8s9qFwJiZxn+FVdQ1wq4jcjhtL/XxgNxEZB4xT1V+8pM8DO6espNXQpk2bOPygg8j+/HMuS3OgHtLOC9gvOu88VJXhI0akfZ3p1LZVw6gHl7at/BuRwC8rftpUSWfb2lcfxhhjKjdlyhQ2rVrPKfUPcOeKCpr7a44yO+t/vPjiixx55JGZLaSpUsKX41S1FHgaeFpE9gEuAL4WkWdxD0XqlJoiVk+hQD3niy8Yk6FAPSQUsF84ejRAtQ7YbXhGY4wxJn4lJSVcdvGldN7cCsmpPAYREToVt+LSiy5m8ODB1m49YFLy31DVd1X1WGBXYDNwfSryrc4uOvdcZNEixtSpk9FAPaStF7BfOnp0ykYoMMYYY0z18Pjjj1O2tphW2bGNKrRtdgEbVq7jueeeS3PJTLxS+tNJVX9Q1TOAQ4DKux7XcMuWLGF/EV8C9ZC2OTl0qleP5cuXV504w/5YV5zW/DcXl7Fu4+a0riMVmjZtyiczy6rsqZ+MFT+WsfTzzTRtGuyHzxhjjEmN4uJirrzsCjoXt4p5qFQRofPmVoz556WUlpamuYTpsbG0lHUlJWl/FWa4ftLSK01VX/WawxizhbPPu4hjjjqMlk3zOLpvQcrzX7exhJP//QO7dduLzp07pzz/VHpp2iwGHdqfP3/+naOvULJzU/vj7psPS5h0gXDDtbew//77pzRvY4wxwTRx4kTqbISts+O7SNM6uxlfrfmVJ598kn/84x9pKl167Nq1K2OfeAJ++aXqxGE2btxIfn5+3Ou7bLfd4l4mUWkbQkJVT0hX3qZ669u3L7PnvM2hBx/Ib38Wc9bgVinL+7c/NnPM9d+yZ5/DuO+BB8nJCfYoKe3bt2f+ex8zZOiRjD9jAafeoeQ3jh6wt9imXtQrJC22qRc1/fvPlzD9jhyeeeJ5DjrooJSW2xhjTDAVFRVxzRVX0724LcQ5LH3o6vrll17G0KFDyc3N7AOoknHP+PHcM3583MuJCKvXr09DiVIn2JGMqbF233135r73IYMG7M/yP5Zx7SnbkJWV3FXlb3/exFHXfMOpp43mqquvrTZPSWzUqBHTX5rNhReN5o6hkzjtfqVl+y1bqLnhGase9aWsVHn5dvjy9Sa8+/brdOrkf1/vjT9vRF+qPi3jir4r8rsIxhiTkAnjx9OguA4tshsntHyrnGZ8veE3Jk2axKhRo1JcOpMIC9aNb9q3b8/c9xZw2CEHcfodP3Df6PbUyU2sG8WCr9Yy9F/fcf1Nt3HaaaenuKTpl52dzV133kuXLrty2UkXccq4Ejr2iv/rWbhBefwSoW7hTiz8YCbNmzdPQ2nj069fP47odQTFy9PTT+GZZ57h+OOPT22m+XD0UHvktjGm+rn+2uvpVdwh7qvq4ToXt+LaK6+xYD0gLFg3vmrevDlz3pjL0CFHcdwN/+PxMdvRMD++3XLmB6s4886lPDL5KQ477LA0lTQzzjj9THbcoSPHDT2SIdeXsesBsf94Kdms3HMy9NvrcB4c/wh16mzxrDJftGrViskPT05b/k9PepqnHn0qbfkbY0x1svLPVTSrv3tSeTTLasiKVZ+lqEQmWRasG9/l5+czddp0Dh5wIJdPXMI957aLednf/tzM8dcvZvr0Vxg4cGAaS5k5paWlqCoPnLUhoeX33qMkraPLGGOMMSZzLFg3gTBh/AN8segj5qxYxyPTl8a9/MUXnscur75BmzZt0lC6zLn33nu46roxDLtT2XHP+J9KWrRReXLMDPY9YG9emjaTFi1apKGUxhhjjMkUC9aNr1SVK68YwzOPT2DWvzvRoXX0kU2qyuOO55azT68ezHj19cAP1xhNSUkJoy84h5dmPsn/PSm0aJtYY8O8fGHYncord31Fj567MePlOXTp0iXFpTXGGGNMptjzZI1viouLGXHqycya9gizxyYWqIMbdunC41pz5dAm7NevN3Pnzk1xSdNrzZo1HHzIAcz99CnOfxpatE3ua5mVJRx2QRb7n7mGPvv2ZObMmSkqqTHGGGMyzYJ144sNGzYw+LCB/PLVG0y/sSMtmyTfGfKE/i2ZcP62HDV4EC+88EIKSpl+33//PXv17krZVh9z2gNKvYapG25yryNzOPWuUk4adgx333NXyvI1xhhjTOZYsG4ybsWKFezXrzctsr7jmSu3p0G9JMaXinBg92a8cN2OnHPGMO679z8pyzddBh91MLsO/o1jrxKyc1I/LvwOPXL4vyeFm269gtdffz3l+RtjjDEmvSxYNxk35pIL6Np6NfeNbkduTup3wW47NuTVWzpx9ZVj+Pbbb1OefyqtXr2a3Q5K79ewYNss2napw+rVq9O6HmOMMcakngXrJuM2bljP3l3qp/UJo9u1qkergvps3LgxbeswxhhjjEk3Gw3GGGNSrGxTEWTVjmshWlrmdxFMLVC/QT5zNk9kvkz1rQwbNq9j9/o7+7Z+U3tZsG6MMSnUsXMnllw83pd1FxUWkle3bkbXWadOHbbddtuMrtPUPg88fB9ffvll0vnsvffezJs3L+Hld9xxx6TLYEy8LFg3xpgU+nLR576tW0TYtD6xJ9+mi6qy8Zcf/C5G2m3eZE3u0qlp06b07t07JXmlKh9jMsWCdWOMMWkhIvzj1OF89/33GV/3e++9l9GgrOFePeyqqzEmLSxYN8YYkxYiwuRHJvq27nffetOXdRtjTCpZsG6MMcYYU4OUoaCa3PImMCxYN8YYYwJm1arvWbLkfb+L8Zdff13sdxFMjNpv246nf3m70jSlpaVkZ1f+QMLtt9s+lcUySbBg3RhjjAmQgw7qz+233838+QtSkt/nn3/OzjsnP+Tg0KHHpaA0Jt1++HFJlWlEhOKSkvQXxqSEBetptLasjJWlpb6WoajMxkA2xpjq5MQTh3LiiUNTlp+IsGBB4sMVGmP8ZcF6muyx116M/+gjHi0uTiqf1atX06RJk4SXz83NpUOHDkmVwRhjjDHG+MOC9TS57uabue7mm5POR0T49c8/U1AiY4wxxhhT3dSO52EbY4wxxhhTDVmwbowxxhhjTEBZMxhjfFQntw5PX7GZvLqVD6GVrCWfbyQ3Nzet6zDGGGNM6lmwbjKucZOmXD7xJ/49ZUVa17Ps13XUr18/retI1sxXXue7776Le7lDDjmEV155Jeb0OTk59O/fP+71GGOMMcZfokk84aom69Gjhy5YkJoxbpMhItS0/9HGjRv58ccf416uc+fOLF4c+4M56tWrR7t27eJeT3VQE/eLRFldlLO6KGd1Uc7qopzVhWP1UC4odSEiC1W1R7R5dmXdZFx+fj6dOnVKaNlElzPGGGOMqY6sg6kxxhhjjDEBZcG6McYYY4wxAWXBujHGGGOMMQFlwboxxhhjjDEBZcG6McYYY4wxAWXBujHGGGOMMQFlwboxxhhjjDEBFchgXUSaisg9IvKpiHwmIk+ISKs486grIjd4y38sIi+LyE7pKrMxxhhjjDGpFrhgXURaAm8B9YHuqrobsBT4QERiehyliNQHpgM9gN6q2g34r5dHt/SU3BhjjDHGmNQKXLAOPAhsA5ynqiXetGsAASaJiMSQx03AvsDpqroBQFUnAF8CT4tI3dQX2xhjjDHGmNQKVLAuIv2AwcDLoSAbQFWLgRdxAfigKvLoAJwNzFPVZRGznwM6AiNSWW5jjDHGGGPSIVDBOnC8974wyrz53vuwKvI4BshJMg9jjDHGGGN8F7Rg/WDvfUmUed977/ukII89rCmMMcYYY4wJusAE615b9FAH0p+jJFnjvbcRkXqVZLVdDHnkhKUzxhhjjKmxRORvr2jTYusSWH1F297K6iJIdZLjdwHCNAOyvc/ro8zfEPa5CbCpgnxaxJHH34jI6cDpAG3btq2srCkR605QVTpVTUVxAqGqba1ofk2qg5DaWheJHBzjWSbo9ZPsySGZ5YNWN37VRdDqoSLxbF8saavLdlfEzqkVq4nbFK/qXAdBCtbDm6VsjjI/vKxFMeQTdx7eiDETAHr06JH2/2p13nHSxeqkXG2ti9q63SG1ffvDWV1Uzurn76w+TE0VmGYwwOqwz3lR5tf33kuBP2PIp7I8AFbGXjRjjDHGGGMyLzDBujdUY6ideYsoSQq89x+18p/PX8WQRyHwW9yFNMYYY4wxJoMCE6x73vLed4gyr4P3/moK8nhLVStrSmOMMcYYY4zvghasT/bee0eZ18N7f6GKPB4HNMk8jDHGGGOM8V2ggnVVnQW8AxwhIn+1Ofc+H4l7Kuksb1qOiDwmIi+LSMOwPBbjAvb9RGSriFUcjxtrfVKaN8UYY4wxxpikBSpY9wzDdSK9SZw6wH24duYnhaXrCpwMHAoMjMhjNPAdcI+I5Hr5XAe0BY5X1cJ0b4QxxhhjjDHJClywrqo/4JqwtAU+Az7AjY++h6ouCUv6BbAA+BaYG5HHaqAPsBb4BPgY9xCkrqq6IM2bYIwxxhhjTEoEaZz1v3hB+XFVpNkI7FnJ/JXAqNSWzBhjjDHGmMwJ3JV1Y4wxxhhjjGPBujHGGGOMMQFlwboxxhhjjDEBZcG6McYYY4wxAWXBujHGGGOMMQFlwboxxhhjjDEBZcG6McYYY4wxASWq6ncZAklEVgBL/S4HUACs9LsQAWF1Uc7qopzVRTmri3JWF+WsLspZXThWD+WCUhftVLVFtBkWrAeciCxQ1R5+lyMIrC7KWV2Us7ooZ3VRzuqinNVFOasLx+qhXHWoC2sGY4wxxhhjTEBZsG6MMcYYY0xAWbAefBP8LkCAWF2Us7ooZ3VRzuqinNVFOauLclYXjtWP8PoEAAAf/klEQVRDucDXhbVZN8YYY4wxJqDsyroxxhhjjDEBZcG6McYYY4wxAWXBujHGGGOMMQFlwXoAicj2IvKkiHwsIp+JyFMisoPf5fKbiHQWkQdE5F2/y+IHETleROaLyCYR+d3bLzr6XS4/iMi+IvKKiPwmIqtEZJaIBHqc3EwRkb1EZLOIPOp3WTJNRG4UEa3g9bnf5fOLiDQSkVEiMlVEXheRf4lIK7/LlW4i0qWS/SH8tb/fZc0EEckTkX+KyAIRWSoiX4vIEhF5UETa+V2+TBKRLBE5wzunLhSRZSLyqIjs5HfZorFgPWBEpCuwAOgO9PJe+wILamMwIs5AEZkBfA6cAdT3uVgZJyK3Ak8DewF1gRbAUGChiHTzs2yZJiKXAG8Cg4CWQDNgADBPRPbzr2T+E5FmwBQg1++yZJqICHBiJUkeylRZgkJEcrzvy4/A1cBU4EBVvVJVl/tbuozoG0Oa34C30l0Qv4lIA9x23gqsAHZS1Y7As8Ao4KOgBqqpJiK5wCvAA8BMVe0O/AcYhou1DvazfNFYsB4gIpINPAM0AV5S1SJV3Qi8CjQGpng7Wa0gIrsA9wEXAgcD4m+J/CEiA4F/An+y5SORGwAPZrxQPhGRI4H+uOC8N27/CMnFBSS1khesTgJq1RWyMHsD2wAborz+BCb7V7TM8364zQFuARYD3VX1cVUt87dkGRVLsD61ltTJVUBP7/N9qlrofb4eUNxFjxv9KJgPrgYGep9f8d7/AxThzqlPiUhrPwpWEQvWg+VoINSsIfyqx1LvfTvg+IyWyEequkhVz1LVgcAsv8vjo4uAk4HmqtoCGAxsCpvfXUTa+lKyzNsNGKSqs1X1fVU9B3gubH5Ln8oVBBcDh/pdCB+dBPxLVRtEeTVT1VV+FzBTRCQfmAH0w51LjlDVFf6Wyhc9gRuA3YGmqiqhF+6qKrgry7VB+LFh29AHVV2Hu9IOsHNGS+QD74LnWWGTVgKo6gZgkTetCe68GxgWrAdL+JepMOxz+GD4gbs9kyG/+V0AP3h3W+5T1SfUeyiCqr4EjItIWpLxwvlAVa+PchXsjbDPMzNZnqAQkX1wt3Bf8LssfvBOwEMov0pW243FNZkDuFFVf/ezMH4QkebA7ap6tap+pqqrw+Zl4y6O/Qa87VcZM2xz2OeLRKQh/FUXTb3pX2S8VJm3A9A87O/wO/bh/VqOy0xxYmPBerD0C/u8uYI0+2WgHEFUK5/epaqlqjotyqz3wz6vUNVfMlWmANrde3+HWtgMRkQKgEdx7bXX+Vsa3wzEnYDf8TodzxOR22tbfw4AEelE+ZXDIlzTqFpHVVep6v0VzO6Huws3VVVLM1gsP80O+9wBmO11Mu6Fa0K4BrjGj4JlWNOIvxuEff4j7PO2IlI3A+WJiQXrASEiWfy9rWlFB5BWXlpTuxWEfa51HedCROQAYDjuzsJ/vD4etYbXTv1xYKyqfup3eXx0kveehwvCegMX4DrNPef9oKktzqL83L4KuF9E/ueN/PGYF8zXdqGrprWlCQzAv3F9F0J6Ap/h+v3MBfZW1UXRFqxhfo74OzzuirzY0SzNZYmZBX3B0ZS//z8q6vCSxd9v4ZjaKTQy0O/A7X4WxA8i0lNEXgFew10VygGeEZGb/S1Zxl0BrFLVWtPJOJI3ysXgSpIcA7wpIo0yVCS/hTenfAE4BdfnpaX3/qGI7OlHwYIgrAnM79SeJjCo6p+4keXChz4uwPUDKsXVR42nqkuB8AsbfcI+14lIvib9JYqNBevBkRdH2lo5KopxvFtzJ+F+0A1X1cgRYmqD/wEPAx9ETB8jIr19KE/GecNUnoAbzrTWUtX1qlofdzt7e1xw/hh/b0q4M3ClD8XLKK9j6fZhk1aq8ynwiDetATAh44ULjn7AVtSuJjAhq3HDd64D1oZN3xd4S0Qim4jUVGfgRokCGCnuGS5ZuEE8Qn7wOp0GggXrwfFnjOkUd2vT1F4X4O7EjFHVWtmhTlU3qurzuOH6xkbMPsyHImWUiGwFTASGqup6v8sTBKq6QVW/V9WpqnoKbmSt8PGzh/hUtEyqLNgKv4rctbY9BCdMqAnMFF9LkWEi0hKYhxuc4CLc3dnwZjFdgFpxZ1JV5wN74poQrsT9gJkIHBSWbIYPRauQBesBoaqbgPBOghX9b36qhVcDjEdEdsN1ohynqrf6XR6/qWqZql7K30cBCUw7wzQahLsK9Fn4kxhxI8KEDPOm1Ure7e6DKL/tv5WPxcmU1RF/54d9XhoxL1DjSGeCd/W01jWB8UygvPnk86r6DXAg8FNYmlNqS584VV2sqv9Q1Y6q2hn3LJPGYUnG+1S0qGrFP6UaCR/ho6JmMe9koiAmeLy2uc/gRv64OGJev2jL1CI3hX3+3rdSmEBR1WLgMu/PJT4WJSO82/bhF31ahH2O7Dz3B7XPvtTCJjAiUg843Ptztar+AeCNInZ5WNJ61N5nVQynPCZ+QlU/87MwkSxYD5apYZ8bVpAmULdmTGaEPZ1yDnB2aMx1EakjIgcB5/tZvgBY6L2X8PfvUU31AtA5yit8mM9p3rTaLrRvPOVrKTInfP8Pf3x8+KAFK4DvMlOcQKmNo8CA66cQiveKIuZND/tcSOxNcmsM72mll3h/fg2M9rE4UVmwHizPUn4A3SZseui2/lL+/rTG2iR8vNPIHtu1wZW427fnAGVhzR6KgFeBL/0sXCaISD8RWSQiE0MP9Aiztfc+VlVrfBCiqmtU9cvIF38fvWCNN61GE+dhb2z1s7wftuHaAt8Ad/lQPD/cRnnnuR5h35Xwq+z3qWqteJBaSEQTmLeqSF6jeE+vDT3wqGXEUKbh59OnVTUymK/RvLp4ETcyziLgwNCdhyCxYD1AVHUzrhPUOmCQiOR5T+Y7yJs2VFULK8ujJvJONuFDjW0nIu39KU3micixwHVVJFtYxfya4HDcqB7DccPP9QV3dwG4BbiDWjDih9lCA9yQhL1xY0a/GRpL3Dt2jAIOUdXADMOWTl5b/eG40XBycR3SAY713l8DbvShaH6rzaPAgBsBZRNuNLnrvB+5WcBV3vyPgAv9Klymedt/NG67dwFuBfZS1WX+liw68e6mmwDxTjQ3425hlwJf4Ub++NrXgmWYiOwOTMY9ba1BxOzNuHo53Ds51UgisiswH9eWsDIdVPWHDBTJN96wYrcCA4BWQDGubhYCz3o9/Gs1EXmU8k6mk1T1VP9Kkzki0gd3G7sH7jkUK3FXy97GBWcVPRG6xhKRPYBLgb64+ijBDd94X20MVkXkXuBsoL+qvu53efwgIp2BMcABuP2hGHc3bgpwd224qu6NijMK970oxT3Z9WlV/c3XglXBgnVjjDHGGGMCyprBGGOMMcYYE1AWrBtjjDHGGBNQFqwbY4wxxhgTUBasG2OMMcYYE1AWrBtjjDHGGBNQFqwbY4wxxhgTUBasG2OMMcYYE1AWrBtjjDHGGBNQFqynmIiMFJEHIqadJiL3hP1dX0RuFZGlIrLZe7/Te0JjRfkeIiJvisinIrJMRKaJyC4VpM0WkfNE5HMR2SQiS0TkOhHJSd2WVi2Wugib3kBELhaR5VXkmS0iF3j18IX3ekNEBlWxXIGI/EtEPklsa5ITpLoIW35nEblXRP4rIreLyP7xbVVi4qmLiDQPi0jMT3GLJb2IjBURjXiViUiXWNeTjETqQkTaeceP6SJyl4gcVUG6KVG2bYOINK+iTCIir4rIkoQ2KkHpqAsRaSki40VkuXes/cY7FtaNsUyB/Y7Ee5xP5LwgcZx30iXGukjknHqKiHwgIl+LyCIReV9ETq6iLL4eLyopVyx1tDhK2cNfn0YsH4g4oiJp3C+aisg93j7/mYg8ISKtKkgbd/4JU1V7pfAFTABOjZj2KHCi97ke8CGgwHJgg/dZga+BFlHyvAD3SOB9vb/rA1OB9UDfKOnvxz1GeCmwOSz/B4JUF97fdYGLgG9C5awiz2eAX4BuYdOOxD06+bQo6ZsCV3t1rcCSIO4XmaiLsDR53j7yC3BkEOsiyjJDYqmTeNIDzYC1Xn2Fv/4bxLrAXVy5FlgFjASyKsm3k3cMiNy2e2Io0yV+fFdSXRdAC+B7oAz4CSgKOxbOA+pVUpbAf0eI8zifQPq4zjt+1QWJnVPHettxYNi0vYF1wI0VlMP340USdbS/Vx/FwArg14iXAtcns78EcJsT2S9aAp8BE4Ecb9pNwDKgXUTauPNPanv9rvCa9gI+ATpHTPsa2M77fBnwBtDR+zsbGAUUev/kiRHL7gmUAtdETG8ArAR+BhqFTR8EPAds5f3dEHjCy7sMaBWUuvD+zvJ2+uahA0Il+fX3tmNUlHnP4k4sdSKm5wE5wK74G6z7XhfevCbAfFwQs21Q6yJiXjvgO+DPyuok3vTA9cA//aiDeOsCqAP8Fxec7hZDvpOBYxMoTw9gsR/flVTXBTAemAK0CVvucu84qMDVFSwX+O8IcR7nE0gf13nH57qI95y6o7fN/4qyrlu97W4dZZ7vx4sk6uhx4DygbpRlu3r1tHOi+0tAtzmu/cJL8yLwB1A/bFou7sf+m4CETY87/6S21+8Kr0kvIB93Agn/h7YAlkfsDFtc0cGdRBRYFTH9WW96nyjL3OnNuzhs2slAdkS6ul65FNgjKHURZZmfqTy4GuNtwxZXuoB/e/OaV7BsLj4F60GpC28/eAt3BWCnTNdDInXhHQDnAkcASyqrk3jSA42Ab8MPykGtC0CAp3FBxL4x5Lsd7uqQxFmehsDnuIA9o9+VVNcF7gf6S0S/4j7B276FUeZVi+8IcR7nE0gf13nH57qI95w61Jt+fpRlzvTmdY+Y7vvxItE68uaPrGT5m4BFyewvQdvmBPeLft70yVGWudebd0ii+Sf7sjbrqdUd+Ei9/5hnb9xVGkREgH+r6qYoyz7pvdeJmL6v9/5rlGXe8t6PCE1Q1cdVtTQ8kaoW4g40v+JOxplQaV1UoLiKPH/23kdEmbcTsEBVV0VbUFWryjudglIX1+EOSDeo6ldV5J8u8dbFNV76F2PMP9b05wIFwCMiMkpEGseYfyrFWhdnAscDD6rqW1TtMtzt3MkicoKI1IuxPPcCD6vqghjTp1Kq6yIfGKOqZVHmVXSshWryHYn3OJ/AeSGu804apeOcGjp2niIi2RHzdvLmL4qYHoTjRUUqrSNV3aiqD1ey/HG4JpV/CVAcUZF07BfHe+8LoywT+u4NSyL/5Pj566gmvIALgQXe63dc+64FYa8VuCt8C4ALK8mnHu7X2NyI6cVE+aXvzevuzfujijLWwd26PDrIdUEVV05xt2BD7etuDJvew5u+exXly9jVwqDVBbADrs3uGqBhJuog2brABU0fAnkx1klM6XGB3ArK2xcqrsnMeUGrC1yfi1W4W8/tY8h/G/7eNltx7a6Pr2K5k4DpeFeqMvFdSXddVLLezt72PV7dvyMRecR1nK8sPSk47/hZF14+FZ1TBXfnSYFJQK43vZ33XTkoIr1vx4sM1NEe3vZ0TGZ/qWbbXNF+8Z03/Ygoy/Tx5v0UQzmj5p/09vu1s9XEF64d5eER02ZGfvkrWLYbUdogezukAqdHWWZPb15xFXmPBc4Oel0QWzOH3rhOPoq7Hd7DW9f2MZQpY8F60OoCd6tTcR3ERuLaH34GfIy7bbdF+3Y/6wIXmH0RfhKprE7iSY+7XXoScD6uXeZ6yk/CE4K0XwCne+Waj+s0Own3g2SR971uFLF8e+AU4GLgZf4euF9RQTk64NqpF4RNy+h3JR11Ucm6jvLyOTBierX6jkRZLq7jfGXpScF5x8+68NJFPad683bEBeaKa3e8K65ZQ7QfJ4E4XqSpjm4BPk52f6lm27zFfoH7AVfiTe8RZZldw/7nFXZMr2q/S2qb/a70mvTC9RhuEzHtNypoRx2R7hbvhJkbMT3UPnA+EW1QcSN/KPB7lPzygAO8HVi9g+9hQa4LYghQvXTdvPwV13b1pBjL5Few7ntdAF96aWbjtTfEBbgveNNfJaKNop91gQuYTom1TuJNH5GuFe42cOhgPCIo+0XY93cBsJ93UskH7vOmfwo0qGQdOwJzwrbtgIj5ObiRUfaLmJ7pYD3tdRGWzzPAa1GmV6vviDc9ruN8rOlJ8LzjZ11EWTbqOTVsfnvcD73Qd+OyGMvky/EiTXX0Pa65WFL7SzXb5i32C9ygDqH/Z6coy3QIm19p59qq9ruEt9nvSq8pL++f/XvEtG2AH2NYdmvc7aWeUeY1DTuJ/Ad3i0VwQzEt9KZHO/G0w11hm0D5lYBiIk7WQaoLYg+uBuGGYxxJ+ZXD62JYLuPBehDqAtfpMnTVoFvEvAZ4o6aQ5qsmsdYFcAbRO/lErZN401dQNsEN16XAl0HZL0LbABwV5X8aOi6MrWJddYBZXtqZEfNuJmLINm96xr4rGa6L3XBNaSJHmKlW35GweXEd52NNT4LnHT/rIiJdhefUsDR7Arfj2t6v8bZpIjH8IMv08SJNdRS6QxJ1FK5E9q9qsM1R9wugDeXBeIcoy3UMm98smf0u4e32q8Jr2gs3lN6siGmDgRdjWHYacEYl85vihpRaBHwEPAKcGHbQ3KJXe8TyrXBXoxR4J6h1QWxNP07EXQnM8v7eP+xAe3kVy/oRrPteF94BpMKrApT3dH/d77oAuuCG5NriCmm0Ook3fRXlq0/5ePxN/K4Lb1poGLDeUfK42Jv3fQzrawNsAlaHTTsANxzZFsFJJr8rmaoL3I+W94FDo8yrNt+RSpaN6zhfVXqSPO/4XBdVnVP3x139rO/9vSveCFzE2LQlk8eLNNXRbcD8ONaV0Tgik/uF978Mff87R5kfatpSQiWjbFW13yXzCnUmMgkSkfNxQ0G1xl2dWRY2extcZ6hfvL+fVtU7I5Yfgws0roxzvTvhrnysxf0y/qOK9F1wPbjXq2rDeNYVR5mSrYsluAcPSAX5twO+wt12fDJs+j7Aa7irHTup6tIKlldgqaq2j3vj4hSkuhCRRrggHqClqq6IyGs47irRN6raMYHNrVScddHDSxOL7YArcXcVYkqvqkuqKOs4XEemFqq6MsZ8YxbvfoG7a9IU2EtVP4zIa3/gdVzb4SpHHhCR54GBqtrA+/s13ImvShXth8nIdF14TztcqKoPRplXnb4jWxwvwvKJ6zifQPq4zjuJSPc5VUQa4joT3qmqN4VN3wl4F3fltreqvh9DWdN6vKhkvUnvL9455m5VvT2O9aY9jqhk3eneL37CXdTYV1Xfjph3EK4Z3A+q2qGC5ROK5WLm16+jmvbCdU6J7PAwi8rHAj4J+E+C65uB+6VXYa/nKMssJsVjf6aqLrw0S6jkSihuWD4FukSZFxp3vLInd/pxZT0QdUF5Z6puUdIf7M17z++6wDXL+LKCV2iEitDfbeJNH0MZzwJ+Dcp+gbtzokQ0/fDmdfLmVThef0T6Wwi7koZ7cFJFdade/X1Jmm/zZ6IucMNZXlJFOarFdySGPOI6zseTngTOO5msC2I4p+KG31PCxswOmxcagz3qU0yjpM/I8SLV+wvQCxfcbpPAOjMSR/iwX4Qe+rRFHwRcU0ul4qf9JhzLxfqycdZTZy+2HBO4G9HH7EREjsTdhj4vyrz8ylYkImfhTh4v4zoCxaoI1/M93eKqizg08d6j/aJ/2XtvlOQ6Ui0odTHNe+8XJX0L7/31JMtUlSrrQlUvU9VO0V544yOHTfs53vQxlLEV7gpqusW6X6Ty/9YK+Gu8ZVU9pZK6A/g54u90SWtdiMg5QL6qjo0yL/xYWy2+IzGI9zgfU/okzjuJStc5NZXnkUwdLyqS6P4yBJinqj8lsM5MxREVSdd+Mdl77x0lmx7e+wtJ5J8cv34d1aQXrhPG9xHTtgf+V0H6o4HHiN5WdDeidJYLm/8P3KgfM3AnoFjLuB2wjirGIs90XUSk+xH36zVqBx9cuzQlymPCgcNxVwqiPn4cyPKWXRbU/SKddQG0BTbihjeMfDLdZFwTgLQ9QjqZughLv4T42qDHm74RrglRWsfYjqcucJ0bl+M6LTWImHc97up3ld9pYFvvmBHTaCZk6C5UuusCdwKN2ukU9+CfO8P+rgnfkbiO87GmJ8HzTqbqgjjOqUBX7/gY7XHzoSH6Do+hjBk5XqR6f8E1kVxGAuPEx7t/+b3N8ewX3rS3cWO454VNy8ON4f5usvknte1+VHhNe+F+pT4VMW0o7mmAkWlPxXVS+Ia/33b+ivLbsFs05cA9vOBJYDPuKXs5UdJk464MzMSNEhLqk9ABeAcYHKS6iEhTgDtRKhUE3F66Z3GPAj8ibFoXrz4rvHXppVFcJ7WWQdsvMlEX3oGlFNdZLsebdqJXJ2ndNxKti4j0S0hBsI4b5vFn3O3wUOfcdrhRL9oGbb/AXenZiLuqk+9N6487aZ4dkfYj71hyWNi0XbxtaxpHGTMVrKezLq7y9vfIJj5f407Iypbj+wf+O0Kcx/l400csW+V5x+/9ggTOqbiOs6WEjSOP+0H7PvBERFpfjxep+u6EpdnH2/aoPzyT2V+CtM0J7hfb4S4IjMP9qKmDuxu5jIgHsSWSfzKvHEwq9MR9ycPtCXwQPkFEjsfdMhPc0/KiKcIFYaFl7sA9DngNrl1WZ1X9LtqCqloqIktxO/TLwPci8jGuM81Qja0ZQLJiqotwXke3HrjhwQDeF5FvVXW3KMlPAP4PuEFE7sR1dFqDe+DLlCh518E9OCVU33nANyLyrqoeEvtmJSRQdaGqU0VkAO4q5Pci8idu3Nw+mv5HzMddF2n0NK6N83jgMhF5HTfKwQWqWpyB9cdVF6r6noj0wbXP/0ZEVuCGHzxaVWdHJJ8IXAA8LyJf4B4NPw93FU1TuA2pkpa6EJFLcPs5uEfIR7McNwZ9eP6B/47Ee5xP5LwQz3knTdJ2TgVQ1YtFZDFwpohchduHinAj3oyPWN7v40VFEj2mDgHeVtXl0WYGJI6oSLr3ix9EpDfux9xnuB81b+Oeu/BXp/NE80+GjQZjjDHGGGNMQFkHU2OMMcYYYwLKgnVjjDHGGGMCyoJ1Y4wxxhhjAsqCdWOMMcYYYwLKgnVjjDHGGGMCyoJ1Y4wxxhhjAsqCdWOMMcYYYwLKgnVjjDHGGGMCyoJ1Y4wxiEhDETlLRD4RkWv9Lo8xxhgnx+8CGGOMSQ8R6QuMAPbGPRr7V0CB14HJQFvgVOBSYAxwEtASmOZDcY0xxkRhV9aNMaaGEZEGIvIkMAf4DthbVTuqaj+gP7AYeAt4AxBV/V1VLwSe8qGse2d6ncYYU53YlXVjjKlBRKQxMA/YCRikqrPD56tqCTBFRN4F3o9YfG1mSumISB3gFqBvJtdrjDHViV1ZN8aYmuVBoAtwX2SgHk5VfwbOiphcls6CRfEvYNsMr9MYY6oVC9aNMaaGEJFBwHHen7dWlV5VXwb+l9ZCVUBETgcu9mPdxhhTnViwbowxNcfp3vsiVV0W4zIPVjRDRDqKyDciot7r0bB594rIBm/6kojlGonIf0TkAxH5TkTKvHTne/NPA07zkrcSkQXe64iwPLYWkXtEZI6ILBORH0VknIg0CEtTX0QuFJGfRaS9iBzipftCRNrEuP3GGBNoFqwbY0wNICIC7O/9+Vmsy6lqhe3UVfVrVd0RuCfKvHOAPSpY9BGgGOipqtvj2qSvCVv2QVXd0/tzuar28F4vetuyIzAVeEBV+wPtgPuBC4E3RKSOiBwMfAiMA1oDXYGJuGY1nYGDY60DY4wJMgvWjTGmZmgONPY+r0xx3h9Hm6iqX0VOE5H6wJHAu6qqXrp3gZviWN9kYJyqfu4tX6aqNwN/Aj2AE1V1JrALsMRb5h/ADsAA3I+LqXGszxhjAstGgzHGmJqhTtjn9SnOW+NIK97rZhH5WlVDV/kfA4ZUubBIN6AXcKWIRLZpXwtsBHYEF8SLyE9Ae+A2VV0PzPZexhhTI1iwbowxNcMq3GguWUCBX4VQ1fUi8gBupJmPRWQKMFZVPwbuiiGLXt77iaq6OIb0pd778vhLa4wxwWfNYIwxpgZQ1SLKR3bZ3s+yAOcA5+J+QAwFPhKRJ70x4KvSzHv3exuMMSYQLFg3xpia40nvva+INPSrEOrcC2wHXILrXHoCMN3rCFuZUBOewRUlEJGKOrYaY0yNY8G6McbUHPcDy3Dt1y+MZQERuVpE8qpIttl7bxY+UUSyvY/ZYdMKROQKAFXdoKq3ArsCPwP74DqFVuYj731YtKBcRPYDdqsiD2OMqTEsWDfGmBpCVdcBxwMbgMtF5KDK0ovIpcBcrwkNlAfd2RFJf/Xe+4lIe2/ZHXFDJQI0j7iSP1xE8sPKtQyY4v1ZEpaumC37Tr0LfIH7wfGqiAwRkRxxBgB3A9PCN8N7z61sW40xprqyYN0YY2oQVX0PGITrcDlDRP4tIm3D04jILiJyN/Cpqr4eNqtrxHvIfNxwkI2Br0VkKfAecJs3vx7wiYic4P29PfCMiLT01tcYNwb8rIhOo98CW4nIViLSUkSOV9Uy4CRgNW44ymeAdbgfIK8Al6nqai/ffFxTG4ADY68lY4ypPsQbBtcYY0wN4gWyw4GjgU64kWIW49qEvwNMUtU/vLSNcQ8Y2jEsi6XAkar6iZdmH1wzmx1wgfq5qrpYRFbjRnm5Q1VXi0gBsMLLoxj4BigCXsSNCrMprIwH4a7OrwcexQ2/WOrN2x64Hvdwo/q45jFXq+pr3vyTcFfZw5vmfA3sqqqbMcaYGsKCdWOMMcYYYwLKmsEYY4wxxhgTUBasG2OMMcYYE1AWrBtjjDHGGBNQFqwbY4wxxhgTUBasG2OMMcYYE1AWrBtjjDHGGBNQFqwbY4wxxhgTUBasG2OMMcYYE1AWrBtjjDHGGBNQFqwbY4wxxhgTUBasG2OMMcYYE1D/D/dOF7kEnvzTAAAAAElFTkSuQmCC\n",
+ "text/plain": [
+ "<Figure size 864x504 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, ax = plt.subplots(1, 1, figsize=(12, 7))\n",
+ "\n",
+ "score_diff_norm_absolute = [len(s) for s in score_diff_cluster]\n",
+ "score_diff_norm_relative = [0.1 + 0.8 * s / np.max(score_diff_norm) for s in score_diff_norm]\n",
+ "bplot = ax.boxplot(score_diff_cluster, showfliers=False, patch_artist=True, notch=True, medianprops=dict(color='black'), meanprops=dict(markerfacecolor='white', markeredgecolor='black', marker='s'), showmeans=True, widths=score_diff_norm_relative)\n",
+ "for patch, color in zip(bplot['boxes'], cluster_colors_values):\n",
+ " patch.set_facecolor([c / 255 for c in color])\n",
+ "\n",
+ "ax.set_xlabel('Cluster')\n",
+ "ax.set_xticklabels(['$\\\\bf{' + str(nr) + '}$' + f'\\n#{num}' for nr, num in zip(range(len(cluster_colors_values)), score_diff_norm_absolute)])\n",
+ "ax.set_ylabel('Absolute Score Difference')\n",
+ "ax.set_title('Score Differences per Cluster')\n",
+ "\n",
+ "fig.savefig('score_differences_cluster.png', bbox_inches='tight');"
+ ]
+ },
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- Clusters not present in test set: 1, 2, 5, 6, 8\n",
"- Clusters present in test set: 0, 3, 4, 7, 9\n",
"- Cluster 3 and 7: Medication sentences\n",
- "- Cluster 2 and 6: Long sentences\n",
- "\n"
+ "- Cluster 2 and 6: Long sentences"
]
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>a</th>\n",
" <th>b</th>\n",
" <th>Label</th>\n",
" <th>Number of Words</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Patient arrives, via hospital wheelchair, Gait steady, History obtained from patient, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>Complex assessment performed, Patient arrives ambulatory, Gait steady, History obtained from, parent, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>3.00</td>\n",
" <td>47</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>The remainder of a complete comprehensive multi-system review of systems is negative except as above.</td>\n",
" <td>The remainder of the complete comprehensive multisystem review of systems is negative except as above.</td>\n",
" <td>5.00</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>Educational literature, developmentally age appropriate, provided at today's visit, including Caring for Your Three- to Five-Year-Old [].</td>\n",
" <td>Educational literature, developmentally age appropriate, provided at today's visit, including Caring for Your Five- to Seven-Year-Old [].</td>\n",
" <td>4.05</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>I have reviewed the history, physical examination, impression, report, and plan with the team in detail and agree with the documentation outlined in their notes from today.</td>\n",
" <td>After reviewing the patient's history, I interviewed the patient with the treatment team, collected additional data, and discussed treatment recommendations.</td>\n",
" <td>1.50</td>\n",
" <td>47</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>Patient arrives, via hospital wheelchair, History obtained from patient, Patient appears, in distress due to pain, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>Complex assessment performed, Patient arrives, via stretcher, via Emergency Medical Services, Unsteady gait, Assistance to cart, History obtained from patient, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>2.50</td>\n",
" <td>57</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>The patient will meet individually with the group provider nearing completion of LEARN and prior to bariatric surgery.</td>\n",
" <td>The patient may shower two weeks after the surgery with the use of the provided cloth sling.</td>\n",
" <td>0.00</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>When visiting a restaurant, the patient typically does add salt to the meal.</td>\n",
" <td>A letter has been sent for the patient to call and schedule.</td>\n",
" <td>0.00</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>44</th>\n",
" <td>Procedural pause conducted prior to each stage of procedure to verify: correct patient identity, procedure to be performed and as applicable, correct side and site, special equipment or special requirements.</td>\n",
" <td>Procedural pause conducted to verify: correct patient identity, procedure to be performed and as applicable, correct side and site, correct patient position, and special equipment or special requirements.</td>\n",
" <td>3.70</td>\n",
" <td>58</td>\n",
" </tr>\n",
" <tr>\n",
" <th>46</th>\n",
" <td>We recommend that the patient remain abstinent from all mood-altering drugs including alcohol for the time period as specified:</td>\n",
" <td>We recommend that the patient remain abstinent from all mood-altering drugs including alcohol for the time period as specified: Duration of program and indefinitely.</td>\n",
" <td>4.70</td>\n",
" <td>43</td>\n",
" </tr>\n",
" <tr>\n",
" <th>55</th>\n",
" <td>Patient arrives ambulatory, Gait steady, History obtained from patient, Patient appears, uncomfortable, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>Patient arrives, via stretcher, via Emergency Medical Services, Unsteady gait, Lift to cart, History obtained from patient, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>2.90</td>\n",
" <td>50</td>\n",
" </tr>\n",
" <tr>\n",
" <th>71</th>\n",
" <td>If the patient experiences any of these possible signs and symptoms of a DVT or PE, report to the local emergency room immediately.</td>\n",
" <td>If the patient develops any sudden shortness of breath or difficulty breathing, the patient should go to the nearest emergency room for evaluation.</td>\n",
" <td>3.40</td>\n",
" <td>46</td>\n",
" </tr>\n",
" <tr>\n",
" <th>74</th>\n",
" <td>The patient's test results were reviewed by the health care team and the patient was informed of the results via telephone.</td>\n",
" <td>The patient's right shoulder was prepped and draped in the usual sterile fashion; the painful area was marked.</td>\n",
" <td>0.00</td>\n",
" <td>39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>77</th>\n",
" <td>No: appendix removal; gallbladder removal; prior hysterectomy (removal of the uterus or womb); removal of both ovaries or tubal ligation or sterilization</td>\n",
" <td>No: appendix removal; gallbladder removal; removal of both ovaries or tubal ligation or sterilization</td>\n",
" <td>3.75</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>78</th>\n",
" <td>Complex assessment performed, Patient arrives ambulatory, Gait steady, History obtained from patient, Patient appears, uncomfortable, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>Complex assessment performed, Patient arrives, via hospital wheelchair, Gait steady, History obtained from patient, Patient appears, in distress due to pain, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>3.90</td>\n",
" <td>54</td>\n",
" </tr>\n",
" <tr>\n",
" <th>81</th>\n",
" <td>Patient arrives, via stretcher, via Emergency Medical Services, Unsteady gait, Lift to cart, History obtained from patient, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>Complex assessment performed, Patient arrives, via stretcher, via Emergency Medical Services, Unsteady gait, Assistance to cart, History obtained from patient, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>4.00</td>\n",
" <td>61</td>\n",
" </tr>\n",
" <tr>\n",
" <th>84</th>\n",
" <td>MEDICAL NECESSITY: The patient would benefit from skilled physical therapy interventions to be able to return the patient to full sporting activities.</td>\n",
" <td>MEDICAL NECESSITY: The patient would benefit from skilled physical therapy interventions to be able to return the patient to full leisure, self-care activities.</td>\n",
" <td>3.45</td>\n",
" <td>45</td>\n",
" </tr>\n",
" <tr>\n",
" <th>87</th>\n",
" <td>Reviewed with the patient the findings from the breast pathology and specifically, difference between in situ and invasive carcinomas.</td>\n",
" <td>In reviewing the history, the patient is followed by primary care physician and diabetes clinic.</td>\n",
" <td>0.50</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>94</th>\n",
" <td>Patient education materials provided: Home exercise program was provided with duration and frequency of exercises included.</td>\n",
" <td>Patient Education: Home exercise program was provided with duration and frequency of exercises included.</td>\n",
" <td>4.50</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>95</th>\n",
" <td>Complex assessment performed, Patient arrives ambulatory, Gait steady, History obtained from patient, Patient appears, uncomfortable, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>Patient arrives, via hospital wheelchair, Gait steady, History obtained from patient, Patient appears, generally ill, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>3.00</td>\n",
" <td>48</td>\n",
" </tr>\n",
" <tr>\n",
" <th>99</th>\n",
" <td>Discharge Instructions: Patient/responsible party indicated understanding of instructions on the following brochure(s) given to patient/responsible party: Care Following your Skin Surgery</td>\n",
" <td>Discharge Instructions: Understanding verbalized, on the following brochure(s) given to patient/responsible party: Care Following Your Sclerotherapy-</td>\n",
" <td>3.75</td>\n",
" <td>37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>114</th>\n",
" <td>Patient is here for the following immunization(s): Live Intranasal Influenza Virus Vaccination</td>\n",
" <td>Patient is here for the following immunization(s): Live Intranasal Influenza Virus Vaccination; Human Papillomavirus Vaccination</td>\n",
" <td>3.25</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>115</th>\n",
" <td>Nursing assessment: Patient's provider will be contacted for additional advice and follow-up will take place with the caller.</td>\n",
" <td>This information will be reviewed by the provider, and the patient will be contacted with additional recommendations.</td>\n",
" <td>3.60</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>120</th>\n",
" <td>Benefits and risks of acupuncture were discussed with patient and patient has signed consent authorization to proceed with treatment.</td>\n",
" <td>The above was discussed with the patient and she voiced understanding of the content and plan.</td>\n",
" <td>3.50</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>121</th>\n",
" <td>The patient tolerated the procedure well and returned to the orthopedic nursing care floor.</td>\n",
" <td>The patient was taken to the operating room, and anesthesia was administered by the Anesthesia staff.</td>\n",
" <td>2.50</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>130</th>\n",
" <td>Educational literature, developmentally age appropriate, provided at today's visit, including Caring for Your Nine-Month-Old .</td>\n",
" <td>Educational literature, developmentally age appropriate, provided at today's visit, including Caring for Your Three- to Five-Year-Old.</td>\n",
" <td>3.75</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>135</th>\n",
" <td>Patient identified using two identifiers and permission was obtained from the patient to perform a fingerstick INR.</td>\n",
" <td>Patient arrives ambulatory, Gait steady, History obtained from patient, Patient appears, cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>0.00</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>145</th>\n",
" <td>Patient arrives, via hospital wheelchair, Unsteady gait, Assistance to cart, History obtained from patient, Patient appears, in distress due to pain, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>Patient arrives ambulatory, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>2.50</td>\n",
" <td>45</td>\n",
" </tr>\n",
" <tr>\n",
" <th>148</th>\n",
" <td>Patient arrives, via Emergency Medical Services, History obtained from patient, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>Patient arrives ambulatory, Gait steady, History obtained from patient, Patient appears, anxious, restless, uncomfortable, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>3.25</td>\n",
" <td>45</td>\n",
" </tr>\n",
" <tr>\n",
" <th>152</th>\n",
" <td>After obtaining informed consent, the patient's identity, procedure, and site were verified during a pause prior to proceeding with the minor surgical procedure as per universal protocol recommendations.</td>\n",
" <td>After obtaining informed consent to include a discussion of the alternatives to the provided treatment, the benefits and the risks to include pain, bleeding, infection, scar formation, recurrence, persisting redness, increase or decrease in skin pigmentation, local nerve damage or numbness, or possible need for further surgery, the patient's identity, procedure, and site were verified during a pause prior to proceeding with the minor surgical procedure as per universal protocol recommendations.</td>\n",
" <td>3.00</td>\n",
" <td>99</td>\n",
" </tr>\n",
" <tr>\n",
" <th>158</th>\n",
" <td>I have reviewed her note in the electronic medical record.</td>\n",
" <td>Collateral history was reviewed from the electronic medical record.</td>\n",
" <td>5.00</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>161</th>\n",
" <td>A dry sterile dressing was applied to the patient's leg, and the patient was transferred to the postanesthesia recovery unit (PACU) in stable condition.</td>\n",
" <td>The patient was taken to the operating room, and anesthesia was administered by the Anesthesia staff.</td>\n",
" <td>1.00</td>\n",
" <td>40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>162</th>\n",
" <td>Respiratory assessment findings include respiratory effort easy, Respirations regular, Conversing normally.</td>\n",
" <td>Respiratory assessment findings include respiratory effort easy, Respirations regular, Conversing normally, no signs of distress, no retractions noted, no cyanosis, Breath sounds clear.</td>\n",
" <td>3.25</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>164</th>\n",
" <td>The rationale for hand therapy intervention was discussed and patient agrees to above plan of care.</td>\n",
" <td>Due to the patient's cognitive impairment, explained diagnosis and treatment plan to the patient and family/caregiver.</td>\n",
" <td>1.00</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>170</th>\n",
" <td>Patient is here for the following immunization(s): Live Intranasal Influenza Virus Vaccination</td>\n",
" <td>Patient is here for the following immunization(s): Inactivated Influenza Virus Vaccination; Hepatitis A Vaccine</td>\n",
" <td>3.50</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>171</th>\n",
" <td>Difficulty breathing with underlying lung disease and little improvement following a health care provider's instructions</td>\n",
" <td>Moderate difficulty breathing; Difficulty breathing with underlying lung disease and little improvement following a health care provider's instructions</td>\n",
" <td>4.50</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>173</th>\n",
" <td>Patient needs to schedule an appointment for a gynecology or medical examination within the next three months.</td>\n",
" <td>Patient needs to schedule an appointment for a gynecology or preventive medical examination within the next 3 months.</td>\n",
" <td>4.90</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>174</th>\n",
" <td>MEDICAL NECESSITY: The patient would benefit from skilled physical therapy interventions to be able to return the patient to full work, home, leisure activities.</td>\n",
" <td>MEDICAL NECESSITY: The patient would benefit from skilled physical therapy interventions to be able to return the patient to full work, home, leisure, self-care, sporting activities.</td>\n",
" <td>4.75</td>\n",
" <td>50</td>\n",
" </tr>\n",
" <tr>\n",
" <th>175</th>\n",
" <td>BENEFITS AND RISKS OF ACUPUNCTURE WERE DISCUSSED WITH PATIENT AND PATIENT CONSENTS TO PROCEED WITH TREATMENT.</td>\n",
" <td>Benefits and risks of acupuncture were discussed with patient and patient has signed consent authorization to proceed with treatment.</td>\n",
" <td>5.00</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>176</th>\n",
" <td>Patient arrives, via hospital wheelchair, Unsteady gait, Assistance to cart, History obtained from patient, Patient appears, uncomfortable, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>Gait steady, History obtained from patient, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>2.50</td>\n",
" <td>41</td>\n",
" </tr>\n",
" <tr>\n",
" <th>178</th>\n",
" <td>Procedural pause conducted to verify: correct patient identity, procedure to be performed and as applicable, correct side and site, correct patient position, and special equipment or special requirements.</td>\n",
" <td>Procedural pause conducted to verify: correct patient identity, procedure to be performed, and as applicable, correct side and site, correct patient position, and availability of implants, special equipment or special requirements.</td>\n",
" <td>4.30</td>\n",
" <td>59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>186</th>\n",
" <td>No: penetrating wound from a gunshot or stabbing; puncture wound that may have been deep enough to damage underlying organs (i.e.</td>\n",
" <td>No: puncture wound that may have been deep enough to damage underlying organs (i.e.gunshot, knife, sharp object).</td>\n",
" <td>3.95</td>\n",
" <td>38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>207</th>\n",
" <td>Patient arrives, via hospital wheelchair, Unsteady gait, Assistance to cart, History obtained from patient, Patient appears, in distress due to pain, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>Patient arrives ambulatory, accompanied by parent, History obtained from parent, Patient alert, happy, smiling and playful, interactive and playful, consolable, appropriately dressed, Skin warm.</td>\n",
" <td>1.75</td>\n",
" <td>54</td>\n",
" </tr>\n",
" <tr>\n",
" <th>215</th>\n",
" <td>Discussed skin cancer and treatment in detail along with consent with risks, benefits, and alternatives.</td>\n",
" <td>I discussed the treatment plan, risks and benefits with the patient and directed the nurse to perform/treat with Cantharidin.</td>\n",
" <td>3.00</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>220</th>\n",
" <td>The patient will continue with physical therapy and rehabilitation exercises as described in the hospital.</td>\n",
" <td>The patient was prepped and draped in the usual sterile fashion and placed in the lithotomy position.</td>\n",
" <td>0.00</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>221</th>\n",
" <td>Patient arrives ambulatory, Gait steady, History obtained from patient, Patient appears, generally ill, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>Patient arrives, via hospital wheelchair, Unsteady gait, Inability to ambulate, History obtained from patient, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>3.15</td>\n",
" <td>48</td>\n",
" </tr>\n",
" <tr>\n",
" <th>222</th>\n",
" <td>To maintain line patency, 2mL of 0.9% preservative free NaCl was administered to the patient: Yes</td>\n",
" <td>To maintain line patency, 10 mL of 0.9% preservative free NaCl is administered to the patient after placement and each blood draw</td>\n",
" <td>3.70</td>\n",
" <td>38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>227</th>\n",
" <td>Time was spent discussing with the patient the neurobiology of nicotine addiction and the rationale for using medications to help with cessation.</td>\n",
" <td>I reviewed with the patient the rationale for and appropriate use of the vitamins.</td>\n",
" <td>0.50</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>232</th>\n",
" <td>Patient arrives, via hospital wheelchair, History obtained from patient, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>Patient arrives, via Emergency Medical Services, Unsteady gait, Inability to ambulate, History obtained from patient, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time.</td>\n",
" <td>3.85</td>\n",
" <td>48</td>\n",
" </tr>\n",
" <tr>\n",
" <th>248</th>\n",
" <td>Benefits and risks of acupuncture were discussed with patient and patient has signed consent authorization to proceed with treatment.</td>\n",
" <td>The goals, risks, benefits and alternatives of proceeding with a left knee injection were discussed with the patient; he expressed understanding and wished to proceed.</td>\n",
" <td>2.75</td>\n",
" <td>44</td>\n",
" </tr>\n",
" <tr>\n",
" <th>264</th>\n",
" <td>male who is being seen today for his final cardiac rehab evaluation.</td>\n",
" <td>Patient is requesting evaluation today for this complaint.</td>\n",
" <td>1.00</td>\n",
" <td>20</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" a \\\n",
"0 Patient arrives, via hospital wheelchair, Gait steady, History obtained from patient, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time. \n",
"13 The remainder of a complete comprehensive multi-system review of systems is negative except as above. \n",
"17 Educational literature, developmentally age appropriate, provided at today's visit, including Caring for Your Three- to Five-Year-Old []. \n",
"20 I have reviewed the history, physical examination, impression, report, and plan with the team in detail and agree with the documentation outlined in their notes from today. \n",
"29 Patient arrives, via hospital wheelchair, History obtained from patient, Patient appears, in distress due to pain, Patient cooperative, alert, Oriented to person, place and time. \n",
"33 The patient will meet individually with the group provider nearing completion of LEARN and prior to bariatric surgery. \n",
"36 When visiting a restaurant, the patient typically does add salt to the meal. \n",
"44 Procedural pause conducted prior to each stage of procedure to verify: correct patient identity, procedure to be performed and as applicable, correct side and site, special equipment or special requirements. \n",
"46 We recommend that the patient remain abstinent from all mood-altering drugs including alcohol for the time period as specified: \n",
"55 Patient arrives ambulatory, Gait steady, History obtained from patient, Patient appears, uncomfortable, Patient cooperative, alert, Oriented to person, place and time. \n",
"71 If the patient experiences any of these possible signs and symptoms of a DVT or PE, report to the local emergency room immediately. \n",
"74 The patient's test results were reviewed by the health care team and the patient was informed of the results via telephone. \n",
"77 No: appendix removal; gallbladder removal; prior hysterectomy (removal of the uterus or womb); removal of both ovaries or tubal ligation or sterilization \n",
"78 Complex assessment performed, Patient arrives ambulatory, Gait steady, History obtained from patient, Patient appears, uncomfortable, Patient cooperative, alert, Oriented to person, place and time. \n",
"81 Patient arrives, via stretcher, via Emergency Medical Services, Unsteady gait, Lift to cart, History obtained from patient, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time. \n",
"84 MEDICAL NECESSITY: The patient would benefit from skilled physical therapy interventions to be able to return the patient to full sporting activities. \n",
"87 Reviewed with the patient the findings from the breast pathology and specifically, difference between in situ and invasive carcinomas. \n",
"94 Patient education materials provided: Home exercise program was provided with duration and frequency of exercises included. \n",
"95 Complex assessment performed, Patient arrives ambulatory, Gait steady, History obtained from patient, Patient appears, uncomfortable, Patient cooperative, alert, Oriented to person, place and time. \n",
"99 Discharge Instructions: Patient/responsible party indicated understanding of instructions on the following brochure(s) given to patient/responsible party: Care Following your Skin Surgery \n",
"114 Patient is here for the following immunization(s): Live Intranasal Influenza Virus Vaccination \n",
"115 Nursing assessment: Patient's provider will be contacted for additional advice and follow-up will take place with the caller. \n",
"120 Benefits and risks of acupuncture were discussed with patient and patient has signed consent authorization to proceed with treatment. \n",
"121 The patient tolerated the procedure well and returned to the orthopedic nursing care floor. \n",
"130 Educational literature, developmentally age appropriate, provided at today's visit, including Caring for Your Nine-Month-Old . \n",
"135 Patient identified using two identifiers and permission was obtained from the patient to perform a fingerstick INR. \n",
"145 Patient arrives, via hospital wheelchair, Unsteady gait, Assistance to cart, History obtained from patient, Patient appears, in distress due to pain, Patient cooperative, alert, Oriented to person, place and time. \n",
"148 Patient arrives, via Emergency Medical Services, History obtained from patient, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time. \n",
"152 After obtaining informed consent, the patient's identity, procedure, and site were verified during a pause prior to proceeding with the minor surgical procedure as per universal protocol recommendations. \n",
"158 I have reviewed her note in the electronic medical record. \n",
"161 A dry sterile dressing was applied to the patient's leg, and the patient was transferred to the postanesthesia recovery unit (PACU) in stable condition. \n",
"162 Respiratory assessment findings include respiratory effort easy, Respirations regular, Conversing normally. \n",
"164 The rationale for hand therapy intervention was discussed and patient agrees to above plan of care. \n",
"170 Patient is here for the following immunization(s): Live Intranasal Influenza Virus Vaccination \n",
"171 Difficulty breathing with underlying lung disease and little improvement following a health care provider's instructions \n",
"173 Patient needs to schedule an appointment for a gynecology or medical examination within the next three months. \n",
"174 MEDICAL NECESSITY: The patient would benefit from skilled physical therapy interventions to be able to return the patient to full work, home, leisure activities. \n",
"175 BENEFITS AND RISKS OF ACUPUNCTURE WERE DISCUSSED WITH PATIENT AND PATIENT CONSENTS TO PROCEED WITH TREATMENT. \n",
"176 Patient arrives, via hospital wheelchair, Unsteady gait, Assistance to cart, History obtained from patient, Patient appears, uncomfortable, Patient cooperative, alert, Oriented to person, place and time. \n",
"178 Procedural pause conducted to verify: correct patient identity, procedure to be performed and as applicable, correct side and site, correct patient position, and special equipment or special requirements. \n",
"186 No: penetrating wound from a gunshot or stabbing; puncture wound that may have been deep enough to damage underlying organs (i.e. \n",
"207 Patient arrives, via hospital wheelchair, Unsteady gait, Assistance to cart, History obtained from patient, Patient appears, in distress due to pain, Patient cooperative, alert, Oriented to person, place and time. \n",
"215 Discussed skin cancer and treatment in detail along with consent with risks, benefits, and alternatives. \n",
"220 The patient will continue with physical therapy and rehabilitation exercises as described in the hospital. \n",
"221 Patient arrives ambulatory, Gait steady, History obtained from patient, Patient appears, generally ill, Patient cooperative, alert, Oriented to person, place and time. \n",
"222 To maintain line patency, 2mL of 0.9% preservative free NaCl was administered to the patient: Yes \n",
"227 Time was spent discussing with the patient the neurobiology of nicotine addiction and the rationale for using medications to help with cessation. \n",
"232 Patient arrives, via hospital wheelchair, History obtained from patient, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time. \n",
"248 Benefits and risks of acupuncture were discussed with patient and patient has signed consent authorization to proceed with treatment. \n",
"264 male who is being seen today for his final cardiac rehab evaluation. \n",
"\n",
" b \\\n",
"0 Complex assessment performed, Patient arrives ambulatory, Gait steady, History obtained from, parent, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time. \n",
"13 The remainder of the complete comprehensive multisystem review of systems is negative except as above. \n",
"17 Educational literature, developmentally age appropriate, provided at today's visit, including Caring for Your Five- to Seven-Year-Old []. \n",
"20 After reviewing the patient's history, I interviewed the patient with the treatment team, collected additional data, and discussed treatment recommendations. \n",
"29 Complex assessment performed, Patient arrives, via stretcher, via Emergency Medical Services, Unsteady gait, Assistance to cart, History obtained from patient, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time. \n",
"33 The patient may shower two weeks after the surgery with the use of the provided cloth sling. \n",
"36 A letter has been sent for the patient to call and schedule. \n",
"44 Procedural pause conducted to verify: correct patient identity, procedure to be performed and as applicable, correct side and site, correct patient position, and special equipment or special requirements. \n",
"46 We recommend that the patient remain abstinent from all mood-altering drugs including alcohol for the time period as specified: Duration of program and indefinitely. \n",
"55 Patient arrives, via stretcher, via Emergency Medical Services, Unsteady gait, Lift to cart, History obtained from patient, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time. \n",
"71 If the patient develops any sudden shortness of breath or difficulty breathing, the patient should go to the nearest emergency room for evaluation. \n",
"74 The patient's right shoulder was prepped and draped in the usual sterile fashion; the painful area was marked. \n",
"77 No: appendix removal; gallbladder removal; removal of both ovaries or tubal ligation or sterilization \n",
"78 Complex assessment performed, Patient arrives, via hospital wheelchair, Gait steady, History obtained from patient, Patient appears, in distress due to pain, Patient cooperative, alert, Oriented to person, place and time. \n",
"81 Complex assessment performed, Patient arrives, via stretcher, via Emergency Medical Services, Unsteady gait, Assistance to cart, History obtained from patient, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time. \n",
"84 MEDICAL NECESSITY: The patient would benefit from skilled physical therapy interventions to be able to return the patient to full leisure, self-care activities. \n",
"87 In reviewing the history, the patient is followed by primary care physician and diabetes clinic. \n",
"94 Patient Education: Home exercise program was provided with duration and frequency of exercises included. \n",
"95 Patient arrives, via hospital wheelchair, Gait steady, History obtained from patient, Patient appears, generally ill, Patient cooperative, alert, Oriented to person, place and time. \n",
"99 Discharge Instructions: Understanding verbalized, on the following brochure(s) given to patient/responsible party: Care Following Your Sclerotherapy- \n",
"114 Patient is here for the following immunization(s): Live Intranasal Influenza Virus Vaccination; Human Papillomavirus Vaccination \n",
"115 This information will be reviewed by the provider, and the patient will be contacted with additional recommendations. \n",
"120 The above was discussed with the patient and she voiced understanding of the content and plan. \n",
"121 The patient was taken to the operating room, and anesthesia was administered by the Anesthesia staff. \n",
"130 Educational literature, developmentally age appropriate, provided at today's visit, including Caring for Your Three- to Five-Year-Old. \n",
"135 Patient arrives ambulatory, Gait steady, History obtained from patient, Patient appears, cooperative, alert, Oriented to person, place and time. \n",
"145 Patient arrives ambulatory, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time. \n",
"148 Patient arrives ambulatory, Gait steady, History obtained from patient, Patient appears, anxious, restless, uncomfortable, Patient cooperative, alert, Oriented to person, place and time. \n",
"152 After obtaining informed consent to include a discussion of the alternatives to the provided treatment, the benefits and the risks to include pain, bleeding, infection, scar formation, recurrence, persisting redness, increase or decrease in skin pigmentation, local nerve damage or numbness, or possible need for further surgery, the patient's identity, procedure, and site were verified during a pause prior to proceeding with the minor surgical procedure as per universal protocol recommendations. \n",
"158 Collateral history was reviewed from the electronic medical record. \n",
"161 The patient was taken to the operating room, and anesthesia was administered by the Anesthesia staff. \n",
"162 Respiratory assessment findings include respiratory effort easy, Respirations regular, Conversing normally, no signs of distress, no retractions noted, no cyanosis, Breath sounds clear. \n",
"164 Due to the patient's cognitive impairment, explained diagnosis and treatment plan to the patient and family/caregiver. \n",
"170 Patient is here for the following immunization(s): Inactivated Influenza Virus Vaccination; Hepatitis A Vaccine \n",
"171 Moderate difficulty breathing; Difficulty breathing with underlying lung disease and little improvement following a health care provider's instructions \n",
"173 Patient needs to schedule an appointment for a gynecology or preventive medical examination within the next 3 months. \n",
"174 MEDICAL NECESSITY: The patient would benefit from skilled physical therapy interventions to be able to return the patient to full work, home, leisure, self-care, sporting activities. \n",
"175 Benefits and risks of acupuncture were discussed with patient and patient has signed consent authorization to proceed with treatment. \n",
"176 Gait steady, History obtained from patient, Patient cooperative, alert, Oriented to person, place and time. \n",
"178 Procedural pause conducted to verify: correct patient identity, procedure to be performed, and as applicable, correct side and site, correct patient position, and availability of implants, special equipment or special requirements. \n",
"186 No: puncture wound that may have been deep enough to damage underlying organs (i.e.gunshot, knife, sharp object). \n",
"207 Patient arrives ambulatory, accompanied by parent, History obtained from parent, Patient alert, happy, smiling and playful, interactive and playful, consolable, appropriately dressed, Skin warm. \n",
"215 I discussed the treatment plan, risks and benefits with the patient and directed the nurse to perform/treat with Cantharidin. \n",
"220 The patient was prepped and draped in the usual sterile fashion and placed in the lithotomy position. \n",
"221 Patient arrives, via hospital wheelchair, Unsteady gait, Inability to ambulate, History obtained from patient, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time. \n",
"222 To maintain line patency, 10 mL of 0.9% preservative free NaCl is administered to the patient after placement and each blood draw \n",
"227 I reviewed with the patient the rationale for and appropriate use of the vitamins. \n",
"232 Patient arrives, via Emergency Medical Services, Unsteady gait, Inability to ambulate, History obtained from patient, Patient appears comfortable, Patient cooperative, alert, Oriented to person, place and time. \n",
"248 The goals, risks, benefits and alternatives of proceeding with a left knee injection were discussed with the patient; he expressed understanding and wished to proceed. \n",
"264 Patient is requesting evaluation today for this complaint. \n",
"\n",
" Label Number of Words \n",
"0 3.00 47 \n",
"13 5.00 30 \n",
"17 4.05 34 \n",
"20 1.50 47 \n",
"29 2.50 57 \n",
"33 0.00 35 \n",
"36 0.00 25 \n",
"44 3.70 58 \n",
"46 4.70 43 \n",
"55 2.90 50 \n",
"71 3.40 46 \n",
"74 0.00 39 \n",
"77 3.75 36 \n",
"78 3.90 54 \n",
"81 4.00 61 \n",
"84 3.45 45 \n",
"87 0.50 34 \n",
"94 4.50 30 \n",
"95 3.00 48 \n",
"99 3.75 37 \n",
"114 3.25 27 \n",
"115 3.60 35 \n",
"120 3.50 35 \n",
"121 2.50 30 \n",
"130 3.75 31 \n",
"135 0.00 36 \n",
"145 2.50 45 \n",
"148 3.25 45 \n",
"152 3.00 99 \n",
"158 5.00 19 \n",
"161 1.00 40 \n",
"162 3.25 34 \n",
"164 1.00 32 \n",
"170 3.50 26 \n",
"171 4.50 33 \n",
"173 4.90 35 \n",
"174 4.75 50 \n",
"175 5.00 35 \n",
"176 2.50 41 \n",
"178 4.30 59 \n",
"186 3.95 38 \n",
"207 1.75 54 \n",
"215 3.00 34 \n",
"220 0.00 32 \n",
"221 3.15 48 \n",
"222 3.70 38 \n",
"227 0.50 36 \n",
"232 3.85 48 \n",
"248 2.75 44 \n",
"264 1.00 20 "
]
},
- "execution_count": 18,
+ "execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cluster_idx = df_train_embeddings[df_train_embeddings['label'] == 5].index.tolist()[0:50]\n",
"df_train.loc[cluster_idx]"
]
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1278"
]
},
- "execution_count": 19,
+ "execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sum(kmeans.labels_[:1642] == kmeans.labels_[1642:]) # Check for how many sentence pairs both sentences end up in the same cluster"
]
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": 22,
"metadata": {},
"outputs": [
{
- "ename": "FileNotFoundError",
- "evalue": "[Errno 2] No such file or directory: '/home/j562r/nlp/output/submission_generation/03_12_2020_20_18_37_original_data/bert_base/1_example_run_step1/preprocessed_data_2020-03-15_21-49-55/test_cluster_idx.npy'",
- "output_type": "error",
- "traceback": [
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- "\u001b[0;32m~/miniconda3/envs/n2c2/lib/python3.6/site-packages/numpy/lib/npyio.py\u001b[0m in \u001b[0;36mload\u001b[0;34m(file, mmap_mode, allow_pickle, fix_imports, encoding)\u001b[0m\n\u001b[1;32m 420\u001b[0m \u001b[0mown_fid\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 421\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 422\u001b[0;31m \u001b[0mfid\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mos_fspath\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfile\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"rb\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 423\u001b[0m \u001b[0mown_fid\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 424\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
- "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/home/j562r/nlp/output/submission_generation/03_12_2020_20_18_37_original_data/bert_base/1_example_run_step1/preprocessed_data_2020-03-15_21-49-55/test_cluster_idx.npy'"
- ]
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+ " <th>Label</th>\n",
+ " <th>Number of Words</th>\n",
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+ " <td>oxycodone [ROXICODONE] 5 mg tablet 0.5-1 tablets by mouth every 4 hours as needed.</td>\n",
+ " <td>pantoprazole [PROTONIX] 40 mg tablet enteric coated 1 tablet by mouth Bid before meals.</td>\n",
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+ " <td>28</td>\n",
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+ " <td>Given current medication regimen, the following parameters should be monitored by outpatient providers: lithium level</td>\n",
+ " <td>3.00</td>\n",
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+ " <td>5.00</td>\n",
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+ " <th>1637</th>\n",
+ " <td>New wheezing or chest tightness, runny or blocked nose, or discharge down the back of the throat</td>\n",
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+ " <td>Explained diagnosis and treatment plan; patient/child/care giver expressed understanding of the content.</td>\n",
+ " <td>Explained diagnosis and treatment plan; patient/child/caregiver expressed understanding of the content and agreement with the plan of care.</td>\n",
+ " <td>4.25</td>\n",
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+ " <td>The patient remained focused on group tasks and displayed interest in others and in the group process.</td>\n",
+ " <td>The patient's medication(s) were reconciled comparing the pre- and post-hospitalization lists and then verified in the electronic orders prescribing tool.</td>\n",
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+ "1 oxycodone [ROXICODONE] 5 mg tablet 0.5-1 tablets by mouth every 4 hours as needed. \n",
+ "2 The patient has missed 0 hours of work in the past seven days for issues not related to depression. \n",
+ "3 Given current medication regimen, the following parameters should be monitored by outpatient providers: None \n",
+ "4 The diagnosis and treatment plan were explained to the family/caregiver who expressed understanding of the information presented. \n",
+ "5 nortriptyline [PAMELOR] 50 mg capsule 1 capsule by mouth every bedtime. \n",
+ "... ... \n",
+ "1636 Nurse visit ten minutes, over half of which was spent in counseling and point-of-care testing. \n",
+ "1637 New wheezing or chest tightness, runny or blocked nose, or discharge down the back of the throat \n",
+ "1638 You should not take any medications that cause drowsiness or sleepiness unless they have been prescribed by your Health Care Provider. \n",
+ "1639 Explained diagnosis and treatment plan; patient/child/care giver expressed understanding of the content. \n",
+ "1640 The patient remained focused on group tasks and displayed interest in others and in the group process. \n",
+ "\n",
+ " b \\\n",
+ "1 pantoprazole [PROTONIX] 40 mg tablet enteric coated 1 tablet by mouth Bid before meals. \n",
+ "2 In the past year the patient has the following number of visits: none in the hospital none in the er and one as an outpatient. \n",
+ "3 Given current medication regimen, the following parameters should be monitored by outpatient providers: lithium level \n",
+ "4 Explained diagnosis and treatment plan; patient expressed adequate understanding of the information presented today. \n",
+ "5 Tylenol Extra Strength 500 mg tablet 2 tablets by mouth every bedtime. \n",
+ "... ... \n",
+ "1636 Nurse visit ten minutes, which over half was spent in consultation and point-of-care testing. \n",
+ "1637 F (38 C) or suspected fever; new wheezing or chest tightness; runny or blocked nose or discharge down the back of the throat; hoarseness or lost voice; night sweats or unintentional weight loss with normal or increased appetite \n",
+ "1638 You should not take any medications that cause drowsiness or sleepiness unless they have been prescribed by your doctor. \n",
+ "1639 Explained diagnosis and treatment plan; patient/child/caregiver expressed understanding of the content and agreement with the plan of care. \n",
+ "1640 The patient's medication(s) were reconciled comparing the pre- and post-hospitalization lists and then verified in the electronic orders prescribing tool. \n",
+ "\n",
+ " Label Number of Words \n",
+ "1 1.00 28 \n",
+ "2 0.00 44 \n",
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+ "\n",
+ "[956 rows x 4 columns]"
+ ]
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+ "metadata": {},
+ "output_type": "execute_result"
}
],
"source": [
"df_train[np.load(os.path.join(TSNE_DIR, 'test_cluster_idx.npy'))]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## $M$-Heads Analysis"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 23,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "ename": "FileNotFoundError",
+ "evalue": "[Errno 2] No such file or directory: '/mtc/experiment/submission_generation/04_27_2020_16_53_55_heads_output/heads/2_run/preprocessed_data_2020-04-27_16-56-22_biobert_pretrain_output_all_notes_150000/kfold0/eval_results_dev_9.json'",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-23-80ba514ed0a6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m150\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mheads_folds\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;34mf'kfold{k}'\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;34m'eval_results_dev_9.json'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'r'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 8\u001b[0m \u001b[0mtrain_result\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mjson\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfile\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/mtc/experiment/submission_generation/04_27_2020_16_53_55_heads_output/heads/2_run/preprocessed_data_2020-04-27_16-56-22_biobert_pretrain_output_all_notes_150000/kfold0/eval_results_dev_9.json'"
+ ]
+ }
+ ],
"source": [
"heads_folds = Path(NLP_EXPERIMENT_PATH) / 'submission_generation/04_27_2020_16_53_55_heads_output/heads/2_run/preprocessed_data_2020-04-27_16-56-22_biobert_pretrain_output_all_notes_150000'\n",
"\n",
"all_pred_heads = []\n",
"all_pred_means = []\n",
"\n",
"for k in range(150):\n",
" with open(heads_folds / f'kfold{k}' / 'eval_results_dev_9.json', 'r') as file:\n",
" train_result = json.load(file)\n",
" \n",
" for preds in train_result['pred_heads']:\n",
" all_pred_heads += preds\n",
" \n",
" all_pred_means += train_result['pred']"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"head_assignments = np.abs(np.array(all_pred_heads) - np.array(df_train['Label'].tolist()).reshape(-1, 1))\n",
"head_assignments = np.argmin(head_assignments, axis=1)\n",
"head_assignments = head_assignments.tolist()\n",
"df_train_embeddings['head_assignment'] = head_assignments + head_assignments"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"fig, ax = plt.subplots(figsize=(12, 10))\n",
"sns.scatterplot(x=\"$t$-SNE Projection 1\", y=\"$t$-SNE Projection 2\", hue=r'head_assignment',\n",
" data=df_train_embeddings.sort_values('label', ascending=True), legend=\"brief\", alpha=0.8, s=80).set_title('Sentence Clustering')\n",
"handles, labels = ax.get_legend_handles_labels()\n",
"#ax.legend(handles=handles[1:], labels=labels[1:], prop={'size': 15})\n",
"#lgd = ax.legend(handles, labels, loc='upper center', bbox_to_anchor=(0.5, -0.2), ncol=3)\n",
"lgd = ax.legend(handles, labels, loc='center left', bbox_to_anchor=(1, 0.5))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"np.unique(head_assignments, return_counts=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.3"
+ "version": "3.6.8"
}
},
"nbformat": 4,
"nbformat_minor": 4
}

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MITK · MIC · IMSY · DKFZ