ml3.3.0.min.js

/** ml@3.3.0, MIT licensed. https://github.com/mljs/ml */
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r=0;r<this.columns;r++)this.set(e,r,this.get(e,r)+t[r]);return this}subRowVector(t){t=(0,s.checkRowVector)(this,t);for(var e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)this.set(e,r,this.get(e,r)-t[r]);return this}mulRowVector(t){t=(0,s.checkRowVector)(this,t);for(var e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)this.set(e,r,this.get(e,r)*t[r]);return this}divRowVector(t){t=(0,s.checkRowVector)(this,t);for(var e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)this.set(e,r,this.get(e,r)/t[r]);return this}addColumnVector(t){t=(0,s.checkColumnVector)(this,t);for(var e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)this.set(e,r,this.get(e,r)+t[e]);return this}subColumnVector(t){t=(0,s.checkColumnVector)(this,t);for(var e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)this.set(e,r,this.get(e,r)-t[e]);return this}mulColumnVector(t){t=(0,s.checkColumnVector)(this,t);for(var e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)this.set(e,r,this.get(e,r)*t[e]);return this}divColumnVector(t){t=(0,s.checkColumnVector)(this,t);for(var e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)this.set(e,r,this.get(e,r)/t[e]);return this}mulRow(t,e){(0,s.checkRowIndex)(this,t);for(var r=0;r<this.columns;r++)this.set(t,r,this.get(t,r)*e);return this}mulColumn(t,e){(0,s.checkColumnIndex)(this,t);for(var r=0;r<this.rows;r++)this.set(r,t,this.get(r,t)*e);return this}max(){for(var t=this.get(0,0),e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)this.get(e,r)>t&&(t=this.get(e,r));return t}maxIndex(){for(var t=this.get(0,0),e=[0,0],r=0;r<this.rows;r++)for(var n=0;n<this.columns;n++)this.get(r,n)>t&&(t=this.get(r,n),e[0]=r,e[1]=n);return e}min(){for(var t=this.get(0,0),e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)this.get(e,r)<t&&(t=this.get(e,r));return t}minIndex(){for(var t=this.get(0,0),e=[0,0],r=0;r<this.rows;r++)for(var n=0;n<this.columns;n++)this.get(r,n)<t&&(t=this.get(r,n),e[0]=r,e[1]=n);return e}maxRow(t){(0,s.checkRowIndex)(this,t);for(var e=this.get(t,0),r=1;r<this.columns;r++)this.get(t,r)>e&&(e=this.get(t,r));return e}maxRowIndex(t){(0,s.checkRowIndex)(this,t);for(var e=this.get(t,0),r=[t,0],n=1;n<this.columns;n++)this.get(t,n)>e&&(e=this.get(t,n),r[1]=n);return r}minRow(t){(0,s.checkRowIndex)(this,t);for(var e=this.get(t,0),r=1;r<this.columns;r++)this.get(t,r)<e&&(e=this.get(t,r));return e}minRowIndex(t){(0,s.checkRowIndex)(this,t);for(var e=this.get(t,0),r=[t,0],n=1;n<this.columns;n++)this.get(t,n)<e&&(e=this.get(t,n),r[1]=n);return r}maxColumn(t){(0,s.checkColumnIndex)(this,t);for(var e=this.get(0,t),r=1;r<this.rows;r++)this.get(r,t)>e&&(e=this.get(r,t));return e}maxColumnIndex(t){(0,s.checkColumnIndex)(this,t);for(var e=this.get(0,t),r=[0,t],n=1;n<this.rows;n++)this.get(n,t)>e&&(e=this.get(n,t),r[0]=n);return r}minColumn(t){(0,s.checkColumnIndex)(this,t);for(var e=this.get(0,t),r=1;r<this.rows;r++)this.get(r,t)<e&&(e=this.get(r,t));return e}minColumnIndex(t){(0,s.checkColumnIndex)(this,t);for(var e=this.get(0,t),r=[0,t],n=1;n<this.rows;n++)this.get(n,t)<e&&(e=this.get(n,t),r[0]=n);return r}diag(){for(var t=Math.min(this.rows,this.columns),e=new Array(t),r=0;r<t;r++)e[r]=this.get(r,r);return e}sum(t){switch(t){case"row":return(0,s.sumByRow)(this);case"column":return(0,s.sumByColumn)(this);default:return(0,s.sumAll)(this)}}mean(){return this.sum()/this.size}prod(){for(var t=1,e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)t*=this.get(e,r);return t}norm(t="frobenius"){var e=0;if("max"===t)return this.max();if("frobenius"===t){for(var r=0;r<this.rows;r++)for(var n=0;n<this.columns;n++)e+=this.get(r,n)*this.get(r,n);return Math.sqrt(e)}throw new RangeError(`unknown norm type: ${t}`)}cumulativeSum(){for(var t=0,e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)t+=this.get(e,r),this.set(e,r,t);return this}dot(t){e.isMatrix(t)&&(t=t.to1DArray());var r=this.to1DArray();if(r.length!==t.length)throw new RangeError("vectors do not have the same size");for(var n=0,i=0;i<r.length;i++)n+=r[i]*t[i];return n}mmul(t){t=this.constructor.checkMatrix(t),this.columns!==t.rows&&console.warn("Number of columns of left matrix are not equal to number of rows of right matrix.");for(var e=this.rows,r=this.columns,n=t.columns,i=new this.constructor[Symbol.species](e,n),o=new Array(r),s=0;s<n;s++){for(var a=0;a<r;a++)o[a]=t.get(a,s);for(var u=0;u<e;u++){var h=0;for(a=0;a<r;a++)h+=this.get(u,a)*o[a];i.set(u,s,h)}}return i}strassen2x2(t){var e=new this.constructor[Symbol.species](2,2),r=this.get(0,0),n=t.get(0,0),i=this.get(0,1),o=t.get(0,1),s=this.get(1,0),a=t.get(1,0),u=this.get(1,1),h=t.get(1,1),l=(r+u)*(n+h),c=(s+u)*n,f=r*(o-h),d=u*(a-n),m=(r+i)*h,g=(s-r)*(n+o),p=(i-u)*(a+h),v=l+d-m+p,w=f+m,y=c+d,x=l-c+f+g;return e.set(0,0,v),e.set(0,1,w),e.set(1,0,y),e.set(1,1,x),e}strassen3x3(t){var e=new this.constructor[Symbol.species](3,3),r=this.get(0,0),n=this.get(0,1),i=this.get(0,2),o=this.get(1,0),s=this.get(1,1),a=this.get(1,2),u=this.get(2,0),h=this.get(2,1),l=this.get(2,2),c=t.get(0,0),f=t.get(0,1),d=t.get(0,2),m=t.get(1,0),g=t.get(1,1),p=t.get(1,2),v=t.get(2,0),w=t.get(2,1),y=t.get(2,2),x=(r+n+i-o-s-h-l)*g,M=(r-o)*(-f+g),b=s*(-c+f+m-g-p-v+y),A=(-r+o+s)*(c-f+g),S=(o+s)*(-c+f),_=r*c,R=(-r+u+h)*(c-d+p),E=(-r+u)*(d-p),O=(u+h)*(-c+d),k=(r+n+i-s-a-u-h)*p,P=h*(-c+d+m-g-p-v+w),C=(-i+h+l)*(g+v-w),j=(i-l)*(g-w),T=i*v,N=(h+l)*(-v+w),V=(-i+s+a)*(p+v-y),D=(i-a)*(p-y),z=(s+a)*(-v+y),F=n*m,L=a*w,I=o*d,q=u*f,X=l*y,B=_+T+F,U=x+A+S+_+C+T+N,W=_+R+O+k+T+V+z,Y=M+b+A+_+T+V+D,$=M+A+S+_+L,J=T+V+D+z+I,G=_+R+E+P+C+j+T,K=C+j+T+N+q,Z=_+R+E+O+X;return e.set(0,0,B),e.set(0,1,U),e.set(0,2,W),e.set(1,0,Y),e.set(1,1,$),e.set(1,2,J),e.set(2,0,G),e.set(2,1,K),e.set(2,2,Z),e}mmulStrassen(t){var r=this.clone(),n=r.rows,i=r.columns,o=t.rows,s=t.columns;function a(t,r,n){var i=t.rows,o=t.columns;if(i===r&&o===n)return t;var s=e.zeros(r,n);return s=s.setSubMatrix(t,0,0)}i!==o&&console.warn(`Multiplying ${n} x ${i} and ${o} x ${s} matrix: dimensions do not match.`);var u=Math.max(n,o),h=Math.max(i,s);return r=a(r,u,h),t=a(t,u,h),function t(r,n,i,o){if(i<=512||o<=512)return r.mmul(n);i%2==1&&o%2==1?(r=a(r,i+1,o+1),n=a(n,i+1,o+1)):i%2==1?(r=a(r,i+1,o),n=a(n,i+1,o)):o%2==1&&(r=a(r,i,o+1),n=a(n,i,o+1));var s=parseInt(r.rows/2,10);var u=parseInt(r.columns/2,10);var h=r.subMatrix(0,s-1,0,u-1);var l=n.subMatrix(0,s-1,0,u-1);var c=r.subMatrix(0,s-1,u,r.columns-1);var f=n.subMatrix(0,s-1,u,n.columns-1);var d=r.subMatrix(s,r.rows-1,0,u-1);var m=n.subMatrix(s,n.rows-1,0,u-1);var g=r.subMatrix(s,r.rows-1,u,r.columns-1);var p=n.subMatrix(s,n.rows-1,u,n.columns-1);var v=t(e.add(h,g),e.add(l,p),s,u);var w=t(e.add(d,g),l,s,u);var y=t(h,e.sub(f,p),s,u);var x=t(g,e.sub(m,l),s,u);var M=t(e.add(h,c),p,s,u);var b=t(e.sub(d,h),e.add(l,f),s,u);var A=t(e.sub(c,g),e.add(m,p),s,u);var S=e.add(v,x);S.sub(M);S.add(A);var _=e.add(y,M);var R=e.add(w,x);var E=e.sub(v,w);E.add(y);E.add(b);var O=e.zeros(2*S.rows,2*S.columns);O=O.setSubMatrix(S,0,0);O=O.setSubMatrix(_,S.rows,0);O=O.setSubMatrix(R,0,S.columns);O=O.setSubMatrix(E,S.rows,S.columns);return O.subMatrix(0,i-1,0,o-1)}(r,t,u,h)}scaleRows(t,e){if((t=void 0===t?0:t)>=(e=void 0===e?1:e))throw new RangeError("min should be strictly smaller than max");for(var r=this.constructor.empty(this.rows,this.columns),i=0;i<this.rows;i++){var o=(0,n.default)(this.getRow(i),{min:t,max:e});r.setRow(i,o)}return r}scaleColumns(t,e){if((t=void 0===t?0:t)>=(e=void 0===e?1:e))throw new RangeError("min should be strictly smaller than max");for(var r=this.constructor.empty(this.rows,this.columns),i=0;i<this.columns;i++){var o=(0,n.default)(this.getColumn(i),{min:t,max:e});r.setColumn(i,o)}return r}kroneckerProduct(t){t=this.constructor.checkMatrix(t);for(var e=this.rows,r=this.columns,n=t.rows,i=t.columns,o=new this.constructor[Symbol.species](e*n,r*i),s=0;s<e;s++)for(var a=0;a<r;a++)for(var u=0;u<n;u++)for(var h=0;h<i;h++)o[n*s+u][i*a+h]=this.get(s,a)*t.get(u,h);return o}transpose(){for(var t=new this.constructor[Symbol.species](this.columns,this.rows),e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)t.set(r,e,this.get(e,r));return t}sortRows(t){void 0===t&&(t=r);for(var e=0;e<this.rows;e++)this.setRow(e,this.getRow(e).sort(t));return this}sortColumns(t){void 0===t&&(t=r);for(var e=0;e<this.columns;e++)this.setColumn(e,this.getColumn(e).sort(t));return this}subMatrix(t,e,r,n){(0,s.checkRange)(this,t,e,r,n);for(var i=new this.constructor[Symbol.species](e-t+1,n-r+1),o=t;o<=e;o++)for(var a=r;a<=n;a++)i[o-t][a-r]=this.get(o,a);return i}subMatrixRow(t,e,r){if(void 0===e&&(e=0),void 0===r&&(r=this.columns-1),e>r||e<0||e>=this.columns||r<0||r>=this.columns)throw new RangeError("Argument out of range");for(var n=new this.constructor[Symbol.species](t.length,r-e+1),i=0;i<t.length;i++)for(var o=e;o<=r;o++){if(t[i]<0||t[i]>=this.rows)throw new RangeError(`Row index out of range: ${t[i]}`);n.set(i,o-e,this.get(t[i],o))}return n}subMatrixColumn(t,e,r){if(void 0===e&&(e=0),void 0===r&&(r=this.rows-1),e>r||e<0||e>=this.rows||r<0||r>=this.rows)throw new RangeError("Argument out of range");for(var n=new this.constructor[Symbol.species](r-e+1,t.length),i=0;i<t.length;i++)for(var o=e;o<=r;o++){if(t[i]<0||t[i]>=this.columns)throw new RangeError(`Column index out of range: ${t[i]}`);n.set(o-e,i,this.get(o,t[i]))}return n}setSubMatrix(t,e,r){t=this.constructor.checkMatrix(t);var n=e+t.rows-1,i=r+t.columns-1;(0,s.checkRange)(this,e,n,r,i);for(var o=0;o<t.rows;o++)for(var a=0;a<t.columns;a++)this[e+o][r+a]=t.get(o,a);return this}selection(t,e){for(var r=(0,s.checkIndices)(this,t,e),n=new this.constructor[Symbol.species](t.length,e.length),i=0;i<r.row.length;i++)for(var o=r.row[i],a=0;a<r.column.length;a++){var 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Error("Determinant can only be calculated for a square matrix.")}pseudoInverse(t){void 0===t&&(t=Number.EPSILON);for(var e=new o.default(this,{autoTranspose:!0}),r=e.leftSingularVectors,n=e.rightSingularVectors,i=e.diagonal,s=0;s<i.length;s++)Math.abs(i[s])>t?i[s]=1/i[s]:i[s]=0;return i=this.constructor[Symbol.species].diag(i),n.mmul(i.mmul(r.transposeView()))}clone(){for(var t=new this.constructor[Symbol.species](this.rows,this.columns),e=0;e<this.rows;e++)for(var r=0;r<this.columns;r++)t.set(e,r,this.get(e,r));return t}}function r(t,e){return t-e}e.prototype.klass="Matrix",e.random=e.rand,e.diagonal=e.diag,e.prototype.diagonal=e.prototype.diag,e.identity=e.eye,e.prototype.negate=e.prototype.neg,e.prototype.tensorProduct=e.prototype.kroneckerProduct,e.prototype.determinant=e.prototype.det;var p,v="\n(function %name%(matrix, %args%) {\n    var newMatrix = new this[Symbol.species](matrix);\n    return newMatrix.%name%(%args%);\n})\n",w=eval;for(var y 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         this.set(i, j, this.get(i, j) %op% matrix.get(i, j));\n        }\n    }\n    return this;\n})\n",{name:`${y[1]}M`,op:y[0]})),A=w(z("\n(function %name%(matrix, value) {\n    var newMatrix = new this[Symbol.species](matrix);\n    return newMatrix.%name%(value);\n})\n",{name:y[1]}));for(p=1;p<y.length;p++)e.prototype[y[p]]=x,e.prototype[`${y[p]}S`]=M,e.prototype[`${y[p]}M`]=b,e[y[p]]=A}var S=[["~","not"]];for(var _ of(["abs","acos","acosh","asin","asinh","atan","atanh","cbrt","ceil","clz32","cos","cosh","exp","expm1","floor","fround","log","log1p","log10","log2","round","sign","sin","sinh","sqrt","tan","tanh","trunc"].forEach(function(t){S.push([`Math.${t}`,t])}),S)){var R=w(z("\n(function %name%() {\n    for (var i = 0; i < this.rows; i++) {\n        for (var j = 0; j < this.columns; j++) {\n            this.set(i, j, %method%(this.get(i, j)));\n        }\n    }\n    return this;\n})\n",{name:_[1],method:_[0]})),E=w(z("\n(function %name%(matrix) {\n    var newMatrix = new this[Symbol.species](matrix);\n    return newMatrix.%name%();\n})\n",{name:_[1]}));for(p=1;p<_.length;p++)e.prototype[_[p]]=R,e[_[p]]=E}for(var O of[["Math.pow",1,"pow"]]){var k="arg0";for(p=1;p<O[1];p++)k+=`, arg${p}`;if(1!==O[1]){var P=w(z("\n(function %name%(%args%) {\n    for (var i = 0; i < this.rows; i++) {\n        for (var j = 0; j < this.columns; j++) {\n            this.set(i, j, %method%(this.get(i, j), %args%));\n        }\n    }\n    return this;\n})\n",{name:O[2],method:O[0],args:k})),C=w(z(v,{name:O[2],args:k}));for(p=2;p<O.length;p++)e.prototype[O[p]]=P,e[O[p]]=C}else{var j={name:O[2],args:k,method:O[0]},T=w(z("\n(function %name%(value) {\n    if (typeof value === 'number') return this.%name%S(value);\n    return this.%name%M(value);\n})\n",j)),N=w(z("\n(function %name%S(value) {\n    for (var i = 0; i < this.rows; i++) {\n        for (var j = 0; j < this.columns; j++) {\n            this.set(i, j, %method%(this.get(i, j), value));\n        }\n    }\n    return this;\n})\n",j)),V=w(z("\n(function %name%M(matrix) {\n    matrix = this.constructor.checkMatrix(matrix);\n    if (this.rows !== matrix.rows ||\n        this.columns !== matrix.columns) {\n        throw new RangeError('Matrices dimensions must be equal');\n    }\n    for (var i = 0; i < this.rows; i++) {\n        for (var j = 0; j < this.columns; j++) {\n            this.set(i, j, %method%(this.get(i, j), matrix.get(i, j)));\n        }\n    }\n    return this;\n})\n",j)),D=w(z("\n(function %name%(matrix, %args%) {\n    var newMatrix = new this[Symbol.species](matrix);\n    return newMatrix.%name%(%args%);\n})\n",j));for(p=2;p<O.length;p++)e.prototype[O[p]]=T,e.prototype[`${O[p]}M`]=V,e.prototype[`${O[p]}S`]=N,e[O[p]]=D}}function z(t,e){for(var r in e)t=t.replace(new RegExp(`%${r}%`,"g"),e[r]);return t}return e};var n=p(r(55)),i=p(r(10)),o=p(r(8)),s=r(6),a=p(r(57)),u=p(r(58)),h=p(r(59)),l=p(r(60)),c=p(r(61)),f=p(r(62)),d=p(r(63)),m=p(r(64)),g=p(r(65));function p(t){return t&&t.__esModule?t:{default:t}}},function(t,e,r){"use strict";Object.defineProperty(e,"__esModule",{value:!0});var n=r(0),i=r(11);e.default=class{constructor(t,e={}){var r,o=(t=n.WrapperMatrix2D.checkMatrix(t)).rows,s=t.columns,a=e.computeLeftSingularVectors,u=void 0===a||a,h=e.computeRightSingularVectors,l=void 0===h||h,c=e.autoTranspose,f=void 0!==c&&c,d=Boolean(u),m=Boolean(l),g=!1;if(o<s)if(f){o=(r=t.transpose()).rows,s=r.columns,g=!0;var p=d;d=m,m=p}else r=t.clone(),console.warn("Computing SVD on a matrix with more columns than rows. 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B=-b[X]/b[k+1],U=k+1;U<o;U++)r[U][X]+=B*A[U]}if(m)for(var W=k+1;W<s;W++)M[W][k]=b[W]}}var Y=Math.min(s,o+1);if(R<s&&(y[R]=r[R][R]),o<Y&&(y[Y-1]=0),E+1<Y&&(b[E]=r[E][Y-1]),b[Y-1]=0,d){for(var $=R;$<v;$++){for(var J=0;J<o;J++)x[J][$]=0;x[$][$]=1}for(var G=R-1;G>=0;G--)if(0!==y[G]){for(var K=G+1;K<v;K++){for(var Z=0,H=G;H<o;H++)Z+=x[H][G]*x[H][K];Z=-Z/x[G][G];for(var Q=G;Q<o;Q++)x[Q][K]+=Z*x[Q][G]}for(var tt=G;tt<o;tt++)x[tt][G]=-x[tt][G];x[G][G]=1+x[G][G];for(var et=0;et<G-1;et++)x[et][G]=0}else{for(var rt=0;rt<o;rt++)x[rt][G]=0;x[G][G]=1}}if(m)for(var nt=s-1;nt>=0;nt--){if(nt<E&&0!==b[nt])for(var it=nt+1;it<s;it++){for(var ot=0,st=nt+1;st<s;st++)ot+=M[st][nt]*M[st][it];ot=-ot/M[nt+1][nt];for(var at=nt+1;at<s;at++)M[at][it]+=ot*M[at][nt]}for(var ut=0;ut<s;ut++)M[ut][nt]=0;M[nt][nt]=1}for(var ht=Y-1,lt=Number.EPSILON;Y>0;){var ct=void 0,ft=void 0;for(ct=Y-2;ct>=-1&&-1!==ct;ct--){var dt=Number.MIN_VALUE+lt*Math.abs(y[ct]+Math.abs(y[ct+1]));if(Math.abs(b[ct])<=dt||Number.isNaN(b[ct])){b[ct]=0;break}}if(ct===Y-2)ft=4;else{var mt=void 0;for(mt=Y-1;mt>=ct&&mt!==ct;mt--){var gt=(mt!==Y?Math.abs(b[mt]):0)+(mt!==ct+1?Math.abs(b[mt-1]):0);if(Math.abs(y[mt])<=lt*gt){y[mt]=0;break}}mt===ct?ft=3:mt===Y-1?ft=1:(ft=2,ct=mt)}switch(ct++,ft){case 1:var pt=b[Y-2];b[Y-2]=0;for(var vt=Y-2;vt>=ct;vt--){var wt=(0,i.hypotenuse)(y[vt],pt),yt=y[vt]/wt,xt=pt/wt;if(y[vt]=wt,vt!==ct&&(pt=-xt*b[vt-1],b[vt-1]=yt*b[vt-1]),m)for(var Mt=0;Mt<s;Mt++)wt=yt*M[Mt][vt]+xt*M[Mt][Y-1],M[Mt][Y-1]=-xt*M[Mt][vt]+yt*M[Mt][Y-1],M[Mt][vt]=wt}break;case 2:var bt=b[ct-1];b[ct-1]=0;for(var At=ct;At<Y;At++){var St=(0,i.hypotenuse)(y[At],bt),_t=y[At]/St,Rt=bt/St;if(y[At]=St,bt=-Rt*b[At],b[At]=_t*b[At],d)for(var Et=0;Et<o;Et++)St=_t*x[Et][At]+Rt*x[Et][ct-1],x[Et][ct-1]=-Rt*x[Et][At]+_t*x[Et][ct-1],x[Et][At]=St}break;case 3:var Ot=Math.max(Math.abs(y[Y-1]),Math.abs(y[Y-2]),Math.abs(b[Y-2]),Math.abs(y[ct]),Math.abs(b[ct])),kt=y[Y-1]/Ot,Pt=y[Y-2]/Ot,Ct=b[Y-2]/Ot,jt=y[ct]/Ot,Tt=b[ct]/Ot,Nt=((Pt+kt)*(Pt-kt)+Ct*Ct)/2,Vt=kt*Ct*(kt*Ct),Dt=0;0===Nt&&0===Vt||(Dt=Vt/(Nt+(Dt=Nt<0?0-Math.sqrt(Nt*Nt+Vt):Math.sqrt(Nt*Nt+Vt))));for(var zt=(jt+kt)*(jt-kt)+Dt,Ft=jt*Tt,Lt=ct;Lt<Y-1;Lt++){var It=(0,i.hypotenuse)(zt,Ft);0===It&&(It=Number.MIN_VALUE);var qt=zt/It,Xt=Ft/It;if(Lt!==ct&&(b[Lt-1]=It),zt=qt*y[Lt]+Xt*b[Lt],b[Lt]=qt*b[Lt]-Xt*y[Lt],Ft=Xt*y[Lt+1],y[Lt+1]=qt*y[Lt+1],m)for(var Bt=0;Bt<s;Bt++)It=qt*M[Bt][Lt]+Xt*M[Bt][Lt+1],M[Bt][Lt+1]=-Xt*M[Bt][Lt]+qt*M[Bt][Lt+1],M[Bt][Lt]=It;if(0===(It=(0,i.hypotenuse)(zt,Ft))&&(It=Number.MIN_VALUE),qt=zt/It,Xt=Ft/It,y[Lt]=It,zt=qt*b[Lt]+Xt*y[Lt+1],y[Lt+1]=-Xt*b[Lt]+qt*y[Lt+1],Ft=Xt*b[Lt+1],b[Lt+1]=qt*b[Lt+1],d&&Lt<o-1)for(var Ut=0;Ut<o;Ut++)It=qt*x[Ut][Lt]+Xt*x[Ut][Lt+1],x[Ut][Lt+1]=-Xt*x[Ut][Lt]+qt*x[Ut][Lt+1],x[Ut][Lt]=It}b[Y-2]=zt;break;case 4:if(y[ct]<=0&&(y[ct]=y[ct]<0?-y[ct]:0,m))for(var Wt=0;Wt<=ht;Wt++)M[Wt][ct]=-M[Wt][ct];for(;ct<ht&&!(y[ct]>=y[ct+1]);){var Yt=y[ct];if(y[ct]=y[ct+1],y[ct+1]=Yt,m&&ct<s-1)for(var $t=0;$t<s;$t++)Yt=M[$t][ct+1],M[$t][ct+1]=M[$t][ct],M[$t][ct]=Yt;if(d&&ct<o-1)for(var Jt=0;Jt<o;Jt++)Yt=x[Jt][ct+1],x[Jt][ct+1]=x[Jt][ct],x[Jt][ct]=Yt;ct++}Y--}}if(g){var Gt=M;M=x,x=Gt}this.m=o,this.n=s,this.s=y,this.U=x,this.V=M}solve(t){for(var e=t,r=this.threshold,i=this.s.length,o=n.Matrix.zeros(i,i),s=0;s<i;s++)Math.abs(this.s[s])<=r?o[s][s]=0:o[s][s]=1/this.s[s];for(var a=this.U,u=this.rightSingularVectors,h=u.mmul(o),l=u.rows,c=a.length,f=n.Matrix.zeros(l,c),d=0;d<l;d++)for(var m=0;m<c;m++){for(var g=0,p=0;p<i;p++)g+=h[d][p]*a[m][p];f[d][m]=g}return f.mmul(e)}solveForDiagonal(t){return this.solve(n.Matrix.diag(t))}inverse(){for(var t=this.V,e=this.threshold,r=t.length,i=t[0].length,o=new n.Matrix(r,this.s.length),s=0;s<r;s++)for(var a=0;a<i;a++)Math.abs(this.s[a])>e?o[s][a]=t[s][a]/this.s[a]:o[s][a]=0;for(var u=this.U,h=u.length,l=u[0].length,c=new n.Matrix(r,h),f=0;f<r;f++)for(var d=0;d<h;d++){for(var m=0,g=0;g<l;g++)m+=o[f][g]*u[d][g];c[f][d]=m}return c}get condition(){return this.s[0]/this.s[Math.min(this.m,this.n)-1]}get norm2(){return this.s[0]}get rank(){for(var t=Math.max(this.m,this.n)*this.s[0]*Number.EPSILON,e=0,r=this.s,n=0,i=r.length;n<i;n++)r[n]>t&&e++;return e}get diagonal(){return this.s}get threshold(){return Number.EPSILON/2*Math.max(this.m,this.n)*this.s[0]}get leftSingularVectors(){return n.Matrix.isMatrix(this.U)||(this.U=new n.Matrix(this.U)),this.U}get rightSingularVectors(){return n.Matrix.isMatrix(this.V)||(this.V=new n.Matrix(this.V)),this.V}get diagonalMatrix(){return n.Matrix.diag(this.s)}}},function(t,e,r){"use strict";var n=r(24);function i(t,e){return t-e}e.max=function(t){for(var e=-1/0,r=0;r<t.length;r++)for(var n=0;n<t[r].length;n++)t[r][n]>e&&(e=t[r][n]);return e},e.min=function(t){for(var e=1/0,r=0;r<t.length;r++)for(var n=0;n<t[r].length;n++)t[r][n]<e&&(e=t[r][n]);return e},e.minMax=function(t){for(var e=1/0,r=-1/0,n=0;n<t.length;n++)for(var i=0;i<t[n].length;i++)t[n][i]<e&&(e=t[n][i]),t[n][i]>r&&(r=t[n][i]);return{min:e,max:r}},e.entropy=function(t,e){void 0===e&&(e=0);for(var r=0,n=t.length,i=t[0].length,o=0;o<n;o++)for(var s=0;s<i;s++)r+=t[o][s]*Math.log(t[o][s]+e);return-r},e.mean=function(t,e){void 0===e&&(e=0);var r,n,i,o,s=t.length,a=t[0].length;if(-1===e){for(r=[0],n=s*a,i=0;i<s;i++)for(o=0;o<a;o++)r[0]+=t[i][o];r[0]/=n}else if(0===e)for(r=new Array(a),n=s,o=0;o<a;o++){for(r[o]=0,i=0;i<s;i++)r[o]+=t[i][o];r[o]/=n}else{if(1!==e)throw new Error("Invalid dimension");for(r=new Array(s),n=a,o=0;o<s;o++){for(r[o]=0,i=0;i<a;i++)r[o]+=t[o][i];r[o]/=n}}return r},e.sum=function(t,e){void 0===e&&(e=0);var r,n,i,o=t.length,s=t[0].length;if(-1===e)for(r=[0],n=0;n<o;n++)for(i=0;i<s;i++)r[0]+=t[n][i];else if(0===e)for(r=new Array(s),i=0;i<s;i++)for(r[i]=0,n=0;n<o;n++)r[i]+=t[n][i];else{if(1!==e)throw new Error("Invalid dimension");for(r=new Array(o),i=0;i<o;i++)for(r[i]=0,n=0;n<s;n++)r[i]+=t[i][n]}return r},e.product=function(t,e){void 0===e&&(e=0);var r,n,i,o=t.length,s=t[0].length;if(-1===e)for(r=[1],n=0;n<o;n++)for(i=0;i<s;i++)r[0]*=t[n][i];else if(0===e)for(r=new Array(s),i=0;i<s;i++)for(r[i]=1,n=0;n<o;n++)r[i]*=t[n][i];else{if(1!==e)throw new Error("Invalid dimension");for(r=new Array(o),i=0;i<o;i++)for(r[i]=1,n=0;n<s;n++)r[i]*=t[i][n]}return r},e.standardDeviation=function(t,r,n){for(var i=e.variance(t,r,n),o=i.length,s=0;s<o;s++)i[s]=Math.sqrt(i[s]);return i},e.variance=function(t,r,n){void 0===n&&(n=!0),r=r||e.mean(t);var i=t.length;if(0===i)return[];for(var o=t[0].length,s=new Array(o),a=0;a<o;a++){for(var u=0,h=0,l=0,c=0;c<i;c++)u+=l=t[c][a]-r[a],h+=l*l;s[a]=n?(h-u*u/i)/(i-1):(h-u*u/i)/i}return s},e.median=function(t){for(var e=t.length,r=t[0].length,n=new Array(r),o=0;o<r;o++){for(var s=new Array(e),a=0;a<e;a++)s[a]=t[a][o];s.sort(i);var u=s.length;n[o]=u%2==0?.5*(s[u/2]+s[u/2-1]):s[Math.floor(u/2)]}return n},e.mode=function(t){var e,r,n=t.length,i=t[0].length,o=new Array(i);for(e=0;e<i;e++){for(var s=new Array(n),a=0;a<n;a++)s[a]=0;var u=new Array(n),h=0;for(r=0;r<n;r++){var l=u.indexOf(t[r][e]);l>=0?s[l]++:(u[h]=t[r][e],s[h]=1,h++)}var c=0,f=0;for(r=0;r<h;r++)s[r]>c&&(c=s[r],f=r);o[e]=u[f]}return o},e.skewness=function(t,r){void 0===r&&(r=!0);for(var n=e.mean(t),i=t.length,o=n.length,s=new Array(o),a=0;a<o;a++){for(var u=0,h=0,l=0;l<i;l++){var c=t[l][a]-n[a];u+=c*c,h+=c*c*c}var f=u/i,d=h/i/Math.pow(f,1.5);if(r){var m=Math.sqrt(i*(i-1)),g=i-2;s[a]=m/g*d}else s[a]=d}return s},e.kurtosis=function(t,r){void 0===r&&(r=!0);for(var n=e.mean(t),i=t.length,o=t[0].length,s=new Array(o),a=0;a<o;a++){for(var u=0,h=0,l=0;l<i;l++){var c=t[l][a]-n[a];u+=c*c,h+=c*c*c*c}var f=u/i,d=h/i;if(r){var m=u/(i-1),g=i*(i+1)/((i-1)*(i-2)*(i-3)),p=h/(m*m),v=(i-1)*(i-1)/((i-2)*(i-3));s[a]=g*p-3*v}else s[a]=d/(f*f)-3}return s},e.standardError=function(t){for(var r=t.length,n=e.standardDeviation(t),i=n.length,o=new Array(i),s=Math.sqrt(r),a=0;a<i;a++)o[a]=n[a]/s;return o},e.covariance=function(t,r){return e.scatter(t,void 0,r)},e.scatter=function(t,r,n){void 0===n&&(n=0),void 0===r&&(0===n?r=t.length-1:1===n&&(r=t[0].length-1));var i=e.mean(t,n),o=t.length;if(0===o)return[[]];var s,a,u,h,l,c=t[0].length;if(0===n){for(s=new Array(c),a=0;a<c;a++)s[a]=new Array(c);for(a=0;a<c;a++)for(u=a;u<c;u++){for(h=0,l=0;l<o;l++)h+=(t[l][u]-i[u])*(t[l][a]-i[a]);h/=r,s[a][u]=h,s[u][a]=h}}else{if(1!==n)throw new Error("Invalid dimension");for(s=new Array(o),a=0;a<o;a++)s[a]=new Array(o);for(a=0;a<o;a++)for(u=a;u<o;u++){for(h=0,l=0;l<c;l++)h+=(t[u][l]-i[u])*(t[a][l]-i[a]);h/=r,s[a][u]=h,s[u][a]=h}}return s},e.correlation=function(t){var r,n,i=e.mean(t),o=e.standardDeviation(t,!0,i),s=e.zScores(t,i,o),a=t.length,u=t[0].length,h=new Array(u);for(r=0;r<u;r++)h[r]=new Array(u);for(r=0;r<u;r++)for(n=r;n<u;n++){for(var l=0,c=0,f=s.length;c<f;c++)l+=s[c][n]*s[c][r];l/=a-1,h[r][n]=l,h[n][r]=l}return h},e.zScores=function(t,r,n){return r=r||e.mean(t),void 0===n&&(n=e.standardDeviation(t,!0,r)),e.standardize(e.center(t,r,!1),n,!0)},e.center=function(t,r,n){r=r||e.mean(t);var i,o,s,a=t,u=t.length;if(!n)for(a=new Array(u),i=0;i<u;i++)a[i]=new Array(t[i].length);for(i=0;i<u;i++){var h=a[i];for(o=0,s=h.length;o<s;o++)h[o]=t[i][o]-r[o]}return a},e.standardize=function(t,r,n){void 0===r&&(r=e.standardDeviation(t));var i,o,s,a=t,u=t.length;if(!n)for(a=new Array(u),i=0;i<u;i++)a[i]=new Array(t[i].length);for(i=0;i<u;i++){var h=a[i],l=t[i];for(o=0,s=h.length;o<s;o++)0===r[o]||isNaN(r[o])||(h[o]=l[o]/r[o])}return a},e.weightedVariance=function(t,r){var n=e.mean(t),i=t.length;if(0===i)return[];for(var o=t[0].length,s=new Array(o),a=0;a<o;a++){for(var u=0,h=0,l=0,c=0;c<i;c++){var f=t[c][a]-n[a],d=r[c];u+=d*(f*f),l+=d,h+=d*d}s[a]=u*(l/(l*l-h))}return s},e.weightedMean=function(t,e,r){void 0===r&&(r=0);var i=t.length;if(0===i)return[];var o,s,a,u,h,l,c=t[0].length;if(0===r){for(o=new Array(c),s=0;s<c;s++)o[s]=0;for(s=0;s<i;s++)for(l=t[s],h=e[s],u=0;u<c;u++)o[u]+=l[u]*h}else{if(1!==r)throw new Error("Invalid dimension");for(o=new Array(i),s=0;s<i;s++)o[s]=0;for(u=0;u<i;u++)for(l=t[u],h=e[u],s=0;s<c;s++)o[u]+=l[s]*h}var f=n.sum(e);if(0!==f)for(s=0,a=o.length;s<a;s++)o[s]/=f;return o},e.weightedCovariance=function(t,r,n,i){i=i||0,n=n||e.weightedMean(t,r,i);for(var o=0,s=0,a=0,u=r.length;a<u;a++)o+=r[a],s+=r[a]*r[a];var h=o/(o*o-s);return e.weightedScatter(t,r,n,h,i)},e.weightedScatter=function(t,r,n,i,o){o=o||0,n=n||e.weightedMean(t,r,o),void 0===i&&(i=1);var s=t.length;if(0===s)return[[]];var a,u,h,l,c,f=t[0].length;if(0===o){for(a=new Array(f),u=0;u<f;u++)a[u]=new Array(f);for(u=0;u<f;u++)for(h=u;h<f;h++){for(c=0,l=0;l<s;l++)c+=r[l]*(t[l][h]-n[h])*(t[l][u]-n[u]);a[u][h]=c*i,a[h][u]=c*i}}else{if(1!==o)throw new Error("Invalid dimension");for(a=new Array(s),u=0;u<s;u++)a[u]=new Array(s);for(u=0;u<s;u++)for(h=u;h<s;h++){for(c=0,l=0;l<f;l++)c+=r[l]*(t[h][l]-n[h])*(t[u][l]-n[u]);a[u][h]=c*i,a[h][u]=c*i}}return a}},function(t,e,r){"use strict";Object.defineProperty(e,"__esModule",{value:!0});var n=r(0);e.default=class{constructor(t){var e,r,i,o,s,a,u,h,l,c=(t=n.WrapperMatrix2D.checkMatrix(t)).clone(),f=c.rows,d=c.columns,m=new Array(f),g=1;for(e=0;e<f;e++)m[e]=e;for(h=new Array(f),r=0;r<d;r++){for(e=0;e<f;e++)h[e]=c.get(e,r);for(e=0;e<f;e++){for(l=Math.min(e,r),s=0,i=0;i<l;i++)s+=c.get(e,i)*h[i];h[e]-=s,c.set(e,r,h[e])}for(o=r,e=r+1;e<f;e++)Math.abs(h[e])>Math.abs(h[o])&&(o=e);if(o!==r){for(i=0;i<d;i++)a=c.get(o,i),c.set(o,i,c.get(r,i)),c.set(r,i,a);u=m[o],m[o]=m[r],m[r]=u,g=-g}if(r<f&&0!==c.get(r,r))for(e=r+1;e<f;e++)c.set(e,r,c.get(e,r)/c.get(r,r))}this.LU=c,this.pivotVector=m,this.pivotSign=g}isSingular(){for(var t=this.LU,e=t.columns,r=0;r<e;r++)if(0===t[r][r])return!0;return!1}solve(t){t=n.Matrix.checkMatrix(t);var e=this.LU;if(e.rows!==t.rows)throw new Error("Invalid matrix dimensions");if(this.isSingular())throw new Error("LU matrix is singular");var r,i,o,s=t.columns,a=t.subMatrixRow(this.pivotVector,0,s-1),u=e.columns;for(o=0;o<u;o++)for(r=o+1;r<u;r++)for(i=0;i<s;i++)a[r][i]-=a[o][i]*e[r][o];for(o=u-1;o>=0;o--){for(i=0;i<s;i++)a[o][i]/=e[o][o];for(r=0;r<o;r++)for(i=0;i<s;i++)a[r][i]-=a[o][i]*e[r][o]}return a}get determinant(){var t=this.LU;if(!t.isSquare())throw new Error("Matrix must be square");for(var e=this.pivotSign,r=t.columns,n=0;n<r;n++)e*=t[n][n];return e}get lowerTriangularMatrix(){for(var t=this.LU,e=t.rows,r=t.columns,i=new n.Matrix(e,r),o=0;o<e;o++)for(var s=0;s<r;s++)i[o][s]=o>s?t[o][s]:o===s?1:0;return i}get upperTriangularMatrix(){for(var t=this.LU,e=t.rows,r=t.columns,i=new n.Matrix(e,r),o=0;o<e;o++)for(var s=0;s<r;s++)i[o][s]=o<=s?t[o][s]:0;return i}get pivotPermutationVector(){return this.pivotVector.slice()}}},function(t,e,r){"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.hypotenuse=function(t,e){var r=0;if(Math.abs(t)>Math.abs(e))return r=e/t,Math.abs(t)*Math.sqrt(1+r*r);if(0!==e)return r=t/e,Math.abs(e)*Math.sqrt(1+r*r);return 0},e.getFilled2DArray=function(t,e,r){for(var n=new Array(t),i=0;i<t;i++){n[i]=new Array(e);for(var o=0;o<e;o++)n[i][o]=r}return n}},function(t,e,r){"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.default=function(t){if(!Array.isArray(t))throw new Error("input must be an array");if(0===t.length)throw new Error("input must not be empty");for(var e=0,r=0;r<t.length;r++)e+=t[r];return e/t.length}},function(t,e,r){"use strict";var n=r(83);function i(){this.children=[],this.distance=-1,this.index=[]}i.prototype.cut=function(t){if(t<0)throw new RangeError("Threshold too small");var e=new i;e.children=this.children,e.distance=this.distance,e.index=this.index;for(var r=[e],n=[];r.length>0;){var o=r.shift();t>=o.distance?n.push(o):r=r.concat(o.children)}return n},i.prototype.group=function(t){if(!Number.isInteger(t)||t<1)throw new RangeError("Number of groups must be a positive integer");var e=new n(function(t,e){return e.distance-t.distance});for(e.push(this);e.size()<t;){var r=e.pop();if(0===r.children.length)break;r.children.forEach(t=>e.push(t))}var o=new i;return 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i,o,s,a,u,h,l,c=t-1;for(h=1;h<=c-1;h++){for(l=0,a=h;a<=c;a++)l+=Math.abs(e[a][h-1]);if(0!==l){for(s=0,a=c;a>=h;a--)r[a]=e[a][h-1]/l,s+=r[a]*r[a];for(o=Math.sqrt(s),r[h]>0&&(o=-o),s-=r[h]*o,r[h]=r[h]-o,u=h;u<t;u++){for(i=0,a=c;a>=h;a--)i+=r[a]*e[a][u];for(i/=s,a=h;a<=c;a++)e[a][u]-=i*r[a]}for(a=0;a<=c;a++){for(i=0,u=c;u>=h;u--)i+=r[u]*e[a][u];for(i/=s,u=h;u<=c;u++)e[a][u]-=i*r[u]}r[h]=l*r[h],e[h][h-1]=l*o}}for(a=0;a<t;a++)for(u=0;u<t;u++)n[a][u]=a===u?1:0;for(h=c-1;h>=1;h--)if(0!==e[h][h-1]){for(a=h+1;a<=c;a++)r[a]=e[a][h-1];for(u=h;u<=c;u++){for(o=0,a=h;a<=c;a++)o+=r[a]*n[a][u];for(o=o/r[h]/e[h][h-1],a=h;a<=c;a++)n[a][u]+=o*r[a]}}}(h,m,g,l),function(t,e,r,n,i){var s,a,u,h,l,c,f,d,m,g,p,v,w,y,x,M=t-1,b=t-1,A=Number.EPSILON,S=0,_=0,R=0,E=0,O=0,k=0,P=0,C=0;for(s=0;s<t;s++)for((s<0||s>b)&&(r[s]=i[s][s],e[s]=0),a=Math.max(s-1,0);a<t;a++)_+=Math.abs(i[s][a]);for(;M>=0;){for(h=M;h>0&&(0===(k=Math.abs(i[h-1][h-1])+Math.abs(i[h][h]))&&(k=_),!(Math.abs(i[h][h-1])<A*k));)h--;if(h===M)i[M][M]=i[M][M]+S,r[M]=i[M][M],e[M]=0,M--,C=0;else if(h===M-1){if(f=i[M][M-1]*i[M-1][M],R=(i[M-1][M-1]-i[M][M])/2,E=R*R+f,P=Math.sqrt(Math.abs(E)),i[M][M]=i[M][M]+S,i[M-1][M-1]=i[M-1][M-1]+S,d=i[M][M],E>=0){for(P=R>=0?R+P:R-P,r[M-1]=d+P,r[M]=r[M-1],0!==P&&(r[M]=d-f/P),e[M-1]=0,e[M]=0,d=i[M][M-1],k=Math.abs(d)+Math.abs(P),R=d/k,E=P/k,O=Math.sqrt(R*R+E*E),R/=O,E/=O,a=M-1;a<t;a++)P=i[M-1][a],i[M-1][a]=E*P+R*i[M][a],i[M][a]=E*i[M][a]-R*P;for(s=0;s<=M;s++)P=i[s][M-1],i[s][M-1]=E*P+R*i[s][M],i[s][M]=E*i[s][M]-R*P;for(s=0;s<=b;s++)P=n[s][M-1],n[s][M-1]=E*P+R*n[s][M],n[s][M]=E*n[s][M]-R*P}else 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if(h=s,0===e[s]?(x=o(-g,-p,f,E),i[s][M-1]=x[0],i[s][M]=x[1]):(d=i[s][s+1],m=i[s+1][s],v=(r[s]-R)*(r[s]-R)+e[s]*e[s]-E*E,w=2*(r[s]-R)*E,0===v&&0===w&&(v=A*_*(Math.abs(f)+Math.abs(E)+Math.abs(d)+Math.abs(m)+Math.abs(P))),x=o(d*O-P*g+E*p,d*k-P*p-E*g,v,w),i[s][M-1]=x[0],i[s][M]=x[1],Math.abs(d)>Math.abs(P)+Math.abs(E)?(i[s+1][M-1]=(-g-f*i[s][M-1]+E*i[s][M])/d,i[s+1][M]=(-p-f*i[s][M]-E*i[s][M-1])/d):(x=o(-O-m*i[s][M-1],-k-m*i[s][M],P,E),i[s+1][M-1]=x[0],i[s+1][M]=x[1])),c=Math.max(Math.abs(i[s][M-1]),Math.abs(i[s][M])),A*c*c>1)for(a=s;a<=M;a++)i[a][M-1]=i[a][M-1]/c,i[a][M]=i[a][M]/c}for(s=0;s<t;s++)if(s<0||s>b)for(a=s;a<t;a++)n[s][a]=i[s][a];for(a=t-1;a>=0;a--)for(s=0;s<=b;s++){for(P=0,u=0;u<=Math.min(a,b);u++)P+=n[s][u]*i[u][a];n[s][a]=P}}}(h,f,c,l,m)}this.n=h,this.e=f,this.d=c,this.V=l}get realEigenvalues(){return this.d}get imaginaryEigenvalues(){return this.e}get eigenvectorMatrix(){return n.Matrix.isMatrix(this.V)||(this.V=new n.Matrix(this.V)),this.V}get diagonalMatrix(){var t,e,r=this.n,i=this.e,o=this.d,s=new n.Matrix(r,r);for(t=0;t<r;t++){for(e=0;e<r;e++)s[t][e]=0;s[t][t]=o[t],i[t]>0?s[t][t+1]=i[t]:i[t]<0&&(s[t][t-1]=i[t])}return s}}},function(t,e,r){"use strict";Object.defineProperty(e,"__esModule",{value:!0});var n=r(0);e.default=class{constructor(t){if(!(t=n.WrapperMatrix2D.checkMatrix(t)).isSymmetric())throw new Error("Matrix is not symmetric");var e,r,i,o=t,s=o.rows,a=new n.Matrix(s,s),u=!0;for(r=0;r<s;r++){var h=a[r],l=0;for(i=0;i<r;i++){var c=a[i],f=0;for(e=0;e<i;e++)f+=c[e]*h[e];h[i]=f=(o.get(r,i)-f)/a[i][i],l+=f*f}for(u&=(l=o.get(r,r)-l)>0,a[r][r]=Math.sqrt(Math.max(l,0)),i=r+1;i<s;i++)a[r][i]=0}if(!u)throw new Error("Matrix is not positive definite");this.L=a}solve(t){t=n.WrapperMatrix2D.checkMatrix(t);var e=this.L,r=e.rows;if(t.rows!==r)throw new Error("Matrix dimensions do not match");var 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set");for(var e=new Array(t.length),r=0;r<e.length;++r)e[r]=u(t[r],this.means,this.calculateProbabilities);return e}toJSON(){return{modelName:"NaiveBayes",means:this.means,calculateProbabilities:this.calculateProbabilities}}static load(t){if("NaiveBayes"!==t.modelName)throw new RangeError("The current model is not a Multinomial Naive Bayes, current model:",t.name);return new a(!0,t)}}function u(t,e,r){for(var n=0,i=-1,o=0;o<r.length;++o){for(var s=r[o][0],a=1;a<r[0][1].length+1;++a)s+=h(t[a-1],e[o][a-1],r[o][a][0],r[o][a][1]);(s=Math.exp(s))>n&&(n=s,i=o)}return i}function h(t,e,r,n){return t-=e,Math.log(r*Math.exp(t*t/n))}e.GaussianNB=a},function(t,e,r){"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.MultinomialNB=void 0;var n=function(t){return t&&t.__esModule?t:{default:t}}(r(0)),i=r(30);class o{constructor(t){t&&(this.conditionalProbability=n.default.checkMatrix(t.conditionalProbability),this.priorProbability=n.default.checkMatrix(t.priorProbability))}train(t,e){if((t=n.default.checkMatrix(t)).rows!==e.length)throw new RangeError("the size of the training set and the training labels must be the same.");var r=(0,i.separateClasses)(t,e);this.priorProbability=new n.default(r.length,1);for(var o=0;o<r.length;++o)this.priorProbability[o][0]=Math.log(r[o].length/t.rows);var a=t.columns;for(this.conditionalProbability=new n.default(r.length,a),o=0;o<r.length;++o){var u=n.default.checkMatrix(r[o]),h=u.sum()+a;this.conditionalProbability.setRow(o,u.sum("column").add(1).div(h).apply(s))}}predict(t){t=n.default.checkMatrix(t);for(var e=new Array(t.rows),r=0;r<t.rows;++r){var i=t.getRowVector(r);e[r]=this.conditionalProbability.clone().mulRowVector(i).sum("row").add(this.priorProbability).maxIndex()[0]}return e}toJSON(){return{name:"MultinomialNB",priorProbability:this.priorProbability,conditionalProbability:this.conditionalProbability}}static load(t){if("MultinomialNB"!==t.name)throw new RangeError(`${t.name} is not a Multinomial Naive Bayes`);return new o(t)}}function s(t,e){this[t][e]=Math.log(this[t][e])}e.MultinomialNB=o},function(t,e,r){"use strict";Object.defineProperty(e,"__esModule",{value:!0});var n=o(r(111)),i=o(r(1));function o(t){return t&&t.__esModule?t:{default:t}}class s{constructor(t,e,r={}){if(!0===t){var o=e;return this.kdTree=new n.default(o.kdTree,r),this.k=o.k,this.classes=new Set(o.classes),void(this.isEuclidean=o.isEuclidean)}for(var s=new Set(e),a=r.distance,u=void 0===a?i.default:a,h=r.k,l=void 0===h?s.size+1:h,c=new Array(t.length),f=0;f<c.length;++f)c[f]=t[f].slice();for(f=0;f<e.length;++f)c[f].push(e[f]);this.kdTree=new n.default(c,u),this.k=l,this.classes=s,this.isEuclidean=u===i.default}static load(t,e=i.default){if("KNN"!==t.name)throw new Error("invalid model: "+t.name);if(!t.isEuclidean&&e===i.default)throw new Error("a custom distance function was used to create the model. Please provide it again");if(t.isEuclidean&&e!==i.default)throw new Error("the model was created with the default distance function. Do not load it with another one");return new s(!0,t,e)}toJSON(){return{name:"KNN",kdTree:this.kdTree,k:this.k,classes:Array.from(this.classes),isEuclidean:this.isEuclidean}}predict(t){if(Array.isArray(t)){if("number"==typeof t[0])return a(this,t);if(Array.isArray(t[0])&&"number"==typeof t[0][0]){for(var e=new Array(t.length),r=0;r<t.length;r++)e[r]=a(this,t[r]);return e}}throw new TypeError("dataset to predict must be an array or a matrix")}}function a(t,e){var r=t.kdTree.nearest(e,t.k),n={},i=-1,o=-1,s=r[0][0].length-1;for(var a of t.classes)n[a]=0;for(var u=0;u<r.length;++u){var h=r[u][0][s],l=++n[h];l>o&&(i=h,o=l)}return i}e.default=s},function(t,e,r){"use strict";
/*
 * Original code from:
 *
 * k-d Tree JavaScript - V 1.01
 *
 * https://github.com/ubilabs/kd-tree-javascript
 *
 * @author Mircea Pricop <pricop@ubilabs.net>, 2012
 * @author Martin Kleppe <kleppe@ubilabs.net>, 2012
 * @author Ubilabs http://ubilabs.net, 2012
 * @license MIT License <http://www.opensource.org/licenses/mit-license.php>
 */
function n(t,e,r){this.obj=t,this.left=null,this.right=null,this.parent=r,this.dimension=e}Object.defineProperty(e,"__esModule",{value:!0});e.default=class{constructor(t,e){if(Array.isArray(t)){this.dimensions=new Array(t[0].length);for(var r=0;r<this.dimensions.length;r++)this.dimensions[r]=r;this.root=function t(e,r,i,o){var s=r%o.length;if(0===e.length)return null;if(1===e.length)return new n(e[0],s,i);e.sort((t,e)=>t[o[s]]-e[o[s]]);var a=Math.floor(e.length/2),u=new n(e[a],s,i);return u.left=t(e.slice(0,a),r+1,u,o),u.right=t(e.slice(a+1),r+1,u,o),u}(t,0,null,this.dimensions)}else this.dimensions=t.dimensions,this.root=t,function t(e){e.left&&(e.left.parent=e,t(e.left)),e.right&&(e.right.parent=e,t(e.right))}(this.root);this.metric=e}toJSON(){var t=function t(e){var r=new n(e.obj,e.dimension,null);return e.left&&(r.left=t(e.left)),e.right&&(r.right=t(e.right)),r}(this.root);return t.dimensions=this.dimensions,t}nearest(t,e,r){var n,o=this.metric,s=this.dimensions,a=new i(function(t){return-t[1]});if(r)for(n=0;n<e;n+=1)a.push([null,r]);this.root&&function r(n){var i,u,h,l,c=s[n.dimension],f=o(t,n.obj),d={};function m(t,r){a.push([t,r]),a.size()>e&&a.pop()}for(l=0;l<s.length;l+=1)l===n.dimension?d[s[l]]=t[s[l]]:d[s[l]]=n.obj[s[l]];u=o(d,n.obj),null!==n.right||null!==n.left?(r(i=null===n.right?n.left:null===n.left?n.right:t[c]<n.obj[c]?n.left:n.right),(a.size()<e||f<a.peek()[1])&&m(n,f),(a.size()<e||Math.abs(u)<a.peek()[1])&&null!==(h=i===n.left?n.right:n.left)&&r(h)):(a.size()<e||f<a.peek()[1])&&m(n,f)}(this.root);var u=[];for(n=0;n<Math.min(e,a.content.length);n+=1)a.content[n][0]&&u.push([a.content[n][0].obj,a.content[n][1]]);return u}};class i{constructor(t){this.content=[],this.scoreFunction=t}push(t){this.content.push(t),this.bubbleUp(this.content.length-1)}pop(){var t=this.content[0],e=this.content.pop();return this.content.length>0&&(this.content[0]=e,this.sinkDown(0)),t}peek(){return this.content[0]}size(){return this.content.length}bubbleUp(t){for(var e=this.content[t];t>0;){var r=Math.floor((t+1)/2)-1,n=this.content[r];if(!(this.scoreFunction(e)<this.scoreFunction(n)))break;this.content[r]=e,this.content[t]=n,t=r}}sinkDown(t){for(var e=this.content.length,r=this.content[t],n=this.scoreFunction(r);;){var i=2*(t+1),o=i-1,s=null;if(o<e){var a=this.content[o],u=this.scoreFunction(a);u<n&&(s=o)}if(i<e){var h=this.content[i];this.scoreFunction(h)<(null===s?n:u)&&(s=i)}if(null===s)break;this.content[t]=this.content[s],this.content[s]=r,t=s}}}},function(t,e,r){"use strict";Object.defineProperty(e,"__esModule",{value:!0});var n=r(113);Object.defineProperty(e,"PLS",{enumerable:!0,get:function(){return n.PLS}});var i=r(114);Object.defineProperty(e,"KOPLS",{enumerable:!0,get:function(){return i.KOPLS}})},function(t,e,r){"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.PLS=void 0;var n=s(r(0)),i=s(r(9)),o=function(t){if(t&&t.__esModule)return t;var e={};if(null!=t)for(var r in 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rows");this.meanX=i.default.mean(t),this.stdDevX=i.default.standardDeviation(t,this.meanX,!0),this.meanY=i.default.mean(e),this.stdDevY=i.default.standardDeviation(e,this.meanY,!0),this.scale&&(t=t.clone().subRowVector(this.meanX).divRowVector(this.stdDevX),e=e.clone().subRowVector(this.meanY).divRowVector(this.stdDevY)),void 0===this.latentVectors&&(this.latentVectors=Math.min(t.length-1,t[0].length));for(var r=t.rows,s=t.columns,a=e.rows,h=e.columns,l=t.clone().mul(t).sum(),c=e.clone().mul(e).sum(),f=this.tolerance,d=this.latentVectors,m=n.default.zeros(r,d),g=n.default.zeros(s,d),p=n.default.zeros(a,d),v=n.default.zeros(h,d),w=n.default.zeros(d,d),y=g.clone(),x=0;o.norm(e)>f&&x<d;){for(var M=t.transpose(),b=e.transpose(),A=u(t.clone().mulM(t)),S=u(e.clone().mulM(e)),_=t.getColumnVector(A),R=e.getColumnVector(S),E=n.default.zeros(r,1);o.norm(_.clone().sub(E))>f;){var O=M.mmul(R);O.div(o.norm(O)),E=_,_=t.mmul(O);var k=b.mmul(_);k.div(o.norm(k)),R=e.mmul(k)}E=_;var P=M.mmul(E),C=E.transpose().mmul(E)[0][0],j=P.div(C),T=o.norm(j);j.div(T),E.mul(T),O.mul(T),P=R.transpose().mmul(E),C=E.transpose().mmul(E)[0][0];var N=P.div(C)[0][0];t.sub(E.mmul(j.transpose())),e.sub(E.clone().mul(N).mmul(k.transpose())),m.setColumn(x,E),g.setColumn(x,j),p.setColumn(x,R),v.setColumn(x,k),y.setColumn(x,O),w[x][x]=N,x++}x--,m=m.subMatrix(0,m.rows-1,0,x),g=g.subMatrix(0,g.rows-1,0,x),p=p.subMatrix(0,p.rows-1,0,x),v=v.subMatrix(0,v.rows-1,0,x),y=y.subMatrix(0,y.rows-1,0,x),w=w.subMatrix(0,x,0,x),this.ssqYcal=c,this.E=t,this.F=e,this.T=m,this.P=g,this.U=p,this.Q=v,this.W=y,this.B=w,this.PBQ=g.mmul(w).mmul(v.transpose()),this.R2X=E.transpose().mmul(E).mmul(j.transpose().mmul(j)).div(l)[0][0]}predict(t){var e=n.default.checkMatrix(t);this.scale&&(e=e.subRowVector(this.meanX).divRowVector(this.stdDevX));var r=e.mmul(this.PBQ);return r=r.mulRowVector(this.stdDevY).addRowVector(this.meanY)}getExplainedVariance(){return 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r=this.kernel.compute(t),i=n.Matrix.eye(r.rows,r.rows,1),o=r;(r=new n.Matrix(this.orthogonalComp+1,this.orthogonalComp+1))[0][0]=o;var s=new n.SingularValueDecomposition(e.transpose().mmul(r[0][0]).mmul(e),{computeLeftSingularVectors:!0,computeRightSingularVectors:!1}),a=s.leftSingularVectors,u=s.diagonalMatrix;a=a.subMatrix(0,a.rows-1,0,this.predictiveComp-1),u=u.subMatrix(0,this.predictiveComp-1,0,this.predictiveComp-1);var h=e.mmul(a),l=new Array(this.orthogonalComp+1),c=new Array(this.orthogonalComp+1),f=new Array(this.orthogonalComp),d=new Array(this.orthogonalComp),m=new Array(this.orthogonalComp),g=new Array(this.orthogonalComp),p=n.Matrix.pow(u,-.5);p.apply(function(t,e){this[t][e]===1/0&&(this[t][e]=0)});for(var v=0;v<this.orthogonalComp;++v){l[v]=r[0][v].transpose().mmul(h).mmul(p);var w=l[v].transpose();c[v]=(0,n.inverse)(w.mmul(l[v])).mmul(w).mmul(h);var y=(s=new n.SingularValueDecomposition(w.mmul(n.Matrix.sub(r[v][v],l[v].mmul(w))).mmul(l[v]),{computeLeftSingularVectors:!0,computeRightSingularVectors:!1})).leftSingularVectors,x=s.diagonalMatrix;d[v]=y.subMatrix(0,y.rows-1,0,0),m[v]=x[0][0],f[v]=n.Matrix.sub(r[v][v],l[v].mmul(w)).mmul(l[v]).mmul(d[v]).mul(Math.pow(m[v],-.5));var M=f[v].transpose();g[v]=n.Matrix.sqrt(M.mmul(f[v])),f[v]=f[v].divRowVector(g[v]);var b=n.Matrix.sub(i,f[v].mmul(f[v].transpose()));r[0][v+1]=r[0][v].mmul(b),r[v+1][v+1]=b.mmul(r[v][v]).mmul(b)}var A=l[this.orthogonalComp]=r[0][this.orthogonalComp].transpose().mmul(h).mmul(p),S=A.transpose();c[this.orthogonalComp]=(0,n.inverse)(S.mmul(A)).mmul(S).mmul(h),this.YLoadingMat=a,this.SigmaPow=p,this.YScoreMat=h,this.predScoreMat=l,this.YOrthLoadingVec=d,this.YOrthEigen=m,this.YOrthScoreMat=f,this.toNorm=g,this.TURegressionCoeff=c,this.kernelX=r}predict(t){var e=this.kernel.compute(t,this.trainingSet),r=e;(e=new n.Matrix(this.orthogonalComp+1,this.orthogonalComp+1))[0][0]=r;var i,o=new Array(this.orthogonalComp),s=new Array(this.orthogonalComp);for(i=0;i<this.orthogonalComp;++i){s[i]=e[i][0].mmul(this.YScoreMat).mmul(this.SigmaPow),o[i]=n.Matrix.sub(e[i][i],s[i].mmul(this.predScoreMat[i].transpose())).mmul(this.predScoreMat[i]).mmul(this.YOrthLoadingVec[i]).mul(Math.pow(this.YOrthEigen[i],-.5)),o[i]=o[i].divRowVector(this.toNorm[i]);var a=this.YOrthScoreMat[i].transpose();e[i+1][0]=n.Matrix.sub(e[i][0],o[i].mmul(a).mmul(this.kernelX[0][i].transpose()));var u=n.Matrix.sub(e[i][0],e[i][i].mmul(this.YOrthScoreMat[i]).mmul(a)),h=o[i].mmul(a).mmul(this.kernelX[i][i]),l=h.mmul(this.YOrthScoreMat[i]).mmul(a);e[i+1][i+1]=u.sub(h).add(l)}return 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a(!0,t)}}e.default=a},function(t,e,r){"use strict";var n=r(0);function i(t,e,r){for(var n=0,i=r(e),o=0;o<t.x.length;o++)n+=Math.abs(t.y[o]-i(t.x[o]));return n}function o(t,e,r,i,o){for(var s=n.Matrix.eye(e.length).mul(r*i*i),a=t.x.length,u=new Array(a),h=o(e),l=0;l<a;l++)u[l]=h(t.x[l]);var c=function(t,e,r,i,o){for(var s=r.length,a=t.x.length,u=new Array(s),h=0;h<s;h++){u[h]=new Array(a);var l=r.concat();l[h]+=i;for(var c=o(l),f=0;f<a;f++)u[h][f]=e[f]-c(t.x[f])}return new n.Matrix(u)}(t,u,e,i,o),f=function(t,e){for(var r=t.x.length,i=new Array(r),o=0;o<r;o++)i[o]=t.y[o]-e[o];return new n.Matrix([i])}(t,u).transposeView(),d=n.inverse(s.add(c.mmul(c.transposeView())));return(e=(e=new n.Matrix([e])).sub(d.mmul(c).mmul(f).mul(i).transposeView())).to1DArray()}t.exports=function(t,e,r={}){var n=r.maxIterations,s=void 0===n?100:n,a=r.gradientDifference,u=void 0===a?.1:a,h=r.damping,l=void 0===h?0:h,c=r.errorTolerance,f=void 0===c?.01:c,d=r.initialValues;if(l<=0)throw new Error("The damping option must be a positive number");if(!t.x||!t.y)throw new Error("The data parameter must have x and y elements");if(!Array.isArray(t.x)||t.x.length<2||!Array.isArray(t.y)||t.y.length<2)throw new Error("The data parameter elements must be an array with more than 2 points");if(t.x.length!==t.y.length)throw new Error("The data parameter elements must have the same size");var m=d||new Array(e.length).fill(1);if(!Array.isArray(m))throw new Error("initialValues must be an array");for(var g=i(t,m,e),p=g<=f,v=0;v<s&&!p;v++)p=(g=i(t,m=o(t,m,l,u,e),e))<=f;return{parameterValues:m,parameterError:g,iterations:v}}},function(module,exports,__webpack_require__){"use strict";Object.defineProperty(exports,"__esModule",{value:!0}),exports.SparseMatrix=void 0;var _mlHashTable=__webpack_require__(39),_mlHashTable2=_interopRequireDefault(_mlHashTable);function _interopRequireDefault(t){return t&&t.__esModule?t:{default:t}}class SparseMatrix{constructor(t,e,r={}){if(t instanceof SparseMatrix){var n=t;this._init(n.rows,n.columns,n.elements.clone(),n.threshold)}else if(Array.isArray(t)){var i=t;t=i.length,r=e||{},e=i[0].length,this._init(t,e,new _mlHashTable2.default(r),r.threshold);for(var o=0;o<t;o++)for(var s=0;s<e;s++){var a=i[o][s];this.threshold&&Math.abs(a)<this.threshold&&(a=0),0!==a&&this.elements.set(o*e+s,i[o][s])}}else this._init(t,e,new _mlHashTable2.default(r),r.threshold)}_init(t,e,r,n){this.rows=t,this.columns=e,this.elements=r,this.threshold=n||0}static eye(t=1,e=t){for(var r=Math.min(t,e),n=new SparseMatrix(t,e,{initialCapacity:r}),i=0;i<r;i++)n.set(i,i,1);return n}clone(){return new SparseMatrix(this)}to2DArray(){for(var t=new Array(this.rows),e=0;e<this.rows;e++){t[e]=new Array(this.columns);for(var r=0;r<this.columns;r++)t[e][r]=this.get(e,r)}return t}isSquare(){return this.rows===this.columns}isSymmetric(){if(!this.isSquare())return!1;var t=!0;return this.forEachNonZero((e,r,n)=>this.get(r,e)!==n?(t=!1,!1):n),t}bandWidth(){var t=this.columns,e=-1;return this.forEachNonZero((r,n,i)=>{var o=r-n;return t=Math.min(t,o),e=Math.max(e,o),i}),e-t}isBanded(t){return this.bandWidth()<=t}get cardinality(){return this.elements.size}get size(){return this.rows*this.columns}get(t,e){return this.elements.get(t*this.columns+e)}set(t,e,r){return this.threshold&&Math.abs(r)<this.threshold&&(r=0),0===r?this.elements.remove(t*this.columns+e):this.elements.set(t*this.columns+e,r),this}mmul(t){this.columns!==t.rows&&console.warn("Number of columns of left matrix are not equal to number of rows of right matrix.");var e=this.rows,r=t.columns,n=new SparseMatrix(e,r);return this.forEachNonZero((e,r,i)=>(t.forEachNonZero((t,o,s)=>(r===t&&n.set(e,o,n.get(e,o)+i*s),s)),i)),n}kroneckerProduct(t){var e=this.rows,r=this.columns,n=t.rows,i=t.columns,o=new SparseMatrix(e*n,r*i,{initialCapacity:this.cardinality*t.cardinality});return this.forEachNonZero((e,r,s)=>(t.forEachNonZero((t,a,u)=>(o.set(n*e+t,i*r+a,s*u),u)),s)),o}forEachNonZero(t){return this.elements.forEachPair((e,r)=>{var n=e/this.columns|0,i=e%this.columns,o=t(n,i,r);return!1!==o&&(this.threshold&&Math.abs(o)<this.threshold&&(o=0),o!==r&&(0===o?this.elements.remove(e,!0):this.elements.set(e,o)),!0)}),this.elements.maybeShrinkCapacity(),this}getNonZeros(){var t=this.cardinality,e=new Array(t),r=new Array(t),n=new Array(t),i=0;return this.forEachNonZero((t,o,s)=>(e[i]=t,r[i]=o,n[i]=s,i++,s)),{rows:e,columns:r,values:n}}setThreshold(t){return 0!==t&&t!==this.threshold&&(this.threshold=t,this.forEachNonZero((t,e,r)=>r)),this}transpose(){var t=new SparseMatrix(this.columns,this.rows,{initialCapacity:this.cardinality});return this.forEachNonZero((e,r,n)=>(t.set(r,e,n),n)),t}}exports.SparseMatrix=SparseMatrix,SparseMatrix.prototype.klass="Matrix",SparseMatrix.identity=SparseMatrix.eye,SparseMatrix.prototype.tensorProduct=SparseMatrix.prototype.kroneckerProduct;var inplaceOperator="\n(function %name%(value) {\n    if (typeof value === 'number') return this.%name%S(value);\n    return this.%name%M(value);\n})\n",inplaceOperatorScalar="\n(function %name%S(value) {\n    this.forEachNonZero((i, j, v) => v %op% value);\n    return this;\n})\n",inplaceOperatorMatrix="\n(function %name%M(matrix) {\n    matrix.forEachNonZero((i, j, v) => {\n        this.set(i, j, this.get(i, j) %op% v);\n        return v;\n    });\n    return this;\n})\n",staticOperator="\n(function %name%(matrix, value) {\n    var newMatrix = new SparseMatrix(matrix);\n    return newMatrix.%name%(value);\n})\n",inplaceMethod="\n(function %name%() {\n    this.forEachNonZero((i, j, v) => %method%(v));\n    return this;\n})\n",staticMethod="\n(function %name%(matrix) {\n    var newMatrix = new SparseMatrix(matrix);\n    return newMatrix.%name%();\n})\n",operators=[["+","add"],["-","sub","subtract"],["*","mul","multiply"],["/","div","divide"],["%","mod","modulus"],["&","and"],["|","or"],["^","xor"],["<<","leftShift"],[">>","signPropagatingRightShift"],[">>>","rightShift","zeroFillRightShift"]];for(var operator of operators)for(var i=1;i<operator.length;i++)SparseMatrix.prototype[operator[i]]=eval(fillTemplateFunction(inplaceOperator,{name:operator[i],op:operator[0]})),SparseMatrix.prototype[operator[i]+"S"]=eval(fillTemplateFunction(inplaceOperatorScalar,{name:operator[i]+"S",op:operator[0]})),SparseMatrix.prototype[operator[i]+"M"]=eval(fillTemplateFunction(inplaceOperatorMatrix,{name:operator[i]+"M",op:operator[0]})),SparseMatrix[operator[i]]=eval(fillTemplateFunction(staticOperator,{name:operator[i]}));var methods=[["~","not"]];for(var method 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